Titre :

Modeling of Beta Diversity in Tunisian Waters: Predictions Using Generalized Dissimilarity Modeling and Bioregionalisation Using Fuzzy Clustering

Auteur(s) :

Ben Rais Lasram, Frida [Auteur]
Laboratoire d’Océanologie et de Géosciences (LOG) - UMR 8187 [LOG]
Ecosystèmes et Ressources Aquatiques [UR03AGRO1]
Hattab, Tarek [Auteur]
Ecologie et Dynamique des Systèmes Anthropisés - UMR CNRS 7058 UPJV [EDYSAN]
Laboratoire des Sciences de l'Environnement Marin (LEMAR) [LEMAR]
Ecosystèmes et Ressources Aquatiques [UR03AGRO1]
Halouani, Ghassen [Auteur]
Laboratoire des Sciences de l'Environnement Marin (LEMAR) [LEMAR]
Ecosystèmes et Ressources Aquatiques [UR03AGRO1]
Romdhane, Mohamed Salah [Auteur]
Ecosystèmes et Ressources Aquatiques [UR03AGRO1]
Le Loc’h, François [Auteur]
Laboratoire des Sciences de l'Environnement Marin (LEMAR) [LEMAR]

Titre de la revue :

PLoS One

Pagination :

e0131728

Éditeur :

Public Library of Science

Date de publication :

2015

ISSN :

1932-6203

Mot(s)-clé(s) en anglais :

ACL
SPECIES DISTRIBUTION
CLIMATE-CHANGE
COASTAL
BIODIVERSITY
ASSEMBLAGES
INDICATOR
PATTERNS
REGIONS
GABES
SCALE

Discipline(s) HAL :

Sciences de l'environnement/Biodiversité et Ecologie

Résumé en anglais : [en]

Spatial patterns of beta diversity are a major focus of ecology. They can be especially valuable in conservation planning. In this study, we used a generalized dissimilarity modeling approach to analyze and predict the ...
Lire la suite >Spatial patterns of beta diversity are a major focus of ecology. They can be especially valuable in conservation planning. In this study, we used a generalized dissimilarity modeling approach to analyze and predict the spatial patterns of beta diversity for commercially exploited, demersal marine species assemblages along the Tunisian coasts. For this study, we used a presence/absence dataset which included information on 174 species (invertebrates and fishes) and 9 environmental variables. We first performed the modeling analyses and assessed beta diversity using the turnover component of the Jaccard’s dissimilarity index. We then performed nonmetric multidimensional scaling to map predicted beta diversity. To delineate the biogeographical regions, we used fuzzy cluster analysis. Finally, we also identified a set of indicator species which characterized the species assemblages in each identified biogeographical region. The predicted beta diversity map revealed two patterns: an inshore-offshore gradient and a south-north latitudinal gradient. Three biogeographical regions were identified and 14 indicator species. These results constitute a first contribution of the bioregionalisation of the Tunisian waters and highlight the issues associated with current fisheries management zones and conservation strategies. Results could be useful to follow an Ecosystem Based Management approach by proposing an objective spatial partitioning of the Tunisian waters. This partitioning could be used to prioritize the adjustment of the actual fisheries management entities, identify current data gaps, inform future scientific surveys and improve current MPA network.Lire moins >

Langue :

Anglais

Vulgarisation :

Non

Collections :

• Laboratoire d'Océanologie et de Géosciences (LOG) - UMR 8187

Source :

Harvested from HAL