Do interspecific differences in morphology influence foraging efficiency of juvenile crappie?
Bibliographic record
Abstract
Sympatric black crappie ( Pomoxis nigromaculatus Lesueur in Cuvier and Valenciennes, 1829) and white crappie ( Pomoxis annularis Rafinesque, 1818) often differ in ecological performance, such that white crappie outnumber black crappie in turbid waterbodies and black crappie predominate in clear waters with abundant cover. Recent work suggests that this performance difference is driven by juvenile white crappie having a limnetic body form and juvenile black crappie having a littoral body form, resulting in differential predation mortality between the species within open-water and vegetated environments. We tested whether these morphologies also lead to interspecific differences in foraging efficiency between the congeners in structure and open water. Juvenile black crappie spent more time pursuing fish prey than white crappie across all trials, suggesting that energetic gains of piscivory may differ between species. However, both species had similar capture efficiencies when attacking fathead minnows ( Pimephales promelas Rafinesque, 1820) within vegetated and open-water habitats. We conclude that variation in morphology between juvenile black crappie and white crappie does not have a large influence on foraging efficiency, at least on fish prey, in dense cover or open water, and suggest their performance in sympatry is likely not driven by predatory capabilities at the onset of piscivory within these different environmental contexts. Instead, the relationship between morphology and predator evasion may drive the distribution and relative abundance of crappie species within sympatric populations.
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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 | 0.000 | 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) | 0.001 | 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".