Element Composition of Shark Vertebrae Shows Promise As a Natural Tag

SPECIAL ISSUE CSIRO PUBLISHING

Marine and Freshwater Research, 2019, 70, 1722–1733 https://doi.org/10.1071/MF18423

Element composition of shark vertebrae shows promise as a natural tag

J. C. A. Pistevos A,B,E, P. Reis-Santos A,C, C. Izzo A,D and B. M. Gillanders A

ASouthern Seas Ecology Laboratories, School of Biological Sciences, The University of Adelaide, SA 5005, Australia. BParis Sciences et Lettres (PSL) Research University, EPHE-UPVD-CNRS, USR 3278 CRIOBE and Laboratoire d’Excellence CORAIL, BP 1013, 98729 Papetoai, Moorea, French Polynesia. CMARE – Marine and Environmental Sciences Centre, Faculdade de Cieˆncias, Universidade de Lisboa, Campo Grande, PT-1749-016, Lisboa, Portugal. DFisheries Research and Development Corporation, PO Box 2733, Kent Town, SA 5071, Australia. ECorresponding author. Email: [email protected]

Abstract. Reconstructing movements and environmental histories of sharks may be possible by using the element composition of vertebrae, but unlocking such possibilities requires an understanding of the effects of extrinsic and intrinsic factors on element composition. We assessed water temperature and pH effects (independently and in combination) on vertebral chemistry of Port Jackson sharks while accounting for intrinsic factors (condition and sex) using indoor aquaria and outdoor mesocosm environments, where the latter may better reflect natural field conditions. We analysed eight element : Ca ratios (7Li, 8B, 24Mg, 55Mn, 65Cu, 88Sr, 138Ba and 238U) by laser ablation inductively coupled plasma mass spectrometry and found positive temperature-dependant responses for multiple elements, including B : Ca, Mn : Ca, Sr : Ca and Ba : Ca (r2 ¼ 0.43, 0.22, 0.60 and 0.35 respectively), whereas pH had a minor effect on vertebral Mg : Ca and Li : Ca (r2 ¼ 0.10 and 0.31 respectively). As shown for teleost otoliths, condition affected element composition (Mn : Ca), suggesting potential physiological influences on element uptake. The suitability of vertebral chemistry as a natural tag appears to be element specific, and likely governed by a suite of potentially codependent extrinsic and intrinsic factors. Overall, variations in vertebrae chemistry show promise to reconstruct movements and habitat use of cartilaginous fishes. Yet, further research is required to understand the ubiquitous nature of the findings presented here.

Additional keywords: acidification, condition, elasmobranchs, Heterodontus portusjacksoni, hydroxyapatite, vertebrae chemistry.

Received 2 November 2018, accepted 1 May 2019, published online 13 August 2019

Introduction histories, population structure, ontogenetic movement and Calcified structures of organisms contain chemical information habitat use (McMillan et al. 2017a). that can unlock patterns of movement and habitat use by mol- Vertebrae of elasmobranchs are widely used for age and luscs and fishes, including the chemical history of their habitats. growth studies because, like otoliths, they show growth incre- In fishes, otoliths (ear bones) are inert aragonitic structures of ments that, for several species, have been validated as forming choice because they are not prone to resorption, biomineralise annually (Cailliet et al. 2004, 2006). Because vertebrae form a with daily or annual growth increments and incorporate che- birth band and grow through accretion at the marginal edge, micals from the environment that can be calibrated against time information within vertebrae can be correlated with the age of (Radtke and Shafer 1992; Campana 1999; Elsdon et al. 2008). the elasmobranch and, if time of collection is known, to a year of Increasingly, other structures of fish are also being investigated, formation. Elasmobranch vertebrae are comprised of calcium especially for threatened or endangered species, to provide phosphate (Ca3(PO4)2), with no evidence of post-deposition additional information to that obtained from otoliths (Gillanders resorption or remodelling of the chemical structure of the et al. 2011; Izzo et al. 2016a; Tzadik et al. 2017). In elasmo- mineral or protein matrix of the vertebrae during growth branchs, which do not possess otoliths, alternative cartilaginous (Clement 1992; Dean and Summers 2006; Dean et al. 2015). structures, such as jaw cartilage, vertebrae or fin spines, have Therefore, these structures are metabolically inert and provide increasingly been used for reconstructing environmental stable chronological records of shark life histories and their

Journal Compilation Ó CSIRO 2019 Open Access CC BY-NC-ND www.publish.csiro.au/journals/mfr Shark vertebrae element composition as natural tags Marine and Freshwater Research 1723 surrounding environment (Tillett et al. 2011; Smith et al. 2013; their combined effects on the chemical composition of McMillan et al. 2017a; Mohan et al. 2018). vertebrae. Several studies have examined sources of intra-individual The aim of the present study was to investigate the effects of natural variation in element composition of shark vertebrae and water temperature and pH (independently and in combination) demonstrated no variation among regions of the vertebral on vertebral element composition of an elasmobranch while column (e.g. cervical, thoracic, precaudal; Lewis et al. 2017), simultaneously: (1) considering a set of biological or intrinsic among vertebrae within similar regions of the vertebral column factors (individual shark condition and specimen sex); and (e.g. Lewis et al. 2017; McMillan et al. 2017a), with the (2) evaluating patterns of element uptake in experimental indoor exception of Zn (Raoult et al. 2018), and little to no variation aquaria v. outdoor mesocosms in relation to temperature and pH, within similar regions of a vertebra (e.g. Tillett et al. 2011; where the latter better replicates natural field conditions. Exper- Smith et al. 2016; Lewis et al. 2017). Other studies have also imental studies on otolith element incorporation in fish have examined the effects of storage and sample cleaning methods on identified differential responses between controlled aquaria shark vertebral chemistry, finding that storage in ethanol or by conditions and field observations (e.g. Elsdon and Gillanders freezing had little effect, although bleaching should be mini- 2005; Miller 2009; Reis-Santos et al. 2013, 2018). Therefore, mised because prolonged exposure can result in changes to Na, unravelling the causes for these discrepancies, including the Mg and Mn concentrations (Tillett et al. 2011; Lewis et al. 2017; potential effects of intrinsic factors under different experimental McMillan et al. 2017a; Mohan et al. 2017). conditions on element composition is essential to help interpret Element uptake and incorporation in calcified structures is a these data in complex and dynamic environments. complex process, involving passage and fractionation of dis- We used the Port Jackson shark Heterodontus portusjack- solved ions across multiple membranes or pathways (e.g. gills, soni, a medium-sized (with a maximum total length (TL) of gut, blood, endolymph; Campana 1999; McMillan et al. 2017a). 1.5 m) oviparous benthic shark endemic to southern Australia, Unlike otoliths, for which there are many experimental studies as our test species (Last and Stevens 2009). Every 9–12 examining how extrinsic (environmental) and intrinsic months, individuals lay batches of eggs that each contain a (biological) factors affect otolith chemistry (e.g. Kalish 1989; single embryo. Development occurs over a 10 to 11-month Fowler et al. 1995; Bath et al. 2000; Elsdon and Gillanders 2003; period, with initial development occurring in an egg capsule Reis-Santos et al. 2013; Sturrock et al. 2015; Martino et al. sealed by a mucous plug. After 4 months, the mucous plug 2017; Izzo et al. 2018), few studies have examined these effects breaks down, surrounding the embryo and yolk with seawater on shark vertebrae. In fact, we are aware of only a single study (Rodda and Seymour 2008). After hatching, juveniles are that directly examines the effect of extrinsic and intrinsic factors benthic. Overall, H. portusjacksoni provides an excellent on elasmobranch vertebral chemistry (Smith et al. 2013). In that model elasmobranch species for laboratory and mesocosm study, no effects or consistent relationships between somatic trials because of its restricted size, reduced habitat require- growth or vertebrae precipitation on element concentrations of ments and diet based on benthic invertebrates (e.g. echino- vertebrae were found, but Ba in the water was positively derms, molluscs, crustaceans). correlated with Ba in the vertebrae of round stingray Urobatis halleri. Temperature also negatively affected incorporation of Materials and methods Mg and Ba, and positively affected incorporation of Mn, but no effect was found for Sr (Smith et al. 2013). Egg collection and rearing of H. portusjacksoni Although knowledge of factors affecting vertebrae chemistry H. portusjacksoni eggs were collected from Edithburg, Gulf is not required for applications such as determining stock St Vincent (South Australia) by snorkelling (7 and 28 June 2013; structure, connectivity, and assessing natal and juvenile habitats n ¼ 98). Eggs were immediately transported to a temperature- (e.g. Tillett et al. 2011; Werry et al. 2011; Izzo et al. 2016b; controlled laboratory and placed in 40-L treatment tanks McMillan et al. 2017a, 2018), it helps in the interpretation of (maximum 8 eggs per tank) with an internal biological filter and such results and is required for applications such as use as an filled with natural sand-filtered seawater that was partially environmental tracer. In addition, experimental studies, exchanged every 2–3 days (minimum 40% water change). although difficult because of logistical issues with holding The embryos within the eggs were in full contact with the elasmobranchs in aquaria or mesocosms, would improve the treatment water because they lacked the mucus plug (eggs were generality of results to date. Moreover, increases of sea surface .4 months old). Treatment acclimation took place over 7 days, temperature allied to ocean acidification due to rising atmo- whereby temperature and CO2 were gradually increased by 18C spheric carbon dioxide (CO2) and consequent decreases in ocean and ,0.1 pH units for the elevated temperature and CO2 treat- pH (e.g. Doney et al. 2009; McNeil and Sasse 2016) generate a ments. In total, there were four replicate tanks per treatment, myriad of potential effects on marine biota, including on with eggs kept in either control (168C) or elevated (198C) tem- elasmobranchs’ physiology, acid–base balance, metabolism, peratures crossed with control (,400 parts per million per growth or behaviour (e.g. Green and Jutfelt 2014; Rosa et al. volume, ppmv) or elevated (,1000 ppmv) CO2 conditions 2014; Pistevos et al. 2015, 2016). Considering that increased (Fig. 1). Temperatures were maintained using heater–chiller temperatures can exacerbate effects of increased CO2 (Harvey units (TR15 Aquarium Chillers; TECO Refrigeration Technol- et al. 2013; Pistevos et al. 2015; Lefevre 2016) and that the ogies, Ravenna, Italy) and 300-W glass heaters. Pumps con- combination of these effects may also hinder the applicability of nected to the chiller units enabled even temperature distribution the chemical composition of calcified structures as natural tags throughout the water baths. Salinity was not manipulated in changing ocean conditions, it is important to further evaluate and was constant at 40 for the duration of the study, including the 1724 Marine and Freshwater Research J. C. A. Pistevos et al.

