4

Effects

As discussed in Chapter 1, pesticides are designed to have biological activity and are “intended for preventing, destroying, repelling or mitigating any pest” [7 U.S.C. § 136 (u)(1)]. Pesticides might cause a variety of effects on nontarget organisms, including listed species, and effects on individuals might ultimately affect a population. Determining the potential for and possible magnitude of effects is a process known as effects analysis, and various aspects of that process are addressed in this chapter.

First, the committee discusses characterization and evaluation of sublethal, indirect, and cumulative effects. Next, it describes the models that are used to estimate effects of a pesticide at the individual and population levels, clarifies the relationship between the models at these two levels, and evaluates major assumptions used in the modeling approaches.

Because there are many sources of uncertainty in effects analysis, the final three sections of this chapter address various aspects of uncertainty. As described in Chapter 3, pesticides are typically mixtures (formulations) of active ingredients and other materials (inerts), are often mixed with other pesticides and other chemicals (adjuvants) in the field, and are applied to areas that already contain mixtures of chemicals. What is evaluated becomes a complicated question and is often viewed as a substantial source of uncertainty. Accordingly, the committee discusses the state of the science of mixtures assessment and provides some guidelines on assessing the hazard posed by a pesticide active ingredient in light of all the other components in the formulation, tank mixture, and environment. It then addresses the uncertainty surrounding interspecies extrapolations and the use of surrogate species and the quantitative characterization of uncertainty.

Throughout this chapter, the committee provides suggestions on how to incorporate the information presented into the approaches used by the US Environmental Protection Agency (EPA) 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) and into the approaches used by the US Fish and Wildlife Service



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4 Effects As discussed in Chapter 1, pesticides are designed to have biological ac- tivity and are “intended for preventing, destroying, repelling or mitigating any pest” [7 U.S.C. § 136 (u)(1)]. Pesticides might cause a variety of effects on non- target organisms, including listed species, and effects on individuals might ulti- mately affect a population. Determining the potential for and possible magnitude of effects is a process known as effects analysis, and various aspects of that pro- cess are addressed in this chapter. First, the committee discusses characterization and evaluation of sublethal, indirect, and cumulative effects. Next, it describes the models that are used to estimate effects of a pesticide at the individual and population levels, clarifies the relationship between the models at these two levels, and evaluates major assumptions used in the modeling approaches. Because there are many sources of uncertainty in effects analysis, the final three sections of this chapter address various aspects of uncertainty. As de- scribed in Chapter 3, pesticides are typically mixtures (formulations) of active ingredients and other materials (inerts), are often mixed with other pesticides and other chemicals (adjuvants) in the field, and are applied to areas that already contain mixtures of chemicals. What is evaluated becomes a complicated ques- tion and is often viewed as a substantial source of uncertainty. Accordingly, the committee discusses the state of the science of mixtures assessment and pro- vides some guidelines on assessing the hazard posed by a pesticide active ingre- dient in light of all the other components in the formulation, tank mixture, and environment. It then addresses the uncertainty surrounding interspecies extrapo- lations and the use of surrogate species and the quantitative characterization of uncertainty. Throughout this chapter, the committee provides suggestions on how to incorporate the information presented into the approaches used by the US Envi- ronmental Protection Agency (EPA) to determine whether a pesticide “may af- fect” (Step 1, Figure 2-1) or is “likely to adversely affect” a listed species (Step 2, Figure 2-1) and into the approaches used by the US Fish and Wildlife Service 91

