Mercury Biomagnification in Marine Zooplankton Food Webs in

Article pubs.acs.org/est

Mercury Biomagnification in Marine Zooplankton Food Webs in Hudson Bay Karen L. Foster,*,†,‡ Gary A. Stern,†,§ Monica A. Pazerniuk,† Brendan Hickie,‡ Wojciech Walkusz,§ Feiyue Wang,† and Robie W. Macdonald†,∥ †

Centre for Earth Observation Sciences (CEOS), Department of Environment and Geography, University of Manitoba, Winnipeg, Canada R3T 2N2 ‡ Trent University, Peterborough, Canada K9J 7B8 § Freshwater Institute, Department of Fisheries and Oceans, Winnipeg, Canada R3T 2N6 ∥ Institute of Ocean Sciences, Department of Fisheries and Oceans, Sidney, Canada V8L 4B2 S Supporting Information *

ABSTRACT: While much research has been carried out on mercury in large marine mammals and associated food webs in northern regions, comparatively less has been conducted on lower trophic levels including zooplankton and the subsequent transfer to predators, which marks the entry of mercury into northern marine food webs. We present here the first database for mercury uptake and transfer exclusively within zooplankton food webs in northern marine waters. We have investigated both total (THg) and monomethylmercury (MMHg) concentrations, and isotopic signatures (δ15N and δ13C) in individual zooplankton taxa collected over a period of eight years (2003−2010) from across Hudson Bay (including Hudson Strait and Foxe Basin) as part of research icebreaker cruises. δ15N values ranged from 3.4 to 14.0‰, implying trophic levels ranging from 1 to 4, and THg concentrations ranged from 5 to 242 ng g−1 dw. Food web linkages were identified within the data set, and mercury biomagnification was evident both with THg and MMHg concentrations increasing from prey to predator, and with trophic magnification factors (TMFs). Total mercury and MMHg transfer in a unique prey− predator linkage (Limacina helicina−Clione limacina) are investigated and discussed with regard to known physiological and biochemical characteristics. The results suggest that exposure to mercury at higher trophic levels including humans can be affected by processes at the bottom of Arctic marine food webs.

■

exposure.8−10 However, zooplankton themselves form a complex subset of animals that cannot be subsumed under a single trophic category and, therefore, need to be understood as a subsystem if we are to make further progress in understanding variability at the top of the food chain. For example, concentrations of total mercury (THg) monitored in the copepod Calanus hyperboreus along the SHEBA drift path in the Beaufort and Chukchi seas were found to be closely linked with δ13C, presumably a result of terrigenous sources of THg such as riverine input, and were mirrored in arctic cod (Boreogadus saida) predators at the next trophic level.2 Persistent organic pollutants (POPs) in zooplankton food webs collected from fjords in Svalbard have been shown to both bioaccumulate and biomagnify, with resulting POP signatures evidently reflecting abiotic factors of the particular system such as ice cover.11,12 When zooplankton species are grouped in large-scale food web analyses the resolution of mercury uptake and transfer

INTRODUCTION The accumulation of mercury by lower trophic level organisms, such as zooplankton, provides the entry point from which subsequent transfers to predators can lead to significant exposure in top predators in northern marine food webs. It is the efficiency of this water-to-food web transfer of mercury and the subsequent biomagnification within lower trophic levels that governs the regional exposure of commonly monitored organisms.1,2 Yet, while much research has been done on mercury in large marine mammals and seabirds,1,3 comparatively little is known about mercury uptake by zooplankton and transfer to predators. Thus, the possible impacts of climate change on mercury cycling in lower trophic levels within northern oceans remain virtually unknown. Climate change has been shown to impact mercury transport, speciation, and cycling within Arctic ecosystems, as well as primary productivity and food web energetics.4−7 Mercury concentrations reported for marine zooplankton are frequently a small component of northern food web investigations which are aimed to assess the efficiency of prey−predator transfer up the food web to large marine mammals of relevance to human consumption and mercury © 2012 American Chemical Society

Received: Revised: Accepted: Published: 12952

August 24, 2012 November 3, 2012 November 7, 2012 November 16, 2012 dx.doi.org/10.1021/es303434p | Environ. Sci. Technol. 2012, 46, 12952−12959

Environmental Science & Technology

Article

Figure 1. Locations of zooplankton collections across Hudson Bay. Hydrological map source: http://geogratis.cgdi.gc.ca/, bathymetrical data (SRTM30 PLUS) source: http://topex.ucsd.edu/.

