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Auteur (up) Gravel, D.; Poisot, T.; Albouy, C.; Velez, L.; Mouillot, D. url  doi
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  Titre Inferring food web structure from predator-prey body size relationships Type Article scientifique
  Année 2013 Publication Revue Abrégée Methods in Ecology and Evolution  
  Volume 4 Numéro 11 Pages 1083-1090  
  Mots-Clés Body size; Niche model; biodiversity; climate-change; community; constraints; ecological networks; ecology; ecosystems; food web; impacts; interaction strengths; metaweb; models; species richness  
  Résumé 1. Current global changes make it important to be able to predict which interactions will occur in the emerging ecosystems. Most of the current methods to infer the existence of interactions between two species require a good knowledge of their behaviour or a direct observation of interactions. In this paper, we overcome these limitations by developing a method, inspired from the niche model of food web structure, using the statistical relationship between predator and prey body size to infer the matrix of potential interactions among a pool of species. 2. The novelty of our approach is to infer, for any species of a given species pool, the three species-specific parameters of the niche model. The method applies to both local and metaweb scales. It allows one to evaluate the feeding interactions of a new species entering the community. 3. We find that this method gives robust predictions of the structure of food webs and that its efficiency is increased when the strength of the body-size relationship between predators and preys increases. 4. We finally illustrate the potential of the method to infer the metaweb structure of pelagic fishes of the Mediterranean sea under different global change scenarios.  
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  Langue English Langue du Résumé Titre Original  
  Éditeur de collection Titre de collection Titre de collection Abrégé  
  Volume de collection Numéro de collection Edition  
  ISSN 2041-210x ISBN Médium  
  Région Expédition Conférence  
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  Numéro d'Appel MARBEC @ isabelle.vidal-ayouba @ collection 674  
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