Mapping functional connectivity

An objective and reliable assessment of wildlife movement is important in theoretical and applied ecology. The identification and mapping of landscape elements that may enhance functional connectivity is usually a subjective process based on visual interpretations of species movement patterns. New methods based on mathematical morphology provide a generic, flexible, and automated approach for the definition of indicators based on the classification and mapping of spatial patterns of connectivity from observed or simulated movement and dispersal events. The approach is illustrated with data derived from simulated movement on a map produced from satellite imagery of a structurally complex, multi-habitat landscape. The analysis reveals critical areas that facilitate the movement of dispersers among habitat patches. Mathematical morphology can be applied to any movement map providing new insights into pattern-process linkages in multi-habitat landscapes.