-
R
Cm
KS
h
••••
a
ARR1AA
KUVTHH
1
aEcPo(R
(
h0
Landscape and Urban Planning 153 (2016) 74–82
Contents lists available at ScienceDirect
Landscape and Urban Planning
j o ur na l ho me pag e: www.elsev ier .com/ locate /
landurbplan
esearch paper
limate adaptation in cities: What trees are suitable for urban
heatanagement?
evin Lanza, Brian Stone Jr. ∗
chool of City & Regional Planning, College of Architecture,
Georgia Institute of Technology, 245 4th Street NW, Suite 204,
Atlanta, GA 30332-0155, USA
i g h l i g h t s
We examine the effect of hardiness zone shifts on tree
distribution in the US.All Southeastern US MSAs in our study lost
tree species over time.Continuing the hardiness zone shift change
pattern results in greater species loss.Of the projected tree
species lost, deciduous outnumbered coniferous 3 to 1.
r t i c l e i n f o
rticle history:eceived 18 May 2015eceived in revised form4
November 2015ccepted 5 December 2015vailable online 17 May 2016
eywords:rban heat islandsegetationree species distribution
a b s t r a c t
Vegetative enhancement in the form of tree planting has been
found to be a highly effective strategyfor cooling urban
environments, yet as cities continue to warm, the suitability of
urban environmentsfor some tree species is changing with shifting
hardiness zones. Trees are assigned to hardiness zones,which are
based on the average annual minimum temperature that a species can
thrive. In recent decades,human induced global warming has shifted
the location of hardiness zones across the United States. Ourstudy
examines the historical range of ∼200 common US tree species and
how climate change-inducedshifts in hardiness zones are affecting
historical tree ranges in 20 highly populated metropolitan
statisticalareas (MSAs) with high rates of urban heat island growth
over time. MSAs are areas with at least oneurban area of 50,000 or
more people and adjoining territory that has a high degree of
social and economicintegration with the core. We found 6 of the 20
MSAs lost tree species, with the Atlanta (13.51%) and
ardiness zoneseat adaptation strategy
Washington DC (3.61%) MSAs suffering the greatest losses. If
historical rates of hardiness zone migrationcontinue, a simple
projection exhibits >6% average tree species loss across all
MSAs in the study. Ashardiness zones continue to migrate northward
with climate change, heat island mitigation and otherenvironmental
management strategies employing green infrastructure must identify
tree species thatare likely to remain well adapted to urban
climates many years into the future.
Published by Elsevier B.V.
. Introduction
As reported in the 2014 US National Climate Assessment
(NCA),nthropogenic climate change has significantly augmented
thearth’s natural climate oscillations to the point of altering
speciesomposition and distribution across space (Groffman et al.,
2014).ast studies validate the NCA’s conclusions of the negative
impacts
f warming on flora and fauna in land and aquatic
environmentsMeyer, Sale, Mulholland, & Poff, 1999; Parmesan
& Yohe, 2003;oot et al., 2003; Walther et al., 2002). While
some argue global
∗ Corresponding author. Tel.: +1 404 894 6488.E-mail addresses:
[email protected] (K. Lanza), [email protected]
B. Stone Jr.).
ttp://dx.doi.org/10.1016/j.landurbplan.2015.12.002169-2046/Published
by Elsevier B.V.
warming is beneficial for increases in primary productivity,
thesegains are offset by potential increases in forest
fragmentation andadaptation struggles of species shifting to new
habitats (Graham &Grimm, 1990).
In recent decades, the distribution of plants and animals
hasshifted faster than previously thought; Chen, Hill, Ohlemuller,
Roy,and Thomas (2011) recorded species movement to higher
latitudesat the median rate of 16.9 km per decade for 22 taxonomic
groups ofspecies. Plant species, in particular, shifted from the
warmer upperlimits of their range to become more competitive in
cooler areasfurther from the equator (Kelly & Goulden, 2008).
But with new
territory comes new problems: plant species moving northwardmay
be unequipped to cope with diseases and insects of frontierregions
(Kirilenko & Sedjo, 2007). Changes in plant species
distribu-tion have deleterious effects on the ecosystem at large by
fracturing
dx.doi.org/10.1016/j.landurbplan.2015.12.002http://www.sciencedirect.com/science/journal/01692046http://www.elsevier.com/locate/landurbplanhttp://crossmark.crossref.org/dialog/?doi=10.1016/j.landurbplan.2015.12.002&domain=pdfmailto:[email protected]:[email protected]/10.1016/j.landurbplan.2015.12.002
-
and U
iisivag&B
utratr2sr
NcaNacliiAtptacpa
fercsUwaaobfmn&
tzUwic
odsWP
K. Lanza, B. Stone Jr. / Landscape
nterspecies relationships. For instance, plants and animals,
includ-ng humans, are dependent on specific tree species for
energy,afety, and shelter. With over half the world’s population
livingn cities, the benefits of urban forests, for example, energy
conser-ation, storm water management, and air quality
improvement,re increasingly important, and tree range changes
induced bylobal temperature increases are a direct threat to humans
(Bolund
Hunhammar, 1999; Cohen, 2003; Nowak & Dwyer, 2007; Roy,yrne,
& Pickering, 2012).
Among the multitude of ecosystem services provided by trees
inrbanized regions is mitigation of the urban heat island (UHI)
effect,he phenomenon through which cities are warmer than
nearbyural areas. Stone (2007) found most large US cities to be
warmingt double the rate of proximate rural areas, a trend
attributed tohe decrease in vegetation, increase in dark building
materials, andising waste heat emissions in cities (Akbari,
Pomerantz, & Taha,001). As cities warm due to both heat island
formation and globalcale climate change, adaptation strategies are
needed to cope withising exposures to heat amongst urban
populations (Staley, 2013).
The importance of trees in managing UHIs is evident from theew
York City (NYC) Regional Heat Island Initiative (2006), whichites
urban forestry, along with living roofs and light surfaces, asn
effective strategy to decrease urban temperatures. While theYC
Initiative ranks tree species for city plantings based on totalir
quality, air temperature reduction, shading/leaf area,
energyonservation, carbon storage, low allergenicity, and long
relativeife span, a conspicuously absent weighted factor is a
tree’s abil-ty to adapt to changing climate conditions. With US
temperaturesncreasing 1.3 to 1.9 ◦F between 1895 and 2012 (National
Climatessessment, 2014), choosing a tree that can survive in
tempera-
ures warmer than the historical temperatures of its location
willromote the tree’s longevity, consequently increasing the time
aree can be effective in mitigating UHIs. As urban trees
experience
shorter average lifespan, i.e., 19–28 years, than their
non-urbanounterparts (Roman & Scatena, 2011), it is important
that munici-al governments and tree planting organizations select
species welldapted to historical and projected shifts in hardiness
zones.
Vegetative enhancement in the form of tree planting has beenound
to be a highly effective strategy for both cooling urbannvironments
(Rosenfeld, Akbari, Romm, & Pomerantz, 1998) andeducing heat
related health impacts (Stone et al., 2014), yet asities continue
to warm, the suitability of urban environments forome tree species
is changing with shifting hardiness zones. TheS Department of
Agriculture (USDA) assigns tree hardiness zones,hich are based on
the average annual minimum temperature that
species can thrive. Hardiness zones range from 1 to 14, with
theverage annual minimum temperature increasing 10 ◦F for
eachne-zone increase. Each hardiness zone has two subzones, a and,
with the average annual minimum temperature increasing 5 ◦From a to
b (USDA, 2014). In recent decades, human-induced cli-
ate change has tended to shift the location of hardiness
zonesorthward across the US (McKenney, Pedlar, Lawrence,
Campbell,
Hutchinson, 2007).Our study examines the historical range of 199
common US
ree species and how climate change-induced shifts in
hardinessones are affecting historical tree ranges in 20
highly-populatedS metropolitan statistical areas (MSAs) with high
rates of urbanarming. The results of our study can guide
policymakers in select-
ng tree species for urban heat management in the face of
climatehange.
We focus here on the influence of shifting hardiness zonesn
adaptive tree ranges as multiple studies acknowledge the
irect influence of extreme minimum temperatures on treepecies
distribution (Sakai & Wardle, 1978; Sakai & Weiser,
1973;
oodward & Williams, 1987). Iverson, Presad, Matthews,
andeters (2008) found temperature to be the most important factor
in
rban Planning 153 (2016) 74–82 75
predicting current and future tree species habitat. Hardiness
zonesare a suitable proxy for multiple parameters measuring tree
distri-bution because hardiness zones are a widely recognized
standardamong arborists to assess where a tree species can thrive
(USDAAgricultural Research Service, 2014). Another rationale for
usinghardiness zones is the ability to assess species adaptability
withoutspecies-specific analysis. An example of a measure of tree
distribu-tion that requires species knowledge is growing degree
days (GDD)to budburst. This measure follows the formula GDDo = a +
be − kc,with a, b, and k being species-specific constants (Murray,
Cannell,& Smith, 1989). Alternatively, hardiness zones allow
for more effi-cient analysis based on a well-established
temperature metric.
