Isotopic assessment of NO<sub>3</sub><sup>−</sup> and SO<sub>4</sub><sup>2−</sup> mobility during winter in two adjacent watersheds in the Adirondack Mountains, New York
Bibliographic record
Abstract
Biogeochemical cycling of N and S was examined at two watersheds in the Adirondack Mountains, New York, to better understand the retention and loss of these elements during winter and spring snowmelt. We analyzed stable isotope compositions of NO3− (δ15N‐NO3−, δ18O‐NO3−) and SO42− (δ34S‐SO42−, δ18O‐SO42−), along with concentrations and fluxes of NO3− and SO42−, in precipitation, throughfall, snowpack, snowmelt, soil water, groundwater, and stream water. Isotopic results showed no evidence of NO3− and SO42− transformations in the forest canopy and snowpack; however, markedly decreased δ18O values of NO3− and SO42− in forest floor water suggest that microbial processing occurred in organic soil horizons. Similarly low δ18O values of NO3− and SO42− were observed in forest floor and mineral soil leachates, groundwater, and streams. Over the winter observation period, most of the NO3− and SO42− in stream water was from a watershed‐derived source, whereas atmospheric contributions were relatively minor. Despite differences in soil water NO3− concentrations between watersheds, the isotopic composition of NO3− (δ15N‐NO3−, δ18O‐NO3−) was similar, and indicated that in both watersheds most of the NO3− was produced by nitrification in the forest soils. Although there was likely some contribution of SO42− from microbial oxidation of carbon‐bonded sulfur, most of the stream water SO42− appeared to be derived from weathering of S‐containing bedrock or parent material. The decreased δ18O values of NO3− and SO42− in upper soil horizons indicate that atmospheric deposition of N and S was not directly linked with stream water losses, even during winter and spring snowmelt.
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) | 0.000 | 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 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".