Comparative Biochemistry and Physiology Part C 133 (2002) 305–343
Review
Extension of the biotic ligand model of acute toxicity to a
physiologically-based model of the survival time of rainbow trout
(Oncorhynchus mykiss) exposed to silver夞
Paul R. Paquina,*, Viktoria Zoltayb, Richard P. Winfieldc, Kuen Benjamin Wua,
Rooni Mathewa, Robert C. Santored, Dominic M. Di Toroa,e
a
HydroQual Inc., 1 Lethbridge Plaza, Mahwah, NJ 07430, USA
b
Environmental Resources Management, Boston, MA, USA
c
USEPA, Region 2, New York, NY, USA
d
HydroQual Inc., 4914 West Genesee Street, Suite 119, Camillus, NY 13031, USA
e
Environmental Engineering Department, Manhattan College, 4513 Manhattan College Parkway, Bronx, NY 10471, USA
Received 3 January 2002; received in revised form 12 June 2002; accepted 20 June 2002
Abstract
Chemical speciation controls the bioavailability and toxicity of metals in aquatic systems and regulatory agencies are
recognizing this as they develop updated water quality criteria (WQC) for metals. The factors that affect bioavailability
may be quantitatively evaluated with the biotic ligand model (BLM). Within the context of the BLM framework, the
‘biotic ligand’ is the site where metal binding results in the manifestation of a toxic effect. While the BLM does account
for the speciation and complexation of dissolved metal in solution, and competition among the free metal ion and other
cations for binding sites at the biotic ligand, it does not explicitly consider either the physiological effects of metals on
aquatic organisms, or the direct effect of water chemistry parameters such as pH, Ca2qand Naq on the physiological
state of the organism. Here, a physiologically-based model of survival time is described. In addition to incorporating the
effects of water chemistry on metal availability to the organism, via the BLM, it also considers the interaction of water
chemistry on the physiological condition of the organism, independent of its effect on metal availability. At the same
time it explicitly considers the degree of interaction of these factors with the organism and how this affects the rate at
which cumulative damage occurs. An example application of the model to toxicity data for rainbow trout exposed to
silver is presented to illustrate how this framework may be used to predict survival time for alternative exposure
durations. The sodium balance model (SBM) that is described herein, a specific application of a more generic ion
balance model (IBM) framework, adds a new physiological dimension to the previously developed BLM. As such it
also necessarily adds another layer of complexity to this already useful predictive framework. While the demonstrated
capability of the SBM to predict effects in relation to exposure duration is a useful feature of this mechanistically-based
framework, it is envisioned that, with suitable refinements, it may also have utility in other areas of toxicological and
regulatory interest. Such areas include the analysis of time variable exposure conditions, residual after-effects of exposure
to metals, acclimation, chronic toxicity and species and genus sensitivity. Each of these is of potential utility to longerterm ongoing efforts to develop and refine WQC for metals.
䊚 2002 Elsevier Science Inc. All rights reserved.
Keywords: Toxicity; Silver; Metals; Rainbow trout; Fish physiology; Ionoregulation; Osmoregulation; Biotic ligand model; Ion
balance model; Sodium balance model
夞 This paper is the outcome of discussions on the Biotic Ligand Model held during the November 2001 SETAC Annual Meeting
in Baltimore, MD, USA.
*Corresponding author. Tel.: q1-201-529-5151; fax: q1-201-529-5728.
E-mail address: ppaquin@hydroqual.com (P.R. Paquin).
1532-0456/02/$ - see front matter 䊚 2002 Elsevier Science Inc. All rights reserved.
PII: S 1 5 3 2 - 0 4 5 6 Ž 0 2 . 0 0 1 0 5 - 9
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P.R. Paquin et al. / Comparative Biochemistry and Physiology Part C 133 (2002) 305–343
1. Introduction
Although water quality criteria (WQC) for metals have been expressed in terms of empirically
derived relationships with hardness for several
decades, other water quality characteristics that
also affect the toxicity of metals have been overlooked in this regard (European Commission,
1996; USEPA, 1999). This was because the previously available test data were both limited in
extent, with regard to the range of water quality
parameters and concentrations of interest, and difficult to interpret, given the complexity of the
chemical and biological interactions that were
reflected in these data.
The development of a clear understanding of
how water quality characteristics affect metal
availability and toxicity to aquatic life has been
steadily advancing over the past three decades.
These advances have clearly been linked to the
development and use of chemical equilibrium
models and improvements in analytical techniques,
as both of these have provided ways to evaluate
the forms of the metal species that are present.
Here, as an introduction to the results to be
presented subsequently, some of the key advances
that have taken place in this regard are discussed.
A somewhat more detailed synopsis of these
important early developments is presented elsewhere in this issue (Paquin et al., 2002), while
Campbell (1995) offers the interested reader a
much more detailed and comprehensive review of
this subject.
Zitko et al. (1973) reported one of the earliest
demonstrations of the mitigating effect of organic
matter on the toxicity of metals to fish and of the
importance of the free metal ion rather than the
total dissolved metal in assessing the potential for
effects. Zitko (1976) also showed that competition
of the hardness cations with the free metal ion, for
binding at the site of action of toxicity, also
mitigated toxicity. During this same time period
Pagenkopf et al. (1974) provided an early example
of the utility of chemical equilibrium modeling as
a way to explain the effect of water chemistry on
metal availability and toxicity to aquatic life.
Numerous investigators extended these early
results to further elucidate how water chemistry
affects metal toxicity (e.g. Sunda and Guillard,
1976; Sunda and Lewis, 1978; Anderson and
Morel, 1978; Sunda et al., 1978; Sunda and Gillespie, 1979; Allen et al., 1980; LeBlanc et al.,
1984), and it was experiments such as these that
served as the foundation for Morel’s elegant
description of the free ion activity model (FIAM)
(Morel, 1983). Of particular relevance to the
investigations herein, Morel suggested that the
degree of effect would be directly related to the
concentration of the reactive metal species (the
free metal ion and possibly others) that interact at
the site of action of toxicity. It will be seen that
this concept has been incorporated in the toxicity
model to be presented.
Although somewhat less well known than
FIAM, the gill site interaction model (GSIM) of
metal toxicity was proposed by Pagenkopf (1983)
at about the same time that Morel first described
FIAM. In contrast to Morel’s description of FIAM,
which was somewhat conceptual in nature, Pagenkopf actually used the GSIM, also a chemical
equilibrium-based approach, to interpret toxicity
data and to account for the effects of both inorganic complexation and competing cations on
metal toxicity. This was done for both individual
metals and for metal mixtures.
While these early models were of great value in
providing a technically sound basis for establishing
meaningful effect levels for metals, they were
never embraced by regulatory agencies as a way
to develop improved WQC. The reasons for this
are not entirely obvious. However, it may have
been due, at least in part, to the perceived complexity of the underlying chemistry models. They
were viewed by some as being too complicated,
too conceptually abstract, to be applied by someone who had not received formal training in this
developing area of expertise.
It was nearly 10 years later when Playle et al.
demonstrated that cation competition and complexation did in fact reduce metal interaction at the
site of action of toxicity. They measured the degree
to which these protective mechanisms actually
reduce metal accumulation at the fish gill, the
proximate site of action of toxicity for a variety
of metals (i.e. for Cu, Cd and Ag; see Playle et
al., 1992, 1993a; Janes and Playle, 1995). Further,
they used these measurements, to calibrate a chemical equilibrium model that could then be used to
predict gill metal accumulation over a range of
water chemistry characteristics (Playle et al.,
1993b; Janes and Playle, 1995). The demonstration
of this capability was an important advance,
because it is the degree of metal accumulation at
the site of action of toxicity that was believed to
P.R. Paquin et al. / Comparative Biochemistry and Physiology Part C 133 (2002) 305–343
307
Fig. 1. Simplified representation showing the relationship between the BLM for silver (left side) and the SBM for a freshwater fish
(right side). The biotic ligand is the point of intersection of these models. In addition to considering the effect of water chemistry on
metal accumulation at the biotic ligand, the SBM also considers other effects of water chemistry on branchial ionoregulation, the
circulatory system and other fluid compartments of the fish, and the overall rates of uptake and loss of sodium from the fish.
be the most direct and meaningful indication of
the degree of exposure of the organism to the
metal, and of the potential for effects. Moreover,
these metal accumulation measurements, which
showed the mitigating effect of cation competition
and complexation on metal accumulation levels,
provided a tangible demonstration of what had
previously been viewed as an intriguing if not
readily observable phenomenon.
An important detail that remained to be figured
out, and one that needed to be addressed if these
models were ultimately be of use to regulatory
agencies, was how to relate the level of metal
accumulation at the site of action of toxicity to an
effect. This had been discussed in the original
description of FIAM by Morel (1983), but a
quantitative link between level of accumulation
and effect was not offered. It would also be useful
if the results could be expressed in terms of the
dissolved metal concentration (including the free
metal ion plus organic and inorganic metal complexes), rather than free ion or gill metal concentrations, since this is the measurement that WQC
are based upon and it is typically made in conjunction with environmental monitoring programs.
These needs were recognized by academic and
industry scientists and by regulators alike (Bergman and Dorward-King, 1997). It was MacRae et
al. who first demonstrated a clear relationship
between metal accumulation level and effects,
showing that the degree of organism response,
rainbow trout mortality in this instance, was directly related to the level of accumulation at the site
of action of copper toxicity, the gill (MacRae,
1994; MacRae et al., 1999). Several models were
also proposed as a way to predict dissolved metal
effect levels over a range of water quality characteristics (Allen and Hansen, 1996; Erickson et al.,
1996). Subsequently, Di Toro et al. (USEPA, 1999;
Di Toro et al., 2000, 2001) proposed the biotic
ligand model (BLM) of the acute toxicity of
metals, a model which integrated several of the
previously described approaches into a unified
framework. The BLM provided a way to link
metal accumulation to effects, and at the same
time, it related this accumulation level to the
dissolved metal concentration as well.
The BLM is a chemical equilibrium modelbased framework in which three important subsets
of reactions are represented. These include reactions of the metal with the important organic,
inorganic and biotic ligands that are present (left
side of Fig. 1). With regard to the latter, the
binding sites at the site of action of toxicity, where
the metal interacts with the organism and exerts a
toxic effect, are represented as a ‘biotic ligand’,
and this is the basis for the model’s name. In the
case of fish, the gill is made up of a suite of
negatively charged proteins to which cations can
bind, and the biotic ligand represents a physiologically active subset of these gill sites. The BLM
of acute toxicity computes the metal accumulation
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P.R. Paquin et al. / Comparative Biochemistry and Physiology Part C 133 (2002) 305–343
level associated with the biotic ligand, under specified water chemistry characteristics, and it is the
dissolved metal concentration in the water that is
associated with the metal:biotic ligand lethal accumulation level at 50% mortality (i.e. the LA50)
that is the predicted dissolved metal LC50. The
LA50 is assumed to be constant, regardless of the
water quality characteristics (Meyer et al., 1999),
even though the LC50 may vary. The version of
the BLM employed herein is based on the Chemical Equilibrium in Soils and Solutions model,
CHESS (Santore and Driscoll, 1995), which
includes a standard set of metal–inorganic matter
reactions. It also incorporates the formulation for
metal–organic matter interactions that is represented in the Windermere Humic Aqueous Model,
WHAM, Model V (Tipping, 1994). The metal–
biotic ligand (Me:BL) interactions follow the
approach of Playle et al. (Playle et al., 1992,
1993a,b; Janes and Playle, 1995), who characterized silver:gill interactions over a range of water
chemistry conditions. The biotic ligand is represented as if it were a dissolved ligand, having a
characteristic binding site density and conditional
stability constants for each of the dissolved chemical species with which it reacts.
Paquin et al. described a silver BLM for acute
toxicity that was applied to both fish (rainbow
trout and fathead minnow) and invertebrates
(Paquin et al., 1999). McGeer et al. (2000),
using a version of the BLM that was based on
MINEQLq, one with a less complex representation
of metal–organic matter interactions, developed an
alternative BLM calibration for rainbow trout.
Their analysis emphasized the mechanistic underpinnings of the model. That is, they highlighted
the reason for the relationship between gill silver
accumulation and toxicity, the inhibition of branchial sodium- and potassium-activated adenosine
triphosphatase activity (Naq yKq-ATPase activity,
or NKA activity as used hereafter). This enzymatic
activity is required in order for the active uptake
of sodium and other ions by freshwater organisms
to proceed. NKA is primarily, but not entirely,
found in the mitochondria-rich chloride cells that
populate the gills of fish and the ionoregulatory
epithelia of other aquatic organisms, generally. It
is the interaction of silver and some other metals
with this enzymatic process that disrupts the ionoregulatory capabilities of aquatic organisms, an
effect that may have lethal consequences (Wood
et al., 1996; Morgan et al., 1997; Webb and Wood,
1998; Bury et al., 1999a,b; Wood et al., 1999).
McGeer et al. (2000) employed a previously evaluated ‘gill binding constant’ for Ag:NKA (Wood
et al., 1999). They also evaluated other binding
constants for important cationic-NKA reactions
(using Bury et al., 1999a,b; Galvez and Wood,
1997 data). They found that with these mechanistically-based estimates of binding constants they
were able to develop a model that predicted the
acute toxicity of silver to rainbow trout. Interestingly, the Ag–NKA binding constant they evaluated on this basis was similar in magnitude (within
a factor of 2) to the biotic ligand binding constant
that was previously evaluated by Paquin et al.
(1999) by calibration of the BLM to gill accumulation and toxicity data (log KAg–Gills7.3 vs.
7.6). This suggests that the use of toxicity data in
the direct calibration of the BLM is a reasonable
basis for model development. Given the impracticality of routinely measuring metal accumulation
at the biotic ligand, not only for rainbow trout, but
for much smaller invertebrates such as D. magna
as well, this was a fortuitous result. The BLM of
acute toxicity for silver, as described by Paquin et
al. (1999), is adopted for use herein.
It is now widely accepted that the site of action
of the acute toxicity of some metals (e.g. cadmium,
copper, silver, zinc and others), to freshwater fish,
is the gill. It is the binding of such metals to
physiologically active sites that interferes with the
essential ionoregulatory processes of the branchial
epithelium. The result is the impaired ability of
fish to regulate internal ion levels (e.g. McDonald
et al., 1989; Wood, 1992; Wood et al., 1996,
1999). Ionoregulatory disturbances were originally
shown to be the direct physiological cause of
acutely toxic effects that result from exposure to
acidic pH levels (Milligan and Wood, 1982;
McDonald, 1983a,b) and it is now known that
elevated levels of some metals, including copper,
silver and others have similar effects. With regard
to the effects of pH, copper and silver, the decrease
in levels of plasma sodium and of other ions that
results from these disturbances initiates a well
characterized cascading sequence of events that
ultimately causes cardiovascular collapse and death
(Milligan and Wood, 1982; McDonald, 1983b;
Wood, 1989 for effects of pH; also Wilson and
Taylor, 1993a; Taylor et al., 1996 for copper, Wood
et al., 1996; Hogstrand and Wood, 1998 for silver).
It has been found that, regardless of either the
P.R. Paquin et al. / Comparative Biochemistry and Physiology Part C 133 (2002) 305–343
specific stressor (pH, Ag or Cu) or the duration
of exposure, an approximate 30% decrease in
plasma sodium levels is associated with lethal
conditions for fish (McDonald et al., 1980; Wood,
1989; Wood et al., 1996; Webb and Wood, 1998;
Hogstrand and Wood, 1998; Grosell et al., 2000).
While it is recognized that death is not a result of
this loss of sodium alone, and that association of
a 30% decrease with death is at best an approximation, this depletion in plasma sodium levels
serves as a convenient end-point for modeling
purposes. It follows that if the degree of inhibition
of sodium uptake and the rate of plasma sodium
depletion that occurs in response to exposure to a
metal could be predicted, it should be possible to
predict the changes in plasma sodium over time
and hence the survival time of the organism.
Of course, the capability to predict plasma
sodium levels has not been required for purposes
of the numerous applications of the BLM that
have been described to date. The effect on plasma
sodium losses, or any other effect that contributes
to metal toxicity, is only implicitly represented in
the model. That is, as long as the effect is
associated with a fixed period of time, and the
corresponding biotic ligand accumulation level is
known for the exposure duration of interest (typically 96 h for fish or 48 h for invertebrates), it is
sufficient to predict the dissolved metal concentration associated with the LA50 value to predict the
LC50 value for that exposure duration. The initial
motivation for considering the kinetics of sodium
uptake and efflux of fish in further detail in regard
to the BLM was the desire to extend the applicability of the BLM framework, developed to predict
acute metal toxicity, to one that could provide a
quantitative framework for use in understanding
the mechanisms and dynamics of both shorter-term
pulse exposures and longer-term chronic exposures. The rationale was that if a fixed decrease in
plasma sodium (i.e. 30%) results in death after 96
h, then exposure to higher or lower levels of a
metal that affects sodium regulation would lead to
a similar effect, but over shorter or longer time
scales, respectively.
It was recognized that the development of a
truly predictive model of plasma sodium levels
would require a fairly detailed representation of
the important ionoregulatory processes. Fortunately, the scientific literature pertaining to ionoregulatory processes is extensive, dating back at least
as far as the pioneering work of Smith (1930),
309
Keys (1931), Keys and Wilmer (1932), Krogh
(1938, 1939), and others during the 1920s and
1930s, when the chloride cell was identified and
its role in ionoregulation was first recognized.
These early results were the first of many that
have shown the importance of the ambient water
chemistry, including pH and the concentrations of
2q
Naq, Cly, HCOy
, to the ionoregulatory
3 and Ca
needs and capabilities of aquatic life. While it is
not possible to review herein all of the important
contributions that have been made in this area
since these early years, a brief review of some of
the highlights is provided elsewhere in this volume
(Paquin et al., 2002). Here, attention will focus on
more contemporary results that have a direct bearing on the sodium balance model (SBM) framework
described
herein,
an
ion-specific
implementation of a more generic ion balance
model (IBM) framework. The SBM structure and
formulation, including the manner in which it
makes use of the previously developed BLM, are
described next. While the SBM is a physiologically-based model, it will be seen that it differs from
conventional physiologically-based pharmacokinetic (PBPK) models, models which are typically
intended for use in simulating the internal translocation, distribution and ultimate disposition of
the stressor chemical. Rather, it is the internal
distribution of sodium, one of the important ions
that are affected by the metal stressor, that is
simulated. The model will be used to predict the
time course of plasma sodium levels and survival
times, from less than 1 h to more than 1 week, for
alternative conditions where rainbow trout are
exposed to silver. The analysis will show that in
the context of the SBM, the previously developed
BLM framework of acute metal toxicity may be
extended to different exposure durations, from
short duration pulse exposures to longer-term exposures of 1 week or more, with the potential for
applicability to longer-term chronic exposures as
well. It will be seen that, while the SBM and the
more general IBM approach have not yet achieved
the initial objective of providing a quantitative
framework for understanding chronic toxicity due
to metals, incorporation of further refinements into
the model framework may ultimately make it
suitable for use in this regard. At the same time,
the concluding discussion will show that there are
a number of other important areas of toxicological
and regulatory interest, including the prediction of
effects resulting from time variable exposure to
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P.R. Paquin et al. / Comparative Biochemistry and Physiology Part C 133 (2002) 305–343
metals, species sensitivity and others, where the
SBM may also be of practical utility. More generally, it is envisioned that the approach may also
have much broader utility, as the specialized application for sodium that is described herein is adapted for use in the context of the considerably more
generalized IBM framework, a framework that
would be of use in the study of a wide variety of
physiological and toxicological processes.
