Copyright © 2009 by the author(s). Published here under license by the Resilience Alliance.
Huijser, M. P., J. W. Duffield, A. P. Clevenger, R. J. Ament, and P. T. McGowen. 2009. Cost–benefit
analyses of mitigation measures aimed at reducing collisions with large ungulates in the United States and
Canada; a decision support tool. Ecology and Society 14(2): 15. [online] URL: http://www.
ecologyandsociety.org/vol14/iss2/art15/

Research, part of a Special Feature on Effects of Roads and Traffic on Wildlife Populations and
Landscape Function

Cost–Benefit Analyses of Mitigation Measures Aimed at Reducing
Collisions with Large Ungulates in the United States and Canada: a
Decision Support Tool
Marcel P. Huijser 1, John W. Duffield 2, Anthony P. Clevenger 1, Robert J. Ament 1, and Pat T. McGowen 1

ABSTRACT. Wildlife–vehicle collisions, especially with deer (Odocoileus spp.), elk (Cervus elaphus),
and moose (Alces alces) are numerous and have shown an increasing trend over the last several decades
in the United States and Canada. We calculated the costs associated with the average deer–, elk–, and
moose–vehicle collision, including vehicle repair costs, human injuries and fatalities, towing, accident
attendance and investigation, monetary value to hunters of the animal killed in the collision, and cost of
disposal of the animal carcass. In addition, we reviewed the effectiveness and costs of 13 mitigation measures
considered effective in reducing collisions with large ungulates. We conducted cost–benefit analyses over
a 75-year period using discount rates of 1%, 3%, and 7% to identify the threshold values (in 2007 U.S.
dollars) above which individual mitigation measures start generating benefits in excess of costs. These
threshold values were translated into the number of deer–, elk–, or moose–vehicle collisions that need to
occur per kilometer per year for a mitigation measure to start generating economic benefits in excess of
costs. In addition, we calculated the costs associated with large ungulate–vehicle collisions on 10 road
sections throughout the United States and Canada and compared these to the threshold values. Finally, we
conducted a more detailed cost analysis for one of these road sections to illustrate that even though the
average costs for large ungulate–vehicle collisions per kilometer per year may not meet the thresholds of
many of the mitigation measures, specific locations on a road section can still exceed thresholds. We believe
the cost–benefit model presented in this paper can be a valuable decision support tool for determining
mitigation measures to reduce ungulate–vehicle collisions.
Key Words: animal–vehicle collisions; cost–benefit analysis; deer; economic; effectiveness; elk; human
injuries and fatalities; mitigation measures; moose; roadkill; ungulate; vehicle repair cost; wildlife–vehicle
collision

INTRODUCTION
Wildlife–vehicle collisions affect human safety,
property and wildlife. The total number of large
mammal–vehicle collisions has been estimated at
one to two million in the United States and at 45
000 in Canada annually (Conover et al. 1995, Tardif
and Associates Inc. 2003, Huijser et al. 2007b).
These numbers have increased even further over the
last decade (Tardif and Associates Inc. 2003,
Huijser et al. 2007b). In the United States, these
collisions were estimated to cause 211 human
fatalities, 29 000 human injuries and over one billion
US dollars in property damage annually (Conover
1

et al. 1995). In most cases, the animals die
immediately or shortly after the collision (Allen and
McCullough 1976). In some cases, it is not just the
individual animals that suffer. Road mortality may
also affect some species on the population level (e.
g., van der Zee et al. 1992, Huijser and Bergers
2000), and some species may even be faced with a
serious reduction in population survival probability
as a result of road mortality, habitat fragmentation,
and other negative effects associated with roads and
traffic (Proctor 2003, Huijser et al. 2007b). In
addition, some species also represent a monetary
value that is lost once an individual animal dies
(Romin and Bissonette 1996, Conover 1997).

Western Transportation Institute, Montana State University, 2University of Montana, Department of Mathematical Sciences

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Although this paper focuses on collisions with large
ungulates, this group is not necessarily the most
abundant or the most important species group hit by
vehicles. Species groups most often reported in
roadkill surveys include amphibians, reptiles, birds,
and mammals (Seibert and Conover 1991, Holsbeek
et al. 1999, Ament et al. 2008, Gryz and Krauze
2008). The relative proportion at which these
species groups are recorded in roadkill surveys in
different countries varies substantially: 1.8%–
70.8% for amphibians, <0.1%–7.4% for reptiles,
3.1%–52% for birds, and 4.2%–87.2% for mammals
(Seibert and Conover 1991, Kratky 1995, Holsbeek
et al. 1999, Gryz and Krauze 2008, Hobday and
Minstrell 2008). A review by Seiler (2003) showed
that the numbers of road-killed birds and mammals
in various countries are typically estimated at
multiple millions per year. Surveys that include
invertebrates indicate that mortality rates of
invertebrates due to collision with vehicles are far
higher than for vertebrates: in one study, 86% of all
observations related to invertebrates (Seibert and
Conover 1991). However, mitigation measures are
most often implemented for species that are large
enough to pose a threat to human safety or species
whose population survival probability is severely
affected by roads and traffic (e.g., Mansergh and
Scotts 1989, van der Ree et al. 2009). In addition,
data collected by law enforcement agencies (crash
data) and transportation agencies (carcass data) are
typically limited to large mammals (Huijser et al.
2007a).
Over 40 types of mitigation measures aimed at
reducing collisions with large ungulates have been
described (see reviews in Hedlund et al. 2004,
Knapp et al. 2004, Huijser et al. 2007b). Examples
include warning signs that alert drivers to potential
animal crossings, wildlife warning reflectors or
mirrors (e.g., Reeve and Anderson 1993, Ujvári et
al. 1998), wildlife fences (Clevenger et al. 2001),
and animal detection systems (Huijser et al. 2006b).
However, the effectiveness and costs of these
mitigation measures vary greatly. When the
effectiveness is evaluated in relation to the costs for
the mitigation measure, important insight is
obtained regarding which mitigation measures may
be preferred, at least from a monetary perspective.
Nonetheless, very few cost–benefit analyses exist
(but see, e.g., Reed et al. 1982), and although this
may seem surprising, wildlife–vehicle collisions, at
least until recently, are not always included in safety
analyses by transportation agencies, let alone in
cost–benefit analyses (Knapp and Witte 2006).

