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2008

This is to certify that the
thesis entitled

CHANGES IN THE URBAN FOREST IN
GRAND JUNCTION, CO, 1980-2004.

presented by
Heidi Marie Frei

has been accepted towards fulfillment
of the requirements for the

MS. degree in Forestry

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/ Z Major Professor’s Signature

5%1/07

Date

MSU is an Affin'native Action/Equal Opportunity Institution

 

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PLACE lN RETURN BOX to remove this checkout from your record.
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6/07 p:/C|RC/DaleDue.indd-p.1

CHANGES IN THE URBAN FOREST IN
GRAND JUNCTION, CO, 1980-2004.

By

Heidi Marie Frei

A THESIS
Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of
MASTER OF SCIENCE
Department of Forestry

2007

ABSTRACT

CHANGES IN THE URBAN FOREST IN
GRAND JUNCTION, CO, 1980-2004.
By

Heidi Marie Frei

Urban forest characteristics, tree size, condition, and species diversity for trees publicly
and privately owned within neighborhoods defined by age, were studied in ten cities
nationwide in 1980. Grand Junction, Colorado, included in the 1980 sample, was again
sampled in 2004 for a comparative analysis that also included a survey of public
perception. Species diversity on public property was far below that on private property
and has decreased considerable during the intervening period. In older neighborhoods,
the influence of ownership had little effect on overall species diversity. Diversity in the
oldest neighborhoods was higher than that found in younger neighborhoods. Trees found
on private property were also in better condition and represented by higher percentages of
saplings than those on public property, although this percentage has decreased
significantly over time. Condition rating and neighborhood age appear to be inversely
related, a trend that remained unchanged over 24 years. Size appeared to increase
incrementally with age of neighborhood. More large and medium size trees were found
on public property. This has remained unchanged during the sample period, due to a

reduction in tree planting on public property.

COPyright by

HEIDI MARIE FREI
2007

It

 

To my family and Mr. Justin Kunkle for their continuous support and encouragement and

in memory of Mr. Michael J. Frei.

iv

ACKNOWLEDGMENTS

This project could not have come together without the support, advice, and
encouragement of a number of people. I owe a great deal of gratitude to my committee,
Dr. J. James Kielbaso, Dr. Mel Koelling, and Dr. Michael Thomas. I would also like to
recognize all of my professors at Michigan State University, during both undergraduate
and graduate studies, particularly those in the Forestry and Urban Planning departments,

whose knowledge and guidance will shape my future.

I’d like to thank my mother, Mary Margaret Jimenez Frei, for her strength and support.
To my brothers, Eric, Roland, and Kurt, and my sisters, Ingrid, Krystal, and Jennifer, for
their love and fi'iendship. Special thanks to my sister, Cheryl, for her assistance in data
collection. To Mr. Justin Kunkle for his enduring encouragement and advice and the

Silveira family for their love and guidance.

Special thanks are due to the community of Grand Junction, CO, The Center for Latin
American and Caribbean Studies for funding my academic program, The US. Forest
Service, the Grand Junction, CO, planning department, Mr. William Cannon, Mr. and

Mrs. Bill Trusty, Juli Kerr, and Jennifer Boice.

TABLE OF CONTENTS

LIST OF TABLES ................................................................................. viii
LIST OF FIGURES ................................................................................. xi
LIST OF APPENDICES ........................................................................... xii
INTRODUCTION .................................................................................... 1
LITERATURE REVIEW ........................................................................... 5
Urban tree benefits ........................................................................... 5

Urban forest comparative analysis ......................................................... 8

Urban forest attitude surveys ............................................................. 14
STUDY SITE: Grand Junction, CO, USA ....................................................... 20
History ....................................................................................... 20
Geography and demographics ............................................................ 20
The Grand Mesa Region .................................................................. 22
Industry ...................................................................................... 24
Development and urban planning ......................................................... 28
MATERIALS AND METHODS .................................................................. 30
Background ................................................................................. 30

1980: Study design ........................................................................ 31
Species diversity ................................................................... 32

Tree Condition ..................................................................... 33

Tree Size ............................................................................ 34

2004: Study design ........................................................................ 34
Species diversity, tree condition, tree size ..................................... 35

Survey of resident attitudes ...................................................... 36

Questionnaire ...................................................................... 36

Survey procedure .................................................................. 38

Data analysis ......................................................................................... 39
Species diversity ........................................................................... 40

Tree condition and size .................................................................... 41
Survey response ............................................................................ 42

vi

RESULTS ............................................................................................ 43

Grand Junction, 1980: Species diversity ................................................ 43

Tree size ............................................................................ 45

Tree condition ...................................................................... 49

Grand Junction, 2004: Species diversity ............................................... 53

Tree size ............................................................................ 55

Tree condition ..................................................................... 57

Comparative analysis, 1980-2004: Species diversity ................................. 61

Tree size ............................................................................. 63

Tree condition ...................................................................... 66

Resident survey, 2004 ..................................................................... 7O
Demographics and return rate ................................................... 70

Urban tree benefits ................................................................ 72

Urban tree annoyances ............................................................ 74

Urban tree condition .............................................................. 74

Urban tree size ..................................................................... 76

Pruning and maintenance ......................................................... 76

Tree plantings ...................................................................... 77
DISCUSSION ....................................................................................... 79
The City of Grand Junction, CO .......................................................... 79

Grand Junction after 24 years ............................................................. 85
Resident survey, 2004 ..................................................................... 87
Summary .................................................................................... 90
Recommendations .......................................................................... 93
APPENDICES ....................................................................................... 94
LIST OF REFERENCES ......................................................................... 129

vii

Table

Table 1

Table 2

Table 3

Table 4

Table 5

Table 6

Table 7

Table 8

Table 9

Table 10

Table 1 1

Table 12

Table 13

Table 14

LIST OF TABLES

Title Page

Guide for assessing condition rating of inventory trees, Grand Junction,

CO. .................................................................................. 33
Chart for determining condition rating of trees inventoried in Grand
Junction, CO. ..................................................................... 34
Size classifications of trees measured, Grand Junction, CO. ............... 34

Age class stratification of neighborhood developments in Grand Junction,

CO. ................................................................................. 35
Size class delineations for trees on public and private property, Grand
Junction, CO. ...................................................................... 36
List of survey questions included in 2004, Grand Junction, CO ............ 42
Mean species diversity indices of public and private forest component,
Grand Junction, CO, 1980 ....................................................... 43
Five most prevalent species, Grand Junction, CO, 1980 ..................... 44
Chi-square test probabilities comparing size of trees in neighborhoods

of varying age, Grand Junction, CO, 1980 ..................................... 46
Chi-square test probabilities comparing size of trees on public and private
property in Grand Junction, CO, 1980 .......................................... 48
Chi-square test probabilities comparing condition of trees in
neighborhoods of varying age, Grand Junction, CO, 1980 ................... 51
Chi-square test probabilities comparing condition of trees on public and
private property in Grand Junction, CO, 1980 ................................. 52
Species diversity indices for all sample areas in Grand Junction, CO,

2004 ................................................................................. 53
Five most prevalent species, Grand Junction, CO, 2004 ..................... 54

viii

Table

Table 15

Table 16

Table 17

Table 18

Table 19

Table 20

Table 21

Table 22

Table 23

Table 24

Table 25

Table 26

Table 27

Table 28

Title Page

Chi-square test probabilities comparing size of trees in neighborhoods of
varying age, Grand Junction, CO, 2004 ....................................... 56

Chi-square test probabilities comparing size of trees on public and private
property in Grand Junction, CO, 2004 .......................................... 58

Chi—square test probabilities comparing condition of trees in
neighborhoods of varying age, Grand Junction, CO, 2004 .................. 59

Chi-square test probabilities comparing condition of trees on public and
private property in Grand Junction, CO, 2004 ................................. 60

Mean species diversity and standard of error comparison of urban forest
from 1980 - 2004, Grand Junction, CO ........................................ 62

Chi-square test probabilities comparing size of trees on public and private
property from 1980-2004, Grand Junction, CO ............................... 64

Chi-square test probabilities comparing size of trees in neighborhoods of
varying age from 1980-2004, Grand Junction, CO ............................ 65

Chi-square test probabilities comparing change in tree condition on public
and private property from 1980-2004, Grand Junction, CO ................. 68

Chi-square test probabilities comparing condition of trees in
neighborhoods of varying age from 1980-2004, Grand Junction, CO. ....69

Survey response rate in selected age classes of neighborhood throughout
Grand Junction, CO, 2004 ....................................................... 7O

Socio—demographic characteristics of survey respondents, Grand Junction,
CO, 2004 ........................................................................... 71

Residents’ mean ratings and ranking of benefits received from the positive
features of urban street trees in selected neighborhoods, Grand Junction,
CO, 2004 ........................................................................... 73

Residents’ mean ratings and ranking of annoyance of negative features
of urban street trees in selected neighborhoods, Grand Junction, CO,
2004 ................................................................................. 75

Residents’ mean condition ratings of street trees in selected
neighborhoods, Grand Junction, CO, 2004 .................................... 76

ix

Table

Table 29

Table 30

Table 31

Table 32

Table 33

Table 34

Table 35

Table 36

Table 37

Table 38

Table 39

Table 40

Title Page

Residents’ mean size ratings of street trees in selected neighborhoods,
Grand Junction, CO, 2004 ....................................................... 76

Residents’ mean pruning ratings of street trees in selected neighborhoods,
Grand Junction, CO, 2004 ....................................................... 77

Residents’ mean rating of city maintenance of street trees, Grand Junction,
CO, 2004 ............................................................................ 77

Residents’ opinions on increasing urban tree plantings, Grand Junction,
CO, 2004 ........................................................................... 78

Mean species diversity and standard of error calculated using Tukey-

Kramer on public and privately managed lands in 10 US. cities,
1980 ................................................................................. 97

Chi-square test probabilities comparing overall condition of all trees
(public and private) in all age developments .................................. 99

Chi-square test probabilities comparing condition of all trees on public
property in the 10 study cities, 1980 .......................................... 103

Chi-square test probabilities comparing condition of all trees on private
property in the 10 study cities, 1980 .......................................... 104

Percentage of tree population of public and private trees in condition
classes, ten selected US cities, 1980 ......................................... 105

Chi-square test probabilities comparing size of all public and private trees
in the 10 study cities, 1980 ..................................................... 107

Chi-square test probabilities comparing size of all publicly owned trees in
the 10 study cities, 1980 ......................................................... 109

Chi-square test probabilities comparing size of all privately owned trees in
the 10 study cities, 1980 ......................................................... 110

LIST OF FIGURES

Figure Title Page

Figure 1 Location of study area, Grand Junction, Mesa County, CO, USA . .21

xi

Apr-r
App»

App

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Appendix

Appendix A.

Appendix B.

Appendix C.

Appendix D.

Appendix E.

Appendix F.

Appendix G.

Appendix H.

LIST OF APPENDICES

Title Page
Grand Junction compared to 10 cities, 1980 ................................... 95

List of species found in Age Class A (0-10 years old), Grand Junction,

CO, 1980 .......................................................................... 113
List of species found in Age Class B (1 1-40 years), Grand Junction, CO,
1980 ................................................................................ 114
List of species found in Age Class C (41 years and older), Grand Junction,
CO, 1980 .......................................................................... 115
List of species found in Age Class A (0-34 years old), Grand Junction,
CO, 2004 .......................................................................... 116
List of species found in Age Class B (35-60 years), Grand Junction, CO,
2004 ................................................................................ 118
List of species found in Age Class C (61 years and older), Grand Junction,
CO, 2004 .......................................................................... 120
Urban tree attitude questionnaire, 2004 ....................................... 122

xii

 

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INTRODUCTION

As communities become increasingly urban and suburban, it is important to realize and
quantify the several values of the urban forest. An estimated 80% of the United States
population can be associated with urban or larger metropolitan areas (Nowak et al. 2001,
US Census Bureau 2000). A growing majority of those associated with a larger
metropolitan area reside in communities in close proximity to urban centers that offer a
more pastoral or natural setting often absent from urban areas (Van Wassenaer et al.
2000). The lure of outlying communities within a reasonable commute, via a modem
network of roadways, continuously drives peri-urban land development. Rapid
population growth followed by the consumption of land has a substantial effect on the
urban forest (Profus 1992), defined by Miller (1997) as the sum of woody vegetation in
and around any human settlement. Due to the sprawling pattern of modern development,
urban and community forestry is becoming increasingly important to improve overall
quality of urban life and to promote urban residency, relaxing pressure on lands valued

for agriculture and recreation (Nowak et. al 2001; Gatrell and Jensen 2003).

Though the benefits of urban trees are widely recognized, continuous development

threatens the ability of urban forests to actualize these benefits (Dwyer et. a1 1992).

 

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While trees and other vegetation in urban areas have a great potential to grow and
survive, they are constantly subjected to the changing designs of humans and their
omnipresent urge to develop and expand. Species selection, planting and care are highly
influenced by a large number of private landowners in metropolitan areas. Likewise,
professionals are charged with the care and management of urban vegetation on public
lands (Miller 1988, Harris 1992). And, unlike natural forest environments, the urban
environment has the potential to experience rapid changes that can influence urban forest
sustainability (Nowak 1993). Vegetation in the urban environment is highly influenced
by urban development history and management regimes that have occurred throughout
time (McBride and Jacobs 1976, 1986; Dwyer et al. 2000). Consequently, land use and
development history create varying quantifiable patterns of urban forest characteristics

distributed piecemeal throughout the city.

Characteristics of urban trees reflects various human activities and habitats and, though
varied on a citywide level, may be homogeneous on the smaller neighborhood level
(Grey and Deneke 1986, Miller 1997). Variations in development history and zoning
patterns throughout a city create a jumble of land use and spatial distributions not equally
amenable to tree growth (Nowak et al. 1996). Planting, management, and an
understanding of natural systems is helpful to mitigating any possible negative
implications of human development (Clark 1997). Additionally, incorporating the
values of urban constituents while educating the population on the benefits reaped

through urban forest management should be integral to the field. However, these

 

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Opinions and attitudes are rarely considered in regard to urban and community forestry

management decisions (Kielbaso 1982).

The urban forest has been defined by Clark et al (1997) and Clark and Matheny (1998) as
“the naturally occurring and planted trees in cities which are managed to provide the
inhabitants with a continuing level of economic, social, environmental, and ecological
benefits today and into the fitture Sustaining this forest requires attention to all trees in
a community regardless of ownership. It also requires a mechanism of relaying this
information and involving the public to continually support urban forestry programs.
Information from accurate and regular urban tree inventories and public perception and

attitudes surveys are also essential to urban and community forest sustainability (Dwyer

et a] 2001).

This current analysis presents a case study in some aspects of the urban forest history of
the community of Grand Junction, Colorado, USA. The objectives of the study were (1)
to determine changes in the urban forest between 1980 and 2004, including tree
condition/health, species composition, and size, and (2) to determine if trends are
influenced by whether trees are a public or privately owned resource, and by age of

neighborhood development; and (3) to identify urban residents’ attitudes towards street

trees.

More specifically, the goals of this study were to:
1. Compare and determine urban forest dynamics in Grand Junction, CO from 1980
to 2004 for the following attributes:
a. Species composition,
b. Size of tree, and
c. Condition/health of tree.
2. Compare the above mentioned characteristics of urban trees between:
a. Private property and public property, and
b. Three age classes of neighborhood development, and to identify whether
public or private management or age of development influence the urban
forest characteristics previously listed.
3. Evaluate attitudes toward urban trees in Grand Junction overall and among three
age classes of neighborhood development for:
a. attitudes regarding both positive and negative attributes of trees,
b. location preferences for future tree plantings,
c. willingness to participate in and pay for various volunteer activities and
ecological programs,
d. the maintenance of urban trees, and

e. the importance of trees in certain locations.

 

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LITERATURE REVIEW

Urban Tree Benefits: the need to evaluate and improve our forests.

Urban and community forests offer a myriad of values to residents that can be classified
as social, economic, environmental, and even spiritual or psychological (Miller 1997).
However, in comparison to related disciplines, not enough is known about this valuable
resource. Socially, urban forests provide a sense of community and identity. The simple
act of planting fosters an attachment to the surroundings and creates a sense of ownership
and pride (Driver et a1 1980). Those who plant a tree and are amongst trees often feel a
spiritual connection or link to nature, not often found in some highly urbanized locations

(Dwyer et a1 2003).

