Week 4

Analyzing Ecological Systems

Option 2: Gulf Oil Spill Case Study

Resource: University of Phoenix Library

Write a 700- to 900-word analysis of the British Petroleum Oil Spill in the Gulf of Mexico. Include the following in your paper:

· Describe the main events of the incident and the principle parties involved in a timeline.

· Describe the laws enforced at the time.

· List the ecological risks of the affected area at the time of the spill.

· Forecast what may be required of the oil industry relative to future risk assessments.

· How can economic value be allocated in this scenario?

· Describe the process of defining ecological value and discuss the application of probabilistic risk assessment methods in this case. Discuss the hazards and the risk uncertainties that can lead to a reanalysis of this case using probabilistic assessment.

· Describe how the risk assessment correlated to observed field studies and evaluate the importance of this type of correlation in general for all risk assessment efforts.

· What are the ecological and social values of concern in this case?

· Establish a value for the ecological components in this case. Are there any tradeoffs between wildlife and development? Why or why not? How is this risk assessment actually determined?

Cite two references.

Format your analysis consistent with APA guidelines.

Reference

Chapter 22 Using Probabilistic Risk Assessment Methods to Predict Effects of Pesticides on Aquatic Systems and Waterfowl That Use Them

PATRICK J. SHEEHAN and JOHN WARMERDAM

Exponent, Oakland, California

SHIH SHING FENG

PE Biosystems/Celera, Foster City, California

22.1 INTRODUCTION

One of the most comprehensive of the early prospective ecological risk assessments published is the Canadian Wildlife Service study entitled “The Impact of Pesticides on the Ecology of Prairie Nesting Ducks” (Sheehan et al., 1987). This assessment was conducted to evaluate the potential direct toxic effects of the more commonly used organochlorine and organophosphate insecticides and the more recently developed pyrethroid insecticides on aquatic macroinvertebrates in sloughs in the pothole region of Canada and the subsequent indirect impact of invertebrate mortality (loss of food resources) on duckling survival and recruitment. Although this assessment provided a thorough and quantitative analysis of the potential risks to duck populations associated with the aerial spraying of insecticides in the agricultural region of the Canadian Prairie and was used to develop a program to manage those risks, the assessment was incomplete by today’s standards in that it did not include a quantitative analysis of uncertainties (SETAC, 1998). A probabilistic approach, where input parameters are characterized as distributions of plausible values, is now employed to represent the variability inherent in diverse populations as well as the uncertainty implicit in the quantification of environmental factors. This case study provides a reanalysis of the Canadian Wildlife Service study data using probabilistic methods to characterize variabilities and uncertainties in estimates of exposure and the direct effects on aquatic macroinvertebrates from pesticides released to prairie pothole sloughs as the result of aerial spraying for agricultural pest control. The assessment also shows how the results of this analysis can be used to relate uncertainties in the magnitude of mortality in the macro-invertebrate community and the food resource for ducklings to associated indirect effects on ducklings and risks to duck populations.

22.2 BACKGROUND

The pothole region of the United States and Canada is the principal grain-growing region of North America. The region is geographically defined as a swath of land crossing the provinces of Alberta, Saskatchewan, and Manitoba in Canada and the states of Minnesota, North and South Dakota, Iowa, and Montana in the United States and is dotted with a vast number of freshwater ponds that are primarily small, shallow, and biologically productive sloughs ringed with aquatic plants. For the purposes of this chapter, slough and pothole are used interchangeably and refer to any depression holding water. Sloughs are critical habitat for a wide variety of aquatic organisms and wildlife, most notable of which are the estimated 16 million ducks that nest there annually. There is an intimate relationship between the ecology of these sloughs and the essential resources they provide to the waterfowl that inhabit them for part of each year. The overlap between agriculture and waterfowl habitat has been of concern to wildlife agencies for more than a decade. The potential impact of the agricultural use of pesticides in the pothole habitat began to receive attention from the Canadian Wildlife Service in the mid-1980s (Shaw et al., 1984; Mineau et al., 1987; Sheehan et al., 1987; Forsyth, 1989) and the U.S. Fish and Wildlife Service (Grue et al., 1986, 1989).

Assessing the indirect risks to waterfowl posed by pesticide use in the pothole region requires an understanding of the extent of spatial and temporal overlap of pesticide spraying and aquatic macroinvertebrates and ducks in this duck nesting habitat. The prairie pothole region of North America covers about 300,000 mi2 (770,000 km2). The average density of sloughs in the pothole region is 12 km−2, with values ranging from 4 to 40 km−2 (Smith et al., 1964). Seasonal and annual variability in the number of sloughs is high. The average number of sloughs decreases, due to drying, 20 to 35 percent between May and July; over 80 percent of the ponds lost are less than 0.5 acres (0.2 ha) in size. More than 8 million pairs of ducks breed and rear young in small prairie sloughs each year. Approximately 93 percent of the breeding ducks in the prairie region nest in agricultural land. Based on potential land use in the prairie region, from 60 to 80 percent of the best waterfowl breeding and rearing areas overlap with the best agricultural land in the pothole region (Sheehan et al., 1987). The reproductive process for ducks takes place in these areas between May and September. Typically, this is also the period during which farmers do most of the spraying of grain crops for pest control.

Of the insect pests of prairie crops, grasshoppers are potentially the most important because they occasionally give rise to outbreaks that cover large areas. Grasshopper infestations in the prairies have affected between 3 and 21 million ha annually (Sheehan et al., 1987). Control of these grasshoppers is considered necessary by farmers; thus large quantities of pesticides are applied during outbreaks. The actual areas sprayed with pesticides each year are more difficult to determine. It has been estimated that 3 to 4 million ha are sprayed during years of serious grasshopper outbreaks. This represents about 10 percent of the agriculturally cultivated land in the pothole region. The primary insecticides sprayed during grasshopper infestations are carbofuran, carbaryl, and pyrethroid compounds such as deltamethrin. From 10 to 25 percent of the spraying for grasshoppers is done aerially.

Typically, spraying to control grasshoppers occurs from late May to August. This time frame includes two of the critical periods in the annual reproductive process of all duck species: egg formation and early foraging by newly hatched ducklings. During the reproductive period, adults and ducklings are highly dependent on food from pothole sloughs, particularly aquatic macroinvertebrates. The nutritional demands of hens for egg formation are met by including high quantities of these macroinvertebrates in their diet (Krapu 1974a, b, 1979). All hens consume more than 70 percent animal food during this period (Noyes and Jarvis, 1985). Aquatic insects, crustaceans, and snails are highly selected, presumably because of their protein and calcium content. Although there are less data available on the diet of ducklings than on the diet of laying hens, evidence indicates a likewise high dependence on animal food, primarily aquatic macroinvertebrates, for a period of 1 to 7 weeks posthatch, depending on the species.

