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Abstract Forest canopy complexity (i.e., the three‐dimensional structure of the canopy) is often associated with increased species diversity as well as high primary productivity across natural forests. However, canopy complexity, tree diversity, and productivity are often confounded in natural forests, and the mechanisms of these relationships remain unclear. Here, we used two large tree diversity experiments in North America to assess three hypotheses: (1) increasing tree diversity leads to increased canopy complexity, (2) canopy complexity is positively related to tree productivity, and (3) the relationship between tree diversity and tree productivity is indirect and driven by the positive effects of canopy complexity. We found that increasing tree diversity from monocultures to mixtures of 12 species increases canopy complexity and productivity by up to 71% and 73%, respectively. Moreover, structural equation modeling indicates that the effects of tree diversity on productivity are indirect and mediated primarily by changes in internal canopy complexity. Ultimately, we suggest that increasing canopy complexity can be a major mechanism by which tree diversity enhances productivity in young forests. 

Abstract Structural diversity—the volume and physical arrangement of vegetation within the three‐dimensional (3D) space of ecosystems—is a predictor of ecosystem function that can be measured at large scales with remote sensing. However, the landscape composition and configuration of structural diversity across macrosystems have not been well described. Using a relatively recently developed method to quantify landscape composition and configuration of continuous habitat or terrain, we propose the application of gradient surface metrics (GSMs) to quantify landscape patterns of structural diversity and provide insights into how its spatial pattern relates to ecosystem function. We first applied an example set of GSMs that represent landscape heterogeneity, dominance, and edge density to Lidar‐derived structural diversity within 28 forested landscapes at National Ecological Observatory Network (NEON) sites. Second, we tested for forest type, geographic location, and climate drivers of macroscale variation in GSMs of structural diversity (GSM‐SD). Third, we demonstrated the utility of these metrics for understanding spatial patterns of ecosystem function in a case study with NDVI, a proxy of productivity. We found that GSM‐SD varied in landscapes within macrosystems, with forest type, geographic location, and climate being significantly related to some but not all metrics. We also found that dominance of high peaks of height and vertical complexity of canopy vegetation and the heterogeneity of the vertical complexity and coefficient of variation of canopy vegetation height within 120‐m patches were negatively correlated with NDVI across the 28 NEON sites. However, forest type always had a significant interaction term between these GSM‐SD and NDVI relationships. Our study demonstrates that GSMs are useful to describe the landscape composition and configuration of structural diversity and its relationship with productivity that warrants further consideration for spatially motivated management decisions. 

Structural diversity, characterizing the volumetric capacity and physical arrangement of biotic components in an ecosystem, controls critical ecosystem functions like light interception, hydrology, and microclimate. This product generates structural diversity metrics for the NEON sites, sourced from the Discrete-Return LiDAR Point Cloud from the NEON Aerial Observation Platform (DP1.30003.001; collected in March 2023). Using R programming, we computed the metrics detailing height, heterogeneity, and density at 30 m, aligned to the Landsat grids, for 243 site years in 57 NEON sites from 2013 to 2022. 

1. Amplified by warming temperatures and drought, recent outbreaks of native bark beetles (Curculionidae: Scolytinae) have caused extensive tree mortality throughout Europe and North America. Despite their ubiquitous nature and important effects on ecosystems, forest recovery following such disturbances is poorly understood, particularly across regions with varying abiotic conditions and outbreak effects. 2. To better understand post-outbreak recovery across a topographically complex region, we synthesized data from 16 field studies spanning subalpine forests in the Southern Rocky Mountains, USA. From 1997 to 2019, these forests were heavily affected by outbreaks of three native bark beetle species (Dendroctonus ponderosae, Dendroctonus rufipennis and Dryocoetes confusus). We compared pre- and post-outbreak forest conditions and developed region-wide predictive maps of post-outbreak (1) live basal areas, (2) juvenile densities and (3) height growth rates for the most abundant tree species – aspen (Populus tremuloides), Engelmann spruce (Picea engelmannii), lodgepole pine (Pinus contorta) and subalpine fir (Abies lasiocarpa). 3. Beetle-caused tree mortality reduced the average diameter of live trees by 28.4% (5.6 cm), and species dominance was altered on 27.8% of field plots with shifts away from pine and spruce. However, most plots (82.1%) were likely to recover towards pre-outbreak tree densities without additional regeneration. Region-wide maps indicated that fir and aspen, non-host species for bark beetle species with the most severe effects (i.e. Dendroctonus spp.), will benefit from outbreaks through increased compositional dominance. After accounting for individual size, height growth for all conifer species was more rapid in sites with low winter precipitation, high winter temperatures and severe outbreaks. 4. Synthesis. In subalpine forests of the US Rocky Mountains, recent bark beetle outbreaks have reduced tree size and altered species composition. While eventual recovery of the pre-outbreak forest structure is likely in most places, changes in species composition may persist for decades. Still, forest communities following bark beetle outbreaks are widely variable due to differences in pre-outbreak conditions, outbreak severity and abiotic gradients. This regional variability has critical implications for ecosystem services and susceptibility to future disturbances.