Cronin, J.P., Tirpak, B.E., Dale, L.L., Robenski, V.L., and Tirpak, J.M., 2021, Data for Beach Mice Bayesian Network Model: U.S. Geological Survey data release, https://doi.org/10.5066/P9OWRTW8.
Summary
This U.S. Geological Survey (USGS) data release represents tabular data that were used to develop the Biological Objectives for the Gulf Coast Project’s Beach Mice Bayesian network model. The USGS partnered with the U.S. Fish and Wildlife Service (USFWS), the Florida Fish and Wildlife Conservation Commission, and their conservation partners to develop a Bayesian Network model that predicts the annual probability of beach mice presence at a local (30-m) scale. The model was used to predict the annual probability of presence across a portion of the USFWS's Central Gulf and Florida Panhandle Coast Biological Planning Unit. This spatial extent included critical habitat for three endangered subspecies of beach mice (Peromyscus polionotus [...]
Summary
This U.S. Geological Survey (USGS) data release represents tabular data that were used to develop the Biological Objectives for the Gulf Coast Project’s Beach Mice Bayesian network model. The USGS partnered with the U.S. Fish and Wildlife Service (USFWS), the Florida Fish and Wildlife Conservation Commission, and their conservation partners to develop a Bayesian Network model that predicts the annual probability of beach mice presence at a local (30-m) scale. The model was used to predict the annual probability of presence across a portion of the USFWS's Central Gulf and Florida Panhandle Coast Biological Planning Unit. This spatial extent included critical habitat for three endangered subspecies of beach mice (Peromyscus polionotus ssp). The annual probability of beach mice presence is predicted from both local and neighborhood habitat characteristics that could be influenced by management actions. When coupled with established population objectives, this study 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 objectives. The results could be used to help guide strategic habitat conservation and adaptive management of beach mice.
Click on title to download individual files attached to this item.
Bayesian network model beach mice casefile.xml Original FGDC Metadata
View
43.75 KB
application/fgdc+xml
beach mice casefile.csv
27.77 MB
text/csv
Purpose
To predict the annual probability of beach mice presence at a local (30-m) scale, data were collected to create a spatially explicit Bayesian network. Available data were used to create spatial datasets across a portion of the USFWS's Central Gulf and Florida Panhandle Coast Biological Planning Unit. The tabular data associated with this metadata was used in conjunction with the R code included in the associated Journal of Wildlife Management publication to replicate the publication’s figures and tables.
