ph.d. thesis by kamran khan

ECOLOGICAL AND SOCIO-ECONOMIC IMPACTS OF

MONOCULTURE OF EXOTIC TREE SPECIES IN

DISTRICT MALAKAND, PAKISTAN

Ph.D. THESIS

BY

KAMRAN KHAN

CENTRE OF PLANT BIODIVERSITY

UNIVERSITY OF PESHAWAR

Session 2015-2016

ECOLOGICAL AND SOCIO-ECONOMIC IMPACTS OF

MONOCULTURE OF EXOTIC TREE SPECIES IN DISTRICT

MALAKAND, PAKISTAN

A thesis submitted to the Centre of Plant Biodiversity, University of Peshawar in

partial fulfilment of the requirement for the degree of

DOCTOR OF PHILOSOPHY

IN

PLANT BIODIVERSITY AND CONSERVATION

BY

KAMRAN KHAN

RESEARCH SUPERVISOR: DR. ASAD ULLAH

Graduate Studies Committee:

1. Dr. Asad Ullah Convener

2. Prof. Dr. Sardar Khan Member

3. Dr. Zahir Muhammad Member

4. Dr. Sana Ullah Khan Member

5. Dr. Syed Ghias Ali Member

CENTER OF PLANT BIODIVERSITY

UNIVERSITY OF PESHAWAR

SESSION 2015-2016

PUBLICATION OPTION

All rights of publication are hereby reserved by the scholar, including right to reproduce

this thesis in any form for a period of 5 years from the date of submission.

Kamran Khan

Dedication

Dedicated to my Parents

and Teachers

Landcover Map of Malakand Protected area

Source: Forest Management Centre, Khyber Pukhtunkhwa Environment

Department, Pakistan.

VITAE

Born on 1st January 1987 in Thana Malakand, Khyber Pakhtunkhwa, Pakistan.

BS (Hons.) in Forestry from University of Malakand in 2010.

M.Phil. in Plant Biodiversity and Conservation from University of Peshawar in 2016.

Presently working as Range Forest Officer at Pakistan Forest Institute Peshawar.

Major Field of Study

Plant Biodiversity and Conservation

S. No Course No Title of course Tutor name

1 CPB-801 Plant Systematics (Theory) Dr. Asad Ullah

2 CPB-801 Plant Systematics (Lab.) Dr. Asad Ullah

3 CPB-806 Plant Reproductive Biology

(Theory)

Dr. Syed Ghias Ali

4 CPB-806 Plant Reproductive Biology

(Lab.)

Dr. Syed Ghias Ali

5 CPB-809 Phylogenetics of Vascular

Plants (Theory)

Dr. Asad Ullah

6 CPB-809 Phylogenetics of Vascular

Plants (Lab.)

Dr. Asad Ullah

7 CPB-811 Soil Plant Relationship

(Theory)

Dr. Fazal Hadi

8 CPB-813 Research Methodology

(Theory)

Dr. Syed Ghias Ali

TABLE OF CONTENTS

S. No. Title Page No.

Acknowledgements i

Abstract iii

1 CHAPTER 1: INTRODUCTION 1

1.1 Description of the study area 1

1.1.2 Area location and boundaries 1

1.1.3 Soil and geology 1

1.1.4 Flora and fauna 1

1.1.5 Climate 2

1.1.6 Socio-economic activities 2

1.2 Topic introduction 3

1.3 Problem statement 4

1.4 Aim and objectives 6

1.5 Justification of study 6

1.6 Socioeconomic benefits 6

2 CHAPTER 2: REVIEW OF LITERATURE 7

3 CHAPTER 3: MATERIALS AND METHODS 31

3.1 Selection of research plots 31

3.2 Data collection 32

3.3 Assessment of ecological impacts 33

A) Study on undergrowth vegetation 33

Undergrowth vegetation survey 33

Determination of quadrat size 33

Quadrat sampling and recording 33

Specimen collection and preservation 34

Specimen examination 34

Specimen identification and nomenclatural Information 35

Supplementary data collection 35

Data analysis 35

Shannon-Wiener Diversity Index 38

B) Study on soil physico-chemical properties 38

Soil sample collection 38

Soil data analysis 39

3.4 Socio-economic impacts of monoculture of exotic tree species 41

Selection and investigation of woodlots and tree growers 41

Benefit cost analysis on the woodlots plantations of exotic tree

species

42

Focus group discussion 43

Key informant interview 44

Secondary data collection 45

3.5 Discharge rate and water table measurement 45

4 CHAPTER 4: RESULTS AND DISCUSSIONS 46

4.1 Ecological impacts 47

4.1.1 Undergrowth vegetation 47

4.1.2 Floristic composition and taxonomic diversity 47

4.1.3 Phytosociology of undergrowth vegetation 56

Undergrowth plant density 56

Relative density 58

Frequency 60

Relative frequency 60

Abundance 61

Relative abundance 62

Communities structure 63

4.1.4 Phytodiversity index 64

4.1.5 Tree productivity 66

4.2 Soil physico-chemical properties 68

pH 68

Organic matter (OM) 70

Organic Carbon (OC) 73

Soil Electric conductivity (EC) 74

Nitrogen (N) 76

Phosphorus (P) 78

Potassium (K) 80

Calcium Carbonate (CaCO3) 81

4.3. Socio-economic impacts of the monoculture of exotic tree species 83

4.3.1 Basic information of the tree growers 83

Education 84

Occupation 84

Land use pattern 84

4.3.2 Characteristics and factors of woodlot plantation of exotic tree

species

87

4.3.3 Expenditure for woodlot plantation of exotic tree species 90

4.3.4 Benefit cost analysis on woodlots of exotic tree species 93

Net Present Value, Internal Rate of Return and Benefit Cost Ratio 93

Sensitivity analysis 93

Plantation damaging factors 96

Purpose of growing exotic species 96

4.3.5 Sources of energy for fulfilling domestic/commercial needs of

people

97

4.3.6 Species used for fuelwood, rates/mound and sale in the market 98

4.3.7 Relative merits and demerits of selected exotic and indigenous

tree species

98

4.4 Impact of exotic plantations on ground water 99

4.4.1 Impact of exotic plantations on springs 100

4.4.2 Impact of exotic plantations on discharge rate of springs 101

5 CHAPTER 5: CONCLUSIONS AND

RECOMMENDATIONS

103

5.1 Conclusions 103

5.2 Recommendations 103

References 105

Appendices 120

Plagiarism certificate 226

LIST OF TABLES

Table No. Title Page No.

Table-4.1 Shannon-Wiener diversity index values recorded for different

research plots.

65

Table-4.2 Mean values of Shannon- weiver diversity index of different

research plots calculated after analysis using statistics 8.1

software two-way ANOVA (LSD) was used to test for significant

differences (P<0.05) for marginal means of variables.

66

Table-4.3 Density of trees, height, DBH, basal area and gross tree stem

volume in different plots of exotic and indigenous species.

67

Table-4.4 Mean values of different physico-chemical parameters of soil of

different research plots.

68

Table-4.5 Means showing nutritional status of different species plots. 76

Table-4.6 Basic information of woodlot tree grower of District Malakand. 85

Table-4.7 Characteristics of different woodlot plantation raised by the tree

growers in District Malaakand.

88

Table-4.8 Expenditure of tree growers for raising one-hectare woodlot

plantations in District Malakand.

91

Table-4.9 Sensitivity of BCR and NPV with reference to changes in the

interest rate for one hectare woodlot monoculture plantation in

District Malakand.

93

Table-4.10 Future valuation and expected profit of woodlot trees per hectare

raised in District Malakand.

94

Table-4.11 Rate per mound of different species and their sale in the local

market

98

Table-4.12 Depth of water table before and after exotic plantation 99

Table-4.13 Number of springs before and after exotic plantations 100

Table-4.14 Discharge rate of springs before and after exotic plantations 101

LIST OF FIGURES

Figure No. Title Page No.

Fig. 4.1 Taxonomic diversity of flora of all research plots. 48

Fig. 4.2 Taxonomic diversity of flora of indigenous research plots. 49

Fig. 4.3 Taxonomic diversity of flora of exotic research plots. 49

Fig. 4.4 Morphological diversity of plants species of all plots. 51

Fig. 4.5 Morphological diversity of plants species of indigenous plots. 52

Fig. 4.6 Morphological diversity of plants species of exotic plots. 52

Fig. 4.7 Numbers of annuals, perennials and biennials in all research plots. 53

Fig. 4.8 Numbers of annuals, perennials and biennials in indigenous plots. 53

Fig. 4.9 Numbers of annuals, perennials and biennials in exotic plots. 54

Fig. 4.10 Species composition in different tree plots in spring, monsoon and

winter seasons in Malakand area.

54

Fig. 4.11 Number of all undergrowth plants and number of tree species in

exotic and indigenous research plots.

55

Fig. 4.12 Number of undergrowth tree species found in different research

plots in the research area.

56

Fig. 4.13 Undergrowth densities per hectare considering all undergrowth

species in three seasons in different research plots in the study area.

58

Fig. 4.14 Average undergrowth density per hectare considering all

undergrowth species in different tree plots in research area.

58

Fig. 4.15 Showing soil pH of plots of different plants in different seasons. 69

Fig. 4.16 Showing organic matter (%) in plots of different plants in

different seasons.

71

Fig. 4.17 Showing soil organic Carbon (%) in plots of different plants in

different seasons.

73

Fig. 4.18 Showing soil electrical conductivity of plots of different plants in

different seasons.

75

Fig. 4.19 Showing Soil total Nitrogen in percent of plots of different plants

in different seasons.

76

Fig. 4.20 Showing soil available Phosphorus (ppm) of plots of different

plants in different seasons.

78

Fig. 4.21 Showing soil Potassium (ppm) of different plants in different

seasons.

80

Fig. 4.22 Showing Calcium Carbonate (mmole /meter) of plots of different


82

Fig. 4.23 Tree grower perception (%age) on plantation damaging factors. 96

Fig. 4.24 Sources of energy used for fulfilling domestic/commercial needs

of the people.

97

LIST OF APPENDICES

S. No. Title Page

No.

Appendix-1 Checklist of undergrowth plant species recorded from

research plots at Malakand.

120

Appendix-2 Total no. of individuals, Density, Relative density, frequency,

relative frequency, abundance, relative abundance considering

all undergrowth species in indigenous plots.

127



all undergrowth species in exotic plots.

133



only tree undergrowth species in indigenous plots.

137



only tree undergrowth species in exotic plots.

138

Appendix-6.1 Shannon-Wiener diversity index (H) values considering all

undergrowth plant species recorded from Pinus roxburghii

plots during spring season

139



plots during monsoon season.

142



plots during winter season.

145

Appendix-6.4 Shannon-Wiener diversity index (H) values considering

undergrowth tree species only recorded from Pinus roxburghii

plots during summer season.

148




149




150


undergrowth plant species recorded from E. camaldulensis


151




153




155


undergrowth tree species only recorded from E. camaldulensis


157



plots during monsoon season

158




159


undergrowth plant species recorded from Acacia modesta

plots during spring season.

160




163




166


undergrowth tree species only recorded from Acacia modesta


169




170




171

Appendix-6.19 Shannon-Wiener diversity index (H) value considering all

undergrowth plant species recorded from R. pseudoacacia


172




174



plots during winter season

176


undergrowth tree species only recorded from R. pseudoacacia


178




179




180

Appendix-6.25 Anova results for comparison of SWDI (H) values of all

research plots considering all undergrowth.

181

Appendix-6.26 Anova results for comparison of SWDI (H) values of all

research plots considering only trees species as undergrowth.

182

Appendix-6.27 Anova results for comparison of SWDI (H) values B/w exotic

and indigenous research plots considering all undergrowth.

183

Appendix-6.28 Anova results for comparison of SWDI (H) values B/w exotic

and indigenous research plots considering only tree species as

undergrowth.

184

Appendix-7.1 Different soil parameters recorded from exotic and indigenous

tree plots during winter season 2017.

185


tree plots during spring season 2018.

187


tree plots during monsoon season 2018.

189

Appendix-8 Soil pH 191

Appendix-9 Organic Matter (OM) 194

Appendix-10 Organic carbon (OC) 197

Appendix-11 Electric conductivity (EC) 200

Appendix-12 Total Nitrogen (N) 203

Appendix-13 Phosphorus (P) 206

Appendix-14 Potassium (K) 209

Appendix-15 Calcium Carbonate (CaCO3) 212

Appendix-16 Calculation of Internal Rate of Return (IRR) 215

Appendix-17 Calculation of Net present value (NPV) and Benefit cost Ratio

(BCR)

216

Appendix-18 Average benefit cost analysis for one-hectare woodlot

plantations in District Malakand

217

Appendix-19 Questionnaire 218

Appendix-20 Photographic Presentation 220

LIST OF MAP

S. No. Map Title Page No.

1 Map of the research plots located at District Malakand 31

i

ACKNOWLEDGEMENTS

First of all, thanks to ALLAH Almighty, the most merciful and beneficient enabling me

to complete this task. Darood-Wa-Salam on his Prophet Muhammad (PBUH), the

source of knowledge and wisdom for the entire humanity.

Its my great pleasure to express my heartiest gratitude, most sincere appreciation and

profound thanks to my supervisors Dr. Asad Ullah, Director Centre of Plant

Biodiversity, University of Peshawar, Khyber Pukhtunkhwa, Pakistan for his overall

supervision, fruitful criticism, valuable suggestions, proper evaluation and continuous

encouragement throughout the research period.

My sincere appreciation goes to all honorable inland and foreign members of the thesis

evaluation committee for their critical and constructive comments and suggestions on

all aspects of the dissertation. I gracefully acknowledge the valuable comments, critics

and suggestions made by Prof. Jerry Roberts, Deputy Vice Chancellor Research and

Enterprise, University of Plymouth, UK for overall improvement of this research work.

I am highly grateful to Dr. Syed Ghias Ali, Dr. Syed Mukaram Shah and all the teaching

and supporting staff of Centre of Plant Biodiversity, University of Peshawar for their

encouragement and support throughout my study period.

I am also thankful to Prof. Dr. Zafar Iqbal, Meritorious Professor, Dean Faculty of Life

and Environmental Sciences, Prof. Dr. Bashir Ahmad, Ex-Dean Faculty of Life and

Environmental Sciences for his valuable suggestions in the research proposal, Prof. Dr.

Siraj-Ud-Din, Dr. Zahir Muhammad, Department of Botany, Prof. Dr. Akram Shah,

Department of Zoology and Prof. Dr. Sardar Khan, Department of Environmental

Sciences, University of Peshawar for their valuable suggestions and corrections in the

research proposal and dissertation throughout the entire study period.

I am especially grateful to Mr. Ghulam Jelani, Lecturer, Department of Botany

University of Peshawar, for his help in identification of plants.

My sincere gratitude goes to Mr. Yousuf Noor, Senior Research Officer, Dr. Samad,

Research Officer and staff of Agriculture Research Institute at Tarnab Farm, Peshawar

for providing permission and laboratory facilities for soil analysis. I must thank to Khan

ii

Afzal, Laboratory Attendant and Staff of Agriculture Research Institute at Tarnab Farm,

Peshawar for providing support and facilities for soil analytical work and also for their

help and suggestions. Thanks are also due to Professor Dr. Farman Ullah, Soil and

Environment Department, The University of Agriculture, Peshawar and Mr. Mukhtiar

Ahmad, M.Phil. Scholar, Soil and Environment Department, The University of

Agriculture, Peshawar for helping in the soil data analysis. I am also thankful to Dr.

Syed Ghias Ali, Assistant Professor, Centre of Plant Biodiversity for helping and

guiding me in proper statistical interpretation of the results.

I am also highly thankful to the field staff of Khyber Pakhtunkhwa Forest Department,

Malakand Forest Division, Malakand for helping me in the data collection during field

survey from the research area throughout the study period. My sincere gratitude to the

forest villagers, local peoples of the study area who consented to provide information

without which it would not be possible to conduct this research work.

Last but not the least, I am extremely grateful to my beloved parents, brothers, sisters,

friends and other relatives for their continuous moral support and encouragement.

Kamran Khan

iii

Ecological and Socio-economic Impacts of Monoculture of Exotic Tree Species in

District Malakand, Pakistan

Abstract

This study was carried out to investigate the impacts of monoculture of exotic

tree species (Eucalyptus camaldulensis and Robinia pseudoacacia) on species

composition and diversity of the undergrowths, physico-chemical properties of soil,

ground water and the socio-economy of the local people in relation to indigenous (Pinus

roxburghii and Acacia modesta) tree plots in district Malakand. Data was collected

from 12 research plots of exotic and indigenous tree species located in public and

private land, and 30 woodlots of exotic tree species through intensive field visits

conducted from April 2017 to March 2019.

A total of 174 plants species which belongs to 74 families and 150 genera were

reported in the selected research plots of trees of indigenous (Pinus roxburghii and

Acacia modesta) and exotic (Eucalyptus camaldulensis and Robinia pseudoacacia)

species. Among the recorded species 143 (82%) were dicotyledons, 26 (15%) species

were monocotyledons and 4 (2.3%) were pteridophytes while only 1 (0.7%) of the

plants recorded were gymnosperms. In both exotic and indigenous tree stands, 97% of

the plant species were Angiosperms, 2.3% were Pteridophytes and only 0.7% were

Gymnosperms. A total of 149 undergrowth species including 23 tree species were found

in indigenous stand and 111 species including 18 tree species in exotic stands. The

exotic tree plots comprised 22% less species in comparison to indigenous plots.

In spring, monsoon and winter seasons, 83 species each in spring and monsoon

and 62 undergrowth species were found in winter season in Pinus roxburghii plots. In

Acacia, Eucalyptus and Robinia plots a total of 89,70 and 67 species respectively were

found in each spring and monsoon season while 67,58 and 34 species respectively in

winter season.

In indigenous tree plots, Acacia modesta was found to have the highest relative

density whereas in exotic plots Robinia pseudoacacia was most prevalent. The shrub

species Dodonaea viscosa was found to have the highest relative frequency in both

exotic and indigenous tree plots respectively.

iv

The average value of Shannon-Wiener diversity index was 3.41 and 3.73

collectively in all exotic and indigenous plots respectively, which depict that the extent

of species diversity was higher in indigenous tree plots than in exotic tree plots. Out of

the four categories of sampling research plots, the Pinus roxburghii plots were clearly

rich in species diversity.

Result showed that soil properties were significantly different in indigenous and

exotic research plots. Soil OM, OC, pH, N, P, K and Calcium Carbonate of the soil of

Acacia modesta plots, Pinus roxburghii plots, Robinia pseudoacacia plots and

Eucalyptus camaldulensis plots were significantly different. Findings of these results

showed that, soil in the exotic species plots of Robinia pseudoacacia and Eucalyptus

camaldulensis were less fertile as compared to the soil in the indigenous plots of Acacia

modesta plots and Pinus roxburghii.

The two major reasons for plantations of fast growing Eucalyptus camaldulensis

over other species for woodlot plantation by the local people were the production of

fuel wood and early income generation from their sale. On average, a tree grower

spends Rs. 159144 for raising one-hectare woodlot plot, and is expecting to sell the

timber for Rs. 2049478 ha after completion of tree rotation, whereas the expected net

profit from timber sale was Rs. 1956206 per ha. Benefit cost analysis for one-hectare

private woodlot plantations showed that, the BCR was 1.25 on ±10 years’ rotation

which was comparatively higher and the NPV was Rs. 165982, whereas the IRR was

14.33% found to be comparatively higher. The base case scenario (lending interest rate)

in interest rate 10% showed the BCR 1.25 and NPV Rs. 165982, which was profitable

in plantation business. If the less interest rate trend found in future (government lending

interest rate decreasing) that will confirm more BCR and NPV, which indicated better

profit for tree growers. The benefit cost analysis indicated that the woodlot project was

financially viable.

Local peoples were found to be interested in planting fast growing exotic tree

species to meet their immediate financial demand within a short period. The

monoculture of exotic species seems financially profitable for the short term projects

and to have a promising prospect in district malakand and its adjacent areas, but if the

long term perspectives are considered then ultimately it is not economically viable and

not appropriate to ensure the sustainability of biodiversity and ecosystem conservation.

v

During the questionnaire survey, the villagers and tree growers identified some

problems with the exotic species, such as the trees of exotic species absorb more ground

water and that other trees hardly grow under them; they had a low number of twigs and

leaves that not decompose after falling on the ground; they allow minimum collection

of fuel wood; and growth of crops is slow under the exotic trees etc. They also opined

that, it was not meaningful to replace Acacia modesta and Pinus roxburghii trees by

any exotic species. Monoculture of exotic species should, therefore, be discouraged for

afforestation but might be operational in some degraded, barren or specified lands.

1

CHAPTER-1

INTRODUCTION

1.1 DESCRIPTION OF THE STUDY AREA

The location, soil, climate, floristic composition and socio-economic aspects of

the study area of District Malakand have been described below.

1.1.2 AREA LOCATION AND BOUNDARIES

The total area of District Malakand is 952 km2. It lies on 34°22՜ to 35°43՜ N

latitudes and 71°36՜ to 72°12՜ E longitudes. The elevation of the study area ranges from

600 to 850 meters. It is surrounded by a series of mountains on the North East which

separate it from District Swat and other ranges of mountains to the west separate it from

Bajaur and Mohmand Agencies. It is surrounded on the north by District Lower Dir, on

north west by District Bajuar, the District Buner lies on the East, the District Mardan is

situated on the south and Charsadda district and Mohmand agency on the south west

(GOP, 2017).

1.1.3 SOIL AND GEOLOGY

The soil composition of Malakand is sandy-loam with gravel layers/loam and

developed from old pediment materials. Soil of the area is either rain fed or irrigated.

The following rock types are present in the area. The northern part of the protected area

is occupied by the main mental thrust material also known as melange zone rocks.

Composed of voleaie, phyllites, shales, green schist, quartzite and other oceanic meta

sediments. The middle part of the agency comprised meta sediments and granite rocks.

The meta sediment is divided into four formations viz. Marghuzar formation. Rahsala

formation, Saidu formation and granitic formation. The granitic formations are further

divided to Malakand granite, Chakdara granite and Bazdara granite. The Malakand

power house Tunnel passes through these rocks formations. In the south near Dargai is

the ophite rock known as Dargai Ophiolite. These Ophiolite rocks contain chromate,

soapstone, asbestos manganese and magnesite. Further south up to Skhakot is the

alluvial plain area, where maximum population of the Malakand is living (GOP, 2017).

1.1.4 FLORA AND FAUNA

Malakand Scrub forest is dominated by native species of Acacia modesta, Pinus

roxburghii, Dodonea viscosa, Olea ferrugenia, Ziziphus mauratiana, Z. numularia,

Acacia nilotica, Punica granatum, Monotheca buxifolia, Capparis aphylla,

2

Cymbopogan jawarancusa, Cynodon dactylon, Cenchrus ciliaris and Chryspogan.

Commonly occurring animals in the area including jackal, leopard, monkey and

wolf. As a result of huge deforestation they became scarce.

1.1.5 CLIMATE

The study area has a dry sub-tropical climate. The rainfall is irregular, mostly

occurring in winter from December to March. It has a hot summer and cold winter. The

average rainfall is low which ranges from 600 to 650 mm (GOP, 2008) and therefore

soil requires artificial irrigation. The month of June is the hottest, having a mean

maximum temperature of 40 oC. The coldest months are December and January, with a

mean minimum temperature of 0 oC (GOP, 2013). Snowfall occurs much rarely and

sometime occurs on mountain tops, which melts rapidly. Frost occurs more commonly

and start by the mid November and its intensity is severe during December and January.

1.1.6 SOCIO-ECONOMIC ACTIVITIES

About 50% of the land area of Malakand Agency is cultivable while the

remaining consist of hills. The cultivable lands are mostly privately held. Nearly 63%

of the households are landless and rely upon labour to earn their livelihood. 32%

among the owners has landholding size less than hectare and 45% of them have

landholding size less than 4 hectares. Agriculture crops like sugarcane, rice wheat,

corn are major crops on irrigated lands. Major portion of the cultivated lands are also

used for growing fruit orchards like citrus, peach and guava. The people of the study

area are interested in raising fast growing tree species around their fruit orchards or on

the boundaries of their agriculture fields, such as Populus deltoides, Ailanthus

altissima and Eucalyptus species. They grow these trees for timber as well as fuel

wood production for their family consumption. About 40% of farmers depend on

agriculture for their livelihood.

The mountains are mostly owned by communities, and sometimes different

segments of the community. The area has protected forest in which the rights to collect

fuelwood and fodder exist. Therefore, most of the people have access to go and collect

the same from the forest which has created difficulties in management of the existing

forest area. The hillsides are mostly used by the local people for grazing livestock and

fuel wood collection. Some parts located at the west side of Malakand are severely

degraded and have very low production. The estimated forest cover is 7.2% of the area.

3

1.2 TOPIC INTRODUCTION

Pakistan forests cover an area of about 4.2 million ha i.e. 4.8% of the total land

area which is too low to fulfil the environmental and socio-economic needs of the

country when compared with the required 25% for the developing countries (GOP,

2005 and FAO, 2000). As a result of excessive rate of deforestation and degradation of

environment, Pakistan has limited forest resources having lowest proportions of area

under forest (Mcketta, 1990). Production from state owned forest are not enough to

meet the demand for timber and fuel wood, raw material for industries, energy

requirements of the agricultural sector and fodder for livestock (Sheikh, 1987),

dependency on conventional fuels like firewood (which alone accounts for 50% of rural

fuel needs), cow dung and agricultural residue indicates the importance of trees in

solving energy needs of rural communities (Siddiqui, 1997). To bridge the gap between

demand and supply of the forest produces, a number of tree plantation

projects/programs were launched by the Government and development agencies that

basically targeted the fallow land, marginal land, roadsides, railway, canal/river banks

and embankments (FAO/UNDP, 1981).

In Pakistan deliberate and planned attempts under the umbrella of social forestry

were made to improve the declining natural resources. For this purpose, many forestry

projects were launched. Most of these projects were donor financed while few were

NGO driven and even some were started by the local community themselves. The

Social Forestry Project in Malakand District was started in February, 1987 jointly by

Government of Pakistan and the Government of Netherland. The main objectives of

these plantations were to improve livelihood of the inhabitants by proper utilization of

hilly tracts and other useless land through increasing productivity. A total area of 28,078

hectares was planted with indigenous and fast growing exotic tree species in different

areas of Malakand, Dir and Alpuri. Among the planted exotic species Eucalyptus

camaldulensis, Robinia pseudoacacia, Ailanthus altisimma were predominant while

among the indigenous species Pinus roxburghii and Acacia modesta were dominant.

Some species among the exotics are causing a number of environmental and social

problems like low water table, micro climate change, soil erosion, fauna and flora loss

and dry springs (Hussain, 2002).

Generally exotic fast growing tree species are preferred in forestry plantation,

which contribute considerably to the economic growth of many regions. These

plantations not only produced extensive changes in natural ecosystem but also affect

4

ecosystem services and biodiversity, which can be mitigated by proper management

therefore, perpetuating this key economic sector (Richardson, 1998 and Hartley, 2002).

According to FAO (2010) natural forests of the world are decreasing day by day while

their fragmentation is increasing due to the expansion and replacement of these natural

forests by exotic tree plantation. Nowadays these plantations are most successful due

to high adoptability by farmers of developing countries. Such forest not only provide

shelter and decreasing edge effects but also enhance connectivity among existing forest

fragments and thus provide opportunities for eco tone specialists and potential forest

species to establish that may benefit from any other forest type (Christian et al., 1998;

Norton, 1998; Davis et al., 2001; Georgie et al., 2007; Richard et al., 2007 and Felton

et al., 2010). Despites such and several other beneficial uses, excessive monoculture

of exotic tree plantations are considered as a threat to existing biodiversity due to the

depletion of soil nutrients, pumping up of water resources, suppression of understory

vegetataion by secretion of allelopathic chemicals and ecosystem degradation (Carnus

et al., 2003; Evans, 1992; FAO, 2001; Proença et al., 2010; Pina, 1989; Jagger &

Pender, 2000; Temes et al., 1985 and Basanta et al., 1989). However, some studies

showed their potential for restoration of woody species diversity (Michelsen et al., 1996

and Yirdaw & Luukkanen, 2003).

Some public opinions have also been raised against the cultivation of exotic

species like Eucalyptus camaldulensis in plantation programs claiming that these

species have a damaging impact on the ecosystems. In this context, comparative studies

on the monoculture of exotic tree species versus indigenous tree species needed to be

conducted from ecological and socio-economic point of view for better understanding

required in correct choice and selection of tree species for future plantation programs

for sustainable development.

1.3 PROBLEM STATEMENT

Plantation in public and private land helps in improving the socioeconomic

condition of the rural people by generating income and employment but the

consequence or advantage and disadvantage of the plantation programs with exotic

species is a matter of great concern. Malakand is one of the districts where Forest

Department of Khyber Pakhtunkhwa province, NGOs, farmers and the local

community people raised large scale plantations of Eucalyptus camaldulensis and

Robinia pseudoacacia in their lands farms and cleared forest lands to get more

5

economic return within short time. Eucalyptus camaldulensis and Robinia

pseudoacacia are most commonly grown in Pakistan in various reforestation and

afforestation programs because of their fast growing characteristics and production of

high volumes of biomass within a short time, short rotation and ability to thrive in poor

soils.

With the increase in population of the study area, deforestation on large scale

took place, which reduced the vegetative cover and consequently, the forest is under

severe biotic pressure. To overcome this problem several attempts are made to carry

out plantation in the area. It has been observed that severe effects have been posed by

largescale plantations of exotic species resulting in to a number of environmental and

social problems like low water table, micro climate change, soil erosion, fauna and flora

loss and drying springs (Hussain, 2002). The native communities of plants were

reduced and were replaced by exotic plantations on large scale. It has also observed that

many species become endangered due to these exotics and the ecosystem services were

badly affected by such plants (Shinwari and Qaiser, 2011; Shinwari et al., 2012; Sangha

and Jalota, 2005; Gareca et al., 2007 and Wang et al., 2011). The extensive plantation

of exotics and its monoculture practices has resulted in to degradation of soil and

productivity due to amassing of allelo chemicals in soil (El-Khawas and Shehata, 2005

and Forrester et al., 2006).

Though, some studies on undergrowth species composition in different areas

have been carried out, However, no integrated and comparative study was carried out

on the composition of undergrowth and understory species diversity in exotic and

indigenous tree plantations. In this context, comparative studies on the monoculture of

exotic tree species versus indigenous tree species needed to be conducted from

ecological point of view for better understanding required in correct choice and

selection of tree species for future plantation programs for sustainable development.

Therefore, the present study was conducted to assess the impacts of monoculture of

exotic tree species on the species composition and status of undergrowth in relation to

that of indigenous tree species, soil fertility status, ground water and socio-economic

conditions of local community.

6

1.4 AIM AND OBJECTIVES

The aim and objectives of this research were to:

1) investigate the comparative status of exotic and indigenous tree plots of the study

area in species composition and species diversity of the undergrowth.

2) examine the physico-chemical properties of soil in both exotic and indigenous tree

plots of the study area.

