Mid-Atlantic Wildlife Studies Distribution and Abundance of Wildlife along the Eastern Seaboard 2012-2014 funDing AnD collAborAting orgAnizAtions Tis material is based upon research supported by the Department of Energy under Award Number DE-EE0005362. Additional funding support for various project components came from the Maryland Department of Natural Resources, Maryland Energy Administration, Bureau of Ocean Energy Management (BOEM), U.S. Fish and Wildlife Service (USFWS), Sea Duck Joint Venture, Te Bailey Wildlife Foundation, Te Nature Conservancy, Ocean View Foundation, Te Bluestone Foundation, Maine Outdoor Heritage Fund, and Davis Conservation Foundation.

Project investigators included scientists from Biodiversity Research Institute, North Carolina State University, City University of New York, Duke University, Oregon State University, and the University of Oklahoma.

Various project components were completed in collaboration with one or more of the following organizations: HiDef Aerial Surveying, Ltd., USGS Patuxent Wildlife Research Center, Memorial University of Newfoundland, Canadian Wildlife Service, Virginia Department of Game and Fisheries, Delaware Division of Fish and Wildlife, Rhode Island Division of Fish and Wildlife, University of Rhode Island, North Carolina Wildlife Resource Commission, Captain Brian Patteson, Inc., and Aquacoustics, Inc. BRI investigators would also like to acknowledge the many staf members who contributed towards this project’s success.

Disclaimers: Tis report was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specifc commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof. Te views and opinions of authors expressed herein do not necessarily state or refect those of the United States Government or any agency thereof. Te statements, fndings, conclusions, and recommendations expressed in this report are those of the author(s) and do not necessarily refect the views of the Maryland Department of Natural Resources or the Maryland Energy Administration. Mention of trade names or commercial products does not constitute their endorsement by the State.

suggesteD citAtion for this report creDits Williams, K.A., I.J. Stenhouse, E.E. Connelly, and Editorial and Production: Deborah McKew S.M. Johnson. 2015. Mid-Atlantic Wildlife Studies: Editorial Assistance: Leah Hoenen, Kate Taylor Distribution and Abundance of Wildlife along the Design Collaboration and Chart Production: RavenMark Eastern Seaboard 2012-2014. Biodiversity Research Boat/Plane Comparison Infographic: Linda Mirabile/Glen Halliday Institute. Portland, Maine. Science Communications Cartography: Jef Tash, Sarah Johnson, Andrew Gilbert, Holly Goyert, Logan Pallin Series BRI 2015-19. 32 pp. Photography: Access to DAtA Cover: Diving Northern Gannet © Matt Doggett (mattdoggett.com) All survey data from this study (including both the Pages 2-3: White-winged Scoter © Daniel Poleschook Mid-Atlantic Baseline Studies and Maryland projects) are Pages 4-5: Banner–Forage fsh © Valengilda Page 4: Sea turtle © Soren Egeberg available for download on the project website: Page 5: Northern Gannet © McLeodPhotographyLondon; www.briloon.org/mabs. Wind turbines © iStock–ts-foto.de-Tomas Stolz Data are also included in the Northwest Atlantic Seabird Pages 6-7: Banner–Researcher ofshore © BRI-Jonathan Fiely Catalog, a federal database managed by the USFWS that is Page 6: North Atlantic Right Whales © HiDef Aerial Surveying, Ltd. Pages 8-9/10-11: Banners–Map illustration © ChrisGorgio used by BOEM and other agencies as a key repository for Page 8: BRI video lab © BRI-Wing Goodale wildlife distribution data on the Atlantic Outer Continental Pages 12-13: Banner–Underwater landscape © RomoloTavani Shelf. Pages 14-15: Banner–Short-beaked Common Dolphins © Anthony Pierce (robertharding.com) Page 16: Surf Scoter © Daniel Poleschook Page 17: Surf Scoter with satellite tag © BRI-Jonathan Fiely Page 18: Red-throated Loon © Ken Archer Page 19: Red-throated Loon with satellite tag © BRI-Rick Gray Page 20: Northern Gannet © BRI-Jonathan Fiely Page 21: Northern Gannet with satellite tag © BRI-Jonathan Fiely Page 22: Humpback Whale © kenglye Page 24: Leatherback Sea Turtle © Michael O’Neill/Oceans-Image/Photoshot Page 25: Loggerhead Sea Turtle © Kate Sutherland Page 26: Banner–Radar blooms courtesy Soar.ou.edu; Cownose Rays © HiDef Aerial 276 Canco Road, Portland, Maine 04103 • 207-839-7600 Surveying, Ltd. www.briloon.org Page 28: Wilson’s Storm-Petrel © Kate Sutherland; Construction of marine wind turbine courtesy Nysted HavmØllepark Back cover: Short-beaked Common Dolphins preying on mackerel © Christopher Swann (oceanus.uk.com) Printing: J.S. McCarthy Printers North America STUDY AREA

Contents

Executive Summary ...... 2 Background Mid-Atlantic Ecosystem ...... 4 Ofshore Wind and Wildlife ...... 5 Study Area and Methods ...... 6 Analytical Methods ...... 8 Atlantic Ocean Comparing Boat and Aerial Surveys ...... 12 Geographic and Temporal Patterns ...... 14 Case Studies: Scoters ...... 16 Red-throated Loons...... 18 Northern Gannets...... 20 Cetaceans ...... 22 Sea Turtles...... 24 Migratory Movements...... 26 Conclusions ...... 28 Literature Cited ...... 29

Executive Summary

he Mid-Atlantic Baseline Studies Project was Tis report is a synthesis of many aspects of the T funded by the Department of Energy’s (DOE) Mid-Atlantic Baseline Studies project. A more detailed Wind and Water Power Technologies Ofce in 2011, examination may be found in the full project report with additional support from a wide range of partners. (Williams et al. 2015) and related publications Te study goal was to provide comprehensive baseline (e.g., Hatch et al. 2013 and others). ecological data and associated predictive models and In this publication, we explore aspects of the maps to regulators, developers, and other stakeholders mid-Atlantic ecosystem; describe our survey and for ofshore wind energy. Tis knowledge will help analytical approaches; and present a range of results, inform the siting and permitting of ofshore wind featuring several case studies on specifc species or facilities on the mid-Atlantic Outer Continental Shelf. phenomena. Each case study includes the integration Research collaborators studied wildlife distributions, of data from multiple study components, presenting abundance, and movements between 2012 and 2014. a comprehensive view of wildlife distribution and Te specifc study area was chosen because it is a movement patterns. Key fndings include: likely location for future wind energy development t Boat-based and digital video aerial surveys each ofshore of Delaware, Maryland, and Virginia, including had specifc advantages and disadvantages, but three federally designated Wind Energy Areas (WEAs). were largely complementary. Digital aerial surveys Project objectives were to: may be particularly useful for covering ofshore t Conduct standardized surveys to quantify wildlife areas at broad scales, where general distributions of abundance seasonally and annually throughout taxonomic groups are a priority; boat surveys can the study region, and identify important habitat provide more detailed data on species identities use or aggregation areas. Boat-based surveys and and behaviors, but are more limited in geographic high resolution digital video aerial surveys were scope due to their slower survey pace. conducted to reach this objective. t Habitat gradients in nearshore waters were t Develop statistical models to help understand important infuences on productivity and patterns the drivers of wildlife distribution patterns and of species distributions and abundance. Areas to predict the environmental conditions likely to ofshore of the mouths of Chesapeake and support large densities of wildlife. Delaware Bays, as well as to the south of Delaware Bay along the coast, were consistent hotspots of t Use individual tracking methods for several focal abundance and species diversity, regardless of bird species to provide information on population survey methodology or analytical approach. connectivity, individual movements, and seasonal site fdelity that is complementary to survey data. t Te study area was important for wintering and breeding taxa, and its location also made it t Identify species that are likely to be exposed to a key migratory corridor. Tere was considerable ofshore wind energy development activities variation in species composition and spatial in the mid-Atlantic study area. patterns by season, largely driven by dynamic t Explore technological advancements and environmental conditions. assessment methods aimed at simplifying Te results of this study ofer insight to help address and minimizing the cost of environmental risk environmental permitting requirements for current and assessments. future projects. Tese data serve as a starting point for t Help meet regulatory data needs by contributing more site-specifc studies, risk analyses, and evaluation of several years of data and analysis towards potential measures to avoid and minimize risks to wild- future Environmental Impact Statements. life from human activity in the ofshore environment. PAGE 3 The Mid-Atlantic Marine Ecosystem

