# Potential Risks of Alachlor Use to Federally Threatened California Red-legged Frog (

Rana aurora draytonii ) and Delta Smelt (Hypomesus transpacificus )

Pesticide Effects Determination s

Environmental Fate and Effects Divisio n Office of Pesticide Program s Washington, D.C. 2046 0

June 15, 200 9

### Primary Authors: Melissa Panger, Ph.D., Biologist Reuben Baris, Physical Scientist

Secondary Review: Thomas St eeger, Ph.D., Senior Biologist R. David Jones, Ph.D., Senior Agronomist

Branch Chief, Environmental RiskBranch 4: Elizabeth Behl

2Table of Contents

1.0 EXECUTIVE SUMMARY

.......................................................................................................... ... 8
1.1. P URPOSE OF A SSESSMENT

........................................................................................................... 8 1.2. A SSESSED C HEMICALS

................................................................................................................ 8 1.3. A SSESSMENT P ROCEDURES

......................................................................................................... 8 1.3.1. Toxicity A ssessment

................................................................................................................. 8 1.3.2. Exposure Assessment

............................................................................................................ .. 9 1.3.3. Measures of Risk

............................................................................................................... ...... 9 1.4. A LACHLOR U SES A SSESSED

...................................................................................................... 1 0 1.5. S UMMARY OF C ONCLUSIONS

..................................................................................................... 1 0
2.0 PROBLEM FORMULATION

....................................................................................................... 1 3
2.1. P URPOSE

.................................................................................................................................... 1 3 2.2. S COPE

........................................................................................................................................ 1 5 2.2.1. Evaluation of Degradates

...................................................................................................... 1 5 2.2.2. Evaluation of Mixtures

......................................................................................................... . 1 9 2.3 P REVIOUS A SSESSMENTS

........................................................................................................... 2 0 2.4 S TRESSOR S OURCE AND D ISTRIBUTION

.................................................................................... 2 1 2.4.1 Environmental Fate Properties

............................................................................................. 2 1 2.4.2 Mechanism of Action

............................................................................................................ . 2 5 2.4.3 Use Characterization

........................................................................................................... . 2 5 2.5 A SSESSED S PECIES

..................................................................................................................... 3 3 2.6. D ESIGNATED C RITICAL H ABITAT

.............................................................................................. 3 7 2.7 A CTION A REA

............................................................................................................................ 3 9 2.8 A SSESSMENT E NDPOINTS AND M EASURES OF E COLOGICAL E FFECT

....................................... 4 1 2.8.1. Assessment Endpoints

........................................................................................................... 4 1 2.8.2 Assessment Endpoints for Designated Critical Habitat

........................................................ 4 4 2.9 C ONCEPTUAL M ODEL

................................................................................................................ 4 4 2.9.1 Risk Hypotheses

................................................................................................................ .... 4 4 2.9.2 Diagram

................................................................................................................................ 4 5 2.10. A NALYSIS P LAN

......................................................................................................................... 4 7
3.0. EXPOSURE ASSESSMENT

....................................................................................................... . 5 1
3.1 A QUATIC E XPOSURE A SSESSMENT

............................................................................................ 5 1 3.1.1. Model Inputs

.......................................................................................................................... 54 3.1.2. Results

................................................................................................................................... 5 8 3.1.3. Existing Monitoring Data

..................................................................................................... 5 9 3.1.4 Impact of Typical Usage Inform ation on Exposure Estimates

.............................................. 6 3 3.2. T ERRESTRIAL A NIMAL E XPOSURE A SSESSMENT

...................................................................... 6 3 3.2.1. Potential Exposure to T errestrial In vertebrates

................................................................... 6 4 3.3 T ERRESTRIAL P LANT E XPOSURE A SSESSMENT

......................................................................... 6 5
4.0. EFFECTS ASSESSMENT

........................................................................................................ .... 6 6
4.1. E COTOXICITY S TUDY D ATA S OURCES

...................................................................................... 6 7 4.2. T OXICITY C ATEGORIES

.............................................................................................................. 6 8 4.3. T OXICITY OF C HEMICAL M IXTURES

.......................................................................................... 6 8 4.4 T OXICITY OF A LACHLOR TO A QUATIC O RGANISMS

................................................................. 6 9 4.4.1 Toxicity to Fish

............................................................................................................... ....... 7 2 4.4.2. Toxicity to Amphibians

......................................................................................................... . 7 3

34.4.3 Toxicity to Aquatic Invertebrates

.......................................................................................... 7 3 4.4.4 Toxicity to Aquatic Plants

..................................................................................................... 7 4 4.5 T OXICITY OF A LACHLOR TO T ERRESTRIAL O RGANISMS

.......................................................... 7 5 4.5.1 Toxicity to Birds and Terrestrial Phase Amphibians

............................................................ 7 7 4.5.2 Toxicity to Mammals

............................................................................................................ . 7 7 4.5.3 Toxicity to Terrestri al Invertebrates

..................................................................................... 7 8 4.5.4 Toxicity to Terrestrial Plants

................................................................................................ 7 8 4.6. U SE OF P ROBIT S LOPE RESPONSE R ELATIONSHIP TO P ROVIDE I NFORMATION ON TH E E NDANGERED S PECIES L EVELS OF C ONCERN

........................................................................................ 7 9 4.7 I NCIDENT D ATABASE R EVIEW

................................................................................................... 8 0
5.0 RISK CHAR ACTERIZATION

..................................................................................................... 8 0
5.1 R ISK E STIMATION

...................................................................................................................... 8 0 5.1.1 Direct Effects RQs

............................................................................................................. .... 8 1 5.1.2 Indirect Effects

............................................................................................................... ....... 8 3 5.1.3 Primary Constituent Elements of Designated Critical Habitat

............................................. 9 3 5.2 R ISK D ESCRIPTION

..................................................................................................................... 9 4 5.2.1. Direct Effects

................................................................................................................. ........ 9 5 5.2.2. Indirect Effects, DS and Aquatic-Phase CRLF

..................................................................... 9 9 5.2.3. Indirect Effects, T errestrial-Phase CRLFs

.......................................................................... 10 1 5.2.4 Spatial Extent of Potential Effects

....................................................................................... 10 5 5.3. M ODIFICATION OF D ESIGNATED C RITICAL H ABITAT

.............................................................. 11 1 5.3.1. CRLF

................................................................................................................................... 11 1 5.3.2. DS

........................................................................................................................................ 11 2 5.4. E FFECTS D ETERMINATIONS

..................................................................................................... 11 3 5.4.1 CRLF

................................................................................................................................... 11 3 5.4.2 DS

........................................................................................................................................ 11 3
6.0 UNCERTAINTIES

...................................................................................................................... 11 4
6.1 E XPOSURE A SSESSMENT U NCERTAINTIES

............................................................................... 11 4 6.1.1 Maximum Use Scenario

...................................................................................................... 11 4 6.1.2. Impact of Vegetative Setbacks on Runoff

............................................................................ 11 4 6.1.3 Aquatic Exposure Modeling of Alachlor

............................................................................. 11 5 6.1.4 Ground Water Uncertainties

............................................................................................... 11 7 6.1.5 Usage Uncertainties

............................................................................................................ 11 8 6.1.6 Terrestrial Exposure M odeling of Alachlor

........................................................................ 11 8 6.2 E FFECTS A SSESSMENT U NCERTAINTIES

.................................................................................. 11 9 6.2.1 Age Class and Sensitivity of Effects Thresholds

.................................................................. 11 9 6.2.2 Impact of Multiple Stressors on th e Effects Determination

................................................ 11 9 6.2.3. Use of Surrogate Sp ecies Effect s Data

................................................................................ 12 0 6.2.4 Location of Wildlife Species

................................................................................................ 12 1
7.0 RISK CO NCLUSIONS

............................................................................................................... 12 2
8.0 REFERENCES

................................................................................................................. ........... 12 4

4Appendices 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................. 1 1 Table 1.2. Effects Determination Summary for Al achlor Use and CRLF and DS Critical Habitat Impact Analysis. ..................................................................................................................................................... 11 Table 2.1. Major and Minor Degradates of Alachlor *

... ............................................................................ 1 6 Table 2.2. Summary of Formation Pathway of Alach lor Degradates of Concern (assumed equal toxicity to parent) a

... ................................................................................................................................................. 17 Table 2.3. Comparison of Aquatic Organism T oxicity Data for Alachlor and its Degradates. ................. 1 8 Table 2.4. Comparison of Mammalian Acute and Chr onic Toxicity Data for Alachlor and its Degradates.

... ................................................................................................................................................................. 19 Table 2.5. General Chemical/Physical Properties of Alachlor. ................................................................. 2 5 Table 2.6. Summary of Alachlor Products Registered in the U.S............................................................... 2 7 Table 2.7. Summary of Alachlor Application Methods and Rates for California.

..................................... 2 9 TABLE 2.8 Summary of California Department of Pesticide Registration (CDPR) Pesticide Use Reporting (PUR) Data from 1999 to 2006 for th e Currently Registered Alachlor Uses. ........................... 33 Table 2.9. Summary of Current Distribution, Habitat Requirements, and Life History Information for the Assessed Listed Species 1

. ........................................................................................................................... 34 Table 2.10. Designated Critical Habitat PCEs for the CRLF and DS........................................................ 3 8 Table 2.11. Taxa Used in the Analyses of Direct and Indirect Effects for the Assessed Listed Species.... 42

5Table 2.12. Assessment Endpoints Used to Evaluate the Potential for the Use of Alachlor to Result i n Direct and Indirect Effects to the CRLF and the DS.

............................................................................ ..... 4 3 Table 3.1. Summary of PRZM Scenarios

. ......................................................................................... ........ 5 4 Table 3.2. Summary of Environmental Fate Data for Alachlor

................................................................. 5 6 Table 3.3. Summary of Management Practices for PRZM/EXAM Modeling Input Parameters.

............. 5 7 Table 3.4. Summary of PRZM/EXAMS Chemcial Input Parameters for Alachlor

................................... 5 8 Table 3.5. Aquatic Total Toxic Residue EECs ( μ g/L) for Alachlor Uses in California

. ........................... 5 9 Table 3.6. Summary of Alachlor Detections in Surf ace Water by Study as Includ ed in the 1998 Alachlo r RED and 2006 Chloroacetanilide Cumulative Risk Assessment

................................................................ 6 2 Table 3.7. Upper-bound Kenega Nomogram EECs fo r Dietary- and Dose-based Exposures of the CRLF and its Prey to Alachlor

....................................................................................................... ........................ 6 4 Table 3.8. EECs (ppm) for Indirect Effects to the Terrestrial-Phase CRLF via Effects to Terrestria l Invertebrate Prey It ems.

.............................................................................................................................. 6 5 Table 3.9. Screening-Level Exposure Estimates for Terrestrial Plants to Alachlor

................................... 6 6 Table 4.1. Categories of Acute Toxicity for Terrestrial and Aquatic Animals

.......................................... 6 8 Table 4.2. Aquatic Toxicity Profile for Alachlor

.............................................................................. ......... 7 0 Table 4.3. Terrestrial Toxi city Profile for Alachlor

.......................................................................... ......... 7 6 Table 5.1. Summary of Aquatic RQs Used to Estimate Direct Effects to Aquatic-Phase CRLF and th e DS 1

... ........................................................................................................................................................... 8 2 Table 5.2. Summary of RQs Used to Estimate Dir ect Effects to Terrestrial-Phase CRLFs (Upper Boun d Kenaga Values, Dose-Based for 20 g Bird that Eats Small Insects) 1

. ... ...................................................... 8 3 Table 5.3. Summary of Acute and Chronic RQs for Aquatic Invertebrates Used to Evaluate Potentia l Indirect Effects to the CRLF and the DS R esulting from Potential Impacts to Food Supply

..................... 8 5 Table 5.4. Summary of Acute RQs for Terrestrial Invertebrates on the Site of Application Used t o Evaluate Potential Indirect Effects to the CRLF R esulting from Potential Impacts to the Food Supply.

.. 8 6 Table 5.5. Summary of Acute RQs for 15g Mammals (LD 50= 930 mg/kg-bw) Used to Evaluate Potentia l Indirect Effects to the CRLF Resulting from Potential Impacts to the Food Supply

.................................. 8 8 Table 5.6. Summary of Chronic RQs for 15g Mammals (NOAEC = 30 mg/kg-diet) Used to Evaluat e Potential Indirect Effects to the CRLF Resulting from Potential Impacts to the Food Supply.

................. 9 0 Table 5.7. Summary of Acute RQs for Aquatic Plants Used to Evaluate Potential Indirect Effects to th e CRLF and DS

.............................................................................................................................................. 9 2 Table 5.8. Non-Listed Species Terrestrial Plant RQs for Alachlor Use in California 1

.

... .......................... 9 3 Table 5.9. Probability of Individu al Effects to Terrestrial-Phase CRLF Based on Acute Data from Birds

.

... ................................................................................................................................................................. 9 7 Table 5.10. Upper Bound Kenaga, Acute Terrestri al Herpetofauna Dose-Based Risk Quotients fo r Alachlor (4 lb a.i./acre, 1 Application).

...................................................................................... ................ 9 8 Table 5.11. Upper Bound Kenaga, Sub-Acute and Chr onic Terrestrial Herpetofauna Dietary-Based Ris k Quotients for Alachlor (1 Application)

......................................................................................... .............. 9 9

6Table 5.12. Distance from Alachlor U se Site Needed to Reduce Exposure from Spray Drift to Levels that Do Not Exceed LOCs for Direct Effects.

......................................................................................... ........ 10 6 Table 5.13. Distance from Alachlor U se Site Needed to Reduce Exposure from Spray Drift to Levels that Do Not Exceed LOCs fo r Indirect Effects

. ....................................................................................... ........ 10 7 Table 7.1. Effects Determination Summary for Effects of Alachlor on the CRLF and the DS

............... 12 2 Table 7.2. Effects Determination Summary for Al achlor Use and CRLF and DS Critical Habit at Impac t Analysis.

................................................................................................................................................... 12 3

List of Figures
Figure 2.1. Estimated Annual Alachlor Usage in the U.S.

....................................................................... . 3 0 Figure 2.2. Average Pounds of Alachlor Applied/Year/CA County from 1999-2006

............................... 3 2 Figure 2.3. Delta Smelt Habitat Areas

. ........................................................................................ .............. 3 5 Figure 2.4. Recovery Unit, Core Area, CriticalHabitat, and Occurrence Designations for CRLF

. .......... 3 6 Figure 2.5. Potential Alachlor Use Sites in Ca lifornia Representing the Initial Area of Concern

............. 4 0 Figure 2.6. Conceptual Model for Risks to Terrestrial-Phase CRLF from Alachlor Use

.......................... 4 6 Figure 2.7. Conceptual Model for Risks to Aquatic-Phase CRLF and the DS from Use of Alachlor

....... 4 7 Figure 3.1 Application Dates for Alachlor (CDPR PUR Data; 2004 – 2005)

.......................................... 5 5 Figure 5.1. Overlap Map: CRLF Habitat and Alachlor Initial Area of Concern.

.................................... 10 9 Figure 5.2. Overlap Map: DS Habitat and Alachlor Initial Area of Concern

. ......................................... 11 0

71.0 Executive Summary

1.1. Purpose of Assessment
The purpose of this assessment is to evaluate potential direct and i ndirect 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-agricu ltural sites. In addition, this assessment evaluates whether these actions can be expected to result ineffects 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, 19 93 (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 herbicid e, 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 degr adates 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). Pote ntial risks to alachlor degradates were not quantified for terrestrial organisms since only on e 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 withprocedures and methodology outlined in the Agency’s Overview Document (USEPA, 2004).

1.3.1. Toxicity Assessment
The assessment endpoints include direct toxic e ffects on survival, reproduction, and growth of individuals, as well as indirecteffects, such as reduction of the food source and/or modification of habitat. Federally-designate d critical habitat has been esta blished 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 se nsitive toxicity value

Page 8 of 132available from acceptable or supplemental studies for each taxon relevant for estimating potential risks to the CRLF and DS and/or their de signated critical ha bitat was used.

1.3.2. Exposure Assessment

1.3.2.1. Aquatic Exposures
Tier-II aquatic exposure models were used to es timate high-end exposures of alachlor in aquatic habitats resulting from runoff and spray drift from different uses. Peak model-estimated environmental concentrations resulting from di fferent 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 fr om 6 lb a.i./acre to 4 lb a.i./acre in the 1990’s. Anapplication rate of 6 lbs a.i. /acre was modeled for comparison purposes using the CAnursery scen ario. Modeling output showed p eak 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 re duced application rate the concentration cannot be used to reflect potential concentrations from current use practice s and is not quantitatively used in this risk assessment.

1.3.2.2. Terrestrial Exposures
The T-REX model was used to estimate potentialalachlor exposures to terrestrial species including birds (surrogate speci es 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 determin e the distance from alachlor use sites the CRLF and the DS may be at risk of direct or indirect e ffects. The TerrPlant model was used to estimate alachlor exposures to terrestrial-phase CRLF habitat, in cluding plants inhabiting semi-aquatic and dry areas, re sulting from uses involving flowable and impregnated bulk fertilizer alachlor applications. The T- HERPS model was used to allow for further characterization of the dietary expos ures 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 compar ed to the Agency’s Levels of Concern (LOCs) to identify instances where alachlor use has the pot ential to adversely aff ect 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 ha ve “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 cau se effects to designated critical habitat, the best available additional information is consid ered to refine the potential for exposure and effects, and

Page 9 of 132distinguish actions that are NL AA (not likely to adversely aff ect) from those that are LAA (likely to adversely affect).