2. Description of the sodium balance model
framework
A fundamental premise of the BLM of acute
toxicity is that, regardless of the site-specific water
chemistry and the magnitude of the 96-h LC50,
which vary markedly with water chemistry, the
LC50 is associated with a fixed level of accumulation at the biotic ligand (i.e. the LA50 is constant). For example, the 96-h LA50 for rainbow
trout has been estimated to be 17 nmolAgygram
wet weight of gill (17 nmolygw; Paquin et al.,
1999), and when the predicted Ag accumulation
level equals this amount, the dissolved Ag concentration should correspond to the LC50, regardless
of the other characteristics of the exposure water.
It should be understood that, in the strictest sense,
the LA50 is not simply the total accumulation of
metal at the gill, but more specifically, it is
intended to be the metal associated with the
physiologically active sites that affect the processes
of interest, iono- and osmoregulation. Thus, measurement of gill metal accumulation does not necessarily provide a direct measure of the quantity
of interest, although they may be related, and
perhaps proportional to each other.
As indicated previously on the left side of Fig.
1, in the context of the BLM, Ca2q, Naq and
Hq are simply viewed as competing cations with
respect to the binding of silver at the biotic ligand.
However, in the context of the SBM, it is recognized that there are other more direct effects of
these cations on the organism itself, effects that
are important even in the absence of exposure to
a metal such as silver. In this regard, the subsequent discussion will focus on the interactions of
these cations at the gill, as they pertain to the
physiological status of the organism, including
both ionoregulatory and, to a lesser degree, osmoregulatory processes (Fig. 1). In fact, for purposes
of this description of the SBM, the BLM itself
will be described only briefly and the focus will
shift from the ‘chemistry-based side’ of the biotic
ligand, shown to the left, to the ‘physiology-based
side’ of the biotic ligand, shown to the right. This
is an area that has previously received only limited
attention in the context of the BLM. Specifically,
as its name implies, the SBM will consider a mass
balance of sodium around the organism itself. The
mass balance will provide a way to evaluate the
changes in sodium that occur over time in response
to the chemistry of the water, including the concentration of silver, the metal of interest herein.
Although it is expected that many of the conceptual ideas to be presented will generally apply not
only to fish, but to essentially all other forms of
aquatic life (Potts and Parry, 1964; Potts, 1994),
of particular interest here are rainbow trout
(Oncorhynchus mykiss).
The right side of Fig. 1 illustrates the principal
routes of uptake and loss of sodium in freshwater
fish generally and rainbow trout in particular. The
important fluxes include the energy-requiring
active sodium uptake or influx at the gill (Ji),
passive diffusive loss or efflux at the gill (Je), and
renal excretion (Jr), urinary losses associated with
the filtration of blood by the kidney. Although
these renal losses are of relatively minor importance in the overall sodium balance, representing
on the order of 10% or less of the uptake rate of
sodium at the gill (Wood, 1989; Curtis and Wood,
1991; Wood, 1992), they are of sufficient magnitude to be included in the model. Similar conclusions have been drawn for some invertebrates as
well. At the same time, inclusion of renal losses
serves to maintain a more general modeling framework for analysis purposes. Although other sources
and sinks of sodium could readily be incorporated
into the analysis, including uptake from drinking
water (important in marine fish), transfer across
the skin and dietary intake, they will be neglected
for purposes of the analyses to be presented herein.
With regard to the dietary source, while not important in short-term acute toxicity studies where the
fish are not fed, such as the studies to be analyzed
subsequently, it may in fact be important in longerterm chronic toxicity studies. The reason is that
dietary sodium intake may account for approximately 25% of the total sodium intake during
chronic exposures and during periods of ionoregulatory stress, fish may quite literally eat their
way out of trouble (D’Cruz and Wood, 1998).
P.R. Paquin et al. / Comparative Biochemistry and Physiology Part C 133 (2002) 305–343
2.1. Effect of water chemistry on ionoregulation
The mechanisms of uptake and efflux that affect
the whole body transfer of ions, especially transfers
at the gill, have been studied extensively and will
not be gone into in detail here (see Hoar and
Randall, 1984; Wood and Shuttleworth, 1995, for
detailed descriptions). Rather, we will focus on
the principal factors that affect the more limited
subject of the sodium balance for fish. A fundamental underlying principle in this regard is that
under normal, long-term average conditions, when
the ambient water quality characteristics are relatively uniform over time, the rates of active sodium
uptake and the sum of passive diffusion losses
plus renal losses of sodium are in balance. The
result is that the overall net uptake rate of sodium
by the fish is approximately zero and a nearly
constant plasma sodium level is maintained.
Three of the cations that are included in various
versions of the BLM as competing cations, ones
which reduce metal availability to the organism by
competing with it for binding at the site of action
of toxicity, are Hq, Ca2q and Naq. Although not
the only ions of importance with regard to ionoregulation by aquatic life, generally, these same
three cations are also of significant physiological
importance to aquatic life with regard to Naq
regulation. It is for this reason that they need to
be considered in the context of the SBM. Additionally, it is also necessary to understand the
effect of the metal stressor itself, how it relates to
the uptake and efflux of sodium to complete the
description. While it will not be possible here to
outline all that is known in regard to these interactions, the essence of these interactions as they
are currently incorporated in the SBM will be
described.
2.1.1. Direct effects of pH on ionoregulation
The pH of the ambient water, while not one of
the controlling variables with regard to the datasets
to be presented subsequently, is still important in
a more general sense and so it will be discussed
briefly here in regard to how it affects sodium
transport. The balance of sodium is affected by
pH in several ways. First, in a process that remains
somewhat controversial among scientists today, it
is commonly believed that Naq is taken up by
aquatic organisms in exchange for Hq (alternatively or along with NHq
4 as well) via a mechanism that is often referred to as the ‘proton-pump’
311
hypothesis (Krogh, 1938; Kirschner, 1979; Potts,
1994). This process allows the organism to maintain acidybase homeostasis in its internal fluids
and to satisfy the requirement of electro-neutrality.
As a consequence of the fact that this exchange
occurs, the pH of the external water (i.e. the
external concentration of Hq) will affect the diffusion gradient of Hq between the ambient water
and the blood. This is expected to have a significant effect on the magnitude of the Hq efflux, and
hence the Naq influx, to which it is tied. (It is
noteworthy to consider in this regard that Kirschner (1988), working with isolated frog skin,
has shown that the apparent saturation of Naq
influx described subsequently is caused by the
limiting efflux of the Hq counterion.) A second
important effect of pH is that acidic pH conditions
can also lead to an increase in gill permeability or
leakiness, thereby increasing diffusive losses of
sodium and other ions from the gill (Milligan and
Wood, 1982; McDonald, 1983a,b). Because pH
levels in the tests to be considered were circumneutral and relatively constant, neither of these
interactions will be considered further. However,
they should be recognized as being of potential
importance in some situations, considered at least
in a qualitative sense when attempting to interpret
experimental data, and as being areas where future
model development refinements would be of use.
Given the present limitations in understanding of
the precise mechanism of how this occurs, the
details of how to formulate this process remain to
be worked out (Potts, 1994; Perry, 1997). Finally,
Playle and Wood (1989a,b, 1991) in working with
aluminum, have demonstrated the importance of
considering the shift in pH of the inspired water,
which occurs in the gill boundary, on Al speciation
in the gill micro-environment. This effect on pH
may also warrant further refinement in future
implementations of the BLM and related models.
2.1.2. Direct effects of calcium on ionoregulation
As in the case of Hq, the calcium ion, Ca2q, is
also included in the BLM as a cation that competes
with the trace metal of concern for binding at the
biotic ligand. However, Ca2q also has another,
more direct effect on the physiology of the fish.
Specifically, it has a direct effect on the ionic
permeability of the gill, that is, on the leakiness
of the gill in regard to the diffusive transfer of
ions. Simply, the paracellular junctions at the gill
are composed of a calcareous material, and it is
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P.R. Paquin et al. / Comparative Biochemistry and Physiology Part C 133 (2002) 305–343
Fig. 2. An example of the sodium uptake kinetics for rainbow trout and the manner in which sodium uptake is inhibited by silver (data
from Morgan et al., 1997). Note how JM, the maximum uptake rate, is inhibited, rather than KM, the half saturation constant.
the tightness of these junctions, a characteristic
that controls the rate of diffusive transfer of neutral
species and charged ionic species through them,
that is affected by the concentration of Ca2q in
the external water. This in turn has a direct effect
on the rate of loss of ions such as sodium by fish
(i.e. it has an effect on Je). The effect of Ca2q on
gill permeability will therefore be considered in
the analyses below.
2.1.3. Direct effects of sodium on ionoregulation
Finally, and perhaps most importantly, the concentration of sodium in the external water needs
to be considered. As with Hq and Ca2q, Naq has
previously been considered in the BLM with
regard to cationic competition between it and the
ionic form of the metal of interest for binding at
the biotic ligand. Hence the more sodium that is
present, the lower the degree of interaction of the
metal at the biotic ligand, and the level of toxicity
is thereby reduced. However, even in the absence
of the metal being present, the concentration of
sodium in the external water is known to have a
direct effect on the ability of the organism to take
up and regulate internal sodium levels. This effect
of sodium is illustrated quite clearly by the data
of Fig. 2 (Morgan et al., 1997). As shown here
by the filled dots and upper solid curve, the uptake
of sodium from the external water conforms to a
Michaelis–Menten relationship (Michaelis and
Menten, 1913):
JisJMwCwyŽCwqKM.x
(1)
where Ji is the sodium influx rate, adjusted for the
concentration of sodium, Cw, in the ambient water,
JM is the maximum sodium uptake rate and KM is
the half saturation concentration for sodium uptake
(the concentration of sodium in the external water
where the uptake is 50% of JM). The analysis of
these data yielded values of the Michaelis–Menten
kinetic parameters ("S.E.M.) of JMs14.7"2.90
mmolykg of fish wet weight per day (mmolykgw y
d) and KMs0.257"0.090 mM. Of particular interest with regard to these results is that, over a range
of representative naturally occurring sodium levels,
a decrease in the external sodium concentration is
associated with a decrease in the sodium uptake
rate. As an example, based on these data, rainbow
trout exposed to an external sodium concentration
of 0.50 mM will take up sodium at 8.4 mmoly
kgw yd. However, if the sodium in the external
water is decreased to approximately 0.15 mM, the
uptake rate will be reduced by about a factor of 2.
The resulting imbalance is similar in degree to that
P.R. Paquin et al. / Comparative Biochemistry and Physiology Part C 133 (2002) 305–343
which, if caused by a metal, could result in
significant adverse effects to the organism.
Although
internal
systemic
compensatory
responses would be stimulated by these conditions,
over the short-term at least, a fish that was subjected to these conditions would be placed at a
distinct ionoregulatory disadvantage at this reduced
sodium level, particularly if this happened in association with exposure to a metal that adversely
affects ionoregulation. This difference highlights
why it is important to consider the effect of the
concentration of sodium in the external water on
the Naq uptake process itself, not just the effect
of metal accumulation at the site of action of
toxicity on sodium uptake, or of the competitive
effect of Naq on accumulation of the metal at the
site of action.
2.1.4. Direct effects of metal concentration on
ionoregulation
The BLM of acute toxicity, as previously proposed for silver, copper, zinc and other metals,
provides a way to predict the dissolved metal
concentration that will be associated with a fixed
effect, such as lethality, given the water quality
characteristics for the site of interest. A fundamental premise of the BLM is that the metal accumulation at the site of action of toxicity that is
associated with the fixed effect is always the same.
Further, it is implicitly assumed that the rate at
which the damage to the organism accumulates,
and hence the time that is required for the resulting
effect to be manifested, is also fixed. That is, the
predictions are associated with a fixed exposure
duration. All that is required to predict an LC50
for a given set of water quality characteristics and
a fixed exposure duration is that the end-point of
interest be related to a fixed LA50. However, if
the objective is to evaluate the effect levels of a
metal for different exposure durations, or for a
situation where the metal concentration or other
water quality characteristics vary over time, in
both magnitude and duration, then a more fundamental representation of the underlying processes
is required. That is, it becomes necessary to understand and be able to define the details of the oneway ion fluxes. This is because the degree of the
impairment (e.g. the degree of inhibition of the
sodium uptake rate in the case of copper and
silver) will vary as the time for the end-point to
be manifested varies. What is required in this
instance is a way to evaluate the one-way fluxes
313
such that it is possible to keep track of the
cumulative damage to the organism.
As discussed previously, the lethality that results
from elevated levels of metals such as silver and
copper is related to, at least in part, the inhibition
of the sodium uptake process. The upper set of
data presented previously on Fig. 2, which showed
the effect of external sodium levels on sodium
uptake, are compared to a second set of results
obtained at 2 mgyl silver to illustrate how exposure
to silver interferes with the kinetics of this uptake
process (dashed curve, unfilled data points). As
shown, when 2 mgyl of silver is added to the
water for 48 h, the curve defining the sodium
uptake kinetics is reduced in magnitude to approximately 50% of the upper curve, which was
obtained in the absence of silver. Analysis of
these data yields a value of JMs9.55"3.02
mmolykgw yd that was significantly lower than the
value for the control, while the value of KMs
0.328"0.126 mM did not differ significantly from
the control (Morgan et al., 1997). The interpretation of these results by Morgan et al. was that the
addition of silver reduces the capacity, and hence
the maximum uptake rate, of the transport system,
but not the affinity of the carrier, for sodium. For
the example of Fig. 2, 2 mgyl of silver resulted in
approximately a 50% inhibition of JM. It is important to recognize that a decrease in JM is directly
reflected in Ji, which varies also with the sodium
concentration in the water, via Eq. (1), as this
relationship will be incorporated in the computations to be presented.
The inhibition of JM is understood to be related
to accumulation of silver at the biotic ligand, or
more specifically, its interaction with NKA.
Although the level of silver accumulation at the
fish gill is a measurable quantity, and while it may
be related to the level of accumulation at the actual
biotic ligand, a direct measurement of the latter
(i.e. the level of BL:Ag) is not readily made. This
is in part because the principal cells of the gill
that are involved in sodium transport, the mitochondria-rich chloride cells where much of the
NKA resides (most cells contain some NKA),
represent only a small fraction (-10%) of the
total number of gill cells (Perry, 1997). Silver may
bind to sites associated with any of these cells,
regardless of whether or not they are of physiological significance. In view of this, establishment of
a definitive relationship between the degree of
inhibition of sodium uptake (i.e. a decrease in Ji
314
P.R. Paquin et al. / Comparative Biochemistry and Physiology Part C 133 (2002) 305–343
at a given wNaqx occurs via a decrease in JM) and
the level of Ag–NKA accumulation is difficult to
achieve on the basis of analytical measurements.
Even so, the available evidence indicates that they
are related in a dose-dependent manner and that
this inhibition occurs rapidly yet is also reversible
(e.g. Morgan et al., 1997; Bury et al., 1999a;
Hussain et al., 1994). In view of these results the
inhibition of JM will be expressed in terms of a
sigmoidal dose–response relationship given by:
w(ln(BL:Ag)yln(EC50)) ybx
∂
JU
MsJMyµ1qe
(2)
Here, JM* is the inhibited maximum sodium
uptake rate and the EC50 (nmolygw) for sodium
uptake inhibition and b, the slope of the dose–
response, will be evaluated by calibration to plasma sodium time series data in conjunction with
the BLM-predicted BL:Ag (nmolygw) concentration that is associated with each of the experimental treatments. Note that the version of the Ag
BLM that was used to predict the BL:Ag concentrations in the analyses described herein (Paquin
et al., 1999) is in the process of being refined by
ongoing calibration efforts with recently obtained
data. As such, the emphasis here is directed to the
utility of the general approach and IBM framework
that are proposed, more than on use of a particular
version of the BLM or SBM that is employed
herein, as the latter are fully expected to continue
to evolve and improve over time.
2.2. Structure and formulation of the ion balance
model for sodium
The proposed model framework is viewed as
being generally applicable, with the incorporation
of appropriate modifications, to both fresh and
marine waters, and to both fish and invertebrates.
While these other applications would require the
inclusion of the appropriate source and sink terms
for sodium uptake (e.g. uptake within the gut and
representation of the gastro-intestinal tract as an
additional site of action of toxicity), and recognition that the diffusive fluxes and active transport
terms may reverse direction, the conceptual
approach should be valid. However, efforts to date
have focused on the development of a framework
for use with fish, rainbow trout in particular, in a
freshwater setting. The model is formulated in
terms of the controlling mass balance equations
for sodium about the fluid compartment volumes
that are represented. These differential equations
are solved numerically for the purpose of evaluating the effects of changes in relevant model
variables on the concentrations of the respective
internal sodium pools over time. This section
describes the model structure and the governing
equations. For ease of reference and comparison,
the notation and units that are used, as well as the
parameter values assigned in the modeling analyses of the three main datasets to be discussed, are
summarized in Table 1.
2.2.1. Representation of the internal fluid
compartments
Of interest is the regulation of levels of dissolved ions, sodium in particular, in the internal
fluid compartments of a fish. There are a number
of ways to configure these compartments and to
represent the exchanges that take place between
them (e.g. Nichols, 1987 describes six variations).
The conceptual representation employed herein
consists of four distinct fluid compartments (Fig.
3). The vascular system is represented in terms of
a primary and secondary system, consistent with
relatively recent observations of the vascular system of the glass catfish (Steffenson and Lomholt,
1992; Fig. 3a). Additionally, interstitial and intracellular fluid compartments are also considered,
consistent with the conventional manner in which
the fluid volumes in fish are reported (e.g. Holmes
and Donaldson, 1969; Olson, 1992). The structure
of these interacting fluid compartments and the
mass transfers of sodium that are considered in the
model are illustrated on Fig. 3b. The physiological
representation is as follows. The gill is the organ
that is primarily responsible for ionoregulation.
The branchial epithelium of the gill, consists of
relatively large chloride cells that control the active
uptake of sodium from the water. The paracellular
junctions between the cells of the gill are where
mass transfer of sodium by passive diffusion
occurs (i.e. net diffusive losses in fresh water and
net gains in salt water). Although somewhat of an
oversimplification, NKA is primarily located at
the basolateral or plasma side of the chloride cell,
and it is inhibition of NKA activity by silver that
leads to a decrease in the active uptake of sodium
from the water and an imbalance in whole body
sodium fluxes. This leads to a net rate of loss of
sodium from the fish and subsequent declines of
internal levels of sodium.
