Dissolved oxygen isotope modelling refines metabolic state estimates of stream ecosystems with different land use background
Bibliographic record
Abstract
Abstract Dissolved oxygen (DO) is crucial for aerobic life in streams and rivers and mostly depends on photosynthesis (P), ecosystem respiration (R) and atmospheric gas exchange (G). However, climate and land use changes progressively disrupt metabolic balances in natural streams as sensitive reflectors of their catchments. Comprehensive methods for mapping fundamental ecosystem services become increasingly important in a rapidly changing environment. In this work we tested DO and its stable isotope (18O/16O) ratios as novel tools for the status of stream ecosystems. For this purpose, six diel sampling campaigns were performed at three low-order and mid-latitude European streams with different land use patterns. Modelling of diel DO and its stable isotopes combined with land use analyses showed lowest P rates at forested sites, with a minimum of 17.9 mg m−2 h−1. Due to high R rates between 230 and 341 mg m−2 h−1 five out of six study sites showed a general heterotrophic state with P:R:G ratios between 0.1:1.1:1 and 1:1.9:1. Only one site with agricultural and urban influences showed a high P rate of 417 mg m−2 h−1 with a P:R:G ratio of 1.9:1.5:1. Between all sites gross G rates varied between 148 and 298 mg m−2 h−1. In general, metabolic rates depend on the distance of sampling locations to river sources, light availability, nutrient concentrations and possible exchanges with groundwater. The presented modelling approach introduces a new and powerful tool to study effects of land use on stream health. Such approaches should be integrated into future ecological monitoring.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".