Agricultural land use alters the seasonality and magnitude of stream metabolism
Bibliographic record
Abstract
We present a comprehensive data set of gross primary production (GPP) and ecosystem respiration (ER) in open‐canopy, nutrient‐rich streams draining row‐crop agriculture in the midwestern United States. We used two approaches to characterize temporal and spatial variation in whole‐stream metabolism: continuous measurements in one agricultural stream for 1 yr, and periodic daily measurements in six agricultural streams on six dates spanning summer, autumn, and winter. Continuous measurements revealed high rates of GPP (range: 0.1 to 22.0 g O 2 m −2 d −1 ) and ER (range: −0.9 to −34.8 g O 2 m −2 d −1 ) that varied seasonally with light availability and temperature. GPP and ER were correlated during periods of high autotrophic production, suggesting that autotrophic respiration comprised a large portion of ER; however, the GPP : ER ratio exceeded 1 for only 4% of the year. While there were distinct temporal patterns in metabolism in one agricultural stream, rates of GPP and ER were similar among six streams when assessed via periodic daily measurements, and 26% of all periodic daily measurements were autotrophic with GPP : ER > 1. However, these periodic measurements were collected under baseflow conditions and may have overestimated the extent of autotrophy in agricultural streams. Overall, the open canopy and elevated nutrients of agricultural streams resulted in higher rates of GPP and ER compared with more pristine systems. Estimates of metabolism are needed from underrepresented systems to accurately quantify carbon fluxes from fluvial ecosystems.
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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".