Fig. 3b illustrates how the gill is positioned in
relation to the principal fluid compartments of a
Table 1
Notation and parameter values used in IBM for sodium
Parameter symbol
Units
Indicator
dilution studies
Plasma Na
simulations
Survival time
simulations
Maximum Na uptake rate
Maximum Na uptake rate
adjusted for Ag inhibition of JM
0
NA
12.0
***
12.0
***
Ji
mmolykgw yd
Active Na uptake rate
sJM f NasJMw(Cw y(CwqKM)x
NA
***
***
KM
mM
Half saturation constant for
Na uptake at gill
w f NasCw y(CwqKM)x
0
0.040
0.050
Je
Jr
mmolykgw yd
mmolykgw yd
Passive Na gill efflux
Passive Na renal efflux
NA
NA
***
***
***
***
Primary intravascular fluid
volume, IVFV1
0.023
0.023
0.023
Fluid compartment volumes
lykgw
V1
lykgw
Secondary intravascular fluid
volume, IVFV2
0.048
0.048
0.048
VIS
VIC
VEC
VNa
lykgw
lykgw
lykgw
lykgw
Interstitial fluid volume, ISFV
Intracellular fluid volume, ICFV
Extracellular fluid volume, ECFV
Sodium space (sexchangeable
Na poolyC1)
0.099
Nil
0.170
NA
0.099
0.160
0.170
0.330
0.099
0.160
0.170
0.330
External water Na concentration
Na concentration initial condition,
Ci(ts0), in compartment i
0
(100%)
0.040
137–139
0.050
140
Inter-compartmental
Na concentration difference
Primary vascular system plasma
Na concentration
Secondary vascular system
plasma Na concentration
Interstitial fluid volume Na
concentration
Intracellular fluid volume Na
concentration
***
***
***
***
***
***
***
***
***
***
***
***
***
***
***
Fluid compartment sodium concentrations
Cw
mM
Cic
mM
CiyCj
mM
C1
mM
C2
mM
CIS
mM
CIC
mM
315
V2
P.R. Paquin et al. / Comparative Biochemistry and Physiology Part C 133 (2002) 305–343
Sodium uptake kinetic parameters
mmolykgw yd
JM
mmolykgw yd
JM*
Description
316
Table 1 (Continued)
Units
Description
Indicator
dilution studies
Plasma Na
simulations
Survival time
simulations
Permeability coefficients
PGo
PG
lykgwyd
lykgwyd
Gill permeability of control fish
Gill permeability of treatment
(exposed) fish, PGs f PGPGo
0.036
***
0.0388–0.0394
***
0.0386
***
f PG
–
NA
NA
***
A
–
NA
NA
3.09=10y4 (or 4.54)
B
–
NA
NA
2.05
C
–
Gill permeability factor;
f PGsawAgqxbwCa2qxc
Lead coefficient in expression for
f PG for Ag in mgyl (or mM) units
Exponent for wAgqxb in expression
for f PG, Agq (units depend on a)
Exponent for wCa2qxc in
expression for f PG, Ca2q in mM
NA
NA
y0.22
Pij
lykgwyd
P1,IS
lykgwyd
0.10
0.10
0.10
P2,IS
lykgwyd
0.10
0.10
0.10
PIS,IC
lykgwyd
0
0.10
0.10
Pr
lykgwyd
NA
a
a
Q12
lykgwyd
0.159
0.159
0.159
IPC
lykgwyd
Primary to secondary plasma
skimming flow rate
Inter-compartmental permeability
coefficient (i.e. Pi,j)
Dissolved silver in exposure
water
Biotic ligand silver, calculated
with the BLM
BL:Ag associated with the 50%
Slope of dose–response curve
for JM inhibitions f (BL:Ag)
effect level
0.0
;3.2
;100
NA
0–12
NA
NA
15.8
0.278
Ca tests: 30.9–32.1
Cl tests: 6.83–32.1
15.8
0.278
Sodium uptake inhibition dose–response parameters
Ag
mgyl
BL:Ag
nmolygw
EC50
b
nmolygw
Inter-compartmental permeability
coefficient for compartments i and j
Permeability between primary
vascular system and ISFV
Permeability between secondary
vascular system and ISFV
Permeability between ISFV
and ICFV
Renal loss rate permeability; set
to achieve Jrs10% of JIN
a, Set to achieve Jrs0.1Ji; ***, calculated by model; NA, not applicable.
P.R. Paquin et al. / Comparative Biochemistry and Physiology Part C 133 (2002) 305–343
Parameter symbol
P.R. Paquin et al. / Comparative Biochemistry and Physiology Part C 133 (2002) 305–343
317
Fig. 3. Representation of fluid compartments in the SBM. (a) Schematic diagram of a section of the arterial system, showing primary
and secondary arteries (adapted from Steffenson and Lomholt, 1992). This is the basis for the 2-compartment representation of the
intravascular fluid volumes (IVFV1 and IVFV2 , or V1 and V2 ) that is incorporated in the model. (b) Representation of fluid compartment
volumes in fish, including the IVFVs, the ISFV and the ICFV. The magnitude of the exchange of sodium between compartments i and
j (indicated by arrows) is defined by the product of the permeability, Pij and the inter-compartmental differences in concentrations, Ciy
Cj. The gill permeability is PG and the concentration of Naq in the water is Cw. (A complete summary of the notation and units is
provided in Table 1).
fish, as configured in the model. The ambient
water, which is in direct contact with the outer
surface of the branchial epithelium, is shown to
the left of the gill. The external water contains
Naq, Hq and Ca2q. Beyond the role that each of
these cations serves with regard to metal speciation
and accumulation at the biotic ligand, as represented in the BLM (Di Toro et al., 1999, 2001;
Paquin et al., 1999; McGeer et al., 2000; Santore
et al., 2001), they also exert more direct physiological effects upon the ionoregulatory capabilities
of the organism itself. As discussed previously,
Naq uptake is affected by the concentration of
Naq in the water via a Michaelis relationship,
while the sodium efflux is affected to a lesser
degree by the ambient sodium concentration via
its effect on the concentration gradient that sets
passive diffusion losses. Also, because Naq is
exchanged for Hq, to maintain electro-neutrality,
pH is also expected to affect Naq uptake as well.
Finally, since passive diffusion of Naq occurs via
the paracellular junctions of the gill, and Ca2q
affects the permeability of these junctions, Ca2q
has a direct effect on ionoregulation as well. Given
their effects upon ionoregulation then, it follows
that these constituents and the manner in which
they affect ionoregulatory processes should generally be considered in performing an ion balance
for an organism. Here, we will consider the effects
of Naq and Ca2q, but will neglect the effect of
pH, given that the data to be analyzed reflect
relatively constant pH levels over time and across
treatment levels.
The total body water of a typical fish is equal
to approximately 70% of its wet weight, or approximately 0.70 lykgw (700 mlykgw). As shown, this
water is distributed among the three principal fluid
compartments of interest, the intravascular fluid
volume (IVFV, consisting of a primary and secondary system), the interstitial fluid volume
(ISFV) and the intracellular fluid volume (ICFV).
IBM analyses of published datasets, to be present-
318
P.R. Paquin et al. / Comparative Biochemistry and Physiology Part C 133 (2002) 305–343
ed subsequently, have provided estimates of these
three fluid volumes of 71, 99 and 530 mlykgw of
the total body water, respectively. As the blood
flows through the gill, it is separated from the
external water by the branchial epithelium and,
upon leaving the gill and circulating through the
rest of the body, it is separated from the interstitial
fluid by the arterial wall. The interstitial fluid is
in turn separated from the intracellular fluid by
the plasma membrane. The blood is filtered by the
kidney (not shown) prior to returning to the gill.
The primary and secondary systems flow in parallel and are connected by capillary-sized vessels
called the arterial anastomoses (Vogel, 1985). The
flow of plasma passing through these vessels is
referred to as the plasma skimming flow rate, in
part because it removes very few red blood cells
from the primary system. This leads to a volume
fraction of RBCs, or hematocrit, of only approximately 1% in the secondary system, compared to
25% or more in the primary system.
With regard to sodium mass transfers, the model
is structured as follows. Transfer of sodium is
allowed to occur across each of the interfaces
mentioned above, the gill epithelium, the arterial
wall and the plasma membrane. As discussed
previously, the active uptake of sodium from the
water that occurs at the gill takes place primarily
via the chloride cells and conforms to Michaelis
kinetics. Passive loss of sodium from the primary
system occurs via diffusion across the paracellular
junctions of the gill, from the higher plasma
sodium concentration, C1, to the lower ambient
freshwater sodium concentration, Cw (the transfer
is in the reverse direction in salt water). The most
general form of the model includes a transfer of
sodium between the primary and secondary arterial
systems at a rate corresponding to the plasma
skimming flow rate (Q12), between each of these
plasma volumes (V1 and V2) and the ISFV (VIS),
and between the ISFV and the ICFV (VIC). The
sodium concentrations in the ISFV and ICFV are
CIS and CIC, respectively. Finally, loss of sodium
may also occur via renal excretion as blood in the
primary system is filtered by the kidney (not
shown), prior to its return to the gill. The main
differences between this representation and the 2pool model presented by Nichols (1987) is that
here, losses occur from the primary compartment
of a 2-compartment plasma system, rather than
from the interstitial fluid, and also, the IBM
includes an intracellular fluid compartment.
2.2.2. Model formulation
The model is described in terms of the differential equations that govern the mass balance of
sodium about each of the four internal fluid compartments. The equation for each compartment
includes terms for the relevant mass transfers of
sodium described above. The formulation proceeds
as follows, beginning with the primary system:
Rate of change of mass of Na in V1
sV1dC1ydtsJiyJe"J12"J1,ISyJr
(3)
where Ji and Je are the sodium influx and efflux
rates, respectively, J12 is the rate of sodium mass
transfer between the primary and secondary systems, J1,IS the rate between the primary system
and ISFV, and Jr represents renal excretion. Note
that the units for volume (V1 in this equation), in
this and in subsequent equations, are liters fluid
per unit whole body wet weight, such that the
units of each term are mmol Naykgw yd. Expressing each of these mass transfers in terms of the
more fundamental model parameters:
Cw
yPGŽC1yCw.
CwqKM
qQ12ŽC2yC1.
qP1,ISŽCISyC1.yPrC1
U
V1dC1ydtsJM
(4)
The first term on the right represents the
Michaelis expression for the active uptake of
sodium from the external water, where JM* is the
maximum or carrier-saturated uptake rate (mmoly
kg wet weight of fishyday, or mmolykgw yd),
corrected for inhibition due to exposure to the
metal, KM is the half saturation concentration for
Naq uptake from water and Cw is the concentration
of Naq in the external water. Consistent concentration units are used throughout. The inhibited
maximum uptake rate, JM* is calculated from Eq.
(2), as described previously, where the EC50 and
b will be evaluated by calibration of the model to
plasma sodium time series data using the BLMpredicted BL:Ag concentrations for each of the
experimental treatment conditions. If warranted for
other metals such as copper, KM could be modified
as well, though this would require a more complicated model calibration procedure.
The second term of Eq. (4) represents the
diffusive exchange of sodium between the blood
and the ambient water. This exchange is proportional to the product of a gill permeability coefficient, PG (lykgw yd) and the difference in the
P.R. Paquin et al. / Comparative Biochemistry and Physiology Part C 133 (2002) 305–343
concentrations of sodium between the primary
plasma volume and the ambient water, C1yCw.
The value of the gill permeability coefficient is
adjusted to account for the effect of calcium and
free silver in the external water as follows:
PGsfPGPGo
(5)
where PGo is the baseline (i.e. pre-exposure) gill
permeability and f PG is a gill permeability adjustment factor. The latter, f PG, modifies the baseline
gill permeability to account for the adverse effect
of high free silver levels on gill permeability, as
well as the protective effect of Ca2q under these
same conditions of elevated concentrations of free
silver. PGo is evaluated by assuming that plasma
sodium levels should be in approximate equilibrium with the uptake and loss rates during preexposure conditions. That is, Eq. (4) is evaluated
at steady state such that dC1 ydts0 and C1s
constant. It follows that C1sC2sCIS and, as a
result of this, that the third and fourth terms on
the right side of Eq. (4) are both equal to 0.
Finally, if renal losses are 10% of Ji then, by
difference, passive diffusion losses from the gill
will be 90% of Ji. Thus, under steady state conditions Eq. (4) simplifies to the following:
0.9Jis0.9JMwCwyŽKMqCw.xsPGoŽC1yCw.
(6)
It is emphasized that Eq. (6) applies to baseline,
pre-exposure equilibrium conditions. Solving for
PGo:
PGos0.9JMfNayŽC1yCw.
(7)
where
fNasCwyŽKMqCw.
(8)
It remains to assign values to JM and C1 and,
because all of the remaining variables on the right
side of Eq. (7) are known, the evaluation of PGo
is direct.
The gill permeability adjustment factor in Eq.
(5) is expressed as:
fPGsawAgqxbywCa2qxc
(9)
The form of this relationship is such that f PG
decreases as the free silver concentration, Agq,
decreases or as calcium increases for positive
values of b and c (i.e. c)0 with wCa2qx in
the denominator). That is, the permeability
(PGs f PGPGo) will decrease with increasing Ca2q
such that diffusive losses of Naq are also reduced
with increasing Ca2q. For the model application
319
described herein, a, b and c are evaluated on the
basis of the survival time test data to be analyzed
subsequently. As such, this expression is only
intended for use in the analyses presented herein
and is applicable when the free silver is greater
than approximately 35 mgyl, the estimated threshold for physical damage to the gill to occur. That
is, the relationship is intended to account for the
effect of exposure to very high experimental treatment levels of free silver (in the range of approximately 35–90 mgyl Agq), levels that could
potentially result in structural damage to the gill
and an overall marked increase in gill permeability.
As applied herein, Eq. (9) is not used to account
for changes in permeability at more representative,
much lower ambient environmental levels of silver
where physical damage to the gill is not expected
to occur.
Returning to Eq. (4), the third term represents
the volumetric exchange of plasma between the
primary and secondary systems via the plasma
skimming flow, Q12, with the mass transfer rate
proportional to the difference in concentrations,
C2yC1. As represented here, it has the same units
as the permeability coefficients (lykgw yd), with
the notation changed from P to Q to distinguish
between these two different processes (i.e. a diffusive flux vs. a volumetric flow or bulk fluid
exchange rate).
The fourth term in the mass balance of sodium
about the plasma volume represents the diffusive
exchange of sodium between the primary IVFV
and the ISFV. Again, as in the case of exchange
with the ambient water, this term is also represented as the product of a permeability coefficient,
P1,IS, times the difference in sodium concentration
between the interstitial fluid compartment and the
primary plasma fluid compartment, CISyC1. Here,
P1,IS is a calibration parameter and C1 and CIS are
computed by the model.
The remaining term on the right side of Eq. (4),
PrC1, represents renal losses of sodium. Renal
filtration controls the magnitude of the loss of
sodium by urinary excretion, a complex process.
The manner in which exposure to metals affects
kidney function is not readily defined. Hence, this
process will not be characterized in detail in the
context of the model to be presented. Rather, for
the analyses to be presented herein, the term for
the overall loss or sodium via renal excretion will
be represented quite simply as the product of a
permeability coefficient times the primary system
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P.R. Paquin et al. / Comparative Biochemistry and Physiology Part C 133 (2002) 305–343
plasma sodium concentration. This approach
should be sufficient, given that renal losses are
typically low in comparison to diffusive losses of
sodium at the gill. Renal losses are not measured
in most toxicity studies. Thus, in the absence of
more detailed information about the magnitude of
renal losses, the renal permeability coefficient, Pr,
will be set to result in renal losses of 10% of the
pre-exposure gill sodium influx (i.e. 10% of Ji as
calculated with Eq. (1)), for the analyses to be
presented herein. Finally, while the model includes
the capability to reduce renal losses with decreasing C1, this option has not been invoked for the
analyses to be described.
Although mass balance equations are also
required for the remaining fluid compartments,
they are relatively simple in form. The mass
balance equation for the secondary vascular system
is as follows:
V2dC2ydtsyQ12ŽC2yC1.qP2,ISŽCISyC2.
(10)
The first term is opposite in sign to the corresponding term for the primary system and is
simply the plasma skimming exchange term
between the primary and secondary systems, while
the second term represents diffusive exchange
between the secondary system and the ISFV. Next,
for the interstitial fluid compartment:
VISdCISydtsyP1,ISŽCISyC1.
yP2,ISŽCISyC2.
qPIS,ICŽCICyCIS.
(11)
As shown, the sodium mass balance about the
interstitial compartment, VIS, is controlled by the
relative magnitudes of the diffusive exchanges of
sodium between it and both of the intravascular
compartments, V1 and V2, as well as the intracellular compartment, VIC. The first and second terms
on the right side of Eq. (11), primary intravascularand secondary intravascular-interstitial sodium
exchange, are equal in magnitude and opposite in
sign, to the corresponding terms of Eqs. (4) and
(10), respectively (i.e. a gain of sodium by one of
these compartments is a loss by the other). The
third
term, interstitial-intracellular sodium
exchange, is similarly represented as the product
of a permeability coefficient, PIS,IC, times the
effective sodium concentration difference between
these two compartments, CICyCIS.
Finally, the sodium mass balance in the intracellular compartment, VIC, is controlled by the
magnitude of the diffusive exchange of sodium
between it and the interstitial compartment, VIS.
Again, the exchange term is of the same form as
in mass balance Eq. (11) for VIS, but opposite in
sign.
VICdCICydtsyPIS,ICŽCICyCIS.
(12)
Note that it is assumed for modeling purposes
that the magnitudes of the net diffusive fluxes
between the water and the plasma, and between
the other fluid volumes as well, are proportional
to the differences in concentration between the
respective volumes, and that concentrations of
sodium are uniform throughout the organism under
equilibrium conditions. The latter assumption is
clearly an oversimplification, as the compartmental
concentrations of sodium are not actually uniform
under normal homeostatic conditions (Krogh,
1939; Holmes and Donaldson, 1969). The requisite
ionic balances are maintained in the presence of
these concentration differences by the establishment of a Donnan equilibrium condition that
depends not only upon the sodium concentrations,
but the concentrations of the other organic and
inorganic constituents in the internal fluids as well
(Krogh, 1939; Potts and Parry, 1964; Potts, 1984).
However, as a practical matter, the assumption of
uniformity in sodium concentration under equilibrium conditions is a simplification that provides
an expedient representation of what would otherwise be an intractable situation, while use of the
sodium space as the total fluid volume ensures
that the size of the exchangeable sodium pool will
be reasonable. At the same time it will be seen
that this representation provides an adequate first
approximation that is suitable for preliminary
assessment purposes. All that remains then is to
numerically integrate the controlling differential
equations (Eqs. (4), (10)–(12)) and solve for the
compartmental sodium concentrations over time.
3. Model application and results
When fish are exposed to elevated levels of
silver, an immediate result is the disruption of
their ability to regulate internal levels of sodium.
When this occurs, there is an imbalance in the
rates of uptake and efflux of sodium, resulting in
a net rate of loss of plasma sodium. This is an
important physiological response, as a cumulative
loss of plasma sodium of approximately 30% has
been associated with lethality (McDonald, et al.,
1980; Wood, 1989; Wood et al., 1996; Webb and
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Wood, 1998; Grosell et al., 2000). Further, the
higher the rate of loss of sodium, the sooner it
will be for this critical level to be achieved, and
the shorter the survival time. The objective of the
model then is to predict the levels of sodium in
the individual fluid compartments over time, keeping track of primary system plasma sodium levels
until such time as a 30% loss occurs, this time
being the predicted survival time.
