Pathogen attack and spatial patterns of juvenile mortality and growth in a temperate tree, <i>Prunus grayana</i>
Bibliographic record
Abstract
To examine whether the Janzen–Connell hypothesis is valid in temperate forests, we investigated the density, growth, mortality, and agents of mortality of seedlings and the density, size, and age of saplings of Prunus grayana Maxim. at three distances (0–3, 6–10, and 16–26 m) from conspecific adults in a temperate forest in Japan. An inoculation experiment was also conducted to test the host range of a leaf pathogen. The probability of mortality was highest at 0–3 m during the first 2 years of growth. Mortality mainly resulted from distance-dependent attack by two types of pathogen that caused damping-off epidemics and spot symptoms on leaves. The leaf pathogen was identified as Phaeoisariopsis pruni-grayanae Sawada, which infected many more seedlings of Prunus grayana than of the two other tree species tested in an inoculation experiment. The vertical and diameter growth was lowest at 0–3 m and highest at 16–26 m in both seedlings and saplings. As a result, the greatest number of large and older saplings was observed at 16–26 m. Our results demonstrate that the Janzen–Connell mechanism operates in a beech-dominated forest in the temperate region of Japan.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 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".