United States 

Department of 

Agriculture Classification 

Forest t3ewice American Metropolitan Areas 

NotZheastern Forest 

Experiment Station by Ecoregion and Potential 

Research 

Paper NE-516 

Natural Vegetation 

Ralph A. Sanders 

Rowan A. Rowntree 
Contents 

The Authors 

Ralph A. Sanders is a research 

geographer (IPA) for urban land use 

systems at the Northeastern Forest 

Experiment Stat ion research project 

located at the State University of 

New York's College of Environmental Science and Forestry, 

Syracuse, New York. He received 

M.A. and Ph.D. degrees in urban 

geography from The Pennsylvania 

State University and the University 

of Minnesota, respectively. 

Rowan A. Rowntree is research 

geographer and Project Leader in urban forest ecology at the Syracuse 

project. He received an M.S. in forest ecology and a Ph.D. in physical 

geography from the University of 

California, Berkeley. 

Manuscript received for 

publication 25 November 1981 

Abstract 

This publication classifies 279 

American metropolitan areas by 

ecoregion and potential natural 

vegetation. The classification forms 

a baseline of expected vegetation 

structure and composition that can 

assist scientists and policy makers 

in making urban forestry generalizations about classes of cities. 

Introduction ................ 1 

Method of Classification. ..... 2 

Results.. .................. .3 

Appendix 1.. ............... .5 

Code Numbers ........... .5 

Appendix il ................ .5 

Alphabetical List of SMSA's 

by ED and PNV.. ......... .5 

Appendix 111. ............... .8 

SMSA Classification by ED .8 

Appendix IV. .............. .12 

SMSA Classification by Zones 

of PNV ................. .12 

Literature Cited. ............ 15 
Introduction 

Urban forestry researchers and 

planners ask: How similar or different are the urban forests of 

American cities? Specifically, for 

example, to what degree does the 

vegetation pattern of Richmond, Virginia resemble that of Wheeling, 

West Virginia, or Peoria, Illinois? 

How dissimilar are Phoenix and 

Spokane? If we were to compfete an 

intensive vegetation survey of 

Omaha, could we extrapolate results 

to a class of similar cities? 

Every city is a unique entity 

that shares some of its characteristics with others, and is able to 

be examined for its unique properties or for its general character. The 

similarity of cities has led to the 

idea of developing classification^.^ 

Many early attempts at classification focused in the functional or 

economic character of cities and 

gave rise to single-level groups such 

as industrial cities,'retailing cities, 

government cities, transportation 

cities, and so on. Later classification attempts were based on the 

morphology of the built environment 

(especially spatial arrangements), 

population growth histories, and 

positions with a hierarchy of city 

sizes. Recently an attempt was 

made to reflect the character of the 

population in urban typologies, and 

one classification for a limited set 

of American cities reflecting the 

physical environment was written2 

Similarly, a taxonomy of cities 

based on the composition and 

The most complete summary of urban classification systems is in Berry 

and Horton (1970), Chapter 5 (p. 106-149) 

and Chapter 6 (p. 150-168). 

* Berry and coworkers (1974) applied 

Q-mode factor analysis to a matrix containing measures of air, water, solid 

waste, pesticide, radiation, and noise 

pollution for 76 metropolitan areas to develop a taxonomy that describes how 

city characteristics and pollution covary 

for these cities. 

distribution of urban vegetation is 

desired. The classificqtion would 

suggest: what the normal, average, 

or usual conditions are, how great 

the contrasts within and between 

cities are, and what regional or 

other patterns of similarity and dissimilarity exist. This information implies what may be true in one city 

from what is known by observation 

in another. It also would suggest 

how widespread one class of 

vegetation problems is and inform 

local policy makers which cities 

might have useful information. In 

general, this classification for urban 

forestry provides a basis for reliable 

inferences where knowledge is limited or unavailable, and lays a 

foundation for establishing scientific generalities and public policy 

guidelines with an economy of effort. 

Generally, the composition and 

distribution of urban vegetation are 

determined by three broad categories of influence: the natural 

environment; the growing space 

available; and the human influences 

on selection, planting, removal, and 

maintenance. Cities may be classified by the pattern of aboveground 

growing space made available by 

the physical morphology of artificial 

surfaces. Also, cities may be classified by the aggregate impact of 

human choices and actions. We selected the simplest factor: natural 

environment, which is a logical 

point of departure for generalizing 

about urban vegetation in different 

parts of the United States, because 

of recent work in mapping ecological regions. 

Our classification system is 

based on the assumption that attributes of the natural environment-climate, soils, gemorphology, and the regional vegetation itself-offer constraints and opportunities for molding the vegetation 

within the urban area. Of course, 

this premise acknowledges the 

importance of the other two factors, 

the distribution of available growing 

space and human influences that 

work in conjunction with the natural 

environment. 

Reliable inventories of urban 

vegetation in the United States, obtained either from on-ground surveys or from remote sensing imagery, do not exist. Existing inventories are confined to specific subsets of urban vegetation, usually 

street tree populations and urban 

public parks. These inventories are 

few and vary in information content 

(Sacksteder and Gerhold 1979). A 

systematic survey of urban vegetation characteristics for a large set of 

American cities, therefore, seems a 

distant hope, particularly because it 

is difficult to determine detailed 

vegetation characteristics from remote sensing. Satellite technology 

(using increased spatial resolution 

of the sensor apparatus and computer-aided interpretation of radiance values associated with 

vegetation characteristics) may offer 

long term promise because of its 

breadth and continuity of coverage 

and the alternative high cost of obtaining on-ground surveys or reliable 

manual interpretations of variable 

quality, low-altitude photography. 

An alternative is to classify 

cities according to characteristics 

of potential vegetation. We suggest 

that knowledge of the regional natural environment in which the city is 

located provides a basis for predicting certain attributes of urban 

vegetation-all tree, shrub, and herbaceous vegetation in the urban 

area. Cities in hot, arid regions will 

tend to have vegetation reflecting 

those facts, and the vegetation of 

these cities usually would differ 

substantially from that in cool, 

moist regions. We believe that 

much urban vegetation, especially 

in less developed and exurban portions, tends to resemble the 

vegetation, at least in general terms, 

of the surrounding ecoregion. 