Transportation agencies in the United States and
Canada typically do not have access to basic cost
and benefit data, and do not have comprehensive
analysis tools available to them (Knapp and Witte
2006). Over the last decades, the dominant practice
for transportation agencies has been to install
wildlife warning signs when (variable) thresholds
were reached for ungulate–vehicle collisions
(Knapp and Witte 2006). However, the
implementation of these signs has typically not been
based on a cost–benefit analysis. In addition, such
thresholds typically relate to relatively short road
sections (e.g., 0.25 or 0.50 miles (402 m or 805 m)),
whereas ungulate–vehicle collisions typically need
to be analyzed and mitigated at a larger spatial scale.
Finally, anecdotal information and crash and
carcass data summaries are also used to justify more
substantial mitigation measures such as wildlife
fencing combined with safe wildlife crossing
opportunities, but decisions to implement such
mitigation measures are rarely based on cost–
benefit analyses (Knapp and Witte 2006; Pat
Basting, Montana Department of Transportation,
pers. comm.; Doug Herbrand, Ontario Ministry of
Transportation, pers. comm.).
In this paper, we compare the monetary costs and
benefits of a range of mitigation measures aimed at
reducing collisions with large ungulates. In the
United States, most of the wildlife–vehicle
collisions reported by agencies involve deer
(Odocoileus spp.). In addition, the vast majority of
all animal–vehicle collisions that result in human
injury (86.9%) or human fatality (77%) involve deer
as well (Conn et al. 2004, Williams and Wells 2005).
The numbers vary between regions: in California,
deer amount to 54.4% of the reported animal–
vehicle collisions, in Maine 81.2% (Huijser et al.
2007b). In certain areas, e.g., Maine, collisions with
moose (Alces alces) are relatively numerous
(15.1%) (Huijser et al. 2007b). Of all the claims
submitted to a major auto insurance company in the
United States (national market share about 17.5%)
in 2006–2007 for vehicle repair as a result of a
collision with deer, elk (Cervus elaphus), or moose,
99.2% related to deer, 0.5% to elk, and 0.3% to
moose (n is approximately 180 000) (Dick Luedke,
State Farm Insurance, pers. comm.). In British
Columbia, Canada, 85.6% of all reported animals
killed by traffic were deer (78.6%) or moose (7.0%)
(Sielecki 2004). In the Ottawa-Carleton area,
Canada, 93.1% of all reported animal–vehicle
collisions involved deer (92.2%) or moose (0.9%)
(Tardif and Associates Inc. 2003). For this paper,

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we conducted separate analyses for the costs and
benefits of mitigation measures aimed at reducing
collisions with deer (white-tailed deer (O.
virginianus) and mule deer (O. hemionus)
combined), elk, and moose.
Our cost–benefit analyses do not include passiveuse costs. Passive or nonuse values are generally
based on existence or bequest motives and include
values in addition to those that arise directly due to
the collision (Krutilla 1967, Daily et al. 1997). In
this context, passive values could include the value
individuals (even those who perhaps never drive the
road section of interest) place on having viable
populations of certain species and well-functioning
ecosystems as a result of the reduced road mortality
and a certain amount of connectivity for wildlife
associated with a mitigation measure. Connectivity
across roads for wildlife is also in the interest of
human safety as animals are more likely to break
through a barrier (e.g., wildlife fencing) if safe
crossing opportunities are not provided or if they
are too few, too small, or too far apart. Even if
wildlife fencing is combined with safe crossing
opportunities for wildlife, animals may still end up
in between the fences, caught in the transportation
corridor, and these animals pose a risk to human
safety. For these reasons, it is considered good
practice to accompany absolute barriers, such as
wildlife fencing, with safe crossing opportunities
for wildlife and escape opportunities for animals
that end up in between the fences. For this paper,
we addressed the importance of safe crossing
opportunities for wildlife by reviewing the
individual mitigation measures for their potential
barrier effect on the movements of large ungulates.
The results of our economic analyses apply to the
United States and Canada, but not necessarily to
other countries or regions, because we used species
characteristics and economic data from these two
countries. Furthermore, we realize that the results
of the analyses are directly dependent on the
parameters included in the analyses and the
assumptions and estimates required to conduct the
analyses. Nonetheless, the results of the cost–
benefit analyses allow for much needed direction
for transportation agencies and natural resource
management agencies in the implementation and
further research and development of mitigation
measures aimed at reducing collisions with large
ungulates.

METHODS
Cost–Benefit Analyses
We estimated the effectiveness of 13 types of
mitigation measures for reducing collisions with
large ungulates such as deer, elk, and moose, and
whether these mitigation measures still allow
animals to cross the road (Table 1). Of the 13
measures listed, only wildlife fencing is an absolute
barrier for large ungulates. In addition, we estimated
the costs (in 2007 US$) of these mitigation measures
per year over a 75-year period (Appendix 1, Table
1). The costs included design, construction or
implementation, maintenance, and removal efforts.
The 75-year period is equal to the longest lifespan
of the mitigation measures reviewed (i.e.,
underpasses and overpasses). In the 75th year, no
new investments were projected (only maintenance
and removal costs) for the following mitigation
measures: wildlife fence alone (Fig. 1); wildlife
fence, gap, and crosswalk; wildlife fence,
underpasses, and jump-outs (Figs. 2 and 3); wildlife
fence, and under- and overpasses (Fig. 4); wildlife
fence and animal detection systems (Fig. 5);
elevated roadway; and road tunnel. Jump-outs are
earthen ramps that allow animals that are trapped in
between the fences in the road corridor to walk up
to the top of the fence and jump down to safety. Well
designed jump-outs are low enough to allow
animals to jump to safety, and high enough to
discourage them from jumping up into the road
corridor.
We also estimated the benefits generated by the 13
mitigation measures. The benefits are a combination
of the effectiveness of the mitigation measures in
reducing collisions with large ungulates and the
costs associated with the average collision. The cost
of a collision with a large ungulate typically
increases with the size and weight of the species.
For this analysis, we estimated the costs for the
average collision with a deer, an elk, or a moose
(Appendix 2, Table 2). Some mitigation measures
take considerable planning and installation time.
For such measures, we did not project any benefits
in the first year of the cost–benefit analyses. This
delay in the start of the benefits applied to all
mitigation measures, except seasonal signs,
vegetation removal, population culling, relocation,
and anti-fertility treatment.
For our cost–benefit analyses, all costs and benefits
are in real terms (i.e., constant 2007 US$).

