Use of Simple Stream Modeling Methods To Assess the Potential

Chapter 11

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Use of Simple Stream Modeling Methods To Assess the Potential Risks of Malathion to Salmonids Richard Reiss* Exponent, Inc., 1800 Diagonal Rd., Suite 500, Alexandria, VA 22314 *E-mail: [email protected]

This paper considers the potential effects of malathion to salmonid populations in the Pacific Northwest. It refines a previous assessment by accounting for stream dilution with the AgDRIFT model for pesticide spray drift. A generalized Haber’s Law model was used to model toxicity for different concentration-time profiles. Risk was considered for salmonids directly and to a sensitive prey species, Daphnia magna, assuming a 100 foot buffer distance between the field edge and the water body. Assuming that the limited ecotoxicology data available to characterize the Haber’s Law exponent are representative, the analysis showed that direct effects to salmonids are highly unlikely. There is a small possibility of effects to Daphnia magna for streams with shallow depths and relatively still water. However, most other invertebrates are much less sensitive to malathion and salmonids have a diverse diet. Therefore, infrequent effects to a small number of prey species are very unlikely to affect salmonid populations.

Introduction In recent years, there has been significant interest regarding the potential effect of pesticides on Pacific salmonids. Under the Endangered Species Act (ESA), the National Marine Fisheries Service (NMFS) has produced a series of biological opinions (BOs) that have assessed the potential risks to salmonids from organophosphorous and carbamate pesticides. This paper is focused on the assessment for malathion, which was included in the first BO along with © 2012 American Chemical Society In Pesticide Regulation and the Endangered Species Act; Racke, K., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.


chlorpyrifos and diazinon (1). The BO included an assessment of potential risks to salmonids in 28 evolutionary significant units (ESUs). The concentrations of malathion in salmonid habitat are generally much too low to directly affect salmonids even with extreme methods of estimating concentrations. However, among several lines of evidence in the BO, one of the key conclusions was that salmonid prey, particularly invertebrates, were more sensitive and could be impacted by malathion, and the loss of prey was determined to have a significant effect on salmonid populations. One of the key sources of information developed in the BO was an estimate of potential concentrations of malathion in salmonid habitat. The estimates were derived using both aquatic water modeling and from a review of historical environmental measurements. While the environmental measurements were predominantly very low, NMFS placed more emphasis on the modeling estimates, which allowed a consideration of worst-case scenarios potentially not captured in the measurement programs. One of the key sources of modeling estimates was derived with the AgDRIFT model (2). AgDRIFT is a commonly used tool that allows the estimation of concentrations in a downwind water body following a pesticide application. The model accounts for a variety of factors, including the application rate, the application method, the droplet size, and the size of the water body. Bogen and Reiss (3) found that the methods used in the BO were flawed because salmonids generally reside in flowing water bodies. However, the AgDRIFT modeling estimates did not consider stream dilution. Instead, the AgDRIFT estimates were based on the instantaneous concentration of pesticide at the moment that a plume hit the water body (assuming instantaneous mixing). This estimate was compared with ecotoxicology data where the organisms were exposed for 48 to 96 hours, which represents a mismatch of exposure and toxicity. If stream dilution was taken into account, Bogen and Reiss (3) estimated that the resulting concentrations for pesticides were about 50- to 300-fold less. This paper applies the stream modeling methodology of Bogen and Reiss (3) to malathion and includes a risk assessment using malathion ecotoxicity data.

Material and Methods While it was not used in the BO, the AgDRIFT model includes a Stream Assessment Tool that allows the user to estimate stream dilution after a pesticide plume first enters a water body. This module within AgDRIFT uses an advection-diffusion equation to estimate the dispersion of pesticide as it travels downstream. The use of this tool enables a calculation of the longer-term average concentrations to which salmonids and prey would be exposed, allowing a more accurate comparison with the ecotoxicity data. The AgDRIFT model provides estimates of concentrations at different distances downstream of the plume impact point. The downstream distance that yielded the highest concentration was used in the analysis. Counterbalancing this conservative assumption, only a single application is considered. It is possible that multiple applications in the same general area could affect stream concentrations. 160 In Pesticide Regulation and the Endangered Species Act; Racke, K., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.


