Bioaccumulation and Biomonitoring

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one single compartment (or box) without further considering any ... affected by both the flows into the system. (influx) and ... chelates with metal ions) can be used to wash ... where ku is the uptake rate constant from the dis- ... where C is the contaminant concentrations in the ..... channel was not involved in the uptake of Cd.
C H A P T E R

4 Bioaccumulation and Biomonitoring W.-X. Wang Hong Kong University of Science and Technology, Kowloon, Hong Kong

the chemistry of contaminants in the environments. Also of concern is modification by biology of the chemistry of contaminants in the environments, and how this in turn affects bioavailability. Finally, bioaccumulation is also concerned with the controls of physiology and biochemistry on contaminant uptake and elimination. In ecotoxicological studies, bioaccumulation and bioavailability are considered jointly. It would be impossible to study bioaccumulation without taking into account bioavailability, and vice versa. Thus, both are considered herein along with the use of bioaccumulation in biomonitoring. Traditional ecotoxicology mainly encompasses three frameworks, namely, the environmental transport, bioaccumulation, and toxicity of contaminants interacting with organisms (Wang, 2011a). Environmental risk assessments build upon these frameworks and provide input to management of contaminants in the environment. Bioaccumulation is the direct link between contaminants in environments and exposed organisms; toxicity can manifest after bioaccumulation occurs. Bioaccumulation directly links environmental chemistry/processes and organism physiology/biochemistry, and thus can be considered as an interface between environmental chemistry and biology.

Bioaccumulation is typically defined as the increase of concentrations of contaminants in aquatic organisms following uptake from the ambient environmental medium. Concentration is thus the central piece of any bioaccumulation study, and the significance of concentration must be understood. Numerous studies have therefore determined the concentrations of different contaminants in various species of aquatic organisms collected from different parts of the world, and the literature contains numerous examples of these data. For aquatic organisms there are different sources of uptake, such as water (as waterborne uptake) and/or food particles (as foodborne uptake). Bioaccumulation focuses on the processes of contaminant uptake and elimination in organisms. Another important concept is bioavailability, which is defined as the fraction of contaminants potentially available for uptake or actually taken up from the environment. Although closely linked, these two concepts are inherently different. Bioaccumulation examines the changes of concentrations of contaminants in the organisms, whereas bioavailability describes the portion of contaminants in the environment that is potentially available for bioaccumulation. Therefore, many bioavailability studies are concerned about

Marine Ecotoxicology http://dx.doi.org/10.1016/B978-0-12-803371-5.00004-7

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Copyright © 2016 Elsevier Inc. All rights reserved.

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4. BIOACCUMULATION AND BIOMONITORING

There has been an enormous body of studies on the bioaccumulation of contaminants in aquatic organisms over the past few decades. It is impossible to summarize all these findings in one single book chapter and the readers are also referred to some earlier reviews of this topic (eg, Spacie et al., 1995). Rather, this chapter mainly discusses the basic principles of bioaccumulation and the methods used to quantify bioaccumulation, some of the important considerations involved in the bioaccumulation assessments, and their use in biomonitoring. Most of the focus of this chapter is on metals; however, organic contaminants are also briefly discussed.

4.1 GENERAL PRINCIPLES OF BIOACCUMULATION Simply put, if an organism can be treated as one single compartment (or box) without further considering any internal transportation, the concentration (bioaccumulation) of a contaminant in the organism (box) is determined by the balance between influx and efflux, as shown in Fig. 4.1. Fig. 4.1 provides a very basic illustration of the bioaccumulation of contaminants in organisms. Although simple, it helps to understand that bioaccumulation is a very dynamic process, affected by both the flows into the system (influx) and out of the system (efflux). This figure shows that it is critical to study the influx and efflux of contaminants in order to understand bioaccumulation and that only examining either

influx or efflux is insufficient to fully appreciate the importance or process of bioaccumulation. Bioaccumulation is the net result of influx (uptake) and efflux. If influx is greater than efflux, contaminant concentration in the organism will increase with exposure time. When the influx is smaller than the efflux, there will be a net loss of contaminants and the concentration in the organism will decrease with exposure time. Under steady-state conditions, influx and efflux are equal, and contaminant concentration remains unchanged. In bioaccumulation modeling, steady-state condition is an important assumption (see below). Influx is defined as the uptake of contaminants from different environmental matrices (water, food); efflux is defined as loss of contaminants from organisms due to metabolic processes (eg, excretion, molting, reproduction). Efflux is rather broadly defined; other terms (eg, depuration, elimination, or loss) are also frequently used to describe efflux. Subtle differences exist among these different terms, eg, depuration is generally defined as the loss of contaminants from organisms following transfer from contaminated to clean environments; elimination generally implies some metabolically controlled processes. Growth is another important term since it can act to dilute contaminant concentrations in organisms. For most aquatic animals, both waterborne and dietborne contaminants contribute to overall bioaccumulation. Kinetic processes can be used to quantify uptake.

4.1.1 Absorption

FIGURE 4.1 A simple illustration of bioaccumulation in an organism. C, net accumulated concentration in the organism; t, time of exposure.