To apply the model, it is necessary to first
evaluate the volumes of the fluid compartments of
interest, the rates of exchange between these compartments, and the size of the total exchangeable
sodium pool that serves as a buffer for sodium
losses from the considerably smaller plasma sodium pool in the primary vascular system. The model
is calibrated by relating the degree of inhibition of
sodium uptake to the predicted biotic ligand silver
concentration, such that the predicted decreases in
plasma sodium levels are consistent with measured
results. At that point it is suitable for use in
simulating plasma sodium levels over time, and
given the critical plasma sodium level associated
with lethality, predicting survival time.
3.1. Analysis of fluid compartment volumes
The first step then is to evaluate the fluid
compartment volumes. While much information is
available in this regard, the results tend to vary
with the method of measurement. Holmes and
Donaldson (1969) provide a comprehensive but
somewhat early review of methods of measurements and results, while Olson (1992) provides a
more recent and updated review, one which focuses
more on the vascular system. The whole body
fluid volume is readily determined from whole
body wet and dry weight measurements, and is
typically in the range of 70–75% of the whole
body wet weight (i.e. 0.70–0.75 lykg wet weight,
or lykgw), for most fish. With regard to the
volumes of the individual compartments, the measurement method in most common use is the indicator dilution technique. This method involves use
of any of a number of different tracers, with each
having its own distinct advantages and disadvantages. Use of the indicator dilution technique to
estimate volumes of the individual compartments
simply involves the injection of a known volume
and concentration of a tracer into the blood,
subsequent sampling to determine the resulting
concentration, and calculation of the relevant vol-
321
ume of interest by a simple dilution calculation.
Because some tracers remain in the vascular system (e.g. radiolabeled red blood cells or Evans
blue dye) while others are considered to diffuse
throughout the extracellular fluid compartment
(e.g. inulin), use of an appropriate tracer provides
a way to estimate the volume of either of these
compartments. The ICFV may be determined by
the difference between whole body water and the
ECFV.
The disadvantage of the preceding approach is
that the concentrations of the tracer in the blood
will change over time, as exchange with the
interstitial fluid occurs gradually, rather than
instantaneously. Hence, the time of sampling
becomes an important consideration, with decreasing plasma concentrations measured with increasing time, thereby leading to increasing estimates
of apparent dilution and fluid volume over time.
This problem accounts for much of the variation
in reported fluid compartment volumes (Steffenson
and Lomholt, 1992). A kinetic modeling approach
will therefore be used to overcome this difficulty.
That is, the SBM equations described previously,
with active uptake set to zero, will be calibrated
to time series data of plasma tracer concentrations.
The data to be analyzed are from two studies with
rainbow trout. The first set of data was previously
analyzed by Nichols (1987), using a variety of
one, two and three fluid compartment representations, leading in one case to estimates of the blood
volume of 0.042 lykgw and of the extracellular
fluid volume of approximately 0.17 lykgw. The
second set of data was reported and analyzed by
Steffenson and Lomholt (1992), using equations
representing a 2-compartment vascular system,
with primary and secondary volumes of 0.023 and
0.048 lykgw.
Results of the kinetic analyses of the two fluid
compartment tracer datasets that are considered
are summarized on Fig. 4. The originally reported
results that were in terms of concentration have
been normalized to the percentage of the initial
dose to facilitate making a comparison on a consistent scale. The filled triangles represent the
results of Nichols (1987) and the open squares the
results of Steffenson and Lomholt (1992). As
shown, either set of data may be reasonably well
reproduced with an independent set of parameter
values (upper and lower dashed lines). However,
because there is no clear basis for accounting for
the differences between these two sets of results,
322
P.R. Paquin et al. / Comparative Biochemistry and Physiology Part C 133 (2002) 305–343
Fig. 4. Analysis of rainbow trout plasma tracer data with the four-compartment model. The data are from two different studies (Nichols,
1987; Steffenson and Lomholt, 1992). Although the model may be fit to either set of data independently (dashed lines), a compromise
fit (solid line) is used to estimate fluid volumes to be used in subsequent simulations of sodium losses from rainbow trout (V1s0.023
lykg, V2s0.048 lykg, VISs0.099 lykg, PGs0.036 lykgwyd, P1,ISsP2,ISs0.08 lykgwyd, Q12s0.159 lykgwyd).
an intermediate fit of the data has been adopted.
Hence the computational results corresponding to
the solid line are used to fit the pooled data. Model
parameter values used to achieve these results are
as follows: V1s0.023 lykgw, V2s0.048 lykgw,
VISs0.099 lykgw, Q12s0.159 lykgw yd, P1,ISs
P2,ISs0.10 lykgw yd and PGs0.036 lykgw yd. Note
that the estimated volumes of the primary and
secondary vascular system compartments have
been assigned to be consistent with the estimates
made by Steffenson and Lomholt while the extracellular fluid volume corresponds to the estimate
made by Nichols (0.17 lykgw). The non-zero gill
permeability reflects an overall loss of the tracer
from the primary system. The loss rate has been
applied to the primary system only, consistent with
the manner in which the SBM is formulated, but
in contrast to the approach of Steffenson and
Lomholt, who applied a loss rate to both the
primary and secondary systems. Because the time
scale of this study was approximately 24 h, and
the expectation was that the tracers would not
move into the ICFV, at least over this time scale,
transfer into this compartment was neglected for
the purpose of fitting these data. While it is
acknowledged that this analysis does not lead to
the determination of a unique set of model param-
eter values that will fit these data, the results do
provide a reasonable overall representation of the
data. Similar studies, if carried out in the future,
could reduce the number of degrees of freedom in
this type of analysis if determinations were made
of the loss of the tracer to the water during the
test and of the residual whole body tracer level at
the end of the test.
It remains to determine the ICFV. Initially, the
whole body fluid volume for rainbow trout was
set equal to 70% (700 mlykg wet weight), consistent with much of the data that have been reported
(Holmes and Donaldson, 1969), and the ICFV
determined by difference. However, this approach
leads to an unreasonably high value for the
exchangeable sodium pool. That is, if the plasma
sodium concentration is assumed to be 150 mM,
and it is assumed to be uniform throughout the
internal fluid compartments, then the exchangeable
sodium pool is 105 mmolykgw (150 mMyl=0.70
lykgw). This may be compared to estimates of
exchangeable sodium that are more typically in
the range of 40–50 mmolykgw (Wood and Randall, 1973; Wood and McDonald, 1982; Wood,
1992). The main reason for this discrepancy is
likely to be that the intracellular sodium levels,
which are associated with a large percentage of
P.R. Paquin et al. / Comparative Biochemistry and Physiology Part C 133 (2002) 305–343
whole body fluids, are known to be significantly
less than the plasma sodium levels (Olson, 1992),
with the gradient maintained by a Donnan equilibrium condition. An alternative approach is therefore followed to overcome this inconsistency. It is
assumed that the sodium space, VNa, corresponds
to the exchangeable sodium pool divided by the
plasma sodium concentration: 50 mmolykgw y150
mMyls0.33 lykgw. (The sodium space is the fluid
volume that would be associated with the
exchangeable sodium pool of 50 mmolykgw if the
sodium contained in this volume was uniformly
distributed at a concentration equal to that of the
plasma sodium concentration.) The difference
between this estimate of the sodium space and the
ECFV that was determined from the kinetic analyses described above (VECsV1qV2qVISs0.17 ly
kgw) is assigned to an effective interacting ICFV
(i.e. VICsVNayVECs0.33y0.17s0.16 lykgw).
The volume of the sodium space used here is
consistent with estimates of the radiosodium space
of 0.34 lykgw made by Wood and Randall (1973).
While the interpretation of the ECFV used above
is consistent with that of Nichols (1987), the
interpretation that the difference is associated with
the intracellular compartment is inconsistent with
the interpretation of Wood and Randall (1973).
An alternative interpretation is that the exchangeable sodium pool (0.33 lykgw) represents the
sodium associated with the extracellular fluid volume in its entirety. In this case, 0.17 lykgw would
correspond to the more readily exchangeable, richly perfused tissues (a fast pool) and the remainder
of 0.16 lykgw would be associated with the extracellular fluid in the less accessible, less highly
perfused tissues (a slow pool). The equations and
computational approach are independent of the
physiological interpretation that is preferred.
3.2. Analysis of plasma sodium data
While the preceding estimates of the fluid compartment volumes are not considered to be definitive, the important consideration is whether or not
this representation can serve as a reasonable basis
for predicting the kinetics of plasma sodium losses
over time. As a first test of this capability, the
model will be applied to a dataset where the
rainbow trout were exposed to 3.2 mgyl of silver,
while chloride was varied, and plasma sodium
levels of the fish were monitored over the ensuing
48 h (McGeer and Wood, 1998). The variation of
323
chloride levels is important, as chloride forms
silver chloro-complexes, primarily AgCl, and this
form of silver has been shown to markedly reduce
the bioavailability of silver to rainbow trout (Bury
et al., 1999a,b). In the context of the silver BLM,
at a fixed dissolved silver concentration, when the
chloride concentration is low, silver availability is
high, and the predicted BL:Ag will be high. Then,
as the chloride level increases, silver availability
decreases, resulting in a decrease in BL:Ag. Recall
it is a premise of the SBM that the response by
the organism to exposure to silver, in this case the
inhibition of the active uptake of sodium from the
water, will be directly related to the concentration
of BL:Ag. Hence the degree of response by the
fish should reflect this change in BL:Ag. What is
required then is to establish this relationship that
is expressed in the form of Eq. (2). This analysis
is summarized next.
The equations presented previously that describe
the sodium balance of a freshwater fish will be
solved numerically to simulate the plasma sodium
results. To do so, it is necessary to assign values
to a number of model inputs. The values of these
inputs are listed in Table 1 under the heading
‘Plasma sodium simulations’. First, the Michaelis
parameters that define active sodium uptake kinetics are required. Initial assignments were JMs0.5
mmolykgw yhs12 mmolykgw yd and KMs0.04
mM for sodium. The value for JM is a typical
value for rainbow trout, and is consistent with the
uninhibited sodium uptake curve shown previously
on Fig. 2. The half saturation constant is not
readily defined, a priori, but it is known that it
will vary with acclimation conditions. McDonald
and Rogano (1986) present results which indicate,
qualitatively at least, that the KM for sodium and
chloride will vary in rough accordance with the
Na and Cl concentration of the acclimation water,
such that the basal ion-transport rate is maintained
(i.e. for JM constant, if KMsCw, then Ji is always
50% of JM). Bury et al. (1999a) also provide data
to indicate this is a reasonable first approximation.
The sodium KM was therefore set equal to the
sodium concentration of the acclimation water,
0.04 mM, which is the same concentration as was
used in the toxicity tests to be analyzed. Next,
recalling that the overall balance of sodium
includes renal losses, the parameter controlling this
process was set to achieve a loss 10% of the
uninhibited sodium influx rate, a representative
value (Wood, 1989; Curtis and Wood, 1991;
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P.R. Paquin et al. / Comparative Biochemistry and Physiology Part C 133 (2002) 305–343
Fig. 5. Plasma sodium time series data (" standard error) are shown for rainbow trout control fish (Ags0) and fish exposed to 3.2
mgyl of dissolved Ag, as Cly varies (data: McGeer and Wood, 1998). Results are shown for (a) control fish, Cly s0.014 mM, BL:Ags
0 and Ags0, followed in order of decreasing chloride and increasing predicted biotic ligand silver: (b) Clys1.44 mM, BL:Ags3.4
nmolygw; (c) Clys0.538 mM, BL:Ags6.4 nmolygw; (d) Cly s0.292 mM, BL:Ags8.3 nmolygw ; (e) Clys0.115 mM, BL:Ags
10.3 nmolygw; and (f) Clys0.014 mM, BL:Ags12 nmolygw . The upper horizontal solid reference line represents the presumed constant
sodium concentration in the absence of exposure to silver. The other four lines, in order of lowest to highest lines, show the predicted
sodium concentrations in the IVFV1 (the lowest solid line, to be compared to the plasma sodium data), IVFV2 , the ISFV and the ICFV.
Wood, 1992). Finally, it is necessary to define the
gill permeability, which is estimated by assuming
steady state applies under pre-toxicity test conditions, and evaluating PGo from Eq. (7) and PG
from Eq. (5), as described previously. (If JM and
C1 have not been measured, they would need to
be assigned on the basis of representative values.)
For the plasma sodium and survival time analyses
to be presented herein, it is assumed that JMs0.5
mmolykgw yhs12 mmolykgw yd; KMsCws0.04
or 0.05 mmolyl (such that f Nas0.5); Jrs10% of
Jis f NaJM (10% of pre-toxicity test sodium influx
rate). Based on these assumptions, it follows that
PGos0.0378 lykgw yd.
It remains to specify a relationship between the
degree of inhibition of the active uptake rate of
sodium, JM, and the BL:Ag concentration, as this
sets the magnitude of the term representing the
active uptake rate of sodium in Eq. (4). The
BL:Ag is first evaluated with the previously developed silver BLM (Paquin et al., 1999) with the
toxicity test water chemistry specified as inputs
for each of the treatments. The parameters of the
dose–response curve, the EC50 for uptake inhibition, and b, which characterizes the slope of the
response, are adjusted by calibration to the
observed response in plasma sodium data. The
results of the SBM simulation analysis are compared to the rainbow trout plasma sodium data on
Fig. 5 and the dose–response curve that is used to
achieve this fit of the plasma data is shown on
Fig. 6. The plasma sodium time series data
("standard error) are shown for the controls
(Ags0) on Fig. 5a. Some unexplained variability
P.R. Paquin et al. / Comparative Biochemistry and Physiology Part C 133 (2002) 305–343
325
Fig. 6. Does response curve for percent inhibition of JM as a function of BLM-predicted BL:Ag. Dose–response curve parameters of
EC50s15.8 nmolygw and bs0.278 are based on calibration of the 4-compartment SBM to the plasma sodium data of Fig. 5. Points
indicated along the curve correspond to the estimates of BLM-predicted BL:Ag for conditions of the three silver datasets analyzed with
the SBM: m, McGeer and Wood, 1998 (Fig. 5); e, Galvez and Wood, 1997, chloride treatments (Fig. 8), and q, Galvez and Wood,
1997, calcium treatments (Fig. 9; shown here as overlapping points at BL-Ag;30 nmolygw and ;95% inhibition; they also coincide
with some of the low chloride treatment results, e).
is evident, as control fish plasma sodium levels
would be expected to remain approximately constant over the 48-h test duration. These changes
are likely to be within the range of normal physiological variation, and may also reflect sampling
and analytical variability. With regard to the model
results, the solid line, the initial condition is set
equal to the average concentration over the test
duration, and it remains constant in time. This is
because the gill permeability was evaluated such
that the uptake and loss terms were in equilibrium,
and because the BL:Ags0, there is no inhibition
of sodium uptake for the control fish.
Fig. 5b through Fig. 5f present comparisons of
model results to the plasma sodium data for the
remaining 3.2 mgyl dissolved Ag treatments,
shown in order of decreasing levels of chloride,
from 1440 to 14 mM and increasing levels of
predicted BL:Ag (3.4–12 nmolygw; see caption
for values for each treatment). At the highest
chloride level (1440 mM; Fig. 5b), the predicted
BL:Ags3.4 nmolygw, resulting in less than 1%
uptake inhibition for the response curve of Fig. 6.
Thus, the decrease in plasma sodium concentration
relative to the initial condition (set to the average
of the initial and 1-h measurements) is negligible
over the 48-h test duration, well within the limits
of the measured plasma sodium levels. As chloride
levels are progressively decreased in the remaining
treatments (Fig. 5c–f), a clear pattern of increasingly severe plasma sodium losses (i.e. decreasing
plasma sodium concentration) is evident in the
data. Because the predicted BL:Ag also increases
with decreasing chloride levels, resulting in an
increasing degree of inhibition of sodium uptake,
the model results follow the same trend as the
data, with progressively higher losses of sodium
over time as chloride levels decrease. Note that
there are five lines, corresponding to predicted
concentrations in each of the four compartments
plus an initial condition reference line, are displayed on each panel, although the different lines
are only discernible on Fig. 5c–f. In each case,
the lowest solid line curve represents the predicted
primary system plasma sodium result, and is the
curve that should be compared to the data. The
next higher three curves, in order of the lowest to
the highest, show the predicted sodium results for
the secondary vascular system, the ISFV, and the
ICFV, respectively. (The upper horizontal line is
326
P.R. Paquin et al. / Comparative Biochemistry and Physiology Part C 133 (2002) 305–343
shown as a point of reference, indicating the initial
plasma sodium level that would persist in the
absence of any inhibition of active uptake.)
The fit of the plasma sodium data of Fig. 5 was
achieved by assigning the IPCs a value of 0.1
lykgw yd in all cases. As a general rule, the lower
line, representing the computed primary system
plasma sodium level, reproduces the measured
trends in plasma sodium quite well. Sodium levels
in the remaining compartments tend to track the
concentrations in the primary system rather closely
when the rate of decrease occurs slowly (Fig. 5c
and d), but lag progressively further behind as the
rate of loss increases (Fig. 5e and f). The reason
for this to occur, as accounted for in the context
of the SBM described here, is that the fluxes
between compartments limit the rate of exchange
of sodium between compartments. Thus, when
plasma sodium losses occur quickly, equilibration
with the other compartments must necessarily lag
behind. The degree of this lag is related to the
value of the permeability coefficients that have
been evaluated. The values of the permeability
coefficients are necessarily approximate due to
limitations of the types of data that were used to
perform the evaluation.
The results of Fig. 5 demonstrate the ability of
the IBM for sodium to predict plasma sodium
levels over time. This is an important capability,
because it is a simple matter for computations
such as those presented on Fig. 5 to be extended
in time until the critical plasma sodium concentration associated with lethality is reached, with that
time being the predicted survival time. Further, an
important benefit of this initial analysis of plasma
sodium levels is that it provides an estimate of the
relationship between the BLM-calculated BL:Ag
and the percent inhibition of active sodium uptake.
The resulting dose–response relationship is shown
on Fig. 6. The EC50 for inhibition of JM is 15.8
nmolygw and the slope of the dose–response curve,
b, is 0.278. The filled triangles indicated on this
curve correspond to the calculated BL:Ag levels
associated with the 5 silver treatments shown on
Fig. 5. Note that for the range of BL:Ag levels
considered, 3.4–12 nmolygw, the percent inhibition
of JM ranges from approximately 1% to somewhat
less than 30%. As will be discussed subsequently,
these results have significant implications with
regard to the longer-term effects to be expected.