he study of ecology attempts to entire annual cycle, including several In these areas, year-round mixing of T identify the connections between dozen species listed as threatened or saline and fresh waters through estuarine organisms and the world around them, endangered at the federal level or state circulation, in combination with strong and explain how those relationships level. Te importance of the region for tidal currents, leads to increased afect, or are impacted by, the physical these wildlife species is due, in part, to primary productivity. Nutrient- and attributes of their habitats. Marine the region’s central location in a major phytoplankton-rich waters fow from ecosystems are particularly complex migratory fyway and a relatively high these bays and are swept southwards by and dynamic assemblages that involve level of primary productivity (growth of the Labrador Current. multitudes of co-evolved species. Tus, phytoplankton). Seasonal stratifcation on the shelf drives research studies integrated across Te Mid-Atlantic Bight is an oceanic annual primary productivity across taxonomic groups and among trophic region that spans an area from the region, with the largest and most levels are critical to understanding marine Cape Cod to Cape Hatteras and is persistent phytoplankton blooms in the ecosystem processes and mechanisms. characterized by a broad expanse late fall and winter. In shallow coastal In this study, we analyzed the of gently sloping, sandy-bottomed waters, sunlight is able to penetrate distributions and movements of continental shelf. Tis shelf extends up a relatively high proportion of the prominent marine wildlife species to 150 km ofshore, where the waters water column, fueling photosynthetic across a large swath of the mid-Atlantic reach about 200 m deep. Beyond activity and growth of phytoplankton coastal region, and also examined the the shelf edge, the continental slope where nutrients are available. Phyto- infuence of environmental factors, descends rapidly to around 3,000 m. plankton blooms are followed by a such as productivity, water depth, and pulse in secondary productivity— Most of this mid-Atlantic coastal region salinity, on these distributions. zooplankton species that forage on is bathed in cool Arctic waters the phytoplankton—which in turn Tis ecosystem-based approach introduced by the Labrador Current. become food for larger predators, such establishes a broad baseline from which At the southern end of this region, as small fshes. to understand the impacts of future around Cape Hatteras, North Carolina, development or management decisions these cool waters collide with the Te Mid-Atlantic Bight is generally rich on the ofshore environment. warmer waters of the Gulf Stream. with small, schooling fshes, known as “forage fsh” due to their critical the MiD-AtlAntic bight Te mid-Atlantic region exhibits a importance for many piscivorous strong seasonal cycle in temperature, Signifcant both ecologically and predators and their pivotal role in with sea surface temperatures spanning economically, the mid-Atlantic region driving ecosystems worldwide (Pikitch 3-30 °C. Tere is also a wide range in is used by a broad range of marine et al. 2014). Te presence of these forage salinity, with large volumes of fresh wildlife species across the fsh populations indicates the high levels water emptying onto the shelf from of productivity in the mid-Atlantic the Hudson Estuary, Delaware region, and is likely responsible, in part, Bay, and Chesapeake Bay. for the large numbers of predators that This influx of fresh water use the area. has a particularly strong effect on the characteristics of this ecosystem WilDlife populAtions around the mouths of the bays, Migrant terrestrial species, such as delivering nutrients such as nitrogen landbirds and bats, may follow the and phosphorous that boost primary coastline on their annual trips or productivity in coastal waters choose more direct fight routes over (Townsend et al. 2006). expanses of open water.

PAGE 4 • BACKGROUND Many marine species also make annual filling the MiD-AtlAntic Tis study migrations up and down the eastern DAtA gAp provides the frst seaboard, taking them directly through comprehensive view of Despite recent and ongoing data the mid-Atlantic region in spring and taxa that are likely to be compilation and survey eforts for fall. Tis results in a complex ecosystem exposed to ofshore wind energy marine wildlife in the western North where the community composition development in the mid-Atlantic region. Atlantic (e.g., extensive survey eforts shifts regularly and temporal and in New Jersey and Rhode Island; Geo- Tese seasonal baseline data on wildlife geographic patterns are highly variable. Marine, Inc. 2010, Paton et al. 2010), species composition, distributions, and Te mid-Atlantic supports large several geographic holes still remain. relative abundance are essential for: populations of marine wildlife in Te Mid-Atlantic Baseline Studies 1. Marine spatial planning eforts; summer, some of which breed in the and Maryland projects, described here, 2. Understanding when and where area, such as coastal birds and some fll a signifcant information gap for a animals may be afected by sea turtles. Other summer residents, large swath of the mid-Atlantic region. anthropogenic activities; and such as shearwaters and storm-petrels, Given the high levels of productivity 3. Identifying species or taxa in visit from the Southern Hemisphere in the region, and its year-round particular need of additional study. (where they breed during the austral importance to a broad suite of summer). In the fall, many of the Tese data can be used during permitting species, it is essential to understand summer residents leave the area and processes for future development, as well this ecosystem in order to manage migrate south to warmer climes, and are as for siting projects and designing it efectively, particularly with regard replaced by species that breed further development plans to minimize wildlife to anthropogenic stressors such as impacts. north and winter in the mid-Atlantic. ofshore development.

offshore WinD AnD WilDlife Ofshore wind energy development vessels; displacement from, or attraction to, habitat use areas; has progressed rapidly in Europe avoidance of facilities during migration or daily movements, since the frst facility became which may necessitate increased energetic expenditures; operational in 1991, and it is now and changes to habitat or prey populations (Fox et al. 2006). being pursued in the U.S. as well. Te scale of development is likely to be important in Tis renewable resource has the determining the signifcance of these efects. Exposure alone potential to reduce global carbon does not necessarily indicate the severity of these efects, emissions, and thus to positively however. Te vulnerability of diferent species to development afect many species. activities will also play a role in determining impacts. Ofshore wind energy developments may also afect local wildlife Overall, the cumulative efects to wildlife will be dependent more directly. Researchers are still learning about how ofshore on the size and number of wind facilities that are built, as wind energy facilities afect marine ecosystems, but it seems clear well as local topography, climate, species ranges, behaviors, that efects vary during diferent development phases, and that and other oceanographic and biological factors. species respond in a variety of ways (Langston 2013). Some species are negatively afected, while others show no net efect, Efects from ofshore wind may also be combined with other or may even be afected positively. natural and anthropogenic stressors. As a result, physical and ecological context is essential for understanding and Possible efects to fsh, marine mammals, sea turtles, birds, and minimizing efects of ofshore development on wildlife. bats include: mortality or injury from collisions with turbines or PAGE 5 Study Area and Methods

he Mid-Atlantic Baseline recorded sea state, visibility, ocean Studies project focused on a 13,245 temperature, and salinity. Distance and T2 km area on the Outer Continental Shelf angle to each animal were also recorded of the coasts of Delaware, Maryland, for use in modeling. and Virginia. Tis study area extended from 5.6 km (3 nautical miles) of the high resolution DigitAl coast to the 30 m isobath (Figure 1). viDeo AeriAl surveys North Atlantic Right Whales in high resolution Beginning in March 2013, surveys were High resolution digital video aerial digital video recorded during aerial surveys. extended ofshore of Maryland (funded surveys are a relatively new method by the Maryland Department of Natural for collecting distribution and relative information on the movements of Resources and the Maryland Energy abundance data on animals (Taxter individuals and potentially identify Administration). and Burton 2009). Our study was the ecologically important areas We used several study methods frst to use these methods on a broad (Montevecchi et al. 2012). Satellite to document animal movements, scale in the U.S. HiDef Aerial Surveying, transmitters send data on locations of distributions, abundance, and habitat Ltd. developed this approach in the individuals to orbiting satellites during use; each method had strengths and United Kingdom and conducted the predetermined periods of the day. weaknesses (Table 1). Te combination surveys for this study. Surveys were We deployed satellite transmitters on of these methods resulted in a more fown in small twin-engine airplanes Surf Scoters, Northern Gannets, Red- comprehensive understanding of at 250 km/hr and an altitude of 610 m, throated Loons, and Peregrine Falcons, wildlife patterns in the region. which is much higher and faster than four species that make use of the study traditional visual aerial surveys (fown at area during wintering or migration boAt surveys 60-180 m). Flying at this altitude is safer periods. Birds were captured at several Boat-based surveys are widely used for the fight crew and less disruptive to locations along the east coast of North to monitor marine wildlife. Due to the animals being counted. America. Satellite transmitters were relatively slow survey speeds (19 km/hr), We conducted 15 surveys over two attached to birds externally or were observers can record detailed data on years (March 2012–May 2014) along surgically implanted. species identities, relative abundance, and 2,857 km of transects (3,601 km Telemetry data presented in this behaviors, including contextual data, including the Maryland project; report were gathered as part of several such as “feeding frenzies” of dolphins Figure 1). Four belly-mounted cameras longer-term studies funded by multiple and seabirds preying on forage fsh. recorded video data, resulting in a agencies and organizations. Tese In collaboration with the City University 200 m wide transect. preliminary results will be updated as of New York, we conducted 16 surveys Video data were analyzed by two teams research continues. over two years (April 2012–April 2014) of observers who located and identifed along 559 km of transects (572 km objects in the footage. Tese processes nocturnAl MigrAtion including the Maryland project in 2013- included multiple quality control Monitoring 14; Figure 1). procedures. Flight heights were estimated Oceans can act as barriers to migrating Our surveys were conducted by teams for fying animals (Hatch et al. 2013). landbirds, including songbirds and of two observers on a 55-foot charter raptors, but many species also make long vessel. In addition to recording the sAtellite teleMetry transoceanic fights, especially at night location, relative abundance, and Tracking techniques, such as attaching (Delingat et al. 2008). We used two behaviors of animals such as marine satellite transmitters to individual methods to document nocturnal avian birds, mammals, and turtles, observers animals, allow us to obtain detailed migration. During nights spent on the