Absorption is defined as uptake from the dissolved phase; in some cases internalization has been used to describe the absorption of contaminants. Contaminant uptake from the dissolved phase involves the initial sorption and the internalization process; however, any measurements of absorption should explicitly remove the initial sorption to the surface of the animals, as this is

4.1 GENERAL PRINCIPLES OF BIOACCUMULATION

external, not internal. For some metals, chelates (eg, EDTA: ethylenediamine tetra-acetic acid, a crystalline acid with a strong tendency to form chelates with metal ions) can be used to wash off the surface sorption, which is defined as the weakly exchangeable fraction. For filter-feeding animals such as bivalves, absorption can be quantified by absorption efficiency, using the equation below: Influx ¼ ku  Cw ¼ a  FR  Cw

(4.1)

where ku is the uptake rate constant from the dissolved phase (L/g/h), Cw is the contaminant concentration in the dissolved phase (mg/L), FR is the filtration (or clearance) rate of the animal (L/g/h), a is the absorption efficiency (%), considered as the first-order rate constant. Strictly speaking, absorption efficiency is independent of the Cw and FR if absorption is not diffusion limited.

4.1.2 Assimilation In contrast to absorption from the dissolved phase, assimilation refers to uptake from a dietary source. When food is ingested by aquatic animals, digestion immediately occurs in the digestive system (eg, stomach). Undigested materials are subsequently egested in the form of feces, whereas the remaining components are absorbed across the gut linings. Following further metabolism, some of these components are lost from the body through elimination, respiration, or excretion; the remainder is finally incorporated into tissues, a process called assimilation (Fig. 4.2). The following equations summarize this energetically: IR ¼ AR þ Feces AR ¼ AE þ Excretion þ Respiration

(4.2) (4.3)

where IR is the total ingestion (feeding) rate, AR is the absorption rate, and AE is the assimilation rate. The assimilation efficiency (AE) is then calculated as the assimilation rate divided by the total ingestion.

FIGURE 4.2

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Processes involved when foods are digested.

4.1.3 Bioconcentration Factor (BCF) BCF is defined as the uptake of contaminants from the dissolved phase; it can be calculated by the following equation: BCF ¼ C=Cw

(4.4)

where C is the contaminant concentrations in the organisms (mg/kg) under equilibrium condition, Cw is the contaminant concentration in the water (mg/L). A key assumption for the calculation or measurement of BCF is that of equilibrium between the contaminant and organism. Equilibrium can be easily achieved for small organisms with fast growth rates; however, equilibrium is very difficult to reach for large organisms such as fish, in which equilibrium may not be reached during their entire life history. Numerous measurements of BCF for different contaminants (metals and organics) in different groups of aquatic organisms are now available, but many of these have potential problems. If the measurements are conducted using field populations, then bioaccumulation involves uptake from both water and food sources; therefore, the BCF should be supplemented with another important parameter, namely, the bioaccumulation factor (BAF), which is calculated as overall bioaccumulation in the organisms divided by the concentration in the environment (both dissolved and particulate phases). If the measurements are conducted in the laboratory, equilibrium between organism and water should be explicitly reached. In many laboratory studies, however, one can use concentration factor instead of BCF to quantify bioaccumulation if equilibrium is unknown.

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4. BIOACCUMULATION AND BIOMONITORING

BCF is an important concept in environmental risk assessment since it gives quantitative information regarding the ability of a contaminant to be taken up by organisms from the water. It is often used as one of the first screening parameters for persistent, bioaccumulative, and toxic substances. However, note that BCF is not a constant (or a factor as generally implied). Instead, BCF is a variable depending on different environmental and biological conditions. BCF is inversely dependent on contaminant concentrations in the water (for metals) or the octanole water partitioning coefficient (Kow) (for organic substances) (McGeer et al., 2003). Similar to BCF, the BAF is not a constant; it is also dependent on the ambient concentration (DeForest et al., 2007). Toxicokinetics describes the kinetic process of contaminants in the organisms, including uptake, assimilation, storage, sequestration, transportation, and elimination. Thus, toxicokinetics is more broadly defined as compared to the bioaccumulation, since it also considers the internal processes of contaminants once they are taken up and accumulated. Toxicokinetics is an important research area in ecotoxicology, especially for organic contaminants due to their significant biotransformation within the body of organisms.

4.2 BIOACCUMULATION MODELING Many models are used to simulate the bioaccumulation of contaminants. Overall, these can be categorized into two types: the equilibrium partitioning model (EqP) and the kinetic model.

4.2.1 Equilibrium Partitioning Model (EqP) The EqP model is relatively simple, assuming that waterborne is the only source of accumulation (Fig. 4.3). Thus, the BCF can be used to quantify bioaccumulation of contaminants by organisms. EqP modeling has been used extensively for organic contaminants mainly because the bioaccumulation of organic contaminants is related to the Kow of the chemicals, thus BCF can be used to predict their bioaccumulation. For metals, this model can be used to predict bioaccumulation in small organisms such as bacteria and phytoplankton since equilibrium in these organisms occurs. However, such an approach is not reliable for larger organisms in which equilibrium does not occur. Table 4.1 summarizes some typical BCF values in marine organisms. Differences in BCF among metals or organisms are considerable and are related to the cell volume or the chemical property of metals (Fisher, 1986). BCF also varies greatly in different environments, and it is impossible to use one single BCF to represent different organisms for every chemical (metal or organic). BCF simply serves as the initial screening value for potential bioconcentration of different contaminants in organisms. Another disadvantage of the EqP model is that it only considers exposure of organisms to contaminants in water and ignores the possible exposure of food source. Due to the importance of trophic transfer in contaminant accumulation in marine organisms (Wang, 2002; Wang and Rainbow, 2008), BCF cannot generally be used alone to model bioaccumulation of contaminants

FIGURE 4.3 A simple equilibrium partitioning model. BCF, bioconcentration factor.

