These areas, however, were the result of many negotiations between a wide variety of stakeholders and not necessarily the result of a systematic, transparent, quantitative process. Renewable energy development has seen more success on land in the US, which reached gigawatts GW of wind capacity and 53 GW of solar at utility scale by [ 4 ].
Lessons on land may translate to improving the efficiency of marine spatial planning [ 5 ]. For instance, multi-criteria decision analysis Stoms et al. Almost no human development is without some environmental impact, which are often difficult to quantify. Still, providing this high-level view can flag potential conflict areas where greater caution should be exercised and conversely expedite permitting of other areas, for instance where species of concern are less likely to occur.
The regulatory landscape for environmental compliance and offshore wind permitting in the United States is quite vast, requiring interagency oversight across a broad sweep of regulations [ 1 ]. The Energy Policy Act of , an amendment to Outer Continental Shelf Lands Act later, grants BOEM as the lead management authority for offshore wind energy projects in federal waters, which are beyond the 3 nm state waters, except within the national marine sanctuaries and monuments where NOAA is the authority under the National Marine Sanctuaries Act.
The Coastal Zone Management Act encourages consistent protections between federal and state waters. To make necessary information available to developers BOEM has also been facilitating the input of relevant spatial data into the online MarineCadastre. Datasets detail individual species distributions and potential conflicts with other industries, such as military and shipping. While the availability of these datasets will no doubt aid the planning process for offshore wind energy development OWED , a comprehensive summary view of overall risk to wildlife that combines the many datasets is still lacking.
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The contrasting tradeoffs between wildlife conservation and energy development can be explicitly modeled in terms of an efficiency frontier [ 6 ]. Originally developed as portfolio analysis to weigh financial investment in terms of risk versus return over time Markowitz , tradeoff analysis provides a useful synoptic view for evaluating across many sites the risk to wildlife versus the profitable return to industry.
Ideally, alternative sites can be chosen that maintain profitability while also maximizing conservation benefit. Plotting the value of each site along two axes i. Although White et al. The study was fine in spatial scale and not framed so as to offer spatial preference of one site versus another. Winiarski et al. This framework has been expanded upon by Furness et al. A subsequent study [ 12 ] incorporated uncertainty to arrive at broadly similar measures of vulnerability. But how then are other species incorporated to the decision-making process?
OWED hazards are considered in terms of: 1 hazard intensity and phases of development pre-construction, construction, operation, and decommissioning ; vulnerability of species; and exposure in terms of space and time; all to be considered cumulatively. Impacts can be both direct, i. Direct impacts of birds and bats colliding with turbines have been reasonably well characterized [ 13 — 15 ] while indirect effects of acoustic disturbance to marine mammals during pile driving has been difficult to quantify [ 16 ].
The majority of direct OWED impacts to cetaceans are acoustic, not during operation but with pile driving during construction [ 16 , 17 ]. Both of these activities impart a large amount of acoustic energy that can kill or harm animals in the immediate vicinity [ 18 ]. For instance, disturbance of harbor porpoises in Germany was demonstrated to reach distances more than 25 km from the pile driving site [ 19 ].
In contrast to Europe where marine mammals are mostly resident, the US North Atlantic seaboard has more migratory marine mammals. Effects on birds generally occur during the long-term operation of wind turbines, whereas impacts on marine mammals are most experienced episodically and acoustically during construction. The varying nature of impacts in space and time leads us to conclude that sites should be selected in space to minimize long-term impacts on birds, and timing of surveying and construction activities to be conducted in times of the year when sensitive migratory marine mammals are least present Fig 1.
The goal of this study is to describe an interactive decision support framework that explores the economic and environmental tradeoffs in space and time to find optimal sites that minimize impact to wildlife while preserving profitability to OWED, using the US Mid-Atlantic as a case study area. 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. To realize the general concept of the spatiotemporal framework Fig 1 three components must be analyzed and brought together Fig 2 : 1 offshore wind energy profitability over space, 2 seabird sensitivity over space, and 3 cetacean sensitivity over space and time.
Profitability to the wind industry is estimated as a function of transmission distance and wind availability. Seabird distributions get aggregated into a single cumulative sensitivity map with weightings based on sensitivity to offshore wind turbines. Each site i. Each of these sites can be assigned a new utility value as a function of each axes, i.
This new utility value can then be mapped out in space. Cetacean distributions are also aggregated into a cumulative sensitivity map, except weights are by extinction risk and a map is made for each month to capture variability in migratory patterns that could be differentially affected by episodic pile driving.
Impact of offshore wind farms on marine species
These general processes Fig 2 are given more in-depth treatment throughout the rest of the methods. See text for more detailed description. The Mid-Atlantic continental shelf of the US presents an opportune area for OWED given its strong offshore winds and proximity to densely populated coastal areas. Species densities are available for cetaceans [ 20 ] and birds Atlantic Offshore Seabird Dataset Catalog; see Winship et al.
