The Relative Sensitivity of Macrophyte and Algal Species ......Macrophyte toxicity data were compiled from open literature and from confidential test reports provided by participating

The Relative Sensitivity of Macrophyte and Algal Species to Herbicides and Fungicides: An Analysis Using Species Sensitivity Distributions

Jeffrey M. Giddings, Ph.D. Compliance Services International

Rochester, Massachusetts, USA

for the Species Sensitivity Distribution Working Group (SSD WG), functioning under the umbrella of the Aquatic Macrophyte Ecotoxicology Group (AMEG)

Society of Environmental Toxicology and Chemistry (SETAC)

September 30, 2011

CSI Report No. 11702

SSD Analysis of Macrophyte Sensitivity to Herbicides and Fungicides p. 2

Compliance Services International Report No. 11702

Acknowledgments

This project was initiated under the sponsorship of the Society of Environmental Toxicology and Chemistry (SETAC) as an activity arising from the 2008 SETAC workshop on Aquatic Macrophyte Risk Assessment for Pesticides (AMRAP). AMRAP projects, including this one led by the Species Sensitivity Distribution (SSD) Working Group, were later incorporated into the activities of the SETAC Aquatic Macrophyte Ecotoxicology Group (AMEG). The SSD Working Group consists of Stefania Loutseti, Chair (DuPont); Gertie Arts (Alterra, Wageningen University and Research Centre); Heino Christl (APC); Jo Davies (Syngenta); Michael Dobbs (Bayer CropScience); Mark Hanson (U. Manitoba); Udo Hommen (Fraunhofer Institute for Molecular Biology and Applied Ecology); Joy Honegger (Monsanto); Phil Manson (Cheminova); Giovanna Meregalli (Dow AgroSciences); and Gabe Weyman (Makhteshim-Agan). Data were contributed by Alterra (through governmental funding by the Ministry of Economic Affairs, Agriculture and innovation), Bayer CropScience, Nina Cedergreen (U. Copenhagen, with support from the Danish Environmental Protection Agency), Cheminova, Dow AgroSciences, DuPont, Fraunhofer Institute, Makhteshim-Agan, Mark Hanson (U. Manitoba), Monsanto, and Syngenta. Funding for data analysis and reporting was provided by Bayer CropScience, Cheminova, Dow AgroSciences, DuPont, Makhteshim-Agan, Monsanto, and Syngenta. Jeffrey Wirtz (Compliance Services International) contributed to the compilation and evaluation of the data. Thomas Priester (Compliance Services International) assisted with development of the SSD calculation spreadsheet.

Disclaimer This report is the result of an activity arising from the 2008 Society of Environmental Toxicology and Chemistry (SETAC) workshop on Aquatic Macrophyte Risk Assessment for Pesticides (AMRAP). Projects originating from AMRAP, including this one led by the Species Sensitivity Distribution (SSD) Working Group, were later incorporated into the activities of the SETAC Aquatic Macrophyte Ecotoxicology Group (AMEG). This report presents the views of its authors, and is not necessarily endorsed by or representative of the policy or views of SETAC.



Table of Contents page

Acknowledgments .............................................................................................................................2 Disclaimer ..........................................................................................................................................2 Table of Contents ...............................................................................................................................3 List of Tables ......................................................................................................................................4 List of Figures .....................................................................................................................................4 1. Introduction: Background and Objectives .....................................................................................6 2. Data Compilation and Evaluation .................................................................................................7 3. SSD Analysis Methods ..................................................................................................................9

3.1 Overview of SSD Analysis ................................................................................................................. 9 3.2 Data Selection ................................................................................................................................ 10 3.3 Lognormal Regression .................................................................................................................... 11 3.4 Presentation of Results .................................................................................................................. 12

4. Results ....................................................................................................................................... 12 4.1 Chemical A ..................................................................................................................................... 12 4.2 Chemical B...................................................................................................................................... 15 4.3 Chemical C ...................................................................................................................................... 17 4.4 Chemical D1 ................................................................................................................................... 19 4.5 Chemical D2 ................................................................................................................................... 21 4.6 Chemical E1 .................................................................................................................................... 23 4.7 Chemical E2 .................................................................................................................................... 24 4.8 Chemical E3 .................................................................................................................................... 26 4.9 Chemical E4 .................................................................................................................................... 28 4.10 Chemical F1 ............................................................................................................................. 30 4.11 Chemical F2 ............................................................................................................................. 32 4.12 Chemical F3 ............................................................................................................................. 34 4.13 Chemical F4 ............................................................................................................................. 36 4.14 Chemical F5 ............................................................................................................................. 38

5. Discussion .................................................................................................................................. 40 5.1 Lemna gibba ................................................................................................................................... 40 5.2 Algae .............................................................................................................................................. 43 5.3 Myriophyllum spicatum ................................................................................................................. 45 5.4 Combined data for Lemna gibba, algae, and Myriophyllum spicatum .......................................... 48

6. Uncertainties ............................................................................................................................. 50 7. Conclusions and Recommendations............................................................................................ 52 8. References ................................................................................................................................. 54 Appendix A. AMRAP SSD database ................................................................................................... 55



List of Tables Table 1. Chemical A: Macrophyte and algal toxicity values used in the analysis. Algal data were not

used to construct the SSD. .................................................................................................................. 14 Table 2. Chemical B: Macrophyte and algal toxicity values used in the analysis. Algal data were not

used to construct the SSD. .................................................................................................................. 16 Table 3. Chemical C: Macrophyte and algal toxicity values used in the analysis. Algal data (other

than macroalgae) were not used to construct the SSD. ..................................................................... 18 Table 4. Chemical D1: Macrophyte and algal toxicity values used in the analysis. Algal data were not

used to construct the SSD. .................................................................................................................. 20 Table 5. Chemical D2: Macrophyte and algal toxicity values used in the analysis. Algal data were not

used to construct the SSD. .................................................................................................................. 22 Table 6. Chemical E1: Macrophyte and algal toxicity values used in the analysis. Algal data were not



used to construct the SSD. .................................................................................................................. 27 Table 9. Chemical E4: Macrophyte and algal toxicity values used in the analysis. Algal data (other

than macroalgae) were not used to construct the SSD. ..................................................................... 29 Table 10. Chemical F1: Macrophyte and algal toxicity values used in the analysis. Algal data were

not used to construct the SSD. ............................................................................................................ 31 Table 11. Chemical F2: Macrophyte and algal toxicity values used in the analysis. Algal data (other

than macroalgae) were not used to construct the SSD. ..................................................................... 33 Table 12. Chemical F3: Macrophyte and algal toxicity values used in the analysis. Algal data were

not used to construct the SSD. ............................................................................................................ 35 Table 13. Chemical F4: Macrophyte and algal toxicity values used in the analysis. Algal data were

not used to construct the SSD. ............................................................................................................ 37 Table 14. Chemical F5: Macrophyte and algal toxicity values used in the analysis. Algal data were

not used to construct the SSD. ............................................................................................................ 39 Table 15. Position of Lemna gibba in macrophyte SSDs. ............................................................................ 41 Table 16. Rank of Lemna gibba among Lemna species in sensitivity to herbicides and fungicides. .......... 41 Table 17. Sensitivity of the most sensitive of the FIFRA algal species relative to macrophyte SSDs. ........ 43 Table 18. Position of Myriophyllum spicatum in macrophyte SSDs. .......................................................... 45 Table 19. Rank of Myriophyllum spicatum among Myriophyllum species in sensitivity to herbicides

and fungicides. .................................................................................................................................... 46 Table 20. Sensitivity of the most sensitive species of Lemna gibba, FIFRA algae, or Myriophyllum

spicatum relative to macrophyte SSDs. .............................................................................................. 48

List of Figures page

Figure 1. Macrophyte SSD for Chemical A .................................................................................................. 13 Figure 2. Macrophyte SSD for Chemical B .................................................................................................. 15 Figure 3. Macrophyte SSD for Chemical C .................................................................................................. 17 Figure 4. Macrophyte SSD for Chemical D1 ................................................................................................ 19 Figure 5. Macrophyte SSD for Chemical D2 ................................................................................................ 21



Figure 6. Macrophyte SSD for Chemical E2 ................................................................................................ 24 Figure 7. Macrophyte SSD for Chemical E3 ................................................................................................ 26 Figure 8. Macrophyte SSD for Chemical E4 ................................................................................................ 28 Figure 9. Macrophyte SSD for Chemical F1 ................................................................................................. 30 Figure 10. Macrophyte SSD for Chemical F2. .............................................................................................. 32 Figure 11. Macrophyte SSD for Chemical F3. .............................................................................................. 34 Figure 12. Macrophyte SSD for Chemical F4. .............................................................................................. 36 Figure 13. Macrophyte SSD for Chemical F5. .............................................................................................. 38 Figure 14. Sensitivity of Lemna gibba relative to all macrophytes. ............................................................ 42 Figure 15. Sensitivity of standard algal species relative to all macrophytes. ............................................. 44 Figure 16. Sensitivity of Myriophyllum spicatum relative to all macrophytes. ........................................... 47 Figure 17. Sensitivity of the most sensitive species of Lemna gibba, FIFRA algae, and Myriophyllum

spicatum relative to all macrophytes. ................................................................................................. 49



1. Introduction: Background and Objectives In January 2008, the Society of Environmental Toxicology and Chemistry (SETAC) held a workshop on Aquatic Macrophyte Risk Assessment for Pesticides (AMRAP) in The Netherlands (Maltby et al. 2010). At the workshop, a Species Sensitivity Distribution (SSD) working group was formed to address questions about the sensitivity of standard surrogate aquatic plant test species relative to other aquatic macrophyte species. For various practical and historical reasons, the macrophytes most widely used in toxicity tests with pesticides are duckweeds of the genus Lemna. However, the sensitivity of Lemna spp. relative to other macrophyte species is largely unknown. The primary objective of the SSD working group was to investigate this question using available data on the toxicity of pesticides, especially herbicides, to aquatic macrophytes. The SSD working group selected Compliance Services International (CSI) to conduct the analysis. Seven companies whose scientists were members of the working group generously provided funding for the project. In 2009, a new SETAC advisory group, the Aquatic Macrophyte Ecotoxicology Group (AMEG), was formed to continue the efforts initiated at the AMRAP workshop. AMEG assumed responsibility for the AMRAP projects, including the SSD project. CSI collected macrophyte and algal toxicity data for nearly 60 herbicides and fungicides from the open literature and confidential company reports. CSI reviewed each data source according to predefined criteria, and only data from studies determined to meet the quality criteria were included in the analysis. (In a few cases data were taken from reliable secondary sources and data quality was not independently confirmed.) For 11 herbicides and 3 fungicides, useful toxicity data were found for at least 6 macrophyte species, which was considered the minimum needed for SSD analysis. Macrophyte SSDs for 13 of these chemicals were fitted using lognormal regression as described below; for one chemical, too many “greater-than” values prevented calculation of an SSD. The position of Lemna gibba in each SSD, as well as the sensitivity of the 4 algal test species required for pesticide registration in the United States under the Federal Insecticide, Fungicide and Rodenticide Act (FIFRA) relative to the macrophytes in each SSD, were determined. The position of a rooted macrophyte species, Myriophyllum spicatum, was also determined where data were available, because a standardized Myriophyllum test is currently under development through another AMRAP working group (Maltby et al. 2010; Dohmen 2010) and through a UBA ring-test (Maleztki and Kussatz 2011; Maleztki et al. 2011) and is recommended under the recent SANCO 11802-2010 draft regulation. To maintain the confidentiality of data provided by pesticide registrants, the identity of the herbicides and fungicides was revealed only to CSI and was not shared with the SSD workgroup. In this report, the chemicals are identified by codes that indicate the mode of action (MoA) of each chemical but not its specific identity. The MoAs included inhibition of amino acid synthesis (Chemical A), auxin simulation (Chemical B), inhibition of cell division or elongation (Chemical C), inhibition of fungal respiration (Chemicals D1 and D2), inhibition of multiple biosynthesis pathways (Chemicals E1, E2, E3, and E4), and inhibition of photosynthesis (Chemicals F1, F2, F3, F4, and F5). Because the six MoAs were not equally represented in the database and three were represented by only a single chemical, conclusions about the relationship between MoA and species sensitivity must be made with caution.



2. Data Compilation and Evaluation Macrophyte toxicity data were compiled from open literature and from confidential test reports provided by participating companies. Algal toxicity data were obtained from the OPP Pesticide Toxicity Database (EPA 2011b) and, in a few cases, from company reports. A few data points (mostly for algae) were obtained from other secondary sources such as the EPA ECOTOX database (EPA 2011a) and the European Commission pesticide review report. Each primary source was examined and evaluated based on a set of criteria established at the beginning of the project. Data used in the analysis were required to meet the following criteria:

Test organisms must be identified at least to genus.

Test substance must be identified. o Active ingredient (a.i.). o Form (technical-grade or specified formulation, including % a.i.).

Test substance must not include more than one active ingredient.

Negative and/or solvent controls (as appropriate) must be included.

Exposure medium must be reported.

Exposure duration must be specified.

Methods for measuring effects must be described.

Test concentration units must be unambiguous. o Active ingredient or whole formulation. o Nominal or measured. o Initial or mean.

Toxicity endpoint (e.g., EC50, NOEC) must be reported or calculable from data presented. Beyond these minimum criteria, other criteria were considered in evaluating the relevance and reliability of the data. These additional criteria were applied in particular cases based on the professional judgment of the reviewer:

Were the data derived using a standard, validated test method?

Was the source of test organisms described?

Were the plants maintained under appropriate conditions before use in the test?

Were the test organisms healthy at the beginning of the exposure period?

Did the study include multiple exposure concentrations? o Tests with only two or three concentrations are insufficient for determination of

ECx values. o No Observed Effect Concentrations (NOECs) are useful only if at least three closely-

spaced concentrations are tested. o Exception: exposure to a single concentration at the water solubility limit is

sufficient to generate a useful NOEC or a “greater than” ECx value.

Were exposure concentrations confirmed by chemical analysis? o Measured concentrations are preferred for endpoint calculation. o Measured concentrations should be at least 50% of nominal concentrations. o Nominal concentrations may be acceptable for relatively stable substances well

below their solubility limits.



Are response measurements reported for each exposure concentration, or only statistical endpoints such as EC50 or NOEC values?

o If only the endpoint is reported, the statistical method must be specified.

Are response measurements for controls and treatment groups reported?

Is control response acceptable?

Are methods documented sufficiently? o Organism collection methods o Pre-exposure acclimation/culture conditions o Size, age, condition, life stage at initiation of exposure o Exposure system o Number of replicates at each concentration o Procedures for randomization o Exposure medium composition o Exposure conditions (light, temperature, aeration, agitation, etc.)

From publications and reports judged to be sound according to the criteria described above, data points usable for SSD analysis were identified. The data points were compiled in a database (Microsoft Access 2007). For each data point, the following supporting information was recorded:

Study ID (a unique ID for each test).

Reference ID (linked to document information, kept confidential to protect chemical identity).

Active Ingredient Code (linked to confidential information such as chemical name, CAS number, chemical class, etc.).

Test Substance Code (linked to confidential information such as product name, percent a.i., formulation type, etc.).

Species scientific name.

Species common name.

Source of test organisms (field, culture).

Part/size/age at test initiation.

Experimental unit.

Test container.

Medium.

Sediment.

Light (intensity, photoperiod).

Temperature.

Other conditions.

Exposure type (static, semi-static renewal, flow-through).

Exposure duration.

Exposure concentrations.

Analytical confirmation (none, stock solution, initial exposure concentration, mean measured, etc.).

Measured concentration as percent of nominal concentration.

Controls.



Number of replicates.

Response: plant part (shoot, root, whole plant, etc.).

Response: measurement (number, length, biomass, etc.).

Response: interval (final, increase/decrease during exposure, specific growth rate during exposure, etc.).

Endpoint (EC50, NOEC, etc.).

Concentration.

Measured or nominal (applies to endpoint concentration).

Control performance.

Comments. The database, without the confidential information about chemical identity and without details about test methods, is provided in Appendix A of this report.

3. SSD Analysis Methods Methods for statistical analysis of SSDs have been thoroughly reviewed by others (e.g., Posthuma et al. 2002; Intrinsik 2009), and advancing the methodology was outside the scope of this project. Given the uncertainties related to data selection and other factors (Section 6), SSD results should be considered approximations regardless of the rigor of the statistical method. To address the question of Lemna gibba and Myriophyllum spicatum position in the SSD, and algal sensitivity relative to all macrophytes, we believe it is sufficient, at least for an initial analysis, to apply a single, generally applicable distribution model, the lognormal, to estimate the SSDs for all chemicals. In specific cases other models may fit the data better than the lognormal. We acknowledge that applying a single statistical model to all datasets adds another source of uncertainty to the results. The analysis reported here could be refined through exploration of alternative distribution models. The ranking of species according to sensitivity is unaffected by the SSD model used.

