sampbias, a method for quantifying geographic sampling biases in species distribution data

bioRxiv (Cold Spring Harbor Laboratory)

Abstract

Abstract Geo-referenced species occurrences from public databases have become essential to biodiversity research and conservation. However, geographical biases are widely recognized as a factor limiting the usefulness of such data for understanding species diversity and distribution. In particular, differences in sampling intensity across a landscape due to differences in human accessibility are ubiquitous but may differ in strength among taxonomic groups and datasets. Although several factors have been described to influence human access (such as presence of roads, rivers, airports and cities), quantifying their specific and combined effects on recorded occurrence data remains challenging. Here we present sampbias , an algorithm and software for quantifying the effect of accessibility biases in species occurrence datasets. Sampbias uses a Bayesian approach to estimate how sampling rates vary as a function of proximity to one or multiple bias factors. The results are comparable among bias factors and datasets. We demonstrate the use of sampbias on a dataset of mammal occurrences from the island of Borneo, showing a high biasing effect of cities and a moderate effect of roads and airports. Sampbias is implemented as a well-documented, open-access and user-friendly R package that we hope will become a standard tool for anyone working with species occurrences in ecology, evolution, conservation and related fields.

Authors 3

1. Alexander Zizka Aachen Naturalis Biodiversity Center

   Leiden University · Leipzig University · German Centre for Integrative Biodiversity Research · Naturalis Biodiversity Center

   Affiliation as printed

   German Centre for Integrative Biodiversity Research Halle-Jena-Leipzig (iDiv), University of Leipzig

   Naturalis Biodiversity Center, Leiden University

   German Centre for Integrative Biodiversity Research Halle-Jena-Leipzig (iDiv), University of Leipzig, Deutscher Platz 5e, 0403 Leipzig, Germany

   Naturalis Biodiversity Center, Leiden University, Leiden, Darwinweg , 333 CR Leiden The Netherlands

2. Alexandre Antonelli

   University of Gothenburg · Royal Botanic Gardens, Kew

   Affiliation as printed

   Department for Biological and Environmental Sciences, University of Gothenburg

   Gothenburg Global Biodiversity Centre, University of Gothenburg

   Royal Botanic Gardens Kew

   Department for Biological and Environmental Sciences, University of Gothenburg, Box 61, 05 30 Gothenburg, Sweden

   Gothenburg Global Biodiversity Centre, University of Gothenburg, Box 461, 405 0 Gothenburg, Sweden

   Royal Botanic Gardens Kew, TW9 3AE, Richmond, Surrey, United Kingdom

3. Daniele Silvestro

   University of Gothenburg · University of Fribourg

   Affiliation as printed

   Department for Biological and Environmental Sciences, University of Gothenburg

   Department of Biology, University of Fribourg

   Gothenburg Global Biodiversity Centre, University of Gothenburg

   Department for Biological and Environmental Sciences, University of Gothenburg, Box 61, 05 30 Gothenburg, Sweden

   Department of Biology, University of Fribourg, Ch. du Musée 10, 1700 Fribourg, Switzerland

   Gothenburg Global Biodiversity Centre, University of Gothenburg, Box 461, 405 0 Gothenburg, Sweden