Clements: “3357_c009” — 2007/11/9 — 12:41 — page 135 — #1 9 Lethal Effects 9.1 OVERVIEW When toxicologists added the prefix eco to the field of toxicology, so that the word became ecotoxicology, they continued primarily to make the same measurements they made before the name changed. (Cairns 1992) Death can result from acute or chronic exposures to toxicants contained in many diverse sources. The distinction between acute and chronic exposure duration, adopted from human toxicology, is based as much on pragmatism as sound toxicology. A lethal exposure is customarily categorized as acute if it is a relatively brief and intense one to a poison. Standard durations are espoused for conducting acute lethality tests. For example, Sprague (1969) argued for 96 h after observing that “For 211 of 375 toxicity tests reviewed, acute lethal action apparently ceased with 4 days, although this tabulation may have been biased ” This kind of correlative analysis and the convenience of fitting a test within the workweek motivated the initial codification of a 96-h test. It is important to note that Sprague stated in his 1969 monograph that his intentions were to describe “profitable bioassay methods” about which there was ample “room for healthy disagree- ment.” Along the vein of healthy disagreement, one could conclude from these same data that a 96-h duration was insufficient for characterizing acute lethality in more than 4 out of 10 tests (Figure 9.1). Further, Sprague notes that the tests considered in making his recommendation included many static tests 1 in which toxicant concentrations probably decreased substantially during the exposures and that those results from continuous flow tests that had much less chance of substantial toxicant con- centration decrease during the tests generally indicated a longer duration was needed than did the static tests. Given the urgency in the 1960s for standard tools for dealing with pervasive pollution, the assumption that mortality by 96 h accurately reflected that occurring during any acute exposure duration is an understandable regulatory stance. However, it is scientifically indefensible and insuf- ficient for today’s needs. Consequently, many thoughtful ecotoxicologists now generate lethal effect metrics several times during acute toxicity tests. 2 And, as we will see, alternative approaches exist that avoid this issue altogether. A similar blend of science and pragmatism contributed to the current selection of test durations for chronic exposures. By recent convention, chronic exposure occurs if exposure duration exceeds 10% of an organism’s lifetime (Suter 1993); however, this has not always been the convention and 10% is an arbitrary cut-off point. Consequently, other durations are specified in some standard chronic test protocols and associated results are reported throughout the peer-reviewed literature. Test protocols have emerged for exposures differing relative to the medium containing the tox- icant(s) as well as exposure duration. For example, test protocols for acute (e.g., EPA 2002a) and chronic (e.g., EPA 2002b) water exposures quantify lethality under these two general categories of exposure duration. Exposures occur by oral, dermal, and respiratory routes, and accordingly, testing techniques have emerged that accommodate these routes (e.g., EPA (2002) for sediments). 1 Generally, the toxicant is introduced into the test tanks at the beginning of a static aquatic toxicity test and not renewed for the test duration. Such tests are often characterized by substantial decreases in toxicant concentrations as the toxicant degrades, volatilizes, adsorbs to solids, or otherwise leaves solution. Such dosing problems in early, static tests have been reduced in current techniques by either periodic renewal of toxicant solutions or supplying a continuous flow of toxicant solution into exposure tanks (see for more detail Buikema et al. 1982). 2 Sprague (1969) recommended this strategy to increase the information drawn from acute lethality tests. 135 © 2008 by Taylor & Francis Group, LLC Clements: “3357_c009” — 2007/11/9 — 12:41 — page 136 — #2 136 Ecotoxicology: A Comprehensive Treatment 125 100 75 50 25 0 Number of days (or less) Number of toxicity tests <1 <2 <4 >4 >7 >14 FIGURE 9.1 The number ofearlytoxicity tests tabulatedby Sprague (1969) inwhich acute mortality appeared to be completely expressed in exposed individuals by the specified exposure duration. Sprague noted that this data set included results from many static exposure tests in which the toxicant solutions were not changed and, as a consequence, the toxicant concentrations likely decreased substantially during testing. The tests are categorized here based on the time interval thought to be adequate for full expression of acute mortality, for example, “<1” = complete acute lethality expressed in 1 day or shorter. Unfortunately, standard methods incorporating predictions of mortality from pulsed exposures are yet to be codified, but methods for dealing with these exposure scenarios are becoming increasingly seen as necessary to consider by ecological risk assessors. Those accommodating simultaneous exposure to several sources are also less common than warranted. Approaches for characterizing or predicting lethal effects of single toxicant exposures are well established although some potentially useful approaches have yet to be explored sufficiently. This being the case, conventional and emerging approaches will be described in this chapter after dis- cussion of some examples of lethality as manifested at the whole organism level of biological organization. 9.1.1 DISTINCT DYNAMICS ARISING FROM UNDERLAYING MECHANISMS AND MODES OF ACTION Molecular, cellular, anatomical, and physiological alterations that contribute to somatic death were sketched out in preceding chapters. Here, organismal consequences of such processes as nar- cosis, uncoupling of oxidative phosphorylation, and general stress will be explored. Hopefully, these examples demonstrate that all lethal responses to poisonings are not identical and that under- standing the suborganismal processes resulting from exposure is extremely helpful for predicting consequences to individuals and populations. Narcosis is often described as a reversible, chemically induced decrease in general nervous system functioning. The decrease in nervous system function results from disruption of nerve cell membrane functioning in higher animals as explained earlier (Chapter 3, Section 3.10); however, narcotic effects due to pervasive membrane dysfunction also manifest as a general depression of biological activity inorganisms lacking nervoussystems. Narcosis ofsufficient intensity andduration lowers biological activities of any organism below those essential to maintaining the soma, resulting in death. But, because narcosis is reversible, postexposure mortality may be low relative to that resulting from damage which requires more time to repair. For example, grass shrimp (Palaemonetes pugio) acutely exposed for 48 or 60 h to polycyclic aromatic hydrocarbons (1-ethylnaphthalene, © 2008 by Taylor & Francis Group, LLC Clements: “3357_c009” — 2007/11/9 — 12:41 — page 137 — #3 Lethal Effects 137 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 0 20 40 60 80 100 120 Proportion dead Time (h) Exposure Postexposure Control 0.2 mg/L 0.3 mg/L 0.4 mg/L 0.6 mg/L FIGURE 9.2 Cumulativemortality, includingpostexposuremortality, ofamphipods (Hyalella azteca) exposed to four concentrations of dissolved copper. (Modified panel from Figure 1 of Zhao and Newman (2004).) Note that substantial mortality occurred after copper exposure ended. 2,6-dimethylnaphthalene, and phenanthrene) showed minimal postexposure mortality (Unger et al. 2007). In contrast, mortality experienced by amphipods (Hyalella azteca) after exposure to dissolved copper was quite high (Figure 9.2) because, as discussed in previous chapters, metals cause extensive biochemical, cellular, and tissue damage that takes considerable time to repair (Zhao and Newman 2004). Another specific mechanism that can produce mortality is oxidative phosphorylation uncoupling. Such disruption of this essential mitochondrial process is typical of many substituted phenols (see Chapter 3, Section 3.9). At the organismal level, consequences range from elevated blood pH to disruption of normal respiratory processes to somatic death. Like the narcosis-related mortality just described, there can be minimal postexposure death in an exposed population. For example, amphipods acutely exposed to sodium pentachlorophenol showed minimal postexposure mortality (Zhao and Newman 2004). The pentachlorophenol is quickly eliminated from this amphipod and effects are reversible (Nuutinen et al. 2003). Mosquitofish (Gambusia holbrooki) acutely exposed to pentachlorophenol showed similar minimal postexposure mortality for the same reasons (Newman and McCloskey 2000). In contrast to the lethal dynamics of such poisons, some toxicants cause pervasive changes or damage that requires considerable time to recover. The copper damage that resulted in the post- exposure mortality shown in Figure 9.2 is one example. The tissue damage resulting from metal exposure took considerable time to repair and, consequently, mortality continued well beyond ter- mination of exposure. Similarly, mosquitofish (G. holbrooki) acutely exposed to high concentrations of sodium chloride showed prolonged and high postexposure mortality (Newman and McCloskey 2000). The cellular and tissue damage caused by the associated isomotic and ionic conditions takes time to repair. Fish, succumbing after exposure ends, did not have enough time or energy reserves to recuperate. The nature of the lethal response can vary in other important ways. Some toxicants will display a concentration or dose threshold below which no lethal consequences are apparent. Mosquitofish exposure to high concentrations of sodium chloride is one obvious example in which death will not occur as long as the individual is able to osmo- and ionoregulate sufficiently at the particular sodium chloride concentration. However, the energetic burden imposed on the individual might © 2008 by Taylor & Francis Group, LLC Clements: “3357_c009” — 2007/11/9 — 12:41 — page 138 — #4 138 Ecotoxicology: A Comprehensive Treatment result in decreased fitness in other aspects of the individual’s life cycle. In addition, some, but not all, toxicants are characterized by a minimum time to die: the individual