Bibliographic record
Abstract
Metal contamination from anthropogenic activities is of great concern due to the associated detrimental effects on ecosystem health. An increase in metal concentrations in the dissolved phase creates greater ecosystem impacts. Thus, the relative extent of metal distribution between sediment and dissolved compartments, and an understanding of the factors that control this partitioning is key to assessing metal impacts. In this thesis, metal concentrations were determined for a suite of 12 metals (Cr, Mn, Co, Cu, Sn, Ag, As, Ni, Zn, Cd, Se and Fe) associated with three compartments, dissolved, surficial bed sediment and suspended particulate matter (SPM) in Hamilton Harbour, Ontario. Due to highly dynamic interactions of anthropogenic impacts that may work together to affect metal distributions as well as processes that occur over small or rapid scales, a high-resolution temporal and spatial scale was used to evaluate these metal distributions over a seasonal timeframe. Concentrations of metals amongst sediment fractions indicated that sediment metal uptake was largely controlled by the concentration of the sediment associated amorphous and crystalline oxyhydroxide fractions accounting for up to 90% of total sediment bound metal, even though the oxyhydroxides only accounted for a maximum of 23% of the total sediment mass for both surficial bed sediment and SPM compartments. The formation and dissolution of amorphous oxyhydroxides is commonly a microbially mediated process. Thus, these results underscore the important role of oxyhydroxides and the microbial processes that contribute to their formation and dissolution m controlling metal dynamics, and likely metal impacts in Hamilton Harbour. Metal partitioning was found to be both spatially and temporally variable for all compartments, temporally ranging 0.5 to 4 orders of magnitude for a given element; indicating highly dynamic metal exchanges between sediment and solution compartments and fluctuating distributions over the time and spatial scales examined. The suite of variables that are considered to control metal distribution between dissolved and sediment compartments, and thus impact metal toxicity (i.e., temperature, pH, specific conductivity, oxidation-reduction potential, dissolved organic carbon concentration, SPM concentration (for SPM associated metals only), fraction concentrations i.e. g carbonate /g solid, g amorphous oxyhydroxide I g solid, etc., and dissolved metal concentrations) did not constrain the variability in observed metal distribution behaviour, indicating that other factors in this system, such as hydrodynamic disturbances associated with shipping traffic and channelized water currents, as well as specific point source metal discharges, may play a larger role in determining metal partitioning in Hamilton Harbour, compared to less anthropogenically, impacted systems. Furthermore, no one master variable defming metal partitioning between the dissolved and sediment compartments was found, rather relationships controlling metal distribution behavior were site, compartment, sediment fraction and element specific highlighting the challenges for the development of a Harbour-wide management plan for priority metal contaminants. The results presented in this thesis, show that it is necessary to consider metal, site and compartment specific conditions as well as fully addressing temporal variability in metal behaviour. In addition, the results of this thesis point to the need to address hydrodynamic disturbance and point source influences on metal behaviour in Hamilton Harbour and likely extend to other multi-impacted metal contaminated systems.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".