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92 Assessing Risks to Endangered and Threatened Species from Pesticides (FWS) and the National Marine Fisheries Service (NMFS)—collectively re- ferred to as the Services—to make jeopardy determinations (Step 3, Figure 2-1). SUBLETHAL, INDIRECT, AND CUMULATIVE EFFECTS Pesticides can kill organisms that are closely or distantly related to their intended targets, and they can cause sublethal changes that can affect reproduc- tion, shorten lifespans, or make the organisms unable to compete. The following sections discuss how to incorporate sublethal effects into ecological risk assess- ments, how effects on one organism might indirectly affect others, and how pes- ticide effects might be modified by exposure to other environmental stressors. Sublethal Effects Pesticides can have sublethal effects at multiple levels of biological organ- ization: molecular, cellular, tissue, organism, population, and community. Only when compensatory or adaptive mechanisms at one level of biological organiza- tion begin to fail do deleterious effects become apparent at higher levels. The committee considered how to assess objectively the degree to which observed effects of pesticides on organisms are adverse. Defining that concept is essential for ecological risk assessment because even if an effect is reliably observed, that alone might not be sufficient to conclude that the effect is adverse. The commit- tee concluded that the only reasonable way to determine whether an effect is adverse and how adverse it might be is to assess the degree to which it affects the organism’s survival and reproductive success. It then is possible to extrapo- late from changes in an individual organism’s survival or reproductive success to estimate population effects. If an adverse effect is large enough, it might lead to extinction of the species. EPA reached a similar conclusion in its overview of the ecological risk-assessment process (EPA 2004, p. 31): “If the effects on the survival and reproduction of individuals are limited, it is assumed that the risk at the population level from such effects will be of minor consequence. However, as the risk of reductions in survival and/or reproduction rates increase, the great- er the potential risk to populations.” EPA and the Services agree on the inclusion of sublethal effects in the risk-assessment process but disagree on the extent to which such effects should be included. For example, in its responses to committee questions, EPA ex- plained that its focus is “on how to relate the relevance of sublethal data to an assessment of the risks to fitness of listed species,” with fitness defined as “an individual’s ability to survive and reproduce” (EPA 2012a, p. 2). Furthermore, EPA considers that incorporation of sublethal effects into an ecological risk as- sessment must be accompanied by an explicit relationship that defines the con- tribution of the sublethal effect to an individual organism’s fitness in terms of the end points of “survival, growth and reproduction” (EPA 2012a, p. 20). EPA

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Exposure 93 stated that it “does not believe that all sub-lethal effects or that all levels of a sub-lethal effect on an individual constitute a compromise of individual fitness” (EPA 2012a, p. 3). EPA’s approach differs from the Services’ approach. For example, FWS “casts a wide net for each potentially affected species to ensure that the most sensitive endpoints are captured and evaluated” (FWS 2012, p. 2). It contends that “at present, data describing ‘sub-lethal’ effects are acknowledged but then set aside and not used by EPA in making effects determinations or characteriz- ing the potential effects of the action, unless other data or studies are available that would enable EPA to quantify a relationship between the ‘sub-lethal’ effect and EPA’s traditional endpoints, survival, growth, or reproduction.” FWS (2012, pp. 2-3) continued that “in contrast, when characterizing the ‘Effects of the Ac- tion’ pursuant to the ESA [Endangered Species Act], the FWS does not limit itself to using only those data that quantify changes in survival, growth, or re- production.” As discussed in the section on effects models below, assessing the effects of pesticides on listed species requires quantifying the effect of a pesticide on survival and reproduction of a species in the wild. Any effect that results in a change in one component is relevant to the assessment. In contrast, any effect that does not change either component is irrelevant with respect to a quantitative assessment of population effects. The relevance of any particular sublethal effect is likely to depend on the species. Growth, for example, might be a relevant ef- fect in some species but not in others. In mammalian species, retarded growth might increase age of first reproduction but not affect reproductive output there- after. In many fish species, size of the individual organism is directly related to reproductive output throughout the lifespan. Many plant species do not need to achieve a particular size for maximal reproductive output. Therefore, the com- mittee recommends that EPA in Step 2 (see Figure 2-1) cast a wide net and iden- tify information about sublethal effects of a chemical. If possible, EPA’s as- sessment should include information about responses at various chemical concentrations (a concentration-response curve) and, at a minimum, include a qualitative assessment of the relationship between sublethal effects and survival and reproduction. In Step 3 (see Figure 2-1), the Services should show how such effects change demographic measures (survival or reproduction) of a listed spe- cies and incorporate such information into the population viability analyses or should state that such relationships are unknown but possible and include a qual- itative discussion in the uncertainty section of the biological opinion (BiOp). The Services face the greatest challenge in Step 3 in determining whether an observed sublethal effect will change survival or reproduction in the natural population and, if so, the magnitude of such a change in relation to the predicted exposure. Relationships between sublethal effects and changes in population growth rates span a continuum of uncertainty that depends on the ability to quantify the

