Predictive sampling effort and species-area relationship models for estimating richness in fragmented landscapes.

ABSTRACT: Loss of habitat, specifically deforestation, is a major driver of biodiversity loss. Species-area relationship (SAR) models traditionally have been used for estimating species richness, species loss as a function of habitat loss, and extrapolation of richness for given areas. Sampling-species relationships (SSRs) are interrelated yet separate drivers for species richness estimates. Traditionally, however, SAR and SSR models have been used independently and not incorporated into a single approach. We developed and compared predictive models that incorporate sampling effort species-area relationships (SESARS) along the entire Atlantic Forest of South America, and then applied the best-fit model to estimate richness in forest remnants of Interior Atlantic Forest of eastern Paraguay. This fram

SUBMITTER: de la Sancha NU 

PROVIDER: S-EPMC6938349 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature