North Atlantic right whale Eubalaena glacialis occurrence in offshore wind energy areas near Massachusetts and Rhode Island, USA

Recent surveys of wind energy areas offshore of Massachusetts and Rhode Island (USA) have demonstrated that they encompass habitat used by the Endangered North Atlantic right whale Eubalaena glacialis. Prior to 2011, little systematic survey effort had been conducted in the area. The Bureau of Ocean Energy Management and the state of Massachusetts supported 3.5 yr of twice-monthly aerial surveys by the Northeast Large Pelagic Survey Collaborative (NLPSC). Additional survey teams including the Northeast Fisheries Science Center and the Center for Coastal Studies have collected sightings data in the region. Data systematically collected by the NLPSC allowed analyses of monthly sightings rates, sightings per unit effort, and hot spots which provided information on current temporal and spatial use patterns. Abundance estimates for each season-year (i.e. a 3 mo period within a given survey year) were calculated. Behaviors observed included feeding and surface active groups. Photo-identification of whales since 2010 yielded a minimum count of 196 unique individuals (annual average = 35), or over one-third of the current population estimate. Analyses of demographics of these individuals revealed that 34 known calving females (30% of the total currently presumed alive) visited the study area. These results demonstrate consistent annual use of this area by a significant portion of the E. glacialis population, with a strong correlation between season and presence. These findings can inform management activities and development planning, and be used as a baseline dataset for assessing long-term impacts to the species.


INTRODUCTION
North Atlantic right whales Eubalaena glacialis are listed as Endangered under the US Endangered Species Act and on the IUCN Red List (Reilly et al. 2012). The most recent 'best estimate' for the species' abundance based on photographic records was 526 individuals (Pettis & Hamilton 2015). E. glacialis use the waters along the entire eastern seaboard of North America, from Florida to Iceland , Knowlton et al. 1992, Jacobsen et al. 2004. Important feeding habitats for the species include the Bay of Fundy (Kraus et al. 1982), the Great South Channel , Georges Basin and the northern edge of Georges Bank, east of Cape Cod and south of Nova Scotia (Waring et al. 2015), Cape Cod Bay (Hamilton & Mayo 1990, Mayo & Marx 1990, Nichols et al. 2008, and the Nova Scotian shelf (Stone et al. 1988). E. glacialis calving occurs primarily off the coasts of Florida and Georgia (Kraus et al. 1986a), although newborn calves and other very small calves have been reported in other areas, including Massachusetts waters (Patrician et al. 2009). Feeding grounds in New England waters and the calving grounds adjacent to Florida and Georgia were federally designated as critical habitats in 1994 (NMFS 1994). In early 2016, the federally designated critical habitats were amended and expanded by 25 227 square nautical miles (n miles) to encompass larger areas -the Northeastern US foraging area and the Southeastern US calving area (NOAA 2016). However, additional sighting records indicate that further E. glacialis habitats may exist, and that existing habitat use patterns may be changing (Weinrich et al. 2000, Cole et al. 2007, Whitt et al. 2013, Khan et al. 2014. Primary threats to E. glacialis include vessel strikes (Knowlton & Kraus 2001, Kraus et al. 2005, Knowlton & Brown 2007, Van der Hoop et al. 2013) and entanglement in fixed fishing gear, with over 80% of the population bearing scars from interactions with gear (Knowlton et al. 2012). In addition, noise generated by ship traffic decreases the ability of E. glacialis to hear each other (Clark et al. 2007, Hatch et al. 2012, may change behavior (Parks et al. 2011), and can increase stress hormones in E. glacialis (Rolland et al. 2012). E. glacialis also face environmental stressors such as algal toxins, climate-driven ocean changes, and reduced prey availability , Doucette et al. 2012, Fortune et al. 2013.
In the context of the many existing anthropogenic and environmental stressors on this species, the possible additional impacts of offshore wind farm construction, installation, and operation are not fully understood. Pile-driving during construction, if not properly mitigated, may create harmful or disruptive levels of sound (Nedwell & Howell 2004, Madsen et al. 2006, Weilgart 2007. Other development concerns include higher collision risks due to increased vessel traffic, modification of food web dynamics, operational noise, sediment disturbance, and pollution (Carstensen et al. 2006, Madsen et al. 2006, Bailey et al. 2014, Bergström et al. 2014. Existing offshore wind facilities are primarily in European waters, where large whales do not commonly occur. Therefore, published effects studies have focused on harbor porpoises, seals, and birds (Carstensen et al. 2006, Bailey et al. 2014, Bergström et al. 2014. Offshore wind energy development in the USA requires comprehensive assessments of biological resources within lease areas. Two federally designated wind energy areas (WEAs) are located offshore of the eastern USA near Massachusetts and Rhode Island. In 2011, the Massachusetts Clean Energy Center (MassCEC) and the Executive Office of Energy and Environmental Affairs contracted the Northeast Large Pelagic Survey Collaborative (NLPSC) consisting of the New England Aquarium, the Center for Coastal Studies (CCS), Cornell University, and the University of Rhode Island to conduct aerial surveys for marine mammals and sea turtles in the WEA offshore of southern Massachusetts (MA WEA). This initial contract included the MA WEA as well as the additional areas of interest (AOI) for energy development known as Muskeget Channel and the Northeast Offshore Renewable Energy Innovation Zone (NOREIZ; Fig. 1). In 2012, the Bureau of Ocean Energy Management (BOEM) joined with the MassCEC and extended the contract to include the additional lease blocks known as the Rhode Island/ Massachusetts (RIMA) WEA (Fig. 1). Prior to the start of this baseline assessment, the only systematic aerial surveys that collected E. glacialis data within the WEAs were conducted by the Cetacean and Turtle Assessment Program (CETAP, 1978(CETAP, − 1982, and additional surveys flown by the Northeast Fisheries Science Center (NEFSC/NOAA).
Here we report the spatial and temporal habitatuse patterns of E. glacialis, using sightings and photoidentification data collected by the NLPSC, NEFSC, CCS, and others from January 2010 to June 2015 in the proposed WEAs, AOI, and surrounding waters. Behavior and demography data were analyzed to determine habitat-use patterns and to characterize the subset of E. glacialis using the WEAs, in order to inform management and conservation efforts.

