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Table 1.

Parameters used in the foraging model and values for simulations.

Because units are arbitrary in the simulations, L is used for generic length units and T is used for generic time units.

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Table 1 Expand

Table 2.

Spatial kernels used in the foraging model.

𝒩2 is the bivariate normal distribution and I is the 2 × 2 identity matrix.

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Table 2 Expand

Table 3.

Behavioral states in the model and corresponding movement process parameters.

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Table 3 Expand

Fig 1.

Sample generated landscapes for different combinations of patch concentration from patchy to smooth and patch size from small to large.

Color indicates resource quality from none (white) to low (light green) to high (dark green). Total resources in each landscape are the same.

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Fig 1 Expand

Fig 2.

Sample trajectories for three movement models (left to right) on two different landscapes (top to bottom).

Trajectories start at the center with color changing through time (from green to light blue to dark blue). For memory and kinesis, thin lines indicate searching and thick lines indicate feeding behavior. Resources are shown at their undepleted level at the beginning of the simulation. Memory is parameterized with best overall parameters, ϕL = 1e − 05, ϕS = 0.01, ψM = 2, γZ = 10.

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Fig 2 Expand

Fig 3.

Consumption for the three movement models across different landscape parameters patch concentration μQ and size γQ for medium regeneration rate βR = 0.01.

Bars show mean consumption values across replicates of landscape parameters while lines show minimum and maximum. Memory is parameterized with best overall parameters, ϕL = 1e − 05, ϕS = 0.01, ψM = 2, γZ = 10. In the figure, M = memory, K = kinesis, R = random walk.

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Fig 3 Expand

Table 4.

Best performing memory parameters (ϕL, ϕS, ψM, γZ) for each landscape environment, a combination of regeneration rate (βR), patch concentration (μQ), and patch size (γQ).

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Table 4 Expand

Table 5.

Permutation importance scores (mean decrease in accuracy) calculated using random forests for the memory model.

Results shown treat parameters as continuous variables. Results were similar when parameters were treated as categorical.

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Table 5 Expand

Fig 4.

Time spent in areas of different resource quality across different landscape parameters patch concentration μQ and size γQ for medium regeneration rate βR = 0.01 compared to the distribution of resources on the landscape.

White represents zero resources while shades of gray from light to dark show quartiles of increasing quality. The memory model is parameterized with best overall parameters, ϕL = 1e − 05, ϕS = 0.01, ψM = 2, γZ = 10. In the figure, M = memory, K = kinesis, R = random walk, L = landscape.

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Fig 4 Expand

Fig 5.

Time spent searching (as opposed to feeding) for memory and kinesis models across different landscape parameter values for patch concentration μQ and size γQ for medium regeneration rate βR = 0.01 as a violin plot showing median values and kernel density plot.

The memory model is parameterized with best overall parameters, ϕL = 1e − 05, ϕS = 0.01, ψM = 2, γZ = 10. In the figure, M = memory, K = kinesis.

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Fig 5 Expand