Journal of Experimental Marine Biology and Ecology 387 (2010) 44–51

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Journal of Experimental Marine Biology and Ecology

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Stable isotopes confirm a foraging dichotomy in juvenile loggerhead sea turtles

Catherine M. McClellan a,⁎, Joanne Braun-McNeill b, Larisa Avens b, Bryan P. Wallace a,c, Andrew J. Read a a Division of Marine Science and Conservation, Duke University Marine Laboratory, 135, Duke Marine Lab Road, Beaufort, NC 28516, USA b NOAA, National Marine Fisheries Service, Southeast Fisheries Science Center, Center for Coastal Fisheries and Habitat Research, 101 Pivers Island Road, Beaufort, NC 28516, USA c Center for Applied Biodiversity Science, Conservation International, 2011 Crystal Drive, Suite 500, Arlington, VA 22202, USA article info abstract

Article history: Differential habitat use and foraging behaviors at various life-stages within a population can have profound Received 2 December 2009 consequences for survivorship, stage duration, and time to maturity. While evidence for plasticity within a Received in revised form 24 February 2010 given life-stage in marine species is mounting, factors that contribute to this diversity remain poorly Accepted 25 February 2010 understood. We used stable isotope analysis of consumer and prey tissues to describe the trophic niche Keywords: width of juvenile loggerhead turtles (Caretta caretta) that have been tracked and previously shown to have Life history variation significant variation in movement behaviors (oceanic versus neritic). Results of a Bayesian mixing model Loggerhead turtle indicated that whereas benthic invertebrates dominated the recent diet of neritic turtles (determined Migration through blood plasma), pelagic prey items contributed substantially to the diets of oceanic turtles. Analysis Neritic fl Oceanic of temporally protracted diet composition (determined through red blood cells) re ected contributions from Stable isotopes pelagic prey for all turtle groups, indicating that all turtles fed in the pelagic zone during overwintering periods. These results imply that the previous satellite tracking results reflect the turtles' prior foraging habits. Our study highlights the need for an integrative management approach of North Atlantic juvenile loggerheads and validates the use of stable isotopes for determining their differential habitat use. © 2010 Elsevier B.V. All rights reserved.

1. Introduction habitat and diet throughout their lives (Carr, 1987; Musick and Limpus, 1997). After hatching, small juvenile loggerheads spend more than a Understanding the behaviors that influence life history and decade in the epi-pelagic zone amongst floating Sargassum, feeding demographic traits is a fundamental goal in ecology. Examples of spatial opportunistically on nektonic organisms (Carr, 1987; Bjorndal et al., and trophic niche polymorphisms are well documented in many 2000; Bolten, 2003a,b; Snover et al., in press). As large juveniles, these vertebrates, particularly within isolated populations (reviewed in turtles return to neritic waters and adopt a demersal foraging strategy Smith and Skúlason, 1996). Species of fish, for example, are often (Carr, 1987; Musick and Limpus, 1997; Hopkins-Murphy et al., 2003). distributed within an environment (e.g., lake, stream, or estuary) based During this developmental period, the turtles undergo morphometric on size, age, or morphology (Mittelbach and Osenberg, 1993; Svanbäck and physiological changes that are consistent with changes in their and Eklöv, 2002; Gillespie and Fox, 2003; Lecomte and Dodson, 2004). foraging ecology (Kamezaki and Matsui, 1997; Hochscheid et al., 2007a; Migratory birds will also segregate terrestrial habitat seasonally by age Snover et al., 2007). Due to disparities in prey abundance and quality class and/or sex (Catry et al., 2004). In marine ecosystems, many according to habitat, variation in foraging areas used by individuals of organisms such as turtles, sharks, and seabirds have complex life the same population can affect important life history traits such as histories with life stages that occur in vastly different habitats (Musick, growth rates (Limpus and Chaloupka, 1997; Diez and van Dam, 2002; 1999; Phillips et al., 2004). Differential habitat use is often poorly Balazs and Chaloupka, 2004; Snover et al., 2007). Furthermore, the understood, however, and can complicate conservation and resource timing and permanence of the oceanic-to-neritic shift in habitat and diet management efforts. Identifying the behavioral strategies and factors can potentially have profound consequences for an individual's that mediate habitat selection is a particular challenge. survivorship, stage duration, and time to maturity (Snover, 2008). Loggerhead sea turtles (Caretta caretta) are long-lived and highly In contrast to long-maintained dogmas about ontogenetic habitat migratory marine reptiles that exhibit profound ontogenetic changes in shifts in immature sea turtles, recent studies have revealed that these patterns can be highly variable, as the oceanic-to-neritic shift is facultative for sea turtle species, life stages, and populations around the world ⁎ Corresponding author. Present address: Centre for Ecology and Conservation, (Witzell, 2002; Hatase et al., 2002, 2006; Hawkes et al., 2006; Casale et al., School of Biosciences, University of Exeter, Cornwall Campus, Penryn TR10 9EZ, UK. Tel.: +44 1326 371872; fax: +44 1326 254205. 2008), including foraging juvenile loggerheads in the North Atlantic E-mail address: [email protected] (C.M. McClellan). (McClellan and Read, 2007; Mansfield et al., 2009). For example,

