Communal or competitive? Stable isotope analysis provides evidence of resource partitioning within a communal shark nursery
Bibliographic record
Abstract
Quantifying the diet of sympatric co-occurring predatory species is a challenging task, made more so when investigations attempt to focus on specific age groups. This is the task that confronts efforts to understand dietary resource partitioning among co-occurring juvenile shark species within nursery areas. Here, stable isotope analysis ( 13 C and 15 N) is used to overcome these challenges in describing species dietary resource partitioning strategies within the communal shark nursery area of Cleveland Bay, Queensland, Australia. We analyzed the isotopic composition of 3 distinct tissues, (muscle, blood plasma, and red blood cells), for 7 species of shark and 3 species of large predatory teleost to investigate whether these communal areas support their diverse array of predators without the need for resource partitioning strategies. Clustered 15 N values for all examined species indicated feeding within the same trophic level; however, wide ranging 13 C values denoted exploitation of several primary carbon sources. Our results demonstrate inter-species resource partitioning strategies at work within the examined communal shark nursery, altering the previous interpretation of these areas as resource-rich and/or competitionlimited environments.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".