Growth Retardation and Altered Isotope ... - ACS Publications

Article pubs.acs.org/est

Growth Retardation and Altered Isotope Composition As Delayed Effects of PCB Exposure in Daphnia magna Caroline Ek,*,† Zandra Gerdes,† Andrius Garbaras,‡ Margaretha Adolfsson-Erici,† and Elena Gorokhova† †

Department of Environmental Science and Analytical Chemistry, Stockholm University, Svante Arrhenius väg 8, SE-106 91 Stockholm, Sweden ‡ Mass Spectrometry Laboratory, Center for Physical Science and Technology, Savanoriu 231, LT-02300 Vilnius, Lithuania S Supporting Information *

ABSTRACT: Trophic magnification factor (TMF) analysis employs stable isotope signatures to derive biomagnification potential for environmental contaminants. This approach relies on species δ15N values aligning with their trophic position (TP). This, however, may not always be true, because toxic exposure can alter growth and isotope allocation patterns. Here, effects of PCB exposure (mixture of PCB18, PCB40, PCB128, and PCB209) on δ15N and δ13C as well as processes driving these effects were explored using the cladoceran Daphnia magna. A two-part experiment assessed effects of toxic exposure during and after exposure; juvenile daphnids were exposed during 3 days (accumulation phase) and then allowed to depurate for 4 days (depuration phase). No effects on survival, growth, carbon and nitrogen content, and stable isotope composition were observed after the accumulation phase, whereas significant changes were detected in adults after the depuration phase. In particular, a significantly lower nitrogen content and a growth inhibition were observed, with a concomitant increase in δ15N (+0.1 ‰) and decrease in δ13C (−0.1 ‰). Although of low magnitude, these changes followed the predicted direction indicating that sublethal effects of contaminant exposure can lead to overestimation of TP and hence underestimated TMF.

■

INTRODUCTION Stable isotope analysis (SIA) of nitrogen and carbon (δ15N and δ13C) is a standard tool for trophic structure analysis.1 In ecotoxicology, SIA has been used to determine the bioaccumulation potential of contaminants using the Trophic Magnification Factor (TMF) approach.2 Briefly, the TMF is the slope of the regression for log contaminant concentration versus trophic position (TP) in a food web; the slope is indicative of the biomagnification potential of the contaminant.3 To estimate TP in TMF, analysis of δ15N signatures is commonly used3 compared to more traditional stomach content analysis and fatty acid analysis.4 This approach assumes that the δ15N value of an organism accurately represents the dietary input plus a trophic discrimination factor (Δ, 3−4 ‰ for δ15N;1,5 1−2 ‰ for δ13C).1,6 The overall accuracy of TMF analysis strongly depends on the TP estimates,3 which, in turn, depends on whether the trophic discrimination factors (Δ) represent the true differences in isotope values between the diet and the consumers. The latter may, however, not always be the case, particularly, in the disturbed ecosystems. The variability in Δ-values related to tissues analyzed, diet isotope values, trophic preferences, and, possibly, also contaminant exposure7−9 is becoming acknowledged in the TMF approach. Uncertainties associated with TP estimates in the TMF analysis has led to the use of discrimination factors © XXXX American Chemical Society

that are specific for area, taxa, and functional-group of consumers.10,11 Recently, the complex of uncertainties in TP assessment affecting TMF estimates has been addressed using Bayesian inference,12 which resulted in improved precision of the estimated TMF. The influence of contaminant exposure on δ15N values, and thus on TP estimates, is particularly interesting for the methodology of TMF approach, because δ15N values are assumed to be independent of the contaminant body burden. However, the effects of chronic exposure on individuals’ physiology and further on stable isotope values are increasingly recognized, because this exposure is incurred with physiological costs.13 Consequently, stress and compromised health may affect various physiological processes underlying isotope fractionation and distribution in the body. In consumers, Δ15N is affected by dietary nitrogen imbalance due to either reduced protein content or low protein quality.14,15 However, various responses in metabolic pathways related to nitrogen metabolism, such as synthesis of detoxifying proteins,13 may also alter bulk δ15N.16 Further, increased protein turnover Received: April 7, 2016 Revised: July 1, 2016 Accepted: July 1, 2016