processes occurring at the lower trophic levels is lost. Trophic magnification factors (TMFs), computed for a food web from the slope of the regression of contaminant concentration on trophic level for each food web member, are presented as evidence of biomagnification.13 Trophic levels (TL), which are computed from nitrogen isotopic signatures (δ15N), for northern marine food webs can range from that of primary producers (TL = 1) up to predators such as seals and seabirds (TL = 5).8−10,13 Thus, in large-scale marine food web investigations zooplankton tend to be grouped together at the low end of concentration versus TL regression lines, while the top consumers predominantly determine the regression.8−10,13 It has been suggested that TMFs are best computed separately for poikilotherms (including zooplankton) and homeotherms since they can yield different biomagnification rates owing to differing energy requirements and abilities to biotransform contaminants.14 Here we present monomethylmercury (MMHg) and THg, as well as carbon and nitrogen stable isotope (δ13C and δ15N), data for zooplankton collected across Hudson Bay (including Hudson Strait and Foxe Basin, Figure 1). Hudson Bay is an estuarine shelf sea that receives 714 km3 y−1 of river runoff.15 The river input to the bay creates gradients in water salinity and terrigenous carbon (inferred from δ13C), with salinity dilution and depleted δ13C occurring at coastal regions.16 Depleted δ13C values in zooplankton have also been associated with terrigenous organic carbon (via rivers and/or coastal erosion) in the Bering, Chukchi, and Beaufort seas, whereas enriched values are associated with marine carbon.17

We tested the hypothesis that the biomagnification of mercury occurs within pelagic zooplankton food webs by assessing the change in mercury (THg, MMHg) concentrations across trophic gradients inferred from δ15N, and from computed Trophic Magnification Factors (TMFs).13 Typically, zooplankton taxa are grouped together and biomagnification is assessed across the range of δ15N or trophic levels represented, thereby assuming that all taxa are members of the same food web, although there are exceptions.11,12 Our approach here was to first establish trophic linkages and food webs using feeding ecology confirmed with stable isotopes, then to assess biomagnification within each of these food webs individually. This approach yields more meaningful assessments as it enables adherence to an underlying assumption of biomagnification analyses; that the taxa included in the assessment be from the same food web.18 To our knowledge, this is the first study to assess mercury transfer specifically within northern marine zooplankton food webs. Such datasets are vital to fill notable data gaps in the literature on mercury in zooplankton in the North and contribute to the understanding of baseline factors that control mercury uptake and fate in lower trophic level northern marine food webs. Zooplankton, in turn, are an important, lipid-rich energy source for upper trophic level organisms such as seabirds, whales, and fish. Arctic cod, for example, feed on zooplankton (copepods, amphipods, euphausiids, and arrow worms depending on life stage), then are themselves a dominant prey of seals, which in turn are preyed upon by polar bears.19 Arctic cod, seals, and polar bears are country 12953

dx.doi.org/10.1021/es303434p | Environ. Sci. Technol. 2012, 46, 12952−12959


Article

Table 1. Stable Isotopes of Nitrogen (δ15N) and Carbon (δ13C), Trophic Levels (TL), Total Mercury (THg), and Percent Monomethylmercury (%MMHg) in Zooplankton Taxa from Hudson Baya n Calanus sp. Limacina helicina Euphausiacea Clione limacina Themisto sp. Paraeuchaeta sp. Hyperoche sp. Sagitta sp. a

36 16 29 24 64 13 10 41

δ15N (‰) 7.18 7.36 8.02 8.59 8.71 10.51 10.91 11.37

± ± ± ± ± ± ± ±

0.31 0.54 0.24 0.43 0.24 0.25 0.61 0.19

2.00 2.08 2.26 2.41 2.44 2.91 3.02 3.14

± ± ± ± ± ± ± ±

THg (ng g‑1 dw)

δ13C (‰)

TL

−22.91 −23.74 −22.54 −24.75 −22.40 −23.00 −22.26 −23.17

0.09 0.14 0.06 0.11 0.06 0.07 0.16 0.05

± ± ± ± ± ± ± ±

0.26 0.54 0.35 0.28 0.22 0.38 0.65 0.29

13.09 83.61 23.82 73.48 26.08 43.59 46.99 17.69

± ± ± ± ± ± ± ±

1.13 12.38 3.98 7.84 1.61 8.56 10.76 1.80

% MMHg 24.2 11.3 34.0 44.2 64.0 104.4

± ± ± ± ± ±

6.23 (n = 7) 3.5 (n = 6) 8.4 (n = 18) 7.2 (n = 5) 5.5 (n = 26) 8.9 (n = 3)

61.6 ± 5.6 (n = 32)

Values shown are means across four sampling years (2003−2005, 2010) ± SE, and are ordered by TL.

Recoveries of MMHg from NRC DORM-2 dogfish muscle reference material were 94 ± 4%. The method detection limit of MMHg, computed as above for THg, was 4 ng g−1 dw. Stable isotopes (δ15N and δ13C) were analyzed at the University of Winnipeg Isotope Laboratory using continuous flow ion ratio mass spectrometry. Precisions of the analyses were ±0.16‰ and ±0.18‰ for δ13C and δ15N, respectively. The percentage of THg present as MMHg is reported as % MMHg. Inorganic Hg concentrations are approximated as the concentration of THg minus that of MMHg. Data Analysis. Trophic levels were calculated for each zooplankton sample (Predator) as in Hobson et al.:24

foods that are part of traditional diets in the North, thus, mercury trends in zooplankton are also of great relevance to human exposure. Data like these, assembled for low trophic levels, are a necessary basis for the development, validation, and interpretation of predictive models of these processes, which can be utilized to predict the effects of climate change on mercury uptake and transfer within Arctic food webs.

