MARINE ECOLOGY PROGRESS SERIESMar Ecol Prog Ser

Vol. 523: 243–253, 2015doi: 10.3354/meps11176

Published March 16

INTRODUCTION

Analysis of stable carbon (δ13C) and nitrogen (δ15N)isotope values in animal tissues can supplement orreplace traditional methods for describing the diet ofhighly mobile, far ranging animals (Newsome et al.2012). Time-depth recorders, accelerometers, stom-ach temperature sensors, animal-mounted camerasand other instruments have been used to provideinsight into foraging behavior of marine animals (LeBoeuf et al. 2000, Bradshaw et al. 2003, 2004, Kuhn etal. 2009, Thums et al. 2011, Costa 2012, Naito et al.2013); however, the dietary composition of many spe-cies remains poorly understood due to the inherentlimitations of those tools.

Isotopic measurements of different tissues collectedfrom an individual animal can reveal dietary infor-mation on varying temporal scales, because differenttissue types have characteristic metabolic (i.e. turn-over) rates (Hobson & Clark 1992, Ogden et al. 2004,MacNeil et al. 2005, MacAvoy et al. 2006, Logan &Lutcavage 2010, Newsome et al. 2012). Continuouslygrowing whiskers can produce a sequential record ofdietary information over large temporal scales, thusoffering an advantage over integrated tissues withfaster turnover rates such as blood (Gannes et al.1998, Dalerum & Angerbjörn 2005, Newsome et al.2010). Time series isotope data ob tained fromwhiskers can address important ecological questionsthat point samples cannot (Zhao & Schell 2004),

© Inter-Research 2015 · www.int-res.com*Corresponding author: roxanne.beltran@gmail.com

Fine-scale whisker growth measurements can reveal temporal foraging patterns from stable

isotope signatures

Roxanne S. Beltran1,4,*, Megan Connolly Sadou2, Richard Condit3, Sarah H. Peterson1, Colleen Reichmuth2, Daniel P. Costa1

1Department of Ecology & Evolutionary Biology, University of California, Santa Cruz, CA 95060, USA2Institute of Marine Sciences, Long Marine Laboratory, Santa Cruz, CA 95060, USA

3Smithsonian Tropical Research Institute, Balboa, Panama City, 0843-03092, Panama4Present address: Department of Biological Sciences, University of Alaska, Anchorage, AK 99508, USA

ABSTRACT: Stable isotope analysis of slow-growing, metabolically inert tissues is a commonmethod for investigating foraging ecology in migratory animals, as direct observations of feedingare often not possible. Using tissue growth dynamics to interpret foraging timelines can maximizethe utility of foraging data; however, applying inappropriate growth models is problematic, andhigh-resolution growth measurements are seldom made. We used photogrammetry to repeatedlymeasure the length of whiskers in 93 follicles over 670 d in a trained, captive northern elephantseal Mirounga angustirostris. We developed and optimized a follicle-specific growth model todescribe the 18 000 whisker length measurements. Whiskers from the captive seal exhibitedasymptotic growth that was described by the von Bertalanffy growth function. Applying thegrowth model to serially sampled whiskers from 4 free-ranging adult female northern elephantseals resulted in alignment of peaks in δ15N along the length of whiskers with the breeding haul-out period, when seals are not feeding. Our study provides a high-resolution whisker growthmodel and is the first to use whisker growth dynamics to improve temporal interpretation of iso-topic ratios.

KEY WORDS: Vibrissae · Whisker · Asymptotic growth rate · Stable isotope · Seal

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including within-individual variation (Newsome etal. 2009, Hückstädt et al. 2012a,b), seasonal diet pat-terns (Lee et al. 2005, Newland et al. 2011), individ-ual foraging strategies (Lewis et al. 2006), changes inhabitat utilization (Bearhop et al. 2003, Cherel et al.2009), and behavioral responses to perturbations(Bodey et al. 2010). Further, the use of whiskers instable isotope analyses for mammals allows for non-lethal, minimally invasive tissue sampling (Newsomeet al. 2010, Hückstädt 2012, Tyrrell et al. 2013).Researchers have used whisker analyses to infer tis-sue deposition time by identifying cycles in isotopes(Cherel et al. 2009, Newland et al. 2011) or biomark-ers (Robertson et al. 2013) that could reflect changesin foraging behavior, but to our knowledge, no onehas applied fine-scale whisker growth rates to inter-pret stable isotope data.

