We develop a model of predators foraging within a single patch, on prey tha
t become temporarily immune to predation (depressed) after detecting a pred
ator. Interference through prey depression occurs because the proportion of
vulnerable prey land hence intake rate) decreases as predator density incr
eases. Predators in our model are not forced to move randomly within the pa
tch, as is the case in other similar models, but can avoid areas of depress
ed prey and so preferentially forage over vulnerable prey. We compare the e
xtent to which different avoidance rules (e.g., move more quickly over depr
essed prey or turn if approaching depressed prey) influence the amount of t
ime spent foraging over depressed and vulnerable prey, and how this influen
ces the strength of interference. Although based on a different mechanism,
our model produces two similar general predictions to interference models b
ased on direct interactions between predators: the strength of interference
increases with (1) increased competitor density and (2) decreased prey enc
ounter rate. This suggests that there are underlying similarities in the na
ture of interference even when it arises through different processes. Not s
urprisingly, avoidance of depressed prey can substantially reduce the stren
gth of interference compared with random foraging. However, we identify the
region of the model's parameter space in which this reduction is particula
rly large and show that the only system for which suitable data are availab
le, redshank Tringa totanus feeding on Corophium volutator; falls within th
is region. The model shows that, by adjusting its search path to avoid area
s of depressed prey, a predator can substantially reduce the amount of the
interference it experiences and that this applies over a wide range of para
meter space, including the region occupied by a real system. This suggests
that behavior-based interference models should consider predator search pat
tern if they are to accurately predict the strength of the interference.