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| Funder | National Science Foundation (US) |
|---|---|
| Recipient Organization | University of Notre Dame |
| Country | United States |
| Start Date | Jun 01, 2021 |
| End Date | Jun 30, 2023 |
| Duration | 759 days |
| Number of Grantees | 1 |
| Roles | Principal Investigator |
| Data Source | National Science Foundation (US) |
| Grant ID | 2141836 |
Forests play a key role in regulating climate due to their ability absorb and store CO2 from the atmosphere. While often treated as a whole, the properties of forests are the aggregated outcome of processes happening on the level of thousands of individual trees. Individual trees within and between species in a forest vary in their physiological and growth response to the environment.
Quantifying this variation is critical for understanding how forests regulate the carbon cycle and therefore for improving models that project how forests will respond to future fluctuations in climate. The present research project uses cutting edge genetic technology coupled with detailed measurements of individual tree growth and physiology to address these outstanding grand challenges in forest biology.
Forested ecosystems are key players in the global carbon cycle. A grand challenge for those investigating current and projecting future forest functioning is linking processes occurring at the level of a leaf to those occurring at the level of a forest. Critical to these efforts is an understanding of where variation exists and the degree to which knowing that information improves projections.
Individuals interact with their environments via their phenotypes and the resulting performance ultimately scales up to provide emergent ecosystem-level properties. Thus, acute and chronic changes to the environment are inherently an individual-level phenomenon. Rich assays of leaf level functioning and linkages of such information to individual tree and whole forest carbon flux are rare in tree ecology due to logistical constraints and a focus on a handful of leaf properties.
The present project assays leaf level functioning throughout several growing seasons through the quantification of leaf physiological traits and gene expression. The sampling is performed at two NEON sites where significant infrastructure exists allowing us to link these leaf level properties to forest scale measures of carbon flux and the environment.
University of Notre Dame
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