Opportunity Information: Apply for L10AS00225
Apply for L10AS00225
- The Bureau of Land Management in the natural resources sector is offering a public funding opportunity titled "Grassland Bird Management on Multiple Use Landscapes" and is now available to receive applicants.
- Interested and eligible applicants and submit their applications by referencing the CFDA number(s): 15.231 Fish, Wildlife and Plant Conservation Resource Management.
- This funding opportunity was created on Jul 23, 2010 and posted on Jul 23, 2010.
- Applicants must submit their applications by Aug 23, 2010. (Agency may still review applications by suitable applicants for the remaining/unused allocated funding in 2026.)
- The funding agency has allocated a total of $100,000.00 to eligible and selected applicants.
- Each selected applicant is eligible to receive up to $5,000.00 in funding.
- The number of recipients for this funding is limited to 1 candidate(s).
- Eligible applicants include: Public and State controlled institutions of higher education.
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Opportunity Summary:
The Grassland Bird Management on Multiple Use Landscapes grant opportunity (Funding Opportunity Number L10AS00225) was a discretionary funding announcement from the U.S. Department of the Interior, Bureau of Land Management (BLM), focused on improving how grassland bird conservation and habitat management decisions are made across working, multiple-use landscapes. The core purpose of the project was to take existing grassland bird occurrence and monitoring data and combine it with spatially explicit habitat and management variables to build advanced species habitat models. These models would be used to predict where grassland birds are most likely to occur and, importantly, to identify which habitat and management factors have the greatest influence on their distribution. In practical terms, the project was designed to help land managers prioritize on-the-ground actions by pointing to the places and conditions where management would likely produce the biggest conservation gains.
A central theme of the opportunity was the use of predictive modeling as a decision-support tool. Rather than collecting entirely new field data, the emphasis was on synthesizing and analyzing data that already existed, then pairing those bird records with mapped environmental and management-related parameters. The announcement highlighted examples of influential features that would be evaluated in the modeling process, including vegetation type, pasture size, and distance from water. By integrating these variables in a spatial framework, the resulting habitat models could generate distribution predictions that guide where to focus management activities, how to adjust land-use practices, and how to allocate limited conservation resources across large landscapes that serve multiple objectives.
From an administrative standpoint, the award was offered as a cooperative agreement, meaning BLM expected to have substantial involvement with the recipient during the project. The funding activity category was Natural Resources, and the program was associated with CFDA number 15.231 (Fish, Wildlife and Plant Conservation Resource Management). The opportunity anticipated a single award, with an estimated total funding amount of $100,000. The listing also indicated an award ceiling and floor of $5,000, which appears in the source information as stated. Cost sharing or matching was not required.
Eligibility was limited to public and state-controlled institutions of higher education, positioning the opportunity for universities and similar entities with expertise in wildlife ecology, quantitative modeling, GIS and remote sensing, and conservation planning. The posting date was July 23, 2010, with an original and current closing date of August 23, 2010, and the opportunity was archived on September 1, 2010. Additional details were available through Grants.gov, and the contact for access issues or questions was Lori Anderson at BLM (406-896-5196, landerso@blm.gov), listed as the Grants Management Officer.
Overall, the grant targeted a fairly specific outcome: produce scientifically defensible, spatially explicit habitat predictions for grassland birds and translate those predictions into clearer management priorities on multiple-use lands. The emphasis on identifying the most influential habitat and management drivers suggests the deliverables were expected to be directly actionable, helping managers decide not only where birds are likely to be, but also which levers (such as vegetation management, pasture configuration, or water-related factors) matter most for improving or maintaining grassland bird habitat.
Grassland Bird Management on Multiple Use Landscapes (L10AS00225) - FAQs
What is the Grassland Bird Management on Multiple Use Landscapes grant opportunity?
This was a discretionary funding opportunity from the U.S. Department of the Interior, Bureau of Land Management (BLM) focused on improving grassland bird conservation and habitat management decisions across working, multiple-use landscapes.
