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Efficacy of Firearms for Bear Deterrence in Alaska

Abstract

We compiled, summarized, and reviewed 269 incidents of bear-human conflict involving firearms that occurred in Alaska during 1883-2009. Encounters involving brown bears (Ursus arctos; 218 incidents, 81%), black bears (Ursus americanus; 30 incidents, 11%), polar bears (Ursus maritimus; 6 incidents, 2%), and 15 (6%) unidentified species provided insight into firearms success and failure. A total of 444 people and at least 367 bears were involved in these incidents. We found no significant difference in success rates (i.e., success being when the bear was stopped in its aggressive behavior) associated with long guns (76%) and handguns (84%). Moreover, firearm bearers suffered the same injury rates in close encounters with bears whether they used their firearms or not. Bears were killed in 61% (n = 162) of bear-firearms incidents. Additionally, we identified multiple reasons for firearms failing to stop an aggressive bear. Using logistic regression, the best model for predicting a successful outcome for firearm users included species and cohort of bear, human activity at time of encounter, whether or not the bear charged, and if fish or game meat was present. Firearm variables (e.g., type of gun, number of shots) were not useful in predicting outcomes in bear-firearms incidents. Although firearms have failed to protect some users, they are the only deterrent that can lethally stop an aggressive bear. Where firearms have failed to protect people, we identified contributing causes. Our findings suggest that only those proficient in firearms use should rely on them for protection in bear country.
Human Dimensions
Efficacy of Firearms for Bear Deterrence
in Alaska
TOM S. SMITH,
1
Wildlife Sciences Program, Faculty of Plant and Wildlife Sciences, Brigham Young University, 451 WIDB, Provo,
UT 84602, USA
STEPHEN HERRERO, Environmental Science Program, Faculty of Environmental Design, University of Calgary, Calgary, AB, Canada T2N 1N4
CALI STRONG LAYTON, Wildlife Sciences Program, Plant and Wildlife Sciences Program, Brigham Young University, 448 WIDB, Provo,
UT 84602, USA
RANDY T. LARSEN, Wildlife Sciences Program, Faculty of Plant and Wildlife Sciences and Monte L. Bean Life Sciences Museum, Brigham Young
University, 407 WIDB, Provo, UT 84602, USA
KATHRYN R. JOHNSON,
2
Alaska Science Center, USGS, 1011 E. Tudor Road, Anchorage, AK 99502, USA
ABSTRACT We compiled, summarized, and reviewed 269 incidents of bear–human conflict involving
firearms that occurred in Alaska during 1883–2009. Encounters involving brown bears (Ursus arctos;
218 incidents, 81%), black bears (Ursus americanus; 30 incidents, 11%), polar bears (Ursus maritimus;
6 incidents, 2%), and 15 (6%) unidentified species provided insight into firearms success and failure. A
total of 444 people and at least 367 bears were involved in these incidents. We found no significant difference
in success rates (i.e., success being when the bear was stopped in its aggressive behavior) associated with long
guns (76%) and handguns (84%). Moreover, firearm bearers suffered the same injury rates in close encounters
with bears whether they used their firearms or not. Bears were killed in 61% (n¼162) of bear–firearms
incidents. Additionally, we identified multiple reasons for firearms failing to stop an aggressive bear. Using
logistic regression, the best model for predicting a successful outcome for firearm users included species and
cohort of bear, human activity at time of encounter, whether or not the bear charged, and if fish or game meat
was present. Firearm variables (e.g., type of gun, number of shots) were not useful in predicting outcomes in
bear–firearms incidents. Although firearms have failed to protect some users, they are the only deterrent that
can lethally stop an aggressive bear. Where firearms have failed to protect people, we identified contributing
causes. Our findings suggest that only those proficient in firearms use should rely on them for protection in
bear country. ß2012 The Wildlife Society.
KEY WORDS Alaska, bear deterrence, bear–human interactions, black bears, brown bears, firearms, grizzly bears, polar
bears, Ursus americanus,Ursus arctos,Ursus maritimus.
People who work and recreate in North American bear
habitat often fear bear encounters. Although the vast major-
ity of bear–human interactions are benign, some yield a
variety of adverse outcomes including destruction of proper-
ty, injuries, and fatalities to both bears and humans (Herrero
2002). Bear attacks are of great interest to the media and can
result in negative consequences for bear conservation
(Craighead and Craighead 1971, Miller and Chihuly
1987, Loe and Roskaft 2004). In 1967, for example, 2 human
fatalities in Glacier National Park led some to call for the
elimination of grizzly bears from America’s national parks
(Moment 1968, 1969). Ultimately, bears were seen as an
integral part of ecosystems and remained (Herrero 1970,
Craighead and Craighead 1971), but ongoing bear–human
interactions and attendant consequences persist.
Until the advent of bear spray in the 1980s, firearms were
the primary deterrent for safety in bear country (Smith et al.
2008). Even now, private, state, and federal agencies in
North America often require employees to carry firearms
while working in bear country. Although bear safety manuals
acknowledge the value of firearms, they also caution that
users must be proficient under duress (Shelton 1994, Smith
2004, Gookin and Reed 2009). Furthermore, data regarding
firearm performance in aggressive bear encounters are lack-
ing. In fact, we could find little published information
quantitatively addressing the effectiveness of firearms as
bear deterrents.
Herrero (2002) noted that firearms have their place in
protecting people from aggressive bears, but did not present
data regarding firearm use or efficacy. Similarly, Bromley
et al. (1992) discussed many aspects of firearm use as bear
deterrents, but provided no supporting data. The United
States Fish and Wildlife Service (2002) stated that people
using firearms in bear encounters were injured 50% of the
time, but no data or references were provided as support
for this figure. Similarly, Meehan and Thilenius (1983)
Received: 20 December 2010; Accepted: 22 October 2011
Additional Supporting Information may be found in the online version
of this article.
