When we think of mangrove forests, seagrass meadows and saltmarshes, we don’t immediately think of shark habitats. But the first global review of links between large marine animals (megafauna) and coastal wetlands is challenging this view – and how we might respond to the biodiversity crisis.
Mangrove forests, seagrass meadows and saltmarshes support rich biodiversity, underpin the livelihoods of more than a billion people worldwide, store carbon, and protect us from extreme weather events.
We know marine megafauna also use these habitats to live, feed and breed. Green turtles and manatees, for instance, are known to eat seagrass, and dolphins hunt in mangroves.
But new associations are also being discovered. The bonnethead shark – a close relative of hammerheads – was recently found to eat and digest seagrass.
The problem is that we’re losing these important places. And until now, we’ve underestimated how important they are for large, charismatic and ecologically important marine animals.
Counting wetland megafauna
Today our review of the connections between marine megafauna and vegetated coastal wetlands was published in the journal Trends in Ecology and Evolution. As it turns out, far more megafauna species use coastal wetlands than we thought.
Before our review, the number of marine megafauna species known to use these habitats was 110, according to the International Union for Conservation of Nature (IUCN) Red List, which assesses species’ conservation status.
We identified another 64 species from 340 published studies, bringing the total number to 174 species. This means 13% of all marine megafauna use vegetated coastal wetlands.
We predominantly documented these habitat associations by electronic tracking, direct observation or from analysing stomach contents or chemical tracers in animal tissues.
Less commonly, acoustic recordings and animal-borne video studies – strapping a camera on the back of turtle, for instance – were used.
Deepening our understanding of how species use their habitats
In recent weeks, the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) released a damming assessment of humanity’s stewardship of the natural world. Up to 1 million species were reported to be facing extinction within decades.
We need to dramatically change how we relate to and engage with species and their habitats, if we are to fix this problem.
But the question is, how can we make global change real, relevant and feasible at local and regional scales? And, as the international community rises to this challenge, what information is needed to support such efforts?
Our study suggests a critical first step to addressing the global biodiversity crisis is to deepen our understanding of links between species and their habitats. We also need to elevate how the evidence is used to both assess extinction risk and prioritise, plan and deliver conservation actions.
More than half of all coastal wetlands have been lost globally and the rest are at risk from a range of serious threats, including deforestation. There is an urgent need to limit and reverse the loss of coastal wetlands to stop biodiversity loss, protect communities and tackle climate change.
Targeting places where high rates of mangrove loss intersect with threatened megafauna could lead to more efficient and effective conservation outcomes. Southeast Asia, Mexico and northern Brazil are such places.
In Southeast Asia, for example, the world’s largest mangrove forest is losing trees at a rate far exceeding global averages, largely due to aquaculture and agriculture. This is threatening the critically endangered green sawfish, which relies on these mangrove habitats.
Habitats should always be considered in assessments
The IUCN Red List assesses the extinction risk for almost 100,000 species. It provides comprehensive information on global conservation statuses, combining information on population sizes, trends and threats.
The wealth of data collected during species’ assessments, including habitat associations of threatened species, is one of the Red List’s most valuable features.
But our study shows many known associations are yet to be included. And for more than half of the assessments for marine megafauna, habitat change is yet to be listed as a threat.
This is concerning because assessments that overlook habitat associations or lack sufficient detail, may not allow conservation resources be directed at the most effective recovery measures.
But it’s also important to note habitat associations have varying strengths and degrees of supporting evidence. For example, a population of animals shown to consume substantial amounts of seagrass is clearly a stronger ecological link than an individual simply being observed above seagrass.
In our paper, we propose a simple framework to address these issues, by clarifying habitat associations in conservation assessments. Ideally, these assessments would include the following:
- list all habitat types the species is known to associate with
- indicate the type of association (occurrence, grazing, foraging or breeding)
- cite the source of supporting evidence
- provide an estimate of the level of habitat dependence.
Data for decision making
Habitat loss is accelerating a global extinction crisis, but the importance of coastal habitats to marine megafauna has been significantly undervalued in assessments of extinction risk.