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Table 1. The estimated effectiveness, present value costs (in 2007 US$, 3% discount rate), and costs per
percent reduction of mitigation measures aimed at reducing collisions with large ungulates over a 75-year
time period. The measures are ordered based on their estimated effectiveness. If a measure is estimated to
be 86% effective, it means that ungulate–vehicle collisions are estimated to reduce by 86% as a result of
the implementation of that mitigation measure (e.g., a reduction from 100 collisions to 14 collisions).

Mitigation
measure

Effectiveness

Crossing
opportunity?

Source

Present value Costs per
costs (US$)
percent
reduction
(US$)

Seasonal wildlife warning
sign

26%

Yes

Sullivan et al. (2004): 51%; Rogers (2004):
0%

$3728

$143

Vegetation removal

38%

Yes

Jaren et al. (1991): 56%; Lavsund and
Sandegren (1991): 20%

$16 272

$428

Fence, gap, crosswalk

40%

Yes

Lehnert and Bissonette (1997): 42%, 37%

$300 468

$7512

Population culling

50%

Yes

Review in Huijser et al. (2007a)

$94 809

$1896

Relocation

50%

Yes

Review in Huijser et al. (2007a)

$391 870

$7837

Anti-fertility treatment

50%

Yes

Review in Huijser et al. (2007a)

$2 183 207

$43 664

Fence (incl. dig barrier)

86%
No

Reed et al. (1982) 79%; Ward (1982): 90%
Woods (1990): 94%–97%; Clevenger et al.
(2001): 80%; Dodd et al. (2007): 87%

Yes

Reed et al. (1982) 79%; Ward (1982): 90%
Woods (1990): 94%–97%; Clevenger et al.
(2001): 80%; Dodd et al. (2007): 87%

Yes

Reed et al. (1982) 79%; Ward (1982): 90%
Woods (1990): 94%–97%; Clevenger et al.
(2001): 80%; Dodd et al. (2007): 87%

Fence, underpass, jumpout

86%

Fence, under- and
overpass,
jump-out

86%

Animal detection system
(ADS)

87%

Fence, gap, ADS

87%

Yes

Yes

$2177
$187 246
$6259
$538 273
$8368
$719 667

Mosler-Berger and Romer (2003): 82%; Dodd $1 099 370
and Gagnon (2008): 91%

$12 636

Mosler-Berger and Romer (2003): 82%; Dodd $836 113
and Gagnon (2008): 91%

$9610

$923 555

Elevated roadway

100%

Yes

Review in Huijser et al. (2007a)

$92 355 498

Road tunnel

100%

Yes

Review in Huijser et al. (2007a)

$147 954 696 $1 479 547

Accordingly, as we excluded inflation effects in our
benefit and cost streams over time, we also used real
(as opposed to nominal) discount rates. Presenting
the analysis in nominal terms with inflation included
in future values and an inflation component in the
discount term would be mathematically equivalent.
In order to correctly compare benefit and cost
elements, which are distributed asymmetrically

over time, we computed present discounted values
and amortized these into equivalent annual terms.
The typical pattern for the mitigation measures we
examined is that costs are largely construction
oriented in the present (e.g., an investment in a fence
with an underpass in the first year of a 75-year
period) whereas benefits are distributed more
uniformly over the life of the project (i.e., a certain

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Fig. 1. A 2.4 m (8 ft) high large-mammal fence, with smaller mesh sizes toward the bottom, on U.S.
Highway 93 on the Flathead Reservation, Montana, USA (copyright: Marcel Huijser).

reduction in collisions and associated costs each
year). In this situation, the cost–benefit analysis is
sensitive to the discount rate chosen. The discount
rate simply corrects for the time value of money.
For example, if an individual can earn a fixed 3%
interest on savings or investments, then a dollar
today is worth US$1.03 one year from now.
Conversely, a dollar promised to be paid one year
from now is worth only (discounted to) about
US$0.97 today.
Following the guidance provided in the U.S. Office
of Management and Budget (OMB) Circular A-94

(U.S. OMB 1992) and other federal guidelines (U.
S. Environmental Protection Agency 2000), we
conducted the analyses for real discount rates of 7%,
3%, and 1%. The 7% rate is required by OMB for
federal benefit–cost analyses and is based on a
shadow price of capital theory; specifically (at least
in 1992) 7% is OMB’s estimate of the real after-tax
return on investment in the private sector
(essentially the opportunity cost of instead investing
in public projects). A more widely accepted
discount parameter for at least intra-generational
accounting is choosing a social discount rate based
on the rate at which individuals translate

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Fig. 2. A large-mammal underpass (7–8 m (23–26.2 ft) wide, 4–5 m (13.1–16.4 ft) high) along U.S.
Highway 93 on the Flathead Reservation, Montana, USA (copyright: Marcel Huijser).

