Town socio-economic status and road width determine street tree density and diversity in Karachi, Pakistan

Journal Pre-proof Town Socio-economic Status and Road Width Determine Street Tree Density and Diversity in Karachi, Pakistan Zafar Iqbal Shams, Mubah Shahid, Zara Nadeem, Shafaq Naz, Dania Raheel, Darakshan Aftab, Tayyab Raza Fraz, Muhammad Sohaib Roomi

PII:

S1618-8667(18)30630-7

DOI:

https://doi.org/10.1016/j.ufug.2019.126473

Reference:

UFUG 126473

To appear in:

Urban Forestry & Urban Greening

Received Date:

2 October 2018

Revised Date:

2 September 2019

Accepted Date:

3 October 2019

Please cite this article as: Shams ZI, Shahid M, Nadeem Z, Naz S, Raheel D, Aftab D, Fraz TR, Roomi MS, Town Socio-economic Status and Road Width Determine Street Tree Density and Diversity in Karachi, Pakistan, Urban Forestry and amp; Urban Greening (2019), doi: https://doi.org/10.1016/j.ufug.2019.126473

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Town Socio-economic Status and Road Width Determine Street Tree Density and Diversity in Karachi, Pakistan

By Zafar Iqbal Shams*[email protected] Mubah [email protected] Zara [email protected] Shafaq [email protected]

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Dania [email protected] Tayyab Raza [email protected]

Institute of Environmental Studies,

University of Karachi, Karachi, Pakistan 2

Department of Statistics,

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University of Karachi, Karachi, Pakistan Highlights

Monoculture planting is prevalent Affluent towns show greater tree density and species richness Wide Roads reveal higher density and diversity

Abstract:

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Muhammad Sohaib [email protected]

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Darakshan [email protected]

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Despite being one of the largest and fastest growing cities of the world, little is known about the urban forest of Karachi. The city consists of eighteen towns. Each town has different socioeconomic status. Therefore, the present study investigates 1) the patterns and differences in the diversity and density of street tree communities across the towns of different socio-economic status, 2) the patterns and differences in the diversity and density of the communities of different road widths, 3) the factors that cause variation in different attributes of the community. The 1

study revealed significant variation in the diversity and density of the tree community of different towns and road categories. The socioeconomic status of towns and different road categories demonstrated statistically significant influence in determining their tree density and species diversity. Statistically significant correlation was found between socioeconomic status and tree density per thousand inhabitants of towns. The study divulges recurring planting of one or few species that decrease the species diversity in many towns and streets. Conocarpus erectus

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revealed strong dominance on wide and medium width roads while it demonstrated co-

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dominance with Azadirachta indica on narrow roads. Overall, 62 species (30 native and 32

exotic) were recorded, which were very unevenly distributed in the streetscape of the city. The

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study also discusses the socioeconomic factors and role of civic agencies in planting trees.

Keywords

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Introduction

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Street trees, Karachi, socioeconomic status, density, diversity, strong dominance

Trees along the streets and avenues have long been cherished in the urban settlements of many parts of the world (Lawrence, 1988; Couch, 1992). Earlier, the street trees were largely raised for the beautification and aesthetics of urban landscape (Ignatieva, et al., 2011). Nowadays,

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ecological, social, psychological and economic benefits are considered for planting trees along the streets (Soares, 2011; Seamans, 2013; Mullaney, et al., 2015; Säumel, et al., 2016; McPherson, et al., 2016). Street trees cool urban temperature and improve human thermal comfort (Coutts, et al., 2016), alleviate urban heat island effect (Gillner, et al., 2015; Gülten, et al., 2016), save energy by 2

reducing electricity use, particularly during hot summer days (Donovan and Butry, 2009), improve human health and well-being (Lovasi, et al., 2008; Taylor, et al., 2015), mitigate air pollution and improve microclimate (Tallis, et al., 2011; Vailshery, et al., 2013), sequester and store tropospheric carbon (Stoffberg, et al., 2010; Tsay, et al., 2015; Ajani and Shams, 2016; Tang, et al., 2016), protect pedestrians and street hawkers from the rain and solar radiation (Nagendra and Gopal, 2010) and increase the value of residential properties (Pandit, et al., 2013).

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Moreover, wooded streets provide important habitats and vital corridors between parks in urban

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neighborhoods for fauna (Fernandez-Juricic, 2000; Choi and Kim, 2014; Shackleton, 2016).

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Consequently, the demand for growing trees along the streets and avenues in the urban expanses has increased over the last few decades to promote socio-ecological sustainability of cities and

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towns because more than half of the global human population currently resides in urban areas

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and is expected to grow to 60 percent by 2030 (United Nations, 2014). Street trees have become an integral part of urban planning and management. The trees are being mapped with accuracy through advance tools in some urban areas (Tanhuanpää, et al., 2014;

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Seiferling, et al., 2017). In recent years, different attributes of street tree community have been investigated in many urban landscapes across the globe for the enhancement of their sustainability in the densely populated human settlements (Frank, et al., 2006; McKinney, 2006,

