FN Archimer Export Format
PT J
TI Selection and validation of a complex fishery model using an uncertainty hierarchy
BT 
AF LEHUTA, Sigrid
   PETITGAS, Pierre
   MAHEVAS, Stephanie
   HURET, Martin
   VERMARD, Youen
   URIARTE, Andres
   RECORD, Nicholas R.
AS 1:1;2:1;3:1;4:2;5:3;6:4;7:5;
FF 1:PDG-RBE-HMMN-RHBL;2:PDG-RBE-EMH;3:PDG-RBE-EMH;4:PDG-RBE-STH-LBH;5:PDG-RBE-HMMN-RHBL;6:;7:;
C1 IFREMER, F-44311 Nantes 03, France.
   IFREMER, Ctr Brest, F-29280 Plouzane, France.
   IFREMER, F-62321 Boulogne, France.
   AZTI Tecnalia, E-20110 Guipuzcoa, Spain.
   Bowdoin Coll, Earth & Oceanog Sci Dept, Brunswick, ME 04011 USA.
C2 IFREMER, FRANCE
   IFREMER, FRANCE
   IFREMER, FRANCE
   AZTI, SPAIN
   BOWDOIN COLL, USA
SI BOULOGNE
   NANTES
   BREST
SE PDG-RBE-HMMN-RHBL
   PDG-RBE-EMH
   PDG-RBE-STH-LBH
IN WOS Ifremer jusqu'en 2018
   copubli-europe
   copubli-int-hors-europe
IF 1.843
TC 18
UR https://archimer.ifremer.fr/doc/00148/25965/24150.pdf
LA English
DT Article
CR PELGAS 2009
BO Thalassa
DE ;Bay of Biscay anchovy;Dynamic fishery model;Model selection;Uncertainty;Validation
AB Assessing the validity of a model is essential for its credibility especially when the model is used as decision making tool. Complex dynamic fishery models are recommended to investigate the functioning of fisheries and to assess the impact of management strategies, particularly spatial fishing regulations. However, their use is limited due to the difficulty and computational cost of parameterizing and gaining confidence, particularly for parameter rich models. These difficulties are compounded by uncertainty regarding parameter values, many of which are often taken from literature or estimated indirectly. Here we propose a methodology to improve confidence and understanding in the model, easily transferable to any complex model. The approach combines sensitivity analysis, scalability of parameters, optimization procedures, and model skill assessment in order to parameterize, validate and achieve the most plausible formulation of a model given the available knowledge while reducing the computational load. The methodology relies on five steps: (1) sensitivity analysis, (2) classification of parameters into a hierarchy according to their sensitivity and the nature of their uncertainty, (3) building of alternative formulations, (4) calibration and (5) skill evaluation. The approach is illustrated here by reviewing the parameterization of the ISIS-Fish model of the anchovy fishery in the Bay of Biscay. By using this approach, it is possible to make a thorough assessment of lacking information (e.g. accessibility to fishing and adult mortality) and to identify the strengths and weaknesses of the model in the context of different hypotheses. When applied to the ISIS-Fish model, the results suggest higher egg and adult mortality than formerly estimated, as well as new estimates for the migration towards spawning areas. They show the reliability of the model in terms of correlations with observations and the need for further efforts to model purse seiner catches. The methodology proved to be a cost-efficient tool for objectively assessing applied model validity in cases where parameter values are a mix of literature, expert opinion and calibration.
PY 2013
PD JUL
SO Fisheries Research
SN 0165-7836
PU Elsevier Science Bv
VL 143
UT 000319491700006
BP 57
EP 66
DI 10.1016/j.fishres.2013.01.008
ID 25965
ER

EF