The Cooperative Agreement for affiliated Partner with the Rocky Mountain Cooperative Ecosystem Studies Unit (CESU) enables a university partner to conduct research on detecting plant species habitat using satellite information. The U.S. Geological Survey’s Fort Collins Science Center is offering this opportunity to improve methodologies and analytic approaches for plant species habitat detection. The research will investigate phenology-informed detection models, model transferability across broad regions, spatial patterns of model uncertainty, and the development and delivery of model results to land management practitioners. Detection of invasive species and fire-promoting plants is a key focus to support risk mitigation and management actions.
This cooperative agreement is issued under the Cooperative Ecosystem Studies Units (CESU) Program, which provides research, technical assistance, and education through partnerships. The USGS and a participating partner from the Rocky Mountain CESU will collaborate to produce research products—data and code—that help the Department of the Interior and other land-management partners understand the geographic distribution of plants and the limits of model predictions. The partnership combines expertise in plant ecology, statistical programming, and remote sensing to address longstanding detection challenges, including transferability, uncertainty, and local-scale model credibility.
Current USGS research interests include but are not limited to:
An important focus is detection of fire-promoting invasive species to inform risk and mitigation activities, consistent with recent executive orders on wildfire prevention and science standards.
Eligible recipients must be a participating partner of the Rocky Mountain Cooperative Ecosystem Studies Unit. The opportunity is open to universities that are part of that CESU network and have the capability to conduct research in plant ecology, statistical programming, and remote sensing.
Applications must be submitted electronically no later than June 29, 2026 by 11:59 PM ET. Applications are submitted through Grants.gov. The funding opportunity number is G26AS00122. All required attachments, including biographical sketches, current and pending support forms, project abstract summary, and geospatial data instructions, must be included as specified in the program announcement.
Rachel Miller
Email: rachel_miller@ios.doi.gov
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Submission Deadline
Jun 29, 2026
Collaboration
Multi-institutional
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