Background/Question/Methods Forest structural diversity characterizes heterogeneity in the three-dimensional location, distribution, and configuration of biotic components in a forest, and includes aggregate metrics like cover, complexity, volume, and density. Studies have found structural diversity to serve as an effective remotely-sensible proxy for biodiversity that is simultaneously accurate, consistent across space and time, and capable of characterizing large extents. This empirically-observed biodiversity – forest structure relationship (BSR) arises in part because structural diversity reflects underlying morphological diversity among constituent individuals (e.g. trees), which subsequently affects spatial-heterogeneity in limiting resources, and by extension, niche distributions and habitat diversity across a range of taxa. However, little is known how BSRs generalize to continental scales, or how climate interacts with structure to jointly drive local patterns in biodiversity. In this study, we used spatial GLMMs based on field measurements, airborne lidar from the NEON airborne observatory, and satellite lidar from the Global Ecosystem Dynamics Investigation (GEDI) sensor to characterize how BSRs vary across the disparate biomes of the United States.
Results provide evidence for significant broad-scale BSRs – based on fine-scale, spatially-coincident plot-lidar BSRs, as well as more generalized relationships using large-scale GEDI sampling. Although large-scale, large-volume sampling doesn’t reflect plot-specific relationships, it does sufficiently reflect regionally-characteristic structural profiles that, in combination with climate and topography, correlate highly with biogeographic patterns in diversity. Critically, climate variables related to water availability, but not temperature, were significant and strong predictors of diversity that interact with structure across coldness, mean temperature, and evapotranspiration gradients to jointly explain variance in BSRs across biomes. We conclude that results suggest that the variance observed across this continental domain reflect how large-scale ecoclimatic gradients differentially impact community dynamics in different environmental contexts. These findings reinforce the centrality of local context dependence in assessing biogeographical patterns of forest biodiversity and provide an empirical foundation for generalizing remotely-sensed estimates of climate and forest structure to model habitat and biodiversity over vast extents.