Effects of leaf herbivory and autumn seasonality on plant secondary metabolites: A meta‐analysis
Bibliographic record
Abstract
Plant secondary metabolites (PSMs) are produced by plants to overcome environmental challenges, both biotic and abiotic. We were interested in characterizing how autumn seasonality in temperate and subtropical climates affects overall PSM production in comparison to herbivory. Herbivory is commonly measured between spring to summer when plants have high resource availability and prioritize growth and reproduction. However, autumn seasonality also challenges plants as they cope with limited resources and prepare survival for winter. This suggests a potential gap in our understanding of how herbivory affects PSM production in autumn compared to spring/summer. Using meta-analysis, we recorded overall production of 22 different PSM subgroups from 58 published papers to calculate effect sizes from herbivory studies (absence to presence) and temperate to subtropical seasonal studies (summer to autumn), while considering other variables (e.g., plant type, increase in time since herbivory, temperature, and precipitation). We also compared production of five phenolic PSM subgroups - hydroxybenzoic acids, flavan-3-ols, flavonols, hydrolysable tannins, and condensed tannins. We wanted to detect a shared response across all PSMs and found that herbivory increased overall PSM production in herbaceous plants. Herbivory was also found to have a positive effect on individual PSM subgroups, such as flavonol production, while autumn seasonality was found to have a positive effect on flavan-3-ol and condensed tannin production. We discuss how these responses might stem from plants producing some PSMs constitutively, whereas others are induced only after herbivory, and how plants produce metabolites with higher costs only during seasons when other resources for growth and reproduction are less available, while other phenolic PSM subgroups serve more than one function for plants and such functions can be season dependent. The outcome of our meta-analysis is that autumn seasonality changes some PSM production differently from herbivory, and we see value in further investigating seasonality-herbivory interactions with plant chemical defense.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.039 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".