Climate affects neighbour‐induced changes in leaf chemical defences and tree diversity–herbivory relationships
Bibliographic record
Abstract
Abstract Associational resistance theory predicts that insect herbivory decreases with increasing tree diversity in forest ecosystems. However, the generality of this effect and its underlying mechanisms are still debated, particularly since evidence has accumulated that climate may influence the direction and strength of the relationship between diversity and herbivory. We quantified insect leaf herbivory and leaf chemical defences (phenolic compounds) of silver birch Betula pendula in pure and mixed plots with different tree species composition across 12 tree diversity experiments in different climates. We investigated whether the effects of neighbouring tree species diversity on insect herbivory in birch, that is, associational effects, were dependent on the climatic context, and whether neighbour‐induced changes in birch chemical defences were involved in associational resistance to insect herbivory. We showed that herbivory on birch decreased with tree species richness (i.e. associational resistance) in colder environments but that this relationship faded as mean annual temperature increased. Birch leaf chemical defences increased with tree species richness but decreased with the phylogenetic distinctiveness of birch from its neighbours, particularly in warmer and more humid environments. Herbivory was negatively correlated with leaf chemical defences, particularly when birch was associated with closely related species. The interactive effect of tree diversity and climate on herbivory was partially mediated by changes in leaf chemical defences. Our findings confirm that tree species diversity can modify the leaf chemistry of a focal species, hence its quality for herbivores. They further stress that such neighbour‐induced changes are dependent on climate and that tree diversity effects on insect herbivory are partially mediated by these neighbour‐induced changes in chemical defences. A free Plain Language Summary can be found within the Supporting Information of this article.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.001 | 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 teacher head, 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".