Pollen gene flow and molecular identification of full-sib families in small and isolated population fragments of <i>Gleditsia triacanthos</i> L.
Bibliographic record
Abstract
To analyze the utility of isolated remnant populations for full-sibling (full-sib) identification among open-pollinated single-tree progeny in the outcrossing and insect-pollinated tree Gleditsia triacanthos L. (honey locust), we performed paternity analyses in forest fragments from two geographic regions using nuclear microsatellites. The first plot (Butternut Valley population) comprised only 7 trees, and 552 seedlings from a single seed parent were characterized at nuclear microsatellites. A large number of putative pollen donors (59) were identified in kinship analyses, but their individual contributions to the progeny were highly variable. Kinship and paternity analyses identified 149 putative full-sibs for genetic mapping sired by an external (unsampled) pollen parent. To better assess the frequency of long-distance pollen dispersal, a total of 180 seeds were collected from 6 seed parents in another fragmented population. In both plots, contemporary pollen dispersal occurred generally from outside the plots (99.38% and 87.50%–100% at the Butternut Valley and Ames Plantation sites, respectively) and thus over very long distances (>12 000 m in the Ames Plantation) suggesting that in highly fragmented landscapes, insect pollinators of honey locust are likely very effective long-distance dispersers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 teacher head, 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".