# document

id: 1ef6c1d2f8ae459ebb8b8f62bfa35d39
created_at: 2023-03-16 14:02:15
updated_at: 2023-03-16 14:02:15
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index: climate_gpt_only_giec
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" Urbanisation \r\nand associated changes in freshwater and sediment dynamics increase \r\nthe vulnerability of coastal ecosystems like sandy beaches, salt \r\nmarshes and mangrove forests to sea level rise and changes in wave \r\nenergy (very high confidence). Although these non-climate drivers \r\nconfound attribution of impacts to climate change, adaptive, inclusive \r\nand evidence-based management reduces the cumulative pressure on \r\nocean and coastal ecosystems, which will decrease their vulnerability \r\nto climate change (high confidence). {3.3, 3.3.3, 3.4.2.4-3.4.2.8, \r\n3.4.3.4, 3.5.3, 3.6.2, Cross-Chapter Box SLR in Chapter 3}"


id: 8f179d2929d60b7b281dbbc2a6045cb5
created_at: 2023-03-16 14:02:15
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vector_id: 20052
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"Escalating impacts of climate change on marine life will further \r\nalter biomass of marine animals (medium confidence), the \r\ntiming of seasonal ecological events (medium confidence) \r\nand the geographic ranges of coastal and ocean taxa (medium \r\nconfidence), disrupting life cycles (medium confidence), \r\nfood webs (medium confidence) and ecological connectivity \r\nthroughout the water column (medium confidence). Multiple \r\nlines of evidence suggest that climate-change responses are very \r\nlikely to amplify up marine food webs over large regions of the ocean. \r\nModest projected declines in global phytoplankton biomass translate \r\ninto larger declines of total animal biomass (by 2080-2099 relative \r\nto 1995-2014) ranging from (mean +- very likely range) -5.7 +- 4.1% \r\nto -15.5 +- 8.5% under SSP1-2.6 and SSP5-8.5, respectively (medium \r\nconfidence)"


id: 243d6bd1a8825a84489c4eb8d97b52c0
created_at: 2023-03-16 14:02:15
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" Projected declines in upper-ocean nutrient concentrations, \r\nlikely associated with increases in stratification, will reduce carbon \r\nexport flux to the mesopelagic and deep-sea ecosystems (medium \r\nconfidence). This will lead to a decline in the biomass of abyssal meio\u0002and macrofauna (by 2081-2100 relative to 1995-2014) by -9.8% and \r\n-13.0% under SSP1-2.6 and SSP5-8.5, respectively (limited evidence). \r\nBy 2100, 18.8 +- 19.0% to 38.9 +- 9.4% of the ocean will very likely\r\nundergo a change of more than 20 d (advances and delays) in the \r\nstart of the phytoplankton growth period under SSP1-2.6 and SSP5-\r\n8.5, respectively (low confidence). This altered timing increases the risk \r\nof temporal mismatches between plankton blooms and fish spawning \r\nseasons (medium to high confidence) and increases the risk of fish\u0002recruitment failure for species with restricted spawning locations, \r\nespecially in mid-to-high latitudes of the Northern Hemisphere (low \r\nconfidence)"


id: 36eff3b32a0515fafbcebd247a7b0319
created_at: 2023-03-16 14:02:15
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" Projected range shifts among marine species (medium \r\nconfidence) suggest extirpations and strongly decreasing tropical \r\nbiodiversity. At higher latitudes, range expansions will drive increased \r\nhomogenisation of biodiversity. The projected loss of biodiversity \r\nultimately threatens marine ecosystem resilience (medium to high \r\nconfidence), with subsequent effects on service provisioning (medium \r\nto high confidence). {3.2.2.3, 3.4.2.10, 3.4.3.1-3.4.3.5, 3.5, WGI AR6 \r\nSection 2.3.4.2.3}"


id: 8c7c97fd177164235126f0c51f521eb9
created_at: 2023-03-16 14:02:15
updated_at: 2023-03-16 14:02:15
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"Ocean conditions are projected to continue diverging from a \r\npre-industrial state (virtually certain), with the magnitude \r\nof  warming, acidification, deoxygenation, sea level rise and \r\nother climate-induced drivers depending on the emission \r\nscenario (very high confidence), and to increase risk of regional \r\nextirpations and global extinctions of marine species (medium \r\nconfidence). Marine species richness near the equator and in the Arctic \r\nis projected to continue declining, even with less than 2degC warming \r\nby the end of the century (medium confidence). In the deep ocean, \r\nall global warming levels will cause faster movements of temperature \r\nniches by 2100 than those that have driven extensive reorganisation \r\nof marine biodiversity at the ocean surface over the past 50  years \r\n(medium confidence). At warming levels beyond 2degC by 2100, risks of \r\nextirpation, extinction and ecosystem collapse escalate rapidly (high \r\nconfidence)"


id: 593a2102c58ffc95a0102e63cac13c9f
created_at: 2023-03-16 14:02:15
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" Paleorecords indicate that at extreme global warming \r\nlevels (>5.2degC), mass extinction of marine species may occur (medium \r\nconfidence). {Box 3.2, 3.2.2.1, 3.4.2.5, 3.4.2.10, 3.4.3.3, Cross-Chapter \r\nBox PALEO in Chapter 1}"


id: 58da9f0493b4ebd9f60ebe88e7289ecc
created_at: 2023-03-16 14:02:15
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"Risks from sea level rise for coastal ecosystems and people \r\nare very likely to increase tenfold well before 2100 without \r\nadaptation and mitigation action as agreed by Parties to the Paris \r\nAgreement (very high confidence). Sea level rise under emission \r\nscenarios that do not limit warming to 1.5degC will increase the risk of \r\ncoastal erosion and submergence of coastal land (high confidence), \r\nloss of coastal habitat and ecosystems (high confidence) and worsen \r\nsalinisation of groundwater (high confidence), compromising coastal \r\necosystems and livelihoods (high confidence). Under SSP1-2.6, \r\nmost coral reefs (very high confidence), mangroves (likely, medium \r\nconfidence) and salt marshes (likely, medium confidence) will be \r\nunable to keep up with sea level rise by 2050, with ecological impacts \r\nescalating rapidly beyond 2050, especially for scenarios coupling high \r\nemissions with aggressive coastal development (very high confidence)"


id: 554d14e504204d03b79c62e34784eec
created_at: 2023-03-16 14:02:15
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" \r\nResultant decreases in natural shoreline protection will place \r\nincreasing numbers of people at risk (very high confidence). The ability \r\nto adapt to current coastal impacts, cope with future coastal risks and \r\nprevent further acceleration of sea level rise beyond 2050 depends on \r\nimmediate implementation of mitigation and adaptation actions (very \r\nhigh confidence).  {3.4.2.1, 3.4.2.4, 3.4.2.5, 3.4.2.6, 3.5.5.3, Cross\u0002Chapter Box SLR in Chapter 3}"


id: ef22c58dd7450bc51a0eb7a824a8ba38
created_at: 2023-03-16 14:02:15
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"Climate impacts on ocean and coastal ecosystems will be \r\nexacerbated by increases in intensity, reoccurrence and \r\nduration of marine heatwaves (high confidence), in some cases, \r\nleading to species extirpation, habitat collapse or surpassing \r\necological tipping points (very high confidence). Some habitat\u0002forming coastal ecosystems including many coral reefs, kelp forests and \r\nseagrass meadows, will undergo irreversible phase shifts due to marine \r\nheatwaves with global warming levels >1.5degC and are at high risk this \r\ncentury even in <1.5degC scenarios that include periods of temperature \r\novershoot beyond 1.5degC (high confidence). Under SSP1-2.6, coral \r\nreefs are at risk of widespread decline, loss of structural integrity and \r\ntransitioning to net erosion by mid-century due to increasing intensity \r\nand frequency of marine heatwaves (very high confidence)"


id: fec69948172c0ebc7e983e1154e029e6
created_at: 2023-03-16 14:02:15
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" Due to \r\nthese impacts, the rate of sea level rise is very likely to exceed that \r\nof reef growth by 2050, absent adaptation. Other coastal ecosystems, \r\nincluding kelp forests, mangroves and seagrasses, are vulnerable to \r\nphase shifts towards alternate states as marine heatwaves intensify \r\n(high confidence). Loss of kelp forests are expected to be greatest \r\nat the low-latitude warm edge of species' ranges (high confidence). \r\n{3.4.2.1, 3.4.2.3, 3.4.2.5, 3.4.4}"


id: 5c3c0268c73f76f652539ee3347661bf
created_at: 2023-03-16 14:02:15
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"Available adaptation options are unable to offset climate\u0002change impacts on marine ecosystems and the services they \r\nprovide (high confidence). Adaptation solutions implemented at \r\nappropriate scales, when combined with ambitious and urgent \r\nmitigation measures, can meaningfully reduce impacts (high \r\nconfidence). Increasing evidence from implemented adaptations \r\nindicates that multi-level governance, early-warning systems for \r\nclimate-associated marine hazards, seasonal and dynamic forecasts, \r\nhabitat restoration, ecosystem-based management, climate-adaptive \r\nmanagement and sustainable harvesting tend to be both feasible \r\nand effective (high confidence). Marine protected areas (MPAs), as \r\ncurrently implemented, do not confer resilience against warming and \r\nheatwaves (medium confidence) and are not expected to provide \r\nsubstantial protection against climate impacts past 2050 (high \r\nconfidence)"


id: a97c933d09db1aa63c4ffaaa58977c57
created_at: 2023-03-16 14:02:15
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vector_id: 24199
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" However, MPAs can contribute substantially to adaptation \r\nand mitigation if they are designed to address climate change, \r\nstrategically implemented and well governed (high confidence). \r\nHabitat restoration limits climate-change-related loss of ecosystem \r\nservices, including biodiversity, coastal protection, recreational use and \r\ntourism (medium confidence), provides mitigation benefits on local to \r\nregional scales (e.g., via carbon-storing 'blue carbon' ecosystems) (high \r\nconfidence) and may safeguard fish-stock production in a warmer \r\nclimate (limited evidence). Ambitious and swift global mitigation \r\noffers more adaptation options and pathways to sustain ecosystems \r\nand their services (high confidence). {3.4.2, 3.4.3.3, 3.5, 3.5.2, 3.5.3, \r\n3.5.5.4, 3.5.5.5, 3.6.2.1, 3.6.2.2, 3.6.2.3, 3.6.3.1, 3.6.3.2, 3.6.3.3, 3.6.5, \r\nFigure 3.24, Figure 3.25}"


id: 9464fc181af7dc64bb6f605d48903321
created_at: 2023-03-16 14:02:15
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"Climate change will alter many ecosystem services provided \r\nby marine systems (high confidence), but impacts to human \r\ncommunities will depend on people's overall vulnerability, \r\nwhich is strongly influenced by local context and development \r\npathways (very high confidence). Catch composition and diversity \r\nof regional fisheries will change (high confidence), and fishers who are \r\nable to move, diversify and leverage technology to sustain harvests \r\ndecrease their own vulnerability (medium confidence). Management \r\nthat eliminates overfishing facilitates successful future adaptation of \r\nfisheries to climate change (very high confidence). Marine-dependent \r\ncommunities, including Indigenous Peoples and local peoples, will be \r\nat increased risk of losing cultural heritage and traditional seafood\u0002sourced nutrition (medium confidence)"


id: b3c943dc4f4f4f0cee11dbfd3ff07e66
created_at: 2023-03-16 14:02:15
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" Without adaptation, seafood\u0002dependent people face increased risk of exposure to toxins, pathogens \r\nand contaminants (high confidence), and coastal communities \r\nface increasing risk from salinisation of groundwater and soil (high \r\nconfidence). Early-warning systems and public education about \r\nenvironmental change, developed and implemented within the local \r\nand cultural context, can decrease those risks (high confidence). \r\nCoastal development and management informed by sea level rise \r\nprojections will reduce the number of people and amount of property \r\nat risk (high confidence), but historical coastal development and \r\npolicies impede change (high confidence). Current financial flows are \r\nglobally uneven and overall insufficient to meet the projected costs \r\nof climate impacts on coastal and marine social-ecological systems \r\n(very high confidence)"


id: 95d1ba4cd9b3973d1907bc7e499894a6
created_at: 2023-03-16 14:02:15
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" Inclusive governance that (a) accommodates \r\ngeographically shifting marine life, (b)  financially supports needed \r\nhuman transformations, (c)  provides effective public education and \r\n(d) incorporates scientific evidence, Indigenous knowledge and local \r\nknowledge to manage resources sustainably shows greatest promise \r\nfor decreasing human vulnerability to all of these projected changes in \r\nocean and coastal ecosystem services (very high confidence). {3.5.3, \r\n3.5.5, 3.5.6, 3.6.3, Box 3.4, Cross-Chapter Box ILLNESS in Chapter 2, \r\nCross-Chapter Box SLR in Chapter 3}"


id: 3b7e9eaf9676c772969051ee9fbf821d
created_at: 2023-03-16 14:02:15
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"Nature-based solutions for adaptation of ocean and coastal \r\necosystems can achieve multiple benefits when well designed \r\nand implemented (high confidence), but their effectiveness \r\ndeclines without ambitious and urgent mitigation (high \r\nconfidence). Nature-based solutions, such as ecosystem-based \r\nmanagement, climate-smart conservation approaches (i.e., climate\u0002adaptive fisheries and conservation) and coastal habitat restoration, \r\ncan be cost-effective and generate social, economic and cultural co\u0002benefits while contributing to the conservation of marine biodiversity \r\nand reducing cumulative anthropogenic drivers (high confidence). \r\nThe effectiveness of nature-based solutions declines with warming; \r\nconservation and restoration alone will be insufficient to protect coral \r\nreefs beyond 2030 (high confidence) and to protect mangroves beyond \r\nthe 2040s (high confidence)"


id: a2daa46f9f096cec44db81ff30e81c68
created_at: 2023-03-16 14:02:15
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index: climate_gpt_only_giec
vector_id: 23190
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" The multidimensionality of climate-change \r\nimpacts and their interactions with other anthropogenic stressors calls \r\nfor integrated approaches that identify trade-offs and synergies across \r\nsectors and scales in space and time to build resilience of ocean and \r\ncoastal ecosystems and the services they deliver (high confidence). \r\n{3.4.2, 3.5.2, 3.5.3, 3.5.5.3, 3.5.5.4, 3.5.5.5, 3.6.2.2, 3.6.3.2, 3.6.5, \r\nFigure 3.25, Table 3.SM.6}"


id: 9ef5088e44c838a23ab94f4ea61f217d
created_at: 2023-03-16 14:02:15
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"Humans are already adapting to climate-driven changes in \r\nmarine systems, and while further adaptations are required even \r\nunder low-emission scenarios (high confidence), transformative \r\nadaptation will be essential under high-emission scenarios \r\n(high confidence).  Low-emission scenarios permit a wider array \r\nof feasible, effective and low-risk nature-based adaptation options \r\n(e.g., restoration, revegetation, conservation, early-warning systems \r\nfor extreme events and public education) (high confidence). Under \r\nhigh-emission scenarios, adaptation options (e.g., hard infrastructure \r\nfor coastal protection, assisted migration or evolution, livelihood \r\ndiversification, migration and relocation of people) are more uncertain \r\nand require transformative governance changes  (high confidence)"


id: 19a02db45e5af7adca0a7c7c8680a35d
created_at: 2023-03-16 14:02:15
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" \r\nTransformative climate adaptation will reinvent institutions to \r\novercome obstacles arising from historical precedents, reducing current \r\nbarriers to climate adaptation in cultural, financial and governance \r\nsectors (high confidence). Without transformation, global inequities will \r\nlikely increase between regions (high confidence) and conflicts between \r\njurisdictions may emerge and escalate. {3.5, 3.5.2, 3.5.5.3, 3.6, 3.6.2.1, \r\n3.6.3.1, 3.6.3.2, 3.6.3.3, 3.6.4.1, 3.6.4.2, 3.6.5, Cross-Chapter Box SLR \r\nin Chapter 3, Cross-Chapter Box ILLNESS in Chapter 2}"


id: 665ebab3e4f0f15e8be099f273b8b4b4
created_at: 2023-03-16 14:02:15
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"by redistributing heat and water (WGI AR6 Chapter  9; Fox-Kemper \r\net al., 2021). The ocean also provides a wealth of aesthetic and cultural \r\nresources (Barbier et al., 2011), contains vast biodiversity (Appeltans \r\net al., 2012), supports more animal biomass than on land (Bar-On et al., \r\n2018) and produces at least half the world's photosynthetic oxygen \r\n(Field et al., 1998). Ecosystem services (Annex II: Glossary) delivered \r\nby ocean and coastal ecosystems support humanity by protecting \r\ncoastlines, providing nutrition and economic opportunities (Figure 3.1; \r\nSelig et al., 2019) and providing many intangible benefits. Even though \r\necosystem services and biodiversity underpin human well-being and \r\nsupport climate mitigation and adaptation (Portner et al., 2021b), there \r\nare also ethical arguments for preserving biodiversity and ecosystem \r\nfunctions regardless of the beneficiary (e.g., Taylor et al., 2020)"


id: db92a5b51c1d94338afb4875f8a8ed7c
created_at: 2023-03-16 14:02:15
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" This \r\nchapter assesses the impact of climate change on the full spectrum of \r\nocean and coastal ecosystems, on their services and on related human \r\nactivities, and it assesses marine-related opportunities within both \r\necological and social systems to adapt to climate change."


id: f529ec81baa274f03c6c1096c7679f6f
created_at: 2023-03-16 14:02:15
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"The ocean contains approximately 97% of Earth's water within a \r\nsystem of interconnected basins that cover 71% of its surface. Coastal \r\nsystems mostly extend seaward from the high-water mark, or just \r\nbeyond, to the edge of the continental shelf and include shores of soft \r\nsediments, rocky shores and reefs, embayments, estuaries, deltas and \r\nshelf systems. Oceanic systems comprise waters beyond the shelf edge, \r\nfrom ~200 m to nearly 11,000 m deep (Stewart and Jamieson, 2019), \r\nwith an average depth of approximately 3700 m. The epipelagic zone, \r\nor upper 200 m of the ocean, is illuminated by sufficient sunlight to \r\nsustain photosynthesis that supports the rich marine food web"


id: e6d47cf70bc9615f2f7c791fe73fdf39
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" Below \r\nthe epipelagic zone lies the barely lit mesopelagic zone (200-1000 m), \r\nthe perpetually dark bathypelagic zone (depth >1000 m) and the \r\ndeep seafloor (benthic ecosystems at depths >200 m), which spans \r\nrocky and sedimentary habitats on seamounts, mid-ocean ridges and \r\ncanyons, abyssal plains and sedimented margins. Semi-enclosed seas \r\n(SES) include both coastal and oceanic systems."


id: cb5e5658de180cbd30d32e6b29316412
created_at: 2023-03-16 14:02:15
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"Figure 3.1 |  Estimated relative human dependence on marine ecosystems for coastal protection, nutrition, fisheries economic benefits and overall. Each \r\nbar represents an index value that semi-quantitatively integrates the magnitude, vulnerability to loss and substitutability of the benefit. Indices synthesize information on people's \r\nconsumption of marine protein and nutritional status, gross domestic product, fishing revenues, unemployment, education, governance and coastal characteristics. Overall \r\ndependence is the mean of the three index values after standardisation from 0-1. (Details regarding component indices are found in Table 1 and Supplementary Material of Selig \r\net al., 2019.) The overall index does not include the economic benefits from tourism or other ocean industries, and data limitations prevented including artisanal or recreational \r\nfisheries or the protective impact of salt marshes (Selig et al., 2019)"


id: ddf1415f06adf226917ee7b86d609468
created_at: 2023-03-16 14:02:15
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" Values for reference regions established in the WGI AR6 Atlas (Gutierrez et al., 2021) were computed as \r\narea-weighted means from original country-level data (Table S6 in Selig et al., 2019)."


id: 4a31c3d1749e44610f324ea2ff58e37b
created_at: 2023-03-16 14:02:15
updated_at: 2023-03-16 14:02:15
content_type: text
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content:
"also influence ocean and coastal systems (Section 3.2; Cross-Chapter \r\nBox  SLR in Chapter  3; Cross-Chapter Box  EXTREMES in Chapter  2; \r\nFigure  3.SM.1), from individual biophysical processes to dependent \r\nhuman activities. Several marine outcomes of CIDs are themselves \r\ndrivers of ecological change (e.g., climate velocities, stratification, \r\nsea ice changes). This chapter updates and extends the assessment \r\nof SROCC (IPCC, 2019b) and WGI AR6 by assessing the ecosystem \r\neffects of the CIDs in WGI AR6 Figure SPM.9 (IPCC, 2021b) and their \r\nbiologically relevant marine outcomes (detailed in Section 3.2), which \r\nare referred to collectively hereafter as 'climate-induced drivers'4\r\n.\r\nDetrimental human impacts on ocean and coastal ecosystems are not \r\nonly caused by climate. Other anthropogenic activities are increasingly \r\naffecting the physical, chemical and biological conditions of the ocean \r\n(Doney, 2010; Halpern et al"


id: 33c593435815274b37d0aea021b3e91
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", 2019), and these 'non-climate drivers5\r\n' also \r\nalter marine ecosystems and their services. Fishing and other extractive \r\nactivities are major non-climate drivers in many ocean and coastal systems \r\n(Steneck and Pauly, 2019). Many activities, such as coastal development, \r\nshoreline hardening and habitat destruction, physically alter marine spaces \r\n(Suchley and Alvarez-Filip, 2018; Ducrotoy et al., 2019; Leo et al., 2019; \r\nNewton et al., 2020; Raw et al., 2020). Other human activities decrease \r\nwater quality by overloading coastal water with terrestrial nutrients \r\n(eutrophication) and by releasing runoff containing chemical, biological \r\nand physical pollutants, toxins, and pathogens (Jambeck et  al., 2015; \r\nLuek et al., 2017; Breitburg et al., 2018; Froelich and Daines, 2020). Some \r\nhuman activities disturb marine organisms by generating excess noise \r\nand light (Davies et al., 2014; Duarte et al"


id: 42e5c4cb9f9de4c326b8f4cac0a4d764
created_at: 2023-03-16 14:02:15
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", 2021), while others decrease \r\nnatural light penetration into the ocean (Wollschlager et  al., 2021). \r\nSeveral anthropogenic activities alter processes that span the land-sea \r\ninterface by changing coastal hydrology or causing coastal subsidence \r\n(Michael et al., 2017; Phlips et al., 2020; Bagheri-Gavkosh et al., 2021). \r\nAtmospheric pollutants can harm marine systems or unbalance natural \r\nmarine processes (Doney et al., 2007; Hagens et al., 2014; Lamborg et al., \r\n2014; Ito et  al., 2016). Organisms frequently experience non-climate \r\ndrivers simultaneously with climate-induced drivers (Section  3.4), and \r\nfeedbacks may exist between climate-induced drivers and non-climate \r\ndrivers that enhance the effects of climate change (Rocha et al., 2015; \r\nOrtiz et al., 2018; Wolff et al., 2018; Cabral et al., 2019; Bowler et al., 2020; \r\nGissi et al., 2021)"


id: f74b81cb9b5fbc7ddd71e24482d9c530
created_at: 2023-03-16 14:02:15
updated_at: 2023-03-16 14:02:15
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index: climate_gpt_only_giec
vector_id: 36422
content:
" SROCC assessed with high confidence that reduction \r\nof pollution and other stressors, along with protection, restoration and \r\nprecautionary management, supports ocean and coastal ecosystems \r\nand their services (IPCC, 2019b). This chapter examines the combined \r\ninfluence of climate-induced drivers and primary non-climate drivers on \r\nmany ecosystems assessed."


id: 4145dd770af3872b177315a33fca6aa5
created_at: 2023-03-16 14:02:15
updated_at: 2023-03-16 14:02:15
content_type: text
index: climate_gpt_only_giec
vector_id: 7663
content:
"and attribute climate impacts on marine-dependent human systems, \r\nwhere culture, governance and society also strongly influence observed \r\noutcomes. To assess climate-driven change in natural and social systems \r\nrobustly, IPCC reports rely on multiple lines of evidence, and the \r\navailable types of evidence differ depending on the system under study \r\n(Section  1.3.2.1, Cross-Working Group Box ATTRIB). Lines of evidence \r\nused for ocean and coastal ecosystems for this and previous assessments \r\ninclude observed phenomena, laboratory and field experiments, long\u0002term monitoring, empirical and dynamical model analyses, Indigenous \r\nknowledge (IK) and local knowledge (LK), and paleorecords (IPCC, 2014b; \r\nIPCC, 2014c; IPCC, 2019b)"


id: d036b9e257f66fd2a50133b8cea728d3
created_at: 2023-03-16 14:02:15
updated_at: 2023-03-16 14:02:15
content_type: text
index: climate_gpt_only_giec
vector_id: 30290
content:
" The growing body of climate research for ocean \r\nand coastal ecosystems and their services increasingly provides multiple \r\nindependent lines of evidence whose conclusions support each other, \r\nraising the overall confidence in detection and attribution of impacts over \r\ntime (Section 1.3.2.1, Cross-Working Group Box ATTRIB in Chapter 3)."


id: 1b340833df1e50c90a47cffd6d51c7c7
created_at: 2023-03-16 14:02:15
updated_at: 2023-03-16 14:02:15
content_type: text
index: climate_gpt_only_giec
vector_id: 1745
content:
"Natural adaptation to climate change in ocean and coastal systems \r\nincludes an array of responses taking place at scales from cells to \r\necosystems. Previous IPCC assessments have established that many \r\nmarine species 'have shifted their geographic ranges, seasonal \r\nactivities, migration patterns, abundances and species interactions \r\nin response to climate change' (high confidence) (IPCC, 2014b; \r\nIPCC, 2014c), which has had global impacts on species composition, \r\nabundance and biomass, and on ecosystem structure and function \r\n(medium confidence) (IPCC, 2019b). Warming and acidification have \r\naffected coastal ecosystems in concert with non-climate drivers (high \r\nconfidence), which have affected habitat area, biodiversity, ecosystem \r\nfunction and services (high confidence) (IPCC, 2019b). Confidence \r\nhas grown in these assessments over time as observational datasets \r\nhave lengthened and other lines of evidence have corroborated \r\nobservations"


id: 2e1b6b286a970eed8d28524a4b286420
created_at: 2023-03-16 14:02:15
updated_at: 2023-03-16 14:02:15
content_type: text
index: climate_gpt_only_giec
vector_id: 4695
content:
" AR5 and SROCC assessed how physiological sensitivity \r\nto climate-induced drivers is the underlying cause of most marine \r\norganisms' vulnerability to climate (high confidence) (Portner et  al., \r\n2014; Bindoff et al., 2019a). Since those assessments, more evidence \r\nsupports the empirical physiological models of tolerance and plasticity \r\n(Sections 3.3.2, 3.3.4) and of interactions among multiple (climate and \r\nnon-climate) drivers at individual to ecosystem scales (Sections 3.3.3, \r\n3.4.5). New experimental evidence about evolutionary adaptation \r\n(Section 3.3.4) bolsters previous assessments that adaptation options \r\nto climate change are limited for eukaryotic organisms. Tools such \r\nas ecosystem models can now constrain probable ecosystem states \r\n(Sections 3.3.4, 3.3.5, 3.4)"


id: 1100bbf37a9db2f02181a02cd5480b68
created_at: 2023-03-16 14:02:15
updated_at: 2023-03-16 14:02:15
content_type: text
index: climate_gpt_only_giec
vector_id: 151
content:
" Observations have increased understanding \r\nof how extreme events affect individuals, populations and ecosystems, \r\nhelping refine understanding of both ecological tolerance to climate \r\nimpacts and ecological transformations (Section 3.4)."


id: 88813b25c16713408b3b657abb2c39ab
created_at: 2023-03-16 14:02:15
updated_at: 2023-03-16 14:02:15
content_type: text
index: climate_gpt_only_giec
vector_id: 19007
content:
"Paleorecords can be used to trace the correlation between past changes in climate and marine life. Paleoclimate is \r\nreconstructed from the chemical composition of shells and teeth or from sediments and ice cores. Changes to sea \r\nlife signalled by changing biodiversity, extinction or distributional shifts are reconstructed from fossils. Using large \r\ndatasets, we can infer the effects of climate change on sea life over relatively long time scalesusually hundreds to \r\nmillions of years. The advantage of paleorecords is that they provide insights into how climate change affects life \r\nfrom organisms to ecosystems, without the complicating influence of direct human impacts. A key drawback is that \r\nthe paleo and modern worlds do not have fully comparable paleoclimate regimes, dominant marine species and \r\nrates of climate change"


id: 3e81f663ef477814e476f8d3e1ac817
created_at: 2023-03-16 14:02:15
updated_at: 2023-03-16 14:02:15
content_type: text
index: climate_gpt_only_giec
vector_id: 7217
content:
" Nevertheless, the paleorecord can be used to derive fundamental rules by which organisms, \r\necosystems, environments and regions are typically most affected by climate change. For example, the paleorecord \r\nshows that coral reefs repeatedly underwent declines during past warming events, supporting the inference that \r\ncorals may not be able to adapt to current climate warming."


id: 18cc03779a97bf6280a240188c89d85a
created_at: 2023-03-16 14:02:15
updated_at: 2023-03-16 14:02:15
content_type: text
index: climate_gpt_only_giec
vector_id: 1401
content:
"This chapter assesses the current understanding of climate-induced \r\ndrivers, ecological vulnerability and adaptability, risks to coastal \r\nand ocean ecosystems, and human vulnerability and adaptation \r\nto resulting changes in ocean benefits, now and in the future \r\n(Figure 3.2). It starts by assessing the biologically relevant outcomes \r\nof anthropogenic climate-induced drivers (Section  3.2). Next, it \r\nsets out the mechanisms that determine the responses of ocean \r\nand coastal organisms to individual and combined drivers from the \r\ngenetic to the ecosystem level (Section 3.3). This supports a detailed \r\nassessment of the observed and projected responses of coastal and \r\nocean ecosystems to these hazards, placing them in context using the \r\npaleorecord (Section 3.4)"


id: 1941bc022851e51e6df7886397565b87
created_at: 2023-03-16 14:02:15
updated_at: 2023-03-16 14:02:15
content_type: text
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vector_id: 1461
content:
" These observed and projected impacts are \r\nused to quantify consequent risks to delivery of ecosystem services \r\nand the socioeconomic sectors that depend on them, with attention \r\nto the vulnerability, resilience and adaptive capacity of social-\r\necological systems (Section 3.5). The chapter concludes by assessing \r\nthe state of adaptation and governance actions available to address \r\nthese emerging threats while also advancing human development \r\n(Section  3.6). Abbreviations used repeatedly in the chapter are \r\ndefined in Table 3.1."


id: 5fc3aee4860cc3c5462b69d5b62a9f
created_at: 2023-03-16 14:02:15
updated_at: 2023-03-16 14:02:15
content_type: text
index: climate_gpt_only_giec
vector_id: 12642
content:
"overlapping climate-induced drivers and non-climate drivers confound \r\nimplementation and assessment of the success of marine adaptation, \r\nrevealing the complexity of attempting to maintain marine ecosystems \r\nand services through adaptation. SROCC assessed with high confidence\r\nthat while the benefits of many locally implemented adaptations exceed \r\ntheir disadvantages, others are marginally effective and have large \r\ndisadvantages, and overall, adaptation has a limited ability to reduce the \r\nprobable risks from climate change, being at best a temporary solution \r\n(Bindoff et al., 2019a). SROCC also concluded that a portfolio of many \r\ndifferent types of adaptation actions, effective and inclusive governance, \r\nand mitigation must be combined for successful adaptation (Bindoff \r\net al., 2019a). The portfolio of adaptation measures has now been defined \r\n(Section 3.6.2), and individual and combined adaptation solutions have \r\nbeen implemented in several marine sectors (Section 3.6.3)"


id: ad255246828ba57dde50c868dc6b03f8
created_at: 2023-03-16 14:02:15
updated_at: 2023-03-16 14:02:15
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index: climate_gpt_only_giec
vector_id: 24787
content:
" Delays in \r\nmarine adaptation have been partly attributed to the complexity of \r\nocean governance (Section 3.6.4; Cross-Chapter Box 3 and Figure CB3.1 \r\nin Abram et  al., 2019) and to the low priority accorded the ocean in \r\ninternational development goals (Nash et al., 2020), but in recent years \r\nthe ocean is being increasingly incorporated in international climate \r\npolicy and multilateral environmental agreements (Section 3.6.4)."


id: fbe6eb1b80b2e9c95433d4aea2ba4133
created_at: 2023-03-16 14:02:15
updated_at: 2023-03-16 14:02:15
content_type: text
index: climate_gpt_only_giec
vector_id: 37126
content:
"Global mean SST has increased since the beginning of the 20th century \r\nby 0.88degC (very likely range: 0.68-1.01degC), and it is virtually certain\r\nthat the global ocean has warmed since at least 1971 (WGI AR6 \r\nSection  9.2; Fox-Kemper et  al., 2021). A key characteristic of ocean \r\ntemperature change relevant for ecosystems is climate velocity, a \r\nmeasure of the speed and direction at which isotherms move under \r\nclimate change (Burrows et al., 2011), which gives the rate at which \r\nspecies must migrate to maintain constant climate conditions. It has \r\nbeen shown to be a useful and simple predictor of species distribution \r\nshifts in marine ecosystems (Chen et al., 2011; Pinsky et al., 2013; Lenoir \r\net al., 2020). Median climate velocity in the surface ocean has been \r\n21.7 km per decade since 1960, with higher values in the Arctic/sub\u0002Arctic and within 15deg of the Equator (Figure 3.3; Burrows et al., 2011)"


id: a6de8c12f1b3b21e5cb6aa2730e08198
created_at: 2023-03-16 14:02:15
updated_at: 2023-03-16 14:02:15
content_type: text
index: climate_gpt_only_giec
vector_id: 23770
content:
" \r\nWhile climate velocity has been slower in the mesopelagic layer (200-\r\n1000 m) than in the epipelagic layer (0-200 m) over the past 50 years, \r\nit has been shown to be faster in the bathypelagic (1000-4000 m) and \r\nabyssopelagic (>4000 m) layers (Figure 3.4; Brito-Morales et al., 2020), \r\nsuggesting that deep-ocean species could be as exposed to effects of \r\nwarming as species in the surface ocean (Brito-Morales et al., 2020)."


id: 3b7fc59cb508874e439e338705a2099
created_at: 2023-03-16 14:02:15
updated_at: 2023-03-16 14:02:15
content_type: text
index: climate_gpt_only_giec
vector_id: 6710
content:
"Marine heatwaves (MHWs) are periods of extreme seawater temperature \r\nrelative to the long-term mean seasonal cycle, that persist for days to \r\nmonths, and that may carry severe consequences for marine ecosystems \r\nand their services (WGI AR6 Box  9.2; Hobday et  al., 2016a; Smale \r\net  al., 2019; Fox-Kemper et  al., 2021). MHWs became more frequent \r\nover the 20th century (high confidence) and into the beginning of the \r\n21st century, approximately doubling in frequency (high confidence) \r\nand becoming more intense and longer since the 1980s (medium \r\nconfidence) (WGI AR6 Box 9.2; Fox-Kemper et al., 2021). These trends in \r\nMHWs are explained by an increase in ocean mean temperatures (Oliver \r\net al., 2018), and human influence has very likely contributed to 84-\r\n90% of them since at least 2006 (WGI AR6 Box 9.2; Fox-Kemper et al., \r\n2021)"


id: d9fa5652951fbb72a97bac3e91f5d79e
created_at: 2023-03-16 14:02:15
updated_at: 2023-03-16 14:02:15
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index: climate_gpt_only_giec
vector_id: 31819
content:
" The probability of occurrence (as well as duration and intensity) \r\nof the largest and most impactful MHWs that have occurred in the past \r\n30 years has increased more than 20-fold due to anthropogenic climate \r\nchange (Laufkotter et al., 2020)."


id: e97c8fddf942211370333567b880ea7b
created_at: 2023-03-16 14:02:15
updated_at: 2023-03-16 14:02:15
content_type: text
index: climate_gpt_only_giec
vector_id: 34245
content:
"Ocean warming will continue over the 21st century (virtually certain), \r\nwith the rate of global ocean warming starting to be scenario\u0002dependent from about the mid-21st  century (medium confidence). \r\nAt the ocean surface, it is virtually certain that SST will continue to \r\nincrease throughout the 21st century, with increasing hazards to many \r\nmarine ecosystems (WGI AR6 Box 9.2; Fox-Kemper et al., 2021). The \r\nfuture global mean SST increase projected by CMIP6 models for the \r\nperiod 1995-2014 to 2081-2100 is 0.86degC (very likely range: 0.43-\r\n1.47degC) under SSP1-2.6, 1.51degC (1.02-2.19degC) under SSP2-4.5, 2.19degC \r\n(1.56-3.30degC) under SSP3-7.0 and 2.89degC (2.01-4.07degC) under SSP5-\r\n8.5 (WGI AR6 Section 9.2.1; Fox-Kemper et al., 2021). Stronger surface \r\nwarming occurs in parts of the tropics, in the North Pacific, and in the \r\nArctic Ocean, where SST increases by >4degC in 2080-2099 under SSP5-\r\n8.5 (Kwiatkowski et al., 2020)"


id: 3217e290bea985116efb9e2ed3d03ff2
created_at: 2023-03-16 14:02:15
updated_at: 2023-03-16 14:02:15
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index: climate_gpt_only_giec
vector_id: 5292
content:
" The CMIP6 climate models also project \r\nocean warming at the seafloor, with the magnitude of projected changes \r\nbeing less than that of surface waters but having larger uncertainties \r\n(Kwiatkowski et al., 2020). The projected end-of-the-century warming \r\nin CMIP6 as reported here is greater than assessed with Coupled Model \r\nIntercomparison Project  5 (CMIP5) models in AR5 and in SROCC for \r\nsimilar radiative forcing scenarios (Figure 3.5; Kwiatkowski et al., 2020), \r\nbecause of greater climate sensitivity in the CMIP6 model ensemble \r\nthan in CMIP5 (WGI AR6 Chapter 4; Forster et al., 2020; Lee et al., 2021)."


id: a289a8ac3490290ea93f3ac030070186
created_at: 2023-03-16 14:02:15
updated_at: 2023-03-16 14:02:15
content_type: text
index: climate_gpt_only_giec
vector_id: 23134
content:
"Ocean stratification is an important factor controlling biogeochemical \r\ncycles and affecting marine ecosystems. WGI AR6 Section  9.2.1.3 \r\n(Fox-Kemper et  al., 2021) assessed that it is virtually certain that \r\nstratification in the upper 200 m of the ocean has been increasing \r\nsince 1970. Recent evidence has strengthened estimates of the rate \r\nof change (Yamaguchi and Suga, 2019; Li et al., 2020a; Sallee et al., \r\n2021), with an estimated increase of 1.0 +- 0.3% (very likely range) \r\nper decade over the period 1970-2018 (high confidence) (WGI AR6 \r\nSection  9.2.1.3; Fox-Kemper et  al., 2021), higher than assessed in \r\nSROCC. It is very likely that stratification in the upper few hundred \r\nmetres of the ocean will increase substantially in the 21st century in all \r\nocean basins, driven by intensified surface warming and near-surface \r\nfreshening at high latitudes (WGI AR6 Section 9.2.1.3; Capotondi et al., \r\n2012; Fu et al., 2016; Bindoff et al., 2019a; Kwiatkowski et al"


id: f6db4856b347a368edec9e7ec4e57192
created_at: 2023-03-16 14:02:15
updated_at: 2023-03-16 14:02:15
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index: climate_gpt_only_giec
vector_id: 36351
content:
"units in 2081-2100 relative to 1995-2014, for SSP1-2.6, SSP2-4.5, \r\nSSP3-7.0 and SSP5-8.5, respectively (Figure 3.5; WGI AR6 Section 4.3.2; \r\nKwiatkowski et al., 2020; Lee et al., 2021). Projected changes in surface \r\npH are relatively uniform in contrast with those of other surface\u0002ocean variables, but they are largest in the Arctic Ocean (Figure 3.6; \r\nWGI AR6 Section  5.3.4.1; Canadell et  al., 2021). Similar declines in \r\nthe concentration of carbonate ions are projected by Earth system \r\nmodels (ESMs; Bopp et al., 2013; Gattuso et al., 2015; Kwiatkowski \r\net al., 2020). The North Pacific, the Southern Ocean and Arctic Ocean \r\nregions will become undersaturated for calcium carbonate minerals \r\nfirst (Orr et al., 2005; Portner et al., 2014). Concurrent impacts on the \r\nseasonal amplitude of carbonate chemistry variables are anticipated \r\n(i.e"


id: 6192b135755897dc64566f53d0cb3bb1
created_at: 2023-03-16 14:02:15
updated_at: 2023-03-16 14:02:15
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vector_id: 12921
content:
", increased amplitude for pCO2 and hydrogen ions, decreased \r\namplitude for carbonate ions; McNeil and Sasse, 2016; Kwiatkowski \r\nand Orr, 2018; Kwiatkowski et al., 2020)."


id: f636651e0a8a27fbea535c7b09f07971
created_at: 2023-03-16 14:02:15
updated_at: 2023-03-16 14:02:15
content_type: text
index: climate_gpt_only_giec
vector_id: 36244
content:
"Ocean acidification is also developing in the ocean interior (very high \r\nconfidence) due to the transport of anthropogenic CO2 to depth by \r\nocean currents and mixing (WGI AR6 Section 5.3.3.1; Canadell et al., \r\n2021). There, it leads to the shoaling of saturation horizons of aragonite \r\nand calcite (high confidence) (WGI AR6 Section 5.3.3.1; Canadell et al., \r\n2021), below which dissolution of these calcium carbonate minerals \r\nis thermodynamically favoured. The calcite or aragonite saturation \r\nhorizons have migrated upwards in the North Pacific (1-2 m yr-1 over \r\n1991-2006) (Feely et al., 2012) and in the Irminger Sea (10-15 m yr-1\r\nfor the aragonite saturation horizon over 1991-2016) (Perez et  al., \r\n2018). In some locations of the western Atlantic Ocean, calcite \r\nsaturation depth has risen by ~300 m since the pre-industrial era \r\ndue to increasing concentrations of deep-ocean dissolved inorganic \r\ncarbon (Sulpis et al., 2018)"


id: 3acfb1d74deea7af037beecd127ed05f
created_at: 2023-03-16 14:02:15
updated_at: 2023-03-16 14:02:15
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index: climate_gpt_only_giec
vector_id: 6621
content:
" In the Arctic, where some coastal surface \r\nwaters are already undersaturated with respect to aragonite due to \r\nthe degradation of terrestrial organic matter (Mathis et  al., 2015; \r\nSemiletov et al., 2016), the deep aragonite saturation horizon shoaled \r\non average 270 +- 60 m during 1765-2005 (Terhaar et al., 2020)."


id: 23ed78871a48d585bbac2dbbeb72a2e3
created_at: 2023-03-16 14:02:15
updated_at: 2023-03-16 14:02:15
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index: climate_gpt_only_giec
vector_id: 3092
content:
"Detection and attribution of ocean acidification in coastal environments \r\nare more difficult than in the open ocean due to larger spatio-temporal \r\nvariability of carbonate chemistry (Duarte et  al., 2013; Laruelle \r\net al., 2017; Torres et al., 2021) and to the influence of other natural \r\nacidification drivers such as freshwater and high-nutrient riverine \r\ninputs (Cai et al., 2011; Laurent et al., 2017; Fennel et al., 2019; Cai \r\net  al., 2020) or anthropogenic acidification drivers (Section  3.1) like \r\natmospherically deposited nitrogen and sulphur (Doney et  al., 2007; \r\nHagens et  al., 2014). Since AR5, the observing network in coastal \r\noceans has expanded substantially, improving understanding of both \r\nthe drivers and amplitude of observed variability (Sutton et al., 2016)"


id: e0960d55d9e6fcbf6892dcfe12657672
created_at: 2023-03-16 14:02:15
updated_at: 2023-03-16 14:02:15
content_type: text
index: climate_gpt_only_giec
vector_id: 32834
content:
" \r\nRecent studies indicate that two more decades of observations may be \r\nrequired before anthropogenic ocean acidification emerges over natural \r\nvariability in some coastal sites and regions (WGI AR6 Section 5.3.5.2; \r\nSutton et al., 2019; Turk et al., 2019; Canadell et al., 2021)."


id: cd5c3814db590d14d658c8e759820c9b
created_at: 2023-03-16 14:02:15
updated_at: 2023-03-16 14:02:15
content_type: text
index: climate_gpt_only_giec
vector_id: 29855
content:
"The most recent estimates of future oxygen loss in the subsurface \r\nocean (100-600 m), using CMIP6 models, amount to -4.1  +-  4.2 \r\n(very likely range), -6.6 +- 5.7, -10.1 +- 6.7 and -11.2 +- 7.7% in \r\n2081-2100 relative to 1995-2014 for SSP1-2.6, SSP2-4.5, SSP3-7.0 \r\nand SSP5-8.5, respectively (Figure  3.5; Kwiatkowski et  al., 2020). \r\nBased on these CMIP6 projections, WGI AR6 concludes that the \r\noxygen content of the subsurface ocean is projected to decline to \r\nhistorically unprecedented conditions over the 21st century (medium \r\nconfidence) (WGI AR6 Section 5.3.3.2; Canadell et al., 2021). These \r\ndeclines are greater (by 31-72%) than simulated by the CMIP5 \r\nmodels in their Representative Concentration Pathway (RCP) \r\nanalogues, a likely consequence of enhanced surface warming and \r\nstratification in CMIP6 models (Figure 3.5; Kwiatkowski et al., 2020)"


id: ef8c1e31e0946a25889f99c690ad7ac3
created_at: 2023-03-16 14:02:15
updated_at: 2023-03-16 14:02:15
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index: climate_gpt_only_giec
vector_id: 35181
content:
" \r\nAt the regional scale and for subsurface waters, projected changes \r\nare not spatially uniform, and there is lower agreement among \r\nmodels than they show for the global mean trend (Bopp et al., 2013; \r\nKwiatkowski et al., 2020). In particular, large uncertainties remain for \r\nthese future projections of ocean deoxygenation in the subsurface \r\ntropical oceans, where the major OMZs are located (Cabre et  al., \r\n2015; Bopp et al., 2017)."


