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data to spatially represent the specific risk elements (e.g. human activities) most likely toimpact critical habitats or key species. This means all risk element features must bespatially mapped on the landscape with precise location and boundaries (when possible)using expert opinion or obtaining (or creating through on-screen digitization) the mostaccurate GIS layers available. Human activities are often the most common risk elementfeatures used to create ERS models. Activities such as agriculture, urbanization, tourismzones and hotels, roads, industry, and population density are examples of risk elementsthat can be used in the creation of an ERS. These models can be developed specificallyfor terrestrial, freshwater, and marine realms, based on available input data and expertassessments for each risk element.Once all input data are gathered, experts must then review and rank each risk element tothe degree that it is a threat to the habitat/species in question. This is done by assigningthree variables to each point, line, or polygon feature that represents the correspondingrisk element. The three variables assigned are intensity value, influence distance, anddistance decay function. These values can be derived through expert evaluation of theextent, severity, and reversibility of each risk element in relation to the conservationtarget(s). In addition to socio-economic data, natural event data for events such ashurricanes, volcanic activity, and climate change may also be used in the creation of anERS, although it may be difficult to rank and assign these values due to the extremeunpredictability and complexity of these events. The figure below shows examples ofpolygon, line, and point risk elements that represent modeled risk surfaces with varyingintensity values and influence distances. The dark red areas represent higher combinedrisk and the lighter blue areas, lower risk as modeled by the mapped risk elementfeatures. Examples of how to assign intensity values, influence distances, and differentdistance decay functions are explained in the next sections.Examples of Environmental Risk Surfaces (ERS) derived from polygon, line, and point risk elementfeatures. Each risk element feature has an intensity, influence distance, and distance decay functionassigned based on the potential threat to biodiversity health. Red represents higher risk values whichdecreases linearly as the distance is increased away from the combined risk element features (i.e. bluerepresents lower risk).TNC Protected Area Tools (PAT) Version 3.0The Nature Conservancy, August 200911