Biogeochemical Processes and Microbial Dynamics Governing Phosphorus Retention and Release in Sediments: A Case Study in Lower Great Lakes Headwaters
Bibliographic record
Abstract
The ability of headwater bed and suspended sediments to mitigate non-point agricultural phosphorus (P) loads to the lower Great Lakes is recognized, but the specific biogeochemical processes promoting sediment P retention or internal P release remain poorly understood. To elucidate these mechanisms, three headwater segments located within priority watersheds of Southern Ontario, Canada, were sampled through the growing season of 2018-2020. The study employed equilibrium P assays along with novel assessments of legacy watershed nutrients, nitrogen (N) concentrations, sediment redox, and microbial community composition. 20-year data revealed elevated total P (TP) and total Nitrogen (TN) at an inorganic fertilizer and manure fertilizer-impacted site, respectively. Overall, sampled sites acted as P sinks; however, agricultural sediments exhibited significantly lower buffering capacity compared to a reference forested watershed. Collection of fine suspended sediment (<63 µm) through time-integrated sampling showed the suspended load at the inorganic-fertilized site was saturated with P, indicating a greater potential for P release into surface waters compared to bed sediments. Through vertical microsensor profiling and DNA sequencing of the sediment microbial community, site-specific factors associated with a distinct P-source event were identified. These included rapid depletion of dissolved oxygen (DO) across the sediment water interface (SWI), as well as the presence of nitrate-reducing bacterial and ammonia-oxidizing archaeal (AOA) genera. This research provides valuable insights into the dynamics of P in headwaters, shedding light on P retention and release. Understanding these processes is crucial for effective management strategies aimed at mitigating P pollution to the lower Great Lakes.
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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) | 0.000 | 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".