Instead of hardiness zones, several studies implement
ClimateEnvelope Models (CEMs), which predict future tree
distributionbased on calculated essential environmental conditions
from thecurrent species distribution (Hamann & Wang, 2006;
Hijmans &Graham, 2006; Pearson & Dawson, 2003). Mechanistic
Models(MM) are another common approach, in which species
distribu-tion is based off of the physiology of a species (Hijmans
& Graham,2006). Our study differs from climate models, as we
are not pro-jecting tree distribution, but alternatively utilizing
past and presentdata to show changes in species adaptability over
time.
2. Methods
For the purposes of this study, tree species limited to
hardi-ness zones that have shifted beyond the geographic boundaries
ofmetropolitan regions are considered no longer adapted to
theseregions. To identify these species, we first associate common
UStree species with historical hardiness zone ranges and then
mea-sure the extent to which hardiness zones have shifted over
the50 year period of 1961–2010. Tree species found in MSA
hardi-ness zones in the first decade of this period (1961–170) but
notfound in MSA hardiness zones in the last decade (2001–2010)
areclassified as no longer adapted to the region and removed
fromrecommended planting lists.
For a tree species list representative of common tree
speciesacross the United States, we relied on the Arbor Day
Foundation.We consolidated the Eastern, Western, and Central US
species listsinto one that comprised 244 species (Arbor Day
Foundation, n.d.).This tree species list was matched with available
tree species rangemaps in vector polygon shapefile format from the
Geosciences andEnvironmental Change Science Center, resulting in a
final masterlist of 199 tree species for the study (USGS,
2013).
In mapping national hardiness ranges, the USDA
methodologyaverages minimum temperatures over a 30 year period and
doesnot map changes in these zones over time. As regional
climateshave changed significantly over the most recent 30 year
period,here we map hardiness zonal ranges based on ten years of
mini-mum temperature data, permitting the migration of these
rangesto be explicitly measured over a five decade period. To do
so, webase hardiness zone creation on Daly, Widrlechner, Halbleib,
Smith,and Gibson (2012) and make use of temperature data from
theGlobal Historical Climatology Network (GHCN) provided by
theNational Climatic Data Center (2013) of the National Oceanic
andAtmospheric Administration (NOAA). We measure hardiness
zoneshifts for 20 large US MSAs found to have the highest rate of
urbanheat island growth over time (Stone, Vargo, & Habeeb,
2012), asthese regions are confronting decadal rates of warming
higher thanother US MSAs (Table 1). We concentrated on these select
MSAs
for their critical need for urban heat management strategies,
e.g.,tree plantings, to slow their urban heat island growth rates.
Treecover has the dual effect of reducing the global greenhouse
effectthrough carbon sequestration and reducing the UHI effect
through
-
76 K. Lanza, B. Stone Jr. / Landscape and U
Table 1The 20 study sites by population and UHI warming rate
rank.
MSA Population1 UHI warmingrate rank2
Louisville/Jefferson County (LOU) 1,235,708
1Phoenix–Mesa–Scottsdale (PHX) 4,192,887 2Atlanta–Sandy
Springs–Roswell (ATL) 5,286,728 3Greensboro–High Point (GSO)
723,801 4Detroit–Warren–Dearborn (DTW) 4,296,250
5Indianapolis–Carmel–Anderson (IND) 1,887,177 6Las
Vegas–Henderson–Paradise (LAS) 1,951,269 7Syracuse (SYR) 662,577
8Oklahoma City (OKC) 1,252,987 9Toledo (TDZ) 651,429
10Portland–Vancouver–Hillsboro (PDX) 2,226,009 11Richmond (RIC)
1,208,101 12Washington–Arlington–Alexandria (IAD) 5,636,232 13Baton
Rouge (BTR) 802,484 14Albuquerque (ABQ) 887,077 15El Paso (ELP)
804,123 16Minneapolis–St. Paul–Bloomington (MSP) 3,348,859
17Philadelphia–Camden–Wilmington (PHL) 5,965,343 18St. Louis (STL)
2,787,701 19New York–Newark–Jersey City (NYC) 19,567,410 20
se
mwvhoscihcMwa
h
Ft
1 2010 US Census.2 Out of 50 largest US MSAs from 1961 to 2010
(Stone, Vargo, & Habeeb, 2012).
hading and evapotranspiration, making tree planting a key
strat-gy in cities with rapidly growing UHIs (EPA, 2015).
Boundaries for the US and 20 MSAs, 199 tree species rangeaps,
and hardiness zone data from 1961–1970 to 2001–2010ere imported
into a geographic information system (ESRI ArcGIS,
ersion 10.1). The 1961–1970 hardiness zones served as
historicalardiness zones, assumed to represent the long-term
distributionf these zones prior to an accelerated rate of warming
over the sub-equent decades. The 2001–2010 hardiness zones
represent theurrent distribution of hardiness zones. Fig. 1 depicts
the changen hardiness zones from 1961–1970 to 2001–2010. To find
whichardiness zones associate with which MSA in both historical
andurrent time periods, hardiness zone data were clipped by eachSA
boundary shapefile. The remaining hardiness zones found
ithin an MSA boundary were considered the hardiness zones
for
n MSA.To create a US map of the historical tree species ranges
and their
ardiness zones, each tree species range map was spatially
joined
ig. 1. MSA study sites in US hardiness zone change map
(1961–1970 to 2001–2010). wo-unit change.
rban Planning 153 (2016) 74–82
to a US 1961–1970 hardiness zone point data map. The
adaptedspecies list of an MSA was produced using a 200 km buffer
fromthe centroid of an MSA. We make use of a uniform buffer
radiusin selecting adapted tree species to account for the widely
varyinggeographic areas of US metropolitan areas. For MSAs
characterizedby a small geographic area – particularly those
sharing a boundarywith immediately adjacent MSAs – we assume a more
extensiveset of tree species is adapted to the urbanized region
than capturedwithin the boundary itself. To ensure a common species
samplingarea, we employ a uniform buffer area of 200 km – large
enough tofully encompass the largest US metropolitan areas –
centered onthe MSA to identify common tree species adapted to the
region inthe historical period (1961–1970).
If a species is found within 200 km of an MSA centroid, and
thespecies range polygon falls within an MSA hardiness zone, even
ifthe species range does not fall within the MSA boundary itself,
itis considered adapted to the MSA and included in the adapted
treespecies list for the MSA. For example, Fig. 2 shows the
historicalspecies range of Sugar Maple falls within the 200 km MSA
bufferin hardiness zones 6b, 7a, and 7b for the Atlanta MSA. Since
har-diness zones 7a and 7b are two of the three 1961–1970
hardinesszones found within the Atlanta MSA during the historical
period,and Sugar Maple is found within 200 km of the MSA centroid,
SugarMaple is considered adapted to the MSA and placed on the
adaptedspecies list.
For a tree species to remain adapted to an MSA as hardinesszones
shift northward between 1961 and 2010, the species mustbe found
within a hardiness zone intersecting the MSA boundaryin both the
historical (1961–1970) and current (2001–2010) timeperiods. If all
historical hardiness zones shift out of an MSA region,and an
adapted tree species is not found within the new composi-tion of
zones, the tree species can no longer be considered adaptedto the
MSA. Sugar Maple in the Atlanta MSA serves as an exam-ple of a
species lost due to new hardiness zone composition inthe current
period, relative to the 1961–1970 period. Fig. 3 illus-trates the
changing composition of hardiness zones in the AtlantaMSA in both
the historical and current periods. As can be seen inthis figure,
two of the three historical zones – 7a and 7b – shift
completely out of the MSA boundary by the 2001–2010 period,while
a single zone, 8a, remains within the boundary in the
currentperiod. A single new zone, 8b, is added to the MSA for the
currentperiod.
Change is measured as the number of hardiness subzone shifts,
e.g., 3a to 4a is a
-
K. Lanza, B. Stone Jr. / Landscape and Urban Planning 153 (2016)
74–82 77
Fig. 2. Atlanta MSA, Sugar Maple, and the 200 km buffer atop
1961–1970 hardiness zones.
cBoszb
bHietitwptt1wb8
Table 2Species counts per MSA.
MSA # Species (200 km)1 # Species lost2 % Species lost2
Albuquerque 41 0 0.00Atlanta 74 10 −13.51Baton Rouge 59 2
−3.39Detroit 69 0 0.00El Paso 27 0 0.00Greensboro 70 1
−1.43Indianapolis 77 0 0.00Las Vegas 35 0 0.00Louisville 78 0
0.00Minneapolis 51 0 0.00New York 78 0 0.00Oklahoma City 50 0
0.00Philadelphia 77 1 −1.30Phoenix 46 0 0.00Portland 40 0
0.00Richmond 74 1 −1.35St. Louis 72 0 0.00Syracuse 66 0 0.00Toledo
72 0 0.00Washington 83 3 −3.61Average 61.95 0.90 −1.231
Table 3 shows the tree species lost for the 6 MSAs that lost
trees
Fig. 3. 1961–1970 and 2001–2010 hardiness zones, Atlanta
MSA.