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94 Assessing Risks to Endangered and Threatened Species from Pesticides link. At one extreme, the relationship between a sublethal effect and survival or reproduction has not been quantified empirically, and the available mechanistic information is not sufficient to model the causal chain quantitatively. For exam- ple, markers of oxidative stress—such as glutathione or superoxide dismutase— indicate a physiological response to a chemical, but the relationship of the re- sponse to survival or reproduction is not known. Such a response could not be easily quantified with respect to population assessment if the observed response were the only pertinent information. At the other extreme, the link between sublethal effects and population persistence might be clear, quantifiable, and well documented in the literature. For example, the singing ability of some male birds directly affects the probability of their establishing and holding a territory and forming pair bonds with mates (Spencer et al. 2003). Impaired singing ability could directly affect reproductive success during the breeding season if the male song did not attract a female mate. Similarly, impaired growth of juvenile salmon might result in a reduction in size of individual salmon as they migrate to sea and could reduce survival. Specifically, Baldwin et al. (2009) modeled the relationship between sublethal effects on acetylcholinesterase activity and feeding behavior of juvenile Chinook salmon and reductions in growth after short-term exposure to environmentally realistic concentrations of organophosphate and carbamate pesticides. Reductions in growth correlated with reduced size at ocean entry and with later survival. Mebane and Arthaud (2010) 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. An example is altered olfactory ability, which has been shown to increase predation risk in some species of salmon because of an inability to detect chemical cues that signal the presence of a predator or be- cause of a loss of homing ability (Scholz et al. 2000). Whether altered olfactory ability affects survival will depend on the degree of its expression in the natural environment, the presence of predators during the time that olfaction is lost, and whether it occurs in fish whose size makes them susceptible to predation. Im- paired immune function is another example in which an organism is affected, but the effect on population viability is unclear. A working immune system is critical for survival, but an alteration of some aspect of immune function and its effect on disease resistance are often less clear—for example, Does a given re- duction in circulating leukocytes affect susceptibility to disease? Furthermore, the effect of an impaired immune system on disease susceptibility hinges partly on the presence of a pathogen. The committee notes that exposure to pesticides in some species might actually increase defense responses to predation. For ex- ample, Barry (1998) observed increased helmet formation—a defense response that deters predation efficiency—in daphnia exposed to low concentrations of endosulfan.

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Exposure 95 Uncertainties in concentration-response relationships or differences be- tween laboratory and field responses, particularly behavioral responses, further complicate the quantification of changes in survival and reproductive success in response to sublethal toxicity. Assessment of sublethal effects, as well as cumu- lative and indirect effects, is even more complicated in species that have com- plex life cycles and population structures, such as Pacific salmon (see Box 4-1 for further discussion). The committee concludes that survival and reproduction are the principal effects in determining population viability. The inability to quantify the relation- ship between sublethal effects and survival or reproductive success does not negate the potential importance of such effects for population persistence. How- ever, the relationship remains a hypothesis that can be described only qualita- tively with reference to the scientific literature for why such a hypothesis is ten- able. Implications for risk characterization can be discussed qualitatively, not quantitatively, as an additional uncertainty beyond uncertainties that are propa- gated in a formal quantitative manner. The narrative can be considered by a de- cision-maker according to the applicable policy constraints regarding risk toler- ance. However, such a separation of important risk components and uncertainty into quantitative and qualitative portions that cannot formally be combined makes it difficult to integrate and interpret the results of a risk assessment. Inte- gration can be improved by quantifying better the relationships that are viewed as critical for understanding the risks posed by a pesticide to a listed species. One way to facilitate integration of the hypothetical relationship into the formal risk assessment is to conduct extensive reviews of comparative data or empirical case studies or to conduct targeted new studies that could help to derive defensi- ble scientific quantification of the links between sublethal effects and survival or reproduction. Indirect Effects The Services have defined indirect effects as “those that are caused by the proposed action and are later in time, but still are reasonably certain to occur” (50 C.F.R. 402.02). Thus, their definition from a regulatory standpoint charac- terizes indirect effects as simply delayed effects. Depending on how one inter- prets that definition, it could be quite restrictive and different from most ecol- ogists’ 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 docu- ments reviewed by the committee, it appears that the restrictive definition is not used by the agencies; therefore, this section discusses indirect effects as includ- ing those normally understood by the term.

