Fig 1.
Summary diagram of spatiotemporal tradeoff framework.
Since turbines from offshore wind operationally impact seabirds, preferred sites in space (x, y) maximize profitability to wind industry and minimize sensitvity to seabirds. Cetaceans, on the other hand, are mostly impacted episodically by pre-operational activities such as pile driving that impart potentially damaging acoustic energy, so should be timed (t) when species of conservation concern are least present at the given site based on migratory patterns.
Fig 2.
Overview of methods for bringing together wind profitability, seabird sensitivity over space, and cetacean sensitivity over space and time.
(See text for more detailed description).
Fig 3.
Mid-Atlantic offshore study area (red) and proposed Atlantic Wind Connection transmission leasing facility (blue). The study area is delimited by the availability of bird density data from the Atlantic Offshore Seabird Dataset Catalog. The pixelated edge is determined by the 10 km grid cells of the cetacean density surfaces (Roberts et al. 2016) in Albers Equal Area projection.
Table 1.
Bird sensitivity to OWED based on the maximum sensitivity of collision or displacement, per Bradbury et al. [11].
Table 2.
Conservation status score by species using NatureServe.
Species are listed amongst one of four large groups: baleen whales, beaked and sperm whales, large delphinoids and small delphinoids. For the 3 guilds (beaked whales, Kogia whales and pilot whales), species scores were averaged across member species. IUCN extinction risk categories were not used because many were data deficient (DD) (other codes: least concern (LC), vulnerable (VU) and endangered (EN)). The Endangared Species Act (ESA) was similarly limiting in providing a range of species weights based on conservation concern.
Table 3.
Lookup values to assign conservation score based on NatureServe conservation status.
Fig 4.
Wind energy valuation (net present value in $US millions).
Bathymetric depths are contoured in light gray.
Fig 5.
Wind energy valuation (net present value in $US millions) with access to the Atlantic Wind Connection (purple lines).
Fig 6.
Cumulative bird sensitivity to offshore wind energy development.
Bird sensitivity dramatically increases with latitutude and slightly further offshore. Contours of the the top 20% and 60% quantile areas denote areas dubbed as “major concern” and “concern” respectively, leaving only the remaining bluest areas offshore from North Carolina (NC) as the only “least concern” areas, per the classification scheme of Garthe & Hüppop (2004).
Fig 7.
Cetacean sensitivity for specific months with site labels.
Fig 8.
Tradeoff for all sites between bird sensitivity and wind profitability as net present value (NPV) in $US millions.
Sites with negative NPV were excluded from this plot. Values were rescaled before calculating average utility () of each site from 11 simulations of the utility function ranging a in Equation 8 from 0 to 1. The slope of the median
is shown as a dotted line passing through the highest utility site E. The red quadrant corresponds to the sites with the least 20% of profitability or the most 20% of bird sensitivity. The upper right blue quadrant corresponds with sites excluding the 60% least profitable and 60% most sensitive, hence a preferred subset for development of offshore wind energy.
Fig 9.
Map of average utility from simulation.
Contours for the top 20%, 40% and 60% quantiles of average utility. Site labels A-E are of highest utility within the 20% contour area and correspond with labels in the tradeoff plot (Fig 8) and table of values (Table 4).
Table 4.
Values of bird sensitivity, wind profitability (net present value in $US millions), average utility across simulations and sorted by overall rank for selected sites, corresponding to labels in the tradeoff plot (Fig 8) and average utility map (Fig 9).
Fig 10.
Map of BOEM Wind Energy Areas and Leases (as of October, 2018) in the context overall utility in grayscale with contours and site labels similar to Fig 9.
Fig 11.
Cetacean sensitivity for specific months for identified sites (Table 4, Fig 9).
The month with the minimum sensitivity is emphasized (filled circle marker) per site.
Fig 12.
Spatiotemporal decision support interface showing interactive map on the left and tradeoff plot of bird sensitivity versus industry profitability on the right.
The pixels of the map are colored by the utility function that maximizes profitability to industry while minimizing bird sensitivity. Clicking on a given pixel in the map will popup cetacean sensitivity over the year and highlight the month with the minimum sensitivity for timing harmful activities such as pile driving and seismic airgun surveying. Selecting rows in the table will highlight them on the tradeoff plot. Selecting points on the tradeoff plot will highlight them in the map. This application is available online at http://shiny.env.duke.edu/bbest/siting.