0022-0981/$ – see front matter © 2010 Elsevier B.V. All rights reserved. doi:10.1016/j.jembe.2010.02.020 C.M. McClellan et al. / Journal of Experimental Marine Biology and Ecology 387 (2010) 44–51 45

McClellan and Read (2007) tracked juvenile loggerheads from North Invertebrates and fish were separated from Sargassum plants for SIA. Carolina, USA, using satellite telemetry and reported that these turtles Because of their small body size, samples of whole crustaceans taken from exhibited two clear migratory patterns: individuals with a permanent different Sargassum patches were pooled to obtain a large enough sample habitat shift into neritic coastal waters where they shuttle between for analysis. These included Sargassum crabs, Portunis sayi (n=10) and summer and winter sites therein (as expected from the original life history shrimp, Latreutes fucorum and Leander teruicornis (n=8). Individual small model) and individuals with a reversible habitat shift that return to the juvenile fishes were also sampled; filefish, Monocanthus hispidus (n=10) oceanic realm. In the six years since tracking of these turtles began, none of and yellow jack, Carangoides bartholomaei (n=5). the oceanic turtles have returned to North Carolina estuaries (based on satellite tracks and NMFS SEFSC, Beaufort, NC Lab unpublished re-capture 2.2. Stable isotope analysis data). On the other hand, approximately 80% of the neritic turtles returned the following year (McClellan and Read, 2007), showing a characteristic In ectothermic vertebrates such as turtles, plasma reflects a short pattern of strong site fidelity to seasonal feeding locations (Avens et al., term diet history (i.e., on the order of weeks) and RBCs represent a 2003; Broderick et al., 2007; Mansfield et al., 2009).Factorssuchastrophic foraging history integrated over about a longer period (i.e., 2 to 7 or more ecology and philopatry that may underlie this behavioral dichotomy (and months) (Seminoff et al., 2007; Reich et al., 2008). Blood samples in this subsequently impact loggerhead life history and population dynamics) study were primarily collected in the autumn (September–November), have yet to be investigated. so the assumption was that plasma samples reflected the summertime Analysis of stable isotope ratios has been used to describe foraging (June–August) foraging in the estuaries and that RBC samples would be variation among individuals (Reich et al., 2007; Snover et al., in press), more representative of the entire previous year, including overwinter- within (Hatase et al., 2002, 2006; Caut et al., 2008) and between life stages ing periods (December–April). Blood samples were separated into (Arthur et al., 2008), between populations (Wallace et al., 2006), and plasma and red blood cell (RBC) components by centrifuge and stored in among species (Godley et al., 1998) of wild marine turtles. Specifically, a freezer at −80 °C for later-analysis. All turtle and prey tissue samples stable isotope ratios of nitrogen (15N:14N, or δ15N) and carbon (13C:12C, or were dried at 60 °C for 48–72 h (except for entire oceanic jellies, which δ13C) are often used as indicators of trophic level and feeding location of were dried for up to 3 weeks) and then ground into powder. Subsamples consumers, respectively (DeNiro and Epstein, 1978, 1981; Minagawa and (0.5–2.5 mg) were micro-spooned into sterilized tin capsules for Wada, 1984; Peterson and Fry, 1987; Hobson, 1999). In this study we analysis by mass spectrometry at the Duke University Environmental combined analyses of stable isotoperatiosofturtleandpreysamples, Stable Isotope Laboratory (DEVIL), in Durham, North Carolina (see turtle remigration (also referred to as seasonal migration) histories, and Wallace et al., 2009 for analytical details). Lipids were not extracted, so a body size to examine variation in the movements and habitat use by post hoc lipid correction factor was applied to our carbon isotope ratios loggerhead sea turtles in the North Atlantic. (δ13C) (Post et al., 2007). Similar to Revelles et al. (2007) and Wallace et al. (2009), isotopic discrimination between turtles and potential prey