Laboratory setup Egg collection (n = 98) Eggs reared in four treatments

Control Temperature pH Temperature × pH

Eggs hatch (1–6 months) Mesocosm setup 7 months

Sharks reared in same four treatments Sharks reared in same four treatments

Control Temperature pH Temperature × pH Control Temperature pH Temperature × pH 68 days After 3 months, 33 of 98 sharks transferred to mesocosm

Vertebrae collection, preparation and analysis

Fig. 1. Summary diagram of the experimental design. The entire experimental period lasted ,7 months from egg collection to the end of the laboratory and mesocosms trials, which were run concurrently. Overall, individual Heterodontus portusjacksoni were collected as eggs and exposed to four experimental treatments (control; increased (m) pH; m temperature; m pH m temperature) from this stage onwards. Prehatching exposure lasted from 65 days to a maximum of 179 days. Once an equal number of sharks hatched from all treatments, randomly selected individuals per treatment (total n ¼ 33) were relocated to a matching mesocosm setup. acclimation period and the laboratory and mesocosm experi- treatments and manipulation methods as described above, and mental duration. Exposure before hatching ranged from a min- again with four tanks per treatment. The number of sharks in imum of 65 days to a maximum of 179 days (for data on each tank ranged from one to eight for the 150-L tanks and from hatching, see Pistevos et al. 2015). one to four for the 100-L tanks (because of differences in Thermal mass flow meters and controllers (PEGAS 4000 MF hatching time and because sharks were also transferred for the Gas Mixer; Columbus Instruments, Columbus, OH, USA) were mesocosm experiment; see below and Fig. 1). Sharks were fed used to regulate CO2 concentration in the seawater by bubbling ad libitum with thawed frozen prawns daily and kept in their enriched air directly into the experimental tanks. Temperature respective tank and treatment for a total of 68 days. Water and the pHNBS (National Bureau of Standards, NBS, scale) of parameters were measured daily (Table 1) and conditions each tank were measured daily using a temperature and pH significantly differed among treatments (see Table S1, available meter (SevenGo SG2; Mettler Toledo, Columbus, OH, USA) as Supplementary material to this paper), with water changes calibrated with fresh buffers each day. In addition, salinity and made every other day (minimum 40% total volume). Water oxygen (HandyPolaris, OxyGuard, Farum, Denmark) were parameter measurement methods are provided above. measured daily. Total alkalinity of seawater was estimated by Gran titration (888 Titrando; Metrohm, Herisau, Switzerland) Mesocosm conditions weekly. Variability in pCO2 measures are higher than for pH Once an equal number of sharks hatched from all treatments, because pCO2 was calculated using weekly measurements of randomly selected individuals per treatment (total n ¼ 36) were total alkalinity, whereas pH was measured on a daily basis. relocated to a treatment matched mesocosm setup (Fig. 1). Three Research activities described herein were undertaken with sharks were introduced in each of the 12 mesocosm tanks approval from the University of Adelaide Animal Ethics (volume 2000 L). Sand-filtered natural seawater in the meso- Committee (Permit S2013-095). cosms was from the same source as the water used in the laboratory experiments, and temperature and CO2 were manip- Experimental setup ulated using TC60 Aquarium heater and chillers (TECO Refrig- Laboratory conditions eration Technologies) and identical thermal mass flow meters As the juvenile sharks hatched they were relocated to new and controllers as in the laboratory experiments. As with the large tanks (volume 100 or 150 L) with the exact same laboratory experiments, temperature, salinity and pH were Shark vertebrae element composition as natural tags Marine and Freshwater Research 1725 it n 63 32 measured daily (Table 1) and conditions differed significantly ) 1 among treatments (see to Table S1). The mesocosms were set up 0.006 16 0.002 12 0.023 20 0.0010.002 8 9 0.008 15 0.001 9 0.004 6 to mimic the local shallow temperate reef habitat and included

U:Ca 5 kelp plants (Ecklonia radiata; mean weight 250 g per plant), mol mol m

( 1 spiny rock lobster (Jasus edwardsii; ,2 kg in weight), 1 crab (Ozius truncatus), 15 snails (Turbo undulatus), 6 urchins ) 1

(Heliocidaris erythrogramma) and .1000 herbivorous amphi- 0.285 0.012 0.2490.263 0.010 0.072 0.0880.293 0.010 0.017 0.224 0.029 0.111 0.011 0.275 0.018 pods (Cymadusa pemptos). The substratum was covered by Ba : Ca

mol mol naturally growing turf algae. Kelp, snails and urchins were m , number of individuals per tank; ( it

n replenished (three times) throughout the experiment. Like fish )

1 in the laboratory, sharks were fed ad libitum with thawed frozen 0.032 1.878 0.0360.027 1.855 2.512 0.0410.024 1.377 2.156 0.025 2.280 0.035 1.484 0.035 2.218 prawns daily, and the mesocosm trial lasted the same 68 days as the laboratory trial. A schematic summarising the experiment is Sr : Ca Heterodontus portusjacksoni mol mol

m shown in Fig. 1. ( ) 1 Vertebral sampling and preparation 1.316 3.147 2.3786.606 3.180 3.185 18.631 3.330 30.067 3.336 26.495 3.188 14.177 3.338 68.510 3.399 At the end of the laboratory and mesocosm experimental peri-

Cu : Ca ods, all sharks were killed with clove oil and TL (cm), body- mol mol m ( weight (g) and specimen sex were recorded (Table 2). Fulton’s K condition index was calculated using the following formula: ) , total number of tanks per treatment; 1 t n 7.612 9.470 3.45316.110 16.483 29.942 3.7646.758 91.784 143.529 8.025 46.380 3.563 80.391 13.110 200.720 K ¼ 100 weightClength3 Mn : Ca mol mol m ( Sections of vertebrae (n ¼ 6–12 per individual) were excised

) posterior to the cranium, separated and cleaned of excess tissue 1 before being oven dried at 508C for 24 h. Vertebrae were then 1.813 28.469 1.911 23.827 2.560 75.293 0.966 29.564 3.073 39.698 2.044 51.917 1.197 29.564 4.451 66.150 embedded in a clear-setting epoxy resin spiked with indium to Mg : Ca mol mol discriminate the vertebrae from the epoxy during elemental m ( analysis. , m

