### AMENDED REVIEW
ECOTOX Record Number and Citation: McGregor, E. B., K. R. Solomon, and M.L. Hanson. 2008. Effects of planting system design on the toxicological sensitivity of

### Myriophyllum spicatum and

### Elodea canadensisto atrazine. Chemosphere. 73(3): 249-260. (MRID 48261124) 

### This study was reevaluated on 3/6/15, and the original DER was amended. Please see the attached sheet at the end of the original DER for changes. Note that the study is Supplemental

.

REVIEWED BY: Frank T. Farruggia, Biologist Date: 2/4/2015 EPA/EFED Signature: Digitally signed by FRANK FARRUGGIA DN: c=US, o=U.S. Government, ou=USEPA, ou=Staff, cn=FRANK FARRUGGIA, dnQualifier=0000048865 Date: 2016.03.24 09:11:04 -04'00'

### Amended DER:
ECOTOX Record Number and Citation: McGregor, E. B., K. R. Solomon, and M.L. Hanson. 2008. Effects of planting system design on the toxicological sensitivity of

### Myriophyllum spicatum and

### Elodea canadensisto atrazine. Chemosphere. 73(3): 249-260. (MRID 48261124) 

### Please note the following amendments tothe original DER (Dated October 17, 2009) Validation Category: Supplemental This study was originally reviewed for its inclusion in the community effects database for atrazine toxicity to aquatic plant communities.However, this study also investigated individual species in several tests with atrazine. The following review focuses only on the results from individual toxicity testing withElodea canadensis. Valid study methods: Three different study designs were included in the study for investigating individual species performance under controlled and atrazine exposure conditions. These were “IND” (Individuals planted in separate pots), “Pop1” (a low-density population of individuals in each pot), and “Pop2” (a high-density population of individuals in each pot). The original review and the authors describe an uneven and poorly monitored herbivory situation in the controls of the IND study. They also describe poor growth in the test concentration of 25 ug/L. For these reasons, the results from the IND study will be excludedfrom this review as confidence in the reported toxicity results is low. Low-density populations (Pop1): Responses varied across measurement endpoints and duration. The most sensitive EC50

### was reported for the 14-day reported values from wet root weight and dry root weight.(6.2 and 4.6 ug/L respectively). For the later time intervals (28 and 42 days) these estimates for these endpoints in Pop1 ranged from 16 - 22 ug/L. Wet-and dry-weight for shoots was also reported, the most sensitive reported EC50

### for these endpoints at the 14-day duration was 21 ug/L for wetweight (27 ug/L for dry-weight), and reported values for longer durations ranged from 18

– 30 ug/L. High-density populations (Pop2): Responses also varied across measurement endpoint and duration. The most sensitive EC50

### from the 14-day duration was 29 ug/L for wet-weight (30 ug/L for dry weight). The longer duration measurements for these endpoints ranged from 21

– 37 ug/L. Wet- and dry-weight for shoots was also reported, the most sensitive reported EC50

### for these endpoints at the 14-day duration was 44 ug/L for dry-weight (79 ug/L for wet-weight), and reported values for longer durations ranged from 23

– 63 ug/L. The 14-day reported value of 4.6 ug/L for root dry-weight from Pop1 represents the most sensitive endpoint from this study.

### Open Literature Review Summary

Chemical Name: Atrazine 

### CAS No: 1912-24-9



### ECOTOX Record Number and Citation: McGregor, E. B., K. 

### R. Solomon, and M.L. Hanson. 2008. Effects ofplanting system design on the toxicological sensitivity of

### Myriophyllum spicatum and 

### Elodea canadensis to atrazine. Chemosphere. 73(3): 249-260. (MRID 48261124)



### Purpose ofReview: Determine potential effects ofatrazine on an aquatic community. Endpoints from this study contribute to the weight-of-evidence regarding effects ofatrazine on aquatic plant communities and associated determination ofa Level ofConcern (LOC).



### Date ofReview: October 17,2009



### Purpose ofStudy: This study examines the potential effects ofatrazine on aquatic plants (macrophytes 

### M spicatum and E. 

### canadensis) grown individually and in population and community-level assemblages in 

### large outdoormicrocosms.


### Summary ofStudy Findings

Methods: The study used 15 outdoormicrocosms located at the University ofGuelph Microcosm Facility at the Guelph Turfgrass Institute, Ontario, Canada. Each microcosm was about 1.2 m deep, 3.9 m in diameter and 12,000 L in volume. Microcosms were lined with black food-grade polyvinyl chloride and were sunk into the ground so the tops were flush with ground level. Water was supplied from an adjacent spring-fed irrigation pond (62 x 62 x 4 m deep). Thirty-five plastic propagation trays (52 x 25 x 7 em) filled with an amended sedimentmix were added to the bottom ofeach microcosm. The sedimentwas a 1:1:1 mixture ofsand, loam, and organic matter and covered approximately 38% ofthe floor ofeach microcosm. Sediment carbon analysis was determined by combustion using a Leco Carbon Analyzer (LECO SC444). Total carbon content was 7.0%, inorganic carbon was 1.0%, and organic carbon was 6.0%.

- 1 - 

# 1II1II1III 2087808Water was circulated between the irrigationpond and microcosms at a rate of 12,000 L per day for 25 days priorto atrazine treatment to reduce variability between and within the microcosms. Six pots of

### M spicatum (plants obtained from several on-site untreated microcosms) were planted in each microcosm during the initialization time, and were not used for effects assessment. Circulation ended two days priorto treatment (July 16, 2006). The macrophytes used for effects assessment (see below) were added to the microcosms on July 17,2006, one day priorto treatment. Treatment occurred on July 18,2006 and the experiment was terminated on August 29,2006 (42 days).

Five planting designs were used: individual plants, population assemblages (low and high density), and community assemblages (low and high densities). Each microcosm contained plants potted in each ofthese arrangements.

For individual planting designs, 

### M spicatum L. (Haloragaceae) and E. 

### canadensis Michx. (Hydrocharitaceae) were obtained from an on-site untreated microcosm whose populations were originally obtained from a local reservoir (Guelph Correctional Facility, Guelph, Ontario). Each plant was grown in an individual 164 mL cone-tainer (a plastic planting tube, 21 ern long with 3.8 em internal diameter, bottomhole plugged with cotton pad) held in a 96-well planting tray. Cone-tainers were filled with the same amended sedimentused in the microcosms and were soaked for several days in irrigation pond water to allow settling. Apical shoots, without side roots or shoots, ofeachplant were cut to 5 em priorto planting. Each shoot was planted 2 ern deep and surrounded by 0.5-1 em ofTurface (Applied Industrial Materials, Buffalo Grove, Illinois) to secure it. Six plants per species were placed evenly spaced in each tray. One tray
was placed in the center ofeach microcosm to provide maximum sunlight and reduce edge effects (total number oftrays per microcosm containing individually pottedplants was not stated). On the day before atrazine application, 10 plant shoots per species were evaluated as a baseline, and on days 14, 28, and 42, two plants from each species per microcosm were sampled at random.