Aerial surveys
The NLPSC conducted 3.5 yr of twice-monthly aerial surveys in the WEAs between October 2011 and June 2015. The NLPSC survey area was designed to include the MA WEA and AOI, and was expanded to include the RIMA WEA in December of 2012 (Fig. 1). Line-transect surveys were used to estimate the abundance and describe the spatial distribution of species , with a particular focus on Eubalaena glacialis, which had been previously reported in the WEAs (Kenney & Vigness-Raposa 2010).
Aerial surveys were conducted from a high-winged Cessna 337 Skymaster (0-2A) with 2 observers positioned on either side of the aircraft employing a scan-ning pattern out to 3.7 km (2 n miles) and using Nikon binoculars (8 × 42, 6.3° field of view) to confirm sighting cues , Taylor et al. 2014. Survey transects were evenly spaced at 13 km (7 n miles) apart, and flight plans were selected at random from a pool of 18 options. Surveys were flown under visual flight rules at an altitude of 305 m (1000 ft) and a groundspeed of 100 knots (185 km h −1 ). Preferred environmental conditions included a minimum ceiling of 610 m (2000 ft), visibility greater than 9 km (5 n miles), wind speed of less than 10 knots (19 km h −1 ), and a Beaufort sea state of 4 or less.
Sightings of marine species were recorded in a format consistent with the North Atlantic Right Whale Consortium (NARWC) Database guide lines (Kenney 2011). A computer data-logging system automatically recorded survey parameters (latitude, longitude, heading, altitude) at frequent intervals (every 2−5 s) (Taylor et al. 2014). Sighting locations were recorded when the detection was abeam of the aircraft, and distance in n miles from the transect line was estimated in the following classes: within 1/8; 1/8 to 1/4; 1/4 to 1/2; 1/2 to 1; 1 to 2; 2 to 4; and > 4, via calibrated markings on the wing struts (Mbugua 1996, Ridgway 2010. Survey, environmental, and sighting data were recorded via digital voice re cor der and manually transcribed post-flight. Transcription in cluded type of flight leg (transit, transect, cross-leg, or circling), transect number, and specific points of a given transect (begin, end, break off, or resume). Environmental data variables included general weather conditions, visibility, Beaufort sea state, cloud cover, and sun glare. Sighting data transcription included species identification to the lowest taxonomic level possible, reliability of that identification ('definite,' 'probable,' or 'possible'), a count of individuals in the group, an index of the precision of that count (±1 to ±100, 'at least,' 'number unknown,' or 'no estimate'), the number of calves or juveniles, whether or not photographs were taken, and notes on behaviors. All data were submitted to the NARWC Database, where they underwent an extensive quality assessment/ quality control (QA/QC) protocol before archiving.
The aircraft deviated from transects at each E. glacialis sighting so observers could obtain photographs for individual identification (Kraus et al. 1986b), using a Nikon D300 with a 300 mm f/2.8 telephoto lens (1.4× teleconverter). Observers attempted to collect oblique photographs of the rostral callosity pattern and other obvious scars or markings, and attempts were made to document each individual within an aggregation. Images were uploaded and processed in the NARWC Catalog (Hamilton et al. 2007), and were compared to other records to identify individuals with assigned catalog numbers. The NOAA and CCS aerial surveys for E. glacialis followed protocols similar to those used by the NLPSC, detailed above. These surveys provided com parable sighting, environmental, and photographic data to the NARWC Database and the NARWC Catalog.

