Postglacial phylogeography, admixture, and evolution of red spruce (Picea rubens Sarg.) in Eastern North America
Bibliographic record
Abstract
Climate change is a major evolutionary force that can affect the structure of forest ecosystems worldwide. Red spruce (Picea rubensSarg.) has recently faced a considerable decline in the Southern Appalachians due to rapid environmental change, which includes historical land use, and atmospheric pollution. In the northern part of its range, red spruce is sympatric with closely related black spruce (Picea mariana(Mill.) B.S.P.), where introgressive hybridization commonly occurs. We investigated range-wide population genetic diversity and structure and inferred postglacial migration patterns and evolution of red spruce using nuclear microsatellites. Moderate genetic diversity and differentiation were observed in red spruce. Genetic distance, maximum likelihood and Bayesian analyses identified two distinct population clusters: southern glacial populations, and the evolutionarily younger northern populations. Approximate Bayesian computation suggests that patterns of admixture are the result of divergence of red spruce and black spruce from a common ancestor and then introgressive hybridization during post-glacial migration. Genetic diversity, effective population size (Ne) and genetic differentiation were higher in the northern than in the southern populations. Our results along with previously available fossil data suggest thatPicea rubensandPicea marianaoccupied separate southern refugia during the last glaciation. After initial expansion in the early Holocene, these two species faced a period of recession and formed a secondary coastal refugium, where introgressive hybridization occurred, and then both species migrated northward. As a result, various levels of black spruce alleles are present in the sympatric red spruce populations. Allopatric populations ofP. rubensandP. marianahave many species-specific alleles and much fewer alleles from common ancestry. The pure southern red spruce populations may become critically endangered under projected climate change conditions as their ecological niche may disappear.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".