1.4. Alachlor Uses Assessed
All potential uses of alachlor wereevaluated 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 in gredient – alachlor. All of the alachlor end-use products are labeled as Restricted Use Pesticides (RUPs).
Based on California Department of Pesticide Regulation Pesticide Us e Reporting (CDPR PUR) data, almost all of the use of alachlor betw een 1999 and 2006 in CA was on corn (55%) and beans (45%). The remaining alachlor uses li sted 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 flowab le applications via gr ound 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 th e 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 th e 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 cumulativ e effects for the DS is provided in Attachment 4

.

Page 10 of 132Table 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 EffectsCalifornia redlegged frog (Rana aurora

draytonii ) LAA 1 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 ) LAA 1 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 ripa rian 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 th e 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 Endange red Species Act should be initiated.

Page 11 of 132When evaluating the significance of this risk assessment’s direct/indire ct 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 a ssumptions of drift and downstream transport ( i.e ., attenuation with distance), pestic ide exposure and associated risks to the species and its resources are expected to decrease with increasing distance away from th e treated field or site of application. Evaluation of the im plication of this non-uniform distribution of risk to the species would require information and assessment tec hniques that are not currently available.
When evaluating the significance of this risk assessment’s direct/indire ct 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, gi ven the assumptions of drif t and downstream transport ( i.e ., attenuation with distance), pesticide expos ure and associated risks to th e species and its resources are expected to decrease with increa sing 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 ty pe 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 applic able designated critic al habitat. This information would allow for quantitativ e 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 fo r 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 prel iminary picture of the types of food sources utilized by the assessed spec ies, it does not establish minimal requirements to sustain healthy individua ls at varying life stages. Such information could be used to establish bi ologically relevant thresholds of effects on the prey base, and ultimately establis h geographical limits to those effects. This information could be used together with the density data discussed above to characterize the likelihood of a dverse effects to individuals.

• Information on population responses of prey base organisms to the pesticide. Currently, methodologies are limited to pr edicting 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 characte ristics 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 pesticid e exposure would allow for a more refined determination of the magnitude and durati on of resource impairment, and together

Page 12 of 132with the information described above, a more complete prediction of effects to individual species and potential m odification to critical habitat.

2.0 Problem Formulation
Problem formulation provides a strategic framework for the risk assessment. By identifying the important components of the proble m, it focuses the assessment on the most relevant life history stages, habitat components, chemical properties, exposure routes, and en dpoints. The structure of this risk assessment is base d 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 labe led uses of alachlor. In ad dition, 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 w ith the methods described in the Agency’s Overview Document (USEPA 2004). The effects determinations for each listed species assessed is based on a we ight-of-evidence method that relie s 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 fo r modification of their desi gnated 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 me thodology described in the Overview Document (USEPA 2004), which specifies that “the assessment proce ss may, on a case-by-case basis, incorporate additional methods, models, and lines of evidence that EPA finds technically appropriate for risk management objectiv es” (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 base d 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 132level 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 rele vant sections of the action area including those geographic areas associated withlocations 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 hab itats associated with them. Designated critical habitat identifies specif ic 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 suit able breeding and non-br eeding 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 juven ile 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’ designate d 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 indire ct effects to individuals of a species are anticipated or effect s may impact the PCEs of the designated critical habitat, a preliminary “may affect” determination is ma de for the FIFRA regul atory action regarding alachlor.

If a determination is made that use of alachlo r “may affect” a listed sp ecies or its designated critical habitat, additional information is consid ered to refine the poten tial 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 ar e not likely to adversely affect” from those actions that “may aff ect 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 Ch aracterization 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 actio n 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 canbe reasonably linked to biolog ically mediated processes ( i.e ., the biological resource requirements for the listed spec ies associated with the critical habitat or

Page 14 of 132important 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. Ev aluation of actions related to use of alachlor that may alter the PCEs of the assessed species’ criticalhabitat form the basis of the critical habitat impact analysis. Actions that may affect the as sessed species’ designatedcritical 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 sunflo wers. The end result of the EPA pesticide registration process is an approve d 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 labe ls is “the action” being assessed.
This ecological risk assessment is for currently registered uses of alach lor in portions of the action area reasonably assumed to be biologically relevant to th e 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 poten tial ecological stressors resulting from the use of alachlor, including alachlor a nd its potential degradates of c oncern. Degradates of concern may include those that are found at significant concentrations (>10% by weight relative to parent) in available degradati on 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 toxicologica l concern is presented in Table 2.2

. Regarding all of the known degradates, the Heal th 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 datafor alachlor oxanilic ac id 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 aci d, 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 oxani lic acid and alachlor-ESA (USEPA, 2006). Theremaining 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 132approach was used for this assessment for aquati c exposure to evaluate th e potential exposure to the residues of risk concern, i.e ., alachlor and the three de gradates 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 applicati on 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-su lfoacetanilide 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-methoxy methyl-2-sulfoacetanilide Alachlor sulfonic acid, Alachlor-ESA MON 5775 XIII 2’,6’-diethyl-2-hydroxy-N -methoxymethylacetanilide None
Minor Degradates I 2’,6’-diethyl acetanilide None V 2’,6’-diethyl-2-me thoxyacetanilide None VI 2’,6’-diethyl-2-methyl sulfinylacetanilide None XII 2’,6’-diethyl- N-methoxymethyl-2-oxoacetanilide None XV 2’,6’-diethyl-N-me thoxymethyl-2-methylth ioacetanilide None
XVI 2’,6’-diethyl-N-methoxymethyl-2­ methylsulfin ylacetanilide None

XVII 2’,6’-diethyl-N-methoxymethyl-2­ methylsulfonylacetanilide None
XX 2’,6’-diethylbenzy l alcohol None XXII 2’,6’-diethyl-N- hydroxymethyl-2-methoxy acetanilide None
XXIII 8-ethyl-N-methoxymethyl-4-methyl-2­ oxotetrahydroquinoline None
XXIV 2’-acetyl-2-chloro-6’-ethyl-N-methoxyme thylacetanilide None *Bold text indicates degradates of toxicologicalconcern previously identified in USEPA, 2006.

Page 16 of 132Table 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) -- --

aValues in parentheses are percentage of parent formed ; half-lives for these compo unds for each formation pathway are presented following the percent fo rmation. 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 mi nor degradate 2,6-diethyaniline. Additionally, rat toxicity data are available for the major alachlor degradates alachlor oxanilic acid, alachlor sulfinylacetic aci d, 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 132Table 2.3. Comparison of Aquatic Organis m 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 EC 50 7.7 (40098001) >104 (43774703) >95 (43774705) --
Freshwater fish Rainbow trout ( Oncorhynchus mykiss ) 96-hr LC 50 1.8 (C.I.* = 1.5 – 2.1) (00023616) >104 (43774704) >100 (43774706) -- Amphibian African clawed frog

( Xenopus laevis ) 96-hr LC 50 6.1 (E66376) (Osano et al., 2002) -- -- 19.4 (E66376) (Osano

et al., 2002)

Aquatic plant (nonvascular) Green algae ( Selenastrum capricornutum ) 5-day EC 50 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 EC 50 EC 50= >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 EC 50 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 EC 50 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 EC 50 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 132Table 2.4. Comparison of Mammalian Acute a nd 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) LD 50930 >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 ingredie nt) each active ingredient is subject to an individual risk assessment for re gulatory decision regarding the active ingredient on a particular use site. If effects data are available for a fo rmulated product containing more than one active ingredient, they may be used qualitatively or quantitatively in accord ance with the Agency’s Overview Document and the Services ’ Evaluation Memorandum (USEPA, 2004; USFWS/NMFS, 2004). Alachlor does have two e nd-use products that are co-formulated with atrazine (and atrazine-re lated compounds), however, neither of these products is registered for use in California. Therefore, none of the alachlo r 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 aloneor 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 in creased. Conversely, when alachlor is found in combination with chemicals that show antagonistic effects, the toxicity of al achlor could be decreased. The potential increase or decrease in toxicity coul d be offset by other f actors including but not necessarily limited to: (1) the expos ed species, (2) the chemicals in th e mixture, (3) the ratio(s) of the chemical concentrations, (4) differences inthe 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 to xicity to any given taxa with confidence is beyond current capabilities. Howeve r, a qualitative discussion of implications of the available pesticide mixture effects data involving alachlor on th e confidence of risk

Page 19 of 132assessment 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 Eligibili ty 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 alach lor as a Restricted Use Pesticide. These mitigation measures have been implemented on current labels. The RED identified potential risk to terres trial 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 expos ure to alachlor, but were iden tified as having low risk from acute exposures.
The following data gaps were identified in th e EFED science chapter for the RED (USEPA, 1998b): terrestrial field dissipati on studies conducted outside of California, additional aquatic plant toxicity studies, an avian reproduction study, and aquatic plant studies for the alachlor degradate alachlor ethane sulf onic acid (alachlor-ESA). A dditionally, 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 cott on (USEPA, 2006a). The screeni ng-level assessment concluded that the use of alachlor on sunflowers and co tton could result in risk to Federally-listed threatened and endangered (listed) and non-lis ted terrestrial and a quatic 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 liste d avian species for several size class/forage item combinations. While a no-obs erved 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 ma mmals 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 effect s 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 1322.4 Stressor Source and Distribution

2.4.1 Environmental Fate Properties
As characterized in the RED (USEPA, 1998b), alachl or is stable to hydrol ysis at pH 3, 6, and 9 and stable to photolysis. Alachlor is metabolized at moderate rates (t 1⁄2 = 26 - 34 d) in aerobic soils, with several degradates observed, including DM-oxanilic acid, alachlor-ESA, alachlor oxanilic acid, and alachlor sulfi nylacetic 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 colu mn 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 appr eciably and is highly mobile.
Terrestrial field dissipation studi es are consistent with laborato ry 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 soilmetabolism study half-lives ranging from 26 to 34 days. It appears that the persistence and mob ility of the chemical may increase as it reaches deeper soil horizons that have lower organic matter content and decreased bi ological activity, thus, increasing its potential to leach into groundwater.
Degradation and Metabolism

Alachlor is a soluble chemi cal (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 K ow 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 so lutions at pH's 3, 6, and 9, and appears to be relatively stable in natural lake water (MRI D 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 re gression on log-transformed data of 26-34 days; the aerobic metabolism rates listed in the RED were faster but were 50% dissipation times (DT 50 ), not half-lives. The terres trial field dissipation studies in clude use of different sites, different formulations, and diffe rent soil types, and indicate that under aerobic soil metabolism conditions, alachlor degrades to several major meta bolites. 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 applie d), alachlor oxanilic acid (22.4% of the applied), and alachlor sulfinylacetic acid (16.2% of the applied). Alachlor sulfinyl acetic 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 persistentthan alachlor, since

Page 21 of 132significant concentrations remained in the soil s at the end of the studies. Carbon dioxide (complete mineralization) is th e 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 acetonitril e, 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’-die thylacetanilide, 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 degr adates include compounds 2’,6’-diethylacetanilide , 2’,6’-diethyl-2-methylsulfinylacetanilide, 2’,6’ -diethyl-N-methoxymethyl-2-oxoacetanilide, 2’,6’-diethyl-N-methoxymethyl-2-methylthioacet anilide, 2’,6’-diethyl-N-methoxymethyl-2­ methylsulfinylacetanilide, 2’,6 ’-diethyl-N-methoxymethyl-2-methyl sulfonylacetanilide, and 2’­ acetyl-2-chloro-6’-ethyl-N-methoxymethylacetanilide.
The major water soluble degradates of alachlo r, compounds DM-oxanilic acid, 2’,6’-diethyl-2­ sulfoacetanilide, alachlor sulf inylacetic 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 e quilibrium study on alachlor-ESA shows that this degradate is very weakly adsorbe d, although quantitative results could be obtained in only one of the soils (Sable silty cl ay 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/kg OC . Total toxic residues approach was usedfor 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 discussi on regarding the toxicity of major degradates of the parent alachlor.
The total residues of concern (TRO C) for alachlor were defined as parent plus 3 degradates of concern as listed in Table 2.2 . Structural analysis suggested th at an assumption of additivity is reasonable (USEPA, 2006). This modeling strate gy requires an assumption that all residues of concern have similar physical, chemical, and partitioning characteristics . The formation of persistent, toxic degradation produc ts is expected to extend the re sidual effects of the parent. Therefore, methology, outlined in the “White Paper on Methods for Assessing Ecological Risks of Pesticides with Persistent, Bioaccumulativ e 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 132methoxymethylacetanilide, and 2’6’-diethyl-2-hydroxy-N-methoxymethylacetanilide). Application rates for alachlor we re used to represent the total mass loading of pesticide and its degradation product. This modeling approach does not consider te mporal occurrence of degradation products.
Mobility
Based upon supplemental studies, alachlor app ears to be mobile in soils (MRID 27139, 27140, 78301, 134327). Freundlich soil partitioning coefficients (K ads ) for alachlor ranged from 0.35 to 3.7 L/kg (MRID 152209). Corresponding organic carbon distribution coefficient from the Alachlor Reregistration Eligibili ty 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 de gradates as well as the parent will be very mobile in soils due to th e 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 K ads value of 0.45 (K oc 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 availabl e for alachlor. The bioconcentration potential of alachlor is unclear, based on conflicting, unacc eptable data on the octanol-water partition coefficient. In the 1998 RED, it was indicated th at alachlor was not exp ected to bioconcentrate significantly in fish, based on a relatively low octanol/water partition coefficient (Kow= 434) and the low K owvalues of similar chloroacetanilides (U SEPA, 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 K owvalue of 3.3 x 10 3 (Hansch et al. , 1995), and the submitted K owvalue 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 fr om the most recent Health Effects Division’s (HED) risk assessment for alachl or (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 biph asic, 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 132urine 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/s andy clay loam soil plante d to corn. Most of the alachlor was found in the 0- to 18-inch soil layers, with occasio nal detections in the 18- to 24-, 24- to 36-, and 36- to 48-inch layers (the de epest layer sampled), indi cating 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 degradat es were detected in the 0­ to 6- and 6- to 12-inch soil depths at aver age concentrations of 0.010-0.045 ppm. Detections were observed through 36- to 48-inch soil depth fo r the oxanilic acid, 18- to 24-inch soil depth for the sulfinylacetic and sulfonic acids, and 6- to 12-inch soil de pth for the DM-oxanilic acid. Generally, detections occurred through 44-90 days post-treatment inthe subsoils. Once in the subsoils, these degradates appeared to persist. Groundwater was not mo nitored 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. Alach lor remained mostly in the 0- to 6-inch soil depth. Detections averaging 0.018-0.046 ppm were reported in th e 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-in ch 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. Alach lor 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 af ter 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 132Table 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 (K ads ) 0.33 - 3.7 L/kg 1 MRID 152209

Organic carbon partitioning coefficient (K oc ) 190 L/kg USEPA, 1998b

Octanol-water partition coefficient (K ow ) 1223 MRID 40396301

Bioconcentration factor (BCF) 48 – 102 (estimated) BCFWIN v2.15

1 Range of K ads 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 grow th inhibitor (Ross and Medlin, 2001), primarily disrupting the growth of new pl ant 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 fo r use on succulent and dry beans, field and sweet corn, cotton, woody ornamentals, peanuts, sorghu m (milo), soybeans, and sunflowers. For the woody ornamentals, there is nothing on the alachlo r labels that restricts the use to commercial uses, therefore, both commercial and residential uses will be considered here. There are currently five alachlor products regi stered 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 herbic ide atrazine (and atrazine-related compounds). However, both of these co-formulated products cont ain 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 132Lasso ® 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 labe led as Restricted Us e Pesticides (RUPs).

Page 26 of 132Table 2.6. Summary of Alachlor Pr oducts 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 inareas 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 al achlor on beans in Kern County, California. The labels also prohibit aeri al applications of alachlor in California, therefore, only ground applications will be assess ed here. The applicatio n rates and application methods are the same for the two products assess ed with the exception th at cotton and sunflower use are allowed on the Micro-Tech ®but not the Lasso ®label (see Table 2.7 ).

Page 27 of 132Both the maximum yearly and maximum single app lication 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 yearlymaximum application rate, are allowed on corn, peanuts, sorghum, and woody ornamentals (a minimu m 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 burndownprior to crop, preplant incorporated, preemergence surface, post-emergence surface (corn only), ground-crack surface (peanuts only), and post-transplant (woody or namentals only).

The Micro-Tech ®label contains restrictions for applications via ground and irri gation equipment. For ground applications, applications are restrict ed 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 chemigati on is limited to center pivots with a maximum wind speed of 10 mph during application. For dry bul k fertilizer applicati ons, 200 - 450 lb of dry bulk fertilizer per acre is stipul ated (with a maximum application rate of 3 to 4 lb a.i./acre, depending on the use, see Table 2.7). Wind sp eeds and droplet size distributions are not stipulated on the Lasso ®label. Both labels also c ontain 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 me thods and rates used in this assessment are summarized in Table 2.7

.

Page 28 of 132Table 2.7. Summary of Alachlor Applicat ion 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

Corn4 4 (no more than 2 can beapplied 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 co mmercial uses; therefore, it is assumed that alachlor coul d 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 labe l (524-314); the remaining uses appear on both labels

.

