Strategic Habitat Conservation for Beach Mice (Peromyscus polionotus ssp.)
WARC researchers partnered with beach mice managers and biologists to estimate habitat objectives and the amount of effort needed to achieve the habitat objective (i.e., management efficiency) for three beach mice subspecies in Florida’s panhandle.
The Science Issue and Relevance: Many beach mice subspecies inhabit coastal dunes in Alabama and Florida and are listed as endangered or threatened under the U.S. Endangered Species Act due to multiple stressors (e.g., habitat loss, habitat degradation, depredation). Conservation opportunities are both limited and costly because beach mice have small ranges and their habitat overlaps with high human activity. Consequently, downlisting a subspecies hinges on knowing where management could most efficiently achieve downlisting objectives. This requires quantitative, spatially explicit decision support tools that can guide strategic habitat conservation.
Methodology for Addressing the Issue: We partnered with beach mice managers and biologists to estimate habitat objectives and the amount of effort needed to achieve the habitat objective (i.e., management efficiency) for three beach mice subspecies in Florida’s panhandle (Fig. 1). We developed a Bayesian network model that uses habitat characteristics to predict the probability of beach mouse presence at a 30-m spatial resolution. We also developed spatial datasets of these habitat characteristics and fed them into the model to predict each subspecies’ presence in a portion of Florida. We used the model to identify alternative management actions for improving dune habitat and determined that strategic implementation of those actions across the landscape could be almost 30% more efficient at meeting downlisting criteria compared to opportunistically implementing restoration across the landscape. The study is described in Cronin et al. 2021 and the products are available on ScienceBase.
Future Steps: These products can provide insight into how much habitat is available, how much more is needed, and where conservation or restoration efforts can most efficiently achieve established downlisting criteria. The model could be incorporated into Species Status Assessments, a tool used by the U.S. Fish and Wildlife Service for listing decisions under the Endangered Species Act.
Below are other science projects associated with this project.
Biological Objectives for the Gulf Coast: Biological Planning Units & Target Species Population Objectives
Strategic Habitat Conservation for Gulf Sturgeon
Strategic Habitat Conservation for Brown Pelican
Strategic Habitat Conservation for Black Skimmer and Gull-billed Tern
WARC researchers partnered with beach mice managers and biologists to estimate habitat objectives and the amount of effort needed to achieve the habitat objective (i.e., management efficiency) for three beach mice subspecies in Florida’s panhandle.
The Science Issue and Relevance: Many beach mice subspecies inhabit coastal dunes in Alabama and Florida and are listed as endangered or threatened under the U.S. Endangered Species Act due to multiple stressors (e.g., habitat loss, habitat degradation, depredation). Conservation opportunities are both limited and costly because beach mice have small ranges and their habitat overlaps with high human activity. Consequently, downlisting a subspecies hinges on knowing where management could most efficiently achieve downlisting objectives. This requires quantitative, spatially explicit decision support tools that can guide strategic habitat conservation.
Methodology for Addressing the Issue: We partnered with beach mice managers and biologists to estimate habitat objectives and the amount of effort needed to achieve the habitat objective (i.e., management efficiency) for three beach mice subspecies in Florida’s panhandle (Fig. 1). We developed a Bayesian network model that uses habitat characteristics to predict the probability of beach mouse presence at a 30-m spatial resolution. We also developed spatial datasets of these habitat characteristics and fed them into the model to predict each subspecies’ presence in a portion of Florida. We used the model to identify alternative management actions for improving dune habitat and determined that strategic implementation of those actions across the landscape could be almost 30% more efficient at meeting downlisting criteria compared to opportunistically implementing restoration across the landscape. The study is described in Cronin et al. 2021 and the products are available on ScienceBase.
Future Steps: These products can provide insight into how much habitat is available, how much more is needed, and where conservation or restoration efforts can most efficiently achieve established downlisting criteria. The model could be incorporated into Species Status Assessments, a tool used by the U.S. Fish and Wildlife Service for listing decisions under the Endangered Species Act.
Below are other science projects associated with this project.