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Estimates of the Potential Cost of Emerald Ash Borer (Agrilus planipennis Fairmaire) in Canadian Municipalities

May 2012
Arboriculture & Urban Forestry 38(3):81-91

DOI:10.48044/jauf.2012.014

Authors:

Daniel McKenney

Natural Resources Canada

Donald Barry Lyons

Natural Resources Canada

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Emerald ash borer (EAB) is an invasive phloem-feeding insect causing extensive mortality to ash (Fraxinus sp.) in North America. Economic costs associated with EAB-related mortality of street and backyard trees in Canadian urban areas were estimated over a 30-year time horizon. The approach employed a simple spread model to approximate EAB arrival times at each community based on three maximum spread rates: slow (∼10 km/year), medium (∼30 km/year), and fast (∼50 km/year). Costs are estimated for four discount rates (0%, 2%, 4%, and 10%) and three treatment rates (0%, 10%, and 50% of trees treated with an insecticide). Ash density along urban roads was estimated from a variety of sources, including a recently developed survey that allows for rapid assessment of street tree compositions. Based on the 30 km/year spread rate, a 4% discount rate, and a 10% treatment rate, the present value of the costs is estimated to be approximately CAD $524 million (2010 currency rate); this value increases to roughly $890 million when costs associated with backyard trees are included. These estimates are conservative because they focus only on damage to street (and backyard) trees; nonetheless, their magnitude suggests considerable justifcation for investments to slow the spread of EAB in Canada.

the number of urban areas, the human population, road length, and estimated number of street ash found within the Canadian range of Fraxinus spp.

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Mean economic impact of EAB over time, based on three scenarios: a) slow spread rate and 0% of ash trees treated, b) medium spread rate and 10% of ash trees treated, and c) fast spread rate and 50% of ash trees treated.

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Street tree parameters used to estimate impact of EAB in eastern Canada.

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Sensitivity of EAB economic impact estimates to model parameter values for: a) eastern Canada, b) western Canada, and c) the entire study area. The sensitivity coefficients were generated using a regression approach; larger values indicate more influence on the impact estimates.

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Model parameters and probability distributions used in the sensitivity analysis of EAB economic impacts. Currency is expressed in 2010 Canadian dollars.

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Arboriculture & Urban Forestry 38(3): May 2012

Daniel W. McKenney, John H. Pedlar, Denys Yemshanov, D. Barry Lyons, Kathy L. Campbell,

and Kevin Lawrence

Estimates of the Potential Cost of Emerald Ash Borer (Agrilus

planipennis Fairmaire) in Canadian Municipalities

Arboriculture & Urban Forestry 2012. 38(3): 81–91

Abstract. Emerald ash borer (EAB) is an invasive phloem-feeding insect causing extensive mortality to ash (Fraxinus sp.) in North America. Eco-

nomic costs associated with EAB-related mortality of street and backyard trees in Canadian urban areas were estimated over a 30-year time horizon.

The approach employed a simple spread model to approximate EAB arrival times at each community based on three maximum spread rates: slow

(~10 km/year), medium (~30 km/year), and fast (~50 km/year). Costs are estimated for four discount rates (0%, 2%, 4%, and 10%) and three treat-

ment rates (0%, 10%, and 50% of trees treated with an insecticide). Ash density along urban roads was estimated from a variety of sources, including

a recently developed survey that allows for rapid assessment of street tree compositions. Based on the 30 km/year spread rate, a 4% discount rate, and

a 10% treatment rate, the present value of the costs is estimated to be approximately CAD $524 million (2010 currency rate); this value increases to

roughly $890 million when costs associated with backyard trees are included. These estimates are conservative because they focus only on damage

to street (and backyard) trees; nonetheless, their magnitude suggests considerable justiﬁcation for investments to slow the spread of EAB in Canada.

Key Words. Agrilus planipennis; Canada; Cost-beneﬁt Analysis; EAB Spread Model; Fraxinus; Urban Forest Management.

Emerald ash borer (EAB), Agrilus planipennis (Coleoptera: Bu-

prestidae), is a metallic wood-boring beetle, native to Asia, that

has destroyed millions of ash trees since being accidentally in-

troduced to North America (Smith et al. 2009). During its larval

stage, EAB feeds on the inner phloem and outer xylem of ash

trees, leading to disrupted vascular ﬂow and ultimately tree death

(Cappaert et al. 2005). Once EAB becomes established in an area,

about 30% of ash trees are killed each year (Herms et al. 2009a);

very few host trees have shown any natural resistance, though

blue ash (Fraxinus quadrangulata Michx.) and Asian ash spe-

cies may be less susceptible (Anulewicz et al. 2007; Rebek et al.

2008). A number of insecticides have proven effective in protect-

ing trees against EAB attack (Herms et al. 2009b; McKenzie et al.

2010); however, they are not likely to be widely applied because

of considerations around cost, efﬁcacy, and safety. Furthermore,

EAB infestations are often difﬁcult to detect until host trees show

obvious signs of stress (McCullough et al. 2009), at which point

it may be too late to reverse the damage (Herms et al. 2009b).

Since being introduced into southern Michigan in the early

1990s (Cappaert et al. 2005), EAB has spread rapidly across east-

ern and central North America, with outbreaks currently reported

from 15 U.S. states and two Canadian provinces (USDA-APHIS

2011). Though a small percentage of mated females are capable

of ﬂying more than 20 km in 24 hours (Taylor et al. 2010), most

larvae that originate from point source introductions are found

within 100 m of adult emergence sites (Mercader et al. 2009).

Thus, human-assisted dispersal via transport of infested ash

material (Cappaert et al. 2005) and/or hitchhiking on vehicles

(Buck and Marshall 2008) is likely the main cause of the ob-

served EAB expansion (Prasad et al. 2010). Over time, EAB is

expected to continue its advance across Canada and the United

States, decimating ash in urban and rural settings along the way.

Given its rapid rate of spread and the prevalence of ash in

both natural and urban forests across much of eastern and cen-

tral North America (Burns and Honkala 1990; Woodall et al.