1
E-mail: tom_smith@byu.edu
2
Present Address: P.O. Box 4374, Palmer, AK 99645, USA.
The Journal of Wildlife Management; DOI: 10.1002/jwmg.342
Smith et al. Bears and Firearms 1
presented data regarding bullet performance at short range
with reference to bear attacks, but did not present ballistics
information from actual bear encounters.
Hence, a study of bear–human conflicts involving firearms
has not been conducted. Moreover, firearm efficacy in
resolving bear–human conflict has not been quantified and
remains speculative. Our specific objectives for this paper
were to 1) review and summarize Alaskan bear–firearm
incidents and 2) identify factors associated with successful
use of firearms in bear–human conflicts in order to promote
both human safety in bear country and bear conservation.
STUDY AREA
Alaska is located in the northwestern portion of North
America and occupies an area of 1,530,699 km
2
. The human
population in Alaska was estimated to be 698,473 in 2009.
The brown or grizzly bear (Ursus arctos) ranges throughout
the state with the most recent estimate at 31,700 (Miller
1993). Black bears (Ursus americanus) are found in most
forested areas of Alaska. Formal population estimates do
not exist for black bears, but an Alaska Department of
Fish and Game (ADFG) biologist roughly estimated
them to number more than 50,000 (Harper 2007). Polar
bears (Ursus maritimus) are marine mammals that rarely
venture onto land (Amstrup 2003). In Alaska, polar bears
from both the Chukchi and Southern Beaufort Seas sub-
populations occasionally range up to 80 km inland, primarily
for maternal denning. Recent estimates put their numbers at
about 3,800 (Amstrup 2003).
METHODS
Compilation and Summary
We compiled information on bear attacks from readily ac-
cessible state and federal records, newspaper accounts, books,
and anecdotal information that spanned the years 1883–
2009. We defined an incident as a single bear–firearm event
that involved 1 or more people and 1 or more firearms. For
each incident we recorded the following variables to the
extent data were available: date, time, month, year, location
of incident, number of people, sex of people, activity at time
of interaction, whether or not people were making noise
prior to the encounter, probable cause of encounter, distance
to bear at time of encounter, bear species and cohort (age–sex
class), whether or not the bear charged, minimum distance to
the bear, presence of fish and/or game meat, type of firearms
used, number of shots fired, warning shots, firearm efficacy,
firearm ratio (number of firearms/number of people), dis-
tance to bear when shot, visibility of habitat (subjectively
rated poor, fair, good based on terrain and vegetation),
reasons for firearm ineffectiveness, extent of human injuries,
and extent of bear injuries. To overcome problems associated
with missing or unclear information, we limited the contri-
butions of each record to what we deemed were the most
trustworthy pieces of information. The review process was
subjective, but we feel confident that we limited our infer-
ences to a minimum while gleaning useful information for
analysis.
For each of these incidents, we also used the following
categories to characterize probable causes for bear–human
encounters: surprised (people startled the bear), curiosity (the
bear’s motivation appears to have been curiosity), provoked
(e.g., a photographer crowding it or a hunter pursuing it),
predatory (the bear treated the human as potential prey), and
carcass defense (the bear defending a food source). We
also subjectively evaluated injuries as follows: slight injuries
included nips, limited biting, and scratches where hospitali-
zation was not required; moderate injuries required hospi-
talization to some degree, and included punctures, bite
wounds and broken bones; and severe injuries resulted in
extended hospitalization and often permanent disability.
We defined a charge as an agonistic behavior typified by a
sudden rush, or lunge, toward the perceived threat. Some
charges terminated prior to contact (i.e., bluff charges)
whereas others resulted in contact. For distance to bears,
we regrouped values into broad categories (i.e., <10 m,
10–25 m, 26–50 m, and >51 m) based on specificity in
the accounts. We used reported distances for greater accuracy
(e.g., distance to bear when shot) whenever possible.
We deemed use of a firearm successful (response coded as
1) when it stopped the offensive behavior of the bear. These
successes included incidents where bears no longer pursued a
person, broke off an attack, abandoned attempts to acquire
food or garbage, were killed, or turned and left the area as a
result of firearm use. Conversely, firearm failures (response
coded as 0) occurred when the bear continued its pursuit,
persisted in attempts to acquire food or garbage, or showed
no change in behavior after firearm use. We excluded inci-
dents from our analysis where firearms were available but no
attempt to use them was made.
Statistical Analysis
We used the G-test of independence (Dytham 2003) when
we had 2 nominal variables, each with 2 or more possible
values, and we wanted to compare frequencies of one to the
other. We also tested the equality of sample means with a
2-sample t-test. We used the Z-test to compare the propor-
tions from 2 independent groups to determine if they were
different. We set significance at P<0.05.
To understand the relationship between variables and
incident outcomes, we used logistic regression where the
response variable was success (1) or failure (0) of firearms.
We identified candidate models representing different
hypotheses related to firearm success as a function of bear,
human, firearm, and spatio-temporal factors (Table 1). Our
analysis followed several steps. First, we evaluated the
number of records and odds associated with different
categories of our explanatory variables to determine which
should be collapsed or combined. Second, we used Akaike’s
Information Criterion adjusted for small sample sizes (AIC
c
)
to rank models (Akaike 1973, Burnham and Anderson 2002)
for each variable type (i.e., bear, firearm, human, spatio-
temporal). We then used the top model and competing
models (DAIC
c
<2.0) within each type in the third stage
of analysis similar to Doherty et al. (2008). Here we com-
bined variables and ranked models based on smallest AIC
c
to
2 The Journal of Wildlife Management
identify a best approximating model. We then evaluated
these models and their associated variables to identify any
uninformative parameters that did not improve AIC
c
and
discarded them (Arnold 2009).
