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dc.contributor.authorGrech, Alana
dc.contributor.authorSheppard, James
dc.contributor.authorMarsh, Helene
dc.date.accessioned2021-02-02T01:45:36Z
dc.date.available2021-02-02T01:45:36Z
dc.date.issued2011
dc.identifier.issn1932-6203
dc.identifier.doi10.1371/journal.pone.0017993
dc.identifier.urihttp://hdl.handle.net/20.500.12634/848
dc.description.abstractBackground Conservation planning and the design of marine protected areas (MPAs) requires spatially explicit information on the distribution of ecological features. Most species of marine mammals range over large areas and across multiple planning regions. The spatial distributions of marine mammals are difficult to predict using habitat modelling at ecological scales because of insufficient understanding of their habitat needs, however, relevant information may be available from surveys conducted to inform mandatory stock assessments. Methodology and Results We use a 20-year time series of systematic aerial surveys of dugong (Dugong dugong) abundance to create spatially-explicit models of dugong distribution and relative density at the scale of the coastal waters of northeast Australia (∼136,000 km2). We interpolated the corrected data at the scale of 2 km * 2 km planning units using geostatistics. Planning units were classified as low, medium, high and very high dugong density on the basis of the relative density of dugongs estimated from the models and a frequency analysis. Torres Strait was identified as the most significant dugong habitat in northeast Australia and the most globally significant habitat known for any member of the Order Sirenia. The models are used by local, State and Federal agencies to inform management decisions related to the Indigenous harvest of dugongs, gill-net fisheries and Australia's National Representative System of Marine Protected Areas. Conclusion/Significance In this paper we demonstrate that spatially-explicit population models add value to data collected for stock assessments, provide a robust alternative to predictive habitat distribution models, and inform species conservation at multiple scales.
dc.description.sponsorship
dc.language.isoen
dc.relation.urlhttp://dx.plos.org/10.1371/journal.pone.0017993
dc.rightsCopyright: © 2011 Grech et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
dc.rights.urihttps://creativecommons.org/licenses/by/3.0/us/
dc.subjectMARINE MAMMALS
dc.subjectMARINE BIOLOGY
dc.subjectOCEANS
dc.subjectHABITATS
dc.subjectECOSYSTEMS
dc.subjectEXPERIMENTAL METHODS
dc.subjectRESEARCH
dc.subjectDUGONGS
dc.subjectAUSTRALIAN REGION
dc.subjectPOPULATIONS
dc.subjectDISTRIBUTION
dc.subjectBIOGEOGRAPHY
dc.subjectHABITAT CONSERVATION
dc.subjectWILDLIFE CONSERVATION
dc.subjectANIMAL-HUMAN RELATIONSHIPS
dc.subjectENVIRONMENTAL POLICIES
dc.titleInforming species conservation at multiple scales using data collected for marine mammal stock assessments
dc.typeArticle
dc.source.journaltitlePLoS ONE
dc.source.volume6
dc.source.issue3
dc.source.beginpagee17993
refterms.dateFOA2021-02-02T02:18:49Z
html.description.abstractBackground Conservation planning and the design of marine protected areas (MPAs) requires spatially explicit information on the distribution of ecological features. Most species of marine mammals range over large areas and across multiple planning regions. The spatial distributions of marine mammals are difficult to predict using habitat modelling at ecological scales because of insufficient understanding of their habitat needs, however, relevant information may be available from surveys conducted to inform mandatory stock assessments. Methodology and Results We use a 20-year time series of systematic aerial surveys of dugong (Dugong dugong) abundance to create spatially-explicit models of dugong distribution and relative density at the scale of the coastal waters of northeast Australia (∼136,000 km2). We interpolated the corrected data at the scale of 2 km * 2 km planning units using geostatistics. Planning units were classified as low, medium, high and very high dugong density on the basis of the relative density of dugongs estimated from the models and a frequency analysis. Torres Strait was identified as the most significant dugong habitat in northeast Australia and the most globally significant habitat known for any member of the Order Sirenia. The models are used by local, State and Federal agencies to inform management decisions related to the Indigenous harvest of dugongs, gill-net fisheries and Australia's National Representative System of Marine Protected Areas. Conclusion/Significance In this paper we demonstrate that spatially-explicit population models add value to data collected for stock assessments, provide a robust alternative to predictive habitat distribution models, and inform species conservation at multiple scales.


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Copyright: © 2011 Grech et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Except where otherwise noted, this item's license is described as Copyright: © 2011 Grech et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.