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Quantifying and sustaining biodiversity in tropical agricultural landscapes.

Abstract：

:Decision-makers increasingly seek scientific guidance on investing in nature, but biodiversity remains difficult to estimate across diverse landscapes. Here, we develop empirically based models for quantifying biodiversity across space. We focus on agricultural lands in the tropical forest biome, wherein lies the greatest potential to conserve or lose biodiversity. We explore two questions, drawing from empirical research oriented toward pioneering policies in Costa Rica. First, can remotely sensed tree cover serve as a reliable basis for improved estimation of biodiversity, from plots to regions? Second, how does tropical biodiversity change across the land-use gradient from native forest to deforested cropland and pasture? We report on understory plants, nonflying mammals, bats, birds, reptiles, and amphibians. Using data from 67,737 observations of 908 species, we test how tree cover influences biodiversity across space. First, we find that fine-scale mapping of tree cover predicts biodiversity within a taxon-specific radius (of 30-70 m) about a point in the landscape. Second, nearly 50% of the tree cover in our study region is embedded in countryside forest elements, small (typically 0.05-100 ha) clusters or strips of trees on private property. Third, most species use multiple habitat types, including crop fields and pastures (to which 15% of species are restricted), although some taxa depend on forest (57% of species are restricted to forest elements). Our findings are supported by comparisons of 90 studies across Latin America. They provide a basis for a planning tool that guides investments in tropical forest biodiversity similar to those for securing ecosystem services.

journal_name

Proc Natl Acad Sci U S A

journal_title

Proceedings of the National Academy of Sciences of the United States of America

authors

Mendenhall CD,Shields-Estrada A,Krishnaswami AJ,Daily GC

doi

10.1073/pnas.1604981113

subject

Has Abstract

pub_date

2016-12-20 00:00:00

pages

14544-14551

issue

51

eissn

0027-8424

issn

1091-6490

pii

1604981113

journal_volume

113

pub_type

杂志文章

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