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 
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 

2 
Table of Contents 

1.0 EXECUTIVE SUMMARY .............................................................................................................8 

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 

2.2.1. 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 

2.9.1 Risk Hypotheses ....................................................................................................................44

2.9.2 Diagram ................................................................................................................................45

2.10. ANALYSIS PLAN.........................................................................................................................47 

3.0. EXPOSURE ASSESSMENT ........................................................................................................51 

3.1 AQUATIC EXPOSURE ASSESSMENT............................................................................................51 

3.1.1. 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 

3.2.1. 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

3
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 

5.1.1 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 

5.2.1. Direct Effects.........................................................................................................................95

5.2.2. Indirect Effects, DS and Aquatic-Phase CRLF .....................................................................99

5.2.3. Indirect Effects, Terrestrial-Phase CRLFs..........................................................................101

5.2.4 Spatial Extent of Potential Effects.......................................................................................105

5.3. MODIFICATION OF DESIGNATED CRITICAL HABITAT..............................................................111 

5.3.1. CRLF...................................................................................................................................111

5.3.2. DS........................................................................................................................................112

5.4. EFFECTS DETERMINATIONS.....................................................................................................113 

5.4.1 CRLF...................................................................................................................................113

5.4.2 DS........................................................................................................................................113

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 of Alachlor.............................................................................115

6.1.4 Ground Water Uncertainties...............................................................................................117

6.1.5 Usage Uncertainties............................................................................................................118

6.1.6 Terrestrial Exposure Modeling of Alachlor........................................................................118

6.2 EFFECTS ASSESSMENT UNCERTAINTIES..................................................................................119 

6.2.1 Age Class and Sensitivity of Effects Thresholds..................................................................119

6.2.2 Impact of Multiple Stressors on the Effects Determination ................................................119

6.2.3. Use of Surrogate Species Effects Data................................................................................120

6.2.4 Location of Wildlife Species................................................................................................121

7.0 RISK CONCLUSIONS ...............................................................................................................122 

8.0 REFERENCES ............................................................................................................................124

4
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)a

....................................................................................................................................................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. Taxa Used in the Analyses of Direct and Indirect Effects for the Assessed Listed Species....42 

5
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 (μg/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 lb 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 

6
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 draytonii) (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-chloro2’,6’-diethylacetanilide, 2’,6’-diethyl-N-methoxymethylacetanilide, and 2’6’-diethyl-2-hydroxyN-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 

Page 8 of 132 
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 μg a.i./L 

(sweet corn, incorporated use) to 56.0 μg a.i./L (woody ornamentals, nursey use). The maximum 

reported monitoring value from surface water data evaluated in this assessment was 91.5 μg/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 μg/L value was 

conducted before the maximum application rates for alachlor were reduced from 6 lb a.i./acre to 

4 lb a.i./acre in the 1990’s. An application rate of 6 lbs 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 μg/L compared to 91.5 

μg/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 

Page 9 of 132 
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 posttransplant (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. 

Page 10 of 132 
Table 1.1. Effects Determination Summary for Effects of Alachlor on the CRLF and the 

DS. 

Species Effects 

Determination 1 Basis for Determination 

Potential for Direct Effects 

California redlegged frog 

(Rana aurora 

draytonii) 

LAA1 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 subacute dietary exposure is low. However, the risk (or potential risk) to terrestrialphase 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. 

Delta Smelt 

(Hypomesus 

transpacificus) 

LAA1 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. 1

 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. 

Page 11 of 132 
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 

Page 12 of 132 
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 

draytonii) (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 et al. 

(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, TREX, 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 nationalPage 13 of 132 
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 

LOC 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 

Page 14 of 132 
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 (HED) 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-methylsulfinylacetanilide, 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-Nmethoxymethylacetanilide, 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, HED assumed that they have the same toxicity as 

alachlor parent and are residues of risk concern (USEPA, 2006). Therefore, a total toxic residues 

Page 15 of 132 
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-Nmethoxymethylacetanilide (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 2-chloro-2’,6’-diethylacetanilide None 

III 2',6'-diethyloxanilic acid DM-oxanilic acid 

IV 2’,6’-diethyl-2-sulfoacetanilide None 

VII 2’,6’-diethyl-N-methoxymethyloxoanilic acid None 

VIII [N-methoxymethyl-N-(2,6-diethylphenyl)-2-amino-2­

oxoethyl]sulfinylacetic acid 

Alachlor sulfinylacetic acid 

MON 5768 

IX 2’,6’-diethyl-N-methoxymethylacetanilide None 

X 2',6'-diethyl-N-methoxymethyloxanilic acid Alachlor oxanilic acid 

MON 5760 

XI 2',6'-diethyl-N-methoxymethyl-2-sulfoacetanilide 

Alachlor sulfonic acid, 

Alachlor-ESA 

MON 5775 

XIII 2’,6’-diethyl-2-hydroxy-N-methoxymethylacetanilide None 

Minor Degradates 

I 2’,6’-diethylacetanilide None 

V 2’,6’-diethyl-2-methoxyacetanilide None 

VI 2’,6’-diethyl-2-methylsulfinylacetanilide None 

XII 2’,6’-diethyl-N-methoxymethyl-2-oxoacetanilide None 

XV 2’,6’-diethyl-N-methoxymethyl-2-methylthioacetanilide None 

XVI 2’,6’-diethyl-N-methoxymethyl-2­

methylsulfinylacetanilide None 

XVII 2’,6’-diethyl-N-methoxymethyl-2­

methylsulfonylacetanilide None 

XX 2’,6’-diethylbenzyl alcohol None 

XXII 2’,6’-diethyl-N-hydroxymethyl-2-methoxyacetanilide None 

XXIII 8-ethyl-N-methoxymethyl-4-methyl-2­

oxotetrahydroquinoline None 

XXIV 2’-acetyl-2-chloro-6’-ethyl-N-methoxymethylacetanilide None 

*Bold text indicates degradates of toxicological concern previously identified in USEPA, 2006. 

Page 16 of 132 
Table 2.2. Summary of Formation Pathway of Alachlor Degradates of Concern (assumed 

equal toxicity to parent)a 

Formation Pathway 

Degradate Photolysis in 

Water 

Photolysis in 

Soil 

Aerobic 

Metabolism 

in Soil 

Anaerobic 

Metabolism 

in Soil 

Anaerobic 

Metabolism 

in Water 

2-chloro-2’,6’­

diethylacetanilide 

(Compound II) 

-- -- X 

(20%, 18 d t 1⁄2) -- --

2’,6’-diethyl-Nmethoxymethylacetanilide 

(Compound IX) 

X 

(1.1%, 48 h t 1⁄2) -- X (2.5%, 14 d t 1⁄2) --

X 

(35.3%, 21 d t 

1⁄2) 

2’,6’-diethyl-2-hydroxy-Nmethoxymethylacetanilide 

(Compound XIII) 

-- X 

(6.5%, 14 d t 1⁄2) 

X 

(10.2%, 7 d t 1⁄2) -- --

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). 

Page 17 of 132 
Table 2.3. Comparison of Aquatic Organism Toxicity Data for Alachlor and its 

Degradates. 

COMPOUND 

TAXA/SPECIES ENDPOINT 

Alachlor (parent) Alachlor Sulfinic 

Acid (MON 5775) 

Oxanilic Acid 

(MON 5760) 2,6-Diethylaniline 

Endpoint (mg 

a.i./L) 

(MRID/Reference) 

Endpoint (mg 

a.i./L) (MRID) 

Endpoint (mg 

a.i./L) (MRID) 

Endpoint (mg 

a.i./L) (Reference) 

Aquatic invertebrate 

Daphnid (Daphnia 

magna) 

48-hr EC50 

7.7 

(40098001) 

>104 

(43774703) 

>95 

(43774705) --

Freshwater fish 

Rainbow trout 

(Oncorhynchus mykiss) 

96-hr LC50

 1.8 

(C.I.* = 1.5 – 2.1) 

(00023616) 

>104 

(43774704) 

>100 

(43774706) --

Amphibian 

African clawed frog 

(Xenopus laevis) 

96-hr LC50 

6.1 

(E66376) (Osano et 

al., 2002) 

-- --

19.4 

(E66376) (Osano 

et al., 2002) 

Aquatic plant 

(nonvascular) 

Green algae 

(Selenastrum 

capricornutum) 

5-day EC50 

0.00164 

(C.I. = 0.0015 – 

0.0024) 

(427638-01) 

>120 

(450460-01) 

-- --

5-day 

NOAEC 

0.00035 

(427638-01) 

120 (highest conc. 

tested) 

(450460-01) 

Aquatic plant 

(nonvascular) 

5-day EC50 

EC50 = >19 

(446497-01) >120 (450460-02) 

-- -- Cyanobacteria 

(Anabaena flos-aquae) 5-day 

NOAEC 

19 

(highest conc. 

tested) 

(446497-01) 

120 (highest conc. 

tested) (450460­

02) 

Aquatic plant 

(nonvascular) 

5-day EC50 

2.63 

(C.I. = 2.4 – 3.0) 

(446497-04) 

3.6 

(C.I. = 2.9 – 4.1) 

(450460-03) -- -- Freshwater diatom 

(Navicula pelliculosa) 5-day 

NOAEC 

NOAEC = 1.0 

(446497-04) 

2.5 

(450460-03) 

Aquatic plant 

(nonvascular) 

5-day EC50 

0.21 

(C.I. = 0.15 – 0.26) 

(446497-03) 

5.0 

(C.I. = 4.6 – 5.6) 

(450460-04) -- -- Marine diatom 

(Skeletonema costatum) 5-day 

NOAEC 

0.098 

(446497-03) 

2.0 

(450460-04) 

Aquatic plant (vascular) 

Duckweed (Lemna 

gibba) 

14-day EC50 

0.0023 

(C.I. = 0.0021 – 

0.0033) 

(446497-02) 

>120 

(450460-05) 

-- --

14-day 

NOAEC 

0.000339 

(446497-02) 

120 (highest conc. 

tested) (450460­

05) 

-- = No data available 

* C.I. = 95% Confidence Interval 

Page 18 of 132 
Table 2.4. Comparison of Mammalian Acute and Chronic Toxicity Data for Alachlor and 

its Degradates. 

