A Markov model for planning and permitting offshore wind energy: A case study of radio-tracked terns in the Gulf of Maine, USA. (15th May 2017)

• Record Type: Journal Article
• Authors: Cranmer, Alexana; Smetzer, Jennifer R.; Welch, Linda; Baker, Erin
• Is Part Of: Journal of environmental management. Volume 193(2017)
• Page Start: 400
• Page End: 409
• Publication Date: 2017-05-15
• Subjects: Automated radio telemetry -- Central-place foragers -- Collision fatality -- Impact function -- Marine spatial planning -- Renewable energy; Environmental policy -- Periodicals; Environmental management -- Periodicals; Environment -- Periodicals; Ecology -- Periodicals; 363.705
• DOI: 10.1016/j.jenvman.2017.02.010
• Languages: English
• ISSNs: 0301-4797

Abstract

Abstract: Quantifying and managing the potential adverse wildlife impacts of offshore wind energy is critical for developing offshore wind energy in a sustainable and timely manner, but poses a significant challenge, particularly for small marine birds that are difficult to monitor. We developed a discrete-time Markov model of seabird movement around a colony site parameterized by automated radio telemetry data from common terns ( Sterna hirundo ) and Arctic terns ( S. paradisaea ), and derived impact functions that estimate the probability of collision fatality as a function of the distance and bearing of wind turbines from a colony. Our purpose was to develop and demonstrate a new, flexible tool that can be used for specific management and wind-energy planning applications when adequate data are available, rather than inform wind-energy development at this site. We demonstrate how the tool can be used 1) in marine spatial planning exercises to quantitatively identify setback distances under development scenarios given a risk threshold, 2) to examine the ecological and technical trade-offs of development alternatives to facilitate negotiation between objectives, and 3) in the U.S. National Environmental Policy Act (NEPA) process to estimate collision fatality under alternative scenarios. We discuss model limitations and data needs, and highlight opportunities for future model extension and development. We present a highly flexible tool for wind energy planning that can be easily extended to other central place foragers and data sources, and can be updated and improved as new monitoring data arises. Highlights: We developed a Markov model to inform wind energy planning for breeding seabirds. The model estimates fatality risk as a function of turbine distance from colony. The tool can compare planning scenarios and balance wildlife and wind energy goals. This flexible tool can be updated with new data and extended to other species.