Because the best approximating model had high AIC
c
weight (w
i
¼0.96), we used it to evaluate the direction
and strength (odds ratios) of associations between explana-
tory variables and firearm efficacy. To test for lack of model
fit, we calculated Hosmer and Lemeshow’s (2000) goodness
of fit statistic. We also used the top model in a 5-fold cross
validation exercise where we withheld 1/5th of the data and
estimated model coefficients. We then used the estimated
coefficients to predict incident outcomes for the withheld
data. We calculated the proportion of outcomes accurately
predicted (estimated probability of success >0.50 for suc-
cessful outcomes and 0.50 for unsuccessful outcomes) for
the withheld data and repeated this process until we obtained
a prediction and accuracy for each observation.
RESULTS
A total of 444 people were involved in 269 incidents. At least
357 bears, including dependent offspring, were involved in
269 incidents, including 300 brown bears (84%), 36 black
bears (10%), 6 polar bears (2%), and 15 of unknown species
(4%). Bear-inflicted injuries occurred in 151 of 269 (56%)
incidents (see Supplemental Information available online at
www.onlinelibrary.wiley.com for additional details regarding
characteristics of bear incidents).
Success rates by firearm type were similar with 84% of
handgun users (31 of 37) and 76% of long gun users (134
of 176) successfully defending themselves from aggressive
bears (Z¼1.0664, P¼0.2862). When we compared out-
comes for people who used their firearm in an aggressive bear
encounter (n¼229) to those who had firearms but did not
use them (n¼40), we found no difference in the outcome
(G
2
¼0.691, P¼0.708), whether the outcome was no
injury, injury, or fatality. However, we found a difference
in the outcome for bears with regard to firearm use: 172 bears
died when people used their firearms, whereas no bears were
killed when firearms were not used.
Firearms failed to protect people for a variety of reasons
including lack of time to respond to the bear (27%), did not
use the firearm (21%), mechanical issues (i.e., jamming;
14%), the proximity to bear was too close for deployment
(9%), the shooter missed the bear (9%), the gun was emptied
and could not be reloaded (8%), the safety mechanism was
engaged and the person was unable to unlock it in time to use
the gun (8%), people tripped and fell while trying to shoot
the bear (3%), and the firearm’s discharge reportedly trig-
gered the bear to charge that ended further use of the gun
(1%).
With respect to efforts to model firearm efficacy, we
classified 156 incidents as successful. Our initial evaluation
of the number of incidents assigned to each category and
associated odds (Appendix 1) suggested (95% CI on odds
ratio included 1) collapsing the species category to black
bears and other (brown, polar, and unknown bears). This
same evaluation suggested our initial breakdown of cohorts
and seasons could be collapsed to female and other (pairs,
males, unknown). Similarly, we combined seasons into 2
categories for summer and other (spring, fall, winter,
unknown).
The best model for firearm success relative to bear variables
included species, cohort, and whether the bear charged
(Table 2). For firearm variables, 2 models received enough
support (DAIC
c
<2.0) to be advanced to the third stage of
analysis. These models included firearm ratio, number of
warning shots, and success of warning shots. We found little
support for models that included firearm type (Table 2).
Analysis of human and spatio-temporal variables indicated
activity, distance, group size, noise, presence of fish or game,
season, and visibility influenced firearm success (Table 2).
After combining variables across categories, a model in-
cluding species, cohort, whether the bear charged, group size,
human activity, noise, and presence of fish or game had the
greatest AIC
c
weight. Because separate removal of group size
and noise improved (reduced) the AIC
c
values compared to
removal of other variables, we considered them uninforma-
tive and eliminated them from the top model. These same 2
variables also had 85% confidence intervals that spanned
zero—further suggesting they were uninformative (Arnold
2009). The resulting top model accounted for 96% of the
AIC
c
weight and was more than 6 DAIC
c
better than the next
competing models (Table 3). Hosemer–Lemeshow’s good-
Table 1. Description of variables used in models of firearm success in bear incidents in Alaska, USA during 1883–2009.
Variable Category Description
Species Bear Species of bear involved in event (black, brown, polar)
Cohort Bear Cohort of bear involved in event (unknown, pairs, female with young, female, and male)
Charge Bear Bear charged (yes, no, unknown)
Group size Human Group size (count of people present)
Activity Human Activity code of humans (active, intermediate, sedentary, unknown)
Fish/game Human Presence of fish or game (no, game, fish, unknown)
Noise Human Noise associated with activity (no, yes, unknown)
Firearm type Firearm Firearm type (handgun, long gun, both, unknown)
No. of shots Firearm Number of shots fired
Warning shots Firearm Number of warning shots fired
Firearm ratio Firearm Number of guns divided by number of individuals in group
Distance Spatio-temporal Distance from bear when firearm discharged (<10 m, 10–20 m, 21–30 m, 31–40 m, >40 m)
Visibility Spatio-temporal Visibility at site (poor, good, unknown)
Season Spatio-temporal Season of incident (spring, summer, fall, winter, unknown)
Smith et al. Bears and Firearms 3
ness of fit statistics (P¼0.26) provided no evidence of lack
of fit. Similarly, 5-fold cross validation using the top model
produced an accurate prediction of incident outcomes on
withheld data for 71.9% of incidents—further suggesting
adequate fit.
When the animal involved in the incident was a black bear,
odds of firearm success were more than 38 times greater than
when the bear was a brown, polar, or unknown bear
(Table 4). Similarly, females without young were associated
with a nearly 7-fold increase in odds of firearm success
(Table 4). Conversely, odds of firearm success were nega-
tively associated with human activity level and charging
behavior by involved bears. Odds of firearm success were
12 and 24 times greater for intermediate and sedentary
activity levels, respectively, compared to people considered
active (Table 4). Once a bear charged, odds of firearm success
decreased nearly 7-fold (Table 4). Interestingly, the presence
of fish or game meat was associated with increases of 4 and 8,
respectively, in odds of firearm success.
