Bioaccumulation of trace metals in the calanoid copepod Metridia gerlachei from the Weddell Sea (Antarctica)

The Science of the Total Environment 295 (2002) 1–16

Bioaccumulation of trace metals in the calanoid copepod Metridia gerlachei from the Weddell Sea (Antarctica) J. Kahle, G.-P. Zauke* ¨ Oldenburg, FB Biologie (ICBM), Postfach 2503, D-26111 Oldenburg, Germany Carl von Ossietzky Universitat Received 26 September 2001; accepted 10 December 2001

Abstract Bioaccumulation of Cd, Co, Cu, Ni, Pb and Zn in the Antarctic calanoid copepod Metridia gerlachei (Giesbrecht 1902) was investigated during a cruise of RV ‘Polarstern’ to the Weddell Sea, primarily to provide information on accumulation strategies for the metals tested. With the sole exception of Cd, the copepod accumulated metals during exposure and depurated them in uncontaminated seawater. The process of uptake and depuration was successfully described by a hyperbolic model, leading to significant estimations of the following experimental bioconcentration factors (BCFs): 210 (Co), 3430 (Cu), 3060 (Ni), 670 (Pb) and 2090 (Zn). Furthermore, we provide an approach to evaluate the sensitivity of Metridia gerlachei as a biomonitor of water-borne metals in the field; the results indicate minimal increments in ambient exposure concentrations of: 0.5 mg Cu ly1 , 0.8 mg Ni ly1 , 0.6 mg Pb ly1 and 0.2 mg Zn ly1, suggesting a high sensitivity of M. gerlachei for biomonitoring. 䊚 2002 Elsevier Science B.V. All rights reserved. Keywords: Antarctic; Biomonitoring; Metals; Toxicokinetic models; Zooplankton

1. Introduction To detect potential human impact on ecosystems in routine biomonitoring programmes, it is essential to understand the organisms’ accumulation strategies, which can vary from regulation to net accumulation. Inferences regarding such strategies are highly dependent on the biological species, on the chemical element considered (Rainbow et al., 1990) and on the concentration and duration of *Corresponding author. Fax: q49-441-798-3701. E-mail address: [email protected] (G.-P.P. Zauke).

the exposure was shown by Borgmann and Norwood (1995) for the amphipod Hyalella actecax. To decide whether an organism is a suitable biomonitor for a given element is a rather long process, starting with the question of accumulation strategy. The accumulation strategy can be evaluated experimentally by modelling data derived from toxicokinetic studies, as frequently described in the literature. Strictly speaking, the models so obtained are valid only for a particular set of experimental conditions, e.g. the range of external metal exposures applied and the time chosen for uptake phases. Although the evaluation of toxicokinetic models can be regarded as an important first

0048-9697/02/$ - see front matter 䊚 2002 Elsevier Science B.V. All rights reserved. PII: S 0 0 4 8 - 9 6 9 7 Ž 0 1 . 0 1 1 4 7 - 0

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step in the calibration of biomonitors, further verification is required to decide whether such models can serve as a predictive tool for a wider range of concentrations as well as on a broader temporal and spatial scale (Zauke et al., 1995; Ritterhoff and Zauke, 1997a; Bernds et al., 1998; Clason and Zauke, 2000; Kahle and Zauke, in press). Toxicokinetic studies usually focus on the uptake of water-borne metals, which is appropriate since this is believed to be the major route by which metals enter organisms; unfortunately, not enough information is yet available to design an experimental set-up that integrates all the factors involved in cation homeostasis so as to match field conditions (e.g. biomagnification). Consequently, some authors argue that a successful verification of models demands comparison of model predictions not only with independent experimental data sets but also with results from field studies (Chapman, 1995; Marinussen et al., 1997). In our opinion, field verification requires a pronounced pollution gradient and in some cases application of the reciprocal transplant (active monitoring) approach (Walsh and Ohalloran, 1998; Tedengren et al., 1999). In any case, models must be verified in the field to show their potential for reliable predictions under field conditions before being employed in routine biomonitoring. To differentiate between natural and anthropogenic metal inputs, which is the main goal in biomonitoring, natural background concentrations of chemicals in organisms and their fluctuations have to be well established. In this respect, investigations in remote areas like the Antarctic Ocean are of increasing interest. In these areas anthropogenic metal inputs are believed to be of minor importance. Furthermore, the sensitivity of prospective biomonitors in detecting environmental changes is crucial: how large must an increase of exposure be, in both magnitude and duration, to produce a detectable increase of metal concentrations in the organisms within routine biomonitoring programs? The objective of this study is to evaluate the potential of the Antarctic calanoid copepod Metridia gerlachei (Giesbrecht, 1902) as a biomonitor for trace metals (Cd, Co, Cu, Ni, Pb, Zn). This

approach was previously outlined for Arctic zooplankton (Ritterhoff and Zauke, 1997a), for benthic invertebrates from the Wadden Sea (Bernds et al., 1998), for estuarine gammarids (Clason and Zauke, 2000) and for the Antarctic copepod Calanoides acutus (Kahle and Zauke, in press). The toxicokinetic study presented in this paper represents an integrated approach in biomonitoring, involving both field investigations and manipulative experiments (Zauke et al., 1995, 1996a). Hence we do not consider the application of radioactive isotopes, but applied metal mixtures instead of single-element dosing. The focus of this presentation is on simultaneously modelling the time course of uptake and depuration of waterborne metals with reference to a set of independent experiments. 2. Materials and methods 2.1. Sampling Zooplankton samples for the bioaccumulation experiments were collected on the cruise of RV ‘Polarstern’ ANT XVIy2 to the Weddell Sea (Fig. 1). Samples were taken with a horizontally (0.5 knt) towed bongo net from approximately 200-m depth to the surface (mesh size 500 mm and 700 mm). On board ship, the animals were transferred to polyethylene buckets containing seawater from different stations (depths)100 m) and kept alive under control conditions (see below) until the experiments were performed. 2.2. Acclimatisation The samples were sorted and allocated to the experimental vessels in a constant-temperature room (5 8C). To acclimatise the test organisms to laboratory conditions, the copepod collectives were kept for 48 h in polyethylene buckets (water temperature approximately 0 8C, no light and no food) in seawater of 33.5–34.5‰ salinity. To avoid the risk of contamination from airborne metals on the ship, the experimental vessels were not aerated. This was possible because an abundant supply of very clean seawater was available from depths below 100 m. No mortality was observed during