Based on the theory of defensible space, that is that the physical features of a
neighborhood impact the strength of communities and, consequently, rates of crime
(Newman 1972), Kuo (2003) analyzed whether trees and urban vegetation in general
could influence social ecology. In a comparative analysis of two Chicago housing

projects, one containing significant vegetation while the other was devoid of vegetation,

 

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it was found that outdoor settings with trees are much more preferred and play a
significant role in inviting residents outside (Kuo 2003). It was found to have higher
use rates of green outdoor spaces by both adults and children and more informal contact
among neighbors (Coley et al. 1997; Kuo et a1. 1998; Kuo 2003). Consequently, outdoor
vegetation could also have implications on social health, including disease and obesity

rates, and childhood activity levels (Talbot et al. 1987).

Previously mentioned studies have demonstrated that outdoor areas that include trees and
green cover promote an increased level of outdoor activity and open socialization. Coley
et a]. (1997) observed that because both children and adults are more socially active in
these areas, mixed interactions among groups also increases, promoting more child-adult
time. Children in greener environments have consistently higher access to adults than in
less greener spaces which can have implications on safety, crime, child development and
educational achievement (Faber Taylor et al. 1998; Jacobs 1961; Kuo 2003; Kuo 2001;

Kuo and Sullivan 1996; Taylor et al. 2001).

Urban trees also have the potential to improve environmental quality directly through
ecological services provided and indirectly through energy conservation. Ecologically,
urban trees stabilize soils, reduce runoff, sequester gaseous pollutants and particulates,
and provide wildlife habitat (Sanders 1984; DeGraaf 1985; Smith 1990; Von Stulpnagel
et al. 1990; McPherson 1991). Urban trees also ameliorate the adverse impacts of the
‘urban heat island’ through shading, evapo-transpiration, and reducing energy needs

(Akbari et al. 1992; McPherson 1993).

 

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These noted benefits also translate into economic savings for municipalities and residents
alike and can lead to a reduction in heating and cooling costs (McPherson and Dougherty
1989; McPherson 1991; Jensen et. a1 2003). Trees have been shown to increase property
values, increase consumer willingness to pay for goods, and increase the time a consumer
spends in a shopping district (Anderson and Cordell 1988; Petit et. al 1995, Wolf 2003;
Wolf 2004). Additionally, the care and maintenance of the urban forest and its benefits

contributes considerably to the economy (Templeton and Goldman 1996).

The above enumerated benefits highlight the importance of urban forest monitoring and
sound management. Ensuring that these benefits will be sustained through the course of
anthropogenic changes in time requires monitoring trends and evaluating resources and
management techniques. Urban vegetation inventories have sought to provide
environmental, biological, and physical information to aid in planning and management
(Gray and Deneke 1986, Miller 1988). Also, by understanding trends through time and
surveying trees and their characteristics, managers are better equipped for present and
future management decisions. Through the aid of a street tree inventory, managers can
assess species diversity, condition, and size structure of public trees. An example from a
southern California study that included street tree inventories from municipalities across
the region found that, among other findings, street tree diversity is decreasing slightly
(Lesser 1996). The current study will use the same tool on both public and private lands

to achieve a more thorough analysis of urban forest characteristics.

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Urban Forest Comparative Analysis

The study of urban trees is unique in that it must also consider the impacts of human
behavior on forest structure and composition. These influences also vary temporally with
development history, spatially with patterns of land use and morphologically through
intensity and design of development creating a highly heterogeneous habitat (Jim and
Liu, 2001). Diversification of land use in this manner creates patterns of suitability and
also preference for tree planting throughout the city. In both natural systems and urban

environs, a plant’s ability to survive is greatly influenced by habitat.

Though areas of natural vegetation and pre-development relics are likely to exist in most
cities, trees in the urban landscape are largely the result of human selection and design.
Trends in species popularity and insect and disease infestation, highlighted by the
afiermath of Dutch elm disease and, more recently, in some areas of the country, emerald
ash borer, are directly human associated and greatly affect urban vegetation. Because
urban trees are so closely tied to the human environment, development and land use
patterns contribute significantly to the age structure, condition, and species composition
of the urban forest (Miller 1997; Sanders 1984a; Nowak 1994). Cultural factors such as
planting policy, lot size, and the decisions of developers can influence the urban tree
landscape (Domey et al. 1984). Therefore, while the urban forest is affected by natural
factors, it can also vary considerably based on temporal trends in tree and urban design
preferences (Whitney and Adams 1980). Forested urban areas can be sorted into a

collection of smaller forest communities characterized by similar community structure

 

 

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and ecologic framework most easily accomplished through age stratification
characterized by periods of development. Such findings can improve urban forest
management by uncovering trends in forest dynamics allowing managers to better
identify management zones, and by revealing ramifications of past management

techniques (Brady et al. 1979).

Case studies in US. cities (Welch 1994; Schmid 1975, McPherson et al. 1997, McBride
and Jacobs 1976, 1986,) and in China (Jim 1989; Jim and Liu 2001) have illustrated the
effect of urban development history on urban forest dynamics and the potential to vary
urban tree management on this basis (Welch 1994). Schmid (1975) studied tree patterns
in residential areas of Chicago and found that patterns of biomass, tree placement, and
species composition varied throughout the city on both public and private property. In
general, these patterns were directly related to age of development and linked to socio-
economic class. Varying structure and characteristics can create a smaller definable
urban forest within the larger urban forest and warrant varying levels of management, a
trend similar to that found in Boston, Massachusetts (Welch 1994). Street tree
composition of Urbana, Illinois neighborhoods over a 50-year time span was analyzed
(Dawson and Khawaja 1985). Based on the information gathered, trends in species
composition were revealed and linked to management that began during the 1970’s. Not
surprisingly, the study found that though American elm (Ulmus americana) formerly
dominated the public landscape, it is today nonexistent along with some other species
such as box elder (Acer negundo) and cottonwood (Populus deltoides), considered in

modern times to be inferior. The street tree population, though plantings seemed to

decrease slightly, was becoming more diverse in comparison to the former elm
monoculture (Dawson and Khawaja 1985).

Studies in Hong Kong (Jim 1989) and in Guangzhou City (Jim and Liu 2001), China
have shown that development history and land use patterns have created urban districts
differing in tree density and species composition. Jim (1989) found that grth
conditions varied considerably throughout the five city districts he identified as

representing differing phases in the ‘life history’ of the city.

These temporal ‘phases’ in the city’s history should also be considered when analyzing
the urban forest as a whole. Using a comparative analysis to indicate overall change
through time, the ability of the urban forest to sustain its benefits can be assessed
(Costanza 1995). Through a comparative analysis, patterns that may potentially be linked
to management and development trends can offer insight into the sustainability, or the
ability to “survive or persist”, and ensure communities are better able to assess the degree
of the aforesaid benefits. Because urban forests can potentially exist with so many
factors that hinder growth, such as development, soil compaction, contaminants, reduced
growing space, and an increased amount of private land owners, analysis of trends is
imperative to an improved understanding of urban tree management (Miller 1998; USDA
1996; Nowak 1991, Nowak 1993). Though there are many factors, both social and
economic, affecting the health and sustainability of the urban forest, the vegetative
resource and its composition, age, and condition, is the basis of urban forest sustainability

and is central to the current investigation (Clark et. al 1997; Dwyer et. al 1992).

10

 

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Planning for sustainability and long-term survival and health is essential to urban forest
management and can easily be evaluated through monitoring temporal trends in urban
forest characteristics (Reeder and Gerhold 1993 ). The dynamic nature of the urban forest
influenced by both biologic (disease, soil, water availability) and artificial (trade-
introduced pests, land clearing, development) change speaks for the necessity of
comparative analysis. Though the importance of monitoring the urban and community
forest is clearly evident, very little research exists that details trends in the overall

condition of the entire urban tree populations over time (Kielbaso et a1. 1993).

Urban areas include a much larger proportion of private property as compared to public
property, and therefore private land use decisions made on the majority of urban land has
a greater influence (Elmendorf and Luloff 1999). Urbanized and suburbanized areas also
have increased numbers of stakeholders involved, each with varying objectives for their
property and varying interpretations of property rights, further increasing the mosaic

pattern of land use and habitat.

While most urban forest analysis has primarily focused on the publicly-owned
component, an estimated 60-90 % of trees in urban areas are found on private property
(Stacksteder and Gerhold 1979; Sampson et. al 1992). Because the majority of urban
trees are privately owned, sustainability and health of the urban forest as a whole depends
largely on homeowners and the degree to which they are informed on its roles/values
(Domey et al. 1984; Clark et. al 1997). By limiting the concept of the urban forest to

public lands along streets and in parks, as commonly practiced among professional urban

11

foresters, complete urban forest management and health cannot be sustained (Stacksteder
and Gerhold 1979; Dwyer et al. 2000; Kielbaso et al. 1993). As a result, the definition of
urban and community forest has grown beyond the previous notion that management and
monitoring is necessary only on public lands to include and recognize the importance of
the private landscape and private land use decisions (Dwyer et. al 2000; Elmendorf et. a1
2003; Nowak et. a1 2001). An all-inclusive inventory and monitoring of the urban forest
is essential to improve urban forest sustainability though it is scarcely practiced and may
involve increased costs to monitor and include private landholdings (Dwyer et. al 2000).
Improving survival, health, and diversity of urban forests through a complete inventory of

public and private lands will definitively have implications on urban forest sustainability.

Few studies have included the private component as a part of the total urban forest
population and are limited to only a handful of urban locales, most notably in California,
Ohio, Nebraska, and Wisconsin. In Oakland, California, both public and private trees
were assessed using historical data to recreate the history of Oakland’s urban forest
(Nowak 1993). By using aerial photographs and historic vegetation maps, Nowak was
able to include the entire urban forest without the restrictions of private property access.
Estimates of species diversity and canopy cover were obtained at various points through
time. However, though inclusive of private property, the study does not offer the
accuracy of a ground sampling (Nowak 1993). Both public and private trees were
measured throughout the City of Sacramento in urban, suburban, and rural zones
(McPherson 1998). Random plots were established in the three stratified zones. The

intent of this study was to determine the sustainability during the time of study of the

12

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whole urban forest and among the stratified areas by quantifying species diversity, age
structure (accomplished by measuring dbh), condition, and species suitability.
McPherson found that while Sacramento’s urban forest is sustainable, diversity and age
structure could be improved. Among street trees, 69% of all trees were represented by
only eight species. Similarly low diversity results were found in all three sectors among
all trees. Most trees were found to be of medium size (estimated age of 25 years) while

few large trees were noted (McPherson 1998).

An urban tree survey was completed by Kielbaso et al. (1993) in the cities of Bowling
Green, Ohio, and Lincoln, Nebraska and analyzed urban tree population trends including
the analysis of privately owned trees. By analyzing trends over a twelve year duration,
researchers were able to draw conclusions about management strategies and trends on
private lands. In the case of Bowling Green, the overall condition of the tree population
declined considerably in respect to that in Lincoln, a trend that is attributed to the fact
that Bowling Green does not proactively manage its urban forest, while Lincoln does.
The findings suggested a lack of management in Bowling Green and inferred that the
presence of a city arborist and planning and maintenance department in Lincoln

contributed to the success of Lincoln’s urban forest.

Researchers were able to assess mortality, condition, and ratios of private and public trees
and compare them to levels in 1980. The number of public trees increased over time in
Lincoln while public trees in Bowling Green decreased despite an increase in private

trees. Overall, the condition of trees in Lincoln declined despite proactive management.

13

 

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Though there were differing levels of management of urban trees when comparing both
cities, the decline in condition is attributed to climate and the fact that Lincoln has semi-
arid, prairie-like conditions, while Bowling Green is a part of the eastern deciduous forest
with a more moist and favorable growing environment. Through monitoring trends in
this manner, inadequacies, such as lack of public planting and the lack of a professional

urban forester can be highlighted.

By utilizing a complete urban tree survey, Kielbaso et al. (1993) were able to gather a
more comprehensive view of urban forest dynamics and trends over time, indicating the
importance of privately owned trees. In similar manner, Domey et al. (1984) inventoried
a Milwaukee suburb. As a result, more accurate measures of trees per hectare and
species composition were achieved while identifying the potential aftermath of Dutch

elm disease by placing importance ratings on private tree species.

Urban Forest Attitude Surveys

Though municipal tree surveys are universally regarded as a critical component of any
urban and community forestry management plan, public attitude surveys have failed to
develop as a plausible technique to determine management goals and procedures.
Surveying constituent attitudes and opinions on any public resource should be an integral
component to management of any public resource (Dwyer et al. 2000) and can be of
utmost value during times of municipal resource scarcity (Kielbaso et al. 1988, Reeder

and Gerhold 1993). They can be used to identify and prioritize areas to allocate funds

14

 

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and to evaluate the effectiveness of current management. Incorporating the community
social context with urban forest management is essential to promote a sustainable public
resource and can function as a two-way mechanism to relay information, and,
consequently, educate the public (Dwyer et al. 2003; Clark et al. 1997). Attitude surveys
can indicate to what degree the public understands the importance of trees in the
community and provide insight into any inadequacies of public tree management. This
kind of information can assist public tree managers to prioritize management objectives
and to allocate funds accordingly by targeting management challenges. Public programs
lacking constituent feedback do not completely possess the ability to evaluate, modify,
and improve management. However, despite the importance of community involvement,

most research and management decisions are made without regard to public preference

(Kielbaso 1982).

Though important, little scientific literature examines public attitudes concerning street
trees and preferences. Some studies have found trees to play a role in the visual
assessment of an area. Trees are highly valued in outdoor urban areas as they affect the
visual quality of residential and commercial streets and increase the appeal to residents
and consumers (Kaplan and Kaplan 1989; Schroeder & Cannon 1987; Wolf 2003). This
reinforces the importance of acknowledging community opinions to determine areas of

need, species desired, and educational shortcomings of the public.

Trees undoubtedly have a profound effect on human environments and are an integral

component of urban landscapes (Gangloff 1995; Dwyer et al. 2003; Dwyer et al. 1992).

15

 

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Research has shown a preference for forested environments and the wildlife it provides to
urban residents (Getz et al. 1982; Shaw et al. 1985). Shroeder and Cannon (1987) also
found that trees have a strong impact on the visual perception of streets and can influence
choice of residence and potentially assist urban renewal efforts. With the increase in
sprawling patterns of urban development, cities have extended their land area and
influence across the landscape while affecting the viability of older urban centers,
increasing the necessity for urban forests (Dwyer et. al 2003). Through survey research,
managers and planners can expose attitudes on such issues and to what degree the public

understands these issues.

Much survey research has been conducted to quantify the degree of benefit received
through public involvement in volunteer tree planting and related activities. Surveys
have found that people involved in volunteer greening projects are motivated by “deep
values” such as those spiritual in nature and to find a connection with nature (Austin
2002; Westphal 1993). Findings of Sommer et. a1 (1994) found those who participated
valued the social benefits of the urban forest and experienced feelings of empowerment
and pride in neighborhood. However, though these findings provide insight into resident

attitudes, they are not inclusive of the general public.

Surveys of the general public have had mixed results. Some find the concept of the urban
forest intangible; therefore its benefits are not well recognized (Steigler 1990; Hull 1992).
Similar to the findings of Sommer et. al (1994), Westphal (1993), and Austin (2002),

residents were able to recognize the emotional significance of trees and their aesthetic

16

 

31

 

attributes in their communities. However, residents did not fully recognize the
environmental, social, and, functional benefits of trees (Hull 1992). A mail survey in
Downers Grove, Illinois, found that while most residents were satisfied with the quantity
and care of urban trees, less than half of the respondents were aware that a municipal

forestry program existed (Schroeder and Appelt 1985).

Other surveys have suggested that the general population does value trees for a multitude
of reasons and that location is also a factor. A survey conducted by a market research
firm of 250 Detroit, Michigan residents analyzed preferences concerning urban trees.
The face-to-face survey revealed that, only second to education, residents would prefer
tax dollars to be redistributed to support parks and street trees followed by recreational
programs. Trees also ranked among the most important attributes that residents value in
area parks, indicating a high value placed on urban trees (Kielbaso and Karrow 1982).
Similarly, Allen (1995) found that Missouri residents, regardless of region, had positive
attitudes towards urban trees and were generally supportive of increased funding to

support urban tree management.

Though trees were found to be important to communities overall, Kielbaso and Karrow
(1982) also found that trees in various locations have varying values to residents.
Relative importance of trees on govemment-managed streets, open park areas, and
wooded areas were measured on a five-point scale. Respondents listed tree-lined streets
to be the most important location for government managed trees, followed by open park

areas, and wooded areas. The survey further weighted the relative importance of trees in

17

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a variety of general locations typical in cities. Again, residential streets ranked highest,
followed by city parks, and front yards. Of least importance were industrial areas and
parking lots (Getz, et al. 1982; Kielbaso and Karrow 1982). Knowledge of similar

preferences can help best effectively manage today’s urban forest.

Kalmbach and Kielbaso (1979) also found that, contrary to some current practices,
residents prefer large street trees as opposed to smaller trees when only aesthetics are
considered. Additionally, 59% of residents preferred increased street tree densities, at a
rate of one tree per urban lot, and residents generally agree that trees improve the urban

environment.