2009), EAB clearly has the potential to bring about signiﬁcant

economic and ecological impacts. Several studies have produced

regional economic impact estimates in the U.S. (Kovacs et al.

2010; Sydnor et al. 2007; Sydnor et al. 2011). The objective

of the current study was to report on efforts to generate EAB-

related cost estimates for Canadian urban areas. The approach

employs a relatively simple spread model to coarsely simulate

EAB expansion to Canadian communities over a 30-year period.

For each community in the study area, costs related to ash

removal, replacement, and treatment are estimated and then

discounted according to the timelines projected by the spread

model. The lack of spatial data on ash distribution and abun-

dance in Canada presents a signiﬁcant challenge for this type

of study. A variety of sources were used to estimate ash abun-

dance along urban streets, including early results from a sur-

vey that allows rapid assessments of street tree composition.

This research focused on street trees because they can be reli-

ably and rapidly surveyed and are almost certain to require

management action (i.e., removal/replacement or treatment)

if attacked. This is an underestimation of total EAB impact.

Regulatory efforts to prevent the introduction of alien species

to Canada and associated research are federal responsibilities,

while long term management of established pests requires strong

McKenney et al.: Cost of EAB in Canadian Municipalities

involvement of provincial ministries and municipalities. The Ca-

nadian Food Inspection Agency has regulatory authority over any

new species entering the country, including the development of

quarantine measures. The Canadian Forest Service is the federal

government’s lead in forest research with a strong capacity in

forest insects and diseases. Provincial and territorial governments

manage most of the forestlands in the country and therefore have

a strong interest in alien species threats. Because of this the Ca-

nadian Forest Service is often engaged in monitoring and survey-

ing efforts. Municipalities (and homeowners) manage removal,

replacement, and treatment efforts in the urban setting—often

bearing the ﬁnancial burden of these frontline activities. All of

these stakeholders have expressed the desire for more quan-

titative damage estimates to help justify mitigation activities.

METHODS

Study Area and Associated Data

This study was carried out for Canadian urban centers that fall within

the natural geographic range of native ash (Fraxinus sp.) as deﬁned

by Little (1971) (Figure 1). Urban centers were identiﬁed using a

digital version of Canada’s urban areas cartographic boundary ﬁle

(Statistics Canada 2007). For this coverage, an urban area is deﬁned

as having a population of at least 1,000 persons and a density of not

fewer than 400 persons per square kilometer. There are 895 urban

areas across Canada in this database; 641 of these fall within the

native range of ash (Figure 1). The study is road based, so a digital

version of the national road network was intersected with the urban

areas boundary ﬁle to provide an estimate of the kilometers of road

in each of these communities. A summary of the human popula-

tion and road network in these communities is provided in Table 1.

Estimating Urban Ash Component in Eastern

Canada

For estimating EAB impacts, the primary focus of the study

authors was ash trees within 10 m of urban roadways (“street

trees”) as these trees would almost certainly require action (i.e.,

removal/replacement or treatment) if attacked. The cost for

these actions would be borne by the municipality, utility com-

pany, or property owner depending on the speciﬁc location and/

or ownership of a given tree. The number of ash street trees

were estimated using a variety of methods and data sources for

both eastern and western Canada. Potential impacts to back-

yard trees were also included as an additional focus. There are

other trees in the urban setting, such as those in parks and ri-

parian areas, which could also have direct ﬁnancial costs if at-

tacked. Reliable data on these urban forest components are

difﬁcult to ﬁnd, hence, not further considered at this stage.

The primary data source on ash abundance in eastern Canada

is a survey that was developed to help rapidly assess the compo-

sition of street trees. Data currently exists for 16 urban centers

in Ontario and New Brunswick, Canada (Table 2). Brieﬂy, the

survey protocol involves participants walking or driving routes

(0.5 km in length) randomly located throughout an urban center.

Trees within 10 m of the road edge are identiﬁed and placed in

coarse height classes (small = 1.5 to 5.0 m; medium = 5.0 to 10.0

m; large = >10 m). In total, the routes covered approximately

10% of the total length of roads in each urban center. While de-

veloping the survey, this level of coverage yielded reasonably ac-

curate estimates of percent cover for major street tree species.

From this data, the total number of trees per km of road was

calculated, the percentage of those trees that were ash, and the

percentage of ash in each size class (Table 2). The survey was

web-based and random survey routes were generated for all 895

urban areas in Canada (contact the authors for further details).

Surveys are ongoing that will enable further reﬁnements to the re-

sults presented here and support other alien species risk analyses.

These tree survey data were augmented with information

from existing tree inventories for Canadian urban centers, for

example, information for three cities in eastern Canada (Table

2) from the Urban Forest Effects model (Nowak et al. 2010).

This program was designed to collect forest composition data

from urban areas in the U.S., but has been applied to several

Canadian communities as well. Information for the city of St.

Johns, Newfoundland, Canada (Table 2) (Environmental De-

sign and Management, Ltd. 2006) was also obtained. All of

these surveys were carried out to estimate tree species composi-

tion for the entire urban landscape. For this analysis it was as-

sumed that the relative composition values were representative

of trees within 10 m of city streets (i.e., deﬁnition of street trees).

A ﬁnal source of information came from high resolution sat-

ellite imagery available through Google Maps. It was not pos-

sible to identify trees to the species level with this approach,

but it was possible to count the total number of trees within 10

Figure 1. Geographical range of Fraxinus spp. (shaded) and lo-

cations of urban centers (dots) in Canada; urban centers falling

within the shaded area were included in the current study.

Table 1. The number of urban areas, the human population, road length, and estimated number of street ash found within the

Canadian range of Fraxinus spp.

Region Urban Human Road Estimated number of ash trees

areas (N) population length (km) Small Medium Large Total

Eastern Canada 545 17,282,389 86,477 138,363 216,193 190,250 544,806

Western Canada 96 1,510,706 11,074 96,348 223,704 364,350 684,401

Total 641 18,793,095 97,552 234,711 439,897 554,599 1,229,207

Arboriculture & Urban Forestry 38(3): May 2012

m of city streets. This was done for a total of 150 randomly lo-

cated 0.5-km street segments across six Ontario cities (Table 2).