The study area is defined by the best available bird density surfaces at the time of the analyses Fig 3.
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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. The candidate wind farm consists of the default InVEST configuration of 80 x 5MW turbines MW capacity farm with a hub height at 90m evaluated over a lifetime of 20 years.
The NPV for a wind farm in the given pixel is determined by the gross revenues from wind energy R t minus the costs C t annualized t over the lifetime T of the wind farm modified by the discount rate i or weighted average cost of capital 1. In terms of siting, revenue is largely determined by wind speed at hub height and costs by transmission distance to the grid. Since grid connection points are not made publicly available, distance to shoreline serves as a proxy. An additional 4 km to connect from shore to the grid was applied for all sites.
An alternate scenario considering access to the Atlantic Wind Connection transmission reduced this distance to shore but did not consider additional as yet unknown leasing costs for its use. Gross revenues R are derived from wind power by multiplying the price per kWh with the annual amount of kWh produced by the wind farm E.
Individual turbine output is based on the default InVEST parameters for the 5 MW turbine configuration cut-in at 3 ms -1 ; rated windspeed at Greater depths increase the cost of foundations and installation due to more required material but is not modeled here due to lack of published data for establishing an explicit relationship.
The jacketed foundations generally required for a 5 MW turbine are more expensive than the less robust monopole foundations used for 3. Floating structures open the possibility of going to still greater depths but are still in the demonstration phase. Although the majority of costs are for installation, operations and maintenance account for a fraction of the capital expenditure annually. The default 3.
Density distributions for 27 individual bird species were downloaded from the Avian Average Annual Abundances [ 24 , 25 ] available at MarineCadastre. The 6 species having density distributions and missing a sensitivity value from Bradbury et al. Density individuals per 2. Terms contributing to collision risk are flight altitude a , flight maneuverability m , percentage of time flying t , and nocturnal flight activity n. Displacement score is determined by disturbance from wind farm structures, ship and helicopter traffic d , habitat specialization h and conservation importance c.
Most terms are based on taxonomic expertise. The conservation importance score was based on UK-based measures: Birds Directive status, percent biogeographic population in English waters, adult survival rate and UK threat status. The maximum of either collision risk or displacement score per species was used to arrive at the Atlantic study weights Table 1 , similar to Bradbury et al. Per 10 km pixel, the average bird density was log-transformed, multiplied by bird sensitivity, and averaged across all species S. Cetacean distributions were gathered from a recently published study [ 20 ] describing density of cetaceans for 26 species and 3 guilds in the US Atlantic using survey data from boats and planes over a 23 year period with a variety of habitat predictors, including depth, temperature, wind, eddies, and productivity.
Impacts to cetaceans from OWED are not well described but understood to be mostly from intense acoustic energy during the construction phase from pile driving [ 16 , 26 ]. The species-specific responses of cetaceans are known for very few marine mammals, and have only been modeled in spatially explicitly detail for the harbor seal [ 27 , 28 ] and harbor porpoise [ 19 , 29 ] due to their common occurrence in European waters where the majority of OWED facilities have been installed. Scores were scaled 1 to Table 3 and applied to species, with averages taken for 3 guilds.
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. The Endangared Species Act ESA was similarly limiting in providing a range of species weights based on conservation concern. Unlike the bird distribution data, the cetacean predictions are available at monthly time steps.
Individual species densities d per 10 km 2 pixel i were rescaled as the difference from mean value over the standard deviation of the density within the study area. Species scores were averaged across all species S to arrive at a cetacean score per pixel and month. Deciding to site offshore wind energy development is based on weighing tradeoffs between wind energy profitability and species conservation.
Each site can be examined according to a tradeoff plot with either value on the axis. Deciding how much influence species conservation will be imposed at the loss of wind profitability is a societal decision involving industry, government regulatory agencies and other stakeholders.
We can quantitatively evaluate this tradeoff over a range of utility functions Equation 8. The weighting term a then indicates a preference of wind profitability versus bird sensitivity. Eventually this term could be implemented as sliders in a user interface. The utility u was then averaged to arrive at an average utility per site.
So then what is a reasonable range of each axis and overall utility to suggest for OWED? We adopted these quantiles across each axes and overall utility as a visual guide. Since the values of each axes wind profitability and bird sensitivity were normalized 0 to 1 , it is worth pointing out that the relationship between these terms is dependent on the extent of the study area and the values contained therein.
All the analysis, besides the wind energy valuation with InVEST, was coded in the free, open-source, cross-platform statistical programming language R [ 31 ].
