Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

SpeciesGeoCoder: Fast categorisation of species occurrences for analyses of biodiversity, biogeography, ecology and evolution

Mats Töpel, Maria Fernanda Calió, Alexander Zizka, Ruud Scharn, Daniele Silvestro, Alexandre Antonelli
doi: https://doi.org/10.1101/009274
Mats Töpel
1University of Gothenburg, Department of Biological and Environmental Sciences, Box 461, SE-405 30 Göteborg, Sweden
2Bioinformatics Infrastructure for Life Sciences,
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: mats.topel@bioenv.gu.se alexandre.antonelli@bioenv.gu.se
Maria Fernanda Calió
1University of Gothenburg, Department of Biological and Environmental Sciences, Box 461, SE-405 30 Göteborg, Sweden
3Universidade de São Paulo, Instituto de Biociências, Departamento de Botânica, Rua do Matão, 277 - Cidade Universitária, CEP: 05508-090, São Paulo, SP, Brazil
4Universidade Federal de São Carlos, Departamento de Botânica, CEP: 13565-905, São Carlos, SP, Brazil
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Alexander Zizka
1University of Gothenburg, Department of Biological and Environmental Sciences, Box 461, SE-405 30 Göteborg, Sweden
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Ruud Scharn
1University of Gothenburg, Department of Biological and Environmental Sciences, Box 461, SE-405 30 Göteborg, Sweden
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Daniele Silvestro
1University of Gothenburg, Department of Biological and Environmental Sciences, Box 461, SE-405 30 Göteborg, Sweden
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Alexandre Antonelli
1University of Gothenburg, Department of Biological and Environmental Sciences, Box 461, SE-405 30 Göteborg, Sweden
5Gothenburg Botanical Garden, Carl Skottsbergs gata 22A, SE-41319, Göteborg, Sweden
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: mats.topel@bioenv.gu.se alexandre.antonelli@bioenv.gu.se
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Preview PDF
Loading

Abstract

Understanding the patterns and processes underlying the uneven distribution of biodiversity across space and time constitutes a major scientific challenge in evolutionary biology. With rapidly accumulating species occurrence data, there is an increasing need for making the process of coding species into operational units for biogeographic and evolutionary analyses faster, automated, transparent and reproducible. Here we present SpeciesGeoCoder, a free software package written in Python and R, that allows for easy coding of species into user-defined areas. These areas may be of any size and be purely geographical (i.e., polygons) such as political units, conservation areas, biomes, islands, biodiversity hotspots, and areas of endemism, but may also include altitudinal 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. The various outputs of SpeciesGeoCoder include quantitative biodiversity statistics, global and local distribution maps, and NEXUS files that can be directly used in many phylogeny-based applications for ancestral state reconstruction, investigations on biome evolution, and diversification rate analyses. Our simulations indicate that even datasets containing hundreds of millions of records can be analysed in relatively short time using a regular desktop computer. We exemplify the use of our program through two contrasting examples: i) inferring historical dispersal of birds across the Isthmus of Panama, separating lowland vs. montane species and optimising the results onto a species-level, dated phylogeny; and ii) exploring seasonal variations in the occurrence of 10 GPS-tracked individuals of moose (Alces alces) over one year in northern Sweden. These analyses show that SpeciesGeoCoder allows an easy, flexible and fast categorisation of species distribution data for various analyses in ecology and evolution, with potential use at different spatial, taxonomic and temporal scales.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
Back to top
PreviousNext
Posted September 18, 2014.
Download PDF
Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
SpeciesGeoCoder: Fast categorisation of species occurrences for analyses of biodiversity, biogeography, ecology and evolution
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
SpeciesGeoCoder: Fast categorisation of species occurrences for analyses of biodiversity, biogeography, ecology and evolution
Mats Töpel, Maria Fernanda Calió, Alexander Zizka, Ruud Scharn, Daniele Silvestro, Alexandre Antonelli
bioRxiv 009274; doi: https://doi.org/10.1101/009274
Reddit logo Twitter logo Facebook logo LinkedIn logo Mendeley logo
Citation Tools
SpeciesGeoCoder: Fast categorisation of species occurrences for analyses of biodiversity, biogeography, ecology and evolution
Mats Töpel, Maria Fernanda Calió, Alexander Zizka, Ruud Scharn, Daniele Silvestro, Alexandre Antonelli
bioRxiv 009274; doi: https://doi.org/10.1101/009274

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Evolutionary Biology
Subject Areas
All Articles
  • Animal Behavior and Cognition (4222)
  • Biochemistry (9095)
  • Bioengineering (6733)
  • Bioinformatics (23916)
  • Biophysics (12066)
  • Cancer Biology (9484)
  • Cell Biology (13720)
  • Clinical Trials (138)
  • Developmental Biology (7614)
  • Ecology (11644)
  • Epidemiology (2066)
  • Evolutionary Biology (15459)
  • Genetics (10610)
  • Genomics (14281)
  • Immunology (9448)
  • Microbiology (22749)
  • Molecular Biology (9057)
  • Neuroscience (48811)
  • Paleontology (354)
  • Pathology (1478)
  • Pharmacology and Toxicology (2558)
  • Physiology (3818)
  • Plant Biology (8300)
  • Scientific Communication and Education (1466)
  • Synthetic Biology (2285)
  • Systems Biology (6163)
  • Zoology (1296)