Open Literature Review Summary 

Chemical Name: Atrazine

CAS No: 1912-24-9

PC Code: 080803

ECOTOX Record Number and Citation: 

Andrus, J.M., D. Winter, M. Scanlan, S. Sullivan, W. Bollman, J.B. Waggoner, A.J. Hosmer, R.A. 

Brain. 2015. Spatial and temporal variation of algal assemblages in six Midwest agricultural 

streams having varying levels of atrazine and other physiochemical attributes. Science of the 

Total Environment 505: 65-89.

Date of Review: February 23, 2016

- This research article describes the seasonal and environmental factors that were 

found to be potentially influencing changes in aquatic plant communities that have 

recorded atrazine exposures. 

- The study sites were selected from a few of the AEEMP monitoring program and 

continued with watersheds sampled in the authors 2013 publication (Andrus et al.

2013; IA-03, IL-10, MO-05) while adding three additional sites from the program (IL17, MO-07N, HO-05). Community sampling sites were selected at one location at the 

point closest to the AEEMP monitoring program data collection location. 

Table 1: Peak and 60-day maximum running average concentrations (μg/L) of measured 

atrazine concentrations reported in the AEEMP monitoring program (EPA calculated averages). 

Shaded cells indicate exceedances of the CELOC (60-day maximum average = 3.4 μg/L) 

Year IA-03 IL-10 IL-17 MO-05 MO-07N OH-05 

Peak 60-

day 

Avg 

Peak 60-

day 

Avg 

Peak 60-

day 

Avg 

Peak 60-

day 

Avg 

Peak 60-

day 

Avg 

Peak 60-

day 

Avg 

2010 50.6 10.5 5.0 0.4 36.7 5.7 84.2 12.9 92.5 20.2 11.0 2.0 

2011 39.8 4.9 11.5 1.4 228.2 17.2 70.5 6.2 90.9 14.6 30.6 1.4 

2012 17.8 2.0 5.4 0.7 39.4 6.3 14.0 4.0 41.1 11.9 14.8 1.9 

- The study collected data relevant to assessing the diversity and community 

composition, as well as abiotic factors that may contribute to changes in the 

community. 

- The study adequately sampled for abiotic environmental factors. 

- The algal community sampling was primarily done in a robust manner given the study 

objectives, with the following concerns: 
o There was only one replicate included within each site per collection, as opposed 

to the Andrus etal 2013 study which included 3 samples per collection. It is 

unclear if the variablity across sites chosen for the 2011 collection year would be 

consistent with the 2012 collection year and across the newly added sites. The 

impact of this reduction in samples is unknown. 

o Different volumes of water were taken to evaluate phytoplankton samples, thus 

it is unclear how changes in the phytoplankton diversity, AFDM, chl-a, and 

community composition may be impacted by the different sample sizes. 

o Periphyton collection using periphytometers submerged at a depth of 5 cm may 

not reflect changes in the stream bed periphyton communities. 

o It was not reported how often or in which localities the periphytometers were 

found above the water surface (dried out), damaged, or incorrectly positioned. 

The authors briefly mention the sue of the reserved periphytometer in those but 

it is not clear in the report how often the reserved periphytometers were relied 

upon or if they showed different communities from the primary periphytometers 

at the same site locations. 

o It is unclear how selection of periphyton samples for chl-a, AFDM and taxonomic 

identification was made to avoid potential sampling bias. 

o Chl-a levels for phytoplankton were below detection limits. The report indicates 

that instream optical chlorophyll probes were relied upon for two streams, but 

these were not identified, and impacts on comparisons between the glass fiber 

filters and the optical probes were not provided to evaluate potential sampling 

method differences. 

o Different water volumes were used to evaluate the taxonomic phytoplankton 

composition of the non-diatom (10 ml subsample) and diatoms (250 ml 

subsample) components. Implications of this difference are unknown. 

Author Conclusions 

- Abundance 

o Periphytic communities were dominated by diatoms 

 Cyanophyta, green algae and euglenophyta generally increased over the 

sampling period. 

 Diatoms remained dominant throughout the sampling period 

o Phytoplankton 

 Diatoms were dominant in the spring 

 Cyanophyta increased in May and June, 

 Green algae and euglenophyta gained dominance in the summer 

o Significant differences in univariate diversity and abundance metrics, as well as 

diatom indices and periphyton and phytoplankton assemblages between sites 

and temporally within sites 

 Most influential gradient in the CCAs was the stream site. 

 Nutrient availability, pH, ion and mineral content, hydrology, 

temperature, land cover, geology and habitat qualtiy contributed to the 
variation associated with the stream sites and accounted for large 

proportions of the assemblage structure in the CCAs 

 Year of sampling explained a large proportion of the assemblage 

structure in the CCAs, and was attributed to the environmental factors 

described above. 

 In this study, variables that exhibited substantial seasonal variation 

included nitrogen, phosphorus, TSS, depth, flow, water temperature, 

wind speed and atrazine. 

o The average algal taxa richness and evenness values for sites monitored in this 

study were generally closely in line with those from the NAWQA dataset from 

the same ecoregion. 

 diatom taxa richness was much greater than NDA taxa richness in both 

periphyton and phytoplankton (approximately 2–3 times higher). 

 Periphytic and planktonic assemblages taken from AEMP sites typically 

had similar or slightly greater taxa richness than the corresponding 

NAWQA sites. 

 At IL-17, MO-05, and MO-07N, periphyton taxa richness was substantially 

higher than mean values for NAWQA sites in the same ecoregions (no 

comparisons were available for phytoplankton assemblages at these 

sites). 

 However, planktonic diatom assemblages at the IL-10 and OH-05 sites 

had much higher richness and evenness than comparable NAWQA sites. 

