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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ftdoajarticles:oai:doaj.org/article:02438f7632814bdf85903de8294f2bf0 2023-05-15T17:38:18+02:00 SEASIM-NEAM: A Spatially-Explicit Agent-based SIMulator of North East Atlantic Mackerel population dynamics Robin Boyd Nicola Walker Kieran Hyder Robert Thorpe Shovonlal Roy Richard Sibly 2020-01-01T00:00:00Z https://doi.org/10.1016/j.mex.2020.101044 https://doaj.org/article/02438f7632814bdf85903de8294f2bf0 EN eng Elsevier http://www.sciencedirect.com/science/article/pii/S2215016120302648 https://doaj.org/toc/2215-0161 2215-0161 doi:10.1016/j.mex.2020.101044 https://doaj.org/article/02438f7632814bdf85903de8294f2bf0 MethodsX, Vol 7, Iss , Pp 101044- (2020) Atlantic mackerel Individual-based model Bioenergetics Spatially-explicit Approximate bayesian computation Science Q article 2020 ftdoajarticles https://doi.org/10.1016/j.mex.2020.101044 2022-12-31T06:27:52Z 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 Directory of Open Access Journals: DOAJ Articles MethodsX 7 101044 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
Atlantic mackerel Individual-based model Bioenergetics Spatially-explicit Approximate bayesian computation Science Q |
spellingShingle |
Atlantic mackerel Individual-based model Bioenergetics Spatially-explicit Approximate bayesian computation Science Q Robin Boyd Nicola Walker Kieran Hyder Robert Thorpe Shovonlal Roy Richard Sibly SEASIM-NEAM: A Spatially-Explicit Agent-based SIMulator of North East Atlantic Mackerel population dynamics |
topic_facet |
Atlantic mackerel Individual-based model Bioenergetics Spatially-explicit Approximate bayesian computation Science Q |
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 |
Robin Boyd Nicola Walker Kieran Hyder Robert Thorpe Shovonlal Roy Richard Sibly |
author_facet |
Robin Boyd Nicola Walker Kieran Hyder Robert Thorpe Shovonlal Roy Richard Sibly |
author_sort |
Robin Boyd |
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 |
publisher |
Elsevier |
publishDate |
2020 |
url |
https://doi.org/10.1016/j.mex.2020.101044 https://doaj.org/article/02438f7632814bdf85903de8294f2bf0 |
genre |
North East Atlantic Northeast Atlantic |
genre_facet |
North East Atlantic Northeast Atlantic |
op_source |
MethodsX, Vol 7, Iss , Pp 101044- (2020) |
op_relation |
http://www.sciencedirect.com/science/article/pii/S2215016120302648 https://doaj.org/toc/2215-0161 2215-0161 doi:10.1016/j.mex.2020.101044 https://doaj.org/article/02438f7632814bdf85903de8294f2bf0 |
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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