PAGE 6 • STUDY AREA AND METHODS STUDY AREA

DE

water, a passive acoustic monitoring device was deployed on the survey vessel to detect fight MD calls of landbirds migrating through the study area. We also analyzed weather surveillance radar (NEXRAD) to detect ofshore migratory activity in the atmosphere on a broad scale. Outer Continental Shelf Neither method allowed for estimation of actual animal abundance, and NEXRAD y a B data were not species specifc, but together e k a these approaches provided information on e p

a ofshore migration during a time of day s e h Mid-Atlantic Study Area when visual surveys were impossible. C Wind Energy Areas/ integrAting MethoDologies Aerial Transects Maryland Project By using the above research methods, we Aerial Transects developed a more complete picture of wildlife Aerial Survey Transects populations in the mid-Atlantic study region Boat Survey Transects (Table 1). For example, satellite tracking provided data on broad-scale movements of VA individual birds, including nocturnal locations that were missing from survey data. Survey data allowed for population-level analyses of Figure 1: Te study areas for the Mid-Atlantic Baseline Studies and Maryland projects, with abundance and distributions that were not WEAs and boat and aerial survey transects. Fine scale aerial transects (20% coverage) were possible with tracking alone. carried out within the WEAs and the Maryland project area.

Video Aerial Boat Satellite Avian Passive WSR-88 Table 1: Methods for studying Survey Survey Telemetry Acoustics Weather Radar ofshore wildlife that were incorporated into this study. Geographic Coverage      Relative strengths and weaknesses Temporal Coverage      of each approach are indicated by depth of color ( = good,  = fair, Population Distributions    —   = poor). A dash indicates that data Abundance*   —   were not available from this survey method. Detection (marine mammals)   — — — Values are subjective; for example, Detection (sea turtles)   — — — while detection bias was not quantifed for aerial surveys, detection Detection (birds)   —   of avian species in our boat surveys appeared to be better than digital Species Identifcation   —  — video aerial surveys in many cases, at Behaviors    — — least after correction for distance bias in boat data. Tus, boat surveys were Movements    —  categorized as “good” for this type of data, while digital video aerial surveys Diurnal Activities    — — were considered “fair.” Nocturnal Activities — —    *Ei ther absolute or relative abundance.

PAGE 7 Analytical Methods

e use several diferent persistent hotspots Figure 2: Types of Maps Used in this W approaches for presenting of AbunDAnce Document* results in this report. Understanding each Persistent hotspots are locations where Example A: Raw Survey Data analytical method and its limitations animals were most often found in large Maps of observation points show where individual animals were recorded during is essential to appropriately interpret aggregations relative to their typical maps, fgures, and other analyses. boat and aerial surveys. Tey do not distribution patterns. Tese areas likely correct for known sources of bias in provide important habitat for foraging, rAW observAtion DAtA observations. roosting, or other activities (Santora Example B: Persistent Hotspots In rare instances, we simply map the and Veit 2013). Persistent hotspot maps use efort- locations where wildlife were observed corrected boat and digital video aerial during surveys, without any additional Before identifying hotspots, we grouped survey data, aggregated across all surveys, analysis (Figure 2A). Tis approach survey observations into grid cells. Tese to illustrate where the highest numbers is straightforward, but has severe cells, or lease blocks, are defned by the of animals were most consistently observed. Tis presentation corrects limitations. Bureau of Ocean Energy Management for ofshore development activities. for variation in efort, but does not address detection bias. Colors range Tere are known sources of bias in Counts were standardized by the raw survey data that make it difcult from no color (never a hotspot) to red amount of survey efort in each lease (in the 95th percentile for persistence of to compare values across space, time, block. Te lease blocks with the largest hotspots across all cells and surveys in and species without frst controlling for efort-corrected relative abundance which the taxon was present). those biases (Burnham and Anderson, values within each survey were labeled Example C: Predicted Abundance 1984, Spear et al. 2004, Wintle et al. as survey-specifc hotspots. Seasonal predicted abundance maps 2004). display outputs from generalized linear Blocks that were repeatedly identifed as models (GLMs) or generalized additive Because of these limitations, we only hotspots during the two years of boat models (GAMs). Tese models use present raw survey data when there and aerial surveys were categorized as efort- and bias-corrected survey data were insufcient observations to support “persistent” hotspots. To combine data from either boat surveys or digital alternative approaches that address these video aerial surveys, in combination from boat and aerial surveys for lease with environmental covariate data, to sources of error (e.g., observations of blocks that were surveyed by both predict seasonal animal distribution baleen whales; Figure 18). methods, we weighted each dataset and abundance across the study area. to address diferences in detection Values represent estimated numbers of and/or identifcation rates between individuals or groups of individuals per grid cell. survey methods. Te survey method that detected or identifed the taxon Example D: Utilization Distribution Utilization distribution (UD) maps are at the highest rate was given greater derived from satellite telemetry data. importance (i.e., weight). Tey display the estimated core use areas, where tagged individuals spent Hotspot maps use a gradation of colors the majority (>50%) of their time, and to indicate increasing hotspot persistence broader utilization distributions, in which (Figure 2B). In addition to showing individuals spent >95% of their time. persistent patterns for various taxonomic While survey data provide “snapshot” groups (e.g., for sea turtles; Figure 21), information on population distributions, UD maps characterize the movements we also use this analytical approach to and habitat use of a group of individual illustrate persistent patterns of species animals over time. richness across all taxa (Figure 7). *Tese example maps show a subset of data Continued on page 10 for the Northern Gannet. PAGE 8 • ANALYTICAL METHODS EXAMPLE A: RAW SURVEY DATA EXAMPLE B: PERSISTENT HOTSPOTS

Mid-Atlantic Study Area Wind Energy Areas Fine-scale Aerial Survey Hotspot Persistence Transects in WEAs Never a Hotspot Maryland Project Aerial <75th Percentile Transects 75-85th Percentile Aerial Survey Transects 85-95th Percentile Boat Survey Transects 95th Percentile l Aerial Observations l Boat Observations

EXAMPLE C: PREDICTED ABUNDANCE EXAMPLE D: UTILIZATION DISTRIBUTION (TELEMETRY)

Wind Energy Areas Wind Energy Areas

Predicted Winter Daily 50% Winter Utilization Abundance (number of animals Distribution (core use area) per 4 km cell) 95% Winter Utilization 200 750 Distribution 350 1,200 500

PAGE 9 Analytical Methods, Continued

Continued from page 8 Several limitations of persistent hotspot “correct” for undercounting of animals also be noted that a causal relationship maps should be noted. First, they do not farther from the transect line. is not explicitly assumed in the model, indicate the full range of species’ habitat Te modeling approaches in this study and that correlations between wildlife use within the study area. Hotspots also use environmental covariates distributions and covariate data may may occur in areas that were not to predict abundance or relative not be direct or causal in nature. Initial surveyed (and are thus not represented abundance. Correlating survey data models for this study incorporated in these maps). Second, individual with remotely sensed environmental either boat or aerial survey data, but grid cell “persistence” values should be data from satellites allows us to make researchers at North Carolina State interpreted with caution, as this analysis predictions in areas or during time University are developing predictive was intended to identify patterns at a periods that were not directly surveyed. models that integrate both survey data regional scale. Distribution models are chosen to ft sets to provide a more comprehensive view of wildlife distributions. preDictive MoDels the observed abundance data (Gardner et al. 2008, Zipkin et al. 2010), similarly Generalized Linear Models: Seabirds Several statistical modeling approaches to ftting a distance curve (Figure 3). are used in this study, including Project collaborators at North Carolina generalized linear models (GLMs) and Te use of models to make predictions State University frst focused on the generalized additive models (GAMs). requires the assumption that development of a community distance Tese modeling frameworks are correlations have consistent causal sampling (CDS) GLM for seabirds frequently used in ecological research mechanisms, so that relationships from the boat survey data. Tis is (Guisan et al. 2002), and can incorporate between wildlife distributions and a novel multi-species approach for environmental data (covariates), efort covariates will remain consistent even estimating seabird abundance and corrections, and observation biases into in locations or time periods where distributions. Like similar models, it their structure. Tese approaches are surveys did not actually occur. It should explicitly estimates detection as well as used to make predictions about where animals occur and what environmental EXAMPLE DETECTION FUNCTION 1.0 factors infuence their distribution or abundance (Mordecai et al. 2011). 0.8 “Detection probability” in modeling is ty the probability of observing an animal 0.6 given that it is present. Tere are several ion Probabili detection biases implicit in survey ct 0.4 te methods. For example, in boat-based De surveys, the probability of detecting an 0.2 animal decreases with its distance from the observer (Figure 3). 0.0 0 100 200 300 400 500 600 Because we recorded the distance and Perpendicular Distance (meters) angle at which each animal was seen from the boat, modelers were able to Figure 3: Detection function for Bottlenose Dolphins from boat surveys (in summer). A ft a detection curve to survey data, detection probability of 1.0 (y-axis) indicates the 100% probability of an observer spotting an indicating the estimated detection animal that is present in the transect strip. Te probability of detection decreases with distance of the animal from the observer (x-axis), with <10% probability of spotting a dolphin at 500 m. probability for an animal at a specifed Actual survey data are summarized by tan bars; the distance curve, ftted to these data, indicates distance. Tis curve can be used to the estimated detection probability for an animal at a specifed strip width.

