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dc.contributor.authorHowell, Kerry L.
dc.contributor.authorHolt, Rebecca E.
dc.contributor.authorEndrino, Ines Pulido
dc.contributor.authorStewart, Heather
dc.date.accessioned2018-12-05T22:06:06Z
dc.date.available2018-12-05T22:06:06Z
dc.date.issued2011
dc.identifier.issn0006-3207
dc.identifier.doi10.1016/j.biocon.2011.07.025
dc.identifier.urihttp://hdl.handle.net/10072/173262
dc.description.abstractInternationally there is political momentum to establish networks of marine protected areas for the conservation of threatened species and habitats. Practical implementation of such networks requires an understanding of the distribution of these species and habitats. Predictive modelling provides a method by which continuous distribution maps can be produced from limited sample data. This method is particularly useful in the deep sea where a number of biological communities have been identified as vulnerable ‘habitats’, including Lophelia pertusa reefs. Recent modelling efforts have focused on predicting the distribution of this species. However the species is widely distributed where as reef habitat is not. This study uses Maxent predictive modelling to investigate whether the distribution of the species acts as a suitable proxy for the reef habitat. Models of both species and habitat distribution across Hatton Bank and George Bligh Bank are constructed using multibeam bathymetry, interpreted substrate and geomorphology layers, and derived layers of bathymetric position index (BPI), rugosity, slope and aspect. Species and reef presence records were obtained from video observations. For both models performance is fair to excellent assessed using AUC and additional threshold dependant metrics. 7.17% of the study area is predicted as highly suitable for the species presence while only 0.56% is suitable for reef presence, using the sensitivity–specificity sum maximisation approach to determine the appropriate threshold. Substrate is the most important variable in the both models followed by geomorphology in the RD model and fine scale BPI in the SD model. The difference in the distributions of reef and species suggest that mapping efforts should focus on the habitat rather than the species at fine (100 m) scales.
dc.description.peerreviewedYes
dc.languageEnglish
dc.publisherElsevier
dc.relation.ispartofpagefrom2656
dc.relation.ispartofpageto2665
dc.relation.ispartofissue11
dc.relation.ispartofjournalBiological Conservation
dc.relation.ispartofvolume144
dc.subject.fieldofresearchEcology not elsewhere classified
dc.subject.fieldofresearchEnvironmental Sciences
dc.subject.fieldofresearchBiological Sciences
dc.subject.fieldofresearchAgricultural and Veterinary Sciences
dc.subject.fieldofresearchcode060299
dc.subject.fieldofresearchcode05
dc.subject.fieldofresearchcode06
dc.subject.fieldofresearchcode07
dc.titleWhen the species is also a habitat: Comparing the predictively modelled distributions of Lophelia pertusa and the reef habitat it forms
dc.typeJournal article
dc.type.descriptionC1 - Articles
dc.type.codeC - Journal Articles
dcterms.licensehttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.description.versionPost-print
gro.rights.copyright© 2011 Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Licence which permits unrestricted, non-commercial use, distribution and reproduction in any medium, providing that the work is properly cited.
gro.hasfulltextFull Text
gro.griffith.authorHolt, Rebecca E.


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