During this process, several other pieces of information were

gathered. First, to estimate impacts in residential backyards,

the number of trees in backyards were counted along the same

150 random street segments used to count street trees (Table

2). In cases where houses backed onto woodlots, making prop-

erty lines difﬁcult to distinguish, only trees within 10 m of the

woodlot edge were counted, as these would have a higher likeli-

hood of being treated or removed in the case of an EAB attack.

The ratio of street trees to backyard trees was 1:1, suggesting

that street tree costs could be doubled to include the backyard

component. However, not all streets are fronted by dwell-

ings with backyards (i.e., some are fronted by parks, industrial

parks), thus the percentage of urban roads fronted by residen-

tial dwellings at the same 150 road segments was also estimated.

Based on these estimates, backyard tree impacts are expected

to be about 68% of those associated with street trees (Table 2).

Estimating Urban Ash Component in Western

Canada

Different data sources were available for provinces in western

Canada (e.g., Manitoba, Saskatchewan, and Alberta). The For-

estry Branch of Manitoba Conservation provided a GIS database

of an ash inventory that had been carried out for 16 urban cen-

ters in Manitoba. To make these data comparable to the street

tree data for eastern Canada, the study authors selected only trees

within a 10 m buffer of the road system in each community. Each

tree in the database had a height attribute, and so were classi-

ﬁed into the same height classes as those outlined for eastern

Canada. The number of street ash per kilometer of road was cal-

culated for each of the 16 communities by summing the number

of street trees in each size class and then dividing each total by

the length of the urban road system in that community (Table 3).

Due to a lack of comparable data from other western provinces,

these values were applied to Saskatchewan and Alberta as well.

There were notable differences in the relative abundance of

ash in eastern and western Canada. In western Canada, there was

an average of 8.7, 20.2, and 32.9 street ash/km in the small, me-

dium, and large size classes, respectively (Table 3); comparable

numbers for eastern Canada were 1.6, 2.5, and 2.2 street ash/km

(calculated from Table 2). This approximately 8× higher inci-

Table 2. Street tree parameters used to estimate impact of EAB in eastern Canada.

City Provincez Data Trees/km % Ash % Ash % Ash % Ash Ratio of %

sourcey road <5 m 5–10 m >10 m backyard to house

tall tall tall front yard trees frontage

Bathurst NB S 84.4 4.0 0 100 0 - -

Barrie ON G 100.4 - - - - 0.95 60.3

Bracebridge ON S 185.7 0.0 - - - - -

Chatham ON S, G 115.9 - - - - 0.75 62.7

Fredericton NB S 123.0 0.0 - - - - -

Guelph ON S, G 112.7 6.3 8.1 16.2 75.7 1.21 82.7

Halifax NS P - 0.4 - - -

Huntsville ON S 164.4 1.5 0 0 100 - -

Kitchener ON G 95.7 - - - - 0.98 74.1

London ON S 97.1 3.3 - - -

Meaford ON S 120.8 8.2 12.5 25.0 62.5

Moncton NB S 72.1 0.1 - - - - -

Oakville ON P - 9.2 - - -

Ottawa - Gatineau ON G 115.5 - - - - 1.05 68.6

Oromocto NB S 149.3 0.4 - - - - -

Owen Sound ON S 106.2 6.7 23.1 46.2 30.8

Parry Sound ON S 50.5 19.8 35 25 40 - -

Sault Ste Marie ON S 91.4 2.2 5.9 28.2 65.9

St. Johns NFLD P - 7.8 - - -

South Porcupine ON S - 1.7 0 36.3 63.6

Sudbury ON S 59.0 4.9 - - -

Thunder Bay ON G 76.8 - - - - 1.08 54.4

Timmins ON S 124.0 0.4 - - - - -

Toronto ON P - 7.8 - - -

Averagex 107.6 6.0 10.4 34.6 54.8 1.0 67.5

z NB = New Brunswick; ON = Ontario; NS = Nova Scotia; NFLD = Newfoundland.

y S = street tree survey; G = Google Maps; P = published values. See text for complete details.

x Average is weighted by population size of urban areas.

Table 3. Number of small, medium, and large ash trees per

kilometer of urban road for 16 communities in western Canada.

Urban area Province Ash trees per km of urban road

<5 m tall 5–10 m tall >10 m tall

Manitou Manitoba 0.1 36.3 38.0

Treherne Manitoba 11.1 31.2 46.6

Altona Manitoba 10.6 35.6 51.2

Beausejour Manitoba 6.3 8.7 16.1

Carberry Manitoba 6.7 22.3 36.5

Carman Manitoba 21.6 19.3 49.2

Dauphin Manitoba 2.6 13.6 18.4

Deloraine Manitoba 26.4 30.7 66.8

Rivers Manitoba 8.8 4.2 16.6

Selkirk Manitoba 3.9 10.0 15.1

Souris Manitoba 11.5 27.7 44.7

Steinbach Manitoba 9.5 24.3 39.8

Stonewall Manitoba 7.6 7.7 16.3

Virden Manitoba 9.0 11.2 23.0

Winkler Manitoba 23.0 48.7 79.6

Portage La Prairie Manitoba 2.8 13.6 19.0

Averagez 8.7 20.2 32.9

z Average is weighted by population size of urban areas.

McKenney et al.: Cost of EAB in Canadian Municipalities

dence of ash in western Canada was supported by two sources:

1) Google Maps counts of street trees at 16 random locations

in four Manitoba communities indicated that there were about

twice as many street trees in Manitoba than Ontario, and 2) street

tree composition data for the city of Saskatoon, Saskatchewan

(Geoff McLeod, pers. obs.) indicated that about 25% of street

trees were ash, approximately 4× that of eastern Canada. This

pattern is perhaps not surprising given the more limited num-

ber of tree species that can tolerate the somewhat more extreme

climate found in the prairies region (McKenney et al. 2007).