A

DOI: 10.1021/acs.est.6b01731 Environ. Sci. Technol. XXXX, XXX, XXX−XXX

Article

Environmental Science & Technology incurs costs on growth,17 an important driver for Δ15N.15 Thus, in addition to the direct metabolic effects related to detoxification, toxic exposure may indirectly affect animal δ15N values by altering growth and/or element turnover.9 In addition, concurrent measurements of δ13C values are often applied in TMF analysis to assign organisms to a specific food web within the ecosystem when evaluating the relationship between the TP and the contaminant level.3 Similar to δ15N, the δ13C values may also be influenced by stress exposure, due to the changes in metabolism.18 The δ13C values reflect mass-specific respiration due to the preferential removal of the isotopically light 12CO2.19 Therefore, fast-growing individuals having higher weight-specific respiration20 would become enriched in 13C. Other metabolic processes causing carbon losses can also lead to isotopic shifts of bulk biomass. For example, consumption of storage fats, which are depleted in 13C relative to bulk,21 would elevate the animal δ13C values. Together, this suggests that stress-related changes in respiration and metabolism can have both direct and indirect effects on δ13C. As a result of these direct and indirect responses leading to isotopic alterations, the observed net effects of toxic exposure on isotopic signatures may vary, with both upward and downward shifts, and with effects being both tissue,22 species-, and contaminant-specific.23 For example, in daphnids exposed to the pesticide lindane, the size-specific δ15N and δ13C values were higher compared to the unexposed animals.9 The authors suggested that these effects were caused by a combination of increased turnover rate, due to detoxification, and greatly decreased growth rate. By contrast, the Eurasian perch exposed to DDT did not exhibit any significant differences in either growth or isotopic signatures compared to the unexposed fish.24 In human biology, nonhuman animal ecology and biomedicine, the innovations in the application of stable isotopes have recently moved beyond diet reconstruction into topics closely allied with physiology and disease processes;25 these approaches have great potential to improve our understanding of the isotopic responses to various stressors, including chemical exposure. By taking into account not just characteristic stable isotope signatures of the diets, but also the physiological factors influencing how stable isotope ratios are fixed by the body under stress and disease conditions, we can advance SIA applications in ecology and ecotoxicology. The aim of this study was to explore the complex effects of toxic exposure on δ15N and δ13C values in Daphnia magna (Straus, 1820). As a model substance, we used a mixture of polychlorinated biphenyls (PCBs). We expected that PCB exposure would affect somatic and reproductive growth, body carbon (%C) and nitrogen (%N) content, and the stable isotope composition (Figure 1). These changes would occur in response to altered resource allocation due to detoxification25 and differential incorporation of carbon and nitrogen.9,26 In particular, we hypothesized that, compared to the controls, PCB-exposed daphnids would have the following: (1) Lower %C and %N (Hypothesis 1) as a result of metabolic costs of detoxification and changes in nutrient allocation;18 (2) Lower body size and fecundity (Hypothesis 2), due to the increased metabolic costs and resource limitation for growth; (3) Higher 15N fractionation (Hypothesis 3) as a result of intensified trans- and deamination during the metabolic

Figure 1. Conceptual model illustrating (A) expected and (B) observed effects (black lines) of PCB exposure on δ15N and δ13C; the effects are primarily mediated via reduced growth due to altered resource allocation. In addition, effects on δ15N may result from an increased protein breakdown (lower nitrogen content, %N). A positive or negative direction of effects (+ or −) is related to an increased value of the driver.