What is the Funding Opportunity Number (FON) for this announcement?
The Funding Opportunity Number was L10AS00225.
What was the main goal of the project funded under this opportunity?
The core goal was to combine existing grassland bird occurrence and monitoring data with spatially explicit habitat and management variables to build advanced species habitat models. These models were intended to predict where grassland birds are most likely to occur and identify which habitat and management factors most influence their distribution.
What kinds of outcomes was BLM looking for from the project?
The opportunity targeted a specific outcome: scientifically defensible, spatially explicit habitat predictions for grassland birds that could be translated into clearer management priorities on multiple-use lands. The intent was that results would be directly actionable for land managers.
How were the habitat models expected to be used by land managers?
The models were framed as decision-support tools to help managers prioritize on-the-ground actions by pointing to the places and conditions where management would likely produce the biggest conservation gains, and by clarifying which management "levers" matter most.
Was the emphasis on collecting new field data?
No. The announcement emphasized synthesizing and analyzing data that already existed, then pairing those bird records with mapped environmental and management-related parameters in a spatial framework.
What types of data or variables were expected to be integrated into the modeling?
The project was expected to integrate existing grassland bird occurrence and monitoring datasets with spatially mapped habitat and management variables. The announcement specifically highlighted examples such as vegetation type, pasture size, and distance from water.
What is meant by "spatially explicit" habitat and management variables in this opportunity?
In this context, "spatially explicit" means the habitat and management factors are mapped and can be analyzed in relation to location across the landscape, enabling the model to generate geographic predictions of grassland bird distribution.
Why did the opportunity focus on identifying influential habitat and management drivers?
Because the project was intended to inform practical management decisions. Knowing which factors most influence bird distribution helps managers decide not only where birds are likely to occur, but also which habitat or management changes are most likely to improve or maintain suitable conditions.
What agency offered this grant opportunity?
The opportunity was offered by the U.S. Department of the Interior, Bureau of Land Management (BLM).
What type of award instrument was anticipated?
The award was offered as a cooperative agreement.
What does it mean that the award was a cooperative agreement?
It means BLM expected to have substantial involvement with the recipient during the project, rather than operating strictly as a hands-off funder.
What was the funding activity category for this opportunity?
The funding activity category was Natural Resources.
What CFDA number was associated with this program?
The opportunity was associated with CFDA 15.231 (Fish, Wildlife and Plant Conservation Resource Management).
How many awards were anticipated?
The announcement anticipated a single award.
What was the estimated total funding amount?
The estimated total funding amount was $100,000.
What were the stated award ceiling and floor?
The listing indicated an award ceiling and an award floor of $5,000 (as stated in the source information).
Was cost sharing or matching required?
No. Cost sharing or matching was not required.
Who was eligible to apply?
Eligibility was limited to public and state-controlled institutions of higher education, such as universities and similar entities.
What kinds of expertise did the opportunity appear to be geared toward?
Based on the project description, the opportunity aligned with organizations capable of wildlife ecology work and advanced modeling using spatial data, including quantitative modeling, GIS and remote sensing, and conservation planning.
When was the opportunity posted?
The posting date was July 23, 2010.
What were the closing dates for applications?
The original closing date and the current closing date were both August 23, 2010.
Is this opportunity still open?
No. The opportunity was archived on September 1, 2010.
Where were additional details made available?
Additional details were available through Grants.gov.
Who was the listed point of contact for access issues or questions?
The listed contact was Lori Anderson, Grants Management Officer at BLM.
What contact information was provided for the BLM point of contact?
Lori Anderson could be reached at 406-896-5196 or by email at landerso@blm.gov.
What types of landscapes were the models intended to support?
The work was intended to support conservation and management decisions across working, multiple-use landscapes, where land management must balance multiple objectives.
How would the project help allocate limited conservation resources?
By producing distribution predictions and identifying the most influential habitat and management factors, the models could help prioritize where to focus management actions and how to adjust practices to achieve the largest conservation gains across large landscapes.
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