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4.2 BIOACCUMULATION MODELING

Bioconcentration Factor (BCF) of Nine Metals in Different Groups of Marine Organisms (L/kg)

TABLE 4.1 Group

Ag

Phytoplankton

5  10

Macrophyte

Cd

Cs

Cr

10

20

5  10

5  103

2  104

50

Zooplankton

2  104

6  104

Mollusks

6  104

Crustaceans Fish

Hg

Ni

Se

Pb

Zn

5

10

3  10

3  10

10

104

6  103

2  104

2  103

103

103

2  103

40

103

4  103

103

6  103

103

105

8  104

60

2  103

2  103

2  103

9  103

5  104

8  104

2  105

8  104

50

102

104

103

104

9  104

3  105

104

5  103

100

2  102

3  104

103

104

2  102

103

4

3

3

5

3

4

Note that here and in this chapter the term “metals” includes metalloids such as arsenic (As) and nonmetals such as selenium (Se). From IAEA (International Atomic Energy Agency), 2004. Sediment Distribution Coefficients and Concentration Factors for Biota in the Marine Environment. Technical Report Series, No. 422. Vienna, Austria.

in organisms. However, for organisms that accumulate contaminants only from the dissolved phase (eg, phytoplankton, macrophytes), BCF can still be a useful and practical approach to modeling bioaccumulation, especially for initial screening.

Under steady-state condition, dC/dt ¼ 0, the steady-state concentration (Css) can be calculated as: Css ¼ ku  Cw =ke

(4.7)

4.2.2 Kinetic Modeling Kinetic modeling is not constrained by equilibrium considerations; it can be used to simulate the kinetic changes in contaminant bioaccumulation over time. There are several developed kinetic models, varying from the simplest one-compartmental model to multicompartmental models (Fig. 4.4). The simple one-compartmental kinetic model can be simulated by the following equation: dC=dt ¼ ku  Cw  ke  C

(4.5)

where ku is the uptake rate constant from water (L/g/h), Cw is the contaminant concentration in the water (mg/L), ke is the efflux rate constant, and C is the accumulated concentration (mg/g). After integration, the accumulated concentration of contaminant at time t can be described by the following equation:   Ct ¼ ku  Cw =ke  1  eke t (4.6)

FIGURE 4.4 Schematic illustrations of one- and twocompartmental models with different rate constants involved (C as concentration, k as rate constant).

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4. BIOACCUMULATION AND BIOMONITORING

With known ku, ke, and Cw, it is then possible to predict the concentration of contaminants under steady-state conditions. Since BCF ¼ Css/Cw, BCF can also be calculated using the two kinetic parameters:

Under steady-state conditions, dC/dt ¼ 0, and the accumulated concentration can be calculated (Css) as:

BCF ¼ ku =ke

Kinetic modeling is a relatively simple concept that was used extensively in radioecology in the 1970s. Thomann (1981) further developed such modeling by introducing bioenergetic concepts into the equation:

(4.8)

The above equation directly quantifies the BCF, especially for large organisms. A simple determination of the ku and ke can then accurately predict the BCF. There are inherent links between the EqP and kinetic models, given the fact that both ku and ke are considered as the kinetic parameters. For many aquatic animals, both dissolved and food sources contribute to contaminant accumulation. The simple kinetic model can incorporate the food exposure source (Fig. 4.5): dC=dt ¼ ½ku  Cw þ kf  Cf   ðke  CÞ

(4.9)

where kf is the uptake rate constant from the food source, Cf is the contaminant concentration in the food. Again, this model can be solved to predict the accumulated concentration at specific time t:   Ct ¼ ½ku  Cw þ kf  Cf =ke  1  eke t (4.10)

Css ¼ ½ku  Cw þ kf  Cf =ke

(4.11)

ku ¼ a  FR

(4.12)

kf ¼ AE  IR

(4.13)

where a is the absorption efficiency of contaminants from the water, FR is the filtration rate of the organisms (eg, amount of water filtered or cleared), AE is the dietary assimilation efficiency, IR is the ingestion rate of the organisms. The kinetic equation has therefore been sometimes termed as a bioenergetic-based model or biokinetic/biodynamic model. The Css can be calculated as: Css ¼ ½a  FR  Cw þ AE  IR  Cf =ke (4.14) The above model ignores the growth of organisms, which can be an important parameter for organisms displaying high growth rates (eg, small organisms such as bacteria and phytoplankton). Thus a more complete kinetic model should also consider the growth rate constant (g) of the organisms: Css ¼ ½a  FR  Cw þ AE  IR  Cf =ðke þ gÞ (4.15)

FIGURE 4.5

Kinetic model simultaneously considers uptake from the waterborne and dietborne phases, with different kinetic parameters used to quantify bioaccumulation.