simply cannot die faster than this threshold time regardless of the exposure concentration or dose (Gaddum 1953). The presence and magnitude of a threshold time depends on the toxicant’s bioaccumulation kinetics and the suborganismal nature of its effect upon any particular species or individual. Complete freedom from stress is death. (Selye 1973) The somatic deaths described above involved specific modes of action but some somatic deaths involve the general stress process. Like the inappropriate toxicant-induced apoptosis described in Chapter 4 (Section 4.2.1) or the adverse consequences of inflammation described in Chapter 4 (Section 4.2.3), inappropriate or inadequate expression of the body’s general reaction to stressors can lead to death of individuals. Such somatic death is said to result from what Selye (1984) described as a disease of adaptation. Regardless of the stressor, the body invokes a general suite of reactions that, because of their universal presence and integrative nature, merit detailed discussion at the level of the individual. 3 The endocrinologist Hans Selye was the first to describe biological stress (Selye 1936). He defined stress as all nonspecific responses induced by intense demands placed on the organism. He named the associated syndrome, the general adaptation syndrome (GAS) (Selye 1950). The GAS has three phases: the alarm reaction, resistance, and exhaustion phases. The alarm phase is easily recognized as the immediate one in which the soma’s resources are mustered suddenly to cope with a stressor. Rapid hormonal changes cause an organism’s pulse and blood pressure to increase, putting it into a “flight or fight” state that takes considerable energy to maintain. Other immediate changes include those to breathing, blood flow to muscles, the immune system, behavior, and even, memory.At the cellular level, secretory granules discharge from cells of the adrenal cortex (Selye 1950). Characteristics emerging later in the resistance phase that Selye first identified in stressed rats are adrenal cortex enlargement with reappearance of normal levels of secretory granules, thymus and lymph node atrophy, and appearance of gastric ulcers. In mammals, such changes are brought about by the hypothalamic-pituitary-adrenal system’s response to a stressor (see Tsigos and Chrousos (2002) for details). Analogous systems are involved in other vertebrates (i.e., the hypothalamo-pituitary-interrenal system of fishes and amphibians). The glucocorticoid cortisol and the catecholamines dopamine, norepinephrine, and epinephrine are prominent facilitators of the stress response. The resistance or adaptation phase is reached only if stress is sufficiently prolonged, resulting inorganand physiological changessuchas those mentionedabove. These shifts areintended to resist changes associated with a stressor by using less energy than changes associated with the alarm phase, and also, to maintain homeostasis. Examples of changes are adrenal gland enlargement to produce glucocorticoids that modify metabolism and also shifts in the immune system so that the body generally has reduced ability to express an inflammation response. 4 Selye refers to this state of artificially increased homeostasis as heterostasis. If stress continues and eventually exceeds the individual’s finite adaptive energy, the exhaustion phase is entered in which the individual gradually loses its ability to maintain any semblance of essential stasis in the presence of the stressor. 3 A reasonable argument could be made that this issue, because of the essential role played by hormones, should have been discussed in Chapter 6. However, the associated processes involve the integration of many biochemicals, organs, tissues, and organ systems within the individual, so it is more appropriate to discuss it here. The fact that it could be covered in either chapter attests to the soundness of the central theme of this book that making linkages among levels of biological organization is important and possible in ecotoxicology. 4 The body’s response to a local stressor is called a Local Adaptation Syndrome (LAS) and will be coordinated within the GAS. An example of such coordination is the influence of the GAS on the degree to which the body expresses inflammation locally in a damaged tissue. © 2008 by Taylor & Francis Group, LLC Clements: “3357_c009” — 2007/11/9 — 12:41 — page 139 — #5 Lethal Effects 139 Box 9.1 The Pharmacologist of Dirt As a University of Prague medical student in 1925, Selye noticed a consistent syndrome with patients suffering from different, but intense, demands on their bodies (Selye 1973, 1984). A decade later as a young researcher studying sex hormones, he saw the same syndrome mani- fest in laboratory rats after injection with ovarian extracts. Rats showed a distinct syndrome in which the adrenal cortex enlarged, lymphatic structures (thymus, spleen, and lymph nodes) shrunk, and stomach ulcers appeared. He later found that injection of extracts from other tissues and even formalin elicited this same syndrome. Because his original intent had been to identify novel sex hormones by injecting ovarian extracts into rats, his findings were extremely disheartening. That tissues other than ovaries elicited the