Effects of herbicide exposure on growth and photosynthetic efficiency of the microalgae Rhodomonas salina (Cryptophyceae) (NESP 3.1.5, AIMS and JCU)

This dataset shows the effects of herbicides (detected in the Great Barrier Reef catchments) on the growth rates (from cell density data) and photosynthesis (effective quantum yield) on the microalgae Rhodomonas salina during laboratory experiments conducted from 2018-2019. The aims of this project were to develop and apply standard ecotoxicology protocols to determine the effects of Photosystem II (PSII) and alternative herbicides on the growth and photosynthetic efficiency of the microalgae Rhodomonas salina. Growth bioassays were performed over 3-day exposures using herbicides that have been detected in the Great Barrier Reef catchment area(O’Brien et al. 2016). Acute effects of herbicides on the photophysiology of R. salina, measured by chlorophyll fluorescence as the effective quantum yield (Delta F/Fm') were investigated in 48-well plates using imaging PAM fluorometry after 24 h herbicide exposure(Mercurio et al. 2018, Schreiber et al. 2002). These toxicity data will enable improved assessment of the risks posed by PSII and alternative herbicides to microalgae for both regulatory purposes and for comparison with other taxa. Methods: The cryptophyte Rhodomonas salina (Wislouch)(Hill and Wetherbee 1989) (Cryptophyceae) (CS-24/01) was purchased from the Australian National Algae Supply Service, Hobart (CSIRO). Cultures of R. salina were established in Guillard’s f2 marine medium(Guillard and Ryther 1962) (0.5 ml l-1 of AlgaBoost F/2, AusAqua in 0.2 µm-filtered seawater (FSW)). Cultures were maintained in sterile 500 ml Erlenmeyer flasks as batch cultures in exponential growth phase with twice weekly transfers of 70 ml of a 3- to 4- day-old R. salina suspension to 350 ml f2 medium under sterile conditions. Clean culture solutions were aerated and maintained at 26 ± 1°C, 35 psu and under a 12:12 h light:dark cycle (90-100 µmol photons m–2 s–1, Osram Lumilux Cool White 36 W). Herbicide stock solutions were prepared using PESTANAL (Sigma-Aldrich) analytical grade products (HPLC greater than or equal to 98%): diuron (CAS 330-54-1), metribuzin (CAS 21087-64-9), hexazinone (CAS 51235-04-2), 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), and 2,4-D (CAS 94-75-7). The selection of herbicides was based on application rates and detection in coastal waters of the GBR(Grant et al. 2017, O’Brien et al. 2016). Stock solutions were prepared in sterile 1 l glass Schott bottles using milli-Q water or FSW. Diuron and simazine were dissolved using HPLC-grade ethanol (< 0.001% (v/v) in exposures). Haloxyfop-p-methyl was dissolved in dimethyl sulfoxide (DMSO) (less than or equal to 0.006% (v/v) in exposure). No solvent carrier was used for the preparation of the remaining herbicide stock solutions. Cultures of R. salina were exposed to a range of herbicide concentrations over a period of 72 h. Inoculum was taken from cultures in exponential growth phase (4-day-old with cell density approximately 1x106 cell ml-1). Individual R. salina working suspensions (3x103 cells ml-1) for each herbicide treatment were prepared in 100 ml Schott bottles and dosed with a series of herbicide concentrations. In each toxicity test, a control (no herbicide) and reference (4 µg l-1 diuron) treatments were added to support the validity of the test protocols and to monitor continued performance of the assays. Replicates (n = 5) of 10 ml of each treatment were transferred into sterile 20 ml scintillation vials and incubated at 26.0 ± 0.6 °C under a 12:12 h light:dark cycle (90-100 µmol photons m–2 s–1, Osram Lumilux Cool White 36 W). Sub-samples (0.5 ml) were taken from each replicate to measure cell densities of algal populations at 0 h and 72 h 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) SGR relative to the control treatment 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 (OECD 2011). Physical and chemical characteristics of each treatment were measured at 0 h and 72 h including pH, salinity and dissolved oxygen. Temperature was logged in 10-min intervals over the total test duration. Analytical samples were taken at 0 h and 72 h. Acute effects of herbicides on the photophysiology of R. salina, measured by chlorophyll fluorescence as the effective quantum yield (Delta F/Fm'), were investigated in 48-well plates using imaging PAM fluorometry (I-PAM, Walz, Germany)(Mercurio et al. 2018, Schreiber et al. 2002) following a single 12:12 h light:dark cycle (90-100 µmol photons m–2 s–1). Light adapted minimum fluorescence (F) and maximum fluorescence (Fm') were determined and effective quantum yield was calculated for each treatment as per equation (2)(Schreiber et