Midpoint attractors and species richness: Modelling the interaction between environmental drivers and geometric constraints
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...
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Published in | Ecology letters Vol. 19; no. 9; pp. 1009 - 1022 |
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Main Authors | , , , , , , , , , , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
England
Blackwell Publishing Ltd
01.09.2016
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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. |
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AbstractList | 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. 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. |
Author | McCain, Christy M. Colwell, Robert K. Gotelli, Nicholas J. Sam, Katerina Moses, Jimmy Kluge, Jürgen Sam, Legi Fayle, Tom M. Beck, Jan Kessler, Michael Klimes, Petr Forister, Matthew L. Kitching, Roger L. Brehm, Gunnar Wang, Xiangping Shapiro, Arthur M. Fiedler, Konrad Longino, John T. Maunsell, Sarah C. Noben, Sarah Ashton, Louise A. Novotny, Vojtech |
Author_xml | – sequence: 1 givenname: Robert K. surname: Colwell fullname: Colwell, Robert K. email: robertkcolwell@gmail.com organization: Department of Ecology and Evolutionary Biology, University of Connecticut, 06269, Storrs, CT, USA – sequence: 2 givenname: Nicholas J. surname: Gotelli fullname: Gotelli, Nicholas J. organization: Department of Biology, University of Vermont, VT, 05405, Burlington, USA – sequence: 3 givenname: Louise A. surname: Ashton fullname: Ashton, Louise A. organization: Environmental Futures Research Institute, Griffith University, 4111, Nathan, Qld, Australia – sequence: 4 givenname: Jan surname: Beck fullname: Beck, Jan organization: University of Colorado Museum of Natural History, 80309, Boulder, CO, USA – sequence: 5 givenname: Gunnar surname: Brehm fullname: Brehm, Gunnar organization: Phyletisches Museum, Friedrich-Schiller Universität, 07743, Jena, Germany – sequence: 6 givenname: Tom M. surname: Fayle fullname: Fayle, Tom M. organization: Institute of Entomology, Biology Centre of the Czech Academy of Sciences and Faculty of Science, University of South Bohemia, Branišovská 31, 370 05, České Budějovice, Czech Republic – sequence: 7 givenname: Konrad surname: Fiedler fullname: Fiedler, Konrad organization: Department of Botany & Biodiversity Research, University of Vienna, Rennweg 14, 1030, Vienna, Austria – sequence: 8 givenname: Matthew L. surname: Forister fullname: Forister, Matthew L. organization: Program in Ecology, Evolution, and Conservation Biology, Department of Biology, University of Nevada, NV89557, Reno, USA – sequence: 9 givenname: Michael surname: Kessler fullname: Kessler, Michael organization: Institute of Systematic Botany, University of Zurich, Switzerland, 8008, Zurich – sequence: 10 givenname: Roger L. surname: Kitching fullname: Kitching, Roger L. organization: Environmental Futures Research Institute, Griffith University, Qld, 4111, Nathan, Australia – sequence: 11 givenname: Petr surname: Klimes fullname: Klimes, Petr organization: Institute of Entomology, Biology Centre of the Czech Academy of Sciences and Faculty of Science, University of South Bohemia, Branišovská 31, 370 05, České Budějovice, Czech Republic – sequence: 12 givenname: Jürgen surname: Kluge fullname: Kluge, Jürgen organization: Department of Geography, University of Marburg, 35032, Marburg, Germany – sequence: 13 givenname: John T. surname: Longino fullname: Longino, John T. organization: Department of Biology, University of Utah, UT, 84112, Salt Lake City, USA – sequence: 14 givenname: Sarah C. surname: Maunsell fullname: Maunsell, Sarah C. organization: Environmental Futures Research Institute, Griffith University, Qld, 4111, Nathan, Australia – sequence: 15 givenname: Christy M. surname: McCain fullname: McCain, Christy M. organization: University of Colorado Museum of Natural History, 80309, Boulder, CO, USA – sequence: 16 givenname: Jimmy surname: Moses fullname: Moses, Jimmy organization: New Guinea Binatang Research Center, P.O. Box 604, Madang, Papua New Guinea – sequence: 17 givenname: Sarah surname: Noben fullname: Noben, Sarah organization: Institute of Systematic Botany, University of Zurich, Switzerland, 8008, Zurich – sequence: 18 givenname: Katerina surname: Sam fullname: Sam, Katerina organization: Institute of Entomology, Biology Centre of the Czech Academy of Sciences and Faculty of Science, University of South Bohemia, Branišovská 31, 370 05, České Budějovice, Czech Republic – sequence: 19 givenname: Legi surname: Sam fullname: Sam, Legi organization: Environmental Futures Research Institute, Griffith University, 4111, Nathan, Qld, Australia – sequence: 20 givenname: Arthur M. surname: Shapiro fullname: Shapiro, Arthur M. organization: Center for Population Biology, University of California, CA, 95616, Davis, USA – sequence: 21 givenname: Xiangping surname: Wang fullname: Wang, Xiangping organization: College of Forestry, Beijing Forestry University, 100083, Beijing, China – sequence: 22 givenname: Vojtech surname: Novotny fullname: Novotny, Vojtech organization: Institute of Entomology, Biology Centre of the Czech Academy of Sciences and Faculty of Science, University of South Bohemia, Branišovská 31, 370 05, České Budějovice, Czech Republic |
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Snippet | We introduce a novel framework for conceptualising, quantifying and unifying discordant patterns of species richness along geographical gradients. While not... |
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SubjectTerms | Animals Bayes Theorem Bayesian model Biodiversity Biogeography data collection Ecosystem elevational gradients environmental factors geometric constraints geometry Insecta - physiology insects mid-domain effect midpoint predictor model Models, Biological mountains Plant Physiological Phenomena sea level simulation models species diversity Species richness stochastic model truncated niche vertebrates Vertebrates - physiology |
Title | Midpoint attractors and species richness: Modelling the interaction between environmental drivers and geometric constraints |
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