FN Archimer Export Format
PT J
TI Identifying mature fish aggregation areas during spawning season by combining catch declarations and scientific survey data
BT 
AF Alglave, Baptiste
   Vermard, Youen
   Rivot, Etienne
   Etienne, Marie-Pierre
   Woillez, Mathieu
AS 1:1,2;2:1;3:2;4:3;5:4;
FF 1:PDG-RBE-HALGO-EMH;2:PDG-RBE-HALGO-EMH;3:;4:;5:PDG-RBE-HALGO-LBH;
C1 DECOD (Ecosystem Dynamics and Sustainability), IFREMER, Institut Agro, INRAE, Nantes, France
   DECOD (Ecosystem Dynamics and Sustainability), Institut Agro, IFREMER, INRAE, Rennes, France
   Mathematical Research Institute of Rennes IRMAR, Rennes University, Rennes, France
   DECOD (Ecosystem Dynamics and Sustainability), IFREMER, Institut Agro, INRAE, Brest, France
C2 IFREMER, FRANCE
   INST AGRO RENNES-ANGERS, FRANCE
   UNIV RENNES, FRANCE
   IFREMER, FRANCE
SI NANTES
   BREST
SE PDG-RBE-HALGO-EMH
   PDG-RBE-HALGO-LBH
UM DECOD
IN WOS Ifremer UMR
   WOS Cotutelle UMR
   copubli-france
   copubli-univ-france
IF 2.4
TC 1
UR https://archimer.ifremer.fr/doc/00817/92910/99342.pdf
LA English
DT Article
DE ;species distribution model;spatio-temporal model;hierarchical model;VMS and logbook data;aggregation areas;fish reproduction areas
AB Identifying and protecting essential fish habitats like spawning grounds requires an accurate knowledge of fish spatio-temporal distribution. Commercial declarations coupled with Vessel Monitoring System provide fine scale information on the full year to map fish distribution and identify essential habitats. We developed an integrated framework to infer fish spatial distribution on a monthly time step by combining scientific and commercial data while explicitly considering the preferential sampling of fishermen towards areas of higher biomass. We developed a method to identify areas of persistent aggregation of biomass during the spawning season and interpret these as spawning areas. The model is applied to infer maps of relative biomass for three species (sole, whiting, squids) in the Bay of Biscay on a monthly time step over a 9-year period. Integrating several fleets in inference provides a good coverage of the area and improves model predictions. The preferential sampling parameters give insights into the temporal dynamics of the targeting behavior of the different fleets. Last, persistent aggregation areas reveal consistent with the available literature on spawning grounds, highlighting the potential of our approach to identify reproduction areas. 
PY 2023
PD MAY
SO Canadian Journal Of Fisheries And Aquatic Sciences
SN 0706-652X
PU Canadian Science Publishing
VL 80
IS 5
UT 000938848300001
BP 808
EP 824
DI 10.1139/cjfas-2022-0110
ID 92910
ER

EF