Predicting EAB Spread

The Canadian Forest Service Forest Bioeconomic Model (CFS-

FBM) was used as the basic modeling framework for projecting

EAB spread over time. The model shares conceptual similarities

with the spread model described by Yemshanov et al. (2009a),

Yemshanov et al. (2009b), and Koch et al. (2009). Brieﬂy, CFS-

FBM provides a grid-based modeling framework for simulating

a variety of processes in a spatial setting, including the spread,

establishment, and impact of alien species. For example, the

model has been used to examine potential wood supply im-

pacts from Sirex noctilio, an invasive alien wasp species (Koch

et al. 2009; Yemshanov et al. 2009a; Yemshanov et al. 2009b).

A simpliﬁed version of CFS-FBM was used to obtain a

coarse depiction of how EAB might spread across the country.

The approach required a spread probability-density function,

or ‘kernel,’ which determined the probability of EAB spread as

a function of the geographic distance to locations with known

EAB infestations. Published EAB spread rates vary by more

than two orders of magnitude, reﬂecting the highly variable

spread of EAB under different conditions. The smallest report-

ed value (30 m/yr) was for a new infestation starting from a

single source (a pile of infested logs) with many ash trees in

the near vicinity (Mercader et al. 2009). In contrast, Kovacs et

al. (2010) reported an average spread rate of 16 km/yr based

on spread data in Michigan, U.S., over the period 1994–2009.

Similarly, Smitley et al. (2008) reported a rate of 10.6 km/yr

for the spread rate of detectable symptoms for an outbreak

in southeastern Michigan over the period 2003–2006. These

larger estimates are based on data that include natural long

distance dispersal events that may be induced by high popula-

tion density and/or low host availability, as well as regional-

scale, human-assisted movements (such as trade and trans-

portation). Based on comparison to observed rates of spread

in southern Ontario, the spread rate reported by Smitley et al.

(2008) was adopted as a baseline value for the current study.

The spread model simulations covered an area extend-

ing from maritime Canada in the east to Alberta in west-

ern Canada with a map cell resolution of ~1 km2. The

model employed a negative exponential function to deter-

mine the probability, p that a cell would become infested as

a function of its distance, d from the nearest infested cell:

[1] p = e-0.0943d

The value of the exponent in Equation 1 (i.e., 0.0934) was

determined such that the mean distance deﬁned by the equation

is 10.6 km (i.e., the desired average spread rate as previously

outlined). To address the wide variation in potential spread rate,

the model was run with three different maximum spread values

to represent slow, medium, and fast linear rates of spread cor-

responding to approximately 10, 30, and 50 km/year. The maxi-

mum spread value truncates the negative exponential probabili-

ty-density function, thus placing an upper limit on the extent of

annual spread – a key factor controlling overall spread rates and

patterns (Koch et al. 2009; Yemshanov et al. 2009a; Yemshanov

et al. 2009b). This approach produced a uniform spread pattern

that predicted consistent arrival times that were not inﬂuenced

by rare (and highly uncertain) long-distance dispersal events.

The model was run over a 30-year time horizon to generate

expected arrival times for EAB at each map cell in the study area.

The model was initiated from known Canadian and U.S. EAB

occurrence locations as of 2009 (USDA-APHIS 2011). An im-

plicit assumption was that any cell that fell within the study area

contained at least some ash that could be a host (and hence path-

way) for colonization. This assumption was necessary because,

as previously noted, detailed spatial data of ash abundance were

not available in Canada; furthermore, ash is considered relatively

common throughout its native Canadian range (Farrar 1995).

Unit Cost Estimates for EAB Damage

Four types of costs were explicitly incorporated into this

study: removal costs, replacement costs, treatment costs,

and what were termed as community overhead costs (Ta-

ble 4). All cost estimates are in year 2010 Canadian dol-

lars and based on a combination of published values from the

United States. (Kovacs et al. 2010) and personal communi-

cations with City Foresters in Windsor, Toronto, Oakville,

London, Ottawa, and Thunder Bay, Ontario; and Saskatoon.

It was assumed that all ash street trees, as deﬁned in this

study, required either removal or treatment. Removal costs

vary widely according to tree size (height and diameter), lo-

cation (e.g., proximity to buildings, and power and telephone

lines), and contractor rate; the cost estimates attempted to de-

scribe an average cost for small, medium, and large trees (Ta-

ble 4). Replacement costs are also highly variable and depend

on the size and source of the planting stock; the estimate of

CAD $400 is representative of the per tree costs incurred by

municipalities when planting well established (i.e., ~ 4 cm in

diameter) saplings. It was posited that only a certain percent-

age of removed trees would actually be replaced; in lieu of

data on this subject, a 50% replacement rate was assumed.

Insecticide treatments were incorporated into the model

as an alternative to cutting large and medium sized trees.

Three plausible treatment scenarios were considered: 1) no

treatments; 2) a modest treatment rate, where 10% of large

and medium trees were treated; and 3) a high treatment rate,

where 50% of large and medium trees were treated. Cur-

rently, the main product used in Canada for protecting trees

against EAB attack is TreeAzin™ (McKenzie et al. 2010).

Treated trees were tracked in a separate cost stream that re-

ceived ongoing biannual treatments for the remainder of the

simulation; cost estimates were based on reported costs as-

sociated with TreeAzin for large and medium trees (Table 4).

Community overhead costs are intended to represent consider-

ations such as staff time to manage and coordinate the response,

communication costs, monitoring and surveillance costs, and dis-

posal operations for tree waste. Based on discussions with city

Arboriculture & Urban Forestry 38(3): May 2012

foresters, it was estimated that these costs would be approximately

$0.40/household – applied in each year that an outbreak was on-

going in a given city. The number of households in each commun-

ity was obtained from Statistics Canada (Statistics Canada 2007).

