Applying distribution model projections for an uncertain future:The case of the Pacific oyster in UK waters

The inherent complexity of the environment is such that attempts to model it must operate under simplifications and assumptions. Considering predictions from alternative models, with a range of assumptions and data requirements, therefore provides a more robust approach. The intractability and uncer...

Full description

Bibliographic Details
Published in:Aquatic Conservation: Marine and Freshwater Ecosystems
Main Authors: Jones, Miranda, Dye, S.R., Pinnegar, J.K., Warren, Rachel, Cheung, W.W.L.
Format: Article in Journal/Newspaper
Language:unknown
Published: 2013
Subjects:
Online Access:https://ueaeprints.uea.ac.uk/id/eprint/47510/
https://doi.org/10.1002/aqc.2364
id ftuniveastangl:oai:ueaeprints.uea.ac.uk:47510
record_format openpolar
spelling ftuniveastangl:oai:ueaeprints.uea.ac.uk:47510 2023-05-15T15:59:06+02:00 Applying distribution model projections for an uncertain future:The case of the Pacific oyster in UK waters Jones, Miranda Dye, S.R. Pinnegar, J.K. Warren, Rachel Cheung, W.W.L. 2013-10-01 https://ueaeprints.uea.ac.uk/id/eprint/47510/ https://doi.org/10.1002/aqc.2364 unknown Jones, Miranda, Dye, S.R., Pinnegar, J.K., Warren, Rachel and Cheung, W.W.L. (2013) Applying distribution model projections for an uncertain future:The case of the Pacific oyster in UK waters. Aquatic Conservation: Marine and Freshwater Ecosystems, 23 (5). pp. 710-722. ISSN 1052-7613 doi:10.1002/aqc.2364 Article PeerReviewed 2013 ftuniveastangl https://doi.org/10.1002/aqc.2364 2023-01-30T21:37:56Z The inherent complexity of the environment is such that attempts to model it must operate under simplifications and assumptions. Considering predictions from alternative models, with a range of assumptions and data requirements, therefore provides a more robust approach. The intractability and uncertainty resulting from a suite of predictions may hinder the application of science in policy, where a single prediction with little ambiguity or uncertainty would be most desirable. Few studies modelling species' distributions attempt to present multi-model outputs in a format most useful to the non-modelling community, and none of these have done so for the marine environment. The problem of uncertainty is particularly prevalent in predicting the distribution of invasive alien species under climate change. As invasive alien species are one of the main drivers of biodiversity loss and may incur significant economic costs, the benefit of applying predictions to highlight areas of possible establishment and inform policy and management may be large. An ensemble prediction is used to assess the distribution of suitable habitat for the Pacific oyster, Crassostrea gigas, in UK waters both currently and in the future. The ensemble incorporates predictions from three species distribution models, using data from two global climate models. A method is developed highlighting the agreement of the ensemble, further applying threshold values to retain information from constituent predictions in the final map of agreement. Ensemble predictions made here suggest that Pacific oyster will experience an opening of suitable habitat in northern UK waters, reaching the Faroe Islands and the eastern Norwegian Sea by 2050. Habitat suitability will increase with warming temperatures in the English Channel and Central North Sea for this species. The approaches applied here can be incorporated into risk assessment frameworks for invasive species, as stipulated in the Convention on Biological Diversity. Article in Journal/Newspaper Crassostrea gigas Faroe Islands Norwegian Sea Pacific oyster University of East Anglia: UEA Digital Repository Faroe Islands Norwegian Sea Pacific Aquatic Conservation: Marine and Freshwater Ecosystems n/a n/a
institution Open Polar
collection University of East Anglia: UEA Digital Repository
op_collection_id ftuniveastangl
language unknown
description The inherent complexity of the environment is such that attempts to model it must operate under simplifications and assumptions. Considering predictions from alternative models, with a range of assumptions and data requirements, therefore provides a more robust approach. The intractability and uncertainty resulting from a suite of predictions may hinder the application of science in policy, where a single prediction with little ambiguity or uncertainty would be most desirable. Few studies modelling species' distributions attempt to present multi-model outputs in a format most useful to the non-modelling community, and none of these have done so for the marine environment. The problem of uncertainty is particularly prevalent in predicting the distribution of invasive alien species under climate change. As invasive alien species are one of the main drivers of biodiversity loss and may incur significant economic costs, the benefit of applying predictions to highlight areas of possible establishment and inform policy and management may be large. An ensemble prediction is used to assess the distribution of suitable habitat for the Pacific oyster, Crassostrea gigas, in UK waters both currently and in the future. The ensemble incorporates predictions from three species distribution models, using data from two global climate models. A method is developed highlighting the agreement of the ensemble, further applying threshold values to retain information from constituent predictions in the final map of agreement. Ensemble predictions made here suggest that Pacific oyster will experience an opening of suitable habitat in northern UK waters, reaching the Faroe Islands and the eastern Norwegian Sea by 2050. Habitat suitability will increase with warming temperatures in the English Channel and Central North Sea for this species. The approaches applied here can be incorporated into risk assessment frameworks for invasive species, as stipulated in the Convention on Biological Diversity.
format Article in Journal/Newspaper
author Jones, Miranda
Dye, S.R.
Pinnegar, J.K.
Warren, Rachel
Cheung, W.W.L.
spellingShingle Jones, Miranda
Dye, S.R.
Pinnegar, J.K.
Warren, Rachel
Cheung, W.W.L.
Applying distribution model projections for an uncertain future:The case of the Pacific oyster in UK waters
author_facet Jones, Miranda
Dye, S.R.
Pinnegar, J.K.
Warren, Rachel
Cheung, W.W.L.
author_sort Jones, Miranda
title Applying distribution model projections for an uncertain future:The case of the Pacific oyster in UK waters
title_short Applying distribution model projections for an uncertain future:The case of the Pacific oyster in UK waters
title_full Applying distribution model projections for an uncertain future:The case of the Pacific oyster in UK waters
title_fullStr Applying distribution model projections for an uncertain future:The case of the Pacific oyster in UK waters
title_full_unstemmed Applying distribution model projections for an uncertain future:The case of the Pacific oyster in UK waters
title_sort applying distribution model projections for an uncertain future:the case of the pacific oyster in uk waters
publishDate 2013
url https://ueaeprints.uea.ac.uk/id/eprint/47510/
https://doi.org/10.1002/aqc.2364
geographic Faroe Islands
Norwegian Sea
Pacific
geographic_facet Faroe Islands
Norwegian Sea
Pacific
genre Crassostrea gigas
Faroe Islands
Norwegian Sea
Pacific oyster
genre_facet Crassostrea gigas
Faroe Islands
Norwegian Sea
Pacific oyster
op_relation Jones, Miranda, Dye, S.R., Pinnegar, J.K., Warren, Rachel and Cheung, W.W.L. (2013) Applying distribution model projections for an uncertain future:The case of the Pacific oyster in UK waters. Aquatic Conservation: Marine and Freshwater Ecosystems, 23 (5). pp. 710-722. ISSN 1052-7613
doi:10.1002/aqc.2364
op_doi https://doi.org/10.1002/aqc.2364
container_title Aquatic Conservation: Marine and Freshwater Ecosystems
container_start_page n/a
op_container_end_page n/a
_version_ 1766394885777129472