Potential Risks of Alachlor Use to Federally
Threatened California Red-legged Frog
(Rana aurora draytonii) and Delta Smelt (Hypomesus
transpacificus)
Pesticide Effects Determinations
Environmental Fate and Effects Division
Office of Pesticide Programs
Washington, D.C. 20460
June 15,2009
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Primary Authors: Melissa Panger, Ph.D., Biologist
Reuben Baris, Physical Scientist
Secondary Review: Thomas Steeger, Ph.D., Senior Biologist
R. David Jones, Ph.D., Senior Agronomist
Branch Chief, Environmental Risk Branch 4: Elizabeth Behl
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Table of Contents
1.0 EXECUTIVE SUMMARY
1.1. PURPOSE OF ASSESSMENT 8
1.2. ASSESSED CHEMICALS 8
1.3. ASSESSMENT PROCEDURES 8
1.3.1. Toxicity Assessment 8
1.3.2. Exposure Assessment 9
1.3.3. Measures of Risk 9
1.4. ALACHLOR USES ASSESSED 10
1.5. SUMMARY OF CONCLUSIONS 10
2.0 PROBLEM FORMULATION 13
2.1. PURPOSE 13
2.2. SCOPE 15
2.27. Evaluation of Degradates 15
2.2.2. Evaluation of Mixtures 19
2.3 PREVIOUS ASSESSMENTS 20
2.4 STRESSOR SOURCE AND DISTRIBUTION 21
2.4.1 Environmental Fate Properties 21
2.4.2 Mechanism of Action 25
2.4.3 Use Characterization 25
2.5 ASSESSED SPECIES 33
2.6. DESIGNATED CRITICAL HABITAT 37
2.7 ACTION AREA 39
2.8 ASSESSMENT ENDPOINTS AND MEASURES OF ECOLOGICAL EFFECT 41
2.8.1. Assessment Endpoints 41
2.8.2 Assessment Endpoints for Designated Critical Habitat 44
2.9 CONCEPTUAL MODEL 44
2.9.7 Risk Hypotheses 44
2.9.2 Diagram 45
2.10. ANALYSIS PLAN 47
3.0. EXPOSURE ASSESSMENT 51
3.1 AQUATIC EXPOSURE ASSESSMENT 51
17.7. Model Inputs 54
3.1.2. Results 58
3.1.3. Existing Monitoring Data 59
3.1.4 Impact of Typical Usage Information on Exposure Estimates 63
3.2. TERRESTRIAL ANIMAL EXPOSURE ASSESSMENT 63
3.2.7. Potential Exposure to Terrestrial Invertebrates 64
3.3 TERRESTRIAL PLANT EXPOSURE ASSESSMENT 65
4.0. EFFECTS ASSESSMENT 66
4.1. ECOTOXICITY STUDY DATA SOURCES 67
4.2. TOXICITY CATEGORIES 68
4.3. TOXICITY OF CHEMICAL MIXTURES 68
4.4 TOXICITY OF ALACHLOR TO AQUATIC ORGANISMS 69
4.4.1 Toxicity to Fish 72
4.4.2. Toxicity to Amphibians 73
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4.4.3 Toxicity to Aquatic Invertebrates 73
4.4.4 Toxicity to Aquatic Plants 74
4.5 TOXICITY OF ALACHLOR TO TERRESTRIAL ORGANISMS 75
4.5.1 Toxicity to Birds and Terrestrial Phase Amphibians 77
4.5.2 Toxicity to Mammals 77
4.5.3 Toxicity to Terrestrial Invertebrates 78
4.5.4 Toxicity to Terrestrial Plants 78
4.6. USE OF PROBIT SLOPE RESPONSE RELATIONSHIP TO PROVIDE INFORMATION ON THE
ENDANGERED SPECIES LEVELS OF CONCERN 79
4.7 INCIDENT DATABASE REVIEW 80
5.0 RISK CHARACTERIZATION 80
5.1 RISK ESTIMATION 80
5.7.7 Direct Effects RQs 81
5.1.2 Indirect Effects 83
5.1.3 Primary Constituent Elements of Designated Critical Habitat. 93
5.2 RISK DESCRIPTION 94
5.27. Direct Effects 95
5.2.2. Indirect Effects, DS and Aquatic-Phase CRLF 99
5.2.3. Indirect Effects, Terrestrial-Phase CRLFs 707
5.2.4 Spatial Extent of Potential Effects 705
5.3. MODIFICATION OF DESIGNATED CRITICAL HABITAT Ill
5.17. CRLF 777
5.12. DS 772
5.4. EFFECTS DETERMINATIONS 113
5.4.1 CRLF 773
5.4.2 DS 773
6.0 UNCERTAINTIES 114
6.1 EXPOSURE ASSESSMENT UNCERTAINTIES 114
6.1.1 Maximum Use Scenario 114
6.1.2. Impact of Vegetative Setbacks on Runoff. 114
6.1.3 Aquatic Exposure Modeling ofAlachlor 775
6.1.4 Ground Water Uncertainties 777
6.1.5 Usage Uncertainties 775
6.1.6 Terrestrial Exposure Modeling ofAlachlor 775
6.2 EFFECTS ASSESSMENT UNCERTAINTIES 119
6.2.1 Age Class and Sensitivity of Effects Thresholds 779
6.2.2 Impact of Multiple Stressors on the Effects Determination 779
6.2.3. Use of Surrogate Species Effects Data 720
6.2.4 Location of Wildlife Species 727
7.0 RISK CONCLUSIONS 122
8.0 REFERENCES 124
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Appendices and Attachments
Appendix A Mixture Data for Alachlor
Appendix B Alachlor Usage Data for California
Appendix C Ecological Effects Data
Appendix D Accepted ECOTOX Data Table (Sorted By Effect)
Appendix E Bibliography of ECOTOX Open Literature for Alachlor
Appendix F RQ Method and LOCs
Appendix G Estimation of the Fraction of the Watershed Area which Receives Application on
Impervious Surfaces in Residential Watersheds
Appendix H PRZM/EXAMS Model Output Files
Appendix I TerrPlant Example Input and Output
Appendix J HED Effects Table
Appendix K Reported Alachlor Wildlife and Plant Incidents
Appendix L T-REX Example Input and Output
Appendix M T-HERPS Example Input and Output
Appendix N GIS Maps and Spatial Analyses
Attachment 1 Life History Information for the CRLF
Attachment 2 Baseline Status and Cumulative Effects for the CRLF
Attachment 3 Life History Information for the DS
Attachment 4 Baseline Status and Cumulative Effects for the DS
List of Tables
Table 1.1. Effects Determination Summary for Effects of Alachlor on the CRLF and the DS 11
Table 1.2. Effects Determination Summary for Alachlor Use and CRLF and DS Critical Habitat Impact
Analysis 11
Table 2.1. Major and Minor Degradates of Alachlor* 16
Table 2.2. Summary of Formation Pathway of Alachlor Degradates of Concern (assumed equal toxicity
to parent)3 17
Table 2.3. Comparison of Aquatic Organism Toxicity Data for Alachlor and its Degradates 18
Table 2.4. Comparison of Mammalian Acute and Chronic Toxicity Data for Alachlor and its Degradates.
19
Table 2.5. General Chemical/Physical Properties of Alachlor 25
Table 2.6. Summary of Alachlor Products Registered in the U.S 27
Table 2.7. Summary of Alachlor Application Methods and Rates for California 29
TABLE 2.8 Summary of California Department of Pesticide Registration (CDPR) Pesticide Use
Reporting (PUR) Data from 1999 to 2006 for the Currently Registered Alachlor Uses 33
Table 2.9. Summary of Current Distribution, Habitat Requirements, and Life History Information for the
Assessed Listed Species1 34
Table 2.10. Designated Critical Habitat PCEs for the CRLF and DS 38
Table 2.11. TaxaUsed in the Analyses of Direct and Indirect Effects for the Assessed Listed Species....42
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Table 2.12. Assessment Endpoints Used to Evaluate the Potential for the Use of Alachlor to Result in
Direct and Indirect Effects to the CRLF and the DS 43
Table 3.1. Summary of PRZM Scenarios 54
Table 3.2. Summary of Environmental Fate Data for Alachlor 56
Table 3.3. Summary of Management Practices for PRZM/EXAM Modeling Input Parameters 57
Table 3.4. Summary of PRZM/EXAMS Chemcial Input Parameters for Alachlor 58
Table 3.5. Aquatic Total Toxic Residue EECs (ug/L) for Alachlor Uses in California 59
Table 3.6. Summary of Alachlor Detections in Surface Water by Study as Included in the 1998 Alachlor
RED and 2006 Chloroacetanilide Cumulative Risk Assessment 62
Table 3.7. Upper-bound Kenega Nomogram EECs for Dietary- and Dose-based Exposures of the CRLF
and its Prey to Alachlor 64
Table 3.8. EECs (ppm) for Indirect Effects to the Terrestrial-Phase CRLF via Effects to Terrestrial
Invertebrate Prey Items 65
Table 3.9. Screening-Level Exposure Estimates for Terrestrial Plants to Alachlor 66
Table 4.1. Categories of Acute Toxicity for Terrestrial and Aquatic Animals 68
Table 4.2. Aquatic Toxicity Profile for Alachlor 70
Table 4.3. Terrestrial Toxicity Profile for Alachlor 76
Table 5.1. Summary of Aquatic RQs Used to Estimate Direct Effects to Aquatic-Phase CRLF and the
DS1 82
Table 5.2. Summary of RQs Used to Estimate Direct Effects to Terrestrial-Phase CRLFs (Upper Bound
Kenaga Values, Dose-Based for 20g Bird that Eats Small Insects)1 83
Table 5.3. Summary of Acute and Chronic RQs for Aquatic Invertebrates Used to Evaluate Potential
Indirect Effects to the CRLF and the DS Resulting from Potential Impacts to Food Supply 85
Table 5.4. Summary of Acute RQs for Terrestrial Invertebrates on the Site of Application Used to
Evaluate Potential Indirect Effects to the CRLF Resulting from Potential Impacts to the Food Supply. ..86
Table 5.5. Summary of Acute RQs for 15g Mammals (LD50 = 930 mg/kg-bw) Used to Evaluate Potential
Indirect Effects to the CRLF Resulting from Potential Impacts to the Food Supply 88
Table 5.6. Summary of Chronic RQs for 15g Mammals (NOAEC = 30 mg/kg-diet) Used to Evaluate
Potential Indirect Effects to the CRLF Resulting from Potential Impacts to the Food Supply 90
Table 5.7. Summary of Acute RQs for Aquatic Plants Used to Evaluate Potential Indirect Effects to the
CRLF and DS 92
Table 5.8. Non-Listed Species Terrestrial Plant RQs for Alachlor Use in California1 93
Table 5.9. Probability of Individual Effects to Terrestrial-Phase CRLF Based on Acute Data from Birds.
97
Table 5.10. Upper Bound Kenaga, Acute Terrestrial Herpetofauna Dose-Based Risk Quotients for
Alachlor (4 Ib a.i./acre, 1 Application) 98
Table 5.11. Upper Bound Kenaga, Sub-Acute and Chronic Terrestrial Herpetofauna Dietary-Based Risk
Quotients for Alachlor (1 Application) 99
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Table 5.12. Distance from Alachlor Use Site Needed to Reduce Exposure from Spray Drift to Levels that
Do Not Exceed LOCs for Direct Effects 106
Table 5.13. Distance from Alachlor Use Site Needed to Reduce Exposure from Spray Drift to Levels that
Do Not Exceed LOCs for Indirect Effects 107
Table 7.1. Effects Determination Summary for Effects of Alachlor on the CRLF and the DS 122
Table 7.2. Effects Determination Summary for Alachlor Use and CRLF and DS Critical Habitat Impact
Analysis 123
List of Figures
Figure 2.1. Estimated Annual Alachlor Usage in the U.S 30
Figure 2.2. Average Pounds of Alachlor Applied/Year/CA County from 1999-2006 32
Figure 2.3. Delta Smelt Habitat Areas 35
Figure 2.4. Recovery Unit, Core Area, Critical Habitat, and Occurrence Designations for CRLF 36
Figure 2.5. Potential Alachlor Use Sites in California Representing the Initial Area of Concern 40
Figure 2.6. Conceptual Model for Risks to Terrestrial-Phase CRLF from Alachlor Use 46
Figure 2.7. Conceptual Model for Risks to Aquatic-Phase CRLF and the DS from Use of Alachlor 47
Figure 3.1 Application Dates for Alachlor (CDPR PUR Data; 2004 - 2005) 55
Figure 5.1. Overlap Map: CRLF Habitat and Alachlor Initial Area of Concern 109
Figure 5.2. Overlap Map: DS Habitat and Alachlor Initial Area of Concern 110
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1.0 Executive Summary
1.1. Purpose of Assessment
The purpose of this assessment is to evaluate potential direct and indirect effects on the
California red-legged frog (Rana aurora draytonif) (CRLF) and the Delta smelt (Hypomesus
transpacificus) (DS) arising from FIFRA regulatory actions regarding use of alachlor (PC Code
090501) on agricultural and non-agricultural sites. In addition, this assessment evaluates
whether these actions can be expected to result in effects to designated critical habitat for the
CRLF and the DS.
The CRLF was listed as a threatened species by USFWS in 1996. The species is endemic to
California and Baja California (Mexico) and inhabits both coastal and interior mountain ranges.
The DS was listed as threatened on March 5, 1993 (58 FR 12854) by the U.S. Fish and Wildlife
Service (USFWS) (USFWS, 2007a). It is only found in Suisun Bay and the Sacramento-San
Joaquin estuary near San Francisco Bay.
1.2. Assessed Chemicals
Alachlor, an acetanilide herbicide, is a seedling cell growth inhibitor (Ross and Medlin, 2001)
that disrupts the growth of new plant seedlings in areas where it is applied. The physiological
details of the mode of action of acetanilide herbicides are not known.
Potential risks to alachlor degradates were quantified for aquatic organisms using the total toxic
residues approach for aquatic exposure modeling, as there were no available data on the fate and
transport of the three potential equally toxic degradates considered in this assessment (2-chloro-
2',6'-diethylacetanilide, 2',6'-diethyl-N-methoxymethylacetanilide, and 2'6'-diethyl-2-hydroxy-
N-methoxymethylacetanilide, see section 2.2.1). Potential risks to alachlor degradates were not
quantified for terrestrial organisms since only one application was modeled and peak estimated
environmental concentrations were used to calculate risk quotients.
1.3. Assessment Procedures
This assessment was completed in accordance with the U.S. Fish and Wildlife Service (USFWS)
and National Marine Fisheries Service (NMFS) Endangered Species Consultation Handbook
(USFWS/NMFS, 1998) and is consistent with procedures and methodology outlined in the
Agency's Overview Document (USEPA, 2004).
1.3.1. Toxicity Assessment
The assessment endpoints include direct toxic effects on survival, reproduction, and growth of
individuals, as well as indirect effects, such as reduction of the food source and/or modification
of habitat. Federally-designated critical habitat has been established for the CRLF and the DS.
Primary constituent elements (PCEs) were used to evaluate whether alachlor has the potential to
affect designated critical habitat. The Agency evaluated registrant-submitted studies and data
from the open literature to characterize alachlor toxicity. The most sensitive toxicity value
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available from acceptable or supplemental studies for each taxon relevant for estimating potential
risks to the CRLF and DS and/or their designated critical habitat was used.
1.3.2. Exposure Assessment
1.3.2.1. Aquatic Exposures
Tier-II aquatic exposure models were used to estimate high-end exposures of alachlor in aquatic
habitats resulting from runoff and spray drift from different uses. Peak model-estimated
environmental concentrations resulting from different alachlor uses range from 3.2 jig a.i./L
(sweet corn, incorporated use) to 56.0 jig a.i./L (woody ornamentals, nursey use). The maximum
reported monitoring value from surface water data evaluated in this assessment was 91.5 |ig/L.
Frequency of detections ranged from 0% to 4.5%. Information from both modeled estimates and
monitoring results are considered in this assessment. The study with the 91.5 |ig/L value was
conducted before the maximum application rates for alachlor were reduced from 6 Ib a.i./acre to
4 Ib a.i./acre in the 1990's. An application rate of 6 Ibs a.i./acre was modeled for comparison
purposes using the CAnursery scenario. Modeling output showed peak concentrations that are
within a reasonable margin of error to the peak monitoring data (84 |ig/L compared to 91.5
|ig/L). Therefore, due to the reduced application rate the concentration cannot be used to reflect
potential concentrations from current use practices and is not quantitatively used in this risk
assessment.
1.3.2.2. Terrestrial Exposures
The T-REX model was used to estimate potential alachlor exposures to terrestrial species
including birds (surrogate species for terrestrial phase CRLFs), mammals (CRLF prey), and
invertebrates (CRLF prey). The AgDRIFT model was used to estimate deposition of alachlor on
terrestrial and aquatic habitats from spray drift and to determine the distance from alachlor use
sites the CRLF and the DS may be at risk of direct or indirect effects. The TerrPlant model was
used to estimate alachlor exposures to terrestrial-phase CRLF habitat, including plants inhabiting
semi-aquatic and dry areas, resulting from uses involving flowable and impregnated bulk
fertilizer alachlor applications. The T-HERPS model was used to allow for further
characterization of the dietary exposures of terrestrial-phase CRLFs relative to birds, which were
used as a surrogate species for the CRLF.
1.3.3. Measures of Risk
Acute and chronic risk quotients (RQs) are compared to the Agency's Levels of Concern (LOCs)
to identify instances where alachlor use has the potential to adversely affect the CRLF or DS or
adversely modify their designated critical habitat. When RQs for a particular type of effect are
below LOCs, the pesticide is considered to have "no effect" on the species and its designated
critical habitat. Where RQs exceed LOCs, a potential to cause adverse effects or habitat
modification is identified, leading to a conclusion of "may affect". If alachlor use "may affect"
the assessed species, and/or may cause effects to designated critical habitat, the best available
additional information is considered to refine the potential for exposure and effects, and
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distinguish actions that are NLAA (not likely to adversely affect) from those that are LAA
(likely to adversely affect).
1.4. Alachlor Uses Assessed
All potential uses of alachlor were evaluated as part of this assessment. In the U.S., alachlor
is currently registered for use on succulent and dry beans, field and sweet corn, cotton,
woody ornamentals, peanuts, sorghum (milo), soybeans, and sunflowers. For the woody
ornamentals, there is nothing on the alachlor labels that restricts the use to commercial uses,
therefore, both commercial and residential uses will be considered here. Only the end-use
products approved for use in California [i.e., Lasso® Herbicide, INTRRO (EPA Reg. No.:
524-314) and Micro-Tech® Herbicide (EPA Reg. No.: 524-344)] are assessed here. These
products only contain one active ingredient - alachlor. All of the alachlor end-use products
are labeled as Restricted Use Pesticides (RUPs).
Based on California Department of Pesticide Regulation Pesticide Use Reporting (CDPR PUR)
data, almost all of the use of alachlor between 1999 and 2006 in CA was on corn (55%) and
beans (45%). The remaining alachlor uses listed in the CDPR PUR data made up <1% of
alachlor use (i.e., 'preplant', 'landscape', and 'research', as listed in the CDPR PUR data). In
California, applications are limited to flowable applications via ground equipment (broadcast
boom or banded) or via center pivot irrigation systems. Additionally, applications via
impregnated bulk fertilizer are allowed for some uses (corn, sorghum, and soybeans).
Application timing includes burndown prior to crop, preplant incorporated, pre-emergence
surface, post-emergence surface (corn only), ground-crack surface (peanuts only), and post-
transplant (woody ornamentals only).
1.5. Summary of Conclusions
Based on the best available information, the Agency makes a May Affect, and Likely to
Adversely Affect (LAA) determination for the CRLF and the DS from the labeled uses of
alachlor as described in Table 1.1. The effects determination is based on potential direct and
indirect effects to terrestrial-phase CRLF and potential indirect effects to aquatic-phase CRLF
and the DS. The LAA determination applies to all currently registered alachlor uses in
California.
Additionally, the Agency has determined that there is the potential for effects to designated
critical habitat of the CRLF and the DS from the use of the alachlor. A summary of the risk
conclusions and effects determinations for each listed species assessed and their designated
critical habitat is presented in Tables 1.1 and 1.2. Further information on the results of the
effects determination is included as part of the Risk Description in Section 5.2. Given the LAA
determination for the CRLF and the DS and potential effects to designated critical habitat for
both species, a description of the baseline status and cumulative effects for the CRLF is provided
in Attachment 2 and the baseline status and cumulative effects for the DS is provided in
Attachment 4.
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Table 1.1.
DS.
Effects Determination Summary for Effects of Alachlor on the CRLF and the
Species
California red-
legged frog
(Rana aurora
draytonii)
Delta Smelt
(Hypomesus
transpacificus)
Effects
Determination 1
LAA1
LAA1
Basis for Determination
Potential for Direct Effects
Aquatic-phase (Eggs, Larvae, and Adults):
None of the RQs for freshwater fish (used as a surrogate for aquatic -phase
amphibians) exceed the Agency's LOCs for any registered alachlor use.
Terrestrial-phase (Juveniles and Adults):
The risk of direct adverse effects to terrestrial-phase CRLF from acute or sub-
acute dietary exposure is low. However, the risk (or potential risk) to terrestrial-
phase CRLF from chronic dietary exposure cannot be precluded and exists for all
dietary classes relevant to the CRLF (for all of the registered alachlor uses).
Potential for Indirect Effects
Aquatic prey items, aquatic habitat, cover and/or primary productivity
Alachlor could potentially impact terrestrial and aquatic plants to an extent that
could result in indirect effects to the CRLF.
Terrestrial prey items, riparian habitat
CRLFs could be affected as a result of potential impacts to grassy /herbaceous
vegetation. Potential effects to amphibian food item abundance that may
indirectly affect terrestrial phase CRLFs could not be precluded.
Potential for Direct Effects
None of the RQs for freshwater fish exceed the Agency's LOCs for any
registered alachlor use.
Potential for Indirect Effects
Labeled uses of alachlor have the potential to adversely affect the DS by
reducing available food (aquatic plants), by impacting the riparian habitat of
grassy and herbaceous riparian areas, and/or by impacting water quality via
effects to aquatic vegetation.
May affect, likely to adversely affect (LAA)
Table 1.2. Effects Determination Summary for Alachlor Use and CRLF and DS Critical
Habitat Impact Analysis.
Assessment
Endpoint
Effects
Determination
Basis for Determination
Modification of
aquatic-phase PCEs
(DS and CRLF)
Habitat Effects
As described in Table 1.1., the effects determination for the potential for
alachlor to affect aquatic-phase CRLFs and the DS is LAA. These
determinations are based on the potential for alachlor to indirectly affect the
DS and aquatic-phase CRLF. Additionally, the potential areas of effect
overlap with critical habitat designated for the CRLF and DS. Therefore,
potential effects to aquatic plants and terrestrial (riparian) plants identified in
this assessment could result in aquatic habitat modification.
Modification of
terrestrial-phase PCE
(CRLF)
As described in Table 1.1., the effects determination for the potential for
alachlor to affect terrestrial-phase CRLFs is LAA. This determination is based
on the potential for alachlor to directly affect terrestrial-phase CRLFs and their
food supply and habitat. Additionally, the potential areas of effect overlap
with critical habitat designated for the CRLF. Therefore, these potential
effects could result in modification of critical habitat.
Based on the conclusions of this assessment, a formal consultation with the U. S. Fish and
Wildlife Service under Section 7 of the Endangered Species Act should be initiated.
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When evaluating the significance of this risk assessment's direct/indirect and adverse habitat
modification effects determinations, it is important to note that pesticide exposures and predicted
risks to the listed species and its resources (i.e., food and habitat) are not expected to be uniform
across the action area. In fact, given the assumptions of drift and downstream transport (i.e..,
attenuation with distance), pesticide exposure and associated risks to the species and its resources
are expected to decrease with increasing distance away from the treated field or site of
application. Evaluation of the implication of this non-uniform distribution of risk to the species
would require information and assessment techniques that are not currently available.
When evaluating the significance of this risk assessment's direct/indirect and adverse habitat
modification effects determinations, it is important to note that pesticide exposures and predicted
risks to the species and its resources (i.e., food and habitat) are not expected to be uniform across
the action area. In fact, given the assumptions of drift and downstream transport (i.e., attenuation
with distance), pesticide exposure and associated risks to the species and its resources are
expected to decrease with increasing distance away from the treated field or site of application.
Evaluation of the implication of this non-uniform distribution of risk to the species would require
information and assessment techniques that are not currently available. Examples of such
information and methodology required for this type of analysis would include the following:
• Enhanced information on the density and distribution of CRLF and the DS life
stages within the action area and/or applicable designated critical habitat. This
information would allow for quantitative extrapolation of the present risk
assessment's predictions of individual effects to the proportion of the population
extant within geographical areas where those effects are predicted. Furthermore,
such population information would allow for a more comprehensive evaluation of
the significance of potential resource impairment to individuals of the assessed
species.
• Quantitative information on prey base requirements for the assessed species.
While existing information provides a preliminary picture of the types of food
sources utilized by the assessed species, it does not establish minimal
requirements to sustain healthy individuals at varying life stages. Such
information could be used to establish biologically relevant thresholds of effects
on the prey base, and ultimately establish geographical limits to those effects.
This information could be used together with the density data discussed above to
characterize the likelihood of adverse effects to individuals.
• Information on population responses of prey base organisms to the pesticide.
Currently, methodologies are limited to predicting exposures and likely levels of
direct mortality, growth or reproductive impairment immediately following
exposure to the pesticide. The degree to which repeated exposure events and the
inherent demographic characteristics of the prey population play into the extent to
which prey resources may recover is not predictable. An enhanced understanding
of long-term prey responses to pesticide exposure would allow for a more refined
determination of the magnitude and duration of resource impairment, and together
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with the information described above, a more complete prediction of effects to
individual species and potential modification to critical habitat.
2.0 Problem Formulation
Problem formulation provides a strategic framework for the risk assessment. By identifying the
important components of the problem, it focuses the assessment on the most relevant life history
stages, habitat components, chemical properties, exposure routes, and endpoints. The structure
of this risk assessment is based on guidance contained in USEPA's Guidance for Ecological Risk
Assessment (USEPA 1998), the Services' Endangered Species Consultation Handbook
(USFWS/NMFS 1998) and is consistent with procedures and methodology outlined in the
Overview Document (USEPA 2004) and reviewed by the U.S. Fish and Wildlife Service and
National Marine Fisheries Service (USFWS/NMFS 2004).
2.1. Purpose
The purpose of this endangered species assessment is to evaluate potential direct and indirect
effects on individuals of the federally threatened California red-legged frog (Rana aurora
draytonit) (CRLF) and/or the Delta smelt (Hypomesus transpacificus) (DS) arising from FIFRA
regulatory actions regarding labeled uses of alachlor. In addition, this assessment evaluates
whether labeled alachlor use is expected to result in effects to designated critical habitat for the
CRLF and/or the DS. This ecological risk assessment has been prepared consistent with the
settlement agreement in Center for Biological Diversity (CBD) vs. EPA et al. (Case No. 02-1580-
JSW(JL)) which addresses the CRLF and was entered in Federal District Court for the Northern
District of California on October 20, 2006. This assessment also addresses the DS for which alachlor
was alleged to be of concern in a separate suit (Center for Biological Diversity (CBD) vs. EPA etal.
(Case No. 07-2794-JCS)).
In this assessment, direct and indirect effects to the CRLF and DS and potential modification to
their designated critical habitat are evaluated in accordance with the methods described in the
Agency's Overview Document (USEPA 2004). The effects determinations for each listed
species assessed is based on a weight-of-evidence method that relies heavily on an evaluation of
risks to each taxonomic group relevant to assess both direct and indirect effects to the listed
species and the potential for modification of their designated critical habitat (i.e., a taxon-level
approach). Screening level methods include use of standard models such as PRZM, EXAMS, T-
REX, TerrPlant, and AgDRIFT, all of which are mentioned in the Overview Document. In
addition, T-HERPS has been used to refine estimates of exposure and risk to amphibians. Use of
such information is consistent with the methodology described in the Overview Document
(USEPA 2004), which specifies that "the assessment process may, on a case-by-case basis,
incorporate additional methods, models, and lines of evidence that EPA finds technically
appropriate for risk management objectives" (Section V, page 31 of USEPA 2004).
In accordance with the Overview Document, provisions of the ESA, and the Services'
Endangered Species Consultation Handbook, the assessment of effects associated with
registrations of alachlor is based on an action area. The action area is the area directly or
indirectly affected by the federal action. It is acknowledged that the action area for a national-
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level FIFRA regulatory decision associated with a use of alachlor may potentially involve
numerous areas throughout the United States and its Territories. However, for the purposes of
this assessment, attention will be focused on relevant sections of the action area including those
geographic areas associated with locations of the CRLF and DS and their designated critical
habitat within the state of California. As part of the "effects determination," one of the following
three conclusions will be reached separately for each of the assessed species regarding the
potential use of alachlor in accordance with current labels:
• "No effect";
• "May affect, but not likely to adversely affect"; or
• "May affect and likely to adversely affect".
The CRLF and the DS have designated critical habitats associated with them. Designated critical
habitat identifies specific areas that have the physical and biological features, (known as primary
constituent elements or PCEs) essential to the conservation of the listed species. The PCEs for
the CRLF are aquatic and upland areas where suitable breeding and non-breeding aquatic habitat
is located, interspersed with upland foraging and dispersal habitat. PCEs for the DS include
characteristics required to maintain habitat for spawning, larval and juvenile transport, rearing,
and adult migration.
If the results of initial screening-level assessment methods show no direct or indirect effects (no
LOG exceedances) upon individuals or upon the PCEs of the species' designated critical habitat,
a "no effect" determination is made for use of alachlor as it relates to each species and its
designated critical habitat. If, however, potential direct or indirect effects to individuals of a
species are anticipated or effects may impact the PCEs of the designated critical habitat, a
preliminary "may affect" determination is made for the FIFRA regulatory action regarding
alachlor.
If a determination is made that use of alachlor "may affect" a listed species or its designated
critical habitat, additional information is considered to refine the potential for exposure and for
effects to each species and other taxonomic groups upon which these species depend (e.g, prey
items). Additional information, including spatial analysis (to determine the geographic
proximity of the assessed species' habitat and alachlor use sites) and further evaluation of the
potential impact of alachlor on the PCEs is also used to determine whether effects to designated
critical habitat may occur. Based on the refined information, the Agency uses the best available
information to distinguish those actions that "may affect, but are not likely to adversely affect"
from those actions that "may affect and are likely to adversely affect" the assessed listed species
and/or result in "no effect" or potential effects to the PCEs of its designated critical habitat. This
information is presented as part of the Risk Characterization in Section 5 of this document.
The Agency believes that the analysis of direct and indirect effects to listed species provides the
basis for an analysis of potential effects on the designated critical habitat. Because alachlor is
expected to directly impact living organisms within the action area (defined in Section 2.7),
critical habitat analysis for alachlor is limited in a practical sense to those PCEs of critical habitat
that are biological or that can be reasonably linked to biologically mediated processes (i.e., the
biological resource requirements for the listed species associated with the critical habitat or
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important physical aspects of the habitat that may be reasonably influenced through biological
processes). Activities that may affect critical habitat are those that alter the PCEs and
appreciably diminish the value of the habitat. Evaluation of actions related to use of alachlor that
may alter the PCEs of the assessed species' critical habitat form the basis of the critical habitat
impact analysis. Actions that may affect the assessed species' designated critical habitat have
been identified by the Services and are discussed further in Section 2.6.
2.2. Scope
Alachlor is a chloroacetanilide herbicide currently registered in the U.S. to control broadleaf
weeds and grasses in succulent and dry beans, field and sweet corn, cotton, woody ornamentals,
peanuts, sorghum (milo), soybeans, and sunflowers. The end result of the EPA pesticide
registration process is an approved product label. The label is a legal document that stipulates
how and where a given pesticide may be used. Product labels (also known as end-use labels)
describe the formulation type, acceptable methods of application, approved use sites, and any
restrictions on how applications may be conducted. Thus, the use or potential use of alachlor in
accordance with the approved product labels is "the action" being assessed.
This ecological risk assessment is for currently registered uses of alachlor in portions of the
action area reasonably assumed to be biologically relevant to the CRLF or the DS habitat and
their designated critical habitat. Further discussion of the action area and designated critical
habitat is provided in Section 2.4 and 2.5.
2.2.1. Evaluation of Degradates
This ecological risk assessment includes all potential ecological stressors resulting from the use
of alachlor, including alachlor and its potential degradates of concern. Degradates of concern
may include those that are found at significant concentrations (>10% by weight relative to
parent) in available degradation studies or those that are of toxicological concern. Major
degradates of alachlor (>10% formation by weight, or are of toxicological concern) are presented
below in Table 2.1, and are discussed below. A summary of formation pathways of the three
degradates of toxicological concern is presented in Table 2.2.
Regarding all of the known degradates, the Health and Effects Division (FIED) chapter for the
RED concluded that alachlor ethane sulfonic acid (alachlor-ESA) is much less toxic than the
parent (USEPA, 1998a). Available toxicity data for alachlor oxanilic acid indicate that its
toxicity is also much less than the parent (USEPA, 2006). The remaining major water soluble
degradates of alachlor, DM-oxanilic acid, 2',6'-diethyl-2-methylsulfmylacetanilide, 2',6'-
diethyl-N-methoxymethyloxoanilic acid, and alachlor sulfinylacetic acid, are also polar oxanilic
or sulfonic acids and are expected to share the poor in vivo absorption and metabolism
characteristics of compounds alachlor oxanilic acid and alachlor-ESA (USEPA, 2006). The
remaining less polar major degradates, 2-chloro-2',6'-diethylacetanilide, 2',6'-diethyl-N-
methoxymethylacetanilide, and 2',6'-diethyl-2hydroxy-N-methoxymethylacetanilide, are more
structurally similar to the parent than the water soluble degradates. Because toxicity data for
these three compounds are unavailable, FIED assumed that they have the same toxicity as
alachlor parent and are residues of risk concern (USEPA, 2006). Therefore, a total toxic residues
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approach was used for this assessment for aquatic exposure to evaluate the potential exposure to
the residues of risk concern, i.e., alachlor and the three degradates 2-chloro-2',6'-
diethylacetanilide, 2',6'-diethyl-N-methoxymethylacetanilide, and 2',6'-diethyl-2hydroxy-N-
methoxymethylacetanilide (identified as compounds II, IX, and XIII in Table 2.2). For
terrestrial exposures, since only one application is modeled for each use and peak estimated
concentrations are used (and, thus, concentrations would not increase even if degradates were
considered), only the parent is modeled.
Table 2.1. Major and Minor Degradates of Alachlor*
Compound
Chemical Name
Synonym
Major Degradates
II
III
IV
VII
VIII
IX
X
XI
XIII
2-chloro-2',6'-diethylacetanilide
2',6'-diethyloxanilic acid
2 ' ,6 ' -diethy 1-2-sulfoacetanilide
2 ' ,6 ' -diethy 1-N-methoxy methyloxoanilic acid
[N-methoxymethyl-N-(2,6-diethylphenyl)-2-amino-2-
oxoethyljsulfinylacetic acid
2 ' ,6 '-diethyl-N-methoxymethylacetanilide
2',6'-diethyl-N-methoxymethyloxanilic acid
2',6'-diethyl-N-methoxymethyl-2-sulfoacetanilide
2 ' ,6 '-diethyl-2-hy droxy-N-methoxymethylacetanilide
None
DM-oxanilic acid
None
None
Alachlor sulfinylacetic acid
MON 5768
None
Alachlor oxanilic acid
MON 5760
Alachlor sulfonic acid,
Alachlor-ESA
MON 5775
None
Minor Degradates
I
V
VI
XII
XV
XVI
XVII
XX
XXII
XXIII
XXIV
2 ' ,6 ' -diethy lacetanilide
2 ' ,6 ' -diethy 1-2-methoxy acetanilide
2 ' ,6 ' -diethy 1-2 -methylsulfinylacetanilide
2 ' ,6 ' -diethyl-N-methoxymethyl-2-oxoacetanilide
2 ' ,6 ' -diethyl-N-methoxymethyl-2-methylthioacetanilide
2 ' ,6 ' -diethyl-N-methoxymethyl-2-
methylsulfiny lacetanilide
2 ' ,6 ' -diethyl-N-methoxymethyl-2-
methylsulfony lacetanilide
2',6'-diethylbenzyl alcohol
2 ' ,6 ' -diethy 1-N-hydroxymethy 1-2 -methoxyacetanilide
8-ethyl-N-methoxymethyl-4-methyl-2-
oxotetrahydroquinoline
2 ' -acetyl-2-chloro-6 ' -ethyl-N-methoxymethy lacetanilide
None
None
None
None
None
None
None
None
None
None
None
*Bold text indicates degradates of toxicological concern previously identified in USEPA, 2006.
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Table 2.2. Summary of Formation Pathway of Alachlor Degradates of Concern (assumed
equal toxicity to parent)"
Degradate
2-chloro-2',6'-
diethylacetanilide
(Compound II)
2',6'-diethyl-N-
methoxymethylacetanilide
(Compound IX)
2' ,6 ' -diethyl-2-hydroxy-N-
methoxymethylacetanilide
(Compound XIII)
Formation Pathway
Photolysis in
Water
--
X
(1.1%, 48ht1/2)
--
Photolysis in
Soil
--
--
X
(6.5%, 14 dt1^)
Aerobic
Metabolism
in Soil
X
(20%, 18dty2)
X
(2.5%, 14 dt1^)
X
(10.2%, 7 dt'/2)
Anaerobic
Metabolism
in Soil
--
--
--
Anaerobic
Metabolism
in Water
--
X
(35.3%, 21 dt
'/2)
--
a Values in parentheses are percentage of parent formed; half-lives for these compounds for each formation pathway
are presented following the percent formation. See USEPA, 2006 for additional discussion on these degradates.