J. Kahle, G.-P.-P. Zauke / The Science of the Total Environment 295 (2002) 1–16

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Fig. 1. Sampling location for the copepod Metridia gerlachei in the Weddell Sea.

the experiments, either in the controls or in the exposed groups, indicating that a good water quality was maintained. 2.3. Set-up of the toxicokinetic studies To study the time course of metal uptake and depuration, test organisms were exposed for a 20day uptake phase to a metal mixture, so as to assess the integrated effect of the non-essential elements Cd, Pb and Ni and the essential elements Zn, Cu and Co. The selection of elements is the same as considered in German governmental monitoring programs (Anonymus, 1994). Subsequently, two depuration phases followed under control conditions: a 14-day depuration phase (D1) starting after 10 days of metal exposure and an 8-day depuration phase (D2) starting after the full 20 days of exposure. Reported soluble metal levels in ambient seawater (Weddell Sea) are rather low: 0.06–0.1 mg Cd ly1; 0.1–0.2 mg Cu ly1; 0.43 mg Ni ly1;

0.01–0.1 mg Pb ly1 and 0.4–0.9 mg Zn ly1 (Orren and Monteiro, 1985; Flegal et al., 1993; Nolting and deBaar, 1994; Niemisto and Perttila, 1995; Loscher, 1999). In this study we selected the nominal exposure concentrations to be approximately 100–200 times higher than the reported ambient soluble metal concentrations to achieve a compromise between considering real environmental exposures and having a chance to obtain a detectable accumulation in the trials. The experimental water was prepared from natural seawater collected at different stations (depth)100 m; settled for 24 h) in containers with 24-l volumes by adding 10 ml of a stock solution containing 12 mg Cd ly1, 12 mg Co ly1, 48 mg Pb ly1, 48 mg Ni ly1, 72 mg Cu ly1 and 144 mg Zn ly1 in double-distilled water. The stock solution itself was prepared from commercially available standard concentrates (Merck; Darmstadt, Germany). From each container one water sample was taken and stabilised with suprapure HNO3 in pre-cleaned polyethylene containers for

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J. Kahle, G.-P.-P. Zauke / The Science of the Total Environment 295 (2002) 1–16

Table 1 Measured (mean"95% confidence intervals) and nominal metal exposures (mg ly1 ) in the toxicokinetic study, just after the water change (0 h) and 24 h later Experiment

Cd

Co

Cu

Ni

Pb

Zn

0h 24 h (nominal)

5.8"0.3 6.2"0.4 (5)

4.6"0.4 3.8"1.0 (5)

31"1 28"3 (30)

20"1 21"3 (20)

21"1 21"2 (20)

68"3 69"5 (60)

Number of independent determinationss19 (0 h) and 5 (24 h); limits of detection for water samples: Cds0.05; Cos1.2; Cus ¨ 0.4; Nis1.9; Pbs0.4 and Zns2 (mg ly1) waccording to Buttner et al. (1980) as 2.6 S.D. of a ‘low value’x.

subsequent analysis by polarography (see below). Samples were not filtered because of the extremely low content of particulate matter in the ambient sea water, inferred from the fact that the bongo net was visible down to 50–75 m. The measured total recoverable metal concentrations throughout the uptake phase are reported in Table 1. The adsorptive capacity of the container walls, test chamber walls and inlets was saturated by presoaking with the test solutions for 3 days (renewal every day). To conform with official test protocols, e.g. OECD (1981), in this study the semi-static approach was chosen because of its simple and convenient set-up. The experiments were run in eight independent vessels (plastic buckets of 6-l volumes), supplied with seawater from different stations: six exposures and two controls. In all vessels the organisms were housed in polypropylene cages in order to facilitate the water renewal (semi-static approach, every 24 h). As mentioned above, no mortality was observed throughout the experiments. During the uptake phase three samples were taken randomly from the exposure treatment on days 0, 1, 2, 4, 6, 8, 10, 12, 14, 16, 18 and 20. During depuration phase D1 (which involved only part of the copepods from the experiment) samples were taken on days 11, 12, 14, 16, 18, 20, 22, 24 and during D2 on days 21, 22, 24, 26, 28. Control samples were taken on days 0, 10,16, 26 and 28. Upon sampling, at least 200 copepods were collected from each vessel under close visual observation, using a binocular microscope to ensure the absence of any foreign particles. They were placed in a small sieve and thoroughly rinsed with double-distilled water. Remaining surface water was removed from

the animals by placing the sieve on good quality filter paper, which had not caused contamination problems in previous studies involving organisms with very low metal concentrations (Zauke et al., 1996a). Subsequently, the animals were placed in Eppendorf reaction tubes (1.5 ml, polypropylene) with the aid of Teflon tweezers. Thus, we obtained three independent replicates from the exposure and the control per sampling day, each consisting of at least 200 specimens. All samples for metal determination were stored frozen at y20 8C. 2.4. Analytical procedures Copepod samples were first weighed prior to and after freeze-drying to determine the fresh weightydry weight ratio (FWyDW). After freezedrying 100 individuals were weighed to determine the individual dry mass. Aliquots of approximately 10 mg dried copepods were digested for 3 h at 80 8C with 100 ml HNO3 (65%, suprapure) in tightly closed 2-ml Eppendorf reaction tubes (Zauke et al., 1996a). The digests were made up to 2-ml volumes with double-distilled water. After appropriate dilution, the final sample and standard solutions were adjusted to concentrations of 3.25% HNO3. Metal determinations, except for Zn, were performed using a Varian SpectrAA 880 Zeeman instrument and a GTA 110 graphite tube atomiser. All elements were measured in the absorbance and concentration calibration mode using wall atomisation with Zeeman background correction. After ten samples a reslope, the second or third standard of the calibration curve, was run automatically. The elements were determined in the order of increasing ashing and atomisation temperatures