2. Methods was accounted for using discrimination factors (Δdt) measured in similarly sized juvenile green turtle (Chelonia mydas) tissues; blood 13 15 2.1. Data collection plasma (Δdt δ C: −0.12±0.03‰, Δdt δ N: 2.92±0.03‰)andRBC 13 15 (Δdt δ C: −1.11±0.05‰, Δdt δ N: 0.22±0.03‰)(Seminoff et al., Based on previous satellite tracking (McClellan and Read, 2007), the 2006). destinations of 35 juvenile loggerhead sea turtles captured in North Carolina estuaries were categorized as either neritic, oceanic, or unknown. 2.3. Data analysis Turtles were classified as ‘oceanic’ if their migratory movements took them past the continental shelf, as defined by the 200 m isobath (n=10), Conventional and bootstrapped logistic regression analyses were ‘neritic’ if they remained on the shelf (n=18),or‘unknown’ if their tracks conducted to explore whether the variation in migratory destination were too short (i.e., b1 mo.) to determine a destination (n=7)(McClellan (neritic versus oceanic) was influenced by factors such as diet (i.e., and Read, 2007). McClellan and Read (2007) previously described the δ13C, δ15N), seasonal remigration, and body size. Separate models tracking methods and subsequent movements of 30 of these animals were run for blood plasma and RBC isotope signatures. tagged in 2002 and 2003. Here, an additional five turtles tagged in 2004 Akaike's information criterion (AIC) was used to guide optimum are included (S1). Although the majority of the turtles were tracked parameter selection with conventional modeling and p-values with beginning in autumn (September–November), five were tagged during bootstrap modeling. Sample sizes differed among parameters because of the summer (May–June). The following procedures were conducted on missing data for some variables; therefore, AICs could only be compared each turtle: 1) collection of a 5 cc blood sample from the dorsal cervical directlybetweenmodelswithequalsamplesize(i.e.,δ13C=δ15Nand sinus for stable isotope analysis (SIA) (Wallace et al., 2009); 2) measured remigration=size). Because of small sample sizes and because certain for standard straight and curved carapace lengths (SCL and CCL; and 3)), variables (i.e., remigration) were highly skewed, bootstrap models were checkedfortagsandmarkednewturtleswithflipper and PIT tags run in order to provide more robust parameter estimation (given probable (Epperly et al., 2007). violations of maximum likelihood estimation-based logistic regression Between July and September 2007, potential neritic prey items within assumptions). Parameter estimation was determined by randomly re- North Carolina estuaries were collected for SIA and potential oceanic prey sampling the data with replacement over 10,000 iterations to approxi- items were collected from the Gulf Stream off of North Carolina (S1). The mate the sampling distribution. Regression analyses were performed in R neritic prey samples were obtained by hand, crab pot, or pound net and using the BRGLM package (Bias Reduced Generalized Linear Model; included muscle tissue from blue crabs, Callinectes sapidus (n=4), Kosmidis and Firth, 2008) with a binomial family and logit link function; lightning and knobbed whelks Busycon contrarium (n=6) and B. carica the BRGLM function penalizes the maximum likelihood estimate for cases (n=4), respectively, spider crabs (Libinia emarginata)(n=11), horse- of perfect separation in the data (i.e., when there is perfect correspon- shoe crabs, Limulus polyphemus ( n=10), and homogenized whole-body dence between the binary response variable and a categorical predictor). tissue from cannonball jellyfish, Stomolophus meleagris (n=5). Oceanic Univariate t-tests were also used to explore variation in habitat prey samples were obtained with a dip-net and included homogenized destinations and tissue type. tissues of four species of jellyfish – moon jellies, Aurelia aurita (n=5), Isotope mixing models are useful tools for inferring diet composition mauve stingers, Pelagia noctiluca (n =8), sea nettles, through the estimation of the proportional contribution of sources Chrysaora quinquecirrha (n=6), and lion's mane jellyfish, Cyanea capillata (potential prey items) within a mixture (consumer tissue) (Phillips and (n=1) – as well as Sargassum spp. (n=10) and associated fauna. Gregg, 2001, 2003; Phillips et al., 2005). To account for the many potential 46 C.M. McClellan et al. / Journal of Experimental Marine Biology and Ecology 387 (2010) 44–51 neritic and oceanic prey items in our study, the wide variability in isotope and bootstrapped logistic regression analyses and for both tissues (i.e., ratios for individual sources and uncertainty in discrimination factors, and plasma and RBCs; habitat∼δ15N+remigration). Remigration was our desire to run all turtle groups (neritic, oceanic, and unknown) significant in both regression methods (plasma pBRGLM =0.022, simultaneously for a robust estimate of our data (Jackson et al., 2009; pbootstrapBRGLM =0.0001, RBC pBRGLM =0.020, pbootstrapBRGLM =0.0001), Parnell et al., 2010), a Bayesian isotopic mixing model available as an open while δ15N was only significant in the bootstrapped analysis of plasma sourceRpackage,SIAR(StableIsotopeAnalysisinR;Parnell et al., 2010) (plasma pBRGLM =0.097, pbootstrapBRGLM =0.019, RBC pBRGLM =0.197, was used. The SIAR model is fit via Markov Chain Monte Carlo (MCMC) pbootstrapBRGLM =0.097) (S2). However, because of the perfect separation methods producing simulations of plausible values of dietary proportions in remigration data (i.e., only neritic animals remigrated), the regression of sources consistent with the data using a Dirichlet prior distribution models may have artificially deflated the significance of the δ15Nvariable. (Jackson et al., 2009; Parnell et al., 2010).TheSIARMCMCwererunfor The standard errors of the bootstrapping results were similar to the 500,000 iterations, discarding the first 50,000 samples and then thinning conventional BRGLM indicating that our model results were robust. by 21 (i.e., {number of groups⁎(number of sources+number of isotopes)} or {(3)⁎(5+2)}) to reduce sample autocorrelation. The 3.4. Turtle trophic niche resulting probability density function distributions of the feasible foraging solutions produced by SIAR allowed direct identification of the most Bivariate plots (Fig. 1) of isotopic signatures describe the mixing probable solution (i.e., the median value) (Jackson et al., 2009; Parnell et space of potential prey groups, within which proximity to the source al., 2010). Upper and lower credibility intervals described the range of indicates the greatest contribution to the diet (Phillips and Gregg, 2001). feasible contribution for each diet item. All turtles fell within the prey values (i.e., encircled by prey) (Fig. 1A). Prior to running SIAR, ecologically similar prey that turtles might Isotopic signatures of neritic turtle plasma were closest to those of consume were grouped, although not all groups were statistically neritic crabs and whelks (i.e., recent foraging), while those of oceanic similar for both δ13C and δ15N (e.g., oceanic jellyfish spp., Sargassum turtle plasma were more removed from these prey items and centered in and associated organisms) (Phillips et al., 2005). Our analyses the mixing polygon toward jellyfish (Fig. 1A). The isotopic signatures of therefore included three turtle (i.e., mixture) groups (neritic, oceanic, the unknown turtle plasma were intermediate to those of the oceanic unknown), three neritic prey groups (crabs, whelks, cannonball and neritic turtles. jellyfish), and two oceanic prey groups (jellies and fish, Sargassum and The results for the RBCs (whose results encompass a more its commensal crabs and shrimp). Separate mixing models were run protracted foraging time frame) were slightly different. In these for plasma and RBCs. instances, signatures for turtles in all groups were shifted to the right side of the mixing space and were unbounded by mean prey values 3. Results (Fig. 1B), but still remained within the mixing polygon because our models encompassed the entire range of data, not just the mean 3.1. Turtle behavior and biology

