COS 52-6 - Estimating climate sensitivity of semi-arid vegetation: What can we learn by comparing forecasts derived from different modeling techniques?

Wednesday, August 10, 2016: 3:20 PM
Grand Floridian Blrm A, Ft Lauderdale Convention Center
Katherine M Renwick, Ecology, Montana State University, Bozeman, MT, Andrew R. Kleinhesselink, Department of Wildland Resources, Utah State University, Logan, UT, Daniel R. Schlaepfer, Section of Conservation Biology, University of Basel, Basel, Switzerland, Caroline A. Curtis, Organismic and Evolutionary Biology, University of Massachusetts, Bethany A. Bradley, Environmental Conservation, University of Massachusetts, Amherst, Amherst, MA, Cameron L. Aldridge, Fort Collins Science Center, U.S. Geological Survey, Fort Collins, CO, Benjamin Poulter, Biosphere, NASA GSFC, Greenbelt, MD and Peter B. Adler, Department of Wildland Resources and the Ecology Center, Utah State University, Logan, UT

Climate change will affect the distribution and abundance of many plant species, altering ecological communities in ways that are difficult to predict. Understanding the sensitivity of key species to climate change is an important challenge in ecology, particularly where other interacting factors such as fire and invasive species may complicate the climate change response. This is particularly true for big sagebrush (Artemisia tridentata), a habitat-defining species found throughout large areas of the western US. Over the past century, many sagebrush ecosystems have declined due to climate warming, fire, invasive species, and land-use change. There is an urgent need to understand how these factors will continue to impact sagebrush in the future.

To understand the climate sensitivity of A. tridentata, we synthesized output from four different modeling approaches. Two models were based on empirically-derived spatial and temporal patterns, while two applied mechanistic approaches to simulate sagebrush recruitment and ecosystem dynamics. One of the mechanistic models, the LPJ-GUESS dynamic global vegetation model (DGVM), was run with four different scenarios: climate change alone, and with the addition of fire, competition, and increasing CO2 concentrations. Models were tested at 726 locations, chosen to represent the full breadth of climate space where sagebrush is found. 


Interestingly, despite the large model differences, they largely agree that sagebrush response to climate change will depend on both the average climate of the site and the magnitude of climate change. Increases in average temperature were associated with increases in sagebrush cover at cool sites with summer precipitation, but the same temperature increase was associated with decreases in sagebrush cover at warmer sites, regardless of the seasonality of precipitation. Models also agree that changes in mean annual temperature will have a much greater impact on sagebrush compared to changes in mean annual precipitation. Shifts in the seasonality of precipitation had a larger impact than shifts in the annual total. Despite these general patterns of agreement between the models, there remained some variability in model projections; this variability suggest new hypotheses regarding the importance of various processes in determining how sagebrush will respond to climate change. The DGVM exhibited strong threshold responses associated with increasing temperatures that were not observed in the other models. The addition of competitive interactions and fire to the DGVM caused an even greater divergence from the results of the other three models, suggesting that these factors may mediate the response of sagebrush to climate change.