3.3. Analysis of survival time data
The preceding analysis of plasma sodium levels
served as a basis for estimating the parameters of
dose–response curve of Fig. 6. The other two sets
of plot symbols indicated on the curve of Fig. 6
correspond to the percent inhibition that is associated with the BL:Ag levels that are predicted for
the treatment conditions of the two survival time
datasets that are to be analyzed next (Galvez and
Wood, 1997). In these experiments, rainbow trout
were exposed to approximately 100 mgyl of silver
(nominal) and either Ca2q, added as either
CaSO4 or Ca(NO3)2, or Cly, added as KCl of
NaCl, were varied from 50 to 5000 mM. The 50%
survival time, the ET50, was the end-point in these
experiments. While the concentration of silver that
was used in these tests was considerably in excess
of an environmentally relevant exposure level
(Campbell et al., 2001), the results are quite useful
because the additions of either calcium or chloride
resulted in a wide range of median survival times,
from less than 1 h to )7 days, the duration of the
test. The cluster of q signs at BL:Ag)30 are
associated with the calcium dataset, and indicate
that active sodium uptake is predicted to be almost
completely suppressed for all of the treatments in
this set of data, with little variation across treatment levels. Conversely for the chloride dataset,
the BL:Ag and hence the predicted inhibition of
the active uptake of sodium varies over a much
wider range (open diamond plot symbols), from
approximately 5% inhibition to 95% inhibition.
This range of results highlights the importance of
Ag complexation by chloride as a means of mitigating the availability and toxicity of silver to
rainbow trout.
As a preface to a discussion of the next set of
results it is useful to first consider what should be
expected when nearly 100% inhibition of active
uptake of sodium occurs, as is predicted for the
calcium experiments. It is readily shown from
simple mass balance calculations that a 30% loss
of the exchangeable sodium pool of 50 mmoly
kgw (i.e. a loss of 15 mmolykgw) would require
approximately 2.5 days at a net efflux of 6 mmoly
kgw yds0.25 mmolykgw yh (at JMs12 mmoly
kgw yd and f Nas0.5). All other things equal, this
would be the shortest survival time to be expected.
However, it turns out that this time estimate is
actually much longer than the range of survival
times that were observed in the calcium treatment
P.R. Paquin et al. / Comparative Biochemistry and Physiology Part C 133 (2002) 305–343
experiments to be reviewed next (-1 h to approximately 9 h) and in the lower chloride treatments
as well (-1 day at up to 500 mM of either NaCl
or KCl). If it is assumed that the permeability of
the exchange surfaces with the primary system are
too low for the other compartments to deliver
sodium at a fast enough rate to offset the loss
from the primary system, which contains only 7%
of the exchangeable sodium pool, then the survival
time could be reduced to as little as approximately
4 h (i.e. a loss of 30% of 3.5 mmolykgw, or about
1 mmolykgw is required). This is in much closer
agreement with the shortest reported survival time
of approximately 0.75 h, but still about a factor of
5 too long. It appears that the reason for the
discrepancy is that the foregoing calculations do
not consider the likelihood of an increase in gill
permeability, a result of physical damage to the
gill during short-term pulse exposures to high
concentrations of metals, much like the effects that
have been observed for low pH conditions where
order of magnitude or greater increases in permeability were estimated to have occurred (Packer
and Dunson, 1970, 1972; McDonald et al., 1983).
A plausible mechanism for the increase in gill
permeability is that damage to the gill occurs as a
result of displacement of calcium from the calcareous material that comprises the paracellular junctions between cells of the gill epithelium. It is this
intercellular cement that maintains the physical
integrity of the gill. This effect has been seen
previously to occur under acidic conditions, where
the calcium is titrated from the gill by protons
(Milligan and Wood, 1982; McDonald, 1983a,b)
and could reasonably be expected as a mechanism
for the deterioration of the gill epithelium by
metals as well. The increase in permeability is
caused by a decrease in the depth of the paracellular junctions as the calcareous intercellular
cement is titrated away (McDonald et al., 1991).
Here, it is assumed that the calcareous material
deteriorates as a result of displacement of calcium
by free silver, while increasing the level of Ca2q
tends to reverse the direction of this displacementtype of reaction. Alternatively, adding chloride
reduces the free silver, resulting in a similar beneficial effect, but for a different reason. Note that
this reaction should not be interpreted as an equilibrium reaction, as this is probably not the case,
at least under conditions of a pulse exposure.
Rather, there would be expected to be a progressive
deterioration of the gill, until such time as the
327
organism is able to adapt during conditions that
are less extreme, or until mortality occurs. It is
this line of reasoning that leads to the form of the
relationship described above (Eq. (9)) which will
be applied to adjust for changes in permeability
when Agq is greater than approximately 35 mgyl.
Note that the effect of chloride on gill permeability
is indirectly accounted for in this relationship via
its effect on the free silver concentration.
Fig. 7 shows how this approach is applied with
the survival time data for the calcium treatments.
The open and filled triangles represent results for
calcium additions in the form of Ca(NO3)2 and
CaSO4, respectively. The model is used in the
same way as in the analysis of the plasma sodium
data, using the same dose–response curve (Fig.
6), in conjunction with the BL:Ag estimated with
the BLM, to predict the degree of inhibition of
JM for each set of test conditions. Plasma sodium
concentrations are then computed over time, until
a 30% decrease occurs. The time at which this
occurs is the estimated ET50 for survival time.
Because the model does not incorporate any mechanism for distinguishing between the effects of the
two added anions, either chemically or physiologically, only one line is shown for the model results.
The model results are consistent with the survival
time data, which also fail to display any systematic
variation with regard to the form in which the Ca
was added. Both measured and predicted survival
times increase from approximately 1 h to slightly
more than 8 h over the range of calcium treatment
levels tested. Consistent with the preceding analysis of gill permeability coefficients, the gill permeability has been increased by a factor of
approximately 5.6 at the lowest calcium levels,
and by about a factor of slightly more than 2 at
the highest Ca levels. This is achieved via Eq. (9)
with as3.09=10y4 for Agq in units of mgyl
(4.54 if mM units), bs2.05 and csy0.22
(Ca2q in mM units).
Finally, consider the effect of increasing the
chloride concentration on survival. The results are
summarized on Fig. 8, where the scale of the yaxis is increased by 20-fold relative to Fig. 7 (the
results for the calcium treatments). As shown,
addition of up to 5 mM chloride (as either KCl or
NaCl), the same increase in molar concentration
as for calcium, increases the survival time ET50
from less than 1 h to approximately 7 days or
longer. For KCl additions (m), the model (solid
line) predicts a median survival time of approxi-
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Fig. 7. Comparison of predicted (solid line) with measured ET50 for rainbow trout exposed to ;100 ugyl silver and variable treatments
of CaSO4 (m) or Ca(NO3)2 (D). Results obtained with sodium JM s12 mmolykgw yd and KM s0.05 mM, PGo s0.0386 lykgwyd, PP,ISs
PIS,ICs0.1 lykgwyd. (Data: Galvez and Wood, 1997).
Fig. 8. Comparison of predicted with measured median survival times for rainbow trout exposed to ;100 ugyl silver and variable
levels of KCl (datasm and modelssolid line) and NaCl (datasD and modelsdashed line). The data point for the high NaCl treatment
(5 mM) is plotted at the 7-day test duration (≠), but actually exceeded 7 dayss168 h (i.e.-50% mortality was observed thru the 7
day test duration) while the model predicts the fish will survive. (The model predicts survival at KCl);2 mM and at NaCl);1
mM). Model parameter values are same as for calcium treatments of Fig. 8. (Data: Galvez and Wood, 1997).
P.R. Paquin et al. / Comparative Biochemistry and Physiology Part C 133 (2002) 305–343
mately 1 h at the lowest chloride level, 0.5–3 days
at the intermediate chloride levels, and for an
indefinite period of time at the highest chloride
level, with all but the result at the highest chloride
treatment in good agreement with the data. The
discrepancy at the highest treatment level could be
eliminated if the gill permeability of the control
fish was increased by somewhat less than a factor
of 2, a difference expected to be within the limits
of experimental variability and the uncertainty of
the equilibrium assumptions used to evaluate control fish gill permeability.
With regard to the NaCl treatments (n), the
predicted BL:Ag levels are similar to the predicted
levels when KCl is added. However, in conformity
with the data, the model predicts an increase in
survival time in comparison to the KCl treatments
when the chloride is added as NaCl. The reason is
that there is an increase in Ji when Naq is added
in association with the chloride, due to the fact
that the uptake rate of sodium is related to the
sodium concentration in the external water via the
Michaelis formulation (Eq. (1)). For the highest
NaCl addition, the ET50 value was reported to be
greater than approximately 7 days, the value indicated on the graph, because less than 50% mortality was observed over the 7-day duration of the
experiment. The model result is consistent with
this observation, predicting rainbow trout survival
for this set of treatment conditions.
As with all of the calcium results, chloride
treatments of less than 1 mM led to survival times
of -2 days, less than could occur even with 100%
inhibition of sodium uptake. The preceding analysis of gill permeability coefficients indicated that
the permeability apparently increased at free silver
levels in excess of approximately 37.5 mgyl. As
such, the explanation of survival times of less than
2 days is attributed to this factor. As discussed
previously, the effect of Agq on gill permeability
was represented via Eq. (9), with PG returned to
baseline conditions when Agq is less than 37.5
mgyl. By adopting this approach the model was
able to predict survival times over the range of
test conditions in the chloride experiments.
329
roughly classified as chemistry-based models (Roy
and Campbell, 1995), bioaccumulation-based
models (Mancini, 1983; Connolly, 1985; McCarty,
1987; McCarty et al., 1993; Meyer et al., 1995;
Marr et al., 1998), physiologically-based models
(Szumski and Barton, 1983), and combinations
and variations thereof (Breck, 1988; Verhaar et
al., 1999). Here, a generalized physiologicallybased modeling framework is presented that may
be used to evaluate the survival time of aquatic
organisms exposed to metals. It is applied in the
analysis of data for rainbow trout exposed to silver.
The model framework is similar in some ways to
a PBPK model, but not entirely. While the model
is founded upon a physiologically-based, 4-compartment representation of a fish, and it includes
accumulation of the metal at the site of action of
toxicity, it differs from a conventional PBPK model in that it does not compute the internal distribution and ultimate disposition of the stressor, in
this case silver, over time. Rather, the concentration of silver at the site of action, as calculated
using the previously developed BLM, is used to
evaluate the degree of effect of silver on the
mechanisms of toxicity, inhibition of the active
uptake of sodium and, at sufficiently high levels,
on the passive diffusive losses. It then accounts
for the subsequent impact of these changes in
uptake and loss of sodium by keeping track of the
cumulative damage to the fish, as manifested by
loss of sodium from the internal fluid compartments. Survival time corresponds to the time when
the cumulative effect is a fixed degree of loss of
sodium, taken here to be 30%, from the primary
vascular system. It is expected that the capability
to perform this type of evaluation, to assess cumulative damage to the organism over time, will offer
regulatory agencies an improved basis for explicitly considering magnitude, duration and frequency
of occurrence when developing updated WQC for
metals. Subject to further refinement, it may also
be useful in extrapolating from acute to chronic
effect levels, and in other areas as well, as
described below.
4. Discussion
4.1. Analysis of indicator dilution and plasma
sodium data
Numerous models have been proposed over the
last 20 years for use in predicting the survival
times of aquatic organisms exposed to either metals or organic chemicals. These models may be
The analyses of the tracer data and the plasma
sodium data were performed, in part, to evaluate
the sizes of the four fluid compartment volumes
and the rates of exchanges between them. It was
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possible to achieve a reasonable fit of both types
of data using fluid compartment volumes that are
generally consistent with compartmental volumes
that have been reported in the literature (Figs. 4
and 5). The inter-compartmental permeability coefficients, or IPCs, were evaluated concurrently with
the fluid volumes for the indicator dilution tracer
data and were preliminarily set at 0.08 lykgw yd.
The same fluid volumes were used in the analysis
of the plasma sodium dataset (Fig. 5) and an effort
was made to fit this dataset by adjusting the IPCs
independent of the values that had been used for
the tracer studies. The model is fairly sensitive to
these coefficients because an increase or decrease
in the IPCs results in a corresponding increase or
decrease in the rate of plasma sodium loss as well.
The reason is that use of relatively high IPCs
results in an effective increase in the plasma
sodium pool that is available to buffer losses of
sodium from the primary system, while a decrease
has the converse effect. As it turns out, the data
were not of sufficient detail to justify the independent evaluation of each of the different IPCs
(P1,IS, P2,IS and PIS,IC) and a value of 0.1 lykgw
yd was assigned in all cases.
There was not any a priori reason to expect that
the IPCs that were evaluated for the indicator
dilution studies performed with inulin and the
plasma sodium studies would have the same values. Rather, it would have been reasonable to
expect that the permeability coefficients for sodium would be considerably higher than for the
tracers that were used in the indicator dilution
studies (McDonald, personal communication).
However, it was decided that the slight difference
between the values of the coefficients that were
initially assigned based on calibration to the measured concentration data (0.08 vs. 0.10 lykgw yd)
could not be justified on the basis of the fit of the
data by the model that was achieved. It was
therefore decided to assign a consistent value of
Pijs0.1 lykgw yd for both sets of data. It is
emphasized that although the model was able to
fit both types of data with a single set of permeability coefficients, this should not be interpreted to
be an indication that the values of these coefficients did not in fact differ significantly. Rather, it
is more likely an indication of the limited discriminatory power of the model with regard to the
interpretation of these data, as well as the practical
limitations associated with what are otherwise
judged to be excellent and relatively detailed
datasets.
Together, the fluid compartment volumes and
permeability coefficients are important model parameters, as they control the response time of the
plasma sodium pool when active uptake is reduced
andyor permeability increases as a result of physical damage to the gill. However, the analysis of
the 24-h tracer dataset was judged to be of limited
use in evaluating what is, ostensibly, the ICFV, as
well as the rate of interaction between this compartment and the remainder of the fluid volume,
the ECFV. The plasma sodium results indicate that
at PIS,ICs0.1 lykgw yd, the rate of exchange
between the extracellular and intracellular fluid
compartments was not rapid, as the calculated
decrease in concentration in this compartment,
even in the most extreme test case, was always
less than 5% over the 48-h test duration (Fig. 5f).
While it is not entirely clear that the model
should include interaction with the ICFV, there is
some precedent for structuring the model in this
way. Investigations of the effect of low environmental pH on rainbow trout provide evidence of
there being a significant contribution by the ICFV
to total body ion losses, including sodium losses
(McDonald and Wood, 1981). These losses of
ions, which initially occur from the blood, lead to
the establishment of osmotic and ionic gradients
that induce shifts of both fluid and ions between
the ECFV and ICFV (McDonald and Wood, 1981;
Milligan and Wood, 1982). Because it is well
known that both acidic conditions and exposure to
metals, such as silver and copper, result in loss of
ions from the blood, it is reasonable to expect that
the ICFV would respond in a similar manner in
either case, regardless of the underlying cause of
the ion depletion (i.e. exposure to low pH conditions or to metals). An alternative interpretation of
the fluid compartments considered herein is that
they correspond to a 2-compartment vascular system exchanging with a 2-compartment ISFV, while
the ICFV is a non-interacting volume. The ISFV
in this case would correspond to a 2-compartment
sodium pool consisting of richly perfused tissues
that are readily accessible for exchange, a ‘fast
pool’, and tissues that are less well perfused, a
‘slow pool’. As configured herein, the slow pool
is connected to the vascular system via the fast
pool (i.e. the 2 pools are connected in series).
There are a number of alternative configurations
of the fluid compartments that could reasonably
P.R. Paquin et al. / Comparative Biochemistry and Physiology Part C 133 (2002) 305–343
be considered. The simplest would be to consider
a single, completely mixed, fluid volume. This
approach was used in the early stages of model
development and it was found to be necessary to
increase the effective volume of the fluid compartment, as survival time increased, to achieve
consistency in response times between model and
data. (The version of the model described herein
may be set up in this way by the appropriate
assignment of inputs.) Another approach would be
to allow both of the extravascular fluid volumes
to exchange directly with the vascular system, with
the exchange rates between the blood and the fast
and slow pools controlled by varying the respective
permeability coefficients. Another variation would
be to have the tissues associated with the fast pool
exchange with the primary vascular system and
those of the slow pool exchange with the secondary vascular system. The model would need to be
modified slightly to represent these latter configurations. It is not clear if these distinctions would
lead to a material change in the ability of the
model to reproduce the observed results, but they
could potentially lead to an improved physiological
representation of the fish. It is expected that the
continued use of this model, including model
sensitivity analyses in conjunction with analysis of
results of suitably designed experiments, will lead
to an improved understanding of how best to
proceed.
Recently, another excellent source of information on tissue fluid volumes in fish has been
identified (Bushnell et al., 1998). This study provides very detailed information on fluid volumes
for a wide variety of tissues. Of particular interest
was their evaluation of the volume of the secondary vascular system, and its rate of exchange with
other compartments, both of which were found to
be of much less importance than the results reported by Steffenson and Lomholt (1992). Further
consideration of these results will be warranted in
conjunction with future applications of the IBM.
4.2. Analysis of survival time data
The survival time data analyzed herein serve as
an excellent basis for model development because
the water chemistry of the test waters reflected a
wide range of conditions that resulted in a correspondingly wide range of effects. Median survival
times ranged from less than 1 h to longer than 1
week. While having its advantages, to some degree
331
the wide range of organism responses was also
problematic, as it resulted in the need to introduce
additional model parameters to represent each of
the mechanisms of toxicity that are reflected in the
data. The discussion that follows will be ordered
in accordance with the different time scales considered by the model, beginning with the shorterterm pulse exposure results followed by the
intermediate range effects. The potential for applicability of a refined version of this model framework to the analysis of chronic effect conditions,
conditions not fully reflected in the data that have
been analyzed herein, will also be discussed.
4.2.1. Short-term pulse exposures
Two sets of experimental results were analyzed
in which lethality occurred on time scales of about
an hour to a few days. To achieve the rapid onset
of lethality, it was necessary to invoke an assumption that there is physical damage to the gill,
leading to an increase in gill permeability and an
accelerated rate of losses due to passive diffusion
from the blood. Based on studies at low pH, it has
been found that the Naq efflux increases progressively as pH decreases (McDonald, 1983a,b). It
can be increased markedly, by more than 10-fold,
at pH 4 (Packer and Dunson, 1970). With influx
essentially eliminated at this pH, the sodium efflux
resulted in a rate of loss of Naq from the body of
approximately 10% per hour. At pH 3, the rate of
Naq efflux increased to 50% per hour and rapidly
resulted in death (Packer and Dunson, 1972). The
mechanism of this increase in efflux has been
attributed to an increase in permeability caused by
low pH titration of the calcium-based intercellular
cement-like material that the tight junctions of the
branchial epithelium are made of. This effect
appears to be similar to what happened in the low
calcium and low chloride datasets analyzed previously, where it was necessary to increase gill
permeability by as much as about a factor of 6 to
account for the short survival time that was
observed.
