A test of the Janzen‐Connell hypothesis in a species‐rich Mediterranean woodland
Bibliographic record
Abstract
Abstract The Janzen‐Connell (JC) hypothesis predicts that conspecific negative density dependence contributes to the maintenance of plant diversity by lowering the recruitment of locally abundant plant species. The JC hypothesis is a widely evoked explanation for the high species diversity in tropical forests, but remains poorly tested in other species‐rich systems such as Mediterranean woodlands. As such, we tested if the JC operates and the role of soil‐borne oomycetes in a species‐rich Mediterranean woodland of Western Australia, where post‐fire recruitment can lead to high seedling densities, using the common Banksia attenuata as a case study. We attempted to decipher the effects of oomycete pathogens and distance from conspecific trees on intraspecific seedling survival and growth. Contrary to the JC hypothesis, we found little evidence of negative density dependence, but our results suggest positive density dependence survival under conspecific trees. Oomycete‐driven mortality in seedlings was also found regardless of the type of tree. Our results suggest that short‐term seedling recruitment patterns in this species‐rich, fire‐prone ecosystem do not follow the JC hypothesis. Future studies should explore whether negative conspecific density and distance dependence could play a greater role in later stages of the post‐fire recovery process.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".