Whether this is true ultimately depends on the unique combination of 

natural and human-urban histories 

that have produced the current urban vegetation configuration. When 

such histories are available, we will 

know how and why the extant 

vegetation pattern differs from the 

expected regional "baseline" (of 
potential natural vegetation). Two 

categories of influence that explain 

variations from the regional baseline 

are the unique distribution of growing spaces in the city, and the set 

of human preferences for species, 

ages, and conditions of plants. 

There are at least three reasons 

why urban vegetation may resemble 

the surrounding regional vegetation 

complex. First, every city contains 

sizable portions of residual or relict 

vegetation, particularly in the newer 

suburban fringes of the urbanized 

area. This vegetation tends to resemble that in the non-urbanized 

portions of the larger urban region, 

having fallen into the urban category during recent stages of urban 

growth. Second, residual urban 

vegetation and that at the urban 

periphery act as seed sources for 

natural or seminatural propagation 

processes. Third, the potentials for 

and limits on vegetation types and 

densities as defined by the regimes 

of temperatures, precipitation, and 

soil types probably do not differ appreciably from urban to rural locations within broad regional limits, 

except perhaps where intensive urban development at the city center 

and the effects of local topography 

create distinctive sites. Thus, we 

need a measure of the regional natural environment for plant growth 

and development that will serve as a 

baseline for predicting what the urban vegetation configuration might 

be in the absence of direct human 

interference. 

This natural region approach to 

urban classification lacks the vastly 

important anthropogenic or cultural 

component or urban vegetation. The 

myriad decisions to breed, plant, 

maintain, and remove vegetation by 

home and business owners and by 

representatives of both private and 

public institutions collectively 

establish a controlling environment 

for plants, the particular results of 

which have never been determined. 

A central question of urban forest 

science today is in what ways and 

to what degree, do anthropogenic 

influences on urban vegetation 

determine its final configuration. 

We conclude, however, that a classification of urban places according 

to the natural properties of the regions of which they are a part provides a useful guide to the similarities and differences in urban 

vegetation. 

Method of Classification 

For this classification, the 

population of American cities is 

taken as the complete set of Standard Metropolitan Statistical Areas 

(SMSA's) as of 1979. According to 

U.S. Bureau of the Census definitions, there are 279 SMSA's in the 

50 states covering about 20 percent 

of the nation's land area. As a set, 

these SMSA's represent all urban 

places which contain at least one 

central city (a political entity) with a 

population of at least 50,000 and the 

counties in which the surrounding 

eeswomieal ly integrated populations 

are contained. The county basis for 

defining SMSA's, therefore, incorporates into the urban definition 

substantial tracts of what might be 

thought of as nonurban land, land 

which in the eyes of some researchers, however, can be regarded 

largely as "preurban," assuming a 

continuation of metropolitan decentralization trends. The 279 SMSA's 

examined in this study represent all 

the large urban areas in the United 

States. 

To delimit the natural environment of the urban places to project 

likely characteristics of urban 

vegetation or sizable portions of it, 

two variables are used: (1) the "ecoregion" in which the city is located, 

and (2) the Potential Natural Vegetation (PNV) of that location. Each of 

these has been succinctly described and mapped (Bailey 1980, 

USDA Forest Service 19783;. 

The ecoregions devised by 

Bailey reflect the distinctive f tora, 

fauna, climate, landform, soil, 

vegetation, and ecological climax of 

a continuous geographical area. 

These regions differ from surrounding regions in one or more important ecological associations or in 

the proportions of the area covered 

by distinctive associations. The ecoregion system is organized into a 

four-tiered hierarchy, each level 

representing a subdivision of the 

area encompassed by the preceding 

hierarchical level. These levels, from 

upper to lower, are domain, division, 

province, and section. For the purpose of this classification, urban 

places were located at the division 

level, which differentiates regions 

primarily according to vegetation 

and climate, but allows the classification to remain relatively simple. The metropolitan areas of the 

United States are located in 11 of 

the 12 ecoregion divisions. The ecoregion division reflects the general 

availability of heat and moisture, 

both determinants of the limitations 

on and potentials for regional 

associations of vegetation, and the 

PNV is simply a more specific variable describing the natural environment. 

The PNV of an area is the 

vegetation that would exist today if 

man were (now) removed from the 

scene and if the plant succession 

after his removal were telescoped 

into a single moment (Kiichler 1964). 

It reflects both the life-forms 

(physiognomy and structure) and 

the taxa (dominant genera for the regions of PNV). PNV is contrasted 

with actual or real vegetation, which 

is normally expressed or mapped as 

a statistic depiction of the regional 

vegetation at a point in time, independent of any impetus or direction 

of change. We chose PNV over 

existing vegetation for this classification because of the rapid 

change in land use in urban areas, 

particularly in inner city areas where 

population densities are falling and 

open spaces emerging, in suburban 

areas where land development processes are most active, and in exurban areas where the economic 

bases of farm and forest practices 

are increasingly challenged by the 

prospect of continuing metropolitan 

decentralization. The existing 

vegetation in these places (even if 
this were now classified) probably 

would be a poor predictor of developing urban vegetation configurations. PNV suggests what kinds of 

vegetation are possible in these 

areas. 

Using Bailey's recent map, we 

recorded the ecoregion division and 

PNV for each of the 279 SMSA's. 

These were determined by finding 

the exact locations of SMSA's on 

the Bailey map, and determining the 

correct classifications at the visual 

center of the SMSA. Where natural 

boundaries of ecoregions or PNV 

appeared to bisect the metropolitan 

area, only that zone which was 

judged to cover the greatest portion 

of the SMSA was recorded. This preserved simplicity in the classification system. The literal interpretation of natural boundaries on maps 

can be a misleading exercise, because most of these represent 

gradual transitions of natural 

characteristics from one region to 

another, and many boundaries merely reflect only the change in proportions of several of the dominant natural characteristics. This means that 

any attempt of a natural urban classification for any large set of metropolitan areeas is imprecise, and 

needs substantial improvements in 

the quality of natural environmental 

data derived for local sources. 