Species-specific whisker growth models are re -quired in order to assign realistic time-scales to iso-topic information embedded in whiskers. Unfortu-nately, whisker growth and shedding studies arelimited to a small number of mammals, and inconsis-tencies in reported growth values have yet to reveala universal set of growth parameters (Oliver 1966,Hirons et al. 2001, Greaves et al. 2004, Zhao & Schell2004, Newland et al. 2011, Robertson et al. 2013).Recent photogrammetric and isotopic studies suggestthat some species exhibit linear whisker growth(Hirons et al. 2001, Tyrrell et al. 2013), while the vonBertalanffy organic growth equation best describesasymptotic whisker growth in other species (Greaveset al. 2004, Hall-Aspland et al. 2005).

Previous studies have found whisker shedding andgrowth patterns to be independent of the relativelyrapid pelage molt in some species (Ling 1968,Greaves et al. 2004), which suggests that animalsmaximize function of the vibrotactile sensory systemby ensuring that a proportion of whiskers are at theirasymptotic length at any given time (Hirons et al.2001, Greaves et al. 2004). In addition, asymptoticwhisker lengths are strongly associated with rowposition across the mystacial cheek pads in rats,mice, and seals, such that whisker length increasespredictably from rostral to caudal sides in any row(Brecht et al. 1997). In this way, individuals can retaina flattened sensory plane despite the curvature of themuzzle.

To obtain high-resolution growth data across an en-tire whisker bed, we consistently measured growth ofwhiskers in a captive northern elephant seal Miro -unga angustirostris using validated photogrammetricmethods and found that a von Bertalanffy growthmodel best fit the data. We applied the values ob-

tained from the model to predict the time periods dur-ing which segments of whisker tissues are establishedin wild elephant seals. With the appropriate uncer-tainty considered, we demonstrate how temporal in-formation can be applied to foraging data with rela-tively high confidence. When applied to stable isotopeanalysis results, whisker growth rates refine currentmethods for dietary reconstruction in mammals.

MATERIALS AND METHODS

Whisker measurement

The main subject of this study was an adult (16 yrold) female northern elephant seal called Burnyce(National Marine Fisheries Service ID no. NOA0004829). The seal was housed at Long Marine Labora-tory at the University of California Santa Cruz from1994 to 2011. Following the procedure de scribed inConnolly Sadou et al. (2014), we obtained 3 photo-graphs each of the right and left mystacial whiskersduring weekly sessions spanning a period of 670 con-secutive days (28 January 2009 to 29 November2010). The seal was trained through positive rein-forcement techniques to maintain steady contactwith a PVC chin station (Fig. 1) for the duration ofeach session. All photographs were taken with aKodak EasyShare Z650 digital camera (6.1 mega -pixel) at a distance of approximately 38 cm, a heightof 30.5 cm and a 30° angle from the tip of the seal’snose. A 1 cm scaling bar was positioned in the frame

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Fig. 1. Mirounga angustirostris. A captive northern elephantseal was trained to rest her chin at a station, with a scale bar(1 cm grid) placed perpendicular to the camera lens andresting above the last whisker of the apical mystacial row to

allow measurements of whisker length

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of each photograph parallel to the animal’s muzzle atthe position of the upper leftmost whisker (Fig. 1).