Packer and Dunson (1970, 1972) provided some
of the earliest demonstrations that exposure of
brook trout to low pH conditions inhibits sodium
uptake and that it is the rate of loss of sodium,
rather than the total amount that is lost, that
correlates best with survival time. Similar effects
have been reported by others (McDonald, 1983b;
Wood, 1989). Packer and Dunson (1972) hypothesized that ‘extremely rapid rates of loss may
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deplete plasma Na to a greater extent than if the
rate is slower and the loss comes from a greater
proportion of the total Na pool.’ This was concluded from the observation that when the rate of
branchial sodium loss and mortality was accelerated the whole body Na loss was reduced. (Overall
losses of sodium by brook trout were well in
excess of 30% in these early studies.) A similar
statement may be made about the SBM. That is,
if the loss of sodium occurs relatively slowly, then
sodium levels in all of the compartments will
decrease at nearly the same rate, and the whole
body sodium loss will approach 30% at the time
of death. Conversely, if sodium is lost quickly
from the primary system, then the decrease of
sodium in the other compartments will lag behind
the concentrations in the primary system and less
sodium will be lost, on a whole body basis, at the
time of death.
The criterion that has been used here of a 30%
loss of plasma sodium at the time of death is
employed as a first approximation, and could be
refined if justified on the basis of a more thorough
review of the available data. It should also be
recognized that use of a 30% decrease in the
plasma sodium level is somewhat of an oversimplification, as it is the overall disruption of ionoregulation that actually leads to adverse effects to
the organism. These effects include changes in the
osmolality of the blood, shifts in fluid volumes
and an ensuing and well-documented cascade of
events that culminates in cardiovascular collapse
and death (Milligan and Wood, 1982; McDonald,
1983b; Wood, 1989 for effects of pH; also Wilson
and Taylor, 1993a; Taylor et al., 1996 for copper,
Wood et al., 1996; Hogstrand and Wood, 1998 for
silver). Sodium has been used herein as a convenient biomarker, a surrogate for the overall effect
on ionoregulation that triggers this ill-fated
sequence of events.
The effect of calcium on gill permeability, a
competitive interaction with silver at the gill paracellular junctions, is not to be confused with the
competitive interaction that is represented in the
BLM of acute toxicity. The competitive interaction
in the BLM represents competition at the biotic
ligand and is related to the inhibition of NKA
activity, rather than an effect on permeability. At
more realistic levels of dissolved silver of approximately 6–8 mgyl, Janes and Playle (1995) have
shown that calcium is ineffective at competing
with silver for interaction at the biotic ligand at
calcium levels as high as 10 mM. Here, even
though the dissolved silver concentration is much
higher, there is evidently a significant benefit
associated with increasing the calcium from 0.05
to 5 mM, as survival time increases by about an
order of magnitude.
The model results described herein have emphasized the role of Ca2q in the model, both with
respect to its role as a competing cation (in the
BLM), as well as its effect on gill permeability
(in the IBM). However, Schwartz and Playle
(2001) have recently reported results that support
the inclusion of Mg2q in the BLM for silver as a
competing cation as well, with its role generally
viewed as being lesser in importance than that of
Ca2q. The reason for this lesser role may be
related to the fact that Ca2q has the added effect
on gill permeability through its ability to stabilize
the gill structure, which is comprised of a calcareous material. In any case, the competitive effect
of even calcium tends to be of less importance
than it appears to be for other metals (Hogstrand
et al., 1996). This reduced benefit is accounted
for, in the context of the Ag BLM, by the relatively
high affinity of Ag in comparison to that of other
metals for binding to the biotic ligand.
4.2.2. Intermediate-term exposures
As indicated by the short survival times reported
by Galvez and Wood (1997), these data appear to
have reflected conditions where gill permeability
was elevated due to the high silver concentration.
The exception to this appears to have been in the
intermediate to high chloride level experiments
where survival times exceeded approximately 2
days. Speciation calculations indicate that the free
silver was less than approximately 35–40 mgyl in
the experiments where survival times were greater
than approximately 2 days and greater than this
when the survival time was substantially less than
2 days. Since ambient levels of silver are typically
much less than this (Campbell et al., 2001), it is
unlikely that physical damage to the gills of fish
will occur under normal field conditions. The
model provided a reasonable prediction of survival
times at a chloride level of 1 mM, but overpredicted survival at 5 mM. The reason for this in
the high KCl treatment may have been that the
gill permeability of the control fish was apparently
less than the exposed fish. In the high NaCl
treatment, both model and data indicated the EC50
P.R. Paquin et al. / Comparative Biochemistry and Physiology Part C 133 (2002) 305–343
would not occur within the time limits of the
experiment.
4.2.3. Acclimation and chronic toxicity
One of the motivating factors that led to the
development of the SBM was the idea that it might
help to better understand, and ultimately to be
better able to predict, the effects that result from
longer-term chronic exposure to metals. It had
been shown that the rate of response of plasma
sodium levels to exposure to silver decreased as
the concentration of available silver decreased
(Fig. 5; McGeer and Wood, 1998). At about the
same time, there were also data that showed that
at silver levels of 0.5–2 mgyl rainbow trout may
eventually recover from an initial loss of sodium,
with the recovery taking place over a time scale
of approximately 28 days (Galvez et al., 1998).
There is a suggestion of this same response in the
data of Fig. 5c and d where, between the time of
the 24- and 48-h measurements, qualitatively at
least if not statistically significantly, there appears
to be either a leveling off or slight increase in the
plasma sodium level. Although the appearance of
acclimation was a positive finding, other results
from even longer-term studies have shown that
reduced survival may still be observed over a
longer period of approximately 18 months, at still
lower silver concentrations of 0.2 mgyl (Davies et
al., 1978). One explanation for why the rainbow
trout in these longer-term experiments apparently
did not fully acclimate is that it may be necessary
for the metal exposure level to first exceed a
threshold level that causes a detectable morphological disturbance (McDonald and Wood, 1993). It
is plausible that the very low exposure levels used
in these well-controlled tests precluded this condition. It follows that under conditions of a more
natural setting, short-term periods where concentrations are elevated above the average concentration might be beneficial in that they may stimulate
the physiological changes that lead to acclimation
over the long term.
Returning to the model, the initial line of reasoning was that at very low silver concentrations,
the organism response to a loss of plasma sodium
would still occur, but at a very slow rate. Given
sufficient time, the critical plasma sodium level
would eventually be reached and mortality would
occur. What was needed then was for the model
to be able to relate the exposure level to the degree
of inhibition of active sodium uptake, and hence
333
to the net rate of loss of sodium, and to then use
this relationship to predict the response of plasma
sodium levels to chronic low-level exposures. The
model was developed and, within reasonable limits, it has been shown to be able to achieve these
objectives with a reasonable level of success.
Interestingly, however, it does not respond in the
manner that had been originally envisioned by the
developers of this model. Rather, it does what a
fish does. That is, if the degree of inhibition is
low, in the range of 5–10%, then plasma sodium
begins to decrease slowly, but eventually it will
stabilize at a new steady state condition. This is
exactly the situation that is illustrated by both the
model and data shown on Fig. 5c and d. The
simple explanation for this is as follows. Under
normal conditions, influx and efflux are in balance
and the plasma sodium level is constant. If they
were not in balance, there would be a net rate of
gain or loss of sodium, and plasma sodium levels
would change. (Renal losses need to be considered
as well, but they are a relatively minor part of the
overall balance and will be neglected for discussion purposes, as the general concept remains the
same in any case.) If the sodium influx rate now
decreases by 10% due to exposure to silver, then
efflux exceeds influx and plasma sodium levels
will begin to decline. But the efflux is to a very
good approximation proportional to the plasma
sodium level, so once the plasma sodium concentration decreases by 10% influx and efflux are
again in balance, though at a new equilibrium
plasma sodium concentration, and the decline of
plasma sodium levels is arrested. The data of Fig.
5c and d illustrate that this in fact occurs, and
while the model is useful in explaining why this
occurs, in hindsight, this result seems obvious.
An interesting consequence to this line of reasoning is that if 30% loss of plasma sodium is
required for death to occur, then at least 30%
inhibition of active uptake is required for lethality,
in the absence of damage to the gill that might
increase the gill permeability. Note that for the
high chloride tests, the model correctly predicted
survival in the NaCl treatment, the reason being
that only approximately 5% inhibition of JM was
predicted. Similarly, only 10% inhibition was predicted in the high KCl treatment, so survival was
predicted in this case as well, even though half of
the fish were somewhat uncooperative in this
regard. Another limitation of the model, besides
failure to be accurate in all instances, is that while
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the model predicts a leveling off at a new equilibrium concentration, the fish will not necessarily
do the same. A variety of acclimatory responses
may intercede, leading to longer-term recovery in
the most favorable of circumstances. For example,
McDonald (1983b) has shown that at low rates of
Naq loss there is an enhanced opportunity for
hormonal adjustments to take effect, reducing gill
permeability and increasing active uptake of sodium, leading to an improved chance of survival.
The results of Zadunaisky (1997) suggest that the
shorter-term response is stimulated by the initial
change in plasma osmolality while the longer-term
response is more likely related to the release of
cortisone by the fish.
What exactly happened in the case of Davies’
early experiments is at this point unclear. However,
the results of more recent long-term data suggest
that water chemistry will continue to be an important factor in assessing silver availability and longterm effects (Davies, 1997). Further, ongoing
studies that are directed at gaining an improved
understanding of these early results will hopefully
shed some light on this matter. Initial results with
fathead minnow have indicated that losses of
sodium continue to be an important biomarker of
adverse effects leading to death (Stubblefield et
al., 2000). In this regard, the SBM highlights the
importance of chemistry not only to metal bioavailability, but to the physiological status of the
organism itself, especially with regard to its ability
to regulate internal levels of sodium, chloride, and
perhaps other ions as well.
4.3. Other considerations
While the capability to predict effects associated
with alternative exposure durations is a useful
feature of this model, it also has applicability to
other aspects that are of toxicological interest as
well. That is, this same framework should also be
useful in the interpretation and analysis of time
variable exposures, residual effects following
exposure to metals, potential effects of chloride
and other ions, and species and genus sensitivity.
It may also have implications to consider for
toxicity models that have been proposed for other
types of chemical stressors.
4.3.1. Time variable exposure and residual aftereffects
The inhibition of NKA activity that results from
exposure to silver has been observed to occur in a
dose-dependent manner (Hussain et al., 1994;
Morgan et al., 1997). Further, the inhibition of
branchial Naq and Cly influxes occurs almost
immediately upon exposure, while the effect on
the corresponding effluxes is much less (Morgan
et al., 1997). The speed of the response is consistent with the reported rapid inhibition of NKA by
both silver and mercury (Anner et al., 1992;
Hussain et al., 1994). Further, Hussain et al.
(1994), working in vitro, showed that the inhibition of NKA activity is both rapid and reversible,
while Morgan et al. (1997) showed that when the
concentration of silver was returned to background
levels after 48 h of exposure at 2 mgyl, the sodium
influx and net flux were almost immediately
returned to control values. Collectively these
results, especially the idea that NKA inhibition is
rapid and reversible, provide a basis for simulating
the effects of time variable exposures. That is, all
that is required is to reinitialize the plasma sodium
concentration and the associated sodium fluxes
each time the silver concentration or other water
quality characteristics change, recompute BL:Ag
and Ji, and continue to calculate the plasma sodium
concentration over time until either the critical
plasma sodium level associated with lethality
occurs, or recovery occurs.
Fig. 9 illustrates use of the model to simulate
time variable effects. The situation is quite simple.
The simulation begins with a pre-exposure period
(t-0), during which time influx and efflux are in
equilibrium and plasma sodium levels remain constant. This is followed by a 12-h exposure to the
metal (0-t-12 h), and then a return to preexposure conditions (beginning at ts12 h). The
computations assume that NKA inhibition occurs
both rapidly and reversibly, such that active sodium
uptake recovers immediately when exposure to the
metal is ended. Active sodium uptake is inhibited
at the start of the exposure, and hence a period of
net loss ensues and plasma sodium decreases. At
ts12 h the exposure to silver is removed, active
uptake returns to normal and, as indicted by the
upper dashed line, the model predicts a recovery
of plasma sodium levels over time, in the direction
of pre-exposure levels. For the second case (lower
curve) it is assumed that the exposure concentration is high enough to result in both inhibition of
active sodium uptake plus physical damage to the
gill. The gill damage is manifested in terms of an
increase in gill permeability such that PG)PGo. In
this case, once the exposure is removed after 12
P.R. Paquin et al. / Comparative Biochemistry and Physiology Part C 133 (2002) 305–343
335
Fig. 9. Illustrative model results that show how delayed effects may occur even after exposure to a metal is eliminated. The computations
assume that active sodium uptake recovers immediately, while the increased gill permeability, resulting from physical damage to the
gill due caused by a short-term pulse exposure, does not recover immediately, once the metal exposure is eliminated. The upper line
shows model prediction in the absence of gill damage, with plasma sodium beginning to return to pre-exposure levels. The lower line
shows how plasma sodium levels may continue to decrease even with uptake returned to normal, because the permeability of the
damaged gill remains elevated. Lethality ensues at 30% depletion, some time after the exposure was eliminated.
h, active uptake returns to normal, but the efflux
remains elevated. As a result, sodium losses continue over time, although at a slower rate than
during the exposure period (the lower curve at
t)12, where influx is returned to normal). With
plasma sodium levels continuing to decline, lethality ensues at the point of 30% depletion of plasma
sodium, approximately 12 h after the exposure was
eliminated. Note that these short duration simulations do not reflect the possible mitigating effects
that longer-term acclimation may have, such as
changes in chloride cell density, active uptake rate,
or reduced gill permeability. Such changes may
have important implications, but they have not yet
been incorporated in the model.
4.3.2. Effect of chloride
As noted previously, exposure to some metals,
including silver and copper, may inhibit not only
sodium uptake but chloride uptake as well (Wilson
and Taylor, 1993a; Morgan et al., 1997). Thus, it
is of interest to speculate about the potential effect
of the ambient chloride concentration on metal
effect levels. In the case of Agq, Cly reduces its
toxicity by forming the relatively non-bioavailable
AgCl complex, concurrently reducing the level of
Agq and hence its degree of interaction at the
biotic ligand. For copper, this would not be an
important factor because Cu2q does not form a
strong chloro-complex. Aside from its effect on
speciation, it seems reasonable to speculate that
chloride may have further effects, in the case of
either metal. Consider that active chloride uptake
occurs in much the same way as active sodium
uptake, conforming to saturation kinetics and having a characteristic maximum uptake rate and half
saturation concentration for chloride in the ambient
water (Goss and Wood, 1990a,b). Also, since it is
the loss of ions from the blood via passive diffusion that causes osmoregulatory disruption, leading
to shifts in fluids between internal compartments,
ultimately leading to cardiovascular collapse and
death, it would be expected that both sodium and
chloride would play a similar roll. If so, it follows
that anything, which affects chloride regulation,
will have a bearing on the response of the organism. Because relatively high chloride levels in the
ambient water will facilitate the active uptake of
chloride, this would be expected to reduce the rate
of any net loss rate of chloride that occurs when
active uptake has been inhibited or, under relatively extreme conditions, where efflux has increased
336
P.R. Paquin et al. / Comparative Biochemistry and Physiology Part C 133 (2002) 305–343
due to an increase in gill permeability. This effect
should occur not only for silver but for copper as
well. In fact, recent test results with Daphnia sp.
have shown that the Cu LC50 values did in fact
increase with an increase in chloride levels in the
test water (Rodriguez et al., 2001).
Another effect of increasing the chloride level
in the ambient water would be to reduce the
concentration gradient between the blood and
water and hence diffusive losses. This would
normally be expected to be a relatively slight
effect in freshwater settings, however, because
ambient chloride levels remain low, typically in
the range of 0.05–5 mM (approximately 2–200
mgyl), in comparison to plasma chloride levels of
approximately 150 mM (5250 mgyl). However,
Lewis and Lewis (1971), in tests with channel
catfish and golden shiner, showed that increasing
the concentration of NaCl in the ambient water to
levels approaching the osmolality of the blood,
actually mitigated the adverse effects of exposure
to Cu. While both sodium and chloride levels were
increased in this case, it was necessary that they
be increased to levels well in excess of where
active uptake is saturated in order to prevent
effects. It follows that at this level of Naq and
Cly in the ambient, the diffusive losses would be
markedly reduced, thereby mitigating what would
otherwise be the expected acute effects of exposure
to copper. Several other examples have been
reported where elevated levels of sodium in the
ambient water affected the diffusive flux of ions
between the water and plasma. Wilson and Taylor
(1993b) showed how plasma sodium levels of
rainbow trout exposed to copper in saltwater
increased (the direction of the diffusion gradient
is reversed in saltwater) until internal and external
levels of sodium were about equal. Packer and
Dunson, in low pH exposures, also showed how
elevated sodium levels extended survival time
from 2 to 8 h, though death eventually ensued,
probably as a result of losses of other ions. It is
expected that elevated external chloride levels
would have a similar beneficial effect, at least in
regard to reducing diffusive losses from the blood.
Chloride uptake could be readily incorporated into
the IBM model framework. If warranted, ionspecific gill permeability coefficients (Potts, 1984)
could also be included. Potts (1984) presents the
equations that describe the fluxes associated with
these electrochemical gradients, should further
refinement be needed.
4.3.3. Species sensitivity
The reason for differences in species sensitivity
to various chemical stressors, including metals, is
not well known. McDonald et al., in an effort to
understand why these differences exist for fish,
conducted a study of the differences in gill morphology of freshwater fish in relation to their
sensitivity to low pH conditions (McDonald et al.,
1991). On the basis of parallel studies with banded
sunfish, yellow perch, smallmouth bass, rainbow
trout and common shiner (listed in order of lowest
to highest sensitivity to pH and spanning the limits
of resistance to pH effects among freshwater teleosts), they concluded that acid tolerance is not
correlated with some of the basic physical dimensions of the gills (surface area, thickness or blood–
water diffusion distance) or with the degree of
mucous formation on the surface (i.e. the ‘degree
of mucification of the surface’). However, they
found that it may be correlated to the chloride cell
density and the branchial ion-transport activity.
They interpreted this to indicate that sensitivity to
low pH is related to the intrinsic ion-permeability
of the gills, which is related to the depth of the
tight junctions between adjacent gill pavement
cells.
The observation of McDonald et al. (1991) that
the chloride cell density increased with increasing
sensitivity may at first seem counterintuitive, since
a high transport capacity would seem to be a
positive attribute. This is in fact a reasonable result
if viewed from a different perspective. That is, the
tendency for the more sensitive fish species to
possess higher chloride cell densities is due to the
fact that their gill epithelium is relatively permeable (i.e. ‘leaky’). This in turn requires that they
possess a relatively high chloride cell density and
an associated high JM to increase their ionic uptake
capacity, a necessity for maintaining homeostasis
with regard to the ionic composition of their
intracellular fluids.
Incorporation of the key physiological features
of sodium uptake and efflux in the SBM makes it
well suited for the analysis of species sensitivity
in a way that considers the preceding mechanisms.
A thought experiment will be used to illustrate
how these characteristics would explain species
sensitivity in the context of the SBM. First, in
order to maintain simplicity without loss of generality, neglect renal losses. Next, consider two
fish species that have the same plasma sodium
concentration, but one has a low sodium influx
P.R. Paquin et al. / Comparative Biochemistry and Physiology Part C 133 (2002) 305–343
rate and the other a relatively high influx rate (e.g.
