Potential Interaction Analysis of Offshore Wind Energy Areas and Breeding Avian Species on the US Mid-Atlantic Coast

Thesis

Title: Potential Interaction Analysis of Offshore Wind Energy Areas and Breeding Avian Species on the US Mid-Atlantic Coast
Authors: Wisman, J.
Publication Date:
September 01, 2018
Thesis Type: Master's Thesis
Academic Department: Old Dominion University Biological Sciences
Pages: 62
Receptor:

Document Access

Website: External Link

Citation

Wisman, J. (2018). Potential Interaction Analysis of Offshore Wind Energy Areas and Breeding Avian Species on the US Mid-Atlantic Coast. Master's Thesis, Old Dominion University.
Abstract: 

Due to increasing US interest in developing wind energy sites in offshore waters, we synthesized existing data on colonial breeding seabird populations with the potential risk of interacting with lease areas in the mid-Atlantic. Previous efforts by BOEM and NOAA have predicted avian density using at-sea survey data; we seek to complement this work by focusing specifically on birds during the critical and energetically demanding breeding life history stage. We combined colony size and location for each species along the mid-Atlantic coast with buffers around the colonies that correlate with the species’ foraging range. We integrated population size, vulnerability to offshore wind, and foraging areas to create a multi-species vulnerability model and overlaid this model onto current BOEM lease areas. Our model determined areas of high-predicted vulnerability in the northern and southern ends of the Eastern Shore of Virginia, southern to mid-areas of the New Jersey coastline, and western Long Island of New York. Out of the total study area, 31.73% of the high-predicted vulnerable areas overlapped with currently leased areas for offshore wind energy development. We also compared our model to NOAA’s predicted density models and found they could be used together to identify areas with both high predicted density and high vulnerability as they overlapped 38.54% in our study area. The differences between these two models also suggest that simply relying on predicted density as a metric for determining impacts may miss areas that are critical for breeding birds. We also collected GPS location data on common terns (Sterna hirundo) at Dawson Shoals, Virginia during their 2017 nesting season. We analyzed their movement and behavior in relation to offshore wind sites. We determined that common terns most often utilized an area roughly half the size of the suggested foraging range found in the literature, and that some traditional risk-models may be overestimating the potential impacts of offshore wind development on seabirds. Tracking data should be integrated into methods used to minimize seabird impacts while developing an offshore wind energy industry in the mid-Atlantic.

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