bascule de visibilité Search & Display Options

Tout Sélectionner    Désélectionner
 |   | 
Détails
   print
  Enregistrements Liens
Auteur CORMON, X.; LOOTS, C.; VAZ, S.; VERMARD, Y.; MARCHAL, P. url  openurl
  Titre Spatial interactions between saithe (Pollachius virens) and hake (Merluccius merluccius) in the North Sea Type Article scientifique
  Année 2014 Publication Revue Abrégée Ices Journal Of Marine Science  
  Volume 71 Numéro 6 Pages 1342-1355  
  Mots-Clés biotic interactions; competition; Generalized linear models; Hake; North sea; overlap; predator-prey relationship; saithe; species distribution modelling  
  Résumé Spatial interactions between saithe (Pollachius virens) and hake (Merluccius merluccius) were investigated in the North Sea. Saithe is a well-established species in the North Sea, while occurrence of the less common hake has recently increased in the area. Spatial dynamics of these two species and their potential spatial interactions were explored using binomial generalized linear models (GLM) applied to the International Bottom Trawl Survey (IBTS) data from 1991 to 2012. Models included different types of variables: (i) abiotic variables including sediment types, temperature, and bathymetry; (ii) biotic variables including potential competitors and potential preys presence; and (iii) spatial variables. The models were reduced and used to predict and map probable habitats of saithe, hake but also, for the first time in the North Sea, the distribution of the spatial overlap between these two species. Changes in distribution patterns of these two species and of their overlap were also investigated by comparing species' presence and overlap probabilities predicted over an early (1991–1996) and a late period (2007–2012). The results show an increase in the probability over time of the overlap between saithe and hake along with an expansion towards the southwest and Scottish waters. These shifts follow trends observed in temperature data and might be indirectly induced by climate changes. Saithe, hake, and their overlap are positively influenced by potential preys and/or competitors, which confirms spatial co-occurrence of the species concerned and leads to the questions of predator–prey relationships and competition. Finally, the present study provides robust predictions concerning the spatial distribution of saithe, hake, and of their overlap in the North Sea, which may be of interest for fishery managers.  
  Adresse  
  Auteur institutionnel Thèse  
  Editeur Lieu de Publication Éditeur  
  Langue Langue du Résumé Titre Original  
  Éditeur de collection Titre de collection Titre de collection Abrégé  
  Volume de collection Numéro de collection Edition  
  ISSN 1054-3139 ISBN Médium  
  Région Expédition Conférence  
  Notes Approuvé pas de  
  Numéro d'Appel MARBEC @ isabelle.vidal-ayouba @ collection 1135  
Lien permanent pour cet enregistrement
 

 
Auteur Poggiale, J.-C.; Dantigny, P.; De Wit, R.; Steinberg, C. url  isbn
openurl 
  Titre Modeling in Microbial Ecology Type Chapitre de livre
  Année 2015 Publication Revue Abrégée  
  Volume Numéro Pages 847-882  
  Mots-Clés Biofilm models; Biotic interactions; Chemostat; Fermenter models; Metabolic models; Microbial Ecology; Population dynamics  
  Résumé The bases and the principles of modeling in microbial community ecology and biogeochemistry are presented and discussed. Several examples are given. Among them, the fermentation process is largely developed, thus demonstrating how the model allows determining the microbial population growth rate, the death rate, and the maintenance rate. More generally, these models have been used to increase the development of bioenergetic formulations which are presently used in biogeochemical models (Monod, Droop, DEB models). Different types of interactions (competition, predation, and virus–bacteria) are also developed. For each topic, a complete view of the models used in the literature cannot be presented. Consequently, the focus has been done on the demonstration how to build a model instead of providing a long list of existing models. Some recent results in sediment biogeochemistry are provided to illustrate the application of such models.  
  Adresse  
  Auteur institutionnel Thèse  
  Editeur Springer Netherlands Lieu de Publication Éditeur Bertrand, J.-C.; Caumette, P.; Lebaron, P.; Matheron, R.; Normand, P.; Sime-Ngando, T.  
  Langue en Langue du Résumé Titre Original  
  Éditeur de collection Titre de collection Titre de collection Abrégé Environmental Microbiology: Fundamentals and Applications  
  Volume de collection Numéro de collection Edition  
  ISSN ISBN 978-94-017-9117-5 978-94-017-9118-2 Médium  
  Région Expédition Conférence  
  Notes Approuvé pas de  
  Numéro d'Appel MARBEC @ alain.herve @ collection 1395  
Lien permanent pour cet enregistrement
 

 
Auteur Yates, K.L.; Bouchet, P.J.; Caley, M.J.; Mengersen, K.; Randin, C.F.; Parnell, S.; Fielding, A.H.; Bamford, A.J.; Ban, S.; Marcia Barbosa, A.; Dormann, C.F.; Elith, J.; Embling, C.B.; Ervin, G.N.; Fisher, R.; Gould, S.; Graf, R.F.; Gregr, E.J.; Halpin, P.N.; Heikkinen, R.K.; Heinanen, S.; Jones, A.R.; Krishnakumar, P.K.; Lauria, V.; Lozano-Montes, H.; Mannocci, L.; Mellin, C.; Mesgaran, M.B.; Moreno-Amat, E.; Mormede, S.; Novaczek, E.; Oppel, S.; Crespo, G.O.; Peterson, A.T.; Rapacciuolo, G.; Roberts, J.J.; Ross, R.E.; Scales, K.L.; Schoeman, D.; Snelgrove, P.; Sundblad, G.; Thuiller, W.; Torres, L.G.; Verbruggen, H.; Wang, L.; Wenger, S.; Whittingham, M.J.; Zharikov, Y.; Zurell, D.; Sequeira, A.M.M. doi  openurl
  Titre Outstanding Challenges in the Transferability of Ecological Models Type Article scientifique
  Année 2018 Publication Revue Abrégée Trends Ecol. Evol.  
  Volume 33 Numéro 10 Pages 790-802  
  Mots-Clés abundance; biotic interactions; climate-change; decision-making; distributions; habitat selection; niche; predictive models; species distribution models; temporal transferability  
  Résumé Predictive models are central to many scientific disciplines and vital for informing management in a rapidly changing world. However, limited understanding of the accuracy and precision of models transferred to novel conditions (their 'transferability') undermines confidence in their predictions. Here, 50 experts identified priority knowledge gaps which, if filled, will most improve model transfers. These are summarized into six technical and six fundamental challenges, which underlie the combined need to intensify research on the determinants of ecological predictability, including species traits and data quality, and develop best practices for transferring models. Of high importance is the identification of a widely applicable set of transferability metrics, with appropriate tools to quantify the sources and impacts of prediction uncertainty under novel conditions.  
  Adresse  
  Auteur institutionnel Thèse  
  Editeur Lieu de Publication Éditeur  
  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 0169-5347 ISBN Médium  
  Région Expédition Conférence  
  Notes Approuvé pas de  
  Numéro d'Appel MARBEC @ alain.herve @ collection 2447  
Lien permanent pour cet enregistrement
Tout Sélectionner    Désélectionner
 |   | 
Détails
   print

Save Citations:
Export Records: