Resource partitioning and asymmetric competition between sympatric freshwater and Omono types of ninespine stickleback,<i>Pungitius pungitius</i>
Bibliographic record
Abstract
The freshwater and Omono types of ninespine stickleback, Pungitius pungitius (L., 1758), coexist in several ponds and a stream in the Omono River system, Japan. We tested the hypothesis that coexistence of the two types is accomplished by resource partitioning through interspecific competition. First, the stomach contents of the two types were compared between sympatric and allopatric populations: the stomach contents of the sympatric freshwater type consisted of almost all Copepoda, whereas those of the sympatric Omono type consisted of not only Copepoda, but also many large benthic invertebrates; the stomach contents of both allopatric types were similar, consisting of Copepoda and large benthic invertebrates. Second, behaviour related to resource use in a sympatric pond was observed in the nonbreeding season: the freshwater type showed little aggressive behaviour, but the Omono type had a high frequency of aggressive behaviour. These results indicate that the sympatric freshwater type does not hold a feeding territory and its food resource is almost all Copepoda, whereas the Omono type has a feeding territory and its food resources are various. This suggests that asymmetric interference competition causes a diet shift of the sympatric freshwater type, allowing the two types to coexist by their resource partitioning.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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".