Do city cachers store less? The effect of urbanization and exploration on spatial memory in individual scatter hoarders
Bibliographic record
Abstract
Urbanization has been shown to affect a variety of traits in animals, including their physiology, morphology, and behaviour, but it is less clear how cognitive traits are modified. Urban habitats contain artificially elevated food sources, such as bird feeders, that are known to affect the foraging behaviours of urban animals. As of yet however, it is not known whether urbanization and the abundance of supplemental food during the winter reduce caching behaviours and spatial memory in scatter hoarders. We aimed to examine individual variation in caching and spatial memory between and within urban and rural habitats to determine i) whether urban individuals cache less frequently and perform less accurately on a spatial task, and ii) explore, for the first time in scatter hoarders, whether slower explorers perform more accurately on a spatial task, indicating a speed-accuracy trade-off within individuals. We assessed spatial memory of wild-caught black-capped chickadees ( Poecile atricapillus ; N = 96) from 14 sites along an urban gradient. While the individuals that cached more food in captivity were all from rural environments, we find no clear evidence that caching intensity and spatial memory accuracy differ along an urban gradient, and find no significant relationship between spatial cognition and exploration of a novel environment within individuals. However, individuals that performed more accurately also tended to cache more frequently, suggesting for the first time that the specialization of spatial memory in scatter hoarders may also occur at the level of the individual in addition to the population and species levels.
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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 | 0.001 |
| 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".