Three different positive discount rates were employed: 2%,

4%, and 10%. These rates reﬂect different perspectives on the

value of delaying payment for incurred costs. In addition, re-

sults are presented with no discounting (a zero discount rate),

to demonstrate the effect of discounting. Some economists

provide theoretical arguments that very low discount rates are

justiﬁable when signiﬁcant intergenerational outcomes are at

stake; species losses could arguably be taken as one such out-

come (Weitzman 1994; Portney and Weyant 1999). For the

positive discount rates, the authors also report the cost esti-

mates in equivalent annual dollars (see Boardman et al. 2001).

Model Scenarios and Sensitivity Analysis

The model was run for 36 different combinations of spread rate

(slow, medium, and fast), treatment rate (0%, 10%, and 50%),

and discount rate (0%, 2%, 4%, and 10%). As with any model,

there was uncertainty in the input parameters; to address this, 100

Monte Carlo simulations were run for each of the 36 scenario

combinations using the @Risk software package (Pallisade Cor-

poration 2002). During each simulation, the value for each input

parameter was drawn from a user-deﬁned distribution of possible

values. Since there were multiple estimates of the tree composi-

tion parameters for eastern and western Canada, a Gaussian dis-

tribution for each parameter was deﬁned using mean and standard

deviation values calculated from the data (Table 4). Due to the rel-

atively small amount of empirical data behind the remaining input

parameters, they were assigned a triangular distribution for the

Monte Carlo simulations. This distribution requires knowledge of

mean, min, and max values, and assumes only a simple triangular

shape. Plots of cumulative mean cost against simulation number

indicated that 100 replications were adequate for this analysis.

The inﬂuence of each input parameter listed in Table 4 on

regional and total EAB economic impact was estimated us-

ing a regression approach (Pallisade Corporation 2002). For

this analysis, each iteration of the simulation produced an ob-

servation for a multiple regression model with cost as the de-

pendent variable and the input parameters as the independent

variables. The standardized slope coefﬁcient associated with

each input parameter was taken as its measure of inﬂuence.

RESULTS

Overall Economic Impact

Approximately 545,000 and 684,000 ash street trees were esti-

mated in eastern and western Canada, respectively, for a total of

~1.2 million ash street trees across the 641 communities included

in the study area (Table 1). Estimated impacts for the 30-year time

horizon ranged from $265 million to $1,177 million depending

on the combination of spread, treatment, and discount rates (Ta-

ble 5). The low estimate resulted from the slow spread rate, 10%

discount rate, and 50% treatment rate; the high estimate resulted

from the fast spread rate, 0% discount rate and 50% treatment

rate. Figure 2 shows cost accumulation through time for selected

spread and treatment rates. These estimates are for street trees

only; the inclusion of expenses associated with backyard trees

can be roughly estimated by multiplying the values in Table 5 by

a factor of 1.7, bringing the range to $451 million to $2,001 mil-

lion. Total costs associated with a "middle-of-the-road" scenario

(i.e., medium spread rate, 10% treatment rate, and 4% discount

rate) were $524 million; this would increase to roughly $890.8

million if expenses related to backyard trees were included.

As would be expected, faster spread rates were associated

with higher economic impacts (Table 5). For example, total street

tree costs ranged from $265 million to $506 million (at posi-

tive discount rates) for the slow spread rate compared, to $371

million to $820 million for the fast spread rate (Table 5). These

Table 4. Model parameters and probability distributions used in the sensitivity analysis of EAB economic impacts. Currency is

expressed in 2010 Canadian dollars.

Parameter name Region Distribution Distribution

type parameters

Total trees/km Eastern Gaussian Mean = 108; S.D. = 30

% Ash Eastern Gaussian Mean = 0.06; S.D. = 0.04

% Ash - small Eastern Gaussian Mean = 0.1; S.D. = 0.1

% Ash - medium Eastern Gaussian Mean = 0.35; S.D. = 0.3

% Ash - large Eastern Gaussian Mean = 0.6; S.D. = 0.3

Small ash/km Western Gaussian Mean = 9; S.D. = 7

Medium ash/km Western Gaussian Mean = 20; S.D. = 12

Large ash/km Western Gaussian Mean = 33; S.D. = 19

Removal - small ($) Canada Triangular Mean = 150; Min = 50; Max = 250

Removal - medium ($) Canada Triangular Mean = 500; Min = 300; Max = 700

Removal - large ($) Canada Triangular Mean = 1000; Min = 700; Max = 1300

Replacement ($) Canada Triangular Mean = 400; Min = 250; Max = 550

Replacement rate (%) Canada Triangular Mean = 0.5; Min = 0.2; Max = 0.8

Treatment - large ($) Canada Triangular Mean = 165; Min = 115; Max = 215

Treatment - medium ($) Canada Triangular Mean = 110; Min = 60; Max = 160

Community cost ($ per Canada Triangular Mean = 0.4; Min = 0.2; Max = 0.6

household)

Detection lag (years) Canada Discrete Uniform (2,3,4)

uniform

McKenney et al.: Cost of EAB in Canadian Municipalities

differences stemmed from the number of communities attacked

over the 30-year time horizon under the fast (634 communities

attacked) and slow (386 communities attacked) spread scenarios.

In fact, based on the slow spread rate, the infestation had not

reached western Canada by the end of the simulation period

(Table 5). This is evident in Figure 2, where there is an obvi-

ous rise in costs mid-to-late in the simulation under the me-

dium and fast spread rates due to the arrival of EAB at cities

in western Canada (particularly Winnipeg, Manitoba); a simi-

lar pattern does not appear under the slow dispersal rate. This

result is largely driven by the high ash abundance in western

communities. There is, of course, an inverse relationship be-

tween the present value of the cost estimates and the discount

rate. For example, a 2% discount rate resulted in costs rang-

ing from $413 million to $870 million, while a 10% discount

rate produced costs ranging from $265 million to $422 mil-

lion (Table 5). Higher discount rates effectively reduce the

present value of future costs. The inﬂuence of discount rate

was also apparent in Figure 2 where the low discount rate

was associated with higher costs, particularly under the fast

spread rate and 50% treatment rate; conversely, the high dis-

count rate resulted in considerably lower costs and relatively

little difference in cost projections between scenarios. Note

however that the equivalent annual cost estimates in Table 5

increase as the discount rate increases. While this may seem

counterintuitive, it is a standard result because present val-

ues of annuities decrease as interest rates increase and in-

crease when interest rates decline (see Boardman et al. 2001).