id: 873af24c59b4be06b7cb1ae891cd1d27
created_at: 2023-03-16 14:02:15
updated_at: 2023-03-16 14:02:15
content_type: text
index: climate_gpt_only_giec
vector_id: 18813
content:
"Earth system models project distinct regional evolutions of the \r\ndifferent CIDs over the 21st century (very high confidence) (Figures 3.5, \r\n3.6, 3.7; Kwiatkowski et al., 2020). Tropical and subtropical oceans are \r\ncharacterised by projected warming and acidification, accompanied by \r\ndeclining nitrate concentrations in equatorial upwelling regions. The \r\nNorth Atlantic is characterised by a high exposure to acidification and \r\ndeclining nitrate concentrations. The North Pacific is characterised by \r\nhigh sensitivity to compound changes, with high rates of warming, \r\nacidification, deoxygenation and nutrient depletion. In contrast, the \r\ndevelopment of compound hazards is limited in the Southern Ocean, \r\nwhere rates of warming and nutrient depletion are lower"


id: e7f7667f66b097ebb83fd06bd2050638
created_at: 2023-03-16 14:02:15
updated_at: 2023-03-16 14:02:15
content_type: text
index: climate_gpt_only_giec
vector_id: 33993
content:
" The Arctic \r\nOcean is characterised by the highest rates of acidification and \r\nwarming, strong nutrient depletion, and it will likely become practically \r\nsea ice free in the September mean for the first time before the year \r\n2050 in all SSP scenarios (high confidence) (Figures  3.5, 3.6, 3.7; \r\nSections 3.2.2, 3.2.3)."


id: 7518e17eedbaf597add1bf6ac8c96cc6
created_at: 2023-03-16 14:02:15
updated_at: 2023-03-16 14:02:15
content_type: text
index: climate_gpt_only_giec
vector_id: 16017
content:
"The availability of nutrients in the surface ocean often limits primary \r\nproductivity, with implications for marine food webs and the biological \r\ncarbon pump. Nitrogen availability tends to limit phytoplankton \r\nproductivity throughout most of the low-latitude ocean, whereas \r\ndissolved iron availability limits productivity in high-nutrient, low\u0002chlorophyll regions, such as in the main upwelling region of the Southern \r\nOcean and the Eastern Equatorial Pacific (high confidence) (Moore \r\net  al., 2013; IPCC, 2019b). Phosphorus, silicon, other micronutrients \r\nsuch as zinc, and vitamins can also co-limit marine phytoplankton \r\nproductivity in some ocean regions (Moore et  al., 2013). Whereas \r\nsome studies have shown coupling between climate variability and \r\nnutrient trends in specific regions, such as in the North Atlantic (Hatun \r\net  al., 2016), North Pacific (Di Lorenzo et  al., 2009; Yasunaka et  al"


id: 2c2c93ebaf372f287352429c4dfc01aa
created_at: 2023-03-16 14:02:15
updated_at: 2023-03-16 14:02:15
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index: climate_gpt_only_giec
vector_id: 4376
content:
", \r\n2014) and tropical (Stramma and Schmidtko, 2021) Oceans, very few \r\nstudies have been able to detect long-term changes in ocean nutrient \r\nconcentrations (but see Yasunaka et al., 2016)."


id: d712bd8323423c141c0bf9402ce85221
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content:
"The literature assessed in SROCC mainly focused on surface ocean \r\nproperties and gradual mean changes. Since then, the time of \r\nemergence has also been investigated for subsurface properties, ocean \r\nextreme events and particularly vulnerable regions, such as the Arctic \r\nOcean (Hameau et al., 2019; Oliver et al., 2019; Burger et al., 2020; \r\nLandrum and Holland, 2020; Schlunegger et al., 2020), but subsequent \r\nassessments are low confidence due to limited evidence. Below \r\nthe surface, changes in temperature typically emerge from internal \r\nvariability prior to changes in oxygen; however, in about a third of the \r\nglobal thermocline, deoxygenation emerges prior to warming (Hameau \r\net al., 2019). Permanent MHW states, defined as when SST exceeds \r\nthe MHW threshold continuously over a full calendar year, will emerge \r\nduring the 21st  century in many parts of the surface ocean (Oliver \r\net al., 2019)"


id: caf3e484131e498facec05abac800d1e
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" Ocean acidification extremes have already emerged from \r\nbackground natural internal variability during the 20th century in most \r\nof the surface ocean (Burger et al., 2020). In the Arctic, anthropogenic \r\nsea ice changes have already emerged from the background internal \r\nvariability, and anthropogenic alteration of air temperatures will \r\nemerge in the early- to mid-21st century (Landrum and Holland, 2020)."


id: 71bb791484701c5955b8468b987eab20
created_at: 2023-03-16 14:02:15
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content:
"This section assesses new evidence since AR5 (Portner et al., 2014) and \r\nSROCC (Bindoff et al., 2019a) regarding biotic responses to multiple \r\nenvironmental drivers. It assesses differential sensitivities among life \r\nstages within individual organisms, changing responses across scales \r\nof biological organisation and the potential for evolutionary adaptation \r\nto climate change (e.g., Przeslawski et  al., 2015; Boyd et  al., 2018; \r\nReddin et al., 2020), providing examples and identifying key gaps and \r\nuncertainties that limit our ability to project the ecological impact of \r\nmultiple climate-induced drivers (Figure 3.8a). The assessment includes \r\nphysiological responses to single environmental drivers and their \r\nunderlying mechanisms (Section 3.3.2), the characteristics of multiple \r\ndrivers and organisms' responses to them (Section 3.3.3), short-term \r\nacclimation and longer-term evolutionary adaptation of populations \r\n(Section  3.3"


id: 3c8c46f94d0982b0800df3af552a4968
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content:
"4), and it concludes with an assessment of progress in \r\nupscaling laboratory findings to ecosystems within in situ settings \r\n(Figure 3.8b; Section 3.3.5)."


id: 223b43986bfa074c4251b9cdad10eb9a
created_at: 2023-03-16 14:02:15
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vector_id: 2835
content:
"Paleoclimatology observations are useful to assess multiple hazards \r\nof environmental change while excluding direct anthropogenic \r\nimpacts (Section 3.4.3.3). Ancient intervals of rapid climate warming \r\nthat occurred between 300 and 50  million  years ago (Ma) were \r\ntriggered by the release of greenhouse gases (high confidence). The \r\nsources of greenhouse gases varied but include volcanic degassing \r\nfrom continental flood basalts and methane hydrates stored in \r\nmarine sediments and soils (Foster et al., 2018). Six extreme ancient \r\nhyperthermal events are known from the last 300 Ma, when tropical \r\nSSTs reached 1.5degC-10degC warmer than pre-industrial conditions, and \r\nwith substantial impacts on ancient life (Cross-Chapter Box  PALEO \r\nin Chapter  1). Warming and deoxygenation in the oceans were \r\nclosely associated in hyperthermal events (high confidence), with \r\nanoxia reaching the photic zone and abyssal depths (Kaiho et  al., \r\n2014; Muller et al., 2017; Penn et al"


id: faf9b4407c471c1c8a71e7a047d65a91
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", 2018; Weissert, 2019), whereas \r\nocean acidification has not been demonstrated consistently (medium \r\nconfidence) (Honisch et al., 2012; Penman et al., 2014; Clarkson et al., \r\n2015; Harper et al., 2020a; Jurikova et al., 2020; Muller et al., 2020)."


id: 3837511784b5496f19e970f3c99f58a1
created_at: 2023-03-16 14:02:15
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content:
"Temperature affects the movement and transport of molecules and, \r\nthereby, the rates of all biochemical reactions; thus, ongoing and \r\nprojected warming (Section 3.2.2.1) that remains below an organism's \r\nphysiological optimum will generally raise metabolic rates (very \r\nhigh confidence) (Portner et  al., 2014). Beyond this optimum (Topt; \r\nFigure  3.9), metabolism typically decreases sharply, finally reaching \r\na critical threshold (Tcrit) beyond which enzymes become thermally \r\ninactivated and cells undergo oxidative stress. Local and regional \r\nadaptation affect the heat tolerance thresholds of organisms. For \r\nexample, organisms adapted to thermally stable environments (e.g., \r\ntropical, polar, deep sea) are often more sensitive to warming than \r\nthose from thermally variable environments (e.g., estuaries) (very \r\nhigh confidence) (Section  3.4; Sunday et  al., 2019; Collins et  al., \r\n2020). Heat tolerance also decreases with increasing organisational \r\ncomplexity (Storch et al"


id: cfcef10164644f8e4963a8c3670c6670
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", 2014; Portner and Gutt, 2016) and is lower in \r\neggs, embryos and spawning fish than for their larval stages or adults \r\noutside the spawning season (high confidence) (Dahlke et al., 2020b). \r\nBy altering physiological responses, projected changes in ocean \r\nwarming (Section 3.2.2.1) will modify growth, migration, distribution, \r\ncompetition, survival and reproduction (very high confidence) \r\n(Messmer et al., 2017; Dahlke et al., 2018; Andrews et al., 2019; Pinsky \r\net al., 2019; Anton et al., 2020)."


id: 70b4ad61f25f04e7dbdeb88cef53b223
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content:
"Increased density stratification and mixed-layer shallowing, caused by \r\nwarming, freshening and sea ice decline, can alter light climate and \r\nnutrient availability within the surface mixed layer (high confidence) \r\n(Section  3.2.2.3). As light and nutrient levels drive photosynthesis, \r\nchanges in these drivers directly affect primary producers, often in \r\ndifferent directions (Matsumoto et al., 2014; Deppeler and Davidson, \r\n2017). Decreased upward nutrient supply is expected to decrease \r\nprimary production in the low-latitude ocean (medium confidence) \r\n(Section  3.4.4.2.1; Moore et  al., 2018a; Kwiatkowski et  al., 2019). \r\nAlternatively, higher mean underwater light levels resulting from \r\nchanges in sea ice and/or mixed layer shallowing can increase primary \r\nproduction in high-latitude offshore regions, provided nutrient levels \r\nremain sufficiently high (medium confidence) (Section 3.4.4.2.1; Cross\u0002Chapter Paper 6; Vancoppenolle et al"


id: 2d9fc7bb6cb7668b597d70ed55379b5b
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content:
", 2013; Deppeler and Davidson, \r\n2017; Tedesco et al., 2019; Ardyna and Arrigo, 2020; Lannuzel et al., \r\n2020). In some parts of the open Southern Ocean, where iron limitation \r\nlargely controls primary productivity (Tagliabue et al., 2017), changes \r\nin wind fields will deepen the summer mixed-layer depth (Panassa \r\net al., 2018), entrain more nutrients, and raise primary productivity in \r\nthe future (medium confidence) (Cross-Chapter Paper 6; Hauck et al., \r\n2015; Leung et al., 2015; Moore et al., 2018a; Kwiatkowski et al., 2020)."


id: b1952468e99ba1d2ec70a285c159eda1
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content:
"macroalgal and seagrass species (high confidence) (Portner et al., 2014; \r\nSeifert et al., 2020; Zimmerman, 2021), while lower pH levels decrease \r\ncalcification (high confidence) (Portner et al., 2014; Falkenberg et al., \r\n2018; Doney et  al., 2020; Fox et  al., 2020; Reddin et  al., 2020) or \r\nsilicification (low confidence) (Petrou et al., 2019). Organisms' capacity \r\nto compensate for or resist acidification of internal fluids depends \r\non their capacity for acid-base regulation, which differs due to \r\norganisms' wide-ranging biological complexity and adaptive abilities \r\n(low to medium confidence) (Vargas et  al., 2017; Melzner et  al., \r\n2020). Detrimental impacts of acidification include decreased growth \r\nand survival, and altered development, especially in early life stages \r\n(high confidence) (Dahlke et al., 2018; Onitsuka et al., 2018; Hancock \r\net al., 2020), along with lowered recruitment and altered behaviour in \r\nanimals (Kroeker et al"


id: 48a6ab76077f1971b9b7cd081d516822
created_at: 2023-03-16 14:02:15
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content:
", 2013a; Wittmann and Portner, 2013; Clements \r\nand Hunt, 2015; Cattano et al., 2018; Esbaugh, 2018; Bednarsek et al., \r\n2019; Reddin et al., 2020). For finfish, laboratory studies of behavioural \r\nand sensory consequences of ocean acidification showed mixed results \r\n(Rossi et al., 2018; Nagelkerken et al., 2019; Stiasny et al., 2019; Velez \r\net  al., 2019; Clark et  al., 2020; Munday et  al., 2020). Calcifiers are \r\ngenerally more sensitive to acidification (e.g., for growth and survival) \r\nthan non-calcifying groups (high confidence) (Kroeker et  al., 2013a; \r\nWittmann and Portner, 2013; Clements and Hunt, 2015; Cattano et al., \r\n2018; Bednarsek et al., 2019; Reddin et al., 2020; Seifert et al., 2020). \r\nFor calcifying primary producers, including phytoplankton and coralline \r\nalgae, ocean acidification has different, often opposing effects, for \r\nexample, decreasing calcification while photosynthetic rates increase \r\n(high confidence) (Riebesell et al., 2000; Van de Waal et al"


id: 121e84955aa35862856756cc6f3dc180
created_at: 2023-03-16 14:02:15
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vector_id: 349
content:
"Climate-induced drivers fluctuate on time scales ranging from diurnal \r\nto annual, with potential consequences for organismal responses \r\n(Figure 3.10), but these fluctuations are commonly not incorporated \r\nexperimentally. Experiments that simulate natural fluctuations in \r\ndrivers, especially beyond tidal or diel cycles, can result in more \r\ndetrimental impacts than those based on quasi-constant conditions \r\n(Eriander et al., 2015; Sunday et al., 2019), but can also ameliorate \r\neffects (Comeau et al., 2014; Laubenstein et al., 2020; Cabrerizo et al., \r\n2021), confirming that the influence of environmental variability \r\nrequires evaluation (Dowd et al., 2015). Marine heatwaves exacerbate \r\nthe impacts of rising mean temperatures, with major ecological \r\nconsequences (very high confidence) (Frolicher et al., 2018; IPCC, 2018; \r\nArafeh-Dalmau et al., 2020; Laufkotter et al., 2020)"


id: 4c8f49626f64a71aac1b0fd09c5b54db
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vector_id: 9467
content:
" Higher temperature \r\nvariability decreased phytoplankton growth and calcification in \r\nEmiliania huxleyi relative to a stable warming regime (Wang et  al., \r\n2019b). Diel fluctuations (i.e., over 24 h) in carbonate chemistry \r\nsuperimposed on current and future pCO2 levels influenced diatom \r\nspecies differently, depending on their habitat (Li et  al., 2016). CO2\r\nfluctuations overlaid on changing mean values also altered phenotypic \r\nevolutionary outcomes of picoeukaryotic algae (Schaum et al., 2016). \r\nIn the bivalve Mytilus edulis, fluctuating pH regimes exerted higher \r\nmetabolic costs (Mangan et  al., 2017), while salinity fluctuations \r\nmight be more influential than pH fluctuations in other bivalves (Velez \r\net al., 2016). The amplitude of diel and seasonal pH and CO2 changes \r\nare projected to increase in the future due to lowered CO2 seawater \r\nbuffering capacity (very high confidence) (Section 3.2.3.1; Burger et al., \r\n2020), which can impose additional stress on organisms."


id: c3709fd879b8e6fb1dc6f2e5271f775a
created_at: 2023-03-16 14:02:15
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vector_id: 28320
content:
"Oxygen concentrations affect aerobic and anaerobic processes, \r\nincluding energy metabolism and denitrification. Projected decreases \r\nin dissolved oxygen concentration (Section 3.2.3.2) will thus impact \r\norganisms and their biogeography in ways dependent upon their \r\noxygen requirements (Deutsch et  al., 2020), which are highest for \r\nlarge, multicellular organisms (Portner et al., 2014). The upper ocean \r\ngenerally contains high dissolved-oxygen concentrations due to \r\nair-sea exchange and photosynthesis, but in subsurface waters, \r\ndeoxygenation may impair aerobic organisms in multiple ways \r\n(Oschlies et al., 2018; Galic et al., 2019; Thomas et al., 2019; Sampaio \r\net  al., 2021). Many processes contribute to lowered oxygen levels: \r\naltered ventilation and stratification; microbial respiration enhanced \r\nby nearshore eutrophication; and less oxygen solubility in warmer \r\nwaters. For example, deoxygenation in highly eutrophic estuarine and \r\ncoastal marine ecosystems (Section 3.4"


id: 75cc3c63d1825d10a923d96bee8e88a
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content:
"2) can result from accelerated \r\nmicrobial activity, leading to acute organismal responses. Under \r\nhypoxia (oxygen concentrations <=2 mg  l-1; Limburg et  al., 2020), \r\nphysiological and ecological processes are impaired and communities \r\nundergo species migration, replacement and loss, transforming \r\ncommunity composition (very high confidence) (Chu and Tunnicliffe, \r\n2015; Gobler and Baumann, 2016; Sampaio et  al., 2021). Hypoxia \r\ncan lead to expanding OMZs, which will favour specialised microbes \r\nand hypoxia-tolerant organisms (medium confidence) (Breitburg \r\net  al., 2018; Ramirez-Flandes et  al., 2019). As respiration consumes \r\noxygen and produces CO2, lowered oxygen levels are often interlinked \r\nwith acidification in coastal and tropical habitats (Rosa et al., 2013; \r\nGobler and Baumann, 2016; Feely et al., 2018) and is an example of a \r\ncompound hazard (Sections 3.2.4.1, 3.4.2.4)."


id: 5dc918eaccf4464f60df9fac318e4456
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"(b) The hierarchy of accumulating physiological knowledge (grey layers), from single (e.g., Portner et al., 2012) to multiple drivers, and from simple outcomes (e.g., Sciandra et al., \r\n2003), interactions among drivers (e.g., Crain et al., 2008) and identification of physiological roles of drivers (e.g., Bach et al., 2015) to mechanistic understanding of drivers (e.g., \r\nThomas et al., 2017). At present, the upper grey layer has been achieved, in full, for two drivers (e.g., temperature and nutrient concentrations), with validation of dual controls \r\non phytoplankton growth rate (Thomas et al., 2017). Hatched layers denote major advances since WGII AR5 Chapter 6 (Portner et al., 2014). The green layer indicates the level of \r\nunderstanding potentially needed to project the response of marine life subjected to multiple drivers"


id: c6055dfeba8ccda336a5defbb75d5af5
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" Red horizontal arrows indicate the influence of confounding factors on our \r\ncurrent understanding, including population genetics, fluctuating oceanic conditions or extreme events."


id: 958ac0a87ee0fece79f96cdacdf35313
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"duration of its exposure to these drivers and associated sensitivities. \r\nBoth geographic location (e.g., polar, tropical) and marine habitat (e.g., \r\nbenthic, pelagic) strongly affect the combination of climate and non\u0002climate drivers to which organisms are exposed. Non-climate drivers \r\n(Section 3.1) can dominate outcomes or amplify vulnerability to climate\u0002induced drivers, with mostly detrimental effects such as extirpation \r\n(very high confidence) (Section 3.4; Boyd et al., 2018; Gissi et al., 2021), \r\nand unique feedbacks may exist between climate change and drivers \r\nlike habitat loss or invasive species that further confound climate\u0002change effects (Ortiz et al., 2018; Wolff et al., 2018; Gissi et al., 2021). \r\nIndividual responses are further influenced by an organism's behaviour, \r\ntrophic level and life-history strategy (Figure 3.10; Przeslawski et al., \r\n2015; Boyd et al., 2018)"


id: c162ad80db62c975a5736847177d804
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" Evidence is increasing that some life-history \r\nstages are more sensitive to specific drivers than others (Dahlke et al., \r\n2020b). To identify the most influential drivers for an organism requires \r\ntargeting key traits (e.g., calcification, reproduction). The trophic level \r\nof the organism must also be considered, because autotrophs directly \r\ndepend on light and nutrients while invertebrates are often more \r\nsensitive to changes in oxygen or altered prey, but temperature plays \r\na key role for both groups (Figure 3.10b)."


id: 30385f448f0b41d6f7816c7bdd98e721
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"Thermal sensitivity of pelagic primary producers changes with nutrient \r\nsupply (high confidence) (Thomas et al., 2017; Maranon et al., 2018; \r\nFernandez et al., 2020). Phosphorus limitation lowers the temperature \r\noptimum for growth of phytoplankton, making these organisms more \r\nprone to heat stress (Thomas et al., 2017; Bestion et al., 2018). This \r\ntrend may hold for open-ocean phytoplankton, which are often iron\u0002limited (medium confidence) (Boyd, 2019). Such temperature-nutrient \r\ninteractions might be especially relevant during summer MHWs \r\n(Section  3.2.2.1; Cross-Chapter Box  EXTREMES in Chapter  2; IPCC, \r\n2018; Holbrook et  al., 2019; DeCarlo et  al., 2020; Hayashida et  al., \r\n2020), when primary producers are often nutrient-limited and near their \r\nthermal limits. Increasingly frequent and intense MHWs along with \r\nprojected decreases in nutrient availability (Section 3.2.3.3) may push \r\nsome primary producers beyond tolerance thresholds"


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" Temperature-\r\nnutrient interactions can also alter the photosynthesis-to-respiration \r\nratio in phytoplankton (Maranon et al., 2018). Overall, rising metabolic \r\nrates due to warming will be restricted to primary producers in high\u0002nutrient regions (medium confidence) (Thomas et al., 2017; Maranon \r\net al., 2018). For zooxanthellae-containing corals, nutrient supply from \r\nupwelling or from runoff can increase coral susceptibility to bleaching \r\nduring warm-season MHWs (DeCarlo et al., 2020; Wooldridge, 2020)."


id: c212e59f63c74e58d05b397638c559ff
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vector_id: 28114
content:
"Co-occurring environmental drivers often cause complex organismal \r\nresponses (high confidence) (Portner et  al., 2014). Individual drivers \r\ncan have detrimental, neutral or beneficial effects, depending on the \r\nrelationship between driver and physiological process (Section 3.3.2; \r\nFigure 3.9a). Multiple drivers can have interactive effects, where the \r\nresponse to one driver alters the sensitivity to another, and outcomes \r\ncannot be deduced from individual drivers' effects (Figure  3.9b). \r\nImpacts of multiple drivers can be additive, synergistic or antagonistic \r\n(Figure 3.9c; Crain et al., 2008; Piggott et al., 2015; Boyd et al., 2018; \r\nBindoff et al., 2019a). Well-controlled laboratory studies on multiple\u0002driver effects have revealed insights into the mode of action of \r\nindividual drivers and their interdependence (Kroeker et al., 2017; Gao \r\net al., 2019; Reddin et al., 2020; Seifert et al., 2020; Green et al., 2021b; \r\nSampaio et  al., 2021)"


id: 6e67ec5041b6d4c28c79620c785e6d9b
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content:
" Understanding the outcomes of interactive \r\ndrivers is important for robustly assessing risks to organisms under \r\ndifferent climate-change scenarios."


id: 50cc6d5513f9ddf8561bd22c3a12b21c
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content:
"The effects of ocean acidification on growth, metabolic rates or \r\nelemental composition of primary producers changes with nutrient \r\navailability and light conditions (high confidence) (Gao et al., 2019; \r\nSeifert et  al., 2020). While interactions with nutrients are often \r\nadditive in phytoplankton, diatoms revealed predominantly synergistic \r\ninteractions (Seifert et al., 2020). Growth or photosynthesis of some \r\ndiatom and HAB species, for instance, are stimulated by ocean \r\nacidification only if nutrients are replete (Hoppe et al., 2013; Boyd et al., \r\n2015b; Eberlein et al., 2016; Griffith et al., 2019a). Interactions with \r\nlight are more complex because relative effects of ocean acidification \r\nare larger under limiting irradiances, while saturating light levels \r\ndecrease beneficial or detrimental effects on these processes (Kranz \r\net al., 2010; Garcia et al., 2011; Rokitta and Rost, 2012; Heiden et al., \r\n2016)"


id: 179c0ad9b49ef7fa8a39053cd6fa8e37
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content:
" For the coccolithophore Emiliania huxleyi, for example, the \r\nimpacts of ocean acidification are less detrimental under high light \r\navailability, which could partly explain why this species is moving \r\npoleward (Winter et al., 2014; Kondrik et al., 2017; Neukermans et al., \r\n2018), although acidification is more pronounced in polar waters \r\n(Section 3.2.3.1; Cross-Chapter Paper 6). Under excess light, however, \r\nthe detrimental impacts of ocean acidification are amplified for many "


id: cc9ebabac4c5c6a7db64fb07808c0807
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index: climate_gpt_only_giec
vector_id: 29731
content:
"Warming and rising CO2 concentrations enhance growth and/or \r\nphotosynthetic rates in many species of cyanobacteria, picoeukaryotes, \r\ncoccolithophores, dinoflagellates and diatoms (high confidence) \r\n(Fu et  al., 2007; Sett et  al., 2014; Hoppe et  al., 2018a; Wolf et  al., \r\n2018; Brandenburg et al., 2019), and the optimum pCO2 for growth \r\nand/or primary production shifts upward under warming (medium \r\nconfidence) (Sett et al., 2014; Hoppe et al., 2018a). Warming and ocean \r\nacidification appear to jointly favour the proliferation and toxicity of \r\nharmful algal bloom (HAB) species (limited evidence, high agreement) \r\n(Section  3.5.5.3; Bindoff et  al., 2019a; Brandenburg et  al., 2019; \r\nGriffith et  al., 2019a; Wells et  al., 2020), but a 2021 analysis found \r\nno uniform global trend in HABs or their distribution over 1985-2018 \r\nonce field data were adjusted for regional variations in monitoring \r\neffort (Hallegraeff et al., 2021)"


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content:
" The predominantly detrimental impacts \r\nof ocean acidification on coccolithophores can partly be offset by \r\nwarming (Seifert et al., 2020) but also be exacerbated, depending on \r\nthe magnitudes of drivers (D'Amario et al., 2020). For non-calcifying "


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"Lievanos et al., 2019; Schwieterman et al., 2019). Warming and hypoxia \r\nare mostly positively correlated and tolerances to both phenomena \r\nare often linked after long-term acclimation (e.g., Bouyoucos et  al., \r\n2020). Acute short-term heat shocks can impair hypoxia tolerance, \r\nfor instance, in intertidal fish (McArley et al., 2020). This is relevant \r\nfor shallow waters, specifically for MHWs (Section  3.2.2.1; Hobday \r\net al., 2016a; IPCC, 2018; Collins et al., 2019a). Ocean acidification can \r\nincrease hypoxia tolerance in some cases, possibly by downregulating \r\nactivity (Faleiro et  al., 2015) and/or changing blood oxygenation \r\n(Montgomery et al., 2019). Other studies, however, reported additive \r\nnegative effects of acidification and warming on hypoxia tolerance \r\n(Schwieterman et al., 2019; Gotze et al., 2020), in line with the oxygen\u0002and capacity-limited thermal tolerance (OCLTT) hypothesis presented \r\nin AR5 (Portner et  al"


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content:
", 2014): Warming causes increased metabolic \r\nrates and oxygen demand in ectotherms, which at some point exceed \r\nsupply capacities (which also depend on environmental oxygen \r\navailability) and reduce aerobic scope. In consequence, expansion of \r\nOMZs and other regions where warming, hypoxia and acidification \r\ncombine will further reduce habitat for many fish and invertebrates \r\n(high confidence) (Sections 3.4.3.2, 3.4.3.3)."


id: ecffb8b22d0dd11aee2d98184eae525f
created_at: 2023-03-16 14:02:15
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content:
"Food availability modulates, and may be more influential than, \r\nother driver responses by affecting the energetic and nutritional \r\nstatus of animals (Cole et  al., 2016; Stiasny et  al., 2019; Cominassi \r\net al., 2020). Laboratory studies conducted under an excess of food \r\nrisk underestimating the ecological effects of climate-induced \r\ndrivers, because increased feeding rates may help mitigate adverse \r\neffects (Nowicki et  al., 2012; Towle et  al., 2015; Cominassi et  al., \r\n2020). Lowered food availability from reduced open-ocean primary \r\nproduction (Sections 3.2.3.3, 3.4.4.2.1) will act as an additional driver, \r\namplifying the detrimental effects of other drivers. However, warming \r\nand higher CO2 availability may increase primary productivity in some \r\ncoastal areas (Section 3.4.4.1), ameliorating the adverse direct effects \r\non animals (e.g., Sswat et al., 2018). Due to the few studies addressing \r\nfood availability under multiple-driver scenarios (Thomsen et al"


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", 2013; \r\nPistevos et al., 2015; Towle et al., 2015; Ramajo et al., 2016; Brown \r\net al., 2018a; Cominassi et al., 2020), there is medium confidence in its \r\nmodulating effect on climate-induced driver responses."


id: 85c7143f9c0f7d9dc28200136f29b773
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content:
"When changing CO2 concentrations affect marine ectotherms, they \r\ntypically combine additively or synergistically with warming (medium \r\nconfidence) (e.g., Lefevre, 2016; Reddin et al., 2020; Sampaio et al., \r\n2021), and their cumulative effects can lead to detrimental, neutral or \r\nbeneficial effects (high confidence) (Figure 3.9a; Bennett et al., 2017; \r\nBuscher et al., 2017; Dahlke et al., 2017; Foo and Byrne, 2017; Johnson \r\net al., 2017b; Cominassi et al., 2019). Higher ocean CO2 influences the \r\nthermal tolerance of species adapted to extreme but stable habitats \r\nin tropical and polar regions, more than that of thermally tolerant \r\ngeneralists (high confidence) (Byrne et al., 2013; Schiffer et al., 2014; \r\nFlynn et al., 2015; Kunz et al., 2016; Portner et al., 2017; Kunz et al., \r\n2018; Bindoff et  al., 2019a; but see Ern et  al., 2017), especially in \r\nearly life stages (Dahlke et  al., 2020a)"


id: e0248bea479d9844e66db7064f755143
created_at: 2023-03-16 14:02:15
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vector_id: 32757
content:
" In thermal generalists from \r\ntemperate and subtropical species, warming and ocean acidification \r\ngenerally have detrimental effects on growth and survival (e.g., Gao \r\net al., 2020), but warming can also alleviate the detrimental effects \r\nof ocean acidification by increasing metabolic rate and/or growth \r\n(Garzke et  al., 2020), provided that other conditions (e.g., thermal \r\nniche, food availability) are beneficial. For example, larval growth and \r\nsurvival of Australasian snapper (Pagrus auratus) appear to benefit \r\nfrom combined acidification and warming (but see Watson et al., 2018; \r\nMcMahon et al., 2020), introducing major uncertainties to population \r\nmodelling (Section 3.3.4; Parsons et al., 2020)."


id: c73089eb2afe574adcc6492cb4ae4820
created_at: 2023-03-16 14:02:15
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vector_id: 28927
content:
"Animal behaviour can be affected by ocean acidification, warming \r\nand hypoxia. While warming and hypoxia mostly induce avoidance \r\nbehaviour, potentially leading to migration and habitat compression \r\n(Section 3.4; McCormick and Levin, 2017; Limburg et al., 2020), the \r\neffects of acidification appear more complex. Some studies reported \r\nthat acidification dominates behavioural effects (Schmidt et al., 2017), \r\nalthough outcomes vary with experimental design and duration \r\nof exposure (low confidence, low agreement) (Maximino and de \r\nBrito, 2010; Munday et  al., 2016; Laubenstein et  al., 2018; Munday \r\net  al., 2019; Sundin et  al., 2019; Clark et  al., 2020; Munday et  al., \r\n2020; Williamson et  al., 2021). Behaviour represents an integrated \r\nphenomenon that can be influenced both directly and indirectly \r\nby multiple drivers. For instance, increased pCO2 can directly act \r\non neuronal signalling pathways (e.g., Gamma-aminobutyric acid \r\nhypothesis; Nilsson et  al"


id: 4bf4d2ad4551548e1b7eecdd526c1d6e
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content:
", 2012; Thomas et  al., 2020) and influence \r\nlearning (Chivers et al., 2014), vision (Chung et al., 2014), and choice \r\nand escape behaviour (Watson et al., 2014; Wang et al., 2017b). There \r\nis further evidence that observed alterations in fish olfactory behaviour "


id: 84c23598dc6a3a85b0c963f38fb29e0b
created_at: 2023-03-16 14:02:15
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vector_id: 18417
content:
"under ocean acidification may result from physiological and molecular \r\nchanges of the olfactory epithelium, influencing olfactory receptors \r\n(Roggatz et al., 2016; Porteus et al., 2018; Velez et al., 2019; Mazurais \r\net al., 2020). Temperature mainly drives metabolic processes and thus \r\nenergetic requirements, which can indirectly influence behaviour, \r\nincluding increased risk-taking during feeding (Marangon et  al., \r\n2020). Ocean warming also accelerates the biochemical reactions \r\nand metabolic processes that are primarily influenced by acidification. \r\nIt is therefore difficult to generalise to what extent co-occurring \r\nocean warming ameliorates or exacerbates effects of acidification on \r\nbehaviour (Laubenstein et al., 2019); outcomes depend upon species \r\nand life stage (Faleiro et al., 2015; Chan et al., 2016; Tills et al., 2016; \r\nWang et al., 2018b; Jarrold et al., 2020), interactions between species \r\n(e.g., Paula et  al"


id: 8cebbc33b24ed3e39f2402a256ea0f7a
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content:
", 2019) along with confounding factors including \r\nfood availability and salinity (medium confidence) (Ferrari et  al., \r\n2015; Pistevos et al., 2015; Pimentel et al., 2016; Pistevos et al., 2017; \r\nHorwitz et al., 2020)."


id: e21373cf135ed8d18af64740f27fca0e
created_at: 2023-03-16 14:02:16
updated_at: 2023-03-16 14:02:16
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vector_id: 33065
content:
"Other mechanisms acting within and across generations can influence \r\nselection and inter-population tolerances to environmental and \r\nclimate-induced drivers. For instance, transgenerational effects and/or \r\ndevelopmental acclimation, both 'carry-over effects' (where the early\u0002life environment affects the expression of traits in later life stages or \r\ngenerations), can influence within- and cross-generational changes \r\nin the tolerances of marine organisms (medium confidence) to ocean \r\nwarming (Balogh and Byrne, 2020) and acidification (Parker et al., 2012). \r\nOver longer time scales, increasing tolerance to these drivers may be \r\nmediated by mechanisms such as transgenerational plasticity (Murray \r\net al., 2014), leading to locally adapted genotypes as seen in bivalves \r\n(Thomsen et al., 2017), annelids (Rodriguez-Romero et al., 2016; Thibault \r\net al., 2020), corals (Putnam et al., 2020) and coralline algae (Cornwall \r\net  al., 2020)"


id: 7672b1ed6f5b4c2cc7ac3fe834109f46
created_at: 2023-03-16 14:02:16
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vector_id: 16226
content:
" However, transgenerational plasticity is species specific \r\n(Byrne et al., 2020; Thibault et al., 2020) and, depending on the rate and \r\nmagnitude of environmental change, it may either be insufficient for \r\nevolutionary rescue (Morgan et al., 2020) or could induce maladaptive \r\nresponses (i.e., reduced fitness) in marine organisms exposed to multiple \r\ndrivers (medium confidence, low evidence) (Figure  3.11; Griffith and \r\nGobler, 2017; Parker et al., 2017; Byrne et al., 2020)."


id: ea4a335aca2e7840997c2ad9234d8964
created_at: 2023-03-16 14:02:16
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vector_id: 34368
content:
"Climate change is and will continue to be a major driver of natural \r\nselection, causing important changes in fitness-related (e.g., growth, \r\nreproduction, survival) and functional (e.g., body/cell size, morphology, \r\nphysiology) traits, and in the genetic diversity of natural populations \r\n(medium confidence) (Pauls et  al., 2013; Merila and Hendry, 2014). \r\nClimate-change impacts will continue to be exacerbated by interactions \r\nwith non-climate drivers such as habitat fragmentation or loss, pollution \r\nor resource overexploitation, which limit the adaptive potential of \r\npopulations to future conditions (Trathan et al., 2015; Gaitan-Espitia \r\nand Hobday, 2021). However the ultimate responses to complex \r\nchange are conditioned by the rate and magnitude of environmental \r\nchange, organisms' capacity for acclimation, the degree of local \r\nadaptation of natural populations and populations' potential for \r\nadaptive evolution (Figure 3.11; Pespeni et al., 2013; Calosi et al"


id: 9938fa4cf43fa364d8022d517dd65da3
created_at: 2023-03-16 14:02:16
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vector_id: 21621
content:
", 2017; \r\nVargas et al., 2017). These controlling factors are mainly determined \r\nby local environmental conditions encountered by populations across \r\ntheir geographic distribution (Boyd et al., 2016). In highly fluctuating \r\nenvironments (e.g., upwelling regions, coastal zones), multiple drivers \r\ncan change and interact across temporal and spatial scales, generating \r\ngeographic mosaics of tolerances and sensitivities to environmental \r\nand climate change in marine organisms (medium confidence) (Pespeni \r\net al., 2013; Boyd et al., 2016; Vargas et al., 2017; Li et al., 2018a). A \r\nfurther challenge for marine life lies in its ability to cope with extreme "


id: 271e9e5f61339bdb365c3ec25509351
created_at: 2023-03-16 14:02:16
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vector_id: 3548
content:
"Acclimation to environmental pressures and climate change via \r\nphenotypic plasticity (Section  3.3.3; Collins et  al., 2020) enables \r\nspecies to undergo niche shifts such that their present-day climatic \r\nniche is altered to incorporate new or shifted conditions (Fox et al., \r\n2019). Although plasticity provides an adaptive mechanism, it is \r\nunlikely to provide a long-term solution for species undergoing \r\nsustained directional environmental change (e.g., global warming) \r\n(medium confidence) (Fox et  al., 2019; Gaitan-Espitia and Hobday, \r\n2021). Beyond the limits for plastic responses (Figure  3.9; DeWitt \r\net al., 1998; Valladares et al., 2007), genetic adjustments are required \r\nto persist in a changing world (Figure  3.11; Fox et  al., 2019). The \r\nability of species and populations to undergo these adjustments (i.e"


id: da0826edc2122945f15d88a59e209aa
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content:
"a plausible envelope of trajectories across a range of assumptions \r\n(Fulton et al., 2018; Peck et al., 2018; Tittensor et al., 2018). On a global \r\nscale, ecosystem models project a -5.7  +-  4.1% (very likely range) \r\nto -15.5  +-  8.5% decline in marine animal biomass with warming \r\nunder SSP1-2.6 and SSP5-8.5, respectively, by 2080-2099 relative to \r\n1995-2014, albeit with significant regional variation in both trends \r\nand uncertainties (medium confidence) (Section  3.4.3.4; Tittensor \r\net  al., 2021). Biological interactions may exacerbate or buffer the \r\nprojected impacts. For instance, trophic amplification (strengthening \r\nof responses to climate-induced drivers at higher trophic levels) may \r\nresult from combined direct and indirect food-web-mediated effects \r\n(medium confidence) (Section 3.4.3.4; Lotze et al., 2019)"


id: ee9b35a4555b1c1fe82388764b16db89
created_at: 2023-03-16 14:02:16
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content:
" Alternatively, \r\ncompensatory species interactions can dampen strong impacts on \r\nspecies from ocean acidification, resulting in weaker responses at \r\nfunctional-group or community level than at species level (medium \r\nconfidence) (Marshall et al., 2017; Hoppe et al., 2018b; Olsen et al., \r\n2018; Gissi et al., 2021). Globally, the projected reduction of biomass \r\ndue to climate-induced drivers is relatively unaffected by fishing \r\npressure, indicating additive responses of fisheries and climate change \r\n(low confidence) (Lotze et al., 2019). Regionally, projected interactions \r\nof climate-induced drivers, fisheries and other regional non-climate \r\ndrivers can be both synergistic and antagonistic, varying across regions, \r\nfunctional groups and species, and can cause nonlinear dynamics with \r\ncounterintuitive outcomes, underlining the importance of adaptations \r\nand associated trade-offs (high confidence) (Sections 3.5.3, 3.6.3.1.2, \r\n4.5, 4.6; Weijerman et al., 2015; Fulton et al"


id: 77606b8e6d65f9759a6a93d9d351fc5b
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", 2018; Hansen et al., 2019; \r\nTrolle et al., 2019; Zeng et al., 2019; Holsman et al., 2020; Pethybridge \r\net al., 2020; Gissi et al., 2021)."


id: 4ce6644dafac4922407a60008fbeaae8
created_at: 2023-03-16 14:02:16
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content:
"Assessing ecological responses to multiple climate-induced drivers \r\nrequires a combination of approaches, including laboratory- and \r\nfield-based experiments, field observations (e.g., natural gradients, \r\nclimate analogues), study of paleo-analogues and the development \r\nof mechanistic and empirical models (Clapham, 2019; Gissi et  al., \r\n2021). Experimental studies of food-web responses are often limited \r\nto an individual driver, although recent manipulations have used a \r\nmatrix of >1000-l mesocosms to explore ecological responses to both \r\nwarming and acidification (see Box  3.1; Nagelkerken et  al., 2020). \r\nHence, complementary approaches are needed to indirectly explore \r\nthe mechanisms underlying ecosystem responses to global climate \r\nchange (Parmesan et al., 2013). Observations from time series longer \r\nthan modes of natural variability (i.e., decades) are essential for \r\nrevealing and attributing ecological responses to climate change (e.g., \r\nSection 3.4; Barton et al"


id: cf92aabced1be82fce0e85fd584df86b
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", 2015b; Brun et al., 2019). Also, paleorecords \r\nprovide insights into the influence of multiple drivers on marine \r\nbiota (Cross-Chapter Box  PALEO in Chapter  1; Reddin et  al., 2020). \r\nSpecifically, associations between vulnerabilities and traits of marine \r\nectotherms in laboratory experiments correspond with organismal \r\nresponses to ancient hyperthermal events (medium confidence) \r\n(Reddin et  al., 2020). This corroboration suggests that responses to \r\nmultiple drivers inferred from the fossil record can help provide insights \r\ninto the future status of functional groups, and hence food webs, under \r\nrapid climate change."


id: 99ce52237fd93a04fcdc0af7664a1d2e
created_at: 2023-03-16 14:02:16
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"Given the limitations of individual ecological models discussed above, \r\nmodel intercomparisons, such as the Fisheries and Marine Ecosystem \r\nModel Intercomparison Project (Fish-MIP; Tittensor et al., 2018) show \r\npromise in increasing the robustness of projected ecological outcomes \r\n(Tittensor et  al., 2018). Model ensembles include a greater number \r\nof relevant processes and functional groups than any single model \r\nand thus capture a wider range of plausible responses. Among the \r\nglobal Fish-MIP models, there is high (temperate and tropical areas) \r\nto medium agreement (coastal and polar regions) on the direction of \r\nchange, but medium (temperate and tropical regions) to low agreement\r\n(coastal and polar regions) on magnitude of change (Lotze et al., 2019; \r\nHeneghan et al., 2021). Although model outputs are validated relative \r\nto observations to assess model skills (Payne et  al., 2016; Tittensor \r\net  al"


id: 95e95189540f97f8fd4f27252fe32fc3
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content:
", 2018), the Fish-MIP models under-represent some sources of \r\nuncertainty, as they often do not include parameter uncertainties and \r\ndo not usually include impacts of ocean acidification, oxygen loss \r\nor evolutionary responses because there remains high uncertainty \r\nregarding the influences of these processes across functional groups. \r\nEnsemble model investigations like Fish-MIP have also identified gaps \r\nin our mechanistic understanding of ecosystems and their responses \r\nto anthropogenic forcing, leading to model improvement and more \r\nrigorous benchmarking. These investigations could inspire future \r\ntargeted observational and experimental research to test the validity \r\nof model assumptions (Payne et al., 2016; Lotze et al., 2019; Heneghan \r\net  al., 2021). The state of the art in such experimental research is \r\npresented in Box 3.1."


id: 7fc921c3338d5e69d5f47791f855bce4
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"Multi-species and integrated end-to-end ecosystem models are \r\npowerful tools to explore and project outcomes to the often-interacting \r\ncumulative effects of climate change and other anthropogenic drivers \r\n(Section 3.1; Kaplan and Marshall, 2016; Koenigstein et al., 2016; Peck \r\nand Pinnegar, 2018; Tittensor et  al., 2018; Gissi et  al., 2021). These \r\nmodels can integrate some aspects of the knowledge accrued from \r\nmanipulation experiments, paleo- and contemporary observations, help \r\ntest the relative importance of specific drivers and driver combinations, \r\nand identify synergistic or antagonistic responses (Koenigstein et al., \r\n2016; Payne et al., 2016; Skogen et al., 2018; Tittensor et al., 2018). \r\nAs these models are associated with wide-ranging uncertainties \r\n(SM3.2.2; Payne et  al., 2016; Trolle et  al., 2019; Heneghan et  al"


id: d12c31e031274b1beef081ab8415947d
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"The majority of the examples in Section 3.3 are from studies mimicking projected conditions in the year 2100 that report the responses \r\nof an individual species or strain to multiple drivers. This powerful generic experimental approach has largely been restricted to single \r\nspecies because it is logistically complex to conduct experiments that straddle multiple trophic levels, and that also include more than \r\ntwo drivers (see Figure Box 3.1.1b); the need for multiple replicates, drivers and treatment levels greatly increase the work required \r\n(Parmesan et al., 2013; Boyd et al., 2018). It is challenging to apply this experimental approach to communities or ecosystems (see Figure \r\nBox 3.1.1). To date, most research on community or ecosystem response to climate-induced drivers has been in large-volume (>10,000 l) \r\nmesocosms (Riebesell and Gattuso, 2014), or at natural analogues such as CO2 seeps, in which only one driver (ocean acidification) is \r\naltered (see (4) in Figure Box 3.1"


id: 1c12f7c4ea371eb33eb5ff9ee7559b26
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"1). Only very recently have two drivers been incorporated into climate-change manipulation studies \r\nexamining responses of primary producers to secondary consumers (see (5) in Figure Box 3.1.1a; Nagelkerken et al., 2020). Therefore, \r\n'natural experiments' from the geological past (Reddin et al., 2020) provide insights into how food webs and their constituents respond to \r\ncomplex change involving multiple drivers. Contemporary observations are occasionally long enough (>50 years) to capture community \r\nresponses to complex climate change. For example, Brun et al. (2019) reported a shift in zooplankton community structure in the North \r\nAtlantic (1960-2014), with major biogeochemical ramifications."