3) find out the impact of exotic species on groundwater.

4) quantify the socio-economic aspects of exotic tree species cultivation in the study

area.

1.5 JUSTIFICATION OF STUDY

The study area harbours the typical sub-tropical Chir pine forest, scrub forest

dominated by Acacia modesta as well as the large scale plantations of exotic tree

species, which provide suitable site for carrying out a comparative study on

undergrowth composition in exotic and indigenous tree plots. The objectives of this

study were to assess the impacts of monoculture of exotic tree species (Eucalyptus

camadulensis and Robinia pseudoacacia) on the species composition and status of

undergrowth in relation to that of indigenous tree species ( Pinus roxburghii and Acacia

modesta) and to provide the baseline data on the undergrowth species of the plantation

forests of exotic and indigenous tree species that might be useful in biodiversity

conservation through appropriate selection of tree species for massive plantation

programs.

Therefore, the present research was initiated to document impact of

monoculture of exotic tree species on species composition and species diversity of the

undergrowth, soil physico-chemical properties, groundwater and quantification of

socio-economic impacts on the local community.

1.6 SOCIO-ECONOMIC BENEFITS

This study explored the extent of socio-economic benefits which are generated

through the plantation of fast growing exotic species. Data from this study would be

useful for the farmers, nursery owners, businessmen, consumers, research and

extension organizations (Forest, Agriculture and Environment Departments) and policy

makers.

7

CHAPTER - 2

REVIEW OF LITERATURE

Fine and Truog (1940) studied the effect of freezing and thawing on the release

of soil fixed potassium. The study suggested that the release of fixed potassium may be

affected due to the freezing and thawing phenomenon.

Fith and Nelson (1956) studied the status of plant nutrients in finding the needs

of lime and fertilizers. The result showed that that when soil levels for phosphorus and

percent organic matter are high, the amount of potential seasonal variation of

phosphorus values tends to increase.

Birch (1958) carried out experiments to indicate the decomposition pattern

occurred in dry and wet periods. Evidence showed that decomposition was dependent

on microbial attack of the solid organic substrate and the pattern of dry and wet

conditions.

Keogh and Maples (1972) reported that the resut of soil test may be different

due to a number of reasons. Six plots were sampled monthy for 38 smonths’ period and

was analysed for P, K, Ca, Mg, pH, OM, SO4‐S, B, and Zn etc. the result showed that

monthly differences could be observed with both fertilized and non‐fertilized soils.

Standard deviations among months were greater with P‐K applications, but the

coefficient of variation was less.

Robertson and Vitousek (1981) measured mineralization and nitrification in soil

from primary on sand dunes and secondary old fields. It was found that Nitrogen

mineralization was comparatively constant in soils from the secondary sere, though the

highest rates were observed in the oldest site. The results of this study do not favour the

hypothesis that nitrification is increasingly inhibited in the course of ecological

succession.

Adams and Sidle (1987) studied landslides for better understanding of

limitations to revegetation and management and found that soil fertility was maximum

in deposit areas and the vegetations and growth of plants ware better than the scour

areas.

8

Akkasaeng et al. (1989) evaluated 14 leguminous trees and shrubs species for

forage and production of fuelwood in Northeast Thailand. Different plants were cut at a

height of 1m, five times during the study period. The result showed that plant species of

Enterolobium cyclocarpum, Cassia siamea, Gmelina arborea and Leucaena

leucocephala produced more than 2 kg of dry matter along with high yield of wood which

were used as fuelwood in the study area. Sesbania sesban leaves was more digestable.

Basanta et al. (1989) studied 10 communities of plants consisting of native oak

land, planted wood land of pine and eucalyptus and shrubland. They found different

species richness, evenness, dominance and diversity in different plant communities

studied due to environmental factors and anthropogenic activities.

Pina (1989) studied censuses of birds for two consecutive breeding seasons in

the plantations of eucalyptus in Portugal. The study revealed that the bird’s density was

very low in the plantations due to the possible factors of growth rate and change in

vegetation structure.

Antinio and Mahall (1991) studied the invasiveness of exotic perennial which

grow rapidly and occupy many indigenous plant species. The result revealed that C.

edulis greatly affected not only the water relationship of H. erecoides and H. ventus

var. sedoides but also their shoot sizes and morphologies by moving downwards the

normal shallow rooted system which resulted in the production of high xylem pressure

potential, as C. edulis uses more water compared to the native shrubs.

Kohli and Singh (1991) focused on the allelopathic impact of volatile oils

derived from the leaves of E. citriodora and Eucalyptus globulus on Avena sativa,

Phaseolus aureus, Hordeum vulgare and Lens esculentum. The result showed that

germination of seeds, plant growth, percentage of cell survival, and water and

chlorophyll of the crop were all inhibited and that the oil vapours of Eucalyptus had

their effect through reducing the respiratory and photosynthetic ability of the target

plants.

Molina et al. (1991) focused on chemical welfare (Allelophathic) effect of

Eucalyptus globulus and found that the allelochemicals released by Eucalyptus

globulus into the soil through the leaching process influenced the structure and

9

composition of understory vegetation of the plantation. Results also suggested that this

effect is due to the decomposition product of decaying litter instead of aerial leachates.

Angers (1992) studied changes in water table aggregation and C content under

continuous silage corn and in the stand of alfalfa which was monitored on monthly basis

on an experimental farm. The result showed that significant relationship was absent

between water content and mean weight diameter under alfalfa which suggested that

aggregates of soil under this treatment were not subject to slakin.

Polglase et al. (1992) found that the concentration of soil available phosphorus

in the topsoil (0–5 cm depth) under Eucalyptus spp. plantation declined from an initial

concentration of 34 to 2.3 µg g−1 after 16 years.

Calder et al. (1993) studied the effects of Eucalyptus plantation on water

resources, erosion and soil nutrients. The results showed that greater soil detachment

occurred through rainfall in exotic Eucalyptus camaldulensis plantations as compared

to indigenous species of Pinus caribaea and Tectona grandis. Growth was affected due

to low availability of nutrients in the dry zone.

Duguma and Tonye (1994) carried out a study to identify 10 plants species with

required properties and their adaptability for agroforestry in the low humid lands of

Cameroon. The result showed that two species of Sesbania were less adapted to the

area while the species of P. falcataria and Calliandra calothyrsus were found best for

agroforestry which improve soil fertility. Moreover, the ability of coppicing of P.

falcataria was below average. Relatively high primary growth and poor coppicing

ability was found for acacia species.

Kamara and Maghembe (1994) carried out a trial of 16 trees and shrubs species

for agroforestry at Chalimbana, Zambia. They observed good survival of all the trees

and shrubs species except Sesbania grandiflora. While Sixteen multipurpose tree and

shrub species (MPTs) for agroforestry were planted in a screening trial at Chalimbana

near Lusaka, Zambia in December 1987. The trial was at 1280 m altitude on a sandy

loam belonging to the luvisol-pharzem soil group, under unimodal rainfall (mean 880

mm). One year after planting all the 16 species except Sesbania grandiflora showed

excellent survival. While Sesbania sesban, Eucalyptus camaldulensis, Eucalyptus

10

grandis, Leucaena leucocephala, Cassia siamea, Flemingia congesta and Acacia

polyacantha grew fast and produce high volume and biomass.

Leinweber and Korschens (1994) studied seasonal variations in soil organic

matter in two different plots i.e. unfertilized plot and in NPK+ farmyard manure plot.

The result showed that carbon concentrations decreased by 0.24% and 0.43% in

unfertilized plot and in NPK+farmyard manure plot respectively which was

significant at p < 0.01 level between the months of June and August and between July

and August the C/N ratios were lowest.

Uemura (1994) categorized leaf phenology of understory plants of forest and leaf

habit were examined in different environmental conditions. Shaded areas were dominated

by perennial-leaved plants, while in less shaded habitats the abundance of annual plants

was greater. The tolerance to shade by the perennial-leaved plants reflected adaptation

to snow tolerance. The biennial- leaved plants were found in euphotic habitats which

competes well during spring because of the rapid sprouting of leaves.

Araujo (1995) carried out measurement of relative biodiversity of Shrub and

bird communities of area planted with Eucalyptus globulus and areas of semi-natural

woodlands and parklands of Quercus suber and Q. rotundifolia in south Portugal.

Result showed that species richness, abundance, taxonomic singularity and endemism

were low in the plantation area and emphasis were given on its conservation according

to their value.

Kirschbaum (1995) studied the relationship between temperature and soil

organic carbon. The study reported that the decomposition rate increased with

temperature at 0°C with a Q10 of almost 8. The data suggested that a 1°C increase in

temperature could ultimately lead to a loss of over 10% of soil organic C in regions of

the world with an annual mean temperature of 5°C, whereas the same temperature

increase would lead to a loss of only 3% of soil organic C for a soil at 30°C.

Thorburn et al. (1995) carried out measurement of ground water uptake at five

different places in a Eucalyptus stand. Analysis revealed that movement of water

upwards depends upon the depth of ground water and salinity as compared to soil

properties. According to the model investigated this uptake of water from the soil would

11

cause salinity over a period of 4 to 30 years until the excess of salts were leached by

flood water.

Rhoades and Binkley (1996) studied soil pH in Eucalyptus saligna (Sm.) and

Albizia falcataria, plantations and found that soil pH decreased from 5.9 to 5.0 in

Eucalyptus plantations whereas pH decreased from 5.9 to 4.6 in Albizia falcataria

plantations. The decrease in soil pH occurred as a result of differences in the degree of

neutralization of the soil exchange complex.

Jan et al. (1996) studied soil nutrients changes in Eucalyptus monocultures of

different ages in comparison to natural Shorea robusta forest Uttar Pradesh. The result

showed that soil nutrients were reduce in 10 and 15 years old monocultures of

Eucalyptus as compared to natural Shorea robusta forest.

Michelsen et al. (1996) studied eighty-three plantations and nearby natural

stands for herbaceous cover of plants and richness of species, biomass, and physical

and chemical properties of soil to assess the impacts of plantations and environmental

factors affecting the growth and distribution of herbaceous plant. The study revealed

that there was no large difference in species richness and diversity between plantations

and natural forest. The study also revealed that the soil in the natural forest was rich in

total N, P and Ca in natural forest as compared to the plantation forest.

Bone et al. (1997) studied floral diversity and composition of understory

vegetation in Eucalyptus camaldulensis plantation in comparison to controlled natural

site and coppice plot. The results of the study showed that species composition in the

plantation and controlled sites were not much different and the diversity index was

found to be high in the coppice plot.

Loumeto and Huttel (1997) worked on the assumption that exotic plantations

reduced native plant biodiversity and affected understory plant diversity. The study

revealed that composition of species in Eucalyptus plantations was largely changed

compared to the surrounding natural vegetation.

McKenzie and Jacquier (1997) predicted the water movement and storage in

soil by developing functional set of morphological descriptors best suited to Ks

prediction. The result showed that prediction at coarse-level of Ks is feasible in routine

12

soil survey and the measurement of Ks directly did not seem to be generally feasible due

to high cost, variation of short range in the field and changing nature of Ks.

Bernhard-Reversat (1998) found that the organic carbon concentration in the 0–

10 cm depth of native Acacia seyal woodland in Keur Maktar, Senegal was twice that

in a corresponding layer of soil under Eucalyptus spp. plantation.

Berendse (1998) reported that at a soil pH of less than 5.5, soil trace nutrients

like Manganese (Mn) and Aluminium (Al) availability increase to levels that become

toxic for most plant growth. Further, soil nutrients such as phosphorus and nitrogen

tend to form insoluble compounds with Al and Fe in acidic soils, become adsorbed and

therefore, made inaccessible for plant uptake.

Kieft et al. (1998) investigated soil nutrients status in the soil samples collected

from areas of grassland undergoing desertification to form shrub-land adjacent

grassland and the sites of creosote bush. In bare soil, plant cover and relative abundance

was calculated by using line transects in each site. The result showed that soils at both

places under plants were greater in total and available nutrients, with more

concentrations under creosotebush as compared to grasses.

Christian et al. (1998) examined small mammals and population of birds present

in Populus plantations and found that plantation forest provides suitable habitat as

provided by the agricultural cropland but were different from the natural forest of the

study area though there were no change in population and structure of bird’s

community.

Doerr et al. (1998) evaluated the in situ severity and spatial variability of

hydrophobicity in Pinus pinaster, Eucalyptus globulus forest and dry burnt summer

conditions of surface soil. The result showed that the litter layer and root zone of E.

globulus act as a source of hydrophobic substances.

Ferreira and Marques (1998) studied species composition, diversity and their

richness of arthropods in the litter of the heterogeneous forest and exotic plantations of

Eucalyptus sp. The study showed that the secondary forest was rich in taxa with 149

morpho species and much diverse (H'=1.80) when compared with the Eucalyptus Sp.

Plantation with 46 species and diversity index of 1.46.

13

Kohli (1998) carried out a study to analyse the vegetation under the monoculture

plantations of exotic (Eucalyptus tereticornis, E. citriodora, Populus deltoids

and Leucaena leucocephala) and indigenous (Albizia lebbeck, Dalbergia

sissoo and Acacia nilotica) tree species. The result showed that exotic plantations

harbour less numbers of plants compared to indigenous plantations. Indices like

diversity, evenness and richness were also comparatively lower under exotic

plantations Furthermore, soil rich in phytotoxic allelochemicals were recorded from

the exotic plantations.

Norton (1998) discussed the aim that plantations protect and integrate

production from the area of plantations despite replacing native species by exotic

species. He concluded that the plantation forest favours indigenous biodiversity by

providing a habitat for the native species, reducing edge effects. He emphasized the

retention of indigenous forest species. Furthermore, arrangements should be made for

various aged compartments and different species types to increase biological diversity

and timber production.

Richardson (1998) reported that increased afforestation of invasive alien trees

and changes in the land use pattern over the last few decades has caused greater

problems of the natural and semi- natural ecosystem. He found that the invasions of

Pine affected large grassland areas and scrub‐brushland by the resulting changes in life‐

form dominance, reduction in structural diversity, increased in biomass, interruption of

usual vegetation dynamics, and changes in the pattern of nutrient cycling.

Islam et al. (1999) evaluated exotic and indigenous species

including Eucalyptus camaldulensis. The study revealed that greater change in growth

and biomass production occurred in each kind of forest species and the species Acacia

auriculiformis adapted well to ecological conditions in the area.

Turnbull (1999) reported that Eucalyptus has been used over 200 years as

fuelwood for wood burning locomotive of the national railway systems and then used

for paper pulp, fibre board, and industrial charcoal. Eucalyptus has been used as a

multipurpose tree which benefits small landholders and a popular exotic in industrial

monocultures. The result revealed that Eucalyptus could be used as a tree of industrial

plantations and as part of farming system in rural areas.

14

Hossain and Pasha (2000) investigated the impacts of more than 300 invasive

alien species including Eucalyptus on the ecosystems. The study revealed that

Eucalyptus camaldulensis grew rapidly and dominated the growth of other native

species and posed a threat to natural ecosystem by invasive plants which has become a

great threat amongst the scientist, conservationist, policy makers, foresters and

ecologist.

Jagger and Pender (2000) studied the large scale plantation of Eucalyptus in

Ethiopia and found that the plantation increased income from the farmland by selling

of poles and other products but despites such benefits the Tigray regional government

imposed a ban on plantation of the species due to concerns of the detrimental

environmental impacts associated with the plantation of such species.

Knops and Tilman (2000) examined the soil carbon and nitrogen dynamics after

abandonment of agricultural fields. The result of resampling of 1900 plots indicated

that soil nitrogen and carbon accumulation over twelve years were dependent upon the

level of carbon and nitrogen in the soil. Furthermore, it was suggested that 75% and

85% loss of soil nitrogen and carbon respectively were due to agricultural practices.

Le Maitre et al. (2000) reported that invasive plants affected areas of

conservation, natural vegetation and agricultural production. The study revealed that

invasive plants invaded 10.1 million ha of South Africa and Lesotho and 3300 million

m3 incremental water were used corresponding to 75% MAR of the Vaal River system.

This larger amount of water used caused a reducion in water in the catchment areas and

their control was difficult with ordinary schemes of water supply.

Cirtin and Syers (2001) studied the effect of liming on the availability of soil P

in six New Zealand soils that varied in P-retention capacity. The result showed that

exchangeable cation has a great influence on the pH-dependence of the phosphate

adsorption-desorption equilibrium. In limed soil, exchangeable Ca and pH increase

instantaneously so that changes in this equilibrium may be small and ditable.

Davis et al. (2001) examined the presence of species of dung beetle in

plantations and primary rainforest. The study reported the presence of twenty-nine

species per transect from plantation while 44.2 species were recorded in primary rain

15

forest area which showed that species richness was lower in plantation than natural

forest.

Foroughbakhch et al. (2001) evaluated 15 indigenous and exotic tree species of

downhill dry shrub land grown in monoculture in four irregular blocks. The result

showed that E. camaldulensis and E. microtheca, along with other native species tend

to have better features as compared to other plants in terms of annual growth, monetary

benefits and management schemes.

Sasikumar et al. (2001) focused on the allelopathic effect of compounds derived

from leaf litter, leaves and bark leachates of Eucalyptus species including E.

camaldulensis, on plant length, growth, vigour index and nitrogenase action of redgram

(CO.5) under the influence of known phenolics along with leachates on germination.

The result showed that germination, vigour index was reduced by catechol, ferulic,

gallic and compound syringic acids.

Tyynela (2001) compared Eucalyptus camaldulensis woodlots and miombo

woodland to evaluate species diversity, species richness and soil properties. The

result showed that miombo woodland was more diverse in terms of plants species

as compared to Eucalyptus plantations.

Bhatti et al. (2002) carried out field and laboratory analysis of some soil

properties under agro-forestry (Eucalyptus + wheat) and agricultural crops (wheat) and

found that 83 % in the surface soil and 94 % in the sub-soil of soil samples in Pakistan

were low (< 1 %) in organic matter under Eucalyptus spp. plantation soils.

Bailey et al. (2005) adds that acidification usually leads to depletion of the soil

base cations (e.g., K+, Mg2+, Ca2+). This depletion arises from replacement of the

basic cations by Al3+ and H+ ions at the exchange site.

Bouillet et al. (2002) studied clonal Eucalyptus plantations for loss of water and

nutrients. The study revealed that root system established rapidly after one year of

plantations and the roots intersection percentage increased with increase in stand age

and soil profile type which showed greater amount of nutrients in the surface layers.

Bergeron et al. (2002) studied fire disturbance particularly frequency of fire,

size and severity in the boreal forest. They suggested that the development of forest

16

management planning strategically and design of silvicultural techniques to sustain a

spectrum of forest compositions and structures at various scales in the landscape is one

possibility to keep this variability.

Hartley (2002) thoroughly reviewed literature from all over the world and

emphasized that monoculture of exotic trees species should be avoided while

polyculture of forest tree should be promoted to increase biodiversity of the area.

Furthermore, he suggested that plantations of native species should be preferred as

compared to exotic species.

White et al. (2002) calculated use of water and water content of soil during year

in a belt of trees consisting of E. camaldulensis and other species of Eucalyptus. The

result showed that plantation belts of trees on contours are an efficient way of

decreasing ground water recharge with negligible tree-crop competition for ground

water.

Carnus et al. (2003) studied the information available on the effects of planted

forest on species and genetic diversity at various spatial scales to find out economic and

ecological effects of management of biodiversity among planted forest and landscapes.

They found that managed plantations produced goods and services by providing timber

and amelioration of climatic conditions.

Jagger and Pender (2003) investigated Eucalyptus grown in woodlots by

inhabitants suffering from biomass and water shortages, land degradation and erosion.

The study showed that Eucalyptus was profitable in terms of production and income

generation but the regional government of Tigray in 1997 imposed a ban on plantation

of eucalyptus on farmlands keeping in view the negative environmental factors

associated with the plantation and less farm area for crop production.

Ramovs and Roberts (2003) analysed and compared different parameters such

as understory vegetations diversity, ecological factors and forest stand structure while

considering four different conditions of management including naturally regenerated

young forests, plantations of conifers and old field plantations. Detrended

correspondence analysis and multi response permutation procedure showed that types

of stand were different in species composition and environments. Plantations were

17

greatly reduced in density of snags, canopy cover, and leaf substrate, and higher in

coniferous canopy cover and needle, twig, and moss substrates than the natural stands.

Webb and Sah (2003) evaluated structure and diversity of natural forest and

managed forest to find out the regeneration pattern of Sal forest developed from two

forest management strategies viz. clearcutting and abandonment, replaced by the

formation and secure regeneration in E. camaldulensis plantations. Findings of the

study revealed that S. robusta abundance decreased in the managed forest after twenty

years in Eucalyptus camaldulensis plantations.

Yirdaw and Luukkanen (2003) studied the regeneration of the understory

woody species diversity of the Eucalyptus plantation in Menagesha where remnants of

natural forest were present. 22 and 20 woody species belonging to 18 and 17 families

were found, and of these species, trees accounted for 68 and 55% at Menagesha and

Chancho, respectively. The study revealed that richness of woody species and their

abundance was 2.4 times and 5.7 times greater than research plots at Chancho where

natural forest was absent.

Figueroa et al. (2004) reported that large numbers of exotics have been

introduced in the Mediterranean region of Chile and the spread of these exotics appear

out of control which has resulted in great disturbance of ecosystem services and

processes like soil composition cycling of soil nutrients, hydrological cycle, soil

hydrology, macro and microclimate and effect and frequency of fire.

Gorgens and Wilgen (2004) reported that large amounts of water were used by

exotic invasive alien plants which was a major factor in the implementation of South

Africa's water programme aimed to save water resources through cutting these plants.

The findings helped in identifying the need of carrying out clearing operations more

effectively in the targeted areas related to water associated benefits.

Stape et al. (2004) carried out an analysis of tropical Eucalyptus plantations and

correlated productivity of the trees with the availability of water. The result showed that

greater amount of wood production depends upon the supply of sufficient amount of

water.

18

Aweto and Moleele (2005) examined the impact of Eucalyptus

camaldulensis plantations in south eastern Botswana. The soil under plantations and

adjoining native Acacia karoo. The study showed that the soil under the two ecosystems

were not significantly different in organic matter, potassium and available phosphorus.

It was suggested that E. camaldulensis immobilizes soil nutrients faster and that

plantation nutrient cycles are less efficient than in the native Acacia woodland. As a

result, soil nutrient decrease will reduce plantation productivity.

EL- Khawas and Shehata (2005) observed the chemical welfare (allelopathic)

properties of leaf leachates of Eucalyptus rostrate and Acacia nilotica on

morphological, biochemical and molecular condition of Zea mays L. (maize) and

Phaseolus vulgaris L. (kidney bean). The study revealed that yield obtained from

maize and kidney-bean were less when treated with Acacia and Eucalyptus leaf

leachates by reducing germination of seeds and seedling growth and that Eucalyptus

leachates had the potential to effect morphological, biochemical and molecular

properties.

Engel et al. (2005) studied the impact of a 40 ha E. camaldulensis stand on

grasslands. The result revealed that ground water table were lowered by more than 0.5

as compared to the adjacent grassland and E. camaldulensis not only used 67% ground

water but also vandose zone of moisture sources reliant on the availability of soil water

Farley et al. (2005) carried out observation of parameters like type of plants,

species to be planted, age of plantation, and mean annual precipitation of 26 catchments

and data sets were evaluated for variation in many ecosystem services and water yield.

The result revealed that afforestation has resulted in increased water shortage in

numerous areas.

Lane et al. (2005) introduced a method to assess the impact of establishment of

plantations on flow duration curve assuming that rainfall and age of vegetation are the

main agents of evapotranspiration. Data were collected from 10 catchments from

Australia, South Africa and New Zealand. The method used in this study proved

satisfactory in removing the changes in rainfall and resulted in gaining useful

information from plantation establishment.

19

Montagnini et al. (2005) highlighted the importance of native plantations in

providing environmental services such as carbon sequestration and restoration of

biodiversity. Using the experience gained 12 years with native species plantations in

Costa Rica, it was recommended to establish incentives for reforestation and

agroforestry systems with indigenous species.

Sanga and Jalota (2005) carried out an assessment of the tangible and intangible

benefits in plantation of exotic E. tereticornis and native species of Dalbergia sissoo

plantations. The study revealed that though exotic Eucalyptus plantations supplied

wood in a short period of time. The ecological benefits such as plant biodiversity, soil

nutrient content and recycling of nutrient through litter were 1.8 times more in

Dalbergia sisso as compared to Eucalyptus plantations.

Van et al. (2005) carried out a study to compare the structure and composition

of native trees species between Eucalyptus, Acacia plantation and an unplanted area.

The result revealed best planting density in Acacia with total 1,660 plants/ hectare,

while 467 trees per ha were found in E. camaldulensis plantations. Tree diversity was

greater in the native forest than the planted areas.

Baber et al. (2006) conducted a study on the effect of Eucalyptus camaldulensis

on soil properties and soil fertility in D.I Khan District in Pakistan. They found that the

organic matter content in the surface soil at 0-15 cm depth ranged from 0.38 to 1.10 %.

By comparing the results with the established criteria for soil fertility, the soil samples

were low in organic matter.

Benyon et al. (2006) carried out measurement of soil water and

evapotranspiration at 21 plantations sites over a period of 2-5 years. The result revealed

that Eucalyptus and P. radiata were capable of utilising a greater amount of ground

water where light- or medium-textured soil existed.

Djego and Sinsin (2006) studied the effect of exotic tree species on the

understory vegetation in an area of exotic tree plantations. The result showed that a

lower number of plant species existed in plantations as compared to the native forest

due to ecological effects of soil acidity, competition, allelopathy, shallows and litter

amount.

20

Forrester et al. (2006) evaluated Eucalyptus mixed plantations with nitrogen

(N2) fixing species and pure Eucalyptus plantation for production without affecting soil

fertility. The result revealed that a mixture of Eucalyptus with other nitrogen fixing

species is more productive (P< 0.001) as compared to pure Eucalyptus plantations.

Fritzsche et al. (2006) carried out comparative soil-plant water relations of two

exotic species of Cupressus lusitanica and Eucalyptus globulus and the indigenous

Podocarpus falcatus in south Ethiopia. The result of the study showed that exotic E.

globulus consumed much of the sub soil water in the dry season which caused depletion

of the ground water in the study area. Lima et al. (2006) found that growth rate and C

fixation potential is high due to which the assimilated C is transported to the soil

through litter fall and rhizo-deposits, and hence increased soil organic content with

time.

Hou (2006) claimed that Eucalyptus plantations growth rate and C fixation is

high due to which the assimilated C is transported to the soil through litter fall and

rhizo-deposits which resulted in increasing soil organic contents with time.

Singh and Singh (2006) carried out a number of experiments in dry tropical

region for the determination of suitability of tree species for plantations, performance

of growth of monoculture of native species and their impact on soil biological fertility

restorations. The study showed that net primary production was due to the amount of

foliage and soil carbon was a function of the amount of litter fall and biomass C was a

function of soil C.

Zabihullah et al. (2006) documented ethnobotanical information on plants

resources of Kot Manzaray Baba Valley, District Malakand. The study showed that 82

plant species of the research area were used for different purposes including 52 for

medicinal purposes, 16 for fuelwood, 11 for fodder, 5 for honey bee, 7 for fruiting, 8

for timber and 6 species as potherb.

Almeida et al. (2007) studied the balance of water, growth pattern of Eucalyptus

pantations considering the catchment hydrology, forest yield and physiological

modelling in Brazil. The result based showed that balance existed between precipitation

and water loss through evapotranspiration. Average precipitation of 1147 mm was

recorded whereas an average evapotranspiration of 1092 mm was recorded annually.

21

Dabek-Szreniawska and Balashov (2007) studied the effect of winter wheat on

seasonal changes in the form of loamy sand Orthic Luvisol cultivated under various

management practices like monoculture, conventional and organic management

practices. The result showed that stronger correlations was observed among the

seasonal changes in the emission of N2O and microbial biomass carbon content,

whereas the organic management practice, compared to the monoculture and

conventional practice due to higher content of microbial biomass N.

Gareca et al. (2007) studied the development of some introduced trees such as

Pinus radiata, and E. globulus in natural vegetation zone where Polylepis subtusalbida

occured. After evaluating various parameters in patches of pure forests of P.

subtusalbida and mixed fragments of P. subtusalbida with other non-native trees, the

results revealed that the seedllings of P. subtusalbida in mixed fragment showed greater

horizontal growth and adventitious roots as compared to pure forest.

Georgie et al. (2007) carried out research in open spaces in plantation forest to

find out that plantations provide opportunities for increasing biodiversity. The result

revealed that greater plant diversity was observed in open spaces rather than the shady

places which provided an opportunity for bryophytes to develop.

Liu et al. (2007) studied the effects of Eucalyptus plantations on soil nutrients

and soil fertility. The results showed that significant differences exist among different

Eucalyptus plantations on soil fertility.

Richard et al. (2007) analysed bird species abundance of 105 study sites in two

selected rural areas of Victoria and south-eastern Australia. Generalised modelling

techniques were used for the assessment of landscape and variables of habitat. The

study revealed that forests mean abundance and birds of woodland was greater in the

plantations of eucalyptus as compared to farmland, and native forest.

Tang et al. (2007) studied the diversity and conservation status of soil in

Eucalyptus plantation in comparison to natural forest. The result showed that low

species diversity and regeneration under the Eucalyptus plantations were found whereas

soil chemical properties were changed and loss of nutrients due to leaching were

reported.

22

Zahid and Nawaz (2007) investigated two species of shisham and Eucalyptus to

determine the difference in physiological responses and water use efficiency (WUE) of

indigenous and exotic tree species, their adaptation in arid conditions and the

environmental concern about the amount of water consumed by Eucalyptus. The result

revealed that Eucalyptus consumed large amounts of water leading to desertification

and lowering ground water table and shortage of aquifer resources.

Ahmed et al. (2008) studied allelopathic effects of leaf litter of E. camaldulensis

on three species Cicer arietinum, Cajanus cajan and Vigna unguiculata. Extensively

used plantations trees Ipil ipil (Leucaena leucocephala) and Sada koroi (Albizia

procera) were selected as bioassay species. The result revealed an increase in the

concentration of leaf litter, the inhibitory effect also increased.

Alhammadi, (2008) studied the effects of exotic E. camaldulensis Dehnh. on

the indigenous tree, Acacia nilotica. The result showed that leaf litter aqueous extract

of Eucalyptus camaldulensis greatly reduced germination percentage, germination ratio

and resulted in high seedling mortality rate.

Baig et al. (2008) highlighted the importance of social forestry by the planting

of trees and other vegetation for the benefits and improvement of the socio economic

condition of local peoples which ensures the economic, environmental and social

benefits to the local inhabitants.

Gupta and Sharma (2008) assessed the variation in the physico-chemical

properties of soil in poplar plantation. The result showed that soil properties were

changed as a result of poplar plantation and soils under plantations were richer in

organic carbon and nutrients.

Lima et al. (2008) reported considerable changes in soil organic matter (SOM)

after replacement of the natural vegetation by short-rotation Eucalyptus spp. plantations

in Brazil.

