Environmental heterogeneity predicts global species richness patterns better than area ...

Aim: It is widely accepted that biodiversity can be determined by niche-relate processes and by pure area effects from local to global scales. Their relative importance, however, is still disputed, and empirical tests are still surprisingly scarce at the global scale. We compare the explanatory powe...

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Main Authors: Udy, Kristy, Fritsch, Matthias, Meyer, Katrin, Grass, Ingo, Hanß, Sebastian, Hartig, Florian, Kneib, Thomas, Kreft, Hoger, Kukuna, Collins, Pe'er, Guy, Reininghaus, Hannah, Tietjen, Britta, Van Waveren, Clara-Sophie, Wiegand, Kerstin, Tscharntke, Teja
Format: Dataset
Language:English
Published: Dryad 2020
Subjects:
Online Access:https://dx.doi.org/10.5061/dryad.1rn8pk0qs
https://datadryad.org/stash/dataset/doi:10.5061/dryad.1rn8pk0qs
id ftdatacite:10.5061/dryad.1rn8pk0qs
record_format openpolar
spelling ftdatacite:10.5061/dryad.1rn8pk0qs 2024-10-29T17:40:03+00:00 Environmental heterogeneity predicts global species richness patterns better than area ... Udy, Kristy Fritsch, Matthias Meyer, Katrin Grass, Ingo Hanß, Sebastian Hartig, Florian Kneib, Thomas Kreft, Hoger Kukuna, Collins Pe'er, Guy Reininghaus, Hannah Tietjen, Britta Van Waveren, Clara-Sophie Wiegand, Kerstin Tscharntke, Teja 2020 https://dx.doi.org/10.5061/dryad.1rn8pk0qs https://datadryad.org/stash/dataset/doi:10.5061/dryad.1rn8pk0qs en eng Dryad https://dx.doi.org/10.1111/geb.13261 Creative Commons Zero v1.0 Universal https://creativecommons.org/publicdomain/zero/1.0/legalcode cc0-1.0 Dataset dataset 2020 ftdatacite https://doi.org/10.5061/dryad.1rn8pk0qs10.1111/geb.13261 2024-10-01T11:13:53Z Aim: It is widely accepted that biodiversity can be determined by niche-relate processes and by pure area effects from local to global scales. Their relative importance, however, is still disputed, and empirical tests are still surprisingly scarce at the global scale. We compare the explanatory power of area and environmental heterogeneity as a proxy for niche-related processes as drivers of native mammal species richnessworldwide and with biogeographical regions. Location: Global Time Period: Data was collated form the IUCN (2013) Major Taxa Studied: All mammal species, including possibly extinct species and species with uncertain presence. Methods: We developed a random walk algorithm to compare the explanatory power of area and environmental heterogeneity on native mammal species richness. As measures for environmental heterogeneity, we used elevation and precipitation ranges, which are well known correlates of species richness. Results: We find that environmental heterogeneity explains species richness ... : Our global terrestrial mammal data comprised 4,954 native species derived from extent-of-occurrence distribution maps provided by IUCN (2013), from which species richness across an equal-area grid with cells of 12,364 km2 (approximately 111 km x 111 km at the equator) was aggregated by Stein et al. (2015). This dataset was split into seven mammalian biogeographic regions (Olson et al. 2001; Kreft & Jetz 2010). We excluded introduced species, vagrant species, bats and species for which no specific localities were known. We removed grid cells with no indigenous terrestrial mammals present (excluding the biogeographic regions Antarctica and Oceania) and grid cells containing only water (oceans and large lakes). We analysed two measures of environmental heterogeneity across the same 12,364 km² grid cells in all biogeographic regions of the globe (except for Antarctica and Oceania): elevation range and precipitation range. These two measures of environmental heterogeneity are known to be strong predictors of ... Dataset Antarc* DataCite
institution Open Polar
collection DataCite
op_collection_id ftdatacite
language English
