Understanding determinants of tropical forests stocks and fluxes from plot to landscape levels.

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Tropical forests occupy 12% of the terrestrial surface, harbor more than half of terrestrial diversity and hold over 40% of terrestrial carbon. These forests are highly threatened globally with deforestation in the tropics accounting for ~10% of total greenhouse gas emission. My research program aims at deepening the understanding of the dynamics of tropical forests carbon stocks. I propose scaling-up and improving the predictive power of the relationship between tree diversity and C storage and cycling in tropical forests. The specific questions addressed in in this proposal are: (1) Can high C storing species or groups of species be predicted from functional traits? (2) Does tree diversity enhance the stability of C stocks and fluxes? (3) How does the relationship between tree diversity and C stocks change with scale? Specific objective 1 will be addressed by complementing Sardinilla's existing functional traits data-base will be complemented with traits related to phenology, architecture as well as phylogeny and comparing the interactions between the functional characteristics of target species and the plot/neighborhood that maximize C storage in Panama, Brazil and China. Specific objective 2 will take advantage of the long-term data set of Sardinilla to break-down for the first time the role of interactions between individuals in their contributions to stabilization and diversity effects. Specific objective 3 will focus on the role of big trees at the landscape level. Building up on earlier work, I propose that the relationship between the variance in C stocks, at the plot-level and area is U-shaped with high at small spatial scale and low at the regional scale. The impact of my proposed Discovery grant proposal will be felt at three main levels. By identifying functional traits identifying species and species combinations maximizing C storage across sites, I will propose an approach improving the predictability of BEF experiment. By testing the importance of species asynchrony and demographic stochasticity at the level of individual trees, I will solidify the understanding of the proposed unified biodiversity and stability analytical framework. Finally, by documenting changes in the relationship between species richness and C storage from plot to landscape level, I will contribute to the scale transition theory. Together these results will greatly increase the predictive power and the ability to scale-up BEF results to the landscape level. These analyses of ecosystem functioning, relevant to as important an ecosystem service as climate regulation, will make a key contribution to the new paradigm of biodiversity science.