Climatic stress mediates the impacts of herbivory on plant population structure and components of individual fitness
Bibliographic record
Abstract
Summary Past studies have shown that the strength of top‐down herbivore control on plant physiological performance, abundance and distribution patterns can shift with abiotic stress, but it is still unclear whether herbivores generally exert stronger effects on plants in stressful or in nonstressful environments. One hypothesis suggests that herbivores' effects on plant biomass and fitness should be strongest in stressful areas, because stressed plants are less able to compensate for herbivore damage. Alternatively, herbivores may reduce plant biomass and fitness more substantially in nonstressful areas, either because plant growth rates in the absence of herbivory are higher and/or because herbivores are more abundant and diverse in nonstressful areas. We test these predictions of where herbivores should exert stronger effects by measuring individual performance, population size structure and densities of a common subshrub,Hibiscus meyeri, in a large‐scale herbivore exclosure experiment arrayed across an aridity gradient in East Africa. We find support for both predictions, with herbivores exerting stronger effects on individual‐level performance in arid (stressful) areas, but exerting stronger effects on population size structure and abundance in mesic (nonstressful) areas. We suggest that this discrepancy arises from higher potential growth rates in mesic areas, where alleviation of herbivory leads to substantially more growth and thus large changes in population size structure. Differences in herbivore abundance do not appear to contribute to our results. Synthesis. Our work suggests that understanding the multiple facets of plant response to herbivores (e.g. both individual performance and abundance) may be necessary to predict how plant species' abundance and distribution patterns will shift in response to changing climate and herbivore numbers.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".