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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: lanza.kevin@gatech.edu (K. Lanza), stone@gatech.edu

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:lanza.kevin@gatech.edumailto:stone@gatech.edudx.doi.org/10.1016/j.landurbplan.2015.12.002

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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

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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.

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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.

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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

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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.

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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