■

MATERIALS AND METHODS Sample Collection. Zooplankton were collected in 2003, 2004, 2005, and 2010 on expedition cruises along the MERICA (CCGS Pierre Radisson and Des Groseillers, August 2003, 2004), and ArcticNet (CCGS Amundsen, September−October 2005, July 2010) cruise transects. Collections were done using net tows (mesh size 200−1600 μm, opening 1 or 9 m2), zooplankton were sorted to the lowest taxonomical level possible in the field with the naked eye and then frozen. Taxa identified included the herbivore Calanus sp. (copepod), omnivores Euphausiacea (krill), Limacina helicina (pteropod mollusc or sea butterfly), and Themisto sp. (amphipod), as well as predators Clione limacina (sea butterfly), Hyperoche sp. (amphipod), Paraeuchaeta sp. (copepod), and Sagitta sp. (chaetognaths or arrow worm). Some species of Themisto have a diet preference ranging from herbivorous to predatorial depending on lifecycle stage,20 thus, for the purpose of the present analyses Themisto is categorized as an omnivore. Mercury and Isotopic Analysis. Composite samples of taxa from each sampling location (grouped across life stages and sex to ensure sufficient biomass) were freeze-dried and analyzed for THg and MMHg using standardized methodologies.21−23 Briefly, for THg analyses samples were acid digested in HNO3/H2SO4 solution at 180 °C for 16 h, THg was then analyzed for all samples using cold vapor atomic absorption spectrometry (Mercury Monitor 3200, Thermo Separation Products, USA). Replicate samples, certified reference materials, and blanks were processed simultaneously with the samples. Recoveries of THg from the National Research Council Canada (NRC) TORT-1 lobster, and National Institute of Science and Technology 2976 mussel reference materials were 104 ± 4% and 102 ± 4% of the certified values, respectively. The THg method detection limit, computed as three standard deviations of the blank values, was 5 ng g−1 dw based on a typical zooplankton sample mass. For MMHg, samples were extracted into KOH, then dichloromethane (DCM) in an acidified solution of KBr/ Cu2SO4. Step-wise extractions of aliquots of the DCM fraction were subsequently done, first with Na2S2O3 solution, then KBr/ Cu2SO4. MMHg was analyzed by gas chromatography atomic fluorescence spectroscopy at the University of Ottawa.

TL Predator = 2 + (δ15 NPredator − δ15 NCalanus sp .)/3.8

(1)

where δ15NCalanus sp. is the mean δ15N value for Calanus sp. across all of Hudson Bay. Calanus sp. are the most abundant planktivores in northern marine waters, dominating the biomass found in shelf regions such as Hudson Bay.25,26 Trophic levels were computed for individual Calanus sp. also using eq 1. Trophic Magnification Factors (TMFs) were computed as the antilogarithm of the slope of the regression of the logarithm of concentration on TL.13 A TMF value greater than 1 indicates that biomagnification is occurring within the food web. The heavier isotope 15N has been shown to become progressively enriched, relative to the lighter isotope 14N, with each trophic transfer in food webs.27 All statistical analyses were done with Systat 12 and SigmaPlot 11.0. Analysis of variance (ANOVA) followed by the Tukey honestly significant difference test (Tukey HSD) were used to determine if the mean values of THg, MMHg, δ15N, and δ13C differed among zooplankton taxa, and which means were significantly different (α = 0.05), respectively.

■

RESULTS AND DISCUSSION The values of δ15N, δ13C, THg, and %MMHg, measured in this study for zooplankton taxa collected from across Hudson Bay, as well as computed trophic levels (TLs), are summarized in Table 1. As these parameters exhibited no significant differences between subregions for most zooplankton taxa across Hudson Bay, all of the samples were pooled. The range in THg concentrations in all zooplankton samples was 5 to 242 ng g−1 dw, spanning a 48-fold difference for a range in δ15N of 3.4 to 14.0‰ and implying a range in TL from 1 to 4. δ15N values in zooplankton (amphipods, chaetognaths, copepods, pteropods) from the eastern Canadian Arctic were similar ranging from 5 to 14‰.28 The ranges in TL and THg across zooplankton taxa indicate that zooplankton are far from 12954



Article

sp., suggesting increased terrigenous organic carbon (from river/coastal runoff) influence.17 Hg Biomagnification in Food Webs. Biomagnification of THg was evident for all of the food webs with positive slopes of the regression of concentration on δ15 N (Figure 3).

uniform in the trophic level at which they feed, and in their bioaccumulation of mercury. Using Isotopic Signatures and Feeding Ecology To Determine Trophic Linkages. Four short, yet distinct, zooplankton food webs were identified in this data set using published feeding ecology studies,29−37 which were generally based on evidence from gut content and/or fatty acid signature analyses. These food webs were confirmed with isotopic data presented here (Figure 2).

