Tit wit: environmental and genetic drivers of cognitive variation along an urbanization gradient
Bibliographic record
Abstract
Abstract Cognitive abilities can promote acclimation to life in cities. However, the genetic versus environmental drivers of cognition have rarely been studied in the wild and there exists a major knowledge gap concerning the role of cognition in adaptation to urban contexts. We evaluate cognitive variation in wild great tits ( Parus major ; N = 393) along an urban gradient, and estimate the genetic basis of this variation using a combination of a common garden experiment, quantitative genetic analysis, and genome-wide association study. Specifically, we measure inhibitory control abilities which affect how animals respond to novel challenges. We find that wild urban and forest tits do not clearly differ in inhibitory control performance (number of errors or the latency to escape) during a motor detour task; a result that was consistent in birds from urban and forest origins reared in a common garden ( N = 73) despite average performance differing between wild and captive birds. Cognitive performance was repeatable ( R = 0.35–0.38) and showed low to moderate heritability in the wild ( h 2 = 0.16–0.28, but both estimates had high uncertainty). We identified five SNPs that were associated with the number of errors during the task, with two of these SNPs linked to genes related to serotonergic and dopaminergic systems that are known to play important roles in cognition. Altogether, our study finds limited evidence that inhibitory control abilities have evolved under novel urban contexts, yet reveals some evidence for a genetic basis of this cognitive trait in great tits.
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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 | 0.000 |
| 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) | 0.000 | 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".