{ "currentVersion": 11.1, "cimVersion": "3.1.0", "serviceDescription": "Biodiversity hotspots are a method to identify those regions of the world where attention is needed to address biodiversity loss and to guide investments in conservation. The idea was first developed by Norman Myers in 1988 to identify tropical forest \u2018hotspots\u2019 characterized both by exceptional levels of plant endemism and serious habitat loss 1, which he then expanded to a more global scope 2. Conservation International adopted Myers\u2019 hotspots as its institutional blueprint in 1989, and in 1999, the organization undertook an extensive global review which introduced quantitative thresholds for the designation of biodiversity hotspots. 3 A reworking of the hotspots analysis in 2004 resulted in the system in place today. 4 Currently, 35 biodiversity hotspots have been identified, most of which occur in tropical forests. They represent just 2.3% of Earth\u2019s land surface, but between them they contain around 50% of the world\u2019s endemic plant species and 42% of all terrestrial vertebrates. Overall, Hotspots have lost around 86% of their original habitat and additionally are considered to be significantly threatened by extinctions induced by climate change.\n\nSpatial data for the five highest biodiversity wilderness areas as defined by Conservation International. These five areas are: Amazonia, Congo Forests, Miombo-Mopane Woodlands and Savannas, North American Deserts and New Guinea.", "mapName": "Layers", "description": "", "copyrightText": "UNEP-WCMC | Conservation International ", "supportsDynamicLayers": true, "layers": [ { "id": 0, "name": "Coral Reefs", "parentLayerId": -1, "defaultVisibility": true, "subLayerIds": null, "minScale": 0, "maxScale": 0, "type": "Feature Layer", "geometryType": "esriGeometryPolygon", "supportsDynamicLegends": true }, { "id": 1, "name": "Mangroves", "parentLayerId": -1, "defaultVisibility": true, "subLayerIds": null, "minScale": 0, "maxScale": 0, "type": "Feature Layer", "geometryType": "esriGeometryPolygon", "supportsDynamicLegends": true }, { "id": 2, "name": "Biodiversity Hotspots", "parentLayerId": -1, "defaultVisibility": true, "subLayerIds": null, "minScale": 0, "maxScale": 0, "type": "Feature Layer", "geometryType": "esriGeometryPolygon", "supportsDynamicLegends": true }, { "id": 3, "name": "High Biodiversity Areas", "parentLayerId": -1, "defaultVisibility": true, "subLayerIds": null, "minScale": 0, "maxScale": 0, "type": "Feature Layer", "geometryType": "esriGeometryPolygon", "supportsDynamicLegends": true } ], "tables": [], "spatialReference": { "wkid": 102100, "latestWkid": 3857, "xyTolerance": 0.001, "zTolerance": 0.001, "mTolerance": 0.001, "falseX": -20037700, "falseY": -30241100, "xyUnits": 1.4892314192838538E8, "falseZ": -100000, "zUnits": 10000, "falseM": -100000, "mUnits": 10000 }, "singleFusedMapCache": false, "initialExtent": { "xmin": -2277008.5069662947, "ymin": -4292943.460904373, "xmax": 6570686.2340913545, "ymax": 3612569.683564527, "spatialReference": { "wkid": 102100, "latestWkid": 3857, "xyTolerance": 0.001, "zTolerance": 0.001, "mTolerance": 0.001, "falseX": -20037700, "falseY": -30241100, "xyUnits": 1.4892314192838538E8, "falseZ": -100000, "zUnits": 10000, "falseM": -100000, "mUnits": 10000 } }, "fullExtent": { "xmin": -9604700.07827932, "ymin": -4638097.361729998, "xmax": 1.310069390727932E7, "ymax": 6273058.685930006, "spatialReference": { "wkid": 102100, "latestWkid": 3857, "xyTolerance": 0.001, "zTolerance": 0.001, "mTolerance": 0.001, "falseX": -20037700, "falseY": -30241100, "xyUnits": 1.4892314192838538E8, "falseZ": -100000, "zUnits": 10000, "falseM": -100000, "mUnits": 10000 } }, "datesInUnknownTimezone": false, "minScale": 0, "maxScale": 0, "units": "esriMeters", "supportedImageFormatTypes": "PNG32,PNG24,PNG,JPG,DIB,TIFF,EMF,PS,PDF,GIF,SVG,SVGZ,BMP", "documentInfo": { "Title": "", "Author": "", "Comments": "Biodiversity hotspots are a method to identify those regions of the world where attention is needed to address biodiversity loss and to guide investments in conservation. The idea was first developed by Norman Myers in 1988 to identify tropical forest \u2018hotspots\u2019 characterized both by exceptional levels of plant endemism and serious habitat loss 1, which he then expanded to a more global scope 2. Conservation International adopted Myers\u2019 hotspots as its institutional blueprint in 1989, and in 1999, the organization undertook an extensive global review which introduced quantitative thresholds for the designation of biodiversity hotspots. 3 A reworking of the hotspots analysis in 2004 resulted in the system in place today. 4 Currently, 35 biodiversity hotspots have been identified, most of which occur in tropical forests. They represent just 2.3% of Earth\u2019s land surface, but between them they contain around 50% of the world\u2019s endemic plant species and 42% of all terrestrial vertebrates. Overall, Hotspots have lost around 86% of their original habitat and additionally are considered to be significantly threatened by extinctions induced by climate change.\n\nSpatial data for the five highest biodiversity wilderness areas as defined by Conservation International. These five areas are: Amazonia, Congo Forests, Miombo-Mopane Woodlands and Savannas, North American Deserts and New Guinea.", "Subject": "East Africa natural habitats.", "Category": "", "Version": "10.1", "AntialiasingMode": "None", "TextAntialiasingMode": "Force", "Keywords": "Africa,ALES,Birds,Coral,EBAs,Endemic Bird Areas,Endemism,GLOBIL,IBA,Kenya,Madagascar,Mozambique,Tanzania,WWF,WWF Norway" }, "capabilities": "Map,Query,Data", "supportedQueryFormats": "JSON, geoJSON, PBF", "exportTilesAllowed": false, "referenceScale": 0.0, "supportsDatumTransformation": true, "archivingInfo": {"supportsHistoricMoment": false}, "supportsClipping": true, "supportsSpatialFilter": true, "supportsTimeRelation": true, "supportsQueryDataElements": true, "mapUnits": {"uwkid": 9001}, "maxRecordCount": 1000, "maxImageHeight": 4096, "maxImageWidth": 4096, "supportedExtensions": "", "serviceItemId": "5dbe70d33f07448faa51788f3c80a7d3" }