Opportunity Information: Apply for F16AS00362
Apply for F16AS00362
- The Department of the Interior, Fish and Wildlife Service in the information and statistics, natural resources sector is offering a public funding opportunity titled "Broad-scale Analysis of Mule Deer Survival: Understanding Process and Improving Prediction" and is now available to receive applicants.
- Interested and eligible applicants and submit their applications by referencing the CFDA number(s): 15.669, 15.670.
- This funding opportunity was created on Jul 19, 2016.
- Applicants must submit their applications by Jul 26, 2016 This Single Source Award is being awarded in accordance with Department of the Interior Policy 505 DM 2.14 B (1) Unsolicited Proposal, and (4) Unique Qualifications, which allows for award without competition to an applicant.. (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 $110,000.00 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).
[Watch] Creating a grant proposal using the step-by-step wizard inside the applicant portal:
Opportunity Summary:
The Broad-scale Analysis of Mule Deer Survival: Understanding Process and Improving Prediction grant opportunity (Funding Opportunity Number F16AS00362) is a discretionary grant from the U.S. Department of the Interior, Fish and Wildlife Service focused on improving how mule deer survival is measured, explained, and predicted across large geographic areas. It sits within the agency's information and statistics and natural resources work (CFDA 15.669 and 15.670) and is designed to turn existing survival datasets into a standardized, analysis-ready foundation that can support rigorous comparisons across herds, regions, and years. The overall intent is not to launch new field data collection, but to leverage and harmonize survival information that wildlife agencies have already gathered, then use it to better understand the drivers of survival and assess how reliably survival can be forecast under varying environmental conditions.
The work described in the opportunity is organized around four core tasks. First, the recipient is expected to synthesize and standardize existing mule deer survival data in close cooperation with participating state or other wildlife agency biologists. In practical terms, this means compiling datasets that may have been collected with different protocols, time frames, definitions, and metadata standards, and then converting them into a consistent structure so they can be analyzed together. Standardization typically involves aligning variables such as age and sex classes, timing and duration of monitoring periods, censoring rules, cause-of-death coding, spatial referencing, and study design features, while also documenting assumptions and data limitations so results remain interpretable across jurisdictions.
Second, the project aims to estimate biological variation in mule deer survival across time and space. That emphasis signals a focus on quantifying how survival differs among locations, seasons, years, and demographic groups, and on separating meaningful biological differences from noise introduced by sampling variation, uneven monitoring effort, or inconsistent methodologies. The goal is to produce broad-scale survival estimates that reflect real patterns, such as regional differences in overwinter survival, drought-year impacts, or long-term trends, while appropriately accounting for the hierarchical nature of the data (for example, individuals nested within herds or study areas, and repeated measures across years).
Third, the recipient is tasked with estimating relationships between mule deer survival and important environmental covariates. This step moves beyond describing survival patterns to explaining them by linking survival outcomes to factors that plausibly influence mule deer populations. While the announcement does not list specific covariates, the framing suggests the analysis will consider major environmental drivers commonly associated with ungulate survival, such as weather severity, drought indicators, vegetation productivity, habitat conditions, disturbance, or other landscape and climatic variables. The intent is to identify which covariates are most strongly associated with survival and under what conditions those relationships hold, helping managers understand mechanisms and evaluate how changing environments might affect mule deer persistence.
Fourth, the opportunity calls for testing the predictive accuracy of the survival analysis. This is a key applied deliverable: it is not enough to fit statistical models that explain past survival; the project also needs to evaluate how well those models predict survival in new times or places. Predictive testing often involves techniques like cross-validation, withholding subsets of data, or evaluating model performance against independent datasets, with the aim of determining whether survival predictions are robust enough to support management planning. This component helps ensure the final products are useful for decision-making, such as anticipating low-survival years, prioritizing habitat actions, or informing broader population modeling efforts.