COMPOUND 

TAXA/ 

SPECIES ENDPOINT 

Alachlor 

(parent) 

Alachlor 

Sulfinic 

Acid 

(MON 

5775) 

Oxanilic 

Acid 

(MON 

5760) 

Sulfinylacetic 

Acid (MON 

5768) 

thydroxyalachlor 

(MON 52707) 

Endpoint 

(mg/kg) 

Endpoint 

(mg/kg) 

Endpoint 

(mg/kg) 

Endpoint 

(mg/kg) 

Endpoint 

(mg/kg) 

Rat 

(acute 

oral) 

LD50 930 >6,000 >5,000 >5,000 

>500 (males) 

>500, <2,000 

(females) 

Rat 

(90-day 

dietary) 

NOAEL 15* 

157 

(males) 

207 

(females) 

13,000 4,000 --

* 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 

Page 19 of 132 
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. 

Page 20 of 132 
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 (t1⁄2 = 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 

2.2x10-5 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 

Page 21 of 132 
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-methylsulfinylacetanilide, 2’,6’-diethyl-N-methoxymethyl-2-oxoacetanilide, 

2’,6’-diethyl-N-methoxymethyl-2-methylthioacetanilide, 2’,6’-diethyl-N-methoxymethyl-2­

methylsulfinylacetanilide, 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 sulfinylacetic 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 (1/n=0.95), yielding an organic carbon partition coefficient (KOC) value of 15 L/kgOC. 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-NPage 22 of 132 
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 Reregistration 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 (2.2×10-5 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 et al., 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 

Page 23 of 132 
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 lbs 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, sulfinylacetic 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 sulfinylacetic 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 lbs 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 postapplication; 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 sulfinylacetic 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 
Table 2.5. General Chemical/Physical Properties of Alachlor. 

Parameter Value Source 

 Chemical name 2-chloro-2',6'-diethyl-Nmethoxymethylacetanilide MRID 134327 

 Molecular Weight 269.77 g/mol MRID 146114 

 Solubility 240 mg/L (24°C) Beestman and Deming, 1974 

 Vapor Pressure 2.2 x 10-5 torr (24°C) Beestman and Deming, 1974 

 Hydrolysis half life (pH 3) stable (25°C) MRID 134327 

 Hydrolysis half life (pH 6) stable (25°C) MRID 134327 

 Hydrolysis half life (pH 9) stable (25°C) MRID 134327 

 Aqueous photolysis half life Assumed stable MRID 23012 

 Soil photolysis half life Assumed stable MRID 23012 

 Aerobic soil metabolism half life 29.7 d (silt loam) 

34.0 d (loamy sand) 

25.8 d (silt) 

MRID 134327 

 Soil-water distribution coefficient 

 (Kads) 

0.33 - 3.7 L/kg1 MRID 152209 

 Organic carbon partitioning 

 coefficient (Koc) 

190 L/kg USEPA, 1998b

 Octanol-water partition

 coefficient (Kow) 

1223 MRID 40396301

 Bioconcentration factor (BCF) 48 – 102 

(estimated) 

BCFWIN v2.15 

1

 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 
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 
Table 2.6. Summary of Alachlor Products Registered in the U.S. 

Product 

Name 

(EPA Reg. 

No.) 

Registrant Percent Active 

Ingredient Form Use(s) Assessed in this Assessment? 

Lasso® 94% 

Stabilized 

Technical 

(524-316) 

Monsanto 

Corporation 94 (alachlor) Technical Used to make enduse products 

No - the technical 

grade chemical is only 

labeled for use in 

producing end use 

products. 

Lariat® 

Herbicide 

(524-329) 

Monsanto 

Corporation 

- 27.2 (alachlor) 

- 16 (atrazine) 

- 0.3 (atrazine-related 

compounds) 

Flowable 

concentrate 

- Corn (all types) 

- Sorghum (milo) 

No – the label contains 

a statement that the 

product is not approved 

for use in California 

Bullet® 

Herbicide 

(524-418) 

Monsanto 

Corporation 

- 25.4 (alachlor) 

- 14.5 (atrazine) 

- 0.8 (atrazine-related 

compounds) 

Emulsifiable 

concentrate 

- Corn (all types) 

- Sorghum (milo) 

No – the label contains 

a statement that the 

product is not approved 

for use in California 

Lasso® 

Herbicide, 

INTRRO

 (524-314) 

Monsanto 

Corporation 45.1 (alachlor) Emulsifiable concentrate 

- Corn 

- Corn (sweet) 

- Sorghum (milo) 

- Soybeans 

- Dry beans 

- Lima beans 

- Woody 

ornamentals 

- Peanuts 

Yes 

Micro-Tech® 

Herbicide 

(524-344) 

Monsanto 

Corporation 41.5 (alachlor) Microencapsulated 

- Corn 

- Corn (sweet) 

- Sorghum (milo) 

- Soybeans 

- Dry beans 

- Lima beans 

- Woody 

ornamentals 

- Peanuts 

- Cotton 

- Sunflowers 

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 
Both the maximum yearly and maximum single application rates for alachlor are 4 lb a.i./acre 

(corn, peanuts, sorghum, woody ornamentals, and sunflowers). For peanuts, the Lasso® label 

allows a maximum application rate of 4 lb a.i./acre/year, whereas the Micro-Tech® label allows a 

maximum rate of 3 lb a.i./acre/year (therefore, for peanuts, the 4 lb 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 lb a.i./acre (soybeans and beans) or 2 lb 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, preemergence 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 lb of dry 

bulk fertilizer per acre is stipulated (with a maximum application rate of 3 to 4 lb 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 
Table 2.7. Summary of Alachlor Application Methods and Rates for California. 

Uses 

Max Appl. 

Rate per Year 

(lbs a.i./acre) 

Max Single 

Appl. Rate 

(lbs a.i./acre) 

Max No. 

Appl. Per 

Year 

Appl. Methods** Appl. Timing 

Corn 4 

4 

(no more than 

2 can be 

applied postmergence) 

2 

- Ground 

- Center pivot irrigation 

- Bulk fertilizer impregnation 

- Burndown prior to crop 

- Preplant incorporated (no 

deeper than 4 inches into the 

soil) 

- Preemergence surface 

- Postemergence surface 

Sweet corn 4 4 1 

- Ground 

- Center pivot irrigation 

- Bulk fertilizer impregnation 

- Preplant incorporated (no 

deeper than 4 inches into the 

soil) 

- Preemergence surface 

Grain sorghum 

(milo) 4 4 2 

- Ground 

- Center pivot irrigation 

- Bulk fertilizer impregnation 

- Burndown prior to crop 

- Preplant incorporated (no 

deeper than 4 inches into the 

soil) 

- Preemergence surface 

Peanuts 4 4 2 - Ground 

- Center pivot irrigation 

- Preplant incorporated (no 

deeper than 4 inches into the 

soil) 

- Preemergence surface 

- Ground-crack surface 

Soybeans 3 3 1 - Ground - Center pivot irrigation 

- Bulk fertilizer impregnation 

- Burndown prior to crop 

- Preplant incorporated (no 

deeper than 4 inches into the 

soil) 

- Preemergence surface 

Dry beans** 3 3 1 - Ground 

- Preplant incorporated (no 

deeper than 4 inches into the 

soil) 

Lima beans 

(green)** 3 3 1 - Ground 

- Preplant incorporated (no 

deeper than 4 inches into the 

soil) 

Woody 

ornamentals 

(Junipers and 

yews)*** 

4 4 

2 

(within 21 

days) 

- Ground -Post-transplant 

Cotton 2 2 1 - Ground - Preplant incorporated (into 

upper 1 – 2 inches of soil) 

- Preemergence surface 

Sunflowers 4 4 1 - Ground - 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 
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 lbs 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. 

Figure 2.1. Estimated Annual Alachlor Usage in the U.S. 

(from http://water.usgs.gov/nawqa/pnsp/usage/maps/show_map.php?year=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 (USDAPage 30 of 132 
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 lbs 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 lb 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, Sutter, 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 lbs of alachlor was applied in CA, whereas a total of 13,734 lbs 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/estindx1.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 
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 lb a.i./acre. The average 95th% and 99th% 

application rate and the maximum reported application rate per county/year ranged from <1 to 

3.99 lb a.i./acre [some counties reported 99th% and maximum application rates higher than the 

registered use rates (i.e., >4 lb 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 
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) 

County 

Avg 

Annual 

Area 

Treated 

(Acres) 

Avg App Rate 

(lb a.i./Acre 

per appl.) 

Avg 95th% 

App Rate (lb 

a.i./Acre per 

appl.) 

Avg 99th% 

App Rate (lb 

a.i./Acre per 

appl.) 

Avg Max App 

Rate (lb 

a.i./Acre per 

appl.) 

Alameda 1 0 -- -- --

Butte 44 2.54 2.99 2.99 2.99 

Fresno 3,283 2.5 3.0 3.99 7.48* 

Glenn 267 3.78 3.99 29.6* 29.6* 

Kern 8 2.85 2.99 2.99 2.99 

Los Angeles 41 1.99 1.99 1.99 1.99 

Madera 3 2.49 2.49 2.49 2.49 

Merced 91 2.51 2.99 2.99 2.99 

Monterey 465 1.87 2.24 2.99 2.99 

Orange 1 2.39 3.99 3.99 3.99 

Riverside 139 1.94 2.99 4.49* 4.49* 

26,060 Sacramento 104 3.1 3.49 3.49 3.49 

San Benito 192 0.83 1.0 1.5 3.74 

San Diego 24 0.96 1.99 1.99 1.99 

San Joaquin 24 3.83 3.99 3.99 3.99 

San Luis Obispo 1 2.99 2.99 2.99 2.99 

Santa Barbara 1,892 2.77 3.49 4.79* 29.91* 

Santa Clara 338 1.67 2.49 4.11* 74.97* 

Solano 302 3.44 3.99 4.10* 4.10* 

Stanislaus 35 2.63 2.99 2.99 2.99 

Sutter 4 1.99 1.99 1.99 1.99 

Tulare 656 2.52 2.99 3.0 3.0 

Ventura 2,116 2.98 3.03 3.96 36.29* 

Yolo 378 2.80 3.99 4.70* 4.70* 

* These rates are higher than 4 lb 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 
Table 2.9. Summary of Current Distribution, Habitat Requirements, and Life History Information for the 

Species1. 

 Assessed Species Size Current Range Habitat Type Designated Reproductive 

Critical Cycle 

Habitat? 