Residents of the largest metropolitan areas in the US. were sampled via telephone
interview (Lohr et al. 2004). Their findings indicate that most residents (83%), regardless
of demographics, throughout the United States value trees and rate them as a contributing
factor to quality of life. Those who did not find trees important to the quality of life in
the community were likely young (between the ages of 18-21), and/or poorly educated,
suggesting education plays a role in urban resident attitudes towards the environment and

street trees.

Residents placed a high value on the function of trees, particularly their capacity to cool
and shade downtown areas (Hull 1992; Stiegler 1990). Other reported values of trees
were calming properties and smog, dust, and noise reduction. Respondents were more

able to identify positive features of streets trees rather than annoyances and found most

18

attributes of urban trees commonly thought of as annoyances inconsequential (Lohr et al.

2004).

19

STUDY SITE

Grand Junction, Colorado, USA

History

The city of Grand Junction, Colorado was established at the confluence of the Grand
(now known as the Colorado River) and Gunnison Rivers in western Colorado, 28
miles east of the Utah border. Settlement occurred in the early 1800’s and was
prompted by the discovery of gold and silver in nearby mountains. Before its
incorporation on October 10, 1881, the site was home to the Northern Ute
Reservation. This native American tribe was later relocated to western Utah. Once
established, the town was named Ute after the native population and was later
changed to West Denver. The town was later renamed Grand Junction for its location

at the confluence of the Grand and Gunnison Rivers.

Geography and Demographics
The city is located in what is known as the Grand Valley at an elevation of 4,586 feet
(1397.8 m.) above sea level. It has a mean annual temperature of 518° F (10.55° C)

and a mean annual precipitation of 8.99 inches (22.83 cm.) and mean annual

20

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snowfall of 22.0 inches (55.88 cm.). The Grand Valley is surrounded by mesa and
mountains to the north, south, and east, most notably, the Grand Mesa, the city’s most

distinctive landscape feature. Today, the city occupies a land area of 26.47 square

miles (42.6 sq. km.).

Grand Junction serves as the largest regional hub between Denver, CO and Salt Lake
City, UT. It serves as Mesa County Seat and home of Mesa State College.
According to the 2000 US. census, the larger Grand Junction Metropolitan Statistical
Area (including the nearby suburban communities of Fruita and Palisades) has a total
population of 116,255, the fifth largest in the state of Colorado and the twelfth fastest
growing in the southwest United States. Grand Junction proper has a population of
41,986, 48.7% male and 51.3% female. The median household income is $33,152.
The majority of the population (57%) is employed by service or retail related
industry. Though there is some light industry, only 8% of the population is employed

by the manufacturing sector.

The Grand Mesa Region

Mesa County was created from existing neighboring counties in 1883 and is located
250 miles west of Denver at the Utah / Colorado border and occupies 3,309 square
miles. Seventy-two percent of Mesa County is publicly-owned, primarily by the US.
Forest Service, the Bureau of Land Management, and the State of Colorado. The
Colorado National Monument and Colorado River State Park are both within close

proximity to Grand Junction. The Grand Mesa National Forest, named after the mesa

22

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of the same name and the largest flattop mountain in the world, also neighbors the
city. Surrounded by unique landscapes, mesas, lakes, and mountains, the region has
become a tourist destination. Studies indicate that tourism accounts for 17% of all

jobs and 11% of income in Mesa County.

Because annual precipitation rates are among the lowest in the state, vegetation in the
region differs greatly from other regions. Generally speaking, pre-settlement
vegetation was characterized by scrub oak, sage, juniper, cedars, and pinyon pines
with cedars more prevalent at lower elevations. In areas of higher elevation, pockets
of aspen are also dispersed throughout the landscape mixed with some pines at the
highest elevations. Cottonwoods, honeysuckle, and buffalo berry are commonly

found along streambanks (Robbins 1910).

Due to the limited amount of rainfall, irrigation was introduced by barrels in 1894,
and in 1913 a mass irrigation system was developed by the US. Government. The
mild climate, an exceptionally long growing season of approximately 182 days (the
longest in the state), and ideal terrain, once irrigated, has perfectly suited the area for
crop production (Robbins 1910). Known locally as the “banana belt”, with the aid of
irrigation, conditions are ideal for fruit crops and have earned Grand Valley the title
of “Colorado’s wine country”. Much of the surrounding land is dedicated to crop

production and orchard fruit production (Baker 1932).

23

 

 

During the last decade, the region has experienced significant grth and
development with a growth rate among the top 10% of counties nationwide. From
1990 to 2000, Mesa County’s population grew by 24% and is projected to reach

143,591 by 2010 (an increase of nearly 23% fiom 2000).

Industry

Industry has historically played a significant role in shaping Grand Junction’s
development. Because of its location on key railroad and transportation routes, the
city began to expand quickly soon after establishment. The first industries in the area
centered on gold and silver mining. Vanadium, a soft, rare metal used to produce
certain alloys, was discovered and mined throughout the Colorado Plateau region.
Early in the 20th century, vanadium mining increased heavily as a result of wartime
demand and quickly became the community’s most lucrative business. During the
process of vanadium mining, uranium was often discarded as waste. Uranium
mining, for which no regulation was mandated at the time, later replaced vanadium in

demand due to the Cold War and efforts of the Manhattan Project (Energy 1995).

In 1950 the Climax Uranium Company entered into contract with the US. Atomic
Energy Commission and commenced development of a 200 acre uranitun mill site.
Located on the bank of the Colorado River within the city of Grand Junction, the mill
produced uranium and vanadium compounds during 1951-1970. In the duration of
operation, the mill produced 11.7 million pounds of U303 (uranium “yellowcake”)

and 46.1 million pounds of V205 (vanadium). Once decommissioned, portions of the

24

site were converted for industrial park use while other areas were ceded to the state.
Ten acres were sold as private property (US. Department of Energy 2002).

Though the site has been inactive for over 30 years, remediation has been a
continuing process. Uranium mill tailings from the Climax mill were available to the
public and were used throughout the community in the construction of private
residences, churches, commercial properties, and schools. An estimated 300,000 tons
of radioactive mill tailings were distributed to the public during the 1950s and 19605.
The widespread use of uranium mill tailings for backfill and as a sand substitute was
deemed hazardous in 1972, and remediation efforts were initiated by both state and
federal governments (U .S. Department of Energy 2002; Long-Term Surveillance and
Monitoring Program). Tons of waste tailings were excavated from four-thousand,
two hundred homes and relocated to a 40 acre temporary containment site (Miller
2002; US. Department of Energy 2002). The actual number of homes and other sites
constructed with radioactive materials is unknown. Despite a 25 year public
campaign to locate and eradicate residual uranium mine tailings, up to one million
cubic yards of tailings are estimated to still be dispersed throughout neighborhoods in
the greater Grand Junction region (U .S. Department of Energy 2002; Long-Tenn

Surveillance and Monitoring Program 1999)

Remediation of the Climax mill site did not begin until late 1988. Remaining
buildings were removed and a 98 acre disposal cell in the town of Whitewater, ten
miles southeast, was prepared to receive and consolidate contaminated materials,

tailings, and dirt (Miller 2002; US. Department of Energy 2002). The Cheney

25

disposal cell now houses radioactive mill tailings previously dispersed throughout the
city and waste removed fi'om the original Climax site. Approximately 4.4 million
cubic yards were relocated to the disposal cell. The mill site was restored with clean
backfill, a wetland was established in 1994, and the site was declared ‘clean’ by NRC

in 1997 (US. Department of Energy 2002).

Though uranium and its residues have been, and continue to be, present in unknown
amounts throughout the region, there is little documentation on their adverse effects
in the community. Accounts from mines located across the Colorado Plateau recount
stories of uranium trucks at the height of the boom recklessly transporting product to
maintain pace with demand. Uranium particulates were part of the dust liberally
added to the air from trucks, equipment, and open mines. Streams leading from
mines moved these sediments across the region. Those employed and, through
exposure from construction materials, those not employed by uranium mines were
exposed to constant radiation. Sheep and cattle herds were lost due to defective
births and children and families played adjacent to mines and buildings constructed
with low-grade mine waste (Navajo 1997). Career uranium mine workers have
developed otherwise inexplicable forms of respiratory problems (Mulloy et. al 2001).
Though these tails are abundant throughout the region, there is little research
available linking the uranium mine industry with adverse human or biotic life effects
(Geiger et. a1 1992), with the exception of radon and gamma radiation exposure
(Uranium 2000). This is due in part to government encouraged secrecy of uranium

mining related to Cold War efforts (Easthouse 1996; Brocious 1993). While the

26

effects of mining in the area are yet to be quantified, little evidence exists to suggest

any adverse effects on local vegetation.

Other than the documented effects of radon and gamma radiation, there is no link to
the adverse effects of the mining industry’s presence in Grand Junction, though there
is evidence of environmental degradation. Yearly sampling of test wells revealed
water levels with excess amounts of molybdenum, uraniunr, and alpha radiation that

has slowly infiltrated to the Colorado River (US. Department of Energy 2002).

Following the uranium boom, the area experienced another period of growth from
development of oil shale found on the western slope. Grand Junction began to
develop rapidly and focused economic interests in the oil business. This eventually
subsided and left many in the area economically depressed. The city has since
diversified its economy and plays a key role in regional trade, services, transportation,
health care, and education. Because of its prime location, adjacent to Interstate 70
and nearly midpoint between Denver and Salt Lake City, Grand Junction has become
an important regional distribution and service center. Regional airport and train

facilities have also played a role in Grand Junction’s service-based growth.

Despite economic growth, over 52% of the city’s jobs are concentrated in
traditionally lower-paying sectors, such as retail and services. Additionally, the
population growth has far exceeded the growth of available affordable housing.

Housing costs have increased as much as 207% while wages have increased just

27

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46.3% over a duration of just ten years. However, developers have continued to cater

to the wealthy by concentrating on more expensive homes.

Development and Urban Planning

Boom and bust growth cycles spurred by the previously mentioned industries have
shaped growth patterns throughout Grand Junction and the greater Grand Mesa
region. Periodic cycles of growth resulting from booms in industry encouraged
haphazard development. Many subdivisions were poorly planned without regard for
future costs and without regard to long-term sustainability (City of Grand Junction,
2003). Utilities and roadways were extended and established to create a pattern of
sprawling development and a financial burden (City of Grand Junction, 2003). In
these boom periods, high demand for housing led to relaxed development standards
that are now evident in some of the city’s oldest and most economically depressed
areas (City of Grand Junction, 2003). Outlying agricultural lands and open space that
have historically lured residents to the area have quickly diminished, converting
farmland and orchards to crammed subdivisions often devoid of urban trees (City of

Grand Junction, 2003).

The cyclic pattern of growth in the city has created a town plan that was influenced
by the land use designs popularized during several eras. Urban planning and design
standards and trends have varied considerably with time and have created land use
patterns of various designs and frequencies. The. current period of rapid growth

centered on automobile convenience has imprinted a large pattern of cul-de-sac style

28

and large commercial areas of ‘big box’ developments with a high level of
impervious surfaces that are inhospitable to tree growth (City of Grand Junction,

2003; Nowak et al. 1996).

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MATERIALS AND METHODS

Background

Urban forest data were collected by the United States Forest Service to determine trunk
size, species composition, and tree condition, and other variables related to trees and land
use in ten cities throughout the United States during 1979-1980. The cities included (in
alphabetical order): Bowling Green, Ohio; Bucyrus, Ohio; Charlottesville, Virginia;
Delaware, Ohio; Grand Junction, Colorado; Hutchinson, Minnesota; Jamestown, New
York; Lincoln, Nebraska; West Springfield, Massachusetts; and Wooster, Ohio. These
data were originally intended to identify the effects of Dutch elm disease (Ophiostoma
ulmi) in communities representing various ecological units and subunits across the US

(Kielbaso 2002) as described by Bailey et al. (1994) and McNab et al. (1994).

The study collected data on both public and private property and delineated three separate
age classifications of development within each city. These baseline data were unique in
that components of the urban forest, both under public and private ownership, are
analyzed. Because both components are inventoried in each locale, the data offer a more

complete portrayal of the urban forest than previously studied, providing a unique

30

vantage into each city’s urban forest during those years sampled. Due to its unique
nature, the data originally collected from all ten cities was analyzed, and a summary of

results can be found in Appendix A.

While the sampling of cities during 1979 and 1980 offers only one perspective dated 25
years, data from these years offer a unique opportunity to investigate trends over the
duration. The city of Grand Junction, CO was selected as the primary research city
because of its unique development history to investigate trends in the urban forest
composition among three characteristics of sustainability: size, condition, and species
diversity. These variables were studied on both public and private property and within
neighborhoods of delineated age classifications to consider the patterns and effects of

development on the aforementioned characteristics (McPherson 1998).

1980

Study Design

Each selected city was stratified by the United States Forest Service researchers in the
original study from 1980 into three age classes of development representing age of
construction: Class A (0-10 years), Class B (1 1-40 years), and Class C (40+ years).
Stratification by age of development assumed that residential areas of similar age would
reflect similar forest composition and results could be extrapolated by age of
development (Whitney and Adams 1980). Whitney and Adams (1980) also found that

the forest complex of developments constructed post World War II differ from those

31

 

constructed before and from those constructed some time following the war. A third
variance was noted in developments constructed some time since WWII that emphasized
the ‘American myth’ of mral life, commonly regarded as suburban flight (Whitney and

Adams 1980)

These classifications were used to delineate age class stratification. Three replicates (one
replicate was considered one city block) were established in each stratum for a total of
nine study blocks, recommended to achieve accurate data collection with minimal time
input (Kielbaso et al. 1993). Experimental design in all ten cities was stratified in the

same manner, described in more detail in 2004 (pg. 33).

Data were recorded for all trees on each block noting the location of each as on either
public or private property. Information was also manually recorded on the property and
individual tree details including: maintenance, lot dimensions, species, trunk diameter,

tree height, crown diameter, percentage of crown exposed to sunlight, and tree condition.

Species Diversity

Trees were identified to genus and species for each tree recorded. Because access was
limited on many private properties, accurate identification was more difficult. Some trees
are identified only to genus, including all elms (Ulmus) and ash (Fraxinus). General
identification of ash and elm species, now threatened by disease and/or insects, and
consequently of low future interest, does not affect diversity measures as it was employed

in all circumstances and indices will all be affected accordingly (Domey et al. 1984).

32

Unidentifiable species were listed as unknown. In some circumstances, enough

information was available to identify to genus (for example, Acer, or maple, rather than

unknown).

Tree Condition

Rating tree condition across a gradient of degrees is commonly done in studies that
include private property (McPherson 1998). Because tree condition is often a subjective
rating and can overlook some symptoms of poor health and condition, a system that
assessed the trunk, crown, and root components of individual trees was developed by
researchers for the original 1980 study. This method focused on diagnostic signs in order
to assign a condition classification (Table 1) and allowed for an efficient yet reliable
method that was easily mastered by novices (Kielbaso et al. 1993). Table 2 was used to
determine a condition rating based on the number of condition compromising signs

present.

Table 1. Guide for assessing condition rating of inventory trees, Grand Junction, CO.

 

 

 

 

 

 

 

Crown Main stem/branches Base and Roots

Size Signs of decay or wounds Decay

Girdling roots or absence of
Color of foliage Broken main branches trunk flare

Roots severed over 25%
Density of foliage Signs of improper pruning circumference
Shoot size after Damaged roots showing scars,

runing Bark overgrowths over 25% circumference

Dead branches and 75% root area covered with
twigs Dark streaks in bark impervious material

 

 

 

33

 

Table 2. Chart for determining condition rating of trees inventoried in Grand Junction,
CO.
Condition Condition 8'

0 - 1 Excellent
2 Good

3-4 Far
5 Poor
lDead

 

Tree size
Because of the access limitations of some private property, tree size was recorded as a

categorical value. Table three lists the diameter classes used to denote size.

Table 3. Size classifications of trees measured, Grand Junction, CO.

 

 

 

 

 

 

 

 

 

 

Size Class DBH (inches) Category
1 < 4 Sapling
2 4-10 Small tree
3 1 1-16 Medium tree
4 > 16 Large tree
2004
Study Design

The city of Grand Junction was stratified into three age classes of neighborhood just as it
was in 1980.. As 24 years had passed since initiation, Age Class A, which originally
included only ten years, was expanded to accommodate newer developments. Though it
was not composed of developments within an identical duration in both 1980 and 2004,
Age Class A represents ‘newest’ developments with common development patterns

created under similar conditions in both study years. Age stratifications were intended to

34

classify urban developments among ‘newest’, ‘middle-aged’, and ‘oldest’ for one point in
time and also represent trends in urban design. As the original delineation for ‘new’
developments spanned only 10 years, including the most recent 24 years distributes age
classifications more evenly throughout the development history of Grand Junction.
Additionally, urban planning and grth patterns were not considered to have changed
considerably from the 1980 study, in which Age Class A included neighborhoods
developed in 1970-1979, to that included in 2004. Age classes of stratification are given

in Table 4.