Our sample of loggerhead sea turtles ranged in size from 52.9–82.2 cm SCL (mean±one standard deviation (SD) 63.1±7.7 cm). Seasonal Table 1 remigration into the estuaries following tagging was determined either Stable isotope signatures of loggerhead sea turtles and potential prey items. Values are from satellite tracks or re-capture records (NMFS Southeast Fisheries means (± one standard deviation). n indicates sample size. * Wallace et al., 2009.

Science Center (SEFSC), Beaufort, NC Lab unpublished data). Fourteen Common name δ15N δ13C loggerheads remigrated to North Carolina estuaries in subsequent years; Mixtures all were neritic animals. Loggerheads Plasma (n=28) 11.88 (1.48) −17.57 (1.25) 3.2. Stable isotopes RBC (n=24) 8.98 (1.41) −17.48 (0.67) Neritic loggerheads − Stable isotope signatures for plasma samples were obtained from 28 Plasma (n=14) 12.33 (1.35) 17.41 (1.26) RBC (n=13) 9.30 (1.23) −17.43 (0.61) turtles and for RBC samples from 24 turtles (Table 1); blood samples were Oceanic loggerheads unavailable for 7 turtles. The trophic niche width of all loggerheads Plasma (n=8) 11.04 (1.37) −17.76 (1.20) determined by the range of δ15Nvalues,was5.2‰ for both plasma and RBC (n=6) 8.14 (0.93) −17.74 (0.37) RBC (Fig. 1).Plasma and RBC δ13Crangedby4.5‰ and 3.1‰, respectively Unknown loggerheads Plasma (6) 11.92 (1.66) −17.69 (1.48) (Fig. 1). RBC (n=5) 9.16 (2.20) −17.27 (1.08) Neritic turtles had significantly higher δ15Nvaluesinbothplasma

