Open Journal of Forestry
2014. Vol.4, No.1, 28-33
Published Online January 2014 in SciRes (
Is Evidence-Based Conservation Applied in Urban Forestry?
A Case Study from Toronto, Canada
Adam R. Martin1,2, W. Eric Davies1, Danijela Puric-Mladenovic1,2, Sandy M. Smith1,2*
1Faculty of Forestry, University of Toronto, Earth Sciences Building, Toronto, Canada
2Information Management and Spatial Analysis, Southern Science and Information Section, Ministry of Natural
Resources, Peterborough, Canada
Email: *
Received October 12th, 2013; revised November 19th, 2013; accepted December 6th, 2013
Copyright © 2014 Adam R. Martin et al. This is an open access article distributed u nder the Creative Commons
Attribution License, which pe rmits unrestricted use, distrib ution, and reprodu ction in any medium, provided the
original work is properly cited. In accordance of the Creative Commons Attribution License all Copyrights ©
2014 are reserved for SCIRP and the owner of the in tellectual property Adam R. Martin et al. All Copyright ©
2014 are guarded by law and by SCIRP as a guardian.
Evidence-based conservation seeks to incorporate sound scientific information into environmental deci-
sion making. The application of this concept in urban forest management has tremendous potential, but to
date has been little applied, largely because existing scientific studies emphasize the importance of urban
forests in large-scale ecological and anthropogenic processes, but in practice, scientific evidence is os-
tensibly incorporated into North American urban forest management only when deciding the fate of indi-
vidual trees. Even under these disjunctive conditions, the degree to which evidence influences tree-level
decisions remains debatable. In analyzing preliminary data from a case study from Toronto, Canada, we
sought to test if and how scientific evidence factored into the decision to remove or preserve 53 trees, lo-
cated in close proximity to a provincially significant area of natural and scientific interest (ANSI). We
found that by far the strongest tree-level correlate of the recommendation to remove or preserve trees was
whether or not an individual tree was in conflict with proposed development. In comparison, species
identity, tree condition, and suitability for conservation were statistically unrelated to the final recom-
mendation. Our findings provide the basis to expand our analysis to multiple case studies across Canada,
and internationally. Furthermore, when interpreted with available research and policy, our preliminary
(and future) analysis highlights clear opportunities where scientific evidence can and should be readily
incorporated into urban forestry management and policy.
Keywords: ANSI; Arboriculture; Black Oak; Evidence-Based Conservation; Land Use Planning; Toronto;
Tree Bylaw; Urban Forestry; Urban Forest Policy
In managed ecosystems, conservation policy and practice
have traditionally been based on expert knowledge or qualita-
tive information, as opposed to systematic evaluation of empir-
ical scientific evidence and/or data (Sutherland et al., 2004).
Inspired by changing practices in medical sciences, over the
past decade, conservation biologists have sought to reverse this
trend by promoting the concept of “evidence-based conserva-
tion” (Pullin & Knight, 2001). Generally, evidence-based con-
servation is a framework that suggests that environmental man-
agement decisions should build upon rigorous scientific infor-
mation stemming from well-designed experiments or other ob-
jective and quantitative data (Pullin & Knight, 2003; Sutherland
et al., 2004).
To date, evidence-based conservation has been more applied
to management of “traditional” systems such as operational
forests and agricultural complexes (e.g. Dicks et al., 2013), or
certain taxonomic groups such as birds and pollinators (e.g.
Williams et al., 2012). Reviewing the scientific evidence asso-
ciated with management activities in these systems has pro-
vided insights into how management may achieve or fail to
reach certain environmental goals. Systematically assessing
scientific evidence associated with management has also re-
vealed important gaps in our ability to evaluate and ultimately
modify management practices in relation to environmental
goals. For example, in managed North American forests biodi-
versity conservation is a well-recognized goal, but due to a lack
of information and/or scientific evidence there is considerable
uncertainty as to how well current forest management practices
are meeting biodiversity targets (Boutin et al., 2009).