Results 

The lack of high-quality local 

data and the forced reliance on 

generalized natural maps prohibit 

highly literal interpretations of the 

classification outlined here. The 

classification merely suggests the 

likely similarity and dissimilarity of 

the wild component of urban 

vegetation between metropolitan 

areas. In this sense, the classification refers less to the specific 

character of vegetation in an urban 

place than to the likelihood of 

resemblance with like places. 

A summary of the natural-urban 

classification resulting from this 

process is given in Table 1. More 

than half of the American metropolitan areas are in the Hot Continental and Subtropical ecoregion 

divisions. From the perspective of 

vegetation, roughly two-thirds of the 

SMSA's are located within the Eastern Broadleaf and the Eastern 

Needleleaf and Broadleaf Forests 

(PNV). This implies that a large number of these urban places share 

similar vegetation characteristics, 

and identification of and solutions 

to both scientific and public policy 

problems in any one place may be 

applied in others. In contrast, seven 

metropolitan areas occupy unique 

positions in this classification system, and many others represent a 

typical or special cases in the classification, sharing their natural 

characteristics with only one or two 

urban places. Scientific or public 

policy solutions learned in these 

cities may not be applied easily to 

other cities. 

The detailed results of the classification are given in three crossindexed lists. Appendix II lists the 

SMSA's alphabetically by the name 

of the city (or principal city) in the 

metropolitan area, so individual 

cities may be located easily in the 

classification. In Appendix II, the 

ecoregion division and PNV are 

given for each place. Appendix Ill 

classifies SMSA's by Ecoregion 

Division (alphabetically by states) 

and theses are cross-referenced for 

PNV. Appendix IV lists cities by 

zones of PNV, organizing these 

broadly into life-form zones. By listing metropolitan areas in each of 

these ways, the classification system provides a convenient description of urban natural classes, the 

internal composition of any class, 

and the particular classification of 

any one urban place. 
Table 1 .-Summary classification of SMSA's by ecoregion and by potential natural vegetation 

Ecoregion division 

Potential 

Natural 

Vegetation Warm Hot Sub- Medi- Rain- Total by S" b- Contin- Contin- trop- Marine Prairie terran- Steppe Desert Savanna forest 

Ecosystem arctic ental ental ical ean 

Regions 

West Needle 

leaf forest 

West Needle 

leaf and 

Broad leaf 

forest 

West Shrub 

West Grassland 

West Shrub 

and Grassland 

Central and 

East Grassland 

Central and 

East Grassland and 

forest 

East Needle 

leaf forest 

East Broadleaf forest 

East Needle 

leaf and 

Broad leaf 

Alaskan Types 

Hawaiian type 

Total 1 23 102 61 8 43 14 19 4 3 I 

(0.4) (8.2) (36.6) (21.9) (2.9) (15.4) (5.0) (6.8) (1.4) (1 .O) (0.4) 279(100.@ 

a Number in parentheses is the percentage of total SMSA's in given category. 

Appendix II (Cont.) 

SMSA 

Danbury. CT ...................... Davenport-Rock Island.Moline. IA-I L . . Dayton. OH ....................... Daytona Beach. FL ................ Decatur. IL ....................... 

SMSA PNV 

69 

94 

74 

93 

92 

Houston. TX ...................... Huntington.Ashland. WV-KY-OH ..... Huntsville. AL ..................... Indianapolis. IN ................... Jackson. MI ....................... 

Denver.Boulder. CO ................ Des Moines. IA .................... Detroit. MI ........................ Dubuque. IA ...................... Duluth.Superior. MN-WI ............ 

Jackson. MS ...................... Jacksonville. FL ................... Jersey City. NJ .................... Johnson City.Kingsport.Bristol. 

TN-VA ......................... Johnstown. PA .................... Eau Claire. WI ..................... Elkhart. IN ........................ El Paso. TX ....................... Elmira. NY ........................ Erie. PA .......................... 

Kalamazoo.Portage. MI ............. Kankakee. IL ...................... Kansas City. MO-KS ............... Kenosha. WI ...................... Killeen.Temple. TX ................. Eugene.Springfield. OR ............ Evansville. IN-KY .................. Fall River. MA-RI .................. Fargo.Moorhead. ND-MN ........... Fayetteville. NC ................... 

Knoxville. TN ..................... Kokomo. IN ....................... La Crosse. WI ..................... Lafayette. LA ..................... Lafayette-West Lafayette. IN ........ ~ayetteville.~pringdale. AR ......... Fitchburg.Leominster. MA .......... Flint. MI .......................... Florence. AL ...................... Fort Collins. @O ................... 

Lake Charles. LA .................. Lakeland-Winter Haven. FL ......... Lancaster. PA ..................... Lansing-East Lansing. MI ........... Laredo. TX ........................ Fort Lauderdale~Hollywood. FL ...... Fort Myers. FL .................... Fort Smith. AR.OK ................. Fort Wayne. 1.N .................... Fresno. CA ....................... 

LasVegas. NV .................... Lawrence. KS ..................... Lawrence.Haverhill. MA-NH ......... Lawton. OK ....................... Lewiston-Au burn. ME .............. Gadsden. AL ...................... Gainesville. FL .................... Galveston-Texas City. TX ........... Gary-Hammond-East Chicago. IN .... Grand Forks. ND.MN ............... 

LexingtonmFayette. KY .............. Lima. OH ......................... Lincoln. NE ....................... Little Rock-North Little Rock. AR ..... Long Branch-Asbury Park. NJ ........ Grand Rapids. MI .................. Great Falls. MT .................... Greeley. CO ...................... Green Bay. WI .................... Greensboro-Winston-Salem-High 

Point. NC ....................... 

Longview. TX ..................... LoraimElyria. OH .................. Los Angeles-Long Beach. CA ....... Louisville. KY4N ................... Lowell. MA-NH .................... 

Greenville.Spartansburg. SC ........ Hamilton.Middletown. OH .......... Harrisburg. PA .................... Hartford. CT ...................... Honolulu. HI ...................... 