X = data available
~ = no data available
Some toxicity data are available for aquatic plants and animals on the alachlor degradates
alachlor sulfonic acid, alachlor oxanilic acid, and the minor degradate 2,6-diethyaniline.
Additionally, rat toxicity data are available for the major alachlor degradates alachlor oxanilic
acid, alachlor sulfinylacetic acid, and the minor degradate t-hydroxyalachlor (MON 52707). For
the aquatic organisms, in all of the taxa-degradate combinations for which data are available,
parent alachlor is more toxic (in many cases, orders of magnitude more toxic) than the
degradates (Table 2.3). For mammals, the parent compound appears either more toxic or
equatoxic with the degradates tested (Table 2.4).
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Table 2.3. Comparison of Aquatic Organism Toxicity Data for Alachlor and its
Degradates.
TAXA/SPECIES
Aquatic invertebrate
Daphnid (Daphnia
magna)
Freshwater fish
Rainbow trout
(Oncorhynchus mykiss)
Amphibian
African clawed frog
(Xenopus laevis)
Aquatic plant
(nonvascular)
Green algae
(Selenastrum
capricornutum)
Aquatic plant
(nonvascular)
Cyanobacteria
(Anabaena flos-aquae)
Aquatic plant
(nonvascular)
Freshwater diatom
(Navicula pelliculosa)
Aquatic plant
(nonvascular)
Marine diatom
(Skeletonema costatum)
Aquatic plant (vascular)
Duckweed (Lemna
gibba)
ENDPOINT
48-hr EC50
96-hr LC50
96-hr LC50
5-day EC50
5 -day
NOAEC
5-day EC50
5 -day
NOAEC
5-day EC50
5 -day
NOAEC
5-day EC50
5 -day
NOAEC
14-day EC50
14-day
NOAEC
COMPOUND
Alachlor (parent)
Endpoint (mg
a.i./L)
(MRID/Reference)
7.7
(40098001)
1.8
(C.I.*= 1.5-2.1)
(00023616)
6.1
(E66376) (Osano et
al, 2002)
0.00164
(C.I. = 0.0015-
0.0024)
(427638-01)
0.00035
(427638-01)
EC50 = >19
(446497-01)
19
(highest cone.
tested)
(446497-01)
2.63
(C.I. =2.4-3.0)
(446497-04)
NOAEC = 1.0
(446497-04)
0.21
(C.I. = 0.15-0.26)
(446497-03)
0.098
(446497-03)
0.0023
(C.I. = 0.0021 -
0.0033)
(446497-02)
0.000339
(446497-02)
Alachlor Sulflnic
Acid (MON 5775)
Endpoint (mg
a.i./L) (MRID)
>104
(43774703)
>104
(43774704)
-
>120
(450460-01)
120 (highest cone.
tested)
(450460-01)
>120 (450460-02)
120 (highest cone.
tested) (450460-
02)
3.6
(C.I. = 2.9-4.1)
(450460-03)
2.5
(450460-03)
5.0
(C.I. = 4.6-5.6)
(450460-04)
2.0
(450460-04)
>120
(450460-05)
120 (highest cone.
tested) (450460-
05)
Oxanilic Acid
(MON 5760)
Endpoint (mg
a.i./L) (MRID)
>95
(43774705)
>100
(43774706)
-
2,6-Diethylaniline
Endpoint (mg
a.i./L) (Reference)
-
-
19.4
(E66376) (Osano
etal, 2002)
-
-
-
-
-
~ = No data available
* C.I. = 95% Confidence Interval
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Table 2.4. Comparison of Mammalian Acute and Chronic Toxicity Data for Alachlor and
its Degradates.
TAXA/
SPECIES
Rat
(acute
oral)
Rat
(90-day
dietary)
ENDPOINT
LD50
NOAEL
COMPOUND
Alachlor
(parent)
Endpoint
(mg/kg)
930
15*
Alachlor
Sulfinic
Acid
(MON
5775)
Endpoint
(mg/kg)
>6,000
157
(males)
207
(females)
Oxanilic
Acid
(MON
5760)
Endpoint
(mg/kg)
>5,000
13,000
Sulfinylacetic
Acid (MON
5768)
Endpoint
(mg/kg)
>5,000
4,000
t-
hydroxyalachlor
(MON 52707)
Endpoint
(mg/kg)
>500 (males)
>500, <2,000
(females)
-
* As reported in HEDs assessment (USEPA, 2006), although the study was not acceptable.
2.2.2. Evaluation of Mixtures
The Agency does not routinely include an evaluation of mixtures of active ingredients (either
those mixtures of multiple active ingredients in product formulations, or those in the applicator's
tank, in its risk assessments. In the case of product formulations of active ingredients (registered
products containing more than one active ingredient) each active ingredient is subject to an
individual risk assessment for regulatory decision regarding the active ingredient on a particular
use site. If effects data are available for a formulated product containing more than one active
ingredient, they may be used qualitatively or quantitatively in accordance with the Agency's
Overview Document and the Services' Evaluation Memorandum (USEPA, 2004;
USFWS/NMFS, 2004). Alachlor does have two end-use products that are co-formulated with
atrazine (and atrazine-related compounds), however, neither of these products is registered for
use in California. Therefore, none of the alachlor products assessed here contains more than one
active ingredient.
Based on the results of the available data, alachlor mixtures have shown additive effects (e.g.,
when alachlor is mixed with atrazine alone or glyphosate alone), synergistic effects (e.g., when
mixed with fluridone alone or with multiple herbicides), and antagonistic effects (e.g., when
mixed with imazapyr alone) (see Appendix A for details). If chemicals that show more than
additive effects with alachlor are present in the environment in combination with alachlor, the
toxicity of alachlor could be increased. Conversely, when alachlor is found in combination with
chemicals that show antagonistic effects, the toxicity of alachlor could be decreased. The
potential increase or decrease in toxicity could be offset by other factors including but not
necessarily limited to: (1) the exposed species, (2) the chemicals in the mixture, (3) the ratio(s) of
the chemical concentrations, (4) differences in the pattern and duration of exposure to the
chemicals, and (5) the differential effects of other physical/chemical characteristics of the
receiving waters (e.g., organic matter present in sediment and suspended water). Quantitatively
predicting the combined effects of all these variables on mixture toxicity to any given taxa with
confidence is beyond current capabilities. However, a qualitative discussion of implications of
the available pesticide mixture effects data involving alachlor on the confidence of risk
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assessment conclusions is addressed as part of the uncertainty analysis for this effects
determination.
2.3 Previous Assessments
Alachlor was first registered in the U.S. in 1969. A Reregistration Eligibility Decision (RED) for
alachlor was signed in 1998 (USEPA 1998b). In the RED, the following mitigation measures
were required: a reduction in application rates and the classification of alachlor as a Restricted
Use Pesticide. These mitigation measures have been implemented on current labels. The RED
identified potential risk to terrestrial birds from chronic exposure and risk to non-target terrestrial
and aquatic plants from exposure to alachlor. Aquatic animals were identified as being at
potential risk from chronic exposure to alachlor, but were identified as having low risk from
acute exposures.
The following data gaps were identified in the EFED science chapter for the RED (USEPA,
1998b): terrestrial field dissipation studies conducted outside of California, additional aquatic
plant toxicity studies, an avian reproduction study, and aquatic plant studies for the alachlor
degradate alachlor ethane sulfonic acid (alachlor-ESA). Additionally, the science chapter
highlighted concerns about the impact that alachlor and its degradates may have on ground water
quality and surface water sources for drinking water.
Subsequent to the RED, EFED conducted an ecological risk assessment for the new use of
alachlor on sunflowers and cotton (USEPA, 2006a). The screening-level assessment concluded
that the use of alachlor on sunflowers and cotton could result in risk to Federally-listed
threatened and endangered (listed) and non-listed terrestrial and aquatic plant species.
Additionally, there was potential risk to small, non-listed birds that forage on short grass,
broadleaf plants and small insects, and potential acute risk to listed avian species for several size
class/forage item combinations. While a no-observed adverse effect concentration (NOAEC)
was not determined for birds, using the lowest observed adverse effect concentration (LOAEC)
tested indicated potential chronic risk to birds in all forage items. Potential acute risk to listed
mammals and potential chronic risk to listed and non-listed mammals was also indicated for
most size class/forage item combinations.
A human health risk assessment on potential cumulative effects of alachlor with other
chloroacetanilide herbicides was also conducted subsequent to the RED. The cumulative
assessment (including the cumulative effects of alachlor and acetochlor) was completed in 2006
(USEPA, 2006b). Similar cumulative assessments have not been conducted for ecological
effects.
EPA conducted an assessment of potential effects of alachlor to 26 listed Pacific salmon and
steelhead and on May 30, 2002, determined the uses of alachlor would have no effect on those
species.
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2.4 Stressor Source and Distribution
2.4.1 Environmental Fate Properties
As characterized in the RED (USEPA, 1998b), alachlor is stable to hydrolysis at pH 3, 6, and 9
and stable to photolysis. Alachlor is metabolized at moderate rates (t/2= 26 - 34 d) in aerobic
soils, with several degradates observed, including DM-oxanilic acid, alachlor-ESA, alachlor
oxanilic acid, and alachlor sulfinylacetic acid. Data submitted to the Agency on 4/4/2008 to
fulfill the identified data gap for alachlor aquatic metabolism are currently under review.
Supplemental batch equilibrium and acceptable column leaching data for alachlor indicate that it
is mobile and is not appreciably adsorbed to soils with low organic matter. A batch equilibrium
study of alachlor-ESA shows that the degradate does not sorb appreciably and is highly mobile.
Terrestrial field dissipation studies are consistent with laboratory studies and demonstrate that
alachlor was mobile and dissipated at moderate rates; dissipation half-lives of 6 and 11 days are
within an order of magnitude of aerobic soil metabolism study half-lives ranging from 26 to 34
days. It appears that the persistence and mobility of the chemical may increase as it reaches
deeper soil horizons that have lower organic matter content and decreased biological activity,
thus, increasing its potential to leach into groundwater.
Degradation and Metabolism
Alachlor is a soluble chemical (240 ppm in water at 24°C), with a moderate vapor pressure of
2.2xlO"5 torr (24°C; MRID 152209) suggesting the compound could volatilize. Octanol/water
partition coefficient (Kow) values were difficult to produce with accuracy and precision; early
values included 33.0 and 37.1 (MRID 152209). More recent studies indicate that alachlor's Kow
value lies in the range of 1100 to 2800, which is higher than the value of 434 reported in the
1998 RED (MRID 257282, 40396301).
Alachlor is stable to hydrolysis in buffered solutions at pH's 3, 6, and 9, and appears to be
relatively stable in natural lake water (MRID 134327). Alachlor does not show any absorption
bands above 240 nm; therefore, it is not expected to undergo photolysis in water or on soil
(MRID 23012).
In soils, under aerobic microbe-rich conditions, alachlor appears to degrade at a moderate rate.
Results of three studies (one acceptable and two supplemental) show that alachlor degrades with
first-order half-lives calculated using linear regression on log-transformed data of 26-34 days;
the aerobic metabolism rates listed in the RED were faster but were 50% dissipation times
(DT50), not half-lives. The terrestrial field dissipation studies include use of different sites,
different formulations, and different soil types, and indicate that under aerobic soil metabolism
conditions, alachlor degrades to several major metabolites. Major degradates in the aerobic soil
metabolism studies were DM-oxanilic acid (with a maximum of 17.0% of the applied), alachlor
sulfonic acid (24.9% of the applied), alachlor oxanilic acid (22.4% of the applied), and alachlor
sulfinylacetic acid (16.2% of the applied). Alachlor sulfinylacetic acid was not observed in the
aerobic soil metabolism study classified as acceptable; however, it was observed in a
supplemental study. All four degradates appear to be more persistent than alachlor, since
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significant concentrations remained in the soils at the end of the studies. Carbon dioxide
(complete mineralization) is the ultimate degradate, comprising 16-30% of the mass applied after
175 days. Unextracted residues comprised <21% of the mass applied at the same test interval,
despite multiple extractions with acetonitrile, ammonium hydroxide, and water (MRIDs 23014,
101531, 134327).
Microbial degradation in aqueous environments is poorly understood; submitted data regarding
this degradation pathway are under review.
Degradates
Major degradates of alachlor include compounds 2-chloro-2',6'-diethylacetanilide, DM-oxanilic
acid, 2',6'-diethyl-2-sulfoacetanilide, 2',6'-diethyl-N-methoxymethyloxoanilic acid, 2',6'-
diethyl-2-hydroxy-N-methoxymethylacetanilide, 2',6'-diethyl-N-methoxymethylacetanilide,
alachlor oxanilic acid, alachlor-ESA, and 2',6'-diethyl-2-hydroxy-N-methoxymethylacetanilide
[Table 2.1 (section 2.2.1)]. Minor degradates include compounds 2',6'-diethylacetanilide ,
2',6'-diethyl-2-methylsulfmylacetanilide, 2',6'-diethyl-N-methoxymethyl-2-oxoacetanilide,
2',6'-diethyl-N-methoxymethyl-2-methylthioacetanilide, 2',6'-diethyl-N-methoxymethyl-2-
methylsulfmylacetanilide, 2',6'-diethyl-N-methoxymethyl-2-methylsulfonylacetanilide, and 2'-
acetyl-2-chloro-6'-ethyl-N-methoxymethylacetanilide.
The major water soluble degradates of alachlor, compounds DM-oxanilic acid, 2',6'-diethyl-2-
sulfoacetanilide, alachlor sulfmylacetic acid, alachlor oxanilic acid, and alachlor-ESA have
carboxylic or sulfonic acid functional groups that render a negative (anionic) character to the
molecule under normal environmental conditions, and, therefore, are expected to be very mobile
in soils. This is based on mobility data for the degradates of propachlor (propachlor sulfonic
acid and propachlor oxanilic acid), which are structurally similar to the degradates of alachlor
(MRID 42485703, 42485704). In addition, a batch equilibrium study on alachlor-ESA shows
that this degradate is very weakly adsorbed, although quantitative results could be obtained in
only one of the soils (Sable silty clay loam; MRID 44405301). The Freundlich Kf value was
0.45 (l/n=0.95), yielding an organic carbon partition coefficient (K0c) value of 15 L/kg0c- Total
toxic residues approach was used for this assessment to evaluate the potential exposure to the
parent and residues of risk concern (i.e., alachlor and 2-chloro-2',6'-diethylacetanilide, 2',6'-
diethyl-N-methoxymethylacetanilide, and 2'6'-diethyl-2-hydroxy-N-methoxymethylacetanilide).
Refer to Section 2.2.1 for a more detailed discussion regarding the toxicity of major degradates
of the parent alachlor.
The total residues of concern (TROC) for alachlor were defined as parent plus 3 degradates of
concern as listed in Table 2.2. Structural analysis suggested that an assumption of additivity is
reasonable (USEPA, 2006). This modeling strategy requires an assumption that all residues of
concern have similar physical, chemical, and partitioning characteristics. The formation of
persistent, toxic degradation products is expected to extend the residual effects of the parent.
Therefore, methology, outlined in the "White Paper on Methods for Assessing Ecological Risks
of Pesticides with Persistent, Bioaccumulative and Toxic Characteristics" presented to the
FIFRA Scientific Advisor Panel, in October, 2008, was followed to calculate total toxic residues
of concern (parent, plus 2-chloro-2',6'-diethylacetanilide, 2',6'-diethyl-N-
Page22of 132
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methoxymethylacetanilide, and 2'6'-diethyl-2-hydroxy-N-methoxymethylacetanilide).
Application rates for alachlor were used to represent the total mass loading of pesticide and its
degradation product. This modeling approach does not consider temporal occurrence of
degradation products.
Mobility
Based upon supplemental studies, alachlor appears to be mobile in soils (MRID 27139, 27140,
78301, 134327). Freundlich soil partitioning coefficients (Kads) for alachlor ranged from 0.35 to
3.7 L/kg (MRID 152209). Corresponding organic carbon distribution coefficient from the
Alachlor Reregi strati on Eligibility Decision Document was 190 L /kg (USEPA, 1998b). These
data range in classification from mobile to moderately mobile according to current guidance
(Environmental Fate and Effects Division, 2006). It is expected that the degradates as well as the
parent will be very mobile in soils due to the water soluble properties and the carboxylic or
sulfonic acid functional groups that render an anionic character to the molecule. Similarly,
alalchlor-ESA was found to be very weakly adsorbed to soils (MRID 44405301), yielding a
Freundlich Kads value of 0.45 (Koc value of 15).
Volatility
Volatilization is not expected to be an important route of dissipation for alachlor; however it
does present a moderate vapor pressure (2.2xlO"5 torr at 24°C; Beestman and Deming, 1974),
and there is some potential for it to volatilize (Section 3.1.3.4).
Bioconcentration
No acceptable bioconcentration data were available for alachlor. The bioconcentration potential
of alachlor is unclear, based on conflicting, unacceptable data on the octanol-water partition
coefficient. In the 1998 RED, it was indicated that alachlor was not expected to bioconcentrate
significantly in fish, based on a relatively low octanol/water partition coefficient (Kow = 434) and
the low Kow values of similar chloroacetanilides (USEPA, 1998b). However, a more recently
submitted octanol/water partition coefficient value (Kow = 1223) offers less support for the
expectation of low bioconcentration (MRID 257282, 40396301).
The screening-level predictive model BCFWIN v2.15 uses alachlor's structural chemistry, an
experimental Kow value of 3.3 x 103 (Hansch etal., 1995), and the submitted Kow value of 1223
to estimate a range of alachlor's bioconcentration factor (BCF = 48 - 102). This range of BCF
estimates supports the expectation of low alachlor bioconcentration in fish but is not
confirmatory.
Furthermore, based on data and a discussion from the most recent Health Effects Division's
(HED) risk assessment for alachlor (USEPA, 2006), alachlor is excreted relatively rapidly in
mammals. Excretion is via both urine and feces, with about 89% of the administered dose
eliminated by 10 days after exposure. Elimination was shown to be biphasic, with an initial
rapid phase (half-life = 0.2 - 10.6 hr), followed by a second slower phase (half-life = 5-16 days)
(MRID 00132045). In rats, alachlor is extensively metabolized (14 metabolites identified in
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urine and 13 in feces). In urine, the sec-amide hydroxymethyl sulfone metabolite was the
predominant metabolite (2.1 - 7.4% of the dose). In feces, the tert-amide mercapturic acid and
the disulfide appeared to be the major metabolites (<5% of dose).
Field Dissipation
In a terrestrial field dissipation study conducted in Chico, California, alachlor, at 4 Ibs a.i./acre,
dissipated with a half-life of 11 days from loam/sandy clay loam soil planted to corn. Most of
the alachlor was found in the 0- to 18-inch soil layers, with occasional detections in the 18- to
24-, 24- to 36-, and 36- to 48-inch layers (the deepest layer sampled), indicating a large extent of
leaching. The four major water-soluble metabolites of alachlor were also monitored in this
study. The soil composition data in this study show increasing percent of clay with soil depth (to
a maximum of 65% clay in the 24- to 36-inch soil depth). This "clay pan" reduces the flow of
water into deeper soils layers, thus, leaching of both parent alachlor and degradates was likely
reduced from what may have occurred if a clay pan was not present (MRID 42528001,
42528002).
The oxanilic acid, sulfmylacetic acid, and ethanesulfonic acid degradates were detected in the 0-
to 6- and 6- to 12-inch soil depths at average concentrations of 0.010-0.045 ppm. Detections
were observed through 36- to 48-inch soil depth for the oxanilic acid, 18- to 24-inch soil depth
for the sulfmylacetic and sulfonic acids, and 6- to 12-inch soil depth for the DM-oxanilic acid.
Generally, detections occurred through 44-90 days post-treatment in the subsoils. Once in the
subsoils, these degradates appeared to persist. Groundwater was not monitored in the study, but
detections of alachlor ethanesulfonic acid in groundwater have been confirmed (USEPA, 1998b).
Alachlor, applied once at 4 Ibs a.i./acre, dissipated with a half-life of 6 days from the 0- to 6-inch
soil depth of a bare-ground plot of sandy loam soil in Hickman, California. Bare ground was
used to simulate preemergent application. Alachlor remained mostly in the 0- to 6-inch soil
depth. Detections averaging 0.018-0.046 ppm were reported in the 6- to 12-inch soil depth on
the day of application and one day afterward (MRID 42528001).
In the Hickman study, the alachlor degradate DM-oxanilic acid was detected in the 0- to 6-inch
soil depth from 1 through day 366 post-treatment. The degradate was detected in the 6- to 12-
inch soil depth only on day 182 post-application (with an average value of 0.004 ppm). Alachlor
oxanilic acid was detected in the 0 to 6-inch soil depth from day 0 through day 366 post-
application; in addition, at three test intervals, detections were reported in the 6- to 12-inch soil
layer. The degradate was also detected in the 12- to 18- and 18- to 24-inch soil layers on day
182 after application. Alachlor sulfmylacetic acid was observed at low levels in the 0- to 6-inch
soil layer from day 1 to 182 after application. In addition, the degradate was detected in the 6- to
12- and 18- to 24-inch soil layers on day 182 after application. Alachlor-ESA was observed at
low levels from day 0 through day 366 after application at average levels ranging from 0.003-
0.010 ppm. Detections were also reported in the 6- to 12-inch soil depth on two test intervals.
Furthermore, alachlor-ESA was detected in the 12- to 18-inch soil depth on day 182 after
application, with an average value of 0.003 ppm (MRID 42528001).
General physical/chemical properties of alachlor are summarized in Table 2.5.
Page 24 of 132
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Table 2.5. General Chemical/Physical Properties of Alachlor.
Parameter
Chemical name
Molecular Weight
Solubility
Vapor Pressure
Hydrolysis half life (pH 3)
Hydrolysis half life (pH 6)
Hydrolysis half life (pH 9)
Aqueous photolysis half life
Soil photolysis half life
Aerobic soil metabolism half life
Soil-water distribution coefficient
(Kads)
Organic carbon partitioning
coefficient (Koc)
Octanol-water partition
coefficient (Kow)
Bioconcentration factor (BCF)
Value
2-chloro-2',6'-diethyl-N-
methoxymethylacetanilide
269.77 g/mol
240 mg/L (24°C)
2.2 x 10'5 torr (24°C)
stable (25°C)
stable (25°C)
stable (25°C)
Assumed stable
Assumed stable
29.7 d (silt loam)
34.0 d (loamy sand)
25.8 d (silt)
0.33 - 3.7 L/kg1
190 L/kg
1223
48 - 102
(estimated)
Source
MRID 134327
MRID146114
Beestman and Deming, 1974
Beestman and Deming, 1974
MRID 134327
MRID 134327
MRID 134327
MRID 23012
MRID 23012
MRID 134327
MRID 152209
USEPA, 1998b
MRID 403 96301
BCFWINv2.15
Range of Kads values for four soils, which may be high due to over-sieving of soils.
2.4.2 Mechanism of Action
An acetanilide, alachlor is a seedling cell growth inhibitor (Ross and Medlin, 2001), primarily
disrupting the growth of new plant seedlings in areas where it is applied. The physiological
details of the mode of action of acetanilide herbicides are not known.
2.4.3 Use Characterization
In the U.S. alachlor is currently registered for use on succulent and dry beans, field and sweet
corn, cotton, woody ornamentals, peanuts, sorghum (milo), soybeans, and sunflowers. For the
woody ornamentals, there is nothing on the alachlor labels that restricts the use to commercial
uses, therefore, both commercial and residential uses will be considered here. There are
currently five alachlor products registered in the U.S. (one product is a technical grade for use in
the manufacture of end-use products and four are end-use products) (see Table 2.6). Of the four
end-use products, two [i.e.., Lariat® Herbicide (EPA Reg. No.: 524-329 and Bullet® Herbicide
(EPA Reg. No.: 524-418)] also contain the herbicide atrazine (and atrazine-related compounds).
However, both of these co-formulated products contain label statements that the products are not
approved for use in California. Only the end-use products approved for use in California [i.e.,
Page 25 of 132
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Lasso® Herbicide, INTRRO (EPA Reg. No.: 524-314) and Micro-Tech® Herbicide (EPA Reg.
No.: 524-344)], which contain only the one active ingredient, i.e., alachlor, are assessed here.
All of the alachlor end-use products are labeled as Restricted Use Pesticides (RUPs).
Page 26 of 132
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Table 2.6. Summary of Alachlor Products Registered in the U.S.
Product
Name
(EPA Reg.
No.)
Lasso® 94%
Stabilized
Technical
(524-316)
Lariat®
Herbicide
(524-329)
Bullet®
Herbicide
(524-418)
Lasso®
Herbicide,
INTRRO
(524-314)
Micro-Tech®
Herbicide
(524-344)
Registrant
Monsanto
Corporation
Monsanto
Corporation
Monsanto
Corporation
Monsanto
Corporation
Monsanto
Corporation
Percent Active
Ingredient
94 (alachlor)
- 27.2 (alachlor)
- 16 (atrazine)
- 0.3 (atrazine-related
compounds)
- 25.4 (alachlor)
- 14.5 (atrazine)
- 0.8 (atrazine-related
compounds)
45.1 (alachlor)
41.5 (alachlor)
Form
Technical
Flowable
concentrate
Emulsifiable
concentrate
Emulsifiable
concentrate
Micro-
encapsulated
Use(s)
Used to make end-
use products
- Corn (all types)
- Sorghum (milo)
- Corn (all types)
- Sorghum (milo)
- Corn
- Corn (sweet)
- Sorghum (milo)
- Soybeans
- Dry beans
- Lima beans
- Woody
ornamentals
- Peanuts
-Corn
- Corn (sweet)
- Sorghum (milo)
- Soybeans
- Dry beans
- Lima beans
- Woody
ornamentals
- Peanuts
- Cotton
- Sunflowers
Assessed in this
Assessment?
No - the technical
grade chemical is only
labeled for use in
producing end use
products.
No - the label contains
a statement that the
product is not approved
for use in California
No - the label contains
a statement that the
product is not approved
for use in California
Yes
Yes
Alachlor can be used nationally in areas where corn, sorghum, soybeans, dry beans, lima beans,
woody ornamentals (junipers and yews), peanuts, cotton, and sunflowers are grown. The two
labels assessed here (Lasso® and Micro-Tech®) prohibit the use of alachlor on beans in Kern
County, California. The labels also prohibit aerial applications of alachlor in California,
therefore, only ground applications will be assessed here. The application rates and application
methods are the same for the two products assessed with the exception that cotton and sunflower
use are allowed on the Micro-Tech® but not the Lasso® label (see Table 2.7).
Page 27 of 132
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Both the maximum yearly and maximum single application rates for alachlor are 4 Ib a.i./acre
(corn, peanuts, sorghum, woody ornamentals, and sunflowers). For peanuts, the Lasso® label
allows a maximum application rate of 4 Ib a.i./acre/year, whereas the Micro-Tech® label allows a
maximum rate of 3 Ib a.i./acre/year (therefore, for peanuts, the 4 Ib a.i./acre rate will be modeled
to represent the maximum application rate). The remaining uses have a maximum yearly and
single application rate of 3 Ib a.i./acre (soybeans and beans) or 2 Ib a.i./acre (cotton). Only a
single application per year is allowed on sweet corn, soybeans, beans, cotton and sunflowers,
while two applications, not to exceed the yearly maximum application rate, are allowed on corn,
peanuts, sorghum, and woody ornamentals (a minimum reapplication interval is not specified on
the current labels). In California, applications are limited to flowable applications via ground
equipment (broadcast boom or banded) or via center pivot irrigation systems. Additionally,
applications via impregnated bulk fertilizer are allowed for some uses (corn, sorghum, and
soybeans). Application timing includes burndown prior to crop, preplant incorporated, pre-
emergence surface, post-emergence surface (corn only), ground-crack surface (peanuts only),
and post-transplant (woody ornamentals only).
The Micro-Tech® label contains restrictions for applications via ground and irrigation equipment.
For ground applications, applications are restricted to a maximum 4-ft boom height, a minimum
ASAE droplet size distribution of medium - coarse, and a maximum wind speed of 10 mph
during application. Application via chemigation is limited to center pivots with a maximum
wind speed of 10 mph during application. For dry bulk fertilizer applications, 200 - 450 Ib of dry
bulk fertilizer per acre is stipulated (with a maximum application rate of 3 to 4 Ib a.i./acre,
depending on the use, see Table 2.7). Wind speeds and droplet size distributions are not
stipulated on the Lasso® label. Both labels also contain the following restriction:
"Do not apply to highly permeable soils (as classified by the USDA Natural Resources
Conservation Service) where the depth to ground water is 30 feet or less"
Although this restriction applies to the entire United States including California, it is not
expected to impact this assessment because ground water in California tends to be deeper than 30
feet. Alachlor application methods and rates used in this assessment are summarized in Table
2.7.
Page 28 of 132
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Table 2.7. Summary of Alachlor Application Methods and Rates for California.
Uses
Corn
Sweet corn
Grain sorghum
(milo)
Peanuts
Soybeans
Dry beans**
Lima beans
(green)**
Woody
ornamentals
(Junipers and
yews)***
Cotton
Sunflowers
Max Appl.
Rate per Year
(Ibs a.i./acre)
4
4
4
4
o
J
3
3
4
2
4
Max Single
Appl. Rate
(Ibs a.i./acre)
4
(no more than
2 can be
applied post-
mergence)
4
4
4
o
J
3
3
4
2
4
Max No.
Appl. Per
Year
2
1
2
2
1
1
1
2
(within 21
days)
1
1
Appl. Methods**
- Ground
- Center pivot irrigation
- Bulk fertilizer impregnation
- Ground
- Center pivot irrigation
- Bulk fertilizer impregnation
- Ground
- Center pivot irrigation
- Bulk fertilizer impregnation
- Ground
- Center pivot irrigation
- Ground
- Center pivot irrigation
- Bulk fertilizer impregnation
- Ground
- Ground
- Ground
- Ground
- Ground
Appl. Timing
- Burndown prior to crop
- Preplant incorporated (no
deeper than 4 inches into the
soil)
- Preemergence surface
- Postemergence surface
- Preplant incorporated (no
deeper than 4 inches into the
soil)
- Preemergence surface
- Burndown prior to crop
- Preplant incorporated (no
deeper than 4 inches into the
soil)
- Preemergence surface
- Preplant incorporated (no
deeper than 4 inches into the
soil)
- Preemergence surface
- Ground-crack surface
- Burndown prior to crop
- Preplant incorporated (no
deeper than 4 inches into the
soil)
- Preemergence surface
- Preplant incorporated (no
deeper than 4 inches into the
soil)
- Preplant incorporated (no
deeper than 4 inches into the
soil)
-Post-transplant
- Preplant incorporated (into
upper 1-2 inches of soil)
- Preemergence surface
- Preplant incorporated (into
upper 1-2 inches of soil)
- Preemergence surface
* Aerial applications are not allowed in CA.
**Not allowed for use on dry beans in Kern County, CA.
*** Nothing on the label restricts the use of alachlor to commercial uses; therefore, it is assumed that alachlor could
be used on woody ornamentals in both commercial and residential settings.
The bolded uses are registered on the Micro-Tech Herbicide label (524-344), but not the Lasso® Herbicide label
(524-314); the remaining uses appear on both labels.
Page 29 of 132
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According to the United States Geological Survey's (USGS) national pesticide usage data (based
on information from 1999 to 2004), an average of 6,221,431 Ibs of alachlor per year are applied
nationally in the U.S. (see Fig. 2.1). Most of the usage (-60%) is for corn, followed by soybeans
(-20%), sorghum (-16%), sweet corn (-3%), dry beans (-2%), and peanuts (<1%). The highest
usage, geographically, is in the corn-growing regions of the Midwestern U.S.
Average annual use of
active ingredient
(pounds per square mile of agricultural
land in county)
D no estimated use
D 0.001 to 0.044
D 0.045 to 0.245
D 0.246 to 1.043
D 1.044 to 2.799
• >=2.8
Crops
corn
soybeans
sorghum
sweet corn
dry beans
peanuts
Total
pounds applied
3687504
1241413
1023185
157974
107155
4200
Percent
national use
59.27
19.95
16.45
2.54
1.72
0.07
Figure 2.1. Estimated Annual Alachlor Usage in the U.S.
(from http://water.usgs.gov/nawqa/pnsp/usage/maps/show map.php?vear=02&map=m8009) [The
pesticide use maps available from this site show the average annual pesticide use intensity expressed as average
weight (in pounds) of a pesticide applied to each square mile of agricultural land in a county. The area of each map
is based on state-level estimates of pesticide use rates for individual crops that were compiled by the CropLife
Foundation, Crop Protection Research Institute based on information collected during 1999 through 2004 and on
2002 Census of Agriculture county crop acreage. The maps do not represent a specific year, but rather show typical
use patterns over the five year period 1999 through 2004.]
The Agency's Biological and Economic Analysis Division (BEAD) provides an analysis of both
national- and county-level usage information (USEPA, 2009) using state-level usage data
obtained from U.S. Department of Agriculture's National Agricultrual Statistics Service (USDA-
Page 30 of 132
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NASS1), Doane (www.doane.com: the full dataset is not provided due to its proprietary nature)
and the CDPR PUR database2. CDPR PUR is considered a more comprehensive source of usage
data than USDA-NASS or Doane's proprietary database, and, thus, the usage data reported for
alachlor by county in this California-specific assessment were generated using CDPR PUR data.
Eight years (1999-2006) of usage data were included in this analysis. Data from CDPR PUR
were obtained for pesticide applications made on use sites at the section level (approximately one
square mile) of the public land survey system. BEAD summarized these data to the county level
by site, pesticide, and unit treated. Calculating county-level usage involved summarizing across
all applications made within a section and then across all sections within a county for each use
site and for each pesticide. The county-level usage data that were calculated include: average
annual pounds applied, average annual area treated, and average and maximum application rate
across all five years. The units of area treated are also provided where available.
The CDPR PUR data indicate that from 1999 to 2006, an average of 26,060 Ibs of alachlor were
applied to an average of 10,315 acres per year in CA. This results in an average application rate
of 2.5 Ib a.i./acre/year (26,060 lbs/10,315 acre). Almost all of the use of alachlor between 1999
and 2006 in CA was on corn (55%) and beans (45%). The remaining alachlor uses listed in the
CDPR PUR data made up <1% of alachlor use (i.e., 'preplant', 'landscape', and 'research', as
listed in the CDPR PUR data).
From 1999 to 2006, alachlor was reportedly used in 24 CA counties (listed in alphabetical order):
Alameda, Butte, Fresno, Glenn, Kern, Los Angeles, Madera, Merced, Monterey, Orange,
Riverside, Sacramento, San Benito, San Diego, San Joaquin, San Luis Obispo, Santa Barbara,
Santa Clara, Solano, Stanislaus, Sutler, Tulare, Ventura, and Yolo (see Fig. 2.3). Based on the
CA usage data, alachlor use has declined over the past several years. For example, in 1999 a
total of 29,327 Ibs of alachlor was applied in CA, whereas a total of 13,734 Ibs was applied in
2006 (see Appendix B)
1 United States Depart of Agriculture (USDA), National Agricultural Statistics Service (NASS) Chemical Use
Reports provide summary pesticide usage statistics for select agricultural use sites by chemical, crop and state. See
http://www.usda. gov/nass/pubs/estindxl .htm#agchem.
2 The California Department of Pesticide Regulation's Pesticide Use Reporting database provides a census of
pesticide applications in the state. See http://www.cdpr.ca.gov/docs/pur/purmain.htm.
Page 31 of 132
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Legend
LBi; .1.1. <:ouiity
No use
[ Item (<9)
(8)
(232)
g^g Monterey Q65 Q
["""I Orar,g* (3)
Sacramento (3 1 9)
San Bern» (180)
| | San Dr«go (39)
[771 ^sn Joaquin (80)
| ] San Uns CNitspo (3)
'^^ SariQ 8atttara (9.17Q)
Sana Ctara (484)
pfij Solano (854)
| 1 Starastaus (9«)
(5 JB47)
Figure 2.2. Average Pounds of Alachlor Applied/Year/CA County from 1999-2006.
Considering each CA county where alachlor was used, the average application rate per
county/year from 1999 to 2006 ranged from <1 to 3.83 Ib a.i./acre. The average 95*% and 99th%
application rate and the maximum reported application rate per county/year ranged from <1 to
3.99 Ib a.i./acre [some counties reported 99th% and maximum application rates higher than the
registered use rates (i.e.., >4 Ib a.i./acre); however, these values are considered misreports or
misuses and were not considered in summary calculations] (see Table 2.8). These data indicate
that, in several CA counties, at least some alachlor users are using the chemical at or near
maximum registered application rates.
Page 32 of 132
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TABLE 2.8 Summary of California Department of Pesticide Registration (CDPR)
Pesticide Use Reporting (PUR) Data from 1999 to 2006 for the Currently Registered
Alachlor Uses.
Average
Pounds
Applied/Year
(for All
Counties)
26,060
County
Alameda
Butte
Fresno
Glenn
Kern
Los Angeles
Madera
Merced
Monterey
Orange
Riverside
Sacramento
San Benito
San Diego
San Joaquin
San Luis Obispo
Santa Barbara
Santa Clara
Solano
Stanislaus
Sutler
Tulare
Ventura
Yolo
Avg
Annual
Area
Treated
(Acres)
1
44
3,283
267
8
41
o
J
91
465
1
139
104
192
24
24
1
1,892
338
302
35
4
656
2,116
378
Avg App Rate
(Ib a.i./Acre
per appl.)
0
2.54
2.5
3.78
2.85
1.99
2.49
2.51
1.87
2.39
1.94
3.1
0.83
0.96
3.83
2.99
2.77
1.67
3.44
2.63
1.99
2.52
2.98
2.80
Avg 95th%
App Rate (Ib
a.i./Acre per
appl.)
