Cognition and covariance in the producer–scrounger game Article Swipe
Michael S. Reichert
,
Julie Morand‐Ferron
,
Ipek G. Kulahci
,
Josh A. Firth
,
Gabrielle L. Davidson
,
Samuel Crofts
,
John L. Quinn
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1111/1365-2656.13551
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1111/1365-2656.13551
The producer–scrounger game is a key element of foraging ecology in many systems. Producing and scrounging typically covary negatively, but partitioning this covariance into contributions of individual plasticity and consistent between individual differences is key to understanding population‐level consequences of foraging strategies. Furthermore, little is known about the role cognition plays in the producer–scrounger game. We investigated the role of cognition in these alternative foraging tactics in wild mixed‐species flocks of great tits and blue tits, using a production learning task in which we measured individuals’ speed of learning to visit the single feeder in an array that would provide them with a food reward. We also quantified the proportion of individuals’ feeds that were scrounges (‘proportion scrounged’); scrounging was possible if individuals visited immediately after a previous rewarded visitor. Three learning experiments—initial and two reversal learning—enabled us to estimate the repeatability and covariance of each foraging behaviour. First, we examined whether individuals learned to improve their scrounging success (i.e. whether they obtained food by scrounging when there was an opportunity to do so). Second, we quantified the repeatability of proportion scrounged, and asked whether proportion scrounged affected production learning speed among individuals. Third, we used multivariate analyses to partition within‐ and among‐individual components of covariance between proportion scrounged and production learning speed. Individuals improved their scrounging success over time. Birds with a greater proportion scrounged took longer to learn their own rewarding feeder. Although multivariate analyses showed that covariance between proportion scrounged and learning speed was driven primarily by within‐individual variation, that is, by behavioural plasticity, among‐individual differences also played a role for blue tits. This is the first demonstration of a cognitive trait influencing producing and scrounging in the same wild system, highlighting the importance of cognition in the use of alternative resource acquisition tactics. The results of our covariance analyses suggest the potential for genetic differences in allocation to alternative foraging tactics, which are likely species‐ and system‐dependent. They also point to the need to control for different foraging tactics when studying individual cognition in the wild.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1111/1365-2656.13551
- https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/1365-2656.13551
- OA Status
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- Cited By
- 16
- References
- 64
- Related Works
- 10
- OpenAlex ID
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- DOI
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https://doi.org/10.1111/1365-2656.13551Digital Object Identifier
- Title
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Cognition and covariance in the producer–scrounger gameWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2021Year of publication
- Publication date
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2021-06-06Full publication date if available
- Authors
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Michael S. Reichert, Julie Morand‐Ferron, Ipek G. Kulahci, Josh A. Firth, Gabrielle L. Davidson, Samuel Crofts, John L. QuinnList of authors in order
- Landing page
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https://doi.org/10.1111/1365-2656.13551Publisher landing page
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https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/1365-2656.13551Direct link to full text PDF
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YesWhether a free full text is available
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bronzeOpen access status per OpenAlex
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https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/1365-2656.13551Direct OA link when available
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Foraging, Covariance, Biology, Cognition, Multivariate statistics, Ecology, Cognitive psychology, Psychology, Statistics, Mathematics, NeuroscienceTop concepts (fields/topics) attached by OpenAlex
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16Total citation count in OpenAlex
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2025: 4, 2024: 3, 2023: 4, 2022: 3, 2021: 2Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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| cited_by_percentile_year.max | 98 |
| cited_by_percentile_year.min | 93 |
| corresponding_author_ids | https://openalex.org/A5041307314 |
| countries_distinct_count | 4 |
| institutions_distinct_count | 7 |
| corresponding_institution_ids | https://openalex.org/I115475287, https://openalex.org/I27577105 |
| citation_normalized_percentile.value | 0.93104431 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |