Implications of changing extreme weather distributions on grassland ecohydrology

Background/Question/Methods

Changing climate will alter the spatial and temporal distribution of weather events. This alteration will likely impact both the mean and tails of the distribution, particularly the occurrence of extreme events like heat waves, extreme precipitation events etc. The goal of this work is to assess these questions: What are the implications of the timing and magnitude of these extreme events on the water and carbon cycling in grassland ecosystems? and What are the likely ecohydrological implications of future climate change in grasslands? To address these questions we focus on the Konza prairie long term ecological research (LTER) site in north-central Kansas. Using a combination of LTER data, eddy covariance, and biweekly site samples we have a robust data record to assess the implications of weather events on mass flux cycling. Next, we utilize two models including a low-dimensional water and carbon cycling model and Biome-BGC to assess the implications of future climate change impacts on extreme events. A stochastic weather generator was used to construct daily weather sequences consistent with both historical and future climate scenarios as determined from the IPCC GCM suite. To quantify the ecohydrological responses we utilized a critical climate period (CCP) analysis that identifies the correlation between end of year biomass and daily weather at specific times as well as an innovative multi-scale information theory to assess the time scales of variability. 

Results/Conclusions

Results indicate that both models were capable of capturing dynamics of changing weather distributions on water and carbon cycling. Historical data shows a sensitivity to spring (early May) precipitation increasing annual biomass, while the temperature in the first week of July is negatively correlated with annual biomass. Eddy covariance and biweekly samples during the 2011 heat wave show drastic differences in the rate of carbon allocated to above ground biomass, with only slight reductions in total carbon assimilation. The Biome-BGC is generally able to capture this change in partitioning. For the future simulations, we note that annual biomass is incredibly sensitive to the timing of precipitation and temperature anomalies, regardless of the trend in the mean climate forcing. These results are important for developing a better understanding of the biophysical response to extreme events as well as understanding the extent to which the current generation of ecophysiological models are able to capture the dominant processes during these rare, but biologically significant, events.