The distance dependence prediction of the Janzen‐Connell hypothesis: a meta‐analysis
Bibliographic record
Abstract
The Janzen‐Connell hypothesis explains the maintenance of tropical diversity through the interacting effects of parent‐centered dispersal patterns and distance‐ and density‐dependent propagule survival. These effects were thought to support regular spacing of species within tropical forest, enhancing diversity. One of the predictions of the hypothesis is that seed and seedling survival should improve with increased parental distance. Although there are many independent tests of this hypothesis for individual species, there are few synthetic studies that have brought these data together to test its validity across species. This paper reports the results of a meta‐analysis of the effect of distance on enhancing propagule survival, employing an odds‐ratio effect size metric. We found no general support for the distance‐dependent prediction of the hypothesis, and conclude that further testing to explore this hypothesis as a diversity‐maintaining mechanism is unnecessary. However, we did find that distance from parent slightly reduces survivorship in the temperate zone, as contrasted with the tropics, and we saw stronger evidence in support of the hypothesis for seedlings than for seeds. The phenomenon of enhanced propagule survival with distance from the parent may be important for the population biology of particular species, but it is not a general phenomenon across communities, life history stages or life forms.
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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 | 0.040 | 0.074 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.014 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".