For Sugar Maple to remain on the adapted species list for
theurrent period, it must be found historically in zones 8a and/or
8b.ased on an examination of Fig. 2, we can see that the native
rangef Sugar Maple does not extend southward into zones 8a or 8b,
ando as zones 7a and 7b migrate out of the Atlanta MSA, no
hardinessones suitable for Sugar Maple are found within the Atlanta
MSAy the 2001–2010 period.
As a final step in our analysis, we assess potential tree
distri-ution changes in the future by posing the following
question:ow many additional species would be lost through a future
shift
n hardiness zones equivalent to the historical shift observed
forach MSA over the 1961 to 2010 period? While it is not possibleo
reliably project how zones will shift in the coming decades, its
possible to assess the impacts of a shift equivalent in magni-ude
to the changes observed over the last 50 years. For each MSA,e
assume the same number of zones lost over the 1961 to 2010eriod is
again lost through northward migration. We further holdhe number of
zones spanning each MSA after this northward shifto the same number
found in 2010. For example, over the period of961 to 2010, the
Atlanta MSA’s historical zones of 7a, 7b, and 8a,
ere replaced with current zones 8a and 8b for a loss of two
zones
etween the two decades. Under our future projection, the zonesa
and 8b are replaced by the next two zones to the south, 9a and
Adapted species list, 200 km buffer.2 Based on 1961–1970 and
2001–2010 hardiness zone shift within MSA bound-
aries.
9b. We then determine how the future adapted species list
changesthrough a comparison of the species lists for 8a/8b and
9a/9b.
3. Results
From 1961–1970 to 2001–2010, hardiness zone shifts caused6 of
the 20, or 30%, of the MSAs in our study to lose adapted
treespecies (Table 2). Overall, an average of 1.23% tree species
per MSAwas lost due to shifting hardiness zones. The greatest tree
losseswere in Atlanta (10) and Washington DC (3), as these MSAs
lost13.51% and 3.61% of their total tree species, respectively.
in our study. Of the 16 different tree species lost, 56.25% were
decid-uous and 43.75% were coniferous. Two tree species were lost
inmore than one MSA, i.e., Balsam Fir (2) and Black Spruce (2).
-
78 K. Lanza, B. Stone Jr. / Landscape and Urban Planning 153
(2016) 74–82
Table 3MSA and corresponding lost tree species.
MSA Species lost1
Atlanta American Mountain Ash, Blue Ash, Eastern Hemlock,Eastern
White Pine, Pin Oak, Pitch Pine, Rock Elm,Striped Maple, Sugar
Maple, Yellow Buckeye
Baton Rouge Scarlet Oak, YellowwoodGreensboro Northern White
CedarPhiladelphia Black SpruceRichmond Balsam FirWashington Balsam
Fir, Black Spruce, Red Pine
1 Based on 1961–1970 and 2001–2010 hardiness zone shift within
MSA bound-aries.
Table 4Projected species counts per MSA.
MSA # Species (200 km)1 # Species lost2 % Species lost2
Albuquerque 41 0 0.00Atlanta 74 27 −36.49Baton Rouge 59 11
−18.64Detroit 69 1 −1.45El Paso 27 1 −3.70Greensboro 70 11
−15.71Indianapolis 77 0 0.00Las Vegas 35 0 0.00Louisville 78 3
−3.85Minneapolis 51 0 0.00New York 78 3 −3.85Oklahoma City 50 0
0.00Philadelphia 77 5 −6.49Phoenix 46 0 0.00Portland 40 1
−2.50Richmond 74 3 −4.05St. Louis 72 0 0.00Syracuse 66 0 0.00Toledo
72 0 0.00Washington 83 20 −24.10Average 61.95 4.30 −6.041 Adapted
species list, 200 km buffer.
f
foafgtt
ptalaM
ocoGswLhbeM
Table 5MSA and corresponding projection of lost tree
species.
MSA Species lost1
Atlanta American Chestnut, American Mountain Ash, BlackLocust,
Blue Ash, Butternut, Chestnut Oak, ChinkapinOak, Common
Serviceberry, Cucumbertree Magnolia,Eastern Hemlock, Eastern
Redcedar, Eastern WhitePine, Hackberry, Northern Red Oak, Ohio
Buckeye, PinOak, Pitch Pine, Rock Elm, Scarlet Oak,
ShellbarkHickory, Shingle Oak, Silver Maple, Striped Maple,Sugar
Maple, Umbrella Magnolia, Yellow Buckeye,Yellowwood
Baton Rouge American Chestnut, Chinkapin Oak,
CommonServiceberry, Cucumbertree Magnolia, EasternRedcedar,
Northern Red Oak, Prairie Crabapple, ScarletOak, Shingle Oak,
Silver Maple, Yellowwood
Detroit White SpruceEl Paso Peachleaf WillowGreensboro American
Basswood, American Mountain Ash, Bigtooth
Aspen, Eastern Hemlock, Eastern White Pine, NorthernWhite Cedar,
Pin Oak, Pitch Pine, Striped Maple, SugarMaple, Swamp White Oak
Louisville Black Maple, Northern White Cedar, Rock ElmNew York
Balsam Fir, Black Spruce, Red PinePhiladelphia Balsam Poplar, Black
Maple, Black Spruce, Northern
White Cedar, Red SprucePortland American BasswoodRichmond Balsam
Fir, Northern White Cedar, Red SpruceWashington American Basswood,
American Mountain Ash, Balsam
Fir, Balsam Poplar, Bigtooth Aspen, Black Maple, BlackSpruce,
Eastern Hemlock, Eastern White Pine,Kentucky Coffeetree, Northern
White Cedar, Pin Oak,Pitch Pine, Red Pine, Red Spruce, Striped
Maple, SugarMaple, Swamp White Oak, Tamarack, Yellow Buckeye
east.
2 Projection assumes the 1960 to 2010 shift in hardiness zones
occurs again inuture.
If the historical shift in hardiness zones occurs again in
theuture, i.e., a doubling of the historical shift, 11 of the 20,
or 55%f the MSAs in our study would lose tree species (Table 4).
Overall,n average of 6.04% of tree species would be lost in
response to auture shift in hardiness zones equivalent to the
historical shift. Thereatest tree losses would again occur in
Atlanta (27) and Washing-on DC (20), as these MSAs would lose
36.49% and 24.10% of theirotal tree species, respectively.
Table 5 shows the tree species lost for the 11 MSAs that
arerojected to lose trees in our study over time. Of the 42
differentree species lost, approximately three-fourths would be
deciduousnd one-fourth would be coniferous. Sixteen tree species
would beost in two MSAs, twelve tree species would be lost in three
MSAs,nd one tree species, Northern White Cedar, would be lost in
fiveSAs.The National Climate Assessment (NCA), which is a
regularly
ccurring scientific assessment of changes in US climate,
studieslimate change at a regional level by subdividing the
contigu-us United States into six zones (Fig. 4): Northwest,
Southwest,reat Plains, Midwest, Northeast, and Southeast (EPA,
2013). In ourtudy, all 6 MSAs that lost species over the period of
1961–2010ere found in the NCA Southeast region, i.e., Washington,
Atlanta,
ouisville, Richmond, Baton Rouge, and Greensboro. Continuing
theistorical shift in hardiness zones again in the future, i.e., a
dou-
ling of the historical shift, would intensify the tree species
loss inach Southeast region, and add the Northwest (1), Great
Plains (1),idwest, (1), and Northeast (2) regions. The only NCA
region that
1 Projection assumes the 1960 to 2010 shift in hardiness zones
occurs again infuture.
would not lose any tree species in our study would be the
South-west.
4. Discussion
Although ongoing climate change has produced a
conspicuousnorthward shift in hardiness zones over the past 50
years, we findmost common tree species to remain spatially adapted
to their orig-inal MSA over time (Table 2). Both tree species and
MSAs spanseveral hardiness zones, and hardiness zones shift
northward atdifferent rates depending on spatial location. Only
MSAs located inthe NCA Southeast region lost tree species during
the 1961–2010period (Table 3), suggesting that climate change is
having a greaterimpact on the adaptability of tree species in this
region than oth-ers. From 1961 to 2010, the Southeast exhibited a
greater shiftin hardiness zones than other NCA regions (Fig. 1);
some treespecies in the Southeast may have already been pushing
their lim-its of temperature tolerance in 1961–1970, and the
hardiness zoneshift caused adaptation loss. According to the
National Oceanic andAtmospheric Administration (2013), average
temperatures in theSoutheastern US are projected to increase 4 to 8
◦F by the year 2100.Although this increase trails other US regions,
the inland portionsof the Southeast are expected to be 1 to 2 ◦F
warmer than coastalportions. The Southeast’s disproportionate
growth of metropolitanareas relative to other parts of the US, and
the consequent landuse and cover changes, are likely to exacerbate
the temperatureincreases expected in the region (National Climate
Assessment,2014). In light of these ongoing changes, urban heat
managementand corresponding tree selection should be priorities for
the South-
Converse to the Southeast region, the MSAs located in the
South-west region maintained all tree species from 1961 to 2010
(Table 2).Even in the future projection of hardiness zone change
(Table 4), the
-
K. Lanza, B. Stone Jr. / Landscape and Urban Planning 153 (2016)
74–82 79
nal C
SithfWibttfirga
oaBsBonpAawdobatm
wladpiofaeo
Fig. 4. 20 MSA study sites in Natio
outhwest will not lose tree species. To evaluate whether
speciesn the Southwest are adapted to thrive in more hardiness
zoneshan species in the Southeast, we compared the average number
ofardiness zones within 200 km of the MSA centroid for all
species
rom the adapted species list for the Atlanta and Phoenix MSAs.e
selected Atlanta for the Southeast MSA because Atlanta exhib-
ted the most tree species loss and Phoenix for the Southwest
MSAecause of complete tree species maintenance (Table 4).