DISCUSSION
Brown bears were disproportionately involved (81%) in these
encounters, a finding that is consistent with the widely held
perception that brown bears are considerably more aggressive
and hence, more likely to be involved in bear–human conflict
leading to injury, than the other 2 species (Herrero and
Table 3. Ranking of supported models (DAIC
c
<10.0) describing firearm success as a function of bear, firearm, human, and spatio-temporal influences in
Alaska, USA during 1883–2009.
Model structure AIC
ca
DAIC
cb
w
ic
K
d
Deviance
Success
e
Species þCohort þCharge þActivity þFish/Game 276.11 0.0 0.96 11 253.00
Success Species þCohort þCharge þDistance þVisibility þSeason 282.93 6.8 0.03 11 259.82
Success Group size þActivity þFish/Game þNoise þDistance þVisibility þSeason 285.28 9.2 0.01 16 250.94
a
Akaike’s Information Criterion adjusted for small sample sizes.
b
Change in AIC
c
from top model.
c
Model weight.
d
Number of estimable parameters.
e
Reduced model after removal of group size and noise which were uninformative.
Table 2. Ranking of supported models (DAIC
c
<10.0) describing firearm success as a function of bear (species, cohort, charge), firearm (firearm type, no.
shots, warning shots, firearm ratio), human (group size, activity, fish/game, noise), and spatio-temporal (distance, visibility, and season) influences in Alaska,
USA during 1883–2009.
Model structure AIC
ca
DAIC
cb
w
ic
K
d
Deviance
Bear
Success Species þCohort þCharge 296.30 0.0 0.97 5 286.05
Success Species þCohort 303.82 7.5 0.02 3 297.72
Success Species þCharge 305.51 9.2 0.01 4 297.35
Firearm
Success No. shots þFirearm ratio þWarning shot 321.31 0.0 0.40 7 306.85
Success No. shots þFirearm ratio 322.34 1.0 0.24 4 314.18
Success Firearm type þNo. shots þFirearm ratio þWarning shot 324.23 2.9 0.09 10 303.31
Success No. shots þWarning shot 324.45 3.1 0.08 5 314.20
Success Firearm ratio þWarning shot 325.80 4.5 0.04 6 313.45
Success Firearm type þNo. shots þFirearm ratio 325.98 4.7 0.04 7 311.52
Success No. shots 326.28 5.0 0.03 2 322.23
Success Firearm type þNo. shots þWarning shot 327.12 5.8 0.02 8 310.52
Success Firearm ratio 327.22 5.9 0.02 3 321.11
Success Warning shot 328.83 7.5 0.01 4 320.67
Success Firearm type þFirearm ratio þWarning shot 328.93 7.6 0.01 9 310.18
Success Firearm type þNo. shots 329.78 8.5 0.01 5 319.53
Success Firearm type þFirearm ratio 331.32 10.0 0.00 6 318.97
Human
Success Group size þActivity þFish/Game þNoise 305.27 0.0 0.59 10 284.35
Success Group size þFish/Game þNoise 307.91 2.6 0.16 7 293.45
Success Activity þFish/Game þNoise 308.16 2.9 0.14 9 289.41
Success Group size þActivity þFish/Game 310.27 5.0 0.05 8 293.67
Success Fish/Game þNoise 311.11 5.8 0.03 6 298.76
Success Group size þActivity þNoise 313.03 7.8 0.01 7 298.57
Success Activity þNoise 314.12 8.8 0.01 6 301.77
Spatio-temporal
Success Distance þVisibility þSeason 300.26 0.0 0.74 7 285.79
Success Distance þSeason 302.36 2.1 0.26 6 290.01
a
Akaike’s Information Criterion adjusted for small sample sizes.
b
Change in AIC
c
from top model.
c
Model weight.
d
Number of estimable parameters.
4 The Journal of Wildlife Management
Higgins 1999, 2003; Herrero 2002). Female bears with
dependent young comprised the second-most common co-
hort involved in firearm incidents. Surprise encounter was
the reason most often given for conflict with this cohort.
Brown bear family groups suddenly confronted by people
were commonly aggressive-defensive, as they protected their
cubs from a perceived threat. Too few incidents involving
black and polar bear family groups (n¼4 and 1, respective-
ly) occurred to support meaningful conclusions, but Herrero
(2002) reported that black bears rarely attack people in
response to sudden encounters. Single bears comprised the
most common cohort involved in firearms incidents, a
reflection of the relative frequency of that cohort in North
American bear populations (Jonkel and Cowan 1971,
Schwartz et al. 2003) and the fact that single bears are the
most hunted cohort.
Although firearms were successful (84% handgun; 76%
long gun) in deterring aggressive bears in the records we
studied, we do not claim that these rates represent the
outcome for all bear–firearm incidents throughout Alaska.
When we initiated this study in the late 1990s, we had access
to the Alaska Department of Fish and Game’s defense of life
or property (DLP) records. However, privacy laws restricted
our access to records from 2001 to present. This incomplete
record potentially affects 3 findings: the number and type of
human injuries, the number and type of bear injuries, and
firearm success rates. First, because bear-inflicted injuries are
closely covered by the media, we likely did not miss many
records where people were injured. Therefore, even if more
incidents had been made available through the Alaska DLP
database, we anticipate that these would have contributed
few, if any, additional human injuries. Second, including
more DLP records would have increased the number of
bears killed by firearms. Finally, additional records would
have likely improved firearm success rates from those
reported here, but to what extent is unknown.
Our modeling results indicated that models with firearm
variables had very limited support (Tables 1 and 3). The type
of firearm, number of shots taken, whether or not the people
fired warning shots, and how many firearms were present in
the group had minimal influence on the outcome. Success
was best predicted by a model that included species and
cohort of bear, whether or not the bear charged, human
activity level, and if fish or game meat were available. These
findings coupled with odds ratios from univariate analyses
(Appendix 1) affirm some of the conventional advice for
avoiding bear encounters: hike in a group, avoid areas of poor
visibility, be more cautious when in brown bear country, and
make noise to avoid startling females with dependent young
(Herrero 2002, Smith 2004).
