Assessing Risks to Endangered and Threatened Species from Pesticides (2013) / Chapter Skim
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4 Effects
4 Effects
Pages 91-147
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From page 91... ...
to determine whether a pesticide "may affect" (Step 1, Figure 2-1) or is "likely to adversely affect" a listed species (Step 2, Figure 2-1)
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The following sections discuss how to incorporate sublethal effects into ecological risk assessments, how effects on one organism might indirectly affect others, and how pesticide effects might be modified by exposure to other environmental stressors. Sublethal Effects Pesticides can have sublethal effects at multiple levels of biological organization: molecular, cellular, tissue, organism, population, and community.
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of a listed species and incorporate such information into the population viability analyses or should state that such relationships are unknown but possible and include a qualitative discussion in the uncertainty section of the biological opinion (BiOp)
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modeled the effects of sublethal effects of low concentrations of copper on growth of juvenile Chinook salmon and projected potential effects on population size, recovery rates, and extinction risks. Many sublethal effects might have a link to population viability, but that link has not yet been quantified.
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Depending on how one interprets that definition, it could be quite restrictive and different from most ecologists' understanding of indirect effects, which typically include effects on prey, competitors, or predators of a listed species or on other aspects of the species' ecological milieu but not direct effects on the species. On the basis of the documents reviewed by the committee, it appears that the restrictive definition is not used by the agencies; therefore, this section discusses indirect effects as including those normally understood by the term.
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As a consequence of the complex population structure of Pacific salmon, some breeding populations can be highly endangered whereas other popula tions of the same species are abundant and able to sustain substantial exploi tation from fisheries -- for example, sockeye salmon in the Stanley Basin of Idaho vs those in Alaska's Bristol Bay (Hilborn et al. 2003; Gustafson et al.
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It also highlights the difficulty of identifying a reliable surrogate species for test ing and analysis, in particular a species whose life history is similar to that of the species of interest. For example, pink salmon generally migrate the short distance to the sea as soon as they emerge as free-swimming fry whereas juvenile Chinook salmon usually remain in freshwater for months to a year (Continued)
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Because some indirect effects can be quantified, the committee recommends that they be incorporated into effects analysis. For example, for a situation in which food is the limiting factor and the major indirect effect is a 50% reduction in the food resource of the species of interest, the indirect effect can be incorporated into the population model by a 50% reduction in carrying capacity (maximum population size that can be supported by a specified area)
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As in the different approaches used to evaluate sublethal effects, EPA and the Services appear to differ (on the basis of their responses to committee questions) in the extent to which they consider indirect effects.
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Their approach encompasses the use of direct and indirect effects of pesticide applications to assess the sensitivity of various communities and to identify which stressors will have the greatest effect. The stressors that currently affect listed species are considered part of the environmental baseline conditions.
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provide an objective, quantitative, and practical framework for incorporating baseline conditions and projected future cumulative effects into the ecological risk assessment in a way that is relevant to the requirements of the ESA. For example, a population model can represent the direct effects estimated from concentration-response relationships as reductions from baseline in survival and reproductive success and also can include effects on survival and reproduction of current and future habitat loss (as decreasing carrying capacity)
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NMFS uses population models as one of several lines of evidence to address the question of population persistence explicitly. The BiOp on the effect of three pesticides on salmonids (NMFS 2008)
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Those types of uncertainty and approaches to incorporating them in individual-level models are discussed below in the section "Interspecies Extrapolations and Surrogate Species." The combined effects of those types of uncertainty can be expressed as confidence intervals around values on the concentration-response curve. To evaluate potential effects on a species correctly, direct effects of pesticides on survival and reproduction must be estimated, and these estimates must correspond to the conditions expected in nature.
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are used in population models to assess effects on listed species. Population models are used to estimate population-level end points -- such as population growth rate, probability of population survival (population viability)
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The committee concludes that in the absence of detailed demographic information, it is appropriate to use such models to characterize the baseline condition of a listed species, provided that the analyst incorporates estimates of uncertainty -- for example, by using reasonable "high" and "low" demographic inputs -- to bound the range of probable lambdas and includes a discussion in the final risk assessment about the magnitude of the uncertainty resulting from this lack of knowledge. The sections that follow discuss important issues related to various components of population models that are especially relevant to assessing the risks posed by pesticide exposure.
