BLM OR WA Cooperative Ecosystems Studies Unit (CESU) Panther Creek Weather Modeling | Apply Online

FAQs - BLM OR/WA CESU Panther Creek Weather Modeling (Funding Opportunity Number L14AS00038)

What is the BLM OR/WA CESU Panther Creek Weather Modeling opportunity (L14AS00038)?

This was a Bureau of Land Management (BLM) discretionary grant offered as a cooperative agreement under the Natural Resources funding activity area. The project focus was Panther Creek, with the goal of improving BLM's understanding and prediction of forest growth and productivity by integrating detailed forest structure information with local weather measurements and mechanistic growth modeling.

What type of funding instrument was used?

The opportunity was offered as a cooperative agreement (noted under the BLM OR/WA Cooperative Ecosystems Studies Unit, or CESU).

How many awards were expected?

The announcement anticipated a single award.

What was the estimated total program funding and the award ceiling?

The estimated total program funding level was $400,000. The award ceiling was $200,000. The award floor was listed as $1.

Was cost sharing or a matching contribution required?

No. The opportunity stated that no cost sharing or matching was required.

Who was eligible to apply?

Eligible applicants were limited to public and state-controlled institutions of higher education, consistent with CESU cooperative research and technical assistance partnerships.

What was the main purpose of the project?

The project was designed to help BLM better estimate and predict forest growth and productivity at Panther Creek by linking (1) fine-scale forest structure metrics derived from existing LiDAR data with (2) on-the-ground weather measurements, and then using these combined inputs in mechanistic forest growth models.

What is meant by an integrated modeling approach in this opportunity?

The integrated approach refers to combining two key information streams: detailed stand structure information (from existing LiDAR-derived data) and measured environmental conditions (from weather stations in or near the study area). These inputs were intended to drive mechanistic forest growth models that translate forest structure plus weather into productivity estimates.

What data sources were specifically mentioned?

The opportunity referenced existing LiDAR-derived data from Panther Creek and weather station measurements in or near the study area.

What kinds of forest structure attributes were expected from the LiDAR data?

LiDAR-derived products were expected to provide fine-scale descriptions of stand structure, including canopy height and density patterns, as well as other structural attributes that influence light interception, microclimate, and growth.

What weather variables were highlighted as important model inputs?

Key environmental inputs mentioned were precipitation and photosynthetically active radiation (PAR), described as the portion of sunlight plants use for photosynthesis.

What is PAR in the context of this project?

PAR stands for photosynthetically active radiation. In this opportunity, PAR was identified as a critical weather-derived input needed to drive mechanistic growth models because it represents the portion of sunlight used by plants for photosynthesis.

What modeling outputs were the project aiming to produce?

The modeling was intended to produce estimates of net primary production (NPP) and then partition that productivity into different components at both stand and individual-tree scales, such as allocation to stems, branches, and other biomass components.

What is NPP as referenced in the opportunity?

NPP refers to net primary production. In this project, NPP was the productivity metric to be estimated by combining LiDAR-derived structure data with measured weather inputs in mechanistic growth models.

Why combine LiDAR-derived structure data with measured weather data?

The stated intent was to achieve a more defensible, data-driven estimate of forest productivity and allocation patterns than would be possible using either remote sensing (structure data) or weather data alone. The integration was meant to ground productivity estimates in measured weather inputs and detailed structural descriptions.

How does this work support BLM resource management needs?

The opportunity described the work as supporting resource management needs tied to vegetation growth, habitat conditions, and broader ecosystem function by improving understanding and prediction of forest growth and productivity at Panther Creek.

What CFDA program area was this aligned with?

The opportunity aligned with CFDA program area 15.231, described as Fish, Wildlife and Plant Conservation Resource Management.

When was the opportunity posted, and when did it close?

The announcement was posted on February 13, 2014. The application closing date was March 19, 2014.

Is this opportunity still open?

No. The listing was later archived on February 12, 2015.

Who was the point of contact for application access issues?

The point of contact listed for application access issues was Jessica Clark, Grants Management Specialist at BLM. Phone: 503-808-6226. Email: j1clark@blm.gov.

What geographic area did the project focus on?

The work was focused on Panther Creek, using Panther Creek-specific LiDAR-derived data and weather station inputs from in or near the study area.

What is the relationship between CESU and this opportunity?

The opportunity was associated with the BLM OR/WA Cooperative Ecosystems Studies Unit (CESU), and eligibility was limited to public and state-controlled institutions of higher education, consistent with CESU cooperative research and technical assistance partnerships.