-
2.99
3.0
3.99
2.99
1.99
2.49
2.99
2.24
3.99
2.99
3.49
1.0
1.99
3.99
2.99
3.49
2.49
3.99
2.99
1.99
2.99
3.03
3.99
Avg 99th%
App Rate (Ib
a.i./Acre per
appl.)
-
2.99
3.99
29.6*
2.99
1.99
2.49
2.99
2.99
3.99
4.49*
3.49
1.5
1.99
3.99
2.99
4.79*
4.11*
4.10*
2.99
1.99
3.0
3.96
4.70*
Avg Max App
Rate (Ib
a.i./Acre per
appl.)
-
2.99
7.48*
29.6*
2.99
1.99
2.49
2.99
2.99
3.99
4.49*
3.49
3.74
1.99
3.99
2.99
29.91*
74.97*
4.10*
2.99
1.99
3.0
36.29*
4.70*
* These rates are higher than 4 Ib a.i./acre (the max registered application rate); therefore, they are considered
misreports or misuses, and not included in summary calculations.
2.5 Assessed Species
Table 2.9 provides a summary of the current distribution, habitat requirements, and life history
parameters for the listed species being assessed. More detailed life-history and distribution
information can be found in Attachments 1 and 3. See Figures 2.3 and 2.4 for a map of the
current range and designated critical habitat of the assessed listed species. Occurrence data at the
section level for the delta smelt is based on information provided in the case, Center for
Biological Diversity (CBD) vs. EPA et al. (Case No. 07-2794-JCS).
Page 33 of 132
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Table 2.9. Summary of Current Distribution, Habitat Requirements, and Life History Information for the Assessed Listed
Species1
Assessed Species
California red-
legged frog
(Rana aurora
draytonii)
Delta smelt
(Hypomesus
transpacificus)
Size
Adult
(85-138 cm
in length),
Females -
9-238 g,
Males -
13-163 g;
Juveniles
(40-84 cm
in length)
Up to 120
mm in
length
Current Range
Northern CA coast, northern
Transverse Ranges, foothills of
Sierra Nevada, and in southern CA
south of Santa Barbara
Suisun Bay and the Sacramento-
San Joaquin estuary (known as the
Delta) near San Francisco Bay, CA
Habitat Type
Freshwater perennial
or near-perennial
aquatic habitat with
dense vegetation;
artificial
impoundments;
riparian and upland
areas
The species is
adapted to living in
fresh and brackish
water. They typically
occupy estuarine
areas with salinities
below 2 parts per
thousand (although
they have been found
in areas up to ISparts
per thousand). They
live along the
freshwater edge of
the mixing zone
(saltwater-freshwater
interface).
Designated
Critical
Habitat?
Yes
Yes
Reproductive
Cycle
Breeding: Nov. to Apr.
Tadpoles: Dec. to Mar.
Young juveniles: Mar. to
Sept.
Spawns in fresh or
slightly brackish water
upstream of the mixing
zone. Spawning season
usually takes place from
late March through mid-
May, although it may
occur from late winter
(Dec.) to mid-summer
(July-August). Eggs
hatch in 9 - 14 days.
Diet
Aquatic -phase2: algae
(tadpoles only),
freshwater aquatic
invertebrates and fish
Terrestrial-phase:
terrestrial invertebrates,
small mammals, and
frogs
Adults forage primarily
on planktonic
copepods, cladocerans,
amphipods, and insect
larvae. Larvae feed on
phytoplankton;
juveniles feed on
zooplankton.
1 For more detailed information on the distribution, habitat requirements, and life history information of the
2 For the purposes of this assessment, tadpoles and submerged adult frogs are considered "aquatic" because
different than those that occur on land.
assessed listed species, see Attachment 3
exposure pathways in the water are considerably
Page 34 of 132
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Delta smelt habitat areas
Map created by US EPA on 04/15/09. Projection: Albers Equal Area
Conic USGS, North American Datum of 1983 (NAD 1983). California
county boundaries, source: ESR] 2002. Water bodies, source:
NHDPIus2006. DS occurrence section information obtained from:
Case No. 07-2794JCS). DS critical habitat obtained from
http://crithab.fws.gov/.
024
I i i i I
Miles
~
,
1:500,000
Figure 2.3. Delta Smelt Habitat Areas.
Page 35 of 132
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Recovery Units
1. Sierra Nevada Foothills and Central Valley
2. North Coast Range Foothills nd Western
Sacramento River Valley
3. North Coast and North San Francisco Bay
4. South and East San Francisc Bay
5. Central Coast
Diablo Range and Salinas Valley
Northern Transverse Rang nd Tehachapi
Mountains
Southern Transverse and Peninsular Ranges
Legend
] Recovery Unit Boundaries
\\ Currently Occupied Core Areas
^B Critical Habitat
BH CNDDB Occurence Sections
County Boundaries g
45
Core Areas
1. Feather River
2. Yuba River- S. Fork Feather River
3. Traverse Creek/ Middle Fork/ American R. Rubicon
4. Cosumnes River
5. South Fork Calaveras River*
6. Tuolumne River*
7. Piney Creek*
8. Cottonwood Creek
9. Putah Creek - Cache Creek*
10. Lake Berryessa Tributaries
11. Upper Sonoma Creek
12. Petaluma Creek — Sonoma Creek
13. Ft. Reyes Peninsula
14. Belvedere Lagoon
15. Jameson Canyon - Lower Napa River
16. East San Francisco Bay
17. Santa Clara Valley
18. South San Francisco Bay
* Core areas that were historically occupied by the California red
19. Watsonville Slough-Elkhorn Slough
20. Carmel River — Santa Lucia
21. Gab Ian Range
22. Estero Bay
23. Arroyo Grange River
24. Santa Maria River - Santa Ynez River
25. Sisquoc River
26. Ventura River - Santa Clara River
27. Santa Monica Bay - Venura Coastal Streams
28. Estrella River
29. San Gabriel Mountain*
30. Forks of the Mojave*
31. Santa Ana Mountain*
32. Santa Rosa Plateau
33. San Luis Ray*
34. Sweetwater*
35. Laguna Mountain*
-legged frog are not included in the map
Figure 2.4. Recovery Unit, Core Area, Critical Habitat, and Occurrence Designations for
CRLF.
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2.6. Designated Critical Habitat
Critical habitat has been designated for the CRLF and the DS. 'Critical habitat' is defined in the
ESA as the geographic area occupied by the species at the time of the listing where the physical
and biological features necessary for the conservation of the species exist, and there is a need for
special management to protect the listed species. It may also include areas outside the occupied
area at the time of listing if such areas are 'essential to the conservation of the species.' Critical
habitat receives protection under Section 7 of the ESA through prohibition against destruction or
modification with regard to actions carried out, funded, or authorized by a federal Agency.
Section 7 requires consultation on federal actions that are likely to result in the destruction or
modification of critical habitat.
To be included in a critical habitat designation, the habitat must be 'essential to the conservation
of the species.' Critical habitat designations identify, to the extent known using the best
scientific and commercial data available, habitat areas that provide essential life cycle needs of
the species or areas that contain certain primary constituent elements (PCEs) (as defined in 50
CFR 414.12(b)). PCEs include, but are not limited to, space for individual and population
growth and for normal behavior; food, water, air, light, minerals, or other nutritional or
physiological requirements; cover or shelter; sites for breeding, reproduction, rearing (or
development) of offspring; and habitats that are protected from disturbance or are representative
of the historic geographical and ecological distributions of a species. Table 2.10 describes the
PCEs for the critical habitats designated for the CRLF and the DS.
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Table 2.10. Designated Critical Habitat PCEs for the CRLF and DS.
Species
CRLF
DS
PCEs
Alteration of channel/pond morphology or geometry and/or increase in
sediment deposition within the stream channel or pond.
Alteration in water chemistry /quality including temperature, turbidity, and
oxygen content necessary for normal growth and viability of juvenile and adult
CRLFs and their food source.
Alteration of other chemical characteristics necessary for normal growth and
viability of CRLFs and their food source.
Reduction and/or modification of aquatic -based food sources for pre-
metamorphs (e.g., algae)
Elimination and/or disturbance of upland habitat; ability of habitat to support
food source of CRLFs: Upland areas within 200 ft of the edge of the riparian
vegetation or dripline surrounding aquatic and riparian habitat that are
comprised of grasslands, woodlands, and/or wetland/riparian plant species that
provides the CRLF shelter, forage, and predator avoidance
Elimination and/or disturbance of dispersal habitat: Upland or riparian dispersal
habitat within designated units and between occupied locations within 0.7 mi of
each other that allow for movement between sites including both natural and
altered sites which do not contain barriers to dispersal
Reduction and/or modification of food sources for terrestrial phase juveniles
and adults
Alteration of chemical characteristics necessary for normal growth and viability
of juvenile and adult CRLFs and their food source.
Spawning Habitat — shallow, fresh or slightly brackish backwater sloughs and
edgewaters to ensure egg hatching and larval viability. Spawning areas also
must provide suitable water quality (i.e., low "concentrations of pollutants) and
substrates for egg attachment (e.g., submerged tree roots and branches and
emergent vegetation).
Larval and Juvenile Transport — Sacramento and San Joaquin Rivers and their
tributary channels must be protected from physical disturbance and flow
disruption. Adequate river flow_is necessary to transport larvae from upstream
spawning areas to rearing habitat in Suisun Bay. Suitable water quality must be
provided so that maturation is not impaired by pollutant concentrations.
Rearing Habitat — Maintenance of the 2 ppt isohaline and suitable water quality
(low concentrations of pollutants) within the Estuary is necessary to provide
delta smelt larvae and juveniles a shallow protective, food-rich environment in
which to mature to adulthood.
Adult Migration — Unrestricted access to suitable spawning habitat in a period
that may extend from December to July. Adequate flow and suitable water
qualityjnay need to be maintained to attract migrating adults in the Sacramento
and San Joaquin River channels and their associated tributaries. These areas
also should be protected from physical disturbance and flow disruption during
migratory periods.
Reference
50CFR414.12(b),
2006
59 FR 65256
65279, 1994
1 These PCEs are in addition to more general requirements for habitat areas that provide essential life cycle needs of
the species such as, space for individual and population growth and for normal behavior; food, water, air, light,
minerals, or other nutritional or physiological requirements; cover or shelter; sites for breeding, reproduction,
rearing (or development) of offspring; and habitats that are protected from disturbance or are representative of the
historic geographical and ecological distributions of a species.
2 PCEs that are abiotic, including, physico-chemical water quality parameters such as salinity, pH, and hardness are
not evaluated because these processes are not biologically mediated and, therefore, are not relevant to the endpoints
included in this assessment.
More detail on the designated critical habitat applicable to this assessment can be found in
Attachment 1 (for the CRLF) and Attachment 3 (for the DS). Activities that may destroy or
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modify critical habitat are those that alter the PCEs and jeopardize the continued existence of the
species. Evaluation of actions related to use of alachlor that may affect the PCEs of the
designated critical habitat for the CRLF and DS form the basis of the critical habitat impact
analysis.
As previously discussed, the Agency believes that the analysis of direct and indirect effects to
listed species provides the basis for an analysis of potential effects on the designated critical
habitat. Because alachlor is expected to directly impact living organisms within the action area,
critical habitat analysis for alachlor is limited in a practical sense to those PCEs of critical habitat
that are biological or that can be reasonably linked to biologically mediated processes.
2.7 Action Area
Deriving the geographical extent of the California portion of the action area is based on
consideration of the types of effects that alachlor may be expected to have on the environment,
the exposure levels to alachlor that are associated with those effects, and the best available
information concerning the use of alachlor and its fate and transport within the state of
California. Specific measures of ecological effect that define the action area include any direct
and indirect toxic effect, including reduction in survival, growth, and fecundity as well as the full
suite of sublethal effects available in the effects literature. Therefore, the action area extends to a
point where environmental exposures are below any measured lethal or sublethal effect threshold
for any biological entity at the whole organism, organ, tissue, and cellular level of organization.
In situations where it is not possible to determine the threshold for an observed effect, the action
area is not spatially limited and is assumed to be the entire state of California. The registered
agricultural and non-agricultural uses relative to potential land cover classes from the National
Land Cover Data (NLCD), which represent the current and possible future extent of the use sites,
represent the initial area of concern and are illustrated in Figure 2.5.
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Alachlor Use - Initial Area of Concern
Developed-open space
Developed-low density
Developed-medium density
Developed-high density
Cultivated crop use
County Boundaries
i Kilometers
0 2040 80 120 160
Compiled ftom California county boundaries
-------
A number of alachlor studies have been conducted that have identified some type of biological
effect (see Appendices C, D, and E). Some studies have identified only exposure levels
associated with an effect without a corresponding no effect level. For example, the most
sensitive available toxicity endpoint for chronic exposure in estuarine/marine invertebrates is a
NOAEC of <0.0001 for a copepod (Tigriopus japonicus) based on an increase in the generation
time for adults in the F0 and FI generations at all of the concentrations tested (Lee et al. 2008,
El04287). Additionally, the most sensitive available NOAEC for birds based on chronic
exposure is <50 mg a.i./kg-diet for mallard ducks (Anasplatyrhynchos) based on significant
treatment-related reductions in hatchling weight at all concentrations tested (MRID 449515-01).
Therefore, a threshold for some type of environmental effect has not been identified, and it is not
possible to identify an alachlor exposure level that is definitively associated with no
environmental effects regardless of the ecological significance of the effect. For this reason, the
action area (area where an effect may occur) has been conservatively defined as the entire state
of California.
2.8 Assessment Endpoints and Measures of Ecological Effect
Assessment endpoints are defined as "explicit expressions of the actual environmental value that
is to be protected."3 Selection of the assessment endpoints is based on valued entities (e.g.,
CRLF and DS), organisms important in the life cycle of the valued entities (i.e., the assessed
species, and the PCEs of their designated critical habitat), the ecosystems potentially at risk (e.g.,
waterbodies, riparian vegetation, and upland and dispersal habitats), the migration pathways of
alachlor (e.g., runoff, spray drift, etc), and the routes by which ecological receptors are exposed
to alachlor (e.g., direct contact, etc.).
2.8.1. Assessment Endpoints
Assessment endpoints for the CRLF and the DS include direct toxic effects on the survival,
reproduction, and growth of individuals, as well as indirect effects, such as reduction of the prey
base or effects to its habitat. In addition, potential effects to critical habitat is assessed by
evaluating potential effects to PCEs, which are components of the habitat areas that provide
essential life cycle needs of the assessed species. Each assessment endpoint requires one or more
"measures of ecological effect," defined as changes in the attributes of an assessment endpoint or
changes in a surrogate entity or attribute in response to exposure to a pesticide. Specific
measures of ecological effect are generally evaluated based on acute and chronic toxicity
information from registrant-submitted guideline tests that are performed on a limited number of
organisms. Additional ecological effects data from the open literature are also considered. It
should be noted that assessment endpoints are limited to direct and indirect effects associated
with survival, growth, and fecundity, and do not include the full suite of sublethal effects used to
define the action area. According to the Overview Document (USEPA 2004), the Agency relies
on acute and chronic effects endpoints that are either direct measures of impairment of survival,
growth, or fecundity or endpoints for which there is a scientifically robust, peer reviewed
relationship that can quantify the impact of the measured effect endpoint on the assessment
endpoints of survival, growth, and fecundity.
'From U.S. EPA (1992). Framework for Ecological Risk Assessment. EPA/630/R-92/001.
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A complete discussion of all the toxicity data available for this risk assessment, including
resulting measures of ecological effect selected for each taxonomic group of concern, is included
in Section 4 of this document. A summary of the assessment endpoints and measures of
ecological effect selected to characterize potential assessed direct and indirect risks for each of
the assessed species associated with exposure to alachlor is provided in Table 2.12.
As described in the Agency's Overview Document (USEPA, 2004), the most sensitive endpoint
for each taxonomic group is used for risk estimation. For this assessment, evaluated taxa include
aquatic-phase amphibians, freshwater and saltwater fish, freshwater and saltwater invertebrates,
aquatic plants, birds (surrogate for terrestrial-phase amphibians), mammals, terrestrial
invertebrates, and terrestrial plants. Acute (short-term) and chronic (long-term) toxicity
information is characterized based on registrant-submitted studies and a comprehensive review
of the open literature on alachlor.
Table 2.11 identifies the taxa used to assess the potential for direct and indirect effects from the
uses of alachlor for each listed species assessed. The specific assessment endpoints used to
assess the potential for direct and indirect effects to each listed species are provided in Table 2.8.
Table 2.11. Taxa Used in the Analyses of Direct and Indirect Effects for the Assessed Listed
Species.
Listed
Species
California
red-legged
frog
Delta
smelt
Birds /
Terr.
Amphibian
Indirect
(prey)
N/A
Mammals
Indirect
(prey)
N/A
Terr.
Plants
Indirect
(habitat)
Indirect
(habitat)
Terr.
Inverts.
Indirect
(prey)
N/A
FW Fish /
Amphibian
Indirect
(prey)
Direct1
FW
Inverts.
Indirect
(prey)
Indirect
(prey)
Estuarine
/Marine
Fish
N/A
Direct
Estuarine
/Marine
Inverts.
N/A
Indirect
(prey)
Aquatic
Plants
Indirect
(food/
habitat)
Indirect
(food/
habitat)
N/A = Not applicable; Terr. = Terrestrial; Invert. = Invertebrate; FW = Freshwater
1 The most sensitive species across freshwater and saltwater environments was used for the DS.
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Table 2.12. Assessment Endpoints Used to Evaluate the Potential for the Use of Alachlor to
Result in Direct and Indirect Effects to the CRLF and the DS.
Taxa Used to Assess
Direct and/or Indirect
Effects to Assessed
Species1
Assessed Listed
Species
Assessment Endpoints
Measures of Ecological Effects
1. Freshwater Fish and
Aquatic-phase
Amphibians
Direct Effect -
-Aquatic-phase CRLF
-DS
Survival, growth, and
reproduction of individuals
via direct effects
Indirect Effect (prey)
-Aquatic-phase CRLF
Survival, growth, and
reproduction of individuals
via indirect effects on
aquatic prey food supply
(i.e., fish and aquatic-phase
amphibians)
la. Amphibian acute LC50 (ECOTOX) or
most sensitive fish acute LC50 (guideline
or ECOTOX) if no suitable amphibian
data are available
Ib. Amphibian chronic NOAEC
(ECOTOX) or most sensitive fish chronic
NOAEC (guideline or ECOTOX)
Ic. Amphibian early-life stage data
(ECOTOX) or most sensitive fish early-
life stage NOAEC (guideline or
ECOTOX)
2. Freshwater
Invertebrates
Indirect Effect (prey)
-Aquatic-phase CRLF
-DS
Survival, growth, and
reproduction of individuals
via indirect effects on
aquatic prey food supply
(i.e., freshwater
invertebrates)
2a. Most sensitive freshwater
invertebrate EC50 (guideline or ECOTOX)
2b. Most sensitive freshwater
invertebrate chronic NOAEC (guideline
or ECOTOX)
. Estuarine/Marine Fish
Direct Effect
-DS
Survival, growth, and
reproduction of individuals
via direct effects on the DS
3a. Most sensitive estuarine/marine fish
LC50 (guideline or ECOTOX)
3b. Most sensitive estuarine/marine fish
chronic NOAEC (guideline or ECOTOX)
4. Estuarine/Marine
Invertebrates
Indirect Effect (prey)
-DS
Survival, growth, and
reproduction of individuals
via indirect effects on
aquatic prey food supply
(i.e., estuarine/marine
invertebrates)
4a. Most sensitive estuarine/marine
invertebrate EC50 (guideline or ECOTOX)
4b. Most sensitive estuarine/marine
invertebrate chronic NOAEC (guideline
or ECOTOX)
5. Aquatic Plants
(freshwater/marine)
Indirect Effect
(food/habitat)
-Aquatic-phase CRLF
-DS
Survival, growth, and
reproduction of individuals
via indirect effects on
habitat, cover, food supply,
and/or primary productivity
(i.e., aquatic plant
community)
5a. Vascular plant acute EC50 (duckweed
guideline test or ECOTOX vascular plant)
5b. Non-vascular plant acute EC50
(freshwater algae or diatom, or ECOTOX
non-vascular)
6. Birds
Direct Effect
-Terrestrial-phase CRLF
Survival, growth, and
reproduction of individuals
via direct effects
Indirect Effect (prey)
-CRLFs
Survival, growth, and
reproduction of individuals
via indirect effects on
terrestrial prey (surrogate
for amphibians)
6a. Most sensitive bird or terrestrial-
phase amphibian acute LC50 or LD50
(guideline or ECOTOX)
6b. Most sensitive birdb or terrestrial-
phase amphibian chronic NOAEC
(guideline or ECOTOX)
7. Mammals
Indirect Effect
-Terrestrial-phase CRLF
Survival, growth, and
reproduction of individuals
via indirect effects on
terrestrial prey (mammals)
7a. Most sensitive laboratory rat acute
LC50 or LD50 (guideline or ECOTOX)
7b. Most sensitive laboratory rat chronic
NOAEC (guideline or ECOTOX)
8. Terrestrial
Invertebrates
Indirect Effect (prey)
-Terrestrial-phase CRLF
Survival, growth, and
reproduction of individuals
via indirect effects on
8a. Most sensitive terrestrial invertebrate
acute EC50 or LC50 (guideline or
ECOTOX)0
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Taxa Used to Assess
Direct and/or Indirect
Effects to Assessed
Species1
9. Terrestrial Plants
Assessed Listed
Species
Indirect Effect
(food/habitat) (non-
obligate relationship)
-Terrestrial- and
aquatic -phase CRLF
-DS
Assessment Endpoints
terrestrial prey (terrestrial
invertebrates)
Survival, growth, and
reproduction of individuals
via indirect effects on food
and habitat (i.e., riparian
and upland vegetation)
Measures of Ecological Effects
8b. Most sensitive terrestrial invertebrate
chronic NOAEC (guideline or ECOTOX)
9a. Distribution of EC2s for monocots
(seedling emergence, vegetative vigor, or
ECOTOX
9b. Distribution of EC2s fordicots
(seedling emergence, vegetative vigor, or
ECOTOX)
1 For the DS both freshwater and estuarine/marine species are considered since the DS can inhabit both freshwater
and estuarine/marine environments.
2.8.2 Assessment Endpoints for Designated Critical Habitat
As previously discussed, designated critical habitat is assessed to evaluate actions related to the
use of alachlor that may affect the PCEs of the assessed species' designated critical habitat.
PCEs for the assessed species were previously described in Section 2.6. Actions that may
modify critical habitat are those that alter the PCEs and jeopardize the continued existence of the
assessed species. Therefore, these actions are identified as assessment endpoints. Evaluation of
PCEs as assessment endpoints is limited to those of a biological nature (i.e., the biological
resource requirements for the listed species associated with the critical habitat) and those for
which alachlor effects data are available.
Assessment endpoints used to evaluate potential for direct and indirect effects are equivalent to
the assessment endpoints used to evaluate potential effects to designated critical habitat. If a
potential for direct or indirect effects is found, then there is also a potential for effects to critical
habitat. Some components of PCEs are associated with physical abiotic features (e.g.., presence
and/or depth of a water body, or distance between two sites), which are not expected to be
measurably altered by use of pesticides.
2.9 Conceptual Model
2.9.1 Risk Hypotheses
Risk hypotheses are specific assumptions about potential adverse effects (i.e., changes in
assessment endpoints) and may be based on theory and logic, empirical data, mathematical
models, or probability models (USEPA, 1998). For this assessment, the risk is stressor-linked,
where the stressor is the release of alachlor to the environment. The following risk hypotheses
are presumed for this assessment:
The labeled use of alachlor may:
• ... directly affect the CRLF and/or the DS by causing mortality or by adversely affecting
growth or fecundity;
• ... indirectly affect the CRLF and/or the DS and/or affect their designated critical habitat
by reducing or changing the composition of the food supply;
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• ... indirectly affect the CRLF and/or the DS and/or affect their designated critical habitat
by reducing or changing the composition of the aquatic plant community in the species' current
range, thus, affecting primary productivity and/or cover;
• ... indirectly affect the CRLF and/or the DS and/or affect their designated critical habitat
by reducing or changing the composition of the terrestrial plant community in the species'
current range;
• ... indirectly affect the CRLF and/or the DS and/or affect their designated critical habitat
by reducing or changing aquatic habitat in their current range (via modification of water quality
parameters, habitat morphology, and/or sedimentation).
2.9.2 Diagram
The conceptual model is a graphic representation of the structure of the risk assessment. It
specifies the alachlor release mechanisms, biological receptor types, and effects endpoints of
potential concern. The conceptual models for aquatic and terrestrial phases of the CRLF and the
DS and the conceptual models for the aquatic and terrestrial PCE components of critical habitat
are shown in Figures 2.6 and 2.7. Although the conceptual models for direct/indirect effects and
effects to designated critical habitat PCEs are shown on the same diagrams, the potential for
direct/indirect effects and effects to PCEs will be evaluated separately in this assessment.
Exposure routes shown in dashed lines are not quantitatively considered because the contribution
of those potential exposure routes to potential risks to the CRLF and the DS and effects to
designated critical habitat is expected to be negligible.
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Stressor
Source
Exposure
Media
Alachlor applied to use site
.T.
Long range
atmospheric
transport
\ Spray drift)
—Dermal uptake/lnaestiorr*—
Root uptake^J
Wet/dry deposition^
Terrestrial/riparian plants
grasses/forbs, fruit, seeds
(trees, shrubs)
Terrestrial-phase
amphibians
Receptors
Birds/terrestrial-
phase amphibians/
reptiles/mammals
Attribute
Change
Individual
organisms
Reduced survival
Reduced growth
Reduced reproduction
Food chain
Reduction in prey
Modification of PCEs
related to prey availability
Habitat integrity
Reduction in primary productivity
Reduced cover
ommunity change
Modification of PCEs related to
habitat
Figure 2.6. Conceptual Model for Risks to Terrestrial-Phase CRLF from Alachlor Use.
Page 46 of 132
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Stressor
Source
Exposure
Media
Alachlor applied to use site
I Spray drift | | Runoff
| Soil }•
*• Groundwater:
Surface water/
Sediment
\
T
.T.
Long range
atmospheric
transport
,.Wet/dry deposition.
Receptors
Uptake/gills
or integument
Uptake/gills
or integument
Aquatic Animals
Invertebrates
Vertebrates
T
Inqe^tion
Fish/aquatic-phase
amphibians
Attribute Individual
Change
organisms
Reduced survival
Reduced growth
Reduced reproduction
Uptake/cell,
roots, leaves
Aquatic Plants
Non-vascular
Vascular
t
Inqestion
Food chain
Reduction in algae
Reduction in prey
Modification of PCEs
related to prey availability
1
Riparian plants
terrestrial
exposure
pathways
Habitat integrity
Reduction in primary
oroductivity
Reduced cover
ommunity change
Modification of PCEs related to
habitat
Figure 2.7. Conceptual Model for Risks to Aquatic-Phase CRLF and the DS from Use of
Alachlor.
2.10. Analysis Plan
In order to address the risk hypothesis, the potential for direct and indirect effects to the CRLF
and the DS, prey items, and habitat is estimated based on a taxon-level approach. In the
following sections, the use, environmental fate, and ecological effects of alachlor are
characterized and integrated to assess the risks. This is accomplished using a risk quotient (ratio
of exposure concentration to effects concentration) approach. Although risk is often defined as
the likelihood and magnitude of adverse ecological effects, the risk quotient-based approach does
not provide a quantitative estimate of likelihood and/or magnitude of an adverse effect.
However, as outlined in the Overview Document (USEPA, 2004), the likelihood of effects to
individual organisms from particular uses of alachlor is estimated using the probit dose-response
slope and either the level of concern (discussed below) or actual calculated risk quotient value.
2.10.1 Measures of Exposure
Measures of exposure are based on aquatic and terrestrial models that predict estimated
environmental concentrations (EECs) of alachlor using maximum labeled application rates and
methods of application. The models used to predict aquatic EECs are the Pesticide Root Zone
Model coupled with the Exposure Analysis Model System (PRZM/EXAMS). The model used to
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predict terrestrial EECs on food items is T-REX. The model used to derive EECs relevant to
terrestrial and wetland plants is TerrPlant. These models are parameterized using relevant
reviewed registrant-submitted environmental fate data.
PRZM (V3.12.2, May 2005) and EXAMS (V2.98.4.6, April 2005) are screening simulation
models coupled with the input shell pe5.pl (August, 2007) to generate daily exposures and 1-in-
10 year EECs of alachlor that may occur in surface water bodies adjacent to application sites
receiving alachlor through runoff and spray drift. PRZM simulates pesticide application,
movement and transformation on an agricultural field and the resultant pesticide loadings to a
receiving water body via runoff, erosion and spray drift. EXAMS simulates the fate of the
pesticide and resulting concentrations in the water body. The standard scenario used for
ecological pesticide assessments assumes application to a 10-hectare agricultural field that drains
into an adjacent 1-hectare water body, 2-meters deep (20,000 m3 volume) with no outlet.
PRZM/EXAMS was used to estimate screening-level exposure of aquatic organisms to alachlor.
The measure of exposure for aquatic species is the l-in-10 year return peak or rolling mean
concentration. The l-in-10-year 60-day mean is used for assessing chronic exposure to fish; the
l-in-10-year 21-day mean is used for assessing chronic exposure for aquatic invertebrates.
Degradates of the parent alachlor were modeled in PRZM/EXAMS using the Total Residues
method, where this modeling strategy requires an assumption that all residues of concern have
similar physical, chemical, and partitioning characteristics. Application rates for the parent
pesticide (alachlor) are used to represent the total mass loading of pesticide and its degradation
product(s). Degradation half-lives are calculated based on cumulative residues of concern and
parent alachlor (USEPA, 2008).
Exposure estimates for the terrestrial animals assumed to be in the target area or in an area
exposed to spray drift are derived using the T-REX model (version 1.4.1, 10/2008). This model
incorporates the Kenega nomograph, as modified by Fletcher et al. (1994), which is based on a
large set of actual field residue data. The upper limit values from the nomograph represented the
95th percentile of residue values from actual field measurements (Hoerger and Kenega, 1972).
The model is parameterized considering relevant, reviewed registrant-submitted and open
literature fate data. The terrestrial exposure estimates are based on parent alachlor alone.
For the post-emergence (corn only), ground-crack surface (peanuts only), and burndown
flowable applications, residues on potential food items (foliage and/or terrestrial invertebrates)
on the field of application will be estimated. For the remaining types of flowable applications,
estimated residues for terrestrial invertebrates will also be made for the target site of application
using T-REX (since invertebrates could be on the field of application during application).
However, foliar residues are not expected on the site of application for soil incorporated (pre-
plant only) or soil surface (pre-plant and pre-emergence) applications to bare soil. Therefore, for
the soil surface applications (pre-plant and pre-emergence) estimated residues on potential
herbaceous food items will be bound using estimates from the site of application (to model
situations when grasses/weeds might be on the field of application) and areas immediately
adjacent to the field of application (to model applications to bare soil).
To estimate the highest potential exposure from foliage (immediately adjacent to the site of
application) for the bare-soil surface applications, the spray drift model AgDRIFT will be used to
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estimate the amount of chemical expected 1 ft off the field of application. The estimated amount
of chemical found 1 ft off the site of application (in Ib a.i./acre) will then be used as an
application rate in T-REX to estimate the foliar residues expected immediately adjacent to the
site of application.
For modeling purposes, direct exposures of the CRLF to alachlor through contaminated food are
estimated using the EECs for a small bird (20 g) that consumes small insects. Dietary-based and
dose-based exposures of potential prey (small mammals) are assessed using the small mammal
(15 g) which consumes short grass. The small bird (20g) consuming small insects and the small
mammal (15g) consuming short grass are used because these categories result in the largest RQs
for the size/dietary categories in T-REX that are appropriate surrogates for the CRLF. Estimated
exposures of terrestrial insects to alachlor are bound by using the dietary-based EECs for small
insects and large insects.
For the alachlor applications using impregnated dry bulk fertilizer, the bulk fertilizer will be
treated as a granular formulation for modeling purposes. Terrestrial exposures from impregnated
fertilizer applications will be estimated using T-REX assuming none of the alachlor-impregnated
fertilizer is incorporated into the soil. Risk to terrestrial animals from ingesting the fertilizer will
be based on LDso/ft2 values. The LDso/ft2 values are calculated using an avian toxicity value and
the EEC (mg a.i./ft2) and are directly compared with Agency's levels of concern (LOCs) for risk
characterization purposes.
Birds are currently used as surrogates for terrestrial-phase amphibians and reptiles. However,
amphibians and reptiles are poikilotherms (body temperature varies with environmental
temperature) while birds are homeotherms (temperature is regulated, constant, and largely
independent of environmental temperatures). Therefore, amphibians and reptiles tend to have
much lower metabolic rates and lower caloric intake requirements than birds or mammals. As a
consequence, birds are likely to consume more food than amphibians and reptiles on a daily
dietary intake basis, assuming similar caloric content of the food items. Therefore, the use of
avian food intake allometric equation as a surrogate to amphibians and reptiles is likely to result
in an over-estimation of exposure and risk for reptiles and terrestrial-phase amphibians. For this
reason, food intake equations more specific to terrestrial phase amphibians were used to refine
the potential dietary exposures to terrestrial phase CRLF. These food intake equations were
incorporated into T-REX to form an exposure model called T-HERPS (v. 1.0), which allows for
an estimation of food intake for poikilotherms using the same basic procedure as T-REX uses to
estimate avian food intake.
EECs for terrestrial plants inhabiting dry and wetland areas are derived using TerrPlant (version
1.2.2, 12/26/2006). This model uses estimates of pesticides in runoff and in spray drift to
calculate EECs. EECs are based upon solubility, application rate and minimum incorporation
depth.
The spray drift model, AgDRIFT is used to assess exposures of terrestrial animals to alachlor
deposited on terrestrial and aquatic habitats by spray drift. In addition to the buffered area from
the spray drift analysis, the downstream extent of alachlor that exceeds the LOG for the areas of
potential effect is also considered.
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2.10.2 Measures of Effect
Data identified in Section 2.8 are used as measures of effect for direct and indirect effects to the
CRLF and the DS. Data were obtained from registrant submitted studies or from literature
studies identified by ECOTOX. The ECOTOXicology database (ECOTOX) was searched in
order to provide more ecological effects data and in an attempt to bridge existing data gaps.
ECOTOX is a source for locating single chemical toxicity data for aquatic life, terrestrial plants,
and wildlife. ECOTOX was created and is maintained by the USEPA, Office of Research and
Development, and the National Health and Environmental Effects Research Laboratory's Mid-
Continent Ecology Division.
The assessment of risk for direct effects to the terrestrial-phase CRLF makes the assumption that
toxicity of alachlor to birds is similar to the toxicity to terrestrial-phase amphibians and reptiles
(this also applies to potential prey items). The same assumption is made for fish and aquatic-
phase CRLF.
The acute measures of effect used for animals in the screening-level portion of this assessment
are the LD50, LCso and ECso. LD stands for "Lethal Dose", and LD50 is the amount of a material,
given all at once, that is estimated to cause the death of 50% of the test organisms. LC stands for
"Lethal Concentration" and LC50 is the concentration of a chemical that is estimated to kill 50%
of the test organisms. EC stands for "Effective Concentration" and the ECso is the concentration
of a chemical that is estimated to produce a specific effect in 50% of the test organisms.
Endpoints for chronic measures of exposure for listed and non-listed animals are the
NOAEL/NOAEC and NOEC. NOAEL stands for "No Ob served-Adverse-Effect-Level" and
refers to the highest tested dose of a substance that has been reported to have no harmful
(adverse) effects on test organisms. The NOAEC (i.e., "No-Observed-Adverse-Effect-
Concentration") is the highest test concentration at which none of the observed effects were
statistically different from the control. The NOEC is the No-Observed-Effects-Concentration.
For non-listed plants, only acute exposures are assessed (i.e., EC25 for terrestrial plants and ECso
for aquatic plants).
The measures of effect for direct and indirect effects to the assessed species and their designated
critical habitat are associated with impacts to survival, growth, and fecundity, and do not include
the full suite of sublethal effects used to define the action area. According the Overview
Document (USEPA, 2004), the Agency relies on effects endpoints that are either direct measures
of impairment of survival, growth, or fecundity or endpoints for which there is a scientifically
robust, peer reviewed relationship that can quantify the impact of the measured effect endpoint
on the assessment endpoints of survival, growth, and fecundity.
2.10.3 Measures of Risk
Risk characterization is the integration of exposure and ecological effects characterization to
determine the potential ecological risk from agricultural and non-agricultural uses of alachlor,
and the likelihood of direct and indirect effects to CRLF and the DS in aquatic and terrestrial
habitats. The exposure and toxicity effects data are integrated in order to evaluate the risks of
adverse ecological effects on non-target species. For the assessment of alachlor risks, the risk
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quotient (RQ) method is used to compare exposure and measured toxicity values. EECs are
divided by acute and chronic toxicity values. The resulting RQs are then compared to the
Agency's levels of concern (LOCs) (USEPA, 2004) (see Appendix F).
For this endangered species assessment, listed species LOCs are used for comparing RQ values
for acute and chronic exposures of alachlor directly to the CRLF and the DS. If estimated
exposures directly to the assessed species of alachlor resulting from a particular use are sufficient
to exceed the listed species LOG, then the effects determination for that use is "may affect".
When considering indirect effects to the assessed species due to effects to prey, the listed species
LOCs are also used. If estimated exposures to the prey of the assessed species of alachlor
resulting from a particular use are sufficient to exceed the listed species LOG, then the effects
determination for that use is a "may affect." If the RQ being considered also exceeds the non-
listed species acute risk LOG, then the effects determination is a LAA. If the acute RQ is
between the listed species LOG and the non-listed acute risk species LOG, then further lines of
evidence (i.e. probability of individual effects, species sensitivity distributions) are considered in
distinguishing between a determination of NLAA and a LAA. If the RQ being considered for a
particular use exceeds the non-listed species LOG for plants, the effects determination is "may
affect". Further information on LOCs is provided in Appendix F.
