Probabilistic models of species discovery and biodiversity comparisons.

ABSTRACT: Inferring large-scale processes that drive biodiversity hinges on understanding the phylogenetic and spatial pattern of species richness. However, clades and geographic regions are accumulating newly described species at an uneven rate, potentially affecting the stability of currently observed diversity patterns. Here, we present a probabilistic model of species discovery to assess the uncertainty in diversity levels among clades and regions. We use a Bayesian time series regression to estimate the long-term trend in the rate of species description for marine bivalves and find a distinct spatial bias in the accumulation of new species. Despite these biases, probabilistic estimates of future species richness show considerable stability in the currently observed rank order of regional divers

SUBMITTER: Edie SM 

PROVIDER: S-EPMC5389289 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature