Predator search pattern and the strength of interference through prey depression

This source preferred by Richard Stillman

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Authors: Stillman, R.A., Goss-Custard, J.D. and Alexander, M.J.

Journal: Behavioral Ecology

Volume: 11

Issue: 6

Pages: 597-605

ISSN: 1045-2249

DOI: 10.1093/beheco/11.6.597

We develop a model of predators foraging within a single patch, on prey that become temporarily immune to predation (depressed) after detecting a predator. Interference through prey depression occurs because the proportion of vulnerable prey (and hence intake rate) decreases as predator density increases. Predators in our model are not forced to move randomly within the patch, as is the case in other similar models, but can avoid areas of depressed prey and so preferentially forage over vulnerable prey. We compare the extent to which different avoidance rules (e.g., move more quickly over depressed prey or turn if approaching depressed prey) influence the amount of time spent foraging over depressed and vulnerable prey, and how this influences the strength of interference. Although based on a different mechanism, our model produces two similar general predictions to interference models based on direct interactions between predators: the strength of interference increases with (1) increased competitor density and (2) decreased prey encounter rate. This suggests that there are underlying similarities in the nature of interference even when it arises through different processes. Not surprisingly, avoidance of depressed prey can substantially reduce the strength of interference compared with random foraging. However, we identify the region of the model's parameter space in which this reduction is particularly large and show that the only system for which suitable data are available, redshank Tringa totanus feeding on Corophium volutator, falls within this region. The model shows that, by adjusting its search path to avoid areas of depressed prey, a predator can substantially reduce the amount of the interference it experiences and that this applies over a wide range of parameter space, including the region occupied by a real system. This suggests that behavior-based interference models should consider predator search pattern if they are to accurately predict the strength of the interference.

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