@article{fdi:010067399, title = {{S}tandardization of catch rates for the eastern tropical atlantic bigeye tuna caught by the {F}rench purse seine {D}f{AD} fishery}, author = {{K}atara, {I}. and {G}aertner, {D}aniel and {M}aufroy, {A}lexandra and {C}hassot, {E}mmanuel}, editor = {}, language = {{ENG}}, abstract = {{T}he drifting {F}ish {A}ggregating {D}evice (d{FAD}) purse seine fishery is complex and fishing effort depends on a multitude of factors. {T}raditional indices of fishing effort such as searching time are meaningless for this fishery. {W}e composed a comprehensive list of 28 candidate variables that describe the d{FAD} fishery and used them as predictors of fishing effort in bigeye tuna {CPUE} standardization of the {F}rench purse seiners operating in the {E}astern {A}tlantic {O}cean during 2007-2013. {W}e performed variable selection using penalized maximum likelihood in {GLM} and {GLMM} frameworks, aiming to improve prediction accuracy and interpretability of the selected models. {W}e applied the {L}asso ({L}east {A}bsolute {S}hrinkage and {S}election {O}perator) regression models to derive the true parsimonious model, because the number of candidate independent variables is large compared to the number of observations. {T}he penalized model selection process retained explanatory variables such as: the skipper, the vessel, the price of targeted tuna species, the density and spatial distribution of {FAD}s and the number/type of deployed buoys. {T}he inclusion of these predictors in {CPUE} standardization models provided realistic estimates of uncertainty. {W}e propose the systematic collection of selected explanatory variables and their usage in d{FAD} related tuna {CPUE}s standardization in a mixed model framework.}, keywords = {{PECHE} {THONIERE} ; {SENNEUR} ; {CAPTURE} ; {THON} ; {DISTRIBUTION} {SPATIALE} ; {EFFORT} {DE} {PECHE} ; {DISPOSITIF} {DE} {CONCENTRATION} {DES} {POISSONS} ; {ANALYSE} {STATISTIQUE} ; {MODELISATION} ; {ATLANTIQUE} ; {FRANCE}}, booktitle = {}, journal = {{C}ollective {V}olume of {S}cientific {P}apers - {ICCAT}}, volume = {72}, numero = {2 ({SCRS}/2015/06)}, pages = {406--414}, ISSN = {1021-5212}, year = {2016}, URL = {https://www.documentation.ird.fr/hor/fdi:010067399}, }