Onset and duration of gray seal (Halichoerus grypus)molt in the Wadden Sea, and the role of environmental conditions

Transcription

1 MARINE MAMMAL SCIENCE, 33(3): (July 2017) 2017 The Authors Marine Mammal Science published by Wiley Periodicals, Inc. on behalf of Society for Marine Mammalogy This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. DOI: /mms Onset and duration of gray seal (Halichoerus grypus)molt in the Wadden Sea, and the role of environmental conditions JESSICA SCHOP, 1 GEERT AARTS,ROGER KIRKWOOD,JENNY S. M. CREMER,SOPHIE M. J. M. BRASSEUR, Wageningen University and Research Wageningen Marine Research, Ankerpark 27, 1781 AG Den Helder, The Netherlands. Abstract Surveys of gray seals (Halichoerus grypus) during the molt period, when they are abundant on land, can be used to monitor changes in population size, but accurate interpretation of results requires an understanding of the molt process and how it may vary between years. This study investigates variability in onset (start date) and duration of visible molt by gray seals in the Wadden Sea, and the influence of environmental conditions on the onset. Molt was monitored in nine captive seals and observed molt phases were applied to wild seals over seven annual molt periods between 2004 and 2010, monitored using aerial photography. The onset of visible molt varied significantly between years, for example it differed 28 d between 2008 and Model selection by AIC retained one environmental variable that correlated with molt onset; however, its effect was inconsistent within the molt season and did not explain some of the apparent observed annual variation. Hence, the main causes of interannual variability in the onset of molt remain unclear and warrant further study. Researchers should account for annual variability in the onset of molt when interpreting survey results based on molt counts. Key words: peak molt, gray seals, Halichoerus grypus, haul-out, population monitoring, annual life cycle, phocid seals, Dutch Wadden Sea, North Sea. Most mammals and birds undergo molt, during which hair or feathers, respectively, are renewed. This is an energetically costly and potentially risky activity since it reduces the time available for other activities, such as foraging or migration and may increase predation (Boily 1995, Portugal et al. 2011). The annual molt in phocid seals involves the shedding of year-old fur and the growth of a new pelage. To enhance this process, seals spend more time on land (Boily 1995). Consequently, a higher proportion of the population is on land during molt than at other times of the year (Daniel et al. 2003, Cronin et al. 2014, Brasseur et al. 2015). Given the potential costs of molting, seals could be expected to time this with the most favorable environmental conditions within the year. 1 Corresponding author ( jessica.schop@wur.nl). 830

2 SCHOP ET AL.: GRAY SEAL MOLT 831 Understanding how the molt process is triggered and when maximum numbers of seals can be expected to haul-out is important when conducting surveys aimed at assessing abundance and trends in pinniped populations (Thomas 1996, H ark onen et al. 1999). However, the timing of the onset (start date) and duration of the molt can vary from year to year changing the proportion of the population that is hauled out on a particular day of the year (Adkison et al. 2003). Thus, an understanding of the variation in timing and duration of molt is important to accurately interpret molt period, population surveys. An over-arching factor controlling when seals molt is photoperiod. Mo et al. (2000) experimentally manipulated the photoperiod experienced by captive harbor seals (Phoca vitulina) and discovered that molt was triggered by changing (in this case decreasing) day length. Within the molt period, though, there is considerable individual variability in timing. In part, this is related to age, sex and internal/ endocrine processes (Bogdanowicz et al. 2013). The annual molt occurs sequentially through age-sex classes: first juveniles molt, then adult females, and finally adult males (Boulva and McLaren 1979, Thompson and Rothery 1987, Daniel et al. 2003, Cronin et al. 2014). Endocrine hormones associated with the reproductive cycle, such as cortisol and thyroxin, are implicated in the age and sex differences (Riviere 1978, Ashwell-Erickson et al. 1986, Boily 1996, Yochem and Stewart 2002). Variation between individuals in the timing of molt can also be influenced by individual condition (influenced by prey capture success), sea temperature, and ambient air temperature also influencing molt duration (Bissonnette 1935, Ling 1970, Mo et al. 2000, Yochem and Stewart 2002, Paterson et al. 2012). High external temperatures, for example, will increase the peripheral blood irrigation to epidermal cells, which theoretically could lead to an acceleration of the molt process in phocids seals (Boily 1995). Accordingly, annual variations in external factors such as prey availability and environmental conditions (particularly sea and air temperature), may cause annual changes to the onset date and duration of molt at the population level. Gray seals (Halichoerus grypus) are phocid seals that undergo an annual molt in spring, rather than autumn as do most phocids. The molting season starts approximately two months after breeding (Bonner 1981). The gray seal s breeding season in the Wadden Sea peaks in December and molt occurs between March and May (Reijnders et al. 1995, Brasseur et al. 2015). Population trends in the Wadden Sea are partly based on the surveys conducted during molt, when gray seals are most abundant (Brasseur et al. 2015), however, no specific study on the onset and duration of gray seal molt exist. The aim of this study was to determine whether there was annual variation in the onset of molt by gray seals in the Wadden Sea, and, if so, whether environmental conditions could drive the variation. The study comprised daily monitoring of captive gray seals, to identify phases of molt, and an analysis of these molt phases in wild gray seals that were photographed during aerial surveys in seven consecutive years. The times of onset of the molt were compared with local environmental conditions and the North Atlantic Oscillation Index, which is derived from climate and sea temperature across the seals foraging range. To interpret how variation in the onset and duration of molt could manifest in the survey data, simulations were run to model how such changes manifested in seal numbers on land.

