Interactions among stressors can produce complex, non-linear species responses.

At-risk species often face multiple, interacting stressors. Although many stressors have been studied in isolation, relatively little is known about how interacting stressors affect populations. What evidence does exist, cautions against the assumption that most interactions are simply additive in nature. Successfully managing at-risk populations on Department of Defense (DoD) installations will require an improved understanding of how populations will respond to interacting stressors, particularly as climate change introduces new stressors and modifies existing ones. The overarching objective of this project is to explore the nature, the drivers, and the impacts of interactions among multiple stressors affecting at-risk populations. To meet this objective, the project team will answer three more specific questions. 1) How common are non-additive effects of multiple interacting stressors? 2) What factors influence the predictability of multiple stressor interactions? 3) How will stressed populations respond to additional, novel stressors?

The project team will take a scenario-based modeling approach to explore the potential effects of multiple interacting stressors on five at-risk populations. More specifically, spatially explicit, individual-based, population models will be used to simulate the potential effects of sets of multiple (three or more) stressors to explore six specific hypotheses. The project team will model populations of the Golden-cheeked Warbler (Setophaga chrysoparia) and Black-capped Vireo (Vireo atricapilla) at Fort Hood, and the Streaked Horned Lark (Eremophila alpestris strigata), Mazama pocket gopher (Thomomys mazama), and the Taylor's checkerspot butterfly (Euphydryas editha taylori) at Joint Base Lewis-McChord. The approach has three main research tasks including 1) model building and parameterization, 2) stressor scenario development, and 3) model simulation to explore the three research questions and six specific hypotheses.

This project will provide benefits to the scientific community, DoD managers, and wildlife biologists. With respect to the greater scientific community, the model simulations will allow the exploration of critical questions about the relative prevalence of additive versus non-additive stressor interactions as well as to explore the potential factors associated with different interaction outcomes. These simulation results will guide the refinement of hypotheses for future empirical studies and lead to a better understanding of stressor interactions and their impacts. The project will benefit DoD managers and wildlife biologists in multiple ways. The results will provide guidance for the management of five at-risk species on two different installations in the face of multiple, interacting stressors. In addition to model results, the project team will provide the models themselves, allowing base biologists and their off-base collaborators to explore additional questions focused on management, restoration, and reintroductions—in the face of existing, interacting stressors.