Hosted/MaxentModeledSeagrassExtent (FeatureServer)

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Service Description: Existing seagrass distribution datasets still suffer from known spatial gaps in knowledge, for instance, the north east Pacific, the coastal area of Scandinavia and the Northern African coast, are at best characterised by point occurrence records, whilst extensive meadows are known to occur. Point occurrence datasets cannot be used in area surface calculations as they do not indicate the spatial extent of seagrass beds. In the absence of in-situ mapping of seagrass extent at a global scale, existing occurrence data can be used in species distribution models to map the biome in unsurveyed areas, and indeed some regional attempts have been made. This polygon layer is a result of a MaxEnt model of the global distribution of seagrass using all available point records.Creation methodology:Species occurrence records were extracted from the Global Biodiversity Information Facility (GBIF), United Nations Environment Programme-World Conservation Monitoring Centre (UNEP-WCMC) Ocean Data Viewer and Ocean biogeographic information system (OBIS). After data cleaning, 39045 occurrence records (combining all seagrass species) were used in species distribution model. 13 environmental variables from Global Marine Environment Datasets (GMED) were interpolated into 30 arc seconds resolution (1 km at the equator) and used in species distribution models. MaxEnt models were generated using 10 cross-validate replicate runs with parameters: convergence threshold = 10-5, regularization multiplier = 1, maximum number of background points = 10,000 and maximum iterations = 1000. The methodology is fully described in the paper Jayathilake and Costello (2018).

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Has Versioned Data: false

MaxRecordCount: 2000

Supported Query Formats: JSON

Supports Query Data Elements: true

Layers:

MaxentModeledSeagrassExtent (0)

Description: Existing seagrass distribution datasets still suffer from known spatial gaps in knowledge, for instance, the north east Pacific, the coastal area of Scandinavia and the Northern African coast, are at best characterised by point occurrence records, whilst extensive meadows are known to occur. Point occurrence datasets cannot be used in area surface calculations as they do not indicate the spatial extent of seagrass beds. In the absence of in-situ mapping of seagrass extent at a global scale, existing occurrence data can be used in species distribution models to map the biome in unsurveyed areas, and indeed some regional attempts have been made. This polygon layer is a result of a MaxEnt model of the global distribution of seagrass using all available point records.Creation methodology:Species occurrence records were extracted from the Global Biodiversity Information Facility (GBIF), United Nations Environment Programme-World Conservation Monitoring Centre (UNEP-WCMC) Ocean Data Viewer and Ocean biogeographic information system (OBIS). After data cleaning, 39045 occurrence records (combining all seagrass species) were used in species distribution model. 13 environmental variables from Global Marine Environment Datasets (GMED) were interpolated into 30 arc seconds resolution (1 km at the equator) and used in species distribution models. MaxEnt models were generated using 10 cross-validate replicate runs with parameters: convergence threshold = 10-5, regularization multiplier = 1, maximum number of background points = 10,000 and maximum iterations = 1000. The methodology is fully described in the paper Jayathilake and Costello (2018).

Copyright Text: Jayathilake D.R.M., Costello M.J. 2018. A modelled global distribution of the seagrass biome. Biological Conservation. https://doi.org/10.1016/j.biocon.2018.07.009

Spatial Reference: 54034 (54034)

Initial Extent:

Full Extent:

Units: esriMeters

Document Info:

Enable Z Defaults: false

Supports ApplyEdits With Global Ids: false

Support True Curves : true

Only Allow TrueCurve Updates By TrueCurveClients : false

Supports Return Service Edits Option : true

Supports Dynamic Layers: false

Child Resources: Info Query Data Elements Relationships SharedTemplates

Supported Operations: Query Query Contingent Values QueryDomains Append Extract Changes Get Estimates