Age and Growth of An Outbreaking Acanthaster cf. solaris Population within the Great Barrier Reef
Bibliographic record
Abstract
Despite having been studied for more than 40 years, much about the basic life history of crown-of-thorns starfish (CoTS; Acanthaster spp.) remains poorly understood. Size at age—a key metric of productivity for any animal population—has yet to be clearly defined, primarily due to difficulties in obtaining validated ages and potentially indeterminate growth due to factors such as starvation; within-population variability is entirely unknown. Here we develop age and growth estimates for an outbreaking CoTS population in Australian waters by integrating prior information with data from CoTS collected from multiple outbreaking reefs. Age estimates were made from un-validated band counts of 2038 individual starfish. Results from our three-parameter von Bertalanffy Bayesian hierarchical model show that, under 2013–2014 outbreak conditions, CoTS on the GBR grew to a 349 (326, 380) mm (posterior median (95% uncertainty interval)) total diameter at a 0.54 (0.43, 0.66) intrinsic rate of increase. However, we also found substantial evidence (ΔDIC > 200) for inter-reef variability in both maximum size (SD 38 (19, 76)) and intrinsic rate of increase (SD 0.32 (0.20, 0.49)) within the CoTS outbreak initiation area. These results suggest that CoTS demography can vary widely with reef-scale environmental conditions, supporting location-based mechanisms for CoTS outbreaks generally. These findings should help improve population and metapopulation models of CoTS dynamics and better predict the potential damage they may cause in the future.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| 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".