For assemblage planting designs, mixed (two species) and monocultures of

### M spicatum and E. 

### canadensis were grown in plastic sterilite containers (34.9 x 20.6 x 32.1 em). Containers were filled with sediment and prepared for planting like the cone-tainers. Monocultures were grown at two densities: low-density consisted ofnine plants per container (one plantper 80 cm2 in a 3x3 grid configuration) and high-density consisted of 18 plants per container (one plantper 40 cm2 in a 6x3 configuration). Two-species mixed planting designs were also grown at two densities: low density was nine plants per species (18 plants total in a 6x3 configuration) and high density was 18 plants per species (configurationnot provided). Species type was alternated in each row of plants. A total of 18 sterilite containers (3 containers per assemblage design) were added to each microcosm; evenly spaced around the cone-tainertrays in the microcosm center. Assemblage planting designs (monoculture and mixed) were sampled on days 14,28, and 42 aftertreatment.

- 2 -After sampling, plants were transported to the laboratory in water from theirrespective microcosm and immediately measured for biomass (wet and dry) ofboth roots and shoots. Chlorophyll 

### a was measured by ethanol extraction with an Ultraspec 3100

### pro UV/Visible Spectrophotometerusing methods described byNusch (1980). Biomasses ofassemblages of plants were normalizedto a per-plantbasis to allow comparison with individually grownplants.

Microcosms were treated with either 0 (controls), 25,50, 100, 

### or250 

### ug/Latrazine (n=3 microcosms pertreatment). Treatments were randomly assignedto microcosms. Atrazine (96% a.i., technical grade) was dissolved in 50 mL acetone in amberbottles, shaken, and added to the microcosms while agitating with a stirrerto promote mixing. Control microcosms received the
same volume ofacetone.

Water samples for atrazine analysis and water quality determination were collected using a metal depth-integrated water column sampler. A composite sample was created from at least four randomly selected locations in each microcosm, and stored at 4°C until analysis (500 mL aliquots were stored for water quality). Water sampling occurred on days -1, 1,4, 7, 14,28, and 42.

Water quality measurements were temperature, dissolved oxygen (DO), pH, alkalinity, hardness, and conductivity. Maximum and minimum temperatures were measured daily Monday through Friday at a water depth of20 em. Pointmeasurements oftemperatures and DO weremade daily at 50 em depth with a HANNA HI-9143 meter. DO was not measured on the lasttwo days of the study due to equipment failure. Waterhardness, alkalinity and conductivity were measured
on days -1, 21, and 42. pH was measured weekly. Hardness and alkalinity were determined with standard methods and kits by Hach. pH and conductivity were measured with an Accumet Research AR20 pH/Conductivity meter. Photosynthetically active radiation (PAR) was measured weekly with a LI-185A Li-Cor QuantumiRadiometerlPhotometer at midday on clear sunny days. Readings were normalized by taking them at the surface ofeach microcosm, at the surface in a glass jar, and at a depth of60 em in a glassjar.

Atrazine concentrations were analyzed by enzyme linked immunosorbent assay (ELISA), using the Abraxis Atrazine Assay Kit. Samples were prepared for analysis by bringing them to room temperature and centrifuging 10 mL aliquots at 805 g for 10 min, then diluting them so concentrations would fall withinthe range ofthe standard response curve (0.1-5 ug/L), Calibration curves were calculated with an Ohmicron RPA-I photometric analyzer. Analyses
were performed within 48 hours ofsampling, generally within 24 hours. Time-weighted averages at each treatment level for the three replicates were calculated.

For each monitored water quality variable and PAR, a one-way analysis ofvariance (ANOVA) was performed to identify significant differences among treatments using SigmaStat 3.5. ANOVA assumptions were tested withthe Kolmogorov-Smimov test for normality ofresiduals
- 3 -and the Levene median test for homogeneous variance. When significance was found (p 

### < 0.05), means were compared with the control using Dunnett's test (a = 0.05).

Planttoxicity (change in biomass endpoints) was evaluated using regression techniques described in Stephenson et al. (2000). Macrophyte data for all treatments was modeled in SigmaPlot 2000 with linear, logistic, and hormetic equations. The best-fit models were selected by visual examination ofthe plots and the correctedr2(1 - [residual sum ofsquares]/[corrected
sum ofsquares

## D. When biomass endpoints showed a significant concentrationresponse (p 

### < 0.05), effective concentrations EC IO, EC2s, and ECso(10%, 25%, and 50% difference between atrazine treatments and controls in measured endpoints) were calculated along with their confidence intervals using proc NUN in SAS v9.1. Only new growth data were used to assess effects via regression analysis: mean biomass data on each sampling day was subtracted from mean biomass data from the previous sampling day.

Relative growth rates (RGR) were calculated from wet and dry biomass ofcontrol plants according to the following equation: RGR = [In(W2)-In(Wd]/(t2 - tl) where WI and W2are plant weights at time tl andt2. RGRs were compared for all planting designs (individual, monoculture at high and low density, mixed culture at high and low density) for samples on days 14,28, and 42 using one-way ANOVA (a = 0.05) in SigmaStat 3.5 and Tukey's test for pairwise comparisons when significance was found.

Interactions between atrazine concentration and planting design factors on biomass endpoints were assessed with two-way ANOVA (a 

### = 0.05) using proc mixed in SAS v9.1. ANOVA assumptions ofresidual normality and homogeneous variance were assessed using the ShapiroWilktest (proc univariate normal) and by graphical interpretation ofresidual plots. Non-normal data were transformed by natural log or square root. When significant interactions between atrazine and planting design were detected, the "slice" command (not further described) was used to see how atrazine effects changed withplanting design. When main factor effects were significantbut interaction effect was not significant, means betweenpairs oftest designs (e.g. individual vs. population) were compared using orthogonal contrasts (procedure not further described).



### Results: Time weighted average (TWA) atrazine concentrations for the 42-day atrazine exposure were close to nominal: control microcosms (O.O±O.O J,!g/L), 25 J,!g/L microcosms (24.5±2.5 J,!g/L), 50 J,!g/L microcosms (49.5±2.8 J,!g/L), 100 J,!g/L microcosms (104.0±5.6 J,!g/L), and 250 J,!g/L microcosms (247.5±12.2 J,!g/L). Measured TWAs were used as the exposure level in data analysis.