Lubbock. TX ...................... Lynchburg. VA .................... Macon. GA ....................... Madison. WI ...................... Manchester. NH ................... 
Appendix I1 (Cont.) 

SMSA 

Mansfield. OH .................... McAllen.Pharr.Edinburg. TX ......... Melbourne-Titusvi lle.Cocoa. FI ...... Memphis. TN.AR.MS ............... Meriden. CT ...................... 

SMSA 

Pittsburgh. PA .................... Pittsfield. MA ..................... Portland. ME ...................... Portland. OR-WA .................. Poughkeepsie. NY ................. 

PNV 

Miami. FL ........................ Midland. TX ....................... Milwaukee. W1 .................... Minneapolis.St . Paul. MN-WI ........ Mobile. AL ........................ 

Providence~Warwick~Pawtucket, RI ... Provo.Orem. UT ................... Pueblo. CO ....................... Racine. Wl ........................ Raleigh.Durham. NC ............... 

Modesto. CA ...................... Monroe. LA ....................... Montgomery. AL ................... Muncie. IN ........................ Muskegon-North Shores-Muskegon 

Heights. MI ..................... 

Reading. PA ...................... Reno. NV ......................... Richland.Kennewick. WA ........... Richmond. VA ..................... Riverside-San Bernardino.Ontario. 

CA ............................ 

Roanoke. VA ...................... Rochester. MN .................... Rochester. NY .................... Rockford. IL ...................... Sacramento. CA ................... 

Nashua. NH ...................... Nashville.Davidson. TN ............. Nassau.Suffolk. NY ................ New Bedford. MA ................. New Britain. CT ................... 

New Brunswick-Perth 

Amboy.Sayreville. N J ............ New Haven-West Haven. CT ........ New London.Norwich. CT .......... New Orleans. LA .................. New York. NY.NJ .................. 

Saginaw. MI ...................... St . Cloud. MN ..................... St . Joseph. MO .................... St . Louis. MO4L ................... Salem. OR ........................ 

Salinas.Seaside.Monterey. CA ....... Salt Lake City.Ogden. UT ........... San Angelo. TX .................... San Antonio. TX ................... San Diego. CA .................... 

Newark. NJ ....................... Newport News.Hampton. VA ........ Norfolk-Virginia Beach.Portsmouth. 

VA-NC ......................... Norwalk. CT ....................... Odessa. TX ....................... San Francisco.Oakland. CA ......... San Jose. CA ..................... Santa Barbara-Santa Maria.Lompoc. 

CA ............................ Santa Cruz. CA .................... Santa Rosa. CA ................... 

Oklahoma City. OK ................ Omaha. NE4A ..................... Orlando. FL ....................... Owensboro. KY ................... Oxnard-Simi Valley.Ventura. CA ..... Sarasota. FL ....................... Savannah. GA ..................... Scranton-Wil kes.Barre*Hazleton. PA . . Seatt1e.Everet-t. WA ................ Sherman.Denison. TX .............. 

Panama City. FL ................... Parkersburg.Marietta. WV-OH ....... Pascagoula-Moss Point. MS ......... Paterson.Clifton~Passaic. NJ ........ Pensacola. FL ..................... Shreveport. LA .................... Sioux City. IA-NE .................. Sioux Falls. SD .................... South Bend. IN .................... Spokane. WA ..................... 

Peoria. lL ......................... Petersburg-Colonial 

Heig hts.Hopewell. VA ............ Philadelphia. PA.NJ ................ Phoenix. AZ ...................... Pine Bluff. AR ..................... 
Appendix II (Cont.) Appendix Ill 

SMSA 

Springfield, IL. . . . . . . . . . . . . . . . . . . . . Springf ield-Chicopee-Holyoke, 

MA-CT ......................... Springfield, MO . . . . . . . . . . . . . . . . . . . Springfield, OH . . . . . . . . . . . . . . . . . . . Stamford, CT . . . . . . . . . . . . . . . . . . . . . 

Steubenville-Weirton, OH-WV . . . . . . . Stockton, CA . . . . . . . . . . . . . . . . . . . . . Syracuse, NY . . . . . . . . . . . . . . . . . . . . . Tacoma, WA.. . . . . . . . . . . . . . . . . . . . . Tallahassee, FL . . . . . . . . . . . . . . . . . . . 

Tampa-St. Petersburg, FL.. . . . . . . . . . Terre Haute, IN.. . . . . . . . . . . . . . . . . . . Texarkana, TX-Texarkana, AR. . . . . . . . Toledo, OH-MI . . . . . . . . . . . . . . . . . . . . Topeka,KS ....................... 

Trenton, NJ. . . . . . . . . . . . . . . . . . . . . . . Tuscon,AZ ....................... Tulsa, OK . . . . . . . . . . . . . . . . . . . . . . . . Tuscaloosa, AL. . . . . . . . . . . . . . . . . . . . Tyler, TX . . . . . . . . . . . . . . . . . . . . . . . . . 

Utica-Rome, NY . . . . . . . . . . . . . . . . . . . Vallejo-Fairfield-Napa, CA . . . . . . . . . . Vineland-Millville-Bridgeton, NJ . . . . . Waco,TX ......................... Washington, DC-MD-VA . . . . . . . . . . . . 

Waterbury, CT. . . . . . . . . . . . . . . . . . . . . Waterloo-Cedar Falfs, IA. . . . . . . . . . . . West Palm Beach-Boca Raton, FL . . . Wheeling, WV-OH . . . . . . . . . . . . . . . . . Wichita, KS.. . . . . . . . . . . . . . . . . . . . . . 

Wichita Falls, TX . . . . . . . . . . . . . . . . . . + Williamsport, PA . . . . . . . . . . . . . . . . . . Wilmington, DE-NJ-MD.. . . . . . . . . . . . Wilmington, NC . . . . . . . . . . . . . . . . . . . Worcester, MA.. . . . . . . . . . . . . . . . . . . 

Yakirna, WA.. . . . . . . . . . . . . . . . . . . . . . York,PA .......................... Youngstown-Warren, OH . . . . . . . . . . . 