consumption through time with reasonable certainty
(e.g., a consumption rate of interest theory). For this,
historical returns on safe assets such as U.S.
Treasury securities are used (post-tax and corrected
for inflation), with empirical estimates for rates in
the 1% to 3% range (U.S. Environmental Protection
Agency 2000). For inter-generational discounting
(for which a project with a lifespan of 75 years would
obviously qualify) other theories based in part on
ethical considerations that explicitly trade-off the
well-being of current and future generations come
into play, and rates of 0.5% to 3% are plausible. As
an example from the economics literature, a recent

survey of several thousand economists on the issue
of an appropriate discount rate for the problem of
global warming indicated a wide-range of opinions
on the appropriate rate, rates declining over the time
period of the analysis from about 4% to 0% for the
very long term, and a long-term average rate of
1.75% in real terms (Weitzman 2001). Sumaila and
Walters (2005) provide an alternative framework
for intergenerational discounting and an overview
of the recent literature on this issue.
After estimating the costs for each mitigation
measure, and after correcting for the discount rate,

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Fig. 3. A short section of perpendicular fence to guide animals on top of a jump-out along a 2.4 m (8 ft)
high fence along U.S. Highway 93 on the Flathead Reservation, Montana, USA (copyright: Marcel
Huijser).

we calculated how much benefit (in 2007 US$) each
mitigation measure needs to generate over a 75-year
period in order to break even and have the benefits
exceed the costs (threshold values). Equation 1
shows our methods for estimating costs:

(1)

The first term is simply the present value of costs
over the period t equals 1 to n with discount rate d
and annual costs (ctj) in year t for mitigation measure
j. The second term is an amortization factor (the
share that yields the annual equivalent of a fixed

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Fig. 4. Wildlife overpass in Banff National Park, Alberta, Canada (copyright: Marcel Huijser).

sum over some time period, as in the annual
payments on a 30-year mortgage); the product of
the two terms equals Aj, which is the amortized real
annual cost over period n for technology j. Annual
benefits are given by Eq. 2:

(2)

Annual benefits are the sum of the reduction in direct
collision costs for species i (equals 1 to m) and any
annual nonuse or passive-use values vij for these
species. With respect to direct collision costs, rj is

the reduction in wildlife–vehicle collisions from
mitigation measure j (r is a ratio) and k is the initial
pre-mitigation level of wildlife–vehicle collisions
per kilometer per year for the road section of
interest. The term rk accordingly is the reduction in
the number of wildlife–vehicle collisions. The
average species-weighted average cost per collision
is the summation of the share of collisions (αi) due
to species i times species-specific collision costs ci.
The summed product of the reduction in collisions
and the average cost per collision (αici) gives the
benefits associated with a given mitigation measure.
Setting annual benefits for mitigation measure j
equal to annual costs and solving for k yields the
breakeven level of pre-mitigation collisions, which
we designate kj*, above which annual benefits will
exceed costs, e.g., net benefits are positive, as shown
in Eq. 3:

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Fig. 5. Animal detection system along U.S. Highway 191 in Yellowstone National Park, Montana, USA
(copyright: Marcel Huijser).

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Table 2. Summary of estimated costs (in 2007 US$) for the average deer–, elk–, and moose–vehicle collision.

Description

Deer
(US$)

Elk
(US$)

Moose
(US$)

Vehicle repair costs per collision

$2622

$4550

$5600

Human injuries per collision

$2702

$5403

$10 807

Human fatalities per collision

$1002

$6683

$13 366

Towing, accident attendance, and investigation

$125

$375

$500

Hunting value animal per collision

$116

$397

$387

$50

$75

$100

$6617

$17 483

$30 760

Carcass removal and disposal per collision
Total

(3)

As one would expect, the number of collisions
required is directly proportional to the mitigation
measure cost A (the higher the costs, the more
collisions needed to justify) and inversely
proportional to the benefit (reduction in collisions)
achieved by the mitigation measure. To the extent
there are annual passive-use benefits (vij), these
reduce annual costs. For the simplified case of a
single species and no passive-use values, the
breakeven value is simply (Eq. 4):

(4)

Note that the right-hand term is simply total annual
costs of the mitigation measure divided by the
benefits (avoided costs) per collision. If one

expresses rj in terms of percent reduction, then Aj/
rj is the cost of a 1% reduction in collisions. It is
useful to compute this unit cost (cost per 1%
reduction) in the following section in comparing the
costs of different mitigation measures. The next two
sections provide a summary of the effectiveness and
costs of the mitigation measures, and the costs
associated with deer–, elk–, and moose–vehicle
collisions.
Effectiveness and Costs of Mitigation Measures
We reviewed approximately 40 different types of
mitigation measures or combinations of mitigation
measures that aim to reduce collisions with large
animals (deer and larger) (for full review see Huijser
et al. 2007b). Based on the available data, 13 of these
measures were considered effective in reducing
collisions with large animals (effectiveness >0%)
(Table 1). For example, if there were 10 reported
collisions with large ungulates per kilometer per
year on a road section, then the implementation of
a combination of wildlife fencing, underpasses, and
jump-outs is estimated to reduce these collisions by
86% to 1.4 reported collisions per kilometer per year
(Table 1). If more than one estimate was available
for the effectiveness of each of the 13 mitigation
measures reviewed, the mean was calculated. As the