Although bear spray, pyrotechnics, noise makers, and other
deterrents may alter a bear’s behavior, only a firearm provides
a lethal force option. However, interviews revealed that some
people were hesitant to use lethal force for fear of shooting
the person being attacked, or because they did not want to
have to skin the bear and pack out its hide, skull, and claws as
required by law. Additionally, some people admitted that
they were reluctant to shoot a protected species. In some
cases, this reluctance proved detrimental when split second
decisions were required for the person to defend themselves
from an aggressive, attacking bear. The decision regarding
which deterrent to use is a personal one, but the consequen-
ces of attempting to use lethal force should be carefully
weighed.
Firearm type received very little support, suggesting that
efficacy of the firearm was unrelated to whether people used a
handgun or long gun. Considering the high intensity, rapidly
unfolding, close-quartered, and chaotic nature of bear
attacks, these results are not surprising. Hence, we cannot
recommend one class of weapon over the other. We did not
have data regarding the level of expertise associated with
those who carried firearms. Regardless, a person’s skill level
plays an influential role in determining the outcome in bear–
firearm incidents.
MANAGEMENT IMPLICATIONS
Firearms should not be a substitute for avoiding unwanted
encounters in bear habitat. Although the shooter may be able
to kill an aggressive bear, injuries to the shooter and others
also sometimes occur. The need for split-second deployment
and deadly accuracy make using firearms difficult, even for
experts. Consequently, we advise people to carefully consider
their ability to be accurate under duress before carrying a
firearm for protection from bears. No one should enter bear
country without a deterrent and these results show that
firearms are not a clear choice. We encourage all persons,
Table 4. Logistic regression coefficients, standard errors (SE), odds ratios, and 95% confidence intervals from the highest ranked model (Akaike’s Information
Criterion adjusted for small sample sizes (AIC
c
) weight ¼0.96) of firearm success as a function of bear, firearm, human, and spatio-temporal influences in
Alaska, USA during 1883–2009.
Coefficient Estimate SE Odds ratio Lower 95% CI Upper 95% CI
Intercept 0.984 1.017
Black bear 3.652 1.180 38.56 5.92 855.38
Female 1.916 0.718 6.79 1.93 34.80
Charge 1.921 0.783 0.15 0.02 0.58
Charge unknown 3.283 0.980 0.04 0.00 0.22
Intermediate activity 2.485 0.912 12.01 2.40 97.04
Sedentary activity 3.180 0.983 24.04 4.11 216.71
Unknown activity 2.141 1.140 8.51 1.01 97.67
Game 1.427 0.482 4.17 1.67 11.21
Fish 2.109 0.690 8.24 2.40 38.86
Unknown 0.662 0.366 1.94 0.95 4.02
Smith et al. Bears and Firearms 5
with or without a firearm, to consider carrying a non-lethal
deterrent such as bear spray because its success rate under a
variety of situations has been greater (i.e., 90% successful for
all 3 North American species of bear; Smith et al. 2008) than
those we observed for firearms.
ACKNOWLEDGMENTS
The United States Geological Survey Alaska Science Center
and Brigham Young University provided support for this
project. We gratefully acknowledge a number of reviewers
who have provided guidance regarding this manuscript, the
Associate Editor and Editor-in-Chief for the Journal of
Wildlife Management in particular. D. Hardy (ADFG re-
tired) provided useful comments that have helped make this
more valuable. Additionally, we appreciate those who helped
us collect bear incident data.
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6 The Journal of Wildlife Management
Appendix 1. Univariate analysis showing log-likelihood, odds, and associated 95% confidence intervals for firearm success in relation to bear, firearm, human,
and spatio-temporal influences in Alaska, USA 1883–2009.
Category Variable Log-likelihood Df Odds Lower 95% CI Upper 95% CI
Bear Species (polar) 152.05 4 2.00 0.39 14.43
Black 13.50 1.07 334.95
Brown 0.65 0.09 3.40
Unknown 2.75 0.26 30.43
Cohort (single) 157.26 5 1.19 0.79 1.80
Female w/young 1.12 0.59 2.15
Female 7.00 2.25 30.86
Male 1.81 0.92 3.63
Pair 1.68 0.31 12.56
Charge (none) 156.77 3 7.33 2.54 30.98
Yes 0.23 0.05 0.69
Unknown 0.07 0.01 0.28
Firearm Type (handgun) 163.40 4 2.44 1.16 5.60
Long gun 0.64 0.27 1.44
Both 0.27 0.03 1.91
Unknown 0.76 0.27 2.05
No. shots 161.12 2 1.20 1.04 1.38
Warning shot (none) 160.33 4 1.63 1.22 2.19
Success 2.05 0.60 9.37
Unsuccessful 1.60 0.75 3.66
Unknown 0.23 0.05 0.82
Firearm ratio (1/group) 160.56 4 6.33 2.16 26.96
1/Person 0.22 0.05 0.67
Unknown 0.31 0.07 1.03
Human Group Size 160.99 2 1.68 1.14 2.53
Activity (active) 157.41 4 0.30 0.07 0.98
Intermediate 5.71 1.68 26.13
Sedentary 11.33 2.86 58.44
Unknown 2.86 0.55 17.52
Fish/game (none) 157.50 4 1.18 0.79 1.76
Game 2.74 1.21 6.68
Fish 5.94 1.89 26.32
Unknown 1.25 0.70 2.24
Noise (none) 155.83 3 1.25 0.87 1.81
Yes 4.16 1.99 9.40
Unknown 1.01 0.55 1.83
Spatio-temporal Distance (<10 m) 151.90 5 1.20 0.81 1.78
11–25 m 2.45 1.23 5.08
26–50 m 1.91 0.93 4.10
>51 m 13.38 2.58 246.08
Unknown 0.44 0.17 1.07
Visibility (poor) 163.69 3 1.59 1.12 2.29
Good 0.78 0.37 1.68
Unknown 1.30 0.73 2.33
Season (spring) 154.04 5 1.17 0.54 2.57
Summer 3.48 1.35 9.06
Fall 1.25 0.51 3.01
Winter 0.86 0.31 2.33
Unknown 0.38 0.08 1.49
Smith et al. Bears and Firearms 7
... The role of firearms and bear spray in resolving humanbear conflicts has been previously addressed (Herrero and Higgins 1998;Smith et al. 2008Smith et al. , 2012. As of 2015, 75 instances of bear spray use were recorded, of which 70 (93.3%) ...