(t15 =2.1,p=0.02) and RBCs (t13 =2.3,p=0.02) than oceanic turtles, but Neritic sources δ13Cvaluesofthetwogroupswerenotsignificantly different in either Blue crab* (n=4) 9.28 (0.38) −16.26 (1.65) − tissue (plasma t =0.7,p=0.26, RBC t =1.4,p=0.10).Plasma and RBC Horseshoe crab* (n=10) 11.62 (0.46) 16.97 (1.31) 15 15 Spider crab* (n=11) 10.65 (0.48) −17.92 (1.33) isotope ratios from unknown turtles were intermediate to and not Crabs* (n=25) 10.82 (0.93) −17.27 (1.46) 15 statistically different from either neritic (δ Nplasmat8=0.5, p=0.30, Whelks* (n=10) 9.41 (0.57) −17.01 (0.70) 13 fi − RBC t5=0.1, p=0.45; δ Cplasmat8=0.4, p=0.35, RBC t5=−0.3, Cannonball jelly sh* (n=5) 7.92 (0.22) 18.85 (0.08) 15 p=0.39) or oceanic turtles (δ Nplasmat10 =1.1, p=0.16, RBC t5= Oceanic sources −1.0, p=0.19;δ13Cplasmat =−0.1, p=0.46, RBC t =0.9,p=0.2).As 10 5 Moon jellyfish (n=5) 8.52 (0.55) −19.50 (0.58) fi δ13 with turtle tissue samples, there were no signi cant differences in C Mauve stinger jellyfish (n=8) 4.61 (0.68) −17.95 (0.51) values between neritic and oceanic prey items (t89 =−0.7, p=0.25),but Sea nettle jellyfish (n=6) 5.19 (0.25) −17.20 (0.68) δ15N values of neritic prey were significantly elevated relative to oceanic Lion's mane jellyfi sh (n=1) 5.29 (0.00) −17.46 (0.00) fi − prey (t =16.4, p≪0.0001) (Table 1). File sh (n=10) 5.92 (1.02) 18.60 (0.74) 100 Yellow jack (n=5) 5.41 (0.28) −17.84 (0.23) Jellies and fish (n=35) 5.78 (1.39) −18.20 (0.91) 3.3. Multivariate modeling Sargassum plant (n=10) 1.54 (1.62) −16.09 (0.91) Sargassum crabs (n=10) 5.09 (1.13) −15.55 (1.44) The parameters that provided the best model fit for predicting turtle Sargassum shrimp (n=8) 4.07 (0.65) −16.66 (0.53) Sargassum +(n=28) 3.53 (1.96) −16.06 (1.11) habitat destinations were remigration and δ15N for both the conventional C.M. McClellan et al. / Journal of Experimental Marine Biology and Ecology 387 (2010) 44–51 47

(Jackson et al., 2009; Parnell et al., 2010). Cannonball jellyfish were consistently represented in only the oceanic turtles in our study, although it is likely that the other turtles occasionally consumed them (Fig. 2C, D). Crabs and whelk were also a consistent part of the diet for loggerheads with unknown migratory destinations, but to a lesser degree than the diet of neritic loggerheads (Fig. 2C, B). Model solutions for plasma samples always represented benthic prey items as a greater part of the diet for neritic turtles than for oceanic turtles (Fig. 2B, D). RBC samples consistently included the Sargassum community and oceanic jellyfish and fish for all three groups of turtles. Meanwhile, the proportion of neritic crabs and whelks sharply declined from plasma samples (Fig. 2E, F, G).

