Advanced Spatial Modeling to Inform Management of Data-Poor Juvenile and Adult Female Rays

Chronic overfishing has depleted numerous elasmobranch stocks in the North East Atlantic, but addressing this issue has been hampered by management complications and lacking data. Spatial management approaches have thus been advocated. This work presents a novel application and further development o...

Full description

Bibliographic Details
Published in:Fishes
Main Authors: Simon Dedman, Rick Officer, Deirdre Brophy, Maurice Clarke, David G. Reid
Format: Article in Journal/Newspaper
Language:English
Published: MDPI AG 2017
Subjects:
BRT
MPA
ray
Online Access:https://doi.org/10.3390/fishes2030012
https://doaj.org/article/88fb877dd1854fbb837ca79721f47436
id ftdoajarticles:oai:doaj.org/article:88fb877dd1854fbb837ca79721f47436
record_format openpolar
spelling ftdoajarticles:oai:doaj.org/article:88fb877dd1854fbb837ca79721f47436 2023-05-15T17:38:27+02:00 Advanced Spatial Modeling to Inform Management of Data-Poor Juvenile and Adult Female Rays Simon Dedman Rick Officer Deirdre Brophy Maurice Clarke David G. Reid 2017-08-01T00:00:00Z https://doi.org/10.3390/fishes2030012 https://doaj.org/article/88fb877dd1854fbb837ca79721f47436 EN eng MDPI AG https://www.mdpi.com/2410-3888/2/3/12 https://doaj.org/toc/2410-3888 2410-3888 doi:10.3390/fishes2030012 https://doaj.org/article/88fb877dd1854fbb837ca79721f47436 Fishes, Vol 2, Iss 3, p 12 (2017) boosted regression trees BRT elasmobranch marine protected area MPA nursery area spawning ground ray Biology (General) QH301-705.5 Genetics QH426-470 article 2017 ftdoajarticles https://doi.org/10.3390/fishes2030012 2022-12-31T03:05:58Z Chronic overfishing has depleted numerous elasmobranch stocks in the North East Atlantic, but addressing this issue has been hampered by management complications and lacking data. Spatial management approaches have thus been advocated. This work presents a novel application and further development of an advanced spatial modeling technique to identify candidate nursery grounds and spawning areas for conservation, by subsetting already limited data. Boosted Regression Tree models are used to predict abundance of juvenile and mature female cuckoo (Leucoraja naevus), thornback (Raja clavata), blonde (Raja brachyura), and spotted (Raja montagui) rays in the Irish Sea using fish survey data and data describing fishing pressure, predation and environmental variables. Model-predicted spatial abundance maps of these subsets reveal distinct nuances in species distributions with greater predictive power than maps of the whole stock. These resulting maps are then integrated into a single easily understood map using a novel approach, standardizing and facilitating the spatial management of data-limited fish stocks. Article in Journal/Newspaper North East Atlantic Directory of Open Access Journals: DOAJ Articles Fishes 2 3 12
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic boosted regression trees
BRT
elasmobranch
marine protected area
MPA
nursery area
spawning ground
ray
Biology (General)
QH301-705.5
Genetics
QH426-470
spellingShingle boosted regression trees
BRT
elasmobranch
marine protected area
MPA
nursery area
spawning ground
ray
Biology (General)
QH301-705.5
Genetics
QH426-470
Simon Dedman
Rick Officer
Deirdre Brophy
Maurice Clarke
David G. Reid
Advanced Spatial Modeling to Inform Management of Data-Poor Juvenile and Adult Female Rays
topic_facet boosted regression trees
BRT
elasmobranch
marine protected area
MPA
nursery area
spawning ground
ray
Biology (General)
QH301-705.5
Genetics
QH426-470
description Chronic overfishing has depleted numerous elasmobranch stocks in the North East Atlantic, but addressing this issue has been hampered by management complications and lacking data. Spatial management approaches have thus been advocated. This work presents a novel application and further development of an advanced spatial modeling technique to identify candidate nursery grounds and spawning areas for conservation, by subsetting already limited data. Boosted Regression Tree models are used to predict abundance of juvenile and mature female cuckoo (Leucoraja naevus), thornback (Raja clavata), blonde (Raja brachyura), and spotted (Raja montagui) rays in the Irish Sea using fish survey data and data describing fishing pressure, predation and environmental variables. Model-predicted spatial abundance maps of these subsets reveal distinct nuances in species distributions with greater predictive power than maps of the whole stock. These resulting maps are then integrated into a single easily understood map using a novel approach, standardizing and facilitating the spatial management of data-limited fish stocks.
format Article in Journal/Newspaper
author Simon Dedman
Rick Officer
Deirdre Brophy
Maurice Clarke
David G. Reid
author_facet Simon Dedman
Rick Officer
Deirdre Brophy
Maurice Clarke
David G. Reid
author_sort Simon Dedman
title Advanced Spatial Modeling to Inform Management of Data-Poor Juvenile and Adult Female Rays
title_short Advanced Spatial Modeling to Inform Management of Data-Poor Juvenile and Adult Female Rays
title_full Advanced Spatial Modeling to Inform Management of Data-Poor Juvenile and Adult Female Rays
title_fullStr Advanced Spatial Modeling to Inform Management of Data-Poor Juvenile and Adult Female Rays
title_full_unstemmed Advanced Spatial Modeling to Inform Management of Data-Poor Juvenile and Adult Female Rays
title_sort advanced spatial modeling to inform management of data-poor juvenile and adult female rays
publisher MDPI AG
publishDate 2017
url https://doi.org/10.3390/fishes2030012
https://doaj.org/article/88fb877dd1854fbb837ca79721f47436
genre North East Atlantic
genre_facet North East Atlantic
op_source Fishes, Vol 2, Iss 3, p 12 (2017)
op_relation https://www.mdpi.com/2410-3888/2/3/12
https://doaj.org/toc/2410-3888
2410-3888
doi:10.3390/fishes2030012
https://doaj.org/article/88fb877dd1854fbb837ca79721f47436
op_doi https://doi.org/10.3390/fishes2030012
container_title Fishes
container_volume 2
container_issue 3
container_start_page 12
_version_ 1766138902933929984