3 832 MARINE MAMMAL SCIENCE, VOL. 33, NO. 3, 2017 Material and Methods Molt in Captive Gray Seals The visible onset and duration of molt was recorded in nine captive gray seals, eight females and one male. Visible molt is obvious in these seals as old hairs are dull cream and brownish colored, whereas new hairs are gray, black, and white colored. Each animal was photographed when out of the water daily between 24 February and 15 June The photographs provided a means of defining phases in molt and recording the duration of each phase for each seal. Six of the seals were based at the Dolfinarium in Harderwijk, the Netherlands. The other three were held at Ecomare on the Island of Texel, the Netherlands. At the Dolfinarium, seals were housed in a fresh-water pond with a sandy haulout site. The water was filtered through sand, treated with a flocculent to maintain clarity, and buffered to stabilize the ph. The seals were fed three to seven times a day with thawed herring (Clupea harengus), mackerel (Scomber scombrus), and sprat (Sprattus sprattus). Added to the fish, as a supplement, were five salt pills (of 1 g sodium chloride) per day and a vitamin tablet once a week (Akwa- Vit, containing 400 mg vitamin E and 100 mg vitamin B1). The male was given a contraceptive (9.4 mg suprelorin SC, since 2008) before each mating season, November December. The five female seals at the Dolfinarium had not received contraceptives for the previous 2 yr. The three female seals at Ecomare were held in a concrete seawater-filled tank with access to an above-water shelf. The seals were fed thawed herring twice a day supplemented with a vitamin tablet (Akwa- Vit) once a week. In aerial photos of wild seals, the first indications of molt, uncovering small patches of new hair and thinning of old fur around the eyes and ears, would not be detected. To enable direct comparisons of molt onset between wild and captive seals, initial subtle changes in the captive seals were defined as pre-visible-molt (Table 1). Once larger patches became visible, clearly showing new silver-gray hair, the animals were considered to be in visible molt. The visible molt was divided into an early and a late phase (described in Table 1). Finally, the post-molt was defined as being when the seals pelage was completely silver-gray. The molt phases were adapted from Badosa et al. (2006), Cronin et al. (2014), and Daniel et al. (2003). These studies describe pre-visible-molt, (visible) active-molt, and post-molt. The two visible molt phases in the present study correlate with those defined as early molt and late molt by Stutz (1967). Note that a clear start and end date can only be defined in the two phases in the visible molt (early-molt and late-molt). Molt in Wild Gray Seals Wild gray seals at haul-out sites between the Wadden Sea islands of Vlieland and Terschelling ( N, Eto N, E) were classified using the defined molt phases (Table 1, Fig. 1). Up to several thousand gray seals haul-out in this area during the molt period (Brasseur et al. 2015). Aerial photographs from 22 surveys over seven years between 2004 and 2010 were analyzed (Table 2). Aerial surveys were conducted from a single engine, fixed wing, aircraft that flew between 160 and 200 km/h at approximately 150 m (500 ft) above the sandbanks where the seals hauled-out. The oblique pictures generally had a distance between 500 and 1,000 m to the seals. Flights

4 SCHOP ET AL.: GRAY SEAL MOLT 833 Table 1. Molt phase classification criteria for gray seals. The pictures are of different captive females at the Dolfinarium in Harderwijk, the Netherlands. Molt phase Captive Description Pre-visible-molt Brown and fading pelage with a dull appearance; hair may start to shed, but new hair is not clearly visible. Visible molt: Early-molt Pelage shows both old hair and new hair; patches of new hair clearly visible on the head, tail and the flippers. The whole torso is covered with brown fur. The old pelage is >50% present. Visible molt: Late-molt Pelage shows both old hair and new hair; new hair is visible along the dorsal and ventral side of the torso; patches of old hair are present on the flanks; new hair dominates (>50%). Post-molt Brown patches have disappeared; pelage patterns are clearly visible; pelage is silver and has a smooth appearance. were conducted between two hours before and two hours after low tide, and were aimed at low tides that occurred between 1000 and 1600 local time, to ensure sufficient daylight (Reijnders et al. 2003). The surveys were only performed if rainfall in the preceding 24 h period was <8.5 mm and predicted winds were below 25 knots (corresponding with a Beaufort sea state of <6). Aerial pictures were taken with a NIKON D2H ( ) and NIKON D3 ( ). The quality of the molt classification varied as a result of blurry images or seals coated in sand. To account for differences in quality, every observation was given a quality class from 1 to 4, 1 = good, 2 = reasonable, 3 = moderate, 4 = bad (Table 3). In analysis, only seals with quality 1 were used. Most adult males could be reliably distinguished from the other sex and age classes, based on the dark color of their fur and larger body size. As this group could molt later than other age or sex classes (Hewer 1974), they were analyzed separately. All other seals, including younger animals and females, were processed together in a second group. Images were processed using Adobe Photoshop CS2. In five of the 22 surveys, subsampling was required due to the great number of seals present (Table 2). To prevent spatial bias, the subsampling was achieved by drawing a random line through all seals and scoring the molt