Sevgi and Tecimen (2008) investigated soil pH, organic matter and total

nitrogen contents of forest floor by collecting 37 sample plots along an altitudinal

gradient which ranged from 1,400 m to 1,710 m. the result showed that nitrogen

contents increased with the elevation and organic matter decreased which showed

23

greater decomposition rate at higher elevation. The study suggested that canopies of

trees provides best decomposition despite of altitude.

Van Wilgen et al. (2008) carried out an aassessment of the present and future

impacts of invasive alien plants on four ecosystem services namely surface water

runoff, groundwater recharge, livestock production and biodiversity. The results

revealed decreased surface water runoff, ground water recharge and impact on

biodiversity in the future.

Alemie (2009) studied soil pH under Eucalyptus spp. plantations in Koga

watershed in Ethiopia and found that soil pH decreased and led to strongly acidic values

ranging between 3.5 to 4.0.

Dogra et al. (2009) carried out a comparative study of the understorey

vegetation in exotic and indigenous tree plantations in Shivalik Hills of India. The result

of the study showed that 104 flowering plants species were found in both exotic and

indigenous tree plantations with greater number in indigenous plantations as compared

to the exotic plantations. The study also showed that alpha diversity under tree

plantations of exotics was decreased compared to indigenous plantations.

Ibrar and Hussain (2009) carried out an ethnobotanical survey of Charkotli

Hills, Batkhela District, Malakand. They documented 100 plants which belong to 49

families. 43 families were dicots, 2 were monocots, 2 were pteridophytes and 1

gymnosperms family. Most of the plants have more than one local use. The study also

emphasized the ecological management and protection of wildlife and plant resources

on sustainable basis.

Liang and Qiang (2009) highlighted the negative effect of Eucalyptus on the

local environment by causing decrease in ground water level, biodiversity, and inducing

degradation of soil. Based on the detailed literature review it was found that indigenous

vegetation in Eucalyptus plantations were lower compared to natural forest and the

plantation of indigenous species. However, negative effects of the introduction of

Eucalyptus could be mitigated by keeping intact the native trees and understory

vegetation with Eucalyptus to support the normal development and regeneration of the

plant community.

24

Ritter and Yost (2009) carried out an analysis of the available data and

observation of herbarium and field of Eucalyptus over the last 150 years of its

introduction to California. The result showed that Eucalyptus has potential ecological

impacts of various species in the locations where they have been introduced.

Semwal et al. (2009) carried out study to determine the physico-chemical

properties of soil. The result showed that minerals were accumulated more in

undisturbed forest as compared to disturbed forest.

Zhang and Fu (2009) studied the effect of Eucalyptus on germination of seeds

and survival of seedling of native species of Delonix regia, Elaeocarpus

sylvestris and Tsoongio dendronodorum in the existence and non-existence of

Eucalyptus leaf litter. The result showed that the germination rate of D. regia was

greatly reduced by all Eucalyptus actions during the early period.

Cao et al. (2010) found that soil pH decreased between 0 to10 cm soil depths of

four areas, which ranged from 4.2 to 4.5, under Eucalyptus spp. plantations in China.

Cavaleri and Sack (2010) carried out an analysis of water use by invasive and

native vegetation of the similar growth form at different scales. The result revealed that

invasive plants used much more water compared to native species.

Felton et al. (2010) conducted a comprehensive study of the variation among

plantations and meadow lands in animals and plant species richness and their

abundance by using meta-analysis techniques. The study revealed the existence of

greater species diversity and abundance in plantations as compared to the pasture land.

Hubbard et al. (2010) carried out measurements of water used by Eucalyptus

grandis x urophylla clones in rain fed and irrigated stands for 1 year. The result revealed

that large amount of water loss occurred due to transpiration and production were

increased due to greater amount of water uptake by the plant.

Leite et al. (2010) carried out study to investigate changes in the edaphic

chararcteristics caused by eucalyptus plantations in Brazil. Result showed that After

several eucalyptus rotations there was a recovery in the SOM content in comparison to

degraded pasture soils, although not to the level of the native forest soil.

25

Proenca et al. (2010) assessed species diversity, richness and evenness of both

plants and animals in areas where natural forest of Quercus spp. and indigenous pinaster

and exotic plantations of Eucalyptus globulus occurred in NW Potugal. The data were

analysed at intra-patch, patch and inter-patch scales. The study revealed that the species

diversity, richness and evenness was greater in Oak forest as compared to the

plantations of Pine and Eucalyptus globulus. A total of 52 plants species were recorded

in Quercus forest while 33 and 28 plants were recorded in Pine and eucalypt plantations

respectively.

Shrestha et al. (2010) studied ecological processes affected by plant diversity

by affecting biomass and properties of soil. Results showed that greatest utility index

of plants was observed in orchards i.e. 61 whereas the lowest species utility index (9)

were observed in Eucalyptus plantations.

Zahid et al. (2010) studied extraction of water by Eucalyptus camaldulensis in

contrast to native species of Acacia nilotica, Albizia procera and Azadirachta indica

developed on cultivated lands to find out the significance of Eucalyptus in water

conservation and ground water resources. The result revealed that one-year-old

Eucalyptus consumed 149.27 litres of water, which was double that of compared to

Albizia and three times more than that of Acacia and Azadirachta. Due to greater water

use by Eucalyptus aquifer resources were reduced.

Zegeye (2010) investigated the impact of exotic Eucalyptus on soil properties,

fauna and flora of the area. The result revealed that soil water and nutrients were

decreased due to intense competition for resources with native flora, allelopathic

chemicals production suppressed the growth of other plants and insufficient food and

habitat for wildlife.

Zhang et al. (2010) focused on the allelopathic effect of Eucalyptus on growth

characteristics and germination of plant species of Lolium perenne, Raphanus sativus

and Phaseolus aureus raised in Eucalypt plantations. The findings showed that liquid

extract derived from the roots of E. grandis reduced germination and early plant growth

of designated plants.

Zhang and Fu (2010) focused on the allelopathic effect of three Eucalyptus

species on radish (Raphanus raphanistrum), cucumber (Cucumis sativus L.), and

26

Chinese cabbage (Brassica napa) through leaf litter and live roots. The result revealed

that leaf litter extracts caused more inhibitory action than live roots and the removal of

this leaf litter was helpful in reducing inhibitory actions.

Barkatullah and Ibrar (2011) carried out an ethnobotanical study in the Pass hills

of Malakand to document information on vegetation and indigenous knowledge about

plant use. A total of 169 plants species belonging to 140 genera and 76 families were

reported. Among the 63 dicot families, 5 were monocots, 4 were pteridophytes and only

one family was gymnosperm. The study also emphasized the ecological management

and protection of wildlife and plant resources on a sustainable basis.

Castro-Diez et al. (2011) reported that soil biological activity tends to be higher

in basic soil than acid soil. It was found that the decomposition rate of litter in exotic

trees were less than litter of native species due to the existence of secondary metabolites

in exotic trees.

Fikreyesus et al. (2011) worked on the allelopathic effect of Eucalyptus

camaldulensis on tomato crop under field and laboratory conditions. The findings

showed that aqueous extracts decreased germination, root and shoot elongation of

tomato plant and it was proposed that eucalyptus appears to be a possible threat to the

vegetable production under limited farming condition.

Shinwari and Qaisar (2011) reported that plant biodiversity reduced as exotic

invasive species invade the area. They grow there and sustained their presence and

resulted in degradation of ecosystems. The study suggested that efficient utilization of

natural resources will lead to the elimination of food insecurity, malnutrition and poor

health conditions of the tribal people and will help to restore, document and diffuse

indigenous botanical knowledge.

Soumare et al. (2012) studied the effect of litter accumulation of Eucalyptus on

growth and development along with groundnut root infection by arbuscular mycorrhizal

fungi and rhizobia. The results showed that high polyphenol content occurred due to

litter of Eucalyptus and lower pH reduced root nodulation and mycorrhiza colonization.

Growth of groundnut, flowers number per plant, pods production and leaf nitrogen and

carbon contents were greatly reduced in soil containing Eucalyptus litter.

27

Suarez et al. (2011) studied dry season hydrology in catchment having shallow

water table where land use was changed from fodder maize and pasture to Eucalyptus

globulus plantation. The study showed that the water table became lowered every year

and the associated discharge reduction resulted in the drying up of streams.

Wang et al. (2011) studied the impact of planting Eucalyptus trees on diversity,

species composition and functional type of understory vegetation. The result revealed

that plantation of Eucalyptus has resulted in a reduction of plant diversity of the area

and the diversity of the understory plant did not match with the elevation gradient.

Eucalyptus plantations showed simpler plant community structure than that of either

secondary evergreen forests or abandoned farmlands.

Alem and Pavlis (2012) carried out an assessment of the impact of E.

camaldulensis plantation raised in semi- arid areas on native diversity of woody plants.

The result showed that species diversity and density were low in plantation areas

whereas it was high in woodland forest.

Calvino et al. (2012) carried out a study to compare the diversity and

composition pattern of undergrowth in poor-management Eucalyptus plantations

including young, intermediate and mature stages with shrub lands and native forests.

The result showed that diversity of plants throughout the study area was poor in

plantations of Eucalyptus in middle age because of high species turnover in young and

mature Eucalyptus plantations.

Demessie et al. (2012) studied plantations of Eucalyptus globulus, Eucalyptus

camaldulensis, Eucalyptus saligna, and coniferous plantations species in comparison

to adjacent broad-leaved natural forest. It was found that the production of litter in

broad-leaved plantations species and natural forest was greater than coniferous species.

Hennessy (2012) reported that the existence of Eucalyptus globules has a

negative affect on the East Bay’s native environment resulting in an increasing fire

threat. The study revealed that Eucalyptus trees played vital role in the 1991 Oakland-

Berkeley fire.

Shinwari et al. (2012) discussed various factors which causes biodiversity loss

like global warming, climatic change, unwise use of existing natural resources, human

28

population and demand for food and medicine. The study showed that biodiversity loss

has resulted in raising infectious diseases which greatly affected economic and

nutritional needs of human.

Zhang et al. (2012) found that young Eucalyptus spp. stands provided less

organic matter to the soil due to the lower addition of plant residues to the soil whereas

organic matter concentration increased with the increase in plantations age.

Bughio et al. (2013) focused on the allelopathic effects of exotic Eucalyptus

camaldulensis on indigenous trees of Acacia nilotica. The result revealed that

Eucalyptus leaf litter caused high mortality rate, decreased seedling vigour index,

relative lenght of roots and shoots. It also caused reduction in the fresh and dry weight

of the plant.

Chen et al. (2013) reported that during deforestation of native vegetation and

establishment of Eucalyptus spp. plantation, soil macro-aggregates are disrupted and

exposed to microbial breakdown, with the consequence of organic matter being lost

from soil.

Zaman et al. (2013) reported 25 medicinal plants species which belonged to 18

families from tehsil Dargai, district Malakand. Out of 25 medicinal plants species 10

species were herbs, 5 species of shrubs and 10 species of trees which were used for the

treatment of various diseases.

Ashraf et al. (2014) carried ou physico-chemical analysis of grassland soil at

four micro sites. Soil characteristics like texture, organic matter, organic carbon,

temperature and calcium contents potassium, magnesium, total phosphorus and sodium

were examined. The result showed that the moisture contents was directly related to the

herbaceous vegetation cover and the amount of organic matter was fairly good while

the important cations like Ca 2+ and Mg 2+ decreased from May to December except

at Site 4 due to good cover of vegetation and good amount of organic matter.

Cortez et al. (2014) studied soil microbial properties like soil microbial C, N,

respiration, carbon use efficiency, and microbial C-to-N ratio

between Eucalyptus plantations of differing ages (1 to 4 years) and native forest in

Northeast Brazil. The result for soil total organic carbon (TOC) indicated that organic

29

C decreased in the first year of the conversion of native forest to Eucalyptus spp.

plantations in Brazil.

Tererai et al. (2014) carried out a study to assess the effect of invasiveness of

Eucalyptus camaldulensis on physio-chemical properties of riparian soils in South

Africa. Soil moisture, temperature, litter depth and thickness, primary textural

components, concentrations of soil macro (C, N, P and K) and micro (Mn, Zn, Cu and

Fe) nutrients, and pH. Available N (NO3−‐N and NH4

+‐N) and P, as well as

exchangeable Ca and Mg were also analysed. The result showed that soil pH and soil

moisture decreased in invaded sites compared to uninvaded sites. Soil macro and micro

nutrients did not vary significantly.

Ali et al. (2016) carried out a study to assess the floristic composition and

ecological characteristics of vegetation of Chail valley of District Swat. 463 species

belonging to 104 families were documented. Among the reported families Asteraceae

with 42 Species was leading followed by Poaceae with 35 Species, Rosaceae and

Lamiaceae both with 26 Species, Papilionaceae with 25 Species, Brassicaceae and

Boraginaceae both with 16 Species), Apiaceae with 14 Species, Solanaceae with 13

Species and Ranunculaceae with 12 plant species. While the remaining families were

having less than 12 plant species. Therophytes being the dominant with 188 plants

species, followed by hemicryptophytes with 77 species.

Muhammad et al. (2016) carried out a survey of ethno-botanically important

plant species in Understory Vegetation in Acacia modesta (Wall) Forests of Malakand.

Results showed that 32 species were used for seven ailments, Dodonea viscosa and

Vitex negundo with High species fidelity of 100%. Species like Dodonea viscosa,

Mallotus philippensis, Vitex negundo and Zizypus nummularia were used more in the

research area which needs conservation.

Muhammad et al. (2016) studied ecological factors which influenced diversity,

density and distribution of vegetations on different soil and topography of Acacia

modesta dominating forests in Malakand Division. A total of 3836 individuals (plants),

consisting of 32 species and belonging to 20 angiosperms families were recorded. Data

analysis of understory vegetation showed that Asteraceae, Poaceae and Sapindaceae

were the dominant families in terms of taxonomic diversity and Family Importance

30

Value (FIV) index, respectively. The dominant species was Dodonea viscosa in terms

of density and percent cover.

Shah et al. (2016) carried out a study to find out the comparative effects of forest

trees species role in improvement and enhancement of soil profile with identified

Vespid fauna in the District Buner. Soil physico-chemical properties were studied and

it was observed that vespid prepared their nest in these trees with the reference to soil

composition.

Ali and Rab (2017) studied the effect of stress of salinity and drought on sodium,

potassium and proline content of Solanum lycopersicum. The plants were exposed to

five different salinity levels. The result showed that across salinity level increase in

sodium and proline contents and decreased in K+ contents which resulted in greater

ratio of Na+ /K+ in root and shoot tissue. The ratio of the Na+ and K+ content, Na+

/K+ ratio decreased as a result of drought stress and increase in the proline content in

both the root and shoot tissue. The interaction of salinity and drought significantly

affected the sodium (Na+) and potassium (K+ ) contents, Na+ /K+ and proline content

of the shoot but K+ content and proline accumulation were not significant.

Khan et al. (2017) carried out a study to document the ethno-medicianal

information of Swat valley. The study emphasized in understanding the relationship

between human-plants and to regulate the practise and selections of ethnobotanical

herbs in the district.

31

CHAPTER - 3

MATERIALS AND METHODS

3.1 SELECTION OF RESEARCH PLOTS

The strategies for selection of research plots comprised (i) data of Khyber

Pakhtunkhwa Forest Department on the exotic tree plantation in District Malakand (ii)

field reconnaissance survey (iii) record of previous studies in the research area (iv) data

on the availability of massive plantations of exotic species (Eucalyptus camaldulensis

L. and Robinia pseudoacacia) (v) consideration of the existence of homogeneous

factors etc. and (vi) relevance to the objectives of this study. Based on the diverse

ecological habitats, topography, species composition and vegetation cover of the forest

areas of Malakand, a total of 12 research plots were selected for this study for data

collection throughout the study period (Figure 3.2).

Fig. 3.2 Map of the research plots located at District Malakand

32

The 12 research plots were located in public and private land composed of 3

Pinus roxburghii plots, 3 Acacia modesta plots, 3 Eucalyptus camaldulensis plots and

3 Robinia pseudoacacia plots. Each research plot size (50 m x 50 m = 0.25 ha) was

considered in connection to research objectives (Figure-3.2). The exotic species

Eucalyptus camaldulensis occupied the major percentage of plantation at the research

area, but the plantations of Robinia pseudoacacia and Acacia modesta were relatively

less in that area. Furthermore, the research area is dominated by indigenous species of

Pinus roxburghii and Acacia modesta which was considered here as true plots for

comparison with the exotic plots for research objectives.

For the convenience of comparison in woodlot-based socio-economic aspects,

a total of 30 private woodlots, including 25 Eucalyptus camaldulenis, and 5 Robinia

pseudoacacia plots were also selected from the adjacent areas and only the average

(mean) data on both types of woodlots were considered in data analyses. Plot area and

related data were converted into one hectare for standard comparison and analysis of

the research.

3.2 DATA COLLECTION

This research consisted of four major parts viz. (i) plant and soil sample

collection (ii) field data recorded on various aspects (iii) questionnaire surveys and (iv)

plant sample study and soil sample analysis in the laboratory.

The research area has a dry subtropical climate characterized by seasonal

variations in rainfall. Three seasons were generally recognized: spring, from April to

May; a rainy monsoon season from July to September; and a cool, dry winter from

Decmber to March. These 3 seasons were considered for sampling and recording data

from the selected sites. The representative data was collected over a period of two years

ranging from April 2017 to March 2019. The plant and soil samples of the selected sites

were collected and recorded 3 times per year i.e., once each in April, August, and

December months covering spring, monsoon and winter seasons respectively. In this

research all the data collected in the plots (50 m x 50 m = 0.25 ha) were converted to

one hectare in order to have better comparison and understanding.

33

3.3 ASSESSMENT OF ECOLOGICAL IMPACTS

This section describes the methodologies of undergrowth vegetation survey, tree

productivity and physico-chemical properties of soil in the study area.

A) Study on Undergrowth Vegetation

Undergrowth Vegetation Survey

A transect method was applied to conduct the survey in the selected plots of the

study area to detect the ecological status of the undergrowth there. In this method, the

transect line was laid out across the area to be surveyed and necessary number of

quadrats were placed in a systematic way. The plant species found inside each of the

quadrats were then recorded with particular collection number and preliminarily

identified, individuals of each species were counted.

Determination of Quadrat Size

To determine the standard size of the quadrate, the ‘Species Area Curve’ (Cain,

1938; Braun-Blanquet, 1964) was prepared first. Based on the data from SAC, the 5m

x 5m size was found to be the convenient quadrate size for collecting the undergrowth

data.

Quadrat Sampling and Recording

Field data for the assessment of undergrowth species diversity were collected

following the modified quadrat method i.e. (Hussain, 1989; Braun-Blanquet, 1932;

Raunkiaer, 1934). In each research plot, 10 quadrats were placed systematically

following transect line. Necessary field data from each quadrat including the

taxonomically important all field characters of each plant specimen with particular

collection or serial number and date were carefully recorded. The number and

frequency of all undergrowth plant species found in each quadrat were recorded

manually using their collection number and scientific or local name in case of known

plants. Quadrat data from all research plots were collected during spring, monsoon and

winter seasons. Thus for undergrowth vegetation survey, the data were collected from

a total of 360 quadrats (12 plots x 10 quadrats x 3 season) placed in these research plots

in 3 seasons over one year.

34

Specimen Collection and Preservation

The representative plant specimens belonging to each species were collected

only from the healthy twigs with bud, flowers and/or fruits in each sampling site. In

case of tree species, collection of smallest flowering branch with fruits and in the case

of small herbaceous species, collection of whole individual plant or tuft of plants with

flowers and fruits were preferred. A particular collection or serial number was given

for each specimen and all relevant field information, viz., date of collection, locality,

local name/s, habit, habitat, height of the stem, color and scent of the flower and fruits

were recorded in the field notebook. Data on the range of local distribution were also

recorded in the note book during the field visits. Flowering and fruiting time were

determined on the basis of field observation during the field trips conducted in different

months and verified with the data available in authentic taxonomic literatures.

Using the standard herbarium techniques (Hyland, 1972; Jain & Rao, 1977), the

freshly collected specimens were properly processed, pressed and managed in the field

station, and dried and preserved at Centre of Plant Biodiversity and Botanical Garden

Herbarium (UPBG) University of Peshawar. The dried specimens were mounted on

Herbarium sheet (42 cm × 28 cm) by using inorganic glue. An herbarium label with

available field information was permanently attached to the sheet of each specimen.

The voucher specimen/s of each taxon was selected considering the best representation

of the vegetative and reproductive characters.

Specimen Examination

Preferably both fresh and the herbarium specimens of each taxon were

examined at the Centre of Plant Biodiversity and Botanical Garden Herbarium (UPBG)

University of Peshawar, using hand lenses and stereo binocular microscopes. Besides

the author’s own collections, the herbarium specimens previously collected from

District Malakand by different collectors and deposited at CPB and Department of

Botany, UOP were also carefully examined. The important taxonomic characters of

representative plant specimens belonging to each taxon were recognized through

matching them with those of closely related taxa and consulting the key characters used

in modern floras e.g. Nasir and Ali (1970-1989); Ali and Nasir (1989-1991) and Ali

and Qaiser (1993-2019).

35

Specimen Identification and Nomenclatural Information

Identification of all plant specimens collected from research area were

confirmed through (1) consultation with the experienced plant taxonomists of Centre

of Plant Biodiversity and Conservation University of Peshawar and (2) matching the

specimens with (i) authentically identified herbarium specimens housed at Herbarium

of the Department of Botany University of Peshawar, (ii) clear type images available

on the websites of different international herbaria, and (iii) taxonomic descriptions and

keys available in standard taxonomic literatures (Hooker, 1872-1897; Prain, 1903 and

Nasir and Ali (1970-1989); Ali and Nasir (1989-1991) and Ali and Qaiser (1993-2019);

Watson et al., 2011; Flora of North America Editorial Committee, 2004) the authentic

interactive keys available in the websites of different scientific institutions. For the

confirmation of the family of unknown plant specimens, the taxonomic keys to the

families of angiosperms or the available interactive keys were followed first and there

after the key to the genera of the relevant family and key to the species of the related

genus were followed, respectively to know the genus and species of the plant

specimens. Thus the identification of each specimen was comprised of its species name,

genus name and family name.

Supplementary Data Collection

The supplementary data included in this dissertation were collected from

relevant publications available at the library of Centre of Plant Biodiversity,

Department of Botany, University of Peshawar, Pakistan Forest Institute (PFI), Khyber

Pakhtunkhwa Forest Department, Forest Management Centre of Khyber Pakhtunkhwa

Forest Department, Agriculture Research Institute at Tarnab Farm Peshawar, The

University of Agriculture, Peshawar and websites of relevant institutions/organisations.

The taxonomic characteristics of the species were compared with that of the recent

floras e.g. Flora of Pakistan.

Data Analysis

Density

Density gives an idea of degree of competition (Shukla and Chandal, 1980 and

Mueller Dombois and Ellenberg, 1974). It is described as the number of individuals per

unit area. In other words, the average number of individuals per unit area is known as

36

density. In this research undergrowth density per quadrat (25 m²) has been multiplied

by 400 to get density per hectare in order to have better understanding and comparison.

It is the numerical strength of a species in relation to a definite unit space. The following

formula was used for calculation of the density of the species:

Density (D) =Total no. of individuals of a species

Total no. of quadrats studied

Relative Density

Number of individuals of one species as a percentage of the total number of

individuals of all species is termed as relative density. The proportion of density of a

species to that of a stand as a whole is also referred to as relative density (Shukla &

Chandal, 1980; Mueller-Dombois & Ellenberg, 1974). The following formula was used

for calculation of the relative density of the species:

Relative Density (RD%) =Total no. of individuals of a species X 100

Total no. of individual of all species

Frequency

Frequency means dividing the number of plots in which a given species is found

by the total number of plots sampled. This is described as the percentage (%) of quadrats

occupied by a given species. The following formula was used for calculation of the

frequency of the species:

Frequency (F) =No. of quadrat in which it occured X 100

Total no. of quadrat studied

Relative Frequency

The dispersion of species in relation to that of all species is termed as relative

frequency for a species. Relative frequency denotes the number of occurrences of one

species as a percentage of the total number of occurrences of all species (Shukla &

Chandal, 1980; Mueller-Dombois & Ellenberg, 1974). The following formula was used

for calculation of the relative frequency of the species:

Relative Frequency (RF%) =Frequency of the species in stand X 100

Sum of frequencies of all species in stand

37

Abundance

The estimated number of individuals of a species per unit area is referred to as

abundance. It is the number of individuals per quadrat of occurrence. The abundance is

usually expressed by assigning the species to one of the classes viz., rare, occasional,

frequent, abundant and very abundant (Shukla & Chandal, 1980 and Mueller-Dombois

& Ellensburg, 1974). It was determined using the following formula:

Abundance (A) =Total no. of individuals

No of quadrats in which species occured

Relative Abundance

Relative abundance is the abundance of each species divided by the total

abundance of all quadrat species combined and multiply by 100 (Shukla & Chandal,

1980 and Mueller Dombois & Ellenberg, 1974). It was calculated using the following

formula.

Relative Abundance (RA%) = Abundance of each species X 100

Total abundance of all quadrat

Study on Tree Productivity

Calculation of no. of trees, height and diameter of trees

The number of trees per plot of each species was manually counted in the

research plots. Tree density was found by counting the number of tree stem (>5 cm dbh)

in a plot each sized (50 m x 50 m = 0.25 hec) and the no. of trees per hectare were

calculated. Trees heights were measured with Haga altimeter and average height of

trees on each research plots of different species were calculated. Tree diameter at breast

height (DBH) above 5 cm was considered as tree and DBH below 5 cm was considered

as sapling/seedlings. DBH of each tree stem was measured by DBH measuring tape.

Calculation of Gross Tree Stem Volume and Basal area

The gross tree volumes were calculated from the measurement of total height of

trees and diameter which was expressed in m³/ha. The formula used for the calculation

was

Gross Tree Stem Volume = (dbh)² / 4 * π * Htot * π * fgross

38

Where, dbh = diameter at breast height, Htot = Tree Total Height, π = 3.1416 and fgross

= 0.5

Basal area in m²/ha was calculated with the help of the following formula of Hedl, 2009.

Basal Area = π (dbh/2) ²/10000, where dbh was in cm and BA was calculated in m².

Shannon-Wiener Diversity Index

The Shannon-Weiner Diversity Index (Shannon & Wiener, 1963) is one of

several diversity indices used to measure the species diversity. It takes into account the

number of species and evenness of the species. This index was calculated from the

following formula given by Magurran (1988):

Shannon-Wiener Diversity Index (H) = -Σ (n/N) In (n/N) = - -Σ pi In pi

Where, Pi = n/N = The proportion of individuals or the abundance of the ith species

expressed as a proportion of total cover.

n= number of individuals of a particular species.

N= total number of individuals of all species.

In = log base, in other words, pi is the proportion of the ith species and the number of

all individuals of all species (ni/N).

The standard range of Shannon-Weiner Diversity Index is 1-4. The highest

value of Shannon-Wiener Diversity Index value indicates highly diversified area and

lowest value indicates low diversified vegetation.

B) Study on Soil Physico-Chemical Properties

Soil sampling and testing provides an estimate of the capacity of the soil to

supply adequate nutrients to meet the needs of growing trees. As one of the key

objectives of this research were to estimate the soil physico-chemical properties and

comparative status of soil nutrients of selected exotic and indigenous tree plots in

different seasons.

Soil Sample Collection

Soil samples were collected from 12 research plots (with 3 replications for each

plot) of exotic (Eucalyptus camaldulensis and Robinia pseudoacacia) and indigenous

plots of (Acacia modesta and Pinus roxburghii) of the study area to know the physico-

39

chemical properties. Soil samples from surface level to 30 cm depth were collected

through soil augur (considering 3 replications for each plot). Three composite (mixture)

soil samples, each of which was prepared by mixing two original soil samples, were

collected from each study plot. The collected soil samples were then dried in shade and

passed through a 2 mm sieve. The sieved soil samples of about 500 gm were then taken

into sample polybags, tagged and preserved for conducting physico-chemical analysis.

This procedure was followed in collection of soil samples from all research plots. Thus

a total of 108 soil samples (12 plots x 3 composite samples x 3 season) were collected

from these research plots in three seasons over a period of one years.

Soil Data Analysis

The collected soil samples were analyzed to determine some major physical and

chemical properties of soils to assess the present soil nutrient status. The soil analysis

was done to know the status of pH, OC, OM, N, P and K in the soil samples. The

laboratory analyses of all soil samples were conducted in Agriculture Research Institute

Tarnab, Peshawar, Pakistan. Standard scientific methods were followed for soil

physico-chemical properties analysis. For accurate results three replicates were

analyzed and their values were used in the results.

Soil pH (1:5)

10 g soil was taken and 50 ml water were added to it. The suspension was then

shaken in a shaker machine for 15 min and soil pH was measured using a pH meter

Model no. MT-103 (McLean, 1982).

Soil Organic Matter Content

One-gram soil was treated with 10 ml of potassium dichromate (1N K2Cr2O7)

and 20 ml concentrated sulfuric acid (H2SO4). Distilled water was added until the

volume reached 250 mL and then left for 30 min until the solution had cooled down.

Two to three drops of indicator (ortho-penonthralien) were added to the solution and

were then titrated against 25 ml ferrous sulfate (0.5N Fe2SO4) solution until the dark

brown color appeared (Nelson & Sommers, 1996). Readings were noted and were

converted to percent organic matter by the following formula.

40

% Soil O.M = ((𝑚𝑙 𝑜𝑓1𝑁 𝐾2𝐶𝑟2𝑂7) −(𝑚𝑙 𝑜𝑓 𝐹𝑒𝑆𝑂4 𝑋 𝑁)) 𝑋 0.69

𝑤𝑒𝑖𝑔ℎ𝑡 𝑜𝑓 𝑠𝑜𝑖𝑙

Organic Carbon

Soil organic carbon was determined by Walkley and Black’s (1934) wet

oxidation method using 1 gm dry soil outlined by Jackson et al. (1973).

Soil Electric Conductivity (1:5)

10 g dry soil was taken and 50 ml water were added to it. The suspension was

then shacked in shaker machine for 15min and soil EC was measured using an EC meter

company Radiometer Copenhagen and model CDM210.

Soil Total Nitrogen

Soil total nitrogen was determined by the kjeldhal method of Bremner &

Mulvany (1996). 0.2-0.5 g soil sample was taken in a semi-micro Kjedhal flask and

digestion mixture containing 790 g of K2SO4, 100 g of CuSO4 and 100 g of ferrous

sulphate was added to the soil. 5-7 ml of sulfuric acid (H2SO4) was then added to the

tubes and kept for thirty minutes in digestion chamber for digestion. After digestion,

the solution was made up to 100 ml. with distilled water. 20 ml of extract were then

taken in Wolf’s bottle and 5 ml of sodium hydroxide was added to the extract (40% -

v/v NaOH). The solution was then distilled in 5 mL boric acid mixed indicator solution.

The distillate was then titrated with 0.005 N hydrochloric acid solution (HCl). Reading

were noted and converted into percent total N by the following formula.

