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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.
Afiliação
  • Töpel M; Department of Marine Sciences, University of Gothenburg, PO Box 460, SE-405 30 Göteborg, Sweden.
  • Zizka A; Bioinformatics Infrastructure for Life Sciences.
  • Calió MF; Department of Biological and Environmental Sciences, University of Gothenburg, PO Box 461, SE-405 30 Göteborg, Sweden.
  • Scharn R; Department of Biological and Environmental Sciences, University of Gothenburg, PO Box 461, SE-405 30 Göteborg, Sweden.
  • Silvestro D; Department of Biological and Environmental Sciences, University of Gothenburg, PO Box 461, SE-405 30 Göteborg, Sweden.
  • Antonelli A; Universidade de São Paulo, Instituto de Biociências, Departamento de Botânica, Rua do Matão, 277, Cidade Universitária, CEP: 05508-090, São Paulo, SP, Brazil.
Syst Biol ; 66(2): 145-151, 2017 Mar 01.
Article em En | MEDLINE | ID: mdl-27486181
ABSTRACT
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. [ancestral area reconstruction; biodiversity patterns; ecology; evolution; point in polygon; species distribution data.].
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Filogenia / Classificação / Biodiversidade / Ecologia Tipo de estudo: Prognostic_studies Limite: Animals Idioma: En Revista: Syst Biol Assunto da revista: BIOLOGIA Ano de publicação: 2017 Tipo de documento: Article País de afiliação: Suécia

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Filogenia / Classificação / Biodiversidade / Ecologia Tipo de estudo: Prognostic_studies Limite: Animals Idioma: En Revista: Syst Biol Assunto da revista: BIOLOGIA Ano de publicação: 2017 Tipo de documento: Article País de afiliação: Suécia