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Table 2 Quality assurance using certified reference materials randomly allocated within the determinations Tort-2 (Lobster hepatopancreas)

Cd Co Cu Ni Pb Zn

CRM 278R (Mussel tissue; Mytilus edulis)

Analysed

N

Certified

Analysed

N

Certified

25.7"0.92 0.55"0.02 109"4 2.3"0.05 0.36"0.04 201"8.9

45 49 50 49 47 35

26.7"0.6 0.51"0.09 106"10 2.5"0.19 0.35"0.13 180"6

0.31"0.01 0.34"0.01 9.08"9.45 0.94"0.04 1.83"0.08 96.0"4.7

54 56 53 52 51 35

0.35"0.007 –"– 9.45"0.13 –"– 2.00"0.04 76"2

Values are means"95% confidence intervals (mg gy1 DW). N, numbers of independent determinations; limits of detection for ¨ biological material: Cds0.1; Cos0.12; Cus4.7; Nis0.74; Pbs0.32; and Zns30 (mg gy1 DW) waccording to Buttner et al. (1980) as 2.6 S.D. of a ‘low value’x.

(600 and 1800 8C for Cd; 1000 and 2200 8C for Pb; 800 and 2300 8C for Co; 800 and 2300 8C for Cu; 800 and 2700 8C for Ni). After the determination of one element had been completed, the tube was cleaned for 5 s at 3000 8C to ensure an appropriate calzero. Nitrogen gas of grade 5.0 was used. Zn was assayed by means of an air–acetylene flame (SpectrAA-300, deuterium background correction) and a manual micro-injection method (100 ml sample volume). All metal concentrations in biological tissues are reported in mg gy1 dry weight (DW). Quality assurance was performed in line with German GLP regulations (Anonymus, 1994), using the following documented criteria: stability of instrumental recalibration, precision of parallel injections (normally showing a coefficient of variation of 1–5%), analytical blanks (also reflecting the digestion procedure). Furthermore, the precision and validity were evaluated using two certified reference materials which were randomly allocated within the determinations (see Table 2). The analysed values for the reference materials are largely in good agreement with the certified values. Limits of detection were calculated according to ¨ (Buttner et al., 1980) as mean blank plus 2.6 S.D. of a ‘low value’. Water samples from the exposure treatments were analysed in standard addition mode by polarography (Metrohm 746 VA Trace Analyser, 747 Stand, CH-9101 Herisau, Programm 5.746.0100, following DIN 38406 Teil 16) using a hanging

mercury drop electrode (HMDE) and a reference electrode filled with 3 M KCl. The linearity of the additions was checked by linear regression analysis, which gave adjusted R 2-values of G0.999. Prior to analyses, samples were degassed with nitrogen (5.0). Peaks were detected under the following conditions: y0.97 V (Zn), y0.6 V (Cd), y0.39 V (Pb), y0.16 V (Cu), y1.1 V (Co) and y0.97 V (Ni), with the application of differential pulse anodic stripping voltametry (DPASV) for Zn, Cd, Pb, Cu and adsorptive cathodic stripping voltametry (AdCSV) for Co and Ni. 2.5. Data evaluation 2.5.1. Model-1 Basically, the time course of metal uptake and depuration was evaluated on the basis of a hyperbolic model (Wilkinson, 1998, p. 688; Kahle and Zauke, in press). With the sole exception of Cd, the uptake phase (e.g. day 0–28) was evaluated using Eq. (1): CAsC0q

Cmax t tmaxy2qt

(1)

where t is time (days); CA is the mean metal concentration in animals (mg gy1 DW); C0 is CA at the start of the experiment (ts0); Cmax is the excess body burden at theoretical equilibrium (mg gy1 DW) (CAyC0 for t™`) and tmaxy2 is the time to reach half of Cmax (days). For the depuration phases D1 (day 10–24) and

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D2 (day 20–28) the following equation was employed: CAsCt*q

ŽC0yCt*.Žtyt*. Žtmaxy2qŽtyt*..

(2)

where Ct* is CA at the beginning of the depuration phase (t*s10 for D1 and 20 for D2) calculated by Eq. (1) (otherwise as defined above). A possible change in CA of the control organisms was estimated as a linear increase or decline over the duration of the experiment, starting at C 0. (3)

CconsC0qUcont

where Ccon is the mean metal concentration in the control animals, and Ucon is the rate (mg dayy1 DW) of change in body burden of the control organisms (otherwise as defined above). Due to a decline in the individual DW in the experiments a correction was necessary to estimate parameters on the basis of the initial individual DW. This correction was performed by multiplication with a time-dependent dry weight correction factor (FDW): FDWs DWt0q

DWt0 ŽDWminyDWt0. t

(4)

ŽtDWminy2qt.

Here DWt0 is the initial dry weight (mg individualy1), at the beginning of the experiment, DWmin is the minimal dry weight (mg individualy1) and tDWminy2 (days) is the half-time constant. Using this dry weight correction factor, an overestimation of model parameters due to the decrease of individual dry weight was avoided, since the increase of metal body burden due to the reduction of body mass was taken as baseline. According to this factor Eq. (3) will lead to the estimation of a significant slope only if changes in CA of the control organisms cannot be ascribed to a change in the DW. For Cd a modification of the basic model was necessary due to a decline in CA throughout the experiment. The measured data obtained during the exposure are understood as a net result of uptake and depuration of Cd by M. gerlachei in

the experiment. To model the uptake phase Eq. (2) was modified by adding the term (Ut), with U being the uptake rate of the organisms under exposure and t as the time (days) (see above). t*s0, because the uptake starts at day 0. Due to insufficient data, the uptake of Cd is modelled as a linear increase in CA during the uptake phase, certainly restricting estimations to the given set of experimental conditions: CAsC0q

ŽCmaxyC0. t Žtmaxy2qt.

qUt

(5)

