Agreement and Uncertainty Among Climate Change Impact Models: A Synthesis of Sagebrush Steppe Vegetation Projections

Abstract

Ecologists have built numerous models to project how climate change will impact rangeland vegetation, but these projections of future changes are difficult to validate, making their utility for land management planning unclear. In the absence of direct validation, researchers can ask whether projections from different models are consistent. High consistency across models, especially those based on different assumptions, would increase confidence in using projections for planning. Here, we analyzed 19 models of climate change impacts on sagebrush (Artemisia tridentata Nutt.), cheatgrass (Bromus tectorum L.), pinyon-juniper (Pinus L. spp. and Juniperus L. spp.), and forage production on Bureau of Land Management (BLM) lands in the US Intermountain West. These models consistently projected the potential for pinyon-juniper declines and forage production increases. In contrast, models of cheatgrass mainly projected no climate change impacts, while sagebrush models projected no change in most areas and declines in southern extremes. In most instances, vegetation projections from high- and low-emission scenarios differed only slightly.The projected vegetation impacts have important management implications for agencies such as the BLM. Pinyon-juniper declines would reduce the need to control pinyon-juniper encroachment, and increases in forage production could benefit livestock and wildlife populations in some regions. Sagebrush conservation and restoration projects may be challenged in areas projected to experience sagebrush declines. Similar projections from high- and low-emission scenario models may increase confidence to consider model projections in planning. However, projected vegetation impacts may also interact with increasing future wildfire risk in ways single-response models do not anticipate. In particular, forage production increases could increase management challenges related to fire.