- Program Areas
- Installation Energy and Water
- Environmental Restoration
- Munitions Response
- Resource Conservation and Resiliency
- Natural Resources
- Infrastructure Resiliency
- Air Quality
- Weapons Systems and Platforms
Evaluating the Use of Spatially Explicit Population Models to Predict Conservation Reliant Species in Non-Analogue Future Environments on DoD Lands
Dr. Brian Hudgens | Institute for Wildlife Studies
The objective of this project is to develop and test a combined empirical protocol and theoretical framework for determining which species are likely to become conservation reliant as global climate change creates novel environments in and around Department of Defense (DoD) lands. Specifically, this project will: (1) use downscaled climate change model output to identify plausible future temperature and precipitation regimes that managed species will face on military lands, (2) use time series and space-for-time studies to determine how demographic rates for a suite of species are expected to change given future predicted temperature and water regimes, (3) build and use Spatially Explicit Environmental Driver (SEED) population models to predict population level changes expected to occur in non-analogue environmental conditions under plausible future conditions, (4) validate SEED model predictions in experimentally created non-analogue environments in which environmental conditions (e.g., temperature and water availability) are pushed outside the ranges and combinations of values used to parameterize the models, and (5) compare SEED model population dynamic predictions and sensitivities across species to determine ecological characteristics of conservation reliant species versus those species that show adaptive capacity under future conditions.
SEED models are next-generation population models that link demographic rates to environmental variables at all points across spatially explicit landscapes and incorporate dispersal of individual organisms between habitat patches to gauge the population consequences of landscape changes in both space and time. The project’s tasks are to: (1) collect demographic data for a suite of species, as well as climate data, across multiple sites and years, and in experiments pushing climate variables beyond their current limits; (2) use maximum likelihood methods to fit non-linear functions for the vital rates versus climate variables, including any justified interactive effects of multiple variables; (3) use downscaled climate models to project the future state of the landscape on DoD lands inhabited by species of conservation concern; (4) use the fitted demographic functions to predict the values of all demographic rates, and use those in turn to update population size; (5) validate the fitted population model by testing its correspondence to simultaneous experimental manipulation of multiple climate variables; (6) add in dispersal behaviors estimated in previous work to enable simulated individuals to seek out suitable habitat; (7) evaluate change in population size over time, to gauge which taxa may become conservation reliant; and (8) repeat the simulation with different climate scenarios to account for multiple plausible futures.
This project will provide two types of benefits to the DoD. First, it will provide a set of tools that will assist DoD land managers to anticipate future management needs as a result of global climate change. Specifically, it will: (1) provide a general theoretical framework for predicting which species are most at risk for becoming conservation reliant due to climate change and (2) demonstrate a validated method (SEED models) for predicting whether specific species are likely to require more or less intensive management, or become conservation reliant, as a result of climate change. Because SEED models include a spatially explicit component, they also will be useful for predicting the effects of habitat conversion in lands surrounding military installations, which may restrict managed species to the installations and increase the management burden on DoD. The project’s approach builds on existing decision support tools already implemented on military installations, and it will provide training to facilitate the expansion of their use to new installations. Secondly, this project will provide specific predictions and management recommendations for four species currently managed at Fort Bragg, North Carolina, and Vandenberg Air Force Base, California. These recommendations will provide guidance for management practices in the short term and facilitate long-term planning to maintain or bolster populations of these species with minimal impact on the military missions of these installations. (Anticipated Project Completion - 2020)