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96 Assessing Risks to Endangered and Threatened Species from Pesticides BOX 4-1 Ecological Risk Assessment in Species That Have Complex Population Structure and Life History: Pacific Salmon and Trout Pacific salmon and trout (Oncorhynchus spp.) are the basis of valuable commercial and recreational fisheries; part of the economy, ceremony, and subsistence of American Indians; components of complex ecosystems to which they contribute great quantities of nutrients; symbols of clean water and healthy rivers; and a host of other attributes related to human and natural systems (NRC 1996). Many factors have contributed to declines in salmon and trout, which are, in some cases, protected under the US Endangered Species Act (Gustafson et al. 2007). Protection of the listed distinct population segments (DPSs) has ramifications for a wide variety of human activities, including application of chemicals to control animals and plants that are con- sidered crop pests and weeds. There are five species of Pacific salmon in North America: Chinook, O. tshawytscha; coho, O. kisutch; sockeye, O. nerka; chum, O. keta; and pink, O. gorbuscha. There are also two trout species of the same genus: rain- bow/steelhead trout, O. mykiss, and cutthroat trout, O. clarkii. Both trout spe- cies are quite variable phenotypically and have several subspecies (Behnke 1992). All Pacific salmon are spawned in freshwater, and most migrate to sea and return to freshwater at maturity to spawn (that is, they are anadromous); however, resident populations of sockeye salmon (kokanee) are well known and a few individuals of other salmon species (such as Chinook salmon) do not migrate to sea but mature to a small size in streams. All trout are spawned in freshwater, but may be exclusively nonanadromous or resident (that is, they spend their whole lives in freshwater), a mix of anadromous and resident, or virtually all anadromous. Each salmon and trout species is struc- tured into discrete breeding populations because the adults return to their natal site to spawn (Quinn 2005). Therefore, the population, rather than the species, is the fundamental unit of conservation, and this is why DPSs of Pa- cific salmon and trout have been listed. 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. 2007). Pacific salmon and trout populations also vary considerably in life- history patterns, including the timing of a series of key events: the return mi- gration by adults from the ocean to freshwater, the spawning season, the emergence of juveniles from gravel nests, the duration of residence in fresh- water, and migration to sea (Quinn 2005). Therefore, depending on the spe- cies and populations in question, fish might be present in one river at vulner- able times of their lives and absent from another river at the same time of that year, and these variations in life-history traits could affect how salmonids are exposed to pesticides. For example, some juvenile Chinook salmon migrate from their natal streams to the ocean in their first summer of life whereas

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Exposure 97 other juveniles of the same species spend a full year in the river system be- fore migrating to sea (Taylor 1990; Healey 1991). The committee notes that the variation in spatial and temporal distribution of juvenile salmon residing in and migrating from river systems is further complicated by the substantial numbers of hatchery-produced juveniles, whose differences from wild fish in size, growth rate, and release timing can all affect migration patterns (Giorgi et al. 1997; Beckman et al. 1998). Sublethal effects on sensory capacity, reaction, swimming ability, buoy- ancy control, or other aspects of performance might increase mortality. For example, chlorpyrifos, a common organophosphate insecticide, inhibited ace- tylcholinesterase in the brain and muscle of salmonids and affected sponta- neous swimming and feeding behaviors of juvenile coho salmon in a concen- tration-dependent manner in the laboratory (Sandahl et al. 2005). Whether and to what degree sublethal effects affect survival in natural conditions is not clear. Laboratory exposure of cutthroat trout to carbaryl, an insecticide ap- plied to oyster beds in some estuaries, affected swimming performance and predator avoidance (Labenia et al. 2007). It is certainly plausible (and per- haps even parsimonious) to conclude that there will be effects on survival in natural settings if environmental concentrations and exposure durations are comparable with those in the laboratory experiments, but the magnitude of the effects in relation to other sources of mortality is difficult to measure or model. Another complication in modeling the effects of pesticide exposure is that salmonids often prey on other salmonids (Duffy and Beauchamp 2008). Moreover, if the population as a whole is stressed by factors that in- crease mortality over natural levels—such as water diversions that reduce flows, dams that alter sediment transport patterns, shoreline development in rivers or estuaries, or predation by nonnative species—the cumulative effects of the many stressors might be sufficient to put populations in jeopardy even though any single stressor, such as pesticide exposure, could have been sus- tained. Chemicals can also have indirect effects on individual organisms and the population. For example, most of the diet of juvenile salmon and trout in streams consists of insects, both larval stages of aquatic insects and terres- trial insects that fall on the stream surface (Nielsen 1992). Reductions in the prey base by pesticides might affect growth rate and life-history transitions that depend on growth (Mangel and Satterthwaite 1998) and have subtle but profound effects on fitness. Analogously, shifts in the insect community and changes in fish behavior associated with fine sediment in the stream bottom might reduce growth and survival of juvenile steelhead (Suttle et al. 2004). Finally, the variation in life-history traits, between and even within species and subspecies, reinforces the importance of knowing the ecology of the par- ticular species and population of concern for ecological risk assessment. 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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98 Assessing Risks to Endangered and Threatened Species from Pesticides BOX 4-1 Continued and coho for more than a year. Pink salmon usually spawn within a few kilo- meters or tens of kilometers of the sea whereas Chinook salmon can migrate 1,500 km upstream or more to spawn, so their juveniles have to migrate the same distance to return to the sea. The different species also have different preferences for spawning substrate, stream sizes, and spawning seasons, all of which vary among their geographic distributions. Thus, the choice of a sur- rogate species for analysis and testing is challenging and complex at best. Even more challenging are the intraspecific variations in behavior, physiology, and distribution. For example, stream-type and ocean-type Chinook salmon differ in many attributes (Quinn 2005) that could affect exposure and vulnera- bility to pesticides. All the variation further emphasizes the need to assess the suitability of the surrogates and the applicability of the laboratory tests careful- ly when making decisions about likely effects of pesticides and other chemi- cals on listed species (Macneale et al. 2010). Pesticides can indirectly affect a given species via effects on other species in the community. Indirect-effects analysis examines how a pesticide affects the habitat of a species. Because the indirect effects of pesticides on the species of concern can be favorable or unfavorable, it is more appropriately described as effects analysis than as hazard analysis. For example, the prey of the species of interest might be reduced in abundance or eliminated by the pesticide, perhaps because the prey is the target pest species or is affected along with the species of interest. Alternatively, populations of its predator or competitor might be re- duced and the abundance of the species of interest thereby increased. 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). In most cases, determining and quantifying such effects are more challenging and might require a conceptual model that incorporates the major components and linkages of the species’ habitat that would respond to pesticide applications (see section “Effects Models” below). The modeling would entail an understanding of the ecology of all the species that might be at risk from pesticide exposure that live in the same area as and use resources similar to those of the listed species. There might be multiple nodes and links between affected species and the species in question, which might result in a fairly complex community dynamics model. There are many candidate models and associated computer software for simulating community and ecosystem interactions (see, for example, Verhoef and Morin 2010). The primary hurdle in their use in decision-making applications is the large number of parameters that are poorly known, which