Data used in analysis
Data collected on E. glacialis by many research organizations in the region are submitted to the 2 complementary databases, the NARWC Database and the NARWC Catalog. The Database contains effort and sightings data, and the Catalog houses E. glacialis photographs and accompanying information. In order to supplement data collected within the NLPSC survey area, additional data from a slightly larger area and longer time period were requested from the NARWC Database and Catalog and were used in analyses of behavior and demographics (see 'Data Request Area' in Fig. 1). This area is hereafter referred to as the study area (SA). The time period selected for the additional data request was between 1 January 2010 and 30 June 2015 (the designated NLPSC survey end date).
Three separate datasets were extracted to best support various analyses (Table 1). Dataset 1, including only data collected by the NLPSC, was used for analyses that benefit from the enhanced statistical accuracy afforded by consistent systematic survey effort. Dataset 2 included sightings data submitted to the NARWC Database, and was culled by platform code to reflect only data collected by established research entities and/or data associated with photographs. Dataset 3 included only sightings accompanied by photographs that could be matched to known individuals within the NARWC Catalog. Only data from the NLPSC are included in the 2015 totals for both Datasets 2 and 3, since the NEFSC and CCS data from 2015 had not yet been submitted.

Analyses of spatial and temporal distribution
To account for variability in sampling effort in comparisons between months, monthly sighting rates were calculated from Dataset 1 as the number of whales sighted divided by amount of effort in km, multiplied by 1000 km (units are whales per 1000 km of survey). Effort was defined as the total km flown including transects, transits, crosslegs, and circling, in sea states up to and including Beaufort 4. Only sightings identified as 'definite' or 'probable' were included. Pooled sighting rate (all survey years combined) was calculated for each month during which E. glacialis were sighted.
An index of annual (1 January to 31 December) sightings per unit effort (SPUE) was calculated to assess annual distribution of E. glacialis in the SA using Dataset 1. The SA was divided into a grid of cells measuring 5 min of latitude (9.3 km) by 5 min of longitude (approximately 7.0 km, narrowing slightly from south to north). Survey transect segments were partitioned into the grid cells, limited to segments at an altitude of 366 m (1200 ft) or lower, clear visibility to at least 3.7 km (2 n miles), and a sea state up to and including Beaufort 3. All E. glacialis sightings made during those same transect segments were also assigned to the 5' × 5' cells, limited to definite and probable identifications. The number of whales sighted and total km of effort were summed within each grid cell by year (2012−2015). SPUE, in whales sighted per 1000 km of effort, was calculated for each grid cell and mapped in ArcMap v. 10.3.1 (ESRI 2016).
A hot spot analysis was performed, using Dataset 1, to delineate the nature of the clustered distribution of E. glacialis within the SA. ArcMap v. 10.3.1 was used to test for hot spots and cold spots in the SPUE data using the Getis-Ord Gi* statistic, which identifies statistically significant spatial clusters of high values (hot spots) and low values (cold spots) and produces probabilities reflecting statistical confidence levels of 99, 95, 90%, or not significant. An annual hot spot map was created using combined SPUE data across all survey years, and seasonal hot spot maps were calculated by combining seasonal SPUE data across all years for the 2 seasons in which sightings occurred. In seasonal analyses, winter is defined as December, January, and February, and spring is defined as March, April and May.
In the Getis-Ord Gi* statistic, the contiguity edges/ corners spatial relationship between cells was used, where cells that share a boundary or corner influence the computations for the target cells. This option is best when polygons are similar in size and distribution, and when spatial interaction increases if the polygons share a boundary. This option is appropriate here, as whales found in one 5' × 5' cell could easily move into an adjoining cell. The Euclidean distance (straight line) method was used to calculate distances from each cell to neighboring cells.
The Getis-Ord local statistic as defined by ESRI is given as: ( 1) where x j is the attribute value for feature j, w i,j is the spatial weight between features i and j, n is equal to the total number of features, and: (2) (3)