id: 59cd5623caf83407a93ae07f115d17fb
created_at: 2023-03-16 14:02:16
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content:
"Conducting sufficiently long manipulation experiments to study the effect of adaptation on organisms is equally difficult (see Figure \r\nBox 3.1.1b), with much research restricted to multi-year studies of the microevolution of fast-growing (more than one division per day) \r\nphytoplankton species responding to single drivers (Lohbeck et al., 2012; Schaum et al., 2016). In a few experimental evolution studies \r\n(see (7) in Figure Box 3.1.1a; Brennan et al., 2017), multiple drivers have been used, but none have used communities or ecosystems (see \r\nFigure Box 3.1.1b). Nevertheless, the fossil record provides limited evidence of adaptations to less rapid (relative to present day) climate \r\nchange (Jackson et al., 2018)"


id: 782b86c1a246548bf151434eef7c6bcb
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" Despite the need to explore ecological or biogeochemical responses to projected future ocean conditions, \r\nlogistical challenges require that assessments of climate-change impacts at scales larger than mesocosms use large-scale, long-term in \r\nsitu observational studies (as documented in Section 3.4)."


id: 87ce0dc69934c46c5f5e6862bac5b33c
created_at: 2023-03-16 14:02:16
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vector_id: 18893
content:
"Ocean acidification and associated declines in aragonite saturation \r\nstate (Oaragonite) decrease rates of calcification by corals and other \r\ncalcifying reef organisms (very high confidence), reduce coral settlement \r\n(medium confidence) and increase bioerosion and dissolution of reef \r\nsubstrates (high confidence) (Hoegh-Guldberg et  al., 2018a; Bindoff \r\net  al., 2019a; Kline et  al., 2019; Pitts et  al., 2020). Warming can \r\nexacerbate the coral response to ocean acidification (Kornder et al., \r\n2018) and accelerate the decrease in coral skeletal density (Guo et al., \r\n2020). In addition, reefs with lower coral cover and a higher proportion \r\nof slow-growing species, because of bleaching, are more sensitive to \r\nacidification (net dissolution occurs Oaragonite  =  2.3 for 100% coral \r\ncover, and Oaragonite  >3.5 for 30% coral cover; Kline et  al., 2019)"


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vector_id: 16754
content:
" \r\nHowever, experimental evidence suggests that coral responses to \r\nocean acidification are species specific (medium confidence) (Fabricius \r\net al., 2011; DeCarlo et al., 2018; Comeau et al., 2019). Evidence from "


id: 44d7a131f5f774fa0b770723e51e70b6
created_at: 2023-03-16 14:02:16
updated_at: 2023-03-16 14:02:16
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index: climate_gpt_only_giec
vector_id: 8251
content:
"larval dispersal and evolutionary processes find limited ability to adapt \r\nthis century at rates of warming at or exceeding that in RCP4.5 (high \r\nconfidence, very likely) (Bay et  al., 2017; Kubicek et  al., 2019; Matz \r\net  al., 2020; McManus et  al., 2020; Logan et  al., 2021; McManus \r\net al., 2021). For example, a global analysis (Logan et al., 2021) finds \r\nthat increased thermal tolerance via evolution or switching to more \r\nstress-tolerant algal symbionts enable most (73-81%) coral to survive \r\nthrough 2100 under RCP2.6, but coral-dominated communities with a \r\nhistorical mix of coral taxa still disappear (0-8% coral survival) under \r\nRCP6.0 in simulations with adaptive mechanisms (Figure 3.13). Due \r\nto the impacts of warming, and to a lesser extent ocean acidification, \r\nglobal reef carbonate production is estimated to decline 71% by \r\n2050 in SSP1-2"


id: 51229ebd3798de7f6d9edcd241ac9043
created_at: 2023-03-16 14:02:16
updated_at: 2023-03-16 14:02:16
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index: climate_gpt_only_giec
vector_id: 10220
content:
"6, and the rate of SLR is estimated to exceed that of \r\nreef growth for 97% of reefs assessed, without adaptation by corals \r\nand their symbionts (WGI AR6 Table 9.9; Cornwall et al., 2021; Fox\u0002Kemper et al., 2021). The increased water depth due to coral loss and \r\nreef erosion, as well as reduced structural complexity, will limit wave \r\nattenuation and exacerbate the risk of flooding from SLR on reef\u0002"


id: d4f18c744473ca058905bd957ed2489e
created_at: 2023-03-16 14:02:16
updated_at: 2023-03-16 14:02:16
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vector_id: 31033
content:
"In response to the global-scale decline in coral reefs and high \r\nfuture risk, recent literature focuses on finding thermal refuges and \r\nidentifying uniquely resilient species, populations or reefs for targeted \r\nrestoration and management (Hoegh-Guldberg et  al., 2018b). Reefs \r\nexposed to internal waves (Storlazzi et al., 2020), turbidity (Sully and \r\nvan Woesik, 2020) or warm-season cloudiness (Gonzalez-Espinosa \r\nand Donner, 2021) are expected to be less sensitive to thermal \r\nstress. Mesophotic reefs (30-150 m) have also been proposed as \r\nthermal refugia (Bongaerts et  al., 2010), although evidence from \r\nrecent bleaching events, subsurface temperature records and species \r\noverlap is mixed (Frade et al., 2018; Rocha et al., 2018b; Eakin et al., \r\n2019; Venegas et al., 2019; Wyatt et al., 2020)"


id: a177133a79626934e905d178f5b38eb0
created_at: 2023-03-16 14:02:16
updated_at: 2023-03-16 14:02:16
content_type: text
index: climate_gpt_only_giec
vector_id: 22962
content:
" A study of 2584 reef \r\nsites across the Indian and Pacific oceans estimated that 17% had \r\nsufficient cover of framework-building corals to warrant protection, \r\n54% required recovery efforts and 28% were on a path to net erosion \r\n(Darling et al., 2019). There is medium evidence for greater bleaching \r\nresistance among reefs subject to temperature variability or frequent \r\nheat stress (Barkley et  al., 2018; Gintert et  al., 2018; Hughes et  al., \r\n2018a; Morikawa and Palumbi, 2019), but with trade-offs in terms of \r\ndiversity and structural complexity (Donner and Carilli, 2019; Magel \r\net  al., 2019). There is limited agreement about the persistence of \r\nthermal tolerance in response to severe heat stress (Le Nohaic et al., \r\n2017; DeCarlo et al., 2019; Fordyce et al., 2019; Leggat et al., 2019; \r\nSchoepf et al., 2020)"


id: 6a5a88ac2b6c400379c5186dab8f4f24
created_at: 2023-03-16 14:02:16
updated_at: 2023-03-16 14:02:16
content_type: text
index: climate_gpt_only_giec
vector_id: 14330
content:
" Recovery and restoration efforts that target heat\u0002resistant coral populations and culture heat-tolerant algal symbionts \r\nhave the greatest potential of effectiveness under future warming \r\n(high confidence) (see Box 5.5 in SROCC Chapter 5; Bay et al., 2017; \r\nDarling and Cote, 2018; Baums et  al., 2019; Bindoff et  al., 2019a; \r\nHowells et al., 2021); however, there is low confidence that enhanced \r\nthermal tolerance can be sustained over time (Section  3.6.3.3.2; \r\nBuerger et  al., 2020). The effectiveness of active restoration and \r\nother specific interventions (e.g., reef shading) are further assessed in \r\nSection 3.6.3.3.2."


id: 536e2d9108e843ffaa9d9ed8aa186f54
created_at: 2023-03-16 14:02:16
updated_at: 2023-03-16 14:02:16
content_type: text
index: climate_gpt_only_giec
vector_id: 10596
content:
"Observations since AR5 and SROCC (Table 3.4) find increased impacts \r\nof ocean warming on rocky shores. This includes extirpation of species \r\nat the warm edge of their ranges (Yeruham et al., 2015; Martinez et al., \r\n2018), extension of poleward range boundaries (Sanford et al., 2019), \r\nmortality from climate extremes (Seuront et  al., 2019), reduction in \r\nsurvival at shallower depths (Sorte et al., 2019; Wallingford and Sorte, \r\n2019) and reorganisation of communities (Wilson et al., 2019; Mulders \r\nand Wernberg, 2020; Albano et al., 2021). Data collected after MHWs \r\nfind ecological phase shifts (moderate evidence, high agreement) \r\n(e.g., California; Rogers-Bennett and Catton, 2019; McPherson et al., \r\n2021) and homogenisation of communities (limited evidence) (e.g., \r\nAlaska; Weitzman et al., 2021). For example, the collapse of sea star \r\npopulations in the Northeast Pacific due to a MHW-related disease \r\noutbreak (Hewson et al., 2014; Menge et al., 2016; Miner et al"


id: ddcd2c5b758964221181019b24e3bc69
created_at: 2023-03-16 14:02:16
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vector_id: 32394
content:
", 2018; \r\nSchiebelhut et  al., 2018), including 80-100% loss of the common \r\npredatory sunflower star, Pycnopodia helianthoides (very high \r\nconfidence) (Harvell et al., 2019), triggered shifts from kelp- to urchin\u0002dominated ecosystems (Schultz et  al., 2016; Gravem and Morgan, \r\n2017; McPherson et al., 2021)."


id: 7b39f1f6389225dc22664d75afd69061
created_at: 2023-03-16 14:02:16
updated_at: 2023-03-16 14:02:16
content_type: text
index: climate_gpt_only_giec
vector_id: 16977
content:
"Multiple lines of evidence find that foundational calcifying organisms \r\nsuch as mussels are at high risk of decline due to both the individual \r\nand synergistic effects of warming, acidification and hypoxia (high \r\nconfidence) (Sunday et al., 2016; Sorte et al., 2017; Sorte et al., 2019; \r\nNewcomb et  al., 2020). Warmer temperatures reduce mussel and \r\nbarnacle recruitment (e.g., northwest Atlantic; Petraitis and Dudgeon, \r\n2020) and the upper vertical limit of mussels (e.g., northeast Pacific, \r\nHarley, 2011; and southwest Pacific, Sorte et al., 2019). Experiments \r\nshow that ocean acidification negatively impacts mussel physiology \r\n(very high confidence), with evidence of reduced growth (Gazeau \r\net  al., 2010), attachment (Newcomb et  al., 2020), biomineralisation \r\n(Fitzer et  al., 2014) and shell thickness (Pfister et  al., 2016; McCoy \r\net  al., 2018)"


id: 5ee2764697188f7e44b396eeac98ac6e
created_at: 2023-03-16 14:02:16
updated_at: 2023-03-16 14:02:16
content_type: text
index: climate_gpt_only_giec
vector_id: 12473
content:
" Net calcification and abundance of mussels and other \r\nfoundational species, including oysters, are expected to decline due to \r\nocean acidification (very high confidence) (Kwiatkowski et al., 2016; \r\nSunday et al., 2016; McCoy et al., 2018; Meng et al., 2018), causing \r\nthe reorganisation of communities (high confidence) (Kroeker et al., \r\n2013b; Linares et al., 2015; Brown et al., 2016; Sunday et al., 2016; \r\nAgostini et al., 2018; Teixido et al., 2018). Experiments indicate that \r\nacidification can interact with warming and hypoxia to increase the "


id: bbef45f8ab358719c467603f67bddaf3
created_at: 2023-03-16 14:02:16
updated_at: 2023-03-16 14:02:16
content_type: text
index: climate_gpt_only_giec
vector_id: 27128
content:
"Figure  3.13 |   Coral reef futures, with and without adaptation. Graphs are based on a model of coral-symbiont evolutionary dynamics from Logan et  al. (2021), \r\nwhich simulates two coral types and symbiont populations for 1925 reef cells worldwide, from 1950 to 2100 drawn from simulations with National Oceanic and Atmospheric \r\nAdministration-Geophysical Fluid Dynamics Laboratory Earth System Model (ESM2M) under four RCPs. Top panels show the simulated fraction of cells with healthy reefs, when \r\nboth coral types are not in a state of severe bleaching or mortality, (i) without adaptive responses and (ii) with adaptive responses (symbiont evolution). Colours indicate maximum \r\nmonthly sea surface temperature increase across all reef cells, versus a 1861-2010 baseline"


id: b28c9dcbac851fa37da4eddf6ce47e17
created_at: 2023-03-16 14:02:16
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index: climate_gpt_only_giec
vector_id: 25612
content:
" Panels (a,b,c) depict snapshots of coral reef conditions at time points in the future, \r\neach with different levels of warming, drawn from the model-projected cover of the two coral types and from a literature assessment (Section 3.4.2.1; Hughes et al., 2018b; Bindoff \r\net al., 2019a; Darling et al., 2019; Leggat et al., 2019; Cornwall et al., 2021)."


id: d382e6567fc8689ad9d97be9c74d604b
created_at: 2023-03-16 14:02:16
updated_at: 2023-03-16 14:02:16
content_type: text
index: climate_gpt_only_giec
vector_id: 30805
content:
"Recent research (Straub et al., 2019; Butler et al., 2020; Filbee-Dexter \r\net  al., 2020b; Tait et  al., 2021) supports the findings of previous \r\nassessments (Table 3.5) that kelp and other seaweeds in most regions \r\nare undergoing mass mortalities from high temperature extremes \r\nand range shifts from warming (very high confidence). Kelp are \r\nhighly sensitive to the direct effect of high temperature on survival \r\n(Nepper-Davidsen et  al., 2019) and indirect impact of temperature \r\non herbivorous species (Ling, 2008; Verges et  al., 2016), upwelling \r\nand nutrient availability (Carr and Reed, 2015; Schiel and Foster, \r\n2015). Synergies between warming, storms, pollution and intensified \r\nherbivory (due to removal or loss of predators including sea stars and \r\notters that constrain herbivory by fish and urchin populations) can \r\nalso cause physiological stress and physical damage in kelp, reducing \r\nproductivity and reproduction (Rogers-Bennett and Catton, 2019; \r\nBeas-Luna et al"


id: 654d9310beec4e7903fbb691788b8b11
created_at: 2023-03-16 14:02:16
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vector_id: 13515
content:
"While reducing non-climate drivers can help prevent kelp loss from \r\nwarming and MHWs, there is limited potential for restoration of kelp \r\necosystems after transition to urchin-dominant ecosystems (high \r\nconfidence). Current restoration efforts are generally small scale \r\n(<0.1 km2\r\n) and less advanced than those in ecosystems like coral \r\nreefs (Coleman et al., 2020b; Eger et al., 2020; Layton et al., 2020). \r\nAlthough abundance of herbivores limits kelp populations, there is \r\nlimited evidence that restoring predators of herbivores by creating \r\nmarine reserves, or directly removing grazing species, will increase \r\nkelp forest resilience to warming and extremes (Verges et al., 2019; \r\nWernberg et  al., 2019). Active reseeding of wild kelp populations \r\nthrough transplantation and propagation of warm-tolerant genotypes \r\n(Coleman et  al., 2020b; Alsuwaiyan et  al"


id: e6a1476b8519827208f85bc96972a2
created_at: 2023-03-16 14:02:16
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vector_id: 33766
content:
", 2021) can overcome low \r\ndispersal rates of many kelp species and facilitate effective restoration \r\n(medium confidence) (Morris et al., 2020c)."


id: a84811bba612dddd5016a96f5f75a992
created_at: 2023-03-16 14:02:16
updated_at: 2023-03-16 14:02:16
content_type: text
index: climate_gpt_only_giec
vector_id: 24004
content:
"Estuaries, deltas and lagoons encounter environmental gradients over \r\nsmall spatial scales, generating diverse habitats that support myriad \r\necosystem services, including food provision, regulation of erosion, \r\nnutrient recycling, carbon sequestration, recreation and tourism, \r\nand cultural significance (D'Alelio et  al., 2021; Keyes et  al., 2021). \r\nAlthough these coastal ecosystems have historically been sensitive to \r\nerosion-accretion cycles driven by sea level, drought and storms (high \r\nconfidence) (Peteet et al., 2018; Wang et al., 2018c; Jones et al., 2019b; \r\nUrrego et  al., 2019; Hapsari et  al., 2020; Zhao et  al., 2020b), they \r\nwere impacted for much of the 20th century primarily by non-climate \r\ndrivers (very high confidence) (Brown et  al., 2018b; Ducrotoy et  al., \r\n2019; Elliott et al., 2019; He and Silliman, 2019; Andersen et al., 2020; \r\nNewton et  al., 2020; Stein et  al., 2020)"


id: 4252fc03f5363c8f6ad81a1d5a05297
created_at: 2023-03-16 14:02:16
updated_at: 2023-03-16 14:02:16
content_type: text
index: climate_gpt_only_giec
vector_id: 7837
content:
" Nevertheless, the influence \r\nof climate-induced drivers has become more apparent over recent \r\ndecades (medium confidence) (Table 3.6)."


id: a3ceb9fa25abcf82fb337007ae7136e6
created_at: 2023-03-16 14:02:16
updated_at: 2023-03-16 14:02:16
content_type: text
index: climate_gpt_only_giec
vector_id: 23336
content:
"Acidification of estuarine water is a growing hazard (medium confidence) \r\n(Doney et al., 2020; Scanes et al., 2020a; Cai et al., 2021), and resident \r\norganisms display sensitivity to altered pH in laboratory settings \r\n(medium confidence) (Young et  al., 2019a; Morrell and Gobler, 2020; \r\nPardo and Costa, 2021). However, attribution of the biological effects \r\nof acidification is difficult because many biogeochemical processes \r\naffect estuarine carbon chemistry (Sections 3.2.3.1, 3.3.2). Warming can \r\nexacerbate the impacts of both acidification and hypoxia on estuarine \r\norganisms (Baumann and Smith, 2018; Collins et al., 2019b; Ni et al., \r\n2020). These effects are further complicated by eutrophication, with high \r\nnitrogen loads associated with lower pH (Rheuban et al., 2019). Warming \r\n(including MHWs) and eutrophication interact to decrease estuarine \r\noxygen content and pH, increasing the vulnerability of animals to MHWs \r\n(Brauko et al"


id: 871eee0fdc97599f26dd9d78331d5c9
created_at: 2023-03-16 14:02:16
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index: climate_gpt_only_giec
vector_id: 18792
content:
", 2020) and exacerbating the incidence and impact of dead \r\nzones (medium confidence) (Altieri and Gedan, 2015). The impacts of \r\nstorms on estuaries are variable and are described in SM3.3.1."


id: 6cf9fc7e3792dc9cfeb5aab511a9a77f
created_at: 2023-03-16 14:02:16
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vector_id: 14769
content:
"All these impacts are projected to escalate under future climate \r\nchange, but their magnitude depends on the amount of warming, \r\nthe socioeconomic development pathway and implementation of \r\nadaptation strategies (medium confidence). Modelling studies (Lopes \r\net al., 2019; Rodrigues et al., 2019; White et al., 2019; Zhang and Li, \r\n2019; Hong et al., 2020; Krvavica and Ruzic, 2020; Liu et al., 2020e; \r\nShalby et  al., 2020) suggest that responses of estuaries to SLR will \r\nbe complex and context dependent (Khojasteh et  al., 2021), but \r\nproject that salinity, tidal range, storm-surge amplitude, depth and \r\nstratification will increase with SLR (medium confidence), and that \r\nmarine-dominated waters will penetrate farther upstream (high \r\nconfidence)"


id: 98724a3383c5e5e76837aaeb6f9bdf63
created_at: 2023-03-16 14:02:16
updated_at: 2023-03-16 14:02:16
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index: climate_gpt_only_giec
vector_id: 21497
content:
" Without careful management of freshwater inputs, \r\nsediment augmentation and/or the restoration of shorelines to more \r\nnatural states, transformation and loss of intertidal areas and wetland \r\nvegetation will increase with SLR (high confidence) (Doughty et  al., \r\n2019; Leuven et al., 2019; Yu et al., 2019; Raw et al., 2020; Shih, 2020; \r\nStein et al., 2020), with small, shallow microtidal estuaries being more \r\nvulnerable to impacts than deeper estuaries with well-developed \r\nsediments (medium confidence) (Leuven et al., 2019; Williamson and \r\nGuinder, 2021). Warming and MHWs will enhance stratification and \r\ndeoxygenation in shallow lagoons (medium confidence) (Derolez et al., \r\n2020) and will continue to drive range shifts among estuarine biota "


id: f90079d5818faa647f08300e40c476bc
created_at: 2023-03-16 14:02:16
updated_at: 2023-03-16 14:02:16
content_type: text
index: climate_gpt_only_giec
vector_id: 36687
content:
"Relative SLR extends the upstream limit of saline waters (high confidence) \r\n(Harvey et  al., 2020; Jiang et  al., 2020) and alters tidal ranges (high \r\nconfidence) (Idier et al., 2019; Talke et al., 2020). Elevated water levels \r\nalso alter submergence patterns for intertidal habitat (high confidence) \r\n(Andres et al., 2019), moving high-water levels inland (high confidence) \r\n(Peteet et al., 2018; Appeaning Addo et al., 2020; Liu et al., 2020e) and \r\nincreasing the salinity of coastal water tables and soils (high confidence) \r\n(Eswar et  al., 2021). These processes favour inland and/or upstream \r\nmigration of intertidal habitat, where it is unconstrained by infrastructure, \r\ntopography or other environmental features (high confidence) (Kirwan \r\nand Gedan, 2019; Parker and Boyer, 2019; Langston et al., 2020; Magolan \r\nand Halls, 2020; Saintilan et al., 2020). The spread of 'ghost forests' along \r\nthe North American east coast (Kirwan and Gedan, 2019) and elsewhere \r\n(Grieger et  al"


id: 3e322cd8c55df9cfff1a342784d7f1f8
created_at: 2023-03-16 14:02:16
updated_at: 2023-03-16 14:02:16
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index: climate_gpt_only_giec
vector_id: 7155
content:
", 2020) illustrates this phenomenon. Along estuarine \r\nshorelines, changing submergence patterns and upstream penetration \r\nof saline waters interact synergistically to stress intertidal plants, \r\nchanging species composition and reducing above-ground biomass, \r\nin some cases favouring invasive species (Xue et al., 2018; Buffington \r\net al., 2020; Gallego-Tevar et al., 2020). Overall, changing salinity and \r\nsubmergence patterns decrease the ability of shoreline vegetation to \r\ntrap sediment (Xue et al., 2018), reducing accretion rates and increasing "


id: 3b6fc5231e2ccb6d3576b7e385bf1807
created_at: 2023-03-16 14:02:16
updated_at: 2023-03-16 14:02:16
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index: climate_gpt_only_giec
vector_id: 6703
content:
"As noted in SROCC, given the diversity of coastal wetlands as well \r\nas the dependence of their future vulnerability to climate change on \r\nadaptation pathways (Krauss, 2021; Rogers, 2021), projections of \r\nfuture impacts based on shoreline elevation estimated from satellite \r\ndata and CMIP5 projections (Spencer et  al., 2016; Schuerch et  al., \r\n2018) vary greatly. Although all approaches have individual strengths \r\nand weaknesses (Tornqvist et al., 2021), paleorecords provide some \r\nclarity because they yield estimates of wetland responses to changes in \r\nclimate in the absence of other anthropogenic drivers and are therefore \r\ninherently conservative. On the basis of paleorecords (Table 3.8), we \r\nassess that mangroves and salt marshes are likely at high risk from \r\nfuture SLR, even under SSP1-1.9, with impacts manifesting in the mid\u0002term (medium confidence). Under SSP5-8"


id: a22bbc000779205e501e792868dbdd49
created_at: 2023-03-16 14:02:16
updated_at: 2023-03-16 14:02:16
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index: climate_gpt_only_giec
vector_id: 23082
content:
"5, wetlands are very likely\r\nat high risk from SLR, with larger impacts manifesting before 2040 \r\n(medium confidence). By 2100, these ecosystems are at high risk of \r\nimpacts under all scenarios except SSP1-1.9 (high confidence), with \r\nimpacts most severe along coastlines with gently sloping shorelines, \r\nlimited sediment inputs, small tidal ranges and limited space for inland \r\nmigration (very high confidence) (Cross-Chapter Box SLR in Chapter 3; \r\nSchuerch et al., 2018; FitzGerald and Hughes, 2019; Leo et al., 2019; \r\nSchuerch et al., 2019; Raw et al., 2020; Saintilan et al., 2020)."


id: 1919be9d80ea65249127a2fac7282546
created_at: 2023-03-16 14:02:16
updated_at: 2023-03-16 14:02:16
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index: climate_gpt_only_giec
vector_id: 1441
content:
"species to expand their ranges poleward (high confidence) (Friess \r\net  al., 2019; Whitt et  al., 2020). This expansion can affect species \r\ninteractions (Guo et  al., 2017; Friess et  al., 2019), and enhance \r\nsediment accretion and carbon storage rates in some instances \r\n(medium confidence) (Guo et al., 2017; Kelleway et al., 2017; Chen \r\net al., 2018b; Coldren et al., 2019; Raw et al., 2019). Drought, low sea \r\nlevels and MHWs can cause significant die-offs among mangroves \r\n(medium confidence) (Lovelock et  al., 2017b; Duke et  al., 2021). \r\nSeagrasses are similarly vulnerable to warming (high confidence) \r\n(Repolho et al., 2017; Duarte et al., 2018; Jayathilake and Costello, \r\n2018; Savva et al., 2018), which has been attributed as one cause of \r\nobserved changes in distribution and community structure (medium \r\nconfidence) (Hyndes et  al., 2016; Nowicki et  al., 2017)"


id: a4cc589d53d6dc456e2a26df850d7ea3
created_at: 2023-03-16 14:02:16
updated_at: 2023-03-16 14:02:16
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index: climate_gpt_only_giec
vector_id: 23505
content:
" MHWs, \r\ntogether with storm-driven turbidity and structural damage, can \r\ncause seagrass die-offs (high confidence) (Arias-Ortiz et  al., 2018; \r\nKendrick et al., 2019; Smale et al., 2019; Strydom et al., 2020), shifts \r\nto small, fast-growing species (high confidence) (Kendrick et  al., \r\n2019; Shields et  al., 2019; Strydom et  al., 2020) and ecosystem \r\ncollapse (Serrano et al., 2021)."


id: 43c7c3cbbb40afea2260d6011ac085c8
created_at: 2023-03-16 14:02:16
updated_at: 2023-03-16 14:02:16
content_type: text
index: climate_gpt_only_giec
vector_id: 8071
content:
"The sensitivity of salt marshes and mangroves to RSLR depends on \r\nwhether they accrete inorganic sediment and/or organic material at \r\nrates equivalent to rising water levels (very high confidence) (Peteet \r\net al., 2018; FitzGerald and Hughes, 2019; Friess et al., 2019; Gonneea \r\net  al., 2019; Leo et  al., 2019; Marx et  al., 2020; Saintilan et  al., \r\n2020). Otherwise, wetland ecosystems must migrate either inland or \r\nupstream, or face gradual submergence in deeper, increasingly saline \r\nwater (very high confidence) (Section  3.4.2.4; Andres et  al., 2019; \r\nJones et  al., 2019b; Cohen et  al., 2020; Mafi-Gholami et  al., 2020; \r\nMagolan and Halls, 2020; Sklar et al., 2021). Ability to migrate depends \r\non local topography, the positioning of anthropogenic infrastructure \r\nand structures placed to defend such infrastructure (Schuerch et al., \r\n2018; Fagherazzi et  al., 2020; Cahoon et  al., 2021). Submergence \r\ndrives changes in community structure (high confidence) (Jones et al"


id: 6bbb0dfac7c1999a781b94a4d708854b
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vector_id: 14575
content:
", \r\n2019b; Yu et al., 2019; Douglass et al., 2020; Langston et al., 2020) \r\nand functioning (high confidence) (Charles et  al., 2019; Buffington \r\net al., 2020; Stein et al., 2020), and will eventually lead to extirpation \r\nof the most sensitive vegetation (medium confidence) (Schepers et al., \r\n2017; Scalpone et al., 2020) and associated animals (low confidence) \r\n(Rosencranz et  al., 2018). The impacts of storms on wetlands are \r\nvariable and described in SM3.3.1."


id: 3e5029b60874d0087b556cf8b42980f7
created_at: 2023-03-16 14:02:16
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"et al., 2017b; Mori et al., 2018; Ritphring et al., 2018; Hallin et al., \r\n2019; Kasmi et  al., 2020). Within regions, projected impacts scale \r\nnegatively with beach width and positively with the magnitude of \r\nprojected SLR. None of these local studies, however, considered \r\nhigh-energy storm events, which are known to also impact sandy \r\ncoasts (high confidence) (e.g., Burvingt et  al., 2018; Garrote et  al., \r\n2018; Duvat et al., 2019; Sharples et al., 2020), and model structure \r\noften had more influence on projected shoreline responses than did \r\nphysical drivers (Le  Cozannet et  al., 2019). Nevertheless, the most\u0002advanced available models, which incorporate multiple coastal \r\nprocesses, including SLR, project that without anthropogenic barriers \r\nto erosion, 13.6-15.2% and 35.7-49.5% of the world's beaches likely\r\nrisk undergoing at least 100 m of shoreline retreat (relative to 2010) \r\nby 2050 and 2100, respectively (low confidence) (Vousdoukas et al., \r\n2020b)"


id: b01ded75098ad0dba45be130ac544c55
created_at: 2023-03-16 14:02:16
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content:
" Aggregating these trends regionally suggests that relative \r\nrates of shoreline change under RCP4.5 and RCP8.5 diverge strongly \r\nafter mid-century, with trends towards erosion escalating under \r\nRCP8.5 by 2100 (medium confidence) (Figure 3.14; Vousdoukas et al., \r\n2020b). This trend supports the WGI AR6 assessment that projected \r\nSLR will contribute to erosion of sandy beaches, especially under high\u0002"


id: 231c1c5947319f6807f26253b5f73233
created_at: 2023-03-16 14:02:16
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vector_id: 2965
content:
"For beach fauna, emerging evidence links range shifts, increasing \r\nrepresentation by warm-affinity species and mass mortalities to ocean \r\nwarming (limited evidence, high agreement) (McLachlan and Defeo, \r\n2018; Martin et  al., 2019). But even amongst the best-studied taxa, \r\nsuch as turtles, vulnerability to warming (high confidence) and SLR \r\n(medium confidence) anticipated on the basis of theory (Poloczanska \r\net al., 2009; Saba et al., 2012; Pike, 2013; Laloe et al., 2017; Tilley et al., \r\n2019) yields only a few detected impacts in the field associated mainly \r\nwith feminisation (female-skewed sex ratios driven by warmer nest \r\ntemperatures) (Jensen et al., 2018; Colman et al., 2019; Tilley et al., 2019), \r\nphenology (Monsinjon et al., 2019), reproductive success (Bladow and \r\nMilton, 2019) and inter-nesting period (Valverde-Cantillo et al., 2019). \r\nMoreover, although established vulnerabilities imply high projected \r\nfuture risk for turtles (high confidence) (e.g"


id: e3924e8dbfcb7aac68796e490cc5f56c
created_at: 2023-03-16 14:02:16
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vector_id: 33286
content:
", Almpanidou et al., 2019; \r\nMonsinjon et al., 2019; Patricio et al., 2019; Varela et al., 2019; Santidrian \r\nTomillo et  al., 2020), many populations remain resilient to change \r\n(Fuentes et al., 2019; Valverde-Cantillo et al., 2019; Laloe et al., 2020; "


id: 36394d915ec21994770fea6a90b3ba12
created_at: 2023-03-16 14:02:16
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content:
"Lamont et al., 2020), perhaps because variation in sand temperatures \r\nat nesting depth among beaches very likely exceeds the magnitude of \r\nwarming anticipated by 2100, even under RCP8.5 (medium confidence) \r\n(Bentley et al., 2020a). As expected for a taxon with a long evolutionary \r\nhistory, turtles display natural adaptation, not only by virtue of broad \r\ngeographic distributions that include natural climate-change refugia \r\n(Boissin et al., 2019; Jensen et al., 2019), but also because some initial \r\nresponses to warming might counteract anticipated impacts. For \r\nexample, although feminisation poses a significant long-term risk to \r\nturtle populations (high confidence), it might contribute to population \r\ngrowth in the near to mid-term (medium confidence) (Patricio et  al., \r\n2019). Resilience to climate change might be further enhanced by range \r\nextensions, alterations in nesting phenology and fine-scale nest-site \r\nselection (medium confidence) (Abella Perez et al"


id: 80fce55b0513f7bdca7cc3103df98af8
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content:
", 2016; Santos et al., \r\n2017; Almpanidou et al., 2018; Rivas et al., 2019; Laloe et al., 2020)."


id: fc538130099fab6ba93b2ebaf9ef94c1
created_at: 2023-03-16 14:02:16
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vector_id: 37201
content:
"Since AR5, there is evidence for increasing frequency and duration of \r\nMHWs, extreme-weather events and a diversity of threats across depth \r\nstrata causing mass-mortality events, local extirpations and coral reef \r\ndecline (high confidence) (Section 3.4.2.1; SM3.3.2; Buchanan et al., \r\n2016a; Shlesinger et al., 2018; Wabnitz et al., 2018b; Garrabou et al., \r\n2019). In most SES, non-climate drivers, including pollution, habitat \r\ndestruction and especially overfishing, are decreasing the local \r\nadaptive capacity of organisms and the ability of ecosystems to cope \r\nwith climate-change impacts (high confidence) (Cramer et al., 2018; \r\nHidalgo et  al., 2018; Ben-Hasan and Christensen, 2019). The SLR is \r\naccelerating faster than expected (high confidence) (Kulp and Strauss, \r\n2019), posing a key risk to SES' coastal ecosystems and the services \r\nthey provide in urban areas, including drinking water provision, \r\nhousing and recreational activities, among others (Herivaux et  al"


id: 7c02ed9041a16e1aeb4baa022270af08
created_at: 2023-03-16 14:02:16
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vector_id: 17115
content:
"In the Mediterranean Sea (Cross-Chapter  Paper  4), the increase in \r\nclimate extremes and mass-mortality events reported in AR5 has \r\ncontinued (very high confidence) (Gomez-Gras et al., 2021). Extreme\u0002weather events (including deep convection; Gonzalez-Aleman et al., \r\n2019) and MHWs have become more frequent (Darmaraki et al., 2019) \r\nand are associated with mass mortality of benthic sessile species \r\nacross the basin (high confidence) (Garrabou et  al., 2019; Gomez\u0002Gras et al., 2021). Since AR5, in the Persian Gulf and Red Sea, extreme \r\ntemperatures, together with disease and predation, have continued \r\nto cause bleaching-induced mortality of corals, along with declines \r\nin the average coral-colony size (high confidence) (Burt et al., 2019). \r\nPoleward migration and tropicalisation of species (Section 3.4.2.3) has \r\nalso continued in the Mediterranean, and these phenomena have also \r\nbecome an issue in the Black Sea (high confidence) (Boltachev and \r\nKarpova, 2014; Hidalgo et al"


id: 3f7486125c18dbfbed7d0e1b932bc5cf
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", 2018). Climate impacts on phytoplankton \r\nproduction and phenology show high spatial heterogeneity across the \r\nMediterranean Sea (medium evidence) (Marba et al., 2015b; Salgado\u0002Hernanz et  al., 2019), with consequent effects on the diversity and \r\nabundance of zooplankton and fish species (medium confidence) \r\n(Peristeraki et al., 2019). Changes in primary production and a decrease \r\nin river runoff have also altered the optimum habitats for small \r\npelagic fish in the Mediterranean, from the local to the basin scale \r\n(Piroddi et al., 2017). Evidence of impacts from ocean acidification is \r\nincreasing, with the rates of coral calcification showing major decline \r\nin the Red Sea (medium confidence) (Section  3.4.2.1; Steiner et  al., \r\n2018; Bindoff et  al., 2019a). In the Mediterranean Sea, evidence of \r\nacidification events have been reported at the local scale (Hassoun \r\net  al"


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", 2015), with impacts on bivalves and coralligenous species \r\n(medium confidence) (Lacoue-Labarthe et al., 2016)."


id: a2f89f466dfc3191912baac0a32d243c
created_at: 2023-03-16 14:02:16
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content:
"Similar to other coastal ecosystems, evidence since SROCC (Table 3.11) \r\nsuggests that shelf-sea ecosystems and the fisheries and aquaculture \r\nthey support are sensitive to the interactive effects of climate-induced \r\ndrivers, as well as non-climate drivers, including nutrient pollution, \r\nsedimentation, fishing pressure and resource extraction (Table  3.12; \r\nFigure  3.12). Changes in freshwater, nutrient and sediment inputs \r\nfrom rivers due to both climate-induced and non-climate drivers can \r\ninfluence productivity and nutrient limitation, ecosystem structure, \r\ncarbon export and species diversity and abundance (Balch et  al., \r\n2012; Picado et  al., 2014), and can result in reduced water clarity \r\nand light penetration (Dupont and Aksnes, 2013; McGovern et  al., \r\n2019). Seasonal bottom-water hypoxia occurs in some shelf seas (e.g"


id: e6e4703bf1e8619956285ef5324d2fe4
created_at: 2023-03-16 14:02:16
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content:
", \r\nnorthern Gulf of Mexico, Bohai Sea, East China Sea) due to riverine \r\ninputs of freshwater and nutrients, promoting stratification, enhanced \r\nprimary production and organic carbon export to bottom waters (high \r\nconfidence) (Zhao et al., 2017; Wei et al., 2019; Del Giudice et al., 2020; \r\nGrosse et al., 2020; Jarvis et al., 2020; Rabalais and Baustian, 2020; \r\nSong et al., 2020a; Xiong et al., 2020; Zhang et al., 2020a)."


id: 758ca7d35da9189a33ae5fb308e0adc9
created_at: 2023-03-16 14:02:16
updated_at: 2023-03-16 14:02:16
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vector_id: 16083
content:
"Ocean warming has shifted distributions of fish (Free et  al., 2019; \r\nFranco et  al., 2020; Pinsky et  al., 2020b; Fredston et  al., 2021) and \r\nmarine mammal species (Salvadeo et al., 2010; Garcia-Aguilar et al., \r\n2018; Davis et al., 2020) poleward (high confidence) or deeper (low \r\nto medium confidence) (Section 3.4.3.1; Nye et al., 2009; Pinsky et al., \r\n2013; Pinsky et al., 2020b). Warming has also tropicalised the pelagic \r\nand demersal fish assemblages of mid- and high-latitude shelves \r\n(high confidence) (Montero-Serra et  al., 2015; Liang et  al., 2018; \r\nMaharaj et al., 2018; Ma et al., 2019; Friedland et al., 2020a; Kakehi \r\net al., 2021; Punzon et al., 2021). Fisheries catch composition in many \r\nshelf-sea ecosystems has become increasingly dominated by warm\u0002water species since the 1970s (high confidence) (Cheung et al., 2013; \r\nLeitao et al., 2018; Maharaj et al., 2018; McLean et al., 2019)"


id: 222d383a92387b5789685b91225c4aca
created_at: 2023-03-16 14:02:16
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vector_id: 2823
content:
" Warming \r\nhas taxonomically diversified fish communities along a latitudinal \r\ngradient in the North Sea but has homogenised functional diversity \r\n(McLean et al., 2019). However, in some regions, changing predator \r\nor prey distributions, temperature-dependent hypoxia, population \r\nchanges, evolutionary adaptation and other biotic or abiotic processes, \r\nincluding species' exploitation, confound responses to climate-induced \r\ndrivers, which must therefore be interpreted with caution (Frank et al., \r\n2018). For example, although, most species' range edges are tracking \r\ntemperature change on the northeast shelf of the USA (medium \r\nconfidence) (Fredston-Hermann et  al., 2020; Fredston et  al., 2021), \r\nrange edges of others are not."


id: 7e5d4d578b82b86eeb9e5f85ec26d62e
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content:
"Since SROCC, changes in the community structure and diversity of \r\nplankton, macrofauna and infauna have been detected in some shelf \r\nseas, although attribution has been regionally specific (e.g., bottom\u0002water warming or hypoxia) (Meyer and Kroncke, 2019; Rabalais and \r\nBaustian, 2020). Detection of the picoplankton Synechococcus spp. in \r\nthe North Sea is potentially linked to a summer decrease in copepod \r\nstocks and declining food-web efficiency (low confidence) (Schmidt \r\net al., 2020). The seasonally distinct phytoplankton assemblages in the \r\nNorth Sea have begun to appear concurrently and homogenise (Nohe \r\net al., 2020)"


id: f004984ef90c8fd461a46e577e494c7
created_at: 2023-03-16 14:02:16
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content:
" Changes in abundance, species composition and size of \r\nzooplankton have been detected in some shelf seas (Yellow Sea, North \r\nSea, Celtic Sea and Tasman Sea), including a decline in stocks of larger \r\ncopepods, increased abundances of gelatinous and meroplankton, and \r\na shift to smaller species due to warming, increased river discharge, \r\ncirculation change and/or extreme events (high confidence) (Wang \r\net al., 2018a; Bedford et al., 2020; Evans et al., 2020; Shi et al., 2020; \r\nEdwards et al., 2021)."


id: 6c01e29334c2160661a0ef311065de62
created_at: 2023-03-16 14:02:16
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index: climate_gpt_only_giec
vector_id: 14617
content:
"Since AR5, increasing spatio-temporal extent of hypoxia has been \r\nprojected due to enhanced benthic respiration and reduced oxygen \r\nsolubility from warming (Del Giudice et  al., 2020). Similar to the \r\nopen ocean, large shifts in the phenology of phytoplankton blooms \r\nhave been projected for shelf seas throughout subpolar and polar \r\nwaters (medium confidence) (Henson et al., 2018a; Asch et al., 2019). \r\nZooplankton, which are important prey for many fish species and sea \r\nbirds, are expected to decrease in abundance on the northeast shelf \r\nof the USA (Grieve et  al., 2017); however, responses vary by shelf \r\necosystem (Chust et  al., 2014b). Trends towards tropicalisation will \r\ncontinue in the future (high confidence) (Cheung et al., 2015; Stortini \r\net al., 2015; Allyn et al., 2020; Maltby et al., 2020; Costa et al., 2021), \r\nbut uncertainty of future projections of fisheries production increases \r\nsubstantially beyond 2040 (Maltby et al., 2020)"


id: ba684a9f209dbaed112e019584a8b836
created_at: 2023-03-16 14:02:16
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vector_id: 26862
content:
" Nevertheless, shelf\u0002sea fisheries at lower latitudes are most vulnerable to climate change \r\n(Monnereau et  al., 2017). Under future climate change marked by \r\nmore frequent and intense extreme events and the influences of \r\nmultiple drivers, more flexible and adaptive management approaches \r\ncould reduce climate impacts on species while also supporting industry \r\nadaptation (high confidence) (Section 3.6.3.1.2; Shackell et al., 2014; \r\nStortini et al., 2015; Hare et al., 2016; Stortini et al., 2017; Greenan \r\net al., 2019; Ocana et al., 2019; Maltby et al., 2020)."


id: 64581452d6259b18cf1271ba88147dac
created_at: 2023-03-16 14:02:16
updated_at: 2023-03-16 14:02:16
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vector_id: 13356
content:
"Major community shifts, both gradual and abrupt, are observed in polar \r\noceans in response to warming trends and MHWs (Arctic only) (high \r\nconfidence) (Figure 3.12; Cross-Chapter Paper 6; Beaugrand et al., 2019; \r\nMeredith et al., 2019; Huntington et al., 2020). In general, abundances \r\nand ranges of Arctic fish species are declining and contracting, while \r\nranges of boreal fish species are expanding, both geographically and \r\nin terms of feeding interactions and ecological roles (high confidence) \r\n(Huserbraten et al., 2019; Meredith et al., 2019; Huntington et al., 2020; \r\nPecuchet et al., 2020a), with variable outcomes for large commercial \r\nfish stocks (Cross-Chapter Paper 6; Kjesbu et al., 2014; Holsman et al., \r\n2018; Free et al., 2019)"


id: bb2ff82da5a9c6147ea51795eeb7e36e
created_at: 2023-03-16 14:02:16
updated_at: 2023-03-16 14:02:16
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vector_id: 26993
content:
" The extreme seasonal solar radiation cycles of \r\nthese high latitudes may both act as a barrier for species immigration \r\nand change predator-prey dynamics in previously ice-covered areas, \r\nfactors not currently considered in projections (limited evidence) \r\n(Kaartvedt and Titelman, 2018; Ljungstrom et al., 2021). Responses by \r\nmarine mammals and birds to the ongoing changes in polar ecosystems \r\nare both positive and negative (Meredith et al., 2019; Bestley et al., \r\n2020). Phenological, behavioural, physiological and distributional \r\nchanges are observed in marine mammals and birds in response to \r\naltered ecological interactions and habitat degradation, especially to \r\nloss of sea ice (high confidence) (see Box  3.2; Cross-Chapter  Paper \r\n6; Beltran et  al., 2019; Cusset et  al., 2019; Descamps et  al., 2019; \r\nMeredith et al., 2019; Huntington et al., 2020)"


id: d01cfaeb32f17ed9f63b5d0e52bc87a9
created_at: 2023-03-16 14:02:16
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content:
" Reproductive failures \r\nand declining abundances attributed to warmer polar oceans and \r\nless sea ice cover are observed in populations of polar bears, Ursus \r\nmaritimus, seals, whales and marine birds (high confidence) (see \r\nBox  3.2; Duffy-Anderson et  al., 2019; Ropert-Coudert et  al., 2019; \r\nBestley et al., 2020; Chambault et al., 2020; Molnar et al., 2020; Stenson \r\net al., 2020). The ongoing changes in polar marine ecosystems can lead \r\nto temporary increases in biodiversity and functional diversity (e.g., \r\ndue to immigration of boreal species in the Arctic, high confidence), \r\nbut reduced trophic-transfer efficiencies and functional redundancy, \r\nwith uncertain consequences for ecosystem resilience and vulnerability \r\n(limited evidence, low agreement) (Griffith et al., 2019b; Alabia et al., \r\n2020; du Pontavice et al., 2020; Alabia et al., 2021; Frainer et al., 2021)"


id: 5301e5e56819cc345ebd0b2520544583
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content:
"\r\nCalcareous polar organisms are among the groups most sensitive \r\nto ocean acidification (high confidence) (Section  3.3.2). Niemi et  al. \r\n(2021) reports that >80% of sampled sea snail, Limacina helicina, a key \r\nspecies in pelagic food webs, displayed signs of shell dissolution in the \r\nAmundsen Gulf. However, bacteria, phytoplankton, zooplankton and \r\nbenthic communities are found to be detrimentally impacted, resilient \r\nor even positively influenced by ocean acidification in observational "


id: c81a41877da016d42a35b194edd65675
created_at: 2023-03-16 14:02:16
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"The polar seas cover ~20% of the global ocean and include the deep \r\nArctic Ocean and surrounding shelf seas as well as the Southern \r\nOcean south of the polar front. They play a significant role in ocean \r\ncirculation and absorption of anthropogenic CO2 (Meredith et  al., \r\n2019). The Arctic is characterised by polar seas surrounded by land, \r\nwhile the Antarctic comprises continental Antarctica surrounded \r\nby the Southern Ocean. These high-latitude ecosystems share key \r\nproperties, including strong seasonality in solar radiation and sea \r\nice coverage. Sea ice regulates water-column physics, chemistry and \r\nbiology, air-sea exchange and is a critical habitat for many species. \r\nIn spring, when solar radiation returns and sea ice melts, intense \r\nphytoplankton blooms fuel food webs that include rich communities \r\nof both resident and summer-migrant species, with typically high \r\ndependency on a few key species for trophic transfer (Meredith et al., \r\n2019; Rogers et al., 2020)"


id: ce576982bc77b1df9f1d08cdb7712ae2
created_at: 2023-03-16 14:02:16
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content:
" Over the past two decades, Arctic Ocean \r\nsurface temperature has increased in line with the global average, \r\nwhile there has been no uniform warming across the Antarctic (high \r\nconfidence) (WGI AR6 Chapter 9; Fox-Kemper et al., 2021). Thus, the \r\nrate of change due to warming, and associated sea ice loss, is greater \r\nin the Arctic than in the Antarctic (high confidence) (Section  3.2; \r\nTable  3.14; WGI AR6 Chapter  9; Fox-Kemper et  al., 2021). Both \r\nArctic and Antarctic regions have a long history of living resource \r\nextraction, including some of the largest fisheries on the globe in \r\nterms of catches. However, only the Arctic hosts human populations, \r\nholding a rich Indigenous knowledge and local knowledge (IKLK) on \r\nthese social-ecological systems (Cross-Chapter  Paper 6; Meredith \r\net al., 2019)."


