globalchange  > 过去全球变化的重建
DOI: 10.1371/journal.pone.0109365
论文题名:
Kernel Density Surface Modelling as a Means to Identify Significant Concentrations of Vulnerable Marine Ecosystem Indicators
作者: Ellen Kenchington; Francisco Javier Murillo; Camille Lirette; Mar Sacau; Mariano Koen-Alonso; Andrew Kenny; Neil Ollerhead; Vonda Wareham; Lindsay Beazley
刊名: PLOS ONE
ISSN: 1932-6203
出版年: 2014
发表日期: 2014-10-7
卷: 9, 期:10
语种: 英语
英文关键词: Corals ; Marine ecosystems ; Biomass (ecology) ; Sponges ; Kernel methods ; Fisheries ; Ecosystems ; Sea water
英文摘要: The United Nations General Assembly Resolution 61/105, concerning sustainable fisheries in the marine ecosystem, calls for the protection of vulnerable marine ecosystems (VME) from destructive fishing practices. Subsequently, the Food and Agriculture Organization (FAO) produced guidelines for identification of VME indicator species/taxa to assist in the implementation of the resolution, but recommended the development of case-specific operational definitions for their application. We applied kernel density estimation (KDE) to research vessel trawl survey data from inside the fishing footprint of the Northwest Atlantic Fisheries Organization (NAFO) Regulatory Area in the high seas of the northwest Atlantic to create biomass density surfaces for four VME indicator taxa: large-sized sponges, sea pens, small and large gorgonian corals. These VME indicator taxa were identified previously by NAFO using the fragility, life history characteristics and structural complexity criteria presented by FAO, along with an evaluation of their recovery trajectories. KDE, a non-parametric neighbour-based smoothing function, has been used previously in ecology to identify hotspots, that is, areas of relatively high biomass/abundance. We present a novel approach of examining relative changes in area under polygons created from encircling successive biomass categories on the KDE surface to identify “significant concentrations” of biomass, which we equate to VMEs. This allows identification of the VMEs from the broader distribution of the species in the study area. We provide independent assessments of the VMEs so identified using underwater images, benthic sampling with other gear types (dredges, cores), and/or published species distribution models of probability of occurrence, as available. For each VME indicator taxon we provide a brief review of their ecological function which will be important in future assessments of significant adverse impact on these habitats here and elsewhere.
URL: http://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0109365&type=printable
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/19455
Appears in Collections:过去全球变化的重建
影响、适应和脆弱性
科学计划与规划
气候变化与战略
全球变化的国际研究计划
气候减缓与适应
气候变化事实与影响

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作者单位: Bedford Institute of Oceanography, Department of Fisheries and Oceans, Dartmouth, Nova Scotia, Canada;Bedford Institute of Oceanography, Department of Fisheries and Oceans, Dartmouth, Nova Scotia, Canada;Departamento de Zooloxía e Antropoloxía Física, Facultade de Bioloxía, Universidade de Santiago de Compostela, Santiago de Compostela, Spain;Bedford Institute of Oceanography, Department of Fisheries and Oceans, Dartmouth, Nova Scotia, Canada;Instituto Español de Oceanografía, Centro Oceanográfico de Vigo, Programa de Pesquerías Lejanas, Vigo, Spain;Northwest Atlantic Fisheries Centre, Department of Fisheries and Oceans, St. John’s, Newfoundland and Labrador, Canada;Centre for Environment, Fisheries and Aquaculture Science, Lowestoft, Suffolk, United Kingdom;Northwest Atlantic Fisheries Centre, Department of Fisheries and Oceans, St. John’s, Newfoundland and Labrador, Canada;Northwest Atlantic Fisheries Centre, Department of Fisheries and Oceans, St. John’s, Newfoundland and Labrador, Canada;Bedford Institute of Oceanography, Department of Fisheries and Oceans, Dartmouth, Nova Scotia, Canada

Recommended Citation:
Ellen Kenchington,Francisco Javier Murillo,Camille Lirette,et al. Kernel Density Surface Modelling as a Means to Identify Significant Concentrations of Vulnerable Marine Ecosystem Indicators[J]. PLOS ONE,2014-01-01,9(10)
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