Overall,he 74 species in Atlanta averaged 6.0 hardiness subzones,
whilehe 46 species in Phoenix averaged 7.6 hardiness subzones.
Thisnding suggests that species historically adapted to the
Phoenixegion may exhibit greater resilience as climate changes due
to areater geographic range than those found in the Atlanta region,
onverage.
In general, more extensive changes in tree species
distributionccur when the hardiness zone shift pattern between
1961–1970nd 2001–2010 per MSA is repeated into the future (Table
4).ecause our tree species list was based on commonly found
USpecies, the relatively high tree species loss exhibited in
Atlanta,aton Rouge, Greensboro, and Washington DC may be
expectedver time to alter the landscape in these MSAs to include
non-ative tree species. Moreover, with the rate of global climate
changerojected to increase over the 21st century (National
Climatessessment, 2014), further geographical shifts in tree
species are
cause for concern. Another important finding from our studyas
the breakdown of the types of tree species lost:
three-fourthseciduous and one-fourth coniferous. The
disproportionate lossf deciduous trees negatively impacts urban
heat managementecause these tree types are more capable of reducing
air temper-tures than conifers. Conifers have a lower albedo than
deciduousrees because of their rough leaf and canopy structure,
which traps
ore radiation near the surface (Oke, 1988).City trees are
particularly stressed by dual heating from global
arming and urban heat islands. In addition to heat stress,
treeoss over time is likely to result from climate change-induced
alter-tions in the frequency, intensity, duration, and timing of
fire,rought, hurricanes, windstorms, ice storms, landslides, insect
andathogen outbreaks, and introduced species (Dale et al., 2001).
For
nstance, the bark beetle, an insect known for threatening
billionsf conifers across millions of acres from Mexico to Alaska,
benefits
rom climate change: higher temperatures accelerate
reproductivend growth cycles while reducing beetle mortality in
winter (Bentzt al., 2010). Tree losses attributed to shifts in
hardiness zonesver time and other climate-induced factors may
intensify UHIs,
limate Assessment (NCA) regions.
as the cooling services of shading and evapotranspiration
providedby trees may be replaced by land covers that more readily
absorbheat and warm the surrounding environment.
Our work focused on climate change-related threats to the
urbanforest, not all potential threats to tree species. We aim to
mea-sure the adaptability of species currently tied to regional
hardinesszones as they shift, not what is on the ground today. For
this reason,our research design did not include species composition
and inter-species competition, even though both conditions
influence canopycover and are impacted by climate change
(Theurillat & Guisan,2001).
Our study of hardiness zones shifts and tree species
distri-bution carries important limitations. The Arbor Day
Foundationlist was non-exhaustive, and so we likely omit important
speciesfrom our analysis. The use of a uniform list of the most
commonnational tree species is likely to underestimate the actual
reductionin species adaptability over time, as common tree species
typicallyspan numerous hardiness zones. Many less common but
widelyplanted trees by MSA are not included in the species list for
ourstudy and may be at a greater risk for habitat stress with
climatechange than common tree species.
Another potential study limitation, variable rates of
climatechange over time prevent us from assessing future shifts
inhardiness zones associated with a specific time frame, such
as2011–2060. Our projected tree loss may serve as a
conservativeprojection, as recent global warming projections exceed
the 1.3 to1.9 ◦F increase in the US between 1895 and 2012. In one
globalwarming projection, immediate and rapid reductions in
emissionsof heat-trapping gas would increase global temperatures
2.5 ◦Fby the year 2100. Yet in another projection, a continuation
ofour current rate of emissions would increase global
temperaturesanywhere from 8 to 11 ◦F (National Climate Assessment,
2014).Adopting either of these temperature projections would
increasehardiness zone shifts and tree species loss beyond what is
found byour analysis.
Given our focus on which historically adapted tree species areno
longer adapted to hardiness zones presently found in large MSAsof
the US, we do not identify through this study which species maybe
newly adapted to MSAs with northward shifting zones. As
thelikelihood of species survival will depend not only on changing
tem-
perature regimes, but other ecological conditions, such as
suitablesoil types, the presence of parasites, and other limiting
factors, wedo not attempt to project how the actual species mix in
each MSAmay change over time.
-
8 and U
pnramgSiht2dbn
trtssifilpacna
5
idfit2aiittraiz
Ac
strobiformis)
0 K. Lanza, B. Stone Jr. / Landscape
An important limitation of using hardiness zones as the
solearameter influencing tree distribution is that a tree species
mayot fare equally in different hardiness zones of its hardiness
zonalange. Sugar Maple, which grows in hardiness zones 2b through
7bcross the nation, may grow poorly in the lower limit, upper
limit, oriddle of this hardiness zonal range. Sugar Maples in these
“poor
rowth” zones may have less growth and shorter life spans
thanugar Maples in optimal hardiness zones, and will be less
effectiven decreasing urban temperatures. Converse to tree
hardiness, treeeat tolerance looks at the other end of the
temperature spectrum:he amount of heat a tree can endure (Colorado
State University,012). Heat tolerance is an understudied factor
influencing treeistribution, and urban foresters and environmental
planners canenefit from the creation of “tolerance zones” analogous
to hardi-ess zones in tree planting decisions.
According to Stone et al. (2014), different combinations of
vege-ative and albedo enhancement strategies are effective in
differentegions. If albedo enhancement reduces temperatures more
effec-ively than increased tree plantings, the focus of the adapted
treepecies list can be on protecting native tree species, rather
than onpecies more suitable for urban heat management. This raises
anmportant question: Should non-native tree species be consideredor
urban heat management? Ecological research must address
themplications of an introduction of a nonnative species; plant
speciesike the Chinese Privet, brought into the US for ornamental
pur-oses, pose a serious threat to natural landscapes (USDA, 2014).
Yet,s the number of native species well adapted to changing
climaticonditions in US cities declines over time, urban arborists
mayeed to expand planting lists beyond historically adapted
specieslone.
. Conclusion
Our study serves as a basis for discussion and further
researchnto the effects of climate change on biotic control
measures toecrease additional heating in urban microclimates. As
recent worknds the frequency, duration, and intensity of heat wave
eventso be increasing in US cities over time (Habeeb, Vargo, &
Stone,015), greater collaboration amongst researchers,
policymakers,nd the general public is needed to offset the local
effects of ris-ng temperatures in densely populated urbanized
regions. Greennfrastructure strategies emphasizing tree planting to
moderateemperatures at the scale of individual neighborhoods
consti-ute a key strategy for urban heat management. For
metropolitanegions investing in green infrastructure for the
purpose of climatedaptation, selection of tree species likely to
thrive in a warm-ng environment must be informed by ongoing shifts
in hardinessones.
