The structure of genetic diversity in Engelmann spruce and a comparison with blue spruce
Bibliographic record
Abstract
Genetic diversity and genetic structure in Engelmann spruce (Picea engelmannii Parry ex Engelm.) were interpreted with respect to the effects of glacial and interglacial displacement and compared with patterns in blue spruce (Picea pungens Engelm.), which occupies a range well south of the last glacial front. On average, Engelmann spruce populations were polymorphic at 80% of 24 isozyme loci, with 2.4 alleles per locus and expected heterozygosity of 0.255. The respective means for four populations of blue spruce were 42.7%, 1.6 alleles, and 0.138. Of total diversity, 14.7% was among populations in Engelmann spruce and 8.6% in blue spruce. In Engelmann spruce, numbers of alleles increased from south to north. Recent bottlenecks were indicated in the three southernmost populations of Engelmann spruce and in the northernmost population of blue spruce. Cluster analysis divided Engelmann spruce into a northern group and a Southwestern group; however, populations from Utah were distributed among both clusters. Genetic distance was correlated with geographic distance between northern populations but not between Southwestern populations, where drift predominated over gene flow. In two Engelmann spruce populations from Utah, multilocus outcrossing rates were 0.951 (±0.016) and 0.940 (±0.071). At Flys Peak, Arizona, the southernmost location of Engelmann spruce, outcrossing was also high, 0.899 (±0.017). Thus, inbreeding coefficients observed for parental (–0.104 to 0.047) and filial (0.011 to 0.026) generations were low. Although Engelmann spruce seemed genetically robust, the evidence of bottlenecks in the southern extreme of its range suggested future problems in an era of global warming.
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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) | 0.000 | 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".