Table 4. Age class stratification of neighborhood developments in Grand Junction, CO.

 

 

 

 

 

Age Class Age in 1980 (yrs) Age in 2004 (as) .
A 0-10 0-34
B 11-40 35-64
C 41 + 65 +

 

 

 

 

 

For this analysis, five plots were randomly selected for inventory in each strata for a total
of 15 blocks overall. Selection was independent of the original sample blocks as those
studied in 1980 could not be located based on the information available. Data were

collected on species, tree ownership, trunk size, and tree condition.

Species Diversity, Condition, and Tree Size

Species diversity and condition were assessed in a manner identical to that done in 1980.
Size of trees was measured as diameter at breast height (dbh - 4.5 feet above ground).
Because trunk diameter can be used as an estimate of height and crown diameter, and is

the standard measurement for most urban forest management, it was the only size

35

measurement considered (Kielbaso et al. 1993). In most instances, additional size
measurements of crown spread and tree height were limited due to lack of access on
private property. Because access to private property was inconsistent, dependent on
whether a resident was present and granted access, exact diameter measurements were

not used. Instead, diameters were classified into four size categories listed in Table 5.

Table 5. Size class delineations for trees on public and private property, Grand Junction,
CO, 1980-2004.

 

 

 

 

 

 

 

 

 

Size Class Diameter Category
1 < 4 Sapling
2 4-10 Small tree
3 11-16 Medium tree
4 > 16 Large tree

 

Survey of Resident Attitudes
Attitudes of residents towards urban trees were also studied. Residents in all three
residential age classes whose neighborhoods were inventoried for the 2004 sampling

received a survey.

Questionnaire

Because each neighborhood block and, consequently, each age classification varied in the
number of households, data were presented proportionally. The survey used was
developed by De Araujo (1994) after review of similar surveys and methodologies to
determine attitudes towards urban trees in Curitiba, Parana, Brazil and modified for this

study. Most questions were closed format, asking for only a yes/no/maybe response,

36

order ranking, or a check mark. Though a few questions were open-ended, the survey

overall required very little written response. The survey can be found in Appendix H.

Residents were asked to evaluate neighborhood trees, defined as those growing within a
one to two block radius from their house, business, apartment, etc. They were asked to
rate the degree of benefit they received relating to 14 possible positive features. Fourteen
possible annoyances commonly reported for street trees were also rated. Responses were
limited to: no benefit / annoyance (1), slight benefit / annoyance (2), some benefit /
annoyance (3), great benefit / annoyance (4), very great benefit / annoyance (5). The
importance of trees in seven possible locations throughout the city, including, city parks,
downtown shopping areas, residential streets, backyards, etc, was rated in the same
manner; very important (I), greatly important (2), somewhat important (3), slightly

important (4), or not important (5).

The survey also asked general questions about trees throughout the city. Residents were
asked to rate the overall condition of street trees, the size of street trees, the pruning of
street trees, and the maintenance of street trees with a multiple choice scale ranging from

excellent (1), very good/well (2), good/well (3), poor (4), very poor (5).

Additionally, the survey probed resident willingness to pay or participate in several
ecologically related activities/programs. Residents responded yes, no, or maybe and
whether they would be willing to pay to enhance city services, such as parks, recreational

programs, street trees, and environmental education. They were also questioned

37

regarding their willingness to participate in ecological related activities, such as Arbor
Day celebrations, environmental education, and volunteer service. Participants were also
provided a list of general potential planting locations throughout the city and asked to
prioritize them by area most in need of tree planting. They were also asked if more trees

should be planted in Grand Junction.

A list of general statements was given and recipients were asked to rate to what degree
they concurred. A gradient scale of strongly agree (1) to strongly disagree (5) was used.
Statements generally related to the quality of life and urban planning of the city and
included: ‘The city is a model of urban planning’, ‘Trees contribute to the quality of life
in the city’, ‘My neighborhood is well-planned’, ‘The city is ecologically conscious’. A

complete survey is provided in Appendix G as well as copies of postcard mailings.

Lastly, demographic information regarding gender, age, level of education, household
income, home ownership, and length of time at residence was included in the survey.

The survey indicated this information would be used for statistical purposes only.

Survey Procedure

During data collection in 2004, residents and businesses on the same randomly-selected
blocks were left with notification that a survey would be mailed to them asking their
opinion on trees in Grand Junction. Notices were either given directly to residents or left
on porches for those who were not home. One week prior to mailing the survey, a

postcard was sent to each address, as one year had passed since initial notification. The

38

survey was mailed in October of 2005 and included an addressed and stamped rettu'n
envelope, the survey, and a one-page cover letter including a brief summary of the
research and its importance. Surveys were printed double-sided on two sheets of white
8.5 x l 1-inch paper, stapled, and letter-folded. Because a city-provided resident listing of
homeowners in sampled neighborhood blocks only supplied the names of actual owners,
not potential renters and others living at the address, survey recipients were simply
addressed as “resident”. Similar surveys did not find this to have an effect on return rate

(Sommer et al. 1989).

To ensure the best possible return rate, a record of surveys returned was kept using a
system of coding on the stamped return envelopes. Each recipient address was provided
with an addressed return envelope coded to identify the return address. A second
reminder postcard preceded the surveys and was mailed to addresses that had not yet
responded. Addresses that did not reply to the initial survey received an identical second
survey four weeks following the first mailing. An additional four weeks was allowed, a

total duration of eight weeks, for return of respondent surveys.

Data analysis

Analyses were completed for data sets in both 1980 and 2004 within the city of Grand
Junction to determine whether neighborhood age or tree ownership had influenced the
characteristics of interest at those points in time. For both years, comparisons were
drawn within the sample year for tree characteristics between public and private

ownership and between age class of neighborhood to identify statistical differences based

39

on ownership or age of development. Overall analysis of each measured characteristic
was completed for 1980 and 2004 to identify trends over the 24 year time period. As the
survey was not included in the 1980 study, analysis of urban tree attitudes was done only

in 2004 and compared attitudes of residents among the three identified age classes of

neighborhood.

Using the 1980 sampling, including all other sampled cities, analysis was completed to
determine if Grand Junction was similar to other cities sampled in regard to species
diversity, tree size, and tree health among public and privately owned trees and among
neighborhoods of varying age. Data was analyzed using JMP IN version 5.1 statistical

package from SAS software using non-parametric statistical tests.

Species Diversity

Because access limited accurate species identification on many private lots, some species
were identified to genus. For example, although many trees were identified as white ash
or green ash, there were a number of trees that, due to limited access, were identified

simply as ‘Ash spp’. For this reason, both green ash and white ash were categorized as

‘ash’. Species diversity was calculated using Shannon’s Diversity Index (H) as given
below:
3
H=jzpi10g Pi

F1

40

where p; equals the proportion of the total number of specimens (i) expressed as a
proportion of the total number of species for all species present. The product of Pi and

log pi for each species is summed and multiplied by negative one to create a positive

value.

Because the Shannon index is relative, it is used only on a comparative basis. Statistical
analysis was performed on these values using the Tukey-Krarner HSD test, or honestly
significant difference for multiple variables and a Student T-test for those variables with

only two.

Size and Condition
As tree size and condition variables of both public and private trees are categorical
response variables, they were analyzed using fi‘equency tables and performing a Pearson

chi-square analysis using the formula presented below:

where O is the observed frequency for the variable and E is equivalent to the expected

frequency of each variable under the assumption of independence.

41

Survey Response

Although the questionnaire used was a slightly modified version of that used by De
Aruajo (1994) to assess resident attitudes in Curitiba, analysis of only selected questions
is presented. Some questions that were questionably appropriate for the study have been
omitted because of their relativity to the study. While important to the study in Curitiba,
this study focused more on physical features of the urban forest rather than centering
entirely on resident attitudes. Additionally, some questions received such a poor
response rate that they could not be analyzed. Questions analyzed included questions 1,

3, 5, 6, 7, 8, 9, and 14 are listed in Table 6.

Table 6. List of survey questions included in 2004, Grand Junction, CO.

 

 

 

 

 

 

 

 

 

 

 

 

Question
# Relevant content
1 Positive benefits of street trees
3 Negative features of street trees
5 Overall opinion of street trees in neighborhood
6 Size of street trees in neighborhood
7 Pruning of street trees in neigborhood
8 Rating of city tree maintenance
9 Should more trees be planted?
14 Demographic information

 

Survey questions were not statistically analyzed for significance as the small sample rate
did not permit reliable results (Kuehl 2000). Instead, analysis of the questions listed in
Table 6 was limited to response percentages and mean ratings. While this does not
provide definitive statistical results that can determine significant differences in attitudes

among neighborhood, it may give useful information on trends in each neighborhood.

42

RESULTS

Analysis within the City of Grand Junction, 1980

Species Diversity

Overall analysis of species diversity, including both public and private properties, within
the three age classifications of neighborhood finds no difference exists with age of
neighborhood in 1980. Table 7 presents the mean species diversity and standard error in
each age class as well as on public and private property in each age class. No differences
in diversity were found between private properties in the varying neighborhood classes.
Similarly, diversity on public property was similar in all age classes. A list of the most

common species found in each age class is given in Table 8.

Table 7. Mean species diversity indices and standard errors of public and private forest
component, Grand Junction, CO, 1980.

 

 

 

 

 

 

 

 

 

 

 

 

1980
Neighborhood Overall Public Private
ageclass 11 Rio n its n Kit:
A (0-10 yrs.) 6 1.64 i 0.463 3 0.67 i 0.378 * 3 2.61 i 0.069 *
B (11-40 yrs.) 6 1.72 :t: 0.429 3 0.78 i 0.161 * 3 2.65 i 0.149 *
C (41+ yrs.) 6 1.89 :t 0.257 3 1.33 i 0.085 * 3 2.46 i 0.053 *
All 18 1.75 3: 0.215 9 0.93 i 0.154 * 9 2.57 i 0.058 *

 

 

 

 

* Statistically significant between public and private property (p = 0.05).

43

 

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44

Though diversity did not differ among age classes of development, differences in species
diversity were found between private and public forests in all age classes. In the most
recent developments, Age Class A, mean public species diversity (0.67) was far lower
than that of its privately managed counterpart (2.61). Mean diversity in Age Class B and
Age Class C was also significantly lower (0.78, 1.33, respectively) on public property
than on private (2.65, 2.57, respectively) property. Overall diversity of public property,
inclusive of all neighborhoods, (mean = 0.93) was also significantly lower than that on

private property (mean = 2.57).

Tree Size

Size of urban trees was measured throughout the city in neighborhoods of varying age
(areas 0-10 years old, 11-34 years old and 35+ years old) on both public and private
property and analyzed using a chi-square test on the frequency of occurrence in each age
class and on public or private property. Chi-square values as well as percentages of the

sample population are presented in Table 9.

Chi-square analysis indicated that an overwhelming majority of trees (90%) found in the
youngest neighborhoods were saplings, identified as trees under 4 inches in diameter.
While 59% of all saplings were present in the newest developments, only 15% and 26%
of total saplings were in the oldest and middle-aged neighborhoods, respectively.
Because of the high frequency of saplings in the most recent developments, and
consequent low frequency in oldest developments, both were found to be highly

significant.

45

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46

Because a significantly higher frequency (90%) of trees in neighborhoods developed
within 0-10 years of the original sample were found to be saplings, the frequency of trees
in all other size classifications was found to be significantly lower. Small trees, those
with a diameter of 4-10 inches, comprised only 9%, compared to 23% and 29% in Age
Class B and C, respectively, of trees while medium-sized trees composed only 1%
compared to 20% and 17% in Age Classes B and C, respectively. Not surprisingly, large
trees, those with a diameter of over 16 inches, made up less than 1% of trees in these

neighborhoods.

Though the urban forest in neighborhoods that were developed between 11 and 40 years
(Age Class B) from the sample period had a more even distribution of tree size compared
to newer developments, a significantly higher frequency, 55% compared to 4% in Age
Class A and 42% in Age Class C, of all medium-sized trees (1 l-16 inches in diameter)

was found.

Within neighborhoods over 41 years in age, tree size was fairly evenly distributed. Table
9 shows that 29% of trees in these neighborhoods were saplings, 29% small trees, 17%
medium trees, and 26% large trees. While there are no significant differences in the
frequency distribution of size classes throughout the neighborhood, differences do exist
when compared to younger neighborhoods. For example, only 15% (highly significant at
the 0.005 level) of all saplings found in the 1980 sampling were located in the oldest
neighborhoods. Similarly, 62% (highly significant at the 0.005 level) of trees over 16
inches in diameter were found in these neighborhoods. Table 10 presents chi-square

analysis of difference in size of trees between public and private property, inclusive of all

47

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48

neighborhoods. Again, frequency of saplings (trees under 4 inches dbh) was found to be
significant with the majority, 94% of all saplings, found on privately owned lands while
only 6% were located on publicly managed lands. Additionally, saplings comprised the

smallest percentage of trees on public property, only 19% of public forest composition.

Frequency of medium-sized trees (1 1-16 inches in diameter) was found to be significant
on both public and private property (Table 10). Medium-sized trees were significantly
lower on private property, only 7% of all trees on private land. The opposite was found
for public land with medium trees accounting for the majority, 35% of public forest
composition. Frequency of the largest trees, those with a diameter of over 16 inches, was
also found to be highly significant on public lands. Only thirty-four percent of all trees

this size was reported on public lands in comparison to sixty-six percent on private

property.

Tree Condition

Overall analysis comparing condition of trees between neighborhoods (Table 11) yielded
little difference, with the only significant difference found in the youngest
neighborhoods. Seventy-seven percent of all trees in Age Class A were identified as
being in excellent condition, significantly higher than that found in all other condition
classes. While a significantly higher proportion of trees were found in excellent
condition, only 2% of trees in Age Class A were observed in poor condition. Those trees

constituted only 7% of all trees in poor condition, most being found in Age Classes B

49

(47%) and C (45%). No differences were noted in the condition analysis of tree

frequency in both Age Classes B and C.

Frequency of tree condition on public and private property in 1980 is reported in Table
12. Of all trees recorded in excellent condition throughout the city, only 10% were
publicly-owned with the majority (90%) found on private property. Additionally, a high
percentage of public trees, 27%, were assessed in poor condition. Of trees publicly
managed, only 32% were found in excellent condition and 21% in good condition
compared to 62% of private trees in excellent and 16% in good condition. A higher
frequency of public trees was also found to be in poor health or dead. Twenty-seven
percent of public trees were in poor health compared to 8% of private trees and 6% of
public trees were dead compared to only 3% of private trees. While this does not present
a positive image of city management of public trees, it should be noted that only 6% of
public trees were dead and a combined total of 53% of trees were in good or fair

condition.

50

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52

Analysis within the City of Grand Junction, 2004

Species Diversity

Similar to that found in 1980, species diversity is significantly higher for the privately-
owned component (2.29 i 0.127) of the urban forest in comparison to the public
component (0.45 :b 0.188, Table 13). However, unlike that found in 1980, the diversity is
significantly higher on private land in Age Classes A and B but not in Age Class C where
no difference was found between private diversity (1.87 :I: 0.208) and public diversity
(1.24 i 0.348). However, public diversity, though low, in Age Class C is statistically
higher than that found in both Age Classes A (0.10 i 0.100) and B (0.00 i 0.000). Private
diversity also differs among the three age classes of development. While diversity did
not differ between Age Class A (2.44 :I: 0.206) and C ( 1.87 i 0.208), C was significantly
lower than that in Age Class B (2.58 d: 0.107). The most common species in each age

class are given in Table 14.

Table 13. Mean species diversity indices and standard errors for all sample areas in
Grand Junction, CO, 2004.

 

 

 

 

 

 

 

 

 

 

Shannon Index
Overall Public Private
Age of # of # of # of
neighborhood blocks i i 0 blocks i i 0 blocks i i: o
a a
A: 0- 34 years 10 1.27 :t 0.404 5 0- 10 i 0.100 5 2-44 i 0.206
a a
B: 35 - 64 years 10 1.29 i 0.433 5 0-00 i 0.000 5 2-53 i 0107
b c
C: 65 + years 10 1.56 i 0.218 5 1.24 d: 0.348 5 1.87 i: 0.208
a a
All 30 1.37 i 0.204 15 0.45 :t: 0.188 15 2.29 :t 0.127

 

 

 

 

 

 

p= 0.05

a Statistically significant between public and private property.

b Statistically significant from all age classes of development within public property.
c Statistically significant from developments 35-64 years only within private property.

