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SpeciesGeoCoder: Fast Categorization of Species Occurrences for Analyses of Biodiversity, Biogeography, Ecology, and Evolution

Understanding the patterns and processes underlying the uneven distribution of biodiversity across space constitutes a major scientific challenge in systematic biology and biogeography, which largely relies on effectively mapping and making sense of rapidly increasing species occurrence data. There...

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Autores principales: Töpel, Mats, Zizka, Alexander, Calió, Maria Fernanda, Scharn, Ruud, Silvestro, Daniele, Antonelli, Alexandre
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5410971/
https://www.ncbi.nlm.nih.gov/pubmed/27486181
http://dx.doi.org/10.1093/sysbio/syw064
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author Töpel, Mats
Zizka, Alexander
Calió, Maria Fernanda
Scharn, Ruud
Silvestro, Daniele
Antonelli, Alexandre
author_facet Töpel, Mats
Zizka, Alexander
Calió, Maria Fernanda
Scharn, Ruud
Silvestro, Daniele
Antonelli, Alexandre
author_sort Töpel, Mats
collection PubMed
description Understanding the patterns and processes underlying the uneven distribution of biodiversity across space constitutes a major scientific challenge in systematic biology and biogeography, which largely relies on effectively mapping and making sense of rapidly increasing species occurrence data. There is thus an urgent need for making the process of coding species into spatial units faster, automated, transparent, and reproducible. Here we present SpeciesGeoCoder, an open-source software package written in Python and R, that allows for easy coding of species into user-defined operational units. These units may be of any size and be purely spatial (i.e., polygons) such as countries and states, conservation areas, biomes, islands, biodiversity hotspots, and areas of endemism, but may also include elevation ranges. This flexibility allows scoring species into complex categories, such as those encountered in topographically and ecologically heterogeneous landscapes. In addition, SpeciesGeoCoder can be used to facilitate sorting and cleaning of occurrence data obtained from online databases, and for testing the impact of incorrect identification of specimens on the spatial coding of species. The various outputs of SpeciesGeoCoder include quantitative biodiversity statistics, global and local distribution maps, and files that can be used directly in many phylogeny-based applications for ancestral range reconstruction, investigations of biome evolution, and other comparative methods. Our simulations indicate that even datasets containing hundreds of millions of records can be analyzed in relatively short time using a standard computer. We exemplify the use of SpeciesGeoCoder by inferring the historical dispersal of birds across the Isthmus of Panama, showing that lowland species crossed the Isthmus about twice as frequently as montane species with a marked increase in the number of dispersals during the last 10 million years.
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spelling pubmed-54109712018-02-05 SpeciesGeoCoder: Fast Categorization of Species Occurrences for Analyses of Biodiversity, Biogeography, Ecology, and Evolution Töpel, Mats Zizka, Alexander Calió, Maria Fernanda Scharn, Ruud Silvestro, Daniele Antonelli, Alexandre Syst Biol Special Issue: Frontiers in Parametric Biogeography Understanding the patterns and processes underlying the uneven distribution of biodiversity across space constitutes a major scientific challenge in systematic biology and biogeography, which largely relies on effectively mapping and making sense of rapidly increasing species occurrence data. There is thus an urgent need for making the process of coding species into spatial units faster, automated, transparent, and reproducible. Here we present SpeciesGeoCoder, an open-source software package written in Python and R, that allows for easy coding of species into user-defined operational units. These units may be of any size and be purely spatial (i.e., polygons) such as countries and states, conservation areas, biomes, islands, biodiversity hotspots, and areas of endemism, but may also include elevation ranges. This flexibility allows scoring species into complex categories, such as those encountered in topographically and ecologically heterogeneous landscapes. In addition, SpeciesGeoCoder can be used to facilitate sorting and cleaning of occurrence data obtained from online databases, and for testing the impact of incorrect identification of specimens on the spatial coding of species. The various outputs of SpeciesGeoCoder include quantitative biodiversity statistics, global and local distribution maps, and files that can be used directly in many phylogeny-based applications for ancestral range reconstruction, investigations of biome evolution, and other comparative methods. Our simulations indicate that even datasets containing hundreds of millions of records can be analyzed in relatively short time using a standard computer. We exemplify the use of SpeciesGeoCoder by inferring the historical dispersal of birds across the Isthmus of Panama, showing that lowland species crossed the Isthmus about twice as frequently as montane species with a marked increase in the number of dispersals during the last 10 million years. Oxford University Press 2017-03 2016-08-02 /pmc/articles/PMC5410971/ /pubmed/27486181 http://dx.doi.org/10.1093/sysbio/syw064 Text en © The Author(s) 2016. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Special Issue: Frontiers in Parametric Biogeography
Töpel, Mats
Zizka, Alexander
Calió, Maria Fernanda
Scharn, Ruud
Silvestro, Daniele
Antonelli, Alexandre
SpeciesGeoCoder: Fast Categorization of Species Occurrences for Analyses of Biodiversity, Biogeography, Ecology, and Evolution
title SpeciesGeoCoder: Fast Categorization of Species Occurrences for Analyses of Biodiversity, Biogeography, Ecology, and Evolution
title_full SpeciesGeoCoder: Fast Categorization of Species Occurrences for Analyses of Biodiversity, Biogeography, Ecology, and Evolution
title_fullStr SpeciesGeoCoder: Fast Categorization of Species Occurrences for Analyses of Biodiversity, Biogeography, Ecology, and Evolution
title_full_unstemmed SpeciesGeoCoder: Fast Categorization of Species Occurrences for Analyses of Biodiversity, Biogeography, Ecology, and Evolution
title_short SpeciesGeoCoder: Fast Categorization of Species Occurrences for Analyses of Biodiversity, Biogeography, Ecology, and Evolution
title_sort speciesgeocoder: fast categorization of species occurrences for analyses of biodiversity, biogeography, ecology, and evolution
topic Special Issue: Frontiers in Parametric Biogeography
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5410971/
https://www.ncbi.nlm.nih.gov/pubmed/27486181
http://dx.doi.org/10.1093/sysbio/syw064
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