) Transverse sections ( 500 m) through the vertebral focus 1 were made using a low-speed diamond saw (Isomet; Buehler, 7.350 33.532 14.693 32.922 15.567 37.415 16.790 38.159 17.266 38.131 9.757 36.919 17.767 39.913 28.587 43.597 throughout the experimental period. Lake Bluff, IL, USA), wet polished on progressively finer % B:Ca

mol mol grades of lapping film (30, 9, 3 mm) and cleaned in ultrapure m ( water. Sections were then mounted onto microscope slides with

) indium-spiked Crystalbond (509) glue (Crystalbond CPI, West 1 0.526 187.364 1.094 183.197 0.833 231.261 0.603 268.054 1.407 312.966 1.322 209.826 1.108 281.731 1.172 336.625 Chester, PA, USA). Finally, to remove any surface contamina- tion, slides were sonicated in ultrapure water for 3 min, triple

mol mol rinsed in ultrapure water, and dried with lint-free tissues before m ( being individually stored in sealed plastic bags. , National Bureau of Standards (NBS) scale; ppmv, parts per million by volume 50.9 19.821 69.9115.0 18.369 19.351 91.964.4 22.480 24.111 15.4 20.178 39.8 25.314 43.5 25.264 NBS Element analysis (ppmv) Li : Ca pH 2 s.e.m. Salinity was constant at 40 The multielement composition of vertebrae was analysed using a CO p New Wave NWR213-ESI 213 nm ultraviolet (UV) laser (Elemental Scientific Lasers, Omaha, NE, USA) connected to an 0.1 589.4 0.10.1 1003.6 1014.3 0.20.1 680.0 734.3 0.3 661.0 0.2 470.2 0.1 517.9 Agilent 7900cx (Agilent Technologies INC, Santa Clara CA, C) 8 ( USA) inductively coupled plasma mass spectrometer (ICP-MS;

Temperature housed at Adelaide Microscopy, The University of Adelaide). Element concentrations quantified included 7Li, 8B, 24Mg, 55Mn, 0.01 16.4 0.010.01 15.9 18.7 0.010.01 17.7 19.5 0.02 18.8 0.01 17.7 0.01 19.5 65 88 138 238 43

NBS Cu, Sr, Ba and U; Ca was used as an internal standard 115 pH and In was measured as a marker to distinguish between spiked resin or CrystalBond and the sample. Laser ablations were per- t 3 7.69 5 7.68 3 8.02 3 7.98 n formed in a sealed chamber with resulting analyte transported to 2 2 the ICP-MS by a smoothing manifold in an Ar and He stream. CO CO Table 1. Experimental conditions for the laboratory and mesocosm treatments and vertebrae chemistry of the Port Jackson shark ¼ ¼ In all, 95 vertebrae (laboratory, n 63; mesocosm, n 32) were analysed at the marginal edge of the corpus calcareum, therefore mitigating any potentially confounding effects of 2 2 maternal contributions to element composition (Smith 2013; Control 4 7.96 Temperature 4 7.87 Temperature Temperature Control 3 8.11 CO Temperature 3 8.10 CO TreatmentLaboratory 16 Experiment conditions Vertebrae chemistry Unless indicated otherwise, data are given as the mean Mesocosm 12 Lewis et al. 2016). Vertebral growth was estimated to range 1726 Marine and Freshwater Research J. C. A. Pistevos et al.

Table 2. Details of the Port Jackson shark samples by treatment Unless indicated otherwise, data are given as the mean s.e.m. Fulton’s K, condition index

Treatment n Total length (cm) Bodyweight (g) Fulton’s K Percentage female

Laboratory 63 Control 16 21.71 0.33 62.69 3.32 0.61 0.02 37.5 Temperature 15 24.68 0.27 92.27 2.92 0.62 0.02 56.8

CO2 12 22.23 0.54 70.75 5.20 0.63 0.02 50.0 Temperature CO2 20 25.10 0.43 96.67 4.58 0.61 0.01 42.8 Mesocosm 32 Control 9 23.32 0.36 74.67 3.30 0.59 0.01 55.6 Temperature 6 24.75 0.89 81.00 3.34 0.55 0.05 83.3

CO2 8 22.56 0.21 66.63 2.46 0.58 0.02 61.1 Temperature CO2 9 24.00 0.50 82.10 5.33 0.59 0.03 55.6

from 98 to 130 mm among treatments based on sharks’ growth The effects of treatment tank-level extrinsic (temperature, rates from Pistevos et al. (2015) fit to a linear relationship pH) and intrinsic (individual Fulton’s K condition, specimen between TL and centrum diameter (C. Izzo, unpubl. data). Given sex) covariates on vertebral element : Ca composition were that all sharks were maintained since their time of collection as explored with general linear models using the lme4 package eggs and, most importantly, from the time of hatching to the end (ver. 1.1-19, D. Bates, M. Maechler, B. Bolker and S. Walker, of the experiment in the exact same treatment conditions, we are see https://github.com/lme4/lme4/). Prior to the modelling confident that ablated material represents recent element incor- approach, multi-collinearity of the data was evaluated among poration during the period of experimental growth. the suite of covariates using pairwise Pearson correlations. Triplicate spot ablations per vertebrae were made using a There was no evidence of collinearity among covariates, laser spot size of 40 mm, with a repetition rate of 5 Hz and an except among TL, bodyweight and temperature (Fig. S1). approximate fluence of 10 J cm2. Background concentrations TL and bodyweight were excluded from subsequent analysis, of elements within the sample chamber were measured for 30 s but Fulton’s K condition index was kept as a predictor before each ablation. For all ablations, we excluded the first because it is an adequate proxy for individual growth and 3–4 s of elemental signal (characterised by a sharp peak in the condition. raw counts data) during the signal selection process, which All vertebral element data were transformed with a log(x þ 1) cleans or removes the effect of any possible surface contami- function to meet the model assumptions of normality and nants on the sample. homoscedasticity, with the quality of model fit visually con- The National Institute of Standards glass standard (NIST-612) firmed by observation of model residuals (Fig. S2). A suite of and the USGS (United States Geological Survey) micro- models comprising all combinations of the fixed extrinsic and analytical carbonate standard (MACS-3) were analysed at the intrinsic covariates including experiment type (laboratory v. start, end and periodically throughout each session (after every 12 mesocosm) was fit to individual element data using the ‘dredge’ ablations) to correct for instrument drift and measure external function in the MuMIn package (ver. 1.15.1, K. Barton´, see precision respectively (the CV for repeated measures for all http://CRAN.R-project.org/package=MuMIn/; Barton´ 2019). elements was ,5%). Data reductions and raw count data con- The Akaike information criterion corrected for small sample versions to element concentrations (ppm) were performed using sizes (AICc) was used to identify the best model. Iolite software (ver. 3, Iolite, The University of Melbourne, Vic., The best-ranked model (based on AICc) was then rerun and Australia) and the Trace Element IS data reduction scheme (Paton the covariate effects extracted from the model. Model parsi- et al. 2011), with individual elements then expressed as ratios to mony and frequency of inclusion (and coherence of direction of Ca, based on a 43Ca percentage weightvalue for H. portusjacksoni effect) were taken into consideration if there were no differences vertebrae of 44.8 (McMillan et al. 2017a). Any outlying values in AICc among the top-ranked models. In those instances where (identified as deviating 2 s.d. of the mean of the three replicate experiment type was identified as one of the factors affecting ablations made per vertebrae) were excluded from the dataset (in vertebrae element composition, the data were partitioned into all, 24 ablations of a total 285 were removed). For each vertebrae, laboratory and mesocosm datasets and the suite of models was a minimum of two ablations was averaged to obtain a single value rerun to better understand how element incorporation differed per specimen. Limits of detection are given in Table S2. between experiment types.

