The mating system and genic diversity in Martínez spruce, an extremely rare endemic of México's Sierra Madre Oriental: an example of facultative selfing and survival in interglacial refugia
Bibliographic record
Abstract
Martínez spruce (Picea martínezii T.F. Patterson) is a conifer currently passing through a bottleneck, reduced to a few relict populations totaling less than 800 trees. We used isozyme markers to analyze the mating system and survey the level of genic diversity in two populations. The mating system was characterized by a high frequency of selfing. The multilocus outcrossing rates (tm) and 95% confidence intervals were only 0.399 (0.197 < tm< 0.601) for the smallest population and 0.589 (0.475 < tm< 0.703) or 0.685 (0.465 < tm< 0.905), depending on year, for the largest. These are among the lowest rates of outcrossing observed in conifers. The fixation indices for the two populations were -0.058 and 0.121, less than expected for such high levels of selfing. Expected heterozygosity, unbiased He, based on 22 loci in 13 enzyme systems, was 0.121 and 0.101 in the two populations. The proportion of the total genic diversity between populations, FST, was 2.4%. Nm, the number of migrants per generation, was about 1.00 or 10.17, depending on the method of estimation. The time since the two populations were isolated was estimated from Nei's genetic distance as only 150 to 15 000 years, which is consistent with a hypothesis of population collapse during late Pleistocene or Holocene warming. We discuss the implications for conservation.
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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".