Herbicide Persistence and Toxicity in the Tropical Marine Environment Mr

Herbicide persistence and toxicity in the tropical marine environment

Mr. Philip Mercurio III

MSc, BSc (Honours)

A thesis submitted for the degree of Doctor of Philosophy at The University of Queensland in 2016

School of Medicine National Research Centre for Environmental Toxicology (Entox) Faculty of Medicine and Biomedical Sciences

Abstract

Agricultural herbicides are ubiquitous in the nearshore water bodies of the World Heritage listed Great Barrier Reef (GBR). The main transport mechanism for herbicides is via offsite migration during intense monsoonal rainfall events of the wet season. However, some herbicides can be detected year round, indicating potentially long persistence. Despite the high mobility and potential toxicity of herbicides, there is very little information on the degradation of herbicides in the marine environment. This study was comprised of 4 major components: (i) flask experiments to test herbicide degradation over 60 days; (ii) an extended flask experiment for 365 days including light and temperature treatments; (iii) an outdoor open tank experiment for 365 days with light and sediment treatments; and (iv) experiments to examine the potential toxicity of transformation products. The flask degradation experiments were designed to mimic natural conditions including low herbicide concentrations, relevant temperatures and light and the inclusion of natural microbial communities. Very little degradation was recorded over the standard 60 d period (Experiment 1). The second experiment over 365 d revealed half-lives of PSII herbicides ametryn, atrazine, diuron, hexazinone and tebuthiuron were consistently greater than a year. The detection of atrazine and diuron metabolites and longer persistence in mercuric chloride-treated seawater confirmed that biodegradation contributed to the breakdown of herbicides. The shortest half-lives were recorded for non-PSII herbicides: 47 d for glyphosate; 88 d for 2,4-D and 281 d for metolachlor. The presence of low light and elevated temperatures affected the persistence of most of the herbicides; however, the scale and direction of the differences were not predictable and were likely due to changes in microbial community composition. The environmental relevance of the degradation experiments were further improved in non- standard 365 d long experiments conducted in large open tanks, under different light scenarios and in the presence and absence of coastal sediments. All PSII herbicides were persistent under control conditions (dark, no sediments) with half-lives of 300 d for atrazine, 499 d diuron, 1994 d hexazinone, 1766 d tebuthiuron, while the non-PSII herbicides were less persistent 147 d metolachlor and 59 d for 2,4-D. The degradation of all herbicides was 2 – 10 fold more rapid in the presence of a diurnal light cycle and coastal sediments; whereas, 2,4-D degraded more slowly in the presence of light. Despite the more rapid degradation observed for most herbicides in the presence of light and sediments, the half-lives remained greater than 100 d for the photosystem II herbicides. Finally, to assess the potential contribution of toxicity by transformation products of four priority PSII herbicides, I directly compared the acute toxicity of partially degraded herbicides

(including transformation products) with their parent herbicide to: (i) coral symbionts (Symbiodinium sp.) and (ii) the green algae Dunaliella sp. (iii) prawn (Penaeus monodon) larvae.

Concentration dependent effects on photosynthetic efficiency (∆F/Fm’) by all parent herbicides was observed in both phototrophic test species. The toxicity in all degraded solutions could be accounted for by the measured concentrations of the parent compound apart from diuron. The increased potency of the degraded diuron solution may be due to transformation products; however, it was unlikely to be caused by the most well-known breakdown product 3,4-DCA, which did not inhibit ∆F/Fm’ in Symbiodinium sp. at concentrations detected in the degraded mixture. Parent herbicides affected prawn larval metamorphosis only at unrealistically high concentrations (≥ 1000 µg l-1). In contrast, larval prawn metamorphosis was sensitive to the transformation products of atrazine, with both DIA and DEA, significantly inhibiting metamorphosis at 3.5 and 3.8 µg l-1, respectively. These transformation products may have contributed to inhibition observed in the degraded atrazine mixtures. 3,4-DCA caused significant inhibition in metamorphosis at 188 µg l-1 and was likewise more toxic to prawn larvae than its parent herbicide diuron. Reliable data on the persistence of chemicals is important for the development of fate models applied to the spatial and seasonal distribution of these chemicals and associated the much needed risk assessments for priority herbicides found in the GBR. The experiments found that: (i) PSII herbicides were more persistent in seawater than common non-PSII herbicides in the presence of natural microbial communities; (ii) environmental conditions including temperature, light and sediments has strong influences on degradation rates, probably due to differences in microbial communities and (iii) some but not all degradation mixtures can be more toxic to phototrophic and non-phototrophic species than expected from the contributions of the parent herbicides. These experiments generated some of the most relevant and reliable data available on the persistence of high priority herbicides but more information is needed to improve our understanding of the potential persistence of emerging pesticides. The potential contribution of herbicide transformation products to total toxicity highlights the need to test the sensitivity of a broader range of non-target species that may be exposed in natural waters, including the GBR.

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Declaration by author

This thesis is composed of my original work, and contains no material previously published or written by another person except where due reference has been made in the text. I have clearly stated the contribution by others to jointly-authored works that I have included in my thesis.

I have clearly stated the contribution of others to my thesis as a whole, including statistical assistance, survey design, data analysis, significant technical procedures, professional editorial advice, and any other original research work used or reported in my thesis. The content of my thesis is the result of work I have carried out since the commencement of my research higher degree candidature and does not include a substantial part of work that has been submitted to qualify for the award of any other degree or diploma in any university or other tertiary institution. I have clearly stated which parts of my thesis, if any, have been submitted to qualify for another award.

I acknowledge that an electronic copy of my thesis must be lodged with the University Library and, subject to the policy and procedures of The University of Queensland, the thesis be made available for research and study in accordance with the Copyright Act 1968 unless a period of embargo has been approved by the Dean of the Graduate School.

I acknowledge that copyright of all material contained in my thesis resides with the copyright holder(s) of that material. Where appropriate I have obtained copyright permission from the copyright holder to reproduce material in this thesis.

Publications during candidature

Peer-reviewed papers Angly, F.E., Pantos, O., Morgan, T.C., Rich, V., Tonin, H., Bourne, D.G., Mercurio, P., Negri, A.P., Tyson, G.W. (2016). Diuron tolerance and potential degradation by pelagic microbiomes in the Great Barrier Reef lagoon. PeerJ 4:e1758; DOI 10.7717/peerj.1758

Mercurio, P., Mueller, J.F., Eaglesham, G., Flores, F., and Negri, A. P. (2015). Herbicide persistence in seawater simulation experiments. PLoS ONE. 10.1371/journal.pone.0136391

Negri AP, Flores F, Mercurio P, Mueller JF, Collier CJ. (2015). Lethal and sub-lethal chronic effects of the herbicide diuron on seagrass. Aquat Toxicol. 165: 73-83.

Wilkinson AD, Collier CJ, Flores F, Mercurio P, O’Brien J, Ralph PJ, Negri, AP (2015). A miniature bioassay for testing the acute phytotoxicity of photosystem II herbicides on seagrass. PLoS ONE. 10.1371/journal.pone.0117541

Mercurio, P., Flores, F., Mueller, J.F., Carter, S., Negri, A.P. (2015). Glyphosate persistence in seawater. Mar Pollut Bull. 85:385-90.

Flores F, Collier CJ, Mercurio P, Negri AP (2013). Phytotoxicity of four photosystem II herbicides to tropical seagrasses. PLoS ONE. 10.1371/journal.pone.0075798

Non-peer-reviewed papers Smith, R., Warne, M, Silburn, M., Lewis, S., Martin, K., Mercurio, P., Borschmann, G., and Vandergragt, M. (2015). Pesticide transport, fate and detection. In: Advancing our understanding of the source, management, transport and impacts of pesticides on the Great Barrier Reef 2011‐2015. A report for the Queensland Department of Environment and Heritage Protection. Devlin, M. Lewis, S. Davis, A. Smith, R. Negri, A. Thompson, M. Poggio, M. (Eds). Tropical Water & Aquatic Ecosystem Research (TropWATER) Publication, James Cook University, Cairns, 134 pp.

Lewis, S., Brodie, J., Davis, A., Eaglesham, G., Elledge, A.E., Gallen, C., Paxman, C., Negri, A.P., Flores, F., Mercurio, P., Mueller, J., O'Brien, D., Packett, B., Rojas, S., Shaw, M., Silburn, M., Smith, R., Thornton, C.M., Turner, R., Warne, M. (2014). Pesticide dynamics in the Great Barrier Reef catchment and lagoon: Management practices (sugar, grazing, bananas) and risk assessments. Overview report for project number RRRD037 and RRRD038. Report to the Reef Rescue Water

Quality Research & Development Program. Reef and Rainforest Research Centre Limited, Cairns (22pp.). ISBN 78-1-925088-24-3

Negri, A.P., Mercurio, P., Flores, F., and Mueller, J.F. (2013). Pesticide dynamics in the Great Barrier Reef catchment and lagoon: grazing, bananas and grain. Herbicide persistence in the marine environment. Report to the Reef Rescue Water Quality Research & Development Program. Reef and Rainforest Research Centre Limited, Cairns (26pp).

Publications included in this thesis

Publication citation – incorporated as Chapter 2. Mercurio, P., Mueller, J.F., Eaglesham, G., Flores, F., and Negri, A. P. (2015). Herbicide persistence in seawater simulation experiments. PLoS ONE. 10.1371/journal.pone.0136391 Contributor Statement of contribution Mercurio Designed experiments (60%) Wrote the paper (70%) Performed the experiments (75%) Mueller Designed experiments (20%) Wrote the paper (10%) Performed the experiments (NA) Eaglesham Designed experiments (NA) Wrote the paper (5%) Performed the experiments (15%) Flores Designed experiments (NA) Wrote the paper (5%) Performed the experiments (10%) Negri Designed experiments (20%) Wrote the paper (10%) Performed the experiments (NA)

Publication citation – incorporated as Chapter 3. Mercurio, P., Flores, F., Mueller, J.F., Carter, S., Negri, A.P. (2015). Glyphosate persistence in seawater. Mar Pollut Bull. 85:385-90. Contributor Statement of contribution Mercurio Designed experiments (60%) Wrote the paper (75%) Performed the experiments (75%) Flores Designed experiments (NA) Wrote the paper (5%) Performed the experiments (10%) Mueller Designed experiments (20%) Wrote the paper (10%) Carter Designed experiments (NA) Wrote the paper (5%) Performed the experiments (15%) Negri Designed experiments (20%) Wrote the paper (10%) Performed the experiments (NA)

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Contributions by others to the thesis

I would like to thank the following people for their contributions to the thesis, as co-authors, and/or for their help and support throughout my experimental work: Andrew Negri (AIMS), Jochen Mueller (Entox, UQ), Geoff Eaglesham (Entox, UQ), Florita Flores (AIMS), Steve Carter (Forensic and Scientific Services, Health Services Support Agency, QLD Department of Health), Jake O’Brien (Entox, UQ), Matt Kenway (AIMS), Cassandra Thompson (JCU/AIMS), Victor Beltran (AIMS), Tom Barker (AIMS), Stephen Parks (JCU), Karen Weynberg (AIMS), Philip Kearns (AIMS), and Scott Turner (Queensland Health).

Statement of parts of the thesis submitted to qualify for the award of another degree

None

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Acknowledgements

I would first like to thank my family. I would not have been able to do this without their continued support, love, encouragement, and patience.

For my PhD, I could not have asked for better supervisors: Andrew Negri and Jochen Mueller. It was only through their tireless efforts and mentoring that made this possible.

I am thankful for this very practical and well thought-out project that I was able to work on. This project was co-funded through the National Environmental Research Program (NERP) and the Australian Government’s Caring for our Country initiative.

I was only able to participate in this PhD due to the generous scholarships obtained though UQ. For those I am grateful.

In addition to the great academic and support staff at AIMS and Entox, I would also like to thank: Helios Martinez, Courtney Remilton (Manager Seafarm Hatchery), Bastien Finet (Pacific Reef Fisheries Technologies Pty Ltd.), Trey Anastasio, Mike Gordon, Jon Fishman, Page McConnell, Jeff Holdsworth, Marc Daubert, Jack Johnson, Dave Matthews, David Gilmour, Roger Waters, Richard Wright, Nick Mason, Michael Diamond, Adam Yauch, Adam Horovitz, and Alexi Murdoch.

Keywords

Herbicides, Persistence, Degradation, Seawater, Tropical, Microbial, Toxicity, Ecotoxicology

Australian and New Zealand Standard Research Classifications (ANZSRC)

ANZSRC code: 039901 Environmental Chemistry, 70% ANZSRC code: 111506 Toxicology, 30%

Fields of Research (FoR) Classification

FoR code: 0305 Organic Chemistry, 70% FoR code: 0699, Other Biological Sciences, 30%

This is dedicated to my Big Love (Reegan) and Little Love (Callia).

Table of Contents

Chapter 1: Fate of herbicides in tropical marine environments ...... 1 1.1 Abstract ...... 1 1.2 Background ...... 1 1.2.1 The issue, Green Revolution, what are herbicides, herbicide dependence ...... 1 1.2.2 Herbicide use in the GBR and detection in the GBRWHA ...... 2 1.2.3 Herbicides detected in the GBR ...... 5 1.2.4 Are the pesticides in the water or the sediments? ...... 7 1.2.5 Modes of herbicide degradation ...... 7 1.2.6 The degradation of priority herbicides in the GBR ...... 8 1.2.7 Data gaps and priorities to improve risk assessments for herbicide movement, persistence and risk in the context of the GBR...... 12 1.3 Objectives and structure of thesis ...... 14 1.4 References ...... 15 Chapter 2: Herbicide persistence in seawater simulation experiments ...... 21 2.1 Abstract ...... 21 2.2 Introduction ...... 21 2.2.1 Runoff affecting the Great Barrier Reef ...... 21 2.2.2 PSII herbicides in the GBR ...... 22 2.2.3 Herbicide persistence in seawater ...... 22 2.3 Materials and Methods ...... 24 2.3.1 Experiment 1 ...... 25 2.3.2 Experiment 2 ...... 25 2.3.3 Herbicide analysis ...... 26 2.3.4 Water chemistry ...... 27 2.3.5 Flow cytometry ...... 28 2.3.6 Data analysis ...... 28 2.4 Results ...... 29 2.4.1 Experiment 1 ...... 29 2.4.2 Experiment 2 ...... 29 2.5 References ...... 38 Chapter 3: Glyphosate persistence in seawater ...... 42 3.1 Abstract ...... 42 3.2 Introduction ...... 42 3.2.1 Water quality and pesticides in the Great Barrier Reef ...... 42 3.2.2 Glyphosate monitoring and toxicity ...... 43 3.2.3 Glyphosate persistence in water ...... 43

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3.3 Methods ...... 44 3.3.1 Simulation test conditions ...... 44 3.3.2 Flow cytometry ...... 45 3.3.3 Glyphosate analysis ...... 45 3.3.4 Data analysis ...... 46 3.4 Results and Discussion ...... 47 3.4.1 Microbial abundance ...... 47 3.4.2 Glyphosate degradation and the formation of AMPA ...... 47 3.4.3 Glyphosate persistence in seawater ...... 48 3.4.4 Application of results from the simulation test ...... 49 3.5 References ...... 50 Chapter 4: Degradation of herbicides in the tropical marine environment: Influence of light and sediment ...... 54 4.1 Abstract ...... 54 4.2 Introduction ...... 54 4.3 Materials and Methods ...... 56 4.3.1 Approach and experimental design ...... 56 4.3.2 Sediments and water ...... 57 4.3.3 Herbicide addition, sampling and analysis ...... 57 4.3.4 Data analysis ...... 58 4.4 Results ...... 58 4.4.1 Overview ...... 58 4.4.2 Degradation rates in the dark no sediments ...... 59 4.4.3 Light and sediment effects ...... 59 4.4.4 Metabolites ...... 66 4.4.5 Herbicides in sediments ...... 66 4.5 Discussion ...... 67 4.6 References ...... 71 Chapter 5: Contribution of transformation products to the total herbicide toxicity in tropical marine organisms ...... 75 5.1 Abstract ...... 75 5.2 Introduction ...... 76 5.3 Methods ...... 78 5.3.1 Degraded herbicide material production ...... 78 5.3.2 Sediments and water ...... 78 5.3.3 Herbicide addition, sampling and analysis ...... 78 5.3.4 Microalgae assay ...... 80 5.3.5 Microalgal cultures ...... 80 xiii

5.3.6 Plate loading and experimental conditions ...... 81 5.3.7 Prawn larvae assay ...... 81 5.3.8 Prawn larvae collection and experimental conditions ...... 81 5.3.9 Metamorphosis assay on naupliar development ...... 82

5.3.10 Data handling, IC50 handling and modelling ...... 82 5.4 Results ...... 83 5.4.1 Symbiodinium / Dunaliella assay ...... 83 5.4.2 Larval prawn assay ...... 85 5.4.3 Herbicide degradation and identification of transformation products ...... 87 5.5 Discussion ...... 90 5.6 References ...... 93 Chapter 6: Summary of research outcomes and conclusions ...... 98 6.1 Objective, aims, and completion ...... 98 6.2 Summary and future directions ...... 104 6.3 References ...... 105 Appendix ...... 107

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List of Figures

Figure 1.1: Satellite image depicting flood plumes travelling 50 km offshore to the Great Barrier Reef...... 5

Figure 1.2: Example degradation pathways for atrazine, cyanazine, propazine, and simazine to DEA and/or DIA...... 9

Figure 2.1: Experiment 1 half-life results. ln(x) concentration of the herbicide mixture: (a) tebuthiuron, (b) ametryn, (c) hexazinone, (d) simazine, (e) atrazine, and (f) diuron over 60 days ...... 31

Figure 2.2: Experiment 2 half-life results for diuron and atrazine. ln(x) concentration of individual herbicide treatments: (a) diuron dark 25°C, (b) diuron light 25°C, (c) diuron dark 31°C, (d) atrazine dark 25°C, (e) atrazine light 25°C, and (f) atrazine dark 31°C over 365 days...... 32

Figure 2.3: Experiment 2 half-life results for hexazinone and tebuthiuron. ln(x) concentration of individual herbicide treatments: (a) hexazinone dark 25°C, (b) hexazinone light 25°C, (c) hexazinone dark 31°C, (d) tebuthiuron dark 25°C, (e) tebuthiuron light 25°C, and (f) tebuthiuron dark 31°C over 365 days...... 33

Figure 2.4: Experiment 2 half-life results for metolachlor and 2,4-D. ln(x) concentration of individual herbicide treatments: (a) metolachlor dark 25°C, (b) metolachlor light 25°C, (c) metolachlor dark 31°C, (d) 2,4-D dark 25°C, (e) 2,4-D light 25°C, and (f) 2,4-D dark 31°C over 365 days...... 34

Figure 2.5: Concentration of metabolites of diuron and atrazine. Concentrations of individual herbicides including measured metabolites (a) diuron light 25°C, (b) atrazine dark 25°C, (c) atrazine light 25°C, and (d) atrazine dark 31°C, over 365 days ...... 35

Figure 3.1: Concentration of glyphosate and AMPA for each treatment: Dark 25°C, Dark 31°C, and Light 25°C during the experiment duration ...... 48

Figure 3.2: Natural log of glyphosate concentrations (μg l-1) and half-life (t½) for each treatment: Dark 25°C, Dark 31°C, and Light 25°C ...... 49

Figure 4.1: Experiment half-life results for diuron. ln(x) concentration of individual herbicide in PSII mixture for treatments: (A) Dark no sediment, (B) Light no sediment, (C) Dark with sediment, and (D) Light with sediment sampled up to 10 times over 365 days...... 60

Figure 4.2: Experiment half-life results for atrazine. ln(x) concentration of individual herbicide in PSII mixture for treatments: (A) Dark no sediment, (B) Light no sediment, (C) Dark with sediment, and (D) Light with sediment sampled up to 10 times over 365 days...... 61

Figure 4.3: Experiment half-life results for hexazinone. ln(x) concentration of individual herbicide in PSII mixture for treatments: (A) Dark no sediment, (B) Light no sediment, (C) Dark with sediment, and (D) Light with sediment sampled up to 10 times over 365 days...... 62

Figure 4.4: Experiment half-life results for tebuthiuron. ln(x) concentration of individual herbicide in PSII mixture for treatments: (A) Dark no sediment, (B) Light no sediment, (C) Dark with sediment, and (D) Light with sediment sampled up to 10 times over 365 days...... 63

Figure 4.5: Experiment half-life results for metolachlor. ln(x) concentration of individual herbicide in non-PSII mixture for treatments: (A) Dark no sediment, (B) Light no sediment, (C) Dark with sediment, and (D) Light with sediment sampled up to 10 times over 365 days ...... 64

Figure 4.6: Experiment half-life results for 2,4-D. ln(x) concentration of individual herbicide in non-PSII mixture for treatments: (A) Dark no sediment, (B) Light no sediment, (C) Dark with sediment, and (D) Light with sediment sampled up to 10 times over 365 days ...... 65

Figure 4.7: Concentration of metabolites of atrazine: DEA and DIA. Concentration (μg l-1) of individual herbicide metabolite in herbicide PSII mixture for treatments: (A) Dark no sediment, (B) Light no sediment, (C) Dark with sediment, and (D) Light with sediment sampled up to 10 times over 365 days...... 67

Figure 5.1: Concentration response curves for herbicides and their transformation products to microalgae. Inhibition of ∆F/Fm’ (% relative to control) for Symbiodinium sp. and Dunaliella sp. for both herbicide and degraded herbicides ...... 84

Figure 5.2: PAM inhibition data as compared to controls for Symbiodinium sp. and Dunaliella sp. for the atrazine transformation product DEA...... 86

Figure 5.3: Concentration response relationships for herbicides and their transformation products to prawn larvae...... 88

Figure 6.1: Flow chart of thesis and experiments designed to fulfil objectives and aims...... 101

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List of Tables

Table 1.1: Some herbicides found in the GBR lagoon, mode of action, and example degradation products...... 3

Table 1.2: Published literature on the degradation half-life experiments in seawater...... 10

Table 1.3: Published literature on the degradation half-life experiments in freshwater...... 11

Table 2.1: Published literature on the degradation half-life experiments in seawater ...... 24

Table 2.2: Experimental details of two degradation experiments investigating herbicide degradation in (1) filtered seawater and (2) unfiltered seawater ...... 26

Table 2.3: Experiment 1 and 2 half-lives ...... 29

Table 2.4: The ratio of half-lives between each treatment from experiment 2 ...... 37

Table 3.1: Example glyphosate concentrations in the aquatic and marine environment ...... 44

Table 3.2: Published glyphosate biodegradation half-life estimates in soil and fresh waters...... 45

Table 3.3: Mean and SEs for each treatment for pH, dissolved oxygen (DO), and total bacterial counts...... 47

Table 4.1: Four experimental treatments in the 40-tank open tank experiment ...... 56

Table 4.2: Experiment half-lives (days ± SE)...... 66

Table 4.3: The persistence ratio of half-lives between each treatment relative to “control” (dark, no sediment) conditions...... 66

-1 Table 5.1: Comparison of IC50 (µg l ) values of standard parent herbicides and degraded mixtures (after 330 d) from each herbicide ...... 85

-1 Table 5.2: Comparison of IC20 and IC10 (µg l ) values of atrazine and transformation product DEA for Symbiodinium sp. and Dunaliella sp...... 87

Table 5.3: Effects of herbicides and their transformation products on the success of prawn larval metamorphosis ...... 87

Table 5.4: Initial herbicide concentration (µg l-1) and day 330, when the experiment was terminated 89

Table 6.1: Experimental half-lives (days ± SE) ...... 103

Appendix Table 1: Quantification and confirmation ions used for herbicide analysis...... 107

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Appendix Table 2: Mean ± SE for each treatment for pH, dissolved oxygen (DO), and total bacterial counts for Experiment 1 and 2 ...... 108

Appendix Table 3: Physical and chemical information for the 0.45 µm and 20 µm filtered seawater used in experiment 1 and experiment 2 ...... 109

Appendix Table 4: Results of Experiment 1 including first order half-life estimates, slopes, r2, average initial concentration, average final concentration, total average degradation ...... 110

Appendix Table 5: Results of Experiment 2 including first order half-life estimates, slopes, r2, average initial concentration, average final concentration, total average degradation ...... 111

Appendix Table 6: Results of statistical testing of Experiment 1 and Experiment 2 ...... 112

Appendix Table 7: Results of statistical testing of Experiment 2 ...... 113

Appendix Table 8: Relevant literature on the degradation half-life experiments in freshwater...... 114

Appendix Table 9: Physical and chemical information for the 20 µm filtered seawater used in the glyphosate persistence experiment...... 115

Appendix Table 10: Glyphosate and AMPA concentrations (μg l-1) for each treatment: Dark 25°C, Dark 31°C, and Light 25°C during the course of the flask degradation experiment ...... 116

Appendix Table 11: The range of physical and chemical information for the seawater and sediment used in the open tank experiment...... 117

Appendix Table 12: Recovery of analytes in sediment extraction using Agilent Quenchers...... 117

Appendix Table 13: Repeated measures ANOVA testing significance of degradation over time...... 118

Appendix Table 14: Herbicide concentrations in sediments (µg kg-1) ...... 119

Appendix Table 15: Results of statistical testing: Two- tailed test for differences between slopes (k)...... 120

Appendix Table 16: Flow cytometry bacterial counts at Time 0 and Time 365 ...... 121

Appendix Table 17: Physical and chemical information for the seawater used in open tank...... 122

Appendix Table 18: Transformation products measured in degraded herbicide samples...... 122

Appendix Table 19: ABSciex 5500 QTrap acquisition parameters ...... 123

Appendix Table 20: ABSciex 5600 TripleTOF acquisition parameters...... 124

Appendix Table 21: Concentrations (µg l-1) of parent and transformation products in degraded solutions for all concentrations used in microalgae experiment...... 125

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Appendix Table 22: One way ANOVA results for the effect of transformation products on microalgae ∆F/Fm’ ...... 127

Appendix Table 23: One way ANOVA results for the effect of parent herbicides, transformation products and degraded herbicide mixtures on larval prawn metamorphosis ...... 127

Appendix Table 24: Herbicide and transformation products concentrations (µg l-1) used in the larval prawn experiment...... 128

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List of Abbreviations

3,4-DCA = 3,4-dichloroaniline AIMS = Australian Institute of Marine Science AMPA = aminophosphonic acid ANOVA = analysis of variance AVPMA = Australian Pesticides and Veterinary Medicines Authority BDL = Below detection limit CI = Confidence interval d = day(s) D25 = Dark 25°C D31 = Dark, 31°C DEA = desethylatrazine DF = degrees of freedom DIA = desisopropylatrazine DIC = dissolved inorganic carbon DIN = dissolved inorganic nitrogen DO = dissolved oxygen DOC = dissolved organic carbon DON = dissolved organic nitrogen EPA = Environmental Protection Agency F or f-ratio = ratio of two mean square values GBR = Great Barrier Reef GBRMPA = Great Barrier Reef Marine Park Authority GBRWHA = Great Barrier Reef World Heritage Area HPLC-MS = High Performance Liquid Chromatography Mass Spectrometry Koc = Soil Organic Carbon-Water Partitioning Coefficient L25 = Light, 25°C LED = light-emitting diode MC= mercuric chloride MRM = multiple reaction-monitoring n = number (of replicates) NA = Not applicable NCSS = Number Cruncher Statistical System NS = not significant OECD = Organisation for Economic Co-operation and Development P = probability PSII = photosystem II PSU = Practical Salinity Unit QuEChERS = Quick, easy, cheap, effective, rugged and safe rpm = rotations per minute SE = standard error TSS = total suspended solids UV = ultraviolet

Chapter 1: Fate of herbicides in tropical marine environments

1.1 Abstract

Herbicides are applied in agriculture to control pest weeds but in tropical ecosystems can be detected in nearshore marine waters in association with flood plumes from intense summer rainfall. Many of these herbicides are toxic to non-target marine species such as seagrass and corals and the detection of herbicides in nearshore waters in the dry winter season indicates they may have long persistence in seawater. Herbicides are thought to degrade primarily via microbial degradation with some contribution by hydrolysis and photodegradation, but despite the potential for movement off farms and toxicity to non-target species, there is very little information on the persistence of herbicides in the marine environment. The available published data is not generally reliable as experiments were either performed over very short periods that do not enable accurate predictions of half-lives, or were performed with unrealistically high concentrations of herbicides which can affect apparent persistence. Furthermore, persistence of herbicides in tropical marine systems is likely to be affected by higher temperatures, a variety of light conditions and local sediment types, none of which has been tested. Currently there are only a limited number of herbicide transformation products that are being monitored in the GBR and we do not understand the potential contribution of transformation products to the toxicity of seawater as the herbicides naturally degrade. Understanding (i) the persistence of herbicides currently detected in nearshore waters of the GBR and (ii) the potential contribution of known and unrecognised herbicide transformation products will greatly improve future risk assessments for the GBR and other marine systems.

1.2 Background

1.2.1 The issue, Green Revolution, what are herbicides, herbicide dependence

The Green Revolution was a collective effort from as early as the 1940’s to the late 1970’s to combat food shortages and famine in developing nations. This effort targeted many aspects of the agricultural industry such as breeding improved varieties of crops, alternate irrigation methods, expanded fertilizer use, and the marked increase usage of pesticides. While these efforts lead to improved crop yields and better nutrition, the reliance upon these types of chemicals has come at an environmental cost (Cleaver, 1972; Hazell and Institute, 2002; Pimentel, 1996).

Pesticides are a diverse group of compounds, both natural and synthetic, used to control pests such as insects, fungus, rodents, and weeds. Often the term pesticide can relate to the overall chemical class or to a specific category like herbicides which specifically target weeds. The different herbicide classes kill weeds using a variety of modes of action and these include inhibition of photosynthesis, amino acid production and growth regulation (See Table 1.1 for examples). Overall use has continued to increase and the types of pesticides in use changes due to both more restrictive regulations and the development of more effective and less toxic and persistent alternatives (Kookana and Simpson, 2000; Zhang et al., 2011). The main use for herbicides has been the agricultural industry for the control of weeds in row crops, vineyards, and orchards (Heri et al., 2008). Specifically they are used in the production of corn/maize, bananas, citrus, coffee, and sugarcane to name a few. Additional crop applications include nursery crops and Christmas tree production (Heri et al., 2008). Herbicides are also used in forestry, on golf courses, residential gardens, weed control for hatchery ponds, and algae control in swimming pools (Heri et al., 2008). Other non-agricultural uses include land clearing, railroad tracks, and as antifoulant on ship hulls (Heri et al., 2008; Okamura, 2002; Thomas et al., 2002; Voulvoulis et al., 2002). Herbicides offered a labour saving technology which allowed farmers to focus on improving other aspects of the industry including water saving technologies and increased crop yields. For example, when the herbicide 2,4-D was first introduced to the sugarcane industry, a single backpack type herbicide sprayer could be as effective with longer lasting results than 15 labourer with hoes at weed management (Smith et al., 2008). The herbicide atrazine enabled corn farmers in the US to increase four-fold the land area that they could grow on and manage (Heri et al., 2008). Atrazine also allowed corn to be grown and become profitable in areas of the world where it would not normally be possible (Heri et al., 2008). While there is no doubt the development and widespread uptake of herbicides has improved the efficiency of food production globally, the development of resistant weeds and exposure and toxicity of herbicides to non-target species has also become a major global concern (see Section: Main herbicides found in the GBR).

1.2.2 Herbicide use in the GBR and detection in the GBRWHA

The Great Barrier Reef World Heritage Area (GBRWHA) consists of 3000 reefs spanning 1800 km along the Queensland coast (Roff, 2010). Extensive crops including sugarcane have been developed on cleared land in adjacent catchments that drain into the GBR lagoon. When herbicides are applied to this agricultural land, the main transport mechanism for offsite migration is from

Table 1.1: Some herbicides found in the GBR lagoon, mode of action, and example degradation products.

Herbicide IUPAC name Substance Mode of Koc Example transformation Structure group/Class action products [Chemspider ID*] 2,4-D 2,4-Dichlorophenoxyacetic acid Phenoxy- Auxin 88.4 2,4-dichlorophenol alkane growth regulator

[1441] Ametryn 2-ethylamino-4- Triazine Photosystem 316 3 metabolites: 2- isopropylamino-6-methylthio- II inhibition methylthio-4-amino-6- 1,3,5-triazine and other isopropylamino-s- enzymatic triazine (GS-11354); 2- processes methylthio-4,6-diamino- s-triazine (GS-26831); and 2-methylthio-4- amino-6-ethylamino-s- [12705] triazine (GS-11355) Atrazine 2-chloro-4-(ethylamino)-6- Triazine Photosystem 100 desisopropylatrazine (isopropylamino)-s-triazine II inhibition (DIA); desethylatrazine (DEA); hydroxyatrazine desethylhydroxyatrazine (DEHA); desisopropyl- 2-hydroxyatrazine (DIHA)

[2169] Diuron DCMU (3-(3,4- Phenylurea Photosystem 813 3,4-dichloroaniline**; dichlorophenyl)-1,1- II inhibition 1-(3-chlorophenyl)-3,1- dimethylurea) dimethylurea (CPDU); 1-(3,4-dichlorophenyl)- 3-methylurea (DCPMU); and 1-(3,4- dichlorophenyl)urea (DCPU) [3008] Glyphosate N-(phosphonomethyl) glycine Phosphono- Inhibition of 1435 aminomethylphosphonic glycine the acid (AMPA) synthesis of aromatic compounds

[3376] Hexazinone 3-Cyclohexyl-6-dimethylamino- Triazinone Photosystem 54 3-cyclohexyl-1-methyl- 1-methyl-1,3,5-triazine-2,4- II inhibition 6- dione methylamino-1,3,5- triazine- 2,4(1H,3H)dione; 3- (4- hydroxycyclohexyl)-6- (dimethyl-amino)-1- methyl-1- (1H,3H)- [36542] dione; and the triazine trione 3

Table 1.1 continued Herbicide IUPAC name Substance Mode of Koc Example transformation Structure group/Class action products [Chemspider ID*] Metolachlor (RS)-2-Chloro-N-(2-ethyl-6- Chloro- Amino acid 120 transformed to methyl-phenyl)-N-(1- acetamide inhibitor ethanesulfonic (ESA) methoxypropan-2-yl)acetamide and oxanilic acid (OA) degradation products

[4025] Simazine 6-chloro-N,N'-diethyl-1,3,5- Triazine Photosystem 130 desisopropylatrazine triazine-2,4-diamine II inhibition (DIA); hydroxysimazine; 2- chloro-4,6-diamino- 1,3,5- triazine; atrazine desethyl desisopropyl- 2-hydroxy

[5027] Tebuthiuron 1-(5-tert-Butyl-1,3,4-thiadiazol- Urea Photosystem 80 N-[5-(1,1- 2-yl)-1,3-dimethylurea II inhibition dimethylethyl)-1,3,4- thiadiazol-2-yl]-N- methylurea; N-[5-(1,1- dimethylethyl)-1,3,4- thiadiazol-2-yl]-N'- methylurea; [5190] 5-(1,1-dimethylethyl)-2 methylamino-1,3,4- thiadiazole; 5-(1,1-dimethylethyl)-2 amino-1,3,4- thiadiazole; N-[5-(1,1- dimethylethyl)-1,3,4- thiadiazol-2-yl]-N- methyl-N'- hydroxymethyl-urea * Chemical structures used with permission from Chemspider (CSID, 2016). **3,4-DCA is a degradation compound of diuron, linuron, and propanil. intense monsoonal rainfall events during the wet season. These major events and river runoff deliver excess sediments, nutrients and pesticides which all contribute to reduced water quality in nearshore and reefal envrionments (Brodie et al., 2012a; Brodie and Waterhouse, 2012; Hutchings et al., 2005; Lewis et al., 2009; Shaw et al., 2010). Satellite imagery effectively captures these events and their associated flood plumes migrating 40-50 km offshore to the GBR, See Fig. 1.1 (Bainbridge et al., 2012; Schroeder et al., 2012). It was recenty demonstrated that some plumes travel further, reaching most reefs up to 130 km to the outer GBR (Brodie et al., 2012a). In 2011, a plume was observed affecting the inner lagoon to 50 km offshore, extending for 1200 km from

Fraser Island at the Southern end of the GBR to Cape Tribulation in the Northern Wet Tropics (Bainbridge et al., 2012; Brodie et al., 2012a; Brodie et al., 2012b).

Figure 1.1: Satellite image depicting flood plumes travelling 50 km offshore to the Great Barrier Reef. Used with author permission (Schroeder et al., 2012). “Flood plumes of the Burdekin River (A) and the O’Connell and Proserpine Rivers (B) captured by MODIS Aqua.”

1.2.3 Herbicides detected in the GBR

While a wide spectrum of pesticides have been detected in waters of the GBR, the herbicides are often more water soluble, mobile and persistent than most insecticides and fungicides and are consequently more often detected in the rivermouths and the ocean (Brodie et al., 2012b; Davis et al., 2011; Lewis et al., 2009). It has been reported that up to 30,000 kg/yr of photosystem II (PSII) herbicides (atrazine, diuron, hexazinone, tebuthiuron, simazine and ametryn) are transported into to the GBR lagoon (Brodie and Waterhouse, 2012; Davis et al., 2012; Kroon et al., 2012). The Mackay-Whitsundays (10,000 kg/yr) and Wet Tropics (12,000 kg/yr) regions account for the majority of the load to the GBR lagoon (Kroon et al., 2012). As a concequence, these herbicides (atrazine, diuron, hexazinone, tebuthiuron, simazine and ametryn ) are also the most commonly detected herbicides in the GBR lagoon (Lewis et al., 2012).

