### Open Literature Review Summary

ChemicalName: 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: Determinepotential effects ofatrazine on an aquatic community. Endpoints from this study contributeto the weight-of-evidenceregarding 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 inpopulation and community-level assemblages in 

### large outdoormicrocosms.


### Summary ofStudy Findings

Methods: The study used 15 outdoormicrocosms located atthe University ofGuelph Microcosm Facility atthe Guelph Turfgrass Institute, Ontario, Canada. Eachmicrocosm 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 sunkinto the ground so the tops were flush with ground level. Waterwas supplied from an adjacent spring-fed irrigationpond (62 x 62 x 4 m deep). Thirty-five plastic propagationtrays (52 x 25 x 7 cm) filled with an amended sedimentmix were addedto the bottom ofeachmicrocosm. The sedimentwas a 1: 1:1 mixture ofsand, loam, and organic matter and covered approximately 38% ofthe floor ofeachmicrocosm. Sediment carbon analysis was determined by combustionusing a Leco CarbonAnalyzer (LECO SC444). Total carboncontent was 7.0%, inorganic carbon was 1.0%, and organic carbon was 6.0%.

- 1 - 

# 1II1II1III 2087808

### Waterwas circulated betweenthe irrigationpond and microcosms at arate of 12,000 Lperday for 25 days priorto atrazine treatmentto 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 initializationtime, and were notused for effects assessment. Circulation endedtwo days priorto treatment (July 16, 2006). The macrophytes used for effects assessment (see below) were added to the microcosms onJuly 17,2006, one day priorto treatment. Treatmentoccurred 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.

Forindividual 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 plantwas grown in an individual 164 mL cone-tainer (aplastic planting tube, 21 cm long with 3.8 cm internal diameter, bottomhole plugged with cottonpad) 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 irrigationpond waterto allow settling. Apical shoots, without side roots or shoots, ofeachplantwere cutto 5 cmpriorto planting. Each shootwas planted 2 cm deep and surrounded by 0.5-1 cm ofTurface (Applied Industrial Materials, Buffalo Grove, Illinois) to secure it. Sixplants per species were placed evenly spaced in eachtray. One tray was placed in the center ofeach microcosm to provide maximum sunlightandreduce edge effects (total number oftrays permicrocosm containing individually pottedplants was not stated). Onthe 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 permicrocosm were sampled atrandom.

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

### M spicatum and E. 

### canadensis were grown inplastic sterilite containers (34.9 x 20.6 x 32.1 cm). Containers were filled with sediment andprepared for planting like the cone-tainers. Monocultures were grown attwo 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 mixedplanting designs were also grown attwo densities: low density was nine plants per species (18 plants total in a 6x3 configuration) and high density was 18 plants per species (configurationnotprovided). Species type was alternated in eachrow of plants. A total of18 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 waterfrom theirrespective microcosm and immediately measured for biomass (wet and dry) ofbothroots and shoots. Chlorophyll 

### a was measuredby ethanol extraction with an Ultraspec 3100

### pro UVNisible Spectrophotometerusing methods described byNusch (1980). Biomasses ofassemblages of plants were normalizedto aper-plantbasis to allow comparison with individually grownplants.

Microcosms were treated with either 0 (controls), 25,50, 100, or 250 Ilg/L atrazine (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 waterquality determination were collected using ametal depth-integrated water column sampler. A composite sample was created from at least four randomly selected locations in each microcosm, and stored at4°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 minimumtemperatures were measured daily Mondaythrough Friday at a water depth of20 cm. Pointmeasurements oftemperatures and DO weremade daily at 50 cm depth with a HANNA HI-9143 meter. DO was notmeasured 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 standardmethods andkits 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 atmidday on clear sunny days. Readings were normalized bytaking them atthe surface ofeach microcosm, atthe surface in a glassjar, and at a depth of60 cm in a glassjar.

Atrazine concentrations were analyzedby enzyme linked immunosorbent assay (ELISA), using the Abraxis Atrazine Assay Kit. Samples were prepared for analysis by bringing themto 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 Ilg/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 eachtreatment level for the three replicates were calculated.

For each monitored waterquality variable and PAR, a one-way analysis ofvariance (ANOVA) was performedto identify significant differences among treatments using SigmaStat 3.5. ANOVA assumptions were tested withthe Kolmogorov-Smimov testfor 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 inbiomass 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 viaregression analysis: mean biomass data on each sampling day was subtracted from mean biomass datafrom 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 andW2are plantweights attime tl andt2. RGRs were compared for all planting designs (individual, monoculture athigh and low density, mixed culture athigh 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 forpairwise comparisons when significance was found.

Interactions between atrazine concentration andplanting design factors onbiomass 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 transformedby natural log or square root. When significantinteractions 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 oftestdesigns (e.g. individual vs. population) were compared using orthogonal contrasts (procedure notfurther 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.