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2008; Deliang, 2009; Nagendra and Gopal, 2010; Kirkpatrick, et al., 2011; Ressler and Kilmer, 2012; Kuruneri-Chitepo and Shackleton, 2011; Yang, et al., 2012; Deb, et al., 2013; Choi and Kim, 2014; Cowett and Bassuk, 2014; McPherson, et al., 2016; Nero, et al., 2017; Gwedla and Shackleton, 2017). The studies on the street trees revealed significant variation in their attributes within the streetscapes of many urban areas, which may be because of the socio-economic and educational status of different areas (Hope, et al., 2003; Kirkpatrick, et al., 2011; Gwedla and 3

Shackleton, 2017), the cultural background, preference or attitude of urban residents for different sizes, shapes and growth rates of street trees (Williams, 2002; Todorova, et al., 2004; Schroeder, et al., 2006) or the replacement of street trees due to pests, diseases or infections (Heimlich, et al., 2008). Pham et al., (2017) investigated the effects of street characteristics, social stratification and

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lifestyle for the variations of street tree cover in Montréal, Canada. Kendal, et al., (2012) discovered that the education level was more important driver of tree cover and species richness

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than household income in Ballarat, Australia. Kuruneri-Chitepo and Shackleton, (2011) revealed

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that affluent residential neighborhoods had significantly higher tree densities than their poorer counterparts in the Eastern Cape, South Africa due to racial segregation of the areas during

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apartheid era. Roman et al., (2018) investigated historical legacy effects on the current patterns of species composition, diversity and tree canopy cover while citing the examples from the

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U.S.A and Canada. Shams (2016) found significant changes in the diversity and composition of street trees of different land uses in Karachi over twenty years.

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Despite compelling benefits and consequent importance of street trees in the urban planning, street trees are removed from the verges and medians of streets for their widening to enhance the infrastructure (Qureshi, et al., 2010; Nagendra and Gopal, 2010). The trees are removed for the

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redevelopment of public land in some urban areas to consolidate the co-usage of highly built-up lands, services and transportation systems and to contain suburban sprawls to stop the degradation of peripheral natural environment (Brunner and Cozens, 2013). Moreover, vandalism by people and damage by livestock cause significant loss of newly planted street trees despite the occurrence of protective structures around them in the Eastern Cape, South Africa (Richardson and Shackleton, 2014). Misbehavior, boredom, lack of appreciation of the trees and 4

collection of timber decrease the size of street tree community (Qureshi, 2010; Shackleton and Blair, 2013).

Karachi exhibits low species diversity mainly due to repeated planting of one or few species on its streets over the years. During the last decade, substantial numbers of trees were removed from

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the verges and medians of streets for their widening to facilitate the smooth and massive flow of

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traffic. Moreover, countless trees were uprooted for the redevelopment of urban infrastructure (Shams, 2016; Bhagwandas, 2017; The NEWS international, 2017) and the collection of timber

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(Ilyas, 2018).

Despite growing importance and understanding, there is a lack of appreciation and dearth of

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knowledge regarding street trees in Karachi with the exception of the study by Shams (2016). It was observed that several major streets do not have any trees. Furthermore, thousands of large

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canopy trees of the central roads of Gulshan Iqbal and North Nazimabad were removed over the last few months for their widening and the construction of Rapid Transit Project. Both the towns

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are predominantly inhabited by high income residents.

The deficiency of knowledge and the importance concerning street trees in Karachi persuaded us to explore the diversity, density and composition of street trees across different towns of the city. The present paper investigates 1) the patterns and differences in the diversity and density of street tree communities in eighteen towns of different socio-economic status, 2) the patterns and differences in the diversity and density of tree communities of different road widths, 3) the 5

factors that influence the variation in different attributes of street trees such as socioeconomic or the role of tree planting agency.

2.0 Materials & Methods: Study Site:

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2.1

Karachi is the largest city of Pakistan and the sixth largest urban agglomeration globally

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(Brinkhoff, 2017). It is located at 24o45’ N to 25o37’ N and 66o42’ E to 67o34’ E along the

shoreline of the Arabian Sea (Fig 1). The city is elevated to 8 m above the sea level. The area is

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classified as arid hot desert (Kottek, et al., 2006). Naturally, it is a shrub land. It experiences long

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warm summer and short mild winter. The summer season stays from March to October with an average daily temperature from 25 oC to 30 oC. The winter season lasts from December to

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February with an average daily temperature from 18 oC to 20 oC. The summers are humid while winters are dry. The city has low average annual precipitation (175 mm), which mainly

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precipitates during monsoon season from July to September.

Currently, about 20 million people reside in the city, which spread over an area of 3,530.00 km2

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(Karachi Metropolitan Corporation 2018). Its annual population growth rate is estimated at 5%. The city has eighteen towns and six cantonment areas. All the towns were included to investigate the taxonomic diversity, density and composition of the street tree community while the cantonment areas were excluded from the study. Each town of the city has different socioeconomic status.

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Lyari is the oldest, smallest and most densely populated town of the city. It is largely inhabited by low income population since the town has poor infrastructure for civic services. Kemari town has the largest seaport of the country. Saddar town has many affluent neighborhoods and commercial centers. Liaquatabad town is heavily populated town with lower middle to high

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income residents. The town has one of the main commercial centers for low to middle income residents of the city. Gadap is the largest and most thinly inhabited town, which mainly produces

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vegetables, fruits, dairy and poultry products for the rest of the city. Sindh Industrial Trading

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Estate (SITE) is the largest industrial hub of the country, which is largely inhabited by low to lower middle income residents. Karachi has three industrial zones which are located in four

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inhabited by low to middle income people.