PSII herbicides kill weeds by binding with a specific protein (quinone protein) in Photosystem II and inhibiting photosynthetic electron transport (Ferrat et al., 2003; Trebst, 2008). Effectively the herbicide outcompetes the normal ligand at the binding site. PSII herbicides are as effective at inhibiting photosynthesis in non-target marine plants and algae as they are at killing weeds. Of particular concern is exposure of sensitive environments including tidal wetlands, estuaries, seagrass beds, and coral reefs to PSII herbicides following monsoonal flood events. These important ecosystems host a wide variety of flora and fauna, include nursery habitat, and support vulnerable, endangered or protected species such as dugong or sea turtles both of which feed on sea grass. While there is a need for more regional GBR research on how these chemicals impact marine species in the tropics, herbicides have already been shown in the laboratory to negatively impact a variety of marine organisms including coral (Cantin et al., 2007; Jones and Kerswell, 2003; Jones et al., 2003; Råberg et al., 2003; Watanabe et al., 2006), coral larvae/gametes/recruits (Negri et al., 2005; Seery et al., 2006), isolated coral symbionts (Symbiodinium sp.) (Owen et al., 2003; Shaw et al., 2012), crustose coralline algae (Harrington et al., 2005; Negri et al., 2011), seagrass (Gao et al., 2011; Haynes et al., 2000; Negri et al., 2015; Nielsen and Dahllöf, 2007; Ralph, 2000; Wilkinson et al., 2015), mangroves (Bell and Duke, 2005; Lewis et al., 2011), and microalgae/forams/diatoms (Bengtson Nash et al., 2005; Bonilla et al., 1998; Macedo et al., 2008; Magnusson et al., 2008; Magnusson et al., 2010; Magnusson et al., 2012; van Dam et al., 2012a; van Dam et al., 2012b; Weiner et al., 2004). The GBR Marine Park Authority (GBRMPA) has issued water quality guideline values for a number of herbicides these are set in order to protect 99, 95, and 90 per cent of marine species (GBRMPA, 2010 Accessed March 2015; Moss et al., 2005). Additional guideline values have been proposed for PSII inhibition thresholds (Lewis et al., 2012). Diuron, atrazine, and tebuthiuron concentration have been detected in receiving waters of the GBR at concentrations above the guideline value as set by GBRMPA, specifically in sampling locations of the Burdekin-Townsville, Mackay-Whitsunday and Fitzroy regions (Kennedy et al., 2012a; Lewis et al., 2009; Lewis et al., 2012). In addition, almost 55% of samples in one study found concentrations above proposed values for PSII inhibition thresholds (Lewis et al., 2012). They concluded that concentrations determined may negatively affect marine plant communities (including coral symbionts) and given that over 70% of samples contained more than two herbicides, mixture toxicity should be addressed (Lewis et al., 2012). This has been supported by previous reports of herbicide mixtures detected in the environment elsewhere (Carriger and Rand, 2008; Kennedy et al., 2012b; King et al., 2013; Lewis et al., 2009). While the herbicides in the GBR lagoon may originate from a variety of sources (e.g. diuron measured in ports from ship antifoulant), it has been proposed that atrazine,

diuron, hexazinone, simazine, and ametryn derive largely from sugarcane growing areas whereas the tebuthiuron is derived from beef grazing areas (Brodie et al., 2008).

1.2.4 Are the pesticides in the water or the sediments?

Many herbicides are considered highly water soluble with low affinity for sediments; however, there has been increasing evidence that sediments may sequester some herbicides and influence their mobility and transport. The Koc value is defined as the soil organic carbon–water partition coefficient of the chemical (Barbash, 2007). The Koc values are inversely related to water solubility (Barbash, 2007). As diuron has one of the highest Koc values of herbicides used in the GBR region (Davis et al., 2012) its potential sediment binding capacity may be the reason behind the prevalence in GBR sediments (Davis et al., 2012). There are exceptions for the Koc and water solubility relationship. Glyphosate for example, which is highly water soluble but has a high Koc value and therefore a greater affinity for adsorption for sediment particle (Davis et al., 2011). Despite the existence of general Koc values for many pesticides, there is limited information on the partitioning of herbicides in aquatic and marine systems in specific habitats, especially those in the tropics. This is especially important for ecologically sensitive environments such as the GBR lagoon which is adjacent to agriculture with particularly high herbicide application (Ecobichon, 2001; van Dam et al., 2012c). Particulate herbicides have been measured in river discharge into the GBR, contributing up to 33% of the total diuron (Brodie and Lewis, 2012; Davis et al., 2012). Atrazine, tebuthiuron, and simazine were also associated with sediments but to a lesser extent (Brodie and Lewis, 2012; Davis et al., 2012). Organic constituents of the sediment material will affect the absorption process, as such regional representatives should be assessed as sediments high in organics may facilitate the transport of herbicides in floodwaters to midshelf reefs, far beyond the assumed zone of impact of nearhshore environments (King et al., 2013).

1.2.5 Modes of herbicide degradation

As a chemical breaks down by physical, chemical or biological mechanisms, the resulting product can be termed transformation product, degradation product, metabolite, or degradates; these terms are often used interchangeably. The persistence (amount of time) if takes for a compound to degrade to 50% of the original concentration is termed the compound’s half-life. In general, the process of chemical breakdown can be chemical or biological through several means. Hydrolysis is a chemical process where chemical bond cleavage takes place with the addition of H or OH from water (Muir, 1991). Photodegradation is the photochemical decomposition of a chemical by 7

sunlight/UV (Burrows et al., 2002). Photodegradation may be of limited importance in flood plumes or where water depth is likely to limit the penetration of UV. Biodegradation is the microbially mediated transformation of a chemical, this process may be aerobic or anaerobic (Muir, 1991). An example degradation pathway can be seen in Fig. 1.2. This example shows how multiple herbicides (atrazine, simazine, and cyanazine; atrazine and propazine) can degrade to the same metabolite desisopropylatrazine (DIA) or desethylatrazine (DEA)(Thurman and Scribner, 2008). The degradation of an herbicide in the marine environment may rely on different means of transformation. According to the OECD methods for the assessment of biodegradability of compounds, degradation experiments may use shake flasks or closed bottles (OECD, 1992). Indoor flasks experiments have the advantage of a highly controlled environment with options for constant shaking, light, and temperature stability. Outdoor pond experiments, microcosm or mesocosm, have been used to assess chemical degradation, fate, and toxicity while using a larger volume of seawater. These larger tank studies may be designed with or without microalgae/microorganisms and sediments. These pond experiments can be used in order to closely mimic conditions found in the natural environment (Boyle and Fairchild, 1997; OECD, 2006; Sanderson et al., 2007).

1.2.6 The degradation of priority herbicides in the GBR

The collective information on the seawater degradation of herbicides detected in the GBR region is patchy at best. Limited data on the degradation of 2,4-D (Dąbrowska et al., 2006), atrazine (Konstantinou et al., 2001; Meakins et al., 1995; Navarro et al., 2004a, b), diuron (Thomas et al., 2002), and simazine (Meakins et al., 1995; Navarro et al., 2004a, b) in seawater can be found in Table 1.2. For comparison purposes, Table 1.3 is provided for herbicide degradation and half- lives from freshwater systems, by no means is this listing exhaustive. The reported half-lives of various herbicides in freshwater was varied, for example atrazine has a range of 2.6 days to 2 years depending on test conditions, Table 1.3. Very little reliable and quality data for marine degradation is available even for herbicides that have been in use since the 1940’s and 1950’s: 2,4-D 1944 (Barceló and Hennion, 2003), diuron 1954 (AVPMA, 2011), simazine (Heri et al., 2008), and atrazine 1958 (USEPA, 2012). Of the sparse information presented several parameters are varied among the experiments: experimental temperature, starting concentration of the herbicide, light

Figure 1.2: Example degradation pathways for atrazine, cyanazine, propazine, and simazine to DEA and/or DIA. Figure used with permission from Elsevier (Thurman and Scribner, 2008). is available even for herbicides that have been in use since the 1940’s and 1950’s: 2,4-D 1944 (Barceló and Hennion, 2003), diuron 1954 (AVPMA, 2011), simazine (Heri et al., 2008), and atrazine 1958 (USEPA, 2012). Of the sparse information presented several parameters are varied among the experiments: experimental temperature, starting concentration of the herbicide, light treatment/regime (some with and without light measurements taken), seawater treatment (natural versus filtered), an indication of analytical measurements for transformation products, and experiment duration. Starting with the temperature parameter, 15 - 20°C was common in the literature found, reflecting conditions found in temperate waters. The experiments which also measured degradation at temperatures of 40°C were not reflective of environmental conditions found even in the tropics and it was unclear why the authors chose to do so (Navarro et al., 2004a). While there are degradation experiments that include higher temperatures, wide pH ranges, or extreme UV, they had a remediation focus and were not representative of natural herbicide degradation. The starting concentrations of the different experiments in Table 1.2 reflect almost an order of magnitude difference. Concentrations in the GBR region have been measure in the ng l-1 to µg l-1 range (Davis et al., 2012; Lewis et al., 2009). Natural microbial degradation relies on indigenous microorganisms to adapt to using the contaminant as a carbon source (Mandelbaum et al., 2008) and unrealistically high concentrations of herbicides in solution could in turn have a high impact the natural microbial community composition. High herbicide concentrations could lead to a longer lag time for the microorganisms capable of degrading the herbicide to grow to sufficient quantities for a noticeable change in herbicide degradation. A more relevant starting concentration would then assess what would happen in the natural marine environment.

Table 1.2: Published literature on the degradation half-life experiments in seawater.

Herbicide Half-life Initial Dark or light? Filtered? Comments Reference (days) concentration Temperature 2,4-D SL = 11.1 2 mg l-1 SL = seawater, unfiltered Also measured other (Dąbrowska et SD = 31.2 natural light compounds al., 2006) SD = seawater, darkness Both at 20°C Atrazine SL = 79 5 mg l-1 SL = seawater, unfiltered Also looked at river (Navarro et al., SD = 206 light seawater and groundwater 2004b) SD = seawater, degradation and darkness; included 2 additional (light, mean of herbicides 8 h sun day; both at 20°C) Atrazine S = 79 5 mg l-1 S = seawater unfiltered Also looked at river (Navarro et al., ST = 65 20°C, light seawater and groundwater 2004a) ST = seawater degradation and elevated included 2 additional temperature herbicides 40°C, light Atrazine No 20 µg l-1 20 days at filtered Noted absence of (Meakins et degradation 20°C with 0.45µm degradation al., 1995) for light and compounds. experiment unfiltered Included 2 duration degradation products. Atrazine 56.3 8-9 mg l-1 Seawater, unfiltered Also looked at river (Konstantinou natural light, seawater water degradation et al., 2001) 22°C average Diuron No 1 mg l-1 Constant light unfiltered Included 2 diuron (Thomas et al., degradation for 42 days, seawater degradation products 2002) for 15°C DCPMU or DCPU. experiment Report DCPMU (t duration 1/2 = 33 days) and DCPMU (t 1/2 = 50 days) Simazine SL = 29 5 mg l-1 SL = seawater, unfiltered Also looked at river (Navarro et al., SD = 49 light seawater and groundwater 2004b) SD = seawater, degradation and darkness; included 2 additional (light, mean of herbicides 8 h sun day; both at 20°C) Simazine S = 29 5 mg l-1 S = seawater unfiltered Also looked at river (Navarro et al., ST = 28 20°C, light seawater and groundwater 2004a) ST = seawater degradation and elevated included 2 additional temperature herbicides 40°C, light Simazine No 20 µg l-1 20 days at filtered Noted absence of (Meakins et degradation 20°C with 0.45µm degradation al., 1995) for light and compounds experiment unfiltered duration

Table 1.3: Published literature on the degradation half-life experiments in freshwater.

Herbicide Half-life water Water type/conditions specified Reference (days, unless otherwise specified) 2,4-D ~2 (suggested) Surface (Barbash, 2007; Mackay et al., 1997) 2,4-D 38 Aqueous photodegradation at pH 7 (PPDB, 2011)A 2,4-D Stable Aqueous hydrolysis, 20°C and pH 7 (PPDB, 2011)A Ametryn No value. States: “Slow Aqueous photodegradation at pH 7 (PPDB, 2011)W degradation in UV light” Ametryn Stable Aqueous hydrolysis, 20°C and pH 7 (PPDB, 2011)W Atrazine ~2 years (suggested) Surface (Barbash, 2007; Mackay et al., 1997) Atrazine 2.6 Aqueous photodegradation at pH 7 (PPDB, 2011)B Atrazine 86 Aqueous hydrolysis, 20°C and pH 7 (PPDB, 2011)K Atrazine Stable, 34–37 days of the River water, 10°C and 20°C (Starner et al., 1999) experiment Atrazine 43 River water, 22°C average (Konstantinou et al., 2001) Diuron ~3 weeks (suggested) Surface (Barbash, 2007; Mackay et al., 1997) Diuron 43 Aqueous photodegradation at pH 7 (PPDB, 2011)A Diuron Stable Aqueous hydrolysis, 20°C and pH 7 (PPDB, 2011)A Diuron 33 Aqueous (DeLorenzo and Fulton, 2012; USEPA, 2003) Glyphosate ~2 months (suggested) Surface (Barbash, 2007; Mackay et al., 1997) Glyphosate 69 Aqueous photodegradation at pH 7 (PPDB, 2011)A Glyphosate Stable Aqueous hydrolysis, 20°C and pH 7 (PPDB, 2011)A Hexazinone 56 Aqueous photodegradation at pH 7 (PPDB, 2011)K Hexazinone 56 Aqueous hydrolysis, 20°C and pH 7 (PPDB, 2011)K Metolachlor ~2 months (suggested) Surface (Barbash, 2007; Mackay et al., 1997) Metolachlor Stable Aqueous photodegradation at pH 7 (PPDB, 2011)Q Metolachlor Stable Aqueous hydrolysis, 20°C and pH 7 (PPDB, 2011)Q Simazine ~3 weeks (suggested) Surface (Barbash, 2007; Mackay et al., 1997) Simazine 1.9 Aqueous photodegradation at pH 7 (PPDB, 2011)K Simazine 96 Aqueous hydrolysis, 20°C and pH 7 (PPDB, 2011)B Simazine Stable, 34–37 days of the River water, 10°C and 20°C (Starner et al., 1999) experiment Tebuthiuron No value Aqueous photodegradation at pH 7 (PPDB, 2011) Tebuthiuron 64 Aqueous hydrolysis, 20°C and pH 7 (PPDB, 2011)L A EU Regulatory & Evaluation Data as published by EC, EFSA (DAR & Conclusion dossiers), EMA / EU Annex III PIC DGD / EU MRL Database (See http://ec.europa.eu/sanco_pesticides/public/index.cfm) B UK CRD and ACP Evaluation Documents / and other DEFRA (UK) documents (See http://www.pesticides.gov.uk/publications.asp?id=202) K Research Datasets (e.g. Pandora, Demetra (See http://www.demetra-tox.net/)) L Pesticide manuals and hard copy reference books / other sources Q Miscellaneous data from On-line Sources W French database provided by ARVALIS-Institut du Végétal

Experimental light regime is an important decision at the start of the experiment. An experiment run in total darkness would exclude any photodegradation of the compound, while experiments with a 24 hour light source would not be reflective of natural conditions and experiments applying a relatively natural diurnal cycle would be more appropriate. Light intensity, light sources, and the reporting of these factors vary from the degradation experiments reviewed. The difference in atrazine half-life reported by Navarro et al. (2004b) between the light (79 day half-life) and the dark treatment (206 day half-life) illustrates the relative importance of sunlight in the degradation of some herbicides. The differences in persistence in this experiment could be due to photodegradation or the different microbial communities under different light regimes. The slow biotransformation pathway of atrazine may be one of the reasons why the parent compounds and transformation products are frequently detected (Barceló and Hennion, 2003). As flood plumes also decrease light penetration as well as carry with it herbicide residues, the short term degradation of the herbicides will be affected during the wet season. The treatment of the seawater prior to experimentation is also another consideration worth review. Filtering the seawater prior to the experiment, depending on filter size (e.g. 0.45 µm) would exclude the majority of organisms such as zooplankton or pelagic organisms, other microorganisms such as some bacteria would remain. Filtering to less (e.g. 20 µm) would include more organisms in the seawater sample but this would be variable among regions and seasons. . One of the major parameters and differences in the marine degradation experiments pertains to experiment duration. One experiment was run for only 20 days and no degradation was observed during that time (Meakins et al., 1995). Another ran for 42 days without any degradation of diuron (Thomas et al., 2002). It is unclear why either experiment was not rerun for a longer duration to enable more accurate half-life estimation. Atrazine and simazine were measured in a marine degradation experiment over the course of 127 days (Navarro et al., 2004b). The experiment showed the degradation and half-lives for the compounds in both light and dark treatment conditions. The experiment duration was long enough to estimate and measure a half-life for simazine under both light and dark conditions and atrazine under the light conditions. It is believed that the authors extrapolated for the half-life atrazine under the dark conditions; however the loss of atrazine appears to be linear at the end of the experiment so perhaps this was justified.

1.2.7 Data gaps and priorities to improve risk assessments for herbicide movement, persistence and risk in the context of the GBR.

While we are beginning to understand the potential effects of herbicides on tropical marine organisms (Haynes et al., 2000; Jones, 2005; Negri et al., 2005; van Dam et al., 2012b), there are many outstanding issues that prevent (i) the development of reliable predictive models for herbicide 12

impacts and (ii) reliable risk assessments for current and emerging herbicides in the GBR catchments. Key information to address both of these issues includes an understanding of: (i) The degradation characterisation, rates, and half-lives of herbicides in the marine environment. (ii) The toxicity of transformation products of current and emerging herbicides to relevant GBR organisms (iii) The partitioning of herbicides between seawater, suspended solids and sediments (iv) The effect of environmental conditions relevant to the tropics on the above issues

The current gap in data on herbicide persistence clearly effects our current ability to temporally model the fate of herbicides and their environmental risk to nearshore GBR ecosystems. Understanding the effects of light and temperature on the degradation of herbicides would improve these predictions in situations where light intensity or penetration would be limited (e.g. flood waters, monsoonal rains). Temperatures along the GBR vary widely and understanding this effect on marine degradation rates is also critical. Most of the previous half-life studies were performed for US or EU conditions and may therefore not be relevant given different temperature and climate conditions (Barceló and Hennion, 2003). Degradation rates may be even more important in the tropics where usage patterns are generally higher than in temperate climates (van Dam et al., 2012c). Also worth considering is whether degradation rates and associated half-lives of herbicides in the marine environment be required information before product approval as surely a risk assessment on the impact in the marine environment without such information would be incomplete. Few toxicity studies of herbicides have considered mixtures of herbicides or their transformation compounds, even though the breakdown products may be found in higher concentrations in the environment (Kolpin et al., 2004; Kolpin et al., 2000; Sinclair and Boxall, 2003; Stuart et al., 2012). When transformation compounds are considered, not only are they frequently detected in environmental assessments, but they can increase the total concentration of the herbicide (parent compound plus breakdown products) by an order of magnitude (Kolpin et al., 2000). An assessment by Sinclair and Boxall (2003) found that 30% of pesticide metabolites are more toxic than the parent herbicide. The toxicities of metabolites can have both acute and chronic toxicity (Kolpin et al., 1998). The main degradation product of diuron, 3,4-dichloroaniline (3,4- DCA), has been reported to be more toxic than diuron (Caracciolo et al., 2005; Kiss and Virág, 2009; Tixier et al., 2000; Tixier et al., 2001). Atrazine’s two main environmental transformation products, desethylatrazine (DEA) and desisopropylatrazine (DIA), are also reported as having equivalent toxicities to their parent compound (Belluck et al., 1991; Meakins et al., 1995). 13

Considering their equivalent toxicities and the potential for contributing significantly to total herbicide residue concentrations in the environment, metabolites should be incorporated into chemical risk assessments (Kookana and Simpson, 2000). The answers to these questions would greatly help regulators of the chemicals themselves (e.g. AVPMA), water protection services, and management agencies (GBRMPA), etc. both domestically within Australia and worldwide.

1.3 Objectives and structure of thesis

The overall objective of my thesis was to determine half-lives, identify transformation products, and assess the toxicity of high priority herbicides in conditions relevant to tropical marine ecosystems. Specifically the aims were to evaluate the fate of herbicides in marine water: 1. Identify the persistence of high priority herbicides in standard simulation experiments under different environmental conditions. 2. Measure the persistence of herbicides under conditions relevant to nearshore marine waters both with and without natural sediments. 3. Determine whether transformation products contribute to the total toxicity of water samples containing herbicides.

This thesis is arranged in the order of the experiments. Chapter 1 introduced the background of herbicide usage and knowledge gaps pertaining to the marine environment especially in the tropics. Each subsequent chapter also has an introduction section specific to its content. Chapter 2 is the first data chapter and describes the degradation of eight herbicides in two experiments. The first was a 60 day degradation experiment modelled after the standard OECD flask tests for biodegradability. In this initial experiment I modified the standard OECD test by applying realistic herbicide concentrations and naturally occurring microbes instead of artificial inoculum. The second experiment in this Chapter 2, was similar but the duration was extended to 365 days and the impacts of different light and temperature conditions on herbicide persistence was explored. Chapter 3 focussed entirely on the persistence of glyphosate which is one of the most widely applied herbicides globally and required different analytical techniques. Transitioning to larger volumes and more environmentally relevant conditions, Chapter 4 examined herbicide persistence in the presence of natural marine sediments and exposure to ambient environmental light and temperature conditions in an open tank experiment which lasted 365 days. In order to produce herbicide transformation products for toxicity assessment, the open tank design was utilised again in Chapter 5. The toxicity of mixtures that contained the parent herbicides and their transformation products were tested after 330 days to determine whether the breakdown products contribute to

overall environmental toxicity. Finally Chapter 6 synthesises the experimental results and discusses relevance to the natural environment, applications for management and future directions in understanding the fate and effects of herbicides in tropical marine ecosystems.

1.4 References

AVPMA, 2011. Diuron: Human health assessment. 1-78. Accessed March 2015. Bainbridge, Z.T., Wolanski, E., Álvarez-Romero, J.G., Lewis, S.E., Brodie, J.E., 2012. Fine sediment and nutrient dynamics related to particle size and floc formation in a Burdekin River flood plume, Australia. Mar. Pollut. Bull. 65, 236-248. Barbash, J.E., 2007. 9.15 - The geochemistry of pesticides, in: Editors-in-Chief: Holland, D.H.a.T., K.K. (Ed.), Treatise on Geochemistry. Pergamon, Oxford, pp. 1-43. Barceló, D., Hennion, M., 2003. Trace determination of pesticides and their degradation products in water. Bell, A.M., Duke, N.C., 2005. Effects of Photosystem II inhibiting herbicides on mangroves— preliminary toxicology trials. Mar. Pollut. Bull. 51, 297-307. Belluck, D., Benjamin, S., Dawson, T., 1991. Groundwater contamination by atrazine and its metabolites: risk assessment, policy, and legal implications, IN: Pesticide Transformation Products: Fate and Significance in the Environment. ACS Symposium Series 459. American Chemical Society, Washington, DC. 1991. p 254-273. 1 tab, 50 ref. Bengtson Nash, S.M., Quayle, P.A., Schreiber, U., Müller, J.F., 2005. The selection of a model microalgal species as biomaterial for a novel aquatic phytotoxicity assay. Aquat. Toxicol. 72, 315-326. Bonilla, S., Conde, D., Blanck, H., 1998. The photosynthetic responses of marine phytoplankton, periphyton and epipsammon to the herbicides paraquat and simazine. Ecotoxicology 7, 99- 105. Boyle, T.P., Fairchild, J.F., 1997. The role of mesocosm studies in ecological risk analysis. Ecological Applications 7, 1099-1102. Brodie, J., Binney, J., Fabricius, K., Gordon, I., Hoegh-Guldberg, O., Hunter, H., O’Reagain, P., Pearson, R., Quirk, M., Thorburn, P., 2008. Synthesis of evidence to support the scientific consensus statement on water quality in the Great Barrier Reef. The State of Queensland (Department of the Premier and Cabinet). Published by the Reef Water Quality Protection Plan Secretariat, Brisbane. 59pp. Brodie, J., Wolanski, E., Lewis, S., Bainbridge, Z.T., 2012a. An assessment of residence times of land-sourced contaminants in the Great Barrier Reef lagoon and the implications for management and reef recovery. Mar. Pollut. Bull. 65, 267-279. Brodie, J.E., Kroon, F.J., Schaffelke, B., Wolanski, E.C., Lewis, S.E., Devlin, M.J., Bohnet, I.C., Bainbridge, Z.T., Waterhouse, J., Davis, A.M., 2012b. Terrestrial pollutant runoff to the Great Barrier Reef: An update of issues, priorities and management responses. Mar. Pollut. Bull. 65, 81-100. Brodie, J.E., Lewis, S.E., 2012. Great Barrier Reef catchment and lagoon: management practices in the sugarcane industry (RRRD037) and pesticide dynamics in the Great Barrier Reef Catchment and lagoon: grazing, bananas and grain crops (RRRD038), Reef Rescue Forum 2012, Brisbane, QLD Australia. Brodie, J.E., Waterhouse, J., 2012. A critical review of environmental management of the ‘not so Great’ Barrier Reef. Estuar. Coast. Shelf Sci. 104–105, 1-22. Burrows, H.D., Canle L, M., Santaballa, J.A., Steenken, S., 2002. Reaction pathways and mechanisms of photodegradation of pesticides. Journal of Photochemistry and Photobiology B: Biology 67, 71-108.

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Jones, R.J., Muller, J., Haynes, D., Schreiber, U., 2003. Effects of herbicides diuron and atrazine on corals of the Great Barrier Reef, Australia. Marine Ecology Progress Series 251, 153-167. Kennedy, K., Bentley, C., Lee-Chue, K., Paxman, C., Carter, S., Lewis, S.E., Brodie, J., Guy, E., Vardy, S., Martin, K.C., Jones, A., Packett, R., Mueller, J.F., 2012a. The influence of a season of extreme wet weather events on exposure of the World Heritage Area Great Barrier Reef to pesticides. Mar. Pollut. Bull. 64, 1495-1507. Kennedy, K., Schroeder, T., Shaw, M., Haynes, D., Lewis, S., Bentley, C., Paxman, C., Carter, S., Brando, V.E., Bartkow, M., Hearn, L., Mueller, J.F., 2012b. Long term monitoring of photosystem II herbicides – Correlation with remotely sensed freshwater extent to monitor changes in the quality of water entering the Great Barrier Reef, Australia. Mar. Pollut. Bull. 65, 292-305. King, J., Alexander, F., Brodie, J., 2013. Regulation of pesticides in Australia: The Great Barrier Reef as a case study for evaluating effectiveness. Agric. Ecosyst. Environ. 180, 54-67. Kiss, A., Virág, D., 2009. Interpretation and modelling of environmental behaviour of diverse pesticides by revealing photodecomposition mechanisms. Microchemical Journal 92, 119- 122. Kolpin, D.W., Schnoebelen, D.J., Thurman, E.M., 2004. Degradates provide insight to spatial and temporal trends of herbicides in ground water. Ground Water 42, 601-608. Kolpin, D.W., Thurman, E.M., Linhart, S., 1998. The environmental occurrence of herbicides: The importance of degradates in ground water. Archives of Environmental Contamination and Toxicology 35, 385-390. Kolpin, D.W., Thurman, E.M., Linhart, S.M., 2000. Finding minimal herbicide concentrations in ground water? Try looking for their degradates. Sci. Tot. Environ. 248, 115-122. Konstantinou, I.K., Zarkadis, A.K., Albanis, T.A., 2001. Photodegradation of selected herbicides in various natural waters and soils under environmental conditions. J. Environ. Qual. 30, 121- 130. Kookana, R.S., Simpson, B.W., 2000. Pesticide fate in farming systems: research and monitoring. Communications in Soil Science & Plant Analysis 31, 1641-1659. Kroon, F.J., Kuhnert, P.M., Henderson, B.L., Wilkinson, S.N., Kinsey-Henderson, A., Abbott, B., Brodie, J.E., Turner, R.D.R., 2012. River loads of suspended solids, nitrogen, phosphorus and herbicides delivered to the Great Barrier Reef lagoon. Mar. Pollut. Bull. 65, 167-181. Lewis, M., Pryor, R., Wilking, L., 2011. Fate and effects of anthropogenic chemicals in mangrove ecosystems: A review. Environ. Pollut. 159, 2328-2346. Lewis, S.E., Brodie, J.E., Bainbridge, Z.T., Rohde, K.W., Davis, A.M., Masters, B.L., Maughan, M., Devlin, M.J., Mueller, J.F., Schaffelke, B., 2009. Herbicides: A new threat to the Great Barrier Reef. Environ. Pollut. 157, 2470-2484. Lewis, S.E., Schaffelke, B., Shaw, M., Bainbridge, Z.T., Rohde, K.W., Kennedy, K., Davis, A.M., Masters, B.L., Devlin, M.J., Mueller, J.F., Brodie, J.E., 2012. Assessing the additive risks of PSII herbicide exposure to the Great Barrier Reef. Mar. Pollut. Bull. 65, 280-291. Macedo, R.S., Lombardi, A.T., Omachi, C.Y., Rörig, L.R., 2008. Effects of the herbicide bentazon on growth and Photosystem II maximum quantum yield of the marine diatom Skeletonema costatum. Toxicology in Vitro 22, 716-722. Mackay, D., Shiu, W.Y., Ma, K.C., 1997. Illustrated handbook of physical-chemical properties and environmental fate for organic chemicals: Pesticide Chemicals. CRC Press. Magnusson, M., Heimann, K., Negri, A.P., 2008. Comparative effects of herbicides on photosynthesis and growth of tropical estuarine microalgae. Mar. Pollut. Bull. 56, 1545- 1552. Magnusson, M., Heimann, K., Quayle, P., Negri, A.P., 2010. Additive toxicity of herbicide mixtures and comparative sensitivity of tropical benthic microalgae. Mar. Pollut. Bull. 60, 1978-1987.

Magnusson, M., Heimann, K., Ridd, M., Negri, A.P., 2012. Chronic herbicide exposures affect the sensitivity and community structure of tropical benthic microalgae. Mar. Pollut. Bull. 65, 363-372. Mandelbaum, R.T., Sadowsky, M.J., Wackett, L.P., 2008. Chapter 22 - Microbial degradation of s- triazine herbicides, in: LeBaron, H.M., McFarland, J.E., Burnside, O.C. (Eds.), The Triazine Herbicides. Elsevier, San Diego, pp. 301-328. Meakins, N.C., Bubb, J.M., Lester, J.N., 1995. The mobility, partitioning and degradation of atrazine and simazine in the salt marsh environment. Mar. Pollut. Bull. 30, 812-819. Moss, A., Brodie, J., Furnas, M., 2005. Water quality guidelines for the Great Barrier Reef World Heritage Area: A basis for development and preliminary values. Mar. Pollut. Bull. 51, 76- 88. Muir, D.C.G., 1991. Chapter 1: Dissipation and transformations in water and sediments, in: Grover, R., Cessna, A.J. (Eds.), Environmental chemistry of herbicides. CRC Press, Inc., pp. 1-88. Navarro, S., Vela, N., Giménez, M.J., Navarro, G., 2004a. Effect of temperature on the disappearance of four triazine herbicides in environmental waters. Chemosphere 57, 51-59. Navarro, S., Vela, N., Giménez, M.J., Navarro, G., 2004b. Persistence of four s-triazine herbicides in river, sea and groundwater samples exposed to sunlight and darkness under laboratory conditions. Sci. Tot. Environ. 329, 87-97. Negri, A.P., Flores, F., Mercurio, P., Mueller, J.F., Collier, C.J., 2015. Lethal and sub-lethal chronic effects of the herbicide diuron on seagrass. Aquat Toxicol 165, 73-83. Negri, A.P., Flores, F., Rothig, T., S., U., 2011. Herbicides increase the vulnerability of corals to rising sea surface temperature. . Limnol. Oceanog. 56, 471-485. Negri, A.P., Vollhardt, C., Humphrey, C., Heyward, A., Jones, R., Eaglesham, G., Fabricius, K., 2005. Effects of the herbicide diuron on the early life history stages of coral. Mar. Pollut. Bull. 51, 370-383. Nielsen, L.W., Dahllöf, I., 2007. Direct and indirect effects of the herbicides glyphosate, bentazone and MCPA on eelgrass (Zostera marina). Aquat. Toxicol. 82, 47-54. OECD, 1992. OECD guidelines for testing of chemicals—306 Biodegradability in seawater, pp. 1- 27; Accessed March 2015. OECD, 2006. No. 53: Guidance document on simulated freshwater lentic field tests (outdoor microcosms and mesocosms), OECD series on testing and assessment, p. 37. Okamura, H., 2002. Photodegradation of the antifouling compounds Irgarol 1051 and diuron released from a commercial antifouling paint. Chemosphere 48, 43-50. Owen, R., Knap, A., Ostrander, N., Carbery, K., 2003. Comparative acute toxicity of herbicides to photosynthesis of coral zooxanthellae. Bull. Environ. Contam. Toxicol. 70, 541-548. Pimentel, D., 1996. Green revolution agriculture and chemical hazards. Sci. Tot. Environ. 188, Supplement, S86-S98. PPDB, 2011. Pesticide Properties Database. Agriculture & Environment Research Unit (AERU), University of Hertfordshire. Accessed March 2015

Råberg, S., Nyström, M., Erös, M., Plantman, P., 2003. Impact of the herbicides 2,4-D and diuron on the metabolism of the coral Porites cylindrica. Marine Environmental Research 56, 503- 514. Ralph, P.J., 2000. Herbicide toxicity of Halophila ovalis assessed by chlorophyll a fluorescence. Aquatic Botany 66, 141-152. Roff, G., 2010. Historical ecology of coral communities from the inshore Great Barrier Reef, Centre for Marine Studies. University of Queensland, p. 138. Sanderson, H., Laird, B., Pope, L., Brain, R., Wilson, C., Johnson, D., Bryning, G., Peregrine, A.S., Boxall, A., Solomon, K., 2007. Assessment of the environmental fate and effects of ivermectin in aquatic mesocosms. Aquat. Toxicol. 85, 229-240.

Schroeder, T., Devlin, M.J., Brando, V.E., Dekker, A.G., Brodie, J.E., Clementson, L.A., McKinna, L., 2012. Inter-annual variability of wet season freshwater plume extent into the Great Barrier Reef lagoon based on satellite coastal ocean colour observations. Mar. Pollut. Bull. 65, 210-223. Seery, C.R., Gunthorpe, L., Ralph, P.J., 2006. Herbicide impact on Hormosira banksii gametes measured by fluorescence and germination bioassays. Environ. Pollut. 140, 43-51. Shaw, C.M., Brodie, J., Mueller, J.F., 2012. Phytotoxicity induced in isolated zooxanthellae by herbicides extracted from Great Barrier Reef flood waters. Mar. Pollut. Bull. 65, 355-362. Shaw, M., Furnas, M.J., Fabricius, K., Haynes, D., Carter, S., Eaglesham, G., Mueller, J.F., 2010. Monitoring pesticides in the Great Barrier Reef. Mar. Pollut. Bull. 60, 113-122. Sinclair, C.J., Boxall, A.B.A., 2003. Assessing the ecotoxicity of pesticide transformation products. Environmental Science & Technology 37, 4617-4625. Smith, D.T., Richard Jr, E.P., Santo, L.T., 2008. Chapter 15 - Weed control in sugarcane and the role of triazine herbicides, in: H., M.L., J., E.M., Orvin, C.B. (Eds.), The Triazine Herbicides. Elsevier, San Diego, pp. 185-197. Starner, K., Kuivila, K.M., Jennings, B., Moon, G.E., 1999. Degradation rates of six pesticides in water from the Sacramento River, California. US Geological Survey Toxic Substances Hydrology Program Water Resource Investigation Rep, 89-99. Stuart, M., Lapworth, D., Crane, E., Hart, A., 2012. Review of risk from potential emerging contaminants in UK groundwater. Sci. Tot. Environ. 416, 1-21. Thomas, K.V., McHugh, M., Waldock, M., 2002. Antifouling paint booster biocides in UK coastal waters: Inputs, occurrence and environmental fate. Sci. Tot. Environ. 293, 117-127. Thurman, E.M., Scribner, E.A., 2008. Chapter 30 - A Decade of measuring, monitoring, and studying the fate and transport of triazine herbicides and their degradation products in groundwater, surface water, reservoirs, and precipitation by the US Geological Survey, in: LeBaron, H.M., McFarland, J.E., Burnside, O.C. (Eds.), The Triazine Herbicides. Elsevier, San Diego, pp. 451-VII. Tixier, C., Bogaerts, P., Sancelme, M., Bonnemoy, F., Twagilimana, L., Cuer, A., Bohatier, J., Veschambre, H., 2000. Fungal biodegradation of a phenylurea herbicide, diuron: Structure and toxicity of metabolites. Pest. Manag. Sci. 56, 455-462. Tixier, C., Sancelme, M., Bonnemoy, F., Cuer, A., Veschambre, H., 2001. Degradation products of a phenylurea herbicide, diuron: Synthesis, ecotoxicity, and biotransformation. Environmental Toxicology and Chemistry 20, 1381-1389. Trebst, A., 2008. Chapter 8 - The mode of action of triazine herbicides in plants, in: LeBaron, H.M., McFarland, J.E., Burnside, O.C. (Eds.), The Triazine Herbicides. Elsevier, San Diego, pp. 101-II. USEPA, 2003. Reregistration Eligibility Decision for Diuron. Environmental Protection Agency, Washington, DC, 66; Accessed March 2015. USEPA, 2012. Atrazine background. van Dam, J.W., Negri, A.P., Mueller, J.F., Altenburger, R., Uthicke, S., 2012a. Additive pressures of elevated sea surface temperatures and herbicides on symbiont-bearing foraminifera. PLoS ONE 7, e33900. van Dam, J.W., Negri, A.P., Mueller, J.F., Uthicke, S., 2012b. Symbiont-specific responses in foraminifera to the herbicide diuron. Mar. Pollut. Bull. 65, 373-383. van Dam, J.W., Negri, A.P., Uthicke, S., Mueller, J.F., 2012c. Chemical pollution on coral reefs: Exposure and ecological effects, in: Sánchez-Bayo, F., van den Brink, P.J., Mann, R.M. (Ed.), Ecological Impacts of Toxic Chemicals. Bentham Science Publishers Ltd., pp. 187- 211. Voulvoulis, N., Scrimshaw, M.D., Lester, J.N., 2002. Partitioning of selected antifouling biocides in the aquatic environment. Marine Environmental Research 53, 1-16.

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Chapter 2: Herbicide persistence in seawater simulation experiments

2.1 Abstract

Herbicides are detected year-round in marine waters, including those of the World Heritage listed Great Barrier Reef (GBR). The few previous studies that have investigated herbicide persistence in seawater generally reported half-lives in the order of months, and several studies were too short to detect significant degradation. Here we investigated the persistence of eight herbicides commonly detected in the GBR or its catchments in standard OECD simulation flask experiments, but with the aim to mimic natural conditions similar to those found on the GBR (i.e. relatively low herbicide concentrations, typical temperatures, light and microbial communities). Very little degradation was recorded over the standard 60 d period (Experiment 1) so a second experiment was extended to 365 d. Half-lives of PSII herbicides ametryn, atrazine, diuron, hexazinone and tebuthiuron were consistently greater than a year, indicating high persistence. The detection of atrazine and diuron metabolites and longer persistence in mercuric chloride-treated seawater confirmed that biodegradation contributed to the breakdown of herbicides. The shortest half-life recorded was 88 d for growth-regulating herbicide 2,4-D at 31°C in the dark, while the fatty acid-inhibitor metolachlor exhibited a minimum half-life of 281 d. The presence of moderate light and elevated temperatures affected the persistence of most of the herbicides; however, the scale and direction of the differences were not predictable and were likely due to changes in microbial community composition. The persistence estimates here represent some of the first appropriate data for application in risk assessments for herbicide exposure in tropical marine systems. The long persistence of herbicides identified in the present study helps explain detection of herbicides in nearshore waters of the GBR year round. Little degradation of these herbicides would be expected during the wet season with runoff and associated flood plumes transporting a high proportion of the original herbicide from rivers into the GBR lagoon.