turnover of proteins involved in detoxification,27 and nitrogen imbalance; (4) Lower 13C fractionation due to the lower growth, and thus lower weight-specific respiration (Hypothesis 4). In addition to the allometric considerations20 behind the hypothesized 13C allocation, the rationale is that PCB exposure can impair both growth28 and swimming (and thus, respiratory function) in daphnids.29 These hypotheses were tested experimentally by feeding newborn Daphnia magna with PCB-contaminated food for 3 days to allow for PCB accumulation in the body. After that, the animals were offered noncontaminated food, which, in concert with growth dilution, resulted in a substantial decrease of the body burden. This experimental design was intended to mimic a pulse exposure of PCBs with a subsequent depuration: an ecologically relevant scenario following the influx of resuspended sediments and/or runoff with high concentrations of PCBs into the water column and subsequent sedimentation.30 The animals were sampled at the end of the exposure (juveniles) and at the end of the depuration period (eggbearing adults) to analyze changes in their somatic and reproductive growth, elemental composition and isotope values (Figure 2). Also, the PCB concentrations were measured on the same occasions. We expected to find support for the hypothesized effects in juveniles that had a high body burden of PCBs, whereas the detectability of the effects after the depuration was open-ended.

■

MATERIALS AND METHODS Test Organisms. As a test organism, we used the freshwater cladoceran Daphnia magna. The animals were cultured in glass beakers containing M7 media (OECD standards 20231 and 21132) at a density of 10 individuals L−1 and fed a mixture of green algae, Pseudokirchneriella subcapitata and Scenedesmus spicatus. These algae were cultured in MBL medium on a shaking table under constant light (70 μE cm−2 s−1) and temperature (24 °C). Algal concentrations were determined using a 10 AU Field Fluorometer (Turner designs, Sunnyvale, California, U.S.). Polychlorinated Biphenyls (PCBs). A mixture of four nondioxin-like PCB congeners was used: PCB18 (2,2,5Trichlorobiphenyl), PCB40 (2,2′,3,3′-Tetrachlorobiphenyl), PCB128 (2,2′,3,3′,4,4′-hexachlorobiphenyl), and PCB209 (AccuStandard Inc., New Haven, CT). The rationale for choosing the specific congeners was to achieve a mixture with B


Article

Environmental Science & Technology

lower than the estimated baseline toxicity LC50 value (D. magna) for PCB-128 (29.1 μg L−1);33 this implies that only sublethal effects would be observed during the experiment. At the start of the experiment, neonates (2).

■

RESULTS Mortality was low in both treatments, with 7% and 4% during the accumulation phase and 1% and 6% during the depuration phase for the control and exposed animals, respectively. At the end of the accumulation phase, a 5- to 6-fold increase in the individual DW was observed in all incubations, which implies that measured isotope values represented the equilibrium state with the diet.9 Part I: Accumulation Phase. In the exposed juveniles, the total PCB body burden was 13.3 ± 6.3 μg g Daphnia−1 (mean ± SD; Table S2), with no detectable levels observed in the control. No significant treatment effects on the body DW, BL, %C or %N in the juvenile daphnids were observed (Table 1). Moreover, no significant treatment effects were observed for either δ15N or δ13C, and these values were unrelated to body DW, %C, and %N (Table 1). In the control and exposed daphnids, the δ15N values were 2.8 ‰ and 3.2 ‰, respectively, with the diet-consumer discrimination factors of +1.9 ‰ and D


