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. 2023 Apr 17;12:e77659. doi: 10.7554/eLife.77659

Figure 4. Foraging frequency scales linearly with empty colony state.

Figure 4.

Foraging frequency was calculated as the inverse of the duration of the forager’s unloading bout in the nest. Unloading bouts were binned into five equally spaced bins of colony state, and the mean and SEM of foraging frequency was calculated for each bin. (A) Experimental data, figure taken from figure 4B of Greenwald et al., 2018. Data was grouped into equally-spaced bins of colony state (n = 57, 39, 28, 26, 26, for bins 1–5, respectively). (B) Data from 200 repeats of the 2D model simulation. Data from all repeats was pooled and grouped into equally-spaced bins of colony state (n = 3869, 4183, 4489, 4895, 6248, for bins 1-5, respectively). (C) Data from 200 repeats of the 1D model simulation. Data from all repeats was pooled and grouped into equally-spaced bins of colony state (n = 1770, 1989, 2222, 2531, 3189, for bins 1-5, respectively).

Figure 4—source data 1. Data from 1D model.
Output data from 200 runs of the 1D agent-based model. The file contains 3 spreadsheets: (1) Forager data. Includes data on the forager’s crop load and position in the nest at every step of the simulation. (2) Trophallaxis data. Includes data on the forager’s and the receiver’s crop loads, and the amount of food transferred at every interaction. (3) Trip data. Aggregated data on each trip of the forager inside the nest, including trip length and forager’s crop load upon exiting.
Figure 4—source data 2. Data from 2D model.
Output data from 200 runs of the 2D agent-based model. Data within the file is as described for the 1D model data. Python code for the agent-based model is available on GitHub (Frankel et al., 2022).