To ensure consistency in measurements, we evalu-ated photographs for 5 criteria: (1) focal length wasconsistent at 38 mm; (2) follicles were visible;(3) whisker tips were visible; (4) scaling bar was per-pendicular to camera; and (5) whiskers were relaxed.If photographs did not meet all 5 criteria, they wereexcluded from analysis. The remaining photographswere calibrated to the scaling grid using Image Processing and Analysis in Java (ImageJ, NIH,http://rsb.info.nih.gov/ij). We identified individualwhiskers throughout the study using the northernelephant seal bed map from Connolly Sadou et al.(2014). We analyzed over 18 000 whisker lengthmeasurements from photographs taken during 52sessions over the sampling period, allowing us togenerate time-series measurements of whisker lengthfor each follicle (available at http:// dx. doi .org/ 10.5479/ si.ctfs.0002). The right and left mystacial bedscontained 48 and 45 follicles, respectively, andwhiskers were distributed across 7 rows.

Whisker growth model

Based on our descriptive assessment of the data,which showed rapid growth followed by slowing at acertain asymptotic length, we started with the vonBertalanffy model described by:

(1)

where asymptotic length (L∞), time of initial growth(T0), and a curvature constant (K) predict the length(L) at time T (Sparre & Venema 1999). Growth is K ×age at time T0, then declines steadily toward 0. Ahigh K value represents more rapid ascent to theasymptote. Solving for T provides an equation for theage (or deposition time) of a whisker at a givenlength:

(2)

This simple model can be used to describe growthof a single whisker. However, the complete modeldescribes sequential whiskers and shedding eventsat a single follicle. The model requires 4 parametersper whisker within a follicle: (1) initiation date (T0 inEq. 1); (2) growth parameter (K in Eq. 1); (3) asymp-totic whisker size (L∞ in Eq. 1); and (4) lifespan M, notincluded in the basic von Bertalanffy model but nec-essary to model a sequence of whiskers. A fullydetailed model of 2 sequential whiskers would thusneed 4 parameters for each whisker: T0(i), M (i), K (i),

L∞(i) for the i th whisker. Because the data neverincluded 3 complete whisker lifespans at one follicle,and only a few included 2, abbreviated models withfewer parameters were needed.

We were able to apply the abbreviated models to44 out of 93 whisker follicles (Table 1). There wereinsufficient reliable follicle measurements on the oth-ers because of the short, thin nature of their whiskers,or because follicles remained empty throughout thestudy.

Three-whisker model

Of the 44 follicles we examined, 14 included obser-vations of one whisker’s entire lifespan, from initia-tion to shedding (Fig. 2a−c). In 10 of these follicles,one whisker was present at the start of the study andthen shed, a second whisker initiated and shed, anda third whisker initiated and remained at the end ofthe study. In the other 4 follicles, no whisker waspresent at the onset, then a whisker grew and shed,and a third whisker started. The initiation date T0 ofthe first whisker was not observed in any of these,and the lifespan M was only observed in 1 whisker.Moreover, the growth portion with curvature wasalways missing for the initial whisker, and in 11 of 14follicles, it was largely missing for the third whisker,meaning only the second whisker provided data onthe curvature constant K. We thus reduced the full 12parameters to 8, because (1) we assumed K was thesame for all whiskers (K = K (1) = K (2) = K (3)); (2) weassumed 2 separate lifespans M, with the second and(if present) third whiskers sharing M while the firstdiffered (M (1), M (2) = M (3)); (3) we likewise assumed 2separate asymptotes, (L∞(1), L∞(2) = L∞(3)); and (4) weincluded all 3 initiation dates, T0(1), T0(2), T0(3). We did

L LtK T T= ⋅ −∞ − −( )( )1 0e

TK

LL

TT= ⎛⎝⎜⎞⎠⎟

⎡⎣⎢

⎤⎦⎥+

∞

–· ln –

11 0

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Parameter K (cm d−1) L∞ (cm) Lifespan (d) Lag (d)

Mean 0.0132 8.17 369.14 28.82SD 0.0065 3.69 73.58 12.72N 44 44 14 44Min 0.0045 2 250 14Max 0.0324 16.4 517 77

