Spruce hybrids show superior lifespan growth but intermediate response to climate stress compared to their ecologically divergent parental species
Bibliographic record
Abstract
Climate change brings new constraints to which trees will have to adapt, including more frequent severe weather events due to climate anomalies. Black spruce and red spruce are phylogenetically close but adapted to different ecological conditions, and they form a natural hybrid zone where their natural distributions come into contact. Thus, they represent an interesting model to study the effect of introgressive hybridization in the context of climate change, given that interspecific gene flow could eventually affect their capacity to adapt where their natural distributions overlap. Using a common garden field test gathering 20-year-old progeny trees resulting from rigorous controlled crosses including previously verified genetic identity of the parents, growth patterns and wood density differences could be observed between species and between them and their F 1 hybrids. A dendroecological analytical approach relying on wood cores was used and revealed similar wood responses to climatic variations between species, both through lifespan climate sensitivity and through episodic stress response indexes. They were however differentially expressed in early- and latewood between black spruce and red spruce, differences likely driven by diverging cambial phenology adaptations to different growing season lengths. F 1 hybrids exhibited hybrid vigor for lifespan cumulative growth under the test site conditions but showed intermediate values for traits related to climate response. These results may assist the management of forest genetic resources and contribute to a better understanding of the dynamics of adaptation to climate in hybrid zones.
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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) | 0.001 | 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".