Insect herbivory on woody broadleaf seedlings along a subtropical elevational gradient supports the resource concentration hypothesis
Bibliographic record
Abstract
PREMISE: Theories of plant-herbivore interactions hold that seedlings are more vulnerable to herbivory in warmer and more stable climates at lower elevations. Hypotheses of plant apparency, resource concentration, and resource availability have been proposed to explain variability in leaf herbivory. However, seasonal differences in the effects of these hypotheses on leaf herbivory on seedlings remain unclear. METHODS: We evaluated the three herbivory hypotheses by comparing the percentage and frequency of leaf herbivory in understory broadleaf seedlings in a subtropical forest in May (spring) and October (autumn) along an elevational gradient (290-1370 m a.s.l.). In total, we measured 2890 leaves across 696 seedlings belonging to 95 species and used beta regressions to test the effects of plant apparency (e.g., leaf area, seedling height), resource concentration (e.g., plant species diversity), and resource availability (e.g., canopy openness, soil available N and P) on leaf herbivory. RESULTS: Seedlings exhibited unimodal patterns of leaf herbivory along elevation, with drivers of leaf herbivory varying by the month. Variation in the frequency of leaf herbivory was best explained by the resource concentration hypothesis (e.g., plant species diversity) in both months, and herbivory was lower on seedlings in sites with higher plant diversity. Plant apparency hypothesis (e.g., leaf area, seedling height) was weakly supported only in spring, and the evidence for resource availability hypothesis (e.g., canopy openness, soil nutrients) was mixed. CONCLUSIONS: This study supports the resource concentration hypothesis and reveals the importance of seasonal difference on understanding leaf herbivory patterns and the drivers of plant diversity in subtropical forests.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".