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Research Grants (Generic)

Sector: Advanced Electronics • Location: United States of America

Source: Grants.gov

Project
Archived

Quantifying abundance of wild animals forms an important component for managing and conserving species populations. The process of acquiring data for quantifying abundance in an accurate and informative manner, however, can be logistically difficult and costly. One method for obtaining vast amounts of data describing species presence and counts over time, inexpensively, includes camera trapping.

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The project “Research Grants (Generic)” is an infrastructure initiative in the Advanced Electronics sector, located in United States of America. Taiyo aggregates data on it from Grants.gov.

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Description

Description

Quantifying abundance of wild animals forms an important component for managing and conserving species populations. The process of acquiring data for quantifying abundance in an accurate and informative manner, however, can be logistically difficult and costly. One method for obtaining vast amounts of data describing species presence and counts over time, inexpensively, includes camera trapping. Yet, it remains uncertain how useful data from camera trapping is for estimating animal abundance in an accurate and defensible manner. This agreement addresses this issue. Specifically, funding in this agreement supports investigations into how best to integrate and analyze data gained from camera traps to estimate species abundance. To date, there are some promising techniques to examine, such as spatial capture recapture and integrated population models. These new approaches are still under development and are rather unestablished in this application. The statistics involved are substantial and the mathematics complicated. Given this situation, this project will test the relevance and applicability of recent analytical techniques for estimating abundance on existing data gained from camera traps targeting populations of desert bighorn sheep, with animals marked and unmarked. If integration with recent statistical approaches proves unproductive, then this project will attempt designing new statistical and or methodological approaches for estimating species abundance with camera trap data. For this pilot effort, the project will initially focus on data gained from populations of desert bighorn sheep. The project, however, can rely on simulated data. The New Jersey Institute of Technology (NJIT) is well positioned to work with the U.S. Fish and Wildlife Service (Service) on this effort. Previously, the Service collaborated with NJIT to advance abundance estimation for bears, using a ���targeted sampling��� approach. Essentially, sampling bears at salmon streams instead of across a wide landscape. The statistics behind this effort were unestablished and required new designs. This agreement follows a similar trajectory, with ���targeted sampling��� ungulates at water sources, and not across landscapes. Like before, the project requires establishing new statistical techniques for analyzing these data. Further, NJIT and the Service have examined how varying scales affect resource selection issues. This is also novel science, established by this team. Hence, this effort continues a trajectory of work between the Service and NJIT. The total project may reach $60,684.00. However, the Service will fund $29,838.75 initially to begin the effort. A subsequent mid year review between the Service and NJIT based on project progress, initial results, promise of reaching project objectives, etc. will determine if the remaining funds are obligated. This decision will be made no later than December 2015. The program authorizing statute citations are: Fish and Wildlife Act of 1956, as amended, 16 U.S.C. (742f (a)(4); Fish and Wildlife Coordination Act, as amended, 16 U.S.C. 661.; Fish and Wildlife Improvement Act of 1978, as amended (16 U.S.C. 753), Land and Water Conservation Fund Act of 1965, as amended (16 U.S.C. 4601, 4 through 11), Endangered Species Act of 1973 (16 U.S.C. 1531 through 1543).

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100%

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