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Improving the dosing method and analysis of metal mixture dose response in soil

dc.contributor.advisorSiciliano, Steven D
dc.contributor.committeeMemberPeak, Derek
dc.contributor.committeeMemberAdl, Sina
dc.contributor.committeeMemberPrager, Sean
dc.creatorCousins, Mark Joseph 1991-
dc.creator.orcid0000-0003-1714-8362 2019
dc.description.abstractExamination of a stressor’s toxic effects on terrestrial organisms is a relatively new field compared to human health and aquatic toxicity, and the toxicity of multiple stressors on terrestrial organisms is newer still. Dose-response functions and statistical analyses have crossed over from aquatic toxicity research, however the effect of soil properties on soil toxicity is still being researched extensively. Being home to about 3.5 million contaminated sites (Swartjes, 2011), the European Union has a large incentive to research the effect of stressors in soil. Smolders et al. (2009) used this research to develop the basis for the EU REACH PNEC calculator. The calculator uses pH, eCEC, clay content, and background metal concentrations to estimate the Predicted No Effect Concentration (PNEC) of a stressor in soil: the upper concentration where there should be no significant effect on a soil ecosystem. The calculator is limited to estimating the PNEC of single stressors, and combinations of are assumed to follow Concentration Addition. Rather than delving into the chemical and biological complexities of how stressors in soil interact with one another and test organisms, Jonker et al. (2005) developed a statistics based tool to evaluate mixture toxicity. Their method uses the concepts of Concentration Addition and the sigmoid dose-response function paired with a deviation parameter. The deviation parameter changes depending on whether a user wants to test perfect Concentration Addition, synergistic or antagonistic effects, dose-ratio dependent deviation, or dose-level deviation. The methods in Jonker et al. (2005) were adapted to analyse binary mixture behaviour using a Microsoft Excel spreadsheet. While this worksheet may work well for small mixtures, it has not been used for larger combinations of stressors. To improve the results found using the Jonker et al. (2005) methods, I created scripts using the optim() function in R (R Development Core Team, 2008). The scripts will evaluate toxicity data for mixtures of up to five stressors for any of the four types of deviation from Concentration Addition. Rather than using an iterative method as developed in the Excel spreadsheet, the R scripts use the uniroot.all() function in the rootSolve R package (Soetaert, iii 2009). The uniroot.all() function simultaneously evaluates all data points to make the Jonker et al. (2005) equations valid. The optim() function then changes the individual stressors’ dose response curves to minimize the differences between the predicted response and the observed response. Using synthetic data with varying data point spread and starting parameters, the R script produced lower sum of square values than the Excel sheet when modified to evaluate mixtures of five stressors. In addition to finding a lower sum of squares, the annotated R scripts offer a solution to researchers examining the effects of mixtures larger than binary without needing to develop the tools themselves and reduces the “black box” of custom Visual Basic for Applications (VBA) functions if they are not familiar with that language. Prior to analyzing mixture toxicity data, one must ensure that one’s data is useful. In some cases, a stressor may be applied directly to a test medium and a researcher can observe its effect on an organism. In the case of metal effects on soil organisms, however, a problem may occur. The standard application of metal salts to a soil and subsequent leaching can remove a different proportion of each stressor from the test medium. Dosing strategies that require specific combinations of metals, such as fixed-ratio rays, can pose a challenge to a researcher. To find an alternative to metal salts, five soils were dosed with five different metal mixtures in three different ways. Metals were applied as aqueous nitrate salts and leached, as dry powdered commercially available metal oxides, and as spinel-like minerals. The spinel-like minerals were made by mixing aqueous nitrate salts, adding iron nitrate in a 2:1 molar ratio of iron to all other metals, precipitated, and annealed in a muffle furnace to remove nitrates. The minerals were intended to resemble franklinite, which is commonly found in contaminated smelter sites. Folsomia candida, an extensively studied and easy to culture hard-bodied soil invertebrate, was used as a response organism. The spinel-like minerals and oxides were both more effective at retaining the relative proportions of each metal to one another. In some cases, over 60% of total metal nitrates added to soils was removed during leaching in addition to losing different amounts of each metal. Even though the metal concentrations were lower in nitrate dosed soils, the average reproduction was similar to the oxide dosed soils, where the spinel dosed soils showed no effect on reproduction. The research here shows that, with some more research, dosing soils using metal oxides is a promising alternative to aqueous nitrate dose method.
dc.subjectmixture toxicity
dc.subjectsoil invertebrates
dc.subjectconcentration addition
dc.titleImproving the dosing method and analysis of metal mixture dose response in soil
local.embargo.terms2020-08-27 Science Science of Saskatchewan of Science (M.Sc.)


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