Opportunity Information: Apply for G24AS00369
This grant opportunity (Funding Opportunity Number G24AS00369) is a discretionary cooperative agreement offered by the U.S. Geological Survey (USGS), specifically through its Northern Rocky Mountain Science Center (NOROCK). The project focus is on strengthening the statistical foundation of bat monitoring in the western United States by improving Bayesian, model-based inference for common bat survey data. In practical terms, the work is meant to help turn multiple kinds of bat monitoring observations into more reliable estimates of bat status and population trends, using modern Bayesian approaches that can better handle uncertainty, imperfect detection, and differences among survey methods.
The scientific need behind the opportunity is tied to how bats are currently monitored across large landscapes. The field data streams emphasized here are stationary acoustic surveys (recorders left in place to capture echolocation calls), mobile transects (acoustics collected while moving along a route), and summertime colony counts (direct counts at roosts or maternity colonies during the summer period). These are the core monitoring methods used by the North American Bat Monitoring Program (NABat), a continent-scale effort that compiles and analyzes data to support periodic, range-wide assessments of bat species status and trends (referenced in the notice as Loeb et al. 2015). The funding is aimed at improving the statistical models that connect these data streams to meaningful biological conclusions, especially in ways that are defensible for management and conservation decisions.
NOROCK frames this work as part of ongoing statistical leadership and development within NABat. The notice highlights that a NOROCK research statistician helped conceptualize NABat, developed the probabilistic master sample design that supports coordinated monitoring across jurisdictions, and continues to identify and address emerging research and development needs for the program's "Bats and Stats Team." That context signals that the cooperative agreement is not just for producing a standalone report; it is intended to contribute to an active monitoring program and to advance the statistical tools that NABat partners rely on for coordinated, large-scale inference.
Administratively, this award is being issued under the Cooperative Ecosystem Studies Unit (CESU) Program, which is a partnership mechanism used by federal agencies to collaborate with universities, research institutions, and other partners on research, technical assistance, and education. Because it is a CESU opportunity, eligibility is limited: applicants must be participating partners in the Rocky Mountain CESU network. The assistance listing associated with the opportunity is CFDA (now commonly referred to as Assistance Listing) 15.808, and the funding activity category is Science and Technology and other Research and Development, reflecting that the deliverables are expected to be research-oriented, technical, and method-focused rather than general outreach or on-the-ground implementation alone.
Key practical details included in the source information are the award ceiling of $499,999 and an original closing date of 2024-06-21. The opportunity is posted by the Geological Survey (USGS) and uses a cooperative agreement funding instrument, which typically implies substantial federal involvement during the project (for example, close collaboration with USGS scientists, iterative development of methods, shared decision-making about technical direction, and alignment with NABat program needs). Overall, the opportunity is best understood as targeted support for a Rocky Mountain CESU partner to work directly with USGS/NOROCK to advance Bayesian modeling approaches that improve how acoustic, transect, and colony-count data are integrated and interpreted for bat conservation monitoring at broad geographic scales.Apply for G24AS00369
- The Geological Survey in the science and technology and other research and development sector is offering a public funding opportunity titled "Cooperative Agreement for CESU-affiliated Partner with Rocky Mountain Cooperative Ecosystem Studies Unit" 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 2024-05-21.
- Applicants must submit their applications by 2024-06-21. (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 $499,999.00 in funding.
- Eligible applicants include: Others.
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Frequently Asked Questions (FAQs)
What is the Funding Opportunity Number (FON) for this grant?
The Funding Opportunity Number is G24AS00369.
Which federal agency is offering this opportunity?
This is offered by the U.S. Geological Survey (USGS).
Which USGS center is leading the work described in the opportunity?
The opportunity is led through the Northern Rocky Mountain Science Center (NOROCK).
What type of funding instrument is this?
This opportunity uses a cooperative agreement as the funding instrument.
What does it mean that this is a cooperative agreement?
Based on the description provided, the cooperative agreement structure indicates substantial federal involvement during the project. In practical terms, that can include close collaboration with USGS scientists, iterative development of methods, shared decision-making about technical direction, and alignment with NABat program needs.
Is this a discretionary award?
Yes. It is described as a discretionary cooperative agreement.
What is the main focus of the project?
The project focuses on strengthening the statistical foundation of bat monitoring in the western United States by improving Bayesian, model-based inference for common bat survey data.
What problem is this funding trying to address?
The opportunity is aimed at improving how bat monitoring observations are turned into reliable estimates of bat status and population trends, especially by using modern Bayesian approaches that better handle uncertainty, imperfect detection, and differences among survey methods.
What kinds of data or surveys are emphasized?