2.2 Introduction

2.2.1 Runoff affecting the Great Barrier Reef

The Great Barrier Reef World Heritage Area (GBRWHA) consists of 3000 reefs spanning 1800 km along the Queensland coast. Extensive agriculture including sugarcane, bananas, horticulture, grazing, and plantation forestry have been developed on cleared land in catchments that drain into the GBR lagoon and herbicides are applied to control weeds and grasses on this land 21

(Shaw et al., 2010; Smith et al., 2012). The main transport mechanism for offsite migration of herbicides is via intense monsoonal rainfall events during the summer wet season (Hargreaves et al., 1999). River runoff then delivers excess sediments, nutrients and pesticides which contribute to reduced water quality in nearshore and reefal environments (Brodie et al., 2012a; Brodie and Waterhouse, 2012; Lewis et al., 2009; Shaw et al., 2010). The transport of contaminants into the GBR lagoon can be extensive with flood plumes migrating 40-50 km to the mid-shelf regions of the GBR (Bainbridge et al., 2012; Schroeder et al., 2012), and sometimes as far as 130 km offshore to the outer GBR (Brodie et al., 2012a). River plumes from multiple catchments can also combine, forming cumulative events along 1200 km of the GBR lagoon (Bainbridge et al., 2012; Brodie et al., 2012a; Brodie et al., 2012b; Schroeder et al., 2012).

2.2.2 PSII herbicides in the GBR

While a wide spectrum of pesticides have been detected in waters of the GBR and its catchments, herbicides are often more mobile than most insecticides and are consequently more often detected in the river mouths and the ocean (Brodie et al., 2012b; Davis et al., 2011; Lewis et al., 2009; Smith et al., 2012). The most commonly detected herbicides in the GBR act through blocking electron transport in photosynthesis and specifically within photosystem II (PSII) (Trebst, 2008). An estimated 30,000 kg yr-1 of PSII herbicides (atrazine, diuron, hexazinone, tebuthiuron, simazine and ametryn) are transported into to the GBR lagoon annually (Brodie and Waterhouse, 2012; Davis et al., 2012; Kroon et al., 2012). The Mackay-Whitsundays (10,000 kg yr-1) and Wet Tropics (12,000 kg yr-1) regions account for the majority of the load to the GBR lagoon (Kroon et al., 2012). Individual PSII herbicides have been detected in in nearshore envrionments at concentrations exceeding 0.9 µg l-1, the current guidleline intended to protect 99% of marine species (Davis et al., 2008; GBRMPA, 2010 Accessed March 2015; Lewis et al., 2012; Smith et al., 2012). Other non-PSII herbicides such as metolaclor, 2,4-D and glyphosate are also frequently detected across the GBR catchments (Smith et al., 2012). The detection of PSII herbicides, far from source rivers in the GBR and during the dry season, many months after the last rainfall and flood plume events (Brodie et al., 2012b; Kennedy et al., 2012; Lewis et al., 2009; Lewis et al., 2012; Shaw et al., 2010) indicates that many of these compounds may be relatively persistent in tropical marine waters.

2.2.3 Herbicide persistence in seawater

Persistence of chemicals is generally measured using flask experiments under controlled conditions, which can provide consistent and repeatable conditions. Despite their common use for over five decades, we found only seven studies that measured and reported half-lives of PSII 22

herbicides atrazine, simazine, diuron and the non-PSII herbicides 2,4-D and glyphosate in seawater (Table 2.1). Experimental parameters including initial herbicide concentration, temperature, light/UV, natural versus filtered seawater, and duration varied considerably between these studies and could affect reported persistence. For example, herbicide concentrations in the marine environment are generally less than 10 µg l-1 (Davis et al., 2012; Lewis et al., 2009); however, most previous studies tested degradation of far higher concentrations (Table 2.1). Very high starting concentrations can potentially result in: (i) the development of unrealistic capacity in microbial communities to metabolise this dominant carbon source, (ii) increased lag times in degradation as microbial communities struggle to adapt to high herbicide concentrations, or (iii) toxicity towards some components of the native microbial communities (Mandelbaum et al., 2008). The majority of previous herbicide degradation experiments in seawater were performed under temperate conditions 15 - 20°C (Table 2.1). In contrast, seawater temperatures during peak herbicide contamination periods in tropical systems are generally between 24 - 31°C (AIMS, 2013) and higher metabolic rates in microbial communities under these conditions may contribute to lower persistence under these warmer conditions (Navarro et al., 2004a). The presence of light can also have an impact on persistence due to contributions from photodegradation or changes in microbial communities. For example, Navarro et al. (Navarro et al., 2004b) demonstrated almost 3-fold more rapid degradation of high atrazine concentrations under full sunlight conditions (Table 2.1). Herbicides transported into the GBR via highly turbid flood plumes are exposed to low- moderate levels of light and UV penetration is likely to be highly attenuated under these conditions (Davies-Colley and Smith, 2001). Some of the previous persistence experiments were conducted for short durations of 20 days for atrazine and simazine (Meakins et al., 1995) and 42 days for diuron (Thomas et al., 2002), not long enough to detect significant degradation. Only longer experimental durations of more than 120 days yielded half-life estimates for atrazine and simazine (Navarro et al., 2004b). While many conditions listed in Table 2.1 may not have been ideal to estimate herbicide persistence in tropical waters, most were conducted using unfiltered or partially- filtered seawater which is suitable to test the ability of natural microbial communities to degrade herbicides (OECD, 2005). Assessing the risks posed by the range of herbicides commonly detected in the GBR lagoon is difficult considering the absence of appropriate persistence data (see above). While there is a far greater body of studies that have investigated herbicide persistence in freshwater and soil systems (PPDB, 2011), there is a requirement for data relevant to tropical marine systems. The aim of this study is to determine persistence, including factors that affect persistence, of herbicides in tropical marine water and provide long needed information towards understanding the fate of herbicides when they enter the GBR. 23

Table 2.1: Published literature on the degradation half-life experiments in seawater. SL = seawater light, SD = seawater dark, S = seawater, ST = seawater at elevated temperature.

Herbicide Half-life Initial Light Temperature Water filtration Reference (days) concentration .(µg l-1) Diuron No 1000 Light 15°C unfiltered (Thomas et degradation al., 2002) for 42 d Atrazine SL = 79 5000 SL SD 20°C unfiltered (Navarro et al., 2004b) SD = 206 Atrazine S = 79 5000 Light S = 20°C unfiltered (Navarro et al., 2004a) ST = 65 ST = 40°C Atrazine No 20 Light 20°C filtered 0.45µm (Meakins et degradation and unfiltered al., 1995) for 20 d Atrazine S = 56 ~8500 Light 22°C unfiltered (Konstantinou et al., 2001) Simazine SL = 29 5000 SL SD 20°C unfiltered (Navarro et al., 2004b) SD = 49 Simazine S = 29 5000 Light S = 20°C unfiltered (Navarro et al., 2004a) ST = 28 ST = 40°C Simazine No 20 Light 20°C filtered 0.45um (Meakins et degradation and unfiltered al., 1995) for 20 d 2,4-D SL = 11.1 2000 SLSD 20°C unfiltered (Dąbrowska et al., 2006) SD = 31.2 Glyphosate D25 = 267 10 Dark 25°C 20 µm filtered (Mercurio et al., 2014) D31 = 315 Dark 31°C L25 = 47 Light 25°C

2.3 Materials and Methods

The experimental approach that was taken follows the standard OECD (OECD, 1992) guidelines for testing biodegradation in seawater modified to OECD (OECD, 2005) “simulation test” criteria which utilise environmentally relevant conditions rather than those conducive to bioremediation. The experiments were conducted in coastal seawater containing native bacterial communities without addition of nutrients or artificial inoculum to best mimic ecological conditions and used low initial concentrations (4-18 µg l-1), relevant to the receiving waters in the field. Background (control) solutions were analysed for herbicides and contained < 0.1 µg l-1 (below analytical detection limit) and did not contribute to the original concentrations.

2.3.1 Experiment 1

Nearshore coastal seawater was collected at the Australian Institute of Marine Science (19°16’ S, 147° 03’ E), Cape Cleveland, QLD under the permit G12/35236.1 issued by the Great Barrier Reef Marine Park Authority. The seawater was filtered to 0.45 μm to remove all particles and added to individual 500 ml Erlenmeyer flasks (300 ml final volume), see Fig. 6.1. The sample treatments were spiked to a final concentration of ~10 µg l-1 for each herbicide (Table 2.2) and the flasks were stoppered with autoclaved cotton bungs to allow for aerobic conditions. Herbicide standards (98.5 - 99.9%) were purchased from Sigma-Aldrich, added to 2 ml of the carrier solvent ethanol (to assist in solubility), and made to 5 mg l-1 concentration with Milli-Q water. The same volume of ethanol (final less than 0.03% v/v) was added to all flasks, including controls for consistency between treatments. Triplicate flasks were shaken at 25°C and 100 rpm in the dark using an Innova 44, incubator shaker. One series of flasks contained a mixture of the six PSII herbicides (ametryn, atrazine, diuron, hexazinone, simazine, tebuthiuron) and the second series of flasks the same herbicide mixture with the addition of 45 mg l-1 mercuric chloride (MC) to eliminate microbial activity (Table 2.2) (OECD, 2004). Sample treatment flasks were weighed before sampling to monitor evaporation losses for concentration adjustments. Flasks were topped up with fresh sterile water (Milli-Q) and any losses were compensated for during calculations. Experiment 1 (pilot) examined the degradation of six PSII herbicides over 60 d (Table 2.2). The 60 day experiment length was set as the maximum by following the OECD method. The purpose of this experiment was to test whether bacteria contributed to biodegradation of these herbicides. Microbial activity is eliminated in the presence of MC and to inform the second experiment which was to be conducted over a longer period.

2.3.2 Experiment 2

The methodology for this second experiment was modified slightly from Experiment 1 (pilot). Coastal seawater was collected and filtered to 20 µm to introduce the total bacterial diversity from this environment. The filtered seawater also included other active substances such as fine mineral/organic particles (<20 µm) and dissolved organic carbon; however, we expect minimal adsorption to particles since the herbicides are characterized by low partition coefficients (log KOW < 3). The 20 µm-filtered seawater (300 ml in three replicate 500 ml Erlenmeyer flasks) was capped with autoclaved and oven dried silicone bungs. A total of seven herbicides were included in this experiment, each with an initial concentration of 4 – 18 µg l-1. Incubator conditions and results

Table 2.2: Experimental details of two degradation experiments investigating herbicide degradation in (1) filtered seawater and (2) unfiltered seawater. All flasks were shaken at 100 rpm. MC = mercuric chloride.

Experiment Experiment 1 (Pilot) Experiment 2 Experimental 3 replicate flasks 3 replicate flasks units Herbicides PSII mix (ametryn, atrazine, diuron, hexazinone, simazine, tebuthiuron) Atrazine Diuron PSII mix (as above) with MC Hexazinone Tebuthiuron Control (no herbicides) Metolachlor 2,4-D Control (no herbicides) Coastal 0.45 µm filtered 20 µm filtered seawater Light Dark only Dark or 40 µE light conditions Temperature 25°C 25°C or 31°C Duration 60 days 365 days Days sampled 0,7, 28, 60 0, 28, 60, 120, 180, 240, 300, 365 for glyphosate were published previously (Mercurio et al., 2014). In brief, the degradation study was conducted under three test conditions (Table 2.2) in three separate temperature-regulated incubator shakers (set to 25°C or 31°C), see Fig. 6.1. An even light environment of 40 µmol photons m-2s-1 over a 12:12 light day cycle was provided in one 25°C shaker using cool white LED strips. This was equivalent to 1.7 mol photons m-2day-1, comparable to shallow 3 – 6 m depths on turbid nearshore reefs of the GBR during the wet season (Uthicke and Altenrath, 2010). The experiment flasks were randomised after every sampling period. Seawater was sampled 19 times over the year-long study, including the 60 day time point to allow for comparisons with Experiment 1. Experiment 2 examined the year-long degradation of four PSII herbicides along with 2,4-D and metolachlor in 20 µm filtered coastal water under three different light and temperature scenarios: (1) in the dark at 25°C which corresponds to the mean annual seawater temperature on the GBR (AIMS, 2013); (2) in low light conditions at 25°C and (3) in the dark and at 31°C which is a summer maximum temperature for nearshore areas of the mid-northern regions of the GBR (AIMS, 2013) (Table 2.2).

2.3.3 Herbicide analysis

Aliquots (2 ml) were transferred into 4 ml amber glass vials and spiked with a surrogate 26

standard, d5-Atrazine (10 µg l-1). The final concentration of the surrogate standard was 5 µg l-1. The samples were stored at -20°C and filtered prior to analysis. After each experiment had ended, samples were run in sequential order. The herbicide and degradation product concentrations were determined by HPLC-MS/MS using an AB/Sciex API5500Q mass spectrometer (AB/Sciex, Concord, Ontario, Canada) equipped with an electrospray (TurboV) interface and coupled to a Shimadzu Prominence HPLC system (Shimadzu Corp., Kyoto, Japan). Column conditions were as follows: Phenomenex Synergi Fusion RP column (Phenomenex, Torrance, CA) 4 µm 50 x 2.0 mm, 45°C, with a flow rate of 0.4 ml min-1. The column was conditioned prior to use and for analyte separation required a linear gradient starting at 8% B for 0.5 min, ramped to 100% B in 8 min then held at 100% for 2.0 min followed by equilibration at 8% B for 2.5 min (A = 1% methanol in HPLC grade water, B = 95% methanol in HPLC grade water, both containing 0.1% acetic acid). The mass spectrometer was operated in the positive ion, multiple reaction-monitoring mode (MRM) using nitrogen as the collision gas. Analyte quantification and confirmation ions are listed in Appendix Table 1. Positive samples were confirmed by retention time and by comparing transition intensity ratios between the sample and an appropriate concentration standard from the same run. Sample were reported as positive if the two transitions were present, retention time was within 0.15 minutes of the standard and the relative intensity of the confirmation transition was within 20% of the expected value. The value reported was that for the quantitation transition. The limit of detection for this method was typically less than 0.1 μg l-1, yielding a reporting limit of 0.2 µg l-1. Response was linear to at least 20 μg l-1. Sample sequences were run with a standard calibration at beginning and end of sequence with additional mid-range standards run every 10 samples.

2.3.4 Water chemistry

The physical/chemical characteristics of the filtered seawater used in the experiment were measured, including dissolved oxygen, salinity and pH. Dissolved oxygen and pH were measured before and at the end of each experiment. The salinity remained between 33 and 34 PSU throughout and the pH and dissolved oxygen (DO) levels of seawater in the flasks were similar between controls, treatments and freshly-collected natural seawater at the end of the 60 and 365 day experiments (in Appendix Tables 2 and 3). Water chemical characteristics were determined using standard techniques and reported in Appendix Table 3.

2.3.5 Flow cytometry

Flow cytometry was used to quantify the microbial populations in the seawater used in the experiment. Samples were fixed with 5% formaldehyde and stored at 4 °C. Sub-samples were stained using Sybr Green, diluted to 1:10,000, and allowed to develop in the dark for 30 min. Samples were run using a BD Accuri C6 cytometer (BD Biosciences, CA, USA) equipped with a red and blue laser (488 nm, 50 mW maximum solid state; 640 nm, 30 mW diode) and standard filter setup. Flow rate was 14 μl min−1, 10-μm core. The natural microbial community populations and their abundances were measured for the initial seawater as well as treatments for the experiment using the Accuri CFlow plus software. On the basis of the flow cytometry results, the seawater in flasks contained similar bacterial abundance at the end of the experiment compared with natural seawater. The values measured were consistent with the range expected for seawater (Appendix Table 2) (Amaral-Zettler et al., 2010; Glöckner et al., 2012; Miller, 2009).

2.3.6 Data analysis

Half-life (t1/2) calculations assumed first order kinetics and were estimated from the decline in experiment concentration of herbicide in seawater using the rate constant (k) slope of the data obtained from plots of the natural logarithm of the concentrations versus time (t), where t1/2 = ln(2)/k (Beulke and Brown, 2001; Lazartigues et al., 2013). First order kinetics were applied as outlined in standard OECD protocols (OECD, 2004, 2005), and previous degradation experiments on herbicides (Dąbrowska et al., 2006; Konstantinou et al., 2001; Navarro et al., 2004a; Stasinakis et al., 2009); however, zero order kinetics may apply for low concentrations of a pesticide in the presence of other natural carbon sources (Ahtiainen et al., 2003) so this approach was also tested. Half-lives for zero order kinetics were obtained by plotting the concentration vs time: t1/2 = 0.5 C0/k0, where C0 is the initial concentration and k0 is the slope. Comparisons between approaches can be found in Appendix Table 4 (Experiment 1) and Appendix Table 5 (Experiment 2), revealing good fits for both zero- and first-order models (similar r2 values for linear plots). Both models predicted similarly long half-lives (on average 25% and 9% difference between approaches in Experiment 1 and Experiment 2 respectively) and we have subsequently presented data from the more conventional first-order approach. Herbicide concentrations below the reporting limit were removed from the analysis. The concentration data was analysed by repeated measures analysis of variance (ANOVA) using Number Cruncher Statistical System (NCSS 9) (Statistical and Power Analysis Software) across the time points sampled. Significance was determined if the resulting p- value was <0.05 between the initial concentration at day 0 and specified time point (e.g. day 60, day

365). The probability that t1/2 was statistically different between light and temperature treatments were tested by comparing the heterogeneity of the regression (whether the slopes were different) using a two-tailed test (Zar, 1984) in Graph Pad Prism V 6.0. When p < 0.05 the slopes were considered significantly different.

2.4 Results

2.4.1 Experiment 1

Significant decreases in all PSII herbicide concentrations over the 60 d duration were recorded in the presence of bacteria with the exception of diuron (Fig. 2.1, Appendix Table 6). The decrease in herbicide concentrations in the presence of bacteria resulted in half life estimates between 420 for ametryn and 631 d for atrazine (Table 2.3). Repeated measures ANOVA indicated that there was no significant degradation of any of the PSII herbicides in the presence of mercuric chloride over 60 d (Fig. 2.1, Appendix Table 6). Metabolites of diuron (3,4 dichloroaniline) and atrazine (desethyl atrazine and desisopropyl atrazine) were not observed in either treatment.

Table 2.3: Experiment 1 and 2 half-lives. MC = mercuric chloride. SE = Standard Error. Significant degradation after 60 and 365 d when p < 0.05 (repeated measures ANOVA, Appendix Table 6), NS = not significant. – indicates herbicide not tested. The superscripts a,b represent significantly different slopes in Figs. 2.3-2.5 graphs (Appendix Table 7), indicating differences in persistence between treatments for that herbicide.

Expt. 1, 60 d Expt. 2, 365 d Herbicide Dark 25°C Dark 25°C + MC Dark, 25°C Light, 25°C Dark, 31°C Diuron NS NS 1568 ± 222a 556 ± 14b 818 ± 51b Atrazine 631 ± 491 NS 1606 ± 129a 2089 ± 338a,b 2066 ± 154b Hexazinone 479 ± 240 NS 2792 ± 172a 2799 ± 467a 1434 ± 114b Tebuthiuron 433 ± 150 NS 5214 ± 705a 2650 ± 291b 2840 ± 358b Ametryn 419 ± 264 NS - - - Simazine 579 ± 294 NS - - - Metolachlor - - 281 ± 1a 320 ± 61a 298 ± 12a 2,4-D - - 146 ± 19a 494 ± 72b 88 ± 6a

2.4.2 Experiment 2

Very little degradation of the PSII herbicides was observed (< 6%) over the first 60 d of the second flask experiment using 20 µm-filtered coastal water and less than 15% degradation of 2,4-D and metolachlor was evident over this period (Figs. 2-4). After 365 d significant degradation was observed for all herbicides in coastal seawater (Appendix Table 6). Diuron exhibited the shortest

(t½ = 1568 d) and tebuthiuron the longest (t½ = 5214 d) half-lives of the PSII herbicide at 25°C under dark conditions (Table 2.3). The non-PSII herbicides metolachlor and 2,4-D degraded much more rapidly exhibiting half-lives of 281 d and 146 d respectively (Table 2.3). Exposure to light and temperature resulted in a significant difference in slopes, ln [concentration] versus time, for of all herbicides apart from metolachlor (Appendix Table 7) but there was no clear pattern between persistence and temperature or light (Table 2.3). For example the most rapid degradation for diuron was in the light at 25°C (t½ = 556 d) whereas atrazine degraded most rapidly at 25°C in the dark (t½ =1606 d). Experiment 2, performed over a longer duration and using less filtered coastal waters, confirmed the high persistence of four PSII herbicides in the dark at 25°C (1568 – 5214 d) and a more rapid degradation of the non-PSII herbicides metolachlor and 2,4-D (146 – 281 d) (Table 2.3). These results indicate that, while the coastal GBR seawater contains high bacterial densities (> 2 x 106 cells ml-1, Appendix Table 2) that either (i) few bacteria are capable of metabolising the herbicides or (ii) other sources of carbon are preferentially utilised (and cycled) in the flasks. This experiment used natural coastal seawater that was only coarsely filtered to retain its native microbial community and excluded larger organisms such as zooplankton (> 20 µm) which may introduce large organic carbon loads and inconsistencies between flasks (OECD, 2005). Without performing an exhaustive independent study of the microbial communities in the seawater we cannot be certain that known herbicide degraders were present; however, coastal GBR seawater usually has wide bacterial diversity between 500 to 7000 operational taxonomic units per litre (Bourne et al., 2013; Webster et al., 2010). Herbicide concentrations used here (~ 10 µg l-1) were within the range of receiving waters that flow into the coastal GBR environment (Davis et al., 2012; Lewis et al., 2009; Smith et al., 2012) and the HPLC-MS was sensitive enough to allow direct analysis of these environmental concentrations without pre-concentrations steps which can introduce further uncertainties. Differences in degradation rates between replicate flasks were potentially due to different microbial communities and unequal distribution of particulates and organic matter between flasks as the water was filtered to 20 µm and not likely to be absolutely uniform between replicates. Most other herbicide degradation experiments in seawater have used very high starting concentrations ≥ 5000 µg l-1 (Konstantinou et al., 2001; Navarro et al., 2004a, b). As natural microbial degradation relies on indigenous bacterial communities to adapt to using the contaminant as a carbon source (Mandelbaum et al., 2008), unrealistically high concentrations of herbicides in solution could artificially influence natural microbial communities and subsequently affect apparent persistence and may even be toxic to some components of the communities. Furthermore, the herbicide concentrations here represent less 30

(a) Tebuthiuron (b) Ametryn 2.6 2.4

2.4 2.2

2.2 2.0

2.0 1.8

1.8 1.6 Tebuthiuron Ametryn 2 Slope -0.0016009, r2 = 0.48 Slope -0.0016557, r = 0.30 1.6 1.4 Tebuthiuron MC Ametryn MC 2 Slope -0.0009738, r2 = 0.14 Slope -0.0005676, r = 0.09 1.4 1.2 0 20 40 60 0 20 40 60

2.6 (c) Hexazinone 2.6 (d) Simazine

) 2.4 2.4

-1 2.2 2.2

2.0 2.0

1.8 1.8 Hexazinone Simazine 2 Concentration (µg l (µg Concentration Slope -0.0014467, r = 0.38 Slope -0.0011960, r2 = 0.35 1.6 1.6 Hexazinone MC Simazine MC 2 Slope -0.0008606, r = 0.14 Slope -0.0003057, r2 = 0.03 1.4 1.4 0 20 40 60 0 20 40 60

(e) Atrazine (f) Diuron 2.6 2.5 2.4 2.0 2.2 1.5 2.0 1.0 1.8 Atrazine Diuron Slope -0.0010987, r2 = 0.26 Slope -0.0013510, r2 = 0.36 1.6 0.5 Atrazine MC Diuron MC Slope -0.0005700, r2 = 0.08 Slope -0.0003976 r2 = 0.04 1.4 0.0 0 20 40 60 0 20 40 60

Time (days) Figure 2.1: Experiment 1 half-life results. ln(x) concentration of the herbicide mixture: (a) tebuthiuron, (b) ametryn, (c) hexazinone, (d) simazine, (e) atrazine, and (f) diuron over 60 days. SE = Standard error. MC = mercuric chloride treatment.

(a) Diuron Dark, 25° C (b) Diuron Light, 25° C (c) Diuron Dark, 31° C

2.5 2.5 2.5 )

-1 2.0 2.0 2.0

1.5 1.5 1.5

1.0 1.0

ln (Concentration ln (Concentration µg l 1.0

0.5 t = 1568 ± 222 days 0.5 t = 556 ± 142 days 0.5 ½ ½ t½ = 818 ± 51 days 2 2 Slope -0.0004419, r = 0.70 Slope -0.0012457, r = 0.51 Slope -0.0008467, r2 = 0.92

0 100 200 300 400 0 100 200 300 400 0 100 200 300 400

(d) Atrazine Dark, 25° C (e) Atrazine Light, 25° C (f) Atrazine Dark, 31° C

2.5 2.5 2.5 )

-1 2.0 2.0 2.0

1.5 1.5 1.5

1.0 1.0

ln (Concentration ln (Concentration µg l 1.0

0.5 t = 1606 ± 129 days 0.5 t = 2089 ± 338 days 0.5 ½ ½ t½ = 2066 ± 154 days 2 2 Slope -0.0004313, r = 0.88 Slope -0.0003318, r = 0.65 Slope -0.0003355, r2 = 0.89

0 100 200 300 400 0 100 200 300 400 0 100 200 300 400

Time (days) Figure 2.2: Experiment 2 half-life results for diuron and atrazine. ln(x) concentration of individual herbicide treatments: (a) diuron dark 25°C, (b) diuron light 25°C, (c) diuron dark 31°C, (d) atrazine dark 25°C, (e) atrazine light 25°C, and (f) atrazine dark 31°C over 365 days. Dashed lines represent 95% confidence intervals. Half-life reported ± SE.

(a) Hexazinone Dark, 25° C (b) Hexazinone Light, 25° C (c) Hexazinone Dark, 31° C

2.5 2.5 2.5 )

-1 2.0 2.0 2.0

1.5 1.5 1.5

1.0 1.0

ln (Concentration ln µg l (Concentration 1.0

0.5 t = 2792 ± 172 days 0.5 t = 2799 ± 467 days 0.5 ½ ½ t½ = 1434 ± 114 days 2 2 Slope -0.0002482, r = 0.92 Slope -0.0002476, r = 0.63 Slope -0.0004833, r2 = 0.88

0 100 200 300 400 0 100 200 300 400 0 100 200 300 400

(d) Tebuthiuron Dark, 25° C (e) Tebuthiuron Light, 25° C (f) Tebuthiuron Dark, 31° C

2.5 2.5 2.5 )

-1 2.0 2.0 2.0

1.5 1.5 1.5

1.0 1.0 1.0 ln (Concentration ln µg l (Concentration

0.5 0.5 0.5 t = 5214 ± 705 days t = 2650 ± 291 days ½ ½ t½ = 2840 ± 358 days 2 2 Slope -0.0001329, r = 0.72 Slope -0.0002615, r = 0.79 Slope -0.0002440, r2 = 0.75 0.0 0.0 0 100 200 300 400 0 100 200 300 400 0 100 200 300 400

Time (days) Figure 2.3: Experiment 2 half-life results for hexazinone and tebuthiuron. ln(x) concentration of individual herbicide treatments: (a) hexazinone dark 25°C, (b) hexazinone light 25°C, (c) hexazinone dark 31°C, (d) tebuthiuron dark 25°C, (e) tebuthiuron light 25°C, and (f) tebuthiuron dark 31°C over 365 days. Dashed lines represent 95% confidence intervals. Half-life reported ± SE.

(a) Metolachlor Dark, 25° C (b) Metolachlor Light, 25° C (c) Metolachlor Dark, 31° C 1.8 1.8 1.8

1.6 1.6 1.6

) -1 1.4 1.4 1.4

1.2 1.2 1.2

1.0 1.0 1.0

0.8 0.8 0.8 ln (Concentration ln µg l (Concentration 0.6 0.6 0.6

0.4 0.4 0.4 t = 281 ± 11 days ½ t½ = 320 ± 61 days t½ = 298 ± 12 days 2 2 0.2 Slope -0.0025371, r = 0.94 0.2 Slope -0.0021684, r = 0.620.2 Slope -0.0023267, r2 = 0.97

0 100 200 300 400 0 100 200 300 400 0 100 200 300 400

(d) 2,4-D Dark, 25° C (e) 2,4-D Light, 25° C (f) 2,4-D Dark, 31° C

3.0 3.0 3.0 )

-1 2.5 2.5 2.5

2.0 2.0 2.0

1.5 1.5 1.5 ln (Concentration ln µg l (Concentration 1.0 1.0 1.0

t = 146 ± 19 days t = 494 ± 72 days 0.5 ½ 0.5 ½ 0.5 t½ = 88 ± 6 days 2 2 Slope -0.0047586, r = 0.76 Slope -0.0014036, r = 0.78 Slope -0.0078874, r2 = 0.94

0 100 200 300 400 0 100 200 300 400 0 100 200 300 400

Time (days) Figure 2.4: Experiment 2 half-life results for metolachlor and 2,4-D. ln(x) concentration of individual herbicide treatments: (a) metolachlor dark 25°C, (b) metolachlor light 25°C, (c) metolachlor dark 31°C, (d) 2,4-D dark 25°C, (e) 2,4-D light 25°C, and (f) 2,4-D dark 31°C over 365 days. Dashed lines represent 95% confidence intervals. Half-life reported ± SE.

(a) Diuron L25 (b) Atrazine D25

1.0 1.0

) -1

8 10 ) -1

0.8 ) 0.8

-1 )

-1 8 6 0.6 0.6

concentration (µg l (µg concentration 6

4 0.4 0.4 4

0.2 l (µg concentration Atrazine 0.2 Diuron concentration (µg l (µg concentration Diuron 2

3,4-Dichloroaniline 2 Desethyl Atrazine concentration (µg l (µg concentration Atrazine Desethyl Diuron 0.0 Atrazine 0.0 3,4-Dichloroaniline Desethyl Atrazine 0 0 0 100 200 300 400 0 100 200 300 400

10 )

-1

-1 )

) 0.8 0.8

-1 -1 8 8

0.6 0.6

6 6

0.4 0.4

4 4

0.2 l (µg concentration Atrazine 0.2 Atrazine concentration (µg l (µg concentration Atrazine

2 2

Desethyl Atrazine concentration (µg l (µg concentration Atrazine Desethyl Desethyl Atrazine concentration (µg l (µg concentration Atrazine Desethyl Atrazine 0.0 Atrazine 0.0 Desethyl Atrazine Desethyl Atrazine 0 0 0 100 200 300 400 0 100 200 300 400

Time (days) Figure 2.5: Concentration of metabolites of diuron and atrazine. Concentrations of individual herbicides including measured metabolites (a) diuron light 25°C, (b) atrazine dark 25°C, (c) atrazine light 25°C, and (d) atrazine dark 31°C, over 365 days. Bars represent ± SE. Note the concentration scales for the parent and metabolite are on opposite sides of each graph.

than 1% of the total organic carbon (the majority of which was dissolved) in the seawater used in Experiment 2 (Appendix Table 2), so bacteria had access to a selection of more abundant and natural carbon sources (which is the case in the natural coastal environment). In combination, the low herbicide concentrations and the abundance of other carbon sources are likely to have limited adaptation rate of the native microbial community in flasks to metabolise the herbicides more rapidly (Ahtiainen et al., 2003). The identification of the atrazine metabolite desethyl atrazine (DEA) in all three treatment conditions (Fig. 2.5) confirms biodegradation of this herbicide (Mandelbaum et al., 2008; Radosevich and Tuovinen, 2003). The diuron metabolite 3,4 dichloroaniline (DCA) was also detected in one treatment and, although sometimes attributed to photodegradation and hydrolysis, DCA is usually considered a product of biodegradation (Moncada, 2004; Stasinakis et al., 2009). The degradation metabolites of other herbicides in the study were either unknown, below detection limits, or not analysed. The appearance of metabolites was late in the experiment ≥ 180 d and the concentrations were less than the reporting limit of 0.2 µg l-1. While these metabolites are sometimes detected in river runoff and in the GBR lagoon (Bainbridge et al., 2009; Davis et al., 2011; Smith et al., 2012), the low concentrations detected and/or absence in the present study is likely to reflect the slow degradation of parent compounds into very low concentrations of metabolites that also start degrading (but at concentrations too low to detect). Greater initial herbicide concentrations would be needed in order positively identify more metabolites and the inclusion of labelled compounds and the establishment of mass balances would also further the understanding herbicide fate in the marine environment. Degradation of herbicides was significantly influenced by temperature and light for all herbicides except metolachlor (Table 2.3 and Appendix Table 6). Although photodegradation can contribute to the breakdown of several of these herbicides (Ganapathy, 1996; Giacomazzi and Cochet, 2004; Gunasekara, 2004; Okamura, 2002), the turbid conditions during flood plumes that transport herbicides into the marine environment are likely to greatly attenuate both visible and UV to levels well below the very high intensities that have been applied in previous studies. As the lights used in the present study emitted no UV component, any difference in persistence between the light (L25) and dark (D25) treatment must be due to changes in bacterial communities. In the presence of light, the two substituted urea herbicides diuron and tebuthiuron degraded at least twice as rapidly (yet still the half-lives remained long at 556 d for diuron and 2650 d for tebuthiuron, Table 2.4). Light had no impact on the persistence of atrazine, hexazinone and metolachlor (Table 2.4). Other studies have reported contrary effects in that atrazine and simazine degrade more rapidly under illumination (Navarro et al., 2004a, b). Differences are likely due to the combination of 36

distinctive microbial communities, different starting concentrations and possibly light intensities (Navarro et al., 2004a, b). Under identical conditions to those in the present study Mercurio et al. (Mercurio et al., 2014) demonstrated more rapid degradation of glyphosate in the presence of low light levels. In contrast to the only other study on the degradation of 2,4-D in seawater (Dąbrowska et al., 2006), this herbicide degraded over 3-fold more slowly in the light (Table 2.4). Again differences in the amount of starting material (Dabrowska et al. (Dąbrowska et al., 2006) used 2000 µg l-1) and microbial community composition and/or light intensity may be responsible.

Table 2.4: The ratio of half-lives between each treatment from experiment 2. The superscripts a,b represent significantly different slopes as compared to D25 (Appendix Table 7) in Figs. 3-5 graphs that in turn indicate differences in persistence between treatments for that herbicide.

Diuron Atrazine Hexazinone Tebuthiuron Metolachlor 2,4-D D25 1.0a 1.0a 1.0a 1.0a 1.0a 1.0a L25 0.4b 1.3a,b 1.0a 0.5b 1.1a 3.4b D31 0.5b 1.3b 0.5b 0.5b 1.1a 0.6a

In the high summer temperature of nearshore waters (31°C, D31) the half-lives of diuron, hexazinone, tebuthiuron and 2,4-D were all shorter by a factor of ~2 (ie 40 – 60 %), whereas the half-life of atrazine was slightly but significantly longer (i.e. 30 %) in comparison to treatments at the mean annual temperature (25°C, D25) (Tables 2.3 and 2.4). More rapid degradation at higher temperatures may reflect more rapid metabolism by the microbial community; however decreases observed for atrazine suggests an influence of temperature on microbial community structure (Bourne and Webster, 2013). Although the increase of 6°C increased the degradation of diuron, hexazinone, tebuthiuron and 2,4-D, the persistence of the PSII herbicides remained long (t1/2 > 800 d), while the shortest half-life observed in this experiment of 88 d was observed for 2,4-D under these warmer conditions (Table 2.3). In a previous study atrazine may have degraded slightly more rapidly at an elevated temperature of 40°C as compared to 20°C (but this was not tested statistically) (Navarro et al., 2004a). Atrazine degraded 30% more slowly at 31°C in the present study, perhaps due to (untested) differences in microbial composition. As with changes in light, the degradation rate of metolachlor was not impacted by these temperature conditions (Table 2.4). Degradation studies which simulate natural conditions, such as low herbicide concentrations, relevant temperatures and light, natural microbial communities and no additional nutrients, provide the most realistic flask conditions for estimating persistence (Ahtiainen et al., 2003; OECD, 2005). This simulation study of degradation of multiple herbicides provides the most representative information to date on persistence in seawater, while a far greater body of studies on

herbicide degradation have been performed in freshwater, See Appendix Table 8 for a relevant summary (Barbash, 2007; DeLorenzo and Fulton, 2012; Mackay et al., 1997; PPDB, 2011; Starner et al., 1999; USEPA, 2003; Vencill, 2002). In the present study very little degradation was recorded in seawater over the standard 60 d period (Experiment 1) and short experiments such as this are insufficient to estimate herbicide persistence in natural seawater. Over 360 d, the presence of moderate light and elevated temperatures affected the persistence of most of the herbicides; however, the scale and direction of the differences were not predictable and were likely due to changes in microbial community composition. Further simulation experiments are needed to assess the wide variety of herbicides detected in marine systems (Davis et al., 2011; Smith et al., 2012), the results of which can be utilised in risk assessments for herbicides in the marine environment. Future studies should also include open tank or pond systems that include relevant sediments and a wider variety of light and temperature conditions to better mimic conditions in the field. The half-lives of the PSII herbicides were all greater than a year, indicating the potential for long persistence in the marine environment. Little degradation of these herbicides would be expected during the wet season with runoff and associated flood plumes transporting a high proportion of the original herbicides in rivers into the GBR lagoon. The long persistence of herbicides identified here also helps explain detection of herbicides in nearshore waters of the GBR year round (Bentley et al., 2012; Shaw et al., 2010) and raises the possibility of accumulation of herbicides and metabolites in some locations. Chronic exposure of GBR and catchment biota to PSII herbicides (from microbial communities to macrophytes) remains largely unstudied (Negri et al., 2015) and should be a future focus for research and risk assessment.

