Species-specific determinants of mortality and recruitment in the forest-steppe ecotone of northeast China
Bibliographic record
Abstract
Tree mortality is a notable phenomenon in the forest-steppe ecotone of China. However, the association between mortality and factors such as a changing climate is uncertain. In the summer of 2014 tree mortality was investigated in 20 × 400 m2 plots to determine the species-specific determinants of mortality and their influence on subsequent species recruitment. Nine soil physical-chemical properties were examined in addition to slope position, mean DBH and total number of trees. Generalized linear models analyzed relationships between these variables and mortality and recruitment. Mortality was positively associated with increasing average diameter and negatively to high soil pH and total nitrogen content. Recruitment models indicate that Populus davidiana recruitment was positively affected by available phosphorus and mortality, and negatively related to mean DBH. Slope position was the most important contributing variable to Betula platyphylla recruitment. With Quercus mongolica recruitment, soil variables played an important role. These results suggest that tree mortality is affected by soil properties, topography and tree size in China's forest-steppe ecotone, and may improve our understanding of species mortality and contribute to improved forest management.
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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 | 0.000 | 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".