Article

Environmental Science & Technology +2.2 ‰. However, the variance for δ15N was significantly lower in the control compared to the PCB treatment (s2control = 0.007 and s2PCB = 0.42; F-test: F3,4 = 0.0179, p-value 90 μg g Daphnia−1 (>7-fold higher than levels observed in juveniles after the accumulation phase).44 By contrast, studies with various Aroclors indicate higher toxicity,45 due to the presence of the more toxic dioxin-like PCBs in these mixtures.46 The δ15N values were best explained by individual DW variability (Table 1). Higher δ15N in the adults from the exposed group was observed, albeit the difference from the control was only 0.1 ‰, the difference so small that the measurement uncertainty becomes an issue. Thus, the observed growth inhibition during the depuration phase was significantly positively related to 15N fractionation supporting Hypothesis 3, although the absolute difference was within the measurement error. Moreover, the difference in the mixed δ15N values for PCB exposed and control daphnids, respectively, was also small, 0.2 ‰; translating to TP of 1.6 and 1.5, respectively. This implies that the increase in daphnid δ15N induced by shortterm PCB exposure has low ecological significance and could only slightly increase TP estimate. One can speculate, however, that this effect can be more pronounced higher up in the food chain. The metabolic transformation capacity of contaminants is known to increase with increasing TP, with the biotransformation potential of, e.g., cytochrome P-450 being highest in mammals and birds,11,47 whereas it is moderate in fish and low in invertebrates.38,47 Metabolic transformation and detoxification are associated with alterations in protein synthesis and physiological costs, which may reduce C and N allocation and impair growth. Thus, effects of toxic exposure could both propagate from low to high trophic levels and be of higher magnitude in the organisms with elevated capacity to metabolize xenobiotics. The δ13C values were only 0.1 ‰ lower in the exposed animals compared to the controls. Similar to the δ15N values, the variability in the δ13C values was best explained by the individual DW variability. These results support Hypothesis 4 with regard to the exposure effects being mediated via growth. However, the low absolute shift δ13C values implies that tracing dietary carbon sources would not be markedly affected by pollution. Noteworthy are the deviating diet-consumer discrimination factors for both δ15N and δ13C compared to the Δ15N and Δ13C values commonly applied in TP analysis. The Δ15N values in D. magna fed green algae were 1.8−2.2 ‰, whereas Δ15N of 3.4 ‰ would be applied to calculate TP. These results are in line with previously reported lower Δ15N values for aquatic herbivorous invertebrates,48 suggesting 3.4 ‰ might not be a suitable value for primary consumers. For Δ13C, the F



■

factors, and climatic conditions can collectively contribute to physiological stress leading to change in the isotopic fractionation. In summary, evidence is accumulating that exposure to environmental contaminants can cause changes in δ15N and thus affect estimates of TP and TMF. However, little is known about the physiological processes driving these effects as well as their magnitude under various exposure regimes. We have linked effects of PCB exposure to physiologically predictable changes in both δ15N and δ13C resulting from growth inhibition. However, the low absolute differences in the δ15N for the exposed and control animals suggest that under a pulse exposure exerting very low sublethal effects, stable isotope values would not be affected appreciably in this type of consumer. However, in wild communities, the sensitivity of different species and life stages may vary, resulting in effects of higher magnitude. Furthermore, it is also possible that effects on δ15N can be propagated higher up in the food chain because of the higher capacity for metabolic transformations in organisms at higher TP; this, however, remains to be tested. When applying the TMF approach in a multicomponent food chain, even minor changes in TP for each organism group can propagate and contribute to an underestimated TMF value for the entire food chain.12 The magnitude of this effect will, however, vary depending on the sensitivity of species comprising the food chain and other pressures affecting growth and metabolism of animal populations in the system.