3.1 Overview of SSD Analysis The SSD analysis method used in this investigation is based on the assumption that the sensitivity of aquatic plant species (represented by data points from toxicity tests) follows a lognormal distribution. For each herbicide or fungicide to be analyzed, one data point is selected from the available data for each species (see Section 3.2). The species data points for that herbicide or fungicide are sorted (lowest to highest), the rank of each data point is transformed based on a normal distribution, and a linear regression is fitted to the data using the log of the data point concentration as the independent variable and the normalized rank as the dependent variable. The slope and intercept of the regression can be used to estimate the concentration at which a specified fraction of species is affected (the HCx value, where x represents the percentage of species, typically 5% or 50%), and to estimate the fraction of



species affected (FA)1 at a specified concentration. The calculations are implemented in a Microsoft Excel 2007 spreadsheet.

3.2 Data Selection The database contained a variety of statistical endpoints, but only median effect concentrations (EC50s) were available for a sufficient number of species to support SSD analysis. The EC50s were based on a wide variety of biological measurements, and these had to be pooled for SSD analysis. Basing SSDs on a variety of measurements was necessary for two reasons. First, differences in biology of the test species necessitate differences in measured responses (e.g. frond number, root length, plant dry weight); to construct an SSD that includes macrophytes with different morphology and growth characteristics requires the use of differently-derived EC50s for different species. Second, as a practical matter, subdividing the database by categories of measured data points severely reduces the number of SSDs that can be evaluated, because equivalent data are often unavailable for 6 or more species. Comparisons across chemicals are also limited if they are based on subsets of the measurement data points. Toxicity data points for aquatic plants are typically derived from single or repeated measurements of plant standing crop. Standing crop can be quantified as biomass (wet or dry weight), shoot length, chlorophyll, or a similar measurement. The effect of the chemical on the plant can be assessed based on (a) the standing crop at a particular point in time, (b) the absolute increase in standing crop over a span of time, or (c) the relative rate of increase (specific growth rate). Even for a single standing crop measurement (e.g., whole plant dry weight), toxicity data points based on (a), (b), and (c) from a single test will differ. Bergtold and Dohmen (2011) present reasons why data points based on specific growth rate are more informative and better suited to effects characterization than data points based on standing crop or standing crop increase (the “yield” response). Growth rate data points are preferred (e.g., OECD Guideline 201) because they are independent of the absolute level of the control growth rate, the slope of the concentration-effect curve, and the test duration; in contrast, all of these factors affect the numerical value of a yield-based data point. For mathematical reasons, an EC50 calculated for growth rate is usually greater than an EC50 calculated for yield from the same experimental data. A small percentage of the data points in the AMRAP database were based on functional measurements, mainly photosynthesis. There were not enough of these data points to support any firm conclusions about their sensitivity relative to yield-based or growth rate data points. Methods for functional measurements are even less standardized than other aspects of aquatic macrophyte ecotoxicology. Given the difficulties of restricting data selection for SSDs based on categories of measurement data points, the SSDs examined in this project used the lowest reported EC50 for each species, regardless of the biological measurement upon which the EC50 was based. While selection of the lowest available EC50 is standard regulatory practice (e.g., US EPA 2004), it leaves open the possibility that a data point based on a non-standard measurement parameter could unduly influence the SSD. If all of the original

1 The meaning of “affected” depends on the data points used in the SSD. In this analysis, the SSDs were based on

EC50 values, so FA indicates the expected fraction of species for which the response measurement (e.g. biomass) is reduced by 50% or more.



data were available for each study, much of the variation among measurement data points could be normalized by re-calculating EC50s based on relative growth rate. However, such re-calculations were outside the scope of the current project.

3.3 Lognormal Regression

The process used to generate each SSD using Microsoft Excel functions was as follows:

1. Sort data points (one per species) from lowest to highest. 2. Assign a rank from 1 to N (number of data points) to each data point. 3. Transform rank of each data point (n) to corresponding Weibull plotting position (p) as follows:

p = n/(N+1) 4. Transform each Weibull plotting position (p) to a normal scale (p’) using Excel NORMSINV

function as follows: p’ = NORMSINV(p)

The NORMSINV() function returns the inverse of the standard normal cumulative distribution, with a mean of zero and a standard deviation of one.

5. Transform concentration value (C) of each data point to a logarithm (c’) as follows: c’ = log(C)

6. Use Excel functions to estimate the parameters of a linear regression with c’ as the independent variable and p’ as the dependent variable:

Slope = SLOPE(p’,c’) Intercept = INTERCEPT(p’,c’)

r2 = RSQ(p’,c’) Note: only values between (but not including) the lowest “greater than” value and the highest “less than” value are used in the regression.

7. Treat “greater than” and “less than” values as follows: a. Include “greater than” and “less than” values when sorting and ranking data points. b. “Greater than” values and all data points larger than the smallest “greater than” value

are not used in the lognormal regression but are included in calculation of rank. c. “Less than” values and all data points smaller than the largest “less than” value are not

used in the lognormal regression but are included in calculation of rank. (Note: This situation was not encountered in this database.)

8. Estimate the HCx (the concentration at which x percent of species are affected) from the slope and intercept of the regression as follows:

HCx = 10^((NORMSINV(x)-Intercept)/Slope) Note: express x as a fraction in the NORMSINV() function.

9. Estimate the lower and upper 95% confidence limits on HCx as follows: LL=100*NORMSDIST(NORMSINV(x)-t0.5,N-2*SQRT((1+1/N+(HCx-average(c’))2/(var(c’)*(N-1)))*S2(y.x))) UL=100*NORMSDIST(NORMSINV(x)+t0.5,N-2*SQRT((1+1/N+(HCx-average(c’))2/(var(c’)*(N-1)))*S2(y.x))) The NORMSDIST() function returns the standard normal cumulative distribution (has a mean of zero and a standard deviation of one).

10. Estimate the fraction of species affected (FA) at any exposure concentration (EC) as follows: FA = NORMSDIST(log(EC)*Slope+Intercept)



3.4 Presentation of Results

The approach to presentation of the SSD analysis was as follows:

1. Tabulate the data points used in the SSD calculation. 2. Report the parameters of the lognormal regression (slope, intercept, r2, N). 3. Plot the fitted lognormal curve and the individual observations (data points).

Note: “Greater than” data points were plotted as open symbols distributed along the upper tail of the regression curve. For each such data point, the vertical plotting position was the assumed Weibull value and the horizontal plotting position was the corresponding concentration derived from the slope and intercept of the regression. This simplification was used as a plotting convention and did not affect the numerical results, because these points were not used in the regression.

4. Report the HC5 and HC50 and their 95% confidence limits as representative descriptors of the SSD.

5. Report the empirical position (as a Weibull value) of Lemna gibba and Myriophyllum spicatum on the macrophyte SSD. For algae, which are not included in the SSD, estimate the fraction of macrophyte species that would be affected (FA) at the EC50 of the most sensitive algal species.

6. Report the ratios of each Lemna gibba and Myriophyllum spicatum data point, and of the lowest algal EC50, to the HC5 concentrations.

7. Report the ratios of each L. gibba and M. spicatum data point, and of the lowest algal EC50, to the data point for the most sensitive macrophyte species.

4. Results Results of the analysis for each of the 14 chemicals are presented below.

4.1 Chemical A Chemical A inhibits amino acid biosynthesis. There are EC50 values for 16 macrophyte species. Myriophyllum spicatum is the most sensitive of 16 macrophyte species. M. sibiricum and M. aquaticum are 4 to 10 times less sensitive than M. spicatum and fall in the upper half of the macrophyte SSD. Lemna minor and L. gibba rank 4th and 5th on the SSD, respectively, with EC50 values 2 to 3 times higher than M. spicatum. L. trisulca is in the upper end of the macrophyte SSD. Two macrophyte species have indeterminate (greater-than) EC50s. Of the standard algal species required for testing under FIFRA, three have indeterminate EC50s as high as >92,800 ppb (Navicula pelliculosa). The only definitive algal EC50, for Pseudokirchneriella subcapitata, is greater than 14 of the 16 macrophyte EC50 values (i.e., all except the indeterminate EC50s). All of the macrophyte data points are standing crop data points. Most (11 of the 16 EC50s) are 14-d leaf area. Three data points, including the two most sensitive species (M. spicatum and Elodea nuttallii) as well as M. sibiricum, are root length or weight. The position of M. spicatum and E. nuttallii at the low end of the SSD is not simply a reflection of root measurements, however: the EC50 for new shoot length



is nearly as low as the lowest EC50 for M. spicatum, and the EC50 for plant dry weight is nearly as low as the lowest EC50 for E. nuttallii (see Appendix A for a listing of all data points).

Figure 1. Macrophyte SSD for Chemical A

Note: larger circles indicate “greater than” points extrapolated from the SSD as described in Section 3.4.

N (total) N (in regression) r2 HC5 (ppb) HC50 (ppb)

16 14 0.8965 0.018 (0.0056-0.060) 0.39 (0.14-1.1)



Table 1. Chemical A: Macrophyte and algal toxicity values used in the analysis. Algal data were not used to construct the SSD.

Species Measurement EC50 (ppb)1 EC50 range2

Myriophyllum spicatum 21-d root length 0.055 0.055 - 1.035 (9)

Elodea nuttallii 21-d root dry wt 0.058 0.058 – 3.82 (33)

Batrachium trichophyllum 14-d leaf area 0.07 0.07 (1)

Lemna minor 14-d leaf area 0.1 0.1 - 1.57 (9)

Lemna gibba 21-d dry wt 0.142 0.142 – 4.00 (11)

Spirodela polyrhiza 14-d leaf area 0.19 0.19 – 0.32 (2)

Ceratophyllum demersum 14-d leaf area 0.2 0.2 - >1000 (3)

Myriophyllum sibiricum 14-d root dry wt 0.22 0.22 – 0.39 (3)

Potamogeton crispus 14-d leaf area 0.23 0.23 (1)

Elodea canadensis 14-d leaf area 0.57 0.57 – 0.79 (2)

Lemna trisulca 14-d leaf area 0.62 0.62 - >1000 (3)

Myriophyllum aquaticum 14-d chlorophyll a 0.624 0.624 - 7.0 (7)

Ceratophyllum submersum 14-d leaf area 2.21 2.21 - >300 (2)

Berula erecta 14-d leaf area 3.92 3.92 (1)

Skeletonema costatum (algae) n.s. >93.6 >93.6 (1)

Anabaena flos-aquae (algae) n.s. >95.4 >95.4 (1)

Pseudokirchneriella subcapitata (algae)

n.s. 130 130 – 286 (3)

Callitriche platycarpa 14-d leaf area >300 >300 (1)

Sparganium emersum 14-d leaf area >1000 >300 - >1000 (2)

Navicula pelliculosa (algae) n.s. >92800 >92800 (1) 1 Lowest EC50 for each species. 2 Number of EC50 values in parentheses. n.s.: measurement not specified in data source.



4.2 Chemical B Chemical B is an auxin herbicide. There are EC50 values for 15 macrophyte species. Myriophyllum sibiricum, M. spicatum, and M. aquaticum are the 3 most sensitive species, with all EC50s in a narrow range. M. brasiliense is the least sensitive rooted macrophyte species, more than 40x less sensitive than the other three Myriophyllum species. This difference may be due to different response measurements: the data point for M. brasiliense is 14-d plant transpiration, a functional measurement, while the other three are standing-crop measurements. Lemna minor, L. gibba and L. trisulca are the 3 least sensitive macrophyte species. All algae are less sensitive than all sediment-rooted macrophytes. Most of the macrophyte data points, including the 9 lowest EC50s, are for standing crop. There is one growth endpoint and one functional endpoint. The lowest EC50s for the three Myriophyllum species clustered at the lower end of the SSD are for a variety of measurements: root length (M. sibiricum), bud number (M. spicatum), and carotenoid contents (M. aquaticum).

Figure 2. Macrophyte SSD for Chemical B



15 13 0.9390 7.7 (3.0-20) 177 (78-400)



Table 2. Chemical B: Macrophyte and algal toxicity values used in the analysis. Algal data were not used to construct the SSD.

Species Measurement EC50 (ppb)1 EC50 range 2 Myriophyllum sibiricum 14-d root length 13 13 - >1470 (3)

Myriophyllum spicatum 5-d bud number 14 14 - 730 (14)

Myriophyllum aquaticum 14-d carotenoid 19 19 - >5100 (9)

Ranunculus aquatilis 28-d root length 92 92 - >3000 (4)

Ranunculus circinatus 28-d root length 100 100 – 2731 (6)

Potamogeton pectinatus 77-d plant biomass 121 121 (1)

Ranunculus peltatus 28-d shoot length 140 140 – 271 (4)

Potamogeton lucens 28-d root length 181 181 - >3000 (5)

Salvinia natans 28-d chlorophyll 250 250 – 5400 (5)

Potamogeton crispus 28-d root length 290 290 - >3000 (6)

Elodea nuttallii 28-d relative growth 292 292 - >3000 (12)

Myriophyllum brasiliense 14-d plant transpiration 690 690 – 2070 (4)

Lemna gibba n.s. 695 695 (1)

Navicula pelliculosa (algae) n.s. 2020 2020 (1)

Skeletonema costatum (algae) n.s. 2020 2020 (1)

Anabaena flos-aquae (algae) n.s. >2020 >2020 (1)

Lemna trisulca 28-d plant dry wt >3000 >3000 (2)


n.s. 33200 33200 – 41772 (2)

Lemna minor 4-d frond number >100000 >100000 (1) 1 Lowest EC50 for each species. 2 Number of EC50 values in parentheses. n.s.: measurement not specified in data source.



4.3 Chemical C Chemical C inhibits cells division and elongation. There are EC50 values for 10 macrophyte species (including Chara intermedia, a macroalga). Lemna gibba is the most sensitive macrophyte. Myriophyllum spicatum and M. aquaticum are relatively insensitive; both are indeterminate (greater-than) values in the extrapolated portion of the SSD. Three of the 4 FIFRA algal species (excluding Anabaena flos-aquae) are more sensitive than all macrophyte species, about twice as sensitive as L. gibba. Most of the macrophyte data points are for standing crop (weight or length) or standing crop increase. The two Lemna data points are for growth rate. EC50 values based on growth rate are expected (for mathematical reasons) to be greater than EC50 values based on standing crop; if a standing crop EC50 were available for L. gibba, the position of this species at the low end of the SSD would be unaffected.

Figure 3. Macrophyte SSD for Chemical C



10 6 0.9723 4.8 (1.7-14) 366 (156-855)



Table 3. Chemical C: Macrophyte and algal toxicity values used in the analysis. Algal data (other than macroalgae) were not used to construct the SSD.

Species Measurement EC50 (ppb)1 EC50 range 2 Skeletonema costatum (algae) n.s. 5.2 5.2 (1)


n.s. 5.4 5.4 (1)

Navicula pelliculosa (algae) n.s. 6.7 6.7 (1)

Lemna gibba 10-d growth rate (frond number)

11.8 11.8 – 288 (14)

Chara intermedia (macroalgae)3 14-d shoot fresh wt 25 25 – 86.5 (3)

Heteranthera zosterifolia 14-d shoot length increase 108 108 – 193 (4)

Ceratophyllum demersum 7-d shoot length 146 146 (1)

Anabaena flos-aquae (algae) n.s. >174 >174 (1)

Lemna minor 7-d growth rate (frond area)

280 280 – 634 (2)

Myriophyllum spicatum 21-d shoot length increase >400 >400 (3)

Egeria densa 7-d shoot length increase >400 >400 (3)

Potamogeton natans 14-d shoot length increase >400 >400 (4)

Hygrophila polysperma 14-d shoot length 403 403 (1)

Myriophyllum aquaticum 14-d shoot length increase 8550 8550 – 24130 (6) 1 Lowest EC50 for each species. 2 Number of EC50 values in parentheses. 3 Included in SSD construction. n.s.: measurement not specified in data source.