From an administrative standpoint, this opportunity is a single expected award with an award ceiling of $110,000. It was issued on July 19, 2016, with an original closing date of July 26, 2016, indicating a short turnaround consistent with a targeted award. The notice states it is a single-source award made under Department of the Interior policy (505 DM 2.14 B) provisions for unsolicited proposals and unique qualifications, which allows the agency to make an award without open competition when a specific applicant is justified based on specialized capability or a proposal initiated by the applicant. Eligibility is listed broadly as "Others" with clarification referenced in the full eligibility text, but the single-source language signals that the award was intended for a particular organization or team with distinctive expertise or access to the necessary data partnerships.
Overall, the opportunity supports an applied, collaborative data-science and ecological statistics effort: assemble and harmonize multi-agency mule deer survival data, quantify how survival varies across landscapes and years, identify environmental drivers linked to those changes, and then validate whether the resulting models can reliably predict survival outcomes. The expected end value is a more defensible, comparable, and forecast-ready understanding of mule deer survival that can strengthen regional management and conservation planning.
Frequently Asked Questions (FAQs)
What is the "Broad-scale Analysis of Mule Deer Survival: Understanding Process and Improving Prediction" grant opportunity?
It is a discretionary grant opportunity from the U.S. Department of the Interior, Fish and Wildlife Service (Funding Opportunity Number F16AS00362). The project focuses on improving how mule deer survival is measured, explained, and predicted across large geographic areas by using and harmonizing existing survival datasets.
What agency is offering this grant?
The U.S. Department of the Interior (DOI), Fish and Wildlife Service (FWS).
What is the Funding Opportunity Number (FON) for this award?
F16AS00362.
What program areas does this opportunity fall under?
The notice places it within the agency's information and statistics and natural resources work, under CFDA 15.669 and 15.670.
What is the main purpose of the project?
The purpose is to turn existing mule deer survival datasets into a standardized, analysis-ready foundation that supports rigorous comparisons across herds, regions, and years, and to use that foundation to better understand drivers of survival and evaluate how reliably survival can be predicted under varying environmental conditions.
Is this grant intended to fund new field data collection?
No. The overall intent is not to launch new field data collection, but to leverage, synthesize, and harmonize survival information already gathered by wildlife agencies.
What types of data will be used in this project?
Existing mule deer survival datasets held by participating state or other wildlife agencies, potentially collected using different protocols, time frames, definitions, and metadata standards.
What are the core tasks described in the opportunity?
The work is organized into four tasks: (1) synthesize and standardize existing mule deer survival data; (2) estimate biological variation in survival across time and space; (3) estimate relationships between survival and environmental covariates; and (4) test the predictive accuracy of the survival analysis.
What does "synthesize and standardize existing mule deer survival data" mean in practice?
It means compiling datasets collected under different approaches and converting them into a consistent structure so they can be analyzed together. The standardization also includes documenting assumptions and data limitations so results remain interpretable across jurisdictions.
What kinds of differences between datasets does standardization need to address?
The opportunity highlights aligning items such as age and sex classes, timing and duration of monitoring periods, censoring rules, cause-of-death coding, spatial referencing, and study design features, along with related metadata and documentation.
Who is the recipient expected to work with during data synthesis and standardization?
The recipient is expected to work in close cooperation with participating state or other wildlife agency biologists.
What does the project mean by estimating "biological variation" in mule deer survival?
It refers to quantifying how survival differs among locations, seasons, years, and demographic groups, and separating meaningful biological differences from variation introduced by sampling noise, uneven monitoring effort, or inconsistent methodologies.
What broad patterns of survival variation does the opportunity suggest might be examined?
Examples implied in the description include regional differences in overwinter survival, drought-year impacts, and long-term trends, while accounting for the structure of the data across herds/study areas and years.
Does the opportunity specify how the analysis should handle data collected across herds and years?
Yes, it notes the need to account for the hierarchical nature of the data, such as individuals nested within herds or study areas, and repeated measures across years.
What is meant by estimating relationships between survival and environmental covariates?
This task focuses on explaining survival patterns by linking survival outcomes to environmental factors that plausibly influence mule deer populations, helping identify which factors are most strongly associated with survival and under what conditions.
Does the announcement list specific environmental covariates that must be used?
No specific covariates are listed, but the description suggests considering major drivers commonly associated with ungulate survival.
