Cooperative Fish and Wildlife Research Units Program: New York
Education, Research and Technical Assistance for Managing Our Natural Resources

New York Project

Density, spatial ecology, and movements of black bears in New York

August 2010 - March 2014


Participating Agencies

  • New York Department of Environmental Conservation

This project will evaluate habitat selection, movements, and landscape permeability of black bears in New York and will provide a DNA-based density estimate of bears using a capture-mark-recapture approach. Project 1: We are investigating how an anthropogenically (related to human activity) fragmented landscape influences the spatial ecology, movements, and habitat selection of black bears in New York. This research will help in predicting where human-bear interactions may occur in the future as bears continue to expand in abundance and distribution. Within the last two decades, black bears in southern New York have continued to increase in abundance, which has caused an expansion of their range northward. This range expansion has resulted in increased utilization of areas with higher human densities, and landscapes with a greater proportion of agriculture. Landscapes with high proportions of developed areas and open agricultural lands have potential to increase home range size of bears, and may influence the movement patterns of bears, given the potentially lower overall habitat quality on the landscape. Data from GPS-collared bears are being used to determine how movements are defining home ranges, and how landscape characteristics (e.g., patch type, patch size, patch distribution, road density, topography, agriculture, human density) influence movements of bears. Additionally, we are evaluating habitat selection and temporal variation in space use between bears in anthropogenically modified landscapes and those in forested landscapes. Project 2: We are using a non-invasive hair sampling technique to investigate the genetic diversity and population demographics of black bears in New York. This research will provide information on black bear populations that will aid in the development of effective management strategies for black bears. Recently, black bears in New York have expanded in range, merging into two large populations from three formerly distinct geographic populations (i.e., Adirondack, Catskills, Allegany populations). The Adirondack and Allegany ranges, now jointly referred to as the Southern black bear population, have been expanding into areas with agriculture and greater human densities. However, a rigorous density estimate of this expanding population does not exist. Characteristic low densities and extensive ranges of black bears make population estimates difficult, but developments in mark-recapture methods (i.e., spatially explicit capture-recapture models) enable greater accuracy and precision in estimating density. To estimate black bear density, we are conducting a non-invasive genetic mark-recapture study to collect black bear hair samples from barbed-wire snares. Individual bears are identified using a suite of variable, mitochondrial genetic markers. These data will inform a spatially-explicit capture-recapture model to estimate population density of black bears. We will incorporate data from multiple sources (e.g., live captures, harvested dead-recoveries) and include habitat covariates at multiple spatial scales. Additionally, through the regional collection of hairs, this study will analyze landscape genetics, potentially identifying landscape features facilitating and/or inhibiting gene flow and genetic diversity in black bears.

Research Publications Publication Date
Royle, J.A., R. B. Chandler, C. C. Sun, and A. K. Fuller. 2013. Integrating resource selection information with spatial capture-recapture. Methods in Ecology and Evolution. doi: 10.1111/2041-210X.12039. | Abstract February 2013
Theses and Dissertations Publication Date
C. Sun. Estimating black bear population density in the southern black bear range of New York with a non-invasive, genetic, spatial capture-recapture study. May 2014