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Lilia Roa-Fuentes, Carlos Rodriguez
The plant community assemblages and their space and time variation are important for understanding the fate of biodiversity under anthropogenic alterations. Understanding this pattern can help us plan ecological restoration for highly diverse ecosystems such as the Amazonian forest. It has been considered that plant attributes and their proportional changes should follow a complicated pattern of direct and indirect relationships among them across environmental gradients. We used models of trait-based community assembly to predict the probability for any species to pass through environmental filters. We suggest that such an approach is useful to refine (or to predict) the best community composition to carry out plantations for restoration. Our study was carried out in in the Amazonian Piedmont in the Caquetá-Colombia, in a disturbed and fragmented landscape. The vegetation cover is composed of a relict of humid tropical forest in different successional states. We selected a pool of plant functional traits to predict species abundance across the chronosequence. We asked if the strength of filtering changes along an age gradient and quantified the trait importance to predict species relative abundances. Preliminary results show that species abundance in the Amazonian forest was explained by leaf dry matter content and wood density. In addition, the landscape measures also explained the abundance. We are moving to use these results to select the plant composition to be used in higher level interventions to restore the humid forest in the Amazonian Piedmont in Caquetá-Colombia.
Audio/Video, Conference Presentation, SER2019
Society for Ecological Restoration