4. Discussion

In this study we were able to distinguish among juvenile loggerhead turtles from the same geographic region that had exhibited two divergent migratory strategies (McClellan and Read, 2007) on the basis of remigration histories and diet composition determined by stable isotope ratios. Specifically, we demonstrated that individuals that use open-ocean habitats have lower stable nitrogen isotope ratios than do those that remain within neritic areas, indicating a dietary dichotomy. Although stable isotope signatures reflected dietary histories prior to determination of spatial habitat use via satellite telemetry, the agreement between the inferred dietary compositions and migration patterns were persistent characteristics. Thus we conclude that a clear dichotomy exists between different groups of turtles exhibiting significant variation in foraging behaviors (e.g., oceanic versus neritic). These behavioral polymorphisms may contribute to the inter-individual variation in somatic growth rates (Snover et al., 2007; Braun-McNeill et al., 2008) and survivorship (Sasso et al., 2007)observedinthispopulation.Thefindings presented here highlight the importance of long-term mark-recapture study, combined with satellite telemetry and stable isotope analysis in elucidating complex life cycle and life history patterns, which in turn can yield enhanced conservation management approaches. Our ability to identify this behavioral polymorphism in rapidly Fig. 1. Bivariate plots of isotopic signatures of loggerhead sea turtles (panel A is for assimilated blood plasma during a metabolically active period of the plasma samples, panel B is for red blood cell samples) and potential prey (plotted year, suggests that, despite their large size, the oceanic turtles may not values corrected by discrimination factors from Seminoff et al., 2006). Points are means yet have been established benthic foragers, but rather may have been and error bars are ± one standard deviation. Color scheme uses black for neritic turtles, entering the neritic habitat for the first time. Four of the 10 oceanic grey for unknown turtles, and white for oceanic turtles. Neritic prey groups include: crabs, whelks, and cannonball jelly; oceanic prey groups include: jellies +fish and turtles were caught multiple times within their tagging season, Sargassum +. indicating that they were consistently sampling the neritic environ- ment throughout the summer and autumn, although they did not values. Neritic and unknown turtle signatures were enriched in δ15N permanently recruit to the neritic waters according to their and nearest to whelks. Oceanic turtles were depleted in both δ15N and subsequent migrations to oceanic areas. It is possible that the δ13C, falling in the direction of the Sargassum community and jellyfish transition to the neritic habitat may occur over an extended period values (Fig. 1B). (multiple attempts, seasons, years) or may never be complete in some In both plasma and RBC samples (i.e., between summer foraging animals (Hatase et al., 2006); the precise mechanisms behind these and overwintering seasons, respectively), there was a clear distinction behavioral shifts in sea turtles are still unknown. The loggerhead between neritic and oceanic turtle groups in the direction expected turtles that demonstrated the classical case of neritic settlement based on their habitat assignment derived from satellite tracking (Lutcavage and Musick, 1985; Avens et al., 2003), on the other hand, (Fig. 2A). Thus, the combined telemetry and stable isotope data exhibited higher nitrogen isotope values and site fidelity within and corroborated that oceanic turtles exploited pelagic prey items to a between seasons. Seasonal cues and environmental factors affecting greater degree than neritic turtles and neritic turtles consumed prey availability are likely to be decoupled between open-ocean and benthic prey to a greater degree than oceanic turtles. The isotopic coastal habitats (Aßmus et al., 2009), and as such may result in signatures of the unknown turtles were intermediate to oceanic and seasonally-asynchronous arrivals of oceanic turtles to near-shore neritic turtles for RBC samples. foraging areas. Before baseline signatures for the diet dichotomies of The potential foraging solutions produced by the SIAR mixing model loggerhead turtles captured in North Carolina can be established for our plasma samples demonstrate that benthic crabs make up the however, further analyses on the inter- and intra-annual variability in largest contribution to the summer and autumn diets of neritic turtles prey signatures would need to be assessed. (median: 41%; 95th% CI: 16–70%), followed by whelks (median: 29%, Several studies have demonstrated distinct gradients in δ13C values 95th% CI: 0.3–53%) (Fig. 2B). The median values of the probability in the diets of marine vertebrates between freshwater and marine density functions are the most likely level of contribution to the diet, but habitats (Smith et al., 1996), inshore and offshore marine habitats solutions could fall anywhere within the credibility intervals (CI) (Hobson, 1993; Hobson et al., 1994), and benthic and pelagic marine 48 C.M. McClellan et al. / Journal of Experimental Marine Biology and Ecology 387 (2010) 44–51

Fig. 2. A. Mean (± one standard deviation) δ15N values of plasma (summer; squares) and red blood cells (winter; circles) for turtle groups demonstrating clear seasonal shifts in foraging behavior (benthic to pelagic) consistent with movement polymorphisms documented by satellite tracking. Results of SIAR Bayesian mixing model showing the trophic mixing space shaped by potential neritic and oceanic prey. Values indicate the most likely (i.e., median) proportional contribution of each diet item neritic turtles (black circles), unknown turtles (grey circles), and oceanic turtles (white circles). Prey symbols are identical to those in the key in Fig. 1. Panels B, C, and D show results from blood plasma samples (recent foraging history). Panels E, F, and G show results for red blood cell samples (protracted foraging history). Frequency distributions represent the 95th credibility intervals of feasible prey contributions to the turtles' diets in each group.

habitats (Jennings et al., 1997). In contrast, we found no difference in was highly variable in prey samples shifting turtle isotope signatures δ13C for either turtle or prey samples. We consider two possible outside of the center of the mixing space for RBC samples, but not for explanations for our results. First, it is possible that isotopic turnover plasma samples. Such decoupling of carbon and nitrogen incorporation rates are not equal between δ15N and δ13C within turtle blood rates has been reported in other isotope studies, but is not well constituents and reflect differential routing (Gannes et al., 1998). δ13C understood (Seminoff et al., 2007; Reich et al., 2007; Arthur et al., 2008). C.M. McClellan et al. / Journal of Experimental Marine Biology and Ecology 387 (2010) 44–51 49

