The impact of pipe flow in riparian peat deposits on nitrate transport and removal
Bibliographic record
Abstract
Abstract The effect of preferential flow in soil pipes on nitrate retention in riparian zones is poorly understood. The characteristics of soil pipes and their influence on patterns of groundwater transport and nitrate dynamics were studied along four transects in a 1‐ to >3‐m deep layer of peat and marl overlying an oxic sand aquifer in a riparian zone in southern Ontario, Canada. The peat‐marl deposit, which consisted of several horizontal layers with large differences in bulk density, contained soil pipes that were generally 0.1 to 0.2 m in diameter and often extended vertically for 1 to >2 m. Springs that produced overland flow across the riparian area occurred at some sites where pipes extended to the peat surface. Concentrations of NO3−–N (20–30 mg L−1) and dissolved oxygen (DO) (4–6 mg L−1) observed in peat pipe systems and surface springs were similar to values in the underlying sand aquifer, indicating that preferential flow transported groundwater with limited nitrate depletion. Low NO3−–N concentrations of <5 mg L−1 and enriched δ15N values indicated that denitrification was restricted to small areas of the peat where pipes were absent. Groundwater DO concentrations declined rapidly to <2 mg L−1 in the peat matrix adjacent to pipes, whereas high NO3−–N concentrations of >15 mg L−1 extended over a larger zone. Low dissolved organic carbon values at these locations suggest that supplies of organic carbon were not sufficient to support high rates of denitrification, despite low DO conditions. These data indicate that it is important to develop a greater understanding of pipes in peat deposits, which function as sites where the transport of large fluxes of water with low biogeochemical reaction rates can limit the nitrate removal capacity of riparian zones. Copyright © 2011 John Wiley & Sons, Ltd.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.001 | 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".