3.0. Exposure Assessment
3.1 Aquatic Exposure Assessment
The assessment of exposure within the action area is dependent upon a combination of modeling
and monitoring data. In accordance with the Overview Document (USEPA, 2004), screening-
level exposures are based on modeling which assumes a static water body. Aquatic exposures
are quantitatively estimated for all of assessed uses using scenarios that represent high exposure
sites for alachlor use. Each of these sites represents a 10-hectare field that drains into a 1-hectare
pond that is 2 meters deep and has no outlet. Exposure estimates generated using the standard
pond are intended to represent a wide variety of vulnerable water bodies that occur at the top of
watersheds including prairie pot holes, playa lakes, wetlands, vernal pools, man-made and
natural ponds, and intermittent and first-order streams. As a group, there are factors that make
these water bodies more or less vulnerable than the standard surrogate pond. Static water bodies
that have larger ratios of drainage area to water body volume would be expected to have higher
peak EECs than the standard pond. These water bodies will be either shallower or have large
drainage areas (or both). Shallow water bodies tend to have limited additional storage capacity,
and, thus, tend to overflow and carry pesticide in the discharge whereas the standard pond has no
discharge. As watershed size increases beyond 10 hectares, at some point, it becomes unlikely
that the entire watershed is planted to a single crop, which is all treated with the pesticide.
Headwater streams can also have peak concentrations higher than the standard pond, but they
tend to persist for only short periods of time and are then carried downstream. More details on
the uncertainties associated with the various exposure assessments and modeling scenarios
specifically may be found in the Uncertainty Section (Section 6.1).
Specific management practices for all of the assessed uses of alachlor were used for modeling,
including application rates, number of applications per year, application intervals, and the first
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application date for each use. Incorporated and broadcast applications were modeled for all uses
to provide a range of expected EECs that are representative of actual management practices. The
broadcast application is expected to result in the highest EECs, because alachlor will be
contained to the upper horizons of the soil profile and can be easily transported to aquatic
resources via runoff. The general conceptual model of exposure for this assessment is that the
highest exposures are expected to occur in headwater streams adjacent to agricultural fields and
non-agricultural use sites (woody ornamentals). Many of the streams and rivers within the action
area defined for this assessment are in close proximity to both agricultural and non-agricultural
uses sites (for this assessment the action area represents the entire state of California).
Available usage data (USEPA, 2009) suggest that the heaviest usage of alachlor relative to the
action area is likely to be in the Central Valley, although these use rates are much less than the
use of alachlor in the Midwestern corn/sorghum belt. All existing PRZM scenarios were
evaluated, and a subset was selected for use in this assessment. The scenarios were selected to
provide a spatial context to predicted exposures.
Currently a suite of 28 PRZM California scenarios are available for use in ecological risk
assessments representing predominantly agricultural uses. Of these, 16 were developed
specifically for the CRLF assessments, 3 were developed for the Organophosphate (OP)
cumulative assessment (USEPA, 2006b), and 9 are standard scenarios. Each scenario is intended
to represent a high-end exposure setting for a particular use site. Scenario locations are selected
based on various factors including crop acreage, runoff and erosion potential, climate, and
agronomic practices. Once a location is selected, a scenario is developed using locally specific
soil, climatic, and agronomic data. Each PRZM scenario is assigned a specific climatic weather
station providing 30 years of daily weather values.
Specific scenarios were selected for use in this assessment using two criteria. First, an
evaluation of all available PRZM scenarios was conducted, and those scenarios that represent
alachlor uses (e.g., CA corn) were selected for modeling. Weather information was assigned to
these scenarios at development. Second, additional scenarios (CA Nursery and CA Residential)
were identified to represent the use of alachlor on woody ornamentals (juniper and yew) for
which a scenario within the action area is not available. These scenarios rely on climatic data
from San Diego (23188) and San Fransico (23234), respectively. Alachlor use on woody
ornamentals was modeled using both the nursery scenario and the residential scenario because
CDPR PUR data indicate that alachlor is used for landscapeing purposes, therefore residential
use cannot be eliminated from this assessment.
Residential use is a potentially important exposure pathway evaluated in this assessment. The
amount of impervious surfaces associated with the urban environment provides a potential direct
conduit in which alachlor-contaminated runoff can easily reach surface water resources.
Estimating the aquatic exposure from the use of alachor on woody ornamentals (juniper and
yew) for residential purposes involves the use of two scenarios, one for California residential turf
and one for California impervious surfaces. EECs are derived for both scenarios, and then
combined by assuming that 50% of the watershed is lawn (a fraction of which is actually planted
with woody ornamentals) and the remainder is impervious surface. It is also assumed that 1.68%
of the impervious surface gets over-sprayed during treatment of the ornamental plants. A detailed
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description of the rationale for these values is provided in Appendix G. Information from a
number of sources concluded that the usage on juniper and yew are mainly restricted to
decorative landscaping, shade, privacy (natural fencing), or foundation protection (Gillman et a/.,
2001; Starbuck, 2003). Therefore as a reasonable estimate for the percent lot treated was
approximately 1,638.4ft2 (0.038 acre, or 15% of a typical lot). This was derived assuming that
the entire perimeter of the 0.25 acre lot (104.4 ft length) of potentially treatable area was planted
with juniper or yew having a row width of approximately 4 ft based on plant phenology; for
modeling purposes, 100% of this 0.04 acre area was assumed to be treated with a broadcast spray
application.
Further description (metadata) and copies of the existing PRZM scenarios may be found at the
following websites.
http://www.epa.gov/oppefedl/models/water/index.htmtfprzmexamsshell
http://www.epa.gov/oppefedl/models/water/przmenvironmentdisclaim.htm
A summary of all the modeled scenarios along with associated weather information is included
in Table 3.1. Both the agricultural and non-agricultural scenarios were used within the standard
framework of PRZM/EXAMS modeling using the standard graphical user interface (GUI) shell,
PE5.pl. The models and GUI used in this assessment may be found at the following website:
http://www.epa.gov/oppefedl/models/water/index.htm
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Table 3.1. Summary of PRZM Scenarios.
Use
Corn
Sweet Corn
Sorghum
Legume Vegetables
(Soybeans, dry
beans, succulent
beans, lima beans)
Woody ornamentals
(Junipers and Yews)
Cotton
Sunflowers
Peanuts
Scenario
CAcornOP
CAcornOP
CAwheatRLF
CARowCropRLF_V2
CANurserySTD_V2
CA ResidentialRLF
CAcotton_WirrgSTD
CAcornOP
CARowCropRLF_V2
First
Application
March 1
(preplan:)
May 1
(30 d post
emergence)
January 2
(preplant)
Nov 20
(preplant)*
Dec 1**
(post transplant)
March 1
(preplant) 60d
prior to
emergence
March 1
(preplant)
Nov 20
(preplant)*
Min.
Application
Interval
NS
NS
NS
NS
21 days
NS
NS
NS
Weather Station
(WBAN #)
Sacramento
(23232)
Sacramento
(23232)
Fresno
(93193)
San Francisco
(23234)
San Diego
(23188)
San Francisco
(23234)
Fresno
(93193)
Sacramento
(23232)
San Francisco
(23234)
NS = Not specified on the federal label.
*Preplant application was modeled, assuming an initial application 6-8 weeks prior to emergence based on data from USDA-
NASS and the phenology of legumes (3 weeks from planting to emergence, and application was assume approximately 3 weeks
prior to planting). Initial application date was modeled on Nov. 20.
"Initial application date for woody ornamental use was modeled on December 1, a conservative estimate for timing of the initial
application. Timing of application was determined based on historical precipitation trends, modeling the time where precipitation
is greatest (Oct - Apr, peak Dec - end of Jan).
3.1.1. Model Inputs
The estimated concentrations from surface water sources were calculated using Tier II PRZM
(Pesticide Root Zone Model) and EXAMS (Exposure Analysis Modeling System). PRZM is
used to simulate pesticide transport as a result of runoff and erosion from a standardized
watershed, and EXAMS estimates environmental fate and transport of pesticides in surface
waters. The linkage program shell (PE5.pl) that incorporates the site-specific scenarios was used
to run these models.
Scenarios used in this assessment consist of four California-specific scenarios developed for uses
being assessed (corn, sorghum, legumes, cotton, and sunflowers), and two California-specific
scenarios as surrogate crops for an alachlor use (woody ornamentals). All scenarios were
modeled using local weather data selected to represent the highest rainfall potential in a region as
described above. Linked site-specific use scenarios and meteorological data were used to
estimate exposure as a result of specific use for each modeling scenario. The PRZM/EXAMS
model was used to calculate concentrations using the standard ecological water body scenario in
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EXAMS. Weather and agricultural practices were simulated over 30 years so that the l-in-10
year exceedance probability at the site was estimated for the standard ecological water body.
The date of initial application was developed based on several sources of information including
data provided by BEAD and Crop Profiles maintained by the USDA
(http://www.ipmcenters.org/cropprofiles/ and
http://usda.mannlib.cornell.edu/reports/nassr/field/planting/uph97.html). In general, the date of
initial application was selected to represent the most vulnerable window of exposure (e.g., timed
with highest expected precipitation). The application dates for alachlor in California from 2004
and 2005 (used as a representative sample) show that the majority of applications occur during
May, but applications can occur as early as January and as late as September (Figure 3.1).
APPLICATION DATES FOR ALACHLOR (CA PUR DATA - 2004 -
2005)
-ifin
140
(0
c
O190
15
° 100
Q.
Q.
<Ł> ^ ^ ^ ^ ^ ^ ^ ^ ^ ^
4fSf*tyS//WS*+**S/&/
Month/Year
Figure 3.1 Application Dates for Alachlor (CDPR PUR Data; 2004 - 2005)
The appropriate PRZM input parameters were selected from the environmental fate data
submitted by the registrant and in accordance with USEPA-OPP EFED water model parameter
selection guidelines, Guidance for Selecting Input Parameters in Modeling the Environmental
Fate and Transport of Pesticides, Version 2.3, February 28, 2002 (USEPA, 2002). These
parameters are consistent with those used in the 1998 RED (USEPA, 1998b) and subsequent risk
assessments (USEPA, 2006a) and are summarized in Table 3.2. More detail on these
assessments may be found at:
http://www.epa.gov/oppsrrdl/REDs/0063.pdf
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http://www.epa.gov/pesticides/cumulative/common_mech_groups.htm#chloro
Crop specific management practices that were used as inputs for PRZM/EXAMS are
summarized in Table 3.3, and all chemical properties and fate input parameters are summarized
in Table 3.4. All PRZM/EXAMS input and output files are included in Appendix H.
Table 3.2. Summary of Environmental Fate Data for Alachlor.
Fate Property
Molecular Weight
Vapor Pressure
Henry's Law Constant
Solubility in Water
Photolysis in Water
Aerobic Soil Metabolism Half -lives
Hydrolysis (25 °C)
Aerobic Aquatic Metabolism (water
column)
Anaerobic Aquatic Metabolism
(benthic)
Soil-water distribution coefficient
(Kd)
Value
269.77 g/mol
2.2 x 10 "5 torr
3.3xlO~8atm*m3/mol
240 mg/L (24°C)
Stable
29.7 d (silt loam)
34.0 d (loamy sand)
25.8 d (silt)
pH 5 - stable
pH 7 - stable
pH 9 - stable
84 d
Stable
0.33
MRID1 (or source)
MRID 146114
Beestman and Deming, 1974
Calculated
Beestman and Deming, 1974
MRID 230 12
MRID 134327
MRID 134327
Represents 2x the high-end
confidence bound on the mean
TTR aerobic soil metabolism
half-life.
Default
MRID 152209
Represents lowest reported
non-sand Kd
1 Master Record Identification (MRID) is record tracking system used within OPP to manage data submissions
to the Agency. Each data submission if given a unique MRID number for tracking purposes.
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Table 3.3. Summary of Management Practices for PRZM/EXAM Modeling Input
Parameters.
Corn
Sweet corn
Sorghum
Legumes
Woody
Ornamentals
Cotton
Sunflowers
Peanuts
Application
rate Ibs ai/A
(kg ai/ha)
4.0
4.0
4.0
3.0
4.0
2.0
4.0
4.0
Max No.
Applications
per year
2
1
2
1
2
1
4
2
Max.
Annual
Application
Rate Ibs
ai/A
4.0
4.0
4.0
3.0
4.0
2.0
4.0
4.0
Application
Interval
NA
NA
NA
NA
21
NA
NA
NA
Application
method
Ground
Ground
Ground
Ground
Ground
Ground
Ground
Ground
Broadcast /
Incorporation
depth
Broadcast &
incorporated
(10cm)
Broadcast &
incorporated
(10cm)
Broadcast &
incorporated
(10cm)
Broadcast &
incorporated
(10cm)
Broadcast
Broadcast &
incorporated
(4cm)
Broadcast &
incorporated
(4cm)
Broadcast &
incorporated
(10cm)
CAM
Input
1,4
2,4
1,4
1,4
2
1,4
1,4
1,4
Spray Drift
Efficiency
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
App.
Efficiency
0.99
0.99
0.99
0.99
0.99
0.99
0.99
0.99
NA = Not applicable, a single annual application was modeled.
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Table 3.4. Summary of PRZM/EXAMS Chemcial Input Parameters for Alachlor
Input Parameter
Molecular Mass (g/mol)
Vapor Pressure at 24°C (torr)
Henry's Law Constant
Solubility in Water at 24°C (mg/L)
Soil-water distribution coefficient
(Kd)
Aerobic Soil Metabolism Half-life (days)
Aerobic Aquatic Metabolism Half-life (days)
Anaerobic Aquatic Metabolism Half-life
(days)
Hydrolysis Half-lives (days)
Aqueous Photolysis
Half-life (days)
Value
269.77
2.2 xlO'5
3.3xlO'8
2400
0.33
34.3
42
84
0 (Stable)
0 (Stable)
0 (Stable)
Source
MRID146114
Beestman and Deming, 1974
Calculated
Represents lOx the measured water
solubility value (Beestman and
Deming, 1974)
Represents the lowest reported
non-sand Kd (MRID 152209)
Represents the high-end confidence
bound on the mean (MRID
134327)
Represents the high-end confidence
bound on the mean total toxic
residues half-life (MRID 134327)
Represents 2x the high-end
confidence bound on the mean
aerobic soil metabolism half-
life (MRID 134327). (USEPA,
2002)
None
Alachlor is stable to hydrolysis at
pH 5, 7, and 9 (MRID 134327)
therefore assumed to be 0 (US
EPA, 2002)
MRID 23012
* Post processing of residential scenario output assuming 5% of lot treated, 1% overspray as per guidance
3.1.2. Results
In general, these EECs show a pattern of exposure for all durations that is influenced by the
persistence of the compound and the lack of flow through the static water body. Predicted
alachlor concentrations, though high across durations of exposure for a single year, do not
increase across the 30-year time series; therefore, accumulation is not a concern. The resulting
EECs are summarized in Table 3.5. PRZM/EXAMS output files are included in Appendix H.
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Table 3.5. Aquatic Total Toxic Residue EECs (
Use Site
(application
method)
Corn (broadcast)
Corn (incorporated)
Sweet Corn
(broadcast)
Sweet Corn
(incorporated)
Sorghum
(broadcast)
Sorghum
(incorporated)
Soybeans
(broadcast)
Soybeans, dry
beans, lima beans
(incorporated)
Woody ornamentals
(Juniper and Yew)
Cotton (broadcast)
Cotton
(incorporated)
Sunflowers
(broadcast)
Sunflowers
(incorporated)
Peasnuts
(broadcast)
Peanuts
(incorporated)
Application
Rate (Ibs
a.i./acre)
4.0
4.0
4.0
4.0
4.0
4.0
3.0
3.0
4.0
(nursery use)
4.0
(residential use)
2.0
2.0
4.0
4.0
4.0
4.0
No. of
Applications
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
ug/L) for Alachlor Uses in California.
l-in-10 year
Peak EEC
44.8
12.6
11.3
3.2
46.7
12.8
32.9
9.3
56.0
6.3
25.2
15.3
44.8
27.3
43.9
12.4
l-in-10 year
21-day average
EEC
43.7
12.3
10.7
3.1
45.6
12.5
31.9
9.0
54.3
5.5
24.4
14.8
43.7
26.6
42.5
12.0
l-in-10 year
60-day average
EEC
41.1
11.5
9.8
2.8
42.7
11.7
27.1
7.7
43.0
4.6
22.8
13.8
41.1
25.0
36.2
10.2
3.1.3. Existing Monitoring Data
A critical step in the process of characterizing EECs is comparing the modeled estimates with
available surface water monitoring data. Included in this assessment are alachlor data from the
USGS National Water Quality Assessment (NAWQA) program (http://water.usgs.gov/nawqa)
focusing on the parent alachlor and three degradate products (alachlor-ESA, alachlor oxanilic
acid, and alachlor sulfynilacetic acid), and data from the CADPR that focused on the parent and
two degradates (alachlor-ESA and alachlor oxanilic acid). In addition, atmospheric monitoring
data for alachlor from the open literature are summarized below.
3.1.3.1. USGS NA WQA Surface Water Data
Data from the USGS NAWQA website for alachlor occurrence in surface water in California
were obtained on February 6, 2009. A total of 2,122 surface water samples were analyzed for
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alachlor spanning a period from 1992 to 2007. Of these, a total of 96 samples detected alachlor
-i
(frequency of detection of 4.5%). Detections ranged from 0.0025 to 0.86 jig L" (MDL ranged
from 0.002 to 0.005 jig L"1). Surface water detections generally occurred in the spring and early
summer months (March through July), which correlates to the maximum use period, according to
CA PUR data. The maximum concentration detected was 0.86 ppb from Stanislaus County in
1992. The three degradate products included in NAWQA (alachlor-ESA, alachlor oxanilic acid,
and alachlor sulfynilacetic acid) were infrequently detected, eight, once, and once, respectively.
These detections were not well correlated with detections of the parent alachlor. Detections of
alachlor-ESA ranged from 0.05-0.07 |ig L"1 (MDL = 0.02 |ig L"1); the detection of alachlor-OXA
was 0.06 jig L"1 (MDL = 0.02 jig L"1), and the detection of alachlor sulfynilacetic acid was 0.03
jig L"1 (MDL = 0.02 jig L"1). These degradates were included in previous assessments and were
found to be less toxic than the parent, therefore, they are not included in this assessment.
3.1.3.2. USGSNAWQA GroundwaterData
Data from the USGS NAWQA website for alachlor occurrence in groundwater in California
were obtained on February 6, 2009. A total of 747 groundwater samples were analyzed for
alachlor spanning a period from 1993 to 2006; there were no reported detections of alachlor
(MDL ranged from 0.002 to 0.005 |ig L"1).
3.1.3.3. California Department of Pesticide Regulation (CPR) Surface
Water Data
Data from the CDPR surface water monitoring database website for the occurrence of alachlor
and two major degradates (alachlor-ESA (ethane sulfonic acid), and alachlor OXA (oxanilic
acid)) were obtained on March 26, 2009. A total of 2,786 surface water samples were analyzed
for alachlor spanning a period from 1992 to 2006. Of these, a total of 69 samples detected
alachlor (detection frequency of 2.5%). Concentrations ranged from 0.003 to 0.86 jig L"1 (LOQa
ranged from 0.002 to 1 jig L"1). Consistent with NAWQA results, detections generally occurred
in the spring and early summer months (March through July), which correlates to the maximum
use period, according to CA PUR data. However, the majority of these data are included in the
NAWQA database; it is presented here to include state-level water quality monitoring. The
maximum concentration detected was 0.86 ppb in Stanislaus County in 1992. A total of 56
samples were analyzed for alachlor-ESA and alachlor-OXA, and only one detection was reported
for alachlor-ESA at 0.064 jig L"1 in Stantinslaus County.
3.1.3.4. Atmospheric Monitoring Data
Available monitoring data for alachlor in air and rainfall were evaluated from the open literature
to provide contextual information for the evaluation of the extent of the action area and estimated
concentrations in surface water. Alachlor may enter the atmosphere via volatilization and spray
drift and is subsequently aerially deposited, typically via wet deposition, or precipitated out on
sorbed particles. Based on the available information (Scheyer et a/., 2007; Kuang, et al, 2003;
Majewski etal., 2000; Foreman, etal, 1999; USGS, 1998; Goolsby etal., 1997; Gish etal.,
1995; Majewski and Capel, 1995; Capel et a/., 1994), alachlor has been detected in rainwater and
air samples across the United States and in France at variable frequency of detections. Often
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these studies are non-targeted to alachlor use and there is a lack of ancillary data in these studies
to determine whether these detections are due to spray drift or longer-range transport due to
volatilization. Alachlor has a relatively low Henry's law constant (3.3xlO"8) and high water
solubility (240 mg/L, Beestman and Deming, 1974). These physical properties have been shown
to favor enrichment in rainwater and preferentially fall out in the particle phase, thus, alachlor is
more efficiently deposited in precipitation (Scheyer et al., 2007). Scheyer et al. (2007) found
that there is a distinct seasonality attributed to the concentrations observed in rainwater at
medium to long distances from use sites (1-1000 km). This study was conducted as a targeted
monitoring study of volatilization of alachlor, and other compounds, from corn fields in eastern
France over a two-year period. The concentrations detected in the reviewed studies (generally
low, and studies were not conducted in California) suggest that atmospheric transport of alachlor
will yield exposures well below those predicted by modeling described above, but transport via
atmospheric processes may be an additional route of exposure for the CRLF and DS.
Specifically, alachlor concentrations in rainfall have been measured up to 6 |ig/L in France
(Scheyer et al., 1997). In 1990-1991, the 95th and 99th percentile alachlor levels in rainfall in the
mid-west were reported to be 0.26 and 0.95 |ig/L, respectively, with a maximum concentration
of 3.2 |ig/L (USGS, 1998; Goolsby etal., 1997). Goolsby et al. (1997) reported detections of
alachlor in approximately 20% of the rainwater samples at concentrations up to 3.2 |ig/L. Capel
et al. (1994) reported the frequency of detections and pesticide levels in rainfall from 1991 to
1993 in Minnesota; in 1991, alachlor was detected in 15 % of the samples with a maximum
concentration of 3.6 |ig/L, in 1992 it was 16 percent and 2.2 |ig/L, and in 1993 it was 74 % and
12 |ig/L. Subsequent 1994 monitoring data from 6 Minnesota sites around the state found
detections in 87% of the samples (range: 82 - 100%) and a maximum level of 1.15 jig/L (range
of maximum levels: 0.57 - 1.15 |ig/L). Further Gish et al. (1995) showed that herbicide
volatilization (alachlor and atrazine) was greater under mulched conditions (impregnated bulk
fertilizer application), but decreased dramatically after the first irrigation.
The data indicate that alachlor can enter the atmosphere via volatilization and spray drift. The
data also suggest that alachlor is frequently found in rain samples and tends to be seasonal,
related to application timing. Finally, the data suggest that although frequently detected, alachor
concentrations measured in rain samples are less than those seen in the open literature surface
water monitoring data (see below, Section 3.1.3.5). The modeling conducted as part of this
assessment support the contention that runoff and spray drift are the principal routes of exposure.
3.1.3.5. Summary of Open Literature Sources of Surface Water
Monitoring Data for Alachlor
Extensive reviews of both groundwater and surface water monitoring data have been previously
reported in the open literature. The 1998 Alachlor RED (USEPA, 1998b) and the Cumulative
Risk Assessment for the Chloroacetanilides (USEPA, 2006d) evaluated much of the monitoring
data on alachlor at a national scale through 2001 (summarized in Table 3.6). Due to label
revisions that occurred prior to RED issuance, maximum agricultural application rates were
reduced to 4 Ibs a.i./acre/yr. Alachlor use has also decreased as alternatives have become
available. Therefore, average annual alachlor concentrations recently monitored in surface water
and groundwater are not expected to exceed those measured before the label revisions took effect
Page 61 of 132
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in the late 1990s. Currently, few data are available after the mid-1990's, except NAWQA,
CDPR, and ARP which reported only very low concentrations for this time period. NAWQA
and CDPR surface water databases are generally non-targeted studies, and, therefore, do not
provide confirmatory data for label revisions. Also, the Acetechlor Reregi strati on Partnership
(ARP) study probably does not accurately capture the effect of label revisions on monitoring
concentration. Therefore, confirmatory data from targeted studies are not available. No trend
can be predicted for peak alachlor concentrations monitored in surface water and groundwater,
however, as monitoring data are not representative of peak exposure values. These monitoring
studies did not include study sites in California, therefore, it is difficult to compare the reported
results to expected exposure levels in California surface waters. However, these data provide
important contextual information on the occurrence of alachlor in surface waters, as many of
these studies are targeted studies examining the occurrence of alachlor in water resources in
relatively close proximity to use sites (e.g., ARP Surface Drinking water Supply Study).
Table 3.6. Summary of Alachlor Detections in Surface Water by Study as Included in the
1998 Alachlor RED and 2006 Chloroacetanilide Cumulative Risk Assessment.
Study
ARP Surface Drinking Water
Supply Study 1995-2001
USGS Midwestern Reservoir
Reconnaissance 1992
USGS Mississippi River Basin
Study 1991-1992
USGS Midwestern Stream
Reconnaissance 1989
State of Illinois 1986-1988
Lake Erie Basin Case Study 1983-
1987
Monsanto Finished Surface Water
Study 1986
Monsanto Finished Surface Water
Study 1985
Ohio Tributaries to Lake Erie
1982-1985
USGS Cedar River Basin Study
1984
Number of
Sites
152-175
76
8
48
30
7
30
30
8
6
Maximum Peak (jig/L)
4.65
~ 5 to 10
3.6
51.3
18
91.47
9.5
12
76
23
Maximum TWMC1
(Hg/L)
0.590
Not reported
0.43
11.6
0.81
1.74
1.1
1.5
3.32
1.7
1 TWMC means time weighted mean concentrations, annual unless otherwise noted.
2 Time weighted mean concentration calculated over a 4 month period of the study; Apr. 15 to Aug. 15.
One of the values from the available monitoring studies (i.e., 91.47 |ig/L, see Table 3.6) is
higher than the highest 1 -in-10-year peak EEC value from PRZM/EXAMS (see Section 3.1.2).
This value was detected in runoff coming from a small watershed, compared to other watersheds
in the study that was primarily dominated by agriculture. The study with the high value was
conducted before the maximum application rates for alachlor were reduced from 6 Ib a.i./acre to
4 Ib a.i./acre in the 1990's. An application rate of 6 Ibs a.i./acre was modeled for comparison
purposes using the CAnursery scenario. Modeling output showed peak concentrations that are
Page 62 of 132
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within a reasonable margin of error to the peak monitoring data (84 |ig/L compared to 91.5
|ig/L). Therefore, due to the reduced application rate the concentration cannot be used to reflect
potential concentrations from current use practices and is not quantitatively used in this risk
assessment.
3.1.4 Impact of Typical Usage Information on Exposure Estimates
A final piece of the exposure characterization includes an evaluation of usage information.
Label application information was provided by EPA's Biological and Economic Analysis
Division and was previously summarized in Table 2.8. This information suggests that alachlor
use on corn and beans (dry and succulent, the two highest uses in the CDPR PUR data) is (at
least sometimes) applied near the maximum label rate of 4.0 Ibs a.i./acre in California based on
CDPR PUR data. This shows that the modeling conducted for this assessment provides
reasonable exposure estimates, based on alachlor use patterns.
3.2. Terrestrial Animal Exposure Assessment
T-REX (Version 1.4.1) is used to calculate dietary and dose-based EECs of alachlor for birds
(surrogate for reptiles and terrestrial-phase amphibians), mammals, and terrestrial invertebrates.
T-REX simulates a 1-year time period. For this assessment, spray and impregnated dry bulk
fertilizer applications of alachlor are considered, as discussed below. Terrestrial EECs were
derived for the uses previously summarized in Table 2.7. Unlike aquatic exposure estimates that
represent total residues (parent plus degradates), terrestrial exposure estimates generated using T-
REX are for parent alone.
Upper-bound Kenaga nomogram values reported by T-REX are used for derivation of dietary
EECs for the terrestrial phase CRLF and their potential prey. When data are absent, as in this
case, EFED assumes a 35-day foliar dissipation half life, based on the work of Willis and
McDowell (1987). Because, for all of the alachlor uses modeled, the maximum single
application rate and the maximum yearly application rate are the same for each use, only a single
application (at the maximum application rate) was modeled, since this would result in the highest
EECs (as opposed to modeling two applications at lower application rates). Potential direct
acute and chronic effects of alachlor to the terrestrial-phase CRLF are initially derived by
considering oral exposures modeled in T-REX for a small bird (20g) consuming small
invertebrates. Potential impacts to mammalian prey base were evaluated in T-REX for a small
mammal (15 g) consuming short grass. Resulting dietary-based EECs (mg/kg-food) and dose-
adjusted EECs (mg/kg-bw) are summarized in Table 3.7.
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Table 3.7. Upper-bound Kenega Nomogram EECs for Dietary- and Dose-based Exposures
of the CRLF and its Prey to Alachlor.
Use(s)
Corn
Sweet corn
Grain
sorghum
Peanuts
Woody
ornamentals
Sunflowers
Soybeans
Dry beans-
Lima beans
(green)
Cotton
Application
Rate (Ib
a.i./acre)
4
o
J
2
EECs for CRLF
(small birds used as a
surrogate)
Dietary-
based EEC
(ppm)
540
405
270
Dose-based
EEC
(mg/kg-bw)
615
461
308
EECs for Prey
(small mammals)
Dietary-based
EEC (ppm)
960
720
480
Dose-based
EEC
(mg/kg-bw)
915
686
458
The impregnated bulk fertilizer applications (corn, sorghum, and soybeans) of alachlor are
treated as granular formulations for modeling purposes. Therefore, an LD50/ft2 analysis was
performed to evaluate potential risks to birds and mammals (for use in risk characterization).
The exposure used in this analysis is the mass of alachlor applied to a square foot area (mg/ft2).
Based on an application rate of 4 Ibs a.i./acre (maximum bulk fertilizer application rate), the
exposure value used in the LD50/ft2 analysis is 42 mg/ft2.
3.2.1. Potential Exposure to Terrestrial Invertebrates
T-REX is also used to calculate EECs for terrestrial invertebrates exposed to alachlor. Dietary-
based EECs calculated by T-REX for small and large insects (units of a.i./g) are used to bound
an estimate of exposure to honey bees (Apis melliferd) (used as a surrogate for terrestrial
invertebrates) (Table 3.8). Available acute contact toxicity data for bees exposed to alachlor (in
units of jig a.i./bee), are converted to jig a.i./g (of bee) by multiplying by 1 bee/0.128 g. The
EECs are compared to the acute contact toxicity data for bees in order to derive RQs.
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Table 3.8. EECs (ppm) for Indirect Effects to the Terrestrial-Phase CRLF via Effects to
Terrestrial Invertebrate Prey Items.
Use
Corn
Sweet corn
Grain sorghum
Peanuts
Woody ornamentals
Sunflowers
Soybeans
Dry beans-
Lima beans
Cotton
Application Rate
(Ib a.i./acre)
4
3
2
Small Insect
540
405
270
Large Insect
60
45
30
3.3 Terrestrial Plant Exposure Assessment
Terrestrial plants in riparian areas may be exposed to alachlor residues carried from application
sites via surface water runoff or spray drift. Exposures can occur directly to seedlings breaking
through the soil surface and through root uptake or direct deposition onto foliage to more mature
plants. Riparian vegetation is important to the water and stream quality of the assessed species
because it serves as a buffer and filters out sediment, nutrients, and contaminants before they
enter the watersheds associated with the assessed species' habitat. Riparian vegetation has been
shown to be essential in the maintenance of a stable stream (Rosgen, 1996). Destabilization of
the stream can have an adverse effect on habitat quality by increasing sedimentation within the
watershed.
Concentrations of alachlor on the riparian vegetation were estimated using OPP's TerrPlant
model (USEPA, 2006e; Version 1.2.2). The TerrPlant model evaluates exposure to plants via
runoff and spray drift and is EFED's standard tool for estimating exposure to non-target plants.
The runoff loading of TerrPlant is estimated based on the solubility of the chemical and
assumptions about the drainage and receiving areas.
Parameter values for application rate, drift assumption, and incorporation depth are based upon
the use and related application method (Table 3.9). A runoff value of 0.05 is utilized based on
alachlor's solubility, which is classified by TerrPlant as >100 mg/L. For ground flowable
application methods, drift is assumed to be 1% (aerial applications were not modeled due to label
restrictions for CA). For modeling purposes, the bulk fertilizer applications are treated as
granular applications (i.e.., no drift is assumed). EECs relevant to terrestrial plants consider
pesticide concentrations in drift and in runoff. These EECs are listed in Table 3.9. An example
output from TerrPlant v. 1.2.2 is available in Appendix I.
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Table 3.9. Screening-Level Exposure Estimates for Terrestrial Plants to Alachlor.
Use
Application rate
(Ibs a.i./A)
Spray drift
EEC
(Ibs a.i./A)
Dry area
EEC
(Ibs a.i./A)
Semi-aquatic
area EEC
(Ibs a.i./A)
Ground, Surface Applications1
Corn
Sweet corn
Grain sorghum
Sunflowers
Peanuts
Woody ornamentals
Soybeans
Cotton
4
o
J
2
0.04
0.03
0.02
0.24
0.18
0.12
2.04
1.53
1.02
Ground, Soil Incorporated (2 inches) Applications^
Corn
Sweet corn
Grain sorghum
Peanuts
Sunflowers
Soybeans
Dry beans
Lima beans
Cotton
4
o
J
2
0.04
0.03
0.02
0.14
0.105
0.07
1.04
0.78
0.52
Bulk Fertilizer Applications3
Corn
Sorghum
Soybeans
4
3
0
0
0.1
0.075
1
0.75
1 Surface applications are not allowed for the dry beans and lima beans uses.
2 Soil incorporated applications are not allowed for the woody ornamentals use
3 The bulk fertilizer applications are treated as granular applications for modeling purposes
For ground applications of alachlor, the highest off-target loadings of alachlor predicted by
TerrPlant are approximately 50% of the application rate for semi-aquatic areas adjacent to
application sites. As expected, resulting exposure estimates for terrestrial plants are higher for
surface than for soil incorporated applications.
4.0. Effects Assessment
This assessment evaluates the potential for alachlor to directly or indirectly affect the CRLF
and/or the DS or affect their designated critical habitat. As discussed in Section 2, assessment
endpoints for the assessed species include direct toxic effects on survival, reproduction, and
growth, as well as indirect effects, such as reduction of the prey base and/or effects to its habitat.
In addition, potential effects to critical habitat are assessed by evaluating potential effects to the
PCEs, which are components of the critical habitat areas that provide essential needs to the
species, such as water quality and food base (see Section 2.4).
Acute (short-term) and chronic (long-term) toxicity information is characterized based on
registrant-submitted studies and a comprehensive review of the open literature on alachlor,
Page 66 of 132
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consistent with the Overview Document (USEPA, 2004). Potential direct and indirect effects to
the CRLF and the DS and potential effects to critical habitat are evaluated in accordance with the
methods (both screening and species-specific refinements) described in the Agency's Overview
Document (USEPA, 2004).
Other sources of information, including use of the acute probit dose response relationships to
establish the probability of an individual effect and reviews of the Ecological Incident
Information System (EIIS), are conducted to further refine the characterization of potential
ecological effects associated with exposure to alachlor.
A summary of the available aquatic and terrestrial organism ecotoxicity information, use of the
probit dose-response relationship, and the incident information for alachlor are provided in the
following sections. A summary of the available data directly used in this assessment is
presented. A more comprehensive list of the available toxicity data is included in Appendix C
of this assessment.
4.1. Ecotoxicity Study Data Sources
Toxicity endpoints are established based on data generated from guideline studies submitted by
the registrant and from open literature studies that meet the criteria for inclusion into the
ECOTOX database maintained by EPA/Office of Research and Development (ORD) (USEPA,
2004). Open literature data presented in this assessment were obtained from the ecological
assessment for the sunflower and cotton uses (USEPA, 2006), as well as ECOTOX information
obtained in a query from December 2008. In order to be included in the ECOTOX database,
papers must meet the following minimum criteria:
• the toxic effects are related to single chemical exposure;
• the toxic effects are on an aquatic or terrestrial plant or animal species;
• there is a biological effect on live, whole organisms;
• a concurrent environmental chemical concentration/dose or application rate is reported;
and
• there is an explicit duration of exposure.
Meeting the minimum criteria for inclusion in ECOTOX does not necessarily mean that the data
are suitable for use in risk estimation. Data that pass the ECOTOX screen are evaluated along
with the registrant-submitted data, and may be incorporated qualitatively or quantitatively into
this endangered species risk assessment. In general, only effects data in the open literature that
are more conservative than the registrant-submitted data are considered. The degree to which
open literature data are quantitatively or qualitatively characterized is dependent on whether the
information is relevant to the assessment endpoints (i.e.., maintenance of survival, reproduction,
and growth; alteration of PCEs in the critical habitat impact analysis) identified in the problem
formulation. For example, endpoints such as biochemical modifications are not likely to be used
to calculate risk quotients unless it is possible to quantitatively link these endpoints with
reduction in survival, reproduction, or growth (e.g., the magnitude of effect on the biochemical
endpoint needed to result in effects on survival, growth, or reproduction is known). A summary
of all accepted open literature and a bibliography of all open literature considered as part of this
Page 67 of 132
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assessment regardless of whether the data were accepted or rejected by ECOTOX is included in
Appendix E.
As described in the Agency's Overview Document (USEPA, 2004), the most sensitive endpoint
for each taxon is used for RQ calculation. Tables 4.3 (aquatic organisms) and 4.4 (terrestrial
organisms) summarizes the most sensitive ecological toxicity endpoints for the CRLF and the
DS and their designated critical habitat based on an evaluation of both the submitted studies and
the open literature. Toxicity information used in this assessment is further described in the
following sections. Additional information on the available submitted and open literature
toxicity studies is provided in Appendices C and D.