Before applying the average concentrations derived by the AgDRIFT Stream Assessment Tool, there is a significant toxicological issue to address. It is conceivable that a short-term pulse exposure might have a different magnitude of effect than a much smaller but constant and longer lasting exposure that has an identical average concentration over time. The effect that the time pattern of exposure has on toxicity is modeled using a generalized version of Haber’s Law (4):

where L is the toxic loading, C is concentration, T is time, and n is the toxic load exponent. When ecotoxicological data are available with the same outcome and different time durations, the toxic load exponent can be estimated. Equation I can then be used to estimate toxicity for different concentration-time regimes. Bogen and Reiss (3) applied the AgDRIFT model to a range of salmonid habitat characteristics accounting for depth and stream velocity. An exponential decline in concentration over time was observed, allowing the model results to be easily characterized mathematically. Applying the exponential concentration decline formulation and the generalized Haber’s Law, Bogen and Reiss found that the dilution ratio, ρ, (initial concentration/equivalent constant concentration) can be estimated as:

where k is the first-order rate constant for the concentration decline, and Tcon is the duration. The equivalent constant concentration represents the time-averaged concentration (over Tcon) that is equivalent in toxicity to the initial pulse concentration, accounting for the Haber’s Law exponent. Thus, the equivalent concentration can be compared with an ecotoxicity effect value for a study with duration of Tcon.

Results Estimation of Haber’s Law Exponent for Malathion Bogen and Reiss (3) searched the literature for ecotoxicology studies that included measurements over multiple time durations and fitted the data using Equation I to derive Haber’s Law exponents for malathion and other pesticides. Several studies with adequate data were identified. Ren et al. measured the LC50 of malathion to Daphnia magna over 24 and 48 hours with exposures up to 10 ppb (5). Daphnia magna was the most sensitive invertebrate species for malathion in the studies conducted by the registrant and was the key basis for the NMFS BiOp conclusions. The registrant Daphnia magna guideline study (6) also included two time points (24 and 48 hours), but did not have a sufficiently robust dose-response (i.e., a range of responses at different doses) to estimate the Haber’s Law exponent with Equation I. However, the 161 In Pesticide Regulation and the Endangered Species Act; Racke, K., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.


registrant study does show a dramatic difference in response at 24 and 48 hours. At the highest exposure of 1.3 ppb, 10% of the organisms were immobilized at 24 hours, while 80% were immobilized at 48 hours. Applying a non-generalized Haber’s Law (i.e., with n = 1), a 40% immobilization would have been predicted at 24 hours based on the 48-hour measurement. The actual immobilization was 4 times lower. The results from Ren et al. (5) and the registrant study were consistent. The 48-hour EC50 in the registrant study was 0.72 ppb, whereas the LC50 in Ren et al. (5) was 0.9 ppb. Gries and Purghart was another registrant-sponsored study for rainbow trout (Oncorhynchus mykiss), a salmonid species (7). In this study, the rainbow trout were exposed to five doses up to 1.6 ppm and observed at six time points up to 96 hours. The 96 hour LC50 was 0.18 ppm (180 ppb). Thus, rainbow trout were about 200 times less sensitive to malathion than Daphnia magna. Legierse et al. measured the LC50 of malathion for guppies (Poecilia reticulate) for 14 different time points up to 336 hours (14 days). While not a common salmonid prey item, this study provides the most extensive dose-response vs. time data that were identified (8). There would be less uncertainty in the analysis if studies were available with as many time points as included in Legierse et al. for more common salmonid prey. The LC50 for malathion ranged from 3.8 ppm at 24 hours to 0.83 ppm at 336 hours. Table I shows the fitted Haber’s Law exponents for each of the three studies. The estimated values were 0.48 (Daphnia magna), 1.8 (rainbow trout), and 0.91 (guppies). A Haber’s Law exponent of 1 indicates that the toxicity at two time points can be estimated as the inverse ratio of the time values. For example, if the LC50 is 10 ppb at 48 hours, the LC50 would be 20 ppb at 24 hours with n = 1. For Haber’s Law exponents less than 1, the ratio of toxicity at different time points is greater than the ratio of durations. At Haber’s Law exponents greater than 1, the inverse ratio of toxicity at different time points is less than the ratio of the durations.