Jis4 and 8 mmolykgw yd). Consistent with the
need to maintain intracellular homeostasis, it can
be estimated from Eq. (7) that the gill permeability
must be higher (i.e. the gill is ‘iono-leakier’) for
the species with the higher uptake rate. More
directly, the effluxes for the two species will be 4
and 8 mmolykgw yd, equal to the respective influxes, for equilibrium conditions to be maintained
with respect to plasma sodium. If it is assumed
that the differences in sodium uptake rates vary in
accordance with NKA activity, and that exposure
to silver in the same test chamber will result in
the same biotic ligand concentration for each fish
species (the biotic ligand and binding constant are
the same in each case), then the percent inhibition
of sodium uptake will also be the same (Fig. 6).
Assuming 75% inhibition occurs for this example,
then the net loss of sodium will be JiyJes2y
8sy6 mmolykgw yd in the one case and JiyJes
1y4sy3 mmolykgw yd in the other case. All
other things equal, the fish with the higher net rate
of loss will lose 30% of its exchangeable sodium
(7.5 mmolykgw if the exchangeable pool is 50
mmolykgw) in 1.25 days while the less sensitive
fish with the lower rate of loss will survive for
2.5 days. Alternatively, it is readily shown that
only 37.5% inhibition is required for a survival
time of 2.5 days for the more sensitive species,
the one with the higher efflux rate, so the LC50
would be lower as well, given the same exposure
water characteristics.
It should be understood that there is somewhat
of a ‘chicken or the egg’ conundrum here, as it is
not perfectly clear what is the more fundamental
parameter that leads to an organism being sensitive
to exposure to metals, the high uptake rate or the
high loss rate of sodium and other ions. While a
high uptake rate in combination with a fixed
exchangeable sodium pool is associated with a
faster response time when an organism is stressed
than is a slow uptake rate, it is not clear that it is
the uptake rate per se that is causally related to
the response time. Rather, the capability to efficiently take up sodium at a relatively high rate is
more likely to be an asset, a capability that has
developed, perhaps evolved, from the need to
overcome the high rate of loss of sodium associated with a leaky branchial epithelium. Further,
considering that this is an energy demanding process, it is not an energetically advantageous process that an organism would be likely to carry out,
337
except out of necessity. The efflux rate is more
logically expected to be the cause of a short
response time, as once the uptake is reduced or
entirely eliminated, it is the efflux alone that
controls how quickly the steady state sodium pool
will decrease in concentration. Regardless of what
logic and intuition might offer in answering this
problem, the insight provided by the mathematical
solution to the problem is that it is the efflux rate
of sodium that controls the response time, rather
than the influx rate. The ratio of the uptake to
efflux rates will control the magnitude of the
steady state plasma sodium concentration, but only
the efflux rate, including both passive losses at the
gill and renal losses, will control the response time
of the organism to exhibit effects due to inhibition
of the active uptake system. At the same time,
perhaps there are some inherent metabolic advantages to a high sodium uptake rate, perhaps related
to the need to maintain acid–base homeostasis in
conjunction with high metabolic needs. If so, there
may be a compensatory advantage, an underlying
need for some organisms to possess a higher efflux
rate of sodium than others. Recent investigations
suggest that this need may derive from energetic
requirements that are related to organism size
(Bianchini et al., 2002; Grosell et al., 2002). The
effect of size on sodium uptake rate could be
added to the model via a simple regression equation that relates sodium uptake rate to size, or by
simply estimating the uptake rate independent of
the model and setting the appropriate value as a
model input.
Finally, it is of interest to consider a comprehensive summary of data on osmo-conformers and
osmo-regulators that has been compiled by Mantel
and Farmer (1983). In view of the results that
have been presented above, review of these data
begs the question of whether or not osmo-conformers, aquatic organisms who’s plasma osmolality
tends to vary with the ambient, would tend to have
a reduced sensitivity to metals, since the low
concentration gradient would reduce the efflux and
hence the rate of change in plasma composition
that arises from diffusive losses or gains.
5. Summary
The model described herein provides a unique
basis for considering the effects of metals on
ionoregulation by aquatic organisms. Though
developed for fish exposed to silver, the same type
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P.R. Paquin et al. / Comparative Biochemistry and Physiology Part C 133 (2002) 305–343
of framework should be readily adaptable to other
types of organisms, including invertebrates, and to
other metals as well. Of course, an understanding
of the underlying physiological mechanisms would
be a pre-requisite to the successful application of
the model. At the same time use of this type of
model should help to elucidate the significance of
these underlying mechanisms. By incorporating a
direct link to the BLM of the acute toxicity of
metals, the SBM extends the utility of this
approach in a number of ways. While the focus of
the BLM is on the chemical interactions of water
quality characteristics on metal availability and
toxicity, the SBM adds an additional dimension,
focusing on the physiological interactions of water
quality characteristics with the organism itself.
With regard to calcium, Playle et al. showed
that it was not protective of gill Ag accumulation,
a result that is consistent with toxicity data that
show that Ca2q (and hardness generally) does not
effectively compete against silver to mitigate the
inhibition of sodium uptake that is caused by
silver. Here, we see that at high silver concentrations, where physical damage to the gill is believed
to have occurred, Ca2q appears to be protective in
a different way, by maintaining the integrity of the
gill structure, specifically the calcareous paracellular junctions.
An equimolar concentration of Cly is even more
protective than Ca2q at the elevated silver levels
considered herein, not only because it reduces free
silver, thereby reducing the inhibition of active
sodium uptake, but because the decrease in free
silver is also protective of the physical integrity of
the gill. Comparison of the results of experiments
with additions of KCl compared to NaCl shows
that Naq is also beneficial to the organism. In the
context of the BLM this benefit is a competitive
one, resulting in reduced inhibition of sodium
uptake kinetics, while in the SBM, there are two
additional benefits of increased levels of sodium
in the external water. These are the enhanced
uptake of sodium via the carrier-mediated uptake
system and, to a lesser degree, a decrease in
diffusive losses due to a decrease in the plasma–
water concentration gradient that controls diffusive
losses.
Finally, while the mechanism is not currently
included in the model, the conceptual framework
suggests, by analogy to sodium, that elevated
chloride levels may have additional physiological
benefits to aquatic organisms. That is, an increase
in the level of chloride would be expected to
facilitate chloride uptake via the carrier-mediated
uptake system and, to a limited degree in the
studies considered herein, it would also decrease
the blood–water concentration gradient of chloride, thereby reducing diffusive losses of chloride.
One of the interesting insights that the SBM
offers is that two very different dissolved LC50
values can have the same time to death and the
critical accumulation level at the biotic ligand,
need not be uniquely defined. This finding is
counter to one of the underlying premises of the
BLM that the LA50 value associated with a fixed
effect is invariant. The reason this may occur is
that there are other non-stressor related water
quality characteristics (e.g. the Naq concentration
in the water) which may affect the ability of the
organism to survive through a direct effect of a
metal on the physiological status of the organism
(e.g. Naq uptake kinetics), without necessarily
interacting with the metal at the site of action of
toxicity. To date, although such effects have been
successfully subsumed within the guise of the
chemical interactions incorporated in the BLM,
they are in fact significant physiological interactions that may, as an alternative, be treated explicitly within the context of the SBM. While adding
to the complexity of the overall analysis, by
considering these interactions in this manner the
potential utility of the BLM is enhanced.
While to some degree the conditions of the
experiments that were analyzed herein made it
possible to distinguish between the chemical and
physiologically processes that concurrently affect
metal availability and biological effects, this distinction was not totally unambiguous. Among the
things that will be needed in the future will be
experiments that are designed to clearly differentiate between those effects that are chemical in
nature, as are currently represented in the BLM
(e.g. competition of Ca2q or Naq with the metal
at the biotic ligand), and those that are more
physiological in nature, as exemplified in the SBM
(e.g. effects of Ca2q on permeability and Naq on
uptake kinetics). The chemical factors serve to
reduce metal availability and provide a first line
of defense for the organism, one that prevents the
manifestation of effects in the first place, while
the physiological factors alter the sensitivity of the
organism to the adverse effects of elevated concentrations of metals, when they are manifested.
In the interim, the BLM of acute toxicity subsumes
P.R. Paquin et al. / Comparative Biochemistry and Physiology Part C 133 (2002) 305–343
these concurrent chemical and physiological processes and related effects into the chemical interactions that are represented in the model. The fact
that it does this may account for some of the
residual uncertainty in BLM predictions, uncertainty that will ultimately be able to be reduced, or as
a minimum better understood, by further consideration of the physiological interactions that take
place.
It will also be of utmost importance in the future
to gain an improved understanding of the processes
that are involved in acclimation of the test organisms, both in the laboratory and the field, and to
introduce these processes into the model framework. This will be of particular utility in helping
to understand chronic effects that result from longterm, low-level exposures to metals. While not
currently included in the model framework
described herein, it is envisioned that the effects
of pH on Naq uptake, and HCO3y on Cly uptake
are additional refinements that will enhance the
applicability of the model and serve to further
elucidate the importance of the interactions of the
many chemical and physiological processes of
importance. Incorporation of osmoregulatory processes that control internal fluid transfers may also
be of use.
The demonstrated capability of the IBMySBM
framework to predict survival time under alternative exposure conditions is a useful feature of this
physiologically-based framework. However, perhaps of even greater importance is its potential
future utility as a framework for analyzing the
effects of time variable exposure conditions, residual after-effects of exposure to metals, acclimation,
chronic toxicity and species and genus sensitivity.
The development of a predictive model that
includes each of these capabilities will require
further refinements and a concerted, collaborative
effort by chemists, physiologists toxicologists and
modelers alike. However, this type of model should
be of great value to regulatory agencies that need
to consider species sensitivity distributions for
acute and chronic toxicity, and the magnitude,
frequency and duration of exceedances in developing refined WQC for metals. These same features will also provide the risk manager with an
improved tool for use in making risk management
decisions with respect to the assessment of the
expected effects of metals in aquatic settings.
339
Acknowledgments
This work was completed with the financial
support of the Eastman Kodak Company, Rochester, NY and the International Imaging Industry
Association, Harrison, NY. The helpful comments,
support and assistance of Mr Joseph Gorsuch of
Eastman Kodak Company and two anonymous
reviewers are also gratefully acknowledged.
References
Allen, H.E., Hall, R.H., Brisbin, T.D., 1980. Metal speciation,
effects on aquatic toxicity. Environ. Sci. Technol. 14, 441.
Allen, H.E., Hansen, D.L., 1996. The importance of trace
metal speciation to water quality criteria. Water Environ.
Res. 68, 42–54.
Anderson, D.M., Morel, F.M.M., March 1978. Copper sensitivity of Gonyaulax tamarensis. Limnol. Oceanogr. 23,
283–295.
Anner, B.M., Moosmayer, M., Imesch, E., 1992. Mercury
blocks Na–K–ATPase by a ligand-dependent and reversible
mechanism. Am. J. Physiol. 262, F830–F836.
Bergman, H.L., Dorward-King, E.J. 1997. Reassessment of
metals criteria for aquatic life protection: priorities for
research and implementation, Proceedings of the Pellston
Workshop on Reassessment of Metals Criteria for Aquatic
Life Protection. February 10–14, 1996, SETAC Press Pensacola, FL.
Bianchini, A., Grosell, M., Gregory, S.M., Wood, C.M., 2002.
Acute silver toxicity in aquatic animals is a function of
sodium uptake rate. Environ. Sci. Technol. 36, 1763–1766.
Breck, J.E., 1988. Relationship among models for acute toxic
effects: applications to fluctuating concentrations. Environ.
Toxicol. Chem. 7, 775–778.
Bury, N.R., McGeer, J.C., Wood, C.M., 1999a. Effects of
altering freshwater chemistry on physiological responses of
rainbow trout to silver exposure. Environ. Toxicol. Chem.
18, 49–55.
Bury, N.R., Galvez, F., Wood, C.M., 1999b. Effects of chloride,
calcium and dissolved organic carbon on silver toxicity:
comparison between rainbow trout and fathead minnows.
Environ. Toxicol. Chem. 18, 56–62.
Bushnell, P.G., Conklin, D.J., Duff, D.W., Olson, K.R., 1998.
Tissue and whole-body extracellular, red blood cell and
albumin spaces in the rainbow trout as a function of time:
a reappraisal of the volume of the secondary circulation. J.
Exp. Biol. 201, 1381–1391.
Campbell, P.G.C., 1995. Interactions between trace metals and
aquatic organisms: a critique of the free-ion activity model.
In: Tessier, A., Turner, D.R. (Eds.), Metal Speciation and
Bioavailability in Aquatic Systems. IUPAC, Wiley, New
York, pp. 45–102.
Campbell P.G.C., Paquin P.R., Adams W.J., Brix K.V., Juberg
D.R., Playle R.C., Ruffing C.J., Wentsel R.S., 2001. In:
A.W. Andren, T.W. Bober, (Eds.) Transport, Fate and Effects
of Silver in the Environment, Chapter 4: Risk Assessment,
Proceedings of Argentum Conference VI, University of
Wisconsin Sea Grant, Madison WI, August 21–25, 1999,
pp.103–148.
340
P.R. Paquin et al. / Comparative Biochemistry and Physiology Part C 133 (2002) 305–343
Connolly, J.P., 1985. Predicting single-species toxicity in natural water systems. Environ. Toxicol. Chem. 4, 573–582.
Curtis, B.J., Wood, C.M., 1991. The function of the urinary
bladder in vivo in the freshwater rainbow trout. J. Exp.
Biol. 155, 567–583.
Davies, P.H., Goettl, J.P., Sinley, J.R., 1978. Toxicity of silver
to rainbow trout (Salmo gairdneri). Water Res. 12, 113–117.
Davies P.H., 1997. Acute and chronic toxicity of silver to
aquatic life at different water hardnesses, Colorado Division
of Wildlife report, Fort Collins, CO.
D’Cruz, L.M., Wood, C.M., 1998. The influence of dietary
salt and energy on the response to low pH in juvenile
rainbow trout. Physiol. Zool. 71, 642–657.
Di Toro D.M., Allen H.E., Bergman H.L., Meyer J.S., Paquin
P.R., Santore R.C., April 1999. A biotic ligand model of the
acute toxicity of metals. I. Technical Basis, Section 3 in
Integrated Approach to Assessing the Bioavailability and
Toxicity of Metals in Surface Waters and Sediments, A
report to the EPA Science Advisory Board, Office of Water,
Office of Research and Development, Washington, DC, pp.
3–1 to 3–26. USEPA-822-E-99-001.
Di Toro D.M., Allen H.E., Bergman H.L., Meyer J.S., Paquin
P.R., Santore R.C., August 2000. The biotic ligand model:
a computational approach for assessing the ecological effects
of metals in aquatic systems, published by the International
Copper Association, Ltd. Environmental Program, as part
of its series on Copper in the Environment and Health.
Di Toro, D.M., Allen, H.E., Bergman, H.L., Meyer, J.S.,
Paquin, P.R., Santore, R.C., 2001. A biotic ligand model of
the acute toxicity of metals. I. Technical basis. Environ.
Toxicol. Chem. 20, 2383–2396.
Erickson R.J., Benoit D.A., Mattson V.R., September 5, 1996.
A prototype toxicity factors model for site-specific copper
water quality criteria, manuscript prepared for USEPA, ERLDuluth, MN.
European Commission, 1996. Technical Guidance Document
in Support of Commission Directive 93y67yEEC on Risk
Assessment for New Notified Substances and Commission
Regulation (EC) No 1488y94 on Risk Assessment for
Existing Substances, Part II, Office for Official Publications
of the European Communities, Luxembourg.
Galvez, F., Wood, C.M., 1997. The relative importance of
water hardness and chloride levels in modifying the acute
toxicity of silver to rainbow trout (Oncorhynchus mykiss).
Environ. Toxicol. Chem. 16, 2363–2368.
Galvez, F., Hogstrand, C., Wood, C.M., 1998. Physiological
responses of juvenile rainbow trout to chronic low level
exposures of waterborne silver. Comp. Biochem. Physiol.
119C, 131–137.
Goss, G.G., Wood, C.M., 1990a. Naq and Cly uptake kinetics,
diffusive effluxes and acidic equivalent fluxes across the
gills of rainbow trout: 1. Responses to environmental hyperoxia. J. Exp. Biol. 152, 521–548.
Goss, G.G., Wood, C.M., 1990b. Naq and Cly uptake kinetics,
diffusive effluxes and acidic equivalent fluxes across the
gills of rainbow trout: II. Responses to bicarbonate loading.
J. Exp. Biol. 152, 549–571.
Grosell, M., Hogstrand, C., Wood, C.M., Hansen, H.J.M.,
2000. A nose-to-nose comparison of the physiological
effects of exposure to ionic silver versus silver chloride in
the European eel (Anguilla anguilla) and the rainbow trout
(Oncorhynchus mykiss). Aquat. Toxicol. 48, 327–342.
Grosell M., Nielsen C., Bianchini A., 2002. Sodium turnover
rate determines sensitivity to acute copper and silver exposure in freshwater animals, Comp. Biochem. Physiol. C,
133, 287–303.
Hoar, W.S., Randall, D.J., 1984. Fish physiology: gills, part B,
ion and water transfer. In: Hoar, W.S., Randall, D.J., Farrell,
A.P. (Eds.), Fish Physiology, vol. 10. Academic Press, New
York.
Hogstrand, C., Galvez, F., Wood, C.M., 1996. Toxicity, silver
accumulation and metallothionein induction in freshwater
rainbow trout during exposure to different silver salts.
Environ. Toxicol. Chem. 15, 1102–1108.
Hogstrand, C., Wood, C.M., 1998. Towards a better understanding of the bioavailability, physiology, and toxicity of
silver in fish: implications for water quality criteria. Environ.
Toxicol. Chem. 17, 547–561.
Holmes, W.N., Donaldson, E.M., 1969. The body compartments and the distribution of electrolytes. In: Hoar, W.S.,
Randall, D.J. (Eds.), Fish Physiology, vol. 1, Excretion,
Ionic Regulation, and Metabolism. Academic Press, Orlando, FL, pp. 1–89.
Hussain, S., Meneghini, E., Moosmayer, M., Lacotte, D.,
Anner, B.M., 1994. Potent and reversible interaction of
silver with pure Na, K-ATPase and Na, K-ATPase-liposomes. Biochim. Biophys. Acta 1190, 402–408.
Janes, N., Playle, R.C., 1995. Modeling silver binding to gills
of rainbow trout (Oncorhynchus mykiss). Environ. Toxicol.
Chem. 14, 1847–1858.
Keys, A.B., 1931. Chloride and water secretion and absorption
by the gills of the eel. Z. Vergl. Physiol. 15, 364–388.
Keys, A.B., Wilmer, E.N., 1932. ‘Chloride secreting cells’ in
the gills of fishes with special reference to the common eel.
J. Physiol. (London) 76, 368–378.
Kirschner, L.B., 1979. Control mechanisms in crustaceans and
fishes. In: Gilles, R. (Ed.), Mechanisms of Osmoregulation
in Animals: Maintenance of Cell Volume. Wiley, New York,
pp. 157–222.
Kirschner, L.B., 1988. Basis for apparent saturation kinetics
of Naq influx in freshwater hyperregulators. Am. J. Physiol.
254, R984–R988.