Secondly, turtles may be feeding in areas that differ substantially in δ15N values were similar to epi-benthic invertebrates from other shelf regions but not in δ13C signatures (Hobson and Schell, 1998). Along North (Sherwood and Rose, 2005). The decline in the contribution of neritic, Carolina's coast, the Gulf Stream is a fluid barrier between the benthic prey items between plasma and RBC samples indicates that they continental shelf waters and the Sargasso Sea; however, it also were rarely consumed by loggerheads outside of the summer and exchanges water between these two marine provinces by entrainment autumn foraging season. Some authors have suggested that sea turtles and meanders (Pietrafesa et al., 1985; Gross, 1987; Olson, 2001). Turtles hibernate or become dormant in the winter based on signature dive feeding in the Gulf Stream may have access to prey entrained from the profiles (Ogren and McVea, 1995; Hochscheid et al., 2005; Hawkes et al., continental shelf and transported along in the current. Similarly, turtles 2007) and therefore might not feed during this period. However, feeding on the continental shelf may consume oceanic items that are Hochscheid et al. (2007b) noted that overwintering behavior is brought near-shore in Gulf Stream meanders. It is also possible that temperature-dependent and that loggerheads may maintain some significant differences in δ13C values may only occur at disparate level of movement and potentially feed during the winter. It is plausible locations such as those recorded in seabird diets (Hobson, 1993; Hobson that turtles inhabiting the warm waters along the Gulf Stream remain et al., 1994). The δ13C values we recorded in North Carolina loggerheads metabolically active and therefore would need to continue to feed at were, however, similar to oceanic-stage turtles sampled from the Azores some level. Our data suggest that loggerheads switched to feeding on (Reich et al., 2009), which supports the lack of a clear distinction pelagic prey items. between oceanic and neritic feeding strategies determined through Oceanic turtle RBC samples had significantly lower δ15Nsignatures carbon ratios. While our Sargassum samples had C:N ratios similar to than those of neritic turtles, suggesting little to no contribution of neritic those reported from regions of higher productivity nearer to the coasts prey to their diet. This implies that the turtles categorized as oceanic based in the western North Atlantic (Lapointe, 1995), our oceanic prey samples on satellite telemetry were likely feeding in the open ocean prior to their were similar in δ15N and only slightly more enriched in δ13Ccomparedto arrivalinNorthCarolinaestuaries.Sargassum often occurs in dense mats those reported in the Mediterranean Sea (Revelles et al., 2007)andthe and provides habitat for a host of associated fauna (Coston-Clements et al., western Pacific Ocean (Hatase et al., 2002). Ultimately, the variation in 1991), likely accounting for a third of their diet based on our mixing prey selection as well as the variation in food webs within and among model. Additionally, jellyfish, which are well described as the primary diet habitats makes understanding feeding behaviors of marine turtles via of leatherback sea turtles (Dermochelys coriacea)(Davenport, 1998; SIA challenging (Reich et al., 2009). Houghton et al., 2006), are also consumed by loggerheads. In particular, mauve stingers have been described as an important part of oceanic 4.1. Seasonal considerations loggerhead diets (Bolten and Balazs, 1995) and may be abundant over broad scales, not just locally available in small intense patches (Doyle et al., Due to the different time periods over which RBCs (long-term) and 2008). As blooms of jellyfish become more frequent, their importance in blood plasma (short-term) integrate into loggerhead dietary histories, turtles' diets may also rise (Richardson et al., 2009). We found that pelagic we were able to identify a seasonal shift in δ15N signatures that jellies and juvenile fishes probably made up another third of the diet of corresponded to an offshore-inshore seasonal movement in both oceanic loggerheads in this study. Isotopic signatures of moon jellies were oceanic and neritic turtles. Plasma signatures demonstrated that similar to cannonball jellyfish in our samples, which were again consistent whereas benthic invertebrates dominated the putative summer and diet items only for oceanic turtles. Both of these jellyfish are commonly autumn diets of all of the turtles, cannonball jellyfish were found in continental shelf waters (Calder, 1982; Lucas, 2001). Interest- consistently present in only the oceanic turtles' diet, demonstrating ingly, cannonball jellyfish frequently maintain an association with spider their selection of pelagic prey. However, when taking into consider- crabs, carrying a post-larval sized crab in their bell (Gutsell, 1928), but we ation a more extended temporal window of foraging (RBC signatures), have no information on whether they may be consumed together or we found that all groups of turtles fed on pelagic prey items (Fig. 2). It whether the crab is able to escape. Spider crabs were only a limited is possible that undescribed tissue-specific factors might also be component of immature loggerhead diets reported in Wallace et al. responsible for the differences in plasma and RBC data; however, (2009). given what we know about the movement patterns of loggerhead turtles in the southeastern US our interpretation of the turnover rates 4.2. Influence of other variables as seasonal indicators of movement and foraging behavior provides the most compelling explanation. Juvenile and adult loggerhead We did not find variation in life history strategy to be related to body turtles routinely overwinter off North Carolina near the warm waters size (McClellan and Read, 2007). Size-based behavior dimorphisms of the Gulf Stream (Keinath, 1993; Epperly et al., 1995; Hawkes et al., have been identified in adult female loggerheads where smaller females 2007; McClellan and Read, 2007; Mansfield et al., 2009) giving them migrate to pelagic feeding habitats and larger females remain in the access to oceanic prey items aggregated in frontal eddies. If over- neritic habitat (Hatase et al., 2002; Hawkes et al., 2006;butnotingreen wintering sites are as consistent as summer foraging areas, which is turtles: Hatase et al., 2006). Within the North Carolina loggerhead likely to be the case (Broderick et al., 2007; Hawkes et al., 2007; population, Braun-McNeill et al. (2008) found high variability in size at Mansfield et al., 2009), then we could infer from our satellite tracks recruitment and in somatic growth rates, which resulted in an expanded that these loggerheads were feeding opportunistically in the epi- estimate for neritic stage duration. Although we could not assess growth pelagia at the edge of the Gulf Stream during the previous winter and rates in oceanic turtles in our study because they have not yet been spring. Unknown turtles' stable isotope signatures were intermediate recaptured, habitat choice may contribute much of the observed to neritic and oceanic turtles, and this group likely reflected both variation in growth rates via resource availability and energy expendi- neritic and oceanic prey items (Fig. 2). ture (Hatase et al., 2004; Hatase and Tsukamoto, 2008; Snover et al., The apparent hiatus in the consumption of benthic crustaceans by 2007; Braun-McNeill et al., 2008; Wallace et al., 2009). loggerheads during the winter and spring, corresponds with low abundances of these prey items on the continental shelf during that 4.3. Conclusions time of year (Stehlik et al., 1991; Viscido et al., 1997). While abundance of demersal crabs is generally low during the winter in the Mid-Atlantic The combination of satellite telemetry, stable isotope analysis, and Bight due to burrowing or migrating behavior (Stehlik et al., 1991), natural history data allowed us to elucidate life history variations observed abundance of shrimp can be quite high (Viscido et al., 1997). We did not in juvenile loggerhead sea turtles captured in North Carolina. A natural sample benthic invertebrates on the continental shelf so we are unable extension of this work could be to develop stable isotope markers to directly compare isotopic signatures with estuarine samples, but our associated with distinct behavioral phenotypes. Moreover, a bioenergetic 50 C.M. McClellan et al. / Journal of Experimental Marine Biology and Ecology 387 (2010) 44–51 assessment of variation in dietary composition could provide insight Caut, S., Fossette, S., Guirlet, E., Angulo, E., Das, K., Girondo, M., Georges, J.-Y., 2008. 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Supplemental Materials