Figure 2. Isotopic carbon and nitrogen signatures of Hudson Bay zooplankton taxa: Calanus sp. (C), Limacina helicina (LH), Euphausiacea (E), Clione limacina (CL), Themisto sp. (T), Paraeuchaeta sp. (P), Hyperoche sp. (H), and Sagitta sp. (S). Symbols indicate herbivores (○), omnivores (gray squares), and predators (◆). Four food web linkages are indicated by numbered regression lines. Values shown are multiyear means ± SE.

The food webs are as follows: (1) Calanus sp.−L. helicina−C. limacina, (2) Calanus sp.−Sagitta sp, (3) Calanus sp.−Paraeuchaeta sp., and (4) Calanus sp.−Euphausiacea−Themisto sp. Each of these four food webs include the prevalent, herbivorous Calanus sp. Hyperoche sp. is not a known member of these food webs but rather a parasite of hosts that include gelatinous zooplankton.32 These food webs represent reported prey− predator linkages, however, zooplankton are generally opportunistic feeders and complete food webs can be more complex. Representative samples of each taxa were not available at all sampling sites for all sampling years. Carbon and N isotopic signatures of the zooplankton taxa are shown in Figure 2. Taxa were found to group by diet, such that with increasing predatory tendency δ15N increased, i.e., values of the herbivores < omnivores < predators (Tukey HSD, all p < 0.01) with three exceptions. Limacina helicina and C. limacina are notable exceptions discussed below as a unique prey− predator food web, also omnivorous Euphausiacea were not significantly different from herbivorous Calanus sp. (Tukey HSD, p = 0.29). With the exception of C. limacina and L. helicina, the taxa occupy a small δ13C range of approximately −22 to −23‰, suggestive of marine organic carbon signals.17 δ13C values were not significantly different between the taxa (Tukey HSD, all p = 0.11 to 1.00), with the exception of C. limacina. Clione limacina had significantly lower δ13C than most of the taxa (Tukey HSD, all p < 0.01), with the exception of L. helicina and Paraeuchaeta

Figure 3. Concentrations of (A) total (THg) and (B) monomethyl (MMHg) mercury versus δ15N for zooplankton taxa collected from Hudson Bay. See Figure 2 for taxa codes and food web linkages. Symbols indicate herbivores (○), omnivores (gray square), and predators (◆). Values shown are multiyear means ± SE.

Monomethylmercury was found to biomagnify in three of the four food webs, the only exception being food web 1; a unique food web discussed below. The magnitudes of the slopes of the regressions in Figure 3 were not identical indicating that the efficiency of biomagnification among the four food webs was not equal. For example, the slope of the regression of THg on δ15N for food web 1 is 22 times that of food web 2. Possible factors that could influence these slopes and apparent biomagnification efficiencies include nondiet-derived environmental exposures, species differences in uptake/transfer/ metabolism efficiencies of mercury, length of food web (note that not all taxa in the zooplankton food web are necessarily represented here), unique individual characteristics (e.g., L. helicina and C. limacine discussed below), to name a few. Hg Speciation. Over the range of δ15N represented by the entire data set, concentrations of THg were found to decrease (linear regression, β = −2.3, p = 0.019), while simultaneously approximated concentrations of inorganic Hg decreased (linear regression, β = −3.9, p < 0.001), and concentrations of MMHg (not shown) were not significantly different (Figure 4). Not surprisingly %MMHg, computed from both MMHg and THg 12955



Article

species in the Barents Sea and Fram Strait.41,42 Clione limacina had δ15N values that were significantly less than those of the other three predators (Tukey HSD, all p < 0.02), and not significantly different from those of the omnivores (Figure 2, Tukey HSD, p = 0.34−1.0). Clione limacina are unusual in that up to 40% of their total lipids are comprised of diacylglycerol ethers (DAGE).32,33 Diacylglycerol ethers are believed to be biosynthesized by C. limacina and to provide an energy reserve when food is scarce;33 of particular relevance given their apparent diet specificity. Increases in δ15N from prey to predator are largely dependent on the amino acids present (e.g., some such as glutamic acid demonstrate higher increases than others).43 Thus, the production of large quantities of DAGE by C. limacina may contribute to δ15N values that are not as high as those of other predatory taxa with more typical fatty acid signatures. Limacina helicina are also unique in that they capture prey using mucus webs, thus, enabling the capture of prey items larger than themselves, including other L. helicina, in addition to phytoplankton, protozoans, and Calanus sp.31,44 The diet of L. helicina, which includes cannibalism, would be expected to increase δ15N, possibly to levels greater than those of the other omnivores. However, no significant difference in δ15N between L. helicina and either the herbivore Calanus sp. or omnivore Euphausiacea was found (Figure 2). Concentrations of THg were not significantly different between prey L. helicina and predator C. limacina (Tukey HSD, p = 0.88) (Figure 3). Elevated concentrations in L. helicina are possibly owing to its cannibalistic nature, and unique mechanism for obtaining prey larger than itself, as discussed above. Together these two species have higher THg concentrations than all other taxa (Tukey HSD, all p < 0.05), which, in part, is likely a result of the transfer of the elevated body burden of THg from L. helicina to C. limacina. However, given the increased terrigenous organic carbon influence on both of these species indicated by δ13C (Figure 2), land-derived mercury input to Hudson Bay, via rivers and/or coastal runoff, could also be a contributing factor. Indeed, concentrations of the more readily biomagnified MMHg support this theory with C. limacina having an average concentration of 23.99 ± 2.74 ng g−1 dw; 3-fold higher than that of L. helicina (8.12 ± 1.91 ng g−1 dw) despite comparable THg concentrations. Trophic Magnification Factors. Trophic magnification factors computed for each of the four food webs were 1.1−1.9 for THg indicating that biomagnification of THg is indeed occurring in all of the four zooplankton food webs (Table 2). Trophic magnification factors computed for MMHg were 0.8− 9.3, indicating that MMHg biomagnification is occurring in three of the four food webs. Food web 1 was the one exception,