Data analysis Results All analyses were undertaken in R (ver. 3.5.3, R Foundation for Temperature and pH manipulations were successful, reflected Statistical Computing, Vienna, Austria). To confirm the success the desired treatment levels and showed significant differences of experimental manipulations, variations in temperature, pH in all stages of the experimental procedure, even if temperature and pCO2 were compared by univariate analysis of variance exhibited higher within-treatment variability (Table 1; for (ANOVA; Table S1). ANOVA, see Table S1). Shark vertebrae element composition as natural tags Marine and Freshwater Research 1727

Table 3. Parameter estimates and test (t-) statistics for the best linear Model ranking for vertebral B : Ca indicated that the highest- models for each element ranked model of the suite of 40 contained the covariates When the best-ranked model contained the term ‘experiment’, the model experiment type and water temperature (r2 ¼ 0.43). When the ranking process was rerun with the data partitioned by ‘experiment type’. laboratory and mesocosm models were reranked independently Experiment type is defined as laboratory (LAB) or mesocosm (MESO). , , , (Table S4), temperature was identified as the common influen- P-values are significant at: ****, P 0.0001; ***, P 0.001; **, P 0.01; tial covariate for both experiment types, with a positive and *, P , 0.05 significant effect on vertebral B : Ca composition (Table 3; Fig. 2a, b). Element Covariates Estimate (s.e.) t-statistic For Mg : Ca, the model that contained the covariates condi-

Li : CaLAB Intercept 1.119 (0.105) 10.638**** tion and pH was the highest ranked of the model suite Condition 0.030 (0.017) 1.769* (Table S3). Overall, this model provided a relatively poor fit 2 Li : CaMESO Intercept 0.716 (1.173) 0.611 to the data (r ¼ 0.10; lowest of all the elements analysed), with pH 0.262 (0.145) 1.804* covariates revealing opposing effects on vertebral Mg : Ca B:CaLAB Intercept 1.872 (0.162) 11.527**** chemistry. pH had a positive effect (Fig. 2i), whereas increasing Temperature 0.024 (0.009) 2.653** condition (non-significantly) decreased Mg : Ca (Table 3). B:CaMESO Intercept 1.841 (0.264) 6.987**** Temperature 0.036 (0.015) 2.278** The best-ranked Mn : Ca model included condition and Mg : Ca Intercept 3.571 (0.557) 6.406**** temperature as influential covariates (Table S3), and provided 2 Condition 0.026 (0.016) 1.631 a moderate fit to the data (r ¼ 0.22). Temperature had a pH 0.144 (0.066) 2.167** significant positive effect on vertebral Mn : Ca (Fig. 2d) and Mn : Ca Intercept 0.229 (0.480) 0.477 condition had a significant negative effect (Table 3). The second Condition 0.082 (0.046) 1.792* highest-ranked model for Mn : Ca only included the temperature Temperature 0.101 (0.021) 4.740**** covariate, although model fit was reduced based on r2 (albeit a Cu : Ca Intercept 0.076 (0.026) 2.955*** minor reduction; Table S3). Temperature 0.005 (0.001) 3.404**** The model containing temperature was the highest ranked for Sr : CaLAB Intercept 0.278 (0.472) 0.589 Cu : Ca (Table S3), although with poor fit to the data (r2 ¼ 0.11), Temperature 0.084 (0.026) 3.195*** with temperature having a significant positive effect on verte- Sr : CaMESO Intercept 0.249 (1.032) 0.241 Temperature 0.128 (0.059) 2.159** bral Cu : Ca (Table 3; Fig. 2c). The second highest-ranked model Ba : Ca Intercept 0.124 (0.151) 0.826 that included pH in addition to temperature provided minor 2 Temperature 0.033 (0.008) 3.921**** improvement to the model fit (based on r ; Table S3).

U:CaLAB Intercept 0.621 The top-ranked Ba : Ca model included temperature, with U:CaMESO Intercept 0.641 (0.002) 317.052**** this predictor present in all top five models (Table S3); however, Sex (male) 0.007 (0.003) 2.128** the fit of the highest-ranked model was relatively poor (r2 ¼ 0.14). Vertebral Ba : Ca was significantly and positively affected by temperature (Table 3; Fig. 2g). Temperature had a positive and significant effect on Sr : Ca General linear models identified and ranked the influence of vertebral composition (Table 3). For Sr : Ca, the top-ranked each of the extrinsic and intrinsic covariates on element verte- model incorporated the covariates temperature and experiment bral composition and enabled us to relate vertebral element type (Table S3), and presented overall the highest model fit of all composition at the individual level to the conditions of the the elements analysed (r2 ¼ 0.60). Reranking the laboratory and individual temperature and pH treatments. The covariates most mesocosm datasets independently revealed that the best-ranked often included in the top five models for all elements were models for both experimental setups contained temperature temperature and experiment type, with specimen sex largely (Fig. 2e, f; Table S4). excluded (Table 3; Fig. 2; see also Table S3). When temperature Experiment type was the only covariate in the best-ranked was present in the best-ranked model, this covariate was model for U : Ca (Table S3). Overall, the goodness of fit for the included in all the top five best-ranked models (Table S3). best U : Ca model (r2 ¼ 0.35) was the third best overall, Overall, consistent positive temperature effects on vertebral following only that of Sr : Ca and B : Ca. When the data were element composition were observed for five of the eight ele- partitioned by experiment type, the model reranking indicated ments investigated (see B : Ca, Mn : Ca, Cu : Ca, Sr : Ca, Ba : Ca that the null model (containing no covariates) was the best- in Table 3; Fig. 2a–g), even if in some of the cases the overall ranked model for the laboratory-reared sharks. In contrast, for variance explained by the models was reduced. the mesocosm sharks, the model containing specimen sex (male Analysing each element individually, the highest ranked v. female) was the best-ranked model, with females having model for Li : Ca (based on the dredge AICc model ranking; significantly higher U : Ca ratios relative to their male counter- see to Table S3) included the covariates experiment type, parts (Table 3). condition (Fulton’s K) and pH (r2 ¼ 0.30). The top ranked laboratory model contained condition, whereas the best-ranked mesocosm model contained the term pH (Fig. 2h). Under the Discussion different experimental setups, both condition and pH had a Although we observed that intrinsic factors (condition and positive effect on Li : Ca, but with marginal significance individual’s sex) can affect elasmobranch vertebral chemistry, (P , 0.05; Table 3). extrinsic factors (temperature and pH) also affected 1728 Marine and Freshwater Research J. C. A. Pistevos et al.

(a)(b)(c) 2.40 2.55 0.03

2.35 2.50 0.02 LAB Cu MESO

B 2.30 65 B 8

8 2.45 0.01

2.25 2.40 0

16.0 17.0 18.0 19.0 20.0 16.5 17.0 17.5 18.0 18.5 16.0 17.0 18.0 19.0 20.0 Temperature (°C) Temperature (°C) Temperature (°C)

(d)(e)(f ) 2.3 1.5 1.8 2.2 1.4 1.7 2.1 1.3 1.6 LAB MESO

Mn 2.0 Sr 55 1.2 Sr 1.5 88 88 1.9 1.1 1.4 1.8 1.0 1.3 1.7 16.0 17.0 18.0 19.0 20.0 16.0 17.0 18.0 19.0 20.0 16.5 17.0 17.5 18.0 18.5 Temperature (°C) Temperature (°C) Temperature (°C)

(g)(h)(i ) 1.44 0.55 4.60 0.50 Ba Mg MESO 1.40 24 138 Li

0.45 7 4.55

0.40 1.36 4.50 16.0 17.0 18.019.0 20.0 8.058.10 8.15 7.7 7.8 7.9 8.0 8.1 8.2 Temperature (°C) pH pH

Fig. 2. Summary plot of the significant main effects of (a–g, in light grey) temperature and (h, i, in dark grey) pH on vertebrae elemental chemistry of Port Jackson shark Heterodontus portusjacksoni under aquarium and mesocosm conditions. Solid lines indicate best fit of the model, whereas shaded areas represent 95% confidence intervals. Experiment type is defined as laboratory (LAB) or mesocosm (MESO). When the best-ranked model contained the term ‘experiment’ the model was rerun with the data partitioned by ‘experiment type’. Note, all element : Ca values were log(x þ 1) transformed. See Fig. S3 for plot with data points. elasmobranch vertebral chemistry and may help with the investigated (B : Ca, Mn : Ca, Cu : Ca, Sr : Ca and Ba : Ca). reconstruction of historical movements and habitats of sharks. Although these findings are consistent with trends observed To date, only one other study has tested the effects of temper- by Smith et al. (2013) in U. halleri, there are also some clear ature and biomineralisation on vertebral element incorporation contrasting results between studies. Overall, Smith et al. (2013) in elasmobranchs (Smith et al. 2013); the present study is the identified positive temperature effects on vertebral Mn : Ca and first to also assess the effect of pH, as well as to simultaneously Zn : Ca (not tested here), but showed negative or no effects for evaluate how intrinsic individual-based factors may affect shark Mg : Ca, Ba : Ca and Sr : Ca. In both studies, Li : Ca composition vertebral chemistry. Overall, we found positive temperature- in vertebrae was not sensitive to temperature. Interspecific dependent responses for most elements, whereas pH had a differences in the effects of extrinsic factors, such as tempera- comparatively minor (positive) effect. Akin to observations in ture, on the element chemistry of calcified structures are teleost otoliths, individual condition played a role in the incor- common and widely reported in the teleost otolith element poration of specific elements (e.g. Mg or Mn; Chang and Geffen literature, including among species in a location or between 2013; Izzo et al. 2015; Sturrock et al. 2015; Reis-Santos et al. laboratory and wild-caught fish of the same species (e.g. Elsdon 2018). Yet, the lack of analogous elasmobranch studies against and Gillanders 2005; Reis-Santos et al. 2008; Chang and Geffen which to compare the present results, in combination with the 2013; Izzo et al. 2018). These differences have been attributed relative importance of ‘experiment type’ and the reduced overall to a range of physiological, metabolic or kinetic factors, variance of some models, limit the explanatory power of some including modes of incorporation (e.g. via the gut v. the gill), inferences, even if our results provide a valuable framework for an element’s role in physiological processes (e.g. essential v. both future laboratory and field measurements. non-essential) and the binding fate in the carbonate structure Consistent positive temperature effects on vertebral element (e.g. substituting for calcium or forming metal–protein com- chemistry were observed for five of the eight elements plexes; Izzo et al. 2015; Stanley et al. 2015; Sturrock et al. Shark vertebrae element composition as natural tags Marine and Freshwater Research 1729

