# Simpler Grants.gov #G27AS00166

USGS Bayesian Spatial Modeling Research for Bat Acoustic Data

**Buyer:** U.S. Geological Survey
**Posted:** October 30, 2026
**Respond By:** December 05, 2026
**Identifier:** G27AS00166
**NAICS:** 541715

The U.S. Geological Survey is seeking research proposals to improve analysis of passive bat acoustic monitoring data.
- **Government buyer:** U.S. Geological Survey (USGS), within the U.S. Department of the Interior; no sub-agency or office is identified.
- **Opportunity:** One cooperative agreement is anticipated for Bayesian spatial modeling research. Eligibility is limited to participating partners of the Great Rivers Cooperative Ecosystem Studies Unit (CESU).
- **Requested research services:** Develop and apply methods to model spatial patterns in bat species occupancy and relative activity; classify species directly from acoustic call characteristics; create efficient model-fitting algorithms and code; and assess how manual review data from multiple observers can be incorporated.
- **Funding:** Estimated total funding is $350,000, including approximately $150,000 for the first budget year. Funding for later years depends on project progress and funding availability.
- **Period of performance:** One base year plus four additional budget years, for a proposed five-year project.
- **Notable requirements:** Applications must include a Data Management Plan. Geospatial data must follow applicable standards and be submitted in open formats with metadata. Projects related to America250 are encouraged.
- **OEMs and vendors:** None are identified; no commercial products or part numbers are requested.

### Description

The U.S. Geological Survey seeks proposals from participating Great Rivers Cooperative Ecosystem Studies Unit partners for research developing Bayesian statistical methods to analyze passive bat acoustic monitoring data. The work will model spatial dependence in species occupancy and relative activity, develop a classifier using acoustic call characteristics, create efficient fitting algorithms, and explore incorporating manual review data from multiple observers. The research is intended to improve estimates and predictions of bat distributions and inform conservation and resource-management decisions. One cooperative agreement is anticipated, with an estimated total of $350,000 across a five-year project period.

[View original listing](https://simpler.grants.gov/opportunity/364176)