The above model treats an organism as one single compartment without further going into the kinetic processes within the organisms (eg, transportation, redistribution, storage, and sequestration). However, with this basic equation, it is then possible to further consider a few special cases. For example, water is the only source of uptake for marine phytoplankton in which g is much higher than ke. The

4.3 KINETIC PARAMETERS

concentration of a contaminant in the phytoplankton can thus be calculated as: Css ¼ ðku  Cw Þ=g ¼ Iw =g

(4.16)

where Iw is the influx from the water source. This equation has significant application in studying the uptake of contaminants in phytoplankton, which can be directly calculated with a known Css and g. If trophic transfer is the only source of bioaccumulation, Eq. (4.15) can also be simplified as: Css ¼ ðkf  Cf Þ=ke

(4.17)

Trophic transfer factor (TTF) or biomagnification factor (BMF) is then calculated as: TTF ¼ BMF ¼ Css =Cf ¼ kf =ke

(4.18)

The concept of a TTF or BMF is very similar to that of BCF. A simple method to quantify the TTF or to examine whether a contaminant has the potential of being biomagnified in the food chain (ie, whether concentrations of a substance increase through three or more trophic levels via food uptake alone) is to compare the two kinetic parameters of kf and ke. A greater than 1 of TTF requires that kf is greater than ke. The biokinetic model provides a complete picture of the overall bioaccumulation of contaminants in organisms. Biological or chemical parameters identified in the model are realistic, but their measurements require much more specialized methodology (eg, radiotracers or clean techniques). Currently, we need a more comprehensive understanding of these kinetic parameters, which will ultimately affect their measurement.

4.3 KINETIC PARAMETERS Kinetic modeling plays an important role in studying the bioaccumulation of contaminants (especially metals) in marine organisms (as

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reviewed by Wang and Rainbow (2008)). There are quite a few parameters that need to be determined for the model simulation. Accurate measurements of these parameters are among the challenges faced by ecotoxicologists. For example, Cw and Cf require specialized analytical skills, especially in the measurements of low Cw in the water. FR, IR, and g are the subjects of physiological ecology studies (eg, feeding and growth processes of marine organisms under complex ecological conditions). AE, ku, and a are the subjects of ecotoxicological study. Over the past decades, there has been significant progress in refining the methodology to quantify these parameters. Researchers now need to carefully consider the methods and caveats for different targeted organisms or contaminants. As methodology improves, the variation of these parameters under different environmental and biological conditions becomes more important.

4.3.1 Dissolved Uptake Rate Constant ku Table 4.2 summarizes some of the measured ku values of metals in different groups of marine organisms, which generally suggests that (1) relatively small organisms tend to have a greater ku value compared to larger organisms and (2) Class B metals have higher ku values compared with Class A metals. SeO3 2 and CrO4 2 had the lowest ku, most likely because they are transported through anionic channels. In comparison with the ku, a (absorption efficiency), the first-order kinetic parameter, is much less well known and investigated; a can be calculated as ku/FR, whereas FR is often not simultaneously quantified in the majority of kinetic determinations of ku. Strictly speaking, comparison of bioavailability among different organisms should be based on a instead of ku since the FR can differ greatly among species of marine organisms.

106 TABLE 4.2

4. BIOACCUMULATION AND BIOMONITORING

Waterborne Dissolved Uptake Rate Constants of Metals in Marine Animals (L/g/d) (Wang, 2011b) Ag

Cd

Zn

Se

Hg(II)

CH3Hg

10.51

99.6

Copepods

Temora sp.

8.45e12.84

0.626e0.796

2.388e3.993

0.017e0.035

Bivalves

Mytilus edulis

1.794

0.365

1.044

0.035

Perna viridis

0.638e8.212

0.206

0.637

0.019

Ruditapes philippinarum

2.620

0.064

0.234

Crassostrea rivularis

0.719

2.050

0.060

Saccostrea glomerata

0.534

1.206

0.064

2.604

3.445

Macoma balthica

0.032

0.091

Chlamys nobilis

0.455

0.677

0.028

0.359

0.006

1.27

2.58

0.030

0.069

0.079

0.108

Polychaetes

Nereis succinea

Gastropods

Thais clavigera Haliotis diversicolor

1.853

1.78

0.056

0.32

Sipunculans

Sipuncula nudus

0.0018

0.035

Fish

Acanthopagrus schlegeli

0.002

0.0055

Plectorhinchus gibbosus

0.195

Lutjanus argentimaculatus

0.005

0.0100

Sparus auratus

0.005

0.004

Numerous studies have determined the influences of different chemical and biological factors on the ku. For example, Veltman et al. (2008) demonstrated the significant relationships between the covalent index representing the binding affinity of metals/biotic ligand and the ku of 10 metals in 17 aquatic species. The covalent index can be calculated from x2m r, where xm is the Pauling electronegativity value and r is the ionic radius. The a of metals was also significantly related to the covalent index. These relationships suggest that facilitated membrane transport is likely the main mechanism for the uptake of many of these metals. The uptake rate, ku, is also closely related to the biology of the organisms, eg, the body size of the animals. Relatively small animals display a higher ku than larger animals (Zhang and Wang,

4.515

0.0008

2007a; Wang and Dei, 1999). An interesting question in ecotoxicology is whether uptake is dependent on the growth rate of the organisms. Based on Eq. (4.16), if the growth rate is independent of the uptake rate (or ku), a faster growth of organisms may lead to a reduced accumulated concentration (eg, the ku remains constant). Conversely, if the uptake is related to g, bioaccumulation will be dependent on the relative magnitude of changes of these two parameters. Answering this question is fundamental in explaining the feedback mechanisms of metal accumulation in phytoplankton (Sunda and Huntsman, 1998). For example, a metal may inhibit the growth of phytoplankton, which then leads to a reduction in g and then a further increase in the metal concentration in the cells. This is considered as a positive feedback mechanism to phytoplankton.

