Abstract
Structurally complex forests optimize resources to assimilate carbon more effectively, leading to higher productivity. Information obtained from Light Detection and Ranging (LiDAR)-derived canopy structural complexity (CSC) metrics across spatial scales serves as a powerful indicator of ecosystem-scale functions such as gross primary productivity (GPP). However, our understanding of mechanistic links between forest structure and function, and the impact of disturbance on the relationship, is limited. Here, we paired eddy covariance measurements of carbon and water fluxes from nine forested sites within the 10 × 10 km CHEESEHEAD19 study domain in Northern Wisconsin, USA with drone LiDAR measurements of CSC to establish which CSC metrics were strong drivers of GPP, and tested potential mediators of the relationship. Mechanistic relationships were inspected at five resolutions (0.25, 2, 10, 25, and 50 m) to determine whether relationships persisted with scale. Vertical heterogeneity metrics were the most influential in predicting productivity for forests with a significant degree of heterogeneity in management, forest type, and species composition. CSC metrics included in the structure-function relationship as well as driver strength was dependent on metric calculation resolution. The relationship was mediated by light use efficiency (LUE) and water use efficiency (WUE), with WUE being a stronger mediator and driver of GPP. These findings allow us to improve representation in ecosystem models of how CSC impacts light and water-sensitive processes, and ultimately GPP. Improved models enhance our capacity to accurately simulate forest responses to management, furthering our ability to assess climate mitigation strategies.
Original language | English |
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Article number | e2021JG006748 |
Journal | Journal of Geophysical Research: Biogeosciences |
Volume | 127 |
Issue number | 6 |
DOIs | |
State | Published - Jun 2022 |
Externally published | Yes |
Funding
This project was financially supported by award AGSˉ1822420 from the National Science Foundation (NSF), the University of Wisconsin‐Madison's Office of the Vice Chancellor for Research and Graduate Education (OVCRGE) fall competition award and NSF Emerging Frontiers Macrosystems Biology award DEBˉ1702996 supporting the Management and Disturbance in Forest Ecosystems (MANDIFORE) project. Jacob May received additional mentorship and funding from Dr. Philip Townsend of the University of Wisconsin‐Madison. Brian Butterworth was additionally supported by the NOAA Physical Sciences Laboratory. We would like to acknowledge that the study domain is located in the ancestral homeland of the Ojibwe people. We honor the indigenous caretakers of these lands before us, today, and of generations to come.
Funders | Funder number |
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NOAA Physical Sciences Laboratory | |
OVCRGE | |
National Science Foundation | |
University of Wisconsin-Madison | |
Office of the Vice Chancellor for Research and Graduate Education, University of Wisconsin-Madison |
Keywords
- LiDAR
- eddy covariance
- forest complexity
- forest management
- scaling
- structure-function