Toxicity of the insecticide imidacloprid and the fungicide propiconazole to the marine barnacle Amphibalanus amphitrite (Arthropoda/Crustacea) (NESP 3.1.5, AIMS)

This dataset shows the effects of of the insecticide imidacloprid and the fungicide propiconazole on larval development of the acorn barnacle Amphibalanus amphitrite experiments conducted in 2018 and 2019. The aim of this project was to apply standard ecotoxicology protocols to determine the effects of the insecticide imidacloprid and the fungicide propiconazole on larval development rate of the acorn barnacle Amphibalanus Amphitrite. Larval development bioassays(4-d exposures) were conducted using a fungicide and insecticide 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 pesticides to marine crustaceans for both regulatory purposes and for comparison with other taxa. Methods: Pesticide stock solutions were prepared using PESTANAL (Merck) analytical grade products (purity greater than or equal to 98%): imidacloprid (CAS 138261-41-3) and propiconazole (CAS 60207-90-1). This selection was based on application rates and detection in coastal waters of the GBR (O’Brien et al., 2016; Grant 2017). 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. Acetone was used to dissolve the imidacloprid and propiconazole (less than or equal to 0.01 % (v/v) in exposure solutions). Stock solutions were stored refrigerated and in the dark. Broodstock barnacles had been grown for several generations in the AIMS-NT aquaria facility (originally sourced from Darwin Harbour – 12°26'57.48"S, 130°51'7.51"E). Broodstock were fed freshly hatched brine shrimp (Artemia salina) and live rotifers daily. Broodstock were spawned as previously described (van Dam et al., 2016) and nauplii collected. Tests were conducted as previously described (van Dam et al., 2016). Nauplii were exposed in a custom-designed experimental test system that allowed for constant movement of the exposure media. The system consisted of a series of silanized glass funnels in which nauplii were exposed to increasing concentrations of imidacloprid or propiconazole and tested against control nauplii. Generally, a total of 24 funnels were used for 7 treatment concentrations and a control group, thus allowing for 3 replicate funnels per treatment. Each treatment vessel contained 100 mL exposure media, 50 newly released stage II nauplii and 1 x 107 cells of rinsed Chaetoceros muelleri. Every 24 h, 1 x 107 cells of rinsed C. muelleri were added to each funnel. After 96 h exposure, funnel contents were drained over a 150 µm nitrile mesh. The mesh was examined under a stereomicroscope and the number of cyprids and settled larvae scored. Quality control criteria (> 70% survival in control group) for test acceptability were met for each test used to derive toxicity estimates. Treatment effects were quantified by the percentage successful transition to cyprid in treatment groups relative to controls. Following prescribed statistical procedures (OECD 2006) the R package DRC (R-project 2015, Ritz & Streibig 2005), was used to model the test data and calculate toxicity estimates. Regression models evaluated included log-logistic and Weibull models of different levels of parametrisation. Model comparisons were conducted using the Akaike Information Criterion (AIC) and models that best described the data were applied to approximate pesticide concentrations eliciting 10 and 50% inhibition of successful transition relative to control animals (EC10 and EC50, respectively). The associated 95% confidence limits were estimated using the delta method. Format: The dataset is summarised in one file named ‘Amphibalanus amphitrite pesticide toxicity data_eAtlas.xlsx’ Data Dictionary: The excel spreadsheet has one tab for each pesticide. 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’_Development tab: 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 No. of nauplii larvae at start = number of larvae per replicate at start of test No. of cyprid larvae day 4 = number of cyprids observed per replicate at end of test 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.go...017/13325 (2017). van Dam, J. W. et al. A novel bioassay using the barnacle Amphibalanus amphitrite to evaluate chronic effects of aluminium, gallium and molybdenum in tropical marine receiving environments. Mar Pollut Bull 112, 427-435, doi:http://dx.doi.org/10.1016/j....16.07.015 (2016). OECD. Current Approaches in the Statistical Analysis of Ecotoxicity Data., (OECD Publishing, 2006). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/. (2015). Ritz, C. & Streibig, J. C. Bioassay analysis using R. Journal of Statistical Software 12, 1-22 (2005). Data Location: This dataset is filed in the eAtlas enduring data repository at: data\nesp3\3.1.5_Pesticide-guidelines-GBR

Principal Investigator
van Dam, Joost, Dr Australian Institute of Marine Science (AIMS)
Co Investigator
Negri, Andrew, Dr Australian Institute of Marine Science (AIMS)
Co Investigator
Fisher, Rebecca, Dr 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
van Dam, Joost, Dr Australian Institute of Marine Science (AIMS) j.vandam@aims.gov.au

Data collected from 27 Jul 2017 until 25 Oct 2019


Data Usage Constraints
  • Attribution 3.0 Australia