Table 1. Mirounga angustirostris. Modeled growth parame-ters from Eqs. (1) & (2) for whiskers of a captive northern ele-phant seal derived from photogrammetric whisker lengthmeasurements. K: curvature constant, where a high K repre-sents a more rapid assent to asymptotic length; L∞: esti-mated asymptotic length of each whisker; Lifespan: timebetween initial growth and shedding; Lag: time betweenshedding of one whisker and growth of a second whisker

from a single follicle

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not omit the first initiation date, because K was well-constrained by data for the second whisker, so thatthe first initiation date is in fact constrained by thecurvature constant K and the shedding date. The 8parameters in the 3-whisker model are thus θ = (K,M (1), M (2), L∞(1), L∞(2), T0(1), T0(2), T0(3)).

Two-whisker model

Thirty other follicles had 2 whiskers during theobservations, but neither whisker was fully observedover its lifecycle. One whisker was present at the out-set and subsequently shed, and then a secondwhisker initiated and was still present at the end

(Fig. 2d−i). Following the same logic for determiningwhich parameters are well-constrained by the data,we built a 6-parameter model for these follicles: θ =(K, M, L∞(1), L∞(2), T0(1), T0(2)), with K (1) = K (2) = K andM (1) = M (2) = M. The lifespan was necessary to buildthe model, but it was nearly unconstrained by thedata and thus was excluded from subsequent datasummaries. The L∞(2) was also poorly constrained,and we only used L∞(1) in data summaries.

Parameter fitting

Model parameters were estimated from data usinga non-linear regression approach in a Bayesian

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Fig. 2. Mirounga angustirostris. Representative time-series plots for vibrissal growth in a captive elephant seal. (a−c) Follicles(N = 14) that included observations of one whisker’s entire lifespan from initiation to shedding, and (d−i) follicles (N = 30) thathad 2 whiskers during the observations, but neither was observed for its full lifespan; after shedding of the first whisker,growth was rapid and non-linear. The code in the upper right of each plot indicates the bed (side of the snout; R: right, L: left),follicle row (A to G, from top to bottom of the snout), and follicle column (1 to 9) as described in Connolly Sadou et al. (2014).

Black dots: raw photogrammetric measurements; blue line: growth model

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framework. This starts with a likelihood functiondefining the probability of observing one follicle’s observations given a full set of whisker growth para -meters. The likelihood requires an error model, whichwe assumed to be Gaussian with a standard deviationσ that increases linearly with whisker length:

σ = a + bLpred (3)

where a and b are parameters, and Lpred is themodel’s prediction of whisker length. The parame-ters a and b must be estimated along with the growthparameters, 1 set for every follicle. A predictedwhisker length (Lpred) was produced on each obser-vation date T given the parameters:

Lpred = ƒ(θ,T) (4)

The likelihood of observed whisker length L, givenmodeled whisker length Lpred and parameters a, b,and σ from Eq. (3) was calculated as:

Like(L,θ,a,b) = Gauss(L, mean = Lpred, SD = σ) (5)

A standard way to locate best-fitting parameters forone set of data is to search for the parameters thatmaximize log(Like). We extended this with a Bayesianapproach, thoroughly sampling parameter combina-tions close to the optimum to provide a best set ofparameters plus credible intervals around them. Thiswas accomplished by searching 7500 parametercombinations using a Metropolis algorithm to gener-ate each new combination, discarding the first 2500as burn-in (see Condit et al. 2007 for details). Theresulting chain of 5000 estimates reproduces the pos-terior distribution for every parameter, and the meanof this distribution was taken as the single best esti-mate for a parameter. The 95th percentiles of the postburn-in chain were used as 95% credible intervals.The chain of parameters was also used to simulatewhisker growth in a way that propagates all sourcesof error in the model. Source code in R for fitting thegrowth model is available along with a small subsam-ple of data at http:// dx. doi. org/ 10.5479/ si. ctfs. 0002.