ppendix A. Arbor Day Foundation US tree species list byommon
name
Tree species (n = 199)Alaska Cedar (Chamaecyparis
nootkatensis)California Walnut (Juglanscalifornica)
Alligator Juniper (Juniperus deppeana) California-Laurel
(Umbellulariacalifornica)
American Basswood (Tilia americana) Canyon Live Oak
(Quercuschrysolepis)
American Beech (Fagus grandifolia) Catalina Cherry (Prunus
lyonii)American Chestnut (Castanea dentata) Chestnut Oak (Quercus
prinus)American Elm (Ulmus americana) Chihuahua Pine (Pinus
leiophylla)American Holly (Ilex opaca) Chinkapin Oak (Quercus
muehlenbergii)American Hornbeam (Carpinus
caroliniana)Chokecherry (Prunus virginiana)
American Mountain Ash (Sorbusamericana)
Cliffrose (Cowania mexicana)
rban Planning 153 (2016) 74–82
Appendix A (Continued )
American Plum (Prunus americana) Coastal Live Oak (Quercus
agrifolia)American Sycamore (Platanus
occidentalis)Colorado Blue Spruce (Piceapungens)
Apache Pine (Pinus engelmannii) Common Serviceberry(Amelanchier
arborea)
Arizona Alder (Alnus oblongifolia) Coulter Pine (Pinus
coulteri)Arizona Cypress (Cupressus arizonica) Cucumbertree
Magnolia (Magnolia
acuminata)Arizona Madrone (Arbutus arizonica) Desert Willow
(Chilopsis linearis)Arizona Sycamore (Platanus wrightii) Digger
Pine (Pinus sabiniana)Arizona Walnut (Juglans major) Douglasfir
(Pseudotsuga menziesii)Arizona White Oak (Quercus arizonica)
Eastern Cottonwood (Populus
deltoides)Atlantic White Cedar (Chamaecyparis
thyoides)Eastern Hemlock (Tsugacanadensis)
Baldcypress (Taxodium distichum) Eastern Hophornbeam
(Ostryavirginiana)
Balsam Fir (Abies balsamea) Eastern Redbud (Cercis
canadensis)Balsam Poplar (Populus balsamifera) Eastern Redcedar
(Juniperus
virginiana)Bigleaf Maple (Acer macrophyllum) Eastern White Pine
(Pinus strobus)Bigtooth Aspen (Populus grandidentata) Emory Oak
(Quercus emoryi)Bigtooth Maple (Acer grandidentatum) Engelmann Oak
(Quercus
engelmannii)Bishop Pine (Pinus muricata) Engelmann Spruce
(Picea
engelmannii)Bitternut Hickory (Carya cordiformis) Flowering
Dogwood (Cornus
florida)Black Cherry (Prunus serotina) Foxtail Pine (Pinus
balfouriana)Black Cottonwood (Populus trichocarpa) Fraser Fir
(Abies fraseri)Black Hawthorn (Crataegus douglasii) Fremont
Cottonwood (Populus
fremontii)Black Locust (Robinia pseudoacacia) Gambel Oak
(Quercus gambelii)Black Maple (Acer nigrum) Golden Chinkapin
(Castanopsis
chrysophylla)Black Oak (Quercus velutina) Grand Fir (Abies
grandis)Black Spruce (Picea mariana) Green Ash (Fraxinus
pennsylvanica)Black Tupelo (Nyssa sylvatica) Hackberry (Celtis
occidentalis)Black Walnut (Juglans nigra) Hollyleaf Cherry (Prunus
ilicifolia)Black Willow (Salix nigra) Honey Locust (Gleditsia
triacanthos)Blue Ash (Fraxinus quadrangulata) Incense-cedar
(Libocedrus
decurrens)Blue Oak (Quercus douglasii) Interior Live Oak
(Quercus
wislizenii)Blue Paloverde (Cercidium floridum) Jack Pine (Pinus
banksiana)Boxelder Maple (Acer negundo) Jeffrey Pine (Pinus
jeffreyi)Bristlecone Pine (Pinus aristata) Jerusalem-Thorn
(Parkinsonia
aculeata)Brown Dogwood (Cornus glabrata) Kentucky Coffeetree
(Gymnocladus
dioicus)Bur Oak (Quercus macrocarpa) Knobcone Pine (Pinus
attenuata)Butternut (Juglans cinerea) Live Oak (Quercus
virginiana)California Black Oak (Quercus kelloggii) Loblolly Pine
(Pinus taeda)California Buckeye (Aesculus
californica)Lodgepole Pine (Pinus contorta)
California Nutmeg (Torreya californica) Longleaf Pine (Pinus
palustris)California Sycamore (Platanus
racemosa)Mesquite (Prosopis juliflora)
Mexican Blue Oak (Quercusoblongifolia)
Shortleaf Pine (Pinus echinata)
Mexican Elder (Sambucus mexicana) Shrub Live Oak (Quercus
turbinella)Mockernut Hickory (Carya tomentosa) Silver Maple (Acer
saccharinum)Monterey Cypress (Cupressus
macrocarpa)Singleleaf Pinyon (Pinusmonophylla)
Monterey Pine (Pinus radiata) Sitka Spruce (Picea
sitchensis)Mountain Hemlock (Tsuga mertensiana) Slash Pine (Pinus
elliottii)Narrowleaf Cottonwood (Populus
angustifolia)Slippery Elm (Ulmus rubra)
Netleaf Hackberry (Celtis reticulata) Sourwood (Oxydendrum
arboreum)New Mexican Locust (Robinia
neomexicana)Southern Red Oak (Quercus falcata)
Noble Fir (Abies procera) Southwestern White Pine (Pinus
Northern Catalpa (Catalpa speciosa) Striped Maple (Acer
pensylvanicum)Northern Red Oak (Quercus rubra) Subalpine Fir (Abies
lasiocarpa)Northern White Cedar (Thuja
occidentalis)Sugar Maple (Acer saccharum)
-
and U
A
R
A
A
B
B
C
C
C
-
K. Lanza, B. Stone Jr. / Landscape
ppendix A (Continued )
Ohio Buckeye (Aesculus glabra) Sugar Pine (Pinus
lambertiana)One-seed Juniper (Juniperus
monosperma)Swamp White Oak (Quercusbicolor)
Oregon Ash (Fraxinus latifolia) Sweetgum
(Liquidambarstyraciflua)
Oregon White Oak (Quercus garryana) Tamarack (Larix
laricina)Osage-Orange (Maclura pomifera) Tanoak (Lithocarpus
densiflorus)Overcup Oak (Quercus lyrata) Thinleaf Alder (Alnus
tenuifolia)Pacific Dogwood (Cornus nutallii) Torrey Pine (Pinus
torreyana)Pacific Madrone (Arbutus menziesii) Umbrella Magnolia
(Magnolia
tripetala)Pacific Silver Fur (Abies amabilis) Utah Juniper
(Juniperus
osteosperma)Pacific Willow (Salix lasiandra) Valley Oak (Quercus
lobata)Pacific Yew (Taxus brevifolia) Velvet Ash (Fraxinus
velutina)Paper Birch (Betula papyrifera) Water Birch (Betula
occidentalis)Parry Pinyon (Pinus quadrifolia) Water Oak (Quercus
nigra)Pawpaw (Asimina triloba) Western Hemlock (Tsuga
heterophylla)Peachleaf Willow (Salix amygdaloides) Western Larch
(Larix occidentalis)Pecan (Carya illinoensis) Western Red cedar
(Thuja plicata)Persimmon (Diospyros virginiana) Western Redbud
(Cercis
occidentalis)Pignut Hickory (Carya glabra) Western White Pine
(Pinus
monticola)Pin Oak (Quercus palustris) White Alder (Alnus
rhombifolia)Pinyon (Pinus edulis) White Ash (Fraxinus
americana)Pitch Pine (Pinus rigida) White Fir (Abies
concolor)Ponderosa Pine (Pinus ponderosa) White Oak (Quercus
alba)Port Orford-cedar (Chamaecyparis
lawsoniana)White Spruce (Picea glauca)
Post Oak (Quercus stellata) Whitebark Pine (Pinus
albicaulis)Prairie Crabapple (Malus ioensis) Willow Oak (Quercus
phellos)Quaking Aspen (Populus tremuloides) Yellow Buckeye
(Aesculus octandra)Red Alder (Alnus rubra) Yellow Paloverde
(Cercidium
microphyllum)Red Fir (Abies magnifica) Yellow-poplar
(Liriodendron
tulipifera)Red Maple (Acer rubrum) Yellowwood (Cladrastis
kentuckea)Red Mulberry (Morus rubra)Red Pine (Pinus resinosa)Red
Spruce (Picea rubens)Red Willow (Salix laevigata)Redwood (Sequoia
sempervirens)River Birch (Betula nigra)Rock Elm (Ulmus
thomasii)Rocky Mountain Juniper (Juniperus
scopulorum)Rocky Mountain Maple (Acer glabrum)Saguaro (Cereus
giganteus)Sassafras (Sassafras albidum)Scarlet Oak (Quercus
coccinea)Scouler Willow (Salix scoulerana)Shagbark Hickory (Carya
ovata)Shellbark Hickory (Carya laciniosa)Shingle Oak (Quercus
imbricaria)
eferences
kbari, H., Pomerantz, M., & Taha, H. (2001). Cool surfaces
and shade trees to reduceenergy use and improve air quality in
urban areas. Solar Energy, 70,
295–310.http://dx.doi.org/10.1016/S0038-092X(00)00089-X
rbor Day Foundation. (n.d.). What tree is that? online.
Retrieved January 20, 2014from
〈http://www.arborday.org/trees/whattree/fullonline.cfm〉.
entz, B. J., Regniere, J., Fettig, C. J., Hansen, E. M., Hayes,
J. L., Hicke, J. A., et al. (2010).Climate change and bark beetles
of the western United States and Canada: Directand indirect
effects. BioScience, 60(8), 602–603.
http://dx.doi.org/10.1525/bio.2010.60.8.6
olund, P., & Hunhammar, S. (1999). Ecosystem services in
urban areas. EcologicalEconomics, 29(2), 293–301.
hen, I. C., Hill, J. K., Ohlemuller, R., Roy, D. B., &
Thomas, C. D. (2011). Rapidrange shifts of species associated with
high levels of climate warming. Science,333(6045), 1024–1026.
http://dx.doi.org/10.1126/science.1206432
ohen, J. E. (2003). Human population: The next half century.