(%)N = (sample − blank) x 0.005N of HCL x meq N x 100

Wt of sample x volume distilled x 100

Soil P and K by ABDTPA extractible method

Phosphorous and potassium were analysed by the procedure proposed by

Soltanpour & Schawab (1997). In this process 10 g dry soil was taken and 20 mL of

ammonium bicarbonate diethylene triamine pentacetic acid (AB-DTPA) were added to

the flask. The solution was then placed in shacked in shaker machine for 15 min. After

shaking the solution was then filtered with Whatman No. 42 filter paper and phosphorus

41

was analysed through spectrophotometer (520 nm) and potassium through flame

photometer.

Calcium Carbonate (CaCO3)

CaCO3 was analyzed by acid neutralization method of Black (1965).

DATA ANALYSIS

Soil data were statistically analysed using statistics 8.1 software two-way

ANOVA (LSD) was used to test for significant differences (P<0.05) for marginal

means of variables. Besides, Microsoft Excel spreadsheets were used for the

arrangement of data and their graphical representations.

3.4 SOCIO-ECONOMIC IMPACTS OF MONOCULTURE OF EXOTIC

TREE SPECIES

Necessary field visits were completed to collect the socio-economic data

through field observation and questionnaire surveys. Detailed information on socio-

economic condition in the study area in respect to monoculture woodlot of exotic trees

in public and private forests was collected. Observations on the following aspects

helped to cross check the collected information and data: (i) indigenous forest

management practices, (ii) wildlife and biodiversity, (iii) woodlot and Farm-forestry

plantations, (iv) local people attitude, (v) agricultural activities, (vi) land use pattern,

(viii) socio-economic activities, and (ix) others related activities.

At first, the necessary informal discussions with the local people on their

socioeconomic activities were conducted. These informal discussions helped to

generate successive questions for interview or further discussions. Accordingly, a

comprehensive semi-structured questionnaire modified after Rahman (2003) was

prepared. Finally, a detailed questionnaire survey and focus group discussion (FGD)

was carried out on the woodlot tree growers of the study areas in 2017-19 and the

necessary information was collected on different aspects of plantation. The number of

interviews as well as relevant data collection varied on the availability of the potential

interviewees, GO and NGOs organisational support and other circumstances.

42

Selection and Investigation of Woodlots and Tree Growers

Woodlots of exotic species Eucalyptus camaldulensis and Robinia

pseudoacacia raised on private land were selected from the study areas through

stratified random sampling and interviews were conducted accordingly. The

appropriate woodlots and respective households who were growing exotic trees or

practicing monoculture of exotic tree species in their own land with at least 0.25 ha (50

m x 50 m) land were searched through reconnaissance field visit and with the help of

local guides, local staffs of KPF&ED and local government authorities. Finally, a total

of 30 exotic woodlot tree growers at private level were selected from different areas of

District Malakand for data collection through a semi-structured questionnaire survey.

The questionnaire was composed of general information and woodlot/block

plantation (Appendix-19). The questionnaire surveys were conducted by a working

team led by the author and the data collected through face to face interviews. The goal

of each interview was to determine participants’ demographic and socio-economic

status as well as the expenditure or maintenance costs of and financial gains or profit

from the tree plantation plots. The tree growers who were cultivated the fast growing

exotic tree species as monoculture in their own land for quick economic return through

timber production were showed as per expenditure and income. The sample unit was

the household of the selected farmer who was involved as the respondent. Information

and data on growth performance of the woodlot trees were collected from the fields and

analysed accordingly. The current and future valuation of woodlots were determined in

consultation with local experts, forester, timber traders and tree growers.

Benefit Cost Analysis on the Woodlots Plantations of Exotic Tree Species

This study has assessed the costs and benefits of woodlot plantations. It focuses

on developing plantation system, followed by estimating the expenditure/costs and

benefits/revenue for the species planted. The costs projected here are based on ±10 year

(with different cycle of harvest depending on the species) rotation for one hectare’s

plantation of woodlot. Based on the costs and benefits estimated, the feasibility for the

woodlot plantation was examined. This feasibility analysis employed three main

economic tools, i.e. the net present value (NPV), benefit cost ratio (BCR) and internal

rate of return (IRR). A spreadsheet model (MS Excel 2016) was used to develop and

calculate the NPV, IRR and BCR.

43

Net Present Value

The term net present value is usually computed by finding the difference

between the present worth of the benefit stream minus the present worth of the cost

stream. The formula use for calculating the net present value is as below (Gittenger,

1974);

Net present value = Ʃ (Bt – Ct)/ (1 + i) t

Where, t = year, B = benefits, C = cost and i = discount rate.

Benefit Cost Ratio

Net present value tells us how much the expected present profit could be earned

from the investment but it does not reveal the proportion of total benefits against the

total costs invested. To do this, benefit cost ratio analysis is the right financial tool to

be employed. The following formula was used for calculating benefit costs ratio

(Gittenger, 1974):

Benefit costs ratio = Ʃ {Bt / (1 + i) t}/ Ʃ {Ct/(1 + i) t}


Internal Rate of Return

Apart from the net present value and benefit cost ratio analysis, internal rate of

return is another financial tool to determine the integrated planting. Internal rate of

return is measured when the discounted total benefits minus discounted total cost is

equal to zero. The investment should only be carried out if the internal rate of return is

more than capital cost interest rate (i.e. bank loan interest rate). The mathematical

formula for the above financial tools can be summarized as follow (Gittenger, 1974);

Internal rate of return = Ʃ {(Bt – Ct)/ (1 + i) t} = 0


Focus Group Discussion

In addition to the individual interviews and direct observation, FGD (a useful

Participatory Rural Appraisal-PRA technique) was also conducted to promote closer

interaction with the interviewees for obtaining more realistic responses. FGD were

separately held with the beneficiaries, tree growers, local people, timber traders and

44

related stakeholders. Gathering of focus groups consisting of local stakeholders living

within and nearby forests were organized by the working team led by the researcher.

The interviews were conducted at different places, preferably at local market (Bazar),

road sides, Hujras and other local community places where local people gathered

spontaneously.

The objectives of FGD were to-

(i) to collect specific information through consultation with local people, forest

villagers, businessman and resource user groups etc. (ii) to find out the socio-economic

impacts of exotic tree plantation in public and private land on rural livelihoods,

business, land use pattern and existing ecosystems.

During FGD, site specific information through consultation with local people,

forest villagers, tree growers, timber traders, different professional groups, resource

user groups (fuel wood collectors, sawmill owners), local public representatives and

government representatives (i.e. KPF&ED) were collected. This was basically through

informal interview but a checklist of issues was identified earlier and used as a basis

for questions. The following aspects were prioritized in FGD: (a) socio-economic and

ecological benefits/losses from the woodlot plantation of exotic species, (b) wildlife in

woodlot plantations and adjacent forests area, (c) potential timber tree species for

commercial woodlot plantations, (d) impacts of exotic tree species monoculture on

socio-economic and ecosystems.

Key Informant Interview

The purposes of this interview were to explore relevant data from different

corners and working groups. Questioning and discussion with key informants (i.e.

Divisional Forest Officer, Sub Divisional Forest Officer, Range Officer and Beat

Officer) were conducted on the traditional forest management system and wildlife

management, and woodlot plantation of exotic tree species at government forest land.

NGOs staff, teachers, government officers, union council chairman and members, and

local elites who provided important data on woodlots of exotic tree species, local

environment/ecosystem. A typical key interview lasted for about one hour and a

prepared checklist of questions was used for the purpose of interview.

45

Secondary Data Collection

Secondary data were collected from related literature and published documents

of government and non-government office for referring or supporting the findings.

Secondary data were collected to assess socio-economic impacts of monoculture of

exotic species, land use pattern, threats to native forests ecosystems and biodiversity.

Some demographic data and other related information were collected from Divisional

Forest Office in Malakand.

3.5. DISCHARGE RATE AND WATER TABLE MEASUREMENT

Three springs were selected randomly from each village. The discharge rate of

springs was measured by diverting the flow of water and passed through a small

hole/opening and the time was noted using a stop watch to fill a bottle of known volume

(300 m L and 1L). For big springs, an ordinary tape was used to measure average width

and depth while multiplying cross-sectional area and current speed (Q = VA). To find

out the speed, light floating object was thrown into the spring water and the time was

noted to cover a known distance. Past discharge rate were predicted by taking the marks

remained on rocks, an ordinary tape was used to measure the average width and depth,

the speed of water was assumed according to the topography of the spring. Water table

was measured using an ordinary tape, reaching it down to the water level in wells

(Kjelstrom, 1995).

46

CHAPTER - 4

RESULTS AND DISCUSSIONS

Khyber Pakhtunkhwa Forest Department and other national and international

organizations launched various types of forestry related projects in the province, in

which large scale plantations of the exotic tree species were carried out. The main

purpose of such plantations was to increase forest cover, reduce of poverty and improve

the livelihood of the local communities in the areas. They focused on establishment of

nurseries to produce the required numbers of seedling of fast growing exotic tree

species to gain economic returns. The existing natural forest is replaced by the

plantations and artificial regenerations of exotic fast growing species. The main

objectives of such projects were to increase the economic returns and ensure that

government strategies of management and policies adopt the same objectives as in the

previous years and is not detrimental to the remaining forests and ecosystems.

The monoculture of exotic species is a matter of great concerns when related to

sustainable development. The plantations of such species and their relative cost and

benefits are controversial subjects between the foresters and tree growers in terms of

social and environmental impacts. The introduction of fast growing species in

plantations projects poses threats to the sustainability of environment and therefore is a

matter of immense importance and is a subject of controversy between conservationists,

botanist, ecologist, foresters and policy makers.

Biodiversity loss and extinction of species may be the results of replacement of

indigenous species with the exotics directly or indirectly by affecting ecosystems. Most

people criticise the plantations as they threaten the habitat of the native forest plants

communities and by taking excessive water from the soil. In addition, ecological

problems were observed when indigenous species were cleared for the plantating of

exotic species (Hussain, 2002).

However, the activities of tree planting are important especially in our country

as the area under forest is lower than the required and the increasing poverty situation

leads to depletion of forests. People near forest area are compelled to cut trees and

overgraze these fragile areas.

47

The historical forestry review of Pakistan showed that the majority of the

projects were launched during the 1970s to 1980s which focused on plantations

establishment but failed to address management of natural forests. Large scale

plantations of exotic fast growing Eucalyptus camaldulensis and other species were

carried out to meet the fuel wood and timber requirements of the people.

No attention in the past has been paid to the ecological and socio-economic

impacts of plantation in District Malakand. This study assessed the ecological and

socio-economic impacts of the monoculture of two exotic tree species Eucalyptus

camaldulensis and Robinia pseudoacacia in comparison to that of indigenous tree

species of Pinus roxburghii and Acacia modesta in District Malakand.

The results of this study assesses the existing status of plant diversity, soil

properties, ground water and socio-economic impacts of monoculture of exotic tree

species on local economy and day to day life of the local people of the research area

have been presented in the following.

4.1. ECOLOGICAL IMPACTS

4.1.1. Undergrowth Vegetation

4.1.2. Floristic composition and Taxonomic Diversity

The plantations of exotic fast growing tree species affect the undergrowth

vegetation and plant diversity to a greater extent because of the invasive properties by

suppressing the indigenous plants species in terms of regenerations and growth. Though

the monoculture of some of the exotic species support the regenerations of the

indigenous species when protected and maintained their wilderness status in the

protected forest of the area. Other factors such as abundance of the planted species,

species types and ecology also affect the regeneration potential of the indigenous

vegetation. The negative impacts of exotic Eucalyptus could be mitigated by keeping

intact the understory vegetation in plantations to favour regeneration and normal plants

development (Liang and Qiang, 2009).

Floristic diversity, as defined by Ali et al. (2016), refers to the sum of all wild

and cultivated plants existing in any geographic area, which reveals the prevailing

climatic conditions, edaphic features, anthropogenic pressure and other natural stresses.

48

The result showed that flora of the research area consisted of a total of 174 plant species

belonging to 74 families and 150 genera, which were found in the selected research

plots of trees of indigenous (Pinus roxburghii, Acacia modesta) and exotic (Eucalyptus

camaldulensis and Robinia pseudoacacia) species. Among the recorded species 143

(82%) were dicotyledons, 26 (15%) species were monocotyledons and 4 (2.3%) were

pteridophytes while only 1 (0.7%) plant was recorded from gymnosperms. (Fig 4.1).

In indigenous plots of Pinus roxburghii, and Acacia modesta a total of 149

species of plants were recorded. Among the recorded species 120 (80%) were Dicots,

24 (16%) were monocots, 4 (3%) were pteridophytes and only 1 (1%) species was found

from gymnosperm as shown Fig. 4.2).

While in the exotic plots of Eucalyptus camaldulensis and Robinia

pseudoacacia a total of 111 species of plants were recorded. Among the recorded

species 93 (84%) were Dicots, 14 (12%) were monocots, 3 (3%) were pteridophytes

and only 1 (1%) species was found from gymnosperm as shown in Fig. 4.3).

Fig. 4.1. Taxonomic diversity of flora of all research plots.

143

25

4 1

174

0

20

40

60

80

100

120

140

160

180

200

Dicot Monocot Pteridophytes Gymnosperm Total

Nu

mb

er o

f sp

ecie

s

Taxonomic groups

49

Fig. 4.2. Taxonomic diversity of flora of indigenous research plots.

Fig. 4.3. Taxonomic diversity of flora of exotic research plots.

Ibrar and Hussain (2009) enlisted 100 ethnobotanical important plants from

Batkhela, District Malakand, which belonged to 49 families and among them 43

families were dicot, 2 of monocot, 2 of pteridophytes, and 1 of gymnosperms.

Barkatullah & Ibrar (2011) reported a total of 169 plant species belonging to 140 genera

and 76 families from Malakand Pass hills. They were represented by 63 dicot families,

5 monocots, 4 pteridophytes and only 1 gymnosperm family. Zabihullah et al. (2006)

documented a total of 82 plant species and their uses for various purposes from kot

Manzaray Baba valley Malakand agency. They found that among these plants 65%

were medicinal, 20% were used for fuelwood, 6% for honeybees, 8% for fruit, 9% for

120

24

4 1

149

0

20

40

60

80

100

120

140

160

Dicot Monocot PteridophytesGymnosperm Total

Nu

mb

er o

f sp

ecie

s

Taxonomic groups

93

14

3 1

111

0

20

40

60

80

100

120

Dicot Monocot Pteridophytes Gymnosperm Total

Nu

mb

er o

f sp

ecie

s

Taxonomic groups

50

timber and 7% as potherb. They also reported that the area is under heavy biotic

pressure of deforestation and overgrazing. Zaman et al. (2013) carried out

ethnobotanical survey of the plant species in Tehsil Dargai and a total of 40 plants were

collected which were represented by 26 families. Out of these 40 plants 12 were trees

and 18, were herbs, 7 were shrubs and 2 were climbers. Muhammad et al. (2016) found

that Dodonea viscosa (L.) Jacq was the dominant shrub species in terms of density and

percent cover. In addition, percent species and abundance show contrast variations with

relative frequency. Muhammad et al. (2016) studied the ethno-botanical importance of

the understorey plants species in Acacia modesta forest of Malakand Division. He

observed that species, such as Vitex negundo, Dodonea viscosa, Zizypus

nummularia and Mallotus philippinensis, were cut down regularly without any

conservation measure. Dogra et al. (2009) carried out comparative study of plant

diversity in exotic and indigenous tree forest. They found that the numbers of plant

species in the plantations of indigenous Pinus roxburghii Sarg. were greater compared

to the exotic Eucalyptus citriodora Hook. Plantations. Khan et al. (2017) reported 264

plants represented by 90 families and 202 genera of which 42 were monocots and 216

were dicots from Tehsil Swat ranizai of District Malakand. Among them 172 plant

species were perennials and 86 were annuals while only 6 species were biennial.

In this research, 174 plants species belonging to 74 families and 150 genera,

were found in the selected research plots of trees of indigenous (Pinus roxburghii,

Acacia modesta) and exotic (Eucalyptus camaldulensis and Robinia pseudoacacia)

origin. Among the recorded species 143 (82%) were dicotyledons, 26 (15%) species

were monocotyledons and 4 (2.3%) were pteridophytes while only 1 (0.7%) plant was

recorded from gymnosperms. (Fig 4.1).

In indigenous plots 149 species of plants were recorded. Among the recorded

species 120 (80%) were Dicots, 24 (16%) were monocots, 4 (3%) were pteridophytes

and only 1 (1%) species was found from gymnosperm as shown Fig. 4.2. In the exotic

plots 111 species of plants were recorded. Among the recorded species 93 (84%) were

Dicots, 14 (12%) were monocots, 3 (3%) were pteridophytes and only 1 (1%) species

was found from gymnosperms as shown Fig. 4.3. The number of uncommon species

were higher in indigenous plots as compared to the exotic plots facing similar extent of

ecological and anthropogenic stresses. This scenario proves that plantations of

51

indigenous species are relatively better in harbouring better species richness and

diversity.

Morphological diversity of the plants of the research plots showed that among

the total 174 plant of all species plots 29 (17%) consisted of trees, 31 (18%) of shrubs,

86 (49%) of herbs, 19 (11%) of grasses, 6 (3.3%) of climbers and only 3 (1.7%)

consisted of sedges (Fig. 4.4).

In indigenous plots a total of 23 (15%), 30 (20%), 74 (50%), 16 (11%), 3 (2%),

3 (2%) were represented by trees, shrubs, herbs, grasses, climbers and sedges

respectively (Fig.4.5).

While in exotic plots a total of 18 (16%) trees, 18 (16%)shrubs, 57 (51%) herbs,

11 (10%) grasses, 5 (5%) climbers and 2 (2%) sedges were recorded (Fig. 4.6).

Fig. 4.4. Morphological diversity of plants species of all plots.

29 31

86

19

6 3

174

0

20

40

60

80

100

120

140

160

180

200

Trees Shrubs Herbs Grasses Climbers Sedges Total

Nu

mb

er o

f p

lan

ts

Morphological diversity groups

52

Fig. 4.5. Morphological diversity of plants species of indigenous plots.

Fig. 4.6. Morphological diversity of plants species of exotic plots.

Based on the life span of the plant species a total of 119 (68%) plants were found

to be perennials, 54 (31%) were found to be annuals and only 1 (1%) plants were

recorded biennial among all the 174 plants in all the research plots of the study area

(Fig. 4.7).

Among the 149 plants of the indigenous plots 108 (72%) were perennials, 41

(28%) were annuals while no plant was recorded as biennials (fig. 4.8). While in the

exotic plots, among 111 plants, 74 (67%), 36 (32%) and 1 (1%) were recorded as

perennials, annuals and biennials respectively (Fig. 4.9).

2330

74

163 3

149

0

20

40

60

80

100

120

140

160


Nu

mb

er o

f p

lan

ts


18 18

57

115 2

111

0

20

40

60

80

100

120


Nu

mb

er o

f p

lan

ts


53

Fig. 4.7. Numbers of annuals, perennials and biennials in all research plots.

Fig. 4.8. Numbers of annuals, perennials and biennials in indigenous plots.

119

54

1

174

0

20

40

60

80

100

120

140

160

180

200

Perennial Annual Biennial Total

Nu

mb

er o

f p

lan

ts

Plant groups

108

41

0

149

0

20

40

60

80

100

120

140

160


Nu

mb

er o

f p

lan

ts

Plant groups

54

Fig. 4.9. Numbers of annuals, perennials and biennials in exotic plots.

It is clear from the Fig. 4.10. that the number of all undergrowth species in Pinus

roxburghii plots in spring, monsoon and winter were 83,83 and 62 respectively. while

in Acacia modesta plots total of 89, 89 and 67 plants species were present in spring,

monsoon and winter seasons respectively.

Fig. 4. 10. Species composition in different tree plots in spring, monsoon and winter

seasons in the study area.

74

36

1

111

0

20

40

60

80

100

120


Nu

mb

er o

f p

lan

ts

Plants group

8389

70 67

8389

70 6762 6758

34

0

20

40

60

80

100

Pinus roxburghii

Plots

Acacia modesta

Plots

Eucalyptus

camaldulensis

Plots

Robinia

pseudoacacia

Plots

Nu

mb

er o

f sp

ecie

s

Plants

Considering all undergrowths species

spring Monsoon winter

55

Similarly, in Eucalyptus camaldulensis plots 70 each in spring and monsoon

and 58 species were recorded during spring, monsoon and winter respectively. While

67 species each in spring and monsoon and 34 plants species of all undergrowths were

recorded during winter in Robinia pseudoacacia plots.

During this study, considering all undergrowth plants a total of 149 species

including 23 tree species were found combined in all indigenous plots in all seasons

whereas 111 undergrowth species including 18 tree species occurred in all exotic plots

in all seasons. (Fig. 4.11).

Fig.4.11. Showing number of all undergrowth plants and number of tree species in

exotic and indigenous research plots.

The findings showed that maximum numbers of plants of all undergrowth were

present in indigenous plots as compared to the exotic plots in the study area. Similarly,

a greater number of trees species were present in indigenous plots as compared to the

exotic plots of the study area.

Maximum number of trees species were found in indigenous Pinus roxburghii

plots which was followed by indigenous Acacia modesta plots and the number of tree

species were 15 and 13 respectively. While 10 tree species were found in both exotic

Eucalyptus camaldulensis and Robinia pseudoacacia plots respectively. Hence 23 tree

species in total were recorded in indigenous plots while 18 species occurred combined

in exotic plots as shown in (Fig.4.12).

111

18

149

23

0

20

40

60

80

100

120

140

160

Number of all undergrowth plants

species

Number of tree species only

Nu

mb

er o

f p

lan

ts

Plants

Exotic Plots Indigenous Plots

56

Fig. 4. 12. Number of undergrowth tree species found in different research plots in the

research area.

4.1.3 PHYTOSOCIOLOGY OF UNDERGROWTH VEGETATION

Undergrowth Plant Density

The result in Fig. 4.13 showed that the density per hectare considering all

undergrowth species in the indigenous Pinus roxburghii Plots were 14933, 17320 and

12907 in spring, monsoon and winter respectively. While in Acacia modesta plots

15773, 18173 and 13427 densities per hectare were found in spring, monsoon and

winter respectively. In exotic Eucalyptus camaldulensis and Robinia pseudoacacia

plots 13387, 14960, 11960 and 14573, 17747, 9813 densities per hectare were recorded

in spring, monsoon and winter respectively. Density per hectare for all indigenous plots

were recorded 15353, 17746.5 and 13167 in spring monsoon and winter respectively

while density per hectare for all exotic plots were recorded 13980, 16353.5 and 10886.5

in spring, monsoon and winter (Fig. 4.13).

The results also showed that the average densities per hectare considering all

undergrowth for Pinus roxburghii, Acacia modesta, Eucalyptus camaldulensis, and

Robinia pseudoacacia plots were found 15053.3, 15791, 13435.7 and 14044.3

respectively. The average density per hectare of indigenous plots of Pinus Roxburghii

and Acacia modesta was 15422.2 whereas the average density per hectare of exotic

plots of Eucalyptus camaldulensis, and Robinia pseudoacacia was 13740. This was

clearly indicated that, the Acacia modesta plots harboured the maximum number of all

species in all seasons, which was followed by Pinus roxburghii plots, Eucalyptus

camaldulensis plots and Robinia pseudoacacia plots (Fig. 4.14).

1513

10 10

18

23

0

5

10

15

20

25

Pinus

roxburghii Plot

Acacia

modesta Plot

Eucalyptus

camaldulensis

Robinia

pseudoacacia

Exotic Plots Indigenous

Plots

Nu

mb

er o

f tr

ee s

pec

ies

Considering undergrowth tree species only

57

Somewhat similar finding was found by Muhammad et al. 2016 in studying

density and diversity of understory vegetation in relation to site conditions in natural

stands of Acacia modesta from malakand division. Densities per hectare recorded for

Otostegia limbata, Justicia adhatoda, Carthamus oxycantha, Chenopodium

album,Cannabis sativa, Cymbopogon distans, Conyza Canadensis, Cenchrus ciliaris,

Parthenium hysterophorus, Solanum nigrum, Saccharum griffthii and Tagetes minuta

occurred with a mean density ranging from 100-460 individuals per ha, and that

Zizyphus nummularia, Nerium indicum, Datura innoxia, Calotropis procera, Daphne

oleoides, Vitex negundo, Grewia optiva, Verbascum thapsus, Amaranthus viridis,

Ajuga bracteosa shared a mean density of 1.25-85 individuals per hectare.

The difference in the density of plants species per hectare and species diversity

may be due to the changes in environmental conditions i.e. light and nutrients

availabilty. In exotic species plantations large and homogenous canopy was formed

with less gaps and because of fast growth of dominant tree species in the plots as shown

in Table 4.3 utilized more soil nutrients. While in indigenous plots the increase numbers

of plants species may be due to the non uniform canopy and the light reached the soil

due to which the regeneration of the understorey vegetations has been affected

differently (Uemura, 1994). The greater densities of plants in the indigenos plots of

species may be due the greater amount of organic matter in the indigenous plots which

produced and returned large amount of litter (Sevgi and Tecimen, 2008). The nutrients

released from litter decomposition were more in indigenous species plots as shown in

Table-4.4 and 4.5 indicated that the soil nutrients like N, P, K, OM, OC was more in

indigenous species plots than exotic species plots.

58

Figure 4.13. Undergrowth densities per hectare considering all undergrowth species in

three seasons in different research plots in the study area.

Fig. 4.14. Average undergrowth density per hectare considering all undergrowth

species in different tree plots in research area.

Relative Density

Considering all undergrowth species, the highest relative density was found in

exotic plots for Dodonaea viscosa (10.42%), followed by Robinia pseudocacia

(7.16%), Eucalyptus camaldulensis (6.81%), Chrysopogon aucheri (3.99%), Olea

0

2000

4000

6000

8000

10000

12000

14000

16000

18000

20000

Pinus

roxburghii

Plot

Acacia

modesta Plot

Eucalyptus

camaldulensis

Plot

Robinia

pseudoacacia

Plot


Plots

Den

sity

/hec

in

dif

fere

nt

seaso

ns

Plants

spring Monsoon winter

15053.3

15791

13435.7

14044.313740

15422.2

12000

12500

13000

13500

14000

14500

15000

15500

16000

Pinus

roxburghii

Plot

Acacia

modesta Plot

Eucalyptus

camaldulensis

Plot

Robinia

pseudoacacia

Plot


Plos

Den

sity

/hec

of

pla

nts

Plants

59

ferruginea (3.84%), Cannabis sativa (2.71%), Symphyotrichum graminifolium

(2.65%), Saccharum filifolium (2.24%). The lowest relative density (0.06%), was found

for Barleria cristata, Calistemin lanceolatus, Caralluma tuberculate, Colebrookea

oppositifolia, Daphne oleoides, Isodon rugosus, Melothria heterophylla, Mentha

longifolia, Peganum harmala, Quercus incana, Rhazya stricta and Salix babylonica

(Appendix-3).

While among the indigenous plots, the relative density was found to be greatest

for Dodonea viscosa (9.26%), Acacia modesta (8.12%), Pinus roxburghii (6.38%),

Chrysopogon aucheri (4.33%), Olea ferruginea (4.15%), Aristida cyanantha (2.26%),

Launaea procumbens (1.97%), Ficus palmata (1.87%). The lowest relative density

(0.05%) was recorded for Colebrookea oppositifolia, Ehretia obtusifolia, Melothria

heterophylla, Mentha longifolia, Monotheca buxifolia, Myrsine africana, Periploca

aphylla, Quercus incana, Solanum surattense, Tecomella undulata, Teucrium

stocksianum and Ziziphus nummularia (Appendix-2).

On the other hand, considering only the seedlings and saplings of the trees

species as the undergrowth, the relative density in the exotic plots was found to be

highest for Robinia pseudocacia (24.8%), Eucalyptus camaldulensis (23.59%), Olea

ferruginea (13.3%), Acacia modesta (6.65%), Mallotus philippensis (6.25%),

Broussonetia papyrifera (5.14%). The lowest relative density (0.2%) was recorded for

Calistemin lanceolatus, Quercus incana and Salix babylonica (Appendix-5).

In indigenous plot the relative density was found to be highest in Acacia

modesta (26.87%), Pinus roxburghii (21.12%), Olea ferruginea (13.73%), Ficus

palmata (6.18%), Mallotus philippensis (5.58%). The lowest relative density (0.17%)

was found for Monotheca buxifolia, Quercus incana and Tecomella undulata

(Appendix-4).

The density of naturally emergent seedlings is mostly damaged due to the

clearing of undergrowth on forest floor, grazing and trampling, and the collection of

leaf litter which were found in the research arae (Kotilouoto and Makandi, 2004).

60

Frequency

Considering all undergrowth species, the highest frequency was found in exotic

plots for Dodonaea viscosa (80%), followed by Olea ferruginea (53.3%), Eucalyptus

camaldulensis (50%), Robinia pseudocacia (48.3%), Pinus roxburghii (25%), Ficus

palmata (25%), Mallotus philippensis (21.6%), Chrysopogon aucheri (21.6%). The

lowest frequency (1.1%) was recorded for Ammi visnaga, Convolvulus arvense,

Heliotropium strigosum, Lathyrus cicera, Malva neglecta, Medicago minima, Papaver

pavoninum, Peganum harmala, Trichodesma indica and Xanthium sibiricum

(Appendix-3).

While among the indigenous plots, frequency was found to be greatest for Olea

ferruginea (78.3%), Dodonea viscosa (73.3%), Acacia modesta (68.3%), Pinus

roxburghii (45%), Ficus palmata (41.6%), Celtis caucasica (40%), Grewia optiva

(28.3%). The lowest frequency (1.1%) was calculated for Martynia annua, Medicago

minima, Oxalis corniculata, Peganum harmala and Plantago major (Appendix-2).

While on the other hand, considering only the seedlings and saplings of the trees

species as the undergrowth, the frequency in the indigenous plot is found to be highest

for Olea ferruginea (78.3%), Acacia modesta (68.3%), Pinus roxburghii (45%), Ficus

palmata (41.6%), Celtis caucasica (40%). The lowest frequency (1.6%), was found for

the Monotheca buxifolia, Quercus incana and Tecomella undulata (Appendix-4).

In exotic plots the frequency was found to be highest for Olea ferruginea

(53.3%), Eucalyptus camaldulensis (50%), Robinia pseudocacia (48.3%), Pinus

roxburghii (25%), Ficus palmata (25%). The lowest frequency (1.6%), was found for


Relative Frequency

Considering all undergrowth species, the highest relative frequency was found

in exotic plots for Dodonaea viscosa (8.3%), followed by Olea ferruginea (5.53%),

Eucalyptus camaldulensis (5.19%), Robinia pseudocacia (5.01%), Ficus palmata

(2.59%), Pinus roxburghii (2.59%), Chrysopogon aucheri (2.25%). The lowest relative

frequency (0.12%), was found for Ammi visnaga, Convolvulus arvense, Heliotropium

strigosum, Lathyrus cicera, Malva neglecta, Medicago minima, Papaver pavoninum,

Peganum harmala, Trichodesma indica and Xanthium sibiricum (Appendix-3).