- 4 -

### Average values for water quality parameters over all sampling days in the course ofthe study are provided in Table 

### 1. No significant (p < 0.05) differences from controls were detected with Dunnett's test for multiple comparisons, except for minimumtemperature and DO. Minimum temperature post-treatment, though significantly different in treatments, showed no concentration-response trend. Dissolved oxygen was significantly decreased at the two highest treatment levels comparedto controls. Figure 1 

### shows trends in DO at each treatment level over the experiment.
For plant toxicity, nonlinearregression analysis showed significant concentration-response relationships for over 90% ofthe sampling times, planting designs, and biomass endpoints examined, and EC lO, 

### EC2S, and ECso were calculated in most cases (Table 

### 2 and Table 

### 3). Effective concentration (ECx) represented atreatment related decrease in all endpoints except for chlorophyll 

### a in individually grown plants. For individually grown M. 

### spicatum (days 14,28, 42) and E. 

### canadensis, chlorophyll increased with increasing atrazine concentrations; therefore, EC IO, 

### EC2s, and ECsorepresent 10%,25%, and 50% increases for these endpoints only. Box plots ofECsoestimates are shown in Figure 

### 2. The study authors do not state which biomass endpoints were plotted, however, the study reviewer assumes that data from all biomass endpoints were combined into each box plot.
Relative growth rates (RGR) ofM. 

### spicatum and E. 

### canadensis in control microcosms are presented in Table 

### 4. RGRs were similar among the differentplanting designs except for the significant difference (p<0.05) in E. 

### canadensis on days 28 and 42. Pairwise comparison showedthat the RGRwet 

### ofindividually grown E. 

### canadensis was significantly lower (p<0.05) than those ofplants grown in high and low density model populations. RGR data is not presented for treated microcosms.

Atrazine had a significant (p<0.05) effecton plantwet and dry biomass at all time points (Table 

### 5). This analysis did not examine atrazine effects from individual treatment concentrations. Plant biomass was significantly affected by planting design in about 60% ofthe endpoints (plant/date/biomass). Generally, there were no significant interactions between atrazine concentration and planting design on wet or dry biomass. The exceptions were day 14 wet shoot biomass of

### M spicatum, wet shoot and total wet biomass ofE. 

### canadensis on day 28, and all biomass endpoints ofE. 

### canadensis on day 42. The "slice" command was applied to assess how atrazine effects varied over planting treatments. The study authors reported that the biomass of individually grown E. 

### canadensis was not significantly differentin each atrazine treatment; however, the biomass ofplants grown in assemblages was significantly different in each atrazine treatment. The study authors also reported that orthogonal contrasts comparing mean biomass measures betweenplanting designs showed few significant differences betweenplanting designs, and no consistenttrends across biomass endpoints for planting systems that showed statistically significant different means. No further information or data was provided by the study authors regarding the 'slice" command and orthogonal contrastresults.

- 5 -

### The study authors mention that individually grown E. 

### canadensis were grazed upon in some control microcosms. They do not indicate ifgrazing occurred in any ofthe treatment microcosms. Plants did not grow at all in the 25 ug/L atrazine treated microcosms. The study authors suggestthat the lack ofgrowth may have been due to the selection oflow-qualityplants or the chance occurrence ofan herbivore. Due to these issues, the study authors suggestthey may have used insufficientreplication. No further information is provided. They also note that relative growth rates ofthe macrophytes were significantly lower than those ofthe same species from previous investigations conducted at the same experimental site over similar experimental lengths.

- 6 -Table 1. Chemical and physical parameters ofthe microcosms averaged over the duration ofthe 42-day experiment, plus pre-treatment values. The values presented are mean ± standard deviation of measurements over all sampling times, calculated from the mean of3 replicate microcosms at each sampling date. pH values were converted to corresponding hydrogen ion concentrations for statistics calculations. Alkalinity and hardness are measured as mglL ofCaCOJ• PAR=photosynthetically active radiation. (study table 1) ConductTreatment Minimum temperature Maximum temperature Dissolved oxygen pH Alkalinity Hardness ivity PAR (JlgIL) (0C) (0C) (mgIL) (n=7) (mgIL) (mg/L) (JlS/cm) (mE2/s) Pre- (n=4) Post- (n=28) Pre- (n=4) Post- (n=28) Pre- (n=4) Post- (n=25) (n=3) (n=3) (n=3) (n=4) Control 22.8 ±2.9 22.2±2.2 25.8 ± 1.8 25 ± 2.4 10.3 ± 0.4 11.4 ± 1.5 8.7 ± 0.4 177 ± 30 305 ± 18 657 ± 26 503 ± 107 25 22.4 ± 2.8 24.4 ± 2.3 * 25.5 ± 2.3 25.2 ± 2.3 10.4 ± 0.4 11.6± 1.6 8.8 ± 0.4 167 ± 34 295 ± 30 630 ± 17 510± 113 50 22.6±2.7 24.1 ± 2.0 * 26.2 ± 1.7 25.3 ± 2 10.4 ± 0.3 II ± 1.6 8.7 ± 0.5 161 ± 44 295 ± 33 647±15 577 ± 134 100 22.7 ± 2.4 22.1 ± 2.3 25.7±2.6 25.2±2.1 10.4 ± 0.4 9 ± 1.4* 8.5 ± 0.6 184 ± 13 311±17 703 ±29 513 ± 148 250 22.5 ± 2.3 22 ± 2.1 26.3 ± 1.8 25.6±2 10.3 ± 0.3 7 ± 1.7* 8.3 ± 0.5 199± 5 333 ±22 727±41 510±142 *Mean significantly different from control mean (p <0.05) by Dunnett's test.