PAGE 10 • ANALYTICAL METHODS abundance parameters for each species. HOW TO INTERPRET CHARTS ILLUSTRATING TEMPORAL CHANGES However, sharing information across species allows us to make inferences about rare species that often have too few observations to be analyzed separately. Building on the CDS model, we incorporated remotely collected environmental covariate data into the hierarchical modeling structure to develop geospatial models that predict Bar charts, as in the example above, were developed to summarize temporal patterns of relative abundance for species or taxonomic groups in the study area. For each seabird abundance throughout the survey method, we summed efort-corrected total counts of individuals by two-month study area by season (Figure 2C). time period, so each period included data from two to four surveys. Boat (, left) and aerial (, right) bars are placed side by side to illustrate diferences in detection and/or Generalized Additive Models: identifcation between the two survey methods. Cetaceans and Sea Turtles GAMs are extensions of GLMs that use Larger bars represent higher efort-corrected counts of a species or group. Relative bar smoothing functions to improve model sizes are comparable among individual species, but not between species and broader taxonomic groups, as species and group percentiles were calculated separately. Te ft. Tese models can be particularly light blue horizontal center line provides a reference point for comparison. useful for situations with complex, nonlinear relationships between predictor and response variables to estimate relative spatial use during et al. 2007). We used these movement (Guisan et al. 2002, Hastie and Tibshirani specifed time intervals. Random patterns to identify the environmental 1990). Collaborators at Duke University samples of point locations from conditions correlated with more intensive developed GAMs with remotely tagged birds were pooled to create a resource use. collected environmental covariate composite utilization distribution map It is important to keep in mind that data to predict sea turtle densities for all wintering individuals. Utilization these distributions represent a small and Bottlenose Dolphin pod densities distributions illustrate the estimated subset of individuals from the broader throughout the study area by season. core use areas, where tagged individuals population, and could potentially be spent the majority (>50%) of their time, teleMetry DAtA AnAlyses afected by animals’ capture location and broader utilization distributions, in or other factors. However, telemetry Satellite telemetry provides data which individuals spent most (>95%) data can provide useful information on on the individual locations (and, by of their time (Figure 2D). the habitat use and likely movements inference, movements) of animals. Tese In addition to utilization distributions, of animals in relation to environmental temporally explicit movement data we used state-space models to identify conditions. are not feasible via surveys, and can be more detailed behavioral patterns As mentioned previously, telemetry aggregated to identify species-specifc in Northern Gannets. Fast, straight patterns in habitat use and movement data presented in this report are movements are generally thought to preliminary (drawn from the frst two behaviors in relation to changing indicate transient behavior, while slower, environmental conditions. years of a four-year study) and results circular movements indicate that the will be updated as research continues. Kernel density estimation involves animal is using resources on or under the the use of point data from telemetry water (perhaps foraging or resting; Jonsen

PAGE 11 Comparing Boat and Aerial Surveys

ogether, boat-based surveys and DigitAl viDeo AeriAl surveys constituting 45% of all observations T high resolution digital video aerial A total of 107,003 animals were (excluding some schools where animals surveys provided a more complete observed in 15 aerial surveys, including could not be individually counted). understanding of the ecology of the more than 46,000 birds and 60,000 Fish were the next most commonly mid-Atlantic than either method aquatic animals. At least 48 species of observed aquatic animals, including achieved alone. birds and 19 species of aquatic animals large groups of forage fshes. Te ideal survey approach will depend were represented. Te greatest numbers Dolphins represented 2% of the on project goals and the particular of animals were observed in March, July, dataset, with Bottlenose Dolphins characteristics of a given study area, but and September, due to peaks in seabird most commonly identifed to species. may involve a combination of these and ray observations. A notable number of sea turtles were complementary survey methods. Scoters were the most abundant birds observed (1.63%, or 1,748 individuals) observed (20% of all observations), in warmer months. boAt-bAseD surveys followed by Northern Gannets (7% of A total of 64,462 animals were observed the dataset) and loons (5%), all pre- coMpAring survey MethoDs in 16 boat surveys, including more than dominantly observed in winter and Te two survey methods generally 62,000 birds and 1,500 aquatic animals spring. A variety of gull and tern species showed similar species-habitat (marine mammals, sea turtles, sharks, were observed throughout the year (4%). relationships, though there were clear and fshes). At least 97 bird species diferences in detectability between the Large numbers of animals were and 12 species of aquatic animals were two survey types (Figure 4). represented. Te greatest numbers of observed below the water’s surface Boat survey observers recorded larger animals were observed in December during digital video aerial surveys. numbers of birds per unit area, likely and January, when large focks of birds Rays were the most common taxon, wintered in the study area. 5 Wintering scoters, including Black

Scoter, White-winged Scoter, and Surf 4.5 Boat Scoter, were the most abundant avian 4 Aerial group observed in boat surveys (34% of 3.5 2 all observations). Various species of gulls 3 and terns were observed throughout r km pe the year, and collectively were the next 2.5 most abundant group (23%), followed 2 by wintering and migrating Northern Animals 1.5 Gannets (22%). Te boat survey dataset 1 also included observations of almost 0.5 600 shorebirds and 200 landbirds. 0 Northern Gulls & Loons WaDucksterfowl & Toothed Fish & Rays Sea Turtles Bottlenose Dolphins were the most Gannets Terns Geese Whales Sharks common aquatic taxon observed (1.4% of the dataset), along with sea Figure 4: Comparison of total efort-corrected boat and aerial survey counts across all surveys for turtles (0.18%, or 114 individuals), selected taxa. Aerial densities were calculated using actual transect strip widths, and boat densities were calculated using estimated strip widths for each taxon. Efective boat transect strip widths predominantly in warmer months. were calculated for avian taxa based on their efective half strip widths, and for aquatic taxa based on their median distance of observations from the boat. Observations of groups that were not individually counted or identifed (e.g., some fsh and ray schools) are excluded from this fgure.

PAGE 12 • RESULTS ,

Figure 5: Boat–aerial survey comparison. Te diagram shows the felds of view available during boat surveys and digital video aerial surveys. Te combined strip width for all four video cameras was 200 m; the boat transect had an intended minimum strip width of 300 m, although observations of animals were made up to 1,000 m from the vessel. Apart from the experimental comparison (see below), boat and plane followed diferent transect lines (Figure 1). because some species were more to species from the air, however (27% data, and many more individuals were reliably detected and identifed from boat, 52% aerial). Scoters are known to detected from the air. the boat. be disturbed by boats, which may have coMpArison stuDy HiDef Aerial Surveying’s digital aerial pushed them out of range for defnitive surveys proved to be highly efective at identifcation by boat-based observers To understand the efectiveness of detecting many aquatic taxa, including in many cases. Excluding scoters, the digital video aerial surveys and the sharks, fsh, and rays (Figure 4). While rate of defnitive identifcations during specifc challenges faced in employing some of these animals were also boat surveys was 97%. the technique in North America, we observed in the boat surveys, the aerial Te relatively low rate of species experimentally compared results from surveys provided an excellent platform identifcations in aerial video was likely simultaneous boat and digital video for detecting and identifying animals due in part to variation in image quality, aerial surveys of of Virginia in 2013 within the upper reaches of the water as well as difculties diferentiating (Figure 5). column that were not easily observed small species with subtle distinguishing Te two methods each had clear from the boat. features. Video reviewers also had strengths and weaknesses. Overall, the In addition to detection of animals, difculty diferentiating Common boat-based survey provided better there were diferences between survey Loons and Red-throated Loons due species identifcation for many species types in observers’ ability to identify to the overlapping body sizes of birds groups than the digital aerial survey, animals. Only 45% of aerial observations wintering in the region (Gray et al. but the boat also caused substantial were identifed to species, as compared 2014). Identifcation rates were lower disturbance for some taxa, potentially to 72% of boat observations. Scoters, for sea turtles from the air than from complicating identifcation eforts and the most common avian group in the boat (21% aerial, 91% boat), but abundance estimation. surveys, were more often identifed more species were observed in aerial

PAGE 13 Geographic and Temporal Patterns

he mid-Atlantic region provides important habitat for T marine wildlife throughout the year. Each season in our study brought a unique shift in habitat characteristics, and with it a new array of species reliant on the specifc resources available (Figure 6).