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Spatial Scale The spatial scale of an assessment has two components: resolution and extent. For most population models, the spatial resolution should coincide with the typical sizes of the areas (or ranges of sizes)
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The committee concludes that population models that incorporate temporal variability and focus on probabilistic results are needed for assessing risks at the population level and that deterministic models are insufficient for this task. However, in the absence of such information, deterministic models with such end points as lambda (the finite rate of increase)
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Those conditions would make the density-dependence functions of baseline and effects models (population models with and without pesticide exposure) have the same shape (Figure 4-1A)
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. This section discusses the state of the science of mixture toxicity, raises practical issues associated with mixture assessments, and provides a case study of the application of information in the context of assessing risks to listed species posed by pesticides.
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Implicit in the application of concentration addition is the assumption that the slopes of the concentration-response curves for all mixture components are identical. The assumption of equal slopes follows directly from the assumption of functionally identical mechanisms of action.
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Therefore, although the concentration-addition model has been demonstrated to predict the toxicity of pesticide active-ingredient mixtures more accurately when the pesticide active ingredients have the same mechanism of action (Belden et al.
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. Synergy Arguably, the greatest concern in evaluating hazards and risks to listed species posed by chemical mixtures that contain pesticides is whether constituents of the mixtures act to enhance the toxicity of the pesticide active ingredient.
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The greatest probability of synergistic effects might be when synergist-containing pesticide formulations are applied directly to aquatic systems or when there is direct contact between the formulation and a species. Synergistic Interactions among Active Ingredients As discussed in Chapter 3, pesticide active ingredients have the potential to coexist in tank mixtures or as environmental mixtures.
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. Interaction thresholds make sense in the context of the underlying kinetics and might be useful in assessing whether concerns about potential toxic interactions are important in exposures to specific mixtures.
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The concept of interaction thresholds simply indicates that the probability of toxic interactions (as opposed to some form of additive joint action) is reduced if the total exposure does not exceed a threshold based on an assumption of additivity.
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the toxicity of a pesticide active ingredient, the pesticide active ingredient must be present at a concentration that actually elicits toxicity. Given that circumstance, the committee concludes that ecological risk assessment should focus on the pesticide active ingredient alone and avoid the added uncertainties associated with estimating the reduction in risk due to the presence of an antagonist.
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The mixture elicited concentration-dependent toxicity at exposure concentrations between the median and 10 times the median concentrations of the chemicals, and the investigators were able to predict the toxicity of the mixture accurately with a model that combined concentration addition and response addition. However, further analyses revealed that the toxicity of the mixture could be explained largely by a single constituent, chlorpyrifos.
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suggest that general guidelines used by EPA have been adopted by NMFS inasmuch as they reference EPA methods for ecological risk assessment (EPA 1998a, 2004)
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certainly recognize and appreciate the potential importance of exposure to mixtures, ecological risk assessments prepared by EPA focus on single active ingredients in the generic risk assessments (EPA 2004)
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With the exception of the guidance document on low-risk polymers, all the inerts guidance documents refer to the Office of Prevention, Pesticides, and Toxic Substances Harmonized Test Guidelines, which are used in the registration of pesticide active ingredients (EPA 2013)
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Chronic toxicity studies are not generally conducted on pesticide formulations and are not available on most inerts. In cases in which a chronic toxicity value is available for an active ingredient (Cha.i.)
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In such cases, more detailed assessments can be conducted on the basis of analyses of toxic interactions or available data on the mixture of concern. Data-Bridging Another problem that arises in using formulation studies to assess the toxicity of inerts in pesticide formulations concerns "data-bridging." Although EPA generally requires at least acute toxicity data on pesticide formulations, it will often allow toxicity studies on one formulation to support the registration of another.
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Magnitude of Interactions EPA seldom addresses interactions quantitatively in ecological risk assessments of pesticides. In three BiOps, NMFS (2008, 2009, 2010)
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. A Case Study: Assessing Pesticide-Containing Mixtures Conventional approaches to assessing the risks posed by exposure to chemical mixtures first determine EECs of the mixture components and then estimate the hazard associated with those exposures.
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Nonylphenol and ethinyl estradiol elicit estrogenic activity and are therefore identified with the letter c. It is necessary at this stage to identify the adverse response of the listed species that is deemed most relevant to the pesticide of concern.
