Hazard warning: model misuse ahead

Type Article
Date 2014-10
Language English
Author(s) Dickey-Collas Mark1, Payne Mark R.2, Trenkel Verena M.ORCID3, Nash Richard D. M.4
Affiliation(s) 1 : ICES, DK-1553 Copenhagen, Denmark.
2 : DTU Aqua, DK-2920 Charlottenlund, Denmark.
3 : IFREMER, F-44300 Nantes 03, France.
4 : IMR, N-5817 Bergen, Norway.
Source Ices Journal Of Marine Science (1054-3139) (Oxford Univ Press), 2014-10 , Vol. 71 , N. 8 , P. 2300-2306
DOI 10.1093/icesjms/fst215
WOS© Times Cited 28
Note Contribution to the Special Issue: ‘Commemorating 100 years since Hjort’s 1914 treatise on fluctuations in the great fisheries of northern Europe’
Keyword(s) climate, fisheries, GAM, management, prediction, projection, recruitment, time-series analysis
Abstract 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.
Full Text
File Pages Size Access
7 356 KB Access on demand
Author's final draft 12 388 KB Open access
Top of the page