California red- Adult Northern CA coast, northern Freshwater perennial Yes Breeding: Nov. to Apr

legged frog (85-138 cm Transverse Ranges, foothills of or near-perennial Tadpoles: Dec. to Mar(Rana aurora in length), Sierra Nevada, and in southern CA aquatic habitat with Young juveniles: Mardraytonii) Females – south of Santa Barbara dense vegetation; Sept. 

9-238 g, Males – 13-163 g; Juveniles (40-84 cm 

artificial impoundments; riparian and upland areas 

in length) 

Delta smelt Up to 120 Suisun Bay and the Sacramento- The species is Yes Spawns in fresh or (Hypomesus mm in San Joaquin estuary (known as the adapted to living in slightly brackish water transpacificus) length Delta) near San Francisco Bay, CA fresh and brackish upstream of the mixin

water. They typically zone. Spawning seasooccupy estuarine usually takes place froareas with salinities late March through mibelow 2 parts per May, although it may thousand (although occur from late winter they have been found (Dec.) to mid-summer in areas up to 18parts (July-August). Eggs per thousand). They hatch in 9 – 14 days. live along the freshwater edge of the mixing zone (saltwater-freshwater interface). 1 For more detailed information on the distribution, habitat requirements, and life history information of the assessed listed species, see 

2 For the purposes of this assessment, tadpoles and submerged adult frogs are considered “aquatic” because exposure pathways in the 

different than those that occur on land. 

Page 34 of 132 
Figure 2.3. Delta Smelt Habitat Areas. 

Page 35 of 132
 and Western 

o Bay 

es and Tehachapi 

nsular Ranges 

Recovery Units 

1. Sierra Nevada Foothills and C entral Valley

2. North Coast Range Foothills 

Sacramento River Valley 

3. North Coast and North San Fr ancisco Bayancisco Bay

4. South and East San Francisc 

5. Central Coast 

6. Diablo Range and Salinas Val ley

7. Northern Transverse Rang 

Mountains 

8. Southern Transverse and Peni 

Core Ar eas

1. Feather River

2. Yuba River- S. Fork Feather River 2. Yuba River- S. Fork Feather River

3. Traverse Creek/ Middle Fork/ American R. Rubicon 3. Traverse Creek/ Middle Fork/ American R. Rubicon

4. Cosumnes River 4. Cosumnes River

5. South Fork Calaveras River* 5. South Fork Calaveras River*

6. Tuolumne River*

7. Piney Creek*

8. Cottonwood Creek

9. Putah Creek – Cache Creek* 9. Putah Creek – Cache Creek*

10. Lake Berryessa Tributaries 10. Lake Berryessa Tributaries

11. Upper Sonoma Creek 11. Upper Sonoma Creek

12. Petaluma Creek – Sonoma Creek 12. Petaluma Creek – Sonoma Creek

13. Pt. Reyes Peninsula 13. Pt. Reyes Peninsula

14. Belvedere Lagoon

15. Jameson Canyon – Lower Napa River 15. Jameson Canyon – Lower Napa River

16. East San Francisco Bay 16. East San Francisco Bay

17. Santa Clara Valley

18. South San Francisco Bay 18. South San Francisco Bay

19. Watsonville Slough-Elkhorn Slough 19. Watsonville Slough-Elkhorn Slough

20. Carmel River – Santa Lucia 20. Carmel River – Santa Lucia

21. Gablan Range 21. Gablan Range

22. Estero Bay 22. Estero Bay

23. Arroyo Grange River 23. Arroyo Grange River

24. Santa Maria River – Santa Ynez River 24. Santa Maria River – Santa Ynez River

25. Sisquoc River 25. Sisquoc River

26. Ventura River – Santa Clara River 26. Ventura River – Santa Clara River

27. Santa Monica Bay – Venura Coastal Streams 27. Santa Monica Bay – Venura Coastal Streams

28. Estrella River 28. Estrella River

29. San Gabriel Mountain* 29. San Gabriel Mountain*

30. Forks of the Mojave* 30. Forks of the Mojave*

31. Santa Ana Mountain* 31. Santa Ana Mountain*

32. Santa Rosa Plateau 32. Santa Rosa Plateau

33. San Luis Ray* 33. San Luis Ray*

34. Sweetwater* 34. Sweetwater*

35. Laguna Mountain* 35. Laguna Mountain*

* Core areas that were historically occupied by the California red-legged frog are not included in the map * Core areas that were historically occupied by the California red-legged frog are not included in the map

Figure 2.4. Recovery Unit, Core Area, Critical Habitat, and Occurrence Designations for 

CRLF. 

Page 36 of 132 
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. 

Page 37 of 132 
Table 2.10. Designated Critical Habitat PCEs for the CRLF and DS. 

Species PCEs Reference 

CRLF Alteration of channel/pond morphology or geometry and/or increase in 

sediment deposition within the stream channel or pond. 

50 CFR 414.12(b), 

2006 

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 premetamorphs (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. 

DS 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). 

59 FR 65256 

65279, 1994 

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 

quality may 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. 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 

Page 38 of 132 
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. 

Page 39 of 132 
Figure 2.5. Potential Alachlor Use Sites in California Representing the Initial Area of 

Concern. 

Page 40 of 132
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 F1 generations at all of the concentrations tested (Lee et al. 2008, 

E104287). Additionally, the most sensitive available NOAEC for birds based on chronic 

exposure is <50 mg a.i./kg-diet for mallard ducks (Anas platyrhynchos) 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. 

3

 From U.S. EPA (1992). Framework for Ecological Risk Assessment. EPA/630/R-92/001. 

Page 41 of 132 
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 

Birds / 

Terr. 

Amphibian 

Mammals Terr. 

Plants 

Terr. 

Inverts. 

FW Fish / 

Amphibian 

FW 

Inverts. 

Estuarine 

/Marine 

Fish 

Estuarine 

/Marine 

Inverts. 

Aquatic 

Plants 

California 

red-legged 

frog 

Direct 

Indirect 

(prey) 

Indirect 

(prey) 

Indirect 

(habitat) 

Indirect 

(prey) 

Direct 

Indirect 

(prey) 

Indirect 

(prey) N/A N/A 

Indirect 

(food/ 

habitat) 

Delta 

smelt N/A N/A Indirect (habitat) N/A Direct1 Indirect 

(prey) Direct Indirect (prey) 

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. 

Page 42 of 132 
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 

1a. Amphibian acute LC50 (ECOTOX) or 

most sensitive fish acute LC50 (guideline 

or ECOTOX) if no suitable amphibian 

data are available 

Indirect Effect (prey) Survival, growth, and 1b. Amphibian chronic NOAEC 

-Aquatic-phase CRLF reproduction of individuals 

via indirect effects on 

aquatic prey food supply 

(i.e., fish and aquatic-phase 

amphibians) 

(ECOTOX) or most sensitive fish chronic 

NOAEC (guideline or ECOTOX) 

1c. Amphibian early-life stage data 

(ECOTOX) or most sensitive fish earlylife stage NOAEC (guideline or 

ECOTOX) 

2. Freshwater Indirect Effect (prey) Survival, growth, and 2a. Most sensitive freshwater 

Invertebrates -Aquatic-phase CRLF 

-DS 

reproduction of individuals 

via indirect effects on 

aquatic prey food supply 

(i.e., freshwater 

invertebrates) 

invertebrate EC50 (guideline or ECOTOX) 

2b. Most sensitive freshwater 

invertebrate chronic NOAEC (guideline 

or ECOTOX) 

3. 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 Indirect Effect (prey) Survival, growth, and 4a. Most sensitive estuarine/marine 

Invertebrates -DS reproduction of individuals 

via indirect effects on 

aquatic prey food supply 

(i.e., estuarine/marine 

invertebrates) 

invertebrate EC50 (guideline or ECOTOX) 

4b. Most sensitive estuarine/marine 

invertebrate chronic NOAEC (guideline 

or ECOTOX) 

5. Aquatic Plants Indirect Effect Survival, growth, and 5a. Vascular plant acute EC50 (duckweed 

(freshwater/marine) (food/habitat) 

-Aquatic-phase CRLF 

-DS 

reproduction of individuals 

via indirect effects on 

habitat, cover, food supply, 

and/or primary productivity 

(i.e., aquatic plant 

community) 

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 

6a. Most sensitive birdb

 or terrestrialphase amphibian acute LC50 or LD50 

(guideline or ECOTOX) 

6b. Most sensitive birdb Indirect Effect (prey) Survival, growth, and or terrestrial-

-CRLFs reproduction of individuals 

via indirect effects on 

terrestrial prey (surrogate 

for amphibians) 

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)c 

Page 43 of 132 
Taxa Used to Assess 

Direct and/or Indirect 

Effects to Assessed 

Species1 

Assessed Listed 

Species Assessment Endpoints Measures of Ecological Effects 

terrestrial prey (terrestrial 

invertebrates) 

8b. Most sensitive terrestrial invertebrate 

chronic NOAEC (guideline or ECOTOX) 

9. Terrestrial Plants Indirect Effect 

(food/habitat) (nonobligate relationship) 

-Terrestrial- and 

aquatic-phase CRLF 

-DS 

Survival, growth, and 

reproduction of individuals 

via indirect effects on food 

and habitat (i.e., riparian 

and upland vegetation) 

9a. Distribution of EC25 for monocots 

(seedling emergence, vegetative vigor, or 

ECOTOX 

9b. Distribution of EC25 for dicots 

(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; 

Page 44 of 132 
• ... 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. 

Page 45 of 132 
Stressor 

Source 

Receptors 

Attribute 

Change 

Alachlor applied to use site 

Direct 

application Spray drift 

Birds/terrestrialphase amphibians/ 

reptiles/mammals 

Terrestrial 

insects 

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 

Community change 

Modification of PCEs related to 

habitat 

Terrestrial/riparian plants 

grasses/forbs, fruit, seeds 

(trees, shrubs) 

Runoff 

Mammals/ 

birds 

Exposure 

Media 

Soil 

Ingestion 

Ingestion 

Ingestion 

Ingestion 

Dermal uptake/Ingestion 

Long range 

atmospheric 

transport 

Root uptake 

Wet/dry deposition 

Terrestrial-phase 

amphibians 

Ingestion 

Figure 2.6. Conceptual Model for Risks to Terrestrial-Phase CRLF from Alachlor Use. 

