Seasonal structural stability promoted by forest diversity and composition explains overyielding

The stability of forest productivity over time is a widely studied parameter often associated with benefits of forest diversity. Yet, the structural stability ( SS ) through the season of forest communities and its relationship to diversity, composition, and productivity remains poorly understood. Using a large-scale (10 ha) young tree diversity experiment, we evaluated how forest structure and multiple dimensions of diversity and composition affect remotely-sensed structural metrics and their stability through the growing season. We then studied the impact of SS across the season (April-October) on the net biodiversity effects of annual wood productivity (i.e., overyielding) of forest mixtures. We surveyed experimental tree communities eight times at regular intervals from before bud-break to after leaf senescence, using an UAV-LiDAR to derive metrics associated with canopy height heterogeneity, gap probability, and forest structural complexity (i.e., fractal geometry). The inverse coefficient of variation of these metrics through the season was used as descriptors SS . These metrics along with their SS were then coupled with annual tree inventories to evaluate their relationships. Our findings indicate that plot wood volume and, to some extent, multiple dimensions of diversity and composition (i.e., taxonomic, phylogenetic, and functional) influence remotely-sensed metrics of forest structure and stability over time. We found that increases in plot wood volume as well as functional and phylogenetic diversity and variability (a measure of diversity independent of species richness), are linked to higher structural stability of forest complexity over time. We further found that higher stability of forest structural complexity and tree cover (i.e., 1 - gap probability) increases net biodiversity effects in forest mixtures through species complementarity. Structural equation models indicate that structural stability explains more the variation among plots in net biodiversity effects than multiple dimensions of diversity or variability, highlighting it as a measure that integrates several contributors to net biodiversity effects. Our results provide evidence that diversity and composition promote temporal stability of remotely-sensed forest structure and, in turn, enhanced productivity. The study highlights the potential to integrate remote sensing and ecology to disentangle the role of forest structural stability into ecological processes.