In‐stream biotic control on nutrient biogeochemistry in a forested stream, West Fork of Walker Branch
Bibliographic record
Abstract
A growing body of evidence demonstrates the importance of in‐stream processing in regulating nutrient export, yet the influence of temporal variability in stream metabolism on net nutrient uptake has not been explicitly addressed. Stream water DIN and SRP concentrations in Walker Branch, a first‐order deciduous forest stream in eastern Tennessee, show a repeated pattern of annual maxima in summer and biannual minima in spring and autumn. Temporal variations in catchment hydrologic flow paths result in lower winter and higher summer nutrient concentrations, but do not explain the spring and autumn nutrient minima. Ambient nutrient uptake rates were measured 2–3 times per week over an 18‐month period and compared to daily rates of gross primary production (GPP) and ecosystem respiration (ER) to examine the influence of in‐stream biotic activity on nutrient export. GPP and ER rates explained 81% of the variation in net DIN retention with high net NO3− uptake (and lower net NH4+ release) rates occurring during spring and autumn and net DIN release in summer. Diel nutrient concentration patterns were examined several times throughout the year to determine the relative importance of autotrophic and heterotrophic activity on net nutrient uptake. High spring GPP corresponded to daily decreases in NO3− over the illuminated hours resulting in high diel NO3− amplitude which dampened as the canopy closed. GPP explained 91% of the variance in diel NO3− amplitude. In contrast, the autumn nutrient minima was largely explained by heterotrophic respiration since GPP remained low and little diel NO3− variation was observed during the autumn.
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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) | 0.001 | 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".