Two adjacent forested catchments: Dramatically different NO<sub>3</sub><sup>−</sup> export
Bibliographic record
Abstract
Two adjacent catchments with similar temperate forest cover and podzolic soils have annual nitrate (NO3−) export that differs by a factor of 10. Monthly rates of mineralization and nitrification measured by the buried bag technique, soil C/N ratios, and the contribution of microbial NO3− to total NO3− in the groundwater as determined by analysis of δ18O in NO3− are also similar. In both catchments, maximum NO3− export occurs during spring melt, but in the catchment with higher export, NO3− concentrations in the stream begin to increase in the fall period. Groundwater NO3− concentrations measured in wells are very different in the two catchments with high groundwater NO3− in the catchment exhibiting high NO3− export. Following spring melt, steeper slopes in the high NO3− catchment promote faster drainage, and the water table declines rapidly while high NO3− concentrations are maintained in groundwaters. Deeper water tables will preserve high NO3− in water infiltrating below the rooting zone and organic‐rich upper soil horizons. In the low NO3− catchment, slower drainage on shallower slopes lead to an increase in soil saturation, and the NO3− disappears from the water before the water table declines. Analyses of δ15N in NO3− during NO3− loss do not show evidence of denitrification, although denitrification proceeding to completion in isolated pockets followed by mixing with higher NO3− groundwaters would yield the same result. Alternatively, active uptake of NO3− by vegetation following spring melt will also deplete the groundwater NO3− in the shallow soil depths without isotopic fractionation. The low NO3− catchment also has lower NO3− in shallow soil waters during spring melt. Shallower slopes promote near‐surface flow paths in organic‐rich soil horizons which may facilitate denitrification during spring melt. Although the catchment with low NO3− export has a large wetland near the catchment outlet, the NO3− attenuating capacity of this wetland is largely unused except in the late fall because growing season groundwater concentrations of NO3− are undetectable and the wetland is frozen during snowmelt. In the high NO3− catchment, organic‐rich soils and vegetation in the riparian zone cannot completely attenuate high NO3− in discharging groundwaters. In our study, factors controlling NO3− in groundwater such as slope, stratigraphy, and hydraulic conductivity can play a larger role than riparian zones in controlling differences in annual NO3− export observed between catchments.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".