What kinds of environmental drivers are suggested as likely covariates?
The opportunity suggests categories such as weather severity, drought indicators, vegetation productivity, habitat conditions, disturbance, and other landscape and climatic variables.
What is the purpose of testing predictive accuracy in this project?
The goal is to determine whether models that explain past survival can reliably predict survival in new times or places, ensuring the final products are useful for management and planning.
How might predictive accuracy be tested according to the opportunity description?
The description points to approaches such as cross-validation, withholding subsets of data, or evaluating model performance against independent datasets.
What are examples of management uses the predictive component could support?
The notice suggests uses such as anticipating low-survival years, prioritizing habitat actions, and informing broader population modeling efforts.
How many awards are expected under this funding opportunity?
A single expected award.
What is the maximum award amount (award ceiling)?
$110,000.
When was this funding opportunity issued?
July 19, 2016.
What was the original closing date for the opportunity?
July 26, 2016.
What does the notice indicate about competition for this award?
It states the award is a single-source award made under DOI policy (505 DM 2.14 B) provisions for unsolicited proposals and unique qualifications, meaning the agency can make an award without open competition when a specific applicant is justified based on specialized capability or a proposal initiated by the applicant.
What does "single-source" imply for prospective applicants?
Based on the notice language, it signals the award was intended for a particular organization or team with distinctive expertise or access to the necessary data partnerships.
Who is eligible to apply?
Eligibility is listed broadly as "Others," with additional clarification referenced in the full eligibility text. The single-source language suggests the opportunity was targeted to a specific qualified applicant.
What is the expected end value or outcome of the project?
The intended outcome is a more defensible, comparable, and forecast-ready understanding of mule deer survival across large areas, built from standardized multi-agency datasets, with validated models that support regional management and conservation planning.
Browse more opportunities from the same category: Information and Statistics, Natural Resources
Next opportunity: Resources Intern
Previous opportunity: Propagation of Public Lands Enrichment Project
USGrants.org Applicant Portal:
Are you interested in learning about about how to apply for this government funding opportunity? You can create a free applicant account and receive instant access to our applicant portal that many business owners like you have benefited from.
Apply for F16AS00362
[Watch] how do funding administrators access proposals?
Applicants also applied for:
Applicants who have applied for this opportunity (F16AS00362) also looked into and applied for these:
| Funding Opportunity |
|---|
| Preservation and Documentation of National Park Service Museum Collections Apply for P16AS00386 Funding Number: P16AS00386 Agency: Department of the Interior, National Park Service Category: Information and Statistics, Natural Resources Funding Amount: $90,000 |
| Glacier Bay NP Backcountry/Wilderness Visitor Use Study Apply for P16AS00520 Funding Number: P16AS00520 Agency: Department of the Interior, National Park Service Category: Information and Statistics, Natural Resources Funding Amount: $100,000 |
| FY17 Great Northern LCC Funding Guidance Apply for F17AS00042 Funding Number: F17AS00042 Agency: Department of the Interior, Fish and Wildlife Service Category: Information and Statistics, Natural Resources Funding Amount: $1,000,000 |
| Visitor Use Study at Katmai NP&P and Lake Clark NP&P Apply for P17AS00027 Funding Number: P17AS00027 Agency: Department of the Interior, National Park Service Category: Information and Statistics, Natural Resources Funding Amount: $120,000 |
| USFWS Region 6 Aquatic Invasive Species Program 2017 Apply for F17AS00080 Funding Number: F17AS00080 Agency: Department of the Interior, Fish and Wildlife Service Category: Information and Statistics, Natural Resources Funding Amount: $100,000 |
| Conservation Assessment and Mapping Products for Rio Grande Fishes Apply for F17AS00117 Funding Number: F17AS00117 Agency: Department of the Interior, Fish and Wildlife Service Category: Information and Statistics, Natural Resources Funding Amount: $42,000 |