■

REFERENCES

(1) Post, D. M. Using stable isotopes to estimate trophic position: Models, methods, and assumptions. Ecology 2002, 83 (3), 703−718. (2) Jardine, T. D.; Kidd, K. A.; Fisk, A. T. Applications, considerations, and sources of uncertainty when using stable isotope analysis in ecotoxicology. Environ. Sci. Technol. 2006, 40 (24), 7501− 7511. (3) Borgå, K.; Kidd, K. A.; Muir, D. C. G.; Berglund, O.; Conder, J. M.; Gobas, F. A. P. C.; Kucklick, J.; Malm, O.; Powell, D. E. Trophic magnification factors: Considerations of ecology, ecosystems, and study design. Integr. Environ. Assess. Manage. 2012, 8 (1), 64−84. (4) Schmidt, K.; Atkinson, A.; Petzke, K.-J.; Voss, M.; Pond, D. W. Protozoans as a food source for Antarctic krill, Euphausia superba: complementary insights from stomach content, fatty acids, and stable isotopes. Limnol. Oceanogr. 2006, 51 (5), 2409−2427. (5) Minagawa, M. W.; Wada, E. Stepwise enrichment of 15N along food chains: Further evidence and the relation between δ15N and animal age. Geochim. Cosmochim. Acta 1984, 48, 1135−1140. (6) Vander Zanden, M. J.; Rasmussen, J. B. Variation in δ15N and δ13C trophic fractionation: Implications for aquatic food web studies. Limnol. Oceanogr. 2001, 46 (8), 2061−2066. (7) Hussey, N. E.; MacNeil, M. A.; McMeans, B. C.; Olin, J. A.; Dudley, S. F.; Cliff, G.; Wintner, S. P.; Fennessy, S. T.; Fisk, A. T. Rescaling the trophic structure of marine food webs. Ecol. Lett. 2014, 17 (2), 239−250. (8) Caut, S.; Angulo, E.; Courchamp, F. Variation in discrimination factors (δ15N and δ13C): the effect of diet isotopic values and applications for diet reconstruction. J. Appl. Ecol. 2009, 46 (2), 443− 453. (9) Ek, C.; Karlson, A. M. L.; Hansson, S.; Garbaras, A.; Gorokhova, E. Stable isotope composition in Daphnia is modulated by growth, temperature, and toxic exposure: implications for trophic magnification factor assessment. Environ. Sci. Technol. 2015, 49 (11), 6934− 6942. (10) Fisk, A. T.; Hobson, K. A.; Norstrom, R. J. Influence of chemical and biological factors on trophic transfer of persistent organic pollutants in the Northwater Polynya marine food web. Environ. Sci. Technol. 2001, 35 (4), 732−738. (11) Ruus, A.; Ugland, K. I.; Skaare, J. U. Influence of trophic position on organochlorine concentrations and compositional patterns in a marine food web. Environ. Toxicol. Chem. 2002, 21 (11), 2356− 2364. (12) Starrfelt, J.; Borgå, K.; Ruus, A.; Fjeld, E. Estimating trophic levels and trophic magnification factors using bayesian inference. Environ. Sci. Technol. 2013, 47 (20), 11599−11606. (13) Calow, P. Physiological costs of combating chemical toxicants: ecological implications. Comp. Biochem. Physiol., C: Comp. Pharmacol. 1991, 100 (1), 3−6. (14) Robbins, C. T.; Felicetti, L. A.; Sponheimer, M. The effect of dietary protein quality on nitrogen isotope discrimination in mammals and birds. Oecologia 2005, 144 (4), 534−540. (15) Martínez del Rio, C.; Wolf, B. O. Mass-balance models for animal isotopic ecology, In Physiological and Ecological Adaptations to Feeding in Vertebrates; Starck, M. J., Wang, T., Eds.; Science Publishers: Enfield, NH, 2005, 141−174. (16) Chikaraishi, Y.; Kashiyama, Y.; Ogawa, N. O.; Kitazato, H.; Ohkouchi, N. Metabolic control of nitrogen isotope composition of amino acids in macroalgae and gastropods: implications for aquatic food web studies. Mar. Ecol.: Prog. Ser. 2007, 342, 85−90. (17) Hawkins, A. J. S. Protein turnover: a functional appraisal. Funct. Ecol. 1991, 5 (2), 222−233. (18) Barber, I.; Baird, D.; Calow, P. Clonal variation in general responses of Daphnia magna Straus to toxic stress. II. Physiological effects. Funct. Ecol. 1990, 4 (3), 409−414. (19) Deniro, M. J.; Epstein, S. Influence of diet on distribution of carbon isotopes in animals. Geochim. Cosmochim. Acta 1978, 42 (5), 495−506. (20) Riisgard, H. U. No foundation of a ″3/4 power scaling law″ for respiration in biology. Ecol. Lett. 1998, 1 (2), 71−73.

ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.est.6b01731. (1) Summary for the contribution of individual PCB congeners to the spiked Spirulina powder (Table S1); (2) congener-specific internal concentrations in daphnids after the accumulation phase and depuration phase (Table S2); (3) summary for the variables measured in daphnids after the accumulation and depuration phases (Table S3); (4) quality assurance for PCB analysis and an overview of the PCB samples analyzed (Table S4). Quality assurance for stable isotope ratio analysis and elemental composition with data for analytical accuracy and precision (Table S5) together with an overview of isotope samples analyzed (Table S6). Information on pilot experiments for establishing the PCB exposure concentration (Table S7) and information on the establishing of a culture-specific length-weight regression (Table S8, Figure S1) (PDF)

■

Article

AUTHOR INFORMATION

Corresponding Author

*Phone: +46 8 674 7336; e-mail: [email protected] (C.E.). Notes

The authors declare no competing financial interest.

■

ACKNOWLEDGMENTS This study was supported by the Swedish Research Council for Environment, Agricultural Sciences and Spatial Planning (FORMAS) project number 216-2009-928, and the Isotope ecology network in the Baltic Sea region (Swedish Institute, Sweden). G


Article


(42) Winberg, G. G., Ed. Methods for the Estimation of Production of Aquatic Animals; Academic Press Inc.; London, U.K., 1971. (43) Main, T.; Dobberfuhl, D.; Elser, J. N: P stoichiometry and ontogeny of crustacean zooplankton: a test of the growth rate hypothesis. Limnol. Oceanogr. 1997, 42 (6), 1474−1478. (44) Dillon, T. M.; Benson, W. H.; Stackhouse, R. A.; Crider, A. M. Effects of selected PCB congeners on survival, growth, and reproduction in Daphnia magna. Environ. Toxicol. Chem. 1990, 9 (10), 1317−1326. (45) Nebeker, A. V.; Puglisi, F. A. Effect of polychlorinated biphenyls (PCB’s) on survival and reproduction of Daphnia, Gammarus, and Tanytarsus. Trans. Am. Fish. Soc. 1974, 103 (4), 722−728. (46) Frame, G. M.; Cochran, J. W.; Bøwadt, S. S. Complete PCB congener distributions for 17 Aroclor mixtures determined by 3 HRGC systems optimized for comprehensive, quantitative, congenerspecific analysis. J. High Resolut. Chromatogr. 1996, 19 (12), 657−668. (47) Boon, J. P.; Eijgenraam, F.; Everaarts, J. M.; Duinker, J. C. A structure-activity relationship (SAR) approach towards metabolism of PCBs in marine animals from different trophic levels. Mar. Environ. Res. 1989, 27 (3), 159−176. (48) Bunn, S. E.; Leigh, C.; Jardine, T. D. Diet-tissue fractionation of δ15N by consumers from streams and rivers. Limnol. Oceanogr. 