Data

Toxicity of eleven herbicides and one fungicide to the marine alga Tisochrysis lutea (Haptophyta) (NESP TWQ 3.1.5, AIMS)

eAtlas
Mueller, Jochen ; Elisei, Gabriele ; Kaserzon, Sarit ; van Dam, Joost ; Stapp, Laura ; Negri, Andrew ; Fisher, Rebecca
Viewed: [[ro.stat.viewed]] Cited: [[ro.stat.cited]] Accessed: [[ro.stat.accessed]]
ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=https://eatlas.org.au/data/uuid/91967f34-b24d-4352-b6b0-526e54ec052f&rft.title=Toxicity of eleven herbicides and one fungicide to the marine alga Tisochrysis lutea (Haptophyta) (NESP TWQ 3.1.5, AIMS)&rft.identifier=https://eatlas.org.au/data/uuid/91967f34-b24d-4352-b6b0-526e54ec052f&rft.description=This dataset shows the effects of herbicides and one fungicide (detected in Great Barrier Reef catchments) on the specific growth rates (from cell density data) of the microalgae Tisochrysis lutea during laboratory experiments conducted from 2018-2019. The aim of this project was to apply standard ecotoxicology protocols to determine the effects of Photosystem II (PSII), alternative herbicides and one fungicide on the growth of the marine microalgae Tisochrysis lutea. Growth bioassays were performed over 3-day exposures using pesticides that have been detected in the Great Barrier Reef catchment area (O'Brien et al., 2016). These toxicity data will enable improved assessment of the risks posed by PSII and alternative herbicides as well as the fungicide propiconazole to microalgae for both regulatory purposes and for comparison with other taxa. Methods: The haptophyte Tisochrysis lutea (formerly known as Isochrysis galbana)(Grant etal. 2017) (strain CS-177) was purchased from the Australian National Algae Supply Service, Hobart (CSIRO). Cultures of T. lutea were established in EDTA-free Guillard’s f/2 marine medium (Trenfield et al. 2015) (1 ml L-1 of f/2 medium in autoclaved natural seawater). Cultures were maintained in sterile 500 ml Erlenmeyer flasks as batch cultures in exponential growth phase with weekly aseptically transfers of 10 ml T. lutea suspension to 300 ml f/2 medium. Culture were maintained at 28 ± 1°C, 33 ± 1.5 psu and under a 12:12 h light:dark cycle (80 – 100 µmol photons m–2 s–1). Pesticide stock solutions were prepared using PESTANAL (Merck) analytical grade products (purity greater than or equal to 98%): diuron (CAS 330-54-1), metribuzin (CAS 21087-64-9), tebuthiuron (CAS 34014-18-1), bromacil (CAS 314-40-9), propazine (CAS 139-40-2), simazine (122-34-9), imazapic (CAS 104098-48-8), haloxyfop-p-methyl (CAS 72619-32-0), 2,4-D (CAS 94-75-7), MCPA (CAS 94-74-6), fluroxypyr (CAS 69377-81-7) and propiconazole (CAS 60207-90-1). The selection of pesticides was based on application rates and detection in coastal waters of the GBR (Grant et al. 2017, O’Brien et al. 2016). Pesticide stock solutions (100 – 1,000 mg L-1) were prepared by dissolving aliquots of the pure compounds in ultrapure water using clean, acid-washed (5% nitric acid) glass screw-top containers. Simazine, tebuthiuron and haloxyfop-p-methyl were dissolved using the carrier dimethyl sulfoxide (DMSO) (less than or equal to 0.02 % (v/v) in exposure solutions). Diuron, imazapic, metribuzin, bromacil, 2,4-D, propazine, MCPA, fluroxypyr and propiconazole were dissolved in acetone (less than or equal to 0.01 % (v/v) in exposure). Stock solutions were stored refrigerated and in the dark. Tests were conducted as previously described (Trenfield et al. 2015). Cultures of T. lutea were exposed to increasing concentrations of individual pesticides over a period of 72 h. Inoculum was taken from cultures in exponential growth phase (4-d old culture) and starting cell density assessed using a haemocytometer. For each treatment, a total volume of 250 mL test media was prepared in a clean, acid-washed 500 mL Schott bottle. Test media consisted of filtered (0.45 µm) seawater spiked with the respective pesticide stock, quarter strength EDTA-free f/2 media as nutrient source and T. lutea at a starting density of 3x103 or 1x104 cells mL-1. In each toxicity test, the response (specific growth rate of the culture) of the treatments exposed to pesticide were assessed against a seawater control group (no herbicide). For each test, 2 – 3 replicate 125 mL Erlenmeyer flasks (50 mL test volume) were assessed. Flasks were incubated at 27 – 29.0°C under a 12:12 h light:dark cycle (80 – 100 µmol photons m–2 s–1). After 72h, sub-samples (7 ml) were taken from each flask and cell densities measured using a flow cytometer (BD Accuri C6, BD Biosciences, CA, USA). Specific growth rates (SGR) were expressed as the logarithmic increase in cell density from day i (ti) to day j (tj) as per equation (1), where SGRi-j is the specific growth rate from time i to j; Xj is the cell density at day j and Xi is the cell density at day i (OECD 2011). SGR i-j = [(ln Xj - ln Xi )/(tj - ti )] (day-1) (1) Mean SGR for a pesticide treatment, relative to the mean control SGR was used to derive chronic effect values for