Evaluating Nutrient Loading from Agricultural Sources and the Biogeochemical Cycling Capacity of Environments Connected to Agricultural Lands in Southwestern Ontario
Bibliographic record
Abstract
Southwestern Ontario is dominated by agricultural lands that are extensively tile drained throughout the region as a management practice to remove excess water from fields. While tile drainage is a common practice, the implementation of constructed preferential flow paths, along with surface runoff from agricultural lands, increases nutrient loading risks to connected and downstream environments, and receiving large lakes. Of particular concern in this region is Lake Erie which has a legacy of severely degraded water quality due to excess nutrient loading from agricultural lands within the lake’s drainage basin. While agricultural lands are a known source for nutrient loading, there is a lack of understanding on the role of microbial functional communities in environments connected to these lands, and how they respond to both nutrient inputs and agricultural management practices.\nThis thesis investigates how sustained agricultural management practices alter microbial nutrient cycling communities in receiving aquatic and sediment environments, and the temporal patterns in both nutrient loading and microbial nutrient cycling communities. Results indicate that fertilization practices and agricultural management practices (e.g. tillage), increase nutrient loads to receiving environments. Nitrogen fertilization in particular drives patterns in nitrogen and phosphorus limited conditions in receiving aquatic environments, and phosphorus limited conditions of both aquatic and sediment environments determines patterns in phosphorus mobilization potentials. Finally, nutrient loads and microbial nutrient cycling capacity in aquatic environments increase during precipitation events and in the non-growing season, but decline significantly with increasing distance from agricultural sources and through areas of natural filtration. In contrast sediment environments are more resilient to agricultural inputs and abiotic factors. This research provides insight into temporal patterns of nutrient loading and how nutrient cycling microbial communities respond in receiving aquatic and sediment environments in agriculturally dominated locations of the southwestern Ontario region.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".