An assessment of the distribution and abundance of dugongs and large in-water turtles in Cleveland Bay and adjacent bays to provide baseline information for the Port of Townsville Channel Upgrade Project: a report for the Port of Townsville Limited
Bibliographic record
Abstract
We conducted standarised aerial surveys of Bowling Green, Cleveland and southern Halifax Bays to assess the distribution and abundance of dugongs and in-water large marine turtles in winter (June) and early summer (November) 2019, prior to the start of the capital dredging for the Port of Townsville Channel Upgrade (CU) project. The aerial surveys design used here was developed for regional scale surveys and the precision of the population estimates at a local scale is low. Comparison of the results of the 2019 surveys with the results of similar surveys conducted by Marsh’s team at JCU, as part of their long-term series of regional surveys, confirmed marked inter-annual differences in the estimated dugong population in Cleveland-southern Halifax Bays. These differences reflect temporal variations in the status of seagrass in the region as revealed by the annual surveys conducted by the JCU Seagrass Ecology Group since 2007. The estimate of relative abundance of dugongs in the survey region in November 2019 was ~500 (+ se 140). Detecting the local-scale impacts of a development on dugongs and large turtles in a construction timeframe is likely to be impossible, unless the impact of the development on the animals is catastrophic. Consequently, it would be more useful for the Port Authority of Townsville to fund research on marine megafauna and proxy studies on water quality and seagrass rather than to attempt to monitor the direct impacts of the CU project on megafauna. Such studies have the potential to inform management of long-term impacts on the megafauna in the face of extreme weather events.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 teacher head, 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".