With respect to urban forestry (sensu Konijnendijk et al.,
2006), the concept of evidence-based conservation has a com-
plex and multi-scale application. On one hand, some of the
strongest evidence in support of conserving and increasing
urban green spaces is at larger spatial scales, such as individual
parks or greenspaces, or entire urban forests as defined by mu-
nicipal boundaries. For instance, the potential for urban forests
to mitigate pollution and sequester CO2 has been well docu-
mented for a number of cities globally (e.g. Nowak, 2006;
Pataki et al., 2006). Similarly, biodiversity and greenspace size/
*Corresponding author.
proximity metrics have been identified as correlates of human
psychological and physical well-being (e.g. Full er et al., 2007),
while total tree canopy was found to correlate with socio-eco-
nomic patterns within cities (Donovan & Butry, 2010) and hu-
man mortality rates across states (Donovan et al., 2013).
The effects of urban forests have traditionally been cumula-
tively measured in order to provide solid scientific evidence of
the ecological and socio-economic benefits at relatively large
spatial scales. However, policy makers have generally neg-
lected the idea that these positive cumulative effects of urban
forests are highly dependent on the ecological value of individ-
ual trees: the organisms that are most affected by existing land
development and/or conservation policies, or lack thereof. One
reason for this is that critical laws and policies pertaining to
urban forest planning and conservation have been historical,
and remain commonly, at the individual tree level (Kon-
ijnendijk et al., 2006; Ordóñez & Duinker, 2013); this, despite
the benefits of urban forests, and evidence in support of their
conservation, are largely understood at the municipal level. An
early example of this disparity is the “tree warden laws” passed
between 1896-1901 in the northeastern United States: laws
explicitly permitting municipalities to appoint tree wardens to
oversee the planting, care, and removal of individual trees
(Ricard, 2005).
Similarly in Canada, typical urban forest management goals
(e.g. species diversity, tree size distribution targets) are based
on, and achieved through, individual tree-level maintenance
and planting programs (e.g. Ordóñez & Duinker, 2013); wheth-
er or not these goals are met is then in turn highly contingent on
urban forest policies (Barker & Kenney, 2012; Kenney et al.,
2011). One example is the City of Toronto’s municipal private
tree bylaw (City of Toronto, 2013), which places strict limita-
tions on the removal of any trees 30 cm diameter at 1.3 m
above ground (“dbh”), and requires the replacement of any
trees that are removed. By comparison, ecosystem-level target s
such as wildlife habitat provisioning and climate change miti-
gation are very poorly defined in Canadian urban forestry
management plans (Ordóñez & Duinker, 2013), despite consi-
derable scientific evidence demonstrating the role urban forests
can play in these ecological processes (e.g. Chace & Walsh,
2006; Nowak, 2006).
Urban forest by-laws and their specific details related to sin-
gle trees have critical implications to decision making and evi-
dence-based conservation in Canadian urban forests. Often, the
final decision for or against tree removal is obtained through a
legal process, where a consulting arborist’s opinion about the
consequences of tree removal is taken as rigorous scientific
evidence. Decision making should therefore be informed by
bylaws and tree-level information including species identity,
tree diameter at breast height (dbh), tree age, and tree condition
(City of Toronto 2013). From a technical perspective, these
lines of evidence should be straightforward to measure because
they are objective, quantitative, and prone to little error and
interpretation relative to ecosystem-level metrics. From an
ecological perspective, these metrics should reliably inform an
objective opinion on the consequences of tree removal, as a
number of scientific studies point to the ecological importance
of these relatively simple tree-level characteristics such as dbh
and species identity (e.g. Lacey, 1986; Lindenmayer et al.,
2013). Even tree condition, arguably the most subjective and
error-prone of tree-level measurements, can be objectively as-
sessed with standard, unbiased and repeatable inventory proto-
cols, or other technologies (e.g. Moore, 1999). However, when
competitive interests exist for valuable urban space, it can be
debatable how single tree-level biological evidence is incorpo-
rated into tree assessments, and ultimately, into the advisement
for or against tree preservation in urban forests. In this prelimi-
nary analysis we present one such example.
