FN Archimer Export Format
PT J
TI Understanding what controls the spawning distribution of North Sea whiting (Merlangius merlangus) using a multi-model approach
BT 
AF LOOTS, CHRISTOPHE
   VAZ, Sandrine
   PLANQUE, Benjamin
   KOUBBI, Philippe
AS 1:1;2:1;3:2;4:3,4;
FF 1:PDG-DOP-DCMMN-HMMN-RHBL;2:PDG-DOP-DCMMN-HMMN-RHBL;3:;4:;
C1 Inst Francais Rech Exploitat Mer, Lab Ressources Halieut, F-62321 Boulogne, France.
   Inst Marine Res, N-9294 Tromso, Norway.
   Univ Paris 06, UMR 7093, Lab Oceanog Villefranche, F-06230 Villefranche Sur Mer, France.
   CNRS, UMR 7093, LOV, F-06230 Villefranche Sur Mer, France.
C2 IFREMER, FRANCE
   INST MAR RES, NORWAY
   UNIV PARIS 06, FRANCE
   CNRS, FRANCE
SI BOULOGNE
SE PDG-DOP-DCMMN-HMMN-RHBL
IN WOS Ifremer jusqu'en 2018
   copubli-france
   copubli-europe
   copubli-univ-france
IF 2.044
TC 20
TU Centre national de la recherche scientifique
   Université Pierre et Marie Curie
UR https://archimer.ifremer.fr/doc/00022/13313/11361.pdf
LA English
DT Article
CR IBTS 2000
   IBTS 2001
   IBTS 2002
   IBTS 2003
   IBTS 2004
   IBTS 2005
   IBTS 2006
   IBTS 2007
   IBTS 92/2
   IBTS 93/1
   IBTS 93/2
   IBTS 94/1
   IBTS 94/2
   IBTS 95/1
   IBTS 95/2
   IBTS 96/1
   IBTS 96/2
   IBTS 97
   IBTS 98
   IBTS 99
   IYFS 92 - IBTS 92/1
BO Thalassa
DE ;Akaike information criterion;hypotheses inference;model selection;North Sea;spawning distribution;whiting
AB The processes that control the spatial distribution of North Sea whiting (Merlangius merlangus) spawning adults are investigated using a statistical multi-model approach. Models of external and internal controls on the population, such as environmental conditions, spatial constraints, present or past spatial distribution, and demographic state of the population, are evaluated, compared and ranked to select those that are the best able to predict the observed distribution of spawning adults. Model selection is greatly influenced by the selection method, either based on data fitting or prediction, as well as by the threshold value used to stop the selection. Model selection based on prediction tends to select simpler models than selection based on data fitting. The hypotheses underlying the selected models are inferred to play a significant role in controlling North Sea whiting spatial distribution. The multi-model inference approach developed in this study enables comparison of several theoretical concepts and hypotheses and the results provide important clues on the processes involved in the control of the spatial distribution of whiting. We conclude that whiting has a high spatial fidelity to spawning site which can be linked to either geographical attachment or year-to-year persistence of the spatial distribution of the population. Environmental factors – temperature and salinity – appear to influence the geographical extent of spawning whiting distribution, whereas local abundance levels are primarily controlled by internal factors, i.e., population size and spatial segregation between ages.
PY 2011
PD JAN
SO Fisheries Oceanography
SN 1054-6006
PU Wiley-blackwell Publishing, Inc
VL 20
IS 1
UT 000285205300002
BP 18
EP 31
DI 10.1111/j.1365-2419.2010.00564.x
ID 13313
ER

EF