id: 4ea37d90d8007fbf2e15e95c1bd0b461
created_at: 2023-03-16 14:02:16
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content:
"declining) in productivity for key ecological and commercial species, \r\nand functional groups, with weak to strong dependence on emission \r\nscenarios, indicating low confidence in future outcomes for polar \r\nmarine ecosystems and associated ecosystem services (Section  3.5; \r\nPinones and Fedorov, 2016; Griffiths et  al., 2017; Klein et  al., 2018; \r\nHansen et al., 2019; Meredith et al., 2019; Steiner et al., 2019; Tai et al., \r\n2019; Alabia et  al., 2020; Holsman et  al., 2020; Reum et  al., 2020; \r\nVeytia et  al., 2020; Sando et  al., 2021). Potentially highly influential \r\ntipping points associated with Arctic sea ice melt and Antarctic ocean \r\ncirculation change adds to this uncertainty (Cross-Chapter  Paper 6; \r\nHeinze et  al., 2021). Nevertheless, increasing evidence supports that \r\nsustainable and adaptive ecosystem-based fisheries practices can \r\nreduce detrimental impacts of climate change on harvested populations \r\n(medium confidence) (Section 3.6.3.1.2; Klein et al"


id: 53a5c4b7f413865e7bae2c4059e76aca
created_at: 2023-03-16 14:02:16
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content:
"and experimental studies (Section 3.3; Hildebrandt et al., 2016; Thor \r\net al., 2018; Ericson et al., 2019; McLaskey et al., 2019; Meredith et al., \r\n2019; Petrou et  al., 2019; Renaud et  al., 2019; Brown et  al., 2020; \r\nHancock et  al., 2020; Henley et  al., 2020; Johnson and Hofmann, \r\n2020; Torstensson et  al., 2021). While fish larval stages may be \r\nsensitive, adult fish are expected to have low vulnerability to projected \r\nacidification levels (Section  3.3.3; Hancock et  al., 2020), although \r\nreduced swimming capacity in polar cod in an ocean acidification \r\nexperiment has been observed (Kunz et  al., 2018). Polar organisms' \r\nsensitivity to ocean acidification may increase with increasing light \r\nlevels due to the loss of sea ice (algae; Donahue et al., 2019; Kvernvik \r\net  al., 2020), temperature stress (pteropods; Johnson and Hofmann, \r\n2020) or indirectly via increased heterotrophic bacterial productivity \r\n(limited evidence) (Vaque et  al., 2019)"


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vector_id: 24378
content:
" Due to limited mechanistic \r\nunderstanding of observed effects, and mixed responses among Arctic \r\nspecies, future impacts of ocean acidification are assigned medium \r\nconfidence for polar species and low confidence for outcomes for polar \r\necosystems (Meredith et al., 2019; Green et al., 2021b)."


id: 1fe62cbdd6700dba9157304418cd6e19
created_at: 2023-03-16 14:02:16
updated_at: 2023-03-16 14:02:16
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vector_id: 2455
content:
"Thermal tolerances of epipelagic populations drive biogeographic \r\nchange (Figures 3.10, 3.15), but the strength and direction of range \r\nshifts tend to be modulated by both climate-induced and non-climate \r\ndrivers (Pinsky et al., 2020b), including: (a) interactive effects of hypoxia \r\nand ocean acidification (Sampaio et al., 2021); (b) oceanic dispersal \r\nbarriers (Choo et al., 2021), food and critical habitat availability (Alabia \r\net  al., 2020; Tanaka et  al., 2021); (c)  geographic position, including \r\ndepth (Mardones et al., 2021); and (d) ocean currents (Sunday et al., \r\n2015; Chapman et  al., 2020; Fuchs et  al., 2020). The difference \r\nbetween physiological thermal tolerances (Section  3.3.2) and local \r\nenvironmental conditions determines safety margins against future \r\nclimate warming in ectotherms (Pinsky et al., 2019). Acclimation and \r\nevolution (Section  3.3.4) and life-history stage (Section  3.3.3) also \r\nalter species' thermal tolerances"


id: 8933f3e8dc24e41db7b088f094b98b97
created_at: 2023-03-16 14:02:16
updated_at: 2023-03-16 14:02:16
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index: climate_gpt_only_giec
vector_id: 19125
content:
"Ensemble global model projections indicate future increases in primary \r\nproduction and total animal biomass towards 2100 under RCP2.6 (~5 \r\nand 50%, respectively) and RCP8.5 (~10 and 70%, respectively), in the \r\nArctic (Bryndum-Buchholz et  al., 2019; Lotze et  al., 2019; Nakamura \r\nand Oka, 2019), highlighting opportunities for, and possibly conflicts \r\nover, new ecosystem services (Section  3.5). For the Southern Ocean, \r\nno overall trends are apparent, but greater variability in both primary \r\nproduction and total animal biomass are projected under RCP2.6, with \r\nan ~5 and 15% increase in primary production and total animal biomass \r\nunder RCP8.5, respectively (Bryndum-Buchholz et al., 2019; Lotze et al., \r\n2019; Nakamura and Oka, 2019). All projections presented exhibit \r\nhigh inter-model variability and hence uncertainty (Heneghan et  al., \r\n2021). Furthermore, regional models project significant distributional \r\nshifts and wide-ranging trends (i.e"


id: c21a35ac721bc76a537a2a83867ab321
created_at: 2023-03-16 14:02:16
updated_at: 2023-03-16 14:02:16
content_type: text
index: climate_gpt_only_giec
vector_id: 28118
content:
"Breitburg et  al., 2018). Oxygen availability and the effects of ocean \r\nacidification (Sections  3.3, 3.4.2) on zooplankton might become a \r\ndominant constraint in the upper ocean's metabolic index, which is \r\nprojected to decrease globally by 20% by 2100 (Deutsch et al., 2015; \r\nSteinberg and Landry, 2017). In addition, extremely rapid acceleration \r\nof climate velocities projected in the mesopelagic under all emissions \r\nscenarios suggest that species in this ocean stratum will be even \r\nmore exposed to future warming than species in the epipelagic \r\n(Figure 3.4; Brito-Morales et al., 2020). But projections also suggest \r\nthat warming-related increases in trophic efficiency lead to a 17% \r\nincrease in the biomass of the deep-scattering layer (zooplankton \r\nand fish in the mesopelagic) by 2100 (low confidence) (Bindoff et al., \r\n2019a)"


id: 860888c4bd5eea5a7256595b23392c92
created_at: 2023-03-16 14:02:16
updated_at: 2023-03-16 14:02:16
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vector_id: 18625
content:
" Observational studies appear to show that mesopelagic fishes \r\nadapted to warm water increased in abundance and distribution in the \r\nCalifornia Current associated with warming and the expansion of OMZ \r\n(Koslow et al., 2019), suggesting that some mesopelagic fish stocks \r\nmight be resilient to a changing climate (medium confidence)."


id: 89331a8520d28115a0348994c1906798
created_at: 2023-03-16 14:02:16
updated_at: 2023-03-16 14:02:16
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vector_id: 19124
content:
"Epipelagic isotherms have recently (1980-2015) deepened at an \r\naverage of 6.6 +- 18.8 m per decade (Pinsky et al., 2019), but there \r\nis low agreement on whether species move deeper in pursuit of \r\nthermal refuge. Prior studies suggested range shifts to depth (Dulvy \r\net al., 2008; Pinsky et al., 2013; Yemane et al., 2014), but increasing \r\nevidence suggests that fish and planktonic communities across large \r\nparts of the North Atlantic, sub-Arctic and northeast Pacific Ocean \r\nredistribute horizontally with horizontal climate velocity, except where \r\nvertical temperature gradients are particularly steep. There is low \r\nconfidence for temperature-driven depth shifts in the epipelagic zone \r\n(Burrows et al., 2019; Campana et al., 2020; Caves and Johnsen, 2021)"


id: b27f359ea347683a4985129a0f8ceb8e
created_at: 2023-03-16 14:02:16
updated_at: 2023-03-16 14:02:16
content_type: text
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vector_id: 25599
content:
" \r\nAt the same time, decreasing oxygen concentrations and the vertical \r\nexpansion of OMZs have already decreased suitable habitat of pelagic \r\nfishes, including tuna and billfishes, by ~15% primarily due to vertical \r\ncompression of environmental niches (Stramma et al., 2012; Deutsch \r\net al., 2015)."


id: 48806e76aa1fec2509b044fc5747b68
created_at: 2023-03-16 14:02:16
updated_at: 2023-03-16 14:02:16
content_type: text
index: climate_gpt_only_giec
vector_id: 8778
content:
"Since SROCC, field data have continued to show that the phenology \r\nof biological events in the ocean is very likely (high to very high \r\nconfidence) advancing in response to climate change, with 71.9% \r\nof published observations consistent with these anticipated effects \r\n(Figure 3.16a,b; Table 3.19), although most reports (95.6%) were from \r\nthe Northern Hemisphere (Figure  3.16a). Biological events that are \r\nshifting earlier in response to climate change include phytoplankton \r\nblooms (Scharfe and Wiltshire, 2019; Chivers et  al., 2020) such as: \r\n(a)  those of HAB species (Forsblom et  al., 2019; Bucci et  al., 2020); \r\n(b) peaks in zooplankton abundance (Chevillot et al., 2017; Forsblom \r\net al., 2019); (c) the migration (Otero et al., 2014; Kovach et al., 2015; \r\nChust et al., 2019) and spawning of commercial fish (McQueen and \r\nMarshall, 2017; Kanamori et  al., 2019), including crabs and squid \r\n(Henderson et al., 2017); and (d) breeding of marine reptiles (Mazaris \r\net al"


id: f6e1219d2d4b307c9a0f70123af38fcd
created_at: 2023-03-16 14:02:16
updated_at: 2023-03-16 14:02:16
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index: climate_gpt_only_giec
vector_id: 36355
content:
", 2008; Cherkiss et al., 2020). Moreover, different trophic levels \r\nwithin epipelagic food webs are responding at different rates (very \r\nhigh confidence) (Table  3.19; Figure  3.16b,c), with greater and \r\nmore consistent responses by lower trophic levels (phytoplankton, \r\nholozooplankton and meroplankton) but less consistent, weaker \r\nand more varied responses by higher trophic levels. There were too \r\nfew independent time series to make robust estimates for benthic \r\ninvertebrates, plants, marine reptiles and mammals. This differential \r\nresponse across trophic levels could lead to trophic mismatches \r\n(Neuheimer et  al., 2018), where predators and their prey respond \r\nasynchronously to climate change (Edwards and Richardson, 2004; \r\nRogers and Dougherty, 2019; Rubenstein et al., 2019; Emond et al., \r\n2020), with potential population-level consequences, including \r\ndeclines in fish recruitment (Burthe et al., 2012; Chevillot et al., 2017; \r\nMcQueen and Marshall, 2017; Asch et al"


id: 327489c5db76400fe69c5fadeacbe177
created_at: 2023-03-16 14:02:16
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content_type: text
index: climate_gpt_only_giec
vector_id: 5352
content:
", 2019; Durant et al., 2019; \r\nRegnier et  al., 2019). Available evidence also suggests that feeding \r\nrelationships could modulate species responses to climate change, "


id: c21498b0e870ecafa7a66bef26ff891b
created_at: 2023-03-16 14:02:16
updated_at: 2023-03-16 14:02:16
content_type: text
index: climate_gpt_only_giec
vector_id: 28115
content:
"The CMIP6 ESM ensembles project that, by 2100, 18.8  +-  19.0% \r\n(mean  +-  very likely range) and 38.9  +-  9.4% of the ocean surface \r\nwill very likely undergo a change of 20 d or more (advance or delay) \r\nin the start of the phytoplankton growth period under SSP1-2.6 and \r\nSSP5-8.5, respectively (Figure  3.17a,b) (low confidence  due to the \r\ndependence with the projected changes in phytoplankton biomass, \r\nthe trends of which are reported with low confidence) (Section 3.4.3.4; \r\nSROCC Section  5.2.3; Bindoff et  al., 2019a). Phytoplankton growth \r\nis projected to begin later in the Northern Hemisphere subtropics, \r\nand earlier at high latitudes in some regions around the Antarctic \r\nPeninsula, and over large areas in the Northern Hemisphere (low to \r\nmedium confidence as there are improved constraints from historical \r\nvariability in this region and consistency with CMIP5-based-studies \r\nresults) (Henson et  al., 2018b; Asch et  al., 2019)"


id: e11d4515dded26a58826cefbbea3e88b
created_at: 2023-03-16 14:02:16
updated_at: 2023-03-16 14:02:16
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vector_id: 32915
content:
"measures indicate that the most dramatic increases in diversity relative \r\nto current conditions are expected for photosynthetic eukaryotes \r\nand copepods in the Arctic Ocean (Ibarbalz et  al., 2019). However, \r\ncomponent eukaryotic taxa, for example diatoms (Busseni et al., 2020), \r\nare projected to lose diversity by 2100 under RCP8.5. Ecosystem models \r\nproject a decline in nutrient supply that drives the disappearance of \r\nless-competitive and larger phytoplankton types, leading to extinction \r\nof up to 30% of diatom types, particularly in the Northern Hemisphere, \r\nby 2100 under RCP8.5 (Henson et al., 2021). Models further suggest \r\nthat high latitudes are likely to encounter entirely novel phytoplankton \r\ncommunities by 2100 under RCP8.5 (100% change in community \r\ncomposition; Dutkiewicz et al., 2019; Reygondeau et al., 2020)"


id: 86855fdb4e5489a552e76cca47c82036
created_at: 2023-03-16 14:02:16
updated_at: 2023-03-16 14:02:16
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vector_id: 18706
content:
" At the \r\npolar edges, the increased richness is projected to coincide with high \r\nspecies turnover and increasing dominance of smaller phytoplankton \r\ntypes (Henson et  al., 2021). These imply pronounced changes to \r\nboth the oceans' ecological and biogeochemical function, as regions \r\ndominated by small phytoplankton typically support less-productive \r\nfood webs (Section 3.4.3.4; Stock et al., 2017; Armengol et al., 2019) \r\nand sequester less particulate organic carbon (POC) in the deep ocean "


id: cd0394ddeacfb0693a26a05d4d162397
created_at: 2023-03-16 14:02:16
updated_at: 2023-03-16 14:02:16
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vector_id: 29801
content:
"At local to regional scales, tropicalisation often increases species \r\nrichness where warm-water species extend their ranges to overlap with \r\nexisting communities and decreases species richness where warming \r\nwaters extirpate species (medium to high confidence) (Friedland et al., \r\n2020a; Chaudhary et  al., 2021; Worm and Lotze, 2021). Latitudinal \r\nestimates from catalogued observations show declining species richness \r\nin equatorial waters over the past 50 years, with concomitant increases \r\nin species richness at mid-latitudes; the pattern is especially prominent \r\nin free-swimming pelagic species (Figure 3.18; Chaudhary et al., 2021). \r\nSimilar patterns among marine animals have been described previously \r\nfor historical warming events (Song et  al., 2020b). Tropicalisation is \r\nassociated with increased representation of herbivorous species (Verges \r\net  al., 2016; Zarco-Perello et  al., 2020; Smith et  al"


id: 7771a2c492f2fcb8f18a5fc9beb02918
created_at: 2023-03-16 14:02:16
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vector_id: 16349
content:
", 2021), although \r\nobservations and theory suggest that dietary generalism can also favour \r\nrange-shifting species (Monaco et al., 2020; Wallingford et al., 2020)."


id: 253b37bac8650b27170ce90c4760c6b2
created_at: 2023-03-16 14:02:16
updated_at: 2023-03-16 14:02:16
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vector_id: 3289
content:
"The profound climatic and environmental changes projected for the \r\nArctic region by 2100 (Cross-Chapter Paper 6) are also anticipated to \r\nalter the composition of apex assemblages like marine mammals (see \r\nBox 3.2; Albouy et al., 2020). Under both RCP2.6 and 8.5 scenarios \r\nthe most vulnerable marine mammal species will be the North Pacific \r\nright whale (Eubalaena japonica, listed as an endangered species; \r\nIUCN, 2020) and the grey whale (Eschrichtius robustus, which has \r\ncritically endangered subpopulations; IUCN, 2020). The extinction of \r\nthe most-vulnerable species will disproportionately eliminate unique \r\nand important evolutionary lineages as well as functional diversity, \r\nwith consequent impacts throughout the entire marine ecosystem \r\n(Section  3.3.4)"


id: fc6f1e78f5f7464bc1117b94726d92d4
created_at: 2023-03-16 14:02:16
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vector_id: 37225
content:
" More generally, future warming and acidification \r\nsimulated in mesocosm experiments support projections of a \r\nsubstantial increase in biomass and productivity of primary producers \r\nand secondary consumers, but a decrease by >40% of primary \r\nconsumers (Nagelkerken et al., 2020). On longer time scales, alteration \r\nof energy flow through marine food webs may lead to ecological \r\ntipping points (Wernberg et al., 2016; Harley et al., 2017) after which \r\nthe food web collapses into shorter, bottom-heavy trophic pyramids \r\n(medium confidence)."


id: 5a9f252200649d922cae383469eb6e1
created_at: 2023-03-16 14:02:16
updated_at: 2023-03-16 14:02:16
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vector_id: 11779
content:
"Climate-change-driven changes in ocean characteristics and the \r\nfrequency and intensity of extreme events (Section 3.2) increase the \r\nrisk of persistent, rapid and abrupt ecosystem change (very high \r\nconfidence), often referred to as ecosystem collapses or regime shifts \r\n(AR6 WGI Chapter 9; Collins et al., 2019a; Canadell and Jackson, 2021; \r\nMa et  al., 2021). Such abrupt changes include altering ecosystem \r\nstructure, function and biodiversity outside the range of natural \r\nfluctuations (Collins et al., 2019a; Canadell and Jackson, 2021). They \r\ncan involve mass-mortality events and 'tipping points' or 'critical \r\ntransitions', where strong positive feedbacks within an ecosystem lead \r\nto self-sustaining change (Figure 3.19a; Scheffer et al., 2012; Mollmann \r\net  al., 2015; Biggs et  al., 2018). Abrupt ecosystem shifts have been \r\nobserved in both large open-ocean ecosystems and coastal ecosystems \r\n(Section 3.4"


id: c9a052995bfa7f62f86805e345461d54
created_at: 2023-03-16 14:02:16
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content:
"2), with dramatic social consequences through significant \r\nloss of diverse ecosystem services (high confidence) (Section 3.5; Biggs \r\net al., 2018; Pinsky et al., 2018; Beaugrand et al., 2019; Collins et al., \r\n2019a; Filbee-Dexter et al., 2020b; Huntington et al., 2020; Trisos et al., \r\n2020; Turner et al., 2020b; Canadell and Jackson, 2021; Ma et al., 2021; \r\nRuthrof et al., 2021). A summary of previous assessments of abrupt \r\necosystem shifts and extreme events is provided in Table 3.21."


id: 9add6a02ffb7a172dd9f5d2d19c8b8e1
created_at: 2023-03-16 14:02:16
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vector_id: 21898
content:
"Marine birds (seabirds and shorebirds) and mammals include charismatic species and species that are economically, culturally and \r\necologically important (Sydeman et al., 2015; Albouy et al., 2020; Pimiento et al., 2020). Their long generation times and slow population \r\ngrowth suggests limited evolutionary resilience to rapid climate change (Section 3.3.4; Sydeman et al., 2015; Miller et al., 2018). According \r\nto the Red List Species Assessments of the International Union for Conservation of Nature (IUCN, 2020), the greatest current hazards to \r\nthese groups include human use of biological resources and areas, invasive species and pollution (see Figure Box 3.2.1; Dias et al., 2019; \r\nLusseau et al., 2021). Impacts of climate change and severe weather are ranked among the five most-important hazards influencing \r\n131 and 45 bird and mammal species, respectively (see Figure Box 3.2"


id: 8505c371fb149eaa3dcf5ea002c16d00
created_at: 2023-03-16 14:02:16
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content:
"1 for selection of species), including 24 bird and 7 mammal \r\nspecies that are currently listed as endangered, critically endangered or threatened. Furthermore, according to these IUCN assessments, \r\nclimate change and severe weather are expected to impact an additional 122 and 18 marine bird and mammal species over the next \r\n50-100 years, respectively (see Figure Box 3.2.1; Dias et al., 2019)."


id: eaa8f9f5a2fccbd642f858b139cfb351
created_at: 2023-03-16 14:02:16
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vector_id: 34429
content:
"Climate change is affecting marine food-web dynamics (high confidence) (Sections 3.4.2, 3.4.3), and the vulnerability and adaptive \r\ncapacity of marine birds and mammals to such changes is linked to the species' breeding and feeding ecology. Higher-vulnerability \r\nspecies include central-place foragers (confined to, for example, breeding colonies fixed in space), diet and habitat specialists, and species \r\nwith restricted distributions such as marine mammal populations in SES (medium confidence) (McMahon et al., 2019; Ropert-Coudert \r\net al., 2019; Albouy et al., 2020; Grose et al., 2020; Sydeman et al., 2021). Surface-feeding and piscivorous marine birds appear to be more \r\nvulnerable to food-web changes than diving seabirds and planktivorous seabirds (medium confidence) (Sydeman et al., 2021). During \r\nthe 2014-2015 Pacific heatwave, around 1 million piscivorous common murres died along a 1500 km coastal stretch in the Pacific USA \r\ndue to reduced prey availability (Jones et al"


id: 375ba0e0227490d2ea2bdb2d840bdb1b
created_at: 2023-03-16 14:02:16
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vector_id: 6093
content:
", 2018b; Piatt et al., 2020). Marine birds are vulnerable to phenological shifts in food-web \r\ndynamics, as they have limited phenotypic plasticity of reproductive timing, with potentially little scope for evolutionary adaptation \r\n(medium confidence) (Keogan et al., 2018), although changes in reproduction timing are observed in several species (Section 3.4.4.1; \r\nSydeman et al., 2015; Descamps et al., 2019; Sauve et al., 2019). There is limited evidence of marine mammals' capacity to adapt to \r\nshifting phenologies, but observed responses include changes in the onset of migrations, moulting and breeding (Section 3.4.4.1; Ramp \r\net al., 2015; Hauser et al., 2017; Beltran et al., 2019; Bowen et al., 2020; Szesciorka et al., 2020)."


id: b009c4d06e0076a0eccbc3a6c9da3f85
created_at: 2023-03-16 14:02:16
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vector_id: 25227
content:
"Ecosystems can recover from abrupt shifts (e.g., Babcock et al., 2019; \r\nChristie et al., 2019; Medrano et al., 2020). However, where climate \r\nchange is a dominant driver, ecosystem collapses increasingly cause \r\npermanent transitions (high confidence), although the extents of \r\nsuch transitions depend on the emission scenario (Trisos et al., 2020; \r\nGarrabou et al., 2021; Klein et al., 2021; Pratchett et al., 2021; Wernberg, \r\n2021). Over the coming decades, MHWs are projected to very likely\r\nbecome more frequent under all emission scenarios (Section 3.2; WGI \r\nAR6 Chapter  9; Fox-Kemper et  al., 2021), with intensities and rates \r\ntoo high for recovery of degraded foundational species, habitats or \r\nbiodiversity (medium confidence) (Babcock et  al., 2019; Garrabou \r\net al., 2021; Klein et al., 2021; Serrano et al., 2021; Wernberg, 2021). \r\nEmission pathways that result in temperature overshoot above 1"


id: de5ad9408f75b2f937a8c88b34519de7
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vector_id: 32478
content:
"5o\r\nC \r\nwill increase the risks of abrupt and irreversible shifts in coral reefs and \r\nother vulnerable ecosystems (Section 3.4.4)."


id: df36c3b1893fa4be61589e054e223548
created_at: 2023-03-16 14:02:16
updated_at: 2023-03-16 14:02:16
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vector_id: 32619
content:
"The time of emergence of ecosystem responses supports planning \r\nfor specific time-bound actions to reduce risks to ecosystems \r\n(Section 3.6.3.2.1; Bruno et al., 2018; Trisos et al., 2020). Although under \r\nRCP8.5, climate refugia from SST after 2050 are primarily in the Southern \r\nOcean in tropical waters, these refugia are mainly from deoxygenation \r\n(Bruno et  al., 2018). Marine assemblages in these places will be \r\nexposed to unprecedented temperatures after 2050, peaking in 2075 \r\n(Figure 3.20a,b; Trisos et al., 2020). In contrast, changes in phytoplankton \r\ncommunity structure will emerge earlier, primarily in the Pacific Ocean \r\nsubtropics and through much of the North Atlantic Ocean (Figure 3.20c,d; \r\nDutkiewicz et  al., 2019). Under RCP8.5, changes in phytoplankton \r\ncommunity structure and, to a lesser extent, exposure of marine species \r\nto unprecedented temperatures, will emerge earlier in marine protected \r\nareas (MPAs), covering ~7.7% of the global oceans (Section 3.6.2"


id: b2b3505a3295c4aa1b0e2bb8458c873b
created_at: 2023-03-16 14:02:16
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index: climate_gpt_only_giec
vector_id: 25638
content:
"3.2.1; \r\nUNEP-WCMC and IUCN, 2020; UNEP-WCMC and IUCN, 2021) as \r\ncompared with non-MPAs (Figure 3.20b,d). Such assessment can support \r\nplanning for future MPA placement and extent. Because MPAs can \r\nserve as refugia from non-climate drivers (Sections  3.6.2.3, 3.6.3.2.1), \r\nthey facilitate opportunities for adaptation among marine species and \r\ncommunities in coastal oceans (Section 3.4.2)."


id: 3479f8ac2c47eff903010c7ff4108400
created_at: 2023-03-16 14:02:16
updated_at: 2023-03-16 14:02:16
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index: climate_gpt_only_giec
vector_id: 5667
content:
"declines (with very likely range) are -5.7 +- 4.1% and -15.5 +- 8.5% \r\nunder SSP1-2.6 and SSP5-8.5, respectively, by 2080-2099 relative to \r\n1995-2014 (Figure 3.21g), showing greater declines and lower inter\u0002model uncertainties (Tittensor et al., 2021). These declines result from \r\ncombined warming and decreased primary production (with low \r\nconfidence in future changes in primary production; Section 3.4.3.5) \r\nand are amplified at each trophic level within all ESM and marine \r\necosystem model projections across all scenarios (medium confidence) \r\n(Kwiatkowski et al., 2019; Lotze et al., 2019; Tittensor et al., 2021). \r\nHowever, there is limited evidence about how underlying food-web \r\nmechanisms amplify the climate signal from primary producers to \r\nhigher trophic levels, and several putative mechanisms have been \r\nproposed (Section 3.4.4.2.2; Chust et al., 2014a; Stock et al., 2014; \r\nKwiatkowski et al., 2019; Lotze et al., 2019; Heneghan et al., 2021)"


id: cdba4dd951527a1b4445a7417bd401d
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vector_id: 29892
content:
"SROCC assessed that reduced food supply to the deep sea will \r\ndrive a reduction in abyssal seafloor biota by 2100 for RCP8.5 \r\n(Table  3.23). Simulations from one size-resolved benthic biomass \r\nmodel coupled to an ocean-biogeochemistry model forced with the \r\nCMIP5 ESM HadGEM2-ES (Yool et al., 2017) project a decline in the \r\nglobally integrated total seafloor biomass of -1.1 and -17.6% by \r\n2100 under RCP2.6 and RCP8.5, respectively (limited evidence, high \r\nagreement). In waters shallower than 100 m, total benthic biomass \r\nis projected to increase by 3.2% on average by 2100 under RCP8.5, \r\nprimarily driven by warming-increased growth rates (Yool et  al., \r\n2013), while at depths >2000 m (representing 83% of the ocean \r\nseafloor), declines of -32% arise from climate-driven decreases in \r\nsurface primary production and POC flux to the seafloor (Yool et al., \r\n2013; Kelly-Gerreyn et al., 2014; Yool et al., 2015; Yool et al., 2017)"


id: 915c561e5d6519c238fb25d143ae4a34
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content:
"Regionally, multi-model mean changes in primary production show \r\ngenerally similar patterns of large declines in the North Atlantic and \r\nthe western equatorial Pacific, while in the high latitudes, primary \r\nproduction consistently increases in CMIP5 and CMIP6 by 2100 \r\n(Cross-Chapter Paper 6; Kwiatkowski et al., 2020). In the Indian Ocean \r\nand subtropical North Pacific, which were regions of consistent NPP \r\ndecline in CMIP5 projections (Bopp et al., 2013), the regional declines \r\nare reduced in magnitude, less spatially extensive and are typically \r\nless robust in CMIP6. Further assessment of simultaneous changes in \r\nprocesses such as nutrient advection, nitrogen fixation, the microbial \r\nloop and top-down grazing pressure (WGI AR6 Section  5.4.4.2; \r\nLaufkotter et al., 2015; Bindoff et al., 2019a; Canadell et al., 2021) are \r\nrequired to fully understand the regional primary production response \r\nin CMIP6 (Kwiatkowski et al., 2020)"


id: b86364cc856763e0ca9891310eb06a43
created_at: 2023-03-16 14:02:16
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vector_id: 26540
content:
" Given the regional variations in \r\nthe estimates of primary production changes and the uncertainty in the \r\nrepresentation of the dominant drivers, there remains low confidence\r\nin the projected global decline in NPP."


id: 3f255632bee69c6d7f241b720aeb5fea
created_at: 2023-03-16 14:02:16
updated_at: 2023-03-16 14:02:16
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vector_id: 7324
content:
"Analyses of satellite-derived primary production over the past two \r\ndecades (1998-2018) showed generally weak and negative trends (up \r\nto -3.0%) at low and mid latitudes (Kulk et  al., 2020). In contrast, \r\npositive trends occurred in large areas of the South Atlantic and South \r\nPacific Oceans, as well as in polar and coastal (upwelling) regions (up \r\nto +4.5%; Cross-Chapter Paper 6; Kulk et al., 2020). Data-assimilating \r\nocean biogeochemical models estimate a global decline in primary \r\nproduction of 2.1% per decade in the period 1998-2015, driven by \r\nthe shoaling mixed layer and decreasing nitrate concentrations (Gregg \r\nand Rousseaux, 2019). This is consistent with previous assessments \r\nthat identified ocean warming and increased stratification as the main \r\ndrivers (high confidence) affecting the regional variability in primary \r\nproduction Bindoff et al. (2019). However, as noted in SROCC and WGI \r\nAR6 Chapter 2 (Table 3.24; Gulev et al"


id: 8593b5f38bd5a252e9e2115b74a876f6
created_at: 2023-03-16 14:02:16
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vector_id: 18551
content:
", 2021), observed interannual \r\nchanges in primary production on global and regional scales are \r\nnonlinear and largely influenced by natural temporal variability, \r\nproviding low confidence in the trends."


id: a7419f663fe810214ff230809e115a24
created_at: 2023-03-16 14:02:16
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vector_id: 23830
content:
"The SROCC medium confidence assessment that warming, stratification, \r\ndeclines in productivity and changes in plankton community in the \r\nepipelagic zone result in reduced export of primary production to deeper \r\nlayers (Table 3.24) is supported by subsequent literature (Bach et al., \r\n2019; Leung et al., 2021). Particulate organic carbon export efficiency \r\nis constrained by altered mixing and nutrient availability (Boyd et al., \r\n2019; Lundgreen et  al., 2019), particle fragmentation (Briggs et  al., \r\n2020) as well as viral, microbial and planktonic community structure \r\n(Fu et al., 2016; Guidi et al., 2016; Flombaum et al., 2020; Kaneko et al., \r\n2021) and metabolic rates (Cavan et al., 2019). These processes are \r\nstrongly interlinked, and their net effect on primary production export \r\nfrom the upper ocean remains difficult to quantify observationally \r\n(Boyd et  al., 2019)"


id: b6ad555755246119e5d073dce2d8612b
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content:
" Since SROCC, there is increasing evidence that \r\nocean deoxygenation can alter zooplankton community structure \r\n(Wishner et al., 2018), zooplankton respiration rates (Cass and Daly, \r\n2014; Cavan et  al., 2017) and patterns of diel vertical migration \r\n(Aumont et  al., 2018), which may focus remineralisation of organic \r\ncarbon at the upper margins of OMZs (Section 3.4.3.4 on depth shifts \r\ndue to OMZ; Bianchi et al., 2013; Archibald et al., 2019)."


id: b799b6106cc92adeaf76f37dce9348e9
created_at: 2023-03-16 14:02:16
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content:
"drivers during the overshoot period. WGI AR6 assessed that temporary \r\novershoot of a 2degC warming threshold has irreversible effects on global \r\nmean sea level and also effects on ocean heat content that persist \r\nbeyond 2100 (WGI AR6 Section 4.6.2.1; Lee et al., 2021). Model results \r\nindicate that sea surface temperatures (high confidence), Arctic sea ice \r\n(high confidence), surface ocean acidification (very high confidence) \r\nand surface ocean deoxygenation (very high confidence) are reversible \r\nwithin  years to decades if net emissions reach zero or below (WGI \r\nAR6 Table 4.10; Lee et al., 2021). Although changes in these surface \r\nocean variables are reversible, habitat-forming ecosystems, including \r\ncoral reefs and kelp forests, may undergo irreversible phase shifts with \r\n>1.5degC warming (Sections 3.4.2.1, 3.4.2.3), and are thus at high risk \r\nthis century in 1.5degC or 2degC scenarios involving overshoot (Tachiiri \r\net al., 2019)"


id: 82743d3a354d5d9e8bf5760f2e2f9923
created_at: 2023-03-16 14:02:16
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vector_id: 18044
content:
" In an overshoot scenario in which CO2 returns to 2040 \r\nlevels by 2100 (SSP5-3.4-OS; O'Neill et al., 2016), SST and Arctic sea \r\nice do not fully return by 2100 to levels prior to the CO2 peak (medium \r\nconfidence) (WGI AR6 Section 4.6.2.1; Lee et al., 2021), suggesting that \r\nreversal of marine ecological impacts from 21st century climate impacts \r\nwould extend into the 22nd century or beyond (McManus et al., 2021). \r\nModels also indicate that global sea level rise, as well as warming, \r\nocean acidification and deoxygenation at depth, are irreversible for \r\ncenturies or longer (very high confidence) (WGI AR6 Section 4.6.2.1 and \r\nTable 4.10; Palter et al., 2018; Li et al., 2020c; Lee et al., 2021)."


id: 1ceecb4dbe50548b38b7728170b18321
created_at: 2023-03-16 14:02:16
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vector_id: 1999
content:
"Deep-sea ecosystems include all waters below the 200-m isobath as well as the underlying benthos, and they provide habitats for highly \r\ndiversified and specialised biota, which play a key role in the cycling of carbon and other nutrients (see Figure Box 3.3.1; Thurber et al., \r\n2014; Middelburg, 2018; Snelgrove et al., 2018). The deep sea covers >63% of Earth's surface (Costello and Cheung, 2010) and is exposed \r\nto climate-driven changes in abyssal, intermediate and surface waters that influence sinking fluxes of particulate organic matter (high \r\nconfidence) (see Figure Box 3.3.1; Sections 3.1, 3.2.1, 3.2.2, 3.4.3.4; WGII AR5 Section 30.5.7; SROCC Sections 5.2.3, 5.2.4; Hoegh-Guldberg \r\net al., 2014; Bindoff et al., 2019a). These ecosystems are also influenced by non-climate drivers, especially fisheries, oil and gas extraction \r\n(Thurber et al., 2014; Cordes et al., 2016; Zhang et al., 2019a); cable laying (United Nations, 2021); and mineral resource exploration (Hein \r\net al"


id: 66f56999a142257b5af810f842ebb1ef
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vector_id: 13788
content:
", 2021); with proposed large-scale deep-sea mining a potential future source of impacts (Danovaro, 2018; Levin et al., 2020)."


id: a2aa20f86ecb28845de92709d7677a7
created_at: 2023-03-16 14:02:16
updated_at: 2023-03-16 14:02:16
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index: climate_gpt_only_giec
vector_id: 23159
content:
"Ocean warming alters biological processes in deep-sea ecosystems in ways that affect deep-sea habitat, biodiversity and material \r\nprocessing. Enhancement of microbial respiration by warming attenuates sinking POC, which has been associated with the globally \r\nprojected declines in total seafloor biomass of -9.8 and -13.0% by 2081-2100 relative to 1995-2014 under SSP1-2.6 and SSP5-8.5, \r\nrespectively (limited evidence) (Section  3.4.3.4). Additionally, climate-change-driven oxygen loss (Section  3.2.3.2; Luna et  al., 2012; \r\nBelley et al., 2016) and geographic shifts in predator distributions (Section 3.4.3.1) are anticipated to affect deep-sea biodiversity (limited \r\nevidence, high agreement) (Smith et al., 2012; Morato et al., 2020). Complex responses of some bathyal crustacean assemblages to \r\nenvironmental change suggest an increase in phylogenetic diversity but limited decreases in abundances with temperature (Ashford \r\net al., 2019)"


id: ce2e17b3a0b54578199b084642290db
created_at: 2023-03-16 14:02:16
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vector_id: 29957
content:
" Acute mortality of some reef-forming cold-water corals to laboratory-simulated warming (Lunden et al., 2014) suggests \r\nthat both long-term warming and the increase of MHWs in intermediate and deep waters (Elzahaby and Schaeffer, 2019) could pose \r\nsignificant risk to associated ecosystems (high confidence). Thermal tolerance thresholds (lethal and sub-lethal) of scleractinians in \r\nlaboratory settings depend on their geographic position and capacity for thermal adaptation, as well as other factors including food, \r\noxygen and pH (medium to high confidence) (Naumann et al., 2013; Hennige et al., 2014; Lunden et al., 2014; Naumann et al., 2014; \r\nGeorgian et al., 2016; Gori et al., 2016; Maier et al., 2016; Buscher et al., 2017)."


id: f4c47c83940ecffcf425e14c96930565
created_at: 2023-03-16 14:02:16
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vector_id: 36017
content:
"The extension and intensification of deep-water acidification (Section 3.2.3.1) has been identified as a further key risk to deep-water coral \r\necosystems (medium confidence) (Bindoff et al., 2019a). Literature since SROCC supports this assessment (Morato et al., 2020; Puerta \r\net al., 2020), although scleractinians and gorgonians are found in regions undersaturated with respect to aragonite (Thresher et al., 2011; \r\nFillinger and Richter, 2013; Baco et al., 2017). Laboratory experiments on reef-forming scleractinians show variable results, with regional \r\nacclimation potential and population-genetic adaptations (Georgian et al., 2016; Kurman et al., 2017). Desmophyllum pertusum7 and \r\nMadrepora oculata maintain calcification in moderately low pH (7.75) and near-saturation of aragonite (Hennige et al., 2014; Maier et al., \r\n2016; Buscher et al., 2017), but lower pH (7.6) and corrosive conditions lead to net dissolution of D. pertusum skeletons (high confidence) \r\n(Lunden et al"


id: 881cd6587c549cfbaf99c89049955476
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vector_id: 18937
content:
", 2014; Kurman et al., 2017; Gomez et al., 2018). Experiments suggest that D. dianthus is more sensitive to warming than \r\nacidification and when both are high, as projected under climate change. Warming appears to compensate for declines in calcification, \r\nwith fitness also sensitive to food availability (Bramanti et al., 2013; Movilla et al., 2014; Gori et al., 2016; Baussant et al., 2017; Buscher \r\net al., 2017; Schonberg et al., 2017; Hofer et al., 2018; Maier et al., 2019)."


id: f9fd10df622d03fa2960a15ca4cc0c29
created_at: 2023-03-16 14:02:16
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vector_id: 36839
content:
"In OMZ regions (Section 3.2.3.2), benthic species distributions (Sperling et al., 2016; Levin, 2018; Gallo et al., 2020), abundance and \r\ncomposition of demersal fishes in canyons (De Leo et al., 2012) and deep-pelagic zooplankton (Wishner et al., 2018) follow oxygen \r\ngradients, indicating that deep-sea biodiversity and ecosystem structure will be impacted by extension of hypoxic areas (medium \r\nconfidence). Fossil records show benthic population collapse and turnover when oxygen ranged from oxic to mildly or severely hypoxic \r\n(Cross-Chapter Box PALEO in Chapter 1; Moffitt et al., 2015). Regional extirpations among cold-water corals in the paleorecord were \r\nassociated with substantial declines in oxygen, coincident with abrupt warming and altered properties of intermediate water-masses \r\n(Wienberg et al., 2018; Hebbeln et al., 2019). Despite mortality and functional impacts from low oxygen concentrations observed in \r\naquaria (Lunden et al"


id: 7f2f066771131b690f47972ec566c88c
created_at: 2023-03-16 14:02:16
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vector_id: 17561
content:
", 2014), recent observations of the deep-water coral D. pertusum suggest adaptive capacity to hypoxia among \r\nspecimens from OMZ regions that are highly productive (low confidence) (Hanz et al., 2019; Hebbeln et al., 2020)."


id: 7d9b582ceb9a2732377b8802cd3f9f3b
created_at: 2023-03-16 14:02:16
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vector_id: 17335
content:
"Climate-driven impacts further limit the resilience of deep-sea ecosystems to impacts from human activities (high confidence) (Levin and \r\nLe Bris, 2015; Rogers, 2015; Sweetman et al., 2017). However, assessing cumulative climatic and non-climatic impacts is challenging for \r\nthese data-poor environments (Ashford et al., 2018; Levin, 2018; Armstrong et al., 2019; Heffernan, 2019; Kazanidis et al., 2020; Orejas \r\net al., 2020), where lack of knowledge increases the possibility of overlooking ecosystem vulnerabilities and risks (Levin, 2021). A paucity \r\nof information about the natural variability and historical trends of these habitats prevents robust assessment of adaptive capacities and \r\npotential vulnerabilities to extreme events (Aguzzi et al., 2019; Levin et al., 2019; Chapron et al., 2020; Danovaro et al., 2020; Le Bris and \r\nLevin, 2020; Levin, 2021)"


id: fa4e2b84bcb5c2f2919cf54911430748
created_at: 2023-03-16 14:02:16
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vector_id: 36901
content:
" The spatial resolution of CMIP5 models is too coarse to robustly project changes in mesoscale circulation at the \r\nseafloor (Sulpis et  al., 2019), on which deep-sea ecosystems depend for organic material supplies and dispersal of planktonic and \r\nplanktotrophic larvae (high confidence) (Fox et al., 2016; Mitarai et al., 2016; Dunn et al., 2018). Higher-resolution modelling from CMIP6 \r\n(Orr et  al., 2017), multi-annual and high-frequency records of ocean bottom-water properties (Meinen et  al., 2020), and better \r\nunderstanding and accounting of biogeochemical mechanisms of organic carbon transport to the ocean interior is expected to improve \r\nthis capacity (Boyd et al., 2019; Seferian et al., 2020)."


id: 3dbb59c6b3fe3f448b24c5547418ffed
created_at: 2023-03-16 14:02:16
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content:
"of non-indigenous species have directly or indirectly decreased \r\ncommercially important fishery species and nursery habitat (Booth \r\net al., 2018). Non-indigenous species outperform indigenous species \r\nin coastal zones experiencing warming and freshening (McKnight \r\net al., 2021). Non-climate drivers, especially marine shipping in newly \r\nice-free locations (Chan et  al., 2019), fishing pressure (Last et  al., \r\n2011), aquaculture of non-indigenous species (Mach et  al., 2017; \r\nRuby and Ahilan, 2018) and marine pollution and debris (Gall and \r\nThompson, 2015; Carlton et  al., 2018; Carlton and Fowler, 2018; \r\nLasut et al., 2018; Miralles et al., 2018; Rech et al., 2018; Therriault \r\net al., 2018), promote range shifts and movement of non-indigenous \r\nspecies (high confidence). Non-climate drivers can also intensify \r\nthe ecological effects of non-indigenous species (Geraldi et  al., \r\n2020)"


id: 2dbc04659aa6ba5e503c1c0b276cfe10
created_at: 2023-03-16 14:02:16
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content:
" Invasive marine species can alter species behaviour, reduce \r\nindigenous species abundance, reduce water clarity, bioaccumulate \r\nmore heavy metals than indigenous species and inhibit ecosystem \r\nresilience in the face of extreme events (medium confidence) \r\n(McDowell et al., 2017; Geburzi and McCarthy, 2018; Anton et al., \r\n2019; Ruthrof et al., 2021). Risks from invasive species to the sources \r\nof other ecosystem services or aquatic goods, including valuable \r\nmaterials, mining activities, shipping or ocean energy installations, \r\nhave not been evaluated."


id: f25b7bf3543421339f634fe85fb3b848
created_at: 2023-03-16 14:02:16
updated_at: 2023-03-16 14:02:16
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vector_id: 35659
content:
"Climate change is a key agent of biodiversity change in numerous ocean \r\nand coastal ecosystems (very high confidence) (Table 3.26; Worm and \r\nLotze, 2021), and climate change and biodiversity loss reinforce each \r\nother (Portner et al., 2021b). Biodiversity has changed in association \r\nwith ocean warming and loss of sea ice (Sections 3.4.2.10, 3.4.3.3.3; \r\nSection  CCP6 2.4.2), SLR (Section  3.4.2; Cross-Chapter  Box  SLR in \r\nChapter 3), coral bleaching (Section 3.4.2.1), MHWs (Sections 3.4.2.1-\r\n3.4.2.5) and upwelling changes (high confidence) (Section  3.4.2.9). \r\nOverlapping non-climate drivers (Section 3.1) also decrease ocean and \r\ncoastal ecosystem biodiversity (very high confidence) (O'Hara et  al., \r\n2021; Portner et al., 2021b). There is medium confidence that local and \r\nregional marine biodiversity losses from climate disrupt ecosystem \r\nservices provided by specific ocean and coastal species or places \r\n(Sections 3.5.3-3.5.6; Figure 3.23; Table 3.26; see Box 3"


id: 868a27f7b1ef55b08775e5d6115e1ca7
created_at: 2023-03-16 14:02:16
updated_at: 2023-03-16 14:02:16
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content:
"3; Dee et al., \r\n2019a; Hossain, 2019; Smale et al., 2019; Teixeira et al., 2019; Martin \r\net al., 2020; Pathak, 2020; Weiskopf et al., 2020; Zunino et al., 2020; \r\nArcher et al., 2021). However, adaptive capacity varies greatly among \r\necosystems, and ecological functions sometimes remain, despite \r\nchanges in species assemblages, as in certain coral reef communities \r\n(Richardson et  al., 2020). Projected changes in biodiversity due to \r\nclimate change (Section 3.4.3.3.3) are expected to alter the flow and \r\narray of ocean and coastal ecosystem services (high confidence) (Smale \r\net  al., 2019; Cavanagh et  al., 2021; Ruthrof et  al., 2021; Worm and \r\nLotze, 2021), but data gaps hinder developing projections of ecosystem \r\nservice changes detailed enough to support decision making (Rosa \r\net al., 2020)."


id: fba5954e24a8ef57848b0c174be8d8e2
created_at: 2023-03-16 14:02:16
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content:
"Globally, about 17% of humans' average per capita intake of animal \r\nprotein in 2017 came from marine and freshwater wild-caught and \r\naquacultured aquatic animals (Costello et  al., 2020; FAO, 2020a). \r\nPer capita intake of seafood is 50% or more in some Small Island \r\nDeveloping States (SIDS) (Vannuccini et al., 2018), and consumption per \r\ncapita is 15 times higher in Indigenous Peoples than non-Indigenous \r\nPeoples (Cisneros-Montemayor et  al., 2016). Fishery products also \r\nsupply critical dietary micronutrients worldwide (Section  3.5.4.1; \r\nHicks et al., 2019; Vianna et al., 2020). Marine and freshwater fisheries \r\nand aquaculture provide livelihoods for an estimated 10-12% of the \r\nworld's population (Barange et  al., 2018). Fishing and aquaculture \r\nprovide women and their families with substantial amounts of food \r\nand income (Harper et  al., 2020b), because at least 11% of small\u0002scale fishers (Harper et al"


id: 879958fe5dd47f3e0511c30bb891c466
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content:
", 2020b) and up to half of all fishery and \r\naquaculture workers (FAO, 2018) are women. This section assesses \r\nhow climate-driven alterations of the abundance or nutritional quality \r\nof food from the sea could affect humans. Aquaculture, catch potential \r\nchanges and human adaptations to changes in wild and cultured \r\nharvests are assessed in Section 5.9."


id: c465765f837dfc993960707d9b8f30f0
created_at: 2023-03-16 14:02:16
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vector_id: 28471
content:
"to have detrimental effects on seabirds, pelagic fish and marine \r\nmammals (medium confidence) (Lindegren et al., 2018; Steiner et al., \r\n2019), which may harm dependent human communities, including \r\nArctic Indigenous Peoples (low confidence) (Arctic Monitoring and \r\nAssessment Programme, 2018; Steiner et al., 2019). Modelled fishery \r\nfutures and revenue depend on environmental scenario, fishing\u0002fleet composition and management, and ocean acidification and \r\ntemperature responses of harvested species (high confidence) (Punt \r\net al., 2014; Punt et al., 2015; Seung et al., 2015; Fernandes et al., 2017; \r\nRheuban et al., 2018; Tai et al., 2019; Punt et al., 2020). Detrimental \r\neffects of ocean acidification are projected to begin emerging in specific \r\nfisheries by 2030 (limited evidence, high agreement) [(southern Tanner \r\ncrab (Chionoecetes bairdi) (Punt et al., 2015); sea scallop (Placopecten \r\nmagellanicus) (Rheuban et  al"


id: 4bf741aa821b049c34088b1b235ae410
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vector_id: 9378
content:
", 2018); Northeast Arctic cod (Gadus \r\nmorhua) (Hansel et al., 2020); Arctic fisheries (Lam et al., 2016)]. At the \r\nsame time, projected hypoxic conditions of ~2 mg l-1 of oxygen will \r\nbe consistently detrimental across taxonomic groups, developmental \r\nstages and climate regions (high confidence) (Sampaio et al., 2021). \r\nEcosystem-based management (Section 3.6.3.1.2) shows promise for \r\ndecreasing risk from interacting climate and non-climate drivers to \r\nforage species and fished species."