4.3 KINETIC PARAMETERS

Conversely, the limitation of an essential metal (eg, reduced availability of Cu or Zn) may reduce phytoplankton growth, leading to an increase in cellular metal concentration. Such feedback alleviates essential metal limitations in the cells. Previous studies specifically designed to test the dependence of metal uptake on phytoplankton showed that metal uptake by the cells increased with increasing phytoplankton growth (Miao and Wang, 2004; Wang et al., 2005). Therefore, with increasing cellular growth concentrations of accumulated metals in cells will be dependent on the relative degree of changes of these two parameters (uptake vs. growth). Environmental factors can of course considerably affect the ku of contaminants. Among these environmental factors, salinity, temperature, dissolved organic matter (DOM), other competing ions such as Hþ, Ca2þ, Mg2þ, and dissolved oxygen have received the most attention. Most of such influences are due to changes in the speciation of contaminants as well as the physiological and biochemical processes of the animals. Salinity is probably the best studied environmental factor influencing the ku (Wang et al., 1996; Wang and Dei, 1999). In addition to its direct effect on speciation, salinity can also cause physiological changes. For example, Zhang and Wang (2007b) acclimated the marine seabream (Acanthopagrus schlegeli) to different salinities (including freshwater) and quantified uptake of Cd and Zn. With a decrease of salinity from 35 to 0 psu, the uptake of Cd increased by 31 times and of Zn increased by 16 times. A significant relationship was then between increased uptake and an increase in water-free ion concentration (for Cd uptake in the gills, the relationship was 1:1), strongly indicating that change of free [Cd2þ] could entirely explain the influence of salinity on Cd uptake in this marine fish. Transport of metals via the ion channel (Ca channel) was different at different salinities. At high salinity, the calcium channel was not involved in the uptake of Cd and Zn, which was primarily facilitated. At

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lower salinity (eg, freshwater), the calcium channel was actively involved in the uptake of Cd and Zn (transcellular uptake). This work illustrates the complexity of metal chemistry and fish physiology in affecting metal uptake in fish at different salinities. Blackmore and Wang (2003a) compared metal uptake in marine green mussels Perna viridis from two contrasting salinity sites in Hong Kong waters after acclimation in the laboratory at different salinities. Mussels collected from a high-salinity site accumulated metals 1.2 to 2.2 times faster than mussels collected from a lowsalinity site when they were acclimated at intermediate and high experimental salinities (>17 psu). This difference was not explained by the gill surface area (which was similar in both populations of mussels) and filtration rate. Instead, the apparent water permeability of the high-salinity population was on average about 1.6 times greater compared with the lowsalinity population and may partially account for the difference in metal uptake between these two populations. This study also suggested that the effect of salinity on metal uptake is dependent on metal biogeochemistry as well as a range of physiological responses. The role of DOM in metal uptake is contradictory for different organisms and presumably for different quantities and qualities of DOM. One school of thought is that DOM can complex metals in the water, thereby effectively reducing the bioavailable fraction of metals and reducing their uptake. However, there is also evidence that DOMemetal complexes may be directly available for organisms such as filter-feeding bivalves. Such cotransport of a DOMemetal complex has been demonstrated in bivalves (Roditi et al., 2000; Pan and Wang, 2004). Clearly the functional physiology of the animals should be considered in examining the influences of different factors on metal uptake in marine organisms. This is probably one of the most important considerations in future bioaccumulation studies.

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4. BIOACCUMULATION AND BIOMONITORING

4.3.2 Assimilation Efficiency The concept of assimilation efficiency (AE) in bioaccumulation has been well developed. Numerous studies have quantified the dietary assimilation of contaminants (mostly metals) in marine animals, largely as a result of the availability of radiotracer techniques. Table 4.3 summarizes the available AEs of different metals in different marine animals. Similar to ku, the AEs are influenced by many biological, chemical, and environmental factors (Wang and Fisher, 1999; Wang and Rainbow, 2008). An active area of research on the bioaccumulation of dietary metals is the control of different cellular fractions of metals in the prey on the assimilation by their predators. In early studies, the distribution of metals in phytoplankton was divided into two fractions: TABLE 4.3

Dietary Assimilation Efficiencies of Metals (%) in Different Marine Animals (Wang, 2011b)

Animals Copepods

Bivalves

the cell wall/membrane, and the cytoplasmic fraction. These studies found that metals bound with the cytosolic fraction displayed a much higher bioavailability to marine herbivores such as copepods and bivalves than to other marine organisms (Reinfelder and Fisher, 1991; Wang and Fisher, 1996). Later studies then focused on the controls of internal metal sequestration in prey on dietary bioavailability in predators. Wallace and Luoma (2003) proposed a concept of trophically available metal (TAM) to explain the trophic availability of Cd and Zn in the bivalve prey to grass shrimp Palaemon macrodatylus. This concept has been tested and verified in several species of marine predators such as gastropods and fish (Cheung and Wang, 2005; Zhang and Wang, 2006; Rainbow et al., 2007).

Ag Acartia sp.

Cd

Zn

Se

66

9

38

Temora sp.

