Population connectivity across east Australia's bioregions and larval duration of the range‐extending sea star<scp><i>Meridiastra calcar</i></scp>
Bibliographic record
Abstract
Abstract The diversity and distribution of marine species in eastern Australia is influenced by one of the world's strongest western boundary currents, the East Australia Current, which propels water and propagules poleward, a flow intensifying due to climate change. Population genetic structure of the asterinid sea starMeridiastra calcarwas investigated across its range in eastern Australia (12° of latitude, 2,500 km) from northern New South Wales to its poleward‐extending range in Tasmania at the southern edge influence of the East Australia Current. Population structure and connectivity ofM. calcarwere examined across six bioregions using six microsatellite loci (nuclear DNA) and the control region (mitochondrial DNA). The potential influence of the extent ofM. calcar's intertidal rock platform habitat was also assessed. Genetic structure analysis indicated that the Hawkesbury Shelf contained distinct genetic clusters, whereas the two sites in the Batemans Shelf differed from each other, with Jervis Bay Marine Park having just one genetic cluster. The Manning Shelf, Twofold Shelf, and Bruny bioregions all had similar genetic composition. Strong self‐seeding (68–98%) was indicated by microsatellite loci for all bioregions, with lower (0.3–6.5%) migration between bioregions. Poleward (New South Wales to Tasmania) migration was low except from the Manning Shelf (30%). Contemporary population connectivity and genetic structure ofM. calcarappear to be influenced by ocean currents, habitat distribution, and its short planktonic larval duration, which was a minimum of 12–14 days, depending on availability of a settlement cue. The dominance of unique genetic groups in the Hawkesbury bioregion shows the importance of this region forM. calcarand possibly a diversity of co‐distributed rock platform species. This highlights how important it is to have a large marine park in the Hawkesbury bioregion, which is presently lacking.
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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) | 0.001 | 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".