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different towns, viz. SITE, Korangi, Landhi and North Karachi. These towns are mostly

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Fifty percent of the population of Karachi lives below poverty line. Around 75% of its households belong to poor and low income groups. Average monthly income of the households in the city is US $150, which greatly varies across low and high income categories (Haq, 2014). Furthermore, Karachi has large number of slums and squatter settlements. These areas are

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generally located in the towns of low or middle income residents. Their numbers are comparatively low in the affluent towns such as Jamshed, Saddar, Gulshan Iqbal and North Nazimabad. Yet, 40% of the people of Karachi live in slums and squatter settlements (Hassan, et al., 2013), which are extremely low-income localities. Eighty nine percent of the population of slums and squatter settlements live below the poverty line (Haq, 2014).

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Federal Board of Revenue (2016) categorized the residential lands of Karachi on the basis of their price, which ranges from US $ 6 to US $ 251 per square yard. Due to unavailability of the data of residents’ income, we used the land price of each settlement of every town to classify all the towns into ten different socioeconomic categories, namely, 1. Lowest income residents, 2.

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Low income residents, 3. Low to lower middle income residents, 4. Lower middle income residents, 5. Lower middle to middle income residents, 6. Lower middle to high income

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residents, 7. High income residents, 8. High to higher income residents, 9. High to highest

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income residents, 10. Higher to highest income residents (Table 2).

Eight towns demonstrated uniform price of their entire lands. However, the price of lands greatly

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varies in ten towns mainly because they have slums that decrease the price of the land. Hence,

2.2

Data Collection:

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the median price of each of the ten towns is used in this study for the analysis.

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The streets of each town were categorized as Wide Road (24m or greater width), Medium Width Road (12m to 24m wide) and Narrow Road (less than 12m width) (Nagendra and Gopal, 2010; Deb, et al., 2013). Wide roads in Karachi are main roads and longer than the medium width and narrow roads. Medium width roads function as link road between the wide and narrow roads.

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Narrow roads are generally smaller than both the categories. The classification of roads on the basis of their width would help to understand the function of different tiers of administration in planting the trees. For instance, wide roads are generally managed by the city district government whereas the town administration manages the narrow and medium width roads. However, local

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inhabitants also grow and care the plants on the narrow roads since their sidewalks are close to their homes.

One transect each of 100 meter length on every kilometer was made from one end of each street of every town for tree sampling. The streets of less than one kilometer were excluded from the

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study. The property line on both sides of the streets was taken as the width of each transect.

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Different numbers of transects were made in different towns since the dimension of towns is

varied. A total of 354 transects on wide roads, 282 transects on medium width roads and 231

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transects on narrow roads were made (Table1). Approximately 10 percent of the total street

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lengths of the city were sampled.

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The street trees of two or more than two meter tall were included for the present study since the measurement of the trunks’ diameter at breast height (DBH) of smaller trees could hardly be

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possible. All the trees were identified up to species level except Eucalyptus. The diameter at breast height (1.3 m) of every tree was measured. The study excluded herbs, shrubs and trees of less than two meter height. The basal area of every individual tree is calculated as:

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Basal Area = 0.00007854 x (DBH) 2

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Where 0.00007854 is a forester constant

Data Analysis:

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2.3.1 Road Width and Socioeconomic Status of Towns in Determining Species Diversity and Tree Density. Shannon-Weiner (Shannon, 1948) and the inverse of Simpson Diversity (Simpson, 1949) indices were applied for species diversity analysis of the street tree community of different towns and road categories (McPherson and Rowntree, 1989; Sun, 1992; Nagendra and Gopal, 2010).

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Two - way analysis of variance (ANOVA) was performed using IBM SPSS statistics to

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determine whether the species diversity and tree density significantly differ in towns of different socioeconomic status and different road width. The analysis also ascertains the interaction of

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socioeconomic status and road width to determine whether the diversity and density significantly differ due to their interactions. Estimated marginal means of the tree density and species

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diversity were also calculated and plotted against the classes of different socioeconomic towns.

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Pearson’s correlation coefficient was computed to determine the relationship of tree density with

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per thousand inhabitants of different towns.

2.3.2 Relative Abundance, Relative Dominance, Relative Frequency and Importance Value: Relative abundance and relative dominance are generally taken to measure the importance value

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of the species in urban forest (McPherson and Rowntree, 1989; Deb, et al., 2013). In the present study, the relative frequency (a third dimension of importance value measure) is included to calculate the importance value of the species which were sampled by transect method. McPherson and Rowntree (1989), who introduced the importance value measure for street tree community, excluded relative frequency for the reason that they used entire street trees of the U.S. cities for the calculation of importance value. 10

One-way analysis of variance (ANOVA) was applied to determine whether various attributes of the community in different towns and road categories differed significantly with each other.

