Risks for overwintering eggs of the dragonfly Sympetrum vicinum in aquatic and terrestrial environments
Bibliographic record
Abstract
Risk-spreading behaviour is often exhibited by animals as a response to unpredictably variable environments. Using field and laboratory studies, we tested the hypothesis that Sympetrum vicinum dragonflies spread the risks of winter environments by laying eggs across a terrestrial–aquatic gradient. Sympetrum vicinum eggs that overwintered in terrestrial and benthic-limnetic habitats had significantly higher hatching success compared with eggs that overwintered in littoral sites. Low success may have been caused by hypoxia due to excess sediment in the littoral samples in the lab. While hypoxia experienced under winter conditions (4°C) had no negative effect on hatching success, hatching in hypoxic and anoxic water significantly decreased hatching success. Opportunistic egg predation by a winter-active caddisfly significantly decreased egg hatching success. Because S. vicinum eggs have a relatively low supercooling point (− 26.25°C), freezing may not be a significant source of mortality in terrestrial or aquatic sites. By ovipositing in both terrestrial and aquatic environments, female dragonflies may be balancing the unpredictable risks of both the failure to inundate the eggs and egg predation. Our research highlights the potential for biotic interactions during winter to shape the behaviour and life-history of aquatic invertebrates.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.009 |
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".