Condition-Dependent Bear Predation of Salmon Sarah 1 Bear eating a salmon as captured on motion-activated camera 1 1 Schooler , Aaron Wirsing , and Thomas 2 Quinn School of Environmental and Forest Sciences, University of Washington 2School of Aquatic and Fishery Sciences, University of Washington A male salmon with its hump and brain consumed by bears. Results Discussion Surplus killing (killing of prey without consumption) and partial prey consumption (predator eats only part of the prey) are two long-standing ecological phenomena that remain poorly understood. Why do animals do this? Salmon condition had the largest effect on whether the fish were bitten but not eaten (“surplus killed”) and which body parts were eaten (Figure 2). Bear condition, as indicated by day of the run, had little impact on surplus killing and body part consumption. As expected, the belly of females (where the eggs are stored) was more likely to be eaten by bears than the belly of males (χ2 = 172.8, p < 0.005). Bear satiation did not seem to be a significant predictor of body part or amount of salmon eaten, indicating that salmon condition may be the primary factor on which surplus killing and partial predation depends in Hansen Creek. Using extensive data on sockeye salmon killed by brown bears in Alaska, I examined surplus killing and partial prey consumption. Objective: Determine how bear satiation and salmon condition affect bear selective prey consumption and surplus killing of salmon. 1 100 0.9 90 0.8 80 0.7 70 0.6 60 0.5 50 0.4 40 0.3 30 0.2 20 0.1 10 0 0 Total Killed Number of Fish Because bears commonly eat only a fraction of the salmon that they kill, studying bear predation on salmon may clarify these interactions. Proportion of Fish with Part Eaten Introduction Body Brain Surplus Killed 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 34 Days Since Beginning of Run Wood River System Figure 1. Location of data collection. Hansen Creek is a small tributary of Lake Aleknagik in the Wood River System in Bristol Bay, Alaska. It is 2 km long and averages 10 cm deep and 4 m wide. The stream is walked every day during the July-August spawning period. Methods A long term salmon study in the Wood River system in southwestern Alaska (Figure 1) provided a dataset of almost 20 years of salmon runs for my analysis. Salmon tagged before the run are observed in the stream each day and then categorized by mode of death, body part consumed, sex, size, and spawning status. Using day of the salmon run as an index for bear satiation and days that the salmon had been seen in the stream as an index for salmon energy content as food for the bears, I used a binomial model with negative log likelihood to determine the best predictors of consumption patterns. Proportion of Fish with Part Eaten 1 300 0.9 250 0.8 0.7 200 0.6 0.5 150 0.4 100 0.3 Number of Fish Bristol Bay, AK Figure 2. Part of salmon eaten with total number of tagged salmon killed on each day of the run across years 2000 to 2014. No clear patterns are evident, consistent with results from modeling, indicating that bear satiation (as determined by number of days passed since beginning of salmon run) had little impact on partial consumption or surplus killing of salmon. Total Killed Body Brain Hump Belly 0.2 50 0.1 0 Surplus Killed 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 Days Alive In Stream Figure 3. Part of salmon eaten with total number of tagged salmon killed on each day of time in stream 2000 to 2014. Some clear patterns, consistent with results from modeling, indicating that salmon condition (as determined by number of days spent in stream before death) has strong impact on partial consumption or surplus killing of salmon. As salmon condition declined (days in the stream increases), the proportion of fish that were surplus killed went up, the proportion with the belly consumed as well as the proportion with brain consumed sharply declined, while the proportion of fish where the body was consumed remained relatively stable (Figure 3). Salmon condition was especially important for consumption of the hump in male salmon and the belly in females, probably because the nutritional value of salmon declines as they approach natural death after spawning. Day of the salmon run may not be a good surrogate for bear satiation, if they have access to alternative prey. However, Hansen Creek’s salmon run is very predictable (same dates every year) and bears congregate to take advantage of them. Particularly surprising was the high incidence of surplus kills early in the salmon run, when bears should be hungry. One explanation for this pattern is possible kleptoparasitism by dominant bears of smaller bears. It may be that the observed trends were due to larger bears asserting dominance over smaller bears and preventing them from eating choice parts of caught fish, or caught fish in good condition. Further research of kleptoparasitisim in this study system would be interesting and beneficial to explain the trends seen in this analysis. Conclusion: Salmon condition was a much better predictor of surplus killing and partial predation of salmon by bears than bear satiation. Kleptoparasitism by bears may have a large impact on the findings of this analysis. Acknowledgements Thanks to Trevor Branch of the University of Washington School of Aquatic and Fisheries Science for valuable help with the modeling and analysis of the data. Thanks also to the Alaska Salmon Program (and people who worked with it) and the School of Aquatic and Fisheries Sciences for providing the resources to produce the dataset I analysed.