| Summary: | Predators do not always eat what they kill. Eating only the most energy-rich tissues may be most efficient for predators with limited stomach space, but why predators leave entire carcasses uneaten is unclear. We found that grizzly bears feeding on salmon routinely discarded completely uneaten and partially eaten fish while seeking the best available prey. When salmon were very abundant, bears discarded whole carcasses of low quality or ate only choice pieces. Selective consumption of prey by predators, observed in many animals, is often attributed to optimal foraging. Consistent with this idea, brown bears (Ursus arctos) often exhibit partial consumption, feeding exclusively on lipid-rich tissues of Pacific salmon (Oncorhynchus spp.), and discarding remains. However, bears also kill and abandon salmon without consuming any tissue. These discarded fish may be consistent with optimal foraging choices if they are of poor quality and if bears have easy access to better prey, or may reveal nonadaptive surplus killing behavior if fish are killed and discarded at random or solely based on prey abundance. Using 21 consecutive years of data from sockeye salmon (O. nerka) carcass surveys in Alaska, we found that foraging to maximize energy intake best explained prey discarding behavior. Specifically, discarding was more common under high prey abundance, late in the salmon run, and with low-quality prey. Patterns of tissue consumption were consistent with these findings; bears were less likely to consume belly, body, and brain tissue when prey condition decreased. Other factors not quantified here (e.g., bear demography, alternative food resources) almost certainly influence prey discard and partial consumption, though the salmon-related factors explored here strongly influenced bear foraging decisions that were consistent with optimal foraging theory. We did not find clear evidence of surplus killing behavior in brown bears foraging on salmon, but prey selectivity manifested itself through both discarding and partial ...
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