same response might be an acceptable finding because tissues other than gonads were known at that time to produce sex hormones. But the appearance of the syndrome after formalin injection was inexplicable by any mechanism involving a sex hormone. After perform- ing several more permutations of his experiments, he reluctantly came to the conclusion that the syndrome was not a specific one to an extracted hormone, but a general defense response to demands placed on the soma by a stressor. But his mood gradually changed from despair to fascination. He had found a general adaptive response, yet medical convention at that time focused solely on telltale effects produced by specific disease agents. Contrary to convention, he had discovered a nonspecific, defensive response. He shared his excitement about this novel vantage with a valued mentor who, after failing to dissuade him from further work along this theme, exclaimed, “But, Selye, try to realize what you are doing before it is too late. You have now decided to spend your entire life studying the pharmacology of dirt.” After recovering from the sting of this comment, Selye spent his career studying what later became known as the theory of stress. Along the way, he published 1500 articles and 30 books that established a completely new discipline. Fortunately, the label “dirt pharmacology” never caught on. What is the point? To use Selye’s own thoughts about his experience, “My advice to a novice scientist is to look for the mere outlines of the big things with his fresh, untrained, but still unprejudiced mind” (Selye 1984). Respect, but do not be confined by, the current thinking in your field (see also Chapter 36). Many changes that appeared during the alarm stage and abated during the resistance phase can reappear during the exhaustion phase (Selye 1950). Death occurs at the end of the exhaustion phase. What is the significance of the GAS-associated shifts relative to coping with an infectious or noninfectious stressor? Selye breaks these changes down into responses facilitated by syntoxic and catatoxic hormones. Syntoxic hormones facilitate an individual’s ability to coexist with the stressor during the period of challenge (e.g., those modulating the inflammation response during a general infection). Specific examples include cortisone and cortisol inhibition of inflammation as well as their altering of glucose metabolism. The catatoxic hormones are designed to enhance stressor destruction, “mostly through the induction of poison-metabolizing enzymes in the liver” (Selye 1984). Dysfunctions of these responses are called diseases of adaptation because they reflect health- enhancing processes gone awry. Human diseases of this sort include hypertension, some heart and kidney diseases, and rheumatoid arthritis. The activation of chemicals by liver enzymes discussed in previous chapters fit into this category of diseases also. Regardless, the reader will probably recognize at this point that the syntoxic and catatoxic hormones are pivotal to integrating the diverse defense mechanisms described in earlier chapters at the organismal level. Not only can stress cause direct mortality of exposed individuals but can also, as suggested by the immunological changes described above, modify an individual’s risk of death from toxicants or © 2008 by Taylor & Francis Group, LLC Clements: “3357_c009” — 2007/11/9 — 12:41 — page 140 — #6 140 Ecotoxicology: A Comprehensive Treatment infectious agents. Friedman and Lawrence (2002) describe such exacerbation by stress of environ- mentally induced human maladies. Contaminants can also modify the stress response of exposed species. Hontela (1998) reported that low, chronic toxicant field exposures of fish appeared to reduce plasma corticosteroid levels, suggesting a compromised ability to respond to other stressors. Amphi- bians (Necturus maculosus) exposed in the field to polychlorinated biphenyls and organochlorine pesticides also demonstrated reduced ability to produce corticosterone when stressed (Gendron et al. 1997). As a final example, Benguira and Hontela (2000) documented reduced ability of rainbow trout (Oncorhychus mykiss) interrenal tissue to secrete cortisol with adrenocorticotropic hormone stimulation after in vitro exposure to o,p -dichlorodiphenyldichloroethane (DDD). So, toxicant-induced death can result from specific and nonspecific effects to or responses of individuals. This conclusion should create in the reader an anticipation that a diversity of mortality dynamics exist within groups of exposed individuals. In the next section, the focus will shift to the nature of these differences among lethally exposed individuals. 