ED PNV 

2500 91 

SMSA Classlflcation by ED4 

1 300 SUBARCTIC Dl VISION 

Alaska 

Anchorage. . . . . . . . . . . . . . . . . . . . . . . . . 

2100 WARM CONTINENTAL DIVISION 

Maine 

Lewiston-Auburn . . . . . . . . . . . . . . . . . . . Portland ........................... Massachusetts 

Brockton . . . . . . . . . . . . . . . . . . . . . . . . . . Fitchburg-Leominster . . . . . . . . . . . . . . . Lowell ............................. Worcester . . . . . . . . . . . . . . . . . . . . . . . . . Michigan 

Bay City . . . . . . . . . . . . . . . . . . . . . . . . . . . Muskegon-North Shores-Muskegon 

Heights . . . . . . . . . . . . . . . . . . . . . . . . . Saginaw . . . . . . . . . . . . . . . . . . . . . . . . . . . Minnesota 

Dulut h-Superior . . . . . . . . . . . . . . . . . . . . New Hampshire 

Manchester ........................ Nashua ............................ New York 

Al bany-Schenectady-Troy . . . . . . . . . . . . Binghamton. . . . . . . . . . . . . . . . . . . . . . . . Elmira ............................. Poughkeepsie . . . . . . . . . . . . . . . . . . . . . . Rochester . . . . . . . . . . . . . . . . . . . . . . . . . Syracuse .......................... Utica-Rome . . . . . . . . . . . . . . . . . . . . . . . . Pennsylvania 

Scranton-Wilkes-Barre-Hazelton.. . . . . . Washington 

Spokane ........................... Wisconsin 

Green Bay . . . . . . . . . . . . . . . . . . . . . . . . . 

The list of SMSA's within ecoregion 

divisions is arranged alphabetically by 

state. Note that for SMSA's with compound names the state of the firstnamed urban place is given and the state 

of the second or third-named urban place 

is not given. 
Appendix Ill (Cont.) 

WOTCONUNENTAL DIVISION 

Alabama 

Florence ........................... Huntsville ......................... Arkansas 

Fayetteville-Springdale .............. Fort Smith ......................... Connecticut 

Bridgeport ......................... Bristol ............................ Danbu ry ........................... Hartford ........................... Meriden ........................... New Britain ........................ New Haven-West Haven .............. New London-Norwich ............... Norwalk ........................... Stamford .......................... Waterbury ......................... Delaware 

Wilmington ........................ Indiana 

Anderson .......................... Bloomington .............. .. ....... El khart ............................ Evansville .......................... Fort Wayne ........................ Gary-Hammond-East Chicago ......... Indianapolis ........................ Kokomo ........................... Lafayette-West Lafayette ............. Muncie ............................ SouthBend ........................ lo wa 

Du buque .......................... Kentucky 

Lexington-Fayette .................. Louisville .......................... Owensboro ........................ Massachusetts 

Boston ............................ Fall River .......................... Lawrence.Haverhiil .................. New Bedford ....................... Springfield-Chicopee-Holyoke ........ Michigan 

Ann Arbor .......................... Battle Creek ........................ Detroit ............................ Flint .............................. Grand Rapids ....................... Jackson ........................... Kalamazoo-Portage ................. Lansing-East Lansing ................ Minnesota 

Minneapolis.St . Paul ................ Rochester ......................... St . Cloud .......................... 

PN V Missouri 

Columbia .......................... 91 

St . Louis ........................... 91 

Springfield ......................... 73 

New Jersey 

Jersey City ......................... 95 

Long Branch-Asbury Park ............ 95 

New Brunswick-Perth 

Amboy-Sayreville ................. 95 

Newark ............................ 95 

Paterson-Clifton-Passaic ............. 95 

Trenton ........................... 95 

New York 

Buffalo ............................ 93 

Nassau-Suffol k ..................... 100 

New York .......................... 95 

North Carolina 

Asheville .......................... 95 

Ohio 

Akron ............................. 93 

Canton ............................ 95 

Cincinnati ......................... 91 

Cleveland .......................... 93 

Columbus ......................... 93 

Dayton ............................ 91 

Hamilton-Middletown ............... 93 

Lima .............................. 93 

Lorain-Elyria ....................... 92 

Mansfield .......................... 93 

Springfield ......................... 73 

Steubenville-Weirton ................ 95 

Toledo ............................ 92 

Youngstown-Warren ................. 93 

Pennsylvania 

Allentown-Bethlehem-Easton ......... 95 

Altoona ........................... 95 

Erie ............................... 93 

Harrisburg ......................... 95 

Johnstown ......................... 95 

Lancaster .......................... 95 

Philadelphia ....................... 95 

Pittsburgh ......................... 95 

Reading ........................... 95 

Williamsport ....................... 95 

York .............................. 95 

Rhode Island 

Providence-Warwick-Pawtucket ....... 95 

Tennessee 

Chattanooga ....................... 101 

Clarksville-Hopkinsvi lle .............. 91 

Johnson City-Kingsport-Bristol ....... 95 

Knoxville .......................... 95 

Nashville-Davidson .................. 91 

Wes t Virginia 

Charleston ......................... 94 

Huntington-Ashland ................. 94 

Parkersburg-Marietta ................ 95 

Wheeling .......................... 95 
Wisconsin 

Appleton-Oshkosh .................. Eau Claire ......................... Kenosha ........................... Lacrosse .......................... Madison ........................... Miiwaukee ......................... Racine ............................ 

