Name: MA Large Gorgonians

Display Field: Latitude

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Description: <DIV STYLE="text-align:Left;"><P><SPAN>Species distribution modelling using a random forest (RF) machine learning approach was used to predict the probability of occurrence and biomass of sponges, sea pens, large and small gorgonians and Vazella pourtalesi in the Maritimes Region. A suite of 66 environmental predictor variables from different data sources were used. Models utilized catch records from the DFO multispecies trawl and scallop stock assessment surveys and in situ benthic imagery observations. Most presence-absence models had good predictive capacity with cross-validated Area Under the Receiver Operating Characteristic Curve (AUC) values ranging from 0.760 to 0.949. These models were used in a Canadian Science Advisory Secretariat (CSAS) process to delineate significant areas of cold-water corals and sponges in the Maritimes Region.</SPAN></P><P><SPAN /></P></DIV>

Service Item Id: 76cdc1f191f14c268583cac76ff8e300

Copyright Text: Fisheries and Oceans Canada, Bedford Institute of Oceanography, P.O. Box 1006, Dartmouth, NS, Canada B2Y 4A2

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