Table I. Estimated Haber’s Law exponents (n) for three studies for malathion Study

Species

n

Ren et al. (5)

Water flea (Daphnia magna)

0.48

Gries and Purghart (7)

Rainbow trout (Oncorhynchus mykiss)

1.8

Legierse et al. (8)

Guppy (Poecilia reticulate)

0.91

To illustrate the effect of a Haber’s Law exponent of less than 1, Figure 1 shows the equivalent constant concentration to cause the same effect for different durations of exposure for n = 0.48 (estimated value for Daphnia magna). A toxic loading factor of 2 was assumed so that the concentration at 2 days is set a 1 ppb. For a 0.1 hour (6 minute) duration, an exposure of 513 ppb will cause the 162 In Pesticide Regulation and the Endangered Species Act; Racke, K., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.


same effect as an exposure of 1 ppb for 2 days. Similarly, the equivalent effect concentrations are 76 ppb at 15 minutes, 18 ppb at 30 minutes, and 4.2 ppb at 1 hour. This dramatically shows how important it is to account for the duration of exposure.

Figure 1. Equivalent effect concentrations for Haber’s Law exponent of n = 0.48.

Estimation of Time-Averaged Exposures in Salmonid Habitat A survey of salmonid habitat in Oregon found that salmonids may sometimes reside in non-flowing types of habitat, such as backwater pools, damned pools, and beaver ponds, accounting for about 20% of the total juvenile salmonid capacity (9). The remainder reside in flowing water bodies, which is the focus of this analysis. It should be noted that even water bodies such as backwater pools will have some dilution over time from either direct exchange of water with the main water body or from hyporheic flow, which is a mixing of shallow groundwater and surface water. Bogen and Reiss (3) considered a range of habitat stream scenarios with different depths and velocities. The depths ranged from 0.1 to 0.5 meters and the velocities ranged from 0.0213 m/sec to 0.5 m/sec. It is important to consider that both very shallow habitat (0.1 meters or about 4 inches) and very slow stream velocity (0.0213 m/sec or about 4 feet per minute) assumptions were included in the analysis. To estimate concentrations in the streams, the AgDRIFT model was used. The application rates allowed for malathion range from less than 1 lb active ingredient (ai)/acre to 2.5 lb ai/acre, with most application rates being between 1 and 2 lb a.i./acre. Aerial applications lead to significantly more drift than other types of applications. To consider a range of possible scenarios, aerial application rates of 1 lb ai/acre and 2.5 lb ai/acre were considered. Table II summarizes other relevant parameters in the AgDRIFT modeling. Of note, the distance between the edge of the field and water body was assumed to be 100 feet. This value was chosen for demonstration purposes, but the methods in the paper can be applied for other distances. At this distance, it is assumed 163 In Pesticide Regulation and the Endangered Species Act; Racke, K., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.

that runoff is not a significant loading factor to the stream. It is also means that the calculations essentially are testing the reliability of a 100 feet buffer zone for controlling impacts of spray drift. Tier 1 AgDRIFT default values were used for all parameters except the application rate, buffer distance, and stream depth and velocity. Of note, among the many conservative assumptions, the wind is assumed to be moving directly from the field to the pond. Any deviation from this assumption would result in lower concentrations and even no impact on the stream for many wind directions.