Regarding the depuration phases Eq. (2) was employed, as mentioned above, but calculating Ct* by Eq. (5). Due to the non-linear decline in the body concentration of Cd in the controls, the controls were also modelled using Eq. (2), with t*s0. 2.5.2. Models 2 and 3 The basic model 1 wEqs. (1)–(4)x assumes that the depuration of metals follows the inverse kinetics of the uptake, leading to the same parameters C0 and tmaxy2 in Eqs. (1) and (2). To test whether different kinetics for the uptake and the depuration phases yield a better fit, different half-life constants for the uptake and the depuration were estimated, leading to model 2: with tmaxy2 in Eq. (1) for the uptake and tmaxDy2 in Eq. (2) for the depurations. Furthermore, a third half-life constant was taken into consideration to differentiate between the kinetics in D1 and D2, producing model 3: tmaxy2 in Eq. (1) for the uptake and tmaxD1y2 in Eq. (2) for the depuration phase D1 and tmaxD2y2 in Eq. (2) for the depuration phase D2. The significance of the better fit was assessed by comparing the residual sum of squares (RSS) of the basic model with the extended model. The more complex model was accepted when the RSS were significantly reduced, according to the sequential F-test (Draper and Smith, 1981), see Table 3. If model 2 did not yield a significantly better fit, model 3 was not tested. Bioconcentration factors (BCFs) for theoretical equilibrium were calculated as: BCFs

Cmax DCA s CW CW

Žfor t™`.

(6)

J. Kahle, G.-P.-P. Zauke / The Science of the Total Environment 295 (2002) 1–16 Table 3 Comparison of the goodness of fit for different models with increasing complexity by sequential F-test Metal (n)

Model

Mean corrected R2

LiP

Residual sum of squares

Cd

1

0.950

0.12

44.2

2

0.955

0.01

39.9

3

0.963

0.02

32.2

1

0.843

0.01

5.6

2

0.889

0.25

3.9

3

0.890

0.24

3.8

1

0.891

0.01

15 908

2

0.892

0.01

15 785

1

0.909

0.38

8546

2

0.921

0.04

7376

3

0.921

0.05

7373

1

0.953

0.02

194

2

0.953

0.01

193

1

0.827

0.60

392 121

2

0.830

0.25

384 201

3

0.831

0.19

382 531

F-value

9.07 (87)

20.20 Co

37.73 (89)

1.02 Cu

0.68 (89) Ni

12.85 (83)

0.03 Pb

0.36 (88) Zn

1.67 (83)

0.35 Critical F-valuesF85y85; 0.05(1.5 winterpolated according to Laubscher (1965)x; LiPsLilliefors probability.

To achieve the best fit for all data sets (uptake, depuration D1, depuration D2 and the controls) and to allow for the change of individual dry weight, estimations were done simultaneously in any case with SYSTAT for Windows (Version 8.0), using the NONLIN subroutine and piecewise regression option (Wilkinson, 1998, p. 643 ff). The goodness-of-fit was assessed with the aid of Lilliefors probabilities (two-tail) to test the normal distribution of residuals (Wilkinson, 1998, p. 711), a corrected R 2 (approx. coefficient of determination) and approximate t-ratios (parameter estimatesyapprox. S.E.; Bates and Watts, 1988, p. 90) compiled in Tables 3 and 4.

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3. Results The FWyDW ratio of the organisms increased throughout the experiments. From the measured FWyDW ratio and the measured individual DW, the decrease of individual FW was calculated and is diplayed in Fig. 2. The time courses for uptake and depuration of metals in M. gerlachei are shown in Figs. 3 and 4, while the estimated parameters of the hyperbolic models appear in Table 4. Generally, the organisms accumulated metals upon external metal exposure, with the sole exception of Cd, where a sharp decline is obvious (Fig. 3a; see Section 4 for more details). In contrast to Cu and Pb, for Co, Ni and Zn the residual sum of squares (RSS) were significantly reduced, when separate half-life constants for the accumulation and the depuration phases were estimated. More parameters, leading to estimates of tminD1y2 and tminD2y2 instead of one tminDy2 yield no significant reduction of the RSS for these metals (Table 3). For Cd this separation of half-life constants significantly reduced the RSS. The BCFs for theoretical equilibrium decreased in the order of Cu)Ni)Zn)Pb)Co. In any case, it is certain that the copepods eliminated the accumulated metals during the depuration phase. Statistical findings (Tables 3 and 4) and inspection of Figs. 3 and 4 suggest that our estimated models give a fair description of the observed data. Regarding approximate t-ratios, model parameters for metal uptake and depuration are largely significantly different from zero and the corrected R 2 values indicate that a high proportion of the variance is represented by the hyperbolic models. The Lilliefors probabilities support the hypothesis of normality of the residuals (as0.01) and there is a good agreement between the measured background levels (Cds12.6; Cos0.1; Cus11.4; Nis11.8; Pbs0.4; Zns425) and the model constants C0. With Cd as the sole exception, control organisms showed no significant net increase or decline in their metal body burden exceeding the effect of a reduced body mass wsee Table 4 (Ucon) and Figs. 3 and 4 (dashed lines; Ckorr)x. Thus, important preconditions for employing this toxicokinetic model are met.

J. Kahle, G.-P.-P. Zauke / The Science of the Total Environment 295 (2002) 1–16

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Table 4 Toxicokinetics of metals in Metridia gerlachei; results of hyperbolic models using simultaneous estimations Metal

Model

Parameter

Cd

3

U C0 Cmax tmaxy2 tmaxD1y2 tmaxD2y2 tmaxcon

"95% CI

T-value

0.05 12.9 0.00 2.19 5.40 18.6 0.71

0.02 0.50 0.51 0.34 1.55 13.2 0.71

4.00 51.7 n.s. 12.71 6.93 2.81 2.00

Estimate

BCF

n.a.

Co

2

C0 Cmax tmaxy2 tmaxDy2 Ucon

0.11 0.98 0.22 10.2 0.00

0.14 0.14 0.33 3.63 0.01

1.59 13.5 n.s. 5.58 n.s.

213

Cu

1

C0 Cmax tmaxy2 Ucon

13.8 106.3 15.58 y0.14

4.96 18.7 4.65 0.29

5.53 11.3 6.66 n.s.

3429

Ni

2

C0 Cmax tmaxy2 tmaxDy2 Ucon

11.4 61.2 3.72 16.3 0.08

5.9 7.69 1.92 5.44 0.29

3.88 15.8 3.85 5.94 n.s.

