Assessing environmental controls on biomass in grasslands using an eco-hydrologic model
Grasses in rangeland ecosystems support livestock for agricultural production and provide a variety of ecosystem services. The allocation of carbon (C) between aboveground and belowground plant compartments is influenced by vegetation characteristics and environmental conditions. For grasses, accurate representation of C allocation can inform potential C storage and/or forage production under changing climate and management conditions. The objectives of this study are to (1) examine the sensitivity of biomass to uncertainty across soil drainage, ecophysiological, and allocation parameters, and (2) assess the sensitivity of biomass under different climatic conditions given parameter uncertainty. For this, we use the Regional Hydro-ecologic Simulation System (RHESSys), a physically-based model that simulates coupled water and biogeochemical processes. A Latin Hypercube Sampling approach is used to determine potential parameter sets across the aforementioned variables. Then, ranked partial correlation coefficients (RPCCs) are calculated for our grassland sites representing different climate regimes. RPCCs are used to examine biomass sensitivity to vegetation characteristics, soil drainage, and allocation parameters. Historical precipitation and temperature data are incrementally changed to simulate climatic change (i.e. warmer and/or wetter conditions). The assessment of parameter sensitivity using RPCCs is repeated under these perturbed conditions, along with biomass sensitivity to these climatic changes.
Using RHESSys, we found distinct relationships among simulated biomass (both above and belowground) and different parameters representing eco-hydrologic processes. Parameters controlling C allocation were ranked in the upper quartile of RPCCs for both aboveground and belowground biomass across all grassland sites. This suggests that variation in allocation strategies can have substantial impacts on grassland biomass at our study sites. Among the other species-specific parameters, specific leaf area was also ranked highly across all sites for both above and belowground biomass. Its relative influence on biomass suggests that vegetation characteristics related to photosynthesis may be important for process-based model parameterization. While simulating potential climatic changes, we found differential responses across sites. Biomass was more sensitive to changes in precipitation than temperature at arid sites. Large changes in minimum temperatures increased biomass sensitivity at the cooler grassland sites, while warmer sites responded with slightly smaller increases. Given the uncertainty in parameters that are used to develop our models, this work increases scientific knowledge on how biomass sensitivity may change under future environmental conditions. Improving our understanding of allocation in grasses can better inform sustainable management of our rangelands.