Modelling abundance hotspots for data-poor Irish Sea rays
•Spatial abundance predictions produced from limited data.•Abundance predictions convert easily to hotspots for MPA candidates.•Method reveals possible refuges and assesses prediction quality.•Boosted regression tree results align with stakeholder knowledge and other studies.•Protecting the most vul...
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Published in | Ecological modelling Vol. 312; pp. 77 - 90 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
Elsevier B.V
01.09.2015
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Subjects | |
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Abstract | •Spatial abundance predictions produced from limited data.•Abundance predictions convert easily to hotspots for MPA candidates.•Method reveals possible refuges and assesses prediction quality.•Boosted regression tree results align with stakeholder knowledge and other studies.•Protecting the most vulnerable species will benefit those less vulnerable.
Skates and rays represent one of the most vulnerable components of fish communities in temperate demersal fisheries such as the Irish Sea. They also tend to be data poor in comparison to commercially exploited teleost fish. Spatial management has been suggested as an important tool to protect these species, but requires an understanding of the abundance distribution, and the relationship the abundance distribution has with the environment at both adult and juvenile life history stages. Here we modelled bottom trawl survey data using delta log-normal boosted regression trees to derive rays’ spatial abundance, and environmental links. The modelling approach allowed the development of high resolution predictive maps of abundance of four skate and ray species targeted by fishing activity: thornback, spotted, cuckoo and blonde rays. The distributions of these species were driven by a general preference for sand and coarser substrates as well as higher salinities, temperatures and currents speeds. Spatial comparisons between abundance distributions and locations of skate and ray commercial landings indicated that the main hotspots for the investigated species are outside of the main commercial fishing areas and overlap with potential MPAs proposed for wider ecosystem protection. The method offers a useful tool for selecting potential MPAs to assist the management and conservation of data-poor species. |
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AbstractList | •Spatial abundance predictions produced from limited data.•Abundance predictions convert easily to hotspots for MPA candidates.•Method reveals possible refuges and assesses prediction quality.•Boosted regression tree results align with stakeholder knowledge and other studies.•Protecting the most vulnerable species will benefit those less vulnerable.
Skates and rays represent one of the most vulnerable components of fish communities in temperate demersal fisheries such as the Irish Sea. They also tend to be data poor in comparison to commercially exploited teleost fish. Spatial management has been suggested as an important tool to protect these species, but requires an understanding of the abundance distribution, and the relationship the abundance distribution has with the environment at both adult and juvenile life history stages. Here we modelled bottom trawl survey data using delta log-normal boosted regression trees to derive rays’ spatial abundance, and environmental links. The modelling approach allowed the development of high resolution predictive maps of abundance of four skate and ray species targeted by fishing activity: thornback, spotted, cuckoo and blonde rays. The distributions of these species were driven by a general preference for sand and coarser substrates as well as higher salinities, temperatures and currents speeds. Spatial comparisons between abundance distributions and locations of skate and ray commercial landings indicated that the main hotspots for the investigated species are outside of the main commercial fishing areas and overlap with potential MPAs proposed for wider ecosystem protection. The method offers a useful tool for selecting potential MPAs to assist the management and conservation of data-poor species. Skates and rays represent one of the most vulnerable components of fish communities in temperate demersal fisheries such as the Irish Sea. They also tend to be data poor in comparison to commercially exploited teleost fish. Spatial management has been suggested as an important tool to protect these species, but requires an understanding of the abundance distribution, and the relationship the abundance distribution has with the environment at both adult and juvenile life history stages. Here we modelled bottom trawl survey data using delta log-normal boosted regression trees on to derive rays' spatial abundance, and environmental links. The modelling approach allowed the development of high resolution predictive maps of abundance of four skate and ray species targeted by fishing activity: thornback, spotted, cuckoo and blonde rays. The distributions of these species were driven by a general preference for sand and coarser substrates as well as higher salinities, temperatures and currents speeds. Spatial comparisons between abundance distributions and locations of skate and ray commercial landings indicated that the main hotspots for the investigated species are outside of the main commercial fishing areas and overlap with potential MPAs proposed for wider ecosystem protection. The method offers a useful tool for selecting potential MPA's to assist the management and conservation of data-poor species. |
Author | Officer, Rick Brophy, Deirdre Reid, David G. Dedman, Simon Clarke, Maurice |
Author_xml | – sequence: 1 givenname: Simon surname: Dedman fullname: Dedman, Simon email: simon.dedman@research.gmit.ie organization: Marine and Freshwater Research Centre, Galway-Mayo Institute of Technology, Galway, Ireland – sequence: 2 givenname: Rick surname: Officer fullname: Officer, Rick email: rick.officer@gmit.ie organization: Marine and Freshwater Research Centre, Galway-Mayo Institute of Technology, Galway, Ireland – sequence: 3 givenname: Deirdre surname: Brophy fullname: Brophy, Deirdre email: deirdre.brophy@gmit.ie organization: Marine and Freshwater Research Centre, Galway-Mayo Institute of Technology, Galway, Ireland – sequence: 4 givenname: Maurice surname: Clarke fullname: Clarke, Maurice email: maurice.clarke@marine.ie organization: Marine Institute, Rinville, Oranmore, Co., Galway, Ireland – sequence: 5 givenname: David G. surname: Reid fullname: Reid, David G. email: david.reid@marine.ie organization: Marine Institute, Rinville, Oranmore, Co., Galway, Ireland |
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CitedBy_id | crossref_primary_10_1371_journal_pone_0188955 crossref_primary_10_1186_s40317_020_00220_0 crossref_primary_10_3389_fmars_2020_00035 crossref_primary_10_1002_mcf2_10120 crossref_primary_10_1093_icesjms_fsw147 crossref_primary_10_3389_feart_2016_00065 crossref_primary_10_1016_j_aaf_2019_12_005 crossref_primary_10_1016_j_agee_2021_107681 crossref_primary_10_1016_j_ecolmodel_2019_108837 crossref_primary_10_1371_journal_pone_0195221 crossref_primary_10_1093_icesjms_fsab162 crossref_primary_10_3389_fmars_2022_851757 crossref_primary_10_1016_j_ocecoaman_2022_106355 crossref_primary_10_3390_fishes2030012 crossref_primary_10_1016_j_ecolmodel_2020_109000 crossref_primary_10_1016_j_pocean_2022_102859 crossref_primary_10_1016_j_ocecoaman_2021_105697 crossref_primary_10_1016_j_ocecoaman_2021_105796 crossref_primary_10_1016_j_fishres_2016_10_011 crossref_primary_10_1016_j_jembe_2018_05_011 crossref_primary_10_1016_j_jenvman_2023_118938 |
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Snippet | •Spatial abundance predictions produced from limited data.•Abundance predictions convert easily to hotspots for MPA candidates.•Method reveals possible refuges... Skates and rays represent one of the most vulnerable components of fish communities in temperate demersal fisheries such as the Irish Sea. They also tend to be... |
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SubjectTerms | Abundance Boosted regression trees Data poor Elasmobranch Fish Fishing Marine Mathematical models Modelling Rays Sand Skates Teleostei |
Title | Modelling abundance hotspots for data-poor Irish Sea rays |
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