FN Archimer Export Format
PT J
TI Ecosystem modelling to assess the impact of rearing density, environment variability and mortality on oyster production
BT 
AF Cugier, Philippe
   Thomas, Yoann
   Bacher, Cedric
AS 1:1;2:2;3:1;
FF 1:PDG-ODE-DYNECO-LEBCO;2:;3:PDG-ODE-DYNECO;
C1 Ifremer, DYNECO, 29280 Plouzané, France
   University of Brest, CNRS, IRD, Ifremer, LEMAR, 29280 Plouzané, France
C2 IFREMER, FRANCE
   UBO, FRANCE
SI BREST
SE PDG-ODE-DYNECO-LEBCO
   PDG-ODE-DYNECO
UM LEMAR
IN WOS Ifremer UPR
   WOS Cotutelle UMR
   DOAJ
   copubli-france
   copubli-univ-france
IF 2.2
TC 1
UR https://archimer.ifremer.fr/doc/00766/87836/93402.pdf
   https://archimer.ifremer.fr/doc/00766/87836/93403.pdf
LA English
DT Article
DE ;3D ecosystem modelling;Individual growth model;Oyster;Environment variability;Mortality;Scenarios;Management tool
AB The natural productivity of ecosystems, farming practices and mortality events drive the rearing density and growth of oysters in shellfish farming areas. The variability of these drivers, which can be of natural or anthropic origin, is therefore an important source of variation in the growth performance and production of shellfish. Knowledge of these variabilities and their relative importance help producers to anticipate their effects and adapt aquaculture practices in order to limit negative impacts and guarantee a constant, or at least acceptable, level of production. In this paper, we implement a 3D model coupling hydrodynamics, primary production and individual growth to predict oyster growth and production in Bourgneuf Bay (French Atlantic coast). We set up numerous scenarios to compare and hierarchize the impacts of aquaculture practices, environmental variability and mortality events on shellfish production. Our results allowed us to propose a simplified management tool, in the form of response functions, to optimize shellfish farming practices interannually. This tool will help shellfish farmers quickly recover production levels in response to variations in mortality and/or environmental conditions. 
PY 2022
SO Aquaculture Environment Interactions
SN 1869-215X
PU Inter-Research Science Center
VL 14
UT 000790579400004
BP 53
EP 70
DI 10.3354/aei00428
ID 87836
ER

EF