Figure 1. Dissolved oxygen (mg/L) concentrations at a depth of50 cm in aquatic microcosms prior to treatment and post treatment with various levels of atrazine over the 42-day exposure duration. (study figure 1)



### - 7 -Table 2. For Elodea canadensis, effective concentrations (ug/L) of atrazine required to cause a decrease in the endpoints ofinterest by 10%,25%, and 50% (ECIO, EC2S, and ECso ) with associated 95% confidence intervals, Chlorophyll a endpoint EC's on day 28 and 42 (not day 14) are those required to cause an increase (110%,125%,150%). EC's were calculated from the best-fit model for endpoints that showed a significant concentration-response relationship (model type, equation, and corrected r 2 are shown). CI = confidence interval; Ind = individually grown plants; Popl = population low-density; Pop2 = population high density; Coml = community low density; Com2 = community high density. (study table 2)

Day Endpoint Planting design EClO (95% CI) EC ,5(95% CI) EC50 (95% CI) Model Parameters Corrected r> 14 Chioro-a Ind nc nc nc nc nc Wet root Ind 41.0 (0, 173.3) 58.3 (0, 182.9) 82.8 (0, 196.0) Logistic b = 3.1298; t = 0.0219; x = 82.8 0.86 Popl 0.4 (0, 4.8) 1.6 (0, 139) 6.2 (0, 35.2) Logistic b = 0.7988; t = 0.0205; x = 6.2 0.98 Pop2 5.5 (0, 17.8) 12.7 (0, 30.9) 29.3 (5.9, 526) Logistic b = 1.3159; t = 0.0137; x = 29.3 0.96 Coml 8.5 (0, 61.9) 230 (0,115.8) 627 (0, 217.2) Logistic b = 1.0972; t = 0.0202; x = 62.7 0.59 Com2 22.8 (8.6, 37.1) 57.1 (21.6,92.6) 114.2 (43.2,185.3) Linear b = 0.0104; x = 114.2 0.35 Dry root Ind 29.3 (0, 599) 73.2 (0, 1497) 146.5 (0,299.4) Linear b = 0.0027; x = 146.5 0.45 Popl 0.4 (0, 69) 1.3 (0, 18.3) 4.6 (0, 43.3) Logistic b = 0.8571; t = 0.0024; x = 4.6 098 Pop2 39 (0, 17.3) 10.8 (0,34.7) 30.2 (0,66.1) Logistic b = 1.0728; t= 0.0012; x = 30.2 0.85 Coml nc nc 0.001 (0,0.4) Logistic b = 0.0739; t = 0.0027; x = 0.001 0.42 Com2 22.5 (9.8, 35.2) 56.3 (24.5, 88.0) 112.5 (490, 176.0) Linear b = 0.0011; x = 112.5 0.48 Wet shoot Ind 0.006 (0, 0.4) 0.4 (0, 15.4) 23.2 (0,296.9) Logistic b = 0.2673; t = 0.2283; x = 23.2 0.81 Popl 1.2(0, 6.0) 5.1 (0, 18.3) 21.8 (0, 49.6) Logistic b = 0.7592; t = 0.2623; x = 21.8 088 Pop2 25.9 (0, 71.4) 45.2 (0, 97.7) 78.9 (18.9, 138.8) Logistic b = 1.9757; t = 0.1777; x = 78.9 0.91 Coml 7.1 (0, 53.2) 209 (0, 107.2) 61.9 (0, 214.2) Logistic b = 1.0126; t = 0.1002; x = 61.9 0.72 Com2 47.9(0,146.7) 61.7 (0,151.0) 79.5 (2.3, 156.7) Logistic b = 4.3312; t = 0.0481; x = 79.5 0.97 Dry shoot Ind 8.6 (0, 379) 19.5 (0, 62.5) 44.2 (0, 1038) Logistic b = 1.3462; t = 0.0165; x = 44.2 0.86 Popl 17.1 (0,37.2) 21.5 (7.5, 35.6) 272 (13.7, 40.7) Logistic b = 4.7348; t = 0.0109; x = 27.2 0.99 Pop2 28.0 (0, 99.5) 35.0 (0, 92.2) 43.7 (8.3, 79.2) Logistic b =4.9281; t=0.0098; x=43.7 0.99 Coml 9.1 (0, 52.0) 18.2 (0, 74.2) 36.2 (0, 105.1) Logistic b = 0.0034; t = 0.0042; x = 36.2 0.39 Com2 27.2 (0, 126.1) 32.8 (0, 117.3) 396 (0, 103.0) Logistic b = 5.8223; t = 0.0040; x = 39.6 0.99 28 Chloro-a Ind nc 82.9 (5.0, 160.8) 165.8 (10.1, 321.5) Linear b = 1.3424; x = 165.8 0.74 Wet root Ind nc nc nc nc nc Popl 9.0 (0, 36.2) 13.4 (0, 39.6) 20.0 (0.7, 39.3) Logistic b =2.7465; t= 0.1791; x=20.0 0.99 Pop2 11.8 (0, 27.1) 16.4 (3.4, 29.4) 22.7(14.4,311) Logistic b = 3.3517; t = 0.1533; x = 227 099 Coml 30.9 (0, 88.7) 48.7(0, 109.1) 76.6 (14.0, 139.2) Logistic b = 2.4223; t = 0.0504; x = 76.6 0.88 Com2 20.2 (9.9, 30.5) 50.5 (24.7, 76.3) 100.9 (49.3, 152.5) Linear b = 0.0612; x = 100.9 0.38 Dry root Ind nc nc nc nc nc Popl 5.8 (0, 326) 9.6 (0, 39.7) 158 (0, 43.2) Logistic b = 2.1900; t = 0.0164; x = 15.8 0.99 Pop2 10.5 (0,26.8) 15.1 (0.4,29.7) 21.6 (11.6, 31.6) Logistic b = 3.0466; t = 0.0135; x = 21.6 099 Coml 33.0 (0, 70.0) 44.8 (11.6, 78.0) 61.0 (27.1,948) Logistic b = 3.5708; t = 0.0050; x = 61.0 0.96 Com2 5.1 (0,22.3) 9.7 (0, 31.4) 18.4 (0, 40.5) Logistic b = 1.7023; t = 0.0134; x = 18.4 099 Wet shoot Ind 4.8EClO (0, 15EC7) 0.00011 (0,0.02) 247 (0, 546.4) Logistic b = 0.0891; t = 0.3655; x = 247 0.83 Popl 4.4 (0, 16.023) 9.5 (0,25.9) 20.3 (1.6,39.1) Logistic b = 1.4347; t = 1.3464; x = 20.3 0.99 Pop2 9.0 (0, 18.0) 16.4 (58, 27.1) 300 (18.6, 41.4) Logistic b = 1.8250; t = 1.1458; x = 30.0 099 Coml nc nc nc nc nc Com2 10.1 (0,36.5) 20.8 (0, 56.1) 427 (0, 88.0) Logistic b = 1.5291; t = 0.2607; x = 42.7 0.97 Dry shoot Ind 30.0 (1.3,58.7) 75.0 (3.4, 146.7) 150.1 (6.7,293.5) Linear b = 0.0418; x 150.1 0.97 

