Predator‐driven behavioural shifts in a common lizard shape resource‐flow from marine to terrestrial ecosystems
Bibliographic record
Abstract
Foraging decisions shape the structure of food webs. Therefore, a behavioural shift in a single species can potentially modify resource-flow dynamics of entire ecosystems. To examine this, we conducted a field experiment to assess foraging niche dynamics of semi-arboreal brown anole lizards in the presence/absence of predatory ground-dwelling curly-tailed lizards in a replicated set of island ecosystems. One year after experimental translocation, brown anoles exposed to these predators had drastically increased perch height and reduced consumption of marine-derived food resources. This foraging niche shift altered marine-to-terrestrial resource-flow dynamics and persisted in the diets of the first-generation offspring. Furthermore, female lizards that displayed more risk-taking behaviours consumed more marine prey on islands with predators present. Our results show how predator-driven rapid behavioural shifts can alter food-web connectivity between oceanic and terrestrial ecosystems and underscore the importance of studying behaviour-mediated niche shifts to understand ecosystem functioning in rapidly changing environments.
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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".