Photogrammetric size versus true size

The observed and fitted whisker lengths from theequations above refer to photographic measurements,but Connolly Sadou et al. (2014) demonstrated by di-rect measurements of a subsample that photographsunderestimate whisker size, mostly because directmeasurements include a subdermal portion. Since thelatter matters in isotope analysis, we applied a correc-tion on top of the model of photographic length

(Eq. 4). First, we repeated Connolly Sadou et al.’s(2014) regression of direct vs. photographic size in theBayesian framework to generate posterior distribu-tions of the regression parameters c and d:

T = c + dL + ε (6)

where ε is a Gaussian error term, modeled exactly asin Eq. (3). The simulations then rely on draws fromposterior distributions of model parameters θ plus cand d.

A simulation started with selection of 1 random setof von Bertalanffy growth parameters, θ, from theBayesian posterior distributions. The model parame-ters needed to simulate 1 whisker's growth werecurve K and asymptotic length L∞. The parameter forinitiation date was irrelevant, and lifespan was un -necessary as our interest was growth prior to theasymptote. We always chose both parameters from 1whisker, in case K and L∞ were correlated. The pairof parameters produced a single simulated trajectoryof photographic size to full whisker size. Subsequentrandom draws from the same parameter distributions(same whisker) were used to produce 10 000 alterna-tive growth curves and thus 95% credible intervalson the predicted photographic size of the whisker onany day. For each of those 10 000 curves, we utilizedposterior distributions of the regression parametersin Eq. (6), randomly choosing 1 pair (c,d) to convertthe photographic size to full whisker size. Each of thecurves can be interpreted as ‘length as a function ofage’ or ‘age as a function of length’. From each curve,we used the age (in d) at 75% of the L∞ to judge agesof whiskers that are still growing.

Whisker bed anatomy

To examine trends in length across the whiskerbed, we examined L∞ as a function of bed position forthe captive seal. A prediction of L∞ ≈ column + row +row2 was regressed against the observed L∞. Wecentered row and column by subtracting 4 from each.Source code in R for fitting the growth model is available at http:// dx. doi. org/ 10.5479/si.ctfs.0002.Model fit was assessed using Akaike’s InformationCriterion (AIC; Hilborn & Mangel 1997).

Applications of whisker growth dynamics todietary reconstruction of wild elephant seals

To apply the whisker growth dynamics to non-captive individuals, we obtained scaled muzzle pho-

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tographs of 4 adult female northern elephant sealsat the Año Nuevo elephant seal colony (San Mateo,California, USA; 37.108° N, 122.336° W), while sealswere sedated for other procedures (Robinson et al.2012) at the beginning of their catastrophic molt(May 2011). Photogrammetric lengths of all whiskerswere determined using the same methods describedfor the captive study. We also plucked 1 whisker (in -cluding the subdermal component) from each of the4 seals and recorded the whisker’s bed locationbased on the standardized bed map provided inConnolly Sadou et al. (2014). These whiskers weremost likely at L∞ because their length was interme-diate to the 2 adjacent whiskers on that row (Brechtet al. 1997). Whiskers were rinsed with de-ionizedwater and mild detergent to remove exogenouslipids and debris, washed with petroleum ether inan ultrasonic bath (Hassrick 2011), and measuredfor total length. On each whisker, only the 5 cmclosest to the base were sampled, because growthrates estimated for phocid seals (mean ± SE: 0.10 ±0.01 mm d−1; Hall-Aspland et al. 2005) suggest thatboth the present molt and the prior breeding seasonfor these seals would be contained within that partof the whisker. We divided the 5 cm section into ten0.5 cm segments and discarded the segment closestto the base to avoid the influence of the subdermalδ15N on overall values. Of the remaining 9 seg-ments, we subsampled 0.5 ± 0.05 mg (mean ± SD) ofwhisker from the proximal end (i.e. closer to thebase) and sealed each subsample in a tin boat. Sam-ples were analyzed for δ15N at the Light Stable Iso-tope Lab (University of California Santa Cruz) usinga Carlo Erba elemental analyzer interfaced with aThermoFinnigan Delta Plus XP mass spectrometer.Isotope ratios are ex pressed as δ values, which arereported in parts per thousand (‰) using: δX = 1000× (Rsample–Rstandard )/ Rstandard, where Rsample is the ratioof heavy to light isotopes (15N:14N), and Rstandard isthe international reference standard. Since higherδ15N values reflect catabolism during prolongedfasts (Lee et al. 2012), we expected peaks in δ15N toalign with the winter haul-out period (26 January to9 March 2011) of the seals during the precedingbreeding season. Sightings of the target individualson land were recorded throughout the breedingseason during a concurrent study (Robinson et al.2012).