seAsonAl pAtterns fall: Seabird species composition shifted as summer residents, such as terns, shearwaters, and storm-petrels, migrated south to more productive waters and milder climes. Winter residents, such as scoters, Northern Gannets, and Red-throated Loons, migrated into the study area from breeding grounds farther north or inland. In general, seabirds tended to be more associated with nearshore habitats in the fall as compared to winter and spring. Songbirds, shorebirds, Eastern Red Bats, and Peregrine Falcons, among other species, migrated over open waters across the Outer Continental Shelf. Cownose Rays were observed in dense migratory aggregations in early fall. Large schools of forage fsh were also observed along the coast. Sea turtles and Bottlenose Dolphins remained in the region through late fall, while Common Dolphins largely arrived in the area in November. Winter: Wintering seabirds generally occupied habitat throughout the study area, although distribution patterns varied among species. Northern Gannets tended to be broadly distributed across the study area, for example, while scoters were most concentrated in nearshore regions adjacent to the bays. Alcids (Atlantic Pufns, Razorbills, Dovekies, and murres) were observed in small numbers throughout the study area. Baleen whales were most commonly observed during this season. Dolphin species composition shifted from Bottlenose Dolphins, which were commonly observed in Figure 6: Temporal changes in relative abundance for major the spring, summer, and fall, to Common Dolphins, which taxonomic groups. Data are from the boat-based surveys (, left) were most abundant in the winter. and high resolution digital video aerial surveys (, right) conducted in 2012-2014. Species included in each category are listed in Williams et spring: Wintering seabirds departed the study area in spring, al. (2015). Labels refer to seasons in the Northern Hemisphere. while summer resident seabirds arrived. Bottlenose Dolphins and a variety of sea turtle species also began using the *Forage fsh were counted as schools, not as individuals, unlike the other animal groups. study area. We observed songbirds, shorebirds, and raptors migrating over open waters across the region.

PAGE 14 • RESULTS PERSISTENT SPECIES RICHNESS HOTSPOTS PERSISTENT ABUNDANCE HOTSPOTS

Wind Energy Areas Wind Energy Areas Species Richness Hotspot Overall Abundance Persistence Hotspot Persistence Never a Hotspot Never a Hotspot <75 th Percentile <75 th Percentile 75-85th Percentile 75-85th Percentile 85-95th Percentile 85-95th Percentile 95th Percentile 95th Percentile

Figure 7: Persistent species richness hotspots—areas with consistently Figure 8: Persistent abundance hotspots—areas with consistently greater numbers of species across all surveys. greater numbers of individuals across all taxa and surveys. summer: Breeding seabirds, such as Common Terns, were south of the bay mouths (roughly within 30 km of shore) observed foraging near shore and near the mouths of the consistently showed high species diversity and relative bays, while nonbreeding species, such as Wilson’s Storm- abundance of animals across all taxa observed in this study Petrels, tended to be more broadly distributed across the (Figures 7 and 8). Areas offshore of Maryland, where high- study area. Across all species, seabirds were generally more density surveys were conducted in nearshore areas, also associated with nearshore areas during summer months. showed high diversity and relative abundance. Large numbers of Cownose Rays migrated through the study Tese areas were likely attractive to a wide variety of animals area, and sea turtles and Bottlenose Dolphins were most due to consistently high primary productivity relative to abundant during the summer. the broader study area. Tis primary productivity forms the persistent pAtterns base of the pelagic food chain on which nearly all species observed during this study rely; thus, areas near the mouths Areas near the mouths of Chesapeake Bay and Delaware Bay of the bays likely provided important and reliable foraging remained important for many diferent taxa throughout the habitat for a multitude of species year-round. year. Specifcally, nearshore waters adjacent to and directly

PPAAGGE 15E 15 [CASE STUDY] Scoters

coters are medium-sized sea ducks that breed near commercial shellfsh harvests (Anderson et al. 2015, BirdLife S lakes or slow-moving rivers in the boreal forest and International 2015). taiga from Labrador to Alaska. Breeding pairs are formed Related sea duck species have demonstrated avoidance in the wintering areas, which are located mostly in shallow at several ofshore wind facilities in Europe (Larsen and bays and estuaries in temperate regions along the east and Guillemette 2007, Petersen and Fox 2007), causing efective west coasts of North America. Tey are known to migrate in habitat loss of feeding or roosting areas. Tere is some focks, fying high over land between breeding and wintering evidence for habituation or re-initiation of habitat use sites, and stopping on inland lakes to rest and molt several years after construction (possibly in relation to (Kaufman 1996, Anderson et al. 2015). changes in prey distributions; Petersen and Fox 2007). Scoters forage exclusively by diving and swimming Scoters are also known to be disturbed by vessel activity, underwater. While on the breeding grounds, they primarily with displacement efects varying by species (Schwemmer et consume aquatic invertebrates as well as some plant al. 2014, Williams et al. 2015). material (Kaufman 1996, Anderson et al. 2015). During the winter, scoters predominately forage on mollusks in shallow nearshore waters with sandy substrates (Stott and Olson 1973, Anderson et al. 2015). Te Surf Scoter and White-winged Scoter both have a Conservation Status of Least Concern from the International Union for Conservation of Nature (IUCN) due to their large population sizes and broad ranges, despite the fact that the population trends for both species indicate a decline (BirdLife International 2015). Te Black Scoter is listed as Near Treatened due to suspected recent population declines (BirdLife International 2015). Treats to these species include habitat degradation, oil spills, human disturbance (such as disturbance from high-speed ferries) and

conteXt } Based on European studies, scoters may be displaced from areas around ofshore wind facilities for some Wind Energy Areas Predicted Abundance (number period of years following construction. of scoters per 4 km cell) 650 9,900 tAKe hoMe MessAges 2,200 17,000 } Telemetry and survey data for scoters indicated strong 4,600 nearshore distribution patterns, which held true across species and were largely driven by water depth. } In the mid-Atlantic, construction and operation of ofshore wind energy facilities (and associated vessel Figure 9: Predicted abundance of scoters (including White-winged trafc) are most likely to cause localized displacement Scoter, Black Scoter, and Surf Scoter) for a given day during winter of of scoters from high-quality feeding areas if these 2012-13. Model outputs combine observation data from boat-based activities occur within about 20 km from shore. surveys with environmental covariate data to predict scoter abundance across the study area. Te highest abundance of scoters was predicted to occur close to shore and in regions with high primary productivity.

PAGE 16 • SCOTERS stuDy finDings } Scoters were the most abundant avian genus observed over the course of the study, with 43,339 individuals observed (25% of all wildlife observations). Te majority of scoter observations were not identifed to species, but observations included at least 30% Black Scoters, 9% Surf Scoters, and 0.001% White-winged Scoters. } Scoters were most abundant in the mid-Atlantic between October and May (Figure 10). Satellite tagged Surf Scoters spent an average of 133 days in the region during winter, generally arriving in the study area between mid-October and mid-December. } Satellite tagged Surf Scoters departed the study area between early January and mid-May, and followed the coastline north to stage briefy in the St. Lawrence Estuary before continuing on to breeding and molting areas in northern Canada. Tis route was reversed during fall migration as birds returned to wintering areas in or near the mid-Atlantic. } Large aggregations of scoters were most consistently Wind Energy Areas Capture Locations observed at the mouth of Chesapeake Bay and just south l 50% Utilization Distribution of the mouth of Delaware Bay, within roughly 30 km of (core use area) shore (Figure 9). Satellite tagged Surf Scoters spent >50% 95% Utilization Distribution of their time in the study area within or at the mouths of the bays (Figure 11). } Core use areas identifed by satellite telemetry of Surf Scoters may have been heavily infuenced by capture locations. However, survey and telemetry data both Figure 11: Winter utilization distribution for satellite-tagged Surf showed that scoters used habitat characterized by shallow Scoters (n=101; data are preliminary). Additional capture locations in Labrador, Québec, and New Brunswick are not shown on this map. nearshore waters with high primary productivity. } Te rotor-swept zone for ofshore wind turbines may include altitudes between approximately 20 m and 200 m (Willmott et al. 2013). In the digital aerial survey video, 77% of fying scoters (all species) were below this range; 19% were between 20 m and 200 m.

Figure 10: Temporal changes in relative abundance for Surf Scoters. Tis chart shows the year-round relative abundance of Surf Scoters observed by boat () and video aerial surveys () in two-month periods. Surf Scoters were most commonly observed in winter and none were observed in May-August. Male Surf Scoter with implanted satellite tag (note antenna visible above tail).

