Density-Dependent Cannibalism in Dragonfly Nymphs (Odonata: Anisoptera) Overwintering in Temperate Freshwater Ponds
Bibliographic record
Abstract
Density-dependent mortality by predation and cannibalism has been observed in aquatic insects such as dragonflies in response to shrinking habitat caused by summer drought. Winter conditions might also reduce the amount of livable habitat in temperate ponds and could augment rates of cannibalism. We hypothesized that cannibalism in dragonfly nymphs would increase in winter due to a seasonal decrease in available habitat caused by stratified lower oxygen levels leading to increased nymph density around pond edges. To determine whether cannibalism in nymphs is density-dependent and size-dependent (i.e., with smaller nymphs consumed) we experimentally manipulated nymph density in aquaria. To evaluate whether these patterns are observed in nature during the winter, we conducted field surveys for nymphs in two ponds across the fall and winter seasons. When nymphs were housed at different densities for 24 h, cannibalism was density-dependent, and only smaller nymphs were preyed upon. Our field surveys found that fewer nymphs were caught in the late winter sampling period (mixed-effects model, P < 0.001), and that these were larger than nymphs caught in the fall, although both patterns were restricted to the deeper pond (P < 0.05). Our results were consistent with the process we hypothesized, and the observed reduction in dissolved oxygen at the bottom of the deeper pond. The lack of significant changes to the relative abundance and size of nymphs in the shallower pond reveals that differences in pond characteristics can influence the degree to which winter conditions induce density-dependent cannibalism among dragonfly nymphs.
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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".