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.

Evaporation and Transpiration From Multiple Proximal Forests and Wetlands

“…This seasonal decline in ET was dominated by a corresponding decline in T (Figure 7a), whereas E was largely aseasonal across the measurement period (Figure 6a) with little difference among ecosystem types in its cumulative sum (Figure 6b) despite different responses to wet conditions that were related to soil texture. The cumulative sum of T across the measurement period differed little among forests as anticipated (Figure 7b), despite differences in forest composition (Butterworth et al, 2021;Murphy et al, 2022), and wetlands supported less cumulative T (Figure 7b). We describe the FVS partitioning outcomes that resulted in these findings before describing seasonal patterns of fluxes and their responses to micrometeorological variability across different ecosystems.…”

Drivers of Decadal Carbon Fluxes Across Temperate Ecosystems

“…These sites sample a broader range of forests, wetlands, and lakes in the landscape that contributed to the scaling goals of the CHEESEHEAD19 study (Butterworth et al, 2021), and included recent clear-cuts to older established forests. Site descriptions are provided at http://cheesehead19.org with further details in Butterworth et al (2021), Murphy et al (2022), andDesai et al (2021) and in the official data repository.…”

“…Aggregation of CO 2 fluxes from a collection of sites in and around the Chequamegon‐Nicolet National Forest in the summers of 2002 and 2003 demonstrated that footprint‐weighted NEE, R eco , and GPP at the tall tower were within 11% of the combined fluxes from 13 surrounding towers (Desai, Noormets, et al., 2008 ). Forest structure and age distribution strongly impact these fluxes, reflecting the history of land management and canopy complexity on modulating regional carbon cycle responses in forests (Desai et al., 2005 , 2007 ; Murphy et al., 2022 ). Wetlands and other aquatic landscapes (lakes, rivers, and ponds) form more than a quarter of the landscape and have been shown to have unique responses to hydrologic change (Buffam et al., 2011 ; Gorsky et al., 2021 ; Pugh et al., 2018 ; Turner et al., 2021 ).…”

Scaling Land‐Atmosphere Interactions: Special or Fundamental?

“…Land-atmosphere field experiments have continued to provide insight on scaling through advances in observing capability as noted in several papers in this collection. For example, from CHEESEHEAD19, Murphy et al (2022) find canopy structural metrics do not linearly scale with spatial resolution, which influences how those metrics link to ecosystem functions through water-use and light-use efficiencies. Meanwhile, with a range of atmospheric profilers and surface radiation observations, Sedlar et al (2022) show how atmospheric boundary layer development is influenced by scales of cloud regimes and its imprint on turbulent fluxes.…”

“…For example, from CHEESEHEAD19, Murphy et al. (2022) find canopy structural metrics do not linearly scale with spatial resolution, which influences how those metrics link to ecosystem functions through water‐use and light‐use efficiencies. Meanwhile, with a range of atmospheric profilers and surface radiation observations, Sedlar et al.…”