Evidence map›Paper›PMID 25289667›Full record

ArticlePloS one2014

Kernel density surface modelling as a means to identify significant concentrations of vulnerable marine ecosystem indicators.

Ellen Kenchington, Francisco Javier Murillo, Camille Lirette, Mar Sacau, Mariano Koen-Alonso, Andrew Kenny, Neil Ollerhead, Vonda Wareham, Lindsay Beazley

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
6.2field-weighted citation impact, top 4% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 76 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors at 4 institutions in 3 countries.

Ellen KenchingtonBedford Institute of Oceanography, Department of Fisheries and Oceans, Dartmouth, Nova Scotia, Canada.
Francisco Javier MurilloBedford 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.
Camille LiretteBedford Institute of Oceanography, Department of Fisheries and Oceans, Dartmouth, Nova Scotia, Canada.
Mar SacauInstituto Español de Oceanografía, Centro Oceanográfico de Vigo, Programa de Pesquerías Lejanas, Vigo, Spain.
Mariano Koen-AlonsoNorthwest Atlantic Fisheries Centre, Department of Fisheries and Oceans, St. John's, Newfoundland and Labrador, Canada.
Andrew KennyCentre for Environment, Fisheries and Aquaculture Science, Lowestoft, Suffolk, United Kingdom.
Neil OllerheadNorthwest Atlantic Fisheries Centre, Department of Fisheries and Oceans, St. John's, Newfoundland and Labrador, Canada.
Vonda WarehamNorthwest Atlantic Fisheries Centre, Department of Fisheries and Oceans, St. John's, Newfoundland and Labrador, Canada.
Lindsay BeazleyBedford Institute of Oceanography, Department of Fisheries and Oceans, Dartmouth, Nova Scotia, Canada.
Fisheries and Oceans Canada · CABedford Institute of Oceanography · CACentre for Environment, Fisheries and Aquaculture Science · GBInstituto Español de Oceanografía · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

Aquatic OrganismsEcosystemModels, TheoreticalAnimalsAtlantic OceanCanadaConservation of Natural ResourcesFisheries

Identifiers

PMID25289667
PMCPMC4188592
OpenAlexW2090073965

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.