61

While among the indigenous plots, the relative frequency was found to be

greatest for Olea ferruginea (6.3%), followed by Dodonea viscosa (5.92%), Acacia

modesta (5. 52%), Pinus roxburghii (3.64%), Ficus palmata (3.37%), Celtis caucasica

(3.23%). The lowest relative frequency (0.09%) was found for Martynia annua,

Medicago minima, Oxalis corniculata, Peganum harmala and Plantago major

(Appendix-2).


species as the undergrowth, the relative frequency in the exotic plots was found to be

highest for Olea ferruginea (17.1%), followed by Eucalyptus camaldulensis (16.04%),

Robinia pseudocacia, (15.5%), Pinus roxburghii (8.02%), Ficus palmata (8.02%),

Mallotus philippensis (6.95%). The lowest relative frequency (0.54%), was found for


In indigenous plots the relative frequency was found to be highest in Olea

ferruginea (17.03%), Acacia modesta (14.8%), Pinus roxburghii (9.78%), Ficus

palmata (9.06%), Celtis caucasica (8.7%), Grewia optiva (6.1%). The lowest relative

frequency (0.36%) was found for Monotheca buxifolia, Quercus incana and Tecomella

undulata (Appendix-4).

Abundance

Considering all undergrowth species, the highest relative abundance was found

in exotic plots for Avena fatua (10.5%), followed by Commelina paludosa (9.17%),

Symphyotrichum graminifolium (9.06%), Dryopteris crenata (7.4%), Heteropogon

contortus (7%), Aerva sanguinolenta (6.8%). The lowest abundance (1%) was found

for Barleria cristata, Calistemin lanceolatus, Caralluma tuberculata, Colebrookea

oppositifolia, Dalbergia sissoo, Daphne oleoides, Datura innoxia, Duchesnea indica,

Isodon rugosus, Maytenus royaleana, Melothria heterophylla, Mentha longifolia,

Nannorrhops ritchiana, Opuntia monacantha, Periploca aphylla, Quercus incana,

Rhazya stricta, Sageretia thea, Salix babylonica and Withania coagulans (Appendix-

3).

While among the indigenous plots, abundance was found to be greatest for

Chrysopogon serrulatus (9%), Apluda mutica (8.5%), Dryopteris jaxtaposta and

Imperata cylindrica (8%), Chrysopogon aucheri (7.14%), Adiantum caudatum,

62

Stipagrostis hirtigluma (6.67%) for each one. The lowest abundance (1%) was found

for Albizia lebbeck, Berberis lyceum, Buddleja crispa, Caralluma tuberculata,

Cissampelos pareira, Colebrookea oppositifolia, Daphne oleoides, Datura innoxia,

Desmodium elegans, Ehretia obtusifolia, Lotus corniculatus, Maytenus

royaleana, Melothria heterophylla, Mentha longifolia, Monotheca buxifolia, Myrsine

Africana, Nannorrhops ritchiana, Periploca aphylla, Punica granatum, Quercus

incana, Sageretia thea, Solanum surattense, Tecomella undulata and Teucrium

stocksianum (Appendix-2).


species as the undergrowth, the abundance in the exotic plots was found to be highest

for Broussonetia papyrifera (6.07%), followed by Robinia pseudocacia (5.08%),

Eucalyptus camaldulensis (4.6%), Acacia modesta (3.3%), Mallotus philippensis

(2.8%). The lowest abundance (1%) was found for Calistemin lanceolatus, Dalbergia

sissoo, Quercus incana and Salix babylonica. (Appendix-5).

In indigenous plot the abundance was found to be highest in Pinus roxburghii

(5.46%), Acacia modesta (4.59%), Mallotus philippensis (3.25%), Pistacia chinensis

(3%), Bauhinia variegata (2.4%), Olea ferruginea (2.04%), Ziziphus mauritiana (2%).

The lowest abundance (1%), was found for Albizia lebbeck, Monotheca buxifolia,

Punica granatum, Quercus incana and Tecomella undulata (Appendix-4).

Relative Abundance

Considering all undergrowth species, the highest relative abundance was found

in exotic plots for Avena fatua (2.9%), Commelina paludosa (2.6%),

Symphyotrichum graminifolium (2.5%), Dryopteris crenata (2%), Heteropogon

contortus (1.9%), Aerva sanguinolenta (1.9%). The lowest (0.28%), relative abundance

was found for Barleria cristata, Calistemin lanceolatus, Caralluma tuberculata,

Colebrookea oppositifolia, Dalbergia sissoo, Daphne oleoides, Datura innoxia,

Duchesnea indica, Isodon rugosus, Maytenus royaleana, Melothria heterophylla,

Mentha longifolia, Nannorrhops ritchiana, Opuntia monacantha, Periploca aphylla,

Quercus incana, Rhazya stricta, Sageretia thea, Salix babylonica and Withania

coagulans (Appendix-3).

63

While among the indigenous plots, the relative abundance was found to be

greatest for Chrysopogon serrulatus (2.06%), Apluda mutica (1.94%), Dryopteris

jaxtaposta and Imperata cylindrica (1.83%), Adiantum caudatum, Cenchrus ciliaris

and Stipagrostis hirtigluma (1.52%), Saccharum filifolium (1.49%), Poa annua

(1.46%). The lowest relative abundance (0.23%), was found for Albizia lebbeck,

Berberis lyceum, Buddleja crispa, Caralluma tuberculata, Cissampelos pareira,

Colebrookea oppositifolia, Daphne oleoides, Datura innoxia, Desmodium

elegans, Ehretia obtusifolia, Lotus corniculatus, Maytenus royaleana, Melothria

heterophylla, Mentha longifolia, Monotheca buxifolia, Myrsine Africana,

Nannorrhops ritchiana, Periploca aphylla, Punica granatum, Quercus incana,

Sageretia thea, Solanum surattense, Tecomella undulata and Teucrium stocksianum

(Appendix-2).

On the other hand, considering only the seedlings and saplings of the tree

species as the undergrowth, the relative abundance in the exotic plot was found to be

greatest for Broussonetia papyrifera (13.7%), Robinia pseudocacia (11.5%),

Eucalyptus camaldulensis, (10.6%), Acacia modesta (7.5%), Mallotus philippensis

(6.46%). The lowest relative abundance (2.2%), was found for Calistemin lanceolatus,

Dalbergia sissoo Quercus incana and Salix babylonica (Appendix-5).

In indigenous plot the relative abundance was found to be highest in Pinus

roxburghii (12.3%), Acacia modesta (10.3%), Mallotus philippensis (7.3%), Pistacia

chinensis (6.7%), Bauhinia variegata (5.4%), Olea ferruginea (4.6%). The lowest

relative abundance value (2.26%), was found for the Albizia lebbeck, Monotheca

buxifolia, Punica granatum, Quercus incana and Tecomella undulata (Appendix-4).

Communities structure

The following plant communities were reported from the study of different species plots

in the research area.

1. Pinus-Dodonea-Olea Community

Pinus-Dodonea-Olea community was reported from the study plots of Pinus

roxburghii. Pinus roxburghii, Dodonea viscosa and Olea ferruginea were dominant

species with importance values of 23.07, 14.4 and 9.64 respectively. Mallotus

64

philippensis was co-dominant tree species with importance value 7.37 and the

associated species were Chrysopogon aucheri (8.02), Dryopteris jaxtaposta (8.09),

Dryopteris crenata (6.60), Launaea procumbens (6.10) and Aristida cyanantha (5.77).

2. Eucalyptus-Dodonea- Acacia Community

Eucalyptus-Dodonea- Acacia community was reported from the study plots of

Eucalyptus camaldulensis. Eucalyptus camaldulensis, Dodonea viscosa and Acacia

modesta were dominant species with importance values of 25.8, 22.8 and 9.48

respectively. Mallotus philippensis was co-dominant tree species with importance value

9.27 and the associated species were Dryopteris crenata (9.28), Olea ferruginea (9.08),

Adiantum caudatum (8.74), Pinus roxburghii (8.46), Chryspogan aucheri (7.68),

Aristida cyanantha (7.61%), Cymbopogon jwarancusa (7.15) and Symphyotrichum

graminifolium (7.09).

3. Acacia- Dodonea-Olea Community

Acacia- Dodonea-Olea community was reported from the study plots of Acacia

modesta. Acacia modesta, Dodonea viscosa and Olea ferruginea were dominant

species with importance values of 23.9, 19.6 and 12.79 respectively. Grevia optiva and

Ficus palmata were co-dominant trees species while the associated species were

Chryspogan aucheri (10.04), Justicia adhatoda (7.48), Saccharum filifolium (7.49),

Cymbopogon jwarancusa (6.35) and Aristida cyanantha (5.90).

4. Robinia-Dodonea-Olea Community

Robinia-Dodonea-Olea community was reported from the study plots of Robinia

pseudoacacia. Robinia pseudoacacia, Dodonea viscosa, Olea ferruginea were

dominant species with importance values of 27.18, 18.8 and 12.4 respectively.

Broussonetia papyrifera was the co-dominant tree species and the associated species

were Chrysopogon aucheri (10.36), Cannabis sativa (8.66), Symphyotrichum

graminifolium (8.53), Saccharum filifolium (7.76). Aerva sanguinolenta (7.72).

Carthamus lanatus (7.57), Euphorbia hirta (6.97) and Parthenium hysterophorus

(6.83).

4.1.4. Phytodiversity Index

In this research, the values of Shannon- wiener diversity index were calculated

(appendixes 6.1-6.24) and was statistically analysed in (appendixes 6.25-6.28) and

65

presented in the Table-4.1 and Table-4.2 respectivey.

Table-4.1: Table showing Shannon-Wiener diversity index values recorded for

different research plots.

Name of

season All undergrowth species Undergrowth tree species only

Pinus

roxburghii

Acacia

modesta

Eucalyptus

camaldulensis

Robinia

pseudoacacia

Pinus

roxburghii

Acacia

modesta

Eucalyptus

camaldulensis

Robinia

pseudoacacia

Spring 3.9 3.7 3.5 3.6 2.01 1.77 1.72 1.5 Monsoon 3.95 3.8 3.4 3.7 2.01 1.8 1.76 1.55 Winter 3.6 3.4 3.3 3 2.01 1.77 1.72 1.5 Average 3.83 3.63 3.4 3.43 2.01 1.78 1.73 1.51 Name of

season All undergrowth species Undergrowth tree species only

Indigenous

Plots


Plots

Exotic Plots

Spring 3.8 3.55 1.9 1.61 Monsoon 3.9 3.55 1.9 1.65 Winter 3.5 3.15 1.89 1.61 Average 3.73 3.14 1.9 1.62

Considering all undergrowth species of all research plots, the value of Shannon-

Wiener diversity index (H) was found to vary between 3.83 to 3.40, where the highest

value 3.95 was recorded from Pinus roxburghii plots in monsoon season and the lowest

value 3 was from Robinia pseudoacacia plot in winter season. The highest mean value

(3.833) of Shannon-Wiener diversity index (H) was found in Pinus roxburghii Plots,

followed by Acacia modesta Plots, Robinia pseudoacacia Plots, and Eucalyptus

camaldulensis Plots and their index values are 3.633, 3.4333 and 3.40 respectively. The

mean value 3.83 of Shannon-Wiener diversity index (H) was recorded as the highest

for indigenous plots, whereas the lowest value 3.40 was recorded for exotic plots. The

data from the Shannon-Wiener diversity index (H) calculated for four types of plots

showed the following pattern in four types of tree plots- Pinus roxburghii > Acacia

modesta > Robinia pseudoacacia > Eucalyptus camaldulensis.

The result of this study on species diversity indicated that indigenous tree plots

harbour greater numbers of plants and are more diverse as compared to the exotic plots

which were having relatively less plants. These observations were supported by similar

surveys undertaken by Kohli (1998): Dogra et al. (2009) and Montagnini et al., (2005).

Greater diversity of different plant groups existed in the indigenous Acacia modesta

and Pinus roxburghii despites the area faced collection of leaf litter, fuelwood and

illegal cutting of trees and grazing pressure.

66

On the other hand, considering only the seedlings and saplings of tree species

as undergrowth, the greater mean value 2.01 was found for Pinus roxburghii Plots,

which was followed by 1.78, 1.73, 1.51 for Acacia modesta Plots, Eucalyptus

camaldulensis Plots and Robinia pseudoacacia Plots respectively. The highest mean

value 2.01 was found in indigenous plots while the lowest value 1.51 occurred in exotic

plots. The mean values of Shannon-Wiener diversity index calculated for the seedlings

and saplings of all tree species as undergrowth in all of the four plots followed the given

pattern Pinus roxburghii Plots > Acacia modesta Plots > Eucalyptus camaldulensis

Plots > Robinia pseudoacacia Plots with the index values 2.01,1.78, 1.73, 1.51

respectively.

Table-4.2. Mean values of Shannon- weiner diversity index of different research plots

calculated after analysis using statistics 8.1 software two-way ANOVA (LSD) was

used to test for significant differences (P<0.05) for marginal means of variables.

Mean values with different alphabet letters shows significanct difference at p < 0.05.

It is clear from the table 4.2 that the highest Shannon-Wiener Diversity index

value (H) was found for Indigenous plots with the index value of 3.73 while the lowest

value 3.41 was found for all exotic plots when all undergrowth species were considered.

While considering only the seedlings and saplings of tree species of undergrowth the

highest index value (1.89) was recorded for indigenous plots followed by exotic plots

(1.62).

4.1.5. Tree productivity

The detail data related to tree productivity which included trees density per hectare,

trees height, DBH, basal area and tree stem volume in the plots of different exotic and

indigenous species are presented below.

Treatments All undergrowth species

Undergrowth tree species

only

PLANTS

Pinus roxburghii Plots 3.833 a 2.01 a

Acacia modesta Plots 3.633 ab 1.78 b

Eucalyptus camaldulensis

Plots 3.4000 b 1.73 c

Robinia pseudoacacia Plots 3.4333 b 1.51 d

LSD 0.25 0.02

Exotics vs Indigenous

Exotic 3.73 1.89

Indigenous 3.41 1.62

Significance significant Significant

67

Table-4.3: Density of trees, height, DBH, basal area and gross tree stem volume

in different plots of exotic and indigenous species.

Types of plots Density/hac Height

(m)

DBH

(cm)

Basal Area

(m2/hac)

Gross tree

stem volume

(m3/hac)

E. camaldulensis 995 12 23 41 778

R. pseudoacacia 1010 5 21 35 274

Exotic species

plots (average) 1002 8.5 22 38 526

A. modesta 1130 5 20 35 278

P. roxburghii 960 10 20 30 473

Indigenous species

plots (average) 1045 7.5 20 32 375

It is evident from the data given in Table-4.3 that the number of trees per hectare

in the plots of E. camaldulensis, R. pseudoacacia, A. modesta, P. roxburghii were 995,

1010, 1130 and 960 respectively. The average number of trees in the exotic and

indigenous plots of species were 1002 and 1045 respectively which indicated that the

average number of trees per hectare in the exotic species plots and indigenous species

plots were not much differet. Mean height of trees in the exotic species plots was

maximum (8.5 m) whereas it was lower (7.5 m) in the Indigenous species plots. The

increased height of trees in the exotic plots indicated that the exotic species grown

rapidly and gain sufficient heigh because of their fast growing nature. The indigenous

species gain low height because they were slow growing.

The result showed that maximum (22 cm) DBH was recorded in exotic species

plots and low (20 cm) in indigenous species plots. It is clear from the DBH data that

the exotic species gain maximum diameter due to fast growth and the indigenous

species gained relatively less diameter because of slow growth. The result showed that

basal area recorded from the plots of exotic species was more (38 m2/hac) as compared

to indigenous species plots (32 m2/hac). Greater basal area of the exotic species plots

showed that canopies of trees covered much of the the area of ground as compared to

the the indigenous species plots. Gross tree stem volume recorded from the exotic

species plots were maximum (526 m3/hac) whereas the it was lower (375 m3/hac) in

indigenous species plots which indicated that the exotic species plots produced more

68

quantity of wood because of their fast growth as compared to the indigenous species

plots which produced relatively low wood due to slow growth.

4.2 SOIL PHYSICO-CHEMICAL PROPERTIES

The detailed results of physico-chemical parameters of soil, such as pH, organic

matter, organic carbon, nitrogen, phosphorus, potassium, soil electric conductivity,

calcium carbonate recorded during winter, spring and monsoon have been presented in

Appendix 7.1, 7.2, and 7.3 respectively. Data were statistically analysed using 8.1

software two-way ANOVA and LSD was used to test for significant differences

(P<0.05) for marginal means of variables. After the analysis of data mean values were

summarized in the Table 4.4 and Table 4.5 described under the following headings.

pH

Soil pH influences plants growth through improvement in soil physical

conditions and the increase or decrease in soil pH affect nutrients availability for plants

growth. The results in (Table 4.4) have shown that pH of soil samples studied varied

from acidic to alkaline with values ranging from 6.78 to 7.06. The pH of the soil in all

types of research plots were significantly different from each other. The result showed

that the exotic species made the soil alkaline (pH = 7.05) while the indigenous species

made it acidic (pH = 6.85) as shown in (Table 4.4).

Table-4.4: Mean values of different physico-chemical parameters of soil of different

research plots.


The soil under the cultivation of different plant species have also significantly

different in different seasons. The results in Fig.4.15 showed that the highest pH was

found during spring season followed by winter and the least pH value were recorded

Plants Soil pH

Organic

matter (%)

Organic

carbon (%)

Soil EC

(dSm-1)

R. pseudoacacia 6.97 b 1.35 c 0.73 c 0.22 a

E. camaldulensis 7.06 a 1.28 d 0.70 d 0.15 b

A. modesta 6.93 c 1.41 b 0.77 b 0.15 b

P. roxburghii 6.78 d 1.91 a 1.07 a 0.14 b

LSD 0.0143 0.0083 0.0056 0.0613


Exotic 7.015 1.31 0.71 0.18

Indigenous 6.85 1.66 0.92 0.14

Significance significant significant Significant Non significant

69

during monsoon in all plots under the cultivation of the different four species. The soil

becomes more acidic under the conditions of warm temperature and excessive rainfall

as weathering of soil takes place rapidly. Leaching of basic cations like, Ca, Mg, K

from the soil profile results in the formation of more stable materials rich in Fe and Al

oxides. This natural process of weathering makes soil more acidic and generally lack

of nutrients (Hue and Uchida, 2000). Shaikh (1996) found that high pH of

Fig.4.15. Showing soil pH of plots of different plants in different seasons.

soil ocuurred in summer and in winter. The present result also revealed that the plots

under cultivation of exotic plants had the high soil pH values while the indigenous

species plots were having low pH values collectively in all seasons. This may be due to

high organic matter contents and undisturbed nature of the indigenous species

plantations as compared to the exotic species plantations. According to Brady and Weil

(2002) the indigenous forest has low pH as compared to the disturbed forest because

organic matter in the form of plant litter, compost, and manure decreased soil pH

through the decomposition process. High amount of humus in the soil of indigenous

plantations is responsible for low soil pH (Dimri et al. 1987). According to De Hann

(1977) low pH occurred due to the accumulation and consequent slow decomposition

of organic matter, which releases acid. Accordind to Bailey et al., 2005 acidification

may lead to depletion of the soil base cations like K+, Mg2+, Ca2+ which arised from

the replacement of the basic cations by Al3+ and H+ ions at the exchange site.

Similarly, Castro-Diez et al. (2011) found that low soil pH limits the growth and

activities of decomposer soil micro-organisms as soil biological activities are reduced

6.96

7.01

6.93

7.05

7.1

7

6.92

6.97

6.89

6.77

6.82

6.746.7

6.8

6.9

7

7.1

Winter Spring Monsoon

Soil

pH

Seasons

Soil pH

R. pseudoacacia

E. camaldulensis

A. modesta

P. roxburghii

70

in acidic soils. As the soil pH in the present study is not as much low as described by

the researchers. Berendse, 1998 reported that at soil pH of below 5.5, soil trace nutrients

like Manganese (Mn) and Aluminium (Al) availability increase to levels that become

toxic for most plant growth. Further, soil nutrients such as phosphorus and nitrogen

tend to form insoluble compounds with Al and Fe in acidic soils, become adsorbed and

therefore, made inaccessible for plant uptake.

The result of this study was supported by Robertson and Vitousek (1981) and

Adams and Sidle (1987) who reported low pH in indigenous forest soils as compared

to plantation forest soils. According to Leskiw (1998) the forest soils should be slightly

acidic to keep balance for nutrient supply. Semwal et al. (2009) found that the pH values

were highly acidic in the indigenous forest as compare to disturbed forest. Contrasting

results were found by Rhoades & Binkley (1996) Cao et al. (2010) and Alemie (2009)

who reported low soil pH in exotic Eucalyptus spp. plantations as compared to native

species plantations. Aweto and Moleele (2005) claimed that Eucalyptus species

immobilized soil exchangeable bases, especially calcium leading to low soil pH.

Organic matter (OM)

Organic matter influences physical and chemical properties of soil and

determines the cation exchange capacity of the soil. The formation of organic matter

occurs as a result of decomposition of plant tissues and digestion of microorganisms.

Soil humus is the result of organic compounds like resistant compounds of high plant

origin such as oil, fats waxes, lignin and new compounds such as polysaccharides and

polyuronides. Soil organic matter in soil speed up the weathering process in the soil and

results in increasing the availability of nutrient ion species. Potassium and phosphorus

in soil in the available form is due to the availability of soil organic matter (Brandy,

1974).

It is clear from the data (Table 4.4) that organic matter contents (%) varied from

1.28% to 1.91% in the soil samples of different research plots of the study area. Mean

values were significantly different from each other. The greatest mean value of 1.91%

was recorded for Pinus roxburghii plots, followed by A. modesta, R. pseudoacacia plots

with the values of 1.41%, 1.35% respectively and the lowest value of 1.28% was

recorded for E. camaldulensis plots soils. Regarding the comparison between

indigenous and exotic, the result showed that maximum organic matter 1.66% was

71

found for indigenous species plots while the lowest organic matter 1.31% were found

for exotic species plots of the study area.

The organic matter content also significantly fluctuated during different

seasons. The result showed that maximum organic matter was recorded during the

monsoon season followed by winter season and the lowest during the spring season, all

the four species plots follow the same patteren as shown in (Fig. 4.16). Organic matter

recorded from all of the four plots during three different seasons showed the following

pattern P. roxburghii > A. modesta > R. pseudoacacia > E. camaldulensis.

Fig. 4.16. Showing organic matter (%) in plots of different plants in different

seasons.

Seasonal variations in soil organic matter have been extensively studied by (Angers,

1992; Leinweber et al.,1994; Powlson et al. 2003; Hendrix, 1997; Kieft et al., 1998;

Knops and Tilman, 2000 and Dabek-Szreniawska and Balashov, 2007). The

accumulation of organic matter in soil is strongly influenced by temperature and by the

availability of oxygen, since the rate of biodegradation decreses with decrease in

temperature; organic matter does not degrade rapidly in colder climates and tend to

build up in soil (Manalian, 1994).

The results showed that the maximum percentage of OM was observed in the

plots of indigenous species plantations and minimum in exotic species plantations. In

all type of plots of species maximum organic matter percentage was recorded in

1.27 1.17

1.57

1.22 1.12

1.51.34 1…

1.64

1…

1.75

2.15

1

1.5

2

2.5


Org

an

ic m

att

er (

%)

Seasons

Organic matter

R. pseudoacacia

E. camaldulensis

A. modesta

P. roxburghii

72

monsoon season followed by winter and minimum during spring season. Declining

trend during the spring season may be due to the decrease in organic matters contents

with increase in temperature and decomposition rates became doubles with every 10 oC

increase in the temperature (Schlesinger, 1997; Hartel, 2005; Kirschbaum, 1995;

Albrecht and Rasmussen, 1995). The greater amount of organic matter in the

indigenous plots may be due to production and returns of large amount of litter (Sevgi

and Tecimen, 2008). The release of nutrients from litter decomposition is a natural

process in the internal biogeochemical cycle of an ecosystem, and decomposers recycle

a large amount of carbon that was bounded in the plant or tree to the atmosphere. The

results also revealed that soils in the indigenous plots had the maximum content of

organic matter in all the seasons and the minimum was observed under exotic plots in

all the seasons. This may be due to large amount of litter produced in indigenous species

plots as compared to exotics species plots therefore, accumulation of organic matter

was higher.

According to Lima et al. (2008) considerable changes in soil organic matter

(SOM) occurred when native vegetation was replaced with exotic Eucalyptus spp.

plantations in Brazil. Similarly, Bhatti et al. (2002) found that 83 % in the surface soil

and 94 % in the sub-soil of soil samples in Pakistan were low (< 1 %) in organic matter

under exotic Eucalyptus spp. plantation soils. Jan et al. (1996) also found great changes

in organic matter in Eucalyptus spp. plantation soils relative to Shorea robusta natural

forest soil in Uttar Pradesh, Bangladesh. Result of a study carried out on the effect of

Eucalyptus camaldulensis plantations on soil properties and soil fertility in D. I. Khan

District in Pakistan, showed that the organic matter content in the surface soil at 0-15

cm depth ranged from 0.38 to 1.10 %., which were low according to the established

criteria (Baber et al., 2006). The level of Organic matter contents is considered low if

it is less than 4 %, medium if it is between 4 % and 8 %, and high if it is above 8 %

(University of Connecticut, Cooperative Extension System, 2003). Chen et al. (2013)

found that during deforestation of native vegetation and establishment of exotic

Eucalyptus spp. plantation, soil macro-aggregates were disrupted and exposed to

microbial breakdown, as a result of organic matter being lost from soil. Zhang et al.

(2012) add that lower organic matter inputs are provided to the soil since young

Eucalyptus spp. stands may provide a low amount of inputs of plant residues to the soil.

73

Organic Carbon

The presence of organic carbon in soil regulates the growth of microorganisms

and makes the system more dynamic. The result revealed in Table 4.4, appendix-10

showed that OC contents (%) calculated from the soil samples of the research plots

during three different seasons showed variations from 0.70% to 1.07%. The result

showed that OC contents in percent in all types of plots of different species were

significantly different from each other. Comparison between exotic and indigenous

species plots showed that more organic carbon (0.92%), was recorded for indigenous

species plots while lower (0.71%) was recorded for exotic species plots.

Fig. 4.17. Showing soil organic carbon (%) in plots of different plants in different

seasons.

The OC percentage in the soil of plots of different species fluctuates during

different seasons. The result showed that maximum OC was recorded during the

monsoon season followed by winter season and the lowest during the spring season

(Fig.4.17). Organic Carbon recorded from all of the four plots during three different

seasons showed the following pattern P. roxburghii > A. modesta > R. pseudoacacia >

E. camaldulensis.

The results revealed in Fig. 4.17 shows that the organic carbon content were

maximum in monsoon followed by winter and minimum in spring. The decrease in the

soil OC in spring may be due to the increase in temperature and high decomposition

0.74

0.64

0.82

0.7

0.6

0.780.78

0.68

0.86

1.07

0.97

1.15

0.4

0.6

0.8

1

1.2


Org

an

ic c

arb

on

(%

)

Seasons

Organic carbon

R. pseudoacacia

E. camaldulensis

A. modesta

P. roxburghii

74

rate (Kirschbaum, 1995; Albrecht and Rasmussen, 1995). Maximum OC in the

indigenous plots may be due to the high amount of litter in soil (Sevgi and Tecimen,

2008). Nutrients released through the process of decomposition by decomposers and

soil carbon was recycled in large quantity that was bounded in the plant or tree to the

atmosphere.

The results also revealed that soils in the indigenous plots had the maximum

content of organic carbon in all the seasons and the minimum was observed under

exotic plots in all the seasons. This may be due to large amount of litter produced in

indigenous plots of species as compared to exotic species plots where the

decomposition rate of litter was comparatively slow therefore, accumulation of organ

carbon was higher in indigenous as compared to exotics.

Similarly, study carried out by Bernhard-Reversat (1998) found that the organic

carbon concentration in the 0–10 cm depth of native Acacia seyal woodland in Keur

Maktar, Senegal was twice that in a corresponding layer of soil under Eucalyptus spp.

plantation. Cortez et al. (2014), reported that organic C decreased in the first year of

the conversion of native forest to exotic plantations in Brazil. Hou (2006) further

suggested that exotic species of Eucalyptus have a high growth rate and C fixation

potential; therefore, part of the assimilated C is transported to the soil through litter fall

and rhizo- deposits, and hence the potential of increasing soil organic content with time

(Lima et al., 2006). Therefore, it is likely that the changes in soil chemical properties,

particularly in SOM, differ after several exotic plantation rotations, varying with the

soil type and dominant climate conditions (Leite et al., 2010).

Soil Electric conductivity

It is evident from the table 4.4 that the highest value 0.22 dSm-1 was recorded

for R. pseudoacacia and the lowest value 0.14 dSm-1 was recorded for P. roxburghii

species plots. The result showed that soil EC among different plots of plant were not

different significantly from each other and the exotic and indigenous plots of plants

were also not significantly different. This may be due to the same soil texture i.e. sandy

loam of soil in all plots of plants due to which the soil EC were not significantly

different from each other.

Soil EC is a measurement that reflects crop productivity, soil texture, cation

exchange capacity (CEC), drainage conditions, organic matter level, salinity and

75

subsoil characteristics. Sands have a low conductivity, silts have a medium

conductivity, and clays have a high conductivity. Soil EC is mainly correlated to the

presence of soluble salts in the soil (Ali and Rub, 2017). In present study, the soluble

salts may drain out from the root zone due to the sandy loam texture of all the plots soil.

Sandy loame texture are always low in EC (McKenzie and Jacquier, 1997).

Fig. 4.18. Showing soil electrical conductivity of plots of different plants in

different seasons.

Among the different seasons the EC fluctuates (Fig.4.18) but not significantly

(Table 4.4). Among the different plants species R. pseudoacacia plots with high E.C

was recorded than the other three species. This may be due to the low absorption of

soluble salts in R. pseudoacacia plots or more sensitivity of the species to salinity than

the rest of the species. While the other three species may have the ability to absorb soil

solutions of relatively high soluble salts (Fig.4.18).

Among the different seasons as in the spring the temperature goes up the soil

become relatively dry, therefore the presence of soluble salts may be related to soil

texture and in monsoon and winter were wet seasons therefore the soluble salts were

drained out as the soil texture is loos.

0.24

0.2 0.22

0.15

0.19

0.13

0.14

0.18

0.120.13

0.17

0.110.1

0.12

0.14

0.16

0.18

0.2

0.22

0.24


Soil

EC

(d

Sm

-1)

Seasons

Soil Electrical Conductivity

R. pseudoacacia

E. camaldulensis

A. modesta

P. roxburghii

76

Nitrogen

The result revealed in Table 4.5 that soil total nitrogen among the plots of

different species varied from 0.110% to 0.077%. Total nitrogen in percent recorded

from different plots of species were significantly different from each other. The highest

value (0.0865%) was recorded for indigenous species plots while the lowest value

(0.07551%) was recorded for exotic species plots.

Table-4.5: Means showing nutritional status of different species plots.


