Living in isolation: ecological, demographic and genetic patterns in northern Australia’s top marsupial predator on Koolan Island
Bibliographic record
Abstract
Koolan Island supports an abundant population of the threatened northern quoll (Dasyurus hallucatus). We used a mark–release–recapture program that produced 2089 captures from 2009 to 2012 to examine demographic and genetic parameters in this insular population and compare to other localities. Every captured female was either lactating or carrying up to eight young over the breeding season, July–September. Unlike several other populations, males on Koolan Island can survive long after breeding, but never into a second breeding season. Females can survive and reproduce for two successive annual breeding seasons and occasionally survive to a third. There is marked sexual dimorphism but it is less pronounced, and both sexes are smaller than their mainland counterparts. Quolls were recorded moving over 4 km and apparent abundance was far higher on Koolan Island than the mainland. Genetic analyses of nuclear and mitochondrial markers demonstrate a distinctive signature. Koolan island has only 34% of the allelic richness of the entire species, and only 38% of the alleles in Kimberley mainland and near-shore island populations. There is no evidence of recent or long-term population decline. Kimberley island faunas have distinctive demographic and genetic profiles that should be appraised before considering translocations for conservation purposes.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".