Density and abundance estimations
Density and abundance estimates were calculated using Dataset 1. The observed distribution of rightangle sighting distances was used in DISTANCE software , Thomas et al. 2010 to estimate the width of the strip effectively sampled on each side of the transect and its inverse, f(0), the probability density function evaluated at 0 distance. To minimize the variance of the f(0) estimate, an ade-quate sample size is necessary, minimally 25−30 sightings , and ideally 40−100 or more (Eberhardt et al. 1979). To reach adequate sample size, all on-transect sightings of large whales with right-angle distance classifications from the surveys were pooled, including E. glacialis, humpback whales Megaptera novaeangliae, fin whales Balaenoptera physalus, sei whales B. borealis, sperm whales Physeter macrocephalus, and unidentified large whales (Jefferson 1996, Barlow 1999. DIS-TANCE software was then used to fit the observed probability distribution to different statistical models and truncation schemes, selecting the output with the lowest Akaike's information criterion (AIC) score to estimate f(0) and its variance.
An estimate of density (d, in whales km −2 ) of E. glacialis was then calculated for each survey transect line by: (4) where n is the number of groups sighted during the transect, g is the average group size for E. glacialis across all sightings during the study, f(0) is the pooled large-whale value output from DISTANCE, and L is the length of the transect. Only sightings meeting the following criteria were included in the estimation: collected during a defined census transect (excludes AOI); Beaufort sea state of 3 or lower; clear visibility of at least 2 n miles; and definite or probable species identification. The variance of the density estimate was calculated additively from the variances of the component parameters: The mean values of n and g, and their variances, were computed empirically from the survey data.
The average density for a season-year was calculated as the mean of the individual transect densities, weighted by the transect lengths. Each seasonyear was defined as a 3 mo period within a given survey year (i.e. Spring-2013 = March, April, and May of 2013). The variance of the mean density was similarly calculated as the length-weighted average of the transect variances. Abundance was the weighted mean density times the area surveyed -6910.78 km 2 for the season-year periods coinciding with the first 25 surveys or 7789.19 km 2 after the RIMA WEA was included. Upper and lower 95% confidence limits on the abundance estimates were

Behavior
Analyses of behavior were performed using Dataset 2. Behavioral data associated with sightings were analyzed for spatial and temporal patterns. Recorded behaviors included surface active groups (SAGs), which can be indicative of courtship (Kraus & Hatch 2001, and feeding. For these surveys, a SAG was defined as 2 or more whales rolling and touching at the surface. Feeding was only recorded in instances when observers could see an E. glacialis individual swimming open-mouthed at or just below the surface.

Demographics
Demographics of E. glacialis individuals were analyzed using Dataset 3. Demographics of the individuals identified in the area were compared with demographics of the entire catalogued population presumed to be alive (as of 2015) to assess the age and sex class proportions of the subset of whales using the SA. Individuals not yet matched to known individuals in the NARWC Catalog were not in cluded in analyses. Sex of individuals was based upon NARWC Catalog data from either genetic or visual determinations (Hamilton et al. 2007). Catalog data also provided information on age classes as follows: juvenile (1−8 yr old), adult (at least 9 yr since calf or first sighting), or unknown. Life history data for all individuals that were identified within the SA were obtained from the NARWC Catalog to assess habitat usage.

RESULTS
In total, 76 systematic aerial surveys were conducted by the NLPSC between October 2011 and June 2015 (Table 2). In addition to this dedicated survey effort in the SA, surveys were also conducted by NEFSC and CCS. Total survey effort by all contributors between January 2010 and June 2015 was 71 292 km (Table 2). With the exception of 2010 and 2011 (the first partial year of NLPSC surveys), the majority of effort (61 803 km) in the SA was con-ducted by the NLPSC. Approximately half of the total systematic survey effort conducted in the SA during 2011 was conducted by the NLPSC, while the other half was conducted by NEFSC.
The total number of Eubalaena glacialis records and data contributors for each database used in analyses varied (Table 3). The NLPSC recorded 60 sightings during the 76 surveys flown during the study period, reflected in Databases 1 and 2. A sighting is a single event in which a whale or whales are observed; therefore, 1 sighting may include 1 or more whales. These 60 sightings contributed to a total of 86 photographed 50  and identified individuals to Database 3. NEFSC collected 32 sightings during the study period. Several of these sightings were of very large groups, which added 167 individual whales to Dataset 3.

Seasonality and distribution
Sightings of E. glacialis only occurred during the winter and spring, beginning in December and ending in April. Monthly sighting rates (whales per 1000 km survey effort) across all years were highest in February (6.95) and March (9.04) (Fig. 2).
The distribution of E. glacialis within the SA varied both annually and seasonally. In the years 2012 and 2015, the majority of whales were documented as scattered throughout the northern limits of the SA, while in 2013 and 2014, whales were primarily sighted along the eastern side of the SA (Fig. 3). The hot spot analysis highlighted areas of seasonally consistent E. glacialis aggregations (Fig. 4). In the winter season, distribution shifted offshore, and hot spots appeared to the north and east of the MA WEA. In the spring, whales tended to be distributed closer to shore, and the largest hot spot was located in the northwestern corner of the RIMA WEA. When viewed cumulatively over all years, hot spots were located in the northwestern part of the SA and to the east, due south of Nantucket Island.

Density and abundance
Seasonal abundance point estimates during winter and spring ranged from 0 in the winter of 2012 to a high of 35 in the winter of 2013 (Table 4). Abundance generally tended to be higher in spring than in winter, with the exception of 2013. The 95% confidence limits for these estimates were typically wide, with the upper confidence limit ranging up to 296. The abundance estimates are not corrected for whales below the surface not sighted during aerial surveys.

Behavior
On 52 occasions feeding or SAG behaviors were recorded, and the remaining 65 sightings were categorized as none/other (Fig. 5). Feeding behavior was recorded for 39 (33%) of the sightings. Feeding was seen in all years of the study period (2010−2015), and exclusively during the months of March and April. There were 13 instances of SAG behavior recorded, involving a total count of 61 whales. The average SAG group size was 4.7 whales, with a range of 2 to 14 whales. This behavior occurred during all years (2010−2015), with the exception of 2011, and was primarily observed during the month of March.

Population demographics
Dataset 3 contained 271 records of 196 identified individuals. Of these 196 individuals, 32 (16%) were documented only in the SA and not in any other known habitat during the January 2010 to June 2015 period. An average of 35 individual whales was identified in the SA annually. Of the 196 photodocumented individuals, 35% (n = 68) were females, 58% (n = 114) were males, and the remainder (n = 14) were of unknown sex. Of the 188 individuals that had assigned age classes, 64% were adults and 32% were juveniles. Six individuals were classified as calves at their time of sighting in the SA. The average age of individuals identified in the SA was 10.8 yr.
There were 34 different reproductive female ('cows') identified in the SA. For 8 of these cows, the only documented record since the start of 2010 was in the SA. Cows sighted varied in reproductive age (first-time mother to 26 yr since first calving) and number of calves born (1−7; ). The majority of cow sightings occurred during the month of April. Of the cows that   from Dataset 1 (see Table 1). All summer and fall estimates were 0 visited the SA, 11 (32%) visited in more than 1 year. Six of the cows sighted in the SA were seen with calves, and the majority of these cow/calf sightings occurred in 2010 and 2011.

DISCUSSION
These surveys represent the most intensive systematic aerial survey effort executed within the SA to date, and they revealed an annually consistent winter and spring occurrence of Eubalaena glacialis. Within the SA, E. glacialis appear to arrive in Decem-ber and leave in May, and this seasonal presence is consistent with historical records (Reeves et al. 1978, CETAP 1982, Kenney & Vigness-Raposa 2010. Although no visual detections of E. glacialis were made in the SA during the month of June, the occurrence of E. glacialis in nearby habitats (the Great South Channel, <100 km east of the SA) is high during that month , Brillant et al. 2015. Acoustic detections of E. glacialis were made in the month of June during concurrent acoustic surveys of the SA ). E. gla cialis were observed using the northern portion of the WEAs as a spring habitat and exhibited skim-feeding behavior there. They also used the areas directly adjacent to the north and east of the WEAs as a winter habitat, although skim feeding was not observed there.
Behavioral observations help define the characteristics and importance of a habitat to any species. E. glacialis were recorded feeding and engaging in SAGs, with observations of feeding behavior occurring exclusively during spring. Since E. glacialis can only forage successfully in areas of dense copepod aggregations (Kenney et al. 1986, Kenney & Wishner 1995, observations of feeding suggest concentrations of zooplankton are present, although prey species could not be confirmed without oceanographic sampling in the area. Sub-surface feeding at depths beyond visibility to observers, which occurs more often than skim-feeding behavior, could not be confirmed in the SA (Mayo & Marx 1990, Kenney & Wishner 1995, Baumgartner & Mate 2003, Baumgartner et al. 2003. However, the lack of uniformity in distribution depicted by the annual SPUE analysis (Fig. 3) and hot spot analysis (Fig. 4), and the apparent presence of high-density zooplankton concentrations in the area, may indicate sub-surface feeding. Whales feeding at depth within the habitat could reduce aerial survey detection rates, as feeding dives can last for up to 20 min . The regular observations of SAGs, observed in all but 1 year, may indicate that animals are mating in this habitat, although mating does not always oc cur in SAGs (Kraus & Hatch 2001. When compared with the latest 'best estimate' of 526 individuals (Pettis & Hamilton 2015), the subset of E. glacialis photo-identified in the SA (n = 196) constitutes 37% of this photographically-based total. The average number of individuals (n = 35) photoidentified in the SA per year was comparable to the combined winter and spring abundance estimates (between 24 and 44). However, counts of individual E. glacialis through photoidentification capture only those whales that are sighted and photographed.  Likewise, the abundance estimates provided here are based only on those animals at the surface, have wide confidence intervals, and are limited by sample size and effort (Marsh & Sinclair 1989). Survey effort was limited to 2 surveys mo −1 , and not all months of all years in the study period were documented. There fore, it is likely that some individuals were missed, and that both the photo graphic counts and the abundance estimates represent the minimum number of E. gla cialis in the area. Every demographic class of E. gla cialis has been documented within the SA since the start of 2010. The sex ratio of E. glacialis documented in the NARWC Catalog is 39% females and 55% males (North Atlantic Right Whale Consortium 2015), which is comparable to the sex ratio of individuals documented in the SA (35% female, 58% male). The number of cows that were sighted here since 2010 constitutes 30% of the 115 known (alive) cows in the population (North Atlantic Right Whale Consortium 2015). Sightings of cows without calves in the SA were particularly valuable, as the opportunity to document cows in years when they do not have calves is rare (Brown et al. 2001). Documentation of these females great ly improves population monitoring, since the apparent loss of even 1 cow can have negative population recovery consequences (Fujiwara & Caswell 2001).
Ongoing monitoring of this E. glacialis habitat will be important in informing habitat use patterns, particularly with recent shifts in habitat use that have occurred elsewhere, and in other seasons , Khan et al. 2014. Combined visual and acoustic monitoring of E. glacialis can better characterize their occurrence (Morano et al. 2012), particularly when aerial surveys are not possible (Clark et al. 2010). In this study, concurrent acoustic monitoring by the Cornell University Lab of Ornithology revealed a longer period of occurrence than the shorter seasonal period that was detected by aerial surveys . Re cent studies of E. glacialis distribution in coastal areas that used a combination of acoustic and visual assessment techniques found that aerial surveys were useful for estimating abundance and identifying individuals, but that acoustic monitoring detected occurrence over longer periods of time (Whitt et al. 2013, Hodge