Page 29 of 132According to the United States Geological Survey’s (USGS) national pestic ide 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 co rn (~3%), dry beans (~2%), and peanuts (<1%). The highest usage, geographically, is in the corn-g rowing 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 av erage annual pesticide use in tensity 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 Di vision (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 132NASS 1 ), Doane ( www.doane.com ; the full dataset is not provideddue to its proprietary nature) and the CDPR PUR database 2 . 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 gene rated 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. Calculati ng county-level usage invo lved summarizing across all applications made within a section and then across all sections with in a county for each use site and for each pesticide. The county-level us age data that were calc ulated include: average annual pounds applied, average annual area treate d, 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 lb s/10,315 acre). Almost all of th e 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 in24 CA counties (listed in alphabetical order): Alameda, Butte, Fresno, Glenn, Kern, Los A ngeles, 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 th e past several years. For example, in 1999 a total of 29,327 lbs of alachlor wa s applied in CA, whereas a total of 13,734 lbs was applied in 2006 (see Appendix B ).

1 United States Depart of Agriculture (USDA), Nationa l 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

. 2The 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 132Figure 2.2. Average Pounds of AlachlorApplied/Year/CA County from 1999-2006.
Considering each CA county where alachlor wa s used, the average application rate per county/year from 1999 to 2006 ranged from <1 to 3.83 lb a.i./acre. The average 95 th % and 99 th % application rate and the maximum reported application rate per c ounty/year ranged from <1 to 3.99 lb a.i./acre [some counties reported 99 th % and maximum applicati on 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 al achlor users are using the chemical at or near maximum registered application rates.

Page 32 of 132TABLE 2.8 Summary of California Departme nt 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 regi stered 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-hi story 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 132Table 2.9. Summary of Current Distribution, Habitat Requirements, and Life History Information for the Assessed ListedSpecies1.Assessed SpeciesSizeCurrent RangeHabitat TypeDesignatedReproductiveDietCriticalCycleHabitat?California red-AdultNorthern CA coast, northernFreshwater perennialYesBreeding: Nov. to Apr.Aquatic-phase2: algaelegged frog(85-138 cmTransverse Ranges, foothills ofor near-perennialTadpoles: Dec. to Mar.(tadpoles only),(Rana aurorain length),Sierra Nevada, and in southern CAaquatic habitat withYoung juveniles: Mar. tofreshwater aquaticdraytonii)Females –south of Santa Barbaradense vegetation;Sept.invertebrates and fish9-238 g,Males –13-163 g;Juveniles(40-84 cmartificialimpoundments;riparian and uplandareasTerrestrial-phase:terrestrial invertebrates,small mammals, andfrogsin length)Delta smeltUp to 120Suisun Bay and the Sacramento-The species isYesSpawns in fresh orAdults forage primarily(Hypomesusmm inSan Joaquin estuary (known as theadapted to living inslightly brackish wateron planktonictranspacificus)lengthDelta) near San Francisco Bay, CAfresh and brackishupstream of the mixingcopepods, cladocerans,water. They typicallyzone. Spawning seasonamphipods, and insectoccupy estuarineusually takes place fromlarvae. Larvae feed onareas with salinitieslate March through mid-phytoplankton;below 2 parts perMay, although it mayjuveniles feed onthousand (althoughoccur from late winterzooplankton.they have been found(Dec.) to mid-summerin areas up to 18parts(July-August). Eggsper thousand).Theyhatch in 9 – 14 days.live along thefreshwater edge ofthe mixing zone(saltwater-freshwaterinterface).1For more detailed information on the distribution, habitat requirements, and life history information of the assessed listedspecies, see Attachment 32For the purposes of this assessment, tadpoles and submerged adult frogs are considered “aquatic” because exposure pathways in the water are considerablydifferent than those that occur on land.Page 34 of 132Figure 2.3. Delta Smelt Habitat Areas.

Page 35 of 13 2and 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 Valley 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 1322.6. 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 specie s at the time of the listing where the physical and biological features n ecessary for the conservation of the speci es exist, and there is a need for special management to protect the listed species. It may also in clude areas outside the occupied area at the time of listing if suchareas are ‘essential to the conservation of the species.’ Critical habitat receives protection under Se ction 7 of the ESA through prohi bition against destruction or modification with regard to actions carried out, funded, or au thorized by a federal Agency. Section 7 requires consultation on fe deral 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 ‘esse ntial to the conservation of the species.’ Critical habitat designati ons identify, to the exte nt known using the best scientific and commercial data available, habitat areas that provide essen tial 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, ai r, 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 disturban ce or are representative of the historic geographical and ecol ogical distributions of a species. Table 2.10 describes the PCEs for the critical habitats designated for the CRLF and the DS.

Page 37 of 132Table 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 grow th and viability of juvenile and adult CRLFs and their food source. Alteration of other chemical characteris tics 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 be tween 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 n ecessary for normal growth and viability of juvenile and adult CRLFs and their food source. DS Spawning Habitat—shallow, fresh or s lightly 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 Suis un Bay. Suitable water quality must be provided so that maturation is not impaired by pollutant concentrations. Rearing Habitat—Maintenance of the 2 pp t isohaline and suitable water quality (low concentrations of pollutants) with in 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 thei r 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 fo r habitat areas that provide essential life cycle needs o f the species such as, space for individual and population grow th and for normal behavior ; food, water, air, light , minerals, or other nutritional or physiological requiremen ts; cover or shelter; sites for breeding, reproduction , rearing (or development) of offspring; and habitats that are protected from disturbance or are representative of th e 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 ar e not evaluated because these processes are not biologically mediated and, therefore, are not relevant to the endpoint s included in this assessment

. More detail on the designated cr itical 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 132modify critical habitat are those that alter the PC Es and jeopardize the con tinued 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 fo r an analysis of potential e ffects on the designated critical habitat. Because alachlor is e xpected 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 canbe reasonably linked to biolog ically mediated processes.

2.7 Action Area
Deriving the geographical extent of the Calif ornia portion of the action area is based on consideration of the types of e ffects that alachlor may be expect ed 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, includ ing reduction in survival, growth, and fecundity as well as the full suite of sublethal effects availabl e 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 determin e 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-agricu ltural uses relativ e 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 132Figure 2.5. Potential Alachlor Use Sites in California Repres enting the Initial Area of Concern.

Page 40 of 13 2A number of alachlor studies have been conducted that have identified some type of biological effect (see Appendices C, D , and E ). Some studies have iden tified only exposure levels associated with an effect without a correspond ing no effect level. For example, the most sensitive available toxicity endpo int 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 F 0and F 1 generations at all of the concentrations tested (Lee et al . 2008, E104287). Additionally, the most sensitive av ailable NOAEC for birds based on chronic exposure is <50 mg a.i./kg-diet for mallard ducks ( Anas platyrhynchos ) based on significant treatment-related reducti ons in hatchling weight at all c oncentrations tested (MRID 449515-01). Therefore, a threshold for some type of environmen tal effect has not been identified, and it is not possible to identify an alachlor exposure leve l 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 envir onmental value that is to be protected.” 3 Selection of the assessment endpoi nts is based on valued entities ( e.g., CRLF and DS), organisms important in th e life cycle of the valued entities ( i.e ., the assessed species, and the PCEs of their de signated 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 eco logical receptors are exposed to alachlor (e.g., direct contact, etc.).

2.8.1. Assessment Endpoints
Assessment endpoints for the CRLF and the DS in clude 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, pot ential 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 a ssessed species. Each assessment endpoint requires one or more “measures of ecological effect,” de fined as changes in the attributes of an assessment endpoint or changes in a surrogate entity or attribute in re sponse to exposure to a pesticide. Specific measures of ecological effect are generally ev aluated 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 limite d to direct and indir ect effects associated with survival, growth, and fecund ity, and do not include the full suit e of sublethal effects used to define the action area. According to the Overview Document (USEPA 2004), the Agency relies on acute and chronic effects endpoin ts that are either direct meas ures of impairment of survival, growth, or fecundity or endpoint s for which there is a scientif ically robust, peer reviewed relationship that can quantify th e impact of the measured ef fect 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 132A complete discussion of all the toxicity dataavailable for this risk assessment, including resulting measures of ecological effect selected for each taxonomi c group of concern, is included in Section 4 of this document. A summary of the assessment endpoints and measures of ecological effect selected to char acterize potential assessed direct and indirect risks for each of the assessed species associ ated with exposure to alachlor is provided in Table 2.12

. As described in the Agency’s Overview Docu ment (USEPA, 2004), the mo st sensitive endpoint for each taxonomic group is used for risk estimati on. For this assessment, evaluated taxa include aquatic-phase amphibians, freshwater and saltwate r fish, freshwater and saltwater invertebrates, aquatic plants, birds (surrogate for terrestrial-phase amphi bians), 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 assess ed. The specific assessment endpoints used to assess the potential for direct and indirect effects to each listed sp ecies are provided in Table 2.8

. Table 2.11. Taxa Used in the Analyses of Direct and Indirect Effects fo r 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 Direct 1 Indirect (prey) Direct Indirect (prey) Indirect (food/ habitat) N/A = Not applicable; Terr. = Terrestrial; Invert. = Invertebrate; FW = Freshwate r 1 The most sensitive species across freshwater an d saltwater environments was used for the DS

.

Page 42 of 132Table 2.12. Assessment Endpoints Used to Evaluatethe 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 Species 1 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 LC 50(ECOTOX) or most sensitive fish acute LC 50(guideline or ECOTOX) if no suitable amphibian data are available 1b. Amphibian chronic NOAEC Indirect Effect (prey) Survival, growth, and -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 EC 50 (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 LC 50 (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 EC 50 (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 EC 50 (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 EC 50 (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 LC 50or LD 50 (guideline or ECOTOX) 6b. Most sensitive bird b or terrestrial- Indirect Effect (prey) Survival, growth, and -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 LC 50or LD 50 (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 terre strial invertebrate acute EC 50 or LC 50 (guideline or ECOTOX) c

Page 43 of 132Taxa Used to Assess Direct and/or Indirect

Effects to Assessed Species 1 Assessed Listed Species Assessment Endpoints Measures of Ecological Effects

terrestrial prey (terrestrial invertebrates) 8b. Most sensitive terre strial 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 EC 25 for monocots (seedling emergence, vegetative vigor, or ECOTOX 9b. Distribution of EC 25 for dicots (seedling emergence, vegetative vigor, or ECOTOX) 1 For the DS both freshwater and estuar ine/marine species are considered sin ce the DS can inhabit both freshwater and estuarine/marine environments.
2.8.2 Assessment Endpoints for De signated 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’ designate d critical habitat. PCEs for the assessed species we re previously described in Section 2.6. Actions that may modify critical habitat are those that alter the PC Es and jeopardize the con tinued existence of the assessed species. Therefore, these actions are identified as assessment e ndpoints. Evaluation of PCEs as assessment endpoints is limite d to those of a biological nature ( i.e ., the biological resource requirements for the listed species associ ated with the critical habitat) and those for which alachlor effects data are available.
Assessment endpoints used to evaluate potential for direct and indirect eff ects are equivalent to the assessment endpoints used to evaluate potential effects to designated critical habitat. If a potential for direct or in direct effects is found, then there is al so a potential for e ffects to critical habitat. Some components of PCEs are associated withphysical abiotic features ( e.g ., presence and/or depth of a water body, or distance betweentwo sites), which are not expected to be measurably altered by us e 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 desi gnated 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 desi gnated 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 desi gnated 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 desi gnated critical habitat by reducing or changing aquatic habi tat 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, biol ogical receptor types, and effects endpoints of potential concern. The conceptual models for a quatic 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 and2.7 . 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 qu antitatively 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 132Stressor

Source

Receptors

Attribute Change Alachlor applied to use site

Direct application Spra ydrift

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 In g estion

Ingestion In g estion Dermal u p take/In g estion Long range atmospheric

transport

Root uptake Wet/dry de p osition

Terrestrial-phase amphibians Ingestion

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

Page 46 of 13 2Stressor

Source

Exposure Media Alachlor applied to use site

Spra ydrift

Surface water/ Sediment Runoff Soil Groundwate r Long range atmospheric

transport

Wet/dry deposition

Uptake/gills Uptake/cell, or integument r oots, l ea v es Uptake/gills Receptors or integument

In g estion

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

In g estion A quatic Plants Non-vascular Vascula r Riparian plants terrestrial exposure pathways

Fish/aquatic-phase amphibians

Attribute Individual organisms Change Reduced survival Reduced growth Reduced reproduction Figure 2.7. Conceptual Model for Risks to A quatic-Phase CRLF and th e 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 estim ated 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 eff ects concentration) approach. A lthough 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 Docume nt (USEPA, 2004), the likelihood of effects to individual organisms from particul ar uses of alachlor is estimated using th e probit dose-response slope and either the level of concern (discussed be low) or actual calculat ed 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 alachlo r using maximum labeled application rates and methods of application. The models used to predict aquatic EECs are th e Pesticide Root Zone Model coupled with the Exposure Analysis Mode l System (PRZM/EXAMS). The model used to

Page 47 of 132predict terrestrial EECs on food items is T-REX. The model used to derive EECs relevant to terrestrial and wetland plants is TerrPlant. Th ese models are parameterized using relevant reviewed registrant-submitted environmental fate data.
PRZM (v3.12.2, May 2005) and EXAMS (v2.98.4.6, Ap ril 2005) are screening simulation models coupled with the input shell pe5.pl (August, 2007) to gene rate daily exposures and 1-in10 year EECs of alachlor that may occur in surf ace water bodies adjacent to application sites receiving alachlor through runo ff and spray drift. PRZM si mulates pesticide application, movement and transformation on anagricultural 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 standardscenario used for ecological pesticide assessments assumes applicati on to a 10-hectare agricultural field that drains into an adjacent 1-hectare water body, 2-meters deep (20,000 m 3 volume) with no outlet. PRZM/EXAMS was used to estimate screening-leve l exposure of aquatic organisms to alachlor. The measure of exposure for aquatic species is th e 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 mode led 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. App lication rates for the parent pesticide (alachlor) are used to represent the total mass loading of pesticide and its degradation product(s). Degradation half-liv es are calculated based on cumu lative residues of concern and parent alachlor (USEPA, 2008).
Exposure estimates for the terrestrial animals assu med to be in the target area or in an area exposed to spray drift are derived using th e T-REX model (version 1.4.1, 10/2008). This model incorporates the Kenega nomogr aph, 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 (Hoe rger and Kenega, 1972). The model is parameterized considering relevant, reviewed registrant-submitted and open literature fate data. The terrestrial exposure estim ates are based on parent alachlor alone.
For the post-emergence (corn only), ground-cr ack 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. Fo r the remaining types of flowable applications, estimated residues for terrestrial invertebrates will also be made for the targ et site of application using T-REX (since invertebrates could be on th e field of application during application). However, foliar residues are not e xpected 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 estimate s 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 132estimate 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./acr e) 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 becau se these categories resu lt in the largest RQs for the size/dietary categories in T-REX that are appropriate surrogates for the CRLF. Estimated exposures of terrestrial insect s 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 bu lk fertilizer will be treated as a granular formulati on for modeling purposes. Terrestrial exposures from impregnated fertilizer applications will be estimated usi ng 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 LD 50/ft 2values. The LD 50/ft 2values are calculated using an avian toxicity value and the EEC (mg a.i./ft 2 ) and are directly compared with Agency’s levels of concern (LOCs) for risk characterization purposes.
Birds are currently used as surrogates for terres trial-phase amphibians and reptiles. However, amphibians and reptiles are poi kilotherms (body temperature varies with environmental temperature) while birds are homeotherms (temperature is regulated, constant, and largely independent of environmental temperatures). Th erefore, amphibians and reptiles tend to have much lower metabolic rates and lower caloric inta ke requirements than birds or mammals. As a consequence, birds are likely to consume morefood than amphibians and reptiles on a daily dietary intake basis, assuming similar caloric co ntent 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 pha se 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 us ing 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 pe sticides 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 aquati c 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 al so considered.

Page 49 of 1322.10.2 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 toxi city data for aquatic life, terrestrial plants, and wildlife. ECOTOX was created and is main tained by the USEPA, Office of Research and Development, and the National Health and Envi ronmental Effects Research Laboratory's MidContinent Ecology Division.

The assessment of risk for direct effects to th e 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). Th e 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 LD 50 , LC 50and EC 50 . LD stands for "Lethal Dose", and LD 50is the amount of a material, given all at once, that is estimated to cause the de ath of 50% of the test organisms. LC stands for “Lethal Concentration” and LC 50is the concentration of a chemical that is estimated to kill 50% of the test organisms. EC stands for “Effective Concentration” and the EC 50is the concentration of a chemical that is estimated to produce a spec ific 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 b een reported to have no harmful (adverse) effects on test organisms. The NOAEC ( i.e. , “No-Observed-Adverse-EffectConcentration”) is the highest test concentratio n at which none of the observed effects were statistically different from the control. The NOEC is the No-O bserved-Effects-Concentration. For non-listed plants, only acute exposures are assessed ( i.e. , EC 25 for terrestrial plants and EC 50 for aquatic plants).

The measures of effect for direct and indirect effects to the assessed sp ecies and their designated critical habitat are associated with impacts to survival, growth , and fecundity, and do not include the full suite of sublethal eff ects used to define the action area. According the Overview Document (USEPA, 2004), the Agency relies on effects endpoints that are e ither direct measures of impairment of survival, growth, or fecundity or endpoints for which there is a scientifically robust, peer reviewed relationshi p that can quantify the impact of the measured effect endpoint on the assessment endpoints of surv ival, growth, and fecundity.