2015; Grønkjær 2016; Thomas et al. 2017). In fact, because the scale and magnitude at which we are able to reconstruct temperature poses osmotic and physiological constraints on ion elasmobranchs’ past environmental histories or patterns of habi- regulation and uptake kinetics, it can drive element uptake and tat use. Moreover, the extent to which intrinsic factors can buffer affect the chemical composition of calcified tissues both directly or magnify environmentally mediated element incorporation in and indirectly (Loewen et al. 2016; Reis-Santos et al. 2018). calcified structures and how that potentially introduces interpre- Smith et al. (2013) also described temperature effects on rates of tation error in environmental and life history reconstructions vertebral element incorporation (by partition factors). However, remain uncertain (Kalish 1989; Sturrock et al. 2014, 2015; we cannot make inferences on changes to incorporation rates in Loewen et al. 2016; Grammer et al. 2017; Reis-Santos et al. H. portusjacksoni (even though we saw changes in vertebral 2018). Here, we found that shark condition (Fulton’s K)increased chemistry) because of a lack of water chemistry data. Neverthe- Mn : Ca and Li : Ca (for the laboratory sharks only) and assume less, the results of this study reinforce the apparent importance of that this is evidence of an intrinsic control or physiological the chemical composition of biogenic tissues, namely of Sr : Ca influence on element uptake and vertebrae chemical composition and Ba : Ca, as natural tags for environmental reconstructions (as per Izzo et al. 2015), even if further investigation is required. (Elsdon et al. 2008; Tillett et al. 2011; Smith et al. 2013; Izzo Moreover, it is unclear, for example, what role diet has in et al. 2016a). Here, approximately 38C of temperature induced affecting both the condition of an individual and vertebral changes in chemical composition (albeit with varying ranges per element composition, where both are likely to be affected by element); nevertheless, a key issue to consider is what magni- extrinsic factors such as temperature (Webb et al. 2012), although tude of variation in the factor of interest (i.e. temperature) diet did not vary among experimental treatments in the present promotes a meaningful change in element chemistry (Sturrock study. This is consistent with hypothesised among-element et al. 2012; Walther 2019). differences in how vertebral elements are affected by intrinsic The pervasive increase in pCO2 in coastal systems poten- as opposed to extrinsic factors (McMillan et al. 2017b), with Mn tially hinders the accretion of biogenic calcified structures in and Li linked to metabolism (Watanabe et al. 1997) and osmo- aquatic systems, even though mixed responses have been regulation (Fleishman et al. 1986) respectively. In teleost otoliths, observed (Wood et al. 2008; Ries et al. 2009; Cattano et al. variations in composition and element incorporation of Mn : Ca 2018). Those few studies exploring the effects of pH (or and Li : Ca have also been related to intrinsic factors directly (e.g. acidification by increased pCO2) in teleost otoliths from natural ontogeny, growth, genetics, metabolism) or indirectly (e.g. envi- (i.e. volcanic vents) and laboratory conditions have not identi- ronmental conditions influence metabolic or physiological pro- fied effects on otolith chemistry (e.g. Martino et al. 2017; cesses, including osmoregulation or biomineralisation, and thus Mirasole et al. 2017). The results of the present study indicated element uptake kinetics) (Campana 1999; Clarke et al. 2011; that pH can affect vertebral Mg : Ca and Li : Ca (albeit a weak Sturrock et al. 2015; Loewen et al. 2016; Grammer et al. 2017; effect for Li : Ca, and thus some caution must be taken). Reis-Santos et al. 2018). However, it is worth noting that Mn : Ca Considering the present study is the first to explore ocean was also significantly affected by temperature, and Li : Ca in the acidification on shark element chemistry, we are yet to gauge mesocosm sharks was affected by pH, suggesting that physiolog- how ubiquitous these results may be. However, such attempts ical controls on vertebral elements are complex and likely will be key to confirming the suitability of using these struc- influenced by environmentally mediated processes. For example, tures as natural tags and tracers of environmental acidification increased temperatures have been shown to significantly decrease in changing oceans. Uranium concentrations have been shown H. portusjacksoni growth when food is limiting (Pistevos et al. to increase with the acidity of the environment in marine 2015), and elicit declines in (Fulton’s K) condition (data not molluscan shells (Doubleday et al. 2017) and cephalopod shown), which is coincident with increases in vertebral Mn : Ca statoliths (Frieder et al. 2014), and we hypothesised a similar (Smith et al. 2013; present study). The complexity of potentially trend for U : Ca in shark vertebrae. However, that was not the codependent extrinsic and intrinsic processes and their effects on case. Overall, apatite is poorly crystallised relative to other element uptake require measures of changes in plasma ion– biogenic calcified structures, and its chemical properties (i.e. protein concentrations, because these are the shared mechanism element incorporation) are expected to differ from those of by which physiological processes modify uptake, incorporation otoliths and other structures (see McMillan et al. 2017a, and chemical composition (Grønkjær 2016). 2017b), with both biogenic (from Serratia sp. bacteria) and Here, we evaluated the consistency in patterns of vertebrae non-biogenic hydroxyapatite showing stable strontium and element composition in controlled experimental indoor aquaria cobalt sorption under a range of pH conditions (Handley- v. outdoor mesocosms, where the latter may better reflect natural Sidhu et al. 2016). Further evaluation of the sensitivity of field conditions. Mesocosms have also become paramount for d13Candd44Ca to acidification in elasmobranch vertebrae acidification trials, which cannot be performed in the natural may provide further insights into the effects of pH on these environment, with the exception of natural sea vents (Doubleday calcified structures and advance the use of vertebrae as natural et al. 2017; Mirasole et al. 2017). Despite the controlled tags (Hinojosa et al. 2012; Mirasole et al. 2017). conditions being similar between the laboratory and mesocosm, Despite positive indications, our ability to interpret variations such as water source, salinity and diet (albeit sharks sporadically in vertebrae chemistry as tracers of elasmobranch environmental predated on some organisms in the mesocosms), the inclusion of histories is still limited, and further evaluations of the effects of experiment type in some top-ranked models for individual extrinsic factors, including temperature, salinity, water chemistry elements likely reflects biological (intrinsic) and chemical and pH, are paramount to better understand common trends interactions (that may affect element availability) taking place across species and environments, as well as to gain insights into in the more complex natural ecosystem of the mesocosm, which 1730 Marine and Freshwater Research J. C. A. Pistevos et al. would be similar to what occurs in the field, where most reconstruct movements and environmental histories will be applications of vertebrae chemistry are aimed. The absence of reliant on unravelling how both extrinsic and intrinsic factors water chemistry impeded the ability to test for potential element contribute to the element chemistry, and further understanding variations or availability in the experimental setup (e.g. due to the mechanisms that directly and indirectly influence uptake and microbial activity), but given our focus was on temperature and incorporation pathways. Further research will also help in our pH variation, this was not required. Still, it is recommended that understanding of the ubiquitous nature of the findings presented future studies comparing trends between wild-caught and exper- here and in other studies that explore the suitability of vertebral imentally reared sharks (and fish) analyse the element composi- element composition as a natural tag for cartilaginous fishes. tion of the surrounding water to help interpretation of the findings. Such water chemistry may also provide a means of Conflicts of interest standardising the two datasets to improve comparisons (i.e. Bronwyn Gillanders is an Associate Editor for Marine and using partition coefficients; Elsdon and Gillanders 2005). Over- Freshwater Research. Despite this relationship, she did not at all, together with the influence of unquantified (and hard to any stage have Associate Editor-level access to this manuscript control for) individual-level intrinsic factors, there is uncer- while in peer review, as is the standard practice when handling tainty over whether trends observed in controlled laboratory manuscripts submitted by an editor to this journal. Marine and conditions would reflect field conditions and changes in natural Freshwater Research encourages its editors to publish in the populations (Elsdon and Gillanders 2005). The continued chal- journal and they are kept totally separate from the decision- lenge for the application and interpretation of chemical signals making process for their manuscripts. The authors have no to resolve environmental reconstructions, or other key ques- further conflicts of interest to declare. tions, is to account for the suite of influential extrinsic and intrinsic factors (Sturrock et al. 2014, 2015). In fact, Walther Declaration of funding (2019) suggests a signal-to-noise approach to differentiate target data from the background of other dynamic factors (natural The authors thank I. Nagelkerken and S. D. Connell for assis- variability, or intrinsic and extrinsic factors). Key to this is tance and providing funding (Australian Research Council understanding the magnitude of non-target data, because this FT120100183 and FT0991953); additional funding was pro- will allow us to resolve the magnitude of change required in the vided from Bronwyn M. Gillanders (FT100100767), the Envi- chemical gradient that enables detectable or relevant environ- ronment Institute and the School of Biological Sciences mental or movement reconstructions. The magnitude and range (The University of Adelaide). This study also had the support of of chemical variations observed were small for some elements, the Fundac¸a˜o para a Cieˆncia e Tecnologia (UID/MAR/04292/ which, together with natural variability and lower model fits, 2019) and a postdoctoral grant (SFRH/BPD/95784/2013) to emphasises the need to further address these issues under both P. Reis-Santos. laboratory and mesocosm or field conditions. Several other assumptions also need to be addressed to Acknowledgements confirm the suitability of vertebral elements as an environmental The authors thank I. Nagelkerken, S. D. Connell and the three anonymous tracer, including the need to understand potential ontogenetic reviewers for their insightful comments that improved the manuscript. The and diagenetic effects (see McMillan et al. 2017a). In previous authors also thank T. Rossi, G. Ghedini and B. Florance for their assistance studies, vertebral element incorporation was not related to with the collection of shark eggs and additional staff who helped with the daily somatic growth or vertebral biomineralisation rates (Smith maintenance of eggs and sharks in the laboratory and mesocosms (M. Olmos, N. Mertens, K. Heldt, K. Anderson, L. Falkenberg, P. Munguia, B. Russell and et al. 2013), with the exception of Zn : Ca (Raoult et al. 2018). M. Rutte). The authors thank Adelaide Microscopy, The University of However, ontogeny and biomineralisation have been shown to Adelaide, and the Australian Microscopy and Microanalysis Research Facility influence rates of element uptake in otoliths of teleost species in for the use of equipment, and in particular S. Gilbert for assistance with the some (but not all) manipulative experiments (Morales-Nin laser ablation inductively coupled plasma mass spectrometry. 2000; DiMaria et al. 2010; Fablet et al. 2011; Loewen et al. 2016). Therefore, analogous experiments designed to evaluate References the effects of somatic and vertebral growth are suggested to Barton´, K. (2019). Package ‘MuMIn’, ver. 1.43.6. Available at https://cran. compare to Smith et al. (2013), and to evaluate trends and the r-project.org/web/packages/MuMIn/MuMIn.pdf [Verified 8 August generality of results in elasmobranchs. Furthermore, informa- 2019]. tion is lacking on the relative effects of water chemistry and diet Bath, G. H., Thorrold, S. T., Jones, C. M., Campana, S. E., McLaren, J. W., on element composition in elasmobranch vertebrae (but see and Lam, J. W. (2000). Strontium and barium uptake in aragonitic Walther and Thorrold 2006; Doubleday et al. 2013) and how this otoliths of marine fish. Geochimica et Cosmochimica Acta 64, 1705– is mediated by environmental conditions (as observed in tele- 1714. doi:10.1016/S0016-7037(99)00419-6 osts; e.g. Webb et al. 2012). Cailliet,G.M.,Goldman,K.J.,Carrier,J.C.,Musick,J.A.,andHeithaus,M.R. In conclusion, we support further research into the use of (2004). Age determination and validation in chondrichthyans fishes. In shark vertebrate as natural tags. Although our work helps ‘Biology of Sharks and Their Relatives’. (Eds J. Carrier, J. A. Musick, and M. Heithaus.) pp. 399–447. (CRC Press: San Diego, CA, USA.) understand trends in elasmobranch chemistry, the suitability Cailliet, G. M., Smith, W. D., Mollet, H. F., and Goldman, K. J. (2006). Age of vertebral chemistry as a natural tag appears to be element and growth studies of chondrichthyan fishes: the need for consistency specific, as it is likely governed by a suite of potentially in terminology, verification, validation, and growth function fitting. codependent extrinsic and intrinsic factors. Hence, advances Environmental Biology of Fishes 77(3–4), 211–228. doi:10.1007/ to using the element composition of vertebrae as a tracer to S10641-006-9105-5 Shark vertebrae element composition as natural tags Marine and Freshwater Research 1731