4.4 Chemical D1 Chemical D1 inhibits fungal respiration. There are EC50 values for 9 macrophyte species. The most sensitive macrophyte species is Elodea nuttallii. Myriophyllum spicatum is in the lower portion of the macrophyte SSD, with an EC50 twice as high as E. nuttallii. M. aquaticum is near the middle of the SSD. Lemna gibba and L. trisulca are near the upper end of the SSD. Only Callitriche platycarpa is less sensitive than the two Lemna species. Three FIFRA algae species are more sensitive than all macrophytes and the fourth species (Pseudokirchneriella subcapitata) is more sensitive than all macrophytes except E. nuttallii. Six of the macrophyte data points are for standing crop (dry weight, shoot length, or root length). The other three macrophyte data points, including M. spicatum, are for growth rate.

Figure 4. Macrophyte SSD for Chemical D1

Note: larger circle indicates “greater than” point extrapolated from the SSD as described in Section 3.4.


9 8 0.8431 36 (7.5-174) 459 (135-1557)



Table 4. Chemical D1: Macrophyte and algal toxicity values used in the analysis. Algal data were not used to construct the SSD.

Species Measurement EC50 (ppb)1 EC50 range 2 Skeletonema costatum (algae) n.s. 13 13 (1)


Anabaena flos-aquae (algae) n.s. 74 74 – 200 (2)

Elodea nuttallii 21-d new shoot length 94 94 - >3300 (7)


n.s. 190 190 (1)

Elodea canadensis 21-d root dry wt 194 194 - >3300 (8)

Myriophyllum spicatum 21-d plant relative growth rate

200 200 - >3300 (5)

Potamogeton crispus 21-d root dry wt 297 297 - >3300 (7)

Ceratophyllum demersum 21-d plant relative growth rate

354 354 – 783 (2)

Myriophyllum aquaticum 14-d root length 480 480 – 4490 (7)

Lemna gibba 14-d frond dry wt 510 510 – 720 (3)

Lemna trisulca 21-d plant relative growth rate

2881 2881 - >3300 (2)

Callitriche platycarpa 21-d plant dry wt >3300 >3300 (2) 1 Lowest EC50 for each species. 2 Number of EC50 values in parentheses. n.s.: measurement not specified in data source.



4.5 Chemical D2 Chemical D2 inhibits fungal respiration. There are EC50 values for 10 macrophyte species. Macrophyte sensitivity to this chemical is highly variable, with EC50 values spanning 3 orders of magnitude. The most sensitive macrophyte species is Elodea canadensis. Myriophyllum spicatum and Lemna gibba are near the midpoint of the macrophyte SSD. L. minor and L. trisulca are at the upper end of the SSD. Skeletonema costatum, the most sensitive of the FIFRA algal species, is 5 times less sensitive than E. canadensis, but the EC50 is still in the low end of the macrophyte SSD. EC50s for all of the FIFRA algal species are in the lower half of the macrophyte SSD. The lowest EC50s for most macrophytes are based on standing crop data points for roots (dry weight or length). Data points based on shoot or whole plant standing crop are as much as 1000 times higher than root data points for all rooted species (see Appendix A for a list of all data points). For example, the lowest non-root EC50 for E. canadensis is 451 ppb for new shoot length, which is 100 times higher than the EC50 for root length. No root-based EC50 is available for Potamogeton cripsus or Callitriche platycarpa, and these species are at or near the upper end of the macrophyte SSD. This SSD is therefore strongly influenced by the differences in data points between and within species.

Figure 5. Macrophyte SSD for Chemical D2



10 9 0.8992 2.8 (0.49-144) 229 (8.7-5966)



Table 5. Chemical D2: Macrophyte and algal toxicity values used in the analysis. Algal data were not used to construct the SSD.

Species Measurement EC50 (ppb)1 EC50 range 2 Elodea canadensis 21-d root length 4 4 - >3300 (8)

Ranunculus peltatus 21-d root dry wt 16 16 – 1108 (6)

Skeletonema costatum (algae) 4-d (n.s.) 20.3 20.3 – 80 (3)

Anabaena flos-aquae (algae) 5-d (n.s.) 50 50 (1)


4-d (n.s.) 50 50 – 290 (2)

Elodea nuttallii 21-d root dry wt 109 109 – 1018 (7)

Navicula pelliculosa (algae) 5-d (n.s.) 124 124 (1)

Myriophyllum spicatum 21-d root dry wt 236 236 – 1599 (6)

Lemna gibba 14-d (n.s.) 250 250 (1)

Potamogeton crispus 21-d plant relative growth rate

338 338 – 888 (3)

Ranunculus circinatus 21-d root length 341 341 – 696 (6)

Lemna minor 2-d (n.s.) 800 800 (1)

Lemna trisulca 21-d plant relative growth rate

1282 1282 – 1656 (2)

Callitriche platycarpa 21-d plant dry wt >3300 >3300 (2) 1 Lowest EC50 for each species. 2 Number of EC50 values in parentheses. n.s.: measurement not specified in data source.



4.6 Chemical E1 Chemical E1 inhibits multiple biosynthesis pathways. There are EC50 values for 6 macrophyte species. There is a broad range of aquatic plant sensitivity to this herbicide, with EC50s spanning 4 orders of magnitude. Three macrophyte species have indeterminate (greater-than) EC50s. There are definitive EC50 values for only 3 macrophyte species, which is insufficient for an SSD. However, the relative sensitivity of the aquatic plants is clear. Lemna gibba is the most sensitive of the 6 macrophyte species. Myriophyllum spicatum is among the three macrophyte species with indeterminate EC50s, at least 75 times less sensitive than L. gibba. Two algal species, Pseudokirchneriella subcapitata and Skeletonema costatum, are similar in sensitivity to L. gibba. Five of the 6 macrophyte data points are for standing crop (dry weight or frond number); 1 (the highest) is for growth rate. Table 6. Chemical E1: Macrophyte and algal toxicity values used in the analysis. Algal data were not used to construct the SSD.

Species Measurement EC50 (ppb)1 EC50 range 2 Pseudokirchneriella subcapitata (algae) 5-d (n.s.) 1.43 1.43 (1)

Lemna gibba 7-d frond number 2.7 2.7 - >26 (9)

Skeletonema costatum (algae) 4-d (n.s.) 3.4 3.4 (1)

Elodea canadensis 27-d dry wt >16 >8 - >16 (10)

Lagarosiphon major 21-d dry wt 47 47 - >200 (5)

Glyceria maxima 70-d dry wt >200 >200 (11)

Myriophyllum spicatum 21-d dry wt >200 >200 (5)

Navicula pelliculosa (algae) 4-d (n.s.) 1380 1380 (1)

Spirodela oligorrhiza 4-d growth rate 6950 6950 (1)

Anabaena flos-aquae (algae) 5-d (n.s.) 35000 35000 (1) 1 Lowest EC50 for each species. 2 Number of EC50 values in parentheses. n.s.: measurement not specified in data source.



4.7 Chemical E2 Chemical E2 inhibits multiple biosynthesis pathways. There are EC50 values for 12 macrophyte species. There is a broad range of aquatic plant sensitivity to this herbicide, with a factor of at least 2750 between the smallest and greatest EC50. Lemna gibba is the most sensitive macrophyte. All other macrophyte species (including L. minor) are more than 40 times less sensitive than L. gibba. Myriophyllum spicatum is in the low end of the SSD. Many macrophyte species have indeterminate (greater-than) EC50s. Pseudokirchneriella subcapitata, the only algal species for which data are available, is comparable in sensitivity to L. gibba and much more sensitive than all other macrophyte species. All of the macrophyte data points are for standing crop.

Figure 6. Macrophyte SSD for Chemical E2



12 6 0.9035 1.4 (0.067-30) 2428 (163-36119)



Table 7. Chemical E2: Macrophyte and algal toxicity values used in the analysis. Algal data were not used to construct the SSD.

Species Measurement EC50 (ppb)1 EC50 range 2 Pseudokirchneriella subcapitata (algae)

5-d (n.s.) 1.64 1.64 – 6 (2)

Lemna gibba 14-d frond number 2.3 2.3 (1)

Ceratophyllum demersum 14-d wet wt increase 85 85 (1)

Myriophyllum spicatum 14-d shoot length 104.3 104.3 - >5018 (3)

Lemna minor 4-d frond number 198 198 – 482 (2)

Najas sp. 14-d wet wt 584 584 (1)

Lagarosiphon major 14-d shoot fresh wt 825.4 825.4 - >2878 (2)

Potamogeton pectinatus 14-d wet wt increase >1000 >1000 (1)

Glyceria maxima 14-d dry wt >1610 >1610 (3)

Elodea canadensis 14-d wet wt increase >3000 >3000 (1)

Myriophyllum heterophyllum 14-d wet wt increase >3000 >3000 (1)

Potamogeton crispus 14-d dry wt >3075 >3075 (3)

Ranunculus penicillatus 14-d dry wt >4499 >4499 (3) 1 Lowest EC50 for each species. 2 Number of EC50 values in parentheses. n.s.: measurement not specified in data source.



4.8 Chemical E3 Chemical E3 inhibits multiple biosynthesis pathways. There are EC50 values for 8 macrophyte species. Lemna gibba is the most sensitive macrophyte. L. paucicostata and L. minor are in the middle and upper portion of the macrophyte SSD. There are no data for Myriophyllum spicatum. The EC50 for M. heterophyllum is indeterminate, and greater than all other tested macrophytes. The most sensitive algal species is Pseudokirchneriella subcapitata, about 4-fold more sensitive than L. gibba. The EC50 for Skeletonema costatum is also in the lower end of the macrophyte SSD, only 1.5 times greater than the EC50 for L. gibba. Other algal species are in the upper end of the macrophyte SSD. All of the macrophyte data points are for standing crop.




8 7 0.8563 6.5 (0.65-66) 244 (43-1389)



Table 8. Chemical E3: Macrophyte and algal toxicity values used in the analysis. Algal data were not used to construct the SSD.


n.s. 10 10 – 77 (2)

Lemna gibba 14-d plant biomass 43 43 – 169 (5)

Salvinia natans 28-d chlorophyll b 50 50 – 550 (5)


Ceratophyllum demersum 14-d plant wet wt increase 70 70 (1)

Lemna paucicostata 7-d plant dry wt 118 118 – 511 (2)

Najas sp. 14-d plant wet wt 242 242 (1)

Lemna minor 4-d frond number 343 343 - >575 (4)


Anabaena flos-aquae (algae) n.s. 1200 1200 (1)

Elodea canadensis 14-d plant wet wt increase 2355 2355 (1)

Myriophyllum heterophyllum 14-d plant wet wt increase >3000 >3000 (1) 1 Lowest EC50 for each species. 2 Number of EC50 values in parentheses. n.s.: measurement not specified in data source.



4.9 Chemical E4 Chemical E4 inhibits multiple biosynthesis pathways. There are EC50 values for 8 macrophyte species, including Chara intermedia (a macroalga). EC50s for macrophytes are within a fairly narrow range (25-fold difference between the highest and lowest). The most sensitive macrophyte species is Ceratophyllum demersum. There are no data for Lemna gibba. L. minor is near the middle of the macrophyte SSD, but only 3 times less sensitive than C. demersum. Myriophyllum spicatum is in the upper end of the macrophyte SSD. Pseudokirchneriella subcapitata is more sensitive than all macrophyte species. The only other algal species for which data are available, Anabaena flos-aquae, is less sensitive than all macrophyte species. All macrophyte data points are based on standing crop. Six of the 8 data points are for shoot length increase.



8 8 0.9739 6.3 (3.5-11) 51 (32-81)



Table 9. Chemical E4: Macrophyte and algal toxicity values used in the analysis. Algal data (other than macroalgae) were not used to construct the SSD.


3-d biomass 1.95 1.95 – 3.96 (2)

Ceratophyllum demersum 7-d shoot length increase 10.3 10.3 – 19.4 (2)

Elodea densa 7-d shoot length increase 25.6 25.6 – 28.9 (2)

Lemna minor 14-d biomass 31.8 31.8 – 39.5 (2)

Heteranthera zosterifolia 14-d shoot length increase 39.6 39.6 (1)

Vallisneria spiralis 21-d leaf length increase 45.4 45.4 (1)

Myriophyllum spicatum 13-d shoot length increase 81.5 81.5 (1)

Chara intermedia (macroalgae)3

7-d shoot length increase 139 139 (1)

Hygrophila polysperma 14-d shoot length increase 258.7 258.7 (1)

Anabaena flos-aquae (algae) 4-d biomass 9400 9400 (1) 1 Lowest EC50 for each species. 2 Number of EC50 values in parentheses. 3 Included in SSD construction.



4.10 Chemical F1 Chemical F1 is a photosynthesis inhibitor. There are EC50 values for 9 macrophyte species. Some of these data come from secondary sources (EPA pesticide toxicity database, peer-reviewed risk assessment) and have not been evaluated for quality; for these, details about experimental methods and measurement endpoints are incomplete. Three macrophyte species with very similar EC50s (Elodea canadensis, Ceratophyllum demersum, and Najas sp.) are at the low end of the SSD. Lemna gibba is the next most sensitive species, with an EC50 within a factor of 2 of E. canadensis, C. demersum, and Najas sp. L. minor is less sensitive, with an EC50 near the middle of the SSD. Myriophyllum spicatum is the least sensitive species, with an EC50 10-fold greater than the next most sensitive macrophyte. M. heterophyllum is near the middle of the SSD. EC50s for algae occur throughout the macrophyte SSD. The most sensitive algal species, Skeletonema costatum, is as sensitive as the most sensitive macrophytes. The lognormal model does not fit the data well, especially at the low end of the SSD. A better fitting model would probably result in a higher HC5.

Figure 9. Macrophyte SSD for Chemical F1


9 9 0.8452 2.5 (0.24-26) 95 (14-638)



Table 10. Chemical F1: Macrophyte and algal toxicity values used in the analysis. Algal data were not used to construct the SSD.

Species Measurement EC50 (ppb)1 EC50 range 2 Elodea canadensis 14-d wet wt increase 21 21 (1)


Najas sp. 14-d wet wt 24 24 (1)

Skeletonema costatum (algae) 5-d EC50 24 24 (1)



5-d EC50 49 49 (1)

Navicula pelliculosa (algae) 5-d EC50 60 60 (1)

Lemna minor 4-d growth rate (frond number)

92 92 (1)

Hydrilla verticillata n.s. 110 110 (1)

Myriophyllum heterophyllum 14-d wet wt increase 132 132 (1)

Anabaena flos-aquae (algae) 5-d EC50 230 230 (1)

Thalassia testudinum n.s. 320 320 (1)

Myriophyllum spicatum 5-d branch number 3700 3700 (1) 1 Lowest EC50 for each species. 2 Number of EC50 values in parentheses. n.s.: measurement not specified in data source.



4.11 Chemical F2 Chemical F2 is a photosynthesis inhibitor. There are EC50 values for 8 macrophyte species, including Chara globularis (a macroalga). The range of macrophyte sensitivity is very narrow, with only a 5-fold difference between the most sensitive (Elodea nuttallii) and the least sensitive (Lemna minor). Myriophyllum spicatum is nearly as sensitive as E. nuttallii. L. gibba is near the upper end of the macrophyte SSD, but still less than 3-fold less sensitive than E. nuttallii. The FIFRA algal species are less sensitive than all macrophytes except the two Lemna species. Nevertheless, even the least sensitive algal species, Pseudokirchneriella subcapitata, is within a factor of 10 of the most sensitive macrophyte. Most of the macrophyte EC50s are for a functional measurement, photosynthesis. The Lemna data points are based on standing crop (L. gibba) and growth rate (L. minor). The two lowest EC50s are for photosynthesis after 35 days of exposure, while the other photosynthesis EC50s are derived from measurements made after 1 day of exposure. Data for both exposure durations are available for E. nuttallii and the resulting EC50s are similar, implying that the difference in exposure duration among species data points is not a significant factor in this SSD.

Figure 10. Macrophyte SSD for Chemical F2.


8 8 0.8147 4.1 (1.6-11) 14 (6.8-30)



Table 11. Chemical F2: Macrophyte and algal toxicity values used in the analysis. Algal data (other than macroalgae) were not used to construct the SSD.

