Unit Leader - New York Cooperative Fish and Wildlife Research Unit
Research Interests
The single unifying theme of Angela's research program that transcends all projects is that they provide information that contributes to the conservation or management of wildlife species and that has an impact on the way species are managed. The first area of her research is on how spatial variation in the environment influences resource use, movements, and population ecology of mammals. This research is focused primarily on mammalian carnivores, which have many traits that make them especially susceptible to landscape change (e.g., large home ranges, relatively low population densities, and long dispersal distances). She frequently uses non-invasive sampling methods that do not require direct capture of individuals. Using these noninvasively collected samples from carnivores, she employs methods for population estimation that incorporate spatial or landscape processes to help explain the density of species across a landscape. The second major program area of her research is in applying structured decision making (SDM) and adaptive management to guide natural resource management and policy outcomes. SDM is a process for helping to make management or policy decisions in a clear and transparent way, and involves evaluating how well alternative management strategies do at achieving objectives that have been identified by the decision maker and stakeholders. This work integrates quantitative modeling to help predict outcomes of the management strategies that were developed to achieve the stated objectives. Both of her research areas involve the spatial ecology of species, investigating how spatial landscape patterns influence the distribution, density, or dynamics of animal populations.
Teaching Interests
- Decision Making for Natural Resources
- Landscape Ecology
- Habitat Ecology
- Forest Landscape Planning
Science and Products
Capture-recapture meets big data: integrating statistical classification with ecological models of species abundance and occurrence
Spatial Capture-Recapture Models to Estimate Abundance and Density of Animal Populations
Science and Products
- Publications
- Science
Capture-recapture meets big data: integrating statistical classification with ecological models of species abundance and occurrence
Advances in new technologies such as remote cameras, noninvasive genetics and bioacoustics provide massive quantities of electronic data. Much work has been done on automated (“machine learning”) methods of classification which produce “sample class designations” (e.g., identification of species or individuals) that are regarded as observed data in ecological models. However, these “data” are actu...Spatial Capture-Recapture Models to Estimate Abundance and Density of Animal Populations
The Challenge: For decades, capture-recapture methods have been the cornerstone of ecological statistics as applied to population biology. While capture-recapture has become the standard sampling and analytical framework for the study of population processes (Williams, Nichols & Conroy 2002) it has advanced independent of and remained unconnected to the spatial structure of the population or the...