In addition to directly measuring the pluckedwhiskers, total length was predicted from follicleposition by applying regression results from the cap-tive seal. We also assigned an estimated age to eachsegment for which isotope ratios were measured,

using the whisker growth rates derived from the captive seal. To do this, we calculated the whiskerlifespan using simulations of whiskers whose asymp-totes were similar. We then calculated T0 by subtract-ing the lifespan from the date of whisker extraction.To examine the ability of post-hoc timestamps to cor-rectly describe past life history events, we overlaiddated isotope ratios with the observed breedinghaul-out periods for each free-ranging seal.

RESULTS

Whisker growth model

We obtained measurements in 52 out of the 66weekly sampling sessions. Some measurementswere missed due to poor animal motivation (no morethan twice per 3 mo). Serial photogrammetric meas-urements of the captive elephant seal revealed rapid initial growth that slowed as whiskers reached anasymp tote of 2.0 to 16.4 cm (Table 1). Whiskers of allsizes had similar initial growth, but small whiskersstopped growing sooner (Fig. 3). The mean (±SD) ofthe curvature constant K was 0.0132 (±0.0065). Themean (±SD) whisker lifespan was 369 (±74) d. Life-span values were underestimated because thegrowth cycle of long-lived whiskers was less likely tobe fully observed. Shedding was not coincident withthe molt but was instead distributed throughout theyear. There was a mean (±SD) of 28.8 (±12.7) dbetween the shedding of one whisker and the detec-tion of a new whisker in photographs, which approx-imates the time required to re-grow the follicle. With-out knowing whether a given whisker had reachedits maximum length, we had high confidence in ourestimates of minimum whisker age, but confidencesurrounding maximum age was weak (Fig. 4). Forinstance, an 11 cm whisker could be no less than 90 dold, but maximum age could be up to 500 d. More-over, longer whiskers had wider predicted ageranges compared to short whiskers (Fig. 4). The pre-diction of whisker age at a given length becamemuch more powerful when only actively growingwhiskers (i.e. not at L∞) were included in the analysis(Fig. 4b). For example, a 10 cm whisker whoseasymptotic length is >12.5 cm would still be in itsrapid growth phase, so the predicted age rangewould be tighter than a 10 cm whisker at its asymp-totic length (Fig. 4). Many of the 95% confidenceintervals spanned a range of 40 to 100 d, which indi-cates that whisker age could be accurately predictedto 1–3 mo.

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Beltran et al.: Whisker growth and dietary reconstruction 249

Whisker bed anatomy

Maximum whisker length increased linearly withcolumn position from the midline extending laterally(Fig. 5a). In contrast, whisker L∞ increased across thefirst 5 descending rows, then decreased across thelast 2 (Fig. 5a). The L∞ ≈ column + row + row2 modelcould be used to predict maximum whisker length foreach row and column using:

L∞ = 8.53 − 1.96y + 2.06x − 0.56x2 (7)

where y = column − 4 and x = row − 4 (R2 = 0.85;Fig. 5b). The model with a row2 term provided thebest fit (AIC = 329.8). The subsequent inclusion of acolumn2 term gave no improvement in the model fit(AIC = 330.7). In the free-ranging seals, visiblewhisker length also increased along rows in a pre-dictable fashion, such that the effective length of thenext more caudal row neighbor of any whisker was1.34 ± 0.27 (mean ± SD) times longer.

