Trees in Towns: Factors Affecting the Distribution of Trees in High Density Residential Areas of Greater Manchester

A thesis submitted to the University of Manchester for the degree of Ph.D. in the Faculty of Humanities

2010

Justine Michelle Hall

School of Environment and Development Planning and Landscape Department

Table of Contents Contents Page

Table of Contents 2

List of Figures 7

List of Tables 10

Abstract 13

Declaration 14

Copyright Statement 14

Acknowledgements 15

Chapter 1 – Introduction 17

1.1 Aims and Objectives of the Thesis 19

Chapter 2 – Trees in the Urban Environment 22

2.1 Introduction 22

2.2 The Benefits of Trees in Urban Areas 23 2.2.1 Trees and Air Quality 23 2.2.2 Trees and Water 26 2.2.3 Trees and the Urban Heat Island Effect 27 2.2.4 Trees and Human Physical and Psychological Health 30

2.3 Factors Affecting the Distribution of Urban Trees 36 2.3.1 Socioeconomic Factors Affecting the Distribution of Urban Trees in the USA 37 2.3.2 Socioeconomic Factors Affecting the Distribution of Urban Trees in the UK 39 2.3.3 The Effects of Housing Density and Land Use on the Distribution of Urban Trees 40 2.3.4 The Effects of Housing Layout on the Distribution of Urban Trees 43 2.3.5 Attitudes and Awareness of Residents about Urban Trees 51

2.4 Potential Factors for Protecting and Increasing Urban Tree Cover 55 2.4.1 Effects of Municipal Regulations 55 2.4.2 Effects of Community Greening Schemes 58 2.4.3 Potential Effects of the Loss of Greenspace in Residential Areas 59

2 2.5 Conclusions 60

Chapter 3 – Research Methodology 62

3.1 The Research Context 62 3.1.1 A Conceptual Framework for the Research 63

3.2 Justification of the case study approach 65

3.3 Case Study Selection 66

3.4 Justification and Overview of the Methods Used in the Thesis 70 3.4.1 Objective One 70 3.4.2 Objective Two 73 3.4.3 Objective Three 74 3.4.4 Objective Four 76

3.5 Conclusion 78

Chapter 4 – An Exploration of Tree Cover and its Location in Differing Housing Types 79

4.1 Introduction 79

4.2 Methods 81 4.2.1 Determination and Delineation of Housing Morphology Types 81 4.2.2 Categorising Surface Covers and Land Uses 88 4.2.3 Position of Trees 93

4.3 Results 94 4.3.1 Housing Morphology 94 4.3.2 Surface Cover and Land Use Analysis 95 4.3.3 Comparative Data 110 4.3.4 Locations of trees 114

4.4 Discussion 115 4.4.1 Distribution and amount of housing types across the study area 115 4.4.2 Influences on tree cover in housing types 116

4.5 Summary and Conclusions 118

Chapter 5 – Increasing Tree Cover and its Effects on Maximum Surface Temperatures and Rainfall Runoff 119

5.1 Introduction 119

5.2 Methods 119 5.2.1 Determination of Potential Increases in Tree Cover 120 5.2.2 Calculating Increase in Tree Cover 122 5.2.3 The Energy Balance Model 122 5.2.4 Surface Runoff Model – Background 127 3 5.3 Results 130 5.3.1 Increases in Tree Cover 130 5.3.2 Location of Potential Trees 131 5.3.3 Energy Exchange Model for Surface Temperature Calculations 133 Temperature Projections with Current and Increased Tree Cover 134 5.3.4 Rainfall Runoff Calculations 146

5.4 Discussion 149 5.4.1 Increases in Tree Cover 149 5.4.2 Location of Potential Trees 149 5.4.3 Maximum surface temperatures 150 5.4.4 Surface Runoff 150

5.5 Summary and Conclusions 151

Chapter 6 – Residents’ Attitudes Towards Trees in Differing Types of High Density Residential Streets 152

6.1 Introduction 152

6.2 Methods 154 6.2.1 Identifying the survey objectives 154 6.2.2 Selecting the sampling frame 154 6.2.3 Determining the sampling method 156 6.2.4 Developing the questionnaire 157 6.2.5 Surveying residents 157 6.2.6 Analysis of Data 158

6.3 Results 159 6.3.1 Response Rates 159 6.3.2 Trees and Everyday Life Questions 161 6.3.3 Positive Statements About Trees 162 6.3.4 Negative Statements About Trees 164 6.3.5 Length of Stay in Current Home 166 6.3.6 Respondents’ Views About Their Street 166 6.3.7 Trees and House Prices and Future Homes 168 6.3.8 Street Specific Questions 169 6.3.9 Socioeconomic data 173 6.3.10 Crosstabulations 176

6.4 Discussion 182 6.4.1 Response Rates 182 6.4.2 The Importance of Trees to Everyday Life 182 6.4.3 Positive Statements about Trees 183 6.4.4 Negative Statements About Trees 185 6.4.5 Length of Stay in Current Home 187 6.4.6 Respondents’ Views About Their Street 187 6.4.7 Trees and House Prices and Future Homes 188 6.4.8 Street Specific Questions 189

6.5 Comparisons of UK data and US data 190

4 6.6 Summary and Conclusions 195

Chapter 7 – Barriers and Opportunities to Increasing Tree Cover 197

7.1 Introduction 197 7.1.1 The Legal and Planning Context for Urban Trees 198

7.2 Practitioner Workshop 201 7.2.1 Methods 201 7.2.2 Results 205 7.2.3 Discussion 211

7.3 Increasing Tree Cover in High Density Housing – Examples 212 7.3.1 Case Study Area Selection 212 7.3.2 Methods 215 7.3.3 Results 215 7.3.4 Discussion 218

7.4 Factors Affecting Red Rose Forest Green Streets Project Uptake 221 7.4.1 Methods 221 7.4.2 Results 221 7.4.3 Summary 223

7.5 Factors Affecting Use of Trees and Greenspace in Regeneration Schemes 224 7.5.1 Methods 224 7.5.2 Chimney Pot Park 224 7.5.3 Grove Village 226 7.5.4 The Use of Greenery in Developments 228 7.5.5 Discussion 228

7.6 Summary and Conclusions 230

Chapter 8 – Discussion 232

8.1 Introduction 232

8.2 Factors Affecting the Distribution of Urban Trees 232 8.2.1 Socioeconomic Factors Affecting the Distribution of Urban Trees 232 8.2.2 The Effects of Housing Layout on the Distribution of Urban Trees 233 8.2.3 Attitudes and Awareness of Residents about Urban Trees 234

8.3 The Benefits of Trees in Urban Areas 238 8.3.1 Increasing Tree Cover and Maximum Surface Temperatures 238 8.3.2 Trees and Rainfall Runoff 239

8.4 Potential Factors for Protecting and Increasing Urban Tree Cover 239 8.4.1 Existing and Potential Tree Cover in Different Housing Types 239 8.4.2 Effects of Municipal Regulations 242 8.4.3 Effects of Municipal Practice 244 8.4.4 Raising Money for Tree Planting and Maintenance 245 5 8.4.5 Saving Money in Arboricultural Departments 247 8.4.6 Encouraging Community Involvement in Tree Based Activities 248 8.4.7 Community Greening Projects 249 8.4.8 Comparison of Differing Approaches to Increasing Tree Cover 250

8.5 Conclusions 250

Chapter 9 – Conclusions 253

9.1 Summary of Main Research Findings 253 9.1.1 Revisiting the Conceptual Framework 253

9.2 Recommendations of the Research 258 9.2.1 National Government 258 9.2.2 Local Government 259 9.2.3 Developers 262 9.2.4 Residents 263 9.2.5 Community Greening Projects 264

9.3 Limitations of the Research Methodology 264

9.4 Recommendations for Further Work 265

References 266

Appendix 1. Cover Letter and Questionnaire Exploring Residents’ Attitudes Towards Trees 280

Appendix 2. ‘Barriers and Opportunities for Increasing Tree Cover within Urban Areas’: Summary of Practitioner Workshop Held On Monday 22 nd February 2010, at the University of Manchester 289

Word count: 77,116

6 List of Figures

Figure 2.1 . Two examples of ‘byelaw’ terraces in Manchester, UK, built pre-1919. (Source: 1:10,000 OS map, within a GIS). 44 Figure 2.2 . A street map of an area of Letchworth Garden City, Bedfordshire, UK. Note the much lower density and lack of straight roads and crossroad junctions compared to Figure 2.1. (Source: 1:10,000 OS map, within a GIS). 45 Figure 2.3 . A block of flats within a high density housing area in Gorton, Manchester. Note the small patch of grass to the left which is the only vegetated area around the flats. The trees are part of a separate development. 48 Figure 2.4 . An example of 1960s housing in Gorton, Manchester, which is only accessible on foot. There is no road access to the rear of the properties either. 49 Figure 3.1 . A conceptual framework outlining potential influences on tree distribution in high density housing areas. Thick arrows indicate relationship described in the literature, thin arrows indicate hypothesised relationships. 64 Figure 3.2 . The location of Greater Manchester within the north west of England, UK, and the study area (white) within Greater Manchester. 69 Figure 4.1 (1). Clockwise from top left –Pre 1919 terraced housing with a front yard; Pre 1919 terraced housing with a front and back garden; Pre 1919 semi-detached housing; 1919-1959 terraced housing; 1960s terraced housing with a driveway; 1960s terraced housing with a walkway; 1919-1959 semi-detached housing; Pre 1919 terraced housing opening directly onto the road. 85 Figure 4.1 (2). Top – Post 1960s terraced housing. Right- Post 1950s semi-detached housing. Bottom – Post 1960s Court/Square housing. 86 Figure 4.2. Examples of high density housing (non shaded area) on a 1:10000 scale OS map within a GIS. 87 Figure 4.3 . An example of high density housing types on an aerial photograph. 88 Figure 4.4 . An example of delineated high density housing categories on a 1:10000 scale OS map within a GIS. 88 Figure 4.5 . A demonstration of classification of land use and surface cover types. 91 Figure 4.6 . A screen shot of the Photo Interpretation Tool in action. The yellow dot is the point which is to be classified; the blue dot is a point to be classified later. 92 Figure 4.7 . Cumulaive frequency graph of percentage surface cover for the pre-1919 semi-detached housing type. 93 Figure 4.8 . Statistics for differing housing types across the study area. 94 Figure 4.9 . Area of high density housing (in hectares) in each local authority of the study area. 95 Figure 4.10 .Surface cover in pre1919 semi-detached housing. 95 Figure 4.11 .Land use in pre1919 semi-detached housing. 96 Figure 4.12 . Surface cover in pre-1919 terraced onto road housing. 97 Figure 4.13 . Land use in pre-1919 terraced onto road housing. 97 Figure 4.14 . Surface cover in pre-1919 terraced housing with front yard. 98 Figure 4.15 . Land use in pre-1919 terraced housing with a front yard. 98 Figure 4.16 . Surface cover in pre-1919 terraced housing with front and back garden. 99 Figure 4.17 . Land use in pre-1919 terraced housing with a front and back garden. 100 Figure 4.18 . Surface cover in 1919-1959 semi-detached housing. 101 Figure 4.19 . Land use in 1919-1959 semi-detached housing. 101 Figure 4.20 . Surface cover in 1919-1959 terraced housing. 102 Figure 4.21 . Land use in 1919-1959 terraced housing. 102 Figure 4.22 . Surface cover in post 1950s semi-detached housing. 103 Figure 4.23 . Land use in post 1950s semi-detached housing. 104 Figure 4.24 . Surface cover in 1960s terrace walkway housing. 104 Figure 4.25 . Land use in 1960s terraced walkway housing. 105 7 Figure 4.26 . Surface cover in 1960s terrace driveway housing. 106 Figure 4.27 . Land use in 1960s terraced driveway housing. 106 Figure 4.28 . Surface cover in post 1960s terraced housing. 107 Figure 4.29 . Land use in post 1960s terraced housing. 108 Figure 4.30 . Surface cover in post 1960s court/square housing. 109 Figure 4.31 . Land use in post 1960s court/square housing. 109 Figure 4.32 . A comparison of surface cover proportions across housing types. 111 Figure 4.33 . A comparison of proportions of land use across housing types. 113 Figure 4.34 . The percentage of tree cover in each housing type. 114 Figure 5.1 . Two examples of the ‘planting’ exercise within a GIS. 121 Figure 5.2 . A diagram demonstrating the location of a newly planted tree according to Red Rose Forest guidelines. 122 Figure 5.3 . A graphical representation of rainfall absorbed by soil and the surface runoff. From: Whitford et al., 2001. 129 Figure 5.4. Scatterplot with regression line showing the relationship between existing and potential tree cover. R 2 = 0.26 131 Figure 5.5 . A comparison of the percentage of potential trees planted into each land use type in all housing categories. 132 Figure 5.6 . The percentages of potential trees planted into each land use type across all housing categories. 133 Figure 5.7 . Modelled changes in maximum surface temperatures in differing climate scenarios for pre 1919 semi-housing for existing and potential levels of tree cover. 135 Figure 5.8 . Modelled changes in maximum surface temperatures in differing climate scenarios for pre 1919 onto road housing for existing and potential levels of tree cover. 135 Figure 5.9 . Modelled changes in maximum surface temperatures in differing climate scenarios for pre 1919 terraced housing with a front yard for existing and potential levels of tree cover. 136 Figure 5.10 . Modelled changes in maximum surface temperatures in differing climate scenarios for pre 1919 terraced housing with a front and back garden for existing and potential levels of tree cover. 137 Figure 5.11 . Modelled changes in maximum surface temperatures in differing climate scenarios for 1919-1959 semi-detached housing for existing and potential levels of tree cover. 138 Figure 5.12 . Modelled changes in maximum surface temperatures in differing climate scenarios for 1919-1959 terraced housing for existing and potential levels of tree cover. 139 Figure 5.13 . Modelled changes in maximum surface temperatures in differing climate scenarios for post 1950s semi-detached housing for existing and potential levels of tree cover. 140 Figure 5.14 . Modelled changes in maximum surface temperatures in differing climate scenarios for 1960s terraced housing with a walkway for existing and potential levels of tree cover. 141 Figure 5.15 . Modelled changes in maximum surface temperatures in differing climate scenarios for 1960s terraced housing with a driveway for existing and potential levels of tree cover. 142 Figure 5.16 . Modelled changes in maximum surface temperatures in differing climate scenarios for post 1960s terraced housing for existing and potential levels of tree cover. 143 Figure 5.17 . Modelled changes in maximum surface temperatures in differing climate scenarios for post 1960s court/square housing for existing and potential levels of tree cover. 144 Figure 5.18 . Reductions in maximum surface temperature in area of high building mass and low building mass with increasing vegetation cover. 145 8 Figure 6.1 . Examples of street types surveyed. Clockwise from top left: Post Green Streets, Pre Green Streets, No Trees, Trees. 155 Figure 6.2 . Scatterplot with linear regression line showing the relationship between IMD score and response rates. 160 Figure 7.1 Participants using the Ketso kit to aid discussions. 202 Figure 7.2 A section of the ‘Legislation’ discussion. Gray leaves indicate barriers, green opportunities, a tick shows another group agrees with a topic, and an exclamation mark shows another groups is also concerned with the same issue. 203 Figure 7.3 . The location of the study sites within Manchester and Salford for comparison of tree planting schemes. Street maps are not to scale. Clockwise from top right: Chimney Pot Park, Grove Village, Edenhall Avenue, Thornton and Horton Roads, Palmerston Avenue. 214 Figure 7.4 . Trees along two different streets in Chimney Pot Park. Left, existing trees integrated into the development. Right, new trees planted. 217 Figure 7.5 . Trees in Grove Village. 217 Figure 7.6 Left: photo showing a felled tree that had grown over its metal tree guard. Right: photo showing a newly planted trees unprotected by a tree guard with a kinked trunk from car damage. 220 Figure 7.7 . The communal garden areas (left) and roads (right) of Chimney Pot Park. 225 Figure 7.8 . A neighbouring street to Chimney Pot Park, where street greening and alleygating has taken place. 226 Figure 7.9 . A section of the Green Route in Grove Village, showing the flat kerbs, trees and bollards that separate the pavement from the parking area. 227 Figure 8.1 . Map demonstrating the variability of housing type in a small geographical area (2860m by 1880m, 538ha) in Langworthy, Salford. The black lines are lower layer super output areas, and the different coloured polygons are differing housing types. Scale bar is 800 metres. 233

9 List of Tables Table 3.1. Address points per hectare for differing residential densities in Greater Manchester. 67 Table 3.2 . Stepwise development of a sampling procedure. 70 Table 3.3 . An outline of stages required for the development of a survey. 75 Table 4.1 . Means, standard deviations and minimum/maximum tree number per 4 hectare square for each housing density. 80 Table 4.2 . Defining features of categories of housing. 83 Table 4.3 . Housing classification categories. 84 Table 4.4 . Land use and surface cover types, showing the relationships between them. 89 Table 4.5. The percentage of tree cover found within different land uses, and the tree cover as a percentage of each land use in pre-1919 semi-detached housing. 96 Table 4.6 . The percentage of tree cover found within different land uses, and the tree cover as a percentage of each land use in pre-1919 terraced onto road housing . 97 Table 4.7 . The percentage of tree cover found within different land uses, and the tree cover as a percentage of each land use in pre-1919 terraced housing with front yard. 99 Table 4.8 . The percentage of tree cover found within different land uses, and the tree cover as a percentage of each land use in pre-1919 terraced housing with front and back garden. 100 Table 4.9 . The percentage of tree cover found within different land uses, and the tree cover as a percentage of each land use in 1919-1959 semi-detached housing. 102 Table 4.10 . The percentage of tree cover found within different land uses, and the tree cover as a percentage of each land use in 1919-1959 terraced housing. 103 Table 4.11 . The percentage of tree cover found within different land uses, and the tree cover as a percentage of each land use in post 1950s semi-detached housing. 104 Table 4.12 . The percentage of tree cover found within different land uses, and the tree cover as a percentage of each land use in 1960s terrace walkway housing. 105 Table 4.13 . The percentage of tree cover found within different land uses, and the tree cover as a percentage of each land use in 1960s terraced driveway housing. 107 Table 4.14 . The percentage of tree cover found within different land uses, and the tree cover as a percentage of each land use in post 1960s terraced housing. 108 Table 4.15 . The percentage of tree cover found within different land uses, and the tree cover as a percentage of each land use in post 1960s court/square housing. 110 Table 4.16. The percentage of surface cover of trees in each appropriate land use. 114 Table 5.1 . Constants used in the Energy Balance Model by previous authors. 124 Table 5.2 . Variable inputs into the Energy Balance Model by previous authors. 125 Table 5.3 . The range of temperatures used in this study to input into the Energy Balance Model for generating likely future temperatures. 127 Table 5.4 . Curve number (CN) of surface covers for soil type C. 128 Table 5.5 . Existing tree cover, potential increase in tree cover and total tree cover for each housing type. 130 Table 5.6 . Existing proportions of surface covers and building mass for each housing type. 133 Table 5.7 . Potential proportions of surface covers and building mass for each housing type. 134 Table 5.8 . Curve numbers (CN) for all housing types for existing surface covers. 146 Table 5.9 . Rainfall storage for an 18mm rainfall event for each housing type, in mm, for existing surface covers. 146 Table 5.10 . Rainfall runoff for an 18mm rainfall event for each housing type, in mm, for existing surface covers. 147 Table 5.11. Rainfall runoff for an 18mm rainfall event for each housing type, in mm, for surface covers with increased tree cover. 148 Table 6.1 . Index of Multiple Deprivation (IMD) scores for Pre Green Streets areas within the Manchester city council area. 155 10 Table 6.2 . Index of Multiple Deprivation (IMD) scores for streets with trees, streets without trees and streets that had a Green Streets project 5 years ago. 156 Table 6.3 . Response rates of individual streets and types of streets 159 Table 6.4 . Responses to the question ‘Do you consider trees to be an important part of your everyday life?’ 161 Table 6.5 . A crosstabulation of answers to the first and last questions. 161 Table 6.6 . Positive statements about trees, ranked by mean agreement level. 163 Table 6.7 . Negative statements about trees, ranked by mean agreement level. 165 Table 6.8 . Percentage of respondents who saw these activities taking place on their street. 166 Table 6.9 . Percentage of respondents who liked certain features of their street. 166 Table 6.10 . Percentage of respondents who saw these problems on their street. 167 Table 6.11 . Percentage of respondents who would like these improvements to their street. 167 Table 6.12 . Responses to the question ‘Do you think presence/planting of trees would affect house prices in your street?’ 168 Table 6.13 . Responses to the question ‘If you think presence/planting of trees would affect house prices in your street, would they be worth…?’ 168 Table 6.14 . Responses to the question ‘If you were to move house, would you try to move to a street with trees?’ 169 Table 6.15 . Responses to the question ‘Do you like the trees in your street?’ 170 Table 6.16. Responses to the question ‘What effects do you think the trees in your street have?’ 170 Table 6.17 . Responses to the question ‘Why do you think your street doesn’t have trees?’. Respondents could tick more than one reason. 171 Table 6.18 . Responses to the question ‘Would you like trees to be planted in your street?’ 171 Table 6.19 . Responses to the question ‘What effect do you think the trees on your street have/will have?’ 172 Table 6.20 . The age range of respondents, with comparison to overall population of Manchester. 173 Table 6.21 . The job status of respondents, with comparison to overall population of Manchester. 173 Table 6.22 . Income levels of respondents. 174 Table 6.23 . The housing tenure type of respondents, with comparison to overall population of Manchester. 174 Table 6.24 . Car ownership levels, with comparison to overall population of Manchester. 174 Table 6.25. The ethnic origin of respondents, in comparison to the overall population of Manchester. 175 Table 6.26 . Qualifications of respondents, compared to the overall population of Manchester. 175 Table 6.27 . A list of statements with statistically significant different mean ranks between different age groups. 176 Table 6.28 . A list of statements with statistically significant different mean ranks between those of differing job status. 177 Table 6.29 . A list of statements with statistically significant different mean ranks by differing income levels. 178 Table 6.30 . A list of statements with statistically significant different mean ranks by differing tenure type. 179 Table 6.31 . A list of statements with statistically significant different mean ranks by car ownership. 180 Table 6.32 . A list of statements with statistically significant different mean ranks by different ethnic groups. 180 11 Table 6.33 . A list of statements with statistically significant different mean ranks by qualification level. 181 Table 6.34 . Positive statements about trees. Statements are paired between countries..191 Table 6.35 . Negative statements about trees. Statements are paired between countries. 193 Table 7.1 . The occurrence of key terms in UK planning policy. Documents downloaded for the Department of Communities and Local Government 199 Table 7.2 . Workshop attendees. 203 Table 7.3 . List of organisations/individuals invited to attend the workshop but were unable to attend/send a representative. 204 Table 7.4 . A comparison of case study areas. 213 Table 7.5 . The potential and achieved numbers of trees for the Green Streets projects.215 Table 7.6 . Tree numbers before and after regeneration. 216 Table 7.7 . The differences in number of residents agreeing to have a tree planted outside their home as part of a Green Streets schemes with and without proactive champions. 222 Table 7.8 . χ2 test for associations for number of residents accepting or declining a tree in streets with and without a proactive Green Streets champion. 222

12 Abstract

The distribution of trees across urban areas of the UK has been shown to be uneven, with lower density residential areas containing many more trees and much higher tree cover than areas of higher density housing. However, in Greater Manchester, tree number within high density housing areas also varies substantially. This thesis sought to explore the reasons for this variation in tree cover, whether tree cover should be increased and if so, how.

The research investigated a potential cause for the variation in number of trees and tree cover within high density housing areas – housing type – for the study area of western Greater Manchester. Eleven different types of high density housing were categorised and all high density housing within the study area was classified as one of these types. Within these housing types, the amount of tree cover was determined, along with the proportions of other surface types. The land uses where the trees were growing were also determined. Finally, the potential increases in tree cover were also calculated for each housing type by a simulated planting technique. Maximum surface temperatures and rainfall runoff were calculated using computer models, for both existing and potential tree cover in each housing type. It was found that urban tree cover varies from 1.6% in pre 1919 terraced housing that opens directly onto the road to 14.8% in 1960s walkway-style housing. Tree cover could theoretically be increased by at least 5% in all housing types, reducing maximum surface temperatures by at least 1°C. In housing types with less than 4% existing tree cover, maximum surface temperatures could be reduced by up to 4.5°C.

The views of residents were determined using a postal questionnaire about urban trees sent to residents of 4 different types of street environment. Residents of all street types surveyed were very positive about urban trees; their attitudes were not affected by whether there are trees in their street or not. The vast majority of respondents considered trees important to their quality of life, and that cost to the council should not prevent tree planting. The views and practices around urban trees and greening by practitioners were determined by running a workshop and their recommendations to increase tree cover are presented. These include changes in funding to include money for tree maintenance after planting, the importance of a full tree inventory and innovative ways to raise funding for trees.

The effectiveness of a community greening scheme at increasing tree cover was compared with two regeneration schemes. The community tree planting scheme was found to deliver tree planting much closer to the potential than regeneration schemes. 13 Declaration

No portion of the work referred to in the thesis has been submitted in support of an application for another degree or qualification of this or any other university or other institute of learning.

Copyright Statement

i. The author of this thesis (including any appendices and/or schedules to this thesis) owns certain copyright or related rights in it (the ‘Copyright’) and s/he has given The University of Manchester certain rights to use such Copyright, including for administrative purposes. ii. Copies of this thesis, either in full or in extracts and whether in hard or electronic copy, may be made only in accordance with the Copyright, Designs and Patents Act 1988 (as amended) and regulations issued under it or, where appropriate, in accordance with licensing agreements which the University has from time to time. This page must form part of any such copies made. iii. The ownership of certain Copyright, patents, designs, trade marks and other intellectual property (the ‘Intellectual Property’) and any reproductions of copyright works in the thesis, for example graphs and tables (‘Reproductions’), which may be described in this thesis, may not be owned by the author and may be owned by third parties. Such Intellectual Property and Reproductions cannot and must not be made available for use without the prior written permission of the owner(s) of the relevant Intellectual Property and/or Reproductions. iv. Further information on the conditions under which disclosure, publication and commercialisation of this thesis, the Copyright and any Intellectual Property and/or Reproductions described in it may take place is available in the University IP Policy (see www.campus.manchester.ac.uk/medialibrary/policies/intellectual- property.pdf), in any relevant thesis restriction declarations deposited in the University Library, the University Library’s regulations (see www.manchester.ac.uk/library/aboutus/regulations) and in The University’s policy on presentation of Theses.

14 Acknowledgements

I would like to thank my supervisors John Handley and Roland Ennos for their thoughtful comments, helpful feedback and continued enthusiasm throughout my research. I also extend my thanks and gratitude to the University of Manchester’s ‘Your Manchester’ alumni support scheme, for their generous funding of this research.

I would also like to thank Peter Stringer and Kevin Wigley at the Red Rose Forest for their help and support for the Green Streets based sections of this research. I would also like to thank Marek Isalski, Anna Gilchrist, Jo Wilkes and Andrew Speake for their excellent help in surveying residents, and John Hewson for help with cumulative frequency graphs.

Thanks also to the members of CURE for help, encouragement and tea during the first half of my PhD, particularly Graeme Sherriff, Nick Green, Anna Gilchrist and Gina Cavan, and thanks to Sam Hayes, Jeni Hall and Vikki Wesslowski for discussions and cake during the second half of my PhD.

15

‘The tree which moves some to tears of joy is in the eyes of others only a green thing that stands in the way.’ William Blake, The Letters , 1799

16 Chapter 1 – Introduction

Trees have been part of the urban landscape for many centuries, in gardens, open land and streets. Within the city, there are clearly areas with larger numbers of trees than others, but precise reasons for this distribution of trees are unclear. The land available for tree planting will limit the number of trees that can grow in different parts of a city; the space available for tree growth may also limit their size, reducing potential canopy cover. Other factors such as the attitudes of residents, developers and policy makers may also influence the level of tree cover in urban areas.

At first glance the uneven distribution of trees across an urban area may seem a minor concern for residents and policymakers. It may be assumed that the only effect of trees is to increase house prices and improve business and shopping areas to increase rental rates and customer satisfaction (e.g. Tyrvainen and Miettinen, 2000; Laverne and Winson- Geideman, 2003; Kaufman and Cloutier, 2006; Wolf, 2008). However, there is a large amount of research that demonstrates that trees have many more effects on an area than directly measurable economic benefits.

Trees can improve air quality by removing pollutants, particularly PM 10 s, from the environment (McPherson et al., 1994; Nowak et al., 2006; Bealey et al., 2007; McDonald et al., 2007; Jim and Chen, 2008). This ecosystem service has been calculated to remove 711,000mt of pollutants across the USA, which is valued at US$3.8 billion (Nowak et al., 2006). This reduction in air pollution can have a particularly noticeable effect for those with asthma and other respiratory problems (e.g. Thach et al., 2010; Wood et al., 2010).

Trees can intercept a large amount of rainfall directly and use more water through transpiration, so reducing the amount of water that flows into sewer systems and reducing the risk of pluvial flooding (King and Harrison, 1998; Xiao et al., 2000; Samba et al., 2001; Gomez et al., 2001; David et al., 2006; Guevara-Escobar et al., 2007; Stovin et al., 2008; Bartens et al., 2009). For example, it has been calculated that over the course of one year, the tree cover of the city of Garland, Texas, USA, prevented 540,000 m 3 of rainfall reaching drainage systems. Building storm-water drains and storage for that amount of water would cost over $38 million (Anon., 2000). The trees therefore save the city $2.8 million annually in infrastructure building and maintenance costs (Anon., 2000).

17 Trees cool their surroundings through shading effects and evapotranspiration (e.g. Kjelgren and Montague, 1998; Akbari et al., 2001; Shasuhua-Bar and Hoffman, 2004; Georgi and Zafiriadis, 2006; Watkins, 2007; Tsiros 2010). These effects are already very important in warm climates, and will become increasingly important in the UK as temperatures increase due to climate change. Gill et al. (2007) used computer modelling to demonstrate that increasing tree and other vegetation cover by just 10% in Greater Manchester, a conurbation in the UK, mitigated all but the most extreme increases in surface temperature predicted under climate change. Trees planted around a home have been shown to reduce energy demand for heating and cooling (McPherson et al., 1994; Hilderbrant and Sarkovich, 1998; Simpson and McPherson, 1998; Akbari, 2002; Solecki et al., 2005) which both reduces energy bills for the homeowner and reduces peak demand and emissions at the power plant supplying the energy (Akbari, 2002).

A growing body of research is demonstrating the positive effects that trees can have on urban residents’ physical and mental health and social interaction. People, particularly children, living near good quality greenspace generally exercise more and have lower body mass indexes and self-report better general health than those living further away (Coen and Ross, 2006; Roemmich et al., 2006; Agyemang et al., 2007; Mitchell and Popham 2007, 2008; Bell et al., 2008; Bjork et al., 2008). Any physical activity within greenspace has been shown to be beneficial for mental as well as physical health (Burls 2007; Parr, 2007; Pretty et al., 2007; Lafortezza et al., 2009). Many studies show faster recovery from illness, stress and mental fatigue with contact and/or views of trees and other natural settings (e.g. Ulrich, 1984; Nicholson-Lord, 1987, p.45; Hartig et al., 1991; Ulrich et al., 1991; Tennessen and Cimprich, 1995). Other studies demonstrate the residents’ appreciation of importance of the ability to escape from everyday stresses into a park and to meet friends and neighbours there (Guite et al., 2006; Cattell et al., 2007). The presence of well maintained trees and greenspaces around people’s homes makes them feel safer (Kuo et al., 1998; Prezza et al., 2005; Maas et al., 2009) and in these areas both property and personal crime is reduced (Kuo and Sullivan, 2001).

This broad selection of research demonstrates that an unequal distribution of trees across an urban area leads to an unequal distribution of the many benefits trees give to both the environment, to individuals and to a community. Therefore, seeking an equitable distribution of urban trees will enable all residents to benefit equally.

18 This thesis seeks to understand the factors influencing tree distribution within high density housing areas in Greater Manchester, UK. Previous research has shown that high density housing has the lowest number of trees and lowest tree cover compared to medium and low density housing (Land Use Consultants, 1993; Handley et al., 2000; Britt et al., 2008), but that this can vary greatly between areas of high density housing (Tame, 2006; Tratalos et al., 2007). Therefore, there must be factors other than housing density which influence tree distribution. This thesis examines some of these potential factors and explores the potential for increasing tree cover in high density residential areas.

1.1 Aims and Objectives of the Thesis

The aim of this thesis is:

To understand the differential provision of tree cover in urban residential environments, the changes in environmental quality that trees confer and the policies and practice that affect tree provision.

This will be achieved through the following four objectives:

1. To explore the nature of variation in tree cover and its causes in residential environments.

2. To examine the influence of actual and potential tree cover on environmental quality of high density residential neighbourhoods in a changing climate.

3. To examine the interdependence between tree cover and residents’ attitudes to it in high density residential areas.

4. In light of objectives 1-3, to inform policy and practice with regard to tree provision in high density residential areas.

Chapter Two presents the literature review. It begins by demonstrating the range of benefits that trees provide to the urban environment and urban residents. This is followed by an exploration of the factors affecting the distribution of trees and greenspaces within the urban environment, including socioeconomic factors, urban morphology and resident 19 attitudes. Potential factors for protecting and increasing urban tree cover are also discussed.

Chapter Three presents an overview of the research methodology, the study area selection and the conceptual framework of the thesis. In order to facilitate understanding of the research design and its application in achieving the stated objectives, detailed methodology is included in the relevant chapter for each thesis objective.

Chapter Four presents research undertaken to achieve Objective One. In this objective, housing types are characterised and delineated, and proportions of surface covers and land uses are calculated. Results are presented for both the 11 housing types and the study area overall.

Chapter Five presents research undertaken to achieve Objective Two. In this objective, guidance for the planting of new trees is outlined, and a representative sample of each housing type is ‘planted’ with trees. The changes in tree cover this will give are calculated, and potential maximum surface temperature and rainfall runoff with current and potential tree cover is calculated.

Chapter Six presents research undertaken to achieve Objective Three. In this objective, residents of streets with old street trees, no street trees, recently planted street trees and street trees planted five years ago were surveyed to determine if street type and attitudes towards trees are related. A similar study undertaken in the USA is compared to the results to determine if there are differences between British and American attitudes to trees in their respective locations.

Chapter Seven presents research undertaken to achieve Objective Four. Results of discussions at a practitioner workshop are presented, which explore opportunities and barriers for increasing tree cover in urban areas. Uptake levels for a community led street greening project are analysed for correlations with housing type, levels of deprivation and an environmental index. The treatment of trees and greenspace are investigated in two recent regeneration schemes of high density housing.

Chapter Eight presents a discussion of the findings of the thesis, placing them in a broader research context. Potential implications of the research are also discussed.

20 Chapter Nine gives the conclusion of the thesis. It summarises the research findings, outlines recommendations for increasing tree cover in high density housing areas, reflects critically on the methodology and discusses further work that may be undertaken to further explore the issues surrounding trees in high density housing areas.

21 Chapter 2 – Trees in the Urban Environment

This chapter summarises research relating to many facets of urban trees, and their distribution in urban areas. Section 2.1 gives a general introduction to trees in urban areas. Section 2.2 summarises the research investigating the benefits of trees in urban areas for air pollution, rainfall runoff, temperatures and people. Section 2.3 describes factors identified in the literature as contributing to the distribution of urban trees in residential areas. Section 2.4 investigates potential factors for protecting and increasing urban tree cover that have been identified by the literature. The conclusions of this chapter inform the research presented in the following chapters, and in particular the Conceptual Framework in Section 3.1.1. The literature from this chapter is revisited in Chapters 8 and 9 in light of the findings of the research.

2.1 Introduction

Trees are a common but decreasing sight within urban areas. There are fewer trees in the urban environment than surrounding rural areas, but there are often more trees than people believe. This may be due to people ‘taking for granted’ the presence of trees, instead focussing on the activities around the trees (Lawrence, 2008, p. xii) or because trees are more common in private gardens and parks rather than streets and squares which people may consider more ‘part of the city’. Trees have been recognised as part of city landscapes for nearly four hundred years, and can greatly influence the character of individual cities, particularly London, Paris and Amsterdam (Lawrence, 2008, p. xi). When thinking of these cities the presence of trees is central to their landscape character, and without trees the cities would look very different. This may also be said about any urban area with trees, though this quality is not often noticed until the trees are threatened or have been felled.

There is an ever-growing amount of research that highlights the benefits of having trees in urban areas, for both the environment and for urban residents. However, the space available for trees to grow is determined by the layout of roads, buildings and green areas, and has changed over the years. Therefore, tree distribution is not equal across the whole urban area, which means some areas have less access to the benefits of trees than others.

22 2.2 The Benefits of Trees in Urban Areas

Trees were originally planted as aesthetic landscape features, appreciated for their own sake. However, over recent decades the effects of trees in cities beyond being ‘something nice to look at’ have been studied, analysed and quantified. This research has shown that trees affect their environment, and the humans within that environment, in a range of sometimes unexpected ways. Researchers are only now beginning to investigate and quantify the extent and magnitude of the many benefits associated with urban trees and forests as well as the many ties between urban forests and the quality of life for urban residents outlined by Dwyer et al., in 1992. Urban forests need to be viewed as ‘living technology’, a key component of the urban infrastructure that helps maintain a healthy environment for urban dwellers (Dwyer et al., 1992). Trees are living things, taking in elements from their environment, synthesising them into materials for respiration, growth and reproduction, and expelling waste products back into the environment. Trees take in carbon dioxide (CO 2) and other gases from the air, and water and other elements from the soil. CO 2 and other gases are waste products from human activity which can lead to pollution. In addition, excess water in cities can lead to localised flooding. As trees take in these potentially problematic elements it is beneficial to have trees growing in cities to give a more pleasant environment.

2.2.1 Trees and Air Quality

Trees take in carbon dioxide and emit oxygen through stomata in their leaves as part of the photosynthetic process. On a global scale, this is what allows almost all life to flourish. What is less well known is that trees absorb other gases, including the urban pollutants carbon monoxide (CO), sulphur dioxide (SO 2), nitrous oxides (NO x), ozone

(O 3) and small particulate matter (PM 10 ) (McPherson et al., 1994; Nowak et al., 2006). Removal of these air pollutants is an important ecosystem service (Jim and Chen, 2008). Trees are efficient scavengers of both gaseous and particulate matter (Bealey et al., 2007; McDonald et al., 2007). These gases may be taken into the leaf through the stomata or deposited onto the leaf and stems via dry deposition (McPherson et al., 1994; Nowak et al., 2006). This then provides a base for further chemical reactions to occur which can break down the pollutants, or the pollutants become re-suspended in water and washed away (Nowak et al., 2006). Therefore, trees are able to reduce levels of pollution and increase air quality in urban areas. Pollutant removal can be increased by planting more

23 trees, diversifying the species present, diversifying the biomass structure and properly managing the trees (Jim and Chen, 2008).

The removal of PM 10 from the air in cities is an important part of improving air quality. A research group at the Centre for Ecology and Hydrology, UK developed a computer modelling programme which simulated planting trees in appropriate locations and calculated possible reductions in PM 10 that were likely to occur. McDonald et al. (2007) used this model for the conurbations of the West Midlands and Glasgow, both in the UK, to determine the effectiveness of using trees to reduce PM 10 concentrations. The models found that a realistic increase in tree cover, given the physical constraints on space for tree planting and growth, could decrease PM 10 concentrations by 10% in the West

Midlands and 2% in Glasgow; planting all green spaces with trees could reduce PM 10 concentrations by 26% in the West Midlands and 17% in Glasgow. There was less space to plant trees in the Glasgow study area, which was also surrounded by other heavily polluted areas; this is likely to account for the lower figures seen here. Bealey et al., (2007) developed the model into a tool for planners to use when examining planning applications. The model was used to simulate new development and the increases in pollution it could bring, and trees were added in to reduce this pollution. It was found that while planting trees can reduce the concentration of PM 10 across a whole local authority area, the most polluted areas do not always have space for tree planting. Therefore, new development in polluted areas should plant trees around the development, or elsewhere in the city if this is not possible, to reduce their impact on the local air quality. High density residential areas in conurbations like Greater Manchester frequently coincide with areas of poor air quality (Handley, pers. comm., 2007) and this is one of the factors that stimulated this research and choice of study area.

It is estimated that trees across the mainland United States remove 711,000mt of pollutants, which is valued at US$3.8 billion (Nowak et al., 2006). The cost for maintaining these trees is highly unlikely to reach this figure, so trees are therefore a very cost effective measure for improving air quality. The long term benefits of trees in terms of monetary value are more than twice the cost of planting and maintenance over the long term (McPherson et al., 1994). In the past, potential benefits of the urban forest have been underestimated, so planning and management efforts have been less effective than they could have been (Dwyer et al., 1992).

24 Conversely, trees can emit chemicals known as biological volatile organic compounds

(BVOCs) which can contribute to the formation of ozone (O 3) (Chameides et al., 1988). These BVOCs are biogenic non-methane hydrocarbons, predominantly isoprene and α- pinene, which react via photo-oxidation with NO x to produce O 3 (Chameides et al., 1988).

They can also break down to produce CO (McPherson et al., 1994). O 3 formation from BVOCs increases as the temperature increases (Cardelino and Chameides, 1990), which suggests higher levels of O 3 are likely as the temperature increases due to climate change. However, the cooling effects of trees should reduce the overall temperature if enough are planted, thus reducing the amount of O 3 produced. A study of an area of similar climate, from Washington D.C. to central Massachusetts, USA, found that trees in urban areas generally reduced O3 levels, but when urban and rural areas were combined O 3 levels tended to increase overall (Nowak et al., 2000). Increasing urban tree cover across this area from 20% to 40% in a computer model indicated an average decrease in hourly ozone concentrations in urban areas during daylight hours of 1ppb (2.4%) with a peak decrease of 2.4ppb (4.1%) (Nowak et al., 2000). This research suggests that even though trees release a small amount of chemical pollutants, their cooling effects can reduce the total amount of pollutants, particularly O 3, created by their emissions. A number of studies in the UK have also noted small decreases in NO 2, SO 2 and O 3 due to the presence of urban trees and greenery (Handley and Gill, 2009).

McPherson et al. (1998) found that in a small scale study in Sacramento, California, USA, trees can reduce pollution in a local area, particularly of ozone and PM 10 , but the reductions in these pollutants are offset by emissions of BVOCs from the trees themselves. Therefore, the paper concluded that there is not convincing evidence that a large scale residential yard tree planting programme will be cost effective if based solely on the reduction of air pollution. However, Nowak et al. (1998) strongly dispute this result, citing problems with McPherson et al.’s (1998) methodology and suggesting a range of others to use. In Santiago, Chile, trees are being used to reduce the concentration of PM 10 s in the air of the city. Escobedo et al. (2008) used Nowak et al.’s (1998) methods and found that managing the urban forest appropriately for PM 10 reduction was a cost effective way to reduce these particles when compared to other strategies, when scored using World Bank efficiency criteria. In the UK, the health benefits arising from reduced particulates and improved urban air quality have been considered an important economic benefit of trees and greenspaces (Willis and Osman, 2005).

25 2.2.2 Trees and Water

Trees take in large amounts of water, and can be an effective store of water during storms rather than water running-off into sewerage and drainage systems. Isolated trees in urban or forest environments have been shown to intercept 100% of a brief rainfall event (Xiao et al., 2000), around 22% of a typical rainfall event (Samba et al., 2001; David et al., 2006), around 3% of more extended storms (Xiao et al., 2000) or between 7% and 25% of annual rainfall (Gomez et al., 2001). In Mexico, an isolated evergreen Ficus tree in an urban area intercepted 59.5% of rainfall and was saturated in an average of 19.5 minutes, after which the canopy began dripping (Guevara-Escobar et al., 2007). In the UK, a study found that an isolated oak tree ( Quercus robur) can intercept between 50 and 70% of rainfall around the centre of the tree, between 30 and 50% over its wider canopy and between 10 and 30% of rainfall over a wider area due to sheltering effects (King and Harrison, 1998). Tree cover therefore can be directly related to the amount of storm- water in an urban drainage or sewerage system after a rainfall event (Stovin et al., 2008); more trees means less storm runoff. It has been calculated that the 11% tree canopy cover of the city of Garland, Texas, USA, reduces storm-water runoff by 540,000 m 3; building storm-water drains and storage for that amount of water would cost over $38 million (Anon., 2000). The trees therefore save the city $2.8 million annually in infrastructure costs (Anon., 2000). The costs of tree planting therefore can be justified on a flood prevention basis alone (Stovin et al., 2008). Combining storm-water storage and tree planting may further reduce the amount of storm-water passing into urban drainage systems and also allows the tree extended rooting space. Bartens et al. (2009) found that two fairly flood tolerant tree species grew well in this combined system; they used stored water for transpiration and grew best when the storage emptied slowly over a 48-hour period. This demonstrates the potential for further increasing the amount of storm-water that trees can intercept, therefore reducing the strain on the sewerage system in high rainfall events. A form of this is already commercially available in the Netherlands, where porous lava is used to fill tree pits extending the length and width of the pavement area, allowing much greater tree rooting space, preventing soil compaction and giving some rainfall storage within the lava grains (Tree Ground Solutions, no date). Although more study is needed for species specific effects, it is clear that rainfall and storm-water interception is one of the most important effects trees have on an urban environment.

The transpiration rate and crown temperatures of trees, and therefore the cooling effect and water demand, can vary depending on the species and the surface over which they

26 are growing. Trees which grow over an asphalt surface have a higher transpiration rate and significantly higher crown temperatures than comparable trees growing over grassed areas (Kjelgren and Montague; 1998; Leuzinger et al., 2010). It is suggested that this higher transpiration rate is due to interception of greater long wave radiation reflected from the warm asphalt surface up to the tree, compared to the cooler irrigated grassland with less radiation (Kjelgren and Montague, 1998). Trees over grassland therefore may be up to 25°C cooler (Kjelgren and Montague, 1998). Species with larger leaves have generally higher leaf and crown temperatures compared to smaller leaved trees and trees which had cooler crowns in temperate conditions (25°C) were not the coolest in much hotter conditions (40°C) (Kjelgren and Montague, 1998; Leuzinger et al., 2010). These aspects can increase transpiration until stomatal closure, although different species transpire at different rates. Species differences should be noted when selecting tree species for urban areas, particularly as summer drought is likely to increase with climate change.

These studies highlight the importance of trees in the hydrological cycle of urban areas, and suggest that trees currently play a large role in reducing urban flooding and this role could be increased. A reduction in runoff may be particularly high during heavy summer storms; both interception and transpiration rates are high as the maximum canopy cover uses a large amount of water to photosynthesise and respire in the increased heat and sunlight levels. Tree selection for urban areas should be driven by the likely temperature changes and the desired purpose for the tree; in areas of possible flooding, trees with high interception and/or transpiration rates may be favoured to decrease storm-water levels, while in areas of possible drought trees with lower transpiration rates may be favoured, despite their lower evaporative cooling effects.

2.2.3 Trees and the Urban Heat Island Effect

Urban areas are subject to a phenomenon called the ‘urban heat island effect’, which means that the urban area is generally a few degrees warmer than the surrounding rural area. London for example has been shown to be up to 7ºC warmer than the surrounding rural area 20km away (Watkins et al., 2007). This heating effect is exacerbated by the use of cooling devices which cool the inside of buildings but heat the outside (Fan and Sailor, 2004). The effects of climate change are predicted to increase temperatures by at least 2ºC worldwide (IPCC, 2007), with some localised temperatures even higher (Watkins et al., 2007). This will lead to intensification of the urban heat island effect, with

27 temperatures in cities making residents uncomfortable and decreasing their quality of life. Even without accelerated climate change, an analysis of the past 100 years of temperature data for a number of US cities found that cities have warmed by between 0.5°C and 3.0°C (Akbari et al., 2001). In 2009, 50% of the world’s population lived in urban areas (Population Reference Bureau, 2009), and this will increase in future years. As the majority of the world’s population will live in urban areas when the full effects of climate change occur, finding ways to cool these areas efficiently without use of artificial devices such as air conditioning units is essential.

Trees have been shown to cool their immediate environment through transpiration and shading effects (e.g. Akbari et al., 2001; Shasuhua-Bar and Hoffman, 2004; Georgi and Zafiriadis, 2006; Watkins, 2007; Tsiros 2010). Trees prevent solar radiation from reaching concrete surfaces which warm and store heat for a long time (Akbari et al., 2001). Trees cool their environment through water loss during transpiration (Kjelgren and Montague, 1998), although this does increase the relative humidity directly around the tree (Georgi and Zafiriadis, 2006). Air temperatures under the canopy of trees can be 1.7°C to 3.3°C cooler than the surroundings (Taha et al., 1988, cited in Georgi and Zafiriadis, 2006), and over a summer the average temperature reduction can be 3.4°C (Parker, 1989, cited in Georgi and Zafiriadis, 2006).

Gill et al. (2007) used computer modelling to demonstrate that increasing vegetation by just 10% in Greater Manchester, a conurbation in the UK, mitigated all but the most extreme increases in surface temperature predicted under climate change. A significant increase in the number of urban trees can moderate the intensity of the urban heat island by altering the heat balance of the entire city (Akbari, 2002). Vegetation, and particularly trees, have been shown to be efficient and cost effective in reducing energy bills for homes in the USA, as homes are shaded in summer and protected from wind in winter (e.g. McPherson et al., 1994; Hilderbrant and Sarkovich, 1998; Simpson and McPherson, 1998; Akbari, 2002; Solecki et al., 2005).

The cooling and sheltering effects of trees may be exploited to reduce residents’ energy bills. In Sacramento, California, USA, the position and size of trees around houses was studied to determine the most cost effective location of the tree. It was found that any sized tree to the west of the house is most cost effective at shading the house and reducing energy consumption, followed by medium or large trees to the south, south- west or south-east but with much lower levels of efficiency (Hilderbrant and Sarkovich,

28 1998). In winter, the sheltering effects of trees are most cost effective to the north, north- west, south-east and south-west (Hilderbrant and Sarkovich, 1998). A separate study in the same area found that an average of 3.1 trees per property reduced annual and peak cooling energy demand, giving $14 of savings each year (Simpson and McPherson, 1998). A study in Chicago suggested that three trees in appropriate locations around a property gives maximum benefits in terms of energy savings, reducing heating and cooling energy demands by 5 to 10%, with street trees planted to the west of buildings reducing energy demands by 2 to 7% (McPherson et al., 1994). A study in three medium- sized US cities (Sacramento in California, Baton Rouge in Louisiana and Salt Lake City in Utah) found that planting four trees around each home would, through lower energy demands, reduce carbon emissions from power plants by 41000 tonnes, 16000 tonnes and 9000 tonnes respectively (Akbari, 2002). This means that each urban tree planted can, each year, avoid combustion of 18kg of carbon, plus taking in and storing 4.5 – 11kg of carbon (through carbon dioxide) for photosynthesis and growth (Akbari, 2002). When considering carbon emissions therefore, each urban tree is equivalent to 3 to 5 forest trees (Akbari, 2002). This research shows that trees can indirectly influence air quality by reducing energy demand for cooling which then reduces emissions from local generators and power plants, as well as reducing the levels of airborne pollutants as discussed previously. A study in Athens, Greece, on an extremely hot day found street trees gave a cooling effect between 0.5 to 1.6°C at 1400 (LST) and from 0.4 to 2.2°C at 1700 h (LST), and therefore a reduction in air conditioning use during the day by 2.6-8.6% and during peak hours by 2.9-9.7% (Tsiros, 2010), again reducing emissions from local and regional power generators. This study also shows that cooling effects remain considerable even when it is unlikely that the tree is transpiring. Similar results were found in La Paz, Mexico, where well planned and planted urban trees with dense branches and foliage were found to be extremely effective at reducing solar radiation reaching buildings, greatly reducing their cooling demand (Gómez-Muñoz et al., 2010).

The amount of vegetation in an urban area affects the surface temperatures. A study in Phoenix, Arizona, USA, found that surface temperature correlates primarily with an index of vegetation cover (Jenerette et al., 2007). Surface temperature also correlates with social characteristics; for every $10,000 increase in average income of an area, a 0.28°C reduction in surface temperature was seen. Variations in temperature, for example between hot roads and pavements and cool vegetated gardens, were lowest in areas of high population density (Jenerette et al., 2007) which is generally associated with low income areas. This shows that increasing vegetation in high density housing areas is very

29 important for moderating the worst effects of temperature increases due to climate change. Community wide, trees can account for a 25% increase in cooling effects (Akbari, 2002).

2.2.4 Trees and Human Physical and Psychological Health

Trees and the natural world provide benefits to humans that cannot be easily quantified using a cash value. Urban trees grow in man-made streets, but also grow in the more natural spaces of parks, gardens and other greenspaces; thus, the benefits of trees alone cannot be separated from the benefits of these natural areas. Trees tend to be considered to add to the quality of parks and greenspaces, and research suggests that high quality greenspaces provide the highest benefits to people. These benefits can be physical, psychological and social, and are often subconscious benefits which people are not immediately aware of.

Trees and Physical Health

A now seminal paper by Ulrich (1984) demonstrated that post-surgical patients with a view from their bed of a stand of deciduous trees recovered faster and requested fewer painkillers than those with a view of a brick wall. Although in this study there were only 46 patients in total, 23 in each group, similar studies support this finding of faster recovery from illness and stress with contact and/or views of trees and other natural settings (e.g. Hartig et al., 1991; Ulrich et al., 1991; Tennessen and Cimprich, 1995). This suggests therefore that people living and working in areas with trees and greenspace will feel less stressed, more relaxed and friendlier due to their contact with natural surroundings than those living and working in very urban areas.

A study in the Netherlands found that residents in neighbourhoods with high levels of psychosocial stressors (nuisance from neighbours, drug misuse, youngsters frequently hanging around, rubbish on the streets, feeling unsafe, dissatisfaction with green space) rated their own health significantly poorer than residents in neighbourhoods with less of these stressors, independent of any other factors (Agyemang et al., 2007). Therefore, improvements in green space and other social factors could potentially improve residents’ self rating of their health. Similarly, Mitchell and Popham (2007) found that a higher proportion of greenspace in an area was generally associated with better self- reported health in the UK. However, this association varied according to the combination

30 of income deprivation and urbanity; high income areas showed no association between green space and health, while in suburban lower income areas, a higher proportion of green space was associated with worse health. This suggests that quality rather than quantity of green space may be more important, and that areas of deprivation need investment into higher quality trees and parks in order to see health benefits associated with access to these facilities. A further study by these researchers (Mitchell and Popham, 2008) found that people suffering income deprivation but with higher access to green space were healthier than those experiencing similar deprivation levels but with lower greenspace access. This suggests that green space may be able to ameliorate many of the poor health issues associated with low income areas, or at least help those suffering with health issues feel better due to a more pleasant environment.

Urban parks can provide an area for recreation among trees and other natural features. Physical activity gives physical health benefits, but undertaking these activities in a natural area gives psychological benefits too. Pretty et al. (2007) examined ten ‘green exercise’ case studies across the UK and found that green exercise led to a significant improvement in self-esteem and gave more stable moods. Surprisingly, improvements in self esteem and mood were not related to the type, intensity or duration of the exercise, suggesting that any activity for even a short time in a green space is highly beneficial for people.

Green exercise may become more popular as temperatures rise due to climate change and the urban heat island effect intensifies; people can escape the high temperatures and also remain active. Lafortezza et al. (2009) studied physical and psychological benefits and general well-being associated with the use of green spaces to people when these heat stress episodes are more likely to occur. They found that visiting green spaces more often and for longer periods of time gave higher perceived benefits and increased well being for users and reduced periods of heat stress. Results also suggest that green spaces offering shaded locations and accessible water could benefit people and, at some extent, alleviate symptoms of thermal discomfort under heat stress conditions. This work also found that the amount of physical activity performed during the visit was correlated with higher benefits and well-being perceived by users, echoing Pretty et al.’s (2007) findings that green exercise is also highly beneficial in non-physical ways. A walk or jog along a cool, shaded tree-lined street is likely to give a similar relief from heat stress as parks.

31 These studies demonstrate a link between greenspace and physical health. Higher quality greenspace, which includes trees, can give more benefits than lower quality greenspace. It is evident that a link between greenspace improvement objectives and health improvement objectives, particularly mental health and physical activity promotion, in terms of priority and funding would be highly beneficial for both.

Trees and Psychological Health

Views and experiences of nature have been shown to decrease people’s stress and anger, and afterwards they report feeling happier and calmer. Students at Delaware University rated how they felt after completing an exam, then were shown photographs of either urban or natural scenes and asked to rate how they felt again. It was found that viewing urban areas significantly increased feelings of sadness, and increased feelings of anger and aggression. In contrast, those that looked at the natural scenes reported feeling friendlier, more affectionate, more carefree and significantly less fearful (Ulrich, 1979). Hartig et al. (1991) found that people who had been on a hiking holiday (‘green exercise’) in a wilderness area reported that they were happier over a longer period of time after their holiday, despite an initial dip just after returning, than those who had been on a non- hiking holiday or those who had not had a holiday. The dip in happiness levels just after the hikers returned home was proposed to be related to feelings of unease about returning to the polluted concrete city (Hartig et al., 1991). This is similar to the findings of Pretty et al. (2007) where green exercise gave more stable moods. In a separate experiment, Hartig et al. (1991) induced cognitive fatigue in a group of individuals who were then sent on either a nature walk, a city walk or told to relax in a comfortable chair. Those who went on the nature walk reported higher levels of happiness than either of the other study groups. Ulrich et al. (1991) conducted a similar experiment, measuring physiological signs and self reports of feelings and stress, where participants were shown a stressful video followed by either images of trees and natural settings or of traffic and people in urban settings. Those shown nature views recovered faster (evident within 5 to 7 minutes) from the stress than those shown urban views. Tennessen and Cimprich (1995) examined the restorative power of views of nature on university students living in halls at a college in the Midwest of the USA. They theorised that views of trees and a natural setting would reduce mental fatigue; students with this type of view from their study room would perform better on a test of directed attention than those with a more urban view. Of the 72 students studied, those with a view of nature from their window performed better than those with a view of buildings or roads (Tennessen and Cimprich,

32 1995). This restorative effect is also seen when people visit a park for as little as 30 minutes, with participants recording changes in mood from tired or anxious to relaxed and energised (Hull 1992). Fuller et al. (2007) showed that this restorative effect is increased as both the perceived and actual plant and animal biodiversity of the visited park increases.

Working and recreation in green areas with trees has been shown to have positive effects on mental health. Burls (2007) found that participants in park improvement schemes for people with mental health issues improved not only their own mental health but also increased their social capital by meeting others in the parks and improved the parks for the local community. Burls (2007) suggests that this is a huge opportunity for joined up policy to both improve green spaces and help those with mental health issues. This is emphasised by a study by Parr (2007) who reviewed historical and current practices of using horticulture and gardening as a treatment for mental health disorders, and found that programmes which improve green space or grow produce can aid programme participants to increase their social capital and feelings of social inclusion and wellbeing, and also benefit both the trees and plants they tend and the local community.

In Greenwich, London, Guite et al. (2006) sent a postal questionnaire to residents to explore the strength of association between physical and social factors in the built environment and mental well-being. This found that dissatisfaction with access to green spaces was a significant factor in respondents’ rating of their mental health and wellbeing. The authors noted that the ability to escape from problems like neighbour noise and over- crowding in the home to an accessible green space is an important part of mental well being. A similar need to escape to the quieter surroundings of nearby greenspace and trees was also found in a study of residents along busy roads in Sweden (Gidlöf- Gunnarsson and İhrström, 2007).

These findings all show how important trees and green spaces are to the thoughts and feelings of urban residents. Taken together, they show that much more effort should be concentrated into improving and maintaining the quality of urban parks, green spaces and street trees in order to benefit urban residents and reduce the stresses associated with the fast pace of urban life or the problems of deprived neighbourhoods. The environment around areas when concentration and stimulation are most important, such as schools, offices, nursing homes and hospitals, are areas where the improvement of natural spaces could be most useful.

33 There is also growing evidence for more conscious effects of trees and green spaces. A study of housing choices in Detroit (Kim et al., 2005) found that for residents with children, access to greenspace and recreational opportunities were more important to them than their commuting distance; the environment was rated more highly than job accessibility. A study looking at access to recreational trails found that almost half of the regular users of these trails reported that living near these trails and other parks was important to them in choosing a place to live (Librett et al., 2006). This means that homes near parks, forests, recreational trails and in a generally pleasant leafy environment are more desired places to live, and this is seen through increases in house prices nearer these locations (e.g. Tyrvainen and Miettinen, 2000; CABE Space, 2005; Kaufman and Cloutier, 2006). People have been shown to prefer landscaped roadsides and report positive retail behaviour associated with roadside shops, such as willingness to pay 8.8% more for goods and services in well-landscaped shopping areas with trees (Wolf, 2008). This preference for landscaped areas is also seen in increases to business rental rates in areas of high quality landscaped areas (e.g. Laverne and Winson- Geideman, 2003; CABE Space, 2005).

Access to greenspace can make the biggest difference to the poorest people (London Sustainability Exchange, 2004), particularly in densely populated areas (O’Brien, 2006). Woodlands are inexpensive places for poorer families to visit, so are particularly appreciated in these areas (O’Brien, 2004). These urban woodlands also make a significant contribution to urban tree cover (Britt et al., 2008). People have mental and emotional benefits from visiting woodlands and experiencing contact with nature, and a visibly ‘cared for’ environment can have an important positive impact on how people perceive, act in and enjoy particular spaces (O’Brien, 2006). These benefits are quite intangible to those who set the budgets for greenspace and tree management in poorer areas but can make a very real difference to those who live in the area. A study of 100 residents of a very poor inner city housing development in the US found that they were very supportive of trees being planted in concrete expanses around their development (Kuo et al., 1998). This study found that a maintained natural area made residents feel safer, regardless of the density or arrangement of trees. Dense trees made non residents (council administrators and police officers) feel more unsafe than residents (Kuo et al., 1998), suggesting that a more general feeling of being unsafe in the whole neighbourhood, rather than concern for residents or their environment, was affecting funding and management opportunities for greening in this case. Dense undergrowth, a common aspect of unmaintained natural areas, was found to make residents feel unsafe

34 (Kuo et al., 1998). Further studies have confirmed this link between more vegetation and fewer crimes. Kuo and Sullivan (2001) found that across 98 inner city apartment blocks, residents in blocks surrounded by more vegetation reported fewer property and violent crimes. A Dutch study of nearly 84,000 people found that more green space around people’s homes is associated with enhanced feelings of social safety, except in very strongly urban areas where enclosed green spaces are associated with reduced feelings of social safety. This may be linked to poor levels of maintenance suggesting an uncared for and ignored area (Maas et al., 2009), echoing Kuo and Sullivan’s (2001) findings that maintained areas of greenspace makes people feel safe while unmaintained areas do not. Mothers in greener areas allow their children greater freedom to play as they feel safer (Prezza et al., 2005). These studies show that increasing street greenery, particularly with trees, can increase feelings of safety and decrease levels of crime.

The research outlined above shows that access to green spaces is very important for reducing stress caused by living in densely populated, noisy urban areas. The presence of well maintained trees in urban areas makes residents feel safer; therefore, they are likely to use an area more. This can decrease both crime rates and perceptions of crime as the area is busier and watched by more people.

Trees and Preference for Greenspace Design

Studies of opinions of greenspace design show that a naturalistic design without evidence of extensive human involvement is generally preferred (Jim and Chen (2006) in China; Ozguner and Kendle (2006) in the UK; Bullock (2008) in Ireland; Budruk et al. (2009) in India). A naturalistic approach incorporates a large number of trees and lots of vegetation; therefore, a preference for this style indicates preference for a large number of trees. However, for a small number of people a naturalistic environment is seen as intimidating or even frightening (Ozguner and Kendle, 2006) where correct behaviour is unclear (Rishbeth and Finney 2008). The size of a park also changes people’s preferred features; in small parks, play areas and a mix of quiet and busy areas were preferred, while in large parks adventure play areas and ample walking and seating facilities were preferred, although areas of woodland are desired in both park sizes (Bullock, 2008). Areas for recreation were also seen as important (Jim and Chen, 2006). Additionally, Budruk et al. (2009) found that those with high place attachment also held pro-environmental opinions, suggesting that attachment to natural areas increases care of the wider environment. These studies suggest a mix of formal and natural areas with many trees and areas for

35 walking and sport, would be most beneficial to urban residents, either within one park or in different parks. These areas would therefore be well used and fears of crime or antisocial behaviour should decrease.

2.3 Factors Affecting the Distribution of Urban Trees

The concept of ‘environmental justice’ states that all people have the right to live and work free from the threats of pollution, contamination and other environmental hazards (Bullard and Johnson, 2000). It focuses on access to environmental ‘goods’ and protection from environmental ‘bads’ for all of society, not just those who can afford it. Environmental ‘goods’ include access to green spaces, trees, clean air and clean water. Environmental ‘bads’ include exposure to pollution through air and/or water, lack of access to green spaces and lack of trees. The research detailed above outlines the many benefits that trees can have on the environment of an urban area and the benefits they can give to residents and the community. An uneven distribution of trees across an urban area would mean that not all urban residents may benefit from trees in an equal way, leading to environmental injustice and inequity.

A growing number of studies have investigated the distribution of trees across urban areas. In the USA, Talarchek (1990), Iverson and Cook (2000), Jensen et al., (2004), Perkins et al., (2004), Solecki et al., (2005), Heynen et al., (2006), Troy et al., (2007), Landry and Chakraborty (2009) and Laudry and Pu (2010) have all noted that tree and other vegetation cover was unevenly distributed across residential areas of New Orleans, Chicago, New Jersey, Terre Haute (Indiana), Milwaukee, Tampa (Florida) and Baltimore (Maryland). The authors almost exclusively cited socioeconomic differences as major factors in the uneven distribution of trees, with richer areas containing higher tree cover than poorer areas. The issue of housing density and its effects on tree cover was briefly addressed by Iverson and Cook (2000) and Solecki et al. (2005) who both found that areas of higher housing density contained less tree cover. However, much less attention has been given to specifically exploring urban morphology or housing type as a factor affecting the distribution of trees.

In the UK, tree cover has been analysed intensively within just Greater Manchester (Handley et al., 2000; Tame, 2006) and Sheffield (Barbosa et al., 2007; Davies et al., 2008), although comparative surveys between cities have covered many more areas (Land Use Consultants, 1993; Tratalos et al., 2007; Britt et al., 2008). Unlike the US 36 researchers, housing density as a factor affecting tree distribution has been more widely explored in the UK. Areas of high density housing have been shown by this research to have the lowest tree cover; medium density housing had more tree cover, and low density housing had the highest levels of tree cover. Sociodemographic effects have been studied in conjunction with aspects of the residential environment, unlike the US research.

The emerging research demonstrates that there is a clear difference in the distribution of trees across urban residential areas. However, it is less clear which specific factors or combination of factors contribute to this difference.

2.3.1 Socioeconomic Factors Affecting the Distribution of Urban Trees in the USA

The first paper to be published exploring possible explanations for unequal distribution of trees and other vegetation, based on research carried out in New Orleans, USA, proposed that the social status and age of housing could be a factor in the amount of tree cover and vegetation in a residential area. Talarchek (1990) looked for associations between the percentage of urban forest present and 16 socioeconomic variables in a range of residential areas. The percentage of surface cover types was calculated, focussing on tree and vegetation cover, and this was related to socioeconomic data for that area. The socioeconomic data included household income, car ownership, job type, whether residents were single or married, housing tenure, size of house and other factors. Overall, the data showed that the distribution of urban forest in these areas of New Orleans is positively associated to the social status of those areas, with higher status neighbourhoods having higher tree and vegetation cover. Talarchek also suggested that older neighbourhoods have higher vegetation cover purely because the vegetation had had longer to establish and grow. It is important to note that there was no attempt to produce generalisations from this research; Talarchek noted that the results were only applicable to the study area of New Orleans, which may be reflected elsewhere but would need further study.

Income levels are linked to social status, and this therefore is also a factor which may affect the distribution of trees in urban residential areas. Jensen et al. (2004) investigated leaf area index, a measure of tree and vegetation cover, using remote sensing methods across Terre Haute, Indiana, USA. This study found that residential areas with higher leaf area indices were associated with higher incomes and higher property values, although the authors cautioned that it was unclear which variable came first. Again this suggests

37 higher tree cover in richer residential areas and lower tree cover in poorer areas, possibly with lower levels of home ownership. Similarly, Iverson and Cook (2000) found that in the Chicago area, residential areas with 3 to 4 times the average wage of the region have the highest percentages of vegetated space. Conversely, Heynen and Lindsay (2003) found that in central Indiana, USA, tree canopy cover was not correlated with median household income. These inconsistent correlations therefore suggest that income may not be a reliable indicator of tree canopy cover in all residential areas.

A further factor affecting tree cover in urban areas may be the housing tenure of the residents. In Milwaukee, USA, Perkins et al. (2004) found a statistically significant negative correlation between rentership rates and residential canopy cover and a statistically significant positive correlation between household income and canopy cover. Looking back to Talarchek’s (1990) work, this does not seem surprising. However, it is unclear how tree canopy data was calculated, as only the resulting distribution map is shown. Perkins et al. (2004) also looked at participation in a tree planting scheme around homes, and found only 11% of scheme participants were renters. This suggests that those who rent are less interested in trees or do not want trees around their home; therefore, areas with large numbers of renters may be areas with few trees. Alternatively, as trees were to be planted on the land around residents’ homes, only long term renters or homeowners would reap the benefits associated with the trees; short term renters may have felt there was little point in them taking part in a scheme they would not benefit from.

Some studies have attempted to combine the factors affecting tree cover identified above with the racial origin of residents to demonstrate the existence of both social and racial injustice. However, the results vary between urban areas. Heynen et al. (2006) found that in Milwaukee, USA, tree canopy cover increases with income, fewer vacant properties, more white residents and fewer Hispanic residents, but found that rentership rates and the percentage of black residents were not significant indicators of tree canopy cover. The correlations between income and fewer vacant properties (indicating a richer area) are expected, but the conclusions about the effects of non-white residents are contradictory. Conversely, a study in Tampa, Florida, USA, found a significantly lower proportion of street tree cover in neighbourhoods containing a higher proportion of African-Americans, low-income residents, and renters (Landry and Chakraborty, 2009). A later study in a similar area by Landry and Pu (2010) found that tree cover decreases with increasing housing density, increasing numbers of Hispanic residents and lower levels of home

38 ownership, while proportion of African American residents was not significant. A study in Baltimore, Maryland, USA, examined the proportion of potential garden space around homes that could grow trees that actually was growing trees, and found that this was positively related with the proportion of African American residents; the more African American people in an area, the nearer to the potential maximum number of trees were found (Troy et al., 2007). This suggests that African Americans are proactive gardeners and encourage trees around their homes, thereby increasing tree cover in their neighbourhood. However, research discussed earlier found there were fewer trees in areas of large African American populations; it may be that they live in areas where there is little potential to plant trees but that any potential space is planted, or that other factors are affecting tree cover in areas of non-white populations.

The research presented here shows consistent links between low tree cover and low incomes and/or low home ownership levels. These links are therefore likely to be replicated in other areas, while other factors such as race are likely to only have effects in some urban areas. Indeed, the strongest correlations with tree cover in Landry and Chakraborty (2009) were income and housing tenure. It is much more likely therefore that non-white residents live in poorer areas of cities because they are poor rather than they are non-white, and tree cover is affected by the status of a neighbourhood and not the racial composition of its residents.

2.3.2 Socioeconomic Factors Affecting the Distribution of Urban Trees in the UK

The UK is a much smaller and older country than the USA, with higher population density and more established patterns of urban settlement. Therefore, comparisons with studies in the USA examining tree cover across urban areas are useful in highlighting potential factors, but findings cannot be generalised to the UK.

Income levels in the UK appear to be correlated with other measures of environmental quality, not just tree cover. A study in Sheffield, UK, found that as distance from public greenspace increased, wealth levels increased, though this is a weak correlation (Barbosa et al., 2007). This is mirrored by the finding that more deprived groups, who tend to live in older housing without gardens or with small gardens, live closer to public green spaces, with elderly people having the greatest access to these areas. This suggests therefore that richer people have access to more private open space while poorer people have access to more public open space. The issue of greenspace quality was not addressed in this study;

39 public greenspace may be of poorer quality with fewer trees than private gardens, leading to a decline in use of the park and fewer people benefitting from greenspace benefits, while rich people can control and improve their gardens to fully exploit the benefits of greenspace and natural environments described above. Related to this, a study by Tratalos et al. (2007) in five cities in the UK found that higher tree cover, particularly in gardens, was associated with a larger proportion of residents in the most educated and affluent social class. When combined with Barbosa et al.’s (2007) work, this suggests that poorer people have access to fewer trees but larger and closer areas of tree-less greenspace than richer people. A similar study in Greater Manchester, UK, Tame (2006) found that areas of general deprivation, health deprivation and low incomes were more likely to have the fewest number of urban trees compared to less deprived, healthier areas.

The small amount of research carried out in the UK and outlined here has demonstrated clear differences in the distribution of trees across urban residential areas in the UK, in patterns similar to the research findings in the USA. Similarly to the USA, tree cover is lower in areas of lower incomes.

2.3.3 The Effects of Housing Density and Land Use on the Distribution of Urban Trees

It is self evident that housing density will affect tree cover. A low density layout with a high percentage of vegetated space obviously allows much more space for trees than a high density layout with a high proportion of impervious surfaces. A small number of studies have explored the effects that housing density, housing layout and the surrounding environment have on tree cover and distribution.

Housing density has been shown by a small number of studies to be a factor in the amount of greenspace in residential areas. Iverson and Cook (2000) classified surface covers in and around Chicago, USA, into ten classes. Topographical maps and aerial photos were used by the ISODATA program to automatically classify the land, which was then related to housing density using simple product moment correlation. This found that areas of higher density had less greenspace and vegetation cover. Projections of housing density for ten year’s time suggested a continuation of current trends of increasing density in the city, combined with increased urban sprawl. The authors expressed concern that further urban sprawl threatens the existence of both urban trees and greenspace and the unspoilt land outside the current urban area, unless development is carefully done.

40 Solecki et al. (2005) used CITYgreen, a GIS-based modelling application, to investigate the effects of increasing vegetation cover and increasing albedo in six residential areas of two towns in urban New Jersey, USA. These areas differed in vegetation cover, housing density and average income. The model showed that increasing tree cover decreases energy demand for cooling. The research showed that richer neighbourhoods were also areas of lower density housing, and contained the most amount of vegetation and the most space for future tree planting. In comparison poorer neighbourhoods contained higher density housing and had less room to plant trees. This means that the poorer neighbourhoods will be less able to plant more trees and therefore benefit from the cooling effects of trees and the subsequent reduction in energy bills, a particular benefit for those on low incomes. As climate change leads to increased temperatures, particularly in summertime, measures to redress the unequal distribution of trees and their cooling effects should become a higher priority for social justice reasons.

Heynen and Lindsay (2003) explored tree canopy cover in relation to a number of different variables across 60 urban areas in central Illinois, USA. This found that areas have more tree canopy cover if their surrounding area has a high level of tree cover, has older housing stock, has both more land and land with slopes greater than 15%, and has denser stream networks. The findings are similar to Nowak et al.’s (1996) findings about the influence of surrounding ecosystems on a city’s vegetation. Areas with more land unsuitable for development due to steepness or flood risk will contain more trees due to natural colonisation processes from the surrounding natural areas of tree cover. Trees associated with older housing are likely to have been planted when the house was built, therefore growing into large trees with large canopies. However, it does suggest that areas left undeveloped for whatever reason in urban areas can contribute greatly to tree cover.

Housing density and the age of housing can have an effect on the number of trees in an urban area. Jim and Liu (2001) found that in Guangzhou City, China, residential areas developed more recently have more trees than older areas, and that these trees are planted more densely, mainly due to lower housing densities. Jim and Chen (2003) analysed tree cover and land use in Nanjing, a city in China. They found that tree cover is significantly related to land use, site conditions and urban development, and also related to levels of home ownership. Jim and Chen (2009) found that in Taipei, a city in Taiwan, tree species diversity was higher than in neighbouring secondary forest. Species diversity was highest in parks with a range of landscapes and habitats but lowest in streets; both the most tree

41 species and most individual trees were found in the older parts of the city. The fewest trees were found in newer industrial areas, where the authors noted little attention had been paid to urban greening. This suggests that tree planting by residents, or due to pressure by residents, to brighten and add variety to their street has greatly contributed to both tree cover and tree diversity.

The effects of both housing density and land use on tree distribution across urban areas have been studied in the UK. Handley et al. (2000) found that tree distribution varies significantly between differing land uses and housing densities; high density housing had the lowest number of trees of any land use, while low density housing had the second highest. Other land uses included managed and unmanaged open space, transport corridors and commercial land. Similarly, in the USA a study of 58 US cities found tree cover in urban areas was highest on vacant land, in parks and in residential areas (Nowak et al., 1996). This highlights the potential that residential areas can have in protecting and increasing tree cover in urban areas, but also the missed opportunities and environmental deprivation of residential areas with few trees.

Housing density is usually highest towards the centre of a city and lowest in the outer suburbs. Tratalos et al. (2007) examined three residential areas along an urban gradient from centre to suburb for five cities in the UK. They found that higher housing density was associated with less tree cover in gardens, and small gardens in any area were less likely to contain trees. A study in Sheffield similarly found that the amount of greenspace was negatively correlated with the density of buildings and the length of roads, and tree cover was negatively correlated with the density of housing, with higher density housing containing less tree cover (Davies et al., 2008). For comparison, a nationwide study found that across 147 towns and cities in England (Britt et al., 2008), low density housing had the highest density of trees and shrubs, while high density housing had the lowest, showing that both Greater Manchester (Handley et al., 2000) and Sheffield (Davies et al., 2008) are comparable with the rest of England.

Tame (2006) used Handley et al.’s (2000) data to examine tree distribution in high, medium and low density housing, finding differences in tree number which were associated with a number of socioeconomic variables. Further analysis of this data shows that housing density is the most significant indicator of tree number; higher density housing indicates lower tree number. However, whereas some high density housing areas had hardly any trees, some areas had higher numbers of trees than some areas of medium

42 or low density housing. This suggests that there may be significant differences between different types of high density housing which influence tree distribution which have not yet been investigated. This thesis seeks to address this question.

2.3.4 The Effects of Housing Layout on the Distribution of Urban Trees

Tame (2006) showed that there were large variations in tree number in areas of high density housing within Greater Manchester, UK. As this housing is of a similar overall density, there must be other factors affecting the tree density, such as the space available for tree planting and growth within different housing layouts and different ages of developments. The trends and preferences affecting high density housing therefore needs to be explored in order to understand how trees and greenspaces have been planned within the housing, and how differing housing design trends may have affected the amount of tree and greenspace cover in varying types of housing. Surprisingly, no other study has looked at this in detail; this thesis therefore presents a brief history of presence and potential for trees and greenspace within the design and type of high density housing found in the UK, and the effects of changing legislation throughout the century.

The First Urban Trees and Parks and their Surrounding Housing

The idea of planting trees in order to alleviate problems caused by dense human settlement and industry was first suggested by John Evelyn, in his book ‘Fumifugium’ published in 1661. He suggested that the factories should be moved away from London, and that sweet smelling trees and plants be planted in their place and in other areas of London to make the air smell sweeter and improve people’s quality of life (Evelyn, 1661, p.6-7). It took until the increasing industrialisation of Britain in the 1800s and concurrent increase in population and pollution in cities for his ideas to be carried out on a large scale. In 1833 the Government set up the Select Committee on Public Walks (Conway, 1991), belatedly recognising that walking had become a national pastime since the Tudor era (Henneberger, 2002). This Select Committee reported that there was a recognisable need to provide public open spaces in which people could walk and spend their increasing leisure time away from the pollution of industry (Conway, 1991). This report helped to spur the municipal park movement during the middle of the 1800s with numerous philanthropists donating money or land in order to create tree-filled public parks (Conway, 1991, p.3). In 1841 the development of Birkenhead Park started, widely acknowledged as the first fully funded public park (Henneberger, 2002). The park’s

43 development and upkeep was funded both by the local municipal authority and by the sale of building plots along the landscaped edges of the park, plus taxes raised indirectly from residents (Henneberger, 2002). The site was previously undesirable, uneconomic land and was set aside by the authority for the specific purpose of affording a space for leisure and recreation of its residents (Henneberger, 2002). The park was opened in 1847, and in 1995 was declared a Grade 1 Listed Historical Landscape (Wirral Council, 2008).

Birkenhead Park served as an example for other municipalities to create their own public parks and inspired other park planners such as Frederick Law Olmstead, the creator of New York’s Central Park (Henneberger, 2002). The idea of housing around these parks, with the park sometimes extending into the housing through landscaped squares and avenues, was influential in Victorian planning and building thought and social reform. Robert Owen, a Welsh manufacturer turned reformer, saw the public park as the centrepiece of a residential development, with dwellings in landscaped surroundings containing trees and other vegetation and connected to squares containing various meeting halls and community facilities (Henneberger, 2002). This was in stark contrast to the prevailing housing of the time, the so-called ‘byelaw’ terraces (Figure 2.1), which were arranged in strict grid patterns of long two or three story terrace housing (Hawkes and Souza, 1981) containing little public space (Burnett, 1991).

Figure 2.1. Two examples of ‘byelaw’ terraces in Manchester, UK, built pre-1919. (Source: 1:10,000 OS map, within a GIS).

44 The Garden City and its Influence on Housing Layout

Another reformer and campaigner against these ‘byelaw terraces’ was Ebenezer Howard, who in 1898 proposed his ‘Garden City’ idea, a self contained community of 1000 acres and about 30,000 residents within 5000 acres of agricultural land. The houses would have large gardens with plenty of recreational areas and trees planted in avenues along the main streets, which were arranged in concentric circles around a central park and commercial area (Howard, 1898). This idea proved to be very influential, with two ‘Garden Cities’ and numerous ‘Garden Suburbs’ built in the first part of the 20 th century, and new housing estates leaving room for recreation areas and trees (Colquhoun, 1999). Architects Raymond Unwin and Barry Parker designed the houses and layout of Letchworth Garden City (1902) and Hampstead Garden Suburb (1906), avoiding the monotonous grid patterns of previous ‘byelaw’ housing (Burnett, 1991, Figure 2.1) and using the existing landforms, trees and hedges to inform the layout (Figure 2.2). These cottage estates with their integration of home and garden captured the imagination of the British public, remaining popular today and influencing many other similar estates (Colquhoun, 1999).

Figure 2.2. A street map of an area of Letchworth Garden City, Bedfordshire, UK. Note the much lower density and lack of straight roads and crossroad junctions compared to Figure 2.1. (Source: 1:10,000 OS map, within a GIS).

After the First World War, new housing laws were enacted to ensure that new homes were of a minimum standard, with a specific layout and distance between rows of properties. Semi-detached houses and short terraces in densities not exceeding those of the Garden Cities and Suburbs (12 per acre, 30 per hectare for the urban working class),

45 in rows 70ft/21m apart were recommended by the Tudor Walters Report of 1919, of which Raymond Unwin was a prominent member (Burnett, 1991; Colquhoun, 1999). Culs-de-sac were a popular way of laying out these estates, as first used at Hampstead Garden Suburb in 1906 by Unwin and Parker (Colquhoun, 1999). The Addison Act (1919) enacted many of the report’s recommendations. However, this was later followed by the Wheatley Housing Act (1924) which reduced subsidies for house building which, coupled with the recession, led to a reduction in quality of both new homes and the landscape surrounding them (Smith, 1989; Burnett, 1991; Colquhoun, 1999)

Howard’s idea of surrounding a town with agricultural land to limit development and demarcate it from other urban areas proved very influential. The 1929 plan for London suggested a ‘green girdle’ of open space around the outskirts of the city (Turner, 1995), similar to Howard’s vision of Garden Cities. Some of this land was purchased, but little was opened up to the public and the ring was never completed (Turner, 1995). However, the ‘green girdle’ or ‘greenbelt’ around urban areas, limiting their growth and sprawl, passed into law in 1955 stating that there should be greenbelts around urban areas which are protected from development (Hardy, 1991), as suggested by Howard’s Garden City plan. This policy remains in place today. Raymond Unwin had become a great believer in the benefits of open space to the population through his work with Howard, and was a technical advisor to the 1929 London plan. In the plan it was suggested that a standard of seven acres of playing fields per one thousand people should be present throughout London (Turner, 1995). Sadly, this was never enacted, but the idea of set amounts of recreational areas for a set number of people was to prove influential.

The County of London Plan by Abercrombie and Forshaw in 1943 examined in detail appropriate housing densities (Hawkes and Souza, 1981) and the possible layouts that housing and associated recreational areas might take. It was recommended that for every 1000 residents there should be 4 acres of open space available for recreational purposes; lower than the 1929 plan but generally much higher than residents at the time could access.

New housing within existing urban areas was rarely considered in conjunction with provision for green and open spaces or street trees. Entire new towns, as proposed in the New Towns Act of 1946, could plan onto an empty site and offered the opportunity to plan housing with recreational areas and greenspace incorporated into them. Some Garden City principles were followed in this Act (Rudlin and Falk, 1999) which, along

46 with the 1947 Town and Country Planning Act, cemented the ideas of governmental control over development and the planning of new communities. Thirty two ‘New Towns’ were created in total across the UK (Hall, 1973). The so-called ‘third wave’ of New Towns were particularly influenced by Garden City ideals in their efforts to avoid the mistakes of previous developments (Hall, 1973; Rudlin and Falk, 1999). Milton Keynes was built around an extensive network of parks, open spaces and greenways for cyclists and pedestrians (Milton Keynes Council, 2004), while Warrington’s New Town Outline Plan stated that the town should contain 1.6 hectares (3.95 acres) of public open space per thousand residents (Warrington Borough Council, 2006) almost reaching the standards set for London by Abercrombie’s 1943 Plan. However, these were exceptions to the prevailing push for development, and the consideration and provision of green spaces in new urban areas remained poor (Burnett, 1991).

The Modernist Influence

During the 1920s and 1930s the Modernist Movement in Europe influenced architects working in the UK. These architects designed single or small groups of houses for those who could afford it (Gould, 1977). The main features of these houses were outer walls with a smooth finish and no exposed brickwork, large windows allowing views to the garden or sea (Modernist buildings were particularly popular in seaside areas) and a sun terrace for occupants to enjoy ‘health giving sunshine’ (Gould, 1977). However, local authorities largely ignored this trend, and speculative builders, who built the vast majority of houses in the inter-war period, merely added in some Modernist touches to their houses, competing with other neo-Georgian and neo-Victorian motifs (Gould, 1977; Burnett, 1991). This is a shame, as the focus on enjoying the views around and of the garden was important to many residents, and could have led to much more focus on the natural environment around the home by the speculative builders. However, the public’s continuing preference for homes with a garden in a landscaped space meant that speculative estates were generally well provided with trees and greenspace (Burnett, 1991), particularly as the private sector built almost exclusively semi-detached dwellings (Hawkes and Souza, 1981). In contrast, public sector (‘council’) housing tended to be built in short terraces of between four and six houses (Hawkes and Souza, 1981, Burnett, 1991), which gave less opportunity for garden space than semi-detached housing, but much more than the previous ‘byelaw’ housing.

47 Post War Rebuilding and Increasing Housing Densities

During the 1940s and 1950s the Government lowered standards of house building, which allowed more homes to be built, at lower standards, for the same price (Burnett, 1991). This was particularly important as many new dwellings were needed to house those whose homes had been destroyed by wartime bombing and to house the growing population. The next 30 years saw an explosion in house building; mixed use developments remained until the late 1950s, when high density, often high rise, housing only estates were developed (Colquhoun, 1999). These were favoured by local authorities as they could reduce population loss in cities and produced a range of new housing types: the 4- or 6-storey maisonette, the high rise block of flats in rectangular, Y- shape, T-shape or cruciform layouts and a revival of terraces of 6 or more homes (Burnett, 1991). Dense housing was favoured, though high rise blocks were acceptable when a higher population density was required, particularly in major city centres (Hawkes and Souza, 1981). This often meant that greenspace was forfeited for car parking and access roads, leaving flat-dwellers with little or no outside space and contact with nature (Figure 2.3).

Figure 2.3. A block of flats within a high density housing area in Gorton, Manchester. Note the small patch of grass to the left which is the only vegetated area around the flats. The trees are part of a separate development.

48 The desire for high density housing led to the common layout of 1960s council housing of short terraces (and often high rise flats) only accessible by a walkway (Figure 2.4), with car parking in a square sometimes a minute or more walk from the house itself, influenced by the Radburn estates of the 1930s in the USA (Burnett, 1991; Colquhoun, 1999, Rudlin and Falk, 1999). This type of housing was not widely liked by residents (Colquhoun, 1999) who expressed dissatisfaction with both the general appearance and character of the high rise buildings and the Radburn style estate and the way the public realm was looked after (Burnett, 1991), but the layout did provide more homes with a front and rear garden which could be designed and planted with trees and shrubs to the resident’s taste. However, more emphasis was placed on the planning of communal leisure and play areas in an attempt to create neighbourliness perceived to have been destroyed by high rise living (Burnett, 1991; Rudlin and Falk, 1999).

Figure 2.4. An example of 1960s housing in Gorton, Manchester, which is only accessible on foot. There is no road access to the rear of the properties either.

A further influence on council housing was the ‘Housing Cost Yardstick’ that combined costs and minimum space standards (Hawkes and Souza, 1981; Colquhoun, 1999): in other words, how cheaply the minimum legal standard house or flat could be built. These standards were derived from the Parker Morris Report of 1961, but were unable to keep up with rising inflation and meant new council homes became very simple in layout (Hawkes and Souza, 1981). This coincided with the reaction against high rise flats (Burnett, 1991), and led to local authorities instead building low rise high and medium 49 density estates from the 1970s onwards, using more traditional designs and methods (Hawkes and Souza, 1981; Rudlin and Falk, 1999) rather than the industrialised and pre- fabrication methods of the preceding years (Colquhoun, 1999). The recommendations of the Parker Morris report were never fully taken up by the private sector, but were mandatory in the public sector until 1980 (Smith, 1989).

Regeneration, 1980s Onwards

From the beginning of the 1980s to the present day, the focus of housing strategies has been regeneration: of pre-1919 houses, of unsuccessful 1960s estates and tower blocks, of run down mixed use town centres, of abandoned industrial sites and crumbling buildings. Government and private sector money was pumped into schemes to regenerate these failed areas. Investigating the causes of riots in poor, decaying council estates, the Scarman Report (HMSO, 1981) concluded that they were in part a product of an alienated society that felt it had little control over its life and surroundings. The report recommended that to avoid a repetition of these riots, residents had to be included in the management and regeneration process of their area. This led to the development of a range of methods for regeneration of housing with community involvement, linking residents, tenants, councils and Housing Associations with private sector finance (Colquhoun, 1999). This has led to a large number of projects regenerating areas of neglected low demand housing with the inclusion of the existing residents. A flagship project of this type was the regeneration of Hulme, Manchester, from failed 1960s massive ‘Crescent’ tower blocks to an area of low rise mixed tenancy and mixed housing types, with the housing preferences of residents taken into account (Colquhoun, 1999, Manchester City Council, 2008). A new park was built, many homes contained private or communal gardens and street trees were planted along many of the new residential roads (Colquhoun, 1999; Manchester City Council, 2008). Another large example is in Tower Hamlets, London, where the redesigning of housing and road layouts provided larger pockets of greenspace (Colquhoun, 1999). These examples are promising, but still reflect a general neglect of the landscape and environment of housing for those of lesser means, while those who can afford to buy a home tend to buy a semi-detached house in a lower density private sector built estate (Rudlin and Falk, 1999) where more attention has been paid to the landscape around the house.

This brief history of high density housing design and building demonstrates that some thought has been given to the provision of trees and greenspace within different housing

50 types, but this thought does not seem to be consistent. Some housing types have more greenspace and potential for trees than others due to their fundamental design. This relationship between urban design and greenspace provision is important but seems to have received limited study, particularly with regard to trees. Clarifying these relationships is a key feature of this thesis.

2.3.5 Attitudes and Awareness of Residents about Urban Trees

Campaigning against environmental hazards has united communities and led to large community action groups being formed in order to protect areas from pollution (Bullard and Johnson, 2000). However, community action on a similar scale is not generally seen when residents campaign for access to environmental ‘goods’, such as more trees or a new park. It may be hypothesised that this is related to the importance placed on trees by the residents; if residents (particularly in poorer areas) do not value trees then they will not treat trees with respect, attempt to save trees or demand that more trees are planted in their area. However, the small amount of research in this area does not back this up.

In a summary of his own research in the USA, Schroeder (1989) reported that a range of his studies have shown that residents enjoy the beauty and tranquillity of natural environments; 99 percent of respondents thought parkway trees were an asset to the community; park and street trees were ranked second only to education programs in priority for receiving additional funding; trees on streets were rated as more important than trees in yards, parks, and wooded areas; removing hazardous trees and controlling insect and disease problems was rated higher in importance than planting new trees; 84 percent of the people said they thought maintenance of parkway trees was adequate, but in a survey in an area suffering municipal budget cuts only 14 percent said that tree maintenance was good or excellent. The aesthetic contribution and shade were rated as the most important benefits that urban trees provide in a number of Schroeder’s studies, with a combination of flowering trees and large shade trees being particularly liked. This is not surprising, as trees can soften urban areas and provide people with contact with nature, and the surveys were carried out in areas of high summer temperatures, where cool, shaded areas are highly valued. Further work by Schroeder and Ruffalo (1996) found that residents’ perceptions of trees around their home and in their street were very positive, and benefits are rated more highly than annoyances. As with Schroeder’s previous work, residents showed a preference for large shade trees from a number of species, disliking a monoculture of street trees.

51 Lohr et al. (2004) conducted a telephone survey of around 1000 adults in a range of US cities, asking whether they agreed or disagreed with seven positive statements and seven negative statements about urban trees. Data about age, gender, ethnic origin, education and income were also collected. Statements were rated on a 1 to 4 scale from ‘strongly disagree’ to ‘strongly agree’. The statements were ranked according to the mean response and 95% confidence intervals. The data about respondents’ gender, age, education, income, ethnic background and childhood environment were analysed using χ2 tests to determine if these variables affected views regarding urban trees. It was found that all residents appreciate and are aware of the benefits of urban trees, regardless of their background. Negative statements regarding possible problems with urban trees were overwhelmingly disagreed with and not seen as reasons not to plant trees. Those with lower income or education level, of African American descent or under 21 were slightly less likely to agree strongly with the positive statements about trees, but still tended to agree with the statements. A similar telephone survey by Zhang et al. (2007) found that 98% of respondents across Alabama, a US state, recognised that trees provide positive values, including aesthetics, shade, and improved air quality to people and their communities, and 75% of respondents stated that the presence of trees was an important factor in choosing both their home and local area. This found that individual characteristics such as race, gender, and residence were not statistically significant factors in explaining attitudes towards trees and the urban forest. The results are similar to those of Lohr et al. (2004) who found only small differences in attitude between some socioeconomic groups.

Gorman (2004) conducted a similar survey to Lohr et al. (2004) in a small college town in Pennsylvania, USA. Surveys were posted to two differing groups of residents, those with a tree outside their home and those without, according to a recent tree inventory. There were 11 positive statements about urban trees and 11 negative statements. Residents were asked to rate the statements on a 1 to 4 scale, of no benefit/annoyance to great benefit/annoyance. The data was analysed using t-tests to look for differences between the ratings of the positive and negative statements, and χ2 tests were used to look for differences between the views of residents with or without a tree in front of their house. Gorman (2004) found that residents value trees highly; those that have a tree outside their home value urban trees slightly higher than those without, though this is not a significant difference. Giving shade and aesthetic pleasure were the most popular benefits of trees. Residents rated safety issues associated with trees (e.g. branch falls) as their highest concern. This work suggests that the value residents place on trees is not

52 closely related to their immediate environment, which is particularly important when considering the views of residents of tree-deprived areas.

Studies of this kind are less common in the UK and their results contrast somewhat with the findings of the researchers outlined above. Hitchmough and Bonugli (1997) conducted a doorstep survey of residents in four tree-less streets in a medium sized town in southwest Scotland. Even though there were no trees in their immediate surroundings, residents felt that adding street trees would improve the appearance of their street; in the two affluent areas planting street trees was seen as the most important factor in improving street appearance, but the least important in a poorer street with mainly older residents. However, most residents were generally happy with their street in its current form, and overall there was little support for tree planting on their streets. This may be due to other factors such as traffic and litter being seen as more pressing problems than lack of greenery in the street. The findings of this study are in contrast to many studies in the USA, which tend to show a lot of support for tree planting, particularly of shade trees. Hitchmough and Bonugli (1997) suggest that this difference is likely to be due to weather patterns in the studied area – other research on residents’ views on trees is generally based in areas with hot and dry summers so any shade is welcomed (e.g. Chicago, USA – Schroeder and Ruffalo, 1996; Melbourne, Australia – Williams, 2002). Southwest Scotland however, is ‘damp, grey and cool’, so shade is not generally necessary, and may be seen as an annoyance when blocking out what little sunshine is present (Hitchmough and Bonugli, 1997).

Schroeder et al. (2006) compared residents’ attitudes towards trees in the USA and the UK, using the results of two previously published research papers. Their findings echoed those of Hitchmough and Bonugli (1997), though the UK study group rated shade as less of a benefit and found annoyances more serious compared to the US group. Again, differing climate was cited as a reason for this difference, as were differences in urban morphology; in the US study area the front gardens were larger, meaning street trees were further away from homes and so negative effects would be lessened but positive effects (shade, aesthetics and so on) would still be present. Data on income levels was incomplete in both studies, but it was stated that all areas were classified as white middle-class.

Hitchmough and Bonugli (1997) and Schroeder et al. (2006), admittedly from contrasting perspectives, propose that climate has a large role to play in the valuing of urban trees by

53 residents. The support of residents is likely to be an important factor in the success of tree planting schemes, particularly in improving tree survival rates after planting and reducing vandalism of trees. The effect of climate should be remembered when beginning tree planting in residential areas, so residents can get the sorts of trees they will appreciate, and hopefully protect.

Veseley (2007) asked residents of 15 cities in New Zealand to consider the impact of a reduction in tree cover around their homes of 20%, and what they may be willing to do to stop this loss of trees. 52% of residents thought that the current number of trees was about right, while 46% thought there were not enough trees. Over 90% of respondents felt that the aesthetic benefits of trees around their homes were important or very important, while other factors of providing shade, carbon storage and protection from wind and noise were seen as less important. Surprisingly, trees causing drainage problems was seen as the most problematic issue of tree around homes. This is in stark contrast to research that demonstrates trees intercepting large amount of rainwater, therefore preventing flooding and drainage problems. However, it is possible that the concern relates to root damage of sewer infrastructure rather than problems with surface standing water as the question was not explicit. The dropping of leaves was perceived to be the least important problem associated with trees, which suggests leaves clogging gutters and causing problems with rainwater is not seen as a problem. More than half of respondents stated that the benefits of trees were the most important reason they wanted to care for trees in their area. 84% of respondents stated that they felt a loss of 20% of their neighbourhood trees would have a serious effect on the area, showing a great concern for the trees and the impact their loss would have. Respondents in this study were very supportive of benefits and rated potential issues with trees as generally of low importance.

In South Korea, the average preferred size for street trees was found to be 6.6m high and 2.3m diameter when measured in combination with other aesthetic preferences for a street (Lee, 2009). Respondents most preferred a street view or vista which contained 40% vegetation, 13% sky, 13% road, 9% pavement and 25% building. This suggests that respondents are willing to have less road or pavement space in return for larger trees and more space for shrubs and other greenery. The preference for large street trees was also found by Schroeder (1989) and Schroeder and Ruffalo (1996) in similarly warm climates, indicating a potential global preference for large shade trees in warm climates.

54 Fraser and Kenney studied the views of residents of four distinct cultural groups in Toronto, Canada (Fraser and Kenney 2000). British, Chinese, Italian and Portuguese immigrants were interviewed about trees around their home and in the local area. British residents were the most supportive of trees, having shade trees on their property and aspirations to plant more. Italian and Portuguese residents preferred fruit trees and did not like their gardens being shaded by trees outside their property. The Chinese did not like trees at all. These finding were seen to be consistent with the prevailing landscape management techniques of the respondent’s cultural origins. This suggests that British UK residents are likely to be quite supportive of trees, but that UK residents of other cultures may not be as supportive of trees and tree planting schemes. This should be considered when looking for reasons why tree cover varies across different areas.

2.4 Potential Factors for Protecting and Increasing Urban Tree Cover

The research highlighted above demonstrates the range of benefits trees provide to urban areas and urban dwellers, and that trees are not evenly distributed across urban areas. There are a range of factors that can explain the current differences in tree cover, but no research has suggested that this difference in tree cover is permanent and unchangeable. It follows therefore that there must be ways of protecting and increasing the existing tree cover in urban areas. The following section outlines the small amount of research examining factors which can aid the increase of tree cover.

2.4.1 Effects of Municipal Regulations

The presence or absence of a proactive local council and effective planning regulations for tree planting and protection can greatly affect tree numbers and cover in urban areas. If trees are protected from damage or removal by local laws and the local authority are proactive in planting more trees, then tree cover can increase.

Schroeder et al. (2003) and Treiman and Gartner (2004) surveyed those responsible for municipal trees and tree care in local communities (similar to local authorities in the UK) in Illinois and Missouri respectively, two states in the USA. Both researchers found most communities, particularly small communities, lack basic information on tree care and do not employ anyone specifically to care for the community’s trees. Surprisingly, many areas did not budget for any tree care, despite officials having strong positive attitudes about the value of trees in their areas and widespread interest in protecting and increasing 55 tree cover (Schroeder et al., 2003; Treiman and Gartner, 2004). This suggests that merely the presence of professionals who value trees and would be likely to ‘fight their corner’ for more funding is not enough to ensure funding for tree care and planting projects; other, wider support is needed. This is disappointing, as it suggests a widespread knowledge gap, and that more information, and possibly culture change, is needed in these communities before more professionals value trees and will therefore try to obtain funding for tree protection.

Heynen and Lindsay (2003) explored tree canopy cover in relation to a number of different variables across 60 urban areas in central Illinois, USA and found that planning and zoning regulations, or status as a Tree City 1 were not correlated with urban canopy cover. This is at first a surprising result, as these measures would be expected to have at least a small effect, but it is possible that these have not been in place long enough to dramatically affect tree canopy cover, so a later study may find significant correlations.

A later study in Tampa, Florida, USA, examined urban tree cover in relation to planning regulations associated with the protection of trees. This revealed significantly greater tree cover on parcels of land with homes built after the adoption of tree protection policies compared to before, despite a trend toward increased building cover of the land parcel (Landry and Pu, 2010). At a neighbourhood level, the percentage of homes built after implementing the policy was a strong predictor of increased tree cover. This demonstrates the effectiveness of the tree protection policies in protecting existing trees when development occurs. Similar laws protecting trees may be expected to have a similar effect elsewhere.

A similar study in Atlanta, Georgia, USA also examined tree cover in relation to planning regulations. Hill et al. (2010) found that when the local planning authority had a set of effective, legally enforced tree care, maintenance and protection laws (tree ordinance clauses), enforced land use planning, and had high quality smart growth projects (developments sensitive to their surroundings which improve or do not impact the local environment), this helped preserve tree canopy bin levels the authors classed as economically and environmentally meaningful amounts. Other softer measures such as simply having tree protection laws, designating a key management person in charge of tree programs, the presence of a tree board, and multiple communication channels

1 To become a Tree City an urban area must commit to a certain level of funding for trees, a minimum number of tree planting events and have certain municipal tree management structures. http://www.arborday.org/programs/treeCityUSA/standards.cfm 56 between relevant individuals and departments were shown to be ineffective (Hill et al., 2010). Therefore, ‘strong’ measures of legal protection of trees and enforcement of these laws when they are broken, plus a local culture of sensitive development were the only effective method of protecting and enhancing tree cover.

Interestingly, Hill et al.’s (2010) findings are different to Heynen and Lindsay’s (2003) findings; it is possible that significant changes in tree cover due to planning regulations took a longer timescale to become evident, and these later papers have demonstrated this relationship. The findings by both Landry and Pu (2010) and Hill et al., (2010) strongly suggest that enforced legal protection and encouragement of tree planting and protection is an effective way to maintain and increase tree cover, while merely having laws and appropriate staff and management is not sufficient to protect and increase tree cover. These findings could easily become recommendations to be replicated elsewhere.

In Europe, little published research attention has been paid to the existence of tree ordinances or the temporal effects of tree protection regulations. In probably the only paper exploring and comparing tree protection laws, Schmied and Pillmann (2003) found that of 34 European cities surveyed, 75% had laws protecting private and/or public trees. In London and Dublin trees are not automatically protected by law and must be protected by a Tree Preservation Order in order to prevent felling; due to the lack of automatic protection, both cities were excluded from further analysis. The laws generally protect trees over a certain circumference or height, though others protect trees which are growing in certain areas or have a ‘Tree Preservation Order’ on them. The trees are generally protected from felling, removal, damage, destruction, modifications, pruning and to enhance their decay. Most cities studied demand replacement planting when a tree is felled, while some allow financial compensation. A financial penalty for unauthorised tree felling occurs in some cities and is reasonably high: between 15,000, and 42,000 Euros for each offence. The authors recommend that up-to-date tree legislation should include the protection of all public and private trees, which may only be felled if the tree is unhealthy or represents a threat to persons or goods and only after local authority authorisation; fines for any damage that occurs to a tree, including damage from substances such as herbicides, deicing salt and sewage; and the giving of penalties for unauthorised tree felling should be implemented and enforced and a department responsible for the enforcement should be designated. Although this paper did not study the influence of tree regulations over time, the authors recognised and highlighted the

57 importance of enforcing the tree protection laws, as have other authors (Laudry and Pu, 2010; Hill et al., 2010).

In the UK, Britt et al. (2008) found that the most common infringement of Tree Preservation Orders, leading to a prosecution, was wilful damage of trees. However, almost 65% of local authorities questioned did not prosecute for any infringements of Tree Preservation Orders; this may be due to no infringements of these orders, or much more likely the lack of effective monitoring and enforcement of these laws. This lack of enforcement of tree protection laws is concerning; research from the USA demonstrates the importance of enforcement of tree protection regulations, which can lead to an increase in tree cover. If effective enforcement is not present in the UK, then it suggests that tree cover will decrease, regardless of any new laws to protect trees.

2.4.2 Effects of Community Greening Schemes

The research described above demonstrates that urban residents like trees, are aware of their benefits and are supportive of tree planting schemes. It is not surprising therefore that there are a number of community driven schemes led by charities to protect and increase tree cover in urban residential areas. These charities aim to improve the urban environment, planting street trees in areas of social deprivation and/or community demand, but low levels of funding mean that this can only have an impact in a small number of places each year.

In the UK, community forests have been set up in 12 urban areas and aim to increase tree cover by planting trees on wasteland, in neglected parks and other areas in need of improvement and regeneration (England’s Community Forests, 2005). The Red Rose Forest, a community forest in Greater Manchester, oversees the Green Streets scheme, a project which plants trees along residential streets (Red Rose Forest, 2010a). A separate charity called Trees for Cities does similar work mainly based in London but extending to seven other English cities and four cities internationally (Trees for Cities, 2010). These schemes increase tree cover in urban areas of all housing densities, and have proven very popular and successful. Both encourage a sense of ownership of the trees and tree pits are often planted with other plants and watered during the summer months by local residents. However, the limitations of funding and the slow growth of trees can mean that widespread impacts take many years to be fulfilled.

58 Local councils also plant street trees, sometimes funded by money from local developments. Appleyard (2000) examined tree planting and tree establishment rates over six planting seasons in high density residential areas of Lambeth, London. He found that the highest establishment rate, and thus lowest death rates of new plantings, occurred when planting were properly planned, accurate records of plantings were kept, community requirements were understood and residents were informed of tree planting schemes. The inclusion of residents can help build a feeling of ownership to a tree planting scheme, meaning the trees may be watered by residents and avoid neglect. As previous studies have demonstrated people’s like and appreciation of trees, it is not unreasonable to expect some care of trees by local residents, similar to that seen by the Red Rose Forest and Trees for Cities schemes.

Other schemes aim to protect existing trees. The Tree Council runs a successful volunteer Tree Warden scheme which allows residents individually or as a local group to look after and learn about the trees in their street and local parks; groups also take part in tree planting activities in schools and parks and tend to actively lobby local authorities for more tree planting in their area (Tree Council, 2010). The information collected by volunteers about their local trees may then be given to the local council to inform their maintenance rota or update their Tree Inventory (Bloriarz and Ryan, 1996).

These examples demonstrate that tree cover can be protected and increased in high density housing areas through public involvement and enthusiasm; tree cover does not have to remain at the present low levels.

2.4.3 Potential Effects of the Loss of Greenspace in Residential Areas

Within high density housing areas there is often little space for trees to be planted. Conversely, a study in Merseyside (Pauleit et al., 2005) showed that in low density affluent areas overall levels of greenspace have decreased since 1975. The main reason for this loss of greenspace is residents paving over the carefully planned front or rear gardens for off road parking, or for low maintenance outdoor space where parking is already provided (Alexander, 2006). This trend is concerning, and is particularly prevalent in London (GLA, 2005; Alexander, 2006). This loss of greenspace within residential areas will severely limit the space available for tree planting, and will also increase the urban heat island effect as previously transpiring, and therefore cooling, surfaces are replaced by artificial surfaces which store heat. In London it is estimated that

59 around two thirds of the total tree cover in the city is within private gardens (Alexander, 2006). Front lawns, which are most commonly paved over (GLA, 2005) represent one of the most suitable areas for tree planting (Attwell, 2000). Combining residents’ demands for parking with their demands for trees and cooling as temperatures increase is a difficult task, but must be faced by researchers and policymakers.

2.5 Conclusions

The literature review has outlined the growing amount of research into the effects of trees in urban areas. Trees shade and cool their surroundings, leading to a more comfortable indoor (through shading effects) and outdoor environment for humans. As climate change leads to higher temperatures, these cooling effects will become even more noticeable and important, particularly for poorer communities which are less likely to be able to afford the costs of air conditioning for example. Trees are able to capture and store rainwater, decreasing the amount running into drains during rainfall or storm events. The intensity of storms is expected to increase due to climate change, therefore safeguarding the capacity of drainage systems, which could potentially lead to pluvial or surface water flooding is very important. This is now recognised as an important environmental justice issue in urban areas, as highlighted by the Pitt Review into flooding events in the UK (Pitt et al., 2008). Trees also clean the air of pollutants, improving the air quality of urban areas, particularly around busy roads. The presence of trees and greenspaces make people feel better, healthier and safer, less stressed, more social and friendlier. The literature shows that tree cover is not equally distributed across urban areas; therefore, some residents have access to fewer trees and greenspaces than others and do not experience the benefits of trees. In light of this, it can be argued that tree cover should be increased in areas of low tree cover, though few studies have directly addressed this, especially in the UK. This thesis will fill that research gap.

The literature review has examined potential socioeconomic factors that may affect tree cover. Research has demonstrated that, in general, areas of low incomes and high levels of rentership have low levels of tree cover. Conversely, in areas of high incomes and high home ownership, tree cover tends to be higher. These relationships are seen in both the USA and the UK. Cultural differences may also explain some of the differences between levels of tree cover.

60 The literature review has examined the historical development of high density housing areas and the treatment of trees and greenspaces within these areas. It is clear that some housing, through both legislation and changing homeowners’ preferences, can contain more vegetated space and therefore more space for trees. The literature has shown that housing density is a contributing factor to the amount of tree cover in residential areas, with higher density areas containing less tree cover. However, no study has looked at the differences between different types of high density housing. This is a gap this thesis will fill.

The international literature reviewed has demonstrated urban residents’ positive views towards trees, and their wishes for more to be planted. However, just two studies have been published which examine the views of UK residents, and one did not show great support for tree planting. This thesis will fill that research deficit, and also look for differences in attitudes between residents of streets with and without trees.

The literature has demonstrated the importance of legislation and enforcement in the promotion and protection of urban trees. This thesis explores the views of practitioners in the UK to determine the barriers and opportunities for increasing tree cover in high density housing areas, again filling a research deficit. Finally, the thesis examines the effects of different interventions on tree cover.

61 Chapter 3 – Research Methodology

The literature review in Chapter 2 has explored a range of factors shown to affect the distribution of trees in high density housing areas. This chapter sets out how these factors are investigated in this study. A conceptual framework is developed which proposes relationships between factors. This will be revisited in Chapter 9 in light of the research findings. The research context for the UK and the study area of western Greater Manchester is given, with a justification of the choice of study area. Methods used for each Objective in the research are briefly outlined, with further detail in Chapters 4 to 7. A justification for the use of these methods is also provided.

3.1 The Research Context

The literature review highlighted the many benefits trees can give to urban residents. The distribution of trees was shown to be uneven in urban areas (e.g. Talarchek, 1990; Iverson and Cook, 2000; Heynen et al., 2006; Troy et al., 2007; Landry and Chakraborty, 2009 and Laudry and Pu, 2010) with income levels and housing tenure cited by many authors (e.g. Jensen et al., 2004; Perkins et al., 2004; Solecki et al., 2005) as an indicator of tree cover. In particular, housing density has been shown to strongly influence tree cover (e.g. Iverson and Cook, 2000; Handley et al., 2000, Solecki et al., 2005, Tame, 2006) with low density housing having the highest tree cover, followed by medium density and finally high density housing. Land uses and residents’ attitudes towards trees have also been suggested to affect tree cover across urban areas (e.g. Nowak et al., 1996; Handley et al., 2000; Lohr et al., 2004; Gorman, 2004).

Despite a number of researchers identifying the influence of housing morphology on tree cover, this has not been studied in detail. This thesis aims to fill this research gap, looking specifically at high density residential areas. Different areas of this housing type have been shown to contain very few trees, a large number of trees or a number in between. The reasons for this variability are unclear. It is probable that this difference is related to housing morphology and the public and private space around housing; however there does not appear to be a classification of homes which addresses these differences. Therefore, a novel housing typology which addresses both housing type and the space around the house potentially available for planting is needed; this thesis will seek to develop such a classification for high density housing in the study area of Greater Manchester.

62 High density housing is also of interest to study as it currently experiences high surface temperatures due to the urban heat island effect, which will increase with climate change. Surface temperature is known to be an important factor in influencing human comfort. As the literature review has shown, trees can reduce urban temperatures significantly; therefore planting more trees in high density housing will help to reduce the high temperatures they experience. Although there is a large amount of research on this subject in both the UK and internationally, no study has addressed the differences in maximum surface temperatures a change in vegetation cover could confer in different types of high density residential areas. Thus, this thesis explores this question which could in turn provide a practical example of the benefits of urban greening.

Attitudes of urban residents have been studied fairly extensively in the USA, but little research has been done in the UK and elsewhere. Surprisingly, no study has looked at the impact of the current residential environment on people’s views about trees. It may be that those who do not like trees live in areas without trees, while those who like trees live in tree-lined streets or have recently had trees planted in their street through a community driven scheme. This thesis explores the views of residents in a range of different streets, and will therefore fill this gap in the literature. It is also one of the few studies investigating urban tree distribution and residents’ attitudes in the UK.

3.1.1 A Conceptual Framework for the Research

Trees in high density housing areas form part of the urban forest, a concept developed in the USA and becoming more popular in the UK and Europe. The concepts of urban forestry are not universally agreed, but broadly urban forestry may be defined as: • areas usually physically linked to form a mosaic of vegetation in or near built-up areas; • a multi-disciplinary and specialised branch of forestry activity that encompasses the design, planning, establishment and management of trees, woodlands and associated flora and open space; • the cultivation and management of trees for their present and potential multi- purpose functions, which includes both the overall ameliorating effect of trees on their environment and their contribution to the physiological, sociological and economic well-being of urban society. (Adapted from Konijnendijk et al., 2006).

63 These concepts propose that urban forests, and therefore urban trees, should be a multifunctional resource giving benefits to both the environment and urban residents, managed by specialists. The involvement of a range of stakeholders with a range of desired outcomes for the urban forest, each with a differing sphere of influence has informed the Conceptual Framework in Figure 3.1. Both the public and professionals have a stake in the urban forest and can influence it for better or worse.

Figure 3.1 (below) shows potential factors that can influence tree distribution in high density housing areas. These factors are examined in this thesis, with a view to informing both scientific understanding of factors influencing urban tree cover and generating recommendations of relevance to policy and practice. Housing density Resident Presence of socioeconomic community status housing layout greening schemes and type

Tree distribution in high density housing areas Developer attitudes

Local government Resident National policy attitudes government policy

Figure 3.1. A conceptual framework outlining potential influences on tree distribution in high density housing areas. Thick arrows indicate relationships described in the literature, thin arrows indicate hypothesised relationships.

A number of studies examined in the literature review (Chapter 2) have demonstrated links between housing density and tree cover (Iverson and Cook, 2000; Handley et al., 2000; Jim and Liu, 2003; Solecki et al., 2005; Tame, 2006; Tratalos et al., 2007; Davies et al., 2008). Therefore, housing density is clearly a factor affecting distribution of trees in high density housing areas and is indicated with a thick arrow in Figure 3.1. Tame (2006) found that even within similar density housing tree number can vary significantly,

64 suggesting that other factors relating to layout, not just housing density, affect tree distribution. This is a hypothesised relationship and is explored in this thesis, shown in Figure 3.1. as ‘housing layout and type’. Local government policies can have a large impact on tree protection and planting (Hill et al., 2010; Landry and Pu, 2010), so this relationship is indicated with a thick line in Figure 3.1. Conversely, there appears to be no study linking national policies with urban tree protection, so this is a hypothesised relationship. The socioeconomic status of residents has been shown to affect tree cover in their neighbourhood (e.g. Talarchek, 1990; Iverson and Cook, 2000; Jensen et al., 2004; Perkins et al., 2004; Section 2.3.1, 2.3.2); this relationship is therefore marked with a thick arrow in Figure 3.1. Residents with a positive, proactive view on trees can also instigate their own schemes with funding from other sources which will increase tree cover; no study has examined this so it is a hypothesised relationship. Developers with a positive attitude towards trees, or a recognition that trees and greenery improve their developments, could also increase tree cover in urban areas. These varied influences are best studied in a defined geographical area, where the relative importance of different influences can be teased out.

3.2 Justification of the case study approach

A case study approach has been used in this study to explore factors affecting the distribution of trees in high density residential areas. Case studies typically involve multiple methods of data collection (Robson, 2002, p.599); multiple methods are used in this study to more fully understand the factors affecting tree distribution in high density residential areas. Most other researchers in this area have used a case study approach; therefore, in order to advance knowledge in this area, similar methods are needed.

Case studies allow comparisons with other case studies and give a context for any results, and allow tentative generalisations to be produced (Silverman, 2005, p129). Despite the lack of a comprehensive sample, case studies can give some kind of generalisability beyond the study area, particularly in developing an understanding of the processes at work in a single situation which are likely to be seen in similar situations elsewhere (Robson, 2002, p177). Flyvbjerg states that, given due care over case study selection, useful generalisations can be made from a single case (Flyvbjerg, 2001, p.74); therefore, the results of this thesis can provide both an understanding of the processes involved in tree distribution in the case study area and given due care the findings may be generalised to other similar areas. 65 3.3 Case Study Selection

In order to select a case study, area criteria need to be generated which the final selected case study will fulfil. In order to fulfil the aims and objectives of this study, the case study area must be: 1) an urban area that contains extensive areas of high density housing of a wide range of different types, built over a long period of time; 2) an area with a broad mix of socioeconomic and cultural groups, in order to investigate differing attitudes of residents; 3) an area where proactive community led street greening and regeneration is occurring.

Additionally, it is desirable that the study area is: 4) an area where areas of differing housing density have been delineated, in order to minimise pre-classification work; 5) an area where tree cover and distribution has been well studied.

Western districts of Greater Manchester fit all these criteria. Due to its industrial past, Greater Manchester contains large amounts of high density housing, built to house rapidly increasing numbers of factory workers during the late 19 th century. Some of these areas have been regenerated over the years to provide more modern high density housing, and high density semi-detached and terraced houses have been almost continuously built across the study area both privately and by local authorities throughout the 19 th and 20 th centuries. Within Greater Manchester there are very few pre-1800 buildings, and the housing is almost exclusively late 18 th century onwards (Freeman, 1962) which makes classification much easier. The constant building and regeneration of housing means that the housing demonstrates most of the prevailing housing trends of these eras. The method of generating a housing classification may be generalised and used in any other city, and as Greater Manchester exhibits most of the types of housing built over the last 150 years it is highly likely that similar housing types will be seen in other industrial cities.

Gill (2006) categorised the housing of Greater Manchester as high, medium or low density. This was based on the layout of the housing, and confirmed using postcode data to determine the density of individual address points per unit area. Address points include both residential and business properties, so there may have been an over-estimation of housing density for these areas, though this will be low as residential areas contain few 66 business addresses (Gill, 2006). High density housing contained an average of 47.3 address points, almost twice that of medium density housing (see Table 3.1 below). High density housing classified by Gill (2006) using both this address point data and aerial photographs formed the basis of the housing typology and classification for this study, reducing the initial classification work needed to study this area.