### - 8 -Day Endpoint Planting design ECIQ (95% CI) EC25 (95% CI) EC50 (95% CI) Model Parameters Corrected [2 Popl 4.5 (0,21.4) 9.1 (0,31.6) 18.3 (0,42.4) Logistic b = 1.5743; t=0.1172; x = 18.3 0.99 Pop2 7.3 (0, 18.3) 12.8 (0.3, 25.3) 22.6 (10.9, 34.3) Logistic b = 1.9342; t=0.1209; x =22.6 0.99 Coml nc nc nc nc nc Com2 10.5 (0,26.0) 19.4 (0.68, 38.0) 35.9 (14.4, 57.3) Logistic b = 1.7821; t =0.0464; x=35.9 0.97 42 Chloro-a Ind nc 80.0 (8.5,151.4) 159.9 (17.0, 302.9) Linear b = 1.1121; x = 159.9 0.54 Wet root Ind nc nc nc nc nc Popl 6.2 (0, 31.8) 10.4 (0, 39.2) 17.6 (0, 43.4) Logistic b =2.0955; t =0.8724; x= 17.6 0.99 Pop2 19.4 (1.7, 37.0) 27.4 (10.5, 44.2) 38.6 (22.7,54.5) Logistic b =3.1936; t= 0.4066; x=38.6 0.99 Coml 20.8 (0, 54.1) 29.1 (0,60.2) 40.6 (12.5, 68.7) Logistic b =3.2826; t= 0.1600; x=40.6 0.99 Com2 4.2 (0, 19.0) 9.8 (0, 32.4) 23.1 (0, 51.3) Logistic b = 1.2907; t= 0.1462; x=23.1 0.98 Dry root Ind nc nc nc nc nc Popl 5.3 (0,30.7) 9.3 (0, 39.7) 16.6 (0, 45.6) Logistic b = 1.9213; t= 0.0864; x= 16.6 0.99 Pop2 5.9 (0, 19.4) 11.4 (0, 28.6) 22.3 (4.4,40.1) Logistic b = 1.6491; t= 0.058; x =22.3 0.98 Coml 21.0 (8.9, 33.0) 52.4 (22.3, 82.6) 104.8 (44.6,165.1) Linear b =0.0222; x = 104.8 0.46 Com2 4.1 (0, 16.5) 9.5 (0,28.4) 22.3 (0, 45.8) Logistic b = 1.2950; t= 0.0215; x =22.3 0.99 Wet shoot Ind nc nc nc nc nc Popl 6.8 (0, 23.6) 14.5 (0,377) 31.1 (2.7, 59.6) Logistic b = 1.4420; t=2.7193; x=31.1 0.97 Pop2 nc nc 62.6 (42.3,82.9) Logistic b =3.5941; t= 1.6819; x= 0.96 Coml 39.1 (0, 140.1) 59.9 (0, 160.3) 91.9 (0, 189.1) Logistic b =2.5733; t =0.4981; x =91.9 0.99 Com2 23.3 (10.8, 35.8) 58.2 (27.0, 89.4) 116.4 (54.1,178.8) Linear b =0.3625; x= 116.4 0.67 Dry shoot Ind nc nc nc nc nc Popl 2.4 (0, 14.1) 7.0 (0, 29.6) 20.8 (0,55.7) Logistic b = 1.0140; t=0.334; x =20.8 0.87 Pop2 17.8 (4.5, 31.2) 30.0 (15.1, 44.9) 50.4 (33.7, 67.1) Logistic b =2.1156; t=0.2582; x=50.4 0.95 Coml 28.6 (0, 105.1) 47.9 (0, 132.4) 80.1 (0, 172.5) Logistic b =2.1365; t =0.1012; x =80.1 0.97 Com2 2.4 (0, 13.2) 8.0 (0, 31.2) 26.9 (0, 67.3) Logistic b =0.9047; t=0.1039; x=26.9 0.83



### - 9 -Table 3. ForMyriophyllum spicatum, effective concentrations (I!g/L)ofatrazine required to cause a decrease in the endpoints ofinterest by 10%,25%, and 50% (EClO, EC2s, and ECso ) with associated 95% confidence intervals, Chlorophylla endpoint EC's are those required to cause an increase (110%, 125%, 150%). EC's were calculated from the best-fit model for endpoints that showed a significant concentration-response relationship (model type, equation, and corrected r2 are shown). CI = confidence interval; Ind = individually grown plants; Pop1 = population low-density; Pop2 = population high density; Com1 = community low density; Com2 = community high density. (study table 3)

