Urbanization alters ecological and evolutionary interactions between Darwin’s finches and <i>Tribulus cistoides</i> on the Galápagos Islands
Bibliographic record
Abstract
Abstract Emerging evidence suggests that urbanization shapes the ecology and evolution of species interactions. Islands are particularly susceptible to urbanization due to the fragility of their ecosystems; however, few studies have examined the effects of urbanization on species interactions on islands. To address this gap, we studied the effects of urbanization on interactions between Darwin’s finches and its key food resource, Tribulus cistoides , in three towns on the Galápagos Islands. We assessed the effects of urbanization on seed and mericarp removal, mericarp morphology, and finch community composition using natural population surveys, experimental manipulations, and finch observations. We found that both seed and fruit removal rates were higher in urban compared to non-urban populations in the natural and experimental populations, and that urbanization modified selection on mericarp size and defense. Urban environments supported smaller and less diverse finch communities than non-urban environments. Together, our results suggest that urbanization can dramatically alter ecological interactions between Darwin’s finches and T. cistoides , leading to modified selection on T. cistoides populations. Our study demonstrates that urban development on islands can have profound effects on the ecology and evolution of trophic interactions.
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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 | 0.001 |
| 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".