We need to strive to protect remaining coastal wetland habitats, not only for their ecological role, but also for their economic, social and cultural values to humans. We can do this by strengthening how we use existing scientific data on habitat associations in species assessments and conservation planning.
Michael Sievers, Research Fellow, Global Wetlands Project, Australia Rivers Institute, Griffith University; Rod Connolly, Professor in Marine Science, Griffith University, and Tom Rayner, Science Communicator, Griffith University
Predicting when a volcano will next blow is tricky business, but lessons we learned from one of Hawaii’s recent eruptions may help.
Kīlauea, on the Big Island of Hawai’i, is probably the best understood volcano on Earth. That’s thanks to monitoring and gathered information that extends back to the formation of the Hawaiian Volcano Observatory in 1912.
The volcano is also subject to the world’s most technologically advanced geophysical monitoring network.
From the skies, satellites collect data that show the changing topography of the volcano as magma moves throughout the internal magma plumbing system. Satellites also look at the composition of volcanic gases.
From the ground, volcanologists use a number of highly sensitive chemical and physical tools to further understand the structure of that magma plumbing system. This helps to study the movement of magma within the volcano.
Earthquakes and vibrations
A lynch pin of volcano monitoring is seismicity – how often, where and when earthquakes occur. Magma movement within the volcano triggers earthquakes, and putting together the data on their location (a technique known as triangulation) tracks the path of magma underground.
A newer technique, seismic interferometry, uses vibrations of energy from ocean waves hitting the distant shorelines that then travel through the volcano.
Changes in the speed of these vibrations help us map the 3D footprint of the volcano’s magma plumbing system. We can then detect when, and in some cases how, the magma plumbing system is changing.
This monitoring provides the “pulse” of the volcano during times of inactivity – a baseline from which to detect change during volcanic unrest. This proved invaluable for early warning, and the prediction of where and when, of the eruption of Kīlauea on May 3, 2018.
The “pulse” of Kīlauea includes cycles of volcano inflation (bulging) and deflation (contraction) as magma moves into and out of the storage region at the summit of the volcano.
The speeds of vibrations travelling through the volcano are predictable during observations of inflation/deflation cycles. When the volcano bulges, the vibrations travel faster through the volcano as rock and magma is compressed. When the volcano contracts these speeds decrease.
We describe this relationship between the two sets of data – the bulging/contraction and the faster/slower speed of vibrations – as coupled.
Compared to our baseline, we saw the coupled data shift 10 days before the Kīlauea eruption on May 3. That told scientists the magma plumbing system had changed in a significant way.
The volcano was bulging due to the buildup of pressure inside the magma chamber, but the seismic waves were slowing down quite dramatically, instead of speeding up.
Our interpretation of this data was that the summit magma chamber was not able to sustain the pressure from an increasing magma supply – the bulge was too big. Rock material started to break around the summit magma chamber.
Breakage of the rocks perhaps then led to changes of the summit magmatic system so that more magma could more easily arrive at the eruption site about 40km away.
As well as Kīlauea, such coupled data sets are regularly collected, investigated and interpreted in terms of magma transport at other volcanoes globally. Sites include Piton de la Fournaise on Reunion Island, and Etna volcano, Italy.
But our modelling was the first to demonstrate these changes in the coupled data relationship could occur due to weakening of the material inside the volcano before an eruption.
The damage model that we applied can now be used for other volcanoes in a state of unrest. This adds to the toolbox volcanologists need to predict the when and where of an impending eruption.
So much data, we need help
When volcanoes are in a heightened state of unrest, the volume of information available from digital data and ground observations is extreme. Scientists tend to rely on observational monitoring first, and other data when time and extra people are available.
But the total amount of incoming data (such as from satellites) is overwhelming, and scientists simply can’t keep up. Machine learning might be able to help us here.
Artificial intelligence is the new kid on the block for eruption prediction. Neural networks and other algorithms can use high volumes of complex data and “learn” to distinguish between different signals.
Automated early alert systems of an impending eruption using sensor arrays exist for some volcanoes today, for example at Etna volcano, Italy. It’s likely that artificial intelligence will make these systems more sophisticated in the future.