As might be expected, increased treatment rates had higher

overall costs for the 0%, 2%, and 4% discount rates; however,

this pattern was reversed under the 10% discount rate (Table 5).

This result is particularly sensitive to the time horizon of the

simulation and the spatiotemporal pattern of the spread. Many

large urban centers in eastern Canada (e.g., Toronto, Ontario;

Montreal, Quebec) were attacked very early in the simulation,

thus a large pool of trees accumulated substantial treatment costs

by the end of the 30-year period. Since treatment costs are ac-

cumulated through time, they are also strongly inﬂuenced by

the discount rate. For example, under a medium spread rate and

0% discount rate, treating 50% of trees resulted in a total cost of

$914 million; for the same spread and treatment rates, this value

dropped to $318 million under a 10% discount rate (Table 5).

Sensitivity Analysis

Table 5 also presents standard deviations of the cost distribu-

tions for each scenario based on the Monte Carlo simulations.

Standard deviation values were generally within 40% of the

mean, indicating that the impact estimates are relatively robust

to plausible changes in the input parameter values. In eastern

Canada, estimated costs were strongly affected by the proportion

of ash and the number of trees per unit of road length (Figure

3a). Costs associated with removal, replacement, and treatment

of large and/or medium trees made up most of the remaining sig-

niﬁcant input parameters. Detection lag had a relatively minor,

negative impact on cost estimates in eastern Canada. Higher lag

values meant that EAB attacks were detected later, resulting in

lower discounted costs or, for grid cells attacked very late in the

simulation, costs being pushed outside the 30-year time horizon.

In western Canada, the most influential parameter on final

cost estimates was the number of large trees/km (Figure 3b).

Detection lag had a much stronger influence in the west; since

many western communities were attacked very late in the simu-

lation, any increase in the detection lag resulted in a significant

number of grid cells being excluded from the 30-year analysis.

Costs associated with removal, replacement, and treatment of

large and/or medium trees made up most of the remaining sig-

Figure 2. Mean economic impact of EAB over time, based on

three scenarios: a) slow spread rate and 0% of ash trees treated,

b) medium spread rate and 10% of ash trees treated, and c) fast

spread rate and 50% of ash trees treated.

Arboriculture & Urban Forestry 38(3): May 2012

nificant input parameters. For all of Canada, the percentage of

ash street trees and the number of street trees per kilometer of

road were the most influential input parameters (Figure 3c).

Impacts on Speciﬁc Urban Areas

The 10 cities showing the greatest EAB-related impacts differed

depending on the spread and discount rates (Table 6). Toronto,

Ontario; Montreal, Ottawa-Gatineau, and Quebec City, Quebec;

and Hamilton, Ontario, were consistently among the most heavily

affected cities with losses of roughly $100 million predicted for

Toronto and Montreal under each of the scenarios shown in Table

6. As noted, under the slow spread rate, no western communities

were attacked within the simulation timeframe. However, under

the faster spread rates, Winnipeg, Manitoba, was projected to ex-

perience some of the heaviest EAB-related losses – nearly $200

million in undiscounted cashﬂow equivalent. Other cities in west-

ern Canada, such as Brandon, Manitoba, and Regina and Moose

Jaw, Saskatchewan, also make the list when costs are not discount-

ed. These western communities are much smaller than some of the

eastern communities that appear in Table 6, but involve comparable

costs due to the considerably higher abundance of ash along urban

streets. The impact of discounting is large in western communities

because they are generally attacked late in the simulation period.

DISCUSSION

It was estimated that, over a 30-year time horizon, the discount-

ed ﬁnancial costs of EAB on urban street trees in Canada may

range from about $0.3 to $0.9 billion; when backyard trees are

included, the range of projected impacts increases to approxi-

mately $0.5 to $1.5 billion. Kovacs et al. (2010) estimated an

economic impact of $10.7 billion (using a 2% discount rate) for

EAB in urban areas of 25 eastern U.S. states. There are a number

of differences between the studies that help explain the disparity

in the magnitude of these estimates. The population base cov-

ered by the Kovacs et al. (2010) study is about 8× that of the

current study; and since urban costs are closely related to popu-

lation size, this explains much of the difference. Furthermore,

Kovacs et al. (2010) estimated the economic impacts associat-

ed with all ash trees in communities, as opposed to only street

(and backyard) trees in the current study. When these factors

are taken into consideration, the estimates are very comparable.

Using a different approach, Sydnor et al. (2007) estimat-

ed removal and replacement costs of $1 to $4.2 billion for the

state of Ohio alone, with costs increasing to $1.8–$7.6 billion

when tree-related beneﬁts such as shading, stormwater mitiga-

tion, pollution abatement, and property values were included

in the calculation. In a related study, Sydnor et al. (2011) esti-

mated removal and replacement costs of $5.7–$11 billion for

Table 5. Estimated economic impacts (mean and standard deviation) of EAB on street trees in Canada over a 30-year time

horizon. Equivalent annual values are shown in parentheses. Currency is expressed in 2010 Canadian dollars.

Max. spread rate Treatment rate Discount Eastern Canada Western Canada Total

(km/year) (% ash treated) rate (%) Mean S.D. Mean S.D. Mean S.D.