PAGE 17 [CASE STUDY] Red-throated Loons

he Red-throated Loon is the most widespread member population size, despite population trends indicating a decline T of the loon family, with a circumpolar distribution. across much of the species’ range (Barr et al. 2000, BirdLife Similar to larger loon species, Red-throated Loons are long- International 2015). In the U.S., fsheries are the major source lived (25-30 years) and experience high adult survival (Barr of adult mortality, via bycatch of birds in nets (Barr et al. et al. 2000, Schmutz 2014). 2000). Red-throated Loons have exhibited long-term and In North America, these loons breed primarily on freshwater possibly permanent displacement from areas around ofshore or brackish ponds and small lakes on the Arctic tundra. wind energy facilities in Europe (Petersen and Fox 2007, Tey likely form monogamous pairs, exhibiting elaborate Langston 2013), making disturbance and efective habitat loss courtship rituals (Kaufman 1996), and often returning to the the primary concern for this species in relation to ofshore same nest site over multiple years. Young move onto the development (Furness et al. 2013). water one day after hatching; both parents feed the young, and chicks can fy after seven weeks (Kaufman 1996). Tey spend the winter in temperate coastal ocean waters, and are known to migrate singly or in small groups within a few kilometers of the coast (Barr et al. 2000, Kaufman 1996). Red-throated Loons swim at the surface with their heads partially submerged to search for prey before diving. Tey primarily eat fsh, including cod and herring, on their wintering grounds, and char, trout, and salmon on the breeding grounds, in addition to aquatic invertebrates and the occasional frog (Kaufman 1996). Many Red-throated Loons forage in marine habitats year-round, the only loon species to do so (Barr et al. 2000, Kaufman 1996). Te Red-throated Loon has an IUCN Conservation Status of Least Concern due to the species’ broad range and large

conteXt Wind Energy Areas } European studies indicate that Red-throated Loons Predicted Abundance (number of loons per 4 km cell) experience long-term, localized disturbance and 22 170 displacement from wind energy facilities, as well as 60 400 related activities such as vessel trafc. 100 tAKe hoMe MessAges } Te greatest overlap between Red-throated Loon distributions and mid-Atlantic WEAs occurred during migration periods, when movements tended to be Figure 12: Predicted abundance of Red-throated Loons for a given located farther ofshore. day in winter of 2013-14 (Nov.-Jan.). Model outputs combine observation data from boat-based surveys with environmental } In winter, Red-throated Loons were most commonly covariate data to predict Red-throated Loon abundance across the study area. Te highest abundance of Red-throated Loons was located west of the WEAs. predicted to occur close to shore, and in regions with cooler water and high primary productivity.

PAGE 18 • RED-THROATED LOONS stuDy finDings } During boat and aerial surveys, 1,770 Red-throated Loons were observed (1% of all wildlife observations from surveys). In many cases, however, Red-throated Loons and Common Loons could not be distinguished in digital video aerial surveys. } Red-throated Loons were most commonly observed between November and May (Figure 13). } During surveys, Red-throated Loons were most consistently observed within approximately 20 km of shore (Figure 12). Tis difered from Common Loons, which were more widely distributed across the study area in winter. } Telemetry data showed that Red-throated Loons preferentially used shallow nearshore waters over fat sandy substrates while wintering in the mid-Atlantic region, particularly around the mouth of Chesapeake Bay and south along the Virginia and North Carolina coasts,

close to original capture locations (Figure 14). Modeled Wind Energy Areas boat survey data indicated that proximity to shore was l Capture Locations the strongest predictor of Red-throated Loon abundance, 50% Utilization Distribution followed by relatively cold sea surface temperature, and (core use area) primary productivity (low in spring, high in winter). 95% Utilization Distribution } Satellite tagged individuals left the study area between late March and early May, and largely followed the coast north to breeding grounds. Greatest ofshore movements occurred during this departure from the study area. During Figure 14: Winter utilization distribution for satellite-tagged Red- fall migration, loons arrived in the study area between throated Loons (n=23; data are preliminary). mid-November and late December. Most individuals stopped over in Hudson Bay, and then moved either to the Gulf of St. Lawrence or to the Great Lakes before fying to Delaware Bay and following the coastline south. } Te rotor-swept zone for ofshore wind turbines may include altitudes between approximately 20 m and 200 m (Willmott et al. 2013). In the digital aerial survey video, 70% of flying loons (both species) were below this range; 28% were between 20 m and 200 m.

Red-throated Loon in winter plumage with implanted satellite tag Temporal changes in relative abundance for Figure 13: (antenna visible above tail). Red-throated Loons. Tis chart shows the year-round relative abundance of Red-throated Loons observed by boat () and video aerial surveys () in two-month periods. Red-throated Loons were most commonly observed in winter. No individuals were observed in July-August by either survey method.

PAGE 19 [CASE STUDY] Northern Gannets

orthern Gannets are the largest seabirds to breed in its exceptionally large range. Te North American breeding N the North Atlantic Ocean, wandering widely over population, which represents 27% of the global population, continental shelf waters. Tey forage on surface-schooling has experienced a healthy rate of growth since 1984 (4.4% per fshes in dramatic plunging dives from the sky; they also year), although that appears to have slowed in recent years dive directly from the ocean’s surface (Garthe et al. 2000, (Chardine et al. 2013). Montevecchi 2007). Te species is vulnerable to mortality from oil spills and Like many seabirds, Northern Gannets are long-lived (20+ fsheries bycatch. Northern Gannets have displayed years) and exhibit high adult survival. Tey begin breeding at avoidance of or displacement from some ofshore wind around fve years of age, nesting in dense colonies on remote facilities in Europe (Lindeboom et al. 2011, Vanermen et al. rocky islands and sea stacks. Females lay only one egg per year 2015) and are also considered to be at high risk of collision and it requires the constant eforts of both parents to raise mortality (Furness et al. 2013). the chick. Adults can fy hundreds of kilometers from the nest in search of prey (Garthe et al. 2007). In the Western Hemisphere, Northern Gannets breed at six colonies in southeastern Canada—three in the Gulf of St. Lawrence, Québec, and three of the eastern and southern coasts of Newfoundland (Nelson 1978, Mowbray 2002). On migration, they move widely down the east coast of North America to winter in the shelf waters of the mid-Atlantic region, the South Atlantic Bight, and the northern Gulf of Mexico (Nelson 1978, Fifield et al. 2014). Te Northern Gannet has an IUCN Conservation Status of Least Concern due to its relatively large population size and

conteXt } European studies indicate a range of possible efects of ofshore wind development on Northern Gannets, including collision mortality and displacement. tAKe hoMe MessAges Wind Energy Areas Predicted Abundance (number } Te broad-scale distribution and movements of Northern of gannets per 4 km cell) Gannets during winter may increase the likelihood that 200 750 350 1,200 individuals would be in the vicinity of ofshore wind 500 developments repeatedly throughout the season. } Important foraging and habitat use areas appear to be defned by a wide variety of habitat characteristics. Construction and operations of ofshore wind energy Figure 15: Predicted abundance of Northern Gannets for a given day in facilities, including associated vessel trafc, could winter of 2013-14. Tis model used observation data from boat-based potentially cause localized displacement anywhere in the surveys and remotely sensed environmental covariate data to predict study area, but this is most likely within about 30-40 km abundance across the study area. Te highest abundance of Northern of shore where Northern Gannets were more abundant. Gannets was predicted to occur closer to shore in regions with high primary productivity.

PAGE 20 • NORTHERN GANNETS stuDy finDings } 21,345 Northern Gannets were observed during the boat and aerial surveys (17% of all wildlife observations). } Northern Gannets were most commonly observed in the study area between October and April (Figure 17). } 35 Northern Gannets were captured and satellite tagged in the study area during the winters of 2012 and 2013. } Northern Gannet migration was highly asynchronous and widely dispersed across the continental shelf. In general, individuals worked their way up the east coast in March- April, often pausing in large bays. In the fall, birds left the breeding colonies in September and either followed the coast or took a more direct route south by following the continental shelf edge. Tey arrived in the wintering area mostly in November-December. } Individual Northern Gannets roamed widely across the region in winter and often visited several areas, showing low site fdelity. Te general locations used by wintering Wind Energy Areas Northern Gannets, however, were relatively consistent l Capture Locations across years. 50% Utilization Distribution } Te rotor-swept zone for ofshore wind turbines may (core use area) include altitudes between approximately 20 m and 200 m 95% Utilization Distribution (Willmott et al. 2013). In the digital aerial survey video, 55% of fying Northern Gannets were below this range; 43% were between 20 m and 200 m. } Northern Gannets were most consistently observed Figure 16: Winter utilization distribution of Northern Gannets in nearshore waters along the length of the study area tracked via satellite telemetry (n=17; data are preliminary). (Figure 15), but satellite data also showed that they regularly ranged up to 50 km out onto the continental shelf (Figure 16). } Telemetry and survey data showed that Northern Gannets in the mid-Atlantic generally used habitat characterized by highly productive, shallower waters and lower sea surface salinities, especially areas closer to shore and over fne sandy substrate. } Northern Gannet behavioral patterns indicated that they Figure 17: Temporal changes in relative abundance for foraged roughly 67% of the time during winter. Within Northern Gannets. Tis chart shows the year-round relative the habitat use areas described above, birds preferred to abundance of Northern Gannets observed by boat () and forage in relatively deeper waters, and in areas with high video aerial surveys () in two-month periods. Gannets were densities of sea surface temperature fronts (e.g., boundary observed year-round, but were present in greatest numbers during winter. areas between water masses of diferent temperatures).