Applications of whisker growth dynamics todietary reconstruction of wild elephant seals

The whiskers had mean (±SD) δ15N values of 14.94(±0.31‰), with maximum observed δ15N of 17.56‰.The 4 whiskers obtained from the free ranging sealshad different total lengths, so the highest δ15N of each

whisker did not align with the otherwhiskers until dates were assigned toeach sample. When stable isotope ra-tios were aligned based on whiskerlength, the δ15N peaks of all whiskers(indicative of fasting by the wildseals) occurred over a range of 3.0 cmfrom the whisker tip. Based on the av-erage curvature constant K from thecaptive seal’s whiskers (K = 0.0132) ,the sections of whiskers where peaksoccur represent a minimum temporalwindow of 83.2 d (Fig. 6a). After thewhiskers were assigned timestampsusing the average K from the captiveseal’s whiskers, the δ15N peaks onlyranged 14.0 d between animals(Fig. 6b). In 2 seals, the fasting peakin δ15N coincided with haul-out; inthe other 2, the fasting peak appearedjust prior to haul-out (Fig. 6b). Thetemporal variation in δ15N maximalikely results from uncertainty sur-rounding the amount of time those

Fig. 4. Mirounga angustirostris. Predicted age as a functionof size for (a) all whiskers and (b) 10 000 simulated whiskersat

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whiskers were at L∞ prior to extraction. These varia-tions fell well within the 1 to 3 mo temporal range thatcan be used to predict whisker age with appropriateconfidence (Fig. 4). Further, the growth model al-lowed us to predict the initial date of growth for eachwhisker, and the measured length of each pluckedwhisker fell within the 95% confidence intervals pre-dicted for that follicle position by the multiple regres-sion from the captive seal.

DISCUSSION

We developed and validated a broadly applicableapproach for assigning time-stamps to stable isotopeanalysis data using quantitative whisker growthdynamics derived from a captive individual. We suc-

cessfully predicted and modeled von Berta-lanffy growth parameters for individualwhisker follicles, and identified the appro-priate temporal resolution with which toestimate the age of a whisker with knownlength. Further, the growth rates calculatedfrom the captive seal enabled us to assignstable isotope analysis data from thewhiskers of free-ranging seals to appropri-ate time intervals. These are the highestresolution whisker growth data availablefor any mammal and the first in a northernelephant seal (Hobson & Sease 1998, Burton& Koch 1999, Clementz & Koch 2001, Auri-oles et al. 2006).

Elephant seal whiskers exhibited a non-linear, von Bertalanffy growth pattern con-sistent with that reported for other phocids,such as gray seals Halichoerus grypus(Greaves et al. 2004), harbor seals Phocavitulina (Hirons et al. 2001) and leopardseals Hydrurga leptonyx (Hall-Aspland etal. 2005). The dynamics of von Bertalanffygrowth allow individuals to maintain anintact whisker array by rapidly re-growingshed whiskers to a length effective for sen-sory function. This pattern of growth differsfrom the linear growth suggested for otheramphibious mammals, including otariids(Steller sea lions Eumetopias jubatus;Hirons et al. 2001) and mustelids (southernsea otters Enhydra lutris nereis; Tyrrellet al. 2013). Our model focused on largerwhiskers (>2 cm), because smaller, finerwhiskers were difficult to measure usingphotogrammetry. We observed whiskers

that were retained for well over a year; however, nofollicle exhibited 2 full growth-to-shed cycles withinthe duration of our 670 d study. Some whiskers werestill present after 500 d but none lasted all 670 d, sug-gesting that, in elephant seals, a single whisker life-span can last for nearly 2 yr but not longer.

