Award Abstract # 1927282

ABSTRACT

Rapid environmental changes, such as rising temperatures and nitrogen pollution, can have dramatic impacts on plant and animal species important to society. Endangered species may be driven extinct, damaging invasive species might increase in distribution and abundance, and changes in the production of timber or forage species can alter rural economies. To help natural resource managers make good decisions, biologists predict the effect of environmental change on important species using population models. However, these predictions are rarely tested against observations. As a result, the ability of population models to make accurate forecasts for large regions is unknown. The goal of this project is to build a state-of-the-art population model and rigorously test its predictions against independent observations. The results will establish a benchmark for the current predictive ability of population models, while also identifying the kind of information required to make good predictions. For example, is it possible to make a skillful forecast without understanding genetic differences between individuals from different locations or accounting for interactions between the study species and its competitors? Graduate students and postdoctoral scientists will be invited to workshops for training in advanced statistical and population modeling techniques. To educate the public about the impacts of invasive species and environmental change, interactive exhibits will be installed at three museums and botanical gardens.

The proposed research focuses on the reaction norm, a quantitative description of how an organism's performance depends on the environment. Success will require new advances to determine the relative importance of processes operating at gene, individual, and community levels in shaping reaction norms and regional population dynamics. The investigators will integrate DNA sequencing, common environment experiments, a regional network of distributed experiments across abiotic gradients, and new statistical techniques to answer the following questions: 1) What processes influencing reaction norms must we understand to predict impacts of environmental change on regional-scale population dynamics? 2) What is the magnitude of intraspecific variation in reaction norms, and to what extent does it reflect local adaptation vs. other processes? 3) How do phenology and physiology interact to determine demographic responses to weather? 4) How do abiotic conditions and competitive environment combine to influence demographic rates? The focal species is the invasive grass Bromus tectorum, which has degraded millions of acres of sagebrush steppe across the western US. Predictions about future changes in B. tectorum abundance across the region, and resulting changes in fire regimes, will help decision-makers prioritize future investments in conservation and restoration.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

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