| Literature DB >> 27358193 |
Robert K Colwell1,2,3, Nicholas J Gotelli4, Louise A Ashton5,6, Jan Beck3,7, Gunnar Brehm8, Tom M Fayle9,10,11, Konrad Fiedler12, Matthew L Forister13, Michael Kessler14, Roger L Kitching5, Petr Klimes9, Jürgen Kluge15, John T Longino16, Sarah C Maunsell5, Christy M McCain3,17, Jimmy Moses18,19, Sarah Noben14, Katerina Sam9, Legi Sam5,9, Arthur M Shapiro20, Xiangping Wang21, Vojtech Novotny9,18.
Abstract
We introduce a novel framework for conceptualising, quantifying and unifying discordant patterns of species richness along geographical gradients. While not itself explicitly mechanistic, this approach offers a path towards understanding mechanisms. In this study, we focused on the diverse patterns of species richness on mountainsides. We conjectured that elevational range midpoints of species may be drawn towards a single midpoint attractor - a unimodal gradient of environmental favourability. The midpoint attractor interacts with geometric constraints imposed by sea level and the mountaintop to produce taxon-specific patterns of species richness. We developed a Bayesian simulation model to estimate the location and strength of the midpoint attractor from species occurrence data sampled along mountainsides. We also constructed midpoint predictor models to test whether environmental variables could directly account for the observed patterns of species range midpoints. We challenged these models with 16 elevational data sets, comprising 4500 species of insects, vertebrates and plants. The midpoint predictor models generally failed to predict the pattern of species midpoints. In contrast, the midpoint attractor model closely reproduced empirical spatial patterns of species richness and range midpoints. Gradients of environmental favourability, subject to geometric constraints, may parsimoniously account for elevational and other patterns of species richness.Entities:
Keywords: Bayesian model; Biogeography; elevational gradients; geometric constraints; mid-domain effect; midpoint predictor model; stochastic model; truncated niche
Mesh:
Year: 2016 PMID: 27358193 DOI: 10.1111/ele.12640
Source DB: PubMed Journal: Ecol Lett ISSN: 1461-023X Impact factor: 9.492