($, millions) ($, millions) ($, millions) ($, millions) ($, millions) ($, millions)

10 (slow) 0 0 468 221 0 0 468 221

2 413 (18) 195 (9) 0 0 413 (18) 195 (9)

4 372 (22) 176 (10) 0 0 372 (22) 176 (10)

10 292 (31) 138 (15) 0 0 292 (31) 138 (15)

10 0 513 251 0 0 513 251

2 440 (20) 216 (10) 0 0 440 (20) 216 (10)

4 388 (22) 190 (11) 0 0 388 (22) 190 (11)

10 292 (31) 143 (15) 0 0 292 (31) 143 (15)

50 0 642 281 0 0 642 281

2 506 (23) 220 (10) 0 0 506 (23) 220 (10)

4 414 (24) 179 (10) 0 0 414 (24) 179 (10)

10 265 (28) 114 (12) 0 0 265 (28) 114 (12)

30 (medium) 0 0 543 270 250 43 793 277

2 482 (22) 240 (11) 149 (7) 26 (1) 630 (28) 244 (11)

4 435 (25) 217 (13) 89 (5) 16 (1) 524 (30) 219 (13)

10 343 (36) 170 (18) 20 (2) 4 (0) 363 (39) 171 (18)

10 0 579 273 235 41 814 283

2 499 (22) 235 (10) 139 (6) 25 (1) 638 (29) 240 (11)

4 441 (25) 207 (12) 83 (5) 15 (1) 524 (30) 210 (12)

10 333 (36) 156 (17) 19 (2) 4 (0) 352 (37) 157 (17)

50 0 741 349 173 32 914 353

2 584 (26) 273 (12) 102 (5) 19 (1) 686 (31) 276 (12)

4 477 (28) 222 (13) 61 (4) 12 (1) 538 (31) 223 (13)

10 305 (32) 140 (15) 14 (1) 3 (0) 318 (34) 140 (15)

50 (fast) 0 0 554 269 467 77 1021 294

2 497 (22) 241 (11) 305 (14) 50 (2) 802 (36) 256 (11)

4 452 26) 218 (13) 202 (12) 34 (2) 654 (38) 228 (13)

10 358 (38) 173 (18) 65 (7) 11 (1) 422 (45) 175 (19)

10 0 602 283 455 83 1058 312

2 524 (23) 246 (11) 296 (13) 55(2) 820 (37) 264 (12)

4 465 (27) 219 (13) 196 (11) 37 (2) 661 (38) 230(13)

10 353 (37) 167 (18) 62 (7) 12 (1) 415 (44) 170 (18)

50 0 778 367 399 61 1177 367

2 615 (27) 290 (13) 255 (11) 39 (2) 870 (39) 289 (13)

4 503 (29) 236 (14) 166 (10) 26 (1) 669 (39) 236 (14)

10 321 (34) 151 (16) 50 (5) 8 (1) 371 (39) 150 (16)

McKenney et al.: Cost of EAB in Canadian Municipalities

communities in four midwestern states, with costs increasing to

$13.4–$26 billion when the extended beneﬁts were considered.

Even after accounting for population size differences, their re-

moval and replacement estimates are about three times higher than

those reported here. Again, this is partly explained by the inclusion

of all street, private, and park trees in their estimates. Another ma-

jor difference is that Sydnor et al. (2007; 2011) did not incorporate

spread dynamics, and hence economic discounting considerations,

into their estimates. As demonstrated here, discounting can have

a major impact on cost estimates. This variation demonstrates the

wide range in projected costs that can result from (sometimes subtle)

methodological differences between impact studies and underlines

the importance of exploring multiple approaches to such work.

The estimates provided here are conservative in a number of

ways, focusing on direct ﬁnancial costs associated with street (and

backyard) tree management. While this represents an important and

more readily quantiﬁable portion of EAB impacts, there are a number

of other direct ﬁnancial considerations that warrant mention. These

estimates do not include costs related to trees in parks and urban

woodlands. Though the number of ash in these land use categories

can be substantial (Nowak et al. 2010), there is signiﬁcant difﬁculty

ﬁnding reliable estimates of ash density for them. Furthermore, it

is not clear what percentage of ash trees in the park\woodland set-

ting would pose safety risks and thus require management action.

These estimates also ignore costs associated with ash trees in smaller

towns and rural residential settings—again, due to data availability.

Finally, it should be recognized that ash trees do exist in urban cen-

ters outside the native range of ash, which could signiﬁcantly add

to the cost of EAB in Canada [e.g., 5.3% of municipal trees in Van-

couver, British Columbia, are ash (McManus, pers. comm.)]. How-

ever, pathways and spread rates into these areas are highly uncertain.

Many other beneﬁts have been attributed to urban trees, including

home value premiums, energy savings, pollution and runoff reduc-

tion, and human health beneﬁts (Dwyer et al. 1992). These beneﬁts

have been quantiﬁed for various locations, allowing approximate

economic values to be attached to urban trees (e.g., McPherson et

al. 2007). Including the loss of these beneﬁts would clearly increase

the economic impact attributed to EAB. In fact, EAB cost estimates

provided by Sydnor et al. (2007) and Sydnor et al. (2011) approxi-

mately doubled when these “landscape values” were included in

their calculations. These beneﬁts were not incorporated here because

widely accepted values do not exist for Canada and published values

are situation dependent (McPherson et al. 2007). Nevertheless, the

incorporation of such values could be the subject of future efforts.

Losses in timber sales would also be expected as a result of an

EAB invasion (Schwan and Elliott 2010). However, detailed spatial

data on ash volumes are not available for much of Canada, making

it very challenging to estimate potential harvest losses in the natural

forest setting. Ash also plays an important ecological role in many

southern Canadian ecosystems. For instance, ash is a common ripari-

an species and its loss will likely effect water quality for both wildlife

and humans (Kreutzweiser 2010). Furthermore, the loss of ash could

have a major impact on biodiversity in agricultural landscapes of

southern Ontario, where it is often a key component of remnant for-

est woodlots (Schwan and Elliott 2010). While these ecosystem ser-

vices are extremely challenging to include in an economic analysis,

they are mentioned here to emphasize the extent to which this assess-

ment underestimates the full impact of this invasive alien species.

For the three lower discount rates, costs increased as treatment

rate increased; this pattern was reversed at the 10% discount rate.

