FN Archimer Export Format
PT J
TI Scale-dependency of the environmental influence on fish β-diversity: Implications for ecoregionalization and conservation
BT 
AF GARCIA, Jessica
   PELLETIER, Dominique
   CARPENTIER, Liliane
   ROMAN, William
   BOCKEL, Thomas
AS 1:1;2:1;3:1;4:1;5:1;
FF 1:PDG-RBE-LEADNC;2:PDG-RBE-EMH;3:PDG-RBE-LEADNC;4:PDG-RBE-LEADNC;5:PDG-RBE-LEADNC;
C1 IFREMER, Unite Rech Lagons Ecosyst & Aquaculture Durable N, Noumea, New Caledonia.
C2 IFREMER, FRANCE
SI NOUMEA
   NANTES
SE PDG-RBE-LEADNC
   PDG-RBE-EMH
IN WOS Ifremer jusqu'en 2018
IF 3.884
TC 5
UR https://archimer.ifremer.fr/doc/00455/56668/58629.pdf
LA English
DT Article
CR CHESTERFIELD-BELLONA 2013
   KONE 2013
DE ;β‐diversity;ecoregion;gradient forest;marine biodiversity;New Caledonia;scale-dependency;species turnover;underwater video
AB Aim To determine the ecoregions (spatial marine areas with similar environmental and physical conditions associated with relatively homogeneous fish assemblages) for shallow reef fish assemblages based on predictive models of beta diversity (β‐diversity) that account for both large‐scale environmental factors and local habitat characteristics. We assessed the influence of a spatial scale to rank the importance of these factors. Location New Caledonian (south‐west Pacific Ocean, 17–24° S, 158–172° W) Exclusive Economic Zone, Coral Sea Marine Park. Taxon Fish. Methods Fish and habitat data that were collected at 13 sites around New Caledonia using unbaited rotating underwater video (285 sampling stations) were analysed. Gradient forest modelling was used to predict the fish β‐diversity along the gradients of environmental factors. Ecoregions were obtained by applying clustering methods to gradient forest predictions. Results The gradient forest models of β‐diversity retained 59 species (total: 206 fish species) with R² > 0, including 19 fish species with R² from 0.03% to 69%. For these 19 species, the models explained up to 26% of the variance. At a large scale, β‐diversity was significantly explained by nutrient concentrations, sea surface salinity and temperature. Among the eight ecoregions that were delineated based on the β‐diversity predictions, three regions corresponded to remote sites under oceanic influence where human pressures are low and the surface nutrient concentrations are high. On the local scale, the benthic habitat explained β‐diversity better than the physical and chemical parameters, particularly in the areas subject to anthropogenic pressures. Main conclusions On the local scale, the respective importance of environmental factors (physical and chemical parameters versus benthic habitat) differed according to ecosystem health. Our findings suggest that nutrient enrichment due to avifauna may have a positive effect on fish β‐diversity when an ecosystem is healthy. The ecoregions reflect fish species composition in relation to a large set of environmental parameters. 
PY 2018
PD AUG
SO Journal Of Biogeography
SN 0305-0270
PU Wiley
VL 45
IS 8
UT 000440297300010
BP 1818
EP 1832
DI 10.1111/jbi.13381
ID 56668
ER

EF