Krogh, A., 1938. The active transport of ions in some freshwater animals. Z. Vergl. Physiol. 25, 335–350.
Krogh A., 1939. Osmotic regulation in aquatic animals, Cambridge University Press. Reprinted from: in an Unabridged
and Unaltered, Dover Publications, Inc., New York, 242
(1965) (reprint).
LeBlanc, G.A., Mastone, J.D., Paradice, A.P., Wilson, B.F.,
Lockhart, H.B., Robillard, K.A., 1984. The influence of
speciation on the toxicity of silver to fathead minnow
(Pimephales promelas). Environ. Toxicol. Chem. 3, 37–46.
Lewis, S.D., Lewis, W.M., 1971. The effect of zinc and copper
on the osmolality of blood serum of the channel catfish,
Ictalurus punctatis Rafinesque and golden shiner Notemigonus crysoleucas Mitchell. Trans. Am. Fish Soc. 100,
639–643.
MacRae R.K. 1994. The copper binding affinity of rainbow
trout (Oncorhynchus mykiss) and brook trout (Salvelinus
fontinalis) gills. MSc thesis, Department of Zoology and
Physiology, University of Wyoming.
P.R. Paquin et al. / Comparative Biochemistry and Physiology Part C 133 (2002) 305–343
MacRae, R.K., Smith, D.E., Swoboda-Colberg, N., Meyer,
J.S., Bergman, H.L., 1999. Copper binding affinity of
rainbow trout (Oncorhynchus mykiss) and brook trout (Salvelinus fontinalis) gills. Environ. Toxicol. Chem. 18,
1180–1189.
Mancini, J.L., 1983. A method for calculating effects, on
aquatic organisms, of time varying concentrations. Water
Res. 17, 1355–1362.
Mantel, L.H., Farmer, L.L., 1983. Osmotic and ionic regulation, in internal anatomy and physiological regulation. In:
Mantel, L.H. (Ed.), The Biology of Crustacea, vol. 5.
Academic Press, pp. 53–161.
Marr, J.C.A., Hansen, J.A., Meyer, J.S., et al., 1998. Toxicity
of cobalt and copper to rainbow trout: applications of a
mechanistic model for predicting survival. Aquat. Toxicol.
4, 225–237.
McCarty L.S., 1987. Relationship between toxicity and bioconcentration for some organic chemicals. I. Examination
of the relationship, In: Kaiser K.L.E., (Ed.), QSAR in
Environmental Toxicology, Volume II, C. Reidel Publishing
Company, Dordrecht, the Netherlands, pp. 207–220.
McCarty, L.S., Mackay, D., Smith, A.D., Ozburn, G.W., Dixon,
D.G., 1993. Residue-based interpretation of toxicity and
bioconcentration QSARs from aquatic bioassays: polar narcotic organics. Ecotoxicol. Environ. Safety 25, 253–270.
McDonald, D.G., Wood, C.M., 1981. Branchial and renal acid
and ion fluxes in the rainbow trout, Salmo gairdneri, at low
environmental pH. J. Exp. Biol. 93, 101–118.
McDonald, D.G., Hobe, H., Wood, C.M., 1980. The influence
of calcium on the physiological responses on the rainbow
trout, Salmo gairdneri to low environmental pH. J. Exp.
Biol. 88, 109–131.
McDonald, D.G., 1983a. The effects of Hq upon the gills of
freshwater fish. Can. J. Zool. 61, 691–703.
McDonald, D.G., 1983b. The interaction of environmental
calcium and low pH on the physiology of the rainbow trout,
Salmo gairdneri I. Branchial and renal net ion and Hq
fluxes. J. Exp. Biol. 102, 123–140.
McDonald, D.G., Walker, R.L., Wilkes, P.R.H., 1983. The
interaction of environmental calcium and low pH on the
physiology of the rainbow trout, Salmo gairdneri II. Branchial ionoregulatory mechanisms. J. Exp. Biol. 102,
141–155.
McDonald, D.G., Rogano, M.S., 1986. Ion regulation by
rainbow trout, Salmo gairdneri in ion-poor water. Physiol.
Zool. 59, 318–331.
McDonald D.G., Reader J.P., Dalziel T.R.K., 1989. The combined effects of pH and trace metals on fish ionoregulation.
In: Morris R., Taylor E.W., Brown D.J.A., Brown J.A.,
(Eds.) Acid Toxicity and Aquatic Animals. Soc. Exp. Biol.
Seminar Series, Vol. 34, Cambridge University Press, Cambridge, UK, pp. 221–242.
McDonald, D.G., Freda, J., Cavdek, V., Gonzalez, R., Zia, S.,
1991. Interspecific differences in gill morphology of freshwater fish in relation to tolerance of low-pH environments.
Physiol. Zool. 64, 124–144.
McDonald, D.G., Wood, C.M., 1993. Branchial mechanisms
of acclimation to metals in freshwater fish. In: Rankin, J.C.,
Jensen, F.B. (Eds.), Fish Ecophysiology. Chapman and Hall,
London, pp. 297–321.
341
McGeer, J.C., Wood, C.M., 1998. Protective effects of water
Cly on physiological responses to waterborne silver in
rainbow trout. Can. J. Fish. Aquat. Sci. 55, 2447–2454.
McGeer, J.C., Playle, R.C., Wood, C.M., Galvez, F., 2000. A
physiologically based biotic ligand model for predicting the
acute toxicity of waterborne silver to rainbow trout in
freshwaters. Environ. Sci. Technol. 34, 4199–4207.
Meyer, J.S., Gulley, D.D., Goodrich, M.S., Szmania, D.C.,
Brooks, A.S., 1995. Modeling toxicity due to intermittent
exposure of rainbow trout and common shiners to monochloramine. Environ. Toxicol. Chem. 14, 165–175.
Meyer, J.S., Santore, R.C., Bobbitt, J.P., et al., 1999. Binding
of nickel and copper to fish gills predicts toxicity when
water hardness varies, but free-ion activity does not. Environ. Sci. Technol. 33, 913–916.
Michaelis, L., Menten, M.L., 1913. Die kinetik der inwertin
wirkung. Biochem. Z. 333.
Milligan, C.L., Wood, C.M., 1982. Disturbances in haematology, fluid volume distribution and circulatory function associated with low environmental pH in the rainbow trout,
Salmo gairdneri. J. Exp. Biol. 99, 397–415.
Morel, F.M., 1983. Complexation: trace metals and microorganisms.Principles of Aquatic Chemistry. Wiley Interscience, New York, pp. 301–308.
Morgan, I.J., Henry, R.P., Wood, C.M., 1997. The mechanism
of acute silver nitrate toxicity in freshwater rainbow trout
(Oncorhynchus mykiss) is inhibition of gill Naq and Cly
transport. Aquat. Toxicol. 38, 145–163.
Nichols, D.J., 1987. Fluid volumes in rainbow trout, Salmo
gairdneri: application of compartmental analysis. Comp.
Biochem. Physiol. 87A, 703–709.
Olson, K.R., 1992. Blood and extracellular fluid volume
regulation: role of the renin-angiotensin system, kallikreinkinin system, and atrial natriuretic peptides. In: Hoar, W.S.,
Randall, D.J., Farrell, A.P. (Eds.), Fish Physiology, Vol 12,
Part B, The Cardiovascular System. Academic Press, New
York, pp. 135–254.
Packer, R.K., Dunson, W.A., 1970. Effects of low environmental pH on blood pH and sodium balance of brook trout. J.
Exp. Zool. 174, 65–72.
Packer, R.K., Dunson, W.A., 1972. Anoxia and sodium loss
associated with the death of brook trout at low pH. Comp.
Biochem. Physiol. 41A, 17–26.
Pagenkopf, G.K., Russo, R.C., Thurston, R.V., 1974. Effect of
complexation on toxicity of copper to fishes. J. Fish REs
Bd., Canada 31, 462–465.
Pagenkopf, G.K., 1983. Gill surface interaction model for
trace-metal toxicity to fishes: role of complexation, pH, and
water hardness. Environ. Sci. Technol. 17, 342–347.
Paquin P.R., Di Toro D.M., Santore R.C., Trivedi D., Wu K.B.,
April 1999. A biotic ligand model of the acute toxicity of
metals. III. Application to fish and Daphnia exposure to
silver, Section 3 in Integrated Approach to Assessing the
Bioavailability and Toxicity of Metals in Surface Waters
and Sediments, a submission to the EPA Science Advisory
Board, Office of Water, Office of Research and Development, Washington, DC, pp. 3–59 to 3–102. USEPA-822-E99-001.
Paquin P.R., Gorsuch, J.W., Apte, S., Batley, G.E., Bowles,
K.C., Campbell, P.G.C., Delos, C.G., Di Toro, D.M., Dwyer,
R.L., Galvez, F., Gensemer, R.W., Goss, G.G., Hogstrand,
342
P.R. Paquin et al. / Comparative Biochemistry and Physiology Part C 133 (2002) 305–343
C., Janssen, C.R., McGeer, J.C., Naddy, R.B., Playle, R.C.,
Santore, R.C., Schneider, U., Stubblefield, W.A., Wood,
C.M., Wu, K.B., 2002. The biotic ligand model. Comp.
Biochem. Physiol. C, 133, 3–35.
Perry, S.F., 1997. The chloride cell: structure and function in
the gills of freshwater fishes. Annu. Rev. Physiol. 59,
325–347.
Playle, R.C., Wood, C.M., 1989a. Water chemistry changes in
the gill micro-environment of rainbow trout: experimental
observations and theory. J. Comp. Physiol. B 159, 527–537.
Playle, R.C., Wood, C.M., 1989b. Water pH and aluminum
chemistry in the gill micro-environment of rainbow trout
during acid and aluminum exposures. J. Comp. Physiol. B
159, 539–550.
Playle, R.C., Wood, C.M., 1991a. Mechanism of aluminum
extraction and accumulation at the gills of rainbow trout,
Oncorhynchus mykiss (Walbaum), in acidic soft water. J.
Fish Biol. 38, 791–805.
Playle, R.C., Gensemer, R.W., Dixon, D.G., 1992. Copper
accumulation on gills of fathead minnows: influence of
water hardness, complexation and pH on the gill microenvironment. Environ. Toxicol. Chem. 11, 381–391.
Playle, R.C., Dixon, D.G., Burnison, K., 1993a. Copper and
cadmium binding to fish gills: modification by dissolved
organic carbon and synthetic ligands. Can. J. Fish. Aquat.
Sci. 50, 2667–2677.
Playle, R.C., Dixon, D.G., Burnison, K., 1993b. Copper and
cadmium binding to fish gills: estimates of metal-gill stability constants and modeling of metal accumulation. Can.
J. Fish. Aquat. Sci. 50, 2678–2687.
Schwartz, M.L., Playle, R.C., 2001. Adding magnesium to the
silver-gill binding model for rainbow trout (Oncorhynchus
mykiss). Environ. Toxicol. Chem. 20, 467–472.
Potts, W.T.W., Parry, G., 1964. Osmotic and Ionic Regulation
in Animals. Pergamon Press, London.
Potts, W.T.W., 1984. Transepithelial potentials in fish gills. In:
Hoar, W.S., Randall, D.J. (Eds.), Fish Physiology, vol. 10B.
Academic Press, Orlando, FL, Chapter 4.
Potts, W.T.W., 1994. Kinetics of sodium uptake in freshwater
animals: a comparison of ion-exchange and proton pump
hypotheses. Am. J. Physiol. 266, R315–R320.
Roy, R.R., Campbell, P.G.C., 1995. Survival time modeling of
exposure of juvenile Atlantic salmon (Salmo salar) to
mixtures of aluminum and zinc in soft water at low pH.
Aquat. Toxicol. 33, 155–176.
Rodriguez P., Torres J.C., Correa J., Villavicencio G., Carvajal
C., Roa P., Urrestarazu P., September 2001. Progress Report
to CIMMyICA on the application of the to Chilean freshwater conditions.
Santore R.C., Driscoll C.T., 1995. The CHESS model for
calculating chemical equilibria in soils and solutions, chemical equilibrium and reaction models, The Soil Society of
America, SSSA Special Publication 42, American Society
of Agronomy.
Santore, R.C., Di Toro, D.M., Paquin, P.R., Allen, H.E., Meyer,
J.S., 2001. A biotic ligand model of the acute toxicity of
metals. II. Application to acute copper toxicity in freshwater
fish and daphnia. Environ. Toxicol. Chem. 20, 2397–2402.
Smith, H.W., 1930. The absorption and excretion of water and
salts by marine teleosts. Am. J. Physiol. 93, 480–505.
Steffenson, J.F., Lomholt, J.P., 1992. The secondary vascular
system. In: Hoar, W.S., Randall, D.J., Farrell, A.P. (Eds.),
Fish Physiol, vol. 12, Part A, The Cardiovascular System.
Academic Press, New York, pp. 185–217.
Stubblefield W.A., Hockett J.R., Kramer J.R., Wood C.M.,
Paquin P.R., Gorsuch J.W., 2000. Chronic silver toxicity:
water quality parameters as modifying factors, Annual
SETAC Meeting, Nashville, TN.
Sunda, W.G., Guillard, R.R.L., 1976. BLM relationship
between cupric ion activity and the toxicity of copper to
phytoplankton. J. Mar. Res. 34, 511–529.
Sunda, W.G., Lewis, J.A.M., 1978. Effect of complexation by
natural organic ligands on the toxicity of copper to a
unicellular alga, Monochrysis lutheri. Limnol. Oceanogr. 23,
870–876.
Sunda, W.G., Engel, D.W., Thoutte, R.M., 1978. Effect of
chemical speciation on toxicity of cadmium to grass shrimp,
Palaemonetes pugio: importance of free Cd ion. Environ.
Sci. Technol. 12, 409–413.
Sunda, W.G., Gillespie, P.A., 1979. The response of a marine
bacterium to cupric ion and its use to estimate cupric ion
activity in seawater. J. Mar. Res. 37, 761–777.
Szumski D.S., Barton D.A., 1983. Development of a mechanistic model of acute heavy metal toxicity, In: Bishop W.E.,
Cardwell R.D., Heidolph B.B., (Eds.) Aquatic Toxicology
and Hazard Assessment: Sixth Symposium, ASTM STP
802, ASTM Publication Code Number (PCN) 04-80200016, Philadelphia, PA, pp. 42–72.
Taylor, E.W., Beaumont, M.W., Butler, P.J., Mair, J., Mujallid,
M.S.I., 1996. Lethal and sub-lethal effects of copper upon
fish: a role for ammonia toxicity. In: Taylor, E.W. (Ed.),
Toxicology of Aquatic Pollution: Physiological, Cellular and
Molecular Approaches. Cambridge University Press, Cambridge, pp. 85–113.
Tipping, E., 1994. WHAM—a chemical equilibrium model
and computer code for waters, sediments, and soils incorporating a discrete siteyelectrostatic model of ion-binding
by humic substances. Comput. Geosci. 20, 973–1023.
USEPA, April 6–7, 1999. Integrated Approach to Assessing
the Bioavailability and Toxicity of Metals in Surface Waters
and Sediments, a report to the EPA Science Advisory Board,
Office of Water, Office of Research and Development,
Washington, DC, EPA-822-E-99-001.
Verhaar, H.J.M., de Wolfe, W., Dyer, S., Legierse, K.C.H.M.,
Seinen, W., Hermens, J.L.M., 1999. An LC50 vs time model
for the aquatic toxicity of reactive and receptor-mediated
compounds. Consequences for bioconcentration kinetics and
risk assessment. Environ. Sci. Technol. 33, 758–763.
Vogel, W.O.P., 1985. Systemic vascular anastomoses, primary
and secondary vessels in fish, and the phylogeny of lymphatics. In: Johansen, K., Burggren, W.W. (Eds.), Cardiovascular Shunts-A. Benzon Symposium 21. Munksgaard,
Copenhagen, pp. 143–159.
Webb, N.A., Wood, C.M., 1998. Physiological analysis of the
stress response associated with acute silver nitrate exposure
in freshwater rainbow trout (Oncorhynchus mykiss). Environ. Toxicol. Chem. 17, 579–588.
Wilson, R.W., Taylor, E.W., 1993a. The physiological
responses of freshwater rainbow trout, Oncorhynchus
mykiss, during acutely lethal copper exposure. J. Comp.
Physiol. B 163, 38–47.
P.R. Paquin et al. / Comparative Biochemistry and Physiology Part C 133 (2002) 305–343
Wilson, R.W., Taylor, E.W., 1993b. Differential responses to
copper in rainbow trout (Oncorhynchus mykiss) acclimated
to sea water and brackish water. J. Comp. Physiol. B 163,
239–246.
Wood, C.M., Randall, D.J., 1973. Sodium balance in the
rainbow trout (Salmo gairdneri) during extended exercise.
J. Comp. Physiol. 82, 235–256.
Wood C.M., McDonald D.G., 1982. Physiological mechanisms
of acid toxicity to fish, In: Johnson R.E., (Ed.) Acid Rainy
Fisheries, Proceedings of an International Symposium on
Acidic Precipitation and Fishery Impacts in Northeastern
North America, Cornell University, Ithaca, NY, August 2-5,
1981, American Fisheries Society, Bethesda, MD, pp. 197–
226.
Wood C.M., 1989. The physiological problems of fish in acid
waters, In: Morris R., Taylor E.W., Brown D.J.A., Brown
J.A., (Eds.) Acid Toxicity and Aquatic Animals. Soc. Exp.
Biol. Seminar Series, Vol. 34, Cambridge University Press,
Cambridge, UK, pp.125–152.
Wood, C.M., 1992. Flux measurements as indices of Hq and
metal effects on freshwater fish. Aquat. Toxicol. 22,
239–264.
343
Wood, C.M., Shuttleworth, T.J., 1995. Cellular and molecular
approaches to fish ionic regulation. In: Hoar, W.S., Randall,
D.J., Farrell, A.P. (Eds.), Fish Physiology, vol. 14. Academic
Press.
Wood, C.M., Hogstrand, C., Galvez, F., Munger, R.S., 1996.
The physiology of waterborne silver toxicity in freshwater
rainbow trout (Oncorhynchus mykiss) 1. The effects of ionic
Agq. Aquat. Toxicol. 35, 93–109.
Wood, C.M., Playle, R.C., Hogstrand, C., 1999. Physiology
and modeling of the mechanisms of silver uptake and
toxicity in fish. Environ. Toxicol. Chem. 18, 71–83.
Zadunaisky J.A., 1997. Gill chloride cells activation by plasma
osmolarity, In: Potts W.T.W., Hazon N., Eddy F.B., Flik G.,
(Eds.) Ionic Regulation in Animals: a Tribute to Professor,
Springer-Verlag, Berlin, pp. 87–105.
Zitko, V., Carson, W.V., Carson, W.G., 1973. Prediction of
incipient lethal levels of copper to juvenile Atlantic salmon
in the presence of humic acid by cupric electrode. Bull.
Environ. Contam. Toxicol. 10, 265–271.
Zitko V., 1976. Structure-activity relations and the toxicity of
trace elements to aquatic biota, Proceeding of the Toxicity
to Biota of Metal Forms in Natural Water, International
Joint Commission, pp. 9–32.