2300 SUBTROPICAL Dl VISION 

PNV 

90 

72 

72 

90 

72 

90 

90 

Alabama 

Anniston .......................... 101 

Birmingham ........................ 101 

Gadsden .......................... 101 

Mobile ............................ 102 

Montgomery ....................... 103 

Tuscaloosa ........................ 101 

Arkansas 

LittleRock-NorthLittleRock .......... 101 

Pine Bluff .......................... 101 

District of Columbia 

Washington ........................ 101 

Florida 

Bradenton ......................... 102 

Daytona Beach ..................... 102 

Fort Myers ......................... 102 

Gainesville ......................... 102 

Jacksonville ....................... 102 

Lakeland-Winter Haven .............. 102 

Melbourne-Titusville-Cocoa .......... 102 

Orlando ........................... 102 

Panama City ....................... 102 

Pensacola ......................... 102 

Sarasota ........................... 102 

Tallahassee ........................ 102 

Tampa-St . Petersburg ................ 102 

Georgia 

Albany ............................ 102 

Atlanta ............................ 101 

Augusta ........................... 101 

Columbus ......................... 101 

Macon ............................ 101 

Savannah .......................... 102 

Louisiana 

Alexandria ......................... 101 

Baton Rouge ....................... 91 

Lafayette .......................... 103 

Lake Charles ....................... 102 

Monroe ............................ 103 

New Orleans ....................... 103 

Shreveport ......................... 103 

Maryland 

Baltimore .......................... 101 

Mississippi 

Biloxi-Gulfport ..................... 102 

Jackson ............................ 101 

Pascagoula-Moss Point .............. 102 

New Jersey PNV 

Atlantic City ........................ 65 

Vineland-Millville-Bridgeton .......... 100 

North Carolina 

Burlington ......................... 101 

Charlotte-Gastonia .................. 101 

Fayetteville ........................ 101 

Greensboro-Winston-Salem-High 

Point ............................ 101 

Raleigh-Durham .................... 101 

Wilmington ........................ 102 

South Carolina 

Charleston-North Charleston ......... 101 

Columbia .......................... 101 

Greenville-Spartansburg ............. 101 

Tennessee 

Memphis .......................... 103 

Texas 

Beaumont-Port Arthur-Orange ........ 69 

Longview .......................... 101 

Texarkana ......................... 101 

Tyler .............................. 101 

Virginia 

Lynchburg ......................... 101 

Newport News-Hampton ............. 101 

Norfolk-Virginia Beach-Portsmouth .... 101 

Petersburg-Colonial 

Heights-Hopewell ................. 101 

Richmond ......................... 101 

Roanoke ..................... ... .. 101 

2400 MA RlNE Dl VISION 

California 

San Francisco-Oakland .............. 40 

Santa Rosa ......................... 25 

Vallejo-Fairf ield-Napa ............... 40 

Oregon 

Eugene-Springfield .................. 24 

Portland ........................... 2 

Salem ............................. 24 

Washington 

Seattle-Everett ..................... 2 

Tacoma ........................... 2 

2500 PRAIRIE DIVISION 

Illinois 

Bloomington-Normal ................ Champaign-Urbana-Rantoul .......... Chicago ........................... Decatur ........................... Kankakee .......................... Peoria ............................. Rockford .......................... Springfield ......................... Indiana 

Terre Haute ........................ 

Appendix IV 

SMSA Classification by Zones of PNVs 

WESTERN NEEDLELEAF FOREST ED 

2 Cedar-hemlock- Douglas-fir forest 

Portland, OR-WA ................... 2400 

Seattle-Everett,WA ................. 2400 

Tacoma,WA ....................... 2400 

1 1 Douglas-fir forest 

Spokane,WA ....................... 2100 

WESTERN NEEDLELEAF AND BROADLEAF FOREST 

24 Cedar-hemlock- Douglas-fir forest 

and Oregon oakwoods 

Eugene-Springfield, OR.. ............ 2400 

Salem, OR.. ....................... 2400 

25 California mixed evergreen forest 

Santa Rosa, CA ..................... 2400 

26 California oakwoods 

Oxnard-Sim i Valley-Ventura, CA. ...... 2600 

Santa Barbara-Santa Maria-Lompoc, CA. .26QO 

Santa Cruz, CA ..................... 2600 

WESTERN SHRUB 

30 Coastal sagebrush 

Riverside-San Bernardino-Ontario, CA . San Diego, CA.. .................... 31 Mountain mahogany--oak scrub 

Provo-Orem, UT .................... 32 Great Basin sagebrush 

Salt Lake City-Ogden, UT ............ 34 Saltbrush-grease wood 

Bakersfield, CA.. ................... 35 Creosote bush 

Las Vegas, IVV ..................... 36 Creosote bush-bur sage 

Phoenix, AZ. ....................... Tucson,AZ ........................ 38 Ceniza shrub 

Laredo, TX. ........................ 

WESTERN GRASSLAND 

40 Fescue-oatgrass 

San Francisco-Oakland, CA .......... 2400 

San Jose, CA ...................... 2600 

Vallejo-Fairfield-Napa,CA ............ 2400 

41 California steppe 

Anaheim-Santa Ana-Garden Grove, CA. 2600 

Fresno,CA ........................ 2600 

Los Angeles-Long Branch, CA ........ 2600 

Saiinas-Seaside-Monterey, CA ........ 2600 

Based on Kuchler (1964). The numerical prefix to the PNV class corresponds 

to that given by Bailey (1978). The numerical suffix to the SMSA refers to the 

ecoregion division. 

42 Tule marshes 

Modesto, CA ....................... Sacramento, CA .................... Stockton, CA. ...................... 47 Grama-galleta steppe 

Albuquerque, NM ................... 

WESTERN SHRUB AND GRASSLAND 

49 Sagebrush steppe 

Boise City, ID ...................... Reno, NV.. ........................ Richland-Kennewick, WA ............ Yakima, WA. ....................... 52 Grama-tobosa shrubsteppe 

ElPaso,TX ........................ 54 Mesquite-acacia-savanna 

Brownsville-Harlingen-San Benito, TX . McAllen-Pharr-Edinburg, TX .......... 

CENTRAL AND EASTERN GRASSLANDS 

Foothills prairie 

Great Falls, MT. .................... Grama-bu f falograss 

Amarillo, TX. ....................... Colorado Springs, CO ............... Denver-Boulder, CO. ................ Fort Collins, CO .................... Greeley, CO ....................... Lubbock, TX ....................... Midland, TX. ....................... Odessa, TX ........................ Pueblo, CO ........................ Bluestem-grama prairie 

Lawton, OK.. ...................... Oklahoma City, OK ................. Northern cordgrass prairie 

Atlantic City, NJ.. .................. Bluestem prairie 

Sioux City, IA-NE ................... Sioux City, SD.. .................... Blackland prairie 

Austin, TX ......................... Dallas-Fort Worth, TX ............... Killeen-Temple, TX .................. Waco,TX .......................... Bluestem-sacahuista prairie 

Beaumont-Port Arthur-Orange, TX. .... Corpus Christi, TX .................. Houston, TX ....................... Southern cordgrass prairie 

Galveston-Texas City, TX ............ 
Appendix IV (Cont.) 

