Kernel Density Analyses of Coral and Sponge Catches from Research Vessel Survey Data (2016)

Kernel Density Analyses of Coral and Sponge Catches from Research Vessel Survey Data (2016) Kernel density estimation (KDE) utilizes spatially explicit data to model the distribution of a variable of interest. It is a simple non-parametric neighbour-based smoothing function that relies on few assumptions about the structure of the observed data. It has been used in ecology to identify hotspots, that is, areas of relatively high biomass/abundance, and in 2010 was used by Fisheries and Oceans Canada to delineate significant concentrations of corals and sponges. The same approach has been used successfully in the Northwest Atlantic Fisheries Organization (NAFO) Regulatory Area. Here, we update the previous analyses with the catch records from up to 5 additional years of trawl survey data from Eastern Canada, including the Gulf of Saint Lawrence. We applied kernel density estimation to create a modelled biomass surface for each of sponges, small and large gorgonian corals, and sea pens, and applied an aerial expansion method to identify significant concentrations of these taxa. We compared our results to those obtained previously and provided maps of significant concentrations as well as point data co-ordinates for catches above the threshold values used to construct the significant area polygons. The borders of the polygons can be refined using knowledge of null catches and species distribution models of species presence/absence and/or biomass. 2024-05-09 Fisheries and Oceans Canada DFO.OESDDataRequest-DSEMDemandededonnes.MPO@dfo-mpo.gc.ca Nature and EnvironmentScience and TechnologyOceans Technical ReportPDF https://publications.gc.ca/collections/collection_2016/mpo-dfo/Fs97-6-3167-eng.pdf Data DictionaryCSV https://api-proxy.edh.azure.cloud.dfo-mpo.gc.ca/catalogue/records/fb1d1c3d-ba6e-4d0d-b629-f4f497edc10f/attachments/KDE2016_DataDictionary3.csv Kernel Density Analyses of Coral and Sponge Catches from Research Vessel Survey Data (2016)FGDB/GDB https://api-proxy.edh.azure.cloud.dfo-mpo.gc.ca/catalogue/records/fb1d1c3d-ba6e-4d0d-b629-f4f497edc10f/attachments/KDEUpdate.gdb.zip Coral and sponge KDE polygons and trawl dataESRI REST https://gisp.dfo-mpo.gc.ca/arcgis/rest/services/FGP/KDE_Analyses_Coral_Sponge_2016_EN/MapServer Coral and sponge KDE polygons and trawl dataESRI REST https://gisp.dfo-mpo.gc.ca/arcgis/rest/services/FGP/KDE_Analyses_Coral_Sponge_2016_FR/MapServer

Kernel density estimation (KDE) utilizes spatially explicit data to model the distribution of a variable of interest. It is a simple non-parametric neighbour-based smoothing function that relies on few assumptions about the structure of the observed data. It has been used in ecology to identify hotspots, that is, areas of relatively high biomass/abundance, and in 2010 was used by Fisheries and Oceans Canada to delineate significant concentrations of corals and sponges. The same approach has been used successfully in the Northwest Atlantic Fisheries Organization (NAFO) Regulatory Area. Here, we update the previous analyses with the catch records from up to 5 additional years of trawl survey data from Eastern Canada, including the Gulf of Saint Lawrence. We applied kernel density estimation to create a modelled biomass surface for each of sponges, small and large gorgonian corals, and sea pens, and applied an aerial expansion method to identify significant concentrations of these taxa. We compared our results to those obtained previously and provided maps of significant concentrations as well as point data co-ordinates for catches above the threshold values used to construct the significant area polygons. The borders of the polygons can be refined using knowledge of null catches and species distribution models of species presence/absence and/or biomass.

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Delivery Point: Bedford Institute of Oceanography, 1 Challenger Drive, P.O. Box 1006

City: Dartmouth

Administrative Area: Nova Scotia

Postal Code: B2Y 4A2

Country: Canada

Electronic Mail Address: DFO.OESDDataRequest-DSEMDemandededonnes.MPO@dfo-mpo.gc.ca

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