Data and code for: Building use-inspired species distribution models: using multiple data types to examine and improve model performance ...
Species distribution models (SDMs) are becoming an important tool for marine conservation and management. Yet while there is an increasing diversity and volume of marine biodiversity data for training SDMs, little practical guidance is available on how to leverage distinct data types to build robust...
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Dryad
2023
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Online Access: | https://dx.doi.org/10.5061/dryad.h44j0zpr2 https://datadryad.org/stash/dataset/doi:10.5061/dryad.h44j0zpr2 |
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ftdatacite:10.5061/dryad.h44j0zpr2 2024-09-15T18:26:23+00:00 Data and code for: Building use-inspired species distribution models: using multiple data types to examine and improve model performance ... Braun, Camrin Arostegui, Martin Farchadi, Nima Alexander, Michael Afonso, Pedro Allyn, Andrew Bograd, Steven Brodie, Stephanie Crear, Daniel Culhane, Emmett Curtis, Tobey Hazen, Elliott Kerney, Alex Lezama-Ochoa, Nerea Mills, Katherine Pugh, Dylan Queiroz, Nuno Scott, James Skomal, Gregory Sims, David Thorrold, Simon Welch, Heather Young-Morse, Riley Lewison, Rebecca 2023 https://dx.doi.org/10.5061/dryad.h44j0zpr2 https://datadryad.org/stash/dataset/doi:10.5061/dryad.h44j0zpr2 en eng Dryad https://dx.doi.org/10.5281/zenodo.7971532 https://dx.doi.org/10.21203/rs.3.rs-2802316/v1 Creative Commons Zero v1.0 Universal https://creativecommons.org/publicdomain/zero/1.0/legalcode cc0-1.0 FOS Earth and related environmental sciences species distribution models prediction Ecological forecasting spatial ecology highly migratory species Climate change Dataset dataset 2023 ftdatacite https://doi.org/10.5061/dryad.h44j0zpr210.5281/zenodo.797153210.21203/rs.3.rs-2802316/v1 2024-07-03T13:03:38Z Species distribution models (SDMs) are becoming an important tool for marine conservation and management. Yet while there is an increasing diversity and volume of marine biodiversity data for training SDMs, little practical guidance is available on how to leverage distinct data types to build robust models. We explored the effect of different data types on the fit, performance and predictive ability of SDMs by comparing models trained with four data types for a heavily exploited pelagic fish, the blue shark (Prionace glauca), in the Northwest Atlantic: two fishery-dependent (conventional mark-recapture tags, fisheries observer records) and two fishery-independent (satellite-linked electronic tags, pop-up archival tags). We found that all four data types can result in robust models, but differences among spatial predictions highlighted the need to consider ecological realism in model selection and interpretation regardless of data type. Differences among models were primarily attributed to biases in how each ... : Please see the README document ("README.md") and the accompanying published article: Braun, C. D., M. C. Arostegui, N. Farchadi, M. Alexander, P. Afonso, A. Allyn, S. J. Bograd, S. Brodie, D. P. Crear, E. F. Culhane, T. H. Curtis, E. L. Hazen, A. Kerney, N. Lezama-Ochoa, K. E. Mills, D. Pugh, N. Queiroz, J. D. Scott, G. B. Skomal, D. W. Sims, S. R. Thorrold, H. Welch, R. Young-Morse, R. Lewison. In press. Building use-inspired species distribution models: using multiple data types to examine and improve model performance. Ecological Applications. Accepted. DOI: < article DOI will be added when it is assigned > ... Dataset Northwest Atlantic morse DataCite |
institution |
Open Polar |
collection |
DataCite |
op_collection_id |
ftdatacite |
language |
English |
topic |
FOS Earth and related environmental sciences species distribution models prediction Ecological forecasting spatial ecology highly migratory species Climate change |
spellingShingle |
FOS Earth and related environmental sciences species distribution models prediction Ecological forecasting spatial ecology highly migratory species Climate change Braun, Camrin Arostegui, Martin Farchadi, Nima Alexander, Michael Afonso, Pedro Allyn, Andrew Bograd, Steven Brodie, Stephanie Crear, Daniel Culhane, Emmett Curtis, Tobey Hazen, Elliott Kerney, Alex Lezama-Ochoa, Nerea Mills, Katherine Pugh, Dylan Queiroz, Nuno Scott, James Skomal, Gregory Sims, David Thorrold, Simon Welch, Heather Young-Morse, Riley Lewison, Rebecca Data and code for: Building use-inspired species distribution models: using multiple data types to examine and improve model performance ... |