Fig. 4.19. Showing soil total nitrogen in percent of plots of different plants in

different seasons.

The result in Fig. 4.19. showed that Soil N contents were recorded highest

during the monsoon season followed by winter season and the lowest was recorded

0.07

0.05

0.10.1

0.08

0.13

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14


Tota

l n

itro

gen

(%

)

Seasons

Total nitrogen

R. pseudoacacia, E. camaldulensis and A. modesta P. roxburghii

Plants

Total

Nitrogen

(%)

Phosphorus

(ppm)

Potassium

(ppm)

Calcium

carbonate

(mmole/meter)

R. pseudoacacia 0.077 c 7.4 c 90.3 c 4.8 c

E.camaldulensis 0.074 d 7.1 d 86.3 d 5.7 a

A. modesta 0.081 b 7.89 b 95.25 b 5.2 b

P. roxburghii 0.110 a 10.8 a 130.3 a 3.4 d

LSD 0.00053 0.053 0.644 0.093


Exotic 0.075 7.25 88.3 5.2

Indigenous 0.086 9.34 112.7 4.3

Significance Significant significant significant Significant

77

during spring season in all types of plots of plants. As all the three species (A. modesta,

R. pseudoacacia and E. camaldulensis plots) have the same recorded values in each and

every season, therefore the graph in Fig. 4.19. shows single line for the three species.

Whereas P. roxburghii plots were having highest N in all seasons as compared to the

other three species.

Among the different seasons the total nitrogen in the soil was less in spring as

compared to the monsoon and winter seasons because the spring season is active season

for most of the plants and most of the N from the soil were utilized due to which the

concentration of N in the soil become low and the soil was depleted in spring season.

The increased nitrogen contents during the rainy monsoon season could be best

explained by the possible activity of nitrogen fixing microbes. Evidence exists to show

that increased biological nitrogen fixation along with increased mineralization rates

occur during the rainy season, which resulted in increased nitrogen content at this time

(Bergeron et al. 2002). Higher values of total nitrogen in the soil profile during rainy

season reflects blue green algae fixation, rain water input and higher rate of release of

mineral nitrogen through microbial decomposition (Birch, 1958 and Choudhri and

Sharma, 1975). Singh and Singh (2006) reported that during dry periods, plant uptake

of nutrients is greatly reduced and the N-mineralization and nitrification are either

immobilized in microbial biomass or accumulate in the soil as inorganic nitrogen and

the minimum was observed in spring season. The results showed that during winter

season with little or no rain, there is no leaching of nutrients from the soil which results

in the accumulation of high nutrients in winter after monsoon season.

The rate of nitrogen release to plant growth is rapid during the warm growing

season and slow during the winter months (Manahan, 1994). According to FAO (2011)

soil total N and available P decreased as a result of reforestation with exotic plantations.

Similarly, study carried out by Leite et al. (2010) concluded that large nutrient amounts

are exported when exotic Eucalyptus spp. plantation are harvested, causing a reduction

in the soil nutrients content such as total N and available P. Jagger and Pender (2000)

found that fast growing non-leguminous exotic species are not recommended for

intercropping with annual crops. Tererai et al. (2014) found that reduction in soil total

N occured with an increase in exotic Eucalyptus camaldulensis cover compared to the

site not covered by the Eucalyptus spp. in South Africa. Alemie (2009) also found that

concentration of soil TN decreased under plantations of exotic species in Ethiopia.

Nitrogen concentration in soils is associated with the rate of decomposition of the plant

78

material (Demessie et al., 2012). Aweto and Moleele (2005) Baber et al. (2006) Cao et

al. (2010) and Demessie et al. (2012) found that Eucalyptus spp. produce litter with

low nutrient concentrations, which decomposes slowly to release low concentrations of

nutrients.

Phosphorus (P)

It is evident from the table 4.5 that the Phosphorus values (ppm) recorded in

different plots of species varied in a range of 7.1 ppm to 10.8 ppm. The greatest mean

value 10.8 ppm was recorded for Pinus roxburghii plots while the lowest value 7.1 ppm

was recorded for E. camaldulensis plots. The result showed that the concentration of

soil phosphorus contents was greater in indigenous plots (9.34%) as compared to exotic

plots (7.25%).

Fig. 4.20. Showing soil available phosphorus (ppm) of plots of different plants in

different seasons.

The phosphorus level also fluctuated significantly during different seasons. The

results in Fig. 4.20 showed that maximum phosphorus occurred during monsoon season

followed by winter season and the lowest were recorded during spring season in all

types of plots of plants. Mean values of phosphorus recorded from all of the four plots

during three different seasons showed the following pattern P. roxburghii > A. modesta

> R. pseudoacacia > E. camaldulensis.

7.42

5.67

9.37

7.08 5.33

9.037.82

6.07

9.77

10.74

8.99

12.69

5

6

7

8

9

10

11

12

13


Ph

osp

horu

s (p

pm

)

Seasons

Phosphorus

R. pseudoacacia

E. camaldulensis

A. modesta

P. roxburghii

79

The high level of phosphorous recorded in indigenous plots of species as

compared to the exotic plots may be due to the production and returns of large amount

of litter and the release of nutrients from litter decomposition (Sevgi and Tecimen,

2008).

Phosphorus is an important component of plants mostly available in

orthophosphate form at the neutral soil pH. The inorganic phosphorus in soil depends

on soil pH, soluble iron, aluminium and manganese, the presence of iron, aluminium

and manganese containing minerals, calcium minerals, amount and decomposition of

organic matters and activities of microorganisms (Manahan, 1994). The decrease in the

soil phosphorus level during the springs season was due to the active season of plants

growth and most of the available phosphorus in the soil was depleted by plant uptake.

While maximum amount of phosphorous during monsoon followed by winter might be

due to more accumulation of minerals in monsoon and winter seasons. According to

Ashraf et al. (2012) soil with more leaching contains less amount of phosphorus in

comparison to the soil with less leaching. The result of the present study is similar with

the study carried out by Fith and Nelson (1956) and Keogh et al. (1972) by concluding

that when soil levels for phosphorus and percent organic matter are high, the amount of

potential seasonal variation of phosphorus values tends to increase. Semwal et al.

(2009) reported that the available phosphorus occurred more in winter season due to

more accumulation of minerals takes place in winter season. Miller and Donahuer

(2001) reported that the soil with high organic matter content have better supplies of

organic phosphate for plant uptake than have the soils with low organic content. Gupta

and Sharma (2008) also reported that carbon and phosphorus were positively correlated

because all these attributes were intimately linked with soil humus.

The result of this research is in accordance with the studies conducted by FAO

(2011) Leite et al. (2010) Jagger and Pender, (2000) pointed out that soil total N and

available P decreased as a result of reforestation with exotic plantation and emphasized

not to recommend the fast growing non-leguminous Eucalyptus spp. for intercropping

with annual crops. Similarly, Aweto and Moleele (2005) found that soil available

phosphorus was relatively low in soil under Eucalyptus spp. plantation due to the long-

term immobilization in the plantation standing biomass. In Australia, Polglase et al.

(1992) found that the concentration of soil available phosphorus in the topsoil (0–5 cm

80

depth) under exotic plantation declined from an initial concentration of 34 to 2.3 µg g−1

of soil after 16 years. Alemie (2009) further reported that soil available phosphorus

concentration in Eucalyptus spp. plantation within 2 cm depth of soil was in the very

low range (< 5 mg kg-1) in Ethiopia.

Potassium

It is clear from the Table 4.5 that the mean values of K recorded from different

plots of species were significantly different from each other and comparison between

indigenous and exotic species plots showed that more K (112.7 ppm) was recorded for

indigenous species plots while low K level (88.3 ppm) was recorded for exotic species

plots.

Fig. 4.21. Showing Soil potassium (ppm) of different plants in different seasons.

The level of K fluctuated significantly during different seasons. The result

revealed in Fig. 4.21 that highest level of K was found during monsoon season followed

by winter season and the lowest during spring season in soil of all species plots. Mean

values of K recorded from all of the four plots during three different seasons showed

the following pattern P. roxburghii > A. modesta > R. pseudoacacia > E. camaldulensis.

The greater availability of potassium observed in the soil of indigenous species

plots as compared to exotic species plots may be due to the presence of dense vegetation

in indigenous plots which reduced loss in soil micro and macro nutrients essential for

plants growth and energy fluxes as compared to the exotic plots where there were less

89.0482.04

100.04

84.9877.98

95.9893.92

86.92

104.92

128.98

121.98

139.98

70

80

90

100

110

120

130

140


Pota

ssiu

m (

pp

m)

Seasons

Potassium

R. pseudoacacia

E. camaldulensis

A. modesta

P. roxburghii

81

vegetations (Iwara et al., 2011). The decreased in the level of soil potassium during

springs season might be due to the high uptake rate during active season of plants

growth and most of the available potassium in the soil was depleted as a result of plants

uptake. While the maximum amount of phosphorous was during the monsoon followed

by winter this might be due to more accumulation of minerals in monsoon and winter

seasons. It was observed from the above results that the greater the organic matter, the

larger is the accumulation of minerals in the soil. This was also reported by Chauhan

(2001) by finding a positive corelationship between organic matter and available

potassium and that with the increase in organic matter tends to increase the

accumulation of available potassium in the soil. Potassium values generally increase

during the winter months because of shifts in soil equilibrium conditions due to freezing

and thawing actions releasing fixed potassium from non exchangeable forms,

depending upon the type of clay minerals present (Fine et al., 1940 and Keogh, et al.

1972).

The result in this study is supported by studies of Nwoboshi (1972) and Chijioke

(1978) in which they reported low concentration of potassium in the soil of exotic tree

species plantations as compared to the indigenous tree species. This low concentration

of potassium showed that exotic tree species absorb more K as compared to the

indigenous tree species.

Calcium carbonate

It is evident from the Table 4.5 that the calcium carbonate contents in different

species plots varied significantly from each other and higher calcium carbonate contents

(5.25 mmole/meter) was found in exotic species plots while lowest (4.3 mmole/meter)

in indigenous species plots.

The results in Fig. 4.22 showed that highest calcium carbonate was found during

the spring season followed by the winter season and the lowest was recorded during the

monsoon season in all plots of different plants. Mean values of calcium carbonate

recorded from all of the four plots during three different seasons showed the following

pattern E. camaldulensis. > A. modesta > R. pseudoacacia > P. roxburghii.

82

Fig. 4.22. Showing Calcium carbonate (mmole /meter) of plots of different


According to Curtin and Smeller (1995) the greater amount of lime in exotic plots

of plants may be due to high pH in exotic plots and low lime contents in indigenous

plots of plants may be due to low soil pH in indigenous plots. The result showed that

highest calcium carbonate was found during the spring season and lowest during the

monsoon season in all plots of different species. This may be due to the increased

leaching effect during the rainy monsoon season and winter season while the

concentration of lime on the surface increase during hot and dry season.

Lime contents affect physically the decomposition of soil organic matter,

synthesis of humus and the stimulation of nitrogen fixing bacteria and chemically by

decreasing the concentration of hydrogen ions, increase in the concentration of

hydroxyl ion, decline in the solubility of iron, aluminium and manganese, increase in

the availability of phosphate and molybdates, increase in the ion exchange of calcium,

magnesium and the availability of potassium while biologically by accelerating the

activity of heterotropic soil organism which not only favours, the formation of humus

but also encourages the elimination of certain organic intermediate product that might

be toxic to plants (Brandy, 1974).

4.35

6.65

3.65

5.17

7.47

4.47

4.67

6.97

3.97

2.9

5.2

2.22

3

4

5

6

7

8


Calc

ium

carb

on

ate

(m

mole

/met

er)

Seasons

Calcium carbonate

R. pseudoacacia

E. camaldulensis

A. modesta

P. roxburghii

83

4.3 SOCIO-ECONOMIC IMPACTS OF THE MONOCULTURE OF

EXOTIC TREE SPECIES

Plantations of fast growing species have increased over the last two decades

which helps in uplifting the socio-economic condition of the local inhabitants by

employment generation in plantation, nurseries and business in timbers. Plantations of

Eucalyptus camaldulensis and R. pseudoacacia are found in the study area.

Agriculture land is mostly used for woodlot plantation. Among all other exotic

species available in Pakistan, Eucalyptus camaldulensis was found to be highly

adaptable and fast growing tree species to withstand even degraded site conditions and

in a wide range of soils under different conditions (Kamara and Maghembe, 1994; NAS,

1980; Duguma and Tonye, 1994 and Akkasaeng et al., 1989). Eucalyptus and Robinia

pseudoacacia proved successful for afforestation, reforestation and agroforestry

programs in Pakistan. Exotic tree species put pressure on the environment and

ultimately directly and indirectly have affect at different levels and there was a need to

undertake a detailed investigation. The decisions to plant exotic tree species are based

primarily on the potential economic benefits and short term gains without considering

long term gains and sustainability of environment.

Mostly poor communities rely on short-term economic gains from exotic

species and do not know the complexity of planting such species. They are unaware of

the negative impacts of monoculture of exotic species on natural ecosystem and

biodiversity that are affecting their long term economic gains. Keeping these views in

mind, the socio-economic impacts of monoculture of exotic tree species in District

Malakand were assessed to determine how monoculture plantations of exotic tree

species are affecting the local economy and every-day life of the local people.

The research area baseline information on the exotic tree growers and their

socio-economic impacts were collected. The cost and benefits of raising woodlot

plantations were calculated. The information was collected through a comprehensive

questionnaire survey. The results of the information gathered has been described under

the following headings.

4.3.1 Basic Information of the tree growers

The results of the survey showed that all household heads who were growing

trees were male and they were all married. The respondents who were growing trees

84

in their land were on average age of 50 years old with a minimum age of 32 years and

a maximum age of 75 years. 90% of the respondents were literate while 10% were

illiterate.

Education

Among the total 30 tree growers, 10% i.e. only 3 respondents were found to be

illiterate while 27 (90%) of the them were literate, of which 8 (27%) were educated up

to primary level, 14 (47%) of the respondents were educated up to secondary school

level, 2 (7%) were educated to higher secondary level while, 2 (7%) were graduate and

only 1(2%) of the respondents were educated to postgraduate level.

Occupation

The occupation of most of the respondents who were growing tree were

agriculture. About 21 (70%) of the respondents had an occupation of agriculture, 6

(20%) of the respondents were doing their own business and 2 (7%) of the respondents

were social workers while only 1 (3%) of the respondent was a teacher.

Land Use Pattern

In the research area lands were utilized mostly for farming, housing and forestry

(tree cultivation) purposes. The average land holding size collectively of the all the

respondents were 0.88 ha, of which 18%, 52% and 30% were used for homesteads,

agricultural and tree plantation purposes respectively. The average land size for each

homestead was 0.16 ha with a minimum size of 0.07 ha to maximum size of 0.52 ha. In

case of land holdings, respondents were divided into three land holdings classes such

as respondents having more than 0.25 ha of land, classified as large farmer; less than

0.25 ha but greater than 0.15 ha, classified as medium farmer; and less than 0.15 ha

were classified as small farmer. Out of 30 respondents, only 9 (30%) households had

above 0.25 ha landholding size used for tree growing. While, 13 (43%) of the

respondents had landholding size between 1.5 hac to 2.5 hac used for growing trees and

only 8 (27%) of the respondents were landholding size below 1.5 hac for growing trees

on their lands (Table-4.6).

85

Table- 4.6. Basic information of woodlot tree grower of District Malakand.

Respondent

ID

Age Education Occupation Plot species Farmer

category

Homestead

land (hac)

Agriculture

land (hac)

Land with

trees (hac)

Total

land

(hac)

1 37 SSC Business Eucalyptus Large 0.2 0.57 0.33 1.1

2 40 SSC Agriculture Eucalyptus Large 0.27 0.78 0.45 1.5

3 45 HSSC Business Eucalyptus Large 0.52 1.51 0.87 2.9

4 51 SSC Business Eucalyptus Medium 0.1 0.29 0.17 0.56

5 70 SSC Business Eucalyptus Small 0.08 0.24 0.14 0.46

6 62 FIVE Agriculture Eucalyptus Medium 0.1 0.28 0.16 0.53

7 47 SSC Agriculture Eucalyptus Medium 0.12 0.33 0.19 0.64

8 38 BA UC Member Robinia Large 0.5 1.46 0.84 2.8


10 46 NIL Agriculture Eucalyptus Large 0.3 0.86 0.5 1.66

11 42 FIVE Agriculture Eucalyptus Small 0.07 0.19 0.11 0.37


13 67 NIL Agriculture Eucalyptus Small 0.07 0.2 0.11 0.38

14 56 SSC Business Eucalyptus Medium 0.12 0.33 0.19 0.64


16 60 FIVE Agriculture Robinia Small 0.08 0.24 0.14 0.47

17 44 MA Teacher Eucalyptus Large 0.34 0.99 0.57 1.9

18 48 BA Business Eucalyptus Medium 0.14 0.41 0.23 0.78



21 50 FIVE Agriculture Eucalyptus Large 0.16 0.46 0.26 0.88


86

23 49 FIVE Agriculture Eucalyptus Small 0.07 0.2 0.12 0.39

24 58 FIVE Agriculture Robinia small 0.08 0.22 0.13 0.42

25 67 SSC Agriculture Eucalyptus small 0.08 0.23 0.13 0.44

26 32 HSSC UC Member Robinia Medium 0.12 0.35 0.2 0.67



29 75 NIL Agriculture Eucalyptus Small 0.08 0.24 0.14 0.46


87

4.3.2 CHARACTERISTICS AND FACTORS OF WOODLOT PLANTATION

OF EXOTIC TREE SPECIES

In the research areas, woodlot plantations of the fast growing exotic tree species

of Eucalyptus camaldulensis and Robinia pseudoacacia were carried out. Among these

Eucalyptus camaldulensis occupied the major portion. A sufficient number of woodlots

of exotic species of different ages were found in the private land of the study areas,

among them 30 similar kinds of woodlot plots were selected based on the objectives of

the present research. Questionnaire survey revealed that, among the 30 woodlot tree

growers (respondents), 80% and 20% tree growers collected seedlings from the local

nurseries and local market respectively.

The tree growers planted seedlings that were 1-year-old and on average 0.79 m

in height. The spacing in plantations was different among different woodlot plantations.

The average number of saplings/seedlings planted initially per hectare was recorded as

2226 with a maximum of 5850 and minimum 740 and these variations in number of

seedlings were mainly due to the spacing reported by the respondents.

The average age of the privately owned woodlot of exotic trees was 4 years, and

on average, one hectare of woodlot plots was comprised 2226 trees, of which the

average tree height and DBH were 6.6 m and 10.3 cm respectively (Table 4.7).

When the respondents were asked about the previous land use pattern, most of

the respondents i.e. 16 (53%) of the respondents had previously used the land for

agricultural purposes, 4 (14%) of the respondents raised trees on barren land, while 10

(33%) raised trees on land previously occupied by scrub forest of Acacia modesta and

Dodonea viscosa.

88

Table-4.7. Characteristics of different woodlot plantation raised by the tree growers in District Malaakand.

Respondent

ID

Plot species Avg.

height of

seedlings

(m)

Avg. age

of

seedlings

Plantation

year

Age

of

trees

(yrs)

Trees/hac

while

survey

Avg.

height

(m) of

trees

Avg. DBH

(cm) of

trees

Tree

growth

pattern

Previous land

use

1 Eucalyptus 0.59 1 2014 4 3596 7.68 10.2 Fast Agriculture







8 Robinia 1.52 1 2014 4 3413 5.19 8.81 Medium Agriculture



11 Eucalyptus 0.63 1 2015 3 640 5.15 8.01 Fast Barren land







18 Eucalyptus 0.63 1 2015 3 893 5.15 8.8 Fast Scrub forest




89










90

4.3.3 EXPENDITURE FOR WOODLOT PLANTATION OF EXOTIC TREE

SPECIES

Woodlot plantation and maintenance is a labour intensive work. Information

collected from the tree growers showed that, out of total average expenditure, 6.1% was

used for seedlings purchase. 61.9% of the average expenditure per hac was used for the

labour and watch and wards. Thus 68% of the total average cost on raising one-hectare

plantation was used for the purchase of seedlings and labour and watcher collectively.

While the rest of the cost incurred on stacking, transport, fencing, thinning and pruning.

About 3% of the cost were used for the transportation of seedlings from the nursery to

the plantation sites While for stacking fencing, thinning and pruning 4%, 6%, 6% and

4% were used. 9% of the cost was used for the purpose of watering.

Expenditure of tree grower for raising one hectare of private woodlot plantations

in District Malakand was summarised in Table 4.8.

91

Table-4.8. Expenditure of tree growers for raising one-hectare woodlot plantations in District Malakand.

Respondent

ID

Purchase of

seedlings (Rs.)

Transport

(Rs.)

Labor/watcher

(Rs.)

Fencing

(Rs.)

Stacking

(Rs.)

Watering

(Rs.)

Thinning

(Rs.)

Pruning

(Rs.)

Total projected

expenditure/cost

up to rotation (Rs.)

1 15780 8403 173379 16806 11204 25209 16806 11204 278789

2 12104 6445 132990 12891 8594 19336 12891 8594 213844

3 23400 12461 257102 24921 16614 37382 24921 16614 413414

4 8128 4328 89304 8656 5771 12984 8656 5771 143599

5 3764 2004 41356 4009 2672 6013 4009 2672 66500

6 7652 4075 84074 8149 5433 12224 8149 5433 135190

7 5112 2722 56167 5444 3630 8166 5444 3630 90315

8 25305 8134 167826 16268 10845 24401 16268 10845 279891

9 8128 4328 89304 8656 5771 12984 8656 5771 143599

10 13448 7161 147757 14322 9548 21483 14322 9548 237589

11 2960 1576 32522 3152 2102 4729 3152 2102 52295

12 10996 5855 120816 11711 7807 17566 11711 7807 194269

13 2960 1576 32522 3152 2102 4729 3152 2102 52295

14 5112 2722 56167 5444 3630 8166 5444 3630 90315

15 10040 5346 110312 10693 7128 16039 10693 7128 177379

16 6587 2117 43686 4235 2823 6352 4235 2823 72857

17 15332 8164 168457 16329 10886 24493 16329 10886 270874

18 3960 2109 43510 4217 2812 6326 4217 2812 69962

19 17212 9165 189113 18331 12221 27496 18331 12221 304089

20 15780 8403 173379 16806 11204 25209 16806 11204 278789

21 12432 6620 136593 13240 8827 19860 13240 8827 219639

22 8946 2876 59331 5751 3834 8627 5751 3834 98949

23 5736 3054 63023 6109 4073 9163 6109 4073 101339

24 6118 1967 40575 3933 2622 5900 3933 2622 67669

92

25 6216 3310 68297 6620 4413 9930 6620 4413 109820

26 9415 3026 62442 6053 4035 9079 6053 4035 104137

27 7172 3819 78801 7638 5092 11457 7638 5092 126710

28 7652 4075 84074 8149 5433 12224 8149 5433 135190

29 6696 3566 73571 7131 4754 10697 7131 4754 118300

30 7172 3819 78801 7638 5092 11457 7638 5092 126710

Average 9711 4774 98508 9548 6366 14323 9548 6366 159144

Percent 6.1% 3% 61.9% 6% 4% 9% 6% 4% 100%

93

4.3.4 BENEFIT COST ANALYSIS ON WOODLOTS OF EXOTIC TREE

SPECIES

The results of benefit-cost analysis on the woodlots have been presented in

Table 4.10. The results showed that on average, a tree grower spent Rs. 159144 for

woodlot plantation in one hectare of land (Table 4.8). On the other hand, they were

expecting to sale the timber/wood for Rs. 2049478 and to get the, expected net profit

of Rs.1956206 over a ten-year rotation period (Table 4.10).

Net Present Value, Internal Rate of Return and Benefit Cost Ratio

Net present value (NPV), internal rate of return (IRR) and benefit cost ratio

(BCR) heve been used to evaluate the financial feasibility of the plantation project. All

costs incurred and revenues gained from the project are discounted to present value for

both NPV and IRR. Hence, a discounted rate (base) of 10% has been used as the

proximity rate of capital loan in Pakistan. Benefit cost analysis for one hectare (average

made from 30 woodlots) private woodlot plantations showed that, the BCR was 1.25

on a ten-year rotation period and the NPV was 165982, whereas the IRR was 14.33%

(Appendix 16 & 17). From a NPV point of view, the net present return from this

woodlot is Rs. 165982 per ha, which is financially a viable option for investment into

woodlot forestry. The result showed that the cultivation of exotic tree species may

provide a regular return to grower of trees and proved that the project of woodlot

plantations is financially viable.

Sensitivity Analysis

Sensitivity of BCR and NPV with reference to changes in the interest rate for one-

hectare woodlot monoculture plantation in the study area has been analysed. If there is no

risk of a crop being destroyed, but the changes in interest rate 5%, 7%, 10% (base case

scenario), 12% and 17% showed BCR 1.61, 1.46, 1.25 (base case scenario), 1.13 and 0.87

respectively and NPV 498178, 341692, 165982, 78795 and -67199 (Table 4.9).

Table-4.9. Sensitivity of BCR and NPV with reference to changes in the interest rate

for one-hectare woodlot monoculture plantation in District Malakand.

Interest Rate Benefit Cost Ratio (BCR) Net Present Value (NPV)

5% 1.61 498178

7% 1.46 341692

10% 1.25 165982

12% 1.13 78795

17% 0.87 -67199

94

Table-4.10. Future valuation and expected profit of woodlot trees (per hectare) raised in District Malakand.

Resp.

ID

Tree species

No. of

sapling

planted

initially

Per ha.

Trees/hac

encountered

after 1st

thinning

Expected

no. of

trees

remained

up to 10

years

rotation

(after 2nd

thinning)

Expected

price/tree

upto

rotation

(Rs.)

Projected

benefit

from tree

sale (Rs.)

Avg.

Benefit

from

thinnin

g (Rs.)

Benefit

from

pruning

(Rs.)

Projected

benefit

including

thinning

and

pruning

(Rs.)

Average

expenditure

cost (Rs.)

Average

expected

profit

(Rs.)

1 Eucalyptus 3945 3590 1831 2000 3662000 67450 49252 3778702 278789 3499913

2 Eucalyptus 3026 2754 1405 1950 2739750 51680 37772 2829202 213844 2615358

3 Eucalyptus 5850 5324 2715 1900 5158500 100130 73052 5331682 413414 4918268

4 Eucalyptus 2032 1849 943 2050 1933150 34770 25368 1993288 143599 1849689

5 Eucalyptus 941 856 437 2000 874000 16150 11732 901882 66500 835382

6 Eucalyptus 1913 1741 888 1950 1731600 32680 23884 1788164 135190 1652974

7 Eucalyptus 1278 1163 593 1950 1156350 21850 15960 1194160 90315 1103845

8 Robinia 3615 3290 1678 1800 3020400 61750 45136 3127286 279891 2847395

9 Eucalyptus 2032 1849 943 1900 1791700 34770 25368 1851838 143599 1708239

10 Eucalyptus 3362 3059 1560 2000 3120000 57570 41972 3219542 237589 2981953

11 Eucalyptus 740 673 343 2100 720300 12730 9240 742270 52295 689975

12 Eucalyptus 2749 2502 1276 2200 2807200 46930 34328 2888458 194269 2694189

13 Eucalyptus 740 673 343 2000 686000 12730 9240 707970 52295 655675

14 Eucalyptus 1278 1163 593 2050 1215650 21850 15960 1253460 90315 1163145

15 Eucalyptus 2510 2284 1165 2000 2330000 42940 31332 2404272 177379 2226893

16 Robinia 941 856 437 1850 808450 16150 11732 836332 72857 763475

17 Eucalyptus 3833 3488 1779 2100 3735900 65550 47852 3849302 270874 3578428

18 Eucalyptus 990 901 460 2000 920000 16910 12348 949258 69962 879296

95

19 Eucalyptus 4303 3916 1997 2050 4093850 73530 53732 4221112 304089 3917023

20 Eucalyptus 3945 3590 1831 2000 3662000 67450 49252 3778702 278789 3499913

21 Eucalyptus 3108 2828 1442 1950 2811900 53200 38808 2903908 219639 2684269

22 Robinia 1278 1163 593 1800 1067400 21850 15960 1105210 98949 1006261

23 Eucalyptus 1434 1305 666 2000 1332000 24510 17892 1374402 101339 1273063

24 Robinia 874 795 405 1850 749250 15010 10920 775180 67669 707511

25 Eucalyptus 1554 1414 721 2200 1586200 26600 19404 1632204 109820 1522384

26 Robinia 1345 1224 624 1850 1154400 22990 16800 1194190 104137 1090053

27 Eucalyptus 1793 1632 832 1950 1622400 30590 22400 1675390 126710 1548680

28 Eucalyptus 1913 1741 888 2000 1776000 32680 23884 1832564 135190 1697374

29 Eucalyptus 1674 1523 777 2000 1554000 28690 20888 1603578 118300 1485278

30 Eucalyptus 1793 1632 832 2000 1664000 30590 22400 1716990 126710 1590280

2226 2026 1033 1982 2049478 38076 27796 2115350 159144 1956206

96

Plantation Damaging Factors

In questionnaire survey, 75% woodlot tree growers expressed the view that

woodlot plantations were damaged by cattle grazing/trampling. While 10% of the

plantations were damaged due to fuelwood collection/debranching and conflict with

neighbours each and only 5% damage occurred due to human interference (Figure

4.23).

Fig. 4.23. Tree growers’ perception (in percentage) on plantation damaging factors.

Purpose of growing Exotic species

When the respondents were asked whether they are growing trees for domestic

consumption or for sale, 80% of the respondents answered that they are growing trees

for sale while 20% of the respondents were growing trees for domestic consumption.

For both the respondents who are growing trees for domestic consumption or

sale, trees have an impact on socio-economic conditions. The farmers growing trees are

getting additional amounts of money and farmers growing trees for domestic

consumptions are saving extra expenses which would have been spent in buying

fuelwood.

01020304050607080

Per

cen

tage%

Damaging Factors

97

4.3.5 SOURCES OF ENERGY FOR FULFILLING DOMESTIC/

COMMERCIAL NEEDS OF PEOPLE

The following sources of energy were used for fulfilling the domestic/commercial

needs of people in the study area.

From the survey data it was found that 75% of people in the area were using

fuel wood other than the wood of Eucalyptus followed by gas 20% and animal dung

3% (Fig.4.24). The species mostly used for fuel wood purposes are mulberry, sanatha,

Poplar, kekar. Out of these species Dodonea viscosa is mostly collected by the local

people for fuelwood, only 2% villagers were using Eucalyptus as fuelwood. The trees

of Eucalyptus which were cultivated under a social forestry project by villagers on

privately owned lands are not allowed for rural people to collect fuelwood for fulfilling

domestic needs.

It is clear from the data that most of the people of the area still are dependent

upon the indigenous species for fuelwood other than Eucalyptus and they have easy

access to go and collect fuelwood from the mountains. This has put the forest under

enormous pressure and deforestation of the indigenous species of the area.

Fig. 4.24. Sources of energy used for fulfilling domestic/commercial needs of the People.

