Stemflow and dissolved organic carbon cycling: temporal variability in concentration, flux, and UV-Vis spectral metrics in a temperate broadleaved deciduous forest in the eastern United States
Bibliographic record
Abstract
No known research has examined the concentration and flux of dissolved organic carbon (DOC) for stemflow across temporal scales from within single storm events to seasonal and annual scales or employed UV-Vis spectral metrics to examine the chemical character of dissolved organic matter (DOM) of stemflow drainage. Thus, our study examined stemflow DOC concentration and flux and DOM character from American beech ( Fagus grandifolia Ehrh.) and yellow poplar ( Liriodendron tulipifera L.) to address this data gap. Intrastorm stemflow DOC concentrations and fluxes diminished by an order of magnitude over time for American beech but remained relatively constant for yellow poplar. Stemflow DOM aromaticity, however, generally increased and E2:E3 ratios generally decreased as events progressed, suggesting transport of different compounds at different moments. Although less enriched in DOC than yellow poplar, American beech stemflow DOC fluxes were double per annum. Differential interspecific stemflow DOM characteristics are ascribed to (i) significant differences in SUVA254 values (aromaticity) for the leafless season and annually and (ii) significantly higher E2:E3 and SR ratios for yellow poplar stemflow than for American beech annually and across leafed and leafless seasons. Our results suggest that stemflow significantly affects the amount and chemical character of carbon flux to the forest floor that may engender hot spots around tree boles.
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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 | 0.000 |
| 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".