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### Average values for water quality parameters over all sampling days inthe 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, exceptfor minimumtemperature and DO. Minimum temperature post-treatment, though significantly different intreatments, showed no concentration-response trend. Dissolved oxygen was significantly decreased atthe two highest treatment levels comparedto controls. Figure 1 

### shows trends inDO at eachtreatment level over the experiment.

Forplanttoxicity, nonlinearregression analysis showed significantconcentration-response relationships for over 90% ofthe sampling times, planting designs, andbiomass endpoints examined, and EC lO, 

### EC2S, and ECso were calculated inmost cases (Table 

### 2 and Table 

### 3). Effective concentration (ECx) represented atreatmentrelated decrease in all endpoints exceptfor chlorophyll 

### a in individually grownplants. Forindividually grown M. 

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

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

### EC2 s, and ECso represent 10%,25%, and 50% increases forthese endpoints only. Box plots ofECso estimates are shown in Figure 

### 2. The study authors do not state whichbiomass endpoints were plotted, however, the study reviewer assumes thatdatafrom all biomass endpoints were combined into eachboxplot.

Relative growthrates (RGR) ofM. 

### spicatum and E. 

### canadensis in control microcosms are presented in Table 

### 4. RGRs were similaramong the differentplanting designs exceptforthe significantdifference (p<0.05) in E. 

### canadensis on days 28 and 42. Pairwise comparison showedthatthe RGRwet 

### ofindividually grown E. 

### canadensis was significantly lower (p<0.05) thanthose ofplants growninhigh and low density model populations. RGR data is notpresented for treatedmicrocosms.

Atrazinehad a significant (p<0.05) effectonplantwet and dry biomass at all time points (Table 

### 5). This analysis did not examine atrazine effects from individualtreatment concentrations. Plantbiomass was significantly affected byplanting design in about 60% ofthe endpoints (plant/date/biomass). Generally, there were no significantinteractions between atrazine concentration andplanting design on wetor dry biomass. The exceptions were day 14 wet shoot biomass of

### M spicatum, wet shoot andtotal wetbiomass ofE. 

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

### canadensis on day 42. The "slice" command was appliedto assess how atrazine effects varied overplanting treatments. The study authors reportedthatthe biomass of individually grown E. 

### canadensis was not significantly differentin each atrazine treatment; however, the biomass ofplants grown in assemblages was significantly different ineach atrazine treatment. The study authors also reportedthat orthogonal contrasts comparing mean biomass measures betweenplanting designs showed few significantdifferences betweenplanting designs, and no consistenttrends across biomass endpoints forplanting systems that showed statistically significantdifferent means. No further information or datawas providedby the study authors regarding the 'slice" command and orthogonal contrastresults.

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### The study authors mentionthat individually grown E. 

### canadensis were grazedupon in some control microcosms. They do not indicate ifgrazing occurred in any ofthe treatment microcosms. Plants did not grow at all inthe 25 Ilg/L atrazine treated microcosms. The study authors suggestthatthe lack ofgrowth may have been due to the selection oflow-qualityplants orthe chance occurrence ofan herbivore. Due to these issues, the study authors suggestthey may have used insufficientreplication. No further informationis provided. They also note that relative growthrates ofthe macrophytes were significantly lowerthan those ofthe same species from previous investigations conducted atthe same experimental site over similarexperimental 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 Minimumtemperature Maximumtemperature 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 differentfrom 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 treatmentwith various levels ofatrazine over the 42-day exposure duration. (study figure 1)



### - 7 -Table 2. ForElodea canadensis, effective concentrations (llglL) ofatrazine 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 r2 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 Wetroot 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 Wetroot 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 (72, 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 Wetroot 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, 1844) 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 Ind 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

-:.

100 150 300 250 200 3:50

50 

# 8
O"'-------.---.,..---.---I----.----'----r---....------.---.,..---r-----'-O 40 80 160 .,-----------

__

### -----,-----------------r 400 Day 14

- 

### E. canadensis Day 14

- 

### M. spicaflJ 140 120**.~** 100 o Ii? U W :0- ro 1jl :;!:

,rod Fopl Pcp2 Coml Com2 'rod Popl Pop2 Coml Com2

120 100 BO
60 40 20 I=:=J t::::::J 20

O.l...----.---.---..,......--.___--.---..l----r----r----.-----r----.---LO 40 60 160,..--------=---=-=---=----:---

.....----------------,- 160 Day 28

- E. canadensis Day 28

- M. spicatu 140 140 120 -J ll00 l/'l 80 u w >- 

### -el

Ind Popl Pop2 Com1 Cem2 100 Pop1 Pap2 Cem1 Com2

40 120
100 140,.----------:=------:-=--=-----:---:-r------------------,- 200 Day 42

- E. canadensis Day 42

- M. spicalu lBO
160 140 120 100 BO 60 40 20**0.l...----.---.---...--_.___----r---...I.---.,..--~--.___-__r--~----l0** Ind Pop1 Pop2 Com! Com2 jrod Papl Pop2 Coml Cam2 

### Figure 2. Box plots ofeffective concentrations ofatrazine resulting in 50% differences in macrophyte growth compared to controls (ECso). 