Campana, S. E. (1999). Chemistry and composition of fish otoliths: path- Journal of Fisheries and Aquatic Sciences 52, 1431–1441. doi:10.1139/ ways, mechanisms and applications. Marine Ecology Progress Series F95-138 188, 263–297. doi:10.3354/MEPS188263 Frieder, C. A., Gonzalez, J. P., and Levin, L. A. (2014). Uranium in larval Cattano, C., Claudet, J., Domenici, P., and Milazzo, M. (2018). Living in a shells as a barometer of molluscan ocean acidification exposure.

high CO2 world: a global meta-analysis shows multiple trait-mediated Environmental Science & Technology 48, 6401–6408. doi:10.1021/ fish responses to ocean acidification. Ecological Monographs 88, ES500514J 320–335. doi:10.1002/ECM.1297 Gillanders, B. M., Elsdon, T. S., Halliday, I. A., Jenkins, G. P., Robins, J. B., Chang, M., and Geffen, A. J. (2013). Taxonomic and geographic influences and Valesini, F. J. (2011). Potential effects of climate change on on fish otolith microchemistry. Fish and Fisheries 14, 458–492. doi:10. Australian estuaries and fish utilising estuaries: a review. Marine and 1111/J.1467-2979.2012.00482.X Freshwater Research 62, 1115–1131. doi:10.1071/MF11047 Clarke, L. M., Thorrold, S. R., and Conover, D. O. (2011). Population Grammer, G. L., Morrongiello, J. R., Izzo, C., Hawthorne, P. J., Middleton, differences in otolith chemistry have a genetic basis in Menidia menidia. J. F., and Gillanders, B. M. (2017). Coupling biogeochemical tracers Canadian Journal of Fisheries and Aquatic Sciences 68, 105–114. with fish growth reveals physiological and environmental controls on doi:10.1139/F10-147 otolith chemistry. Ecological Monographs 87, 487–507. doi:10.1002/ Clement, J. (1992). Re-examination of the fine structure of endoskeletal ECM.1264 mineralization in Chondrichthyans: implications for growth, ageing and Green, L., and Jutfelt, F. (2014). Elevated carbon dioxide alters the plasma calcium homeostasis. Marine and Freshwater Research 43, 157–181. composition and behaviour of a shark. Biology Letters 10, 20140538. doi:10.1071/MF9920157 doi:10.1098/RSBL.2014.0538 Dean, M. N., and Summers, A. P. (2006). Mineralized cartilage in the Grønkjær, P. (2016). Otoliths as individual indicators: a reappraisal of the skeleton of chondrichthyan fishes. Zoology 109, 164–168. doi:10.1016/ link between fish physiology and otolith characteristics. Marine and J.ZOOL.2006.03.002 Freshwater Research 67, 881–888. doi:10.1071/MF15155 Dean, M. N., Ekstrom, L., Monsonego-Ornan, E., Ballantyne, J., Witten Handley-Sidhu, S., Mullan, T. K., Grail, Q., Albadarneh, M., Ohnuki, T., and E. P., Riley, C., Habraken, W., and Omelon, S. (2015). Mineral homeo- Macaskie, L. E. (2016). Influence of pH, competing ions, and salinity stasis and regulation of mineralization processes in the skeletons of sharks, on the sorption of strontium and cobalt onto biogenic hydroxyapatite. rays and relatives (Elasmobranchii). Seminars in Cell & Developmental Scientific Reports 6, 23361. doi:10.1038/SREP23361 Biology 46, 51–67. doi:10.1016/J.SEMCDB.2015.10.022 Harvey, B. P., Gwynn-Jones, D., and Moore, P. J. (2013). Meta-analysis DiMaria, R., Miller, J., and Hurst, T. (2010). Temperature and growth effects reveals complex marine biological responses to the interactive effects of on otolith elemental chemistry of larval Pacific cod, Gadus macroce- ocean acidification and warming. Ecology and Evolution 3, 1016–1030. phalus. Environmental Biology of Fishes 89, 453–462. doi:10.1007/ doi:10.1002/ECE3.516 S10641-010-9665-2 Hinojosa, J. L., Brown, S. T., Chen, J., DePaolo, D. J., Paytan, A., Shen, S., Doney, S. C., Fabry, V. J., Feely, R. A., and Kleypas, J. A. (2009). Ocean and Payne, J. L. (2012). Evidence for end-Permian ocean acidification