5 834 MARINE MAMMAL SCIENCE, VOL. 33, NO. 3, 2017 Figure 1. Aerial photograph of molting gray seals on a Wadden Sea sandbank. Seals are in pre-visible-molt (A), early-molt (B), late-molt (C), or post-molt (D). Recognizable adult males were noted separately. The quality was not always consistent due to glare or sand, and therefore seals were defined to have high (1), moderate (2), bad (3), or inadequate quality (4). The contrast of the pelage color in the true picture (upper image) was automatically selected using color select in Adobe Photoshop CS (lower image). The brown old fur was colored orange, and the grayish new fur was colored blue showing an even stronger contrast between early- and late-molt. status of every odd numbered seal (i.e., 1st, 3rd, 5th, etc.) using an on/off method. In this way, 50% of the seals present were scored. Environmental conditions measured at weather stations close to the seal haul-outs, included air temperature, wind speed, sunshine period, sea level pressure, humidity, precipitation (data from Royal Netherlands Meteorological Institute, KMNI, weather station at Hoorn, Terschelling), water temperature (data from the Rijkswaterstaat, station at Eierlandse gat), and North Atlantic Oscillation (NAO) Index data ( To examine longer-term periods for which environmental factors could have influenced the onset of molt, daily data were averaged by month. Simulations Simulations were run to study and illustrate how variation in the onset and duration of molt could influence the number of molting seals observed on a particular day of the year. The number of individuals commencing visible molt was assumed to follow a Gaussian distribution with parameters l (the mean start date) and r (the standard deviation or individual variability in start date). As a starting point in the simulations, the durations of early-molt and late-molt were derived from the captive seals (see Results) and l and r were chosen such that the simulated temporal pattern in the number of molting seals approximated those observed in the field data (Fig. 2). Further, it was assumed that on a given day, 50% of seals that were in pre-visible-molt were hauled-out, 100% of seals in visible molt (early and late) were hauled-out, and 25% of seals in post-molt were hauled-out (Fig. 2). The exact haul-out proportion during pre-visible-molt and visible molt are unknown, the assumed levels were selected as being reasonable to provide a first indication of patterns. The haul-out proportion during post-molt in late spring, was based on satellite trackers in June September between 2006

6 SCHOP ET AL.: GRAY SEAL MOLT 835 Table 2. Total number of gray seals scored for their molt status per survey date. The number of seals with the highest quality score (quality = 1) and recognizable adult males are listed separately. Total number of individuals observed Number of recognizable adult males Year Date All Quality = 1 All Quality = March April April April 1, April April May March April 1,370 1, April 1, March 1, April 1, March 1, April 1, April 1, March a 692 (from 1,384) April a 843 (from 1,686) April 1, March March a 737 (from 1,474) April a 658 (from 1,316) May a 465 (from 930) a Subsampled surveys: 50% of the seals present were scored for their molt phase. Table 3. The percentage of seals in each molt phase for each quality class (1 = good, 2 = reasonable, 3 = moderate, and 4 = bad). Quality classes ranked how clear individual seals appeared in the photographs. Quality class Pre-visible-molt Early-molt Late-molt Post-molt Not available 1 47% 18% 14% 21% 0% 2 44% 23% 18% 16% 0% 3 44% 22% 17% 17% 0% 4 0% 0% 0% 0% 100% and 2008(Brasseur et al. 2015). Next, the simulation was manipulated by the mean start date (l), the individual variability in start date (r) (i.e., synchronicity in molt), and duration of the early- and late-molt phases. It is important to note that, over time, the relationship between numbers of seals in visible molt that were in late-molt was linear (Fig. 2e, f). Changes in the relative position and slope of the line result from changes in the onset date and durations and haul-out proportion of the molt stages (see Results).

7 836 MARINE MAMMAL SCIENCE, VOL. 33, NO. 3, 2017 Figure 2. To aid interpretation of the data, this figure presents a progression of data processing in a simulation. (A) Observations of potential absolute seal numbers on a sandbank against day of the year, using assumptions described in the text. (B) The relative proportions (prop.) of seals in each molt phase changes over time. (C) The proportion of seals in pre-visible-molt (light blue) decreases over time and the proportion in post-molt increases, the seals in early- and late-molt (green lines) peak at certain times. (D) Over time, the numbers of seals on the sandbanks that are in each visible molt phase (i.e., excludes seals in pre- and post-molt), (E) Over time, the proportions of seals in visible molt that are in early- or late-molt. (F) The proportion of seals in visible molt that were in late-molt. Note that the change over time in this proportion is linear (the horizontal dashed line indicates 50% in each stage, which occurs in this simulation on day 105). Data Analysis Relative proportions of seals in the early- and late-molt were used rather than actual numbers, because there was an exponential increase in the numbers of gray seals in the Dutch Wadden Sea during the study period (Brasseur et al. 2015). This increase complicated interpretations of interannual variation in numbers ashore during molt. A generalized linear model (GLM) with a binominal distribution was fitted to the proportions of seals in visible molt that were in latemolt, and modeled as a function of several explanatory variables: year, sex (discernible adult males and all other age and sex classes), and environmental conditions. Different GLMs were fitted, starting with an intercept only model, followed by adding day of the year as an explanatory variable. The day of the year variable captures the daily increase in the proportion of visible molting seals that were in latemolt. Subsequently, we tested whether the onset of molt (captured by the intercept) differed between years and sex (i.e., adult males vs. all other seals), by adding the factor variables year and sex, respectively. Furthermore, we tested whether the daily increase in the proportion of seals in late-molt varied by year or sex (i.e., modeled using an interaction between the slope of day of the year, and year and sex, respectively). An analysis of variance (ANOVA) chi-square likelihood ratio test was used to