al. 2002). Delta F/Fm’ = (Fm’-F)/Fm’ (2) Imaging PAM settings were set to actinic light = 1 (corresponding to photosynthetically active radiation (PAR) of 90-100 µmol photons m-2 s-1), measuring intensity = 11, gain = 3; damp = 2. Mean percent inhibition in SGR and Delta F/Fm' of each treatment relative to the control treatment was calculated as per equation (3)(OECD 2011), where Xcontrol is the average SGR or Delta F/Fm' of control and Xtreatment is the average SGR or Delta F/Fm' of single treatments. % Inhibition = [(X control - X treatment )/X control] x 100 (3) Format: Rhodomonas salina herbicide toxicity data_eAtlas.xlsx Data Dictionary: There are two tabs for each herbicide in the spreadsheet. The first tab corresponds to the specific growth rate (SGR) data; the second tab is the pulse amplitude modulation (PAM) fluorometry data. The last tab of the dataset shows the measured water quality (WQ) parameters (pH, salinity, dissolved oxygen (DO), and temperature) of each herbicide test. Diu – Diuron Met – Metribuzin Hexa – Hexazinone Imaz – Imazapic Teb – Tebuthiuron Sim – Simazine Halo – Haloxyfop Brom – Bromacil Prop – Propazine For each ‘herbicide’_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; SC denotes solvent control which is no herbicide and contains less than 0.006% v/v solvent carrier as per the treatments; D4 denotes diuron reference at 4 µg/L Measured (µg/L) = measured concentrations analysed by The University of Queensland Rep = Replicate: for SGR, notation is 1-5; for PAM data, notation is 1-5 T3_CellsPerMl = cell density at day 3 ln(day3) = natural logarithm of cell density at day 3 Average T0_CellsPerMl = average cell density at day 0 ln(Day0) = natural logarithm of cell density at day 0 For each ‘herbicide’_PAM tab: PAM = pulse amplitude modulated fluorometry to calculate effective quantum yield (light adapted) Nominal (µg/L) = nominal herbicide concentrations used in the bioassays; SC denotes solvent control which is no herbicide and contains less than 0.006% v/v solvent carrier as per the treatments; D4 denotes diuron reference at 4 µg/L Measured (µg/L) = measured concentrations analysed by The University of Queensland Rep = Replicate: for SGR, notation is 1-5; for PAM data, notation is 1-5 Delta F/Fm' = effective quantum (light adapted) yield measured by a Pulse Amplitude Modulated (PAM) fluorometer References: Grant, S., Gallen, C., Thompson, K., Paxman, C., Tracey, D. and Mueller, J. (2017) 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.go...017/13325 Guillard, R.R. and Ryther, J.H. (1962) Studies of marine planktonic diatoms: I. Cyclotella nana Hustedt, and Detonula confervacea (Cleve) Gran. Canadian Journal of Microbiology 8(2), 229-239. Hill, D.R. and Wetherbee, R. (1989) A reappraisal of the genus Rhodomonas (Cryptophyceae). Phycologia 28(2), 143-158. Mercurio, P., Eaglesham, G., Parks, S., Kenway, M., Beltran, V., Flores, F., Mueller, J.F. and Negri, A.P. (2018) Contribution of transformation products towards the total herbicide toxicity to tropical marine organisms. Scientific Reports 8(1), 4808. O’Brien, D., Lewis, S., Davis, A., Gallen, C., Smith, R., Turner, R., Warne, M., Turner, S., Caswell, S. and Mueller, J.F. (2016) Spatial and temporal variability in pesticide exposure downstream of a heavily irrigated cropping area: application of different monitoring techniques. Journal of Agricultural and Food Chemistry 64(20), 3975-3989. OECD (2011) OECD guidelines for the testing of chemicals: freshwater alga and cyanobacteria, growth inhibition test, Test No. 201. https://search.oecd.org/env/...23-en.htm (accessed 28 August 2019). Schreiber, U., Müller, J.F., Haugg, A. and Gademann, R. (2002) New type of dual-channel PAM chlorophyll fluorometer for highly sensitive water toxicity biotests. Photosynthesis Research 74(3), 317-330. Data Location: This dataset is filed in the eAtlas enduring data repository at: data\nesp3\3.1.5_Pesticide-guidelines-GBR

Co Investigator
Negri, Andrew, Dr Australian Institute of Marine Science (AIMS)
Principal Investigator
Thomas, Marie Australian Institute of Marine Science (AIMS)
Co Investigator
Flores, Florita Australian Institute of Marine Science (AIMS)
Co Investigator
Mueller, Jochen The University of Queensland, Queensland Alliance for Environmental Health Science (QAEHS)
Co Investigator
Elisei, Gabriele The University of Queensland, Queensland Alliance for Environmental Health Science (QAEHS)
Co Investigator
Sarit, Kaserzon The University of Queensland, Queensland Alliance for Environmental Health Science (QAEHS)
Point Of Contact
Negri, Andrew, Dr Australian Institute of Marine Science (AIMS) a.negri@aims.gov.au

Data collected from 28 Aug 2018 until 15 Dec 2019


Data Usage Constraints
  • Attribution 3.0 Australia