Here, we present an analysis of the evidence used in a recent
decision to remove or preserve 53 individual trees in close
proximity to a provincially significant ecological area, in To-
ronto, Canada, in advance of an ongoing high-density residen-
tial development. Using publically available court documents,
we sought to provide the first stage of a larger analysis that
evaluates the extent to which scientific evidence is used when
recommending the removal or preservation of urban trees. In
doing so, we also sought to identify areas and opportunities
where scientific evidence can and must be entered into urban
forest conservation policies and practices.
A Case Study from Toronto
Study Site
Our preliminary study was based at the site of an ongoing
residential development located north of High Park, a 161-ha
greenspace in central T oronto, Canada (43˚38'47''N, 7 9˚27'47''W;
Figure 1). The park itself (High Park) maintains approximately
60% canopy cover and is bound by streets to the north (Bloor
Street), east (Parkside Drive), and south (Queensway), and by
both a street (Ellis Park Drive) and 14.2-ha pond (Grenadier
Pond) to the west (Figure 1; Kidd et al., 2000). In addition to
being a popular recreational site, High Park contains a rare
remnant patch of oak savannah that prior to European settle-
ment was once part of a savannah ecosystem that remains in
less than 1% of its original distribution in southern Ontario.
The oak savannah canopy is dominated by black oak (Quer-
cus velutina), and maintains a high-diversity understorey com-
prised of several grass and forb species, many of which are
provincially rare (Kidd, et al., 2000). Since 1999, the savannah
ecosystem in High Park has been actively restored and ma-
naged through a combination of periodic controlled burns and
removal of exotic species (Kidd et al., 2000). The City of To-
ronto has designated High Park as an “Ecologically Sensitive
Area” (ESA), and has incorporated the park into its natural
heritage system. Due to the rarity of the oak savannah ecosys-
tem at a provincial scale, large portions of High Park have also
been designated by the government of Ontario as an “Area of
Natural and Scientific Interest” (ANSI; Figure 1; Kidd et al.,
Our study was based at a 0.65-ha development site located
approximately 25 m north of the northern boundary of High
Park (43˚39'13''N, 79˚27'46''W; Figure 1). The site is the loca-
tion of an ongoing high-rise development, which was pre-
viously a high-density area occupied by 13 two-to-three-storey
residences. The site is slated to be replaced by a single
14-storey mixed residential-retail building (Ages Consultants
Limited, 2013). The primary ecological concern prior to com-
mencing development was determining whether or not several
of the large trees on the site were to be conserved, based on
their ecological value and condition. Specifically, it was re-
quired that an impact study be conducted that would make ex-
plicit recommendations to preserve or remove 53 individual
Figure 1.
Location of case study site in Toronto, Canada (red outline), relative to the area of natural and
scientific interest (ANSI) in High Park (g reen shaded areas), as delinetated by Ontario’s Minis try
of Natural Resources.
trees, based on visual examinations performed following stan-
dardized arboricultural criteria (Tree Care Industry Association,
Tree-level evaluations were conducted in the summer of
2012 at which time data from an arboricultural assessment were
presented within a report provided by a consulting arborist
(Ages Consultants Limited, 2013, their Appendix 3). Within the
report several qualitative and quantitative tree-level measure-
ments were presented: 1) tree species identity; 2) tree size ex-
pressed as diameter at breast height (dbh); 3) tree condition,
assessed as “poor”, “fair”, “good”, “excellent”, or “hazardous”
(following the Council of Tree and Landscape Appraisers,
2000); 4) Tree by-law policy requirements for tree protection
determined by location and dbh (e.g. “Trees with diameters of
30 cm or more, situated on private property on the subject
site.”); 5) suitability for conservation, categorized as “poor”,
“moderate”, or “good”, which was in turn derived based on the
criteria: a) tree health, b) structural integrity, c) species re-
sponse, and d) tree age and longevity (following standards of
Tree Care Industry Association, 2012); and 6) generalized qua-
litative comments on tree status. In the final category, the only
information presented for each individual tree assessed is
whether or not it was “in conflict with proposed construction”
versus “clear of proposed construction”. Based on the set of
these six tree-level attributes, an explicit recommendation was
made for each tree as “remove”, “preserve”, or “transplant”.