Table II. Parameters for AgDRIFT modeling Parameter

Values

Application rate

1.5 or 5 lb ai/acre

Distance between edge of field and water body

100 feet

Stream depth

0.1 to 0.5 meters

Stream velocity

0.0213 to 0.5 m/sec

Stream width

30 m

Flight lines

20

Swath width

60 feet

Riparian interception factor

0.2

Droplet size

Fine-to-medium distribution (volume median diameter or 255 μm)

Wind speed

10 miles per hour

Wind direction

Directly from field to stream

Temperature

86°F

Humidity

50%

Atmospheric stability

Neutral

Tables III and IV summarize the estimated equivalent concentrations over 48 hours (Daphnia magna) and 96 hours (rainbow trout) using Equation II and applying the AgDRIFT Stream Assessment estimates compiled from Bogen and Reiss (3). The equivalent concentration is a time-weighted average concentration that accounts for the Haber’s Law exponent. Table III provides the results for an application rate of 1.0 lb ai/acre and Table IV provides the results of application rate of 2.5 lb ai/acre. The concentrations for Daphnia magna and rainbow trout are different because the averaging duration is different (48 hours for Daphnia magna 164 In Pesticide Regulation and the Endangered Species Act; Racke, K., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.


and 96 hours for rainbow trout) to allow comparison with standard ecotoxicity test, and because the Haber’s Law exponent is factored in, which is why the term “equivalent concentration” is used. The estimated equivalent concentrations for Daphnia magna range from 0.0002 to 0.38 ppb for a 1.0 lb ai/acre application rate and from 0.001 to 0.94 ppb for a 2.5 lb ai/acre application rate. For rainbow trout, the estimated equivalent concentrations range from 0.2 to 6.3 ppb at 1.0 lb ai/acre and from 0.5 to 15.7 ppb at 2.5 lb ai/acre.

Table III. Equivalent concentrations using Equation II for an application rate of 1.0 lb/acre (100 foot buffer distance) Equivalent Concentration Depth (m)

Velocity (m/sec)

k (hr-1)

Co (ppb)

0.1

0.0213

0.57

0.1

0.1

0.1

Daphnia magna (a)

Rainbow Trout

80.4

0.38

6.3

1.9

55.8

0.021

2.2

0.2

3.2

46.2

0.006

1.4

0.1

0.3

4.5

41.2

0.003

1.0

0.1

0.5

6.5

36.8

0.001

0.74

0.25

0.0213

0.79

37.4

0.089

2.4

0.25

0.1

3.0

27

0.004

0.84

0.25

0.3

7.0

20.2

0.001

0.39

0.5

0.0213

1.1

20.4

0.024

1.1

0.5

0.1

4.6

15.02

0.001

0.37

0.5

0.3

8.0

11.24

0.0002

0.20

(b)

(a)

Equivalent concentration over 48 hours accounting for Haber’s Law exponent of n = 0.48. (b) Equivalent concentration over 96 hours accounting for Haber’s Law exponent of n = 1.8.

Estimation of Risk Quotients for Daphnia magna and Rainbow Trout From the equivalent concentration estimates in Tables III and IV, the risk quotient (RQ) can be estimated using the LC50 of 0.9 ppb for Daphnia magna and the LC50 of 180 ppb for rainbow trout, as summarized in Table V. The RQ is defined as the exposure divided by the toxicity level. Thus, lower numbers mean that the exposure is relatively less than the level that may cause an effect.

165 In Pesticide Regulation and the Endangered Species Act; Racke, K., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.

