Vegetation patterns and causal factors in different reaches of an endorheic basin in arid China
Bibliographic record
Abstract
Understanding the response of vegetation to a changing global climate is important. The relationships among 33 topographic, soil and climatic variables and 74 vegetation assemblages were analyzed by detrended canonical correspondence analysis (DCCA) to determine the most important variables that affect vegetation patterns and their distribution in different reaches of the Heihe River Basin. Altitude was the most significant factor across the entire basin and in the middle reach (oasis-desert area, 1289–3920 m). Mean temperature of the warmest month and mean annual evapotranspiration were the most significant factors in the upper reach (mountain area, 2180–5547 m) and the lower reach (desert area, 820–2593 m), respectively. The annual average insolation and the aridity index also had significant relationships with vegetation distribution in the mountain area. Mean temperature of the coldest month and annual cumulated temperatures ≥ 10°C also were important in the oasis-desert area, and soil organic matter and groundwater depth in the desert area. Conservation of varying tree, shrub and grass species should be considered based on their thermal and water requirements in the mountain area.
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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 | 0.000 | 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".