Data Analysis
Our analyses were designed to examine the relationship be-
tween tree-level attributes measured and assessed, and the final
tree-level recommendations (“remove”, “preserve”, or “trans-
plant”) of the impact study (Ages Consultants Limited, 2013).
For all analyses, we treated the final recommendation as a bi-
nary response variable as being either “preserve” or “remove”
(coded for analysis as 1 and 0 respectively); the single tree
recommended for a “transplant” was classified as “preserve”.
We first used Chi-square tests to examine if the number of trees
falling into each “tree condition” category were significantly
related to “final recommendation”; the same analysis was per-
formed to examine the relationship between “tree suitability for
conservation” and “final recommendation”. For these analyses,
due to several expected frequencies that were very low, all
Chi-square test statistics and associated P-values were calcu-
lated using Monte Carlo simulations with 2000 replicates used.
We then used a logistic regression model to examine what
tree-level variables best predicted the final recommendation.
The logistic regression was performed as a generalized linear
model with a binomial error distribution, and was of the form:
( )
01234 5
Sp dbh Cd St Cf
ββ βββ β
−+ +++ +
where p represents the probability that a tree will be recom-
mended for preservation, ßo represents the intercept, ß1
represents the coefficient for species (“Sp”), ß2 represents the
coefficient for tree dbh, ß3 represents the coefficient for tree
condition (“Cd”), ß4 represents the coefficient for suitability for
conservation (“St”), and ß5 represents the coefficient for
whether or not the tree was in conflict with development (“Cf”).
We then used a backward stepwise regression procedure on the
full model (Equation (1)) to identify which set of predictor
variables most parsimoniously explained the recommended
outcome. Models were compared using Akaike’s Information
Criteria (AIC) with the lowest AIC indicating the most parsi-
monious prediction of recommended outcomes. All data ana-
lyses were performed using R v. 2.10.1 (R Foundation for Sta-
tistical Computing, Vienna, Austria).
Of the 30 total trees deemed to be of “good” suitability for
conservation, 5 were recommended for preservation while 25
were recommended for removal. Trees deemed to be of “mod-
erate” suitability were largely recommended for removal (n = 7)
as opposed to preservation (n = 1). All trees of “poor” conser-
vation suitability (n = 15) were recommended for removal. The
number of trees falling into each suitability-by-fina l-recom-
mendation category did not differ significantly from a random
expectation (χ2 = 2.78, P = 0.206), suggesting suitability for
conservation was statistically unrelated to the final recommen-
Similarly, we found that tree condition and final recommen-
dation were statistically unrelated, with the distribution of indi-
viduals falling into each condition-by-recommendation group
not differing significantly from a random expectation (χ2 = 5.33,
P = 0.176). Of the trees considered to be of “fair” condition (n
= 35), 85.7% were recommended for removal (n = 30) while
14.3% were recommended for preservation (n = 5). All trees in
the “poor” (n = 14) and “hazardous” (n = 2) condition catego-
ries were recommended for removal, while the two trees
deemed to be of “good” quality were split evenly between re-
moval and preservation recommendations. No trees evaluated
were deemed to be of “excellent” quality.
We found that the most parsimonious explanation of recom-
mended outcomes was predicted by a combination of whether
or not the tree was in conflict with the proposed development,
and tree dbh (AIC = 9.6 vs. AIC = 46 in the full model, Table
1). Of these two variables, tree conflict was a much more im-
portant variable: the AIC value of a model including only the
conflict term (AIC = 13.72) was considerably lower than that
from a model with only tree dbh as a predictor (AIC = 36.73;
Table 1). This was supported by qualitative evaluation of the
data. Of the total trees recommended for preservation (n = 6),
only one was in conflict with development (though this tree
was in fact recommended for transplantation). All other trees in
the dataset that were in conflict with construction (n = 47) were
recommended for removal. Recommendations for preservation
or removal based on dbh were less systematic: of the six trees
slated for preservation dbh ranged widely from 2 - 41 cm dbh,
with a mean preserved tree dbh of 24 ± 17.7 (s.d.) cm dbh.