topic_facet |
FOS Earth and related environmental sciences species distribution models prediction Ecological forecasting spatial ecology highly migratory species Climate change |
description |
Species distribution models (SDMs) are becoming an important tool for marine conservation and management. Yet while there is an increasing diversity and volume of marine biodiversity data for training SDMs, little practical guidance is available on how to leverage distinct data types to build robust models. We explored the effect of different data types on the fit, performance and predictive ability of SDMs by comparing models trained with four data types for a heavily exploited pelagic fish, the blue shark (Prionace glauca), in the Northwest Atlantic: two fishery-dependent (conventional mark-recapture tags, fisheries observer records) and two fishery-independent (satellite-linked electronic tags, pop-up archival tags). We found that all four data types can result in robust models, but differences among spatial predictions highlighted the need to consider ecological realism in model selection and interpretation regardless of data type. Differences among models were primarily attributed to biases in how each ... : Please see the README document ("README.md") and the accompanying published article: Braun, C. D., M. C. Arostegui, N. Farchadi, M. Alexander, P. Afonso, A. Allyn, S. J. Bograd, S. Brodie, D. P. Crear, E. F. Culhane, T. H. Curtis, E. L. Hazen, A. Kerney, N. Lezama-Ochoa, K. E. Mills, D. Pugh, N. Queiroz, J. D. Scott, G. B. Skomal, D. W. Sims, S. R. Thorrold, H. Welch, R. Young-Morse, R. Lewison. In press. Building use-inspired species distribution models: using multiple data types to examine and improve model performance. Ecological Applications. Accepted. DOI: < article DOI will be added when it is assigned > ... |
format |
Dataset |
author |
Braun, Camrin Arostegui, Martin Farchadi, Nima Alexander, Michael Afonso, Pedro Allyn, Andrew Bograd, Steven Brodie, Stephanie Crear, Daniel Culhane, Emmett Curtis, Tobey Hazen, Elliott Kerney, Alex Lezama-Ochoa, Nerea Mills, Katherine Pugh, Dylan Queiroz, Nuno Scott, James Skomal, Gregory Sims, David Thorrold, Simon Welch, Heather Young-Morse, Riley Lewison, Rebecca |
author_facet |
Braun, Camrin Arostegui, Martin Farchadi, Nima Alexander, Michael Afonso, Pedro Allyn, Andrew Bograd, Steven Brodie, Stephanie Crear, Daniel Culhane, Emmett Curtis, Tobey Hazen, Elliott Kerney, Alex Lezama-Ochoa, Nerea Mills, Katherine Pugh, Dylan Queiroz, Nuno Scott, James Skomal, Gregory Sims, David Thorrold, Simon Welch, Heather Young-Morse, Riley Lewison, Rebecca |
author_sort |
Braun, Camrin |
title |
Data and code for: Building use-inspired species distribution models: using multiple data types to examine and improve model performance ... |
title_short |
Data and code for: Building use-inspired species distribution models: using multiple data types to examine and improve model performance ... |
title_full |
Data and code for: Building use-inspired species distribution models: using multiple data types to examine and improve model performance ... |
title_fullStr |
Data and code for: Building use-inspired species distribution models: using multiple data types to examine and improve model performance ... |
title_full_unstemmed |
Data and code for: Building use-inspired species distribution models: using multiple data types to examine and improve model performance ... |
title_sort |
data and code for: building use-inspired species distribution models: using multiple data types to examine and improve model performance ... |
publisher |
Dryad |
publishDate |
2023 |
url |
https://dx.doi.org/10.5061/dryad.h44j0zpr2 https://datadryad.org/stash/dataset/doi:10.5061/dryad.h44j0zpr2 |
genre |
Northwest Atlantic morse |
genre_facet |
Northwest Atlantic morse |
op_relation |
https://dx.doi.org/10.5281/zenodo.7971532 https://dx.doi.org/10.21203/rs.3.rs-2802316/v1 |
op_rights |
Creative Commons Zero v1.0 Universal https://creativecommons.org/publicdomain/zero/1.0/legalcode cc0-1.0 |
op_doi |
https://doi.org/10.5061/dryad.h44j0zpr210.5281/zenodo.797153210.21203/rs.3.rs-2802316/v1 |
_version_ |
1810466876494446592 |