A Review of Overlapping Landscapes: Pseudoreplication or a Red Herring in Landscape Ecology?

Identifying the spatial scale at which a species or population most strongly responds to habitat composition and configuration is known as scale-of-effect and is a fundamental pursuit of landscape ecology. In conducting scale-of-effect studies, it is common to measure habitat in landscape buffers of varying sizes surrounding sample sites. When sample sites are in close spatial proximity to one another, these landscape buffers will overlap. Researchers commonly worry that data generated from these overlapping landscapes, and subsequently used as predictor variables in statistical modeling, represent a form of pseudoreplication that violates the assumption of independence. Here, we review the concept of overlapping landscapes and their theoretical and practical implications in landscape ecology. We suggest that the perceived problem of overlapping landscapes is distinct from more important issues in landscape ecology, such as a robust sampling design complete with a discrete assessment of spatial autocorrelation. Through simulation, we demonstrate that changing the amount of landscape overlap does not alter the degree of spatial autocorrelation. Yet, in reviewing over 600 journal articles, we found that a third (29%) of the studies perceived overlapping landscapes as an issue requiring either changes in sampling design or statistical solutions. Researchers concerned with overlapping landscapes often go to great lengths to alter their sampling design by removing or aggregating sites. Overlapping landscapes remain a prevalent concern in landscape ecology despite previous studies that show that overlapping landscapes are not a violation of independence and represent an oversimplification of the statistical concerns of spatial autocorrelation. The concern over overlapping landscapes as a form of pseudoreplication persists in landscape ecology, but acts as a potential red herring detracting from more relevant concerns of proper sampling design and spatial autocorrelation in ecological studies.