The spatial correlation between trawl surveys and planned wind energy infrastructure on the US Northeast Continental Shelf

Abstract

Abstract The development of wind energy on the US Northeast Continental Shelf (NES) may preclude resource-monitoring programmes from continuing in their original study designs. We considered the spatial requirements of energy developers and the spatial autocorrelation of resident species as a means to inform survey mitigation. The spatial requirements of the NES wind industry were considered in respect to the delineation of settled lease areas. We suggest access metrics ranging from 8 to 21 km representing the interquartile range of chord distances across the settled lease areas. Using survey data and concentrating on commercial species with stock assessment requirements, we computed indices of spatial autocorrelation. Tests of spatial autocorrelation using Moran’s I and join counts statistics were significant (p < 0.05) for most species, suggesting a high level of spatial correlation in their distributions. To characterize a scalar extent of spatial correlation, variograms were fit to estimate the physical range of correlated catches. These data suggest most species were spatially correlated well beyond the distance metrics derived from the lease area shapes. Sampling by a range of gears has the potential of producing spatially accurate depictions of species distributions and abundance despite the restrictions wind lease areas may place on sampling designs.