Page 46 of 132
Stressor 

Source 

Exposure 

Media 

Alachlor applied to use site 

Spray drift 

Surface water/ 

Sediment 

Runoff Soil Groundwater Long range 

atmospheric 

transport 

Wet/dry deposition 

Uptake/gills Uptake/cell, 

or integument roots, leaves 

Uptake/gills 

Receptors or integument 

Ingestion 

Food chain 

Reduction in algae 

Reduction in prey 

Modification of PCEs 

 related to prey availability 

Habitat integrity 

Reduction in primary 

productivity 

Reduced cover 

Community change 

Modification of PCEs related to 

habitat 

Aquatic Animals 

Invertebrates 

Vertebrates 

Ingestion 

Aquatic Plants 

Non-vascular 

Vascular 

Riparian plants 

terrestrial 

exposure 

pathways 

Fish/aquatic-phase 

amphibians 

Attribute Individual 

Change organisms 

Reduced survival 

Reduced growth 

Reduced reproduction 

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 

Page 47 of 132 
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-in10 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 1-in-10 year return peak or rolling mean 

concentration. The 1-in-10-year 60-day mean is used for assessing chronic exposure to fish; the 

1-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 (preplant 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 

Page 48 of 132 
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 lb 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 LD50/ft2

 values. The LD50/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 LOC for the areas of 

potential effect is also considered. 

Page 49 of 132 
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 MidContinent 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 aquaticphase CRLF. 

The acute measures of effect used for animals in the screening-level portion of this assessment 

are the LD50, LC50 and EC50. 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 EC50 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 Observed-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-EffectConcentration”) 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 EC50 

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 

Page 50 of 132 
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 LOC, 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 LOC, then the effects 

determination for that use is a “may affect.” If the RQ being considered also exceeds the nonlisted species acute risk LOC, then the effects determination is a LAA. If the acute RQ is 

between the listed species LOC and the non-listed acute risk species LOC, 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 LOC 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), screeninglevel 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 

Page 51 of 132 
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 

Page 52 of 132 
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 al., 

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/oppefed1/models/water/index.htm#przmexamsshell 

http://www.epa.gov/oppefed1/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/oppefed1/models/water/index.htm 

Page 53 of 132 
Table 3.1. Summary of PRZM Scenarios. 

Use Scenario First 

Application 

Min. 

Application 

Interval 

Weather Station 

(WBAN #) 

Corn CAcornOP March 1 

(preplant) NS Sacramento (23232) 

Sweet Corn CAcornOP 

May 1 

(30 d post 

emergence) 

NS Sacramento 

(23232) 

Sorghum CAwheatRLF January 2 

(preplant) NS Fresno (93193) 

Legume Vegetables 

(Soybeans, dry 

beans, succulent 

beans, lima beans) 

CARowCropRLF_V2 Nov 20 

(preplant)* NS San Francisco (23234) 

Woody ornamentals 

(Junipers and Yews) 

CANurserySTD_V2 

CA ResidentialRLF 

Dec 1** 

(post transplant) 21 days 

San Diego 

(23188) 

San Francisco 

(23234) 

Cotton CAcotton_WirrgSTD 

March 1 

(preplant) 60d 

prior to 

emergence 

NS Fresno 

(93193) 

Sunflowers CAcornOP March 1 

(preplant) NS Sacramento 

(23232) 

Peanuts CARowCropRLF_V2 Nov 20 

(preplant)* NS 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 USDANASS 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 

Page 54 of 132 
EXAMS. Weather and agricultural practices were simulated over 30 years so that the 1-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) 

0 

20 

40 

60 

80 

10 0 

12 0 

14 0 

16 0 

January '04 

February '04 

March '04 

April '04 

May '04 

June '04 

July '04 

August '04 

September '04 

October '04 

November '04 

December '04 

January '05 

February '05 

March '05 

April '05 

May '05 

June '05 

July '05 

August '05 

September '05 

October '05 

November '05 

December '05 

Month/Year 

Number of Applications 

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/oppsrrd1/REDs/0063.pdf 

Page 55 of 132 
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 Value MRID1 (or source) 

Molecular Weight 269.77 g/mol MRID 146114 

Vapor Pressure 2.2 x 10 -5 torr Beestman and Deming, 1974 

Henry’s Law Constant 3.3 x 10-8 atm*m3

/mol Calculated 

Solubility in Water 240 mg/L (24oC) Beestman and Deming, 1974 

Photolysis in Water Stable MRID 23012 

Aerobic Soil Metabolism Half-lives 

29.7 d (silt loam) 

34.0 d (loamy sand) 

25.8 d (silt) 

MRID 134327 

Hydrolysis (25 oC) 

pH 5 – stable 

pH 7 – stable 

pH 9 - stable 

MRID 134327 

Aerobic Aquatic Metabolism (water 

column) 84 d 

Represents 2x the high-end 

confidence bound on the mean 

TTR aerobic soil metabolism 

half-life. 

Anaerobic Aquatic Metabolism 

(benthic) Stable Default 

 Soil-water distribution coefficient 

 (Kd) 0.33 

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. 

Page 56 of 132 
Table 3.3. Summary of Management Practices for PRZM/EXAM Modeling Input 

Parameters. 

Application 

rate lbs ai/A 

(kg ai/ha) 

Max No. 

Applications 

per year 

Max. 

Annual 

Application 

Rate lbs 

ai/A 

Application 

Interval 

Application 

method 

Broadcast / 

Incorporation 

depth 

CAM 

Input 

Spray Drift 

Efficiency 

App. 

Efficiency 

Corn 

4.0 2 4.0 NA Ground 

Broadcast & 

incorporated 

(10cm) 

1, 4 0.01 0.99 

Sweet corn 

4.0 1 4.0 NA Ground 

Broadcast & 

incorporated 

(10cm) 

2, 4 0.01 0.99 

Sorghum 

4.0 2 4.0 NA Ground 

Broadcast & 

incorporated 

(10cm) 

1, 4 0.01 0.99 

Legumes 

3.0 1 3.0 NA Ground 

Broadcast & 

incorporated 

(10cm) 

1, 4 0.01 0.99 

Woody 

Ornamentals 4.0 2 4.0 21 Ground Broadcast 2 0.01 0.99 

Cotton 

2.0 1 2.0 NA Ground 

Broadcast & 

incorporated 

(4cm) 

1, 4 0.01 0.99 

Sunflowers 

4.0 4 4.0 NA Ground 

Broadcast & 

incorporated 

(4cm) 

1, 4 0.01 0.99 

Peanuts 

4.0 2 4.0 NA Ground 

Broadcast & 

incorporated 

(10cm) 

1, 4 0.01 0.99 

NA = Not applicable, a single annual application was modeled. 

Page 57 of 132 
Table 3.4. Summary of PRZM/EXAMS Chemcial Input Parameters for Alachlor 

Input Parameter Value Source 

Molecular Mass (g/mol) 269.77 

MRID 146114 

Vapor Pressure at 24o

C (torr) 2.2 x 10-5 Beestman and Deming, 1974 

Henry’s Law Constant 3.3 x 10-8 Calculated 

Solubility in Water at 24o

C (mg/L) 2400 

Represents 10x the measured water 

solubility value (Beestman and 

Deming, 1974) 

 Soil-water distribution coefficient 

 (Kd) 0.33 Represents the lowest reported 

non-sand Kd (MRID 152209) 

Aerobic Soil Metabolism Half-life (days) 

34.3 

Represents the high-end confidence 

bound on the mean (MRID 

134327) 

42 

Represents the high-end confidence 

bound on the mean total toxic 

residues half-life (MRID 134327) 

Aerobic Aquatic Metabolism Half-life (days) 84 

Represents 2x the high-end 

confidence bound on the mean 

aerobic soil metabolism halflife (MRID 134327). (USEPA, 

2002) 

Anaerobic Aquatic Metabolism Half-life 

(days) 0 (Stable) None 

Hydrolysis Half-lives (days) 0 (Stable) 

Alachlor is stable to hydrolysis at 

pH 5, 7, and 9 (MRID 134327) 

therefore assumed to be 0 (US 

EPA, 2002) 

Aqueous Photolysis 

Half-life (days) 0 (Stable) 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. 

Page 58 of 132 
Table 3.5. Aquatic Total Toxic Residue EECs (μg/L) for Alachlor Uses in California. 

Use Site 

(application 

method) 

Application 

Rate (lbs 

a.i./acre) 

No. of 

Applications 

1-in-10 year 

Peak EEC 

1-in-10 year 

21-day average 

EEC 

1-in-10 year 

60-day average 

EEC 

Corn (broadcast) 4.0 1 44.8 43.7 41.1 

Corn (incorporated) 4.0 1 12.6 12.3 11.5 

Sweet Corn 

(broadcast) 4.0 1 11.3 10.7 9.8 

Sweet Corn 

(incorporated) 4.0 1 3.2 3.1 2.8 

Sorghum 

(broadcast) 4.0 1 46.7 45.6 42.7 

Sorghum 

(incorporated) 4.0 1 12.8 12.5 11.7 

Soybeans 

(broadcast) 3.0 1 32.9 31.9 27.1 

Soybeans, dry 

beans, lima beans 

(incorporated) 

3.0 1 9.3 9.0 7.7 

Woody ornamentals 

(Juniper and Yew) 

4.0 

(nursery use) 1 56.0 54.3 43.0 

4.0 

(residential use) 1 6.3 5.5 4.6 

Cotton (broadcast) 2.0 1 25.2 24.4 22.8 

Cotton 

(incorporated) 2.0 1 15.3 14.8 13.8 

Sunflowers 

(broadcast) 4.0 1 44.8 43.7 41.1 

Sunflowers 

(incorporated) 4.0 1 27.3 26.6 25.0 

Peasnuts 

(broadcast) 4.0 1 43.9 42.5 36.2 

Peanuts 

(incorporated) 4.0 1 12.4 12.0 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 NAWQA 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 

Page 59 of 132 
alachlor spanning a period from 1992 to 2007. Of these, a total of 96 samples detected alachlor 

(frequency of detection of 4.5%). Detections ranged from 0.0025 to 0.86 μg L-1 (MDL ranged 

from 0.002 to 0.005 μg 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 μg L-1 (MDL = 0.02 μg L-1); the detection of alachlor-OXA 

was 0.06 μg L-1 (MDL = 0.02 μg L-1), and the detection of alachlor sulfynilacetic acid was 0.03 