3.0 Results: 3.1 Socioeconomic Status of Towns and Road Categories in Determining their Species

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Diversity and Tree Density

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The results of two-way ANOVA to determine the effects of towns’ socioeconomic status and road categories on the tree density and species diversity are reported in Table 4. The analysis

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demonstrated that both the variables had statistically significant effects in determining the tree

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density and species diversity in different towns of the city. The estimated marginal means of the density and diversity, which were plotted against each combination of towns’ socioeconomic

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status and road category, also exhibited statistically significant interactions. Statistically significant correlation was found between the socioeconomic status and tree density per thousand

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inhabitants.

Wide road had the highest number of trees per transect (12.9 + 20.8 trees) whereas the lowest number of trees per transect (1.4+ 3.7 trees) was enumerated on the narrow road. Nevertheless,

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5.7 + 8.8 trees per transect were recorded on medium width road. On an average, Karachi had 7.5+ 15.1 street trees per transect (Table 1). Trees per transect were found significantly different (p<0.001) in 18 towns of the city. Tree density in many towns of low income population was recorded substantially below the city average. Of 867 designated transects, 483 transects (55.7 %) had a total of 6,507 street trees from 62 species (30 native and 32 exotic) whereas 387 transects (44.6 %) did not have any street trees 11

(Table 1). Of the 483 tree supporting transects, 245 transects (50.7 %) were on wide roads, which had a total of 4,533 trees (69.7 %) from 48 different species, 171 transects (35.4%) were on medium width roads, which had 1,634 trees (25.1%) of 48 species while 67 transects (13.9 %) were on narrow road that had 340 trees (5.2%) of 34 species. Wide Road had the lowest percentage (31.1%) of treeless transects while the highest percentage

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(71.1 %) of treeless transects was counted on the narrow road. However, medium width road demonstrated 39.4% treeless transects. Lyari, the most populous, oldest and a town of low

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income residents, had the highest percentage (80.9 %) of treeless transects whereas North

residents) did not have any treeless transect (Table 2).

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Nazimabad town (high to higher income residents) and Kemari town (lower middle income

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Moreover, Lyari Town had the lowest number of trees per transect (1.4 + 5.5 trees) while the

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highest number of trees per transect (24.3+14.0 trees) was recorded in Kemari town. Higher street tree densities were recorded in affluent towns such as North Nazimabad (20.0+ 20.4 trees per transect) and Gulshan Iqbal (14.2+ 21.2 trees per transect) compared to the towns of low

transect).

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income residents such as Lyari (1.4 + 5.5 trees per transect) and Baldia (1.8+ 4.2 trees per

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3.2 Species Diversity and Species Richness of Street Trees in Different Towns and Road Categories.

Shannon and Inverse Simpson indices were exercised for the measurement of species diversity in different road categories (Table 1) and towns (Table 2). Orangi, a town of low income residents, recorded the highest Shannon diversity index (2.42) and one of the lowest tree densities (2.9 + 12

4.5 tree per transect). Liaquatabad, a town of lower middle to high income residents, demonstrated the highest Inverse Simpson diversity index (6.17), primarily due to greater evenness in species distribution. Both Orangi and Liaquatabad towns had greater species richness compared to that of eleven towns of low to high income population. Gulshan Iqbal, a town of high to higher income residents, demonstrated one of the lowest species diversities (Shannon Index, 1.12; Inverse SDI, 1.70), despite the town had the highest species richness (30

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species). The low species diversity is due to overrepresentation of a single species. Gadap, a

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town of lowest income residents, revealed the lowest species diversity (Shannon index, 0.19;

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Inverse SDI, 1.07).

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In road categories, narrow roads demonstrated the highest species diversity (Shannon Index,

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2.57; Inverse SDI, 6.36) whereas wide roads revealed the lowest species diversity (Shannon Index, 1.49; Inverse SDI, 2.18). Altogether, Karachi revealed low species diversity (Shannon

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Index 1.72; Inverse SDI, 2.48).

As a whole, 23 families, 46 genera and 62 species of trees were enumerated on the streets in Karachi (Table 3). The highest number of genera (36) was found on the medium width roads of

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the city whereas the lowest number of genera (26) was counted on the narrow roads. However, wide roads had 35 genera (Table 1).

3.3 Relative Importance of Different Species Growing along Different Road Categories.

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Conocarpus erectus exhibited the highest importance value (130.21), which was followed by Azadirachta indica (34.14). Of 62 species, the importance values of 33 species were lower than one (Table 3). Top five species accounted for 89.1 %, 81.3 % and 65.9 % of the tree community of the wide, medium width and narrow roads respectively while the top five species comprised 85.4 % of the total street tree community of Karachi (Table 1). Conocarpus erectus accounted for 61.8 % in the entire tree community, which was followed by Guaiacum officinale (9.0 %)

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(Table 3).

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Figures 6 - 8 depict all the three attributes of top 10 importance value species on the streets of the

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city. Analysis of Variance (ANOVA) revealed that the relative values of top ten species were significantly different (p < 0.001). The relative values of Conocarpus erectus were the highest in

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all the three attributes. Azadirachta indica is the second most dominant and frequent species while Guaiacum officinale is the second most abundant species. Furthermore, the study reveals

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that C. erectus was the most abundant, dominant and frequent species on the wide and medium width roads whereas A. indica was the most frequent and dominant species on the narrow road.