Table 3.1. Address points per hectare for differing residential densities in Greater Manchester. From: Gill (2006). Residential Mean Min Max Std. Std. Error N density Deviation of Mean High 47.3 5.7 132.9 15.8 1 245 Medium 26.8 3.6 58.6 7.5 0.3 612 Low 14.8 1.5 46.6 7.9 0.7 145 Average 30.0 1.5 132.9 14.7 0.5 -

Handley et al. (2000) and Tame (2006) have examined tree cover in Greater Manchester, and their research has also formed a basis for this study. Handley et al., (2000) found that tree distribution varies significantly between differing land uses and housing densities; high density housing had the lowest number of trees of any land use, while low density housing had the second highest of any urban morphology type. Tame (2006) used this data to examine tree distribution in high, medium and low density housing, finding differences in tree number which were associated with a number of socioeconomic variables. Further analysis of this data shows that housing density is the most significant indicator of tree number; higher density housing indicates lower tree number. However, some areas of high density housing had a high number of trees, as high or higher than the number of trees in some areas of medium or low density housing. Reasons for this were not explored in Tame’s (2006) work, so will be explored here.

Greater Manchester displays variations in levels of deprivation both between local authorities and within their boundaries. The average index of multiple deprivation 2 score ranged from 4 th most deprived to 178 th most deprived, of the 354 English local authorities. Similar ranges of high to fairly low levels of deprivation exist within the districts. The 2001 census also shows there is a range of cultural groups within the area; the 19% non

2 The Index of Multiple Deprivation 2007 combines a number of indicators, chosen to cover a range of economic, social and housing issues, into a single deprivation score for each small area in England. This allows each area to be ranked relative to one another according to their level of deprivation. http://www.communities.gov.uk/communities/neighbourhoodrenewal/deprivation/deprivation07/ 67 white population in Manchester itself is comprised fairly equally of all ethnic groups recognised by the census.

Thus far, all of Greater Manchester fits the case study selection criteria. The final criterion is the presence of a proactive community led street greening project. This is only active across six of the Greater Manchester local authorities: Bolton, Bury, Manchester, Salford, Trafford, and Wigan. These districts form the area covered by the Red Rose Forest, a project aiming to increase tree cover and greenery by planting in streets and on derelict and underused land which can then be made accessible to the public (Red Rose Forest, 2010). The Red Rose Forest oversees a scheme to increase tree cover in residential areas called Green Streets. This is proving a successful and popular scheme with community groups and residents. Residents form a small group and approach Red Rose Forest’s Green Streets team for help and support to get funding for street tree planting. If funding is successful, contractors will plant the trees in late autumn and winter. Residents are free to plant around the base of the tree with plants of their choice, and are encouraged to water the tree, particularly in hot weather. The links that Red Rose has with the residents of these areas, and their own experience of community tree planting schemes, formed the basis of the study into community views and best practice for increasing urban tree cover within this thesis.

This information explains and justifies the choice of western Greater Manchester (Figure 3.2) as a case study area for this study of tree cover in high density housing areas.

68

Bury Bolton

Wigan

Salford

Trafford Manchester

Figure 3.2. The location of Greater Manchester within the north west of England, UK, and the study area (white) within Greater Manchester.

69 3.4 Justification and Overview of the Methods Used in the Thesis

In order to explore the influences on tree number and cover within the study area, a range of methods have been used. These are outlined below and given in much greater detail within the methodology sections of each chapter.

3.4.1 Objective One

To explore the nature of variation in tree cover and its causes in residential environments.

Objective One explores the influence of housing design and layout on the distribution of trees in high density housing areas. To achieve Objective One, the extent of high density housing present in the study area needed to be delineated. This had been previously completed by Gill (2006), and her delineation was used in this study. The further development of methods for Objective One was guided by the sampling procedure set out by Robinson (1998) and adapted below (Table 3.2).

Table 3.2. Stepwise development of a sampling procedure. Adapted from Robinson (1998) Stages Process 1. Define the geographical area Defined in terms of: (a) units, (b) elements, (c) area, (d) time period 2. Define sampling frame How the elements of the geographical area can be described 3. Specify sampling unit Identify units for sampling, e.g. city street, households 4. Determine sampling method Methods by which units are to be sampled e.g. probability vs. non- probability schemes 5. Determine size of sample The number of units to be selected 6. Specify sampling plan and method of The operational procedures necessary for collecting data selecting data

Stage 1 is outlined in Section 3.3 above. The sampling frame is the high density housing, and the specific housing types within these areas the sampling unit. The types of high density housing within these areas then needed to be classified. There are a number of methods of classification of urban areas in the literature, including Alexander’s Pattern 70 Language (Alexander, 1977), Space Syntax (Hillier and Hanson, 1984) and Route Structure Analysis (Marshall, 2005). These concentrate on the future design of urban areas, with emphasis on network analysis and the connection between different types of urban land use, rather than on the analysis of existing structures. Therefore they cannot be used in this thesis to analyse existing housing types. Instead, a novel classification has been generated, using the sparse literature on housing types and forms described in Chapters 2 and 4, plus site visits to high density housing in the study area. The classification was particularly focussed on the space around homes, as potential areas where trees may grow or be planted. The generation and characteristics of these types is discussed in Chapter 4.

Within the sampling unit of the housing types, surface covers and land uses needed to be sampled using an appropriate method. Classification of surface covers using remote sensing (e.g. Jensen et al., 2004; Landry and Pu, 2010) was not considered appropriate due to the high level of technical skill required to classify surface covers appropriately and the small, non contiguous patches of urban area studied. Remote sensing is also unable to define land use at the fine detail required for this study. While surface cover categories would probably be easily identified by computerised aerial photograph analysis, though there may be issues differentiating between similar surface covers like ‘tree’ and ‘shrub’. For land use calculation, it is highly unlikely that computerised aerial photograph analysis could differentiate between the categories used in this thesis, as it is context dependent and requires human interpretation.

Therefore, a simple point classification system using aerial photographs was considered the most appropriate method. Aerial photographs can provide a lot of information about surface cover and land use. Within high density housing, trees can be identified as growing in open space, on a street or highway, in a back garden or a front garden (Handley et al., 2000). Surface cover in urban areas may be classified as built, asphalt, pavement, open soils/gravel, vegetation or freshwater (Pauleit and Duhme, 2000). Vegetation may be further classified into trees, shrubs, herbs and grasses, lawn or flower beds (Pauleit and Duhme, 2000), turf grass, rough grass, sub-shrubs, vegetables or arable crops (Sekliziotis, 1980). These classifications show how much detail it is possible to obtain from aerial photographs. The number and characteristics of trees in urban areas is closely related to the basic land use of the area as well as the age of the development and the tenure patterns of the area (Land Use Consultants, 1993, p.4) and so it is important to define land use as well as surface cover.

71 There are a range of simple point sampling methods which may be used to classify surface covers and land uses on aerial photographs. Data collected in this study may be used to infer findings to a wider area; therefore a probability sampling method is required for data collection. The two most basic forms of probability sampling are random sampling and systematic sampling (Robinson, 1998, p.29). Random sampling selects points based on co-ordinates drawn from a random number generator or table, while systematic sampling selects every nth point to sample. Both methods have potential issues to consider: random sampling can under sample some areas and over sample others, while systematic sampling can replicate underlying regularities in the sample frame e.g. grid pattern roads (ibid.).

Stratification may be used to minimise these problems in both sampling strategies. Random sampling within a spatial sampling frame (stratification) can produce a more even spread of sample points in a given area (Robinson, 1998, p.29). Care must be taken when determining the boundaries of the sampling frame to ensure that certain areas are not over or under represented. This does have the advantage that a grid pattern is not needed, as the high density housing areas are generally irregular in shape. Systematic sampling with a stratified sampling frame does require a grid pattern. In this procedure (called Systematic Stratified Unaligned Sampling) a grid is placed over the sample and a point is chosen in each square using co-ordinates. Along rows x is constant; down columns y is constant. This has been found to be a superior system when compared to random, systematic and stratified sampling (Keyes et al., 1976, cited in Robinson, 1998, p.30).

Random sampling was chosen as the best sampling strategy for analysis of land use and surface cover; the housing type polygons are small and of irregular shapes, so using a grid based sampling strategy was deemed unworkable. Dangers of oversampling in one area and undersampling in another are not a great concern; as each area of housing has been classified due to its similarity to other blocks of housing, differences in numbers of sampling points across different geographical areas should not give differences in land use or surface cover for that type of housing.

A third type of sampling, transect sampling, was discarded due to its need for large linear areas and problems of oversampling underlying recurring features, such as roads, which would give inaccurate results in urban areas.

72 Surface cover and land uses were therefore defined and classified using the random point sampling method set out in Nowak et al. (1996), Gill (2006) and Gill et al. (2008). More detailed methods for this objective are found in Chapter 4. The proportions of surface covers and land uses found in this chapter are also used as part of Chapter 5.

3.4.2 Objective Two

To examine the influence of actual and potential tree cover on environmental quality of high density residential neighbourhoods in a changing climate.

Objective Two investigated to what extent tree cover may be increased in each housing type, and the effects that an increase in tree cover would have in relation to changed weather patterns due to climate change. To achieve Objective Two, guidelines were developed to inform the ‘planting’ exercise in the high density housing areas. These guidelines were informed by Red Rose Forest street tree planting rules, distance from built structures, availability of parking spaces and a consideration of the number of trees that would be acceptable to residents in their gardens. This gave a theoretical level of tree planting that could be achieved with unlimited funding and resident support, and was calculated for the whole study area as outlined in Section 3.3. Then, eleven polygons of each housing type were ‘planted’ with trees according to these guidelines, giving a potential maximum number of trees which could be planted in favourable conditions. The potential increase in tree cover was calculated and combined with existing tree cover to give a potential maximum level of tree cover. Similar studies exist in the literature (e.g. McPherson et al., 2008; Wu et al., 2008; Kirnbauer et al., 2009) but use detailed information about underground and overground services which is not available for the UK, therefore comparable methods could not be used. It is important to study the potential for increasing tree cover to demonstrate the realistic levels of vegetation that may be achieved if funding and support is available.

The current and potential levels of tree cover were inputted, along with the proportions of other surface types generated as part of Chapter 4 and meteorological data, into computer models that had previously been developed and used by Whitford et al. (2001), Gill (2006) and Gill et al. (2007). These models calculate the changes in the maximum surface temperatures and the levels of rainfall runoff of areas, given their particular surface cover. Therefore this procedure gave the effects on maximum temperature and rainfall runoff that increasing tree cover would give. These models were also used to

73 determine the effects of incremental increases in vegetation in areas of high and low building mass. Full methods and results for this Objective are given in Chapter 5.

3.4.3 Objective Three

To examine the interdependence between tree cover and residents’ attitudes to it in high density residential areas.

The views of residents are likely to influence the amount of tree cover near their homes; those who are positive about trees would probably live in areas of high tree cover or would pressure authorities to plant trees in their area, while those who do not like trees would not. To achieve Objective Three, a questionnaire to assess residents’ attitudes towards urban trees was developed, using the literature and consultations with the Red Rose Forest, a local charity who run a successful street greening project called Green Streets. A postal questionnaire was used as this is the method used by almost all other researchers investigating residents’ attitudes towards trees. The development of the survey methods and strategy followed the same stages as for Objective 1 (adapted from Robinson, 1998), with additional stages outlined for survey development by Fink (1995). These are shown in Table 3.3 below.

74 Table 3.3. An outline of stages required for the development of a survey. Adapted from Robinson (1998) and Fink (1995). Stages Process 1. Define the geographical area Defined in terms of: (a) units, (b) elements, (c) area, (d) time period 2. Identify the survey’s objectives Defined by survey theme and use of eventual data 3. Define sampling frame Defined by the area(s) of interest and the similarities and differences between them 4. Specify sampling unit Identify units for sampling, e.g. city street, households 5. Determine size of sample The number of units to be selected 6. Determine sampling method Methods by which units are to be sampled e.g. questionnaires, focus groups 7. Develop the sampling instrument Using the literature, adapt/write and test questions to be used in the survey 8. Administer the survey instrument Carry out the survey, improving as necessary. Ensure follow ups are conducted. 9. Analyse and evaluate the data Use appropriate statistical tests and reporting methods for the survey method

The geographical area of the survey is limited to the local authority area of Manchester within Greater Manchester, unlike the rest of this thesis which in addition studies Bolton, Bury, Salford, Trafford and Wigan. This is because the Green Streets project has been most concentrated in Manchester, and because proximity to the research base meant that travelling to survey residents did not become impractical. Residents are familiar with their own street and are likely to have strongly held opinions about it; therefore, questions pertaining to the street environment were deemed most appropriate. The existing streetscape where people live is likely to have a large influence on how they perceive trees; in a street of many attractive, well maintained trees it is probable that residents would have a positive view about trees, while in a street where there are no trees, residents may have inaccurate ideas about the size of street trees and a disproportionate view of the potential problems trees may cause. Four differing street types within high density housing areas were selected: 1. streets with no trees, either on the pavement or in front gardens, but with enough room for trees to be planted (2.15metres wide pavement); 2. streets with old trees (established street trees 40 or more years old); 3. streets which were awaiting planting of a Green Streets project; 4. streets which had Green Streets project trees planted 5 years ago. Around 180 homes in 4 or 5 streets were selected in each type, giving a total of 726 homes selected. Streets in areas of varying deprivation were selected to ensure a spread of responses across socioeconomic status. The questionnaire was sent out by post and 75 homes were visited on a designated day to remind residents to return the questionnaire. Responses were analysed in the statistical package SPSS v.15. The responses were compared with a similar study in the USA (Lohr et al., 2004) to explore any potential differences between the countries. More detailed methods and full results are given in Chapter 6.

3.4.4 Objective Four

In light of objectives 1-3, to inform policy and practice with regard to tree provision in high density residential areas.

Objectives 1 to 3, detailed in Chapters 4 to 6, showed the extent of tree cover in different housing types, the potential for increasing tree cover and residents’ attitudes towards trees. Objective Four examines practical examples of increasing tree cover and generates recommendations for future policy and practice for urban tree planting. To achieve Objective Four, three different approaches were used. Firstly, a workshop was held and practitioners from local authorities, local and national greening charities, statutory Governmental bodies, local housing associations and regional planning authorities were invited. Preliminary results of the thesis were presented, and barriers and opportunities to increasing tree cover were discussed in four different themes. These themes were generated with reference to the literature and to discussions with the Red Rose Forest. Trudgill (1990) suggests that major types of barriers to a better environment are agreement, knowledge, technological, economic, social and political (p.3). The literature review has shown that there is a large amount of knowledge and agreement about the benefits of trees in urban areas; thus, these may not be seen as barriers to increasing tree cover. The remaining barriers do exist, and were presented in the workshop as: • Design (a technological barrier) Trees cannot always be fitted into urban areas or may cause problems when they are, so better urban design could be an opportunity to plant more trees which will grow and not disturb their surroundings in a negative way; • Funding (an economic barrier) It can be expensive to plant trees, particularly if concrete needs to be dug up to provide space for a tree pit. There are some existing funding schemes but this may not always be available;

76 • Residents (a social barrier) Residents may be supportive and encouraging of a scheme or may block a scheme, preventing any tree planting; • Legislation (a political barrier) There may be legislation that can be used to protect existing trees or may be able to encourage planting of new trees, or laws that may be used creatively to facilitate more tree planting.

Participants discussed each topic in turn in small groups using a Ketso kit, an aid to facilitating discussions developed by Tippett (Tippett, 2004; Tippett et al., 2007). This kit allows participants to write their ideas on movable labels which may link with themes already on the table or create a new theme for discussion. It also aids consideration of a number of themes or topics at the same time. These discussions formed recommendations to overcome these barriers and to increase tree cover in urban areas. These recommendations could make a great difference to the levels of tree cover in high density housing areas if they were implemented, and therefore form an important part of the findings of this thesis.

Secondly, potential factors affecting the number of households agreeing to have a tree planted outside their home as part of a Green Streets project were investigated. The records of Red Rose Forest’s Green Streets projects were analysed and the percentage of households who agreed to have a tree planted outside their home was calculated for each project. This was then correlated with deprivation levels, housing types, presence of a proactive ‘Green Streets Champion’ and environmental quality indicators to determine what, if any, factors affected the supportiveness of residents.

Thirdly, the effectiveness of the differing approaches of Green Streets projects and housing regeneration schemes to increase tree cover was explored. Two regeneration projects were selected, and compared with a small number of Green Streets projects in streets of similar housing. Site visits were carried out to determine the number of new trees planted and existing trees retained in these projects. Interviews with the lead staff members for the two regeneration projects were carried out to explore the extent to which trees and greenspace were increased after regeneration was completed. The number of trees planted or retained was compared with the maximum potential number of trees planted in the public realm of the streets, using the methodology developed as part of

77 Objective Two in Chapter 5. More detailed methods and full results may be found in Chapter 7. Recommendations are also highlighted in Chapter 9.

3.5 Conclusion

This chapter has outlined the research context which frames this thesis. It has given justifications for the study area and methods used in the thesis. A brief outline of the methods used to achieve each objective has also been given, with more detail given in each appropriate chapter.

78 Chapter 4 – An Exploration of Tree Cover and its Location in Differing Housing Types

This chapter states how Objective One ‘To explore the nature of variation in tree cover and its causes in residential environments ’ was achieved. A brief overview and justification of the methods was given in Section 3.4.1, and the methods are expanded in this chapter. This chapter describes the generation of a housing typology appropriate to the study area, and the classification of surface covers and land uses. The results give the amount of different housing types across the study area and the proportions of surface covers and land uses in each housing type. Most importantly, the results show the differences in tree cover in each housing type and the land uses in which trees have grown. The surface cover and land use results found in this chapter will be used as part of Objective Two, described in Chapter 5, to determine the effects of existing and changed surface cover proportions on future surface temperature and rainfall runoff in each housing type.

4.1 Introduction

Previous research has shown that the distribution of trees in urban areas, particularly residential areas, is uneven. For instance, Handley et al. (2000) looked at the differences in tree distribution related to land use across the six western Local Authorities of Greater Manchester that make up the Red Rose Forest area (see Figure 3.2 for map). They found that in different densities of housing, there are distinct differences in the numbers of trees. Tree number is reasonably high in medium and low density housing, with an estimated average of 40 and 51 trees per hectare respectively. However, in high density housing the researchers estimated an average of just 14 trees per hectare. Tame (2006) looked at this data in greater detail, counting the number of trees in randomly selected 4 hectare (200m x 200m) squares in each density of housing. He found that there are fewer trees in high density housing areas than in medium or low density housing, and that there is a large standard deviation of tree number in all housing types (Table 4.1). This shows that there is a large variability in tree cover even within a single residential urban morphology type (UMT). It was unclear why this variability in tree numbers occurs, so there is a clear need for these areas to be studied in greater detail.

79 Table 4.1. Means, standard deviations and minimum/maximum tree number per 4 hectare square for each housing density. From: Tame (2006). Low density Medium density High density Mean 70.11 54.17 32.89 Standard deviation 42.025 23.586 19.296 Maximum number 157 104 78 of trees Minimum number 6 17 3 of trees

Further analysis of this Red Rose Forest dataset, using one way ANOVA, shows that housing density was the strongest indicator of tree number (F 2,53 = 6.99, p = 0.002), whereas Local Authority did not have a significant effect (F 5,53 = 0.84, p = 0.527). This shows that possible local authority-level differences in tree management practices did not have a significant influence on tree numbers.

Although all densities of housing are shown to have high variability in tree number, high density housing is the most interesting to study. High density housing has the least amount of space for trees to grow, as much of the land is housing or roads. Despite this apparent lack of space, some areas of high density housing contain a large number of trees. This would suggest that there may be differences in land use within high density housing areas which leads to wide variation in tree number. The location and number of trees must be affected by the amount of space available for their growth, and in turn this can be affected by housing type. For example, apartment blocks are likely to have more incidental space associated with them where trees may be planted than a similar area of Victorian terraced housing, while semi-detached houses are likely to have bigger gardens where trees can be grown.

This chapter describes a study which investigated the way in which housing type affects surface cover and land use of high density housing areas within Greater Manchester, concentrating especially on how this affects the numbers of trees they contain and the resulting tree cover.

80 4.2 Methods

4.2.1 Determination and Delineation of Housing Morphology Types

Areas of high density housing within Greater Manchester were previously determined by Gill (2006). In this study, areas of high density housing over 1 hectare in size were classified into 11 more detailed categories. No appropriate categorisation existed in the literature.

These categories are based on the age and type of the housing, the road pattern of the area and the size of the garden associated with the houses. Within Greater Manchester there are very few pre-1800 buildings, and the housing is almost exclusively late 18 th century onwards (Freeman, 1962). Interestingly for a northern UK city, back-to-back houses (where houses share both side walls and the rear wall with other dwellings) were outlawed in 1844, and those that did exist disappeared by the 1940s (Freeman, 1962), though they remained common in other cities such as Leeds and Liverpool (Burnett, 1991, p.157). In 1867 the city of Manchester went as far as passing regulations to ensure every new house had a small private yard (Burnett, 1991, p.158). Following the passing of the Housing of the Working Class Act in 1890, Manchester city council began to clear slums and built better housing within its council boundaries from 1891 onwards (Smith, 1989; Anon., 1995), with neighbouring authorities following its example. The housing was greatly influenced by the 1875 Public Health Act that gave minimum standards for housing size and spacing and were set in long, parallel, tree-less streets of houses that opened directly onto the street or had a tiny front garden separated from the street by a low wall (Burnett, 1991, p.160). Private developers built terraces with larger gardens and semi-detached dwellings. Much of this housing still remains in Greater Manchester, though many areas were cleared and rebuilt in the 1960s (Anon., 1995). The 1919 Housing and Town Planning Act meant that housing across the UK was then built at generally lower densities than previously (Hawks and Souza, 1981). For this reason, 1919 has been used as a cut-off point for this housing classification. After the First World War, the author of ‘The Home I Want’ wrote that ‘the comfortless and badly planned house with no garden must be a thing of the past’ (Burnett, 1991, p.222); in response to this growing aspiration both local authorities and private developers built lower density, mainly semi-detached housing with gardens (Hawkes and Souza 1981). Private developers built these homes using features from the past, including Tudor wood panelling, ornamental brickwork and bay windows, responding to the desire for 81 ‘character’ in people’s homes (Burnett, 1991, p.220). These are uncommon in the study area, as they are across the country; rents were capped by the Government to pre war levels, so private builders did not have much to gain by building these homes (Burnett, 1991, p.222). After the Second World War there was a time of great housing need, which was mainly provided for by the Government while private developers continued to provide mainly low density ‘homes of character’ for those with the means to buy them (Burnett, 1991, p.271, 286). From 1956 onwards, chimney pots disappeared from new housing as more efficient heating was installed (Burnett, 1991, p. 310). The presence or absence of a chimney is therefore an excellent method of estimating the completion date of housing. During the 1960s, housing densities rose again to house the growing population and high rise blocks of flats and car-less ‘Radburn style’ estates of short terraced housing were built, often on the sites of demolished Victorian terraces (Burnett, 1991, p.300; Colquhoun, 1999). These have been built extensively across the study area, mainly in Manchester itself, on large swathes of demolished slum housing. The terraces were built around courtyards and greenspace, with a large emphasis on the planning of communal leisure and play areas to ‘create feelings of neighbourliness’ (Burnett, 1991, p.312). After the 1960s, there was a general feeling of revolt against high rise living and the separation of parking and housing; new local authority housing focussed on low rise housing with individual parking spaces in high density estates from the 1970s onwards (Burnett, 1991, p.312; Colquhoun, 1991). The layout of these estates has generally been much more coherently planned with houses built along winding roads and in culs-de-sac, with landscaped greenspace and the provision of street furniture and trees (Smith, 1989; Burnett, 1991, p.328). Within the study area, a number of 1960s high-rise flats have been demolished and replaced with low rise terraces similar to other post 1960s terraces and a new form of housing, the courtyard/square type. This type of housing is low-rise (5 stories maximum) completely enclosing a central private greenspace and/or parking area. The redevelopment of Hulme, Manchester, after the demolition of the high rise Crescents is a particularly well known example (Colquhoun, 1999; Manchester City Council, 2008).

The housing type categories were developed using the sources above and additional information from Gould (1977) and Brown and Steadman (1991), plus field visits to a number of high density sites within Manchester City Council. General characteristics of housing built in different periods are given in Table 4.2 below.

82 Table 4.2. Defining features of categories of housing. Housing type Attributes Pre 1919 Terraces -Grid road pattern -‘Byelaw’ terraces – influenced by the 1875 Public Health Act for minimum building and sanitation standards -Long terraces -Small back yard, usually in an L shape around the rear of the house -Alleyways between rear yards of properties -Chimneypots on angular roof -May open directly onto the road, have a small front and back yard or a small front yard and larger back yard/garden -Ground floor bay windows in some areas Pre 1919 Semi- General features as above with additional features: detached -Housing built in pairs not terraces, with narrow access to the rear of properties between pairs -Bay windows extending to ground and first floor 1919 – 1959 Terraces -Short terraces -Simple design -Brick built -Equal sized windows, can be fairly large, with crossbars -Front and back garden -Chimneypots 1919 – 1959 Semi- -Brick built with pattern detailing detached -Windows similar sizes -Front and back gardens/drives -Façade a mix of styles from different eras – Tudor wood panelling, Victorian bay windows etc -Bay windows on ground and first floors -Arch or porch over entrance -Grid pattern in high densities, culs-de-sac in lower densities -Chimneypots 1960s Terraces – -General culs-de-sac road pattern drive/front garden -Small windows -Concrete or tile façade rather than bricks -Garden or drive at front, small garden to rear -Roofs often unequally balanced or flat -Small air vent on roof 1960s Terraces – open General features as above with additional features: onto walkway -Radburn style road pattern of culs-de-sac and walkways -Face pedestrian walkway and/or greenspace -Front yard if desired -Includes maisonettes and blocks of flats Post 1960s Terraces -Curved roads -May be in grid, cul-de-sac or courtyard form -Brick built with limited ornamentation -Even sized, often small windows -Front and rear gardens or drive -Small air vent on roof or no openings -Porches built with house -Some gabling in later houses

83 Post 1950s Semi- -Curved roads detached -Culs-de-sac or grid pattern (uncommon) -Façades uncommon -Patterns in brickwork -Even sized windows -Front and rear gardens -Small air vent on roof or no openings -Evenly balanced roof

These defining features were then developed into eleven discrete housing categories which were used in this thesis, and are given in Table 4.3 below.

Table 4.3. Housing classification categories. Construction date Housing type Further morphology Pre 1919 Terraced Opens directly onto the street Pre 1919 Terraced Has a small front yard, extending around 1m from house Pre 1919 Terraced Has a front garden extending over 1m from house, often vegetated Pre 1919 Semi-detached - 1919 - 1959 Semi-detached - 1919 - 1959 Terraced - Post 1950s Semi-detached - 1960s Terraced Has driveway or potential for driveway 1960s Terraced or blocks Does not have a driveway, usually of flats only accessible on foot via walkways Post 1960s Terraced - Post 1960s Terraced Terraced housing which forms squares, quads or courts

Photographs of typical examples of each housing type are below (Figure 4.1).

84

Figure 4.1(1). Clockwise from top left –Pre 1919 terraced housing with a front yard; Pre 1919 terraced housing with a front and back garden; Pre 1919 semi-detached housing; 1919-1959 terraced housing; 1960s terraced housing with a driveway; 1960s terraced housing with a walkway; 1919-1959 semi- detached housing; Pre 1919 terraced housing opening directly onto the road.

85

Figure 4.1 (2). Top – Post 1960s terraced housing. Right- Post 1950s semi-detached housing. Bottom – Post 1960s Court/Square housing.

A preliminary trial, testing these categories using photographs from field visits, aerial photographs, Ordnance Survey 1:10,000 maps and local knowledge, proved the classification to be very workable, reliable and replicable. The categorisation was then carried out across the whole of the Greater Manchester study area, giving 2626 hectares of high density housing in total.

Demonstration of Housing Classification

To give a better idea of the process, an example of how the housing was classified is given below. Ordnance Survey 1:10000 street maps downloaded from the Edina mapping service and high resolution aerial photographs acquired from the Greater Manchester Geological Unit (GMGU) were used to allow classification of housing types. The aerial photographs were taken in 1997, and the street maps were updated around 2005; this led to some conflicting data in areas undergoing regeneration but this was overcome by site visits, local knowledge and the use of internet mapping resources (e.g. Googlemaps, Multimap).

Firstly, an area of high density housing, previously categorised by Gill (2006), was selected. The non-shaded area in Figure 4.2 (below) is an area of high density housing, 86 shown on an Ordnance Survey map at 1:10000 scale, in the Arc GIS 9 programme (ESRI, 2004). Within this high density housing area, the OS map shows that there is a mix of terraces and semi-detached housing.

Terraces

Semi detached

Figure 4.2. Examples of high density housing (non shaded area) on a 1:10000 scale OS map within a GIS.

The aerial photograph (Figure 4.3 below) shows that all the houses have chimneys on angular roofs but not all have gardens. The houses are also reasonably large. This shows that these houses were built before 1919, and site photos confirm this. The aerial photograph shows that the houses at the top of the high density housing area have a front and back garden, but that behind the house it is paved. Despite the paving, this put them into the pre-1919 terrace-front and back garden category. The houses below are semi- detached, and so are classified as pre-1919 semi-detached. The houses below those are terraces with front yards and very small back yards. These are classified as pre-1919 terrace-front yard. Housing types are highlighted in Figure 4.3 and delineated in Figure 4.4.

87 Pre 1919 terrace - front and back garden

Pre 1919 semi detached

Pre 1919 terraces – front yard

Figure 4.3. An example of high density housing types on an aerial photograph.

Figure 4.4. An example of delineated high density housing categories on a 1:10000 scale OS map within a GIS.

This process was then replicated for all other areas of high density housing across the study area.

4.2.2 Categorising Surface Covers and Land Uses

Once housing types were classified, land use and surface cover percentages could be determined using the same aerial photographs.

88 Aerial photograph analysis requires that surface covers and land uses are defined before analysis begins. Surface cover in urban areas may be classified as built, asphalt, pavement, open soils/gravel, vegetation or freshwater (Pauleit and Duhme, 2000). Vegetation may be further classified into trees, shrubs, herbs and grasses, lawn or flower beds (Pauleit and Duhme, 2000), turf grass, rough grass, sub-shrubs, vegetables or arable crops (Sekliziotis, 1980). For this study of surface covers and land uses in residential areas the classifications listed in Table 4.4 below were used, based on Gill (2006) and with additional land uses deemed important for this research as areas where trees may grow or be planted.

Table 4.4. Land use and surface cover types, showing the relationships between them. Based on Gill (2006). Land Use Surface Cover Building Building Road Other impervious Pavement Other impervious Tree Shrub On road parking Other impervious Off road parking Other impervious Tree Shrub Front garden Other impervious Mown grass Rough grass Tree Shrub Back garden Other impervious Mown grass Rough grass Tree Shrub Alleyway Other impervious Tree Shrub Public open space Tree Shrub Mown grass Rough grass Communal open space Tree Shrub Mown grass Rough grass

In order to reduce errors in classification, these land uses had to be defined: Buildings are defined as any built structure, including houses, shops, offices and industrial premises. Roads are defined as any impermeable surface primarily used for vehicle movement. Footpaths are defined as any surface (tarmac/paved or permeable)

89 primarily used by pedestrians. Off road car parking is defined as any surface used as an off road car park (public or private). On road car parking is defined as any impermeable surface separated from the road by paint or other road markings for on road car parking. Front gardens are defined as an area in front of a house, facing the road. Back gardens are defined as an area behind a house, facing the back of other houses. Alleyways are defined as a walkway separating the back gardens of houses, leading out into the street. Trees are defined as a tree of any species, age or condition. Shrubs are defined as a shrub of any species, age or condition. Public open space is defined as any area that is open to the public. Communal open space is defined as any enclosed area available only to residents of the building which encloses it, such as courtyards and quads.

‘Private open space’ was also originally an additional land use category, but it proved to be too difficult to differentiate from public open space or communal open space using only street maps and aerial photographs so this category was abandoned. Cultivated land, disturbed land, water, bare soil/gravel and crops were also originally included, but none of these land uses or surface covers were identified in the study area during the analysis, so have been omitted here.

A preliminary test was carried out to determine the ease of working with these categories and aerial photographs. The diagrams below (Figure 4.5) give examples of the different classifications.

Other impervious back garden

Other impervious -On road parking

Tree – communal open space

Mown grass - communal open space

Other impervious - Mown grass Building Other impervious 90 pavement - back garden – off road parking Shrub – front garden

Tree – back garden

Other impervious – road

Tree - Other impervious - pavement alleyway

Rough grass – back garden

Tree – public open space

Tree – front garden

Mown grass – public open space

Figure 4.5. A demonstration of classification of land use and surface cover types.

These classifications were easy to consistently identify using aerial photographs, and so were used to classify the whole of the study area.

91 Methods of accurately sampling land use and surface cover percentages

As discussed in 3.4.1, random point sampling was chosen as the most appropriate sampling method to determine proportions of surface covers and land uses within the study area.

To generate random points, an extension in ArcGIS 3.3 (ESRI, 1999) was used, available from the United States Forestry Department (USDA, no date). This was combined with the Photo Interpretation Tool, available from the same source. 500 random points were generated for each housing category, and each point was classed as a certain surface cover or land use. Classification of surface cover and land use were done separately using the same randomly generated points.

Figure 4.6 (below) shows a screen shot of the Photo Interpretation tool in use analysing surface cover. The yellow dot is the point to be classified, and it is classed as a tree.

Point to be classified

Point to be classified later

Figure 4.6. A screen shot of the Photo Interpretation Tool in action. The yellow dot is the point which is to be classified; the blue dot is a point to be classified later.

92 To ensure that 500 points was sufficient to give consistent results, a cumulative frequency chart was produced for each housing category, detailing the percentages of surface cover or land use calculated as each point was calculated. Figure 4.7 below demonstrates this graphically for surface covers in the pre-1919 semi-detached housing type.

50

Building

40 Road

30 Tree

Shrub 20 Percent surface cover Mown grass 10 Rough grass

0 0 50 100 150 200 250 300 350 400 450 500 Point number

Figure 4.7. Cumulaive frequency graph of percentage surface cover for the pre-1919 semi-detached housing type.

The graph shows that the percentages of surface covers varied greatly to begin with, but by around 150 points the percentages became quite consistent. This pattern was repeated in the other housing types for both surface cover and land use, showing that 500 points gives reliable percentages of surface cover and land use.

4.2.3 Position of Trees

For each housing type, the amount of surface cover of trees within each land use was also determined. This was possible as the same 500 points were classified for both surface cover and land use. Tree position was calculated using the ‘crosstabulate’ function in SPSS, a statistical program. This shows both the amount of tree cover over a single land use and the percentage of total tree cover that is found in each land use.

93 4.3 Results

4.3.1 Housing Morphology

Figure 4.8 below shows the percentage area covered by each housing type.

Pre 1919 Semi

Pre 1919 Terrace Onto Road

Pre 1919 Terrace Front Yard

Pre 1919 Terrace Front and Back Garden 1919-1959 Semi

1919-1959 Terrace

Post 1950s Semi

1960s Terrace – Drive

1960s Terrace – Walkway

Post 1960s Terrace

Post 1960s Terrace – Court/Square

Figure 4.8. Statistics for differing housing types across the study area.

It is clear that the largest area of high density housing is covered by pre 1919 terraced housing with a front yard. This is followed by pre 1919 terraced housing that opens onto the road, then 1960s terraced housing with a driveway. Almost half (45.5%) of high density housing was built before 1919, indicated by the line shading in Figure 4.8. The square shading shows the proportion of housing built in the 1960s; 19% in total. 16.5% of high density housing was built between 1919 and 1959, 19% was built in the 1960s, 10% was built post 1970 and 8.9% was built as semi-detached housing post 1960.

94 The figure below (Figure 4.9) shows amounts of high density housing by local authority. Local authority Area (ha) Bolton Bolton 478.7933 Bury 229.934 Bury Manchester 830.4308 Salford 456.0266 Manchester

Trafford 180.3853 Salford Wigan 446.69 Total 2626 Trafford

Wigan

Figure 4.9. Area of high density housing (in hectares) in each local authority of the study area.

Manchester has the largest amount of high density housing, followed by Bolton, while Trafford and Bury have the lowest amount.

4.3.2 Surface Cover and Land Use Analysis

The following figures show the differences in surface cover and land use of each type of housing.

Pre 1919 Semi-detached Housing Surface Covers

Cumulative Frequency Percent Percent Building Building 154 30.8 30.8 Other impervious Other Tree 206 41.2 72.0 impervious Shrub Mown grass Tree 58 11.6 83.6 Rough grass Shrub 32 6.4 90.0 Mown grass 37 7.4 97.4 Rough grass 13 2.6 100.0 Total 500 100.0

Figure 4.10.Surface cover in pre1919 semi-detached housing.

Buildings and other impervious surfaces equate to 72% of the total area of this housing type, as shown in Figure 4.10. A fairly large amount of rough grass exists; during analysis it was noted that this appeared to be within the large unmaintained gardens of large houses probably converted to flats or other uses rather than a single family home. There is a relatively high proportion of trees, 11.6%, in this category.

95 Land Use

Building Cumulative Road Frequency Percent Percent Pavement Building 154 30.8 30.8 On road parking Road 61 12.2 43.0 Off road parking Pavement 49 9.8 52.8 Front garden Back garden On road 7 1.4 54.2 parking Alleyway Off road Public open space 6 1.2 55.4 parking Front 45 9.0 64.4 garden Back 150 30.0 94.4 garden Alleyway 19 3.8 98.2 Public open 9 1.8 100.0 space Total 500 100.0

Figure 4.11.Land use in pre1919 semi-detached housing.

Figure 4.11 shows that this housing type has a large amount of back garden space. There is little space for dedicated car parking. Nearly 10% of all the land is pavement, and there is a very small amount of public open space. During analysis it was noted that some of this space was due to the demolition of one or two houses in a street, leaving bare ground which became vegetated.

Table 4.5. The percentage of tree cover found within different land uses, and the tree cover as a percentage of each land use in pre-1919 semi-detached housing. Pavement Off road Front Back Alleyway Public parking garden garden open space Tree cover 5.2 1.7 10.3 67.2 1.7 13.8 Percentage of 6.1 16.7 13.3 26.0 5.3 88.9 land use that is a tree

Table 4.5 shows that trees are mainly found in back gardens in this housing type, with some trees found in public open space and in front gardens. Trees account for a large amount of surface cover in public open space, but account for only a quarter of the surface cover of back gardens.

96 Pre 1919 Terraced Onto Road Surface Cover

Cumulative Building Frequency Percent Percent Other impervious Building 210 42.0 42.0 Tree Other 254 50.8 92.8 Shrub impervious Mown grass Tree 8 1.6 94.4 Shrub 13 2.6 97.0 Mown 15 3.0 100.0 grass Total 500 100.0

Figure 4.12. Surface cover in pre-1919 terraced onto road housing.

Figure 4.12 shows that 92.8% of land in this housing type is building or other impervious surfaces. There is very little vegetated cover. Land Use

Building Cumulative Frequency Percent Percent Road Pavement Building 210 42.0 42.0 On road parking Road 69 13.8 55.8 Off road parking Pavement 61 12.2 68.0 Back garden On road 11 2.2 70.2 Alleyway parking Off road Public open space 1 .2 70.4 parking Back 101 20.2 90.6 garden Alleyway 42 8.4 99.0 Public open 5 1.0 100.0 space Total 500 100.0

Figure 4.13. Land use in pre-1919 terraced onto road housing.

Land use in this housing type is mainly building and back gardens, as shown in Figure 4.13. As with the ‘pre-1919 semi-detached’ housing type, there is little dedicated space for car parking. Percentage land use for roads and pavements is also similar to the ‘pre- 1919 semi-detached’ category, though there is more alleyway space in this housing category. During analysis it was noted that, analogous to ‘pre-1919 semi-detached’, some of the small amount of public open space is due to the demolition of one or two houses in a street, rather than planned public space.

Table 4.6. The percentage of tree cover found within different land uses, and the tree cover as a percentage of each land use in pre-1919 terraced onto road housing . Pavement Back garden Public open space Tree cover 25 37.5 37.5 Percentage of land 3.3 3.0 60.0 use that is a tree

97 The few trees which are found in this housing type are found in pavements, back gardens and public open space, shown in Table 4.6. Trees account for very little surface cover in pavements and back gardens, but account for a large amount of surface cover in public open space.

Pre-1919 Terraced with Front Yard

Surface Cover

Cumulative Frequency Percent Percent Building Building 192 38.4 38.4 Other impervious Other Tree 267 53.4 91.8 impervious Shrub Tree 13 2.6 94.4 Mown grass Shrub 19 3.8 98.2 Mown grass 9 1.8 100.0 Total 500 100.0

Figure 4.14. Surface cover in pre-1919 terraced housing with front yard.

Similar to ‘pre-1919 terrace onto road’, 91.8% of land is building or other impervious, shown in Figure 4.14. However, there are more shrubs in this category, mostly within the front yards as small hedges or potted shrubs. Land Use

Cumulative Percent Frequency Percent Building Building 192 38.4 38.4 Road Road 83 16.6 55.0 Pavement Pavement 53 10.6 65.6 On road parking On road Front garden 9 1.8 67.4 parking Back garden Front Alleyway 34 6.8 74.2 garden Public open space Back 80 16.0 90.2 garden Alleyway 48 9.6 99.8 Public open 1 .2 100.0 space Total 500 100.0

Figure 4.15. Land use in pre-1919 terraced housing with a front yard.

There is less area of back gardens in this category and more front garden area than the previous categories, shown in Figure 4.15. There is very little public open space, even when compared to the low amount in the two previous categories. The amount of alleyway space is similar to ‘pre1919 terrace onto road’; the overall housing layout is almost identical between these categories so some similarity is expected. There is very little dedicated car parking space, similar to the other ‘pre-1919’ categories. 98 Table 4.7. The percentage of tree cover found within different land uses, and the tree cover as a percentage of each land use in pre-1919 terraced housing with front yard. Pavement Back garden Alleyway Public open space Tree cover 15.4 46.2 30.8 7.7 Percentage of 3.8 7.5 8.3 100 land use that is a tree

Table 4.7 shows that trees are mainly found in back gardens, with some trees found in alleyways, with fewer trees found in pavements and public open space. Trees form very little of the surface cover of pavements, back gardens and alleyways in this housing category. Trees form 100% of the surface cover of public open space, which shows how little public open space there is in this housing type.

Pre-1919 Terraced with Front and Back Garden

Surface Cover

Cumulative Frequency Percent Percent Building Building 173 34.6 34.6 Other impervious Other 223 44.6 79.2 Tree impervious Shrub Tree 18 3.6 82.8 Mown grass Shrub 32 6.4 89.2 Rough grass Mown 51 10.2 99.4 grass Rough 3 .6 100.0 grass Total 500 100.0

Figure 4.16. Surface cover in pre-1919 terraced housing with front and back garden.

Overall, 79.2% of land in this category is building or other impervious, less than the ‘onto road’ and ‘front yard’ categories, and more comparable with the ‘semi-detached’ category. This is shown in Figure 4.16. This similarity continues with the appearance of ‘rough grass’ in this category. However, there are fewer trees in this category than in the semi-detached category, with much more mown grass.

99 Land Use

Building Cumulative Road Frequency Percent Percent Pavement Building 173 34.6 34.6 On road parking Off road parking Road 69 13.8 48.4 Front garden Pavement 37 7.4 55.8 Back garden On road 2 .4 56.2 Alleyway parking Public open space Off road 1 .2 56.4 Communal open space parking Front 49 9.8 66.2 garden Back 126 25.2 91.4 garden Alleyway 35 7.0 98.4 Public open 4 .8 99.2 space Communal open 4 .8 100.0 space Total 500 100.0

Figure 4.17. Land use in pre-1919 terraced housing with a front and back garden.

There is more front garden space in this category than any other ‘pre-1919’ category, shown in Figure 4.17. A large amount of back garden space is present, but not as much as the ‘pre1919 semi-detached’ category. As with the other ‘pre-1919’ categories, there is very little dedicated parking space. There is slightly more public open space than the other ‘pre-1919’ classes, and there is also communal open space in this category. There is slightly less alleyway space in this category.

Table 4.8. The percentage of tree cover found within different land uses, and the tree cover as a percentage of each land use in pre-1919 terraced housing with front and back garden. Pavement Front garden Back garden Alleyway Tree cover 27.8 11.1 55.6 5.6 Percentage of 13.5 4.1 7.9 2.9 land use that is a tree

In this housing type, trees are predominantly found in back gardens and pavements, shown by Table 4.8. Fewer trees are found in front gardens and in alleyways. Trees account for a fairly small amount of surface cover of any land use.

100 1919 – 1959 Semi-detached Housing

Surface Cover

Cumulative Frequency Percent Percent Building Other impervious Building 120 24.0 24.0 Tree Other 167 33.4 57.4 impervious Shrub Tree 57 11.4 68.8 Mown grass Shrub 38 7.6 76.4 Mown 118 23.6 100.0 grass Total 500 100.0

Figure 4.18. Surface cover in 1919-1959 semi-detached housing.

Figure 4.18 shows that just 57.4% of this category is building or other impervious, much lower than previous categories. Accordingly there is a much higher percentage of mown grass than previous categories. There are more trees here than previous ‘pre 1919 terrace’ categories.

Land Use

Building Cumulative Road Frequency Percent Percent Pavement Building 120 24.0 24.0 Off road parking Road 56 11.2 35.2 Front garden Pavement 46 9.2 44.4 Back garden Off road 1 .2 44.6 Alleyway parking Public open space Front 76 15.2 59.8 garden Back 189 37.8 97.6 garden Alleyway 5 1.0 98.6 Public open 7 1.4 100.0 space Total 500 100.0

Figure 4.19. Land use in 1919-1959 semi-detached housing.

This housing category has much larger front and back gardens than previous categories, shown in Figure 4.19. There is a much lower amount of space for alleyways, reflecting the larger garden space, the changes in housing estate layout and the improvements in sanitation negating the need for rear access to properties. There is very little dedicated parking.

101 Table 4.9. The percentage of tree cover found within different land uses, and the tree cover as a percentage of each land use in 1919-1959 semi-detached housing. Pavement Front garden Back garden Public open space Tree cover 12.3 10.5 66.7 10.5 Percentage of 15.2 7.9 20.1 85.7 land use that is a tree

Table 4.9 shows that trees are mainly found in back gardens in this housing type. A small number of trees are found in pavements, front gardens and public open space. Trees cover a large amount of public open space, but less of the other land uses.

1919 – 1959 Terraced

Surface Cover

Cumulative

Frequency Percent Percent Building Building 147 29.4 29.4 Other impervious Other 182 36.4 65.8 Tree impervious Shrub Tree 28 5.6 71.4 Mown grass Shrub 44 8.8 80.2 Mown grass 99 19.8 100.0 Total 500 100.0 Figure 4.20. Surface cover in 1919-1959 terraced housing.

Figure 4.20 shows that 65.8% of the land in this category is building or other impervious, more than the semis of the same era but much less than previous terraced housing. Like the semis of this era, there is more mown grass than other vegetated land, and more shrubs. Land Use

Building Cumulative Road Frequency Percent Percent Pavement Building 147 29.4 29.4 Off road parking Road 68 13.6 43.0 Front garden Pavement 39 7.8 50.8 Back garden Off road Alleyway 6 1.2 52.0 parking Public open space Front Communal open space 71 14.2 66.2 garden Back 138 27.6 93.8 garden Alleyway 13 2.6 96.4 Public open 13 2.6 99.0 space Communal open 5 1.0 100.0 space Total 500 100.0

Figure 4.21. Land use in 1919-1959 terraced housing.

102 Figure 4.21 shows that there is more parking in this category than in the ‘1919-1959 semis’. Front garden size is comparable to the ‘1919-1959 semis’, but back gardens are smaller. There is more alleyway space in this category compared to the ‘1919-1959 semis’. There is some communal open space in this category, while there is none in ‘1919-1959 semis’.

Table 4.10. The percentage of tree cover found within different land uses, and the tree cover as a percentage of each land use in 1919-1959 terraced housing. Pavement Front garden Back garden Public open space Tree cover 3.6 14.3 67.9 14.3 Percentage of 2.6 5.6 13.8 30.8 land use that is a tree

In this category, trees are found in pavements, front and back gardens and public open space. They are most common in back gardens, shown by Table 4.10. Trees account for 30.8% of surface cover of public open space, but tree cover is fairly low over other land uses.

Post 1950s Semi-detached Housing

Surface Cover

Cumulative Building Frequency Percent Percent Other impervious Tree Building 119 23.8 23.8 Shrub Other impervious 158 31.4 55.4 Mown grass Tree 29 5.8 61.2 Shrub 38 7.6 68.8 Mown grass 157 31.4 100.0 Total 500 100.0

Figure 4.22. Surface cover in post 1950s semi-detached housing.

Just 55.2% of land in this category is building or other impervious, much lower than previous categories, shown in Figure 4.22. There are fewer trees and much more mown grass than other categories.

103 Land Use Building Cumulative Road Frequency Percent Percent Pavement Building 119 23.8 23.8 Off road parking Road 67 13.4 37.2 Front garden Pavement 25 5.0 42.2 Back garden Off road Public open space 10 2.0 44.2 parking Communal open space Front 84 16.8 61.0 garden Back 172 34.4 95.4 garden Public open 21 4.2 99.6 space Communal open 2 .4 100.0 space Total 500 100.0

Figure 4.23. Land use in post 1950s semi-detached housing.

Figure 4.23 shows that there is more off road parking in this category than previous categories. The area of front and back gardens is comparable with ‘1919-1959 semi- detached’, and is higher than the other previous categories. There is a lot more public open space than previous categories.

Table 4.11. The percentage of tree cover found within different land uses, and the tree cover as a percentage of each land use in post 1950s semi-detached housing. Pavement Front Back Public open Communal garden garden space open space Tree cover 13.8 13.8 51.7 17.2 3.4 Percentage 16.0 4.8 8.7 23.8 50.0 of land use that is a tree

Trees are mainly found in back gardens in this housing type, shown in Table 4.11. Trees cover nearly a quarter of public open space, and half of communal open space, but account for less surface cover in other land uses.

1960s Walkway Surface Cover

Cumulative Frequency Percent Percent Building Other impervious Building 139 27.8 27.8 Tree Other 152 30.4 58.2 Shrub impervious Mown grass Tree 74 14.8 73.0 Shrub 9 1.8 74.8 Mown grass 126 25.2 100.0 Total 500 100.0

Figure 4.24. Surface cover in 1960s terrace walkway housing.

104 Figure 4.24 shows that just 58.2% of land is covered by building or impervious surfaces in this category. Trees account for a high percentage of surface cover. The large amount of mown grass suggests that trees may not be very close to buildings.

Land Use

Building Cumulative Frequency Percent Percent Road Pavement Building 139 27.8 27.8 Off road parking Road 45 9.0 36.8 Front garden Pavement 51 10.2 47.0 Back garden Off road Public open space 56 11.2 58.2 parking Communal open space Front 7 1.4 59.6 garden Back 16 3.2 62.8 garden Public open 171 34.2 97.0 space Communal open 15 3.0 100.0 space Total 500 100.0

Figure 4.25. Land use in 1960s terraced walkway housing.

Unsurprisingly for this housing category of ‘1960s-walkway’, pavements account for more land use than roads, as shown by Figure 4.25 above. Public open space covers more land than buildings, which is very unusual. There is a large amount of off road parking in this housing type compared to other housing types. Front and back garden space is low, as flats do not have gardens and most housing along walkways do not have front gardens.

Table 4.12. The percentage of tree cover found within different land uses, and the tree cover as a percentage of each land use in 1960s terrace walkway housing.

Pavement Off road Front Back Public Communal parking garden garden open space open space Tree cover 5.4 5.4 2.7 2.7 78.4 5.4 Percentage 7.8 7.1 28.6 12.5 33.9 26.7 of land use that is a tree

Trees are found almost entirely in public open space in this category, shown in Table 4.12. They are also found in off road parking, pavements and front and back gardens, but to a much lesser degree. Trees account for a reasonable amount of the surface cover of public open space, front gardens and communal open space, but fairly small amounts of other land uses.

105 1960s Driveway

Surface Cover

Cumulative Frequency Percent Percent Building Other impervious Building 132 26.4 26.4 Tree Other 209 41.8 68.2 Shrub impervious Mown grass Tree 27 5.4 73.6 Shrub 21 4.2 77.8 Mown grass 111 22.2 100.0 Total 500 100.0

Figure 4.26. Surface cover in 1960s terrace driveway housing .

Overall, 68.2% of land is covered by buildings and other impervious surfaces in this category, shown in Figure 4.26. Tree and shrub cover is low, with low maintenance mown grass covering almost as much space as buildings. The high level of impervious surfaces demonstrates the number of driveways which categorise this housing type.

Land Use

Cumulative Building Frequency Percent Percent Road Pavement Building 132 26.4 26.4 Off road parking Road 60 12.0 38.4 Front garden Pavement 65 13.0 51.4 Back garden Off road Public open space 35 7.0 58.4 parking Communal open space Front garden 86 17.2 75.6 Back garden 82 16.4 92.0 Public open 36 7.2 99.2 space Communal 4 .8 100.0 open space Total 500 100.0

Figure 4.27. Land use in 1960s terraced driveway housing.

Figure 4.27 shows that pavement accounts for more land use than road, which is similar to the ‘1960s-walkway’ category. There is more garden area in this category, but not as much as the ‘1919-1959’ categories. There is much less public open space in this class than the ‘1960s-walkway’; this may be compensated for in the larger gardens. There is still a large amount of off road parking in this category, despite the widespread provision of driveways for homes. Not all homes were built with a driveway, just the potential for one, so this must be remembered when analysing the figures.

106 Table 4.13. The percentage of tree cover found within different land uses, and the tree cover as a percentage of each land use in 1960s terraced driveway housing. Pavement Off road Front Back Public Communal parking garden garden open space open space Tree cover 14.8 11.1 11.1 29.6 25.9 7.4 Percentage 6.2 8.6 3.5 9.8 19.4 50 of land use that is a tree

Table 4.13 shows that in this housing type, trees are found in pavements, off road parking, front and back gardens and public and communal open space. They are mainly found in back gardens and public open space, with fairly even distribution across other land uses. Trees cover half of communal open space and nearly 20% of public open space, but cover little of other land uses.

Post 1960s Terrace

Surface Cover

Cumulative Frequency Percent Percent Building Building 111 22.2 22.2 Other impervious Other 210 42.0 64.2 Tree impervious Shrub Tree 31 6.2 70.4 Mown grass Shrub 21 4.2 74.6 Mown grass 127 25.4 100.0 Total 500 100.0

Figure 4.28. Surface cover in post 1960s terraced housing.

In total, 64.2% of this housing type is building or other impervious, with other impervious covering a lot more area than the buildings, shown in Figure 4.28. Mown grass cover is very high, with low tree and shrub cover.

107 Land Use

Building Cumulative Road Frequency Percent Percent Pavement Building 111 22.2 22.2 Off road parking Road 66 13.2 35.4 Front garden Pavement 61 12.2 47.6 Back garden Off road Public open space 38 7.6 55.2 parking Communal open space Front 69 13.8 69.0 garden Back 104 20.8 89.8 garden Public open 48 9.6 99.4 space Communal open 3 .6 100.0 space Total 500 100.0

Figure 4.29. Land use in post 1960s terraced housing.

There is around the same amount of land use for pavement as for road in this category, shown in Figure 4.29. There is a fairly large amount of off road parking compared to other housing types. The area of front and back gardens is much smaller than in the semis of the same period, though fairly high compared to other terraced housing.

Table 4.14. The percentage of tree cover found within different land uses, and the tree cover as a percentage of each land use in post 1960s terraced housing. Pavement Front garden Back garden Public open space Tree cover 9.7 9.7 48.4 32.3 Percentage 4.9 4.3 14.4 20.8 of land use that is a tree

The trees in this housing type are mainly found within back gardens and public open space, with a few found in pavements and front gardens, shown in Table 4.14 above. Trees account for 20.8% of the surface cover of public open space, but less of other land uses.

108 Post 1960s Court/Square

Surface Cover

Cumulative Frequency Percent Percent Building Other impervious Building 168 33.6 33.6 Tree Other 191 38.2 71.8 Shrub impervious Mown grass Tree 22 4.4 76.2 Shrub 24 4.8 81.0 Mown grass 95 19.0 100.0 Total 500 100.0

Figure 4.30. Surface cover in post 1960s court/square housing.

Figure 4.30 shows that overall, 71.8% of land in this category is building or other impervious surfaces. Building and impervious surfaces cover a similar amount of land, which is different to the previous few categories, and is more comparable to the pre-1919 categories.

Land Use

Building Cumulative Road Frequency Percent Percent Pavement On road parking Building 168 33.6 33.6 Off road parking Road 66 13.2 46.8 Front garden Pavement 61 12.2 59.0 Back garden On road Public open space 3 .6 59.6 parking Communal open space Off road 40 8.0 67.6 parking Front garden 17 3.4 71.0 Back garden 44 8.8 79.8 Public open 24 4.8 84.6 space Communal 77 15.4 100.0 open space Total 500 100.0

Figure 4.31. Land use in post 1960s court/square housing.

Figure 4.31 shows that road and pavements cover a similar amount of land in this housing type, which is surprising. On road parking is present in very small quantities, with a reasonable amount of off road parking. Front and back garden space is small, while there is a fair amount of communal open space available in the courtyards of this housing type. There is not a lot of public open space.

109 Table 4.15. The percentage of tree cover found within different land uses, and the tree cover as a percentage of each land use in post 1960s court/square housing. Off road Front garden Public open Communal parking space open space Tree cover 4.5 4.5 40.9 50 Percentage 2.5 5.9 37.5 14.3 of land use that is a tree

Table 4.15 shows that trees are mainly found in public and communal open space, with few found in front gardens and off road parking. No trees are found in pavements or in back gardens, which is unique to this housing type.

4.3.3 Comparative Data

Figure 4.32 (below) shows a comparison of surface covers across housing types, and the average for all high density housing. The lowest percentage surface cover of buildings was in post 1960s terraced housing (22.2%), and the highest percentage was in pre1919 terraced housing which opens directly onto the road (42%). It is interesting to note that all types of pre1919 terraced housing have similar percentages of surface cover of buildings, which then dropped as housing density decreased after 1919. The amount of area covered by impervious surfaces varied greatly, from 30.4% in ‘1960s walkway’ housing to 53.4% in ‘pre 1919 terraced housing with a front yard’. Impervious surfaces decreased in housing developments built between 1919 and the 1960s, but increased in newer housing.

Tree cover varied greatly, from 1.6% tree cover in ‘pre 1919 onto road’ housing to 14.8% tree cover in ‘1960s walkway’ housing, with an average of 6.64%. There was no clear pattern across ages of housing. Mown grass cover is low in the earlier housing types (below 11%), which is much lower than the average. Mown grass cover was much higher in later housing types, higher than average at around 20%, reaching as much as 31.4% of surface cover in the ‘post 1950s semi-detached’ category.

These average surface covers found in this study match very closely with the findings of Gill (2006), upon which this study of high density housing areas was based.

110 Rough grass Rough grass Mown Shrub Tree Other impervious Building Overall Average Post 1960s CourtSquare Terrace Post 1960s 1960s Terrace Walkway 1960s Terrace Terrace Drive Semi Post 1950s Terrace 1919-1959 Housing type Housing Semi 1919-1959 Garden Pre1919 and and Back Front Front Yard Pre1919 Front Front Yard Pre1919 Onto Onto Road Semi Pre1919 0%

80% 60% 40% 20%

100% Percentage surface cover surface Percentage

Figure 4.32. A comparison of surface cover proportions across housing types.

111 Figure 4.33 (below) shows a comparison of land use across housing types, and the overall average. The amount of pavement varied from 13% in ‘1960s terrace drive’ to just 5% in ‘post 1950s semi-detahced’ housing, with an average of 9.96%. There was little dedicated space for on road parking, which only appears in pre 1919 housing types and in ‘post 1960s courtsquare’ housing. There was also little off road parking in pre 1960s housing and in post 1950s semi-detached housing; however, terraced housing from the 1960s onwards did contain a reasonable amount of off road parking. Front and back garden space varied greatly, though all housing types had a similar or larger amount of back garden space compared to front garden space. The largest front and back gardens were found in 1919-1959 houses and in post 1950s semi-detached housing. The smallest gardens were found in ‘1960s walkway’ housing; pre 1919 housing also had fairly small gardens. The levels of public open space varied from almost none in the pre 1919 housing types, with a little more in 1919-1959 housing types, to around 5% or more post 1959. The exception was the very large amount of public open space in ‘1960s walkway’ housing. There was also very little or no communal open space in housing types other than ‘post 1960s courtsquare’ type, where communal open space was a defining feature of the housing.

112 Communal open space open Public space Alleyway Back garden Front garden Off road parking road On parking Pavement Road Building Overall Average Post 1960s CourtSquare Terrace Post1960s 1960s Terrace Walkway 1960s Terrace Terrace Drive Semi Post 1950s Terrace 1919-1959 Housing type Housing Semi 1919-1959 Garden Pre1919 andBack Front Front Yard Pre1919 Front Front Yard Pre1919 Onto Road Onto Semi Pre1919

0%

80% 60% 40% 20% 100% use land Percentage

Figure 4.33. A comparison of proportions of land use across housing types.