2.10.3 Measures of Risk
Risk characterization is the integration of e xposure and ecological effects characterization to determine the potential ecological risk from agri cultural and non-agricultural uses of alachlor, and the likelihood of direct and i ndirect effects to CRLF and the DS in aquatic and terrestrial habitats. The exposure and toxicity effects data ar e integrated in order to evaluate the risks of adverse ecological effects on non-targ et species. For the assessmen t of alachlor risks, the risk

Page 50 of 132quotient (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 sp ecies LOCs are used for comparing RQ values for acute and chronic exposures of alachlor dire ctly 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 assesse d 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, th en the effects determination is a LAA. If the acute RQ is between the listed species LOC and the non-listed acu te risk species LOC, then further lines of evidence ( i.e . probability of individual effects, species se nsitivity 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 informati on 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 dependentupon a combination of modeling and monitoring data. In accordance with the Overview Document (USEPA, 2004), screeninglevel exposures are based on modeling which assu mes a static water body. Aquatic exposures are quantitatively estimated for all of assessed us es using scenarios that represent high exposure sites for alachlor use. Each of these sites represents a 10-hectare fi eld 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 vul nerable water bodies that occur at the top of watersheds including prairie potholes, playa lakes, wetlands, vernal pools, man-made and natural ponds, and intermittent and first-order str eams. As a group, there are factors that make these water bodies more or less vulnerable than the standard surrogate po nd. Static water bodies that have larger ratios of drai nage area to water body volume w ould be expected to have higher peak EECs than the standard pond. These water bodies will be either sh allower 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 inthe 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 concentr ations 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 Un certainty Section (Section 6.1).
Specific management practices for all of the a ssessed uses of alachlor were used for modeling, including application rates, numbe r of applications per year, app lication intervals, and the first

Page 51 of 132application date for each use. In corporated 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 prof ile and can be easily tr ansported to aquatic resources via runoff. The general conceptual mo del 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 pr oximity to both agricultural and non-agricultural uses sites (for this assessment the action area represents the entire stat e of California).
Available usage data (USEPA, 2009) suggest that the heaviest usag e of alachlor relative to the action area is likely to be in the Central Valle y, although these use rates are much less than the use of alachlor in the Midwes tern 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 Ca lifornia scenarios are availabl e for use in ecological risk assessments representing predominantly agricu ltural uses. Of these, 16 were developed specifically for the CRLF assessments, 3 we re developed for the Organophosphate (OP) cumulative assessment (USEPA, 2006b), and 9 are standard scenarios. Each scenario is intended to represent a high-end e xposure setting for a particular use site . Scenario locations are selected based on various factors including crop acreage, runoff and eros ion 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 wa s conducted, and those scen arios that represent alachlor uses ( e.g., CA corn) were selected for modeling. Weather information was assigned to these scenarios at development. Second, addition al 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 av ailable. 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 s cenario and the residential scenario because CDPR PUR data indicate that alachlor is usedfor landscapeing purposes , therefore residential use cannot be eliminated from this assessment.
Residential use is a pote ntially important exposure pathway evaluated in this assessment. The amount of impervious surfaces associated with th e 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 tw o scenarios, one for Calif ornia residential turf and one for California impervious surfaces. EEC s 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 132description of the rationale fo r 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 fo r the percent lot treated was approximately 1,638.4ft 2(0.038 acre, or 15% of a typical lot). This wa s derived assuming that the entire perimeter of the 0.25 acre lot (104.4 ft le ngth) 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/w ater/przmenvironmentdisclaim.htm
A summary of all the modeled scenarios along withassociated 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 in terface (GUI) shell, PE5.pl. The models and GUI used in this as sessment may be found at the following website:
http://www.epa.gov/oppefed1/models/water/index.htm

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

Use Scenario First Application Min. Application

Interval Weather Station (WBAN #)

CornCAcornOP 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)

CottonCAcotton_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 em ergence 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 precipitati on 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 (Exp osure Analysis Modeling System). PRZM is used to simulate pesticide transport as a re sult of runoff and erosi on from a standardized watershed, and EXAMS estimates environmental fate and transport of pesticides in surface waters. The linkage program shell (PE5.pl) that in corporates the site-specific scenarios was used to run these models.

Scenarios used in this assessment consist of fourCalifornia-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 se lected to represent the highest rainfall potential in a region as described above. Linked site-specific use scenarios and meteor ological data were used to estimate exposure as a result of specific use for each mode ling scenario. The PRZM/EXAMS model was used to calculate conc entrations using the standard ecological water body scenario in

Page 54 of 132EXAMS. 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 Pr ofiles maintained by the USDA ( http://www.ipmcenters.org/cropprofiles/ and http://usda.mannlib.cornell.edu/re ports/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 app lication dates for alachl or 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

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une

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Month/YearNumber of Applications

Figure 3.1 Application Dates for Al achlor (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 Inpu t Parameters in Modeling the Environmental Fate and Transport of Pesticides, Versi on 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 132http://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 fateinput 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 MRID 1 (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*m 3 /molCalculated
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 (K d ) 0.33 MRID 152209 Represents lowest reported non-sand K d 1 Master Record Identification (MRID) is record tracking system used w ithin OPP to manage data submissions to the Agency. Each data submission if give n a unique MRID number for tracking purposes.

Page 56 of 132Table 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 132Table 3.4. Summary of PRZM/EXAMS Chemci al Input Parameters for Alachlor Input Parameter Value Source

Molecular Mass (g/mol) 269.77 MRID 146114

Vapor Pressure at 24 o 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 24 o C (mg/L) 2400 Represents 10x the measured water solubility value (Beestman and Deming, 1974) Soil-water distribution coefficient (K d ) 0.33 Represents the lowest reported non-sand K d(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 meanaerobic 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 assu ming 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 hi gh across durations of exposur e 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 132Table 3.5. Aquatic Total Toxic Residue EECs ( μ g/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 characterizi ng 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 A ssessment (NAWQA) program ( http://water.usgs.gov/nawqa ) focusing on the parent alachlor and three degrad ate products (alachlor-ESA, alachlor oxanilic acid, and alachlor sulfynilacetic ac id), and data from the CADPR that focused on the parent and two degradates (alachlor-ESA and alachlor oxani lic acid). In additi on, 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 132alachlor spanning a period from 1992 to 2007. Of these, a total of 96 samples detected alachlor (frequency of detection of 4.5%). Det ections ranged from 0.0025 to 0.86 μg L -1 (MDL ranged from 0.002 to 0.005 μg L -1 ). Surface water detections generallyoccurred in the spring and early summer months (March through July), which correl ates to the maximum us e period, according to CA PUR data. The maximum concentration dete cted was 0.86 ppb from Stanislaus County in 1992. The three degradate product s included in NAWQA (alachlor-E SA, 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 al achlor. 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 alachl or sulfynilacetic acid was 0.03 μg L -1 (MDL = 0.02 μg L -1 ). These degradates were includedin previous assessments and were found to be less toxic than the parent, therefor e, they are not included in this assessment.

3.1.3.2. USGS NAWQA Groundwater Data
Data from the USGS NAWQA website for alachl or 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; th ere were no reported detections of alachlor (MDL ranged from 0.002 to 0.005 μg L -1 ).

3.1.3.3. California Department of Pe sticide 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%). Con centrations 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), wh ich correlates to the maximum use period, according to CA PUR da ta. However, the majority of these data are included in the NAWQA database; it is presente d 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 evaluate d 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 de position, 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 132these studies are non-targeted to alachlor use and ther e 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 ha s 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 seasona lity attributed to the concentr ations 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, fr om 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 95 thand 99 thpercentile 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 leve ls in rainfall from 1991 to 1993 in Minnesota; in 1991, alachlor was detect ed in 15 % of the samples with a maximum concentration of 3.6 μg/L, in 1992 it was 16 pe rcent and 2.2 μg/L, and in 1993 it was 74 % and 12 μg/L. Subsequent 1994 monitoring data fr om 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 atmo sphere 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 prin cipal 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 Al achlor RED (USEPA, 1998b) and the Cumulative Risk Assessment for the Chloroacetanilides (U SEPA, 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 132in the late 1990s. Currently, few data ar e available after the mid-1990’s, except NAWQA, CDPR, and ARP which reported only very low c oncentrations 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 Re registration Partnership (ARP) study probably does not accu rately capture the effect of label revisions on monitoring concentration. Therefore, confirmatory data fromtargeted studies are no t available. No trend can be predicted for peak alachlor concentratio ns monitored in surface water and groundwater, however, as monitoring data are not representative of peak e xposure 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 occurren ce of alachlor in surfac e waters, as many of these studies are targeted studies examining th e 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 Chloroacetani lide Cumulative Risk Assessment. Study Number of Sites Maximum Peak (μg/L) Maximum TWMC 1 (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 3.3 2
USGS Cedar River Basin Study 1984 6 23 1.7

1 TWMC means time weighted mean concentrations, annual unless otherwise noted

. 2Time 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-1 0-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 ag riculture. The study with the high value was conducted before the maximum application rates for alachlor were reduced fr om 6 lb a.i./acre to 4 lb a.i./acre in the 1990’s. Anapplication rate of 6 lbs a.i. /acre was modeled for comparison purposes using the CAnursery scen ario. Modeling output showed p eak concentrations that are

Page 62 of 132within a reasonable margin of error to the peak monitoring data (84 μg/L compared to 91.5 μg/L). Therefore, due to the re duced application rate the concentration cannot be used to reflect potential concentrations from current use practice s 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 s uggests 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./acr e in California based on CDPR PUR data. This shows that the modeling conducted for this assessment provides reasonable exposure estimates, ba sed on alachlor use patterns.

3.2. Terrestrial Animal Exposure Assessment
T-REX (Version 1.4.1) is used to calculate diet ary and dose-based EECs of alachlor for birds (surrogate for reptiles and terrestrial-phase amphi bians), mammals, and terres trial 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 expo sure estimates that represent total residues (parent plus degradates), terrestrial exposure estim ates 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 y early application rate are the same for each use, only a single application (at the maximum application rate) was modeled, since this woul d 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-RE X for a small bird (20g) consuming small invertebrates. Potential impacts to mammalian pr ey base were evaluated in T-REX for a small mammal (15 g) consuming short grass. Resu lting dietary-based EECs (mg/kg-food) and doseadjusted EECs (mg/kg-bw) are summarized in Table 3.7.

Page 63 of 132Table 3.7. Upper-bound Kenega Nomogram EECs for Di etary- 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 (c orn, sorghum, and soybeans) of alachlor are treated as granular formulations for m odeling purposes. Therefore, an LD50/ft 2analysis 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/ft 2 ). Based on an application rate of 4 lbs a.i./acre (maximum bulk fertilizer application rate), the exposure value used in the LD50/ft 2analysis is 42 mg/ft 2

.
3.2.1. Potential Exposure to Terrestrial Invertebrates

T-REX is also used to calculate EECs for terrestrial invertebrates exposedto alachlor. Dietarybased EECs calculated by T-REX for small and larg e 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 da ta for bees exposed to alachlor (in units of μg a.i./bee), are conve rted 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 132Table 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 3 405 45 Dry beans~ Lima beans Cotton 2 270 30

3.3 Terrestrial Plant Ex posure Assessment
Terrestrial plants in riparian ar eas may be exposed to alachlor residues carried from application sites via surface water runoff or spray drift. Ex posures can occur directly to seedlings breaking through the soil surface and through r oot uptake or direct deposition onto foliage to more mature plants. Riparian vegetation is important to th e 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 ve getation were estimated using OPP’s TerrPlant model (USEPA, 2006e; Version 1.2.2). The TerrPl ant 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, th e bulk fertilizer applic ations are treated as granular applications ( i.e. , no drift is assumed). EECs relevantto 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 132Table 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 Applications 1 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) Applications 2 Corn

4 0.04 0.14 1.04 Sweet corn Grain sorghum Peanuts Sunflowers Soybeans 3 0.03 0.105 0.78 Dry beans Lima beans Cotton 2 0.02 0.07 0.52 Bulk Fertilizer Applications 3 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 applic ation rate for semi-aquatic areas adjacent to application sites. As expecte d, resulting exposure estimates for terrestrial plants are higher for surface than for soil incor porated applications.

4.0. Effects Assessment
This assessment evaluates the potential for alachlo r to directly or indirectly affect the CRLF and/or the DS or affect their de signated critical habitat. As discussed in Section 2, assessment endpoints for the assessed species include direct toxic effect s 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 ev aluating potential effects to the PCEs, which are components of the critical habi tat 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) toxi city information is characterized based on registrant-submitted studies and a comprehensive review of the open literature on alachlor,

Page 66 of 132consistent with the Overview Document (USEPA, 2004). Potential direct and indirect effects to the CRLF and the DS and potential effects to cri tical habitat are evaluated in accordance with the methods (both screening and speci es-specific refinements) descri bed 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 eff ect and reviews of the Ecological Incident Information System (EIIS), are conducted to fu rther refine the charac terization of potential ecological effects associated w ith exposure to alachlor.
A summary of the available aquatic and terrestrial organism ecot oxicity information, use of the probit dose-response relationship, an d 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 comprehens ive 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 or der 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 concentr ation/dose or applicati on rate is reported; and

• there is an explicit duration of exposure.
Meeting the minimum criteria for inclusion in EC OTOX 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 inco rporated qualitatively or quantitatively into this endangered species risk assessment. In genera l, only effects data in the open literature that are more conservative than the registrant-submitte d data are considered. The degree to which open literature data are quantitatively or qualitatively characteri zed 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 bioc hemical modifications are not likely to be used to calculate risk quotients unle ss it is possible to quantitati vely link these endpoints with reduction in survival, re production, or growth ( e.g ., the magnitude of effect on the biochemical endpoint needed to result in effects on surviv al, growth, or reproducti on is known). A summary of all accepted open literature and a bibliography of all open literature considered as part of this

Page 67 of 132assessment regardless of whether the data were accepted or rejected by ECOTOX is included in Appendix E

. As described in the Agency’s Overview Docu ment (USEPA, 2004), the mo st sensitive endpoint for each taxon is used for RQ calculation. Tables 4.3 (aquatic organisms) and 4.4 (terrestrial organisms) summarizes the most sensitive ecolo gical 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 andD

.
4.2. Toxicity Categories Toxicity to fish, aquatic invert ebrates, birds, and mammals is categorized using the system shown in Table 4.1 (USEPA, 2004). For non-target terrestrial insects, chemicals with LD 50 values of <2, 2 – 11, and >11 μg/bee are classifi ed as highly toxic, m oderately toxic, and practically nontoxic, resp ectively. Toxicity categories for terrestrial and a quatic plants have not been defined.
Table 4.1. Categories of Acute Toxicityfor Terrestrial and Aquatic Animals.

Toxicity Category Aquatic Animals [LC 50/EC 50(mg/L)] Birds and Mammals [LD 50(mg/kg-bw)] Birds [LC 50(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 formulati on, the available toxicity data show that other pesticides may combine with alachlor to produce synergistic, additive, an d/or antagonistic toxic interactions. The results of available toxicity data for mixtures of alachlo r 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 pres ent in the mixture. The variety of chemical interactions presented in the available data set suggest that the toxic e ffect 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 alach lor and co-contaminant concentrations, (4) differences in the pattern and duration of exposure among contaminan ts, and (5) the differential effects of other physical/chemical characteristic s 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 confid ence is beyond the capabilities of the available data.

Page 68 of 1324.4 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 rele vant to this ecological risk assessment for the CRLF and DS is presented below. A dditional information is provided in Appendix C.

Page 69 of 132Table 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 LC 50= 1.8 4.5 1 00023616 The study was conducted using TGAI 2 ; 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 LC 50= 6.1 4.5 1 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 EC 50= 2.5 4.5 1 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 132Assessment 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 LC 50= 3.9 4.5 1 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 LC 50= 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 EC 50= 1.6 4.5 1 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 F 0and F 1 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

EC 50= 0.00164 N/A427638-01 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

IC 50= 0.0023 N/A446497-02 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. 2TGAI = Technical grade active ingredient

Page 71 of 1324.4.1 Toxicity to Fish
Fish toxicity data were used to evaluate poten tial 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 avai lable for a few fish species [rainbow trout ( Oncorhynchus mykiss ), bluegill sunfish (Lepomis macrochirus ), channel catfish (Ictalurus punctatus ) and sheepshead minnow ( Cyprinodon variegates )]. LC 50values are similar across these species and range from 1.8 (rainbow trout ) to 16.7 (channel catfis h) 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 speci es 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 LC 50values for fish were not located in the open literature. Therefore, the lowest LC 50of 1.8 mg a.i./L reportedfor rainbow trout (MRID 00023616), is used for risk quotient calculations for the CRLF and DS. The LC 50value 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 (f reshwater fish) via potential effects to growth and reproduction. For fish, considering both re gistrant-submitted and open literature studies, there is only one acceptable chronic study availabl e 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 co ncentration. 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 re sults in a sheepshead mi nnow NOAEC of 0.41 mg a.i./L (rainbow trout LC 50= 1.8 mg a.i./L; rainbow trout NOAEC = 0.187 mg a.i./L; sheepshead minnow LC 50= 3.9 mg a.i./L; rainbow trout ACR = 1.8/0.187 = 9.6; 3.9/9.6 = 0.406).