Figure 4. Mercury speciation across the range of δ15N values measured in zooplankton from Hudson Bay. Multiyear data for all taxa and all samples are shown for (A) total mercury (THg), (B) percentage monomethylmercury (%MMHg), and (C) inorganic mercury approximated as the concentration of THg − MMHg. Regressions with a significant slope are indicated with “*”.

concentrations, increased with δ15N (linear regression, β = 5.5, p < 0.001). Taken together, these results suggest that as trophic levels of marine zooplankton increase, THg concentrations decrease largely as a result of the decreasing uptake and/or retention of inorganic Hg, while %MMHg increases because MMHg concentrations remain constant despite decreasing THg concentrations. Thus, MMHg appears to be efficiently retained with progression up the food web, while inorganic Hg seems to be more readily cleared. A possible confounding factor could be that the size of zooplankton may also increase with δ15N; zooplankton fractionated by size to assess the trophic transfer of POPs had increasing δ15N values with size.38 Thus, growth dilution with increasing trophic level could be occurring and thus contributing to decreasing trends in THg concentrations. Over the small range of δ13C represented by the zooplankton in this data set, THg concentrations were found to decrease (linear regression, β = −6.2, p < 0.001), as were approximated inorganic Hg concentrations (linear regression, β = −5.7, p < 0.001). Concentrations of MMHg were not found to change significantly with δ13C (linear regression, p = 0.52), however, % MMHg increased with δ13C (linear regression, β = 6.5, p < 0.001). These results indicate that higher THg and inorganic Hg concentrations in zooplankton are associated with increased terrigenous organic carbon influence, which has been associated with increased anthropogenic fluxes of mercury into Hudson Bay.2,39 A Unique Prey−Predator Food Web. Clione limacina are thought to feed exclusively on the omnivore L. helicina,40 yet were found to have δ15N values not significantly different from those of L. helicina (Tukey HSD, p = 0.34) (Figure 2). This similarity in δ15N has previously been observed between these

Table 2. Trophic Magnification Factors (TMFs) Computed for Total (THg) and Monomethyl (MMHg) Mercury for Each of Four Hudson Bay Zooplankton Food Webs, and for All Taxa Pooled Together (See Figure 2 for Taxa Codes) TMFs

12956

food web

taxa

THg

MMHg

1 2 3 4 pooled

C−LH−CL C−S C−P C−E−T all

1.4 1.2 1.9 1.1 0.9

0.8 2.4 9.3 1.7 1.1



Article

following recommendations for the direction of future studies of mercury in northern food webs: (1) the inclusion of multiple trophic linkages within lower trophic level organisms such as zooplankton (including herbivores, omnivores, and predators); (2) taxonomic identification of zooplankton targeted for analysis and an understanding of the feeding ecology of each taxa analyzed, including the identification of unique cases (e.g., L. helicina and C. limacina) where trophic transfer assumptions might be violated; (3) additional investigations of the most suitable protocol for assessing trophic levels and biomagnification in zooplankton food webs; and (4) the use of known trophic linkages between zooplankton (e.g., food webs 1−4) to enable unconfounded studies of the efficiency of mercury transfer between taxa and also to adhere to TMF computation assumptions. An understanding of both the trophic, regional, and climatic factors controlling mercury levels in zooplankton taxa, and the use of predictive models of mercury fate in lower trophic level food webs, would improve the interpretation of concentration trends observed in larger marine organisms, such as seals, polar bears, and ultimately humans.