113 4.3.4 Locations of trees

The table below shows where trees were located across all housing types. Of the total area surveyed, 48.1% was either ‘building’, ‘road’ or ‘on road parking’, where trees cannot grow or be planted. That left 51.9% of the area which could be a tree; of which just 11.8% of the possible area and just 7.28% of the total area was actually a tree. The table below shows where the trees were located in all housing types.

Table 4.16. The percentage of surface cover of trees in each appropriate land use. Land use Pavement Off Front Back Alleyway Public Communal road garden garden open open space parking space Percentage 9.6 2.5 8.5 42.6 1.6 30.2 4.9 of total trees

Trees were most commonly found in back gardens and public open space, and rarely found in alleyways and off road parking. Nearly half of trees are found on public land.

16

14

12 Pre1919 Semi Pre1919 Onto Road 10 Pre1919 Front Yard Pre1919 FrontYard BackGarden 1919-1959 Semi 8 1919-1959 Terrace Post50s Semi 60s Terrace Drive 6 60s Terrace Walkway

Percentage Surface Cover Surface Percentage Post60s Terrace Post60s CourtSquare 4

2

0

Figure 4.34. The percentage of tree cover in each housing type.

Figure 4.34 (above) shows the percentage of tree cover in different housing categories. The highest tree cover was found in ‘1960s walkway’ housing, followed by ‘1919-1959 semi-detached’ housing and ‘pre 1919 semi-detached’ housing. Tree cover was low in pre 1919 terraced housing but increased in later built housing, although tree cover decreased slightly in the most recent housing type, ‘post 1960s courtsquare’ housing.

114 4.4 Discussion

The results have demonstrated that high density housing in the study area may be classified into eleven distinct housing types, and that tree cover varies greatly between these housing types.

4.4.1 Distribution and amount of housing types across the study area

Manchester has the largest area of high density housing, followed by Bolton, while Trafford and Bury have the lowest amount. This is not surprising; Manchester and Bolton developed rapidly during the 19 th century and built large amounts of high density housing to accommodate increasing numbers of workers, and much of this housing remains today or has been replaced with similar density homes. Trafford and Bury developed later, with less defined centres and more undeveloped land, so the small amount of high density housing is expected.

The categories ‘pre 1919 terraced housing with a front yard’ and ‘pre 1919 terraced housing that opens onto the road’ account for the largest and second largest amounts of high density housing, and all pre 1919 built housing accounts for nearly half of all the high density housing in the study area. This is not surprising given Greater Manchester’s history as an industrial conurbation which developed rapidly during the Victorian era, with cheap dense housing built to accommodate a growing number of workers and their families. The category ‘1960s driveway’ housing is the third largest type of housing; after the Second World War, much of the poor quality Victorian terraces were cleared as part of slum clearance schemes, and 1960s housing built in its place. Some 1960s housing was itself cleared and replaced with ‘post 1960s terraces’ and ‘post 1960s courtsquare’ housing.

The process of urban building and renewal is reflected in the amount of housing built in each era. 45.5% was built before 1919, in dense Victorian terraces. 16.5% was built between 1919 and 1959, as short terraces and semi-detached housing with gardens. 19% of the housing was built in the 1960s as high rise flats and as pedestrianised estates, usually on the site of cleared Victorian terraced housing. Just 10% of the study area’s housing was built as terraces or in courtyard form post 1970, and a mere 8.9% was built as semi-detached housing post 1960.

115 4.4.2 Influences on tree cover in housing types

The category of ‘1960s walkway’ housing contained the highest amount of tree cover. It was the third least built up and contained the third highest amount of mown grass, which alone would not be expected to give the highest amount of trees. This housing category contained by far the most amount of public open space however (34.2% of total land use, higher than buildings), where 78.4% of its trees were found and contributed to its tree cover of 15%. The buildings in this housing category were mainly blocks of flats surrounded by greenspace, or blocks of houses linked by footpaths and surrounded by greenspace, so the large amount of public open space is less surprising than is first evident. The public open space is maintained by the local authority and it may be argued that trees surrounded by mown grass is low maintenance as the trees may be mown around and very infrequently maintained as they are, for the most part, not close enough to buildings to cause a perceived nuisance. If public open space becomes neglected it is possible that trees may move in naturally from surrounding areas; this would have increased tree cover with little official effort. The same may be said for the tree cover in areas of communal open space (where 5.4% of trees are found). However, it is difficult to find evidence of this.

‘Pre 1919 semi-detached’ housing had the second highest level of tree cover (12%). and ‘1919-1959 semi-detached’ housing had the third highest level of tree cover (11%). This reflects the larger amount of space around semi-detached houses for tree growth and possibly also the long timeframe trees have had to grow and mature to the present day. ‘1919-1959 semi-detached’ housing contained the second lowest amount of buildings and impervious surfaces and the largest amount of back garden space, where 66.7% of its trees were found. This suggests there is more room for trees to grow in garden soil, therefore the relatively high tree cover is not surprising. The remainder of trees found in this housing type were quite evenly spread across pavement, front garden and public open space. In contrast, ‘pre 1919 semi-detached’ was the 4 th most built up housing type, but with 30% of land use as back garden and very small amounts of other land uses. Therefore, there was a large amount of pervious garden space where trees may grow, and it is not surprising that 67.2% of trees were found in back gardens. The remainder of trees were found in small numbers in all other appropriate land uses. These three housing types accounted for just 18.2% of the high density housing area in this study; high density housing with a comparatively high level of tree cover is therefore uncommon.

116 Pre 1919 terraced housing contained very few trees and little vegetation. These three housing types were the most built up, with ‘pre 1919 onto road’ and pre 1919 front yard’ containing over 90% built and impervious surfaces. Front and back gardens were almost all impervious, allowing little chance of tree growth. Of the small number of trees that were present in these housing types, the majority were found in back gardens, with around a quarter growing in pavements and the rest in front gardens, alleyways and public open space. This is similar to the overall figures of tree growth location, though more trees were present in pavements in these housing types than the overall figure. These housing types accounted for 43.8% of housing across the study area; therefore, a large proportion of the study area contained very few trees.

The amount of mown grass and area for gardens increased from 1919 onwards, reflecting the decreasing in housing density ordered by the 1919 Housing and Town Planning Act (Hawks and Souza, 1981) and the growing demand for garden space, though this increase in non-built space does not link with an increase in tree growth. Tree cover does increase after 1919 but remained relatively stable at around 4-6%, excluding the exceptions mentioned above. The reasons for this are unclear; despite space for trees, trees were not planted nor did they move in naturally. For more recent housing (newer post 1960s housing), the lack of trees may be due to the time needed for trees to colonise the new areas of gardens and open space naturally, or for residents to decide their area would be improved if trees were planted. For older housing, reasons for lack of tree cover are less clear; it is possible that residents’ desire for a low maintenance lawn override any ideas of tree planting on their property.

Overall, trees were mainly found in back gardens and public open spaces, and just under half of trees were found on public land. This suggests that residents and local authorities have equal responsibility for tree care and planting across high density housing areas, although the precise amount varies. These findings are compared with similar studies as part of the overall discussion in Chapter 8.

117 4.5 Summary and Conclusions

This chapter has presented the methodology (Section 4.2) and results (Section 4.3) of classifying high density housing within the study area, and analysing its surface cover and land use to determine tree distribution. It has examined the relationship of housing density and housing layout on the distribution of trees in high density housing areas, given in the Conceptual Framework of Section 3.1.1. The main findings of this chapter are: • there are 11 different types of high density housing within the study area; • the majority of housing was built either before 1919 or in the 1960s; • there are very different amounts of surface cover and land uses between housing of different types; • tree cover varies from 1.6% to 15% – variation of a factor of 9; • tree cover is affected by house type, housing age, the amount of public open space and the amount of built and impervious surface cover; • semi-detached housing contains more trees than terraced housing and housing built post 1919 contains more trees; • for post 1959 terraced housing, the more public open space in a housing type, the more trees there are.

The differences in housing type reflect the historical development of Greater Manchester, and the specific housing types are likely to be seen in other industrial cities. Differences in surface covers and land uses were expected, although the scale of differences was surprising. Differences in tree cover were expected, but the scale of differences is startling. It is clear that both housing density and housing type have a large role to play in determining the amount and distribution of trees. The lower the amount of built and impervious surfaces the more potential there is for trees, although this potential is not always fully realised; this is particularly seen in post 1950s semi-detached housing, where a large amount of mown grass has not been planted with trees. The results demonstrate that there is a relationship between housing layout and tree distribution, which can be added to the Conceptual Framework in Section 9.1.1.

This potential for tree planting will be examined in the next chapter, which sets out how Objective Two is achieved. Data about surface covers and land uses calculated in this chapter will be used with other methods to determine the potential for increasing tree cover, and how this increase will affect surface temperatures and rainfall runoff. 118 Chapter 5 – Increasing Tree Cover and its Effects on Maximum Surface Temperatures and Rainfall Runoff

This chapter states how Objective Two ‘ To examine the influence of tree cover on environmental quality of high density residential neighbourhoods in a changing climate ’ was achieved. A brief overview of methods was given in Section 3.4.2, with more detailed methods given here. This chapter presents work examining the potential for tree planting in each of the housing types, using a method based on aerial photographs, surface covers and land uses. Using this new data, plus surface cover and land use data generated in the previous chapter (Chapter 4), environmental quality under varying climate change scenarios is calculated for each housing type. The variables used as an assessment of environmental quality are surface temperature and rainfall runoff.

5.1 Introduction

The urbanising of an area greatly affects the natural functions of the ecosystem upon which it has been built. Concreting and paving areas increases rainwater runoff as the ground is now impervious, and these materials also store heat, leading to increased temperatures compared to surrounding non urban land. The effects of these changes have been studied in great detail and a number of models have been developed to predict what changes may occur due to urbanisation (e.g. Whitford et al., 2001). These models use proportions of surface covers to predict surface temperatures and rainfall runoff in built up areas. Using the proportions of surface covers calculated in Chapter Four, this chapter uses two such models to determine effects of increasing temperatures and rainfall events on each high density housing type. Previous research in the study area (Gill et al., 2007) suggested that if greenspace is increased by 10% in urban residential areas, surface temperatures may be kept at around 1990 levels, despite the predicted increase in temperatures due to climate change. However, the feasibility of this in high density housing areas is unknown.

5.2 Methods

In order to determine how the planting of more trees may affect the surface temperatures and rainfall runoff of high density housing areas, it was necessary to determine how

119 many trees could in principle be planted in each housing type, and what land use and surface cover they would replace.

5.2.1 Determination of Potential Increases in Tree Cover

Firstly, areas to sample were chosen. Polygon areas were calculated using functions within ArcGIS 9.0. An area of around 10,000m 2 was selected as an appropriate size for sampling, as this contains one or two streets or culs-de-sac of between 40 and 70 homes in each housing type. This was judged to give a good example of the typical morphology of each housing type and so a good idea of where extra trees may be planted. For each housing type, polygon size was listed numerically, and the polygon with an area nearest to 10,000m 2 identified. A further ten polygons were selected, five listed above the polygon nearest to 10,000m 2 and five below. These polygons were then located in ArcGIS 9.0, and potential tree sites were identified, as shown in Figure 5.1. Location of potential trees was subject to a number of considerations, which are outlined below. The land use and surface cover of under each potential tree was noted for use in later analysis.

Cursor tool. With viewfinder tool, around 2m diameter at this scale (1:654)

Trees ‘planted’ in pavement 8m apart, in front of houses

Trees ‘planted’ in back gardens

120 Trees ‘planted’ in pavement 8m apart

Trees ‘planted’ in public open space

Trees ‘planted’ in off road parking

Figure 5.1. Two examples of the ‘planting’ exercise within a GIS.

Trees cannot be planted into roads or into on road parking and cannot replace buildings. It was assumed that trees could be planted into any other land use/surface cover combination in an area of at least 2.5m x 2.5m, regardless of any underground services that may be present, the cost of planting, the pavement width (as this may be changed as part of a planting project) and any potential resident objections. Where there was open space, trees were ‘planted’ at least 2m apart, usually in rows to give the largest number of trees per area. Therefore, the calculated figures for tree cover increase must be treated as an ideal maximum, with any actual increases viewed as a proportion of the total.

The Green Streets team of the Red Rose Forest plant trees around 8m apart along pavements, or at the boundary between two houses, whichever seems more appropriate (see Figure 5.2 below). This guidance has been followed when selecting potential tree planting sites along pavements. It has been assumed that the trees planted would be small ornamental or pioneer species, and silver birch ( Betula pendula ) was taken as a typical example. This tree has a canopy of around 1.15m 2 at approximately 5 years old.

121

Figure 5.2. A diagram demonstrating the location of a newly planted tree according to Red Rose Forest guidelines.

5.2.2 Calculating Increase in Tree Cover

Once all polygons were ‘planted’ with trees, it was possible to calculate the potential tree cover for each housing type. The number of trees was converted to number of square metres covered by the trees (total trees x 1.15m 2), which was then divided by the total area surveyed to give percentage of land covered by trees.

Increasing tree cover will affect maximum surface temperatures and the rainfall runoff of an area. There are a number of computer models described in the literature for calculating these changes, although many are very complex and require a large amount of detailed data to produce results (Tso et al., 1991). However, there are models which require only fairly basic information about climate and surface covers of an area to calculate these environmental changes. These two models for maximum surface temperature and surface runoff are described briefly below, and used to calculate current and potential scenarios in each housing type in this study.

5.2.3 The Energy Balance Model

Existing computer models analysing temperature changes may be split into those that are related to the microscale climate within the (below-roof level) urban canopy layer, and the so-called mesoscale climate within the (above roof level) urban boundary layer (Tso et al., 1991). Most models are complex and cannot easily be solved analytically, therefore are unsuitable for the extensive comparisons of climate variations required in this study. Tso et al. (1991) developed a simple, easily solved model of microscale climate effects for the city of Kuala Lumpur, Malaysia, using simultaneous linear differential equations. This model has a number of underlying assumptions about climate

122 interactions 3, and requires a small amount of local climate data and the proportion of building and evapotranspiring surfaces in order to predict surface temperatures through the day. This was further refined by Whitford et al. (2001) for Liverpool, UK and used by Gill (2006) and Gill et al. (2007) for Greater Manchester, UK. As this model is simple to use, requires easily obtainable data and has already been proven successful across the study area, it will also be used in this research.

Tables 5.1 and 5.2 (below) give the weather variables used as part of the Energy Balance Model. Table 5.1 shows the constants used for Kuala Lumpur (Tso et al., 1991), Liverpool, UK (Whitford et al., 2001) and Manchester, UK (Gill et al., 2007), while Table 5.2 shows the variable values. Gill et al.’s (2007) constants were also used in the current study, as the area studied is the same and so will be under the same assumed meteorological conditions.

3 The model is based on six main assumptions about the local climate (Gill, 2006). Firstly, it is assumed that all the meteorological and soil parameters remain constant horizontally. Secondly, the turbulent diffusivities for heat and water are given by the near-neutral value for momentum. Thirdly, the turbulent fluxes of heat and water are assumed to be constant over the surface boundary layer (SBL). Fourthly, the temperature, wind speed, and specific humidity are assumed to be constant at the heat of the SBL. Fifthly, the urban canopy is assumed to have a unique roughness length. Finally, anthropogenic heat sources such as vehicles and air conditioning units have been neglected (Tso et al., 1991; Gill, 2006).

123 Table 5.1. Constants used in the Energy Balance Model by previous authors. Parameter Unit Value Comments and notation 4 Tso et al. Whitford et Gill et al. (1991) al. (2001) (2007) Specific heat of J/kg/°C 1006* 1006 1006 *At 27°C air, Ca 5 (Holman, 2010) Specific heat of J/kg/°C 880* 880 880 *Holman, 2010 concrete, C c Density of air, kg/m 3 1.177* 1.777 1.208 + *At 27°C 6 ρa (Holman, 2010) +At 21°C Thermal W/m/°C 1.225* 1.225 1.083 + *average for conductivity of dry and soil, k s saturated clay Specific heat of J/kg/°C 1185* 1185 1180 + soil (Oke, 1978) + soil, C s average for dry Density of soil, kg/m 3 1800* 1800 1800 and saturated ρs sandy soils (Oke, 1978) Latent heat of J/kg 2.437x10 6 2.437x10 6 2.452x10 6 *At 27°C (Oke, evaporation, L * + 1978) 7 +At 21°C Roughness m 5* 2+ 2 *Assumption + length, Z 0 UK Met Office data Height of SBL, m 300* 800 800 *Assumption + Z2 ‘Average’ for clear hot day, UK Met Office Wind velocity m/s 5* 5+ 5 *Average, at SBL, U 2 Malaysian Meteorological Service +Average, UK Met Office Sunrise time hours 6 5 6* *Sunrise for a summer day Sunset time hours 18 19 20* *Sunset for a summer day

Footnotes to table 5.1 above. 4 Three variables are affected by temperature, and so could change considerably when running the model under different temperature regimes. These are: 5 The specific heat of air varies by just 0.3J/kg/°C between 20°C and 35°C so is assumed to be a constant for the temperatures used in this model. 6 The latent heat of evaporation varies by 0.034 (1.4%) between 18°C and 36°C; Gill (2006) found that when varying the latent heat of evaporation by ±10%, the maximum surface temperature only varied by just 0.4°C, therefore it has been assumed to be a constant for the temperatures used in this model. 7 The density of air varies by 0.048 (4%) between 21°C and 32°C; Gill (2006) found that when varying the density of air by ±10%, the maximum surface temperature varied by 1.13°C, therefore this also has been assumed to be a constant for the temperatures used in this model. 124 Peak W/m 2 750* 750 802.5 + *Curve fitting insolation, a 3 to a measured diurnal solar intensity in Malaysia +Curve fitting for idealised solar intensity of a summer day in Manchester Night W/m 2 -148.7* -148.7 -93 + *Estimated, radiation, a' 3 Malaysian Meteorological Service +calculated for black body at air temp on a cloudless night Hours of hours 12 14* 16 + *Assumption daylight, hoD +Average for a summer day Specific - 0.003* 0.002 + 0.002 + *Assumption humidity at +Average, UK SBL, q 2 Met Office Soil depth, 2d m 0.2* 0.2 0.2 *Assumption

Table 5.2. Variable inputs into the Energy Balance Model by previous authors. Parameter Unit Value Comment and notation Tso et al. Whitford et Gill et al. (1991) al. (2001) (2007) Reference °C 27* 17* 20.6 # *Assumptions temperature, T f for linearization of specific humidity #UK Met Office Air °C 25* 15 + 15.4 # *Average, temperature at Malaysian SBL, T 2 Meteorological Service +Assumption #calculated by Gill (2006) to constantly be 5.2°C cooler than T f Soil °C 25 15 20 + +calculated by temperature at Gill (2006) to depth 2d, T b be constantly 0.6° cooler than Tf

125 Evaporating - 0.1* varies varies *Assumption fraction at surface, E f Average mass kg/m 2 700* 700 Road *average over a of concrete, 255.5 + defined city + (M c) Building area calculated 842 + by Gill, (2006) based on residential road and typical 2 story house in study area Building kg/m 2 - varies by varies by *Varies mass/unit built site* site* according the land, m c proportion of built fraction

In this study, the temperature inputs vary according to the climate scenario examined, and is explained in further detail below. Evaporating fraction (E f) and building mass (m c) vary between housing types, and were calculated as part of Chapter Four. The evaporating fraction was calculated by adding the proportions of tree, shrub, mown grass and rough grass cover in each housing type. The built mass was calculated by multiplying the proportion of buildings and impervious surfaces by Gill’s (2006) M c figures above, for each housing type.

Generation of reference temperatures

Table 5.3 (below) shows the reference temperatures (T f) and scenarios used in this work. The data is from UKCP09, which used computer models to predict future temperatures under three different greenhouse gas emission scenarios; low, medium and high. The temperatures were calculated for the relatively rural area south west of Manchester city centre, which encompasses the airport. Gill (2006) used previous data calculated for the airport in her study, therefore similar data is used here. Using the airport and surrounds as a reference temperature means there is very little urban heat island effect affecting the temperatures. This is necessary as the model takes into account the energy exchanges that happen in built up areas; using temperatures which are relatively unaffected by the urban heat island effect therefore does not inadvertently ‘double up’ the possible increases in temperature.

126 Table 5.3. The range of temperatures used in this study to input into the Energy Balance Model for generating likely future temperatures. Emissions Modelled daily summer temperature (°C) Time period scenario 50% 98% 1961 – 1990 (baseline) - 14.9 20.6 Low 21.259 23.685 2020s Medium 21.216 23.798 High 21.141 23.570 Low 22.251 26.174 2050s Medium 22.568 26.934 High 22.983 27.724 Low 22.806 27.900 2080s Medium 23.877 30.104 High 25.069 32.522

The 50% figure referred to in Table 5.3 is the maximum daily temperature which has a 50% likelihood of occurring and a 50% likelihood of not occurring; it may be thought of as the average temperature increase. The 98% figure is the maximum daily temperature which has a 2% likelihood of happening and a 98% likelihood of not happening; it is an unlikely but possible high temperature event.

5.2.4 Surface Runoff Model – Background

Rainfall lands in cities and is absorbed by vegetation and bare soil, with any excess rainfall going into the city’s drainage system. Urbanisation has a profound effect on the hydrology of an area, and the amount of greenspace in an area can greatly change the hydrological processes of that area (Chow et al., 1988). The higher the proportion of impervious surfaces in an area the higher the percentage of rainfall that becomes runoff and goes into the drainage system.

Soil Conservation Service Rainfall Runoff Model

Whitford et al. (2001) and Gill (2006) used the Soil Conservation Service model of rainfall runoff in small watersheds (SCS, 1972; Chow et al., 1988) to calculate the effects of vegetation and impervious surfaces on the hydrology of urban areas. This model is a conceptual model of hydrologic abstraction (rainfall that does not become runoff) of storm rainfall, and will estimate direct runoff volume from storm rainfall depth, based on a curve number (CN) (Ponce and Hawkins, 1996). Proportions of surface cover are required as an input along with precipitation, antecedent moisture conditions and hydrologic soil type. For each surface type and antecedent moisture conditions, CNs have

127 previously been calculated for different soil types (SCS, 1972; Chow et al., 1988; Gill, 2006) and may be multiplied by surface cover proportions to give the CN for an urbanised area. Gill (2006) used this model for Greater Manchester, and so it will also be used in this study of smaller sections of the same area.

Before CN can be calculated, the hydrologic soil type of the study area must be determined. For the high density housing areas of the six districts of Greater Manchester forming the study area, the underlying soil type is almost exclusively Type 24 or Type 10 (HOST classification, National Soil Resources Institute (NSRI), 2004). Type 24 is classified as ‘slowly permeable, seasonally waterlogged soils over slowly permeable substrates with negligible storage capacity’, while Type 10 is classified as ‘soils seasonally waterlogged by fluctuating groundwater and with relatively rapid lateral saturated conductivity’. Both these soil types were classed as SCS type C by Gill (2006), and Table 5.4 below lists the curve number for this soil type of each surface cover used in this study.

Table 5.4. Curve number (CN) of surface covers for soil type C (adapted from Gill, 2006). Antecedent moisture Surface cover type Curve number CN conditions (AMC) AMCII (Normal) building 98 other impervious 98 tree 70 shrub 77 mown grass 74 rough grass 71 AMCI (Dry) building 95.4 other impervious 95.4 tree 49.5 shrub 58.4 mown grass 54.4 rough grass 50.7 AMCIII (Wet) building 99.1 other impervious 99.1 tree 84.3 shrub 88.5 mown grass 86.7 rough grass 84.9

These curve numbers are then weighted according to the proportions of surface covers present, using the equation below.

128 CN Housing category = Σ (CN x proportion of building), (CN x proportion of other impervious), (CN x proportion of tree), (CN x proportion of shrub), (CN x proportion of mown grass), (CN x proportion of rough grass).

The curve numbers and resulting equations have been developed through empirical study of many small watersheds (SCS, 1972, Chow et al., 1988). These curve numbers are then used in a further equation, described below, to calculate the amount of rainfall stored in the area and the amount of rainfall that becomes surface runoff.

For the storm as a whole, the amount of direct runoff (Pe) is always less than or equal to the depth of precipitation (P). Similarly, after runoff begins, the additional depth of water retained in the watershed (Fa), is less than or equal to some potential maximum retention S (Chow et al., 1988). There is some amount of rainfall Ia (initial abstraction before ponding) for which no runoff will occur, so the potential runoff is P — Ia (Chow et al., 1988). This is shown graphically in Figure 5.3 below. The hypothesis of the SCS method is that the ratios of the two actual to the two potential quantities are equal, and so storm runoff may be calculated.

Figure 5.3. A graphical representation of rainfall absorbed by soil and the surface runoff. From: Whitford et al., 2001.

The potential maximum rainfall storage (mm) of the watershed may be calculated by:

S = (2540 / CN) - 25.4 (Whitford et al., 2001)

The amount of runoff is not consistently proportional to the amount of rainfall, i.e. runoff is not a fixed percentage of rainfall, regardless of rainfall amount. The equation below 129 sets out the relationship between rainfall (P), runoff (Pe) and watershed storage capacity (S).

Pe = (P – 0.2S) 2 / (P + 0.8S) where P > 0.2S Pe is considered zero if P < 0.2S (Whitford et al., 2001)

The SCS model of runoff used here does not allow for any consideration of the duration of a rainfall event. Daily rainfall data is most readily available and so has been used in this research. Gill (2006) used the 99th percentile winter daily precipitation as its input, a rainfall event that occurs approximately once per winter, the wettest time of the year. The 99 th percentile daily winter rainfall was 18mm for 1961–1990 (Gill, 2006); this figure was used in this study.

5.3 Results

5.3.1 Increases in Tree Cover

Table 5.5 shows the existing and potential tree cover of each housing type.

Table 5.5. Existing tree cover, potential increase in tree cover and total tree cover for each housing type. Housing type Existing tree cover Potential tree cover Total tree cover (%) (%) (%) Pre 1919 semi 11.6 5.0 16.6 Pre 1919 onto road 1.6 7.6 9.2 Pre 1919 front yard 2.6 8.0 10.6 Pre 1919 frontback 3.6 6.5 10.1 1919-1959 semi 11.4 6.5 17.9 1919-1959 terrace 5.6 7.4 13.0 Post 50s semi 5.8 6.3 12.1 60s walkway 14.8 6.2 21.0 60s drive 5.4 10.5 15.9 Post 60s terrace 6.2 8.4 14.6 Courtsquare 4.4 8.0 12.4 Overall average 6.64 7.3 14.0

Tree cover could be increased in all housing types by at least 5%. The highest existing tree cover was in 1960s walkway, which could be increased by 6.2% to give by far the highest total cover of trees. Tree cover could be increased by 10.5%, the largest increase of all housing types, in 1960s drive housing. The biggest impact of increasing tree cover was in pre 1919 terraced housing, where extremely low tree cover may be increased to almost 10% or more. Figure 5.4 shows existing and potential tree cover of housing areas. The regression line shows that as existing tree cover increased, the potential to plant more trees decreased. 130

Figure 5.4. Scatterplot with regression line showing the relationship between existing and potential tree cover. R 2 = 0.26

5.3.2 Location of Potential Trees

The graph below (Figure 5.5) shows the percentages of potential trees which could be planted into each land use type across all housing types. In each housing type, except 1960s walkway, the largest number of trees may be planted into pavements and back gardens. In 1960s walkway housing, the largest number of trees could be planted into public open space. In some housing types, notably 1919-1959 semi-detached and post 1950s semi-detached housing, a large number of trees may also be planted into front gardens.

131 Communal open space Public open space Alleyway Back garden Front garden Off road parking Pavement post1960s courtsquare terrace 1960s drive1960s post1960s 1960s walkway semi post1950s terrace 1919-1959 Housing Housing type semi 1919-1959 back garden back Pre1919 front Pre1919 Pre1919 frontyard road Pre1919 semiPre1919 onto Pre1919

0%

80% 60% 40% 20% 100% use land in planted trees potential of Percentage

Figure 5.5. A comparison of the percentage of potential trees planted into each land use type in all housing categories.

132

Figure 5.6 shows the total percentages of trees which could be planted into each land use. By far the most trees could be planted into pavements, followed by back gardens. A fairly large number of trees may also be planted into front gardens.

45

40

35

30

25

20

15

10 Percentage of potential trees Percentage potential of

5

0 Pavement Off road Front garden Back garden Alleyway Public open Communal parking space open space Land use

Figure 5.6. The percentages of potential trees planted into each land use type across all housing categories.

5.3.3 Energy Exchange Model for Surface Temperature Calculations

Table 5.6 shows the existing proportions of each surface cover and building mass for each housing type. These are the inputs into the Energy Exchange Model from which maximum surface temperature is calculated.

Table 5.6. Existing proportions of surface covers and building mass for each housing type. Housing type Building Impervious Pervious Building surfaces surfaces mass (Mc) (kg/m 2) pre1919semi 0.308 0.412 0.28 364.602 pre1919onto road 0.42 0.508 0.072 483.434 pre1919frontgarden 0.384 0.534 0.082 459.765 pre1919frontandback 0.346 0.446 0.208 405.285 1919-1959semi 0.24 0.334 0.426 287.417 1919-1959terrace 0.294 0.364 0.342 340.55 post1950semi 0.238 0.314 0.448 280.623 1960swalkway 0.278 0.304 0.418 311.748 1960sdrive 0.264 0.418 0.318 329.087 post1960sterrace 0.222 0.42 0.358 294.234 post1960scourtyard 0.336 0.382 0.282 380.513

133 Table 5.7 shows the potential proportions of surface cover if tree cover were increased to the levels indicated previously.

Table 5.7. Potential proportions of surface covers and building mass for each housing type. Housing type Building Impervious Pervious Building surfaces surfaces mass (Mc) (kg/m 2) pre1919semi 0.308 0.3771 0.315 355.685 pre1919onto road 0.42 0.4361 0.144 465.064 pre1919frontgarden 0.384 0.4736 0.142 444.333 pre1919frontandback 0.346 0.4062 0.248 395.116 1919-1959semi 0.24 0.3113 0.449 281.617 1919-1959terrace 0.294 0.3226 0.383 329.972 post1950semi 0.238 0.2954 0.467 275.871 1960swalkway 0.278 0.2631 0.459 301.298 1960sdrive 0.264 0.3885 0.347 321.55 post1960sterrace 0.222 0.3693 0.409 281.28 post1960scourtyard 0.336 0.3413 0.323 370.114

Surface Temperature Projections with Current and Increased Tree Cover

The following graphs demonstrate the changes in maximum surface temperature that are likely to occur due to climate change over the next 70 years for each housing type, with regard to current and potential tree cover. Changes in temperatures are those calculated as part of the UKCP09 scenarios, and are detailed in Table 5.3 in Section 5.2.3. The average refers to expected average temperatures, and high refers to expected extreme high temperatures. These formed the reference temperature for each model run, with changes in surface cover and built mass also inputted. Current surface covers and built mass are detailed in Table 5.6, and the changes in surface cover and built mass due to increased tree cover are detailed in Table 5.7. Within the graphs, ‘current surface covers’ refers to the maximum surface temperatures that would be expected in future scenarios if no changes to surface covers or tree cover occurred, and ‘increased tree cover’ refers to the maximum surface temperatures that would be expected in future scenarios if tree cover was to be increased to the potential maximum number of trees.

134 Pre 1919 Semi-detached housing

36

34

32 Existing surface covers - average

30 Increased tree cover - average

Existing surface 28 covers - high

Increased tree cover Temperature (degrees Temperature C) - high 26

24

22 Baseline low medium high low medium high low medium high 2020s 2050s 2080s Time/Emissions Scenario

Figure 5.7. Modelled changes in maximum surface temperatures in differing climate scenarios for pre 1919 semi-housing for existing and potential levels of tree cover.

An increase from 11.6% tree cover to 16.6% tree cover gave a reduction in maximum surface temperature of at least 0.77°C, and a 1.12°C reduction in the highest temperature increase scenario.

Pre 1919 terrace housing opening directly onto the road

46

44

42

40 Existing surface covers - average 38 Increased tree 36 cover - average Existing surface 34 covers - high Increased tree 32 cover - high

30 Temperature (degreesC)

28

26

24

22 Baseline low medium high low medium high low medium high 2020s 2050s 2080s Time/Emissions Scenario

Figure 5.8. Modelled changes in maximum surface temperatures in differing climate scenarios for pre 1919 onto road housing for existing and potential levels of tree cover.

135 An increase from 1.6% tree cover to 9.2% tree cover gave a reduction in maximum surface temperature of at least 2.25°C, and a 4.53°C reduction in the highest temperature increase scenario.

Pre 1919 terrace housing with a front yard

46

44

42

40 Existing surface 38 covers - average 36 Increased tree cover - average 34

Existing surface 32 covers - high

30 Temperature(degrees C) Increased tree cover - high 28

26

24

22 Baseline low medium high low medium high low medium high 2020s 2050s 2080s Time/Emissions Scenario

Figure 5.9. Modelled changes in maximum surface temperatures in differing climate scenarios for pre 1919 terraced housing with a front yard for existing and potential levels of tree cover.

An increase from 2.6% tree cover to 10.6% tree cover gave a reduction in maximum surface temperatures of at least 1.84°C, and a 3.74°C reduction in the highest temperature increase scenario.

136 Pre 1919 terrace with a front and back garden

38

36

34 Existing surface covers - average

32 Increased tree cover - average Existing surface covers - high 30 Increased tree cover - high

28 Temperature (degrees C)

26

24

22 Baseline low medium high low medium high low medium high 2050s 2020s 2080s Time/Emissions Scenario

Figure 5.10. Modelled changes in maximum surface temperatures in differing climate scenarios for pre 1919 terraced housing with a front and back garden for existing and potential levels of tree cover.

An increase from 3.6% tree cover to 10.1% tree cover gave a reduction in maximum surface temperatures of at least 0.97°C, and a 1.63°C reduction in the highest temperature increase scenario.

137 1919 – 1959 Semi-detached housing

32

30

Existing surface covers - average 28 Increased tree cover - average Existing surface covers - high 26 Increased tree cover - high Temperature (degrees C)

24

22 Baseline low medium high low medium high low medium high 2020s 2050s 2080s Time/Emissions Scenario

Figure 5.11. Modelled changes in maximum surface temperatures in differing climate scenarios for 1919- 1959 semi-detached housing for existing and potential levels of tree cover.

An increase from 11.4% tree cover to 18% tree cover gave a reduction in maximum surface temperatures of between 0.38°C and 0.5°C. Tree and vegetation cover is already high in this housing type, therefore more trees made little difference to the existing cooling effects.

138 1919 – 1959 terraced housing

34

32 Existing surface covers - average 30 Increased tree cover - average Existing 28 surface covers - high Increased tree cover - high 26 Temperature(degrees C)

24

22 Baseline low medium high low medium high low medium high 2050s 2020s Time/Emissions Scenario 2080s

Figure 5.12. Modelled changes in maximum surface temperatures in differing climate scenarios for 1919- 1959 terraced housing for existing and potential levels of tree cover.

An increase from 5.6% tree cover to 13% tree cover gave a reduction in maximum surface temperatures of at least 0.82°C, and a reduction of 1.08°C in the highest temperature increase scenario. As with the previous housing type, vegetation cover is already relatively high, therefore temperatures do not decrease dramatically with the addition of more trees.

139 Post 1950s Semi-detached housing

32

30 Existing surface covers - average

28 Increased tree cover - average

Existing surface covers - high 26 Increased tree

Temperature (degrees C) cover - high

24

22 Baseline low medium high low medium high low medium high 2020s 2050s 2080s Time/Emissions Scenario

Figure 5.13. Modelled changes in maximum surface temperatures in differing climate scenarios for post 1950s semi-detached housing for existing and potential levels of tree cover.

An increase from 5.8% tree cover to 12.1% tree cover gave a reduction in maximum surface temperatures of between 0.32°C and 0.39°C. As with the previous two housing types, vegetation cover was already relatively high so temperatures did not change greatly with the addition of more trees.

140 1960s terrace housing with walkways

32

30 Existing surface covers - average

28 Increased tree cover - average

Existing surface covers 26 - high

Temperature Temperature C) (degrees Increased tree cover - high

24

22 Baseline low medium high low medium high low medium high 2020s 2050s 2080s Time/Emissions Scenario

Figure 5.14. Modelled changes in maximum surface temperatures in differing climate scenarios for 1960s terraced housing with a walkway for existing and potential levels of tree cover.

An increase from 14.8% tree cover to 21% tree cover gave a reduction in maximum surface temperatures of at least 0.69°C, and a 0.89°C reduction in the highest temperature increase scenario. As with the previous housing type, vegetation cover was already comparatively high so temperatures barely decrease with addition of more trees.

141 1960s terraced housing with a driveway

34

32 Existing surface covers - average

30 Increased tree cover - average

Existing surface 28 covers - high

Increased tree cover - high 26 Temperature (degrees C)

24

22 Baseline low medium high low medium high low medium high 2020s 2050s 2080s Time/Emissions Scenario

Figure 5.15. Modelled changes in maximum surface temperatures in differing climate scenarios for 1960s terraced housing with a driveway for existing and potential levels of tree cover.

An increase from 5.4% tree cover to 15.9% tree cover gave a reduction in maximum surface temperatures of between 0.61°C and 0.84°C. Existing vegetation cover was fairly high in this housing type, thus temperatures did not decrease dramatically with addition of more trees. This is despite this housing type containing the highest potential increase in tree cover.

142 Post 1960s terrace housing

34

32 Existing surface covers - average

30 Increased tree cover - average

Existing surface 28 covers - high

Increased tree cover - high 26 Temperature (degrees C)

24

22 Baseline low medium high low medium high low medium high 2020s 2050s 2080s Time/Emissions Scenario

Figure 5.16. Modelled changes in maximum surface temperatures in differing climate scenarios for post 1960s terraced housing for existing and potential levels of tree cover.

An increase from 6.2% tree cover to 14.6% tree cover gave a reduction in maximum surface temperatures of at least 0.96°C, and a reduction of 1.28°C in the highest temperature increase scenario. As with the previous housing types, existing vegetation cover was already quite high so temperatures did not decrease dramatically with addition of more trees.

143 Post 1960s court/square housing

36

34

32 Existing surface covers - average

30 Increased tree cover - average

Existing surface 28 covers - high

Temperature (degrees C) (degrees Temperature Increased tree cover - high 26

24

22 Baseline low medium high low medium high low medium high 2020s 2050s 2080s Time/Emissions Scenario

Figure 5.17. Modelled changes in maximum surface temperatures in differing climate scenarios for post 1960s court/square housing for existing and potential levels of tree cover.

An increase from 4.4% tree cover to 12.3% tree cover gave a reduction in maximum surface temperatures of at least 0.89°C, and a 1.27°C reduction in the highest temperature increase scenario. Similarly to later housing types, vegetation cover was already high so surface temperatures do not decrease dramatically with addition of more trees.

Influence of Increasing General Vegetation Cover

Figure 5.18 (below) shows the effects of incrementally increasing vegetation cover in areas of high building mass (pre-1919 onto road terraced housing) and low building mass (post 1950s semi-detached housing).

144 36

34

32 High Built 30 Mass

28 Low Built Mass

26 Temperature (degrees C)

24

22

20 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 Percentage of vegetated surface cover

Percentage Vegetation Cover High Built Mass – Max. Low Built Mass – Max. Surface Temperature Surface Temperature 1 33.4 35.23 10 30.08 31.51 20 27.14 28.23 30 24.83 25.61 40 22.89 23.52 50 21.25 21.76

Figure 5.18. Reductions in maximum surface temperature in area of high building mass and low building mass with increasing vegetation cover.

The graph and table show that increasing vegetation cover decreased surface temperatures more when existing vegetation cover was low. Areas of low built mass had higher surface temperatures because the low amount of impervious surfaces and buildings warmed to air temperature quickly, and extra sunshine increased the temperature of these above the air temperature. Conversely, the large amount of impervious surfaces and buildings in areas of high built mass warmed to air temperature slowly, with less time for extra sunshine to warm them above air temperature.

145 5.3.4 Rainfall Runoff Calculations

A number of stages have to be undertaken in order to calculate the surface runoff of the study area. Firstly, the table below gives the curve numbers for each housing type, which depend on the proportions of differing surface covers present.

Table 5.8. Curve numbers (CN) for all housing types for existing surface covers. Curve number Housing type AMCII (Normal) AMCI (Dry) AMCIII (Wet) pre 1919 semi 90.93 83.51 95.42 pre 1919 onto road 96.29 92.47 98.22 pre 1919 front yard 96.04 92.06 98.09 pre 1919 front and back 93.04 86.93 96.54 garden 1919-1959 semi 87.55 77.68 93.68 1919-1959 terrace 89.83 81.46 94.88 Post 1950s semi 87.24 77.05 93.54 1960s terrace walkway 87.43 77.68 93.59 1960s terrace driveway 90.28 82.27 95.10 Post 1960s terrace 89.29 80.59 94.59 Post 1960 court/square 91.2 83.81 95.58

The table below shows the potential maximum rainwater storage for each housing type.

Table 5.9. Rainfall storage for an 18mm rainfall event for each housing type, in mm, for existing surface covers. Potential maximum rainfall storage (S) (mm) Housing type AMCII (Normal) AMCI (Dry) AMCIII (Wet) pre 1919 semi 2.53 5.02 1.22 pre 1919 onto road 0.98 2.07 0.46 pre 1919 front yard 1.05 2.19 0.49 pre 1919 front and back 1.9 3.82 0.91 garden 1919-1959 semi 3.61 7.3 1.71 1919-1959 terrace 2.88 5.78 1.37 Post 1950s semi 3.71 7.56 1.75 1960s terrace walkway 3.65 7.32 1.74 1960s terrace driveway 2.74 5.48 1.31 Post 1960s terrace 3.05 6.12 1.45 Post 1960 court/square 2.45 4.9 1.17

Connected to storage capacity, as shown in Table 5.9 above, is rainfall runoff. The amount of rain that becomes runoff in each housing type is shown in Table 5.10 below.

146 Table 5.10. Rainfall runoff for an 18mm rainfall event for each housing type, in mm, for existing surface covers. Rainfall runoff (mm) from 18mm daily rainfall Housing type AMCII (Normal) AMCI (Dry) AMCIII (Wet) pre 1919 semi 15.28 13.12 16.61 pre 1919 onto road 16.88 15.74 17.46 pre 1919 front yard 16.8 15.61 17.42 pre 1919 front and back 15.9 14.11 16.95 garden 1919-1959 semi 14.29 11.48 16.1 1919-1959 terrace 14.96 12.54 16.45 Post 1950s semi 14.2 11.3 16.05 1960s terrace walkway 14.26 11.46 16.07 1960s terrace driveway 15.09 12.77 16.52 Post 1960s terrace 14.8 12.29 16.37 Post 1960 courtsquare 15.36 13.21 16.66

Rainfall runoff was smallest in all housing types when prevailing moisture conditions were dry and largest when prevailing moisture conditions were wet. Runoff is largest in all conditions for pre1919 terraced housing, which contained the highest proportions of buildings and impervious surfaces (calculated in objective 1). Similarly, rainfall runoff was lowest in 1919-1959 semi-detached housing and post 1950s semi-detached housing, which both contained the highest amounts of vegetated surfaces. However, it should be noted that in all housing types the majority of rainfall became runoff and was not absorbed by vegetation.

Effects of increasing vegetation cover

The amount of vegetation present is important in the calculations of rainfall runoff in this model. If tree cover is increased, rainfall runoff will decrease. The table below shows how rainfall runoff changed if tree cover is increased by the potential maximum amount described earlier.

147 Table 5.11. Rainfall runoff for an 18mm rainfall event for each housing type, in mm, for surface covers with increased tree cover. Rainfall runoff (mm) from 18mm daily rainfall (% reduction) Housing type AMCII (Normal) AMCI (Dry) AMCIII (Wet) pre 1919 semi 14.98 (2.0) 12.65 (3.6) 16.45 (1.0) pre 1919 onto road 16.27 (3.6) 14.76 (6.2) 17.13 (1.9) pre 1919 front yard 16.28 (3.1) 14.78 (5.4) 17.15 (1.6) pre 1919 front and back 15.54 (2.3) 13.54 (4.0) 16.75 (1.2) garden 1919-1959 semi 14.06 (1.6) 11.13 (3.0) 15.97 (0.8) 1919-1959 terrace 14.57 (2.6) 11.95 (4.7) 16.24 (1.3) Post 1950s semi 14.01 (1.4) 11.01 (2.6) 15.95 (0.7) 1960s terrace walkway 13.85 (2.8) 10.85 (5.3) 15.85 (1.4) 1960s terrace driveway 14.79 (1.9) 12.33 (3.4) 16.35 (1.0) Post 1960s terrace 14.35 (3.0) 11.59 (5.7) 16.12 (1.5) Post 1960 courtsquare 14.97 (2.5) 12.62 (4.5) 16.45 (1.3)

The smallest reduction in rainfall runoff was seen in the post 1950s semi-detached housing type in AMCIII (Wet) conditions. The largest change in rainfall runoff was seen in pre 1919 onto road housing type, in AMCI (Dry) conditions. However, both of these changes were small, and rainfall runoff was still a large majority of the rainfall event.

148 5.4 Discussion

5.4.1 Increases in Tree Cover

Tree cover may be increased in all housing types by at least 5%. The smallest increase in tree cover was in pre 1919 semi-detached housing, while the biggest increase was seen in 1960s terraced housing with a driveway. The small increase in tree cover was not surprising in pre 1919 semi-detached housing; existing tree cover was relatively high, so little space would exist to plant more trees. Conversely, the highest amount of potential tree cover may be expected to be found in the housing type with the lowest existing tree cover. This was not the case; the largest increase in tree cover was found in the 1960s terraced housing with a driveway housing type. Data from Chapter Four showed that this housing type had a large amount of mown grass into which trees may easily be planted; therefore the large potential increase no longer seems surprising. The most surprising results were seen in the pre 1919 terraced housing categories, where tree cover could be potentially increased to over 9%. Although there is little vegetated space in these areas, there is a large amount of impervious surfaces into which trees could be planted.

5.4.2 Location of Potential Trees

In all housing types except 1960s walkway housing, the largest number of trees may be planted into pavements and into back gardens. In some housing types, trees may also be planted into front gardens. Trees in pavements would be planted by the council or a tree planting project rather than individual residents, which suggests that any large scale tree planting schemes would potentially be preferable in housing types where most trees may be planted in pavements if funding was available. This could allow the largest increase in tree cover as residents do not legally need to be consulted about whether a tree is planted outside their house, although resident support and involvement is greatly preferred to aid establishment and future care of the trees. Where the largest number of trees may be planted in private space of front and back gardens, residents would need to be encouraged to plant a tree, and may need education about the benefits of trees. If a tree was offered to residents free of charge it is likely that tree planting rates would be higher.

Further projects to increase tree cover on a large scale in high density housing should consider these issues in order to most effectively target their resources.

149 5.4.3 Maximum surface temperatures

Any increase in tree cover decreases maximum surface temperatures, although the amount of reduction reduces as existing tree cover increases. The largest reductions in surface temperatures were seen in housing types where existing tree cover was under 4% and increased to 9% or more. These housing types showed a reduction in surface temperatures of between 0.97°C and 4.53°C. Other housing types did not show such dramatic decreases in surface temperatures. Gill et al. (2007) demonstrated that increasing vegetation cover by 10% could keep future surface temperatures around the level of current surface temperatures; this study investigated the feasibility of increasing vegetation cover to this level using just trees. In only one housing type (1960s driveway) was there potential to increase tree cover by over 10%, and in other housing types tree cover could be increased by just 8.35% or less. Therefore, if future surface temperature increases due to climate change are to be ameliorated using just the cooling effects of vegetation, further interventions which complement increasing tree cover are needed, such as green roofs or permeable parking surfaces. However, the model only addressed maximum surface temperatures, not air or globe temperatures which make a much greater contribution to human comfort. Tree shade and cooling can decrease temperatures and increase human comfort in hot weather (Hwang et al., 2010), and can prevent buildings being heated by sunshine leading to a cooler indoor climate (Gómez-Muñoz et al., 2010). Therefore, trees would make a considerable difference to temperatures and human comfort that is not reflected in the model.

5.4.4 Surface Runoff

Increasing tree cover can help reduce runoff, but only by a small percentage. Rainfall runoff is smallest in housing types that contained a large amount of vegetation, and highest in housing types that contained a large amount of impervious surfaces and buildings. Unsurprisingly, the reduction in runoff is highest when the prevailing soil conditions are dry. To decrease runoff further, solutions other than tree planting should be examined, such as sustainable urban drainage systems (SUDS). However, as temperatures increase due to climate change, the transpiration rates of vegetation will increase, meaning that water could be removed from the soil at a faster rate than anticipated by the model. If transpiration rates are higher, interception rates (where water is stored on plant leaves) could be higher as water enters leaf stomata and does not become run off.

150 5.5 Summary and Conclusions

This chapter has presented the methodology (Section 5.2) and results (Section 5.3) of determining a potential increase in tree cover, and the effects this would have on maximum surface temperatures and rainfall runoff under a range of climate change scenarios. The main findings are: • tree cover could be increased by at least 5% in all housing types; • tree cover may be increased by the largest amount in 1960s driveway housing; • housing types with relatively high existing tree cover had less potential tree cover; • a majority of potential trees could be planted in pavements; • a large amount of trees may also be planted in front and back gardens; • only one housing type could accommodate a 10% increase in tree cover, which Gill (2006) and Gill et al. (2007) suggest will keep surface temperatures around 1990 levels; • increased tree cover reduced surface temperatures in all housing types, but this decrease was most dramatic in housing types with less than 4% existing tree cover, with decreases between 0.97°C and 4.53°C; • rainfall runoff under extreme conditions could be reduced by between 0.7% and 6.2% if the potential number of trees were planted.

It must be remembered that the number of trees planted is an idealised absolute maximum, and any realistic tree planting scheme would only be able to plant a proportion of these. This would most likely be due to monetary restrictions, resident opposition and issues with underground services. As the majority of new trees may be planted into pavements, this suggests that projects addressing increasing tree cover in urban areas should focus on increasing tree planting specifically in pavements. However, in certain housing types where a large proportion of potential trees could be planted into gardens this instead could be the focus of these projects. Only one housing type can accommodate a 10% increase in vegetation solely using trees; therefore, ways will need to be found to increase vegetation other than tree planting to reduce maximum surface temperatures in these housing types. Surface runoff can only be reduced by a small percentage in all housing types, suggesting that methods other than increasing vegetation should be used to reduce or channel runoff. However, increased transpiration and interception rates of vegetation due to higher temperatures are not addressed in this model, and could play a small role in reducing runoff in these areas

151 Chapter 6 – Residents’ Attitudes Towards Trees in Differing Types of High Density Residential Streets

This chapter states how Objective Three ‘ To examine the interdependence between tree cover and residents’ attitudes to it in high density residential areas ’ was achieved. This chapter describes the development and carrying out of a questionnaire to assess the attitudes towards trees of residents of different street types within high density housing in Manchester. It may be that those who like trees live in areas of high tree cover, or lobby authorities to plant trees in their area. Conversely, those who do not like trees may live in areas with no trees, and would not support or take part in greening programmes. In either case, residents can have an influence on the distribution of trees in urban areas. A brief overview of methods was given in Section 3.4.3, and methods are given in more detail in Section 6.2. Results of the questionnaire are given in Section 6.3 for each question and each street type, with the results of additional street-specific questions given separately. Crosstabulations are also given, which allow correlations to be explored between attitudes and socioeconomic variables. The data found as part of this research are compared with a similar study in the USA, to determine if there are great differences between urban populations of each country. Implications of this research are briefly outlined at the end of the chapter, and explored in more detail in Chapters 8 and 9.

6.1 Introduction

Residents’ attitudes towards trees are likely to be one of the most important factors deciding the presence or absence of trees in a given area. Previous studies suggest that people are generally positive towards trees regardless of their socioeconomic background, want to see more trees planted and would pay for their upkeep to ensure they were not removed from cities (see Chapter 2). However, these studies are mainly in the United States, so cannot easily be generalised to the UK. Two studies have been carried out in the UK, and gave contrasting results to the overwhelmingly positive attitudes seen in the USA. A study in a small town in south west Scotland (Hitchmough and Bonugli, 1997) found residents of tree-less streets did not feel the planting of trees in their street would greatly improve it and were more concerned with reductions in traffic and litter. A study in two towns in south west England (Schroeder et al., 2006) found residents were more concerned with negative effects of trees and less concerned about the availability of shade than their American counterparts. This difference in attitudes needs to be studied in

152 greater detail to see if these attitudes are replicated in a large urban area in the UK. Separate studies have investigated the attitudes of residents in different types of street, but no study has directly compared attitudes in different streets. The presence or absence of trees around their homes may have a large effect on residents’ views, therefore it is important that this is studied. Recent participation in a street tree planting scheme may also affect residents’ viewpoints; newly planted trees may enthuse residents and make them very positive about trees, but after the initial excitement the interest and appreciation of the new trees may have disappeared. Therefore, a comparative study of four different street types to compare attitudes towards trees is an interesting and necessary addition to the existing research of residents’ attitudes.

153 6.2 Methods

6.2.1 Identifying the survey objectives

The aim of the survey was to explore residents’ attitudes to trees in varying residential environments. Questions were asked about trees in urban areas in general, then questions about their street and questions about trees in their street (if there are any). This was in order to study if there are any differences between views of trees in general and views of trees in their street.

The survey data was used as part of this thesis, and will also help the Red Rose Forest with analysis of their projects and to help them alter their information given to residents.

6.2.2 Selecting the sampling frame

Residents are familiar with their own street and are likely to have strongly held opinions about it, which will be helpful for this survey. The existing streetscape where people live is likely to have a large influence on how they perceive trees; in a street of many attractive, well maintained trees it is probable that residents would have a positive view about trees, while in a street where there are no trees residents may be less well informed of the benefits of trees while taking a disproportionate view of the potential problems trees may cause. Attitudes may also be influenced by information campaigns linked to street tree planting programmes or the involvement of residents in a recently completed tree planting programme. In light of this, four different types of street were identified as places to survey: • streets with no trees, either on the pavement or in front gardens, but with enough room for trees to be planted (2.15metres wide pavement) • streets with old trees (established street trees 40 or more years old), • streets which were awaiting planting of a Green Streets project, • streets which had Green Streets project trees planted 5 years ago, within high density housing areas inside the defined study area. Individual houses are the sampling unit, within the larger sampling frame of selected streets. Figure 6.1 (below) shows each street type.

154 Figure 6.1. Examples of street types surveyed. Clockwise from top left: Post Green Streets, Pre Green Streets, No Trees, Trees.

Five streets awaiting Green Streets project trees were identified, with a total of 177 homes. By coincidence, the streets were in areas of differing socioeconomic status, from low status to relatively high status. Index of Multiple Deprivation (IMD) scores for 2004 and 2007 for these streets is given in Table 6.1. For an explanation of IMD scores see footnote 2 in Section 3.3. A score of 85 is the most deprived area in England, while a score of 1 or less is a very affluent area.

Table 6.1. Index of Multiple Deprivation (IMD) scores for Pre Green Streets areas within the Manchester city council area. Street IMD 2004 IMD 2007 1 (Whitehead Road) 21.29 17.29 2 (Holtby Street) 52.19 45.9 3 (Artillery Court) 77.58 72.98 4 (Greenheys Lane) 50.37 42.62 5 (Maine Road) 41.96 32.84

The remaining three types of streets were selected using the same criteria: location in high density housing within the study area, 4 or more streets totalling 170 or more houses and across a range of socioeconomic classes (see Table 6.2 below).

155 Table 6.2. Index of Multiple Deprivation (IMD) scores for streets with trees, streets without trees and streets that had a Green Streets project 5 years ago. Streets with existing trees Street IMD 2004 IMD 2007 St Anne’s Road 18 16.07 Birch Lane 51.87 48.24 Hamilton Road 55.33 50.3 Dean Road 41.06 40.51 Streets with no trees Street IMD 2004 IMD 2007 Lytham Avenue 36.89 34.17 Norbreck Avenue 36.89 34.17 Fairhaven Avenue 31.48 23.46 Berkeley Avenue 47.69 49.44 Meade Grove 55.33 50.3 Claremont Road 66.72 46.22 Rawcliffe Street 66.72 46.22 Streets that had a Green Streets project 5 years ago Street IMD 2004 IMD 2007 Griffin Grove 31.4 27.11 Delamere Road 49 46.38 Greenway Avenue 55.4 51.32 Hannah Street 67.6 53.30

It was intended to select a wider range of socioeconomic areas containing streets with and without trees, but this was not possible. Reasonably deprived areas, with an IMD score over 60, which contained existing street trees proved impossible to find within the study area. as did deprived areas with trees. A one-way ANOVA test showed that for both 2004 and 2007 IMD scores there is no difference in mean IMD score for each type of street; therefore, there is not an overall difference in deprivation levels between street types.

6.2.3 Determining the sampling method

There are many different ways to survey a population. Previous studies exploring residents’ attitudes to trees have been questionnaire based, either by post, telephone or door to door surveying. It was decided to also use a questionnaire format to survey residents, for a number of reasons. Firstly, it is not too resource intensive; secondly, it allows direct comparison with previous studies; thirdly, it allows collection of a large amount of data without too much researcher time. Focus groups were considered, but due to resource constraints and potential difficulties of attracting a diverse range of people questionnaires were deemed to be a better choice.

156 6.2.4 Developing the questionnaire

The questionnaire was developed using existing questionnaires from the literature and through working with the Red Rose Forest team, who have a wealth of experience in surveying residents in postal questionnaire form. Questions were adapted from Lohr et al. (2004) and Hitchmough and Bonugli (1997), with original questions developed in consultation with Pete Stringer at the Red Rose Forest (Community Forests North West (RRF)). The data found through this questionnaire formed both a part of this thesis and made a valuable contribution to a North West European INTERREG 4b Project the Red Rose Forest was undertaking on establishing the importance of green infrastructure to communities.

The consultation focussed on the most common complaints and praise encountered by the Green Streets team in their years of operation and incorporated these into the questions. The questions were closed-ended multiple choice, but with an opportunity for respondents to add other answers and comments where appropriate. The questionnaire was split into two sections, the first containing questions about street trees in general and the second containing questions about their street and any trees planted there. A separate section asked socioeconomic background questions; age, income, job status, tenure, car ownership, ethnic origin and education level. Questions about their street and any trees within it were modified to fit each street; for example, questions about the Green Streets project were only asked in streets where this was carried out, and residents in streets with no trees were asked why they thought there were no trees in their street. A full copy of the questionnaire and cover letter is in Appendix 1.

6.2.5 Surveying residents

To increase the response rate of postal questionnaires, a reminder is needed. It was decided that researchers would visit each street on a predetermined day in the early evening to remind residents to fill in their surveys and collect any that had not yet been returned. The questionnaire was also put online using SelectSurveyASP Advanced 8.1.1 (ClassApss.com, 2004) and an easy URL created for respondents to enter in order to answer the survey. It was hoped that this would ensure a reasonable response rate. The questionnaire was posted to all residential dwellings in the selected streets (or sections of streets) in University of Manchester branded envelopes. Addresses were determined using the Royal Mail’s online Postcode Finder tool (www.royalmail.com/postcodefinder).

157 The envelopes contained the 5 page questionnaire on 3 pages of A4 paper, a freepost envelope for returning the questionnaire and a cover letter explaining the reason for the questionnaire, how the data would be used, details of when their street would be visited and the URL of the online survey. The letter also stated that if residents did not want to be disturbed on the stated evening, that they should put the letter in their door or window so researchers would not call. The questionnaires were posted second class and the streets were visited 10 to 14 days after posting. Two researchers then visited residents on the stated day, showing residents the cover letter and questionnaire, asking if they had received it and if they had filled it in. If residents had filled it in and returned it, they were thanked for taking part in the research. If residents had received it but not returned it, they were encouraged to fill it in and return. If residents had not received it, or had but since lost it, a replacement was offered with a new freepost envelope. If residents did not answer, a reminder slip was posted through their door with the web address for the survey and contact details for more information if needed.

6.2.6 Analysis of Data

Statistical tests were carried out on the data using SPSS (version 15, SPSS Ins., 2006) and Microsoft Excel 2003. The tests used were one way ANOVA, to look for differences in means, χ2 test for associations to look for associations between answers and street type, the Kruskal Wallis test to look for differences between street types and ranked opinion data and the Dunn’s post hoc test to determine which street types were different from each other.

