Biodiversity and ecosystem function in three dimensions: Using NEON airborne remote sensing to understand ecosystem patterns and processes in a temperate forest

Kyla Dahlin and Meicheng Shen, Geography, Environment, & Spatial Sciences, Michigan State University, East Lansing, MI, Aaron G. Kamoske, US Forest Service, Salt Lake City, UT, Jeffrey Atkins, Virginia Commonwealth University, Richmond, VA, Ben Bond-Lamberty, Joint Global Change Research Institute, Pacific Northwest National Laboratory, Christopher Gough, Department of Biology, Virginia Commonwealth University, Richmond, VA, Shawn P. Serbin, Environmental and Climate Sciences Department, Brookhaven National Laboratory, Upton, NY, Scott C. Stark, Department of Forestry, Michigan State University, East Lansing, MI, Jason Tallant, University of Michigan, Ann Arbor, MI

Background/Question/Methods
The three-dimensional structure of forests, a product of canopy architecture and resource distribution, is both an indicator and a driver of the connections between biodiversity and ecosystem function. More structurally heterogeneous forests are often more productive, and should generate more niche space for a wider array of organisms. Here we explore connections between forest 3-D structure, carbon uptake, and biodiversity at the University of Michigan Biological Station (UMBS). Over the past ~100 years, UMBS has both hosted several large-scale disturbance experiments that have reshaped forest structure and been subject to many natural disturbances, making it an ideal setting for exploring connections between structural heterogeneity, biodiversity, and ecosystem function. In August 2019, the National Ecological Observatory Network’s Airborne Observation Platform (NEON AOP) collected hyperspectral imagery and lidar data over UMBS as part of an Assignable Asset campaign. Simultaneously, field data were collected to train the AOP data to generate site-wide maps of the vertical distribution of leaf area density (LAD, m2 m-3), top of canopy leaf traits (leaf mass per area (LMA, g m-2), leaf carbon (%), and leaf nitrogen (%)), and spectral diversity (spectral principal components convex hull volume, SPCHV). We used these maps, individually and combined through an unsupervised clustering approach, to assess their connections with field measured patterns of plant biodiversity and ecosystem function. We compared our maps of forest 3-D structure to known disturbance experiments and their net primary production, tree diversity plots, and understory vegetation.
Results/Conclusions
We found that the AOP-derived maps of structural and functional heterogeneity and spectral diversity successfully distinguished different stand-scale disturbance regimes and their rates of primary production across the landscape, though more subtle disturbances at smaller spatial scales were more difficult to detect. For example, regrowth following clearcut and burn experiments is clearly visible in the AOP data, while more subtle disturbances are difficult to discern from the surrounding landscape. Correlations between remotely sensed metrics of 3-D structure varied in their ability to explain in situ patterns of biodiversity, depending on the specific trophic levels of the organisms and their context. For example, we compared spectral diversity area relationships to species-area relationships both across the landscape and within 1-ha plots. Overall, this work demonstrates the importance of both horizontal and vertical structure in understanding the spatial context of ecosystem processes and connections between biodiversity and ecosystem function at the landscape scale.