with a negative slope of the regression of log MMHg on TL; possible factors contributing to this are discussed above. Trophic magnification factors for MMHg were generally higher than those of THg supporting that MMHg is a readily biomagnifying form of mercury in zooplankton. Trophic magnification factors computed using the entire data set for all zooplankton samples/taxa are less meaningful as data represent different food webs thereby failing a criterion assumption of TMF computations,18 but were computed for comparison. Plots of the logarithm of both MMHg and THg concentrations versus TL had slightly positive and negative slopes, respectively (β = 0.06 and −0.04), with neither slope significantly different from zero. Thus, the TMF for MMHg was 1.1, and for THg was 0.9, suggesting that neither THg, nor MMHg are strong biomagnifiers in zooplankton food webs when pooling all data together. Therefore, conclusions as to whether or not THg and MMHg biomagnify (if TMFs > 1) in zooplankton food webs differ depending on whether TMFs are computed based on known food web linkages, or on data for all taxa combined. This emphasizes the critical importance of using feeding ecology in addition to stable isotopes to establish trophic linkages in assessments of mercury TMFs and biomagnification. Similarly, it was noted in a study of POPs biomagnification in zooplankton food webs that biomagnification is most readily apparent when taxa are grouped by feeding strategy, i.e. herbivores, omnivores, and predators, and shifts in contaminant burdens are examined.12 Zooplankton food webs challenge some of the major underpinning assumptions of TMFs for the assessment of biomagnification as summarized by Borgå et al.18 Perhaps most notably the assumption that predators are at steady-state with respect to their diets, i.e. that tissue δ15N values and contaminant exposures are constant with time. Differences in the age of zooplankton individuals/taxa (e.g., life cycles can range from one year in the case of T. libellula to multiple years in the case of Euphausiacea),29,30 periods of fasting/starvation for some species (e.g., C. limacina),32 seasonal differences in diet, and highly opportunistic feeding, to name a few, are typical attributes of zooplankton food webs, particularly in northern and polar regions, which violate the steady-state assumption and undermine TMF computations. The most effective method for assessing contaminant biomagnification in zooplankton food webs requires additional study. However, it is clear that feeding ecology and dietary preferences are critical components that must be taken into consideration, along with stable isotopes, to assess trophic linkages and discern which organisms should be included in any given biomagnification assessment. Recommendations for Mercury Monitoring in Northern Food Webs. Given the changing climate in the cryosphere, it is of paramount importance to understand each trophic step in the mercury pathway from water to top predators. It is well understood that changes in foraging location or dietary sources affect contaminant exposure in top predators.10 It is equally clear that climate change and associated shifts in abiotic variables can lead to whole-scale change in the lowest components of the food web,7 and yet we have few data to evaluate how these changes in lower trophic levels affect the exposure of higher food web components to mercury and other contaminants. This study seeks to alleviate the notable gap in the literature of mercury data for zooplankton, but clearly additional research, particularly regarding the impact of climate change on mercury transfer within lower trophic levels, is required. To that end we offer the

■

ASSOCIATED CONTENT

S Supporting Information *

Tables of Tukey HSD p values for zooplankton taxa comparisons of δ15N, δ13C, THg, and MMHg. This material is available free of charge via the Internet at http://pubs.acs.org.

■

AUTHOR INFORMATION

Corresponding Author

* Phone: (705) 748-1011 ext. 6017; e-mail: kfoster411@gmail. com; mail: Environmental Resource Studies Program, Trent University, Peterborough, ON, Canada, K9J 7B8. Notes

The authors declare no competing financial interest.

■

ACKNOWLEDGMENTS We are grateful to ArcticNet, a Canadian Network of Centres of Excellence, Fisheries and Oceans Canada, and the Natural Sciences and Engineering Research Council of Canada (NSERC) for supporting this research. A special thanks to the officers and crew of the CCGS ships the Amundsen, Des Groseillers, and Pierre Radisson, and to the Fortier group (Laval University) for their help with sample collections.

■

REFERENCES

(1) Louis, V. L. S.; Derocher, A. E.; Stirling, I.; Graydon, J. A.; Lee, C.; Jocksch, E.; Richardson, E.; Ghorpade, S.; Kwan, A. K.; Kirk, J. L.; Lehnherr, I.; Swanson, H. K. Differences in mercury bioaccumulation between polar bears (Ursus maritimus) from the Canadian high- and sub-Arctic. Environ. Sci. Technol. 2011, 45, 5922−5928. (2) Stern, G.; Macdonald, R. Biogeographic provinces of total and methyl mercury in zooplankton and fish from the Beaufort and Chukchi seas: Results from the SHEBA drift. Environ. Sci. Technol. 2005, 39, 4707−4713. (3) Braune, B.; et al. Are contaminants in the Arctic increasing or decreasing, and why? In AMAP Assessment 2011: Mercury in the Arctic; Arctic Monitoring and Assessment Programme (AMAP), Oslo, Norway, 2011; pp 85−112. (4) Macdonald, R. W.; Wang, F.; Stern, G.; Outridge, P. The overlooked role of the ocean in mercury cycling in the Arctic. Mar. Pollut. Bull. 2008, 56, 1963−1965. 12957