9.1.2 LETHALITY DIFFERENCES AMONG INDIVIDUALS It has been recognized that in bioassays, the least and most resistant individuals in a group show much greater variability in response than individuals near the median. A good deal of accuracy may therefore be gained by measuring some average response rather than a minimum or maximum response (Sprague 1969) Not surprisingly, toxicologists see variability in the resistance of individuals to lethal agents. Several factors contribute to this variability including allometric scaling, sex, age, genetics, and random chance. Even inthe earliestpublications quantifyinglethal effects (e.g.,Gaddum 1933), theinfluences of these factors were known. Except for random chance, which will be discussed in Sections 9.1.2.1 and 9.1.2.2, these factors will be described briefly here. Scaling is simply the influence of organism size on structural and functional characterist- ics (Schmidt-Nielsen 1986). Many relevant processes such as those determining bioaccumulation (Anderson and Spear 1980), structures such as gill exchange surface area (Hughes 1966), and states such as metal body burden (Newman and Heagler 1991) are subject to scaling, so it is no surprise that the risk of death can be influenced by organism size. In fact, allometry, the science of scaling, is used to quantitatively predict differences in mortality for individuals differing in size (see New- man (1995) for details). Bliss (1936) developed a general power model that, in its various forms, currently enjoys widespread use for scaling lethal effects. As an important example, Anderson and Weber (1975) extended Bliss’s approach to predict the mortality expected in a toxicity test if tested fish differed in size: Probit(P) = a −b log(M/W h ), (9.1) where Probit(P) = the probit transform 5 of the proportion of exposed fish dying, M = the toxicant concentration, W = the weight of the exposed fish for which prediction was being made, and h = an exponent adjusting mortality predictions for fish weight. Hedtke et al. (1982) used Equation 9.1 successfully to quantify the influence of Coho salmon (Oncorhynchus kisutch) size on the lethal effects of copper, zinc, nickel, and pentachlorophenol. Anderson and Weber (1975) advocated that this relationship be applied generally; however, some studies such as Lamanna and Hart (1968) show that not all data sets fit this relationship. As will be discussed later in this chapter, scaling effects on mortality can also be easily accommodated using survival time modeling, as implemented by many statistical programs. 5 See Section 9.2.2 for details about the probit transformation. © 2008 by Taylor & Francis Group, LLC Clements: “3357_c009” — 2007/11/9 — 12:41 — page 141 — #7 Lethal Effects 141 Sex and age can influence the risk of dying during toxicant exposure. Several studies have shown differences in sensitivity between the sexes including Kostial et al. (1974) and Newman et al. (1989). Age is commonly an important factor determining sensitivity of toxicants (e.g., Hogan et al. 1987) although its influence isoftenconfounded by its positive correlation withsize. Acursory reviewofthe previous chapters should reveal important biochemical, physiological, and anatomical differences that could give rise to sex- and age-dependent sensitivities. Some of these differences can produce unexpected results in combination. As an example, Williamson (1979) found that age and size of the land snail (Cepaea hortensis) had opposite effects on cadmium accumulation and probably the adverse effects of this toxic metal. As a quick glance ahead to Chapters 16 through 18 will confirm, many opportunities exist for genetic qualities to contribute to tolerance differences. 6 There is no need to discuss genetic tolerance further at this point except to point out that one example described in Box 18.1 can be linked to the GAS. In that example, mosquitofish differed in the genetically determined form of a glycolytic enzyme(glucosephosphate isomerase) that ispivotalin the processing ofglucose through metabolic pathways. Glucosephosphate isomerase-2genotypesdiffered intheir survival probabilities under stress and these differences were correlated with those in changes in glycolytic flux under general stress. Downward in the biological hierarchy, explanation for these response differences could notionally be linked to syntoxic hormone (glucocorticoid) responses in which blood glucose increases under stress. As done in Chapter 16, the glucosephosphate isomerase genotype differences during stress can also be projected upward in the biological hierarchy as one mechanism contributing to phenotypic plasticity and associated changes in life history strategies. 9.1.2.1 Individual Effective Dose Hypothesis On this theory, the dosage-mortalitycurve isprimarilydescriptive ofthe variation insusceptibility between individuals of a population the susceptibility of each individual may be represented by a smallest dose which is sufficient to kill it, the individual lethal dose. (Bliss 1935) The distributions of the individual effective doses and the results of the tests are in most cases “lognormal” (Gaddum 1953) In modeling lethal effects, the variation in response among tested individuals is most often explained in the context of the individual effective dose or lethal tolerance hypothesis. The two quotes above present the essential features of this hypothesis. There is a minimum dose (or concentration) that is characteristic of each individual in a population at or above which it will die, and below which it will survive under the specified exposure conditions. For most populations, the distribution of such tolerances is believed to be described best by a log normal distribution with some individuals being very tolerant (Figure 9.3). Early toxicologists conjectured mechanisms for differences based on the then-popular Weber–Fechner Law 7 or conventional adsorption laws such as the Langmuir isotherm model. The context from which these conjectures emerged was conventional laboratory toxicity testing in which most variables such as animal age, sex, and size were controlled, so the tolerance differences being explained were inherent—perhaps genetic—qualities. However, because conventional ecotoxicity test data are generated for diverse inbred laboratory lines or field-collected 6 See Mulvey and Diamond (1991) for a general review. 