Science, 302,1172–1175.
http://dx.doi.org/10.1126/science.1088665
olorado State University. (2012). Herbaceous plants, right
plant, rightplace. Retrieved February 15 2014 from
〈http://www.ext.colostate.edu/mg/gardennotes/512.html#heat〉.
rban Planning 153 (2016) 74–82 81
Dale, V. H., Joyce, L. A., McNulty, S., Neilson, R. P., Ayres,
M. P., Flannigan, M. D.,et al. (2001). Climate change and forest
disturbances. Bioscience, 51(9),
723–734.〈http://dx.doi.org/10.1641/0006-3568(2001)051[0723:CCAFD]2.0.CO;2〉.
Daly, C., Widrlechner, M. P., Halbleib, M. D., Smith, J. I.,
& Gibson, W. P. (2012). Devel-opment of a new USDA plant
hardiness zone map for the United States. Journalof Applied
Meteorology and Climatology, 51, 242–264.
http://dx.doi.org/10.1175/2010JAMC2536.1
EPA. (2015). Using trees and vegetation to reduce heat islands.
Retrieved October27 2015 from
〈http://www2.epa.gov/heat-islands/using-trees-and-vegetation-reduce-heat-islands〉.
EPA. (2013). ICLUS data for the national climate assessment.
Retrieved June 19 2014from
〈http://www.epa.gov/global-adaptation/iclus/nca regions.html〉.
Graham, R. W., & Grimm, E. C. (1990). Effects of global
climate change on the pat-terns of terrestrial biological
communities. Trends in Ecology & Evolution, 5(9),289–292.
http://dx.doi.org/10.1016/0169-5347(90)90083-P
Groffman, P. M., Kareiva, P., Carter, S., Grimm, N. B., Lawler,
J., Mack, M., et al. (2014).Ch. 8: Ecosystems, biodiversity, and
ecosystem services. In J. M. Melillo, T. C.Richmond Terese, &
G. W. Yohe (Eds.), Climate change impacts in the United States:The
third national climate assessment (pp. 195–219).
http://dx.doi.org/10.7930/J0TD9V7H
Habeeb, D., Vargo, J., & Stone, B. (2015). Rising heat wave
trends in large US cities. Nat-ural Hazards, 76(3), 1651–1665.
http://dx.doi.org/10.1007/s11069-014-1563-z
Hamann, A., & Wang, T. (2006). Potential effects of climate
change on ecosystemand tree species distribution in British
Columbia. Ecology, 87(11),
2773–2786.http://dx.doi.org/10.1890/0012-9658(2006)87[2773:PEOCCO]2.0.CO;2
Hijmans, R. J., & Graham, C. H. (2006). The ability of
climate envelope models to pre-dict the effect of climate change on
species distributions. Global Change Biology,12(12), 2272–2281.
http://dx.doi.org/10.1111/j.1365-2486.2006.01256.x
Iverson, L. R., Presad, A. R., Matthews, S. N., & Peters, M.
(2008). Estimating potentialhabitat for 134 eastern US tree species
under six climate scenarios. Forest Ecologyand Management, 254(3),
390–406. http://dx.doi.org/10.1016/j.foreco.2007.07.023
Kelly, A. E., & Goulden, M. L. (2008). Rapid shifts in plant
distribution with recent cli-mate change. Proceedings of the
National Academy of Sciences of the United Statesof America,
105(33), 11823–11826. http://dx.doi.org/10.1073/pnas.0802891105
Kirilenko, A. P., & Sedjo, R. A. (2007). Climate change
impacts on forestry. Proceedingsof the National Academy of Sciences
of the United States of America, 104(50),19697–19702.
http://dx.doi.org/10.1073/pnas.0701424104
McKenney, D., Pedlar, J., Lawrence, K., Campbell, K., &
Hutchinson, M. (2007). Beyondtraditional hardiness zones: Using
climate envelopes to map plant range limits.BioScience, 57,
929–937. http://dx.doi.org/10.1641/B571105
Meyer, J. M., Sale, M. J., Mulholland, P. J., & Poff, N. L.
(1999). Impacts of climate changeon aquatic ecosystem functioning
and health. Journal of the American WaterResources Association,
35(6), 1373–1386.
http://dx.doi.org/10.1111/j.1752-1688.1999.tb04222.x
Murray, M. B., Cannell, M. G. R., & Smith, R. I. (1989).
Date of budburst of fifteentree species in Britain following
climatic warming. Journal of Applied Ecology, 26,693–700.
National Climate Assessment. (2014). Ch. 2: Our changing
climate. In J. M. Melillo,T. C. Richmond Terese, & G. W. Yohe
(Eds.), Climate change impacts in the UnitedStates: The third
national climate assessment (pp. 19–67). U.S. Global ChangeResearch
Program. http://dx.doi.org/10.7930/J0KW5CXT
National Climatic Data Center. (2013). Climate data online.
Retrieved November 22,2013 from
〈http://www.ncdc.noaa.gov/cdo-web/〉.
New York City Regional Heat Island Initiative. (2006).
Mitigating New YorkCity’s heat island with urban forestry, living
roofs, and light surfaces(Final report 06-06). Retrieved from
〈https://www.nyserda.ny.gov/-/media/Files/Publications/Research/Environmental/EMEP/NYC-Heat-Island-Mitigation.pdf〉.
NOAA. (2013). Regional climate trends and scenarios for the U.S.
national cli-mate assessment (NOAA technical report NESDIS 142-2).
Retrieved from〈http://www.nesdis.noaa.gov/technical reports/NOAA
NESDIS Tech Report 1422-Climate of the Southeast U.S.pdf〉.
Nowak, D. J., & Dwyer, J. F. (2007). Urban and community
forestry in the Northeast(2nd ed.). New York, NY: Springer.
Oke, T. R. (1988). Boundary layer climates. London and New York:
Methuen & Co.,Ltd. and Methuen, Inc.
Parmesan, C., & Yohe, G. (2003). A globally coherent
fingerprint of climate changeimpacts across natural systems.
Nature, 421, 37–42. http://dx.doi.org/10.1038/nature01286
Pearson, R. G., & Dawson, T. P. (2003). Predicting the
impacts of climate change onthe distribution of species: Are
bioclimate envelope models useful? Global Ecol-ogy and
Biogeography, 12(5), 361–371.
http://dx.doi.org/10.1046/j.1466-822X.2003.00042.x
Roman, L. A., & Scatena, F. N. (2011). Street tree survival
rates: Meta-analysis of previous studies and application to a field
survey inPhiladelphia, PA, USA. Urban Forestry & Urban
Greening, 10,
269–274,http://dx.doi.org/10.1016/j.ufug.2011.05.008.
Root, T. L., Price, J. T., Hall, K. R., Schneider, S. H.,
Rosenzweig, C., & Pounds, J. A. (2003).Fingerprints of global
warming on wild animals and plants. Nature, 421,
57–60.http://dx.doi.org/10.1038/nature01333
Rosenfeld, A. H., Akbari, H., Romm, J. J., & Pomerantz, M.
(1998). Cool communities:Strategies for heat island mitigation and
smog reduction. Energy and Buildings,28(1), 51–62,
http://dx.doi.org/10.1016/S0378-7788(97)00063-7.
