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Layer: MA Grandes gorgones (ID: 3)

Name: MA Grandes gorgones

Display Field: Latitude

Type: Feature Layer

Geometry Type: esriGeometryPoint

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: c91be5e730844fc1b0e82d684b134952

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

Default Visibility: true

MaxRecordCount: 2000

Supported Query Formats: JSON, geoJSON, PBF

Min Scale: 0

Max Scale: 0

Supports Advanced Queries: true

Supports Statistics: true

Has Labels: false

Can Modify Layer: true

Can Scale Symbols: false

Use Standardized Queries: true

Supports Datum Transformation: true

Extent:
Drawing Info: Advanced Query Capabilities:
HasZ: false

HasM: false

Has Attachments: false

HTML Popup Type: esriServerHTMLPopupTypeAsHTMLText

Type ID Field: null

Fields:
Supported Operations:   Query   Query Attachments   Query Analytic   Generate Renderer   Return Updates

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