8 SCHOP ET AL.: GRAY SEAL MOLT 837 test whether the additions of year and sex, significantly improved model fit. The addition of both year and sex as factor variable resulted in a significant improvement of the model fit. Next, the variables day of the year and sex were retained, but the variable year was replaced by each of the environmental variables (i.e., weather variables, water temperature and NAO Index). The mean of the environmental variable for each month between December and April were used. This was done to study whether the observed interannual variation could be explained by interannual variation in any of these environmental conditions. Akaike Information Criteria (AIC) were used to select the best model. The best environmental condition, according to the lowest AIC value, was used to fit additional GLMs to create a set of models that considered a combination of two environmental conditions. Data of both wild and captive seals were processed in Microsoft Excel The statistical models were fitted in R statistical computing (R Development Core Team 2013) and graphics were made using R package ggplot2 (Wickham 2009). Throughout the results, the standard deviation was used to describe variability in the data. Results Captive Gray Seals The nine captive seals observed in 2010 showed comparable molt progressions through the four molt phases. During the pre-visible-molt phase, thinner pelage was visible on the nose, around the eyes and vibrissae. Due to thinning of the pelage, the coloration gradually became lighter. The first hairs were found in water filters of the seal s enclosure at Ecomare on 18 February 2010, 53 d before the first seal appeared to commence visible molt. This shows that the molt process starts well before it becomes visible. Figure 3. The molt progress of nine captive gray seals recorded daily in The individuals were kept at two locations (Dolfinarium and Ecomare), had different origins, ages, and sexes (see y-axis). Note that the onset and end of molt varied per individual but the duration of the phases in the visible molt (early-molt and late-molt) were similar.

9 838 MARINE MAMMAL SCIENCE, VOL. 33, NO. 3, 2017 Animal handlers noted that the captive seals hauled-out more often during molt than they did at other times of the year; however, the seals never remained out of the water for a whole day. Visible molt appeared between March and April for eight of the seals (Fig. 3). Mean day of the onset of visible molt for eight seals was on day 99 7 d (8 April). The remaining seal (Hg03) commenced visible molt on day 155 (3 June), 56 d later. This seal was blind. For all seals, the early-molt lasted d (range 6 12 d) and late-molt lasted d (range 5 to 12 d). The average time-span of visible molt on captive animals was d (range 12 to 20 d). The only adult male (Hg05) molted around the same time as did the females. Field Observations From the aerial photographs, 18,378 seals were observed. Of these, 12,835 seals (69.8%) were classed as image quality = 1. The molt patterns were comparable to those on the captive animals, starting on the head and flippers (earlymolt), followed by an area along the spine and finally on the flanks of the body (late-molt). The number of seals in early-molt and late-molt peaked in the end of April (Fig. 4). There was an increase over time in the proportion of visible molting seals that were in late-molt (Fig. 5). The model incorporating only day of the year as a variable had an AIC of (log likelihood = , df = 2). Incorporating year as a factor variable significantly improved model fit (likelihood ratio test: deviance = 44.44, P < 0.001, AIC = , log likelihood = , df = 8), showing there was annual variation in the onset of molt, independent of molt duration. Separating adult males from other seals improved the fit significantly (likelihood ratio rest, deviance = 17.39, P < 0.001, AIC = , log likelihood = , df = 9) (Fig. 5). Across the years, the mean date when >50% of the Figure 4. The proportion of wild gray seals (given an observation quality = 1) in different molt stages over time. The proportion in pre-visible-molt decreases and that in post-molt increases over time, while numbers in early- and late-molt peak during the molt period. Data are represented by the colored dots, the lines indicate the simulation of Fig. 2c.