Roy, S., Byrne, J., & Pickering, C. (2012). A systematic
quantitative reviewof urban tree benefits, costs, and assessment
methods across cities in
dx.doi.org/10.1016/S0038-092X(00)00089-Xdx.doi.org/10.1016/S0038-092X(00)00089-Xdx.doi.org/10.1016/S0038-092X(00)00089-Xdx.doi.org/10.1016/S0038-092X(00)00089-Xdx.doi.org/10.1016/S0038-092X(00)00089-Xdx.doi.org/10.1016/S0038-092X(00)00089-Xdx.doi.org/10.1016/S0038-092X(00)00089-Xdx.doi.org/10.1016/S0038-092X(00)00089-Xdx.doi.org/10.1016/S0038-092X(00)00089-Xdx.doi.org/10.1525/bio.2010.60.8.6dx.doi.org/10.1525/bio.2010.60.8.6dx.doi.org/10.1525/bio.2010.60.8.6dx.doi.org/10.1525/bio.2010.60.8.6dx.doi.org/10.1525/bio.2010.60.8.6dx.doi.org/10.1525/bio.2010.60.8.6dx.doi.org/10.1525/bio.2010.60.8.6dx.doi.org/10.1525/bio.2010.60.8.6dx.doi.org/10.1525/bio.2010.60.8.6dx.doi.org/10.1525/bio.2010.60.8.6dx.doi.org/10.1525/bio.2010.60.8.6http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0020http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0020http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0020http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0020http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0020http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0020http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0020http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0020http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0020http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0020http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0020http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0020http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0020dx.doi.org/10.1126/science.1206432dx.doi.org/10.1126/science.1206432dx.doi.org/10.1126/science.1206432dx.doi.org/10.1126/science.1206432dx.doi.org/10.1126/science.1206432dx.doi.org/10.1126/science.1206432dx.doi.org/10.1126/science.1206432dx.doi.org/10.1126/science.1206432dx.doi.org/10.1126/science.1088665dx.doi.org/10.1126/science.1088665dx.doi.org/10.1126/science.1088665dx.doi.org/10.1126/science.1088665dx.doi.org/10.1126/science.1088665dx.doi.org/10.1126/science.1088665dx.doi.org/10.1126/science.1088665dx.doi.org/10.1126/science.1088665http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0035http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0035http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0035http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0035http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0035http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0035http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0035http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0035http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0035http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0035http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0035http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0035http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0035http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0035http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0035http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0035http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0035http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0040http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0040http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0040http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0040http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0040http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0040http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0040http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0040http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0040http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0040http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0040http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0040http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0040http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0040http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0040http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0040dx.doi.org/10.1175/2010JAMC2536.1dx.doi.org/10.1175/2010JAMC2536.1dx.doi.org/10.1175/2010JAMC2536.1dx.doi.org/10.1175/2010JAMC2536.1dx.doi.org/10.1175/2010JAMC2536.1dx.doi.org/10.1175/2010JAMC2536.1dx.doi.org/10.1175/2010JAMC2536.1dx.doi.org/10.1175/2010JAMC2536.1http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0050http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0050http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0050http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0050http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0050http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0050http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0050http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0050http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0050http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0050http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0050http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0050http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0050http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0050http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0050http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0050http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0050http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0050http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0050http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0055http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0055http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0055http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0055http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0055http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0055http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0055http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0055http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0055http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0055http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0055http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0055http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0055http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0055http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0055http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0055http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0055http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0055dx.doi.org/10.1016/0169-5347(90)90083-Pdx.doi.org/10.1016/0169-5347(90)90083-Pdx.doi.org/10.1016/0169-5347(90)90083-Pdx.doi.org/10.1016/0169-5347(90)90083-Pdx.doi.org/10.1016/0169-5347(90)90083-Pdx.doi.org/10.1016/0169-5347(90)90083-Pdx.doi.org/10.1016/0169-5347(90)90083-Pdx.doi.org/10.1016/0169-5347(90)90083-Pdx.doi.org/10.1016/0169-5347(90)90083-Pdx.doi.org/10.7930/J0TD9V7Hdx.doi.org/10.7930/J0TD9V7Hdx.doi.org/10.7930/J0TD9V7Hdx.doi.org/10.7930/J0TD9V7Hdx.doi.org/10.7930/J0TD9V7Hdx.doi.org/10.7930/J0TD9V7Hdx.doi.org/10.7930/J0TD9V7Hdx.doi.org/10.1007/s11069-014-1563-zdx.doi.org/10.1007/s11069-014-1563-zdx.doi.org/10.1007/s11069-014-1563-zdx.doi.org/10.1007/s11069-014-1563-zdx.doi.org/10.1007/s11069-014-1563-zdx.doi.org/10.1007/s11069-014-1563-zdx.doi.org/10.1007/s11069-014-1563-zdx.doi.org/10.1007/s11069-014-1563-zdx.doi.org/10.1007/s11069-014-1563-zdx.doi.org/10.1007/s11069-014-1563-zdx.doi.org/10.1890/0012-9658(2006)87[2773:PEOCCO]2.0.CO;2dx.doi.org/10.1890/0012-9658(2006)87[2773:PEOCCO]2.0.CO;2dx.doi.org/10.1890/0012-9658(2006)87[2773:PEOCCO]2.0.CO;2dx.doi.org/10.1890/0012-9658(2006)87[2773:PEOCCO]2.0.CO;2dx.doi.org/10.1890/0012-9658(2006)87[2773:PEOCCO]2.0.CO;2dx.doi.org/10.1890/0012-9658(2006)87[2773:PEOCCO]2.0.CO;2dx.doi.org/10.1890/0012-9658(2006)87[2773:PEOCCO]2.0.CO;2dx.doi.org/10.1890/0012-9658(2006)87[2773:PEOCCO]2.0.CO;2dx.doi.org/10.1890/0012-9658(2006)87[2773:PEOCCO]2.0.CO;2dx.doi.org/10.1890/0012-9658(2006)87[2773:PEOCCO]2.0.CO;2dx.doi.org/10.1111/j.1365-2486.2006.01256.xdx.doi.org/10.1111/j.1365-2486.2006.01256.xdx.doi.org/10.1111/j.1365-2486.2006.01256.xdx.doi.org/10.1111/j.1365-2486.2006.01256.xdx.doi.org/10.1111/j.1365-2486.2006.01256.xdx.doi.org/10.1111/j.1365-2486.2006.01256.xdx.doi.org/10.1111/j.1365-2486.2006.01256.xdx.doi.org/10.1111/j.1365-2486.2006.01256.xdx.doi.org/10.1111/j.1365-2486.2006.01256.xdx.doi.org/10.1111/j.1365-2486.2006.01256.xdx.doi.org/10.1111/j.1365-2486.2006.01256.xdx.doi.org/10.1111/j.1365-2486.2006.01256.xdx.doi.org/10.1016/j.foreco.2007.07.023dx.doi.org/10.1016/j.foreco.2007.07.023dx.doi.org/10.1016/j.foreco.2007.07.023dx.doi.org/10.1016/j.foreco.2007.07.023dx.doi.org/10.1016/j.foreco.2007.07.023dx.doi.org/10.1016/j.foreco.2007.07.023dx.doi.org/10.1016/j.foreco.2007.07.023dx.doi.org/10.1016/j.foreco.2007.07.023dx.doi.org/10.1016/j.foreco.2007.07.023dx.doi.org/10.1016/j.foreco.2007.07.023dx.doi.org/10.1016/j.foreco.2007.07.023dx.doi.org/10.1073/pnas.0802891105dx.doi.org/10.1073/pnas.0802891105dx.doi.org/10.1073/pnas.0802891105dx.doi.org/10.1073/pnas.0802891105dx.doi.org/10.1073/pnas.0802891105dx.doi.org/10.1073/pnas.0802891105dx.doi.org/10.1073/pnas.0802891105dx.doi.org/10.1073/pnas.0802891105dx.doi.org/10.1073/pnas.0701424104dx.doi.org/10.1073/pnas.0701424104dx.doi.org/10.1073/pnas.0701424104dx.doi.org/10.1073/pnas.0701424104dx.doi.org/10.1073/pnas.0701424104dx.doi.org/10.1073/pnas.0701424104dx.doi.org/10.1073/pnas.0701424104dx.doi.org/10.1073/pnas.0701424104dx.doi.org/10.1641/B571105dx.doi.org/10.1641/B571105dx.doi.org/10.1641/B571105dx.doi.org/10.1641/B571105dx.doi.org/10.1641/B571105dx.doi.org/10.1641/B571105dx.doi.org/10.1641/B571105dx.doi.org/10.1111/j.1752-1688.1999.tb04222.xdx.doi.org/10.1111/j.1752-1688.1999.tb04222.xdx.doi.org/10.1111/j.1752-1688.1999.tb04222.xdx.doi.org/10.1111/j.1752-1688.1999.tb04222.xdx.doi.org/10.1111/j.1752-1688.1999.tb04222.xdx.doi.org/10.1111/j.1752-1688.1999.tb04222.xdx.doi.org/10.1111/j.1752-1688.1999.tb04222.xdx.doi.org/10.1111/j.1752-1688.1999.tb04222.xdx.doi.org/10.1111/j.1752-1688.1999.tb04222.xdx.doi.org/10.1111/j.1752-1688.1999.tb04222.xdx.doi.org/10.1111/j.1752-1688.1999.tb04222.xdx.doi.org/10.1111/j.1752-1688.1999.tb04222.xhttp://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0110http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0110http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0110http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0110http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0110http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0110http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0110http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0110http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0110http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0110http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0110http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0110http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0110http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0110http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0110http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0110http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0110http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0110http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0110http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0110http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0110http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0110dx.doi.org/10.7930/J0KW5CXTdx.doi.org/10.7930/J0KW5CXTdx.doi.org/10.7930/J0KW5CXTdx.doi.org/10.7930/J0KW5CXTdx.doi.org/10.7930/J0KW5CXTdx.doi.org/10.7930/J0KW5CXTdx.doi.org/10.7930/J0KW5CXThttp://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0120http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0120http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0120http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0120http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0120http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0120http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0120http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0120http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0120http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0120http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0120http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0120http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0120http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0125http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0125http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0125http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0125http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0125http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0125http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0125http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0125http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0125http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0125http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0125http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0125http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0125http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0125http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0125http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0125http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0125http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0125http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0125http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0125http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0125http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0125http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0125http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0125http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0125http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0125http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0130http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0130http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0130http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0130http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0130http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0130http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0130http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0130http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0130http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0130http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0130http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0130http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0130http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0130http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0130http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0130http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0130http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0130http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0130http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0130http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0130http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0130http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0130http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0130http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0130http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0130http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0130http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0130http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0130http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0130http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0130http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0130http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0130http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0130http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0135http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0135http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0135http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0135http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0135http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0135http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0135http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0135http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0135http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0135http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0135http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0135http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0135http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0140http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0140http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0140http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0140http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0140http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0140http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0140http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0140http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0140http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0140http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0140http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0140http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0140http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0140http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0140dx.doi.org/10.1038/nature01286dx.doi.org/10.1038/nature01286dx.doi.org/10.1038/nature01286dx.doi.org/10.1038/nature01286dx.doi.org/10.1038/nature01286dx.doi.org/10.1038/nature01286dx.doi.org/10.1038/nature01286dx.doi.org/10.1046/j.1466-822X.