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effectiveness of some of the mitigation measures is
highly variable or based on only one study,
additional studies may lead to an adjustment of these
values at a later time. Mitigation measures
considered ineffective (effectiveness estimated at
0% (Huijser et al. 2007b)), lacking effectiveness
data, or having insufficient data were excluded from
the cost–benefit analyses in this paper.
Each mitigation measure’s suitability depends on
the species concerned, the specific objectives of a
project, and local circumstances. This paper does
not discuss the advantages and disadvantages of
each mitigation measure, but it is important to be
aware that some mitigation measures may only be
suited for very specific circumstances. For example,
population culling, the relocation of individuals or
infertility treatment of individuals may only be
practical and effective for relatively small and
closed populations (Seagle and Close 1996,
Rudolph et al. 2000). Furthermore, such measures
are typically applied to deer rather than other
species. See Huijser et al. (2007a) for a discussion
on other considerations.
The estimated costs for each of the mitigation
measures over a 75-year period vary greatly, as did
the costs per percent reduction in collisions (Table
1). Appendix 1 provides a rationale for the estimated
costs of the individual mitigation measures.
Cost Estimates for Deer–, Elk–, and Moose–
Vehicle Collisions
The justification for the cost estimates for deer-,
elk-, and moose–vehicle collisions is in Appendix
2. The total estimated costs for the average deer–,
elk–, and moose–vehicle collision is summarized in
Table 2. As we calculated the costs for an average
collision, the costs of collisions that result in human
injuries or fatalities, in addition to property damage,
are higher than this average. Similarly, the costs of
collisions that result in property damage only are
lower than these average costs. The advantage of
using the costs of an average collision is that no
assumptions have to be made whether a particular
accident (past or future) did or will result in human
injuries or fatalities; this is averaged out. Most of
the costs are associated with human injuries and
fatalities (deer: 56.0%; elk: 69.1%; moose: 78.6%)
rather than vehicle repair costs (deer: 39.6%; elk:
26.0%; moose: 18.2%). Based on a total estimate of
one to two million collisions with large mammals

per year in the United States (Huijser et al. 2007b)
and the estimate that 99.2% of all reported wildlife–
vehicle collisions related to deer, 0.5% to elk, and
0.3% to moose (see introduction), the total
estimated annual costs associated with ungulate–
vehicle collisions is estimated at US$6 247 759 000–
US$12 495 518 000. In Canada, with an estimated
45 000 large mammal–vehicle collisions, the
estimated annual costs are US$281 149 155 (Tardif
and Associates Inc. 2003). Although we
acknowledge that there is geographical variation in
the body size of deer, elk, and moose, and thus in
the costs associated with a collision, the estimates
presented in this manuscript are typically based on
average values for large geographical areas (e.g., a
nation) or the results of several studies in different
geographical areas, resulting in estimates for the
United States and Canada combined rather than
estimates for a particular region.
RESULTS
Illustration Output Cost–Benefit Model
Figure 6 shows the threshold values (in 2007 US$)
for a specific mitigation measure: fencing with
underpasses and jump-outs. For this specific
mitigation measure, there is an initial construction
cost in the first year of US$416 191, with annual
maintenance of US$1500 per year and fence
removal and replacement in year 25 and 50 of
US$107 500 and removal less salvage in year 75 of
US$26 500 (all costs in 2007 US$ per kilometer)
(see Appendix 1 for justification). The present value
(3% discount rate) of this mitigation measure is
US$538 273 and annual amortized value per
kilometer is US$18 123. The annual amortized
values at 7% and 1% are US$32 457 and US$12
437, respectively. These annual costs at the three
discount rates are shown as horizontal lines (Fig. 6).
The lines representing the costs associated with premitigation collisions with deer, elk, and moose cross
the horizontal lines representing the annual
amortized values at the break-even points. For 3%
discount rate, the break-even point for deer, elk, and
moose is 3.2, 1.2, and 0.7 collisions per kilometer
per year, respectively (Fig. 6). If more collisions
occur, then implementing fencing with underpasses
and jump-outs generates economic benefits in
excess of costs. Similarly, if fewer collisions occur
then the implementation of this mitigation measure
has costs in excess of benefits.

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Fig. 6. The number of deer–, elk–, and moose–vehicle collisions per kilometer per year (dotted lines)
needed to reach the threshold values (7%, 3%, and 1% discount rate) (in real 2007 US$) (solid lines) for
fencing with underpasses.

Another way to look at the same data is in terms of
the actual “product” or output of the mitigation
measures, which is the number of collisions avoided
per kilometer per year (Fig. 7). From this
perspective, the average benefits per collision
avoided are constant (horizontal lines in Fig. 7) and
depend on the species: deer US$6617, elk US$17
483, and moose US$30 760 per kilometer per year.

Average costs per collision avoided, however,
decline with the number of collisions avoided,
illustrating the spreading of fixed costs that
underlies the economics of these mitigation
measures. The break-even point for deer, elk, and
moose is at 2.7, 1.0, and 0.6 collisions avoided per
kilometer per year, respectively (Fig. 7). If more
collisions are avoided, then fencing with

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underpasses and jump-outs generates economic
benefits in excess of costs. Similarly, if fewer
collisions are avoided then this mitigation measure
has costs in excess of benefits. Note that the breakeven values divided by the reduction achieved by
the specific fencing with underpasses mitigation
measure of 0.86 (or 86%) yields the break-even
point in terms of pre-mitigation collisions (Fig. 6).

Threshold Values for the Mitigation Measures
The minimum amount (in 2007 US$) that a
mitigation measure needs to generate in order to
reach the break-even point increases with the
discount rate (Tables 3 and 4). However, this value
is not dependent on the discount rate for mitigation
measures that require the same investment every
year (i.e., for vegetation removal and anti-fertility
treatment) (Table 3). These dollar-value thresholds
were translated into break-even points for deer–,
elk–, and moose–vehicle collisions per kilometer
per year (Tables 3 and 4). If a road section has costs
or wildlife–vehicle collision numbers that exceed
these threshold values, then the benefits of that
mitigation measure exceed the costs over a 75-year
time period (measured in 2007 US$). For example,
if a road section averages 0.1 deer–vehicle collisions
per kilometer per year, and if the collisions are
concentrated in certain times of the year, a seasonal
warning sign would be economically feasible
(because the threshold value of <0.1 (3% discount
rate) is exceeded), but this measure is only estimated
to reduce collisions by 26% (see Table 1). If a road
section averages 4.4 deer–vehicle collisions per
kilometer per year, a combination of wildlife
fencing, under- and overpasses, and jump-outs
would be economically feasible (because the
threshold value of 4.3 (3% discount rate) is
exceeded), and this measure is estimated to reduce
collisions by 86% (see Table 1). Naturally, other
mitigation measures that have threshold values
lower than 4.4 deer per kilometer per year would
also be economically feasible. Note that the
threshold values presented in Tables 3 and 4 are
based on a series of assumptions and estimates and
that they should be taken as indicative values rather
than exact values.

