Environmental quality determines finder-joiner dynamics in socially foraging three-spined sticklebacks (Gasterosteus aculeatus)
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Animals that forage in groups have access to social information concerning the quality and location of food resources available. The degree to which individuals rely on social information over their own private information depends on a myriad of ecological and social factors. In general, where resources are patchy in space and/or time, individuals that use social information and join others at previously identified food patches can reduce both search times and the variance in finding food. Here, we explore social foraging dynamics of shoals of three-spined sticklebacks (Gasterosteus aculeatus) and investigate when fish tend to use private information and find food themselves, or rely on social information and attend to the food discoveries of others. We show that fish’s allocation to alternative foraging tactics (i.e. finding or joining) can be explained by environmental quality. In environments with large food patches, fish experience a reduced finder’s share and tend to adopt joining foraging tactics; in environments with small food patches, fish rely on private information and tend to discover their own food patches. However, we found that finding and joining do not result in equal foraging returns as predicted by theory, and instead payoffs were higher for fish adopting finding tactics in all environments we studied. These unequal payoffs may be explained, in part, by consistent inter-individual differences in the amount of food fish consumed per foraging event and by heavier fish consuming more food. Overall, our simple experimental approach suggests that socially foraging three-spined sticklebacks do show a degree of behavioural flexibility that enables them to efficiently exploit food patches under a range of environmental conditions.
Statement of significance
Animals must continually make decisions to secure resources to survive and reproduce; however, inherent variability in the spatio-temporal distribution of resources means that the best decision is not fixed. How do animals ensure they respond effectively to variation? For animals that live and forage in groups, how do environmental conditions determine whether they use private information or social information to meet these challenges? These are important questions in behavioural ecology and have great significance to animals’ ability to deal with unheralded environmental change. Here, we show empirically that three-spined sticklebacks flexibly and adaptively switch between behavioural tactics to acquire foraging resources in accordance with the abundance and distribution of forage in their environment, establishing a new model system to extend and build our understanding of social foraging dynamics and how animal groups optimally function in a variable world.
KeywordsFinder-joiner dynamics Social foraging Information sharing Three-spined sticklebacks
The authors would like to thank two anonymous reviewers whose comments greatly enhanced the manuscript.
Compliance with ethical standards
All applicable international, national and/or institutional guidelines for the care and use of animals were followed, and experiments were approved by Swansea University Ethics Committee (Reference IP-1213-3).
This work was supported by a German Research Foundation Fellowship (DFG; FU-985/1-1) awarded to IF, and a Natural Environment Research Council (NE/H016600/3) Fellowship awarded to AJK.
- Bates D, Mächler M, Bolker B, Walker S (2014) Fitting linear mixed-effects models using lme4. arXiv preprint arXiv:14065823Google Scholar
- Beauchamp G (2013) Social predation: how group living benefits predators and prey. Elsevier, LondonGoogle Scholar
- Giraldeau L-A, Caraco T (2000) Social foraging theory. Princeton University Press, PrincetonGoogle Scholar
- Giraldeau L-A, Livoreil B (1998) Game theory and social foraging. In: Dugatkin LA, Reeve HK (eds) Game theory and animal behavior, 1st edn. Oxford University Press, New York, pp 16–37Google Scholar
- R Development Core Team (2014) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, AustriaGoogle Scholar