growth inhibition. A test was considered valid, if the SGR of control replicates was greater than or equal to 0.92 day-1 4. Physical and chemical characteristics of each treatment were measured at 0 h and 72 h including pH, salinity, electrical conductivity and dissolved oxygen. Temperature was logged in 10-min intervals over the duration of the test. Sub-samples for chemical analysis were taken at 0 h and 72 h from each treatment. Format: The dataset is summarised in one file named ‘Tisochrysis lutea pesticide toxicity data_eAtlas.xlsx’ Data Dictionary: The excel spreadsheet has one tab for each pesticide which incl specific growth rate (SGR) data. The last tab of the dataset shows the measured (start and end of test) water quality (WQ) parameters (pH, salinity, dissolved oxygen (DO), and temperature) of each pesticide test. For each ‘pesticide’_SGR tab: SGR = specific growth rate - the logarithmic increase from day 0 to day 3 Nominal (µg/L) = nominal herbicide concentrations used in the bioassays Measured (µg/L) = measured concentrations analysed by The University of Queensland Rep = replicate notation is 1-3 Average T3_CellsPer_ml = cell density at day 3 Average ln(day3) = natural logarithm of cell density at day 3 T0_CellsPer_ml = average cell density at day 0 ln(day0) = natural logarithm of cell density at day 0 References: O’Brien, D. et al. Spatial and temporal variability in pesticide exposure downstream of a heavily irrigated cropping area: application of different monitoring techniques. J. Agric. Food Chem. 64, 3975-3989 (2016). Grant, S. et al. Marine Monitoring Program: Annual Report for inshore pesticide monitoring 2015-2016. Report for the Great Barrier Reef Marine Park Authority, Great Barrier Reef Marine Park Authority, Townsville, Australia. 128 pp, http://dspace-prod.gbrmpa.gov.au/jspui/handle/11017/13325 (2017). Trenfield, M. A. et al. Aluminium, gallium, and molybdenum toxicity to the tropical marine microalga Isochrysis galbana. Environ. Toxicol. Chem. 34, 1833-1840, doi:10.1002/etc.2996 (2015). OECD. Test No. 201: Freshwater Alga and Cyanobacteria, Growth Inhibition Test. (OECD Publishing, 2011). Data Location: This dataset is filed in the eAtlas enduring data repository at: data\nesp3\3.1.5_Pesticide-guidelines-GBR&rft.creator=Mueller, Jochen &rft.creator=Elisei, Gabriele &rft.creator=Kaserzon, Sarit &rft.creator=van Dam, Joost &rft.creator=Stapp, Laura &rft.creator=Negri, Andrew &rft.creator=Fisher, Rebecca &rft.date=2020&rft.coverage=130.86854374952014,-12.379103082919485 130.86667365388,-12.378911840243902 130.86483434840864,-12.378531450187523 130.86304598492165,-12.377966080383402 130.86132815710374,-12.377221925141413 130.8596996858359,-12.376307137582145 130.85817841299013,-12.375231740309474 130.85678100594998,-12.37400751560098 130.8555227749996,-12.372647876318808 130.85441750558044,-12.371167718955405 130.85347730725556,-12.369583260424577 130.8527124810346,-12.36791186038559 130.85213140651365,-12.366171831047026 130.8517404500668,-12.36438223653441 130.85154389509466,-12.362562684019792 130.85154389509466,-12.360733108901215 130.8517404500668,-12.358913556386554 130.85213140651365,-12.357123961873995 130.8527124810346,-12.355383932535418 130.85347730725556,-12.353712532496417 130.85441750558044,-12.352128073965588 130.8555227749996,-12.35064791660217 130.85678100594998,-12.34928827732 130.85817841299013,-12.348064052611534 130.8596996858359,-12.346988655338876 130.86132815710374,-12.346073867779566 130.86304598492165,-12.345329712537605 130.86483434840864,-12.344764342733455 130.86667365388,-12.344383952677092 130.86854374952014,-12.344192710001522 130.87042414616985,-12.344192710001522 130.87229424181004,-12.344383952677092 130.87413354728136,-12.344764342733455 130.87592191076834,-12.345329712537605 130.87763973858625,-12.346073867779566 130.8792682098541,-12.346988655338876 130.88078948269992,-12.348064052611534 130.88218688974,-12.34928827732 130.88344512069045,-12.35064791660217 130.8845503901096,-12.352128073965588 130.8854905884345,-12.353712532496417 130.8862554146555,-12.355383932535418 130.88683648917635,-12.357123961873995 130.88722744562324,-12.358913556386554 130.8874240005954,-12.360733108901215 130.8874240005954,-12.362562684019792 130.88722744562324,-12.36438223653441 130.88683648917635,-12.366171831047026 130.8862554146555,-12.36791186038559 130.8854905884345,-12.369583260424577 130.8845503901096,-12.371167718955405 130.88344512069045,-12.372647876318808 130.88218688974,-12.37400751560098 130.88078948269992,-12.375231740309474 130.8792682098541,-12.376307137582145 130.87763973858625,-12.377221925141413 130.87592191076834,-12.377966080383402 130.87413354728136,-12.378531450187523 130.87229424181004,-12.378911840243902 130.87042414616985,-12.379103082919485 130.86854374952014,-12.379103082919485&rft_rights=Creative Commons Attribution 3.0 Australia License http://creativecommons.org/licenses/by/3.0/au/&rft_subject=biota&rft.type=dataset&rft.language=English Access the data

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Full description

This dataset shows the effects of herbicides and one fungicide (detected in Great Barrier Reef catchments) on the specific growth rates (from cell density data) of the microalgae Tisochrysis lutea during laboratory experiments conducted from 2018-2019. The aim of this project was to apply standard ecotoxicology protocols to determine the effects of Photosystem II (PSII), alternative herbicides and one fungicide on the growth of the marine microalgae Tisochrysis lutea. Growth bioassays were performed over 3-day exposures using pesticides that have been detected in the Great Barrier Reef catchment area (O'Brien et al., 2016). These toxicity data will enable improved assessment of the risks posed by PSII and alternative herbicides as well as the fungicide propiconazole to microalgae for both regulatory purposes and for comparison with other taxa. Methods: The haptophyte Tisochrysis lutea (formerly known as Isochrysis galbana)(Grant etal. 2017) (strain CS-177) was purchased from the Australian National Algae Supply Service, Hobart (CSIRO). Cultures of T. lutea were established in EDTA-free Guillard’s f/2 marine medium (Trenfield et al. 2015) (1 ml L-1 of f/2 medium in autoclaved natural seawater). Cultures were maintained in sterile 500 ml Erlenmeyer flasks as batch cultures in exponential growth phase with weekly aseptically transfers of 10 ml T. lutea suspension to 300 ml f/2 medium. Culture were maintained at 28 ± 1°C, 33 ± 1.5 psu and under a 12:12 h light:dark cycle (80 – 100 µmol photons m–2 s–1). Pesticide stock solutions were prepared using PESTANAL (Merck) analytical grade products (purity greater than or equal to 98%): diuron (CAS 330-54-1), metribuzin (CAS 21087-64-9), tebuthiuron (CAS 34014-18-1), bromacil (CAS 314-40-9), propazine (CAS 139-40-2), simazine (122-34-9), imazapic (CAS 104098-48-8), haloxyfop-p-methyl (CAS 72619-32-0), 2,4-D (CAS 94-75-7), MCPA (CAS 94-74-6), fluroxypyr (CAS 69377-81-7) and propiconazole (CAS 60207-90-1). The selection of pesticides was based on application rates and detection in coastal waters of the GBR (Grant et al. 2017, O’Brien et al. 2016). Pesticide stock solutions (100 – 1,000 mg L-1) were prepared by dissolving aliquots of the pure compounds in ultrapure water using clean, acid-washed (5% nitric acid) glass screw-top containers. Simazine, tebuthiuron and haloxyfop-p-methyl were dissolved using the carrier dimethyl sulfoxide (DMSO) (less than or equal to 0.02 % (v/v) in exposure solutions). Diuron, imazapic, metribuzin, bromacil, 2,4-D, propazine, MCPA, fluroxypyr and propiconazole were dissolved in acetone (less than or equal to 0.01 % (v/v) in exposure). Stock solutions were stored refrigerated and in the dark. Tests were conducted as previously described (Trenfield et al. 2015). Cultures of T. lutea were exposed to increasing concentrations of individual pesticides over a period of 72 h. Inoculum was taken from cultures in exponential growth phase (4-d old culture) and starting cell density assessed using a haemocytometer. For each treatment, a total volume of 250 mL test media was prepared in a clean, acid-washed 500 mL Schott bottle. Test media consisted of filtered (0.45 µm) seawater spiked with the respective pesticide stock, quarter strength EDTA-free f/2 media as nutrient source and T. lutea at a starting density of 3x103 or 1x104 cells mL-1. In each toxicity test, the response (specific growth rate of the culture) of the treatments exposed to pesticide were assessed against a seawater control group (no herbicide). For each test, 2 – 3 replicate 125 mL Erlenmeyer flasks (50 mL test volume) were assessed. Flasks were incubated at 27 – 29.0°C under a 12:12 h light:dark cycle (80 – 100 µmol photons m–2 s–1). After 72h, sub-samples (7 ml) were taken from each flask and cell densities measured using a flow cytometer (BD Accuri C6, BD Biosciences, CA, USA). Specific growth rates (SGR) were expressed as the logarithmic increase in cell density from day i (ti) to day j (tj) as per equation (1), where SGRi-j is the specific growth rate from time i to j; Xj is the cell density at day j and Xi is the cell density at day i (OECD 2011). SGR i-j = [(ln Xj - ln Xi )/(tj - ti )] (day-1) (1) Mean SGR for a pesticide treatment, relative to the mean control SGR was used to derive chronic effect values for growth inhibition. A test was considered valid, if the SGR of control replicates was greater than or equal to 0.92 day-1 4. Physical and chemical characteristics of each treatment were measured at 0 h and 72 h including pH, salinity, electrical conductivity and dissolved oxygen. Temperature was logged in 10-min intervals over the duration of the test. Sub-samples for chemical analysis were taken at 0 h and 72 h from each treatment. Format: The dataset is summarised in one file named ‘Tisochrysis lutea pesticide toxicity data_eAtlas.xlsx’ Data Dictionary: The excel spreadsheet has one tab for each pesticide which incl specific growth rate (SGR) data. The last tab of the dataset shows the measured (start and end of test) water quality (WQ) parameters (pH, salinity, dissolved oxygen (DO), and temperature) of each pesticide test. For each ‘pesticide’_SGR tab: SGR = specific growth rate - the logarithmic increase from day 0 to day 3 Nominal (µg/L) = nominal herbicide concentrations used in the bioassays Measured (µg/L) = measured concentrations analysed by The University of Queensland Rep = replicate notation is 1-3 Average T3_CellsPer_ml = cell density at day 3 Average ln(day3) = natural logarithm of cell density at day 3 T0_CellsPer_ml = average cell density at day 0 ln(day0) = natural logarithm of cell density at day 0 References: O’Brien, D. et al. Spatial and temporal variability in pesticide exposure downstream of a heavily irrigated cropping area: application of different monitoring techniques. J. Agric. Food Chem. 64, 3975-3989 (2016). Grant, S. et al. Marine Monitoring Program: Annual Report for inshore pesticide monitoring 2015-2016. Report for the Great Barrier Reef Marine Park Authority, Great Barrier Reef Marine Park Authority, Townsville, Australia. 128 pp, http://dspace-prod.gbrmpa.gov.au/jspui/handle/11017/13325 (2017). Trenfield, M. A. et al. Aluminium, gallium, and molybdenum toxicity to the tropical marine microalga Isochrysis galbana. Environ. Toxicol. Chem. 34, 1833-1840, doi:10.1002/etc.2996 (2015). OECD. Test No. 201: Freshwater Alga and Cyanobacteria, Growth Inhibition Test. (OECD Publishing, 2011). Data Location: This dataset is filed in the eAtlas enduring data repository at: data
esp3\3.1.5_Pesticide-guidelines-GBR