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Exposure 99 results in substantial implicit uncertainty. Because of the uncertainty, it is important when using such modeling tools to strive to estimate component un- certainties quantitatively in a realistic and scientifically defensible way and to propagate all the component uncertainties through the community-level analysis formally and explicitly. Such methods as Bayesian networks and Monte Carlo approaches for quantifying uncertainty in analyses were discussed in Chapter 2. If quantitative information about community relationships is lacking, a qualita- tive modeling approach could be considered, such as signed digraphs, loop anal- ysis, and matrix analysis (Puccia and Levins 1991). Those types of modeling can help to determine which variables should be included in a community or ecosys- tem model and can provide insight into which ones should be measured to pro- vide the greatest reduction in uncertainty. 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 ques- tions) in the extent to which they consider indirect effects. EPA (2012a, p. 22) stated that “if the best available biological information for a listed species does not establish a relationship between the affected taxa and the listed species, EPA believes that a no effect conclusion is warranted.” That approach is logical, but relationship is not defined. FWS (2012, p. 5) stated that EPA does not consider potentially important “tertiary” effects and that “community-level effects are not considered.” FWS (2012, p. 5) continued that EPA “only considers potential direct effects to those resources immediately relevant to the listed species.” Likewise, NMFS (2012, p. 4) stated that “aspects such as prey dynamics (e.g., how quickly prey availability returns to background levels) and trophic conse- quences of herbicide applications are not considered” by EPA. EPA uses a chemocentric approach to the assessment and begins with what is known about a chemical and its potential to affect various attributes of species’ habitat. The Services take a species-centric approach and describe what is known about the life history of the species of concern, from which they infer the potential for pesticide-related effects. The different approaches seem to fol- low the same pattern as those used to evaluate sublethal effects, in which EPA takes a more quantitative approach and the Services a more qualitative approach. However, both quantitative information and qualitative information are neces- sary for comprehensive ecological assessments of the interactions of xenobiotic chemicals with the critical features of a species’ habitat. Development of a spe- cies-specific conceptual model during the problem-formulation phase of the ecological risk assessment includes a specific enumeration of the important habitat components, which can then be addressed quantitatively or qualitative- ly—depending on the available information—during the effects analysis. The FIFRA Endangered Species Task Force has already begun to gather information on habitat and niche requirements of endangered species into an electronic data- base accessible to EPA and the Services (FESTF 2012).

