Local Adaptation and Response of Platycladus orientalis (L.) Franco Populations to Climate Change
Bibliographic record
Abstract
Knowledge about the local adaptation and response of forest tree populations to the climate is important for assessing the impact of climate change and developing adaptive genetic resource management strategies. However, such information is not available for most plant species. Here, based on 69 provenances tested at 19 common garden experimental sites, we developed a universal response function (URF) for tree height at seven years of age for the important and wide-spread native Chinese tree species Platycladus orientalis (L.) Franco. URF was recently used to predict the potential growth response of a population originating from any climate and growing in any climate conditions. The developed model integrated both genetic and environmental effects, and explained 55% of the total variation in tree height observed among provenances and test sites in China. We found that local provenances performed better than non-local counterparts in habitats located in central, eastern, and southwestern China, showing the evidence of local adaptation as compared to other regions. In contrast, non-local provenances outperformed local ones in peripheral areas in northern and northwestern China, suggesting an adaptational lag in these areas. Future projections suggest that the suitable habitat areas of P. orientalis would expand by 15%–39% and shift northward by 0.8–3 degrees in latitude; however, the projected tree height of this species would decline by 4%–8% if local provenances were used. If optimal provenances were used, tree height growth could be improved by 13%–15%, along with 59%–71% suitable habitat expansion. Thus, assisted migration with properly selected seed sources would be effective in avoiding maladaptation in new plantations under a changing climate for P. orientalis.
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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) | 0.008 | 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; both teacher heads agree on what is shown here.
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".