On multiple drivers predicting ecosystem functioning in a tropical forest
Authors:   , Rodrigues Alice Cristina 
Published: February 2023

Understand the relative contribution of different factors that can determine the structure and diversity of forest communities along environmental gradients and secondary succession time has been a relevant theme in contemporary ecology. Recently the impact of these environmental factors (e.g., soils, topography, and climate) on biodiversity-ecosystem function relationship has gained importance in understanding tropical forests. Topographic and edaphic gradients together with climate can influence the distribution of functional traits, and consequently, ecosystem functioning. The study of the secondary succession of tropical forests with an approach based on the relation of functional traits and environmental factors has allowed elucidating emerging patterns of the ecosystem processes, mainly of the production and storage of biomass. Thus, the community weighted mean (CWM) are the diversity metrics to test effects on aboveground biomass. This research will assess how abiotic factors and biotic factors affect the assembly of tree communities and the ecosystem functioning of the forest Atlantic in southeastern Brazil. For this, we will analyze how species richness, composition and dominance can change through edaphic-topographic-climatic gradients and time of succession in permanent plots. For this, the following hypotheses will be tested: (1) The edaphic-topographic factors and the time of succession affect the richness, composition and dominance of the species in terms of their contribution to an ecosystem process (2) the variability climate over time of succession has implications for the classification of leaf phenology groups of tree communities. Finally, (3) we propose that AGB increases with time of succession, but changes depending on environmental variability (soil and topography), and that the variation in biomass can be explained by the functional traits of the species through functional dominance (CWM) in secondary forest communities. To answer these questions, we selected three areas with different topographic conditions located in a fragment in the secondary regeneration stage in Viçosa, MG, Brazil. Each area has permanent plots of 1 ha covering a topographic gradient from the valleys to the plateau. Each permanent plot has 100 subplots of 10m x 10m. Totaling two hectares of forest and 200 subplots. In each subplot, all individuals of the living arboreal species with stem circumference showed a height of 10 cm or greater and a height of 130 cm. For each subplot, three topographic variables (elevation, slope and convexity) were measured and calculated using a total station with the aid of an engineer and surface soil samples with a depth of 0 to 10 cm to determine physical and chemical parameters. The aboveground biomass was calculated for each tree individual sampled in the subplots by an allometric equation. We selected different types of functional traits such as leaf phenology, wood density and tree diameter. Multivariate regression analyzes were performed to classify habitat types according to topographic variables and species composition. In addition, we constructed a series of models to explain the effect of potential predictor variables on the response of species richness, species composition, and ecosystem functioning. We also used machine learning to classify leaf phenology groups under the effect of environmental variables. Our study demonstrated that topographic variability, mainly elevation and convexity, determine soil fertility. These results advance our understanding that context-dependent conditions based on topography and soil properties have a high variability at a fine-scale. Furthermore, we found that different topographic conditions and successional timing affect community composition, richness, abundance and proportion of carbon-dominant species over time. We found that different topographic conditions and stand age change community composition, richness, abundance, and carbon dominant species along the late-secondary stage. This study advances our understanding of the mechanisms that drive carbon stock in tropical forests and supports the ‘mass ratio’ hypothesis. We observe that evergreen species show higher richness; meanwhile the deciduous species has a greater contribution to aboveground carbon stock. Thus, the leaf phenology groups can affect the relationships between species richness and aboveground carbon stock. For example, deciduous species are key to maintaining higher carbon stock with smaller numbers of species; meanwhile evergreen species are important to maintain a higher species richness. Thus, we presumed that the leaf phenology group's distribution could be responsible for the cobenefits (positive aboveground carbon stock and species richness relationship) in tropical forests. Using random forest, it was observed that the most influential predictor in the classification of functional groups was topography and soil properties. We emphasize that the information generated in this research can be important for the planning of forest restoration activities (passive and active) based on the high variability of environmental variables on a local scale. We also emphasize the relevance of the functional traits approach to understanding the functioning, conservation and management of tropical forests. Keywords: Biotic and abiotic factors. Cobenefits. Functional diversity. Topographical heterogeneity. Assembly community. Machine learning.