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Boyd, Robin, Walker, Nicola, Hyder, Kieran 
ORCID: https://orcid.org/0000-0003-1428-5679, Thorpe, Robert, Roy, Shovonlal and Sibly, Richard
(2020)
SEASIM-NEAM: A Spatially-Explicit Agent-based SIMulator of North East Atlantic Mackerel population dynamics.
MethodsX, 7.
ISSN 2215-0161
Abstract
In 2018 we published a spatially-explicit individual-based model (IBM) that uses satellite-derived maps of food availability and temperature to predict Northeast Atlantic mackerel (Scomber scombrus, NEAM) population dynamics. Since then, to address various ecological questions, we have extended the IBM to include additional processes and data. Throughout its development, technical documents have been provided in the form of e.g. supplementary information to published articles. However, we acknowledge that it would be difficult for potential users to collate information from separate supplementary documents and gain a full understanding of the current state of the IBM. Here, we provide a full technical specification of the latest version of our IBM. The technical specification is provided in the standard ODD (Overview, Design concepts and Details) format, and supplemented by a TRACE (TRAnsparent and Comprehensive model Evaludation) document. For the first time, we give our model the acronym SEASIM-NEAM: a Spatially-Explicit Agent-based SIMulator of North East Atlantic Mackerel population dynamics. This article supersedes previous documentation. Going forward we hope that this article will stimulate development of similar models. • This article collates improvements that have been made to SEASIM-NEAM over time.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | approximate bayesian computation,atlantic mackerel,bioenergetics,individual-based model,seasim-neam,spatially-explicit,clinical biochemistry,medical laboratory technology ,/dk/atira/pure/subjectarea/asjc/1300/1308 |
| Faculty \ School: | Faculty of Science > School of Environmental Sciences |
| Related URLs: | |
| Depositing User: | LivePure Connector |
| Date Deposited: | 25 Nov 2023 03:21 |
| Last Modified: | 25 Sep 2024 17:34 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/93786 |
| DOI: | 10.1016/j.mex.2020.101044 |
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