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"strains (Section 5.9.4; Barton et al., 2015a). Laboratory studies show \r\nthat ocean acidification decreases the fitness, growth or survival of \r\nmany economically and culturally important larval or juvenile shelled \r\nmollusks (high confidence) (Cao et  al., 2018; Onitsuka et  al., 2018; \r\nStevens and Gobler, 2018; Griffith et al., 2019a; Mellado et al., 2019) \r\nand of several valuable wild-harvest crab species (Barton et al., 2015a; \r\nPunt et al., 2015; Miller et al., 2016; Swiney et al., 2017; Gravinese \r\net al., 2018; Tomasetti et al., 2018; Long et al., 2019; Trigg et al., 2019). \r\nOcean acidification alters larval settlement and metamorphosis of fish \r\nin laboratory studies (high confidence) (Cattano et al., 2018; Espinel\u0002Velasco et al., 2018), suggesting possible changes in fish survival and \r\nthus fishery characteristics"


id: 2300a6bdc07c417fb6c74263a8f68980
created_at: 2023-03-16 14:02:16
updated_at: 2023-03-16 14:02:16
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content:
" Deoxygenation can decrease size and \r\nabundance of marine species and suppress trophic interactions (Levin, \r\n2003), decrease the diversity within marine ecosystems (Sperling et al., \r\n2016) while temporarily increasing catchability and increasing the risk \r\nof overfishing (Breitburg et  al., 2018) and decrease the ecosystem \r\nservices provided by specific fisheries (Orio et al., 2021). The chronic \r\neffects of deoxygenation on wild fisheries are complex and highly \r\ninteractive with co-occurring drivers and overall ecosystem responses \r\n(medium evidence, high agreement) (Townhill et al., 2017; Rose et al., \r\n2019). Detecting and attributing marine ecosystem responses to \r\nocean acidification and deoxygenation outside of laboratory studies \r\nremains challenging because of the strong influence of co-occurring \r\nenvironmental changes on natural systems (Section 3.3.5; Rose et al., \r\n2019; Doo et al., 2020)."


id: 7aa6df20bdace8e56a6cb9251a9a7b5
created_at: 2023-03-16 14:02:16
updated_at: 2023-03-16 14:02:16
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vector_id: 16873
content:
"The interaction of climate and non-climate drivers endangers the \r\nsupply of non-food consumable products developed from marine \r\norganisms (limited evidence, high agreement). This broad class \r\nincludes nutraceuticals (derived from fish, krill, shellfish, seaweeds and \r\nmicrobes), food preservatives or additives (derived from crustaceans, \r\nfish, microalgae and seaweeds, and cyanobacteria), pharmaceuticals \r\n(derived from fish, shellfish, microbes, cyanobacteria, corals and \r\nsponges) or cosmetic products (derived from sponges, phytoplankton \r\nand seaweeds, fish etc.) (Freitas et  al., 2012; Dewapriya and Kim, \r\n2014; Leal and Calado, 2015; Stengel and Connan, 2015; Greene \r\net al., 2016; Ciavatta et al., 2017; Gutierrez-Rodriguez et al., 2018). \r\nBut biodiversity changes, warming, acidification and non-climate \r\ndrivers (especially fishing pressure) may decrease the availability \r\nof these organisms or the potency of the compounds they produce \r\n(Section  5.7.5.1; Figure  3"


id: c10d8f00725fe360c0dc320ea2f31e0e
created_at: 2023-03-16 14:02:16
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content:
"23; Table  3.26; Webster and Taylor, 2012; \r\nMehbub et al., 2014; Kotta et al., 2018; Martins et al., 2018; Conrad \r\net al., 2021). Observed and projected declines and movement of fish \r\nstocks due to fishing pressure and climate change impacts (IPCC, \r\n2019b) have generated concerns that the supply and safety of fish and \r\nkrill oil for human dietary supplements may decline (Section 5.7.5.1; \r\nGribble et al., 2016; Lloret et al., 2016). This risk can be lowered by \r\ntechnological adaptations (Section 3.6.2.2), such as increasing the use \r\nof alternative sources like marine phytoplankton, macroalgae, marine \r\nmicrobes (Dewapriya and Kim, 2014; Greene et al., 2016; Dave and \r\nRoutray, 2018; Nguyen et al., 2020) and underutilised resources such \r\nas fish, seal, crab and shrimp byproducts (Dave and Routray, 2018), \r\nand by improving extraction and processing efficiency (Cashion et al., \r\n2017)"


id: 35dac463725953921d1c7b3f52512f02
created_at: 2023-03-16 14:02:16
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vector_id: 5887
content:
" Climate effects on non-food consumable products could be \r\nwidespread yet poorly detected, complicating assessment of impacts, \r\nrisks and vulnerability reduction."


id: 9000ccdaa6a2d56f3767f28851242964
created_at: 2023-03-16 14:02:16
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vector_id: 20183
content:
"Temperature will continue to be a major driver of fisheries changes \r\nglobally, but other non-climate factors like organism physiology and \r\necosystem response (Section 3.3) and fishing pressure (Chapter 5), as \r\nwell as other climate-induced drivers like acidification, deoxygenation \r\nand sea ice loss (Section 3.2), will play critical roles in future global \r\nand local fisheries changes (high confidence). Warming, acidification \r\nand business-as-usual fishing policy under RCP8.5 are projected \r\nto place around 60% of global fisheries at very high risk (medium \r\nconfidence) (Cheung et  al., 2018). Model intercomparison showed \r\nthat ocean acidification and protection affect ecosystems more than \r\nfishing pressure, and ecological adaptation will significantly determine \r\nimpacts on fishery biomass, catch and value until approximately 2050 \r\n(medium confidence) (Olsen et  al., 2018)"


id: d002e8ffcf4160ecea8f8c7d3115a32d
created_at: 2023-03-16 14:02:16
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content:
" Ecosystem responses to \r\nwarming water, fishing pressure, food-web changes, MHWs and sea \r\nice algal populations have been responsible for highly variable or \r\ncollapsing populations of Northern Hemisphere high-latitude forage \r\nfish species including sand lances (Ammodytes spp.), Arctic cod \r\n(Boreogadus saida), capelin (Mallotus catervarius) and herring (Clupea \r\nspp.) (Lindegren et  al., 2018; Steiner et  al., 2019; Arimitsu et  al., \r\n2021; Suca et al., 2021). Declining stocks of forage fish are expected "


id: d49f09ce25cb37c8080603254152d331
created_at: 2023-03-16 14:02:16
updated_at: 2023-03-16 14:02:16
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vector_id: 30974
content:
"There is insufficient evidence to develop global projections of future \r\nclimate impacts on humans through changes in non-food consumable \r\nmarine products, but specific local examples have been investigated, \r\nsuch as the Arctic ooligan (eulachon; Thaleichthys pacificus), a small \r\nsmelt fish. Ooligan grease has been used by Indigenous Peoples of the \r\nNorth Pacific coast (Phinney et al., 2009) for at least 5000 years to treat \r\nstomach aches, colds and skin conditions, and as a traditional food \r\nsource high in omega-3 fatty acids (Byram and Lewis, 2001; Cranmer, \r\n2016; Patton et al., 2019). Analysis of remains have shown that ooligan \r\ncould comprise up to 67% of traditional historical fisheries catches \r\n(Patton et al., 2019)"


id: 17e8fde67bd4d289938362f21079f0f0
created_at: 2023-03-16 14:02:16
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vector_id: 1256
content:
" Because ooligan spawning relies on the timing \r\nof the spring freshet, and because the species has declined in the past \r\n25 years due to fishing pressure and predation, the species may be at \r\nrisk from combined climate-induced and non-climate drivers (medium \r\nconfidence) (Talloni-Alvarez et  al., 2019). Projections under RCP2.6 \r\nor RCP8.5 estimate reductions by 21 or 31% by 2050 in essential \r\nnutrients from traditional seafood for Indigenous Peoples in Canada, \r\nrelative to 2000, with a modelled nutritional deficit that includes non\u0002traditional dietary substitutions (Marushka et al., 2019)."


id: 3c8ac1c42fd72579e9145c70aa5c95b3
created_at: 2023-03-16 14:02:16
updated_at: 2023-03-16 14:02:16
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vector_id: 6891
content:
"Climate impacts have already altered ocean and coastal habitats \r\n(Section 3.4.2; Table 3.26; Gissi et al., 2021) in ways that have led to \r\nspecies range shifts, biodiversity changes, phenology changes and \r\nregime shifts (Section  3.4.3) from the surface ocean to the seafloor \r\n(very high confidence) (see Box 3.3; Figure 3.22). Continued ocean and \r\ncoastal habitat impacts are projected, and their severities will depend \r\non emissions scenario and co-occurring drivers (Section 3.4.3; Qiu et al., \r\n2019) or extremes (e.g., Babcock et al., 2019). Warming and physical \r\ncirculation are projected to change larval dispersal, a habitat-related \r\nservice (Bashevkin et  al., 2020), but identifying probable outcomes \r\nremains challenging owing to the high variability among species, \r\nlocations and recruitment (Schilling et  al., 2020; King et  al., 2021; Le \r\nCorre et al., 2021; Raventos et al., 2021)"


id: 8735dab3e7fbf843528a3af8a6cf470b
created_at: 2023-03-16 14:02:16
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vector_id: 18804
content:
" Climate risks to habitat can \r\nbe decreased by reducing non-climate drivers, preserving ecosystems or \r\nrestoring habitat (Sections 3.6.2, 3.6.3.2). Risk to larval dispersal cannot \r\nbe meaningfully addressed at scale by human-implemented adaptations; \r\ninstead, declines in this service will pressure natural systems to adapt via \r\nphysiological plasticity or evolution (Section 3.3; Bashevkin et al., 2020)."


id: 61b12b4848952568ab05e0f6ad2701e1
created_at: 2023-03-16 14:02:16
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vector_id: 12939
content:
"Limited evidence about climate impacts exists for valuable non-food \r\naquatic materials. Ocean warming and acidification harm red coral \r\n(Corallium rubrum) (Bramanti et al., 2013) and communities hosting \r\nblack coral (Antipatharian spp.), both used for jewellery (Ross et al., \r\n2020). While no-take MPAs (Section  3.6.3.2) enhance red-coral \r\nstructural complexity, they only weakly compensate for warming effects \r\n(Cerrano et al., 2013; Montero-Serra et al., 2019). Antipatharian spp. \r\nare not well studied or monitored (Gress and Andradi-Brown, 2018). \r\nAcidification and warming negatively impact pearl oysters (Welladsen \r\net al., 2010; Liu and He, 2012; Liu et al., 2012; Hoegh-Guldberg et al., \r\n2014; Zhang et  al., 2019b). For example, projected climate impacts \r\nfor 2035 would decrease the average net present value of French \r\nPolynesia's pearl aquaculture industry by 29.1% compared with the \r\npresent (Hilsenroth et  al., 2021)"


id: 75ccc56a0839cd1d049023b5db4cf454
created_at: 2023-03-16 14:02:16
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content:
" Climate impacts on ornamental \r\nspecies sought by aquarists have not been well studied (Dee et  al., \r\n2019b)."


id: 30f2798052e0f2f4107f34ea5c58e1cd
created_at: 2023-03-16 14:02:16
updated_at: 2023-03-16 14:02:16
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vector_id: 5127
content:
"Decreasing the vulnerability of renewable-energy installations, \r\nparticularly wind turbines, to climate risks (Table 3.26; Bindoff et al., \r\n2019a) could include technological adaptations (Section 3.6.2.2) such \r\nas storm 'survival mode' settings (Penalba et al., 2018); preparation \r\nfor hazards such as icing, SLR, drifting sea ice and wave activity (Neill \r\net al., 2018; Goodale and Milman, 2019; Solaun and Cerda, 2019); and \r\nbiofouling (medium confidence) (Want and Porter, 2018; Joyce et al., \r\n2019; Vinagre et al., 2020), which is expected to increase in response \r\nto warming and acidification (medium confidence) (Dobretsov et al., \r\n2019; Khosravi et  al., 2019; Liu et  al., 2020d; Lamim and Procopio, \r\n2021). Macroalgae and fish-processing byproducts are being tested \r\nfor biofuel use (Greene et al., 2016; Alamsjah et al., 2017; Saifuddin \r\nand Boyce, 2017; Sakthivel et al., 2018; Sudhakar et al., 2019; Nguyen \r\net al., 2020; Ramachandra and Hebbale, 2020; Tan et al"


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content:
", 2020), but \r\nweather variability could pose financial risk to this sector (Kleiman \r\net al., 2021)."


id: 6805d381e05a46aaa3428a34a55f9086
created_at: 2023-03-16 14:02:16
updated_at: 2023-03-16 14:02:16
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content:
"the geographic spread and risk of marine-borne human pathogen \r\noutbreaks, including Vibrio spp. (very high confidence) (Table  3.26; \r\nBindoff et al., 2019a; Logar-Henderson et al., 2019; Froelich and Daines, \r\n2020; Montanchez and Kaberdin, 2020; Semenza, 2020; Ferchichi \r\net  al., 2021). Climate change affects at least 30 human pathogens \r\nwith aquatic-system infection routes (e.g., ingestion of contaminated \r\nwater or seafood, or contact with wounds; Table  3.SM.2; Cross\u0002Chapter Box ILLNESS in Chapter 2; Nichols et al., 2018). Conditions \r\nfavourable for Vibrio cholerae are increasing globally, which raises the \r\nrisk to humans (Cross-Chapter Box ILLNESS in Chapter 2). Increased \r\nstorm-related flooding and SLR further increase human encounters with \r\nVibrio spp. (Froelich and Daines, 2020). Aquatic diseases, particularly \r\nVibrio spp., have caused large economic losses in aquaculture by \r\ndecreasing the quality or survival of cultured species (Lafferty et al"


id: 3e377e4d4e47d0bedb039d83d727ba9a
created_at: 2023-03-16 14:02:16
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vector_id: 7161
content:
", \r\n2015; Novriadi, 2016). Temperature-based model projections show that \r\nall Canadian shellfish beds will experience conditions that promote \r\nhigh risk of Vibrio spp. growth by 2100 for both RCP4.5 and RCP8.5 \r\nscenarios (Ferchichi et al., 2021). Climate-induced drivers may increase \r\nVibrio spp. loads in seafood species: laboratory-simulated heatwaves \r\nincrease Vibrio spp. abundance in Pacific oyster (Crassostrea gigas) \r\n(Green et al., 2019) and simulated ocean acidification increases hard \r\nclam (Mercenaria mercenaria) susceptibility to Vibrio spp. infection \r\n(Schwaner et al., 2020). Projected increases in temperature, extreme \r\nand variable rainfall conditions, coastal flooding and SLR (Section 3"


id: 4d5449e303c462bbf44175090e5a7e49
created_at: 2023-03-16 14:02:16
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"2; \r\nCross-Chapter  Box  SLR in Chapter  3) strongly increase the risk of \r\nfrequent and severe aquatic human pathogen outbreaks in ocean \r\nand coastal areas that will continue to harm human health and cause \r\neconomic losses (high confidence) (Cross-Chapter  Box  ILLNESS in \r\nChapter 2; Froelich and Daines, 2020; Semenza, 2020; Ferchichi et al., \r\n2021). Section 3.6.3.1.5 assesses human adaptations to increasing risk \r\nof marine-borne pathogens."


id: 887f5f23a0b2672f99d8273126f481d3
created_at: 2023-03-16 14:02:16
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content:
"et al., 2020; Mastrocicco and Colombani, 2021). Coastal salinisation \r\nis attributed to regionally varying combinations of climate-induced \r\ndrivers, like SLR and storm-related flooding by seawater, and non\u0002climate drivers, like water withdrawal and land-use changes (very high \r\nconfidence) (Islam et al., 2019; Rahman et al., 2019; Paldor and Michael, \r\n2021). Monitoring-related adaptations (Section  3.6.2.2.2), including \r\nadvances in modelling and monitoring, are providing decision-relevant, \r\nregional-scale information (Colombani et  al., 2016; Mukhopadhyay \r\net  al., 2019; Slama et  al., 2020; Corwin, 2021). For example, new \r\nprojections indicate which drinking-water intake stations on China's \r\nPearl River Estuary will be unable to meet demands by 2100 due to \r\nSLR and drought (Wang and Hong, 2021), while others show that SLR \r\neffects on seawater intrusion into the coastal aquifer in Kerala, India, \r\nunder both RCP4.5 and RCP8.5 scenarios are negligible (Sithara et al., \r\n2020)"


id: 5136b34507357b43c22556a441093e50
created_at: 2023-03-16 14:02:16
updated_at: 2023-03-16 14:02:16
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index: climate_gpt_only_giec
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content:
" Salinisation-associated changes may disproportionately burden \r\nwomen responsible for securing drinking water and fuel, such as in \r\nthe Indian Sundarbans (Mukhopadhyay et al., 2019). Salinisation will \r\ncontinue to endanger coastal water and soil quality in the future (high \r\nconfidence) (Islam et  al., 2019; Paldor and Michael, 2021), but the \r\nevidence assessed above shows that subsequent impacts to human \r\nhealth and agriculture will depend heavily on regional variations in \r\nenvironment and human behaviour (medium confidence)."


id: a1a2eb3b0915113b743aaeebbde4cc24
created_at: 2023-03-16 14:02:16
updated_at: 2023-03-16 14:02:16
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index: climate_gpt_only_giec
vector_id: 22987
content:
"Together, climate-induced and non-climate drivers can mobilise \r\ntoxins and contaminants in ways that harm human and marine \r\nspecies health (very high confidence) (see Box  3.2), and climate \r\nchange is altering these relationships (high confidence) (Table  3.26; \r\nBindoff et al., 2019a). Under warming or ocean acidification, marine \r\nmolluscs exposed to pharmaceuticals via wastewater experience \r\nmore detrimental biological consequences or greater bioaccumulation \r\n(limited evidence, high agreement) (Costa et al., 2020a; Costa et al., \r\n2020b; Dionisio et al., 2020; Freitas et al., 2020; Kibria et al., 2021). \r\nPhysical circulation, temperature and biogeochemical characteristics \r\n(Bowman et al., 2020; Liu et al., 2020a; Liu et al., 2020b; Sun et al., \r\n2020; Zhang et al"


id: 72bb609160a6f6abd4f9ee067349db9
created_at: 2023-03-16 14:02:16
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", 2020b) control the ubiquitous oceanic distribution of \r\nmethylmercury, and ocean acidification- and warming-driven changes \r\nin planktonic speciation and interactions can promote additional food\u0002web bioaccumulation of methylmercury (Tada and Marumoto, 2020; \r\nWu et al., 2020b; Zhang et al., 2020b; Zhang et al., 2021a). Interactions \r\namong drivers also matter: temperature plus overfishing increased \r\ntissue methylmercury concentrations in Atlantic bluefin tuna from \r\nthe 1970s to the 2000s more than the decreases in the late 1990s \r\nand 2000s from lower environmental mercury levels (Schartup et al., \r\n2019). This appears true for persistent organic pollutants as well, but \r\ntheir bioaccumulation is related more to temperature effects on animal \r\nbehaviour than on pollutant dynamics (Houde et  al., 2019; Wagner \r\net  al., 2019; Kalia et  al., 2021). By 2100 under RCP8"


id: 1f4545798bc6bf32ed5267a120ef2fc1
created_at: 2023-03-16 14:02:16
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content:
"5, productivity \r\nchanges and community structure shifts are expected to increase \r\nmethylmercury concentrations in polar oceans and high-latitude \r\nphytoplankton and decrease it in low latitudes (Zhang et al., 2021a). \r\nThe estimated average global cost of mercury-related health effects by \r\n2050, mainly from seafood consumption during 2010-2050, will be \r\n19 trillion USD (2020), assuming a 3% discount rate, if methylmercury \r\nemissions are not reduced (Zhang et al., 2021b).\r\nSince previous assessments, evidence has increased that climate \r\nimpacts, such as warming, extreme weather and SLR, are increasing "


id: 17dbd119e0bec62e3e4cb2a3816c94ac
created_at: 2023-03-16 14:02:16
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index: climate_gpt_only_giec
vector_id: 1246
content:
"Climate-driven changes in temperature, salinity (from ice melt and \r\nprecipitation changes), deoxygenation and ocean acidification can \r\nalter dynamics of infectious diseases that target ocean and coastal \r\nspecies by increasing hosts' susceptibility or pathogens' abundance \r\nor virulence (high confidence) (Burge and Hershberger, 2020; Byers, \r\n2021). Coral and urchin diseases have increased over time driven \r\nby warming-related declines in organism recovery and survival or \r\nimmunity (medium confidence) (Cohen et al., 2018; Tracy et al., 2019). \r\nSeagrass and sea star wasting disease outbreaks have occurred \r\nunder combinations of ocean warming or MHWs and non-climate \r\ndrivers (e.g., eutrophication, bottom trawling), but attribution of \r\nthese outbreaks to specific drivers is still not resolved (Harvell et al., \r\n2019; Jakobsson-Thor et al., 2020; Krause-Jensen et al., 2021)"


id: 7beaebf47a90b8cae8478919f8e2c0f3
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vector_id: 17099
content:
" Disease \r\noutbreaks threaten marine biodiversity, species that create habitat or \r\ndampen wave action, and keystone species (Harvell and Lamb, 2020). \r\nAttributing observed changes in marine disease patterns to climate \r\nremains extremely difficult owing to interacting climate and non\u0002climate drivers (Burge and Hershberger, 2020) and lack of baseline \r\ndata (Tracy et al., 2019). Projected increases in the frequency, duration \r\nand intensity of warming events would reduce survival and recovery \r\nof some species from hot events, reduce immunity of other species to \r\npathogens, extend poleward ranges of some pathogens and increase \r\ninfection risk when host species congregate in scarce habitat (Cohen \r\net al., 2018). Pathogens that target ocean and coastal organisms may \r\nthemselves be sensitive to future climate conditions or subsequent "


id: 7ddd51fea40aef2ef735037393212779
created_at: 2023-03-16 14:02:16
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content:
"New examples have illustrated how toxic HABs interfere with regulating, \r\nprovisioning (Section 3.5.3) and cultural ecosystem services (Section 3.5.6) \r\nin interconnected ways (limited evidence, high agreement). A massive \r\ntoxic Pseudo-nitzschia spp. bloom in 2013-2016 along the USA West \r\nCoast triggered Dungeness crab, rock crab and razor clam fishery \r\nclosures to protect human consumers (Sections 3.6.2, 3.6.3.1.5; McCabe \r\net al., 2016), and this disproportionately harmed fishers, especially small\u0002vessel owners, and fishing-support service industries, primarily through \r\nlost revenue (Ritzman et al., 2018; Moore et al., 2019; Trainer et al., 2019; \r\nJardine et al., 2020; Moore et al., 2020a). Toxic Alexandrium spp. blooms \r\npromoted by climate-driven coastal extremes (e.g., MHWs, stratification, \r\nrunoff) in Tasmania, Australia, in 2012 and Chile in 2016 caused fish kills, \r\nshellfish product recalls, substantial economic losses, and human sickness \r\nand death (Trainer et al"


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", 2019). The Chile event caused an estimated loss \r\nof 800 million USD in the farmed salmon industry (Diaz et al., 2019) \r\nand resulted in a series of large, long-lasting regional protests calling \r\nfor national aid (Delgado et al., 2019). New evidence, however, suggests \r\nthat the perceived global increase in harmful algal blooms results from \r\nbetter monitoring and more detrimental bloom impacts, rather than a \r\nclimate-linked mechanism (Hallegraeff et al., 2021)."


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content:
"Coastal ecosystems physically protect people and property from storms \r\nand flooding, and climate change threatens this protection function \r\n(Figure  3.22; Table  3.26). Increasingly detailed models show how \r\nwarm-water coral reefs (Reguero et  al., 2019; Storlazzi et  al., 2019; \r\nReguero et al., 2021) mangroves (Blankespoor et al., 2017; Menendez \r\net  al., 2020; Tregarot et  al., 2021) and wetlands (Sun and Carson, \r\n2020) prevent billions of US dollars of direct and indirect damage to \r\nprivate and public property and shield millions of people from flooding \r\neach year. Protection by mangroves provides more economic benefits \r\nin higher-income nations and shields more people in lower-income \r\nnations (Menendez et  al., 2020). Seagrasses (James et  al., 2020; \r\nJames et al., 2021), kelp (Morris et al., 2020b; Zhu, 2020), suspended \r\nshellfish aquaculture (Gentry et al., 2020; Zhu et al., 2020a), oyster reefs \r\n(Chowdhury et al., 2019), coastal wetlands (Moller, 2019; Keimer et al"


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", \r\n2021) and sandy coastlines (Section 3.4.2.6) Herivaux et al., 2018) also \r\nmeasurably decrease wave energy. Non-climate drivers [e.g., invasive \r\nspecies (James et al., 2020), sediment-supply changes (Ganju, 2019; Ladd \r\net al., 2019; Ilia, 2020), erosion and storm damage (Mehvar et al., 2019; \r\nBacopoulos and Clark, 2021)], acting together with climate-induced \r\ndrivers and associated impacts [e.g., SLR (Cross-Chapter  Box  SLR in \r\nChapter 3), changes in plant biodiversity (Section 3.5.2; Lee Smee, 2019; \r\nSilliman et al., 2019; Schoutens et al., 2020), MHWs (Section 3.4.3.7) \r\nand acidification (Section 3.4.2.1)], compromise physical protection by \r\ncoastal ecosystems (very high confidence). (See Cross-Chapter Box SLR \r\nin Chapter  3 and Sections  3.6.3.1 and 3.6.3.2.2 for assessment of \r\nadaptations that address this ecosystem service.)"


id: 232e9ceb6db4d1fb76239b4df482d240
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"Natural and engineered systems have long been used effectively \r\nto manage precipitation and wastewater safely (see  Box  4.5), and \r\nmaintaining and enhancing them is a key nature-based adaptation \r\nstrategy for coastal communities (Section 3.6.2.3; Cross-Chapter Paper \r\n2). Estimated values of water purification and stormwater management \r\nprovided by coastal ecosystems are in the hundreds to thousands \r\nof USD per hectare [e.g., 272  Euro per 0.01 km2\r\n  yr-1 from the \r\nMediterranean's sandy coastline (Herivaux et  al., 2018); 1100-2800 \r\nUSD per 0.01 km2\r\n  yr-1 from the state of Maryland, USA (Campbell \r\net al., 2020b); 600 USD per 0.01 km2\r\n yr-1 in Zhuzhou City, China (Zhan \r\net al., 2020)]. Both wild and cultured organisms also provide filtration \r\nservices. Seagrasses' ability to purify water is well recognised by coastal \r\nresidents and ocean resource users in tropical and temperate locations \r\n(Ambo-Rappe et al., 2019; Quevedo et al., 2020; Heckwolf et al"


id: 9aeafc1fceb6b8b02c606c6bc098f290
created_at: 2023-03-16 14:02:16
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", 2021; \r\nMcKenzie et  al., 2021a). Globally, aquacultured shellfish remove an \r\nestimated 49,000 tonnes of nitrogen and 6000 tonnes of phosphorus \r\nfrom coastal waters, worth a potential 1.20 billion USD, and they may \r\nhelp improve existing engineered wastewater treatment systems (van \r\nder Schatte Olivier et al., 2020). Climate change, especially episodic \r\nextreme rains and RSLR (Romero-Lankao et al., 2014), is challenging \r\nmanagement and design of wastewater and stormwater systems (high \r\nconfidence) (Flood and Cahoon, 2011; Trtanj et  al., 2016; Hummel \r\net al., 2018; Kirshen et al., 2018; Nazarnia et al., 2020; Reznik et al., \r\n2020; McKenzie et  al., 2021b) and the integrity of coastal landfills \r\n(Beaven et al., 2020). Without substantial adaptation that addresses \r\nprojected wastewater management challenges and community needs \r\n(Section  4.2.6.1; Kirshen et  al., 2018; Kirchhoff and Watson, 2019; \r\nKool et al., 2020; Nazarnia et al., 2020; Hughes et al"


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content:
", 2021), coastal \r\nwater quality in many areas will decrease because of more frequent \r\nor severe releases of untreated wastes (high confidence) (Flood and \r\nCahoon, 2011; Hummel et  al., 2018; Hughes et  al., 2021; McKenzie \r\net al., 2021b), and this will have harmful consequences for human and "


id: 8f497d743b4dac54619ad349dd205caa
created_at: 2023-03-16 14:02:16
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content:
"Current and future total carbon storage and cycling in the ocean are \r\ngoverned by past and future CO2 emissions trajectories (Table 3.26), \r\nbut regional ocean and coastal carbon stocks and cycling vary over \r\ntime and space due to processes being altered by climate, including \r\nocean circulation, sea ice cover, coastal upwelling and thermal \r\nstratification (Section 3.2.2.3); ocean primary production and export \r\n(Sections  3.2.3, 3.4.4); and marine ecosystem biodiversity (high \r\nconfidence) (Section 3.5.2; Figure 3.22). Quantifying regional carbon \r\nfluxes and stocks is still challenging and relies on indirect measures \r\n(e.g., Fennel et  al., 2019; Clay et  al., 2020), especially in coastal \r\necosystems where drivers interact. Carbon cycling and storage co\u0002occurs with other regulating services such as habitat provision, \r\nwater-quality maintenance and coastal protection (Ouyang et  al., \r\n2018), particularly in vegetated coastal ecosystems (see Box  3.4)"


id: 8a1f6736b618457dda50f69f5a61c378
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" \r\nAdaptations to support regional carbon cycling and storage generally \r\nfocus on area-based management and conservation (Section 3.6.3.2), \r\nbut interventions to enhance ocean carbon storage are being explored \r\nfor mitigation (WGIII AR6 Chapter 7)."


id: 40d9cae25cb6057cd3bd75d45b40a492
created_at: 2023-03-16 14:02:16
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"Climate change and other anthropogenic drivers, including eutrophication, land-use changes and overexploitation, directly and indirectly \r\nthreaten blue carbon ecosystems (Annex II: Glossary). Commonly considered blue carbon ecosystems include vegetated coastal ecosystems \r\n(Sections 3.4.2.3-3.4.2.5), whose mangroves, salt marshes and seagrass beds host rooted, vascular plants known to store large amounts of \r\ncarbon for long periods and to be amenable to management (Lovelock and Duarte, 2019). Other ocean and coastal taxa, including rooted \r\nor floating macroalgae (e.g., non-vascular multicellular kelp or seaweed genera such as Macrocystis spp., Sargassum spp. or Laminaria spp. \r\n(Filbee-Dexter and Wernberg, 2020), phytoplankton and even pelagic fauna (e.g., finfish or whales; Chami et al., 2019), have also been \r\nproposed as blue carbon ecosystems. Terrestrial vascular-plant-derived material can also carry and store significant amounts of carbon in \r\nmarine environments (Cragg et al"


id: 43d3acbb7f1eb5226ed24eff4bbb0f51
created_at: 2023-03-16 14:02:16
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", 2020). There is increasing evidence about the coverage and carbon content of macroalgal, planktonic \r\nand faunal taxa, but low agreement about their long-term carbon-storage potential and manageability (Alongi, 2018b; Wernberg and \r\nFilbee-Dexter, 2018; Lovelock and Duarte, 2019; Ortega et al., 2019; Pfister et al., 2019; Queiros et al., 2019; Filbee-Dexter et al., 2020a; \r\nGallagher, 2020; Mariani et al., 2020; Thorhaug et al., 2020; van Son et al., 2020; Bach et al., 2021; Bayley et al., 2021; Cavanagh et al., 2021; \r\nFrontier et al., 2021; Martin et al., 2021; Pedersen et al., 2021; Weigel and Pfister, 2021). This section focuses on the array of ecosystem \r\nservices and adaptation opportunities provided by vegetated coastal blue carbon ecosystems, where consensus and evidence are most \r\nabundant. Mitigation potential of blue carbon ecosystems is assessed with land-based mitigation options in WGIII AR6 Section 7.4."


id: 3c62009fbd0d3a03c4380a8f4f5d84b1
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content:
"Carbon storage and burial in mangroves, salt marshes and seagrass meadows (see Table Box 3.4.1) help regulate ocean and coastal carbon \r\ncycling and may contribute to nature-based mitigation, although regional estimates vary widely based on climatic and edaphic conditions \r\n(WGIII AR6 Section  7.4). In addition, coastal vegetated ecosystems provide substantial and interdependent regulating, provisioning \r\nand cultural ecosystem services. These services include: (a) disproportionately high biodiversity per unit area (Portner et al., 2021a); \r\n(b) abundant habitat (Section 3.5.5.1) and nurseries for aquatic, terrestrial, aerial and microbial species; (c) natural filtration of waste \r\nand stormwater runoff into the coastal ocean (Sections 3.5.5.3, 4.2.7; Cross-Chapter Box ILLNESS in Chapter 2); (d) coastal protection \r\n(Section 3.5.5.4; Ouyang et al., 2018; Quevedo et al., 2020); (e) food and natural materials (Sections 3.5.3, 3.5"


id: 6ebe777875d6865f887b0fd2507403e0
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"4); and (f) support for \r\ntourism, livelihoods and cultural activities (Section  3.5.6). Global estimates of services provided by coastal blue carbon ecosystems \r\ndepend on the quality of available mapping, which is currently best developed for mangroves (Macreadie et al., 2019), and improving for \r\nsalt marshes and seagrasses (McOwen et al., 2017; McKenzie et al., 2020; Young et al., 2021)."


id: 47e2dca37462660f4cba2539903662b8
created_at: 2023-03-16 14:02:16
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content:
"Coastal vegetated ecosystems are vulnerable to harm from multiple climate-induced and non-climate drivers, and together these have \r\nreduced wetland area globally (high confidence) (Section 3.4.2.5) and endangered the services provided by these ecosystems (high \r\nconfidence). Loss of coastal vegetated ecosystems changes biodiversity (Sections 3.5.2, 3.4.2.3-3.4.2.5; Numbere, 2019; Parreira et al., \r\n2021), increases risk of damage and erosion from SLR and storms (Sections 3.4.2.3-3.4.2.5; Cross-Chapter Box SLR in Chapter 3; Galeano \r\net al., 2017) and impacts provisioning (Sections 3.5.3-3.5.4; Li et al., 2018b; Maina et al., 2021). These changes also strongly determine \r\nthe quantity and longevity of blue carbon storage (high confidence) (Macreadie et al., 2019; Lovelock and Reef, 2020). Specific site \r\ncharacteristics and ecosystem responses to climate change will determine future local blue carbon storage or loss (high confidence) (see \r\nTable Box 3.4.2)"


id: 4984768f3166dec2340acf4e197bfeb
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"storage (Kelleway et al., 2016); however, this change in the dominant vegetation and associated faunal changes can modify carbon stocks \r\nand sequestration, as well as other ecosystem services (Martinetto et al., 2016; Kelleway et al., 2017; Smee et al., 2017; Macreadie et al., \r\n2019; Macy et al., 2019). Landward range expansion of mangroves, marshes and seagrass in response to gradual RSLR can enhance \r\ncarbon sequestration (Section 3.4.2.5; Cross-Chapter Box SLR in Chapter 3; Macreadie et al., 2019), but coastal squeeze can limit this \r\n(Phan et al., 2015; Schuerch et al., 2018) and RSLR can either submerge and bury or erode and release stored blue carbon (Section 3.4.2.5; \r\nMacreadie et al., 2019; Lovelock and Reef, 2020). Gains and losses of mangrove habitat area (and therefore carbon storage) projected for \r\nnations under RCP4.5 and RCP8"


id: 553d65e239fa072722d97dd270f1d258
created_at: 2023-03-16 14:02:16
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content:
"5 depend primarily on the combination of SLR rate, adaptation scenario (including coastal development) \r\nand island or continental status (Lovelock and Reef, 2020). The influence of warming, MHWs and acidification on seagrass meadows \r\n(Kendrick et al., 2019; Strydom et al., 2020), and associated coralligenous reefs (Zunino et al., 2019), suggests that future warming and \r\nespecially MHWs will cause more widespread loss of services from these ecosystems (Section 3.4.2.5). Loss of blue carbon ecosystems \r\nwill not only halt carbon storage but also release stored carbon: emissions after 2000 due to global mangrove deforestation have been \r\nestimated at 23.5-38.7 Tg Cyr-1 (Ouyang and Lee, 2020). Mitigation estimates for avoided conversion and restoration of coastal wetlands \r\nand the implications of the impacts of climate change are assessed in WGIII AR6 Section 7.4."


id: 7d30ffe907648ca81a5171cdd0a46235
created_at: 2023-03-16 14:02:16
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content:
"To date, initiatives aiming to restore coastal wetland ecosystems primarily address ecosystem characteristics other than carbon storage \r\n(Herr et al., 2017; de los Santos et al., 2019; Lovelock and Duarte, 2019; Friess et al., 2020a). But recovery of coastal vegetated ecosystems is \r\nexpected to bring back the full suite of ecosystem services they provide, not just carbon storage (medium confidence) (Marba et al., 2015a; \r\nBurden et al., 2019; Friess et al., 2020a), making coastal restoration a low-risk action that offers both adaptation and mitigation benefits \r\n(Steven et al., 2020; Gattuso et al., 2021). Successful restoration requires using appropriate plant species in suitable environmental settings \r\n(Wodehouse and Rayment, 2019; Friess et al., 2020a) with favourable geomorphology and biophysical conditions (Cameron et al., 2019; Ochoa\u0002Gomez et al., 2019) and considering social, economic, policy and operational constraints (Section 3.6.3.2"


id: 70858ff362594061b5e9a1e568baf4a
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"2; Cross-Chapter Box NATURAL in \r\nChapter 2), now and in the future (high confidence) (Duarte et al., 2020; Lovelock and Reef, 2020). Nevertheless, restored spaces may not \r\nstore carbon at rates equal to those of undisturbed spaces (Yang et al., 2020), and it may take decades to determine or achieve carbon-storage \r\noutcomes of restoration (Sasmito et al., 2019; Duarte et al., 2020; Oreska et al., 2020). Integration improves efforts to restore or conserve \r\ncoastal wetland ecosystems to accomplish both adaptation and mitigation outcomes (Steven et al., 2020). Government-led conservation of \r\nblue carbon ecosystems as part of national and subnational climate strategies (e.g., Friess et al., 2020a; Kelleway et al., 2020; Wedding et al., \r\n2021) benefits from coordination with private activities, such as incentivising conservation with payments for ecosystem services (Muenzel \r\nand Martino, 2018; Friess et al., 2020a)"


id: 709c7191a6ce6ab1f757ca8099491c91
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" Moreover, successful area-based protection measures consider both environmental and social issues \r\n(Section 3.6.3.2). Continued integration and alignment of policies at international to local levels (Section 3.6.5) will also support achieving \r\nthe adaptation and mitigation benefit of blue carbon spaces (Friess et al., 2020a; Steven et al., 2020; Wu et al., 2020a)."


id: 78fae4b625648ec6e86374cd53deaabd
created_at: 2023-03-16 14:02:16
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"Cultural services provided by ocean and coastal ecosystems help maintain \r\npsychological well-being, cultural development, human identities, \r\neducational opportunities and reserves that could support development \r\nof future goods or activities (Table 3.25). Most recent studies of ocean \r\nand coastal cultural services simply detail local benefits using replicable \r\nmethods (e.g., Drakou et al., 2018; Folkersen, 2018; Forster et al., 2019; \r\nLau et al., 2019; Pouso et al., 2019; Weitzman, 2019; Yang et al., 2019), \r\nfocusing on diverse ocean and coastal environments and ecosystems \r\n(Jobstvogt et al., 2014; Balzan et al., 2018; Drakou et al., 2018; Ingram \r\net al., 2018; Pouso et al., 2018; Zapata et al., 2018; Ghermandi et al., \r\n2019; Pouso et al., 2019; Tanner et al., 2019; Turner et al., 2019; Ortiz \r\nLinan and Vazquez Solis, 2021). Cultural ecosystem services may directly \r\nbenefit from marine development activities, such as marine aquaculture \r\n(e.g., Alleway et al"


