SEASIM-NEAM: A Spatially-Explicit Agent-based SIMulator of North East Atlantic Mackerel population dynamics

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...

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Published in:MethodsX
Main Authors: Boyd, Robin, Walker, Nicola, Hyder, Kieran, Thorpe, Robert, Roy, Shovonlal, Sibly, Richard
Format: Article in Journal/Newspaper
Language:unknown
Published: 2020
Subjects:
Online Access:https://ueaeprints.uea.ac.uk/id/eprint/93786/
https://doi.org/10.1016/j.mex.2020.101044
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spelling ftuniveastangl:oai:ueaeprints.uea.ac.uk:93786 2024-06-23T07:55:22+00:00 SEASIM-NEAM: A Spatially-Explicit Agent-based SIMulator of North East Atlantic Mackerel population dynamics Boyd, Robin Walker, Nicola Hyder, Kieran Thorpe, Robert Roy, Shovonlal Sibly, Richard 2020-09-09 https://ueaeprints.uea.ac.uk/id/eprint/93786/ https://doi.org/10.1016/j.mex.2020.101044 unknown Boyd, Robin, Walker, Nicola, Hyder, Kieran, 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 doi:10.1016/j.mex.2020.101044 Article PeerReviewed 2020 ftuniveastangl https://doi.org/10.1016/j.mex.2020.101044 2024-06-11T14:24:07Z 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. Article in Journal/Newspaper North East Atlantic Northeast Atlantic University of East Anglia: UEA Digital Repository MethodsX 7 101044
institution Open Polar
collection University of East Anglia: UEA Digital Repository
op_collection_id ftuniveastangl
language unknown
description 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.
format Article in Journal/Newspaper
author Boyd, Robin
Walker, Nicola
Hyder, Kieran
Thorpe, Robert
Roy, Shovonlal
Sibly, Richard
spellingShingle Boyd, Robin
Walker, Nicola
Hyder, Kieran
Thorpe, Robert
Roy, Shovonlal
Sibly, Richard
SEASIM-NEAM: A Spatially-Explicit Agent-based SIMulator of North East Atlantic Mackerel population dynamics
author_facet Boyd, Robin
Walker, Nicola
Hyder, Kieran
Thorpe, Robert
Roy, Shovonlal
Sibly, Richard
author_sort Boyd, Robin
title SEASIM-NEAM: A Spatially-Explicit Agent-based SIMulator of North East Atlantic Mackerel population dynamics
title_short SEASIM-NEAM: A Spatially-Explicit Agent-based SIMulator of North East Atlantic Mackerel population dynamics
title_full SEASIM-NEAM: A Spatially-Explicit Agent-based SIMulator of North East Atlantic Mackerel population dynamics
title_fullStr SEASIM-NEAM: A Spatially-Explicit Agent-based SIMulator of North East Atlantic Mackerel population dynamics
title_full_unstemmed SEASIM-NEAM: A Spatially-Explicit Agent-based SIMulator of North East Atlantic Mackerel population dynamics
title_sort seasim-neam: a spatially-explicit agent-based simulator of north east atlantic mackerel population dynamics
publishDate 2020
url https://ueaeprints.uea.ac.uk/id/eprint/93786/
https://doi.org/10.1016/j.mex.2020.101044
genre North East Atlantic
Northeast Atlantic
genre_facet North East Atlantic
Northeast Atlantic
op_relation Boyd, Robin, Walker, Nicola, Hyder, Kieran, 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
doi:10.1016/j.mex.2020.101044
op_doi https://doi.org/10.1016/j.mex.2020.101044
container_title MethodsX
container_volume 7
container_start_page 101044
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