3056

Pb

1

C0 Cmax tmaxy2 Ucon

0.0 14.1 4.21 0.01

0.53 1.13 0.62 0.03

n.s. 24.7 13.59 n.s.

670

Zn

2

C0 Cmax tmaxy2 tmaxDy2 Ucon

431.8 141.9 1.39 4.55 0.36

38.2 44.8 2.30 4.26 1.93

22.5 6.3 n.s. 2.12 n.s.

2086

C0slocation parameter of the hyperbolic model (mg gy1 DW) (ts0); Cmax sexcess body burden at theoretical equilibrium (mg gy1 DW); tmaxy2shalf-life constant for uptake (days) (model-1); tmaxDy2 half-life constant for depuration (model-2); tmaxD1y2 and tmaxDy2 half-life constants for depuration D1 and D2 (model-3); tmaxconshalf-life constant for the controls (applied only for Cd); Usuptake rate during exposure (applied only for Cd); Uconsuptake rate for the controls; BCFsbioconcentration factorsCmax y CW (DW basis); d.f.: Cds86, Cos85, Cus88, Nis82, Pbs87 and Zns82; t-valuesestimateyS.E.; critical t-value (two sided): t80; 0.05s1.99.

4. Discussion 4.1. Model constraints

evaluation

and

experimental

Due to the decrease of the organisms’ body mass throughout the experiment, the DW correction factor was applied while performing nonlinear regression analyses in all cases. Changes in the individual dry weight (mg ind.y1) can largely

affect the modelling results for the uptake from the soluble phase when referring to dry weight (mg). A reduced body mass — for instance, due to a consumption of storage lipids, which are believed to contain negligible concentrations of the observed metals — will result in an increase of measured CA without any uptake from the water. This might explain our findings for Zn in the controls (Fig. 4g). The obvious rise in the measured body burden of the control organisms can be

J. Kahle, G.-P.-P. Zauke / The Science of the Total Environment 295 (2002) 1–16

Fig. 2. Changes of the fresh weight to dry weight ratio (FWyDW) of Metridia gerlachei in the toxicokinetic study.

fully explained by the reduced body mass, so that the increase of body burden is not significant after application of the DW correction factor (Table 4; Zn, Ucon). In this study all calculations took into account the decrease of body mass; therefore the rise in body concentration due to this process is not interpreted as uptake. Dashed lines in Figs. 3 and 4 (Mcorr and Ccorr) show the uptake, without the increase of metal concentration in the organisms due to the decrease of body mass. As outlined by Rainbow (1997), there are different ways in which metal ions can enter the cell. Considering the possibilities of passive diffusion or carrier-mediated transport and transport through protein channels as the main uptake processes, the relationship between metals in organisms (CA) and external soluble exposure (CW) can either be linear or saturable for a given time span. Experimental data reported in the literature provide evidence for both possibilities (Borgmann and Norwood, 1995; Reincke and Barthel, 1997; Ritterhoff and Zauke, 1997a; Bernds et al., 1998; Kahle and Zauke, in press). Since in the present study experiments were performed only for one exposure, no information is available on the relationship between the change in CA with increasing CW. The hyperbolic model was chosen due to its greater flexibility in this respect, so estimations are not dependent on either of the uptake mechanisms proposed. The

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resulting BCFs yield results similar to those obtained from compartment models wfor further discussion on this issue see Kahle and Zauke (in press)x. Both compartment and hyperbolic models assume the same inverse kinetics for uptake and elimination of metal ions, since the accumulated body burden is the net result of uptake and loss. For Cu and Pb a separate estimation of half-life constants for the uptake and depuration did not significantly reduce the RSS of the model. Since in simultaneous model estimations statistical results are influenced by data for the uptake as well as for the depuration, our results for Cu and Pb suggest the same depuration rate under exposure as under depuration. The depuration phase follows the uptake phase in time, which can lead to a mismatch of these inverse kinetics, as a result of intracellular changes brought about by the metal exposure. If a mismatch occurs between uptake and depuration, more complex models are required, leading to three- or more-compartment models, or in the case of hyperbolic modelling to the separate estimation of different half-life constants for the uptake and the depuration phase. Otherwise the depuration of chemicals from organisms might be overestimated, as chemicals might be retained in the organisms for a longer time than assumed, which is especially dangerous regarding environmental conditions (Butte, 1991). In the case of Cd, Co, Ni and Zn the RSS were significantly reduced by a separate estimation of half-life constants for the uptake and depuration, suggesting different depuration rates under exposure and depuration conditions (Table 3). In any case the half-life constants during the depuration phase exceeded those of the uptake (Table 4), implying a reduced rate of depuration during the depuration phase. Detoxification processes might be induced during the exposure, as shown for the formation of branchial metallothionein (MT) mRNA in oyster (Unger and Roesijadi, 1996), leading to a change of intracellular composition. Following such intracellular changes, excretory processes might run at an enhanced rate under the challenge of metal exposure, returning to reduced rates in the depuration phase because of the reduced influx of metals. The organisms in

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Fig. 3. Bioaccumulation of Cd, Co and Cu in Metridia gerlachei: time course of uptake (A) and depuration (D1 and D2), comparing observed net uptake (filled circles) and controls (open circles) with model predictions (M, C), calculated by simultaneous hyperbolic modelling including the rise in concentration due to reduced body mass (black line); pure uptake, as corrected uptake for model predictions (Mcorr) and the controls (Ccorr) (broken line); toxicokinetic parameters in Table 4; values for CW in Table 2; see text for more details.

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Fig. 4. Bioaccumulation of Ni, Pb and Zn in Metridia gerlachei: time course of uptake (A) and depuration (D1 and D2), comparing observed net uptake (filled circles) and controls (open circles) with model predictions (M, C), calculated by simultaneous hyperbolic modelling including the rise in concentration due to reduced body mass (black line); pure uptake, as corrected uptake for model predictions (Mcorr) and the controls (Ccorr) (broken line); toxicokinetic parameters in Table 4; values for CW in Table 1; see text for more details.

