Short‐ and Long‐Term Growth Response to Multiple Drought Episodes: Evidence of Genetic Adaptation in a Conifer Species
Bibliographic record
Abstract
ABSTRACT Drought tolerance of tree species is a concern in the context of climate change, and tree ring analyses can be used to assess past growth response(s), to drought events. In the current study, we applied this approach to 1281 individuals with known pedigree in long‐term genetic test plantations of lodgepole pine in western Canada. We assessed resistance, resilience, and recovery metrics, and analyzed their causal relationships with long‐term growth and susceptibility to disease through structural equation modeling. We found that trees with low short‐term resilience to drought events also experienced severe reductions in long‐term growth. Narrow‐sense heritability of drought tolerance metrics was low for short‐term responses at specific sites, while a new long‐term decline index for families showed moderate heritability ( of 0.15 to 0.30 ± 0.03). We also detected evidence of local adaptation, with trees from lower elevation showing better drought adaptation. We conclude that the selection of genotypes for drought tolerance is possible, and that other species or populations could be screened using this method. We also note that the new long‐term decline index developed in this study shows a higher degree of genetic control than other metrices, and may therefore be of broader interest in dendrochronological research.
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 | 0.001 |
| 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) | 0.000 | 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".