Exploring the role of hydraulic conductivity on the contribution of the hyporheic zone to in‐stream nitrogen uptake
Bibliographic record
Abstract
Abstract Nitrogen uptake (N‐uptake) within the hyporheic zone provides key ecological services, such as nutrient removal, of stream ecosystems. We hypothesize that the hydraulic conductivity (Kf) of the hyporheic sediments governs nutrient uptake rates through effects on the (a) surface and subsurface flow (i.e., hyporheic flow) and (b) hyporheic N‐uptake. Here, we worked at two hierarchical spatial scales (reach and hyporheic scale) to disentangle the role of Kf on N‐uptake. At the reach scale, we performed coinjected N‐NH4+ and Cl– additions in six reaches with contrasting reach Kf (10−1–10−5 m/s) and simultaneously determined (a) in‐stream N‐uptake (hyporheic+benthic N‐uptake) and (b) hyporheic flow, and (c) N‐uptake and microbial community abundance at the hyporheic scale. Results suggest that Kf determines the contribution of the hyporheic zone to hydrological exchange but that its role varies between scales to determine in‐stream N‐uptake. At the reach scale, Kf variability seems to determine the extent at which the hyporheic zone contributes to hyporheic flow and, thus, to N‐uptake velocity. At the hyporheic scale, Kf seems to indirectly determine hyporheic N‐uptake through the proportion of surface water that enters the hyporheic zone (i.e., relative connectivity) and the abundance of the microbial community. These results suggest an interplay between Kf at both scales and its spatial heterogeneity, which will ultimately drive in‐stream N‐uptake at reach scale. In this sense, we found that Kf can be considered as a unifying variable for stream biogeochemical processes and as an important variable to derive the contribution of hyporheic zone to in‐stream nutrient removal capacity.
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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".