Issued: 20 03 2020

Data time period: 2018-01-28 to 2019-11-30

This dataset is part of a larger collection

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130.86948394785,-12.361647896461

Subjects
biota |

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Other Information
NESP TWQ Project page

url : https://nesptropical.edu.au/index.php/round-3-projects/project-3-1-5/

eAtlas Web Mapping Service (WMS) (AIMS)

url : https://eatlas.org.au/data/uuid/71127e4d-9f14-4c57-9845-1dce0b541d8d

Project web site

url : https://eatlas.org.au/nesp-twq-3/pesticide-guidelines-gbr-3-1-5

Excel File + Photo + Metadata [Zip 1.51 MB]

url : https://nextcloud.eatlas.org.au/apps/sharealias/a/au-nesp-twq-3-5-1-aims-pesticide-guidelines-tisochrysis-lutea-2020-02-27

global : bb4ae8d4-cbe3-4116-becf-c93832cf5b6c

ror : 03x57gn41

ror : 03x57gn41

ror : 03x57gn41

ror : 03x57gn41

ror : 03x57gn41

NESP TWQ Project 3.1.5 - Ecotoxicology of pesticides on the Great Barrier Reef for guideline development and risk assessments, 2017-2019 (AIMS)

raid : 10.82210/a611d299

Identifiers
  • global : 91967f34-b24d-4352-b6b0-526e54ec052f
ACN 633 798 857