Increasing trend in ecosystem-scale photosynthetic efficiency in the Yellow River Basin since 2000 caused by afforestation and climate change
Bibliographic record
Abstract
We used the leaf area index (LAI) and solar-induced chlorophyll fluorescence (SIF) to represent vegetation greenness and photosynthetic capacity, respectively, and the ratio of SIF to LAI (SIF/LAI) as an indicator of ecosystem-scale photosynthetic efficiency. We analyzed the spatial-temporal dynamics of SIF/LAI and its driving factors in the Yellow River Basin (YRB) of China from 2000 to 2021. The annual increase rate was 1.89% for SIF and 1.21% for LAI. The greater increase in SIF relative to LAI led to a significant increase in SIF/LAI ratio from 2000 to 2021, with an annual increase of 0.63%. This suggests an enhanced photosynthetic capacity per unit LAI over time. Forest cover explained 48% of the SIF/LAI rising trend, followed by temperature (26%) and the standardized precipitation-evapotranspiration index (SPEI, 16%). Regionally, the SIF/LAI had annual increasing rates of 1.25% and 1.10% in the upper and middle reaches of the YRB, respectively. Meanwhile, the SIF/LAI of the source region and lower reaches did not show a significant trend. This study deepens the understanding of the relationship between vegetation greening and photosynthetic capacity, which has implications for ecosystem management.
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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 | 0.002 |
| 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".