There is a substantial spatial and temporal overlap between pesticide spraying and reproducing ducks in the prairie pothole region. This overlap indicates the potential for direct exposure of both adults and ducklings to the pesticides. In addition, due to the importance of macroinvertebrates in the diets of laying hens and ducklings and the widespread aerial application of pesticides for control of grasshoppers, there is also the potential of broad-scale pesticide-induced mortality within the exposed sloughs’ macroinvertebrate community and subsequent indirect effects on duck reproductive success.

22.3 PROBLEM FORMULATION

Problem formulation is the first step in an ecological risk assessment. The problem formulation identifies the ecological receptors to be evaluated, the chemicals of interest, the relevant exposure scenarios, measurement and assessment endpoints, the risk assessment approach, and other specifications or limits of the assessment.

22.3.1 Receptors of Interest

Although the risks of pesticide use on duck populations are of ultimate interest, this assessment is focused on estimating the probability and magnitude of the effects of spraying pesticides (aerially) on aquatic macroinvertebrates, a critical food resource for reproducing ducks. Therefore, the aquatic macroinvertebrate community in pothole sloughs is the receptor of primary interest in this assessment.

The high diversity of microhabitats in pothole sloughs supports a diverse invertebrate fauna. Species in 38 orders and families have been reported in these sloughs (Perret, 1962; Sugden, 1964; Swanson et al., 1974). It is the species of classes Gastropoda, Crustacea, and Insecta that are of greatest interest because they are the preferred invertebrate food of ducks. The families of macroinvertebrates from these three classes commonly found in prairie sloughs are given in  Table 22.1 . The taxa of macroinvertebrates most often cited as dominant in freshwater sloughs are gastropods, amphipods, notonectids, corixids, and the larvae of dipterans, tricopterans, odonates, and ephemeropterans (Joyner, 1980, 1982). These taxa are generally found on submergent vegetation and associated with a variety of substrates such as rock, sand, silt, or detritus. It is clear the dominant macroinvertebrate taxa in these sloughs are also the preferred prey for ducklings ( Table 22.2 ).

The vegetation provides habitat for the greatest number of macroinvertebrates. The abundance of macroinvertebrates associated with aquatic plants has been estimated to range between 1000 and 6000 individuals/m2 of the vegetated area of slough (Biggs and Malthus, 1982; Scheffer et al., 1984; Keast, 1984). The total invertebrate abundance and/or biomass usually reaches the highest value in late spring or early summer (late May to late June) in pothole sloughs (Swanson et al., 1974; Joyner, 1982).

22.3.2 Chemicals of Interest

The most commonly used insecticides for grasshopper control on cereal grain, oil seed, and forage crops in the prairie pothole region are azinphos-methyl, carbaryl, carbofuran, cypermethrin, deltamethrin, dimethoate, malathion, and methamidophos (Saskatchewan Agriculture, 1984; Manitoba Agriculture, 1984). The three most widely used insecticides in the Canadian prairies for grasshopper control in the late 1980s and 1990s were carbofuran, carbaryl, and deltamethrin. This assessment is focused on two of these compounds: carbaryl and deltamethrin. These compounds represent the widely used organophosphate insecticides and more recently developed synthetic pyrethroid insecticide groups.

22.3.3 Assessment and Measurement Endpoints

Assessment endpoints are the characteristics of the ecological system to be protected. In this case, it is the protection of the macroinvertebrate community from reductions in survival, growth, and/or reproduction resulting from exposure to the pesticide in water. The measurement endpoint is the comparison of estimated concentrations of the pesticide in water with concentrations determined to be toxic in laboratory toxicity tests with macroinvertebrate species.

TABLE 22.1  Invertebrate Taxa Commonly Found in Prairie Sloughs

Source: From Perret (1962), Sugden (1964), and Swanson et al. (1974).

Phylum	Order (Suborder)	Family	Common Name
Protozoa			Protozoans
Porifera	Haploscelerina	Spongillidae	Freshwater sponges
Coelenterata			Hydras
Plathelminthes			Flatworms
Gastroticha			Gastrotrichs
Rotatoria			Rotifers
Nematoda			Nematodes
Annelida			Aquatic earthworms
Hirundinea			Leeches
Gastropoda	Basommatophora	Physidae	Freshwater snails
		Lymnaeidae	(e.g., Lymnae, Physa, Helisoma)
		Planorbidae
Pelecypoda		Unionidae	Freshwater mussels
		Sphaeriidae	Freshwater clams
Arthropoda	Acarina
	Trombidiformes		Water mites
Crustacea
Branchiopoda	Anostraca		Fairy shrimps
	Notostraca		Tadpole shrimps
	Diplostraca
	Conchostraca		Clam shrimps
	Cladocera		Water fleas
Ostracoda			Seed shrimp
Copepoda			Copepods
Malacostraca	Isopoda		Isopods (aquatic sow bugs)
	Amphipoda		Amphipods (scuds, side swimmers)
Insecta	Collembola		Springtails
	Emphemeroptera		Mayflies
	Odonata
	Anisoptera		Dragonflies
	Zygoptera		Damselflies
	Hemiptera	Gerridae	Water striders
		Notonectidae	Back swimmers
		Belostomatidae	Giant water bugs
		Corixidae	Water boatmen
	Neuroptera		Dobsonflies
	Trichoptera		Caddisflies
	Coleoptera		Aquatic beetles
		Dystricidae	Predaceous diving beetles
	Diptera		Flies, mosquitoes, midges
		Culicidae	Mosquitos, phantom midges
		Chironomidae	True midges
		Stratiomyidae	Soldier flies

TABLE 22.2  Macroinvertebrate Prey Selected by Flightless Ducklings Foraging in Prairie Pothole Region

Species	Selected Macroinvertebrate Prey in Approximate Order of Importance	Reference
Dabblers Mallard	True fly larvae, pupae (primarily Chironomidae)	Chura, 1961; Perret, 1962
	Caddisfly larvae (primarily Limnophilidae)
	Aquatic snails (particularly Lymnaeidae)
	Dragon- and damselfly nymphs (Odonata)
	Water boatman adults, nymphs (Corixidae)
	Beetle larvae, adult (Hydrophilidae, Dytiscidae)
Divers Lesser scaup	Scuds (Amphipods)	Bartonek and Hickey, 1969a, b; Sugden, 1973
	Aquatic snails (Lymnaeidae)
	Midge larvae, pupae (Chironomidae)
	Dragonfly naiads (Zygoptera)
	Caddisfly larvae (Leptoceridae)
	Beetle larvae (Haliplidae, Dytiscidae)

