Opportunity Information: Apply for L16AS00112
The BLM UT Cedar City Field Office Landscape Conservation Forecasting Model opportunity (Funding Opportunity Number L16AS00112) is a Bureau of Land Management discretionary grant offered as a cooperative agreement under CFDA 15.231 (Natural Resources). It was designed to fund a single award (Expected Awards: 1) with a maximum federal amount of $110,000, and it was open to unrestricted applicants. The opportunity was posted on May 11, 2016, with an original closing date of July 11, 2016.
This project builds directly on earlier Landscape Conservation Forecasting work that began when the Cedar City Field Office received funding in 2012 for a vegetative monitoring study. That initial effort, carried out by The Nature Conservancy and finalized in a report released in January 2016, focused on the Bald Hills and Hamlin Valley. The earlier study used a practical framework organized around "Maps, Measures, and Models" to connect ecological conditions to specific, on-the-ground vegetation treatment actions. One of the key outputs was a set of recommended management actions for major vegetation types within the Cedar City Field Office, emphasizing treatment approaches expected to yield a high return on investment. Those actions were intended to move ecological sites toward improved Desired Plant Communities while taking cost and budget limits into account.
The new grant opportunity sought a non-federal partner to help the BLM develop science-based management strategies supporting both short-term and long-term watershed restoration across the Cedar City Field Office, with particular attention to the Mountain Home and Pine Valley areas. A central expectation was the use of geospatial methods, including satellite imagery, to help assess conditions at a landscape scale and guide where and how vegetation treatments should be implemented on public lands. Through this collaboration, the BLM and the partner would work on developing state-and-transition ecological models, which are commonly used to describe how plant communities can shift between conditions due to disturbances, management actions, and environmental drivers. These models would then be used to shape and prioritize future restoration projects.
The practical goal of the effort was to produce a decision-support model that helps managers determine where to invest restoration funding on the ground in a cost-beneficial way. In other words, the work is aimed at improving how treatment dollars are targeted by tying ecological condition mapping and predictive modeling to budget realities and expected outcomes, so that restoration actions can be selected and placed where they are most likely to deliver measurable ecological improvement per dollar spent.
The stated public benefit centers on generating GIS-based ecological condition datasets and forecasting tools that predict how conditions may change under different management scenarios. Those products would support the development of clearer management goals, objectives, and actions for future watershed restoration, while also providing scenario-based comparisons of alternative strategies. A notable emphasis is on including cost-benefit analyses in the GIS modeling scenarios, so that the public and land managers can see which restoration approaches and technologies are likely to be the most cost-effective for conserving, protecting, and improving ecological conditions through future vegetation treatments.Apply for L16AS00112
- The Bureau of Land Management in the natural resources sector is offering a public funding opportunity titled "BLM UT Cedar City Field Office Landscape Conservation Forecasting Model" and is now available to receive applicants.
- Interested and eligible applicants and submit their applications by referencing the CFDA number(s): 15.231.
- This funding opportunity was created on 2016-05-11.
- Applicants must submit their applications by 2016-07-11. (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: Unrestricted.
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Frequently Asked Questions (FAQs)
What is the name of this grant opportunity?
The opportunity is titled the "BLM UT Cedar City Field Office Landscape Conservation Forecasting Model" opportunity.
What is the Funding Opportunity Number (FON)?
The Funding Opportunity Number is L16AS00112.
Which federal agency is offering this opportunity?
This opportunity is offered by the Bureau of Land Management (BLM).
What type of award is this?
This is a discretionary grant offered as a cooperative agreement.
What is the CFDA number and program area?
The listing is under CFDA 15.231, Natural Resources.
How many awards were expected?
The opportunity was designed to fund a single award (Expected Awards: 1).
What was the maximum federal funding amount?
The maximum federal amount was $110,000.
Who was eligible to apply?
The opportunity was open to unrestricted applicants.
When was the opportunity posted?
It was posted on May 11, 2016.
What was the original closing date?
The original closing date was July 11, 2016.
What prior work did this project build on?
This project builds directly on earlier Landscape Conservation Forecasting work that began in 2012, when the Cedar City Field Office received funding for a vegetative monitoring study.
Who carried out the earlier vegetative monitoring study?
The earlier effort was carried out by The Nature Conservancy.
When was the earlier study finalized?
The earlier study was finalized in a report released in January 2016.
Which areas did the earlier study focus on?
The initial effort focused on the Bald Hills and Hamlin Valley.
What framework did the earlier study use?
The earlier study used a practical framework organized around "Maps, Measures, and Models" to connect ecological conditions to specific vegetation treatment actions on the ground.
What were some key outputs of the earlier work?
One key output was a set of recommended management actions for major vegetation types within the Cedar City Field Office, emphasizing approaches expected to deliver a high return on investment.
What management objective did the earlier recommended actions support?
Those actions were intended to move ecological sites toward improved Desired Plant Communities while considering cost and budget limitations.
What was the main purpose of the new grant opportunity?
The new opportunity sought a non-federal partner to help BLM develop science-based management strategies that support short-term and long-term watershed restoration across the Cedar City Field Office.
Which areas were highlighted for particular attention in the new effort?
The opportunity placed particular attention on the Mountain Home and Pine Valley areas.
What methods were expected to be used in the project?
A central expectation was the use of geospatial methods, including satellite imagery, to assess conditions at a landscape scale and guide where and how vegetation treatments should be implemented on public lands.
What kind of ecological modeling was mentioned?
The work included developing state-and-transition ecological models, which describe how plant communities can shift between conditions due to disturbances, management actions, and environmental drivers.
How were the ecological models intended to be used?
They were intended to shape and prioritize future restoration projects.
What is the practical end product the project aimed to deliver?
The practical goal was to produce a decision-support model that helps managers determine where to invest restoration funding on the ground in a cost-beneficial way.
How does the project tie restoration decisions to budgets?
The effort aimed to improve how treatment dollars are targeted by linking ecological condition mapping and predictive modeling to budget realities and expected outcomes, so restoration actions can be selected and placed where they are most likely to deliver measurable ecological improvement per dollar spent.
What public benefits were stated for this opportunity?
The stated public benefit centers on generating GIS-based ecological condition datasets and forecasting tools that predict how conditions may change under different management scenarios.
What kinds of decisions would the forecasting tools support?
These products would support clearer management goals, objectives, and actions for future watershed restoration and enable scenario-based comparisons of alternative strategies.
Was cost-benefit analysis emphasized as part of the work?
Yes. A notable emphasis was on including cost-benefit analyses in the GIS modeling scenarios to show which restoration approaches and technologies are likely to be the most cost-effective for conserving, protecting, and improving ecological conditions through future vegetation treatments.
What land base was the work intended to inform?
The opportunity specifically referenced guiding vegetation treatments on public lands within the Cedar City Field Office.
How does this opportunity relate to watershed restoration?
It focused on developing science-based strategies and forecasting tools that would support both short-term and long-term watershed restoration planning and prioritization across the Cedar City Field Office.
What is meant by "scenario-based comparisons" in this context?
Based on the description, scenario-based comparisons refer to using GIS-based modeling to compare alternative management or restoration strategies and see how ecological conditions and cost-effectiveness may differ under each scenario.
Did the opportunity specify that the partner must be non-federal?
Yes. The opportunity sought a non-federal partner to collaborate with BLM on the described work.
What is the core idea behind the decision-support model described?
The core idea is to combine ecological condition mapping, forecasting, and cost-benefit considerations so managers can prioritize vegetation treatments where they are expected to generate the greatest ecological improvement relative to available funding.
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