Cooperative Ecosystem Studies Unit, Rocky Mountain CESU

The summary for the Cooperative Ecosystem Studies Unit, Rocky Mountain CESU grant is detailed below. This summary states who is eligible for the grant, how much grant money will be awarded, current and past deadlines, Catalog of Federal Domestic Assistance (CFDA) numbers, and a sampling of similar government grants. Verify the accuracy of the data FederalGrants.com provides by visiting the webpage noted in the Link to Full Announcement section or by contacting the appropriate person listed as the Grant Announcement Contact. If any section is incomplete, please visit the website for the Geological Survey, which is the U.S. government agency offering this grant.

Cooperative Ecosystem Studies Unit, Rocky Mountain CESU: The purpose of the Northern Rocky Mountain Science Center (NOROCK) funding opportunity is to develop a GIS-based, spatially explicit model of probability of occurrence of grizzly bears in the Greater Yellowstone Ecosystem (GYE). The model will be used to identify important habitats and rank them according to the probability that they will be used by grizzly bears. As part of the modeling process, habitat characteristics highly correlated with bear use will be identified. The modeling will encompass the entire GYE, consisting of Yellowstone and Grant Teton National Parks, six national forests, and various state and private lands in parts of Wyoming, Montana and Idaho. This work will employ a use-availability type study design. Information about grizzly bear habitat use will be provided by the Center from data collected as part of ongoing research and monitoring efforts. Information about habitat availability will come from existing GIS layers for the GYE. These themes describe vegetational, physiographic, and anthropogenic characteristics believed important to bear habitat selection. A variety of methods will be considered for modeling probability of use or ranking habitats according to probability of use, which include: logistic discriminant analysis (Seber 1984) for ranking habitats according to probability of use; the parametric weighted distribution approach of Lele and Keim (2006) for modeling actual probabilities of use; and produce kernel density estimation (Scott 1992) with Bayesian bandwidth selection (Zhang et al 2006) for nonparametric modeling of probabilities of use. It should be noted that because wildlife habitat-selection modeling is an extremely active area of research, with new methods being proposed on a regular basis, the final suite of modeling methods explored in this study may vary somewhat from those listed above.