4.2. Toxicity Categories
Toxicity to fish, aquatic invertebrates, birds, and mammals is categorized using the system
shown in Table 4.1 (USEPA, 2004). For non-target terrestrial insects, chemicals with LDso
values of <2, 2-11, and >11 jig/bee are classified as highly toxic, moderately toxic, and
practically nontoxic, respectively. Toxicity categories for terrestrial and aquatic plants have not
been defined.
Table 4.1. Categories of Acute Toxicity for Terrestrial and Aquatic Animals.
Toxicity Category
Very highly toxic
Highly toxic
Moderately toxic
Slightly toxic
Practically nontoxic
Aquatic Animals
[LC50/EC50 (mg/L)]
<0.1
0.1-1
> 1-10
> 10 - 100
>100
Birds and Mammals
[LD50 (mg/kg-bw)]
<10
10-50
51-500
501-2000
>2000
Birds
[LC50 (mg/kg-diet)]
<50
50 - 500
501 - 1000
1001 - 5000
>5000
4.3. Toxicity of Chemical Mixtures
As previously discussed in the problem formulation, the available toxicity data show that other
pesticides may combine with alachlor to produce synergistic, additive, and/or antagonistic toxic
interactions. The results of available toxicity data for mixtures of alachlor with other pesticides
are presented in Appendix A. If alachlor is present in the environment in combination with
other chemicals, the toxicity of the mixture may be increased relative to the toxicity of each
individual chemical, offset by other environmental factors, or even reduced by the presence of
antagonistic contaminants if they are also present in the mixture. The variety of chemical
interactions presented in the available data set suggest that the toxic effect of alachlor, in
combination with other pesticides used in the environment, can be a function of many factors
including but not necessarily limited to (1) the exposed species, (2) the co-contaminants in the
mixture, (3) the ratio of alachlor and co-contaminant concentrations, (4) differences in the
pattern and duration of exposure among contaminants, and (5) the differential effects of other
physical/chemical characteristics of the receiving waters (e.g. organic matter present in sediment
and suspended water). Quantitatively predicting the combined effects of all these variables on
mixture toxicity to any given taxon with confidence is beyond the capabilities of the available
data.
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4.4 Toxicity of Alachlor to Aquatic Organisms
Table 4.2 summarizes the most sensitive aquatic toxicity endpoints based on an evaluation of
both the submitted studies and the open literature, as previously discussed. A brief summary of
submitted and open literature data considered relevant to this ecological risk assessment for the
CRLF and DS is presented below. Additional information is provided in Appendix C.
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Table 4.2. Aquatic Toxicity Profile for Alachlor.
Assessment
Endpoint
Freshwater
fish (can be
used as a
surrogate for
aquatic-phase
amphibians)
Aquatic -phase
amphibian
Freshwater
invertebrates
Acute/
Chronic
Acute
Chronic
Acute
Chronic
Acute
Chronic
Species
Rainbow trout
(Oncorhynchus
mykiss)
Rainbow trout
(Oncorhynchus
mykiss)
African clawed
frog (Xenopus
laevis)
African clawed
frog (Xenopus
laevis)
Chironomid
(Chironomus
plumosus)
Chironomid
(Chironomus
plumosus)
Toxicity Value Used
in Risk Assessment
(mg a.i./L)
96-hr LC50= 1.8
NOAEC = 0.187
96-hr LC50 = 6.1
NOAEC = 0.64
48-hrEC50 = 2.5
NOAEC = 0.036
Slope (95%
C.I.)
4.51
Not
Applicable
(N/A)
4.51
N/A
4.51
N/A
MRID/
ECOTOX
Ref. No.
00023616
438626-01
E66376
(Osano etal.,
2002)
N/A
40098001
N/A
Comment
The study was
conducted using
TGAI2; this study is
classified as
'supplemental' (some
study parameters were
not reported) and
adequate for use in RQ
calculations
The study is classified
as 'acceptable' and was
conducted using TGAI;
the endpoints are based
on reduced growth
(length and wet
weight); LOAEC =
0. 388 mg a.i./L
The study was
conducted using TGAI ;
the study was non-
guideline (no guidelines
currently exist for an
amphibian acute
toxicity test) but
scientifically sound
This endpoint is based
on an ACR using acute
and chronic data from
Oncorhynchus mykiss
and acute data from
Xenopus laevis', the
Oncorhynchus mykiss
NOAEC was based on
reduced growth (see
text for details)
The study was
conducted using TGAI;
this study is classified
as 'supplemental'
because the raw data
were not available for
review
This endpoint is based
on an ACR using acute
and chronic data from
Daphnia magna and
acute data from
Chironomus plumosus',
the Daphnia NOAEC
was based on reduced
adult length (see text
Page 70 of 132
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Assessment
Endpoint
Estuarine/
marine fish
Estuarine/
marine
invertebrates
Aquatic plants
Acute/
Chronic
Acute
Chronic
Acute
Acute
Chronic
N/A
N/A
Species
Sheepshead
minnow
(Cyprinodon
variegates)
Sheepshead
minnow
(Cyprinodon
variegates)
Mysid
(Americamysis
bahia)
Eastern oyster
(Crassostrea
virginicd)
Copepod
(Tigriopus
japonicus)
Aquatic plant
(nonvascular)
(Selenastrum
capricornutum)
Aquatic plant
(vascular)
(Lemna gibba)
Toxicity Value Used
in Risk Assessment
(mg a.i./L)
96-hrLC50 = 3.9
NOAEC = 0.41
96-hr LC50 = 2.4
96-hr shell deposition
EC50 = 16
NOAEC < 0.0001
NOAEC = 0.00035
EC50 = 0.00 164
NOAEL = 0.000339
IC50 = 0.0023
Slope (95%
C.I.)
4.51
N/A
8.7
(5.1-12.4)
4.51
N/A
N/A
N/A
MRID/
ECOTOX
Ref. No.
445243-01
N/A
445243-02
445243-03
E104287 (Lee
et al. 2008)
427638-01
446497-02
Comment
for details)
The study is classified
as 'acceptable' and was
conducted using TGAI
This endpoint is based
on an ACR using acute
and chronic data from
Oncorhynchus mykiss
and acute data from
Cyprinodon variegates',
the Oncorhynchus
mykiss NOAEC was
based on reduced
growth (see text for
details)
The study is classified
as 'acceptable' and was
conducted using TGAI
The study is classified
as 'acceptable' and was
conducted using TGAI
The study was
conducted using TGAI
and is classified as
'supplemental'; a
definitive endpoint
could not be established
because effects
(increase in the
generation time for
adults in the F0 and FI
generations) were seen
at all of the cone.
tested; a non-native
species was used in the
study.
The study is classified
as 'acceptable' and was
conducted using TGAI;
the NOAEC was based
on reduced cell density
The study is classified
as 'acceptable' and was
conducted using TGAI;
the NOAEC was based
on % inhibition
1 A slope was not determined in the study, therefore, the default slope is used.
2 TGAI = Technical grade active ingredient
Page 71 of 132
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4.4.1 Toxicity to Fish
Fish toxicity data were used to evaluate potential direct effects to aquatic-phase CRLF and the
DS and indirect effects to the CRLF. A summary of acute and chronic fish and aquatic-phase
amphibian data, including data from the open literature, is provided in the following sections.
Additional information is included in Appendix C.
4.4.1.1. Acute Exposure (Mortality) Studies
Acceptable alachlor toxicity data are only available for a few fish species [rainbow trout
(Oncorhynchus mykiss), bluegill sunfish (Lepomis macrochirus), channel catfish (Ictalurus
punctatus) and sheepshead minnow (Cyprinodon variegates)}. LCso values are similar across
these species and range from 1.8 (rainbow trout) to 16.7 (channel catfish) mg a.i./L (see
Appendix C for additional details on these studies). Therefore, alachlor is classified as slightly
to moderately toxic to fish on an acute exposure basis.
For the CRLF, the most sensitive freshwater fish species is used as a surrogate to help
characterize the potential risk to aquatic-phase CRLF. For the DS, the most sensitive species
among the freshwater and estuarine/marine fish species tested is used to calculate risk quotients
regardless of the salinity environment because the DS enters both freshwater and saltwater
environments. More sensitive acceptable acute LCso values for fish were not located in the open
literature. Therefore, the lowest LCso of 1.8 mg a.i./L reported for rainbow trout (MRID
00023616), is used for risk quotient calculations for the CRLF and DS. The LCso value from the
only available acute toxicity study with an estuarine/marine fish [i.e., 3.9 mg a.i./L for
sheepshead minnow (MRID 445243-01)] will be used to help characterize the risk of alachlor
use to DS in saltwater environments.
4.4.1.2. Chronic Exposure (Growth/Reproduction) Studies
Chronic fish toxicity studies are used to assess potential direct effects to the DS (freshwater and
estuarine/marine fish) and aquatic-phase CRLFs (freshwater fish) via potential effects to growth
and reproduction. For fish, considering both registrant-submitted and open literature studies,
there is only one acceptable chronic study available for alachlor [an early life-stage study with
rainbow trout) (MRID 438626-01)]. In this study, length and wet weight were reduced by 3%
and 11%, respectively, at the 0.388 mg a.i./L concentration. Additionally, there was reduced
posthatch survival, increased rates of exopthalmia (abnormal bulging of the eyes), and a 3-day
delay in time to swim-up of larvae at the 1.63 mg a.i./L concentration. The corresponding
NOAEC for this study is 0.187 mg a.i./L.
Chronic data for estuarine/marine fish and alachlor are not available. To help characterize the
risk to DS in saltwater environments, an acute to chronic ratio (ACR) using acute and chronic
data from rainbow trout and acute data from sheepshead minnow is used to estimate a chronic
endpoint for estuarine/marine fish. This results in a sheepshead minnow NOAEC of 0.41 mg
a.i./L (rainbow trout LCso = 1.8 mg a.i./L; rainbow trout NOAEC = 0.187 mg a.i./L; sheepshead
minnow LC50 = 3.9 mg a.i./L; rainbow trout ACR = 1.8/0.187 = 9.6; 3.9/9.6 = 0.406).
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4.4.2. Toxicity to Amphibians
Acute toxicity data for alachlor and aquatic-phase amphibians are available from two studies in
the open literature. In the first study, the 96-hr LC50 value for African clawed frog (Xenopus
larvis) embryos (midblastula to early gastrula stages) exposed to technical grade alachlor was 6.1
mg a.i./L (E66376, Osano etal., 2002). Sublethal effects, including edema, axial flexure, and
gut and eye abnormalities, were also reported in this study (96-hr ECso = 3.6 mg a.i./L).
In an additional study involving fire-bellied toad (Bombina orientalis) embryos (newly
fertilized), a 96-hr LC50 value was not determined (E81388, Kang et al, 2005). After a 96-hr
exposure to technical grade alachlor, however, there was 52.7% mortality of the embryos at a
concentration of 2.7 mg a.i./L. Additionally, various embryonic abnormalities (including
abnormalities associated with the neural plate, tail bud, muscle repose, tail fin circulation,
operculum, and bastula) occurred at 1.4 mg a.i./L and/or higher concentrations.
In a study using leopard frog (Ranapipiens) larvae, the effects of alachlor alone (at a
concentration of 0.1 jig a.i./L) and in a mixture of nine chemicals (0.1 jig a.i./L of each chemical
and 10 jig a.i./L of each chemical) was investigated (E85815, Hayes etal., 2006). The nine
pesticide mixture (4 herbicides: atrazine, metolachlor, alachlor, and nicosulfuron; 3 insecticides:
cyfluthrin, cyhalothrin, and tebupirimphos; and 2 fungicides: methalaxyl and propiconizole) was
meant to represent a potential environmentally relevant mixture. At the concentrations tested,
alachlor alone had no impact on the measured endpoints. However, the mixtures containing
alachlor (0.1 jig a.i./L of each chemical) did impact some of the measured endpoints (e.g.,
mortality, time to metamorphosis, and size at metamorphosis). All of the animals exposed to the
9-compound mixture at 10 ppb died after the first day of exposure.
Because the mortality endpoint for freshwater fish is lower than the mortality endpoints in the
amphibian studies, the acute freshwater fish endpoint will be used to calculate risk quotients for
aquatic-phase CRLF and the amphibian data will be used to help characterize risks to CRLF
from acute exposure to alachlor. No chronic toxicity data are currently available for amphibians
and alachlor, therefore, the chronic endpoint for freshwater fish will be used to calculate risk
quotients for aquatic-phase CRLF.
Although chronic data are not available for frogs, an ACR (9.6) using acute and chronic data
from rainbow trout and acute data from the African clawed frog is used to estimate a chronic
endpoint for amphibians to help characterize risk to aquatic-phase CRLF. This results in an
African clawed frog NOAEC of 0.64 mg a.i./L (rainbow trout LCso =1.8 mg a.i./L; rainbow
trout NOAEC = 0.187 mg a.i./L; African clawed frog LCso = 6.1 mg a.i./L; rainbow trout ACR =
1.8/0.187 = 9.6; 6.1/9.6 = 0.64).
4.4.3 Toxicity to Aquatic Invertebrates
Aquatic invertebrate toxicity studies are used to assess potential indirect effects to the DS and the
CRLF. A summary of acute and chronic freshwater invertebrate data, including data published
in the open literature, is provided below in the following Sections.
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4.4.3.1. Acute Studies
Aquatic invertebrate toxicity data are used to evaluate potential indirect effects to the CRLF and
the DS because each assessed species depends on aquatic invertebrates for food. For the indirect
effects assessment, the most sensitive aquatic invertebrate species is initially used for risk
estimation, which is consistent with USEPA (2004). The most sensitive aquatic invertebrate
tested is the Eastern oyster (Crassostrea virginicd) (96-hr shell deposition ECso =1.6 mg a.i./L)
(MRID 445243-03). Other freshwater and estuarine/marine invertebrates have similar sensitivity
to alachlor when compared to the Eastern oyster. The 48-hr LCso for the freshwater midge
(Chironomus plumosus) is 2.5 mg a.i./L (MRID 40098001) while the 96-hr LC50 for the
estauarine/marine mysid (Americamysis bahid) is 2.4 mg a.i./L (MRID 445243-02). Therefore,
alachlor is classified as moderately toxic to aquatic invertebrates.
The most important food organism for all sizes of the Delta smelt has been reported to be the
copepod Eurytemora affinis (USFWS, 1995 and 2004), which is a marine copepod.
Supplemental toxicity data are available from the open literature for a non-native copepod,
Tigriopus japonicus (Lee et a/., 2008). In this study, conducted with technical grade alachlor,
the 96-hr LCso value was 7.3 mg a.i./L.
4.4.3.2. Chronic Exposure Studies
Toxicity data from chronic exposure to alachlor are available for one freshwater [daphnid
(Daphnia magna)] and one estuarine/marine invertebrate species [copepod (Tigriopus
japonicus)]. The daphnid study, conducted with technical grade alachlor, resulted in a NOAEC
of 0.11 mg a.i./L based on reduced adult length (MRID 437747-07). There was also reduced egg
production and reduced adult survival at concentrations of 0.45 mg a.i./L and 1.7 mg a.i./L,
respectively. The LOAEC for this study was 0.23 mg a.i./L.
A definitive NOAEC or LOAEC could not be determined in the copepod study because
reproductive effects (i.e., an increase in the generation time for adults in the FO and FI
generations) were seen in all of the concentrations tested (E104287, Lee et a/., 2008). The
lowest concentration tested in the study was 0.0001 mg a.i./L (0.1 jig a.i./L). Therefore, the
resulting NOAEC and LOAEC values were <0.0001 mg a.i./L.
4.4.4 Toxicity to Aquatic Plants
Aquatic plant toxicity studies are used as one of the measures of effect to evaluate whether
alachlor may affect primary production. Aquatic plants may also serve as dietary items of
aquatic-phase CRLFs. In addition, freshwater vascular and non-vascular plant data are used to
evaluate a number of the PCEs associated with the critical habitat impact analysis.
Alachlor is toxic to the freshwater green alga (Pseudokirchneriella subcapitata, formerly
Selenastrum capricornutum), with a 120-hr ECso of 0.00164 mg a.i./L (1.64 jig ai/L) and a
NOAEC of 0.00035 mg a.i./L (0.35 |ig ai/L), based on reduced cell density (MRID 427638-01).
The aquatic vascular plant tested, duckweed (Lemna gibba), is almost as sensitive to alachlor as
the freshwater green alga [i.e., EC50= 0.0023 mg a.i./L (2.3 |ig ai/L); NOAEC = 0.000339 mg
Page 74 of 132
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a.i./L (0.339 |ig ai/L); based on percent inhibition] (MRID 446497-02). The other aquatic plants
tested are less sensitive to alachlor when compared to P. subcapitata and duckweed [i.e., the
freshwater diatom, Naviculapelliculosa, has an ECso value of 2.63 mg ai/L (MRID 446497-04);
the marine diatom, Skeletonema costatum, has an ECso value of 0.21 mg a.i./L (MRID 446497-
03); and the cyanobacteria, Anabaenaflos-aquae., has an ECso value of >19 mg ai/L (446497-
01)].
4.5 Toxicity of Alachlor to Terrestrial Organisms
Table 4.3 summarizes the most sensitive terrestrial toxicity endpoints based on an evaluation of
both the submitted studies and the open literature. A brief summary of submitted and open
literature data considered relevant to this ecological risk assessment for the CRLF and DS is
presented below. Additional information is provided in Appendix C.
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Table 4.3. Terrestrial Toxicity Profile for Alachlor.
Assessment
Endpoint
Bird (used as a
surrogate for
terrestrial-
phase
amphibians)
Mammal
Terrestrial
invertebrate
Terrestrial
plants
Acute/
Chronic
Acute
Sub-chronic
Chronic
Acute
Chronic
Acute
(Contact)
N/A
(Vegetative
vigor)
N/A
(^^•rllino
emergence)
Species
Bobwhite quail
(Colinus
virginianus)
Bobwhite quail
(Colinus
virginianus)
Mallard duck
(Anas
platyrhynchos)
Norway rat (Rattus
norvegicus)
Sprague Dawley
rat
Honey bee (Apis
mellifera)
Monocot
(Rye grass -
endpoint based on
reduced dry
weight)
Dicot (Cucumber-
endpoint based on
weight)
Monocot
(Rye grass -
endpoint based on
reduced dry
weight)
Dicot
(Lettuce -
endpoint based on
phytotoxicity)
Toxicity Value
Used in Risk
Assessment
LD50 = 1499 mg
LC50 = >5620 mg
a.i./kg-diet
NOAEC = <50 mg
a.i./kg-diet
LD50 = 930 mg/kg-
bw
NOAEC = 30
mg/kg-diet
LD50 >36.3 uga.i.
/bee
EC25 = 0.068 Ib
a.i./acre
NOAEL = 0.037 Ib
a.i./acre
PP — 1 4 1h
NOAEL = 0.67 Ib
a.i./acre
EC25 = 0.0067 Ib
a.i./acre
NOAEL - 0.0023 Ib
a.i./acre
EC25 = 0.034 Ib
a.i./acre
NOAEL- 0.019 Ib
a.i./acre
Slope (95%
C.I.)
4.51
Not
Applicable
(N/A)
N/A
4.51
N/A
4.51
N/A
N/A
N/A
N/A
MRID/
ECOTOX Ref.
No.
00079523
430871-01
449515-01
00139383
00075062
00028772
(Atkins et al.
1973)
424686-01
494687 01
Comment
The study is classified as
'acceptable' and was conducted
using TGAI
The study is classified as
'acceptable' and was conducted
using TGAI; there were no
mortalities during the study
The study is classified as
'supplemental' and was
conducted using TGAI; there
were significant reductions in
hatchling weight at all
concentrations tested
The study is classified as
'acceptable' and was conducted
using TGAI
The study is classified as
'acceptable' and was conducted
using TGAI; there were no
reproductive effects at the
highest dose tested (30 mg/kg-
diet); LOAEL = >30 mg/kg-
diet
The study is classified as
'supplemental' since it was
conducted using a formulation
(Lasso®, 45% a.i.) rather than
TGAI; there was only 0.41%
mortality at the highest
treatment level
The study is classified as
'supplemental'; no solvent
control was included in the
study; TGAI was used instead
ofaTEP
The study is classified as
'supplemental'; no solvent
study; TGAI was used instead
ofaTEP
A slope was not determined in the study, therefore, the default slope is used.
Page 76 of 132
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4.5.1 Toxicity to Birds and Terrestrial Phase Amphibians
As specified in the Overview Document, the Agency uses birds as a surrogate for terrestrial-
phase amphibians when sufficient toxicity data for each specific taxonomic group are not
available (USEPA, 2004).
4.5.1.1. Birds: Acute andSubacute Exposure (Mortality) Studies
The available data indicate that alachlor is slightly to practically nontoxic to avian species on an
acute oral exposure basis; a study with bobwhite quail (Colinus virginianus) resulted in an LD50
value of 1,499 mg ai/kg-bw (MRID 00079523). Alachlor is also practically nontoxic to
bobwhite quail and mallard duck (Anasplatyrhynchos) on a subacute dietary exposure basis
(LC50>5620 mg ai/kg-diet; MRIDs 43087001, 43087101). There were no mortalities attributed
to treatment in the subacute dietary studies.
4.5.1.2. Birds: Chronic Exposure (Growth, Reproduction) Studies
An avian reproduction study with the bobwhite quail (MRID 449515-02) resulted in aNOAEC
of 50 mg a.i./kg-diet, based on decreased mean hatchling weight (9% reduction at the 150 mg
a.i./kg-diet concentration). Mean hatchling weight was also reduced in a reproduction study with
mallard ducks. In the mallard duck study (MRID 449515-01), mean hatchling weight was
decreased at all of the concentrations tested (range = 5.5% to 19% reduction) (NOAECX50 mg
a.i./kg-diet); therefore, a NOAEC has not been established for avian species or species for which
they are surrogates. In the mallard duck study there was also a statistically significant reduction
in egg production, embryo viability and hatchability at the 1,000 mg a.i./kg-diet concentration.
4.5.1.3. Toxicity to Reptiles and Terrestrial Phase Amphibians
No data are currently available for the effects of alachlor on reptiles or terrestrial-phase
amphibians.
4.5.2 Toxicity to Mammals
4.5.2.1. Mammals: Acute Exposure (Mortality) Studies
Alachlor is slightly toxic to mammals on an acute oral exposure basis. An acute oral study with
Norway rats (Rattus norvegicus) resulted in an LDso value of 930 mg a.i./kg-bw (MRID
00139383). Additional information can be found in Appendix J.
4.5.2.2. Reproduction Toxicity in Mammals
In a 3-generation reproduction study (MRID 00075062) technical grade alachlor was
administered to Charles River Sprague-Dawley rats (R. norvegicus) in the diet at concentrations
of 0, 3, 10, and 30 mg a.i./kg-diet. Each generation was mated twice during the study. No
effects on reproductive parameters were observed. Therefore, the reproductive toxicity NOAEC
is 30 mg/kg-diet and a LOAEC for reproductive effects was not established in the study. There
Page 77 of 132
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were some systemic effects at 30 mg/kg-diet [kidney discoloration and decreased kidney weights
and lower ovary weights in females of each parental generation and the F3 females (maximal
decrease of 17%)]. Therefore, the systemic toxicity LOAEC in this study was 30 mg/kg-diet.
4.5.3 Toxicity to Terrestrial Invertebrates
Terrestrial invertebrate toxicity data are used to evaluate potential indirect effects to the CRLF
and to adversely modify designated critical habitat. A summary of the available terrestrial insect
data is provided below. Additional details on the data are included in Appendix C.
Alachlor is considered practically nontoxic to honey bees (Apis melliferd) on an acute contact
exposure basis (MRID 00028772). In this study, adult bees were exposed to a formulated
product (Lasso®, 45% active ingredient) at concentrations up to 36.3 jig a.i./bee. At the highest
concentration tested, 0.41% of the bees died. This study is classified as supplemental because it
was not conducted using technical grade alachlor. Therefore, the LDso value for alachlor and
honey bees is >36.3 jig a.i./bee.
4.5.4 Toxicity to Terrestrial Plants
Terrestrial plant toxicity data are used to evaluate the potential for alachlor to affect the riparian
zone of occupied water bodies and critical habitat. Riparian zone effects could impact habitat
and stream water quality as discussed in detail in Section 5.2.
Plant toxicity data from both registrant-submitted studies and studies in the scientific literature
were reviewed for this assessment. Registrant-submitted studies are conducted under conditions
and with species defined in EPA toxicity test guidelines. Sub-lethal endpoints such as plant
growth, dry weight, and biomass are evaluated for both monocots and dicots, and evaluate
effects at both seedling emergence and vegetative life stages. A guideline study generally
evaluates toxicity to ten crop species. A drawback to these studies is that they are conducted on
herbaceous agricultural crop species only, and extrapolation of effects to other species, such as
woody shrubs, trees, and wild herbaceous species contributes uncertainty to risk conclusions.
Commercial crop species have been selectively bred, and may be more or less resistant to
particular stressors than wild herbs and forbs. The direction of this uncertainty for specific plants
and stressors, including alachlor, is largely unknown. Homogenous test plant seed lots also lack
the genetic variation that occurs in natural populations, so the range of effects seen from tests is
likely to be smaller than would be expected from wild populations.
Two terrestrial plant studies with alachlor have been submitted to the Agency: a seedling
emergence study (MRID 424687-01) and a vegetative vigor study (MRID 424686-01). Both
studies are scientifically sound but do not meet the requirements for Tier 2 seedling emergence
or vegetative vigor tests using non-target plants. The report did not state if the control pots were
treated with a 75% acetone, 25% deionized water solution for the emergence test or a 1%
acetone/deionized water solution for the vegetative vigor test. Additionally, only one parameter
was monitored during the vegetative vigor study and the NOAELs for height and weight for
cabbage were not determined for the emergence study. The Ł€25 values for onion height and
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tomato dry weight were not determined for the emergence study. These studies are classified as
'supplemental'.
Based on the results of the submitted terrestrial plant toxicity studies, alachlor is phytotoxic to
many plant species. The herbicide reduces plant height, weight and survival. Annual rye grass
(Lolium perenne), a monocotyledonous species, was the most sensitive species in both the
vegetative vigor and seedling emergence studies. In the seedling emergence study, the EC25 was
0.0067 Ib a.i./acre (NOAEL= 0.0023 Ib a.i./acre) based on biomass reduction. In the vegetative
vigor study, the Ł€25 was 0.068 Ib a.i./acre (NOAEL=0.037 Ib a.i./acre) based on biomass
reduction. The most sensitive dicot in the seedling emergence study was lettuce (Lactuca saliva)
based on phytotoxicity, with an Ł€25 of 0.034 Ibs a.i./acre and a NOAEC of 0.019 Ibs a.i./acre.
The most sensitive dicot in the vegetative vigor study was cucumber (Cucumis sativus) based on
biomass reduction, with an Ł€25 of 1.4 Ibs a.i./acre and a NOAEC of 0.67 Ibs a.i./acre.
Based on the results of the submitted terrestrial plant toxicity tests, it appears that emerged
seedlings are more sensitive to alachlor via soil/root uptake exposure than emerged plants via
foliar routes of exposure. However, all tested plants, with the exception of soybeans (Glycine
max) in the seedling emergence study, exhibited adverse effects following exposure to alachlor.
4.6. Use of Probit Slope Response Relationship to Provide Information on the
Endangered Species Levels of Concern
The Agency uses the probit dose-response relationship as a tool for providing additional
information on the potential for acute direct effects to individual listed species and aquatic
animals that may indirectly affect the listed species of concern (USEPA, 2004). As part of the
risk characterization, an interpretation of acute RQs for listed species is discussed. This
interpretation is presented in terms of the chance of an individual event (i.e., mortality or
immobilization) should exposure at the EEC actually occur for a species with sensitivity to
alachlor on par with the acute toxicity endpoint selected for RQ calculation. To accomplish this
interpretation, the Agency uses the slope of the dose response relationship available from the
toxicity study used to establish the acute toxicity measures of effect for each taxonomic group
that is relevant to this assessment. The individual effects probability associated with the acute
RQ is based on the mean estimate of the slope and an assumption of a probit dose response
relationship. In addition to a single effects probability estimate based on the mean, upper and
lower estimates of the effects probability are also provided to account for variance in the slope, if
available.
Individual effect probabilities are calculated based on an Excel spreadsheet tool IECV1.1
(Individual Effect Chance Model Version 1.1) developed by the USEPA, OPP, Environmental
Fate and Effects Division (June 22, 2004). The model allows for such calculations by entering
the mean slope estimate (and the 95% confidence bounds of that estimate) as the slope parameter
for the spreadsheet. In addition, the acute RQ is entered as the desired threshold.
For the acute toxicity endpoints used in this assessment, the only study that allowed for the
determination of a slope was the estauarine/marine invertebrate (mysid) study (MRID 445243-
02). This study resulted in a slope of 8.7 (95% C.I. = 5.1 - 12.4). For the remaining taxa, the
Page 79 of 132
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default slope is used to estimate individual effect probabilities [i.e., slope = 4.5 (95% C.I. = 2 -
9)].
4.7 Incident Database Review
A review of the EIIS database for ecological incidents involving alachlor was completed in
January 2009. Based on the EIIS database, there have been a total of 43 reported ecological
incidents potentially involving alachlor (9 involving aquatic animals and 34 involving terrestrial
plants). These incidents are summarized below. A more complete list of the incidents involving
alachlor is included as Appendix K.
The nine reported alachlor aquatic animal incidents occurred between 1983 and 1995 and
involved from an 'unknown' number of dead freshwater fish to 'thousands'. The legality of use
was undetermined in four of the incidents; involved a misuse in three incidents (two intentional
and one accidental); and involved a registered use in two incidents. Other chemicals besides
alachlor, including other herbicides and/or insecticides, were involved in all but one of the
reported incidents involving aquatic animals. The certainty that alachlor was responsible for the
fish deaths ranged from 'unlikely' (two incidents) to 'possible' (four incidents) to 'highly
probable' (three incidents).
The 34 reported alachlor terrestrial plant incidents occurred between 1991 and 2002 and
involved from an 'unknown' number of impacted acres to 1,792 acres. The legality of use was
undetermined in seven of the incidents; involved an accidental misuse in four incidents; and
involved a registered alachlor use in 23 incidents. Other herbicides besides alachlor were
involved in all but 11 of the reported incidents involving terrestrial plants (i.e., 11 of the
incidents involved only alachlor and no other chemicals). The certainty that alachlor was
responsible for the plant damage ranged from 'possible' (28 incidents) to 'probable' (six
incidents).
5.0 Risk Characterization
Risk characterization is the integration of the exposure and effects characterizations. Risk
characterization is used to determine the potential for direct and/or indirect effects to the CRLF
and the DS or modification to their designated critical habitat from the use of alachlor. The risk
characterization provides an estimation (Section 5.1) and a description (Section 5.2) of the
likelihood of adverse effects; articulates risk assessment assumptions, limitations, and
uncertainties; and synthesizes an overall conclusion regarding the likelihood of adverse effects to
the assessed species or their designated critical habitat (i.e., "no effect," "likely to adversely
affect," or "may affect, but not likely to adversely affect").
5.1 Risk Estimation
Risk is estimated by calculating the ratio of the estimated environmental concentration (EEC)
(from PRZM/EXAMS for aquatic organisms, T-REX for terrestrial animals, and TerrPlant for
terrestrial plants) (Section 3) and the appropriate toxicity endpoint (Section 4). This ratio is the
Page 80 of 132
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risk quotient (RQ), which is then compared to pre-established acute and chronic levels of
concern (LOCs) for each category evaluated (Appendix F).
In cases where the baseline RQ exceeds one or more LOG (i.e., "may affect"), additional factors,
including the life history characteristics of the assessed species, refinement of the baseline EECs
using site-specific information, and available monitoring data are considered and used to
characterize the potential for alachlor to adversely affect the assessed species and/or their
designated critical habitat. Risk quotients used to evaluate potential direct and indirect effects to
the CRLF and DS and to designated critical habitat are in Sections 5.1.1 (direct effects) and 5.1.2
(indirect effects). RQs are described and interpreted in the context of an effects determination in
Section 5.2 (risk description).
5.1.1 Direct Effects RQs
The species considered in this risk assessment include a frog and a fish species. Direct effects to
the DS are evaluated using the lowest acute and chronic toxicity values across freshwater and
saltwater fish species. Direct effects to the aquatic phase CRLF are evaluated using the lowest
freshwater acute and chronic toxicity values across fish and amphibian toxicity studies.
However, fish were consistently shown to be more sensitive than aquatic-phase amphibians and
the available amphibian studies are classified as 'supplemental'; therefore, fish acute and chronic
toxicity values are used to calculate RQs for aquatic-phase amphibians. Direct effects to
terrestrial-phase CRLFs are evaluated using the lowest acute and chronic toxicity values for birds
exposed to alachlor (since no terrestrial-phase amphibian toxicity data were available for
alachlor). Toxicity values used to calculate RQs are discussed in Section 4, and exposure values
are discussed in Section 3. RQs used to estimate acute and chronic direct effects are in Tables
5.1 (DS and aquatic-phase CRLF) and 5.2 (terrestrial-phase CRLF).
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Table 5.1. Summary of Aquatic RQs Used to Estimate Direct Effects to Aquatic-Phase
CRLF and the DS1
Use Site
Corn (broadcast)
Corn (incorporated)
Sweet corn (broadcast)
Sweet corn (incorporated)
Sorghum (broadcast)
Sorghum (incorporated)
Soybeans (broadcast)
Soybeans, dry beans, lima beans
(incorporated)
Woody ornamentals (nursery-use)
Woody ornamentals (residential use)
Cotton (broadcast)
Cotton (incorporated)
Sunflowers (broadcast)
Sunflowers (incorporated)
Peanuts (broadcast)
Peanuts (incorporated)
Exposure
Type
Acute
Chronic
Acute
Chronic
Acute
Chronic
Acute
Chronic
Acute
Chronic
Acute
Chronic
Acute
Chronic
Acute
Chronic
Acute
Chronic
Acute
Chronic
Acute
Chronic
Acute
Chronic
Acute
Chronic
Acute
Chronic
Acute
Chronic
Acute
Chronic
EEC
Peak = 44.8 ug/L
60-day = 4 1.1 ug/L
Peak = 12.6 ug/L
60-day = 11.5 ug/L
Peak= 11.3 ug/L
60-day = 9.8 ug/L
Peak = 3.2 ug/L
60-day = 2.8 ug/L
Peak = 46.7ug/L
60-day = 42.7 ug/L
Peak = 12.8 ug/L
60-day = 11.7 ug/L
Peak = 32.9 ug/L
60-day = 27.1 ug/L
Peak = 9.3 ug/L
60-day = 7.7 ug/L
Peak = 56.0 ug/L
60-day = 43.0 ug/L
Peak = 6.3 ug/L
60-day = 4.6 ug/L
Peak = 25. 2 ug/L
60-day = 22.8 ug/L
Peak= 15.3 ug/L
60-day =13.8 ug/L
Peak = 44.8 ug/L
60-day = 4 1.1 ug/L
Peak = 27.3 ug/L
60-day = 25.0 ug/L
Peak= 43.9 ug/L
60-day = 36.2 ug/L
Peak = 12.4 ug/L
60-day = 10.2 ug/L
RQ
0.02
0.22
0.01
0.06
0.01
0.05
0.002
0.01
0.03
0.23
0.01
0.06
0.02
0.14
0.01
0.04
0.03
0.23
0.004
0.02
0.01
0.12
0.01
0.07
0.02
0.22
0.02
0.13
0.02
0.19
0.01
0.05
1 Based on an LC50 of 1,800 ug a.i./L (Rainbow Trout) and a NOAEC of 187 ug a.i./L (Rainbow Trout).
None of the RQs for any use exceed the Agency's acute or chronic risk LOG for listed fish. Fish
are used as a surrogate species for aquatic-phase CRLFs. These RQs are further characterized in
the context of the effects determination in Section 5.2.
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Table 5.2. Summary of RQs Used to Estimate Direct Effects to Terrestrial-Phase CRLFs
(Upper Bound Kenaga Values, Dose-Based for 20g Bird that Eats Small Insects)1.
Use Site
Appl. Rate
(Ib
a.i./acre)
Exposure Type
EEC (ppm)
RQ
Flowable Soil Applications
Corn
Sorghum
Peanuts
Woody ornamentals
Sunflowers
Soybeans
Dry beans
Lima beans
Cotton
4
3
2
Acute
Chronic
Acute
Chronic
Acute
Chronic
615
461
308
0.57
>10.8
0.43
>8.1
0.28
>5.4
Impregnated Bulk Fertilizer Surface Applications
Corn
Sorghum
Soybeans
4
o
J
Acute
Acute
42 mg a.i./ft2
31 mga.i./ft2
1.93
1.45
1 Based on an LD50 of 1,499 mg/kg-bw (Bobwhite Quail) and a NOAEC of <50 mg/kg-diet
(Mallard Duck)
2 Treated as a granular formulation for modeling purposes
- Bolded RQs exceed the acute or chronic listed species LOG for birds (0.1 and 1, respectively)
Avian RQs exceed the endangered species LOG of 0.1 for acute risk and 1.0 for chronic risk for
all of the alachlor uses modeled (both flowable and the impregnated bulk fertilizer applications).
Birds are used as surrogate species for terrestrial-phase CRLFs. These RQs are further
characterized in the context of the effects determination in Section 5.2.
5.1.2 Indirect Effects
This section presents RQs used to evaluate the potential for alachlor to induce indirect effects.
