The Human Modification (HM) model is designed to provide a comprehensive, but parsimonious approach, that uses several stressor/threats datasets to estimate level of human modification. There are three important elements that define the HM approach: (a) the human modification stressors and their data sources (b) the measurement unit used for each stressor, and (c) the method used to combine the effects of multiple stressors into an overall score of human modification. The way in which these various data layers are combined into a single index is quite important. We use a method that minimizes bias associated with non-independence among several stressor/threats layers (Theobald 2013). The HM model assumes the contribution of a given threat decreases as values from other threats overlap. Locations with multiple threats will have a higher human modification value than locations with just a single threat (assuming the same value), but the cumulative human modification score converges to 1.0 as multiple human impact data layers are added. Individual factors were combined across multiple data layers using an increasive function (Theobald 2013). Details of the HM model are described in: Theobald, DM. 2013. A general model to quantify ecological integrity for landscape assessments and US application. Landscape Ecology DOI 10.1007/s10980-013-9941-6. We updated using datasets described in Theobald et al. 2017.