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\begin{document}

\title{Unravelling Forest Complexity: Resource Use Efficiency, Disturbance, and
the Elusive Structure-Function Relationship}



\author[1]{Bailey Murphy}%
\author[1]{Jacob May}%
\author[1]{Brian Butterworth}%
\author[1]{Christian Andresen}%
\author[1]{Ankur Desai}%
\affil[1]{University of Wisconsin Madison}%


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  \date{May 24, 2024}


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\begin{abstract}
Structurally complex forests optimize light and water resources to
assimilate carbon more effectively, leading to higher productivity.
Information obtained from Light Detection and Ranging (LiDAR)-derived
structural complexity (SC) 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 in temperate forests collected
in the CHEESEHEAD19 field campaign with drone LiDAR measurements of SC
to establish which SC metrics were strong drivers of GPP, and tested
potential mediators of the relationship. Mechanistic relationships were
inspected at four metric calculation resolutions 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. SC metrics included in the structure-function
relationship as well as the strength of drivers 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 SC impacts light and
water-sensitive processes, and ultimately GPP. Improved models enhance
our ability to simulate true ecosystem responses to management,
resulting in a more accurate assessment of forest responses to
management regimes and furthering our ability to assess climate
mitigation and strategies.%
\end{abstract}%



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