Abiotic conditions rather than resource availability cues determine aerial dispersal behaviour in spiderlings of <i>Dolomedes triton</i> (Araneae: Pisauridae)
Bibliographic record
Abstract
Abstract Many species respond to risks and benefits of dispersal that vary over the short term through condition-dependent dispersal. We used wind tunnels to investigate how abiotic factors, spiderling age, and indicators of environmental quality affect aerial dispersal behaviour of spiderlings in Dolomedes triton (Walckenaer) (Araneae: Pisauridae), a denizen of temporary habitats. More than half of all spiderlings exhibited preballooning, ballooning, or spanning behaviours. Warm temperatures (>22.5 °C) and low wind speeds (<2.0 m/second) increased aerial dispersal. Aerial dispersal behaviour increased significantly until 5 days after hatch, after which it decreased, coinciding with the onset of active hunting by spiderlings. In contrast, cues about ambient food availability (egg sac number and food limitation of the mother) and potential resource competition or risk of cannibalism (conspecific density) did not affect aerial dispersal propensity. Offspring from different females ballooned in different proportions, except at the peak of dispersal, but a female's reproductive output and propensity of her offspring to balloon were uncorrelated. Thus, it appears that spiderlings of D. triton adopt a fixed strategy of high dispersal rate under optimal abiotic conditions, rather than reducing dispersal in response to cues about local food availability or conspecific density.
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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 | 0.000 | 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".