Article

(5) Outridge, P. M.; Macdonald, R. W.; Wang, F.; Stern, G. A.; Dastoor, A. P. A mass balance inventory of mercury in the Arctic Ocean. Environ. Chem. 2008, 5, 89−111. (6) Stern, G. A.; Macdonald, R. W.; Outridge, P. M.; Wilson, S.; Chetelat, J.; Cole, A.; Hintelmann, H.; Loseto, L. L.; Steffen, A.; Wang, F.; Zdanowicz, C. How does climate change influence arctic mercury? Sci. Total Environ. 2012, 414, 22−42. (7) Leu, E.; Søreide, J. E.; Hessen, D. O.; Falk-Petersen, S.; Berge, J. Consequences of changing sea-ice cover for primary and secondary producers in the European Arctic shelf seas: Timing, quantity, and quality. Prog. Oceanogr. 2011, 90, 18−32.8. (8) Campbell, L.; Norstrom, R.; Hobson, K.; Muir, D.; Backus, S.; Fisk, A. Mercury and other trace elements in a pelagic Arctic marine food web (Northwater Polynya, Baffin Bay). Sci. Total Environ. 2005, 351, 247−263. (9) Jaeger, I.; Hop, H.; Gabrielsen, G. W. Biomagnification of mercury in selected species from an Arctic marine food web in Svalbard. Sci. Total Environ. 2009, 407, 4744−4751. (10) Loseto, L. L.; Stern, G. A.; Deibel, D.; Connelly, T. L.; Prokopowicz, A.; Lean, D. R. S.; Fortier, L.; Ferguson, S. H. Linking mercury exposure to habitat and feeding behaviour in Beaufort Sea beluga whales. J. Mar. Syst. 2008, 74, 1012−1024. (11) Hallanger, I. G.; Ruus, A.; Herzke, D.; Warner, N. A.; Evenset, A.; Heimstad, E. S.; Gabrielsen, G. W.; Borgå, K. Influence of season, location, and feeding strategy on bioaccumulation of halogenated organic contaminants in Arctic marine zooplankton. Environ. Toxicol. Chem. 2011, 30, 77−87. (12) Hallanger, I. G.; Ruus, A.; Warner, N. A.; Herzke, D.; Evenset, A.; Schoyen, M.; Gabrielsen, G. W.; Borgå, K. Differences between Arctic and Atlantic fjord systems on bioaccumulation of persistent organic pollutants in zooplankton from Svalbard. Sci. Total Environ. 2011, 409, 2783−2795. (13) 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, 732−738. (14) Hop, H.; Borgå, K.; Gabrielsen, G. W.; Kleivane, L.; Skaare, J. U. Food web magnification of persistent organic pollutants in poikilotherms and homeotherms from the Barents Sea. Environ. Sci. Technol. 2002, 36, 2589−2597. (15) Déry, S. J.; Stieglitz, M.; McKenna, E. C.; Wood, E. F. Characteristics and trends of river discharge into Hudson, James, and Ungava Bays, 1964−2000. J. Climate 2005, 18, 2540−2557. (16) Kuzyk, Z. Z. A.; Macdonald, R. W.; Tremblay, J.-É.; Stern, G. A. Elemental and stable isotopic constraints on river influence and patterns of nitrogen cycling and biological productivity in Hudson Bay. Cont. Shelf Res. 2010, 30, 163−176. (17) Schell, D. M.; Barnett, B. A.; Vinette, K. A. Carbon and nitrogen isotope ratios in zooplankton of the Bering, Chukchi and Beaufort seas. Mar. Ecol.: Prog. Ser. 1998, 162, 11−23. (18) 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. 2011, 8, 64−84. (19) Ecological characteristics of the Arctic. In AMAP Assessment Report: Arctic Pollution Issues; Arctic Monitoring and Assessment Programme (AMAP): Oslo, Norway, 2008. (20) Weslawski, J. M.; Kwasniewski, S.; Stempniewicz, L.; Blachowiak-Samolyk, K. Biodiversity and energy transfer to top trophic levels in two contrasting Arctic fjords. Polar Res. 2006, 27, 259−278. (21) Armstrong, J. A. J.; Uthe, J. F. Semi-automated determination of mercury in animal tissue. At. Absorpt. Newsl. 1971, 10, 101−103. (22) Cai, Y.; Tang, G.; Jaffe, R.; Jones, R. Evaluation of some isolation methods for organomercury determination in soil and fish samples by capillary gas chromatography - Atomic fluorescence spectrometry. Int. J. Environ. Anal. Chem. 1997, 68, 331−345.