Species Endpoint EC50 (ppb)1 EC50 range 2 Elodea nuttallii 35-d photosynthesis 8.3 8.3 – 13.4 (3)

Ceratophyllum demersum 35-d photosynthesis 8.7 8.7 (1)

Myriophyllum spicatum 1-d photosynthesis 11.8 11.8 (1)

Chara globularis (macroalga)3

1-d photosynthesis 12.1 12.1 (1)

Potamogeton crispus 1-d photosynthesis 12.9 12.9 (1)

Ranunculus circinatus 1-d photosynthesis 13.2 13.2 (1)


Lemna gibba 7-d dry wt increase 21.0 21 – 55 (3)

Skeletonema costatum (algae) n.s. 35.9 35.9 (1)

Anabaena flos-aquae (algae) n.s. 38.8 38.8 (1)

Lemna minor 7-d growth rate (plant biomass) 46.5 46.5 – 85.2 (4)


n.s. 67.0 67.0 (1)

1 Lowest EC50 for each species. 2 Number of EC50 values in parentheses. 3 Included in SSD construction. n.s.: measurement not specified in data source.



4.12 Chemical F3 Chemical F3 is a photosynthesis inhibitor. There are EC50 values for 6 macrophyte species. The lognormal distribution is not a good fit for these data (r2 = 0.7602); thus the HCx values and ratios based upon them are uncertain. However, the relative sensitivity of species can still be determined from the data. The most sensitive macrophyte species is Lemna minor, and the least sensitive species is L. gibba. These EC50s span a 20-fold range. There are no data for Myriophyllum spicatum. M. heterophyllum is near the middle of the macrophyte SSD. The most sensitive algal species, Pseudokirchneriella subcapitata, is nearly as sensitive as L. minor. Other algal species are scattered throughout the macrophyte SSD. All of the macrophyte data points are based on standing crop.



6 6 0.7602 1.8 (0.12-28) 22 (3.2-154)




Species Endpoint EC50 (ppb)1 EC50 range 2 Lemna minor 14-d plant biomass 7.9 7.9 – 37 (5)


n.s. 8.09 8.09 – 43 (3)



Myriophyllum heterophyllum 14-d wet wt increase 17 17 (1)


Najas sp. 14-d plant wet wt 19 19 (1)

Elodea canadensis 14-d wet wt increase 21 21 (1)

Skeletonema costatum (algae) n.s. 80.88 80.88 (1)

Lemna gibba n.s. 160 160 (1) 1 Lowest EC50 for each species. 2 Number of EC50 values in parentheses. n.s.: measurement not specified in data source.



4.13 Chemical F4 Chemical F4 is a photosynthetic inhibitor. There are EC50 values for 10 macrophyte species. There is only about a 15-fold EC50 range among macrophyte species. The most sensitive macrophyte species is Lemna gibba, and the least sensitive species is L. trisulca. L. minor is in the lower end of the macrophyte SSD. Myriophyllum spicatum is near the middle of the macrophyte SSD, but its EC50 is within a factor of 4 of the EC50 for L. gibba. Pseudokirchneriella subcapitata, the most sensitive algal species, is 5-fold more sensitive than L. gibba. Navicula pelliculosa is also more sensitive than all macrophyte species. EC50s for the other two FIFRA algal species are in the middle of the macrophyte SSD. All of the macrophyte data points except L. gibba are for standing crop. The L. gibba EC50 comes from the EPA pesticide toxicity database, which does not specify the measurement endpoint.



10 10 0.9366 10 (4.8-22) 75 (39-142)




Species Endpoint EC50 (ppb)1 EC50 range 2 Pseudokirchneriella subcapitata (algae)

n.s. 3.2 3.2 (1)



Ceratophyllum submersum 14-d plant dry wt 17 17 – 69 (2)


Lemna minor 14-d plant dry wt 40 40 – 182 (6)

Myriophyllum spicatum 14-d plant dry wt 55 55 (1)

Elodea canadensis 14-d plant dry wt 98 98 – 305 (2)


Potamogeton crispus 14-d plant dry wt 109 109 – 199 (2)

Callitriche platycarpa 14-d plant dry wt 119 119 – 158 (2)

Spirodela polyrhiza 14-d plant dry wt 146 146 – 228 (2)

Ceratophyllum demersum 14-d plant dry wt 196 196 (1)

Lemna trisulca 14-d plant dry wt 254 254 (1) 1 Lowest EC50 for each species. 2 Number of EC50 values in parentheses. n.s.: measurement not specified in data source.



4.14 Chemical F5 Chemical F5 is a photosynthetic inhibitor. There are EC50 values for 8 macrophyte species. The most sensitive macrophyte species is Spirodela polyrhiza. There are no data for Lemna gibba; L. minor is the least sensitive macrophyte species, and L. trisulca is near the middle of the macrophyte SSD. Myriophyllum spicatum is less sensitive than all macrophytes except L. minor. Skeletonema costatum, the only standard FIFRA species for which data are available, is more sensitive than all macrophyte species. Nearly all of the macrophyte data points are based on growth rate. EC50s for both Lemna species are based on a functional measurement, photosynthesis.



8 8 0.9832 2.9 (1.8-4.7) 26 (18-39)




Species Endpoint EC50 (ppb)1 EC50 range 2 Skeletonema costatum (algae) 3-d growth 0.86 0.86 (1)

Spirodela polyrhiza 21-d relative growth 4.6 4.6 – 33.1 (2)

Elodea nuttallii 21-d relative growth 11.8 11.8 – 97.7 (2)

Ceratophyllum demersum 21-d relative growth 12.9 12.9 – 1357.3 (2)

Elodea canadensis 21-d relative growth 23.4 23.4 – 44.5 (2)

Lemna trisulca 21-d photosynthesis 36.1 36.1 – 64.5 (2)

Potamogeton crispus 21-d relative growth 38.8 38.8 (1)

Myriophyllum spicatum 21-d relative growth 73.4 73.4 (1)

Lemna minor 21-d photosynthesis 130.4 130.4 – 198.9 (2) 1 Lowest EC50 for each species. 2 Number of EC50 values in parentheses.



5. Discussion Taken together, the results described above for the 14 chemicals show that neither Lemna gibba nor Myriophyllum spicatum is consistently among the most sensitive macrophyte species for all herbicides and fungicides. For the majority of the chemicals examined, the most sensitive of the FIFRA algal species is more sensitive than the most sensitive macrophyte. For 13 of the 14 chemicals, one or more of the EC50s for L. gibba and the 4 FIFRA algal species is near or below the EC50 for the most sensitive macrophyte species. For the remaining chemical, while neither Lemna gibba nor the FIFRA algal species lie within the lower portion of the macrophyte SSD, M. spicatum is among the most sensitive species. The positions of L. gibba, the most sensitive algal species, and M. spicatum relative to the macrophyte SSD are characterized below in three ways:

1. The position of the species in the macrophyte SSD. For L. gibba and M. spicatum, position is expressed as a Weibull percentile (p = n/(N+1)). This is an empirical value, independent of the distribution model. For algae, position is expressed as the fraction of macrophyte species with EC50 below the EC50 of the algal species (Fraction Affected), which is estimated from the lognormal SSD regression. The algae are not included in the SSD.

2. The ratio of the EC50 for the species to the HC5 of the macrophyte SSD. This is a function of the rank (or, in the case of algae, the equivalent macrophyte FA) of the species and the slope of the macrophyte SSD. This ratio is subject to the uncertainties of the HC5 estimation; for example, a poor fit of the lognormal model will introduce error in the EC50/HC5 ratio.

3. The ratio of the EC50 for the species to the EC50 of the most sensitive macrophyte. This is an empirical measure of the difference in sensitivity between the species and the most sensitive macrophyte species.

As summarized below, evaluation of the results in terms of these parameters indicates that, while no single species consistently represents the most sensitive macrophyte species, the combination of L. gibba and the 4 FIFRA algae includes a data point near or below the most sensitive macrophyte data point or the macrophyte HC5 for 13 of the 14 chemicals examined. For the remaining chemical, M. spicatum is among the most sensitive macrophyte species.

5.1 Lemna gibba The position of Lemna gibba in the macrophyte SSD for the 12 chemicals for which data are available ranges from 7.7% to 85.7% (Table 15 and Figure 14). For 5 of the 12 chemicals, the position of L. gibba is low (below the 15th percentile). For the other chemicals, L. gibba EC50s are distributed through the middle and upper end of the SSD. The L. gibba EC50 is within a factor of 10 of the HC5 of the macrophyte SSD for 6 of 11 chemicals. (The HC5 cannot be calculated for Chemical E1 due to fewer than 6 definitive EC50s.) Among the other 5 chemicals, the EC50/HC5 ratio ranges from 14 to 90. The L. gibba EC50 is within a factor of 10 of the lowest macrophyte EC50 for 9 of the 12 chemicals. For the other 3 chemicals, the EC50/lowest EC50 ratio ranges from 20 to 63.



By all of these measures, L. gibba is among the most sensitive macrophyte species for 5 of the 12 chemicals for which data are available (Chemicals C, E1, E2, E3,and F4). For these chemicals plus four others (Chemicals A, D1, F1, and F2), the L. gibba EC50 is within a factor of 10 of both the macrophyte HC5 and the lowest macrophyte EC50. For the other 3 chemicals (Chemicals B, D2, and F3), L. gibba is among the least sensitive macrophyte species by all measures. Table 15. Position of Lemna gibba in macrophyte SSDs.

Chemical Empirical Percentile EC50/HC5 EC50/lowest EC50

A 29.4% 7.8 2.6

B 81.3% 90 54

C 9.1% 2.5 1.0

D1 70.0% 14 5.4 D2 45.5% 90 63

E1 14.3% No SSDa 1.0 E2 7.7% 1.6 1.0 E3 11.1% 6.6 1.0 E4 No data No data No data

F1 40.0% 15 1.8 F2 77.8% 5.2 2.5 F3 85.7% 88 20 F4 9.1% 1.5 1.0 F5 No data No data No data aNo SSD analysis (fewer than 6 definitive EC50 values), so HC5 is not determined.

For 10 of the 11 chemicals for which data are available for L. gibba and at least one other Lemna species, L. gibba is the most sensitive Lemna species (Table 16). The exception is Chemical F3, to which L. minor is the most sensitive macrophyte and L. gibba the least sensitive macrophyte, with EC50 values separated by a factor of 20 (Table 12). Table 16. Rank of Lemna gibba among Lemna species in sensitivity to herbicides and fungicides.

Chemical Number of Lemna species in database Rank of L. gibba among Lemna species

A 3 1

B 3 1

C 2 1

D1 2 1

D2 3 1

E1 1 1

E2 2 1

E3 3 1

E4 1 No data for L. gibba

F1 2 1

F2 2 1

F3 2 2

F4 3 1

F5 2 No data for L. gibba



Figure 14. Sensitivity of Lemna gibba relative to all macrophytes.



5.2 Algae EC50s for the most sensitive of the FIFRA algal test species (Pseudokirchneriella subcapitata, Navicula pelliculosa, Anabaena flos-aquae, and Skeletonema costatum) for 14 chemicals correspond to positions on the macrophyte SSD ranging from less than 1% to 99.8% (Table 17 and Figure 15). For half of the chemicals, the lowest algal EC50 is below the 10th percentile of the macrophyte SSD; 10 of 14 are at or below the 25th percentile. (These percentiles are used here for comparative purposes only; no special significance is attributed to the 10th or 25th percentiles.) The only chemicals for which algae are substantially less sensitive than the most sensitive macrophytes (greater than 25% of macrophyte species affected at the lowest algal EC50) are Chemicals A, B, and F2. It should be noted that not all chemicals have data for all four FIFRA species. The lowest algal EC50 is within a factor of 10 of the HC5 of the macrophyte SSD for 11 of 13 chemicals. The only exceptions are Chemicals A and B. For 10 of 14 chemicals, algal EC50 values are less than or equal to the EC50 of the most sensitive macrophyte. The four exceptions are Chemicals A, B, D2, and F2. By these measures, algae are at least as sensitive as the most sensitive macrophytes to nearly all of these chemicals. For a few, especially Chemicals A and B, algae are much less sensitive than macrophytes. Table 17. Sensitivity of the most sensitive of the FIFRA algal species relative to macrophyte SSDs.

Chemical Fraction Affected EC50/HC5 EC50/lowest EC50

A 99.8% 5110 1702

B 90.0% 261 155

C 5.3% 1.1 0.4

D1 1.0% 0.4 0.1 D2 18.3% 7.3 5.1

E1 No SSD No SSD 0.5 E2 5.4% 1.2 0.7 E3 7.3% 1.5 0.2 E4 0.52% 0.3 0.2

F1 26.6% 9.6 1.1 F2 47.9% 3.4 1.7 F3 25.4% 4.5 1.0 F4 0.43% 0.3 0.2 F5 0.55% 0.3 0.2



Figure 15. Sensitivity of standard algal species relative to all macrophytes.



5.3 Myriophyllum spicatum The position of Myriophyllum spicatum in the macrophyte SSD for 12 chemicals ranges from 5.9% to 90% (Table 18 and Figure 16). M. spicatum is among the most sensitive macrophyte species (i.e., within the lower quartile) for 3 of the 12 chemicals (Chemicals A, B, and E2). The M. spicatum EC50 is within a factor of 10 of the macrophyte HC5 for 5 of 11 chemicals. Among the other 6 chemicals, the EC50/HC5 ratio ranges from 13 to 1473. The M. spicatum EC50 is within a factor of 10 of the lowest macrophyte EC50 for 6 of the 12 chemicals. For the other 6 chemicals, the EC50/lowest EC50 ratio ranges from 16 to 176. Overall, M. spicatum is among the most sensitive macrophyte species for one quarter of the chemicals, and for about half of the chemicals the M. spicatum EC50 is within a factor of 10 of both the macrophyte HC5 and the lowest macrophyte EC50. For the remaining half of the chemicals, M. spicatum is among the least sensitive macrophyte species. Table 18. Position of Myriophyllum spicatum in macrophyte SSDs.

Chemical Empirical Percentile EC50/HC5 EC50/lowest EC50

A 5.9% 3.0 1.0

B 12.5% 1.8 1.1

C 72.7% >84 >34

D1 30.0% 5.5 2.1 D2 36.4% 85 59

E1 ≥57.1% No SSD >74 E2 23.1% 75 45 E3 No data No data No data E4 66.7% 13 7.9

F1 90.0% 1473 176 F2 33.3% 2.9 1.4 F3 No data No data No data F4 36.4% 5.3 3.4 F5 77.8% 26 16

For 5 of the 6 chemicals for which data are available for M. spicatum and at least one other Myriophyllum species, M. spicatum is the most sensitive Myriophyllum species (Table 16). The exception is Chemical F1, to which M. heterophyllum is 30 times more sensitive than M. spicatum (Table 10).



Table 19. Rank of Myriophyllum spicatum among Myriophyllum species in sensitivity to herbicides and fungicides.

Chemical Number of Myriophyllum species in database

Rank of M. spicatum among Myriophyllum species

A 3 1

B 4 1

C 2 1

D1 2 1

D2 1 1

E1 1 1

E2 2 1

E3 1 No data for M. spicatum

E4 1 1

F1 2 2

F2 1 1

F3 1 No data for M. spicatum

F4 1 1

F5 1 1



Figure 16. Sensitivity of Myriophyllum spicatum relative to all macrophytes.



5.4 Combined data for Lemna gibba, algae, and Myriophyllum spicatum When the most sensitive species of interest (i.e., L. gibba, the 4 FIFRA algae, and M. spicatum) are considered, the lowest of the EC50s is within the lower 25th percentile of the macrophyte SSD for nearly all chemicals (Table 20 and Figure 17). For 10 of the 14 chemicals, at least one of these species is within the 15th percentile of the macrophyte SSD. (These percentiles are used here only for descriptive purposes; no special significance is attributed to the 15th or 25th percentiles.) The EC50 for the most sensitive of these species is at or below the corresponding macrophyte HC5 for 6 of 14 chemicals. The lowest EC50 of these species is within a factor of 10 of the HC5 for all chemicals. The lowest of these EC50s is at or below the EC50 of the most sensitive macrophyte for all chemicals except Chemicals D2 and F2; even for these exceptions, the difference is within a factor of 5. (Chemical D2 is an uncertain SSD – see Section 4.5.) Table 20. Sensitivity of the most sensitive species of Lemna gibba, FIFRA algae, or Myriophyllum spicatum relative to macrophyte SSDs.

