Vegetation structural complexity and biodiversity in the Great Smoky Mountains

Seasonal structural stability promoted by forest diversity and composition explains overyielding

The stability of forest productivity is a widely studied phenomenon often associated with tree species diversity. Yet, drivers of stability in forest structure and its consequences for forest productivity remain poorly understood. Using a large (10 ha) young tree diversity experiment, we evaluated how forest structure and multiple dimensions of diversity and composition are related to remotely sensed structural metrics and their stability through the growing season. We then examined whether structural stability (SS) across the growing season (April-October) could explain overyielding (i.e., the net biodiversity effect, NBE) in annual wood productivity. Using Uncrewed Aerial Vehicle-Light Detecting and Ranging (UAV-LiDAR), we surveyed experimental tree communities eight times at regular intervals from before bud break to after leaf senescence to derive metrics associated with canopy height heterogeneity, fractional plant cover, and forest structural complexity (based on fractal geometry). The inverse coefficients of variation for each of these three metrics through the season were used as measures of SS. These metrics were then coupled with annual tree inventories to evaluate their relationships with the NBE. Our findings indicate that wood volume and, to some extent, multiple dimensions of diversity and composition (i.e., taxonomic, phylogenetic, and functional) explain remotely sensed metrics of forest structure and their SS. Increases in wood volume as well as functional and phylogenetic diversity and variability (a measure of diversity independent of species richness) were linked to higher SS of forest complexity and canopy height heterogeneity. We further found that higher SS of forest complexity and fractional plant cover were associated with increased overyielding, which was mostly attributable to the complementarity effect. Structural equation models indicate that the stability of structural complexity explains more variation in NBE among plots than dimensions of diversity or variability, highlighting its value as an informative metric that likely integrates multiple drivers associated with overyielding. This study highlights the potential to integrate remote sensing and ecology to disentangle the role of forest SS in shaping ecological processes.

Unraveling the Influence of Structural Complexity, Environmental, and Geographic Factors on Multi-Trophic Biodiversity in Forested Landscapes

Multi-trophic diversity is often overlooked in land management decisions due to the absence of cost- and time-effective assessment methods. Here, we introduce a new method to calculate a combined terrain and canopy structural complexity metric using LiDAR data, enabling the prediction of multi-trophic diversity-a combined diversity metric that integrates diversity across trophic levels. We selected 34 forested sites of the National Ecological Observatory Network to test the model by using observed data on plant presence, beetle pitfall trap, and bird count to calculate multi-trophic diversity. Our results show that multi-trophic diversity increases with increasing structural complexity, but this relationship differs across different forest types. The environmental and geographic factors account for about 40% variability in multi-trophic diversity, which further increases to about 60% when combined with structural complexity. This research offers a powerful approach to evaluate biodiversity at a landscape scale using remotely sensed data and highlights the importance of considering multi-trophic diversity in land management decisions.

The return of tall forests: Reconstructing the canopy resilience of an extensively harvested primary forest in Mediterranean mountains

Understanding recovery times and mechanisms of ecosystem dynamics towards the old-growth stage is crucial for forest restoration, but still poorly delineated in Mediterranean. Through tree-ring methods, we reconstructed the return of a tall canopy after severe human disturbance in a mixed beech (Fagus sylvatica) and silver fir (Abies alba) forest, located at a mountain site in the southern edge of both species' range (Gariglione, south Italy). The primary forest was extensively harvested between 1930 and 1950, removing up to 91 % of the biomass. Growth histories, climate-growth relationships and time-series of growth dominance in Gariglione were compared with a network of protected mature and old-growth beech forests distributed along a wide elevational gradient in the same region. We found that the renewed tall canopy of Gariglione is mainly composed of remnant trees, which include uncut trees and saplings, and the post-harvesting regeneration mostly represented by fir. Canopy beech trees reached maximum basal area increment (BAI) in the 1970s, 40-50 years after cutting. Then, beech BAI shifted towards negative trends in phase with drying climate (PDSI), while fir maintained a sustained growth until 2000. This growth asynchrony between the two species conferred community stability over the last decades. The network comparison highlighted the common negative impact of summer drought on high-frequency growth signals of beech in south Italy. However, analysis of long-term mean growth trends indicates decreasing BAI limited to Gariglione beech, revealing relevant differences due to site ecology and its interactions with legacy effects of past management in driving growth responses to climate change. Indeed, lowland mature beech forests showed increasing BAI in the last decades, while primary high-mountain forests displayed a remarkably stable low oscillating growth. In all the Mediterranean forests we studied, large and old trees showed a marked growth acclimation despite ongoing climate warming, demonstrating the effectiveness of landscape rewilding.

Diversity Effects on Canopy Structure Change throughout a Growing Season in Experimental Grassland Communities

Increasing plant diversity commonly enhances standing biomass and other ecosystem functions (i.e., carbon fluxes, water use efficiency, herbivory). The standing biomass is correlated with vegetation volume, which describes plant biomass allocation within a complex canopy structure. As the canopy structure of plant communities is not static throughout time, it is expected that its changes also control diversity effects on ecosystem functioning. Yet, most studies are based on one or two measures of ecosystem function per year. Here, we examine the temporal effects of diversity of grassland communities on canopy structural components in high temporal (bi-weekly throughout the growing season) and spatial resolutions as a proxy for ecosystem functioning. Using terrestrial laser scanning, we estimate metrics of vertical structure, such as biomass distribution (evenness) and highest biomass allocation (center of gravity) along height strata. For horizontal metrics, we calculated community stand gaps and canopy surface variation. Our findings show that species-rich communities start filling the vertical space (evenness) earlier in the growing season, suggesting a more extended period of resource use (i.e., light-harvesting). Moreover, more diverse communities raised their center of gravity only at the peak of biomass in spring, likely triggered by higher interspecific competition inducing higher biomass allocation at upper layers of the canopy. Furthermore, richer communities were clumpier only after mowing, revealing species-specific differences in regrowth. Lastly, species richness strongly affected canopy variation when the phenology status and height differences were maximal, suggesting differences in plant functional strategies (space to grow, resource use, and flowering phenology). Therefore, the effects of diversity on ecosystem functions depending on those structural components such as biomass production, decomposition, and herbivory, may also change throughout the season due to various mechanisms, such as niche differences, increased complementarity, and temporal and spatial variation in biological activity.

TLSLeAF: automatic leaf angle estimates from single-scan terrestrial laser scanning

Leaf angle distribution (LAD) in forest canopies affects estimates of leaf area, light interception, and global-scale photosynthesis, but is often simplified to a single theoretical value. Here, we present TLSLeAF (Terrestrial Laser Scanning Leaf Angle Function), an automated open-source method of deriving LADs from terrestrial laser scanning. TLSLeAF produces canopy-scale leaf angle and LADs by relying on gridded laser scanning data. The approach increases processing speed, improves angle estimates, and requires minimal user input. Key features are automation, leaf-wood classification, beta parameter output, and implementation in R to increase accessibility for the ecology community. TLSLeAF precisely estimates leaf angle with minimal distance effects on angular estimates while rapidly producing LADs on a consumer-grade machine. We challenge the popular spherical LAD assumption, showing sensitivity to ecosystem type in plant area index and foliage profile estimates that translate to c. 25% and c. 11% increases in canopy net photosynthesis (c. 25%) and solar-induced chlorophyll fluorescence (c. 11%). TLSLeAF can now be applied to the vast catalog of laser scanning data already available from ecosystems around the globe. The ease of use will enable widespread adoption of the method outside of remote-sensing experts, allowing greater accessibility for addressing ecological hypotheses and large-scale ecosystem modeling efforts.