The amount of time represented by segments ofeach whisker differed vastly depending on the loca-tion on the whisker. For instance, a 0.5 cm segment atthe base of a 10 cm whisker contained 52.5 d of forag-ing information, whereas the same size segment atthe whisker tip represented only 5.2 d of foraging in-formation. The absence of seasonal shedding patternsin our captive seal is consistent with the findings ofNewland et al. (2011) for southern elephant sealsMirounga leonina, Greaves et al. (2004) for harborseals, and Tyrrell et al. (2013) for sea otters. The ob-

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Fig. 5. (a) L∞ ≈ column + row + row2 model to predict maximum (i.e.asymptotic) length (L∞) of whiskers in each row and column, and (b)variance in the relationship between observed and predicted L∞. Themeasured length of each plucked whisker from 4 free-ranging adultfemale northern elephant seals fell within the 95% confidence intervals predicted for that follicle position by this multiple regression

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served whisker shedding trends allow animals tomaintain functional sensory systems year round.

For researchers interested in assigning age towhisker segments, we suggest plucking a whiskerthat has not reached asymptotic length (e.g. 75% ofits asymptotic length). After a whisker reaches itsmaximum length, its age is difficult to determinebecause the whisker may have just reached thislength (generally 100 to 150 d) or it could havereached L∞ more than a year prior. Therefore, agepredictions using whisker length will have higheraccuracy if the sample whisker has not reached L∞and is still growing. Because no whisker within oursampled subset had an asymptote

Mar Ecol Prog Ser 523: 243–253, 2015

Whiskers and other inert tissues record dietaryinformation over relatively long periods as animalstravel across extensive landscapes that are oftencompletely inaccessible to researchers. Quantifyingthe growth rates of such archival tissues can furtherenhance the utility of stable isotope analysis byallowing researchers to assign relatively fine-scaletemporal scales to their samples, so long as the reso-lution of the growth data respected. For instance, iso-topic signatures from whiskers depict a large diver-sity of foraging strategies (Ben-David & Schell 2001,Cherel et al. 2009, Hückstädt et al. 2012b) and spatialdistribution of prey items (Graham et al. 2010); whencoupled with information about tissue growth, theseisotope data will present a unique opportunityto reconstruct the seasonal habitats and diets of ani-mals in scenarios that render other diet techniquesimpracticable.

Acknowledgements. The authors gratefully acknowledgesupport from the following institutions and individuals: M.Gaynor, A. Bernard, and members of the Pinniped Cognitionand Sensory Systems Laboratory for their aid in data collec-tion; P. Raimondi for help with statistical analysis; D.Andreasen, T. Lambert, and the UCSC Stable Isotope Labo-ratory for aid in isotopic analysis; L. Hückstädt, C. Goetsch,K. Goetz, and other members of the Costa Lab for supportwith data and sample processing; T. Boudreaux, C. Ito andS. Walcott for aiding in photogrammetric analysis; P. Robin-son and J. Burns for helpful discussions; Clairol for animalmarking supplies; and the rangers and docents at AñoNuevo State Park for facilitating and sharing our research. Aportion of this work was performed at the University of Cal-ifornia Natural Reserve System Año Nuevo Reserve. Thelive animal use protocols for this research were reviewedand approved by the University of California Santa CruzInstitutional Animal Care and Use Committee. Researchwas conducted under National Marine Fisheries Servicemarine mammal research permits 932-1489, 14535, and14636. Financial support for this research was provided inpart by the Friends of Long Marine Laboratory StudentResearch and Education Award (to R.S.B.), Dr. Earl H. Myersand Ethel M. Myers Oceanographic and Marine BiologyTrust (to R.S.B.), and Stevenson College Student ResearchAward (to R.S.B.). Captive animal work was supported bythe Office of Naval Research (ONR), Marine Mammals andBiological Oceanography program (to C.R.). Field samplingwas supported by ONR grant N00014-08-1-1195 (to D.P.C.).

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Editorial responsibility: Christine Paetzold,Oldendorf/Luhe, Germany

Submitted: July 23, 2014; Accepted: December 30, 2014Proofs received from author(s): February 23, 2015

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