Macroecological and macroevolutionary patterns of leaf herbivory across vascular plants
Bibliographic record
Abstract
The consumption of plants by animals underlies important evolutionary and ecological processes in nature. Arthropod herbivory evolved approximately 415 Ma and the ensuing coevolution between plants and herbivores is credited with generating much of the macroscopic diversity on the Earth. In contemporary ecosystems, herbivory provides the major conduit of energy from primary producers to consumers. Here, we show that when averaged across all major lineages of vascular plants, herbivores consume 5.3% of the leaf tissue produced annually by plants, whereas previous estimates are up to 3.8× higher. This result suggests that for many plant species, leaf herbivory may play a smaller role in energy and nutrient flow than currently thought. Comparative analyses of a diverse global sample of 1058 species across 2085 populations reveal that models of stabilizing selection best describe rates of leaf consumption, and that rates vary substantially within and among major plant lineages. A key determinant of this variation is plant growth form, where woody plant species experience 64% higher leaf herbivory than non-woody plants. Higher leaf herbivory in woody species supports a key prediction of the plant apparency theory. Our study provides insight into how a long history of coevolution has shaped the ecological and evolutionary relationships between plants and herbivores.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".