 Algal community evenness at the sites monitored in this study was very 

similar to those at the NAWQA sites, again with the exception of 

planktonic diatom assemblages at the IL-10 and OH-05 sites, which, 

although similar to other evenness values in this study, were substantially 

more even than communities at NAWQA sites. 

 These data suggest that assemblages from the sites monitored in this 

study are reasonably typical of local algal communities, although the 

number of NAWQA samples in each ecoregion varied and therefore the 

data may be representative of streams in each ecoregion to differing 

degrees. 

- Seasonality 

o The algal communities are changing with the seasons, and these changes are 

similar across the study sites 

o Stream flow, NO2+NO3, total phosphorus, solar radiation, pH, wind speed, 

alkalinity and hardness, and atrazine concentration showed substantial vector 

projection in the direction of the chronology CA plots for all sites. 

o Attribute primary changes in community changes to seasonality and flow. 

- Atrazine Effects 

o the influence of the days since ≥30 μg/L atrazine variable was higher in models of 

both algal communities than of the days since ≥10 μg/L (the set of events ≥ 10 

μg/L also including events ≥ 30 μg/L), and both were of greater influence than 
the daily composite atrazine concentration (periphyton: 0.67% and 0.56% vs. 

0.33%; phytoplankton: 0.84% and 0.63% vs.0.54%). That the ≥30 μg/L threshold 

is more influential than the ≥10 μg/L threshold indicates that the set of pulses ≥

10 μg/L but <30 ppb are considerably less influential to the community structure. 

Additionally, the collective inertia explained by the entire group of atrazine 

variables was low (periphyton: 1.47%; phytoplankton: 2.16%) and was the least 

of all variable groups [similar results for TSS and nutrients]

o The two variable groups explaining the most unique inertia in both periphyton 

and phytoplankton assemblages were water chemistry and hydroclimate 

(periphyton: 5.28% and 6.01%; phytoplankton: 7.46% and 6.19%) 

o As a group, the atrazine variables explain the least unique inertia. This finding is 

consistent both with the first year of data in this study, which suggested that 

other environmental variables have a greater effect on community structure 

relative to atrazine (Andrus et al., 2013), and with other studies that found that 

seasonal or other environmental changes had a larger role in structuring algal 

community composition than did concentrations of atrazine 

o the algal communities at the sites monitored in this study may be more tolerant 

in general to anthropogenic inputs. It could therefore be expected that diatom 

dominated communities such as those in this study would be less sensitive 

overall to atrazine. 

o The mean Pollution Index (where Most Pollution Sensitive species have a score 

of 1 and Most Pollution Tolerant species have a score of 3) at our sites reflect an 

overall moderate to high pollution tolerance (IA-03: 1.83; IL-10: 2.15; IL-17: 1.98; 

MO-05: 1.79; MO-07 N: 1.89; OH-05: 2.08). We would therefore expect atrazine 

concentrations to have less of an observable influence on community structure 

at the monitored sites as all sites had communities generally tolerant to 

anthropogenic disturbance. 

o Both the periphyton and phytoplankton models suggest that community shifts 

abate with greater time elapsed since an atrazine perturbation. 

o Models of algal univariate metrics and assemblages show several consistent 

patterns. 

 the inclusion of parameters with seasonal dynamics in models reflects 

algal community succession and known seasonal abundance patterns. 

 Geographic variables are also prevalent in all models, and imply 

landscape-scale controls on algal communities. Both scour effects from 

stochastic events and differences in hydrology between 2011 and 2012 

are visible in these models. Variation partitioning of these models show 

that, for diversity and abundance metrics, the amount of variation 

uniquely explained by individual variable groups was generally of the 

order shared variation > water chemistry > geography > hydroclimate > 

atrazine. 

 For CCA models of periphyton assemblages, this order was: shared 

variation > hydroclimate > water chemistry > geography > atrazine 
 For phytoplankton assemblage the order was: shared variation > water 

chemistry > hydroclimate > geography > atrazine. 

 Collectively, atrazine variables uniquely accounted for no more than 2.2% 

of inertia in assemblage models. 

 The uniquely explained variance or inertia of the days since ≥30 ppb 

atrazine variable in assemblage models was larger than that of other 

atrazine variables 

x This analysis is consistent with the pulsatile behavior of atrazine 

exposure, where atrazine variables associated with peaks (e.g. 

days since ≥30 ppb)were of considerably greater consequence to 

algal community structure than variables representing daily or 

longer term exposure trends (daily composite and site average 

atrazine concentrations), implying a transitory nature (i.e. 

recovery of some form) of community changes potentially 

associated with atrazine 

 In all models, substantial variation or inertia was shared between variable 

groups, suggesting that considerable ambiguity exists in determining the 

effects of environment on algal communities in these systems. 

Description of Use in Document (QUAL, QUAN, INV): QUAL 

Rationale for Use: The study contributes to the understanding of aquatic plant community 

composition and seasonal dynamics within streams exposed to atrazine and other agricultural 

and anthropogenic stressors. 

Limitations: The primary limitation in this study is the lack of a set of reference streams which 

have had limited or no atrazine exposure. The streams have peak values that reach toxic levels 

for individual species based on laboratory testing, and 60-day average concentrations for IA-03, 

IL-17, MO-05, and MO-07 exceed the 2015 CELOC of 3 ug/L. However, these exceedances of 

the CELOC represent a 50% chance of an effect on the communities, so not seeing a strong and 

direct atrazine influence in the study results is not unanticipated, especially given the prior 

exposure history and anthropogenic impacts expected in these streams. 

Primary Reviewer: Frank T. Farruggia Ph.D., EPA/OCSPP/OPP/EFED/ERB3 

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 08:59:55 -04'00'