Chemical Most sensitive of the six species1

Percentile or Fraction Affected

EC50/HC5 EC50/lowest EC50

A M. spicatum, L. gibba 5.9 3 1.0

B M. spicatum 12.5 1.8 1.1

C S. costatum, P. subcapitata, N. pelliculosa,

L. gibba

5.3 1.1 0.4

D1 S. costatum, N. pelliculosa

1 0.4 0.1

D2 S. costatum, A. flos-aquae, P. subcapitata

18.3 7.3 5.1

E1 P. subcapitata, L. gibba, S. costatum

14.3 No SSD2 0.5

E2 P. subcapitata, L. gibba 5.4 1.2 0.7 E3 P. subcapitata 7.3 1.5 0.2 E4 P. subcapitata 0.52 0.3 0.2

F1 S. costatum, L. gibba, P. subcapitata, N. pelliculosa

26.6 9.6 1.1

F2 M. spicatum, N. pelliculosa, L. gibba, S.

costatum

33.3 2.9 1.4

F3 P. subcapitata, N. pelliculosa, A. flos-aquae

25.4 4.5 1.0

F4 P. subcapitata 0.43 0.3 0.2 F5 S. costatum 0.55 0.3 0.2 1 Numerical values in table are based on the most sensitive of the 6 species under consideration. When multiple species are similar in sensitivity (EC50 within a factor of 3), all are listed in order of sensitivity. 2 No SSD analysis (fewer than 6 definitive EC50 values), so HC5 is not determined.



Figure 17. Sensitivity of the most sensitive species of Lemna gibba, FIFRA algae, and Myriophyllum spicatum relative to all macrophytes.

A, L, and M indicate that the lowest value for each chemical is based on algae (FIFRA species), Lemna gibba, or Myriophyllum spicatum, respectively. In some cases two or three of these species are similar in sensitivity, as indicated by multiple letters separated by commas.



6. Uncertainties This analysis has examined the data to address the question of sensitivity of standard aquatic plant test species relative to other macrophyte species. The answer to this question depends on the data selected for the analysis. Each particular data point – each toxicity test result – varies according to many factors, and the SSD analysis is itself conditioned by data selection and statistical methodology. The macrophyte SSD for each chemical, the position of particular species in each SSD, and the overall conclusions based on comparisons among chemicals, are contingent upon the scope of the data examined, including:

Chemicals: the identities of the chemicals, their mechanisms of toxic action, and their form (technical grade active ingredient or formulated product);

Species: the test species, their growth habits (e.g., submersed, emergent, floating) and habitats (e.g., flowing or standing water, depth);

Measurements: the measured biological responses, including what plant part is affected (e.g. shoot, root, frond, whole plant), the quantified response (e.g. final length or weight, increase during the test, growth rate, area under the growth curve), and the duration of exposure or the period over which the response is measured;

Endpoints: the statistical endpoints (EC50, No Observed Effect Concentration, etc.). When data are available for a sufficient number of chemicals, it will be possible to examine the data to better understand how the relative sensitivity of macrophyte species varies depending on what chemicals, species, measured responses, and test endpoints are included in the SSD. Unfortunately, the current data (see Appendix A) are too sparse to support such an exploration. Thus, the scope of the present analysis is based on certain assumptions and exclusions:

In most cases, only data for technical grade active ingredient are used; in a few exceptional cases, data for formulations are included.

No distinctions are made based on mechanism of action. In some cases SSDs are similar for chemicals with similar mechanism of action, but there are many exceptions. Information on specific mechanisms of action is not factored into the analysis.

No distinctions are made based on growth habit or habitat. That is, separate SSDs are not examined for subsets of the available macrophyte species (rooted species, flowing water species, etc.). Individual SSDs may be dominated by different groups of macrophytes, but this is not factored into the analysis.

No distinctions are made based on the nature of the measured biological response. For each species, the lowest reliable EC50 value is selected regardless of the measured effect or the duration of exposure. This is common regulatory practice, but it is not ideal for scientific analysis of SSDs.

The analysis is based entirely on EC50 values. Data for other statistical endpoints (e.g., EC20s, NOECs) are much more limited.

Each individual toxicity test result used in the SSD may also be affected by a suite of experimental variables, such as:



Test organism: The outcome of a toxicity test can vary depending on the organism source (e.g., laboratory culture, field collection, or commercial supplier); plant part (e.g., shoot, whole plant) used as inoculum; and age, size, and condition of the plants at the start of test.

Test conditions and procedures: The source and type of aqueous medium; presence or absence and source of sediment; light, temperature, and other water quality parameters during exposure; and exposure system (e.g., static, semi-static, or flow-through), can influence the result of the toxicity test.

Chemical exposure regime: Most of the data were based on aqueous chemical exposure, and all data points are given as aqueous concentrations (ppb); some studies reported results for surface spray (µg/m2) or spiked sediment (µg/kg), but these were not incorporated into the data analysis. Results were reported based on nominal or measured concentrations, with measured concentrations preferred but not necessarily more reliable. When concentrations decrease during the exposure period, data points based on mean measured concentrations may differ from data points based on initial concentrations.

Because toxicity test results are understood to be dependent on these and other methodological factors, standardized test guidelines attempt to reduce variability by specifying the methods and conditions required for an acceptable test. This may enhance the comparability of results from different tests, but does not eliminate the uncertainties, for at least three reasons: (1) test guidelines cannot specify the acceptable range for every conceivable experimental parameter; (2) the influence of many experimental conditions on toxicity is unknown; and (3) the specified test conditions cannot represent the full range of conditions encountered in the field. As the AMRAP database was compiled, information on test methods and conditions was extracted from the original data sources and documented in the database for possible further evaluation – for example, comparison of results for a particular species with and without sediment present, or for static vs flow-through exposure regimes. Such methodological explorations were beyond the scope of the SSD analysis, but could be highly relevant to the development of test guidelines and the interpretation of test results. Finally, the analysis is subject to several sources of statistical uncertainty. Some of these are associated with individual data points:

Experimental design: Parameters such as the number and spacing of test concentrations, the number of replicates per concentration, and number of organisms per replicate, influence the calculation of both point-based (e.g., EC50) and hypothesis-based (e.g., NOEC) endpoints.

Experimental variability: The accuracy and precision of point-based estimates and the power of hypothesis tests are a function of the variability of measurements among individual organisms, between experimental replicates, and between treatment groups in a given test. Some of this variability is presumably inherent in the biology of the test organisms, while some is due to laboratory technique (test organism handling, maintenance of test conditions, etc.) and some reflects measurement error.

Statistical method for deriving endpoints: Estimation of EC50, NOEC, and other endpoints from a given set of experimental data entails a suite of statistical uncertainties related to model selection and model fitting.



Similar statistical issues – data variability, model selection, model fitting – relate to the SSD analysis, and have been addressed by others (Hart et al. 2006; Intrinsik 2009; Posthuma et al. 2002; Rodney and Moore 2008). In addition to these, the SSD analysis is subject to uncertainties arising from the criteria used to select or derive the final dataset from the larger database of available test results. Particular issues are described below. The manner in which these issues are addressed can affect the results and interpretation of the analysis.

Data points from multiple tests: In situations where multiple equally reliable data points are available for a species and a chemical, a geometric mean is often considered the most appropriate representation of the species in the SSD. This approach was followed in the current analysis. Some regulatory agencies prefer to select the lowest data point as a precautionary policy. This may be appropriate for some purposes, but the objective of SSD analysis is to quantify the distribution of sensitivity among species, and that quantification is more robust when based on species means than on extreme test results.

Representation of indeterminate (greater-than) values: Although indeterminate toxicity values are less useful than determinate values in evaluating relative sensitivity, to ignore them completely would be to lose valuable information and would distort the SSD. However, a large number of indeterminate values adds uncertainty to the SSD, both by reducing the number of data points available and by concentrating the analysis on the lower end of the sensitivity distribution. In the long run, the best solution to this situation is to develop determinate toxicity data and avoid generating indeterminate results.

Data quality: When studies are conducted and reported according to appropriate Good Laboratory Practices, they are usually reliable. Deficiencies of studies reported under GLP can almost always be clearly seen by an experienced reviewer, and questionable studies identified. Studies that are not conducted or reported according to GLP may be fully as robust and reliable as GLP studies, but are not always so, and deficiencies are more difficult to evaluate. When both GLP and non-GLP studies are available for a single species and chemical, the GLP study will usually, but not always, be found to be more complete and reliable and therefore preferred over the non-GLP study. However, reliable data from non-GLP studies are extremely valuable in developing SSDs, because GLP studies are conducted with a limited number of species for which standard methods exist.

The SSD analysis presented here is subject to all of these sources of uncertainty: limitations in scope (chemicals, species, data points), experimental variability (test organisms, conditions, procedures, and exposure regimes), statistical methods, and data selection decisions.

7. Conclusions and Recommendations

Neither Lemna gibba nor Myriophyllum spicatum is consistently among the most sensitive macrophyte species for all herbicides and fungicides.

Lemna gibba is among the most sensitive macrophyte species for approximately half of the herbicides and fungicides examined. L. gibba is quite insensitive to about a quarter of the chemicals.

M. spicatum is among the most sensitive macrophyte species for approximately one-quarter of the herbicides and fungicides examined. M. spicatum is among the least sensitive macrophytes to several others.



For a majority of the chemicals examined, the most sensitive of the FIFRA algal species is more sensitive than the most sensitive macrophyte. In a few cases, the tested algae are much less sensitive than most macrophytes.

While no single species consistently represents the most sensitive macrophyte species, the combination of L. gibba and the 4 FIFRA algae almost always includes a data point that is near or below the most sensitive macrophyte data point and the macrophyte HC5.

For the exceptional chemicals for which the EC50s of L. gibba and the FIFRA algae are not near or below the most sensitive macrophyte EC50, M. spicatum is among the most sensitive species.

These conclusions are subject to the limitations of the available data. This analysis is based on chemicals representing 6 different modes of action but some modes of action are represented by only one chemical. As data become available for additional chemicals, it may be possible to refine the analysis.



8. References Bergtold M, Dohmen GP. 2011. Biomass or growth rate endpoint for algae and aquatic plants: relevance for the aquatic risk assessment of herbicides. Integr Environ Assess Manag 7:237-247. Dohmen P. 2010. Myriophyllum sp. – Test Methodology for a Rooted Aquatic Macrophyte. Presentation at the SETAC North America 31st Annual Meeting. 7–11 November 2010, Portland, Oregon, USA. Hart A et al. 2006. EUFRAM - Concerted action to develop a European Framework for probabilistic risk assessment of the environmental impacts of pesticides. Final Report. Volume 1 - 4. Available from www.eufram.com. Accessed August 2, 2011. Intrinsik. 2009. Framework and derivation of benchmarks for the protection of aquatic life from pesticides. Report prepared by Intrinsik Environmental Sciences for National Guidelines and Standards Office, Environment Canada, Ottawa, Ontario, Canada. Maltby L, Arnold D, Arts G, Davies J, Heimbach F, Pickl C, Poulsen V. 2010. Aquatic Macrophyte Risk Assessment for Pesticides. Society of Environmental Toxicology and Chemistry (SETAC). Pensacola, FL. Maletzki D, Kussatz CK. 2011. Myriophyllum spicatum as a test organism for eco toxicity testing and the impact of sucrose in the test medium on the photosynthesis activity and sensitivity of the test species. Poster presentation at the SETAC Europe 21st Annual Meeting, 15-19 May 2011, Milan, Italy. Maletzki, D, Kussatz, CK, Ratte, MR, Ratte, TR. 2011 Myriophyllum spicatum toxicity test: design and first results of an interlaboratory ring test using a sediment-free test system. Poster presentation at the SETAC Europe 21st Annual Meeting, 15-19 May 2011, Milan, Italy. Posthuma L, Traas TP, Suter GW (eds.). 2002. Species Sensitivity Distributions in Risk Assessment. Boca Raton, FL, USA: CRC Press. Rodney SI, Moore DRJ. 2008. Development of an Excel-based tool for fitting and evaluating species sensitivity distributions. Report prepared for National Guidelines and Standards Office, Environment Canada, Ottawa, Ontario, Canada. U.S. EPA (United States Environmental Protection Agency). 2004. Overview of the Ecological Risk Assessment Process in the Office of Pesticide Programs, U.S. Environmental Protection Agency, Office of Prevention, Pesticides and Toxic Substances, Washington, DC. U.S. EPA (United States Environmental Protection Agency). 2011a. ECOTOX Database. Accessed from http://cfpub.epa/ecotox/, January 2011. U.S. EPA (United States Environmental Protection Agency). 2011b. Office of Pesticide Programs (OPP) Pesticide Toxicity Database. Accessed from http://www.ipmcenters.org/Ecotox/index.cfm, January 2011.

http://www.eufram.com/



Appendix A. AMRAP SSD database

Explanation of fields and abbreviations Chem: Chemical code Exp. Type: Exposure type (S = static, R = static renewal, F = flowthrough) Interval: Time period (d) of measurement; range (e.g., 0-14) indicates period of growth rate calculation or increase in plant part measurement Meas/Nom: Measured or nominal exposure concentrations (M = measured, N = nominal) Study: Study identification number (all records with the same Study ID were from a single study)



Chem Species Exp. Type

Plant Part Measurement Interval (d)

Endpoint Conc (µg a.s./L)

Meas/Nom

Study

A Anabaena flos-aquae S EC50 >95.4 234

A Batrachium trichophyllum

R plant specific leaf area 14 EC50 0.07 M 27

A Berula erecta R plant specific leaf area 14 EC50 3.92 M 80

A Callitriche platycarpa R plant specific leaf area 14 EC50 >300 M 77

A Ceratophyllum demersum

R plant specific leaf area 14 EC50 >1000 M 76


R plant growth rate (biomass)

0-14 EC50 4.13 M 19



A Ceratophyllum submersum


A Ceratophyllum submersum

R plant specific leaf area 14 EC50 >300 M 81

A Elodea canadensis R plant specific leaf area 14 EC50 0.57 M 22

A Elodea canadensis R plant specific leaf area 14 EC50 0.79 M 23

A Elodea nuttallii S root dry weight 21 EC10 0.036 N 47

A Elodea nuttallii S new shoots number 21 EC50 0.789 N 48

A Elodea nuttallii S new shoots average length 21 EC10 0.034 N 48

A Elodea nuttallii S new shoots average length 21 NOEC 0.100 N 48

A Elodea nuttallii S new shoots length 21 EC50 0.271 N 48


A Elodea nuttallii S new shoots length 21 NOEC 0.100 N 48


A Elodea nuttallii S new shoots number 21 NOEC 0.100 N 48

A Elodea nuttallii S main shoot length 21 NOEC 3.3 N 48



A Elodea nuttallii S root number 21 EC50 0.338 N 48

A Elodea nuttallii S root dry weight 21 NOEC 0.033 N 47

A Elodea nuttallii S plant dry weight 21 NOEC 3.3 N 47

A Elodea nuttallii S root length 21 NOEC 0.033 N 48




A Elodea nuttallii S root average length 21 EC50 0.133 N 48


A Elodea nuttallii S root average length 21 NOEC 0.033 N 48

A Elodea nuttallii S root number 21 NOEC 0.1 N 48

A Elodea nuttallii S root length 21 EC10 0.048 N 48

A Elodea nuttallii S shoot total length 21 NOEC 0.100 N 48




A Elodea nuttallii S shoot dry weight 21 NOEC 1.000 N 48

A Elodea nuttallii S shoot total length 21 EC50 1.133 N 48









Meas/Nom

Study








































A Elodea nuttallii S plant dry weight 21 EC10 0.01 N 48







A Elodea nuttallii S new shoots average length 21 NOEC 1 N 46








Meas/Nom

Study








A Elodea nuttallii S plant dry weight 21 EC50 0.08 N 48




















A Lemna gibba S frond number 7 EC50 0.377 M 43

A Lemna gibba S plant dry weight 14 EC50 4.00 N 45

A Lemna gibba S frond growth rate 0-7 NOEC 0.201 M 43

A Lemna gibba S frond number 7 EC10 0.204 M 43

A Lemna gibba S frond growth rate 0-7 EC50 0.541 M 43

A Lemna gibba S frond growth rate 0-7 EC10 0.200 M 43

A Lemna gibba S frond area under growth curve

0-7 EC50 0.375 M 43


0-7 EC10 0.184 M 43

A Lemna gibba S plant dry weight increase 0-7 EC10 0.137 M 43

A Lemna gibba S frond number 7 LOEC 0.623 M 43

A Lemna gibba S frond growth rate 0-7 LOEC 0.623 M 43


0-7 NOEC 0.060 M 43


0-7 LOEC 0.201 M 43

A Lemna gibba S frond dry weight increase 0-7 NOEC 0.201 M 43

A Lemna gibba S EC50 0.41 238

A Lemna gibba S frond number 14 EC50 2.93 N 45

A Lemna gibba S frond number 14 NOEC 2.00 N 45

A Lemna gibba S plant biomass 14 NOEC 1.00 N 45

A Lemna gibba S frond number 7 NOEC 0.201 M 43






Meas/Nom

Study

A Lemna gibba S frond dry weight increase 0-7 LOEC 0.623 M 43









A Lemna gibba S plant dry weight 21 NOEC 0.100 N 51


A Lemna gibba S frond mean dry weight per frond

21 NOEC 3.3 N 51

A Lemna gibba S plant dry weight increase 0-7 EC50 0.581 M 43



A Lemna minor S EC50 0.36 233

A Lemna minor S frond growth rate (area) 0-7 EC50 0.79 N 53


A Lemna minor S frond number 4 LOEC 0.2 N 55

A Lemna minor S frond number 4 NOEC <0.2 N 55

A Lemna minor S frond number 4 EC50 0.4 N 55


A Lemna minor R plant growth rate (biomass)