description Aim: It is widely accepted that biodiversity can be determined by niche-relate processes and by pure area effects from local to global scales. Their relative importance, however, is still disputed, and empirical tests are still surprisingly scarce at the global scale. We compare the explanatory power of area and environmental heterogeneity as a proxy for niche-related processes as drivers of native mammal species richnessworldwide and with biogeographical regions. Location: Global Time Period: Data was collated form the IUCN (2013) Major Taxa Studied: All mammal species, including possibly extinct species and species with uncertain presence. Methods: We developed a random walk algorithm to compare the explanatory power of area and environmental heterogeneity on native mammal species richness. As measures for environmental heterogeneity, we used elevation and precipitation ranges, which are well known correlates of species richness. Results: We find that environmental heterogeneity explains species richness ... : Our global terrestrial mammal data comprised 4,954 native species derived from extent-of-occurrence distribution maps provided by IUCN (2013), from which species richness across an equal-area grid with cells of 12,364 km2 (approximately 111 km x 111 km at the equator) was aggregated by Stein et al. (2015). This dataset was split into seven mammalian biogeographic regions (Olson et al. 2001; Kreft & Jetz 2010). We excluded introduced species, vagrant species, bats and species for which no specific localities were known. We removed grid cells with no indigenous terrestrial mammals present (excluding the biogeographic regions Antarctica and Oceania) and grid cells containing only water (oceans and large lakes). We analysed two measures of environmental heterogeneity across the same 12,364 km² grid cells in all biogeographic regions of the globe (except for Antarctica and Oceania): elevation range and precipitation range. These two measures of environmental heterogeneity are known to be strong predictors of ...
format Dataset
author Udy, Kristy
Fritsch, Matthias
Meyer, Katrin
Grass, Ingo
Hanß, Sebastian
Hartig, Florian
Kneib, Thomas
Kreft, Hoger
Kukuna, Collins
Pe'er, Guy
Reininghaus, Hannah
Tietjen, Britta
Van Waveren, Clara-Sophie
Wiegand, Kerstin
Tscharntke, Teja
spellingShingle Udy, Kristy
Fritsch, Matthias
Meyer, Katrin
Grass, Ingo
Hanß, Sebastian
Hartig, Florian
Kneib, Thomas
Kreft, Hoger
Kukuna, Collins
Pe'er, Guy
Reininghaus, Hannah
Tietjen, Britta
Van Waveren, Clara-Sophie
Wiegand, Kerstin
Tscharntke, Teja
Environmental heterogeneity predicts global species richness patterns better than area ...
author_facet Udy, Kristy
Fritsch, Matthias
Meyer, Katrin
Grass, Ingo
Hanß, Sebastian
Hartig, Florian
Kneib, Thomas
Kreft, Hoger
Kukuna, Collins
Pe'er, Guy
Reininghaus, Hannah
Tietjen, Britta
Van Waveren, Clara-Sophie
Wiegand, Kerstin
Tscharntke, Teja
author_sort Udy, Kristy
title Environmental heterogeneity predicts global species richness patterns better than area ...
title_short Environmental heterogeneity predicts global species richness patterns better than area ...
title_full Environmental heterogeneity predicts global species richness patterns better than area ...
title_fullStr Environmental heterogeneity predicts global species richness patterns better than area ...
title_full_unstemmed Environmental heterogeneity predicts global species richness patterns better than area ...
title_sort environmental heterogeneity predicts global species richness patterns better than area ...
publisher Dryad
publishDate 2020
url https://dx.doi.org/10.5061/dryad.1rn8pk0qs
https://datadryad.org/stash/dataset/doi:10.5061/dryad.1rn8pk0qs
genre Antarc*
genre_facet Antarc*
op_relation https://dx.doi.org/10.1111/geb.13261
op_rights Creative Commons Zero v1.0 Universal
https://creativecommons.org/publicdomain/zero/1.0/legalcode
cc0-1.0
op_doi https://doi.org/10.5061/dryad.1rn8pk0qs10.1111/geb.13261
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