Day Endpoint Planting design ECIO (95% CI) EC25 (95% CI) EC50 (95% CI) Model Parameters Corrected r' 14 Chloro-a Ind 29.9 (20.9, 39.0) 74.8 (52.2, 97.5) 149.7 (1043,195.0) Linear b = 0.6449; x = 149.7 0.99 Wet root Ind 21.8 (0, 52.8) 36.0 (1.8, 70.1) 59.4 (21.7, 97.1) Logistic b=2.1893; t=0.7622; x= 59.4 0.92 Popl 18.4 (0,472) 323 (0, 65.9) 56.7 (17.5, 95.8) Logistic b = 1.9567; t = 0.5426; x = 56.7 0.82 Pop2 23.9 (0, 506) 39.1 (10.1,68.1) 63.9 (32.2, 95.6) Logistic b = 2.2337; t = 0.489; x = 63.9 0.9 Coml 15.1 (0,30.2) 26.5 (8.9,44.1) 465 (26.1, 669) Logistic b = 1.9487; t = 0.444; x = 46.5 0.97 Com2 24.7 (0, 55.1) 35.7 (73, 64.1) 51.5 (25.0, 77.9) Logistic b = 2.9887; t = 0.4183; x = 51.5 0.74 Dry root Ind 27.7 (0, 75.2) 43.7 (0, 93.7) 69.0 (16.1,121.8) Logistic b = 2.4067; t = 0.0417; x = 69.0 0.88 Popl 26.5 (12.9,40.2) 663 (32.1, 100.5) 132.7 (64.3, 201.0) Linear b = 00275; x = 132.7 0.5 Pop2 256 (0, 53.2) 41.7 (11.8, 71.5) 67.8 (35.4, 100.2) Logistic b = 2.2532; t = 0.0298; x = 67.8 0.9 Coml 13.4 (0, 29.5) 23.4 (5.0, 41.9) 40.9 (20.0, 61.8) Logistic b = 1.9724; t = 0.0264; x = 40.9 0.99 Com2 240 (12.0, 36.0) 59.9 (29.9, 90.0) 120.0 (59.8, 180.0) Linear b = 0.0204; x = 120.0 0.47 Wet shoot Ind 75.4 (0, 196.8) 188.6 (0,492.0) 377.2 (0, 984.0) Linear b = 0.5696; x = 377.2 03 Popl 277 (13.2, 42.2) 693 (33.1, 105.4) 138.5 (66.2,210.8) Linear b = 1.2575; x = 1385 0.29 Pop2 26.1 (0,65.4) 50.2 (0.7, 99.6) 96.4 (34.8, 157.9) Logistic b = 1.6825; t = 1.0424; x = 96.4 0.79 Coml 12.4 (0, 37.5) 36.8 (0, 83.0) 109.4 (23.9, 1949) Logistic b = 1.0079; t = 1.2698; x = 109.4 0.97 Com2 261 (15.1,37.1) 653 (37.7,928) 130.5 (75.4, 1857) Linear b = 0.8469; x = 130.5 0.69 Dry shoot Ind 357 (7.2, 643) 893 (17.9, 160.7) 178.6 (35.8, 321.4) Linear b = 0.0673; x = 178.6 0.43 Popl 24.0 (15.2, 32.7) 599 (38.0, 81.8) 119.8 (76.1,163.5) Linear b = 0.1006; x = 119.8 0.51 Pop2 27.6 (0, 62.617) 427 (6.5, 79.0) 66.2 (283, 104.2) Logistic b = 2.5083; t = 0.1008; x = 66.2 0.82 Coml 3.6 (0, 13.4) 14.1 (0,38.0) 55.8 (5.0, 106.6) Logistic b = 0.7975; t = 0.1139; x = 55.8 0.92 Com2 18.7 (U, 363) 31.7 (11.9, 51.6) 53.9 (31.5, 763) Logistic b = 2.0750; t = 0.0853; x = 53.9 0.88 28 Chloro-a Ind 21.0 (15.1, 26.9) 52.4 (37.6, 67.2) 104.9 (753, 134.5) Linear b = 1.0226; x = 104.8 0.94 Wet root Ind 6.4 (0, 143) 14.6 (2.9, 263) 33.5 (18.1,48.9) Logistic b = 1.3271; t = 2.2309; x = 33.5 0.94 Popl 22.2 (7.0, 375) 55.5 (17.4, 93.6) 111.0 (34.8, 1873) Linear b = 0.8680; x = 111.0 0.25 Pop2 171 (0,509) 25.7 (0, 59.6) 38.7 (47,72.7) Logistic b = 2.6884; t = 1.3293; x = 387 0.99 Coml 21.9 (1.6, 42.1) 26.4 (7.4, 45.4) 31.8 (8.9,54.7) Logistic b = 5.8401; t = 1.3301; x = 31.8 0.99 Com2 233 (12.2, 34.4) 58.2 (30.4, 860) 116.5 (60.9,172.1) Linear b = 0.4201; x = 116.5 0.46 Dry root Ind 1.7 (0, 10.2) 65 (0, 273) 25.2 (0, 65.4) Logistic b = 0.8142; t = 0.2445; x = 25.2 0.87 Popl 2U (45,37.7) 528 (11.4, 94.1) 105.5 (22.7, 1883) Linear b = 0.0841, x = 105.5 OJ7 Pop2 24.4 (0, 75.8) 31.2 (0, 76.4) 399 (38, 75.9) Logistic b =4.4753; t = 0 1333; x = 39.9 0.99 Coml 18.2 (0, 46.2) 22.4 (4.0, 40.8) 276 (6.9, 483) Logistic b = 5.2685; t = 0.168; x = 27.6 0.99 Com2 3.4 (0, 393) 73 (0, 58.9) 15.5 (0, 75.7) Logistic b=1.4515;t=0.1619;x=155 0.99 Wet shoot Ind 303 (17.6, 429) 75.6 (44.0, 107.3) 151.3 (88.0,2145) Linear b = U559; x = 151.3 0.61 Popl 240 (62, 41.8) 600 (15.5,1046) 120.1 (31.0,209.2) Linear b = 1.9232; x = 120.1 031 Pop2 377 (0, 1393) 57.2 (0,1581) 86.9 (0, 184.4) Logistic b = 2.6307; t = 1.2715; x = 869 0.96 Coml 268 (6.1,47.5) 670 (152,1188) 133.9 (30.3, 2375) Linear b = 1.7578; x = 1339 0.18

- 10-Day Endpoint Planting design ECIO (95% CI) EC25 (95% CI) EC50 (95% CI) Model Parameters Corrected

