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Drawing ecological inferences from coincident patterns of population- and community-level biodiversity

期刊

MOLECULAR ECOLOGY
卷 23, 期 12, 页码 2890-2901

出版社

WILEY
DOI: 10.1111/mec.12756

关键词

community ecology; environmental gradients; functional traits; genetic diversity; population genetics; species diversity

资金

  1. Natural Sciences and Engineering Research Council, Canada
  2. Beatriu de Pinos postdoctoral fellowship from Agencia de Gestio d'Ajuts Universitaris i de Recerca, Catalunya [BP-DGR-2011]

向作者/读者索取更多资源

Biodiversity is comprised of genetic and phenotypic variation among individual organisms, which might belong to the same species or to different species. Spatial patterns of biodiversity are of central interest in ecology and evolution for several reasons: to identify general patterns in nature (e.g. species-area relationships, latitudinal gradients), to inform conservation priorities (e.g. identifying hotspots, prioritizing management efforts) and to draw inferences about processes, historical or otherwise (e.g. adaptation, the centre of origin of particular clades). There are long traditions in ecology and evolutionary biology of examining spatial patterns of biodiversity among species (i.e. in multispecies communities) and within species, respectively, and there has been a recent surge of interest in studying these two types of pattern simultaneously. The idea is that examining both levels of diversity can materially advance the above-stated goals and perhaps lead to entirely novel lines of inquiry. Here, we review two broad categories of approach to merging studies of inter- and intraspecific variation: (i) the study of phenotypic trait variation along environmental gradients and (ii) the study of relationships between patterns of molecular genetic variation within species and patterns of distribution and diversity across species. For the latter, we report a new meta-analysis in which we find that correlations between species diversity and genetic diversity are generally positive and significantly stronger in studies with discrete sampling units (e.g. islands, lakes, forest fragments) than in studies with nondiscrete sampling units (e.g. equal-area study plots). For each topic, we summarize the current state of knowledge and key future directions.

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