10 SCHOP ET AL.: GRAY SEAL MOLT 839 Figure 5. The proportion of visible molting seals in late-molt over time for the years between 2004 and The onset of molt varied per year: the earliest onset in 2009 and the latest onset in The bubble size indicates the number of animals with an observation quality score of 1 for each survey. The dashed horizontal line shows the 50% level and the vertical bold red and black dashed lines show at what day of the year 50% of the visible molting animals were in late-molt, respectively. male seals were in late-molt was on day 121 (1 May) 8.5 d. For all other seals, the mean date was 16 d earlier, on day 105 (15 April) 8.5 d. Late-molt occurred earliest in 2009: for example, in adult males, on day 106 (16 April) 50% of visible molters were in late-molt. The latest was in 2008, when 50% of the males were in late-molt on day 134 (14 May). For all seals, the mean onset of molt varied by 28 d across the seven consecutive years The statistical output is comparable between quality = 1 and quality = 1 3 (Appendix S2). Simulations Simulations were designed to examine how the observed variation between years in onset and progression of molt could be achieved. The simulations demonstrated that changes in molt duration, onset, individual variation, or haul-out behavior could affect the proportion of molting gray seals that were in late-molt (Fig. 6).

11 840 MARINE MAMMAL SCIENCE, VOL. 33, NO. 3, 2017 Figure 6. Simulations of changes in the proportion of seals in visible molt that were in latemolt, compared to the base scenario (black). These figures show the effect of shorter (red) and longer visible (orange) molt durations (A); shorter early-molt (light green) or shorter late-molt (dark green) durations (B); changes in the day of onset of molt (C); changes in the variability between individuals (SD) (D); and changes in the haul-out percentage during early- and latemolt (E). The base scenario was derived from the parameters from captive seals identified in this study, i.e., visible molt commences on average on day 99, early-molt lasts 8.2 d and late-molt lasts 8.7 d. The standard deviation that defines the variability between individuals is 15 d. This base senario assumed that the haul-out behavior is the same during early- and late-molt. Changes to the overall duration of visible molt influenced the slope of the line (Fig. 6a). If the duration was shortened (i.e., gray seals molted at a faster rate), the slope of the relationship between early- and late-molters (red dots in Fig. 6a). In addition, fewer seals were present on sandbanks at the peak of molt. With a longer duration of visible molt (i.e., seals molted at a slower rate), the slope of the relationship increased (orange dots in Fig. 6a). Changes to the duration of the early- or late-molt phase caused the position of the y-intercept to change (Fig. 6b). For example, if the duration of only early-molt was shortened, the slope flattened, as per an overall shortening of the duration, and the position of the y-intercept increased (light green in Fig. 6b). If only the duration of late-molt was shortened, the y-intercept decreased (dark green in Fig. 6b). The peak of molt numbers would occur earlier, if early-molt was shorter, or later, if late-molt was shorter. In both cases, fewer seals would be hauled out during the molt peak. If the onset date of visible molt was varied, but molt durations remain unchanged, the slope of the line describing the proportion of seals in late-molt remained constant, but the x-intercept changed (blue dots in Fig. 6c). If the between-individual variability in onset of molt changed, it caused differences in the slope, and thus in the observed duration of the molting season (Fig. 6d).

12 SCHOP ET AL.: GRAY SEAL MOLT 841 The smaller the individual differences in the onset, the steeper the slope (pink dots in Fig. 6d), and thus the peak in numbers would be higher and for a shorter duration. On the other hand, if the individual variability was high, the slope would be shallower (purple dots in Fig. 6d), fewer seals would be hauled out during surveys at one particular moment, and the molting season would be longer. If the proportion of seals on land was not equal between early- and late-molt, it would also affect the simulation shape. If animals hauled out less during earlymolt than during late-molt, the intercept of the line shifted forward, meaning that the number of seals counted during surveys will stay the same, but the peak of molt was earlier (light gray dots in Fig. 6e). If the percentage of late-molt hauled out was lower than early-molt, both the slope and the intercept of the line changed (dark gray dots in Fig. 6e). In this scenario, the number of seals during peak of molt would be higher, but the period that seals were in molt would be shorter. The haul-out ratio between early- and late-molt may be different, but this is unlikely to differ between years. Examining the actual variation between years, the model fitted to the data from wild seals suggested that in the line describing the proportion of seals in late-molt, the intercept, not the slope, varied (Fig. 5). This corresponded best with the simulation scenario in which the date of onset of the molt varied between years (Fig. 6c). Environmental Conditions and the Onset of Molt For nine different environmental factors in five different monthly periods, different GLMs were produced to detect possible relationship(s) with the onset of gray seal molt. Environmental factors were added to the GLM with only sex as a factor (AIC = , log likelihood = , df = 3). The environmental condition correlating best with the molt onset was the daily mean wind speed in April, which indicated that increasing wind could delay the molting process (AIC = , log likelihood = , df = 4, deviance = 45.88, P < 0.001). Additional environmental factors were added to the existing model with the factors sex and daily mean wind speed in April. The additional factor with the best correlation to the onset of molt, was the daily mean sea level pressure in April (AIC = , log likelihood = , df = 5). This model with two environmental factors was significantly better than the model with a single environmental factor (deviance = 4.69, P = 0.03). However, the models including environmental factors, did not explain some of the apparent year to year variation, such as 2008 or Furthermore, these models were not significantly different to the model that included the factor year instead of an environmental factor (AIC = , log likelihood = , df = 9, deviance = , P = 0.22 with one environmental factor, deviance = 2.26, P = 0.69 including both environmental factors). The different individual environmental factors were also considered for longer periods (several months) and shorter periods (weeks) (see Appendix S1). None of these explained all between-year variability. Discussion This study demonstrates that onset of molt by wild gray seals varies significantly among years. In the Dutch Wadden Sea, over a 7 yr period, there was a 28 d variation

13 842 MARINE MAMMAL SCIENCE, VOL. 33, NO. 3, 2017 between the earliest and the latest estimated mean molt date (Fig. 5). Several factors could cause these annual differences, such as variability in the onset date of molt, variability in the duration of the different molt phases, variability between-individuals, and the composition of individuals that molt at a site. Exploring which of these could explain the inter-annual variability seen requires data on the progression of molt of individuals, which were not available. Data from the simulations, however, aided interpretations. The simulations showed that annual variations in onset date could best be explained by either variability in the duration of early- or late-molt (as shown in Fig. 6b) or a shift in the mean start date of visible molt per year (as shown in Fig. 6c). As the study of captive study indicated there was little variation in the duration between early- and late-molt, variation in the onset of molt between years seems the most likely factor to cause the between year variations seen in wild gray seals. Further data on captive seals could be used to investigate individual, between-year, variability. The nine captive gray seals all went through the defined molt stages consecutively. There were no indications of reverse molt, when first the torso molt followed by the limbs and head, as described by Lydersen et al. (2000). The duration of early- and late-molt on the captive seals was d (range d). It is difficult to define potential effects of captivity on molt duration (i.e., feeding regime, haul-out possibilities); however, in lack of data on wild gray seals, the captive seal data are as assumed to be indicative of molt durations in the wild. Published values for molt duration in wild phocid seals are d for harbor seals (Thompson and Rothery 1987), approximately 14 d for Mediterranean monk seals (Monachus monachus) (Badosa et al. 2006), 7 14 d for female southern elephant seals (Mirounga leonina) (Boyd et al. 1993, Fedak et al. 1994), and 28 d for northern elephant seals (Mirounga angustirostris) (Worthy et al. 1992). The measurements in this study are in the lower range compared to other phocids, however, slight variations between studies in the exact definition of the molt phases could have affected this result. Compared to the molt duration, the onset of early-molt varied considerably between individual captive seals. One seal which was blind (Hg03) deviated substantially from the rest, starting its molt 2 mo later than the other seals. When investigated 5 yr later (in 2015), this individual started to molt 21 d before the two other seals held in the same facility (JS, personal observations). Possibly a lack of perception of light and, therefore, changes in day length, influenced how this seal timed its annual molt cycle, as demonstrated for captive harbor seals by Mo et al. (2000). The other eight seals commenced early-molt on 8 April 7 d; however, there was still considerable individual variation with one completing its molt before others had started. All captive seals were kept in similar environments and fed similar diets, hence the variability attests to individual flexibility in the onset of molt that may relate to a seal s innate condition or additional factors, such as genetics, age, stress, or disease/inflammation. Despite reservations about how well captive seal molt could reflect molt in the wild, the captive seals provided a starting point to understand the molt process in wild seals and their data were used in the simulations (Fig. 6). Limitations Simulations in this study provided a first insight into how the molt period at a gray seal haul-out progresses; however, many issues remain unresolved. The simulation was created by making assumptions, such as the haul-out behavior. With no alternative data, it was assumed that 100% of the seals will haul-out during visible molt, 50% during pre-visible-molt and 25% in post-molt. Only the 25% was based

14 SCHOP ET AL.: GRAY SEAL MOLT 843 on actual studies using telemetry data; though valid for the months June September (Brasseur et al. 2015). As the tracking device used to measure the haul-out of the seals, was attached to the fur using epoxy, no haul-out data were available for the molting phase. Note that these simplifications may have impacted the outcome of the simulation. Interannual variability in the timing of molt, as found in the present study, has consequences for the interpretation of gray seal population parameters based on surveys conducted during molt. Usually, the timing of a single or, in some cases, a series of surveys is based on a fixed, expected, annual molt peak. When using the counts as an index to infer population changes, it is important to standardize the count as much as possible (Thomas 1996, Udevitz et al. 2005). Potentially, incorporatinganindexof the ratios of seals in pre-visible-molt, early-molt, late-molt, and post-molt will assist in future interpretations of population parameters that are based on molt surveys. The Role of Environmental Conditions This study indicated a correlation between the onset of gray seal molt, and both the average wind speed and the average sea level pressure in April. The correlation with daily mean wind speed indicated that little wind in April would result in an early molt onset, same as a high sea level pressure. However, the molting process is well underway by April and many seals have completed molt by then. The present study seems to indicate, that neither air temperature, nor water temperature, has a causal relationship with the onset changes in proportion of gray seals in visible molt. This coincides with Ling (1972) who suggested that molt might be triggered by temperature if thermoregulation is the main function of the fur. However, the fur of adult phocids functions mainly for smoothing the body (i.e., facilitating hydrodynamics), protection against abrasion (Sokolov 1962, Ling 1970, Stenn and Paus 2001, Kvadsheim and Aarseth 2002), and only to a small extent for thermoregulation (Kvadsheim and Aarseth 2002). This could partially explain the lack of evidence that air or water temperature could drive the onset of molt and thus, there must be other factors driving the observed interannual variation. Other reasons should be sought to account for the observed annual variability in onset of the molt. In general, the molt of phocids occurs after or during the breeding season (Ling 1970, Ashwell-Erickson et al. 1986). Gray seals molt approximately two months after pupping (Bonner 1981). Between 1985 and 2013, gray seal pupping in the Dutch Wadden Sea shifted forwards on average 1.3 d per year (Brasseur et al. 2015). No apparent shift was found in the present molt data, but the length of the time-series on molt used in this study might be too small to detect a consistent trend. The interannual variation in the onset of molt could be triggered by conditions experienced elsewhere than the molting grounds, for example at more distant foraging areas. Those conditions could fluctuate between years. Here we used only the North Atlantic Oscillation Index as a general proxy for conditions on the foraging grounds. Possibly, a factor that related more accurately with where individual seals were foraging might be required to demonstrate an effect. In East Atlantic gray seals, a longitudinal gradient is observed in both onset of pupping and molt; animals in the west of Britain tend to breed 1 3 mo earlier than animals in the Wadden Sea (SCOS 2012). Seals observed to molt in the Wadden Sea could comprise a mix of locally breeding seals, feeding either locally or in other regions, and temporary migrants from other regions, such as the UK (Brasseur et al. 2015). Interannual

15 844 MARINE MAMMAL SCIENCE, VOL. 33, NO. 3, 2017 variability in the proportions of seals from different breeding sites/foraging strategies coming to molting sites in the Dutch Wadden Sea could cause fluctuations in the observed mean date of molt. For example, an increase in the number of seals that breed in the UK and molt in the Wadden Sea could cause a slightly earlier mean molt date. This represents a plausible explanation for the observed variation. Possibly, longer term monitoring and a better understanding of the extent to which the composition of seals present in relation to their area of origin, could determine if and how the onset of molt correlates with the mean pupping date. Implications for Population Monitoring This study demonstrates that interpreting population trends of seals from counts of numbers ashore during the molt period needs to take into account likely annual changes in the date of onset of molt and molt duration. In the Wadden Sea, this can be done by completing a series of surveys during the molting period and modeling changes in seal numbers and the proportions of seals in different molt stages. While arduous, compared with simple counts of numbers present on a single day, this provides more accurate data for the interpretation of population trends. Further research is needed to elucidate factors influencing annual change in the timing of molt by phocids. Gray seals in the Dutch Wadden Sea may not be the best study system for such analysis because numbers ashore are likely influenced by changes in the composition (local vs. western North Sea) of seals present. A study incorporating individual recognition of wild seals (e.g., using photo-id or marking) and how their molt strategy varies between years could also help reduce knowledge gaps of the molt process in phocids. Acknowledgments Aerial surveys were funded by the Dutch Ministry of Economic Affairs. We thank Aad Droog, who piloted all aerial surveys, and Elze Dijkman, Hans Verdaat, Andre Meijboom, and Tamara van Polanen Petel for their help in data collection. We also thank the personnel of the Dolfinarium for making daily photographs of their captive individuals and their excellent help and cooperation, and the animal care team of Ecomare for giving us daily access to their captive seals. Furthermore, we would like to thank Gerbrand Gaaff, for his observations of the captive individuals at Ecomare in We also thank Peter Reijnders and the journal referees for their time and critical remarks on the manuscript. Literature Cited Adkison, M. D., T. J. Quinn and R. J. Small Evaluation of the Alaska harbor seal (Phoca vitulina) population survey: A simulation study. Marine Mammal Science 19: Ashwell-Erickson, S., F. H. Fay, R. Elsner and D. Wartzok Metabolic and hormonal correlates of molting and regeneration of pelage in Alaskan harbor and spotted seals (Phoca vitulina and Phoca largha). Canadian Journal of Zoology 64: Badosa, E., T. Pastor, M. Gazo and A. Aguilar Moult in the Mediterranean monk seal from Cap Blanc, western Sahara. African Zoology 41: Bissonnette, T. H Relations of hair cycles in ferrets to changes in the anterior hypophysis and to light cycles. The Anatomical Record 63:

