Modeling Tools

The Greater Sage-grouse Population Monitoring Framework fills a prominent information gap to help inform current assessments of sage-grouse population trends at nested spatial and temporal scales. It is centered on four objectives: (1) create a standardized database of lek counts; (2) develop spatial population structures by clustering leks; (3) estimate spatial trends at different temporal...

Researchers within the U.S. Geological Survey (USGS) and Colorado State University (CSU) worked with BLM and State Wildlife Agencies to develop a hierarchical population monitoring framework for managing greater sage-grouse ( Centrocercus urophasianus) populations and the sagebrush ecosystems that they depend upon for survival and reproduction. This hierarchical population monitoring strategy now...

Land and wildlife managers require accurate estimates of sensitive species’ trends to help guide conservation decisions that maintain biodiversity and promote healthy ecosystems. Researchers within the U.S. Geological Survey (USGS) and Colorado State University (CSU) worked with the Bureau of Land Management (BLM) and State Wildlife Agencies to develop a hierarchical population monitoring...

Wildlife management boundaries frequently lack biological context, such as information on habitat resource availability and wildlife movements. To address this, we developed multiple levels of biologically relevant and hierarchically nested greater sage-grouse ( Centrocercus urophasianus) population units that could facilitate management and conservation of populations and habitats.

The U.S. Geological Survey’s Eastern Ecological Science Center is home to the Northeast Amphibian Research and Monitoring Initiative (NEARMI), one of 7 ARMI regions across the United States. NEARMI works on public lands in thirteen states from Maine to Virginia, including many National Parks and National Wildlife Refuges.

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.

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.

Researchers will develop and optimize an eDNA assay to delineate the current distribution of P. inflatus. The assay will then be used to provide up-to-date distributional information and detection rates for P. inflatus in the Pearl River basin.

The U.S. Geological Survey Upper Midwest Environmental Sciences Center is developing deep learning algorithms and tools for the automatic detection, enumeration, classification, and annotation of seabirds and other marine wildlife from digital aerial imagery — advancing cutting-edge research in collaboration with the Bureau of Ocean Energy Management (BOEM), the U.S. Fish and Wildlife Service (FWS...

WARC researchers will estimate the density and distribution of bobcats in relation to environmental variables through the development of spatially explicit capture-recapture and occupancy models.

Applying quantitative methods to evaluate ecological hypotheses for wild animal populations is inherently challenging due to the complexity of ecological systems and the sampling process that is used to monitor them.

A USGS forecasting tool helps Everglades natural resource managers identify management actions that can benefit one or more species while quantifying the potential costs to others.