| NSF Org: |
DEB Division Of Environmental Biology |
| Recipient: |
|
| Initial Amendment Date: | June 16, 2021 |
| Latest Amendment Date: | June 16, 2021 |
| Award Number: | 2106080 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Matthew Kane
mkane@nsf.gov (703)292-7186 DEB Division Of Environmental Biology BIO Directorate for Biological Sciences |
| Start Date: | June 15, 2021 |
| End Date: | May 31, 2025 (Estimated) |
| Total Intended Award Amount: | $249,963.00 |
| Total Awarded Amount to Date: | $249,963.00 |
| Funds Obligated to Date: |
|
| History of Investigator: |
|
| Recipient Sponsored Research Office: |
886 CHESTNUT RIDGE ROAD MORGANTOWN WV US 26505-2742 (304)293-3998 |
| Sponsor Congressional District: |
|
| Primary Place of Performance: |
330 Brooks Hall Morgantown WV US 26506-6300 |
| Primary Place of
Performance Congressional District: |
|
| Unique Entity Identifier (UEI): |
|
| Parent UEI: |
|
| NSF Program(s): | MacroSysBIO & NEON-Enabled Sci |
| Primary Program Source: |
|
| Program Reference Code(s): |
|
| Program Element Code(s): |
|
| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.074 |
ABSTRACT
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.
Please report errors in award information by writing to: awardsearch@nsf.gov.