Pesticides have the potential to exert indirect effects upon listed species by inducing changes in
structural or functional characteristics of affected communities. Perturbation of forage or prey
availability and alteration of the extent and nature of habitat are examples of indirect effects. A
number of these indirect effects are also considered as part of the critical habitat modification
evaluation. In conducting a screen for indirect effects, direct effects LOCs for each taxonomic
group (e.g., freshwater fish, invertebrates, aquatic plants, and terrestrial plants) are employed to
make inferences concerning the potential for indirect effects upon listed species that rely upon
non-listed organisms in these taxonomic groups as resources critical to its life cycle (USEPA,
2004). This approach used to evaluate indirect effects to listed species is endorsed by the
Services (USFWS/NMFS, 2004). If no direct risk to listed species LOCs are exceeded for
organisms on which the assessed species depends for survival or reproduction, indirect effects
are not expected to occur.
If LOCs are exceeded for organisms on which the assessed species depends for survival or
reproduction, dose-response analysis is used to estimate the potential magnitude of effect
associated with an exposure equivalent to the EEC. The greater the probability that exposures
Page 83 of 132
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will produce effects on a taxa, the greater the concern for potential indirect effects for listed
species dependant upon that taxa (USEPA, 2004).
As an herbicide, indirect effects to the assessed species from potential effects on primary
productivity of aquatic plants are a principle concern. If plant RQs fall between the risk to
endangered species and non-endangered species LOCs, a no effect determination is made for
listed species that rely on multiple plant species to successfully complete their life cycle (termed
plant dependent species). If plant RQs are above risk to non-endangered species LOCs, this
could be indicative of a potential for adverse effects to those listed species that rely either on a
specific plant species (plant species obligate) or multiple plant species (plant dependant) for
some important aspect of their life cycle (USEPA, 2004). Based on the information provided in
Section 2.3, the assessed species do not have any known obligate relationship with a specific
species of aquatic plant.
Direct effects to riparian zone vegetation may also indirectly affect the assessed species by
reducing water quality and available spawning habitat via increased sedimentation. Direct
impacts to the terrestrial plant community (i.e.., riparian habitat) are evaluated using submitted
terrestrial plant toxicity data. If terrestrial plant RQs exceed the Agency's LOG for direct risk to
non-endangered plant species, based on EECs derived using EFED's Terrplant model (Version
1.2.1), a conclusion that alachlor may affect the CRLF and DS via potential indirect effects to the
riparian habitat (and resulting impacts to habitat due to increased sedimentation) is made.
Further analysis of the potential for alachlor to affect the CRLF and the DS via reduction in
riparian habitat includes a description of the importance of riparian vegetation to the assessed
species and types of riparian vegetation that may potentially be impacted by alachlor use within
the action area.
RQs used to evaluate the potential for alachlor to induce indirect effects to the assessed species
are presented in Sections 5.1.2.1 to 5.1.2.4. These RQs suggest that potential indirect effects
could occur by potentially impacting food availability and primary productivity as indicated by
LOG exceedances. These RQs were based on the most sensitive surrogate species tested across
aquatic invertebrate, fish, and aquatic plant species tested. Discussion of these RQs in the
context of this effects determination is presented in Section 5.2.
5.1.2.1. Aquatic Invertebrates
Aquatic invertebrate RQs are summarized in Table 5.3 and are used to evaluate the potential for
alachlor to affect the CRLF and the DS by potentially impacting the food supply. Both the
CRLF and the DS consume aquatic invertebrates as part of their diet. Acute risk quotients for
invertebrates were based on peak EECs in the standard pond and the lowest acute toxicity value
for freshwater and saltwater invertebrates. Chronic risk was based on 21-day EECs and the
lowest chronic toxicity value for freshwater and saltwater invertebrates.
Page 84 of 132
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Table 5.3. Summary of Acute and Chronic RQs for Aquatic Invertebrates Used to
Evaluate Potential Indirect Effects to the CRLF and the DS Resulting from Potential
Impacts to Food Supply.
Use Site
Corn (broadcast)
Corn (incorporated)
Sweet corn (broadcast)
Sweet corn (incorporated)
Sorghum (broadcast)
Sorghum (incorporated)
Soybeans (broadcast)
Soybeans, dry beans, lima
beans (incorporated)
Woody ornamentals
(nursery-use)
Woody ornamentals
(residential use)
Cotton (broadcast)
Cotton (incorporated)
Sunflowers (broadcast)
Sunflowers (incorporated)
Peanuts (broadcast)
Peanuts (incorporated)
Exposure
Type
Acute
Chronic
Acute
Chronic
Acute
Chronic
Acute
Chronic
Acute
Chronic
Acute
Chronic
Acute
Chronic
Acute
Chronic
Acute
Chronic
Acute
Chronic
Acute
Chronic
Acute
Chronic
Acute
Chronic
Acute
Chronic
Acute
Chronic
Acute
Chronic
EEC
Peak = 44.8 ug/L
21-day = 43.7 ug/L
Peak = 12.6 ug/L
2 1-day =12.3 ug/L
Peak= 11.3 ug/L
2 1-day = 10.7 ug/L
Peak = 3.2 ug/L
2 1-day = 3.1 ug/L
Peak = 46.7ug/L
2 1-day = 45.6 ug/L
Peak = 12.8 ug/L
2 1-day =12.5 ug/L
Peak = 32.9 ug/L
2 1-day = 3 1.9 ug/L
Peak = 9.3 ug/L
2 1-day = 9.0 ug/L
Peak = 56.0 ug/L
21-day = 54.3 ug/L
Peak = 6.3 ug/L
21-day = 5.5 ug/L
Peak = 25. 2 ug/L
2 1-day = 24.4 ug/L
Peak= 15.3 ug/L
2 1-day = 14.8 ug/L
Peak = 44.8 ug/L
21-day = 43.7 ug/L
Peak = 27.3 ug/L
2 1-day = 26.6 ug/L
Peak= 43. 9 ug/L
21-day = 42.5 ug/L
Peak = 12.4 ug/L
2 1-day = 12.0 ug/L
RQ (Freshwater
Invertebrates)1
0.02
1.2
0.01
0.34
0.005
0.30
0.001
0.09
0.02
1.3
0.01
0.35
0.01
0.89
0.004
0.25
0.02
1.5
0.003
0.15
0.01
0.68
0.01
0.41
0.02
1.2
0.01
0.74
0.02
1.2
0.005
0.33
RQ
(Estuarine/
Marine
Invertebrates)2
0.02
>437
0.01
>123
0.005
>107
0.001
>31
0.02
>456
0.01
>125
0.01
>319
0.004
>90
0.02
>543
0.003
>55
0.01
>244
0.01
>148
0.02
>437
0.01
>266
0.02
>425
0.01
>120
1 Based on Chironomusplumosus endpoints (ECso = 2,500 ug a.i./L; NOAEC = 36 ug a.i./L).
2 Based on LCso = 2,400 ug a.i./L (Americamysis bahia) and NOAEC < 0.1 ug a.i./L (Tigriopus
japonicus)
Bolded numbers exceed the Agency's listed species LOCs (RQ > acute endangered species LOG of 0.05
and the chronic LOC of 1.0).
None of the acute RQs for freshwater or estuarine/marine invertebrates exceed the risk to
endangered species LOC (0.05). The freshwater invertebrate RQs exceed the chronic risk LOC
of 1.0 for the corn (broadcast) (RQ = 1.2), sorghum (broadcast) (RQ = 1.3), woody ornamentals
(nursery-use) (RQ = 1.5), sunflower (broadcast) (RQ = 1.2), and the peanut (broadcast) (RQ =
1.2) The Agency's chronic risk LOC is exceeded for saltwater invertebrates for all uses
modeled [range : >31 (sweet corn, incorporated use) - >543 (woody ornamentals)]. These RQs
Page 85 of 132
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were based on the most sensitive surrogate species across aquatic invertebrate species tested.
Discussion of these RQs in the context of this effects determination is presented in Section 5.2.
5.1.2.2. Terrestrial Invertebrates
Terrestrial invertebrate RQs are used to evaluate the potential for alachlor to affect the CRLF by
potentially impacting their food supply. Terrestrial invertebrate RQs are presented in Table 5.4.
Table 5.4. Summary of Acute RQs for Terrestrial Invertebrates on the Site of Application
Used to Evaluate Potential Indirect Effects to the CRLF Resulting from Potential Impacts
to the Food Supply.
Use
Corn
Sorghum
Peanuts
Woody ornamentals
Sunflowers
Soybeans
Dry beans
Lima beans
Cotton
Application
Rate (Ib
a.i./acre)
4
3
2
Size Class
Small insect
Large insect
Small insect
Large insect
Small insect
Large insect
EEC (ppm)
540
60
405
45
270
30
RQ1
<1.9
<0.21
<1.4
<0.16
<0.95
<0.11
1 Available acute contact toxicity data for bees exposed to alachlor (in units of ug a.i./bee) are converted to
ug a.i./g (of bee) by multiplying by 1 bee/0.128 g (LD50 = >36.3 ug a.i./bee = >283.6 ug/g).
- Bolded RQs potentially exceed the interim risk to listed species LOG for terrestrial invertebrates (0.05).
Because the available toxicity data for honey bees resulted in only 0.41% mortality at the highest
concentration tested (36.3 jig a.i./bee), a definitive LDso value was not determined. Therefore,
although the estimated RQs for all alachlor uses are potentially above the Agency's interim risk
to listed species LOG for terrestrial invertebrates (0.05), the actual RQs would likely be lower
than those reported in Table 5.4. However, it is not clear if the actual RQs would be above or
below the Agency's LOG without definitive data, therefore, risks cannot be precluded at this
time. Discussion of these RQs in the context of this effects determination is presented in Section
5.2.
5.1.2.3. Mammals and Amphibians
Potential risks to mammals are derived using T-REX and acute and chronic rat toxicity data.
RQs are typically derived for various sizes of mammals (15 g, 35 g, and 1000 g); however, RQs
are not presented for 1000 g mammals because it is improbable that even the largest CRLF
would consume a mammal of that size. Therefore, the evaluation for potential indirect effects to
the CRLF resulting from potential reductions in mammal abundance as food is based on the 15 g
size class, which results in higher RQs than the 35 g mammal. The California mouse
(Peromyscus californicus) is a particular species known to be consumed by the CRLF. The
California mouse is omnivorous and consumes grasses, fruits, flowers, and invertebrates (USC,
Page 86 of 132
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2005; http://wotan.cse.sc.edu/perobase/systematics/p_calif.htm). Therefore, the short grass food
item was used to determine if mammals could be impacted; however, RQs based on EECs on
other food items were also derived for characterization purposes. A range of RQs for mammals
is presented in Table 5.5 (acute) and Table 5.6 (chronic) (see also Appendix L).
Page 87 of 132
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Table 5.5. Summary of Acute RQs for 15 g Mammals (LD50 = 930 mg/kg-bw) Used to
Evaluate Potential Indirect Effects to the CRLF Resulting from Potential Impacts to the
Food Supply.
Use Site
Appl. Rate (Ib
a.i./acre)
Dietary Category
EEC (ppm)
RQ
Flowable Post-Plant, Pre-Plant, Pre-Emergence, and Burndown Applications1
Com
Sorghum
Peanuts
Woody ornamentals
Sunflowers
Soybeans
Dry beans
Lima beans
Cotton
4
3
2
Short grass
Tall grass
Broadleaf plants/small insects
Fruits/pods/large insects
Seeds
Short grass
Tall grass
Broadleaf plants/small insects
Fruits/pods/large insects
Seeds
Short grass
Tall grass
Broadleaf plants/small insects
Fruits/pods/large insects
Seeds
915
420
515
57
13
686
315
386
43
10
458
210
257
29
6
0.45
0.21
0.25
0.03
0.01
0.34
0.15
0.19
0.02
0.00
0.22
0.10
0.13
0.01
0
Flowable Pre-Plant and Pre-Emergence Bare Soil Applications2
Com
Sorghum
Peanuts
Woody ornamentals
Sunflowers
Soybeans
Dry beans
Lima beans
Cotton
4
(3.42, it would be
lower for
sunflowers )3
3
(2.57)3
2
(0.53)3
Short grass
Tall grass
Broadleaf plants
Fruits/pods
Seeds
Small insects
Large insects
Short grass
Tall grass
Broadleaf plants
Fruits/pods
Seeds
Small insects
Large insects
Short grass
Tall grass
Broadleaf plants
Fruits/pods
Seeds
Small insects
Large insects
783
359
440
49
11
515
57
588
270
331
37
8
386
43
121
56
68
8
2
257
29
0.38
0.18
0.22
0.02
0.01
0.25
0.03
0.29
0.13
0.16
0.02
0
0.19
0.02
0.06
0.03
0.03
0
0
0.13
0.01
Impregnated Bulk Fertilizer Surface Applications4
Com
Sorghum
Soybeans
4
3
Not Applicable
Not Applicable
42 mg a.i./ft2
31 mg a.i./ft2
1.36
1.02
1 Estimated residiues for potential food items found on the site of application.
Estimated residiues for potential food items found immediately adjacent to the site of application (except for small and large insects which may
be exposed to alachlor on the site of application).
3 AgDRIFT was run, to estimate an 'application rate' 1 ft off the site of application, using the default settings in Tier 1. Except for the sunflower
and cotton uses that are only on the label that has spray drift restrictions (ASAE medium-coarse droplet size distribution; <10 mph wind speed;
maximum 4-ft boom height). Only ground applications were modeled for all uses.
4 Treated as a granular formulation for modeling purposes
- Bolded RQs exceed the acute risk LOC for listed mammals (0.1)
Page 88 of 132
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On the site of application, the RQs for 15 g mammals that eat short grass, tall grass, and
broadleaf plants/small insects exceed the Agency's acute risk LOG for listed mammals for all
alachlor uses (flowable and bulk fertilizer applications). Immediately adjacent to application
sites, the RQs exceed the Agency's acute risk LOG for listed mammals that eat short grass, tall
grass, and broadleaf plants/small insects for all uses except for cotton.
The only RQs that exceed the Agency's acute risk LOG for non-listed mammals are for the
impregnated bulk fertilizer applications (corn, sorghum, and soybeans). The acute risk LOG for
non-listed species is not exceeded for any other alachlor use/application combination.
Page 89 of 132
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Table 5.6. Summary of Chronic RQs for 15 g Mammals (NOAEC = 30 mg/kg-diet) Used to
Evaluate Potential Indirect Effects to the CRLF Resulting from Potential Impacts to the
Food Supply.
Use Site
Appl. Rate (Ib
a.i./acre)
Dietary Category
Chronic
Dose-Based
RQ
Chronic
dietary-
Based RQ
Flowable Post-Plant, Pre-Plant, Pre-Emergence, and Burndown Applications1
Corn
Sorghum
Peanuts
Woody ornamentals
Sunflowers
Soybeans
Dry beans
Lima beans
Cotton
4
3
2
Short grass
Tall grass
Broadleaf plants/small insects
Fruits/pods/large insects
Seeds
Short grass
Tall grass
Broadleaf plants/small insects
Fruits/pods/large insects
Seeds
Short grass
Tall grass
Broadleaf plants/small insects
Fruits/pods/large insects
Seeds
278
127
156
17
3.9
208
95
117
13
2.9
138
64
78
9
1.9
32
15
18
2
2
24
11
14
1.5
1.5
16
7
9
1
1
Flowable Pre-Plant and Pre-Emergence Bare Soil Applications
Corn
Sorghum
Peanuts
Woody ornamentals
Sunflowers
Soybeans
Dry beans
Lima beans
Cotton
4
(3.42, it would
be lower for
sunflowers )2
3
(2.57)2
2
(0.53)2
Short grass
Tall grass
Broadleaf plants
Fruits/pods
Seeds
Small insects
Large insects
Short grass
Tall grass
Broadleaf plants
Fruits/pods
Seeds
Small insects
Large insects
Short grass
Tall grass
Broadleaf plants
Fruits/pods
Seeds
Small insects
Large insects
237
109
134
15
3
156
17
178
82
100
11
2
117
13
37
17
21
2
0.5
78
9
27
13
15
2
2
18
2
21
9
12
1
1
14
1.5
4
1.9
2.4
0.3
0.3
9
1
1 Estimated residiues for potential food items found on the site of application.
2 Estimated residiues for potential food items found immediately adjacent to the site of application (except for small
and large insects which may be exposed to alachlor on the site of application). AgDRIFT was run using the default
settings in Tier 1. Except for the sunflower and cotton uses that are only on the label that has spray drift restrictions
(ASAE medium-coarse droplet size distribution; <10 mph wind speed; maximum 4-ft boom height). Only ground
applications were modeled for all uses.
- Bolded RQs exceed (or are near) the chronic listed species LOG for mammals (1)
Page 90 of 132
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The chronic RQs (all dietary categories; both dose- and dietary-based) for all of the uses
modeled exceed the Agency's chronic risk for listed species LOG of 1, except for the RQs for the
cotton use (applications to bare soil) and the fruits/pods (dietary-based) and seeds (dose- and
dietary-based) dietary categories.
For potential terrestrial-phase amphibian prey items, birds are used as a surrogate. As discussed
above for direct effects to terrestrial-phase CRLF, avian RQs exceed the endangered species
LOG of 0.1 for acute risk and 1.0 for chronic risk for all of the alachlor uses modeled (both
flowable and the impregnated bulk fertilizer applications).
Based on acute and chronic risk LOG exceedances, there is potential for alachlor to impact
mammal and amphibian abundance, which could result in indirect effects to the CRLF.
Discussion of these RQs in the context of this effects determination is presented in Section 5.2.
5.1.2.4 Aquatic and Terrestrial Plants
Aquatic plants serve as food supply for both the CRLF and the DS and can impact water quality.
Additionally, effects to terrestrial plants can impact terrestrial habitat quality and water quality
parameters. Therefore, RQs for vascular and non-vascular aquatic plants are used to evaluate the
potential for alachlor to affect the CRLF and/or the DS by potentially impacting the food supply
and water quality, and, thus, habitat (Table 5.7). RQs for terrestrial plants are used to evaluate
the potential for alachlor to impact aquatic habitats (i.e., water quality) (aquatic-phase CRLF and
DS) and/or terrestrial habitats (terrestrial-phase CRLF) (Table 5.8).
Page 91 of 132
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Table 5.7. Summary of Acute RQs for Aquatic Plants Used to Evaluate Potential Indirect
Effects to the CRLF and DS.
Use Site
Soybeans, dry beans, lima
beans (incorporated)
Woody ornamentals
(nursery-use)
Woody ornamentals
(residential use)
Plant Type
Non-vascular aquatic plant1
Vascular aquatic plant2
Non-vascular aquatic plant1
Vascular aquatic plant2
Non-vascular aquatic plant1
Vascular aquatic plant2
Non-vascular aquatic plant1
Vascular aquatic plant2
Non-vascular aquatic plant1
Vascular aquatic plant2
Non-vascular aquatic plant1
Vascular aquatic plant2
Non-vascular aquatic plant1
Vascular aquatic plant2
Non-vascular aquatic plant1
Vascular aquatic plant2
Non-vascular aquatic plant1
Vascular aquatic plant2
Non-vascular aquatic plant1
Vascular aquatic plant2
Non-vascular aquatic plant1
Vascular aquatic plant2
Non-vascular aquatic plant1
Vascular aquatic plant2
Non-vascular aquatic plant1
Vascular aquatic plant2
Non-vascular aquatic plant1
Vascular aquatic plant2
Non-vascular aquatic plant1
Vascular aquatic plant2
Non-vascular aquatic plant1
Vascular aquatic plant2
EEC
P^oV _ A A 0 ..fffl
P^oV _ i ^) /; ^/r
P^oV _ 1 1 0 II4T/T
P^oV — 1 O 8 1 1 (T/T
P^oV _ O') Q ||4T/T
P^oV _ Q 0 ||4T/T
P^oV _ ^C ^ II (T/T
P^oV _ ICO , , (T/T
P^oV _ A A 0 ||4T/T
p^oV _ ^^7 o II4T/T
P^oV _ JO Q ||4T/T
P^oV _ 1 0 A 1 1 (T/T
RQ
27.3
19.5
7.7
5.4
6.9
4.9
2.0
1.4
28.5
20.3
7.8
5.6
20.1
14.3
5.7
4.0
34.1
24.3
3.8
2.7
15.4
11.0
9.3
6.7
27.3
19.5
16.6
11.9
26.8
19.1
7.6
5.4
1 Based on an ECso = 1.64 ug a.i./L (Selenastrum capricornutum)
1 Based on an EC50 = 2.3 ug a.i./L (Lemna gibba)
Bolded numbers exceed the Agency's aquatic plant LOG (RQ < 1.0).
The RQs for non-vascular and vascular aquatic plants exceed the Agency's LOCs for all uses
modeled [non-vascular plant RQ range = 2.0 (sweet corn, incorporated use) - 34.1 (woody
ornamental use); vascular plant RQ range =1.4 (sweet corn, incorporated use) - 24.3 (woody
ornamental use).
Potential indirect effects resulting from effects on terrestrial vegetation were assessed using RQs
from terrestrial plant seedling emergence and vegetative vigor Ł€25 data as a screen. Based on
the results of the submitted terrestrial plant toxicity tests, emerging seedlings are more sensitive
to alachlor via soil/root uptake than emerged plants via foliar routes of exposure. Therefore, the
seedling emergence data were used to estimate terrestrial plant RQs for alachlor use. RQs used
to estimate potential indirect effects to the CRLF and/or the DS from potential effects to
terrestrial plants within their habitat areas are summarized in Tables 5.8.
Page 92 of 132
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Table 5.8. Non-Listed Species Terrestrial Plant RQs for Alachlor Use in California
Use
Application
Type
ADJACENT
UPLAND
Monocot
Dicot
ADJACENT
WETLAND
Monocot
Dicot
DRIFT ONLY
Monocot
Dicot
4 Ib a.i./acre
Corn
Sorghum
Peanuts
Woody ornamentals
Sunflowers
Corn
Sorghum
Peanuts
Sunflowers
Corn
Sorghum
Soil Surface
Soil
Incorporated
(2-inch
incorporation)
Impregnated
Bulk Fertilizer2
36
21
15
7
4
3
304
155
149
60
31
29
6
6
<0.1
1
1
<0.1
3 Ib a.i./acre
Soybeans
Soybeans
Dry beans
Lima beans
Soybeans
Soil Surface
Soil
Incorporated
(2-inch
incorporation)
Impregnated
Bulk Fertilizer2
27
16
11
5
3
2
228
116
112
45
23
22
4
4
<0.1
0.9
0.9
0.1
2 Ib a.i./acre
Cotton
Soil Surface
Soil
Incorporated
(2-inch
incorporation)
9
5
2
1
76
39
15
8
1
1
0.3
0.3
1 Based on the following: monocots - EC25 = 0.0067 Ib a.i./acre (seedling emergence) and EC25 = 0.068 Ib a.i./acre
(vegetative vigor) in annual dry grass (Lolium perenne); dicots - EC25 = 0.034 Ibs a.i./acre [seedling emergence,
lettuce (Lactuca sativd)] and EC25 =1.4 Ibs a.i./acre [vegetative vigor, cucumber (Cucumis sativus)].
2 Impregnated bulk fertilizer applications are treated as granular applications for modeling purposes.
- Bolded RQs exceed the Agency's non-listed species LOG for terrestrial plants (RQ = 1).
Monocots are more sensitive to alachlor than are dicots, based on available data. However, for
adjacent upland and wetland plants, terrestrial plant RQs for both monocots and dicots exceed
the Agency's risk to non-listed species LOG for all alachlor uses and application types (RQs
range from 1-60 for dicots; and 5 - 304 for monocots). For the drift only RQs (range = <0.1 -
6), all of the RQs exceed the Agency's LOG except for the impregnated bulk fertilizer
applications (all uses) and the dicot RQs for the cotton use (all application types).
Therefore, LOCs were exceeded for both aquatic and terrestrial plants, which could result in
indirect effects to the CRLF or the DS. These LOCs and their impact on the effects
determination are described in Section 5.2.
5.1.3 Primary Constituent Elements of Designated Critical Habitat
For alachlor use, the assessment endpoints for designated critical habitat PCEs involve the same
endpoints as those being assessed relative to the potential for direct and indirect effects to the
listed species assessed here. Therefore, the effects determinations for direct and indirect effects
Page 93 of 132
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presented in Section 5.1 are used as the basis of the effects determination for potential
modification to designated critical habitat.
5.2 Risk Description
The risk description synthesizes overall conclusions regarding the likelihood of adverse impacts
leading to an effects determination (i.e., "no effect," "may affect, but not likely to adversely
affect," or "likely to adversely affect") for the assessed species and the potential for effects to
their designated critical habitat.
If the RQs presented in the Risk Estimation (Section 5.1) show no direct or indirect effects for
the assessed species, and no effects to PCEs of the designated critical habitat, a "no effect"
determination is made, based on alachlor's use in California. However, if LOCs for direct or
indirect effect are exceeded or there are effects to the PCEs of the critical habitat, the Agency
concludes a preliminary "may affect" determination for the FIFRA regulatory action regarding
alachlor.
None of the RQs for alachlor exceed the listed species LOCs (acute and chronic risk) for fish.
Fish are used as a surrogate for aquatic phase amphibians. The RQs for 20 g birds that eat short
grass (used as a screening-level surrogate for terrestrial-phase CRLF) exceed the risk to
endangered species LOCs (acute and chronic) for all of the alachlor uses (both flowable and the
impregnated bulk fertilizer applications). Therefore, there is a potential for direct effects to
terrestrial-phase CRLF from all alachlor uses.
Regarding the potential for indirect effects to DS and CRLF and effects to their designated
critical habitat, at least some of the RQs for mammals, aquatic invertebrates, birds, plants
(aquatic and terrestrial) and potentially terrestrial invertebrates exceed the Agency's listed
species LOCs. Therefore, there is a potential for indirect effects to DS and CRLF and effects to
their critical habitat. Due to the potential for direct and/or indirect effects, alachlor use 'may
affect' DS and CRLF and/or their designated critical habitat.
Following a "may affect" determination, additional information is considered to refine the
potential for exposure based on the life history characteristics (i.e., habitat range, feeding
preferences, etc) of the assessed species. Based on the best available information, the Agency
uses the refined evaluation to distinguish those actions that "may affect, but are not likely to
adversely affect" from those actions that are "likely to adversely affect" the assessed species and
its designated critical habitat.
The criteria used to make determinations that the effects of an action are "not likely to adversely
affect" the assessed species or modify its designated critical habitat include the following:
• Significance of Effect: Insignificant effects are those that cannot be meaningfully
measured, detected, or evaluated in the context of a level of effect where "take" occurs
for even a single individual. "Take" in this context means to harass or harm, defined as
the following:
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• Harm includes significant habitat modification or degradation that results in
death or injury to listed species by significantly impairing behavioral patterns
such as breeding, feeding, or sheltering.
• Harass is defined as actions that create the likelihood of injury to listed species
to such an extent as to significantly disrupt normal behavior patterns which
include, but are not limited to, breeding, feeding, or sheltering.
• Likelihood of the Effect Occurring: Discountable effects are those that are extremely
unlikely to occur.
• Adverse Nature of Effect: Effects that are wholly beneficial without any adverse effects
are not considered adverse.
A description of the risk and effects determination for each of the established assessment
endpoints for the CRLF and DS and their designated critical habitat is provided in the following
sections. The effects determination section for each listed species assessed will follow a similar
pattern. Each will start with a discussion of the potential for direct effects, followed by a
discussion of the potential for indirect effects. The section will end with a discussion on the
potential for effects to the critical habitat from the use of alachlor.
5.2.1. Direct Effects
5.2.1.1. DS and Aquatic-Phase CRLFs
None of the RQs for any alachlor use exceed the acute or chronic risk LOCs for listed fish. The
listed species LOG of 0.05 is associated with a probability of an individual effect of
approximately 1 in 418,000,000 (using a default slope of 4.5).
The available alachlor toxicity data for aquatic-phase amphibians (African clawed frog; LCso =
6.1 mg a.i./L, NOAEC = 640 jig a.i./L) and estuarine/marine fish (sheepshead minnow; LCso =
3.9 mg a.i./L, NOAEC = 410 jig a.i./L) indicate that amphibians and estuarine/marine fish are
equally as (or perhaps slightly less) sensitive to alachlor than freshwater fish. For example,
using the acute and chronic toxicity endpoints for the African clawed frog and the sheepshead
minnow would also result in no LOG exceedances for any alachlor use. The sheepshead minnow
results are consistent with a 5-year field study that investigated the effects of three pesticides
(including alachlor) on estuaries in North Carolina from runoff from adjacent farm lands (MRTD
44105503) (see Appendix A for details). The pesticides in this study did not have a measurable
impact on the estuarine biological community adjacent to application sites.
Although risks to fish are not expected based on the available toxicity data and exposure models,
there are nine reported fish kills associated with alachlor in the EIIS database (they occurred
between 1983 and 1995 and involved from an 'unknown' number of dead freshwater fish to
'thousands') (see Appendix K). Therefore, to explore further the potential impact of alachlor
use on fish, a more detailed evaluation of the nine reported fish kills associated with alachlor was
conducted. In seven of the nine reported fish kill incidents involving alachlor, other chemicals
known to be highly toxic to fish were also involved in the incidents and are the more likely cause
of the fish kills (i.e., 1000636-003, B000164-001,1000799-009,1000038-001,1003826-017,
1002793-001, and 1000636-012).
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In another incident (1005002-008), the co-formulated product Bullet (alachlor + atrazine) (this
product is not registered for use in California) was used on an agricultural field and shortly after
it began to rain. Within 3 days, dead fish (bass and bluegill sunfish) were evident in a nearby
pond. Ten days following application, alachlor, atrazine, and metolachlor residues were detected
in the water from the affected pond. This incident was reported as an 'accidental misuse' (the
reason is not provided in the EIIS report).
In the remaining reported incident (1000431-001), no other pesticides besides alachlor were
associated with the fish kill. In this incident, a fish kill in a 'fish tank' occurred 3.5 weeks
following the application of Micro-Tech® to a 165-acre agricultural field. Both perch and bass,
but not catfish, were affected. No water or fish tissues were analyzed for residues. The legality
of use for this incident was classified as 'undetermined'. Therefore, in one of the nine reported
fish kill incidents, a registered use of alachlor could not be excluded as a potential cause of the
incident. Because of the relatively low toxicity of alachlor to fish and the timing of the incident
(i.e.., it occurred 3.5 weeks after the alachlor use), however, it is unlikely that the fish were
directly affected by alachlor. A more likely scenario is that the alachlor impacted the aquatic
plant community of the 'fish tank' which in turn affected the water quality parameters in the tank
(e.g., dissolved oxygen) and indirectly affected the fish.
Therefore, the weight of evidence based on the currently available data suggests that direct
effects to aquatic-phase CRLFs and DS are not expected from the use of alachlor in California.
The potential for indirect effects is evaluated in Section 5.2.2.
5.2.1.2. Terrestrial-Phase CRLF
Acute and chronic LOCs are exceeded for birds. Acute RQs range from 0.28 (flowable
applications to cotton) to 1.93 (bulk fertilizer applications to corn/sorghum). These RQs exceed
the acute risk to endangered species LOG and are associated with a probability of an individual
effect of approximately 1 in 1 to 1 in 156, depending on the use being evaluated (Table 5.9).
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Table 5.9. Probability of Individual Effects to Terrestrial-Phase CRLF Based on Acute
Data from Birds.
Use Site
Appl. Rate
Ob
a.i./acre)
Acute RQ
Slope
(95% C.L)1
Chance of
Individual Effects
Flowable Soil Applications
Corn
Sorghum
Peanuts
Woody ornamentals
Sunflowers
Soybeans
Dry beans
Lima beans
Cotton
4
o
3
2
0.57
0.43
0.28
4.5
2
9
4.5
2
9
4.5
2
9
~ in 7.35
~ in 3.2
~ in 71.4
~ in 20.2
~ in 4.3
~ in 206
~ in 156
~ in 7.4
~ in 3, 070,000
Impregnated Bulk Fertilizer Surface Applications1
Corn
Sorghum
Soybeans
4
o
J
1.93
1.45
4.5
2
9
4.5
2
9
~ in .1
~ in .4
~ in
~ in .3
~ in .6
~ in .1
Default slopes were used
Birds were used as surrogate species for terrestrial-phase CRLFs. Terrestrial-phase amphibians
are poikilotherms, which means that their body temperature varies with environmental
temperature, while birds are homeotherms (temperature is regulated, constant, and largely
independent of environmental temperatures). As a consequence, the caloric requirements of
terrestrial-phase amphibians are markedly lower than birds. Therefore, on a daily dietary intake
basis, birds consume more food than terrestrial-phase amphibians. This can be seen when
comparing the caloric requirements for free living iguanid lizards (used in this case as a
surrogate for terrestrial phase amphibians) to song birds (USEPA, 1993):
iguanid FMR (kcal/day)= 0.0535 (bw g)°'799
passerine FMR (kcal/day) = 2.123 (bw g)°'749
With relatively comparable slopes to the allometric functions, one can see that, given a
comparable body weight, the free-living metabolic rate (FMR) of birds can be 40 times higher
than reptiles, though the requirement differences narrow with high body weights.
Because the existing risk assessment process is driven by the dietary route of exposure, a finding
of safety for birds, with their much higher feeding rates and, therefore, higher potential dietary
exposure, is reasoned to be protective of terrestrial-phase amphibians. For this not to be the case,
terrestrial-phase amphibians would have to be 40 times more sensitive than birds for the
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differences in dietary uptake to be negated. However, existing dietary toxicity studies in
terrestrial-phase ampibians for alachlor are lacking. To quantify the potential differences in food
intake between birds and terrestrial-phase CRLFs, food intake equations for the iguanid lizard
were used to replace the food intake equation in T-REX for birds, and additional food items of
the CRLF were evaluated. These functions were encompassed in a model called T-HERPS. T-
HERPS is available at: http://www.epa.gov/oppefedl/models/terrestrial/index.htm.
For the uses with the highest application rates (4 Ib a.i./acre), none of the acute RQs for
terrestrial herpetofauna exceed the Agency's listed species LOG for acute exposure (Table 5.10).
Therefore, none of the registered uses of alachlor are expected to result in acute direct effects to
terrestrial-phase CRLF (see also Appendix M).
Table 5.10. Upper Bound Kenaga, Acute Terrestrial Herpetofauna Dose-Based Risk
Quotients for Alachlor (4 Ib a.i./acre, 1 Application).
Size
Class
(grams)
1.4
37
238
LDSO
(mg
a.i./kg-bw)
1499.00
1499.00
1499.00
EECs and RQs
Broadleaf
Plants/
Small Insects
EEC
20.98
20.62
13.51
RQ
0.01
0.01
0.01
Fruits/Pods/
Seeds/
Large Insects
EEC
2.33
2.29
1.50
RQ
0.00
0.00
0.00
Small Herbivore
Mammals
EEC
N/A1
N/A
93.03
RQ
N/A
N/A
0.06
Small
Insectivore
Mammal
EEC
N/A
N/A
5.81
RQ
N/A
N/A
0.00
Small
Amphibians
EEC
N/A
0.72
0.47
RQ
N/A
0.00
0.00
1 N/A = not applicable (a 1.4 or 37 g frog is not expected to be large enough to eat a 35 g mammal).
At the 4 Ib a.i./acre application rate (corn, sorghum, peanuts, woody ornamentals, and
sunflowers), the sub-acute RQs for terrestrial herpetofauna that eat broadleaf plants/small insects
and small herbivorous mammals exceed the Agency's listed species LOG (Table 5.11). None of
the RQs for any other use exceed the LOG based on sub-chronic exposure.
For chronic exposure, all of the alachlor uses exceed the Agency's chronic listed species LOG of
1 for at least one of the dietary categories using an avian NO AEG of 50 mg a.i./kg-diet (Table
11). However, since a definitive NOAEC was not determined for birds (i.e., the NOAEC <50
mg a.i./kg-diet) all of the calculated RQs for chronic exposure are greater-than values.
Therefore, risks to terrestrial-phase frogs from chronic exposure cannot be precluded for any of
the uses or dietary categories at this time.
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Table 5.11. Upper Bound Kenaga, Sub-Acute and Chronic Terrestrial Herpetofauna
Dietary-Based Risk Quotients for Alachlor (1 Application).
Appl.
Rate (Ib
a.i./acre)
Endpoint
(mg
a.i./kg-
diet)
EECs and RQs
Broadleaf Plants/
Small Insects
EEC
RQ
Fruits/Pods/
Seeds/
Large Insects
EEC
RQ
Small Herbivore
Mammals
EEC
RQ
Small
Insectivore
Mammals
EEC
RQ
Small
Amphibians
EEC
RQ
Sub-Acute (Dietary)
4
3
2
1^50 —
5620
540.00
405.00
270.00
0.10
0.07
0.05
60.00
45.00
30.00
0.01
0.01
0.01
632.59
474.44
316.29
0.11
0.08
0.06
39.54
29.65
19.77
0.01
0.01
0.00
18.74
14.06
9.37
0.00
0.00
0.00
Chronic (Dietary)
4
3
2
NOAEC
<50
540.00
405.00
270.00
>10.80
>8.10
>5.40
60.00
45.00
30.00
>1.20
>0.90
>0.60
632.59
474.44
316.29
>12.65
>9.49
>6.33
39.54
29.65
19.77
>0.79
>0.59
>0.40
18.74
14.06
9.37
XK37
>0.28
XL 19
- Bolded numbers (black) exceed the Agency's listed species LOG.
- Bolded numbers (gray) potentially exceed the Agency's listed species LOG.
These results indicate that the risk of direct adverse effects to terrestrial-phase CRLF from acute
oral or sub-acute dietary exposure is likely low. However, the risk (or potential risk) to
terrestrial-phase CRLF from chronic dietary exposure cannot be precluded and exists for all
dietary classes relevant to the CRLF (for all of the registered alachlor uses).
5.2.2. Indirect Effects, DS and Aquatic-Phase CRLF
As discussed in Section 2, the diet of aquatic-phase CRLF tadpoles and DS larvae is composed
primarily of unicellular aquatic plants (i.e., algae and diatoms) and detritus. However, aquatic
invertebrates are also consumed by both CRLFs and the DS, and fish are consumed by adult
CRLFs. Therefore, potential impacts to each of these potential food items are evaluated.
