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 n
ested within low-density patches at larger scales. In order to track the sy
stem, the forager uses long travel distances within large-scale patches and
short travel distances within small-scale patches. The forager estimates i
ts position in the system according to recent experience and changes its se
arch pattern accordingly. The scaling of the prey system was adapted accord
ing to marine pelagic systems of krill and schooling fish, and a forager wa
s simulated for varying prey abundance and prey aggregation. The model sugg
ests that tracking efficiency, defined as the forager's mean position withi
n the system, increases for increasing prey abundance. Furthermore, the mod
el 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 hierarc
hical patch system with high general prey density might potentially increas
e the information flow and, hence, the tracking efficiency of a predator. I
t is suggested that these results might be applicable to a wide array of sy
stems where predators track unpredictable hierarchical patch systems.