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USGS Gap Analysis Project Additional Data: Human Impact Avoidance

October 1, 2018

Environments dominated by human disturbance such as roads, cities, and the constructed materials that support human habitation have profound effects on species. For most species, this data layer was used to exclude species from a portion of the landscape. However, some species respond favorably to human habitats, therefore this data layer was used in an inclusionary manner. The human impact avoidance dataset describes high exclusion/high inclusion proximity to urban environments, and roads. This dataset was derived from US Census TIGER/Line files and the GAP Analysis Project's (GAP) National Land Cover Database developed by USGS, in particular the impervious dataset. These data are divided into 6 regions across the US (Northwest, Southwest, Great Plains, Upper Midwest, Southeast, and Northeast). If you want complete coverage of the entire US, all 6 regional files are needed. These raster data have a 30 m x 30 m cell resolution. Level of avoidance: High - For species that are very intolerant of human disturbance. All portions of the landscape identified as being directly influenced by human disturbance are eliminated from the predicted distribution. Medium - For species that are moderately intolerant of human disturbance. Only portions of the landscape identified as being highly or moderately influenced by human disturbance are eliminated from the predicted distribution. Low - For species that are partially intolerant of human disturbance. Only portions of the landscape identified as being highly influenced by human disturbance are eliminated from the predicted distribution. No selection of this parameter indicates the species' model is not contingent on an index of human disturbance. GAP used the best information available to create the human impact avoidance ancillary data; however GAP seeks to improve and update these data as new information becomes available.