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008161201s2016    oncbd   o    f000 0 eng d
040 |aCaOODSP|beng
041 |aeng|bfre
043 |an-cn---
0861 |aFs70-5/2016-093E-PDF
24500|aDelineation of coral and sponge significant benthic areas in eastern Canada using kernel density analyses and species distribution models |h[electronic resource] / |cE. Kenchington ... [et al.].
2461 |iTitle at head of French abstract: |aDélimitation des zones benthiques importantes de coraux et d’éponges dans l’est du Canada à l’aide des analyses des noyaux de densité et des modèles de répartition des espèces
260 |aOttawa : |bFisheries and Oceans Canada, |cc2016.
300 |avi, 178 p. : |bcol. maps, graphs, figs.
4901 |aCanadian Science Advisory Secretariat research document, |x1919-5044 ; |v2016/093, Maritimes, Newfoundland and Labrador, Gulf, Quebec, and Central and Arctic Regions
500 |aCover title.
500 |a“November 2016.”
504 |aIncludes bibliographical references (p. 123-126).
520 |a"Significant Benthic Areas are defined in DFO’s Ecological Risk Assessment Framework (ERAF) as “significant areas of cold-water corals and sponge dominated communities”, where significance is determined “through guidance provided by DFO-lead processes based on current knowledge of such species, communities and ecosystems”. Here we provide maps of the location of significant concentrations of corals and sponges on the east coast of Canada produced through quantitative analyses of research vessel trawl survey data, supplemented with other data sources where available. We have conducted those analyses following a bio-regionalization approach in order to facilitate modelling of similar species, given that many of the multispecies surveys do not record coral and sponge catch at species level resolution. The taxa analyzed are sponges (Porifera), large and small gorgonian corals (Alcyonacea), and sea pens (Pennatulacea). We applied kernel density estimation (KDE) to create a modelled biomass surface for each of those taxa, and applied an aerial expansion method to identify significant concentrations, following an approach first applied in 2010 to this region. We compared our results to those obtained previously. KDE uses only geo-referenced biomass data to identify “hot spots”. The borders of the areas so identified can be refined using knowledge of null catches and species distribution models that predict species presence-absence and/or biomass, both incorporating environmental data. We present such predictive models produced using a random forest machine-learning technique, and in one region compare the biomass random forest models for sea pens to those produced by generalized additive models (GAMs). Together, these distribution maps can be used to identify significant concentrations of corals and sponges in eastern Canada; an essential first step in the identification of Sensitive Benthic Areas“--Abstract, p. v.
546 |aIncludes abstract in French.
69207|2gccst|aAquaculture
69207|2gccst|aAquatic plants
69207|2gccst|aGeographic data
7001 |aKenchington, E., |d1959-
7101 |aCanada. |bDepartment of Fisheries and Oceans.
7101 |aCanada. |bEcosystems and Oceans Science.
7102 |aCanadian Science Advisory Secretariat.
7102 |aMaurice Lamontagne Institute.
830#0|aResearch document (Canadian Science Advisory Secretariat)|x1919-5044 ; |v2016/093, Maritimes, Newfoundland and Labrador, Gulf, Quebec, and Central and Arctic Regions|w(CaOODSP)9.507396
85640|qPDF|s13.44 MB|uhttps://publications.gc.ca/collections/collection_2016/mpo-dfo/Fs70-5-2016-093-eng.pdf