53

 

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54

Species composition (Table 14) appears to be similar in both Age Classes A and B, with
four out of five of the same species present in both groups. Though Age Class C has
some species in common with that found in the younger age classes, it appears to be

composed primarily of pioneer or weed species, such as ailanthus and Siberian elm.

Tree Size

Size of trees recorded in all three age classifications of neighborhood is presented in
Table 15 showing comparisons among neighborhoods and also within neighborhoods,
which yielded no significant differences. The forest population in each size class appears
to be evenly distributed in each age class of neighborhood. Each size category also

appears to have even representation throughout the age classes.

Size analysis was also performed based on ownership of property; either publicly
managed or privately owned, and is presented in Table 16. While no significant
differences were discovered when analyzed by age class, differences were apparent when
analyzed by ownership of trees. The majority of saplings, 96%, were found on privately
owned lands, leaving only 4% of all saplings under public management, which was found
to be highly significant. The percentage of large trees on public property, 35% of all
public trees, was also highly significant compared to only 13% of trees on private
property. The proportion of medium trees on public property was also significantly
higher, representing 28% of the public tree population, than that found on private

property, only 16% of the private tree population.

55

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56

Tree Condition

Condition of trees did not appear to vary greatly with age of neighborhood (Table 17).
With the exception of the newest neighborhoods, Age Class A, no significant differences
were found. Much like that found in the 1980 sample, the majority, 82%, of trees in
these neighborhoods were assessed to be in excellent condition compared to 51% and
62% in Age Classes B and C, respectively. Frequency of trees in all other condition

classes does not differ significantly.

More differences were noted in comparing public tree condition versus private tree
condition, with poor and dead condition categories having no significant differences
(Table 18). Public lands were found to have fewer trees in excellent condition, 28% of
all publicly managed trees compared to 67% of all private trees, but more trees in good
and fair condition categories. The majority, 96%, of all trees in excellent health were
found on private lands. Forty-five percent of the public tree population was listed in
good health compared to only 20% of private trees. Also significant, yet not as highly
significant as good and excellent trees, are public trees in fair condition with 19% of
public trees compared to only 8% of private trees. While a larger percentage of the
public tree population was found in poor condition, 7% compared to 2% of the private

forest component, this was not found to be significant.

57

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60

Comparative Analysis within the City of Grand Junction, 1980-2004

Species diversity

While no differences were noted among the overall species diversity of the entire urban
tree population in Grand Junction between 1980 (1.75 d: 0.215) and 2004 (1.37 i 0.204),
differences were found among public and private property and age classes of

development (Table 19); nor was there change in overall diversity in all age classes.

Overall diversity of public street trees, inclusive of all age classes, was found to be
significantly higher in 1980 (0.93 i 0.154) than in 2004 (0.45 i 0.188, Table 19).
Diversity decreased significantly in all age classes except in Age Class C where diversity
only decreased from 1.33 (:1: 0.085) to 1.24 (i 0.348) from 1980 to 2004, respectively.
Diversity in Age Class A decreased from an average diversity index of 0.67 (:1: 0.378) to
0.10 (i 0.100) in 2004. Neighborhoods in Age Class B saw the highest decline
decreasing from 0.78 (:t 0.161) in 1980 to no trees in the sample area, hence no diversity

(0.00 i 0.000), in 2004.

Less change in species diversity was observed on private property (Table 19). Though
overall private tree diversity decreased, the change was not statistically significant as was
the case in both A and B class neighborhoods. However, neighborhoods in Age Class C
saw a significant decrease in diversity from 2.46 (:t 0.053) in 1980 to 1.87 (i 0.208) in

2004.

61

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62

 

Tree Size

Chi-square analysis of public and private trees comparing size from 1980 to 2004 found
the most variation occurred in private trees (Table 20). The percentage of saplings (under
four inches diameter) was highly significant as it fell from 64% of the total private tree
population to 36% in 2004. Small trees, those four to ten inches in diameter, increased
significantly from 19% in 1980 to 36% of the total private tree population in 2004. Trees
11 - 16 inches in diameter also rose significantly from 7% in 1980 to 16% in 2004. No

significant difference in the frequency of large trees was found on private property.

Though some change occurred among the frequency of size classes on public property,
none were found to be significant. The largest change was found in large trees, those

over 16 inches in diameter, which rose from 25% in 1980 to 35% in 2004.

Table 21 presents the chi-square values of frequency of trees in each size category in
each age class of neighborhood, inclusive of all public and private trees. Comparing the
sample years of 1980 and 2004, the most differences are noted in Age Class A. In 1980,
90% of all trees in Age Class A were saplings (> 4 in. diameter) compared to 32% in
2004. Because the majority of trees recorded in 1980 were in the smallest category, very
few trees were found in larger sizes, and as the frequency of trees in each of those larger
categories has increased, they were all found to be significantly higher than in 1980.
Trees measuring four to ten inches in diameter accounted for only 9% of the population
in Age Class A in 1980 whereas they were the majority of trees in this age class in 2004

(43% of trees). The populations of trees 11-16 inches in diameter and over 16 inches in

63

Table 20. Chi-square test probabilities comparing size of trees on public and private

property from 1980-2004, Grand Junction, CO.

 

Privately-owned trees

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

<4in. 4-10in. 11-l6in. >l6in.
n chi-square n chi-scyare n chi-square n chi-square
1980 478 50.74 *** 143 27.86 *** 54 17.67 *** 75 1.89
% tree pop.“ 64% l9°/o 7% 10%
2004 450 30.11 "* 452 16.53 *** 201 10.48 "‘ 161 1.12
% tree pop. " 36% 36% 16% 13%
DF= 3 A % of tree population durinj sample year
Publicly-managed trees
<4in. 4-10in. ll-l6in. >l6in.
n chi—square n chi-square n chi-square n chi-square
1980 30 0.39 33 0.01 54 0.39 38 1.09
% tree pop.A 19% 21% 35% 25%
2004 17 0.51 26 0.02 33 0.52 41 1.45
% tree pop.A 15% 22% 28% 35%
DF= 3 " % of tree population during sample year

* significant at the .05 level
** significant at the .01 level
*" significant at the .005 level

diameter also rose significantly from 1980-2004. In 1980, only 1% and 0%, respectively,
of the population in these age groups which increased to 14% and 11% giving the

population a more even size dispersal.

Fewer changes were noted in Age Classes B and C. In middle-aged neighborhoods, the
only significant difference identified was the frequency of trees under four inches in
diameter, which decreased from 44% in 1980 to 26% in 2004. Other size classes
increased slightly, creating a more even size distribution in the recent sample year. While
saplings (trees under 4 inches diameter) decreased in Age Class B, their fi'equency grew,
but not significantly, in Class C, rising from 29% to 40%. Trees sized 4-10 inches also

increased (29% to 31%) though it was not significant. The only size class of trees in Age

64

Class C to change significantly were the largest trees, those over 16 inches in diameter,

which fell from 26% of the population to 13%.

Table 21. Chi-square test probabilities comparing size of trees in neighborhoods of

varying age from 1980-2004, Grand Junction, CO.

 

Age Class A: 0-34 years

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

<4in. 4-10in. ll-16in. >16in.
n chi-square n chi-square n chi-square n chi-square
1980 298 47.31 *** 29 38.18 *" 4 18.31 "* 1 17.32 ***
% tree pop.A 90% 9% 1% 0%
2004 108 46.20 *""‘ 146 37.29 "* 48 17.88 *** 38 16.91 "*
% tree pop.A 32% 43% 14% 1 1%
DF= 3
Age Class B: 35-64 ears
<4in. 4-10in. 11-16in. >16in.
n chi-square n chi-square n chi-square n chi-square
1980 132 9.26 " 69 4.12 59 0.04 42 1.97
% tree pop.A 44% 23% 20% 14%
2004 1 1 1 6.63 142 2.94 86 0.03 83 1.41
% tree pop.A 26% 34% 20% 20%
DF= 3
Age Class C: 65 + years
<4in. 4-10in. 11-l6in. >16in.
n chi-square n chi-square n chi-square n chi-square
1980 78 4.56 78 0.16 45 0.02 70 12.55 **
% tree pop.A 29% 29% 17% 26%
2004 248 1.99 190 0.07 100 0.01 81 5.49
% treyop.“ 40% 31% 16% 13%
DF= 3 7
* p = 0.05
" p = 0.01 level

*t*

p = 0.005 level

A = % of tree population during sample year.

65

 

 

 

Tree Condition
Condition of trees was compared between the sample years for those trees found on
public and private property (Table 22) and also for trees in each age class of development

(Table 23).

Among trees on private property, the frequency of trees in excellent and good condition
in these populations increased from 1980 to 2004, though not significantly. The only
significant change was found in the frequency of private trees in poor condition which

decreased from 8% to 2% of the population.

No significant changes in the condition of public trees were found. The public tree
population experienced a decrease in the frequency of trees in excellent condition during
the sample years though it was not statistically significant. The percentages of trees in
good and fair conditions did increase from 21% in 1980 to 45% in 2004 and 13% in 1980

to 19% in 2004, respectively, though this was also not found to be significant.

No significant differences occurred in the condition of trees in Age Class A between
1980 through 2004 though some were observed in Age Classes B and C (Table 23).
Although the percentage of the urban tree population reported in excellent and good
conditions in Age Class B increased over this time span, they were not found to be
significant. The only significant difference was observed in the percentage of trees found

in poor condition, which decreased from 16% in 1980 to 4% in 2004.

66

The same trend was found in Age Class C with percentages of the tree population in
excellent and good conditions increasing, though not significantly. The percentage of the
tree population found in poor condition decreased significantly from 17% in 1980 to 3%
in 2004. A significant difference was also found in the percentage of trees in fair

condition, which decreased from 20% in 1980 to 9% in 2004.

67

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69

Residents ’ Attitude Survey, Grand Junction, 2004

Response rate and demographic characteristics

Though the sample size of residents surveyed in Grand Junction was small and limited to
the neighborhood blocks inventoried, the response rate was good overall, especially in
Age Classes A and C (Table 24). Overall, 43.75% or surveys mailed were returned.
Within the neighborhoods, the highest return rate was observed in Age Class A (57.14%)
while Age Class B had the lowest rate (33.96%). Of the responses received, 34.29%
were from residents in Age Class A and 40% were from Age Class C. The least
responses were received from residents in Age Class B which made up only 25.71% of

the surveys received.

Table 24. Survey response rate in selected age classes of neighborhood throughout
Grand Junction, CO, 2004.

 

 

 

 

 

 

Age class of Return % Response
neighborhood Sent Rec'd Rate received
A: 0-34 years 42 24 57.14% 34.29%
B: 35-64 years 53 18 33.96% 25.71%
C: 65 + years 65 28 43.08% 40.00%
Overall 160 70 43 .75% 100.00%

 

 

 

 

 

 

The majority of respondents, 56.92%, were female while only 43.08% were male (Table
25). Most were homeowners (86.57%) and were also over the age of 60 (38.24%).
Approximately 71% had a completed an Associate’s degree or higher level of college
education. Less than 2% had completed less than a high school education. Levels of

income were rated

70

Table 25. Socio-demographic characteristics of survey respondents, Grand Junction, CO,

 

 

 

 

 

 

 

 

2004.
Characteristic n % Characteristic n %
Gender Education
Male 28 43.08% Grade school 1 1.52%
Female 37 56.92% High school 18 27.27%
65* 100.00% Associates 19 28.79%
Bachelors 21 31 .82%
Age Masters! PhD 7 10.61%
18-25 years 6 8.82% 66* 100.00%
26-35 years 13 19.12%
36-45 years 8 11.76% Income/month
46-60 years 15 22.06% < $2000 17 27.87%
$2001 -
60+ years 26 38.24% $3000 16 26.23%
$3001 -
68* 100.00% $4000 9 14.75%
$4001 -
$5000 8 13.11%
Ownership > $5000 11 18.03%
Own 58 86.57% 61* 100.00%
Rent 9 13.43%

 

67* 100.00%
* Though sixty-eight surveys were returned, some were incomplete. Some did not choose to respond to
gender, ownership of home, education, and income.

71

in increments with most, 27.87% and 26.23%, earning less than $2,000 and between

$2,001 and $3,000, respectively, each month.

Urban street tree benefits (survey question 1)
Residents were asked to rate the degree of benefit received for fourteen statements of

positive features of trees listed below:

la. provides shade; 1h. slows wind speed;

1b. pleasing to the eye; 1i. increases privacy ;

1c. flowers on trees; 1 j. filters dust from air;

1d. autumn color; 1k. increases property value;
1e. neighborhood more livable; 11. bring nature close;

If. reduce noise; lm. attract birds and wildlife;
1g. cools building in summer; In. gives sense of pride.

For each neighborhood, mean benefit ratings (rated on a scale of 1 to 5 with 1 being the
least benefit and 5 the most benefit) are given in Table 26. Overall, residents rated the
aesthetic statements; pleasing to the eye (i= 4.33), autumn color (i= 4.22), and
neighborhood more livable (i= 4.16) as providing the most benefit. Some of the
functional benefits of trees; slows wind speed (i: 3.32), reduces noise (it'= 3.36), and

filters dust from the air (i = 3.33) received the lowest ratings.

Ratings did not vary considerably among the neighborhoods though some patterns were
found. In all but two of the statements, ratings in Age Class C were higher than given in
the other two neighborhoods (§= 3.95, all statements). The average rating for all

statements given in question 1 in Age Class A was the lowest (3.59).

72

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73

Urban street tree annoyances (survey question 3)
Similar to the format presented in question one, residents were asked to rate the degree of

annoyance received from negative features of street trees. Negative features included:

3a. sidewalks damaged; 3h. falling branches;

3b. insects/disease in trees; 3i. darkens street at night;

3c. break power lines in storms; 3 j. causes allergies;

3d. suckers grow at base; 3k. limited visibility reduces security;
3e. fruit or seeds fall; 31. blocks sun in winter;

3f. flower parts fall; 3m. branches block line of sight;

3g. leaves fall in autumn; 3n. roots clog sewers.

Overall, residents in Grand Junction rated insects and disease (2: 2.51) as the most
annoying negative feature of street trees (Table 27). Other features receiving high
annoyance ratings were: roots clog sewer (k= 2.39), fruits or seeds that fall (i= 2.35),
and falling branches (§= 2.24). Residents in Age Classes A and C were most annoyed
by insects and disease in trees (i=2.70, i= 2.57, respectively). Those living in Age

Class B found falling fi'uit/seeds to be the most annoying feature (i: 2.59).

Opinion of tree condition (survey question 5)

Residents in all age classes rated the street trees in their neighborhoods in good to very
good condition (§= 3.63, Table 28). The mean rating of condition in each class ranged
from 3.58 (Age Class A) to 3.68 with residents of Age Class C giving their street tree the

highest rating. Little variation was found in the mean condition ratings between

neighborhoods.

74

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75

Table 28. Residents’ mean condition ratings" of street trees in selected neighborhoods,
Grand Junction, CO, 2004.

Age Class of neighborhood n i

 

 

 

 

A: 0-34 years 24 3.58
B: 35-64 years 18 3.61
C: 65 + years 28 3.68

 

 

 

 

 

Overall 70 3.63
*Means are based on resident ratings on a scale from 1 (very poor) to 5 (excellent).

 

Size of street trees (survey question 6)
As depicted in Table 29, residents in Age Class C rated the size of their street trees to be
slightly less than desirable (E: 1.96). As a rating of 2.0 was considered to be ‘just

right’, residents in Age Class A were also not satisfied with the size of trees in their

neighborhood (3? = 2.58).

Table 29. Residents’ mean size ratings“ of street trees in selected neighborhoods, Grand
Junction, CO, 2004.

 

Age Class of neighborhood n i

 

 

 

A: 0-34 years 24 2.58
B: 35-64 years 18 2.50
C: 65 + years 28 1.96

 

 

 

 

Overall 70 2.38
*Means are based on resident ratings on a scale from 1 (too small) to 3 (too large).

 

 

Pruning and city maintenance of street trees (survey questions 7 and 9)

Residents in Grand Junction judged the pruning of their street trees to be satisfactory with
a mean overall rating of 3.14 (Table 30). This assessment did not vary with
neighborhood age. The lowest rating was found in Age Class C (i = 2.92) and the

highest in Age Class B (i = 3.31). Maintenance of street trees was rated slightly higher

76

overall and in all neighborhoods (2 = 3.28, overall) than ratings of city pruning (Table

31).

Table 30. Residents’ mean pruning ratings“ of street trees in selected neighborhoods,
Grand Junction, CO, 2004.