7 Afield called psycho-physics emerged during the first half of the nineteenth century in an attempt to quantify the intensity of human sensation resulting from a stimulus of a specified magnitude. The Weber–Fechner Law of psycho-physics states that the magnitude of the sensation (expressed on an arithmetic scale) increases in proportion to the logarithm of the stimulation. Extending this law, early toxicologists related the magnitude of toxic response to the logarithm of the dose or exposure concentration. © 2008 by Taylor & Francis Group, LLC Clements: “3357_c009” — 2007/11/9 — 12:41 — page 142 — #8 142 Ecotoxicology: A Comprehensive Treatment Proportion dying (P) ln exposure concentration P = .50 P = .50 P = .84 P = .16 Mean −1 SD +1 SD cdf pdf Frequency FIGURE 9.3 The upper panel shows the typical sigmoid concentration- (or dose-) mortality curve. The logarithm of the exposure concentration is plotted on the x-axis against the proportion of individuals dying during the exposure (P). This sigmoid curve can be described as a cumulative density function (cdf, upper panel) in which P = .16, .50, and .84 correspond to approximately –1 standard deviation below the mean, the mean, and +1 standard deviation above the mean. The antilogarithm of the x-value associated with P = .50 is an estimate of the median lethal concentration (LC50) or dose (LD50). The bottom panel shows the same data expressed as a probability density function, that is, as the conventional normal “bell curve.” The cumulative area to the left of the mean is .50, corresponding to P = .50 in the cdf above. individuals, it is difficult to imagine a genetic mechanism that consistently produced a log normal distribution of tolerances for most populations and toxicants. Mono- and multigenetic differences in tolerance (see Chapters 17 and 18) could produce a variety of distributions from ecotoxicity testing. Moreover, some conventional tests use metazoan clones (e.g., Daphnia magna or Lemna minor)or unicellular algal or bacterial cultures. It is difficult to invoke a genetic mechanism that produces a log normal distribution of tolerances for these diverse clones, laboratory strains, and field-caught individuals. It is more plausible that phenotypic plasticity (see Chapter 16) might generate variability in many of these cases but there does not seem to be a clear mechanism associated with phenotypic plasticity that would consistently produce a log normal distribution of tolerances. Regardless, this concept of a log normal distribution of inherent tolerance differences in all test populations was the first, and remains the dominant, explanation presented in the current ecotoxicology literature. 9.1.2.2 Probabilistic Hypothesis If it is seriously believed that there is some physical property more or less stably characterizing each organism, which determines whether or not it succumbs, then it is justifiable to advance the hypothesis of tolerances. In that case one should be prepared to suggest the nature of this characteristic so that © 2008 by Taylor & Francis Group, LLC Clements: “3357_c009” — 2007/11/9 — 12:41 — page 143 — #9 Lethal Effects 143 the hypothesis may be capable of corroboration by independent experiments. If on the other hand the [log normal] formulation is only that of a “mathematical model” then it would be [better] not to create any hypothetical tolerances (Berkson 1951) This quote by Berkson precedes his counterargument that it is better to apply a log logistic model than a log normal one to toxicity data. But, more generally, it is an eminently reasonable point that remains inadequately addressed more than half a century later (see Box 12.2 in Chapter 12). Disinterest with the underlying mechanismby the founders ofmoderntoxicology arises from pragmatismas is evident in the following quote from Finney’s seminal book (1947): The validity and appropriateness of the logarithmic transformation in the analysis of experimental data are not dependent on the truth or falsity of any hypotheses relating to adsorption; use of the log concentration requires no more justification than it introduces a simplification into the analyses. In his arguments, Berkson (1951) related one experiment involving human tolerances to high altitude conditions that did not support the individual tolerance hypothesis, suggesting instead that differences in individual tolerances during testing were mostly random. Such a conclusion gives rise to an alternate explanation (probabilistic or stochasticity hypothesis) that most of the variation among similar individual’s results from a random process (or processes) that is best modeled with a log normal or a similar skewed distribution. Which