22.3.4 Conceptual Assessment Model

The aquatic macroinvertebrate community in pothole sloughs is potentially exposed to pesticides sprayed aerially for grasshopper control when the ponds are directly sprayed and/or when drift from spraying in the upwind direction is deposited on the ponds. The highest concentrations in slough water resulting from spraying occur within the initial 24 hours after spraying as the pesticide mixes into the water column. It is the likelihood and magnitude of invertebrate mortality during the initial high exposure period that are of interest in this assessment. Macroinvertebrates are exposed to the pesticides through gill absorption, dermal uptake, and ingestion of the chemical in water and food. In this case, the primary measure of exposure is the estimated concentration of the pesticide in slough water. Sediment concentrations are not considered in this analysis, as steady-state partitioning between the water column and sediments is unlikely to be reached in the short time frame considered immediately after pesticide application. A distribution of exposure concentration is developed based on the variability and uncertainties in application and slough parameters. Effects on the macroinvertebrate community are characterized using mortality data from laboratory toxicity tests with aquatic insect and crustacean species. Effects distributions representing lethal concentrations for the “community” of test species are developed from test data. The exposure concentration distribution is then compared to the effects distribution to characterize the probability and magnitude of mortality in the exposed aquatic macroinvertebrate community.

22.4 RISK ASSESSMENT APPROACH

To assess the risks of aerial spraying of pesticides on the macroinvertebrate community in the slough ecosystem, a number of exposure assessment, effects assessment, and risk characterization tasks must be completed. These include the following:

Exposure assessment:

· Estimation of the distribution of concentrations of aerially sprayed pesticides in slough water based on application rates and efficiencies and slough conditions

Effects assessment:

· Compilation of toxicity test data for aquatic macroinverebrates for the pesticides

· Development of distributions of effect concentrations for the aquatic macroinvertebrate community

Risk characterization:

· Comparison of the overlap in the estimated concentration distribution with the lethal effects distributions for the macroinvertebrates

· Calculation of the probability of the exposure concentration exceeding the effects concentration for macroinvertebrate species

· Calculation of the probability of the exposure concentration exceeding specific percentiles of the effects concentration

22.5 EXPOSURE ASSESSMENT

Exposure assessment is the process used to characterize the magnitude, frequency, and duration of exposure concentrations or doses of a chemical to the receptors of interest. In this case, exposure is characterized as the estimated distribution of pesticide concentrations in water in oversprayed sloughs. Water column concentrations are estimated based on application rate, application efficiency, slough size and depth, and mixing assumptions.

22.5.1 Considerations

The entry of pesticides into pothole sloughs is expected to occur through direct application (overspray), droplet drift, runoff, or seepage. The likelihood of direct application is highly dependent on the selected mode of application and is greatest for aerial application. Analysis of direct overspray in the pothole region depends on assumptions about applicator ability, specific limitations in aircraft control, the effectiveness of buffer zones, and the size, number, and locations of the sloughs. For small sloughs (less than 0.4 ha) with narrow margins, which are common in cultivated lands, partial overspray is highly probable. These ponds may account for 60 to 80 percent of the sloughs available to ducks in May and June, when pesticide spraying is likely. In the worst case of direct aerial overspray, 100 percent of the applied amount would be deposited on the sloughs and margins. Under a variety of meteorological and application conditions, on-target deposits have been found to vary substantially and rarely approach 100 percent. An average on-target deposit of 50 percent of the application rate has been estimated from a single-swath application. Each additional overflight of a slough can potentially increase the amount of the pesticide deposited into the slough. Overspray deposits of approximately 80 percent of applied quantities are expected from multiswath applications common in grasshopper control (Ware et al., 1970). Therefore, in areas being sprayed aerially, the amount of pesticide reaching slough water is largely a function of the application rate and the number of swaths sprayed.

The second substantial source of pesticide contamination is drift droplet deposition from upwind application. The concentration of pesticide deposited off-target decreases rapidly with distance. Studies show that deposits at 50 m downwind of the direct area of application ranged from 1 to 10 percent of applied quantities (Argauer et al., 1968; Ware et al., 1969; Renne and Wolf, 1979; Currier et al., 1982). In contrast, runoff is expected to be a relatively small contributor in areas of aerial application, perhaps less than 1 percent (Wauchope, 1978). In this case, only deposition from direct overspray due to a single-swath application is considered in estimating pesticide concentrations in slough water.

The other primary factors to be considered in estimating the exposure concentration in slough water are the slough conditions. These include water depth and mixing conditions for incorporating the deposited mass of pesticide and the processes that would remove the pesticide from the water column. Among the assumptions made about these sloughs is that mixing occurs through the entire water column more rapidly than other rate-governed processes (partitioning, degradation) and that the surface film effect and other physical and chemical processes (volatilization, photodegradation) will have negligible influence on water column concentrations in the short term. This is a reasonable assumption because the time frame within which the initial high concentration is achieved in slough water is short, generally less than 24 hours, and is insufficient for rate-governed transfer and removal processes to substantially affect concentrations in the water column.

22.5.2 Exposure Methods

The concentration of the pesticide in slough water shortly after spraying can therefore be estimated as a function of the application rate, the application efficiency, and the depth of the water body that is oversprayed, assuming that aerial applications are generally single swath and the additional contribution from drift is negligible. The application rate is expressed in terms of grams of pesticide applied per square meter; application efficiency as the fraction of the applied pesticide that reaches the water body; and depth of the water body as the average depth, in meters. The concentration in the water column in grams per cubic meter or milligrams per liter due to direct overspray is calculated as follows:

It is expected that water column concentration distributions based on this methodology are representative of operating conditions as drift input, which would increase deposition, is ignored and surface film effects and removal processes, which would limit water column concentrations, are discounted.

22.5.3 Application Rate

Application rates for individual pesticides are recommended by the manufacturer and by governmental agricultural agencies. Rates recommended by insect control agencies in Alberta, Manitoba, and Saskatchewan are 7.5 g/ha for deltamethrin and 1100 g/ha for carbaryl (Sheehan et al., 1987). Variation in application rates is introduced through mechanical, physical, and chemical processes and human error. Applicators introduce error when mixing volumes of pesticides with adjuncts and the spray medium (typically water). Pesticides are metered out through nozzles on the trailing edge of airplane wings. Improperly adjusted or malfunctioning nozzles or pumps affect the application rate. Fluid dynamics (settling, miscibility, and density effects) of the pesticide and mixtures also cause variation in the application rate over the course of a single application. Pilot error with respect to ground speed and application altitude also contributes to variation in application rates. These and other factors combine to produce a range of possible application rates for each pesticide. Little data exist to help define the extent of this type of variability with respect to recommended application rates. We assume that the suggested application rate is the mean value of the distribution of actual application rates and that the standard deviation of the application rate is 10 percent of the suggested application rate. We further assume that application rates are normally distributed and that the distribution is truncated on both ends, three standard deviations from the mean. This distribution provides a representation of application rates that includes the variability and uncertainty described previously.  Table 22.3  and  Figures 22.1  and  22.2 summarize characteristics of the random variables used to describe the application rates for carbaryl and deltamethrin.