μg L-1 (MDL = 0.02 μg 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. USGS NAWQA Groundwater Data 

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 μg 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 μg L-1 (LOQa 

ranged from 0.002 to 1 μg 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 μg 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 al., 2007; Kuang, et al, 2003; 

Majewski et al., 2000; Foreman, et al, 1999; USGS, 1998; Goolsby et al., 1997; Gish et al., 

1995; Majewski and Capel, 1995; Capel et al., 1994), alachlor has been detected in rainwater and 

air samples across the United States and in France at variable frequency of detections. Often 

Page 60 of 132 
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 (3.3x10-8) 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 μg/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 μg/L, respectively, with a maximum concentration 

of 3.2 μg/L (USGS, 1998; Goolsby et al., 1997). Goolsby et al. (1997) reported detections of 

alachlor in approximately 20% of the rainwater samples at concentrations up to 3.2 μg/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 μg/L, in 1992 it was 16 percent and 2.2 μg/L, and in 1993 it was 74 % and 

12 μg/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 μg/L (range 

of maximum levels: 0.57 – 1.15 μg/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 lbs 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 
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 Reregistration 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 Number of 

Sites Maximum Peak (μg/L) Maximum TWMC1 

(μg/L) 

ARP Surface Drinking Water 

Supply Study 1995-2001 152-175 4.65 0.590 

USGS Midwestern Reservoir 

Reconnaissance 1992 76 ~ 5 to 10 Not reported 

USGS Mississippi River Basin 

Study 1991-1992 8 3.6 0.43 

USGS Midwestern Stream 

Reconnaissance 1989 48 51.3 11.6 

State of Illinois 1986-1988 30 18 0.81 

Lake Erie Basin Case Study 1983­

1987 7 91.47 1.74 

Monsanto Finished Surface Water 

Study 1986 30 9.5 1.1 

Monsanto Finished Surface Water 

Study 1985 30 12 1.5 

Ohio Tributaries to Lake Erie 

1982-1985 8 76 3.32 

USGS Cedar River Basin Study 

1984 6 23 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 μg/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 lb a.i./acre to 

4 lb a.i./acre in the 1990’s. An application rate of 6 lbs a.i./acre was modeled for comparison 

purposes using the CAnursery scenario. Modeling output showed peak concentrations that are 

Page 62 of 132 
within a reasonable margin of error to the peak monitoring data (84 μg/L compared to 91.5 

μg/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 lbs 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 TREX 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 doseadjusted EECs (mg/kg-bw) are summarized in Table 3.7. 

Page 63 of 132 
Table 3.7. Upper-bound Kenega Nomogram EECs for Dietary- and Dose-based Exposures 

of the CRLF and its Prey to Alachlor. 

Use(s) 

Application 

Rate (lb 

a.i./acre) 

EECs for CRLF 

(small birds used as a 

surrogate) 

EECs for Prey 

(small mammals) 

Dietarybased EEC 

(ppm) 

Dose-based 

EEC 

(mg/kg-bw) 

Dietary-based 

EEC (ppm) 

Dose-based 

EEC 

(mg/kg-bw) 

Corn 

4 540 615 960 915 

Sweet corn 

Grain 

sorghum 

Peanuts 

Woody 

ornamentals 

Sunflowers 

Soybeans 

3 405 461 720 686 Dry beans~ 

Lima beans 

(green) 

Cotton 2 270 308 480 458 

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 lbs 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. Dietarybased 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 mellifera) (used as a surrogate for terrestrial 

invertebrates) (Table 3.8). Available acute contact toxicity data for bees exposed to alachlor (in 

units of μg a.i./bee), are converted to μg 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. 

Page 64 of 132 
Table 3.8. EECs (ppm) for Indirect Effects to the Terrestrial-Phase CRLF via Effects to 

Terrestrial Invertebrate Prey Items. 

Use Application Rate 

(lb a.i./acre) Small Insect Large Insect 

Corn 

4 540 60 

Sweet corn 

Grain sorghum 

Peanuts 

Woody ornamentals 

Sunflowers 

Soybeans 

Dry beans~ 3 405 45

Lima beans 

Cotton 2 270 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. 

Page 65 of 132 
Table 3.9. Screening-Level Exposure Estimates for Terrestrial Plants to Alachlor. 

Use Application rate 

(lbs a.i./A) 

Spray drift 

EEC 

(lbs a.i./A) 

Dry area 

EEC 

(lbs a.i./A) 

Semi-aquatic 

area EEC 

(lbs a.i./A) 

Ground, Surface Applications1 

Corn 

4 0.04 0.24 2.04 

Sweet corn 

Grain sorghum 

Sunflowers 

Peanuts 

Woody ornamentals 

Soybeans 3 0.03 0.18 1.53 

Cotton 2 0.02 0.12 1.02 

Ground, Soil Incorporated (2 inches) Applications2 

Corn 

4 0.04 0.14 1.04 

Sweet corn 

Grain sorghum 

Peanuts 

Sunflowers 

Soybeans 

Dry beans 3 0.03 0.105 0.78 

Lima beans 

Cotton 2 0.02 0.07 0.52 

Bulk Fertilizer Applications3 

Corn 

4 0 0.1 1 Sorghum 

Soybeans 3 0 0.075 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 
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 
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 LD50 

values of <2, 2 – 11, and >11 μg/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 Aquatic Animals 

[LC50/EC50 (mg/L)] 

Birds and Mammals 

[LD50 (mg/kg-bw)] 

Birds 

[LC50 (mg/kg-diet)] 

Very highly toxic < 0.1 <10 <50 

Highly toxic 0.1 - 1 10 – 50 50 – 500 

Moderately toxic > 1 - 10 51 – 500 501 – 1000 

Slightly toxic > 10 - 100 501 – 2000 1001 – 5000 

Practically nontoxic > 100 >2000 >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. 

Page 68 of 132 
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. 

Page 69 of 132 
Table 4.2. Aquatic Toxicity Profile for Alachlor. 

Assessment 

Endpoint 

Acute/ 

Chronic Species 

Toxicity Value Used 

in Risk Assessment 

(mg a.i./L) 

Slope (95% 

C.I.) 

MRID/ 

ECOTOX 

Ref. No. 

Comment 

Freshwater 

fish (can be 

used as a 

surrogate for 

aquatic-phase 

amphibians) 

Acute 

Rainbow trout 

(Oncorhynchus 

mykiss) 

96-hr LC50 = 1.8 4.51

 00023616 

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 

Chronic 

Rainbow trout 

(Oncorhynchus 

mykiss) 

NOAEC = 0.187 

Not 

Applicable 

(N/A) 

438626-01 

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 

Acute 

African clawed 

frog (Xenopus 

laevis) 

96-hr LC50 = 6.1 4.51 

E66376 

(Osano et al., 

2002) 

The study was 

conducted using TGAI ; 

the study was nonguideline (no guidelines 

currently exist for an 

amphibian acute 

toxicity test) but 

scientifically sound 

Aquatic-phase 

amphibian 

Chronic 

African clawed 

frog (Xenopus 

laevis) 

NOAEC = 0.64 N/A N/A 

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) 

Freshwater 

invertebrates 

Acute 

Chironomid 

(Chironomus 

plumosus) 

48-hr EC50 = 2.5 4.51

 40098001 

The study was 

conducted using TGAI; 

this study is classified 

as ‘supplemental’ 

because the raw data 

were not available for 

review 

Chronic 

Chironomid 

(Chironomus 

plumosus) 

NOAEC = 0.036 N/A N/A 

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 
Assessment 

Endpoint 

Acute/ 

Chronic Species 

Toxicity Value Used 

in Risk Assessment 

(mg a.i./L) 

Slope (95% 

C.I.) 

MRID/ 

ECOTOX 

Ref. No. 

Comment 

for details) 

Acute 

Sheepshead 

minnow 

(Cyprinodon 

variegates) 

96-hr LC50 = 3.9 4.51 

445243-01 

The study is classified 

as ‘acceptable’ and was 

conducted using TGAI 

Estuarine/ 

marine fish 

Chronic 

Sheepshead 

minnow 

(Cyprinodon 

variegates) 

NOAEC = 0.41 N/A N/A 

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) 

Acute 

Mysid 

(Americamysis 

bahia) 

96-hr LC50 = 2.4 8.7 

(5.1 – 12.4) 445243-02 The study is classified 

as ‘acceptable’ and was 

conducted using TGAI 

Acute 

Eastern oyster 

(Crassostrea 

virginica) 

96-hr shell deposition 

EC50 = 1.6 4.51 

445243-03 

The study is classified 

as ‘acceptable’ and was 

conducted using TGAI 

Estuarine/ 

marine 

invertebrates 

Chronic Copepod 

(Tigriopus 

japonicus) 

NOAEC < 0.0001 N/A E104287 (Lee 

et al. 2008) 

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 F1 

generations) were seen 

at all of the conc. 

tested; a non-native 

species was used in the 

study. 

Aquatic plants 

N/A 

Aquatic plant 

(nonvascular) 

(Selenastrum 

capricornutum) 

NOAEC = 0.00035 

EC50 = 0.00164 

N/A 427638-01 

The study is classified 

as ‘acceptable’ and was 

conducted using TGAI; 

the NOAEC was based 

on reduced cell density 

N/A 

Aquatic plant 

(vascular) 

(Lemna gibba) 

NOAEL = 0.000339 

IC50 = 0.0023 

N/A 446497-02 

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 
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)]. LC50 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 LC50 values for fish were not located in the open 

literature. Therefore, the lowest LC50 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 LC50 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 LC50 = 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). 

Page 72 of 132 
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 et al., 2002). Sublethal effects, including edema, axial flexure, and 

gut and eye abnormalities, were also reported in this study (96-hr EC50 = 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 (Rana pipiens) larvae, the effects of alachlor alone (at a 

concentration of 0.1 μg a.i./L) and in a mixture of nine chemicals (0.1 μg a.i./L of each chemical 

and 10 μg a.i./L of each chemical) was investigated (E85815, Hayes et al., 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 μg 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 LC50 = 1.8 mg a.i./L; rainbow 

trout NOAEC = 0.187 mg a.i./L; African clawed frog LC50 = 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. 

