Behavioral DiverCity: individual differences in behavior change along an urbanization gradient
Bibliographic record
Abstract
Abstract Urbanization is occurring globally at an unprecedented rate and, despite the eco-evolutionary importance of individual variation, we still have limited insight on how phenotypic variation is modified by anthropogenic environmental change. Urbanization can increase individual differences in some contexts, but whether this is generalizable to behavioral traits, which directly affect how organisms interact with, and respond to, environmental variation, is not well known. Here we examined variation across three behavioral traits linked to stress reactivity, anti-predator response, and novelty-coping (breath rate, handling aggression, and exploration behavior) in great tits Parus major along an urbanization gradient. We phenotyped > 1000 individuals across 9 yr, to test whether individual differences in behavior increased with urbanization and spatial environmental heterogeneity. We used two different approaches: a city vs. forest comparison (ie a binary descriptor) and an urbanization gradient approach (ie a continuous quantitative score from 0 to 1) to explore the influence of built-up areas at different spatial scales. Our results reveal that urban individuals display more diverse stress-related and anti-predator behaviors (breath rate and handling aggression), yet show more similarity in their exploratory behavior than forest counterparts. However, there was no evidence that individual variation changes along the percentage of built-up areas for any traits. This study suggest that generalizations about how behavioral traits respond to urbanization will differ across behavioral dimensions. In particular, we may expect decreased individual diversity in urban birds for traits related to behavioral response to novelty.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".