5.2.2.1. Potential Impacts to Fish (Indirect Effects to CRLF Only)
Fish are food items of the CRLF. None of the RQs exceed the Agency's listed species LOCs for
fish. Therefore, indirect effects to CRLF from a decline in potential fish prey are not expected
from the use of alachlor in California.
5.2.2.2. Potential Impacts to Aquatic Invertebrates
CRLF
The acute risk to listed and non-listed species LOCs of 0.05 and 0.5 were not exceeded for
freshwater invertebrates for any alachlor use based on toxicity values from the most sensitive
freshwater species for which data are available. The highest acute RQ is 0.02 [for the woody
ornamental (nursery) use]. At this RQ and using the default slope (4.5), the probability of an
effect would be approximately 1 in 9.6E+13. Based on chronic exposure, the Agency's chronic
risk LOG of 1 is exceeded for the corn (broadcast) (RQ = 1.2), sorghum (broadcast) (RQ = 1.3),
woody ornamentals (nursery-use) (RQ = 1.5), sunflower (broadcast) (RQ = 1.2), and the peanut
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(broadcast) (RQ = 1.2) uses. Based on the CADPR PUR data, from 1999 to 2006 an average of
<1 Ib of alachlor per year was applied to woody ornamentals in California. Alachlor was not
used at all on sunflowers, sorghum, or peanuts in California during the same time period (again,
based on the CADPR PUR data). Therefore impacts to wildlife in California from these uses are
not expected. Corn, however, is one of the major uses for alachlor in California.
The NOAEC used to calculate the chronic freshwater invertebrate RQs is based on an endpoint
of reduced adult length and the EECs are only slightly above the NOAEC (-1.5X for the woody
ornamental use and ~1X for the corn, sorghum, sunflower, and peanut uses). What effect
reduced adult length would have on aquatic invertebrate populations is unclear, but the effect is
not likely to reduce aquatic invertebrate populations to a level that would impact the CRLF (i.e.,
from loss of potential prey items).
Based on the low anticipated direct impacts to the most sensitive freshwater invertebrates, any
potential impact to aquatic-phase CRLFs would likely be immeasurable in the environment and
would, therefore, constitute an insignificant effect. Therefore, exceedance of the chronic risk to
endangered species LOG suggests that there could be some effect to sensitive freshwater aquatic
invertebrates from the woody ornamental and sunflower uses; however, such an effect would
likely be insignificant to the CRLF.
DS
The DS eats small zooplankton. They primarily eat planktonic copepods, cladocerans,
amphipods, and insect larvae. However, the most important food organism appears to be
Eurytemora qffinis, which is a euryhaline copepod (USFWS, 1995 and 2004). Based on toxicity
data from mysid, none of the RQs for any alachlor use exceed the Agency's acute risk LOCs
(listed or non-listed species) [acute RQs range from 0.001 (sweet corn) to 0.02 (woody
ornamentals)]. At the highest RQ (0.02) and using a slope of 8.7, the probability of an effect
would be approximately 1 in 1.03E+49. Therefore, impacts to potential estuarine/marine
invertebrate prey are not expected from acute exposure to alachlor.
For chronic risk to estuarine/marine invertebrates, the only species for which data from chronic
exposure are available is the copepod (non-native) Tigriopusjaponicus. Based on the T.
japonicus endpoint, the chronic RQs exceed the Agency's LOG for all uses [RQs range from >31
(sweet corn) to >543 (woody ornamentals)]. In the T. japonicus study, a definitive NOAEC was
not established because potential reproductive effects (i.e., increase in the generation time by ~1
day related to the duration of the nauplius phase) were seen at all concentrations tested (the
lowest concentration = 0.1 jig a.i./L). No other reproductive traits (i.e., fecundity, sex ratio, or
survival rate) showed any significant change after exposure to alachlor, even at the highest
concentration tested (100 jig a.i./L). If the 100 jig a.i./L endpoint is used to calculate RQs, none
of the RQs for any alachlor use exceed the chronic risk LOG [the highest RQ = 0.54 (woody
ornamentals)]. This indicates that effects to copepod fecundity, sex ratio, and survival rate are
not expected from alachlor use.
Therefore, the conclusion regarding the potential for indirect effects to the DS from a reduction
in prey availability is dependent on the significance of the effect of extending the nauplius phase
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in copepod prey by roughly one day. Although increased generation time could decrease
copepod populations over an extended period of time, the impact from alachlor use to copepod
(and other estuarine/marine invertebrate) populations is not expected to be large enough to
impact the DS indirectly. This, again, is consistent with the study that investigated the effects of
three pesticides (including alachlor) on estuaries in North Carolina from runoff from adjacent
farm lands (MRID 44105503) (see Appendix A for details). The pesticides in this study did not
have a measurable impact on the estuarine biological community adjacent to application sites.
5.2.2.3. Potential Impacts to Aquatic Plants
CRLF tadpoles consume primarily algae, and DS larvae consume phytoplankton. Algal RQs
ranged from approximately 2 (sweet corn) to 34 (woody ornamentals), which means that the
EECs calculated for alachlor uses are ~2 to 34 times higher than the most sensitive algal ECso of
1.64 |ig/L. From spray drift alone, impacts to non-vasular aquatic plants are expected up 216 ft
(0.07 km) and 151 ft (0.05 km) from application sites for corn and dry beans (the two most
common alachlor uses in California), respectively (see Section 5.2.4 and Table 5.13). Based on
the downstream dilution analysis, effects to aquatic plants could extend up to 285 km from use
sites for the corn and woody ornamental (nursery) uses. Therefore, impacts to aquatic plants
found near alachlor use sites are expected.
5.2.3. Indirect Effects, Terrestrial-Phase CRLFs
As discussed in Section 2, the diet of terrestrial-phase CRLFs includes terrestrial invertebrates,
small mammals, and amphibians. Potential impacts to each of these potential food items are
evaluated below.
5.2.3.1. Terrestrial Invertebrates
When the terrestrial-phase CRLF reaches juvenile and adult stages, its diet is mainly composed
of terrestrial invertebrates. Alachlor is classified as practically nontoxic to non-target insects on
an acute contact exposure basis. An acute contact LDso for terrestrial invertebrates could not be
determined based on available data. For honey bees, a contact concentration of 36.3 jig a.i./bee
(equivalent to 284 ppm) resulted in 0.41% mortality of exposed adults. Only one concentration
was used in this study; therefore, a definitive LDso value and response slope could not be
determined. Using an LDso of >36.3 jig a.i./bee results in RQs less than 1.9 and 0.21 for small
and large insects, respectively; however, it is not clear if the actual RQs are above or below the
interim LOG of 0.05 for acute risk to endangered terrestrial invertebrates.
The chance of individual effects for terrestrial invertebrates using the IECvl.l.xls spreadsheet,
the acute risk to endangered species LOG of 0.05, and default slope of 4.5 (upper and lower
bound = 2 and 9) is ~1 in 4.18E+08 (with upper and lower bounds of ~1 in 216, and ~1 in
1.75E+31).
As stated above, in the submitted honey bee study, a concentration of 284 ppm resulted in 0.41%
mortality. Based on T-REX, a flowable alachlor application of 4 Ib a.i./acre results in EEC
values of 60 and 540 ppm for large and small insects, respectively. Therefore, the concentration
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on the site of application at the maximum allowable application rate is not expected to reach
levels high enough to cause 0.41% mortality in large insects.
For small insects, the concentration on the site of application is expected to be 1.9 times the
concentration that would result in 0.41% mortality. AgDRIFT (Tier I ground application, Very
Fine to Fine ASAE droplet size distribution) was used to model the fraction of applied pesticide
that is predicted to be 5 ft (1.5 m) off the field. The resulting fraction of applied pesticide is 45%
(i.e.., 1.79 Ib a.i./A). Inputting an application rate of 1.79 Ib a.i./acre into T-REX results in EECs
of 242 ppm for small insects, which is below the concentration that resulted in 0.41% mortality
in adult bees. Therefore, the concentration of alachlor >5 ft from the site of application is not
expected to reach levels high enough to cause even 0.41% mortality in small insects based on the
available honey bee data.
Therefore, the Agency concludes that the potential for alachlor use to impact terrestrial
invertebrate populations to levels high enough to impact the CRLF is low and discountable.
5.2.3.2. Mammals
Terrestrial-phase CRLFs consume small mammals. This assessment used a 15 g mammal as a
potential mammalian prey. Several RQs for mammals exceed the Agency's acute risk to listed
species LOG, however, the only RQs that exceed the Agency's acute risk LOG for non-listed
mammals are for alachlor applications via impregnated bulk fertilizer [RQs = 1.36 (corn and
sorghum) and 1.02 (soybeans)]. Assuming a default probit slope of 4.5, the probability of an
individual effect would be approximately 1 in 1.4 and 1 in 2 for the RQs 1.4 and 1.0,
respectively. Assuming that probability of an individual effect provides insight into the potential
for reductions in a local population of small mammals, a probability of 1 in 1 to 2 could result in
a measurable impact to mammal abundance on and/or around alachlor application sites (corn,
sorghum, soybeans) and could, therefore, constitute a potentially significant effect.
Regarding the potential for impacts from chronic exposure, almost all of the RQs for chronic
exposure exceed the Agency's chronic risk LOG for non-listed mammals [all alachlor
use/application combinations, dietary- and dose-based for 15 g mammal (all dietary categories)].
The RQs range from 0.3 (cotton; flowable bare soil application; seed-eating mammal, dietary-
based) to 278 (corn, sorghum, peanuts, woody ornamentals, and sunflowers; flowable, non-bare
soil application; mammal that eats short grass, dose-based). These RQs are based on a NO AEG
of 30 mg/kg-diet (the highest concentration tested) from a 3-generation rat study in which no
reproductive effects were observed (i.e., no reproductive LOAEC was determined) (MRID
00075062). Therefore, the actual NO AEG for reproductive effects is likely higher than 30
mg/kg-diet. How much higher is unknown at this time.
In the 3-generation study, there were some systemic effects at 30 mg/kg-diet [kidney
discoloration and decreased kidney weights and lower ovary weights in females of each parental
generation and the FS females (maximal decrease of 17%)]. However, none of these effects were
correlated with growth, survival, or reproductive endpoints.
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Therefore, the Agency concludes that the potential for alachlor use to impact mammalian prey
populations to levels high enough to impact the CRLF is low and discountable.
5.2.3.3. Amphibians
CRLF are known to prey on aquatic-phase amphibians. The potential risk to amphibians based
on fish toxicity data is expected to be low based on the RQs (i.e., all RQs < 0.05). Additionally,
using the acute toxicity endpoints for the African clawed frog (African clawed frog; LC50 = 6.1
mg a.i./L) results in no LOG exceedances for any alachlor use. Therefore, indirect effects to
CRLF from a decline in potential aquatic phase amphibian prey are not expected from the use of
alachlor in California.
Terrestrial amphibian prey of the CRLF include small amphibians such as tree frogs that do not
prey on mammals. Therefore, the mammalian food group is not relevant in the evaluation of
potential reductions in amphibian prey abundance. The RQs for acute and sub-acute dietary
exposure from T-HERPS range from 0 to 0.01 (acute) and 0.01 to 0.10 (sub-acute) (including
only the broadleaf plants/small insects and fruits/pods/seeds/large insect dietary categories) (see
above). Therefore, none of the RQs for acute or sub-acute exposure exceed the Agency's acute
risk LOG for non-listed terrestrial animals. This indicates that the risk for indirect adverse
effects to the CRLF from loss of amphibian prey after acute or sub-acute exposure to alachlor is
low.
For chronic exposure, however, all of the alachlor uses exceed the Agency's chronic risk to non-
listed species LOG of 1 for at least one of the relevant dietary categories (chronic RQs for the
broadleaf plants/small insects and fruits/pods/seeds/large insect dietary categories range from
>0.60 to >10.8). However, since a definitive NOAEC was not determined for birds (i.e.,effects
were seen at all treatment levels) all of the calculated RQs for chronic exposure are greater-than
values. Therefore, risks to terrestrial-phase amphibians from chronic exposure cannot be
precluded for any of the alachlor uses at this time.
Again, it is difficult to determine if potential effects from chronic exposure to alachlor would
impact terrestrial amphibian abundance to an extent that could result in indirect effects to the
CRLF; however, such impacts cannot be precluded at this time based upon available
information. Therefore, the Agency concludes that there exists the potential for alachlor use to
impact terrestrial phase amphibian prey populations to levels high enough to impact the CRLF.
5.2.3.4. Potential Effects to Habitat
Aquatic plants serve several important functions in aquatic ecosystems. Non-vascular aquatic
plants are primary producers and provide the autochthonous energy base for aquatic ecosystems.
Vascular plants provide structure, rather than energy, to the system, as attachment sites for many
aquatic invertebrates, and refugia for juvenile organisms, such as fish and frogs. Emergent
plants help reduce sediment loading and provide stability to nearshore areas and lower
streambanks. In addition, vascular aquatic plants are important as attachment sites for egg
masses of aquatic species. Results of the indirect effects assessment are used as the basis for the
habitat modification analysis. From spray drift alone, impacts to non-vasular aquatic plants are
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expected up to 216 ft (0.07 m) and 151 ft (0.05 m) from application sites for corn and dry beans
(the two most common alachlor uses in California), respectively (see Section 5.2.4 and Table
5.13). Based on the downstream dilution analysis, effects to aquatic plants could extend up to
285 km from use sites for the corn and woody ornamental (nursery) uses. Therefore, impacts to
aquatic plants found near alachlor use sites are expected.
Terrestrial plants serve several important habitat-related functions for the listed assessed species.
Among other things, riparian vegetation helps to maintain the integrity of aquatic systems by
providing bank and thermal stability, serving as a buffer to filter out sediment, nutrients, and
contaminants before they reach the watershed, and serving as an energy source (CRLF and DS).
In addition to providing shelter and cover from predators while foraging, upland vegetation,
including grassland and woodlands, provides cover during dispersal (CRLF).
Based on the results of the submitted terrestrial plant toxicity studies and the reported terrestrial
plant incidents, the herbicide alachlor is phytotoxic to many plant species (seedling emergence
endpoints are more sensitive than vegetative vigor endpoints). Additionally, monocots are more
sensitive to alachlor than are dicots, based on available data. However, for adjacent upland and
wetland plants, terrestrial plant RQs for both monocots and dicots exceed the Agency's risk to
non-listed species LOG for all alachlor uses and application types. For the drift only RQs, all of
the RQs exceed the Agency's LOG except for the impregnated bulk fertilizer applications (all
uses) and the dicot RQs for the cotton use (all application types). Based on the spray drift
analysis, effects to terrestrial plants could occur >800 ft (>0.24 km) from alachlor application
sites (see Section 5.2.4).
A general conclusion that can be drawn from these data is that the inhibition of new growth may
occur in non-target terrestrial plants from registered uses of alachlor. Inhibition of new growth
could result in degradation of high quality riparian habitat over time because as older growth dies
from natural or anthropogenic causes, plant biomass may be prevented from being replenished in
the riparian area. Inhibition of new growth may also slow the recovery of degraded riparian
areas that function poorly due to sparse vegetation because alachlor deposition onto bare soil
would be expected to inhibit the growth of new vegetation. Additionally, because effects were
seen in most species tested in the seedling emergence and vegetative vigor studies, it is likely
that many species of herbaceous plants could be potentially affected by exposure to alachlor.
It is difficult to estimate the magnitude of potential impacts of alachlor use on riparian habitat
and the magnitude of potential effects on stream water quality from such impacts as they relate to
survival, growth, and reproduction of the CRLF and DS. The level of exposure and any resulting
magnitude of effect on riparian vegetation are expected to be highly variable and dependent on
many factors. The extent of runoff and/or drift into stream corridor areas is affected by the
distance the alachlor use site is offset from the stream, local geography, weather conditions, and
quality of the riparian buffer itself. The sensitivity of the riparian vegetation is dependent on the
susceptibility of the plant species exposed to alachlor and composition of the riparian zone (e.g.
vegetation density, species richness, height of vegetation, width of riparian area).
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In summary, terrestrial and aquatic plant RQs are above plant LOCs for all uses; therefore,
labeled use of alachlor has the potential to affect both aquatic and riparian vegetation within
CRLF and DS habitats.
5.2.4 Spatial Extent of Potential Effects
Since this assessment defines taxa that are predicted to be exposed through runoff and drift to
alachlor at concentrations above the Agency's LOG, analysis of the spatial extent of potential
effects requires expansion of the area from the treated site to include all areas where risk to the
CRLF and/or the DS exceed LOCs.
To determine this area, the footprint of alachlor's use pattern is identified, using corresponding
land cover data. The spatial extent of the effects determination also includes areas beyond the
initial area of concern that may be impacted by runoff and/or spray drift (potential use areas +
distance down stream or down wind from use sites where organisms relevant to the CRLF and/or
DS may be affected). The determination of the buffer distance and downstream dilution for
spatial extent of the effects determination is described below.
5.2.4.1. Spray Drift
In order to determine terrestrial and aquatic habitats of concern due to alachlor exposures
through spray drift, it is necessary to estimate the distance that spray applications can drift from
the treated area and still be present at concentrations that exceed levels of concern. Applications
of alachlor via impregnated bulk fertilizer are not expected to result in any spray drift (they are
considered similar to granular applications for modeling purposes). For the flowable uses, a
quantitative analysis of spray drift distances was completed using AgDRIFT (v. 2.01) using
default inputs for ground applications (i.e., high boom, ASAE droplet size distribution = Very
Fine to Fine, 90th data percentile), except for the analyses for cotton which used labeled
restrictions (i.e., high boom, ASAE droplet size distribution = Fine to Medium/Coarse, 90th data
percentile).
For direct effects to the terrestrial-phase CRLF, the RQs for 20 g birds that eat small insects were
used to estimate the fraction of the application rates that would no longer exceed the listed
species LOG (i.e., fraction of applied = LOC/RQ). This number was used in AgDRIFT to
calculate the distance from the field where the amount of alachlor that equaled the 'fraction of
applied' would be expected to occur (as spray drift) (Table 5.12). For direct effects to aquatic-
phase CRLF and DS, the distance from the site of application in which spray drift could reach
levels high enough to exceed the acute risk to endangered species LOG, the 'active rate' (i.e., the
highest maximum labeled rate) and the 'initial average concentration' (i.e., LCso value X 0.05)
were inputted into AgDRIFT. For this analysis, the farm pond (i.e., a pond with a depth of 2
meters and a downwind width of 63.61 m and flight line width of 157.21 m) was used as a proxy
for CRLF and DS habitat. The other AgDRIFT inputs were the same as described above in the
terrestrial distance analysis.
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Table 5.12. Distance from Alachlor Use Site Needed to Reduce Exposure from Spray Drift
to Levels that Do Not Exceed LOCs for Direct Effects.
Use Site
Corn
Sweet corn
Sorghum
Peanuts
Woody ornamentals (nursery)
Woody ornamentals (residential)
Sunflowers
Soybeans
Dry beans
Lima beans
Cotton
Appl. Rate
(Ib
a.i./acre)
4
3
2
Terrestrial-phase CRLF
RQ
0.57
0.43
0.28
Distance
from Site of
Appl. (in ft)
16.4
13.1
3.3
Aquatic-phase
CRLF and DS
Distance from Site
of Appl. (in ft)
0
0
0
For indirect effects, a spray drift analysis is conducted using endpoints for terrestrial and aquatic
plants (the most sensitive taxa to alachlor). The distance from the field for terrestrial plants is
based on the most sensitive terrestrial plant non-listed species endpoint (i.e., monocot seedling
emergence EC25 = 0.0067 Ib a.i./acre). This endpoint is used to estimate the fraction of the
application rates that would no longer exceed the 25% level of effects for terrestrial plants (i.e.,
fraction of applied = 0.0067 Ib a.i./acre divided by the application rate in Ib a.i./acre) (Table 4.2).
For aquatic plants, the RQ for the most sensitive aquatic plant (i.e., non-vascular plant EC50 =
1.64 jig a.i./L) is used to estimate the initial average concentration that would no longer exceed
the LOG for plants (/.e.,ECso X 1). This number is used in AgDRIFT to calculate the distance
from the field where the amount of alachlor that equals the 'initial average concentration' would
be expected to occur (as spray drift) (Table 5.13).
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Table 5.13. Distance from Alachlor Use Site Needed to Reduce Exposure from Spray Drift
to Levels that Do Not Exceed LOCs for Indirect Effects.
Use Site
Corn
Sorghum
Peanuts
Woody
ornamentals
Sunflowers
Soybeans
Dry beans
Lima beans
Cotton
Appl.
Rate (Ib
a.i./acre)
4
3
2
Terrestrial Plants
Distance from Site of
Appl. (in ft)
886
748
246
Aquatic Plants
Distance from Site of
Appl. (in ft)
216
151
85
Therefore, when only spray drift is considered, potential risks for both direct and indirect effects
would be below concern levels at distances from alachlor use sites equal to or greater than 886 ft
(0.27 km)
5.2.4.2 Downstream Dilution Analysis
The maximum downstream extent of alachlor exposure in streams and rivers where the EEC can
potentially be above levels that would exceed LOCs was estimated to determine the potential
areas of effect for CRLF and DS in aquatic environments (see Appendix N for details). For
potential direct effects to aquatic-phase CRLF and DS, none of the RQs for fish exceed the
Agency's listed species LOG. Therefore, the potential for direct effects to aquatic-phase CRLF
and DS is low from all uses.
Considering the potential for indirect effects, for the DS (based on the chronic endpoint for
estuarine/marine invertebrates) the area of potential effects extends to >43.4 km from residential
use sites (woody ornamentals) and >285 km from application sites for corn and woody
ornamentals (nursery). For aquatic-phase CRLF (based on toxicity data for non-vascular aquatic
plants) the area of potential effects extends up to 5 km from residential use sites (woody
ornamentals); 285 km from woody ornamentals (nursery) and corn use sites.
5.2.4.3. Overlap of Potential Areas of Effect and CRLF and DS Habitat
The spray drift and downstream dilution analyses help to identify areas of potential effect to the
CRLF and DS from registered uses of alachlor. The potential area of effects for the CRLF and
DS from alachlor spray drift extend from the site of application to 0.27 km from the site of
application depending on the use. For exposure to runoff and spray drift, the area of potential
effects extends up to 285 km downstream from the site of application (again, depending on the
use). When these distances are added to the footprint of the initial area of concern (which
represents potential alachlor use sites) and compared to CRLF and DS habitat, there are several
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areas of overlap (Figures 5.1 and 5.2). The overlap between the areas of effect and CRLF and
DS habitat, including designated critical habitat, indicates that alachlor use in California has the
potential to affect the CRLF and DS.
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Alachlor Use & CRLF Habitat Overlap
*•"?.
; Alachlor use &CRLF habitat overhp
CNDDB occurrence sections
| Critical habitat
Core areas
County boundaries
i Kilo meters
0 2040 80 120 160
Compiled from California County boundaries (ESRI, 2002),
USDA Gap Analysis Program Orchard/Vineyard Landcover (GAP)
National Land Cover Database (NLCD) (MRLC, 2001)
Map created by US Environmental Protection Agency, Office
of Pesticides Programs, Environmental Fate and Effects Division.
Projection:AlbersEqualAreaConicUSGS,NorthAmerican
Datum of 1983 (NAD 1983).
3/20/2009
Figure 5.1. Overlap Map: CRLF Habitat and Alachlor Initial Area of Concern.
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Alachlor Use Sites
& Delta Smelt Habitat
Delta smelt critical habitat
Overlap of alachlor use & DS habitat
DS_sect
Cultivated crop use
Developed land use (high, med, low, open)
CA counties
v/
J >.
J^ l" I \
•f -J t jf'l,
f. * •*,
Map created by US EPA on 04/15/09. Projection: Alters Equal Area
Conic USGS, North American Datum of 1983 (NAD 1983). California
county boundaries, source: ESRI 2002. Water bodies, source:
NHDPIus2006. DS occurrence section information obtained from:
Case No. 07-2794JCS). DS critical habitat obtained from
http://crithab.lws.gov/.
24 B Miles
i i I i i i I
1;475,000
Figure 5.2. Overlap Map: DS Habitat and Alachlor Initial Area of Concern.
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5.3. Effects to Designated Critical Habitat
The risk conclusions for the designated critical habitat are based on conclusions described for
indirect effects previously described. Potential effects to habitat is described below.
5.3.1. CRLF
5.3.1.1. Aquatic-Phase PCEs
Three of the four assessment endpoints for the aquatic-phase primary constituent elements
(PCEs) of designated critical habitat for the CRLF are related to potential effects to aquatic
and/or terrestrial plants:
• Alteration of channel/pond morphology or geometry and/or increase in sediment
deposition within the stream channel or pond: aquatic habitat (including riparian
vegetation) provides for shelter, foraging, predator avoidance, and aquatic dispersal for
juvenile and adult CRLFs.
• Alteration in water chemistry/quality including temperature, turbidity, and oxygen
content necessary for normal growth and viability of juvenile and adult CRLFs and their
food source.
• Reduction and/or modification of aquatic-based food sources for pre-metamorphs (e.g.,
algae).
Conclusions for potential indirect effects to the CRLF via direct effects to aquatic and terrestrial
plants are used to determine whether effects to critical habitat may occur. As previously
discussed, alachlor may cause effects to habitat by potentially impacting aquatic plants and
terrestrial plants.
The remaining aquatic-phase PCE is "alteration of other chemical characteristics necessary for
normal growth and viability of CRLFs and their food source." Alachlor may impact algae as
food items for tadpoles. Alachlor may also impact riparian areas that are predominantly grassy
or herbaceous, and the potential areas of effect overlap with designated critical habitat for the
CRLF (see Fig. 5.1). Therefore, there is a potential for effects to habitat by potentially impacting
the chemical characteristics of the habitat.
5.3.1.2. Terrestrial-Phase PCEs
Two of the four assessment endpoints for the terrestrial-phase PCEs of designated critical habitat
for the CRLF are related to potential effects to terrestrial plants:
• Elimination and/or disturbance of upland habitat; ability of habitat to support food source
of CRLFs: Upland areas within 200 ft (0.06 km) of the edge of the riparian vegetation or
drip line surrounding aquatic and riparian habitat that are comprised of grasslands,
woodlands, and/or wetland/riparian plant species that provides the CRLF shelter, forage,
and predator avoidance.
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• Elimination and/or disturbance of dispersal habitat: Upland or riparian dispersal habitat
within designated units and between occupied locations within 0.7 mi (1.1 km) of each
other that allow for movement between sites including both natural and altered sites
which do not contain barriers to dispersal.
As an herbicide, alachlor may affect sensitive terrestrial plants; information from the reported
terrestrial plant incident data support this. Additionally, risk to terrestrial plant LOCs are
exceeded for all uses and the potential areas of effect overlap with designated critical habitat for
the CRLF (see Fig. 5.1).
The third terrestrial-phase PCE is "reduction and/or modification of food sources for terrestrial-
phase juveniles and adults." To assess the impact of alachlor on this PCE, acute and chronic
toxicity endpoints for terrestrial invertebrates, mammals, and terrestrial-phase frogs are used as
measures of effects. There is a potential for habitat modification based on potential reductions in
prey base (mammals and frogs, as previously described), and, again, the areas of potential effect
overlap with CRLF critical habitat (Fig. 5.1).
The fourth terrestrial-phase PCE is based on alteration of chemical characteristics necessary for
normal growth and viability of juvenile and adult CRLFs and their food source. There is a
potential for habitat modification based on potential direct (Section 5.2.1) and indirect effects
(Sections 5.2.2) to terrestrial-phase CRLFs.
5.3.2. DS
Primary constituent elements (PCEs) of designated critical habitat for the DS include the
following:
• Spawning Habitat—shallow, fresh or slightly brackish backwater sloughs and edgewaters
to ensure egg hatching and larval viability. Spawning areas also must provide suitable
water quality (i.e., low "concentrations of pollutants) and substrates for egg attachment
(e.g., submerged tree roots and branches and emergent vegetation).
• Larval and Juvenile Transport—Sacramento and San Joaquin Rivers and their tributary
channels must be protected from physical disturbance and flow disruption. Adequate
river flow_is necessary to transport larvae from upstream spawning areas to rearing
habitat in Suisun Bay. Suitable water quality must be provided so that maturation is not
impaired by pollutant concentrations.
• Rearing Habitat—Maintenance of the 2 ppt isohaline and suitable water quality (low
concentrations of pollutants) within the estuary is necessary to provide Delta smelt larvae
and juveniles a shallow protective, food-rich environment in which to mature to
adulthood.
• Adult Migration— Unrestricted access to suitable spawning habitat in a period that may
extend from December to July. Adequate flow and suitable water qualityjnay need to be
maintained to attract migrating adults in the Sacramento and San Joaquin River channels
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and their associated tributaries. These areas also should be protected from physical
disturbance and flow disruption during migratory periods.
• PCEs also include more general requirements for habitat areas that provide essential life
cycle needs of the species such as space for individual and population growth and for
normal behavior; food, water, air, light, minerals, or other nutritional or physiological
requirements; cover or shelter; sites for breeding, reproduction, rearing (or development)
of offspring; and habitats that are protected from disturbance or are representative of the
historic geographical and ecological distributions of a species.
The potential for direct effects to the DS from alachlor use could not be precluded based on
incident data. Furthermore, it was concluded that alachlor is likely to adversely affect the DS by
potentially affecting its habitat (aquatic and terrestrial plants) and the potential areas of effect
overlap with critical habitat designated for DS (Fig. 5.2). Therefore, alachlor may also affect
critical habitat of the DS that is located in close proximity to alachlor use sites.
5.4. Effects Determinations
5.4.1 CRLF
The weight of evidence indicates that alachlor use has the potential to directly adversely affect
CRLF. The risk to aquatic-phase CRLF is low based on the RQ analyses. Although the risk to
terrestrial-phase CRLF from acute or sub-acute dietary exposure is low, the potential risk to
terrestrial-phase CRLF from chronic dietary exposure cannot be precluded and exists for all
dietary classes relevant to the CRLF (for all of the registered alachlor uses).
Regarding the potential for indirect effects, exceedance of the chronic risk to endangered species
LOG indicates that there could be some effect to sensitive aquatic invertebrates from the woody
ornamental and sunflower uses; however, such an effect would likely be insignificant to the
CRLF. Furthermore, the Agency concludes that the potential for alachlor use to impact
terrestrial invertebrate populations to levels high enough to impact the CRLF is low and
discountable. Impacts to non-vascular aquatic and terrestrial plants, however, are expected from
all of the current alachlor uses. Additionally, the Agency concludes that there exists the
potential, which cannot currently be precluded, for alachlor use to impact amphibian prey
populations to levels high enough to impact CRLF. Spatial analyses show that potential areas of
effect from alachlor use overlap with CRLF habitat and their designated critical habitat.
Therefore, the Agency makes a "may affect, and likely to adversely affect" determination for the
CRLF and a habitat effects determination for their designated critical habitat from the use of
alachlor based on the potential for direct and indirect effects and effects to the PCEs of critical
habitat.
5.4.2 DS
The weight of evidence indicates that alachlor use will not directly adversely affect DS.
Regarding the potential for indirect effects, the impact from alachlor use to estuarine/marine
invertebrate populations is not expected to be large enough to impact the DS indirectly. This,
again, is consistent with the study that investigated the effects of three pesticides (including
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alachlor) on estuaries in North Carolina from runoff from adjacent farm lands which showed no
measurable impact on the estuarine biological community adjacent to application sites (MRID
44105503). Impacts to non-vascular aquatic and terrestrial plants, however, are expected from
all of the current alachlor uses. Spatial analyses show that potential areas of effect from alachlor
use overlap with DS habitat and their designated critical habitat. Therefore, the Agency makes a
"may affect, and likely to adversely affect" determination and a a determination of potential
effects to PCEs of the designated critical habitat for the DS from the use of alachlor based on the
potential for indirect effects and effects to habitat.
The labeled use of alachlor may:
• ... directly affect terrestrial-phase CRLF by causing acute mortality or by adversely
affecting chronic growth or fecundity;
• ... indirectly affect the CRLF and the DS and/or affect their designated critical habitat by
reducing or changing the composition of the food supply;
• ... indirectly affect the CRLF and the DS and/or affect their designated critical habitat by
reducing or changing the composition of the aquatic plant community in the species' current
range, thus, affecting primary productivity and/or cover;
• ... indirectly affect the CRLF and the DS and affect their designated critical habitat by
reducing or changing the composition of the terrestrial plant community in the species' current
range;
• ... indirectly affect the CRLF and the DS and affect their designated critical habitat by
reducing or changing aquatic habitat in their current range (via modification of water quality
parameters, habitat morphology, and/or sedimentation).
6.0 Uncertainties
6.1 Exposure Assessment Uncertainties
6.1.1 Maximum Use Scenario
The screening-level risk assessment focuses on characterizing potential ecological risks resulting
from a maximum use scenario, which is determined from labeled statements of maximum
application rate and number of applications with the shortest time interval between applications.
The frequency at which actual uses approach this maximum use scenario may be dependant on
pest resistance, timing of applications, cultural practices, and market forces.
6.1.2. Impact of Vegetative Setbacks on Runoff
Unlike spray drift, models are currently not available to evaluate the effectiveness of a vegetative
setback on runoff and loadings. The effectiveness of vegetative setbacks is highly dependent on
the condition of the vegetative strip. For example, a well-established, healthy vegetative setback
can be a very effective means of reducing runoff and erosion from agricultural fields (USD A,
NRCS, 2000). Alternatively, a setback of poor vegetative quality or a setback that is channelized
can be ineffective at reducing loadings. Until such time as a quantitative method to estimate the
effect of vegetative setbacks on various conditions on pesticide loadings becomes available, the
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aquatic exposure predictions are likely to overestimate exposure where healthy vegetative
setbacks exist and underestimate exposure where poorly developed, channelized, or bare
setbacks exist.
6.1.3 Aquatic Exposure Modeling of Alachlor
The standard ecological water body scenario (EXAMS pond) used to calculate potential aquatic
exposure to pesticides is intended to represent conservative estimates, and to avoid
underestimations of the actual exposure. The standard scenario consists of application to a 10-
hectare field bordering a 1-hectare, 2-meter deep (20,000 m3) pond with no outlet. Exposure
estimates generated using the EXAMS pond are intended to represent a wide variety of
vulnerable water bodies that occur at the top of watersheds including prairie pot holes, playa
lakes, wetlands, vernal pools, human-made and natural ponds, and intermittent and lower order
streams. As a group, there are factors that make these water bodies more or less vulnerable than
the EXAMS pond. Static water bodies that have larger ratios of pesticide-treated drainage area
to water body volume would be expected to have higher peak EECs than the EXAMS pond.
These water bodies will be either smaller in size or have larger drainage areas. Smaller water
bodies have limited storage capacity and thus may overflow and carry pesticide in the discharge,
whereas the EXAMS pond has no discharge. As watershed size increases beyond 10-hectares, it
becomes increasingly unlikely that the entire watershed is planted with a single crop that is all
treated simultaneously with the pesticide. Headwater streams can also have peak concentrations
higher than the EXAMS pond, but they likely persist for only short periods of time and are then
carried and dissipated downstream.
The Agency acknowledges that there are some unique aquatic habitats that are not accurately
captured by this modeling scenario and modeling results may, therefore, under- or over-estimate
exposure, depending on a number of variables. For example, some organisms may inhabit water
bodies of different size and depth and/or are located adjacent to larger or smaller drainage areas
than the EXAMS pond. In addition, the Services agree that the existing EXAMS pond
represents the best currently available approach for estimating aquatic exposure to pesticides
(USFWS/NMFS 2004).
In general, the linked PRZM/EXAMS model produces estimated aquatic concentrations that are
expected to be exceeded once within a ten-year period. The Pesticide Root Zone Model is a
process or "simulation" model that calculates what happens to a pesticide in an agricultural field
on a day-to-day basis. It considers factors such as rainfall and plant transpiration of water, as
well as how and when the pesticide is applied. It has two major components: hydrology and
chemical transport. Water movement is simulated by the use of generalized soil parameters,
including field capacity, wilting point, and saturation water content. The chemical transport
component can simulate pesticide application on the soil or on the plant foliage. Dissolved,
adsorbed, and vapor-phase concentrations in the soil are estimated by simultaneously considering
the processes of pesticide uptake by plants, surface runoff, erosion, decay, volatilization, foliar
wash-off, advection, dispersion, and retardation.
Uncertainties associated with each of these individual components add to the overall uncertainty
of the modeled concentrations. Additionally, model inputs from the environmental fate
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degradation studies are chosen to represent the upper confidence bound on the mean values that
are not expected to be exceeded in the environment approximately 90 percent of the time.
Mobility input values are chosen to be representative of conditions in the environment. The
natural variation in soils adds to the uncertainty of modeled values. Factors such as application
date, crop emergence date, and canopy cover can also affect estimated concentrations, adding to
the uncertainty of modeled values. Factors within the ambient environment such as soil
temperatures, sunlight intensity, antecedent soil moisture, and surface water temperatures can
cause actual aquatic concentrations to differ for the modeled values.
The modeling for the residential woody ornamental uses two scenarios in tandem requiring post-
processing of the modeled output in order to derive a weighted EEC that represent the
contribution of both the pervious residential and the impervious surfaces. The residential
scenario assumes that less than 100% of the watershed of a urban/suburban system will be
treated (assuming a typical lot equals approximately 1A of an acre). For alachlor treatments to
woody ornamentals (post transplant), it was estimated that approximately 15% of the surface
area of the lot could be treated because a typical lawn would not be planted with 100% juniper or
yew (section 3). These EECs are based on potential routes of exposure and it is unlikely that
every home will be planted with juniper and yew (i.e., there are other planting options). In
general, incorporation of impervious surfaces into the exposure assessment results in increasing
runoff volume in the watershed, which tends to reduce overall pesticide exposure assuming
1.68% overspray to the impervious surface. Alternative assumptions for percent impervious
surfaces, percentage of use site treated, and percentage of overspray should be considered in
order to characterize the assumptions presented above in the context of the individual exposure
assessment and risk conclusions.
