The spatial distribution of Mustelidae in France

PLoS One. 2015 Mar 26;10(3):e0121689. doi: 10.1371/journal.pone.0121689. eCollection 2015.

Abstract

We estimated the spatial distribution of 6 Mustelidae species in France using the data collected by the French national hunting and wildlife agency under the "small carnivorous species logbooks" program. The 1500 national wildlife protection officers working for this agency spend 80% of their working time traveling in the spatial area in which they have authority. During their travels, they occasionally detect dead or living small and medium size carnivorous animals. Between 2002 and 2005, each car operated by this agency was equipped with a logbook in which officers recorded information about the detected animals (species, location, dead or alive, date). Thus, more than 30000 dead or living animals were detected during the study period. Because a large number of detected animals in a region could have been the result of a high sampling pressure there, we modeled the number of detected animals as a function of the sampling effort to allow for unbiased estimation of the species density. For dead animals -- mostly roadkill -- we supposed that the effort in a given region was proportional to the distance traveled by the officers. For living animals, we had no way to measure the sampling effort. We demonstrated that it was possible to use the whole dataset (dead and living animals) to estimate the following: (i) the relative density -- i.e., the density multiplied by an unknown constant -- of each species of interest across the different French agricultural regions, (ii) the sampling effort for living animals for each region, and (iii) the relative detection probability for various species of interest.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Agriculture
  • Animals
  • France
  • Geography
  • Models, Biological
  • Mustelidae / physiology*
  • Population Density
  • Reproducibility of Results
  • Species Specificity

Grants and funding

This paper was partially funded by: The program MASTODONS of the Centre national de la recherche scientifique (http://www.cnrs.fr/mi/spip.php?article53&lang=fr), under the title “Statistiques Crowdsourcing biodiversité” (funded author RR). The program CiSStats funded by the program “réseaux incitatifs” of the Institut national de la recherche agronomique (funded author PM, http://ciam.inra.fr/cisstats/). The program “Chaire de modélisation mathématique et biodiversité” from Véolia, École Polytechnique and Museum national d’histoire naturelle (funded authors CG and RJ; http://www.cmap.polytechnique.fr/chaire-mmb/). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.