### r Com2 25.9 (10.9, 40.9) 64.7 (27.2,102.3) 129.5 (54.4,204.6) Linear b = 1.0324; x = 129.5 033 Dry shoot Ind 4.8 (0, 17.6) 14.2 (0, 38.6) 42.5 (1.6, 83.5) Logistic b = 1.0025; t = 0.1960; x = 42.5 0.78 Popl 22.6 (6.6,38.5) 56.4 (16.6,96.3) 112.8 (33.1, 192.5) Linear b = 0.2842; x = 112.8 0.43 Pop2 43.3 (0, 143.6) 57.8 (0, 150.9) 77.2 (0, 163.1) Logistic b = 3.7953; t = 0.1551; x = 77.2 0.96 Coml 21.0 (9.8, 323) 52.6 (24.5, 80.6) 105.1 (49.0, 161.3) Linear b = 0.2354; x = 105.1 0.44 Com2 35.8 (0, 107.5) 51.3 (0, 120.8) 73.5 (5.1,141.8) Logistic b = 3.0615; t = 0.1749; x = 73.5 0.71 42 Chloro-a Ind 24.6 (9.4, 39.8) 61.5 (23.5, 99.4) 122.9 (47.1,198.8) Linear b = 0.8665; x = 122.0 0.79 Wet root Ind 25.0 (8.9 41.2) 62.6 (22.2 103.0) 125.2 (44.4 206.0) Linear b = 1.3906; x = 125,2 0.57 Popl nc nc 28.2 (0, 2363) Hormetic b=-0,0513; t=0.5160; 0.56 h = -0.0447; x = 28.2 Pop2 nc nc 35.6 (0, 251.6) Hormetic b = 1.0022; t = 0.8844; 0.53 h = -0.0447; x = 35.6 Coml 20.8 (0, 54.1) 29.1 (0, 60.2) 40.6 (12.5, 68.7) Logistic b = 3.2826; t = 0.16; x = 40.6 0.99 Com2 22.9(3.7,42.1 57.2 (93, 105.2) 114.4 (18.5, 210.4) Linear b = 1.0049; x = 114.4 0.63 Dry root Ind 22.9 (4.6, 41.2) 57.2 (11.4,103.1) 114.5 (22.8,206.1) Linear b = 0.1934; x = 114.5 0.43 Popl nc nc 24.6 (0, 435.0) Hormetic b = 1.0073; t = 0.0924; 032 h = -0.0409; x = 24.6 Pop2 nc nc nc nc nc Coml 21.0 (8.9, 33.0) 52.4 (223, 82.6) 104.8 (44.6,165.1) Linear b = 0.0222; x = 104.8 0.46 Com2 423 (0, 121.0) 52.1 (0, 122.9) 64.0 (0, 154.7) Logistic b = 5.3061; t = 0.1674; x = 64.0 0.95 Wet shoot Ind 34.8 (9.4, 60.1) 86.9 (23.5, 1503) 173.8 (47,0, 300.5) Linear b = 1.0201; x= 173.8 0.41 Popl nc nc 53.1 (0 157.4) Hormetic b = 0.8781; t = 1.4204; 0.12 h = -0.0731; x = 53.1 Pop2 nc nc nc nc nc Coml 36.0 (0, 136.1) 52.1 (0, 149.8) 75.5 (0, 170.8) Logistic b = 2.9648; t = 03721; x = 75,5 0.99 Com2 25.8 (1.9, 49.7) 64.5 (4.7, 124.2) 129.0 (9.5,248.4) Linear b = 1.2199; x = 129.0 0.6 Dry shoot lnd 13.6 (0, 32.5) 22,7 (2.0, 43.4) 37.8 (15.4, 603) Logistic b = 2.148; t = 0.2596; x = 37.8 0.88 Popl 21.3 (5.2, 37.4) 53.3 (130, 93.5) 106.6 (26.0,187.1) Linear b = 0.2862; x = 106.6 0.16 Pop2 nc nc 54.8 (0, 136.8) Hormetic b = 0.9117; t = 0.1119; 0.71 h = -0.0759; x = 54.8 Coml 26.8 (0, 101.5) 45.1 (0, 128.5) 75.9 (0, 168.2) Logistic b =2.1099; t = 0.1317; x = 75.9 0.97 Com2 23.4 (63 40.5) 58.4 (15.7,101.2) 116.9 (31.3, 202.5) Linear b = 0.1899; x = 116.9 0.65

- 11 -:.

100 150 300

50 3:50

250 200 Day 14 - M. 

### socetu Day 14

- E. canadensis



# 8 2()

O"'-------.---.,..--...---I----...---'----r----..------.---.,..---r-----'-O 40 80 60 120**.~** 100 o Ii? U W :0- ro 1jl :;!:

ind Fopl Pcp2 Coml Com2 ind Popl Pop2 Coml Com2

120 Day 28

- M. sotcetu Day 28 - E. canadensis

40 60 160,..--------=---=-=---=----:---

.....----------------,- 160 140 140 120 -J ll00 l/'l 80 o w >- -el

Ind Pcpl Pop2 cernt Cem2 100 Popl Pop2 Cem1 Com2 Day 42

- M. spicalu Day 42 - E. canadensis

40 60 100 120

Ind Popl Pop2 Com1 Com2 ind Popl Pcp2 Coml Com2 Figure 2. Box plots of effective concentrations ofatrazine resulting in 50% differences in macrophyte growth compared to controls (ECso ) . Boxes range from 

## zs" to 75th percentiles, whiskers from 10th to 90th percentiles, and solid line within the box represents the median. Ind =individually grown plants; Popl =low-density population; Pop2 = high density population; Coml = low density community; Com2 =high density community. The growth endpoint (wet or dry roots or shoots) plotted is not provided. The study reviewer assumes that each box plot represents data from all biomass endpoints. (study figure 2)



### - 12 -Table 4. Relative growth rates ofE. canadensis and M. spicatum grown in control microcosms. Values are mean (n=3) ± standard deviation. P-values are from results ofone-way ANOVA. Post-hoc pairwise comparisons with Tukey's test were performed for significant differences as determined by ANOVA (p < 0.05). (study table 4) Low-density High-density Low-density High-density

Endpoint Individual population population community community p-Value E. canadensis Day 14 RGRwet 0.060 ± 0.057 0.082 ± 0.008 0.061 ± 0.021 0.040 ± 0.036 0.025 ± 0.013 0.301 RGRdry 0.041 ± 0.023 0.033 ± 0.017 0.027 ± 0.022 0.017 ± 0.016 0.014 ± 0.011 0.414 Day 28 RGRwet 0.049 ± 0.016 0.088±0.017 * 0.085 ± 0.005 * 0.019 ± 0.015 0.047 ± 0.011 <0.001 RGRdry 0.033 ± 0.036 0.066 ± 0.023 0.069 ± 0.012 0.014 ± 0.013 0.047 ± 0.006 0.029 Day 42 RGRwet 0.029 ± 0.025 0.077 ± 0.015 * 0.066 ± 0.002 * 0.040 ± 0.014 0.040 ± 0.008 0.014 RGRdry 0.034 ± 0.031 0.069 ± 0.015 0.066 ± 0.003 0.041 ± 0.018 0.045 ± 0.008 0.14 M spicatum Day 14 RGRwet 0.126 ± 0.009 0.132±0.018 0.132 ± 0.003 0.141 ± 0.023 0.120±0.022 0.619 RGRdry 0.112 ± 0.013 0.118 ± 0.020 0.120 ± 0.003 0.129 ± 0.022 0.111 ± 0.018 0.692 Day 28 RGRwet 0.096 ± 0.005 0.063 ± 0.038 0.079 ± 0.027 0.084 ± 0.028 0.061 ± 0.016 0.452 RGRdry 0.102 ± 0.006 0.067 ± 0.044 0.078 ± 0.033 0.094 ± 0.030 0.079 ± 0.033 0.683 Day 42 RGRwet 0.047 ± 0.021 0.048 ± 0.024 0.045 ± 0.016 0.023 ± 0.014 0.041 ± 0.026 0.596 RGRdry ** 0.067 ± 0.006 0.053 ± 0.023 0.050 ± 0.020 0.037 ± 0.018 0.052 ± 0.026 0.518 *Significant (p<0.05) difference from individually grown plants (pairwise comparison) using Tukey's test. **Data that did not meet the assumption ofequal variance were LN transformed ..