Page 72 of 1324.4.2. Toxicity to Amphibians
Acute toxicity data for alachlor and aquatic-phase amphibians are available from two studies in the open literature. In th e first study, the 96-hr LC 50value for African clawed frog ( Xenopus larvis ) embryos (midblastula to early gastrula stages) exposed to te chnical grade alachlor was 6.1 mg a.i./L (E66376, Osano et al ., 2002). Sublethal effects, incl uding edema, axial flexure, and gut and eye abnormalities, were also reported in this study (96-hr EC 50= 3.6 mg a.i./L).
In an additional study invol ving fire-bellied toad ( Bombina orientalis ) embryos (newly fertilized), a 96-hr LC 50value 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) occurr ed 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, metolach lor, alachlor, and nicosulfuron; 3 insecticides: cyfluthrin, cyhalothrin, and tebupi rimphos; and 2 fungicides: methalaxyl and propiconizole) was meant to represent a potential environmentally rele vant mixture. At the concentrations tested, alachlor alone had no impact on the measured e ndpoints. However, th e 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 metamo rphosis). 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 fishis lower than the mortality endpoints in the amphibian studies, the acute freshwat er fish endpoint will be used to calculat e 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 toxi city data are currently available for amphibians and alachlor, therefore, the chronic endpoint for fr eshwater 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 Afri can clawed frog is used to estimate a chronic endpoint for amphibians to help ch aracterize risk to aquatic-phas e CRLF. This results in an African clawed frog NOAEC of 0. 64 mg a.i./L (rainbow trout LC 50= 1.8 mg a.i./L; rainbow trout NOAEC = 0.187 mg a.i./L; African clawed frog LC 50= 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 e ffects 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 1324.4.3.1. 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 a quatic invertebrates for food. For the indirect effects assessment, the most sensitive aquatic in vertebrate species is initially used for risk estimation, which is consistent with USEPA (20 04). The most sensitive aquatic invertebrate tested is the Eastern oyster ( Crassostrea virginica ) (96-hr shell deposition EC 50= 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 LC 50for the freshwater midge ( Chironomus plumosus ) is 2.5 mg a.i./L (MRID 40098001) while the 96-hr LC 50for the estauarine/marine mysid ( Americamysis bahia ) is 2.4 mg a.i./L (MRID 445243-02). Therefore, alachlor is classified as moderatelytoxic 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 LC 50value was 7.3 mg a.i./L.

4.4.3.2. Chronic Exposure Studies
Toxicity data from chronic exposure to alachl or are available for one freshwater [daphnid ( Daphnia magna )] and one estuarine/marine invertebrate species [copepod ( Tigriopus japonicus )]. The daphnid study, conducted with techni cal 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 F 0and F 1 generations) were seen in all of th e 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 ar e 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-vasc ular plant data are used to evaluate a number of the PCEs associated wi th the critical habitat impact analysis.

Alachlor is toxic to the freshwater green alga ( Pseudokirchneriella subcapitata , formerly Selenastrum capricornutum) , with a 120-hr EC 50of 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), ba sed 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. , EC 50 = 0.0023 mg a.i./L (2.3 μg ai/L); NOAEC = 0.000339 mg

Page 74 of 132a.i./L (0.339 μg ai/L); based on percent inhibi tion] (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 EC 50 value of 2.63 mg ai/L (MRID 446497-04); the marine diatom, Skeletonema costatum , has an EC 50value of 0.21 mg a.i./L (MRID 446497­ 03); and the cyanobacteria, Anabaena flos-aquae , has an EC 50value of >19 mg ai/L (446497­ 01)].

4.5 Toxicity of Alachlor to Terrestrial Organisms

Table 4.3 summarizes the most sensitive terrestrial to xicity 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 132Table 4.3. Terrestrial Toxici ty 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 ) LD 50= 1499 mg a.i./kg-bw 4.5 1 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 ) LC 50= >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 ) LD 50= 930 mg/kgbw 4.5 1 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 thehighest dose tested (30 mg/kgdiet); LOAEL = >30 mg/kgdiet

Terrestrial invertebrate Acute (Contact) Honey bee ( Apis mellifera ) LD 50>36.3 μg a.i. /bee 4.5 1 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) EC 25 = 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) EC 25 = 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) EC 25 = 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) EC 25 = 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 1324.5.1 Toxicity to Birds and Terrestrial Phase Amphibians
As specified in the Overview Document, the Agen cy 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 LD 50 value of 1,499 mg ai/kg-bw (MRID 00079523). Al achlor is also practically nontoxic to bobwhite quail and mallard duck ( Anas platyrhynchos ) on a subacute dietary exposure basis (LC 50 >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 (Gro wth, Reproduction) Studies
An avian reproduction study with the bobwh ite quail (MRID 449515-02) resulted in a NOAEC of 50 mg a.i./kg-diet, based on decreased mean hatchling weight (9% re duction at the 150 mg a.i./kg-diet concentration). Mean hatchling we ight 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 concen trations 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 th ere was also a statistic ally significant reduction in egg production, embryo viability and hatchabil ity 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 effect s 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. Anacute oral study with Norway rats (Rattus norvegicus ) resulted in an LD 50value 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 (M RID 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 gene ration 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 fo r reproductive effects was not es tablished in the study. There

Page 77 of 132were some systemic effects at 30 mg/kg-diet [kidney discoloration and de creased kidney weights and lower ovary weights in females of each parental generation and the F 3 females (maximal decrease of 17%)]. Therefore, the systemic toxicity LOAEC inthis study was 30 mg/kg-diet.

4.5.3 Toxicity to Terrestrial Invertebrates
Terrestrial invertebrate toxicity data are used to evaluate poten tial 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 practical ly nontoxic to honey bees ( Apis mellifera ) on an acute contact exposure basis (MRID 00028772). In this study, a dult 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. Th is study is classified as supplemental because it was not conducted using technical gr ade alachlor. Therefore, the LD 50value 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 eff ects could impact habitat and stream water quality as discu ssed 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 bioma ss are evaluated for both monocots and dicots, and evaluate effects at both seedling emergence and vege tative life stages. A guideline study generally evaluates toxicity to ten crop spec ies. A drawback to these studies is that they are conducted on herbaceous agricultural crop species only, and extrapol ation of effects to other species, such as woody shrubs, trees, and wild herb aceous species contributes uncertainty to risk conclusions.
Commercial crop species have b een selectively bred, and may be more or less resistant to particular stressors than wild herbs and forbs. Th e direction of this uncertainty for specific plants and stressors, including alachlor, is largely unknown. Homogenous testplant 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 vege tative 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 vegetativ e 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 EC 25 values for onion height and

Page 78 of 132tomato dry weight were not determined for the emergence study. These studi es are classified as ‘supplemental’.
Based on the results of the submitted terrestrial pl ant toxicity studies, alachlor is phytotoxic to many plant species. The herbicid e 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 studie s. In the seedling emergence study, the EC 25 was 0.0067 lb a.i./acre (NOAEL= 0.0023 lb a.i./acre) ba sed on biomass reduction. In the vegetative vigor study, the EC 25 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 EC 25 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 EC 25 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 so il/root uptake exposure than emerged plants via foliar routes of exposure. However, all te sted plants, with the exception of soybeans ( Glycine

max ) in the seedling emergence study, exhibited adverse effects follo wing exposure to alachlor.

4.6

. Use of Probit Slope Response Relati onship to Provide Information on the Endangered Species Levels of Concern
The Agency uses the probit dose-response relationship as a tool fo r providing additional information on the potential for acute direct eff ects to individual list ed species and aquatic animals that may indirectly affect the listed spec ies of concern (USEPA, 2004). As part of the risk characterization, an interp retation 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 toxi city 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 toxi city measures of effect for each taxonomic group that is relevant to this assessment. The indivi dual effects probability associated with the acute RQ is based on the mean estimate of the slop e and an assumption of a probit dose response relationship. In addition to a single effects probab ility estimate based on the mean, upper and lower estimates of the effects proba bility are also provided to account for variance in the slope, if available.
Individual effect probabilitie s are calculated based on an Ex cel 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 m odel 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 132default 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 alac hlor was completed in January 2009. Based on the EIIS database, ther e have been a total of 43 reported ecological incidents potentially involving alachlor (9 invol ving 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; involve d a misuse in three inci dents (two intentional and one accidental); and involved a registered use in two incide nts. Other chemicals besides alachlor, including other herbicid es and/or insecticides, were involved in all but one of the reported incidents involving aquatic animals. Th e certainty that alachlor was res ponsible for the fish deaths ranged from ‘unlikel y’ (two incidents) to ‘possibl e’ (four incident s) 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; involvedan accidental misuse in four incidents; and involved a registered alachlor us e in 23 incidents. Other herb icides besides alachlor were involved in all but 11 of th e reported incidents invol ving terrestrial plants ( i.e. , 11 of the incidents involved only alachlor and no other ch emicals). 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 th e exposure and effects characterizations. Risk characterization is used to determine the potential for direct and/or indire ct effects to the CRLF and the DS or modification to thei r 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 li kelihood 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 132risk 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”), a dditional 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 advers ely affect the assessed species and/or their designated critical habitat. Risk quotients used to eval uate 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 descri bed 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 incl ude 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 ar e classified as ‘supplemental’; th erefore, 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 lowe st acute and chronic toxi city values for birds exposed to alachlor (since no terrestrial-phase amphibian toxicity datawere available for alachlor). Toxicity values used to calculate RQ s are discussed in Secti on 4, and exposure values are discussed in Section 3. RQs used to esti mate acute and chronic direct effects are in Tables 5.1 (DS and aquatic-phase CRLF) and 5.2 (terrestrial-phase CRLF).

Page 81 of 132Table 5.1. Summary of Aquatic RQs Used to Estimate Direct Effects to Aquatic-Phase CRLF and the DS 1

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 LC 50of 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 acu te or chronic risk LOC for listed fish. Fish are used as a surrogate species for aquatic-phase CRLFs. These RQs are fu rther characterized in the context of the effects determination in Section 5.2.

Page 82 of 132Table 5.2. Summary of RQs Used to EstimateDirect 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 0.57 Sorghum 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 Applications 2 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 LD 50of 1,499 mg/kg-bw (Bobwhite Quail) and a NOAEC of <50 mg/kg-diet (Mallard Duck) 2Treated 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 po tential for alachlor to induce indirect effects. Pesticides have the potential to exert indirect effects upon listedspecies by inducing changes in structural or functional characteristics of affect ed communities. Perturbation of forage or prey availability and alteration of the ex tent and nature of habitat are ex amples 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, invertebrate s, aquatic plants, and terrestrial plants) are employed to make inferences concerning the potential for in direct 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 indirecteffects to listed sp ecies 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 fo r survival or reproduction, indirect effects are not expected to occur.
If LOCs are exceeded for organisms on which th e 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 proba bility that exposures

Page 83 of 132will 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 asse ssed species from potential effects on primary productivity of aquatic plants ar e a principle concern. If plant RQs fall between the risk to endangered species and non-endangered species LO Cs, 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 effect s to those listed specie s 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 zonevegetation may also indirectly affect the assessed species by reducing water quality and avai lable 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 RQ s exceed the Agency’s LOC for direct risk to non-endangered plant species, ba sed 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 im pacts to habitat due to increa sed sedimentation) is made. Further analysis of the potential for alachlor to affect the CRLF and the DS via reduction in riparian habitat includes a descri ption 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 availa bility and primary productivity as indicated by LOC exceedances. These RQs were based on the mo st sensitive surrogate species tested across aquatic invertebrate, fish, and aquatic plant sp ecies tested. Discussion of these RQs in the context of this effects determinati on 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 impacti ng 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 st andard 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 freshw ater and saltwater invertebrates.

Page 84 of 132Table 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 (EC 50 = 2,500 μg a.i./L; NO AEC = 36 μg a.i./L)

. 2 Based on LC 50= 2,400 μg a.i./L ( Americamysis bahia ) and NOAEC < 0.1 μg a.i./L ( Tigriopu s japonicus ) Bolded numbers exceed the Agency’s listed species LO Cs (RQ > acute endangered species LOC of 0.0 5 and the chronic LOC of 1.0)

. None of the acute RQs for freshwater or estu arine/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), so rghum (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 exceed ed for saltwater invert ebrates for all uses modeled [range : >31 (sweet corn, incorporateduse) - >543 (woody ornamentals)]. These RQs

Page 85 of 132were based on the most sensitive surrogate species across aquatic invertebrate species tested. Discussion of these RQs in the cont ext of this effects determinati on 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 Inv ertebrates 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) RQ 1

Corn

4 Small insect 540 < 1.9 Sorghum 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 (LD 50= >36.3 μg a.i./b ee = >283.6 μg/g).

- Bolded RQs potentially exceed the in terim risk to listed species LOC fo r 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 LD 50value was not determined. Therefore, although the estimated RQs for all alachlor uses ar e potentially above the Agency’s interim risk to listed species LOC for terres trial invertebrates (0.05), the ac tual 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 inmammal abundance as food is based on the 15 g size class, which results in higher RQs thanthe 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 gra sses, fruits, flowers, and invertebrates (USC,

Page 86 of 1322005; http://wotan.cse.sc.edu/pero base/systematics/p_calif.htm ). Therefore, the short grass food item was used to determine if mammals coul d 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 132Table 5.5. Summary of Acute RQs for 15 g Mammals (LD 50= 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 Applications 1
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 an d Pre-Emergence Bare Soil Applications 2

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 Applications 4 Corn 4 Not Applicable 42 mg a.i./ft 2 1.36 Sorghum Soybeans 3 Not Applicable 31 mg a.i./ft 2 1.02

1 Estimated residiues for potential food items found on the site of application

. 2Estimated residiues for potential food items found immediately adjacent to the site of application (except for small and largeinsects which ma y be exposed to alachlor on the site of application)

. 3 AgDRIFT was run, to estimate an ‘applicati on rate’ 1 ft off the site of application, using the default settings in Tier 1. Exce pt for the sunflowe r and cotton uses that are only on the label that has spray drift restrictions (ASAE medium-coars e droplet size distribution; ≤ 10 mph wind speed ; maximum 4-ft boom height). Only ground app lications were modeled for all uses

. 4 Treated as a granular formulation for modeling purpose s

- Bolded RQs exceed the acute risk LOC fo r listed mammals (0.1)

Page 88 of 132On 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 applic ations). Immediately adjacent to application sites, the RQs exceed the Agency’s acute risk LO C for listed mammals that eat short grass, tall grass, and broadleaf plants/small in sects 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 applic ations (corn, sorghum, and soyb eans). The acute risk LOC for non-listed species is not exceeded for any othe r alachlor use/application combination.

Page 89 of 132Table 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 ChronicdietaryBased RQ Flowable Post-Plant, Pre-Plant, Pre-Emergence, and Burndown Applications 1 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 Applications 2

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. 2Estimated residiues for potential food items found immediately adj acent to the site of app lication (except for small and large insects which may be exposed to alachlor on the site of applicati on). AgDRIFT was run using the default settings in Tier 1. Except for the sunflower and cotton uses th at 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 132The chronic RQs (all dietary cate gories; 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 am phibian prey items, birds are usedas a surrogate. As discussed above for direct effects to te rrestrial-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 bul k fertilizer applications).
Based on acute and chronic risk LOC exceedances, there is potential for alachlor to impact mammal and amphibian abundance, which could re sult in indirect effects to the CRLF. Discussion of these RQs in the cont ext of this effects determinati on 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 im pact terrestrial habitat quality and water quality parameters. Therefore, RQs for va scular and non-vascular aquatic pl ants are used to evaluate the potential for alachlor to affect the CRLF and/orthe DS by potentially impacting the food supply and water quality, and, thus, habitat ( Table 5.7 ). RQs for terrestrial plan ts 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 132Table 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 plant 1 Peak = 44.8 μg/L 27.3 Vascular aquatic plant 2 19.5 Corn (incorporated) Non-vascular aquatic plant 1 Peak = 12.6 μg/L 7.7 Vascular aquatic plant 2 5.4 Sweet corn (broadcast) Non-vascular aquatic plant 1 Peak = 11.3 μg/L 6.9 Vascular aquatic plant 2 4.9 Sweet corn (incorporated) Non-vascular aquatic plant 1 Peak = 3.2 μg/L 2.0 Vascular aquatic plant 2 1.4 Sorghum (broadcast) Non-vascular aquatic plant 1 Peak = 46.7 μg/L 28.5 Vascular aquatic plant 2 20.3 Sorghum (incorporated) Non-vascular aquatic plant 1 Peak = 12.8 μg/L 7.8 Vascular aquatic plant 2 5.6 Soybeans (broadcast) Non-vascular aquatic plant 1 Peak = 32.9 μg/L 20.1 Vascular aquatic plant 2 14.3 Soybeans, dry beans, lima Non-vascular aquatic plant 1 5.7 beans (incorporated) Vascular aquatic plant 2 Peak = 9.3 μg/L 4.0 Woody ornamentals Non-vascular aquatic plant 1 34.1 (nursery-use) Vascular aquatic plant 2 Peak = 56.0 μg/L 24.3 Woody ornamentals Non-vascular aquatic plant 1 3.8 (residential use) Vascular aquatic plant 2 Peak = 6.3 μg/L 2.7 Cotton (broadcast) Non-vascular aquatic plant 1 Peak = 25.2 μg/L 15.4 Vascular aquatic plant 2 11.0 Cotton (incorporated) Non-vascular aquatic plant 1 Peak = 15.3 μg/L 9.3 Vascular aquatic plant 2 6.7 Sunflowers (broadcast) Non-vascular aquatic plant 1 Peak = 44.8 μg/L 27.3 Vascular aquatic plant 2 19.5 Sunflowers (incorporated) Non-vascular aquatic plant 1 Peak = 27.3 μg/L 16.6 Vascular aquatic plant 2 11.9 Peanuts (broadcast) Non-vascular aquatic plant 1 Peak = 43.9 μg/L 26.8 Vascular aquatic plant 2 19.1 Peanuts (incorporated) Non-vascular aquatic plant 1 Peak = 12.4 μg/L 7.6 Vascular aquatic plant 2 5.4 1 Based on an EC 50= 1.64 μg a.i./L ( Selenastrum capricornutum ) 2 Based on an EC 50= 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 pl ants 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 EC 25 data as a screen. Based on the results of the submitted terrestrial plant toxici ty tests, emerging seedlings are more sensitive to alachlor via soil/root uptake th an emerged plants via foliar rout es of exposure. Therefore, the seedling emergence data were used to estimate terrestrial plant RQs for alachlor use. RQs used to estimate potential indirecteffects to the CRLF and/or th e DS from potential effects to terrestrial plants within their habitat areas are summarized in Tables 5.8

.