158 6.3 Results

6.3.1 Response Rates

Table 6.3. Response rates of individual streets and types of streets Street name Street IMD 2007 Response Response Number of Type Score Rate of Rate of Responses Street Street Type Hamilton Road Trees 50.3 15 23.7 51 Birch Lane 48.24 16 St Anne’s Road 16.07 48.9 Dean Road 40.51 19 Berkeley Avenue No Trees 49.44 20 26.3 44 Meade Grove 50.3 15.4 Chorlton 28.82 39.2 Claremont Road 46.22 12.5 Rawcliffe Street 46.22 33 Whitehead Road Pre Green 17.29 58.0 25.3 43 Holtby Street Streets 45.9 25.0 Artillery Court 72.98 21.3 Greenheys Lane 42.62 19.4 Maine Road 32.84 20.0 Greenway Avenue Post 51.32 24.2 31.5 56 Delamere Road Green 46.38 33.3 Griffin Grove Streets 27.11 36.4 Hannah Street 53.30 29.6 Totals 26.7 - 194

The overall response rate was 26.7%, a total of 194 responses from 726 questionnaires. This is considered high for Red Rose Forest surveys and other resident correspondence. Overall, the highest responses rates were seen in St Anne’s Road, Chorlton streets and Whitehead Road. These three streets are located in the same suburb of Manchester. The lowest response rates were seen in Claremont Road, Hamilton Road, Meade Grove and Birch Lane.

Figure 6.2 (below) shows the correlation between IMD 2007 scores and response rates. There was a clear correlation between these, as shown by the R 2 value of 0.52. Less deprived areas had higher response rates than areas of higher deprivation.

159

Figure 6.2. Scatterplot with linear regression line showing the relationship between IMD score and response rates.

However, although responses rates and deprivation levels varied within street types, between street types there was no significant difference in response rates or deprivation levels, calculated by a one way ANOVA in SPSS. Therefore, street types can be compared confidently knowing that there are no underlying differences between street types which may affect the survey responses.

160 6.3.2 Trees and Everyday Life Questions

Table 6.4. Responses to the question ‘Do you consider trees to be an important part of your everyday life?’

Type Pre Green Post Green Trees No Trees Streets Streets Total Count 37 40 30 43 150 Yes % within Type 86.0% 95.2% 75.0% 82.7% 84.7% Count 3 1 2 1 7 No % within Type 7.0% 2.4% 5.0% 1.9% 4.0% Never Count 3 1 8 8 20 thought % within Type 7.0% 2.4% 20.0% 15.4% 11.3% about it Total 43 42 40 52 177

In all street types, at least three quarters of respondents stated that trees are an important part of their everyday life. Very few respondents answered ‘no’. The highest percentages of ‘never thought about it’ are from streets with Green Streets projects.

Table 6.5 shows a crosstabulation of the answers to the first and last question, which asked ‘Do you consider trees to be an important part of your everyday life?’ at the beginning and end of the survey.

Table 6.5. A crosstabulation of answers to the first and last questions. *Total number different due to respondents not answering both questions. After completing this questionnaire, do you consider trees to be important to your everyday life? Yes No Total Do you consider Yes 143 6 149 trees to be an 81.3% 3.4% important part of No 4 3 7 your everyday 2.3% 1.7% life? Never thought 8 12 20 about it 4.5% 6.8% Total 155 21 176*

The vast majority of respondents who considered trees important to their everyday life at the beginning of the questionnaire still felt this at the end of the questionnaire. After answering the questions, a small number had changed their opinion from ‘yes’ to ‘no’, with a similar number changing ‘no’ to ‘yes’ or answering ‘no’ to both questions. Of

161 those that had not considered trees and their importance to everyday life, 40% concluded that yes, trees are important to their everyday life, while 60% decided that they are not.

6.3.3 Positive Statements About Trees

Table 6.6 shows positive statements about trees ranked in order of agreement level, where strongly disagree is ranked ‘1’ and strongly agree is ranked ‘4’. The highest ranked statement is ‘trees are important as they provide resources such as wood and fruit to humans’. The second most highly rated statements are ‘trees are important to my quality of life’ and ‘trees can play an important role in stopping climate change’. ‘Trees should be planted in cities because they reduce noise’ and ‘trees should be planted in residential areas as they reduce the risk of flooding’ are the least agreed with statements. The overall score for positive statements is 1.51, just over halfway between ‘agree’ and ‘agree strongly’.

162 Table 6.6. Positive statements about trees, ranked by mean agreement level (1 strongly disagree to 4 – strongly agree). +Does not include ‘don’t know’ answers. Differences between street types significant at the *0.05 level, **0.01 level. Kruskal Mean+ Median S.E. Wallis Test Trees are important as they provide 4 0.038 4.037 3.73 resources such as wood and fruit to humans Trees are important to my quality of life 3.65 4 0.043 14.567**

Trees can play an important part in stopping 4 0.044 3.375 3.65 climate change Trees in shopping areas makes it a nicer 3.63 4 0.047 4.026 place to spend time and shop Trees help me tell the changing of the 4 0.043 2.952 3.58 seasons Trees in cities help people feel better and 3.57 4 0.049 9.681* less stressed Trees are important in town centres because 3.46 4 0.052 11.111** they shade and cool their surroundings Trees should be planted in cities as they 3.45 4 0.055 2.936 provide a link with nature and the countryside Trees should be planted in town centres to 3.43 4 0.064 8.453* reduce smog and dust from cars and buses Trees should be planted in cities because 3.35 4 0.063 10.69** they are associated with soothing sounds such as rustling leaves and bird song Trees should be planted in cities to attract 3.33 4 0.063 4.992 wildlife Trees should be planted in cities because 3.26 3 0.071 14.79** they reduce noise Trees should be planted in residential areas 3.25 3 0.077 12.084** as they reduce the risk of flooding Mean Agreement Score for Positive Effects 3.49

Using the Kruskal Wallis test, the median rank for seven different statements varied between street types. A Dunn’s post hoc test, calculated by hand, showed which street types the differences were between. For the statement ‘Trees are important to my quality of life’ the Dunn’s post hoc test showed that there was a significant difference between respondents in ‘No Trees’ streets and those in ‘Pre Green Streets’. Respondents who do not have trees in their street agreed significantly more strongly than residents in ‘Pre Green Streets’. For the statements ‘Trees should be planted in cities because they reduce noise’ and ‘Trees should be planted in cities because they are associated with soothing sounds such as rustling leaves and bird song’ the Dunn’s test showed that respondents in ‘Post Green streets’ agreed significantly more strongly with the statements than respondents in ‘Pre Green Streets’. For the statements ‘Trees are important in town

163 centres because they shade and cool their surroundings’, ‘Trees in cities help people feel better and less stressed’ and ‘Trees should be planted in residential areas as they reduce the risk of flooding’ the Dunn’s test did not show which street types were different from each other, although the raw data suggests that respondents in ‘No Trees’ streets agreed significantly more strongly with the statements than ‘Pre Green Streets’ respondents. For the statement ‘Trees should be planted in town centres to reduce smog and dust from cars and buses’ the Dunn’s test did not show which street types were different from each other, although the raw data suggests that respondents in ‘Post Green Streets’ agreed significantly more strongly with the statement than respondents in ‘Pre Green Streets’.

6.3.4 Negative Statements About Trees

Table 6.7 shows negative statements about trees ranked in order of disagreement level, where strongly disagree is ranked ‘1’ and strongly agree is ranked ‘4’. The most disagreed with statement was ‘trees should not be planted in cities because they cost the council too much’. The next most disagreed with statement was ‘trees should not be used in cities because they make it difficult to detect criminal behaviour’. The most highly rated problems with trees in cities (the least disagreed with) were ‘trees should not be planted because their roots crack pavements’ and ‘trees should not be planted in residential streets as their roots could damage house foundations and boundary walls’

The overall score for all negative statements was 3.43, just under halfway between ‘disagree strongly’ and ‘disagree’.

164 Table 6.7. Negative statements about trees, ranked by mean agreement level (1 strongly disagree to 4 – strongly agree). +Does not include ‘don’t know’ answers. Differences between street types significant at the *0.05 level **0.001 level. Kruskal Mean + Median S.E. Wallis Test Trees should not be planted in cities because 1.41 1 0.054 1.119 they cost the council too much Trees should not be used in cities because 1.45 1 0.052 4.749 they make it difficult to detect criminal behaviour Trees should be removed from cities 0.057 4.567 because they can fall across power lines, 1.49 1 cars, houses or fall on people Trees should not be used in town centres 0.062 2.177 because they block shop signs and get in 1.5 1 people's way Trees should not be planted along streets as 1.5 1 0.058 7.987* they reduce space for car parking Trees should not be planted in cities as they 1.51 1 0.063 1.815 increase dog mess and litter Trees should not be planted in cities because 1.52 1 0.063 3.459 they are ugly when they are not maintained Trees should not be planted in cities as they 1.57 1 0.061 1.286 can block out sunshine and street lights Trees grow too high to be planted in 1.62 1 0.069 2.001 residential streets Trees should not be planted along streets 1.65 1 0.064 20.207** because they drip sap or sticky substances on parked cars Trees are a problem in cities because they 1.67 1 0.069 1.526 cause allergies Trees should not be planted because their 2 0.067 5.637 1.74 roots crack pavements Trees should not be planted in residential 1.76 2 0.070 1.656 streets as their roots could damage house foundations and boundary walls Mean Agreement Score for Negative Effects 1.57

Using the Kruskal Wallis test, the median rank for two statements varied between street type. For the statement ‘Trees should not be planted along streets as they reduce space for car parking’ the Dunn’s test did not show which street types were most different from each other. The raw data suggested that respondents in ‘No Trees’ streets disagreed with this statement more strongly than those in ‘Trees’ streets, though as this was not seen in a Dunn’s test this was not a significant difference. For the statement ‘Trees should not be planted along streets because they drip sap or sticky substances on parked cars’ the Dunn’s test showed that respondents in ‘Trees’ streets disagreed with this statement less strongly than all other respondents.

165 6.3.5 Length of Stay in Current Home

The mean length of residency in their current home was similar in each type of street, from around 9 years in ‘Pre Green Streets’ to around 16 years in ‘No Trees’ streets. A one way ANOVA test did not show any significant differences in the mean length of stay between street types.

6.3.6 Respondents’ Views About Their Street

Table 6.8. Percentage of respondents who saw these activities taking place on their street. Respondents could tick more than one activity. Differences between street types significant at the *0.05 level **0.01 level. Activity Percentage of Total χ2 test for Respondents associations Car parking 96.4 N/A Children playing 59.3 3.508 Cars driving between two main 55.7 5.344 roads Meeting neighbours/socialising 49.7 7.128 Total number of respondents 167 -

‘Car parking’ was seen by respondents as the most common activity on their street. A χ2 test showed there were no associations between street type and activity.

Table 6.9. Percentage of respondents who liked certain features of their street. Respondents could tick more than one feature. Differences between street types significant at the *0.05 level **0.001 level.

Liked Feature Percentage of Total χ2 test for associations Respondents Good location 70.8 14.367* Friendly neighbours 61.9 6.174 There’s a sense of street 28.6 5.34 community The roads and pavements are 25.6 3.629 clean and smooth The street looks well cared for 25 10.645 Total number of respondents 168 -

The most common like about a respondent’s street was ‘good location’, followed by ‘friendly neighbours’. A χ2 test for association did not show any association between ‘likes’ and street type, except for ‘good location’. Fewer respondents than expected in ‘No Trees’ and ‘Post Green Streets’ stated that their street was in a good location, while more than expected in ‘Trees’ and ‘Pre Green Streets’ said their street was in a good location.

166 Table 6.10. Percentage of respondents who saw these problems on their street. Respondents could tick more than one problem. Differences between street types significant at the *0.05 level **0.001 level. Problem Percentage of total χ2 test for associations respondents Rubbish/litter 56.6 11.731** Too much traffic 42.2 3.389 Not enough car parking space 37.3 15.903** Vandalism/noisy gangs of 26.5 3.721 children Feels unsafe at night 23.5 1.408 Total number of respondents 166 -

Rubbish/litter was the overall most common problem on streets, but specific problems vary in each street type. A χ2 test shows that there is an association between street type and ‘rubbish/litter’; more respondents than expected in ‘Post Green streets’ cited ‘rubbish/litter’ as a problem. A χ2 test shows that there is an association between street type and ‘not enough parking space’; more respondents than expected in ‘Trees’ cited ‘not enough parking space’ as a problem, while fewer respondents than expected in ‘Pre Green Streets’ listed it as a problem.

Table 6.11. Percentage of respondents who would like these improvements to their street. Respondents could tick more than one improvement. Differences between street types significant at the *0.05 level **0.02 level. Potential improvement Percentage of total χ2 test for associations respondents More/better trees and flowers 66.1 10.509** More community spirit 45.5 1.668 Less traffic 43.0 4.902 Place for children to play 38.8 0.496 More car parking space 30.9 9.552* Better street lighting 26.7 1.173 Total number of respondents 165 -

More/better trees and flowers was by far the most popular way to improve residents’ streets, followed by ‘More community spirit’. A χ2 test showed that there was an association between street type and ‘more/better trees and flowers’; more respondents than expected in ‘No Trees’ cited ‘more/better trees and flowers’ as a desired improvement. A χ2 test showed that there was an association between street type and ‘more car parking’; more respondents than expected in ‘Trees’ cited ‘more car parking space’ as a desired improvement.

167 6.3.7 Trees and House Prices and Future Homes

Table 6.12. Responses to the question ‘Do you think presence/planting of trees would affect house prices in your street?’ *Does not include ‘Don’t Know’ answers. Type Total

Trees No Pre Post

Trees Green Green

Streets Streets Count 19 25 11 17 72 Yes % within 38.8% 59.5% 27.5% 35.4% 40.2% Type Count 27 13 29 29 98 No % within 55.1% 31.0% 72.5% 60.4% 54.7% Type Count 3 4 0 2 9 Don’t % within 6.1% 9.5% .0% 4.2% 5.0% know Type Total Count 49 42 40 48 179 % within 100.0 100.0% 100.0% 100.0% 100.0% Type % Pearson χ2 test for 12.733 (significant at the 0.05 level) associations *

A majority of respondents (59.5%) in ‘No Trees’ felt that having trees planted would affect house prices in their street, the highest positive response. The lowest positive response came from ‘Pre Green Streets’. Overall, a majority of respondents did not think that trees will affect house prices, though there was a small minority in ‘No Trees’ streets. The χ2 result shows that there is an association between street type and whether respondents think house prices will increase. Significantly more respondents in ‘No Trees’ trees thought that house prices will increase if trees were planted, while significantly fewer respondents in ‘Pre Green Streets’ roads felt that house prices would increase due to trees being planted.

Table 6.13. Responses to the question ‘If you think presence/planting of trees would affect house prices in your street, would they be worth…?’ Type Post Pre Green Green Trees No Trees Streets Streets Total Count 14 23 11 14 62 More % within 73.7% 92.0% 100.0% 82.4% 86.1% Type Count 5 2 0 3 10 Less % within 26.3% 8.0% .0% 17.6% 13.9% Type Total 19 25 11 17 72

168 The vast majority of those who thought presence of trees affects house prices thought that prices would increase. The small number of respondents who thought that trees would or do lower their house price means a χ2 test cannot be carried out on this question.

Table 6.14. Responses to the question ‘If you were to move house, would you try to move to a street with trees?’

Type Pre Post No Green Green Trees Trees Streets Streets Total Count 20 24 17 29 90 Yes, definitely % within 39.2% 54.5% 41.5% 51.8% 46.9% Type Count 20 11 16 16 63 Yes, probably % within 39.2% 25.0% 39.0% 28.6% 32.8% Type Count 7 7 7 8 29 Would not % within 13.7% 15.9% 17.1% 14.3% 15.1% matter to me Type Count 3 0 0 2 5 Probably not % within 5.9% .0% .0% 3.6% 2.6% Type Count 1 1 1 1 4 No % within 2.0% 2.3% 2.4% 1.8% 2.1% Type Count 0 1 0 0 1 Don’t know % within .0% 2.3% .0% .0% .5% Type Total 51 44 41 56 192

79.7% of respondents stated that if they were to move house, they would try to move to a street with trees. Just 4.7% of respondents said that they would not like to move to a street with trees. The figures are around the same for each type of street, which suggests a desire to live in a street with trees is similar in all types of street. The ‘yes, definitely’ figure is highest in streets with no trees.

6.3.8 Street Specific Questions

A small number of questions were asked only to residents of certain streets to explore their attitudes and thoughts about their current residence. Street specific questions were needed in order to determine residents’ feelings about their current street environment. It also allowed investigation of residents’ opinions about specific issues such as possible reasons for a lack of trees in a street, or views about the existing trees. Questions about

169 the recent Green Streets tree planting schemes also gave an opportunity for an evaluation of the project and its impacts on the streetscape.

‘Trees’ Only Questions

Table 6.15. Responses to the question ‘Do you like the trees in your street?’ Frequency Percentage Yes 45 90 No 4 8.0 Yes and No 1 2.0 Total 50 100

Almost all residents (90% of respondents) like the trees in their street. Just 8% do not, while one respondent has mixed feelings about them.

Table 6.16. Responses to the question ‘What effects do you think the trees in your street have?’ Respondents could tick more than one effect. Frequency Percent

Makes the street more attractive 45 88.2 Makes the street feel friendlier 32 62.7 Provide space for wildlife 31 60.8 Clean the air of pollution 27 52. Drip sticky substances onto cars 26 51 Street looks more cared for than nearby streets without trees 24 47.1 Trees cool the street 20 39.2 Crack the pavements with their roots 17 33.3 Create too much litter from leaf and fruit fall 6 11.8 Leaves and berries make the pavement slippery 6 11.8 Trees block sunshine coming into my home 6 11.8 Prevent cars parking 3 5.9 Other 2 3.9 Total number of respondents 51 -

The most popular effects of the established trees in these streets are that they ‘make the street look more attractive’ and ‘make the street feel friendlier’. The most noted annoyance of trees is the dripping of sticky substances onto cars, by 51% of respondents. ‘Trees cracking pavements with their roots’ is the second most noted annoyance. It is important to note that the positive effects of trees are much more highly rated than the annoyances associated with trees.

170 ‘No Trees’ Only Questions

Table 6.17. Responses to the question ‘Why do you think your street doesn’t have trees?’. Respondents could tick more than one reason. Frequency Percent

There's not enough space for trees 17 38.6 The council can’t afford trees here 14 31.8 Other 11 25 Don’t know 6 13.6 Trees would stop cars parking on the street 4 9.1 Trees grow too high to be planted here 2 4.5 No one likes trees here 1 2.3 Trees would get damaged if they were planted here 1 2.3 Total 44 -

The most common answer to this question is ‘there is not enough space to plant trees here’, followed by ‘the council can’t afford trees here’. ‘Other’ responses included ‘the council is not interested in improving this area’, ‘trees are not a council priority’ and ‘this street was missed out when other nearby streets got trees’. There are a number of respondents who do not know or could not guess why there were not trees on their street. Vandalism and no one liking trees in their street are not seen as reasons why trees are not in their street.

Table 6.18. Responses to the question ‘Would you like trees to be planted in your street?’ Frequency Percentage Yes 37 84.1 No 7 15.4 Total 44 100

A very high percentage of respondents would like trees to be planted in their street, despite the issues with trees cited above. Interestingly, although a large number of respondents do not think there is enough space for trees in their street, they would still like trees planted.

171 ‘Pre Green Streets’ and ‘Post Green Streets’ Questions

Table 6.19. Responses to the question ‘What effect do you think the trees on your street have/will have?’ Pre Green Streets Post Green Streets Frequency Percent Frequency Percent Street looks more cared for 38 88.4 38 67.9 Street feels friendlier 28 65.1 24 42.9 More wildlife 25 58.1 18 32.1 Street feels less polluted 20 46.5 12 21.4 Neighbours are talking more 6 14 7 12.5 now More litter 3 7 7 12.5 Less space to park cars 7 16.3 3 5.36 Leaves and berries have made 2 4.7 3 5.36 pavements slippery Trees block sunlight coming 0 0 1 1.79 into my home Other 4 9.3 7 12.5 Total number of respondents 43 - 56 -

Almost all (98.1%) of ‘Post Green Streets’ respondents liked the trees in their street, and 90% thought that the trees have made a positive difference to their street. This compares to 97.7% of respondents in ‘Pre Green Streets’ who thought that the trees will make a difference to their street.

Respondents in both ‘Pre’ and ‘Post’ Green Streets projects expected or saw similar effects of trees on their streets, although a higher percentage of respondents expected to see positive differences (Pre Green Streets) than actually did see positive differences. The most anticipated or seen effects of street tree planting was that the street looks more cared for, the street feels friendlier and there is more wildlife. All potential negative effects of street trees were expected or seen by fewer respondents than positive aspects. The loss of car parking caused by street tree planting was expected by a higher percentage of respondents than actually experienced it.

The Green Streets project was popular with respondents, with 87.8% of ‘Pre Green Streets’ respondents and 95.7% of ‘Post Green Streets’ respondents stating they would encourage friends and family to take part in a Green Streets project, In ‘Pre Green Streets’ areas just under half of respondents thought their views about trees would change as a result of the Green Streets project, while just over half did not think their views would change. 56.5% of ‘Post Green Streets’ respondents stated that their views have changed since being part of the Green Streets project, with 82.1% of them stating

172 that they would like to see more trees planted elsewhere, and 42.9% stating that they are now more aware of trees around them.

In ‘Post Green Streets’ 34.5% of respondents stated that they consider there to be maintenance issues with the trees; comments linked to this question showed these issues centred around problems of litter accumulation in tree guards.

6.3.9 Socioeconomic data

Table 6.20. The age range of respondents, with comparison to overall population of Manchester. *Approximate values due to differing categories used. Frequency Percent Manchester 8 percentage* 18 - 21 10 5.4 8 22 - 30 28 15.1 26 31 - 40 51 27.4 15.5 41 - 50 34 18.3 15.5 51 - 60 28 15.1 15.5 Over 60 35 18.8 19.5 Total 186 100.0 100.0

The age range of respondents broadly matched the age structure for the overall Manchester city council area in 2001. The mean and median age of respondents in this study falls within the 31-40 age group, which is the same as the general population of the Manchester city council area.

Table 6.21. The job status of respondents, with comparison to overall population of Manchester. Frequency Percent Manchester percentage I do not work 56 30.3 44.1 I do not work due to illness 20 10.8 9.5 I work part time 35 18.9 9.9 I work full time 74 40.0 36.5 Total 185 100.0 100.0

A majority of respondents worked full time, and there was a large proportion who did not work. The respondents to this survey had broadly similar characteristics to the general population of Manchester, although fewer people did not work and more people worked part time.

8 Data for Manchester Local Authority, from 2001 Census (Office for National Statistics, 2004). 173 Table 6.22. Income levels of respondents. Frequency Percent

Under £10,000 55 34.6 £10,000 - £15,000 29 18.2 £15,000 - £20,000 15 9.4 £20,000 - £25,000 18 11.3 £25,000 - £30,000 14 8.8 Over £30,000 28 17.6 Total 159 100.0

Some respondents purposely left this question blank. Over half the respondents earnt under £15,000, which is half of the average national wage of £29,331 (GMB, 2006). A large number of respondents earn over £30,000, who mainly live in the middle class areas surveyed. A comparison to Manchester is not available, as the census does not collect data on income.

Table 6.23. The housing tenure type of respondents, with comparison to overall population of Manchester. Frequency Percent Manchester percentage Own my own home 118 63.8 44.68 Rent from private landlord 32 17.3 16.42 Rent from housing association 24 13.0 36.58 Other 11 5.9 2.32 Total 185 100.0 100.0

A majority of respondents owned their own homes, a higher value than Manchester overall. There was a lower percentage of respondents who rented their homes from the council/housing association than in Manchester overall.

Table 6.24. Car ownership levels, with comparison to overall population of Manchester. Frequency Percent Manchester percentage Owns a car 110 59.1 52.21 Does not own a car 76 40.9 47.79 Total 186 100.0

Three fifths of respondents owned a car, while two fifths did not. This is fairly comparable to Manchester overall.

174 Table 6.25. The ethnic origin of respondents, in comparison to the overall population of Manchester. Frequency Percent Manchester percentage White 142 76.4 80.96 Mixed Race 12 6.4 3.23 Asian 25 13.4 9.13 Black 5 2.7 4.52 Chinese 2 1.1 1.3 Other 0 0 0.86 Total 186 100.0 100

The vast majority of respondents described themselves as white. The next biggest ethnic group is Asian. This broadly reflects the ethnic diversity in Manchester, although for the areas which were surveyed a higher proportion of Asian respondents would have been more representative of the residents.

Table 6.26. Qualifications of respondents, compared to the overall population of Manchester. *Categories combined due to more complex methods of recording qualifications in the Census. Frequency Percent Manchester percentage* No formal qualifications 22 13.3 34.0 GCSEs/O Levels/other exams taken at 16 9.7 26.6 age 16 NVQs 11 6.7 A Levels/other exams taken at age 18 18 10.9 13.1 HND 8 4.8 21.4 Undergraduate degree (e.g. BSc, BA) 40 24.2 Postgraduate degree (e.g. MSc, MA, 39 23.6 PhD) Other professional qualifications (e.g. 11 6.7 4.9 for plumber, electrician, builder, hairdresser) Total 165 100.0

Nearly half of respondents have completed an undergraduate degree or a postgraduate degree. This is not surprising, as the study area is close to three universities, and students commonly stay in the city after graduating, living in the areas they lived as students. This result is much higher than for the whole of Manchester however, where 21.4% of residents have an undergraduate degree or higher.

175 6.3.10 Crosstabulations

Crosstabulations explore linkages between characteristics. The answers to the survey questions could be related to the socioeconomic background of the respondent. The following crosstabulations explore this.

Table 6.27. A list of statements with statistically significant different mean ranks between different age groups. Differences between groups *significant at the 0.05 level, **significant at the 0.01 level. Age Statement 18 - 22 - 31 - 41 - 51 - Over Mean Kruskal 21 30 40 50 60 60 rank Wallis test Trees can play an important part in stopping 1.6 1.32 1.21 1.5 1.19 1.52 1.35 11.617* climate change Trees are a problem in cities because they cause 3.7 3.3 3.56 3.25 3.48 2.8 3.33 11.131* allergies Trees should be removed from cities because they can fall across power lines, 3.38 3.56 3.8 3.31 3.44 3.21 3.5 14.619** cars, houses or fall on people Trees should not be planted in cities because they are 3.56 3.6 3.67 3.29 3.54 3.08 3.47 11.128* ugly when they are not maintained Trees should not be planted in cities because they cost 3.86 3.65 3.77 3.44 3.62 3.25 3.59 11.105* the council too much Mean number of 8.2 22 45.2 28.2 23.8 26.2 - - respondents

Table 6.27 above gives the statements which displayed significant differences in mean rank between age groups. A post hoc Dunn’s test did not show which age groups were different from each other.

176 Table 6.28. A list of statements with statistically significant different mean ranks between those of differing job status. Differences between groups *significant at the 0.05 level, **significant at the 0.01 level. Job status statement I do not I do not I work I work Mean Kruskal work work due part full time rank Wallis test to illness time Trees can play an important part in 1.47 1.36 1.52 1.19 1.35 11.115** stopping climate change Trees should not be used in town centres because 3.32 3.24 3.75 3.6 3.51 8.84* they block shop signs and get in people's way Trees should be removed from cities because they can fall across 3.37 3.0 3.71 3.64 3.5 12.036** power lines, cars, houses or fall on people Trees should not be planted in cities 3.3 3.0 3.58 3.66 3.47 11.019** as they increase dog mess and litter Mean number of 48.75 16.75 31.25 67.75 - - respondents

Table 6.28 above gives the statements which displayed significant differences in mean rank between job status groups. A post hoc Dunn’s test did not show which groups were different from each other.

177 Table 6.29. A list of statements with statistically significant different mean ranks by differing income levels. Differences between groups *significant at the 0.05 level, **significant at the 0.01 level Income level (in thousands) Mean Kruskal Under £10 - £15 - £20 - £25 - Over Rank Wallis £10 £15 £20 £25 £30 £30 Test Trees should be planted in cities as they provide a link 1.62 1.68 1.43 1.72 1.0 1.46 1.57 11.119* with nature and the countryside Trees should not be used in town centres because 3.36 3.33 3.79 3.44 3.62 3.89 3.54 15.00** they block shop signs and get in people's way Trees should not be planted because 3.15 3.36 3.08 3.31 3.9 3.46 3.31 12.545* their roots crack pavements Trees should not be planted in cities as they can block 3.28 3.57 3.5 3.25 3.75 3.75 3.48 11.281* out sunshine and street lights Mean number of 49.5 26 13.75 17 12.5 25.8 - - respondents

Table 6.29 above gives the statements which displayed significant differences in mean rank between income levels. A post hoc Dunn’s test did not show which groups were different from each other.

178 Table 6.30. A list of statements with statistically significant different mean ranks by differing tenure type. Differences between groups *significant at the 0.05 level, **significant at the 0.01 level Tenure Mean Kruskal Statement Own my Rent Rent from Other Rank Wallis own privately housing Test home association Trees are important as they provide resources such as 1.21 1.28 1.74 1.18 1.29 20.172** wood and fruit to humans Trees help me tell the changing of the 1.38 1.37 1.73 1.45 1.43 9.153* seasons Trees in cities help people feel better 1.39 1.32 1.76 1.55 1.44 12.092** and less stressed Trees should be planted in town centres to reduce 1.52 1.48 1.95 1.6 1.57 8.523* smog and dust from cars and buses Trees in shopping areas makes it a 1.32 1.28 1.82 1.0 1.15 18.886** nicer place to spend time and shop Trees should not be planted because their 3.28 3.53 2.95 2.9 3.26 9.635* roots crack pavements Mean number of 109.5 29.5 21.6 11 - - respondents

Table 6.30 above gives the statements which displayed significant differences in mean rank between tenure groups. A post hoc Dunn’s test showed differences in agreement levels for the statements Trees are important as they provide resources such as wood and fruit to humans’, ‘Trees in cities help people feel better and less stressed’ and ‘Trees in shopping areas makes it a nicer place to spend time and shop’. For all these statements, those who own their own home agreed significantly more than those who rent their home from a housing association; those who privately rent their home also agreed significantly more than those who rent from a housing association for the statement ‘Trees in shopping areas makes it a nicer place to spend time and shop’. The Dunn’s test did not show differences between groups for the other statements. However, care must be taken when interpreting these results; many more respondents own their home than rent, so there were problems of small sample size.

179 Table 6.31. A list of statements with statistically significant different mean ranks by car ownership. Differences between groups *significant at the 0.05 level, **significant at the 0.01 level Own a car? Mean Kruskal Statement Yes No Rank Wallis Test Trees should not be planted because their 3.36 3.1 3.25 5.702** roots crack pavements Trees should be removed from cities because they can fall 3.61 3.35 3.5 4.95* across power lines, cars, houses or fall on people Trees should not be planted in cities as they can block out 3.53 3.25 3.43 4.936* sunshine and street lights Mean number of 96 64.3 - - respondents

Table 6.31 above gives the statements which displayed significant differences in mean rank between income levels. A post hoc Dunn’s test could not be carried out due to the small number of groups.

Table 6.32. A list of statements with statistically significant different mean ranks by different ethnic groups. Differences between groups *significant at the 0.05 level, **significant at the 0.01 level Ethnic Origin Mean Kruskal Statement White Mixed Asian Afro- Chinese Rank Wallis Caribbean test Trees should not be used in town centres because they 3.61 3.36 3.04 3.6 2.0 3.5 14.8** block shop signs and get in people's way Trees should not be planted because their 3.26 3.7 3 3.75 2.0 3.25 10.123* roots crack pavements Mean number 127.5 10.5 22.5 4.5 2 - - of respondents

Table 6.32 above gives the statements which displayed significant differences in mean rank between ethnic groups. A post hoc Dunn’s test did not show which groups were

180 different from each other. The small sample size for minority groups suggest that care must be taken when interpreting the results.

Table 6.33. A list of statements with statistically significant different mean ranks by qualification level. Differences between groups *significant at the 0.05 level, **significant at the 0.01 level Qualifications Mean Kruskal Rank Wallis test None 16At age 18At age NVQs HND Degree Post grad degree Other Trees should be 21.333 removed from ** cities because they can fall across 3.0 3.4 3.5 3.3 3.8 3.78 3.77 3.3 3.55 power lines, cars, houses or fall on people Trees should not 16.677* be planted in cities 2.7 3.5 3.6 3.0 3.4 3.76 3.61 3.4 3.51 as they increase dog mess and litter Trees should not 23.884 be planted in cities ** as they can block 3.3 3.1 3.4 2.9 3.3 3.73 3.62 3.4 3.46 out sunshine and street lights Trees should not 22.510 be planted in cities ** because they cost 3.2 3.1 3.7 3.3 3.4 3.82 3.83 3.5 3.63 the council too much Mean number of 13 13. 15. 9.5 7.5 34.3 36.8 8.7 - - respondents 5 8 5

Table 6.33 above gives the statements which displayed significant differences in mean rank between education levels. The Dunn’s test for the statement ‘Trees should not be planted in cities as they can block out sunshine and street lights’ showed that those educated to undergraduate level disagreed more strongly with the statement than those educated to GCSE level. The Dunn’s test did not show group differences for any other statement.

181 6.4 Discussion

The responses to the survey were very positive, with little difference between street types. It is important to compare opinions between street types, as opinions may be different in different types of street depending on the level of contact with and experiences of street trees. It may be suggested for example that residents in streets without trees do not like or value trees, while those in streets with large existing trees are indifferent towards them. However, this research has shown that residents are very positive and appreciative about urban trees, regardless of their street type.

6.4.1 Response Rates

While the response rates between street types did not vary significantly, the response rates within street types did vary. The streets with lower index of multiple deprivation scores generally gave higher response rates than those with higher scores, although local knowledge suggests that lower response rates were more linked to the levels of transient residents and the community language spoken. Where there were high levels of transient residents, response rates decreased, possibly as residents felt that they had no views about their street as they had not lived there long or were moving soon. Where the most common language spoken was not English, responses rates were lower. This may be due to difficulties with comprehension of the survey or apprehension about filling in a survey at all, though there is no evidence to support this.

6.4.2 The Importance of Trees to Everyday Life

In all street types, at least three quarters of respondents stated that trees are an important part of their everyday life. Surprisingly, the highest ‘yes’ percentage was from streets that do not have trees. It is possible that the lack of trees in their own street made residents more aware of trees in other areas and felt that not having trees outside their home was of concern for them. Very few respondents answered ‘no’, which while a good comparison statistic, it must be remembered that those who do not like trees, or are not interested in them, are unlikely to have completed a questionnaire about them. It is interesting to note that the highest percentages of ‘never thought about it’ are from streets with Green Streets projects. A high figure for ‘Pre Green Streets’ is understandable, as the residents are just getting used to very recently planted trees; conversely, in ‘post Green Streets’ the trees had been present for 5 years, so the lower figure is unexpected. 182 However, this may be an indication that the residents here have become accustomed to the trees to the extent they have almost become invisible and not noticed on a daily basis. It is possible attitudes may change when the trees reach a significant size, and begin to present perceived problems.

Of those that had not considered trees and their importance to everyday life, 40% concluded that yes, trees are important to their everyday life, while 60% decided that they are not. This suggests that even with education about trees and their positive effects there will not be 100% support for tree planting.

6.4.3 Positive Statements about Trees

Overall, respondents were very positive about trees. Some differences were seen between streets, but these were small differences in the mean rank of statements between ‘strongly agree’ and ‘agree’, showing that only strength of agreement with these statements varies. However, it must be remembered that people with indifferent or negative attitudes about trees are very unlikely to fill in a survey about trees, and so a self selecting sample of those who like trees is inevitable in a study of this type.

Some possible reasons behind the small differences in agreement level between streets on certain statements are discussed below.

For the statement ‘Trees are important to my quality of life’ a significant difference was seen between respondents in ‘No Trees’ streets and those in ‘Pre Green Streets’, with the former agreeing significantly more than the latter. This is an interesting and surprising result; it is possible that once respondents knew they were going to have street trees the importance of street trees decreased in their life, and for those without trees it is possible that they value, or want, trees more as they do not currently have them.

For the statement ‘Trees should be planted in cities because they reduce noise’ there was a significant difference between respondents in ‘Pre Green Streets’ streets and those in ‘Post Green Streets’, with those in the former agreeing significantly less strongly that trees can help reduce noise than the latter. This suggests that noise reduction is not an expected effect of street tree planting, particularly the small species planted, but that once trees are planted and grow residents become aware of their increasing noise reducing

183 effects, either actual or perceived. The comparatively low agreement level also suggests that respondents did not think that trees could reduce urban noise.

For the statement ‘Trees should be planted in cities because they are associated with soothing sounds such as rustling leaves and bird song’, respondents of ‘Pre Green Streets’ agreed significantly less than respondents in ‘Post Green Streets’. It is difficult to suggest reasons for this; it may be because ‘Pre Green Streets’ respondents are unfamiliar with the sounds associated with trees so do not agree that this is a reason to plant trees, but respondents in ‘No Trees’ roads would also not be familiar with these sounds yet have rated this statement fairly highly. Another reason may be that respondents of ‘Pre Green Streets’ are more concerned about bird mess than other respondents and so rate it as more of a problem than birdsong is a benefit.

The remaining statements did not show significant differences between street types or the differences between street types were unclear.

The statement ‘Trees are important as they provide resources such as wood and fruit to humans’ was the most agreed with statement, and suggests respondents have a great appreciation of the role trees play in human life. However, those who rent their home from a housing association agreed significantly less strongly than other respondents about this statement; the reasons for this are unclear, and may be due to sampling effects due to a small sampling size.

The high level of agreement for the statement ‘Trees can play an important part in stopping climate change’ suggests that education and the media are effectively increasing awareness of ways to deal with climate change.

The high level of agreement with ‘Trees in shopping areas makes it a nicer place to spend time and shop’ was surprising, and it suggests that shopping areas wishing to increase visitors should consider improving and increasing their greenery. However, those who rented their home from a housing association agreed significantly less strongly with this statement that those who owned or privately rented theirs homes. The reasons for this are unclear; it may be due to housing association tenants not having much disposable income to shop, or due to small sample effects.

184 The high level of agreement with ‘Trees help me tell the changing of the seasons’ was also surprising, as it was hypothesised that urban residents may be fairly unaware of seasons. In urban areas the changes of seasons can be masked and go unnoticed, but respondents use urban trees to help them follow the seasons.

The statements ‘Trees are important in town centres because they shade and cool their surroundings’, ‘Trees should be planted in town centres to reduce smog and dust from cars and buses’ and ‘Trees should be planted in residential areas as they reduce the risk of flooding’ were less strongly agreed with than other statements, which suggests that respondents think these are good but not highly important reasons to plant trees. This difference may be due to respondents being unaware of the extent to which trees may have this effect. Education about how much trees can help reduce smog, temperatures and flooding could help increase the strength of agreement.

The lower level of agreement with the statement ‘Trees should be planted in cities to attract wildlife’ suggests that respondents are unsure how much wildlife a tree may attract, or may be concerned about problems that could be caused by any wildlife. Again, further education could increase the strength of this agreement.

6.4.4 Negative Statements About Trees

Very few respondents agreed with any of the reasons why trees should not be planted in cities, therefore respondents do not agree that potential negative issues around trees are a reason they should not be planted.

The levels of disagreement were very similar across all street types. The levels of disagreement for just one statement ‘Trees should not be planted along streets because they drip sap or sticky substances on parked cars’ was shown by the Dunn’s test to vary significantly across streets; respondents in ‘Trees’ streets disagreed significantly less with this statement that respondents in all other streets. While respondents still disagreed that this factor should stop trees being planted, on average they disagreed with this statement while other respondents strongly disagreed. This result is not surprising, as the trees growing in ‘Trees’ streets are mainly sycamore and other sap dripping species, while trees planted in other streets are not. While ‘doorknocking’ to increase survey responses, a number of residents mentioned issues of tree sap dripping and fruit drop, and the pavements and some cars were covered in sycamore planes. As respondents in ‘Pre’

185 and ‘Post Green Streets’ did not have issues with sap dripping due to careful selection of trees planted, it may be suggested that the planting of these species should continue. No other differences between responses by street type were shown by a Dunn’s post hoc test.

The Dunn’s test for the statement ‘Trees should not be planted in cities as they can block out sunshine and street lights’ showed that those educated to undergraduate level disagreed more strongly with the statement than those educated to GCSE level. The reasons for this are unclear. A very speculative reason may be that those who have or are studying for an undergraduate degree have different working and sleeping patterns to those who have GCSEs, so they are more sensitive to loss of sunshine or street lighting. The Dunn’s test did not show differences between any other socioeconomic group for any other statement.

The two statements ‘Trees should not be planted because their roots crack pavements’ and ‘Trees should not be planted in residential streets as their roots could damage house foundations and boundary walls’ were the least strongly disagreed with statements. This shows that tree root effects caused the most concern for respondents, although the statement was still overwhelmingly disagreed with. This suggests that future tree planting schemes should address the issues of tree root damage, with evidence that tree will not do the amount of damage perceived by residents. The use of flexible pavements which allow tree root growth under them without cracking should be more widespread in order to prevent residents desiring tree removal for this reason.

The most strongly disagreed with statements were ‘Trees should not be planted in cities because they cost the council too much’ and ‘Trees should not be used in cities because they make it difficult to detect criminal behaviour’. The strong level of disagreement with the first statement is positive as respondents think that the benefits of trees outweigh the costs, and that cost should not be a factor in tree planting and maintenance decisions. This is an important finding for local councils, who may cut funding for trees, seeing it as unimportant and unappreciated expenditure. The high disagreement level for the statement ‘Trees should not be used in cities because they make it difficult to detect criminal behaviour’ is interesting; during research a number of anecdotal reports of woody areas used for behaviour perceived as antisocial were heard and it was expected that this statement would have a lower disagreement score as respondents were concerned about this issue. However, respondents did not think this was a reason to not have trees in urban areas. This is encouraging particularly for tree planting in more

186 deprived areas where the fear of crime is higher and there is often a lot of opportunity for tree planting.

6.4.5 Length of Stay in Current Home

There was no significant difference between length of stay in respondents’ current home in differing street types. It was hypothesised that areas with trees may have a more stable community, but this was not the case, with the highest average stay seen in ‘No Trees’ streets.

6.4.6 Respondents’ Views About Their Street

There were no differences in differing activities seen on streets by respondents, so all activities may be said to happen equally on each street. It was hypothesised that the presence of trees may lead to more socialising and children playing on streets, but this was not the case.

Good location was the most liked feature of respondents’ streets, although the χ2 test indicated that fewer respondents than expected in ‘No Trees’ and ‘Post Green Streets’ and more respondents than expected in ‘Trees’ and ‘Pre Green Streets’ felt their street was in a good location. Evidently the location of their home was very important to respondents, and the presence or absence of trees did not affect this. Friendly neighbours was the second highest ranked ‘like’ about their street, similar across all street types, showing that living in an area where people know each other is still important and valued by respondents. The remaining ‘likes’ about their street, ‘There’s a sense of street community’, ‘The roads and pavements are clean and smooth’ and ‘The street looks well cared for’ were indicated by only around a quarter of respondents, suggesting that these qualities are not generally present on their roads.

Rubbish/litter was the overall most common problem on streets. The χ2 test indicated that more respondents than expected in ‘Post Green Streets’ cited ‘rubbish/litter’ as a problem, and comments from respondents stated that there were problems with rubbish being caught in tree guards and not removed by the street cleaners. More respondents than expected in ‘Trees’ cited ‘not enough parking space’ as a problem, while fewer respondents than expected in ‘Pre Green Streets’ listed it as a problem. This is not surprising, as when ‘doorknocking’ the large number of cars in ‘Trees’ streets, plus the

187 lack of driveways, meant that car parking space along pavements was quite difficult to find. Conversely, there appeared to be fewer cars in ‘No Trees’ streets with some areas having off road parking, therefore issues of car parking were not seen.

More/better trees and flowers was by far the most popular way to improve residents’ streets, followed by ‘More community spirit’ and ‘Less traffic’. More respondents than expected in ‘No Trees’ cited ‘more/better trees and flowers’ as a desired improvement. This is not surprising, as there was no street greenery in these areas and respondents were very positive about trees, so they would appreciate greenery being added to their street. More respondents than expected in ‘Trees’ cited ‘more car parking space’ as a desired improvement. which is not surprising when compared to the ‘Problems’ question above, where many respondents stated that lack of car parking was a problem.

6.4.7 Trees and House Prices and Future Homes

A majority of respondents thought that the presence or planting of trees would not affect their house prices. This was a surprising statistic, as research tends to suggest that the presence of trees or a green area increases house prices (e.g. Tyrvainen and Miettinen, 2000; CABE Space, 2005; Kaufman and Cloutier, 2006). However, those that did think trees affected house prices overwhelming felt that house prices increased with the presence of trees, as other research has found. Significantly more respondents in ‘No Trees’ streets felt that house prices would increase than those in ‘Pre Green Streets’. It is difficult to suggest reasons for this. It is perhaps possible that residents typically do think that trees increase house prices as people are likely to pay more to live in a pleasant looking street. However, as it was not mentioned in the materials sent out as part of the Green Streets project, which sets out many other benefits of trees, residents may think that an increase in house prices does not happen or is much smaller than they has thought. Thus, the exclusion of an effect of trees in a street means that residents may not think this effect happens, regardless of any other information they may have. This is an important finding for the development of Red Rose Forest’s Green Streets consultation materials.

The vast majority of respondents stated that they would probably or definitely try to move to a street with trees in future, which suggests a very high appreciation of trees. This result is slightly in conflict with the result of a majority of respondents thinking that trees do not affect house prices; if most people want to move to a street with trees, than it is very likely that house prices would increase due to competition between buyers. This

188 result also suggests that in order to increase housing demand in an area, street trees and other greenery may be planted.

6.4.8 Street Specific Questions

For ‘Trees’ streets and ‘Post Green Streets’ areas at least 90% of respondents stated that they liked the trees. This is very positive, and shows great support for urban trees. Interestingly, 80.4% of respondents in ‘Post Green Streets’ thought that the trees had made a difference to their street, compared to 97.7% of respondents in ‘Pre Green Streets’ who anticipated a difference to their street from the trees. Again, these are very positive results and show great support and appreciation of the Green Streets scheme. The top three seen/expected effects of trees in streets were ‘Street looks more attractive/more cared for’, ‘Street feels friendlier’ and ‘Gives space for wildlife’. These are highly rated positive effects, again showing how appreciative and supportive residents are about urban trees. The aesthetic reasons were more highly rated than other positive effects, which were also more highly rated than negative effects, which were only seen by a few respondents. These overwhelmingly positive results should be highlighted when encouraging tree planting schemes.

Respondents in ‘No Trees’ streets mainly thought that the reasons for not having trees in their street were ‘There's not enough space for trees’ and ‘The council can’t afford trees here’. However neither statement was stated by a majority of respondents. Encouragingly, the perception that if trees were planted they would be vandalised was not seen as a concern by many respondents. Interestingly, 84.1% of respondents stated that they would like trees planted, regardless of whether or not they thought there was room to plant trees. This suggests that people may be able to overlook issues of narrow pavements or issues of car parking in order to have trees planted.

189 6.5 Comparisons of UK data and US data

The postal questionnaire sent to residents was specifically designed to allow direct comparisons between the results in this thesis and the results found by Lohr et al. (2004). Lohr et al. (2004) used seven positive statements about trees and eight negative statements in a telephone survey of residents of large metropolitan areas in the USA. These statements were adapted for use in the UK as part of the postal questionnaire, and the comparisons between responses are given below. It is useful to compare attitudes in the US and UK; numerous studies show that respondents in the USA are very positive towards trees, and this appreciation can be used to gain more support for tree planting from local authorities and from residents both financially and in kind. Of the two published papers examining attitudes towards trees in the UK, one found fairly positive views (Schroder et al., 2006) while another found relatively ambivalent views towards trees in urban areas (Hitchmough and Bonugli, 1997). If in fact UK residents are just as positive as US residents, it can be hoped that the level of support and kinds of projects found in the USA may also be found in the UK. It would also show that there are no underlying cultural differences affecting people’s attitudes towards trees in these two countries.

6.5.1 Reasons to Plant Trees

Respondents in the UK agree more strongly overall with the positive statements about trees than US respondents, although the rank of statements is different (see Table 6.34 below).

190 Table 6.34. Positive statements about trees. Statements are paired between countries. Statements were ranked by respondents: 1 strongly disagree, 4 strongly agree.

UK Positive Aspects Rated 1-7 Mean US Positive Aspects Rated 1-7 Mean Trees in shopping areas makes it a 3.63 Trees in shopping areas make 3.18 nicer place to spend time and shop people think the stores care about the environment Trees in cities help people feel 3.57 Trees in cities help people feel 3.56 better and less stressed calmer Trees are important in town centres 3.46 Trees are important in downtown 3.69 because they shade and cool their areas because they shade and cool surroundings their surroundings Trees should be planted in town 3.43 Trees should be planted in 3.49 centres to reduce smog and dust business districts to reduce smog from cars and buses and dust Trees should be planted in cities 3.35 Trees should be used in cities 2.97 because they are associated with because they make interesting soothing sounds such as rustling sounds as their leaves rustle leaves and bird song Trees should be planted in cities to 3.33 Trees should be planted in cities 2.93 attract wildlife to attract wildlife Trees should be planted in cities 3.26 Trees should be used in cities 3.36 because they reduce noise because they reduce noise Mean Agreement Score for 3.43 Mean Agreement Score for 3.31 Positive Effects Positive Effects

In the UK, the highest rated positive effect of trees is ‘trees in shopping areas makes it a nicer place to spend time and shop’, which is fairly similar to the US ‘trees in shopping areas make people think the stores care about the environment’. This question could not be used exactly in the UK as most shopping areas are owned by councils, rather than shops themselves, so trees reflect the council’s behaviour and not the shops, so the question would be irrelevant in the UK. This differing wording has led to this statement being most highly rated in the UK, with a high agreement level, while in the US it is lower.

Both countries rate ‘Trees in cities help people feel better and less stressed’ as the second most important aspect of trees. The wording was changed to reflect more widely used vocabulary in the UK. The agreement level is very similar, showing that both sets of respondents value the positive mental health aspects of trees.

In the UK ‘trees are important in town centres because they shade and cool their surroundings’ is rated as the third most important aspect, while in the US it is the most important aspect. This is likely to be due to the differences in climate between the two countries; shading and cooling is most important in areas which have high summer 191 temperatures, which the UK does not have but the US does, so respondents in the US will be more aware of these positive aspects of trees.

‘Trees should be planted in town centres to reduce smog and dust from cars and buses’ is rated 4 th in the UK but third in the US, though with fairly similar agreement levels. Smog is more of an issue in the US due to high temperatures, so this may be why this has been rated more highly.

‘Trees should be used in cities because they make interesting sounds as their leaves rustle’ is rated as the 5 th most important positive aspect of trees in the UK, while it is rated 6 th in the US. More US respondents disagreed with this statement, so this is why the number is over 2 (‘agree’), while it remains under 2 in the UK, showing that more people agreed with this statement.

‘Trees should be planted in cities to attract wildlife’ is rated 6 th in the UK and 7 th in the US. The agreement levels remain quite high in the UK for this, while it is approaching neutral in the US. This may be due to trees attracting less desirable wildlife in the US which can cause serious problems (e.g. raccoons) while in the UK the wildlife attracted to trees is generally restricted to birds and insects.

The least agreed with statement in the UK is ‘trees should be planted in cities because they reduce noise’, which is rated 4 th in the US. Despite being the least agreed with statement in the UK, it still has higher levels of agreement than the 5 th , 6 th and 7 th place statements in the US. The low rating of this statement in the UK is likely to be due to a lack of knowledge about the effects of trees on noise, or the fact that most urban trees are fairly small and so ineffective at reducing noise. In the US large trees are the norm, and so are more effective at reducing noise, so respondents are more likely to be aware of this benefit.

6.5.2 Problems with Trees

The comparison of negative statements about trees with US ratings is very interesting (Table 6.35). Overall UK respondents disagree less strongly with the problems with trees than US respondents, suggesting they are more annoyed by negative aspects of trees.

192 Table 6.35. Negative statements about trees. Statements are paired between countries. Statements were ranked by respondents: 1 strongly disagree, 4 strongly agree.

UK Problems – Rating 1 - 8 Mean US Problems – Rating 1 - 8 Mean Trees should not be planted in cities 1.41 Trees should not be planted in 1.3 because they cost the council too cities because they cost the city much too much Trees should not be used in cities 1.45 Trees should not be used in cities 1.43 because they make it difficult to because they make it difficult to detect criminal behaviour detect criminal behaviour Trees should be removed from cities Trees should be removed from 1.44 because they can fall across power 1.49 cities because they can fall across lines, cars, houses or fall on people power lines Trees should not be used in town Trees should not be used in 1.57 centres because they block shop 1.50 business districts because they signs and get in people's way block store signs Trees should not be planted in cities 1.52 Trees should not be planted in 1.32 because they are ugly when they are cities because they are ugly when not maintained they are not maintained Trees should not be planted along 1.65 Trees should not be planted along 1.42 streets because they drip sap or streets because they drip sap or sticky substances on parked cars sticky residue on parked cars Trees are a problem in cities because 1.67 Trees are a problem in cities 1.64 they cause allergies because they cause allergies Trees should not be planted because Trees should not be planted 1.5 their roots crack pavements 1.74 because their roots crack sidewalks Mean Agreement Score for Negative Mean Agreement Score for 1.45 1.55 Effects Negative Effects

Although both set of respondents rate ‘Trees should not be planted in cities because they cost too much’ as the lowest reason to not plant trees, the US disagreement figure is higher. ‘Trees should not be used in cities because they make it difficult to detect criminal behaviour’ is rated as the second most disagreed with problem in the UK, but the 4 th in the US, but again with a higher disagreement level.

‘Trees should be removed from cities because they can fall across power lines, cars, houses or fall on people’ is the third most disagreed with problem in the UK, but the 5 th in the US, again with a higher disagreement level. The lower level of disagreement in the UK could be due to the larger scope of the question, or due to more media coverage of very rare tree fall incidents in the UK.

‘Trees should not be used in town centres because they block shop signs and get in people's way’ is the fourth most disagreed with statement in the UK, and the 6 th most

193 disagreed with in the US. The level of disagreement is lower in the US, suggesting that trees can block shops signs and cause problems for people. The higher level of disagreement in the UK suggests that trees are planted further from shop fronts or are cut more often so do not block shop signs so respondents are unfamiliar with this problem.

‘Trees should not be planted in cities because they are ugly when they are not maintained’ is the fifth most disagreed with problem in the UK, while it is the second in the US. This suggests either than in the US trees are maintained more often, do not show signs of low maintenance as easily as trees in the UK, or US respondents do not think unmaintained trees are ugly. However, the statement is quite highly disagreed with by both sets of respondents, so it is difficult to suggest any concrete conclusions.

The sixth most disagreed with statement in the UK is ‘trees should not be planted along streets because they drip sap or sticky substances on parked cars’, and is rated 3 rd in the US. The lower level of disagreement with this statement in the UK is not surprising; in the UK sample, almost all cars were parked in the street, under any street trees, so any sap dripping would be immediately noticeable and problematic, while in the US cars are typically parked on a driveway or garage a short distance from the street, so issues of sap on cars would be unnoticed by these residents.

‘Trees are a problem in cities because they cause allergies’ is rated as the seventh most disagreed with statement in the UK, while in the US it is the least disagreed with statement (rated 8 th ). The disagreement level is slightly higher in the US than the UK. The causing of allergies is identified by both sets of respondents as a possible reason why trees should not be planted, though the disagreement level is still high. This suggests that when planting trees, non allergenic species should be chosen and residents informed of this.

The least disagreed with (and so the most agreed with) statement in the UK is ‘trees should not be planted because their roots crack pavements’, and the 6 th most disagreed with in the US survey. The differences between the responses is again due to differing urban morphology between the two countries; in the US pavements are quite wide, but due to the ‘car culture’ are not used very much by people, while in the UK pavements are generally fairly narrow and well used, meaning that tree roots can cause more problems which are seen by more people.

194 Overall, the two sets of respondents in different countries have very similar attitudes towards urban trees. UK respondents agreed more strongly overall with the positive statements and disagreed less strongly about trees than US respondents, though these differences are very small. Further comparisons with other studies may be found in Chapter 8, Section 4.

6.6 Summary and Conclusions

This chapter has described in Section 6.2 the development and implementation of a questionnaire to assess the attitudes towards trees of residents of different types of streets within high density housing. It has addressed the ‘resident attitudes’ potential relationship identified in the Conceptual Framework in Section 3.1.1, and results are given in Section 6.3 and 6.5. The main results of this chapter are: • the responses from residents of four difference types of street vary little in their strongly positive attitudes towards trees; • a small number of differences were seen between agreement levels and street type or housing tenure or education level, but these differences were merely small differences between agreement or disagreement level; • socioeconomic variables have little effect on the positive attitudes shown by respondents towards trees; • respondents overwhelmingly liked the trees in their street: those in Green Streets project areas were very positive about the scheme and would recommend it to others; • the vast majority of respondents stated they would probably or definitely try to move to a street with trees in the future; • the vast majority of respondents that thought trees made a difference to house prices felt that prices increased with the presence or addition of trees to a street; • the results in the UK are quite similar to the results of a similar survey undertaken in the USA, although UK respondents agree more strongly with positive statements and rate reasons to prevent tree planting higher than US respondents.

The results suggest that as all respondents are very positive about trees, resident attitude is not a large factor in affecting tree cover in high density housing areas. Therefore, there is not a relationship between resident attitude and distribution of trees in urban areas and absence of a relationship is recorded in the revised Conceptual Framework of Section 9.1.1. However, as the questionnaire was self-selecting, it may be possible that those who 195 did not like trees did not complete the questionnaire and their views are not represented in the results.

The results have shown that when developing the information for residents to accompany a tree planting scheme for streets it may be helpful to highlight certain aspects of trees in order to achieve the highest level of support for tree planting on a street. Improved information on the aspects of trees with lower agreement levels may be useful in order to increase agreement levels, particularly information related to flood prevention.

The small amount of difference in levels of agreement and disagreement between the US and UK respondents may be accounted for by the differences in housing layout and lower density housing in the USA, problems associated with American wildlife such as raccoons and the differences in climate between the two countries. Similar attitudes between countries suggest that American-style urban forestry programmes may be welcomed in the UK.

196 Chapter 7 – Barriers and Opportunities to Increasing Tree Cover

This chapter states how Objective 4 ‘ In light of objectives 1-3, to inform policy and practice with regard to tree provision in high density residential areas ’ was achieved. Brief methods were outlined in Section 3.4.4, and are covered in greater detail here. This chapter takes the results from previous Objectives, detailed in Chapters 4, 5 and 6, which demonstrate a large variation in tree cover in different types of high density housing, a large potential for tree planting in all types of high density housing and positive attitudes towards trees of residents in high density housing, and explores what is happening in policy and practice in urban areas to increase tree cover. This was achieved through a workshop of practitioners (Section 7.2), and explorations of schemes increasing tree cover (Section 7.3), factors affecting uptake of trees in a community greening scheme (Section 7.4) and factors affecting tree planting and greenery in new developments (Section 7.5).

7.1 Introduction

Objectives 1, 2 and 3 in Chapters 4, 5 and 6 have demonstrated large differences in the amount of tree cover in different types of high density housing, that tree cover may, in principle, be increased in these housing types and that residents are very positive and supportive of tree planting schemes. Therefore, the question now becomes ‘how may tree cover be practically increased in these areas?’.

There are a number of different ways to increase tree cover, and many barriers and opportunities for these projects. Trees may be planted at the same time new houses are built, may be planted as part of an urban regeneration scheme, or may be planted into a street that is undergoing no other change. Tree planting alongside (re)development may be driven by the developer or by the local council, via legislation or aesthetic considerations. Tree planting into existing housing may be driven by the local community through a Green Streets type scheme, or may be driven by the local council, again via legislation or aesthetic considerations.

There is a growing amount of research highlighting best practise for planting trees in urban areas (e.g. Jones et al., 1996; West et al., 1999; Appleyard, 2000; Pauleit et al., 2002; Watson, 2005) and the UK Government has produced good practice guidance for 197 site selection and planting of street trees (DCLG/Trees for Cities, 2008). However, no study has directly compared approaches to increasing tree cover, or explored the barriers encountered by practitioners to increasing tree cover. This chapter aims to address that research deficit.

7.1.1 The Legal and Planning Context for Urban Trees

In order to understand the issues surrounding urban trees and the potential for increasing urban tree cover, the legal aspects around urban trees must be explored. The following section provides an outline of the key legislation which affects urban trees and tree planting in the UK.

The main legal protection trees have is a Tree Preservation Order (TPO), which allows any tree to be protected from felling or destructive pruning. The tree must be considered to contribute ‘amenity value’ to its surroundings, and the TPO may apply to single trees or a group of trees (Hartle, 1981). Tree Preservation Orders were introduced by the Town and Country Planning Act 1971, along with powers to demand new tree planting as part of new development or in return for felling a tree subject to a TPO. Specific points relating to TPOs were updated in the Town and Country Planning Act 1990, and the name was changed to Tree Preservation Regulations in the Town and Country Planning Act 2008. Non-woodland trees without TPOs on them are not protected from damage or felling, except under laws relating to damage to property (Hartle, 1981). Unfortunately, it can be very time consuming to keep track of and enforce TPOs and there is usually little budget for this. If prosecutions are brought, penalties are often low and do not provide a deterrent to others (Hartle, 1981; Britt et al., 2008).

