  Many foraging animals find food using composite random search strategies,
which consist of intensive and extensive search modes. Models of composite
search can generate predictions about how optimal foragers should behave in
each search mode, and how they should determine when to switch between search
modes. Most of these models assume that foragers use resource encounters to
decide when to switch between search modes. Empirical observations indicate
that a variety of organisms use non-directional sensory cues to identify areas
that warrant intensive search. These cues are not precise enough to allow a
forager to directly orient itself to a resource, but can be used as a criterion
to determine the appropriate search mode. As a potential example, a forager
might use olfactory information, which could help it determine if an area is
worth searching carefully. We developed a model of composite search based on
non-directional sensory cues. With simulations, we compared the search
efficiencies of composite foragers that use resource encounters as their
mode-switching criterion with those that use non-directional sensory cues. We
identified optimal search patterns and mode-switching criteria on a variety of
resource distributions, characterized by different levels of resource
aggregation and density. On all resource distributions, foraging strategies
based on the non-directional sensory criterion were more efficient than those
based on the resource encounter criterion. Strategies based on the
non-directional sensory criterion were also more robust to changes in resource
distribution. Our results suggest that current assumptions about the role of
resource encounters in models of optimal composite search should be
re-examined. The search strategies predicted by our model can help bridge the
gap between random search theory and traditional patch-use foraging theory.