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However, C. erectus is the most abundant species on the narrow road. It had the lowest (p < 0.001) average diameter at breast height (DBH) among the top five species of the city. Six species, viz. C. erectus, A. indica, G. officinale, Eucalyptus sp., Ficus virens and F. rubiginosa

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were common among the top 10 species in all the road categories. Figure 9 demonstrates that the proportional distribution of exotic species was greater than native species in all the towns and road categories. Gadap, Kemari and Lyari towns had more than 90% trees of exotic species. While greater number of native trees was found in Landhi, Bin Qasim, Liaquatabad and Korangi towns. 4.0

Discussion 14

4.1 Relative Importance of Street Tree Populations Results revealed strong dominance of Conocarpus erectus on the streetscape of the city since its importance value was greater than 25 percent, which was followed by Azadirachta indica with importance value of less than 15 percent (Table 3). Furthermore, the pattern exhibited strong dominance of C. erectus on the wide and medium width roads. Narrow road demonstrated co-

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dominance of C. erectus and A. indica since the importance values of each of these species were greater than 10 percent and their sum was higher than 25 percent (MacPherson and Rowntree,

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1989).

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The structure of street tree community in Karachi could be compared with that of five U.S. cities that exhibited strong dominance of single species in their street tree communities during late

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1980s (MacPherson and Rowntree, 1989). In U.S. cities, the relative dominance of leading

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species was greater than their relative abundance. On the contrary, the relative abundance of Conocarpus erectus was greater than its relative dominance in all the road categories because the species has been extensively planted over the last decade (Shams, 2016). For that reason, the

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average diameter at breast height (DBH) of C erectus was the lowest among the top five species of the tree community. Large diameter trees of C. erectus were uncommon on the streets of the city during the study. Furthermore, C. erectus is a medium statured species. In contrast, the

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leading species on the street of the U.S. cities were large statured. Moreover, they were much older than those in Karachi. The relative dominance of 2ndleading species (Azadirachta indica) in Karachi was greater than its relative abundance mainly because of its stature and age. It could be concluded that greater relative importance of Conocarpus erectus was largely due to its number on the streets in the

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city. However, it could be envisaged that the relative dominance of C. erectus may upsurge with the increasing age of their individuals. Monoculture plantings, particularly of exotic species, are very common on the streetscape of the city even in most of the official tree planting initiatives (Hussain, 2003; Shams, 2016), which resulted in the strong dominance of a single species on the wide and medium width roads. Civic

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agency usually cultivates and cares the trees of wide and medium width roads. The agency infrequently cultivates trees on narrow road, which may be due to overhead electric lines or the

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underground water and sewerage lines that are more frequent along the narrow roads compared

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to wide and medium width roads. Local residents generally raised the trees of their choice along narrow roads since their sidewalks are near to their homes. This increased the relative

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importance of other species and decreased that of C. erectus. The inhabitants usually prefer to plant A. indica, which increased its relative importance to the level of co-dominance on narrow

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road. Co-dominance of two or more species provides greater stability against disease, pests and

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infections compared to strong dominance of single species (McPherson and Rowntree, 1989).

Monoculture planting with one dominant species typically requires lower maintenance costs, but may sustain heavy costs for their removal and replacements due to disease, infection or

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senescence in the dominant species within few years (McPherson and Rowntree, 1989). Monoculture planting of street trees instigated massive losses in many urban areas of the world. For instance, millions of American elm trees (Ulmus Americana), which were widely monocultured in the streetscape of North America, were wiped out due to Dutch elm disease (Ophiostoma ulmi). Increasing taxonomic diversity in street tree community decreases the risk of

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their possible damages from pests, diseases and environmental changes (Raupp, et al., 2006; Gwedla and Shackleton, 2017; Sjöman, and Östberg, 2019). Another area of concern is extensive planting of exotic species across Karachi. Garcia-Garcia,et al., (2016) disclosed that exotic species were less suitable for planting in urban area compared to native species. Moreover, native street trees support significantly greater diversity and density of

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avifauna than those of exotic species (Narango, et al., 2018). On the contrary, significantly higher prevalence of mistletoes was found in exotic species compared to native species

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(Shackleton, 2016). However, Chalker-Scott (2015) advocates that exotic and native species

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offer the same ecological services for the stability of urban landscape. According to Sjöman, et al., (2016), the exclusion of exotic species from urban forestry is generally not affordable, largely

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due to limited availability of native species to fulfill the need of ecosystem services in harsh urban landscape. Many exotic species provide better ecosystem services than native species in

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adverse urban environment (Chalker-Scott, 2015).

The civic agency preferred the planting of exotic species, primarily due to their fast growth,

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which increased their proportion in this coastal city. Their proportion is greater on the wide and medium width roads compared to those on narrow road, mainly due to the influence of the agency. Greater number of exotic trees was found in the towns ranging from high income

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residents (Gulshan Iqbal) to lowest income residents (Lyari). Gulshan Iqbal is centrally located in the city and has higher land value, which drew the attention of civic agency for the provision of its better infrastructure and massive tree planting programs, preferably of exotic species. While in Lyari, native species were replaced with exotic species over the years because it is the oldest town of the city. The peripheral towns of low to lower middle income residents such as Landhi, Bin Qasim exhibited lower number of exotic trees compared to the old and affluent 17

towns since weak infrastructure of civic services and low land value infrequently attract civic agency for substantial tree planting. This is also evident from the fact that the tree density per transect in the affluent towns such as North Nazimabad and Gulshan Iqbal was found up to 10 times greater than that in towns of low income residents like Lyari and Baldia.