8e19

33e53

52e64

50e59

Mytilus edulis

4e34

28e34

32e45

56e72

Perna viridis

13e32

11e25

21e32

59

Ruditapes philippinarum

30e52

38e55

33e59

Crassostrea rivularis

58e75

68e80

56e74

Saccostrea glomerata

52e67

60e65

52e68

Macoma balthica

88

50

74

Chlamys nobilis

94

83

5e44

24e57

75

80

Polychaetes

Nereis succinea

Gastropods

Thais clavigera Haliotis diversicolor

12e27

58e83

Hg(II)

CH3Hg

41e70

36e60

33e59

20

70

70

95

65e78

Sipunculans

Sipuncula nudus

6e30

5e15

Fish

Terapon jarbua

3e9

2e52

13e26

Plectorhinchus gibbosus Lutjanus argentimaculatus

20

40

Sparus auratus

45

18

65

23e43

90

20

80

4.3 KINETIC PARAMETERS

Guo et al. (2013) investigated how the subcellular metal distribution and the metal burden in prey affected the transfer of metals to a marine fish, the grunt Terapon jarbua. Oysters, Crassostrea hongkongensis, which had different contaminated histories, were collected and separated into three subcellular fractions (metal-rich granules, cellular debris, and a combined fraction of organelles, heat-denatured proteins, and metallothioneinlike proteins, defined as TAM). These purified fractions, representing a wide range of metal concentrations, were fed to the fish for a period of 7 days at a daily comparable feeding rate of 3% of fish body weight. Bioaccumulation of Cd, Cu, and Zn was quantified by the trophic transfer factor (TTF). All three subcellular fractions were bioavailable to the fish. With a certain degree of variation among metals, the TTFs showed a metal uptake sequence of cellular debris > TAM > metal-rich granules, indicating the impact of subcellular distribution in prey on metal bioavailability. However, significant inverse relationships between the TTFs and the metal concentrations in diets were also found in this study, especially for Cd and Zn, suggesting the high dependence of TTF on metal concentration in prey. In this case, the subcellular metal compartmentalization might be less important than the overall metal concentration in prey influencing the trophic transfer. While the physicochemical form of the accumulated metal in prey is an important factor affecting the metal AE and trophic transfer (Luoma and Rainbow, 2008; Rainbow et al., 2011), physiological conditions certainly affect assimilation (Wang and Rainbow, 2005). Digestion processes such as the gut passage time, partitioning of extracellular and intracellular digestion, or induction of various binding ligands are all important considerations.

4.3.3 Efflux Efflux is an important determinant of metal accumulation in marine organisms. The

109

application of radiotracer technique offers an opportunity to quantify the efflux of contaminants in a variety of marine organisms (Table 4.4). However, efflux measurements must be done carefully with particular attention to the duration of radiolabeling (allowing sufficient equilibration of radioisotopes within the internal tissues). Fig. 4.6 illustrates the results of radiolabeling to measure metal efflux in marine animals. A predominant distribution in the digestive system (fast uptake compartment, eg, a short feeding time or radiolabeling) results in a relatively small partitioning of radiotracer in the physiological turnover (slow) compartment (involved mainly in metabolism) (k2), which then leads to the predominance of fast compartment loss over the true efflux. Conversely, if the physiological turnover compartment becomes a dominant pool of metals, the potential influence of the fast metal uptake compartment on efflux would be small. Compared to influx or uptake, the role of efflux in determining bioaccumulation has been less recognized, primarily due to the relatively conservative behavior of efflux in marine animals, as well as the long timeframe required to realistically determine efflux. In measuring efflux, organisms are exposed to radiotracers and then depurated for a longer duration (weeks to months for larger animals such as bivalves or fish). Therefore, ke measurement is much more tedious as compared to measurements of dissolved uptake or dietary assimilation. A common consensus for efflux is that the difference among metals is smaller than the difference among organisms. For example, the efflux rate constant of different metals in marine bivalves ranges between 0.01 and 0.03 d1, whereas for small organisms such as copepods with a much higher weightspecific metabolic rate, the ke can be much higher. Some of these animals even have a turnover rate of once per day (Table 4.4). Efflux can lead to the hyperaccumulation of metals (Luoma and Rainbow, 2005). Oysters are the best-known marine organisms

110 TABLE 4.4

4. BIOACCUMULATION AND BIOMONITORING

Typical Efflux Rate Constants of Metals in Different Marine Organisms (d1) (Wang, 2011b) Ag

Cd

Zn

Se

0.590

0.620

0.890

0.173e0.294

0.108e0.297

0.079e0.108

0.155

Mytilus edulis

0.034

0.011

0.020

0.026

Perna viridis

0.032e0.087

0.020

0.029

Ruditapes philippinarum

0.010

0.023

Crassostrea rivularis

0.014

0.014

0.034

Saccostrea glomerata

0.004

0.003

0.013

Macoma balthica

0.018

0.012

Chlamys nobilis

0.005e0.009

0.012e0.023

Hg(II)

CH3Hg

0.027

0.014

COPEPODS Acartia sp. Temora sp. BIVALVES

POLYCHAETES Nereis succinea Gastropods Haliotis diversicolor

0.003

0.011

0.011

FISH Acanthopagrus schlegeli

0.089

0.016

0.043

Plectorhinchus gibbosus

0.028e0.055

Lutjanus argentimaculatus

0.025e0.047

0.015

Sparus auratus

0.016

0.006

accumulating very high concentrations of Cu and Zn; barnacles are the typical hyperaccumulators of Zn. These high metal concentrations are primarily driven by the very low efflux of metals. For example, the ke of Zn in the barnacle Balanus amphitrite can be as low as 0.001 d1 (Table 4.4). Oysters also have a very low efflux of Cu and Zn. The physiological or biochemical mechanisms underlying the ke are less well known, for instance, how metals are turned over in the organisms and whether their turnover is coupled with the turnover of their potential binding ligands (such as proteins).