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this study were kept without food, so an energyconsuming depuration process might also lead to a reduced rate of depuration as the experiment proceeds. Noteworthy in this context is the decline in body mass DW (mg*100 ind.y1) of the organisms during the experiment (Fig. 2). In the case of Co the uptake is exceptionally fast: the half-life constant is approximately 5 h, so that uptake is approximately 45 times faster than release. Since the incorporation of metal ions into the organism is thought to be a relatively slow process, these findings may indicate other processes such as adsorption. In this case differences in the kinetics of uptake and depuration might be explained by the different energy requirements for adsorption and desorption. Nevertheless, for C. acutus a very short half-life constant of just 1 day has likewise been reported (Kahle and Zauke, in press). In contrast to Co, Ni and Zn, further separation of the half-life constants for the depuration into tminD1y2 and tminD2y2 did reduce the RSS significantly for Cd. Measurements of Cd show a distinct decline in body burden even during the exposure phase (Fig. 3a), indicating the ability of the copepods to depurate Cd efficiently, even under elevated soluble Cd concentrations. This capability seems to decrease with increasing external concentration and duration of exposure, leading to an increase of biological half-lives in the following order: controls)exposure)depuration 1)depuration 2. Exposed M. gerlachei depurate Cd at a lower rate than the controls, suggesting that this depuration process is suppressed under Cd exposure. This interpretation is supported by data derived from experiments with Calanoides acutus from the Weddell Sea, showing almost the same behaviour of Cd depuration decreasing with increasing external metal dosing (Kahle and Zauke, in press). The faster depuration of Cd in D1 than in D2 might be explained by the influence of the exposure, as mentioned above for Co, Ni and Zn. While in this case a longer exposure would have to enhance this effect, a deterioration of the organisms’ physiological state might also lead to reduced depuration rates, because a smaller energy supply is available for excretory processes.

The fact that depuration of Cd takes place even under control conditions points to a probable mismatch in the environmental variables (e.g. temperature, salinity, food supply) between the experimental set up and previous field conditions. For copepods from the Greenland Sea caught during the Arctic summer, Cd concentrations were found to be approximately one order of magnitude higher than those in the same species when caught just after the winter (Pohl, 1992; Ritterhoff and Zauke, 1997a). Thus, it seems very likely that these differences are related to seasonal changes. The uptake of phytoplankton has been considered as a source of Cd, leading to elevated body burden during the summer. If no phytoplankton is taken up anymore, a strong depuration mechanism might drop Cd levels even against the rise in body concentration following the loss of body weight due to the consumption of fat reserves laid down in summer (Ritterhoff and Zauke, 1997c). What the authors suggest happens throughout the Arctic winter might also be true for copepods used in our experiments. If phytoplankton is the source for the elevated Cd levels in M. gerlachei from the field, depuration will be the dominant process in our experiment since the copepods were kept without food. This interpretation might be true as long as the main uptake route is not via the soluble metal ion in the water, but by ingestion of probably highly Cd-contaminated food. Studies dealing with other uptake routes such as food, particulate matter or sediments are evidently important in this regard (Wang and Fisher, 1998, 1999). In contrast, strategies involving net accumulation of water-borne metals have been reported for Cd in other marine and estuarine crustaceans in the mg ly1 range (e.g. the decapod Palaemon elegans and the amphipod Echinogammarus pirloti; Rainbow and White, 1989). The interpretation of our findings might help to explain the contradictory results cited above, because if crustaceans possess efficient mechanisms to depurate Cd different surveys may well produce different results, depending on the physiological state of their organisms, their experimental set up, the applied metal dose and, of course, on the capability of the observed species to employ the process mentioned.

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4.2. Calibration of biomonitors For the establishment of a biomonitoring programme an interspatial and interspecific calibration is of great importance and can be achieved by a comparison of BCFs. Literature data for crustaceans from polar regions, for a comparison to our modelling results, are rather scarce. Results are available for copepods from the Greenland Sea (Ritterhoff and Zauke, 1997b) and for Calanoides acutus from the Weddell Sea (Kahle and Zauke, in press). For Pb and Zn reported BCFs (Pbs90– 200; Zns230–480; Ritterhoff and Zauke, 1997b) are somewhat lower then the results from this study (Table 4). For Cu the reported BCFs (6200– 10 000)) are approximately double. The differences between our results and those of (Ritterhoff and Zauke, 1997a) might be related to interspecific differences and different physiological states of the copepods studied. This hypothesis can be supported by the fact that the copepods from the Greenland Sea were caught at the end of their diapause (below 500 m depth), whereas the animals in this study were caught during the Antarctic summer in the upper water layer (0–200 m). Comparing our findings to those of Kahle and Zauke (in press) for C. acutus, it is interesting that both copepods show the same distinct decline in Cd body burden throughout the whole experiment. The reported BCFs for the metals Co, Cu, Ni, Pb and Zn amount to approximately 50% of those found in this study. These differences in the BCFs are unlikely to be due to different physiological states, since both copepods were caught during the same cruise, but might be due to interspecific differences like the smaller size of M. gerlachei compared to C. acutus. Investigations for the amphipod Gammarus zaddachi showed a decreasing BCF with increasing bodysize (Wang and Zauke, unpublished data). Since BCFs represent the potential for bioaccumulation, a comparative ranking is of great interest. Our results yield BCFs in the decreasing order of Cu)Ni)Zn)Pb)Co which is largely in agreement with reported data for copepods and amphipods (Kahle and Zauke, in press and literature cited therein). The essential metals Cu and Zn are usually taken up at a higher rate than