TABLE 22.3  Summary Statistics for Application Rates

Pesticide	Mean Value (mg/m2)	Standard Deviation (mg/m2)	Minimum Value (mg/m2)	Maximum Value  (mg/m2)
Carbaryl	110	11	77	143
Deltamethrin	0.75	0.075	0.525	0.975

22.5.4 Application Efficiency

Application efficiency is a measure of how much of the applied pesticide actually reaches its intended target and is affected primarily by physical and chemical processes. Wind speed and droplet size are the two most important factors in determining application efficiency. Smaller droplets tend to stay airborne longer, leaving them vulnerable to lateral dispersion by wind. The pesticide formulation and the atomization process used for pesticide application determine the droplet size distribution. Pesticide formulations vary in specific characteristics, such as surface tension, density, and viscosity, which affect the droplet size distribution. Other factors that influence application efficiency include application height, relative humidity, ambient temperature, sunlight, and backwash turbulence of the applicator aircraft. Empirical studies show that between 14 and 95 percent of applied pesticides are deposited on-target (Maybank et al., 1976, 1978a, b; Renne and Wolf, 1979; Ware et al., 1970, 1984; Hill and Kinniburgh, 1984). None of the data are conclusive in characterizing the shape of the application efficiency distribution. To ensure a conservative concentration estimate, a minimum and maximum application efficiency of 40 and 100 percent are used, and 80 percent is designated as the most likely application efficiency. The distribution of application efficiencies is modeled as a random variable with a triangular distribution, whose characteristics are summarized in  Table 22.4  and  Figure 22.3 .

Figure 22.1  Distribution of carbaryl application rates.

Figure 22.2  Distribution of deltamethrin application rates.

22.5.5 Pond Depth

The depth of the affected water body is the final variable modeled as a random variable. The four classifications of water bodies used in this study are ephemeral potholes, temporary potholes, semipermanent potholes, and permanent wetlands. The depth of these water bodies varies depending on weather and time of year. The depth and permanency of these water bodies are given in  Table 22.5 .

Breeding pairs of birds exhibit preferences for different water body types. Kantrud and Stewart (1984) demonstrated that 64 percent of breeding pairs nested in or near semipermanent potholes, 33 percent chose temporary potholes, 2 percent chose permanent wetlands, and 1 percent were found in ephemeral potholes. From this information, a custom distribution is constructed to model water body depth ( Table 22.5 ,  Figure 22.4 ).

TABLE 22.4  Characteristics of Application Efficiency Distribution

Pesticide	Minimum (fraction or target)	Maximum (fraction or target)	Most Likely Value (fraction or target)
Carbaryl	0.4	1.00	0.80
Deltamethrin	0.4	1.00	0.80

Figure 22.3  Insecticide application efficiency distribution.

TABLE 22.5  Depth and Permanency of Water Body Types

Water Body Type	Depth (m)	Permanency	Probability of Use by Ducklings
Ephemeral potholes	0–0.3	Few days to few weeks	0.01
Seasonal potholes	0.3–0.61	4–12 weeks	0.33
Semipermanent potholes	0.61–1.52	Several years	0.64
Permanent wetlands	1.52–3.0	Indefinite	0.02

22.5.6 Exposure Concentration Distributions

Exposure concentration distributions for carbaryl and deltamethrin were estimated from input parameter distributions using Crystal Ball version 4.0 and 100,000 Monte Carlo simulations.  Figures 22.5  and  22.6  present the estimated frequency distributions for carbaryl and deltamethrin concentrations in pothole sloughs.  Table 22.6  presents the summary statistics for the estimated pesticide concentrations.

Figure 22.4  Distribution of depth of waters in pothole sloughs.

Figure 22.5  Distribution of carbaryl concentrations in water in pothole sloughs.

Figure 22.6  Distribution of deltamethrin concentrations in water in pothole sloughs.

A series of standard continuous distributions (including normal, lognormal, and Weibull) were fit to the concentration data for each pesticide. The lognormal distribution provided the best fit of the data, and the concentration distributions are characterized as approximately lognormal. These data are used to characterize the range and distribution of exposure concentrations to which macroinvertebrates might be exposed in oversprayed sloughs.

TABLE 22.6  Summary Statistics for Water Column Concentrations

Pesticide	Mean Value (μg/L)	Standard Deviation (μg/L)	Minimum Value (μg/L)	Maximum Value (μg/L)
Carbaryl	119	84.2	14.5	2080
Deltamethrin	0.811	0.57	0.102	13.9

22.6 EFFECTS ASSESSMENT

The effects assessment is a quantitative description of the relationship between the concentration or dose of the chemical and the type and incidence of adverse effects elicited in exposed receptors. The most commonly reported toxicological benchmark from laboratory toxicity tests is the LC50, that is, the concentration killing 50 percent of the test organisms within a specific exposure period, normally 24, 48, or 96 hours. The LC50 data, if reported with confidence limits or the slope of the concentration–response curve, can be used to estimate lethal concentrations for various percentages of the test organisms (e.g., LC1, LC10, LC20, LC30, LC40, LC60, LC70, LC80, LC90, LC99). These data are then used to develop an effects distribution for each test species and aggregated to develop effects distributions for the “community” of invertebrate test species. It is these lethal concentration distributions that are used to characterize the effects relationship for the macroinvertebrate community.

22.6.1 Toxicity Data

The concentration-response relationships for carbaryl and deltamethrin are characterized based on toxicity test data for aquatic invertebrate species. The effects of acute exposures to carbaryl have been evaluated in tests with 23 aquatic macroinvertebrate species ( Table 22.7 ). These include data for mosquitoes, midges, stoneflies, mayflies, dragonflies, amphipods, and daphnids. The effects of acute exposures to deltamethrin in water have been evaluated for 22 species; however, these represent primarily midges and mosquitoes ( Table 22.8 ). To provide test data for a broader range of macroinvertebrate taxa, data for a toxicologically similar pyrethroid pesticide, cypermethrin, are included in this evaluation ( Table 22.8 ). The 24-hour LC50 values for cypermethrin and deltamethrin for the same genera of mosquitoes and midges are generally within a factor of 4 (Sheehan et al., 1987).

22.6.2 Toxicity Model

The response endpoint of interest is the lethal concentration associated with a 24-hour exposure. Since not all invertebrate tests report lethal concentrations for 24-hour exposure periods, the initial step in constructing distributions of lethal concentrations was to extrapolate LC50 values for 48- and 96-hour exposure periods to equivalent values for the 24-hour exposure period of interest. This extrapolation was accomplished with an integrated toxicity model based on the premise that lethal toxicity is a function of percent mortality and exposure time. Discounting any lag time or delayed effects in response to exposure, the relationship between the median lethal concentration of the chemical and the duration of exposure can be expressed as LC50 × exposure duration = toxicity constant, which approximates the integrated median lethal exposure. Although the relationship between lethality and time does not hold for all pesticides and aquatic invertebrate species, it has been shown to be a good general model for estimating lethal concentrations from 24- to 96-hour tests (Allison, 1977; Sheehan et al., 1987; French, 1991).

Lethal concentrations are generally estimated from test data using the log-probit model; that is, percent mortality is a lognormal function of exposure concentration [Finney, 1971; U.S. Environmental Protection Agency (EPA), 1975; Stephan, 1977], Using the log-probit model and the reported or extrapolated 24-hour LC50 value and confidence limits or concentration-response slope, the LC1, LC10, LC20, LC30, LC40, LC60, LC70, LC80, LC90, and LC99 were estimated for populations of each invertebrate test species exposed to carbaryl or deltamethrin. For the cases where neither confidence limits nor concentration-response slope were reported, the slope for a taxonomically similar species was used to calculate the lethal concentrations for the selected percentages of response.

22.6.3 Lethal Concentration Profiles

The lethal concentration profiles for populations of invertebrates for which relevant data are available are shown in  Tables 22.9  and  22.10  for carbaryl and deltamethrin, respectively. These profiles were used to characterize the lethal concentration distribution for the population of each test species. A similar approach was used by French (1991) to develop the toxicity database that is used in the Natural Resource Damage Assessment Model to estimate mortality of aquatic biota following spills of toxic substances in both freshwater and saltwater environments.

If one assumes that the species tested reasonably represent a cross section of the invertebrates in prairie sloughs, then the lethal concentration profiles for test species can be aggregated to develop effects distributions for the aquatic invertebrate community. That is, probability density distributions can be developed for each lethal concentration percent with the range and shape of the distribution representing the sensitivity of the community to acute exposures to the pesticide. Although it is clear that the test species do not represent the full suite of invertebrate taxa in prairie sloughs (see  Table 22.1 ), they do represent reasonably well the dominant taxa in these freshwater wetlands and the preferred prey of ducklings (see  Table 22.2 ). The taxa of invertebrates most often cited as dominant in prairie sloughs are the gastropods, amphipods, notonectids, corixids, larval dipterns, tricopterns, odonates, and ephemeropterns (Dvorak, 1970; Krull, 1970; Joyner, 1980, 1982; Mittlebach, 1981; Biggs and Malthus, 1982; Dvorak and Best, 1982). Daphnids are also quite common in deeper sloughs (Collias and Collias, 1963). Of the dominant taxa, tests with carbaryl do not include data for gastropods, notonectids, corixids, or tricopterns. For deltamethrin, there are no test data for gastropods, notonectids, tricopterns, or odonates. Perhaps the most important taxa for which no test data are available are the gastropods. While not the most numerous taxa, gastropods often contribute the most to the total invertebrate biomass in prairie sloughs. Available data for other pyrethroid insecticides suggest that the snails are relatively tolerant to these compounds (Sheehan et al., 1987). The aggregated distributions of lethal concentrations are therefore reasonably representative of dominant slough taxa but may overestimate toxicity to the more tolerant invertebrate taxa, such as gastropods.

TABLE 22.7  Summary of Toxicity Data for Carbaryl

Species Tested	Stage	Test Type	Toxicity Reported	LC50 Concentration, µg/L (95% fiducial limits)	Slope of Concentration-Response Curve	References a
Mosquito
Culex p. pipiens	4th instar	S	24 h LC50	75	1.77	Rawash et al., 1975
Aedes cantans	4th instar	S	24 h LC50	377	1.86	Rettich, 1977
Aedes vexans	4th instar	S	24 h LC50	322	1.63	Rettich, 1977
Aedes excrucians	4th instar	S	24 h LC50	145	3.02	Rettich, 1977
Aedes communis	4th instar	S	24 h LC50	168	2.59	Rettich, 1977
Aedes punctor	4th instar	S	24 h LC50	298	2.10	Rettich, 1977
C. p. pipiens	4th instar	S	24 h LC50	333	1.55	Rettich, 1977
Culex p. molestus	4th instar	S	24 h LC50	418	1.80	Rettich, 1977
Culiseta annulata	4th instar	S	24 h LC50	180	1.62	Rettich, 1977
Aedes aegypti	2nd instar	S	96 h LC50	1.9	–	Lakota et al., 1981
Phantom midge, Chaoborus sp.	larvae	S	24 h LC50	650	1.90	Bluzat and Seuge, 1979
Midge, Chironomus plumosus	larvae	S	48 h LC50	10		Sanders et al., 1983
Stonefly Pteronarcys californica	30-35 mm	S	24 h LC50	30 (22-40)	–	Sanders and Cope, 1968
	30-35 mm	S	48 h LC50	13 (10-16)	–	Sanders and Cope, 1968
	30-35 mm	S	96 h LC50	4.8 (3.0-7.7)	–	Sanders and Cope, 1968
Pteronarcella baddia	15-20 mm	S	24 h LC50	5.0 (3.6-7.0)	–	Sanders and Cope, 1968
	15-20 mm	S	48 h LC50	3.6 (2.9-4.8)	–	Sanders and Cope, 1968
	15-20 mm	S	96 h LC50	1.7 (1.4-2.4)		Sanders and Cope, 1968
	Nymph	S	96 h LC50	13	–	Woodward and Mauck, 1980
Mayfly Cloeon sp.	Nymph	S	48 h LC50	480		Bluzat and Seuge, 1979
Cloeon dipterum	9.3 mm	S	48 h TLm	370	–	Hashimoto and Nishiuchi, 1981
Dragonfly, Orthethrum albistylum speciosum	23 mm	S	48 h TLm	430	–	Hashimoto and Nishiuchi, 1981
Amphipod Gammarus lacustris	2 months	S	24 h LC50	40 (32-49)	–	Sanders, 1969
	2 months	S	48 h LC50	22 (16-30)	–	Sanders, 1969
	2 months	S	96 h LC5O	16 (12-19)	–	Sanders, 1969
Gammarus fasciatus	–	S	96 h LC50	26 (16-39)	–	Sanders, 1972
Gammarus pseudolimnaeus	–	S	96 h LC50	4.1-11.9	–	Woodward and Mauck, 1980
	Mature	S	96 h LC50	16 (12-19)	–	Sanders et al., 1983
Gammarus pulex	Mature	S	24 h LC50	35 (32-29)	–	Bluzat and Seuge, 1979
Waterflea Daphnia magna	5d	S	48 h LC50immobilization	7.2	–	Lakota et al., 1981
	1 st instar	S	48 h EC50immobilization	5.6 (2.7-12.0)	–	Sanders et al., 1983
Daphnia pulex	–	S	3 h TLm	30	–	Hashimoto and Nishiuchi, 1981
	1 st instar	S	48 h EC50immobilization	6	–	Cope, 1966
	–	S	48 h EC50immobilization	6.4 (4.5-8.9)	–	FWPCA, 1968
Daphnia carinata	2-2.5 mm	S	24 h TLm	100	–	Santharam et al., 1976
	2-2.5 mm	S	48 h TLm	35	–	Santharam et al., 1976
Simocephalus serrulatus	1 st instar	S	48 h EC50immobilization	8.0	–	Cope, 1966
	1 st instar	S	48 h EC50immobilization	7.6 (6.2-9.3)	–	Sanders and Cope, 1966

a  FWPCA, Federal Water Pollution Control Administration.