et al. 2015, Oedekoven et al. 2015. A variety of offshore industrial activities underway or proposed off the eastern coast of North America are likely to contribute to the ongoing alteration of E. glacialis habitats, potentially adding stressors to a species already under threat from fishing and shipping (Kraus & Rolland 2007). Underwater noise from some wind energy facility construction or operation activities in this region may require mitigation, as  Table 1). Behaviors are categorized as feeding, surface active group (SAG), or none/other. Existing shipping lanes are depicted in light blue. Other abbreviations and additional details of the study area are shown in Fig. 1 E. glacialis communicate less in the presence of elevated sound levels, and physiological stress is increased (Hatch et al. 2012, Rolland et al. 2012). Increased stress levels may contribute to reduced fecundity, suppressed immunity and reduced reproductive rates . A recent analysis demonstrated a decline in overall health in all E. glacialis individuals over the last 30 yr, possibly the result of cumulative stressors (Rolland et al. 2016). However, there may also be positive effects from the operational phase of wind energy facilities, including the possible exclusion of fisheries from areas frequented by E. glacialis, with an associated reduction in entanglement risk (Bergström et al. 2014). In response to vessel strikes and stress created by shipping noise, seasonal management areas (SMAs) have been implemented by NMFS to slow ships and alert mariners and fishermen to E. glacialis occurrence in portions of their range during distinct seasonal periods. The current shipping lanes that exist within the SA are depicted in light blue in Fig. 1.
Since there is an annually and seasonally consistent use of this habitat, an SMA could provide E. glacialis protection from ship strikes and potentially other anthropogenic activities ( Van der Hoop et al. 2013. Mitigation options for wind energy facility installations have been identified and used in other regions (IWC 2012), and our study provides important findings to support development and refinement of such measures in this area. For example, construction activities that may have harmful impacts could be scheduled outside the seasonal presence of E. glacialis in the WEAs. Additionally, the E. glacialis distribution patterns shown here can be used to dictate the timing and location of some activities. The 'Right Whale Exclusion Zone' for the RIMA WEA currently proposed by BOEM in Alternative B (BOEM 2013) overlaps with areas of high E. glacialis occurrence identified in the hot spot analysis, and could be further adapted to reflect these findings. Similarly, the exclusion zone currently proposed in the MA WEA (BOEM 2014) can be updated with the findings in this study. Areas of lowest E. glacialis use appear to be in the southern portion of the MA WEA lease blocks, which may indicate that development in these areas would have less impact on the species.
In conclusion, this area appears to be a seasonally important habitat for E. glacialis, and combined visual and acoustic monitoring as well as management actions and mitigation strategies can be applied to ensure minimal impacts. Recent evidence that factors like fisheries interactions and declining overall health are negatively affecting the E. glacialis population (Knowlton et al. 2012, Rolland et al. 2016, combined with a lack of available data on the impacts of wind energy development on the species, call for cautious and comprehensive measures to provide protection. The long-term impacts of wind farm construction and placement on large whales are unknown; therefore, the first facilities placed in large whale habitat will offer an opportunity to test their effects. The baseline data collected in these WEAs can be combined with well-known life history information to assess impacts on the E. glacialis population, and this may inform appropriate strategies for future wind energy development in other known E. glacialis or large whale habitats. Acknowledgements. NLPSC aerial surveys were conducted under NOAA Permit 14233, issued to S.D.K. The MassCEC and BOEM supported this study under Cooperative Agreement number M12AC00. Scientists and observers who participated in this work include J. Taylor, T. Montgomery, O. O'Brien, M. Hagbloom, R. Lynch, and L. Crowe. We thank them for their contributions to data collection and data processing. We are grateful to our collaborators at the Cornell Lab of Ornithology, including C. Clark, A. Rice, B. Estabrook, and J. Tielens. This work includes additional data collected by aerial surveys conducted by the NEFSC, and we specifically acknowledge the work of A. Henry, C. Khan, J. Gatzke, and P. Duley. We also recognize additional collaborators from the CCS, including L. Ganley and P. Hughes. These surveys would not have been possible without the extraordinary efforts of EnviroEye LLC (formerly ASSIST Aviation Solutions LLC), particularly pilots Aiden Seltsam-Wilps, Keith Lapierre, Don Turner, and Dan Fields. We acknowledge the cheerful and knowledgeable support of P. Hamilton