Real-World Examples
The costs associated with deer–, elk–, and moose–
vehicle collisions for 10 road sections in the United
States and Canada varied between US$3636 and
US$46 155 per kilometer per year (Table 5). Even
though some of the road sections only have data for
a relatively short period, and the search and
reporting effort varies for the different road sections,
the average costs are higher than the threshold
values for some of the mitigation measures (see
Tables 3 and 4), indicating that the benefits of
implementing such mitigation measures over the
full length of the road sections concerned exceed
the costs, and that these measures would be
economically feasible. When comparing the costs
per kilometer per year to the threshold values in
Tables 3 and 4, please note that these threshold
values are based on a divided four-lane road, and
that two-lane roads have lower threshold values for
some of the mitigation measures (e.g., those that
include under- or overpasses). A more detailed cost
analysis for one of the road sections in Table 5, MT
Hwy 83, showed that, even though the average costs
per kilometer per year may not meet the thresholds
of many of the mitigation measures, certain
locations on a road section can still exceed these
thresholds (Fig. 8). For example, the benefits of
animal detection systems as a stand-alone
mitigation measure exceed the costs on 4.2% of the
76.9 km (47.8 miles) road section. Similarly, this
percentage is 9.4% for wildlife fencing with gaps
and animal detection systems in these gaps and
jump-outs: 16.3% for wildlife fencing with underand overpasses and jump-outs; and 26.8% for
wildlife fencing with underpasses and jump-outs
(Fig. 8).

DISCUSSION
The costs associated with deer–, elk–, and moose–
vehicle collisions are substantial. Most of the costs
are associated with human injuries and fatalities
(deer 56.0%; elk 69.1%; moose: 78.6%) rather than
vehicle repair costs (deer: 39.6%; elk: 26.0%;
moose: 18.2%). Of the approximately 40 different
types of mitigation measures reviewed, only 13
were considered to be effective in reducing
collisions with large ungulates. However, the degree
of effectiveness and the costs of these 13 mitigation
measures vary greatly and, consequently, there are
substantial differences in the threshold values

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Fig. 7. The average costs per collision avoided per year for deer, elk, and moose for the mitigation
measure fencing with underpasses (solid lines) (at 7%, 3%, and 1% discount rate) and the costs
associated with the average deer–, elk–, or moose–vehicle collision (dotted lines) (all in real 2007 US$).

between the individual mitigation measures above
which the benefits of a mitigation measure exceed
the costs. Collision and carcass data from 10 road
sections throughout the United States and Canada
showed that some road sections easily meet the
threshold values for some of the mitigation
measures. This means that the benefits of
implementing such mitigation measures over the
full length of the road sections concerned exceed
the costs and that the implementation of mitigation
measures would be economically feasible.
However, when calculating the average costs of
wildlife–vehicle collisions over relatively long road
sections, potential concentrations of wildlife–

vehicle collisions are ignored. Therefore, it is
important that more detailed analyses are carried
out at a finer spatial scale (e.g., at 0.1–1.0 km or
0.1–1.0 mile resolution) to identify road sections
where the benefits of mitigation measures may
exceed the costs. Previous cost–benefit analyses
estimated that wildlife fencing and wildlife fencing
in combination with underpasses required 7.5 and
11.3 deer–vehicle collisions per kilometer per year,
respectively, at a discount rate of 6% (Reed et al.
1982). These thresholds are higher than in our study,
primarily because Reed et al. (1982) did not include
the costs associated with human injuries and
fatalities.

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Table 3. Threshold values for individual mitigation measures that are estimated to reduce collisions with
large ungulates by ≤50% (see Table 1 for estimated percentages).

Threshold values

Disco- Seasonal
unt
sign
rate

Vegetation
removal

Fence, gap,
signs,
crosswalk,
jump-outs

Population
culling

Relocation

Anti-fertility
treatment

US$/km/yr

1%

$114

$530

$8153

$3040

$12 652

$71 110

US$/km/yr

3%

$121

$530

$10 116

$3099

$12 764

$71 110

US$/km/yr

7%

$140

$530

$14 972

$3215

$13 164

$71 110

deer/km/yr

1%

<0.1

0.2

3.1

0.9

3.8

21.5

deer/km/yr

3%

<0.1

0.2

3.8

0.9

3.9

21.5

deer/km/yr

7%

<0.1

0.2

5.7

1.0

4.0

21.5

elk/km/yr

1%

<0.1

<0.1

1.2

0.4

1.5

8.1

elk/km/yr

3%

<0.1

<0.1

1.5

0.4

1.5

8.1

elk/km/yr

7%

<0.1

<0.1

2.1

0.4

1.5

8.1

moose/km/yr

1%

<0.1

<0.1

0.7

0.2

0.8

4.6

moose/km/yr

3%

<0.1

<0.1

0.8

0.2

0.8

4.6

moose/km/yr

7%

<0.1

<0.1

1.2

0.2

0.9

4.6

Although it may appear attractive to implement
mitigation measures that have relatively low
threshold values, not all mitigation measures reduce
wildlife–vehicle collisions substantially. Therefore,
whereas mitigation measures with relatively low
threshold values and with limited effectiveness may
be considered for road sections with relatively few
wildlife–vehicle collisions, mitigation measures
with higher threshold values and higher
effectiveness may be considered for road sections
that have relatively many wildlife–vehicle
collisions.
Wildlife fencing as a stand-alone mitigation
measure has relatively low threshold values and
reduces wildlife–vehicle collisions substantially.
However, we strongly advise against increasing the

barrier effect of roads and traffic without providing
for safe crossing opportunities at appropriate
intervals (see, e.g., Bissonette and Adair 2008,
Huijser et al. 2008). The reason wildlife fencing has
relatively low thresholds is that connectivity for
wildlife (a passive-use cost) was not included in our
cost–benefit analyses. However, depending on the
species and local population structure, connectivity
across the landscape, including roads, can be critical
for the long-term population viability of the species
concerned, and perhaps especially for species that
may not be frequently hit by cars and that have low
population density in the area (e.g., Jaeger and
Fahrig 2004). Future cost–benefit analyses may
include a monetary value for having viable
populations of different species, as well as other
passive-use values.