Page 73 of 132 
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 virginica) (96-hr shell deposition EC50 = 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 LC50 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 bahia) 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 al., 2008). In this study, conducted with technical grade alachlor, 

the 96-hr LC50 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 F0 and F1 

generations) were seen in all of the concentrations tested (E104287, Lee et al., 2008). The 

lowest concentration tested in the study was 0.0001 mg a.i./L (0.1 μg 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 EC50 of 0.00164 mg a.i./L (1.64 μg ai/L) and a 

NOAEC of 0.00035 mg a.i./L (0.35 μg 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 μg ai/L); NOAEC = 0.000339 mg 

Page 74 of 132 
a.i./L (0.339 μg 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, Navicula pelliculosa, has an EC50 value of 2.63 mg ai/L (MRID 446497-04); 

the marine diatom, Skeletonema costatum, has an EC50 value of 0.21 mg a.i./L (MRID 446497­

03); and the cyanobacteria, Anabaena flos-aquae, has an EC50 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. 

Page 75 of 132 
Table 4.3. Terrestrial Toxicity Profile for Alachlor. 

Assessment 

Endpoint 

Acute/ 

Chronic Species 

Toxicity Value 

Used in Risk 

Assessment 

Slope (95% 

C.I.) 

MRID/ 

ECOTOX Ref. 

No. 

Comment 

Acute 

Bobwhite quail 

(Colinus 

virginianus) 

LD50 = 1499 mg 

a.i./kg-bw 4.51

 00079523 

The study is classified as 

‘acceptable’ and was conducted 

using TGAI 

Bird (used as a 

surrogate for 

terrestrialphase 

amphibians) 

Sub-chronic 

Bobwhite quail 

(Colinus 

virginianus) 

LC50 = >5620 mg 

a.i./kg-diet 

Not 

Applicable 

(N/A) 

430871-01 

The study is classified as 

‘acceptable’ and was conducted 

using TGAI; there were no 

mortalities during the study 

Chronic 

Mallard duck 

(Anas 

platyrhynchos) 

NOAEC = <50 mg 

a.i./kg-diet N/A 449515-01 

The study is classified as 

‘supplemental’ and was 

conducted using TGAI; there 

were significant reductions in 

hatchling weight at all 

concentrations tested 

Acute Norway rat (Rattus 

norvegicus) 

LD50 = 930 mg/kgbw 4.51

 00139383 

The study is classified as 

‘acceptable’ and was conducted 

using TGAI 

Mammal 

Chronic Sprague Dawley 

rat 

NOAEC = 30 

mg/kg-diet N/A 00075062 

The study is classified as 

‘acceptable’ and was conducted 

using TGAI; there were no 

reproductive effects at the 

highest dose tested (30 mg/kgdiet); LOAEL = >30 mg/kgdiet 

Terrestrial 

invertebrate 

Acute 

(Contact) 

Honey bee (Apis 

mellifera) 

LD50 >36.3 μg a.i. 

/bee 4.51 

00028772 

(Atkins et al. 

1973) 

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 

N/A 

Monocot 

(Rye grass – 

endpoint based on 

reduced dry 

weight) 

EC25 = 0.068 lb 

a.i./acre 

NOAEL = 0.037 lb 

a.i./acre 

N/A 

424686-01 

The study is classified as 

‘supplemental’; no solvent 

control was included in the 

study; TGAI was used instead 

of a TEP 

Terrestrial 

plants 

vigor) 

(Vegetative 

Dicot (Cucumber– 

endpoint based on 

reduced dry 

weight) 

EC25 = 1.4 lb 

a.i./acre 

NOAEL = 0.67 lb 

a.i./acre 

N/A 

N/A 

(Seedling 

emergence) 

Monocot 

(Rye grass - 

endpoint based on 

reduced dry 

weight) 

EC25 = 0.0067 lb 

a.i./acre 

NOAEL – 0.0023 lb 

a.i./acre 

N/A 

424687-01 

The study is classified as 

‘supplemental’; no solvent 

control was included in the 

study; TGAI was used instead 

of a TEP 

Dicot 

(Lettuce – 

endpoint based on 

phytotoxicity) 

EC25 = 0.034 lb 

a.i./acre 

NOAEL – 0.019 lb 

a.i./acre 

N/A 

1

 A slope was not determined in the study, therefore, the default slope is used. 

Page 76 of 132 
4.5.1 Toxicity to Birds and Terrestrial Phase Amphibians 

As specified in the Overview Document, the Agency uses birds as a surrogate for terrestrialphase amphibians when sufficient toxicity data for each specific taxonomic group are not 

available (USEPA, 2004). 

4.5.1.1. Birds: Acute and Subacute 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 (Anas platyrhynchos) 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 a NOAEC 

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) (NOAEC<50 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 LD50 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 
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 mellifera) 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 μg 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 LD50 value for alachlor and 

honey bees is >36.3 μg 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 EC25 values for onion height and 

Page 78 of 132 
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 lb a.i./acre (NOAEL= 0.0023 lb a.i./acre) based on biomass reduction. In the vegetative 

vigor study, the EC25 was 0.068 lb a.i./acre (NOAEL=0.037 lb a.i./acre) based on biomass 

reduction. The most sensitive dicot in the seedling emergence study was lettuce (Lactuca sativa) 

based on phytotoxicity, with an EC25 of 0.034 lbs a.i./acre and a NOAEC of 0.019 lbs a.i./acre. 

The most sensitive dicot in the vegetative vigor study was cucumber (Cucumis sativus) based on 

biomass reduction, with an EC25 of 1.4 lbs a.i./acre and a NOAEC of 0.67 lbs 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 
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 
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 LOC (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). 

Page 81 of 132 
Table 5.1. Summary of Aquatic RQs Used to Estimate Direct Effects to Aquatic-Phase 

CRLF and the DS1 

Use Site Exposure 

Type EEC RQ 

Corn (broadcast) Acute Peak = 44.8 μg/L 0.02 

Chronic 60-day = 41.1 μg/L 0.22 

Corn (incorporated) Acute Peak = 12.6 μg/L 0.01 

Chronic 60-day = 11.5 μg/L 0.06 

Sweet corn (broadcast) Acute Peak = 11.3 μg/L 0.01 

Chronic 60-day = 9.8 μg/L 0.05 

Sweet corn (incorporated) Acute Peak = 3.2 μg/L 0.002 

Chronic 60-day = 2.8 μg/L 0.01 

Sorghum (broadcast) Acute Peak = 46.7μg/L 0.03 

Chronic 60-day = 42.7 μg/L 0.23 

Sorghum (incorporated) Acute Peak = 12.8 μg/L 0.01 

Chronic 60-day = 11.7 μg/L 0.06 

Soybeans (broadcast) Acute Peak = 32.9 μg/L 0.02 

Chronic 60-day = 27.1 μg/L 0.14 

Soybeans, dry beans, lima beans 

(incorporated) 

Acute Peak = 9.3 μg/L 0.01 

Chronic 60-day = 7.7 μg/L 0.04 

Woody ornamentals (nursery-use) Acute Peak = 56.0 μg/L 0.03 

Chronic 60-day = 43.0 μg/L 0.23 

Woody ornamentals (residential use) Acute Peak = 6.3 μg/L 0.004 

Chronic 60-day = 4.6 μg/L 0.02 

Cotton (broadcast) Acute Peak = 25.2 μg/L 0.01 

Chronic 60-day = 22.8 μg/L 0.12 

Cotton (incorporated) Acute Peak = 15.3 μg/L 0.01 

Chronic 60-day = 13.8 μg/L 0.07 

Sunflowers (broadcast) Acute Peak = 44.8 μg/L 0.02 

Chronic 60-day = 41.1 μg/L 0.22 

Sunflowers (incorporated) Acute Peak = 27.3 μg/L 0.02 

Chronic 60-day = 25.0 μg/L 0.13 

Peanuts (broadcast) Acute Peak = 43.9 μg/L 0.02 

Chronic 60-day = 36.2 μg/L 0.19 

Peanuts (incorporated) Acute Peak = 12.4 μg/L 0.01 

Chronic 60-day = 10.2 μg/L 0.05 1

 Based on an LC50 of 1,800 μg a.i./L (Rainbow Trout) and a NOAEC of 187 μg a.i./L (Rainbow Trout). 

None of the RQs for any use exceed the Agency’s acute or chronic risk LOC 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. 

Page 82 of 132 
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 

(lb 

a.i./acre) 

Exposure Type EEC (ppm) RQ 

Flowable Soil Applications 

Corn 

4 

Acute 

615 

Sorghum 0.57 

Peanuts 

Woody ornamentals Chronic >10.8 Sunflowers 

Soybeans 

3 

Acute 

461 

0.43 

Dry beans Chronic >8.1 Lima beans 

Cotton 2 Acute 308 0.28 

Chronic >5.4 

Impregnated Bulk Fertilizer Surface Applications2 

Corn 4 Acute 42 mg a.i./ft2 1.93 Sorghum 

Soybeans 3 Acute 31 mg a.i./ft2 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 LOC for birds (0.1 and 1, respectively) 

Avian RQs exceed the endangered species LOC 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 
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 LOC 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 

LOC 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 
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 Exposure 