Table IV. Equivalent concentrations using Equation II for an application rate of 2.5 lb/acre (100 foot buffer distance)


Equivalent Concentration Depth (m)

Velocity (m/sec)

k (hr-1)

Co (ppb)

0.1

0.0213

0.57

0.1

0.1

0.1

Daphnia magna (a)

Rainbow Trout

201

0.94

15.7

1.9

139.5

0.05

5.6

0.2

3.2

115.5

0.01

3.5

0.1

0.3

4.5

103

0.01

2.6

0.1

0.5

6.5

92

0.00

1.9

0.25

0.0213

0.79

93.5

0.22

6.1

0.25

0.1

3.0

67.5

0.01

2.1

0.25

0.3

7.0

50.5

0.001

1.0

0.5

0.0213

1.1

51

0.06

2.8

0.5

0.1

4.6

37.55

0.002

0.9

0.5

0.3

8.0

28.1

0.001

0.5

(b)

(a)

Equivalent concentration over 48 hours accounting for Haber’s Law exponent of n = 0.48. (b) Equivalent concentration over 96 hours accounting for Haber’s Law exponent of n = 1.8.

At 1.0 lb ai/acre, the RQs are all below unity, indicating that the exposure is less than the LC50. The highest RQ was 0.42 for scenario 1 (a shallow depth and low stream velocity scenario) for Daphnia magna. The highest RQ for rainbow trout was 0.035, which shows that the exposures do not approach the LC50 level at 1.0 lb ai/acre for the assumptions used in this analysis. At 2.5 lb ai/acre, the highest RQ for Daphnia magna was 1.0. For rainbow trout, the highest RQ was 0.087. Thus, direct effects to rainbow trout are unlikely. Even for Daphnia magna, the RQs for 9 of 11 scenarios are less than 0.07, indicating a very large margin of safety. Nonetheless, effects to Daphnia magna cannot be ruled out for extreme circumstances of shallow depth, low stream velocity, and winds from the field to the water body.

Discussion The analysis in this paper shows that is very unlikely that malathion concentrations in salmonid habitat could ever reach levels that would directly impact salmonids. However, it is possible that malathion concentrations could occasionally reach a level that could impact the most sensitive salmonid prey item, Daphnia magna, but only under extreme circumstances of very shallow water depth and virtually still water. 166 In Pesticide Regulation and the Endangered Species Act; Racke, K., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.

Table V. Estimated risk quotients for Daphnia magna and rainbow trout


Application Rate = 1.0 lb ai/acre

Application Rate = 2.5 lb ai/acre

Daphnia magna

Rainbow Trout

Daphnia magna

Rainbow Trout

0.42

0.035

1.0

0.087

0.024

0.012

0.059

0.031

0.0066

0.0077

0.016

0.019

0.0029

0.0057

0.0072

0.014

0.0012

0.0041

0.0030

0.010

0.098

0.014

0.25

0.034

0.0044

0.0047

0.0110

0.012

0.0006

0.0022

0.0014

0.0054

0.027

0.0061

0.067

0.015

0.0010

0.0020

0.0025

0.0051

0.0002

0.0011

0.0006

0.0028

Malathion has a wide range of sensitivity to invertebrate species. Considering the ecotoxicity data summarized by the U.S. Fish and Wildlife Service (10) and the EPA (11), the range of LC50 values for invertebrates is 0.5 to 10000 ppb. In this assessment, a Daphnia magna LC50 of 0.9 ppb was considered, which is at the low end of the range of invertebrate toxicity. This leaves the question of whether some infrequent effects to a small part of the invertebrate population will incur any significant effects to salmonids. Higgs et al. provided an extensive review of salmonid diets by lifestage (12). In particular, the publication reviews numerous studies that analyzed the stomach contents of salmonids. One of the overarching conclusions was that salmonids are opportunistic feeders with significant diversity in prey, which includes a wide variety of insect species, crustaceans, other fish, algae, eggs of fish and insects, etc. Thus, even if some sensitive invertebrates were to be affected by malathion, the salmon would have alternative species as prey. Therefore, some infrequent effects to daphnids or other similarly sensitive species are not likely to harm salmonid populations. This assessment has a number of uncertainties that should be considered. First, there is relatively limited data on the characteristics of salmonid habitat. To account for this uncertainty, very shallow depths with extremely slow stream velocities were considered. However, even less data are available on other types of habitats like backwater pools. The Haber’s Law exponents in the paper were derived from relatively limited data. Most ecotoxicity studies do not contain data with robust dose-responses at multiple durations of exposure. Future ecotoxicity studies would benefit from observations at more time points and higher exposure concentrations that cause effects for very short durations. Such data would help to more accurately apply the generalized Haber’s Law concept. 167 In Pesticide Regulation and the Endangered Species Act; Racke, K., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2012.

