Cooperative Ecosystem Studies Unit, Pacific Northwest CESU | G20AS00134

Opportunity Information: Apply for G20AS00134

The Cooperative Ecosystem Studies Unit, Pacific Northwest CESU opportunity (Funding Opportunity Number G20AS00134) was a discretionary USGS funding call issued by the Department of the Interior, U.S. Geological Survey to support a single cooperative agreement project focused on species vulnerability to environmental change. The award was intended specifically for an eligible CESU partner (the announcement lists eligibility as "Others" with clarification in the full text), reflecting the CESU model where federal agencies collaborate with a network of partner institutions to deliver applied research that can be used directly by resource managers. The program area is categorized under Science and Technology and other Research and Development, with CFDA 15.808. The opportunity was posted on August 17, 2020, with an original closing date of September 4, 2020, and anticipated one award with a maximum (ceiling) of $80,394.

The core problem the grant aimed to address is that land and wildlife management agencies increasingly need credible, defensible assessments of how species will respond to changing environmental conditions, but many of the species most in need of assessment are also the least studied. Agencies such as the U.S. Fish and Wildlife Service have responsibilities tied to species status assessments and broader conservation decisions, which require understanding three major dimensions of vulnerability: sensitivity to environmental conditions, exposure to changes (such as shifts in climate, hydrology, disturbance regimes, or habitat availability), and adaptive capacity (the ability to cope with or adjust to those changes). Traditional vulnerability assessment frameworks tend to assume detailed, species-specific knowledge of traits, life history, ecology, and habitat requirements, which creates a real bottleneck when data are sparse or uneven across taxa. As a result, applying methods designed around well-studied species to poorly understood species can be questionable, difficult to defend, and time-intensive for agency staff.

To reduce that burden while maintaining scientific defensibility, the opportunity emphasized using advances in machine learning and statistical clustering as a practical way to infer vulnerability characteristics for lesser-studied species. The general idea is to develop predictive approaches that can leverage patterns learned from better-known species, using available trait and ecological data, and then extend those patterns to priority species where direct information is limited. Statistical clustering can help group species into meaningful categories based on shared traits or ecological similarities, while machine learning can be used to build predictive models that estimate sensitivity and adaptive capacity in a consistent way across many species. By pairing a predictive model with an associated classification tree, the project was expected to produce outputs that are not only analytically robust but also accessible to decision-makers: a classification tree is typically easier to interpret than a "black box" model, and it can clearly show which inputs drive a species into higher- or lower-vulnerability categories.

Overall, the expected deliverable implied by the announcement is a transparent, repeatable framework that agencies can apply to prioritize conservation actions and streamline species assessments when time, staff capacity, and data availability are limited. Rather than requiring extensive new field studies for each poorly known species, the proposed approach would provide a structured and explainable way to estimate vulnerability, document assumptions, and standardize decision support across species. In practical terms, the opportunity was designed to help agencies make quicker, more consistent, and better-supported management decisions in the face of environmental change, while acknowledging the reality that comprehensive ecological data do not exist for many species that nevertheless require assessment and action.

• The Department of the Interior, U. S. Geological Survey in the science and technology and other research and development sector is offering a public funding opportunity titled "Cooperative Ecosystem Studies Unit, Pacific Northwest CESU" and is now available to receive applicants.
• Interested and eligible applicants and submit their applications by referencing the CFDA number(s): 15.808.
• This funding opportunity was created on Aug 17, 2020.
• Applicants must submit their applications by Sep 04, 2020. (Agency may still review applications by suitable applicants for the remaining/unused allocated funding in 2026.)
• Each selected applicant is eligible to receive up to $80,394.00 in funding.
• The number of recipients for this funding is limited to 1 candidate(s).
• Eligible applicants include: Others (see text field entitled Additional Information on Eligibility for clarification).

Apply for G20AS00134

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