Information on tree species identity, tree condition, and tree
suitability for conservation were not retained as important pre-
dictors of final recommendations (Table 1).
In urban forestry, conservation and management decisions,
or recommendations on the fate of individual trees, should be
based on quantitative information such as: tree-level characte-
ristics (i.e. species, age, and tree size); objective and repeatable
evaluations of tree condition; and importance of urban trees at
different spatial scales of urban forests (i.e. across land use
types, municipalities, neighborhoods, etc.). This is ostensibly
the purpose of mandating standard tree evaluations prior to
development, and is ultimately critical if we are to incorporate
urban forest conservation into land use planning. Given that
urban forestry is an applied science (Konijnendijk et al., 2006)
and interacts with other disciplines (e.g. land use planning), it is
tempting to think that evidence-based urban forest conservation,
management and planning are implicitly incorporated into the
decision making process. The results from our preliminary
analysis raise questions as to the validity of this underlying
In our preliminary case, we found no empirical evidence that
tree-level metrics or ecological considerations had any influ-
ence on the final recommendations about the removal or con-
servation of the 53 trees. Recommendations on tree removal or
conservation, prior to development were almost wholly deter-
mined by whether or not an individual tree was in conflict with
the planned development. Tree level measurements were not
Table 1.
Aikaikes information criteria (AIC) values for six competing logistic
regression models used to predict the final recommendation to remove
or preserve 53 individual trees in Toronto , Canada. The functional f orm
of the full logistic regression model is presented in Equation (1), where
predictor variables include species (“Sp”), tree dbh, tree condition
(“Cd”), suitability for conservation (“St”), and whether or not the tree
was in conflict wit h dev elo p ment (“Cf ”). The most parsimonious model
fit is highlighted in bold.
Model parameters AIC
Sp + dbh + Cd + St + Cf 46
dbh + Cd + St + Cf 16
dbh + Cd + Cf 12
dbh + Cf 9.6
Cf 9.72
dbh 32.73
taken into account, nor were 1) the fact that the site and trees
are in close proximity (~25 m) to a provincially significant
ANSI (Figure 1), and 2) the fact that these trees contribute to
overall urban canopy of the area. Whether or not this finding is
supported in other cases, both in Canada and elsewhere, will be
the focus of our future research.
To further motivate the importance of this type of research, it
should also be noted that our analysis here was restricted to
only those empirical and qualitative data available for trees in
our analyzed impact assessment report (Ages Consultants
Limited, 2013). However, a cursory review of other informa-
tion (as well as associated policy guidelines such as the City of
Toronto tree bylaw (2013)) raises additional questions as to
whether any ecological evidence is being incorporated into the
actual land development decision-making. For example, one of
the six trees recommended for preservation in our study was a
22-cm dbh black ash tree (Fraxinus nigra), a tree that is highly
likely to be killed by the invasive emerald ash borer (EAB)
(Agrilus planipennis) within a very short timeframe (Kovacs et
al., 2010). In fact, in North American cities where EAB is
present, preemptive ash removal is a recognized strategy for
managing this rapidly spreading invasive species (Vannatta et
al., 2012). Similarly, seven of the total trees recommended for
removal had the added notation of “irreversible decline with
limited lifespan”. These observations were based on qualitative
assessments of tree crown dieback made in summer in 2012;
one of the hottest and driest years on record for Toronto
(Environment Canada, 2013). Therefore, observations of di-
eback may well reflect short-term leaf and crown responses to
extreme weather, as opposed to “irreversible decline” (e.g.
Filewod, 2011); in larger trees crown thinning could also reflect
natural ontogenic changes in leaf area index (Nock et al., 2008).