### Boxes range from 25th 

### 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 testwere 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. 

### ** Datathat did notmeetthe assumption ofequal variance were LN transformed

..



### - 13 -Table 5. Main and interactive effects ofatrazine 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 Wetroot 0.0028* 0.3139 0.8018 Wet shoot 0.0008* 0.0099* 0.9771 Total wet 0.0005* 0.0167* 0.9846 Dryroot 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 Wetroot' <.0001 * <.0001 * 0.0009* Wet shoot 0.0004* <.0001 * 0.0001* Total wet 0.0003* <.0001 * 0.0002* Dryroot' 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 Wetroot <.0001 * 0.0010* 0.9694 Wet shoot <.0001 * 0.0001 * 0.0113* Total wet <.0001 * 0.0482* 0.5595 Dryroot <.0001 * 0.0011 * 0.9326 Dry shoot <.0001 * 0.0907 0.083 Total dry <.0001 * 0.0654 0.3964 Wetroot 0.0003* <.0001* 0.0817 Wet shoot 0.0029* 0.219 0.3389 Total wet 0.0006* 0.0582 0.3159 Dryroot' 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

• Dataset does notmeet 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 Effectmagnitudes 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 IlglL' No comparing treatment and control at each sampling date. Decrease in However, the study dissolved authors compared the control and oxygen treatment microcosmDO measurements 50% decrease 250 flglL Day 1 247.5±12.2 No averaged overthe IlgIL' entire study. For that comparison, there was a significant difference (p<0.05) for the 100 and 250 IlgIL treatment levels.
1 TWA calculated by study authors for the entrre 42-day expenmentalpenod.



### - 15

-

### Reviewer Comments: 

### Data analysis and statisticalprocedures are, for the mostpart, described completely and are appropriate forthe aims ofthe study. Exceptions were minor, and include notenough informationprovided onthe "slice" command oron orthogonal contrastprocedures, and lack of information on which biomass endpointwas used forthe ECso 

### boxplots.

In general, effects at eachtested atrazine concentration couldnotbe determined due to the way in which data and analyses were presented. Forinstance, forthe ANOVA analysis presentedin Table 5, the effects ofatrazine were analyzed withoutregard to atrazine concentration (i.e., all treatment levels were combined). Additionally, biomass datawere notpresented so effects at eachtested atrazine concentrationlevel could notbe determinedby the reviewer. Regression results and effectconcentrations are provided in detail, butthe ECxs ofthe biomass endpoints were highly variable, thus cannotbe consideredreliable for establishing effectconcentrations. Specifically, there was great overlap among confidence intervals for ECI0, EC25, and EC50. Furthermore, inmany cases the ECx was notboundedby the treatment concentrationrange and the lowerbound 95% confidence interval was 0**~glL.** 

### Althoughthe microcosms were multispecies, endpoints exceptdissolved oxygen were presented for effects on individual macrophyte species ratherthan community-level effects.

Dissolved oxygenmeasurements were a function ofphotosynthesis by all macrophytes in a microcosm. In addition, any phytoplankton inthe microcosms wouldhave contributedto photosynthesis as well. The study authors do notreport information aboutphytoplankton inthe microcosms, howeveritis likelythatthey were present giventhatthe microcosms were outdoors and were filled with waterfrom 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 orlimitthe ability to detect effects ofatrazine. Forinstance, macrophyte growth in the control microcosms was lowerthan expectedby the study authors and led to reduced biomass accumulation. They suggested anumber offactors that may have contributed to the low growth. As a consequence, low biomass accumulation likely limited the abilityto detect effects ofatrazine on growth-based endpoints (root and shoot weight). Otherissues were herbivore grazing ofsome microcosms butnot others and no growth inthe 25**~g/L** 

### microcosms.

- 16

-

### Description ofUse 

### in Document: Qualitative (excepteffective concentration datais 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: Dataand analyses were notpresented in a way in which effects from each atrazine treatment concentration couldbe determined. Biomass datafor each atrazine treatment level was notpresented (regressionresults are provided instead). There was high variability inthe ECx values. Several factors may have limitedthe ability to detect effects of atrazine as the causal stressor: selective herbivory, no growthinthe 25 /lg/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 onplanting 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: BrianAnderson, Biologist, EPA

# ~:Ir r

# /1

# ;jL--

- 17

-