CENTRAL AND EASTERN GRASSLAND AND 

FOREST COMBINATION 

72 Oak savanna 

Eau Claire. Wl ...................... Kenosha. WI ....................... Madison. Wl ....................... Minneapofis.St. Paul. MN-WI ......... St . Cloud. MN ...................... 73 Bluestem prairie and oak-hickory forest 

Bloomington.Normal. IL ............. Champaign.Urbana.Rantou1. I L ....... Chicago. IL ........................ Kankakee. IL ....................... Lawrence. KS ...................... Rockford. IL ....................... St Joseph. . MO ..................... Springfield. OH ..................... Springfield. MO .................... Topeka. KS ........................ 74 Cedar glades 

Huntsville. AL ...................... 75 Cross timbers 

Sherman.Denison. TX ............... Tulsa. OK .......................... 76 Mesquite-buffalo grass 

Abilene. TX ........................ San Angelo. TX ..................... Wichita Falls. TX ................... 78 Mesquite-oak savanna 

San Antonio. TX .................... 

EASTERN NEEDLELEAF FOREST 

86 Great Lakes pine forest 

Muskegon-North Shores-Muskegon 

Heights. MI ...................... Duluth.Superior. MN-WI ............. 

EASTERN BROADLEA F FOREST 

89 Northern floodplain forest 

Billings. MT ........................ Bismarck. ND ...................... Fargo.Moorhead. N D-M N ............ Grand Forks. ND-MN ................ Lincoln. NE ........................ Wichita. KS ........................ 90 Maple-basswood forest 

Appleton.Oshkosh. Wl ............... Dubuque. IA ....................... La Crosse. WI ...................... Milwaukee. WI ..................... Racine. WI ......................... Rochester. MN ..................... 91 Oak- hickory forest 

Ann Arbor. MI ...................... Baton Rouge. LA ................... Battle Creek. MI .................... Bryan-College Station. TX ............ Cedar Rapids. IA ................... Cincinnati. OH.KY.IN ................ Clarksville~Hopkinsville. TN-KY ....... Columbia. MO ...................... 

Davenport-Rock Island.Moline. IA4L ... Dayton. OH ........................ Decatur. IL ......................... Des Moines. IA ..................... Elkhart. IN ......................... Fayetteville.Springdale. AR .......... Flint. MI ........................... Florence. AL ....................... Fort Wayne. IN ..................... Gary-Hammond-East Chicago. IN ..... Kalamazoo~Portage. Mi .............. Kansas City. MO.KS ................. Lafayette-West Lafayette. IN ......... Lexington.Fayette. KY ............... Louisville. KY4N .................... Nashville~Davidson. TN .............. Omaha. N E-IA ...................... Owensboro. KY ..................... Peoria. lL .......................... St . Louis. MO4L .................... South Bend. IN ..................... Springfield* IL ...................... Terre Haute. IN ..................... Waterloo-Cedar Falls. IA ............. 92 Elm-ash forest 

Bay City. MI ........................ Detroit. MI ......................... Jackson. MI ........................ LoraimElyria. OH ................... Saginaw. MI ........................ Toledo. OH.MI ...................... 93 Beech-maple forest 

Akron. OH ......................... Anderson. IN ....................... Bloomington. IN .................... Buffalo. NY ........................ Cleveland. OH ...................... Columbus. OH ..................... Erie. PA ........................... Grand Rapids. MI ................... Hamilton.Middletown. OH ........... Indianapolis. IN .................... Kokomo. IN ........................ Lansing-East Lansing. MI ............ Lima. OH .......................... Mansfield. OH ...................... Muncie. IN ......................... Utica-Rome. NY .................... Youngstown.Warren. OH ............. 94 Mixed mesophytic forest 

Charleston. WV ..................... Huntington.Ashland. WV-KY-OH ...... 95 Appalachian oak forest 

Allentown.Bethlehem.Easton. PA ..... Altoona. PA ........................ Asheville. NC ...................... Boston. MA ........................ Bridgeport. CT ..................... 
Appendix IV (Cont.) ED 

Bristol. CT ......................... Canton. OH ........................ Danbury. CT ....................... Elmira. NY ......................... Fall River. MA471 .................... Harrisburg. PA ..................... Hartford. CT ....................... Jersey City. NJ ..................... Johnson City.Kingsport.Bristo1. TN-VA 

Johnstown. PA ..................... Knoxville. TN ....................... Lancaster. PA ...................... Lawrence.Haverhil1. MA-NH .......... Long Branch-Asbury Park. NJ ........ Meriden. CT ........................ New Bedford. MA ................... New Britain. CT .................... New Brunswick-Perth AmboySayreville. NJ ...................... New Haven-West Haven. CT .......... New London.Norwich. CT ............ New York. NY-NJ ................... Newark. NJ ........................ Norwalk. CT ........................ Parkersburg.Marietta. WV-OH ........ Paterson-Cl ifton.Passaic. N J ......... Philadelphia. PA-NJ ................. Pittsburgh. PA ...................... Poughkeepsie. NY .................. Providence~Warwick~Pawtucket. RI .... Reading. PA ....................... Scranton.Wilkes.Barre~Hazelton. PA ... Springfield.Chicopee.Holyoke. MA-CT . Stamford. CT ....................... Steubenville.Weirton. OH.WV ......... Trenton. NJ ........................ Waterbury. CT ...................... Wheeling. WV.OH ................... Williamsport. PA .................... Wilmington. DE-NJ-MD .............. York. PA ........................... 