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4.2 Socioeconomic Status of Towns and Density and diversity of Street Tree Community

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The towns of high income residents demonstrated high tree density compared to those of low income residents which was mainly because of high land value and better infrastructure of the

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roads and the sidewalks. The civic agency seldom took interest in massive tree planting on the

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streets of low income residents. The trees were infrequently planted in great numbers on their streets. The tree density in the affluent landscape of the Eastern Cape, South Africa was also

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significantly greater compared to that of their poorer counterparts during apartheid years (Kuruneri-Chitepo and Shackleton, 2011). Similarly, the tree density in the towns of low income

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residents was found lower compared to the affluent towns of Karachi. On the contrary, the towns of some low income residents (Orangi, Baldia and Korangi) had greater species richness. The agency hardly took interest in massive tree planting programs in the towns of low income residents that allowed the local people to have a preference of planting the

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trees of their own choice, which increased their diversity. The agency generally removes all the trees, while planting one or two species of its choice. For that reason, Orangi town had the highest species diversity and one of the lowest tree densities. Lyari, a town of lowest income residents, had the lowest tree density and one of the lowest species diversities, which shows lack of appreciation of street trees by both the agency and local residents. Moreover, the town lacks

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wide verges and spacious median on its streets, which could be one of the reasons of low tree planting. Nonetheless, some affluent towns demonstrated very low species diversity, mainly due to monoculture planting on their streets. For instance, Gulshan Iqbal demonstrated low species diversity with very high species richness. The town accounted for 75 % trees of Conocarpus

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erectus in its street tree community. Low species diversity in street tree community is one of the most serious management issues that show its overreliance on merely a few species (McPherson

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et al., 2016).

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It is worth mentioning that the species diversity on the street of Karachi was found lower than that of twenty-two U.S cities (McPherson and Rowntree, 1989) and the towns of Eastern Cape,

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South Africa (Kuruneri-Chitepo and Shackleton, 2011).

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5.0 Conclusion

The diversity, density and composition of the street trees in the city could be increased by

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planting new and well adapted species from diverse genera and families in treeless transects because these transects were found in almost every town. However, greater number of treeless transects were found on the narrow road, particularly in the towns of low income population. The dominance of few species in the city could be reduced by planting new species on the extensive

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spaces, which are available along all the road categories. Moreover, additional taxa should be introduced in the tree community of the towns that have low species richness and diversity. Furthermore, exotic species could be planted to enrich the diversity. However, invasive species, which spread without human assistance, must not be planted in the city.

19

For a sustainable and healthy urban forest, the trees of high taxonomic diversity should be evenly distributed on the streets (Sjöman, et al., 2012; McPherson, et al., 2016). The tree community should not be dominated by few species and genera. Moll (1989) suggests that the proportion of any single species should not exceed 5% in urban tree community. Santamour (1990) extended “10:20:30” guidelines to raise the taxonomic diversity, which suggest that the urban forest should not exceed 10% trees of any species, 20% tree of any genus, 30% trees of any family.

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Overreliance on a few species could be a potential threat of their complete elimination from the

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streets due to diseases, pests or environmental changes.

20

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of ro -p re lP ur na Jo Fig 1: Karachi with its 18 towns and Cantonments

28

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Fig 2: Estimated marginal means of tree density in towns of different socioeconomic status.

29

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Fig 3: Estimated marginal means of species diversity in towns of different socioeconomic status.

30

r = 0.51 (p < 0.03)

16 14 12 10 8

y = 0.7591x + 1.1542

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6 4 2

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Trees per Thousand Human Population

18

0 1

2

3

8

9

10

High

-p

Low

4 5 6 7 Socioeconomic Status of Towns

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Fig 4: Pearson’s Correlation between socioeconomic status and trees per thousand human population of towns

31

Myrtaceae

Family

Moraceae Meliaceae Zygophylaceae Combretaceae

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Eucalyptus

Genus

Ficus

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Azadirachta

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Guaiacum Conocarpus

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Ficus virens

Species

Eucalyptus ssp

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Azadirachta indica

Guaiacum officinale

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Conocarpus erectus

0

20

40

60

Percentage

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Fig 5: Proportion of top five taxa in street tree community in Karachi

32

Ficus rubiginosa

Relative Frequency Ficus benghalensis

Relative Dominance Albizia julibrissin

Relative Abundance

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Ficus religiosa

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Phoenix dactylifera

-p

Ficus virens

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Eucalyptus

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Guaiacum officinale Azadirachta indica

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Conocarpus erectus

0

20

40

60

Percentage

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Fig 6: Relative frequency, relative dominance and relative abundance of top 10 Importance value species on wide roads in Karachi

