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.