0.010e0.013

0.027e0.031

Fig. 4.7 provides a conceptual framework for the possible subcellular systems involved in the efflux of metals although presently knowledge is lacking on the kinetic changes of metal distributions in the internal metal pools and how these will affect overall efflux. This is clearly an important future research area. Ng and Wang (2005) examined the dynamics of subcellular distribution of Cd, Ag, and Zn in the green mussel P. viridis by partitioning the metals into the insoluble fraction (IF), heatsensitive proteins, and metallothionein-like proteins (MTLP) during elimination. During efflux,

4.4 APPLICATION OF BIOACCUMULATION MODELING

111

FIGURE 4.6 An illustration of the loss of metals from digestive (fast) compartment (DG) and physiological turnover (slow) compartment (PT). (A) dominated by digestion process; (B) dominated by physiological turnover process.

metals in the soluble fraction mediated depuration, whereas metals in the insoluble fraction acted as a final storage pool. A higher efflux rate of Ag and Cd was related to a higher partitioning in the MTLP and a lower partitioning in the IF. Pan and Wang (2008a) investigated the dynamics of subcellular distribution in the scallop Chlamys nobilis, which accumulated very high concentrations of Cd and Zn. Storage in the nontoxic form both in organelles and MTLP accounted for the low efflux rate of Cd from scallops. During efflux, an increasing percentage of Cd was sequestered in organelles (eg, lysosomes), but that in the MTLP fraction remained stable, implying that MTLP may act simply as a sink in the metal detoxification process. Internal Cd may be eventually eliminated slowly from lysosomes or removed to and deposited in the MTLP fraction for storage, leading to the highest percentage of Cd in the MTLP fraction.

In contrast, Zn is eliminated more quickly than Cd from the scallops; its redistribution among each subcellular compartment was much faster than the redistribution of Cd, suggesting an effective regulation mechanism. Efflux is influenced by environmental conditions such as temperature, tissue concentrations of the contaminants, route of exposure, as well as food conditions (Wang and Fisher, 1998) or internal sequestration. For example, once Ag was complexed by S in tissues of the mussel P. viridis, depuration basically did not occur (Shi et al., 2003). Buchwalter et al. (2008) also found that the efflux of Cd in 21 species of aquatic insects was directly related to its partitioning in the MTLP fraction. Poteat et al. (2013) explored species-specific traits in contributing to differences in environmental sensitivity among species. The efflux of Cd and Zn strongly covaried across species in aquatic insect families (Ephemerellidae and Hydropsychidae). Taxonomic groups (arthropods, mollusks, annelids, and chordates, 77 species total) exhibited marked variability in efflux, suggesting that some groups are more constrained than others in their abilities to eliminate metals.

4.4 APPLICATION OF BIOACCUMULATION MODELING

FIGURE 4.7 Hypothetical subcellular ligands binding with metals (L1, L2, L3) and possible efflux from different compartments. ke is the overall efflux from the organism.

A bioaccumulation conceptual model, which provides a general framework for studying bioaccumulation, is reviewed by Luoma and Rainbow (2008) and Wang and Rainbow (2008).

112

4. BIOACCUMULATION AND BIOMONITORING

The model cannot only be used to simulate and predict bioaccumulation, but also to examine the various exposure pathways, and generally to help understand the bioaccumulation processes. It is well known that Hg concentrations in marine fish increase with body size, in strong contrast with most of the other metals (ie, their concentrations decrease with body size). Such lack of growth dilution puzzled ecotoxicologists, whose speculations included shifts in dietary requirements (eg, a shift from a more herbivorous diet to a predatory diet) and slower elimination of Hg in larger fish. Dang and Wang (2012) addressed this interesting issue by first quantifying the size dependence of Hg concentrations in field-collected juvenile blackhead seabream A. schlegeli. Due to the size limit of kinetics measurements, only juvenile fish (3.8e12 cm) were examined. Hg measurements confirmed that total mercury (THg) and methylmercury (MeHg) concentrations were related to fish mass over a wide size range with a power coefficient of 0.19 and 0.33, respectively. Table 4.5 summarizes the body size dependence of different biokinetic parameters of Hg(II) and MeHg in the fish. Negative correlations between Hg biokinetics and body size were documented for ku, ke, and g, whereas the AE of Hg(II) increased with body size and

TABLE 4.5

Allometric Relationship Hg(II) and MeHg in Marine Fish Acanthopagrus schlegeli

Parameters

Hg(II)

MeHg

ku (L/g/d)

0.24W0.68

0.36W0.54

AE (%)

25.6W0.260

80e100

ke (d1)

0.050W0.36

0.0062W0.40

g (d1)

0.0077W0.42

Body concentration (ng/g)

5.91W0.33

21.5W0.19

Data from Dang, F., Wang, W.-X., 2012. Why mercury concentration increases with fish size? Biokinetic explanation. Environ. Pollut. 163, 192e198.