A commonly used method of funding tree planting and other greenspace and park improvements is the use of developer agreements, in which money for these improvements is given to the local authority in return for allowing development. These ‘Planning Obligations’ are commonly known as ‘Section 106 agreements’ after the legislation within the Town and Country Planning Act 1990 which created the power to make these agreements. The law is quite vague and it is dependent on the local planning department to decide whether to enforce planning obligations and if so, what obligations to insist on. The law has been used to give a diverse range of benefits, from larger flats and more affordable homes in the development, to funding towards local schools, community and leisure facilities, the improvement of parks and greenspaces and the planting of trees (Crook et al., 2010). A forthcoming law intended to extract some of the 198 windfall gain due to development, called the Community Infrastructure Levy, is intended to work in conjunction with section 106 agreements and this will relate to all except the smallest scale developments (Crook et al., 2010).

Planning policy in the UK is undergoing revision and updating; it would be expected that, in light of the numerous benefits trees provide (highlighted in Chapter 2), the planting and protection of trees would be mandatory or at least highly recommended for development and regeneration. Unfortunately, this does not seem to be the case (see Table 7.1 below).

Table 7.1. The occurrence of key terms in UK planning policy. Documents downloaded for the Department of Communities and Local Government http://www.communities.gov.uk/planningandbuilding/planningsystem/planningpolicy/planningpolicystate ments/ Planning Policy Statement (PPS) or Number of Number of Guidance (PPG) mentions of ‘green mentions of [year passed] infrastructure’ ‘tree’ or ‘trees’ PPG2: Green Belts [1995] 0 1 PPG17: Planning for Open Space, Sport and 0 0 Recreation [2002] PPS7: Sustainable Development in Rural Areas 0 1 [2004] PPS1: Delivering Sustainable Development 0 0 [2005] PPS9: Biodiversity and Geological 0 2 Conservation [2005] PPS25: Development and Flood Risk [2006] 1 0 PPS3: Housing [2006] 0 0 PPS1: Supplement: Planning and Climate 1 2 Change [2007] PPS12: Local Spatial Planning [2008] 2 0 PPS1: Supplement: Eco Towns [2009] 2 0 PPS4: Planning for Sustainable Economic 0 1 Growth [2009] PPS: Planning for a Natural and Healthy 116 14 Environment 9 (consultation document) [2010]

9 This consultation document proposes consolidating the existing Planning Policy Guidance 17: Planning for Open Space, Sport and Recreation, Planning Policy Guidance 20: Coastal Planning, Planning Policy 199 The table shows that in Government planning policy there is very little consideration given specifically to trees. More recent Government documents seem to favour the buzzword ‘green infrastructure’ over the much more tangible ‘tree’. Green infrastructure is defined by the Government as ‘a network of multi-functional green space, both new and existing, both rural and urban, which supports the natural and ecological processes and is integral to the health and quality of life of sustainable communities’ (DCLG, 2008, p.6). Green infrastructure can and should include trees within the green spaces, but there is no Government requirement that they do. None of the documents insist on tree planting and protection; where protection is mentioned, consultation of existing Tree Preservation Orders is demanded to ensure protection of amenity trees. No policy mentions street trees specifically.

The lack of reference to trees in national planning documents, combined with few penalties for those that damage trees, means it is difficult to suggest or demand that new trees be planted and old trees protected, as there is not the basis in planning policy or an effective legal deterrent. This may be rectified to some extent at the local level with Local Authority Development Plans, though it very much depends on the attitude of the Local Authority concerned. The use of planning obligations can provide money to plant and maintain trees, but there are many competing demands for this money and trees may be sidelined in favour of other projects.

Statement 7: Sustainable Development in Rural Areas, and Planning Policy Statement 9: Biodiversity and Geological Conservation into a single document. The consultation closed on 1/6/10. 200 7.2 Practitioner Workshop

Increasing tree cover in urban areas is affected by a range of factors, and can be influenced by a range of stakeholders ranging from the local council, community forests, residents groups, housing associations and regional development bodies. Almost all professionals in the planning and greenspace sectors recognise the positive aspects of increasing trees and greenspaces in urban areas, but face different barriers and can access different opportunities. Therefore, any discussion about increasing tree cover requires the involvement of all stakeholders in order to properly explore the barriers and opportunities available. A workshop with a range of attendees from these differing groups was organised to in order to explore their differing views and experiences of the barriers and opportunities to increasing tree cover in high density housing areas.

7.2.1 Methods

In order to share the research finding of objectives 1 to 3 with professionals working in with trees in urban areas, and to explore the barriers and opportunities faced by them in their attempts to increase urban tree cover, it was decided that a workshop with presentations and discussions would be the most appropriate setting. The workshop was entitled ‘Barriers and Opportunities to Increasing Tree Cover in Urban Areas’. A half day event was chosen as it would mean professionals taking the least amount of time from their schedules. Participants arrived for lunch, then were given an introduction to the event by the researcher’s first supervisor followed by two presentations: one outlining the findings of objective 1 to 3 in this research, and one describing related work by another PhD candidate working on measuring experimentally the effects of trees on the biophysical environment of urban areas. After this, participants were split into smaller groups to discuss four themes around urban tree planting which may be both barriers and opportunities. These themes were legislation, funding, residents and design, as outlined in chapter 3.4.4.

The workshop discussions used Ketso kits as an aid to recording conversations and thoughts. The kit has been developed over a number of years and iterations by Tippett, and participation methodologies are discussed in Tippett (2004) and Tippett et al. (2007). The kit allows consideration of a number of related ideas at the same time, broadening the basis of discussion and helping people move outside their area of expertise (see Figure 7.1). This was seen as particularly helpful for this workshop discussion, as 201 participants would be looking at themes with which they may not be familiar; for example, a participant who works with Tree Preservation Orders may be unfamiliar with issues of funding. The Ketso kit was chosen to facilitate discussion for both the individual and the small group.

Figure 7.1. Participants using the Ketso kit to aid discussions.

Using the Ketso kit, ideas and discussions points were written on different coloured leaves to signify whether an idea was a barrier, opportunity or example of existing good practice. Symbols and comments cards were also used to highlight potential good solutions or problems, and ideas clarified where necessary (see Figure 7.2). After around 20-25 minutes, participants moved to another theme, where they could discuss previous groups’ ideas displayed on the Ketso kit and add their own. The workshop concluded with feedback from the discussions and a brief consideration of the future for street trees, including the best methods to plant more and look after existing trees.

202

Figure 7.2. A section of the ‘Legislation’ discussion. Grey leaves indicate barriers, green leaves opportunities, a tick shows another group agrees with a topic, and an exclamation mark shows another group is also concerned with the same issue.

Potential participants for the workshop were selected from the local councils in the study area, and public and private sector organisations active in the Greater Manchester area. Participants from national organisations concerned with tree planting and protection were also invited. Organisations were contacted by phone and informed about the workshop, and asked to suggest the most relevant person who might be able to attend the workshop. Details of the workshop were then sent by email. A list of attendees in Table 7.2 below, and organisations contacted but unable to send a representative is given in Table 7.3.

Table 7.2. Workshop attendees. Organisation Role Name Manchester City Council Arboricultural Officer Steve Leaff Bolton Council Adaptation to Climate Jonathan Mayo Change Planner Bolton Council Tree and Woodland Matthew Rainer Manager Bury Council Landscape Planner and Michael Dowd TPO Officer

203 Salford City Council Assistant Principal Officer, Richard Boyer Parks and Countryside Trafford Council Senior Arboricultural Derek Austin Planner Wigan Council Trees and Woodlands Sarah Sadler Officer Wigan Leisure and Culture Senior Arboriculture Ged Collins Trust Officer Natural England Delivery Leader - Green Martin Moss Infrastructure Forestry Commission Newlands Project Adam Davison Development Officer Red Rose Forest Special Projects manager Pete Stringer Mersey Forest Green Streets Coordinator Ben Greenaway Woodland Trust Senior Advisor - Evidence Mike Townsend and Policy Development Trees for Cities Policy Director Emma Hill Tree Council Tree Warden coordinator Margaret Lipscombe Freelance consultant - Nerys Jones Creative Concern NW Forestry Framework Steve Connor chair TEP Arboricultural Consultant Jonathan Smith

Table 7.3. List of organisations/individuals invited to attend the workshop but were unable to attend/send a representative. Organisation Role Name Manchester City Council Green City Team Corin Bell Salford City Council Tree Officer Paul Jones Trafford Council Tree Officer Andy McKenzie GM Ecology Department - [no individual contact] Government Office NW - [no individual contact] Highways Agency Environmental Advisor Sheena Crombie NWDA Head of Environmental Richard Tracey Quality 4NW Regional Planning Officer Debra Holroyd

204 Environment Agency - [no individual contact] Forest Research Head of the Land Tony Hutchings Regeneration and Urban Greening Group CABE Space - [no individual contact] Wildlife Trusts Conservation Officer for Tim Mitcham GM London Trees and Design CABE Space contact Chris Edwards Action Group New Charter Housing Operations Manager Danny Vose Association New Charter Homes Ltd National Housing North West Regional Sallie Bridgen Federation Manager Urban Roots Planning Director Murray Graham Treework Environmental Principal Arboricultural Neville Fay Practice Consultant and Company Director

7.2.2 Results

The presentations and discussions at the workshop were very lively, and lots of different points were raised about trees in urban areas. Although discussions were held in four distinct themes, points were raised that crossed over between themes and this is highlighted in the results and recommendations detailed below. Workshop discussions demonstrated that existing barriers may become opportunities if certain aspects are changed; therefore, barriers and opportunities have not been separated within the results. A more detailed summary of the workshop, which was sent to attendees, is included as appendix 2.

A. Legislation

As indicated in section 7.1.1, there is little direct legislation related to trees. Some legislation, like Section 106 Agreements, may be used creatively to gain money for trees, while others, such as climate change legislation may be used to infer support for trees through broad statements about sustainability and liveability.

205 A.i.) Planning Policy

The current streamlining of Planning Policy Statements (PPS) was found by practitioners to be leading to a loss of important information and guidance about practically implementing the policies. Therefore, is it recommended that PPSs need to be kept with the appropriate guidance notes to allow proper understanding and carrying out of the policies.

It was felt that although there are some good examples of tree planting and green infrastructure planning, especially the London Olympic project, new legislation is required to ensure that green infrastructure is a critical part of new development, designed in from the beginning, not as an afterthought or because it is currently ‘trendy’. New legislation should also take account of emerging research findings about trees and greenspaces.

The workshop participants felt that it is essential that gardens are reclassified as greenbelt land, not previously developed (‘brownfield’) land to prevent urban infill development. Since the workshop there has been a change in government in the UK; one of their first acts was to remove gardens from the ‘previously developed land’ category (DCLG, 2010). This may be seen as a small victory for the protection of urban trees.

A.ii.) Planning Policy Conditions and Enforcement

A revision and tightening of planning conditions given to new planning permissions for new developments was seen as a good way to introduce tree care and greenspace planning into a development. It was recommended that planning conditions should be able to ensure consultation with an arboriculturist, landscape architect and highways officer so trees may be properly included in developments in a way appropriate to the surrounding landscape. Other conditions should include following recommendations of the Trees and Design Action Group’s ‘Right Tree Right Place’ resource, and extending the establishment period, during which new trees receive specific aftercare, from 2 to 5 years.

Issues with relaxed attitudes to upholding planning and development laws were highlighted, as it was felt that these do not deter developers and homeowners from cutting down trees on their land. Therefore, laws must be strengthened to protect urban

206 trees from unnecessary felling and development. This could include higher penalties given to those proven to have illegally felled a healthy tree. It was recommended that all urban trees over a certain size should be automatically protected from unnecessary felling, and all local authority trees should automatically be covered with a TPO.

A.iii) Local Authorities and Trees

Workshop participants stressed the importance of every local authority conducting a Tree Inventory, which is maintained and updated. This should then inform a Tree/Green Infrastructure Strategy, which would aid a strategic overview of tree planting and maintenance. Linked to this, the potential for extending the London and Birmingham Trees and Design Action Groups, which give support and advice on trees in urban areas, to other regions should be investigated.

Service Level Agreements (SLAs) between local authority tree officers and Arms Length Management Organisations (ALMOs – similar to Housing Associations) should be investigated to protect and improve trees and greenspaces.

B. Funding

Funding was a theme by itself, but it is such a major issue for urban trees that it spilled over into the other themes too. A great issue for tree planting is starting finance and the overall cost of projects. Workshop participants felt that new and different ways of funding need to be investigated, as council budgets are cut. Funding schemes should be sought which allow money for tree maintenance for a number of years after planting; many projects do not currently allocate money for this, meaning that tree officers are wary of taking on new projects knowing the potential future costs.

B.i.) Barriers to Funding

Barriers mentioned during the discussion centred on the low priority tree planting can have in local authorities, particularly when competing against other issues such as housing and health and against the background of looming council cuts. The problems surrounding using council capital or revenue money for trees and maintenance were highlighted, something that could be changed with legislative change. There is a lack of money for regular maintenance of existing and newly planted trees, which can lead to

207 resident complaints or a growing dislike of trees due to issues of leaf and fruit fall on pavements and cars, issues of TV reception or branches hitting property, hindering support for new tree planting.

When new trees are planted, there is very often no money for their future maintenance included in the project budget. The cost of aftercare is usually not addressed; there are special considerations of establishing street trees, and balancing of tree budgets or funding across planting, nurturing and mature maintenance was seen as a good way to plan tree care budgets or project funding. However, often with externally funded tree planting schemes, funding is very short term and/or the criteria do not allow money to be set aside for tree maintenance in the future. This needs to change if new trees planted are to survive to maturity and avoid some resident complaints.

Lack of money for planning and arboricultural services also means that new trees on new development sites may not be monitored, meaning that trees planted as a condition of planning permission may die but not be registered in time to force the developer to plant a new tree.

B.ii.) Existing funding schemes

A range of funding schemes to plant new urban trees were highlighted at the workshop. Section 106 agreements (outlined in 7.1.1) were praised for their ringfenced funding, which can be use for tree planting and park maintenance. Workshop participants were positive about the new Community Infrastructure Levy (outlined in 7.1.1), which they hope will give more strategic off-site mitigation of development and more strategic planning of trees and greenspace. Other funding opportunities mentioned were the Forestry Commission’s Woodland Creation Grants, the Playbuilder/National Play schemes to improve play areas in parks (which may also be used to tidy up surrounding parkland), the Green Streets schemes, National Lottery funding (although priorities change frequently) and small local charities.

B.iii.) Inventive accessing of other funding

There are a number of existing grant schemes that could be accessed with creative thinking and promotion of the benefits of trees, such as PCT Health and Well-Being grants which could be used to improve parkland for health walks and other recreation,

208 and the Future Jobs Fund, which could be used to set up a small parks maintenance company for example. Utility companies could be encouraged to plant trees to reduce peak run off to waste water treatment works, either for their own sake to reduce their costs, as part of the Flooding and Water Management Act 2010 or through a carbon credit scheme. Money may be able to be diverted from other council departments to arboriculture departments through virements (a strictly regulated process of transferring items, especially public funds, from one financial account to another) as part of a regeneration, public health or education scheme.

B.iv.) Other methods of funding

Other methods to potentially indirectly generate funding were discussed. Although not having funding of their own, green initiatives such as Eco-Schools and Transition Towns may be used to increase the profile of urban trees and their benefits to encourage funding by other sources. Use of celebrities such as David Bellamy to increase the profile of urban trees, as well as using National Tree Week for extra promotion of tree schemes for extra donations/funding was suggested.

B.v.) Funding through ‘urban timber to biomass’ schemes

The potential for using urban timber for biomass or timber use was mentioned on a number of separate occasions, suggesting there is strong support for the potential of this revenue generating scheme. The potential should be investigated on both a local, regional and national scale, both as a revenue stream and as a way of reducing carbon emissions.

C. Residents

Residents can have a large influence on the success or failure of tree planting schemes, and the involvement of local residents and the community in tree related activities were cited and praised by many participants.

C.i.) Residents and Funding

It was suggested that as many residents are very positive and supportive of urban trees and greenspace, money could be raised directly from them. An example of this is the existing ‘Adopt A Tree’ scheme in Trafford in which the resident pays for and cares for

209 the tree and Trafford Council pays for planting. Another method could be through a levy on car parking charges in city centres or on sports facilities that is ringfenced for urban tree planting and maintenance, or residents could contribute money through a scheme similar to the monies raised for maintenance of London squares from neighbouring residents. Similarly, residents could gain reductions in their council tax, or future Carbon Tax Credits, in return for green concessions (e.g. insulation, fewer miles driven) or for help maintaining urban trees (e.g. leaf litter picking, issue reporting). Residents may also choose to ringfence council or personal taxes for urban forestry. Trees and improving greenery may be used as community payback for improvements in other aspects e.g. setting up a Neighbourhood Watch scheme. Some companies may wish to sponsor a tree planting scheme near their offices, so these possibilities should be investigated.

C.ii.) Residents and Information

Workshop participants felt that more promotion of benefits of trees could help change resident antipathy and ambivalence into positive views or even enthusiasm about trees. Damage to trees through vandalism was listed as a problem by workshop attendees, who had experienced problems with residents arguing that trees should not be planted as they will be vandalised and it will be a waste of money. This is despite extensive work by Bradshaw et al. (1995) which has shown that poor maintenance or an absence of maintenance is much more commonly responsible for tree damage and death than isolated incidents of vandalism. Community projects like Green Streets see quite low levels of vandalism and involve residents in regular maintenance; this suggests that community projects that address these two issues for tree survival are likely to have lower levels of tree mortality than other schemes. Consultation was listed as a good existing method, a barrier to and an opportunity for increasing tree cover, showing that involving the community is both positive and negative.

It was suggested that information about realistic tree and tree root damage needs to be circulated to give people more confidence when dealing with insurance companies and unscrupulous tree surgeons. Anecdotal evidence at the workshop highlighted a number of cases where tree surgeons had cut down trees on safety grounds which were healthy or cut trees back so much that they subsequently died.

210 D. Urban Design

The issue of trees competing for space in crowded pavements with cramped underground services was raised on a number of occasions. It was felt that engineering solutions to trees in streets can and must be found. This could include trees in pots on pavements, although this raises issues of irrigation. Enough interest was shown in this topic that there is likely to be a potential PhD exploring different scenarios.

7.2.3 Discussion

The discussions at the workshop showed that practitioners were very aware of the issues that surround urban trees, and the emerging academic research about their effects on the local environment. Practitioners were keen to suggest improvements for legislation and funding schemes, and had imaginative ideas of ways to raise funding for urban trees and tree planting. A number of good existing schemes were highlighted, although ways of sharing this good practice did not appear to be well defined. It was encouraging that practitioners appeared relatively upbeat and positive about the continued existence of trees in urban areas, despite the current barriers and problems faced by trees. The potential of using urban trees and woodlands as a source of biomass was a popular subject, and suggests that further research should be done to investigate the feasibility of this. If it can be shown to be workable and practical then it is likely there would be considerable support for such a scheme from practitioners.

211 7.3 Increasing Tree Cover in High Density Housing – Examples

Chapter 5 explored the potential maximum achievable level of tree cover in high density housing types. In order to gain an understanding of how tree cover may practically be increased, a number of case studies were examined to determine the extent to which different approaches may increase tree cover. The two approaches compared here are planting trees as part of a regeneration project versus the planting of trees through a community driven tree planting scheme of the Red Rose Forest’s Green Streets project.

7.3.1 Case Study Area Selection

All recently completed Green Streets projects and areas that had recently undergone regeneration were identified within the study area. The housing type of each Green Streets area and regeneration area was noted. Areas of regeneration were then matched with areas of similar housing where a Green Streets scheme had been carried out. These areas could then be compared to give a meaningful comparison of tree planting in both types of scheme.

Two regeneration areas were selected to compare with Green Streets projects. The first area was in Langworthy, Salford, and was named Chimney Pot Park. This is an area of pre 1919 terraced housing that opens directly onto the road, and was an area of very low housing demand; so much so that the houses were scheduled for demolition. Through the intervention of the area’s MP, the developers Urban Splash were brought in to develop an innovative way of regenerating the housing and making it an area people would want to live in. Urban Splash were originally unsure whether the housing could be dramatically changed, but with their architects a very innovative style of housing was produced. The second regeneration area was the area which has become Grove Village, in Ardwick, Manchester. This again was an area of very low housing demand, and consisted of run down 1960s walkway and driveway council housing. Using newly given powers, Manchester City Council initiated a housing Private Finance Initiative (PFI) to transform the estate into a sustainable, mixed tenure, well-managed urban village, where people would choose to live. It was the first housing PFI project to reach contract signing in the country, and the consortium included Harvest Housing Group, MJ Gleeson Group and Nationwide Building Society. 436 homes have been demolished and 663 homes for rent have been refurbished. These rented homes remain property of Manchester City Council. By completion (around 2012) around 660 new homes will be built for sale. 212 Table 7.4 and Figure 7.3 below show the areas chosen and their location. The two regeneration areas, described above, were selected for their housing type, recent completion and a perceived interest on behalf of the developer in greening the area. Areas considered good or excellent Green Streets projects were assessed for their suitability to compare with the regeneration areas. The areas selected are detailed in Table 7.4 and Figure 7.3. Palmerston Avenue and Edenhall Avenue were considered as a single case study, due to their similarity and small size, and were comparable to the Chimney Pot Park regeneration area. The Whitekirk Close area was selected as it was comparable to the Grove Village regeneration area.

Three of the case studies are in Manchester, one in Salford; previous analysis has not shown any difference in tree cover in different local authorities (see Section 4.1 and Tame, 2006) therefore this should not affect the results. It may be argued that the Green Streets schemes are too small to give an accurate comparison with the larger regeneration schemes. A large Green streets scheme in Thornton and Horton Roads has therefore been included as an example of larger scale street tree planting. The housing type in these roads in ‘Pre-1919 terraced housing with a front yard’ and so it not directly comparable to the regeneration schemes, but is included to demonstrate the potential of the scheme on a larger scale.

Table 7.4. A comparison of case study areas. Project Type Area Name Housing Type Regeneration area Chimney Pot Park Pre-1919 terrace onto road Green Streets Palmerston Ave and Pre-1919 terrace onto road (2 Edenhall Ave small examples) Regeneration area Grove Village 1960s walkway/driveway Green Streets Whitekirk Close area 1960s walkway/driveway Green Streets Thornton/Horton Pre-1919 terrace with front yard Demonstration Scheme Roads

213

Bury Oldham

Salford

Manchester

Tameside

Trafford Stockport

Figure 7.3. The location of the study sites within Manchester and Salford for comparison of tree planting schemes. Street maps are not to scale. Clockwise from top right: Chimney Pot Park, Grove Village, Edenhall Avenue, Thornton and Horton Roads, Palmerston Avenue.

214 7.3.2 Methods

Each study area was visited and the location of each tree recorded. However, only trees in the public realm were recorded, as access to private space to record tree numbers was deemed unworkable. This would be a problem if provision of all trees and planting were to be studied; this is not the case in these study areas, and this section will only deal with street trees and the appearance of an area from the street.

In order to determine the effectiveness of a planting programme, the potential maximum number of trees that could be planted into an area must be calculated. For each case study area this was done following the methods outlined in section 5.2.1. This used aerial photographs to determine where trees may be appropriately planted. As only street tree increases were considered in this section, the 8 metre boundary between trees planted in pavements, as recommended by the Red Rose Forest Green Streets team, was of particular importance. Tree number was considered the most appropriate measurement as comparing the percentage of tree cover between existing and newly planted trees would not give a fair comparison; tree cover will increase as trees grow, so number is more appropriate.

7.3.3 Results i.) Green Streets For the Green Streets case study areas, there were no trees in the public realm before the project. The table below shows how close the schemes came to achieving the maximum number of trees planted. The potential figure refers to the number of trees that could be planted if resident support and funding is unlimited (see 5.2.1 for further details).

Table 7.5. The potential and achieved numbers of trees for the Green Streets projects. Scheme Potential Tree Achieved Tree % of potential Number Number achieved Palmerston Ave 12+15 10+13 83.3%+86.6% and Edenhall Ave Whitekirk Close 58 25 43.1% area Thornton/Horton 222 111 50% Roads

215 Palmerstone Avenue and Edenhall Avenue had very high uptake levels, planting almost the maximum potential number of trees. These were two small scale projects in the ‘pre1919 onto road’ housing type. The lowest percentage of potential trees actually planted was in the Whitekirk Close area, an area of ‘1960s walkway’ housing.

In the larger scale Green Streets example, Thornton and Horton Roads, 50% of the maximum number of trees were planted. If this figure is compared to Palmerston and Edenhall Avenues it seems rather low, but the number of trees planted is much higher as their streets are larger. ii.) Regeneration Areas

In the regeneration areas, there were trees in the public realm before the projects began. Table 7.6 shows the number of trees before and after regeneration. The potential figure refers to the number of trees that could be planted if resident support and funding is unlimited (see 5.2.1 for further details).

Table 7.6. Tree numbers before and after regeneration. Area Tree Number Number of Tree Number Potential % of Before Trees After Tree potential Regeneration Removed 10 Regeneration Number achieved Chimney Pot 51 14 57 266 21.4 Park Grove Village 136 11 90 291 825 35.3

In both regeneration areas, more trees were planted than were removed, but less than a quarter of the potential maximum number of trees were planted in Chimney Pot Park, and less than two fifths of the potential maximum number of trees were planted in Grove Village. Figure 7.4 below shows the use of existing and new trees within Chimney Pot Park. Note the asymmetric planting scheme, unlike the more usual avenues of street trees.

10 Includes the number of trees (if any) removed because they were dead/dying/diseased. 11 An estimation of the number of trees that could have been kept alongside the extensive remodelling of streets. 216

Figure 7.4. Trees along two different streets in Chimney Pot Park. Left, existing trees integrated into the development. Right, new trees planted.

In Grove Village, many large trees such as those on the right of Figure 7.5 (below) have been removed. Small trees like those on the left of Figure 7.5 have been planted instead, into semi-permeable tree pits rather than grass verges.

Figure 7.5. Trees in Grove Village.

It must be remembered that ‘potential tree number’ assumes complete resident support and unlimited funding, which could overcome physical barriers to tree planting, such as underground services, too narrow pavements or poorly sited lampposts. 217 iii.) Comparison between Housing Types

In the ‘pre1919 terraced housing opening directly onto the road’ housing type, tree number was increased to around 85% of its potential by Green Streets projects, while it was increased by just 21.4% in the regeneration project. The percentage of potential number of trees planted that were actually planted in the regeneration area was much lower than in the Green Streets areas; the housing type is the same so there must be other factors involved that influence the planting of street trees.

In the 1960s housing of Grove Village and the Whitekirk Close area, tree number was increased by fairly similar amounts: 35.3% and 43.1% respectively. This suggests that it is more difficult to reach the potential maximum number of trees planted in these areas and that other factors influence tree planting in these areas.

7.3.4 Discussion i.) Increasing Tree Number – Green Streets Projects

There were no existing street trees in the public realm in the projects studied. Tree number was increased to almost the maximum number of trees in the smaller streets of Edenhall Avenue and Palmerston Avenue. The larger area of the Whitekirk Close estate reached 43.1%, and the two streets of Thornton and Horton reached 50% of potential trees planted.

The small streets of Palmerston Avenue and Edenhall Avenue had a very high planting rate; their small size meant neighbours were perhaps more likely to know each other and persuade each other to accept a tree, and both streets had a proactive champion. The lack of front gardens may have been a factor; a street tree would be an opportunity to green the street they may not get again. The small street size also meant there were fewer issues with lampposts and siting of trees.

The Whitekirk Close area planted a fairly low percentage of their potential trees. The reasons for this are unclear; the layout of the estate meant that no resident would be directly affected by the trees so residents were asked only for comments or refusal of a tree. Therefore, it is likely that lampposts and other underground services prevented further planting, or a lack of funding, rather than resident opposition to trees.

218 The street layout of short terraces and alleyways in Thornton and Horton Roads suggests that problems may have been encountered fitting trees in due to lampposts and alleyway access. Despite this project not planting close to the maximum number of trees, the scale of the project meant the effect of the tree planting was dramatic. ii.) Increasing Tree Number through Regeneration

More trees were planted during both redevelopments than were removed. However, the success of the tree planting will depend on the species of tree planted and the planting medium chosen.

In Grove Village, a major difference between retained and newly planted trees was the planting medium. Existing trees were generally growing in grass verges, while new trees were planted in tree pits surrounded by permeable concrete (see Figure 7.3 above and Figure 7.6 below in Section 7.5.3). Trees in grass verges need to compete for nutrients with grass and other plants, which may limit their growth. Trees in tree pits do not have this problem, but instead are greatly affected by soil compaction. Smiley et al. (2006) demonstrated that cherry and elm trees grow much better in pits where the soil cannot be compacted. It is not known how the replacement trees in Grove Village were planted; this will greatly affect the success of the tree planting scheme.

The trees in Chimney Pot Park were planted in a similar way to the retained trees, suggesting that they may reach a similar size. However, a mix of species was planted; some new hornbeam trees were planted, similar to some existing trees, which could reach a similar size. Other trees planted included ornamental pear (Pyrus callaryana ‘Chanticleer’) which would be unlikely to reach a similar size. The new trees were not protected by a tree guard as many retained trees were. Bradshaw et al. (1995, p179) warns against the use of guards due to the range of damage to a tree they can cause if unmaintained; indeed, damage to trees from the tree guard was seen in streets neighbouring Chimney Pot Park (see left of Figure 7.6 below) where one tree had grown over and around the guards and was subsequently cut down. Unfortunately, at least one tree in Chimney Pot Park had been driven into and the trunk had kinked, though it appeared otherwise healthy (see right of Figure 7.6); this may have been prevented with the use of a tree guard for trees in areas that cars could access.

219

Figure 7.6. Left: photo showing a felled tree that had grown over its metal tree guard. Right: photo showing a newly planted trees unprotected by a tree guard with a kinked trunk from car damage.

220 7.4 Factors Affecting Red Rose Forest Green Streets Project Uptake

Some Green Streets projects are able to plant more trees than others, as more residents are supportive of the scheme and agree to tree planting outside their home. The reasons for this are unclear; it may be due to housing type, socioeconomic factors or environmental factors, such as being close to a park. This section explores any correlations between uptake levels and other factors.

7.4.1 Methods

Red Rose Forest keep records of all Green Streets projects, including the number of homes consulted, the number of residents that wanted a tree, the number of residents that did not want a tree and the number of trees planted. Five years of data was used for this study, from the 2004/5 planting season up the 2009/10 planting season. The percentage of homes agreeing to have a tree planted outside their home was analysed for any correlation with index of multiple deprivation (IMD), housing type, percentage of homeowners and the Natural Environment Index (PBRS, 2007). The Natural Environment Index was developed by a consultancy for a range of statutory bodies in the North West, and gives a value for areas based on their natural environment and local access to greenspace.

7.4.2 Results

Over 5 years of the Green Street project, 68 streets and 2 small estates have had a total of 945 trees planted in them. No correlations were found using linear regression analysis between the variables of percentage of residents wanting a tree, percentage of residents not wanting a tree, percentage of residents who did not respond, and index of multiple deprivation, housing type (scaled to reflect built portion of surface covers, as calculated in chapter 4), percentage of homeowners and the Natural Environment Index. The largest R2 value was 0.15, a non significant value.

22 streets were deemed to have a proactive Green Streets Champion (Red Rose Forest, pers. comm., 2010) who encouraged their neighbours to agree to tree planting outside their home. The differences between these streets are shown below.

221 Table 7.7. The differences in number of residents agreeing to have a tree planted outside their home as part of a Green Streets schemes with and without proactive champions. Percentage Yes Percentage No With Proactive Without With Proactive Without Champion Proactive Champion Proactive Champion Champion Mean 76.6 67.8 7.4 10.25 Median 80 66.7 6.5 8.2 Std. Dev. 12.9 24.4 6.1 11.5 Minimum 45.6 18.2 0 0 Maximum 100 100 22 50 N 22 38 22 38 2 sample t- t = 1.551, Sig. = 0.126 t = -1.078, Sig = 0.285 test One way F = 2.4, Sig = 0.126 F = 1.16, Sig = 0.285 ANOVA

The percentage of residents agreeing to a tree outside their home was higher in streets with a proactive champion than in streets without one. In particular the standard deviations were smaller in streets with a proactive champion than streets without. However, both a two sample t-test and a one way ANOVA did not show significant differences in percentages of residents that did or did not agree to have a tree whether with or without a proactive champion. For these tests, percentages of those respondents who did want a tree, did not want a tree or did not respond were used, as size of street(s) would not affect the results, e.g. comparing a large street with a proactive Green Streets champion with a small street without a proactive champion. Other tests may be performed using the raw numbers of residents who did or did not want a tree. This χ2 test for associations is given in Table 7.8 below.

Table 7.8. χ2 test for associations for number of residents accepting or declining a tree in streets with and without a proactive Green Streets champion. Number accepting a tree Number declining a tree Proactive Champion 525 55 Without proactive Champion 613 145 Pearson χ2 value 24.050 (significant at the 0.000 level)

222 Table 7.8 shows that the presence of a proactive champion has a significant effect on the number of trees accepted by residents. This demonstrates the importance of active community engagement in increasing numbers of trees in community greening projects.

7.4.3 Summary

It is surprising that no correlations were found between percentage of residents wanting or not wanting a tree or those who did not respond to the consultation and any of the potential indicators. The only reliable indicator of the percentage of residents agreeing to have a tree was the presence of a proactive Green Streets Champion, who encouraged neighbours to have a tree planted outside their home, leading to a higher uptake level. When raw numbers are used, rather than percentages, a statistically significant effect was found. This suggests that, over the whole Green Streets project, the presence of a proactive champion helps to increase uptake of trees on their street, but that on a street by street level, in terms of overall percentages, this effect is lessened.

223 7.5 Factors Affecting Use of Trees and Greenspace in Regeneration Schemes

7.5.1 Methods

In order to determine how and why trees were used in the two case study regeneration schemes, it was necessary to interview professionals who were involved in the schemes. The developers responsible for each scheme were contacted and asked who the most relevant person to interview would be. For the Urban Splash project, the director of development was interviewed. For the Grove Village project, a landscape architect at PRP Architects, the firm responsible for the design of the area, was interviewed.

7.5.2 Chimney Pot Park

During the planning of the regeneration of this area, the developers investigated the housing style and the things that worked well and did not work well. It was found that the space behind houses was not well used by residents, leading to the alleyways between rear yards becoming an area for dumping rubbish and petty crime, as well as allowing access for burglars. The security of cars parked outside homes was also a concern. Combining these issues lead to the raising of the rear spaces of homes with secure car parking underneath (see Figure 7.7 below).

The first plan was to have a large communal garden on this raised section, in the style of apartment blocks, but it was decided that some divisible space was preferable for individual residents to cultivate. Each house has a private area of decking, separated from their neighbour by bamboo plants. There is a communal fire escape corridor running the length of the housing block. There are large planters at either end of this corridor, planted with edible plants; these were designed as communal so anyone could plant into them and enjoy them. Individual residents are now tending these areas, which has pleased the developers as they wanted to foster an environment where they provided resources and the residents themselves moved the ideas on. Some edible plants were also planted into private areas with the idea that neighbours would take cuttings from each other and foster a sense of community. The developers considered methods to increase resident interaction, and therefore foster a sense of community, an important part of the development. This was seen as particularly key due to the close proximity of the housing, and as something different to most new housing schemes, where ideas of community, 224 civility and interaction between neighbours are lost. It was hoped that the interaction in the garden areas would create a link between residents so that they’d at least look out for their neighbours and try to find out a little bit about them, so for example if they were away a neighbour would look after their property.

The scheme aimed to keep as many trees as possible and plant more, but balanced with the requirements of parking on the streets, in addition to parking under the raised gardens. Existing trees were growing in ‘build outs’ from the pavement, and new trees were planted in these to replace removed trees, although this was not done symmetrically. However, many of the smaller retained trees were planted within tree guards, while new trees were not. The streets were remodelled with further build outs at the top and bottom of each street, though not all have been planted with trees. A comparison of the public streetscape and the private garden area of Chimney Pot Park (Figure 7.7 below) showed the distinct differences between public and private greenery.

Figure 7.7. The communal garden areas (left) and roads (right) of Chimney Pot Park.

In comparison to the fairly bare streets of Chimney Pot Park, existing non-regenerated residential streets near Chimney Pot Park have been greened. Existing street trees have been retained, and pot plants and hanging baskets placed outside homes to increase the greenery on the street (left of Figure 7.8). Some residents have even placed benches outside in order to enjoy the greenery. Alleygating has taken place on these streets, and these have also been greened by residents (right of Figure 7.8). This planting is not as lush as the planting of the gardens of Chimney Pot Park, but the streetscape is more welcoming. This is an example of a different way Chimney pot Park may have been greened.

225

Figure 7.8. A neighbouring street to Chimney Pot Park, where street greening and alleygating has taken place.

The developer admits that when interacting with the Chimney Pot Park area on foot it feels less welcoming than the nearby streets with street greening, and that it is a shame that the lush feeling of the decking areas is not available to people visiting the area. If Urban Splash had been more conservative in their regeneration plans, it is likely that a scheme similar to this would have been put in place, but as the scheme was much more ambitious the greenery has been shifted into private rather than public view.

7.5.3 Grove Village

The road layout was significantly altered for this scheme, therefore many street trees were lost as roads were moved and remodelled. The original design intended a Green Route to run through the centre of the development, improving permeability of the estate and allowing pedestrians to find their way more easily. This route was bulldozed through the existing roads, housing and trees and incorporated three new neighbourhood parks and play areas. The Green Route was originally intended to be a new, tree-lined avenue with traffic calming methods giving pedestrians priority. It was designed as a potential homezone, and much of this design has made it to construction. Parking was arranged in an informal manner with trees and other street furniture forming demarcation of a carriageway without upstand kerbs (see Figure 7.9). It was intended to be constructed of completely different materials to the rest of the roads to make it visibly a safe pedestrian 226 and cycling route. However, ‘Value Engineering’ (using cheaper materials to decrease costs) by the constructor meant that the Green Route is made of the same materials as the other roads, and is a clear vehicle-way and not shared with pedestrians. Additional regulations from the Highways Department to decrease vehicle permeability and routes directly through the estate also meant the Green Route could not be vehicle free. Due to this and due to restrictions on the placement of trees, the architect now feels it may be described more as a green transport route for walking rather than a green vegetated route.

Figure 7.9. A section of the Green Route in Grove Village, showing the flat kerbs, trees and bollards that separate the pavement from the parking area.

None of the existing trees in Grove Village had Tree Preservation Orders on them, so tree health was assessed and dying/diseased trees removed. Most roadside trees away from the Green Route were kept, and all trees on the Green Route were removed to allow the new road layout to go ahead.

The architect felt that the implementation of all of the intended planting scheme was hampered by the location of a plethora of underground services, including high voltage cables linking two sub stations along the green route, which prevented some tree planting. The implementation of the new street lighting layout was also a barrier to planting, and

227 the degree of value engineering (cost cutting) by the developer created barriers for the planned Green Route.

7.5.4 The Use of Greenery in Developments

Both the developer from Urban Splash and the landscape architect from PRP Architects were asked about the use of greenspace in developments more generally.

The landscape architect at PRP felt that the external environment is quite poorly funded in regeneration schemes, but that it is difficult to improve this. They found that Manchester City Council have been proactive in pushing for higher quality public realm, and the experience of Grove Village, an early PFI, has encouraged this higher consideration for the public realm. The problem of value engineering by the developers, leading to a compromised architectural design and a poorer public realm is also an issue during redevelopment.

Urban Splash have been involved in another scheme in Ancoats, Manchester, where poor housing and low housing demand have led to the depopulation of an inner city estate. This area is undergoing regeneration, with nearly 1000 new homes built. It was felt that with this many new homes being built residents should have access to good quality green spaces and parks. As part of the plan orchards, water gardens and shared parks have been built for residents, and will be opened to the public in the future. The developer felt that greening a regeneration area must be approached on a case by case basis; Chimney Pot Park was an area of good potential for private greening, while the Ancoats scheme, with more land, gave opportunities for public greening. The problems of implementing a design from the drawing board to the ground were highlighted, whether the greenspace is a visual amenity or an area of social space. Greenspace of any kind was seen as very important in a scheme; a building should address the street with some greenery but also have a ‘secret garden’ in the private space. Landscape is a key ingredient in any scheme, especially regeneration, helping with placemaking and giving communities a place to meet and to develop.

7.5.5 Discussion

The uneven planting scheme in Chimney Pot Park suggested that public realm planting was a low priority for the scheme. The developer indicated that the priority for this

228 scheme was to improve the housing stock and plant private and communal gardens, in order to help interaction between residents and foster a sense of community, and not specifically to improve the public realm. Nearby improvements to the public realm by the council and residents demonstrated the extent to which greenery may be used to make similar streets more welcoming, but none of this was used in the Chimney Pot Park project. It is possible that as residents become more settled in the development they will contact the council to have a similar scheme on their street. This could be influenced by residents wishing to transfer the lush feel of the garden areas to their street.

The problems of the Green Route in Grove Village showed the difficulties in getting a design from the architects into reality. The intervention of the highways department meant that the overall development was less permeable for traffic with fewer through routes. The constructors used the same materials for the Green Route as other roads, so in practice the route is not distinct. The Green Route was designed for pedestrians and cyclists to have priority over vehicles, but this has not happened due to the value engineering of the constructor. However, many aspects of the Green Route were kept and made the route more assessable for pedestrians and cyclists, including flat kerbs and fairly wide pavements, with traffic kept off pavements with bollards (see Figure 7.6). The presence of underground services hampered the implementation of the architects’ design; this suggests that before greenery is designed, a full survey of the development site, including underground services, should be obtained.

It is encouraging that developers and architects are keen for their developments to contain greenery and to look at different ways of achieving this. One interesting point with the two cases studies here is that they were both in areas of low housing demand, which through regeneration and the reworking of greenspace and vegetation have become areas where people want to live. In objective 3, residents overwhelmingly stated that if they were to move, they would probably or definitely try move to a street with trees. Therefore, it may be suggested that in addition to the refitting of the homes, the improvement to greenery and vegetation also made a difference to the desirability of these new homes.

229 7.6 Summary and Conclusions

This chapter has explored the issues affecting urban trees and the prospects for increasing tree cover from the perspective of practitioners and through examining a small number of case studies. It has examined the possible relationships between policy, developer attitudes and presence of community greening schemes identified in the Conceptual Framework of Section 3.1.1. The results of this chapter were: • practitioners were reasonably positive about the future of urban trees, aided by recent research about their benefits in urban areas; • practitioners suggested a range of improvements to planning regulations, legislation and funding schemes to help protect urban trees and encourage their planting and maintenance; • small streets (around 25 houses) participating in a Green Streets scheme were more likely to plant close to the maximum potential number of trees than larger streets (50 or more houses); • more trees were planted than were removed in the two regeneration case studies, but far less than in the Green Streets areas. The trees were not planted in the same way as the trees removed however, so it is unclear whether the new trees will be able to grow in a similar way and reach a similar size to those removed; • uptake of Green Streets schemes were not affected by deprivation levels, housing type or local environment, but uptake was significantly higher where a Green Street Champion was active; • greenery in one regeneration scheme was used to create private and communal space where neighbours may interact and encourage a sense of community. In the other regeneration scheme studied, greenery and different surfaces were intended to create a Green Route for shared use between pedestrians, cars and cyclists, though this was compromised through cost cutting by the developer.

The results show that practitioners remain positive about the future for urban trees, despite potential and actual barriers to their planting and maintenance, particularly funding cuts. Their recommendations are explored more fully in Chapter 9. The results show how successful a community based tree planting project can be, planting close to the potential maximum number of trees calculated in Chapter 5, suggesting that this style of project will be best to increase tree cover in urban areas in the future. The regeneration schemes show a growing awareness by developers that a green environment is desirable for residential developments, although investment in urban greenspace may be

230 vulnerable to funding cuts and cost saving as schemes are implemented. A consideration of high density housing layouts allowing high numbers of trees, shown in Chapter 4, should be considered in the future by developers to give the maximum number of trees in a development.

The results of this chapter suggest that a relationship does exist between the attitudes of developers and the presence of a community greening scheme. These may be added to the Conceptual Framework in Section 9.1.1. However, the research into policy was inconclusive; further work is needed to fully explore any relationships between policy and urban tree distribution. From the large number of changes and improvements to policy suggested by those at the workshop, it may be hypothesised that current policies are ineffective at protecting and increasing urban tree cover.

231 Chapter 8 – Discussion

8.1 Introduction

Chapter 2, the literature review, identified a range of factors which previous researchers have suggested affect the distribution of trees in urban areas. This chapter presents the findings of the thesis, given in chapters 4 to 7, within this wider research context. Section 8.2 highlights the factors affecting the distribution of urban trees identified in this research and links them to existing literature. Section 8.3 summarises the benefits of urban trees, as calculated in Chapter 5, with reference to published literature on the effects of trees on temperature and rainfall runoff. Section 8.4 describes the potential factors for protecting and increasing urban tree cover, using the findings of all chapters and relating them to published studies. The chapter concludes with a summing up of the results of this study and the results of published studies to present an up to date view of the research area.

8.2 Factors Affecting the Distribution of Urban Trees

The literature review identified a number of factors which could affect the distribution of urban trees. This section examines the results of this thesis in a context of the literature.

8.2.1 Socioeconomic Factors Affecting the Distribution of Urban Trees

The influence of socioeconomic factors on tree cover has not been addressed in this thesis, unlike many other studies of urban tree cover. This is because the different types of housing are found in small contiguous areas within each area of similar deprivation, to which it would be very difficult to accurately assign socioeconomic attributes. Lower layer super output areas, a type of small census district with a minimum population of 1000 people, give the most geographically accurate demographics of an area, but very few contain only high density housing, and of those even fewer contain just one type of high density housing. This is a reflection of both the large amount of infill (re)development in the study area and the generally small scale of housing estates in the UK. Figure 8.1 below demonstrates the variability of high density housing in a small geographical area. The data in this thesis has shown that in Greater Manchester housing type is hugely responsible for the amount of tree cover in an area; further research would

232 be needed to clarify the relationship, if any, between tree cover, housing type and deprivation levels.

800m

Figure 8.1. Map demonstrating the variability of housing type in a small geographical area (2860m by 1880m, 538ha) in Langworthy, Salford. The black lines are lower layer super output areas, and the different coloured polygons are differing housing types. Scale bar is 800 metres.

8.2.2 The Effects of Housing Layout on the Distribution of Urban Trees

This thesis has shown that there are 11 clearly defined types of high density housing within the study area of Greater Manchester. The results are consistent with a historical view of Greater Manchester, with older, higher density housing in areas of early industrial activity, some of which was demolished for slum clearances and rebuilt in the 1950s and 1960s; these two ages of housing made up the vast majority of high density housing. The classification is robust and may be used by other researchers in other UK cities to classify their housing, potentially with local additions or exclusions. The final housing typologies are relatively similar to those found by Brown and Steadman (1991) in the much less industrial city of Cambridge, UK, suggesting that although the classification has not been tested in other cities, it is highly likely that many, or all, of the housing types are present in other cities in the UK. This is mainly due to the influence of nationwide legislation and general housing trends on the housing in Greater Manchester, which will be seen in other cities. The classification is unlikely to be able to be directly used in other countries, as UK housing is unique, although the combined approach of historical study and site visits may be used to inform a similar classification.

233 As stated in the literature review, there is very little published research exploring different types of housing morphology, particularly in the UK, so it is difficult to put the findings of this thesis into a wider research context.

8.2.3 Attitudes and Awareness of Residents about Urban Trees

The results in this thesis have shown that all respondents to the survey were very positive about urban trees, regardless of the type of street they lived on and any socioeconomic variables. Small variations existed between streets, but this was only in the strength of agreement or disagreement. The overall results are very comparable with Lohr et al.’s (2004) findings in the USA that all respondents were very positive about trees. Respondents in the UK rated benefits more highly and problems less highly than respondents in the USA, but overall there were little differences in the responses.

The aesthetic improvements trees give to a street, making it look nicer and feel friendlier, were the highest rated benefits by respondents who lived in streets with trees in this study. This has been found by other researchers in New Zealand (Vesely, 2007) and in the USA, where shading effects are also highly valued (Sheets and Manzer, 1991; Flowers and Gerhold, 2000; Gorman, 2004; Lohr et al., 2004; Schroeder et al., 2006; Zhang et al., 2007). Sheets and Manzer (1991) found that people looking at pictures of tree-lined urban streets felt friendlier, more co-operative, less sad and less depressed, although they did not rate tree-lined streets as more attractive than non tree-lined streets. This difference was not seen in this or other studies; this may be due to differences in wording or experimental design, or respondents considering other factors more important in rating the attractiveness of a street.

Interestingly, members of the British community in Toronto, Canada, expressed a much stronger preference for shade trees than other respondents of the Chinese, Italian and Portuguese communities (Fraser and Kenney, 2000).They also expressed a preference for trees in front of their homes in order to increase privacy. This suggests that in warmer climates shade trees are preferred by British people, and the added benefits of privacy are also liked; therefore as temperatures increase in the UK, preference for shade trees could increase. The issue of trees blocking sunshine into people’s homes was not seen as a problem by respondents surveyed for this thesis, perhaps because in the cool, cloudy climate of Greater Manchester it is rarely sunny enough for trees to cast significant shade. Privacy was not asked about in this survey, although the reasonable number of hedges in

234 front of people’s homes seen when ‘doorknocking’ does suggest that privacy is important to residents, and hedges are chosen rather than single trees. Woody shrubs or dwarf trees were generally used, which suggests that greening may be achieved by offering or encouraging hedge planting for privacy reasons.

A study in tree-less streets in Ayr, Scotland, UK, found that most respondents did not see trees as important in improving the quality of their street and rated 'no litter', 'improved street lighting' and 'improved pedestrian and vehicular surfaces' as more desirable improvements than trees (Hitchmough and Bonugli, 1997). This is directly opposite to the findings of this thesis, where ‘more/better trees and flowers’ was rated as the most desired improvement overall, and significantly more respondents in tree-less streets stated that the planting of trees and flowers would improve their street than those in streets with trees. Hitchmough and Bonugli (1997) found an association between less deprived streets and more support for trees to improve their street, but generally the presence of trees and vegetation was not seen as a factor in making a street a good place to live. This is unlike many other studies (e.g. Sheets and Mazer 1991; Zhang et al., 2007) and also unlike the results found in this thesis, where respondents strongly agreed that the presence of trees was important to their quality of life, trees and greenery would improve their street and they would probably or definitely try to move to a street with trees in the future. It is difficult to suggest reasons for these differences. Hitchmough and Bonugli (1997) compared their results in Ayr to work in the USA, where higher temperatures and more sunshine give a need for cooling and shading by trees, while their study area was usually cool and windy and would not need tree shade; the authors suggested that respondents had less need for the benefits of tree shade and would prefer other street improvements with more useful benefits. The study area in this thesis has a similar climate to Hitchmough and Bonugli’s (1997) study area, so again shade from high temperatures and sunshine is unlikely to be a pressing need, yet respondents highly rated trees and wanted them in their street. Manchester is a much more urbanised area than Ayr and distant from areas of countryside and coast; the positive attitudes and desire for street trees of the Manchester respondents may be due to a feeling of ‘remoteness’ from the countryside and nature, and a feeling of wanting greenery in their street. Residents of Ayr are close to the coast and large areas of countryside, so it is unlikely they feel distant from nature and therefore perhaps do not feel a need to have trees and wildlife directly outside their home. The increase in support for trees seen in respondents in Manchester may also be due to an increasing awareness of the other benefits of trees, such as taking in carbon, therefore reducing carbon emissions and the threat of climate change, or

235 reducing pollution, or providing space for wildlife and increasing biodiversity. This study was taken over ten years after Hitchmough and Bonugli’s (1997), in which time awareness of climate change, biodiversity loss, pollution problems and other environmental issues has increased greatly. This may go some way to explaining the differences in opinions, in addition to considerations of the location of the studies.

Hitchmough and Bonugli (1997) found that respondents did not want trees planted in their street as they felt trees would be vandalised and therefore be a waste of money, that leaves would become a litter problem and that trees and roots would damage walls and buildings. Conversely, in this study, just one person (2.3%) in a ‘No Trees’ street stated that they thought trees would be vandalised if they were planted, with issues of space for trees and council financial concerns rated as the most likely reasons why their street did not have trees. Trees increasing litter was not seen as a reason to not plant trees in urban areas in this study, and the cost of trees to the council was seen as the least important reason to not plant trees. Again, this is opposite to Hitchmough and Bonugli (1997), and reasons are not clear why this occurred. However, respondents’ concern about tree root damage to housing and walls was apparent in both studies, even though this is very unlikely in the north of the UK. Hitchmough and Bonugli (1997) point out this is most common in southern parts of the country, where shrinkable clay soil, high transpiration rates and large precipitation deficits (where the soil dries out faster than rain falls to replenish the soil moisture (Biddle, 1981)), coincide to dry out the soil and lead to soil movement, whereas in cool, damp Scotland this is very unlikely. Building foundations built on this shrinkable clay soil can be damaged as tree roots take up water and dry out the clay, which then differentially shrinks and can cause structural damage to the whole building (Biddle, 1981). The south east of the UK is most at risk from this type of root damage, as much of the soil is London clay, which is shrinkable. The north west of England and all of Scotland rarely experience these precipitation deficits, so this type of root damage is not an issue. However, as temperatures increase and rainfall patterns change due to climate change, the areas at risk of shrinkable clay soil damage due to tree roots could increase.

All respondents in this thesis disagreed on a similar scale about possible reasons to not plant trees in urban areas, except for the problem of some species of tree dripping sap onto the ground. The statement ‘Trees should not be planted along streets because they drip sap or sticky substances on parked cars’ was disagreed with by residents in ‘Trees’ streets, while other respondents strongly disagreed with it. Schroeder et al. (2006) found

236 that this was also a high annoyance for respondents in the south west of England, UK, while for US residents it was seen as much less of a problem. The authors stated that this is likely to be due to the differing layout of residential streets; in the UK, streets are fairly narrow with trees close to homes, while in the US streets are wider and trees are further away from homes. Much car parking is on street in the UK, underneath street trees, unlike in the USA. Therefore, any sap dripping from trees onto the street will be much more noticeable in the UK, as cars tend to be parked in the street; therefore the more highly rated annoyance of this aspect of trees in the UK is not surprising.

Overall, UK residents rated benefits more highly and annoyances as more of a problem than US residents in two comparative studies (Schroder et al., 2006; Section 6.5). This suggests that the differing layout of homes between the UK and the US, with street trees much closer to homes in the UK than the US, is likely to be a large factor in the differences in opinions about street trees between the two countries. For UK residents, benefits and annoyances are closer and therefore more apparent, so the higher ratings of both are not surprising.

This research found that, overall, the majority of respondents do not think that house prices are affected by the presence or absence of trees. A minority of respondents thought that trees could increase house prices. This is despite the vast majority of respondents stating that they would probably or definitely try to move to a street with trees in the future. This finding is confusing; respondents would preferentially move to a street with trees but do not associate their desire for a home with pleasant surroundings with an increase in the price of a home due to its surroundings. It is possible that respondents in this study want to move to a street with trees but would not pay for the privilege. This unexpected difference has been seen by other researchers. Orland et al. (1992) found that respondents shown photos of recently sold homes could judge their selling price reasonably accurately, and that the addition of trees around the home increased the respondent’s valuation of the home. However, there was no clear correlation between respondents’ perception of the attractiveness of a house and the value of the home, even when extra trees were added to the garden. Therefore, even though the house became more attractive to the respondent, they did not increase its value. Sheets and Manzer (1991) found that people looking at pictures of tree-lined urban streets rated the area as a better, safer, cleaner place to live than pictures of non vegetated streets. This would suggest that people would pay more to live in these homes, but this does not seem to be the case. However, studies of actual house selling price does show that tree cover

237 increases a house’s selling price (Tyrvainen, 1997; Payton et al., 2008) up to a defined level of tree cover (Netusil et al., 2010,), and tree cover in the neighbourhood can increase selling prices by up to 2.52% (Netusil et al., 2010) over a neighbourhood of around 11 acres (Payton et al., 2008). Research of house prices around parks also shows that house selling prices increase with proximity to a well kept green space (CABE Space, 2005). This research suggests that people do value trees around homes and will pay more for this. Therefore, the results in this thesis are difficult to explain.

8.3 The Benefits of Trees in Urban Areas

The literature review demonstrated a range of benefits of trees in urban areas. Two of these benefits were studied as part of this thesis, and a discussion of these results in a wider research context is given below.

8.3.1 Increasing Tree Cover and Maximum Surface Temperatures

The planting experiment detailed in chapter 5 showed that tree cover may be theoretically increased by between 5% and 10.5% in differing housing types, giving a total of between 9.15% and 21.04% tree cover; an average of 14% across all housing types. This gave the largest reduction in maximum surface temperatures in areas where existing tree cover was less than 4%, reducing maximum surface temperatures by as much as 4.5°C. In areas where existing tree cover was over 4%, increasing tree cover did not make such a large difference to maximum surface temperatures, reducing them by around 1°C. However, the model did not address direct shading and human comfort effects, which are likely to make areas with more tree cover and shading feel more pleasant. This therefore is a strong argument in favour of using trees to cool urban areas, particularly trees with a large canopy and large shading effects; these should, where possible, preferentially be used over other greening methods such as green walls and roofs.

Just one housing type showed the potential to increase tree cover by over 10%. If increasing overall vegetation cover by 10% in order to mitigate increases in temperature due to climate change (Gill et al., 2007) is a priority, then ways of achieving this with more than tree planting must be addressed. Other ways of greening urban areas can be through window boxes and potted outdoor plants, as seen in nearby streets to the Chimney Pot Park regeneration project in chapter 7. Green walls of ivy and other climbing plants such as honeysuckle or jasmine may be used to both cool the building 238 and reflect heat to ensure the street does not become too warm. Climbing plants may also be planted around lampposts and signs, with regular maintenance to ensure they do not obstruct the object. Green roofs may also be used to insulate homes in winter and prevent excessive solar heating in summer, although the steep roofs of many of the high density housing types may not be suitable for such greening.

8.3.2 Trees and Rainfall Runoff

Increasing tree cover made only small reductions in rainfall runoff; in an extreme rainfall event of 18mm a maximum of 6.2% reduction in runoff was seen in the most build up housing type, pre 1919 onto road terraced housing, in the driest scenario. This is surprising, as trees have been shown to reduce stormwater runoff dramatically across urban areas (Anon., 2000; Stovin et al., 2008). However, it is understandable that a very localised model in areas of high impervious surface covers would give small reductions in stormwater runoff, while a model encompassing a whole urban area with lower density housing and parkland, would give more significant reductions. The model suggests that if reducing flood risk becomes a priority in high density housing areas, methods other than tree planting should be considered. Water will need to be channelled away from high density housing towards areas where water may be absorbed into the soil, perhaps into remnant greenspaces planted up with trees, where trees may intercept high levels of rainfall and use water for transpiration (Kjelgren and Montague, 1998; King and Harrison, 1998; Xiao et al., 2000; Samba et al., 2001; Gomez et al., 2001; David et al., 2006; Guevara-Escobar et al., 2007; Bartens et al., 2009).

8.4 Potential Factors for Protecting and Increasing Urban Tree Cover

The literature review identified a number of factors which may aid the protection of existing trees and the planting of more trees. The following section discusses the results of chapter 5, which determined a potential maximum amount of increase in tree cover for each housing type and how this relates to existing research. Barriers and opportunities for increasing tree cover, as explored in chapter 7, are also discussed here.

8.4.1 Existing and Potential Tree Cover in Different Housing Types

This thesis has shown that tree cover varied significantly between different types of high density housing. Although many studies have shown that tree number and cover is lower 239 in high density housing areas (e.g. Land Use Consultants, 1993; Handley et al., 2000; Gill, 2006; Tame 2006; Tratalos et al., 2007; Britt et al., 2008; Davies et al., 2008), no published study has, to the researcher’s knowledge, looked at the differences within areas of high density housing. Therefore it is very difficult to say how this research relates to existing research. Comparable figures exist for high density housing as a single category: Britt et al.’s (2008) average figure for tree cover in high density housing areas across the UK was 3.6%, Gill (2006) calculated an average of 7% tree cover across the whole of Greater Manchester, while the average figure for the study area in this thesis was 6.64% (calculated in chapter 4). Comparisons with Handley et al. (2000) and Tame (2006) were not possible as tree number, rather than canopy cover, was calculated in these studies. The average tree cover found by this thesis and by Gill (2006) for Greater Manchester is nearly twice the national average, suggesting that tree cover in high density housing areas in Greater Manchester is comparatively high. However, the average masks the low (under 3%) tree cover of pre 1919 terraced housing, which made up 43.8% of the housing in study area, showing that large areas of high density housing will have very low tree cover, lower than the national average (Britt et al., 2008). It is probable that Britt et al.’s (2008) average also masks large differences in tree cover. The highest tree cover in this thesis was found in 1960s walkway housing, pre 1919 semi-detached housing and 1919-1959 semi-detached housing, which, when combined, cover just 18.2% of the study area. This shows that although there were areas of high density housing where tree cover was relatively high, this was not common, and most (81.8%) of the total area of high density housing had less than the average tree cover.