0-14 EC50 1.13 M 17

A Lemna minor R frond number 14 EC50 0.356 N 44

A Lemna minor R plant specific leaf area 14 EC50 0.10 M 17

A Lemna minor R plant specific leaf area 14 EC50 0.18 M 16


A Lemna minor R plant growth rate (biomass)

0-14 EC50 0.80 M 16

A Lemna trisulca R plant growth rate (biomass)

0-14 EC50 10.44 M 18

A Lemna trisulca R plant specific leaf area 14 EC50 0.62 M 18

A Lemna trisulca R plant specific leaf area 14 EC50 >1000 M 75

A Myriophyllum aquaticum S root total length 14 EC50 4.0 N 56

A Myriophyllum aquaticum S root number 14 EC50 3.0 N 56

A Myriophyllum aquaticum S shoot length increase 0-14 EC50 7.0 N 56

A Myriophyllum aquaticum S shoot area under curve (length)

0-14 EC50 1.0 N 56

A Myriophyllum aquaticum S plant carotenoid 14 EC50 0.882 N 56

A Myriophyllum aquaticum S plant chlorophyll a 14 EC50 0.624 N 56

A Myriophyllum aquaticum S plant chlorophyll b 14 EC50 0.882 N 56

A Myriophyllum sibiricum S root number 14 IC25 0.19 N 52

A Myriophyllum sibiricum S shoot length 14 IC25 0.15 N 52

A Myriophyllum sibiricum S shoot length 14 IC50 0.39 N 52

A Myriophyllum sibiricum S root dry weight 14 IC50 0.22 N 52

A Myriophyllum sibiricum S root dry weight 14 IC25 0.06 N 52

A Myriophyllum sibiricum S root number 14 IC50 0.29 N 52

A Myriophyllum spicatum S root dry weight 21 EC10 0.034 N 50






Meas/Nom

Study

A Myriophyllum spicatum S root dry weight 21 EC50 0.080 N 50

A Myriophyllum spicatum S root average length 21 EC10 0.021 N 50

A Myriophyllum spicatum S root dry weight 21 NOEC 0.033 N 50

A Myriophyllum spicatum S plant dry weight 21 NOEC 0.033 N 50

A Myriophyllum spicatum S root average length 21 EC50 0.101 N 50

A Myriophyllum spicatum S root length 21 EC10 0.013 N 50

A Myriophyllum spicatum R plant specific leaf area 14 EC50 0.29 M 25

A Myriophyllum spicatum S root length 21 EC50 0.055 N 50

A Myriophyllum spicatum S root number 21 EC50 0.388 N 50

A Myriophyllum spicatum S root number 21 EC10 0.030 N 50

A Myriophyllum spicatum S root average length 21 NOEC 0.033 N 50

A Myriophyllum spicatum S root length 21 NOEC 0.033 N 50

A Myriophyllum spicatum S shoot dry weight 21 NOEC 0.001 N 50

A Myriophyllum spicatum S new shoots number 21 EC50 0.104 N 50

A Myriophyllum spicatum S new shoots number 21 EC10 0.014 N 50

A Myriophyllum spicatum S new shoots length 21 NOEC 3.3 N 50

A Myriophyllum spicatum S new shoots length 21 EC10 0.007 N 50

A Myriophyllum spicatum S new shoots length 21 EC50 0.061 N 50

A Myriophyllum spicatum S new shoots average length 21 NOEC 3.3 N 50

A Myriophyllum spicatum S new shoots average length 21 EC10 0.078 N 50

A Myriophyllum spicatum S shoot total length 21 NOEC 0.330 N 50

A Myriophyllum spicatum S root number 21 NOEC 0.330 N 50

A Myriophyllum spicatum S main shoot length 21 NOEC 0.330 N 50

A Myriophyllum spicatum S main shoot length 21 EC10 0.082 N 50

A Myriophyllum spicatum S main shoot length 21 EC50 1.035 N 50

A Myriophyllum spicatum S new shoots average length 21 EC50 0.397 N 50

A Myriophyllum spicatum S new shoots number 21 NOEC 0.330 N 50

A Navicula pelliculosa S EC50 >92800 237

A Potamogeton crispus R plant specific leaf area 14 EC50 0.23 M 26

A Pseudokirchneriella subcapitata

S plant fluorescence 4 NOEC <19 N 92


S EC50 285.6 232


S plant fluorescence 4 EC50 190 N 92


S plant fluorescence 4 LOEC 19 N 92


S EC50 130 236

A Skeletonema costatum S EC50 >93.6 235

A Sparganium emersum R plant specific leaf area 14 EC50 >1000 M 78

A Sparganium emersum R plant specific leaf area 14 EC50 >300 M 79

A Spirodela polyrhiza R plant specific leaf area 14 EC50 0.19 M 21

A Spirodela polyrhiza R plant specific leaf area 14 EC50 0.32 M 20

B Anabaena flos-aquae S EC50 >2020 198

B Chlorococcum sp. S growth EC50 50000 196

B Dunaliella tertiolecta S growth EC50 75000 195

B Elodea nuttallii S root length 28 EC50 997 N 90

B Elodea nuttallii S plant dry weight 28 EC50 2243 N 90

B Elodea nuttallii S root number 28 EC50 1807 N 90






Meas/Nom

Study

B Elodea nuttallii S root dry weight 28 EC50 898 N 84

B Elodea nuttallii S shoot length 28 EC50 >3000 N 84

B Elodea nuttallii S root length 28 EC50 574 N 84

B Elodea nuttallii S plant relative growth 0-28 EC50 292 N 90

B Elodea nuttallii S root number 28 EC50 982 N 84

B Elodea nuttallii S root dry weight 28 EC50 1096 N 90

B Elodea nuttallii S shoot length 28 EC50 785 N 90

B Elodea nuttallii S plant dry weight 28 EC50 >3000 N 84

B Elodea nuttallii S plant relative growth 0-28 EC50 >3000 N 84

B Isochrysis galbana S growth EC50 50000 193

B Lemna gibba S EC50 695 202

B Lemna gibba F plant photosynthesis (oxygen production)

1 NOEC 900 N 104

B Lemna gibba S EC50 <2020 201

B Lemna minor S frond number 4 EC50 >100000 N 70

B Lemna minor S frond number 4 LOEC >100000 N 70

B Lemna minor S frond number 4 NOEC 100000 N 70

B Lemna trisulca S plant relative growth 0-28 EC50 >3000 N 83

B Lemna trisulca S plant dry weight 28 EC50 >3000 N 83

B Myriophyllum aquaticum S shoot length increase 0-10 EC50 >5100 N 82

B Myriophyllum aquaticum S shoot length increase 0-10 NOEC 150 N 82

B Myriophyllum aquaticum S root number 14 EC50 158 N 62

B Myriophyllum aquaticum S root total length 14 EC50 50 N 62

B Myriophyllum aquaticum S plant dry weight 10 NOEC 5100 N 82

B Myriophyllum aquaticum S plant chlorophyll b 14 EC50 22 N 62

B Myriophyllum aquaticum S plant carotenoid 14 EC50 19 N 62

B Myriophyllum aquaticum S plant fresh weight increase

0-10 EC50 >5100 N 82

B Myriophyllum aquaticum S plant dry weight 10 EC50 >5100 N 82

B Myriophyllum aquaticum S plant chlorophyll a 14 EC50 20 N 62

B Myriophyllum aquaticum S root length 10 EC50 260 N 82

B Myriophyllum aquaticum S plant fresh weight increase

0-10 NOEC 5100 N 82

B Myriophyllum aquaticum S root length 10 NOEC 51 N 82

B Myriophyllum brasiliense S shoot dry weight 14 EC50 1530 N 183

B Myriophyllum brasiliense S root dry weight 14 NOEC 2210 N 182

B Myriophyllum brasiliense S plant transpiration 7 NOEC 22.1 N 182

B Myriophyllum brasiliense S shoot fresh weight 14 NOEC 221 N 183

B Myriophyllum brasiliense S root fresh weight 14 NOEC 2210 N 183

B Myriophyllum brasiliense S shoot dry weight 14 NOEC 221 N 183

B Myriophyllum brasiliense S root dry weight 14 NOEC 2210 N 183

B Myriophyllum brasiliense S shoot dry weight 14 NOEC 221 N 182

B Myriophyllum brasiliense S plant transpiration 14 NOEC 221 N 183

B Myriophyllum brasiliense S plant transpiration 14 NOEC 22.1 N 182

B Myriophyllum brasiliense S root dry weight 14 EC50 2070 N 183

B Myriophyllum brasiliense S plant transpiration 7 EC50 1350 N 183

B Myriophyllum brasiliense S plant transpiration 14 EC50 690 N 183

B Myriophyllum brasiliense S plant transpiration 7 NOEC 553 N 183

B Myriophyllum brasiliense S shoot fresh weight 14 NOEC 221 N 182






Meas/Nom

Study

B Myriophyllum brasiliense S root fresh weight 14 NOEC 221 N 182

B Myriophyllum sibiricum S shoot growth 14 IC50 >1470 N 91

B Myriophyllum sibiricum S shoot growth 14 IC25 410 N 91

B Myriophyllum sibiricum S root number 14 IC25 8 N 91

B Myriophyllum sibiricum S root number 14 IC50 18 N 91

B Myriophyllum sibiricum S root length 14 IC25 5 N 91

B Myriophyllum sibiricum S root length 14 IC50 13 N 91

B Myriophyllum spicatum F root biomass 77 EC50 50 M 185

B Myriophyllum spicatum F shoot height 77 EC50 102 M 185

B Myriophyllum spicatum S plant number of leaves 5 NOEC 100 N 178

B Myriophyllum spicatum S plant number of new structures

5 EC50 28 N 178

B Myriophyllum spicatum S plant number of leaves 5 EC50 23 N 178

B Myriophyllum spicatum F shoot dry weight 140 EC50 30 MI 184

B Myriophyllum spicatum F shoot biomass 77 NOEC <30 M 185

B Myriophyllum spicatum F root biomass 77 NOEC 50 M 185

B Myriophyllum spicatum S plant number of new structures

5 NOEC 20 N 178

B Myriophyllum spicatum S plant number of branches 5 EC50 26 N 178

B Myriophyllum spicatum F shoot height 77 NOEC 50 M 185

B Myriophyllum spicatum S plant number of buds 5 EC50 14 N 178

B Myriophyllum spicatum F shoot biomass 77 EC50 57 M 185

B Myriophyllum spicatum S plant number of roots 5 NOEC 20 N 178

B Myriophyllum spicatum F root dry weight 140 EC50 134 MI 184

B Myriophyllum spicatum F plant photosynthesis (oxygen production)

1 NOEC 450 N 105

B Myriophyllum spicatum S plant number of branches 5 NOEC 20 N 178

B Myriophyllum spicatum S plant branch number reduction

5 EC50 40 N 176

B Myriophyllum spicatum S plant biomass (after posttreatment period)

1.5 EC50 550 N 181

B Myriophyllum spicatum S plant biomass (after posttreatment period)

2 EC50 150 N 181

B Myriophyllum spicatum S plant visual injury (after posttreatment period)

1.5 EC50 730 N 181

B Myriophyllum spicatum S plant visual injury (after posttreatment period)

2 EC50 140 N 181

B Navicula pelliculosa S EC50 2020 199

B Phaeodactylum tricornutum

S growth EC50 50000 194

B Potamogeton crispus S plant relative growth 0-28 EC50 >3000 N 87

B Potamogeton crispus S plant dry weight 28 EC50 >3000 N 87

B Potamogeton crispus S root dry weight 28 EC50 347 N 87

B Potamogeton crispus S shoot length 28 EC50 1988 N 87

B Potamogeton crispus S root length 28 EC50 290 N 87

B Potamogeton crispus S root number 28 EC50 326 N 87

B Potamogeton lucens S plant dry weight 28 EC50 >3000 N 89

B Potamogeton lucens S shoot length 28 EC50 1063 N 89






Meas/Nom

Study

B Potamogeton lucens S root length 28 EC50 181 N 89

B Potamogeton lucens S root number 28 EC50 299 N 89

B Potamogeton lucens S plant relative growth 0-28 EC50 1300 N 89

B Potamogeton pectinatus F plant biomass 77 NOEC 30 M 186

B Potamogeton pectinatus F plant biomass 77 EC50 121 M 186

B Pseudokirchneriella subcapitata

S EC50 33200 197






S plant fluorescence 4 NOEC 25000 N 98

B Ranunculus aquatilis S plant dry weight 28 EC50 >3000 N 86

B Ranunculus aquatilis S plant relative growth 0-28 EC50 242 N 86

B Ranunculus aquatilis S root length 28 EC50 92 N 86

B Ranunculus aquatilis S shoot length 28 EC50 683 N 86

B Ranunculus circinatus S root length 28 EC50 100 N 85

B Ranunculus circinatus S root number 28 EC50 112 N 85

B Ranunculus circinatus S shoot length 28 EC50 1120 N 85

B Ranunculus circinatus S root dry weight 28 EC50 111 N 85

B Ranunculus circinatus S plant relative growth 0-28 EC50 719 N 85

B Ranunculus circinatus S plant dry weight 28 EC50 2731 N 85

B Ranunculus peltatus S root dry weight 28 EC50 245 N 88

B Ranunculus peltatus S root number 28 EC50 271 N 88

B Ranunculus peltatus S root length 28 EC50 263 N 88

B Ranunculus peltatus S shoot length 28 EC50 140 N 88

B Salvinia natans S plant chlorophyll b 28 NOEC 83 N 99

B Salvinia natans S stem length 28 EC50 5400 N 99

B Salvinia natans S plant fresh weight 28 LOEC 8300 N 99

B Salvinia natans S plant fresh weight 28 NOEC 830 N 99

B Salvinia natans S plant fresh weight 28 EC50 5400 N 99

B Salvinia natans S leaf number 28 LOEC 8300 N 99

B Salvinia natans S leaf number 28 NOEC 830 N 99

B Salvinia natans S leaf number 28 EC50 4980 N 99

B Salvinia natans S stem length 28 NOEC 830 N 99

B Salvinia natans S stem length 28 LOEC 8300 N 99

B Salvinia natans S plant chlorophyll a 28 EC50 250 N 99

B Salvinia natans S plant chlorophyll b 28 LOEC 830 N 99

B Salvinia natans S plant chlorophyll b 28 EC50 250 N 99

B Salvinia natans S plant chlorophyll a 28 NOEC 83 N 99

B Salvinia natans S plant chlorophyll a 28 LOEC 830 N 99

B Skeletonema costatum S EC50 2020 200

C Anabaena flos-aquae S growth EC50 >174 242

C Ceratophyllum demersum

S shoot length 0-7 EC10 4.0 MS 9


S shoot length 0-7 EC50 146 MS 9


S shoot length 0-7 NOEC 36.9 MS 9

C Chara intermedia S shoot length 0-7 EC50 42.2 MS 11






Meas/Nom

Study

C Chara intermedia S shoot length 0-7 EC10 27.6 MS 11

C Chara intermedia S shoot length 0-7 NOEC 25.0 MS 11

C Chara intermedia S shoot fresh weight 14 EC50 25.0 MS 11

C Chara intermedia S shoot dry weight 14 EC50 86.5 MS 11

C Chara intermedia S shoot fresh weight 0-14 NOEC ≥ 100 MS 11

C Chara intermedia S shoot dry weight 0-14 NOEC 50.0 MS 11

C Chara intermedia S shoot dry weight 0-14 EC10 27.2 MS 11

C Egeria densa S shoot fresh weight 7 EC50 >400 N 10

C Egeria densa S shoot fresh weight 7 NOEC 400 N 10

C Egeria densa S shoot dry weight 7 EC50 >400 N 10

C Egeria densa S shoot length increase 0-7 NOEC 400 N 10

C Egeria densa S shoot dry weight 7 NOEC 400 N 10

C Egeria densa S shoot length increase 0-7 EC50 >400 N 10

C Heteranthera zosterifolia S shoot length increase 0-14 EC20 39.7 MS 12

C Heteranthera zosterifolia S shoot dry weight 14 EC50 137 MS 12

C Heteranthera zosterifolia S shoot dry weight 14 EC20 38.9 MS 12

C Heteranthera zosterifolia S shoot dry weight 14 EC10 20.1 MS 12

C Heteranthera zosterifolia S shoot fresh weight 14 EC50 193 MS 12

C Heteranthera zosterifolia S shoot length increase 0-14 EC50 108 MS 12



C Heteranthera zosterifolia S shoot length increase 0-7 EC50 153 MS 12


C Heteranthera zosterifolia S shoot fresh weight 14 EC20 7.2 MS 12

C Hygrophila polysperma S shoot total length increase

0-14 EC50 403 N 13

C Hygrophila polysperma S plant fresh and dry weight

0-21 NOEC ≥ 400 N 13

C Hygrophila polysperma S shoot total length increase

0-14 EC10 112 N 13

C Lemna gibba S frond number (area under curve)

