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
- Overview
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.
Sources/Usage: Public Domain. Visit Media to see details.Alabama beach mouse (Peromyscus polionotus ammobates) (Public domain.) 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.
Sources/Usage: Public Domain. Visit Media to see details.Figure 1. Bayesian network model study area for three beach mice subspecies (Fig 1 in Cronin et al. 2021a). 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.
- Science
Below are other science projects associated with this project.
Biological Objectives for the Gulf Coast: Biological Planning Units & Target Species Population Objectives
The USGS partnered with the U.S. Fish and Wildlife Service and its conservation partners to develop 16 Biological Planning Units (BPU) and six Aquatic Extensions and compile population objectives for 166 species that are representative of habitats within each BPU.Strategic Habitat Conservation for Gulf Sturgeon
WARC researchers partnered with Gulf Sturgeon decision makers and biologists to develop a Bayesian network model that uses habitat characteristics to predict the quantity of juvenile winter foraging habitat under alternative river discharge and timing of juvenile arrival scenarios.Strategic Habitat Conservation for Brown Pelican
WARC researchers partnered with managers and species experts to develop a Bayesian network model and a geospatial habitat characteristics dataset to predict the number of Brown Pelican breeding pairs on islands in the northern Gulf of Mexico.Strategic Habitat Conservation for Black Skimmer and Gull-billed Tern
WARC researchers partnered with managers and species experts to develop a Bayesian network model and a geospatial habitat characteristics dataset to predict the number of breeding pairs of Black Skimmer and Gull-billed Tern along the northern Gulf of Mexico. - Data
- Publications