Defining ecological roles of sharks on coral reefs
Bibliographic record
Abstract
Sharks have often been perceived to play a critical role in the dynamics of coral reef ecosystems globally. Yet, there is relatively little evidence to support this idea across all but a limited set of species and contexts. Research on the roles and importance of reef sharks has been complicated by logistical challenges in collecting data on sharks compounded by widespread declines in shark populations and reef state due to anthropogenic stressors. However, a better understanding of ecological roles is essential to uncover when, where, how, and to what degree sharks contribute to the function of coral reefs. To address this lack of understanding, we present a standardized framework for determining the ecological roles of reef sharks, including how different streams of data related to movement ecology, trophic ecology, demographics, and ecological context can be combined within specific functional components that collectively define the ecological roles of reef sharks. A series of steps and questions are used to guide research on individual species and promote collection of necessary data. We explore what data in real-world examples can mean for uncovering roles and how data can be interpreted from a functional perspective. Although the framework is centred around breaking down ecological roles into simpler components, it forces researchers to complete a comprehensive evaluation of the animal's ecology and consider how data from each of these components complements each other in a broader context. The need for a detailed and directed approach for researchers to explore the mechanisms, patterns, and causes that comprise reef shark ecological roles is supported by a literature review showing expansive knowledge gaps that persist for most coral-reef-resident and smaller-bodied species. Existing research on the movement and trophic ecology of reef sharks is diverse and spans a broad range of topics and contexts, indicating potential for combining and re-evaluating existing data to improve current knowledge of roles. Resident species with relatively large amounts of published research included grey reef (Carcharhinus amblyrhynchos), blacktip reef (Carcharhinus melanopterus), and whitetip reef sharks (Triaenodon obesus), which are among the most widely abundant sharks on coral reefs. As ongoing changes to coral reefs may alter rates of ecological processes, understanding the roles and importance of reef sharks will be crucial to predicting future reef states and enacting effective conservation and management strategies to preserve key functions.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".