Additionally to our knowledge, there are no existing studies
directly linking crown dieback to prospective tree lifespan; for
example, one study analyzing > 7500 A. saccharum trees across
Ontario found no evidence for a relationship between crown
condition and short-term (1 - 2 years) mortality rates (Tomina-
ga et al., 2008). To support evidence-based decision making,
tree lifespan could potentially be predi cted t o within a ~15-year
span using dendrochronological information such as relative
growth rates and short-term growth trends (Bigler & Bugmann,
2004). A more extensive analysis of arborist reports such as the
one analyzed here is needed to determine whether urban forest
practitioners have adopted such scientifically-based methods;
such criteria were certainly not incorporated into the arborist’s
speculation on prospective tree lifespan in our preliminary
study .
Dendrochronological information could also be easily incor-
porated into tree age estimates, which can strongly influence
the decision making process. For example, in our case study all
black oaks >100 years old would predate the original housing
development, and hence represent a genetic remnant of the ad-
jacent black oaks and a remnant of provincially significant oak
savannah habitat (Figure 1). However, ages for the black oaks
were only qualitatively estimated from visual tree assessments,
and were ultimately never precisely quantified prior to removal
(Ages Consultants Limited, 2013). In comparison, our prelimi-
nary dendrochronological analysis, based on photographs of the
tree cross-sections taken while they were being transported to a
dumpsite, suggested that the trees were at minimum 120
years of age. In the absence of definitive age data, all trees on
the study site were considered ornamental landscape trees with
no natural heritage value, and could therefore be simply re-
placed with new individuals (Ages Consultants Limited, 2013).
This lack of definitive tree ages and exclusion of natural herit-
age value ultimately led decision makers to overlook the larg-
er-scale ecological and historical importance of the trees at our
site. For example, removal of the “ornamental” black oaks was
suggested to have no impact on the genetic viability of the
nearby oak population (Ages Consultants Limited, 2013)a
statement that is not at all supported by scientific evidence giv-
en a) the complete lack of dendrochronological data employed
when dating trees (Ages Consulting Limited, 2013), and b) a
poor scientific understanding of minimum viable populations
needed to conserve genetic variability in black oaks, and trees
more generally (Koskela et al., 2013). Qualitatively ageing
trees and the resultant dissociation of trees at our study site
from those at the nearby ANSI (Figure 1), also likely influ-
enced an undervaluing of the ecological role the trees at our site
play in terms of wildlife habitat provisioning (Chace & Walsh,
2006)—a point that deserves considerably more attention than
is permitted in our preliminary analysis.
Over the past decade, urban forestry has emerged as an im-
portant field of study owing to the work of scientists demon-
strating many environmental, social and economic benefits
urban forests provide to built-up areas (Bowler et al., 2010;
Chace & Walsh, 2006; Donovan & Butry, 2010; Nowak, 2006;
Schipperijn et a l., 2013). Unfortunately, these lines of evi dence
do not factor heavily into the existing legalities related to land
development, land use planning, urban forest and tree preserva-
tion: a disconnect that has resulted in the loss of countless trees,
many of which are keystone large old trees (Lindenmayer et al.,
2013), due to development within and of the edge of the cities.
In light of the existing urban development decisions, single tree
assessments, which are often heavily based on an arboricultural
approach, provide information for tree maintenance, but are
simply not enough for impact assessment.
Our intent in this preliminary analysis was to gain insights
into the potential to further study the degree to which scientific
evidence is incorporated into urban forest conservation and land
development policy and practice. Prior to completion of our
comprehensive analysis, our hope is that the case study pre-
sented in this preliminary analysis will serve as a cautionary
tale that data collection and evaluation during impact studies
need to be quantitative and repeatable. We also caution that
decision makers need adequate tree-level and ecological data to
rigorously evaluate impact study reports. Therefore, in moving
towards an evidence-based approach, it is necessary to ensure
that sound scientific data and information are incorporated into
urban forest management and land use planning. Such a rigor-
ous approach to urban forest management and conservation
represents a cross-disciplinary and long-term transformation,
but examples from the field of conservation biology are instruc-
tive in showing that it is possible, timely, and critically impor-
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