75%

20%

3%2%

Fuel Wood other than

Eucalyptus

Gas

Animal Dung

Eucalyptus as Fuel Wood

98

4.3.6 SPECIES USED FOR FUELWOOD, RATES/MOUND AND SALE IN

THE MARKET

Table-4.11: Rate per mound of different species and their sale in the local market

S.no Species Average Rates/mound (dry wood) Sale/month (mound)

1 Mulberry Rs. 450 2500

2 Bakian Rs. 450 1900

3 Poplar Rs. 450 3000

4 Ailanthus Rs. 450 2000

5 Eucalyptus Rs. 450 1800

6 Peach Rs. 450 1700

7 Apricot Rs. 450 1600

It has been found that the rates per mound of different species in the local markets

of the area were almost the same i.e. Rs. 450 (Table-4.11). Data analysis shows that

people of the area mostly prefer to use the species of Mulberry, Poplar, Ailanthus,

Bakain and according to the business persons most of the people do not like to buy

Eucalyptus as fuel wood from the market.

4.3.7. RELATIVE MERITS AND DEMERITS OF SELECTED EXOTIC AND

INDIGENOUS TREE SPECIES

Exotics Indigenous

They are relatively fast growing than the

indigenous species.

Relatively slow growing but valuable

trees for afforestation/reforestation.

It competes with understorey crops for

nutrients and water.

Less competition with understorey crops

for nutrients and water.

It sometime affect the indigenous

biodiversity of the area where it is

planted.

It support the indigenous biodiversity.

Its monoculture may affect natural

ecosystem of the area.

It maintains the ecosystem of an area in

natural conditions.

Due to fast growing nature of such plants

nutrients recycling is affected negatively

The decomposton rate of the litter and

organic matter in the soil of indigenous

99

due to slow rate of decomposition of the

litterfall and organic matter.

species is rapid due to which it helps in

the nutrients recycling.

It can be easily attacked by termites in

young stage e.g. Eucalyptus while it is

attacked by termites in mature stage e. g

R. pseudoacacia.

They are mostly diseased free and less

insect problems have been identified.

It coppices well e.g. Eucalyptus while it

is also produced from seeds and

vegetatively e.g. R. pseudoacacia.

Natural regenerations occurs rapidly on

barren soil.

It generates early income. Income generation is low and steady.

Eucalyptus is used for carriages, fuel,

charcoal,oil, shelter belts, apiculture,

pulp, fibre board while R .pseudoacacia

uses includes fodder, fuel, charcoal,

erosion control, fencing, apiculture.

Acacia modesta is used for fodder, fuel,

agriculture implements, hedge,

apiculture and gum. Whereas Pinus

roxburghii can be used for consruction,

fuel, resin, erosion control, sleeper, food

(edible seed), various wood product,

furniture, match sticks, Tar and Tannin

4.4. IMPACT OF EXOTIC PLANTATIONS ON GROUND WATER

Table-4.12: Depth of water table before and after exotic plantation

Union Council Depth before

plantations (m)

Depth after

plantations

(m)

Water table

lowered (m)

Rate of

water table

falling/year

(m)

Thana Khas 73 85 12 0.8

Thana Jadeed 78 91 13 0.86

Thana Bandajat 75 85 10 0.66

Alladand Dherai 68 79 11 0.73

It has been found that exotic planations have negatively affected ground water

and water table has lowered at an average of 0.76 m per year in the research area. The

water table in Thana Khas before plantation of Eucalyptus was 73 m. The depth of water

table is now 85 m which shows that it has increased by up to 0.8 m. In Thana Jadeed

100

the depth of the water table before plantation was 78 m but now the depth has reached

91 m which has resulted in a lowering of the water table by up to 0.86 m. Similarly, in

Thana Bandajat the depth of water table before plantation was 75 m, now the water

table in the area has reached 85 m resulting in a lowering of the water table at an average

of 0.66 m per year. While the depth of water table before plantation in Alladand Dheri

was 68 m and now the depth has reached to 79 m which showed that the water table has

lowered at an average of 0.73 m per year (Table 4.12).

4.4.1. IMPACT OF EXOTIC PLANTATIONS ON SPRINGS

Excessive monoculture of exotic plantations has affected the indigenous water

resources (Almeida et al., 2007). Afforestations with exotic plants could negatively

affect the water resouces of an area by decreasing water yield (Lane et al., 2003 &

2005). The results of the study carried out by Suarez et al. (2011) in exotic plantations

of Eucalyptus in the meadow pasture land showed that annual maximum water table

depth was increased on an average by 2-2.5 mm daily while the discharge rate of flow

was reduced from the catchment.

Table-4.13: Number of springs before and after exotic plantations

Union council No. of

springs

before

exotic

plantations

No. of springs

after exotic

plantations

No. of

springs dried

No. of

springs

became

seasonal

Thana Jadeed 12 5 5 2

Thana Khas 10 3 5 2

Thana Bandajat 29 18 7 4

Alladand Dheri 30 5 20 5

Total 81 31 37 13

The data from the Table 4.13 shows that the total number of springs in the study

area was 81 before plantation of exotic plant species. The number of springs in the study

area has now decreased to 31 which constitute 38% of the total springs. The number of

dried springs are 37, constituting of 46% of the total number of springs. While 13

101

springs became seasonal which makes 16% of the total reported springs from the

research area.

In Thana jadeed the total number of springs before plantation were 12, out of

which 5 springs were dried and two springs have become seasonal. In Thana Khas 10

springs existed before plantations in the area now there are only 3 springs remaining

while five springs dried and two springs became seasonal. Similarly, in Thana Bandajat,

Alladand Dherai the total number of springs before plantations were 29 and 30

respectively. The number of dried springs in these villages are 18 and 5 respectively

while four springs become seasonal in Thana Bandajat and five in Alladand Dheri.

4.4.2. IMPACT OF EXOTIC PLANTATIONS ON DISCHARGE RATE OF

SPRINGS

The root systems developed in exotic species of Eucalyptus are of two types

namely shallow rooted system and tap rooted system. In shallow roots system the roots

spreads just below the ground surface from three to five meters which spreads

horizontally and they absorb water from the soil surface. On the other hand, in the tap

rooted system roots grow down deeply in to the soil layers and absorb water from it. It

generally reaches down to 9 meters deep and absorb water from aquifers. This tap roots

system helps Eucalyptus to grow and develop in areas having shortage of water even in

dry conditions (Fritzsche et al., 2006). Due to this root system exotic Eucalyptus

camaldulensis plantations have badly affected discharge rate of natural springs in the

study area.

Table 4.14: Discharge rate of springs before and after exotic plantations

Union

Council

Spring Discharge rate

before plantations

(Litre/sec)

Discharge rate after

plantations

(Litre/sec)

Flow

reduced

(Litre/sec)

Thana

Jadeed

Spring 1 6 2 4

Spring 2 3 0.5 2.5

Spring 3 4 1 3

Thana

Khas

Spring 1 5 1 4

Spring 2 4 2 2

Spring 3 2 0 2

Thana

Bandajat

Spring 1 5 2 3

Spring 2 4 0.5 3.5

Spring 3 2 0 2

Alladand

Dherai

Spring 1 4 1 3

Spring 2 5 1.5 3.5

Spring 3 2 0 2

102

Three springs from each union council were selected randomly and

measurement of their discharge rates was carried out. The result in the table show that

in Thana jadeed the discharge rate of the first spring has decreased from 6 litres/sec to

2 litres/sec. The discharge rate of the second spring has decreased from 3 litres/sec to

0.5 litres/sec and the discharge rate of the third spring were decreased from four

litres/sec to one litre/sec (Table-4.14). In Thana Khas reduction occurred in the

discharge rate of spring 1 from 4 to 2 litres/sec and the discharge rate of the 3rd spring

has reduced to zero i.e. the spring is completely dry now. The discharge rate of spring

1 in Thana Bandajat has decreased from 5 to 2 litres/sec which recorded 3 litres/sec

decrease in flow of water and the discharge rate of the 2nd spring has reduced from 4 to

0.5 litre/sec, while the third spring is completely dry now. The discharge rate of the 1st

spring has decreased from 4 to 1 litre/sec. Similarly, the discharge rate of the 2nd spring

has decreased from 5 to 1.5 litres/sec and the 3rd spring is completely dry now in

Alladand Dheri.

103

CHAPTER-5

CONCLUSIONS AND RECOMMENDATIONS

5.1 CONCLUSIONS

The results of this comparative study gives an insight into the ecological and

socio-economic impacts of monoculture of exotic tree species with following

conclusions:

1) The indigenous tree plots harbor higher number of plant species as compared to

exotic tree plots. The undergrowth plant density and Shannon-Wiener diversity

indices were greater in indigenous tree plots than exotic tree plots, which showed

that the plantations of indigenous species favor the establishment of understorey

vegetation.

2) Result of the present study concluded that, the monoculture of exotic trees

significantly affects the soil OM, OC, pH, N, P, K and calcium carbonate in the

study area, but the soil EC was non significantly different. The indigenous species

maintained soil fertility and support diversity of plants and help in conservation of

important understorey plants.

3) Result of present research studies showed that plantations of exotic tree species

absorb more ground water than indigenous tree species, causing lowering of water

and drying of natural springs in the research area.

4) Raising of woodlots of exotic fast growing tree species has short term economic

impacts on the local economy and socio-economic development. But fails to ensure

the sustainability of biodiversity and healthy ecosystem, and therefore, be

discouraged for massive afforestation programs.

5.2 RECOMMENDATIONS

1) Afforestation of indigenous species should be given priority in large scale

afforestation projects or programs based on ecological and socio-economic needs

and government ploicies and strategies should be formulated to safeguards the

sustainability of natural ecosystem.

104

2) For maintaining soil fertility and providing natural habitat conditions to the

understorey plants, the monoculture of exotic species should be avoided and

plantations of indigenous species must be promoted.

3) Indigenous species is recommended for water conservation and maintaining water

table at natural level.

4) Indigenous fast growing species should be identified and adopted for such

plantations to support the economy, livelihood, sustainability of ecosystem and

conservation of biodiversity.

105

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Appendix 1. Checklist of undergrowth plant species recorded from research plots at Malakand.

Sr.no Scientific name Family Name Common/

Local Name

Habit Group Life

span

Exotic

plot

Indigenous

plot

1 Acacia modesta Wall. Mimosaceae Palusa Tree D P

2 Acacia nilotica (L.) Willd. ex Del. Mimosaceae Kekar Tree D P

3 Achyranthes aspera L. Amaranthaceae Spey botey Herb D P

4 Adiantum caudatum D.Don. Adiantaceae Sumbal Fern Pt P

5 Aerva javanica (Burm.f.) Juss. Ex Schult. Amaranthaceae Kharbotey Herb D P

6 Aerva sanguinolenta (L.) Blume. Amaranthaceae Kharbotey Herb D P

7 Ailanthus altissima (Mill.) Swingle. Simaroubaceae Angrezi shandai Tree D P

8 Ajuga bracteosa Wall ex. Benth. Lamiaceae Guti Herb D P

9 Ajuga parviflora Benth. Lamiaceae Boti Herb D P

10 Albizia lebbeck (L.) Benth. Mimosaaceae Sreekh Tree D P

11 Alternanthera pungens Kunth. Amaranthaceae Ghana Herb D P

12 Allium griffithianum Boiss., Diagn. Alliaceae Piazakai Herb M P

13 Amaranthus spinosus L. Amaranthaceae Ghano chalwae Herb D A

14 Amaranthus viridis L. Amaranthaceae Ganhar Herb D A

15 Ammi visnaga (L.) Lam Apiaceae Sperke Herb D A

16 Anisomeles indica (L.) Lamiaceae Skha botai Herb D P

17 Apluda mutica L. Poaceae Wakha Grass M P

18 Aristida cyanantha Nees ex Steud. Poaceae Mashkeeza Grass M P

19 Artemisia scoparia Waldest. Asteraceae Jokey Herb D P

20 Asparagus adscendens Roxb. Liliaceae Tendoney Shrub M P

21 Avena fatua L. Poaceae Jamdar Grass M A

22 Barleria cristata L. Acanthaceae Shrub D P

23 Bauhinia variegata L. Ceasalpinaceae Kulyar Tree D P

24 Berberis lycium Royle. Berberidaceae Ziarlarge,

Kwarey

Shrub D P

25 Bidens pilosa L. Asteraceae Herb D A

121

26 Boerhavia procumbens Banks ex Roxb. Nyctaginaceae Ensut Herb D P

27 Brachiaria ramosa (L.) Stapf. Poaceae Shamokha Grass M A

28 Broussonetia papyrifera (L.) L’Herit. ex Vent. Moraceae Gul toot Tree D P

29 Buddleja crispa Benth., Scroph. Buddlejaceae Spera botay Shrub D P

30 Calistemin lanceolatus (Sm.) Sweet. Myrtaceae Bottle brush Tree D P

31 Commelina paludosa Blume, Enum. Commelinaceae Shingulay Herb D A

32 Cannabis sativa L. Cannabaceae Bhang Herb D B

33 Caralluma tuberculata N.E. Brown, Gardn. Chron. Asclepiadaceae Pamankey Herb D P

34 Carthamus lanatus L. Asteraceae Kareza Herb D A

35 Carthamus oxycantha Bieb. Asteraceae Kareza Herb D A

36 Cassia occidentalis L. Caesalpiniaceae Shrub D A

37 Celtis caucasica Willd. Ulmaceae Tagha Tree D P

38 Cenchrus ciliaris L. Poaceae Barwaz, Wakha Grass M P

39 Cheilanthes pteroides Sw. Pteridaceae Sumbal Fern Pt

40 Chenopodium album L. Chenopodiacea Sarmey Herb D A

41 Chenopodium ambrosioides L. Chenopodiacea Saarme Herb D A

42 Chenopodium botrys L. Chenopodiaceae Kharwa Herb D P

43 Chrysopogon aucheri (Boiss.) Stapf. Poaceae Spin wakhe Grass M P

44 Chrysopogon serrulatus Trin. Poaceae Spin wakhey Grass M P

45 Cissampelos pareira L. Menispermaceae Prewatai Climber D P

46 Cleome viscosa L. Capparidaceae Tick weed Herb D A

47 Colebrookea oppositifolia Smith, Exot. Lamiaceae Bhirmoli, Shrub D P

48 Convolvulus arvense L. Convolulaceae Prewatkey Climber D A

49 Conyza canadensis (L.) Cronquist. Asteraceae Dhnya botey Herb D A

50 Conyza stricta Willd. Asteraceae Erect

Horseweed

Herb D A

51 Coronopus didymus (L.) Smith. Brassicaceae Shka botay Herb D A

52 Cucumis melo subsp. agrestis var. agrestis Naudin. Cucurbitaceae Khro hindwana Herb D A

53 Cymbopogon jwarancusa (Jones) Schult. Poaceae Sargare Grass M P

122

54 Cynodon dactylon (L.) Pers. Poaceae Kabal Grass M P

55 Cynoglossum lanceolatum Forssk. Boraginaceae Geshay Herb D P

56 Cyperus rotundus L. Cyperaceae Dela Sedge M P

57 Dalbergia sissoo Roxb. ex DC. Fabaceae Shawa Tree D P

58 Daphne oleoides Schreb. Thymeleaceae Leghoney Shrub D P

59 Datura innoxia Miller. Solanaceae Bathora Shrub D P

60 Debregeasia saeneb (Forsskal) Hepper and Wood. Utricaceae Ajlae Tree D P

61 Desmodium elegans DC. Papilionaceae Tick clover Shrub D P

62 Desmostachya bipinnata L. Poaceae Drab Grass M P

63 Dichanthium annulatum (Forsk.) Stapf. Poaceae Gaya, Wakha Grass M P

64 Dodonaea viscosa (L.) Jacq. Sapindaceae Ghwaraskey Shrub D P

65 Dryopteris crenata (Forssk.) Kuntze. Dryopteridaceae Sumbal Herb Pt P

66 Dryopteris jaxtaposta Christ. Dryopteridaceae Sumbal Herb Pt P

67 Duchesnea indica (Andr.) Focke. Rosaceae Zmakey toot Herb D P

68 Ehretia obtusifolia Hoches. Boraginaceae Ghatabotai Shrub D P

69 Euphorbia granulata Forssk. Euphorbiaceae Warmaga Herb D A

70 Euphorbia hirta L. Euphorbiaceae Paybotai Herb D A

71 Euphorbia indica Lam., Euphorbiaceae Warmaga Herb D A

72 Erioscirpus comosus (Wall.) Palla. Cyperaceae Nembarwaza Rhizome M P

73 Eryngium biebersteinianum Nervski ex Bobrov. Asteraceae Manzari Panja Shrub D P

74 Eucalyptus camaldulensis L. Myrtaceae Lachi Tree D P

75 Ficus palmata Forssk., Fl. Moraceae Inzar Tree D P

76 Ficus racemosa L. Moraceae Oormal Tree D P

77 Fumaria indica Pugsley. Fumariaceae Papra Herb D A

78 Geranium rotundifolium D.Don ex Sweet. Geraniaceae Sra zeal Herb D P

79 Grewia optiva J. R. Drumm. ex Burret. Tiliaceae Pastawooney Tree D P

80 Heliotropium strigosum Willd. Boraginaceae Storay botay Herb D A

81 Herniaria hirsuta L. Illecebraceae Rupturewort Herb D A

82 Heteropogon contortus (L.) Beauv. ex

Roemer and JA Schultes.

Cyperaceae Soormal Sedge M P

83 Hyoscyamus niger L. Solanaceae Bargak Herb D P

123

84 Imperata cylindrica (L.) Beauv. Poaceae Pesholakey Grass M P

85 Iindigofera heterantha L. Papilionaceae Ghwareja Shrub D P

86 Isodon rugosus Wall. ex Benth Lamiaceae Sperkey Shrub D P

87 Justicia adhatoda L. Acanthaceae Baikar Shrub D P

88 Kickxia ramosissima (Wall.) Janch. Plantaginaceae Fluelins Herb D P

89 Lamarckia aurea (L.) Moench. Poaceae Brush wakha Grass M A

90 Lathyrus cicera L. Papilionaceae Marghae Khpa Climber D A

91 Launaea procumbens (Roxburgh.) Ramayya. Asteraceae Shawda pae Herb D P

92 Lotus corniculatus L. Fabaceae Fathkhaney Herb D P

93 Mallotus philippensis (Lam.) Moll. Arg. Euphorbiaceae Kanbela Tree D P

94 Malva neglecta Wall. Malvaceae Panerak Herb D A

95 Martynia annua L. Martyniaceae Herb D A

96 Maytenus royaleanus (Wall. ex Lawson) Cufodontis

in Senck.

Celastraceae Soor azghay Shrub D P

97 Medicago minima (L.) Grub. Papilionaceae Peshtarey Herb D A

98 Melia azedarach L. Meliaceae Tora Shandae Tree D P

99 Melothria heterophylla (Lour.) Cogn. Cucurbitaceae Kakora Climber D P

100 Mentha longifolia (L.) Huds. Lamiaceae Enaley Herb D P

101 Micromeria biflora (Buch. Ham. ex D.Don) Benth. Lamiaceae Narey

Shamakey

Herb D P

102 Mimosa himalayana Gamble in Kew Bull. Mimosaceae Ghanawar kekar Tree D P

103 Monotheca buxifolia (Falc.) A.DC. Sapotaceae Gwargwara Tree D P

104 Morus alba L. Moraceae Spin Toot Tree D P

105 Morus nigra L. Moraceae Toor Toot Tree D P

106 Myrsine africana L. Myrsinaceae Manro Shrub D P

107 Nannorrhops ritchiana - (Griff.) Aitch. Arecaceae Mezarey Shrub M P

124

108 Nepeta griffithii Hedge. Lamiaceae Herb D A

109 Nerium odorum Soland. Apocynaceae Ganderey Shrub D P

110 Olea ferruginea Royle. Oleaceae Khona Tree D P

111 Onosma hispida Wall. ex G. Don. Boraginaceae Ratanjot Herb D P

112 Opuntia dilleni Haw. Cactaceae Kamala Herb D P

113 Opuntia monacantha (Willd.) Haw. Cactaceae Zuqam Shrub D P

114 Origanum vulgare L. Lamiaceae Shamakey Herb D P

115 Otostegia limbata (Bth.) Boiss. Lamiaceae Spin Azghey Shrub D P

116 Oxalis corniculata L. Oxalidaceae Taruke Herb D A

117 Papaver pavoninum Schrenk, Enum. Papaveraceae Redeygulay Herb D A

118 Parthenium hysterophorus L. Asteraceae Tarkha Herb D P

119 Peganum harmala L. Rutaceae Spelaney Herb D A

120 Pentanema vestitum (Wallich. ex Candolle.) Asteraceae Herb D A

121 Pennisetum flaccidum Grise. Poaceae Grass M P

122 Periploca aphylla Dcne. Apocynaceae Barara Shrub D P

123 Phyllanthus niruri Hook. f., Fl. Brit. Euphorbiaceae Shrub D P

124 Physalis divaricata D. Don, Prodr. Solanaceae Tamatar botay Herb D A

125 Pinus roxburghii Sarg. Pinaceae Nakhtar Tree GM P

126 Piptatherum aequiglume (Duthie ex Hook.f.) Poaceae Wakha Grass M P

127 Pistacia chinensis Bunge. Anacardaceae Shnae Tree D P

128 Plantago lanceolata L. Plantaginaceae Jabai Herb D A

129 Plantago major L. Plantaginaceae Speghol Herb D A

130 Poa annua L. Poaceae Wakha Grass M A

131 Polygala erioptera DC. Polygalaceae Herb D P

132 Polygonum barbatum L. Polygonaceae Palpolak Herb D A

133 Portulaca olearaceae L. Portulaceae Warkharey Herb D A

134 Punica granatum L. Punicaceae Anangonrey Shrub D P

135 Pupalia lappacea (L.) Juss. Amaranthaceae Gheshay Herb D P

136 Quercus incana Roxb. Fagaceae Banj Tree D P

137 Rhazya stricta Decne. Apocyanaceae Ghandairi Shrub D P

125

138 Rhynchosia minima (L.) DC. Fabaceae Herb D P

139 Ricinus communis L. Polygonaceae Arhanda Shrub D P

140 Robinia pseudocacia L. Papilionaceae Kekar Tree D P

141 Rubus fruticosus L. Rosaceae Karwara Herb D P

142 Rumex hastatus D. Don. Polygonaceae Tarokey Herb D A

143 Saccharum filifolium Nees ex Steud. Poaceae Kahe Grass M P

144 Saccharum griffthii Munro. Ex Boiss. Poaceae Bogara Grass M P

145 Sageretia thea (Osbeck) M.C. Johnston. Rhamnaceae Mamanra Shrub D P

146 Salix babylonica L. Salicaceae Wala Tree D P

147 Salvia lanata Roxb. Lamiaceae Kayan Herb D P

148 Salvia moorcroftiana Wall. Lamiaceae Khardag Herb D P

149 Salvia plebia R.Br. Lamiaceae Gwamrey Herb D A

150 Setaria pumila (Poir.) Roem. & Schult. Poaceae Wakha Grass M A

151 Sida cordata (Burm.f.) Borss. Malvaceae Herb D P

152 Solanum nigram L. Solanaceae Karmacho A

153 Solanum surattense Burm.f. Solanaceae Maraghoney Herb D P

154 Sonchus asper L. Asteraceae Shawdapae Herb D P

155 Stipagrostis hirtigluma (Steud. ex Trin. & Rupr.) Poaceae Wakha Grass M A

156 Symphyotrichum graminifolium (Spreng.) G.L.

Nesom.

Compositae Herb D A

157 Taraxacum officinale L. Asteraceae Ziar Gulai Herb D A

158 Tecomella undulata (Roxb.) Seeman. Bignoniaceae Tree D P

159 Teucrium stocksianum Boiss. Lamiaceae Aspabotey Herb D P

160 Tithonia sp. Asteraceae Zangali nwar

parast

Herb D A

161 Tribulus terestris L. Zygophylaceae Markundae Herb D A

162 Trichodesma indicum (L.) R.Br. Boraginaceae Ghwa jabai Herb D A

163 Urtica dioica L. Urticaceae Sezonkey Herb D P

164 Vicia sativa L. Papillionaceae M a r g h a i k h

p a

Climber D A

165 Vitex negundo L. Verbinaceae vermondey Shrub D P

126

166 Verbascum thapsus L. Scrophulariaceae Kharghwag Herb D A

167 Vitis jacquemontii R.Parker. Vitaceae Gedar kwar Climber D P

168 Withania coagulans (Stocks) Dunal. Solanaceae Spera botey Shrub D P

169 Woodfordia fruiticosa (L.) S. Kurz in Journ. Lythraceae Datkay Shrub D P

170 Xanthium sibiricum Patrin ex Widder. Asteraceae Geshay Herb D A

171 Xanthium strumarium L. Asteraceae Geshey Herb D A

172 Ziziphus mauritiana Lamk. Rhamnaceae

Bera

Tree D P

173 Ziziphus nummularia (Burm.f) Wight and Arn. Rhamnaceae

Karkana Shrub D P

174 Zizipus oxyphyla Edgrew. Rhamnaceae Elanae Tree D P

127

Appendix-2. Total no. of individuals, Density, Relative density, frequency, relative frequency, abundance, relative abundance considering all

undergrowth species in indigenous plots.

S.no. Species name Total no. of

individuals

Quadrat

found

Total

quadrat

Density/

Hac

Relative

Density

(%)

Frequency

(%)

Relative

Frequency

(%)

Abundance Relative

Abundance

(%)