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nonessential metals under study. As in the study of C. acutus mentioned above, Ni was taken up at a fairly high rate in the present study, suggesting that it might be essential for copepods to some extent, or at least has a structure analogous to that of essential metals. In the latter case the selectivity of the uptake process would be insufficient to discriminate between Ni and the essential elements. A similar situation was inferred to explain extremely high Cd concentrations in Antarctic crustaceans that were accompanied by indications of a Cu deficiency (Petri and Zauke, 1993). 4.3. Implications for biomonitoring An important precondition for using organisms as biomonitors is a net accumulation strategy (Zauke et al., 1996b). To decide whether or not this prerequisite is met, the constraints of the exposure levels applied and the time chosen for uptake phases have to be considered. Our study suggests a net accumulation strategy for all observed metals, with the sole exception of Cd. In agreement with the present study net accumulation strategies were reported for crustaceans from polar regions with respect to Pb and Cu in Arctic zooplankton Calanus hyperboreus, Calanus finmarchicus, Metridia longa, Themisto abyssorum (Ritterhoff and Zauke, 1997a,b) and to Co, Cu, Ni, Pb and Zn in the Antarctic copepod Calanoides acutus (Kahle and Zauke, in press). When considering the use of biomonitors to evaluate environmental quality, the sensitivity of prospective biomonitors to detect environmental changes is crucial: how large must an increase of exposure be and how long must it last to produce a detectable increase of metal concentrations in the organisms within routine biomonitoring programs? The following calculations aim at providing an approximate solution to this problem. The minimum increment in body concentration which can be detected (minDCA) is obtained from the following equation: NsŽt-value*S.D.yminDCA.2. S.D. is the square root of the mean squared residuals derived from the model estimations, the

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number of samples is assumed to be Ns3, the resulting two-sided t-value (as0.05) is 4.303. Thus, the smallest detectable difference in body concentration will be a function of S.D.: minDCAs4.303y30.5*S.D. One advantage of this approach is that random errors due to independent subsamples (evaluation units) or due to the analytical procedure will be reflected in the subsequent evaluation of the sensitivity of organisms as biomonitors. Considering the experimental BCFs listed in Table 4 it is possible to calculate the approximate minimal changes in the external metal exposure necessary to produce the minimal increment in net metal uptake calculated above (minDCWsminDCA y BCF): 2.3 mg Co ly1, 9.3 mg Cu ly1, 8.3 mg Ni ly1, 5.8 mg Pb ly1 and 64.3 mg Zn ly1. Apparently, these figures depend on the assumed number of samples (here ns3), on the variability between the evaluation units, on the bioconcentration factors of water-borne metals and on a good standard in the analytical procedures, especially regarding determinations close to the limits of detection. When transferring this sensitivity to other M. gerlachei collectives it must be possible to discriminate between metal concentrations of C0 and (C0qminDCA) by the end of the uptake phase. This situation is comparable to the signaly noise ratio in analytical chemistry. Under other circumstances — for example, when transferring model predictions to organisms with a different life-history status or a different value for C0 — the estimated minDCW values vary substantially as well as the sensitivity of organisms for biomonitoring. This sensitivity will, for example, decrease with increasing C0, as has been previously demonstrated for gammarid amphipods (Clason and Zauke, 2000). However, our experimental BCFs reflect explicitly the fact that uptake of water-borne metals is valid only for the given set of experimental conditions, e.g. the range of external metal exposures applied and the time chosen for uptake phases; therefore hypotheses based on them should be regarded only as tentative. In the field other metal species might be predominant and the metals taken up might be subject to subcellular sequestration

(see discussions in Viarengo and Nott, 1993; Dallinger, 1995; Ritterhoff and Zauke, 1998). Furthermore, other uptake routes such as food, particulate matter or sediments have to be taken into account (e.g. Wang and Fisher, 1998, 1999). Therefore, field BCFs (BCFfield) are normally much higher than experimental BCFs. On the basis of our measured C0 values (mg gy1) (Cds12.6; Cos0.1; Cus11.4; Nis11.8; Pbs0.4; Zns425) and the seawater data cited in the Section 2 (no data available for Co) we propose the following field BCFs: Cds157 000; Cus76 000; Nis 27 000; Pbs8000 and Zns850 000. These yield the following tentative field-to-experimental BCF ratios: Cdsn.a.; Cus20; Nis10; Pbs10 and Zns400. Under field conditions the derived minimal increments in the exposure concentrations therefore should be corrected by the BCF ratios, leading to minDCW fieldsminDCA yBCFfield: 0.5 mg Cu ly1, 0.8 mg Ni ly1, 0.6 mg Pb ly1 and 0.2 mg Zn ly1. This suggests a high sensitivity of M. gerlachei for biomonitoring, since the concentrations would be of the same order of magnitude as metals in ambient seawater; however, further evaluation is needed. In conclusion, our results show that the calanoid copepod Metridia gerlachei may be used in biomonitoring studies to assess the environmental quality. This view is supported by a net accumulation strategy found for Co, Cu, Ni, Pb and Zn, within the constraints of our experimental design. In contrast, Cd seems to be mainly taken up via pathways other than the soluble phase and therefore cannot be evaluated by the experimental procedure used in this study. Acknowledgments We thank the captain and the crew of RV ‘Polarstern’ for their kind co-operation, as well as the participating scientists. Special thanks to J. Ritterhoff (Oldenburg) for his intensive help during the whole expedition. This study is part of the Ph.D. thesis of J. Kahle, who is supported by the ‘Studienstiftung des Deutschen Volkes’, D-53173 Bonn, Germany.