Age Class of neighborhood n x

 

 

 

 

A: 0-34 years 22 3.05
B: 35-64 years 16 3.31
C: 65 + years 26 2.92

 

 

 

 

 

Overall 64 3.14
*Means are based on resident ratings on a scale from 1 (very poor) to 5 (excellent).

 

Table 31. Residents’ mean rating of city maintenance“ of street trees, Grand Junction,
CO, 2004.

 

Age class of neighborhood n x

 

 

 

A: 0-34 years 22 3.09
B: 35-64 years 16 3.44
C: 65 + years 26 3.12

 

Overall 64 3.28
*Means are based on resident ratings on a scale from 1 (very poor) to 5 (excellent).

 

 

 

 

 

Tree plantings (Question 10)

Most residents in each neighborhood believed more trees should be planted along streets
in Grand Junction (Table 32). The overall percentage of respondents favoring more
trees was 82.26% compared to only 17.74% of residents that did not support more trees.
The highest proportion of residents in favor of planting more trees was found in Age
Class C (88.46%) while the lowest was found in Age Class A (72.73%). Though the
majority of residents agreed trees were important for the community, the highest

percentage of residents opposed to increasing urban tree plantings was found in Age

77

Class A (27.27%) compared to only 14.29% and 11.54% in Age Class B and C,
respectively.

Table 32. Residents’ opinions on increasing urban tree plantings, Grand Junction, Co,
2004.

 

 

 

 

 

 

 

 

 

 

 

 

 

All Yes No
Age class of neighborhood n n % No %
A: 0-34 years 22 16 72.73% 6 27.27%
B: 35-64 years 14 12 85.71% 2 14.29%
C: 65 + years 26 23 88.46% 3 11.54%
Overall 62 51 82.26% 1 1 17.74%

 

78

DISCUSSION

The City of Grand Junction, C 0

Comparative analysis of the complete urban forest, inclusive of all public and private
trees, revealed several key differences between the two components, as indicated in both
1980 and 2004. Similarly, by stratifying the city’s developments by age, other
differences were noted about each area’s urban forest which can aid urban managers in

caring for and improving the urban forest.

Overall, in the city of Grand Junction, privately-owned trees were found to be more
diverse than the publicly-owned trees. This may come as no smprise, considering that
many public urban forest managers limit the variety of trees to be planted in public space
due to budgeting restrictions, maintenance factors, pests/disease/annoyance factors, and
public preference. Public forests are commonly composed of a few select species that:
a.) perform well under urban stresses with minimal maintenance; b.) are desired for some
aesthetic attribute; and c.) perhaps less likely to be damaged during periodic adverse

weather conditions.

79

This was evident in both sample years of 1980 and 2004 with some differences found
within the 2004 sample. Overall species diversity on publicly-owned land, which
included all age classes of neighborhoods, was significantly lower than overall private
species diversity. However, when analyzed by age of neighborhood, this trend was found
in both Age Class A and B, but not in Age Class C, where no difference occurred
between public and private tree diversity. This may be attributed to the lack of public
street trees in Age Class B and the reduced number in Age Class A in comparison to Age
Class C. Public diversity in Age Class C was also significantly higher than the public
diversity in Age Class A and B in 2004. This suggests that, though fewer public trees
were found in these areas, diversity and planting of street trees in neighborhoods has not
been a priority in more recent times. Recent developments, often designed in a
curvilinear fashion and lacking traditional sidewalks, differ in style from those of older,
more-established neighborhoods that are commonly arranged in a traditional grid pattern
that promotes walkability and usually have sidewalks and treelawns. In the absence of a
sidewalk and treelawn, many developers leave out street trees as part of the development
plan, which seemingly are not required by a municipal policy. Additionally, with
development spreading farther from the city’s core, economic strain is added to public
services departments which now must incur the increased cost of providing water,
sewage, and other municipal services to the outskirts, possibly resulting in less funding
available for street trees. In fact, less revenue is collected from residential land than is
typically spent on services to these homes (Macie 1998). Contrarily, considerably less
money is spent to service agricultural and rural land than collected in revenue (Macie

1998)

80

This trend was not affected by age of neighborhood in 1980, as diversity was consistently
higher on private property than on public property in all three age classes. No differences
were noted between the age classes, indicating that no difference in management and
planting patterns existed between public and private properties in each neighborhood.
However, age of neighborhood did influence size distribution of the overall urban forest
during the 1980 sampling, while the sizes of urban trees did not differ among
neighborhoods in 2004. In 1980, newer developments, established within the previous
decade had a significantly higher proportion of saplings in comparison to the two older
neighborhood classifications. These areas also had significantly fewer medium and
large-sized trees. In the same manner, middle-aged neighborhoods, built between 11-40
years prior, had a significantly higher percentage of medium-sized trees, while the oldest
areas, those built over 60 years prior, had a higher percentage of large trees. These
patterns reflect upon development practices and the need for stricter tree preservation
measures. Because it may seem advantageous for some developers to remove any and all
vegetation prior to development and begin with a ‘clean slate’ that will permit easy
access of large equipment and allow new homeowners to design their own landscape,
most trees in recent developments were established as young trees after building. As the
entire community benefits from trees established on all private properties, this suggests
the need for tree preservation ordinances and more collaboration between city zoning and

development officials and private developers as part of the public good.

Public and private ownership also affected size distribution of trees. Owing to the

restrictions imposed on public urban tree plantings, managers are not only limited with

81

the variety of species available to plant but also must adhere to size limitations that allow
only trees of a certain potential size to be planted in public areas. These trees are
subjected to more human contact, urban environmental limitations, and less
individualized care. Consequently, establishment of small trees and saplings is not
practical. Public urban trees are also selected by species for desirable characteristics such
as durability, adaptation to urban stresses, and a reduced amount of seeds or suckers
produced, among other features. Several of the species found on private property were
those that could be classified as prolific seeders or pioneer species, such as Siberian elm
and ailanthus, which are considered by many professionals to be weed trees and are
commonly restricted from planting by public managers. This was apparent in the
distribution of tree sizes in both sample years on public and private property. In 1980, an
overwhelming majority of saplings (less than four inches diameter) were found on private
property while significantly more medium (diameter of 11-16 inches) and large-sized
trees (over 16 inches diameter) were located on public property. Similarly, during the
2004 sample, the public forest composition held a significantly lower percentage of
saplings and a higher percentage of large trees than did the private sector. This could be
attributed to the preference of larger trees lining boulevards and the financial incentive
cities have to select trees that will attain a larger size, higher survivorship, and,
consequently have a longer lifespan and more contribution to the city. Additionally,
private land can change ownership several times, while during the same period public
property will remain a public good. Thus, private land managers with varying objectives

are more likely to manage and alter the vegetation on their property.

82

Of the trees located on private property in 1980, they were also found to be in better
health, as indicated by the percentage of trees found in the various condition classes, than
those under public management. Significantly more trees on public property were found
in poor condition and significantly fewer trees in excellent condition than on private
property, suggesting that ownership or location of trees can influence maintenance, care,
and, consequently, tree health. Generally, trees planted on private property are cared for
by the homeowner, whereas a small division of public management within the city is
charged with the care of the entire public urban forest population. Although the
population of trees in the public component is less than that in the private component,
individual care from the time of deliberate planting can lead to improved tree health and
condition of the entire urban forest. Additionally, publicly-owned trees are neither the
direct property nor responsibility of a single individual and are not guarded by any one
party in the same manner that private homeowners may provide. Thus, destructive
behavior towards the public good is not a serious concern of many homeowners and may

not be reported to city managers.

Condition trends were similar in the 2004 sampling. Even though significantly fewer
trees in excellent condition were found on public property, the percentages of public trees
reported in both good and fair condition were significantly higher than found on private
property, indicating that the public forest management has consistently maintained tree
condition, and that the overall condition of managed trees can be considered good. These
values could indicate that forest managers are doing a better job overall on care and

maintenance of urban trees as well as selecting more appropriate species. An additional

83

factor could also be the reduction in the American elm population along streets since
1980. The original 1980 sampling was intended to determine the effects of Dutch elm
disease (DED) nationwide, which had begun to affect elm trees in Grand Junction, the
western-most city included in the study at that time. In the time since DED, the
municipal forestry department has been removing diseased elms that were once very
prevalent on city streets, thereby removing some of the trees that may have been assessed

in poor condition in 1980.

Within neighborhoods, trees in the most recent developments (Age Class A) were found
to be in better condition than in other neighborhoods in both sample years. These areas
exhibited significantly more trees in excellent condition and fewer trees in poor condition
in 1980. In 2004, significantly more trees in excellent condition were found in the same
age class, though there were no differences in the frequencies of poor and dead trees like
that found in 1980. As more young trees, as indicated by size, were also found in
younger neighborhoods the better health of the population could be attributed to. the fairly
young population of trees that have been less exposed to urban conditions. Additionally,
because the trees on the privately owned sector comprise the majority of trees in each age
class, this effect could likely be attributed to individual property owner care. Saplings in
newer developments are likely to be those purposefully planted with the monetary and
physical input from the landowner, and thus guarded and cared for. No difference in
condition was found in Age Class B and Age Class C suggesting that as these plantings

and volunteers age, care does not differ between the neighborhoods.

84

Grand Junction after 24 years

Urban forest managers often have very little historical information of population
dynamics and change to guide their practices and to assist in outreach and technical
problems with residents (Kielbaso et a1 1993). Using the data collected in 1980 as a base
point, changes in species diversity, tree size, and tree condition were identified for a 24-

year duration until 2004.

The overall species diversity index of the entire urban forest population remained
unchanged after 24 years, giving the appearance that urban managers and residents
maintained urban forest diversity. However, through analysis of varying neighborhoods
and ownership, it is clear that this is not the case. Though no differences in overall
species diversity were noted from 1980-2004 among the age classes (diversity did decline
though the change was not significant), that was not the case on public versus private
property. Overall public forest diversity decreased markedly from 1980 to 2004, mostly
attributed to diversity decline occurring in the youngest (Age Class A) and middle-aged
neighborhoods (Age Class B). This could possibly coincide with a decrease in funding
and plantings and an increase in street tree removals as indicated by another urban forest
survey conducted in 1989 (Hoefer). No difference was found in the public species
diversity in the oldest neighborhoods suggesting that species diversity has not been of

prime importance in recent years.

In respect to changes in tree size structure, publicly owned tree size distribution remained

unchanged, indicating the city has been consistent with plantings and removals in the last

85

24 years. Though this does not mean that the city has been maintaining an adequate
stock of urban trees, rather, it implies that they have maintained earlier stocking levels

which were found to be largely under-stocked (Hoefer 1989).

While low stocking levels remained in the public sector, many changes were observed in
the private sector, which infer that tree plantings on private property have declined over
the years. The percentage of the private tree population identified as saplings decreased
significantly while increasing in the next two larger categories, suggesting that as these
trees grow and advance to the subsequent size cohort, creating an increase in the
following size class, more saplings are not being planted to replace those that have grown

into these next size classes.

Through analysis of change among age classes of neighborhood, it is apparent that much
of this trend can be attributed to activities in the youngest development, Age Class A.
Much like the pattern described above, the percentage of saplings decreased significantly
in this age class while significant increases were observed in all other size classes,
including larger trees. This could indicate that as new developments and subdivisions
are added to the community, the value of planting and preserving trees has been
overlooked. While increases in small, medium, and large-sized trees have occurred,
implying the progression of size as trees mature, the frequency of saplings decreased,
suggesting a decline in new plantings. The only additional temporal change noted was
found in Age Class C where the presence of large trees decreased significantly,
suggesting a higher mortality rate among some of the oldest trees that may have

succumbed to Dutch elm disease or to old age.

86

Less noticeable changes occurred in tree condition. Percentages of publicly managed
trees in all condition categories remained constant, indicating that city managers have
maintained the level of health in the street tree population. Though the frequencies of
trees in all condition classes have not changed, it may indicate that urban forest
management, while maintaining the care given to street trees, has not sufficiently cared
for trees to improve condition. Residents indicated a general disdain for urban forest
management practices at the time of the initial survey, and decline, due partly to disease
and insects, was noted among many of the cities street trees (Cannon 1980; Denison and

Winegardner 1980).

The same was found in analysis among neighborhood age. No change was seen in the
condition of trees in the newest developments while the percentage of trees in poor
condition in both Age Classes B and C declined significantly, possibly indicating that
residents are planting more species adapted to local conditions. Remarks found in the
original sample data sheets from 1980 alluded to a trend among non-native homeowners
(primarily from eastern states) to plant species native to their original homes, as they
were more familiar and usually desirable for fall color (Cannon 1980). This was not

markedly evident in the 2004 sampling as fewer non-native species were observed.

Resident survey, Grand Junction, 2004
Awareness of the physically apparent positive features of street trees, such as fall color
and pleasing to the eye, appears to be more important than some of the functional benefits

of trees, for example noise reduction and reducing wind speed. Residents in all

87

neighborhoods consistently rated the more visibly apparent features as providing more
benefit than the functional features, suggesting that they may not be aware that trees

provide these services.

Of the annoying features, residents consistently rated problematic roots and
insects/disease as the most annoying features of trees. One possible explanation could be
that the species commonly found in abundance in urban lots (Siberian elm, silver maple)
tend to have extensive root systems that often conflict with sewer systems. However,
these problems are more recognizable to residents who, therefore, are more aware these
annoyances exist. Because the city experienced Dutch elm disease more recently than the
eastern portion of the country and the city had also been affected by lilac borers, locals
may be more aware of the effects the disease had on their street tree population. Disease
is clearly evident to residents while some may not make a connection between some
indirect features, such as ‘blocks sun and line of sight’ or ‘darkens streets at night’, and

urban trees.

Ratings of annoyance were generally low among all potentially negative features of street
trees. Residents seem to view trees as a positive feature of their community and
overwhelmingly agreed, in all neighborhoods, that urban street tree plantings should be

increased.

Opinions on tree size and condition did not vary among neighborhoods. Residents in all

neighborhoods rated their street trees in good to very good condition implying they are

88

satisfied with urban forest care. Little variation was also found in size ratings though
residents in newer developments (Age Classes A and B) rated their trees as slightly too
large, those in the oldest developments (Age Class C), and highest percentage of large

street trees (Table 21), rated size as satisfactory.

Many residents appeared indifferent when asked opinions on city maintenance of urban
trees and pruning. Though most of the population was found to be in good condition
(Table 23) , which may be due to city maintenance, most responses rated the overall
maintenance and pruning as ‘good’ with very little variation among neighborhoods. This
could likely be the case that trees in Grand Junction are generally well cared for and

pruned, though it is uncertain to what degree residents are educated on proper pruning

and maintenance.

89

Summary

0 What are the difirerences in species diversity, condition, and size of urban trees in

neighborhoods of varying age?

1.) Species diversity may be influenced by the age of neighborhood development as
indicated by the 2004 sampling. This could be accounted for by development trends and
residential preferences that change over time.

2.) The age of a neighborhood does affect the size structure of the urban forest as more
smaller trees are found in areas most recently developed while the size of trees seems to
increase according to age of development. This supports the idea of increased tree
preservation, if present, at the time of construction to preserve trees of varying age.

3.) Trees appear to be in better health in newer developments, likely resulting from the

higher frequency of saplings or younger trees.

0 What are the differences in species diversity, condition, and size of urban trees on

public and private property?

1.) Species diversity significantly increases under private ownership due in part to the
better growing environment and care these trees receive and, consequently, the fact that
private landowners are able to select species that public managers may be restricted from

planting.

90

2.) Public species diversity may be higher, as found in 2004 and not in 1980, in older
neighborhoods due to trends in urban plantings.

3.) Because planting smaller, more vulnerable trees on public rights-of-way is not a
practical practice, saplings are more likely to be found under private ownership than
public.

4.) Trees are consistently more likely to be in excellent condition when located on
private grounds. Though trees in the 2004 sample were not found to be in mostly poor
condition on public property (many were rated in good or fair condition), more trees in

excellent condition were found on private property in both sample years.

0 How do species diversity, condition, and size of urban trees change over time?

1.) Species diversity on public rights-of-way has declined considerably while no change
in private diversity occurred.

2.) The presence of saplings has significantly decreased on private property and in the
newest neighborhoods (Age Class A), possibly indicating a reduction in tree plantings by
private homeowners, particularly those in newer subdivisions.

3.) Urban tree size distribution has remained unchanged on public property.

4.) Urban tree condition has remained unchanged on public property.

5.) Condition of trees on private lands has improved and may be due to an increased

awareness of planting more climate appropriate species.

91

0 Does the age of neighborhood and characteristics of the urban tree population

influence the attitudes of residents towards street trees?

0 What are the opinions of residents in Grand Junction towards street trees?

1.) Though the sample size and return rate were not high enough to allow statistical
analysis, some trends were apparent. Most notably, residents did not seem to have a clear
understanding of many of the positive features trees provide urban residents and the
potential hazards (negative features).