2.5 References

Ahtiainen, J., Aalto, M., Pessala, P., 2003. Biodegradation of chemicals in a standardized test and in environmental conditions. Chemosphere 51, 529-537. AIMS, 2013. Sea temperature monitoring program, Australian Institute of Marine Science, Townsville, http://www.aims.gov.au/docs/data-centre/seatemperatures.html. Amaral-Zettler, L., Artigas, L.F., Baross, J., Bharathi, L., Boetius, A., Chandramohan, D., Herndl, G., Kogure, K., Neal, P., Pedrós-Alió, C., 2010. A global census of marine microbes, Life in the world’s oceans: Diversity, distribution and abundance. Oxford: Wiley-Blackwell, pp. 223-245. Bainbridge, Z.T., Brodie, J.E., Faithful, J.W., Sydes, D.A., Lewis, S.E., 2009. Identifying the land- based sources of suspended sediments, nutrients and pesticides discharged to the Great Barrier Reef from the Tully–Murray Basin, Queensland, Australia. Mar. Freshwater Res. 60, 1081-1090. Bainbridge, Z.T., Wolanski, E., Álvarez-Romero, J.G., Lewis, S.E., Brodie, J.E., 2012. Fine sediment and nutrient dynamics related to particle size and floc formation in a Burdekin River flood plume, Australia. Mar. Pollut. Bull. 65, 236-248.

Barbash, J.E., 2007. 9.15 - The geochemistry of pesticides, in: Editors-in-Chief: Holland, D.H.a.T., K.K. (Ed.), Treatise on Geochemistry. Pergamon, Oxford, pp. 1-43. Bentley, C., Chue, K.L., Devlin, M., Mueller, J., Paxman, C., 2012. Pesticide monitoring in inshore waters of the Great Barrier Reef using both time-integrated and event monitoring techniques (2011 - 2012). University of Queensland, Coopers Plains, pp. 1-94. Beulke, S., Brown, C.D., 2001. Evaluation of methods to derive pesticide degradation parameters for regulatory modelling. Biol. Fert. Soils 33, 558-564. Bourne, D.G., Dennis, P.G., Uthicke, S., Soo, R.M., Tyson, G.W., Webster, N.S., 2013. Coral reef invertebrate microbiomes correlate with the presence of photosymbionts. ISME J. 7, 1452- 1458. Bourne, D.G., Webster, N.S., 2013. Coral reef bacterial communities, The Prokaryotes. Springer, pp. 163-187. Brodie, J., Wolanski, E., Lewis, S., Bainbridge, Z.T., 2012a. An assessment of residence times of land-sourced contaminants in the Great Barrier Reef lagoon and the implications for management and reef recovery. Mar. Pollut. Bull. 65, 267-279. Brodie, J.E., Kroon, F.J., Schaffelke, B., Wolanski, E.C., Lewis, S.E., Devlin, M.J., Bohnet, I.C., Bainbridge, Z.T., Waterhouse, J., Davis, A.M., 2012b. Terrestrial pollutant runoff to the Great Barrier Reef: An update of issues, priorities and management responses. Mar. Pollut. Bull. 65, 81-100. Brodie, J.E., Waterhouse, J., 2012. A critical review of environmental management of the ‘not so Great’ Barrier Reef. Estuar. Coast. Shelf Sci. 104–105, 1-22. Dąbrowska, D., Kot-Wasik, A., Namieśnik, J., 2006. Stability studies of selected phenoxyacid herbicides in water samples and determination of their transformation products. Bull. Environ. Contam. Toxicol. 77, 245-251. Davies-Colley, R.J., Smith, D.G., 2001. Turbidity, suspended sediment, and water clarity: A review. J. Am. Water Resour. As. 37, 1085-1101. Davis, A., Lewis, S., Bainbridge, Z.T., Brodie, J., Shannon, E., 2008. Pesticide residues in waterways of the lower Burdekin region: Challenges in ecotoxicological interpretation of monitoring data. Aust. J. Ecol. 14, 89-108. Davis, A.M., Lewis, S.E., Bainbridge, Z.T., Glendenning, L., Turner, R.D.R., Brodie, J.E., 2012. Dynamics of herbicide transport and partitioning under event flow conditions in the lower Burdekin region, Australia. Mar. Pollut. Bull. 65, 182-193. Davis, A.M., Thorburn, P.J., Lewis, S.E., Bainbridge, Z.T., Attard, S.J., Milla, R., Brodie, J.E., 2011. Environmental impacts of irrigated sugarcane production: Herbicide run-off dynamics from farms and associated drainage systems. Agric. Ecosyst. Environ. DeLorenzo, M.E., Fulton, M.H., 2012. Comparative risk assessment of permethrin, chlorothalonil, and diuron to coastal aquatic species. Mar. Pollut. Bull. 64, 1291-1299. Ganapathy, C., 1996. Environmental fate of hexazinone. Environmental Monitoring & Pest Management Branch, Department of Pesticide Regulation Sacramento, CA, 1-15. GBRMPA, 2010 Accessed March 2015. Water quality guidelines for the Great Barrier Reef Marine Park. Great Barrier Reef Marine Park Authority. http://www.gbrmpa.gov.au/__data/assets/pdf_file/0017/4526/GBRMPA_WQualityGuidelin esGBRMP_RevEdition_2010.pdf Giacomazzi, S., Cochet, N., 2004. Environmental impact of diuron transformation: A review. Chemosphere 56, 1021-1032. Glöckner, F.O., Stal, L.J., Sandaa, R., Gasol, J.M., O'Gara, F., Hernandez, F., Labrenz, M., Stoica, E., Varela, M.M., Bordalo, A., 2012. Marine microbial diversity and its role in ecosystem functioning and environmental change. ESF Marine Board Position Paper 17. Gunasekara, A.S., 2004. Environmental Fate of Simazine, Environmental Monitoring Branch, Cal/EPA Department of Pesticide Regulation. 1-36.

Hargreaves, P.A., Simpson, B.W., Ruddle, L.J., Packett, R., 1999. Persistence and fate of pesticides in sugarcane soils, Proceedings Australian Society of Sugar Cane Technologists. Watson Herguson and Company, pp. 287-293. Kennedy, K., Schroeder, T., Shaw, M., Haynes, D., Lewis, S., Bentley, C., Paxman, C., Carter, S., Brando, V.E., Bartkow, M., Hearn, L., Mueller, J.F., 2012. Long term monitoring of photosystem II herbicides – Correlation with remotely sensed freshwater extent to monitor changes in the quality of water entering the Great Barrier Reef, Australia. Mar. Pollut. Bull. 65, 292-305. Konstantinou, I.K., Zarkadis, A.K., Albanis, T.A., 2001. Photodegradation of selected herbicides in various natural waters and soils under environmental conditions. J. Environ. Qual. 30, 121- 130. Kroon, F.J., Kuhnert, P.M., Henderson, B.L., Wilkinson, S.N., Kinsey-Henderson, A., Abbott, B., Brodie, J.E., Turner, R.D.R., 2012. River loads of suspended solids, nitrogen, phosphorus and herbicides delivered to the Great Barrier Reef lagoon. Mar. Pollut. Bull. 65, 167-181. Lazartigues, A., Thomas, M., Banas, D., Brun-Bellut, J., Cren-Olivé, C., Feidt, C., 2013. Accumulation and half-lives of 13 pesticides in muscle tissue of freshwater fishes through food exposure. Chemosphere 91, 530-535. Lewis, S.E., Brodie, J.E., Bainbridge, Z.T., Rohde, K.W., Davis, A.M., Masters, B.L., Maughan, M., Devlin, M.J., Mueller, J.F., Schaffelke, B., 2009. Herbicides: A new threat to the Great Barrier Reef. Environ. Pollut. 157, 2470-2484. Lewis, S.E., Schaffelke, B., Shaw, M., Bainbridge, Z.T., Rohde, K.W., Kennedy, K., Davis, A.M., Masters, B.L., Devlin, M.J., Mueller, J.F., Brodie, J.E., 2012. Assessing the additive risks of PSII herbicide exposure to the Great Barrier Reef. Mar. Pollut. Bull. 65, 280-291. Mackay, D., Shiu, W.Y., Ma, K.C., 1997. Illustrated handbook of physical-chemical properties and environmental fate for organic chemicals: Pesticide Chemicals. CRC Press. Mandelbaum, R.T., Sadowsky, M.J., Wackett, L.P., 2008. Chapter 22 - Microbial degradation of s- triazine herbicides, in: LeBaron, H.M., McFarland, J.E., Burnside, O.C. (Eds.), The Triazine Herbicides. Elsevier, San Diego, pp. 301-328. Meakins, N.C., Bubb, J.M., Lester, J.N., 1995. The mobility, partitioning and degradation of atrazine and simazine in the salt marsh environment. Mar. Pollut. Bull. 30, 812-819. Mercurio, P., Flores, F., Mueller, J.F., Carter, S., Negri, A.P., 2014. Glyphosate persistence in seawater. Mar. Pollut. Bull. 85, 385-390. Miller, C.B., 2009. Biological Oceanography. Wiley-Blackwell. Hoboken, NJ, USA. Moncada, A., 2004. Environmental fate of diuron. Environmental Monitoring Branch, Department of Pesticide Regulation, Sacramento, CA, 1-11. Navarro, S., Vela, N., Giménez, M.J., Navarro, G., 2004a. Effect of temperature on the disappearance of four triazine herbicides in environmental waters. Chemosphere 57, 51-59. Navarro, S., Vela, N., Giménez, M.J., Navarro, G., 2004b. Persistence of four s-triazine herbicides in river, sea and groundwater samples exposed to sunlight and darkness under laboratory conditions. Sci. Tot. Environ. 329, 87-97. Negri, A.P., Flores, F., Mercurio, P., Mueller, J.F., Collier, C.J., 2015. Lethal and sub-lethal chronic effects of the herbicide diuron on seagrass. Aquat Toxicol 165, 73-83. OECD, 1992. OECD guidelines for testing of chemicals—306 Biodegradability in seawater, pp. 1- 27; Accessed March 2015. OECD, 2004. Test No. 309: Aerobic mineralisation in surface water – Simulation biodegradation test. OECD Guidelines for the Testing of Chemicals, Section 3, OECD Publishing, Paris. OECD, 2005. OECD Guideline for testing of chemicals: Part 1: Principles and strategies related to the testing of degradation of organic chemicals. Accessed March 2015. Okamura, H., 2002. Photodegradation of the antifouling compounds Irgarol 1051 and diuron released from a commercial antifouling paint. Chemosphere 48, 43-50. PPDB, 2011. Pesticide Properties Database. Agriculture & Environment Research Unit (AERU), University of Hertfordshire. Accessed March 2015 40

Radosevich, M., Tuovinen, O.H., 2003. Microbial degradation of atrazine in soils, sediments, and surface water, Pesticide Decontamination and Detoxification. American Chemical Society, pp. 129-139. Schroeder, T., Devlin, M.J., Brando, V.E., Dekker, A.G., Brodie, J.E., Clementson, L.A., McKinna, L., 2012. Inter-annual variability of wet season freshwater plume extent into the Great Barrier Reef lagoon based on satellite coastal ocean colour observations. Mar. Pollut. Bull. 65, 210-223. Shaw, M., Furnas, M.J., Fabricius, K., Haynes, D., Carter, S., Eaglesham, G., Mueller, J.F., 2010. Monitoring pesticides in the Great Barrier Reef. Mar. Pollut. Bull. 60, 113-122. Smith, R., Middlebrook, R., Turner, R., Huggins, R., Vardy, S., Warne, M., 2012. Large-scale pesticide monitoring across Great Barrier Reef catchments – Paddock to Reef Integrated Monitoring, Modelling and Reporting Program. Mar. Pollut. Bull. 65, 117-127. Starner, K., Kuivila, K.M., Jennings, B., Moon, G.E., 1999. Degradation rates of six pesticides in water from the Sacramento River, California. US Geological Survey Toxic Substances Hydrology Program Water Resource Investigation Rep, 89-99. Stasinakis, A.S., Kotsifa, S., Gatidou, G., Mamais, D., 2009. Diuron biodegradation in activated sludge batch reactors under aerobic and anoxic conditions. Water Res. 43, 1471-1479. Thomas, K.V., McHugh, M., Waldock, M., 2002. Antifouling paint booster biocides in UK coastal waters: Inputs, occurrence and environmental fate. Sci. Tot. Environ. 293, 117-127. Trebst, A., 2008. Chapter 8 - The mode of action of triazine herbicides in plants, in: LeBaron, H.M., McFarland, J.E., Burnside, O.C. (Eds.), The Triazine Herbicides. Elsevier, San Diego, pp. 101-II. USEPA, 2003. Reregistration Eligibility Decision for Diuron. Environmental Protection Agency, Washington, DC, 66; Accessed March 2015. Uthicke, S., Altenrath, C., 2010. Water column nutrients control growth and C: N ratios of symbiont-bearing benthic foraminifera on the Great Barrier Reef, Australia. Limnol. Oceanog. 55, 1681-1696. Vencill, W.K., 2002. Herbicide Handbook. Weed Science Society of America. Webster, N.S., Taylor, M.W., Behnam, F., Lücker, S., Rattei, T., Whalan, S., Horn, M., Wagner, M., 2010. Deep sequencing reveals exceptional diversity and modes of transmission for bacterial sponge symbionts. Environ. Microbiol. 12, 2070-2082. Zar, J.H., 1984. Biostatistical analysis. 2nd edition. Prentice Hall USA.

2.6

Chapter 3: Glyphosate persistence in seawater

3.1 Abstract

Glyphosate is one of the most widely applied herbicides globally but its persistence in seawater has not been reported. Here we quantify the biodegradation of glyphosate using standard “simulation” flask tests with native bacterial populations and coastal seawater from the Great Barrier Reef. The half-life for glyphosate at 25°C in low-light was 47 days, extending to 267 days in the dark at 25°C and 315 days in the dark at 31°C, which is the longest persistence reported for this herbicide. AMPA, the microbial transformation product of glyphosate, was detected under all conditions, confirming that degradation was mediated by the native microbial community. This study demonstrates glyphosate is moderately persistent in the marine water under low light conditions and is highly persistent in the dark. Little degradation would be expected during flood plumes in the tropics, which could potentially deliver dissolved and sediment-bound glyphosate far from shore.

3.2 Introduction

3.2.1 Water quality and pesticides in the Great Barrier Reef

There has been increasing concern over the global loss of corals and seagrass and this has been particularly well documented for the World Heritage listed Great Barrier Reef (GBR) (De’ath et al., 2012; Orth et al., 2006). Management of this vast resource requires balancing coastal pressures from port and urban development, the extensive agriculture industry in GBR catchments, and needs to consider potential impacts on water quality from these activities (Brodie et al., 2013). Nearshore water quality around reefs and seagrass beds is most heavily impacted during the summer wet season from November to March when heavy rains deliver river runoff containg excess sediments, nutrients, and pesticides (Brodie et al., 2012a; Brodie and Waterhouse, 2012; Lewis et al., 2009). Satellite imagery effectively captures these events and their associated flood plumes migrating up to 50 km offshore as far as the midshelf coral reefs (Bainbridge et al., 2012). A wide spectrum of pesticides have been detected in waters of the GBR, but herbicides are often more water soluble and mobile than contemporary insecticides and fungicides, and as a consequence, are more frequently detected in the river mouths and GBR lagoon (Brodie et al., 2012b; Davis et al., 2011; Lewis et al., 2009). The photosystem II herbicides have been the primary group detected in GBR waters; however, glyphosate (CAS number 1071-83-6) is the most widely

used herbicide in Australia, in the GBR catchments and elsewhere, with approximately 15,000 tonnes applied annually to control agricultural, urban and roadside weeds (Beeton et al., 2006; Radcliffe, 2002). The popularity of glyphosate has increased steadily since its introduction in the mid 1970’s as it exhibits: (i) relatively low toxicity to non-target organisms (Borggaard and Gimsing, 2008; Duke and Powles, 2008); (ii) apparent rapid microbial degradation to a major metabolite aminophosphonic acid (AMPA) (Giesy et al., 2000) and (iii) strong adsorption to soils and sediments potentially limiting runoff in surface water (Duke and Powles, 2008; Pérez et al., 2012; Solomon and Thompson, 2003).

3.2.2 Glyphosate monitoring and toxicity

Glyphosate has not often been included in regular monitoring programs as the stand-alone analytical methods are often cost-prohibitive, resulting in a long term deficiency in global datasets (Barceló and Hennion, 2003). However, glyphosate has been regularly detected in a diversity of waterbodies when samples were analysed (See Table 3.1). For example, glyphosate and AMPA were detected in 36% and 69% of water samples respectively, following extensive sampling of aquatic ecosystems in the Midwestern United States (Battaglin et al., 2005; Scribner et al., 2003). Concentrations measured in field studies in Australia have been reported as high as 54 µg l-1 (Davis et al., 2011). A similar concentration (40.8 µg l-1) was measured in Canada (Struger et al., 2008), while field dissipation studies found concentrations as high as 1700 µg l-1 (Mensink and Janssen, 1994; NHMRC, 2011). Glyphosate exhibits a relatively low toxicity to non-target marine organisms, with the LC50s of glyphosate (lethal concentration which affects half of the sample population) in the 10-1000 mg l-1 range. However, recent research suggests that low µg l-1 concentrations can affect natural coastal microbial communities (Stachowski-Haberkorn et al., 2008). The toxicity of the glyphosate compound compared to glyphosate formulations has been extensively reviewed with multiple studies demonstrating that the formulations and surfactant additives are usually more toxic to test species (Barceló and Hennion, 2003; Giesy et al., 2000). The Australian guideline trigger values for the protection of 90% and 99% of freshwater species are 2000 and 370 µg l-1 respectively (ANZECC and ARMCANZ, 2000) and these may in some instances be applied as “low reliability” guidelines in the absence of marine values.

3.2.3 Glyphosate persistence in water

As glyphosate is heavily used in the agriculture industry, the literature on its persistence is heavily weighted towards degradation in soil (See Table 3.2 for example half-lives). The average half-life in natural freshwaters for glyphosate is >60 days, with the most important route of 43

Table 3.1: Example glyphosate concentrations in the aquatic and marine environment. BDL = Below detection limit.

Concentration µg l-1 Sample type, location Reference 54 (peak) Paddock Run-off, Queensland Australia (Davis et al., 2011) BDL - 0.74 River Jauron, Central France (Pesce et al., 2008) 1.2 (peak) Marennes-Oléron Bay, Atlantic coast, (Samain and France McCombie, 2008) BDL – 4.5 Streams, Midwestern United States (Scribner et al., 2003) BDL – 40.8 Surface water, Southern Ontario, Canada (Struger et al., 2008) BDL – 0.59 Tributaries to River Ruhr, Germany (Skark et al., 1998) degradation being mediated by bacteria (Bonnet et al., 2007). Increasingly, there has been evidence for off-site movement of glyphosate into aquatic ecosystems (Table 3.1), but no information has been published on glyphosate persistence in seawater. The aim of this study is to quantify the persistence of glyphosate in seawater in standard tests but under natural conditions and at environmentally relevant concentrations.

3.3 Methods

3.3.1 Simulation test conditions

A series of glyphosate degradation experiments were carried out in flasks according to the OECD methods for “simulation tests” (OECD, 2005). The tests were conducted in natural seawater containing a native bacterial community and no addition of nutrients or artificial inoculum to best mimic ecological conditions. The tests were conducted under three scenarios: (1) 25°C in the dark which corresponds to the mean annual seawater temperature on the GBR (AIMS, 2013); (2) 25°C in low light conditions and (3) 31°C in the dark which is a summer maximum temperature for nearshore areas of the mid-northern regions of the GBR (AIMS, 2013). Three temperature- regulated incubator shakers (Thermoline TLM-530) were used in the experiments. A series of 6 x 900 mm LED strips (Superlight LED Lighting, Generation 3 High-Output LED Turbostrip) were fitted to one shaker, providing an even light environment of 40 µmol photons m-2s-1 over a 12:12 light day cycle. This is equivalent to 1.7 mol photons m-2day-1 which is within the range of light environments measured in shallow 3 – 6 m depths on turbid nearshore reefs of the GBR during the wet season (Uthicke and Altenrath, 2010). The position of flasks was randomised after every sampling period and flasks were consistently shaken at 100 rpm. All glassware was washed at 90°C with laboratory detergent, rinsed and oven dried at 100°C, acid washed (10% HCl), rinsed x 5 with Reverse osmosis (RO) water, then Milli-Q water

Table 3.2: Published glyphosate biodegradation half-life estimates in soil and fresh waters.

Half- Matrix (if Reference life specified) (days) 12 Soil (field) (FPPD, 2012) 5-21 Soil (field) (FPPD, 2012) 49 Soil (lab) (FPPD, 2012) 4-180 Soil (lab) (FPPD, 2012) 87(2.5) Water-sediment (FPPD, 2012) (water fraction only) 47 __ (Peterson et al., 1994; Wauchope et al., 2002; Wauchope et al., 1992) 60 Soil (Verschueren, 2001) 30-174 Soil (Singh and Walker, 2006) <28 Soil-water (Mackay et al., 2006; Muir, 1991; Rueppel et al., 1977) > 63 Lake water (Mackay et al., 2006; Muir, 1991; Rueppel et al., 1977) 70 Pond water (Ghassemi et al., 1981; Mackay et al., 2006; Muir, 1991) 63 Swamp water (Ghassemi et al., 1981; Mackay et al., 2006; Muir, 1991) 49 Bog water (Ghassemi et al., 1981; Mackay et al., 2006; Muir, 1991) 49-70 Natural waters (Ghassemi et al., 1981; Muir, 1991) until pH neutral, oven dried a second time at 100°C, baked in a muffle furnace at 350°C for 30 minutes, and capped with aluminium foil until use. The glyphosate standard was purchased from Sigma-Aldrich, added to 2 mL of the carrier solvent ethanol (to assist in solubility), and made to 5 mg L-1 concentration with Milli-Q water. Coastal water was collected from 19°16' (S), 147° 03' (E) and filtered to 20 µm to introduce the total bacterial diversity from this environment. The seawater was added to 500 mL Erlenmeyer flasks to a final volume of 300 mL and sample treatments were spiked with a final concentration of 10 µg l-1 glyphosate. The same volume of carrier was added to control sample flasks and was 0.0004% (v/v). Each flask was stoppered with autoclaved silicone bungs to allow for aerobic conditions. The physical/chemical characteristics of the filtered seawater were measured for: pH, DIC, DOC, DIN, DON, TSS, bacterial counts, and particle size distribution.

3.3.2 Flow cytometry

Please see section 2.3.5 in Chapter 2 for flow cytometry method and approach.

3.3.3 Glyphosate analysis

For each sampling period, 5 mL control and glyphosate samples were collected and stored at 4°C. The glyphosate samples were then sent to Queensland Health Forensic and Scientific Services (Coopers Plains, Australia) for analysis. Standards and blanks were derivatised with fluorenylmethylchloroformate. The derivatisation procedure follows a published method with minor 45

adjustments for volume of sample available (Hanke et al., 2008). The sample was then concentrated on a SPE cartridge (Phenomenex Strata X 200 mg 3 ml-1) prior to analysis by HPLC- MS/MS. The glyphosate and degradation product concentrations were determined by HPLC- MS/MS using an ABSciex 4000Q Trap mass spectrometer (ABSciex, Concord, Ontario, Canada) equipped with an electrospray (TurboV) interface and coupled to a Shimadzu Prominence HPLC system (Shimadzu Corp., Kyoto, Japan). Column conditions were as follows: Phenomenex Gemini- NX C18 column (Phenomenex, Torrance, CA) 3 µm 30 x 2.0 mm, 40°C, with a flow rate of 0.35 ml min-1. The column was conditioned prior to use and for analyte separation required a linear gradient starting at 0% B for 1.0 min, ramped to 100% B in 8 min then held at 100% for 2 min followed by equilibration at 0% B for 7 min (A = HPLC grade water, B = 95% methanol in HPLC grade water, both containing 5mM ammonium acetate and 0.008% (v/v) 32% ammonia solution). The mass spectrometer was operated in the negative ion, multiple reaction-monitoring mode (MRM) using nitrogen as the collision gas. The transition ions monitored after sample derivatisation were 390/168, 390/150 for glyphosate and 332/110, 332/136 for AMPA. Detection of glyphosate and/or its metabolite in a given sample were confirmed by retention time and by comparing transition intensity ratios between the sample and an appropriate concentration standard from the same run. Samples were reported as positive if the two transitions were present, retention time was within 0.15 min of the standard and the relative intensity of the confirmation transition was within 20% of the expected value. The value reported was that for the quantitation transition. The limit of detection for the method was typically less than 0.1 μg l-1, with a reporting limit of 0.2 µg l-1 in the sample. Response was linear to at least 100 μg l-1 which is within the range of the samples with r2 from 0.995 to 0.999. Sample sequences were run with a standard calibration at the beginning and end of each sequence with, with additional mid-range standards run every 10 samples.

3.3.4 Data analysis

Half-life (t1/2) calculations assumed first order kinetics and were estimated from the decline in experiment concentration of glyphosate in seawater using the rate constant (k) (slope of the data obtained from plots of the natural logarithm of the concentrations versus time (t), where t1/2 = ln(2)/k (Beulke and Brown, 2001; Lazartigues et al., 2013). Glyphosate concentrations approaching the detection limit were removed from the analysis.

3.4 Results and Discussion

3.4.1 Microbial abundance

The pH and dissolved oxygen (DO) levels of seawater in the flasks were similar between controls, treatments and freshly-collected natural seawater at the end of the 330 day experiment (Table 3.3). Other water quality properties can be found in Appendix Table 9. The seawater in flasks contained identical bacterial abundance at the end of the experiment compared with natural seawater (Table 3.3) and is consistent with the range expected for seawater (Amaral-Zettler et al., 2010; Glöckner et al., 2012; Miller, 2009). The high densities of bacteria measured at the end of the experiment in each of the treatments indicate that the presence of 10 µg l-1 glyphosate did not reduce the microbial populations.

Table 3.3: Mean and SEs for each treatment for pH, dissolved oxygen (DO), and total bacterial counts. Natural Control Dark Dark Light seawater 25°C 31°C 25°C Total bacterial counts 2.66 ± 2.65 ± 2.59 ± 2.61 ± 2.70 ± (x 106) 0.4 0.29 0.02 0.02 0.02 pH 8.20 ± 8.22 ± 8.24 ± 8.33 ± 8.34 ± 0.01 0.02 0.02 0.01 0.01 DO (mg l-1) 6.5 ± 6.24 ± 5.95 ± 5.89 ± 6.13 ± 0.07 0.15 0.12 0.18 0.08

3.4.2 Glyphosate degradation and the formation of AMPA

Glyphosate degraded most rapidly under low light conditions at 25°C with none detected by day 180, and most slowly in the dark at 31°C where 52% remained by day 330 (Fig. 3.1, Appendix Table 10). The major biodegradation metabolite of glyphosate is AMPA (Barceló and Hennion, 2003; Pérez et al., 2012; Wright, 2012) and this was detected in flasks in each of the treatments. In the dark at 25°C AMPA increased over the course of the experiment duration to 1.42 μg l-1 by day 330, approximately 15% of the initial glyphosate concentration (Fig. 3.1, Appendix Table 10). Similar results were obtained for the generation of AMPA at 31°C in the dark. Under low light conditions, AMPA was only detected (0.35 ± 0.01 μg l-1 SE) at day 28 (Fig. 3.1, Appendix Table 10).

12 (a) Dark, 25°C 12 (b) Dark, 31°C 12 (c) Light, 25°C Glyphosate AMPA

10 10 10 )

-1 8 8 8

6 6 6

4 4 4 Concentration (µg L 2 2 2

0 0 0

0 100 200 300 0 100 200 300 0 30 60 90 120 Time (days) Figure 3.1: Concentration of glyphosate and AMPA for each treatment: Dark 25°C, Dark 31°C, and Light 25°C during the experiment duration. Concentrations reported in μg l-1.

Biodegradation is the primary pathway for glyphosate loss (Bonnet et al., 2007) and the detection of AMPA in each of the temperature and light treatments confirms that degradation of glyphosate in the flasks was mediated by bacteria from the native microbial communities. While glyphosate can also be lost due to hydrolysis and photodegradation (Lund-HØie and Friestad, 1986; Mallat and Barceló, 1998), these pathways are considered less important. The more rapid degradation of glyphosate under low light conditions (relevant to nearshore levels in the wet season) was likely due to differences in microbial community populations. Differences in microbial communities may also account for the slightly more rapid degradation of glyphosate in the dark at 25°C compared to 31°C. These results indicate that the available light will affect glyphosate persistence in the field and very low light levels expected during flood plumes may slow degradation.

3.4.3 Glyphosate persistence in seawater

The half-lives (t½) for glyphosate were calculated by plotting the natural logarithms of the concentrations against time (Fig. 3.2). The linear correlations of each of the plots were high (r2 ≥ 0.82) and the resulting slopes were -0.0026, -0.0022 and -0.0149 for the dark 25°C, dark 31°C and light 25°C treatments respectively (Fig. 3.2). Assuming first order kinetics (Beulke and Brown,

2001; Lazartigues et al., 2013) the t½ for glyphosate were estimated as 267 ± 21 (SE) days for the dark at 25°C, 315 ± 29 days for the dark 31°C and 47 ± 7 days for light 25°C treatments (Fig. 3.2).

The half-life (t½) for glyphosate of 47 days under low-light conditions was similar to reports for fresh water (Table 3.2); however, the persistence in dark at both 25°C and 31°C (267 and 315 days) was by far the longest reported.

3.4.4 Application of results from the simulation test

The simulation tests performed in this study provide both standardized conditions required for inter-study comparisons and the most natural conditions possible in flask tests (native microbial communities without additional nutrients). The consistent bacterial densities between flasks at the end of the experiment and freshly-collected natural seawater confirmed the presence of abundant bacteria required for herbicide degradation. There is in the order of thousands of different bacteria in a litre of seawater (Sogin et al., 2006) so a high diversity of microbes would be expected to be available to facilitate biodegradation, and this should be confirmed using molecular techniques in future studies.

(a) Dark, 25oC (b) Dark, 31oC (c) Light, 25oC

2.5 2.5 2.5 ) -1 2.0 2.0 2.0

1.5 1.5 1.5

1.0 1.0 1.0 ln (Concentration µg L µg ln (Concentration

0.5 0.5 0.5 t½ = 267 ± 21 days (± SE) t½ = 315 ± 29 days (± SE) t½ = 47 ± 7 days (± SE) Slope -0.0026, r2 = 0.93 Slope -0.0022, r2 = 0.85 Slope -0.015, r2 = 0.82

0 100 200 300 0 100 200 300 0 30 60 90 120 Time (days) -1 Figure 3.2: Natural log of glyphosate concentrations (μg l ) and half-life (t½) for each treatment: Dark 25°C, Dark 31°C, and Light 25°C. Graphs show 95% confidence intervals for each slope.

This study indicates glyphosate is moderately persistent in the marine environment under low light conditions and is highly persistent in the dark, with a minor influence of temperature between 25°C and 31°C. While these simulation tests mimic natural conditions better than many alternative “standard” tests, further work is needed to understand the persistence and fate of glyphosate in the marine environment. For example, glyphosate binds strongly to organic matter (Solomon and Thompson, 2003) and is therefore considered to have a low potential for offsite transport (Barceló and Hennion, 2003). However, this strong binding allows for long distance 49

transport and persistence in the environment as binding may help protect glyphosate from degradation (Solomon and Thompson, 2003). Furthermore, vast quantities of sediments (~17,000 ktonnes yr-1), potentially contaminated with glyphosate and other pesticides, are transported into the GBR during monsoonal floods (Brodie et al., 2010; Brodie et al., 2012b; Kroon et al., 2012; Lewis et al., 2009), representing an alternative transport pathway to the dissolved fraction. Glyphosate is not generally considered in most marine monitoring programs despite it being one of the most widely used herbicides in GBR catchments and globally. Recent work has also reported that surfactants and wetting agents in commercial glyphosate formulations are themselves more toxic or increase the bioavailability and toxicity of glyphosate to non-target species (Pérez et al., 2012; Stachowski-Haberkorn et al., 2008). It is possible that the persistence of glyphosate may be affected by the toxicity of formulation surfactants if they influence microbial populations or alter the partitioning of the herbicide between water and particles. However, the relevance of testing persistence in the presence of formulation surfactants is unknown as data on co-occurrence with glyphosate in the field is lacking. The long persistence of glyphosate in these flask experiments indicates that little degradation is likely during flood events which may deliver dissolved and sediment-bound herbicide far into the GBR lagoon. Further work is therefore needed to improve the monitoring and identify the fate of glyphosate for water quality risk assessments in marine ecosystems of high conservation value such as the GBR.

3.5 References

AIMS, 2013. Sea temperature monitoring program, Australian Institute of Marine Science, Townsville, http://www.aims.gov.au/docs/data-centre/seatemperatures.html. Amaral-Zettler, L., Artigas, L.F., Baross, J., Bharathi, L., Boetius, A., Chandramohan, D., Herndl, G., Kogure, K., Neal, P., Pedrós-Alió, C., 2010. A global census of marine microbes, Life in the world’s oceans: Diversity, distribution and abundance. Oxford: Wiley-Blackwell, pp. 223-245. ANZECC, ARMCANZ, 2000. Australian and New Zealand guidelines for fresh and marine water quality. Australian and New Zealand Environment and Conservation Council and Agriculture and Resource Management Council of Australia and New Zealand. Available: http://www.environment.gov.au/water/publications/quality/nwqms-guidelines-4-vol1.html. Last accessed: 26 June 2013. Bainbridge, Z.T., Wolanski, E., Álvarez-Romero, J.G., Lewis, S.E., Brodie, J.E., 2012. Fine sediment and nutrient dynamics related to particle size and floc formation in a Burdekin River flood plume, Australia. Mar. Pollut. Bull. 65, 236-248. Barceló, D., Hennion, M., 2003. Trace determination of pesticides and their degradation products in water. Battaglin, W.A., Kolpin, D.W., Scribner, E.A., Kuivila, K.M., Sandstrom, M.W., 2005. Glyphosate, other herbicides, and transformation products in Midwestern streams, 2002. J. Am. Water Resour. As. 41, 323-332. Beeton, R., Buckley, K., Jones, G., Morgan, D., Reichelt, R., Trewin, D., 2006. Australian State of the Environment Committee 2006. Independent report to the Australian Government 50

Minister for the Environment and Heritage. Department of the Environment and Heritage. http://www.environment.gov.au/soe/2006/publications/report/pubs/soe-2006-report.pdf. Beulke, S., Brown, C.D., 2001. Evaluation of methods to derive pesticide degradation parameters for regulatory modelling. Biol. Fert. Soils 33, 558-564. Bonnet, J.L., Bonnemoy, F., Dusser, M., Bohatier, J., 2007. Assessment of the potential toxicity of herbicides and their degradation products to nontarget cells using two microorganisms, the bacteria Vibrio fischeri and the ciliate Tetrahymena pyriformis. Environ. Toxicol. 22, 78-91. Borggaard, O.K., Gimsing, A.L., 2008. Fate of glyphosate in soil and the possibility of leaching to ground and surface waters: A review. Pest. Manag. Sci. 64, 441-456. Brodie, J., Schroeder, T., Rohde, K., Faithful, J., Masters, B., Dekker, A., Brando, V., Maughan, M., 2010. Dispersal of suspended sediments and nutrients in the Great Barrier Reef lagoon during river-discharge events: conclusions from satellite remote sensing and concurrent flood-plume sampling. Mar. Freshwater Res. 61, 651-664. Brodie, J., Waterhouse, J., Schaffelke, B., Kroon, F., Thorburn, P., Rolfe, J., Johnson, J., Fabricius, K., Lewis, S., Devilin, M., Warne, M., McKenzie, L., 2013. 2013 Scientific Consensus Statement: Land use impacts on the Great Barrier Reef water quality and ecosystem condition. Reef Water Quality Plan Secretariat, QLD. http://www.reefplan.qld.gov.au/about/scientific-consensus-statement.aspx. Brodie, J., Wolanski, E., Lewis, S., Bainbridge, Z.T., 2012a. An assessment of residence times of land-sourced contaminants in the Great Barrier Reef lagoon and the implications for management and reef recovery. Mar. Pollut. Bull. 65, 267-279. Brodie, J.E., Kroon, F.J., Schaffelke, B., Wolanski, E.C., Lewis, S.E., Devlin, M.J., Bohnet, I.C., Bainbridge, Z.T., Waterhouse, J., Davis, A.M., 2012b. Terrestrial pollutant runoff to the Great Barrier Reef: An update of issues, priorities and management responses. Mar. Pollut. Bull. 65, 81-100. Brodie, J.E., Waterhouse, J., 2012. A critical review of environmental management of the ‘not so Great’ Barrier Reef. Estuar. Coast. Shelf Sci. 104–105, 1-22. Davis, A.M., Thorburn, P.J., Lewis, S.E., Bainbridge, Z.T., Attard, S.J., Milla, R., Brodie, J.E., 2011. Environmental impacts of irrigated sugarcane production: Herbicide run-off dynamics from farms and associated drainage systems. Agric. Ecosyst. Environ. De’ath, G., Fabricius, K.E., Sweatman, H., Puotinen, M., 2012. The 27–year decline of coral cover on the Great Barrier Reef and its causes. Proc. Natl. Acad. Sci. 109, 17995-17999. Duke, S.O., Powles, S.B., 2008. Glyphosate: A once-in-a-century herbicide. Pest. Manag. Sci. 64, 319-325. FPPD, 2012. Glyphosate. ‘Footprint’ Pesticide Properties Database. http://sitem.herts.ac.uk/aeru/footprint/index2.htm. Ghassemi, M., Fargo, L., Painter, P., Painter, P., Quinlivan, S., 1981. Environmental fates and impacts of major forest use pesticides. US Environmental Protection Agency, Office of Pesticides and Toxic Substances, Washington DC. Giesy, J.P., Dobson, S., Solomon, K.R., 2000. Ecotoxicological Risk Assessment for Roundup® Herbicide, in: Ware, G.W. (Ed.), Reviews of Environmental Contamination and Toxicology. Springer New York, pp. 35-120. Glöckner, F.O., Stal, L.J., Sandaa, R., Gasol, J.M., O'Gara, F., Hernandez, F., Labrenz, M., Stoica, E., Varela, M.M., Bordalo, A., 2012. Marine microbial diversity and its role in ecosystem functioning and environmental change. ESF Marine Board Position Paper 17. Hanke, I., Singer, H., Hollender, J., 2008. Ultratrace-level determination of glyphosate, aminomethylphosphonic acid and glufosinate in natural waters by solid-phase extraction followed by liquid chromatography–tandem mass spectrometry: Performance tuning of derivatization, enrichment and detection. Anal. Bioanal. Chem. 391, 2265-2276. Kroon, F.J., Kuhnert, P.M., Henderson, B.L., Wilkinson, S.N., Kinsey-Henderson, A., Abbott, B., Brodie, J.E., Turner, R.D.R., 2012. River loads of suspended solids, nitrogen, phosphorus and herbicides delivered to the Great Barrier Reef lagoon. Mar. Pollut. Bull. 65, 167-181. 51

Lazartigues, A., Thomas, M., Banas, D., Brun-Bellut, J., Cren-Olivé, C., Feidt, C., 2013. Accumulation and half-lives of 13 pesticides in muscle tissue of freshwater fishes through food exposure. Chemosphere 91, 530-535. Lewis, S.E., Brodie, J.E., Bainbridge, Z.T., Rohde, K.W., Davis, A.M., Masters, B.L., Maughan, M., Devlin, M.J., Mueller, J.F., Schaffelke, B., 2009. Herbicides: A new threat to the Great Barrier Reef. Environ. Pollut. 157, 2470-2484. Lund-HØie, K., Friestad, H.O., 1986. Photodegradation of the herbicide glyphosate in water. Bull. Environ. Contam. Toxicol. 36, 723-729. Mackay, D., Shiu, W., Ma, K.C., Lee, S.C., 2006. Handbook of physical-chemical properties and environmental fate for organic chemicals, Second ed. CRC press. Mallat, E., Barceló, D., 1998. Analysis and degradation study of glyphosate and of aminomethylphosphonic acid in natural waters by means of polymeric and ion-exchange solid-phase extraction columns followed by ion chromatography–post-column derivatization with fluorescence detection. J. Chromatogr. A 823, 129-136. Mensink, H., Janssen, P., 1994. Glyphosate. World Health Organization Programme on Chemical Safety, Environmental Health Criteria 159. Miller, C.B., 2009. Biological Oceanography. Wiley-Blackwell. Hoboken, NJ, USA. Muir, D.C.G., 1991. Chapter 1: Dissipation and transformations in water and sediments, in: Grover, R., Cessna, A.J. (Eds.), Environmental chemistry of herbicides. CRC Press, Inc., pp. 1-88. NHMRC, 2011. Australian drinking water guidelines paper 6 national water quality management strategy. National Health and Medical Research Council, National Resource Management Ministerial Council, Commonwealth of Australia: Canberra, p. 1126. OECD, 2005. OECD Guideline for testing of chemicals: Part 1: Principles and strategies related to the testing of degradation of organic chemicals. Accessed March 2015. Orth, R.J., Carruthers, T.J.B., Dennison, W.C., Duarte, C.M., Fourqurean, J.W., Heck Jr, K.L., Hughes, A.R., Kendrick, G.A., Kenworthy, W.J., Olyarnik, S., 2006. A global crisis for seagrass ecosystems. Bioscience 56, 987-996. Pérez, G.L., Vera, M.S., Miranda, L.A., 2012. Effects of herbicide glyphosate and glyphosate-based formulations on aquatic ecosystems. Herbicides—Properties, Synthesis and Control of Weeds, 334-368. Pesce, S., Fajon, C., Bardot, C., Bonnemoy, F., Portelli, C., Bohatier, J., 2008. Longitudinal changes in microbial planktonic communities of a French river in relation to pesticide and nutrient inputs. Aquat. Toxicol. 86, 352-360. Peterson, H.G., Boutin, C., Martin, P.A., Freemark, K.E., Ruecker, N.J., Moody, M.J., 1994. Aquatic phyto-toxicity of 23 pesticides applied at expected environmental concentrations. Aquat. Toxicol. 28, 275-292. Radcliffe, J.C., 2002. Pesticide use in Australia. Australian Academy of Technological Sciences and Engineering, Parkville, Victoria. Rueppel, M.L., Brightwell, B.B., Schaefer, J., Marvel, J.T., 1977. Metabolism and degradation of glyphosate in soil and water. J. Agr. Food Chem. 25, 517-528. Samain, J.F., McCombie, H., 2008. Summer mortality of Pacific oyster Crassostrea gigas: The Morest Project. Éditions Quae. Scribner, E.A., Battaglin, W.A., Dietze, J.E., Thurman, E.M., 2003. Reconnaissance data for glyphosate, other selected herbicides, their degradation products, and antibiotics in 51 streams in nine Midwestern states, 2002. US Department of the Interior, US Geological Survey. Singh, B.K., Walker, A., 2006. Microbial degradation of organophosphorus compounds. FEMS Microbiol. Rev. 30, 428-471. Skark, C., Zullei-seibert, N., Schöttler, U., Schlett, C., 1998. The occurrence of glyphosate in surface water. Int. J. Environ. Anal. Chem. 70, 93-104.

Sogin, M.L., Morrison, H.G., Huber, J.A., Welch, D.M., Huse, S.M., Neal, P.R., Arrieta, J.M., Herndl, G.J., 2006. Microbial diversity in the deep sea and the underexplored “rare biosphere”. Proc. Natl. Acad. Sci. 103, 12115-12120. Solomon, K., Thompson, D., 2003. Ecological risk assessment for aquatic organisms from over- water uses of glyphosate. J. Toxicol. Env. Heal. B. 6, 289-324. Stachowski-Haberkorn, S., Becker, B., Marie, D., Haberkorn, H., Coroller, L., De La Broise, D., 2008. Impact of Roundup on the marine microbial community, as shown by an in situ microcosm experiment. Aquat. Toxicol. 89, 232-241. Struger, J., Thompson, D., Staznik, B., Martin, P., McDaniel, T., Marvin, C., 2008. Occurrence of glyphosate in surface waters of southern Ontario. Bull. Environ. Contam. Toxicol. 80, 378- 384. Uthicke, S., Altenrath, C., 2010. Water column nutrients control growth and C: N ratios of symbiont-bearing benthic foraminifera on the Great Barrier Reef, Australia. Limnol. Oceanog. 55, 1681-1696. Verschueren, K., 2001. Handbook of Environmental Data on Organic Chemicals (4th Edition). John Wiley & Sons. Hoboken, NJ, USA. Wauchope, R., Yeh, S., Linders, J.B.H.J., Kloskowski, R., Tanaka, K., Rubin, B., Katayama, A., Kördel, W., Gerstl, Z., Lane, M., Unsworth, J.B., 2002. Pesticide soil sorption parameters: Theory, measurement, uses, limitations and reliability. Pest. Manag. Sci. 58, 419-445. Wauchope, R.D., Buttler, T.M., Hornsby, A.G., Augustijn-Beckers, P.W.M., Burt, J.P., 1992. The SCS/ARS/CES pesticide properties database for environmental decision-making. Reviews of Environmental Contamination and Toxicology 123, 1-155. Wright, R., 2012. Canadian Water Quality Guidelines for the Protection of Aquatic Life. Canadian Environmental Quality Guidelines Canadian Council of Ministers of the Environment, 2012. http://www.ccme.ca/assets/pdf/wqi_techrprtfctsht_e.pdf.

3.6

Chapter 4: Degradation of herbicides in the tropical marine environment: Influence of light and sediment

4.1 Abstract

Widespread contamination of nearshore marine systems, including the Great Barrier Reef (GBR) lagoon, with agricultural herbicides has been long recognised. The fate of these contaminants in the marine environment is poorly understood but the detection of photosystem II (PSII) herbicides in the GBR year-round suggests very slow degradation rates. Here we evaluated the persistence of a range of commonly detected herbicides in marine water under field-relevant concentrations and conditions. Twelve month degradation experiments were conducted in large open tanks, under different light scenarios and in the presence and absence of natural sediments. All PSII herbicides were persistent under control conditions (dark, no sediments) with half-lives of 300 d for atrazine, 499 d diuron, 1994 d hexazinone, 1766 d tebuthiuron, while the non-PSII herbicides were less persistent 147 d metolachlor and 59 d for 2,4-D. The degradation of all herbicides was 2 – 10 fold more rapid in the presence of a diurnal light cycle and coastal sediments; whereas, 2,4-D degraded more slowly in the presence of light. Despite the more rapid degradation observed for most herbicides in the presence of light and sediments, the half-lives remained greater than 100 d for the PS II herbicides. The effects of light and sediments on herbicide persistence were likely due to their influence on microbial community composition and its ability to utilise the herbicides as a carbon source. These results help explain the year-round presence of PSII herbicides in marine systems, including the GBR, but more research on the transport, degradation and toxicity on a wider range of pesticides and their transformation products is needed to improve their regulation in sensitive environments.

4.2 Introduction

Pesticides play an integral role in global food production; however, some have long persistence in the environment and are toxic to non-target species (Fenner et al., 2013). Chronic pesticide exposure has contributed to the decline of water quality in the Great Barrier Reef (GBR) region where intensive agricultural practices occur adjacent to sensitive marine habitats (King et al., 2013). It is estimated that up to 30 tonnes photosystem II (PSII) herbicides are transported into the GBR lagoon annually (Kroon et al., 2012) and concentrations higher than 10 μg l-1 can be detected in the receiving waters (Smith et al., 2012). PSII herbicide concentrations in the GBR lagoon are generally lower but have exceeded current water quality guidelines (GBRMPA, 2010 Accessed March 2015; Lewis et al., 2012) and can affect photosynthesis and growth in sensitive marine 54

organisms such as seagrass (Flores et al., 2013; Negri et al., 2015). The five most commonly detected PSII herbicides, diuron, atrazine, hexazinone, tebuthiuron and ametryn, have been designated “priority herbicides” by management agencies and are monitored and managed as part of an overall GBR management and protection plan (GBRMPA, 2009 Accessed March 2015). Although most extensively studied in the catchments and the lagoon of the GBR, PSII herbicides are present in nearshore marine systems across the world (Bocquené and Franco, 2005; Kemp et al., 1983; Potter et al., 2013; Salvat et al., 2015; Shaw et al., 2008). PSII herbicides are detected at higher concentrations during flood plumes which enter the GBR lagoon over the summer monsoon period (Kennedy et al., 2012a; Kennedy et al., 2012b), but these contaminants are also found in low concentrations year round (Magnusson et al., 2012; Shaw et al., 2010) suggesting long environmental persistence. Evidence of degradation in the environment is shown by the detection of the breakdown products of atrazine and diuron in the GBR region (Bentley et al., 2012; Kennedy et al., 2012a; Kennedy et al., 2012b), sometimes reaching concentrations over 2 μg l-1 at highly contaminated sites (O’Brien et al., 2013). The persistence of contaminants in the environment is governed by the rates of multiple processes including hydrolysis, light/ UV driven photodegradation and microbial degradation (metabolism) (Barceló and Hennion, 1997; Cessna, 2008; Mandelbaum et al., 2008). Microbial degradation is considered the dominant route of degradation for most PSII herbicides in aquatic systems (Ganapathy, 1996; Howard, 1991; Mandelbaum et al., 2008) and our recent standard flask study indicates very slow degradation of diuron, atrazine, hexazinone and tebuthiuron in seawater, with evidence of both hydrolysis and microbial metabolism of these herbicides (Mercurio et al., 2015). There is a relatively large number of in situ and laboratory studies on the persistence of PSII herbicides in freshwater aquatic systems (see (Pathiratne and Kroon, 2015)); however, few laboratory studies have examined persistence in seawater (summarised in (Mercurio et al., 2015)). The long seawater persistence of PSII herbicides observed in standard flask studies (half-lives greater than 500 d) (Mercurio et al., 2015) indicates slower degradation than in freshwater, and may be influenced by a range of factors including salinity, pH and alternative organic carbon food sources, which in turn affect microbial degradation and hydrolysis. Most previous studies on PSII herbicide persistence in seawater were not conducted for long enough to calculate reliable estimates of half-lives and several of these studies applied very high initial concentrations of herbicides (e.g. 5000 µg l-1) which may affect degradation rates by artificially influencing natural microbial communities and/or may be toxic to some components of the communities (Mercurio et al., 2015). Our previous degradation studies applied the most natural conditions practical in a standard flask environment (OECD, 1992), including low contaminant concentrations (~10 µg l-1), native microbial communities, no artificial nutrients and tests were conducted over 12 months under 55

different light and temperature conditions (Mercurio et al., 2014; Mercurio et al., 2015). The application of low light increased the degradation rates of diuron, tebuthiuron and the non-PSII herbicide glyphosate and slowed the degradation of the non-PSII herbicide 2,4-D (Mercurio et al., 2014; Mercurio et al., 2015). An increase in temperature from 25°C to 31°C increased degradation of diuron, hexazinone, tebuthiuron, 2,4-D and glyphosate and slowed the degradation of atrazine. While providing some of the first reliable standard flask persistence data in marine systems for several herbicides under highly controlled conditions, these studies highlighted the strong influence on persistence of field-relevant factors, including light and temperature (Mercurio et al., 2014; Mercurio et al., 2015). The potential environmental risks posed by pesticides can only be assessed when their fate in the environment, including potential degradation rates under field-relevant conditions are understood (Fenner et al., 2013). Here we conducted a year-long degradation experiment using concentrations of commonly detected herbicides in a series of replicate open tanks. We included different light conditions and natural sediments in treatments to improve the ecological relevance and applicability for inclusion by regulators and resource managers in future risk assessments.

4.3 Materials and Methods

4.3.1 Approach and experimental design

This study describes a series of outdoor open tank experiments to measure the degradation of herbicides under conditions more natural than those applied in standard flask tests. These tests were conducted in large open tanks with water circulation over the course of a year under both fully dark and light conditions (partially shaded, natural diurnal cycle) and in the presence and absence of natural sediments (Table 4.1) Refer to Fig. 6.1.

Table 4.1: Four experimental treatments in the 40-tank open tank experiment. The PSII mix comprised of diuron, atrazine, hexazinone and tebuthiuron and the non-PSII mix of 2,4-D and metolachlor, each added at ~10 µg l-1. Each tank contained 120 l coastal seawater, temperature range (21- 37° C).

Light conditions Sediment conditions Sediment free Coastal Sediments Dark No herbicides (n = 3) No herbicides (n = 3) PSII mix (n = 4) PSII mix (n = 4) non-PSII mix (n=3) non-PSII mix (n=3) Light No herbicides (n = 3) No herbicides (n = 3) PSII mix (n = 4) PSII mix (n = 4) non-PSII mix (n=3) non-PSII mix (n=3)

The open fibreglass tanks (120 l) were situated in an outdoor glasshouse in two stacked rows of 10 (20 in the top rows and 20 in the bottom rows). The top 20 tanks were partially shaded (70%) and exposed to a natural diurnal cycle (maximum of 700 µE photons m-2s-1) over the course of the experiment (Hobo light and temperature loggers UA-001-64, Onset, Bourne, MA). The bottom row was fully shaded at all times. Evaporation was minimised with loose-fitting clear acrylic lids on the top row and opaque foam on the bottom row and water continuously circulated in each tank using Turbelle Nanostream pumps. After every sampling period evaporation losses were replenished with equal volumes of MilliQ freshwater. Logged temperatures averaged 28°C (range 21-37°C) in the light and 26°C (21-32°C) in the dark.

4.3.2 Sediments and water

Unfiltered coastal seawater was collected from the Australian Institute of Marine Science (19°16’ S, 147° 03’ E), Cape Cleveland, QLD. Intertidal sediments, containing no detectable concentrations of herbicides (see Results) were collected from the intertidal zone of low tide from Cockle Bay, Magnetic Island, Queensland (19°10’ S, 146° 49’ E). The sediments were prepared one week prior to use by sieving (> 2 mm removed), thorough mixing and conditioning in shallow trays placed in two 1000 l tanks with 20 µm filtered and aerated seawater. During this conditioning process, half of the sediment was held in a dark trough (dark treatment) and the other half was held in 70% shaded sunlight (light treatment). This conditioning process allowed for microbial community transition to final experimental conditions prior to the start of the experiment. To allow for periodic sediment sampling without disruption of sediment communities, the sediments were distributed into a single large and 11 small dishes in each tank which could be removed without disturbing the majority of the sediment. The large dish (25 cm x 22 cm 5 cm) were filled with 3.0 kg of sediment (wet weight) and the small ceramic dishes (6.5 cm diameter) 70 g sediment. Physical and chemical information on the seawater and sediments used the open tank experiment may be found in Appendix Table 11.

4.3.3 Herbicide addition, sampling and analysis

Herbicide treatments and replicates (n = 3 or 4, see Table 4.1) were randomized among tanks. The six herbicides (Table 4.1) were purchased from Sigma Aldrich (>95% purity) and introduced as mixtures to the seawater of each tank at low concentrations (nominal 10 µg l-1, measured concentrations reported in Results) to maximise environmental relevance (Lewis et al., 57

2012; Mercurio et al., 2015; OECD, 1992). Sample collection, internal standard addition, and analytical techniques (HPLC-MS/MS using an AB/Sciex API5500Q mass spectrometer equipped with an electrospray interface and coupled to a Shimadzu Prominence HPLC system) were as previously reported (Mercurio et al., 2015). Samples were collected on days 0, 21, 60, 100, 120, 180, 210, 240, 300, and 365. Samples were run via direct injection, with a standard calibration at beginning and end and additional quality control standards run every 10 samples. Samples for flow cytometry and physical-chemical characterisation (pH, DO, TSS, DIC, DOC, DIN, DON) were collected and analysed as previously reported (Mercurio et al., 2015). Sediments were sampled by removing small dishes using long aluminium tongs. The sediment samples were homogenised and then transferred to centrifuge tubes and weighed. The samples were centrifuged for 10 min at 3000 x g, excess water removed, and stored at -20°C prior to herbicide extraction (OECD, 2000). Sediments were exhaustively extracted with acetone and concentrated to near dryness. Agilent QuEChERS kits and protocols were used for extract clean-up as per the manufacturer’s protocols (Agilent application notes 5990-3937EN and 5989-8614EN). Samples for 2,4-D required a pre-extraction hydrolysis step with 5M NaOH for 30 min (Santilio et al., 2011). The pH of the samples was then neutralised with 5N H2SO4. Cleaned extracts were evaporated to dryness and reconstituted into MilliQ water prior to HPLC/MS analysis (Mercurio et al., 2015). Percent recovery for herbicide concentrations in the sediment samples were 87.1 to 118.5% (Appendix Table 12).

4.3.4 Data analysis

Please see section 2.3.6 in Chapter 2 for half-life (t1/2) calculations and statistical analysis.

4.4 Results

4.4.1 Overview

All herbicides degraded according to pseudo-first order kinetics with linear relationships evident for plots of ln (concentration) vs time under all four treatment conditions (Figs. 1 – 6). All herbicides degraded significantly over 365 days in each of the treatment types (Appendix Table 13) and the persistence for all conditions and herbicides calculated from the Figures 4.1 – 4.6 are summarised in Table 4.2.

4.4.2 Degradation rates in the dark no sediments

In the dark without sediments, atrazine and diuron degraded 3- to 6–fold more rapidly than hexazinone and tebuthiuron (Table 4.2). The non-PSII herbicides metolachlor and 2,4-D degraded more rapidly than the PSII herbicides under these conditions with the shortest half-life being 59 days for 2,4-D (Table 4.2).

4.4.3 Light and sediment effects

The effects of light and sediment resulted in significantly different degradation rates (ln [concentration] versus time) for all herbicides under most experimental conditions (Appendix Table 13). The persistence ratios (half-life of herbicide from a given treatment divided by the half–life of the same herbicide under control (dark, without sediments) conditions) demonstrates the scale of effect of the different treatments (Table 4.3). For example the t½ for diuron of 404 d in the light, no sediments (Table 4.2) was shorter than under “standard” (dark, no sediment) conditions and consequently had a persistence ratio of 0.81 (Table 4.3). Light also significantly reduced the persistence of hexazinone and metolachlor, while atrazine degradation was not affected (Table 4.3). The presence of light increased the persistence of tebuthiuron almost 2-fold and 2,4-D over 30-fold to 1920 d (Tables 4.2 and 4.3). The addition of sediments under dark conditions increased the rates of degradation of diuron, atrazine, hexazinone and metolachlor by between (~30% and 50%) but had no impact on the degradation rates of tebuthiuron or 2,4-D (Table 4.2). The simultaneous effects of sediments and light resulted in the most rapid degradation of all herbicides except for 2,4-D (Tables 4.2 and 4.3). Atrazine exhibited the most rapid degradation of all the PSII herbicides under these conditions with a t½ of 107 d (Table 4.2), while the t½ of 32 d for metolachlor represented the most rapid degradation in the experiment. 2,4-D degraded almost 4- fold slower under these conditions than in the dark without sediments (Tables, 4.2 and 4.3).

A: Dark no sediment B: Light no sediment

2.5 2.5

2.0 2.0

1.5 1.5

1.0 1.0

)] -1 0.5 t½ = 499 ± 31 days 0.5 t½ = 404 ± 16 days Slope -0.0013882, r2 = 0.87 Slope -0.0017135, r2 = 0.94

0 100 200 300 400 0 100 200 300 400

C: Dark with sediment D: Light with sediment

ln [Concentration (µg l (µg ln [Concentration 2.5 2.5

2.0 2.0

1.5 1.5

1.0 1.0

0.5 0.5 t½ = 279 ± 7 days t½ = 139 ± 6 days Slope -0.0024853, r2 = 0.97 Slope -0.0049768, r2 = 0.96

0 100 200 300 400 0 100 200 300 400

Time (days)

A: Dark no sediment B: Light no sediment

2.5 2.5

2.0 2.0

1.5 1.5

1.0 1.0

] 1 - 0.5 0.5 t½ = 300 ± 13 days t½ = 330 ± 32 days Slope -0.0023132, r2 = 0.94 Slope -0.002099, r2 = 0.81

0 100 200 300 400 0 100 200 300 400

C: Dark with sediment D: Light with sediment

ln [Concentration (µg l (µg [Concentration ln 2.5 2.5

2.0 2.0

1.5 1.5

1.0 1.0

t = 107 ± 7 days 0.5 t = 201 ± 6 days 0.5 ½ ½ Slope -0.006457 2 Slope -0.0034505, r = 0.97 r2 = 0.82

0 100 200 300 400 0 100 200 300 400

Time (days)

A: Dark no sediment B: Light no sediment 2.5 2.5

2.0 2.0

1.5 1.5

1.0 1.0 )]

-1 0.5 t½ = 1994 ± 207 days 0.5 t½ = 1186 ± 73 days Slope -0.0003476, r2 = 0.71 Slope -0.0005844, r2 = 0.88

0 100 200 300 400 0 100 200 300 400

C: Dark with sediment D: Light with sediment

2.5 2.5 ln [Concentration (µg l (µg ln [Concentration

2.0 2.0

1.5 1.5

1.0 1.0

0.5 0.5 t½ = 1025 ± 51 days t½ = 201 ± 18 days Slope -0.0006758, r2 = 0.91 Slope -0.0034533, r2 = 0.72

0 100 200 300 400 0 100 200 300 400

Time (days)

A: Dark no sediment B: Light no sediment t½ = 1766 ± 188 days t½ = 3330 ± 419 days 2.5 Slope -0.0003924, r2 = 0.70 2.5 Slope -0.0002081, r2 = 0.63

2.0 2.0

1.5 1.5

1.0 1.0 )]

-1 0.5 0.5

0 100 200 300 400 0 100 200 300 400

C: Dark with sediment D: Light with sediment t½ = 1474 ± 106 days t½ = 944 ± 52 days ln [Concentration (µg l (µg [Concentration ln 2.5 2.5 Slope -0.0004701, r2 = 0.84 Slope -0.0007342, r2 = 0.93

2.0 2.0

1.5 1.5

1.0 1.0

0.5 0.5

0 100 200 300 400 0 100 200 300 400

Time (days)

A: Dark no sediment B: Light no sediment 2.5 2.5

2.0 2.0

1.5 1.5

1.0 1.0 )]

-1 0.5 0.5 t = 93 ± 8 days t½ = 147 ± 13 days ½ 2 Slope -0.0047179, r2 = 0.88 Slope -0.0074192, r = 0.92

0 100 200 300 400 0 100 200 300 400

C: Dark with sediment D: Light with sediment

2.5 2.5 ln [Concentration (µg l (µg ln [Concentration

2.0 2.0

1.5 1.5

1.0 1.0

0.5 0.5 t½ = 103 ± 5 days t½ = 32 ± 3 days Slope -0.0067346, r2 = 0.97 Slope -0.0217938, r2 = 0.93

0 100 200 300 400 0 100 200 300 400

Time (days)

A: Dark no sediment B: Light no sediment

2.5 2.5

2.0 2.0

1.5 1.5

1.0 1.0

)]

-1 0.5 t = 1920 ± 417 days 0.5 t½ = 59 ± 15 days ½ 2 Slope -0.0116596 r2 = 0.65 Slope -0.0003609, r = 0.45

0 100 200 300 400 0 100 200 300 400 C: Dark with sediment D: Light with sediment

ln [Concentration (µg l (µg ln [Concentration 2.5 2.5

2.0 2.0

1.5 1.5

1.0 1.0

0.5 t½ = 56 ± 6 days 0.5 t½ = 288 ± 12 days Slope -0.0124153 r2 = 0.93 Slope -0.0024078, r2 = 0.93

0 100 200 300 400 0 100 200 300 400

Time (days)

Table 4.2: Experiment half-lives (days ± SE). SE = Standard Error. The superscripts a,b,c,d represent significantly different slopes in Figs. 1-6 (F test in Graph Pad Prism V 6.0, Appendix Table 15), indicating differences in persistence between treatments for that herbicide.

Herbicide Dark no sediment Light no sediment Dark with sediment Light with sediment Diuron 499 ± 31 a 404 ± 16 b 279 ± 7 c 139 ± 6 d Atrazine 300 ± 13 a 330 ± 32 a 201 ± 6 b 107 ± 7 c Hexazinone 1994 ± 207 a 1186 ± 73 b 1025 ± 51 b 201 ± 18 c Tebuthiuron 1766 ± 188 a 3330 ± 419 b 1474 ± 106 a 944 ± 52 c Metolachlor 147 ± 13 a 93 ± 8 b 103 ± 5 b 32 ± 3 c 2,4-D 59 ± 15 a 1920 ± 417 b 56 ± 6 a 288 ± 12 c

Table 4.3: The persistence ratio of half-lives between each treatment relative to “control” (dark, no sediment) conditions. Dark no Light no Dark with Light with Herbicide sediment sediment sediment sediment Diuron 1.00 0.81 0.56 0.28 Atrazine 1.00 1.1 0.67 0.36 Hexazinone 1.00 0.59 0.51 0.10 Tebuthiuron 1.00 1.89 0.83 0.53 Metolachlor 1.00 0.63 0.70 0.22 2,4-D 1.00 33 0.95 4.9

4.4.4 Metabolites

Metabolites for atrazine were observed for all treatments which contained atrazine at concentrations above the reporting limit of 0.2 µg l-1. On average, desethyl atrazine (DEA) was detected more often and at slightly higher concentrations than desisopropyl (DIA) atrazine in the PSII treatments (See Fig. 4.7). The maximum individual concentrations for the metabolites were 0.38 and 0.76 μg l-1 for DIA atrazine and DEA respectively (365 day samples, dark with sediment treatment). These metabolites were detectable from the 60 day sampling onwards and were generally detected for the rest of the experiment. As the concentrations were close to the reporting limit no quantitative comparisons have been made. The main stable metabolite for diuron, 3,4- dichloroaniline, was not detected in water samples.

4.4.5 Herbicides in sediments

Herbicides were analysed in sediments at 60 and 365 d and in all cases less than 1% of the total herbicides in each tank was associated with the sediments (Appendix Table 14). For all herbicides, concentrations were higher in the 60 day samples (maximum ≤ 4 µg kg-1) than the 365 day samples; the only exception was tebuthiuron in the light which did not change between sampling periods. Metabolites of atrazine were detected at low concentrations (≤ 0.03 µg kg-1) in sediments (Appendix Table 14).

A: Dark no sediment B: Light no sediment 0.8 0.8

0.6 0.6

0.4 0.4

0.2 0.2 DEA

DIA )

-1 0.0 0.0 0 100 200 300 400 0 100 200 300 400

C: Dark with sediment D: Light with sediment

0.8 0.8 Concentration (µg l (µg Concentration 0.6 0.6

0.4 0.4

0.2 0.2

0.0 0.0 0 100 200 300 400 0 100 200 300 400

Time (days) Figure 4.7: Concentration of metabolites of atrazine: DEA and DIA. Concentration (μg l-1) of individual herbicide metabolite in herbicide PSII mixture for treatments: (A) Dark no sediment, (B) Light no sediment, (C) Dark with sediment, and (D) Light with sediment sampled up to 10 times over 365 days. Bars represent ± SE.

4.5 Discussion

An important element in assessing environmental risks posed by pesticides in the environment is to measure their potential degradation rates (Fenner et al., 2013). Our previous standard flask experiments demonstrated very long persistence of herbicides in coastal seawater (Mercurio et al., 2014; Mercurio et al., 2015). Here, under more environmentally relevant conditions, we confirm the long persistence of PSII herbicides in seawater and demonstrate very strong influences of variable light in combination with the presence of coastal sediments, which can reduce persistence by up to 10-fold. Although the effects of these environmental factors on persistence was consistent for the PSII herbicides and the non-PSII herbicide metolachlor, light had an opposite effect on the degradation of 2,4-D which exhibited a 5-fold longer half-life in the presence of light and sediment in comparison to the standard dark, no sediment conditions. These results help explain the year-round presence of PSII herbicides in tropical estuarine and marine systems and underscore the need for more realistic experimental data on pesticide persistence in sensitive marine habitats. The presence of variable light: (i) significantly shortened the persistence of diuron, hexazinone and metolachlor; (ii) had no effect on atrazine; and (iii) increased the half-lives of tebuthiuron and, more dramatically 2,4-D. Photodegradation may have contributed in cases of more rapid degradation (by 19 – 41%); however, other studies have reported only minor contributions of hydrolysis and photodegradation of diuron (Moncada, 2004; Okamura, 2002) and hexazinone (Ganapathy, 1996). We previously showed how low light (40 µmol photons m-2s-1) can significantly affect degradation of PSII herbicides in seawater, most likely due to changes in microbial community structure affecting the biodegradation (Mercurio et al., 2015). However, the influence of light on the rates of biodegradation is unlikely to be predictable and may increase or decrease biodegradation, depending on intensity, duration and the initial community composition. In the cases of tebuthiuron and 2,4-D which exhibited (1.9 fold – 33-fold) longer persistence, the presence of light may have directly favoured bacteria less able to metabolise the herbicides (a direct effect) or may have changed the nature of other organic carbon in the system to form more appealing carbon sources (indirect effect). The treatments exposed to light were slightly (mean 2°C) warmer than the fully dark treatments and a slight effect of temperature on persistence cannot be discounted (Mercurio et al., 2015). The total number of bacteria in the light treatments was not affected by the presence of light (Appendix Table 16) and only by quantifying genes related to the biodegradation pathways and a comprehensive analysis of transformation products could we determine the mechanistic contribution of light to degradation (Fenner et al., 2013). There was no effect of moderate light (this study) on the persistence of atrazine, supporting other studies which indicate biodegradation (and not photodegradation) as the primary degradation pathway (Fenner et al., 2013). 68

The presence of coastal sediments increased degradation of all herbicides in the water column (apart from 2,4-D) in comparison with standard (dark, no sediment) treatments. Less than 1% of the mass balances of herbicides were detected in the sediments, indicating the sediments were not an important “sink” for herbicides in the water column. Instead, the likely mechanism for increased degradation rates of 17 – 44% was due to differences in the microbial communities, including the possibility that coastal sediments in the tanks introduced a more natural, wider diversity, including more taxa capable of utilising the herbicides as a substrate. The microbial communities on the sediments may be exposed to dissolved herbicides due to the large surface area of the sediments used. Thouland et al. (Thouand et al., 2011), described how the fate of chemicals in degradations studies are strongly influenced by the original inoculum used, largely depending on cell density, microbial diversity, and whether or not the microbial community may have been pre- exposed to the test chemical. Previous studies in freshwater have demonstrated more rapid (~3-fold) loss of atrazine and metolachlor in the presence of natural sediments, attributing this to more rapid biodegradation as well as sequestration by the sediments (Rice et al., 2004). Up to 10% of the herbicides were physically associated with sediments in that study, highlighting differences in the potential of sediments (affected by type) on removal of herbicides from the water column and their potential bioavailability. The inclusion of sterile sediment treatments allowed Rice et al., (Rice et al., 2004) to postulate that the presence of sediments may also influence non-biotic degradation rates. For example, humic acids often associated with sediments have been shown to increase photodegradation and hydrolysis of a range of contaminants (Cessna, 2008; Lin et al., 2008; Steen et al., 2000). Atrazine and metolachlor had similar rates of degradation (224 and 98 days respectively) in the absence of sediments in a microcosm experiment mimicking tropical freshwater wetland environments (Laabs et al., 2007). Again, the addition of natural sediments significantly increased removal from the water column, further reinforcing the utility of these more realistic conditions in experiments for predicting environmental persistence. The most rapid degradation was observed for all herbicides (apart from 2,4-D) in the presence of both moderate light and coastal sediments (2 – 10- fold more rapid). The more rapid degradation is likely to be due to the combined effects of both light and sediments on microbial community composition as discussed above. Only the persistence of 2,4-D opposed this trend, being 5-fold more persistent than in the absence of light and sediment. This effect could also have been caused by the presence of different microbial communities, including the presence of more phototropic organisms, and is consistent with longer persistence in the presence of low light observed in our standard flask experiments (Mercurio et al., 2015). Despite the more rapid degradation observed for most herbicides in the presence of light and sediments, the half-lives of PSII herbicides were still greater than 100 days for diuron, atrazine and 69

hexazinone, which helps explain their year-round presence in waterways of tropical Queensland (Shaw et al., 2010). The presence and concentration of these herbicides in the coastal zone is therefore more likely to be influenced by water exchange/dilution rather than degradation in the months following flood plumes. Even in the presence of light and sediments, the half-life of tebuthiuron was almost 3 years, indicating that this herbicide is very persistent in seawater. Tebuthiuron is commonly applied to control tree growth on grazing lands in the catchments of the southern GBR and its long persistence may contribute to detection in ~90% of water samples from this region (Packett et al., 2009). Degradation was more rapid for all herbicides tested under these more environmentally relevant conditions than we previously reported from standard OECD-style flask experiments (Mercurio et al., 2015), refer to Table 6.1. While the standard flask experiments provide repeatable conditions that enable reliable comparisons between laboratories and contaminants, half-lives from flask experiments may not be suitable for application in risk assessments. This is especially the case where unrealistically high concentrations of contaminant are tested in the presence of additional nutrients and inoculated with highly enriched and active microbial consortia (e.g. from wastewater plants and alike) (Ahtiainen et al., 2003). Even when standard flasks studies are conducted to better simulate natural conditions they are often not run for sufficient time to enable half-life calculations (Mercurio et al., 2015). The static, yet open large tank experiments here, conducted in the presence of natural sediments and variable light and temperature provide conditions much more representative of those in the natural environment. The long persistence of herbicides we report is likely to be related to the limited capacity of natural microorganisms to metabolise the herbicides in the presence of other carbon sources and to the low concentrations of the herbicides in solution. Although the natural microbial populations used in the current experiment may have been previously exposed to low concentrations of these herbicides, in the tank experiments (as in the natural environment) they are likely to have access to a more abundant and diverse array of carbon sources that may be more easily assimilated (Ahtiainen et al., 2003). The active growth of bacterial communities in low-nutrient systems such as seawater is supported by the ability of most bacteria to adapt to a range of carbon sources (Egli, 2010). However, the specific enzymatic pathways for metabolising complex organics like pesticides may only be induced above a “utilization threshold”, often in the range of 1 – 100 µg l-1 (Egli, 2010). The concentrations of herbicides applied in the current study were low in comparison to many studies and the microbial communities are less likely to induce herbicide metabolism of these low concentrations when other carbon sources are available. Concentrations of herbicides in situ are usually lower still (rarely above 10 µg l-1) underscoring the importance of degradation studies for risk assessment mimicking natural concentrations as closely as possible.

Conditions in the light + sediment treatment were the most environmentally relevant experimental degradation conditions applied and the herbicide half-lives obtained under these conditions represent the most reliable estimates for herbicide persistence in tropical marine waters available. Nevertheless, the differences in degradation rates under the four experimental conditions highlights the strong effects of light and the presence of sediments on herbicide persistence in seawater. Different sediment types (and levels) will contain different concentrations of minerals and humic acids which may further aid non-biotic degradation processes and differentially sequester herbicides from the water column (Rice et al., 2004). It is highly likely that full sunlight conditions would enhance photodegradation processes, although the highest concentrations of herbicides are found in river plumes where light penetration is strongly attenuated. Herbicide transport into the marine environment in river plumes also raises the question of relative persistence in fresh vs marine waters. The result from the present study indicate persistence of herbicides may be longer in seawater than freshwater (PPDB, 2011; Starner et al., 1999), but comparisons between studies may be misleading as relative persistence has not been experimentally tested under similar conditions. Since herbicide degradation is largely dominated by biotic processes (Fenner et al., 2013), the effects of light, sediments (including nutrients), temperature and salinity on degradation rates are most likely due to influences on bacterial community structure and population densities. The current study helps address an important knowledge gap on pesticide transformation for regulators by measuring herbicide degradation at low concentrations in seawater (Fenner et al., 2013). Future research needs to test the persistence of a wider range of pesticides at low concentrations in natural coastal waters of varying salinities and in the presence of different sediment types. In particular, research into the mobility, transport, degradation and toxicity of newly registered or alternative herbicides is lacking and risks posed by these herbicides to the marine environment remains unclear (Davis et al., 2014). Attention to the metabolites (transformation products) of herbicide degradation, which may be persistent and toxic, is also needed (Fenner et al., 2013). Herbicide metabolites were not specifically addressed in the current study, although the presence of DEA and DIA confirmed the role of bacteria in the degradation of atrazine (Moncada, 2004; Stasinakis et al., 2009). In combination, new advances in HPLC-MS techniques and quantitative molecular tools should enable far more comprehensive analysis of transformation products, degradation pathways and potential in the laboratory and in situ.

