Final Report Evaluating the Use of Spatially Explicit Population Models to Predict Conservation Reliant Species in Nonanalogue Future Environments on DoD Lands SERDP Project RC-2512

Introduction and objectives: The Department of Defense (DoD) is responsible for managing threatened, endangered, and rare species inhabiting its properties. Predicting which of these species will need ongoing management due to changing climate conditions is valuable for planning and prioritizing natural resource management needs. We developed and tested an empirical protocol and theoretical framework for determining if target species are likely to become conservation reliant in the future. Technical approach: We tested the empirical protocol using seven species: hydaspe fritillary butterfly (Speyeria hydaspe), Appalachian brown butterfly (Satyrodes Appalachia, western snowy plovers (Charadrius nivosus nivosus), red-legged frogs (Rana aurora and R. draytonii), Alaskan douglasia (Douglasia alaskana), Venus flytraps (Dionaea muscipula) and red-cockaded woodpeckers (Dryobates borealis). These species are either special status species or closely related surrogates for special status species managed on or near DoD properties. We used time series or space-for-time data and experimental manipulations to determine how climate influences the demographic rates of each species. We then used these relationships and downscaled global climate change models to build Spatially Explicit Environmental Driver (SEED) models to predict population level changes for each species under future climate scenarios. We also developed another tool, the Climate Contribution Index (CCI) that identifies the relative importance of different aspects of a species life history in shaping population responses to climate change. Results: Climate influenced demographic rates in numerous and complex ways. In many cases, demographic rates were affected by multiple climate variables, and it was not uncommon for the same climate variable to have opposing effects on different demographic rates. We found that projected population growth rates for our seven study species were typically either unaffected or positively influenced by future climate change. Only three of the 49 populations evaluated across all seven species were projected to have decreasing growth rates under future climate conditions. The populations most at risk for becoming conservation reliant due to climate change were those in the warmest parts of the species ranges. On the other hand, populations in the coolest parts of species ranges tended to benefit the most from projected changes in climate. Like the responses themselves, the dem