Page 92 of 132Table 5.8. Non-Listed Species Terrestrial Plant RQs for Alachlor Use in California 1.

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 Fertilizer 2 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 Fertilizer 2 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 - EC 25 = 0.0067 lb a.i./acre (seedling emergence) and EC 25 = 0.068 lb a.i./acre (vegetative vigor) in annual dry grass (Lolium perenne ); dicots - EC 25 = 0.034 lbs a.i./acre [seedling emergence, lettuce (Lactuca sativa )] and EC 25 = 1.4 lbs a.i./acre [vegetative vigor, cucumber ( Cucumis sativus )]. 2Impregnated bulk fertilizer applications are treatedas 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 fo r all alachlor uses and application types (RQs range from 1 – 60 for dicots; and 5 – 304 for mo nocots). 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 fo r 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 as sessment endpoints for designated criti cal habitat PCEs involve the same endpoints as those being assessed re lative to the potential for directand indirect effects to the listed species assessed here. Therefore, the effects determinations for direct and indirect effects

Page 93 of 132presented in Section 5.1 are used as the basi s of the effects determination for potential modification to designated critical habitat.

5.2 Risk Description
The risk description synthesizes overall conclusi ons 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 th e 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 orindirect effects for the assessed species, and no effect s 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 th ere are effects to the PCEs of th e critical habitat, the Agency concludes a preliminary “may af fect” determination for the FI FRA regulatory action regarding alachlor.
None of the RQs for alachlor exc eed the listed species LOCs (acu te and chronic risk) for fish. Fish are used as a surrogate for aquatic phase am phibians. The RQs for 20 g birds that eat short grass (used as a screening-level surrogate fo r terrestrial-phase CRLF) exceed the risk to endangered species LOCs (acute an d chronic) for all of the alachlo r 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 indi rect effects to DS and CRLF and effects to their designated critical habitat, at least some of the RQs fo r mammals, aquatic invertebrates, birds, plants (aquatic and terrestrial) and potentially terres trial invertebrates exceed the Agency’s listed species LOCs. Therefore, there is a potential fo r indirect effects to DS and CRLF and effects to their critical habitat. Due to the potential for di rect and/or indirect effects, alachlor use ‘may affect’ DS and CRLF and/or thei r designated critical habitat.
Following a “may affect” determination, additiona l 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 contex t 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, br eeding, 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 benefi cial 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 designatedcritical 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 acu te or chronic risk LOCs for listed fish. The listed species LOC of 0.05 is associated witha 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; LC 50= 6.1 mg a.i./L, NOAEC = 640 μg a. i./L) and estuarine/marine fish (sheepshead minnow; LC 50= 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 toxi city endpoints for the African clawed frog and the sheepshead minnow would also result in no LOC exceedances fo r any alachlor use. The sheepshead minnow results are consistent with a 5-ye ar field study that investigated the effects of three pesticides (including alachlor) on estuaries in North Carolin a from runoff from adjacent farm lands (MRID 44105503) (see Appendix A for details). The pestic ides 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 th e available toxicity data and exposure models, there are nine reported fish kills associated w ith alachlor in the EIIS database (they occurred between 1983 and 1995 and involved from an ‘unknow n’ 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 ninereported fish kills asso ciated with alachlor was conducted. In seven of the nine reported fish kill incidents involving al achlor, other chemicals known to be highly toxic to fish were also involvedin the incidents and ar e 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 132In another incident (I005002-008), the co-formulated product Bullet ® (alachlor + atrazine) (this product is not registered for use in California) wa s used on an agricultural field and shortly after it began to rain. Within 3 days, dead fish (ba ss and bluegill sunfish) we re evident in a nearby pond. Ten days following application, alachlor, atrazine, and metolachlor residues were detected in the water from the affected pond. This incide nt 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 incide nt, a fish kill in a ‘fis h 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 ‘undete rmined’. 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 relativel y low toxicity of alachlor to fishand 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 s cenario 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 indir ectly affected the fish.
Therefore, the weight of evidence based on the currently available data suggests that direct effects to aquatic-phase CRLFs a nd DS are not expected from the use of alachlor in California. The potential for indirect effect s 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 co rn/sorghum). These RQs exceed the acute risk to endangered spec ies LOC and are associated with a probability of an individual effect of approximately 1 in 1 to 1 in156, depending on the use being evaluated ( Table 5.9 ).

Page 96 of 132Table 5.9. Probability of Individual Effect s 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 9 ~1 in 71.4 Woody ornamentals 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 Applications 1 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 terres trial-phase CRLFs. Terrestrial-phase amphibians are poikilotherms, whic h means that their body temperatur e 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. Theref ore, 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 amphi bians) 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 al lometric 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 di fferences 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 feed ing 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 be40 times more sensitive than birds for the

Page 97 of 132differences in dietary uptake to be negated. Ho wever, existing dietary toxicity studies in terrestrial-phase ampibians for al achlor 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 inT-REX for birds, and additional food items ofthe 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./a cre), 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 Terres trial Herpetofauna Dose-Based Risk Quotients for Alachlor (4 lb a.i./acre, 1 Application). EECs and RQs Size Class (grams) LD 50 (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/A 1 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 herp etofauna that eat broadl eaf 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 ex ceed 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 expos ure 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 132Table 5.11. Upper Bound Kenaga, Sub-Acute a nd Chronic Terrestrial Herpetofauna Dietary-Based Risk Quotients fo r Alachlor (1 Application).

Appl. Rate (lb a.i./acre) Endpoint (mga.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 LC 50= 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 ex ceed the Agency’s listed species LOC.

These results indicate that the ri sk of direct adverse effects to terrestrial-phase CRLF from acute oral or sub-acute dietary exposure is likely low. However, the risk (or po tential risk) to terrestrial-phase CRLF from chronic dietary expo sure cannot be preclude d and exists for all dietary classes relevant to the CRLF (forall 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 (I ndirect 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 a nd 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 availabl e. The highest acute RQ is 0.02 [for the woody ornamental (nursery) use]. At this RQ and usi ng 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 (bro adcast) (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 CADP R PUR data, from 1999 to 2006 an average of <1 lb of alachlor per year was applied to w oody 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 freshwat er 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 th e most sensitive freshwater invertebrates, any potential impact to aquatic-phase CRLFs would likely be immeas urable 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 su nflower uses; however, such an effect would likely be insignificant to the CRLF.

DS
The DS eats small zooplankton. They primarily eat planktonic c opepods, cladocerans, amphipods, and insect larvae. However, the mo st 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 alachlo r use exceed the Agency’s acute risk LOCs (listed or non-listed species) [acute RQs range fr om 0.001 (sweet corn) to 0.02 (woody ornamentals)]. At the highest RQ (0.02) and us ing a slope of 8.7, the prob ability of an effect would be approximately 1 in 1.03E+49. Therefor e, 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 af ter 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 us e exceed the chronic risk LO C [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 significan ce of the effect of extending the nauplius phase

Page 100 of 132in copepod prey by roughly one day. Although increased generation time could decrease copepod populations over an extend ed period of time, the impactfrom alachlor use to copepod (and other estuarine/marine invertebrate) populations is not exp ected to be large enough to impact the DS indirectly. This, again, is consiste nt with the study that inve stigated the effects of three pesticides (including alach lor) on estuaries in North Carolin a 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 biolog ical 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 EC 50of 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 s ites 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 orname ntal (nursery) uses. Therefor e, impacts to aquatic plants found near alachlor use s ites are expected.

5.2.3. Indirect Effects, T errestrial-Phase CRLFs
As discussed in Section 2, the di et of terrestrial-phase CRLFs includes terrestrial invertebrates, small mammals, and amphibians. Potential imp acts 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. Al achlor is classified as practical ly nontoxic to non-target insects on an acute contact exposure ba sis. An acute contact LD 50for terrestrial invert ebrates could not be determined based on available data. For honey b ees, a contact concentration of 36.3 μg a.i./bee (equivalent to 284 ppm) resulted in 0.41% morta lity of exposed adults. Only one concentration was used in this study; therefore, a definitive LD 50value and response slope could not be determined. Using an LD 50of >36.3 μg a.i./bee results in RQs less than 1.9 and 0.21 for small and large insects, respectively; how ever, it is not clear if the ac tual RQs are above or below the interim LOC of 0.05 for acute risk to e ndangered terrestrial invertebrates.

The chance of individual effects for terrestrial invert ebrates using the IECv1.1.xls spreadsheet, the acute risk to endangered species LOC of 0.05, and defaul t 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 insect s, respectively. Theref ore, the concentration

Page 101 of 132on the site of application at the maximum allowable application rate is not expected to reach levels high enough to cause 0.41% mo rtality 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% mort ality. 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 fr action of applied pesticide is 45% ( i.e ., 1.79 lb a.i./A). Inputting an ap plication rate of 1.79 lb a.i./acre into T-REX results in EECs of 242 ppm for small insects, which is below th e concentration that re sulted in 0.41% mortality in adult bees. Therefore, the concentration of alac hlor >5 ft from the site of application is not expected to reach levels high enough to cause ev en 0.41% mortality in small insects based on the available honey bee data.
Therefore, the Agency concludes that the pote ntial for alachlor use to impact terrestrial invertebrate populations to leve ls 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 excee d 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 defau lt 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 indi vidual effect provides insi ght 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 si gnificant 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, diet ary- and dose-based for 15 g mamm al (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 reproduc tive effects is likely higher than 30 mg/kg-diet. How much highe r 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 F 3 females (maximal decrease of 17%)]. However, none of these effects were correlated with growth, survival , or reproductive endpoints.

Page 102 of 132Therefore, the Agency concludes that the poten tial for alachlor use to impact mammalian prey populations to levels high enough to imp act the CRLF is low and discountable.

5.2.3.3. Amphibians
CRLF are known to prey on aquatic-phase amphibian s. The potential risk to amphibians based on fish toxicity data is expectedto be low based on the RQs ( i.e ., all RQs < 0.05). Additionally, using the acute toxicity endpoi nts for the African clawed fr og (African clawed frog; LC 50= 6.1 mg a.i./L) results in no LOC exceedances for any al achlor use. Therefore, indirect effects to CRLF from a decline in potential aquatic phase am phibian prey are not expected from the use of alachlor in California.
Terrestrial amphibian prey of the CRLF include sm all 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 amphibi an prey abundance. The RQs for acute and sub-acute dietary exposure from T-HERPS range from 0 to 0.01 (a cute) 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 thatthe risk for indirect adverse effects to the CRLF from loss of amphibian prey after acute or s ub-acute exposure to alachlor is low.
For chronic exposure, however, al l of the alachlor uses exceed the Agency’s chronic risk to nonlisted species LOC of 1 for at l east one of the relevant dietary categories (chronic RQs for the broadleaf plants/small insects and fruits/pods/se eds/large insect dietary categories range from >0.60 to >10.8). However, since a defin itive NOAEC was not determined for birds ( i.e .,effects were seen at all treatment levels) all of the cal culated RQs for chronic exposure are greater-than values. Therefore, risks to terrestrial-phaseamphibians from chronic exposure cannot be precluded for any of the alach lor 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 prec luded at this time based upon available information. Therefore, the Agency concludes thatthere exists the potential for alachlor use to impact terrestrial phase amphibian prey populati ons to levels high enough to impact the CRLF.

5.2.3.4. Potential Eff ects to Habitat
Aquatic plants serve several important functions in aquatic ecosystems. Non-vascular aquatic plants are primary producers and provide the auto chthonous energy base for aquatic ecosystems. Vascular plants provide structure, rather than energy, to the syst em, as attachment sites for many aquatic invertebrates, and refugi a for juvenile organisms, such as fish and frogs. Emergent plants help reduce sediment loading and provi de stability to nearshore areas and lower streambanks. In addition, vascular aquatic plan ts 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 132expected 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 Ca lifornia), 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 orname ntal (nursery) uses. Therefore, impacts to aquatic plants found near alachl or use sites are expected.
Terrestrial plants serve several important habitat-re lated functions for the li sted 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 fr om predators while foraging, upland vegetation, including grassland and woodlands, provi des cover during dispersal (CRLF).
Based on the results of the submitted terrestrial plan t toxicity studies and the reported terrestrial plant incidents, the herbicide alachlor is phytotoxic to many pl ant species (seedling emergence endpoints are more sensitive than vegetative vi gor endpoints). Additionally, monocots are more sensitive to alachlor than are di cots, based on available data. However, for adjacent upland and wetland plants, terrestrial plant RQs for both monoc ots and dicots exceed the Agency’s risk to non-listed species LOC for all alachlor uses and app lication 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). Ba sed on the spray drift analysis, effects to terrestrial plants could occur >800 ft (> 0.24 km) from alach lor application sites (see Section 5.2.4).
A general conclusion that can be drawn from these data is that the inhibi tion of new growth may occur in non-target terrestrial plan ts from registered uses of alac hlor. 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 biom ass 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 ne w vegetation. Additionally, because effects were seen in most species tested in the seedling em ergence 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 pot ential impacts of alachlor use on riparian habitat and the magnitude of potential eff ects on stream water quality from su ch 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 drif t 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 itsel f. The sensitivity of the ripari an vegetation is dependent on the susceptibility of the plant species exposed to al achlor and composition of the riparian zone ( e.g

. vegetation density, species rich ness, height of vegetation, wi dth of riparian area).

Page 104 of 132In summary, terrestrial and aquatic plant RQs are above plant LOCs for all uses; therefore, labeled use of alachlor has the potential to aff ect 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 thro ugh 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 eff ects determination also in cludes areas beyond the initial area of concern that may be impacted by runoff and/or sp ray drift (potential use areas + distance down stream or down wind from use site s 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 ha bitats of concern due to alachlor exposures through spray drift, it is necessary to estimate th e distance that spray applications can drift from the treated area and still be present at concentrati ons 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 fo r modeling purposes). Fo r 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, 90 thdata percentile), except for the an alyses for cotton which used labeled restrictions ( i.e ., high boom, ASAE droplet size distribution = Fine to Medium/Coarse, 90 thdata 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 fi eld 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 ., LC 50value 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 fli ght line width of 157.21 m) was used as a proxy for CRLF and DS habitat. The other AgDRIFT i nputs were the same as described above in the terrestrial distance analysis.

Page 105 of 132Table 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 3 0.43 13.1 0 Dry beans Lima beans
Cotton 2 0.28 3.3 0

For indirect effects, a spray drift analysis is conducted using endpoints fo r terrestrial and aquatic plants (the most sensitive taxa to alachlor). The distance from the field for terrestrial plants is based on the most sensitive terrestria l plant non-listed species endpoint ( i.e ., monocot seedling emergence EC 25 = 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 applicati on rate in lb a.i./acre) ( Table 4.2 ).
For aquatic plants, the RQ for th e most sensitive aquatic plant ( i.e ., non-vascular plant EC 50= 1.64 μg a.i./L) is used to estimate the initial av erage concentration that would no longer exceed the LOC for plants ( i.e .,EC 50X 1). This number is used in AgDRIFT to calculate the distance from the field where the amount of alachlor that e quals the ‘initial average concentration’ would be expected to occu r (as spray drift) ( Table 5.13 ).

Page 106 of 132Table 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 3 748 151 Dry beans Lima beans
Cotton 2 246 85

Therefore, when only spray drift is considered, pot ential risks for both dire ct 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 expos ure 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 Nfor details). For potential direct effects to aquatic-phase CRL F and DS, none of the RQs for fish exceed the Agency’s listed species LOC. Therefore, the potential for direct effect s 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 potenti al 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 (b ased on toxicity data for non-vascular aquatic plants) the area of potential effects extends up to 5 km from reside ntial 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 ex tend from the site of applicati on 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 th e site of application (again, depending on the use). When these distances are added to the f ootprint of the initial area of concern (which represents potential alachlor use sites) and compared to CRLF and DS habitat, there are several

Page 107 of 132areas 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.

Page 108 of 132Figure 5.1. Overlap Map: CRLF Habitat an d Alachlor Initial Area of Concern.

Page 109 of 13 2Figure 5.2. Overlap Map: DS Habitat and Alachlor Initial Area of Concern.

Page 110 of 13 25.3. Effects to Designated Critical Habitat
The risk conclusions for the designated criticalhabitat are based on conclusions described for indirect effects previously de scribed. 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 th e 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 ge ometry and/or increase in sediment deposition within the stream channel or pond: aquatic habitat (including riparian vegetation) provides for shelte r, foraging, predator avoidance, and aquatic dispersal for juvenile and adult CRLFs.

• Alteration in water chemistry/quality in cluding temperature, turbidity, and oxygen content necessary for normal growth and viabil ity of juvenile and adult CRLFs and their food source.

• Reduction and/or modification of aquatic-b ased food sources for pre-metamorphs ( e.g., algae). Conclusions for potential indirect effects to the CRLF via direct e ffects to aquatic and terrestrial plants are used to determine wh ether effects to cri tical 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 impactriparian areas that are predominantly grassy or herbaceous, and the potential areas of effect overlap with de signated critical habitat for the CRLF (see Fig. 5.1 ). Therefore, there is a potential for effects to habitat by potentially impacting the chemical characteri stics of the habitat.

