How do variations in the temporal distribution of rainfall events affect ecosystem fluxes in seasonally water-limited Northern Hemisphere shrublands and forests?
Bibliographic record
Abstract
Abstract. Rainfall regimes became more extreme over the course of the 20th century, characterised by fewer and larger rainfall events. Such changes are expected to continue throughout the current century. The effect of changes in the temporal distribution of rainfall on ecosystem carbon fluxes is poorly understood, with most available information coming from experimental studies of grassland ecosystems. Here, continuous measurements of ecosystem carbon fluxes and precipitation from the worldwide FLUXNET network of eddy-covariance sites are exploited to investigate the effects of differences in rainfall distribution on the carbon balance of seasonally water-limited shrubland and forest sites. Once the strong dependence of ecosystem fluxes on total annual rainfall amount is accounted for, results show that sites with rainfall distributions characterised by fewer and larger rainfall events have significantly lower gross primary productivity, slightly lower ecosystem respiration and consequently a smaller net ecosystem productivity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".