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Glob Chang Biol ; 24(2): 597-607, 2018 02.
Artigo em Inglês | MEDLINE | ID: mdl-29095549

RESUMO

Despite the general recognition that fragmentation can reduce forest biomass through edge effects, a systematic review of the literature does not reveal a clear role of edges in modulating biomass loss. Additionally, the edge effects appear to be constrained by matrix type, suggesting that landscape composition has an influence on biomass stocks. The lack of empirical evidence of pervasive edge-related biomass losses across tropical forests highlights the necessity for a general framework linking landscape structure with aboveground biomass. Here, we propose a conceptual model in which landscape composition and configuration mediate the magnitude of edge effects and seed-flux among forest patches, which ultimately has an influence on biomass. Our model hypothesizes that a rapid reduction of biomass can occur below a threshold of forest cover loss. Just below this threshold, we predict that changes in landscape configuration can strongly influence the patch's isolation, thus enhancing biomass loss. Moreover, we expect a synergism between landscape composition and patch attributes, where matrix type mediates the effects of edges on species decline, particularly for shade-tolerant species. To test our conceptual framework, we propose a sampling protocol where the effects of edges, forest amount, forest isolation, fragment size, and matrix type on biomass stocks can be assessed both collectively and individually. The proposed model unifies the combined effects of landscape and patch structure on biomass into a single framework, providing a new set of main drivers of biomass loss in human-modified landscapes. We argue that carbon trading agendas (e.g., REDD+) and carbon-conservation initiatives must go beyond the effects of forest loss and edges on biomass, considering the whole set of effects on biomass related to changes in landscape composition and configuration.


Assuntos
Biomassa , Conservação dos Recursos Naturais/métodos , Florestas , Carbono , Modelos Biológicos , Árvores
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