specific individual dies within a treatment is a matter of chance. Nearly half a century later, Newman and McCloskey (2000) tested these two hypotheses, rejecting the customary assumption that the individual tolerance hypothesis was the sole explanation for observed differences in response of lethally exposed individuals. The stochasti- city hypothesis was supported in two cases and the individual tolerance hypothesis in another. Neither hypothesis alone was adequate to explain the observed differences. Similar conclusions were recently made by Zhao and Newman (2007) for amphipods (H. azteca) exposed to copper or sodium pentachlorophenol. Two questions may have occurred to the critical reader at this point. First, why was the underly- ing mechanism for a foundation approach in classic toxicology left undefined for so long? Second, why is an understanding of the underlying mechanism important to the practicing ecotoxicologist? An inkling of an answer to the first question emerges from statements of prominent toxicologists of the time such as that of Finney above. Originally, the log normal model was applied to quantify relative poison toxicity or drug potency so it did not matter what the underlying mechanism was. Within the context of the laboratory bioassay, one chemical was or was not more potent than another. Classic toxicology could progress just fine without knowing the reason that data seemed to fit a skewed distribution. Precipitate explanation was presented without much scrutiny and the methods were broadly applied in studies of poisons and drugs. Unfortunately, because many ecotoxico- logists tend to feel that anything good for mammalian toxicologists is good enough for them, it has been erroneously supposed that the underlying mechanism is also an esoteric issue in eco- toxicology, the science concerned with effects ranging from those to individuals to those to the biosphere. The error in this supposition can be shown in several ways but we will illustrate it here using only population consequences under repeated toxicant exposures. Suppose that a pop- ulation was exposed for exactly 96 h to a toxicant concentration that kills half of the exposed individuals. Only the most tolerant individuals remain alive according to the individual tolerance theory but the stochasticity hypothesis would predict that, after recovery, the tolerances of the survivors will be the same as those of the original population. During a second exposure, the concentration-response curve could be very different (individual tolerance theory) or the same (stochasticity theory) as that for the original population during the first exposure. Indeed, dur- ing a sequence of such exposures, the survivors would drop in numbers by 50% during the first exposure and then remain at that number under the individual tolerance hypothesis but would drop © 2008 by Taylor & Francis Group, LLC Clements: “3357_c009” — 2007/11/9 — 12:41 — page 144 — #10 144 Ecotoxicology: A Comprehensive Treatment Proportion dying (P ) ln exposure concentration Threshold model Spontaneous mortality model Hormesis FIGURE 9.4 Conventional sigmoid and sigmoid models with spontaneous (natural) mortality or a dose/concentration threshold. The inset illustrates hormesis at sublethal concentrations. down 50% with each exposure under the stochasticity hypothesis. The likelihood of local popu- lation extinction is quite different depending on which hypothesis is most appropriate or if both manifest in combination. Knowing which hypothesis is correct should be important to the ecotoxic- ologist attempting to predict population and associated community changes resulting from multiple exposures. 9.1.3 SPONTANEOUS AND THRESHOLD RESPONSES The model shown in Figure 9.3 can have an additional feature in some cases. If the test involves a prolonged exposure relative to the longevity of the test organism or tested life stage of the organism, there can be a certain level of spontaneous (natural) mortality. Unfortunately, in still other cases in which the husbandry of the test species is imperfect, there may be background mortality associated with the general stress placed on the test organisms. In these cases, the mortality curve will take on an additional feature as shown in Figure 9.4. Another change in Figure 9.3 is required if a threshold concentration or dose is characteristic of a chemical agent (Cox 1987). Like the minimum time-to-death described in Section 9.1.1, some toxicity test data appear to have a minimum concentration or dose that must be exceeded before any deaths occur in the test treatments (Figure 9.4). 9.1.4 HORMESIS The nature of toxicologically-based dose-response relationships has a long history that is rooted in the development and interpretation of the bioassay. While the general features of the bioassay were clearly established in the 19th century, the application of statistical principles and techniques to the bioassay is credited to Trevan and the subsequent contributions of Bliss and Gaddum [which] described the nature of the S-shaped dose-response relationship and the distribution of susceptibility within the context of the normal curve Despite this long history of the S-shaped dose-response relationship, a substantial number of toxicologically-based publications from the 1880s to the present indicate that biologically relevant activity may occur below the NOAEL 8 (Calabrese and Baldwin 1998) 8 The NOAEL (no observed adverse effect level) is a statistically derived measure often used to imply a threshold concentration or dose below which no effect will be observed. See Chapter 10, Section 10.3 for more detail. © 2008 by Taylor & Francis Group, LLC [...]