acidification: the other CO2 problem. Marketing Science 1, 169–192. from calcium isotopes in biogenic apatite. Geology 40, 743–746. doi:10. doi:10.1146/ANNUREV.MARINE.010908.163834 1130/G33048.1 Doubleday, Z., Izzo, C., Woodcock, S., and Gillanders, B. (2013). Relative Izzo, C., Doubleday, Z., Schultz, A., Woodcock, S., and Gillanders, B. contribution of water and diet to otolith chemistry in freshwater fish. (2015). Contribution of water chemistry and fish condition to otolith Aquatic Biology 18, 271–280. doi:10.3354/AB00511 chemistry: comparisons across salinity environments. Journal of Fish Doubleday, Z. A., Nagelkerken, I., and Connell, S. D. (2017). Ocean life Biology 86, 1680–1698. doi:10.1111/JFB.12672 breaking rules by building shells in acidic extremes. Current Biology 27, Izzo, C., Doubleday, Z. A., Grammer, G. L., Gilmore, K. L., Alleway, H. K., R1104–R1106. doi:10.1016/J.CUB.2017.08.057 Barnes, T. C., Disspain, M. C., Giraldo, A., Mazloumi, N., and Elsdon, T., and Gillanders, B. (2003). Relationship between water and Gillanders, B. M. (2016a). Fish as proxies of ecological and environ- otolith elemental concentrations in juvenile black bream Acanthopagrus mental change. Reviews in Fish Biology and Fisheries 26, 265–286. butcheri. Marine Ecology Progress Series 260, 263–272. doi:10.3354/ doi:10.1007/S11160-016-9424-3 MEPS260263 Izzo, C., Huveneers, C., Drew, M., Bradshaw, C. J. A., Donnellan, S. C., and Elsdon, T., and Gillanders, B. (2005). Consistency of patterns between Gillanders, B. M. (2016b). Vertebral chemistry demonstrates movement laboratory experiments and field collected fish in otolith chemistry: an and population structure of bronze whaler. Marine Ecology Progress example and applications for salinity reconstructions. Marine and Series 556, 195–207. doi:10.3354/MEPS11840 Freshwater Research 56, 609–617. doi:10.1071/MF04146 Izzo, C., Reis-Santos, P., and Gillanders, B. M. (2018). Otolith chemistry Elsdon, T. S., Wells, B. K., Campana, S. E., Gillanders, B. M., Jones, C. M., does not just reflect environmental conditions: a meta-analytic evalua- Limburg, K. E., Secor, D. H., Thorrold, S. R., and Walther, B. D. (2008). tion. Fish and Fisheries 19, 441–454. doi:10.1111/FAF.12264 Otolith chemistry to describe movements and life-history parameters of Kalish, J. M. (1989). Otolith microchemistry: validation of the effects of fishes: hypotheses, assumptions, limitations and inferences. Oceanog- physiology, age and environment on otolith composition. Journal of raphy and Marine Biology – an Annual Review 46, 297–330. doi:10. Experimental Marine Biology and Ecology 132, 151–178. doi:10.1016/ 1201/9781420065756.CH7 0022-0981(89)90126-3 Fablet, R., Pecquerie, L., de Pontual, H., Høie, H., Millner, R., Mosegaard, Last, P., and Stevens, J. (2009). ‘Sharks and Rays of Australia’, 2nd edn. H., and Kooijman, S. A. (2011). Shedding light on fish otolith biomin- (CSIRO Publishing: Melbourne, Vic., Australia.) eralization using a bioenergetic approach. PLoS One 6, e27055. doi:10. Lefevre, S. (2016). Are global warming and ocean acidification conspiring 1371/JOURNAL.PONE.0027055 against marine ectotherms? A meta-analysis of the respiratory effects

Fleishman, D. G., Saulus, A. A., and Vasilieva, V. F. (1986). Lithium in of elevated temperature, high CO2 and their interaction. Conservation marine elasmobranchs as a natural marker of rectal gland contribution in Physiology 4, cow009. doi:10.1093/CONPHYS/COW009 sodium balance. Comparative Biochemistry and Physiology – A. Physi- Lewis, J. P., Patterson, W. F., Carlson, J. K., and McLachlin, K. (2016). ology 84, 643–648. doi:10.1016/0300-9629(86)90379-8 Do vertebral chemical signatures distinguish juvenile blacktip shark Fowler, A. J., Campana, S. E., Thorrold, S. R., and Jones, C. M. (1995). (Carcharhinus limbatus) nursery regions in the northern Gulf of Experimental assessment of the effect of temperature and salinity on Mexico? Marine and Freshwater Research 67(7), 1014–1022. elemental composition of otoliths using laser ablation ICPMS. Canadian doi:10.1071/MF15088 1732 Marine and Freshwater Research J. C. A. Pistevos et al.

Lewis, J., Patterson, W., and Carlson, J. (2017). Natural variability and Raoult, V., Howell, N., Zahra, D., Peddemors, V. M., Howard, D. L., de effects of cleaning and storage procedures on vertebral chemistry of the Jonge, M. D., Buchan, B. L., and Williamson, J. E. (2018). Localized blacktip shark Carcharhinus limbatus. Journal of Fish Biology 91, zinc distribution in shark vertebrae suggests differential deposition 1284–1300. doi:10.1111/JFB.13462 during ontogeny and across vertebral structures. PLoS One 13, Loewen, T. N., Carriere, B., Reist, J. D., Halden, N. M., and Anderson, W. G. e0190927. doi:10.1371/JOURNAL.PONE.0190927 (2016). Linking physiology and biomineralization processes to ecologi- Reis-Santos, P., Vasconcelos, R., Ruano, M., Latkoczy, C., Gu¨nther, D., cal inferences on the life history of fishes. Comparative Biochemistry Costa, M., and Cabral, H. (2008). Interspecific variations of otolith and Physiology – A. Molecular & Integrative Physiology 202, 123–140. chemistry in estuarine fish nurseries. Journal of Fish Biology 72, 2595– doi:10.1016/J.CBPA.2016.06.017 2614. doi:10.1111/J.1095-8649.2008.01871.X Martino, J., Doubleday, Z. A., Woodcock, S. H., and Gillanders, B. M. Reis-Santos, P., Tanner, S. E., Elsdon, T. S., Cabral, H. N., and Gillanders, (2017). Elevated carbon dioxide and temperature affects otolith devel- B. M. (2013). Effects of temperature, salinity and water composition on opment, but not chemistry, in a diadromous fish. Journal of Experimen- otolith elemental incorporation of Dicentrarchus labrax. Journal of tal Marine Biology and Ecology 495, 57–64. doi:10.1016/J.JEMBE. Experimental Marine Biology and Ecology 446, 245–252. doi:10. 2017.06.003 1016/J.JEMBE.2013.05.027 McMillan, M. N., Izzo, C., Wade, B., and Gillanders, B. (2017a). Elements Reis-Santos, P., Vasconcelos, R. P., Tanner, S. E., Fonseca, V. F., Cabral, and elasmobranchs: hypotheses, assumptions and limitations of elemen- H. N., and Gillanders, B. M. (2018). Extrinsic and intrinsic factors shape tal analysis. Journal of Fish Biology 90, 559–594. doi:10.1111/JFB. the ability of using otolith chemistry to characterise estuarine environ- 13189 mental histories. Marine Environmental Research 140, 332–341. doi:10. McMillan, M. N., Izzo, C., Junge, C., Albert, O., Jung, A., and Gillanders, 1016/J.MARENVRES.2018.06.002 B. M. (2017b). Analysis of vertebral chemistry to assess stock structure Ries, J. B., Cohen, A. L., and McCorkle, D. C. (2009). Marine calcifiers

