Regional Deforestation Drives The Impact Of Forest Cover And Matrix Quality On Primate Species Richness

BIOLOGICAL CONSERVATION(2021)

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摘要
Land-use change transforms natural ecosystems, threatening species persistence worldwide. There is increasing evidence that forest loss negatively affects forest-dependent species and matrix quality can favor species main-tenance, whereas forest fragmentation has mainly null or positive effects on species. However, the effects of these landscape attributes may depend on the level of regional deforestation. Here, we assess the effects of forest cover, matrix quality, and forest fragmentation (forest patch density) on primate species richness in 92 landscapes in Brazil. We grouped landscapes by their regional deforestation level into low, intermediate, high, and severe deforestation. The effects of landscape attributes varied depending on the level of regional deforestation. Forest loss decreased the proportion of primate species in the four regional deforestation levels, but this association was more important in the low, intermediate and high regional deforestation levels. Matrix quality was positively related to the proportion of primate species in three regional deforestation levels and this association was more important in the high regional deforestation level. Yet, matrix quality decreased the proportion of primate species in the severe regional deforestation level. Forest fragmentation had no clear effects across all defores-tation levels. Therefore, different conservation strategies should be prioritized under distinct scenarios. Pre -venting forest loss is needed in all regions. Increasing matrix quality has positive effects on species richness, especially in highly deforested regions (30-15% remaining forest cover). Finally, as fragmentation had no clear effects on the proportion of primate species, landscape composition should be prioritized in conservation planning over landscape configuration.
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关键词
Habitat loss, Landscape perspective approach, Landscape heterogeneity, Multi-scale approach, Monkeys
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