EASTERN NEEDLELEAF AND BROADLEAF FOREST 

97 Northern hard woods 

Al bany.Schenectady.Troy. NY ........ Binghamton. NY-PA ................. Brockton. MA ...................... Fitchburg.Leominster. MA ........... Green Bay. Wl ...................... Lewiston.Auburn. ME ............... Lowell. MA-NH ..................... Manchester. NH .................... Nashua..NH. ....................... Pittsfield. MA ...................... Portland. ME ....................... Rochester. NY ...................... Syracuse. NY ....................... Worcester. MA ..................... 

100 Northeas tern oak-pine forest 

Nassau.Suffolk. NY ................. Vineland.Millville~Bridgeton. NJ ....... 101 Oak-hickory-pine forest 

Alexandria. LA ..................... Anniston. AL ....................... Atlanta. GA ........................ Augusta. GA-SC .................... Baltimore. MD ...................... Birmingham. AL .................... Burlington. NC ..................... Chattanooga. TN-GA ................ Charleston-North Carolina. SC ........ Charlotte.Gastonia. NC .............. Columbia. SC ...................... Columbus. GA.AL ................... Fayetteville. NC .................... Gadsden. AL ....................... Greensboro-Winston-Salem-High Point. 

NC .............................. Greenvil le.Spartansburg. SC .......... Jackson. MS ....................... Little Rock-North Little Rock. AR ..... Longview. TX ....................... Lynchburg. VA ..................... Macon. GA ......................... Newport News.Hampton. VA ......... Norfolk-Virginia Beach.Portsmouth. 

VA-NC .......................... Petersburg-Colonial Heights.Hopewel1. 

VA .............................. Pine Bluff. AR ...................... Raleigh.Durham. NC ................ Richmond. VA ...................... Roanoke. VA ....................... Texarkana. TX.Texarkana. AR ......... Tuscaloosa. AL ..................... Tyler. TX ........................... Washington. DC-MD-VA ............. 102 Southern mixed forest 

Albany. GA ........................ Biloxi.Gulfport. MS .................. Bradenton. FL ...................... Daytona Beach. FL .................. Fort Lauderdale~Hollywood. FL ....... Fort Myers. FL ...................... Gainesville. FL ..................... Jacksonville. FL .................... Lake Charles. LA ................... Lakeland-Winter Haven. FL ........... Me1 bourne~Titusville~Cocoa. FL ....... Mobile. AL ......................... Orlando. FL ........................ Panama City. FL .................... Pascagoula-Moss Point. MS .......... Pensacola. FL ...................... Sarassta. FL ....................... Savannah. GA ...................... Tallahassee. FL ..................... Tampa.St . Petersburg. FL ............ West Palm Beach-Boca Raton. FL ..... Wilmington. NC .................... 
AppendJx IV (Cont.) Literature Cited 

103 Southern floodplain forest 

Evansville, IN-KY ................... Fort Smith, AR-OK.. ................ Lafayette, LA.. ..................... Memphis, TN-AR-MS ................ Monroe,LA ........................ Montgomery, AL.. .................. New Orleans, LA ................... Sh reveport, LA ..................... 106 Sub tropical pine forest 

Miami, FL. ......................... 

ALASKAN VEGETATION 

\ 

113 Black spruce forest 

Anchorage, AK.. ................... 

HAWAllA N VEGETATION 

121 Schlerophyllous 

forest-shrubland-grassland 

Honolulu, HI.. ..................... 

Bailey, Robert G. Descriptions of 

the ecoregions of the United 

States. U.S. Dep. Agric. For. Sew.; 

1980; Misc. Pub. No. 1391. 77 p. 

Berry, Brian J. L.; Morton, Frank E. 

Geographic perspectives on urban 

systems. Englewood Cliffs, N.J.: 

Pren t ice-Hal 1; 1970. 564 p. 

Berry, Brian J. L. [et al.]. Land use, 

urban form, and environmental 

quality. Univ. Chicago; 1974; 

Geogr. Res. Pap. No. 155,440 p. 

Kuchler, A. W. Potential natural 

vegetation of the coterminous 

United States. Am. Geogr. Soc.; 

1964; Spec. Pub. No. 36. 116 p. 

Sacksteder, Christopher J.; Gerhold, 

Henry. A guide to urban tree inventory systems. The Pennsylvania State Univ,; 1979; The Pennsylvania State Univ.; For. Resour. 

Res. Pap. No. 43. 52 p. 

U.S. Department of Agriculture, 

Forest Service, Ecosystems of the 

United States, RARE II, Map B. 

Washington, D.C.: U.S. Department of Agriculture, Forest Service; 1978. 
Sanders, Ralph A.; Rowntree, Rowan A. Classification of 

American metropolitan areas by ecoregion and potential 

natural vegetation. Res. Pap. NE-516. Broomall, PA: U.S. Department of Agriculture, Forest Service, Northeastern Forest Experiment Station.; 1983. 15 p. 

This publication classifies 279 American metropolitan areas 

by ecoregion and potential natural vegetation. The classification forms a baseline of expected vegetation structure and 

composition that can assist scientists and policymakers in 

making urban forestry generalizations about classes of cities. 

Keywords: urban forestry; regional ecology 

* U. S. GOVERNMENT PRINTING QEE.U3h 1983-605424 :57 
Headquarters of the Northeastern Forest Experiment Station are in 

Broomall, Pa. Fiild laboratories are maintained at: 

Amherst, Massachusetts, in cooperation with the University of 

Massachusetts. 

Berea, Kentucky, in cooperation with Berea College. 

Burlington, Vermont, in cooperation with the University of 

Vemont. 

Delaware, Ohio. 

, New Hampshire, in cooperation with the University of 

New Hatnphire. 

Harmden, Connwticut, in cooperation with Yale University. 

0 Morgantown, West Virgtnia, in cooperation with West Virginia 

University, Morgmtown. 

@ Orono, Mhe, in cooperation with the University of Maine, 

Orono. 

Parsons, West Virginia. 

Princeton, West Virginia. 

Syracuse, New York, in cooperation with the State University of 

New York College of Environmental Sciences and Forestry at 

Syracuse University, Syracuse. 

0 University Park, Pennsylvania, in cooperation with the 

Pennsylvania State University. " Warren, Pennsylvania.