What causes geographical variation in the species–area relationships? A test from forests in China
Bibliographic record
Abstract
The increase of species richness with sampling area and the decrease with latitude and altitude are two of the most frequently studied patterns in biogeography. However, few studies have simultaneously examined these two patterns to investigate how species–area relationships (SAR) vary with latitude and altitude. In this study, we explore the spatial patterns of SAR in forests in China by investigating numbers of species by life form group (trees, shrubs and herbs) in 32 nested plots from 12 mountains ranging from 18.7°N to 51.9°N in latitude and from 300 to 3150 m in altitude. The slopes of the power law SAR ( z ‐values) decreased with increasing latitude for all life forms except herbaceous plants, and also decreased with increasing altitude for all life forms but not for shrubs. Latitude and altitude, as well as their interactions, together explained 65.4, 61.8, 48.9 and 45.3% of the variation in z ‐values for overall species, trees, shrubs and herbaceous plants, respectively. In addition, actual evapotranspiration affected SAR significantly, but this effect varied significantly among life forms. We concluded that there are significant geographical patterns of SAR for China's forests, which is primarily controlled by energy availability.
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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 | 0.001 |
| 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".