Early detection sounds wonderful for authorities charged with public safety, but many volcanologists are wary.
If they lead to multiple false alarms then that could slash trust in scientists for both managers of volcanic crises and the public alike.
Discussions on how to address climate change have focused, very appropriately, on reducing greenhouse gas emissions, particularly those of carbon dioxide, the major contributor to climate change and a long-lived greenhouse gas. Reducing emissions should remain the paramount climate goal.
However, greenhouse gas emissions have been increasing now for two centuries. Damage to the atmosphere is already profound enough that reducing emissions alone won’t be enough to avoid effects like extreme weather and changing weather patterns.
In a paper published today in Nature Sustainability, we propose a new technique to clean the atmosphere of the second most powerful greenhouse gas people produce: methane. The technique could restore the concentration of methane to levels found before the Industrial Revolution, and in doing so, reduce global warming by one-sixth.
Our new technique sounds paradoxical at first: turning methane into carbon dioxide. It’s a concept at this stage, and won’t be cheap, but it would add to the tool kit needed to tackle climate change.
The methane menace
After carbon dioxide, methane is the second most important greenhouse gas leading to human-induced climate change. Methane packs a climate punch: it is 84 times more powerful than carbon dioxide in warming the planet over the first 20 years of its molecular life.
Methane emissions from human activities are now larger than all natural sources combined. Agriculture and energy production generate most of them, including emissions from cattle, rice paddies and oil and gas wells.
The result is methane concentrations in the atmosphere have increased by 150% from pre-industrial times, and continue to grow. Finding ways to reduce or remove methane will therefore have an outsize and fast-acting effect in the fight against climate change.
What we propose
The single biggest challenge for removing methane from the atmosphere is its low concentration, only about 2 parts per million. In contrast, carbon dioxide is now at 415 parts per million, roughly 200 times higher. Both gases are much more diluted in air than when found in the exhaust of a car or in a cow’s burp, and both would be better served by keeping them out of the atmosphere to start with.
Nonetheless, emissions continue. What if we could capture the methane after its release and convert it into something less damaging to climate?
That is why our paper proposes removing all methane in the atmosphere produced by human activities – by oxidising it to carbon dioxide. Such an approach has not been proposed before: previously, all removal techniques have only been applied to carbon dioxide.
This is the equivalent of turning 3.2 billion tonnes of methane into 8.2 billion tonnes of carbon dioxide (equivalent to several months of global emissions). The surprising aspect to this trade is that it would reduce global warming by 15%, because methane is so much more warming than carbon dioxide.
This reaction yields energy rather than requires it. It does require a catalyst, though, such as a metal, that converts methane from the air and turns it into carbon dioxide.
One fit-for-purpose family of catalysts are zeolites. They are crystalline materials that consist of aluminum, silicon and oxygen, with a very porous molecular structure that can act as a sponge to soak up methane.
They are well known to industrial researchers trying to oxidise methane to methanol, a valuable chemical feedstock.
We envision arrays of electric fans powered by renewable energy to force large volumes of air into chambers, where the catalyst is exposed to air. The catalyst is then heated in oxygen to form and release CO₂. Such arrays of fans could be placed anywhere where renewable energy – and enough space – is available.
We calculate that with removal costs per tonne of CO₂ rising quickly from US$50 to US$500 or more this century, consistent with mitigation scenarios that keep global warming below 2℃, this technique could be economically feasible and even profitable.
We won’t know for sure, though, until future research highlights the precise chemistry and industrial infrastructure needed.
Beyond the clean-up we propose here, methane removal and atmospheric restoration could be an extra tool in humanity’s belt as we aim for stringent climate targets, while providing new economic opportunities.
Future research and development will determine the technical and economic feasibility of methane removal. Even if successful, methane- and other carbon-removal technologies are no substitute for strong and rapid emissions reductions if we are to avoid the worst impacts of global warming.
Pep Canadell, Chief research scientist, CSIRO Oceans and Atmosphere; and Executive Director, Global Carbon Project, CSIRO and Rob Jackson, Chair, Department of Earth System Science, and Chair of the Global Carbon Project, globalcarbonproject.org, Stanford University