Geographic variation and adaptation to current and future climates of <i>Callitropsis nootkatensis</i> populations
Bibliographic record
Abstract
Forty-one range-wide Callitropsis nootkatensis (D. Don) Orsted (syn. Chamaecyparis nootkatensis (D. Don) Spach) populations were tested at 12 geographically and ecologically diverse sites throughout British Columbia, Canada. There were significant region and population within region effects for 15-year height at most sites but not for adaptability, a binary trait combining survival and cold hardiness. Across-site analysis revealed significant site by population within region interaction for both traits. These interactions were less pronounced when just the core sites were analysed and without two southern disjunct populations. Based on a productivity index that combined height, survival, and cold hardiness, populations were adapted to broad temperature gradients compared with most temperate tree species and were relatively insensitive to moisture. Only the northern California population from the extreme southernmost part of the species’ range had consistent and significant adaptive differentiation, showing maladaptation characterized by severe cold damage and mortality at all test sites. Northern populations grew slowly but survived well. Productivity of this montane species is likely to increase in situ with projected warming across the range of tested sites. Transfer to sites warmer than the population origin increases productivity. Currently and in the long term, populations from the core of the species’ range can be widely transferred for reforestation with minimal risk of maladaptation, provided highly inbred sources from isolated, small populations and sites at risk for yellow cypress decline are avoided.
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 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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".