The notice emphasizes three core monitoring data streams: stationary acoustic surveys (recorders left in place to capture echolocation calls), mobile transects (acoustics collected while moving along a route), and summertime colony counts (direct counts at roosts or maternity colonies during the summer period).
What are stationary acoustic surveys in the context of this opportunity?
Stationary acoustic surveys refer to deploying acoustic recorders at a location and leaving them in place to record bat echolocation calls.
What are mobile transects in the context of this opportunity?
Mobile transects refer to collecting acoustic data while traveling along a defined route, rather than leaving recorders in one fixed location.
What are summertime colony counts?
Summertime colony counts are direct counts conducted at roosts or maternity colonies during the summer period.
How is this work connected to NABat?
The monitoring methods and data streams highlighted are described as core tools used by the North American Bat Monitoring Program (NABat), a continent-scale effort that compiles and analyzes data to support periodic, range-wide assessments of bat species status and trends.
What is NABat?
NABat stands for the North American Bat Monitoring Program. In the provided description, it is a continent-scale program that compiles and analyzes bat monitoring data to support periodic, range-wide assessments of species status and trends.
What is the intended outcome or use of the improved statistical methods?
The improved models are intended to connect multiple bat monitoring data streams to meaningful biological conclusions in ways that are defensible for management and conservation decisions.
What is meant by "Bayesian, model-based inference" in this opportunity?
Within the context provided, it refers to using modern Bayesian statistical approaches to estimate bat status and trends from survey data, with explicit attention to uncertainty, imperfect detection, and differences among survey methods.
Why does the opportunity emphasize imperfect detection and uncertainty?
The description indicates that bat monitoring data can involve uncertainty and imperfect detection, and that modern Bayesian approaches can better account for these issues when estimating status and population trends.
Is the work expected to be integrated with ongoing USGS and NABat efforts?
Yes. The description frames the effort as part of ongoing statistical leadership and development within NABat and indicates it is meant to contribute to an active monitoring program rather than producing only a standalone report.
Who is expected to collaborate on the project from the federal side?
The opportunity is described as working directly with USGS/NOROCK, including collaboration with USGS scientists as part of the cooperative agreement approach.
What program mechanism is used to issue this award?
The award is issued under the Cooperative Ecosystem Studies Unit (CESU) Program.
What is the CESU Program in the context of this opportunity?
The CESU Program is described as a partnership mechanism used by federal agencies to collaborate with universities, research institutions, and other partners on research, technical assistance, and education.
How does CESU affect eligibility for this opportunity?
Because it is a CESU opportunity, eligibility is limited to participating partners in the Rocky Mountain CESU network.
Who is eligible to apply?
Applicants must be participating partners in the Rocky Mountain CESU network.
Is eligibility open to all organizations?
No. Eligibility is limited due to the CESU structure, and only Rocky Mountain CESU partners are eligible based on the information provided.
What is the Assistance Listing (CFDA) number associated with this opportunity?
The associated Assistance Listing is 15.808 (formerly referenced as CFDA 15.808).
What is the funding activity category?
The funding activity category is Science and Technology and other Research and Development.
Does the opportunity emphasize research-oriented deliverables?
Yes. The category and description indicate the deliverables are expected to be research-oriented, technical, and method-focused rather than general outreach or on-the-ground implementation alone.
What is the maximum award amount (award ceiling)?
The award ceiling is $499,999.
What is the application deadline (closing date) provided?
The original closing date listed is 2024-06-21.
What geographic region is the project focused on?
The project focus is on bat monitoring in the western United States, while also being tied to NABat, which is described as continent-scale.
Why is NOROCK highlighted as part of the opportunity context?
The description notes NOROCK has provided statistical leadership within NABat, including conceptual contributions and ongoing identification of research and development needs for the program's "Bats and Stats Team." This signals the funded work is meant to advance tools used by NABat partners.
What is the "Bats and Stats Team" referenced in the opportunity?
The notice references a NABat "Bats and Stats Team" in the context of identifying and addressing emerging research and development needs, indicating a coordinated group focused on the program's statistical and analytical work.
What is the "probabilistic master sample design" mentioned in the opportunity?
The description states that a NOROCK research statistician developed a probabilistic master sample design to support coordinated monitoring across jurisdictions. This is provided as context for NOROCK's role in NABat-related statistical development.
Is this grant intended for on-the-ground bat conservation actions?
The information provided emphasizes research, technical, and method-focused outcomes aimed at improving statistical inference from monitoring data, rather than describing on-the-ground implementation as the primary purpose.
In plain terms, what will successful work help accomplish?
In practical terms, it is meant to help convert multiple kinds of bat monitoring observations (acoustic and colony-count data) into more reliable estimates of bat status and population trends using Bayesian modeling approaches that handle uncertainty and imperfect detection.
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