Performance of simple low-cost edge-of-field filters for mitigating P losses in surface runoff from agricultural fields
Bibliographic record
Abstract
Nutrient losses from agricultural fields are the largest sources of phosphorus (P) entering the Great Lakes in North America. Stacked conservation practices (CPs) may reduce P losses from individual fields. Simple low-cost, low disturbance, commercially available filters containing wood chips and phosphorus sorbing materials (PSM) were installed on two fields already using conservation practices in midwestern Ontario (ILD and LON) to quantify their ability to remove soluble reactive P (SRP), particulate P (PP), total P (TP) and total suspended sediments (TSS) from surface runoff. Laboratory tests on unused (new) and used (field) filter materials were also conducted to estimate P sorption and remobilization potentials. During the two-year study period, the filter retained 0.018 kg ha-1 of SRP, 0.38 kg ha-1 of PP, 0.4 kg ha-1 of TP and 8.75 kg ha-1 of TSS from surface runoff at the ILD site. In contrast, although the filter at LON removed 37 kg ha-1 of TSS and 0.07 kg ha-1 of PP, it released 0.22 kg ha-1 of SRP and 0.15 kg ha-1 TP. A reduction in filter efficacy was observed over time, particularly at the site with greater cumulative surface runoff and larger runoff events (LON). The majority of the SRP retained by the filter was held in a loosely bound form, thus, susceptible to P remobilization. The results of this study demonstrate that low-cost, simple PSMs have some potential to retain P from surface runoff, but their efficacy may decline over time and their P retention capability may differ with site hydrology (e.g., runoff volumes and velocity) and P supply.
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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 | 0.000 |
| 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".