- 13 -Table 5. Main and interactive effects of atrazine and planting design (Pdesign) on biomass endpoints for E. canadensis and M. spicatum, as determined by a mixed-model two-way ANOVA. Main effects Interaction Dataset Atrazine Pdesign Atrazine*Pdesign p-value p-value p-value E. canadensis Day 14 Wet root 0.0028* 0.3139 0.8018 Wet shoot 0.0008* 0.0099* 0.9771 Total wet 0.0005* 0.0167* 0.9846 Dry root 0.0132* 0.0401* 0.3133 Dry shoot <.0001 * 0.0074* 0.8526 Total dry 0.0299* 0.0299 0.9173 Day 28 Wetroot' 0.0005* 0.9502 0.3693 Wet shoot <.0001 * <.0001 * 0.0014* Total wet <.0001 * <.0001 * 0.0042* Dry root' 0.0003* 0.8053 0.49 Dry shoot <.0001 * 0.5531 0.2189 Total dry <.0001 * 0.6569 0.2669 Day 42 Wet root' <.0001 * <.0001* 0.0009* Wet shoot 0.0004* <.0001* 0.0001* Total wet 0.0003* <.0001* 0.0002* Dry root' 0.0003* 0.0020* 0.0135* Dry shoot 0.0002* <.0001 * 0.0174* Total dry 0.0002* <.0001 * 0.0144* M spicatum Day 14

Day 28

Day 42 Wet root <.0001 * 0.0010* 0.9694 Wet shoot <.0001 * 0.0001 * 0.0113* Total wet <.0001 * 0.0482* 0.5595 Dry root <.0001 * 0.0011* 0.9326 Dry shoot <.0001 * 0.0907 0.083 Total dry <.0001 * 0.0654 0.3964 Wet root 0.0003* <.0001* 0.0817 Wet shoot 0.0029* 0.219 0.3389 Total wet 0.0006* 0.0582 0.3159 Dry root' 0.0110* 0.0019* 0.5266 Dry shoot 0.0007* 0.6833 0.4465 Total dry 0.0016* 0.2752 0.4536 Wetroot' 0.0001* 0.0187* 0.7913 Wet shoot 0.0138* 0.0048* 0.181 Total wet 0.0032* 0.0003* 0.2286 Dry root' 0.0001 * 0.0187* 0.7913 Dry shoot 0.0001* 0.1855 0.1697 Total dry 0.0006* 0.0073* 0.6759

a Dataset does not meet ANOVA assumptions ofresidual normality and homogeneous variance * Statistically significant (p<0.05)



### - 14 -

### Data Summary Table Time Weighted Did Nominal Average Recovery Magnitude of Atrazine Day of Study Atrazine Occur-if Effect Effectrelative to Concentration Effect Concentration so, when Comments controls (Ilg/ L) Occurred from Day Oto (see When Effect comment)? Occurred

No effect 251lg/L Not applicable Not applicable Not Effect magnitudes applicable estimated from figure 1. No effect 50llgiL Not applicable Not applicable Not applicable No statistics were 104.0±5.6 provided 35% decrease 100llgiL Day 1 ug/L' No comparing treatment and control at each sampling date. Decrease in However, the study dissolved authors compared the control and oxygen treatment microcosm DO measurements 50% decrease 250 flglL Day 1 247.5±12.2 No averaged over the IlgIL' entire study. For that comparison, there was a significant difference (p<0.05) for the 100 and 250 IlgILtreatment levels.
1 TWA calculated by study authors for the entire 42-day expenmental penod.



### - 15 -

### Reviewer Comments: 

### Data analysis and statistical procedures are, for the most part, described completely and are appropriate for the aims ofthe study. Exceptions were minor, and include not enough informationprovided on the "slice" command or on orthogonal contrastprocedures, and lackof information on which biomass endpoint was used for the ECso

### box plots.
In general, effects at each tested atrazine concentration could not be determined due to the way in which data and analyses were presented. For instance, for the ANOVA analysis presented in Table 5, the effects ofatrazine were analyzed without regard to atrazine concentration (i.e., all treatment levels were combined). Additionally, biomass data were not presented so effects at each tested atrazine concentrationlevel could not be determined by the reviewer. Regression results and effectconcentrations are provided in detail, but the ECxsofthe biomass endpoints were highly variable, thus cannot be considered reliable for establishing effect concentrations. Specifically, there was great overlap among confidence intervals for ECI0, EC25, and EC50. Furthermore, in many cases the ECx was not bounded by the treatment concentrationrange and the lower bound 95% confidence interval was 0 ug/L.
Althoughthe microcosms were multispecies, endpoints except dissolved oxygen were presented for effects on individual macrophyte species ratherthan community-level effects.

Dissolved oxygen measurements were a function ofphotosynthesis by all macrophytes in a microcosm. In addition, any phytoplankton in the microcosms would have contributedto photosynthesis as well. The study authors do not report information about phytoplankton in the microcosms, however it is likelythatthey were present given that the microcosms were outdoors and were filled with water from an irrigation pond. Therefore, effects ofatrazine on both macrophytes and phytoplankton would have contributedto the observed effects on dissolved oxygen.

Several experimental factors discussed by the study authors may have confounded the interpretation ofatrazine as the causal stressor or limit the ability to detect effects ofatrazine. For instance, macrophyte growth in the control microcosms was lower than expected by the study authors and led to reduced biomass accumulation. They suggested a number offactors that may have contributed to the low growth. As a consequence, low biomass accumulation likely limited the ability to detect effects ofatrazine on growth-based endpoints (root and shoot weight). Other issues were herbivore grazing ofsome microcosms but not others and no growth in the 25 ug/L microcosms.

- 16 -

### Description ofUse 

### in Document: Qualitative (except effective concentration data is invalid due to high variability, single species effects, and factors confounding interpretation ofatrazine as the causal stressor)



### Rationale for Use: Microcosm experiments contribute to the weight ofevidence regarding effects ofatrazine on aquatic plant communities.



### Limitations ofStudy: Data and analyses were not presented in a way in which effects from each atrazine treatment concentration couldbe determined. Biomass data for each atrazine treatment level was not presented (regressionresults are provided instead). There was high variability in the ECx values. Several factors may have limited the ability to detect effects of atrazine as the causal stressor: selective herbivory, no growth in the 25 ug/L atrazine treatment, and overall low growth in all microcosms. Except for dissolved oxygen; endpoints were presented for effects on individual macrophyte species ratherthan community-level effects. Experimental design and presentation ofthe results focused on planting system design effects.


### Primary Reviewer: SaraH. Hendrix, M.S., Subcontracting Scientist, Cambridge Environmental Inc. 

### Secondary Reviewer: Michael Lowit, Ph.D., Ecologist, EPA 

# 1t7,t:tJ**~~** Tertiary Reviewer: Brian Anderson, Biologist, EPA

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