This ﬁnding suggests, for example, municipalities/homeowners

that have high borrowing costs should consider treating a portion

of their trees because this results in a series of smaller, delayed

payments compared to large scale removal and replacement ef-

forts (McKenney and Pedlar 2012). Even at lower discount rates,

the opportunity to spread removal costs over time through the use

of treatments may be appealing to some municipalities. These re-

sults provide a simple approximation of how overall costs may

vary under different treatment rates. However, it is important to

note that decisions to treat versus remove trees can be complex

and involve not only relatively straightforward considerations such

as treatment, removal, and replacement costs, but also more subtle

factors like the inﬂuence of tree cover on property values, energy

budgets, and pollution control. Recent studies have examined this

topic from the perspective of both individual homeowners (McK-

enney and Pedlar 2012) and municipalities (Sadof et al. 2011).

Additionally, these results may be roughly interpreted to sup-

port slow-the-spread efforts against EAB. If the medium or fast

spread rate models are deemed to be more indicative of likely

outcomes, then the cost differences between the slow versus me-

Figure 3. Sensitivity of EAB economic impact estimates to model

parameter values for: a) eastern Canada, b) western Canada, and

c) the entire study area. The sensitivity coefcients were gener-

ated using a regression approach; larger values indicate more

inuence on the impact estimates.

Arboriculture & Urban Forestry 38(3): May 2012

dium and fast spread models are suggestive of potential beneﬁts

for slowing the spread of EAB. The difference in annual costs

between the slow and medium spread rate models are between

$6 million/year and $10 million/year (derived from the differ-

ences in the annuity values shown in Table 5). Cost differences

are of course higher for the slow versus fast rate models ($11–

$18 million/year). Notably in slow rate models, western Canada

has not been affected in the 30-year simulation period. Clearly

the arbitrary cut-off of a 30-year time horizon does affect these

results but with higher discount rates (e.g., 10%), this effect is

lessened simply because of the strong effect of discounting over

that length of time. At the 10% discount rate, the differences

between the fast and slow spread rate models range from about

$11 to $14 million/year ($3 to $7 million/year for the medium

versus slow spread rate). Annual expenditures up to these lev-

els to slow the spread of EAB would be justiﬁed on economic

efﬁciency grounds if indeed they were judged to be effective.

CONCLUSION

EAB-related street tree damage was estimated in the study area

over a 30-year time horizon to range from $265 million to $1,177

million depending on the combination of spread, treatment, and

discount rates (~$451 million to $2,001 million with backyard

trees included). Based on a medium spread rate, 10% treatment

rate, and 4% discount rate, estimated costs were $524 million;

this value increased to $891 million when costs were extended

to include backyard trees. Cast in equivalent annual values,

these estimates range from $18 million/year (2% discount rate,

Table 6. Canadian cities projected to show the greatest economic impact from EAB invasion over the next 30 years; ten cities

are listed for each of three spread rates and two discount rates. Currency is expressed in Canadian dollars.

Max. spread rate 0% Discount rate 4% Discount rate

(km/year) City Impact City Impact

($, millions) ($, millions)

10 (slow) Toronto 96 Toronto 85

Montréal 95 Montréal 76

Ottawa - Gatineau 27 Ottawa - Gatineau 24

Québec 23 Hamilton 18

Hamilton 20 St. Catherines - Niagara 13

St. Catherines - Niagara 15 Kitchener 9

Kitchener 13 Windsor 9

Windsor 10 London 9

London 10 Québec 8

Oshawa 8 Oshawa 7

30 (medium) Winnipeg 161 Toronto 85

Toronto 97 Montréal 78

Montréal 93 Winnipeg 58

Ottawa - Gatineau 27 Ottawa - Gatineau 24

Québec 25 Hamilton 18

Hamilton 20 Québec 15

Brandon 16 St. Catherines - Niagara 13

St. Catherines - Niagara 15 Kitchener 10

Kitchener 13 Windsor 9

Windsor 10 London 9

50 (fast) Winnipeg 172 Toronto 85

Toronto 96 Winnipeg 84

Montréal 92 Montréal 78

Regina 53 Ottawa - Gatineau 24

Ottawa - Gatineau 27 Regina 19

Québec 25 Hamilton 18

Moose Jaw 23 Québec 17

Brandon 22 St. Catherines - Niagara 13

Hamilton 20 Brandon 10

St. Catherines - Niagara 15 Kitchener 10

slow spread, and no treatments) to $45 million/year (10% dis-

count rate, fast spread, and no treatments). Including backyard

trees would increase these annual equivalents to ~$31 million

and $77 million per year. Though conservative, these estimates

are comparable to a similar study carried out in the U.S. (Ko-

vacs et al. 2010), once differences in population size and study

scope are taken into account. Community-speciﬁc cost esti-

mates can be obtained by contacting the corresponding author.

These ﬁndings can provide some justiﬁcation for slow-the-

spread initiatives, such as early detection surveys and wood

movement laws. However, the net value of a slow-the-spread

program depends on two major considerations: 1) the ex-

tent to which it delays EAB arrival at a given urban centre,

and 2) the perceived time value of expenditures as inﬂuenced

by the discount rate. Nevertheless, even just the simple no-

tion of preserving ash in communities for future generations

may be an important consideration for some decisionmak-

ers, especially if EAB proves to be as devastating as some be-

lieve. Given the magnitude of the damage estimates provided

here, there is also considerable economic justiﬁcation for on-

going research efforts to better understand and manage EAB.

Acknowledgements. We thank: Irene Pines, Robert McMahon, and oth-

ers at Manitoba Conservation for generously sharing their ash survey data;

the Ontario Stewardship Rangers and all other volunteers who have helped

to collect street tree data in eastern Canada; and Geoff McLeod, Bill Roe-

sel, Jason Pollard, John McNeil, and Richard Ubbens for feedback on tree

removal and replacement costs. We also thank two anonymous reviewers

for their comments. Any errors remain the responsibility of the authors.

McKenney et al.: Cost of EAB in Canadian Municipalities

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