Pest defenses under weak selection exert a limited influence on the evolution of height growth and drought avoidance in marginal pine populations
Bibliographic record
Abstract
Whilst droughts, intensified by climate change, have been affecting forests worldwide, pest epidemics are a major source of uncertainty for assessing drought impacts on forest trees. Thus far, little information has documented the adaptability and evolvability of traits related to drought and pests simultaneously. We conducted common-garden experiments to investigate how several phenotypic traits (i.e., height growth, drought avoidance based on water-use efficiency inferred from δ13C, and pest resistance based on defense traits) interact in five mature lodgepole pine populations established in four progeny trials in western Canada. The relevance of interpopulation variation in climate sensitivity highlighted that seed-source warm populations had greater adaptive capability than cold populations. In test sites, warming generated taller trees with higher δ13C and increased the evolutionary potential of height growth and δ13C across populations. We found, however, no pronounced gradient in defenses and their evolutionary potential along populations or test sites. Response to selection was weak in defenses across test sites, but high for height growth, particularly at warm test sites. Response to selection of δ13C varied depending on its selective strength relative to height growth. We conclude that warming could promote the adaptability and evolvability of growth response and drought avoidance with limited evolutionary influence from pest (biotic) pressures.
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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 | 0.000 |
| 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 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".