Vulnerability of threatened Australian humpback dolphins to flooding and port development within the southern Great Barrier Reef coastal region
Bibliographic record
Abstract
In this study, we used a 10-year (2007–2016) mark-recapture dataset to investigate the potential effects of flooding and port development on the population dynamics of Australian humpback dolphins (Sousa sahulensis), inhabiting the Fitzroy River and Port Curtis, within the southern Great Barrier Reef region. A Multisite Capture-Recapture model was used to quantify population size and demographic parameters for both sexes and sites. Flood occurrence and intensity (both sites), and port development (Port Curtis) were included as explanatory variables. Abundance estimates indicated that about 77 adult dolphins were present in both sites, of which 69% were females. Most females (69%) were resident with a yearly recruitment close to zero for most years. Most males and unsexed (68%) individuals showed little evidence of long-term residency. The abundances of males and unsexed individuals varied between 15 and 20 dolphins in the Fitzroy River and 19–26 in Port Curtis, but the accuracy was too low to assess changes. Female abundances started at 56 in both sites and declined to about 32 per site in 2011, coinciding with port development construction activities and a concurrent major flood. In Port Curtis, the number of females returned to their original levels once the port development was completed in 2013. In the Fitzroy River, the declining trend continued and reached the lowest estimated abundance of 29 in 2016. As port developments and floods are expected to increase along the Queensland coastal region over coming decades, the results of this study highlight increasing concerns about the vulnerability and long-term sustainability of inshore dolphins in the GBR.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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".