TABLE 22.8  Summary of Laboratory Studies of Toxicity of Deltamethrin and Cypermethrin

Species Tested	Size/Stage	Test Type	Toxic Effect Reported	Value, µg/L (95% fiducial limits)	Slope of Concentration-Response Curve	References
Deltamethrin
Mosquito
Culex p. quinquefasciatus	4 instar	S	24 h LC50	0.02	1.68	Mulla et al., 1980
Culex tarsalis	4 instar	S	24 h LC50	0.06	1.21	Mulla et al., 1980
Culiseta incidens	4 instar	S	24 h LC50	0.3	2.37	Mulla et al., 1980
Aedes nigromaculis	4 instar	S	24 h LC50	0.2	2.19	Mulla et al., 1980
Aedes taeniorhynchus	4 instar	S	24 h LC50	0.05	1.56	Mulla et al., 1980
Psorophora columbiae	4 instar	S	24 h LC50	0.1	2.45	Mulla et al., 1980
Culex pipiens pipiens	4 instar	S	24 h LC50	0.19	2.48	Rettich, 1979
Culex pipiens molestus	4 instar	S	24 h LC50	0.09	2.05	Rettich, 1979
Culiseta annulata	4 instar	S	24 h LC50	0.23	1.84	Rettich, 1979
Aedes cantans	4 instar	S	24 h LC50	0.03	2.70	Rettich, 1979
Aedes sticticus	4 instar	S	24 h LC50	0.02	2.57	Rettich, 1979
Aedes vexans	4 instar	S	24 h LC50	0.09	2.95	Rettich, 1979
Midge Tanytarsus spp.	4 instar	S	24 h LC50	0.016	2.07	Ali et al., 1978
Procladius spp.	4 instar	S	24 h LC50	0.029	2.79	Ali et al., 1978
Chironomus decorus	4 instar	S	24 h LC50	0.23	2.54	Ali et al., 1978
Chironomus utahensis	4 instar	S	24 h LC50	0.29	2.16	Ali and Mulla, 1978
Crictopus spp.	4 instar	S	24 h LC50	0.15	2.16	Ali and Mulla, 1980
Midge, Dicrotendipea californicus	4 instar	S	24 h LC50	0.14	3.16	Ali and Mulla, 1980
Blackfly, Simulium virgatum	Late instar	CF	24 h LC50	0.9	1.80	Mohsen and Mulla, 1981
Mayfly, Baetis parvus	Nymph, late instar	S	LC50 (24 h after 1 h exposure)	0.4	—	Mohsen and Mulla, 1981
Caddisfly, Hydropshche California	Larva, late instar	S	LC50 (24 h after 1 h exposure)	0.4	—	Mohsen and Mulla, 1981
Lobster, Homarus americanus	450 g	SR	96 h LC50	0.0014	—	Zitko et al., 1979
Waterflea Daphnia magna	—	S	24 h LC50	8	—	Hoechst Canada, unpublished
	—	S	48 h LC50	5	—	Hoechst Canada, unpublished
Cypermethrin
Mayfly, Cloeon dipterum	Nymph	S	24 h LC50	0.6 (0.3-1)	—	Stephenson, 1982
Beetle, Gyrinua natator	Adults	S	24 h LC50	5	—	Stephenson, 1982
Water boatman, Corixa punctata	Adults	S	24 h LC50	5	—	Stephenson, 1982
Waterflea, Daphnia magna	24 h	S	24 h LC50	2 (1.5-3.1)	—	Stephenson, 1982
Amphipod, Gammarus pulex	3-8 mm	S	24 h LC50	0.1 (0.08-0.2)	—	Stephenson, 1982
lsopod, Asselus spp.	3-8 mm	S	24 h LC50	0.2 (0.1 -0.4)	—	Stephenson, 1982
Mite, Piona carnea	adults	S	24 h LC50	0.05 (0.03-0.08)	—	Stephenson, 1982
Shrimp, Crangon septomapinosa	1.3 g	SR	96 h LC50	0.01	—	McLeese et al., 1980
Lobster, Homarus americanus	450 g	SR	96 h LC50	0.04	—	McLeese et al., 1980

TABLE 22.9  Estimated l ethal Concentrations (µg/L) for Percentages of Aquatic Species Populations Exposed to Carbaryl in Laboratory Toxicity Tests

Species	LC1	LC10	LC20	LC30	LC40	LC50	LC60	LC70	LC80	LC90	LC99
Mosquito
Aedes cantons	88.8	170	224	273	323	377	440	521	635	834	1600
Aedes vexans	103.1	172	214	250	285	322	364	415	485	602	1010
Aedes excrucians	11.0	35.2	57.3	81.6	110	145	191	258	367	597	1900
Aedes communis	18.3	49.7	75.5	102	132	168	213	276	374	568	1540
Aedes punctor	52.9	115	160	203	248	298	359	438	556	770	1680
Culex p. pipiens	119.9	190	230	265	298	333	372	418	481	584	925
Culex p. molestus	106.3	197	255	308	361	418	484	567	685	887	1640
Culiseta annulata	58.5	97.1	120	140	160	180	203	231	270	334	554
Aedes aegypti	1.50	3.20	4.30	5.30	6.40	7.60	9.00	10.8	13.5	18.2	37.3
Phantom midge, Chaoborus sp.	145.7	286	379	466	554	650	763	908	1110	1480	2900
Midge, Chironomus plumosus	4.10	8.30	11.3	14.0	16.9	20.0	23.7	28.5	35.5	47.9	98.2
Stonefly Pteronarcys californica	13.4	19.2	22.3	24.9	27.3	30.3	32.4	35.5	39.6	46.0	65.9
Pteronarcella baddia	2.10	3.10	3.60	4.10	4.60	5.00	5.50	6.10	6.90	8.20	12.1
Mayfly, Cloeon dipterum	323.8	472	553	620	683	740	817	900	1010	1180	1720
Dragonfly, Orthethrum albistylum speciosur	376.3	549	642	721	794	860	950	1050	1170	1370	2000
Amphipod Gammarus lacustris	22.5	29.1	32.4	35.0	37.4	40.0	42.2	45.0	48.7	54.2	70.0
Gammarus fasciatus	30.7	52.5	65.7	77.4	88.8	104	115	132	155	194	331
Gammarus pseudolimnae	32.8	43.5	48.9	53.3	57.3	64.0	65.5	70.4	76.7	86.3	114
Gammarus pulex	27.1	30.5	32.0	33.2	34.3	35.0	36.3	37.4	38.8	40.7	45.9
Waterflea Daphnia magna	1.559	3.81	5.55	7.28	9.17	11.2	14.0	17.7	23.2	33.7	82.5
Daphnia pulex	5.16	7.96	9.54	10.9	12.2	12.8	15.0	16.7	19.1	22.9	35.3
Simocephalus serrulatus	8.858	11.295	12.5	13.5	14.3	15.2	16.1	17.1	18.4	20.4	26.0

