Contributions of dynamic environmental signals during life-cycle transitions to early life-history traits in lodgepole pine ( <i>Pinus contorta</i> Dougl.)
Bibliographic record
Abstract
Abstract. Environmental signals are important triggers in the life-cycle transitions and play a crucial role in the life-history evolution. Yet very little is known about the leading ecological factors contributing to the variations of life-history traits in perennial plants. This paper explores both the causes and consequences for the evolution of life-history traits (i.e., seed dormancy and size) in lodgepole pine (Pinus contorta Dougl.) across British Columbia (B.C.), Canada. We selected 83 logepole pine populations covering 22 ecosystem zones of B.C. and through their geographic coordinate, 197 climatic variables were generated accordingly for the reference (1961–1990) and future (2041–2070) periods. We found that dynamic climatic variables rather than constant geographic variables are the true environmental driving forces in seed dormancy and size variations and thus provide reliable predictors in response to global climate change. Evapotranspiration and precipitation in the plant-to-seed chronology are the most critical climate variables for seed dormancy and size variations, respectively. Hence, we predicted that levels of seed dormancy in lodgepole pine would increase across large tracts of B.C. in 2050s. Winter-chilling is able to increase the magnitude of life-history plasticity and lower the bet-hedge strategy in the seed-to-plant transition; however, winter-chilling is likely to be insufficient in the north of 49° N in 2050s, which may delay germination while unfavorable conditions during dry summers may result in adverse consequences in the survival of seedlings owing to extended germination span. These findings provide useful information to studies related to assessments of seed transfer and tree adaptation.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".