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Heterogenization of remaining biodiversity in fragmented tropical forests across agricultural landscapes

C. Y. Vidal, D. Souza Bezerra Rocha, M. Ferreira de Siqueira, R. R. Rodrigues, T. Siqueira

Abstract

The increasing worldwide interest on the conservation of tropical forests reflects the conversion of over 50% of their area into agricultural lands and other uses. Understanding the distribution of remaining biodiversity across agricultural landscapes is an essential task to guide future conservation strategies. To understand the long-term effects of fragmentation on biodiversity, we investigated whether forest fragments in southeastern Brazil are under a taxonomic homogenization or heterogenization process. We estimated pre-deforestation species richness and composition based on a Species Distribution Modelling approach, and compared them to the observed patterns of - and {beta}-diversity. In particular, we asked (i) if changes in {beta}-diversity reveal convergence or divergence on species composition; (ii) if these changes are similar between forest fragments in Strictly Protected Areas (SPAs) (n=20) and within private lands (n=367) and in different regions of the state (West, Center, and Southeast). We detected steep reductions in observed local species richness in relation to our modeled predictions, and this was particularly true among forest fragments in non-protected private lands. The higher observed {beta} diversity indicated an overall biotic heterogenization process, consistent with the idea that the originally diverse vegetation is now reduced to small and isolated patches, with unique disturbance histories and impoverished communities derived from a large regional species pool. Since conservation of biodiversity extends beyond the boundaries of strictly Protected Areas, we advocate forest fragments are valuable for conservation in agricultural landscapes, with particular relevance for private lands, which represent the most exposed and neglected share of what is left.

PDFDOI

02 /Specification & Classification

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