PPPAAAGGGE 21E 21 [CASE STUDY] Cetaceans

etaceans include two major types of aquatic Right Whale, among the rarest of all marine mammals, is of C mammals, both of which breathe air and birth live particular interest to regulators, and very little information young. Toothed whales, such as dolphins and porpoises, exists on their movements and habitat use in the mid-Atlantic. have rows of teeth and eat fsh and other large prey. Tey use Acoustic disturbance from construction and operation of sound to sense objects around them (“echolocation”). Baleen ofshore wind facilities may afect all marine mammals (Bergstrm whales, including many of the large endangered whale species, et al. 2014). European studies have shown displacement of Harbor eat krill, copepods, and small fsh by fltering them through Porpoises during construction (Teilmann et al. 2006, Tomsen bristles or plates on their jaws. While baleen whales do not et al. 2006), though displacement during operations has been echolocate, they do use sound for communication. variable in duration and degree (Teilmann and Carstensen 2012, Tere are two genetically distinct ecotypes of Bottlenose Scheidat et al. 2011). Dolphins in the western North Atlantic. Te “ofshore” Tere is evidence for disturbance of large whales by other ecotype inhabits colder, deeper waters on the Outer anthropogenic activities (e.g., McCauley et al. 2000, Tyack et al. Continental Shelf and shelf edge, while “coastal” dolphins 2011), but no information is available about their interactions occur in more nearshore areas (Waring et al. 2014). In the with ofshore wind facilities, as large whales are not common mid-Atlantic, the coastal ecotype is thought to include at in European waters where development has occurred to date. least two diferent migratory stocks, or subpopulations, whose migration may be partially related to water temperature (Waring et al. 2014). Many other cetaceans also migrate seasonally between wintering and breeding grounds. Migratory routes are poorly defned for many species, though several are known to migrate through the mid-Atlantic region. All cetaceans that occur in the U.S. are protected under the Marine Mammal Protection Act. Te North Atlantic

conteXt } Ofshore wind energy facilities present signifcant increases in underwater noise during construction, which may afect all marine mammals. Our current lack of understanding of the hazards posed to baleen whales Mid-Atlantic Study Area by ofshore wind energy development make these Wind Energy Areas species a particular concern for regulators in the U.S. Aerial Survey Transects Boat Survey Transects tAKe hoMe MessAges l Fin Whale } Relatively little is known about migratory routes for many l Humpback Whale rare whale species in the mid-Atlantic, although data l Minke Whale from this and other studies are beginning to fll this gap. l Right Whale } Bottlenose Dolphins may be most likely to be exposed l Sei Whale to development activities during summer and in the l Unidentifed Whale northern end of the study area, as well as in western areas of the mid-Atlantic WEAs in spring and fall. Common Dolphins have a more ofshore distribution and may be particularly abundant in WEAs during winter Figure 18: Large whale observations (Mysticeti) from boat and and spring. video aerial surveys (March 2012-May 2014). Aerial surveys were also conducted at high transect densities within certain areas (Figure 1). PAGE 22 • CETACEANS spring (Mar–May) suMMer (Jun–Aug) fAll (sep–nov)

Wind Energy Areas Predicted Number of Pods (per 4 km cell) 1 9 3 15 5

Figure 19: Predicted numbers of Bottlenose Dolphin pods by season, based on two years of boat survey data (2012-2014). Models used observation data from boat-based surveys and remotely sensed environmental covariate data to predict numbers of pods across the study area. Strong nearshore distributions were predicted in spring and fall, likely driven by the species’ resident coastal ecotype. Dolphins were predicted to be more evenly distributed longitudinally in summer.

Figure 20: Temporal changes in relative abundance of dolphins from surveys. Tis chart illustrates the relative abundance of dolphins observed by boat () and video aerial Bottlenose Dolphin surveys () in two-month periods. Bottlenose Dolphins were most common in the spring, summer, and fall, while Common Dolphins were most abundant from late fall to early spring. Common Dolphin

stuDy finDings } We observed 3,289 marine mammals in boat and aerial } Cold-tolerant Common Dolphins were most frequently surveys. Te majority (99%) were dolphins and porpoises observed in ofshore areas in winter and early spring. (from at least fve species), but the data included 51 } Distance from shore, primary productivity, and sea baleen whales, also from at least fve species. surface temperature were important predictors of } We observed nine North Atlantic Right Whales Bottlenose Dolphin distributions. Tis is possibly because (Figure 18), which is notable for this species in the of their use of areas of high productivity for feeding, mid-Atlantic region. We also observed endangered particularly in and around the mouths of Chesapeake Humpback Whales and Fin Whales. Bay and Delaware Bay, and their temperature-related } Baleen whales were most frequently observed in winter, migratory behaviors. although present in small numbers year-round (Figure 6). } Many Bottlenose Dolphins may have been residents } Bottlenose Dolphins, the most abundant delphinid in from coastal stocks, leading to the nearshore distribution surveys, were observed primarily in spring, summer, and patterns we observed. A more robust density gradient fall (Figure 20). Models suggest minimal presence of from west to east was observed in summer (Figure 19), Bottlenose Dolphins within mid-Atlantic WEAs during possibly due to an infux of transient populations during cooler months. the warmer period.

PPAAGGE 23E 23 [CASE STUDY] Sea Turtles

ea turtles are long-lived animals with a world-wide Te mid-Atlantic region has large populations of a high S oceanic distribution. Five species occur in our study area: diversity of turtles, but there are many existing threats that the Loggerhead, Leatherback, Kemp’s Ridley, Hawksbill, and could cause population declines (Wallace et al. 2011). Tese Green Sea Turtles. All are listed as threatened or endangered include mortality from bycatch in fshing nets (Murray under the Endangered Species Act. and Orphanides 2013), collisions with vessels, especially Female sea turtles lay clutches of tens to hundreds of eggs those traveling at high speeds (Hazel et al. 2007), loss of that they bury in sandy beach nests. After an incubation nesting habitat to coastal development, and disturbance or period, tiny hatchlings emerge and head to the sea, where destruction of nests by humans or other animals (Wallace they forage in foating sargassum seaweed mats and travel et al. 2011). thousands of miles ofshore as they grow (Mansfeld et al. In addition to vessel trafc, potential concerns from ofshore 2014). Tey take many years to reach maturity, and can grow wind energy development include the efects of noise and to be enormous; adult Leatherbacks grow up to 2 m (6.5 feet) vibrations from seismic profling, pile driving, and trenching and 900 kg (2,000 lbs). (Read 2013). Adults migrate seasonally, with some migrations up to 10,000 km (James et al. 2005). Teir body temperatures vary considerably with their environment, limiting them to waters in specific temperature ranges (Gardner et al. 2008, Epperly et al. 1995). Sea turtle foraging strategies are varied: Leatherbacks dive up to 1,000 m in search of jellyfish (Eckert et al. 1988), while herbivorous Green Sea Turtles graze on seagrasses on shallow sea foors.

conteXt } Te efects of ofshore wind development on sea turtles remain poorly understood, most notably in relation to noise and the potential for collisions with vessels.

tAKe hoMe MessAges } Tere may be species-specifc diferences in habitat Wind Energy Areas use or movements that were not distinguishable in Sea Turtle Hotspot Persistence this study. Never a Hotspot th } Digital aerial surveys seem to have higher detection <75 Percentile 75-95th Percentile rates of sea turtles than other survey approaches, but 95th Percentile application of newer technologies with improved species diferentiation is needed. } Construction of ofshore wind energy facilities in mid-Atlantic WEAs is likely to occur in warmer months Figure 21: Persistent abundance hotspots for turtles (Testudines spp.) and sea turtles will be present during these periods. observed in video aerial surveys, March 2012–May 2014. Data are split into only three persistence classes as the 75th and 85th percentile of persistence fell at the same value.

PAGE 24 • SEA TURTLES spring (Mar–May) suMMer (Jun–Aug) fAll (sep–nov)

Wind Energy Areas Predicted Abundance (number of turtles per 4 km cell) 2 22 8 28 15

Figure 22: Predicted relative abundance of sea turtles by season, based on two years of digital video aerial survey data (2012–2014). Models used observation data from aerial surveys and remotely sensed environmental covariate data to predict abundance across the study area. Turtles had a dense southerly distribution in the spring, and were dispersed more broadly in the summer. By the fall, they were distributed fairly evenly across the mid-Atlantic in ofshore areas.

stuDy finDings } There were 1,862 sea turtles observed in boat and aerial surveys (1.5% of all wildlife observations). } Turtles were more frequently observed in digital aerial surveys than in boat surveys, likely in part because they could be detected even when fully submerged. Because of these high detection rates, we used only aerial data Figure 23: Temporal changes in relative abundance for sea to identify persistent hotspots (Figure 21) and develop turtles. Tis chart illustrates the relative abundance of sea predictive models of sea turtle distributions (Figure 22). turtles observed by boat () and video aerial surveys () in } We detected all fve species of sea turtles that occur in two-month periods. Sea turtles were most common in the our study area. Loggerhead and Leatherback Sea Turtles early spring, summer, and fall, and were more commonly were most frequently observed. observed in aerial surveys. } Sea turtles were most abundant from May to October (Figure 23), with very few individuals present in winter. } Models predicted highest turtle densities in areas far from shore of of Virginia in spring, and in areas with warmer sea surface temperatures (Figure 22). In summer, sea turtles were predicted to be distributed across a broader range, as females moved to shore to lay eggs on sandy beaches. Sea turtles were most widely distributed across the study area in fall, predominantly in ofshore areas. } In addition to water temperature, primary productivity and distance from shore were important infuences on sea turtle densities. } Tere was substantial overlap between sea turtle distributions and areas of planned ofshore wind energy development, particularly in the southern mid-Atlantic Surfacing Loggerhead Turtle observed during boat-based surveys. (Figure 21).

