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Abstract The terrestrial net ecosystem productivity (NEP) has increased during the past three decades, but the mechanisms responsible are still unclear. We analyzed 17 years (2001–2017) of eddy‐covariance measurements of NEP, evapotranspiration (ET) and light and water use efficiency from a boreal coniferous forest in Southern Finland for trends and inter‐annual variability (IAV). The forest was a mean annual carbon sink (252 [42] gC ), and NEP increased at rate +6.4–7.0 gC (or ca. +2.5% ) during the period. This was attributed to the increasing gross‐primary productivity GPP and occurred without detectable change in ET. The start of annual carbon uptake period was advanced by 0.7 d , and increase in GPP and NEP outside the main growing season contributed ca. one‐third and one‐fourth of the annual trend, respectively. Meteorological factors were responsible for the IAV of fluxes but did not explain the long‐term trends. The growing season GPP trend was strongest in ample light during the peak growing season. Using a multi‐layer ecosystem model, we showed that direct fertilization effect diminishes when moving from leaf to ecosystem, and only 30–40% of the observed ecosystem GPP increase could be attributed to . The increasing trend in leaf‐area index (LAI), stimulated by forest thinning in 2002, was the main driver of the enhanced GPP and NEP of the mid‐rotation managed forest. It also compensated for the decrease of mean leaf stomatal conductance with increasing and LAI, explaining the apparent proportionality between observed GPP and trends. The results emphasize that attributing trends to their physical and physiological drivers is challenged by strong IAV, and uncertainty of LAI and species composition changes due to the dynamic flux footprint. The results enlighten the underlying mechanisms responsible for the increasing terrestrial carbon uptake in the boreal zone.
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Unraveling Forest Complexity: Resource Use Efficiency, Disturbance, and the Structure‐Function Relationship
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.
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- PAR ID:
- 10373600
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Journal of Geophysical Research: Biogeosciences
- Volume:
- 127
- Issue:
- 6
- ISSN:
- 2169-8953
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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