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", 2018), and indirectly benefit from marine activities \r\nthat increase biodiversity (e.g., Causon and Gill, 2018). Cultural services \r\nare generally quantified using interviews and revealed-preference or \r\nstated-preference valuation (National Research Council, 2005; Sangha \r\net  al., 2019), but people often are especially reluctant to evaluate \r\ncultural ecosystem services in monetary terms, given the spiritual and \r\ncommunity linkages to these services (Oleson et al., 2018)."


id: eeb8bfb87c9da3703c30fcf6585b0ba2
created_at: 2023-03-16 14:02:16
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content:
"Observed disruption of ocean and coastal cultural services by climate \r\nimpacts, plus increasingly severe and widespread projected climate\u0002change impacts on ocean and coastal ecosystems, imply that the risk \r\nto cultural ecosystem services will remain constant or even increase \r\n(medium confidence) (Figure 3.22; Table 3.26). Recent studies assert \r\nthat cultural ecosystem services are at risk from climate change (high \r\nconfidence) (Singh et al., 2019a; Koenigstein, 2020). However, limited \r\nevidence and complex social-ecological interactions (e.g., Ingram et al., \r\n2018) challenge development of specific projections"


id: c2f0ce82499b7dbb6a2332556f2a2055
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" For instance, the \r\nlittle auk (Alle alle) in the North Water Polynya is traditionally harvested \r\nby Indigenous Inughuit for food and community-wide celebrations and \r\nseasonal activities, but harvests are threatened to an undetermined \r\ndegree as the seabird competes for food with recovering bowhead \r\nwhale (Balaena mysticetus) populations and northward range shifts \r\nof capelin (Mallotus villosus) due to warming (Mosbech et al., 2018). \r\nSection 3.6 assesses the cultural implications of implemented human \r\nadaptations."


id: 9bac1fa5256ce8da1f86adad161c41c1
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"Additional evidence since previous assessments (Table 3.26) confirms \r\nthat climate-change impacts on ocean and coastal cultural ecosystem \r\nservices have already disrupted people's place-based emotional \r\nattachments and cultural activities (limited evidence, high agreement) \r\n(Figure  3.22). Bleaching and mortality of corals in the Great Barrier \r\nReef have induced measurable 'reef grief', a type of solastalgia, among \r\nreef visitors and researchers (Conroy, 2019; Curnock et  al., 2019; \r\nMarshall et al., 2019). The mental health of people in Tuvalu (Gibson \r\net  al., 2020), Alaska (Allen, 2020) and Honduras (Kent and Brondo, \r\n2020) have suffered from both the experience of climate impacts \r\non ocean and coastal ecosystems (e.g., SLR and changes in fisheries \r\nand wildlife), and the anticipation of more in the future. The climate\u0002associated MHWs and harmful algal bloom events in 2014-2016 in \r\nthe US Pacific Northwest (Moore et al"


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", 2019) prevented seasonal razor \r\nclam harvests culturally important to Indigenous Peoples and the local \r\ncommunity (Section 3.5.5.3; Crosman et al., 2019). Sea level rise and \r\nstorm-driven coastal erosion endanger coastal archaeological and \r\nheritage sites around the world (very high confidence) (Hoque and \r\nHoque, 2008; Carmichael et al., 2018; Reimann et al., 2018; Elliott and \r\nWilliams, 2019; Ravanelli et  al., 2019; Anzidei et  al., 2020; Chemeli \r\net al., 2020; Garcia Sanchez et al., 2020; Harkin et al., 2020; Hil, 2020; \r\nRivera-Collazo, 2020)."


id: e37bbe3475dc0115e0d42d249c484f45
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"Human adaptation comprises an array of measures (adaptation options; \r\nIPCC, 2014a) that modulate harm or exploit opportunities from climate \r\nchange (Section  1.2.1.3). Adaptation options that respond to key \r\nocean and coastal risks (Section 3.4) focus on individuals, livelihoods \r\nand economic sectors that benefit from ocean and coastal ecosystem \r\nservices (Section 3.5). AR5 concluded that local adaptation measures \r\nwould not alone be enough to offset global effects of increased \r\nclimate change on marine and coastal ecosystems, and that mitigation \r\nof emissions would also be necessary (high confidence) (Table 3.27; \r\nPortner et  al., 2014; Oppenheimer et  al., 2019). SROCC assessed \r\nthat ecosystem-based adaptation, including MPAs (high confidence) \r\n(Bindoff et  al"


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", 2019a) and adaptive management, are effective to \r\nreduce climate-change impacts (IPCC, 2018; IPCC, 2019b), but that \r\nexisting marine governance is insufficient to provide an effective \r\nadaptation response in the marine ecosystem (high confidence) (IPCC, \r\n2019c)."


id: 4cfe6b3faa8900e2355d9a464687f402
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"Increasing evidence shows that an effective solution portfolio includes \r\nsocial and institutional adaptation (Figure 3.23, top; Table 3.28). Social \r\nadaptation to climate change is already occurring, as people use \r\nstrategies ranging from accommodating change, to coping, adapting \r\nand transforming their livelihoods (Bene and Doyen, 2018; Fedele \r\net al., 2019; Galappaththi et al., 2019; Barnes et al., 2020; Ojea et al., \r\n2020; Green et al., 2021c). Although management and institutions have \r\nmajor roles in adaptation (Gaines et al., 2018; Barange, 2019), marine \r\ngovernance is impeded by increasing numbers of often-competing \r\nusers and uses (Boyes and Elliott, 2014); sector-led, fragmented efforts \r\n(Nunan et al., 2020); and a legal framework less clear than those on \r\nland (Crespo et al., 2019; Guggisberg, 2019)"


id: ecb2a8cbe0043cb696fdc63fe8fc254
created_at: 2023-03-16 14:02:16
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" Future social responses \r\ndepend on warming levels and on the institutional, socioeconomic \r\nand cultural constructs that allow or limit livelihood changes (medium \r\nconfidence) (Chapter 18; Galappaththi et al., 2019; Ford et al., 2020; \r\nGreen et  al., 2021c). Both social and institutional transformations \r\nare needed to change the structures of power, culture, politics and/\r\nor identity associated with marine ecosystems (Section 1.5.2; Wilson \r\net  al., 2020b). Ideally, institutional and social adaptation will work \r\ntogether to sustain knowledge systems and education, enhance \r\nparticipation and social inclusion, facilitate livelihood support and \r\ntransformational change of dependent coastal communities, provide \r\neconomic and financial instruments, and include polycentric and multi\u0002level governance of transboundary management (Fedele et al., 2019; \r\nFulton et al., 2019)."


id: 92afc17c038429f5880c6ccf79c394dc
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"The vulnerability of communities to losses in marine ecosystem services varies within and among communities. \r\nTourists seeking to replace lost cultural services can adapt by engaging in the activity elsewhere. But communities \r\nwho depend on tourism for income or who have strong cultural identity linked to the ocean have a more \r\ndifficult time. Furthermore, climate-change impacts exacerbate existing inequalities already experienced by some \r\ncommunities, including Indigenous Peoples, Pacific Island countries and territories and marginalised peoples, such \r\nas migrants and women in fisheries and mariculture. These inequities increase the risk to their fundamental human \r\nrights by disrupting livelihoods and food security, while leading to loss of social, economic and cultural rights"


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" \r\nThese maladaptive outcomes can be avoided by securing tenure and access rights to resources and territories for \r\nall people depending on the ocean, and by supporting decision-making processes that are just, participatory and \r\nequitable."


id: dd7b05434051c6e5125d2f86ec4ccb5b
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"Engineering and technology support marine and coastal adaptation \r\n(Table  3.29). Built infrastructure includes engineered solutions that \r\nprotect, accommodate or relocate coastal assets using hard engineering, \r\nlike seawalls, and soft engineering, such as beach and shore nourishment \r\n(Cross-Chapter Box SLR in Chapter 3). Technological tools include early\u0002warning systems for extreme events (Bindoff et al., 2019a; Collins et al., \r\n2019a), improved forecast and hindcast models (Winter et  al., 2020; \r\nDavidson et  al., 2021; Spillman and Smith, 2021) and environmental \r\nmonitoring (Claudet et  al., 2020a; Wilson et  al., 2020a; Melbourne\u0002Thomas et al., 2021) that support informed decision making (Tommasi \r\net  al., 2017; Rilov et  al., 2020; A. Maureaud et  al., 2021). Emerging \r\nadaptation technologies, such as habitat development, active restoration \r\nand assisted evolution (Bostrom-Einarsson et al., 2020; Kleypas et al"


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", \r\n2021), intend to accelerate recovery of damaged ecosystems and \r\npromote ecological adaptation to climate change (Jones et al., 2018a; \r\nBostrom-Einarsson et al., 2020; Kleypas et al., 2021)."


id: 6c09e0d7042f9b25762697371104d476
created_at: 2023-03-16 14:02:16
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"The ocean and coastal adaptation portfolio (Figure  3.23) also \r\nincludes marine and coastal NbS (Table 3.30). NbS that contribute \r\nto climate adaptation, also known as ecosystem-based adaptations \r\n(EBA), are cross-cutting actions that harness ecosystem functions to \r\nrestore, protect and sustainably manage marine ecosystems facing \r\nclimate-change impacts, while also benefiting social systems and \r\nhuman security (Abelson et  al., 2015; Barkdull and Harris, 2019) \r\nand supporting biodiversity (high confidence) (Annex II: Glossary; \r\nCross-Chapter  Box  NATURAL in Chapter  2; Seddon et  al., 2021). \r\nNbS are expected to contribute to global adaptation and mitigation \r\ngoals (high confidence) (Beck et  al., 2018; Cooley et  al., 2019; \r\nHoegh-Guldberg et al., 2019b; Menendez et al., 2020; Morris et al., \r\n2020a) by protecting coastal environments from SLR and storms \r\n(Cross-Chapter  Box  SLR; Reguero et  al., 2018), and by storing \r\nsubstantial quantities of carbon (Sections  3.4.2"


id: e4d92c65e2ae4dc53ee72ad4a50bd354
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"Since SROCC, coastal adaptation using NbS, like restoration of coastal \r\nvegetation, has advanced substantially (Cohen-Shacham et al., 2019; \r\nKuhl et al., 2020; Kumar et al., 2020; Morris et al., 2020a). Field and \r\nmodelling studies confirm that wetland restoration and preservation \r\nare key actions to restore coastal protection and reduce community \r\nvulnerability to flooding (very high confidence) (see also Section 3.6; \r\nChapter  15; Cross-Chapter  Box  SLR in Chapter  3; Jones et  al., 2020; \r\nMenendez et al., 2020; Van Coppenolle and Temmerman, 2020), while \r\nmaintaining coastal ecosystem services (Section  3.5). Restoring coral \r\nreefs, oyster reefs and mangroves (Section  3.6.2.1) and protecting \r\nmacrophyte meadows dissipates wave energy (Section  3.4.2.1; Yates \r\net  al., 2017; Beck et  al., 2018; Wiberg et  al., 2019; Menendez et  al"


id: a021a583b4eeb2ed9c6f75335f1d40c7
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", \r\n2020), accretes sediment and elevate shorelines, which reduces \r\nexposure to waves and storm surges, and offsets erosional losses \r\n(medium confidence) (Kench and Mann, 2017; Pomeroy et  al., 2018; \r\nDasgupta et al., 2019; James et al., 2019; Morris et al., 2019; David and \r\nSchlurmann, 2020; Masselink et al., 2020). However, irreversible regime \r\nshifts in ocean ecosystems due to SLR and extreme events, such as MHWs, \r\ncan limit or compromise restoration in the long term (high confidence) \r\n(Section 3.4.3.3.3; Cross-Chapter Box SLR in Chapter 3; Marzloff et al., \r\n2016; Johnson et  al., 2017a). Under all warming scenarios, coastal \r\nwetlands will be impacted by warming and MHWs (Sections 3.2.2.1, \r\n3.2.4.5; Cross-Chapter  Box  9.1 in WGI Chapter  9; Fox-Kemper et  al., \r\n2021), while also being pressed inland by RSLR (Section 3.4.2.5; Cross\u0002Chapter Box SLR in Chapter 3)"


id: be9deacc236ff6b2ac971e89c8ee00a1
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" Therefore, restoration and conservation \r\nare more successful when non-climate drivers are also minimised (high \r\nconfidence) (Brodie et al., 2020; Duarte et al., 2020; Liu et al., 2021)."


id: aa3d9fbfceed46baa0fa23c15dcb3d74
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"Mobility allows fishing fleets and fishers to adapt to shifts in marine \r\nspecies distributions (high agreement) (Sections 3.4.3.1, 3.5.3; Peck \r\nand Pinnegar, 2018; Pinsky et al., 2018; Frazao Santos et al., 2020) \r\nbut with limits and unintended consequences (Pinsky and Fogarty, \r\n2012; Bell et  al., 2021). Diversification of target species, harvest \r\ntactics and employment sectors, including transitions from fisheries \r\nto mariculture and ecotourism, allows some fishers to accommodate \r\nsome impacts on their livelihoods (Miller et al., 2018; Robinson et al., \r\n2020; Gonzalez-Mon et  al., 2021). Technology and infrastructure \r\nadaptations can improve marine harvest efficiency, reduce risk and \r\nsupport resource management goals (Friedman et al., 2020; Bell et al., \r\n2021; Melbourne-Thomas et al., 2021), but their ability to overcome \r\nclimate-change impacts remains uncertain (Bell et  al., 2020)"


id: 922e3cf4fe54aba23adb0c55d57450b9
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" \r\nImproving capacity to predict anomalous conditions in coastal and \r\nmarine ecosystems (Jacox et al., 2019; Holbrook et al., 2020; Jacox \r\net al., 2020), storm-driven flooding in reef-lined coasts (Scott et al., \r\n2020; Winter et  al., 2020) and fisheries stocks (Payne et  al., 2017; \r\nTommasi et  al., 2017; Muhling et  al., 2018) can improve forecasts \r\nof coastal and marine resources; these can enhance sustainability \r\nof wild-capture fisheries under climate change (high confidence) \r\n(Blanchard et  al., 2017; Tommasi et  al., 2017; Pinsky et  al., 2020a; \r\nBell et  al., 2021). Limiting overexploitation is the central goal of \r\nfishery management, and it very likely benefits fisheries adaptation \r\nto climate change (Burden and Fujita, 2019; Free et al., 2019; Sumaila "


id: b9b5d8d501d9ff8bf0e261004741bc94
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"The rate of global mean SLR was 1.35 mm yr-1 (0.78-1.92 mm yr-1, very likely range) during 1901-1990, faster than during any century \r\nin at least 3000 years (high confidence) (WGI AR6 Chapter 9; Stanley and Warne, 1994; Woodroffe et al., 2016; Fox-Kemper et al., 2021). \r\nGlobal mean SLR has accelerated to 3.25 mm yr-1 (2.88-3.61 mm yr-1, very likely range) during 1993-2018 (high confidence). Extreme \r\nsea levels have increased consistently across most regions (WGI AR6 Chapter 9; Fox-Kemper et al., 2021). The largest observed changes \r\nin coastal ecosystems are being caused by the concurrence of human activities, waves, current-induced sediment transport and extreme \r\nstorm events (medium confidence) (Chapters 3, 15, 16; Takayabu et al., 2015; Mentaschi et al., 2018; Duvat, 2019; Murray et al., 2019; \r\nOppenheimer et al., 2019)"


id: 3187851ca5c06db79619a2273a5251ea
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" Early impacts of accelerating SLR detected at sheltered or subsiding coasts include chronic flooding at high tides, \r\nwetland salinisation and ecosystem transitions, increased erosion and coastal flood damage (Chapters 3, 11, 13-16; WGI AR6 Chapter 9; \r\nSweet and Park, 2014; Moftakhari et al., 2015; Nunn et al., 2017; Oppenheimer et al., 2019; Sharples et al., 2020; Fox-Kemper et al., 2021; \r\nStrauss et al., 2021). The exposure of many coastal populations and ecosystems to SLR is high: economic development is disproportionately \r\nconcentrated in and around coastal cities and settlements (virtually certain) (Chapters 3, 9-15; Cross-Chapter Papers 2, 4)."


id: ab4f92216f40699154905a85b44d81e9
created_at: 2023-03-16 14:02:16
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"Risks from SLR are very likely to increase by one order of magnitude well before 2100 without adaptation and mitigation action as \r\nagreed by parties to the Paris Agreement (very high confidence). Global mean SLR is likely to continue accelerating under SSP1-2.6 and \r\nmore strongly forced scenarios (Figure BoxSLR1; WGI AR6 Chapter 9; Oppenheimer et al., 2019; Fox-Kemper et al., 2021), increasing the \r\nrisk of chronic coastal flooding at high tide, serious flooding during extreme events such as swells, storms and hurricanes, and erosion, \r\nand coastal ecosystem losses across many low-lying and erodible coasts (very high confidence) (Chapters 3, 9-15; Cross-Chapter Paper \r\n2; Hinkel et al., 2014; McLachlan and Defeo, 2018; Kulp and Strauss, 2019; Vousdoukas et al., 2020b). The compounding of rainfall, river \r\nflooding, rising water tables, coastal surges and waves are projected to exacerbate SLR impacts on low-lying areas and rivers further \r\ninland (Chapters 4, 11-15; Bevacqua et al"


id: 6994cf8a86cfee1f6021badba60c7e53
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"There is high confidence that coastal risks will increase by at least one order of magnitude over the 21st century due to committed SLR \r\n(Hinkel et al., 2013; Hinkel et al., 2014; IPCC, 2019b). Exposure of population and economic assets to coastal hazards is projected to \r\nincrease over the next decades, particularly in coastal regions with fast-growing populations in Africa, Southeast Asia and Small Islands \r\n(medium evidence) (Chapters 9-15; Cross-Chapter Papers 2, 4; Neumann et al., 2015; Jones and O'Neill, 2016; Merkens et al., 2016; \r\nMerkens et al., 2018; Rasmussen et al., 2020). For RCP8.5, 2.5-9% of the global population and 12-20% of the global gross domestic \r\nproduct is projected to be exposed to coastal flooding by 2100 (Kulp and Strauss, 2019; Kirezci et al., 2020; Rohmer et al., 2021). Above \r\n3degC global warming levels (GWL) and with low adaptation, SLR may cause disruptions to ports and coastal infrastructure (Camus et al., \r\n2019; Christodoulou et al"


id: b47e3e0c593005190d19ac6cdde01384
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", 2019; Verschuur et al., 2020; Yesudian and Dawson, 2021), which in turn may cascade and amplify across \r\nsectors and regions, generating impacts to financial systems (Chapters 11, 13; Mandel et al., 2021). Depending on the hydrogeological \r\ncontext, SLR causes salinisation of groundwater, estuaries, wetlands and soils, adding constraints to water management and livelihoods \r\nin agriculture sectors, for example, in deltas (Chapters 9, 15; Cross-Chapter Paper 4; Oppenheimer et al., 2019; Nicholls et al., 2020)."


id: a10633c3d60b1e939d627588b62bc992
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"Under a high-emissions, low-likelihood/high-impact scenario, where low confidence ice-sheet mass loss occurs, global mean SLR could \r\nexceed the likely range by more than one additional metre in 2100 (Figure BoxSLR1b; Cross-Chapter Box DEEP in Chapter 17; WGI AR6 \r\nTechnical Summary and Chapter 9; Arias et al., 2021; Fox-Kemper et al., 2021). This is a reason for concern given that rapid SLR after the \r\nlast glacial-interglacial transition caused a drowning of coral reefs (high confidence) (Camoin and Webster, 2015; Sanborn et al., 2017; \r\nWebster et  al., 2018), extensive loss of coastal land and islands, habitats and associated biodiversity (high confidence) (AR6 WGI \r\nChapter 9; Fruergaard et al., 2015; Fernandez-Palacios et al., 2016; Hamilton et al., 2019; Helfensdorfer et al., 2019; Kane and Fletcher, \r\n2020; Fox-Kemper et al"


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", 2021), and triggered Neolithic migrations in Europe and Australia (medium confidence) (Cross-Chapter Box PALEO \r\nin Chapter 1; Turney and Brown, 2007; Brisset et al., 2018; Williams et al., 2018)."


id: fc8b05414b95ab6d262d8002712373ff
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"Risks can be anticipated, planned and decided upon, and adaptation interventions can be implemented over the coming decades \r\nconsidering their often long lead- and lifetimes, irrespective of the large uncertainty about SLR beyond 2050 (high confidence) \r\n(Figure  BoxSLR1; Cross-Chapter  Box  DEEP in Chapter  17; Cross-Chapter  Paper 2; Chapters  11, 13; Haasnoot et  al., 2018; Stephens \r\net al., 2018; Stammer et al., 2019). Adaptation capacity and governance to manage risks from projected SLR typically require decades \r\nto implement and institutionalise (high confidence) (Chapters 11, 13; Haasnoot et al., 2021). Without considering both short- and long\u0002term adaptation needs, including beyond 2100, communities are increasingly confronted with a shrinking solution space, and adverse \r\nconsequences are disproportionately borne by exposed and socially vulnerable people (Chapters 1, 8)"


id: 62eef5e4994ef10512e54deccc8ee85c
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" Sea level rise is likely to compound \r\nsocial conflict in some settings (high confidence) (Oppenheimer et al., 2019)."


id: 7787993b00200c57948b5808ebd09905
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"Coastal impacts of SLR can be avoided by preventing new development in exposed coastal locations (Chapters 3, 9-15; Cross-Chapter Paper \r\n2; Doberstein et al., 2019; Oppenheimer et al., 2019). For existing developments, a range of near-term adaptation options exists, including: \r\n(a) engineered, sediment- or ecosystem-based protection; (b) accommodation and land-use planning, to reduce the vulnerability of people \r\nand infrastructure; (c) advance through, for example, land reclamation; and (d) retreat through planned relocation or displacements and \r\nmigrations due to SLR (Chapters 9-15; Cross-Chapter Paper 2; Oppenheimer et al., 2019). Only avoidance and relocation can remove \r\ncoastal risks for the coming decades, while other measures only delay impacts for a time, have increasing residual risk or perpetuate risk \r\nand create ongoing legacy effects and virtually certain property and ecosystem losses (high confidence) (Cross-Chapter Paper 2; Siders \r\net al., 2019)"


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" Large-scale relocation has immense cultural, political, social and economic costs, and equity implications, which can be \r\nreduced by fast implementation of climate mitigation and adaptation policies (Chapter 8; Cross-Chapter Paper 2; Gibbs, 2015; Haasnoot \r\net al., 2021). While relocation may currently appear socially unacceptable, economically inefficient or technically infeasible today (Lincke \r\nand Hinkel, 2021), it becomes the only feasible option as protection costs become unaffordable and the limits to accommodation become \r\nobvious (Chapters 11, 13, 15; Hino et al., 2017; Siders et al., 2019; Strauss et al., 2021). Effective responses to rising sea level involve \r\nlocally applicable combinations of decision analysis, land-use planning, public participation and conflict resolution approaches; together \r\nthese can anticipate change and help to chart adaptation pathways, over time addressing the governance challenges due to rising sea \r\nlevel (high confidence) (Oppenheimer et al"


id: e09c7f2d8ea212b74feb048b64cef6b7
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"Figure Cross-Chapter BoxSLR.1 |  The challenge of coastal adaptation in the era of sea level rise (SLR): (a) typical time scales for the planning, implementation \r\n(grey triangles) and operational lifetime of current coastal risk-management measures (blue bars); (b) global sea level projections, which are representative of relative SLR \r\nprojected for 60-70% of global shorelines, within +-20% errors (WGI AR6 Chapter 9; Fox-Kemper et al., 2021); (c) frequency of illustrative adaptation decisions to +0.5 m \r\nof SLR under different SSP-RCP scenarios. In response to accelerated SLR, adaptation either occurs earlier and faster, or accounts for higher amounts of SLR (e.g., to +1 m \r\ninstead of to +0.5 m). Adaptation to +0.5 m from today's sea levels have a lifetime of 90 years for SSP1-2.6, but lifetime is reduced to 60 years for SSP5-8.5 and 30 years \r\nfor a high-end scenario involving low confidence processes. Adaptations to +0"


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"5 m are comparable to, for example, the Thames Barrier in the United Kingdom or the Delta \r\nWorks in the Netherlands, which primarily had an intended lifetime of 100-200 years. Adaptation measures to +0.2 m may include nourishment or wetland or setback zones."


id: 526b630de2e0298be2f50df0a4844754
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"There is increasing evidence that current governance and institutional arrangements are unable to address the escalating risks in low\u0002lying coastal areas worldwide (high confidence). Barriers to adaptation, such as decision making driven by short-term thinking or vested \r\ninterests, funding limitations and inadequate financial policies and insurance, can be addressed equitably and sustainably through \r\nimplementation of suites of adaptation options and pathways (Chapters  11, 13, 17-18; Cross-Chapter  Paper 2). Improved coastal \r\nadaptation governance can be supported by approaches that consider changing risks over time, such as 'dynamic adaptation pathways' \r\nplanning (Chapters  11, 13, 18; Cross-Chapter  Box  DEEP in Chapter  17). Integrated coastal zone management and land-use and \r\ninfrastructure planning are starting to consider SLR by, for example, monitoring early signals (Haasnoot et al., 2018; Stephens et al., 2018; \r\nKool et al"


id: afe9a7e1b3321c314988cb1340ac4910
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", 2020), updating sea level projections (Stephens et al., 2017; Hinkel et al., 2019; Kopp et al., 2019; Stammer et al., 2019), \r\nconsidering uncertainties of sea level projections and coastal impacts (e.g., Stephens et al., 2017; Jevrejeva et al., 2019; Rohmer et al., \r\n2019), as well as engaging with communities, practitioners and scientists, recognising the values of current and future generations (e.g., \r\nNicholls et al., 2014; Buchanan et al., 2016b). While there is high agreement that the majority of adaptation needs are not met yet, there \r\nis robust evidence of SLR increasingly being considered in coastal adaptation decision making and being embedded in national and local \r\nguidance and regulations (Nicholls et al., 2014; Le Cozannet et al., 2017; Lawrence et al., 2018; Kopp et al., 2019; McEvoy et al., 2021)."


id: 58b6878e9be92645bb0a81fb34eb3996
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"and Tai, 2020). Conventional tools include catch and size limits, spatial \r\nmanagement and adaptive management. Ecosystem-based fisheries \r\nmanagement outperforms single-species management (Fulton et al., \r\n2019), is widely legislated (Bryndum-Buchholz et  al., 2021) and \r\ncan reduce climate impacts in fisheries in the near-term, especially \r\nunder low-emission scenarios (Karp et  al., 2019; Holsman et  al., \r\n2020). Transboundary agreements on shifting fisheries will reduce \r\nthe risk of overharvesting (medium confidence) (Gaines et al., 2018). \r\nPermits tradable across political boundaries could also address this \r\nchallenge, but limited evidence is available regarding their efficacy \r\n(Cross-Chapter  Box  MOVING SPECIES in Chapter  5; Pinsky et  al., \r\n2018). Climate-smart conservation (Section  3.6.32.1) under the \r\nnegotiations on areas beyond national jurisdiction (ABNJ) (Pinsky \r\net al., 2018; Tittensor et al., 2019; Frazao Santos et al"


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", 2020), and in \r\nthe Convention on Biological Diversity (CBD) areas designed as other \r\neffective area-based conservation measures (OECMs) (Tittensor et al., \r\n2019), provide further benefits. Despite the potential for adaptive \r\nmanagement to achieve sustainable fisheries, outcomes will very \r\nlikely be inequitable (Gaines et al., 2018; Lam et al., 2020), with lower\u0002income countries suffering the greater biomass and economic losses, \r\nincreasing inequalities, especially under higher-emission scenarios \r\n(high confidence) (Boyce et  al., 2020). Flexible and polycentric \r\ngovernance approaches have facilitated some short-term successes in \r\nachieving equitable, sustainable fisheries practices, but these may be \r\nchallenging to implement where other governance systems, especially \r\nhierarchical systems, are well established (Cvitanovic et al., 2018; Bell \r\net al., 2020)."


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"Marine ecotourism, integrating conservation, education and provision \r\nof benefits to local communities (Donohoe and Needham, 2006) can \r\nprovide significant economic benefits (Wabnitz, 2019) and is among \r\nthe most common livelihood alternatives to support both marine \r\nconservation and climate-change adaptation (Kutzner, 2019; Pham, \r\n2020; Prasetyo et al., 2020). Ecotourism can enhance social and political \r\nwill for marine conservation (Cisneros-Montemayor and Sumaila, \r\n2014) and facilitates integration of local and Indigenous Peoples in \r\nemployment, ownership and industry governance. The community \r\nof Cabo Pulmo, Mexico, self-imposed an MPA and replaced fishing \r\nwith ecotourism, which now generates millions of USD yr-1, sustains \r\nlocally owned and operated tour companies and has increased some \r\nfish populations tenfold (Knowlton, 2020)"


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" In Misool, Indonesia, local \r\necotourism incorporates IK by including local communities' preferences \r\nand sustainable resource use (Prasetyo et al., 2020)."


id: b988893f0683c6e473d8de6402c27243
created_at: 2023-03-16 14:02:16
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content:
"and NbS (Section 3.6.2.3). Seafood quality and safety are decreasing \r\ndue to climate-driven increases in marine-borne diseases (Cross\u0002Chapter Box ILLNESS in Chapter 2), toxic HABs or toxin bioaccumulation \r\n(high agreement) (Karagas et al., 2012; Krabbenhoft and Sunderland, \r\n2013; Rafaj et  al., 2013; Curtis et  al., 2019; Schartup et  al., 2019; \r\nThackray and Sunderland, 2019). Future exposure to seafood-borne \r\ncontaminants also depends partly on consumers' seafood preferences \r\n(Elsayed et  al., 2020) and seafood supply (Sunderland et  al., 2018). \r\nReducing this risk by decreasing seafood consumption increases the risk \r\nof eating less nutritious foods, and loss of cultural practices (Chapter 5; \r\nCross-Chapter Box MOVING SPECIES in Chapter 5; Donatuto et al., 2011; \r\nBindoff et  al., 2019a)"


id: 2cb83ba413d278b74baff203b7b570c3
created_at: 2023-03-16 14:02:16
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content:
" Models incorporating high-resolution satellite \r\nimages, field survey data, meteorological observations and historical \r\nrecords can provide early-warning forecasts of HABs or conditions that \r\nfavour microbial pathogen outbreaks (Cross-Chapter  Box  ILLNESS in \r\nChapter  2; Semenza et  al., 2017; Franks, 2018; Hattenrath-Lehmann \r\net al., 2018; Borbor-Cordova et al., 2019; Davis et al., 2019; Campbell \r\net  al., 2020a; Davidson et  al., 2021). Forecasts facilitate preventive \r\npublic health measures (World Health Organisation and United Nations \r\nChildren's Fund, 2017), or seafood harvest guidance (Maguire et  al., \r\n2016; Leadbetter et al., 2018; Anderson et al., 2019; Bolin et al., 2021), \r\nreducing risks of disease outbreaks, waste and contaminated seafood \r\nentering the market (medium confidence) (Cross-Chapter Box ILLNESS \r\nin Chapter  2; Nichols et  al., 2018)"


id: 64b331dcf0fd12a42c227d3e01cea509
created_at: 2023-03-16 14:02:16
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content:
" Monitoring of water quality and \r\nseafood safety (Cross-Chapter Box ILLNESS in Chapter 2), paired with \r\neffective public communication and education (Ekstrom et al., 2020), \r\ninform individual and local adaptations, including use of (a) personal \r\nprotective equipment, (b) seafood selection and preparation (Elsayed \r\net al., 2020; Froelich and Daines, 2020; Fielding et al., 2021), (c) income \r\ndiversification (Section  3.6.2.1; Moore et  al., 2020b), (d)  public \r\neducation (Borbor-Cordova et al., 2019) or (e) community-level actions \r\nto decrease risk from coastal aquifer and soil salinisation (Slama et al., \r\n2020; Mastrocicco and Colombani, 2021), HAB toxins (Ekstrom et al., \r\n2020) and other contaminants (e.g., methylmercury, metals, persistent \r\norganic pollutants) in seafood (Chan et al., 2021). A full assessment of \r\nclimate-change impacts on human health is found in Chapter 7 and \r\nCross-Chapter Box ILLNESS in Chapter 2."


id: b4ac6d531d5874032e4904cb628b86a1
created_at: 2023-03-16 14:02:16
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"Increased maritime transport and cruise-ship tourism in the Arctic are \r\nalready impacting local and Indigenous Peoples, revealing conflicts \r\nover the uses of the ocean and the governance needed to support local \r\npeople and a sustainable blue economy (high confidence) (Debortoli \r\net al., 2019; Palma et al., 2019; Berman et al., 2020; Dundas et al., 2020). \r\nWhile shipping and its associated environmental impacts are projected \r\nto grow (Palma et al., 2019; Dawson et al., 2020), adaptation efforts \r\nare only at the planning stage (Debortoli et al., 2019). Increased Arctic \r\ntraffic due to ice loss can benefit trade, transportation and tourism \r\n(medium confidence), but will also affect Arctic marine ecosystems \r\nand livelihoods (high confidence) (Palma et al., 2019; Dawson et al., \r\n2020). Increasing search-and-rescue activities (Ford and Clark, 2019) \r\nreveal capacity gaps to support future demands (Ford and Clark, 2019; \r\nPalma et al., 2019)"


id: dd15dd0126c18df55c95a943a2765a6
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content:
" The Low-Impact Shipping Corridors initiative has \r\nbeen developed as an adaptation strategy in the Arctic, although with \r\nlimited inclusion of IKLK (Dawson et al., 2020)."


id: 1bba85edb12eafc2a33ccee00ab6a53a
created_at: 2023-03-16 14:02:16
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content:
"Relative SLR and the increased frequency and severity of storms \r\nare already affecting port activity, infrastructure and supply chains, \r\nsometimes disrupting trade and transport (Monios and Wilmsmeier, \r\n2020), but these hazards are not systematically incorporated into \r\nadaptation planning (medium evidence) (Monios and Wilmsmeier, \r\n2020; O'Keeffe et  al., 2020). Climate-change impacts that increase \r\nfood insecurity, income loss and poverty can exacerbate maritime \r\ncriminal activity, including illegal fishing, drug trafficking or piracy \r\n(medium evidence) (Germond and Mazaris, 2019). A transformational \r\nadaptation approach to address climate impacts on maritime activities \r\nand increase security (Germond and Mazaris, 2019) would relocate \r\nports, change centres of demand, reduce shipping distances or shorten \r\nsupply chains (medium agreement) (Walsh et al"


id: 295a9f48bdbf28df3e82b0d24630b89d
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", 2019; Monios and \r\nWilmsmeier, 2020) as well as decrease marginalisation of vulnerable \r\ngroups, develop polycentric governance systems and eliminate \r\nmaladaptive environmental policies and resource loss (Belhabib et al., \r\n2020; O'Keeffe et al., 2020)."


id: 6430956f9d59047c6141c088d92d064e
created_at: 2023-03-16 14:02:16
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"underscores the urgent need to pursue biodiversity, ecosystem\u0002service provision and climate-adaptation goals simultaneously, while \r\nacknowledging inherent trade-offs (Claudet et al., 2020a; Sala et al., \r\n2021). Frameworks to create 'climate-smart' MPAs (Tittensor et  al., \r\n2019) generally include: (a) defining conservation goals that embrace \r\nresource vulnerabilities and co-occurring hazards; (b)  carefully \r\nselecting adaptation strategies that include IKLK while respecting \r\nIndigenous rights and accommodating human behaviour (Kikiloi et al., \r\n2017; Thomas, 2018; Yates et  al., 2019; Failler et  al., 2020; Wilson \r\net al., 2020a; Croke, 2021; Reimer et al., 2021; Vijayaraghavan, 2021); \r\n(c)  developing protection that is appropriate for all ocean depths \r\n(Brito-Morales et al., 2018; Frazao Santos et al., 2020; Wilson et al., \r\n2020a), especially considering climate velocity (Arafeh-Dalmau et al"


id: 9c0e0914adfb93ea861d19674d88a6bf
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", \r\n2021); (d) using dynamic national and international management tools \r\nto accommodate extreme events or species distribution shifts (Gaines \r\net al., 2018; Pinsky et al., 2018; Bindoff et al., 2019a; Scheffers and \r\nPecl, 2019; Tittensor et al., 2019; Cashion et al., 2020; Crespo et al., \r\n2020; Frazao Santos et al., 2020; Maxwell et al., 2020b), which could \r\nbuild on dynamic regulations already in place for fishing or ship strikes \r\n(Maxwell et  al., 2020b); and (e)  seeking to increase connectivity \r\n(Wilson et al., 2020a), using genomic or multi-species model insights \r\n(Xuereb et al., 2020; Friesen et al., 2021; Lima et al., 2021)."


id: 5ec11001b828f409b8f7c2e028607259
created_at: 2023-03-16 14:02:16
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vector_id: 12448
content:
"Figure  3.26; Bates et  al., 2014; Lubchenco and Grorud-Colvert, 2015; \r\nGattuso et  al., 2018) because they alleviate non-climate drivers and \r\npromote biodiversity (i.e., 'managed resilience hypothesis') (Bruno \r\net  al., 2019; Maestro et  al., 2019; Cinner et  al., 2020). Current MPAs \r\noffer conservation benefits such as increases in biomass and diversity \r\nof habitats, populations and communities (high confidence) (Pendleton \r\net al., 2018; Bates et al., 2019; Stevenson et al., 2020; Lenihan et al., 2021; \r\nOhayon et al., 2021), and these benefits may last after some (possibly \r\nclimate-enhanced) disturbances (e.g., tropical cyclones) (McClure et al., \r\n2020). But current MPAs do not provide resilience against observed \r\nwarming and heatwaves in tropical-to-temperate ecosystems (medium \r\nconfidence) (Bates et al., 2019; Bruno et al., 2019; Freedman et al., 2020; \r\nGraham et al., 2020; Rilov et al., 2020)"


id: b33e0a088ffb0d38cdde890055909d3b
created_at: 2023-03-16 14:02:16
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vector_id: 25714
content:
" There is robust evidence that \r\nprocesses around MPA design and implementation strongly influence \r\nwhether outcomes are beneficial or harmful for adjacent human \r\ncommunities (McNeill et al., 2018; Zupan et al., 2018; Ban et al., 2019)."


id: f7f6aebbfd798e253d2554a78da54b21
created_at: 2023-03-16 14:02:16
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"Current placement and extent of MPAs will not provide substantial \r\nprotections against projected climate change past 2050 (high \r\nconfidence), as the placement of MPAs has been driven more often \r\nby political expediency (e.g., Leenhardt et al., 2013) than by managing \r\nkey drivers of biodiversity loss (Cockerell et al., 2020; Stevenson et al., \r\n2020) or climate-induced drivers (Bruno et  al., 2018). Only 3.5% of \r\nthe area currently protected will provide refuges from both SST \r\nand deoxygenation by 2050 under both RCP4.5 and RCP8.5 (Bruno \r\net al., 2018), and MPAs are more exposed to climate change under \r\nRCP8.5 than non-MPAs (Section 3.4.3.3.4; Figure 3.20d). Community \r\nthermal tolerances will be exceeded by 2050 in the tropics and by \r\n2150 for many higher-latitude MPAs (Bruno et al., 2018). Most MPA \r\ndesign has focused on the surface ocean, but MPAs are assumed to \r\nprotect the entire water column and benthos. Climate-induced drivers \r\n(Section  3"


id: 1f6c79996a6c0934317b52ebf5babc05
created_at: 2023-03-16 14:02:16
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content:
"2) throughout the water column and rapidly accelerating \r\nclimate velocities at depths below 200 m (Johnson et al., 2018; Brito\u0002Morales et al., 2020) are projected to affect virtually all North Atlantic \r\ndeep-water and open-ocean area-based management zones in the \r\nnext 20-50 years (Johnson et al., 2018), and the conservation goals of \r\nbenthic MPAs in the North Sea are not expected to be fulfilled (Weinert \r\net al., 2021). Heightened risk of non-indigenous species immigration \r\nfrom vessel traffic plus climate change further endangers MPA success \r\n(Iacarella et  al., 2020), a particular concern in the Mediterranean \r\n(D'Amen and Azzurro, 2020; Mannino and Balistreri, 2021), where \r\nthe current MPA network is already highly vulnerable to climate \r\nchange (Kyprioti et  al., 2021)"


id: 4d9ca5ce89b05d29719b0b1744e3d131
created_at: 2023-03-16 14:02:16
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content:
" This new evidence supports SROCC's \r\nhigh confidence assessment that present governance arrangements, \r\nincluding MPAs, are too fragmented to provide integrated responses \r\nto the increasing and cascading risks from climate change in the ocean \r\n(SROCC SPMC1.2; IPCC, 2019c)."


id: eb46da5ccc4c5af652da5f9f9d4b1b30
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"2019; Coleman et  al., 2020b; Fredriksen et  al., 2020; Wade et  al., \r\n2020). Managed breeding of corals has also had limited success in the \r\nlaboratory and at small local scales (National Academies of Sciences, \r\n2019). There is also limited evidence that physiological interventions, \r\nsuch as algal-symbiont or microbiome manipulation, could increase \r\ncoral thermal tolerance in the field (National Academies of Sciences, \r\n2019). Employing the natural adaptive capacity of species or \r\nindividuals in active restoration for corals and kelps with current \r\ntechnology involves fewer risks than assisted evolution or long\u0002distance relocation (high confidence) (Filbee-Dexter and Smajdor, \r\n2019; National Academies of Sciences, 2019). More ambitious \r\nengineered interventions like reef shading remain theoretical and \r\nnot scalable to the reef level (Condie et al., 2021)"


id: de30262b4861c8f2f643b2646f345889
created_at: 2023-03-16 14:02:16
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content:
" Debate continues \r\non how to apply planned adaptation in cost-effective ways that will \r\naccomplish the intended goals (National Academies of Sciences, 2019; \r\nDuarte et al., 2020; Kleypas et al., 2021)."


id: c8dccf94d487553156a1c97072e2745
created_at: 2023-03-16 14:02:16
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content:
"Local restoration projects often target vegetated ecosystems like \r\nmangroves, seagrasses and salt marshes that are valued and used \r\nby coastal communities (Veettil et al., 2019; Duarte et al., 2020; Wu \r\net  al., 2020a; Bertolini and da Mosto, 2021). Detail on mangroves \r\nand corals as EbA and protection/restoration hotspots is provided in \r\nSM3.8. Common and effective actions (Sasmito et  al., 2019; Duarte \r\net  al., 2020; Oreska et  al., 2020) include securing accommodation \r\nspace (Sections 3.4.2.4-3.4.2.5), restoring hydrological (Kroeger et al., \r\n2017; Al-Haj and Fulweiler, 2020) and sediment dynamics; managing \r\nharvesting (particularly in mangroves); reducing pollution (especially \r\nin seagrasses) (de los Santos et al., 2019); and replanting appropriate \r\nspecies in suitable environmental settings (Wodehouse and Rayment, \r\n2019; Friess et al., 2020a). Although efficacy is context dependent (Zeng \r\net al., 2020; Krause-Jensen et al"


id: d50338cb269805e798da9441a1ff5174
created_at: 2023-03-16 14:02:16
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content:
", 2021) and implementation is most \r\noften local (Alongi, 2018a), such projects facilitate tangible community \r\nengagement in climate action. Moreover, because these ecosystems \r\nsequester disproportionate amounts of carbon (blue carbon) (Annex II: \r\nGlossary; see Box 3.4), restoration supports climate-change mitigation \r\n(Lovelock and Reef, 2020; Gattuso et  al., 2021). Yet, constraints \r\nremain. For instance, Southeast Asia has 1.21 million km2\r\n of terrestrial, \r\nfreshwater and mangrove area biophysically suitable for reforestation, \r\nwhich could mitigate 3.43 +- 1.29 Pg CO2e yr-1 through 2030; however, \r\nreforestation is only feasible in a small fraction of this area (0.3-18%) \r\ngiven financial, land-use and operational constraints (Zeng et al., 2020). \r\nNevertheless, the multiple benefits offered by ecosystem restoration \r\nwill likely outweigh competing costs and increase its relevance as part \r\nof adaptation-strategy portfolios (Silver et  al., 2019; Wedding et  al"


id: 547e020561db567abfc6863c66d8cfcb
created_at: 2023-03-16 14:02:16
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content:
", \r\n2021), national carbon-accounting systems and nationally determined \r\ncontributions by parties to the Paris Agreement (Friess et al., 2020a; \r\nWu et al., 2020a)."


id: 86210c62fd1ef89662a131b29ecdf614
created_at: 2023-03-16 14:02:16
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content:
"Models show that a combination of available management approaches \r\n(restoration, reducing non-climate drivers) and speculative interventions \r\n(e.g., enhanced corals, reef shading) can contribute to sustaining some \r\ncoral reefs beyond 1.5degC of global warming with declining effectiveness \r\nbeyond 2degC of global warming (medium confidence) (Figure  3.25; \r\nWGII Chapter  17). These proposed interventions are also currently \r\ntheoretical and impractical over large scales; for example, engineered \r\nsolutions like reef shading are untested and not scalable at the reef \r\nlevel (Condie et al., 2021). Existing projects suggest that restoration \r\nand ecological interventions to habitat-forming ecosystems have the \r\nadditional benefits of raising local awareness, promoting tourism, \r\nand creating jobs and economic benefits (Fadli et al., 2012; Bostrom\u0002Einarsson et al., 2020; Hafezi et al"


id: 31a2b456bd16967c176de146eed1cd0a
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content:
", 2021), provided communities are \r\ninvolved in planning, operation and monitoring (Bostrom-Einarsson \r\net al., 2020)."


