Date of Award:

7-2013

Document Type:

Dissertation

Degree Name:

Doctor of Philosophy (PhD)

Department:

Wildland Resources

Advisor/Chair:

Peter B. Adler

Abstract

We used demographic methods to address one of the main challenges facing ecological science: forecasting the effect of climate change on plant communities. Ecological forecasts will be crucial to inform long-term planning in wildland management and demographic methods are ideal to quantify changes in plant abundance. We carried out our research in the sagebrush steppe, one of the most extensive plant ecosystems of Western North America. Our research intended to inform ecological forecasts on an exotic invader, cheatgrass (Bromus tectorum). Moreover, we investigated the general question asking: to what degree competition among plants influences the outcome of ecological forecasts on the effect of climate change? We carried out two field experiments to test the hypothesis that warming will increase cheatgrass abundance in the sagebrush steppe. This hypothesis was strongly supported by both experiments. Warming increased cheatgrass abundance regardless of elevation, neighboring vegetation or cheatgrass genotype. Moreover, we found cheatgrass was hindered by snow cover. Therefore, warming increases cheatgrass growth directly by increasing temperature, and indirectly by decreasing or removing snow cover. In our last experiment, we tested whether forecasts of climate change effects on rare species can ignore competition from neighbors. This should occur because rare species should have little niche overlap with other species. The lower the niche overlap, the less competition with other species. To test this hypothesis, we used a long-term data set from an Idaho sagebrush steppe. We built population models that reproduced the dynamics of the system by simulating climate and competition. Model simulations supported our hypothesis: rare species have little niche overlap and little competitive interactions with neighbor species.

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