Computer simulations challenge the Lévy Foraging Hypothesis and advocate for a cognitive forager model.
• Lévy Foraging Hypothesis assumes sparce food locations, instant renewal of consumed food and clueless memory-less foragers. • It assumes foragers adopt randomly directed steps and step lengths with Lévy probability P( ℓ)= aℓ −µ with 1<µ≤3. • It predicts foragers will adopt the optimal value of µ=2 which maximises rate of food encounter and finds general agreement. • This prediction results from modelling artefacts and the LFH should be replaced with a revamped cognitive forager approach. The Lévy Foraging Hypothesis (LFH) posits that an organism, searching optimally for sparsely and randomly distributed locations of food or other resources, that are instantly renewed after consumption, will adopt a simple random walk with step lengths determined by a Lévy probability distribution with optimal exponent µ equal to 2, from possible values 1< µ≤3. However, computer simulations based on this model reveal that this hypothesis arises because of two artefactual processes, both of which occur as µ increases from 1 to 3. The first is an increase in quick immediate revisits to food locations (i.e., revisits to food locations after few intervening steps and hence quick; and no intervening visits to food locations and thus immediate) that happen to be near one another. The second is an increase in path resurveying. These artefactual processes tend to increase and decrease the rate of food intake respectively. These processes are easily altered or eliminated by slight modelling modifications, which result in the optimal µ changing or disappearing, thus demonstrating that the LFH results from a model artefact. This reinforces the call for the LFH to be abandoned in favour of Optimal Foraging Theory with a cognitive forager approach to movement ecology.
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Pyke et al. (2026) studied this question.
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