2.) Neighborhood of residence had little or no effect on the attitudes towards urban tree
size, condition, maintenance, and pruning in Grand Junction.

3.) Residents in all neighborhoods were generally postive about trees, rating the benefits
received as higher than degree of annoyances received, and agreed more trees should be

planted in public right-of-ways.

92

Recommendations

1.) Increasing species diversity on public property should be a paramount concern of
urban managers, particularly in newer developments while at least maintaining existing
diversity in older areas.

2.) Policies should be set that encourage more planting in new developments and tree
preservation during construction. Urban managers should work toward increasing green
cover in all areas, but particularly in locations of most recent development.

3.) More funding should be secured for better care of public urban trees. While overall
urban tree condition was good, trees on privately-owned land were found to be in better
condition, indicating that some improvement could be achieved.

4.) Programs to educate residents on the social, economic, and environmental benefits of
urban trees would be beneficial to the entire urban forest. More awareness of the benefits
of trees would encourage their planting in newer neighborhoods and provide support for
preservation measures while helping residents to better understand the value of a diverse
urban forest. Also, because the area has experienced increased growth in recent years,
increasing awareness of native species would be beneficial to persons not native to
Western Colorado.

5.) Engage residents in street tree plantings utilizing the enthusiasm and support for
increasing the urban tree population. This will also serve to increase awareness of the
benefits of urban trees and also provide an example of proper tree planting and species

selection that residents may replicate on private property.

93

APPENDICES

94

APPENDIX A

Grand Junction compared to 10 cities, I 980

The city of Grand Junction was among ten cities selected across the US. to study the
effects of ownership, whether public or private, and age of development in 1980 by US.
Forest Service researchers. The following analysis compares the city of Grand Junction,
Colorado to the nine other geographically dispersed cities based on their data. Though it
was never published, this study provides important comparative data of urban forests
across the nation, as well as a basis for the current 1980 to 2004 comparison of conditions

in Grand Junction, CO.

1980

The city of Grand Junction was compared to the nine other cities included in the 1980
sampling to compare urban forest conditions. Since each city is representative of a
unique geographical condition, the information should not imply that Grand Junction is
similar to other cities in different eco-regions. Instead, it should serve solely for
informative purposes to identify the state of the urban forest in Grand Junction as
compared to other cities nationwide. Species diversity indices were calculated for each

city’s private and public forest populations and also calculated for each age classification

95

of neighborhood. Condition and size of public and private trees in each age class of

development are also compared.

Species Diversity

Analysis of overall species diversity in each city, inclusive of all age classes and public
and private trees, found no difference in diversity indices between the ten sample cities
(Table 33). Though there are no differences in collective urban forest diversity among
sample cities, differences were noted once the overall forest was analyzed separately by

the public and private components.

Publicly-owned and privately-owned components of the urban forest were compared
among cities. Analysis of overall species diversity (both public and private and all age
classes) in each city indicated no differences, while analysis by tree ownership (public or
private) indicated a few differences among sample cities as listed in Table 33. The
diversity index of the private component of Grand Junction’s urban forest, ranked as
having the seventh highest diversity index, was found to be no different than that in the
nine other sample cities. However, differences were noted among the nine additional
sample cities. All cities in the state of Ohio; Wooster (ranked second), Delaware (ranked
fourth), Bucyrus (ranked third), and Bowling Green (ranked first); were significantly
different from the privately owned urban forests of Jamestown, New York (ranked tenth).
In addition to Jamestown, private species diversity in Bowling Green was significantly

different from Charlottesville, Virginia (ranked sixth in private diversity), Hutchinson,

96

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Minnesota (ranked eighth in private diversity), and Springfield, Massachusetts (ranked

ninth in private diversity).

Analysis of public tree diversity, inclusive of all age classes found that Grand Junction is
similar to all sample cities with the exception of Charlottesville, Virginia, which ranked
as having the lowest diversity among the ten cities (Table 33). Among the ten sample
cities, Grand Junction ranked as having the fifth highest diversity. Though it ranked as
having median diversity, public tree diversity in Grand Junction was only significantly
higher than that found in Charlottesville. Diversity in Charlottesville was also
significantly lower than that in Bucyrus (ranked fourth), Wooster (ranked third), Bowling
Green (ranked first), and Hutchinson (ranked second). However, the small sample size of
public tree species in Charlottesville in comparison to all other cities should also be
considered as a factor. Again, cities in Ohio ranked as those with the highest diversity

indices.

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development, were compared and are presented in Table 34. In comparison to the nine
other sample cities in 1980, overall condition of the urban forest, inclusive of all public
and private property and all age classes, in the city of Grand Junction differs significantly
in the frequency of trees reported in both excellent and poor condition. With only 57% of
trees in the city in excellent condition, the frequency of trees in this category are
significantly lower than all other study cities with the exception of Hutchinson which

reported only 55% of its total trees in excellent condition. Trees reported in poor

98

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condition in Grand Junction also differed significantly. Eleven percent of all trees
included in the study were reported in poor condition, significantly higher than that found

in all other cities.

Significant differences were noted not only in the city of Grand Junction. The frequency
of all city trees in excellent, good, and fair condition in the city of Hutchinson, MN was
significantly different for each (Table 34, p = 0.005). While significantly fewer trees
were reported in excellent condition (only 55%, the lowest of all ten cities) the frequency
of trees in good condition and fair condition (24% and 13%, respectively, of total urban
trees) was considerably higher. A comparative difference was also noted in the city of

Jamestown, NY. Significantly fewer trees were reported in good condition.

The frequency of trees in each condition rating on public property in all 10 cities did not
differ with the exception of Grand Junction (Table 35). A significantly higher frequency
of trees was found in poor condition in comparison to the other cities nationwide.
Twenty-seven percent of all public city trees were reported in poor condition in
comparison to an average of 7.14% for the remaining nine cities. Though Grand Junction
also held the highest percent of dead trees (7%), it was not found to differ significantly
from the sample group. Grand Junction also had the lowest portion of public trees ranked
in excellent condition, only 32%, which was far lower than the upper limits
(Charlottesville, 88%) but was not found to be statistically different. All other cities

appear to be similar in respect to the condition of trees on public property (Table 35).

100

Within the nine other sample cities, the health of the public trees in 1980 was quite good
(Table 35). Public trees in only four cities, Delaware, Lincoln, Bucyrus, and Grand
Junction, had over ten percent in poor condition. Trees were found to be in the worst
condition in Grand Junction with 27% poor, significantly higher than all other cities. No
other significant differences among the ten cities were found in the excellent, good, fair,
and dead categories. Trees in the cities of Charlottesville (88% of the total population),
Bowling Green (78%), Wooster (73%), West Springfield (83%), and Jamestown (73%)
were found to be in the best condition and above the average of 62% although not

significantly higher than that found in all other cities (Table 35).

Contrarily, no significant differences were found among trees in all age classes on private
property in the city of Grand Junction in comparison to other study cities (Table 36).
Though it did rank as having the lowest frequency (62%) in excellent condition and the
highest frequency in poor condition (8%) these values were not found to be statistically
significant. However, differences existed among the other sampled cities. The city of
Hutchinson was found to differ significantly in the frequency of trees found in condition
categories excellent, good, fair, and poor. While lower frequencies of Hutchinson’s
private trees were found in excellent condition, higher frequencies were found in the poor
and fair categories. Jamestown was the only other exception with a significantly lower

frequency of trees in good condition.

Table 37 summarizes the percentages of trees in each city found in excellent condition

and groups those in good and fair condition as well as those in poor and dead condition.

101

Though this table provides only an overall average percentage in each category and does
not provide any statistics on significance, it can be used to get a better overall picture of
condition on public and private lands. In the city of Grand Junction, the condition of
public trees appears to be worse than that found on private property. The percentage of
public trees in excellent condition was far lower (32%) than the overall city average
(64%) and, while the same was found on private lands (62%, 79%, respectively) to a
lesser extent, less private trees were found combined in poor and dead condition (10.8%

compared to 34%).

The overall condition of privately-owned trees in all cities appears to have been better
than that of the publicly-owned trees. F ifty-five percent or more of the private tree
populations were found to be in excellent condition. Though the private trees in the City
of Grand Junction found to be in poor/dead condition was only slightly above 10%

(10.8%), it was the only city above that marker.

102

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105

Size

The percentage of each city’s tree population size found within each category was
compared to that found in the ten sample cities. Chi-square analysis of the entire urban
forest population, inclusive of all public and private trees, found that the size structure in
Grand Junction was not significantly different from that of any other city (Table 38). The
percentage of saplings, those defined as having a diameter less than four inches, found in
Grand Junction was 56% of the urban forest population, slightly above the ten city
average of 53.2%. The same was found for small (4-10 inches in diameter), medium (11-
16 inches in diameter), and large trees (over 16 inches in diameter). Small trees
represented 20% of the population compared to an average of 23.3%; medium trees were
12% of the population compared to an average of 10.8%, and large trees composed 13%

of the population compared to an average of 12.8%.

While no differences existed in the city of Grand Junction, several were noted in the
cities of Bowling Green, Charlottesville, Delaware, Hutchinson, and Lincoln. Of the ten
cities, the city of Bowling Green had the highest percentage of saplings with 70% of the
population found in this group along with the lowest percentages, 5% and 7%, found in
the medium and large tree categories, respectively. The opposite was found in
Charlottesville, which had the least percentage (39%) of saplings and the highest
percentages of medium (17%) and large trees (20%). Hutchinson and Lincoln also had
high percentages of large trees (19% and 20%, respectively) while Delaware had the

lowest percentage of large trees (7%).

106

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107

Few differences were found in public tree size distributions of the ten sample cities
(Table 39). Grand Junction reported a highly significant proportion of medium-sized
trees, 33% of the public population, the highest in that category among the sampled
cities. No other significant differences were found in Grand Junction. In Lincoln, 60%
of the public tree population was composed of large trees, the most extreme of all sample

cities.

Table 40 compares the privately-owned component of the urban forest. No significant
differences were found in the city of Grand Junction. However, significant differences
were noted in the cities of Bowling Green, Charlottesville, and Hutchinson. Bowling
Green held the highest percentage of saplings (trees under four inches) on private
property at 71% which was highly significant compared to the sample group. Owing to
this large proportion, a significantly lower percentage, 5%, of all private trees fell into the
11-16 inch category. While most of Bowling Green’s private population was
represented by saplings, only 38% were saplings in Charlottesville resulting in a
significantly higher proportion of medium and large trees (17% and 20%, respectively).
The proportion of large trees in Hutchinson was also highly significant, making up 17%

of the private population, although this did not lead to differences in other size categories.

108

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110

DISCUSSION: Grand Junction as compared to cities nationwide, 1980

Though regional climatic variance plays an important role in determining the species
composition and characteristics of the 10 cities sampled nationwide in 1980, some trends
were identified and the data provided some additional background information on the

status of urban forestry in Grand Junction, CO in 1980.

Generally speaking, cities in Ohio, Bowling Green, Bucyrus, Delaware, and Wooster;
were consistently ranked with higher diversity indices overall and on public and private
property. Grand Junction consistently ranked with average diversity, possibly reflective

of management during that time.

In regard to tree condition, Grand J unction’s urban forest population did not fare well
compared to that found in other cities, which is likely due to climate as it was the
westernmost and driest locale selected. As noted in 1980, this comparison was strikingly
apparent during the first sampling (Cannon 1980). Public trees, in particular, were found
to be in the worst condition, suggesting that urban trees grown in drier environments do
require and benefit from more individual care. Private tree condition in Grand Junction

was also significantly lower than that found nationwide, though better than that observed

111

on publicly-owned property within the city. Public trees were found to be in poor
condition suggesting that urban forestry managers should focus on better care and site-

appropriate species of public trees.

Tree condition, as with species diversity, appeared to be related more to geography, as
trees in eastern cities (those east of the Mississippi River) tended to be in better health
than those found in the three western cities. In particular, public trees appeared to be in
the worst condition in Grand Junction while private trees in Hutchinson, MN were in the

worst condition, which may have been influenced by the arrival of DED.

Size did vary, as expected, among the ten sample cities, yet minimal differences were
noted in Grand Junction. Most notably, more large size public trees were found in Grand
Junction which may be a result of the city’s western location as all other cities had been
exposed to DED for several years before its effects were felt in western Colorado.
Hence, many of the larger elms, which were a major component of the urban landscape
for much of the last century, had been declining from disease and removed from urban
streets before DED progressed westward. As indicated in notes and Grand Junction’s
Community Forestry Plan, large elms, though they had begun to decline, were still

abundant on city streets (Cannon 1980, Denison and Winegardner, 1980).

112

APPENDIX B

List of species found in Age Class A (0-10 years old), Grand Junction, CO, 1980.

Species n % Total
Apple Malus spp. 45 13.60%
Apricot Prunus armeniaca 3 0.91%
Ash spp. Fraxinus spp. 35 10.57%
Aspen Populus tremuloides 29 8.76%
Austrian Pine Pinus nigra 23 6.95%
Birch Betula spp. 7 2.11%
Black Walnut Juglans nigra 1 0.30%
Blue Spruce Picea pungens 20 6.04%
Catalpa Catalpa speciosa 2 0.60%
Cherry Prunus avium 6 l .81%
Cottonwood Populus deltoides 10 3.02%
Crabapple Malus pumila 5 1.51%
Doug Fir Psuedotsuga menziesii 2 0.60%
Honeylocust Gleditsia triacanthos 8 2.42%
Lombardy Poplar Populus nigra var italica 1 0.30%
Mountain Ash Sorbus americana 4 1.21%
Mulberry Morus spp. 2 0.60%
Norway Maple Acer platanoides 1 0.30%
Norway Spruce Picea abies 1 0.30%
Peach Prunus persica 19 5.74%
Pear Pyrus spp. 2 0.60%
Plum Prunus domestica 7 2.11%
Redbud C ercis canadensis 3 0.91%
Russian Olive Elaeagnus angustifolia 15 4.53%
Scotch Pine Pinus sylvestris 15 4.53%
Silver Maple Acer saccarinum 9 2.72%
Sycamore Platnus occidentalus 2 0.60%
Unknown 2 0.60%
Unknown Pine Pinus spp. 1 0.30%
Western Red Cedar Juniperus scopulorum 15 4.53%
White Poplar Populus alba 4 1.21%
Willow spp. Salix spp. 32 9.67%
Total 331 100.00%

113

APPENDIX C

List of species found in Age Class B (1 1-40 years), Grand Junction, CO, 1980.

Species n % Total
Ailanthus Ailanthus altissima 27 8.94%
Apple Malus spp. 12 3 .97%
Ash spp. Fraxinus spp. 60 19.87%
Aspen Populus tremuloides 4 1.32%
Austrian Pine Pinus nigra 1 0.33%
Birch Betula spp. 3 0.99%
Black Locust Robinia psuedoacacia l 0.33%
Black Walnut Juglans nigra 5 1.66%
Blue Spruce Picea pungens 6 1.99%
Catalpa Catalpa speciosa 3 0.99%
Cherry Prunus avium 3 0.99%
Cottonwood Populus deltoids 12 3 .97%
Crabapple Malus pumila 7 2.32%
Elm Ulmus spp. 29 9.60%
Honeylocust Gleditsia triacanthos 8 2.65%
Lombardy Poplar Populus nigra var italica 22 7.28%
Magnolia Magnolia spp. 1 0.33%
Mulberry Moms spp. 7 2.32%
Norway Maple Acer platanoides 2 0.66%
Norway Spruce Picea abies 1 0.33%
Peach Prunus persica 7 2.32%
Pear Pyrus spp. 2 0.66%
Redbud C ercis canadensis l 0.33%
Russian Olive Elaeagnus angustifolia 12 3.97%
Scotch Pine Pinus sylvestris 1 0.33%
Silver Maple Acer saccarinum 4 1.32%
Sycamore Platnus occidentalus 3 0.99%
Unknown 6 1.99%
Western Red Cedar Juniperus scopulorum 24 7.95%
White Poplar Populus alba 8 2.65%
White Spruce Picea glauca 1 0.33%
Willow spp. Salix spp. 19 6.29%
Total 302 100.00%

114

APPENDIX D

List of species found in Age Class C (41 years and older), Grand Junction, CO, 1980.