Type EEC RQ (Freshwater Invertebrates)1 

RQ 

(Estuarine/ 

Marine 

Invertebrates)2 

Corn (broadcast) Acute Peak = 44.8 μg/L 0.02 0.02 

Chronic 21-day = 43.7 μg/L 1.2 >437 

Corn (incorporated) Acute Peak = 12.6 μg/L 0.01 0.01 

Chronic 21-day = 12.3 μg/L 0.34 >123 

Sweet corn (broadcast) Acute Peak = 11.3 μg/L 0.005 0.005 

Chronic 21-day = 10.7 μg/L 0.30 >107 

Sweet corn (incorporated) Acute Peak = 3.2 μg/L 0.001 0.001 

Chronic 21-day = 3.1 μg/L 0.09 >31 

Sorghum (broadcast) Acute Peak = 46.7μg/L 0.02 0.02 

Chronic 21-day = 45.6 μg/L 1.3 >456 

Sorghum (incorporated) Acute Peak = 12.8 μg/L 0.01 0.01 

Chronic 21-day = 12.5 μg/L 0.35 >125 

Soybeans (broadcast) Acute Peak = 32.9 μg/L 0.01 0.01 

Chronic 21-day = 31.9 μg/L 0.89 >319 

Soybeans, dry beans, lima Acute Peak = 9.3 μg/L 0.004 0.004 

beans (incorporated) Chronic 21-day = 9.0 μg/L 0.25 >90 

Woody ornamentals Acute Peak = 56.0 μg/L 0.02 0.02 

(nursery-use) Chronic 21-day = 54.3 μg/L 1.5 >543 

Woody ornamentals Acute Peak = 6.3 μg/L 0.003 0.003 

(residential use) Chronic 21-day = 5.5 μg/L 0.15 >55 

Cotton (broadcast) Acute Peak = 25.2 μg/L 0.01 0.01 

Chronic 21-day = 24.4 μg/L 0.68 >244 

Cotton (incorporated) Acute Peak = 15.3 μg/L 0.01 0.01 

Chronic 21-day = 14.8 μg/L 0.41 >148 

Sunflowers (broadcast) Acute Peak = 44.8 μg/L 0.02 0.02 

Chronic 21-day = 43.7 μg/L 1.2 >437 

Sunflowers (incorporated) Acute Peak = 27.3 μg/L 0.01 0.01 

Chronic 21-day = 26.6 μg/L 0.74 >266 

Peanuts (broadcast) Acute Peak = 43.9 μg/L 0.02 0.02 

Chronic 21-day = 42.5 μg/L 1.2 >425 

Peanuts (incorporated) Acute Peak = 12.4 μg/L 0.005 0.01 

Chronic 21-day = 12.0 μg/L 0.33 >120 

1 Based on Chironomus plumosus endpoints (EC50 = 2,500 μg a.i./L; NOAEC = 36 μg a.i./L). 

2 Based on LC50 = 2,400 μg a.i./L (Americamysis bahia) and NOAEC < 0.1 μg a.i./L (Tigriopus

japonicus) 

Bolded numbers exceed the Agency’s listed species LOCs (RQ > acute endangered species LOC 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 
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 

Application 

Rate (lb 

a.i./acre) 

Size Class EEC (ppm) RQ1 

Corn 

4 

Sorghum Small insect 540 <1.9 

Peanuts 

Woody ornamentals Large insect 60 <0.21 Sunflowers 

Soybeans 

3 Small insect 405 <1.4 Dry beans 

Lima beans Large insect 45 <0.16 

Cotton 2 

Small insect 270 <0.95 

Large insect 30 <0.11 1 Available acute contact toxicity data for bees exposed to alachlor (in units of μg a.i./bee) are converted to 

μg a.i./g (of bee) by multiplying by 1 bee/0.128 g (LD50 = >36.3 μg a.i./bee = >283.6 μg/g). 

- Bolded RQs potentially exceed the interim risk to listed species LOC 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 μg a.i./bee), a definitive LD50 value was not determined. Therefore, 

although the estimated RQs for all alachlor uses are potentially above the Agency’s interim risk 

to listed species LOC 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 LOC 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 
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 
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 (lb 

a.i./acre) Dietary Category EEC (ppm) RQ 

Flowable Post-Plant, Pre-Plant, Pre-Emergence, and Burndown Applications1 

Corn 

Sorghum 

Peanuts 

Woody ornamentals 

Sunflowers 

4 

Short grass 915 0.45 

Tall grass 420 0.21 

Broadleaf plants/small insects 515 0.25 

Fruits/pods/large insects 57 0.03 

Seeds 13 0.01 

Soybeans 

Dry beans 

Lima beans 

3 

Short grass 686 0.34 

Tall grass 315 0.15 

Broadleaf plants/small insects 386 0.19 

Fruits/pods/large insects 43 0.02 

Seeds 10 0.00 

Cotton 2 

Short grass 458 0.22 

Tall grass 210 0.10 

Broadleaf plants/small insects 257 0.13 

Fruits/pods/large insects 29 0.01 

Seeds 6 0 

Flowable Pre-Plant and Pre-Emergence Bare Soil Applications2 

Corn 

Sorghum 

Peanuts 

Woody ornamentals 

Sunflowers 

4 

(3.42, it would be 

lower for 

sunflowers )3 

Short grass 783 0.38 

Tall grass 359 0.18 

Broadleaf plants 440 0.22 

Fruits/pods 49 0.02 

Seeds 11 0.01 

Small insects 515 0.25 

Large insects 57 0.03 

Soybeans 

Dry beans 

Lima beans 

3 

(2.57)3 

Short grass 588 0.29 

Tall grass 270 0.13 

Broadleaf plants 331 0.16 

Fruits/pods 37 0.02 

Seeds 8 0 

Small insects 386 0.19 

Large insects 43 0.02 

Cotton 

2 

(0.53)3 

Short grass 121 0.06 

Tall grass 56 0.03 

Broadleaf plants 68 0.03 

Fruits/pods 8 0 

Seeds 2 0 

Small insects 257 0.13 

Large insects 29 0.01 

Impregnated Bulk Fertilizer Surface Applications4 

Corn 4 Not Applicable 42 mg a.i./ft2 1.36 Sorghum 

Soybeans 3 Not Applicable 31 mg a.i./ft2 1.02 

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). 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 
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 LOC 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 LOC 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 LOC for non-listed mammals are for the 

impregnated bulk fertilizer applications (corn, sorghum, and soybeans). The acute risk LOC for 

non-listed species is not exceeded for any other alachlor use/application combination. 

Page 89 of 132 
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 (lb 

a.i./acre) Dietary Category 

Chronic 

Dose-Based 

RQ 

Chronic 

dietaryBased RQ 

Flowable Post-Plant, Pre-Plant, Pre-Emergence, and Burndown Applications1 

Corn 

Sorghum 

Peanuts 

Woody ornamentals 

Sunflowers 

4 

Short grass 278 32 

Tall grass 127 15 

Broadleaf plants/small insects 156 18 

Fruits/pods/large insects 17 2 

Seeds 3.9 2 

Soybeans 

Dry beans 

Lima beans 

3 

Short grass 208 24 

Tall grass 95 11 

Broadleaf plants/small insects 117 14 

Fruits/pods/large insects 13 1.5 

Seeds 2.9 1.5 

Cotton 2 

Short grass 138 16 

Tall grass 64 7 

Broadleaf plants/small insects 78 9 

Fruits/pods/large insects 9 1 

Seeds 1.9 1 

Flowable Pre-Plant and Pre-Emergence Bare Soil Applications2 

Corn 

Sorghum 

Peanuts 

Woody ornamentals 

Sunflowers 

4 

(3.42, it would 

be lower for 

sunflowers )2 

Short grass 237 27 

Tall grass 109 13 

Broadleaf plants 134 15 

Fruits/pods 15 2 

Seeds 3 2 

Small insects 156 18 

Large insects 17 2 

Soybeans 

Dry beans 

Lima beans 

3 

(2.57)2 

Short grass 178 21 

Tall grass 82 9 

Broadleaf plants 100 12 

Fruits/pods 11 1 

Seeds 2 1 

Small insects 117 14 

Large insects 13 1.5 

Cotton 

2 

 (0.53)2 

Short grass 37 4 

Tall grass 17 1.9 

Broadleaf plants 21 2.4 

Fruits/pods 2 0.3 

Seeds 0.5 0.3 

Small insects 78 9 

Large insects 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 LOC for mammals (1) 

Page 90 of 132 
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 LOC 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 

LOC 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 LOC 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 
Table 5.7. Summary of Acute RQs for Aquatic Plants Used to Evaluate Potential Indirect 

Effects to the CRLF and DS. 

Use Site Plant Type EEC RQ 

Corn (broadcast) Non-vascular aquatic plant1 

Peak = 44.8 μg/L 27.3 

Vascular aquatic plant2 19.5 

Corn (incorporated) Non-vascular aquatic plant1 

Peak = 12.6 μg/L 7.7 

Vascular aquatic plant2 5.4 

Sweet corn (broadcast) Non-vascular aquatic plant1 

Peak = 11.3 μg/L 6.9 

Vascular aquatic plant2 4.9 

Sweet corn (incorporated) Non-vascular aquatic plant1 

Peak = 3.2 μg/L 2.0 

Vascular aquatic plant2 1.4 

Sorghum (broadcast) Non-vascular aquatic plant1 

Peak = 46.7 μg/L 28.5 

Vascular aquatic plant2 20.3 

Sorghum (incorporated) Non-vascular aquatic plant1 

Peak = 12.8 μg/L 7.8 

Vascular aquatic plant2 5.6 

Soybeans (broadcast) Non-vascular aquatic plant1 

Peak = 32.9 μg/L 20.1 

Vascular aquatic plant2 14.3 

Soybeans, dry beans, lima Non-vascular aquatic plant1 5.7 

beans (incorporated) Vascular aquatic plant2 Peak = 9.3 μg/L 4.0 

Woody ornamentals Non-vascular aquatic plant1 34.1 

(nursery-use) Vascular aquatic plant2 Peak = 56.0 μg/L 24.3 

Woody ornamentals Non-vascular aquatic plant1 3.8 

(residential use) Vascular aquatic plant2 Peak = 6.3 μg/L 2.7 

Cotton (broadcast) Non-vascular aquatic plant1 

Peak = 25.2 μg/L 15.4 

Vascular aquatic plant2 11.0 

Cotton (incorporated) Non-vascular aquatic plant1 

Peak = 15.3 μg/L 9.3 

Vascular aquatic plant2 6.7 

Sunflowers (broadcast) Non-vascular aquatic plant1 

Peak = 44.8 μg/L 27.3 

Vascular aquatic plant2 19.5 

Sunflowers (incorporated) Non-vascular aquatic plant1 

Peak = 27.3 μg/L 16.6 

Vascular aquatic plant2 11.9 

Peanuts (broadcast) Non-vascular aquatic plant1 

Peak = 43.9 μg/L 26.8 

Vascular aquatic plant2 19.1 

Peanuts (incorporated) Non-vascular aquatic plant1 

Peak = 12.4 μg/L 7.6 

Vascular aquatic plant2 5.4 

1 Based on an EC50 = 1.64 μg a.i./L (Selenastrum capricornutum) 

2 Based on an EC50 = 2.3 μg a.i./L (Lemna gibba) 

Bolded numbers exceed the Agency’s aquatic plant LOC (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 EC25 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 
Table 5.8. Non-Listed Species Terrestrial Plant RQs for Alachlor Use in California1. 

