“Perceptual ranges, information gathering, and foraging success in dynamic landscapes”

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William F. Fagan, Eliezer Gurarie, Sharon Bewick, Allison Howard, Robert Steven Cantrell, and Chris Cosner

Modeling perceptual ranges shows foragers can exploit non-local information to improve success in dynamic landscapes

A Mongolian gazelle (Procapra gutturosa) wearing a GPS collar to track its movements over 2+ years. The Eastern Steppes of Mongolia, where this species thrives, are some of the most dynamic and spatiotemporally unpredictable landscapes on the planet.
(Credit: William F. Fagan)

Abstract

How organisms gather and utilize information about their landscapes is central to understanding land-use patterns and population distributions. When such information originates beyond an individual’s immediate vicinity, movement decisions require integrating information out to some perceptual range. Such non-local information, whether obtained visually, acoustically, or via chemosensation, provides a field of stimuli that guides movement. Classically, however, models have assumed movement based on purely local information (e.g., chemotaxis, step-selection functions). Here, we explore how foragers can exploit non-local information to improve their success in dynamic landscapes. Using a continuous time / continuous space model in which we vary both random (diffusive) movement and resource-following (advective) movement, we characterize the optimal perceptual ranges for foragers in dynamic landscapes. Non-local information can be highly beneficial, increasing the spatiotemporal concentration of foragers on their resources up to twofold compared to movement based on purely local information. However, non-local information is most useful when foragers possess both high advective movement (allowing them to react to transient resources) and low diffusive movement (preventing them from drifting away from resource peaks). Non-local information is particularly beneficial in landscapes with sharp (rather than gradual) patch edges and in landscapes with highly transient resources. Read the Article