|dc.description.abstract||Metal contamination is a major environmental concern especially in metal mining countries like Canada. The assessment and cleanup of soils with elevated metal concentrations is an area that has been widely studied. A major challenge faced by environmental scientists when assessing metal toxicity in soils is the wide difference in toxic effects between laboratory spiked soils and field contaminated soils. Also, since contamination occur as mixtures, researchers are faced with understanding metal mixture interactions in soil to help quantify risks associated with metal mixture contamination. When assessing the toxic effects of metals in a laboratory setting, it is recommended to use fixed ratio rays, but maintaining desired metal ratios in soils is challenging because of metal loss from leaching metal salt-spiked soils. To eliminate leaching, which is a required step, two alternative metal types (metal oxides and spinel minerals) were evaluated. The main objectives of the thesis were to investigate the differences in toxicity of three metal types found in contaminated soils and to test the adherence of mixture toxicity to additivity models using the activity of soil enzymes as model toxicity endpoints. I also extended our understanding of the effects of metal mixtures on the quality of ecosystem services using soil properties as predictors.
First, the toxicity of metal salts, metal oxides and spinel minerals were assessed using acid phosphatases (ACP) and ammonia monooxygenases (AMO) as model processes in three Canadian soils. The activity of both enzymes in the soils were determined in leached and non-leached soils, as well as soils spiked with mixtures containing Pb, Cu, Ni, Co, and Zn in five fixed ratio rays. The results showed that the activity of AMO was inhibited when soils were leached with artificial rainwater. Generally, metal salts were the most toxic, while the spinel minerals were the least toxic. Two extractants, CaCl2 and Diethylenetriamine Pentaacetic Acid (DTPA), were evaluated for their ability to link toxicity to metals across all three metal forms. Salt toxicity was closely linked to CaCl2 extractable concentrations but DTPA was the most appropriate for oxides. I determined that combining fixed ratio rays with metal oxides for metal mixture studies was more appropriate for conducting mixture studies since soil ratios created using oxides were more precise and required less experimental effort compared to salts and spinel minerals.
Following the investigation into the differences in toxicity of metal mixture types, I evaluated the adherence of metal mixture toxicity to the concentration addition (CA) and response addition (RA) models. I assessed mixture toxicity using metal oxides (Cu, Co, Pb, Zn, and Ni) in two Canadian soils. The additivity models were used because current risk assessment is conducted assuming metals are non-interactive and have similar modes of action. I investigated the sensitivity of the carbon (C) and phosphorus (P) cycles to the mixtures using two soil enzymes, beta glucosidases (BGD) and ACP as model processes. In general, P cycling (ACP) was a more sensitive enzyme to both single and metal mixtures compared to C cycling (BGD). Upon exposure to quinary mixtures, both synergistic and antagonistic deviations from both reference models were observed. The antagonistic deviations were observed across all concentrations, thus from low to high, but synergism was only observed at lower concentrations for both additivity models. The results indicate that, the effects of metal mixtures are greater than singles at lower concentrations which is important in the risk assessment of metal mixtures. I also observed that Cu, an essential metal, may be protecting biogeochemical cycles from mixture toxicity.
In the third chapter, I developed adverse ecosystem service pathway (AESP) models to study the soil ecosystem’s response to a metal mixture containing Cu, Pb, Zn, Co, and Ni. I assessed the effects using the relationships between soil properties and ecosystem services (ES) in the presence and absence of the metal mixtures. Forty-seven (47) soils were sampled and 15 soil processes that represented five ES including food production and water purification were measured. Using a Pearson bivariate correlation matrix, I confirmed that ecosystem services were closely linked to soil properties, especially cation exchange capacity and organic carbon. Results from t-tests also showed that, except for the three soil enzyme activities measured (p < 0.05), the processes underlying ecosystem services are significantly reduced in metal-impacted soils. Using soil properties as the main predictors of ecosystem services, I built two AESP models: one for metal-impacted soils and another for control soils. These models showed adverse effects to ecosystem services in metal-impacted soils, depicted as changes in partial correlation coefficients. An AESP model, therefore, can be an important tool to better understand complex ecosystems and improve site specific risk assessment and natural resource management.||