0-7 LOEC 7.54 M 71

C Lemna gibba R frond number (growth rate)

0-7 EC20 27.6 M 73


0-7 EC50 288 M 73

C Lemna gibba S frond growth rate 0-7 NOEC 3.0 M 71


0-7 NOEC 3.0 M 71


0-7 EC50 25.7 M 71

C Lemna gibba S frond number (growth rate)

0-7 EC50 11.8 M 71

C Lemna gibba R plant dry weight 7 NOEC 5 M 15

C Lemna gibba R frond number 7 EC50 12.2 M 72

C Lemna gibba R plant dry weight 7 EC10 4.26 M 72


C Lemna gibba R plant dry weight 7 EC50 260 M 73

C Lemna gibba R plant dry weight 7 EC50 210 M 15








Meas/Nom

Study

C Lemna gibba R frond number 7 NOEC 5 M 15

C Lemna gibba S frond growth rate 0-7 LOEC 7.54 M 71


0-7 EC50 268 M 15


0-7 NOEC 5 M 15


0-7 LOEC 10 M 15

C Lemna gibba R frond number 7 EC50 71 M 15


C Lemna gibba R frond number 7 LOEC 10 M 15

C Lemna gibba R plant dry weight 7 LOEC 10 M 15


0-7 EC50 36.6 M 72





C Lemna gibba R plant growth rate (dry weight)

0-7 EC50 >263 M 72


0-7 EC10 14.1 M 73


0-7 EC10 12.8 M 72


0-7 EC20 12.7 M 72



0-7 EC10 7.21 M 72

C Lemna gibba S plant dry weight 7 NOEC 3.0 M 71

C Lemna gibba S plant dry weight 7 LOEC 7.54 M 71

C Lemna gibba S plant dry weight 7 EC50 >65.0 M 71


0-7 EC20 38.4 M 72

C Lemna gibba S growth EC50 12.5 243

C Lemna minor S frond growth rate (area) 0-7 EC10 41 N 60




C Myriophyllum aquaticum S plant chlorophyll a 14 EC50 13970 N 63

C Myriophyllum aquaticum S root number 14 EC50 24130 N 63

C Myriophyllum aquaticum S shoot length increase 0-14 EC50 10744 N 63

C Myriophyllum aquaticum S shoot area under curve (length)

0-14 EC50 8550 N 63

C Myriophyllum aquaticum S plant chlorophyll b 14 EC50 16450 N 63

C Myriophyllum aquaticum S plant carotenoid 14 EC50 16360 N 63

C Myriophyllum spicatum S shoot dry weight 21 NOEC > 400 MS 8

C Myriophyllum spicatum S shoot length increase 0-21 EC50 > 400 MS 8

C Myriophyllum spicatum S shoot fresh weight 21 NOEC > 400 MS 8

C Myriophyllum spicatum S shoot dry weight 21 EC50 > 400 MS 8

C Myriophyllum spicatum S shoot length increase 0-21 NOEC ≥ 400 MS 8

C Myriophyllum spicatum S shoot fresh weight 21 EC50 > 400 MS 8






Meas/Nom

Study

C Navicula pelliculosa S growth EC50 6.7 241

C Potamogeton natans S shoot fresh weight 14 EC50 > 400 MS 14

C Potamogeton natans S shoot length increase 0-14 EC50 > 400 MS 14

C Potamogeton natans S shoot length increase 0-7 EC50 > 400 MS 14

C Potamogeton natans S shoot length increase 0-7 NOEC 400 MS 14

C Potamogeton natans S shoot dry weight 14 NOEC 400 MS 14

C Potamogeton natans S shoot length increase 0-14 NOEC 400 MS 14

C Potamogeton natans S shoot dry weight 14 EC50 > 400 MS 14

C Potamogeton natans S shoot fresh weight 14 NOEC 400 MS 14

C Pseudokirchneriella subcapitata

S EC50 5.4 239

C Skeletonema costatum S growth EC50 5.2 240

D1 Anabaena flos-aquae S plant biomass (area under curve)

0-5 NOEC 20 N 121

D1 Anabaena flos-aquae S plant growth rate 0-5 NOEC 40 N 121

D1 Anabaena flos-aquae S plant growth rate 0-5 EC50 200 N 121

D1 Anabaena flos-aquae S plant biomass (area under curve)

0-5 EC50 74 N 121

D1 Callitriche platycarpa R plant relative growth 0-21 EC50 >3300 N 111

D1 Callitriche platycarpa R plant dry weight 21 EC50 >3300 N 111

D1 Ceratophyllum demersum

R plant relative growth 0-21 EC50 354 N 112

D1 Ceratophyllum demersum

R plant dry weight 21 EC50 783 N 112

D1 Elodea canadensis R plant relative growth 0-21 EC50 299 N 107

D1 Elodea canadensis R root number 21 EC50 485 N 107

D1 Elodea canadensis R shoot length 21 EC50 >3300 N 107

D1 Elodea canadensis R root length 21 EC50 286 N 107

D1 Elodea canadensis R new shoot number 21 EC50 >3300 N 107

D1 Elodea canadensis R plant dry weight 21 EC50 >3300 N 107

D1 Elodea canadensis R new shoot length 21 EC50 >3300 N 107

D1 Elodea canadensis R root dry weight 21 EC50 194 N 107

D1 Elodea nuttallii R new shoot number 21 EC50 786 N 109

D1 Elodea nuttallii R plant dry weight 21 EC50 >3300 N 109

D1 Elodea nuttallii R plant relative growth 0-21 EC50 >3300 N 109

D1 Elodea nuttallii R shoot length 21 EC50 >3300 N 109

D1 Elodea nuttallii R new shoot length 21 EC50 94 N 109

D1 Elodea nuttallii R root number 21 EC50 323 N 109

D1 Elodea nuttallii R root dry weight 21 EC50 189 N 109

D1 Lemna gibba R frond dry weight increase 0-14 EC50 510 M 122

D1 Lemna gibba R frond number (growth rate)

0-14 NOEC 290 M 122

D1 Lemna gibba R frond number (growth rate)

0-14 EC50 720 M 122

D1 Lemna gibba S EC50 630 210

D1 Lemna gibba R frond dry weight increase 0-14 NOEC 290 M 122

D1 Lemna trisulca R plant dry weight 21 EC50 >3300 N 106

D1 Lemna trisulca R plant relative growth 0-21 EC50 2881 N 106

D1 Myriophyllum aquaticum S plant chlorophyll a 14 EC50 2680 N 64

D1 Myriophyllum aquaticum S plant chlorophyll b 14 EC50 2540 N 64

D1 Myriophyllum aquaticum S plant carotenoid 14 EC50 2550 N 64






Meas/Nom

Study

D1 Myriophyllum aquaticum S shoot area under curve (length)

0-14 EC50 4490 N 64

D1 Myriophyllum aquaticum S shoot length increase 0-14 EC50 2940 N 64

D1 Myriophyllum aquaticum S root total length 14 EC50 480 N 64

D1 Myriophyllum aquaticum S root number 14 EC50 2210 N 64

D1 Myriophyllum spicatum R plant relative growth 0-21 EC50 200 N 108

D1 Myriophyllum spicatum R new shoot length 21 EC50 468 N 108

D1 Myriophyllum spicatum R shoot length 21 EC50 >3300 N 108

D1 Myriophyllum spicatum R plant dry weight 21 EC50 693 N 108

D1 Myriophyllum spicatum R new shoot number 21 EC50 1626 N 108

D1 Navicula pelliculosa S EC50 14 212

D1 Potamogeton crispus R plant dry weight 21 EC50 907 N 110

D1 Potamogeton crispus R root dry weight 21 EC50 297 N 110

D1 Potamogeton crispus R new shoot number 21 EC50 404 N 110

D1 Potamogeton crispus R new shoot length 21 EC50 299 N 110

D1 Potamogeton crispus R shoot length 21 EC50 >3300 N 110

D1 Potamogeton crispus R root number 21 EC50 615 N 110

D1 Potamogeton crispus R plant relative growth 0-21 EC50 354 N 110

D1 Pseudokirchneriella subcapitata

S EC50 190 209

D1 Skeletonema costatum S EC50 13 211

D2 Anabaena flos-aquae S EC50 50 246

D2 Callitriche platycarpa R plant relative growth 0-21 EC50 >3300 N 114

D2 Callitriche platycarpa R plant dry weight 21 EC50 >3300 N 114

D2 Dunaliella tertiolecta S EC50 170 248

D2 Elodea canadensis R root dry weight 21 EC50 296 N 118

D2 Elodea canadensis R root number 21 EC50 18 N 118

D2 Elodea canadensis R new shoot length 21 EC50 471 N 118

D2 Elodea canadensis R new shoot number 21 EC50 501 N 118

D2 Elodea canadensis R shoot length 21 EC50 >3300 N 118

D2 Elodea canadensis R plant relative growth 0-21 EC50 827 N 118

D2 Elodea canadensis R plant dry weight 21 EC50 3265 N 118

D2 Elodea canadensis R root length 21 EC50 4 N 118

D2 Elodea nuttallii R root number 21 EC50 371 N 117

D2 Elodea nuttallii R new shoot number 21 EC50 778 N 117

D2 Elodea nuttallii R root length 21 EC50 305 N 117

D2 Elodea nuttallii R shoot length 21 EC50 973 N 117

D2 Elodea nuttallii R root dry weight 21 EC50 109 N 117

D2 Elodea nuttallii R plant relative growth 0-21 EC50 670 N 117

D2 Elodea nuttallii R plant dry weight 21 EC50 1018 N 117

D2 Lemna gibba S EC50 250 244

D2 Lemna minor S EC50 800 252

D2 Lemna trisulca R plant relative growth 0-21 EC50 1282 N 113

D2 Lemna trisulca R plant dry weight 21 EC50 1656 N 113

D2 Myriophyllum spicatum R plant relative growth 0-21 EC50 568 N 120

D2 Myriophyllum spicatum R plant dry weight 21 EC50 1599 N 120

D2 Myriophyllum spicatum R root dry weight 21 EC50 236 N 120

D2 Myriophyllum spicatum R root length 21 EC50 309 N 120

D2 Myriophyllum spicatum R new shoot number 21 EC50 626 N 120






Meas/Nom

Study

D2 Myriophyllum spicatum R new shoot length 21 EC50 471 N 120

D2 Navicula pelliculosa S EC50 124 247

D2 Potamogeton crispus R plant relative growth 0-21 EC50 338 N 119

D2 Potamogeton crispus R new shoot length 21 EC50 888 N 119

D2 Potamogeton crispus R plant dry weight 21 EC50 512 N 119


S EC50 50 254


S EC50 290 250

D2 Ranunculus circinatus R new shoot number 21 EC50 369 N 115

D2 Ranunculus circinatus R root number 21 EC50 610 N 115

D2 Ranunculus circinatus R plant dry weight 21 EC50 592 N 115

D2 Ranunculus circinatus R plant relative growth 0-21 EC50 402 N 115

D2 Ranunculus circinatus R shoot length 21 EC50 696 N 115

D2 Ranunculus circinatus R root length 21 EC50 341 N 115

D2 Ranunculus peltatus R shoot length 21 EC50 1108 N 116

D2 Ranunculus peltatus R root length 21 EC50 18 N 116

D2 Ranunculus peltatus R root number 21 EC50 362 N 116

D2 Ranunculus peltatus R plant dry weight 21 EC50 922 N 116

D2 Ranunculus peltatus R plant relative growth 0-21 EC50 588 N 116

D2 Ranunculus peltatus R root dry weight 21 EC50 16 N 116


D2 Skeletonema costatum S EC50 20.3 253


D2 Thalassiosira pseudonana

S EC50 179 249

E1 Anabaena flos-aquae S EC50 35000 203

E1 Elodea canadensis S main shoot length 27 NOEC 8 N 283

E1 Elodea canadensis S main shoot dry weight 27 EC50 >8 N 282

E1 Elodea canadensis S main shoot moisture content 27 NOEC 0.5 N 282

E1 Elodea canadensis S main shoot length 27 EC50 >8 N 283

E1 Elodea canadensis S main shoot wet weight 27 NOEC 8 N 283

E1 Elodea canadensis S main shoot dry weight 27 NOEC 8 N 283

E1 Elodea canadensis S main shoot wet weight 27 EC50 >8 N 282

E1 Elodea canadensis S main shoot moisture content 27 NOEC 8 N 283

E1 Elodea canadensis R main shoot wet weight 27 EC50 >16 N 284

E1 Elodea canadensis R main shoot moisture content 27 EC50 >16 N 284

E1 Elodea canadensis R main shoot wet weight 27 NOEC 16 N 284

E1 Elodea canadensis R main shoot dry weight 27 NEOC 16 N 284

E1 Elodea canadensis R main shoot dry weight 27 EC50 >16 N 284

E1 Elodea canadensis S main shoot moisture content 27 EC50 >8 N 283

E1 Elodea canadensis R main shoot moisture content 27 NOEC 16 N 284

E1 Elodea canadensis S main shoot dry weight 27 EC50 >8 N 283

E1 Elodea canadensis S main shoot wet weight 27 EC50 >8 N 283

E1 Elodea canadensis S main shoot moisture content 27 EC50 >8 N 282

E1 Elodea canadensis S main shoot wet weight 27 NOEC 8 N 282

E1 Elodea canadensis S main shoot dry weight 27 NOEC 8 N 282

E1 Glyceria maxima S shoot dry weight 21 NOEC 125 N 270

E1 Glyceria maxima S shoot height 14 EC50 >200 N 269






Meas/Nom

Study

E1 Glyceria maxima S shoot height 14 NOEC 125 N 269

E1 Glyceria maxima S shoot dry weight 14 EC50 >200 N 269















E1 Glyceria maxima S shoot number 70 NOEC 200 N 271

E1 Glyceria maxima S shoot number 70 EC50 >200 N 271



E1 Lagarosiphon major S shoot dry weight 7 NOEC 50 N 273

E1 Lagarosiphon major S shoot dry weight 70 EC50 166 N 276



E1 Lagarosiphon major S shoot dry weight 7 EC50 >200 N 273


E1 Lagarosiphon major S shoot dry weight 4 EC50 >200 N 272




E1 Lemna gibba S frond biomass (dry weight)

4 NOEC <0.85 M 264

E1 Lemna gibba R frond number (growth rate)

0-14 EC50 5.3 M 263

E1 Lemna gibba R frond number (growth rate)