4.6 References

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Lin, C.H., Lerch, R.N., Garrett, H.E., George, M.F., 2008. Bioremediation of atrazine-contaminated soil by forage grasses: Transformation, uptake, and detoxification. J. Environ. Qual. 37, 196-206. Magnusson, M., Heimann, K., Ridd, M., Negri, A.P., 2012. Chronic herbicide exposures affect the sensitivity and community structure of tropical benthic microalgae. Mar. Pollut. Bull. 65, 363-372. Mandelbaum, R.T., Sadowsky, M.J., Wackett, L.P., 2008. Chapter 22 - Microbial degradation of s- triazine herbicides, in: LeBaron, H.M., McFarland, J.E., Burnside, O.C. (Eds.), The Triazine Herbicides. Elsevier, San Diego, pp. 301-328. Mercurio, P., Flores, F., Mueller, J.F., Carter, S., Negri, A.P., 2014. Glyphosate persistence in seawater. Mar. Pollut. Bull. 85, 385-390. Mercurio, P., Mueller, J.F., Eaglesham, G., Flores, F., Negri, A.P., 2015. Herbicide persistence in seawater simulation experiments. PLoS ONE 10, e0136391. Moncada, A., 2004. Environmental fate of diuron. Environmental Monitoring Branch, Department of Pesticide Regulation, Sacramento, CA, 1-11. Negri, A.P., Flores, F., Mercurio, P., Mueller, J.F., Collier, C.J., 2015. Lethal and sub-lethal chronic effects of the herbicide diuron on seagrass. Aquat Toxicol 165, 73-83. O’Brien, D.S., Lewis, S.E., Davis, A., Gallen, C., Paxman, C., Smith, R., Warne, M., Mueller, J., Brodie, J.E., 2013. Pesticide exposure within the Barratta Creek Catchment, Report to the Reef Rescue Water Quality Research & Development Program. Reef and Rainforest Research Centre Limited, Cairns, p. 49. OECD, 1992. OECD guidelines for testing of chemicals—306 Biodegradability in seawater, pp. 1- 27; Accessed March 2015. OECD, 2000. OECD guidelines for testing of chemicals—106: Adsorption-Desorption using a batch equilibrium method, pp. 1-44; Accessed March 2015. Okamura, H., 2002. Photodegradation of the antifouling compounds Irgarol 1051 and diuron released from a commercial antifouling paint. Chemosphere 48, 43-50. Packett, R., Dougall, C., Rohde, K., Noble, R., 2009. Agricultural lands are hot-spots for annual runoff polluting the southern Great Barrier Reef lagoon. Mar. Pollut. Bull. 58, 976-986. Pathiratne, A., Kroon, F.J., 2015. Using species sensitivity distribution approach to assess the risks of commonly detected agricultural pesticides to Australia's tropical freshwater ecosystems. Environ Toxicol Chem. Potter, T.L., Bosch, D.D., Dieppa, A., Whitall, D.R., Strickland, T.C., 2013. Atrazine fate and transport within the coastal zone in southeastern Puerto Rico. Mar. Pollut. Bull. 67, 36-44. PPDB, 2011. Pesticide Properties Database. Agriculture & Environment Research Unit (AERU), University of Hertfordshire. Accessed March 2015

Rice, P.J., Anderson, T.A., Coats, J.R., 2004. Effect of sediment on the fate of metolachlor and atrazine in surface water. Environ Toxicol Chem 23, 1145-1155. Salvat, B., Roche, H., Ramade, F., 2015. On the occurrence of a widespread contamination by herbicides of coral reef biota in French Polynesia. Environ Sci Pollut Res, 1-12. Santilio, A., Stefanelli, P., Girolimetti, S., Dommarco, R., 2011. Determination of acidic herbicides in cereals by QuEChERS extraction and LC/MS/MS. J Environ Sci Heal B 46, 535-543. Shaw, C.M., Lam, P.K.S., Mueller, J.F., 2008. Photosystem II herbicide pollution in Hong Kong and its potential photosynthetic effects on corals. Mar. Pollut. Bull. 57, 473-478. Shaw, M., Furnas, M.J., Fabricius, K., Haynes, D., Carter, S., Eaglesham, G., Mueller, J.F., 2010. Monitoring pesticides in the Great Barrier Reef. Mar. Pollut. Bull. 60, 113-122. Smith, R., Middlebrook, R., Turner, R., Huggins, R., Vardy, S., Warne, M., 2012. Large-scale pesticide monitoring across Great Barrier Reef catchments – Paddock to Reef Integrated Monitoring, Modelling and Reporting Program. Mar. Pollut. Bull. 65, 117-127.

Starner, K., Kuivila, K.M., Jennings, B., Moon, G.E., 1999. Degradation rates of six pesticides in water from the Sacramento River, California. US Geological Survey Toxic Substances Hydrology Program Water Resource Investigation Rep, 89-99. Stasinakis, A.S., Kotsifa, S., Gatidou, G., Mamais, D., 2009. Diuron biodegradation in activated sludge batch reactors under aerobic and anoxic conditions. Water Res. 43, 1471-1479. Steen, R.J.C.A., Van Hattum, B., Brinkman, U.A.T., 2000. A study on the behaviour of pesticides and their transformation products in the Scheldt estuary using liquid chromatography- electrospray tandem mass spectrometry. J Environ Monitor 2, 597-602. Thouand, G., Durand, M.-J., Maul, A., Gancet, C., Blok, H., 2011. New concepts in the evaluation of biodegradation/persistence of chemical substances using a microbial inoculum. Frontiers in Microbiology 2, 164.

Chapter 5: Contribution of transformation products to the total herbicide toxicity in tropical marine organisms

5.1 Abstract

Few studies have considered the toxicity of herbicide degradation (transformation) products, even though these are frequently detected in the environment, and sometimes at concentrations higher than the parent compounds. The combined contributions of parent herbicide and transformation products have been included in the some risk assessments for aquatic and marine systems but this is not a universally applied method. In order to assess the potential contribution of toxicity by known and unknown transformation products of four commonly detected PSII herbicides we compared the acute toxicity of partially degraded PSII herbicides (including transformation products) with their parent compounds to tropical photosynthetic organisms: (i) coral symbionts (Symbiodinium sp.) and (ii) the green algae Dunaliella sp. and a non- photosynthetic organism (iii) prawn (Penaeus monodon) larvae. Concentration dependent inhibition of photosynthetic efficiency (∆F/Fm’) as measured by pulse amplitude modulation fluorometry by all parent herbicides was observed in both microalgal species. Apart from diuron, the toxicity in all degraded solutions could be accounted for by the measured concentrations of the parent compound. While this increased toxicity of the degraded diuron solution may be due to transformation products, it was unlikely to be caused by the best known breakdown product 3,4-

DCA, which in pure form did not inhibit ∆F/Fm’ in Symbiodinium sp. at concentrations up to those detected in the degraded mixture. Parent herbicides affected prawn larval metamorphosis only at the highest concentrations used in the experiment (≥ 1000 µg l-1). Larval prawn metamorphosis was sensitive to the pure transformation products of atrazine, with both DIA and DEA, significantly affecting metamorphosis at 3.5 and 3.8 µg l-1 respectively. These transformation products are likely to have contributed to inhibition of metamorphosis observed in the degraded atrazine mixtures. 3,4- DCA caused significant inhibition in metamorphosis at 188 µg l-1 and was likewise more toxic to prawn larvae than its parent diuron. The approach used in this study to produce naturally degraded herbicide material enabled us to explore the potential for multiple transformation products to contribute to herbicide toxicity. The likelihood that some herbicide transformation products to contribute to toxicity in the environment identified here supports the recommendation that the toxicity of emerging compounds and their transformation products to be assessed for their impact in the marine environment.

5.2 Introduction

Tropical marine ecosystems host a wide variety of flora and fauna, including nursery habitats, and support vulnerable, endangered or protected species such as corals, seagrass, dugong and sea turtles. In tropical North Queensland Australia, these sensitive marine environments lie adjacent to vast areas of agriculture, which represents a source of nutrients, sediments and chemicals that has contributed to the decline of reef health and water quality of the World Heritage- listed Great Barrier Reef (GBR) (Brodie et al., 2013). Agricultural herbicides target weeds, and their relatively high water solubility and mobility has led to contaminaion of marine environment, including the GBR (Lewis et al., 2009; Smith et al., 2012). The most widely detected group of herbicides in marine ecosystems are the photosystem II (PSII) herbicides which block photosynthetic electron transport in weeds (Trebst, 2008), but are also effective at inhibiting photosynthesis in non-target marine plants and algae. Of particular concern is the chronic exposure of sensitive environments including tidal wetlands, estuaries, seagrass beds, and coral reefs to PSII herbicides following monsoonal flood events (King et al., 2012). The risks of long-term exposures are likely as PSII herbicides can be detected in marine and estuarine systems year round (Magnusson et al., 2012; Shaw et al., 2010), and this is at least partly due to their long persistence (half-lives greater than 100 d) in seawater (Mercurio et al., 2015; Mercurio et al., Submitted). Herbicides have been shown in the laboratory to negatively impact tropical marine organisms including coral (Cantin et al., 2007; Jones and Kerswell, 2003; Negri et al., 2011; Watanabe et al., 2006), isolated coral symbionts (Symbiodinium sp.) (Shaw et al., 2012; van Dam et al., 2015), seagrass (Flores et al., 2013; Haynes et al., 2000; Negri et al., 2015; Ralph, 2000; Wilkinson et al., 2015b), and microalgae (Bengtson Nash et al., 2005; Magnusson et al., 2010). However, few herbicide toxicity studies have considered their degradation compounds or transformation products, even though these are frequently detected in the environment, often at concentrations higher than the parent compounds (Kolpin et al., 2004; Kolpin et al., 2000; Sinclair and Boxall, 2003; Stuart et al., 2012). The toxicities of transformation products can have both similar acute and chronic toxicity to the parent compound (Kolpin et al., 1998). An assessment by Sinclair and Boxall (2003) found that 30% of pesticide transformation products are more toxic than the parent herbicide. When the toxicity of herbicide transformation products and parent compounds are combined, the total toxicity of water samples can increase by up to an order of magnitude (Kolpin et al., 2000). Diuron and atrazine represent two commonly detected PSII herbicides in tropical marine systems(Lewis et al., 2009). The main transformation product of diuron is 3,4-dichloroaniline (3,4-DCA) and this has been reported to be more toxic to some species than diuron (Caracciolo et al., 2005; Kiss and Virág,

2009; Tixier et al., 2000; Tixier et al., 2001). Atrazine’s main environmental transformation products, desethylatrazine (DEA) and desisopropylatrazine (DIA), are reported as having comparable toxicities (Belluck et al., 1991; Meakins et al., 1995). Tropical benthic microalgae were less sensitive to 3,4-DCA and DEA than their parent herbicides (Magnusson et al., 2010), adding to the uncertainty regarding contributions of herbicide transformation products to overall toxicity. The transformation products of atrazine and diuron have been reported frequently in the GBR region (Kennedy et al., 2012a; Kennedy et al., 2012b), sometimes reaching concentrations over 2 μg l-1 (O’Brien et al., 2013). The combined contributions of parent compounds and transformation products have been included in the overall risk assessment (Giddings et al., 2005; Solomon, 1999, 2001), but this is not a universally applied method. When the mode of action of herbicide and transformation products are the same, chemical addition (∑Ci x Pi, where Ci is the concentration of herbicide i and P is the potency of herbicide i relative to the reference herbicide) can be used to generate total mixture toxicities (Magnusson et al., 2010; Porsbring et al., 2010; Shaw et al., 2009). However, this approach does not take into account (i) transformation products that have not been identified, (ii) transformation products of unknown herbicidal toxicity (Fenner et al. 2013) and (iii) transformation products that have a different mode of toxicity and may therefore affect other non-target species such as animals. Furthermore, PSII herbicides have very long persistence (Mercurio et al., 2015) and if the persistence of their transformation products is also long, this may contribute to previously unrecognised risk. Transformation products should be incorporated into water quality guidelines and chemical risk assessments (Kookana and Simpson, 2000) but specific toxicity data on the myriad of potential transformation products is not available (Fenner et al. 2013). In order to assess the potential contribution of toxicity by known and unknown transformation products of four PSII herbicides we compared the acute toxicity of partially degraded PSII herbicides (including transformation products) with their parent compounds to both non-target photosynthetic organisms (i) coral symbionts (Symbiodinium sp.) and (ii) the green algae Dunaliella sp. and a non-photosynthetic organisms (iii) prawn (Penaeus monodon) larvae. For the following experiment there were two null hypotheses: 1. The toxicity of mixtures containing parent herbicides and their transformation products are not more toxic to tropical microalgae than the equivalent concentrations of parent herbicide. 2. Herbicide transformation products are not more toxic to prawn larva than their parent herbicides.

5.3 Methods

5.3.1 Degraded herbicide material production

In this study, PSII herbicides/transformation product mixtures were generated by adding herbicides to seawater within separate 120 l outdoor tanks, in the presence of natural coastal sediments and sampled for toxicity tests after 330 d. The tanks were partially shaded (70%) and exposed to a maximum of 700 µmol photons m-2s-1 over the course of the experiment (Hobo light and temperature loggers UA-001-64, Onset, Bourne, MA). The application of a natural diurnal light regime and coastal sediment were previously shown to increase the rates of PSII herbicide degradation and represent more natural conditions than those used in standard degradation tests (Mercurio et al., Submitted). The 20 tanks included replicates for control seawater (n = 4) and the PSII herbicides diuron (n = 4), atrazine (n = 3), simazine (n = 3), hexazinone (n = 3), and ametryn (n = 3). Evaporation was minimised with loose-fitting clear acrylic lids on the top row and the water continuously circulated using Turbelle Nanostream pumps. Prior to every sampling period evaporation losses were replenished with equal volumes of MilliQ water. The average temperature was 25.7°C with a range of 15.6 – 36.6°C over the course of the study.

5.3.2 Sediments and water

Unfiltered coastal seawater and intertidal sediments were collected from Australian Institute of Marine Science (19°16’ S, 147° 03’ E), Cape Cleveland, QLD. The sediments were prepared one week prior to use by sieving (> 2 mm removed) and thorough mixing. Each tank contained 5 kg of sediment. Physical and chemical information on the seawater and sediments used the open tank experiment can be found in Appendix Table 17).

5.3.3 Herbicide addition, sampling and analysis

Herbicide treatments and replicates (n = 3 or 4) were randomized among tanks. The five herbicides were purchased from Sigma Aldrich (>95% purity) and were introduced at relatively high concentrations (~1 mg l-1) to allow direct chemical and toxicological analysis of the herbicide transformation product mixtures. Sample collection, internal standard addition, and analytical techniques (HPLC-MS/MS using an AB/Sciex API5500Q mass spectrometer equipped with an electrospray interface and coupled to a Shimadzu Prominence HPLC system) were as previously

reported (Mercurio et al., 2015). Samples were periodically monitored for the parent herbicide (i.e. diuron, atrazine) and common herbicide transformation products (i.e. diuron degrading to 3,4-DCA; atrazine degrading to DEA and DIA) over the course of the regular sampling. Herbicide transformation product mixtures containing the most degraded parent herbicide were chosen for the toxicity experiments. Individual replicates were analysed using HPLC/TripleTOF mass spectrometry for possible transformation products. 0.2 µm-filtered samples were directly injected into an ABSciex API5600+ Triple TOF mass spectrometer (ABSciex, Concord, Ontario, Canada) equipped with an electrospray (TurboV) interface coupled to a Shimadzu Nexera HPLC system (Shimadzu Corp., Kyoto, Japan). Separation was achieved using a 4 micron 50 x 2.0 mm Phenomenex Synergi Fusion RP column (Phenomenex, Torrance, CA) run at 45oC, and a flow rate of 0.4 mL min-1 with a linear gradient starting at 8% B for 0.5 minutes, ramped to 100% B in 8 minutes then held at 100% for 2.0 minutes followed by equilibration at 8% B for 2.5 minutes. (A = 1% methanol in HPLC grade water, B = 95% methanol in HPLC grade water, both containing 0.1% acetic acid). The mass spectrometer was operated in positive ion SWATH mode. Briefly this mode comprises a TOF scan of 50 millisecond duration followed by small segments of the mass range being transmitted through the quadrupole, fragmented in the collision cell and full TOF mass spectra taken of the transformation products. Data from these experiments was examined using the Masterview software (ABSciex). Potential transformation products identified using TOF mass spectrometry and other potential transformation products identified from literature were then re-examined by HPLC/ triple quadrupole mass spectrometry using multiple reaction monitoring. Product ions used were as identified from QTOF data or from literature references and parameters such as collision energy optimised by repeated injections of samples for compounds detected. Standards were obtained for some of these compounds and all samples re run (method details as for parent compound analysis with extra transformation products as per Appendix Table 18). The toxicology samples were analysed via direct injection using HPLC-MS/MS with multiple reaction monitoring (Appendix Tables 19/20), with a standard calibration at beginning and end, and additional quality control standards run every 10 samples (Mercurio et al., 2015). The degraded herbicide solutions were made using the degraded control seawater. Control treatments for each toxicity assay included: 0.2 µm filtered fresh seawater (FSW), 0.2 µm filtered solvent control seawater, and 0.2 µm filtered seawater sampled from control tanks after 330 d (=degraded control).

5.3.4 Microalgae assay

As primary producers, microalgae play an important role in the marine food web and have been used in a number of sensitive assays for the assessment of toxicity of both herbicides and their transformation products (Booij et al., 2015; Magnusson et al., 2010; Shaw et al., 2012). High throughput 96 well plate designs allow for increased replication and a wide range of concentrations especially when paired with pulse amplitude modulation (PAM) fluorometry (for a review of the technique see: (Muller et al., 2008; Schreiber et al., 2007). PAM fluorometry measures chlorophyll fluorescence and can be used to calculate inhibitions of effective quantum yield ∆F/Fm’ (Magnusson et al., 2010; Wilkinson et al., 2015a), which is proportional to reduced photosynthetic efficiency (Schreiber, 2003) and growth in microalgae (Magnusson et al., 2008; Magnusson et al., 2010) and can be plotted against toxicant concentrations to derive concentrations that inhibit

∆F/Fm’ by 10 and 50% (IC10 and IC50). In the present study the green algae (Dunaliella sp.) and coral symbiont (Symbiodinium sp.) were exposed to herbicides and degraded herbicide solutions for 24 h in a 96-well plate format. A Maxi-Imaging-PAM (I-PAM) (Walz, GmbH Germany) was used to measure inhibition of ∆F/Fm’ using settings provided below.

5.3.5 Microalgal cultures

Symbiodinium cells were isolated by air blasting from coral branches of Acropora tenuis colony (collected under the permit G10-33440.1) growing at 2-5 m depth in Nelly Bay, Magnetic Island, GBR. Coral tissue/symbiont material was removed from coral pieces by tissue blasting and resuspended into 0.2 µm filtered seawater followed by three sequential washes in filtered seawater (5 min at 1600 g). Clean Symbiodinium cells were inoculated into sterile IMK growing media, the culture was purified, DNA extracted, and Clade C1 identified as published previously (Beltran et al., 2012; Stat et al., 2013; van Oppen et al., 2001). Cultures were maintained at 26°C, 60 µE PAR, 14:10 light:dark photoperiod inside environmental chambers (Steridium e500). The Dunaliella sp. (CS-353) (Chlorophyceae) was obtained from the Commonwealth Scientific and Industrial Research Organisation (CSIRO) Collection of Living Microalgae (CCLM). The algae was subcultured and grown in F2 media. For the toxicology assays, an exponentially growing culture was employed (Magnusson et al., 2008) and density adjusted by hemocytometry under 10X magnification. Day 7 sub-cultures were used throughout the experiment.

5.3.6 Plate loading and experimental conditions

A Perkin Elmer Janus liquid handling system was used to accurately deliver solutions to each treatment plate. Black 96-well plates (Perkin Elmer) were utilised and each well received 100 µl solution from the liquid handling robot and then 100 µl of algal suspension was added manually via multi-channel pipette and finally the solution was gently mixed. The 96 well plate positions included controls (as described above; filtered seawater controls (n = 16), solvent controls (n = 8), degraded controls (n = 8)) and randomised treatment samples across a concentration range targeting -1 IC50 values (n = 4 at each concentration). Each plate include a positive diuron control (3 µg l , n=4) in order to confirm consistent sensitivities among the replicate algal subcultures. Treatment and positive control positions were randomised across the plates in duplicate pairs. The 96 well plate assay and design was based upon previous method development and approach from previous authors (Magnusson, 2009; Muller et al., 2008; Schreiber et al., 2007). Plates containing the Symbiodinium culture were incubated over a 12:12 h light:dark cycle at 26°C and 60-70 µmol photons m-2s-1 and the plates with the Dunaliella sp. were incubated at Walk-in incubator: 26°C and 130 µmol photons m-2s-1. After the cultures were added, the microalgae were exposed for 24 hours before PAM measurements. Maxi-IPAM settings for both species were: Actinic light = 1, ML = 10, ML frequency = 8, gain = 2 and damping = 1 throughout the experiment. Samples were subjected to the 50 µmol photons m-2s-1 actinic light for 1 min prior to measurement.

5.3.7 Prawn larvae assay

Penaeus monodon or the giant tiger prawn is distributed throughout the tropical Indo-Pacific region and is widely available from aquaculture facilities with well-described life cycle. The objective of the larval prawn assay was to determine if the herbicides and or their transformation products may negatively impact early naupliar development. The eggs hatch into their first larval stage (nauplii), typically 12-15 hours after spawning (Fisheries, 2007). During development the nauplii are lecithotrophic, and over the course of the next 1.5 days, nauplii pass through 6 sub- stages before transforming into protozoae (Fisheries, 2007; Marsden, 2008). Postlarvae of Penaeus monodon have been used for pesticide ecotoxicology previously where the potential effects of dredge sediment containing endosulfan and lindane were investigated (Sumith et al., 2009).

5.3.8 Prawn larvae collection and experimental conditions

Freshly hatched nauplii from a commercial hatchery were harvested by light attraction over a 30 min period, as healthy individuals have a strong phototaxis response (Fisheries, 2007). The

nauplii were washed and aerated for 10 min with fresh seawater, and transported to AIMS in Townsville, Queensland. Pilot experiments demonstrated normal development without feeding at stocking density up to 1000 nauplii l-1 and we subsequently cultured at conservative stocking densities of 75-150 nauplii l-1. The toxicity assay was performed in temperature-regulated incubator shakers (set to 30°C) where conditions were maintained under very low light conditions and with gentle shaking to prevent the nauplii adhering to the side of experimental containers/jars.

5.3.9 Metamorphosis assay on naupliar development

The larval stock was gently concentrated via reverse-gravity filtration to a higher density before dispensing 8-10 individuals per 20 ml glass scintillation vial containing the same treatment conditions and concentrations as in the coral larvae toxicity assay. Additional positive control treatments in the form of 4 concentrations of copper II chloride solution (2 to 900 µg l-1 Cu), were included for test validation. The static assay was terminated after 24 h when control treatments when larvae in control treatments had reached maximum metamorphosis. Immediately after the experiment, 10% seawater formalin was added to each vial as a preservative for later microscopy. Metamorphosis was considered successful when nauplii had developed into protozoea.

5.3.10 Data handling, IC50 handling and modelling

Inhibition was defined as the impact upon of metamorphosis (prawn larvae) or photosynthetic efficiency (Symbiodinium sp. or Dunaliella sp.) in each of the toxicology assays. Inhibition was calculated as the percent relative to control from treatment data (as inhibition % relative to control) where Inhibition (%) = 100  [(% metamorphosiscontrol –

%metamorphosistreatment)/% metamorphosiscontrol]. The concentration of herbicide, transformation products (e.g. DEA, DIA), or degraded solution (based upon the parent compound concentration) that inhibited 10% and 50% of photosynthetic yield (IC10 and IC50) was calculated from concentration-response curves (four-parameter logistic models) fitted to the % inhibition and log transformed concentration data of each treatment using the program GraphPad Prism (v6, San Diego, USA). The model was constrained by applying a lower limit of 0% inhibition and all curves were tested for normality of the residuals and a replicate test was applied to assess the goodness of fit. The probability that IC50 values generated by the logistic curves were statistically different was tested by applying the F test in Graph Pad Prism v6. IC50s were considered different when p < 0.05. One-way analysis of variance (ANOVA) was performed to identify treatments which caused significant (p < 0.05) inhibition of metamorphosis in comparison with control treatments (NCSS v9, 82

Utah, USA). The larval prawn experimental data was arcsin square root transformed prior to statistical analysis.

5.4 Results

5.4.1 Symbiodinium / Dunaliella assay

Concentration dependent inhibition of ∆F/Fm’ by all parent herbicides was observed in both microalgal species (Fig. 5.1). From the ∆F/Fm’ data IC50 were able to be calculated for the parent herbicides and degraded herbicides, these are reported in Table 5.1. Comparisons were made of the inhibition of the parent herbicide compounds (fresh standard solutions) and degraded herbicide material that contained the parent compound and transformation products. Concentrations of degraded solutions including parent and transformation products for all concentrations used in the microalgae experiment are outlined in Appendix Table 21. Apart from diuron, the toxicity in all degraded solutions could be accounted for by the concentrations of the parent compound (e.g. the

IC50s of concentration-response curves of the parent compound were not significantly different) (Table 5.1). For the degraded diuron treatment, this indicates potential contribution to the observed inhibition of ∆F/Fm’ by transformation products we were able to identify (Table 5.1) or transformation products that remain unknown. Symbiodinium sp. and Dunaliella sp. were exposed to standard solutions of diuron’s transformation product 3,4-DCA at concentrations up to 273 µg l-1, but no significant inhibition of

∆F/Fm’ was observed at that concentration. The relative equivalent potency (REP) could therefore not be calculated as the 3,4-DCA. A literature search could not find comparable data on the toxicity of the identified transformation products on microalgae to assess the potential contribution of these compounds to the unexplained toxicity of degraded diuron solutions. Some inhibition (<8%) was observed due to atrazine’s transformation product DIA at concentrations of 458 µg l-1 for both Symbiodinium sp. and Dunaliella sp. and this inhibition was significant for Dunaliella sp.

A: Symbiodinium sp. , Diuron B: Dunaliella sp., Diuron 100 100

80 80

60 60

40 40

20 Herbicide 20 Degraded herbicide 0 0 0.1 1 10 100 0.1 1 10 100

C: Symbiodinium sp., Atrazine D: Dunaliella sp., Atrazine 100 100

80 80

60 60

40 40

20 20

) ' 0 0

m 0.1 1 10 100 0.1 1 10 100

F/F  E: Symbiodinium sp., Ametryn F: Dunaliella sp., Ametryn 100 100

80 80

60 60

40 40

% Inhibition ( Inhibition %

20 20

0 0 0.1 1 10 100 0.1 1 10 100 G: Symbiodinium sp., Hexazinone H: Dunaliella sp., Hexazinone 100 100

80 80

60 60

40 40

20 20

0 0 0.1 1 10 100 1000 0.1 1 10 100 1000

I: Symbiodinium sp., Simazine J: Dunaliella sp., Simazine 100 100

80 80

60 60

40 40

20 20

0 0 0.1 1 10 100 0.1 1 10 100 Herbicide concentration (µg l-1)

-1 Table 5.1: Comparison of IC50 (µg l ) values of standard parent herbicides and degraded mixtures (after 330 d) from each herbicide. These IC50 values represent the concentration of parent herbicide in the toxicity assays that inhibit ∆F/Fm’ by 50% and correspond to the concentration-response curves in Fig. 1. Differences in IC50s were assessed using the F-test in GraphPad considered significant when < 0.05 and this was only the case for Symbiodinium sp. exposed to diuron vs the degraded diuron solutions.

2 IC50 95% CI r F(df) P value Symbiodinium sp. Diuron 1.4 1.3 to 1.6 0.996 Degraded Diuron 0.95 0.92 to 0.99 0.996 F (1,84) = 34.11 < 0.0001 Atrazine 34.5 31.7 to 35.4 0.995 Degraded Atrazine 31.9 26.6 to 38.2 0.973 F (1,110) = 0.3521 0.5541 Ametryn 2.2 2.1 to 2.3 0.996 Degraded Ametryn 2.3 2.2 to 2.4 0.995 F (1,93) = 2.133 0.1475 Hexazinone 45.7 39.5 to 52.9 0.978 Degraded Hexazinone 50.5 45.5 to 56.2 0.982 F (1,89) = 3.413 0.068 Simazine 84 76.6 to 92.0 0.987 Degraded Simazine 72.5 63.2 to 83.3 0.993 F (1,74) = 1.591 0.2111 Dunaliella sp. Diuron 4.4 4.2 to 4.6 0.994 Degraded Diuron 4.1 3.8 to 4.5 0.993 F (1,103) = 0.9801 0.3245 Atrazine 34.6 32.0 to 37.5 0.988 Degraded Dtrazine 40.4 34.9 to 46.8 0.994 F (1,95) = 1.956 0.1652 Ametryn 3.4 3.2 to 3.6 0.996 Degraded Ametryn 3.7 3.5 to 3.8 0.997 F (1,81) = 17.27 0.0789 Hexazinone 37.9 36.0 to 40.0 0.993 Degraded Hexazinone 40.1 37.6 to 42.7 0.994 F (1,87) = 2.236 0.1384 Simazine 86.8 78.8 to 95.7 0.991 Degraded Simazine 103 73.4 to 146 0.993 F (1,78) = 0.8414 0.3618

(ANOVA, p < 0.05). Significant inhibition (>9-35%) was caused by DEA at 84 µg l-1 for -1 Symbiodinium sp. and at 56 µg l for Dunaliella sp. (Fig. 5.2 and Appendix Table 22). IC20 and

IC10 values for DEA were able to be derived for both microalgae species (Table 5.2).

5.4.2 Larval prawn assay

Prawn larval metamorphosis was 88.3 – 93.3% in control conditions and this was not different between SW, solvent and degraded control water (Fig. 5.3, Appendix Table 23). Three concentrations of copper were used as a reference compound in order to bracket the estimated

24 hr IC50s from previously published work on larval prawns (Bambang et al., 1995; Chen and Lin, 2001; Lawrence et al., 1981). The copper treatment was included in order to demonstrate that the 85

assay was sensitive in the expected range of toxicity. In general, the parent herbicide standards affected the larval metamorphosis significantly only at the highest concentrations used in the experiment with the exception of ametryn and diuron which did not inhibit metamorphosis (Fig. 5.3, Table 5.3). The degraded herbicides also affected the metamorphosis significantly in comparison with the controls only at the highest concentrations used in the experiment and the degraded ametryn mixture did not inhibit metamorphosis at any concentration. While, there appeared to be differences in inhibition between parent herbicides and breakdown mixtures in Fig. 5.3, most of the low-medium concentrations did not cause significant inhibition. The only exception for the comparison of effective concentrations was the herbicide diuron as compared to degraded diuron. The highest concentration of degraded diuron used in the experiment was 70.6 µg l-1 and the parent compound was 100 and 325 µg l-1 yet did not result in having a significant effect on metamorphosis. See Appendix Table 24 for concentrations of degraded solutions containing the parent compound and transformation products.

100 Symbiodinium sp. DEA

) 80

' Dunaliella sp. DEA m

F/F 60 

20 % Inhibition ( Inhibition %

0.1 1 10 100 1000

DEA concentration (µg l-1)

Figure 5.2: PAM inhibition data as compared to controls for Symbiodinium sp. and Dunaliella sp. for the atrazine transformation product DEA.

Larval prawn metamorphosis was sensitive to the transformation products of atrazine, with both DIA and DEA significantly affecting metamorphosis at all concentrations applied in the experiment (ranging from 3.5 to 917 µg l-1) (Fig. 3, Table 3). The highest concentration of degraded atrazine contained 278 µg l-1 of the parent herbicide atrazine and also 5.1 and 36.3 µg l-1 DIA and DEA respectively, enough to significantly affect metamorphosis. Larval metamorphosis was less sensitive to diuron’s transformation product 3,4-DCA with inhibition only at the highest concentrations of 189 and 547 µg l-1 (Fig. 5.3, Table 5.3). However, the contribution of the

transformation products 3,4-DCA to the overall toxicity of the degraded diuron solution is not clear. The highest concentration of degraded diuron used (70.6 µg l-1 diuron) only contained 2.1 µg l-1

-1 Table 5.2: Comparison of IC20 and IC10 (µg l ) values of atrazine and transformation product DEA for Symbiodinium sp. and Dunaliella sp.

2 IC10 95% CI IC20 95% CI r

Symbiodinium sp. Atrazine 8.61 7.97 to 9.30 14.2 13.5 to 15.0 0.99 DEA 103 93.4 to 115 218 203 to 233 0.95 Dunaliella sp. Atrazine 12.4 11.0 to 14.0 18.1 16.5 to 19.8 0.99 DEA 157 142 to 173 310 290 to 332 0.93

Table 5.3: Effects of herbicides and their transformation products on the success of prawn larval metamorphosis. NOEC = no observed significant effect concentration and LOEC = lowest observed significant effect concentration. Significantly different from solvent control when ANOVA p < 0.05.

NOEC LOEC (µg l-1) (µg l-1) F(df) P value Diuron 874 >874 0.53 (6,47) 0.7819 Degraded diuron 34 71 3.3 (6,47) 0.0096 3,4-DCA 54 188 16.6 (6,45) 0.000 Atrazine 197 899 3.97 (6,47) 0.0032 Degraded Atrazine 143 278 3.34 (6,47) 0.0090 DIA 0 3.5 23.9 (6,47) 0.000 DEA 0 3.8 63.6 (6,47) 0.000 Ametryn 517 >517 0.57 (6,47) 0.7493 Degraded Ametryn 188 >188 0.9(6,47) 0.5044 Copper reference 11 91 98.0 (3,29) 0.000

3,4-DCA. Two other identified transformation products were present at greater concentration than the parent herbicide (Table 5.4), which may have contribute to toxicity but this is uncertain as they are not available as analytical standards for toxicity testing.

5.4.3 Herbicide degradation and identification of transformation products

After 330 d the experiment was stopped as our previous study indicated that considerable proportions of the parent herbicides should have degraded by this time (Mercurio et al. 2016).

Between 56-93% of each of the parent herbicides remained after this time (Table 5.4). Transformation products were identified for each of the herbicides and these are listed in Appendix Table 18. Transformation products, where possible, were confirmed by comparison of retention

Figure 5.3: Concentration response relationships for herbicides and their transformation products to prawn larvae. Metamorphosis (%) for larval prawns for parent herbicides, degraded herbicides, and copper. * indicates significant decrease in metamorphosis in comparison to solvent control samples (p < 0.05, ANOVA Appendix Table 23). C = controls. The reduced metamorphosis in the DIA and DEA treatments were all significantly different than controls.

Table 5.4: Initial herbicide concentration (µg l-1) and day 330, when the experiment was terminated. Includes transformation products and concentrations which were measured and estimated. (See Appendix Tables 19 and 20 for identification and quantification details).

Time Parent Transformation Herbicide (days) herbicide products 3,4- Diuron DCPU DCPMU mCPDMU Dichloroaniline Degraded Diuron 0 967 BDL BDL BDL BDL Degraded Diuron 330 70.6 2.1 84.5 236.0 BDL Degradation ~93%

Desisopropyl Atrazine Atrazine Desethyl Atrazine Atrazine hydroxy Degraded Atrazine 0 773 BDL BDL BDL

Degraded Atrazine 330 278.0 36.3 5.1 29.9

Degradation ~64%

Ametryn Ametryn Ametryn Ametryn hydroxy desethyl desisopropyl

Degraded Ametryn 0 429 BDL BDL BDL

Degraded Ametryn 330 188.6 188.4 23.4 BDL

Degradation ~56%

Hexaz Hexazinone Hexaz oxy Hexaz hydroxy desmethyl

Degraded Hexazinone 0 871 BDL BDL BDL

Degraded Hexazinone 330 365.7 25.9 5.4 90.5

Degradation ~58%

Desethyl Simazine Simazine Simazine Simazine hydroxy amine Degraded Simazine 0 1024 BDL BDL BDL

Degraded Simazine 330 384.1 79.3 45.4 31.1

Degradation ~63%

time and spectra with available standards (Appendix Table 18). Other potential transformation products, for which no standards were available. were identified by comparison of fragmentation patterns with literature data. The fragments used to quantify transformation products are provided in Appendix Tables 19 and 20. ABSciex Multiquant software was used for quantification of transformation products by comparison to a five point calibration curve using analytical standards when available or from response factors of the parent compound (modified as indicated) when standards were not available (Appendix Table 18).

5.5 Discussion

In order to protect the GBR, water quality programs monitor the levels of suspended sediments, nutrients, and pesticides (including herbicides) that flow into the nearshore marine environment. However, the majority of monitoring programs and risk assessments for herbicides only consider the parent herbicide compounds and at best a small subset of transformation products (Davis et al., 2008; Davis et al., 2011; Lewis et al., 2009; Smith et al., 2012). Recently there has been an increased interest to include transformation products as part of the risk assessment process, as these potentially toxic compounds have been shown to be present (sometimes at greater concentrations) in the environment (Fenner et al., 2013; O’Brien et al., 2013). The present study aimed to determine whether or not there was a difference in toxicity of degraded herbicide solutions, which through a natural degradation process would include transformation products, in comparison with the parent herbicide. In general most of the degraded herbicide mixtures, the transformation products, did not contribute significantly to the toxicity of PSII herbicides in microalgae. However, degraded diuron mixtures were significantly more toxic to Symbiodinium. This additional toxicity was likely due to the contribution of transformation products that are not usually monitored in the environment. Furthermore, the toxicity of DEA and DIA to prawns indicate pesticide risk assessments would be improved by the inclusion of toxicity data for transformation products of herbicides to both phototrophic species and heterotrophs. Acute toxicity assays with microalgae in 96 well plates offer the ability to sensitively screen PSII across a wide range of concentrations (Magnusson et al., 2010; Muller et al., 2008). The parent herbicides inhibited ∆F/Fm’ in the current study assays at similar concentrations to previous studies on microalgae (Magnusson et al., 2010; Muller et al., 2008). For diuron and ametryn and their respective degraded herbicide solutions, IC50 values were within the range of concentrations that could be found in waters flowing into the nearshore coastal habitat during first flush or flood plumes (Davis et al., 2008). Concentration-response curves (IC50s) of degraded solutions were only different to the parent herbicides for Symbiodinium sp. where the degraded diuron solution had an

IC50 33% lower than the diuron alone. While this increased toxicity of the degraded diuron solution may be due to transformation products, it is most likely not due to the best known breakdown product 3,4-DCA, which in pure form did not inhibit ∆F/Fm’ in Symbiodinium sp. at concentrations up to 273 µg l-1. This outcome was consistent with previous experiments on microalgae (Magnusson et al., 2010). In this instance, additional toxicity testing is required to determine whether the toxicity was due to the other transformation products within the degraded diuron solution.

Of the three transformation products that were available commercially and tested in the assays, significant effects on photosynthetic efficiency in microalgae were observed from DEA (both Symbiodinium sp. and Dunaliella sp.) and DIA (Dunaliella sp), See Appendix Table 22.

