Skip directly to content

Minimize RSR Award Detail

Research Spending & Results

Award Detail

Doing Business As Name:University of Maryland Center for Environmental Sciences
  • Andrew J Elmore
  • (301) 689-7124
Award Date:06/16/2021
Estimated Total Award Amount: $ 69,912
Funds Obligated to Date: $ 69,912
  • FY 2021=$69,912
Start Date:06/15/2021
End Date:05/31/2024
Transaction Type:Grant
Awarding Agency Code:4900
Funding Agency Code:4900
CFDA Number:47.074
Primary Program Source:040100 NSF RESEARCH & RELATED ACTIVIT
Award Title or Description:Collaborative Research: MSA: Tree crown economics: testing and scaling a functional trait-based theory
Federal Award ID Number:2106058
DUNS ID:021463831
Parent DUNS ID:003256088
Program:MacroSysBIO & NEON-Enabled Sci
Program Officer:
  • Diana Pilson
  • (703) 292-0000

Awardee Location

Street:BOX 775
Awardee Cong. District:01

Primary Place of Performance

Organization Name:University of Maryland Center for Environmental Science
Street:301 Braddock Rd.
Cong. District:06

Abstract at Time of Award

Climate change is subjecting trees to new environmental conditions and it is increasingly important to understand how trees respond to these changes. While ecologists have long known that tree crown architecture (the arrangement and orientation of leaves within a tree crown) can be an important way that trees adapt and acclimate to environmental change, there is not well-established theory or techniques for measuring crown architecture. This study tests novel theory and applies new technologies for measuring crown architecture, including from automated cameras mounted to nine National Ecological Observation Network (NEON) towers in the eastern USA, and from accompanying laser ranging (LiDAR) measurements from the NEON Airborne Observation Platform (AOP). By testing how measured differences in crown architecture relate to coincident airborne and satellite measurements of tree productivity, the research can inform ecological models and forest management techniques aimed at maximizing sustainable forest growth. The research team includes students from West Virginia University (WVU) participating in a research experience for undergraduates (REU) program, as well as hundreds of sixth-graders and their teachers making tree architecture and productivity measurements from a “Sustainability Treehouse” used by the WVU Science Adventure School. Complementing the successful theory of leaf economics, the research develops a trait-based theory of crown economics. First, by measuring the trait of mean leaf angle from new time-lapse cameras mounted to nine NEON towers and the Sustainability Treehouse, and traits of crown density and rugosity from NEON AOP LiDAR data, the researchers assess theory positing that economic tradeoffs drive co-variation in these three crown traits. Second, the researchers examine the role of crown traits in driving patterns of near-infrared reflectance from vegetation (NIRv), as measured by: (1) tower-mounted phenocams, (2) NEON AOP spectral data, and (3) Landsat phenology metrics of peak NIRv reflectance and the rate of NIRv “greendown” within a growing season. The research team uses spatial variability within and across the sites to test that the annual peak of NIRv (and correlated rates of water, carbon, and albedo fluxes) is higher in denser, but less rugose, crowns that have more horizontal leaf angles. And, the team uses temporal variability to gauge the degree to which rates of NIRv greendown are driven by increasingly vertical leaf angles through the growing season. Thus, by analyzing these relationships among crown traits and NIRv, the research can demonstrate how predictions of crown economic theory can elucidate new mechanisms controlling local- to continental-scale responses of forests to climate change. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

For specific questions or comments about this information including the NSF Project Outcomes Report, contact us.