Few studies have analysed the potential for tree planting in urban areas, so it is difficult to compare the results found here with the literature. Kirnbauer et al. (2009) developed a computer model to aid planning of tree planting in Canada, with a pilot study in two long streets in Hamilton, Ontario, Canada. The model analysed both the space available for planting (above and below ground) and the biotic and abiotic factors of the site in question, and gave appropriate planting area and species for the study area. Local authority guidance and best management practices compiled from across the USA and Canada were used to determine optimum tree planting sites for energy conservation, reducing the urban heat island effect, maximising passive solar gain, channelling summer breezes into homes for natural cooling and directing winter winds up and over structures to reduce heating loads. A guidance document was also developed to accompany these aspects of the model (Kirnbauer et al., 2009). Currently, the UK does not plant trees with regard to any of these considerations, so no comparable guidance is available which may

240 have informed the research in this thesis. As temperatures in the UK increase due to climate change, and energy bills rise, it would be highly recommended for both householders and local authorities to study these guidelines when planting trees to maximise their benefits. This would give a strategic increase in tree cover, rather than a general increase in tree cover, and its implications would need to be considered in any tree planting strategies.

A study in Los Angeles, USA, using a ‘trained’ computer program, found that an additional 12.4% of vegetated surfaces could be covered by trees than actually were (McPherson et al., 2008; Wu et al., 2008). However, the authors warn that planting in every potential site is unrealistic, and that a target of planting in 50% of target sites should be set for the city, increasing tree cover by 6.2%. Just 15% of potential sites were in medium/high density housing, with 14% of trees actually planted in these sites (McPherson et al., 2008). This would increase tree cover in medium/high density housing by 8.4%, on top of the existing 14.5% tree cover to give a total of 22.9% tree cover (Wu et al., 2008). One of the aims of the report was to distribute trees equitably across the study area, which explains the high proportion of potential sites that would be planted with trees. The levels of existing and potential tree cover found by these two Los Angeles studies was much higher than the average 6.64% existing tree cover, 7.3% increase and 14% potential total tree cover found by this thesis (Chapter 5). This difference is likely to be mainly due to the combining of medium and high density housing by the researchers, as well as the lower density of all housing in the USA and the differences in housing layout. Other differences include the much higher need and appreciation of tree shading in the hot climate of Los Angeles compared to the cool climate of Greater Manchester, UK, so homeowners would be more likely to plant trees to shade their property.

Interestingly, the same Los Angeles study found that 14.3% of medium/high density housing was vegetated space (McPherson et al., 2008) while this thesis found a slightly higher average of 17.47% vegetated space in high density housing. However, tree cover could be increased by a larger amount in Los Angeles than in this thesis’ study area of Greater Manchester, despite the higher percentage of plantable space. In the study area, much of this plantable space was found in small, non continuous patches, which may not be large enough for trees to be planted. Therefore, the higher percentage of tree cover increase in Los Angeles is likely to be due to the presence of larger strips of land where many trees could be planted. This low amount of easily planted space in Greater Manchester, coupled with the success of programmes such as the Green Streets projects,

241 is why, unlike McPherson et al. (2008), the potential tree planting study in this thesis included impervious surfaces.

Unlike Kirnbauer et al.’s (2009) study, the potential tree planting sites in this thesis were not subject to analysis of underground services, and unlike McPherson et al.’s (2008) study a realistic amount of tree planting into potential sites has not been calculated. A realistic figure for number of trees planted should take into account funding limitations, resident support or opposition and issues of pavement space, underground space available for the tree pit and space available for parking. It is unlikely that all of these considerations will be favourable for every potential tree planting site, so a realistic figure for tree planting will be lower than the potential figure. Therefore, the potential tree cover for high density housing types in Greater Manchester will realistically be lower, perhaps much lower, than the figures presented in chapter 5 of this thesis. Data regarding underground services in the UK is very difficult to obtain from the privatised utility companies and it would therefore be impossible for this thesis to incorporate into a simple estimate of tree planting potential. Issues of lamppost siting and minimum pavement width were also not incorporated into the tree planting exercise, as these may be changed if project cost is unlimited. These limitations suggest that actual tree cover is very unlikely to reach the maximum potential increase in tree cover, perhaps even as low as the 50% of potential tree cover suggested by McPherson et al. (2008) and seen in the large scale Green Streets project in Thornton and Horton Roads in Chapter 7. However, some Green Streets projects can reach 85% of potential sites planted, suggesting that with the right approaches tree cover can be increased to very near the potential maximum.

8.4.2 Effects of Municipal Regulations

Many participants at the workshop expressed a wish for stronger legal protection for urban trees and higher penalties for people who cut down or damage trees protected by Tree Preservation Orders (TPOs). It was felt that the law is too relaxed at the moment and penalties are not high enough to deter residents and developers from cutting down trees. In Atlanta, Georgia, USA, Hill et al. (2010) found that strong tree planting and protection regulations helped increase tree cover over a ten year period. The regulations were as follows: establishment of ‘tree banks’ or alternative compliance [where money is given to fund tree planting elsewhere]; site requirements during development, such as specification of tree preservation areas, allowances on tree removal, landscape plans, or tree replacement; requirement of a tree removal permit for previously developed private

242 land; requirement of a tree removal permit for new development; buffer requirements for root zone protection during development; adherence to protect exceptional trees during development (i.e. specimen and historic tree protection) [similar to a Tree Preservation Order]; allowance for tree unit credits or replacement fees of no less than 100% the costs of the tree removed; requirement of street trees (i.e. street lining, minimum quantities, and species requirements); parking lot requirements (i.e. islands, trees per space, and percent of parking lot dedicated to tree requirements). For the presence, and presumed enforcement, of a single one of these laws, Hill et al. (2010) calculated that there was a 1.03% increase in tree cover over a decade.

The laws cited in Hill et al. (2010) do not have any equivalents in the UK, where any tree may be felled if it is not protected by a TPO or within a Housing Conservation Area, and even if it is an application may be made for its felling. The ability for developers to pay into a tree planting scheme or pay for other community benefits does exist in the UK (see Section 106 Agreements in section 7.1.1), but this is at the discretion of the local planning authority. Other aspects of street tree planting exist as local guidelines, not legal requirements, and there is no legal requirement for vegetation in parking areas. These regulations may be added into UK law and could make a big difference to the amount of tree cover in urban areas. These laws may be made nationally or as local regulations. National regulations are preferable as all local authorities must comply with them, and good practice may easily be disseminated across the country. It is also preferable, as developers could not threaten to move lucrative developments to a neighbouring authority because of disagreements about the number of trees to be kept or planted or the amount of money donated to a tree care fund, as it would be the same for all authorities. Until national legislation is developed and passed, local authorities will have to rely on the inventiveness and influence of tree professionals in ensuring that trees are protected in developments, that more trees are planted and that money is taken from developers to specifically fund tree planting and maintenance.

A similar study in Tampa, Florida, USA (Landry and Pu, 2010), found that although the tree regulations were not as detailed as in Atlanta, Georgia (Hill et al., 2010) they still contributed to a significant increase in tree cover in the area since the regulations were introduced. In Tampa a permit was required for removal of any tree greater than 15cm diameter (measured at 0.9m above ground) located on private land, for trimming any branch greater than 10cm diameter or for removal of any size tree located within a public right-of-way. Criteria for removal were limited to trees that posed a safety hazard, trees

243 that prevented the development or use of a parcel, and diseased or damaged trees. A landscape master plan documenting the location of all trees greater than 15cm diameter was required for development of residential land larger than one acre, and removal was limited to no more than 30% of trees. Compliance was enforced by a multi-stakeholder board established to review tree removal permits under the guidelines of the ordinances. Although there were fewer regulations, the enforcement process appeared clearer than in Atlanta. Again, these laws could easily be adapted for use in the UK; indeed, the workshop run as part of this thesis suggested some sort of mandatory protection for all trees over a certain size would be very helpful in retaining tree cover and would be easier in practice than TPOs. Protection for trees over a certain circumference is already the case in many European cities, particularly German cities, while in Paris, Lyon, Marseilles, Budapest, Florence and Milan all urban trees are protected from felling (Schmeid and Pillmann, 2003).

The importance of enforcement to protect urban trees is shown by Jim and Liu (2000) in China, where all land is owned by the state. The study found that despite high protection for trees and urban greenspaces, they are commonly felled and built on, particularly by various parts of the state. This disregard for the law by governmental departments means that enforcement of the law does not happen, and trees are effectively not protected from harm. While this does not happen in the UK, it does demonstrate the importance of enforcement and the importance of governmental bodies applying the same rules to their own development plans as others.

8.4.3 Effects of Municipal Practice

The workshop highlighted problems of lack of communication between different departments working on urban tree issues. Konijnendijk (2004) found that the development and strengthening of links between many different stakeholders, including community and professional groups and researchers, as well as a close relationship with policymakers, was seen as an essential way to increase the success of urban forestry and to ensure that the benefits of trees are well known and available to all people. Therefore, improving communication between all groups who work to plant and protect urban trees would be of great benefit. Sipila and Tyrvainen (2005) found that in Helsinki, Finland, participants in a collaborative, participatory planning approach to local urban forest areas felt that the participatory approach prevented conflicts in planning and increased residents' awareness of matters concerning green areas, and most respondents were

244 satisfied with this system of consultation. Although this method can be time consuming and expensive, having resident support and letting them know about changes in their nearby urban forest, including street trees, was seen as important by some in the workshop. The initial resistance of some groups to partnership working, due to the large amount of time needed to properly co-ordinate the Los Angeles Million Tree Initiative, was noted by Pincetl (2010), but the project has eventually become a success despite the added complexities of partnership working and multiple sources of funding required. In Chicago, USA, there are many different groups working to purchase, plant and protect urban greenspaces in the city; Ruliffson et al. (2002) found this diversity of groups working at different levels and/or in partnership was very strong and successful at achieving their aims of increasing green infrastructure. Many good examples of partnership working can be found in the UK, such as community forests (including the Red Rose Forest) and the Tree Council working with residents’ groups and local authorities to protect and increase tree cover, and the Trees and Design Action Group and Trees for Cities linking tree officers and policy developers to share and develop polices and good practice guidance. The research shows that good partnership working can greatly help urban tree planting and care schemes, and better communication and partnership working should be encouraged in order to help protect and increase tree cover.

The workshop highlighted the importance of every local authority having a Tree and Woodlands Strategy, in order to guide investment and funding bids, to influence planning applications and polices and to demonstrate the value of trees to the local area and residents. Appleyard (2000) looked at the planting regime and strategy for planting trees in high density housing areas. He found that for high levels of tree establishment and growth it was essential to have a clear, carefully constructed strategy, applied from the very first planning meeting to aftercare and maintenance. Resident consultation and support for tree planting was also seen as important. This paper strongly emphasises the importance of a Tree Strategy and Planting Strategy, which supports the views of the workshop attendees.

8.4.4 Raising Money for Tree Planting and Maintenance

One great issue for the urban forest and street trees in particular is the issue of funding for planting and maintenance. A number of studies have shown that residents are very willing to pay small sums to ensure that trees and vegetation are taken care of around their homes. In Marion County, Indiana, USA, households are willing to pay between

245 $15 and $92 annually for a permanent 1% countywide increase in denser, healthier urban forests. The total value is between $3.1 million and $19.2 million if those values hold for the entire owner-occupied housing stock (Payton et al., 2008). In New Zealand, households would pay an average of 184NZD a year to prevent a 20% reduction in trees around their home, with half of respondents paying more that 105NZD and half paying less (Vesely, 2007). When asked to volunteer time to care for trees rather than donate money 66% of the sample agreed to contribute 4 hours of volunteer work a year and 55% of those who did not want to pay would instead give their time (Vesely, 2007). In Finland, more than two-thirds of study respondents were willing to pay for the use of recreation areas; good location and active management raised the average willingness-to-pay, and around half of the respondents were willing to pay for preventing construction in urban forests (Tyrvainen, 2001). Encouragingly, Tyrvainen’s (2001) study showed that the monetary value of amenity benefits in recreation areas is much higher than the present maintenance costs, suggesting an easily sustained amount of recreational area could be kept free from construction. Although willingness to pay or volunteer to help and protect trees was not asked about in the survey part of this thesis, the evidence of maintenance and care of trees was seen when ‘doorknocking’ in areas of Green Streets trees, with plants planted in the tree pits, and lots of anecdotal evidence from the Green Streets team. Therefore, willingness to donate time seems more likely in the survey sample, particularly as Zhang et al. (2007) found that less educated respondents were less likely to be willing to pay for the upkeep of the urban forest, and the majority (73.7%) of this survey’s respondents had only A-levels or less. Direct taxation from residents, either into a neighbourhood pot of money or ringfenced through council tax, was suggested in the workshop, and the studies cited above suggest that there would be support for this, although less support in the area of the survey. Therefore, money or time contribution could be offered. One workshop suggestion was that volunteer time clearing leaves or watering trees for example could be rewarded with council tax discounts. Other schemes suggested a levy through the use of recreational facilities or car parking; although there are no studies exploring the support for this, workshop attendees generally thought this would be possible and supported by residents.

At the workshop, a very popular potential revenue scheme for the urban forest was the use of cuttings and felled trees as a source of biomass for fuel and energy generation. MacFarlane (2009) studied the potential uses of urban timber in Michigan, USA (slightly larger than the UK) and found the annual yields of wood biomass just from dead and dying urban trees described were the equivalent in energy content to between 1.2 and 1.7

246 million barrels of oil per year, or the equivalent of one 97.5MW power plant. In Portugal, an assessment of the amount of forest cuttings available as biomass calculated that using biomass-powered combined heat and power stations, 45% of the country’s energy demand could be met (Viana et al., 2010). In the UK, Britt et al. (2008) highlighted the importance of local authorities finding different ways to dispose of waste arising from urban tree and park maintenance to avoid sending waste to landfill and incurring large costs. A range of local authorities currently use this ‘green waste’ as a composting material for their own land or for sale to the public, as domestic fuel for sale to the public and as biomass for power generation, with the London Borough of Croydon’s holistic approach to planning and management cited as an excellent case study example (Britt et al., 2008). Even leaves may be used as biomass, which not only eliminates the cost of landfilling leaves collected from parks and streets but also reduces issues of leaf drop on pavements and associated resident concern. A product on sale in the UK and based in the West Midlands produces ‘Leaf Log’ solid fuel pellets which burns as hot as coal and for 3 times as long as wood (BioFuels International Limited, no date). These examples suggest that utilising trees and green waste for biomass burning and composting could be a good way of generating funding for local authority tree departments, though Britt et al. (2008) warn that utilising waste materials is not a panacea to budgetary pressures, but can help to address budget constraints and help to fulfil wider sustainable development objectives.

8.4.5 Saving Money in Arboricultural Departments

The correct siting of trees is very important, and can save money in maintenance and removal costs as the tree will not cause problems due to its inappropriate growth form. A study in Missouri, USA found that the ‘right trees in the right places’ were on average in a fair to good condition, while ‘wrong’ trees were usually in a poor to fair condition (Gartner et al., 2002). This idea of ‘Right Tree Right Place’ is beginning to be adopted in the UK, with the London Trees and Design Action Group publishing guidance; many attendees to the workshop highlighted this good work and the need to use it as a condition of planning permission. In Canberra, Australia, a computer program has been developed which recommends replacement trees which are similarly aesthetically pleasing, ecologically sound and socially acceptable (Banks and Brack, 2003). The authors recommend that consideration should be given to early removal of some trees, to reduce maintenance costs and safety issues, and to avoid areas of similar-age trees all

247 being removed at once, and replanting the area to give a mix of street ages to avoid this problem in future.

Gartner et al. (2002) found more trees in their survey than did a previous survey of the same area, suggesting that a large amount of tree planting had occurred. However, older trees were in a worse condition than those in the original survey. The authors suggest that this was due to resources being used for planting of new trees, which were in a good condition, rather than for maintenance of older trees. The availability of money and seeming priority for tree planting but not tree maintenance was raised as an issue in the workshop; it is clear that this is not an issue in the UK alone.

Conversely to the logical view that richer areas will spend more on urban forestry schemes, Lewis and Boulahanis (2008) found that in 13 central states of the USA this was not the case. They instead found that the most significant aspects for successful routine tree maintenance was for towns to have a basic organisational structure in place for tree issues, including a specific department, person, and budget dedicated to tree maintenance, and having legal tree protection clauses. This suggests therefore that absolute budgets are not important, and that the urban forest benefits more from organised overseeing than from absolute budget increases or decreases. This may be a positive note for the future in the UK, where most workshop attendees were very concerned about budget cuts for urban forestry. It also backs up a strong feeling from the workshop about the importance and need for every local authority to have a public tree inventory.

8.4.6 Encouraging Community Involvement in Tree Based Activities

This thesis presented very positive views from residents about the trees planted by Red Rose Forest, a community greening project. 90% of respondents stated that the planting of trees had made a positive difference to their street, and in streets with newly planted trees 98% expected to see a difference in their street as the trees grow. In the Green Streets programme, residents do not take part in planting trees, as it requires heavy machinery to dig into the pavement surface, although they do have a key role in tree aftercare, particularly watering. However, in other urban forest schemes, residents are actively encouraged to take part in the planting of trees. In Detroit, Michigan, trees were planted by local people into vacant areas of local authority owned vegetated land in residential areas, and residents were encouraged to look after the trees as they grew

248 through a partnership between the local authority, a tree planting organisation and community groups. A study of this process found that the main motivations for participants in continuing to care for the trees and surrounding vegetation was that they enjoyed working with nature, wanted to help their neighbourhood, and considered the maintenance a chance to create something in their neighbourhood, to give something back to the community and to get to know others in their neighbourhood (Austin, 2002). This shows how greenspace can bring communities together, as different people work together for a single goal and community cohesion can increase. Although the study does not address the quality of maintenance of the volunteers, the social benefits alone are enough to justify this type of community involvement.

Bloriarz and Ryan (1996) evaluated the use of volunteers to collect data for an urban tree inventory in Brookline, Massachusetts, USA. This found that results collected by trained volunteers were valid, the accuracy of their results compared favourably with results collected by professionals, and that the cost of utilising these volunteers was competitive with similar schemes conducted by professionals. The authors also identified other benefits of involving community volunteers, including increasing the public’s awareness of urban trees and forests, increasing environmental awareness and giving volunteers an increased political voice. In the UK it is common to hear that local authorities do not have a tree inventory as it would be too expensive; Bloriarz and Ryan’s (1996) work suggests that volunteers can accurately, and cheaply, provide data for a tree inventory. However, a common problem can be finding volunteers who are able to commit to the time needed for such exercises (Elmendorf et al., 2003).

8.4.7 Community Greening Projects

The analysis of street tree planting as part of the Red Rose Forest Green Streets scheme found no correlations between levels of deprivation, housing type, percentage of homeowners and quality of the surrounding environment on the uptake levels of trees outside residents’ homes. Conversely, Perkins et al. (2004) found that the vast majority of trees planted around homes as part of a municipal scheme in Milwaukee, Wisconsin, USA, were on owner-occupied properties, suggesting that those that rent their homes are not supportive of tree planting schemes or do not care as they are just temporary residents, or that the house owner does not want trees on their property. Although the Red Rose Forest data does not show the tenure of those that accepted a tree outside their home, the highly localised census data gives a good indication of the levels of home

249 ownership in the street; using this data no correlations were found between tenure and acceptance of a tree, suggesting that in Greater Manchester housing tenure does not affect the acceptance of street trees. However, the comparison with this data and with Perkins et al.’s (2004) is not like for like; in Manchester, trees are planted in public land, while in Milwaukee trees were planted on private land. Renters in Manchester may therefore be more likely to accept a tree as they do not have to ask their landlord for permission. Perkins et al.’s (2004) suggestion therefore that those that rent are less likely to want trees around their home as they will not see the monetary benefits in terms of increased house prices and may not stay in their home for long enough to watch the tree grow are not supported in Manchester. However, many residents rent from the local authority or a housing association in Manchester, which gives a high level of stability, suggesting that long term renters feel as secure as homeowners and intend to remain in their property for a long time and can watch a tree grow.

8.4.8 Comparison of Differing Approaches to Increasing Tree Cover

This thesis has demonstrated that in comparable regeneration projects and community greening projects, the community greening projects were able to increase tree cover to levels much closer to the potential maximum number of trees. There does not appear to be any other published research comparing the success of a non profit tree planting scheme with a developer-based scheme, though Summit and Sommer (1998) have compared the effectiveness of different non-profit tree planting schemes. Summit and Sommer (1998) found that the most effective tree planting schemes are those that make it very easy for individuals to get involved, make the scheme sociable and that emphasise the practical, personal benefits of environmentally responsible actions. The authors also found that schemes working in partnership with other community groups are most successful, similar to other research discussed earlier. Summit and Sommer’s (1998) work, when combined with the findings of this study of higher planting levels of community greening projects, suggest that resident based non profit projects are best to increase tree cover in urban areas.

8.5 Conclusions

This thesis has found a large difference in the amount of tree cover in different types of high density housing in Greater Manchester, described in Chapter 4. Pre 1919 terraced housing had the least, while semi-detached housing and 1960s walkway housing had the

250 most. Although the study area contained above average amounts of tree cover compared to Britt et al. (2008), the average masked great variation in tree cover with very low levels across nearly half of the study area.

This thesis has found that tree cover may in principle be increased by between 5% and 10.5% in differing high density housing types, described in Chapter 5; if money and support are unlimited and underground services and lampposts are not an issue. Published studies suggest that it is realistic to plant 50% of these locations, which would greatly reduce the potential tree cover in these areas. This would also reduce the potential reductions in maximum surface temperatures. If temperatures reductions are to be achieved, increasing non-tree vegetation is needed, for example through green roofs and walls. The potential maximum number of trees does not make a large difference to reducing rainfall runoff, so any schemes to reduce flooding in these areas should concentrate on channelling the water away from high density housing areas towards a more suitable drainage area, planted with large number of trees.

Overall, the views of residents found in this UK study and described in Chapter 6 are comparable with similar studies in other parts of the world, except questions about sunshine and shade. Shade was not highly rated as a reason to plant trees by UK respondents, while in other countries it tends to be a high priority; this is probably due to its cool cloudy climate, where warm days when shade is needed are rare, although this is likely to change as climate change increases temperatures.

The literature generally supports the issues raised at the workshop, outlined in Section 7.2. Greater legal protection for trees generally and in the planning process was seen as very important by the attendees of the workshop, and the literature demonstrates the effectiveness of strong tree laws to maintain and increase tree cover, and the importance of strong enforcement. The literature shows that residents are happy, in principle, to pay for maintenance and protection of the urban forest, and the workshop suggested a number of novel ways this willingness to pay may be used. They should be explored in the future. The importance of tree inventories and strategies to aid tree protection and planting was stressed by the workshop, and the literature supports this as both a potential money saving aspect, as funds are better spent, and as a way to get residents involved and interested in the urban forest. The potential for use of urban timber as a source of biomass was strongly supported in the workshop, and the literature supports this as a potential revenue strand for local authorities.

251 Community based tree planting projects have planted much nearer the potential number of trees than regeneration schemes, shown in Section 7.3. Thus it is more likely than non- profit resident driven tree planting schemes will plant nearer the maximum number of trees than other methods of tree planting.

252 Chapter 9 – Conclusions

This chapter summarises the research findings, and presents recommendations to increase tree cover in high density housing areas in the future. The conceptual framework of Section 3.1.1 is revisited in light of the research findings. The findings as they relate to different stakeholders are presented, with appropriate recommendations to increase tree cover in the future.

9.1 Summary of Main Research Findings

9.1.1 Revisiting the Conceptual Framework

Housing density Resident Presence of socioeconomic community status housing layout greening schemes and type

Tree distribution in high density housing areas Developer attitudes

Local government Resident National policy attitudes government policy

Figure 9.1. A reprise of the Conceptual Framework of Chapter 3, in light of the research findings. Thick black arrows demonstrate a relationship found in by the literature, thick blue arrows demonstrate a relationship found in this research. Thin black arrows demonstrate a hypothesised relationship before the research began, thin blue arrows demonstrate no relationship found during the research. The absence of a blue arrow indicates further research needed, although recommendations are given for policy improvements.

This thesis has demonstrated that there is a strong relationship between high density housing type and the amount of tree cover it contains, as shown in Figure 9.1. This is a new finding for the literature, and is in addition to published research demonstrating that the density of housing influences tree cover. The published literature is unanimous in

253 finding higher tree cover in areas of lower density housing, and all use techniques similar to those used in this thesis.

Figure 9.1 shows no relationship hypothesised or found between resident attitudes and distribution of trees in high density housing areas. Published research using questionnaires agree that residents are overwhelmingly positive about urban trees; this study reinforces this finding using the same methods in a different country (the UK) to those previously studied (USA, New Zealand), and finds no relationship between attitude of residents and their residential environment. It appears that in the study area of high density housing respondents liked and wanted trees regardless of the setting of their home.

Figure 3.1 gave a hypothesised relationship between community greening schemes and the distribution of trees in high density housing areas. This thesis has shown that the presence of a community greening scheme (in this case Red Rose Forest’s Green Streets scheme) with a proactive champion helped plant significantly more trees than those without, and also planted more than similar redevelopment schemes. In Figure 9.1 it is given as a confirmed relationship, a new finding for the literature.

The literature review (Section 2.3.1 and 2.3.2) suggests a relationship between socioeconomic differences and the distribution of trees in high density housing areas, and has been presented accordingly in Figure 3.1. However, there is not acceptance of the specific socioeconomic factors that affect tree distribution; income is regarded by most authors as a factor, while correlations between ethnic origin and tree cover are mixed. It is possible that slight variations in statistical tests used are responsible for these different results, or that there are genuine correlations between ethnic origin and tree cover in some neighbourhoods that cannot be replicated in other geographic areas. An exploration of any socioeconomic factors was not possible in this thesis, due to the small geographic size of housing types which would not give accurate ideas of the socioeconomic status of residents. This is described in more detail in Section 8.1. Further work is needed to explore this in more detail, and all socioeconomic factors identified in the literature should be tested, regardless of whether a relationship was found.

The literature review (Section 2.4.1) suggested links between local planning policies and the distribution of trees, and therefore both national and local government policies were given as possible factors in the distribution of trees in high density housing areas in

254 Figure 3.1. Local government policies were not mentioned as important by developers, therefore due to time constraints on the research these were not studied in this thesis. Therefore, further study is needed to determine if local planning polices have an effect on tree distribution, as suggested in the literature. Section 7.1.1 showed that there is little consideration for trees in national policy documents, but more work is needed to ascertain if national or local government policies have a direct, measurable effect on tree cover, therefore a relationship has not been suggested in Figure 9.1. Practitioners who attended the workshop (Section 7.2) did identify a range of improvements to national and local policies regarding tree protection and planting; this suggests that current policies are not as effective as they could be. Therefore, if the recommendations are implemented, they could protect and increase tree cover more effectively than current regulations.

9.1.2 Research Conclusions

The aim of the thesis was ‘ To understand the differential provision of tree cover in urban residential environments, the changes in environmental quality that trees confer and the policies and practice that affect tree provision’. This has been achieved through four objectives, and the findings are given below.

Objective 1. To explore the nature of variation in tree cover and its causes in residential environments.

This thesis has demonstrated that there were clearly defined types of high density housing within the study area of Greater Manchester. Pre 1919 terraced housing types accounted for 44% of the housing in the study area; 18% was semi-detached housing; 10.6% was 1960s driveway housing; 8.6% was 1960s walkway housing; the remainder consisted of 1919-1959 terraced housing and post 1970s terraces. Within these housing types tree cover varied by a factor of 9, from 1.6% to 15%. Therefore, a relationship between housing type and tree cover has been found. Pre 1919 terraced housing types had the lowest amount of tree cover, while semi-detached housing types and 1960s walkway housing had the highest level of tree cover.

Objective 2. To examine the influence of actual and potential tree cover on environmental quality of high density residential neighbourhoods in a changing climate.

255 Tree cover may be increased in principle in all housing types, by between 5% and 10.5%, with the smallest increase in pre 1919 semi-detached housing, and the highest in 1960s driveway housing. These trees could mainly be planted in pavements and back gardens. This increase in tree cover gave the largest decreases in maximum surface temperatures of 4.5°C in response to increasing temperatures due to climate change, within housing types that contained less than 4% tree cover; housing types with more than 4% tree cover had decreases in temperature of around 1°C. Increasing tree cover does little to decrease rainfall runoff in extreme rainfall events.

Objective 3. To examine the interdependence between tree cover and residents’ attitudes to it in high density residential areas.

Residents surveyed in differing street types were all very positive about urban trees and their benefits. Street type only slightly affected strength of agreement or disagreement with statements about trees, although those in streets with old street trees disagreed less strongly that sap dripping onto cars was a reason why trees should not be planted. Trees making the street friendlier and more attractive were the highest rated benefits of trees, followed by attracting wildlife and reducing pollution. Respondents that had taken part in the community greening project ‘Green Streets’ were very positive about it; over 90% stating that trees had made a positive difference to their street or that newly planted trees will make a difference to their street, and over 85% would recommend the project to a friend. These positive reactions from respondents are also commonly seen in the literature, although shading by trees is ranked more highly by respondents in other studies. A minority of respondents thought that trees would increase the price of their house, which is not reflected by the literature, which finds that house prices increase with presence of trees. The vast majority of respondents stated that they would try to move to a street with trees in the future.

Objective 4. In light of objectives 1-3, to inform policy and practice with regard to tree provision in high density residential areas.

A workshop with professionals working with urban trees found that funding issues are a major problem, as is lack of legal protection and enforcement for urban trees. Inventive ways of finding funding were suggested, including direct and indirect methods of raising money from urban residents. The problem of the availability of funding for tree planting but not for tree maintenance was raised, which suggests funding bids, laws and

256 regulations need to be changed in order to fund essential maintenance of urban trees. The use of tree trimmings and felled trees as biomass was a popular suggestion as a way to contribute to the funding of tree planting and maintenance works. Methods of automatic protection for trees over a certain size and much harsher enforced penalties for tree felling and damage were seen as good methods to protect urban trees. The importance of local authorities conducting a Tree Inventory, which should influence a Tree Strategy, was also highlighted; these can aid funding applications and influence planning permission decisions, and are particularly important for developing a sound management and investment strategy.

Two different ways to increase urban tree cover were analysed. The community driven Red Rose Forest ‘Green Streets’ scheme increased tree cover to much nearer the potential maximum number of trees than regeneration schemes in similar housing types. No factors were found that affected levels of acceptance of a tree outside people’s homes in the Green Streets scheme, suggesting that it is the only the community involvement aspect of the project that enables high planting rates. The two regeneration schemes demonstrated an understanding of the importance of vegetation around homes, however tree planting rates were nowhere near the potential maximum. In Chimney Pot Park private and communal areas of vegetation were seen as good ways to increase community interaction. In Grove Village, a planned green route was not built as planned due to cost cutting and the presence of large underground services, which also limited the number of trees planted. Unfortunately there is a tendency for contractors to cut money from the public realm when project costs increase; the non-fulfilment of the planned Green Route shows the importance of properly costing schemes with consideration of potential increases. The inability to plant some trees where planned demonstrates the importance of thorough knowledge of a site above and below ground before design and selecting tree planting sites may begin. In both schemes more trees were planted than removed, but placement and potential growth of trees was changed. The overall balance of tree distribution in Chimney Pot Park was uneven, and trees were not protected from damage by cars with tree guards, which may be a problem for trees in areas where cars can easily access. In Grove Village, trees were removed from large grass verges and new trees planted into small pits in pavement and parking areas, suggesting that trees will have less room for root growth in the future.

257 9.2 Recommendations of the Research

For the presentation of recommendations to help increase tree cover in urban areas, it is appropriate to give recommendations targeted at specific stakeholders in the urban forest. Stakeholders were identified through the conceptual framework using the concepts of urban forestry and during the research, particularly the practitioner workshop. The following section presents research from the literature, new research found as part of this study and recommendations for increasing tree cover as applicable to each stakeholder.

9.2.1 National Government

The literature does not, to the researcher’s knowledge, contain any comparative data of national legislation related to tree protection. The studies presented in Section 2.4.1 are all studies of city or county-wide legislation, not national. The literature does give a range of recommendations for local tree protection legislation which have been shown to be effective in protecting and increasing tree cover in residential areas. These have previously been discussed in Sections 2.4.1 and 8.4.2, and would work better in the UK if implemented on a national level; urban areas in the UK are often spread over more than one local authority, especially in the case of cities, so local adoption of consistent policies can be problematic.

The practitioner workshop (Section 7.2) identified a range of national Government policies and strategies that could be introduced or improved in order to help protect, maintain and improve the urban forest. This legislation should be stronger, with enforceable and enforced protection of urban trees, drafted in consultation with urban tree professionals and be made at a national level across the whole of the UK, with interim arrangements made locally. The most important recommendations are given below, plus those identified in the literature review (Section 2.4.1). Additional, lower priority, recommendations from the workshop are given in Section 7.2.2. • protect all trees on local authority land and all other trees over a certain size, perhaps 15cm diameter at 0.9m high as in other countries, with applications for felling made to the local authority; • allow for larger fines or other disincentives as a punishment for those who cut down trees illegally; • provide legislation and guidance to allow for alternative ways of funding trees and their maintenance; 258 • withdraw legislation that prevents the use of capital funding (e.g. money generated through Section 106 Agreements) for tree maintenance: if capital funding is used to plant the trees then capital funding should also be allocated for the maintenance of these trees, at least during the establishment phase of the trees, or the trees may die, wasting capital money; • specific mention of trees and tree planting in documents and policies relating to the urban environment and residential areas, with minimum numbers of trees in developments and protection for existing trees.

Constraints to the Implementation of Legislative Changes

The passing of this legislation is likely to be hampered by a lack of political will on a national level to change laws to help protect and increase tree cover. Even if these laws are passed, a lack of political will on a local level may prevent them being promoted or enforced; a lack of funding for trees in general could also hamper changes, particularly with regards to enforcement of tree protection as part of development. However, funding can be found if there is the political will to earmark money or to apply for outside grants or sponsorship. Lack of political will to protect and increase trees in urban areas was cited by many in the workshop as a barrier; this suggests a culture of ‘political short term-ism’ where politicians cannot or do not think beyond their elected term of office. Trees can cost a lot now but their benefits will increase with age, after a politician may be out of office; therefore, politicians are reluctant to spend money on things they may not get credit for during the next election campaign. This can happen at any level of office, from local to national.

9.2.2 Local Government

The results in this thesis show that there is a large variation in tree cover in different types of high density housing, and that there is potential to plant more trees in all high density housing types identified. Therefore, local authorities should not automatically discount high density housing areas as areas where there is no room for trees when planning tree planting schemes. This is the most important recommendation to local authorities to emerge from this research; further recommendations continue below.

259 Policy and Strategy

There were a number of recommendations produced in workshop (Section 7.2) that local authorities could implement without requiring legislation change from national government: • develop and maintain a detailed Tree Inventory, accompanied by a Tree or Green Infrastructure Strategy • issue more Tree Preservation Orders, or blanket protect trees of a certain size, and punish those who damage or fell these trees more harshly; • investigate the use of fallen leaves and wood generated as part of tree maintenance as biomass fuel, either for compost, heating council buildings or for sale to the public or industry.

Conditions related to planning permissions

Local authorities approve planning permissions in their area and can attach conditions to the granting of this permission. The workshop held as part of Objective 4 (Section 7.2) gave a number of recommendations of conditions to attach to the granting of planning permission to developers, and developments should be monitored to ensure their compliance. Conditions are as follows: • consultation with an arboriculturist, landscape architect and highways officer before building begins so trees may be properly included in developments in a way appropriate to the surrounding landscape; • following recommendations of the Trees and Design Action Group’s ‘Right Tree Right Place’ resource; • extending the establishment period of trees on site, during which new trees receive specific aftercare, from 2 to 5 years, and including appropriate monitoring and replanting if necessary.

Interestingly, research has shown that people will pay more for goods and businesses will pay higher rents in areas with trees and greenery (Laverne and Winson-Geiderman, 2003; CABE Space, 2005; Wolf, 2008) and people pay more for homes in leafy areas (Tyrvainen and Miettinen, 2000; CABE Space, 2005; Kaufman and Cloutier, 2006). Therefore, a new retail, industrial or residential development forced through planning conditions to contain a large number of trees and greenspace could generate more money

260 over the long term for the local authority in terms of business rates, council tax and other income.

Resident Support and Inclusion

The literature demonstrates wide support and positive attitudes towards trees (e.g. Schroeder, 1989; Sheets and Manzer, 1991, Schroeder and Ruffalo, 1996; Lohr et al., 2004; Gorman, 2004; Schroeder et al., 2006), as does the research in this thesis (Chapter 4). The high levels of disagreement with the statement ‘trees should not be planted as they cost the council too much’ found in this research (Section 6.4.4) suggests that councils should not be worried about residents’ perception of the costs of tree planting schemes as residents want trees planted regardless of costs. However, these costs must be balanced against other forms of public investment. Other literature (e.g Bloriarz and Ryan, 1996; Austin, 2002; Sipila and Tyrvainen, 2005) has shown the positive benefits of involving the community in decisions about greenspace and the planting and upkeep of urban trees and greenspaces. This thesis has shown that the involvement of a proactive Green Streets Champion significantly increases the uptake of trees in street greening schemes (Section 7.4). Therefore, local authorities should be more positive and proactive about involving the community in tree and greenspace improvements. This can even lead to cost savings, with trained volunteers collecting data to inform a Tree Inventory; this was found to be cost effective by Bloriarz and Ryan (1996).

Constraints to the Implementation of Recommendations

Issues around ‘political short term-ism’ identified at the end of Section 7.2.1 above also apply to local politicians and local authorities. An overall policy of accepting any development at any cost may also hamper efforts to increase tree numbers in new developments. Again, the ability to pay for staff to develop and enforce regulations could be a barrier to the effective implementation of these regulations. A lack of money for staff time would also impact greatly on the amount of community engagement that could take place. However, some staff time to begin with can be offset by volunteer time in the future, particularly with regards to developing a Tree Inventory. Again, ‘political short term-ism’ becomes a problem in this case as the cost is now while benefits and staff time savings may be far in the future.

261

9.2.3 Developers

No published research has, to the researcher’s knowledge, explored the responses of developers to issues of trees and increasing tree cover in developments. Therefore, recommendations are made solely from the research in this thesis. Additional recommendations related to planning permissions given to developers by local planning authorities are highlighted in Section 9.2.2 above.

Developers are constrained by the legal requirements of house building, such as street width, local planning regulations and what people expect in a new housing development. Changes are needed in national and local planning guidance to require space for tree planting as part of new developments, and these are outlined above. Some developers are beginning to see the importance of including greenery in their developments (see Section 7.5), and the following recommendations should help them increase tree cover in their developments. However, if a developer is not interested in increasing greenery in their development then these recommendations would be ignored. This demonstrates the importance of education of all stakeholders in the benefits trees can bring, with financial impacts of particular interest to developers.

Housing layout

The literature has shown that there are differences in tree cover between different densities of housing (e.g. Land Use Consultants, 1993; Iverson and Cook, 2000; Handley et al., 2000; Solecki et al., 2005; Tame 2006; Britt et al., 2008), with high density housing containing, on average, the lowest amount of tree cover. This thesis has shown that tree cover varies dramatically between different types of high density housing, but that all types of housing have opportunities to increase tree cover. Therefore, developers building high density housing should be able to design and build housing that allows for tree planting and growth, such as those demonstrated by Rudlin and Falk (1999). The housing type ‘1960s walkway’ contained the largest number of trees, and ‘1960s driveway’ contained the largest number of potential tree planting sites; modern versions of these housing types could be built with large numbers of trees and other vegetation. Unfortunately, this type of housing is highly unpopular in the UK (Colquhoun, 1999, p15-17); new interpretations of this housing type are therefore needed in order to build at high densities but still allow fairly high levels of tree cover. The designs suggested by

262 Rudlin and Falk (1999) give a range of high density housing designs and guidance that incorporates trees, green space and parking, similar to housing in many European cities. Therefore, future high density housing could have a high level of tree cover if designs are well planned and executed. In housing of this type community involvement and action in maintaining the surrounding greenspaces may be a good way of protecting and enhancing the area for trees and community use.

House prices

A range of literature (e.g. Tyrvainen, 1997; CABE Space, 2005; Payton et al., 2008; Netusil et al., 2010) and results in this thesis show that residents value trees around their home and would pay more to live in these areas. Therefore, it would make sense for developers to provide their new estates with trees in order to increase its attractiveness and also to increase the price the homes are sold for. Conversely, a development without trees, or a development where trees have been removed, may reduce in value as it is not seen as an attractive place to live.

9.2.4 Residents

The literature (e.g. Schroeder, 1989; Sheets and Manzer, 1991; Flowers and Gerhold, 2000; Lohr et al., 2004; Vesely, 2007) and the research conducted as part of this thesis (Chapter 6) show that residents are very positive about trees, like having them around their homes and in the wider urban area, despite their potential problems and costs, and would like to live in areas with trees, even paying more for these houses. This suggests that residents would be supportive of new tree planting schemes, and many would like to be involved in these schemes. Research has shown that many people would pay or donate time to protect, maintain and increase the urban forest (Vesely, 2007; Zhang et al., 2007). Research has also shown that utilising community volunteers to help collect information about urban trees is cost effective, with wider community benefits (Bloriarz and Ryan, 1996).

Therefore, residents should be seen as supportive stakeholders in the urban forest, who may be approached to help protect and increase this resource through donations of money or time by other stakeholders. Similarly, residents should be proactive in seeking schemes and funding to increase the tree cover in their area; resident driven schemes such as Green Streets studied in this research are very successful.

263

9.2.5 Community Greening Projects

This thesis has shown there is potential for tree planting in high density housing, and that there is resident support for this (Chapter 5 and 6). Therefore, community greening schemes such as the Red Rose Forest Green Streets project, should be continued and expanded, in order to increase tree cover in these areas. This is particularly important as the largest proportion of potential trees could be planted into pavements, as is Green Streets trees current practice. However, long term maintenance funding is needed for these trees, which currently is not usually covered by funding bids. Community involvement can mean that basic tree management is done by residents, which can keep maintenance costs down.

Community greening projects can also help give correct information about the benefits of trees and a realistic idea of any damage trees may cause. This could help increase support and reduce fears of tree damage to property and associated insurance problems.

9.3 Limitations of the Research Methodology

The research is limited in a number of ways. The following section outlines the methods chosen and their impacts on the results, and the potential effects of the use of other methods.

The levels of potential maximum tree cover may not be realistic as issues of existing pavement width and over/underground surfaces were not considered. A more accurate method would have taken these into account and produced a more realistic level of potential maximum tree cover. More data would have been needed for this to be carried out, much of which is unavailable, e.g. underground water pipe locations. Therefore, the method used was most appropriate for the level of data available, but it may have over estimated the potential to increase tree cover.

The questionnaire was a self-selecting sample, where people chose to fill it in. It is probable that those who do not like or want trees chose not to fill it in as they did not want to ‘waste their time’, or saw the Red Rose Forest name and thought that a proactive tree planting organisation would ignore their ‘anti-tree’ views. Therefore, the respondents that did fill out the questionnaire are likely to be people who already like trees but are not 264 representative of the whole community, and so the results must be treated with caution. It is difficult to suggest ways through which this may be avoided; those who do not like trees are unlikely to ever want to answer a survey about them. It may be possible to include questions about trees in a wider survey about other neighbourhood issues, or to explore them through focus groups looking at the wider issue of neighbourhood quality or service provision.

9.4 Recommendations for Further Work

This study may be extended to other cities with large amounts of high density housing, to determine if similar housing types exist elsewhere and if the patterns of tree distribution are replicated. The technique used for estimation of potential tree cover may be used in any area to give a general idea of the levels of tree cover that may be planted. It may be of particular use in areas where local authorities are considering the use of vegetation to mitigate the high temperatures predicted by climate change; if areas are not able to support a 10% increase in tree cover, predicted by Gill et al. (2007) to keep temperatures around 1990 levels then other methods of greening may be implemented, such as green walls or green roofs.

Further work is needed within a UK context to determine the effects of trees on house prices and people’s willingness to pay higher prices for a more vegetated environment. CABE Space (2005) have studied this comparing proximity to green spaces and the recent selling prices of homes, but little work has been done exploring people’s opinions. Some work has been done in the USA and New Zealand which suggests residents would willingly pay for the upkeep of the urban forest and pay more for houses in areas of high tree cover, but this has not been greatly explored in the UK. Further surveys of residents’ attitudes towards trees may be carried out; residents’ positive views towards urban trees have been consistently seen in the USA, Canada, Australia and New Zealand, though not in the UK. Further work in the UK should determine the influence of other factors such as climate and levels of urbanisation which may affect opinions about urban trees. A survey of views related to specific greening projects would be of more use in the future, particularly for schemes bidding for funds for tree planting that require resident support. Further studies setting out the potential for green space and trees within new high density housing developments would be of particular value in showing how the amount of tree cover in high density residential areas could be increased.

265 References

Agyemang C., van Hooijdonk C., Wendel-Vos W., Lindeman E., Stronks K., Droomers M. 2007. The Association of Neighbourhood Psychosocial Stressors and Self- Rated Health in Amsterdam, The Netherlands. Journal of Epidemiology and Community Health , 61 :1042 - 1049.

Akbari H., Pomerantz M and Taha H. 2001. Cool Surfaces and Shade Trees to Reduce Energy Use and Improve Air Quality in Urban Areas. Solar Energy , 70 :295 - 310.

Akbari H. 2002. Shade Trees Reduce Building Energy Use and CO2 Emissons From Power Plants. Environmental Pollution , 116 :S119 - 126.

Alexander C. 1977. A Pattern Language : Oxford University Press, New York, USA. pp1171.

Alexander D.A. 2006. The Environmental Importance of Front Gardens. Municipal Engineer , 159 :239 - 244.

Anon. 2000. Texas City Relies On Tree Canopy to Reduce Runoff. Civil Engineering , 70 :18.

Anon. 1995. Manchester - 50 Years of Change : HMSO, London, UK.

Appleyard H.S.G. 2000. A Strategy to Establish Trees Among High-Density Housing Journal of Arboriculture , 26 :78 - 86.

Attwell K. 2000. Urban Land Resources and Urban Planting - Case Studies from Denmark. Landscape and Urban Planning , 52 :145 - 163.

Austin M E . 2002. Partnership Opportunities in Neighborhood Tree Planting Initiatives: Building from Local Knowledge. Journal of Arboriculture , 28 :178 - 186.

Banks J. C. G., and Brack C.L. 2003. Canberra's Urban Forest: Evolution and Planning for Future Landscapes. Urban Forestry & Urban Greening , 1:151 - 160.

Barbosa O., Tratalos J.A., Armsworth P.R., Davies R.G., Fuller R.A., Johnson P. and Gaston K.J. 2007. Who Benefits from Access to Green Space? A Case Study from Sheffield, UK. Landscape and Urban Planning , 83 :187-195.

Bartens J, Day S.D., Harris J. R., Wynn T. M., Dove, J. E. . 2009. Transpiration and Root Development of Urban Trees in Structural Soil Stormwater Reservoirs. Environmental Management , 44 :646 - 657.

Bealey W.J., McDonald A.G., Nemitz E., Donovan R., Dragosits U., Duffy T.R. and Fowler D. 2007. Estimating the Reduction of Urban PM10 Concentrations by Trees Within an Environmental Information System for Planners. Journal of Environmental Management , 85 :44 - 58.

Bell J. F., Wilson J.S. and Liu G.C. 2008. Neighborhood Greenness and 2-Year Changes in Body Mass Index of Children and Youth. American Journal of Preventive Medicine , 35 :547 - 553.

266 Biddle G. 1981. Physical Problems Caused by Trees to Buildings and Services. In Clouston B. and Stansfield K (eds.). Trees in Towns. Architectural Press, London. p17 - 47.

BioFuels International Limited. no date. Leaf Log – FAQs. http://www.leaflog.com/environmental.php Accessed 31/5/2010.

Bjork J, Albin M, Grahn P, Jacobsson H, Ardo J, Wadbro J, Ostergren P O and Skarback E. 2008. Recreational Values of the Natural Environment in Relation to Neighbourhood Satisfaction, Physical Activity, Obesity and Wellbeing. Journal of Epidemiology and Community Health, 62.

Bloniarz D V. and H. D. P. Ryan, III 1996. The Use of Volunteer Initiatives in Conducting Urban Forest Resource Inventories. Journal of Arboriculture , 22 :75 - 82.

Bradshaw A., Hunt B. and Walmsley T. 1995. Trees in the Urban Landscape: Principles and Practice. E and FN Spon, London, UK. pp272.

Britt C. J M, Riding A., Slater J. , King H., Gladstone M., McMillan S., Mole A., Allder C., Ashworth P., Devine T., Morgan C., and Martin J.,. 2008. Trees in Towns II. DCLG, UK Government.

Brown F.E. and Steadman J.P. 1991. Housing in Cambridge: A Computerised Catalogue of a Sample of British House Plans. In Configurational Studies Report Series .

Budruk M, Thomas H and Tyrrell T. 2009. Urban Green Spaces: A Study of Place Attachment and Environmental Attitudes in India. Society & Natural Resources, 22: 824- 839.

Bullard R.D., and Johnson G.S. 2000. Environmental Justice: Grassroots Activism and Its Impact on Public Policy Decision Making. Journal of Social Issues , 56 :555 - 578.

Bullock C H, , . 2008. Valuing Urban Green Space: Hypothetical Alternatives and the Status Quo. Journal of Environmental Planning and Management , 51 :15 - 35.

Burls A. 2007. People and Green Spaces: Promoting Public Health and Mental Well- Being Through Ecotherapy. Journal of Public Mental Health , 6:24 - 39.

CABE Space. 2005. Does Money Grow On Trees? Commission for Architecture and the Built Environment (CABE) Publications. Available from http://www.cabe.org.uk/files/does-money-grow-on-trees.pdf Accessed 1/8/2010.

Cardelino C.A., and Chameides W.L. 1990. Natural Hydrocarbons, Urbanisation and Urban Ozone. Journal of Geophysical Research , 95 :13971 - 13979.

Cattell V., Dines N., Gesler W. and Curtis S. 2007. Mingling, Observing, and Lingering: Everyday Public Spaces and their Implications for Well-Being and Social Relations. Health & Place , 14 :544 - 561.

Chameides W.L. L R W, Richardson J. and Kiang C.S. 1988. The Role of Biogenic Hydrocarbons in Urban Photochemical Smog: Atlanta as a Case Study. Science , 241 :1473 -1475.

Chow V.T., Maidment D.R., Mays L.W. 1988. Applied Hydrology : McGraw-Hill. 267

Coen S.E., Ross N.A. 2006. Exploring the Material Basis for Health: Characteristics of Parks in Montreal Neighborhoods with Contrasting Health Outcomes. Health & Place , 12 :361 - 371.

Colquhoun I. 1999. RIBA Book of 20th Century British Housing , Oxford, UK: Butterworth-Heinemann.

Conway H. 1991. People's Parks: The Design and Development of Victorian Parks in Britain , Cambridge, UK: Cambridge University Press.

Crook A.D.H., Dunning R., Ferrari E.T., Henneberry J.M., Watkins C.A., Burgess G., Lyall Grant F., Monk S., Whitehead C.M.E. and Rowley S. 2010. The Incidence, Value and Delivery of Planning Obligations in England in 2007-08. Final Report. DCLG, UK Government. Available at: http://www.communities.gov.uk/documents/planningandbuilding/pdf/1517816.pdf

David T.S., Gash, J. H. C., Valente, F., Pereira, J. S., Ferreira, M. I., David, J. S., . 2006. Rainfall Interception by an Isolated Evergreen Oak Tree in a Mediterranean Savannah. Hydrological Processes , 20 :2713 - 2726.

Davies R G, , Barbosa, O., Fuller R.A., Tratalos J., Burke N., Lewis D., Warren P.H., and Gaston K.J. 2008. City-Wide Relationships Between Green Spaces, Urban Land Use and Topography. Urban Ecosystems , 11 :269 - 287.

DCLG (Department for Communities and Local Government) and Trees for Cities. 2008. Best Practice Guidelines: How to Assess the Suitability of a Site for Street Tree Planting and What to do Next. Department for Communities and Local Government, UK Government. pp. 8. Available from: http://www.treesforcities.org/files_reports/tfc_bestPractice_streetTrees.pdf

DCLG (Department for Communities and Local Government). 2008. Planning Policy Statement 12: Local Spatial Planning. Department for Communities and Local Government, UK Government. pp.35. Available from: http://www.communities.gov.uk/planningandbuilding/planningsystem/planningpolicy/pla nningpolicystatements/

DCLG (Department for Communities and Local Government). 2010. Letter to Chief Planning Officers: New Powers for Local Authorities to Stop 'Garden Grabbing'. DCLG, UK Government. Available at: http://www.communities.gov.uk/documents/planningandbuilding/pdf/1615265.pdf

Dwyer J.F, McPherson E.G., Schroeder H.W. and Rowntree R.A. 1992. Assessing the Benefits and Cost of the Urban Forest. Journal of Arboriculture , 18 :227 - 234.

Edina. Digimap Collections, Ordnance Survey data. www.edina.ac.uk/digimap/

Elmendorf W.F., Cotrone V.J., and Mullen J.T. 2003. Trends in Urban Forestry Practices, Programs, and Sustainability: Contrasting a Pennsylvania, U.S., Study. Journal of Arboriculture , 29 :237 - 248.

England’s Community Forests. 2005. About Us. http://www.communityforest.org.uk/aboutenglandsforests.htm Accessed 26/8/08.

268 Escobedo F.J., Wagner J.E., Nowak D.J., De la Maza C.L., Rodriguez M. and Crane D.E. 2008. Analyzing the Cost Effectiveness of Santiago, Chile's Policy of Using Urban Forests to Improve Air Quality. Journal of Environmental Management , 86 :148 - 157.

ESRI. ArcMap 3.0, 1999. www.esri.com

ESRI. ArcMap 9.0, 2004. www.esri.com

Evelyn J. 1661. Fumifugium or the Inconveniencie of the Aer and Smoak of London Dissipated Together with some Remedies humbly proposed by J.E. Esq. to His Sacred Majestie, and to the Parliament now Assembled.

Fan H., and Sailor D.J. 2004. Modeling the Impacts of Anthropogenic Heating on the Urban Climate of Philadelphia: a Comparison of Implementations in two PBL Schemes. Atmospheric Environment , 39 :73 - 84.

Fink A. 1995 . The Survey Handbook (p78-80). Sage Publications Inc, California, USA.

Flowers D.E., and Gerhold H.D. 2000. Replacement of Trees Under Utility Wires Impacts Attitudes and Community Tree Programs. Journal of Arboriculture , 26 :309 - 318.

Fraser E.D.G., and Kenney W.A. . 2000. Cultural Background and Landscape History as Factors Affecting Perceptions of the Urban Forest. Journal of Arboriculture , 26 :107 - 113.

Freeman T.W. 1962. The Manchester Conurbation. In Manchester and its Region - A Survey Prepared for the British Association , pp. 47 - 60.

Fuller R.A., Irvine K.N, Devine-Wright P., Warren P.H. and Gaston K.J. 2007. Psychological Benefits of Greenspace Increase With Biodiversity. Biology Letters , 3:390 - 394.

Gartner J. T., Treiman T. and Frevert T. 2002. Missouri Urban Forest: A Ten-Year Comparison. Journal of Arboriculture , 28 :76-83.

Gidlof-Gunnarsson A, , and Ohrstrom, E. 2007. Noise and Well-Being in Urban Residential Environments: The Potential Role of Perceived Availability to Nearby Green Areas. Landscape and Urban Planning , 83 :115-126.

Georgi N.J., and Zafiriadis K. 2006. The Impact of Park Trees on Microclimate in Urban Areas. Urban Ecosystems , 9:195 - 209.

Gill S.E. 2006. Climate Change and Urban Greenspace. PhD Thesis, School of Environment and Development . University of Manchester.

Gill S.E., Handley J.F., Ennos A.R. and Pauleit S. 2007. Adapting Cities for Climate Change: The Role of the Green Infrastructure. Built Environment , 33 :115 - 133.

Gill S.E., Handley J.F., Ennos A.R., Pauleit S., Theuray N. and Lindley S.J. 2008. Characterising the Urban Environment of UK Cities and Towns: A Template for Landscape Planning. Landscape and Urban Planning , 87 :210 - 222.

269 GLA. 2005. Crazy Paving: The Environmental Importance of London's Front Gardens. http://www.london.gov.uk/assembly/reports/environment/frontgardens.pdf Accessed 11/08/2008.

GMB Union. 2006. Directors And Chief Executives Top 2006 UK Pay League Earning Over Sixteen Times The National Minimum Wage. http://www.gmb.org.uk/Templates/PressItems.asp?NodeID=95240 Accessed 16/7/09

Greater Manchester Geological Unit (GMGU). A department of the Association of Greater Manchester Authorities (AGMA) and linked with the University of Manchester. www.gmgu.org.uk

Gould J. 1977. Modern Houses in Britain, 1919 - 1939 , London, UK: Society of Architectural Historians of Great Britain.

Gómez J.A., Giráldez J.V and Fereres E. 2001. Rainfall Interception by Olive Trees in Relation to Leaf Area. Agricultural Water Management , 49 :65 - 76.

Gómez-Muñoz V.M., Porta-Gándara M.A., and Fernández J.L. 2010. Effect of Tree Shades in Urban Planning in Hot-Arid Climatic Regions Landscape and Urban Planning , 94 :149 - 157.

Gorman J. 2004. Residents' Opinions on the Value of Street Trees Depending on Tree Location. Journal of Arboriculture , 30 :36 - 44.

Guevara-Escobar A. G-S E, Veliz-Chavez C., Ventura-Ramos E., and Ramos- Salinas M. 2007. Rainfall Interception and Distribution Patterns of Gross Precipitation Around an Isolated Ficus benjamina Tree in an Urban Area. Journal of Hydrology , 333 :532 - 541.

Guite HF., Clark C, Ackrill G . 2006. The Impact of the Physical and Urban Environment on Mental Well-Being. Public Health. Public Health , 120 :1117 - 1126.

Handley J., Wood R., and Ruff A. 2000. The Red Rose Forest Urban Timber Initiative: A Report on the Sampling of the Street, Park and Garden Tree Population. Red Rose Forest Report. pp. 76.

Harte D. 1981. The Impact of the Law. In: Clouston B. and Stansfield K. (eds.). Trees in Towns. Architectural Press, London. p92 – 127.

Hartig T., Mang M. and Evans G.W. 1991. Restorative Effects of Natural Environment Experiences. Environment and Behaviour , 23 :3 - 26.

Hardy D . 1991 . From New Towns to Green Politics . E and FN Spon, London. 238pp.

Hawkes D. and Souza C. 1981. Passive Solar Heating in Existing Housing - a Survey of Housing Stock of Cambridge. Martin Centre, University of Cambridge Architecture Department, Cambridge, UK.

Henneberger . 2002. Origins of Fully Funded Public Parks. George Wright Forum , 19 :13 - 20.

Heynen N.C. 2003. The Scalar Production of Injustice within the Urban Forest. Antipode , 35 :980 - 998. 270 Heynen N.C., and Lindsay G. 2003. Correlates of Urban Forest Canopy Cover: Implications for Local Public Works. Public Works Management and Policy , 8:33 - 47.

Heynen N.C., Perkins H.A. and Roy P. . 2006. The Political Ecology of Uneven Urban Green Space - The Impact of Political Economy on Race and Ethnicity in Producing Environmental Inequality in Milwaukee Urban Affairs Review , 42 :3 - 25.

Hildebrandt E.W., and Sarkovich M. 1998. Assessing the Cost-Effectiveness of SMUD'S Shade Tree Program. Atmospheric Environment , 32 :85 - 94.

Hill E, , Dorfman J.H., and Kramer E. 2010. Evaluating the impact of government land use policies on tree canopy coverage. Land Use Policy , 27 :407 - 414.

Hillier B. and Hanson J. 1984. The Social Logic of Space. Cambridge University Press, Cambridge, UK. pp281

Hitchmough J.D., and Bonugli A.M. 1997. Attitudes of Residents of a Medium Sized Town in South West Scotland to Street Trees. Landscape Research , 22 :327 - 337.

Howard E. 1898. Garden Cities of To-Morrow (1965 reprint). Faber, London. pp165.