| Recreational Trail Use Visitor Survey, Santa Monica Mountains National Recreation Area Apply for P17AS00427 Funding Number: P17AS00427 Agency: Department of the Interior, National Park Service Category: Information and Statistics, Natural Resources Funding Amount: $80,000 |
| Biological Studies at Fort Carson, Colorado Apply for F17AS00275 Funding Number: F17AS00275 Agency: Department of the Interior, Fish and Wildlife Service Category: Information and Statistics, Natural Resources Funding Amount: $1,000,000 |
| Section 10 Permits Database Apply for F17AS00320 Funding Number: F17AS00320 Agency: Department of the Interior, Fish and Wildlife Service Category: Information and Statistics, Natural Resources Funding Amount: $18,000 |
| Facilitating WAFWA population level monitoring and analyses Apply for F17AS00318 Funding Number: F17AS00318 Agency: Department of the Interior, Fish and Wildlife Service Category: Information and Statistics, Natural Resources Funding Amount: $500,000 |
| White Sturgeon Sex and Stage of Maturity in Lower Columbia River, Canada Apply for F17AS00358 Funding Number: F17AS00358 Agency: Department of the Interior, Fish and Wildlife Service Category: Information and Statistics, Natural Resources Funding Amount: $120,000 |
| Characterization of space use of birds utilizing newly-restored riparian buffer habitat. Apply for F17AS00451 Funding Number: F17AS00451 Agency: Department of the Interior, Fish and Wildlife Service Category: Information and Statistics, Natural Resources Funding Amount: $70,000 |
| Johnson Grass Control on McConnell AFB Apply for F17AS00452 Funding Number: F17AS00452 Agency: Department of the Interior, Fish and Wildlife Service Category: Information and Statistics, Natural Resources Funding Amount: $2,000,000 |
| The Effect of Bear Viewers on Bears at Katmai National Park & Preserve Apply for P18AS00021 Funding Number: P18AS00021 Agency: Department of the Interior, National Park Service Category: Information and Statistics, Natural Resources Funding Amount: $50,000 |
| USFWS Region 6 Aquatic Invasive Species Program 2018 Apply for F18AS00121 Funding Number: F18AS00121 Agency: Department of the Interior, Fish and Wildlife Service Category: Information and Statistics, Natural Resources Funding Amount: $110,000 |
| Lake Roosevelt Burbot Maturation Apply for F18AS00126 Funding Number: F18AS00126 Agency: Department of the Interior, Fish and Wildlife Service Category: Information and Statistics, Natural Resources Funding Amount: $26,230 |
| Community Harvest Assessment Buckland Baseline Update Apply for P18AS00332 Funding Number: P18AS00332 Agency: Department of the Interior, National Park Service Category: Information and Statistics, Natural Resources Funding Amount: $115,594 |
| Northern Great Plains Joint Venture - III Apply for F18AS00290 Funding Number: F18AS00290 Agency: Department of the Interior, Fish and Wildlife Service Category: Information and Statistics, Natural Resources Funding Amount: $1,250,000 |
| Wildlife Occupancy Modelling and Monitoring in Sonoran Desert Parks Apply for P18AS00501 Funding Number: P18AS00501 Agency: Department of the Interior, National Park Service Category: Information and Statistics, Natural Resources Funding Amount: $34,391 |
| USAFA Urban Reforestation Apply for F18AS00295 Funding Number: F18AS00295 Agency: Department of the Interior, Fish and Wildlife Service Category: Information and Statistics, Natural Resources Funding Amount: $30,000 |
Grant application guides and resources
It is always free to apply for government grants. However the process may be very complex depending on the funding opportunity you are applying for. Let us help you!
Apply for Grants
Premium leads for funding administrators, grant writers, and loan issuers
Thousands of people visit our website for their funding needs every day. When a user creates a grant proposal and files for submission, we pass the information on to funding administrators, grant writers, and government loan issuers.
If you manage government grant programs, provide grant writing services, or issue personal or government loans, we can help you reach your audience.
Subscribe to Leads
Request more information:
Would you like to learn more about this funding opportunity, similar opportunities to "F16AS00362", eligibility, application service, and/or application tips? Submit an inquiry below:
Don't forget to subscribe to our grant alerts mailing list to receive weekly alerts on new and updated grant funding opportunities like this one in your email.