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The spatial-temporal decision support system web-based interface was developed with the R package Shiny [ 32 ] using leaflet [ 33 ] for interactive mapping and ggvis [ 34 ] with plotly [ 35 ] for interactive plotting. The net present value of OWED for the US Mid-Atlantic Fig 4 shows a trend of increasing value offshore and more northern latitudes that is a driven by higher wind speeds in these areas.
Most coastal pixels near New Jersey and Delaware are even negative, thus unrealistic for investment. This pattern is consistent when modeling with the Atlantic Wind Connection Fig 5 with higher profit to be gained near the transmission line and further offshore. Bathymetric depths are contoured in light gray. Bird sensitivity exhibits a strong latitudinal gradient with Massachusetts to the north having the highest values and lowest offshore from North Carolina Fig 6.
Bird sensitivity dramatically increases with latitutude and slightly further offshore. The cycle integrates not only the results from Wozep but also the results from other research projects national and international. We are currently updating the KEC with the knowledge developed over the past two years.
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Cumulative effects have been calculated again to identify any change in the impact on protected species compared with the calculations from This newsletter will inform you about the results as soon as they have been finalised. The newsletter will be sent to Wozep stakeholders twice a year to describe the progress of the research and share the latest insights. It will include a number of articles about recently-completed research projects or new research activities. As well as describing results, we will also set out at the consequences of these results for decisions about wind-farm sites.
All the articles will include links to our website , where you can find the full research reports. Wozep research programme investigates the ecological impact of offshore wind farms. Figure 1: Locations of present dark green and planned route map offshore wind parks source: RVO Our research areas The effects of wind farms can be broken down into two broad categories: effects above and below the surface. Retrieved 7 May Environmental Health Perspectives. Toronto Star. Retrieved 16 December Lipscomb, Robert J. McCunney, Michael T. Domestica to the proximity of wind turbines".
Polish Journal of Veterinary Sciences. Cleveland; P. Endres 1 January Vestas , 29 December Accessed: 27 November Accessed: 1 February The EU's Externality study. Natural Resources Research. Journal of Industrial Ecology. Retrieved 29 August Archived from the original on 5 June National Renewable Energy Laboratory, p. Renewable and Sustainable Energy Reviews. London: Daily Mail. London: The Sunday Times. The New York Times. Bloomberg L. Developing greener, cheaper magnets Ames Laboratory.
Accessed: 10 March Scientific American. Argus Leader. Retrieved 5 September Valley Morning Star. London: Imperial College London. Bibcode : Natur. Sunday Herald.
Archived from the original on 27 June Retrieved 20 May Toronto Hydro. Landscape Ecology. Cornell University. Archived from the original PDF on 1 September Retrieved 17 August I even explicitly state this, as well, in the conclusion: 'the rudimentary numbers presented here are intended to provoke further research and discussion,' in the abstract 'this paper should be respected as a preliminary assessment,' and in the title of the study, which has the word 'preliminary' in it Letter to the Department of the Interior. American Bird Conservancy. Wildlife Society Bulletin.
USA Today. Department of the Interior. Retrieved July 30, University of Southern California. A21 New York edition , and May 13, online. Retrieved from nytimes. Quote: "In January, scientists concluded that, nationwide, million to million birds die annually after crashing into buildings and houses. National Audubon Society. Cats Kill Up To 3. Retrieved from The Globe and Mail website, January 30, Current Biology. Bibcode : CBio Laysource includes audio podcast of interview with author. Willis; Robert M. Barclay; Justin G. Boyles; R. Mark Brigham; Virgil Brack Jr.
Waldien; Jonathan Reichard Energy Policy. Atomic Insights. Retrieved 26 August Biological Conservation. Baerwald; J. Gruver Canadian Journal of Zoology. Archived from the original PDF on 4 March Retrieved 28 June Ryan Zimmerling, Andrea C. Pomeroy, Marc V. Los Angeles Times. Journal of Ornithology. Retrieved online November 2, Retrieved online, November 4, The Skeptical Environmentalist. The Auk. Upland birds face displacement threat from poorly sited wind turbines press release , Royal Society for the Protection of Birds website, September 26, Retrieved August 2, This press release in turn cites: Pearce-Higgins, J.
Journal of Applied Ecology. The Times. New Scientist : Biology Letters. The jury is still out on what works to protect wildlife. By Andrew Curry, for National Geographic. Archived from the original on 16 April Retrieved 29 October Bureau of Land Management.
Archived from the original on 14 August Auburn University. Associated Press. Bat Conservation International. American Wind Energy Association. London: The Guardian. Cresswell, Will ed. Bibcode : PLoSO Lay summary — The Guardian Proceedings of the National Academy of Sciences. Bibcode : PNAS.. Wind farms are not only beautiful, they're absolutely necessary , The Guardian , 12 August