2003.00042.xdx.doi.org/10.1046/j.1466-822X.
2003.00042.xdx.doi.org/10.1046/j.1466-822X.
2003.00042.xdx.doi.org/10.1046/j.1466-822X.
2003.00042.xdx.doi.org/10.1046/j.1466-822X.
2003.00042.xdx.doi.org/10.1046/j.1466-822X.
2003.00042.xdx.doi.org/10.1046/j.1466-822X.
2003.00042.xdx.doi.org/10.1046/j.1466-822X.
2003.00042.xdx.doi.org/10.1046/j.1466-822X.
2003.00042.xdx.doi.org/10.1046/j.1466-822X.
2003.00042.xdx.doi.org/10.1046/j.1466-822X.
2003.00042.xdx.doi.org/10.1046/j.1466-822X.
2003.00042.xhttp://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0155http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0155http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0155http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0155http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0155http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0155http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0155http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0155http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0155http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0155http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0155http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0155http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0155http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0155http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0155http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0155http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0155http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0155http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0155http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0155http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0155http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0155http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0155http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0155http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0155http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0155http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0155http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0155http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0155http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0155http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0155dx.doi.org/10.1038/nature01333dx.doi.org/10.1038/nature01333dx.doi.org/10.1038/nature01333dx.doi.org/10.1038/nature01333dx.doi.org/10.1038/nature01333dx.doi.org/10.1038/nature01333dx.doi.org/10.1038/nature01333http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0165http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0165http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0165http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0165http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0165http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0165http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0165http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0165http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0165http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0165http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0165http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0165http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0165http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0165http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0165http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0165http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0165http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0165http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0165http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0165http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0170http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0170http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0170http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0170http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0170http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0170http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0170http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0170http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0170http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0170http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0170http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0170http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0170http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0170http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0170
-
8 and U
S
S
S
S
S
S
Walther, G., Post, E., Convey, P., Menzel, A., Parmesan, C.,
Beebee, T. J. C., et al. (2002).
2 K. Lanza, B. Stone Jr. / Landscape
different climatic zones. Urban Forestry & Urban Greening,
11, 351–363,http://dx.doi.org/10.1016/j.ufug.2012.06.006.
akai, A., & Wardle, P. (1978). Freezing resistance of New
Zealand trees and shrubs.New Zealand Journal of Ecology, 1,
51–61.
akai, A., & Weiser, C. J. (1973). Freezing resistance of
trees in North America withreference to tree regions. Ecology,
54(1), 118–126.
taley, D. C. (2013). Urban forests and solar power generation:
Partners in urbanheat island mitigation. International Journal of
Low-Carbon Technologies, 0, 1–9.
tone, B. (2007). Urban and rural temperature trends in proximity
to large US cities:1951–2000. International Journal of Climatology,
27, 1801–1807. http://dx.doi.org/10.1002/joc.1555
tone, B., Vargo, J., & Habeeb, D. (2012). Managing climate
change in cities: Will
climate action plans work? Landscape and Urban Planning, 107,
263–271. http://dx.doi.org/10.1016/j.landurbplan.2012.05.014
tone, B., Vargo, J., Liu, P., Habeeb, D., DeLucia, A., Trail,
M., et al. (2014). Avoidedheat-related mortality through climate
adaptation strategies in three US cities.PLoS ONE, 9(6), 1–8.
http://dx.doi.org/10.1371/journal.pone.0100852
rban Planning 153 (2016) 74–82
Theurillat, J. P., & Guisan, A. (2001). Potential impact of
climate change on vegetationin the European Alps: A review.
Climatic Change, 50(1), 77–109. http://dx.doi.org/10.1023/A:
1010632015572
USDA. (2014). Plant guide: Chinese privet. Retrieved September
29 2014 from〈http://plants.usda.gov/plantguide/pdf/pg
lisi.pdf〉.
USDA Agricultural Research Service. (2014). USDA plant hardiness
zone map.Retrieved October 12 2013 from
〈http://planthardiness.ars.usda.gov/PHZMWeb/〉.
USGS. (2013). Digital representations of tree species range maps
from ‘atlas of UnitedStates trees’ by Elbert L. Little, Jr. (and
other publications). Retrieved October 202013 from
〈http://esp.cr.usgs.gov/data/little/〉.
Ecological responses to recent climate change. Nature, 416,
389–395. http://dx.doi.org/10.1038/416389a
Woodward, F. I., & Williams, B. G. (1987). Climate and plant
distributions at globaland local scales. Vegetatio, 69, 189–197.
http://dx.doi.org/10.1007/BF00038700
http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0170http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0170http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0170http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0170http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0170http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0170http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0170http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0170http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0170http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0170http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0170http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0170http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0170http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0170http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0170http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0175http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0175http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0175http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0175http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0175http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0175http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0175http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0175http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0175http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0175http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0175http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0175http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0175http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0175http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0175http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0175http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0175http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0175http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0175http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0180http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0180http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0180http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0180http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0180http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0180http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0180http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0180http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0180http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0180http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0180http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0180http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0180http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0180http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0180http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0180http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0180http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0180http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0180http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0185http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0185http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0185http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0185http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0185http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0185http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0185http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0185http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0185http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0185http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0185http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0185http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0185http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0185http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0185http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0185http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0185http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0185http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0185http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0185http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0185http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0185http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0185dx.doi.org/10.1002/joc.1555dx.doi.org/10.1002/joc.1555dx.doi.org/10.1002/joc.1555dx.doi.org/10.1002/joc.1555dx.doi.org/10.1002/joc.1555dx.doi.org/10.1002/joc.1555dx.doi.org/10.1002/joc.1555dx.doi.org/10.1002/joc.1555dx.doi.org/10.1016/j.landurbplan.2012.05.014dx.doi.org/10.1016/j.landurbplan.2012.05.014dx.doi.org/10.1016/j.landurbplan.2012.05.014dx.doi.org/10.1016/j.landurbplan.2012.05.014dx.doi.org/10.1016/j.landurbplan.2012.05.014dx.doi.org/10.1016/j.landurbplan.2012.05.014dx.doi.org/10.1016/j.landurbplan.2012.05.014dx.doi.org/10.1016/j.landurbplan.2012.05.014dx.doi.org/10.1016/j.landurbplan.2012.05.014dx.doi.org/10.1016/j.landurbplan.2012.05.014dx.doi.org/10.1016/j.landurbplan.2012.05.014dx.doi.org/10.1371/journal.pone.0100852dx.doi.org/10.1371/journal.pone.0100852dx.doi.org/10.1371/journal.pone.0100852dx.doi.org/10.1371/journal.pone.0100852dx.doi.org/10.1371/journal.pone.0100852dx.doi.org/10.1371/journal.pone.0100852dx.doi.org/10.1371/journal.pone.0100852dx.doi.org/10.1371/journal.pone.0100852dx.doi.org/10.1371/journal.pone.0100852dx.doi.org/10.1023/A:
1010632015572dx.doi.org/10.1023/A:
1010632015572dx.doi.org/10.1023/A:
1010632015572dx.doi.org/10.1023/A:
1010632015572dx.doi.org/10.1023/A:
1010632015572dx.doi.org/10.1023/A:
1010632015572dx.doi.org/10.1023/A:
1010632015572http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0210http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0210http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0210http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0210http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0210http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0210http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0210http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0210http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0210http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0210http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0210http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0210http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0210http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0210http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0210http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0215http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0215http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0215http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0215http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0215http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0215http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0215http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0215http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0215http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0215http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0215http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0215http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0215http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0215http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0215http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0215http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0220http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0220http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0220http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0220http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0220http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0220http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0220http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0220http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0220http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0220http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0220http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0220http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0220http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0220http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0220http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0220http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0220http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0220http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0220http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0220http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0220http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0220http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0220http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0220http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0220http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0220http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0220http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0220http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0220http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0220http://refhub.elsevier.com/S0169-2046(15)00244-3/sbref0220dx.doi.org/10.1038/416389adx.doi.org/10.1038/416389adx.doi.org/10.1038/416389adx.doi.org/10.1038/416389adx.doi.org/10.1038/416389adx.doi.org/10.1038/416389adx.doi.org/10.1038/416389adx.doi.org/10.1007/BF00038700dx.doi.org/10.1007/BF00038700dx.doi.org/10.1007/BF00038700dx.doi.org/10.1007/BF00038700dx.doi.org/10.1007/BF00038700dx.doi.org/10.1007/BF00038700dx.doi.org/10.1007/BF00038700
Climate adaptation in cities: What trees are suitable for urban
heat management?1 Introduction2 Methods3 Results4 Discussion5
ConclusionAppendix A Arbor Day Foundation US tree species list by
common nameReferences