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

New York Project

Novel approaches to big problems: Integrating citizen science to monitor and estimate black bear populations in New York

April 2014 - August 2019


Participating Agencies

  • New York State Department of Environmental Conservation

Black bears (Ursus americanus) are an important game species in New York State. In the last two decades, the bear population in the state has been growing due to conservative bear management and increasing anthropogenic resources. Successful management of the population requires estimating population and home range sizes, and understanding patterns of resources selection and population density in relation to landcover. New York covers approximately 141,000 km2, and so, to collect spatially representative data for such a large region, we must consider approaches to sampling that supplement intensive, traditional capture-recapture and occupancy methods. Such an addition could utilize citizen science, which engages a disperse but wide-ranging network of the public in the scientific research process, often through assistance with data collection. Citizen science has a long and successful history in monitoring natural systems over large spatial and temporal ranges, and recent advances in technology and computation have made the large quantity and variable quality of citizen science data more tractable. We describe a conceptual framework for joining non-invasive citizen science efforts with telemetry, spatial capture recapture, and occupancy methods into a single integrated population model for managing black bears. This integrated approach would be valuable for identifying patterns of black bear distribution, resource selections and movement across a range of spatial scales, for gaining a more mechanistic understanding of black bear population dynamics, and for helping to develop a comprehensive management plan for black bears in New York.

Research Publications Publication Date
Sun, C.C., A.K. Fuller, M.P. Hare, and J. Hurst. 2017. Evaluating population expansion of a black bear population using noninvasive, genetic spatial capture-recapture. Journal of Wildlife Management 81: 814–823. doi:10.1002/jwmg.21248 April 2017
Sun, C.C., A.K. Fuller, and J.A. Royle. Incorporating citizen science data in spatially explicit integrated population models. Ecology. July 2019
Presentations Presentation Date
Sun, C. S., A. K. Fuller, and J.A. Royle. Novel approaches to big problems: Integrating citizen science to monitor and estimate black bear populations in New York. 71st Annual Northeast Fish and Wildlife Conference. 20 April, 2015. April 2015
Sun, C.S., A.K. Fuller, and J.A, Royle. Multi-scale integrated modeling framework of animal population dynamics incorporating spatial capture-recapture and occupancy data collected from citizen science and traditional sampling. Ecological Society of America Annual Meeting, Baltimore, Maryland. 13 August, 2015. August 2015
Sun, C. C., A. K. Fuller, J. A. Royle, and M. Hare. Joint estimation of black bear resource selection and population density. The Wildlife Society Annual Conference, Milwaukee, WI. 7 October, 2013. October 2013
Sun, C. S., A. K. Fuller, and J. Andrew Royle. Joint estimation of black bear resource selection and population density. 22nd International Conference on Bear Research and Management, Provo, UT. 19 September, 2013. September 2013
Sun, C.S. and A.K. Fuller. 2017. Use of citizen scientists in black bear management. New York Chapter of the Wildlife Society 2017 annual meeting. Hamilton, NY. 1 March, 2017. March 2017
Sun, C.C., M.P. Hare, A.K. Fuller, and J.E. Hurst. 2017. Phylogeography of black bears in the northeastern United States. 24th Annual Conference of the Wildlife Society. Albuquerque, New Mexico. 26 September, 2017. September 2017
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