... by these early workers Newman and coworkers (McCloskey and Newman 199 6, Newman and McCloskey 199 6, Newman et al 199 8, Ownby and Newman 2003, Tatara et al 199 8) did this, using what they called a quantitative ion character–activity relationship (QICAR) approach Newman et al ( 199 8) and Ownby and Newman (2003) provide a general description of this QSAR-like approach, discussing the ion characters most... summary statistics can be eked out of data sets in which all of the treatments had either complete or no mortality at all A binomial method can provide an estimate for such data sets with no partial kills Parametric and nonparametric methods exist for analyzing data from concentration-lethal response tests Many can also be applied for nonlethal effects Each (Figure 9. 5) carries advantages and disadvantages... general advantages and disadvantages of Time-to-event data No Assume model? Not full Yes Assume only proportional hazards or fully parametric model? Yes Productlimit or life table analysis Cox proportional hazards analysis Model: exponential Weibull Full Proportional hazards? No Model: normal, log normal, gamma, etc FIGURE 9. 6 Methods for analyzing time-to-event data including nonparametric, semiparametric... particularly necessary since such a tabulation may apparently be easily biased (Sprague 196 9) What was really being advocated in this and similar statements that emerged during a period when environmental issues required immediate, pragmatic solutions? A critical reading of Sprague’s argument indicates that 4 days was not sufficient for 4 of 10 tests Sprague also indicates that considerable data used... associated models can be found in Calabrese et al ( 198 7), Calabrese and Baldwin ( 199 8, 2001), and Sagan ( 198 7) 9. 1.5 TOXICANT INTERACTIONS To this point, the lethal effects of single toxicants have been emphasized, but many exposures involve simultaneous exposure to several toxicants that can interact There are two traditional vantages for discussing the joint action of toxicants: mode of action and additivity... Silva and Williams 199 1, Jones and Vaughn 197 8) Hard metals are not as polarizable as soft metals Other metals are intermediate to the soft and hard metals Acid–base refers to the Lewis acid (accepting an electron pair) or base (donating an electron pair) context for predicting the nature and stability of the metal interaction with ligands © 2008 by Taylor & Francis Group, LLC Clements: “3357_c0 09 —... correlated metal bioactivity with metrics of metal binding to oxygen, nitrogen, or sulfur donor atoms of biomolecules A series of researchers (Babich et al 198 6a, b, Biesinger et al 197 2, Binet 194 0, Jones 193 9, 194 0, Jones and Vaughn 197 8, Kaier 198 0, Loeb 194 0, McGuigen 195 4, Turner et al 198 5, Willams and Turner 198 1) expanded this approach, incorporating a range of metals, species, and metal qualities... Gaddum ( 195 3), Newman ( 199 5), Sprague ( 196 9) for details) Methods even exist for extrapolating from the abundant acute lethality metrics to chronic lethal effects using a variety of approximations (Mayer et al 199 4) Shareware is available to facilitate the associated calculations (Ellersieck et al 2003) Recently, Duboudin et al (2004) used species distributions to do such extrapolations However, each of... semiparametric and fully parametric methods © 2008 by Taylor & Francis Group, LLC Clements: “3357_c0 09 — 2007/11 /9 — 12:41 — page 151 — #17 Ecotoxicology: A Comprehensive Treatment 152 each approach The reader is directed to Miller ( 198 1), Cox and Oakes ( 198 4), Marubini and Grazia Valsecchi ( 199 5), Newman ( 199 5), and Crane et al (2002) for more detail Nonparametric methods include the Product Limit (also called... Effects of various metals on survival, growth, reproduction, and metabolism of Daphnia magna, Can J Fish Aquat Sci., 29, 1 691 –1700, 197 2 Binet, M.P., Sur la toxicité comparée des métaux alcalins et alcalino-terreux, C.R Acad Sci Paris, 115, 225–253, 194 0 Bliss, C.I., The calculation of the dosage-mortality curve, Ann Appl Biol., 22, 134–307, 193 5 Bliss, C.I., The size factor in the action of arsenic upon . Ecotoxicology: A Comprehensive Treatment each approach. The reader is directed to Miller ( 198 1), Cox and Oakes ( 198 4), Marubini and Grazia Valsecchi ( 199 5), Newman ( 199 5), and Crane et al. (2002). data can be fit to all of the candidate models and then the results compared. Comparison usually involves plotting the actual dataandmodel predictions, and also calculating agoodness-of-fit statistic such. reader to understand the general advantages and disadvantages of Time-to-event data Assume model? Assume only proportional hazards or fully parametric model? No Yes Product- limit or life table analysis Cox proportional hazards analysis Not full Full Proportional hazards? Ye