0-14 NOEC 2.3 M 263

E1 Lemna gibba R frond dry weight increase 0-14 NOEC 0.12 M 263

E1 Lemna gibba R frond dry weight increase 0-14 EC50 3.4 M 263

E1 Lemna gibba S frond number 4 EC50 6.6 M 264

E1 Lemna gibba S frond growth rate 0-4 EC50 >26 M 264


4 EC50 5.7 M 264

E1 Lemna gibba S frond number 7 NOEC <0.85 M 265

E1 Lemna gibba S frond number 7 EC50 2.7 M 265

E1 Lemna gibba S frond growth rate 0-7 NOEC <0.85 M 265

E1 Lemna gibba S frond growth rate 0-7 EC50 7.4 M 265


7 EC50 3.6 M 265

E1 Lemna gibba S frond number 4 NOEC <0.85 M 264






Meas/Nom

Study


7 NOEC <0.85 M 265

E1 Lemna gibba EC50 3.4 204

E1 Lemna gibba S frond growth rate 0-4 NOEC <0.85 M 264

E1 Myriophyllum spicatum S shoot dry weight 7 NOEC 200 N 278



E1 Myriophyllum spicatum S shoot dry weight 14 EC50 >200 N 279







E1 Navicula pelliculosa S EC50 1380 206

E1 Pseudokirchneriella subcapitata

S EC50 1.43 207

E1 Skeletonema costatum S EC50 3.4 205

E1 Spirodela oligorrhiza S plant growth rate 0-4 EC50 6950 N 266

E2 Ceratophyllum demersum

S plant wet weight increase 0-14 EC50 85 N 125

E2 Elodea canadensis S plant wet weight increase 0-14 EC50 >3000 N 129

E2 Glyceria maxima shoot dry weight 14 EC50 >1610 190

E2 Glyceria maxima shoot fresh weight 14 EC50 >1610 190

E2 Glyceria maxima shoot shoot length 14 EC50 >1610 190

E2 Lagarosiphon major shoot fresh weight 14 EC50 825.4 191

E2 Lagarosiphon major shoot dry weight 14 EC50 >2878 191

E2 Lemna gibba frond number EC50 2.3 187

E2 Lemna minor S frond number 4 EC50 198 N 67

E2 Lemna minor S frond number (growth rate)

0-4 EC50 482 N 141

E2 Lemna minor S plant growth ? 2 EC50 14.5 N 172

E2 Lemna minor S plant growth ? 2 EC50 10.1 N 171

E2 Lemna minor S frond number 4 NOEC 32 N 67

E2 Lemna minor S frond number 4 LOEC 62 N 67

E2 Myriophyllum heterophyllum

S plant wet weight increase 0-14 EC50 >3000 N 133

E2 Myriophyllum spicatum shoot length 14 EC50 104.3 192

E2 Myriophyllum spicatum shoot fresh weight 14 EC50 908.6 192

E2 Myriophyllum spicatum shoot dry weight 14 EC50 >5018 192

E2 Najas sp. S plant wet weight 14 EC50 584 N 137

E2 Potamogeton crispus shoot length 14 EC50 >3075 189

E2 Potamogeton crispus shoot dry weight 14 EC50 >3075 189

E2 Potamogeton crispus shoot fresh weight 14 EC50 >3075 189

E2 Potamogeton pectinatus S plant/tuber wet weight increase 0-14 EC50 >1000 N 170

E2 Potamogeton pectinatus S plant/tuber wet weight increase 0-14 NOEC 1000 N 170










Meas/Nom

Study


S EC50 1.64 208



E2 Ranunculus penicillatus shoot dry weight 14 EC50 >4499 188

E2 Ranunculus penicillatus shoot fresh weight 14 EC50 >4499 188

E2 Ranunculus penicillatus shoot length 14 EC50 >4499 188

E3 Anabaena flos-aquae S EC50 1200 219



E3 Desmodesmus subspicatus

S EC50 57100 224

E3 Elodea canadensis S plant wet weight increase 0-14 EC50 2355 N 130

E3 Lemna gibba S plant biomass (dry weight)

14 EC50 43 MI 150

E3 Lemna gibba S EC50 48 218

E3 Lemna gibba S plant frond density 14 NOEC 8.4 MI 150

E3 Lemna gibba S plant frond density 14 EC50 51 MI 150

E3 Lemna gibba S plant biomass (dry weight)

14 NOEC 15 MI 150

E3 Lemna gibba R frond number 7 EC50 169 M 151

E3 Lemna gibba S EC50 >95400 223

E3 Lemna gibba S EC50 43000 225

E3 Lemna gibba F plant photosynthesis (oxygen production)

1 NOEC 250 N 147

E3 Lemna gibba R plant dry weight 7 EC50 78 M 151

E3 Lemna minor R frond number 7 EC50 >562 M 152

E3 Lemna minor S frond number (growth rate)

0-4 EC50 360 N 142

E3 Lemna minor S frond number 4 EC50 343 N 68

E3 Lemna minor S frond number 4 NOEC 187 N 68

E3 Lemna minor R plant dry weight 7 EC50 >575 M 152

E3 Lemna minor S frond number 4 LOEC 375 N 68

E3 Lemna paucicostata R plant dry weight 7 EC50 118 M 153

E3 Lemna paucicostata R frond number 7 EC50 511 M 153

E3 Myriophyllum heterophyllum

S plant wet weight increase 0-14 EC50 >3000 N 134

E3 Myriophyllum spicatum F plant photosynthesis (oxygen production)

1 NOEC 250 N 148

E3 Najas sp. S plant wet weight 14 EC50 242 N 138

E3 Navicula pelliculosa S EC50 380 222








S EC50 10 221

E3 Salvinia natans S plant chlorophyll b 28 EC50 50 N 149

E3 Salvinia natans S leaf number 28 EC50 75 N 149

E3 Salvinia natans S plant chlorophyll a 28 NOEC 10 N 149






Meas/Nom

Study

E3 Salvinia natans S plant chlorophyll b 28 LOEC 100 N 149

E3 Salvinia natans S plant chlorophyll a 28 LOEC 100 N 149

E3 Salvinia natans S plant chlorophyll a 28 EC50 80 N 149

E3 Salvinia natans S stem length 28 LOEC 1000 N 149

E3 Salvinia natans S stem length 28 NOEC 100 N 149

E3 Salvinia natans S stem length 28 EC50 550 N 149

E3 Salvinia natans S plant fresh weight 28 LOEC 1000 N 149

E3 Salvinia natans S plant fresh weight 28 NOEC 100 N 149

E3 Salvinia natans S plant fresh weight 28 EC50 150 N 149

E3 Salvinia natans S leaf number 28 NOEC 10 N 149

E3 Salvinia natans S plant chlorophyll b 28 NOEC 10 N 149

E3 Salvinia natans S leaf number 28 LOEC 100 N 149

E3 Skeletonema costatum S EC50 61 220

E4 Anabaena flos-aquae biomass 4 EC50 9400 290


S shoot length increase 0-14 EC10 2.3 M 2




S shoot length increase 0-14 NOEC 14.6 M 2










S shoot length increase 0-7 NOEC 14.6 M 2

E4 Chara intermedia S shoot length increase 0-7 EC20 6.0 M 4

E4 Chara intermedia S shoot length increase 0-7 NOEC 14.6 M 4

E4 Chara intermedia S shoot length increase 0-7 EC50 139 M 4

E4 Chara intermedia S shoot length increase 0-7 EC10 1.2 M 4

E4 Elodea densa S shoot length increase 0-13 NOEC <2.0 M 3

E4 Elodea densa S shoot length increase 0-7 EC50 25.6 M 3






E4 Elodea densa S shoot length increase 0-7 NOEC 5.4 M 2

E4 Heteranthera zosterifolia S shoot length increase 0-14 EC50 39.6 M 5


E4 Heteranthera zosterifolia S shoot length increase 0-14 NOEC 14.6 M 5


E4 Hygrophila polysperma S shoot length increase 0-14 EC20 31.6 M 6

E4 Hygrophila polysperma S shoot length increase 0-14 NOEC 39.4 M 6








Meas/Nom

Study

E4 Lemna minor R frond number (growth rate)

0-7 EC10 2.6 N 74


0-7 EC50 31.8 N 74

E4 Lemna minor R frond dry weight increase 0-7 NOEC 1.0 N 74

E4 Lemna minor biomass 14 EC50 7.9 292

E4 Lemna minor R frond dry weight increase 0-7 EC10 0.8 N 74

E4 Lemna minor R frond dry weight increase 0-7 EC50 39.5 N 74


0-7 NOEC 1.0 N 74

E4 Myriophyllum spicatum S shoot length increase 0-13 EC20 50.3 M 1



E4 Myriophyllum spicatum S shoot length increase 0-13 NOEC 106 M 1


biomass Day 3 EC50 1.95 291


growth Day 3 EC50 3.96 291

E4 Vallisneria spiralis S leaf length increase 0-21 EC20 0.2 M 7

E4 Vallisneria spiralis S leaf length increase 0-21 NOEC <2.0 M 7

E4 Vallisneria spiralis S leaf length increase 0-21 EC50 45.4 M 7

F1 Ceratophyllum demersum


F1 Elodea canadensis S plant wet weight increase 0-14 EC50 21 N 127

F1 Hydrilla verticillata EC50 110 261

F1 Lemna gibba S 14 EC50 37 260

F1 Lemna gibba F plant photosynthesis (oxygen production)

1 NOEC <25 N 144

F1 Lemna minor S frond number 4 NOEC 75 N 65

F1 Lemna minor S frond number 4 LOEC 150 N 65

F1 Lemna minor F plant photosynthesis (oxygen production)

1 NOEC <200 N 145

F1 Lemna minor S frond number (growth rate)

0-4 EC50 92 N 139

F1 Lemna minor S frond number 4 EC50 153 N 65

F1 Myriophyllum heterophyllum


F1 Myriophyllum spicatum S plant number of new structures

5 NOEC 30000 N 179

F1 Myriophyllum spicatum S plant branch number reduction

5 EC50 3700 N 177

F1 Myriophyllum spicatum S plant number of buds 5 NOEC 100000 N 179

F1 Myriophyllum spicatum S plant number of leaves 5 NOEC <100 N 179

F1 Myriophyllum spicatum S plant number of branches 5 NOEC 30000 N 179

F1 Myriophyllum spicatum F plant photosynthesis (oxygen production)

1 NOEC <200 N 146

F1 Myriophyllum spicatum S plant number of roots 5 NOEC 100000 N 179

F1 Najas sp. S plant wet weight 14 EC50 24 N 135

F1 Potamogeton pectinatus S plant/tuber wet weight increase 0-14 NOEC <100 N 169

F1 Pseudokirchneriella subcapitata









Meas/Nom

Study



F1 Thallassia testudinum EC50 320 262

F2 Anabaena flos-aquae S EC50 38.8 216


S shoot photosynthesis (fluorescence)

35 EC50 8.7 N 161

F2 Chara globularis S shoot photosynthesis (fluorescence)

1 EC50 12.1 N 159

F2 Elodea nuttallii S shoot photosynthesis (fluorescence)

1 EC50 13.4 N 155


35 EC50 8.3 N 160


1 EC50 9.0 M 154

F2 Lemna gibba R frond number (growth rate)

0-7 NOEC 10 N 175

F2 Lemna gibba R frond number (growth rate)

0-7 EC50 55 N 175

F2 Lemna gibba R plant biomass increase (dry weight)

0-7 NOEC 10 N 175

F2 Lemna gibba R plant biomass increase (dry weight)

0-7 EC50 21 N 175

F2 Lemna gibba S EC50 27.3 214

F2 Lemna minor R frond specific growth rate 0-7 NOEC 12.4 N 174

F2 Lemna minor R frond specific growth rate 0-7 EC50 62.0 N 174

F2 Lemna minor R frond biomass growth 0-7 EC50 46.5 N 174

F2 Lemna minor R frond biomass growth 0-7 NOEC 12.4 N 174

F2 Lemna minor R frond log biomass growth 0-7 EC50 77.5 N 174

F2 Lemna minor R frond log biomass growth 0-7 NOEC 12.4 N 174

F2 Lemna minor R plant log biomass dry weight

0-7 NOEC 12.4 N 174

F2 Lemna minor R plant log biomass dry weight

0-7 EC50 85.2 N 174

F2 Myriophyllum spicatum S plant number of buds 5 NOEC 100000 N 180

F2 Myriophyllum spicatum S shoot photosynthesis (fluorescence)

1 EC50 11.8 N 156

F2 Myriophyllum spicatum S plant number of new structures

5 NOEC 100000 N 180

F2 Myriophyllum spicatum S plant number of branches 5 NOEC 100000 N 180

F2 Myriophyllum spicatum S plant number of roots 5 NOEC 100000 N 180

F2 Myriophyllum spicatum S plant number of leaves 5 NOEC 100000 N 180

F2 Navicula pelliculosa S EC50 13.7 215

F2 Potamogeton crispus S shoot photosynthesis (fluorescence)

1 EC50 12.9 N 157


S EC50 67 213

F2 Ranunculus circinatus S shoot photosynthesis (fluorescence)

1 EC50 13.2 N 158

F2 Skeletonema costatum S EC50 35.9 217

F3 Anabaena flos-aquae S EC50 17 229



F3 Elodea canadensis S plant wet weight increase 0-14 EC50 21 N 128

F3 Lemna gibba S EC50 160 230






Meas/Nom

Study

F3 Lemna minor S frond number 4 LOEC 38 N 66

F3 Lemna minor R plant biomass 14 NOEC 0.58 N 173

F3 Lemna minor R frond number 0-14 EC50 13.3 N 173

F3 Lemna minor R frond number 0-14 NOEC 0.58 N 173

F3 Lemna minor R frond number 0-7 EC50 17.8 N 173

F3 Lemna minor R frond number 0-7 NOEC 1.0 N 173

F3 Lemna minor R plant biomass 14 EC50 7.9 N 173

F3 Lemna minor S frond number 4 NOEC 19 N 66

F3 Lemna minor S frond number 4 EC50 37 N 66

F3 Lemna minor S frond number (growth rate)

0-4 EC50 36 N 140

F3 Myriophyllum heterophyllum


F3 Najas sp. S plant wet weight 14 EC50 19 N 136

F3 Navicula pelliculosa S EC50 11.9 227


S EC50 20.8 226








S EC50 8.09 228

F3 Skeletonema costatum S EC50 80.88 231

F4 Anabaena flos-aquae S EC50 99 258

F4 Callitriche platycarpa R plant dry weight 14 EC50 158 M 34





R plant dry weight 14 EC50 196 M 42



F4 Ceratophyllum submersum








F4 Elodea canadensis R plant dry weight 14 EC10 64 M 37




F4 Lemna gibba S EC50 16 255

F4 Lemna minor R plant dry weight 14 EC50 40 M 28








Meas/Nom

Study

F4 Lemna minor R plant growth rate (dry weight)

0-14 EC50 153 M 29


F4 Lemna minor R plant growth rate (dry weight)

0-14 EC50 182 M 28

F4 Lemna minor S frond growth rate (area) 0-7 EC10 35 N 57




F4 Lemna trisulca R plant dry weight 14 EC50 254 M 30

F4 Lemna trisulca R plant dry weight 14 EC10 38 M 30

F4 Myriophyllum spicatum R plant dry weight 14 EC50 55 M 35

F4 Myriophyllum spicatum R plant dry weight 14 EC10 20 M 35

F4 Navicula pelliculosa S EC50 11 256

F4 Potamogeton crispus R plant dry weight 14 EC10 63 M 39





S EC50 3.2 259

F4 Skeletonema costatum S EC50 31 257

F4 Spirodela polyrhiza R plant dry weight 14 EC10 16 M 32





S plant photosynthesis (fluorescence)

21 EC50 1357.3 N 165


S plant relative growth 0-21 EC50 12.9 N 165

F5 Elodea canadensis S plant relative growth 0-21 EC50 23.4 N 168

F5 Elodea canadensis S plant photosynthesis (fluorescence)

21 EC50 44.5 N 168

F5 Elodea nuttallii S plant relative growth 0-21 EC50 11.8 N 166

F5 Elodea nuttallii S plant photosynthesis (fluorescence)

21 EC50 97.7 N 166

F5 Lemna minor S plant relative growth 0-21 EC50 198.9 N 167

F5 Lemna minor S plant photosynthesis (fluorescence)

21 EC50 130.4 N 167

F5 Lemna trisulca S plant photosynthesis (fluorescence)

21 EC50 36.1 N 164

F5 Lemna trisulca S plant relative growth 0-21 EC50 64.5 N 164

F5 Myriophyllum spicatum S plant relative growth 0-21 EC50 73.4 N 169

F5 Potamogeton crispus S plant relative growth 0-21 EC50 38.8 N 163

F5 Scenedesmus quadricauda

growth 0-12 EC50 1.429 285


photosynthesis 12 EC50 4.51 285


photosynthesis 2 EC50 18.62 286


chlorophyll 2 EC50 1 286






Meas/Nom

Study

F5 Scenedesmus subspicatus

growth 0-3 EC50 32 287

F5 Skeletonema costatum growth 0-3 EC50 0.86 288

F5 Spirodela polyrhiza S plant relative growth 0-21 EC50 4.6 N 162

F5 Spirodela polyrhiza S plant photosynthesis (fluorescence)

21 EC50 33.1 N 162

F5 Thalassiosira guillardii growth 0-3 EC50 1.09 289

Documents

The Relative Sensitivity of Macrophyte and Algal Species ......Macrophyte toxicity data were compiled from open literature and from confidential test reports provided by participating