2013, 58 (3), 765−773. (49) Hutchinson, T. H.; Solbe, J.; Kloepper-Sams, P. J. Analysis of the ecetoc aquatic toxicity (EAT) database IIIcomparative toxicity of chemical substances to different life stages of aquatic organisms. Chemosphere 1998, 36 (1), 129−142. (50) Woltering, D. M. The growth response in fish chronic and early life stage toxicity tests: a critical review. Aquat. Toxicol. 1984, 5 (1), 1− 21. (51) Nakari, T.; Huhtala, S. Comparison of toxicity of congener-153 of PCB, PBB, and PBDE to Daphnia magna. Ecotoxicol. Environ. Saf. 2008, 71 (2), 514−518. (52) Borgå, K.; Fisk, A. T.; Hoekstra, P. F.; Muir, D. C. Biological and chemical factors of importance in the bioaccumulation and trophic transfer of persistent organochlorine contaminants in arctic marine food webs. Environ. Toxicol. Chem. 2004, 23 (10), 2367−2385. (53) Forsman, A.; Wennersten, L. Inter-individual variation promotes ecological success of populations and species: evidence from experimental and comparative studies. Ecography 2016, 39 (7), 630−648. (54) Orlando, F. E.; Guillette, J. L. A re-examination of variation associated with environmentally stressed organisms. Apmis 2001, 109 (S103), S178−S186. (55) Forbes, V. E.; Moller, V.; Depledge, M. Intrapopulation variability in sublethal response to heavy metal stress in sexual and asexual gastropod populations. Funct. Ecol. 1995, 9 (3), 477−484. (56) Haile, C. L. Chlorinated Hydrocarbons in the Lake Ontario Ecosystem (IFYGL); Ecological Research Series; National Environmental Research Center: Oregon, U.S., 1975. (57) Bhavsar, S. P.; Jackson, D. A.; Hayton, A.; Reiner, E. J.; Chen, T.; Bodnar, J. Are PCB Levels in Fish from the Canadian Great Lakes Still Declining? J. Great Lakes Res. 2007, 33 (3), 592−605. (58) Bignert, A.; Olsson, M.; Persson, W.; Jensen, S.; Zakrisson, S.; Litzén, K.; Eriksson, U.; Häggberg, L.; Alsberg, T. Temporal trends of organochlorines in Northern Europe, 1967−1995. Relation to global fractionation, leakage from sediments and international measures. Environ. Pollut. 1998, 99 (2), 177−198. (59) Afful, S.; Awudza, J. A.; Osae, S.; Twumasi, S. K. Persistent organochlorine compounds in the water and sediment samples 2 from the Lake Bosomtwe in Ghana 3. Am. Chem. Sci. J. 2013, 3 (4), 434− 448. (60) De March, B.; De Wit, C.; Muir, D.; Braune, B.; Gregor, D.; Norstrom, R.; Olsson, M.; Skaare, J.; Stange, K. Persistent organic pollutants. In AMAP Assessment Report: Arctic Pollution Issues; Arctic Monitoring and Assessment Programme (AMAP): Oslo, Norway, 1998, 190. (61) Evenset, A.; Christensen, G. N.; Skotvold, T.; Fjeld, E.; Schlabach, M.; Wartena, E.; Gregor, D. A comparison of organic

