Optimal foraging can drive emergent initiator-follower dynamics in social groups
Data files
Sep 11, 2025 version files 25.16 KB
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Figure1.R
6.67 KB
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Figure2A.R
6.28 KB
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Figure2B.R
1.50 KB
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Figure3_plots.R
2.94 KB
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Figure3_Simulation_overall_code.R
5.61 KB
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README.md
2.15 KB
Abstract
Deciding when and where to move is a challenge for group-living animals as differences in preferences must be resolved for the group to maintain cohesion. In many species, consensus is reached through shared decisions-making, whereby group members initiate group movements by stopping foraging and making directed movements away from a feeding source. Yet, despite being widespread, it is unclear how this initiation process has emerged in animal groups, and theory has yet to resolve the paradox of why some individuals forego foraging to instigate collective movements. By applying theoretical predictions from the marginal value theorem to heterogeneous foraging groups, we show that (i) movement initiations can reduce subsequent within-group conflict over when to depart, (ii) habitat heterogeneity and within-group differences in foraging rate shape who initiates, and (iii) different forms of collective decision-making can emerge under different environmental conditions. These results demonstrate that optimal foraging theory can resolve outstanding questions about leadership in collective movements of animal groups.
Dataset DOI: 10.5061/dryad.w0vt4b95c
Description of the data and file structure
Each file corresponds to one figure. Figure 3 is split into the simulation code (which has the option of saving the data to an RData file) and plotting code (which has the option of loading the simulation outputs from an RData file). All of the code is written in base R with no dependencies, so should run on any R version (tested on R 4.3.0).
Files and variables
File: Figure1.R
Description: R code for Figure 1. This is an illustrative figure that shows the effects of adding waiting time to the predictions of the Marginal Value Theorem.
File: Figure2A.R
Description: R code for Figure 2A. This is an illustrative figure that shows the effects of waiting time on the optimal departure time as predicted by the marginal value theorem.
File: Figure2B.R
Description: R code for Figure 2B. This is an illustrative figure that shows the effects of waiting time and changes in patch quality on the optimal departure time as predicted by the marginal value theorem.
File: Figure3_plots.R
Description: R code for Figure 3 (plotting). This is the code that runs simulations of groups of animals within which individuals vary in size (N), in the variation of foraging rates among group members (between lambda.low and lambda.high), and that experience different environments (proportion.egalitarian.patches and travel.time variables). Groups use threshold for departure (depature.point) that defines how many individuals should have passed their optimal departure time at the point the group departs.
File: Figure3_Simulation_overall_code.R
Description: R code for Figure 3 (simulations). Code for plotting the results from the simulations for Figure 3. This can either take the data currently loaded in R after running the simulations or load these up from a file saved at the end of the previous code.
Code/software
Base R. Tested on 4.3.0. No dependencies or packages are loaded.