id: 516532fdf7fe08299de1a86c8468d00a
created_at: 2023-03-16 14:02:16
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"Interactions with oceans are fundamental to the identities of many coastal \r\nIndigenous Peoples (Norman, 2017), and this influences Indigenous \r\nresponses to climate hazards and adaptation. Around 30  million \r\nIndigenous Peoples live along coasts (Cisneros-Montemayor et  al., \r\n2016). Seafood consumption among Indigenous Peoples is much higher \r\nthan for non-Indigenous populations, and marine species support many \r\ncultural, medicinal and traditional activities contributing to public health \r\n(Section 3.5.3.1; Kenny et al., 2018). Perpetuation of Indigenous cultures \r\ndepends on protecting marine ecosystems and on adapting to changes \r\nin self-led ways (Section  3.5.6; Sangha et  al., 2019) that promote self\u0002determination (von der Porten et  al., 2019)"


id: 780d950f74078220a3fc0fa5d8dd5818
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content:
"Countries with large ocean areas within their EEZs have opportunities \r\nto develop 'blue-green economies' to reduce emissions and finance \r\nadaptation pathways (Chen et al., 2018a; Lee et al., 2020). Shifting from \r\ngrants to results-based financing can help attract more private capital \r\nto ocean adaptation (Lubchenco et  al., 2016; Claudet et  al., 2020a). \r\nPublic-private partnerships can also increase ocean adaptation finance \r\n(Goldstein et al., 2019; Sumaila et al., 2021). For example, the financial \r\nbenefits that biodiversity conservation confers to seafood harvest \r\nresilience could be used to leverage industry participation in adaptation \r\nand conservation finance (Barbier et al., 2018). Connecting restoration \r\nof blue carbon ecosystems with offset markets (e.g., Vanderklift \r\net  al"


id: 2f2991399c4d1f1aa106e3770afac54b
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", 2019) shows potential, but uncertainties remain about the \r\ninternational emissions trading under the UN Framework Convention \r\non Climate Change and climate impacts on blue carbon ecosystems \r\n(Section 3.6.3.1.6; Lovelock et al., 2017a; Macreadie et al., 2019)."


id: c78b388f1a9b07d794cc922db0f28a08
created_at: 2023-03-16 14:02:16
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content:
"Finance is a key barrier globally for ocean health, governance and \r\nadaptation to climate change (high agreement) (Annex II: Glossary; \r\nCross-Chapter  Box  FINANCE in Chapter  17; Hinkel et  al., 2018; \r\nMiller et al., 2018; Wabnitz and Blasiak, 2019; Woodruff et al., 2020; \r\nSumaila et al., 2021). Global adaptation finance was estimated to total \r\n30 billion USD yr-1 in 2017-2018, or 5% of all climate finance (CPI, \r\n2019), with no tracking specifically for coastal or marine adaptation in \r\nlow- to middle-income countries. Marine-focused adaptation finance \r\nis difficult to trace and label due to the cross-sectoral nature of many \r\nprojects (Blasiak and Wabnitz, 2018) and the lack of clear definitions \r\nabout what qualifies as adaptation or as new and additional finance \r\n(Donner et  al., 2016; Weikmans and Roberts, 2019)"


id: 2268839e09d248691abe76a30680464
created_at: 2023-03-16 14:02:16
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" Finance for \r\nmarine conservation from Overseas Development Assistance doubled \r\nbetween 2003 and 2016, reaching 634 million USD in 2016, similar to \r\nthe level provided by philanthropic foundations (Berger et al., 2019). \r\nYet coastal adaptation to SLR alone is projected to cost hundreds of \r\nbillions of USD yr-1, depending on the model and emission scenario \r\n(e.g., Wong et al., 2014; Nicholls et al., 2019). Economic and financing \r\nbarriers to marine adaptation are often higher in low- to middle\u0002income countries, where resources influence governance and constrain \r\noptions for implementation and maintenance (high confidence) \r\n(Hinkel et al., 2018; Klock and Nunn, 2019; Tompkins et al., 2020), and \r\nimpacts on their coastal and marine ecosystems could total several \r\npercentage points of their gross domestic product (Wong et al., 2014)"


id: 8ded088ff150b2e0cb95c0036e059636
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" \r\nCurrent financial flows are insufficient to meet the costs of coastal and \r\nmarine impacts of climate change (very high confidence) and ocean\u0002focused finance is unevenly distributed, with higher flows within, and \r\nto, developed countries (very high confidence)."


id: 97431dea22746c6cc4f1332fbdbd19cf
created_at: 2023-03-16 14:02:16
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"Transparency, coherence between different actors and initiatives, and \r\nproject monitoring and evaluation enhance success in adapting and \r\nachieving SDG14 (Life Below Water) (Blasiak et al., 2019). Maladaptation \r\n(WGII Chapter  16; Magnan et  al., 2016) is a common risk of current \r\nproject-based funding due to the pressure to produce concrete results \r\n(medium confidence) (Parsons and Nalau, 2019; Nunn et  al., 2020; \r\nNunn et al., 2021). Maladaptation can be avoided through a focus on \r\nbuilding adaptive capacity, community-based management, drivers of \r\nvulnerability and site-specific measures (low confidence) (Magnan and \r\nDuvat, 2018; Piggott-McKellar et al., 2020; Schipper, 2020). More research \r\nis needed to identify ways that governance and financing agreements can \r\nhelp overcome financial barriers and sociocultural constraints to avoid \r\nmaladaptation in coastal ecosystems (high confidence) (Hinkel et  al., \r\n2018; Miller et al., 2018; Piggott-McKellar et al"


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"Communities and governments at all levels increasingly use decision\u0002making frameworks (e.g., structured decision making) or decision\u0002analysis tools to evaluate trade-offs between different responses, \r\nrather than applying generic best practices to different physical, \r\ntechnical or cultural contexts (high confidence) (Watkiss et al., 2015; \r\nHaasnoot et al., 2019; Palutikof et al., 2019). Increased effort has also \r\nbeen devoted to developing climate services (actionable information \r\nand data products) that bridge the gap between climate prediction \r\nand decision making (Hewitt et al., 2020). Climate services have the \r\npotential to inform decision making related to disaster-risk reduction, \r\nadaptation responses, marine environmental management (e.g., \r\nfisheries management and MPA management) and ocean-based \r\nclimate mitigation (e.g., renewable-energy installations) (Le Cozannet \r\net  al., 2017; Gattuso et  al., 2019; Gattuso et  al., 2021)"


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" Although \r\nimproving observational and modelling capacity is important to \r\ndeveloping ocean-focused services, particularly in high-risk regions \r\nlike SIDS where regional climate projections are scarce (WGI AR6 \r\nChapter  9; Morim et  al., 2019; Fox-Kemper et  al., 2021), data are \r\nnot the only limiting factor in decision making (Weichselgartner and \r\nArheimer, 2019). Focusing on user engagement, relationship building \r\nand the decision-making context ensures that climate services are \r\nuseful to, and used by, different stakeholders (high confidence) (Soares \r\net  al., 2018; Mackenzie et  al., 2019; Weichselgartner and Arheimer, \r\n2019; Findlater et al., 2021; West et al., 2021)."


id: 65a86655df71607ffd739e5c7e90d83a
created_at: 2023-03-16 14:02:16
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"Relationships between Climate Action (SDG13) targets and SDG14 \r\ntargets are mostly synergistic (Figure  3.26; Fuso Nerini et  al., 2019). \r\nResponding to climate-change impacts requires transformative \r\ngovernance (high confidence) (Chapters  1, 18; Collins et  al., 2019a; \r\nBrodie Rudolph et al., 2020; Claudet et al., 2020a), especially for extreme \r\nevents and higher-impact scenarios (e.g., higher emissions) (Fedele et al., \r\n2019), and for achieving SDGs through one of the global ecosystems \r\ntransitions (Chapter 18; Sachs et al., 2019; Brodie Rudolph et al., 2020). \r\nOpportunities to transform ocean governance exist in developing new \r\ninternational and local agreements, regulations and policies that reduce \r\nthe risks of relocating ocean and coastal activities (Section 3.6.3.1.1) \r\nor in reinventing established practices (Section  3.6.3.3.3). Policy \r\ntransformations improving ocean sustainability under SDG14 also help \r\naddress SDG13 (Brodie Rudolph et al., 2020; Dundas et al"


id: b377397289cd2730f1116b70cda6671c
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", 2020; Claudet, \r\n2021; Sumaila et al., 2021). Emergent situations, such as the COVID-19 \r\npandemic, may provide opportunities to implement transformative \r\n'green recovery plans' that support achievement of the SDGs and NDCs \r\n(Cross-Chapter Box COVID in Chapter 7)."


id: 23c8bff5b49c1b431d920d8b2542f723
created_at: 2023-03-16 14:02:16
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"Ocean and coastal NbS can contribute to global mitigation efforts, \r\nespecially with ocean renewable energy and restoration and \r\npreservation of carbon ecosystems (see Box  3.4; Section  3.6.2.3). \r\nTechnological, economic and financing barriers presently hamper \r\ndevelopment of renewable ocean energy (AR6 WGIII Chapter 6). Such \r\ndevelopment could help small nations reliant on imported fuel meet \r\ntheir climate-mitigation goals and decrease risk from global fuel\u0002supply dynamics (Millar et al., 2017; Chen et al., 2018a), but progress \r\nis limited by lack of investment (Millar et al., 2017; Lee et al., 2020) or \r\nequipment (Aderinto and Li, 2018; Rusu and Onea, 2018). Wave-energy \r\ninstallations, possibly co-located with wind turbines (Perez-Collazo \r\net al., 2018), are promising for both low- to middle-income nations and \r\nareas with significant island or remote coastal geographies (Lavidas \r\nand Venugopal, 2016; Bergillos et al., 2018; Jakimavicius et al., 2018; \r\nKompor et al"


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", 2018; Penalba et al., 2018; Saprykina and Kuznetsov, \r\n2018; Lavidas, 2019). Wave-energy capture may also diminish storm\u0002induced coastal erosion (Abanades et al., 2018; Bergillos et al., 2018). \r\nTidal energy is a relatively new technology (Haslett et al., 2018; Liu et al., \r\n2018; Neill et al., 2018) with limiting siting requirements (Mofor et al., \r\n2013). Ocean renewable-energy expansion faces other technological \r\nobstacles including lack of implementable or scalable energy-capture \r\ndevices, access to offshore sites, competing coastal uses, potential "


id: 1f7d299e104772e2984af71a844e117b
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"from risks associated with poverty (SDG1), hunger (SDG2), health \r\nand water sanitation (SDG3 and SDG6), and inequality (SDG10) by \r\nsupporting aquaculture (Sections  3.5.3, 3.6.3.1), alerting the public \r\nabout poor water quality (Sections 3.5.5.3, 3.6.3.1) and empowering \r\nmarginalised groups, such as women and Indigenous Peoples, with \r\ndecision-relevant information (medium evidence, high agreement) \r\n(Sections  3.5.5.3, 3.6.3.1). Effectively implemented and managed \r\nmarine NbS (Section 3.6.2.3) contribute to attainment of social SDGs \r\nby: (a)  preserving biodiversity (Carlton and Fowler, 2018; Warner, \r\n2018; Scheffers and Pecl, 2019), which benefits most ocean and \r\ncoastal ecosystem services (Section 3.5.3; Figure 3.22); (b) increasing \r\nmarine fishery and aquaculture sustainability (Section  3.6.3); (c) \r\nincluding vulnerable people and communities in management \r\n(Section  3.6.3.2"


id: 9fa5c4c4c0ec13171c207e2839e6abf3
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"1); (d)  lowering risk of flooding from storms and \r\nSLR (Cross-Chapter  Box  SLR in Chapter  3; Sections  3.6.3.1.1); and \r\n(e) implementing spatial-management tools that make room for \r\nnew uses like renewable-energy development (Section  3.6.3.3.4). \r\nNature-based solutions can therefore help support achievement of \r\nNo Poverty (SDG1) (Ntona and Morgera, 2018), Zero Hunger (SDG2), \r\nGood Health and Well-Being (SDG3) (Duarte et al., 2020), Affordable \r\nand Clean Energy (SDG7) (Fuso Nerini et  al., 2019; Levin et  al., \r\n2020) and Reduced Inequality (SDG10). Socio-institutional marine \r\nadaptations (Section  3.6.2.2) that support current livelihoods and \r\nhelp develop alternatives can contribute to attainment of social SDGs \r\nby enhancing social equity and supporting societal transformation \r\n(medium confidence) (Cisneros-Montemayor et al., 2019; Pelling and \r\nGarschagen, 2019; Nash et  al., 2021)"


id: f47fc67ea54e975c4efbd3c11336221a
created_at: 2023-03-16 14:02:16
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" Even societal changes that \r\nare not directly marine related can decrease human vulnerability to \r\nocean and coastal climate risks by improving overall human adaptive \r\ncapacity (Section 1.2).\r\nMarine adaptation also shows promise for helping support achievement \r\nof economic SDGs (medium confidence) (Figure  3.26). Marine NbS \r\ncould help blue-economy frameworks achieve Decent Work and \r\nEconomic Growth (SDG8) (Lee et al., 2020) by sustainably and equitably \r\nincorporating ecosystem-based fisheries management, restoration "


id: 75eaab52bf00654bde94a5818901da33
created_at: 2023-03-16 14:02:16
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"or conservation (Sections  3.6.3.1.2, 3.6.3.2.1, 3.6.3.2.2; Voyer et  al., \r\n2018; Cisneros-Montemayor et al., 2019; Cohen et al., 2019; Okafor\u0002Yarwood et  al., 2020). Nature-based solutions that involve active \r\nrestoration or accommodation can contribute to Sustainable Cities and \r\nCommunities (SDG11) and Infrastructure (SDG9) (Section  3.6.3.1.1). \r\nNewly developed marine industries and livelihoods associated with \r\nNbS might support attainment of Sustainable Communities (SDG11) \r\n(Cisneros-Montemayor et al., 2019). Finance and market mechanisms \r\nto support disaster relief or ocean ecosystem services, such as blue \r\ncarbon or food provisioning, and innovations (SDG9) including new \r\ntechnologies like vessel-monitoring systems (Kroodsma et  al., 2018), \r\ncan contribute to Responsible Consumption and Production (SDG12) \r\n(Sumaila and Tai, 2020)"


id: 30a895f02b649d3876467a93f40dfaa2
created_at: 2023-03-16 14:02:16
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" Blue-economy growth that includes sustainable \r\nshipping, tourism, renewable ocean energy and transboundary fisheries \r\nmanagement (Pinsky et al., 2018) have the potential to contribute to \r\nEconomic Development (SDG8), affordable and clean energy (SDG7) as \r\nwell as global mitigation efforts (SDG13) (Hoegh-Guldberg et al., 2019b; \r\nDuarte et  al., 2020). Participatory approaches and co-management \r\nsystems (Section 3.6.2.1) in many maritime sectors can contribute to \r\nSDG11 and SDG12 while helping align the blue economy and the SDGs \r\n(high agreement) (Lee et al., 2020; Okafor-Yarwood et al., 2020)."


id: c828f9f3e97fa0e53baf980345b5388a
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"shellfish harvesting (Turner et  al., 2020a) and account for 11% of \r\nglobal artisanal fisheries participants (Harper et al., 2020b), they are \r\noften not specifically counted in datasets and excluded from decision \r\nmaking and support programmes (Cross-Chapter  Box  GENDER in \r\nChapter  18; Harper et  al., 2020b; Michalena et  al., 2020). Targeted \r\nefforts to incorporate knowledge diversity, and include artisanal \r\nfishers, women and Indigenous Peoples within international, regional \r\nand local policy planning, promote marine adaptation that supports \r\nachievement of gender equality (SDG5) and reduces inequalities \r\n(SDG10) (limited evidence, high agreement) (FAO, 2015). Integrated \r\nplanning, financing and implementation can help overcome these \r\nlimitations (Section  3.6.3.3.2; Cross-Chapter  Box  FINANCE in \r\nChapter  17), ensuring that marine adaptations do not compromise \r\noverall human equity or specific SDGs (Osterblom et al., 2020; Nash \r\net al"


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"approach to both mitigation and adaptation. Following adoption of \r\nthe Paris Agreement in 2015, the UN SDGs (Table  3.31) came into \r\nforce in 2016, including SDG14 specifically dedicated to Life Below \r\nWater (Table 3.31). In 2017, the first UN Ocean Conference was held \r\n(United Nations, 2017), the UNFCCC adopted the Ocean Pathway to \r\nincrease ocean-targeted multilateral climate action (COP23, 2017) \r\nand the UN Assembly declared 2021-2030 the Decade for Ocean \r\nScience for Sustainable Development (Visbeck, 2018; Lee et al., 2020). \r\nNext, 14 world leaders formed the High-Level Panel for a Sustainable \r\nOcean Economy to produce the New Ocean Action Agenda, founded \r\non 100% sustainable management of national ocean spaces by 2025 \r\n(Ocean Panel, 2020)"


id: 4e8f8792357023296ee44f940e583d6c
created_at: 2023-03-16 14:02:16
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" All of these initiatives position oceans centrally \r\nwithin the climate-policy and biodiversity-conservation landscapes \r\nand seek to develop a coherent effort and common frameworks to \r\nachieve marine sustainability (Visbeck, 2018; Lee et  al., 2020), new \r\neconomic opportunities (Konar and Ding, 2020; Lee et al., 2020), more \r\nequitable outcomes (Osterblom et  al., 2020) and decisive climate \r\nmitigation and adaptation (Hoegh-Guldberg et al., 2019a), to achieve \r\ntruly transformative change (Claudet et al., 2020a)."


id: 121b974063ca96e637aab2fbc334682f
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"Adaptation efforts (Sections  3.6.3.1-3.6.3.2) have three common \r\ncharacteristics that facilitate implementation and success, and \r\ncontribute to climate resilient development pathways (Chapter  18). \r\nFirst, availability of multiple types of information (e.g., monitoring, \r\nmodels, climate services; Section 3.6.3.3) exposes the magnitude and \r\nnature of the adaptation challenge. Well-developed observation and \r\nmodelling capabilities (Reusch et al., 2018) offer insights on climate\u0002associated risks at different time scales (Cvitanovic et al., 2018; Hobday \r\net  al., 2018), and this facilitates adaptation within multiple areas \r\n(e.g., industries over shorter time scales, societies over longer scales) \r\n(Hobday et  al., 2018). Environmental data have supported building \r\nsocietal and political (socio-institutional) will to adopt national and \r\nsubnational adaptive management principles (Hobday et  al., 2016b; \r\nChampion et al., 2018; McDonald et al., 2019)"


id: cb04927fc775ec16329a6105049ce3b1
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" However, incorporating \r\nIKLK at the same time provides more diverse social-environmental \r\ninsight (Section 3.6.3.4.1; Goeldner-Gianella et al., 2019; Petzold and \r\nMagnan, 2019; Wilson et al., 2020b). This can help align adaptation \r\nsolutions with cultural values and increase their legitimacy with \r\nIndigenous and local communities (Chapter 1.3.2.3), achieving climate \r\nresilient development pathways (Chapter 18; Adger et al., 2017; Nalau \r\net al., 2018; Penaherrera-Palma et al., 2018; Raymond-Yakoubian and \r\nDaniel, 2018; Wamsler and Brink, 2018). Second, implementation of \r\nmultiple low-risk options (Hoegh-Guldberg et al., 2019a; Gattuso et al., \r\n2021) such as economic diversification (Section 3.6.2.1) can provide \r\nculturally acceptable livelihood alternatives and food supplies (e.g., \r\nfishing to ecotourism and mariculture) (Froehlich et al., 2019) while also \r\nproviding environmental benefits (e.g"


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", seaweed mariculture's potential \r\ncarbon storage co-benefits) (WGIII AR6 Chapter  7; Hoegh-Guldberg \r\net al., 2019a; Gattuso et al., 2021). Third, inclusive governance that is \r\nwell aligned to the systems at risk from climate change is fundamental \r\nfor effective adaptation (Barange et al., 2018). Solutions implemented \r\nwithin polycentric governance systems (Section  3.6.3; Bellanger \r\net al., 2020) benefit from synergies between knowledge, action and \r\nsocial-ecological contexts and stimulate governance responses at \r\nappropriate spatio-temporal scales (Cvitanovic and Hobday, 2018). \r\nGovernance aligned with Indigenous structures and local structures \r\nsupports successful outcomes that prioritise the concerns and rights \r\nof involved communities (Section 3.6.3; Mawyer and Jacka, 2018) and \r\nbetter leverages existing social organisation (i.e., network structures), \r\nlearning processes and power dynamics (Barnes et al., 2020)."


id: c387e89578dffa0d2a53d9f12073ee0d
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"There is robust evidence that a combination of global and local solutions \r\noffers the greatest benefit in reducing climate risk (Gattuso et al., 2018; \r\nHoegh-Guldberg et al., 2019a; Hoegh-Guldberg et al., 2019b). Ambitious \r\nand swift global mitigation offers more adaptation options and pathways \r\nto sustain ecosystems and their services (Figure 3.25). Some solutions \r\ntarget both mitigation and adaptation (e.g., blue carbon conservation; \r\nCross-Chapter  Box  NATURAL in Chapter  2;  see Box  3.4), and cross\u0002cutting solutions simultaneously support several ocean-related sectors \r\n(e.g., area-based measures support fishing, tourism; Section 3.6.3.2.1) or \r\necosystem functions (e.g., NbS support coastal protection, biodiversity, \r\nhabitat, etc.; Section 3.6.3.2.2; Sala et al., 2021). Combined solutions \r\nalso leverage a variety of existing policies and governance systems \r\n(Section 3.6.4.3; Duarte et al., 2020) to advance climate mitigation and \r\nadaptation"


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" Even communities that face the limits of adaptation, like \r\nthose who must relocate to cope with rising seas (McMichael et  al., \r\n2019; Bronen et  al., 2020), urgently require solutions that combine \r\nscientific projections, IKLK, cultural and community values, and ways to \r\npreserve cultural identity to support planning and implementation of \r\nrelocation (McMichael and Katonivualiku, 2020)."


id: eadfc246a89f33a2bfe6b88d2f587d96
created_at: 2023-03-16 14:02:17
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"Nature-based solutions are showing promising results in achieving \r\nadaptation and mitigation outcomes across marine and coastal \r\necosystems (Sections  3.6.3.2.1-3.6.3.2.2), but NbS have different \r\ndegrees of readiness in marine ecosystems (Duarte et al., 2020). Habitat \r\nrestoration and recovery are highly effective in specific settings and \r\nconditions (McLeod et al., 2019). Restoring and conserving vegetated \r\ncoastal habitats (Sections  3.4.2.4-3.4.2.5) represent robust NbS, \r\nespecially in the tropics, and particularly when paired with restoration and \r\nconservation of terrestrial ecosystems (robust evidence) (e.g., peatlands \r\nand forests; WGIII AR6 Chapter 7; Hoegh-Guldberg et al., 2019b; Duarte \r\net al., 2020; Griscom et al., 2020). Although most of the focus on NbS \r\nefficacy has been on coastal and shelf ecosystems (Section  3.6.3"


id: 60600e3005c6aa2c0b5864b55a686398
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"2), \r\nrecent advances point to an emerging role of NbS beyond coastal waters \r\nin the form of area-based management tools in marine areas beyond \r\nnational jurisdiction (Section 3.6.2.3; Gaines et al., 2018; Pinsky et al., \r\n2018; Crespo et al., 2020; O'Leary et al., 2020; Visalli et al., 2020; Wagner \r\net al., 2020), because sustainable fisheries and aquaculture and climate\u0002responsive MPAs have high potential to adapt (Tittensor et al., 2019)."


id: b218ef19f2b6b001878db41b3b494b9c
created_at: 2023-03-16 14:02:17
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"There is an opportunity to improve current practices when developing \r\nnew ocean and coastal adaptation efforts so that they routinely contain \r\nthese successful characteristics and resolve technical, economic, \r\ninstitutional, geophysical, ecological and social constraints (Figure 3.25; \r\nSection  3.6.3.3; IPCC, 2018; Singh et  al., 2020). Enhancements are \r\nneeded in human, technical and financial resources; regulatory \r\nframeworks (Ojwang et  al., 2017); political support (Rosendo et  al., \r\n2018); institutional conditions and resources for fair governance (Gupta \r\net al., 2016; Scobie, 2018); political leadership; stakeholder engagement; \r\nmultidisciplinary data availability (Gopalakrishnan et al., 2018); funding \r\nand public support for adaptation (Cross-Chapter  Box  FINANCE in \r\nChapter 17; Ford and King, 2015); and incorporating IKLK in decision \r\nmaking (Nalau et al., 2018; Jabali et al., 2020; Petzold et al., 2020)"


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"Contributing Authors: Malcolm Araos (Canada/USA), Soumya Balasubramanya (Sri Lanka/\r\nIndia), Angelica Katharina Casparina Brackel (the Netherlands), John Caesar (UK), Holly B. \r\nCaggiano (USA), Benjamin Cook (USA), Constantino Dockendorff (Germany/Chile), Calynn Dowler \r\n(USA), Robert Dunn (UK/Germany), Lina Elisabeth Erika Eklund (Sweden), Zhang Fan (China), \r\nValeria Fanghella (Italy), Rodrigo Fernandez (USA/Guatemala), Colin M. Finlayson (Australia), \r\nSabine Fuss (Germany), Animesh Kumar Gain (Italy/Bangladesh), Freya Garry (UK), Laila Gohar \r\n(UK), Valentin Golosov (Russian Federation), Sharlene Liane Gomes (the Netherlands/Canada), \r\nBenjamin Jerome Gray (USA), Lukas Gudmundsson (Switzerland/Germany/Iceland), Tania Guillen \r\nBolaneos (Germany/Nicaragua), Kate Halladay (UK), Ed Hawkins (UK), Greeshma Hegde (India), \r\nMasoud Irannezhad (China/Iran), Bjorn Klove (Finland/Norway), Aristeidis G"


id: 57521e4d2f10d892b69884cf1b971fed
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" Koutroulis (Greece), \r\nManish Kumar (India), Jonathan Lautze (South Africa/USA), Deborah Ley (Mexico/Guatemala), \r\nAshwina Mahanti (India), Ganquan Mao (China), Deborah McGregor (Canada), Mamta Mehar \r\n(India), Megan Mills-Novoa (USA), Tessa Moller (Germany/Luxemburg), Sanchari Mukhopadhyay \r\n(India), Tero Mustonen (Finland), Lakshmikantha N. R. (India), Gustavo Naumann (Italy/Argentina/\r\nGermany), Prajjwal Kumar Panday (USA/Nepal), Vishnu Prasad Pandey (Nepal), Jagadish Parajuli \r\n(USA/Nepal), Assela Pathirana (the Netherlands/Sri Lanka), Ritu Priya (India), E. B. Uday Bhaskar \r\nReddy (India), Ekaterina Rets (Russian Federation), Pamela Rittelmeyer (USA), Conrado M. Rudorff \r\n(Brazil), Orie Sasaki (Japan), Corinne Schuster Wallace (Canada/Wales), Christopher A"


id: d57822e223c9b5be8d2dd90dc606e8a0
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content:
"challenges (Bijl et  al., 2018). Vulnerability to water-related impacts \r\nof climate change and extreme weather are already felt in all major \r\nsectors and are projected to intensify in the future, for example, in \r\nagriculture (high confidence) (Sections  4.3.1, 4.5.1); energy and \r\nindustry (high confidence for observed drought impacts and projected \r\nimpacts) (Sections  4.3.2, 4.5.2); water for health and sanitation \r\n(high confidence about links to precipitation extremes and disease \r\noutbreaks) (Sections  4.3.3, 4.5.3); water for urban, peri-urban and \r\nmunicipal sectors (medium confidence) (Sections  4.3.4, 4.5.4) and \r\nfreshwater ecosystems (high confidence in climate change as a driver \r\nin degradation of freshwater ecosystems) (Sections  4.3.5, 4.5.5). \r\nAgriculture and irrigation account for the most significant proportion \r\nof consumptive water use and account for 60-70% of total water \r\nwithdrawals (Hanasaki et al., 2018; Burke et al., 2020; Muller Schmied \r\net al., 2021)"


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" Globally, 10% of the most water-stressed basins account \r\nfor 35% of global irrigated calorie production (Qin et al., 2019), and \r\nfood production is at risk in those basins and worldwide due to \r\nchanges in hydrological components of climate change. Lack of access \r\nto clean water and sanitation has been one of the leading causes of \r\nwater-borne diseases. In 2017, approximately 2.2 billion people lacked \r\naccess to safe drinking water, and roughly 4.2 billion people could not \r\naccess safe sanitation (WHO and UNICEF, 2019). Inequities in access to \r\nsafe water are being amplified during the current COVID-19 pandemic \r\n(Box 4. 5 and Cross-Chapter Box COVID in Chapter 7). The same 10% \r\nof most water-stressed basins also account for 19% of global thermal \r\nelectricity generation (Qin et al., 2019), and globally, both production \r\nof hydropower and thermal power has been negatively affected by \r\ndroughts and other extreme events"


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" Globally, between 16% and 39% \r\nof cities experienced surface-water deficits between 1971 and 2000. \r\nIf environmental flow requirements (EFRs) are accounted for, these \r\nnumbers increase to 36% and 63%, respectively. Even under a scenario \r\nwhere urban water gets the highest priority, more than 440.5 million \r\npeople in cities globally are projected to face a water deficit by 2050 \r\n(Florke et  al., 2018). The situation is particularly precarious in the \r\nGlobal South, where most of the population lacks access to piped \r\nwater (WRI, 2019)."


id: 55f65b0840c77d0d1fa0d6a654c5d11f
created_at: 2023-03-16 14:02:17
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content:
"Water security is defined as 'the capacity of a population to safeguard \r\nsustainable access to adequate quantities of acceptable quality water \r\nfor sustaining livelihoods, human well-being, and socio-economic \r\ndevelopment, for ensuring protection against water-borne pollution \r\nand water-related disasters, and for preserving ecosystems in a climate \r\nof peace and political stability' (Grey and Sadoff, 2007). Risks emanating \r\nfrom various aspects of water insecurity have emerged as a significant \r\nglobal challenge. The Global Risks Report by the World Economic Forum \r\nlists water crisis as one of the top five risks in all its reports since 2015 \r\n(WEF, 2015; WEF, 2016; WEF, 2017; WEF, 2018; WEF, 2019; WEF, 2020). \r\nWater also features prominently in the SDGs (Section 4.8) and plays a \r\ncentral role in various systems transitions needed for climate resilient \r\ndevelopment. Most SDGs cannot be met without access to adequate \r\nand safe water (Ait-Kadi, 2016; Mugagga, 2016)"


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" In addition, without \r\nadequate adaptation, future water-related impacts of climate change \r\non various sectors of the economy are projected to lower the global \r\nGDP by mid-century, with higher projected losses expected in low- and \r\nmiddle-income countries (World Bank, 2017; GCA, 2019)."


id: 4db0b5c57f91182f8a3a474a9d41728e
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"First, approximately half the world's population (~4  billion out of \r\n~8 billion people) are assessed as being currently subject to severe water \r\nscarcity for at least some part fo the year (medium confidence) due to \r\nclimatic and non-climate factors (Box 4.1). Water insecurity arises from \r\nmany factors, both environmental and societal. Environmental factors \r\ninclude too little freshwater due to drought or pollution, and too much \r\nwater, due to extreme precipitation and flooding, and are being affected \r\nby climate change. Societal factors include economic and governance\u0002related barriers to water access or protection from water-related damages. \r\nCurrently, many people are experiencing climate change on a day-to-day \r\nbasis through water-related impacts such as the increased frequency \r\nand intensity of heavy precipitation (high confidence) (Section 4.2.1.1, \r\nSeneviratne et al., 2021 ); accelerated melting of glaciers (high confidence) \r\n(Section 4.2.2, Douville et al"


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", 2021); changes in frequency, magnitude and \r\ntiming of floods (high confidence) (Section 4.2.4, Seneviratne et al., 2021 \r\n); more frequent and severe droughts in some places (high confidence) \r\n(Section 4.2.5, Seneviratne et al., 2021); decline in groundwater storage \r\nand reduction in recharge (medium confidence) (Section 4.2.6, Douville \r\net  al., 2021) and water quality deterioration due to extreme events \r\n(medium confidence) (Section  4.2.7). For example, since the 1970s, \r\n44% of all disaster events have been flood-related (WMO, 2020). With \r\nthe added stressor of climate change, globally, a larger fraction of land \r\nand population are projected to face increased water scarcity due to \r\nclimate change. For example, at an approximately 2degC GWL, between \r\n0.9 and 3.9 billion people are projected to be at increased exposure to \r\nwater stress, depending on regional patterns of climate change and the \r\nsocioeconomic scenarios considered (Koutroulis et al., 2019)."


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"Third, a large majority (~60%) of all adaptation responses documented \r\nsince 2014 are about adapting to water-related hazards like droughts, \r\nfloods and rainfall variability (Berrang-Ford et  al., 2021b) (high \r\nconfidence). Water-related adaptation action features prominently in \r\nNDC pledges by a large majority of countries in both Global North \r\nand Global South (GWP, 2018). These adaptation responses and their \r\ncurrent benefits and effectiveness in reducing water-related risks in \r\nthe future are systematically assessed in this chapter (Sections  4.6, \r\n4.7.1, 4.7.2 and 4.7.3). These adaptation measures aim to reduce \r\nimpacts of water-related hazards through responses such as irrigation, \r\nwater and soil moisture conservation, rainwater harvesting, changes \r\nin crops and cultivars, improved agronomic practices, among others \r\n(Sections 4.6.2; 4.7.1)"


id: 3a6b23cfc7fd77efe61ded27b06a158c
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" Only ~20% of all documented case studies on \r\nobserved water-related adaptations measure outcomes (positive or \r\nnegative), but the link between positive outcomes and climate risk \r\nreduction is unclear and remains challenging to assess (Section 4.7.1) \r\n(medium confidence). On the other hand, most of the future projected \r\nwater-related adaptations are more effective at lower GWLs (1.5degC) \r\nthan at higher GWLs, showing the importance of mitigation for future \r\nadaptations to remain effective (high confidence)."


id: 94e8e944134e3160ba30e78c36ac4bf4
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"This chapter draws on previous IPCC reports and new methodologies \r\n(Section 4.1.1 and SM4.1, SM4.2) and assesses the impacts of climate \r\nchange on natural and human dimensions of the water cycle with \r\na particular focus on water-related vulnerabilities and adaptation \r\nresponses (Figure 4.1). Section 4.2 assesses observed changes in the \r\nhydrological cycle, and Section 4.3 focuses on their societal impacts \r\nand detects which parts of these changes are directly attributable to \r\nclimate change. Section 4.4 assesses projected risks of changes in the \r\nhydrological cycle on various components of the hydrological cycle, and \r\nSection 4.5 assesses the same for sectoral risks. Projections and risks \r\nassessments for future impacts are framed in terms of GWLs and time \r\nhorizons, as these are useful for informing mitigation policy under the \r\nParis Agreement and informing adaptation planning. Sections 4.6 and \r\n4"


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"7 assesses current and future water-related adaptation responses in \r\nreducing climate and associated impacts and risks and looks at limits \r\nto adaptations, especially in a future warmer world. Finally, Section 4.8 \r\noutlines the enabling principles for meeting water security, SDGs and \r\nclimate resilient development."


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"Water scarcity and water insecurity are related concepts but not identical, and each has a range of interpretations leading to some overlap. \r\nWater scarcity can be broadly described as a mismatch between the demand for fresh water and its availability, quantified in physical terms. \r\nWater security/insecurity is a broader concept with definitions beyond physical water scarcity, encompassing access to water services, safety \r\nfrom poor water quality and flooding, and appropriate water governance that ensures access to safe water (Sadoff et al., 2020). Metrics \r\nof water security include both physical and socioeconomic components and are a tool for comparison between different locations and \r\ncountries regarding relative levels of water security in the context of water-related risks. Some definitions of water scarcity also incorporate \r\nthese broader issues"


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" For example, 'economic water scarcity' has been defined as a situation where 'human, institutional, and financial \r\ncapital limit access to water, even though water in nature is available locally to meet human demands' (Comprehensive Assessment of Water \r\nManagement in Agriculture, 2007). Economic water scarcity can also occur where infrastructure exists, but water distribution is inequitable \r\n(Jaeger et al., 2017). Much of the literature exploring the impacts of climate change on water security, however, focuses on quantifying \r\nphysical water scarcity. Discussions in this box consider physical water scarcity as a quantifiable measure of water availability compared to \r\nits demand and consider the societal elements of economic water scarcity to be part of the more comprehensive concept of water insecurity."


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"Using a Water Scarcity Index (WSI) defined as the ratio of demand and availability, accounting for EFRs, it is estimated that 4 billion \r\npeople live under conditions of severe water scarcity for at least one month per year (Figure Box 4.1.1a; Mekonnen and Hoekstra, 2016). \r\nNearly half of these people live in India and China. Although regions with high water scarcity are already naturally dry (virtually certain2\r\n),\r\nhuman influence on climate is leading to reduced water availability in many regions. It is very likely that global patterns of soil moisture \r\nchange are being driven by human influence on climate, and an overall global decline in soil moisture is attributable to greenhouse \r\nforcing [4.2.1.3]. Climate change patterns of streamflow change include declines in western North America, northeast South America, the \r\nMediterranean and South Asia (medium confidence) [4.2.3]"


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" However, quantification of the contribution of anthropogenic climate change \r\nto current levels of water scarcity is not yet available."


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"Figure Box 4.1.1 |  Geographical distributions of current water scarcity and levels of challenge for policies addressing future change.\r\n(a) The number of months per year with severe water scarcity (ratio of water demand to availability > 1.0). Reproduced from Mekonnen and Hoekstra (2016).\r\n(b) Local levels of policy challenges for addressing water scarcity by 2050, considering both the central estimate (median) and the change uncertainty in projections of a \r\nWater Scarcity Index (WSI) from the present day to 2050 (Greve et al., 2018). Projections used five CMIP5 climate models, three global hydrological models from ISIMIP \r\nand three Shared Socioeconomic Pathways (SSPs). Levels of policy challenges refer to the scale and nature of policies to address water scarcity and range from monitoring \r\nand reviewing risks ('low') through transitional changes in water systems ('medium') to transformational changes ('high')"


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" Low policy challenges arise when the projected \r\nwater scarcity in 2050 is lower (<0.4), and the level of uncertainty remains relatively stable in future projections. Medium policy challenge arises when either the central \r\nestimate of water scarcity remains low but uncertainty increases, or the uncertainty is stable but the central estimate of water scarcity for 2050 is higher (>0.4). High \r\npolicy challenges arise when the central estimate of water scarcity is higher and the uncertainty increases. White areas show grid points defined as non-water-scarce (75th \r\nquantile of the WSI < 0.1 at all times) or very low average water demand. Reproduced from Greve et al. (2018)."


id: e120d16b2fbd844d6850c71bda37a30d
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"Gain et al. (2016) define a Global Water Security Index (GWSI) metric on a scale of 0 to 1 combining indicators of relative levels of availability \r\nof freshwater, accessibility to water services, water management and water quality and safety (including flood risk, which can affect water \r\nquality as well as being a direct physical hazard). Global application of this index indicates large worldwide differences in water security \r\narising from different combinations of reasons (Figure Box 4.1.2a). In North Africa, the Middle East, large parts of the Indian sub-continent \r\nand north China, low water security arises predominantly from low water availability. However, many areas with relatively high water \r\navailability have relatively low levels of water security due to other factors. In 2015, 29% of the world's population did not have access to safe \r\ndrinking water (Ritchie and Roser, 2019)"


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" In large parts of South and Southeast Asia, significant contributions to water insecurity came from \r\nincreased flood risk and deteriorated water quality (Burgess et al., 2010; Ward et al., 2017; Farinosi et al., 2018). Water availability is relatively \r\nhigh across most of Africa, but water security is relatively low due to low accessibility, management and safety/quality standards. Most \r\npeople in Africa do not have access to safe drinking water and improved sanitation (Marson and Savin, 2015; Naik, 2017; Armah et al., 2018)."


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"(a) Top: a global map of local values of GWSI constructed from the following components with their subjectively weighted contribution to the combined metric indicated \r\nin brackets. Middle left: relative effectiveness of water management (15%), comprising a World Governance Index at country scale (itself representing six components: \r\nvoice and accountability, political stability and absence of violence/terrorism, government effectiveness, regulatory quality, rule of law and control of corruption) and \r\nindicators of transboundary legal frameworks and political tensions at a river-basin scale. Middle right: relative accessibility to water services (20%), including drinking \r\nwater and sanitation. Bottom left: relative water quality and safety (20%), including a Water Quality Index and Flood Frequency Index. Bottom right: relative availability of \r\nfresh water (45%), comprising a Water Scarcity Index, Drought Index and the groundwater depletion rate"


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" Data for the components do not apply to the same set of dates \r\nbut are generally applicable to recent decades up to 2010. White areas indicate no data available for at least one component. For further details, see Gain et al. (2016).\r\n(b) Factors through which climate change or action on mitigation or adaptation could influence water security."


id: fd58dc320ce7a490a8d78d440dc1549f
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"Future water security will depend on the magnitude, rate and regional details of future climate change and non-climatic factors, including \r\nagricultural practices, water demand and governance. In many cases, climate change may not be the dominant factor affecting water \r\nsecurity. Nevertheless, climate change poses clear risks to water security in many regions through potential impacts on water availability, \r\nquality and flooding. The range of possible outcomes is extremely large, and assessing the likelihood of particular outcomes depends on \r\nconsideration of uncertain regional climate changes and uncertain socioeconomic futures. Uncertainty in future water scarcity projections \r\nmakes climate change risks to water security and planning for adaptation challenging"


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content:
" Limiting climate change to lower levels of global \r\nwarming would reduce the risks to water security arising from climate change, partly because uncertainties in regional climate change \r\nare smaller at lower levels of warming."


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"In summary, roughly half of the world's population are assessed as currently subject to severe water scarcity for at least some part \r\nof the year due to climatic and non-climatic factors, and this is projected to be exacerbated at higher levels of warming (medium \r\nconfidence). General water insecurity issues are seen worldwide, particularly in South Asia, North China, Africa and the Middle East, due \r\nto high population densities often coupled with low water availability, accessibility, quality and governance (high confidence). Areas with \r\nhigh water availability can also be water-insecure due to increased flood risk, deteriorated water quality, and poor governance (high \r\nconfidence). Future water security will depend on the evolution of all these socioeconomic and governance factors and future regional \r\nclimate change (high confidence)"


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" The main climate change contribution to water insecurity is the potential for reduced water availability, \r\nwith a secondary contribution from increased flooding risk (medium confidence). Future socioeconomic conditions are a crucial driver of \r\nwater insecurity, implying the need for further adaptation to some level of future climate change (medium confidence). However, policy \r\nchallenges are high in many regions, with uncertainty in the regional climate outcomes being a key factor (high confidence)."


id: b23b573c9bca4d04481d3e3274eb5331
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content:
"The Sixth Assessment Report (AR6) Working Group I (WGI) (Douville \r\net  al., 2021) concluded that anthropogenic climate change has \r\nincreased atmospheric moisture and precipitation intensity (very likely\r\nby 2-3% per 1degC) (high confidence), increased terrestrial ET (medium \r\nconfidence) and contributed to drying in dry summer climates including \r\nin the Mediterranean, southwestern Australia, southwestern South \r\nAmerica, South Africa and western North America (medium to high \r\nconfidence), and has caused earlier onset of snowmelt and increased \r\nmelting of glaciers (high confidence) since the mid-20th century. The \r\nreport also stated with high confidence that the water cycle variability \r\nand extremes are projected to intensify, regardless of the mitigation \r\npolicy. The share of the global population affected by water-related \r\nhazards and water availability issues is projected to increase with the \r\nintensification of water cycle variability and extremes"


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"Second, this chapter follows the developments set in motion by \r\nSR1.5, SRCCL and SROCC to incorporate Indigenous knowledge (IK), \r\ntraditional knowledge (TK) and local knowledge (LK). SR1.5 stated \r\nthat disadvantaged and vulnerable populations, including Indigenous \r\nPeoples and certain local communities, are at disproportionately \r\nhigher risk of suffering adverse consequences due to global warming \r\nof 1.5degC or more (Roy et al., 2018). SRCCL highlighted the enhanced \r\nefficacy of decision-making and governance with the involvement \r\nof local stakeholders, particularly those most vulnerable to climate \r\nchange, such as Indigenous Peoples (Arneth et  al., 2019). SROCC \r\nfound adaptation efforts have benefited from the inclusion of IK and \r\nLK (IKLK) (Abram et al., 2019). In this chapter, we engage directly with \r\nIndigenous contributing authors and use multiple evidence-based \r\napproaches, as undertaken by the IPBES (Tengo et  al., 2014; Tengo \r\net al., 2017)"


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" This approach is guided by the understanding that the co\u0002production of knowledge (between scholars and local communities) \r\nabout water and climate change vulnerability, impacts and adaptation \r\nhas the potential to lead to new water knowledge and context\u0002specific governance strategies (Arsenault et  al., 2019; Chakraborty \r\nand Sherpa, 2021). Additionally, shifting beyond the exclusive use \r\nof technical knowledge and Western viewpoints redresses the \r\nshortcomings of resource- and security-oriented understandings to \r\nwater and acknowledges the more holistic and relational approaches \r\ncommon to IKLK (Section 4.8.4) (Stefanelli et al., 2017; Wilson, 2019; \r\nChakraborty and Sherpa, 2021)."


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"annual or seasonal precipitation and others less, (b) many regions have \r\nseen increased heavy precipitation, and many have seen either increases \r\nor decreases in dry spells and (c) some regions have seen shifts towards \r\nheavier precipitation events separated by more prolonged dry spells \r\n(Section  4.2.1.1). Observationally based calculations suggest that ET \r\nhas changed in response to changes in precipitation and increasing \r\ntemperatures, resulting in changing patterns of soil moisture worldwide \r\nwhich are now detectable by satellite remote sensing (Sections 4.2.1.2, \r\n4.2.1.3). Rising temperatures have caused profound and extensive \r\nchanges in the global cryosphere, with mountain glaciers, land ice and \r\nsnow cover shrinking, causing substantial, permanent impacts on the \r\nways of life of people in these regions, particularly Indigenous Peoples \r\nwith strong cultural links to long-term or seasonally frozen environments \r\n(Sections 4.2.2, 4.3.8)"


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" Groundwater recharge in spring may have been \r\nreduced due to shorter snowmelt seasons, although the dominant impact \r\non groundwater has been non-climatic and through intensification of \r\nirrigation (Section 4.2.6). The global-scale pattern of streamflow changes \r\nis now attributable to observed historical climate change, with human \r\nland and water use insufficient by themselves to explain the observed \r\nstreamflow changes at global scales (Section 4.2.3). Numerous examples \r\nof extreme hydrometeorological events, including heavy precipitation, \r\nflooding, drought and wildfire events causing deaths, high levels of \r\neconomic damage and extensive ecological impacts, have been shown \r\nto have been made more likely by human influence on climate through \r\nincreased GHG concentrations in the atmosphere (Sections 4.2.1.1, 4.2.4, \r\n4.2.5). Overall, there is a clear picture of human alteration of the global \r\nwater cycle, which is now affecting societies and ecosystems across the "


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"The intensity of heavy precipitation has increased in many regions (high \r\nconfidence), including much of North America, most of Europe, most \r\nof the Indian sub-continent, parts of northern and southeastern Asia, \r\nmuch of southern South America, parts of southern Africa and parts of \r\ncentral, northern and western Australia (Figure 4.3 f) (Dunn et al., 2020; \r\nSun et al., 2020). Conversely, heavy precipitation has decreased in some \r\nregions, including eastern Australia, northeastern South America and \r\nwestern Africa. The length of dry spells has also changed, with increases \r\nin annual mean consecutive dry days (CDD) in large areas of western, \r\neastern and southern Africa, eastern and southwestern South America, \r\nand Southeast Asia, and decreases across much of North America \r\n(Figure 4.3g). Precipitation extremes have changed in some places where \r\nannual precipitation shows no trend"


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" Some regions such as southern \r\nAfrica and parts of southern South America are seeing increased heavy \r\nprecipitation and longer dry spells. Many regions with changing extremes \r\nare highly populated, such as the Indian sub-continent, Southeast Asia, \r\nEurope and parts of North America, South America and southern Africa \r\n(Figure 4.3h,i). Substantially more people (~709 million) live in regions \r\nwhere annual maximum one-day precipitation has increased than in \r\nregions where it has decreased (~86  million) (medium confidence). \r\nHowever, more people are experiencing longer dry spells than shorter \r\ndry spells: approximately 711 million people live in places where annual \r\nmean CDD is longer than in the 1950s, and ~404 million in places with \r\nshorter CDD (medium confidence) (Figure 4.3i)."


id: 7b8a3dc66697dae05d5b1e04866e9ff6
created_at: 2023-03-16 14:02:17
updated_at: 2023-03-16 14:02:17
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vector_id: 17032
content:
"AR6 WGI (Douville et  al., 2021) concluded that GHG forcing has \r\ndriven increased contrasts in precipitation amounts between wet and \r\ndry seasons and weather regimes over tropical land areas (medium \r\nconfidence), with a detectable precipitation increase in the northern \r\nhigh latitudes (high confidence). GHG forcing has also contributed \r\nto drying in dry summer climates, including the Mediterranean, \r\nsouthwestern Australia, southwestern South America, South Africa \r\nand western North America (medium to high confidence) (Figure 4.3). \r\nAR6 WGI (Seneviratne et al., 2021) also concluded that the frequency \r\nand intensity of heavy precipitation events have likely increased at the \r\nglobal scale over most land regions with good observational coverage. \r\nHeavy precipitation has likely increased on the continental scale \r\nover North America, Europe and Asia"


id: a33d01c0a423974b7ca7580f473b44dd
created_at: 2023-03-16 14:02:17
updated_at: 2023-03-16 14:02:17
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index: climate_gpt_only_giec
vector_id: 23250
content:
" Regional increases in heavy \r\nprecipitation frequency and (or) intensity have been observed with \r\nat least medium confidence for nearly half of the AR6 WGI climatic \r\nregions (Figure 4.3). Human influence, in particular GHG emissions, is \r\nlikely the main driver of the observed global-scale intensification of \r\nheavy precipitation in land regions"


id: d06d68673929037926aa564ccb0e4457
created_at: 2023-03-16 14:02:17
updated_at: 2023-03-16 14:02:17
content_type: text
index: climate_gpt_only_giec
vector_id: 30319
content:
"Large numbers of people live in regions where the annual mean \r\nprecipitation is now 'unfamiliar' compared to the mean and variability \r\nbetween 1891 and 2016 (Figure  4.3c). \"Unfamiliar\" is defined as \r\nthe long-term change being greater than one standard deviation in \r\nthe annual data (Figure  4.3b). In 2020, approximately 498  million \r\npeople lived in unfamiliarly wet areas, where the long-term average \r\nprecipitation is as high as previously seen in only about one in \r\n6 years (medium confidence) (Figure 4.3c). These areas are primarily \r\nin mid and high latitudes (Hawkins et al., 2020). On the other hand, \r\napproximately 163 million people lived in unfamiliarly dry areas, mostly \r\nin low latitudes (medium confidence). Due to high variability over time, \r\nthe signal of long-term change in annual mean precipitation is not \r\ndistinguishable from the noise of variability in many areas (Hawkins \r\net al"


id: ac2682eb4d97a0b7d75fcb7b347f5dfa
created_at: 2023-03-16 14:02:17
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vector_id: 24617
content:
", 2020), implying that the local annual precipitation cannot yet be \r\ndefined 'unfamiliar' by the above definition."


id: 722ed114c07f77f1159d6735eb2a558f
created_at: 2023-03-16 14:02:17
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vector_id: 15590
content:
"Recent studies report global ET increases from the early 1980s to \r\n2009 and 2013 (Table  4.1). Calculations informed by observations \r\nsuggest that ET has increased in most regions, with statistically \r\nsignificant (p<0.05) trends of up to 10 mm yr-2 observed in large parts \r\nof North America and northern Eurasia. Larger increases in ET are \r\nalso observed in several regions, including northeast Brazil, western \r\ncentral Africa, southern Africa, southern India, southern China, and \r\nnorthern Australia. Decreases of around 10 mm yr-2 are reported for \r\nwestern Amazonia and central Africa (Miralles et al., 2014), although \r\nnot across all data sets (Zeng et  al., 2018). In estimates of past \r\nchanges in long-term drying or wetting of the land surface driven by \r\nclimate, uncertainties in ET observations or reconstructions make a \r\nmore substantial contribution to the overall uncertainty than observed \r\nchanges in precipitation (Greve et al., 2014)"


id: 1d4341ebffdacb50e1855d343351528f
created_at: 2023-03-16 14:02:17
updated_at: 2023-03-16 14:02:17
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vector_id: 2045
content:
" Other changes in ET are \r\nalso driven strongly by land cover changes and irrigation (Bosmans \r\net al., 2017)."


id: 4e7c43745513122bb98f8587a6df425e
created_at: 2023-03-16 14:02:17
updated_at: 2023-03-16 14:02:17
content_type: text
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vector_id: 9778
content:
"Regional and global decreasing trends in glacier mass loss are about \r\nlinear until 1990, after which they accelerated, especially in western \r\nCanada, the USA, and the southern Andes (WGMS, 2017). There is a \r\nworldwide growth in the number, total area and total volume of glacial \r\nlakes by around 50% between 1990 to 2018 due to the global increase \r\nin glacier melt rate (Shugar et al., 2020) (Shugar et al., 2020) that can \r\npotentially increase risks of glacial lake outburst floods (GLOFs) with \r\nsignificant negative societal impacts (Ikeda et  al., 2016). A drop in \r\nglacier runoff has happened in the regions where the glaciers have \r\nalready passed their peak water stage, for example, in the Canadian \r\nRocky Mountains, European Alps, tropical Andes and North Caucasus \r\n(Bard et al., 2015; Hock et al., 2019b; Rets et al., 2020)"


id: b13b2a41f8ce15e65b3ab221a9f84d9f
created_at: 2023-03-16 14:02:17
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vector_id: 25390
content:
" There is medium \r\nconfidence that the accelerated melting of glaciers has negatively \r\nimpacted glacier-supported irrigation systems worldwide (Buytaert \r\net al., 2017; Nusser and Schmidt, 2017; Xenarios et al., 2019). Varying \r\nimpacts on hydropower production (Schaefli et al., 2019) and tourism \r\nindustry in some places due to cryospheric changes have also been \r\ndocumented (Hoy et al., 2016; Steiger et al., 2019)."


id: 6c78bdfe8010429f009b0ece4158db40
created_at: 2023-03-16 14:02:17
updated_at: 2023-03-16 14:02:17
content_type: text
index: climate_gpt_only_giec
vector_id: 14690
content:
"Recent studies confirmed with high confidence that snow cover extent \r\ncontinues to decrease across the Northern Hemisphere in all months \r\nof the year (see Douville et al. (2021); Eyring et al. (2021); Fox-Kemper \r\net al. (2021) for more details). From 1922 to 2018, snow cover extent in \r\nthe Northern Hemisphere peaked in the 1950s to 1970s (Mudryk et al., \r\n2020) and has consistently reduced since the end of the 20th century \r\n(Hernandez-Henriquez et  al., 2015; Thackeray et  al., 2016; Mudryk \r\net al., 2017; Beniston et al., 2018; Hammond et al., 2018; Thackeray \r\net al., 2019; Mudryk et al., 2020). The consistently negative snow-mass \r\ntrend of approximately 5 Gt yr-1 in 1981-2018 for all winter-spring \r\nmonths (Mudryk et al., 2020), including 4.6 Gt yr-1 decrease of snow \r\nmass across North America and a negligible trend across Eurasia, \r\nhas been observed (Pulliainen et al., 2020). Negative trends in snow\u0002dominated period duration of 2.0-6"


id: 97ae87eca2954d06e8cf55e45d9ea574
created_at: 2023-03-16 14:02:17
updated_at: 2023-03-16 14:02:17
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vector_id: 21390
content:
"5 weeks per decade was detected \r\nfrom surface and satellite observations during 1971-2014 (Allchin \r\nand Dery, 2017), mainly owing to earlier seasonal snowmelt (Fox\u0002Kemper et  al., 2021). The observed decrease of snow cover metrics \r\n(extent, mass, duration) led to changes in runoff seasonality and has \r\nimpacted water supply infrastructure (Bloschl et al., 2017; Huss et al., \r\n2017), particularly in southwestern Russia, western USA and central \r\nAsia. In these regions, snowmelt runoff accounts for more than 30% \r\nof irrigated water supplies (Qin et  al., 2020). Negative impacts on \r\nhydropower production due to changes in the seasonality of snowmelt \r\nhave also been documented (Kopytkovskiy et al., 2015)."


id: ef270129e3e4c43bc1647df1269870b6
created_at: 2023-03-16 14:02:17
updated_at: 2023-03-16 14:02:17
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vector_id: 35097
content:
"Permafrost changes mainly refer to changes in temperature and active \r\nlayer thickness (ALT) (Hock et  al., 2019b; Fox-Kemper et  al., 2021; \r\nGulev et  al., 2021). Permafrost temperature near the depth of zero \r\nannual temperature amplitude increased globally by 0.29+-0.12degC \r\nduring 2007-2016, by 0.39+-0.15degC in the continuous permafrost \r\nand by 0.20+-0.10degC in the discontinuous permafrost (Biskaborn \r\net al., 2019). Thus, permafrost has been warming during the last 3-4 \r\ndecades (Romanovsky et  al., 2017) with a rate of 0.4degC-1.4degC per \r\ndecade throughout the Russian Arctic, 0.1degC-0.8degC per decade in \r\nAlaska and Arctic Canada during 2007-2016 (Biskaborn et al., 2019) \r\nand 0.1degC-0.24degC per decade in the Tibetan plateau (Wu et al., 2015). \r\nThe ALT has also been increasing in the European and Russian Arctic and \r\nhigh-mountain areas of Eurasia since the mid-1990s (Hock et al., 2019b; \r\nFox-Kemper et al., 2021; Gulev et al., 2021)"


id: 5aef6f4f77797081afb752708311132b
created_at: 2023-03-16 14:02:17
updated_at: 2023-03-16 14:02:17
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vector_id: 11822
content:
" Unfortunately, unlike glaciers \r\nand snow, the lack of in situ observations on permafrost still cannot be \r\ncompensated for by remote sensing. Still, some methodological progress \r\non this front has been happening recently (Nitze et al., 2018)."


id: 451dbdf940200eb2b001082cf6d3c9c3
created_at: 2023-03-16 14:02:17
updated_at: 2023-03-16 14:02:17
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vector_id: 8294
content:
"different basins worldwide, with conclusions on the relative contribution \r\nof climatic and anthropogenic factors sometimes depending on the \r\nmethodology (Dey and Mishra, 2017). Precipitation explains over 80% \r\nof the changes in discharge of large rivers from 1950 to 2010 in northern \r\nAsia and northern Europe, where the impact of human activities is \r\nrelatively limited (Li et al., 2020b). In northwest Europe, precipitation \r\nand evaporation changes explain many observed trends in streamflow \r\n(Vicente-Serrano et al., 2019). In several polar areas in northern Europe \r\n(e.g., Finland), North America (e.g., British Columbia in Canada) and \r\nSiberia, many studies reported increased winter streamflow primarily \r\ndue to climate warming, for instance, more rainfall instead of snowfall \r\nand more glacier runoff in the winter period (e.g., Bonsal et al., 2020) \r\n(Section 4.2.2)"


id: 2167073c91e5c27182e0d18167de08cb
created_at: 2023-03-16 14:02:17
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content:
" A similar phenomenon of the earlier snowmelt runoff is \r\nalso found in North America during 1960-2014 (Dudley et al., 2017). \r\nThus, climate drivers largely explain changes in the average and \r\nmaximum runoff of predominantly snow-fed rivers (Yang et al., 2015a; \r\nBring et al., 2016; Tananaev et al., 2016; Frolova et al., 2017b; Ficklin \r\net al., 2018; Magritsky et al., 2018; Rets et al., 2018)."


id: aa7442f16e640571f3f10224adfd3ca5
created_at: 2023-03-16 14:02:17
updated_at: 2023-03-16 14:02:17
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index: climate_gpt_only_giec
vector_id: 24350
content:
"Shi et  al. (2019) found that in 40 major basins worldwide, both \r\nclimatic and direct human impact contribute to observed flow \r\nchanges to varying degrees. Climate change or variability is the main \r\ncontributor to changes in basin-scale trends for 75% of rivers, while \r\ndirect human effects on streamflow dominate for 25%. However, this \r\ndoes not consider attribution of the climate drivers to anthropogenic \r\nforcing. Using time series of low, mean and high river flows from 7250 \r\nobservatories around the world (1971-2010) and global hydrological \r\nmodels (GHMs) driven by Earth System Model (ESM) simulations with \r\nand without anthropogenic forcing of climate change, Gudmundsson \r\net  al. (2021) also found direct human influence to have a relatively \r\nsmall impact on global patterns of streamflow trends. Gudmundsson \r\net al. (2021) further identified anthropogenic climate change as a causal \r\ndriver of the global pattern of recent trends in mean and extreme river \r\nflow (Figure 4.7)"


id: 7dfcf74c959726c6c55171c3ec17afc2
created_at: 2023-03-16 14:02:17
updated_at: 2023-03-16 14:02:17
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index: climate_gpt_only_giec
vector_id: 17395
content:
" Overall, the sign of observed trends and simulations \r\naccounting for human influence on the climate system was found to \r\nbe consistent for decreased mean flows in western and eastern North \r\nAmerica, southern Europe, northeast South America and the Indian sub\u0002continent, and increased flows in northern Europe. Similar conclusions \r\nwere drawn for low and high flows, except for the Indian sub-continent. \r\nHowever, in some regions, the observed trend was opposite to that \r\nsimulated with anthropogenic climate forcing. Thus, human water and \r\nland use alone did not explain the observed pattern of trends."


id: ae33df5cf4b368c7045d7dee7ada8aa
created_at: 2023-03-16 14:02:17
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vector_id: 24939
content:
"There is high confidence that the frequency and magnitude of river \r\nfloods have changed in the past several decades in some regions \r\nmentioned below (and in WGI 11.5.2; SM4.1) with impacts across \r\nhuman and natural systems (Section  4.3). A global flood database \r\nbased on in situ measurement and satellite remote-sensing during \r\n1985-2015 show that floods have increased 4-fold and 2.5-fold in the \r\ntropics and northern mid-latitudes, respectively (Najibi and Devineni, \r\n2018). Estimates of flood exposure using satellite-derived inundation \r\narea and high-resolution population data showed a 20-24% increase \r\nduring 2000-2018 (Tellman et al., 2021). Analyses of in situ streamflow \r\nmeasurement showed both increases and decreases in the frequency \r\nof river floods for 1960-2010 in Europe (Berghuijs et  al., 2017a; \r\nBloschl et al., 2019a) and the USA (Berghuijs et al., 2017a), an overall \r\nincrease in China, Brazil and Australia (Berghuijs et  al"


id: edfca7e63f2a02f9520cc28bba051880
created_at: 2023-03-16 14:02:17
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vector_id: 34920
content:
", 2017a) but \r\ndecrease in some areas in the Mediterranean (Tramblay et al., 2019) \r\nand southern Australia (Ishak et al., 2013; Do et al., 2017). Warming \r\nin the last 40-60 years has led to a 1-10-d earlier per decade spring \r\nflood occurrence depending on the location (the most frequent being \r\n2-4 d per decade) (high confidence) (Yang L. et  al., 2015; Bloschl \r\net al., 2017; Dudley et al., 2017; Solander et al., 2017; Rokaya et al., \r\n2018; Kireeva et al., 2020)."


id: 5ec4f530914c2ca8b991f7e7528c36b0
created_at: 2023-03-16 14:02:17
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vector_id: 12450
content:
"Between 1970 to 2019, 44% of all disasters and 31% of all economic \r\nlosses were flood related (WMO, 2021). Observed flood risks changes \r\nin recent decades are often caused by human factors such as increased \r\nurbanisation and population growth rather than climate change \r\nalone (Tramblay et al., 2019). There is medium confidence that flood \r\nvulnerability varies among various regions and countries (Jongman \r\net al., 2012; Scussolini et al., 2016; Tanoue et al., 2016) (Figure 4.8), \r\nreflecting differences in GDP, severity and characteristics of hazard and \r\npolitical and social conditions (Rufat et al., 2015). Flood vulnerability \r\nhas decreased with economic development in many regions, while \r\nincreased exposure has elevated risk in some places (Mechler, 2016; \r\nTanoue et al., 2016). Global annual mean expected damage considering \r\nthe current flood protection standard is estimated to be USD 54 million \r\nunder the climate of 1976-2005 and unevenly distributed (Alfieri et al"


id: 5fef445db6f6fa97dd495466d1fab01b
created_at: 2023-03-16 14:02:17
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vector_id: 12676
content:
", \r\n2017). Similar estimation using different models shows an increase of \r\nflood exposure in the past (USD 31 million for 1971-1990 and USD \r\n45 million for 1991-2010 without population change as fixed in 2010) \r\n(Tanoue et al., 2016) (Section 4.7.5)."


id: 3603f0b48b63edf20696b7492d0a1a0c
created_at: 2023-03-16 14:02:17
updated_at: 2023-03-16 14:02:17
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index: climate_gpt_only_giec
vector_id: 5902
content:
"The link between rainfall and flooding is complex. While observed \r\nincreases in extreme precipitation have increased the frequency and \r\nmagnitude of pluvial floods and river floods in some regions, floods \r\ncould decrease in some regions due to other factors. These factors \r\ncould include soil wetness condition, cryospheric change, land cover \r\nchange and river system management, adaptation measures or water \r\nusage within the river basin (WGI FAQ8.2). For example, in the USA \r\nand Europe, a study indicated that major (e.g., 25-100-year return \r\nperiod) floods did not show significant long-term trends (Hodgkins \r\net  al., 2019). Nevertheless, anthropogenic climate change increased \r\nthe likelihood of a number of major heavy precipitation events and \r\nfloods that resulted in disastrous impacts in southern and eastern \r\nAsia, Europe, North America and South America (Table  4.3) (high \r\nconfidence). Davenport et al"


id: 25ba379a7ce8c222d2c68c69a6e1f837
created_at: 2023-03-16 14:02:17
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content:
" (2021) demonstrated that anthropogenic \r\nchanges in precipitation extremes had contributed one third of the \r\ncost of flood damages (from 1988 to 2017) in the USA. Anthropogenic \r\nclimate change has altered 64% (eight out of 22 events increased, \r\neight decreased) of floods events with significant losses and damages \r\nduring 2010-2013 (Hirabayashi et  al., 2021a). Gudmundsson et  al. \r\n(2021) attributed observed change in extreme river flow trends to \r\nanthropogenic climate change (Section  4.2.3). Although there is \r\ngrowing evidence on the effects of anthropogenic climate change \r\non each event, given the relatively poor regional coverage and high \r\nmodel uncertainty, there is low confidence in the attribution of human\u0002induced climate change to flood change on the global scale."


id: 1b3b78ac85422122670f319b1724714b
created_at: 2023-03-16 14:02:17
updated_at: 2023-03-16 14:02:17
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index: climate_gpt_only_giec
vector_id: 1749
content:
"When hazard, vulnerability and exposure are considered together, \r\ndrought risk is lower for sparsely populated regions, such as tundra \r\nand tropical forests, and higher for populated areas and intensive \r\ncrop and livestock farming regions, such as southern and central Asia, \r\nsoutheastern South America, central Europe and the southeastern \r\nUSA (Figure  4.9). Dynamics in exposure and vulnerability are rarely \r\naddressed (Jurgilevich et al., 2017; Hagenlocher et al., 2019). Quantifying \r\neconomic vulnerability to drought in terms of damages as a percentage \r\nof exposed GDP, Formetta and Feyen (2019) show a disproportionate \r\nburden of drought impact on low-income countries, but with a clear \r\ndecrease in global economic drought vulnerability between 1980-1989 \r\nand 2007-2016, including a convergence between lower-income and \r\nhigher-income countries due to stronger vulnerability reduction in \r\nless-developed countries"


id: 8a76176415c8a120453d43f1e132c603
created_at: 2023-03-16 14:02:17
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vector_id: 19323
content:
" Nevertheless, during 2007-2016, economic \r\nvulnerability to drought was twice as high in lower-income countries \r\ncompared to higher-income countries (Formetta and Feyen, 2019)."


id: 1a47cb16cb25c6336d4312b27571b271
created_at: 2023-03-16 14:02:17
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vector_id: 1603
content:
"In addition, there is high confidence in anthropogenic influence on \r\nincreased meteorological drought in southwestern Australia and \r\nmedium confidence that recent drying and severe droughts in southern \r\nAfrica and southwestern South America can be attributed to human \r\ninfluence. Increased agricultural/ecological and (or) meteorological and \r\n(or) hydrological drought is also seen with either medium confidence \r\nor high confidence in the trend but with low confidence on attribution \r\nto anthropogenic climate change in western, northeastern and central \r\nAfrica; central, eastern and southern Asia; eastern Australia; southern \r\nand northeastern South America and the South American monsoon \r\nregion; and western and central Europe"


id: 43073ee17f829614e4cd392fb6061ee4
created_at: 2023-03-16 14:02:17
updated_at: 2023-03-16 14:02:17
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index: climate_gpt_only_giec
vector_id: 7941
content:
" Finally, decreased drought in \r\none or more categories is seen with medium confidence in western \r\nand eastern Siberia; northern and central Australia; southeastern South \r\nAmerica; central North America and northern Europe, but with low \r\nconfidence in attribution to anthropogenic influence, except in northern \r\nEurope, where anthropogenic influence on decreased meteorological \r\ndrought is assessed with medium confidence."


id: b18f5d9ed5c4b52962c1c85bc941340b
created_at: 2023-03-16 14:02:17
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vector_id: 25433
content:
"Globally, groundwater use has societal and economic benefits, providing \r\na critical buffer against precipitation variability. Groundwater irrigation \r\nhas ensured food security, livelihood support and poverty alleviation, \r\nfor example, in India (Sekhri, 2014), Bangladesh (Salem et al., 2018) \r\nand sub-Saharan Africa (Taylor et al., 2013a; Cuthbert et al., 2019b). \r\nGroundwater is a safe drinking water source during natural hazard\u0002induced disasters (Richts and Vrba, 2016). However, groundwater over\u0002exploitation leads to the attenuation of societal benefits, including \r\nreduced agricultural production (Asoka and Mishra, 2020; Jain et al., \r\n2021), decrease in adaptive capacity of communities (Blakeslee et al., \r\n2020) and water quality deterioration (Mas-Pla and Mencio, 2019). \r\nLoss of traditional water systems based on groundwater, such as \r\nfoggara in Tunisia (Mokadem et al"


id: 9c5ae468b56120eebe5958d86fe3d5bd
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vector_id: 22152
content:
", 2018), qanat in Pakistan (Mustafa \r\nand Usman Qazi, 2008), aflaj in Oman (Remmington, 2018) and spring \r\nboxes in the Himalayas (Kumar and Sen, 2018), also leads to loss of \r\ncultural values for local communities."


id: 77ee1a50fe9cc3d8c366a4524af326d5
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vector_id: 16430
content:
"(Shamsudduha and Taylor, 2020) of GRACE satellite measurements \r\n(2002-2016) for the 37 world's large aquifer systems reveals that \r\ntrends in groundwater storage are mostly nonlinear and declines are \r\nnot secular (high confidence). There are strong statistical associations \r\nbetween changes in groundwater storage and extreme annual \r\nprecipitation from 1901 to 2016 in the Great Artesian Basin (Australia) \r\nand the California Central Valley aquifer (USA). Groundwater recharge \r\nof high magnitudes can be generated from intensive precipitation \r\nevents. On the other hand, recharge can become more episodic, mostly \r\nin arid to semiarid locations (robust evidence, medium agreement). For \r\nexample, in central Tanzania, seven rainfall events between 1955 and \r\n2010 generated 60% of total recharge (Taylor et al., 2013b). Similarly, \r\nin southern India (Asoka et  al., 2018) and the southwestern USA \r\n(Thomas et al"


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vector_id: 17195
content:
", 2016), focused recharge via losses from ephemeral river \r\nchannels, overland flows, and floodwaters is documented (Cuthbert \r\net al., 2019b)."


id: e1959d384aaffe7bd7f9c5b19af0d082
created_at: 2023-03-16 14:02:17
updated_at: 2023-03-16 14:02:17
content_type: text
index: climate_gpt_only_giec
vector_id: 32984
content:
"Groundwater-dependent ecosystems (GDEs), such as terrestrial \r\nwetlands, stream ecosystems and estuarine and marine ecosystems \r\n(Klove et al., 2014), support wetlands and biodiversity, provide water \r\nsupply and baseflows to rivers, offer recreational services and help \r\ncontrol floods (Rohde et al., 2017). Globally, 10-23% of the watersheds \r\nhave reached the environmental flow limits due to groundwater \r\npumping (de Graaf et al., 2019). A recent study of 4.2 million wells \r\nacross the USA shows that induced groundwater recharge in nearly \r\ntwo thirds of these wells could reduce stream discharges, thereby \r\nthreatening GDEs (Jasechko et al., 2021). Work (2020) found reduced \r\nspring flow due to increased groundwater abstraction in 26 out of 56 \r\nsprings studied in Florida (USA)"


id: a0934d57b73ba543077f0cf9698b0a5e
created_at: 2023-03-16 14:02:17
updated_at: 2023-03-16 14:02:17
content_type: text
index: climate_gpt_only_giec
vector_id: 22800
content:
" GDEs in semiarid and arid regions \r\ntend to have much longer groundwater response times and may be \r\nmore resilient to climate change than those in humid areas where \r\ngroundwater occurrence is mostly at shallow levels (Cuthbert et al., \r\n2019a; Opie et al., 2020). However, groundwater depletion impacts on \r\nthe full range of ecosystem services remain understudied (Bierkens and \r\nWada, 2019)."


id: 9908bbd7cc8b8cb14025328920fce356
created_at: 2023-03-16 14:02:17
updated_at: 2023-03-16 14:02:17
content_type: text
index: climate_gpt_only_giec
vector_id: 21593
content:
"aesthetic value, compromising recreational activities, reducing tourism \r\nand property values and creating challenges for management and \r\ndrinking water treatment (Eves and Wilkinson, 2014; Khan et al., 2015; \r\nWalters et al., 2015).\r\nBetween 2000 and 2010, ~10% of the global population faced \r\nadverse water quality issues (van Vliet et al., 2021). Adverse drinking \r\nwater quality has been associated with extreme weather events \r\nin countries located in Asia, Africa and South and North America \r\n(Jagai et  al., 2015; Levy et  al., 2016; Huynh and Stringer, 2018; \r\nLeal Filho et al., 2018; Abedin et al., 2019) (medium evidence, high \r\nagreement). Dilution factors in 635 of 1049 US streams fell extremely \r\nlow during drought conditions. Additionally, the safety threshold for \r\nendocrine-disrupting compound concentration exceeded in roughly \r\na third of streams studied (Rice and Westerhoff, 2017)"


id: 8359c46c802a5f6687b3e9890a1b2e15
created_at: 2023-03-16 14:02:17
updated_at: 2023-03-16 14:02:17
content_type: text
index: climate_gpt_only_giec
vector_id: 18190
content:
" Natural acid \r\nrock drainage, which can potentially release toxic substances, has \r\nexperienced intensification in an alpine catchment of the Central \r\nPyrenees due to climate change and severe droughts in the last \r\ndecade. River length affected by natural acid drainage increased \r\nfrom 5 km in 1945 to 35 km in 2018 (Zarroca et al., 2021). Threefold \r\nincreases in contaminants and fivefold increases in nutrients have \r\nbeen observed in water sources after wildfires (Khan et al., 2015). Due \r\nto permafrost thawing, the concentration of major ions, especially \r\nSO4\r\n2- in two high Arctic lakes, has rapidly increased up to 500% and \r\n340% during 2006-2016 and 2008-2016, respectively (Roberts et al., \r\n2017). The exports of dissolved organic carbon (DOC), particulate \r\norganic carbon and mercury in six Arctic rivers were reported to \r\nincrease with significant deepening of active layers caused by climate \r\nwarming during 1999-2015 (Mu et al., 2019)"


id: 13d5ab0c9394a1c67e66d5c85f3c970b
created_at: 2023-03-16 14:02:17
updated_at: 2023-03-16 14:02:17
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index: climate_gpt_only_giec
vector_id: 625
content:
" Sustained warming in \r\nLake Tanganyika in Zambia during the last ~150 years reduced lake \r\nmixing, which has depressed algal production, shrunk the oxygenated \r\nbenthic habitat by 38% and further reduced fish and mollusc yield \r\n(Cohen et  al., 2016). From 1994 to 2010, coastal benthos at King \r\nGeorge Island in Antarctica have observed a remarkable shift primarily \r\nlinked to ongoing climate warming and the increased sediment runoff \r\ntriggered by glacier retreats (Sahade et al., 2015). The recovery time \r\nof macroinvertebrates from floods was found longer in cases of pre\u0002existing pollution problems (Smith et al., 2019a)."


id: 9386849487cee4fcd900d971daa88aab
created_at: 2023-03-16 14:02:17
updated_at: 2023-03-16 14:02:17
content_type: text
index: climate_gpt_only_giec
vector_id: 20725
content:
"Climate change impacts soil erosion and sedimentation rates both \r\ndirectly from increasing rainfall or snowmelt intensity (Vanmaercke \r\net al., 2014; Polyakov et al., 2017; Diodato et al., 2018; Golosov et al., \r\n2018; Li et al., 2020a; Li et al., 2020b) and indirectly from increasing \r\nwildfires (Gould et al., 2016; Langhans et al., 2016; DeLong et al., 2018), \r\npermafrost thawing (Schiefer et al., 2018; Lafreniere and Lamoureux, \r\n2019; Ward Jones et al., 2019) and vegetation cover changes (Micheletti \r\net al., 2015; Potemkina and Potemkin, 2015; Carrivick and Heckmann, \r\n2017; Beel et  al., 2018). In addition, accelerated soil erosion and \r\nsedimentation have severe societal impacts through land degradation, \r\nreduced soil productivity and water quality (Section 4.2.7), increased \r\neutrophication and disturbance to aquatic ecosystems (Section 4.3.5), \r\nsedimentation of waterways and damage to infrastructure (Graves et al., \r\n2015; Issaka and Ashraf, 2017; Schellenberg et al"


id: f2053dcba5caee35379b8a1e8a217a8d
created_at: 2023-03-16 14:02:17
updated_at: 2023-03-16 14:02:17
content_type: text
index: climate_gpt_only_giec
vector_id: 35607
content:
"In the largest river basin of the Colombian Andes, regional climate change \r\nand land use activities (ploughing, grazing and deforestation) caused \r\na 34% erosion rate increase over 10  years, with the anthropogenic \r\nsoil erosion rate exceeding the climate-driven erosion rate (Restrepo \r\nand Escobar, 2018). Sedimentation increases due to soil erosion in \r\nmountainous regions burned by wildfires, as a result of warming and \r\naltered precipitation, is documented with high confidence in the USA \r\n(Gould et al., 2016; DeLong et al., 2018), Australia (Nyman et al., 2015; \r\nLanghans et al., 2016), China (Cui et al., 2014) and Greece (Karamesouti \r\net al., 2016) and can potentially damage downstream aquatic ecosystems \r\n(Section 4.3.5) and water quality (Section 4.2.7) (Cui et al., 2014; Murphy \r\net al., 2015; Langhans et al., 2016) (medium confidence)"


id: cbc32142b62aa1baa6e9923d3949f6d
created_at: 2023-03-16 14:02:17
updated_at: 2023-03-16 14:02:17
content_type: text
index: climate_gpt_only_giec
vector_id: 29599
content:
" In Australia, for \r\ninstance, sediment yields from post-fire debris flows (113-294 t ha-1) \r\nare 2-3 orders of magnitude higher than annual background erosion \r\nrates from undisturbed forests (Nyman et al., 2015). The positive trend \r\nin sediment yield in small ponds in the semiarid southwestern USA over \r\nthe last 90 years was not entirely related to the rainfall or runoff trends, \r\nbut was a result of complex interaction between long-term changes in \r\nvegetation, soil and channel networks (Polyakov et al., 2017)."


id: cb2adaf0bdeff20e7c81d5b7d326e326
created_at: 2023-03-16 14:02:17
updated_at: 2023-03-16 14:02:17
content_type: text
index: climate_gpt_only_giec
vector_id: 29522
content:
"Regional climate changes (precipitation decrease) and human \r\nactivities (landscape engineering, terracing, large-scale vegetation \r\nrestoration, soil conservation) over the Loess Plateau (China) caused \r\na distinct stepwise reduction in sediment loads from the upper-middle \r\nreach of the Yellow River, with 30% of the change related to climate \r\nchange (Tian et al., 2019). Substantial increases in sediment flux were \r\nidentified on the Tibetan Plateau (Li et al., 2020a; Li et al., 2021a), for \r\nexample, the sediment load from the Tuotuohe headwater increased by \r\n135% from 1985-1997 to 1998-2016, mainly due to climate change \r\n(Li et al., 2020a). In 1986-2015, the sedimentation rate in dry valley \r\nbottoms of the Southern Russian Plain was two-2-5 times lower than \r\nin 1963-1986 due to the warming-induced surface runoff reduction \r\nduring spring snowmelt (Golosov et  al., 2018)"


id: 3fc92fa9433a3a2449ae08ea9e7160ea
created_at: 2023-03-16 14:02:17
updated_at: 2023-03-16 14:02:17
content_type: text
index: climate_gpt_only_giec
vector_id: 7417
content:
" Declining erosion \r\ntrends are primarily associated with soil conservation management \r\nin northern Germany (Steinhoff-Knopp and Burkhard, 2018) and \r\nreforestation in southwestern China (Zhou et al., 2020)."


id: b0a4911ed095a633f996838db21ebf43
created_at: 2023-03-16 14:02:17
updated_at: 2023-03-16 14:02:17
content_type: text
index: climate_gpt_only_giec
vector_id: 25311
content:
"Europe (Vanmaercke et al., 2014) and northern Africa (Achite and Ouillon, \r\n2016). Still, such correlation is yet to be found for the other European \r\nrivers (Vanmaercke et  al., 2015). Increased sediment and particulate \r\norganic carbon fluxes in the Arctic regions are caused by permafrost \r\nwarming (Schiefer et al., 2018; Lafreniere and Lamoureux, 2019; Ward \r\nJones et al., 2019). Potemkina and Potemkin (2015) demonstrate that \r\nregional warming and permafrost degradation have contributed to an \r\nincreased forested area over the last 40-70 years, reducing soil erosion \r\nin eastern Siberia. The sediment dynamics of small rivers in the eastern \r\nItalian Alps, depending on extreme floods, is sensitive to climate change \r\n(Rainato et  al., 2017). In the northeastern Italian Alps, precipitation \r\nchange during 1986-2010 affected soil wetness conditions, influencing \r\nsediment load (Diodato et  al., 2018)"


id: d0a645c93987b21602205f712c7e4a0e
created_at: 2023-03-16 14:02:17
updated_at: 2023-03-16 14:02:17
content_type: text
index: climate_gpt_only_giec
vector_id: 30355
content:
" Regional warming in northern \r\nAfrica (Algeria) dramatically changed river streamflow and increased \r\nsediment load over four decades (84% more every decade compared to \r\nthe previous) (Achite and Ouillon, 2016)."


id: 8252cace10909239c6faae89084907fd
created_at: 2023-03-16 14:02:17
updated_at: 2023-03-16 14:02:17
content_type: text
index: climate_gpt_only_giec
vector_id: 18029
content:
"Globally, 23% of croplands are irrigated, providing 34% of global calorie \r\nproduction. Of these lands, 68% experience blue water scarcity at the \r\nleast one month yr-1 and 37% up to five months yr-1. Such agricultural \r\nwater scarcity is experienced in mostly drought-prone areas in low\u0002income countries (Rosa et al., 2020a). Approximately three quarters of \r\nthe global harvested areas (~454 million hectares) experienced drought\u0002induced yield losses between 1983 and 2009, and the cumulative \r\nproduction losses corresponded to USD 166 billion (Kim et al., 2019). \r\nGlobally, droughts affected both harvested areas and yields, with a \r\nreported cereal production loss of 9-10% due to weather extremes \r\nbetween 1964 and 2007. Yield losses were greater by about 7% during \r\nrecent droughts (1985-2007) due to greater damage--reducing \r\nharvested area--compared to losses from earlier droughts (1964-1984), \r\nwith 8-11% greater losses in high-income countries than in low-income \r\nones (Lesk et al"


id: a3946c38781a953ee52f9fd3363c1820
created_at: 2023-03-16 14:02:17
updated_at: 2023-03-16 14:02:17
content_type: text
index: climate_gpt_only_giec
vector_id: 23299
content:
", 2016). Globally, between 1961 and 2006, it has been \r\nestimated that 25% yield loss occurred, with yield loss probability \r\nincreasing by 22% for maize, 9% for rice and 22% for soybean under \r\ndrought conditions (Leng and Hall, 2019). Mean climate and climate \r\nextremes are responsible for 20-49% of yield anomalies variance, with \r\n18-45% of this variance attributable to droughts and heatwaves (Vogel \r\net al., 2019). Drought has been singled out as a major driver of yield \r\nreductions globally (high confidence) (Lesk et  al., 2016; Meng et  al., \r\n2016; Zipper et al., 2016; Anderson et al., 2019; Leng and Hall, 2019)."


id: 3f8fd13c0f7aedee3e3cb9cacdcb8b56
created_at: 2023-03-16 14:02:17
updated_at: 2023-03-16 14:02:17
content_type: text
index: climate_gpt_only_giec
vector_id: 7386
content:
"Yields of major crops in semiarid regions, including the Mediterranean, \r\nsub-Saharan Africa, South Asia and Australia, are negatively affected \r\nby precipitation declines in the absence of irrigation (Iizumi et  al., \r\n2018; Ray et al., 2019), but this trend is less evident in wetter regions \r\n(Iizumi et al., 2018). Precipitation and temperature changes reduced \r\nglobal mean yields of maize, wheat and soybeans by 4.1, 1.8 and \r\n4.5%, respectively (Iizumi et  al., 2018). Of the global rice yield \r\nvariability of ~32%, precipitation variability accounted for a larger \r\nshare in drier South Asia than in wetter East and Southeast Asia \r\n(Ray et al., 2015). Between 1910 and 2014 agro-climatic conditions \r\nbecame more conducive to maize and soybean yield growth in the \r\nAmerican Midwest due to increases in summer precipitation and \r\ncooling due to irrigation (Iizumi and Ramankutty, 2016; Mueller et al., \r\n2016) (Box 4.3)"


id: 484c4145281474eacfbc57b3ce9672
created_at: 2023-03-16 14:02:17
updated_at: 2023-03-16 14:02:17
content_type: text
index: climate_gpt_only_giec
vector_id: 8747
content:
" In Australia, between 1990 and 2015, the negative \r\neffects of reduced precipitation and rising temperature led to yield \r\nlosses, but yield losses were partly avoided because of elevated \r\nCO2 atmospheric concentration and technological advancements \r\n(Hochman et  al., 2017a). Overall, temperature-only effects are \r\nstronger in wetter regions like Europe and East and Southeast Asia, \r\nand precipitation-only effects are stronger in drier regions (Iizumi \r\net al., 2018; Ray et al., 2019) (medium evidence, high agreement). \r\nIn Asia, the gap between rain-fed and irrigated maize yield widened "


id: f588c4e2879e545afff024165e0f0979
created_at: 2023-03-16 14:02:17
updated_at: 2023-03-16 14:02:17
content_type: text
index: climate_gpt_only_giec
vector_id: 36154
content:
"from 5% in the 1980s to 10% in the 2000s (Meng et al., 2016). In \r\nNorth America, yields of maize and soybeans have increased (1958-\r\n2007), yet meteorological drought has been associated with 13% of \r\noverall yield variability. However, yield variability was not a concern \r\nwhere irrigation is prevalent (Zipper et  al., 2016). However, when \r\nwater scarcity has reduced irrigation, yields have been negatively \r\nimpacted (Elias et  al., 2016). In Europe, yields have been affected \r\nnegatively by droughts (Beillouin et  al., 2020), with losses tripling \r\nbetween 1964 and 2015 (Bras et al., 2021). In West Africa, between \r\n2000 and 2009, drought, among other altered climate conditions, \r\nled to millet and sorghum yield reductions between 10 and 20% \r\nand 5 and 15%, respectively (Sultan et al., 2019). Between 2006 and \r\n2016, droughts contributed to food insecurity and malnutrition in \r\nnorthern, eastern and southern Africa, Asia and the Pacific"


id: 23ab1b5509146479494ac91a088ef27b
created_at: 2023-03-16 14:02:17
updated_at: 2023-03-16 14:02:17
content_type: text
index: climate_gpt_only_giec
vector_id: 3062
content:
" In 36% of \r\nthese nations--mainly in Africa--where severe droughts occurred, \r\nundernourishment increased (Phalkey et  al., 2015; Cooper et  al., \r\n2019). An attribution study showed that anthropogenic emissions \r\nincreased the chances of October-December droughts over the \r\nregion by 1.4-4.3 times and resulted in below-average harvests in \r\nZambia and South Africa (Nangombe et  al., 2020). Root crops, a \r\nstaple in many tropics and subtropical countries, and vegetables are \r\nparticularly prone to drought, leading to smaller fruits or crop failure \r\n(Daryanto et al., 2017; Bisbis et al., 2018). Livestock production has \r\nalso been affected by changing seasonality, increasing frequency of \r\ndrought, rising temperatures and vector-borne diseases and parasites \r\nthrough changes in the overall availability, as well as reduced \r\nnutritional value, of forage and feed crops (Varadan and Kumar, \r\n2014; Naqvi et al., 2015; Zougmore et al., 2016; Henry et al., 2018; \r\nGodde et al"


id: 5a061a3fb000ddc4500c2a8613c054f1
created_at: 2023-03-16 14:02:17
updated_at: 2023-03-16 14:02:17
content_type: text
index: climate_gpt_only_giec
vector_id: 11677
content:
"Floods have led to harvest failure and crop and fungal contamination \r\n(Liu et  al., 2013; Uyttendaele et  al., 2015). Globally, between 1980 \r\nand 2018, excess soil moisture has reduced rice, maize, soybean and \r\nwheat yields between 7 and 12% (Borgomeo et al., 2020). Changes \r\nin groundwater storage and availability, which are affected by the \r\nintensity of irrigated agriculture, also negatively impacted crop yields \r\nand cropping patterns (Section 4.2.6, Box 4.3, 4.7.2). Moreover, extreme \r\nprecipitation can lead to increased surface flooding, waterlogging, \r\nsoil erosion and susceptibility to salinisation (high confidence). For \r\nexample, in Bangladesh, in March and April 2017, floods affected \r\n220,000 ha of a nearly harvest-ready summer paddy crop and resulted \r\nin almost a 30% year-on-year increase in paddy prices"


id: 9252ae1067838adf777bba0acfb305a7
created_at: 2023-03-16 14:02:17
updated_at: 2023-03-16 14:02:17
content_type: text
index: climate_gpt_only_giec
vector_id: 20543
content:
" An attribution \r\nstudy of those pre-monsoon extreme rainfall events in Bangladesh \r\nconcluded that anthropogenic climate change doubled the likelihood \r\nof the extreme rainfall event (Rimi et  al., 2019). Moreover, floods, \r\nextreme weather events and cyclones have led to animal escapes and \r\ninfrastructure damage in aquaculture (Beveridge et al., 2018; Islam and \r\nHoq, 2018; Naskar et al., 2018; Lebel et al., 2020) (see Section 5.9.1)."


id: 35da3e8b8d6a531b7d182b32d09056e4
created_at: 2023-03-16 14:02:17
updated_at: 2023-03-16 14:02:17
content_type: text
index: climate_gpt_only_giec
vector_id: 5885
content:
"Literature since AR5 confirms that temperature, precipitation and \r\nextreme weather events are linked to increased incidence and \r\noutbreaks of water-related and neglected tropical diseases (Colon\u0002Gonzalez et al., 2016; Levy et al., 2016; Azage et al., 2017; Harp et al., \r\n2021) (high confidence). For example, the rainy season in Senegal has \r\nbeen associated with an 84% increase in relative risk of childhood \r\ndiarrhoea, and an additional wet day per week was associated with \r\nup to 2% increases in diarrhoeal disease in Mozambique (Thiam et al., \r\n2017; Horn et al., 2018). In Ecuador, increases of 1.5 cases of diarrhoea \r\nper 1000 were associated with heavy rainfall after dry periods, while \r\na decrease of one case per 1000 was associated with heavy rain after \r\nwet periods (Carlton et al., 2014). Floods have been associated with \r\n22% increases in relative risk of diarrhoea in China (Liu et al., 2018c)"