33

Ficus religiosa Relative Frequency

Ficus rubiginosa Relative Dominance Relative Abundance

Peltophorum pterocarpum

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Albizia julibrissin

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Eucalyptus

-p

Ficus microcarpa

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Ficus virens

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Azadirachta indica

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Guaiacum officinale

Conocarpus erectus

0

10

20

30 40 Percentage

50

60

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Fig 7: Relative frequency, relative dominance and relative abundance of top 10 importance value species on medium width roads in Karachi

34

Ziziphus jujuba

Relative Frequency Cocos nucifera

Relative Dominance Relative Abundance

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Guaiacum officinale

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Ficus rubiginosa

-p

Prosopis juliflora

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Eucalyptus

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Ficus microcarpa

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Ficus virens

Azadirachta indica

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Conocarpus erectus

0

10

20

30

40

50

60

Percentage +

Fig 8: Relative frequency, relative dominance and relative abundance of top 10 importance value species on narrow roads in Karachi

35

Narrow Roads

60.1

Medium Roads

76.1

Wide Roads

81.3

Entire Karachi

78.9

Landhi

51.8

Bin Qasim

54.0

Liaquatabad

Korangi

59.8

Orangi

64.7

Baldia

ro

69.1

77.8

SITE

78.2

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Shah Faisal

Jamshed

78.5

Saddar

re

79.7

North Nazimabad

82.9

Gulberg

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85.7

New Karachi Gulshan Iqbal

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Malir Lyari

86.6 87.2 90.0 91.0

Keemari

96.0

Gadap

95.4

0%

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57.3

20%

40%

Native

60%

80%

100%

Exotic

Fig 9: Proportion of native and exotic street trees on different road categories and towns in Karachi.

36

Table 1: Different Attributes of Street Trees along Different Street Categories in Karachi Street Type Sr #

Attributes

1

Wide Road

Medium Width Road

Narrow Road

Transect

867

354

282

231

2

Genera

46

35

36

26

3

Species

62

48

48

34

4

Shannon Index

1.72

1.49

1.92

5

Simpson Index

2.48

2.18

2.92

7

Trees

6,507

4,533

1,634

340

8

Trees per transect

7.5 + 15.1

12.9 + 20.8

5.8 + 8.1

1.4 + 3.6

9

Species per transect

1.4 + 1.8

1.8 + 1.9

1.4 + 1.7

0.7 + 1.3

10

Top 5 species (%)

85.4

89.1

81.3

65.9

11

Treeless transect

44.5

2.57

re

-p

ro

6.36

39.4

71.1

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31.1

of

Entire Karachi

37

Table 2: Socioeconomic Status and different attributes of Street Tree Community in different Towns of Karachi

Sr . #

Town

Price per Sociosqua econo re mic yard Class (US $)

1

Baldia

6

1

22,073 510.2 55

2

Gadap

6

1

200

3

Lyari

13

2

4

Orangi

13

5

Korangi

13

6

Reside nts Per km2

Road No. of Total Total Shann Leng Transe Gene Speci on th cts ra es Index (km)

Simps on Index

18

1.99

3.48

2

2

0.19

1.07

117,303 189.1 47

3

4

0.52

2

46,860 742.1 75

23

27

2.42

2

20,469 716.0 70

12

16

Malir

24.5 3

35,140 376.2 14

3

4

7

SITE

24.5 3

28,105 274.6 53

18

8

Bin Qasim

24.5 3

914

13

9

Landhi

36

4

25,584 426.7 47

Kemari

36

4

1,357

1 5

ro

5.89

0.84

1.69

24

2.25

4.53

17

1.72

3.77

7

8

1.79

5.15

814.5 22

9

11

0.37

1.12

39.5 5

49,446 517.5 26

9

11

0.47

1.41

39.5 5

43,657 285.2 28

11

13

1.48

2.64

lP

re

792.4 99

-p

4.62

61

6

87,374 309.2 14

17

21

2.34

6.17

86

7

48,560 284.1 33

23

25

1.16

1.63

132.5 8

44,034 308.8 30

16

19

1.46

2.73

132.5 8

17,912 845.2 103

25

30

1.12

1.70

Jamshed 168.5 9

48,567 544.7 86

22

27

1.56

2.11

Saddar

38,532 350.2 63

23

29

1.71

2.57

Gulberg

North Nazimab ad Gulshan Iqbal

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1 6 1 7 1 8

New Karachi Shah Faisal Liaquata bad

1.27

1.92

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1 0 1 1 1 2 1 3 1 4

1519. 7 8

215

10

1.8 + 4.2 6.1 + 5.0 1.4 + 5.5 3.0 + 4.5 2.8 + 4.2 2.9 + 3.5 4.3 + 5.4 5.9 + 8.3 3.0 + 4.7 24.3 + 14.0 13.9 + 19.3 6.6 + 12.1 13.2 + 12.0 12.7 + 31.9

67.3 28.6

of

13

Treele Trees ss Per Transe Transe ct ct (%)

20.0 + 20.4 14.2 + 21.2 6.5 + 19.1 9.8 + 15.2

80.9 49.3 57.1 42.9 35.9 59.6 57.5 0 28.0 46.4 74.1 42.4 0 25.2 52.3 34.9

38

Table 3: Importance values and populations of different species along the streets in Karachi (Native *)