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100 Assessing Risks to Endangered and Threatened Species from Pesticides Cumulative Effects In the context of the ESA, cumulative effects are defined as “those effects of future State or private activities, not involving Federal activities that are rea- sonably certain to occur within the action area of the Federal action subject to consultation” (50 CFR 402.02). As is the case with indirect effects, that defini- tion is not the common definition used by many ecologists who tend to use the definition promulgated by the Council on Environmental Quality (CEQ) under the National Environmental Policy Act (40 CFR Parts 1500-1508, 1978) in which a cumulative effect is “the incremental [effect] of [an] action when added to other past, present, and reasonably foreseeable future actions.” In other words, cumulative effects are ones that “interact or accumulate over time and space, either through repetition or in combination with other effects” (NRC 2003, p. 2). However, the regulatory definition in 50 CFR 402.02 becomes much more like the CEQ definition if one incorporates the “environmental baseline,” which includes past and present conditions. The committee could not determine a scientific basis for excluding other federal actions from the consideration of cumulative effects. Present and past federal actions are included in the environ- mental baseline. Therefore, in the following discussion, the committee’s under- standing of cumulative effects incorporates the environmental baseline. The committee notes that cumulative effects are related to aggregate effects—effects that result from exposure through multiple pathways. However, such effects would also be captured by considering or incorporating baseline conditions Species live in variable environments and are constantly subjected to a va- riety of stressors. Some stressors, such as extreme weather, are stochastic (ran- dom and inherently unpredictable in magnitude and frequency) and might act on populations in a non-density-dependent fashion. In other words, the effects will be the same regardless of how many organisms are present. Other stressors, such as parasitism and predation, are more predictable and are density-dependent (they depend on the number of organisms present). Exposure to pesticides is one of many exogenous stressors that might influence the type and degree of re- sponse of species (Coors and De Meester 2008). Rohr et al. (2006) proposed using concepts in community ecology and evolutionary theory to provide in- sights about cumulative effects of pesticides and other anthropogenic or natural stressors. 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. Therefore, the interaction of existing stress- ors with the pesticides under consideration is within the purview of the Services and appropriately part of a BiOp. EPA, as the action agency, is responsible for providing the Services with any information that is known about how toxicity of a pesticide is modified by environmental factors (for example, effects of cold

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Exposure 101 stress on pesticide toxicity). The responses to multiple stressors that are likely to have an effect (or have an increased effect) in the future are the cumulative ef- fects. The committee has concluded that population models (see section “Effects Models at the Population Level” below) 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), habitat fragmentation (as changes in the spatial structure of the model), and climate change (for example, as increases in temporal variability of survival and fecundity to simulate the effect of an increase in frequency of extreme weather events). Such an approach will necessarily be chemocentric because the pesticide is the additive stress, but the approach also takes into ac- count species-environment interactions and includes the effects of stressors oth- er than the pesticide on a species. In some cases, the pesticide being assessed has been in use for a long time, and the baseline population model already includes pesticide-induced reductions in survival and fecundity. Therefore, the calculated reductions in survival and fecundity are added to the baseline model's survival and fecundity (thus increas- ing their values) to obtain a model that simulates the dynamics of a population that is not exposed to the pesticide. The difference between the projections of that model and of the baseline model is an estimate of the degree to which cur- rent use and past use of the pesticide are contributing to the risks faced by a listed species or preventing its recovery. Thus, the risk assessor uses the infor- mation (risks with and without the pesticide) to inform the reregistration deci- sion. The procedure described here does not require any more data than the case in which the baseline data are coming from populations that are not exposed to a pesticide. EFFECTS MODELS Effects models are used to characterize the effects of a pesticide at the in- dividual level (effects on survival and reproduction) and at the population level (effects on population viability and recovery). EPA and NMFS use different models to evaluate the potential effects of a pesticide active ingredient on listed species and critical habitat. As described in its overview of ecological risk as- sessments for listed species (EPA 2004), EPA does not use effects models in its assessments. It assesses direct effects associated with different pesticide concen- trations by using a risk-quotient (RQ) model that involves dividing an estimated exposure concentration by an effect concentration based on various prescribed toxicity tests and on published data. The derived RQ is compared with various levels of concern (LOCs) to determine whether a direct effect is likely. During

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