Hwang R-L., Lin T-P., Cheng M-J. and Lo J-H. 2010. Adaptive Comfort Model for Tree-Shaded Outdoors in Taiwan. Building and Environment , 45 :1873 - 1879.

Intergovernmental Panel on Climate Change (IPCC). 2007. Climate Change 2007 - Summary for Policymakers . http://www.ipcc.ch/pdf/assessment- report/ar4/syr/ar4_syr_spm.pdf Accessed 11/08/08.

Iverson L.R., and Cook E.A. 2000. Urban Forest Cover of the Chicago Region and its Relation to Household Density and Income. Urban Ecosystems , 4:105 - 124.

Jenerette G.D., Harlan S.L., Brazel A., Jones N., Larsen L. and Stefanov W.L. 2007. Regional Relationships Between Surface Temperature, Vegetation and Human Settlement in a Rapidly Urbanizing Ecosystem. Landscape Ecology , 22 :353 - 365.

Jensen R, Gatrell J., Boulton J., and Harper B. 2004. Using Remote Sensing and Geographic Information Systems to Study Urban Quality of Life and Urban Forest Amenities. Ecology and Society , 9:5 - 14.

Jim C.Y., and Liu H.T. 2001. Patterns and Dynamics of Urban Forests in Relation to Land Use and Development History in Guangzhou City, China. Geographical Journal , 167 :358 - 375.

Jim C.Y., and Chen S. 2003. Variations of the Treescape in Relation to Urban Development in a Chinese City: The Case of Nanjing. Professional Geographer , 55 :70 - 82.

Jim C. Y., and Chen W. Y. 2006. Perception and Attitude of Residents toward Urban Green Spaces in Guangzhou (China). Environmental Management , 38 :338 - 349.

Jim C.Y., and Chen W.Y. 2008. Assessing the Ecosystem Service of Air Pollutant Removal By Urban Trees in Guangzhou (China). Journal of Environmental Management , 88 :665 - 676.

271 Jim C. Y., and Chen W.Y. 2009. Diversity and Distribution of Landscape Trees in the Compact Asian City of Taipei. Applied Geography , 29 :577 - 587.

Jones R. H., Chappelka A. H. and West D. H. 1996. Use of Plastic Shelters for Low- Cost Establishment of Street Trees. Southern Journal of Applied Forestry , 20 (2): 85 - 89.

Kaufman D.A., and Cloutier N.R. 2006. The Impact of Small Brownfields and Greenspaces on Residential Property Values. Journal of Real Estate Finance and Economics , 33 :19 - 30.

Kim T.K., Horner M.W. and Marans R.W. 2005. Life Cycle and Environmental Factors in Selecting Residential and Job Locations. Housing Studies , 20 :457 - 473.

King B.P., and Harrison S.J. 1998. Throughfall Patterns Under an Isolated Oak Tree. Weather , 53 :111 - 121.

Kirnbauer M C, , Kenney W.A., Churchill C. J., and Baetz B. W. . 2009. A Prototype Decision Support System for Sustainable Urban Tree Planting Programs. Urban Forestry & Urban Greening , 8:3 - 19.

Kjelgren R., and Montague T. 1998. Urban Tree Transpiration Over Turf and Asphalt Surfaces. Atmospheric Environment , 32 :35 - 41.

Konijnendijk C C . 2004. Enhancing the Forest Science-Policy Interface in Europe: Urban Forestry Showing the Way. Scandinavian Journal of Forest Research , 19 :123 - 128.

Konijnendijk C.C., Ricard R.M., Kenney A. and Randrup T.B. 2006. Defining Urban Forestry – A Comparative Perspective of North America and Europe. Urban Forestry and Urban Greening, 4 (3-4): 93-103.

Kuo F.E., Bacaicoa M. and Sullivan W.C. . 1998. Transforming Inner-City Landscapes: Trees, Sense of Safety and Preference. Environment and Behaviour , 30 :28 - 59.

Kuo F E, and W. C. Sullivan 2001. Environment and Crime in the Inner City - Does Vegetation Reduce Crime? Environment and Behaviour , 33 :343 - 367.

Lafortezza R, Carrus G, Sanesi G and Davies C . 2009. Benefits and Well-Being Perceived by People Visiting Green Spaces in Periods of Heat Stress. Urban Forestry & Urban Greening , 8:97-108.

Land Use Consultants (LUC). 1993. Trees in Towns . Department of the Environment, UK Government.

Landry S M, and Chakraborty J. . 2009. Street Trees and Equity: Evaluating the Spatial Distribution of an Urban Amenity. Environment and Planning A 41(11): 2651- 2670. , 41 :2651 - 2670.

Landry S., and Pu R. L. 2010. The Impact of Land Development Regulation on Residential Tree Cover: An Empirical Evaluation Using High-Resolution IKONOS Imagery. Landscape and Urban Planning , 94 :94 - 104.

Laverne R.J., and Winson-Geideman K. 2003. The Influence of Trees and Landscaping on Rental Rates at Office Buildings. Journal of Arboriculture , 29 :281 - 290. 272 Lawrence H.W. 2008. City Trees: A Historical Geography from the Renaissance through the Nineteenth Century , University of Virginia Press, Charlottesville, Virginia, USA.

Lee B.J. J T Y, Wang W., and Namgung M. 2009. Design Criteria for an Urban Sidewalk Landscape Considering Emotional Perception. Journal of Urban Planning and Development , 135 :133 - 140.

Leuzinger S., Vogt R., and Körner C. . 2010. Tree Surface Temperature in an Urban Environment. Agricultural and Forest Meteorology , 150 :56 - 62.

Lewis B. L., and Boulahanis J. G. . 2008. Keeping Up the Urban Forest: Predictors of Tree Maintenance in Small Southern Towns in the United States. Arboriculture & Urban Forestry , 34 :41 - 46.

Librett J.J., Yore M.M. and Schmid T.L. 2006. Characteristics of Physical Activity Levels Among Trail Users in a US National Sample. American Journal of Preventative Medicine , 31 :399 - 405.

Lohr V.I., Pearson-Mims C.H., Tarnai J. and Dillman D.A. 2004. How Urban Residents Rate and Rank the Benefits and Problems Associated With Trees In Cities. Journal of Arboriculture , 30 :28 - 35.

London Sustainability Exchange. 2004. Environmental Justice in London. http://www.lsx.org.uk/docs/page/2604/Environmental%20Justice%20in%20London%20- %20Linking%20the%20Equalities%20and%20Environment%20Policy%20Agendas.pdf Accessed 15/08/08.

MacFarlane D W. 2009. Potential Availability of Urban Wood Biomass in Michigan: Implications for Energy Production, Carbon Sequestration and Sustainable Forest Management in the USA. Biomass & Bioenergy , 33 :628 - 634.

Maas J, Spreeuwenberg P, Van Winsum-Westra M, Verheij R A, de Vries S and Groenewegen P P . 2009. Is Green Space in the Living Environment Associated with People's Feelings of Social Safety? Environment and Planning A , 41 :1763-1777.

Manchester City Council. 2008. About Hulme Park. http://www.manchester.gov.uk/site/scripts/documents_info.php?documentID=1490 Accessed 9/7/08.

Marshall S. 2005 . Streets and Patterns . Spon, London, UK. pp318

McDonald A G, , Bealey, W. J., Fowler, D., Dragosits, U., Skiba, U., Smith, R. I., Donovan, R. G., Brett, H. E., Hewitt, C. N., and Nemitz, E. 2007. Quantifying the Effect of Urban Tree Planting on Concentrations and Depositions of PM10 in Two UK Conurbations. Atmospheric Environment , 41 :8455 - 8467.

McPherson G.E. S, J.R., Xiao Q., Wu C. 2008. Los Angeles 1-Million tree canopy cover assessment - General Technical Report PSW-GTR-207, pp. 52.

McPherson E.G., Scott K.I. and James R. Simpson 1998. Estimating Cost Effectiveness of Residential Yard Trees for Improving Air Quality in Sacramento, California, Using Existing Models. Atmospheric Environment , 32 :75 - 84.

273 McPherson E.G., Nowak D.J. and Rowntree R.A. 1994. Chicago's Urban Forest Ecosystem: Results of the Chicago Urban Forest Climate Project : General Technical Report NE-186. USDA Forest Service, Northeastern Forest Experiement Station, Radnor, Pennsylvania, USA.

Milton Keynes Council . 2004. A Plan for a New City. http://www.mkweb.co.uk/Milton%5FKeynes%5FGeneral/DisplayArticle.asp?ID=285 Accessed 8/7/2008.

Mitchell R. and Popham F. . 2007. Greenspace, Urbanity and Health: Relationships in England. Journal of Epidemiology and Community Health , 61 :681-683.

Mitchell R. and Popham F . 2008. Effect of Exposure to Natural Environment on Health Inequalities: an Observational Population Study. Lancet , 372 :1655-1660.

National Soil Resources Institute. 2004. Soils Site Reporter. http://www.landis.org.uk/index.cfm Accessed 25/9/2009

Netusil N R, , Chattopadhyay S. and Kovacs K. F. 2010. Estimating the Demand for Tree Canopy: A Second-Stage Hedonic Price Analysis in Portland, Oregon. Land Economics , 86 :281 - 293.

Nicholson-Lord N. 1987. The Greening of the Cities , London: Routledge and Kegan Paul.

Nowak D.J., Cardelino C.A., Rao S.T. and Taha H. 1998. Estimating Cost Effectiveness of Residential Yard Trees for Improving Air Quality in Sacramento, California, Using Existing Models Atmospheric Environment , 32 :2709 - 2710.

Nowak D.J., Civerolo K.L.Trivikrama Rao S., Sistla G., Luley C.J. and Crane D.E . 2000. A Modeling Study of the Impact of Urban Trees on Ozone. Atmospheric Environment , 34:1601 - 1613.

Nowak D.J., Crane D.E. and Stevens J.C. 2006. Air Pollution Removal by Urban Trees and Shrubs in the United States. Urban Forestry and Urban Greening , 4:115 - 123.

O'Brien E. 2004. Social and Cultural Values of Woodlands in Northwest and Southeast England. http://www.forestry.gov.uk/fr/INFD-5Z5CDR Accessed 20/04/2010.

O'Brien E. 2006. Social Housing and Green Space: A Case Study in Inner London. Forestry , 79 :535 - 551.

Orland B., Vining J. and Ebreo A. 1992. The Effect of Street Trees on Perceived Values of Residential Property. Environment and Behaviour , 24 :298 – 325

Ozguner H. and Kendle AD . 2006. Public Attitudes towards Naturalistic versus Designed Landscapes in the City of Sheffield (UK). Landscape and Urban Planning , 74 :139 - 157.

Parr H. 2007. Mental Health, Nature Work, and Social Inclusion. Environment and Planning D: Society and Space , 25 :537 - 561.

Pauleit S., and Duhme F. 2000. Assessing the Environmental Performance of Land Cover Types for Urban Planning. Landscape and Urban Planning , 52 :1 - 20. 274 Pauleit S., Jones N., Garcia-Martin G., Garcia-Valdecantos J.L., Rivière L.M, Vidal-Beaudet L., Bodson M., and Randrup T.B. 2002. Tree Establishment Practice in Towns and Cities – Results from a European Survey Urban Forestry & Urban Greening , 1(2):83 - 96.

Pauleit S., Golding Y and Ennos R. 2005. Modelling the Environmental Impacts of Urban Land Use and Land Cover Change: A Study in Merseyside, UK. Landscape and Urban Planning , 71 :295 - 310.

Payton S., Lindsey G., Wilson J., Ottensmann J. R., and Man J. 2008. Valuing the Benefits of the Urban Forest: A Spatial Hedonic Approach. Journal of Environmental Planning and Management , 51 :717-736.

PBRS. 2007. Northwest Natural Environment Index 2007. http://www.pbrs.org.uk/applications_content.php?ID=77 Accessed 28/3/2010.

Perkins H.A., Heynen N. and Wilson J. 2004. Inequitable Access to Urban Reforestation: the Impact of Urban Political Economy on Housing Tenure and Urban Forests. Cities , 21 :291 - 299.

Pincetl S . 2010. Implementing Municipal Tree Planting: Los Angeles Million-Tree Initiative. Environmental Management , 45 :227 - 238.

Pitt M. 2008. The Pitt Review: Learning Lessons for the 2007 Floods. HMSO, UK Government. Available at: http://archive.cabinetoffice.gov.uk/pittreview/thepittreview/final_report.html Accessed 13/8/2010

Pretty J, Peacock J, Hine R, Sellens M, South N and Griffin M . 2007. Green Exercise in the UK Countryside: Effects on Health and Psychological Well-Being, and Implications for Policy and Planning. Journal of Environmental Planning and Management , 50 :211-231.

Prezza M, Alparone, F. R., Cristallo, C., and Luigi, S. 2005. Parental Perception of Social Risk and of Positive Potentiality of Outdoor Autonomy for Children: The Development of Two Instruments. Journal of Environmental Psychology , 25 :437 - 453.

Ponce V.M., and Hawkins R.H. 1996. Runoff Curve Number: Has It Reached Maturity? Journal of Hydrologic Engineering , 1:11 – 19

Population Reference Bureau. 2009. 2009 World Population Data Sheet http://www.prb.org/pdf09/09wpds_eng.pdf Accessed 11/05/2010.

Red Rose Forest . 2010a. Forest Projects: Green Streets. Available at http://www.redroseforest.co.uk/web/content/view/43/143/ Accessed 3/6/2010.

Red Rose Forest. 2010b. About Red Rose Forest. http://www.redroseforest.co.uk/web/content/view/125/182/ Accessed 24/05/2010.

Rishbeth C and Finney N. 2006. Novelty and Nostalgia in Urban Greenspace: Refugee Perspectives. Tijdschrift Voor Economische En Sociale Geografie, 97: 281-295.

Robinson G.M. 1998. Methods and Techniques in Human Geography , Wiley. Chicester, UK: 275 Roemmich J.N., Epstein L.H., Raja S., Yin L., Robinson J. and Winiewicz D. 2006. Association of Access to Parks and Recreational Facilities with the Physical Activity of Young Children. Preventive Medicine , 43 :437 - 441.

Rudlin D. and Falk N. 1999. Sustainable Urban Neighbourhood: Building the 21st Century Home. Architectural Press, London, UK. pp344.

Ruliffson J A, Gobster, P. H., Haight, R. G. and Homans, F. R. 2002. Niches in the Urban Forest: Organizations and their Role in Acquiring Metropolitan Open Space. Journal of Forestry , 100 :16 - 23.

Samba S.A.N, Camiré C. and Margolis H.A. 2001. Allometry and Rainfall Interception of Cordyla pinnata in a Semi-Arid Agroforestry Parkland, Senegal. Forest Ecology and Management , 154 :277 - 288.

Schroeder H W. 1989. Aesthetic Perceptions of the Urban Forest: A Utility Perspective. Journal of Arboriculture , 15 :292 - 294.

Schroeder H.W., and Ruffalo S.R. 1996. Householder Evaluations of Street Trees in a Chicago Suburb. Journal of Arboriculture , 22 :35 - 43.

Schroeder H.W., Green T.L. and Howe T.J. 2003. Community Tree Programs in Illinois, U.S.: a Statewide Survey and Assessment. Journal of Arboriculture , 29 :218 - 225.

Schroeder H., Flannigan J. and Coles R. 2006. Residents’ Attitudes Toward Street Trees in the UK and U.S. Communities. Arboriculture and Urban Forestry , 32 :236 - 246.

Seklizotis S. 1980 . A Survey of Urban Open Space Using Colour Infra-red Aerial Photographs. PhD Thesis, University of Aston, Aston, UK.

Shashua-Bar L., and Hoffman M.E. 2004. Quantitative Evaluation of Passive Cooling of the UCL Microclimate in Hot Regions in Summer - Case Study: Urban Streets and Courtyards with Trees. Building and Environment , 39 :1087 - 1099.

Sheets V.L., and Mazer C.D. 1991. Affect, Cognition, and Urban Vegetation: Some Effects of Adding Trees Along City Streets. Environment and Behaviour , 23 :285 - 304.

Silverman D . 2005. Doing Qualitative Research , Sage, London, UK. pp395.

Simpson J.R., and McPherson E.G. 1998. Simulation of Tree Shade Impacts on Residential Energy Use for Space Conditioning in Sacramento. Atmospheric Environment , 32 :69 - 74.

Sipila M., and Tyrvainen L. 2005. Evaluation of Collaborative Urban Forest Planning in Helsinki, Finland. Urban Forestry & Urban Greening , 4:1 - 12.

Smiley E.T., Calfee L., Fraedrich B.R., Smiley E.J. 2006. Comparison of Structural and Noncompacted Soils for Trees Surrounded by Pavement. Arboriculture and Urban Forestry 32 (4): 164 - 169.

Soil Conservation Service (SCS). 1972. SCS National Engineering Handbook, Section 4, U.S. Dept. of Agriculture, Washington, D.C.

276 Solecki W.D., Rosenzweig C., Parshall L., Pope G., Clark M., Cox J. and Wiencke M. 2005. Mitigation of the Heat Island Effect in Urban New Jersey. Environmental Hazards , 6:39 - 49.

Stake R. 2000. Case Studies (p435 - 54). In Denzin N. and Lincoln Y. (eds.) Handbook of Qualitative Research, 2nd ed. Sage, Thousand Oaks, California, USA

Statistical Program for Social Scientists (SPSS). version 15.

Stovin V.R., Jorgensen A. and Clayden A. 2008. Street Trees and Stormwater Management. Arboricultural Journal , 30 :297 - 310.

Summit J., and Sommer R. 1998. Urban Tree Planting Programs - A Model for Encouraging Environmentally Protective Behaviour. Atmospheric Environment , 32 (1):1 - 5.

Talarchek G. 1990. The Urban Forest of New Orleans: An Exploratory Analysis of Relationships. Urban Geography , 11 :65 - 86.

Tame I.D. 2006. Developing an Intervention Plan to Challenge the Environmental Inequity of Urban Trees. Master’s Thesis, Planning and Landscape Department, School of Environment and Development . University of Manchester.

Tennessen C.M, and Cimprich B. 1995. Views to Nature: Effects on Attention. Journal of Environmental Psychology , 15 :77 - 85.

Thach T-Q., Wong C-M., Chan K-P., Chau Y-K., Chung Y-N., Ou C-Q., Yang L. and Hedley A.J. 2010. Daily Visibility and Mortality: Assessment of Health Benefits from Improved Visibility in Hong Kong. Environmental Research , 110 (6):617 - 623.

The Tree Council. 2010. Tree Wardens – Homepage. http://www.treecouncil.org.uk/?q=tree-wardens-homepage Accessed 17/05/2010.

Tippett J. 2004. “Think Like an Ecosystem” – Embedding a Living System Paradigm Into Participatory Planning. Systemic Practice and Action Research , 17 (6):603 - 622.

Tippett J., Handley J.F. and Ravetz J. 2007. Meeting the Challenges of Sustainable Development—A Conceptual Appraisal of a New Methodology for Participatory Ecological Planning. Progress in Planning , 67 (1):9 - 98.

Tratalos J, , Fuller R. A., Warren P. H., Davies R. G. and Gaston K. J. 2007. Urban Form, Biodiversity Potential and Ecosystem Services. Landscape and Urban Planning , 83 :308 - 317.

Trieman T, , and Gartner J. 2004. Community Forestry in Missouri, U.S: Attitudes and Knowledge of Local Officials. Journal of Arboriculture , 30 :205 - 213.

Trees for Cities. 2010. FAQs. http://www.treesforcities.org/page.php?id=55 Accessed 17/05/2010.

Tree Ground Solutions. 2010. Tree Ground Solutions, Specialist in Growth Area Facilities. www.tgs.nl Accessed 13/05/2010.

277 Troy A.R., Grove J.M., O'Neil-Dunne J.P.M., Pickett S.T.A. and Cadenasso M.L. 2007. Predicting Opportunities for Greening and Patterns of Vegetation on Private Urban Lands. Environmental Management , 40 :394 - 412.

Trudgill S. 1990. Barriers to a Better Environment . Belhaven Press, Pinter Publishers, London, UK. pp151.

Tsiros I.X. 2010. Assessment and Energy Implications of Street Air Temperature Cooling by Shade Trees in Athens (Greece) Under Extremely Hot Weather Conditions. Renewable Energy , 35 :1866 - 1869.

Tso C.P., Chan B.K. and Hashim M.A. 1991. Analystical Solutions to the Near-Neutral Atmospheric Surface Energy Balance with and without Heat Storage for Urban Climatological Studies. Journal of Applied Meterology , 30 :413 - 424.

Turner T. 1995. Greenways, Blueways, Skyways and Other Ways to a Better London. Landscape and Urban Planning. 33 : 269-282.

Tyrvainen L . 1997. The Amenity Value of the Urban Forest: An Application of the Hedonic Pricing Method Landscape and Urban Planning , 37 :211 - 222.

Tyrvainen L and Miettinen A . 2000. Property Prices and Urban Forest Amenities. Journal of Environmental Economics and Management , 39 :205-223.

Tyrvainen L . 2001. Economic Valuation of Urban Forest Benefits in Finland. Journal of Environmental Management , 62 :75 – 92

Ulrich R.S . 1984. View Through a Window May Influence Recovery From Surgery. Science , 224 :420 - 421.

Ulrich R.S. S R F, Losito B.D., Fiorito E., Miles M.A. and Zelson M. 1991. Stress Recovery During Exposure to Natural and Urban Environments. Journal of Environmental Psychology , 11 :201 - 230.

UKCP09. 2009. U.K. Climate Projections User Interface. http://ukcp09.defra.gov.uk/ Accessed 15/10/2009.

USDA. Urban Forests, Environmental Quality and Human Health / Publications and Products / Tools / Aerial Photo Interpretation Tool. Available from http://nrs.fs.fed.us/units/urban/pubs/tools/ Accessed 14/7/09.

Vesely E.T. 2007. Green for Green: The Perceived Value of a Quantitative Change in the Urban Tree Estate of New Zealand. Ecological Economics , 63 :605 - 615.

Viana H., Coen W.B., Lopes D. and Aranha J. 2010. Assessment of Forest Biomass for Use as Energy. GIS-based Analysis of Geographical Availability and Locations of Wood-Fired Power Plants in Portugal. Applied Energy , 87 (8): 2551 - 2560.

Warrington Borough Council. 2006 . Open Space Review. http://www.warrington.gov.uk/images/OSR%202006%20Final%20Report_tcm15- 11079.pdf Accessed 15/6/2008.

278 Watkins R., Palmer J. and Kolokotroni M. 2007. Increased Temperature and Intensification of the Urban Heat Island: Implications for Human Comfort and Urban Design. Built Environment , 33 :85 - 96.

Watson W.T. 2005. Influence of Tree Size on Transplant Establishment and Growth. HortTechnology , 15 (1):118 - 122.

West D. H., Chappelka A.H., Tilt K.M., Ponder H.G., and Williams J.D. 1999. Effect of Tree Shelters on Survival, Growth, and Wood Quality of 11 Tree Species Commonly Planted in the Southern United States. Journal of Arboriculture , 25 (2):69 - 75.

Whitford V., Ennos A.R. and Handley J.F. 2001. "City Form and Natural Process" - Indicators for the Ecological Performance of Urban Areas and their Application to Merseyside, UK. Landscape and Urban Planning , 57 :91 - 103.

Williams K. 2002. Exploring Resident Preferences for Street Trees in Melbourne, Australia. Journal of Arboriculture , 28 :161 – 170

Wirral Council. 2008 . Birkenhead Park. http://www.wirral.gov.uk/LGCL/100006/200073/670/content_0001109.html Accessed 3/7/08.

Wolf K.L. 2008. Community Context and Strip Mail Retail Public Response to the Roadside Landscape. Transportation Research Record , 2060 :95 - 103.

Wood A.M., Harrison R.M., Semple S., Ayres J.G. and Stockley R.A. 2010. Outdoor Air Pollution is Associated with Rapid Decline of Lung Function in Alpha-1-antitrypsin Deficiency. Occupational and Environmental Medicine , 67 (8):556 - 561.

Wu C, Xiao Q. McPherson, G.E. 2008. A Method for Locating Potential Tree-Planting Sites in Urban Areas: A Case Study of Los Angeles, USA. Urban Forestry & Urban Greening 7(2): 65-76. , 7:65 - 76.

Xiao Q. M E G, Ustin S., Grismer M. and Simpson J.R. 2000. Winter Rainfall Interception by Two Mature Open-Grown Trees in Davis, California. Hydrological Processes , 14 :763 - 784.

Zhang Y., Hussain A., Deng J. and Letson N. 2007. Public Attitudes Toward Urban Trees and Supporting Urban Tree Programs. Environment and Behaviour , 39 :797 - 814.

279 Appendix 1. Cover Letter and Questionnaire Exploring Residents’ Attitudes Towards Trees

Centre for Urban and Regional Ecology 2.10 Humanities Bridgeford Street University of Manchester Oxford Road Manchester M13 9PL 0161 2756920

Wednesday 4 th February Dear Resident

The Red Rose Forest and the University of Manchester are conducting some research to find out residents’ views about trees in their local area and street.

Your street has been selected as an area of interest in this study, and your views on street trees will form an important part of this research.

The research is in the form of a questionnaire, which is attached overleaf. This questionnaire will ask about your thoughts, feelings and opinions about your street, the trees in your street and trees more generally. Any comments about trees are welcome, whether they are good or bad. Comments about the Green Streets programme are also welcome, and will help improve future projects.

You can answer this questionnaire in 3 ways:

1) Answer the questionnaire overleaf and post it back to us using the enclosed pre-paid envelope, or through the letterbox of 5 Whitehead Road (the Green Streets Champion Anne Rockliffe). 2) Answer it online at [http://snipurl.com/avg90] 3) Answer the questions in person when we visit your street on: [date] between 5:30PM and 7PM If you would not like to be disturbed on this evening, or have already completed this questionnaire, please place the reverse of this letter in your window or door displaying the appropriate message and we will not visit you.

We hope that you will choose to answer this questionnaire, and that you will enjoy taking part in our research.

Thank you in advance

Justine Hall Centre for Urban and Regional Ecology University of Manchester [email protected]

280 Questions Sent to All Residents

Thank you for agreeing to take part in this survey. The results will inform a study at the University of Manchester and the future work of the Red Rose Forest.

Firstly, some questions about trees generally:

1). Do you consider trees to be an important part of your everyday life? [ ] Yes [ ] No [ ] Never thought about it

2). Please could you rate the following statements about trees by circling your answer, from 1-strongly agree, to 4-strongly disagree. Please circle ‘8’ if you don’t know or are unsure about a statement, or if you think it is not applicable to you.

Strongly Strongly Don’t agree disagree know Trees are important to my quality of life 1 2 3 4 8 Trees can play an important part in stopping climate 1 2 3 4 8 change Trees are important as they provide resources such as 1 2 3 4 8 wood and fruit to humans Trees help me tell the changing of the seasons 1 2 3 4 8 Trees are important in town centres because they 1 2 3 4 8 shade and cool their surroundings Trees in cities help people feel better and less stressed 1 2 3 4 8 Trees should be planted in town centres to reduce 1 2 3 4 8 smog and dust from cars and buses Trees should be planted in cities because they reduce 1 2 3 4 8 noise Trees in shopping areas makes it a nicer place to spend 1 2 3 4 8 time and shop Trees should be planted in cities because they are 1 2 3 4 8 associated with soothing sounds such as rustling leaves and bird song Trees should be planted in cities to attract wildlife 1 2 3 4 8 Trees should be planted in cities as they provide a link 1 2 3 4 8 with nature and the countryside Trees should be planted in residential areas as they 1 2 3 4 8 reduce the risk of flooding Trees are a problem in cities because they cause 1 2 3 4 8 allergies Trees should not be used in town centres because they 1 2 3 4 8 block shop signs and get in people’s way Trees should not be planted because their roots crack 1 2 3 4 8 pavements Trees should be removed from cities because they can 1 2 3 4 8 fall across power lines, cars, houses or fall on people Trees should not be used in cities because they make it 1 2 3 4 8 difficult to detect criminal behaviour Trees should not be planted along streets because they 1 2 3 4 8 drip sap or sticky substances on parked cars Trees should not be planted along streets as they 1 2 3 4 8 reduce space for car parking Trees should not be planted in cities as they increase 1 2 3 4 8 dog mess and litter 281

Trees should not be planted in residential streets as 1 2 3 4 8 their roots could damage house foundations and boundary walls Trees should not be planted in cities as they can block 1 2 3 4 8 out sunshine and street lights Trees should not be planted in cities because they are 1 2 3 4 8 ugly when they are not maintained Trees grow too high to be planted in residential streets 1 2 3 4 8 Trees should not be planted in cities because they cost 1 2 3 4 8 the council too much

Now, some questions about the street where you live:

3). How long have you lived in your current home? ______years ______months

4). What activities happen on your street? (tick all that apply) [ ] Car parking [ ] Children playing [ ] Meeting neighbours/socialising [ ] Cars driving between two main roads [ ] Other______

5). What do you like about your street? (tick all that apply) [ ] Friendly neighbours [ ] The street looks well cared for [ ] The road and pavements are clean and smooth (no potholes or cracks) [ ] There’s a sense of street community [ ] Good location [ ] Other______

6). What problems (if any) exist on your street? [ ] Too much traffic [ ] Rubbish/litter [ ] Vandalism/Noisy gangs of children [ ] Not enough car parking space [ ] Feels unsafe at night [ ] Other______

7). What could improve your street? (tick all that apply) [ ] Less traffic [ ] More car parking space [ ] More/better trees and flowers [ ] Better street lighting [ ] Place for children to play [ ] More community spirit [ ] Other______

282 Please could you fill in some information about yourself? Some researchers have suggested that things like income, culture and education affect people’s views about trees, and we would like to investigate this here in Manchester. This information will be kept completely confidential and will not be linked to you, your house number or street and will only be used in this research.

1). How old are you? [ ] 18 – 21 [ ] 22 – 30 [ ] 31 – 40 [ ] 41 – 50 [ ] 51 – 60 [ ] Over 60

2). What is your job status? [ ] I do not work [ ] I do not work due to illness [ ] I work part time [ ] I work full time

3) What would you say your income is? [ ] Under £10,000 [ ] £10,000 to £15,000 [ ] £15,000 to £20,000 [ ] £20,000 to £25,000 [ ] £25,000 to £30,000 [ ] £30,000 plus.

4). What is your residential status? [ ] Own my own home [ ] Rent from private landlord [ ] Rent from Housing Association [ ] Other______

5). Do you own a car? [ ] Yes [ ] No

6). What is your ethnic group? Choose ONE section from A to E, then the appropriate box to indicate your ethnic group. A White [ ] British [ ] Irish Any Other White background, please write in ______

B Mixed [ ] White and Black Caribbean [ ] White and Black African [ ] White and Asian Any Other Mixed background, please write in______

C Asian or Asian British [ ] Indian [ ] Pakistani [ ] Bangladeshi Any Other Asian background, please write in______

D Black or Black British [ ] Caribbean [ ] African 283 Any Other Black background, please write in______

E Chinese or other ethnic group [ ] Chinese Any Other, please write in______

7). Do you have any educational qualifications? (please tick all that apply) [ ] No formal qualifications [ ] GCSEs/O-Level/other exams taken at age 16 [ ] A-Levels/other exams taken at age 18 [ ] NVQs [ ] HND [ ] Undergraduate degree (e.g. BSc, BA) [ ] Postgraduate degree (e.g. MSc, MA, PhD) [ ] Other professional qualifications (e.g. for plumber, electrician, builder, hairdresser)

Thank you for taking part in our research.

284 Questions Sent to Those in ‘Trees’ Streets

Now, some questions about the trees in your street:

8). Do you like the trees in your street? [ ] Yes [ ] No Comments:______

9). What effects do you think the trees in your street have? [ ] Street looks more cared for than nearby streets without trees [ ] Trees cool the street [ ] Provide space for wildlife [ ] Clean the air of pollution [ ] Makes the street more attractive [ ] Makes the street feel friendlier [ ] Create too much litter from leaf and fruit fall [ ] Drip sticky substances onto cars [ ] Prevent cars parking [ ] Crack the pavements with their roots [ ] Leaves and berries make pavements slippery [ ] Trees block sunshine coming into my home [ ] Other______Which ONE effect do you think is most important? ______

10). Do you think the trees affect house prices in your street? [ ] Yes [ ] No If yes, do you think houses prices on your street are more or less than neighbouring streets without trees? [ ] More [ ] Less

11). If you were to move house, would you try to move to a street with trees? [ ] Yes, definitely [ ] Yes, probably [ ] Would not matter to me [ ] Probably not [ ] No

12). After completing this questionnaire, do you consider trees to be important to your everyday life? [ ] Yes [ ] No

Questions Sent to Those in ‘No Trees’ Streets

Now, some questions about street trees:

8). Why do you think your street doesn’t have trees? [ ] There’s not enough space for trees [ ] No one likes trees here [ ] The council can’t afford trees here [ ] Trees would get damaged if they were planted here [ ] Trees grow too high to be planted here [ ] Trees would stop cars parking on the street [ ] Other______

9). Would you like trees to be planted here? [ ] Yes [ ] No Comments:______

10). Do you think if trees were planted they would affect house prices in your street? [ ] Yes [ ] No If yes, do you think they will: [ ] Increase in price [ ] Decrease in price

11). If you were to move house, would you try to move to a street with trees? [ ] Yes, definitely [ ] Yes, probably [ ] Would not matter to me [ ] Probably not [ ] No

12). After completing this questionnaire, do you consider trees to be important to your everyday life? [ ] Yes [ ] No

286 Questions Sent to Those in ‘Pre Green Streets’

Now, some questions about the trees in your street:

9). Do you think the trees planted by Red Rose Forest will make a difference to your street? [ ] Yes [ ] No If yes, in what way? [ ] Street will look more cared for [ ] Neighbours will talk more [ ] There will be more wildlife [ ] The street will feel friendlier [ ] The street will feel less polluted [ ] There will be less space to park cars [ ] There will be more litter due to leaf fall [ ] The leaves will make the pavements slippery [ ] Other (please specify) ______

10). Do you think the planting of the trees will affect house prices in your street? [ ] Yes [ ] No If yes, do you think they will: [ ] Increase in price [ ] Decrease in price

11). Would you encourage your friends and family to take part in a Green Streets project? [ ] Yes [ ] No Comments:______

12). Do you think your views about trees will change as a result of being part of a Green Streets project? [ ] Yes [ ] No

13). If you were to move house, would you try to move to a street with trees? [ ] Yes, definitely [ ] Yes, probably [ ] Would not matter to me [ ] Probably not [ ] No

14). After completing this questionnaire, do you consider trees to be important to your everyday life? [ ] Yes [ ] No

287 Questions Sent to Those in ‘Post Green Streets’

Now, some questions about the trees in your street:

8). Do you like the trees that have been planted in your street by Red Rose Forest? [ ] Yes [ ] No Comments:______

9). Have the trees made a difference to your street? [ ] Yes [ ] No [ ] I moved in after the trees were planted (please skip to question 13) If yes, how have they made a difference? [ ] Street looks more cared for [ ] Neighbours are talking more now [ ] More wildlife [ ] Street feels friendlier [ ] Street feels less polluted [ ] Less space to park cars [ ] More litter [ ] Leaves and berries have made pavements slippery [ ] Trees block sunlight coming into my home [ ] Other______

10). Do you think the planting of the trees has affected house prices in your street? [ ] Yes [ ] No If yes, do you think they have: [ ] Increased in price [ ] Decreased in price

11). Would you encourage your friends and family to have a Green Streets project in their street? [ ] Yes [ ] No Comments:______

12). Has being involved in the Green Streets project changed your view on trees? [ ] Yes [ ] No If yes, could you say how? [ ] I like trees a bit more now [ ] I like trees a lot more now [ ] I am more aware of trees around me [ ] I would like to see more trees planted elsewhere [ ] Other______Comments:______

13) Are there any maintenance issues with the trees? [ ] Yes [ ] No Details:______

14). If you were to move house, would you try to move to a street with trees? [ ] Yes, definitely [ ] Yes, probably [ ] Would not matter to me [ ] Probably not [ ] No

15). After completing this questionnaire, do you consider trees to be important to your everyday life? [ ] Yes [ ] No

288 Appendix 2. ‘Barriers and Opportunities for Increasing Tree Cover within Urban Areas’: Summary of Practitioner Workshop Held On Monday 22 nd February 2010, at the University of Manchester

1. Introduction

The workshop began with an introduction by Professor John Handley, welcoming participants and detailing previous research that has led to the research to be presented today. This work includes a study for the Red Rose Forest in 2000, exploring possibilities for urban timber harvesting and examining tree distribution across different land types. Following this, a Masters’ dissertation (by Ian Tame) looked further into this data and found a link between levels of tree cover and health; in areas of fewer trees, residents reported poorer levels of health. A separate project, forming a PhD thesis by Susannah Gill, looked at urban morphology and climate change effects on urban heat island and urban run off levels, as part of the national Adaptation Strategies for Climate Change in the Urban Environment (ASCCUE) project. This found that in urban areas, increasing greenspace by 10% can keep temperatures around present day levels even in the high temperature climate scenarios of the 2080s.

These research projects have led to Justine’s research in high density residential areas, which are most affected by high temperatures. Justine is a both a scientist and social campaigner, so has also examined residents’ attitudes to trees and how more trees may be planted to protect these people from the high temperatures climate change will bring. David’s work is more practical, giving precise numbers to Susannah’s computer modelling work with experimental tree plots along the Oxford Road corridor, when the University of Manchester is situated.

2. Presentations

2.1 The role of trees in improving the environmental performance of urban areas

(David’s work will be published in an academic journal in the near future, so circulation of his presentation is not possible at this time. Here is a summary, and details of the journal article will, if possible, be circulated in due course.)

Over a 4 month period in the summer of 2009, an experiment was conducted to investigate the effect of trees and grassland areas upon the temperature balance of urban areas. This experiment used small test plots installed at the University of Manchester Botanical Grounds, where the surface and radiant temperatures of 4 different surface types (Tarmac, concrete, woodchip and grass) were recorded in the presence or absence of tree shade. This study showed that engineered surfaces such as Tarmac and concrete in full sun increased in temperature over twice as fast as air; this temperature gain could be reduced in the presence of tree shade to almost parity with the air temperature. Perhaps most importantly this study showed that grassed areas in full sun actually gained heat more slowly than engineered surfaces in shade. Measurements of radiant temperatures indicated that surface types had little bearing upon how comfortable a person would feel but tree shade could significantly reduce a person's temperature balance by over 8ºC making an individual more comfortable on hot days. This study has shown that trees could play a vital role in reducing the temperature balance of urban areas and may play an even greater role in making urban areas more comfortable places to live. ([email protected])

289 After this presentation, some questions were asked about how human discomfort may be quantified, as this is subjective and can vary wildly from person to person. A study cited by Professor Handley in Manchester and Lewes, West Sussex, decided to use temperatures over 24°C as the point as which human discomfort occurs, as this was when people questioned became conscious of greenery and shading effects for their comfort, answering that there should be more greenery in urban areas in temperatures over this level. Details about air temperatures were also asked about; studies have shown that within 2 hectares cooling could be found and there is significant air circulation within the city by fluxes and convection currents and these become more important as the scale increases.

2.2 The distribution of trees in high density housing areas

A previous study in Greater Manchester found that high density housing tends to have fewer trees than lower density housing, but some areas of high density housing do have a relatively large number of trees. This study classified high density housing into a further 11 categories, and found that tree cover within these types ranges from 1.6% to 14.8%. The housing types with lowest tree cover are terraces built before 1919, while semi- detached housing and 1960s flats/road-free housing have the highest tree cover. These housing categories were then ‘planted’ with trees, to the potential maximum number of new trees without financial or other constraints. This found that tree cover may be increased by between 4.8% and 10.5%, bringing levels of tree cover to between 10% and 20% across high density housing. These trees may be mainly planted into pavements and back gardens, with some in front gardens. This increase in tree cover is able to give reductions in maximum surface temperatures of around 4°C for the areas with very low existing tree cover, but much lower reductions in areas where existing tree cover is over 5%. A survey of residents found that residents of all street types and socioeconomic types are very positive and supportive about trees, and the most strongly disagreed with statement was ‘Trees should not be planted because they cost the council too much’. The study shows that there is potential to plant trees which can make a great difference to some high density housing areas, and that there is great resident support for trees. ([email protected])

After this presentation, the issues regarding garden size was raised; gardens are becoming smaller in new developments and the size of individual gardens will impact the number of trees which may be planted. The age of trees and their effectiveness at cooling an area was also addressed; it was suggested that there could be a recognition of age in the study as older trees (in a physiological sense) may close their stomata and have a lower impact on temperature than growing trees, as evapotranspiration, and so evaporative cooling, ceases. The amount of cooling trees provide is proportional to water loss and the growth of trees.

290 3. Discussions

Discussions took places around 4 themes: legislation, funding, residents and design. The discussions were recorded using a Ketso kit, a tool which allows linking of ideas, easy classification of thoughts and facilitates overall discussion as thoughts must be written rather than spoken in order to be recorded.

Due to the nature of the subject of ‘Barriers and Opportunities for Increasing Urban Tree Cover’ many of the discussion points crossed over between more than one theme; the discussions below have tried to address this but retain an idea of theme.

3.1 Legislation and planning

The current ‘streamlining’ of PPSs is leading to a loss of essential policy guidance – this should be stopped, or Government should keep them as archive documents for council use.

The problem of gardens being classified as brownfield land, and as such suitable for infill housing development, was highlighted by many participants as a major threat to urban trees and greenspace. Gardens should be classified as greenspace and treated as protected areas, not interpreted as areas for development under brownfield land policies.

It was noted that Green Infrastructure is at the heart of the 2012 Olympic Masterplan. If green infrastructure is incorporated at this high level then it should be incorporated in other plans.

3.1.1 Tree Preservation Orders

TPOs are seen as a good legislation tool, but the penalty for illegal felling by developers is not a deterrent, even though it is a criminal offence. It was suggested that there should be blanket conservation status for all trees over a certain size, following Germany’s example where this already occurs. All trees in conservation areas are protected under section 211, although precise conditions cannot be attached to this which can be a barrier to protection.

3.1.2 Other legislation that can be helpful

Existing and forthcoming legislation including the Local Government (Miscellaneous Provisions) Act 1982, the Highways Act 1980, the Hedgerow Act 1997, Hardstanding Surfaces regulations, Smokeless Zones and associated Clean Air legislation, the Climate Change Act, the Flooding and Water Management Bill (through both increasing tree cover for surface water management and through SUDS schemes) and more general common law were cited as being (potentially) helpful for tree protection. However, these laws require better enforcement and larger penalties. British Standard 5837:2005 (Trees in relation to construction) was also cited as being a useful tool to protect trees. Felling licences issued by the Forestry Commission were highlighted as a useful method for controlling tree cutting, although garden trees and trees in areas given planning permission are not covered by this law.

3.1.3 Government policies and themes which can include tree planting

Similarly, the Government’s Quality of Place strategy, Business Improvement Districts (BIDs), proposed Eco Towns and the Regional Forestry Framework give 291 opportunities to increase tree cover in urban areas. The development of Low Carbon Action Plans also gives potential to aid increases in tree cover. Conversely, many participants cited the Government’s aims of increasing housing density (part of PPS3) as a barrier to increasing tree cover in housing areas.

3.1.4 Future opportunities for change

New planning laws from the next government may bring opportunities for increasing tree cover. New planning legislation is required to back up the need for green infrastructure in design, and designing in GI with other critical services should occur. Compulsory street tree planting, maximising the street tree capacity could occur.

Research was seen as very important in its ability to drive forward legislation and in linking theory and practice; funding for research to back up the need for green infrastructure in design and to identify the economic benefits of trees, leading to a Standard Tree Valuation System were particular priorities. Research into finding a cost effective design for street trees and tree pits was also seen as an important topic.

3.1.5 Use of planning conditions

Planning conditions on developments to protect existing trees or increase tree cover are seen as very important, particularly investment in trees as part of new build, but the variations in planning officers means these conditions vary from development to development and place to place. For example, Sefton Council ask for a contribution to urban trees when planning consent is granted. Working to BS5837:2005 (Trees in relation to construction) guidance should be a condition of planning permission, and extending the establishment period for trees in new development from 2 years to 5 years should be considered, in order to ensure the tree will survive into the future. However, the present lack of tree health monitoring of development sites could be a barrier for this.

Planning conditions could include a condition to employ a consulting arboriculturist and to consult the Trees and Design Action Group’s ‘Right Tree Right Place’ resource. Conditions may also include greater involvement of tree officers and highways officers in the design of new developments at an early stage, however participants highlighted this idea as interesting but possibly problematic. Planning conditions that consider the landscape implications may also be helpful. In some cases tree planting against historic facades is not appropriate, and there needs to be more research and evidence to show this in applications.

3.2 Planning based barriers for tree planting

3.2.1 Strategy

Workshop participants stressed the importance of every local authority conducting and maintaining a Tree Inventory, preferably computerised. This can then feed into a Tree Strategy, highlighting areas of low tree cover and opportunities for further tree planting.

Councils’ lack of a Green Space/Green Infrastructure and/or Tree Strategy was seen as a barrier for protecting and increasing tree cover; a requirement for all councils to produce one would be a good first step to help raise the profile of trees. 292 The lack of a more general planting policy was also seen as a hindrance for increasing tree cover. Specifications for tree pits were seen as a barrier for increasing tree cover, possibly for the cost involved. The London Mayor’s Street Tree Initiative was noted as a good existing strategy to increase tree cover.

3.2.2 Housing transfers

The recent stock transfer of council housing to the private sector and to Arms Length Management Organisations (ALMOs) has led to a lack of management of trees and greenspace in many areas, and the introduction of Service Level Agreements (SLAs) between ALMOs and tree officers/planners could be a good opportunity to improve these features for residents.

The Right To Buy scheme for council houses was given as a reason behind urban deforestation as people buy their homes and cut down trees over concerns about liabilities.

3.2.3 Land ownership and insurance liabilities and issues

Land values and land ownership are issues for increasing tree planting, where the land is more valuable developed or the landowner does not agree to tree planting. One attendee cited the long arm of the developer using the law to rid places of trees in order to allow development.

Local authorities are selling their land assets, which can lead to loss of trees as the land is built on or redeveloped.

The potential for insurance claims is becoming more of a barrier for urban tree planting. Insurance companies now require residents to list all trees within the proximity of their home. This is a growing problem which is rarely backed up with evidence of tree damage, so education and awareness raising may help allay fears of root damage. There are reports of rogue tree surgeons playing on people’s vulnerability and fears about nearby trees and giving a poor level of service to both the tree and the residents. This is an over-reaction to health and safety concerns, which again may be allayed by education.

3.3 Planning based opportunities for funding

Section 106 agreements were praised for their ringfenced funding, which may be used for maintenance of existing parks and streets or for new planting.

The Community Infrastructure Levy was highlighted by many participants as potentially a more strategic version of section 106 funding methods. It is hoped that it will allow for more strategic off site mitigation of development and more strategic planning of trees and greenspace. Urban regeneration programmes and projects, such as the Housing Market Renewal (HMR) scheme, are seen as good ways to help improve the greenery of an area. Aligning your own project with a major scheme like this is an opportunity to get significant funding.

3.4 Communication issues within local authorities

Cross disciplinary communication in planning and management of trees was highlighted as a barrier to increasing urban tree cover. Not listening to landscape architects and 293 landscape architects themselves were also listed as barriers. The prominence and power of engineers in urban design was also highlighted as a problem, though an engineering based solution to in-street planting was agreed to be most likely in the future.

3.5 Community involvement and resident support for tree planting

The involvement of local residents and the community in tree related activities were cited and praised by many participants. Projects, schemes and activities seen as important in helping increase tree cover include the community involvement aspect of the Green Streets projects, Friends Of parks groups (particularly Friends of Blackley Forest, a Local Nature Reserve) Tree Wardens, green guerrillas, planting schemes involving private gardens, free tree and tree advice schemes, planting projects with schools/young people, promotion of trees and planting projects as part of National Tree Week and the Tree O’Clock record attempt and the continuing effects of the Trees of Time and Place scheme. However, a barrier for urban trees is community resistance to necessary maintenance/felling, where the community do not understand why a tree needs to be removed. Issues of excessive pruning when trees are maintained can also cause community friction.

3.5.1 Further ways of involving local residents

A number of ways of further involving the community were suggested. A Community Tree Nursery could be started to provide trees for streets, parks and gardens. Residents could contribute to the maintenance of the public realm green infrastructure, as happens with the management fees of London squares. A shared cost scheme operates in Trafford where the resident pays for the tree and Trafford Council pays for the planting, and the resident then adopts the tree. A similar ‘Adopt A Tree’ scheme using existing trees could be a good opportunity to protect trees. Promoting roof gardens on blocks of flats or offices were also mentioned as a potential way to increase tree cover. Computer based visualisation was cited as a good way to engage communities. Eco schools provide a way of educating children about their local trees. The increasing popularity of memorial trees can increase tree cover while helping people link with their local environment.

3.5.2 Ways to increase resident support

Some residents are still wary about trees and have negative perceptions of them, and more should be done to promote the benefits of trees and give a more realistic idea of the likelihood of damage by trees to foundations and drains, and their low contribution to subsidence (certainly in NW soil types). More promotion of benefits of trees could also help change antipathy and ambivalence into positive views or even enthusiasm about trees. Damage to trees through vandalism was listed as a problem, with people arguing trees should not be planted as they will be vandalised and it will be a waste of money. Community projects like Green Streets see quite low levels of vandalism so it can be avoided with the right methods. Consultation was listed as a good existing method, a barrier to and an opportunity for increasing tree cover, showing that involving the community is both positive and negative.

One method proposed to encourage residents to support street tree planting is quicker removal of leaf litter.

3.6 Trees and urban design

294 Urban design can allow or deny opportunities for tree planting. The Commission for the Built Environment (CABE) were cited as a resource for advice, particularly for their ‘Grey to Green’ publication. Designing out cars would give more room for trees, although people are very attached to their cars so it may not be popular. More integrated street scenes could include cars and trees, with cars reducing their speed due to the street design. Designed in off road car parking can be helpful in this. Residents’ fears of a rise in crime as trees could hide muggers can be a barrier to increasing tree cover, although some research shows that more trees and greenspace create more community surveillance and crime levels fall. The cutting of trees for sightlines of CCTV cameras was mentioned as a problem linked with perceptions of crime levels.

3.6.1 Ways to incorporate trees into the urban fabric

‘Build outs’ and Home Zones were cited as good ways the urban environment can be redesigned to accommodate trees. These ways ensure DDA access to pavements continues, which may not be possible if trees are planted in the conventional way. Thoughtful design, location and grouping of services/utilities should be encouraged to allow tree planting to occur more easily and minimise root intrusion. There is a lot of competition for space in streets, and one solution may be to plant trees in pots on the pavement rather than into the pavement, although this raises questions about their sustainability with access to water.

3.6.2 The Trees and Design Action Group

The Trees and Design Action Group should be extended to all regions, and their ‘Right Tree Right Place’ resource used to get over the barrier of uncertainty about knowing the right type of tree to plant that can affect tree planting schemes. This resource will be particularly important in planning for climate change effects.

3.7 Use of urban timber as biomass – a solution to a range of problems?

The use of urban timber as biofuel for homes or business was suggested by a number of participants. They gave a range of ways this may be implemented, such as temporary greening of ‘land in limbo’, planting up housing clearance sites to give a community managed source of biomass and using arisings from arboricultural work and tree pruning. Urban timber production may also be used for timber and woodchip as well as renewable biomass energy. This system acts as a carbon sink and could be part of carbon tax credits in the future, or a Low Carbon Transition Plan. The sale of biomass and other timber products can go back into funding the woodland or for further tree planting and maintenance elsewhere.

3.8 Funding – Barriers

Issues around funding were, as expected, discussed in detail. There are many barriers to increasing budgets for tree planting, but there are also a number of national schemes and innovative ways money can be raised for urban trees. Barriers mentioned during the discussion centre around the low priority tree planting can have in local authorities, particularly when competing against other issues such as housing and health and in the background of looming council cuts, possibly £20m. The problems surrounding using council capital or revenue money for trees and maintenance were highlighted, something that could be changed with legislation change. There is a lack of money for regular maintenance of existing and newly planted trees, which can lead to resident complaints or tree resentment, hindering support for new tree planting. When new trees are planted, there is very often no money for their future maintenance included in the project budget. 295 The cost of aftercare is usually not addressed; there are special considerations of establishing street trees, and balancing of tree budgets or funding across planting, nurturing and mature maintenance was seen as a good way to plan tree care budgets or project funding. However, often with outside funded tree planting schemes funding is very short term and/or the criteria does not allow money to be set aside for tree maintenance in the future. This needs to change if new trees planted will survive to maturity and avoid some resident complaints. Appropriate maintenance can avoid knee jerk reactions to tree problems, particularly felling trees instead of maintaining them and instead of solving the problem in other ways e.g. blocked drains, reducing trip hazards. Lack of money for maintenance also means that new trees on new development sites may not be monitored, meaning that trees planted as a condition of planning permission may die but not be registered in time to force the developer to plant a new tree.

3.9 Funding – Opportunities

A great issue for tree planting is starting finance and the overall cost of projects. There are a range of funding schemes to plant new urban trees, including section 106 agreements, the new Community Infrastructure Levy, the Forestry Commission’s Woodland Creation Grants, the Playbuilder/National Play schemes to improve play areas in parks and could be used to tidy up surrounding parkland, the Green Streets schemes, National Lottery funding, although priorities change frequently, small local charities. There are a number of grant schemes that could be accessed with creative thinking and promotion of the benefits of trees, such as PCT Health and Well Being grants which could be used to improve parkland for health walks and other recreation, and the Future Jobs Fund, which could be used to set up a small parks maintenance company for example. Utilities companies could be encouraged to plant trees to reduce peak run off to waste water treatment works, either for their own sake to reduce their costs, as part of the Flooding and Water Management Bill or through a carbon credits scheme. Money may be able to be diverted from other council departments to arboriculture departments through virements (a strictly regulated process of transferring items, especially public funds, from one financial account to another) as part of a regeneration, public health or education scheme.

3.9.1 Funding raised directly from residents

Money could be raised directly from urban residents, for example through the existing ‘Adopt A Tree’ scheme in Trafford where the resident pays for and cares for the tree and Trafford Council pays for planting, through a levy on car parking charges in city centres or on sports facilities that is ringfenced for urban tree planting and maintenance or residents could contribute money through a scheme similar to the monies raised for maintenance of London squares from neighbouring residents. Similarly, residents could gain reductions in their council tax, or future Carbon Tax Credits, in return for green concessions (e.g. insulation, fewer miles driven) or for help maintaining urban trees (e.g. leaf litter picking, issue reporting). Residents may also choose to ringfence council or personal taxes for urban forestry. Trees and improving greenery may be used as community payback for improvements in other aspects e.g. setting up a Neighbourhood Watch scheme. Money may also be generated from urban timber and/or biomass initiatives, as mentioned earlier. Some companies may wish to sponsor a tree planting scheme near their offices, so these possibilities should be investigated.

3.9.2 Other methods to potentially indirectly generate funding

296 Although not having funding of their own, green initiatives such as Eco-Schools and Transition Towns may be used to increase the profile of urban trees and their benefits to encourage funding by other sources.

Use of celebrities such as David Bellamy to increase the profile of urban trees, as well as using National Tree Week for extra promotion of tree schemes for extra donations/funding was suggested.

Changes in politics within the local authority could aid tree planting, for example local councillors fighting to plant trees and be seen to be green, and greening the council itself with good social tree work.

3.10 Residents’ problems with urban trees

Below is a list of problems that residents commonly complain about. Apart from more appropriate tree species choice there is little that can be done about these, but they are worth noting, particularly to generate a standard response or advice when a resident complains.

Worldview of housebound elderly people restricted by trees Hay fever Insect attractant Poplar seed casing Fruit used as missiles Noise of leaves Squirrels accessing my loft Laburnum – poisonous seedpods [though not serious poison, merely stomach upset] Tilia eurochlora [lime] is bad for my bees [very attractive to bees but gives them a narcotic effect] Aphid dew dripping onto ‘my new car’ Fear of swaying trees Berries and leaves on ground are slippery Problems of bird dirt ‘on my car’ TV reception Lack of light

297 4 The Future of Trees discussion

This gave participants as chance to highlight things from the discussion they felt particularly strongly about, and a range of potential schemes to increase tree cover were also noted.

• There is a need for more work on evaluating the economic side of tree planting - the worth of trees as a long term investment. • Trees can be used to generate income, for instance by-products from the industry may become biomass, though the infrastructure may have to be altered to make it a viable industry. Although it may not be cheap initially, the long term aspects should be taken account of. • There is a need for structural and engineering solutions to incorporate more trees into streets. • Increasing tree cover is more than just changing attitudes, there is a need for cross disciplinary work plus widespread attitude change. • The issue of gardens classed as brownfield sites still hasn’t been addressed, despite debate in political parties. Even though there is a need for high density housing, there is also a need for high quality green spaces with them. • There is a general confusion about what precisely ‘large’ trees refers to – is it a forest species which will grow to be large, or is it a semi-mature tree that will not grow a great deal larger? This needs to be solved in order to move the conversation about ‘big trees vs. small trees’ forwards. - As part of this, the fact that small young trees grow faster and so evapotranspire at higher levels than mature trees means small trees give a higher cooling effect but a lower shading effect. Both aspects are important for reducing the urban heat island so both types of tree are valuable in urban areas. • There are a range of possible schemes to increase tree cover in urban areas, including: - residents paid by the council to plant and look after trees on their own property, but there are maintenance and checking issues/costs, and issues of who to blame if things go wrong e.g. a tree causes subsidence, resident says the council told me to plant it there – would the council be liable for that? - There have been a few similar schemes in Hulme - planted trees of appropriate scale and maintenance but was very labour intensive - Residents could be ‘rewarded’ with trees and greenspace for setting up community/neighbourhood schemes e.g. Neighbourhood Watch, which can also help to limit vandalism - There have been schemes where seeds were given out freely but people spread them inconvenient places - caused some problems - Key is to develop and properly plan areas, increase and extend cover in specific places and implement tree wardens - Adopt a tree schemes – residents look after a tree over a period of time. Council knows the exact location and who’s responsible, can target people who are interested, and willing with the time - Difficulties with the tree warden schemes in urban areas are the investment of officers to maintain interest and provide information to the public - Possibility of a tree warden network and steering scheme (but hard to implement) - Scheme in London where youths adopted a tree each and the community oversaw them, with a yearly reward from a local restaurant

298 - Groundwork have a tree warden scheme across Greater Manchester and found that having the local authority, parks ‘friends of’ groups and wildlife groups which engaged the volunteers as a support network was very beneficial - Community orchard schemes using SLOAP land (space left over after planning). However, care must be taken as there is the issue of contaminated soil - for example from arsenic. This would have the advantage of raising awareness and people’s knowledge about the use and potential of soil. • Large areas of land are currently used as golf courses, and are not used to capacity in tree planting or landscape impact • Climate change and its impacts are becoming a reality and knowledge is increasing - however cold temperatures could obstruct people’s views of climate change, so it is better to talk of climate chaos when possible. • When thinking about community involvement, projects must also factor in the social advances to the community - more people are becoming aware of the benefits of trees and greenspace and the threat of climate change, and knowledge is increasing • Engineering professionals need to be persuaded to become part of the infrastructure planning and design to allow tree planting – a similar event to today could be held with engineering professionals to include them in the discussions about tree cover.

299 5 Recommendations from the workshop

• PPSs need to be kept with the appropriate guidance notes to allow proper understanding and carrying out of the policies. • Laws must be strengthened to protect urban trees from unnecessary felling and development. - Higher penalties should be given to those proven to have illegally felled a healthy tree. All urban trees over a certain size should be protected, and all local authority trees should automatically be covered with a TPO. • New legislation to ensure green infrastructure is a critical part of new development, designed in from the beginning. • Planning conditions should be able to ensure consultation with an arboriculturist, landscape architect and highways officer so trees may be properly included in developments in a way appropriate to the surrounding landscape. - Other conditions should include following recommendations of the Trees and Design Action Group’s ‘Right Tree Right Place’ resource, and extending the establishment period of new trees from 2 to 5 years. • Gardens must be reclassified as greenbelt land, not brownfield land. • All councils should develop a Tree/Green Infrastructure Strategy. • The potential for extending the Trees and Design Action Group to other regions should be investigated. • Service Level Agreements (SLAs) between local authority tree officers and ALMOs should be investigated to protect and improve trees and greenspaces. • Education about realistic tree and tree root damage needs to be circulated to give people more confidence when dealing with insurance companies and unscrupulous tree surgeons. • Different ways of funding need to be investigated, particularly ones which allow money for tree maintenance in following years. • The potential for using urban timber for biomass or timber use should be investigated, both as a revenue stream and as a way of reducing carbon emissions. • Research into economic and non economic benefits of trees needs to continue and feed into legislation. • Engineering solutions to trees in streets should be found – there is a potential PhD in this topic.

300