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References ¨ ¨ die Anonymus. Gemeinsames BundyLander-Meßprogramm fur ¨ ¨ ¨ Nordsee. Gewassergutemessungen im Kustenbereich der ¨ Bundesrepublik Deutschland, Gutedaten 1992y93.Nieder¨ sachsisches Umweltministerium, Hannover, Germany, 1994. Bates DM, Watts DG. Nonlinear regression analysis and its applications. New York, USA: John Wiley, 1988. ¨ Bernds D, Wubben D, Zauke G-P. Bioaccumulation of trace metals in polychaetes from the German Wadden Sea: evaluation and verification of toxicokinetic models. Chemosphere 1998;37:2573 –2587. Borgmann U, Norwood WP. Kinetics of excess (above background) copper and zinc in Hyalella azteca and their relationship to chronic toxicity. Can J Fish Aquat Sci 1995;52:864 –874. Butte W. Mathematical description of uptake, accumulation and elimination of xenobiotics in a fishywater system. Weinheim: VCH Verlagsgesellschaft, 1980. (pp. 78–88). ¨ Buttner JR, Borth R, Boutwell HJ, Broughton PMG, Bowyer RC. Approved recommendation (1978) on quality control in clinical chemistry. J Clin Chem Clin Biochem 1980;18:78 –88. Chapman PM. Extrapolating laboratory toxicity results to the field. Environ Toxicol Chem 1995;14:927 –930. Clason B, Zauke G-P. Bioaccumulation of trace metals in marine and estuarine amphipods: evaluation and verification of toxicokinetic models. Can J Fish Aquat Sci 2000;57:1410 –1422. Dallinger R. Mechanisms of metal incorporation into cells. Bilbao: Universidad del Pais Vasco, 1995. (pp. 135–154). Draper NR, Smith H. Applied regression analysis. New York: John Wiley, 1981. Flegal AR, Maring H, Niemeyer S. Anthropogenic lead in Antarctic sea water. Nature 1993;365:242 –244. Kahle J, Zauke G-P. Bioaccumulation of trace metals in the copepod Calanoides acutus from the Weddell Sea (Antarctica): comparison of two-compartment and hyperbolic toxicokinetic models. Aquat Toxicol in press. Laubscher NF. Interpolation in F-Tables. Am Stat 1965;19:28, 40. Loscher B. Relationships among Ni, Cu, Zn, and major nutrients in the Southern Ocean. Mar Chem 1999;67:67 – 102. Marinussen MPJC, Vanderzee SEATM, Dehaan FAM. Cu accumulation in Lumbricus rubellus under laboratory conditions compared with accumulation under field conditions. Ecotoxicol Environ Saf 1997;36:17 –26. Niemisto L, Perttila M. Trace elements in the Weddell Sea water and sediments in the continental shelf area. Chemosphere 1995;31:3643 –3650. Nolting RF, deBaar HJW. Behaviour of nickel, copper, zinc and cadmium in the upper 300 m of a transect in the Southern Ocean (578–628S, 498W). Mar Chem 1994;45:225 –242.

15

OECD. Guideline for testing chemicals. Bioaccumulation No. 305 A–E. Organisation for Economic Co-operation and Development, Paris, France, 1981. Orren MJ, Monteiro PMS. In: Siegfried WR, Condy PR, Laws RM, editors. Trace element geochemistry in the Southern Ocean. Berlin: Springer, 1985. p. 30 –37. Petri G, Zauke G-P. Trace metals in crustaceans in the Antarctic Ocean. Ambio 1993;22:529 –536. Pohl C. Wechselbeziehungen zwischen Spurenmetallkonzentrationen (Cd, Cu, Pb, Zn) im Meerwasser und in Zooplanktonorganismen (Copepoda) der Arktis und des Atlantiks. Ber Polarforsch 1992;101:1 –198. Rainbow PS. Ecophysiology of trace metal uptake in crustaceans. Estuarine Coastal Shelf Sci 1997;44:169 –175. Rainbow PS, White SL. Comparative strategies of heavy metal accumulation by crustaceans: zinc, copper and cadmium in a decapod, an amphipod and a barnacle. Hydrobiologia 1989;174:245 –262. Rainbow PS, Phillips DJH, Depledge MH. The significance of trace metal concentrations in marine invertebrates, a need for laboratory investigation of accumulation strategies. Mar Pollut Bull 1990;21:321 –324. Reincke T, Barthel D. Silica uptake kinetics of Halichondria panicea in Kiel Bight. Mar Biol 1997;129:591 –593. Ritterhoff J, Zauke G-P. Bioaccumulation of trace metals in Greenland Sea copepod and amphipod collectives on board ship: verification of toxicokinetic model parameters. Aquat Toxicol 1997a;40:63 –78. Ritterhoff J, Zauke G-P. Evaluation of trace metal toxicokinetics in Greenland Sea copepod and amphipod collectives from semi-static experiments on board ship. Polar Biol 1997b;17:242 –250. Ritterhoff J, Zauke G-P. Trace metals in field samples of zooplankton from the Fram Strait and the Greenland Sea. Sci Total Environ 1997;199:255 –270. Ritterhoff J, Zauke G-P. Potential role of metal-binding proteins in cadmium detoxification in Themisto libellula (Mandt) and Themisto abyssorum Boeck from the Greenland sea. Mar Environ Res 1998;45:179 –191. Tedengren M, Olsson B, Bradley B, Zhou LZ. Heavy metal uptake, physiological response and survival of the blue mussel (Mytilus edulis) from marine and brackish waters in relation to the induction of heat-shock protein 70. Hydrobiologia 1999;393:261 –269. Unger ME, Roesijadi G. Increase in metallothionein mRNA accumulation during Cd challenge in oysters preexposed to Cd. Aquat Toxicol 1996;34:185 –193. Viarengo A, Nott JA. Mini-review. Mechanisms of heavy metal cation homeostasis in marine invertebrates. Comp Biochem Physiol C Comp Toxicol 1993;104C:355 –372. Walsh AR, Ohalloran J. Accumulation of chromium by a population of mussels (Mytilus edulis (L.)) exposed to leather tannery effluent. Environ Toxicol Chem 1998;17:1429 –1438. Wang WX, Fisher NS. Accumulation of trace elements in a marine copepod. Limnol Oceanogr 1998;43:273 –283.

16

J. Kahle, G.-P.-P. Zauke / The Science of the Total Environment 295 (2002) 1–16

Wang WX, Fisher NS. Delineating metal accumulation pathways for marine invertebrates. Sci Total Environ 1999;238:459 –472. Wilkinson L. In SYSTAT 8.0 Statistics. SPSS Inc., Chicago, IL, USA, 1998. Zauke G-P, Krause M, Weber A. Trace metals in mesozooplankton of the North Sea: concentrations in different taxa and preliminary results on bioaccumulation in copepod collectives (Calanus finmarchicusyC. helgolandicus). Int Rev Ges Hydrobiol 1996;81:141 –160.

Zauke G-P, Petri G, Ritterhoff J, Meurs H-G. Theoretical background for the assessment of the quality status of ecosystems: lessons from studies of heavy metals in aquatic invertebrates. Senckenbergiana marit 1996;27:207 –214. Zauke G-P, von Lemm R, Meurs H-G, Butte W. Validation of estuarine gammarid collectives (Amphipoda: Crustacea) as biomonitors for cadmium in semi-controlled toxicokinetic flow-through experiments. Environ Pollut 1995;90:209 –219.