Use Application 

Type 

ADJACENT 

UPLAND 

ADJACENT 

WETLAND DRIFT ONLY 

Monocot Dicot Monocot Dicot Monocot Dicot 

4 lb a.i./acre 

Corn 

Sorghum 

Peanuts 

Woody ornamentals 

Sunflowers 

Soil Surface 36 7 304 60 6 1 

Corn 

Sorghum 

Peanuts 

Sunflowers 

Soil 

Incorporated 

(2-inch 

incorporation) 

21 4 155 31 6 1 

Corn 

Sorghum 

Impregnated 

Bulk Fertilizer2 15 3 149 29 <0.1 <0.1 

3 lb a.i./acre 

Soybeans Soil Surface 27 5 228 45 4 0.9 

Soybeans 

Dry beans 

Lima beans 

Soil 

Incorporated 

(2-inch 

incorporation) 

16 3 116 23 4 0.9 

Soybeans Impregnated 

Bulk Fertilizer2 11 2 112 22 <0.1 <0.1 

2 lb a.i./acre 

Cotton 

Soil Surface 9 2 76 15 1 0.3 

Soil 

Incorporated 

(2-inch 

incorporation) 

5 1 39 8 1 0.3 

1

 Based on the following: monocots - EC25 = 0.0067 lb a.i./acre (seedling emergence) and EC25 = 0.068 lb a.i./acre 

(vegetative vigor) in annual dry grass (Lolium perenne); dicots - EC25 = 0.034 lbs a.i./acre [seedling emergence, 

lettuce (Lactuca sativa)] and EC25 = 1.4 lbs 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 LOC 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 LOC 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 LOC 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 
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: 

Page 94 of 132 
 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 LOC 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; LC50 = 

6.1 mg a.i./L, NOAEC = 640 μg a.i./L) and estuarine/marine fish (sheepshead minnow; LC50 = 

3.9 mg a.i./L, NOAEC = 410 μg 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 LOC 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 (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. 

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., I000636-003, B000164-001, I000799-009, I000038-001, I003826-017, 

I002793-001, and I000636-012). 

Page 95 of 132 
In another incident (I005002-008), 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 (I000431-001), 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 LOC 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). 

Page 96 of 132 
Table 5.9. Probability of Individual Effects to Terrestrial-Phase CRLF Based on Acute 

Data from Birds. 

Use Site 

Appl. Rate 

(lb 

a.i./acre) 

Acute RQ Slope 

(95% C.I.)1 

Chance of 

Individual Effects 

Flowable Soil Applications 

Corn 

4 0.57 

4.5 ~1 in 7.35 

Sorghum 2 ~1 in 3.2 

Peanuts 

Woody ornamentals 9 ~1 in 71.4 

Sunflowers 

Soybeans 

3 0.43 

4.5 ~1 in 20.2 

Dry beans 2 ~1 in 4.3 

Lima beans 9 ~1 in 206 

Cotton 2 0.28 

4.5 ~1 in 156 

2 ~1 in 7.4 

9 ~1 in 3,070,000 

Impregnated Bulk Fertilizer Surface Applications1 

Corn 

4 1.93 

4.5 ~1 in 1.1 

Sorghum 2 ~1 in 1.4 

9 ~1 in 1 

Soybeans 3 1.45 

4.5 ~1 in 1.3 

2 ~1 in 1.6 

9 ~1 in 1.1 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)0.799 

passerine FMR (kcal/day) = 2.123 (bw g)0.749 

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 

Page 97 of 132 
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. THERPS is available at: http://www.epa.gov/oppefed1/models/terrestrial/index.htm. 

For the uses with the highest application rates (4 lb a.i./acre), none of the acute RQs for 

terrestrial herpetofauna exceed the Agency’s listed species LOC 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 lb a.i./acre, 1 Application). 

EECs and RQs 

Size 

Class 

(grams) 

LD50 

(mg 

a.i./kg-bw) 

Broadleaf 

Plants/ 

Small Insects 

Fruits/Pods/ 

Seeds/ 

Large Insects 

Small Herbivore 

Mammals 

Small 

Insectivore 

Mammal 

Small 

Amphibians 

EEC RQ EEC RQ EEC RQ EEC RQ EEC RQ 

1.4 1499.00 20.98 0.01 2.33 0.00 N/A1 N/A N/A N/A N/A N/A 

37 1499.00 20.62 0.01 2.29 0.00 N/A N/A N/A N/A 0.72 0.00 

238 1499.00 13.51 0.01 1.50 0.00 93.03 0.06 5.81 0.00 0.47 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 lb 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 LOC (Table 5.11). None of 

the RQs for any other use exceed the LOC based on sub-chronic exposure. 

For chronic exposure, all of the alachlor uses exceed the Agency’s chronic listed species LOC of 

1 for at least one of the dietary categories using an avian NOAEC 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. 

Page 98 of 132 
Table 5.11. Upper Bound Kenaga, Sub-Acute and Chronic Terrestrial Herpetofauna 

Dietary-Based Risk Quotients for Alachlor (1 Application). 

Appl. 

Rate (lb 

a.i./acre) 

Endpoint 

(mg 

a.i./kgdiet) 

EECs and RQs 

Broadleaf Plants/ 

Small Insects 

Fruits/Pods/ 

Seeds/ 

Large Insects 

Small Herbivore 

Mammals 

Small 

Insectivore 

Mammals 

Small 

Amphibians 

EEC RQ EEC RQ EEC RQ EEC RQ EEC RQ 

Sub-Acute (Dietary) 

4 

LC50 = 

5620 

540.00 0.10 60.00 0.01 632.59 0.11 39.54 0.01 18.74 0.00 

3 405.00 0.07 45.00 0.01 474.44 0.08 29.65 0.01 14.06 0.00 

2 270.00 0.05 30.00 0.01 316.29 0.06 19.77 0.00 9.37 0.00 

Chronic (Dietary) 

4 

NOAEC 

<50 

540.00 >10.80 60.00 >1.20 632.59 >12.65 39.54 >0.79 18.74 >0.37 

3 405.00 >8.10 45.00 >0.90 474.44 >9.49 29.65 >0.59 14.06 >0.28 

2 270.00 >5.40 30.00 >0.60 316.29 >6.33 19.77 >0.40 9.37 >0.19 

- Bolded numbers (black) exceed the Agency’s listed species LOC. 

- Bolded numbers (gray) potentially exceed the Agency’s listed species LOC. 

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 LOC 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 

Page 99 of 132 
(broadcast) (RQ = 1.2) uses. Based on the CADPR PUR data, from 1999 to 2006 an average of 

<1 lb 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 LOC 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 affinis, 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) Tigriopus japonicus. Based on the T. 

japonicus endpoint, the chronic RQs exceed the Agency’s LOC 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 μg 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 μg a.i./L). If the 100 μg a.i./L endpoint is used to calculate RQs, none 

of the RQs for any alachlor use exceed the chronic risk LOC [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 

Page 100 of 132 
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 EC50 of 

1.64 μg/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 LD50 for terrestrial invertebrates could not be 

determined based on available data. For honey bees, a contact concentration of 36.3 μg 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 LD50 value and response slope could not be 

determined. Using an LD50 of >36.3 μg 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 LOC of 0.05 for acute risk to endangered terrestrial invertebrates. 

The chance of individual effects for terrestrial invertebrates using the IECv1.1.xls spreadsheet, 

the acute risk to endangered species LOC 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 lb a.i./acre results in EEC 

values of 60 and 540 ppm for large and small insects, respectively. Therefore, the concentration 

Page 101 of 132 
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 lb a.i./A). Inputting an application rate of 1.79 lb 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 LOC, however, the only RQs that exceed the Agency’s acute risk LOC 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 LOC 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, dietarybased) 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 NOAEC 

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 NOAEC 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 F3 females (maximal decrease of 17%)]. However, none of these effects were 

correlated with growth, survival, or reproductive endpoints. 

Page 102 of 132 
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 LOC 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 LOC 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 nonlisted species LOC 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 

Page 103 of 132 
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 LOC for all alachlor uses and application types. For the drift only RQs, all of 

the RQs exceed the Agency’s LOC 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). 

Page 104 of 132 
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 LOC, 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 LOC (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 aquaticphase 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 LOC, the ‘active rate’ (i.e., the 

highest maximum labeled rate) and the ‘initial average concentration’ (i.e., LC50 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. 

Page 105 of 132 
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 

Appl. Rate 

(lb 

a.i./acre) 

Terrestrial-phase CRLF Aquatic-phase 

CRLF and DS 

RQ 

Distance 

from Site of 

Appl. (in ft) 

Distance from Site 

of Appl. (in ft) 

Corn 

4 0.57 16.4 0 

Sweet corn 

Sorghum 

Peanuts 

Woody ornamentals (nursery) 

Woody ornamentals (residential) 

Sunflowers 

Soybeans 

Dry beans 3 0.43 13.1 0

Lima beans 

Cotton 2 0.28 3.3 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 lb 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 lb a.i./acre divided by the application rate in lb 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 μg a.i./L) is used to estimate the initial average concentration that would no longer exceed 

the LOC for plants (i.e.,EC50 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). 

Page 106 of 132 
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 

Appl. 

Rate (lb 

a.i./acre) 

Terrestrial Plants Aquatic Plants 

Distance from Site of 

Appl. (in ft) 

Distance from Site of 

Appl. (in ft) 

Corn 

4 886 216 

Sorghum 

Peanuts 

Woody 

ornamentals 

Sunflowers 

Soybeans 

Dry beans 3 748 151 

Lima beans 

Cotton 2 246 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 LOC. 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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Figure 5.1. Overlap Map: CRLF Habitat and Alachlor Initial Area of Concern. 

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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 terrestrialphase 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 quality may 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 

LOC 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 (USDA, 

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 postprocessing 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 1⁄4 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 remobilization of some chemicals from sediments can occur with changes in salinity (e.g., Means 

1995; Swarzenski et al. 2003; Jordan et al. 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 unconfined 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 upperbound 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 concentrationbased 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 aquaticphase 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 Disruptor 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 

LOC 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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Species Effects 

Determination 1 Basis for Determination 

Potential for Direct Effects 

California redlegged frog 

(Rana aurora 

draytonii) 

LAA1 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 subacute dietary exposure is low. However, the risk (or potential risk) to terrestrialphase 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. 

Delta Smelt 

(Hypomesus 

transpacificus) 

LAA1 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. 

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. Effects Determination Summary for Effects of Alachlor on the CRLF and the 

DS. 

1

 May affect, likely to adversely affect (LAA) 

Page 122 of 132 
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. 

Page 123 of 132 
• 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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