Population structure of an endemic vulnerable species, the Jamaican boa (<i>Epicrates subflavus</i>)
Bibliographic record
Abstract
The Jamaican boa (Epicrates subflavus; also called Yellow boa) is an endemic species whose natural populations greatly and constantly declined since the late 19th century, mainly because of predation by introduced species, human persecution, and habitat destruction. In-situ conservation of the Jamaican boa is seriously hindered by the lack of information on demographic and ecological parameters as well as by a poor understanding of the population structure and species distribution in the wild. Here, using nine nuclear microsatellite loci and a fragment of the mitochondrial cytochrome b gene from 87 wild-born individuals, we present the first molecular genetic analyses focusing on the diversity and structure of the natural populations of the Jamaican boa. A model-based clustering analysis of multilocus microsatellite genotypes identifies three groups that are also significantly differentiated on the basis of F-statistics. Similarly, haplotypic network reconstruction methods applied on the cytochrome b haplotypes isolated here identify two well-differentiated haplogroups separated by four to six fixed mutations. Bayesian and metaGA analyses of the mitochondrial data set combined with sequences from other Boidae species indicate that rooting of the haplotypic network occurs most likely between the two defined haplogroups. Both analyses (based on nuclear and mitochondrial markers) underline an Eastern vs. (Western + Central) pattern of differentiation in agreement with geological data and patterns of differentiation uncovered in other vertebrate and invertebrate Jamaican species. Our results provide important insights for improving management of ex-situ captive populations and for guiding the development of proper in-situ species survival and habitat management plans for this spectacular, yet poorly known and vulnerable, snake.
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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 | 0.000 | 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) | 0.001 | 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".