(21) Deniro, M. J.; Epstein, S. Mechanism of carbon isotope fractionation associated with lipid synthesis. Science 1977, 197 (4300), 261−263. (22) Shaw-Allen, P. L.; Romanek, C. S.; Bryan, A. L.; Brant, H.; Jagoe, C. H. Shifts in relative tissue δ15N values in snowy egret nestlings with dietary mercury exposure: a marker for increased protein degradation. Environ. Sci. Technol. 2005, 39 (11), 4226−4233. (23) Bayona, Y.; Roucaute, M.; Cailleaud, K.; Lagadic, L.; Basseres, A.; Caquet, T. Isotopic niche metrics as indicators of toxic stress in two freshwater snails. Sci. Total Environ. 2014, 484, 102−113. (24) Banas, D.; Vollaire, Y.; Danger, M.; Thomas, M.; OliveiraRibeiro, C. A.; Roche, H.; Ledore, Y. Can we use stable isotopes for ecotoxicological studies? Effect of DDT on isotopic fractionation in Perca f luviatilis. Chemosphere 2009, 76 (6), 734−739. (25) Reitsema, L. J. Beyond diet reconstruction: stable isotope applications to human physiology, health, and nutrition. Am. J. Hum. Biol. 2013, 25 (4), 445−456. (26) Paulet, Y. M.; Lorrain, A.; Richard, J.; Pouvreau, S. Experimental shift in diet δ13C: A potential tool for ecophysiological studies in marine bivalves. Org. Geochem. 2006, 37 (10), 1359−1370. (27) Macko, S. A.; Estep, M. L. F.; Engel, M. H.; Hare, P. E. Kinetic fractionation of stable nitrogen isotopes during amino acid transamination. Geochim. Cosmochim. Acta 1986, 50 (10), 2143−2146. (28) Maki, A.; Johnson, H. Effects of PCB (aroclor 1254) and p,p’DDT on production and survival of Daphnia Magna strauss. Bull. Environ. Contam. Toxicol. 1975, 13 (4), 412−416. (29) Schmidt, K.; Steinberg, C. E.; Staaks, G. B. Influence of a xenobiotic mixture (PCB and TBT) compared to single substances on swimming behavior or reproduction of Daphnia magna. Acta Hydrochim. Hydrobiol. 2005, 33 (4), 287−300. (30) Baker, J. E.; Eisenreich, S. J.; Johnson, T. C.; Halfman, B. M. Chlorinated hydrocarbon cycling in the benthic nepheloid layer of Lake Superior. Environ. Sci. Technol. 1985, 19 (9), 854−861. (31) OECD. OECD 202 Guideline for testing of chemicals. Daphnia sp., acute immobilisation test. 2004. (32) OECD. OECD 211 Guideline for testing of chemicals. Daphnia magna reproduction test. 2012. (33) Escher, B. I.; Hermens, J. L. Modes of action in ecotoxicology: their role in body burdens, species sensitivity, QSARs, and mixture effects. Environ. Sci. Technol. 2002, 36 (20), 4201−4217. (34) Furuhagen, S.; Liewenborg, B.; Breitholtz, M.; Gorokhova, E. Feeding activity and xenobiotics modulate oxidative status in Daphnia magna: implications for ecotoxicological testing. Environ. Sci. Technol. 2014, 48 (21), 12886−12892. (35) Free Statistics Software, Of fice for Research Development and Education Website, version 1.1.23-r27; http://www.wessa.net/. (36) Schielzeth, H. Simple means to improve the interpretability of regression coefficients. Methods in Ecology and Evolution 2010, 1 (2), 103−113. (37) Leblanc, G. A.; Cochrane, B. J. Modulation of substrate-specific glutathione S-transferase activity in Daphnia magna with concomitant effects on toxicity tolerance. Comp. Biochem. Physiol., C: Comp. Pharmacol. 1985, 82 (1), 37−42. (38) Ade, P.; Soldaini, M. B.; Castelli, M.; Chiesara, E.; Clementi, F.; Fanelli, R.; Funari, E.; Ignesti, G.; Marabini, A.; Orunesu, M. Biochemical and morphological comparison of microsomal preparations from rat, quail, trout, mussel, and water flea. Ecotoxicol. Environ. Saf. 1984, 8 (5), 423−446. (39) McManus, G. B.; Wyman, K. D.; Peterson, W. T.; Wurster, C. F. Factors affecting the elimination of PCBs in the marine copepod Acartia tonsa. Estuarine, Coastal Shelf Sci. 1983, 17 (4), 421−430. (40) De Coen, W. M.; Janssen, C. R. The missing biomarker link: relationships between effects on the cellular energy allocation biomarker of toxicant-stressed Daphnia magna and corresponding population characteristics. Environ. Toxicol. Chem. 2003, 22 (7), 1632− 1641. (41) Sancho, E.; Villarroel, M.; Andreu, E.; Ferrando, M. Disturbances in energy metabolism of Daphnia magna after exposure to tebuconazole. Chemosphere 2009, 74 (9), 1171−1178. H


Article

Environmental Science & Technology contaminants in two high Arctic lake ecosystems, Bjørnøya (Bear Island), Norway. Sci. Total Environ. 2004, 318 (1), 125−141.

I


Growth Retardation and Altered Isotope ... - ACS Publications

Recommend Documents