Biodiversity & Conservation

, Volume 15, Issue 3, pp 799–815 | Cite as

Inferences from Common Species Communities for Selecting Conservation Areas

  • Frederic JiguetEmail author
  • Romain Julliard


We aimed at identifying probabilistic areas of high biodiversity value over a large spatial scale, e.g., an entire country (France) within the temperate region, that could work as valuable conservation areas for both rare and common species. We aimed at identifying areas where four measures on bird community overpass a selected threshold value, by using probability interpolation models. The four variables considered were the rare species number, and three measures related to common bird community: relative abundance, estimated species richness and composition originality. For the latter, we developed an indicator that discriminates original from more ordinary compositions of common bird communities, accounting for the number of representatives in each species. This indicator was positively correlated to rare breeding species number, so that original composition of common bird communities allows us to identify areas also supporting the rarest species. Areas with high probabilities of two indicators reaching their threshold values represented 2.9% of continental France. Most double-indicator areas were those with high species richness and high relative abundance, then with original communities and high rare species number. The originality indicator was revealed valuable to identify the most suitable areas that could ensure the preservation of both rare and common species, at a national scale. By preserving sites supporting original common bird communities, conservationists would ensure the protection of rare and common species.


Bird community Common species Conservation Originality indicator Probability kriging Rare species 


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Copyright information

© Springer 2005

Authors and Affiliations

  1. 1.Centre de Recherches sur la Biologie des Populations d'Oiseaux, UMR 5173 ‘Conservation des espèces, restauration et suivi des populations’Muséum National d’Histoire NaturelleParisFrance

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