Marine ecosystems model development should be rooted in past experiences, not anchored in old habits. (3rd December 2019)

• Record Type: Journal Article
• Authors: Maps, Frédéric; Record, Nicholas R
• Editors: Andersen, Ken
• Is Part Of: ICES journal of marine science. Volume 77:Number 1(2020)
• Page Start: 46
• Page End: 57
• Publication Date: 2019-12-03
• Subjects: anchoring -- best practices -- model design -- numerical modelling -- parameterization; Ocean -- Periodicals; Fisheries -- Periodicals; Fishes -- Periodicals; Marine biology -- Bibliography -- Periodicals; 551.4605
• DOI: 10.1093/icesjms/fsz218
• Languages: English
• ISSNs: 1054-3139

Abstract

Abstract: Numerical models of marine ecosystems tend to increase in complexity, incorporating a growing number of functions and parameters. Here, we reflect on the issue of "anchoring" inherent to model development, i.e. the tendency for modellers to take processes, functional forms and parameters from previous studies as granted. We focused on the particular example of the parameterization of temperature-dependent ontogeny in Calanus spp. copepods. We could identify 68 studies that implemented and parameterized this functional relationship. Semantic analysis identified distinct clusters of research scopes and coauthor networks. We showed that biases in parameters origin have the potential to produce misleading results, while recent experimental studies were often not assimilated into contemporary modelling studies. Anchoring involves external constraints in numerical models' development such as conceptual gaps and data scarcity, as well as internal drivers such as academic ontogeny and cultural background of the modeller. Retrospective quantitative literature analyses help identify how biases have worked their way into the collective understanding and help to suggest ways forward for the research community. These involve implementation of revision management systems for parameters and functional forms as already exists for numerical codes, and, as always, a more efficient dialogue between modellers, experimentalists and field ecologists.