... Long guns were the predominant firearm used on both black (73%) and grizzly bears (82%). Given that nearly 50% of all encounters occurred within <10 m, it is not surprising that firearms can be difficult to bring into play in many bear encounters (Smith et al. 2012). ...
... This finding is consistent with previous studies of the effectiveness of bear spray Higgins 1998, Smith et al. 2008). Persons carrying firearms fared worse (76% success rate overall; Smith et al. 2012). Attempting to dispatch a charging bear in heavy cover over uneven ground while under extreme duress is undoubtedly difficult. ...
Article
Full-text available
We present an analysis of human–bear (Ursus spp.) conflicts that occurred in Alaska, USA, from 1880 to 2015. We collected 682 human–bear conflicts, consisting of 61,226 data entries, from various sources available to us. We found that human–bear attacks are rare events, averaging 2.6/year across the study period, though increasing to 7.6/year in the current decade. Grizzly bears (U. arctos) dominated conflicts (88%), followed by black bears (U. americanus; 11%), and lastly polar bears (U. maritimus; 1%). Although grizzly bear family groups are often involved in conflicts (32% of all attacks), single grizzlies are involved more than any other cohort (45%). Human–bear conflicts occurred during every month of the year and the majority occurred during daytime when people were most active (82%). Human group size was a significant factor in bear conflicts: the larger the group (≥2 persons), the less likely to be involved in a confrontation. Habitat visibility also contributed to conflict, the poorer the visibility the more likely bears were to engage with people, presumably because of an inability to detect them until very close. When domestic dogs intervened in attacks, they terminated them nearly half of the time (47.5%). However, in 12.5% of cases, dogs appeared to have initiated the conflict. When involved, rescuers terminated maulings in 90.3% of cases, but were themselves mauled 9.7% of the time. We offer these, and other, insights derived from this work that will inform wildlife biologists’ bear safety training and public outreach. © 2018 The Wildlife Society.
... Safety in bear country is a personal responsibility and which deterrent(s) one chooses to carry is a personal decision. Bear spray has out-performed firearms in aggressive encounters in North America (Smith et al. 2012), but individuals are not statistical averages. Persons proficient in the use of firearms, as compared to those who are not, have a decided advantage in an aggressive bear encounter. ...
Presentation
Full-text available
Several studies have documented the effectiveness of bear spray in protecting users from aggressive bears. However, bear spray failures have also been reported along with speculation regarding the influences of temperature, wind, repeated canister use, and canister age on spray efficacy. We designed lab and field experiments to document the influence that temperature, wind, repeated discharges from the same canister, and canister age have on bear spray performance. To determine the influence of temperature on spray performance we recorded canister head pressures at temperatures ranging from -23 deg C to + 25 deg C and found a strong, positive linear relationship. Even at the lowest temperature tested (- 23 deg C), bear spray had a range > 4 m, though the plume was narrow and spray not well aerosolized. As canister temperature increased, head pressure, plume distance and dispersion increased. Using computational fluid dynamics modeling, we simulated the effect that headwinds, crosswinds, and tailwinds of varying speeds had on spray performance. We found that even under high headwind and crosswind scenarios (> 10 m/s), sprays reached targets that were ~ 2 m directly in front of the user. Crosswinds affected spray plume distance similar to headwinds but was not as pronounced. As expected, tailwinds improved spray performance with respect to speed and distance. By weighing unused canisters of various ages (18 years old to present), we found that brands tested lost weight ranging from 0.65 to 1.92 g/year, presumably due to propellant that escaped canister seals. We also documented that bear spray head pressure declines in a logarithmic, not linear, fashion with over half of a new (seven second spray time) canister’s pressure lost in the first one second of spray. We discuss these findings in the context of bear safety implications as well as commonly cited reasons for lacking confidence in this deterrent’s ability to deter aggressive bears.
... Karelian Bear Dogs are moreover probably one of the most challenging tools to deploy for hazing purposes given the training demands placed on both dogs and handlers. 42 For example, there is good evidence supporting the efficacy of pepper spray in situations where a person is not carrying a firearm suited to firing non-lethal projectiles (Section 2.2;Hunt [1984];Rogers [1984];Herrero & Higgins [1998];Smith et al. [2008Smith et al. [ , 2012;Smith & Herrero [2018]), or rubber projectiles if a person is carrying and trained to use the requisite shotgun(Stenhouse et al. , 1984. ...