TABLE 22.10  Estimated Concentrations (µg/L) Lethal to Percentage of Population of Aquatic Species Exposed to Deltamethrin in Laboratory Toxicity Tests

Species	LC1	LC10	LC20	LC30	LC40	LC50	LC60	LC70	LC80	LC90	LC99
Mosquito
Culex p. quinquefasciatus	0.006	0.010	0.013	0.015	0.018	0.02	0.023	0.026	0.031	0.039	0.067
Culex tarsalis	0.038	0.047	0.051	0.054	0.057	0.06	0.063	0.066	0.070	0.077	0.094
Culiseta incidens	0.040	0.099	0.145	0.192	0.242	0.30	0.372	0.470	0.619	0.905	2.24
Aedes nigromaculis	0.032	0.073	0.104	0.133	0.164	0.20	0.243	0.301	0.386	0.546	1.24
Aedes taeniorhynchus	0.018	0.028	0.034	0.040	0.045	0.05	0.056	0.063	0.073	0.088	0.141
Psorophora columbiae	0.012	0.032	0.047	0.063	0.080	0.10	0.125	0.159	0.212	0.315	0.807
Culex p. pipiens	0.023	0.059	0.089	0.118	0.151	0.19	0.238	0.305	0.407	0.608	1.58
Culex p. molestus	0.017	0.036	0.049	0.062	0.075	0.09	0.108	0.131	0.164	0.226	0.479
Culiseta annulatus	0.056	0.105	0.138	0.168	0.197	0.23	0.268	0.316	0.384	0.502	0.952
Aedes cantans	0.003	0.008	0.013	0.018	0.023	0.03	0.038	0.050	0.069	0.107	0.304
Aedes sticticus	0.002	0.006	0.009	0.012	0.016	0.02	0.025	0.033	0.044	0.067	0.0180
Aedes vixans	0.007	0.023	0.036	0.051	0.069	0.09	0.118	0.158	0.223	0.359	1.12
Midge Tanytarsus spp.	0.003	0.006	0.009	0.011	0.013	0.016	0.019	0.023	0.029	0.041	0.087
Procladius spp.	0.003	0.008	0.012	0.017	0.022	0.029	0.037	0.049	0.069	0.108	0.317
Chironomus decorus	0.026	0.070	0.105	0.142	0.182	0.23	0.290	0.373	0.503	0.758	2.02
Chironomus utahansis	0.048	0.108	0.152	0.194	0.239	0.29	0.352	0.433	0.554	0.777	1.75
Crictopus spp.	0.025	0.056	0.079	0.101	0.124	0.15	0.182	0.224	0.286	0.402	0.902
Dicrotendipes californicus	0.010	0.032	0.053	0.077	0.105	0.14	0.187	0.255	0.368	0.611	2.04
Blackfly, Simulium virgatum	0.229	0.424	0.549	0.663	0.777	0.90	1.04	1.22	1.48	1.91	3.54
Mayfly, Cloeon dipterum	0.112	0.231	0.313	0.391	0.471	0.60	0.666	0.802	1.00	1.36	2.81
Beetle, Gyrinus natator	0.764	1.80	2.54	3.28	4.08	5.00	6.10	7.58	9.80	14.0	32.5
Water boatman, Corixa punctata	0.764	1.80	2.54	3.28	4.08	5.00	6.10	7.54	9.80	14.0	32.5
Waterflea, Daphnia magna	0.253	0.667	1.00	1.35	1.73	2.00	2.74	3.52	4.73	7.11	18.8
Amphipod, Gammarus pulex	0.032	0.058	0.074	0.089	0.104	0.10	0.138	0.161	0.193	0.248	0.450
Isopod, Asellus spp.	0.032	0.073	0.103	0.133	0.164	0.20	0.244	0.302	0.389	0.551	1.26
Mite, Piona camea	0.013	0.024	0.031	0.037	0.043	0.05	0.057	0.066	0.079	0.101	0.182
Shrimp, Crangon septomspinosa	0.008	0.017	0.023	0.029	0.035	0.04	0.051	0.062	0.078	0.107	0.228

22.7 RISK CHARACTERIZATION

Risk characterization is the final step in the risk assessment process and is the integration of the exposure and effects analysis to describe the nature and likelihood of adverse effects associated with estimated exposures. To characterize risks to the invertebrate community, the first step is to visually compare the overlap between the estimated exposure concentration distribution for each pesticide and the lethal concentration (effects) distribution.

22.7.1 Overlap of Exposure and Effects Distributions

To graphically demonstrate the results of this analysis, the overlaps of exposure and effects distributions for populations of two test species are shown in  Figures 22.7  and  22.8 , respectively. The carbaryl exposure distribution is overlapped with the effects distribution for a mosquito (Culiseta annulata) and the deltamethrin exposure distribution is overlapped with the effects distribution for a waterflea species (Daphnia magna).

To evaluate the likelihood of mortality within the invertebrate community, the distributions of LC50 concentrations for all invertebrate test species populations for carbaryl and deltamethrin were overlain on the distributions of slough water concentrations ( Figures 22.9  and  22.10 , respectively). These data indicate the greater probability of exceeding 50 percent mortality for the variety of species exposed to deltamethrin compared to those exposed to carbaryl.

Figure 22.7  Overlap of estimated carbaryl concentration distribution with lethal concentration distribution for  Culiseta annulata.

Figure 22.8  Overlap of estimated deltamethrin concentration distribution with lethal concentration distribution for Daphnia magna.

Figure 22.9  Overlap of estimated carbaryl concentration distribution with LC50 distribution for exposed aquatic invertebrate community.

Figure 22.10  Overlap of estimated deltamethrin concentration distribution with LC50 distribution for exposed aquatic invertebrate community.