In order to account for uncertainties associated with modeling, available monitoring data were
compared to PRZM/EXAMS estimates of peak EECs for the different uses. As discussed above,
several data values were available from NAWQA, and other sources (e.g., California DPR) for
alachlor concentrations measured in surface waters receiving runoff from agricultural areas.
However, there is only a limited dataset relevant to potential exposure in California. For the
NAWQA data, the specific use patterns (e.g. application rates and timing, crops) associated with
the agricultural areas are unknown, however, they are assumed to be representative of potential
alachlor use areas. Use information is well correlated with the California DPR surface water
data, as the Cal PUR data is of high quality at the county level. Use information for other data
sources is unknown.
6.1.4. Uncertainties Regarding Dilution and Chemical Transformations in
Estuaries
PRZM-EXAMS modeled EECs were initially calibrated to represent relatively small ponds and
low-order streams. Therefore it would seem likely that results from the PRZM-EXAMS model
should greatly over-estimate potential concentrations in much larger receiving water bodies such
as estuaries, embayments, and coastal marine areas; chemicals in runoff water (or spray drift,
etc.) should simply be diluted by a much larger volume of water than would be found in the
'typical' EXAMS pond. However, as chemical constituents in water draining from freshwater
streams encounter brackishness or other near-marine-associated conditions, there is potential for
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important chemical transformations to occur. Many chemical compounds can undergo changes
in mobility, toxicity, or persistence when changes in pH, conductivity (Eh), salinity, dissolved
oxygen (DO) content, or temperature are encountered. For example, desorption and re-
mobilization of some chemicals from sediments can occur with changes in salinity (e.g., Means
1995; Swarzenski etal. 2003; Jordan etal. 2008), changes in pH (e.g., Wood and Baptista 1993;
Parikh et al. 2004; Fernandez et al. 2005), Eh changes (Wood and Baptista 1993; Velde and
Church 1999), and other factors. Thus, although chemicals in discharging rivers may be diluted
by large volumes of water within receiving estuaries and embayments, the hydrochemistry of the
marine-influenced water may negate some of the attenuating impact of the greater water volume;
for example, the effect of dilution may be partly counteracted by increased mobility of a
chemical in brackish water. In addition, freshwater contributions from discharging streams and
rivers do not instantaneously mix with more saline water bodies. In these settings, water will
commonly remain highly stratified, with fresh water lying atop denser, heavier saline water -
meaning that exposure to concentrations found in discharging stream water may propagate some
distance beyond the outflow point of the stream (especially near the water surface).
Therefore, EFED does not automatically assume that discharging water will be rapidly diluted by
the entire water volume within an estuary, embayment, or other coastal aquatic environment;
PRZM-EXAMS model results should be considered consistent with concentrations that might be
found near the head of an estuary unless there is specific information to indicate otherwise.
Conditions nearer to the mouth of a bay or estuary, however, may be closer to a marine-type
system, and thus more subject to the notable buffering, mixing, and diluting capacities of an open
marine environment. Conversely, tidal effects (pressure waves) can propagate much further
upstream than the actual estuarine water, so discharging river water may become temporarily
partially impounded near the mouth (discharge point) of a channel, and resistant to mixing until
tidal forces are reversed.
6.1.4 Ground Water Uncertainties
Although the potential impact of discharging ground water on CRLF populations is not explicitly
delineated, it should be noted that, in some areas of the country, ground water could provide a
source of pesticide to surface water bodies - especially low-order streams, headwaters, and
ground water-fed pools. This is particularly likely if the chemical is persistent and mobile, the
pesticide is applied to highly permeable soils overlying shallow unconfmed ground water, and
rainfall is sufficient to drive the chemical through the soil to ground water. Soluble chemicals
that are primarily subject to photolytic degradation will be very likely to persist in ground water,
and can be transportable over long distances. Similarly, many chemicals degrade slowly under
anaerobic conditions (common in aquifers) and are thus more persistent in ground water. Under
the right hydrologic conditions, this ground water may eventually be discharged to the surface -
often supporting stream flow in the absence of rainfall. Continuously flowing low-order streams
in particular are sustained by ground water discharge, which can constitute 100% of stream flow
during baseflow (no runoff) conditions. Thus, it is important to keep in mind that pesticides in
ground water may impact surface water quality during base flow conditions with subsequent
impact on CRLF habitats. However, many smaller streams in CA are net dischargers of water to
ground water that go dry during portions of the year and are not supplied by baseflow from
ground water.
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Although concentrations in a receiving water body resulting from ground water discharge cannot
be explicitly quantified, it should be assumed that significant attenuation and retardation of the
chemical will have occurred prior to discharge. Nevertheless, where alachlor is applied to highly
permeable soils over shallow ground water where there is a net recharge to adjacent streams,
ground water could still be a consistent source of chronic background concentrations in surface
water, and may also add to surface runoff during storm events (as a result of enhanced ground
water discharge typically characterized by the 'tailing limb' of a storm hydrograph).
6.1.5 Usage Uncertainties
County-level usage data were obtained from CDPR PUR database. Eight years of data (1999 -
2006) were included in this analysis because statistical methodology for identifying outliers, in
terms of area treated and pounds applied, was provided by CDPR for these years only. CDPR
PUR documentation indicates that errors in the data may include the following: a misplaced
decimal; incorrect measures, area treated, or units; and reports of diluted pesticide
concentrations. In addition, it is possible that the data may contain reports for pesticide uses that
have been cancelled. The CPDR PUR data does not include home owner applied pesticides;
therefore, residential uses are not likely to be reported. As with all pesticide usage data, there
may be instances of misuse and misreporting. The Agency made use of the most current,
verifiable information; in cases where there were discrepancies, the most conservative
information was used.
6.1.6 Terrestrial Exposure Modeling of Alachlor
The Agency relies on the work of Fletcher et al. (1994) for setting the assumed pesticide residues
in wildlife dietary items. These residue assumptions are believed to reflect a realistic upper-
bound residue estimate, although the degree to which this assumption reflects a specific
percentile estimate is difficult to quantify. It is important to note that the field measurement
efforts used to develop the Fletcher et al. (1994) estimates of exposure involve highly varied
sampling techniques. It is entirely possible that much of this data reflects residues averaged over
entire above ground plants in the case of grass and forage sampling.
It was assumed that ingestion of food items in the field occurs at rates commensurate with those
in the laboratory. Although the screening assessment process adjusts dry-weight estimates of
food intake to reflect the increased mass in fresh-weight wildlife food intake estimates, it does
not allow for gross energy differences. Direct comparison of a laboratory dietary concentration-
based effects threshold to a fresh-weight pesticide residue estimate would result in an
underestimation of field exposure by food consumption by a factor of 1.25 - 2.5 for most food
items.
Differences in assimilative efficiency between laboratory and wild diets suggest that current
screening assessment methods do not account for a potentially important aspect of food
requirements. Depending upon species and dietary matrix, bird assimilation of wild diet energy
ranges from 23 - 80%, and mammal's assimilation ranges from 41 - 85% (USEPA, 1993). If it
is assumed that laboratory chow is formulated to maximize assimilative efficiency (e.g., a value
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of 85%), a potential for underestimation of exposure may exist by assuming that consumption of
food in the wild is comparable with consumption during laboratory testing. In the screening
process, exposure may be underestimated because metabolic rates are not related to food
consumption.
For the terrestrial exposure analysis of this risk assessment, a generic bird or mammal was
assumed to occupy either the treated field or adjacent areas receiving a treatment rate on the
field. Actual habitat requirements of any particular terrestrial species were not considered, and it
was assumed that species occupy, exclusively and permanently, the modeled treatment area.
Spray drift model predictions suggest that this assumption leads to an overestimation of exposure
to species that do not occupy the treated field exclusively and permanently.
6.1.7 Spray Drift Modeling
Factors, including variations in topography, cover, and meteorological conditions over the
transport distance are not accounted for by the AgDRIFT model (i.e., it models spray drift from
aerial and ground applications in a flat area with little to no ground cover and a steady, constant
wind speed and direction). Therefore, in most cases, the drift estimates from AgDRIFT may
overestimate exposure, especially as the distance increases from the site of application, since the
model does not account for potential obstructions (e.g., large hills, berms, buildings, trees, etc}.
Furthermore, conservative assumptions are made regarding the droplet size distributions being
modeled ('ASAE Very Fine to Fine') and boom height ('High') unless spray drift restrictions are
specified on the label. Alterations in any of these inputs would decrease the area of potential
effect.
6.2 Effects Assessment Uncertainties
6.2.1 Age Class and Sensitivity of Effects Thresholds
It is generally recognized that test organism age may have a significant impact on the observed
sensitivity to a toxicant. The acute toxicity data for fish are collected on juvenile fish between
0.1 and 5 grams. Aquatic invertebrate acute testing is performed on recommended immature age
classes (e.g., first instar for daphnids, second instar for amphipods, stoneflies, mayflies, and third
instar for midges).
Testing of juveniles may overestimate toxicity at older age classes for pesticide active
ingredients that act directly without metabolic transformation because younger age classes may
not have the enzymatic systems associated with detoxifying xenobiotics. In so far as the
available toxicity data may provide ranges of sensitivity information with respect to age class,
this assessment uses the most sensitive life-stage information as measures of effect for surrogate
aquatic animals, and is therefore, considered as protective.
6.2.2 Impact of Multiple Stressors on the Effects Determination
The influence of length of exposure and concurrent environmental Stressors to the CRLF and the
DS (i.e., construction of dams and locks, fragmentation of habitat, change in flow regimes,
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increased sedimentation, degradation of quantity and quality of water in the watersheds of the
action area, predators, etc.) will likely affect the species' response to alachlor. Additional
environmental stressors may increase sensitivity to the herbicide, although there is the possibility
of additive/synergistic reactions. Timing, peak concentration, and duration of exposure are
critical in terms of evaluating effects, and these factors are expected to vary both temporally and
spatially within the action area. Overall, the effect of this variability may result in either an
overestimation or underestimation of risk. However, as previously discussed, the Agency's
LOCs are set to be protective given the wide range of possible uncertainties.
6.2.3. Use of Surrogate Species Effects Data
Freshwater fish are used as surrogate species for aquatic-phase amphibians. Some data are
available on alachlor that evaluated its toxicity to amphibians. Overall, these data do not suggest
that amphibians are more sensitive than fish to alachlor. Therefore, endpoints based on
freshwater fish ecotoxicity data are assumed to be protective of potential direct effects to aquatic-
phase amphibians including the CRLF, and extrapolation of the risk conclusions from the most
sensitive tested species to the aquatic-phase CRLF is likely to overestimate the potential risks to
those species. Efforts are made to select the organisms most likely to be affected by the type of
compound and usage pattern; however, there is an inherent uncertainty in extrapolating across
phyla. In addition, the Agency's LOCs are intentionally set very low, and conservative estimates
are made in the screening level risk assessment to account for these uncertainties.
6.2.5. Sublethal Effects
The assessment endpoints used in ecological risk assessment include potential effects on
survival, growth, and reproduction of the CRLF and the DS and organisms on which these
species depend for survival and reproduction such as invertebrates. A number of studies were
located that evaluated potential sublethal effects to fish from exposure to alachlor. Although
many of these studies reported toxicity values that were less sensitive than the submitted studies,
they were not considered for use in risk estimation (see Appendix K).
EPA is required under the FFDCA, as amended by FQPA, to develop a screening program to
determine whether certain substances (including all pesticide active and other ingredients) "may
have an effect in humans that is similar to an effect produced by a naturally occurring estrogen,
or other such endocrine effects as the Administrator may designate." Following the
recommendations of its Endocrine Disrupter Screening and Testing Advisory Committee
(EDSTAC), EPA determined that there were scientific bases for including, as part of the
program, androgen and thyroid hormone systems, in addition to the estrogen hormone system.
EPA also adopted EDSTAC's recommendation that the Program include evaluations of potential
effects in wildlife. When the appropriate screening and/or testing protocols being considered
under the Agency's Endocrine Disrupter Screening Program (EDSP) have been developed and
vetted, alachlor may be subjected to additional screening and/or testing. For further information
on the status of the Endocrine Disrupter Screening Program please visit our website:
http://www.epa.gov/endo/.
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6.2.6. Exposure to Pesticide Mixtures
In accordance with the Overview Document and the Services Evaluation Memorandum (USEPA,
2004; USFWS/NMFS, 2004), this assessment considers the single active ingredient of alachlor.
However, the assessed species and its environments may be exposed to multiple pesticides
simultaneously. Interactions of other toxic agents with alachlor could result in additive effects,
more than additive effects, or less than additive effects. As previously discussed, evaluation of
pesticide mixtures is beyond the scope of this assessment because of the myriad of factors that
cannot be quantified based on the available data. Those factors include identification of other
possible co-contaminants where the CRLF and the DS reside and their concentrations,
differences in the pattern and duration of exposure among contaminants, and the differential
effects of other physical/chemical characteristics of the receiving waters (e.g. organic matter
present in sediment and suspended water). Evaluation of factors that could influence
additivity/synergism/antagonism is beyond the nature and quality of the available data to allow
for an evaluation. However, it is acknowledged that not considering mixtures could over- or
under-estimate risks depending on the type of interaction and factors discussed above.
6.3. Uncertainty in the Potential Effect to Riparian Vegetation vs. Water Quality
Impacts
Effects to riparian vegetation were evaluated using submitted guideline seedling emergence and
vegetative vigor studies. LOCs were exceeded for seedling emergence and vegetative vigor
endpoints with the seedling emergence endpoint being considerably more sensitive. Based on
LOG exceedances and the lack of readily available information to allow for characterization of
riparian areas of the CRLF and the DS, it was concluded that alachlor use is likely to adversely
affect these species by potentially impacting grassy/herbaceous riparian vegetation resulting in
increased sedimentation. However, soil retention/sediment loading is dependent on a number of
factors including land management and tillage practices. Use of herbicides (including alachlor)
may be incorporated into a soil conservation plan. Therefore, although this assessment
concludes that alachlor is likely to adversely affect the assessed listed species and their
designated critical habitat by potentially impacting sensitive herbaceous riparian areas, it is
possible that adverse impacts on sediment loading may not occur in areas where soil retention
strategies are used.
6.2.4 Location of Wildlife Species
For the terrestrial exposure analysis of this risk assessment, a generic bird or mammal was
assumed to occupy either the treated field or adjacent areas receiving a treatment rate on the
field. Actual habitat requirements of any particular terrestrial species were not considered, and it
was assumed that species occupy, exclusively and permanently, the modeled treatment area.
Spray drift model predictions suggest that this assumption leads to an overestimation of exposure
to species that do not occupy the treated field exclusively and permanently.
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7.0 Risk Conclusions
Based on the best available information, the Agency makes a May Affect, and Likely to
Adversely Affect (LAA) determination for the CRLF and the DS from the labeled uses of
alachlor as described in Table 7.1. The effects determination is based on potential direct and
indirect effects to terrestrial-phase CRLF and indirect effects to aquatic-phase CRLF and the DS.
The LAA determination applies to all currently registered alachlor uses in California.
Additionally, the Agency has determined that there is the potential for effects to designated
critical habitat of the CRLF and the DS from the use of the alachlor. A summary of the risk
conclusions and effects determinations for each listed species assessed and their designated
critical habitat is presented in Tables 7.1 and 7.2. Further information on the results of the
effects determination is included as part of the Risk Description in Section 5.2. Given the LAA
determination for the CRLF and the DS and potential effects to designated critical habitat for
both species, a description of the baseline status and cumulative effects for the CRLF is provided
in Attachment 2 and the baseline status and cumulative effects for the DS is provided in
Attachment 4.
Table 7.1.
DS.
Effects Determination Summary for Effects of Alachlor on the CRLF and the
Species
California red-
legged frog
(Rana aurora
draytonii)
Delta Smelt
(Hypomesus
transpacificus)
Effects
Determination 1
LAA1
LAA1
Basis for Determination
Potential for Direct Effects
Aquatic-phase (Eggs, Larvae, and Adults):
None of the RQs for freshwater fish (used as a surrogate for aquatic -phase
amphibians) exceed the Agency's LOCs for any registered alachlor use.
Terrestrial-phase (Juveniles and Adults):
The risk of direct adverse effects to terrestrial-phase CRLF from acute or sub-
acute dietary exposure is low. However, the risk (or potential risk) to terrestrial-
phase CRLF from chronic dietary exposure cannot be precluded and exists for all
dietary classes relevant to the CRLF (for all of the registered alachlor uses).
Potential for Indirect Effects
Aquatic prey items, aquatic habitat, cover and/or primary productivity
Alachlor could potentially impact terrestrial and aquatic plants to an extent that
could result in indirect effects to the CRLF.
Terrestrial prey items, riparian habitat
CRLFs could be affected as a result of potential impacts to grassy /herbaceous
vegetation. Potential effects to amphibian food item abundance that may
indirectly affect terrestrial phase CRLFs could not be precluded.
Potential for Direct Effects
None of the RQs for freshwater fish exceed the Agency's LOCs for any
registered alachlor use.
Potential for Indirect Effects
Labeled uses of alachlor have the potential to adversely affect the DS by
reducing available food (aquatic plants), by impacting the riparian habitat of
grassy and herbaceous riparian areas, and/or by impacting water quality via
effects to aquatic vegetation.
May affect, likely to adversely affect (LAA)
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Table 7.2. Effects Determination Summary for Alachlor Use and CRLF and DS Critical
Habitat Impact Analysis.
Assessment
Endpoint
Effects
Determination
Basis for Determination
Modification of
aquatic-phase PCEs
(DS and CRLF)
Habitat Effects
As described in Table 7.1., the effects determination for the potential for
alachlor to affect aquatic-phase CRLFs and the DS is LAA. These
determinations are based on the potential for alachlor to indirectly affect the
DS and aquatic-phase CRLF. Additionally, the potential areas of effect
overlap with critical habitat designated for the CRLF and DS. Therefore,
potential effects to aquatic plants and terrestrial (riparian) plants identified in
this assessment could result in aquatic habitat modification.
Modification of
terrestrial-phase PCE
(CRLF)
As described in Table 7.1., the effects determination for the potential for
alachlor to affect terrestrial-phase CRLFs is LAA. This determination is based
on the potential for alachlor to directly affect terrestrial-phase CRLFs and their
food supply and habitat. Additionally, the potential areas of effect overlap
with critical habitat designated for the CRLF. Therefore, these potential
effects could result in modification of critical habitat.
Based on the conclusions of this assessment, a formal consultation with the U. S. Fish and
Wildlife Service under Section 7 of the Endangered Species Act should be initiated.
When evaluating the significance of this risk assessment's direct/indirect and adverse habitat
modification effects determinations, it is important to note that pesticide exposures and predicted
risks to the listed species and its resources (i.e., food and habitat) are not expected to be uniform
across the action area. In fact, given the assumptions of drift and downstream transport (i.e..,
attenuation with distance), pesticide exposure and associated risks to the species and its resources
are expected to decrease with increasing distance away from the treated field or site of
application. Evaluation of the implication of this non-uniform distribution of risk to the species
would require information and assessment techniques that are not currently available.
When evaluating the significance of this risk assessment's direct/indirect and adverse habitat
modification effects determinations, it is important to note that pesticide exposures and predicted
risks to the species and its resources (i.e., food and habitat) are not expected to be uniform across
the action area. In fact, given the assumptions of drift and downstream transport (i.e., attenuation
with distance), pesticide exposure and associated risks to the species and its resources are
expected to decrease with increasing distance away from the treated field or site of application.
Evaluation of the implication of this non-uniform distribution of risk to the species would require
information and assessment techniques that are not currently available. Examples of such
information and methodology required for this type of analysis would include the following:
• Enhanced information on the density and distribution of CRLF and the DS life
stages within the action area and/or applicable designated critical habitat. This
information would allow for quantitative extrapolation of the present risk
assessment's predictions of individual effects to the proportion of the population
extant within geographical areas where those effects are predicted. Furthermore,
such population information would allow for a more comprehensive evaluation of
the significance of potential resource impairment to individuals of the assessed
species.
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• Quantitative information on prey base requirements for the assessed species.
While existing information provides a preliminary picture of the types of food
sources utilized by the assessed species, it does not establish minimal
requirements to sustain healthy individuals at varying life stages. Such
information could be used to establish biologically relevant thresholds of effects
on the prey base, and ultimately establish geographical limits to those effects.
This information could be used together with the density data discussed above to
characterize the likelihood of adverse effects to individuals.
• Information on population responses of prey base organisms to the pesticide.
Currently, methodologies are limited to predicting exposures and likely levels of
direct mortality, growth or reproductive impairment immediately following
exposure to the pesticide. The degree to which repeated exposure events and the
inherent demographic characteristics of the prey population play into the extent to
which prey resources may recover is not predictable. An enhanced understanding
of long-term prey responses to pesticide exposure would allow for a more refined
determination of the magnitude and duration of resource impairment, and together
with the information described above, a more complete prediction of effects to
individual species and potential modification to critical habitat.
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MRID Reference
40396301 Monsanto Co. (1987) Alachlor Product Chemistry—Response to Agency Review: R.D. No.
831. Unpublished study. 47 p.
152209 Brightwell, B.; Rueppel, M. (1976) Lasso and Ramrod: Physical Properties and Their
Relationship to the Environment: Report No. 443. Unpublished study prepared by Monsanto
Co. 14 p.
134327 Suba, L.; Pearson, D.; Malik, J. (1979) The Environmental Studies of Alachlor: RD. #258:
Report Nos. MSL-0860, MSL-0861. Final rept. (Unpublished study received Oct 11, 1979
under 524-285; submitted by Monsanto Co., Washington, DC; CDL:241135-A; 241136)
23012 Sutherland, M.L.; Curtis, T.G.; Darlington, W.A.; et al. (1972) Final Report on Lasso and the
Environment: Part 4: Photolysis of Lasso on Soil and in Water: Agricultural Research Report
No. 262. (Unpublished study received Jun 29, 1973 under 3F1372; submitted by Monsanto
Co., Washington, D.C.; CDL:093660-L)
101531 Banduhn, M.; Livingston, C.; Kloek, J.; et al. (1981) Comparative Environmental Fate and
Crop Uptake Studies of Encapsulated and Unencapsulated Alachlor: Report No. MSL-2070.
(Unpublished study received May 10, 1982 under 524-344; submitted by Mon- santo Co.,
Washington, DC; CDL:070841-B)
134327 Suba, L.; Pearson, D.; Malik, J. (1979) The Environmental Studies of Alachlor: RD. #258:
Report Nos. MSL-0860, MSL-0861. Final rept. (Unpublished study received Oct 11, 1979
under 524-285; submitted by Monsanto Co., Washington, DC; CDL:241135-A; 241136)
23014 Sutherland, M.L.; Curtis, T.G.; Darlington, W.A.; et al. (1972) Final Report on Lasso and the
Environment: Part 6: Soil Dissipa- tion of Lasso: Agricultural Research Report No. 264.
(Unpub- lished study received Jun 29, 1973 under 3F1372; submitted by Monsanto Co.,
Washington, D.C.; CDL:093660-N)
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44405301 Blumhorst, M. (1997) Soil Adsorption/Desorption of (carbon 14) Alachlor Sulfonic Acid
Metabolite (ESA) by the Batch Equilibrium Method: Lab Project Number: 97-24-M-l:
115S12: MSL-14976. Unpublished study prepared by EPL Bio-Analytical Services, Inc. 106
P-
27139 Weidner, C.W. (1974) Degradation in Groundwater and Mobility of Herbicides. Master's
thesis, Univ. of Nebraska, Dept. of Agron- omy. (Unpublished study received Jul 19, 1978
under 201-403; submitted by Shell Chemical Co., Washington, D.C.; CDL:234472-O)
27140 Lavy, T.L. (1974) Mobility and Deactivation of Herbicides in Soil- Water Systems: Project A-
024-NEB. (Available from: National Technical Information Service, Springfield, VA: PB-238
632; un- published study received Jul 19, 1978 under 201-403; prepared by Univ. of
Nebraska, Water Resources Research Institute, sub- mitted by Shell Chemical Co.,
Washington, D.C.; CDL:234472-P)
78301 Guth, J.A. (1975) CGA-24705 Leaching Model Study with the Herbicide CGA-24705 in Four
Standard Soils: Nr. SPR 3/75. (Unpublished study received Jul 23, 1981 under 100-587;
prepared by Ciba- Geigy, Ltd., Switzerland, submitted by Ciba-Geigy Corp., Greens- boro,
N.C.; CDL:245628-E)
134327 Suba, L.; Pearson, D.; Malik, J. (1979) The Environmental Studies of Alachlor: RD. #258:
Report Nos. MSL-0860, MSL-0861. Final rept. (Unpublished study received Oct 11, 1979
under 524-285; submitted by Monsanto Co., Washington, DC; CDL:241135-A; 241136)
152209 Brightwell, B.; Rueppel, M. (1976) Lasso and Ramrod: Physical Prop- erties and Their
Relationship to the Environment: Report No. 443. Unpublished study prepared by Monsanto
Co. 14 p.
42528001 Schott, M.; Schlicher, M. (1990) Terrestrial Field Dissipation of Alachlor at Two Sites in
California: Lab Project Number: MSL-10395: RD 1138. Unpublished study prepared by
Monsanto Company. 313 p.
42528002 Schlicher, M.; Schott, M. (1991) Terrestrial Field Dissipation of Alachlor Metabolites in
Chico, California: Lab Project Number: MSL-10844: 1138. Unpublished study prepared by
Monsanto Company. 251 p.
Submitted Ecotoxicity Studies:
79523 Fink, R; Beavers, J.B.; Brown, R; et al. (1979) Final Report: Acute Oral LD50~Bobwhite Quail:
Project No. 139-179. (Unpub- lished study received Jun 2, 1981 under 524-285; prepared by
Wildlife International, Ltd., submitted by Monsanto Co., Wash- ington, D.C.; CDL:245260-A)
43087001 Grimes, J.; Jaber, M. (1986) Alachlor: A Dietary LC 50 Study with the Mallard: Lab Project
Number: 139-232: WL-86-205: RD 1218. Unpublished study prepared by Wildlife International
Ltd. 31 p.
43087101 Grimes, J.; Jaber, M. (1986) Alachlor: A Dietary LC 50 Study with the Bobwhite: Lab Project
Number: RD 1217: 139-231: WL-86-206. Unpublished study prepared by Wildlife International
Ltd. 32 p.
44951501 Gallagher, S.; Beavers, J.; Jaber, M. (1999) Alachlor: A Reproduction Study with the Mallard
(Anas platyrhynchos): Lab Project Number: R.D.I 492: WL-97-144: 139-436. Unpublished study
prepared by Wildlife International, Ltd. 183 p.
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44951502 Gallagher, S.; Beavers, J.; Jaber, M. (1999) Alachlor: A Reproduction Study with the
Northern Bobwhite (Colinus virginianus): Lab Project Number: R.D.NO.1492: WL-97-145: 139-
435. Unpublished study prepared by Wildlife International, Ltd. 182 p.
43774704 Bowman, J.; Downing, J.; Hurshman, B. (1995) Acute Toxicity of MON 5775 to Rainbow
Trout (Oncorhynchus mykiss): Amended Final Report: Lab Project Number: 41729: AB-94-156:
1321. Unpublished study prepared by ABC Labs, Inc. 26 p.
43774706 Bowman, J.; Hurshman, B. (1995) Acute Toxicity of MON 5760 to Rainbow Trout
(Oncorhynchus mykiss): Final Report: Lab Project Number: 41731: AB-94-154: 1321.
Unpublished study prepared by ABC Labs, Inc. 27 p.
43774703 Bowman, J.; Hurshman, B. (1994) Acute Toxicity of MON 5775 to Daphnia magna: Final
Report: Lab Project Number: 41728: AB-94-155: RD. 1321. Unpublished study prepared by
ABC Labs, Inc. 26 p.
43774705 Bowman, P.; Hurshman, B. (1994) Acute Toxicity of MON 5760 to Dahnia magna: Final
Report: Lab Project Number: 41730: AB-94-153: 1321. Unpublished study prepared by ABC
Labs, Inc. 26 p.
44524301 Graves, W.; Swigert, J.; Krueger, H. (1998) A 96-Hour Flow-Through Acute Toxicity Test
with the Sheepshead Minnow (Cyprinodon variegatus): Alachlor: Final Report: Lab Project
Number: 1410: WL-96-189: 139A-195. Unpublished study prepared by Wildlife International
Ltd. 43 p.
44524302 Graves, W.; Swigert, J.; Krueger, H. (1998) A 96-Hour Flow-Through Acute Toxicity Test
with the Saltwater Mysid (Mysidopsis bahia): Alachlor: Final Report: Lab Project Number:
139A-196: WL-96-190: 1410. Unpublished study prepared by Wildlife International Ltd. 42 p.
44524303 Graves, W.; Swigert, J.; Krueger, H. (1998) A 96-Hour Shell Deposition Test with the Eastern
Oyster: Alachlor: Final Report: Lab Project Number: 139A-197: WL-96-191: 1410. Unpublished
study prepared by Wildlife International Ltd. 44 p.
23615 Thompson, C.M.; Forbis, A.D.; McAllister, W.A. (1978) Acute Toxic- ity of Technical Alachlor
(AB-78-166) to Bluegill Sunfish (?~Lepomis macrochirus-?). (Unpublished study received Aug
16, 1978 under 524-285; prepared by Analytical Biochemistry Labora- tories, Inc., submitted by
Monsanto Co., Washington, D.C.; CDL: 234628-C)
23616 Forbis, A.D.; McAllister, W.A. (1978) Acute Toxicity of Technical Alachlor to Rainbow Trout
(?~Salmo gairdneri). (Unpublished study received Aug 16, 1978 under 524-285; prepared by
Analyt- ical Biochemistry Laboratories, Inc., submitted by Monsanto Co., Washington, D.C.;
CDL:234628-D)
28550 Thompson, C.M.; Forbis, A.D. (1978) Acute Toxicity of Lasso (MCB/ Cg) (AB-78-111) to
Rainbow Trout (?~Salmo_gairdneri~?). (Unpub- lished study received Dec 28, 1979 under 524-
285; prepared by Analytical Bio Chemistry Laboratories, Inc., submitted by Monsanto Co.,
Washington, D.C.; CDL:241535-B)
28551 Thompson, C.M.; Forbis, A.D. (1978) Acute Toxicity of Lasso (MCB/ Cg) (AB-78-111) to
Bluegill Sunfish (?~Lepomis macro-?- ?~chirus~?). (Unpublished study received Dec 28, 1979
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under 524-285; prepared by Analytical Bio Chemistry Laboratories, Inc., submitted by Monsanto
Co., Washington, D.C.; CDL: 241535-C)
43774707 Forbis, A. (1995) Chronic Toxicity of Alachlorto Daphniamagna Under Flow-Through Test
Conditions: Final Report: Lab Project Number: 41517: AB-94-061: 1321. Unpublished study
prepared by ABC Labs, Inc. 39 p.
43862601 Rhodes, J.; Muckerman, M. (1995) Early Life-Stage Toxicity of Alachlor to the Rainbow
Trout (Oncorhynchus mykiss) Under Flow-Through Conditions: Lab Project Number: 42187:
AB-94-280: RD. 1331. Unpublished study prepared by ABC Labs, Inc. 339 p.
139383 Heenehan, P.R; Rinehart, W.E.; Braun, W.G. (1979) Acute Oral Toxicity Study in Rats;
Compound: Alachlor(Technical): Project No. 4899-77; BD-77-433. Rev. (Unpublished study,
including letters dated Aug 6, 1979 from W.E. Rinehart to George Levin- skas; Aug 31, 1979
from F.B. Oleson to W.D. Carpenter, received Oct 16, 1979 under 524-285; prepared by
Bio/dynamics, Inc., submitted by Monsanto Co., Washington, B.C.; CDL:241273-N)
75062 Schroeder, R.E.; Hogan, G.K.; Smock, M.E.; et al. (1981) A Three Generation Reproduction
Study in Rats with Alachlor: Project No. 77-2066. Final rept. (Unpublished study received Jul 10,
1981 under 524-285; prepared by Bio/dynamics, Inc., submitted by Monsanto Co., Washington,
D.C.; CDL:070177-A)
42763801 Blasberg, J.; Hicks, S.; Leak, T. (1993) Acute Toxicity of (carbon 14)-Alachlor to
Selenastrum capricornutum Printz: Final Report: Lab Project Number: 40815: AB-93-52: 1171.
Unpublished study prepared by ABC Labs, Inc. 56 p.
42468601 Canez, V. (1992) Tier 2 Vegetative Vigor Nontarget Phytotoxicity Study Using Alachlor: Lab
Project Number: BL91-480: 0624-91-9. Unpublished study prepared by Pan-Agricultural
Laboratories Inc. 226 p.
42468701 Chetram, R. (1992) Tier 2 Seed Germination/Seedling Emergence Nontarget Phytotoxicity
Study Using Alachlor: Lab Project Number: BL91-481: 0624-91-8. Unpublished study prepared
by Pan-Agricultural Laboratories Inc. 281 p
44649701 Drottar, K.; Kruegar, H. (1998) Alachlor: A 5-Day Toxicity Test with the Freshwater Alga
(Anabaena flos-aquae): Final Report: Lab Project Number: 139A-215: WL-97-172: 1435.
Unpublished study prepared by Wildlife International Ltd. 43 p.
44649702 Drottar, K.; Kruegar, H. (1998) Alachlor: A 14-Day Toxicity Test with Duckweed (Lemna
gibbaG3): Final Report: Lab Project Number: 1435: 139A-216: WL-97-174. Unpublished study
prepared by Wildlife International LTD. 46 p.
44649703 Drottar, K.; Kruegar, H. (1998) Alachlor: A 5-Day Toxicity Test with the Marine Diatom
(Skeletonema costatum): Final Report: Lab Project Number: 1435: 139A-217: WL-97-171.
Unpublished study prepared by Wildlife International Ltd. 44 p.
44649704 Drottar, K.; Kruegar, H. (1998) Alachlor: A 5-Day Toxicity Test with the Freshwater Diatom
(Naviculapelliculosa): Final Report: Lab Project Number: 1435: 139A-218: WL-97-173.
Unpublished study prepared by Wildlife International Ltd. 43 p.
Page 131 of 132
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45046001 Sutherland, C; Kendall, T.; Krueger, H. (2000) MON 5775: A 5-Day Toxicity Test with
Freshwater Alga (Selenastrum capricornutum): Lab Project Number: 1999-191: RDNO1499:
139A-24. Unpublished study prepared by Wildlife International, Ltd. 50 p.
45046002 Sutherland, C.; Kendall, T.; Krueger, H. (2000) MON 5775: A 5-Day Toxicity Test with the
Freshwater Alga (Anabenaflos-aquae): Lab Project Number: RDNO1499: 1997-197: 139A-244.
Unpublished study prepared by Wildlife International, Ltd. 49 p.
45046003 Sutherland, C.; Kendall, T.; Krueger, H. (2000) MON 5775: A 5-Day Toxicity Test with the
Freshwater Diatom (Naviculapelliculosa): Lab Project Number: RDNO1499: WL1999-193:
139A-246. Unpublished study prepared by Wildlife International, Ltd. 49 p.
45046004 Sutherland, C.; Kendall, T.; Krueger, H. (2000) MON 5775: A 5-Day Toxicity Test with the
Marine Diatom (Skeletonemacostatum): Lab Project Number: RDNO1499: WL-199-192: 139A-
248A. Unpublished study prepared by Wildlife International, Ltd. 49 p.
45046005 Sutherland, C.; Kendall, T.; Krueger, H. (2000) MON 5775: A 5-Day Toxicity Test with
Duckweed (LemnagibbaG3): Lab Project Number: RDNO1499: WL-1999-196: 139A-245A.
Unpublished study prepared by Wildlife International, Ltd. 45 p.
40098001 Mayer, F.; Ellersieck, M. (1986) Manual of Acute Toxicity: Interpretation and Data Base 410
Chemicals and 66 Species of Fresh-Water Animals. US Fish & Wildlife Service; Resource
Publication (160): 579 p.
00028772 Atkins, E.L., E.A. Greywood, R.L. Macdonald (1973). Toxicity of Pesticides and Other
Agricultural Chemicals to Honey Bees: Laboratory Studies. Rev. by University of California -
Riverside, Dept. of Entomology. Riverside, CA: UC Agricultural Extension Service.
00028549 McAllister, W.A., A.D. Forbis (1978). Acute Toxicity of Technical Alachlor (AB-78-200) to
Daphnia magna. (Unplublished study received Dec. 28, 1979 under 524-285; prepared by
Analytical Bio Chemistry Laboratories, Inc., submitted by Monsanto Co., Washington, DC;
CDL:241535-A)
00028552 McAllister, W.A., A.D. Forbis (1978). Acute Toxicity of Lasso (MCB/Cg) (AB-78-111) to
Daphnia magna. (Unplublished study received Dec. 28, 1979 under 524-285; prepared by
Analytical Bio Chemistry Laboratories, Inc., submitted by Monsanto Co., Washington, DC;
CDL:241535-D)
00087855b McAllister, W.A. (1979). Residue accumulation study in channel catfish (Ictalurus punctatus)
with alachlor-ul-phenyl-14C under static conditions. Accumulation, distribution, and elimination.
Report No. 22764. Unpublished study performed and submitted by Analytical BioChemistry
Laboratories, Inc. Columbia, MO.
44105503 Kirby-Smith, W.W., S.J. Eisenreich, J.T. Howe, RA. Luetich, Jr. (1993). The Effects in
Estuaries of Pesticide Runoff from Adjacent Farm Lands. Duke University Marine Laboratory,
Laboratory Report ID - CF 813415.
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