Paternity and relatedness of American black bears recolonizing a desert montane island
Bibliographic record
Abstract
American black bears (Ursus americanus (Pallas, 1780)) are characterized by female philopatry and male-biased dispersal, with predictable consequences for genetic structure of populations. We studied a recolonizing population of black bears on a desert montane island to test genetic-based predictions of bear social behavior. We assessed genetic paternity and relatedness among bears within Big Bend National Park, Texas, from 1998 to 2001 via maternally and biparentally inherited markers and field observations. Data from seven microsatellite loci permitted us to assign paternity for 7 of 12 cubs, and multiple paternity was revealed in one litter. Levels of relatedness in the Park were comparable to those found in a nearby large population in Coahuila, Mexico. Adult female bears in the Park were more closely related to each other than males were to each other. Microsatellite data were consistent with previous analyses of mtDNA sequences that indicated bears in the Mexico-Texas metapopulation exhibit male-biased dispersal. Demographic and genetic data provided a pedigree for 23 of 31 sampled bears and depicted the matriarchal structure of this recently recolonized population. Although females in this insular population are closely related to each other, as predicted by characteristics of ursine social ecology, incoming dispersal by unrelated males results in periodic supplementation of genetic variation.
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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 | 0.000 | 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 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".