(23) Uthe, J. F.; Solomon, J.; Grift, B. Rapid semimicro method for the determination of methyl mercury in fish tissue. J. Assoc. Off. Anal. Chem. 1972, 55, 583−9. (24) Hobson, K.; Fisk, A.; Karnovsky, N.; Holst, M.; Gagnon, J.; Fortier, M. A stable isotope (delta C-13, delta N-15) model for the North Water food web: Implications for evaluating trophodynamics and the flow of energy and contaminants. Deep-Sea Res., Part II 2002, 49, 5131−5150. (25) Darnis, G.; Barber, D. G.; Fortier, L. Sea ice and the onshoreoffshore gradient in pre-winter zooplankton assemblages in southeastern Beaufort Sea. J. Mar. Syst. 2008, 74, 994−1011. (26) Mumm, N.; Auel, H.; Hanssen, H.; Hagen, W.; Richter, C.; Hirche, H. J. Breaking the ice: large-scale distribution of mesozooplankton after a decade of Arctic and transpolar cruises. Polar Biol. 1998, 20, 189−197. (27) Cabana, G.; Rasmussen, J. Modeling food-chain structure and contaminant bioaccumulation using stable nitrogen isotopes. Nature 1994, 372, 255−257. (28) Pomerleau, C.; Winkler, G.; Sastri, A. R.; Nelson, R. J.; Vagle, S.; Lesage, V.; Ferguson, S. H. Spatial patterns in zooplankton communities across the eastern Canadian sub-Arctic and Arctic waters: Insight from stable carbon (δ13C) and nitrogen (δ15N) isotope ratios. J. Plankton Res. 2011, 33, 1779−1792. (29) Auel, H.; Werner, I. Feeding, respiration and life history of the hyperiid amphipod Themisto libellula in the Arctic marginal ice zone of the Greenland Sea. J. Exp. Mar. Biol. Ecol. 2003, 296, 183−197. (30) Brodeur, R. D.; Terazaki, M. Springtime abundance of chaetognaths in the shelf region of the northern Gulf of Alaska, with observations on the vertical distribution and feeding of Sagitta elegans. Fish. Oceanogr. 2009, 8, 93−103. (31) Falk-Petersen, S.; Hagen, W.; Kattner, G.; Clarke, A.; Sargent, J. Lipids, trophic relationships, and biodiversity in Arctic and Antarctic krill. Can. J. Fish. Aquat. Sci. 2000, 57, 178−191. (32) Gasca, R.; Haddock, S. H. D. Associations between gelatinous zooplankton and hyperiid amphipods (Crustacea: Peracarida) in the Gulf of California. Hydrobiologia 2004, 530, 529−535. (33) Gannefors, C.; Böer, M.; Kattner, G.; Graeve, M.; Eiane, K.; Gulliksen, B.; Hop, H.; Falk-Petersen, S. The Arctic sea butterfly Limacina helicina: Lipids and life strategy. Mar. Biol. 2005, 147, 169− 177. (34) Kattner, G.; Hagen, W.; Graeve, M.; Albers, C. Exceptional lipids and fatty acids in the pteropod Clione limacina (Gastropoda) from both polar oceans. Mar. Chem. 1998, 61, 219−228. (35) Laakmann, S.; Kochzius, M.; Auel, H. Ecological niches of Arctic deep-sea copepods: Vertical partitioning, dietary preferences and different trophic levels minimize inter-specific competition. Deep-Sea Res., Part I 2009, 56, 741−756. (36) Lee, R. F.; Hagen, W.; Kattner, G. Lipid storage in marine zooplankton. Mar. Ecol.: Prog. Ser. 2006, 307, 273−306. (37) Marion, A.; Harvey, M.; Chabot, D.; Brêthes, J.-C. Feeding ecology and predation impact of the recently established amphipod, Themisto libellula, in the St. Lawrence marine system, Canada. Mar. Ecol.: Prog. Ser. 2008, 373, 53−70. (38) Sobek, A.; Cornelissen, G.; Tiselius, P.; Gustafsson, O. Passive partitioning of polychlorinated biphenyls between seawater and zooplankton: A study comparing observed field distributions to equilibrium sorption experiments. Environ. Sci. Technol. 2006, 40, 6703−6708. (39) Hare, A.; Stern, G. A.; Kuzyk, Z. Z. A.; Macdonald, R.; Johannessen, S. C.; Wang, F. Natural and anthropogenic mercury distribution in marine sediments from Hudson Bay, Canada. Environ. Sci. Technol. 2010, 44, 5805−5811. (40) Conover, R. J.; Lalli, C. M. Feeding and growth in Clione limacina (Phipps), a pteropod mollusc. J. Exp. Mar. Biol. Ecol. 1972, 9, 279−302. (41) Søreide, J. E.; Hop, H.; Carroll, M. L.; Falk-Petersen, S.; Hegseth, E. N. Seasonal food web structures and sympagic-pelagic coupling in the European Arctic revealed by stable isotopes and a twosource food web model. Prog. Oceanogr. 2006, 71, 59−87. 12958



Article

(42) Hop, H.; Falk-Petersen, S.; Svendsen, H.; Kwasniewski, S.; Pavlov, V.; Pavlova, O.; Søreide, J. E. Physical and biological characteristics of the pelagic system across Fram Strait to Kongsfjorden. Prog. Oceanogr. 2006, 71, 182−231. (43) McClelland, J. W.; Montoya, J. P. Trophic relationships and the nitrogen isotopic composition of amino acids in plankton. Ecology 2002, 83, 2173−2180. (44) Gilmer, R. W.; Harbison, G. R. Diet of Limacina helicina (Gastropoda: Thecosomata) in Arctic waters in midsummer. Mar. Ecol.: Prog. Ser. 1991, 77, 125−134.

12959


Mercury Biomagnification in Marine Zooplankton Food Webs in

Recommend Documents