Behavioural, morphological, and life history shifts during invasive spread
Bibliographic record
Abstract
Invasive species are common around the world, but we still do not know which traits are most important for successfully establishing in new environments. Different stages of the invasion process, including transport, introduction, establishment, and spread, can act as selective filters for different combinations of phenotypic traits. Theoretical and empirical studies predict that invasive populations should have suites of behaviours that improve dispersal and spread, including higher boldness, dispersal propensity, and activity levels than native populations. In this study, we tested these predictions by comparing the morphology, life history, and behaviour of an invasive populations of redback spiders, Latrodectus hasselti, from Japan to a population of native spiders from Australia, with additional comparisons of another invasive population from New Zealand. We found that both a longer-established invasive New Zealand population and the more recently-established invasive Japanese population were more dispersive than the native Australian population. The Japanese invasive population showed elevated levels of sibling cannibalism relative to the native population, which may increase total reproductive success of females under food limitation. Japanese spiders were also less bold in response to a simulated predator threat compared to the native Australian population. In contrast to the prediction that invasive populations would show uniformly fast life history traits, the invasive Japanese population was more fecund, yet took longer to develop than the native population under laboratory conditions. Overall, our results show that invasive populations are phenotypically distinct from native populations, with some behavioural, life history, and morphological traits that would increase spread (dispersal tendency, high fecundity) and persistence (sibling cannibalism) in new habitats.
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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".