Only IC20 and IC10 values were able to be calculated as there was only moderate inhibition of

∆F/Fm’ at the highest concentrations applied in the experiment. The IC10 values for DEA were comparable to other microalgae using maximum inhibition as an experimental endpoint. From

Table 5.2, the calculated IC10 values for Symbiodinium sp. and Dunaliella sp were 103.7 and 156.8 -1 -1 µg l DEA respectively. IC10 values for DEA using Navicula sp. (111 µg l ), Nephroselmis pyriformis (26.6 µg l-1), Phaeodactylum tricornutum (46 µg l-1) and Cylindrotheca closterium (102 µg l-1) were reported previously (Magnusson et al., 2010). Low concentrations of DIA and DEA (< -1 40 µg l ) were detected in the degraded atrazine solutions, but well below their calculated IC10 concentrations. Their lack of toxicity to these species was confirmed with nearly identical IC50s calculated from concentration-response curves for atrazine and its degraded mixture. The concentrations of DIA and DEA that inhibited photosynthetic efficiency in these microalgae were also far higher than environmentally relevant concentrations found in the nearshore GBR region (Davis et al., 2008; O’Brien et al., 2013). Invertebrates, including shrimps and prawns, are generally not sensitive to herbicides unless exposed in the mg l-1 concentration range (GBRMPA, 2010 Accessed March 2015) and could potentially be due to a non-specific (baseline effect) toxicity (Verhaar et al., 1992). However, there remains a possibility that transformation products may be more toxic to non-phototrophic species than the parent herbicide. Sensitivity to the reference toxicant copper, indicated that inhibition of prawn larval metamorphosis could be applied to detect additional toxicity of transformation products to non-phototrophic organisms. The response of prawn larvae to herbicides and their degraded mixtures was more variable than the effects on photosynthesis of microalgae. There was no significant effect of ametryn or its degraded mixture on larval metamorphosis. Hexazinone and its degraded mixture inhibited metamorphosis at concentrations of 1026 and 366 µg l-1 respectively and above, but the limited range of concentrations meant we were not able to determine whether transformation products may have contributed to toxicity. The degraded diuron solution containing transformation products was more toxic towards larval metamorphosis than diuron itself. The diuron transformation product 3,4-DCA was tested in an individual chemical assay but, as with the Symbiodinium sp. and Dunaliella sp. assay, most likely did not contribute to the toxicity. In the degraded solution the LOEC for 3,4-DCA was much higher than for concentrations detected in the degraded diuron solutions (max ~ 2 µg l-1). Toxicity was therefore again likely to have been due to other transformation products. Previous work on

3,4-DCA toxicity has been reported with a wide range of results, from LC50 values of 57.5 – 61.5 91

mg l-1 for Brachionus plicatilis and Brachionus calyciflorus respectively (Ferrando and Andreu- Moliner, 1991) to NOEC values for Gammarus pulex (60 µg l-1, 24 hr), Daphnia longispina (1 µg l- 1, 17 d), and Simocephalus vetulus (1 µg l-1, 17 d) (Giacomazzi and Cochet, 2004). An unexpected outcome was the sensitivity of prawn larvae to the transformation products of atrazine as tested individually. DIA and DEA were potent inhibitors of naupliar development; however, it is suggested to approach this information cautiously for two reasons. Firstly, an additional experiment should be performed as this was only a single series of tests (as prawns spawn only for a limited period there was no opportunity for repeated trials). Secondly, while the degraded atrazine significantly affected larval metamorphosis, based on their potency in individual tests, DEA and DIA detected in the highest degraded atrazine solution should have caused more inhibition than was observed (~ 59% metamorphosis at a combined DIA and DEA concentration of -1 over 40 µg l ). In contrast to our larval metamorphosis results, the 96-hour LC50 values for Hyalella azteca and Diporeia spp. have been reported as >3000 µg l-1 for both DEA and DIA (Ralston-Hooper et al., 2009). While most of the degraded solutions only affected naupliar development at concentrations higher than expected in the environment, this assay holds promise as a method to identify toxicity of transformation products (especially DIA and DEA) to non-target species and therefore deserves further development and assessment. The approach used in this study to produce naturally degraded herbicide material enabled us to simultaneously explore (in a practical way) the potential for multiple (known and unknown) transformation products to contribute to herbicide toxicity. The approach also provided us with enough material to recognise and identify a suite of potential transformation products that could be monitored in the future. Unknown structures were identified from mass spectral databases, descriptions of potential transformation products in relevant literature (e.g. hexazinone hydroxy and oxy, where our compounds matched the data), or were assigned tentative identifications as postulated from fragmentation (QTOF spectra) data (e.g. simazine amine). In the instance of simazine amine, confirmation would be required with standards or isolation and interrogation via additional structural platforms (e.g. NMR). This approach could provide a framework or structure for future work that includes incorporating transformation products for the full risk assessment, especially for emerging herbicide compounds or relevant species (tropical marine algae, invertebrates). Few toxicological studies have considered the impact of herbicide mixtures or mixtures containing transformation products (Bonnet et al., 2007; Cedergreen et al., 2004; Magnusson et al., 2010; Pesce et al., 2010). The transformation products of diuron and atrazine contributed to additional toxicity in Symbiodinium and in prawn larvae. And, while transformation products of the other herbicides did not appear to contribute significantly to toxicity of some degraded herbicide 92

mixtures, under other natural circumstances different (or different proportions of) potentially toxic martial may be formed, adding to unrecognised environmental risk. Further experimental degradation data for targeted environments and conditions, such as the tropics and the toxicity to a range of representative species, is required to improve confidence in environmental risk assessments (Fenner et al., 2013). The current study revealed relatively high toxicity of atrazine’s transformation products DIA and DEA to a non-phototropic organism, highlighting the need to consider harm to taxa that would not be normally considered sensitive to the parent contaminant. The potential for herbicide transformation products to contribute to toxicity in the environment identified here supports the recommendation that the toxicity of emerging compounds and their transformation products to be assessed for their impact in the marine environment.

5.6 References

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Lawrence, A.L., Fox, J., Castille, F.L., 1981. Decreased toxicity of copper and manganese ions to shrimp nauplii (Penaeus stylirostris Stimpson) in the presence of EDTA. Journal of the World Mariculture Society 12, 271-280. Lewis, S.E., Brodie, J.E., Bainbridge, Z.T., Rohde, K.W., Davis, A.M., Masters, B.L., Maughan, M., Devlin, M.J., Mueller, J.F., Schaffelke, B., 2009. Herbicides: A new threat to the Great Barrier Reef. Environ. Pollut. 157, 2470-2484. Magnusson, M., 2009. Effects of priority herbicides and their breakdown products on tropical, estuarine microalgae of the Great Barrier Reef Lagoon. James Cook University, Townsville, Queensland. Australia. Magnusson, M., Heimann, K., Negri, A.P., 2008. Comparative effects of herbicides on photosynthesis and growth of tropical estuarine microalgae. Mar. Pollut. Bull. 56, 1545- 1552. Magnusson, M., Heimann, K., Quayle, P., Negri, A.P., 2010. Additive toxicity of herbicide mixtures and comparative sensitivity of tropical benthic microalgae. Mar. Pollut. Bull. 60, 1978-1987. Magnusson, M., Heimann, K., Ridd, M., Negri, A.P., 2012. Chronic herbicide exposures affect the sensitivity and community structure of tropical benthic microalgae. Mar. Pollut. Bull. 65, 363-372. Marsden, G.E., 2008. Factors affecting reproductive performance of the prawn, Penaeus monodon, School of Natural Resource Sciences. Queensland University of Technology, p. 211. Meakins, N.C., Bubb, J.M., Lester, J.N., 1995. The mobility, partitioning and degradation of atrazine and simazine in the salt marsh environment. Mar. Pollut. Bull. 30, 812-819. Mercurio, P., Mueller, J.F., Eaglesham, G., Flores, F., Negri, A.P., 2015. Herbicide persistence in seawater simulation experiments. PLoS ONE 10, e0136391. Mercurio, P., Mueller, J.F., Eaglesham, G., O'Brien, J., Flores, F., Negri, A.P., Submitted. Degradation of herbicides in the tropical marine environment: Influence of light and sediment PLoS ONE. Muller, R., Schreiber, U., Escher, B.I., Quayle, P.a., Bengtson Nash, S.M., Mueller, J.F., 2008. Rapid exposure assessment of PSII herbicides in surface water using a novel chlorophyll a fluorescence imaging assay. Sci. Tot. Environ. 401, 51-59. Negri, A.P., Flores, F., Mercurio, P., Mueller, J.F., Collier, C.J., 2015. Lethal and sub-lethal chronic effects of the herbicide diuron on seagrass. Aquat Toxicol 165, 73-83. Negri, A.P., Flores, F., Rothig, T., S., U., 2011. Herbicides increase the vulnerability of corals to rising sea surface temperature. . Limnol. Oceanog. 56, 471-485. O’Brien, D.S., Lewis, S.E., Davis, A., Gallen, C., Paxman, C., Smith, R., Warne, M., Mueller, J., Brodie, J.E., 2013. Pesticide exposure within the Barratta Creek Catchment, Report to the Reef Rescue Water Quality Research & Development Program. Reef and Rainforest Research Centre Limited, Cairns, p. 49. Pesce, S., Lissalde, S., Lavieille, D., Margoum, C., Mazzella, N., Roubeix, V., Montuelle, B., 2010. Evaluation of single and joint toxic effects of diuron and its main metabolites on natural phototrophic biofilms using a pollution-induced community tolerance (PICT) approach. Aquat. Toxicol. 99, 492-499. Porsbring, T., Backhaus, T., Johansson, P., Kuylenstierna, M., Blanck, H., 2010. Mixture toxicity from photosystem II inhibitors on microalgal community succession is predictable by concentration addition. Environmental Toxicology and Chemistry 29, 2806-2813. Ralph, P.J., 2000. Herbicide toxicity of Halophila ovalis assessed by chlorophyll a fluorescence. Aquatic Botany 66, 141-152. Ralston-Hooper, K., Hardy, J., Hahn, L., Ochoa-Acuña, H., Lee, L.S., Mollenhauer, R., Sepúlveda, M.S., 2009. Acute and chronic toxicity of atrazine and its metabolites deethylatrazine and deisopropylatrazine on aquatic organisms. Ecotoxicology 18, 899-905. Schreiber, U., 2003. Pulse amplitude (PAM) fluorometry and saturation pulse method. Chlorophyll a fluorescence: A signature of photosynthesis. Advances in Photosynthesis and Respiration 95

Series, ed. by G. Papageorgiou and Govindjee. Dordrecht, Kluwer Academic Publishers, 1- 41. Schreiber, U., Quayle, P., Schmidt, S., Escher, B.I., Mueller, J.F., 2007. Methodology and evaluation of a highly sensitive algae toxicity test based on multiwell chlorophyll fluorescence imaging. Biosensors and Bioelectronics 22, 2554-2563. Shaw, C.M., Brodie, J., Mueller, J.F., 2012. Phytotoxicity induced in isolated zooxanthellae by herbicides extracted from Great Barrier Reef flood waters. Mar. Pollut. Bull. 65, 355-362. Shaw, M., Furnas, M.J., Fabricius, K., Haynes, D., Carter, S., Eaglesham, G., Mueller, J.F., 2010. Monitoring pesticides in the Great Barrier Reef. Mar. Pollut. Bull. 60, 113-122. Shaw, M., Negri, A., Fabricius, K., Mueller, J.F., 2009. Predicting water toxicity: Pairing passive sampling with bioassays on the Great Barrier Reef. Aquat. Toxicol. 95, 108-116. Sinclair, C.J., Boxall, A.B.A., 2003. Assessing the ecotoxicity of pesticide transformation products. Environmental Science & Technology 37, 4617-4625. Smith, R., Middlebrook, R., Turner, R., Huggins, R., Vardy, S., Warne, M., 2012. Large-scale pesticide monitoring across Great Barrier Reef catchments – Paddock to Reef Integrated Monitoring, Modelling and Reporting Program. Mar. Pollut. Bull. 65, 117-127. Solomon, K.R., 1999. Integrating environmental fate and effects information: The keys to ecotoxicological risk assessment for pesticides. Special Publication - Royal Society of Chemistry 233, 313-326. Solomon, K.R., 2001. Chapter 13 - Ecotoxicological risk assessment of pesticides in the environment, in: Robert, I.K., William, C.K. (Eds.), Handbook of Pesticide Toxicology (Second Edition). Academic Press, San Diego, pp. 353-373. Stat, M., Pochon, X., Franklin, E.C., Bruno, J.F., Casey, K.S., Selig, E.R., Gates, R.D., 2013. The distribution of the thermally tolerant symbiont lineage (Symbiodinium clade D) in corals from Hawaii: Correlations with host and the history of ocean thermal stress. Ecology and evolution 3, 1317-1329. Stuart, M., Lapworth, D., Crane, E., Hart, A., 2012. Review of risk from potential emerging contaminants in UK groundwater. Sci. Tot. Environ. 416, 1-21. Sumith, J.A., Parkpian, P., Leadprathom, N., 2009. Dredging influenced sediment toxicity of endosulfan and lindane on black tiger shrimp (Penaeus monodon Fabricius) in Chantaburi River estuary in Thailand. International Journal of Sediment Research 24, 455-464. Tixier, C., Bogaerts, P., Sancelme, M., Bonnemoy, F., Twagilimana, L., Cuer, A., Bohatier, J., Veschambre, H., 2000. Fungal biodegradation of a phenylurea herbicide, diuron: Structure and toxicity of metabolites. Pest. Manag. Sci. 56, 455-462. Tixier, C., Sancelme, M., Bonnemoy, F., Cuer, A., Veschambre, H., 2001. Degradation products of a phenylurea herbicide, diuron: Synthesis, ecotoxicity, and biotransformation. Environmental Toxicology and Chemistry 20, 1381-1389. Trebst, A., 2008. Chapter 8 - The mode of action of triazine herbicides in plants, in: LeBaron, H.M., McFarland, J.E., Burnside, O.C. (Eds.), The Triazine Herbicides. Elsevier, San Diego, pp. 101-II. van Dam, J.W., Uthicke, S., Beltran, V.H., Mueller, J.F., Negri, A.P., 2015. Combined thermal and herbicide stress in functionally diverse coral symbionts. Environ. Pollut. 204, 271-279. van Oppen, M.J.H., Palstra, F.P., Piquet, A.M.T., Miller, D.J., 2001. Patterns of coral– dinoflagellate associations in Acropora: Significance of local availability and physiology of Symbiodinium strains and host–symbiont selectivity. Proceedings of the Royal Society of London B: Biological Sciences 268, 1759-1767. Verhaar, H.J.M., van Leeuwen, C.J., Hermens, J.L.M., 1992. Classifying environmental pollutants. Chemosphere 25, 471-491. Watanabe, T., Yuyama, I., Yasumura, S., 2006. Toxicological effects of biocides on symbiotic and aposymbiotic juveniles of the hermatypic coral Acropora tenuis. Journal of Experimental Marine Biology and Ecology 339, 177-188.

Wilkinson, A.D., Collier, C.J., Flores, F., Mercurio, P., O’Brien, J., Ralph, P.J., Negri, A.P., 2015a. A miniature bioassay for testing the acute phytotoxicity of photosystem II herbicides on seagrass. PLoS ONE 10, e0117541. Wilkinson, A.D., Collier, C.J., Flores, F., Negri, A.P., 2015b. Acute and additive toxicity of ten photosystem-II herbicides to seagrass. Scientific Reports 5, 17443.

Chapter 6: Summary of research outcomes and conclusions

6.1 Objective, aims, and completion

Herbicides have been used for effective weed management since the 1940’s and 1950’s, but there are key knowledge gaps about their fate and persistence through unintentional release and their downstream environmental consequences. Perhaps this is because of their initial development and intended application/usage conditions, for which the soil environment received the greatest attention. When first interrogating the available literature on the topic of the degradation of herbicides in the marine environment (Chapter 1), I was surprised how little information there was available. Of the handful of published studies that listed half-lives for the marine environment, several key parameters such as experimental setup, low temperatures, high initial concentrations, and short duration (Chapter 2, Table 2.1) made their relevance to the natural environment and/or tropical marine environments questionable. Furthermore, there were no studies that had tested the potential for transformation (degradation) products of herbicides to contribute to toxicity in mixtures likely to be encountered by marine species. The shortcoming in relevant fate and toxicity data clearly needed to be addressed in order to better assess the risks posed by the herbicides detected in catchments and nearshore areas of the Great Barrier Reef. The overall objective of my thesis was therefore to determine half-lives, identify transformation products, and assess the toxicity of high priority herbicides in conditions relevant to tropical marine ecosystems. Keys aims that I sought to accomplish, were to: (I) identify the persistence of high priority herbicides in standard simulation experiments under different environmental conditions; (II) measure the persistence of herbicides under conditions relevant to nearshore marine waters both with and without natural sediments; and (III) determine whether transformation products contribute to the total toxicity of water samples containing herbicides. With this objective in mind, I will discuss how each experiment and chapter of the thesis met each of the specific aims listed above. Before commencing experimental work, standard techniques for determining testing persistence in water were reviewed including OCED methods (Chapters 1 and 2). It became clear that the standard methods were often biased in their approach by the addition of nutrients or through applying modified microbial inocula, often from wastewater treatment plants (OECD, 1992, 2005). Microorganism consortia from such sources are likely to be preconditioned to metabolising synthetic contaminants such as pesticides and herbicides as carbon sources or at the very least pre- exposed to complex mixtures of contaminants prior to the degradation experiment commencing

(Thouand et al., 2011). Very high concentrations (> 1 mg l-1) of herbicides were also often applied in previous studies which can potentially result in: (i) the development of unrealistic capacity in microbial communities to metabolise this dominant carbon source, (ii) increased lag times in degradation as microbial communities struggle to adapt to high herbicide concentrations, or (iii) toxicity towards some components of the native microbial communities (Mandelbaum et al., 2008). Overall, the standard OECD method (OECD, 2005) as often applied was not considered reflective of the natural marine environment where degradation from a spill or movement to the nearshore environment would take place. As such, my experiments were designed to better mimic these nearshore environments that would be exposed to herbicides during high rain events or during the monsoon season. A suite of herbicides regularly detected in the catchments and lagoon of the GBR (including six PSII herbicides and three non-PSII herbicides) were prioritised for testing in the series of persistence and toxicity studies. A preliminary experiment (Experiment 1) was conducted (Chapter 2) to trial the modifications to standard flask techniques, analytical techniques and pathways to degradation. The first experiment followed the standardised flask methods with the exceptions of (i) using a low starting concentrations of herbicides and (ii) relying on the natural microorganisms as collected (rather than an artificial inoculum). The experimental duration would be a maximum of 60 days as per the OECD method, and include the use of mercuric chloride to enable assessment of the degradation from those microbes versus hydrolysis (Fig. 6.1). The treatment with mercuric chloride revealed that microbial metabolism contributed more than hydrolysis to the degradation of PSII herbicides and that longer durations were required to more accurately estimate the half-lives of these compounds (Table 6.1). The next experiment (Experiment 2) was designed to improve: (i) the environmental relevance, (ii) half-life estimations and (iii) range of herbicides (Chapter 2). Experiment 2 (Fig. 2.1), addressed AIM I to measure persistence under standard simulation experiments by testing a wider range of herbicides, including the non-PSII herbicides 2,4-D and metolachlor under three sets of environmental conditions to examine the potential influence of relevant temperatures and light conditions on degradation rates. A limitation of the experiment in hindsight was not including a light 31°C treatment, but resources were unavailable at the time. Over the course of the 365 day experiment, Experiment 2 revealed that light and an increase in temperature could affect the degradation of individual herbicides under controlled conditions but the effects were highly dependent on each herbicide. Both Experiment 1 and Experiment 2 determined herbicide half-lives that were much longer than anticipated from the limited aquatic and marine data in the literature (Table 6.1). The longest half-lives in experiment 2 were calculated as multiple years (e.g. 1606 – 2089 d; hexazinone 1434 – 2799 d; tebuthiuron 2650 – 5214 d). A separate experiment was 99

conducted (Chapter 3) solely on the degradation of glyphosate which is one of the most widely used herbicides but is not part of regular monitoring programs, possibly due to the specialised analytical requirements and expense for that particular herbicide. Glyphosate’s half-life of 47 d in the light 25°C condition was the shortest half-life calculated from the flask experiments, Table 6.1. The long persistence of herbicides indicates that that either (i) natural microbial populations are capable of metabolising the herbicides or (ii) other sources of carbon are preferentially utilised (and cycled) in the flasksThe results indicated that little degradation of these herbicides would be expected during the wet season with runoff and associated flood plumes transporting a high proportion of the original herbicides in rivers into the GBR lagoon. The long persistence of herbicides identified here also helps explain detection of herbicides in nearshore waters of the GBR year round (Bentley et al., 2012; Shaw et al., 2010) and raises the possibility of accumulation of herbicides and metabolites in some locations. While further simulation experiments are needed to assess the wide variety of herbicides detected in marine systems (Davis et al., 2011; Smith et al., 2012), the results of which can be utilised in risk assessments for herbicides in the marine environment. One of the criticisms of the standard flask experiment with long term duration is the relatively small volume (usually less than a litre) and its associated pool of microorganisms. This community of microorganisms changes over time and may adapt to using the herbicide as a carbon source, however a “bottle effect” can occur where limited resources limit the dynamics of the microbial community. One or two dominant species which can utilise the herbicide as a carbon source can become the dominant species in this closed environment, which would not normally occur in the natural environment. There are also limitations to how laboratory-based fate studies reflect the natural environment. Building off the flask experiment design, the next degradation experiment was intended to represent more realistic experimental conditions to generate improved half-lives for use in risk assessments. Experiment 4 addressed Aim II to measure the persistence of herbicides under conditions relevant to nearshore marine waters both with and without natural sediments (Chapter 5). Here open tank tests were conducted with a larger volume of seawater (120 l versus 300 ml in the flask experiment), exposure to environmental temperatures, natural diurnal (shaded) sunlight, and the inclusion of nearshore sediments. The results from the open tank experiment overall were shorter half-lives for all herbicides in comparison with the flask tests in Chapter 3, the only exception was tebuthiuron. The results for the herbicide 2,4-D also confirmed the results from flask experiment 2 in that this herbicide degraded faster in the dark environment, opposing trends for the other herbicides. The light with sediment treatment in the open tank experiment had the shortest half- lives for each of the remaining herbicides. Sediments were analysed from day 60 and day 365, the 100

Prioritization of herbicides to test and review of standardised test methods and existing herbicide degradation information relevant to the marine environment (Chapter 1)

Pilot study (Experiment 1) to trial the Second and third standard flask degradation modifications to standard flask experiments, Experiments 2 and 3, improved: (i) the including analytical techniques and pathways environmental relevance, (ii) half-life to degradation. Conditions included: dark estimations and (iii) range of herbicides. treatment only, 25°C, 60 d duration (Chapter Conditions included: dark + light treatments, 2) 25°C and 31°C, 365 d duration (Chapters 3 and 4)

The large volume open system used in Experiment 4 allowed the assessment of persistence under more natural conditions: outdoor, dark + light treatments with coastal sediments over 365 d (Chapter 5)

The potential for transformation products to contribute to the total toxicity of water samples containing herbicides was tested following 330 d natural degradation in large open tanks with coastal sediments (Chapter 6).

Figure 6.1: Flow chart of thesis and experiments designed to fulfil objectives and aims.

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concentrations measured of herbicides associate with sediments were less than 1% of the total contained in each open tank. While the sediment bound herbicides could have herbicide transport implication for movement offshore during monsoon events, the fraction bound would be negligible. Whether or not the herbicides bound to sediment would be bioavailable or impact marine life would be the subject of another study in the future The presence of variable light: (i) significantly shortened the persistence of diuron, hexazinone and metolachlor; (ii) had no effect on atrazine; and (iii) increased the half-lives of tebuthiuron and, more dramatically 2,4-D. Photodegradation may have contributed in cases of more rapid degradation (by 19 – 41%); however, other studies have reported only minor contributions of hydrolysis and photodegradation of diuron (Moncada, 2004; Okamura, 2002) and hexazinone (Ganapathy, 1996). We previously showed how low light (40 µmol photons m-2s-1) can significantly affect degradation of PSII herbicides in seawater, most likely due to changes in microbial community structure affecting the biodegradation (Mercurio et al., 2015). In the cases of tebuthiuron and 2,4-D which exhibited (1.9 fold – 33-fold) longer persistence, the presence of light may have directly favoured bacteria less able to metabolise the herbicides (a direct effect) or may have changed the nature of other organic carbon in the system to form more appealing carbon sources (indirect effect). There was no effect of moderate light (this study) on the persistence of atrazine, supporting other studies which indicate biodegradation (and not photodegradation) as the primary degradation pathway (Fenner et al., 2013). The presence of coastal sediments increased degradation of all herbicides in the water column (apart from 2,4-D) in comparison with standard (dark, no sediment) treatments. The likely mechanism for increased degradation rates of 17 – 44% was due to differences in the microbial communities, including the possibility that coastal sediments in the tanks introduced a more natural, wider diversity, including more taxa capable of utilising the herbicides as a substrate. The most rapid degradation was observed for all herbicides (apart from 2,4-D) in the presence of both moderate light and coastal sediments (2 – 10- fold more rapid). The more rapid degradation is likely to be due to the combined effects of both light and sediments on microbial community composition as discussed above. Only the persistence of 2,4-D opposed this trend, being 5-fold more persistent than in the absence of light and sediment. This effect could also have been caused by the presence of different microbial communities, including the presence of more phototropic organisms, and is consistent with longer persistence in the presence of low light observed in our standard flask experiments (Mercurio et al., 2015). The same open tank system was employed in the final Experiment 5 to address Aim III: to test whether transformation products contribute to the total toxicity of water samples containing

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Table 6.1: Experimental half-lives (days ± SE). MC = mercuric chloride. SE = Standard Error. NS = not significant. – indicates herbicide not tested.

Expt. 1, 60 d Expt. 2, 365 d Herbicide Dark 25°C Dark 25°C + MC Dark, 25°C Light, 25°C Dark, 31°C Diuron NS NS 1568 ± 222 556 ± 14 818 ± 51 Atrazine 631 ± 491 NS 1606 ± 129 2089 ± 338 2066 ± 154 Hexazinone 479 ± 240 NS 2792 ± 172 2799 ± 46 1434 ± 114 Tebuthiuron 433 ± 150 NS 5214 ± 705 2650 ± 291 2840 ± 358 Ametryn 419 ± 264 NS - - - Simazine 579 ± 294 NS - - - Metolachlor - - 281 ± 1 320 ± 61 298 ± 12a 2,4-D - - 146 ± 19 494 ± 72 88 ± 6 Glyphosate - - 267 ± 21 47 ± 7 315 ± 29

Open tank Expt. 4, 365 d Dark no Light no Dark with Light with sediment sediment sediment sediment Diuron 499 ± 31 404 ± 16 279 ± 7 139 ± 6 Atrazine 300 ± 13 330 ± 32 201 ± 6 107 ± 7 Hexazinone 1994 ± 207 1186 ± 73 1025 ± 51 201 ± 18 Tebuthiuron 1766 ± 188 3330 ± 419 1474 ± 106 944 ± 52 Metolachlor 147 ± 13 93 ± 8 103 ± 5 32 ± 3 2,4-D 59 ± 15 1920 ± 417 56 ± 6 288 ± 12

herbicides (Chapter 6). For the toxicity experiment, it was important to continue working with herbicides that have similar modes of action and which also had a sensitive bioassay related to the mode of action such as PAM fluorometry (Magnusson et al., 2010; Muller et al., 2008), so PSII herbicides were selected from the previous experiments. As we were not testing degradation rates we applied higher starting concentrations in the open tank experiment, which allowed the production of degraded material high enough to generate full concentration response curves from the organisms used in the toxicity assays. The assays focussed on two species of microalgae (Symbiodinium sp. and Dunaliella sp.) as microalgae have been successfully utilised as model species in toxicity assays for herbicides, especially PSII herbicides which would affect photosynthetic yields through PAM assays. In a second experiment, I wanted to include an additional organism, one which would normally not be greatly affected by PSII herbicides, but could possibly be affected at a sensitive life stage event. Previous work has been performed on corals during spawning where survival, metamorphosis and larval settlement have been used as sensitive toxicity end points. I decided to trial early life stage metamorphosis using larval Penaeus monodon. The results of the microalgae assays indicated little contribution of toxicity from transformation products to overall mixture toxicity. The only exception to this was degraded diuron; however, separate toxicity assays indicated that the main transformation product 3,4-DCA was

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unlikely to be responsible and additional toxicity was possibly due to other transformation products. The other outcome of the toxicity experiments was the sensitivity of the prawn larvae to atrazine’s transformation products: DEA and DIA; however, further works should be performed to determine whether this result is consistent and what the mechanism of toxicity could be. Including transformation products as part of the risk assessment process is required to improve confidence in environmental risk assessments (Fenner et al., 2013). The toxicity experiments revealed relatively high toxicity of atrazine’s transformation products DIA and DEA to a non-phototropic organism, highlighting the need to consider harm to taxa that would not be normally considered sensitive to the parent contaminant. The potential for herbicide transformation products to contribute to toxicity in the environment identified the recommendation that the toxicity of emerging compounds and their transformation products to be assessed for their impact in the marine environment.

6.2 Summary and future directions

The overall aims of the experimental work were to generate persistence data for high priority herbicides found in tropical marine ecosystems and to test whether degradation products may contribute to toxicity of seawater samples containing both parent and degradation products. This data is valuable for spatial models for herbicide fate and to improve future risk assessments for herbicides in nearshore waters. The experiments indicated that: (i) in the presence of natural microbial communities persistence of PSII herbicides was longer than expected (Chapters 2, 3 and 4); (ii) environmental conditions including temperature, light and sediments has strong influences on degradation rates, probably due to differences in microbial communities (Chapters 3, 4) and (iii) some but not all degradation mixtures can be more toxic to phototrophic and non-phototrophic species than expected from the contributions of the parent herbicides (Chapter 5). While these experiments generated some of the most relevant data available on the persistence of high priority herbicides and insights into toxicity of transformation products, many questions remain. For example, variation between environmental conditions which led to large differences in persistence indicate that standard degradation tests (especially those using artificial microbial inocula or nutrient additions) are unlikely to provide relevant results for risk assessments and therefore it would be of great benefit to regulating agencies and resource managing bodies to adopt this type of independent approach before chemical registration and in risk assessment modelling. Additionally, any degradation experiment could be affected by the starting microbial community and in instances where sediments are included, the physio-chemical nature of those sediments. The work presented here provides far more relevant data on the fate/behaviour of herbicides in the marine environment than standardised methods often relied upon by regulators and

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industry. Additional improvements to future experiments could include the addition of radio- labelled compounds, detecting CO2 evolution, investigating co-metabolism when low concentrations of herbicides are used, and screening shifts in the microbial population over the course of the experiment. Future research on the toxicity of transformation products could benefit by the inclusion of additional species that would offer sensitivity to PSII herbicide such as green macro algae and seagrass. A novel technique using a plate design was developed recently which could offer the ability to screen a number of herbicides and transformation products (Wilkinson et al., 2015). Due to time constraints with this project, I was unable to pursue additional toxicology end points that were planned using metabolomics, something I hope to pursue in the future. Metabolomics has the potential ability to aid in developing sub-lethal stress responses to herbicides, degraded mixtures with transformation products, or unknown compounds (Aliferis and Jabaji, 2011; Keum et al., 2010; Veldhoen et al., 2012). There are number of herbicides which are currently in use within Australia as well as a multitude of emerging pesticides that have little or no published and relevant persistence and toxicity data (Davis et al., 2014; Davis et al., 2011; Lewis et al., 2009). The approach taken here to test naturally degrading herbicide samples for toxicity could provide a practical framework for future work on herbicides as transformation product standards can be difficult to obtain. In addition to the toxicity and degradation of the growing suite of emerging pesticides, there has been scant attention paid to the combined impacts of additives in commercial formulations and booster or wetting agents that may affect both toxicity and persistence of herbicides in the environment.

6.3 References

Aliferis, K.A., Jabaji, S., 2011. Metabolomics – A robust bioanalytical approach for the discovery of the modes-of-action of pesticides: A review. Pesticide Biochemistry and Physiology 100, 105-117. Bentley, C., Chue, K.L., Devlin, M., Mueller, J., Paxman, C., 2012. Pesticide monitoring in inshore waters of the Great Barrier Reef using both time-integrated and event monitoring techniques (2011 - 2012). University of Queensland, Coopers Plains, pp. 1-94. Davis, A.M., Lewis, S.E., Brodie, J.E., Benson, A., 2014. The potential benefits of herbicide regulation: A cautionary note for the Great Barrier Reef catchment area. Sci. Tot. Environ. 490, 81-92. Davis, A.M., Thorburn, P.J., Lewis, S.E., Bainbridge, Z.T., Attard, S.J., Milla, R., Brodie, J.E., 2011. Environmental impacts of irrigated sugarcane production: Herbicide run-off dynamics from farms and associated drainage systems. Agric. Ecosyst. Environ. Fenner, K., Canonica, S., Wackett, L.P., Elsner, M., 2013. Evaluating pesticide degradation in the environment: Blind spots and emerging opportunities. Science 341, 752-758. Ganapathy, C., 1996. Environmental fate of hexazinone. Environmental Monitoring & Pest Management Branch, Department of Pesticide Regulation Sacramento, CA, 1-15.

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Keum, Y.S., Kim, J.H., Li, Q.X., 2010. Chapter 22 - Metabolomics in pesticide toxicology, in: Krieger, R. (Ed.), Hayes' Handbook of Pesticide Toxicology (Third Edition). Academic Press, New York, pp. 627-643. Lewis, S.E., Brodie, J.E., Bainbridge, Z.T., Rohde, K.W., Davis, A.M., Masters, B.L., Maughan, M., Devlin, M.J., Mueller, J.F., Schaffelke, B., 2009. Herbicides: A new threat to the Great Barrier Reef. Environ. Pollut. 157, 2470-2484. Magnusson, M., Heimann, K., Quayle, P., Negri, A.P., 2010. Additive toxicity of herbicide mixtures and comparative sensitivity of tropical benthic microalgae. Mar. Pollut. Bull. 60, 1978-1987. Mandelbaum, R.T., Sadowsky, M.J., Wackett, L.P., 2008. Chapter 22 - Microbial degradation of s- triazine herbicides, in: LeBaron, H.M., McFarland, J.E., Burnside, O.C. (Eds.), The Triazine Herbicides. Elsevier, San Diego, pp. 301-328. Mercurio, P., Mueller, J.F., Eaglesham, G., Flores, F., Negri, A.P., 2015. Herbicide persistence in seawater simulation experiments. PLoS ONE 10, e0136391. Moncada, A., 2004. Environmental fate of diuron. Environmental Monitoring Branch, Department of Pesticide Regulation, Sacramento, CA, 1-11. Muller, R., Schreiber, U., Escher, B.I., Quayle, P.a., Bengtson Nash, S.M., Mueller, J.F., 2008. Rapid exposure assessment of PSII herbicides in surface water using a novel chlorophyll a fluorescence imaging assay. Sci. Tot. Environ. 401, 51-59. OECD, 1992. OECD guidelines for testing of chemicals—306 Biodegradability in seawater, pp. 1- 27; Accessed March 2015. OECD, 2005. OECD Guideline for testing of chemicals: Part 1: Principles and strategies related to the testing of degradation of organic chemicals. Accessed March 2015. Okamura, H., 2002. Photodegradation of the antifouling compounds Irgarol 1051 and diuron released from a commercial antifouling paint. Chemosphere 48, 43-50. Shaw, M., Furnas, M.J., Fabricius, K., Haynes, D., Carter, S., Eaglesham, G., Mueller, J.F., 2010. Monitoring pesticides in the Great Barrier Reef. Mar. Pollut. Bull. 60, 113-122. Smith, R., Middlebrook, R., Turner, R., Huggins, R., Vardy, S., Warne, M., 2012. Large-scale pesticide monitoring across Great Barrier Reef catchments – Paddock to Reef Integrated Monitoring, Modelling and Reporting Program. Mar. Pollut. Bull. 65, 117-127. Thouand, G., Durand, M.-J., Maul, A., Gancet, C., Blok, H., 2011. New concepts in the evaluation of biodegradation/persistence of chemical substances using a microbial inoculum. Frontiers in Microbiology 2, 164. Veldhoen, N., Ikonomou, M.G., Helbing, C.C., 2012. Molecular profiling of marine fauna: Integration of omics with environmental assessment of the world's oceans. Ecotoxicology and Environmental Safety 76, 23-38. Wilkinson, A.D., Collier, C.J., Flores, F., Negri, A.P., 2015. Acute and additive toxicity of ten photosystem-II herbicides to seagrass. Scientific Reports 5, 17443.

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Appendix

Appendix Table 1: Quantification and confirmation ions used for herbicide analysis. Q1: precursor mass, Q3: fragment mass (1 = quantifier, 2 = qualifier), Dwell: dwell time in milliseconds (MRM) or retention time of analyte (sMRM), DP: declustering potential, EP: entrance potential, CE: collision energy, CXP: collision cell exit potential. Compound 1 (e.g. Desisopropyl Atrazine 1) transitions used for quantitation 174.1/103, other compound designated 2 (Desisopropyl Atrazine 2) is for confirmation, 174.1/68.

Precursor Product Q1 Q3 Dwell Compound ID DP EP CE CXP Desisopropyl 174.1 104 30 70 10 34 10 Atrazine 1 Desisopropyl 174.1 68 30 70 10 38 11 Atrazine 2 188.1 146 30 Desethyl Atrazine 1 65 10 25 10 188.1 104 30 Desethyl Atrazine 2 65 10 38 10 202.1 132 30 Simazine 1 140 10 27 17 202.1 124 30 Simazine 2 140 10 25 17 253.1 171.1 30 Hexazinone 1 70 10 23 20 253.1 71 30 Hexazinone 2 70 10 43 11 229.1 172.1 30 Tebuthiuron 1 65 10 26 11 229.1 116 30 Tebuthiuron 2 65 10 38 10 162 127 30 3,4 Di Cl Analine 1 60 10 30 10 162 74 30 3,4 Di Cl Analine 2 60 10 70 10 216.1 174.1 30 Atrazine 1 70 10 25 10 216.1 96 30 Atrazine 2 70 10 35 11 221 179.1 30 D5 Atrazine 1 95 10 25 20 221 69 30 D5 Atrazine 2 95 10 50 10 228.1 186 30 Ametryn 1 100 10 25 20 228.1 68 30 Ametryn 2 100 10 57 11 235.1 72 30 Diuron 1 80 10 26 10 235.1 46 30 Diuron 2 80 10 35 10 284.19 252 30 Metolachlor 1 60 10 21 25 284.19 176 30 Metolachlor 2 60 10 35 20 219 161 50 24D 1 -70 -4 -17 -10 221 163 50 24D 2 -70 -4 -17 -10

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Appendix Table 2: Mean ± SE for each treatment for pH, dissolved oxygen (DO), and total bacterial counts for Experiment 1 and 2.

