This document describes three resiliency metrics that measure a system’s ability to recover from disturbance or stress, as opposed to the other metrics, which assess sources of anthropogenic stress. Resiliency is both a function of the local ecological setting, since some settings are naturally more resilient to disturbance and stress (e.g., an isolated wetland is less resilient to species loss than a well-connected wetland because the latter has better opportunities for recolonization of constituent species), and the level of anthropogenic stress, since the greater the stressor the less likely the system will be able to fully recover or maintain ecological functions. All three of these metrics are based on assessing the distance from the focal cell to cells in its neighborhood in ecological settings space, as defined by a suite of 24 ecological settings variables. The settings variables are an attempt to capture the geophysical attributes that are primary determinants of ecological systems, e.g., temperature, sunlight, moisture, hydrology, and soils (McGarigal et al 2017). Settings also include several anthropogenic variables, such as development, traffic rates, and impervious surfaces. Ecological distance is low for points that fall nearby in settings space (e.g., two points that are on dry ridgetops with similar soils and climate), and higher for points that are further apart in settings space (e.g., a ridgetop and a valley wetland). Ecological distance is highest between natural and anthropogenic points (e.g., the ecological distance between a forest and a point in the middle of an expressway is extremely high, despite any similarities in landform or climate). Note that ecological distance is unrelated to physical distance (although two points that are nearby are more likely to share similar ecological settings).
Environmental Sciences | Sustainability
McGarigal, Kevin; Compton, Brad; Plunkett, Ethan; DeLuca, Bill; and Grand, Joanna, "Designing Sustainable Landscapes: Resiliency metrics: similarity, connectedness, and aquatic connectedness" (2017). Data and Datasets. 31.