Foraging in a hierarchical patch system

This study presents a model of a forager searching for prey in a stochastic hierarchical patch system where high-density patches at small scales are nested within low-density patches at larger scales. In order to track the system, the forager uses long travel distances within large-scale patches and short travel distances within small-scale patches. The forager estimates its position in the system according to recent experience and changes its search pattern accordingly. The scaling of the prey system was adapted according to marine pelagic systems of krill and schooling fish, and a forager was simulated for varying prey abundance and prey aggregation. The model suggests that tracking efficiency, defined as the forager's mean position within the system, increases for increasing prey abundance. Furthermore, the model suggests that maximum tracking efficiency is found at intermediate prey aggregations and that tracking efficiency decreases for aggregations above and below this point. The model demonstrates that a well-structured hierarchical patch system with high general prey density might potentially increase the information flow and, hence, the tracking efficiency of a predator. It is suggested that these results might be applicable to a wide array of systems where predators track unpredictable hierarchical patch systems.