Raw data from: Consumer-resource interactions along urbanization gradients drive natural selection
Bibliographic record
Abstract
Urbanization is an important component of global change. Urbanization affects species interactions, but the evolutionary implications are rarely studied. We investigate the evolutionary consequences of a common pattern: the loss of high trophic-level species in urban areas. Using a gall-forming fly, Eurosta solidaginis, and its natural enemies that select for opposite gall sizes, we test for patterns of enemy loss, selection, and local adaptation along five urbanization gradients. Eurosta declined in urban areas, as did predation by birds, which preferentially consume gallmakers that induce large galls. These declines were linked to changes in habitat availability, namely reduced forest cover in urban areas. Conversely, a parasitoid which attacks gallmakers that induce small galls was unaffected by urbanization. Changes in patterns of attack by birds and parasitoids resulted in stronger directional selection, but loss of stabilizing selection in urban areas, a pattern which we suggest may be general. Despite divergent selective regimes, gall size did not very systematically with urbanization, suggesting but not conclusively demonstrating that environmental differences, gene flow, or drift, may have prevented the adaptive divergence of phenotypes. We argue that the evolutionary effects of urbanization will have predictable consequences for patterns of species interactions and natural selection.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.031 | 0.022 |
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".