Herbicide Treatment Experiment Total bacterial counts pH ± SE DO (mg l-1) ± SE (x 106) ± SE Initial seawater used 1 0.94 ± 0.01 8.24 ± 0.01 6.4 ± 0.03 Control 1 0.94 ± 0.01 8.40 ± 0.02 6.35 ± 0.05 Herbicide mixture 1 0.91 ± 0.01 8.35 ± 0.03 6.02 ± 0.01 Herbicide mixture plus 1 0 8.42 ± 0.01 6.05 ± 0.08 mercuric chloride Initial seawater used 2 2.66 ± 0.4 8.20 ± 0.01 6.5 ± 0.07 Control D25 2 2.43 ± 0.01 8.21 ± 0.01 6.41 ± 0.07 Control L25 2 2.29 ± 0.02 8.22 ± 0.02 5.84 ± 0.04 Control D31 2 2.21 ± 0.01 8.24 ± 0.01 6.46 ± 0.33 Diuron D25 2 2.34 ± 0.02 8.25 ± 0.01 5.85 5 ± 0.15 Diuron L25 2 2.55 ± 0.02 8.24 ± 0.01 6.54 ± 0.05 Diuron D31 2 2.41 ± 0.03 8.31 ± 0.01 6.30 ± 0.14 Atrazine D25 2 2.40 ± 0.01 8.24 ± 0.01 5.52 ± 0.11 Atrazine L25 2 2.48 ± 0.01 8.23 ± 0.01 6.22 ± 0.40 Atrazine D31 2 2.44 ± 0.03 8.34 ± 0.01 5.30 ± 0.38 Hexazinone D25 2 2.33 ± 0.26 8.24 ± 0.01 5.79 ± 0.12 Hexazinone L25 2 2.85 ± 0.01 8.26 ± 0.01 5.89 ± 0.06 Hexazinone D31 2 2.43 ± 0.01 8.33 ± 0.01 6.14 ± 0.05 Tebuthiuron D25 2 2.33 ± 0.01 8.27 ± 0.01 6.15 ± 0.10 Tebuthiuron L25 2 2.61 ± 0.14 8.29 ± 0.04 6.55 ± 0.05 Tebuthiuron D31 2 2.44 ± 0.04 8.34 ± 0.01 6.40 ± 0.14 Metolachlor D25 2 2.29 ± 0.02 8.26 ± 0.02 6.31 ± 0.14 Metolachlor L25 2 2.64 ± 0.08 8.27 ± 0.01 6.70 ± 0.12 Metolachlor D31 2 2.46 ± 0.01 8.33 ± 0.01 6.30 ± 0.15 2,4-D D25 2 2.30 ± 0.01 8.24 ± 0.01 5.55 ± 0.12 2,4-D L25 2 3.01 ± 0.32 8.26 ± 0.01 6.41 ± 0.19 2,4-D D31 2 2.52 ± 0.03 8.31 ± 0.02 6.19 ± 0.10

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Appendix Table 3: Physical and chemical information for the 0.45 µm and 20 µm filtered seawater used in experiment 1 and experiment 2. NA = not applicable for 0.45 µm filtered seawater.

Parameter Mean experiment 1 Mean experiment 2 Units pH 8.2 8.2 POC NA 0.35 mg l-1 N NA 0.05 mg l-1 NPOC/DOC (TOC) 1.13 1.35 mg l-1 DIC NA 24.87 mg l-1 -1 NH4 0.63 0.23 µmol l -1 PO4 0.14 0.24 µmol l -1 NO2 + NO3 0.10 4.76 µmol l -1 NO2 0.01 0.01 µmol l Si 8.38 8.11 µmol l-1 TDP 0.31 0.31 µmol l-1 TDN 8.25 11.18 µmol l-1 Salinity 34 34 ‰

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Appendix Table 4: Results of Experiment 1 including first order half-life estimates, slopes, r2, average initial concentration, average final concentration, total average degradation. Additional results for Experiment 1 for zero order half-life estimates, r2, and the % difference between first order and zero order half-life estimates.

Treatment condition Atrazine Diuron Hexazinone Tebuthiuron Simazine Ametryn Initial concentration average (x) Dark 25°C 11.8 5.63 9.13 11 10.48 8.26 Dark 25°C + MC 11.62 8.99 9.04 10.28 9.72 8.04 Final concentrationaverage (x) Dark 25°C 10.77 5.19 8.18 9.81 9.68 7.23 Dark 25°C + MC 11.04 8.69 8.39 9.55 9.43 7.71 Total degradation (%) Dark 25°C 8.69 7.83 10.39 10.8 7.64 12.51 Dark 25°C + MC 4.94 3.34 7.2 7.14 2.97 4.19 Half-life (days), first order with SE Dark 25°C 631 ± 491 513 ± 284 479 ± 240 433 ± 150 579 ± 294 419 ± 264 Dark 25°C + MC 1216 ± 312 1743 ± 524 805 ± 181 712 ± 160 2267 ± 751 1221 ± 314 r2 from ln(x), first order Dark 25°C 0.26 0.36 0.38 0.48 0.35 0.3 Dark 25°C + MC 0.07 0.04 0.14 0.14 0.03 0.09 Half-life (days), zero order with SE Dark 25°C 480 ± 83 395 ± 58 366 ± 53 333 ± 42 440 ± 67 325 ± 53 Dark 25°C + MC 899 ± 234 1318 ± 389 606 ± 133 537 ± 115 1639 ± 525 894 ± 221 r2 from concentration (x) Dark 25°C 0.26 0.36 0.37 0.48 0.34 0.3 Dark 25°C + MC 0.08 0.05 0.14 0.15 0.03 0.1 Difference (%) between first order half-life and zero order half-life estimate Dark 25°C 24 23 24 23 24 22 Dark 25°C + MC 26 24 25 25 28 27

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Appendix Table 5: Results of Experiment 2 including first order half-life estimates, slopes, r2, average initial concentration (µg l-1), average final concentration, total average degradation. Additional results for Experiment 2 for zero order half-life estimates, r2, and the % difference between first order and zero order half-life estimates.

Treatment Condition Atrazine Diuron Hexazinone Tebuthiuron 2,4-D Metolachlor Initial concentration average (x) Dark, 25°C 10.52 8.55 9.68 11.37 17.26 5.03 Light, 25°C 10.08 8.23 9.24 11.05 17.31 4.26 Dark, 31°C 10.12 8.62 9.18 11.30 17.52 3.91 Final concentration average (x) Dark, 25°C 9.00 7.27 8.81 10.77 1.08 1.99 Light, 25°C 8.83 5.70 8.42 10.17 11.16 1.71 Dark, 31°C 8.87 6.38 7.72 10.37 0.36 1.74 Total degradation (%) Dark, 25°C 14.47 15.00 8.92 5.26 93.74 60.37 Light, 25°C 12.42 30.68 8.90 8.02 35.54 59.95 Dark, 31°C 12.38 25.97 15.91 8.17 97.92 55.43

Half-life (days), first order with SE Dark, 25°C 1606 ± 129 1568 ± 222 2792 ± 172 5214 ± 705 146 ± 19 281 ± 11 Light, 25°C 2089 ± 338 556 ± 142 2799 ± 467 2650 ± 291 494 ± 72 320 ± 61 Dark, 31°C 2066 ± 154 818 ± 51 1434 ± 114 2840 ± 358 88 ± 6 298 ± 12 r2 from ln(x), first order Dark, 25°C 0.88 0.70 0.92 0.72 0.76 0.94 Light, 25°C 0.65 0.51 0.63 0.79 0.78 0.62 Dark, 31°C 0.89 0.92 0.88 0.75 0.94 0.97 Half-life (days), zero order with SE Dark, 25°C 1257 ± 91 1226 ± 179 2113 ± 92 3873 ± 538 169 ± 12 310 ± 19 Light, 25°C 1628 ± 270 519 ± 95 2141 ± 304 2009 ± 222 449 ± 47 294 ± 37 Dark, 31°C 1596 ± 101 686 ± 44 1127 ± 84 2139 ± 246 157 ± 10 307 ± 15 r2 from concentration (x) Dark, 25°C 0.88 0.70 0.92 0.72 0.91 0.93 Light, 25°C 0.65 0.58 0.64 0.80 0.81 0.75 Dark, 31°C 0.89 0.92 0.89 0.75 0.92 0.96 Difference (%) between first order half-life and zero order half-life estimate Dark, 25°C 22 22 24 26 -16 -10 Light, 25°C 22 7 24 24 9 8 Dark, 31°C 23 16 21 25 -79 -3

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Appendix Table 6: Results of statistical testing of Experiment 1 and Experiment 2. Repeated measures ANOVA testing significance of degradation over time.

Experiment 1 DF F p Diuron 3,12 2.04 0.209746 Atrazine 3,12 11.58 0.006591 Hexazinone 3,12 12.02 0.006002 Tebuthiuron 3,12 34.2 0.003610 Ametryn 3,12 48.52 0.000134 Simazine 3,12 12.52 0.005418 Diuron + MC 3,12 2.55 0.151562 Atrazine + MC 3,12 4.01 0.069913 Hexazinone + MC 3,12 5.17 0.042153* Tebuthiuron + MC 3,12 15.01 0.003398* Ametryn + MC 3,12 1.44 0.320276 Simazine + MC 3,12 1.96 0.221648 Experiment 2 Dark 25°C Diuron 7,24 26.44 0.000000 Atrazine 7,24 13.3 0.000033 Hexazinone 7,24 41.43 0.000000 Tebuthiuron 7,24 11.31 0.000082 Metolachlor 7,24 76.12 0.000000 2,4-D 7,24 41.99 0.000000 Light 25°C Diuron 7,24 5.33 0.003879 Atrazine 7,24 18.25 0.000005 Hexazinone 7,24 16.77 0.000008 Tebuthiuron 7,24 13.13 0.000035 Metolachlor 7,24 18.88 0.000004 2,4-D 7,24 20.87 0.000002 Dark 31°C Diuron 7,24 49.97 0.000000 Atrazine 7,24 49.4 0.000000 Hexazinone 7,24 153.03 0.000000 Tebuthiuron 7,24 9.46 0.000221 Metolachlor 7,24 125.55 0.000000 2,4-D 7,24 477.19 0.000000 * Significantly different at 28 days but not at day 60

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Appendix Table 7: Results of statistical testing of Experiment 2. Two- tailed test for differences between slopes (k).

Experiment 2 DF F p Dark 25°C vs Light 25°C Diuron 1,44 8.99 0.0044 Atrazine 1,44 2.52 0.1193 Hexazinone 1,44 0.0001 0.9893 Tebuthiuron 1,44 14.80 0.0004 Metolachlor 1,44 0.39 0.5357 2,4-D 1,44 46.42 p<0.0001 Dark 25°C vs Dark 31°C Diuron 1,44 25.16 p<0.0001 Atrazine 1,44 5.08 0.0292 Hexazinone 1,44 32.87 p<0.0001 Tebuthiuron 1,44 10.06 0.0028 Metolachlor 1,44 0.71 0.4028 2,4-D 1,44 3.17 0.0818 Light 25°C vs Dark 31°C Diuron 1,44 2.25 0.141 Atrazine 1,44 0.004 0.9488 Hexazinone 1,44 18.12 0.0001 Tebuthiuron 1,44 0.18 0.6764 Metolachlor 1,44 0.92 0.3426 2,4-D 1,44 157.54 p<0.0001

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Appendix Table 8: Relevant literature on the degradation half-life experiments in freshwater.

Herbicide Half-life freshwater Water type/conditions specified Reference (days, unless otherwise specified) 2,4-D ~2 d (suggested) (Barbash, 2007; Mackay et al., 1997) 2,4-D 13 d pH 7 (PPDB, 2011) 2,4-D Stable 20°C and pH 7 (PPDB, 2011) Ametryn No value. States: “Slow pH 7 (PPDB, 2011) degradation in UV light” Ametryn Stable 20°C and pH 7 (PPDB, 2011) Ametryn 212 d 5-29°C and pH 7, natural light (Vencill, 2002) Atrazine 335 d 12-45°C and pH 7, natural light (Vencill, 2002) Atrazine ~2 years (suggested) Surface (Barbash, 2007; Mackay et al., 1997) Atrazine 2.6 d pH 7 (PPDB, 2011) Atrazine 86 d 20°C and pH 7 (PPDB, 2011) Atrazine Stable, 34–37 d of the 10°C and 20°C (Starner et al., 1999) experiment Atrazine 43 d 22°C (Konstantinou et al., 2001) Diuron ~3 weeks (suggested) (Barbash, 2007; Mackay et al., 1997) Diuron 43 d pH 7 (PPDB, 2011) Diuron Stable 20°C and pH 7 (PPDB, 2011) Diuron 33 d (DeLorenzo and Fulton, 2012; USEPA, 2003) Hexazinone Degraded ~20% in 56 d artificial sunlight (Vencill, 2002) Hexazinone 56 d pH 7 (PPDB, 2011) Hexazinone 56 d 20°C and pH 7 (PPDB, 2011) Glyphosate ~2 months (suggested) (Barbash, 2007; Mackay et al., 1997) Glyphosate 69 d pH 7 (PPDB, 2011) Glyphosate Stable 20°C and pH 7 (PPDB, 2011) Metolachlor >200 d pH 1-9 (Vencill, 2002) Metolachlor ~2 months (suggested) Surface (Barbash, 2007; Mackay et al., 1997) Metolachlor Stable pH 7 (PPDB, 2011) Metolachlor Stable 20°C and pH 7 (PPDB, 2011) Simazine ~3 weeks (suggested) Surface (Barbash, 2007; Mackay et al., 1997) Simazine 1.9 d pH 7 (PPDB, 2011) Simazine 96 d 20°C and pH 7 (PPDB, 2011) Simazine Stable, 34–37 days of the River water, 10°C and 20°C (Starner et al., 1999) experiment Tebuthiuron Stable pH 5,7, and 9 at 20°C (Vencill, 2002) Tebuthiuron No value pH 7 (PPDB, 2011) Tebuthiuron 64 d 20°C and pH 7 (PPDB, 2011)

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Appendix Table 9: Physical and chemical information for the 20 µm filtered seawater used in the glyphosate persistence experiment.

Parameter Mean Units pH 8.2 POC 0.35 mg l-1 N 0.05 mg l-1 NPOC/DOC 1.35 mg l-1 DIC 24.87 mg l-1 -1 NH4 0.23 µmol l -1 PO4 0.24 µmol l -1 NO2 + NO3 4.76 µmol l -1 NO2 0.01 µmol l Si 8.11 µmol l-1 TDP 0.31 µmol l-1 TDN 11.18 µmol l-1 Particle size (Mean) 4.34 μm

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Appendix Table 10: Glyphosate and AMPA concentrations (μg l-1) for each treatment: Dark 25°C, Dark 31°C, and Light 25°C during the course of the flask degradation experiment. All time points had 3 sample replicates analysed unless noted.

Time (days) Glyphosate SE AMPA SE Dark 25°C 0 10.37 0.17 NA NA 21 9.41 0.09 0.21 0.01 42 8.86 0.08 0.37 0.02 80 8.01 0.11 0.67 0.05 120 7.22 0.26 0.77 0.04 180 7.24 0.17 1.11 0.07 270 5.41 0.12 1.39 0.18 330* 4.23 0.61 1.42 0.12

Dark 31°C 0 10.48 0.48 NA NA 28 10.23 0.42 0.41 0.02 80 8.98 0.64 0.63 0.06 120 8.01 0.46 0.90 0.05 180 6.73 0.12 1.16 0.07 270 5.41 0.67 1.38 0.10 330 5.49 0.46 1.62 0.17

Light 25°C 0 9.94 0.29 NA NA 28 9.12 0.43 0.35 0.01 60 4.75 2.38 NA NA 80 2.75 1.42 NA NA 100 1.15 0.99 NA NA 120 0.38 0.38 NA NA 180 0.00 0.00 NA NA NA = Not applicable; * Samples for the Dark 25°C, time point 330 days only had 2 replicates as 1 was lost in transport.

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Appendix Table 11: The range of physical and chemical information for the seawater and sediment used in the open tank experiment.

Parameter Open tank experiment Units Temperature light treatment average 28°C (range 21-37°C ) °C Temperature dark treatment average 26°C (range 21-32°C) °C pH 8.2 - 8.3 N 0.03 - 0.04 mg l-1 NPOC/DOC 1.01 - 1.13 mg l-1 POC 0.31 - 0.33 mg l-1 TOC 1.32 - 1.46 mg l-1 DIC 25.8 - 26.1 mg l-1 -1 NH4 0.3 - 0.61 µmol l -1 PO4 0.14 - 0.20 µmol l -1 NO2 + NO3 1.25 - 1.32 µmol l -1 NO2 0.04 - 0.14 µmol l Si 7.41 - 8.57 µmol l-1 TDP 0.24 - 0.28 µmol l-1 TDN 9.55 - 9.70 µmol l-1 Salinity 33 - 34 ‰ Sediment TC 3.29 % Sediment TOC 0.06 % Sediment TN 0.009 % Sediment mean particle size 733.5 µm

Appendix Table 12: Recovery of analytes in sediment extraction using Agilent Quenchers. n = 3.

Average recovery ± Herbicide SE Diuron 101.7 ± 6.1 Atrazine 87.1 ± 13.2 Hexazinone 118.5 ± 6.7 Tebuthiuron 99.5 ± 6.0 Metolachlor 113.9 ± 12.1 2,4-D 96.3 ± 7.6

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Appendix Table 13: Repeated measures ANOVA testing significance of degradation over time.

Dark no sediment DF f-ratio p Diuron F3,40 62.21 p<0.0001 Atrazine F3,40 135.82 p<0.0001 Hexazinone F3,40 24.43 p<0.0001 Tebuthiuron F3,40 24.81 p<0.0001 Metolachlor F2,30 179.83 p<0.0001 2,4-D F2,30 154.73 p<0.0001

Light no sediment DF f-ratio p Diuron F3,40 248.57 p<0.0001 Atrazine F3,40 53.92 p<0.0001 Hexazinone F3,40 61.53 p<0.0001 Tebuthiuron F3,40 13.46 p<0.0001 Metolachlor F2,30 268.37 p<0.0001 2,4-D F2,30 11.58 p<0.0001

Dark with sediment DF f-ratio p Diuron F3,40 258.85 p<0.0001 Atrazine F3,40 368.82 p<0.0001 Hexazinone F3,40 75.97 p<0.0001 Tebuthiuron F3,40 42.21 p<0.0001 Metolachlor F2,30 415.42 p<0.0001 2,4-D F2,30 858.74 p<0.0001

Light with sediment DF f-ratio p Diuron F2,30* 994.57 p<0.0001 Atrazine F2,30* 296.14 p<0.0001 Hexazinone F2,30* 34.03 p<0.0001 Tebuthiuron F2,30* 87.02 p<0.0001 Metolachlor F2,30 328.3 p<0.0001 2,4-D F2,30 75.27 p<0.0001 * Lost replicate 4 for time point 120 d, Repeated ANOVA run with replicates 1-3 only.

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Appendix Table 14: Herbicide concentrations in sediments (µg kg-1). PSII herbicides n = 4; Non-PSII herbicides n = 3.

Herbicide Sediment Dark Sediment Light Time Average Average Diuron 60 1.77 ± 0.08 1.65 ± 0.12 Diuron 365 1.28 ± 0.09 0.57 ± 0.12 Atrazine 60 0.59 ± 0.06 0.55 ± 0.05 Atrazine 365 0.18 ± 0.02 0.03 ± 0.01 Desisopropyl Atrazine 60 0.01 ± 0.01 0.01 ± 0.01 Desisopropyl Atrazine 365 0.01 ± 0.00 0.01 ± 0.00 Desethyl Atrazine 60 0.03 ± 0.00 0.03 ± 0.00 Desethyl Atrazine 365 0.03 ± 0.00 0.01 ± 0.00 Hexazinone 60 1.91 ± 0.13 1.66 ± 0.05 Hexazinone 365 1.03 ± 0.19 1.12 ± 0.34 Tebuthiuron 60 1.87 ± 0.18 1.51 ± 0.08 Tebuthiuron 365 1.1 ± 0.21 1.54 ± 0.20 Metolachlor 60 0.67 ± 0.13 0.14 ± 0.03 Metolachlor 365 0.08 ± 0.01 BDL* 2,4-D 60 0.52 ± 0.01 1.36 ± 0.29 2,4-D 365 0.02 ± 0.0 0.46 ± 0.08 *BDL = Below detection limit

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Appendix Table 15: Results of statistical testing: Two- tailed test for differences between slopes (k).

DF F p Dark no sediment vs light no sediment Diuron 1,76 8.7593 0.004106 Atrazine 1,76 1.24927 0.2672 Hexazinone 1,76 22.017 p<0.0001 Tebuthiuron 1.76 14.3101 0.0003071 Metolachlor 1,35 10.4329 0.002693 2,4-D 1,37 59.6548 p<0.0001 Dark with sediment vs light with sediment Diuron 1,75 252.007 p<0.0001 Atrazine 1,75 130.569 p<0.0001 Hexazinone 1,75 63.3583 p<0.0001 Tebuthiuron 1,75 32.245 p<0.0001 Metolachlor 1,23 90.6487 p<0.0001 2,4-D 1,35 78.7164 p<0.0001 Dark no sediment vs dark with sediment Diuron 1,76 100.928 p<0.0001 Atrazine 1,76 63.2743 p<0.0001 Hexazinone 1,76 44.7124 p<0.0001 Tebuthiuron 1,76 2.13348 0.1482 Metolachlor 1,38 12.5437 0.001071 2,4-D 1,16 0.0334772 0.8571 Light no sediment vs light with sediment Diuron 1,75 395.61 p<0.0001 Atrazine 1,75 212.685 p<0.0001 Hexazinone 1,75 67.5164 p<0.0001 Tebuthiuron 1,75 162.894 p<0.0001 Metolachlor 1,20 55.9023 p<0.0001 2,4-D 1,56 189.969 p<0.0001 Dark no sediment vs light with sediment Diuron 1.75 430.615 p<0.0001 Atrazine 1,75 232.097 p<0.0001 Hexazinone 1,75 79.1258 p<0.0001 Tebuthiuron 1,75 42.4027 p<0.0001 Metolachlor 1,29 66.0661 p<0.0001 2,4-D 1,37 36.0735 p<0.0001 Dark with sediment vs light no sediment Diuron 1,76 66.5587 p<0.0001 Atrazine 1,76 47.5453 p<0.0001 Hexazinone 1,76 3.46509 0.06654 Tebuthiuron 1,76 38.3567 p<0.0001 Metolachlor 1,29 1.17974 0.2864 2,4-D 1,35 222.252 p<0.0001

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Appendix Table 16: Flow cytometry bacterial counts at Time 0 and Time 365. Control n = 4; PSII herbicides n = 4; Non-PSII mixture n = 3.

Total bacterial counts Treatment Day (x 106) ± SE Control dark no sediment 0 2.65 ± 0.01 Control dark with sediment 0 2.62 ± 0.01 Control light no sediment 0 2.56 ± 0.04 Control light with sediment 0 2.45 ± 0.01 Control dark no sediment 365 2.50 ± 0.01 Control dark with sediment 365 2.49 ± 0.01 Control light no sediment 365 2.58 ± 0.02 Control light with sediment 365 2.51 ± 0.01 PSII herbicides dark no sediment 365 2.31 ± 0.01 PSII herbicides dark with sediment 365 2.29 ± 0.02 PSII herbicides light no sediment 365 2.41 ± 0.07 PSII herbicides light with sediment 365 2.41 ± 0.01 Non-PSII mixture dark no sediment 365 2.22 ± 0.02 Non-PSII mixture dark with sediment 365 2.23 ± 0.01 Non-PSII mixture light no sediment 365 2.52 ± 0.1 Non-PSII mixture light with sediment 365 2.48 ± 0.01

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Appendix Table 17: Physical and chemical information for the seawater used in open tank.

Parameter Toxicity Units experiment pH 8.2 POC 0.35 mg l-1 N 0.04 mg l-1 NPOC/DOC (TOC) 1.44 mg l-1 DIC 26.0 mg l-1 -1 NH4 0.61 µmol l -1 PO4 0.2 µmol l -1 NO2 + NO3 1.32 µmol l -1 NO2 0.14 µmol l Si 8.57 µmol l-1 TDP 0.28 µmol l-1 TDN 9.55 µmol l-1 Salinity 34 ‰ Sediment TC 1.04 % Sediment TOC 0.46 % Sediment TN 0.02 % Sediment mean particle 218.5 µm size

Appendix Table 2: Transformation products measured in degraded herbicide samples. Bold indicates quantified against an analytical standard, other metabolites were quantified using response factors as indicated.

Herbicide Transformation products Diuron DMCPU DCPU 3,4 - dichloro aniline (3,4-DCA) Atrazine hydroxy atrazine desethyl atrazine (DEA) desisopropyl atrazine (DIA)

simazine amine (not positively confirmed, structure suggested Simazine hydroxy simazine desethyl simazine (DEA) from TripleTOF data)

ametryn desethyl (from ametryn desisopropyl (from ametryn response modified by ametryn response modified by relative response of the relative response of the equivalent atrazine metabolite equivalent atrazine metabolite to Ametryn hydroxy ametryn to atrazine) atrazine) hexazinone desmethyl (from hexazinone response modified by ratio of response of atrazine and hexazinone oxy (from hexazinone hydroxy (from Hexazinone desethyl atrazine) hexazinone response) hexazinone response)

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Appendix Table 19: ABSciex 5500 QTrap aquisition parameters. Q1: precursor mass, Q3: fragment mass (1 = quantifier, 2 = qualifier), Dwell: dwell time in milliseconds (MRM) or retention time of analyte (sMRM), DP: declustering potential, EP: entrance potential, CE: collision energy, CXP: collision cell exit potential. Note: Atrazine hydroxy and Ametryn hydroxy have the same structure as do their desethyl and desisopropyl forms. Desisopropyl atrazine and desethyl simazine also have the same structure.

Q1 Q3 Dwell/RT ID DP EP CE CXP 202.1 132 15 Simazine 1 70 10 27 14 202.1 124 15 Simazine 2 70 10 25 14 184.1 114 15 Simazine hydroxy 1 70 10 27 12 184.1 69 15 Simazine hydroxy 2 70 10 37 10 183.1 113 15 Simazine amine 1 70 10 27 12 183.1 68 15 Simazine amine 2 70 10 42 10 174.1 104 15 Simazine desethyl 1 70 10 32 10 174.1 96 15 Simazine desethyl 2 70 10 25 9 233.05 72 15 Diuron 1 70 10 40 12 233.05 46 15 Diuron 2 70 10 38 12 162 127 15 3,4-dichloroaniline 1 70 10 28 12 162 74 15 3,4-dichloroaniline 2 70 10 68 12 199.02 72 15 mCPDMU 1 60 10 32 10 199.01 46 15 mCPDMU 2 60 10 29 9 205.03 127 15 DCPU 1 60 10 38 13 205.01 162 15 DCPU 2 60 10 21 15 219.01 127 15 DCPMU 1 60 10 35 13 219.02 162 15 DCPMU 2 60 10 20 15 216.1 174 15 Atrazine 1 70 10 25 16 216.1 96 15 Atrazine 2 70 10 34 12 188.1 146 15 Desethyl Atrazine 1 70 10 24 17 188.1 104 15 Desethyl Atrazine 2 70 10 35 12 253.2 171 15 Hexazinone 1 70 10 22 16 253.2 71 15 Hexazinone 2 70 10 40 8 267.1 171 15 Hexazinone oxy 1 70 10 27 16 267.1 71 15 Hexazinone oxy 2 70 10 42 8 269.1 171 15 Hexazinone hydroxy 1 70 10 27 16 269.1 71 15 Hexazinone hydroxy 2 70 10 42 8 239.1 157 15 Hexazinone desmethyl 1 70 10 27 16 239.1 71 15 Hexazinone desmethyl 2 70 10 42 8 228.2 186 15 Ametryn 1 70 10 26 16 228.2 116 15 Ametryn 2 70 10 36 14 200.1 158 15 Ametryn desethyl 1 70 10 27 12 200.1 68 15 Ametryn desethyl 2 70 10 50 12 186.1 144 15 Ametryn desisopropyl 1 70 10 27 14 186.1 116 15 Ametryn desisopropyl 2 70 10 32 10 198.11 156 15 Ametryn hydroxy 1 70 10 25 14 198.11 86 15 Ametryn hydroxy 2 70 10 32 10 156.11 86 15 Ametryn hydroxy desisopropyl 1 70 10 22 10

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156.11 114 15 Ametryn hydroxy desisopropyl 2 70 10 22 12 170.11 128 15 Ametryn hydroxy desethyl 1 70 10 23 12 170.11 86 15 Ametryn hydroxy desethyl 2 70 10 21 10

Appendix Table 20: ABSciex 5600 TripleTOF acquisition parameters.

SWATH 5600+ TripleTOF ABSciex Total cycle time 0.82 seconds Collision Energy TOF Q2 Dwell (milliseconds) (milli volts) Collision Energy Spread (range 10-1000) 100 - 1000 50 no collision energy full scan 100 - 150.5 30 35 15 full scan 149.5 - 170.5 30 35 15 full scan 169.5 - 185.5 30 35 15 full scan 184.5 - 197.5 30 35 15 full scan 196.5 - 209.5 30 35 15 full scan 208.5 - 221.5 30 35 15 full scan 220.5 - 233.5 30 35 15 full scan 232.5 - 245.5 30 35 15 full scan 244.5 - 257.5 30 35 15 full scan 256.5 - 269.5 30 35 15 full scan 268.5 - 281.5 30 35 15 full scan 280.5 - 293.5 30 35 15 full scan 292.5 - 305.5 30 35 15 full scan 304.5 - 317.5 30 35 15 full scan 316.5 - 329.5 30 35 15 full scan 328.5 - 341.5 30 35 15 full scan 340.5 - 353.5 30 35 15 full scan 352.5 - 365.5 30 35 15 full scan 364.5 - 377.5 30 35 15 full scan 376.5 - 389.5 30 35 15 full scan 385.5 - 398.5 30 35 15 full scan 400.5 - 413.5 30 35 15 full scan 412.5 - 500.5 30 35 15 full scan 499.5 - 1000 30 35 15 full scan

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Appendix Table 3: Concentrations (µg l-1) of parent and transformation products in degraded solutions for all concentrations used in microalgae experiment.

Diuron 3,4-dichloroaniline DCPU DCPMU mCPDMU Degraded Diuron 0.10 BDL BDL BDL BDL Degraded Diuron 0.47 BDL 0.60 1.72 BDL Degraded Diuron 0.52 BDL 0.60 1.88 BDL Degraded Diuron 1.09 BDL 1.31 3.95 BDL Degraded Diuron 2.15 BDL 2.48 7.67 BDL Degraded Diuron 2.16 BDL 2.58 7.83 BDL Degraded Diuron 2.33 BDL 2.69 8.24 BDL Degraded Diuron 4.23 BDL 4.97 15.21 BDL Degraded Diuron 4.58 BDL 5.38 16.28 BDL Degraded Diuron 8.80 0.14 10.22 31.61 BDL Degraded Diuron 9.07 0.19 10.71 32.37 BDL Degraded Diuron 17.11 0.38 19.62 59.33 BDL Degraded Diuron 17.68 0.37 20.93 61.90 BDL Degraded Diuron 35.29 1.07 42.26 117.98 BDL

Desethyl Desisopropyl Atrazine Atrazine Atrazine Atrazine hydroxy Degraded Atrazine 1.26 0.14 BDL 0.12 Degraded Atrazine 2.47 0.28 BDL 0.23 Degraded Atrazine 4.94 0.53 BDL 0.45 Degraded Atrazine 8.01 0.85 0.12 0.74 Degraded Atrazine 9.80 1.06 0.16 0.87 Degraded Atrazine 16.14 1.72 0.25 1.44 Degraded Atrazine 16.37 1.82 0.27 1.52 Degraded Atrazine 19.49 2.10 0.34 1.78 Degraded Atrazine 25.10 2.77 0.43 2.32 Degraded Atrazine 32.60 3.58 0.50 3.01 Degraded Atrazine 40.06 4.43 0.66 3.69 Degraded Atrazine 47.55 5.48 0.80 4.48 Degraded Atrazine 61.59 7.17 1.09 5.90 Degraded Atrazine 71.51 8.53 1.29 7.22 Degraded Atrazine 139.00 18.12 2.55 14.94

Ametryn Ametryn Ametryn Ametryn hydroxy desethyl desisopropyl Degraded Ametryn 0.71 0.88 BDL BDL Degraded Ametryn 0.96 1.21 0.13 BDL Degraded Ametryn 1.34 1.74 0.19 BDL Degraded Ametryn 2.11 2.73 0.29 BDL Degraded Ametryn 2.12 2.81 0.30 BDL 125

Degraded Ametryn 2.69 3.53 0.37 BDL Degraded Ametryn 3.33 4.20 0.45 BDL Degraded Ametryn 4.10 5.56 0.58 BDL Degraded Ametryn 5.27 6.67 0.71 BDL Degraded Ametryn 6.05 8.48 0.88 BDL Degraded Ametryn 8.69 11.19 1.18 BDL Degraded Ametryn 10.73 13.24 1.41 BDL Degraded Ametryn 20.52 27.12 2.93 BDL Degraded Ametryn 37.69 52.86 5.98 BDL

Hexazinone Hexazinone Hexazinone Hexazinone oxy hydroxy desmethyl Degraded Hexazinone 0.89 BDL BDL 0.16 Degraded Hexazinone 2.22 0.10 BDL 0.38 Degraded Hexazinone 4.35 0.20 BDL 0.76 Degraded Hexazinone 8.41 0.39 BDL 1.46 Degraded Hexazinone 14.42 0.66 0.14 2.55 Degraded Hexazinone 32.36 1.57 0.32 6.06 Degraded Hexazinone 42.59 2.08 0.42 7.91 Degraded Hexazinone 51.27 2.60 0.55 10.17 Degraded Hexazinone 60.26 3.19 0.65 12.45 Degraded Hexazinone 72.06 3.96 0.79 14.99 Degraded Hexazinone 93.08 5.17 1.09 19.94 Degraded Hexazinone 106.62 6.65 1.34 23.91 Degraded Hexazinone 182.83 12.96 2.70 45.22 BDL = Below detection limit

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Appendix Table 22: One way ANOVA results for the effect of transformation products on microalgae ∆F/Fm’. NOEC = no significant observed effect concentration. LOEC = lowest significant observed effect concentration. Effects on ∆F/Fm’ were considered significant when p < 0.05.

Transformation product df F ratio p NOEC (µg l-1) LOEC (µg l-1) Symbiodinium sp. DIA 15,67 1.05 0.427 458.31 >458.31 DEA 15,67 133.04 0.000 55.63 83.68 3,4-DCA 15,67 0.79 0.684 273.41 >273.41 Dunaliella sp. DIA 15,67 5.51 0.000 148.97 458.31 DEA 15,67 65.37 0.000 33.30 55.63 3,4-DCA 15,67 1.04 0.433 273.41 >273.41

Appendix Table 23: One way ANOVA results for the effect of parent herbicides, transformation products and degraded herbicide mixtures on larval prawn metamorphosis. NOEC = no significant observed effect concentration. LOEC = lowest significant observed effect concentration. Effects on metamorphosis were considered significant when p < 0.05. Control test solutions included seawater control, solvent control, and degraded controls.

Herbicide df F ratio p NOEC (µg l-1) LOEC (µg l-1) Controls 2,35 1.47 0.2455 Diuron 6,47 0.53 0.7819 874 >874 Degraded Diuron 6,47 3.3 0.0096 34 71 Atrazine 6,47 3.97 0.0032 197 899 Degraded Atrazine 6,47 3.34 0.0090 143 278 Ametryn 6,47 0.57 0.7493 517 >517 Degraded Ametryn 6,47 0.9 0.5044 188 >188

Hexazinone 6,44 4.6 0.0013 242 1026 Degraded Hexazinone 6,46 3.7 0.0051 213 366 DIA 6,47 23.9 0.000 0 3.5 DEA 6,47 63.6 0.000 0 3.8 3,4-DCA 6,45 16.6 0.000 54 188 Copper (reference toxicant) 3,29 98.0 0.000 11 91

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Appendix Table 24: Herbicide and transformation products concentrations (µg l-1) used in the larval prawn experiment.

Herbicide Measured Diuron 3,4-dichloroaniline DCPU DCPMU mCPDMU Degraded Diuron 2.20 2.61 7.99 BDL Degraded Diuron 4.30 4.95 15.33 BDL Degraded Diuron 8.47 9.94 30.43 BDL Degraded Diuron 17.60 0.27 20.44 63.22 BDL Degraded Diuron 34.21 0.76 39.23 118.65 BDL Degraded Diuron 70.57 2.14 84.52 235.96 BDL

Desethyl Desisopropyl Atrazine Atrazine Atrazine Atrazine hydroxy Degraded Atrazine 9.87 1.06 0.90 Degraded Atrazine 19.60 2.11 0.32 1.74 Degraded Atrazine 38.98 4.21 0.67 3.55 Degraded Atrazine 80.12 8.85 1.32 7.38 Degraded Atrazine 143.02 17.06 2.58 14.43 Degraded Atrazine 277.99 36.25 5.10 29.88

Ametryn Ametryn Ametryn Ametryn hydroxy desethyl desisopropyl Degraded Ametryn 5.37 7.06 0.74 BDL Degraded Ametryn 10.54 13.34 1.43 BDL Degraded Ametryn 21.46 26.49 2.82 BDL Degraded Ametryn 41.03 54.24 5.87 BDL Degraded Ametryn 75.39 105.73 11.95 BDL Degraded Ametryn 188.56 188.37 23.43 BDL

Hexazinone Hexazinone Hexazinone Hexazinone oxy hydroxy desmethyl Degraded Hexazinone 16.82 0.77 2.92 Degraded Hexazinone 35.55 1.59 0.35 6.44 Degraded Hexazinone 64.72 3.14 0.64 12.13 Degraded Hexazinone 120.53 6.39 1.29 24.90 Degraded Hexazinone 213.25 13.29 2.68 47.81 Degraded Hexazinone 365.65 25.92 5.40 90.45

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