Future analyses could build on these methods using more complex stream dynamics, modeling the simultaneous contribution of runoff and spray drift, and evaluating the impact of multiple applications affecting a stream.


Conclusions A risk assessment was conducted for potential malathion effects to Pacific salmonids. A time-varying exposure profile was constructed using the AgDRIFT model. A generalized Haber’s Law model was used to estimate toxicity. Direct effects to salmonids are highly unlikely due to the relatively low toxicity of malathion to salmonids. There is the possibility of infrequent effects to sensitive invertebrate species in very shallow water habitats with low water velocities. However, most invertebrate species are much less sensitive to malathion than Daphnia magna and the available literature shows that salmonids have a diverse diet. Therefore, infrequent effects to sensitive invertebrates are not likely to impact salmonid populations.

References National Marine Fisheries Service. Endangered Species Act Section 7 Consultation: Biological opinion: Environmental Protection Agency registration of pesticides containing chlorpyrifos, diazinon, and malathion; 2008. 2. Teske, J. H.; Bird, S. L.; Esterly, D. M.; Curbishley, T. B.; Ray, S. L.; Perry, S. G. Environ. Toxicol. Chem. 2002, 21, 659–671. 3. Bogen, K. T; Reiss, R. Risk Anal. 2012, 32, 250–258. 4. ten Berge, W. F.; Zwart, A.; Appleman, L. M. J. Hazard. Mater. 1986, 13, 301–309. 5. Ren, Z.; Zha, J.; Ma, M.; Wang, Z.; Gerhardt, A. Environ. Monit. Assess. 2007, 134, 373–383. 6. Greis, T.; Purghart, V. Malathion technical: acute immobilisation test with daphnids (Daphnia magna) under flow-through conditions. Study performed by Springborn Laboratories for Cheminova A/S. Study number 1005.018.115. 2001. 7. Greis, T.; Purghart, V. Malathion technical: acute toxicity test with rainbow trout (Oncorhynchus mykiss) under flow-through conditions. Study performed by Springborn Laboratories for Cheminova A/S. Study number 1005.018.108. 2001. 8. Legierse, K. C. H. M.; Verhaar, H. J. M.; Vaes, W. H. J.; De Bruiijn, J. H. M.; Hermens, J. L. M. Environ. Sci. Technol. 1999, 33, 917–925. 9. Nickelson, T. E. Habitat-based assessment of coho salmon production potential and spawner escapement needs for Oregon coastal streams. Oregon Department of Wildlife Information Reports Number 98-4; 1998. 10. Johnson, W. W.; Finley, M. T. Handbook of acute toxicity of chemicals to fish and aquatic invertebrates; Fish and Wildlife Service: Washington, DC, 1980; Resource Publication 137. 1.



11. EPA. Malathion reregistration eligibility document, environmental fate and effects chapter; U.S. Environmental Protection Agency: Washington, DC, 2005. 12. Higgs, D. A.; MacDonald, J. S.; Levings, C. D.; Dosanjh, B. S. Nutrition and feeding habits in relation to life history stage. In Physiological Ecology of Pacific Salmon; Groot, C., Clarke, W. C., Eds.; University of British Columbia Press: Vancouver, 1995.


Use of Simple Stream Modeling Methods To Assess the Potential

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