DIEL CHANGES OF DISSOLVED ORGANIC MATTER IN STREAMS OF VARYING WATERSHED LAND USE
Bibliographic record
Abstract
ABSTRACT We examined diel changes in dissolved organic matter (DOM) under summer low‐flow conditions for six streams selected across a gradient of agricultural land use intensity (21%–73% cropland). Trends in concentration [dissolved organic carbon (DOC) concentration] and optical properties of DOM showed a high degree of synchrony. During a 24‐h period, DOC changed by between 2.9 and 4.3 mg L−1. For all sites, the highest DOC was observed during dark periods and the lowest concentration during light periods. DOM sampled during daylight hours was more complex (humic) as determined using specific absorbance. DOM source, measured using fluorescence spectroscopy, usually varied during the 24‐h period, but few similarities in temporal fluorescence trends were identified between sites. Human landscape alterations appear to have little direct influence on the temporal nature of diel DOM dynamics in our study region. However, our results indicate that landscape characteristics are likely more broadly important in defining the magnitude temporal change in DOC. Woodland areas were negatively correlated with early afternoon DOC (r2 = 0.89, p = 0.005), positively correlated with diel percent change in DOC (r2 = 0.87, p = 0.007) and positively with diel change in discharge (r2 = 0.64, p = 0.054). Together, these results indicate the likely influence of differing riparian transpiration rates and changing subsurface inputs on DOC loading. Reduced DOC and discharge rates during daylight hours resulted in a mean underestimation of DOC export rate by 61% for early afternoon versus early morning sampling. Variation in the dominant source of DOM entering theses streams was strongly related to agricultural land use, and DOM in high cropland streams was more microbially derived. In addition, high cropland streams also exhibited the lowest minimum dissolved oxygen concentrations, a pattern related to high rates of productivity at these sites. Copyright © 2012 John Wiley & Sons, Ltd.
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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 | 0.000 | 0.000 |
| 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) | 0.001 | 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".