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    "description" : "Climatic\nniche models (CNM) use correlation,\nmachine-learning and statistical approaches to define climate conditions within\neach species’ currently mapped range boundary. These relationships are then\napplied to projected climate changes to identify where on the landscape those\nclimate conditions are projected to be in the future. This map shows CNM results\nbased on results from Global Circulation Models (GCMs): XXX, XXX, XXX. Both models use the A2 (high) emissions scenario. CNMs are\nbased on climate conditions alone and do not account for dispersal ability,\ngenetic adaptation, interspecies interactions, or other aspects of habitat\nsuitability. Once projected range shifts were modeled, current land uses and\nprojected vegetation types (using Shafer et al. 2015)\nunlikely to support species occurrence were removed. For example, areas\ncurrently defined as urban were removed for species unable to live in urban\nlandscapes, and grassland habitats were removed for forest-dependent species. The majority\nwould be shown as unsuitable.\n\nDark gray areas indicate areas of the species’ current\nrange that are projected to remain climatically suitable by GCMs (i.e.\nrange is expected to remain “stable”). Dark pink areas are projected to become\nless climatically suitable by the all of GCMs (i.e. range is expected to “contract”).\nLighter pink areas are projected to become less suitable by the majority of the GCMs. The lightest pink areas are projected to remain stable  by the majority of the GCMs. Dark green areas are areas not within the\nspecies’ current range that are projected to become climatically suitable by 100% of the GCMs considered (i.e. the range is expected to “expand”). Lighter green areas are\nprojected to become climatically suitable by the majority of the GCMs considered. The lightest green areas are projected to expand by a minority of the GCMs considered.\n\nThis dataset was uploaded to Data Basin and is available with additional information at: /datasets/5c5199c583154d4ab218ef17f1df38f5",
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