5.3.1.2. Terrestrial-Phase PCEs
Two of the four assessment endpoints for the terres trial-phase PCEs of designated critical habitat for the CRLF are related to potential effects to terrestrial plants:

• Elimination and/or disturbance of upland habi tat; 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 a nd riparian habitat that ar e comprised of grasslands, woodlands, and/or wetland/riparian plant species that provi des the CRLF shelter, forage, and predator avoidance.

Page 111 of 132• Elimination and/or disturbance of dispersal habitat: Upland or riparian dispersal habitat within designated units and between occupi ed locations within 0.7 mi (1.1 km) of each other that allow for movement between site s 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. A dditionally, risk to terr estrial plant LOCs are exceeded for all uses and the potential areas of eff ect 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 imp act of alachlor on this PCE, acute and chronic toxicity endpoints for terrestrialinvertebrates, 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 de scribed), and, again, the areas of potential effect overlap with CRLF critical habitat ( Fig. 5.1 ).
The fourth terrestrial-phase PCE is based on alte ration 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 potenti al 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 di sturbance and flow disruption. Adequate river flow is necessary to transport larvae from upstream spawning areas to rearing habitat in Suisun Bay. Suitable water quality mu st 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) w ithin the estuary is necessary to provide Delta smelt larvae and juveniles a shallow protective, food-ri ch 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 th e Sacramento and San Joaquin River channels

Page 112 of 132and their associated tributaries. These ar eas also should be protected from physical disturbance and flow disrup tion during migratory periods.

• PCEs also include more general requirements for habitat areas that provide essential life cycle needs of the species such as space fo r 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 ecologicaldistributions of a species. The potential for direct effects to the DS fr om 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 terrestria l 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 locate d in close proximity to alachlor use sites.

5.4. Effects Determinations

5.4.1 CRLF
The weight of evidence indicates th at 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 di etary exposure is low, the potential risk to terrestrial-phase CRLF from chronic dietary expo sure cannot be preclude d and exists for all dietary classes relevant to the CRLF (for all of the regi stered alachlor uses).
Regarding the potential for indire ct effects, exceedance of the chronic risk to endangered species LOC indicates that there could besome effect to sensitive aquatic invertebrates from the woody ornamental and sunflower uses; however, such aneffect would likely beinsignificant to the CRLF. Furthermore, the Agency concludes th at the potential for alachlor use to impact terrestrial invertebratepopulations to levels high enough to impact the CRLF is low and discountable. Impacts to non-vascular aquatic and terrestrial plants, howev er, 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 us e 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 hab itat 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 di rect and indirect effects and e ffects 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 indire ct effects, the impact from al achlor use to estuarine/marine invertebrate populations is not ex pected to be large enough to imp act the DS indirectly. This, again, is consistent with the study that investig ated the effects of three pesticides (including

Page 113 of 132alachlor) on estuaries in North Carolina from runoff from adjacent farm lands which showed no measurable impact on the estuarine biological co mmunity adjacent to application sites (MRID 44105503). Impacts to non-vascular aquatic and terre strial 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 th eir designated critical habitat. Therefore, the Agency makes a “may affect, and likely to adversely affect” de termination 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 effect s and effects to habitat.
The labeled use of alachlor may:

• ... directly affect terrestrial-phase CRLF by causing acute mortality or by adversely affecting chronic grow th 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 terres trial 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 habi tat in their current range (viamodification 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 char acterizing potential ec ological risks resulting from a maximum use scenario, which is determined from labeled statements of maximum application rate and number of applications with th e 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 effectivenes s 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 runo ff and erosion from agricultural fields (USDA, NRCS, 2000). Alternatively, a setback of poor vege tative 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

Page 114 of 132aquatic exposure predictions are likely to overestimate e xposure where healthy vegetative setbacks exist and underestimate exposure wh ere poorly developed, channelized, or bare setbacks exist.

6.1.3 Aquatic Exposure Modeling of Alachlor
The standard ecological water body scenario (EXAM S pond) used to calculate potential aquatic exposure to pesticides is intended to repres ent conservative estimates, and to avoid underestimations of the actual expos ure. The standard scenario c onsists of application to a 10­ hectare field bordering a 1-h ectare, 2-meter deep (20,000 m 3 ) pond with no outlet. Exposure estimates generated using the EXAMS pond are intended to represent a wide variety of vulnerable water bodies that occu r at the top of watersheds in cluding 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 larg er 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 pestic ide in the discharge, whereas the EXAMS pond has no discharge. As watershed size increases beyond 10-hectares, it becomes increasingly unlikely that the entire wate rshed 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 persis t for only short periods of time and are then carried and dissipated downstream.
The Agency acknowledges that there are some uni que aquatic habitats that are not accurately captured by this modeling scenario and modeling results may, therefore, u nder- or over-estimate exposure, depending on a number of variables. Fo r example, some organisms may inhabit water bodies of different size and depth and/or are locatedadjacent to larger or smaller drainage areas than the EXAMS pond. In addition, the Serv ices agree that th e existing EXAMS pond represents the best currently available approachfor estimating aquatic exposure to pesticides (USFWS/NMFS 2004).
In general, the linked PRZM/EXAMS model produces estimated aquatic con centrations 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 pe sticide in an agricultural field on a day-to-day basis. It consid ers factors such as rainfall and plant transpiration of water, as well as how and when the pesticide is applie d. 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 pesticid e application on the soil or onthe plant foliage. Dissolved, adsorbed, and vapor-phase concen trations in the soil are estimated by simultaneously considering the processes of pesticide upt ake by plants, surface runoff, erosion, decay, volatilization, foliar wash-off, advection, disper sion, and retardation.

Uncertainties associated with eachof these individual components add to the overall uncertainty of the modeled concentrations. Additionally, model inputs from the environmental fate

Page 115 of 132degradation studies are chosen to represent th e upper confidence bound on th e mean values that are not expected to be exceeded in the envir onment approximately 90 percent of the time. Mobility input values are chosen to be represen tative of conditions in the environment. The natural variation in soils adds to the uncertainty of modeled values. Fact ors such as application date, crop emergence date, and canopy cover can al so affect estimated concentrations, adding to the uncertainty of modeled values. Factors within the ambient environment such as soil temperatures, sunlight intensity, antecedent so il moisture, and surface water temperatures can cause actual aquatic conc entrations to differ for the modeled values.
The modeling for the residential woody ornamentaluses 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 al achlor treatments to woody ornamentals (post transplant), it was estim ated 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 potenti al 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 uncertain ties associated with modeling, available monitoring data were compared to PRZM/EXAMS estimates of peak EEC s for the different uses. As discussed above, several data values were availabl e 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 relevantto potential exposure in California. For the NAWQA data, the specific use patterns ( e.g . application rates and timi ng, crops) associated with the agricultural areas are unknown, however, they are assumed to be representative of potential alachlor use areas. Use information is well co rrelated with the Calif ornia 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 repres ent 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 largervolume of water than would be found in the ‘typical’ EXAMS pond. However, as chemical cons tituents in water draining from freshwater streams encounter brackishness or other near-marine-associated condi tions, there is potential for

Page 116 of 132important 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 temper ature are encountered. For example, desorption and remobilization of some chemicals from sedime nts 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 ch emicals in discharging rivers may be diluted by large volumes of water within receiving estu aries 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 in creased mobility of a chemical in brackish water. In addition, freshw ater contributions from discharging streams and rivers do not instantaneously mix with more salin e water bodies. In these settings, water will commonly remain highly stratified, with fresh water lying atop denser, h eavier saline water – meaning that exposure to concentrations found indischarging stream water may propagate some distance beyond the outflow point of the stream (especially near the water surface).
Therefore, EFED does not automatically assume th at discharging water will be rapidly diluted by the entire water volume within an estuary, em bayment, or other coas tal aquatic environment; PRZM-EXAMS model results should be considered c onsistent with concentr ations that might be found near the head of an estuary unless there is specific inform ation to indicate otherwise. Conditions nearer to the mouth of a bay or es tuary, however, may be cl oser 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 di scharging ground water on CRLF pop ulations is not explicitly delineated, it should be noted that, in some ar eas 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 chemicalis persistent and mobile, the pesticide is applied to highly permeable soil s 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 degradatio n will be very likely to persist in ground water, and can be transportable over long distances. Similarly, many chemicals degrade slowly under anaerobic conditions (comm on in aquifers) and are thus more persistent in ground water. Under the right hydrologic conditions, th is 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 gr ound water discharge, which can c onstitute 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 di schargers of water to ground water that go dry during portions of the year and are not suppl ied by baseflow from ground water.

Page 117 of 132Although concentrations in a re ceiving water body resulting from ground water discharge cannot be explicitly quantified, it shoul d 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 th ere is a net recharge to adjacent streams, ground water could still be a cons istent source of chronic backgr ound concentrations in surface water, and may also add to surface runoff duri ng 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 obt ained from CDPR PUR database. Eight years of data (1999 – 2006) were included in this analysis because st atistical methodology for identifying outliers, in terms of area treated and pounds applied, was pr ovided 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 contai n reports for pes ticide uses that have been cancelled. The CPDR PUR data doe s 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 assu mptions 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 exposur e involve highly varied sampling techniques. It is entirely possible that much of this data reflects residues averaged over entire above ground plants in the cas e of grass and forage sampling.
It was assumed that ingestion of food items in th e field occurs at rates commensurate with those in the laboratory. Although the screening assessment process ad justs dry-weight estimates of food intake to reflect the increased mass in fres h-weight wildlife food intake estimates, it does not allow for gross energy differences. Direct co mparison of a laboratory dietary concentrationbased effects threshold to a fresh-weight pes ticide 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 diet s suggest that current screening assessment methods do not account fo r 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

Page 118 of 132of 85%), a potential for underestimation of expo sure may exist by assuming that consumption of food in the wild is comparable with consumption during laborato ry testing. In the screening process, exposure may be underestimated becau se metabolic rates ar e 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 particul ar terrestrial species werenot considered, and it was assumed that species occupy, exclusively an d permanently, the modeled treatment area. Spray drift model predictions sugg est that this assumption leads to an overestimation of exposure to species that do not occupy the treate d field exclusively and permanently.

6.1.7 Spray Drift Modeling
Factors, including variations in topography, c over, 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 gr ound cover and a steady, constant wind speed and direction). Therefore, in mo st cases, the drift estimates from AgDRIFT may overestimate exposure, especially as the distance in creases 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 si ze distributions being modeled (‘ASAE Very Fine to Fine’) and boom hei ght (‘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 datafor fish are collected on juvenile fish between 0.1 and 5 grams. Aquatic invertebrate acute te sting 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 overe stimate 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 withdetoxifying xenobiotics. In so far as the available toxicity data may provide ranges of se nsitivity 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 therefor e, considered as protective.

6.2.2 Impact of Multiple Stressors on the Effects Determination
The influence of length of exposure and concurre nt environmental stresso rs to the CRLF and the DS ( i.e. , construction of dams and locks, fragmentation of habitat, change in flow regimes,

Page 119 of 132increased 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 increas e sensitivity to the he rbicide, although ther e 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. Howe ver, 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 beprotective of potential direct effects to aquaticphase amphibians including the CRLF, and extrapol ation 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 or ganisms most likely to be affected by the type of compound and usage pattern; however, there is an inherent uncertainty inextrapolating across phyla. In addition, the Agency’s LOCs are intentionally set very low, and conservative estimates are made in the screening level risk a ssessment to account fo r these uncertainties.

6.2.5. Sublethal Effects
The assessment endpoints used in ecological ri sk assessment include potential effects on survival, growth, and reproduction of the CRL F 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 thatwere 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 byFQPA, 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 aneffect produced by a natu rally occurring estrogen, or other such endocrine eff ects as the Administrator may designate.” Following the recommendations of its Endocrine DisruptorScreening and Testing Advisory Committee (EDSTAC), EPA determined that there were scie ntific 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 thatthe Program include ev aluations of potential effects in wildlife. When the appropriate scr eening and/or testing prot ocols being considered under the Agency’s Endocrine Disrupter Screeni ng 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 Sc reening Program please visit our website: http://www.epa.gov/endo/.

Page 120 of 1326.2.6

. 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 c ould 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 as sessment because of the my riad 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 e xposure among contaminants, and the differential effects of other physical/chemical charac teristics of the r eceiving waters ( e.g . organic matter present in sediment and suspended water). Evaluation of factors that could influence additivity/synergism/antagonism is beyond the natureand 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 in teraction and factors discussed above.

6.3

. Uncertainty in the Potential Effect toRiparian Vegetation vs. Water Quality Impacts
Effects to riparian vegetation were evaluated using submitted guideline seedling emergence and vegetative vigor studies. LOCs were exceededfor seedling emergence and vegetative vigor endpoints with the seedling emergence endpoint be ing considerably more sensitive. Based on LOC exceedances and the lack of readily availabl e information to allow for characterization of riparian areas of the CRLF and the DS, it was conc luded that alachlor use is likely to adversely affect these species by potentially impacting gr assy/herbaceous riparianvegetation resulting in increased sedimentation. However, soil retentio n/sediment loading is de pendent on a number of factors including land management and tillage pr actices. Use of herbic ides (including alachlor) may be incorporated into a soil conservation plan. Therefore, although this assessment concludes that alachlor is likel y to adversely affect the asse ssed listed species and their designated critical habitat by pot entially impacting sensitive herb aceous riparian areas, it is possible that adverse impacts on sediment loadi ng 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 particul ar terrestrial species werenot considered, and it was assumed that species occupy, exclusively an d permanently, the modeled treatment area. Spray drift model predictions sugg est that this assumption leads to an overestimation of exposure to species that do not occupy the treate d field exclusively and permanently.

Page 121 of 132Species Effects Determination 1 Basis for Determination
Potential for Direct EffectsCalifornia redlegged frog (Rana aurora

draytonii ) LAA 1 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 ) LAA 1 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 ripa rian 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 us es 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 th e 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 th e 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 cumulativ e 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 132Table 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 th e 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 Endange red Species Act should be initiated.
When evaluating the significance of this risk assessment’s direct/indire ct 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 a ssumptions of drift and downstream transport ( i.e ., attenuation with distance), pestic ide exposure and associated risks to the species and its resources are expected to decrease with increasing distance away from th e treated field or site of application. Evaluation of the im plication of this non-uniform distribution of risk to the species would require information and assessment tec hniques that are not currently available.
When evaluating the significance of this risk assessment’s direct/indire ct 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 a nd habitat) are not expected to be uniform across the action area. In fact, given th e assumptions of drift and downstr eam transport (i.e., attenuation with distance), pesticide expos ure and associated risks to th e species and its resources are expected to decrease with increa sing 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 ty pe 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 applic able designated critic al habitat. This information would allow for quantitativ e 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 fo r 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 prel iminary picture of the types of food sources utilized by the assessed spec ies, it does not establish minimal requirements to sustain healthy individua ls at varying life stages. Such information could be used to establish bi ologically relevant thresholds of effects on the prey base, and ultimately establis h geographical limits to those effects. This information could be used together with the density data discussed above to characterize the likelihood of a dverse effects to individuals.

• Information on population responses of prey base organisms to the pesticide. Currently, methodologies are limited to pr edicting 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 characte ristics 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 pesticid e exposure would allow for a more refined determination of the magnitude and durati on of resource impairment, and together with the information described above, a more complete prediction of effects to individual species and potential m odification to critical habitat.

8.0 References
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USEPA. 2006c. Risks of Atrazine Use to Federally Listed Endangered Barton Springs Salamanders (Eurycea sosorum). Pesticide Effects Determination. Office of Pesticide Programs, Environmental Fate and Effects Division. August 22, 2006.
USEPA. 2006d. Cumulative Drinking Water Exposur e Assessment for Chlo roacetanilides (Acetochlor and Alachlor). U.S. Environmental Protection Agency, Office of Pesticide Programs, Environmental Fate and Effects Division, Memorandum, Feb. 6, 2006.

USEPA. 2006e. TerrPlant Version 1.2.2 (December 26, 2006) User’s Guide. U.S. Environmental Protection Agency, Office of Pesticide Programs, Environmental Fate and Effects Division.
USEPA. 2008. White Paper on Methods for Assessing Ec ological Risks of Pesticides with Persistent, Bioaccumulative and Toxic Characteristics. Submitted to the FIFRA Scientific Advisory Panel. October 28-31, 2008. Office of Pesticide Program s, Environmental Fate and Effects Division, Washington, D.C.
USEPA. 2009. County-Level Usage fo r Propanil, Paraquat Dichloride , Pendimethalin, Myclobutanil, Prometryn, Dicofol, Alachlor, and Endosulfan In California in Support of a Red Legged Frog Endangered Species Assessment. U.S. Environmental Protection Agency, Office of Pesticide Programs, Environmental Fate and Effects Division, Memorandum, February 4, 2009.

U.S. Fish and Wildlife Service (USFWS)

. 1995. Sa cramento-San Joaquin Delta Native Fishes Recovery Plan. U.S. Fish and Wildlife Service, Portland, Oregon. Available online at: http://ecos.fws.gov/docs/recovery_plan/961126.pdf (Accessed on January 28, 2008).

