Windthrows control biomass patterns and functional composition of Amazon forests.

Amazon forests account for ~25% of global land biomass and tropical tree species. In these forests, windthrows (i.e., snapped and uprooted trees) are a major natural disturbance, but the rates and mechanisms of recovery are not known. To provide a predictive framework for understanding the effects of windthrows on forest structure and functional composition (DBH ≥10 cm), we quantified biomass recovery as a function of windthrow severity (i.e., fraction of windthrow tree mortality on Landsat pixels, ranging from 0%-70%) and time since disturbance for terra-firme forests in the Central Amazon. Forest monitoring allowed insights into the processes and mechanisms driving the net biomass change (i.e., increment minus loss) and shifts in functional composition. Windthrown areas recovering for between 4-27 years had biomass stocks as low as 65.2-91.7 Mg/ha or 23%-38% of those in nearby undisturbed forests (~255.6 Mg/ha, all sites). Even low windthrow severities (4%-20% tree mortality) caused decadal changes in biomass stocks and structure. While rates of biomass increment in recovering vegetation were nearly double (6.3 ± 1.4 Mg ha-1  year-1 ) those of undisturbed forests (~3.7 Mg ha-1  year-1 ), biomass loss due to post-windthrow mortality was high (up to -7.5 ± 8.7 Mg ha-1  year-1 , 8.5 years since disturbance) and unpredictable. Consequently, recovery to 90% of "pre-disturbance" biomass takes up to 40 years. Resprouting trees contributed little to biomass recovery. Instead, light-demanding, low-density genera (e.g., Cecropia, Inga, Miconia, Pourouma, Tachigali, and Tapirira) were favored, resulting in substantial post-windthrow species turnover. Shifts in functional composition demonstrate that windthrows affect the resilience of live tree biomass by favoring soft-wooded species with shorter life spans that are more vulnerable to future disturbances. As the time required for forests to recover biomass is likely similar to the recurrence interval of windthrows triggering succession, windthrows have the potential to control landscape biomass/carbon dynamics and functional composition in Amazon forests.

Different facets of tree sapling diversity influence browsing intensity by deer dependent on spatial scale.

Browsing of tree saplings by deer hampers forest regeneration in mixed forests across Europe and North America. It is well known that tree species are differentially affected by deer browsing, but little is known about how different facets of diversity, such as species richness, identity, and composition, affect browsing intensity at different spatial scales. Using forest inventory data from the Hainich National Park, a mixed deciduous forest in central Germany, we applied a hierarchical approach to model the browsing probability of patches (regional scale) as well as the species-specific proportion of saplings browsed within patches (patch scale). We found that, at the regional scale, the probability that a patch was browsed increased with certain species composition, namely with low abundance of European beech (Fagus sylvatica L.) and high abundance of European ash (Fraxinus excelsior L.), whereas at the patch scale, the proportion of saplings browsed per species was mainly determined by the species' identity, providing a "preference ranking" of the 11 tree species under study. Interestingly, at the regional scale, species-rich patches were more likely to be browsed; however, at the patch scale, species-rich patches showed a lower proportion of saplings per species browsed. Presumably, diverse patches attract deer, but satisfy nutritional needs faster, such that fewer saplings need to be browsed. Some forest stand parameters, such as more open canopies, increased the browsing intensity at either scale. By showing the effects that various facets of diversity, as well as environmental parameters, exerted on browsing intensity at the regional as well as patch scale, our study advances the understanding of mammalian herbivore-plant interactions across scales. Our results also indicate which regeneration patches and species are (least) prone to browsing and show the importance of different facets of diversity for the prediction and management of browsing intensity and regeneration dynamics.

Taking a closer look: disentangling effects of functional diversity on ecosystem functions with a trait-based model across hierarchy and time.

Biodiversity and ecosystem functioning (BEF) research has progressed from the detection of relationships to elucidating their drivers and underlying mechanisms. In this context, replacing taxonomic predictors by trait-based measures of functional composition (FC)-bridging functions of species and of ecosystems-is a widely used approach. The inherent challenge of trait-based approaches is the multi-faceted, dynamic and hierarchical nature of trait influence: (i) traits may act via different facets of their distribution in a community, (ii) their influence may change over time and (iii) traits may influence processes at different levels of the natural hierarchy of organization. Here, we made use of the forest ecosystem model 'LPJ-GUESS' parametrized with empirical trait data, which creates output of individual performance, community assembly, stand-level states and processes. To address the three challenges, we resolved the dynamics of the top-level ecosystem function 'annual biomass change' hierarchically into its various component processes (growth, leaf and root turnover, recruitment and mortality) and states (stand structures, water stress) and traced the influence of different facets of FC along this hierarchy in a path analysis. We found an independent influence of functional richness, dissimilarity and identity on ecosystem states and processes and hence biomass change. Biodiversity effects were only positive during early succession and later turned negative. Unexpectedly, resource acquisition (growth, recruitment) and conservation (mortality, turnover) played an equally important role throughout the succession. These results add to a mechanistic understanding of biodiversity effects and place a caveat on simplistic approaches omitting hierarchical levels when analysing BEF relationships. They support the view that BEF relationships experience dramatic shifts over successional time that should be acknowledged in mechanistic theories.