PAGE 25 [CASE STUDY] Migratory Movements

easonal variation in the environment has led to the S development of migratory behavior in many taxa, in conteXt which they undertake seasonal long-distance movements } Te consequences of interactions between migratory between ecosystems. Te migratory journey can take many wildlife and ofshore wind facilities are unclear. Some weeks and is often an arduous and risky undertaking. Migrants species may have increased collision risk. Others may face challenges on their seasonal routes, including inclement have increased energetic expenditures from avoidance weather, lack of food, and hungry predators. during migratory movements, although these efects will depend on the scale and number of ofshore Migration is a difcult phenomenon to study, particularly wind facilities along a migration route. in ofshore areas, but a wide range of taxa move over or through open water habitats during migration. If we are to tAKe hoMe MessAges understand the potential efects of ofshore activities on } Our research suggests that a wide variety of animals wildlife populations, we must determine when and where migrate through areas that have been proposed for this phenomenon occurs. ofshore wind energy development in the mid-Atlantic We employed several methods to document the timing and region. Additional research on migrant populations routes of animal migration through the mid-Atlantic region, may be warranted for sites proposed for development including analysis of weather radar (Next Generation Radar, or other ofshore activities. or NEXRAD) data, the use of avian passive acoustic recorders, satellite telemetry, and boat and aerial surveys. surveys recorded immense migratory schools near the water’s surface in the mid-Atlantic, up to 75 km from shore. We rAys observed almost 48,000 rays in the summer and fall of 2012- Te Cownose Ray is a species of eagle ray that primarily eats 2013. Te unexpected detection of these massive migrations mollusks and shellfsh. In large groups, these rays migrate is a reminder of how little we truly know about the migratory north and into inland bays, such as the Chesapeake, to breed lives of many ocean creatures. during the summer (Goodman et al. 2011). While their bAts breeding habits are reasonably well known, the migratory period is poorly understood. However, digital video aerial Bats are not commonly thought of as ofshore migrants, although anecdotal observations of migrating bats over the Atlantic Ocean (particularly during fall migration) have been reported since at least the 1890s (Hatch et al. 2013). In September of 2012 and 2013, a total of two bats were documented during boat-based surveys and 15 in high resolution video aerial surveys, all between approximately 16 and 70 km from shore. Most of these bats were identifed as Eastern Red Bats, a tree-roosting species that migrates long distances and some- times collides with land-based wind turbines. Most bats seen in digital aerial surveys were estimated to be fying several hundred meters above sea level (Hatch et al. 2013). Despite generally nocturnal habits, all bats were observed during the day. Weather conditions were good at the time of these observations, sug- Image of a migratory school, or “fever,” of Cownose Rays extracted gesting that these bats were deliberately migrating ofshore and from the high resolution digital video recorded during aerial surveys. had not been driven ofshore by severe weather.

PAGE 26 • MIGRATION songbirDs several consecutive days over open water, soar and forage at Like bats, the movements of individual songbirds can be night, and often roost on ofshore structures and vessels (Voous difcult to track because of their small body size. Most 1961, Cochran 1975, Johnson et al. 2011, Desorbo et al. 2012). songbirds also migrate at night, making the study of their Satellite telemetry data indicated that though peregrines often migrations particularly difcult. Weather radar can detect migrated relatively close to shore, individuals were capable of migratory activity in the atmosphere (see “Radar Blooms”), fying hundreds of kilometers ofshore (Figure 26) and staying in which allowed us to document broad-scale geographic and those areas for weeks. temporal patterns of nocturnal migrants in the ofshore During migration, Peregrine Falcons primarily prey on other environment. Nocturnal acoustic sensors deployed on the migrating birds, such as songbirds and shorebirds (White et survey boat also allowed us to identify some of the species al. 2002). It is possible that falcon migratory routes in ofshore making these fights. areas are dictated by the migratory paths of their prey. Songbirds regularly few over open water, particularly in the fall, when ofshore migratory activity was often higher than rADAr blooMs over land (Figure 25). For many birds, expansive areas of open Weather radars send microwaves into the atmosphere to water on the Outer Continental Shelf may not be the barrier detect precipitation. Tese microwaves also indicate the to movement that we previously thought. locations of fying animals, such as birds, bats, and insects. fAlcons During migration, “blooms” of migratory activity can be seen surrounding radar units on unfltered radar maps (in the radar Peregrine Falcons are the world’s fastest animal, and their aerial map depicted in the banner at the top of opposite page, the dexterity allows them to catch birds on the wing. Tis foraging irregular green and yellow areas represent precipitation, while prowess, among other attributes, allows them to migrate over the more circular blue and gray areas are migratory activity). large expanses of the Atlantic Ocean. Tey are able to fy for

Mid-Atlantic Study Area Relative Migratory Activity (dB η) l 17.7 – 18.4 Mid-Atlantic Study Area l 18.5 – 19.9 Wind Energy Areas 20.0 – 20.7 l l Peregrine Falcon l 20.8 – 21.6 Telemetry Locations 21.7 – 22.9 Peregrine Falcon l Fall Movements

Figure 25 (left): Predicted average levels of nocturnal migratory activity during fall migration at 144 study sites along the eastern seaboard, correcting for nuisance variables like distance from radar unit and elevation. Values are model predictions based on data from six NEXRAD units located between New York and North Carolina (Sept.-Oct., 2010-2012). Red and orange colors show areas of highest migratory activity. Figure 26 (right): Interpolated movement patterns of Peregrine Falcons with satellite transmitters along the Atlantic U.S. coast during fall migration, 2010–2014 (n=16) indicating extensive use of the ofshore environment.

PAGE 27 Conclusions

survey AnD AnAlysis MethoDs Northern Gannets, and storm-petrels, while other species Study methods and analytical approaches have substantial occurred primarily in ofshore areas, including Common infuences on resulting wildlife distribution and abundance Dolphins, sea turtles, and alcids. Despite the importance of data. Understanding the limitations of these methods is ofshore areas for many species, the highest abundance and essential in order to interpret results. diversity of species occurred in nearshore areas. Tis pattern has also been observed elsewhere, and may be driven in part by In this study, boat and high resolution digital video aerial bathymetry (Paton et al. 2010). survey methods each had particular strengths and weak- nesses, though technological advances and the development iMplicAtions for offshore DevelopMent of more sophisticated analytical approaches could help Risk to wildlife from ofshore development can be thought of strengthen the digital aerial survey approach. as a combination of exposure to construction and operation activities; hazards posed to individuals that are exposed; and geogrAphic AnD teMporAl pAtterns the implications of individual-level efects for population Te distributions and relative abundance of wildlife in the vulnerability (Crichton 1999, Fox et al. 2006). Te baseline mid-Atlantic region were largely driven by environmental assessment described in this report focused on understanding variables, including weather, habitat characteristics, prey the potential exposure of wildlife to future ofshore distributions, and the topography of the coastline. Wildlife development. It will be important to focus future studies on responses to these factors varied widely by species and time species most likely to be impacted due to their exposure, of year. Tere were strong seasonal variations in community conservation status, or other factors. composition and wildlife distributions. Interannual variation was also substantial, and the results presented in this report Tis study is an important frst step towards understanding the should be interpreted with caution when attempting to implications of ofshore wind energy development for wildlife identify longer-term (e.g., interdecadal) patterns in wildlife populations in the mid-Atlantic United States. Results from distribution, abundance, or movements. this project will be used in combination with data from other recent and ongoing studies along the eastern seaboard (e.g., Te mid-Atlantic region is important for many species that Bailey and Rice 2015, NEFSC and SEFSC 2011, O’Connell et al. use the area during breeding and nonbreeding periods. Tis 2009). Collectively, these baseline data can be used to inform study also indicated the importance of ofshore areas in the siting of future ofshore wind energy projects, address the migratory routes for many taxa, including rays, sea turtles, environmental permitting requirements for current and future marine mammals, passerines, shorebirds, and seabirds. projects, and inform the development of mitigation approaches Areas ofshore and south of the mouths of Delaware Bay aimed at minimizing potential efects. and Chesapeake Bay were consistent hotspots of relative abundance for many species, as well as hotspots of species richness. Tese areas were likely attractive to a wide variety of species due to gradients in salinity, water temperature, and primary productivity. More generally, we observed greater abundances of many species in nearshore areas (within approximately 30-40 km of shore). Scoters were one driver of this pattern, as they were highly abundant, and large focks occurred almost universally in nearshore areas. Red-throated Loons and Bottlenose Dolphins also tended to occur in nearshore areas. Tis pattern was far from universal, however, with many species widely distributed across the study area, including Common Loons, Marine wind turbine under construction of the coast of Denmark.

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