U.S. Fish and Wildlife Service (USFWS). 2004. 5- Year Review. U.S. Fish and Wildlife Service, Sacramento Field Office, Sacramento, California. 50 pp. Available online at:

Page 127 of 132http://www.fws.gov/sacramento/es/docum ents/DS%205-yr%20rev%203-31-04.pdf (Accessed on January 28, 2007).
USFWS/NMFS. 1998. Endangered Species Cons ultation Handbook: Procedures for Conducting Consultation and Conference Activities Under Sec tion 7 of the Endangered Species Act. Final Draft. March 1998
USFWS/NMFS. 2004. 50 CFR Part 402. Joint Counterpart Endangered Species Act Section 7 Consultation Regulations; Final Rule. FR 47732-47762.
USGS. 1998. Herbicides in Rainfall Across the Midwestern and Northeastern United States, 1990-91. USGS Fact Sheet 181-97. http://ks.water.usgs.gov/pubs/fact-sheets/fs.181-97.html

. Velde B. and T. Church. 1999. Rapid clay tran sformations in Delaware salt marshes. Applied Geochemistry 14(5): 559-568.
Wood, T.M. and A.M. Baptista. 1993. A model for dia gnostic analysis of estuarine geochemistry. Water Resources Research 29(1): 51–71.

Submitted Fate Studies

MRI D Reference
4039630 1 Monsanto Co. (1987) Alachlor Product Ch emistry--Response to Agency Review: R.D. No. 831. Unpublished study. 47 p.
15220 9 Brightwell, B.; Rueppel, M. (1976) Lasso and Ramrod: Physical Properties and Their Relationship to the Environment: Report No. 443. Unpublished study prepared by Monsanto Co. 14 p.
13432 7 Suba, L.; Pearson, D.; Malik, J. (1979) The Environmental Studies of Alachlor: R.D. #258: Report Nos. MSL-0860, MSL-0861. Final rept . (Unpublished study received Oct 11, 1979 under 524-285; submitted by Monsanto Co ., Washington, DC; CDL:241135-A; 241136)
2301 2 Sutherland, M.L.; Curtis, T.G.; Darlington, W.A.; et al. (1972) Final Report on Lasso and the Environment: Part 4: Photolysis of Lasso on So il and in Water: Agricultural Research Report No. 262. (Unpublished study received Jun 29 , 1973 under 3F1372; submitted by Monsanto Co., Washington, D.C.; CDL:093660-L)
10153 1 Banduhn, M.; Livingston, C.; Kloek, J.; et al. (1981) Comparative Environmental Fate and Crop Uptake Studies of Encapsulated and Unencapsulated Alachlor: Report No. MSL-2070. (Unpublished study received May 10, 1982 under 524-344; submitted by Mon- santo Co., Washington, DC; CDL:070841-B)
13432 7 Suba, L.; Pearson, D.; Malik, J. (1979) The Environmental Studies of Alachlor: R.D. #258: Report Nos. MSL-0860, MSL-0861. Final rept . (Unpublished study received Oct 11, 1979 under 524-285; submitted by Monsanto Co ., Washington, DC; CDL:241135-A; 241136)
2301 4 Sutherland, M.L.; Curtis, T.G.; Darlington, W.A.; et al. (1972) Final Report on Lasso and the Environment: Part 6: Soil Dissipa- tion of Lasso: Agricultural Research Report No. 264. (Unpub- lished study received Jun 29, 1973 under 3F1372; submitted by Monsanto Co., Washington, D.C.; CDL:093660-N)

Page 128 of 1324440530 1 Blumhorst, M. (1997) Soil Adsorption/Desorption of (carbon 14) Alachlor Sulfonic Acid Metabolite (ESA) by the Batch Equilibrium Method: Lab Project Number: 97-24-M-1: 115S12: MSL-14976. Unpublished study prepared by EPL Bio-Analytical Services, Inc. 106 p. 2713 9 Weidner, C.W. (1974) Degradation in Gr oundwater and Mobility of Herbicides. Master's thesis, Univ. of Nebraska, Dept. of Agron- omy. (Unpublished study received Jul 19, 1978 under 201-403; submitted by Shell ChemicalCo., Washington, D.C.; CDL:234472-O)
2714 0 Lavy, T.L. (1974) Mobility and Deactivation of Herbicides in Soil- Water Systems: Project A024-NEB. (Available from: National Technical In formation Service, Springfield, VA: PB-238 632; un- published study received Jul 19, 1978 under 201-403; prepared by Univ. of Nebraska, Water Resources Research Ins titute, sub- mitted by Shell Chemical Co., Washington, D.C.; CDL:234472-P)
7830 1 Guth, J.A. (1975) CGA-24705 Leaching Model Study with the Herbicide CGA-24705 in Four Standard Soils: Nr. SPR 3/75. (Unpublished study received Jul 23, 1981 under 100-587; prepared by Ciba- Geigy, Ltd., Switzerland, submitted by Ciba-Geigy Corp., Greens- boro, N.C.; CDL:245628-E)
13432 7 Suba, L.; Pearson, D.; Malik, J. (1979) The Environmental Studies of Alachlor: R.D. #258: Report Nos. MSL-0860, MSL-0861. Final rept . (Unpublished study received Oct 11, 1979 under 524-285; submitted by Monsanto Co ., Washington, DC; CDL:241135-A; 241136)
15220 9 Brightwell, B.; Rueppel, M. (1976) Lasso and Ramrod: Physical Prop- erties and Their Relationship to the Environment: Report No. 443. Unpublished study prepared by Monsanto Co. 14 p.
4252800 1 Schott, M.; Schlicher, M. (1990) Terrestrial Field Dissipation of Alachlor at Two Sites in California: Lab Project Number: MSL-10395: RD 1138. Unpublished study prepared by Monsanto Company. 313 p.
4252800 2 Schlicher, M.; Schott, M. (1991) Terrestri al Field Dissipation of Alachlor Metabolites in Chico, California: Lab Project Number: MSL- 10844: 1138. Unpublished study prepared by Monsanto Company. 251 p.

Submitted Ecotoxicity Studies:

7952 3 Fink, R.; Beavers, J.B.; Brown, R.; et al. ( 1979) Final Report: Acute Oral LD50--Bobwhite Quail: Project No. 139-179. (Unpub- lished study recei ved Jun 2, 1981 under 524-285; prepared by Wildlife International, Ltd., submitted by Mon santo Co., Wash- ington, D.C.; CDL:245260-A)
43087001 Grimes, J.; Jaber, M. (1986) Alachlor: A Dietary LC 50 Study with the Mallard: Lab Project Number: 139-232: WL-86-205: RD 1218. Unpublishe d study prepared by Wildlife International Ltd. 31 p.
43087101 Grimes, J.; Jaber, M. (1986) Alachlor: A Dietary LC 50 Study with the Bobwhite: Lab Project Number: RD 1217: 139-231: WL-86-206. Unpublishe d study prepared by Wildlife International Ltd. 32 p.
44951501 Gallagher, S.; Beavers, J.; Jaber, M. (199 9) Alachlor: A Reproduction Study with the Mallard (Anas platyrhynchos): Lab Project Number: R. D.1492: WL-97-144: 139-436. Unpublished study prepared by Wildlife International, Ltd. 183 p.

Page 129 of 13244951502 Gallagher, S.; Beavers, J.; Jaber, M. (1999) Alachlor: A Reproduction Study with the Northern Bobwhite (Colinus virginianus): Lab Project Number: R.D.NO.1492: WL-97-145: 139­ 435. Unpublished study prepared by Wildlife International, Ltd. 182 p.
43774704 Bowman, J.; Downing, J.; Hurshman, B. (1995) Acute Toxicity of MON 5775 to Rainbow Trout (Oncorhynchus mykiss): Amended Final Report: Lab Project Number: 41729: AB-94-156: 1321. Unpublished study prepared by ABC Labs, Inc. 26 p.
43774706 Bowman, J.; Hurshman, B. (1995) Acute Toxicity of MON 5760 to Rainbow Trout (Oncorhynchus mykiss): Final Report: Lab Project Number: 41731: AB-94-154: 1321. Unpublished study prepared by ABC Labs, Inc. 27 p.
43774703 Bowman, J.; Hurshman, B. (1994) Acute Toxicity of MON 5775 to Daphnia magna: Final Report: Lab Project Number: 41728: AB-94-155: R.D. 1321. Unpublished study prepared by ABC Labs, Inc. 26 p.
43774705 Bowman, P.; Hurshman, B. (1994) Acute Toxicity of MON 5760 to Dahnia magna: Final Report: Lab Project Number: 41730: AB-94-153: 1321. Unpublished study prepared by ABC Labs, Inc. 26 p.
44524301 Graves, W.; Swigert, J.; Krueger, H. (1998) A 96-Hour Flow-Through Acute Toxicity Test with the Sheepshead Minnow (Cyprinodon variegatus): Alachlor: Final Report: Lab Project Number: 1410: WL-96-189: 139A-195. Unpublished study prepared by Wildlife International Ltd. 43 p.
44524302 Graves, W.; Swigert, J.; Krueger, H. (1998) A 96-Hour Flow-Through Acute Toxicity Test with the Saltwater Mysid (Mysidopsis bahia): Alachlor: Final Report: Lab Project Number: 139A-196: WL-96-190: 1410. Unpublished study prepared by Wildlife International Ltd. 42 p.
44524303 Graves, W.; Swigert, J.; Krueger, H. (1998) A 96-Hour Shell Deposition Test with the Eastern Oyster: Alachlor: Final Report: Lab Project Number: 139A-197: WL-96-191: 1410. Unpublished study prepared by Wildlife International Ltd. 44 p.

2361 5 Thompson, C.M.; Forbis, A.D.; McAllister, W.A. (1978) Acute Toxic- ity of Technical Alachlor (AB-78-166) to Bluegill Sunfish (?~Lepomis ma crochirus~?). (Unpublished study received Aug 16, 1978 under 524-285; prepared by Analytical Biochemistry Labora- tories, Inc., submitted by Monsanto Co., Washington, D.C.; CDL: 234628-C)

2361 6 Forbis, A.D.; McAllister, W.A. (1978) Acute T oxicity of Technical Alachlor to Rainbow Trout (?~Salmo gairdneri). (Unpublished study recei ved Aug 16, 1978 under 524-285; prepared by Analyt- ical Biochemistry Laboratories, Inc ., submitted by Monsanto Co., Washington, D.C.; CDL:234628-D)

2855 0 Thompson, C.M.; Forbis, A.D. (1978) Acute Toxicity of Lasso (MCB/ Cg) (AB-78-111) to Rainbow Trout (?~Salmo_gairdneri~?). (Unpub- lished study received Dec 28, 1979 under 524­ 285; prepared by Analytical Bio Chemistry Laboratories, Inc., submitted by Monsanto Co., Washington, D.C.; CDL:241535-B)

2855 1 Thompson, C.M.; Forbis, A.D. (1978) Acute Toxicity of Lasso (MCB/ Cg) (AB-78-111) to Bluegill Sunfish (?~Lepomis macro~?- ?~chirus~?). (Unpublished study received Dec 28, 1979

Page 130 of 132under 524-285; prepared by Analytical Bio Chemistry Laboratories, Inc., submitted by Monsanto Co., Washington, D.C.; CDL: 241535-C)
43774707 Forbis, A. (1995) Chronic Toxicity of Alachlor to Daphnia magna Under Flow-Through Test Conditions: Final Report: Lab Project Number: 41517: AB-94-061: 1 321. Unpublished study prepared by ABC Labs, Inc. 39 p.
43862601 Rhodes, J.; Muckerman, M. (1995) Early Life-Stage Toxicity of Alachlor to the Rainbow Trout (Oncorhynchus mykiss) Under Flow-T hrough Conditions: Lab Project Number: 42187: AB-94-280: R.D. 1331. Unpublished study prepared by ABC Labs, Inc. 339 p.
139383 Heenehan, P.R.; Rinehart, W.E.; Braun, W.G. (1979) Acute Oral Toxicity Study in Rats; Compound: Alachlor(Technical): Project No. 4899-77; BD-77-433. Rev. (Unpublished study, including letters dated Aug 6, 1979 from W.E. Rinehart to George Levin- skas; Aug 31, 1979 from F.B. Oleson to W.D. Carpenter, received Oct 16, 1979 under 524-285; prepared by Bio/dynamics, Inc., submitted by Monsanto Co., Washington, D.C.; CDL:241273-N)

7506 2 Schroeder, R.E.; Hogan, G.K.; Smock, M. E.; et al. (1981) A Three Generation Reproduction Study in Rats with Alachlor: Project No. 77-2066. Final rept. (Unpublished study received Jul 10, 1981 under 524-285; prepared by Bio/dynamics, Inc., submitted by Monsanto Co., Washington, D.C.; CDL:070177-A)
42763801 Blasberg, J.; Hicks, S.; Leak, T. (1993) Acute Toxicity of (carbon 14)-Alachlor to Selenastrum capricornutum Printz: Final Report: Lab Project Number: 40815: AB-93-52: 1171. Unpublished study prepared by ABC Labs, Inc. 56 p.
42468601 Canez, V. (1992) Tier 2 Vegetative Vigor Nontarget Phytotoxicity Study Using Alachlor: Lab Project Number: BL91-480: 0624-91-9. Unpublished study prepared by Pan-Agricultural Laboratories Inc. 226 p.
42468701 Chetram, R. (1992) Tier 2 Seed Germination/Seedling Emergence Nontarget Phytotoxicity Study Using Alachlor: Lab Project Number: BL91-481: 0624-91-8. Unpublished study prepared by Pan-Agricultural Laboratories Inc. 281 p
44649701 Drottar, K.; Kruegar, H. (1998) Alachlor: A 5-Day Toxicity Test with the Freshwater Alga (Anabaena flos-aquae): Final Report: Lab Pr oject Number: 139A-215: WL-97-172: 1435. Unpublished study prepared by Wildlife International Ltd. 43 p.
44649702 Drottar, K.; Kruegar, H. (1998) Alachlor: A 14-Day Toxicity Test with Duckweed (Lemna gibba G3): Final Report: Lab Project Number : 1435: 139A-216: WL-97-174. Unpublished study prepared by Wildlife International LTD. 46 p.
44649703 Drottar, K.; Kruegar, H. (1998) Alachlor: A 5-Day Toxicity Test with the Marine Diatom (Skeletonema costatum): Final Report: Lab Project Number: 1435: 139A-217: WL-97-171. Unpublished study prepared by Wildlife International Ltd. 44 p.
44649704 Drottar, K.; Kruegar, H. (1998) Alachlor: A 5-Day Toxicity Test with the Freshwater Diatom (Navicula pelliculosa): Final Report: Lab Project Number: 1435: 139A-218: WL-97-173. Unpublished study prepared by Wildlife International Ltd. 43 p.

Page 131 of 13245046001 Sutherland, C.; Kendall, T.; Krueger, H. (2000) MON 5775: A 5-Day Toxicity Test with Freshwater Alga (Selenastrum capricornutum): Lab Project Number: 1999-191: RDNO1499: 139A-24. Unpublished study prepared by Wildlife International, Ltd. 50 p.
45046002 Sutherland, C.; Kendall, T.; Krueger, H. (2000) MON 5775: A 5-Day Toxicity Test with the Freshwater Alga (Anabena flos-aquae): Lab Pr oject Number: RDNO1499: 1997-197: 139A-244. Unpublished study prepared by Wildlife International, Ltd. 49 p.
45046003 Sutherland, C.; Kendall, T.; Krueger, H. (2000) MON 5775: A 5-Day Toxicity Test with the Freshwater Diatom (Navicula pelliculosa) : Lab Project Number: RDNO1499: WL1999-193: 139A-246. Unpublished study prepared by Wildlife International, Ltd. 49 p.
45046004 Sutherland, C.; Kendall, T.; Krueger, H. (2000) MON 5775: A 5-Day Toxicity Test with theMarine Diatom (Skeletonema costatum): Lab Project Number: RDNO1499: WL-199-192: 139A248A. Unpublished study prepared by Wildlife International, Ltd. 49 p.
45046005 Sutherland, C.; Kendall, T.; Krueger, H. (2000) MON 5775: A 5-Day Toxicity Test with Duckweed (Lemna gibba G3): Lab Project Number: RDNO1499: WL-1999-196: 139A-245A. Unpublished study prepared by Wildlife International, Ltd. 45 p.
40098001 Mayer, F.; Ellersieck, M. (1986) Manual of Acute Toxicity: Interpretation and Data Base 410 Chemicals and 66 Species of Fresh-Water Animals. US Fish & Wildlife Service; Resource Publica tion (160): 579 p.
00028772 Atkins, E.L., E.A. Greywood, R.L. Macdonald (1973). Toxicity of Pesticides and Other Agricultural Chemicals to Honey Bees: Laboratory Studies. Rev. by University of California – Riverside, Dept. of Entomology. Riverside, CA: UC Agricultural Extension Service.

00028549 McAllister, W.A., A.D. Forb is (1978). Acute Toxicity of Technical Alachlor (AB-78-200) to Daphnia magna. (Unplublished study received Dec. 28, 1979 under 524-285; prepared by Analytical Bio Chemistry Laboratories, Inc., submitted by Monsanto Co., Washington, DC; CDL:241535-A)
00028552 McAllister, W.A., A.D. Forbis (1978). Acute Toxicity of Lasso (MCB/Cg) (AB-78-111) to Daphnia magna. (Unplublished study received Dec. 28, 1979 under 524-285; prepared by Analytical Bio Chemistry Laboratories, Inc., submitted by Monsanto Co., Washington, DC; CDL:241535-D)
00087855b McAllister, W.A. (1979). Residue accumulati on study in channel catfish (Ictalurus punctatus) with alachlor-ul-phenyl- 14 C under static conditions. Accumulation, distribution, and elimination. Report No. 22764. Unpublished study performed and submitted by Analytical BioChemistry Laboratories, Inc. Columbia, MO.
44105503 Kirby-Smith, W.W., S.J. Eisenreich, J.T. Howe, R.A. Luetich, Jr. (1993). The Effects in Estuaries of Pesticide Runoff from Adjacent Farm Lands. Duke University Marine Laboratory, Laboratory Report ID – CF 813415.

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