Technical Report
Full-text available
Bear managers are increasingly using non-lethal methods to resolve human-bear conflicts—largely because the public is demanding that wildlife be treated more humanely and with greater regard for their intrinsic value. Hazing or a fixed infrastructure designed to inflict pain and discomfort are the most common non-lethal means employed by managers to drive bears away from people and human facilities or, even more ambitiously, teach them to indefinitely avoid roads, residences, and campgrounds. The 2021 technical report entitled “Teaching Bears: Complexities and Contingencies of Deterrence and Aversive Conditioning” focuses not only on the uses of deterrents to haze bears away from conflict situations, but also, more importantly, on the complexities that bedevil efforts to educate wild bears under field conditions. Aversive conditioning—a general term for pain-based fear-instilling learning processes—is probably the most complex endeavor that a manager can undertake with a bear. “Teaching Bears” delves into the many facets of aversive conditioning, including terminology and concepts relevant to understanding the basics of how animals learn about their world. However, most of this report is devoted to describing what it is that individual animals bring to a learning process, and how these internal complexities along with the particulars of a given context largely dictate whether efforts by managers to deter and aversively-condition bears are likely to be successful or not. The report concludes that aversive conditioning will almost invariably have a limited role in non-lethal management of human-bear conflicts, especially in contrast to efforts focused on people. At its most useful, hazing can be used to temporarily drive bears away from a conflict situation, providing a respite during which managers can then address human-related elements such as the availability of attractants or problematic behaviors of people.
... Bear deterrent spray is an effective tool for defusing brown bear-human conflict in a nonlethal manner (Smith et al. 2008). Reliance on use of bear deterrent spray by Project personnel will promote human safety and conservation of brown bears while reliance on firearms would be much less effective (Smith et al. 2012). ...
Technical Report
Full-text available
The primary objective of this document is to review and evaluate the completeness of the US Army Corp of Engineers’ response to comments submitted on the Draft Environmental Impact Statement and response to issues identified on the potential impacts of the proposed Pebble Mine Project (i.e., roads, natural gas pipelines, road corridors, and port facilities) on brown bears in Southwest Alaska. Response to comments and issues identified concerning the potential impacts on brown bears associated with public viewing sites will be of particular interest. A secondary objective is to review response to comments and issues identified concerning general potential impacts of the Project on brown bears throughout Southwest Alaska.
... Importantly, having a deterrent did not guarantee that the person would avoid injury; but those with deterrents suffered less injury, and less-severe injuries, than those without. Of particular note, those persons with bear spray largely escaped injury (98%), whereas persons bearing firearms suffered more (24% were injured; Smith et al. 2012). ...
Chapter
The media and scientific literature are increasingly reporting an escalation of large carnivore attacks on humans, mainly in the so-called developed countries, such as Europe and North America. Although large carnivore populations have generally increased in developed countries, increased numbers are not solely responsible for the observed rise in the number of attacks. Of the eight bear species inhabiting the world, two (i.e. the Andean bear and the giant panda) have never been reported to attack humans, whereas the other six species have: sun bears Helarctos malayanus, sloth bears Melursus ursinus, Asiatic black bears Ursus thibetanus, American black bears Ursus americanus, brown bears Ursus arctos, and polar bears Ursus maritimus. This chapter provides insights into the causes, and as a result the prevention, of bear attacks on people. Prevention and information that can encourage appropriate human behavior when sharing the landscape with bears are of paramount importance to reduce both potentially fatal human–bear encounters and their consequences to bear conservation.
... Safety in bear country is a personal responsibility and which deterrent(s) one chooses to carry is a personal decision. Bear spray has out-performed firearms in aggressive encounters in North America (Smith et al. 2012), but individuals are not statistical averages. Persons proficient in the use of firearms, as compared to those who are not, have a decided advantage in an aggressive bear encounter. ...
Article
Full-text available
Several studies have documented the effectiveness of bear spray in protecting users from aggressive bears. Bear spray failures, however, have also been reported along with speculation regarding the influences of temperature, wind, repeated canister use, and canister age on spray efficacy. We designed lab and field experiments to document the influence that temperature, wind, repeated discharges from the same canister, and canister age have on bear spray performance. To determine the influence of temperature on spray performance, we recorded canister head pressures at temperatures ranging from −23°C to 25°C and found a strong, positive linear relationship. Even at the lowest temperature tested (−23°C), bear spray had a range >4 m, though the plume was narrow and the spray was not well aerosolized. As canister temperature increased, head pressure, plume distance, and dispersion increased. We used computational fluid dynamics modeling and simulated the effect that headwinds, crosswinds, and tailwinds of varying speeds had on spray performance. Even under high headwind and crosswind scenarios (>10 m/sec), sprays reached targets that were approximately 2 m directly in front of the user. Crosswinds affected spray plume distance similar to headwinds, but the effect was not as pronounced. Tailwinds improved spray performance with respect to speed and distance. By weighing unused canisters ≤18 years old, brands tested lost weight ranging from 0.65 g/year to 1.92 g/year, presumably because of propellant that escaped canister seals. We also documented that bear spray head pressure declines in a logarithmic, not linear, fashion; over half of a new (7-sec spray time) canister's pressure was lost in the first 1 second of spray. We recommend not test-firing cans, keeping cans warm when in the cold, and retiring them when ≥4 years of age. Our results provide no compelling reason to not carry bear spray in all areas where bears occur, even if it is windy or cold.
... This was caused by high variation of the effectiveness of deterrents in different study cases, with successful applications in some cases and failures in the others. In only 10 out of 26 aversion cases did we find effective applications of deterrents which reduced damage by 50-100% [12][13][14]31,40,46,53,54 . At the other extreme were 11 cases, in which deterrents reduced damage poorly by less than 20%, did not make a change or even increased damage 41,46,[55][56][57][58][59] . ...
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Full-text available
Abstract Human-bear conflicts triggered by nuisance behaviour in public places and damage to livestock, crops, beehives and trees are among the main threats to bear populations globally. The effectiveness of interventions used to minimize bear-caused damage is insufficiently known and comparative reviews are lacking. We conducted a meta-analysis of 77 cases from 48 publications and used the relative risk of damage to compare the effectiveness of non-invasive interventions, invasive management (translocations) and lethal control (shooting) against bears. We show that the most effective interventions are electric fences (95% confidence interval = 79.2–100% reduction in damage), calving control (100%) and livestock replacement (99.8%), but the latter two approaches were applied in only one case each and need more testing. Deterrents varied widely in their effectiveness (13.7–79.5%) and we recommend applying these during the peak periods of damage infliction. We found shooting (− 34.2 to 100%) to have a short-term positive effect with its effectiveness decreasing significantly and linearly over time. We did not find relationships between bear density and intervention effectiveness, possibly due to differences in spatial scales at which they were measured (large scales for densities and local fine scales for effectiveness). We appeal for more effectiveness studies and their scientific publishing in regard to under-represented conflict species and regions.
