FN Archimer Export Format PT J TI Hazard warning: model misuse ahead BT AF DICKEY-COLLAS, Mark PAYNE, Mark R. TRENKEL, Verena M. NASH, Richard D. M. AS 1:1;2:2;3:3;4:4; FF 1:;2:;3:PDG-RBE-EMH;4:; C1 ICES, DK-1553 Copenhagen, Denmark. DTU Aqua, DK-2920 Charlottenlund, Denmark. IFREMER, F-44300 Nantes 03, France. IMR, N-5817 Bergen, Norway. C2 ICES, DENMARK UNIV TECH DENMARK (DTU AQUA), DENMARK IFREMER, FRANCE INST MARINE RES, NORWAY SI NANTES SE PDG-RBE-EMH IN WOS Ifremer jusqu'en 2018 copubli-europe IF 2.377 TC 40 UR https://archimer.ifremer.fr/doc/00222/33371/32179.pdf LA English DT Article DE ;climate;fisheries;GAM;management;prediction;projection;recruitment;time-series analysis AB The use of modelling approaches in marine science, and in particular fisheries science, is explored. We highlight that the choice of model used for an analysis should account for the question being posed or the context of the management problem. We examine a model-classification scheme based on Richard Levins' 1966 work suggesting that models can only achieve two of three desirable model attributes: realism, precision, and generality. Model creation, therefore, requires trading-off of one of these attributes in favour of the other two: however, this is often in conflict with the desires of end-users (i.e. mangers or policy developers). The combination of attributes leads to models that are considered to have empirical, mechanistic, or analytical characteristics, but not a combination of them. In fisheries science, many examples can be found of models with these characteristics. However, we suggest that models or techniques are often employed without consideration of their limitations, such as projecting into unknown space without generalism, or fitting empirical models and inferring causality. We suggest that the idea of trade-offs and limitations in modelling be considered as an essential first step in assessing the utility of a model in the context of knowledge for decision-making in management. PY 2014 PD OCT SO Ices Journal Of Marine Science SN 1054-3139 PU Oxford Univ Press VL 71 IS 8 UT 000343317100029 BP 2300 EP 2306 DI 10.1093/icesjms/fst215 ID 33371 ER EF