S1. (Figure) Map of study area. Stars indicate capture locations of sea turtles. Polygons are locations where potential prey samples were collected; neritic (black) and oceanic (white).

Dashed line denotes position of the Gulf Stream when prey samples were collected (August –

September 2007). Shading is bathymetry showing the continental shelf and break. 2

S2. (Table) Logistic regression results of the best-fit model predicting turtle habitat destinations.

* indicates statistically significant variables.

a. Penalized maximum likelihood results

Coefficients Estimate Standard Error Z-value P-value plasma intercept 15.670 9.187 1.706 δ15N -1.219 0.733 -1.662 0.097 remigration -5.153 2.249 -2.292 0.022* RBC intercept 8.604 6.101 1.410 δ15N -0.864 0.672 -1.285 0.199 remigration -4.127 1.774 -2.326 0.020* b. Bootstrap results

Coefficients Mean Standard Error 2.5 % LCL 97.5 % UCL P-value

plasma intercept 18.204 10.084 3.174 45.832 δ15N -1.423 0.838 -3.694 -0.057 0.019* remigration -5.505 1.699 -10.138 -3.435 0.0001* RBC intercept 10.123 8.327 -0.257 28.321 δ15N -1.029 1.002 -3.266 0.2912 0.097 remigration -4.272 1.019 -6.102 -2.589 0.0001*