Assessing assisted population migration (seed transfer) for eastern white pine at northern planting sites
Bibliographic record
Abstract
Assisted population migration (APM) has been proposed as an adaptive strategy to enhance forest resilience and productivity under a warming climate. Previous studies have shown tangible benefits of APM on tree growth, including eastern white pine. However, climatic conditions strongly affecting tree growth may also influence the expression of provenance variation and, consequently, benefits from conducting APM. Estimated benefits of APM at warm field trial sites thus may not be attainable at colder northerly sites. In this study, we assessed the potential benefits of APM for eastern white pine at climatically mild and cold sites using data from six field provenance trials in Ontario and Quebec, Canada. Results indicated that annual tree height increment, inter-provenance variation, and achievable benefits from provenance selection were significantly affected by climatic conditions of trial sites. At climatically warm and mild sites where frost or winter low temperature did not cause tree injury, annual height increment was more than 50 % greater and achievable benefit was about twice as large as that at cold sites near the edge of species’ natural range limit. Provenance variation in survival was, however, negligible across trials. Based on patterns of spatial provenance variation, the southern and northern limits of provenances suitable for use as seed sources for planting sites in Ontario and Quebec were delineated using latitudinal coordinates or thermal variables. The potential benefits of APM at northerly sites in anticipation of future climate change are discussed. • Assisted population migration (APM) relies on meaningful inter-provenance variation. • Climatic conditions may influence inter-provenance variation in trait of interest. • We assessed benefits of APM for eastern white pine at mild and cold planting sites. • Estimated benefits of APM were greater at warmer field trials during the recent past. • APM may achieve rapid benefit at lower cost than traditional tree improvement.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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".