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Table 4. Threshold values for individual mitigation measures that are estimated to reduce collisions with
large ungulates by ≥80% (see Table 1 for estimated percentages).

Threshold values

Disc- Fence
ount
rate

Fence,
Fence,
underpass, under- and
jump-outs overpass,
jump-outs

ADS

Fence, gap, Elevated
ADS, jump- roadway
outs

Road tunnel

US$/km/yr

1%

$5223

$12 437

$15 975

$35 279

$25 634

$2 233 094

$3 328 567

US$/km/yr

3%

$6304

$18 123

$24 230

$37 014

$28 150

$3 109 422

$4 981 333

US$/km/yr

7%

$8931

$32 457

$45 142

$41 526

$34 437

$5 369 961

$9 246 617

deer/km/yr

1%

0.9

2.2

2.8

6.1

4.5

337.5

503.0

deer/km/yr

3%

1.1

3.2

4.3

6.4

4.9

470.0

752.8

deer/km/yr

7%

1.6

5.7

7.9

7.2

6.0

811.6

1397.4

elk/km/yr

1%

0.4

0.8

1.1

2.3

1.7

127.7

190.4

elk/km/yr

3%

0.4

1.2

1.6

2.4

1.9

177.9

284.9

elk/km/yr

7%

0.6

2.2

3.0

2.7

2.3

307.2

528.9

moose/km/yr

1%

0.2

0.5

0.6

1.3

1.0

72.6

108.2

moose/km/yr

3%

0.2

0.7

0.9

1.4

1.1

101.1

161.9

moose/km/yr

7%

0.3

1.2

1.7

1.6

1.3

174.6

300.6

Wildlife fencing in combination with underpasses
and jump-outs, or a combination of under- and
overpasses and jump-outs, have thresholds low
enough to be met at many road sections that have a
concentration of collisions with large ungulates.
Although the costs for an individual wildlife
overpass is typically many times that for a wildlife
underpass (estimated at 10 times higher costs, see
Appendix 1), wildlife overpasses only increase the
threshold values by 28.4%, 33.7% or 39.1% (at 1%,
3%, or 7% discount rate, respectively) when used
sparingly in large-scale mitigation projects (in this
case once every 24 km, see Appendix 1).
Animal detection systems as a stand-alone
mitigation measure, and wildlife fencing combined
with both jump-outs and animal detection systems

installed at gaps, have higher thresholds than
wildlife fencing in combination with under- and
overpasses and jump-outs, but they still are low
enough to be met at many road sections that have a
concentration of collisions with large ungulates.
Nonetheless, although the data on the effectiveness
of animal detection systems are encouraging, the
estimate of the effectiveness of this mitigation
measure are not nearly as robust as that for wildlife
fencing in combination with under- and overpasses.
Therefore, animal detection systems should still be
considered experimental (see Huijser et al. (2006a)
for a discussion on the relative strengths and
weaknesses of animal detection systems and
wildlife fencing in combination with under- and
overpasses).

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Table 5. The cost of deer–, elk–, and moose–vehicle collisions for selected road sections in the USA and
Canada (all in 2007 US$). R = research project, HM = highway maintenance reports, AR = highway accident
reports, PWI = park warden incident reports, MSR = meat salvage reports.

Road section

Road length (km) Data collection
and year

Collisions/km/yr Total cost/km/yr
(costs in 2007
(US$)
US$)

SR260 (Christopher Creek section),
Payson, AZ, USA

7.2

R, HM, AR
(2002–2003)

2.64 elk ($46
155)

$46 155

Dodd et al. 2007

I-90 (309.0–330.9) (four-lane),
Bozeman Pass, MT, USA

35.2

R, HM (2003)

3.38 deer ($22
365)
0.21 elk ($3671)
0.06 moose
($1845)

$27 881

Hardy et al. 2006

I-80/90 (50.0–70.0), Indiana Toll Road 32.2
(four-lane), IN, USA

HM (2005)

2.89 deer ($19
123)

$19 123

Sedat Gulen,
Indiana DOT,
pers. comm.

Alaska Hwy 1 (58.0–79.0) (two-lane),
AK, USA

33.8

AR, MSR (2006) 0.56 moose ($17 $17 226
226)

Rick Ernst, Kenai
National Wildlife
Refuge, pers.
comm.

I-95 (near Medway) (four-lane), ME,
USA

32.2

AR (2005)

0.06 deer ($397)
0.53 moose (16
303)

$16 700

Duane Brunell,
Maine DOT, pers.
comm.

Hwy 1, Banff National Park (Phase 3b) 28.1
(two-lane), AB, Canada

AR, R, PWI
(2005)

0.60 deer
($3970)
0.32 elk ($5595)
0.07 moose
($2153)

$11 718

Shelagh Wrazej,
Parks Canada,
pers. comm.

Route 169 (1.0–61.0) (two-lane),
Laurentides Wildlife Reserve, QC,
Canada

61.0

HM, AR (2003)

0.33 moose ($10 $10 151
151)

Yves Leblanc,
Tecsult Inc., pers.
comm.

I-90 (55.0–70.0) (four-lane),
Snoqualmie Pass, WA, USA

24.1

HM (2005)

0.70 deer
($4632)
0.25 elk ($4371)

$9003

Victoria Fursman,
Washington DOT,
pers. comm.

