Non‐additive effects of simulated heat waves and predators on prey phenotype and transgenerational phenotypic plasticity
Bibliographic record
Abstract
Understanding the effects of extreme climatic events on species and their interactions is of paramount importance for predicting and mitigating the impacts of climate change on communities and ecosystems. However, the joint effects of extreme climatic events and species interactions on the behaviour and phenotype of organisms remain poorly understood, leaving a substantial gap in our knowledge on the impacts of climatic change on ecological communities. Using an aphid-ladybeetle system, we experimentally investigated the effects of predators and heat shocks on prey body size, microhabitat use, and transgenerational phenotypic plasticity (i.e., the asexual production of winged offspring by unwinged mothers). We found that (i) aphids were smaller in the presence of predators but larger when exposed to frequent heat shocks; (ii) frequent heat shocks shifted aphid distribution towards the plant's apex, but the presence of predators had the opposite effect and dampened the heat-shock effects; and (iii) aphids responded to predators by producing winged offspring, but heat shocks strongly inhibited this transgenerational response to predation. Overall, our experimental results show that heat shocks inhibit phenotypic and behavioural responses to predation (and vice versa) and that such changes may alter trophic interactions, and have important consequences on the dynamics and stability of ecological communities. We conclude that the effects of extreme climatic events on the phenotype and behaviour of interacting species should be considered to understand the effects of climate change on species interactions and communities.
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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".