MeHg had a comparable AE among different sizes of fish. With these determined relationships, Dang and Wang (2012) then modeled the scaling exponents of Hg accumulation to be 0.21 for MeHg and 0.21 to 0.25 for THg, which were in fact very close to independent field measurements (0.33 for MeHg and 0.19 for THg). The allometric biokinetic parameters thus reasonably well explained the size-dependent mercury accumulation patterns observed in juveniles in natural systems. Sensitivity analysis further showed that a decrease of g and ke with increasing body size effectively increased the Hg concentrations, and were the key drivers for such relationships. Dang and Wang (2012) demonstrated that slower growth coupled with a lower mercury efflux rate increased both MeHg and THg concentrations and yielded positive size-dependent allometric correlations. To manage Hg contamination in fish, factors that enhance the g and ke should be explored. Interestingly, farmed fish have a low Hg body concentration as a result of their rapid growth in the farming system, as well as the use of artificial diets with low Hg concentrations; Hg concentrations are also lower in eutrophic systems where the fish can grow rapidly than in oligotrophic waters. Chen and Folt (2005) analyzed fish Hg burdens and plankton densities from 38 lakes in the northeastern USA and found a negative correlation between zooplankton density and Hg concentrations in zooplankton and in both herbivorous and predatory fish. Zooplankton density alone explained more than 40% of the variation in predatory fish Hg concentrations across lakes. Rapid growth from high-quality food consumption can also significantly reduce the accumulation and trophic transfer of MeHg in freshwater food webs (Karimi et al., 2007). Ward et al. (2010) also examined the effect of growth on trace element concentrations in fish by measuring the concentrations of seven metals (As, Cd, Cs, Hg, Pb, Se, Zn) in stream-dwelling

113

4.5 BIOMONITORING

Atlantic salmon from 15 sites encompassing a 10-fold range in salmon growth. The fastgrowing salmon had lower concentrations of all metals than slow-growing salmon, similarly suggesting that dilution of metals in larger biomass led to lower concentrations in fastgrowing fish. Another application of the biokinetic model is that of predicting the TTF of different contaminants in marine animals involved only in trophic transfer (dietary or food intake). Assuming that food is the only source for contaminant accumulation in marine animals, the TTF is calculated as: TTF ¼ BMF ¼ C=Cf ¼ AE  IR=ke

(4.19)

Clearly, potential biomagnification of contaminants is determined by three kinetic parameters, ie, AE, IR, and ke. Wang (2002) predicted the TTF in different species of marine animals based on extensive measurements of these biokinetic parameters. Based on that prediction, contaminants and predators differ considerably in their potential biomagnification along food chains. Whereas it is well known that MeHg is biomagnified, other metals such as Cs, Se, or even Zn (for small fish) can potentially have a TTF > 1 in marine fish. Many benthic invertebrates such as bivalves and predatory gastropods show a high potential of TTF being greater than 1 for different reasons. For example, bivalves have a very high IR, as well as a high dietary metal AE, whereas predatory gastropods have a very high AE, although their IRs are typically low. Fish have a relatively low AE and IR for the majority of the metals, and their potential TTF is the lowest for the majority of metals. Ecotoxicologists need to appreciate the diversity of metal biology in studying the food chain transfer of contaminants. Such complexity has often been neglected in making the general conclusion regarding biomagnification of contaminants. Strictly speaking, TTF is not a constant but rather is variable depending on the three kinetic parameters (AE, IR, and ke) that are highly controlled by the environmental conditions as

well animal physiology. In some cases, metal concentrations in marine animals are not related to food chain metal concentrations. Filterfeeding oysters hyperaccumulate Cu and Zn; scallops hyperaccumulate Cd; and barnacles hyperaccumulate Zn. The highest concentrations of Cu and Zn in oysters were around 2.5% of body tissue dry weights collected from a severely contaminated estuary in China (Wang et al., 2011; Wang and Wang, 2014). Wang et al. (2011) and Tan et al. (2015) have studied the mechanisms underlying such phenomenal metal concentrations. The TTF for organic contaminants in marine animals has been relatively less well documented compared to metals; studies examining the biokinetic processes of organic contaminants in marine animals (eg, DDTs, PCBs, PAH) are limited. Some typical values for these contaminants are summarized in Table 4.6.

4.5 BIOMONITORING The classical example of biomonitoring based on bioaccumulation is the Mussel Watch Program, first proposed in the 1970s (Phillips, 1976, 1977; Goldberg et al., 1978). Since the concentrations of many contaminants in marine waters are generally low and difficult to accurately measure, using biomonitors to reflect environmental contaminant concentrations is certainly an attractive approach. Bioconcentration of contaminants in the biomonitors can reach up to a few orders of magnitude higher than the ambient concentrations (Table 4.1) and can be measured with reasonable certainty. The most important reason for using the biomonitors is that these measured concentrations indicate the bioavailable fractions in the environments and are thus much more biologically relevant than simply measuring chemical concentrations in water (or sediments). However, following significant improvements in analytical techniques, it is now possible to

114 TABLE 4.6

4. BIOACCUMULATION AND BIOMONITORING

Biokinetics of Selected Organic Contaminants in Marine Animals ku (L/g/h)

AE (%)

ke (dL1)

TTF

References

0.82e1.66