Data from: Insect herbivory on seedlings of rainforest trees: effects of density and distance of conspecific and heterospecific neighbours
Bibliographic record
Abstract
1. Natural enemies of plants such as insect herbivores can contribute to structuring and maintaining plant diversity in tropical forests. Most research in this area has focused on the role of specialised enemies and the extent to which herbivory on individual plant species is density-dependent. 2. Relatively few insect herbivores specialise on a single host plant species. Insect herbivores that feed on more than one plant species may link the regeneration dynamics of their host species through ‘apparent competition’ or ‘apparent mutualism’. 3. We investigated herbivory and survival of seedlings of two tropical tree species (Cordia alliodora and Cordia bicolor) in the forests of Barro Colorado Island (Panama). We used experiments and observations to assess seedling fate in relation to the presence of conspecifics and heterospecifics across a range of spatial scales. 4. Herbivory significantly increased seedling mortality and was highest at high local densities of C. alliodora seedlings. There was also evidence that high local densities of C. alliodora increased herbivory on co-occurring C. bicolor seedlings. 5. Synthesis. The elevated rates of seedling herbivory at high densities of conspecifics documented in our study are consistent with the predictions of the Janzen-Connell hypothesis, which explains how so many plant species can coexist in tropical forests. Our data also highlight the possibility that herbivore-mediated density-dependence, facilitated by herbivores that feed on multiple plant species, can also occur across plant species. Enemy-mediated indirect effects of this sort have the potential to structure plant communities.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.071 | 0.019 |
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".