MT Hwy 83 (two-lane), MT, USA

76.9

HM (1998–2003) 1.19 deer
($7287)
0.01 elk ($176)

$7463

Huijser et al.
2006b

Highway 93 S (two-lane), Kootenay
National Park, BC, Canada

34.2

AR, PWI (2005)

$3636

Shelagh Wrazej,
Parks Canada,
pers. comm.

0.41 deer
($2713)
0.03 moose
($923)

Source

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Fig. 8. The costs (in 2007 US$) associated with wildlife–vehicle collisions (deer and elk) along the twolane MT Hwy 83 (mile reference posts 0.0–47.8) per year (average 1998–2003), and the threshold
values (at 3% discount rate) that need to be met in order to have the benefits of individual mitigation
measures exceed the costs over a 75-year time period. Note that the costs at each 0.1 mile concerned and
five adjacent 0.1 mile units were summed (0.6 mile = 1 km) to estimate the costs per kilometer.

Elevated roadways and road tunnels have very high
threshold values, suggesting that these measures are
unlikely to be implemented based on an economic
analysis of deer–, elk–, or moose–vehicle collisions
alone. Elevated roadways or road tunnels appear to
be put in place primarily because of landscape
characteristics (e.g., the presence of a mountain or
a canyon), ecosystem processes (e.g., the flow of
large amounts of water in rivers), and perhaps

concerns for specific threatened or endangered
species (e.g., Evink 2002, Huijser et al. 2007b). This
also illustrates another limitation of our cost–benefit
analyses; it is primarily focused on the costs and
benefits of collisions with large ungulates and the
impacts on human safety. If other parameters are
included it may change the threshold values
substantially.

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The threshold values for the individual mitigation
measures are based on the mitigation of relatively
long road sections (e.g., at least several kilometers
or miles). This is especially important for the
mitigation measures that include safe crossing
opportunities (one safe crossing opportunity per 2
km, see Appendix 1). In this context, it is also critical
to consider the habitat and home range of the species
concerned to prevent individual animals from
simply walking to the beginning or end of a
mitigated road section to cross the road there,
potentially reducing the effectiveness of the
mitigation measure (see, e.g., Huijser et al. 2008).
The costs associated with collisions with large
ungulates are a current estimate and may be subject
to change when additional studies are conducted.
The same is true for the costs (e.g., price of fuel,
concrete, and steel) and effectiveness of the
individual mitigation measures. In addition, mass
production, the use of less expensive materials and
construction techniques, and incorporating mitigation
measures early in the planning of road (re-)
construction projects may further reduce the costs
for mitigation measures. Furthermore, there may be
biases in our estimates for the costs of collisions
with large ungulates. For example, the cost
estimates for deer–, elk–, and moose–vehicle
collisions only relate to the collisions reported to
the insurance industry or to law enforcement
agencies, and one could argue that unreported
collisions are likely to be less costly than reported
collisions. Therefore, we may have overestimated
the average costs of a collision with a deer, elk, or
moose. On the other hand, insurance industry
reports and police accident reports may
underestimate ungulate–vehicle collisions by about
50% (Tardif and Associates Inc. 2003, Riley and
Marcoux 2006), and law enforcement agencies may
only record a fraction (14%) of the deer–vehicle
collisions reported to the insurance industry
(Donaldson and Lafon 2008). Furthermore, in most
states and provinces in the United States and
Canada, no accident report is filled out by law
enforcement agencies if the estimated vehicle
damage is less than US$1000 (Huijser et al. 2007b).
The most conservative approach would be to only
include collisions that were reported to the
insurance industry or law enforcement agencies and
screen the data for potential duplicates. However,
based on the studies cited above, it is clear that such
an approach may lead to a serious underestimation
of the actual costs of collisions with large ungulates,
and one may choose to include carcass reports,

recognizing that although this may overestimate the
average costs associated with a deer–, elk-–, or
moose–vehicle collision, it may still underestimate
the actual number of ungulate–vehicle collisions by
about 50%. Crash and carcass data collection can
be much improved (see also Huijser 2007b), which
would greatly benefit the accuracy of cost–benefit
analyses that evaluate the economic feasibility of
mitigation measures.
CONCLUSION
We believe that the cost–benefit model presented in
this paper can be a valuable decision-support tool
for transportation agencies and natural resource
management agencies when deciding on the
implementation of mitigation measures to reduce
ungulate–vehicle collisions. The tool allows for the
selection of the appropriate road sections as well as
the type of mitigation measure. The results suggest
that there must be many road sections in the United
States and Canada where the benefits of mitigation
measures exceed the costs and where the mitigation
measures would help society save money and
improve road safety for humans and wildlife.
Mitigation measures that include safe crossing
opportunities for wildlife may not only substantially
reduce road mortality, but also allow for wildlife
movements across the road. This connectivity is
essential to the survival probability of the
fragmented populations for some species in some
regions.
Responses to this article can be read online at:
http://www.ecologyandsociety.org/vol14/iss2/art15/
responses/

Acknowledgments:
This effort was funded, in part, by the Wilburforce
Foundation. The authors would like to thank the
Wilburforce Foundation for their support. In
addition, the authors also thank Pat Basting, Duane
Brunell, Rick Ernst, Jon Fleming, Victoria
Fursman, Yves Leblanc, Dick Luedke, Terry
McGuire, Sedat Gulen, Doug Herbrand, Chris
Neher, Lloyd Salsman, Rodney van der Ree,
Bethanie Walder, Shelagh Wrazej, and three
anonymous reviewers for their help, comments, and
suggestions.

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Appendix 1. Cost Estimates for Mitigation Measures
Please click here to download file ‘appendix1.pdf’.

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Appendix 2. Cost Estimates for Deer-, Elk-, and Moose-Vehicle Collisions
Please click here to download file ‘appendix2.pdf’.