16 SCHOP ET AL.: GRAY SEAL MOLT 845 Bogdanowicz, W., M. Pilot, M. Gajewska, E. Suchecka and M. Golachowski Genetic diversity in a moulting colony of southern elephant seals in comparison with breeding colonies. Marine Ecology Progress Series 478: Boily, P Theoretical heat flux in water and habitat selection of phocid seals and beluga whales during the annual molt. Journal of Theoretical Biology 172: Boily, P Metabolic and hormonal changes during the molt of captive gray seals (Halichoerus grypus). American Journal of Physiology - Regulatory, Integrative and Comparative Physiology 270: Bonner, W. N Grey seal. Pages in S. H. Ridgway and R. J. Harrisson, eds. Handbook of marine mammals. Volume 2. Seals. Academic Press, London, U.K. Boulva, J., and I. A. Mclaren Biology of the harbor seal, Phoca vitulina, in Eastern Canada. Bulletin of the Fisheries Research Board of Canada 200:1 24. Boyd, I., T. Arnbom and M. Fedak Water flux, body composition, and metabolic rate during molt in female southern elephant seals (Mirounga leonina). Physiological Zoology 66: Brasseur, S. M. J. M., T. D. Van Polanen Petel, T. Gerrodette, E. H. W. G. Meesters, P. J. H. Reijnders and G. Aarts Rapid recovery of Dutch gray seal colonies fueled by immigration. Marine Mammal Science 31: Cronin, M., S. Gregory and E. Rogan Moulting phenology of the harbour seal in southwest Ireland. Journal of the Marine Biological Association of the United Kingdom 94: Daniel, R. G., L. A. Jemsion, G. W. Pendletonand and S. M. Crowley Molting phenology of harbor seals on Tugidak Island, Alaska. Marine Mammal Science 19: Fedak, M. A., T. A. Arnbom, B. J. Mcconnell, C. Chambers, I. L. Boyd, J. Harwood and T. S. Mccann Expenditure, investment, and acquisition of energy in southern elephant seals. Pages in B. J. Le Boeuf and R. M. Laws, eds. Elephant seals: Population ecology, behavior, and physiology. University of California Press, Berkeley, CA. H ark onen, T., K. C. Harding and S. G. Lunneryd Age and sex specific behaviour in harbour seals Phoca vitulina leads to biased estimates of vital population parameters. Journal of Applied Ecology 36: Hewer, H. R The grey seal annual moult and spring behaviour. Pages in British seals. Collins, London, U.K. Kvadsheim, P. H., and J. J. Aarseth Thermal function of phocid seal fur. Marine Mammal Science 18: Ling, J. K Pelage and molting in wild mammals with special reference to aquatic forms. The Quarterly Review of Biology 45: Lydersen, C., K. M. Kovacs and M. O. Hammill Reversed molting pattern in starveling gray (Halichoerus grypus) and harp (Phoca groenlandica) seal pups. Marine Mammal Science 16: Mo, G., C. Gili and P. Ferrando Do photoperiod and temperature influence the molt cycle of Phoca vitulina in captivity? Marine Mammal Science 16: Paterson, W., C. E. Sparling, D. Thompson, P. P. Pomeroy, J. I. Currie and D. J. McCafferty Seals like it hot: Changes in surface temperature of harbour seals (Phoca vitulina) from late pregnancy to moult. Journal of Thermal Biology 37: Portugal, S. J., J. A. Green, T. Piersma, G. Eichhorn and P. J. Butler Greater energy stores enable flightless moulting geese to increase resting behaviour. Ibis 153: R Development Core Team R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. Reijnders, P. J. H., J. Van Dijk and D. Kuiper Recolonization of the Dutch Wadden Sea by the grey seal Halichoerus grypus. Biological Conservation 71: Reijnders, P. J. H., K. Abt, S. M. J. M. Brasseur, S. Tougaard, U. Siebert and E. Vareschi Sense and sensibility in evaluating aerial counts of harbour seals in the Wadden Sea. Wadden Sea Newsletter 28:9 12.

17 846 MARINE MAMMAL SCIENCE, VOL. 33, NO. 3, 2017 Riviere, J. E Molting in the harbor seal (Phoca vitulina) and its possible significance to exotic animal medicine. The Journal of Zoo Animal Medicine 9: SCOS Scientific advice on matters related to the management of seal populations: 2012 Reports of the UK Special Committee on Seals. Available at Sokolov, W Adaptations of the mamalian skin to the aquatic mode of life. Nature 195: Stenn, K. S., and R. Paus Controls of hair follicle cycling. Physiological Reviews 81: Stutz, S. S Moult in the Pacific harbour seal Phoca vitulina richardi. Journal of the Fisheries Research Board of Canada 24: Thomas, L Monitoring long-term population change: Why are there so many analysis methods? Ecology 77: Thompson, P., and P. Rothery Age and sex differences in the timing of moult in the common seal, Phoca vitulina. Journal of Zoology 212: Udevitz, M. S., C. V. Jay and M. B. Cody Observer variability in pinniped counts: Ground-based enumeration of walruses at haul-out sites. Marine Mammal Science 21: Wickham, H ggplot2: Elegant graphics for data analysis. Springer, New York, NY. Worthy, G. A. J., P. A. Morris, D. P. Costa and B. J. Le Boeuf Moult energetics of the northern elephant seal (Mirounga angustirostris). Journal of Zoology 227: Yochem, P. K., and B. S. Stewart Hair and fur. Pages in W. F. Perrin, B. W ursig and J. G. M. Thewissen, eds. Encyclopedia of marine mammals. Academic Press, San Diego, CA. Received: 8 October 2015 Accepted: 21 January 2017 Supporting Information The following supporting information is available for this article online at onlinelibrary.wiley.com/doi/ /mms.12404/suppinfo. Appendix S1. AIC s of glm(response~day.of.the.year + sex + environmental.factors, family = binomial, data = molt.stats). AIC glm(response~day.of.the.year + sex, family = binomial, data = molt.stats) = Appendix S2. Statistical output differences between quality = 1 and quality = 1 3.