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Near-global freshwater-specific environmental variables for biodiversity analyses in 1 km resolution
The lack of freshwater-specific environmental information at sufficiently fine spatial grain hampers broad-scale analyses in aquatic biology, biogeography, conservation, and ecology. Here we present a near-global, spatially continuous, and freshwater-specific set of environmental variables in a stan...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4672682/ https://www.ncbi.nlm.nih.gov/pubmed/26647296 http://dx.doi.org/10.1038/sdata.2015.73 |
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author | Domisch, Sami Amatulli, Giuseppe Jetz, Walter |
author_facet | Domisch, Sami Amatulli, Giuseppe Jetz, Walter |
author_sort | Domisch, Sami |
collection | PubMed |
description | The lack of freshwater-specific environmental information at sufficiently fine spatial grain hampers broad-scale analyses in aquatic biology, biogeography, conservation, and ecology. Here we present a near-global, spatially continuous, and freshwater-specific set of environmental variables in a standardized 1 km grid. We delineate the sub-catchment for each grid cell along the HydroSHEDS river network and summarize the upstream climate, topography, land cover, surface geology and soil to each grid cell using various metrics (average, minimum, maximum, range, sum, inverse distance-weighted average and sum). All variables were subsequently averaged across single lakes and reservoirs of the Global lakes and Wetlands Database that are connected to the river network. Monthly climate variables were summarized into 19 long-term climatic variables following the ‘bioclim’ framework. This new set of variables provides a basis for spatial ecological and biodiversity analyses in freshwater ecosystems at near global extent, yet fine spatial grain. To facilitate the generation of freshwater variables for custom study areas and spatial grains, we provide the ‘r.stream.watersheds’ and ‘r.stream.variables’ add-ons for the GRASS GIS software. |
format | Online Article Text |
id | pubmed-4672682 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-46726822015-12-10 Near-global freshwater-specific environmental variables for biodiversity analyses in 1 km resolution Domisch, Sami Amatulli, Giuseppe Jetz, Walter Sci Data Data Descriptor The lack of freshwater-specific environmental information at sufficiently fine spatial grain hampers broad-scale analyses in aquatic biology, biogeography, conservation, and ecology. Here we present a near-global, spatially continuous, and freshwater-specific set of environmental variables in a standardized 1 km grid. We delineate the sub-catchment for each grid cell along the HydroSHEDS river network and summarize the upstream climate, topography, land cover, surface geology and soil to each grid cell using various metrics (average, minimum, maximum, range, sum, inverse distance-weighted average and sum). All variables were subsequently averaged across single lakes and reservoirs of the Global lakes and Wetlands Database that are connected to the river network. Monthly climate variables were summarized into 19 long-term climatic variables following the ‘bioclim’ framework. This new set of variables provides a basis for spatial ecological and biodiversity analyses in freshwater ecosystems at near global extent, yet fine spatial grain. To facilitate the generation of freshwater variables for custom study areas and spatial grains, we provide the ‘r.stream.watersheds’ and ‘r.stream.variables’ add-ons for the GRASS GIS software. Nature Publishing Group 2015-12-08 /pmc/articles/PMC4672682/ /pubmed/26647296 http://dx.doi.org/10.1038/sdata.2015.73 Text en Copyright © 2015, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0 This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0 Metadata associated with this Data Descriptor is available at http://www.nature.com/sdata/ and is released under the CC0 waiver to maximize reuse. |
spellingShingle | Data Descriptor Domisch, Sami Amatulli, Giuseppe Jetz, Walter Near-global freshwater-specific environmental variables for biodiversity analyses in 1 km resolution |
title | Near-global freshwater-specific environmental variables for biodiversity analyses in 1 km resolution |
title_full | Near-global freshwater-specific environmental variables for biodiversity analyses in 1 km resolution |
title_fullStr | Near-global freshwater-specific environmental variables for biodiversity analyses in 1 km resolution |
title_full_unstemmed | Near-global freshwater-specific environmental variables for biodiversity analyses in 1 km resolution |
title_short | Near-global freshwater-specific environmental variables for biodiversity analyses in 1 km resolution |
title_sort | near-global freshwater-specific environmental variables for biodiversity analyses in 1 km resolution |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4672682/ https://www.ncbi.nlm.nih.gov/pubmed/26647296 http://dx.doi.org/10.1038/sdata.2015.73 |
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