Araucariaceae

Arecaceae

Bignoniaceae

Boraginaceae

Cordia

Capparaceae Caricaceae Casuarinaceae

Crateva Carica Casuarina Conocarpus Terminalia

Combretaceae

ur na

Albizia Cassia

Jo

Fabaceae

Dalbergia Delonix Erythrina Leucaena Pithecellobium Parkinsonia Peltophorum Prosopis Tamarindus Punica Bombax Ceiba

Lythraceae Malvaceae

Importance Value 0.40 0.79 3.00 0.11 0.11 3.12 0.41 5.65 1.25 0.13 0.12 0.42 0.27 0.26 0.12 0.83 0.23 1.24 0.11 0.42 130.21 1.51 5.94 2.42 0.85 0.75 0.38 0.37 1.09 1.86 0.84 0.91 1.65 2.90 0.36 0.11 0.24 0.15

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Apocynaceae

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Mangifera Polyalthia Alstonia Nerium Araucaria Cocos Livistona Phoenix Roystonea Washingtonia Millingtonia Tabebuia Fernandoa

-p

Anacardiaceae Annonaceae

Street Trees Mangifera indica L. 4 Polyalthia longifolia Sonn., Thwaites 9 *Alstonia scholaris L., R.Br. 33 Nerium oleander L. 1 Araucaria cunninghamii Sweet 1 *Cocos nucifera L. 49 Livistona chinensis (N.J. Jacquin) R. Brown 3 *Phoenix dactylifera L. 81 Roystonea regia (Kunth) O.F. Cook 13 Washingtonia robusta Wendl 1 Millingtonia hortensis L. f., 2 Tabebuia heterophylla (DC.) Britton 7 Fernandoa adenophylla (Wall. Ex G. Don) 3 *Cordia gharaf (Forssk.) 2 *Cordia macheodii (Griff.) Hook.f. & Thoms 1 *Cordia myxa L. Sp. Pl. 9 Cordia sebestena L. 2 *Crateva adansonii DC. 27 Carica papaya L. 1 Casuarina equisetifolia L. 8 Conocarpus erectus L. 4023 *Terminalia catappa L. 20 *Albizia julibrissin Durazz. 67 *Albizia lebbeck L., Benth 26 *Cassia fistula L. 10 Cassia siamea Lamk. 13 *Dalbergia sissoo Roxb. 3 Delonix regia (Bojer) Rafin., 4 *Erythrina suberosa Roxb. 14 Leucaena leucocephala Lam., de Wit 19 Pithecellobium dulce Rox., Benth 9 Parkinsonia aculeata L. 12 Peltophorum pterocarpum (DC.) Baker 12 Prosopis juliflora (Swart) DC. 33 Tamarindus indica L. 4 *Punica granutum L. 1 *Bombax ceiba L. 3 *Ceiba pentandra (L.) Gaertn. 3 Species

re

Genus

lP

Family

39

16 554 20 4 35 7 11 1 68 15 55 52 4 161 2 34 232 3 50 43 18 1 1 587

-p

re

Jo

ur na

lP

1.47 34.14 1.52 0.52 3.56 0.69 0.76 0.12 6.45 1.26 5.46 4.63 0.57 14.71 0.21 2.59 16.67 0.34 1.07 3.46 1.78 0.12 0.11 26.26

of

*Thespesia pupulnea L. *Azadirachta indica Adr. Juss Meliaceae *Melia azedarach L. *Ficus amplissima J.E. Sm. *Ficus benghalensis L.,Sp. Pl. Ficus benjamina L. Ficus elastica Rox., Ficus lyrata Warb. Ficus Ficus microcarpa L. f., Moraceae *Ficus racemosa L. *Ficus religiosa L., Sp. Pl. Ficus rubiginosa Deaf. ex Vent., lard *Ficus rumphii Blume *Ficus virens Dryand. Morus Morus nigra L. Moringaceae Moringa *Moringa oleifera Lam. Eucalyptus Eucalyptus ssp Myrtaceae Syzgium Syzgium cumini (L.) Skeels Poaceae Dendrocalamus *Dendrocalamus stricta Roxb. Nees *Ziziphus jujuba Mill., Rhamnaceae Ziziphus *Ziziphus mauritiana Lam. Rutaceae Aegle *Aegle marmelos (L.) Correa Sapotaceae Manilkara Manilkara zapota (L.) P. van Royen Zygophylaceae Guaiacum Guaiacum officinale L.

ro

Thespesia Azadirachta Melia

40

Table 4: Effects of Town Socioeconomic Status and Road Width on Tree Density and Species Diversity.

Dependent variable: Tree density F statistic

P value

Socioeconomic Class

9

2.343

0.013

Road Category

2

30.186

0.000

Socioeconomic Class * Road Category

17

1.799

Error

838

Dependent variable: Species diversity

F statistic

P value

9

4.156

0.000

2

21.775

0.000

Socioeconomic Class * Road Category

17

2.723

0.000

Error

838

re

df

0.024

ro

-p

R2 = 0.180 (Adjusted R2 = 0.152)

of

df

Socioeconomic Class

lP

Road Category

Jo

ur na

R2 = 0.206 (Adjusted R2 = 0.179)

41