Island phytophagy: explaining the remarkable diversity of plant-feeding insects
Bibliographic record
Abstract
Plant-feeding insects have undergone unparalleled diversification among different plant taxa, yet explanations for variation in their diversity lack a quantitative, predictive framework. Island biogeographic theory has been applied to spatially discrete habitats but not to habitats, such as host plants, separated by genetic distance. We show that relationships between the diversity of gall-inducing flies and their host plants meet several fundamental predictions from island biogeographic theory. First, plant-taxon genetic distinctiveness, an integrator for long-term evolutionary history of plant lineages, is a significant predictor of variance in the diversity of gall-inducing flies among host-plant taxa. Second, range size and structural complexity also explain significant proportions of the variance in diversity of gall-inducing flies among different host-plant taxa. Third, as with other island systems, plant-lineage age does not predict species diversity. Island biogeographic theory, applied to habitats defined by genetic distance, provides a novel, comprehensive framework for analysing and explaining the diversity of plant-feeding insects and other host-specific taxa.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".