22.7.2 Probability of Exceeding Lethal Concentrations

To quantitatively compare the extent of overlap between exposure and effects distributions requires an application of reliability theory to estimate the “probability of failure.” In this case, the probability of failure is defined as the probability that the exposure concentration exceeds the lethal effects concentration. Reliability theory seeks to calculate the probability of occurrence for a particular event or series of events. In its simplest form for engineering applications, two independent variables are used to describe a probable scenario and are defined as resistance R and load Q [Ang and Tang, 1975; Colorado State University (CSU), 1987]. The units of both of these variables are the same and each variable is described by a probability density function. A failure of this system occurs when the load variable exceeds the value of the resistance variable (i.e., R — Q < 0). The probability that the load is within the interval defined by x + dx is calculated as the probability of Q at x multiplied by the differential, dx. This is generally expressed for all values of x as fQ(x) dx. The probability that failure occurs while Q is within this interval is the probability that Q is within the interval multiplied by the probability that R is less than x, which is the cumulative probability for R at x and is expressed as FR(x). The probability of failure for all values of Q is then defined as the integral product of these two variables (Ang and Tang, 1975):

In most cases, a closed-form solution to this equation is impractical and approximate methods or numerical techniques are relied upon. For problems where both input distributions are normal, an exact solution exists such that a reliability index β is calculated from the mean and variance of both distributions:

where μ is the mean value and α is the standard deviation.

Beta is evaluated from the standard normal distribution and represents the probability that the load Q exceeds the resistance R for the entire range of values for Q and R. A similar closed-form solution exists when each input variable can be represented by the lognormal distribution (CSU, 1987). In this case, the reliability index is expressed as

where V is the coefficient of variation.

For this assessment, the random variables considered are all determined, through curve fitting, to be approximately lognormally distributed. The first variable is the concentration of pesticides in prairie potholes following aerial application. This variable is analogous to the load Q described above and is described in units of micrograms per liter. The LC curves for individual invertebrate species are analyzed to derive a resistance curve R, which is also expressed in units of micrograms per liter. The intersection of these two distributions is an expression of reliability and is the estimation of the fraction of each individual prey species that would be expected to die due to pesticide exposure.

The probability that exposure concentrations will exceed lethal concentrations for test species is shown for carbaryl and deltamethrin in  Figures 22.11  and  22.12 , respectively.  Figure 22.11  indicates that greater than 90 percent mortality is expected from the range of exposure concentrations for 9 of the 23 species tested. The more sensitive taxa include one mosquito species, Aedes aegypti; the midge, Chironomus; two stonefly species; two amphipod species; and the three waterflea species. In contrast, most mosquito species, the phantom midge, mayfly, and dragonfly species populations are expected to show less than 30 percent mortality from the range of estimated carbaryl exposures.  Figure 22.12 indicates that greater than 80 percent mortality is expected in populations of 19 of 27 species. Only the whirligig beetle, water boatman, and waterflea are expected to have less than 20 percent mortality when exposed to deltamethrin at estimated concentrations.

Figure 22.11  Estimated percent mortality for populations of species for range of estimated distribution of carbaryl exposure concentrations.

Figure 22.12  Estimated percent mortality for populations of species for range of estimated distribution of deltamethrin exposure concentrations.

Figure 22.13  Probability that estimated carbaryl concentrations will exceed lethal concentration percentiles for exposed invertebrate community.

This analysis can be extended to estimate the probability of invertebrate community mortality associated with the estimated distribution of exposure concentrations. For clarity, this analysis relies on the assumption that the water column density of all prey species is approximately equal. The analysis can readily be modified to account for actual differences in prey density, mass density, or nutritional value of different prey species. By applying the reliability theory analysis to an aggregation of lethal concentration distributions for the test community, the probability of exceeding a lethal concentration percentile can be estimated. This comparison is shown for estimated carbaryl exposures in  Figure 22.13  and for estimated deltamethrin exposures in  Figure 22.14 . For carbaryl, there is approximately a 50 percent probability of 20 percent mortality in the exposed community and approximately a 20 percent probability that the mortality would reach the 80 percent level. For deltamethrin, there is approximately a 50 percent probability that mortality would reach the 90 percent level in the exposed invertebrate community.

22.7.3 Comparison to Field Studies

One of the major uncertainties in a risk assessment based on laboratory toxicity tests is the correspondence between the level of mortality measured in the laboratory and that observed under field conditions. The response of the invertebrate community in ponds aerially treated with carbaryl has been studied. Hunter et al. (1984) applied carbaryl at 840 g/ha to four woodland ponds (the risk assessment evaluated carbaryl applied at a rate of 1100 g/ha). Amphipod populations were reduced by approximately 99 percent following the carbaryl application and mayfly, and caddisfly populations were reduced by approximately 75 and 66 percent, respectively. However, the numbers of chironomid midges were significantly reduced in only one of the four treated ponds. In the treated ponds, the total numbers of invertebrates were reduced by 30 to 60 percent of the control pond levels, and biomass was reduced by 60 to 75 percent of the pretreatment standing crop. These data agree reasonably well with the risk assessment estimates of approximately a 50 percent probability of 30 percent mortality and approximately a 35 percent probability of 60 percent mortality in the exposed community. The risk assessment also qualitatively predicts the relative high sensitivity of amphipods to carbaryl exposures, but not the relative tolerance of chironomids. Unfortunately, there are no equivalent quantitative field studies of deltamethrin effects on aquatic invertebrates. Tooby et al. (1981) reported that deltamethrin applied to ponds at 50 g/ha severely depleted or eliminated several insect and crustacean families, and Rawn et al. (1983) reported that a single application of 10 g/ha reduced insect emergence. In a field study of cypermethrin, Crossland (1982) reported that the insecticide caused widespread planktonic and benthic invertebrate mortality: 21 of 23 taxa present in pretreatment samples were absent two weeks after application. The risk assessment estimates approximately a 50 precent probability of 90 percent mortality in the invertebrate community following deltamethrin overspray of sloughs.

Figure 22.14  Probability that estimated deltamethrin concentrations will exceed lethal concentration percentiles for exposed aquatic invertebrate community.

Clearly, any risk assessment of a complex exposure situation such as evaluated in this analysis will have a relatively high level of uncertainty associated with mortality estimates. However, the probabilistic analysis applied in this assessment provides some quantification of uncertainties in risk estimates, as well as a technique to estimate the probability that exposure concentrations will exceed selected levels of mortality in the exposed invertebrate community. A logical extension to this work is the prediction of the effects of the depletion of the macroinvertebrate community, due to pesticide application, on the recruitment and survival of ducklings living in or near prairie potholes. Prey mass density and duckling energetic requirements could be characterized in a similar fashion to chemical concentrations, and estimates of duckling survival could be calculated. This approach promises to provide methods to estimate both the probability and severity of impacts resulting from exposures, information which has been missing from many of the ecological risk assessments conducted for aquatic systems.

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