Grid-based monitoring methods for detecting population declines: Sensitivity to spatial scale and consequences of scale correction

A decrease in the area of occupancy of a species is often criterion by which a species is classified as threatened (i.e. IUCN Red List). However, it is unclear how to accurately measure change in area of occupancy. Area of occupancy is a measure of distribution and the spatial scale at which the distribution is measured will affect the ability to detect a decline. To overcome errors introduced by measuring distribution at different spatial scales, scale correction methods are often applied. It is known that scale correction reliably estimates area of occupancy; however, its suitability to estimate trends in area of occupancy has not been assessed. We investigate the effect of spatial scale and implementation of scale correction when estimating two different forms of decline in area of occupancy: spatially correlated and spatially uncorrelated declines. We explore these issues using simulations of three declining species and a grid-based monitoring method designed to detect the declines. Our results suggest that current grid-based methods are inadequate for detecting uncorrelated local extinctions, even if the total decline is substantial (e.g. 65% of the original range). We demonstrate that scale correction will lead to misleading conclusions in some situations. We suggest an alternative survey method to accurately estimate changes in area of occupancy over time. We provide guidelines for designing grid surveys to measure changes in area of occupancy to assess a species threat status using the IUCN Red List criterion.