... Bear deterrent spray is an effective tool for defusing brown bear-human conflict in a nonlethal manner (Smith et al. 2008). Widespread use of bear deterrent spray by Project personnel will promote human safety and conservation of brown bears while reliance on firearms would be less effective (Smith et al. 2012). ...
Technical Report
Full-text available
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Conference Paper
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Hundreds of thousands of bear-human encounters occur each year. Some involve bear-human interactions so close that safe, comfortable coexistence can depend on the ability of humans to read the bear's mood and intentions, and to convey appropriate impressions to the bear. Mood and intentions can be read from a bear's vocalizations, other sounds, gaits, postures, gestures, and facial expressions. Those signals are often misunderstood, in part because (a) few people are familiar with bears, and may expect them to signal like dogs or cats; or because (b) they see bears through preconceptual "lenses" colored rose by romantic fantasies or red by nightmarish imagination and media hype. Accurate interpretations of brown bear (Ursus arctos) body language will be illustrated using diagrams, slides, audio/video recordings. Signals will be identified which are diagnostic of various motives for aggression (e.g., protectiveness of self or cubs; competition for status, mates or resources; or predation) and for non-aggressive behaviors (e.g., play which may involve aggression-like actions; curiosity; appeasement). Methods will be presented for sounding out a bear whose signals are ambiguous, and for defusing aggression. The kinds of human behavior likely to appease a frightened bear can differ from those which effectively appease or deter a domineering bear and those which discourage a predatory bear.
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Full-text available
The sex, age, and other characteristics of 668 brown bears (Ursus arctos) killed in nonsport circumstances in Alaska during the period 1970-85 were examined. These data represent an unknown fraction of total nonsport kills as not all kills were reported. Both sport harvests and nonsport kills are increasing in Alaska. Nonsport harvests averaged 5.1% of total sport and nonsport kills. Areas with the highest human density had the highest ratio of nonsport to sport harvests. Nonsport harvests are most common during periods when most people are in remote areas to hunt or fish. Males predominate in the nonsport kills of younger bears and females in the nonsport kills of older bears. Regulations and other factors make adult male bears more vulnerable to sport hunters than adult female bears. Partially as a result, nonsport kills contain more adult females than sport kills. An analysis based on affidavits from 224 persons killing bears revealed that bears were shot to avoid perceived danger (72%), to protect property (21%), and to eliminate nuisances (7%). Int. Conf. Bear Res. and Manage. 7:51-58 Human presence in bear habitat usually leads to conflicts between bears and people, frequently with fatal consequences for the bear but rarely leading to injury or death for the person (Herrero 1985). In all of the United States except Alaska, brown-grizzly bears (hereafter brown bears) are so rare that the incidence of such contacts is too small to permit thorough analyses of the characteristics of the bear subpopulation that comes into conflict with humans. Herrero (1985) studied circumstances in which brown bears caused injuries to humans, and others examined circumstances where bears caused depredation prob- lems (Murie 1948, Johnson and Griffel 1982, Jor- gensen 1983, Knight and Judd 1983). Greer (1981) investigated deaths of Montana and Wyoming grizzly bears in nonsport circumstances. Jope (1983) pre-
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Attacks by large carnivores on humans can occasionally help to generate significant resistance to carnivore conservation efforts. We have reviewed research addressing concerns for human safety in large carnivore conservation, and have evaluated statements about the frequencies and causes of attacks based on our findings concerning i) existing data on the number of attacks by large carnivores in various parts of the world; ii) information systems documenting details of attacks; and iii) research that provides credible advice on what to do when encountering a large carnivore, to minimize the likelihood of being attacked. We conclude that little information exists for any of these criteria and what is available is often inadequate to determine the frequency of attacks, their causes and how to avoid them. We suggest that information systems, including database(s) on attacks and encounters, should be established for large carnivore conservation efforts, to supply information and to answer future requests for this information.
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As use of Akaike's Information Criterion (AIC) for model selection has become increasingly common, so has a mistake involving interpretation of models that are within 2 AIC units (ΔAIC ≤ 2) of the top-supported model. Such models are <2 ΔAIC units because the penalty for one additional parameter is 2 AIC units, but model deviance is not reduced by an amount sufficient to overcome the 2-unit penalty and, hence, the additional parameter provides no net reduction in AIC. Simply put, the uninformative parameter does not explain enough variation to justify its inclusion in the model and it should not be interpreted as having any ecological effect. Models with uninformative parameters are frequently presented as being competitive in the Journal of Wildlife Management, including 72 of all AIC-based papers in 2008, and authors and readers need to be more aware of this problem and take appropriate steps to eliminate misinterpretation. I reviewed 5 potential solutions to this problem: 1) report all models but ignore or dismiss those with uninformative parameters, 2) use model averaging to ameliorate the effect of uninformative parameters, 3) use 95 confidence intervals to identify uninformative parameters, 4) perform all-possible subsets regression and use weight-of-evidence approaches to discriminate useful from uninformative parameters, or 5) adopt a methodological approach that allows models containing uninformative parameters to be culled from reported model sets. The first approach is preferable for small sets of a priori models, whereas the last 2 approaches should be used for large model sets or exploratory modeling.
Chapter
IntroductionSummary Measures of Goodness-of-FitLogistic Regression DiagnosticsAssessment of Fit via External ValidationInterpretation and Presentation of the Results from a Fitted Logistic Regression ModelExercises