Species n % Total
Ailanthus Ailanthus altissima 36 13.19%
Apple Malus spp. 5 1.83%
Apricot Prunus armeniaca 4 1.47%
Ash spp. Fraxinus spp. 37 13.55%
Basswood Tilia americana 1 0.37%
Blue Spruce Picea pungens 6 2.20%
Box Elder Acer negundo 3 1.10%
Catalpa Catalpa speciosa 5 1.83%
Cherry Prunus avium 1 0.37%
Cottonwood Populus deltoides 12 4.40%
Crabapple Malus pumila 6 2.20%
Elm Ulmus spp. 48 17.58%
Honeylocust Gleditsia triacanthos 20 7.33%
Lombardy Poplar Populus nigra var italica 1 0.3 7%
Magnolia Magnolia spp. 1 0.37%
Mountain Ash Sorbus americana 2 0.73%
Mulberry Morus spp. 8 2.93%
Norway Spruce Acer platanoides 2 0.73%
Peach Prunus persica 6 2.20%
Plum Prunus domestica 4 1.47%
Ponderosa Pine Pinus ponderosa 1 0.37%
Russian Olive Elaeagnus angustifolia 3 1.10%
Scotch Pine Pinus sylvestris 2 0.73%
Sumac Rhus spp. 2 0.73%
Sycamore Platnus occidentalus 21 7.69%
Western Red Cedar Juniperus scopulorum 26 9.52%
White Poplar Populus alba l 0.37%
Willow spp. Salix spp. 9 3.30%
273 100.00%

115

APPENDIX E

List of species found in Age Class A (0-34 years old), Grand Junction, CO, 2004.

Species n % Total

Ailanthus Ailanthus altissima 6 0.89%
Amur Maple Acer ginnala 1 0.15%
Apple Malus spp. 50 7.45%
Apricot Prunus armeniaca 4 0.60%
Ash spp. Fraxinus spp. 69 10.28%
Aspen Populus tremuloides 107 15.95%
Austrian Pine Pinus nigra 31 4.62%
Birch Betula spp. 7 1.04%
Black Walnut Juglans nigra 3 0.45%
Blue Spruce Picea pungens 34 5.07%
Callery Pear Pyrus calleryana 2 0.30%
Catalpa Catalpa speciosa 2 0.30%
Cherry Prunus avium 15 2.24%
Cottonwood Populus deltoides 15 2.24%
Crabapple Malus pumila 17 2.53%
Doug Fir Psuedotsuga menziesii 2 0.30%
Elm Ulmus spp. 3 0.45%
European Birch Betula pendula 1 0.15%
Gray Birch Betula populifolia 1 0.15%
Hawthorne Crataegus spp. l 0.15%
Honeylocust Gleditsia triacanthos 22 3.28%
Lombardy Poplar Populus nigra var italica 3 0.45%
Mountain Ash Sorbus americana 5 0.75%
Mugo Pine Pinus mugo 2 0.30%
Mulberry Morus spp. 13 1.94%
Norway Maple Acer platanoides 2 0.30%
Norway Spruce Picea abies l 0.15%
Oriental Arborvitea Platycladus orientalis 8 1.19%
Peach Prunus persica 24 3.58%
Pear Pyrus spp. 5 0.75%
Pinyon Pine Pinus edulis 2 0.30%
Plum Prunus domestica 10 1.49%
Ponderosa Pine Pinus ponderosa 13 1.94%

116

Red Maple
Redbud

Russian Olive
Scotch Pine
Silver Maple
Sycamore
Unknown
Unknown Maple
Unknown Pine
Western Red Cedar
White Birch
White Cedar

White Oak
White Poplar
White Spruce
Willow spp.

Acer rubrum

Cercis canadensis
Elaeagnus angustifolia
Pinus sylvestris

Acer saccarinum
Platnus occidentalus

Acer spp.

Pinus spp.

Juniperus scopulorum
Betula papyrifera
Thuja occidentalis

Quercus spp.
(Lepidobalanus)

Populus alba
Picea glauca
Salix spp.

117

671

0.45%
1.34%
2.98%
2.24%
1.94%
0.75%
0.45%
0.30%
0.30%
6.41%
0.15%
1.64%

0.45%
2.24%
0.30%
6.41%

100.00%

APPENDIX F

List of species found in Age Class B (35-60 years), Grand Junction, CO, 2004.

Species n % Total

Ailanthus Ailanthus altissima 31 4.28%
Amur Maple Acer ginnala l 0.14%
Apple Malus spp. 38 5.25%
Apricot Prunus armeniaca 5 0.69%
Ash spp. Fraxinus spp. 100 13.81%
Aspen Populus tremuloides 63 8.70%
Austrian Pine Pinus nigra 16 2.21%
Birch Betula spp. 3 0.41%
Black Locust Robinia psuedoacacia 8 1.10%
Black Walnut Juglans nigra 5 0.69%
Blue Spruce Picea pungens 26 3.59%
Box Elder Acer negundo l 0.14%
Callery Pear Pyrus calleryana 1 0.14%
Catalpa Catalpa speciosa 7 0.97%
Cherry Prunus avium 35 4.83%
Cottonwood Populus deltoides 18 2.49%
Crabapple Malus pumila 19 2.62%
Elm Ulmus spp. 45 6.22%
European Birch Betula pendula 2 0.28%
Honeylocust Gleditsia triacanthos 27 3.73%
Lodgepole Pine Pinus contorta 1 0.14%
Lombardy Poplar Populus nigra var italica 29 4.01%
Magnolia Magnolia spp. 1 0.14%
Mugo Pine Pinus mugo 1 0.14%
Mulberry Morus spp. 14 1.93%
Norway Maple Acer platanoides 2 0.28%
Norway Spruce Picea abies 1 0.14%
Oriental Arborvitea Platycladus orientalis 5 0.69%
Peach Prunus persica 10 1.38%
Pear Pyrus spp. 4 0.55%
Pinyon Pine Pinus edulis 1 0.14%
Ponderosa Pine Pinus ponderosa 3 0.41%
Red Maple Acer rubrum 1 0.14%

118

Redbud

Russian Olive
Scotch Pine
Silver Maple
Sumac
Sycamore
Unknown
Unknown Maple
Unknown Pine
Western Red Cedar
White Cedar
White Poplar
White Spruce
Willow spp.

C ercis canadensis
Elaeagnus angustzfolia
Pinus sylvestris

Acer saccarinum

Rhus spp.

Platnus occidentalus

Acer spp.

Pinus spp.

Juniperus scopulorum
T huja occidentalis
Populus alba

Picea glauca

Salix spp.

119

25

w—‘QNNON

55

21

40
724

0.14%
3.45%
0.97%
2.62%
0.28%
0.97%
0.83%
0.14%
0.41%
7.60%
1.52%
2.90%
0.28%
5.52%

100.00%

APPENDIX G

List of species found in Age Class C (61 years and older), Grand Junction, CO, 2004.

Species 11 % Total

Ailanthus Ailanthus altissima 137 15.36%
Alder Alnus spp. 2 0.22%
Apple Malus spp. 12 1.35%
Apricot Prunus armeniaca 6 0.67%
Ash spp. F raxinus spp. 65 7.29%
Aspen Populus tremuloides 27 3.03%
Austrian Pine Pinus nigra 1 0.11%
Basswood Tilia americana l 0.11%
Blue Spruce Picea pungens 18 2.02%
Box Elder Acer negundo 4 0.45%
Callery Pear Pyrus calleryana 2 0.22%
Catalpa Catalpa speciosa 10 1.12%
Cherry Prunus avium 4 0.45%
Cottonwood Populus deltoides 20 2.24%
Crabapple Malus pumila 7 0.78%
Dogwood C ornus spp. 1 0.1 1%
Elm Ulmus spp. 21 1 23.65%
Golden Raintree Koelreuteria paniculata 2 0.22%
Hackberry Celtis occidentalis 2 0.22%
Honeylocust Gleditsia triacanthos 80 8.97%
Lodgepole Pine Pinus contorta 1 0.11%
Lombardy Poplar Populus nigra var italica 1 0.11%
Magnolia Magnolia spp. 1 0.1 1%
Mountain Ash Sorbus americana 3 0.34%
Mugo Pine Pinus mugo 3 0.34%
Mulberry Morus spp. 54 6.05%
Norway Maple Acer platanoides 4 0.45%
Norway Spruce Picea abies 2 0.22%
Paulownia Paulownia tomentosa 1 0.11%
Peach Prunus persica 7 0.78%
Pear Pyrus spp. 6 0.67%
Pladycladus Platycladus orientalis 9 1.01%
Plum Prunus domestica 7 0.78%

120

Ponderosa Pine
Russian Olive
Scotch Pine
Silver Maple
Sugar Maple
Sumac
Sycamore
Unknown
Unknown Pine
Western Red Cedar
White Cedar

White Oak
White Poplar
White Spruce
Willow spp.

Pinus ponderosa
Elaeagnus angustifolia
Pinus sylvestris

Acer saccarinum

Acer saccharum

Rhus spp.

Platnus occidentalus

Pinus spp.
Juniperus scopulorum
Thuja occidentalis

Quercus spp.
(Lepidobalanus)

Populus alba
Picea glauca
Salix spp.

121

Nt-‘OODJOOH

34

i—‘UJ

88

ONQUJ

892

1.23%
0.90%
0.34%
0.90%
0.1 1%
0.22%
3.81%
0.34%
0.1 1%
9.87%
0.1 1%

0.34%
0.67%
0.22%
1.12%

1 00.00%

APPENDIX H

Urban tree attitude questionnaire, 2004.

122

COVER LETTER MAILED WITH SURVEY

MICHIGAN STATE UNIVERSITY
URBAN TREE ATTITUDE STUDY, GRAND JUNCTION, CO.

October 13, 2005

Greetings:

Your neighborhood has been involved in research conducted by Michigan State
University, Department of Forestry. Led by Dr. J .James Kielbaso, the study will analyze
trends in the urban forest throughout the City of Grand Junction.

The study was conducted during the years of 1980 and 2004. Trees on both private and
public property (the area between the sidewalk and the curb) were surveyed in randomly
selected blocks throughout the city. Information was collected on tree species, size, and
the condition. The data will be used to compare and determine trends in the urban forest
from 1980 to present.

Additionally, the study seeks to determine resident attitudes towards trees in general in
the City of Grand Junction. The enclosed survey requires very little written response and
will take very little of your time. The survey does not require you to identify yourself and
your responses will neither be linked to you nor your residence. The responses will be
used for statistical research purposes only and you will remain anonymous. The
information gathered is critical to the success and accuracy of the study and can be used
to improve the natural environment and quality of life in your city. Return postage has
also been provided on the enclosed stamped envelope.

Please feel free to contact Ms. Heidi F rei (contact information below) with any questions
you may have.

Thank you for taking the time to improve your community forest and your city.

Sincerely,

 

Heidi Frei

Research Assistant

MSU, Dept. of Forestry
Natural Resources Building
East Lansing, MI 48824
freiheid@msu.edu

123

QUESTIONNAIRE

MICHIGAN STATE UNIVERSITY
EVALUATING YOUR NEIGHBORHOOD STREET TREES

The following questions refer to the trees growing along the street in your immediate
neighborhood, that is, within a block or two of your house, apartment, or place of
business. This research is attempting to find out how these trees contribute to the quality

of life in your neighborhood. The questionnaire will only take a few minutes to fill out.
THANK YOU!

1. Here are some possible positive features of street trees. Please check below the degree
of benefit m receive fiom these trees.
Please check only one box per line.

 

Slight Some Great V ety great
No benefit benefit benefit benefit benefit

 

Provides shade

 

9" 9’

Pleasing to the eye

 

c. Flowers on trees

 

9-

Autumn color
Neighborhood more
livable

 

 

Reduce noise

 

Cools building in summer

 

PCP”?

Slows wind speed

 

Increases privacy

 

Filters dust from air

C—u
O

 

k. Increases property value

 

l. Brings nature close

 

m. Attract birds/wildlife

 

 

 

 

 

 

 

 

n. Gives sense of pride

 

2. What type(s) of things would you like to see more of in your local parks?
PLEASE NUMBER 1,2,3....10 FROM MORE IMPORTANT (1) TO LEAST IMPORTANT (10).

__ picnic area __ playground equipment __ benches

_ basketball court __ tennis court __ trees and shrubs
__ garden / flower beds _ volleyball court _ other

__ soccer field _ walking / biking path

124

3. Here are some possible negative features of street trees. Please check below the degree
of annovance m receive from these trees.
Please check only one box per line.

 

Not an Slight Some Great V ery great
annoyance annoyance annoyance annoyance annoyance

 

a. Sidewalks damaged

 

b. Insect/disease in tree
Branches break power lines in

 

 

c. storm
Suckers grow around base of the
d. tree

 

Fruit or seeds fall

 

Flower parts fall

 

Falling leaves in autumn

 

3709?”?

Falling branches

 

~.
I

Darkens street at Light

 

j. Causes allergies
Limited visibility reduces
k. security

 

 

1. Blocks sun in winter

 

m. Branches block line of sight

 

 

n. Roots clog up sewer

 

 

 

 

 

 

 

5. Would you be willing to participate in these programs if available?
Maybe/Don't
Yes Know No
a. Ecological programs in general _ _ __
b. Arbor Day programs _ __ __
c. Environmental education program _ __ _
d. Voluntary service program __ _ __
e. Adopt a street program _ __ ._
f. other _ _ _
6. What is your overall opinion of the condition of the street trees in your neighborhood?
excellent _ very good _ good __ poor __ very poor
Why do you feel this way?

 

125

 

7. Do you feel that the size of the street trees in your neighborhood is:

too small just right too large no opinion

8. The pruning of street trees in you neighborhood is:

excellent very good good poor very poor

9. How well do you think that the City is maintaining the street trees?
excellent very good good poor very poor

10. Do you feel that more trees should be planted in the City?

If yes, where? —— yes —— N0
streets parks plazas own yards other
11. Do you participate in recycling?
yes no sometimes

_—.

12. How immrtant _t_g ygg are trees and shrubs in the following areas?
Please check only one box per line.

Not Slightly Somewhat Greatly Very

important important important important important
a. in a city park __ __ _ __ __
b. in downtown shopping areas _ __ __ __ __
c. in front yards of homes __ __ _ __ _
(1. along residential streets _ __ __ _ __
e. in and around parking lots _ _ __ _ __
f. in industrial areas

g. in backyards of homes

13. Would you be willing to pay for more of the following community services?

No

Yes No opinion
a. recreational programs _ __ __
b. parks __ __ __
c. environmental education _ _ __
d. street trees _ _ __
e. bicycle path __ __ __
f. other

 

126

15. Here are some statements regarding the City of Grand Junction and its environment.
Check the box that mu feel best describes the statement.
Please check only one box per line.

 

Strongly Not sure/ Strongly
a ee Agree don't know Disagree disagree

 

The city is a model of urban
a. lanning.

 

Trees contribute to the quality of
b. life in the city.

My neighborhood is well-
c. planned.

 

 

The city is ecologically
cl. conscious.

 

Trees influence my choice of a
e. place to live.

 

The city should preserve more
f. rgleen/natural areas.

 

The city needs to improve the
g. gality of its urban tree plantings.

 

 

 

 

 

 

 

 

17. The following questions are for statistical purpose only- you will not be identified.

a. How long have you occupied this house / building? _ years

b. Do you own or rent? _ own _ rent _ rent to own

c. Are you: _ Male _ Female

(1. Your age: _ 18-25 __ 26-35 _ 36-45 _ 46-60 _ 60+

e. Your education (circle highest level achieved):

Grade school High school College: Associates Bachelors Masters PhD.

f. What is your approximate monthly household income?
Less than $2,000 $3001 - 4,000 over $5,000

$2,001 - 3,000 $4,001 - 5,000

Thank you! Please use the enclosed envelope for your convenience.

127

FOLLOW-UP SURVEY LETTER

MICHIGAN STATE UNIVERSITY
EVALUATING YOUR NEIGHBORHOOD STREET TREES

November 23, 2005

Greetings:

A survey was mailed to you during the month of October to assist in research at Michigan
State University, Department of Forestry. The survey, part of a study conducted during
the years of 1980 and 2004, will assess resident attitudes towards trees in general in the

City.

For whatever reason, a number of surveys have not been completed and returned. Using
the return rate, I have randomly selected a percentage of addresses to resend the survey.
If you have already completed your survey, I sincerely thank you. If you have not yet
had the opportunity, please take the time to assist in our research.

Although the upcoming season is typically busy for all, we would greatly appreciate your
time and effort. Please remember that the survey requires very little written response
and very little time to complete and you will remain anonymous. The information
gathered is critical to the success and accuracy of the study and can be used to improve
the natural environment and quality of life in your city. Return postage has also been
provided on the enclosed stamped envelope.

Please feel free to contact Ms. Heidi M. Frei (contact information below) with any
questions you may have.

Thank you for taking the time to improve your community forest and your city.

Sincerely,

 

Heidi M. Frei

Research Assistant

MSU, Dept. of Forestry
Natural Resources Building
East Lansing, MI 48824
freiheid@msu.edu

128

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129

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