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Slope Formulationb Cypermethrin 0.05 250 0.01 0.015 a 5.0 14 PBO 1.0 5,000 0.2 0.205 Cyper: 1.0c 10,000 5.0 Delta: 1.0c Tank Deltamethrin 100 0.004 0.004 a 3.1 15 Polysorbate 20 10,000 0.40 0.40 b 25,000 2.3 Epoxisoy 5,000 0.20 0.20 75,000 3.3 Environment Nonylphenol 0.001 0.001 b,c 1,500 5.7 Ethinyl estradiol 0.05 0.05 c 1,400 6.1 Caffeine 500 500 33,000 3.9 Acetaminophen 0.01 0.01 100 6.3 PBO 0.005 Cypermethrin 0.005 a Chemicals that act similarly are assigned the same letter. b Formulations can be evaluated for the potential contribution of inerts as described in the section "Formulation Toxicity." c K values of 1.0 were assigned to the synergist PBO because the environmental exposure concentration of PBO in this exercise was considered to be below the interaction threshold.
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Typically, the data are determined experimentally by using a surrogate species after an appropriate exposure duration. EC50 data are often available from the literature, and EC50 and slope values are required for FIFRA guideline studies.
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Although the idea of finding a scientifically credible surrogate species might be appealing, the committee finds this approach difficult for two reasons. First, it is not always straightforward to select a scientifically credible surrogate for a listed species.
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If different life histories lead two related species that have similar toxicological sensitivities to a chemical to occupy different locations at different times, their susceptibility to a chemical could be quite different. Listed species are not inherently more sensitive to chemicals than species that are not listed (Sappington et al.
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available for each species to assign values to parameters in the population model with a Monte Carlo approach. For example, the percentage of the population that survives an estimated exposure can be randomly selected from all the species tested.
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Although they all report confidence intervals around most of the effects end points, they ultimately use only deterministic approaches (single point estimates of the magnitude of effect at a particular exposure concentration) or qualitative descriptions (particularly for behavioral and sublethal effects other than quantifiable reproduction responses)
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Any effect that results in a change in survival or reproduction is relevant to the assessment, and any effect that does not change either outcome is irrelevant with respect to a quantitative assessment of population effects. To determine whether a pesticide is "likely to adversely affect" a listed species, a broad search should be conducted to identify information on sublethal effects of the pesticide and possible concentration-response relationships.
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However, in the absence of such data, it is appropriate to use generic, single-population models that characterize the life history of a group of species to estimate the effects of a pesticide on a given species. The assumption that mortality due to pesticide exposure will always be compensated for by density dependence is not scientifically valid because such exposure will likely decrease the growth rate of the population at all densities and generally depress the population growth-density curve.
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4. In the absence of any data that would support the hypothesis of a synergistic interaction between the pesticide active ingredient and other mixture components, the effects analysis should proceed on the assumption that the components have additive effects.
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An alternative approach to using a single surrogate species is to define a range of sensitivities within which the sensitivity of the species of concern could reasonably be expected to occur or a range of sensitivities that could be used to make reasoned extrapolations from species that have been tested by using inferences based on other chemicals. Because listed species are not inherently more sensitive to chemicals than species that are not listed, similar methods of cross-species extrapolations can be used for any ecological risk assessment and include interspecies correlation analysis and species sensitivity distributions.
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Chronic toxicity of copper and pentachlorophenol to two endangered species and two surrogate species.
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2001. Matrix Population Models: Construction, Analysis, and Interpretation, 2nd Ed.
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2010. Toxicological interaction thresholds of chemical mixtures.
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Environmental Protection Agency: Endangered and Threatened Species Effects Determinations. Office of Pre vention, Pesticides and Toxic Substances, Office of Pesticide Programs, U.S.
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Pp. 31-52 in Applica tion of Uncertainty Analysis to Ecological Risks of Pesticides, W.J.
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Pp. 311-393 in Pacific Salmon Life Histories, C
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2009. The synergistic toxicity of pesticide mixtures: Implications for risk assessment and the conservation of endangered Pacific salmon.
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2007. Density dependence in ecological risk assessment.
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Response to Questions from the Committee on Ecological Risk Assessment under FIFRA and ESA, from Scott Hecht, NOAA, to David Policansky, March 30, 2012 [online]
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2008. Protectiveness of species sensitivity distribution hazard concentrations for acute toxicity used in endangered species risk assessment.
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2008. Potential effects of freshwater and estuarine contaminant exposure on lower Columbia River Chinook salmon (Oncorhynchus tshawytscha)
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2007. Initial analyses of the relationship between "Thresholds" of toxicity for individual chemicals and "Interaction Thresholds" for chemical mixtures.
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