in a deep-sea shark, Etmopterus spinax. ICES Journal of Marine Science exhibit mixed responses to CO2-induced ocean acidification. Geology 74(3), 793–803. doi:10.1093/ICESJMS/FSW176 37, 1131–1134. doi:10.1130/G30210A.1 McMillan, M. N., Huveneers, C., Semmens, J. M., and Gillanders, B. M. Rodda, K., and Seymour, R. (2008). Functional morphology of embryonic (2018). Natural tags reveal populations of conservation dependent development in the Port Jackson shark Heterodontus portusjacksoni school shark use different pupping areas. Marine Ecology Progress (Meyer). Fish Biology 72(4), 961–984. doi:10.1111/J.1095-8649.2007. Series 599, 147–156. doi:10.3354/MEPS12626 01777.X McNeil, B. I., and Sasse, T. P. (2016). Future ocean hypercapnia driven by Rosa, R., Baptista, M., Lopes, V. M., Pegado, M., Paula, J., Tru¨benbach, K., anthropogenic amplification of the natural CO2 cycle. Nature 529, 383. Leal, M., Calado, R., and Repolho, T. (2014). Early-life exposure to doi:10.1038/NATURE16156 climate change impairs tropical shark survival. Proceedings of the Royal Miller, J. A. (2009). The effects of temperature and water concentration on Society of London – B. Biological Sciences 281, 20141738. doi:10.1098/ the otolith incorporation of barium and manganese in black rockfish RSPB.2014.1738 Sebastes melanops. Journal of Fish Biology 75, 39–60. doi:10.1111/ Smith, W. D. (2013). Vertebral elemental markers in elasmo- J.1095-8649.2009.02262.X branchs: potential for reconstructing environmental history and Mirasole, A., Gillanders, B., Reis-Santos, P., Grassa, F., Capasso, G., population structure. Ph.D. Thesis, Oregon State University, Scopelliti, G., Mazzola, A., and Vizzini, S. (2017). The influence of Corvallis, OR, USA.

high pCO2 on otolith shape, chemical and carbon isotope composition of Smith, W. D., Miller, J. A., and Heppell, S. S. (2013). Elemental markers six coastal fish species in a Mediterranean shallow CO2 vent. Marine in elasmobranchs: effects of environmental history and growth on Biology 164, 191. doi:10.1007/S00227-017-3221-Y vertebral chemistry. PLoS One 8, e62423. doi:10.1371/JOURNAL. Mohan, J. A., TinHan, T. C., Miller, N. R., and Wells, R. J. (2017). Effects of PONE.0062423 sample cleaning and storage on the elemental composition of shark Smith, W. D., Miller, J. A., Ma´rquez-Farı´as, J. F., and Heppell, S. S. (2016). vertebrae. Rapid Communications in Mass Spectrometry 31, 2073–2080. Elemental signatures reveal the geographic origins of a highly migratory doi:10.1002/RCM.7998 shark: prospects for measuring population connectivity. Marine Ecology Mohan, J. A., Miller, N. R., Herzka, S. Z., Sosa-Nishizaki, O., Kohin, S., Progress Series 556, 173–193. doi:10.3354/MEPS11844 Dewar, H., Kinney, M., Snodgrass, O., and Wells, D. R. (2018). Elements Stanley, R. R., Bradbury, I. R., DiBacco, C., Snelgrove, P. V., Thorrold, S. R., of time and place: manganese and barium in shark vertebrae reflect age and Killen, S. S. (2015). Environmentally mediated trends in otolith and upwelling histories. Proceedings of the Royal Society of London – composition of juvenile Atlantic cod (Gadus morhua). ICES Journal of B. Biological Sciences 285, 20181760. doi:10.1098/RSPB.2018.1760 Marine Science 72, 2350–2363. doi:10.1093/ICESJMS/FSV070 Morales-Nin, B. (2000). Review of the growth regulation processes of Sturrock, A., Trueman, C., Darnaude, A., and Hunter, E. (2012). Can otolith otolith daily increment formation. Fisheries Research 46, 53–67. elemental chemistry retrospectively track migrations in fully marine doi:10.1016/S0165-7836(00)00133-8 fishes? Journal of Fish Biology 81, 766–795. doi:10.1111/J.1095-8649. Paton, C., Hellstrom, J., Paul, B., Woodhead, J., and Hergt, J. (2011). Iolite: 2012.03372.X freeware for the visualisation and processing of mass spectrometric data. Sturrock, A. M., Trueman, C. N., Milton, J. A., Waring, C. P., Cooper, M. J., Journal of Analytical Atomic Spectrometry 26, 2508–2518. doi:10.1039/ and Hunter, E. (2014). Physiological influences can outweigh environ- C1JA10172B mental signals in otolith microchemistry research. Marine Ecology Pistevos, J. C., Nagelkerken, I., Rossi, T., Olmos, M., and Connell, S. D. Progress Series 500, 245–264. doi:10.3354/MEPS10699 (2015). Ocean acidification and global warming impair shark hunting Sturrock, A., Hunter, E., Milton, A. J., EIMF, Johnson, R. C., Waring, C. P., behaviour and growth. Scientific Reports 5, 16293. doi:10.1038/ and Trueman, C. N. (2015). Quantifying physiological influences on SREP16293 otolith microchemistry. Methods in Ecology and Evolution 6, 806–816. Pistevos, J. C., Nagelkerken, I., Rossi, T., and Connell, S. D. (2016). doi:10.1111/2041-210X.12381 Antagonistic effects of ocean acidification and warming on hunting Thomas, O. R., Ganio, K., Roberts, B. R., and Swearer, S. E. (2017). sharks. Oikos 126(2), 241–247. doi:10.1111/OIK.03182 Trace element–protein interactions in endolymph from the inner ear Radtke, R., and Shafer, D. (1992). Environmental sensitivity of fish otolith of fish: implications for environmental reconstructions using microchemistry. Marine and Freshwater Research 43, 935–951. doi:10. fish otolith chemistry. Metallomics 9, 239–249. doi:10.1039/ 1071/MF9920935 C6MT00189K Shark vertebrae element composition as natural tags Marine and Freshwater Research 1733

Tillett, B., Meekan, M., Parry, D., Munksgaard, N., Field, I., Thorburn, D., Watanabe, T., Kiron, V., and Satoh, S. (1997). Trace minerals in and Bradshaw, C. (2011). Decoding fingerprints: elemental composition fish nutrition. Aquaculture 151, 185–207. doi:10.1016/S0044- of vertebrae correlates to age-related habitat use in two morphologically 8486(96)01503-7 similar sharks. Marine Ecology Progress Series 434, 133–142. doi:10. Webb, S., Woodcock, S., and Gillanders, B. (2012). Sources of otolith 3354/MEPS09222 barium and strontium in estuarine fish and the influence of salinity and Tzadik, O. E., Curtis, J. S., Granneman, J. E., Kurth, B. N., Pusack, T. J., temperature. Marine Ecology Progress Series 453, 189–199. doi:10. Wallace, A. A., Hollander, D. J., Peebles, E. B., and Stallings, C. D. 3354/MEPS09653 (2017). Chemical archives in fishes beyond otoliths: a review on the Werry, J., Lee, S., Otway, N., Hu, Y., and Sumpton, W. (2011). A multi- use of other body parts as chronological recorders of microchemical faceted approach for quantifying the estuarine–nearshore transition in constituents for expanding interpretations of environmental, ecological, the life cycle of the bull shark, Carcharhinus leucas. Marine and and life-history changes. Limnology and Oceanography, Methods 15, Freshwater Research 62, 1421–1431. doi:10.1071/MF11136 238–263. doi:10.1002/LOM3.10153 Wood, H. L., Spicer, J. I., and Widdicombe, S. (2008). Ocean acidification Walther, B. D. (2019). The art of otolith chemistry: interpreting patterns may increase calcification rates, but at a cost. Proceedings of the Royal by integrating perspectives. Marine and Freshwater Research. Society of London – B. Biological Sciences 275, 1767–1773. doi:10. [Published online early 21 January 2019]. doi:10.1071/MF18270 1098/RSPB.2008.0343 Walther, B., and Thorrold, S. (2006). Water, not food, contributes the majority of strontium and barium deposited in the otoliths of a marine fish. Marine Ecology Progress Series 311, 125–130. doi:10.3354/ MEPS311125 Handling Editor: Benjamin Walther