Weak Local Adaptation to Climate in Seedlings of a Deciduous Conifer Suggests Limited Benefits and Risks of Assisted Gene Flow
Bibliographic record
Abstract
ABSTRACT Assisted migration provides a potential solution to mitigate the increasing risks of forest maladaptation under climate change. Western larch ( Larix occidentalis Nutt.) is a deciduous conifer species undergoing assisted migration beyond its natural range in British Columbia into areas that have become suitable based on climatic niche modelling. We established a seedling common garden experiment in raised beds in a warm location outside the natural range for three growing seasons, with 52 natural populations from across the species range and 28 selectively bred families from British Columbia. Intraspecific genetic variation in growth, phenology and cold hardiness was analyzed to test for signals of local adaptation and the effects of selective breeding to better understand the implications for assisted migration and breeding for future climates. We found weak differentiation among populations in all traits, with the proportion of additive genetic variance ( Q ST ) ranging from 0.10 to 0.28. Cold hardiness had the weakest population differentiation and exhibited no clines with geographic or climatic variables. Selective breeding for faster growth has maintained genetic variation in bud flush phenology and cold hardiness despite delaying bud set. The weak signals of local adaptation we found in western larch seedlings highlights that assisted gene flow among populations is likely to have limited benefits and risks for mitigating maladaptation with climate change. Our findings suggest that assisted migration outside of the range and selective breeding may be important management strategies for western larch for future climates.
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 | 0.001 |
| 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".