Effects of herbicide exposure on growth and photosynthetic efficiency of the aquatic fern Azolla pinnata (Pteridophyta) (NESP TWQ 3.1.5, AIMS and JCU)

Brief description

This dataset shows the effects of herbicides (detected in the Great Barrier Reef catchments) on growth rates (from surface area and biomass) and photosynthesis (effective quantum yield) on the aquatic fern Azolla pinnata during laboratory experiments conducted in 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 aquatic fern Azolla pinnata. Growth bioassays were performed over 14-day exposures using herbicides that have been detected in the Great Barrier Reef catchment area (O’Brien et al. 2016). Chronic effects of herbicides on the photophysiology of A. pinnata, measured by chlorophyll fluorescence as the effective quantum yield (Delta F/Fm’) were investigated using PAM fluorometry after 14-day herbicide exposure. These toxicity data will enable improved assessment of the risks posed by PSII and alternative herbicides to aquatic macrophytes for both regulatory purposes and for comparison with other taxa.

Methods:
The aquatic fern Azolla pinnata was sourced from Watergarden Paradise Nursery, NSW. Cultures were established in IRRI2 medium (Pereira & Carrapiço 2009). Cultures were maintained in 10 L tubs containing 3–5 L IRRI2 as batch cultures with weekly transfers to fresh medium. Clean culture solutions were maintained at 26 ± 1 °C, under a 12:12 hr light:dark cycle (65-77µmol photons m–2 s–1).

Herbicide stock solutions were prepared using PESTANAL (Sigma-Aldrich) analytical grade products (HPLC greater than or equal to 98%): diuron (CAS 330-54-1), fluometuron (CAS 2164-17-2), fluroxypyr (CAS 69377-81-7), haloxyfop-p-methyl (CAS 72619-32-0), imazapic (CAS 104098-48-8), isoxaflutole (CAS 141112-29-0) and triclopyr (CAS 5535-06-3). 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 100 mL glass volumetric flasks using milli-Q water. Diuron, haloxyfop-p-methyl and isoxaflutole were dissolved using analytical grade acetone (< 0.01% (v/v) in exposures). Imazapic was dissolved in methanol (less than 0.01% (v/v) in exposure). No solvent carrier was used for the preparation of the remaining herbicide stock solutions.

Cultures of A. pinnata were exposed to a range of herbicide concentrations over a period of 14 days. Fronds were selected from actively growing cultures free of overt disease or deformity. Four triplicate fronds each comprising eight ramets were added to 100 mL of each herbicide solution concentration and control treatment. In each toxicity test, control (no herbicide) and solvent control (if used) treatments were added to support the validity of the test protocols and to monitor continued performance of the assays. Experiments were conducted in IRRI2 medium (Pereira & Carrapiço 2009) with solutions replaced at Day 7. Three replicates of each treatment solution and control were prepared and incubated at 26.6 ± 0.5 °C under a 12:12 h light:dark cycle (90 ± 6 µmol photons m–2 s–1). Each replicate treatment was photographed at a standard height to estimate surface area at Day 0 and Day 14. Biomass of a representative numbers of fronds were weighed to 4 significant figures using an analytical balance after blotting for 15 seconds to remove excess moisture. Fronds from each treatment replicate were weighed at Day 14 using the same technique. Specific growth rates (SGR) were expressed as the logarithmic increase in surface area or biomass 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 surface area or biomass at day j and Xi is the surface area or biomass at day i (OECD 2006).

SGR i-j = [(ln Xj - ln Xi )/(tj - ti )] (day-1)

SGR relative to the control / solvent control treatment was used to derive chronic effect values for growth inhibition. A test was considered valid, if the SGR for frond number or surface area of control replicates was greater than or equal to 0.0.0495 day-1 (OECD 2014). Physical and chemical characteristics of each treatment were measured at 0, 7 and 14 days on new and old treatment solutions for pH, electrical conductivity and temperature. Temperature was also logged in 15-min intervals over the total test duration. Analytical samples were taken at 0 and 14 days.

Chronic effects of herbicides on the photophysiology of A. pinnata, measured by chlorophyll fluorescence as the effective quantum yield (Delta F/Fm’), were investigated at 14 days using PAM fluorometry (mini-PAM, Walz, Germany). 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’

Mini- PAM settings were set to ETR-F = 0.84, F-Offset = 46, measuring light frequency = 3, measuring intensity = 4, gain = 2; damp = 3. Saturation pulse settings: intensity = 6, width = 0.6.
Mean percent inhibition in SGR and Delta F/Fm’ of each treatment relative to the control treatment was calculated as per equation (3)(OECD 2006), 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


Format:
Azolla pinnata herbicide toxicity data_eAtlas.xlsx

Data Dictionary:

There are two or three tabs for each herbicide in the spreadsheet. The first tab corresponds to the specific growth rate – surface area (SGR-SA) data; the second tab is biomass (SGR-B) data; and the pulse amplitude modulation (PAM) fluorometry data. The last tab of the dataset shows the measured water quality (WQ) parameters (pH, electrical conductivity and temperature) of each herbicide test. Where value equals '-', measurement not taken.
Diu – Diuron
Fluo - Fluometuron
Flur - Fluroxypyr
Halo – Haloxyfop
Imaz - Imazapic
Isox - Isoxaflutole
Tri – Triclopyr


For each ‘herbicide’_SGR tab:
SGR = specific growth rate - the logarithmic increase from day 0 to day 14 as either surface area (SA) (mm2) or biomass (B) (g)
Nominal (µg/L) = nominal herbicide concentrations used in the bioassays; SC denotes solvent control which is no herbicide and contains less than 0.01% v/v solvent carrier as per the treatments
Measured (µg/L) = measured concentrations analysed by The University of Queensland
Rep = replicate notation is 1-3
T14_Growth = surface area (mm2) or biomass (g) at day 14
ln(day14) = natural logarithm of surface area (mm2) or biomass (g) at day 14
Average T0_Growth = surface area (mm2) or biomass (g) at day 0
ln(day0) = natural logarithm of surface area (mm2) or biomass (g) at day 0


For each ‘herbicide’_PAM tab:
PAM = pulse amplitude modulation 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 0.01% v/v solvent carrier as per the treatments;
Measured (µg/L) = measured concentrations analysed by The University of Queensland
notation is 1-3; for PAM data, notation is 1-3
Delta F/Fm' = effective quantum (light adapted) yield measured by a Pulse Amplitude Modulation (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.gov.au/jspui/handle/11017/13325

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 (2006) Current approaches in the statistical analysis of ecotoxicity data. OECD Publishing.
OECD (2014) Test No. 238: Sediment-Free Myriophyllum Spicatum Toxicity Test, OECD Guidelines for the Testing of Chemicals, Section 2, OECD Publishing, Paris.

Pereira, A.L., and Carrapiço, F. (2009) Culture of Azolla filiculoides in artificial conditions. Plant Biosystems, 143(3), 431-434

Rueden, C.T., Schindelin, J., Hiner, M.C. et al. (2017) ImageJ2: ImageJ for the next generation of scientific image data. BMC Bioinformatics 18:529, PMID 29187165, doi:10.1186/s12859-017-1934-z


Data Location:

This dataset is filed in the eAtlas enduring data repository at: data\nesp3\3.1.5_Pesticide-guidelines-GBR