1 Acacia modesta 1128 246 360 1253.33 8.12 68.33 5.52 4.59 1.05

2 Acacia nilotica 84 66 360 93.33 0.6 18.33 1.48 1.27 0.29

3 Achyranthes aspera 84 24 360 93.33 0.6 6.67 0.54 3.5 0.8

4 Adiantum caudatum 120 18 360 133.33 0.86 5 0.4 6.67 1.52

5 Aerva javanica 156 48 360 173.33 1.12 13.33 1.08 3.25 0.74

6 Aerva sanguinolenta 124 24 360 137.78 0.88 6.67 0.54 5.17 1.18

7 Ailanthus altissima 64 60 360 71.11 0.47 16.67 1.35 1.07 0.24

8 Ajuga bracteosa 148 50 360 164.44 1.06 13.89 1.12 2.96 0.68

9 Ajuga parviflora 40 16 360 44.44 0.29 4.44 0.36 2.5 0.57

10 Albizia lebbeck 12 12 360 13.33 0.08 3.33 0.27 1 0.23

11 Allium griffithianum 120 24 360 133.33 0.86 6.67 0.54 5 1.14

12 Amaranthus spinosus 36 8 360 40 0.26 2.22 0.18 4.5 1.03

13 Amaranthus viridis 66 24 360 73.33 0.47 6.67 0.54 2.75 0.63

14 Ammi visnaga 18 12 360 20 0.13 3.33 0.27 1.5 0.34

15 Anisomeles indica 36 18 360 40 0.26 5 0.4 2 0.46

16 Apluda mutica 102 12 360 113.33 0.73 3.33 0.27 8.5 1.94

17 Aristida cyanantha 312 54 360 346.67 2.26 15 1.21 5.78 1.32

18 Asparagus adscendens 32 12 360 35.56 0.23 3.33 0.27 2.67 0.61

19 Barleria cristata 42 18 360 46.67 0.31 5 0.4 2.33 0.53

20 Bauhinia variegata 58 24 360 64.44 0.41 6.67 0.54 2.42 0.55

21 Berberis lyceum 18 18 360 20 0.13 5 0.4 1 0.23

22 Bidens pilosa 44 16 360 48.89 0.31 4.44 0.36 2.75 0.63

23 Boerhavia procumbens 102 54 360 113.33 0.73 15 1.21 1.89 0.43

24 Brachiaria ramosa 92 20 360 102.22 0.67 5.56 0.45 4.6 1.05

25 Buddleja crispa 30 30 360 33.33 0.21 8.33 0.67 1 0.23

128

26 Cannabis sativa 30 6 360 33.33 0.21 1.67 0.13 5 1.14

27 Caralluma tuberculata 12 12 360 13.33 0.08 3.33 0.27 1 0.23

28 Cassia occidentalis 28 16 360 31.11 0.21 4.44 0.36 1.75 0.4

29 Celtis caucasica 198 144 360 220 1.43 40 3.23 1.38 0.32

30 Cenchrus ciliaris 120 18 360 133.33 0.86 5 0.4 6.67 1.52

31 Cheilanthes pteroides 150 30 360 166.67 1.09 8.33 0.67 5 1.14

32 Chenopodium album 138 44 360 153.33 0.99 12.22 0.99 3.14 0.72

33 C. ambrosioides 50 12 360 55.56 0.36 3.33 0.27 4.17 0.95

34 Chenopodium botrys 60 24 360 66.67 0.44 6.67 0.54 2.5 0.57

35 Chrysopogon aucheri 600 84 360 666.67 4.33 23.33 1.88 7.14 1.63

36 Chrysopogon serrulatus 108 12 360 120 0.78 3.33 0.27 9 2.06

37 Cissampelos pareira 12 12 360 13.33 0.08 3.33 0.27 1 0.23

38 Cleome viscosa 24 8 360 26.67 0.18 2.22 0.18 3 0.69

39 C. oppositifolia 6 6 360 6.67 0.05 1.67 0.13 1 0.23

40 Conyza canadensis 32 8 360 35.56 0.23 2.22 0.18 4 0.91

41 Conyza stricta 40 12 360 44.44 0.29 3.33 0.27 3.33 0.76

42 Coronopus didymus 46 20 360 51.11 0.34 5.56 0.45 2.3 0.53

43 Cucumis melo

sp. agrestis

32 24 360

35.56 0.23

6.67 0.54 1.33 0.3

44 Cymbopogon jwarancusa 192 42 360 213.33 1.37 11.67 0.94 4.57 1.04

45 Cynodon dactylon 84 24 360 93.33 0.6 6.67 0.54 3.5 0.8

46 C. lanceolatum 72 24 360 80 0.52 6.67 0.54 3 0.69

47 Cyperus rotundus 48 30 360 53.33 0.34 8.33 0.67 1.6 0.37

48 Daphne oleoides 12 12 360 13.33 0.08 3.33 0.27 1 0.23

49 Datura innoxia 12 12 360 13.33 0.08 3.33 0.27 1 0.23

50 Debregeasia saeneb 36 24 360 40 0.26 6.67 0.54 1.5 0.34

51 Desmodium elegans 12 12 360 13.33 0.08 3.33 0.27 1 0.23

52 Dichanthium annulatum 78 24 360 86.67 0.57 6.67 0.54 3.25 0.74

53 Dodonaea viscosa 1284 264 360 1426.67 9.26 73.33 5.92 4.86 1.11

54 Dryopteris crenata 186 30 360 206.67 1.35 8.33 0.67 6.2 1.42

55 Dryopteris jaxtaposta 240 30 360 266.67 1.74 8.33 0.67 8 1.83

129

56 Duchesnea indica 36 12 360 40 0.26 3.33 0.27 3 0.69

57 Ehretia obtusifolia 6 6 360 6.67 0.05 1.67 0.13 1 0.23

58 Euphorbia granulata 68 16 360 75.56 0.49 4.44 0.36 4.25 0.97

59 Euphorbia hirta 36 16 360 40 0.26 4.44 0.36 2.25 0.51

60 Euphorbia indica 48 12 360 53.33 0.34 3.33 0.27 4 0.91

61 Erioscirpus comosus 144 36 360 160 1.04 10 0.81 4 0.91

62 E. biebersteinianum 12 6 360 13.33 0.08 1.67 0.13 2 0.46

63 Ficus palmata 258 150 360 286.67 1.87 41.67 3.37 1.72 0.39

64 Ficus racemose 74 42 360 82.22 0.54 11.67 0.94 1.76 0.4

65 Fumaria indica 42 16 360 46.67 0.31 4.44 0.36 2.63 0.6

66 Geranium rotundifolium 144 24 360 160 1.04 6.67 0.54 6 1.37

67 Grewia optiva 160 102 360 177.78 1.14 28.33 2.29 1.57 0.36

68 Heliotropium strigosum 82 32 360 91.11 0.6 8.89 0.72 2.56 0.59

69 Herniaria hirsuta 56 12 360 62.22 0.41 3.33 0.27 4.67 1.07

70 Heteropogon contortus 114 24 360 126.67 0.83 6.67 0.54 4.75 1.09

71 Hyoscyamus niger 12 6 360 13.33 0.08 1.67 0.13 2 0.46

72 Imperata cylindrica 48 6 360 53.33 0.34 1.67 0.13 8 1.83

73 Indigofera heterantha 96 24 360 106.67 0.7 6.67 0.54 4 0.91

74 Isodon rugosus 12 6 360 13.33 0.08 1.67 0.13 2 0.46

75 Justicia adhatoda 210 84 360 233.33 1.5 23.33 1.88 2.5 0.57

76 Kickxia ramosissima 120 48 360 133.33 0.86 13.33 1.08 2.5 0.57

77 Lamarckia aurea 94 24 360 104.44 0.67 6.67 0.54 3.92 0.9

78 Launaea procumbens 272 60 360 302.22 1.97 16.67 1.35 4.53 1.04

79 Lotus corniculatus 12 12 360 13.33 0.08 3.33 0.27 1 0.23

80 Mallotus philippensis 234 72 360 260 1.69 20 1.62 3.25 0.74

81 Martynia annua 12 4 360 13.33 0.08 1.11 0.09 3 0.69

82 Maytenus royaleana 48 48 360 53.33 0.34 13.33 1.08 1 0.23

83 Medicago minima 12 4 360 13.33 0.08 1.11 0.09 3 0.69

84 Melia azedarach 62 42 360 68.89 0.44 11.67 0.94 1.48 0.34

85 Melothria heterophylla 6 6 360 6.67 0.05 1.67 0.13 1 0.23

86 Mentha longifolia 6 6 360 6.67 0.05 1.67 0.13 1 0.23

130

87 Micromeria biflora 72 30 360 80 0.52 8.33 0.67 2.4 0.55

88 Mimosa himalayana 24 12 360 26.67 0.18 3.33 0.27 2 0.46

89 Monotheca buxifolia 6 6 360 6.67 0.05 1.67 0.13 1 0.23

90 Morus nigra 90 72 360 100 0.65 20 1.62 1.25 0.29

91 Myrsine africana 6 6 360 6.67 0.05 1.67 0.13 1 0.23

92 Nannorrhops ritchiana 30 30 360 33.33 0.21 8.33 0.67 1 0.23

93 Nepeta griffithii 30 12 360 33.33 0.21 3.33 0.27 2.5 0.57

94 Nerium odorum 12 6 360 13.33 0.08 1.67 0.13 2 0.46

95 Olea ferruginea 576 282 360 640 4.15 78.33 6.33 2.04 0.47

96 Onosma hispida 84 36 360 93.33 0.6 10 0.81 2.33 0.53

97 Origanum vulgare 66 30 360 73.33 0.47 8.33 0.67 2.2 0.5

98 Otostegia limbata 198 60 360 220 1.43 16.67 1.35 3.3 0.75

99 Oxalis corniculata 12 4 360 13.33 0.08 1.11 0.09 3 0.69

100 Papaver pavoninum 12 8 360 13.33 0.08 2.22 0.18 1.5 0.34

101 Parthenium hysterphorus 78 24 360 86.67 0.57 6.67 0.54 3.25 0.74

102 Peganum harmala 12 4 360 13.33 0.08 1.11 0.09 3 0.69

103 Pentanema vestitum 96 16 360 106.67 0.7 4.44 0.36 6 1.37

104 Pennisetum flaccidum 48 18 360 53.33 0.34 5 0.4 2.67 0.61

105 Periploca aphylla 6 6 360 6.67 0.05 1.67 0.13 1 0.23

106 Phyllanthus niruri 24 12 360 26.67 0.18 3.33 0.27 2 0.46

107 Physalis divaricata 38 12 360 42.22 0.29 3.33 0.27 3.17 0.72

108 Pinus roxburghii 884 162 360 982.22 6.38 45 3.64 5.46 1.25

109 Piptatherum aequiglume 54 24 360 60 0.39 6.67 0.54 2.25 0.51

110 Pistacia chinensis 54 18 360 60 0.39 5 0.4 3 0.69

111 Plantago lanceolata 42 12 360 46.67 0.31 3.33 0.27 3.5 0.8

112 Plantago major 12 4 360 13.33 0.08 1.11 0.09 3 0.69

113 Poa annua 102 16 360 113.33 0.73 4.44 0.36 6.38 1.46

114 Polygala erioptera 24 6 360 26.67 0.18 1.67 0.13 4 0.91

115 Polygonum barbatum 48 12 360 53.33 0.34 3.33 0.27 4 0.91

116 Punica granatum 12 12 360 13.33 0.08 3.33 0.27 1 0.23

117 Pupalia lappacea 42 18 360 46.67 0.31 5 0.4 2.33 0.53

131

118 Quercus incana 6 6 360 6.67 0.05 1.67 0.13 1 0.23

119 Rhazya stricta 12 6 360 13.33 0.08 1.67 0.13 2 0.46

120 Rhynchosia minima 30 12 360 33.33 0.21 3.33 0.27 2.5 0.57

121 Ricinus communis 18 12 360 20 0.13 3.33 0.27 1.5 0.34

122 Rubus fruticosus 72 42 360 80 0.52 11.67 0.94 1.71 0.39

123 Rumex hastatus 42 16 360 46.67 0.31 4.44 0.36 2.63 0.6

124 Saccharum filifolium 234 36 360 260 1.69 10 0.81 6.5 1.49

125 Saccharum griffthii 126 24 360 140 0.91 6.67 0.54 5.25 1.2

126 Sageretia thea 18 18 360 20 0.13 5 0.4 1 0.23

128 Salvia lanata 30 12 360 33.33 0.21 3.33 0.27 2.5 0.57

129 Salvia moorcroftiana 96 42 360 106.67 0.7 11.67 0.94 2.29 0.52

130 Salvia plebia 24 8 360 26.67 0.18 2.22 0.18 3 0.69

131 Setaria pumila 92 16 360 102.22 0.67 4.44 0.36 5.75 1.31

132 Sida cordata 78 42 360 86.67 0.57 11.67 0.94 1.86 0.43

133 Solanum surattense 6 6 360 6.67 0.05 1.67 0.13 1 0.23

134 Stipagrostis hirtigluma 40 6 360 44.44 0.29 1.67 0.13 6.67 1.52

135 Taraxacum officinale 30 8 360 33.33 0.21 2.22 0.18 3.75 0.86

136 Tecomella undulata 6 6 360 6.67 0.05 1.67 0.13 1 0.23

137 Teucrium stocksianum 6 6 360 6.67 0.05 1.67 0.13 1 0.23

138 Tithonia sp. 48 12 360 53.33 0.34 3.33 0.27 4 0.91

139 Tribulus terestris 32 12 360 35.56 0.23 3.33 0.27 2.67 0.61

140 Trichodesma indica 48 12 360 53.33 0.34 3.33 0.27 4 0.91

141 Urtica dioica 24 12 360 26.67 0.18 3.33 0.27 2 0.46

142 Vitex negundo 16 6 360 17.78 0.1 1.67 0.13 2.67 0.61

143 Verbascum thapsus 72 36 360 80 0.52 10 0.81 2 0.46

144 Vitis jacquemontii 72 24 360 80 0.52 6.67 0.54 3 0.69

145 Withania coagulans 26 24 360 28.89 0.18 6.67 0.54 1.08 0.25

146 Woodfordia fruiticosa 60 36 360 66.67 0.44 10 0.81 1.67 0.38

147 Ziziphus mauritiana 84 42 360 93.33 0.6 11.67 0.94 2 0.46

148 Ziziphus nummularia 8 6 360 8.89 0.05 1.67 0.13 1.33 0.3

149 Zizipus oxyphyla 84 54 360 93.33 0.6 15 1.21 1.56 0.36

132

13880 4456 15422.22 100 1237.78 100 437.57 100

133

Appendix-3. Total no. of individuals, Density, Relative density, frequency, relative frequency, abundance, relative abundance considering all

undergrowth species in exotic plots.


individuals

Quadrat

found

Total

quadrat

Density/

hac

Relative

Density

(%)

Frequency

(%)

Relative

Frequency

(%)

Abundance Relative

Abundance

(%)

1 Acacia modesta 238 72 360 264.44 1.92 20 2.07 3.31 0.94

2 Adiantum caudatum 222 42 360 246.67 1.8 11.67 1.21 5.29 1.5

3 Aerva javanica 126 36 360 140 1.02 10 1.04 3.5 0.99

4 Aerva sanguinolenta 204 30 360 226.67 1.66 8.33 0.86 6.8 1.92


6 Ajuga bracteosa 144 60 360 160 1.16 16.67 1.73 2.4 0.68

7 Ajuga parviflora 30 12 360 33.33 0.23 3.33 0.35 2.5 0.71

8 Alternanthera pungens 150 24 360 166.67 1.22 6.67 0.69 6.25 1.77

9 Ammi visnaga 12 4 360 13.33 0.09 1.11 0.12 3 0.85

10 Apluda mutica 120 24 360 133.33 0.96 6.67 0.69 5 1.41

11 Aristida cyanantha 174 30 360 193.33 1.4 8.33 0.86 5.8 1.64

12 Artemisia scoparia 78 24 360 86.67 0.64 6.67 0.69 3.25 0.92

13 Avena fatua 84 8 360 93.33 0.67 2.22 0.23 10.5 2.97

14 Barleria cristata 6 6 360 6.67 0.06 1.67 0.17 1 0.28

15 Bidens pilosa 96 24 360 106.67 0.79 6.67 0.69 4 1.13

16 Boerhavia procumbens 36 12 360 40 0.29 3.33 0.35 3 0.85

17 Broussonetia papyrifera 182 30 360 202.22 1.48 8.33 0.86 6.07 1.72

18 Calistemin lanceolatus 6 6 360 6.67 0.06 1.67 0.17 1 0.28

19 Commelina paludosa 110 12 360 122.22 0.9 3.33 0.35 9.17 2.6

20 Cannabis sativa 336 72 360 373.33 2.71 20 2.07 4.67 1.32

21 Caralluma tuberculata 6 6 360 6.67 0.06 1.67 0.17 1 0.28

22 Carthamus lanatus 194 44 360 215.56 1.57 12.22 1.27 4.41 1.25

23 Carthamus oxycantha 88 24 360 97.78 0.7 6.67 0.69 3.67 1.04

24 Cassia occidentalis 30 12 360 33.33 0.23 3.33 0.35 2.5 0.71

25 Celtis caucasica 52 36 360 57.78 0.41 10 1.04 1.44 0.41

134

26 Chenopodium album 216 52 360 240 1.75 14.44 1.5 4.15 1.17

27 C. ambrosioides 72 16 360 80 0.58 4.44 0.46 4.5 1.27

28 Chenopodium botrys 138 36 360 153.33 1.11 10 1.04 3.83 1.08

29 Chrysopogon aucheri 492 78 360 546.67 3.99 21.67 2.25 6.31 1.79

30 C. oppositifolia 6 6 360 6.67 0.06 1.67 0.17 1 0.28

31 Convolvulus arvense 18 4 360 20 0.15 1.11 0.12 4.5 1.27

32 Conyza Canadensis 104 16 360 115.56 0.84 4.44 0.46 6.5 1.84

33 Cucumis melo

subsp. Agrestis 12 8

360 13.33 0.09 2.22 0.23 1.5 0.42

34 Cymbopogon jwarancusa 168 42 360 186.67 1.37 11.67 1.21 4 1.13

35 Cynodon dactylon 120 18 360 133.33 0.96 5 0.52 6.67 1.89

36 C. lanceolatum 102 42 360 113.33 0.82 11.67 1.21 2.43 0.69

37 Cyperus rotundus 126 48 360 140 1.02 13.33 1.38 2.63 0.74

38 Dalbergia sissoo 12 12 360 13.33 0.09 3.33 0.35 1 0.28

39 Daphne oleoides 6 6 360 6.67 0.06 1.67 0.17 1 0.28

40 Datura innoxia 12 12 360 13.33 0.09 3.33 0.35 1 0.28

41 Debregeasia saeneb 40 30 360 44.44 0.32 8.33 0.86 1.33 0.38

42 Desmostachya bipinnata 18 12 360 20 0.15 3.33 0.35 1.5 0.42

43 Dichanthium annulatum 48 18 360 53.33 0.38 5 0.52 2.67 0.76

44 Dodonaea viscosa 1290 288 360 1433.33 10.42 80 8.3 4.48 1.27

45 Dryopteris crenata 222 30 360 246.67 1.8 8.33 0.86 7.4 2.09

46 Dryopteris jaxtaposta 96 18 360 106.67 0.79 5 0.52 5.33 1.51

47 Duchesnea indica 12 12 360 13.33 0.09 3.33 0.35 1 0.28

48 Euphorbia granulata 88 24 360 97.78 0.7 6.67 0.69 3.67 1.04

49 Euphorbia hirta 248 60 360 275.56 2.01 16.67 1.73 4.13 1.17

50 Euphorbia indica 128 32 360 142.22 1.05 8.89 0.92 4 1.13

51 Eucalyptus camaldulensis 842 180 360 935.56 6.81 50 5.19 4.68 1.32

52 Ficus palmata 156 90 360 173.33 1.25 25 2.59 1.73 0.49

53 Grewia optiva 60 30 360 66.67 0.49 8.33 0.86 2 0.57

54 Heliotropium strigosum 20 4 360 22.22 0.17 1.11 0.12 5 1.41

55 Heteropogon contortus 168 24 360 186.67 1.37 6.67 0.69 7 1.98

135

56 Isodon rugosus 6 6 360 6.67 0.06 1.67 0.17 1 0.28

57 Justicia adhatoda 126 36 360 140 1.02 10 1.04 3.5 0.99

58 Kickxia ramosissima 24 12 360 26.67 0.2 3.33 0.35 2 0.57

59 Lathyrus cicero 26 4 360 28.89 0.2 1.11 0.12 6.5 1.84

60 Launaea procumbens 108 48 360 120 0.87 13.33 1.38 2.25 0.64

61 Lotus corniculatus 66 12 360 73.33 0.52 3.33 0.35 5.5 1.56

62 Mallotus philippensis 222 78 360 246.67 1.8 21.67 2.25 2.85 0.81

63 Malva neglecta 12 4 360 13.33 0.09 1.11 0.12 3 0.85

64 Maytenus royaleana 12 12 360 13.33 0.09 3.33 0.35 1 0.28

65 Medicago minima 14 4 360 15.56 0.12 1.11 0.12 3.5 0.99

66 Melothria heterophylla 6 6 360 6.67 0.06 1.67 0.17 1 0.28

67 Mentha longifolia 6 6 360 6.67 0.06 1.67 0.17 1 0.28

68 Micromeria biflora 18 12 360 20 0.15 3.33 0.35 1.5 0.42

69 Morus alba 54 24 360 60 0.44 6.67 0.69 2.25 0.64

70 Morus nigra 88 36 360 97.78 0.7 10 1.04 2.44 0.69

71 Nannorrhops ritchiana 12 12 360 13.33 0.09 3.33 0.35 1 0.28

72 Olea ferruginea 476 192 360 528.89 3.84 53.33 5.53 2.48 0.7

73 Onosma hispida 36 18 360 40 0.29 5 0.52 2 0.57

74 Opuntia dilleni 48 24 360 53.33 0.38 6.67 0.69 2 0.57

75 Opuntia monacantha 12 12 360 13.33 0.09 3.33 0.35 1 0.28

76 Otostegia limbata 136 60 360 151.11 1.11 16.67 1.73 2.27 0.64

77 Papaver pavoninum 12 4 360 13.33 0.09 1.11 0.12 3 0.85

78 Parthenium

hysterophorus 240 36

360 266.67 1.95 10 1.04 6.67 1.89

79 Peganum harmala 6 4 360 6.67 0.06 1.11 0.12 1.5 0.42

80 Periploca aphylla 18 18 360 20 0.15 5 0.52 1 0.28

81 Phyllanthus niruri 24 12 360 26.67 0.2 3.33 0.35 2 0.57

82 Physalis divaricata 30 8 360 33.33 0.23 2.22 0.23 3.75 1.06


84 Plantago lanceolata 42 12 360 46.67 0.35 3.33 0.35 3.5 0.99

85 Plantago major 52 20 360 57.78 0.41 5.56 0.58 2.6 0.74

136

86 Polygala erioptera 72 30 360 80 0.58 8.33 0.86 2.4 0.68

87 Polygonum barbatum 114 52 360 126.67 0.93 14.44 1.5 2.19 0.62

88 Portulaca olearacea 24 8 360 26.67 0.2 2.22 0.23 3 0.85

89 Quercus incana 6 6 360 6.67 0.06 1.67 0.17 1 0.28

90 Rhazya stricta 6 6 360 6.67 0.06 1.67 0.17 1 0.28

91 Ricinus communis 30 18 360 33.33 0.23 5 0.52 1.67 0.47

92 Robinia pseudocacia 884 174 360 982.22 7.16 48.33 5.01 5.08 1.44

93 Rubus fruticosus 24 18 360 26.67 0.2 5 0.52 1.33 0.38

94 Rumex hastatus 82 42 360 91.11 0.67 11.67 1.21 1.95 0.55

95 Saccharum filifolium 276 42 360 306.67 2.24 11.67 1.21 6.57 1.86

96 Saccharum griffthii 78 54 360 86.67 0.64 15 1.56 1.44 0.41

97 Sageretia thea 18 18 360 20 0.15 5 0.52 1 0.28

98 Salix babylonica 6 6 360 6.67 0.06 1.67 0.17 1 0.28

99 Setaria pumila 76 16 360 84.44 0.61 4.44 0.46 4.75 1.34

100 Solanum nigram 16 12 360 17.78 0.12 3.33 0.35 1.33 0.38

101 Solanum surattense 60 24 360 66.67 0.49 6.67 0.69 2.5 0.71

102 Sonchus asper 60 30 360 66.67 0.49 8.33 0.86 2 0.57

103 S. graminifolium 326 36 360 362.22 2.65 10 1.04 9.06 2.56

104 Tribulus terestris 22 12 360 24.44 0.17 3.33 0.35 1.83 0.52

105 Trichodesma indica 12 4 360 13.33 0.09 1.11 0.12 3 0.85

106 Vicia sativa 36 12 360 40 0.29 3.33 0.35 3 0.85

107 Verbascum thapsus 54 12 360 60 0.44 3.33 0.35 4.5 1.27

108 Vitis jacquemontii 96 54 360 106.67 0.79 15 1.56 1.78 0.5

109 Withania coagulans 18 18 360 20 0.15 5 0.52 1 0.28

110 Xanthium sibiricum 10 4 360 11.11 0.09 1.11 0.12 2.5 0.71

111 Xanthium strumarium 18 12 360 20 0.15 3.33 0.35 1.5 0.42

12366 3470 13740 100 963.89 99.99 353.36 100

137

Appendix-4. Total no. of individuals, Density, Relative density, frequency, relative frequency, abundance, relative abundance considering only

tree undergrowth species in indigenous plots.


individuals

Quadrat

found

Total

quadrat

Density/

hac

Relative

Density

(%)

Frequency

(%)

Relative

Frequency

(%)

Abundance Relative

Abundance

(%)

1 Acacia modesta 1128 246 360 1253.33 26.87 68.33 14.85 4.59 10.36

2 Acacia nilotica 84 66 360 93.33 1.97 18.33 3.98 1.27 2.87


4 Albizia lebbeck 12 12 360 13.33 0.26 3.33 0.72 1 2.26

5 Bauhinia variegata 58 24 360 64.44 1.37 6.67 1.45 2.42 5.46

6 Celtis caucasica 198 144 360 220 4.72 40 8.7 1.38 3.12

7 Debregeasia saeneb 36 24 360 40 0.86 6.67 1.45 1.5 3.39

8 Ficus palmata 258 150 360 286.67 6.18 41.67 9.06 1.72 3.88

9 Ficus racemose 74 42 360 82.22 1.8 11.67 2.54 1.76 3.97

10 Grewia optiva 160 102 360 177.78 3.78 28.33 6.16 1.57 3.54

11 Mallotus philippensis 234 72 360 260 5.58 20 4.35 3.25 7.34

12 Melia azedarach 62 42 360 68.89 1.46 11.67 2.54 1.48 3.34

13 Mimosa himalayana 24 12 360 26.67 0.6 3.33 0.72 2 4.51

14 Monotheca buxifolia 6 6 360 6.67 0.17 1.67 0.36 1 2.26

15 Morus nigra 90 72 360 100 2.15 20 4.35 1.25 2.82

16 Olea ferruginea 576 282 360 640 13.73 78.33 17.03 2.04 4.61


18 Pistacia chinensis 54 18 360 60 1.29 5 1.09 3 6.77

19 Punica granatum 12 12 360 13.33 0.26 3.33 0.72 1 2.26

20 Quercus incana 6 6 360 6.67 0.17 1.67 0.36 1 2.26

21 Tecomella undulata 6 6 360 6.67 0.17 1.67 0.36 1 2.26

22 Ziziphus mauritiana 84 42 360 93.33 1.97 11.67 2.54 2 4.51

23 Zizipus oxyphyla 84 54 360 93.33 1.97 15 3.26 1.56 3.52

4194 1656 4660 100 460 100 44.3 100

138

Appendix-5. Total no. of individuals, Density, Relative density, frequency, relative frequency, abundance, relative abundance considering only

tree undergrowth species in exotic plots.


individuals

Quadrat

found

Total

quadrat

Density/

hac

Relative

Density

(%)

Frequency

(%)

Relative

Frequency

(%)

Abundance Relative

Abundance

(%)

1 Acacia modesta 238 72 360 264.44 6.65 20 6.42 3.31 7.5


3 Broussonetia papyrifera 182 30 360 202.22 5.14 8.33 2.67 6.07 13.76

4 Calistemin lanceolatus 6 6 360 6.67 0.2 1.67 0.54 1 2.27

5 Celtis caucasica 52 36 360 57.78 1.41 10 3.21 1.44 3.26

6 Dalbergia sissoo 12 12 360 13.33 0.3 3.33 1.07 1 2.27

7 Debregeasia saeneb 40 30 360 44.44 1.11 8.33 2.67 1.33 3.01

8 Eucalyptus camaldulensis 842 180 360 935.56 23.59 50 16.04 4.68 10.61

9 Ficus palmata 156 90 360 173.33 4.33 25 8.02 1.73 3.92

10 Grewia optiva 60 30 360 66.67 1.71 8.33 2.67 2 4.53

11 Mallotus philippensis 222 78 360 246.67 6.25 21.67 6.95 2.85 6.46

12 Morus alba 54 24 360 60 1.51 6.67 2.14 2.25 5.1

13 Morus nigra 88 36 360 97.78 2.42 10 3.21 2.44 5.53

14 Olea ferruginea 476 192 360 528.89 13.31 53.33 17.11 2.48 5.62


16 Quercus incana 6 6 360 6.67 0.2 1.67 0.54 1 2.27

17 Robinia pseudocacia 884 174 360 982.22 24.8 48.33 15.51 5.08 11.51

18 Salix babylonica 6 6 360 6.67 0.2 1.67 0.54 1 2.27

3570 1122 3966.67 100 311.67 100 44.13 100

139

Appendix-6.1. Shannon-Wiener diversity index (H) values considering all

undergrowth plant species recorded from Pinus roxburghii plots during spring season.

S. No Species name

Total

individuals Pi log Pi*log

Shannon-

Wiener

index

(H)

1 Acacia modesta

19 0.0 -4.1 -0.1 3.9

2 Achyranthes aspera 2 0.0 -6.3 0.0

3 Adiantum caudatum 19 0.0 -4.1 -0.1

4 Aerva sanguinolenta 19 0.0 -4.1 -0.1

5 Ajuga bracteosa 8 0.0 -4.9 0.0

6 Ajuga parviflora 4 0.0 -5.6 0.0

7 Ammi visnaga 3 0.0 -5.9 0.0

8 Anisomeles indica 5 0.0 -5.4 0.0

9 Aristida cyanantha 26 0.0 -3.8 -0.1

10 Asparagus adscendens 5 0.0 -5.4 0.0

11 Bauhinia variegata 9 0.0 -4.8 0.0

12 Barleria cristata 7 0.0 -5.1 0.0

13 Bidens pilosa 2 0.0 -6.3 0.0

14 Boerhavia procumbens 10 0.0 -4.7 0.0

15 Brachiaria ramosa 23 0.0 -3.9 -0.1

17 Cassia occidentalis 4 0.0 -5.6 0.0

18 Celtis caucasica 15 0.0 -4.3 -0.1

19 Chenopodium ambrosioides 11 0.0 -4.6 0.0

20 Cheilanthes pteroides 25 0.0 -3.8 -0.1

21 Chrysopogon aucheri 41 0.0 -3.3 -0.1

22 Cissampelos pareira 2 0.0 -6.3 0.0

23 Conyza stricta 7 0.0 -5.1 0.0

24 Conyza canadensis 6 0.0 -5.2 0.0

25 Cynodon dactylon 14 0.0 -4.4 -0.1

26 Cynoglossum lanceolatum 12 0.0 -4.5 0.0

27 Daphne oleoides 2 0.0 -6.3 0.0

28 Debregeasia saeneb 6 0.0 -5.2 0.0

29 Desmodium elegans 2 0.0 -6.3 0.0

30 Dichanthium annulatum 13 0.0 -4.5 -0.1

31 Dodonaea viscosa 85 0.1 -2.6 -0.2

32 Dryopteris crenata 31 0.0 -3.6 -0.1

33 Dryopteris jaxtaposta 40 0.0 -3.3 -0.1

34 Erioscirpus comosus 24 0.0 -3.8 -0.1

35 Euphorbia granulata 13 0.0 -4.5 -0.1

36 Euphorbia hirta 2 0.0 -6.3 0.0

37 Euphorbia indica 8 0.0 -4.9 0.0

140

38 Ficus palmata 19 0.0 -4.1 -0.1

39 Ficus racemosa 12 0.0 -4.5 0.0

40 Fumaria indica 7 0.0 -5.1 0.0

41 Geranium rotundifolium 24 0.0 -3.8 -0.1

42 Heteropogon contortus 19 0.0 -4.1 -0.1

43 Imperata cylindrica 8 0.0 -4.9 0.0

44 Indigofera heterantha 16 0.0 -4.2 -0.1

45 Kickxia ramosissima 7 0.0 -5.1 0.0

46 Launaea procumbens 14 0.0 -4.4 -0.1

47 Mallotus philippensis 35 0.0 -3.5 -0.1

48 Medicago minima 2 0.0 -6.3 0.0

49 Micromeria biflora 10 0.0 -4.7 0.0

50 Mimosa himalayana 4 0.0 -5.6 0.0

51 Morus nigra 7 0.0 -5.1 0.0

52 Nannorrhops ritchiana 3 0.0 -5.9 0.0

53 Nepeta griffithii 5 0.0 -5.4 0.0

54 Olea ferruginea 36 0.0 -3.4 -0.1

55 Origanum vulgare 11 0.0 -4.6 0.0

56 Otostegia limbata 11 0.0 -4.6 0.0

57 Oxalis corniculata L. 2 0.0 -6.3 0.0

58 Periploca aphylla 1 0.0 -7.0 0.0

59 Phyllanthus niruri 4 0.0 -5.6 0.0

60 Physalis divaricata 2 0.0 -6.3 0.0

61 Pinus roxburghii 143 0.1 -2.1 -0.3

62 Piptatherum aequiglume 9 0.0 -4.8 0.0

63 Pistacia chinensis 9 0.0 -4.8 0.0

64 Plantago lanceolata 7 0.0 -5.1 0.0

65 Polygala erioptera 4 0.0 -5.6 0.0

66 poa annua 19 0.0 -4.1 -0.1

67 Punica granatum 2 0.0 -6.3 0.0

68 Quercus incana 1 0.0 -7.0 0.0

69 Rhynchosia minima 5 0.0 -5.4 0.0

70 Rubus fruticosus 12 0.0 -4.5 0.0

71 Rumex hastatus 7 0.0 -5.1 0.0

72 launaea procumbens 28 0.0 -3.7 -0.1

73 Sageretia thea 3 0.0 -5.9 0.0

74 Setaria pumila 17 0.0 -4.2 -0.1

75 Sida cordata 7 0.0 -5.1 0.0

76 Stipagrostis hirtigluma 5 0.0 -5.4 0.0

77 Taraxacum officinale 5 0.0 -5.4 0.0

78 Tribulus terestris 4 0.0 -5.6 0.0

79 Urtica dioica 4 0.0 -5.6 0.0

141

80 Verbascum Thapsus 10 0.0 -4.7 0.0

81 Vitis jacquemontii 12 0.0 -4.5 0.0

82 Woodfordia fruiticosa 10 0.0 -4.7 0.0

83 Zizypus oxyphyla 14 0.0 -4.4 -0.1

Total 1120 -3.9

142

Appendix-6.2. Shannon-Wiener diversity index (H) values considering all undergrowth

plant species recorded from Pinus roxburghii plots during monsoon season.

S. No Species name

Total


Shannon-

Wiener

index (H)

1 Acacia modesta 23 0.02 -4.03 -0.07 3.95

2 Achyranthes aspera 2 0.00 -6.48 -0.01



5 Ajuga bracteosa 13 0.01 -4.60 -0.05

6 Ajuga parviflora 12 0.01 -4.68 -0.04

7 Ammi visnaga 6 0.00 -5.38 -0.02

8 Anisomeles indica 8 0.01 -5.09 -0.03


10 Asparagus adscendens 6 0.00 -5.38 -0.02

11 Bauhinia variegata 11 0.01 -4.77 -0.04

12 Barleria cristata 7 0.01 -5.22 -0.03

13 Bidens pilosa 2 0.00 -6.48 -0.01

14 Boerhavia procumbens 10 0.01 -4.87 -0.04

15 Brachiaria ramosa 23 0.02 -4.03 -0.07

17 Cassia occidentalis 4 0.00 -5.78 -0.02


19 Chenopodium ambrosioides 14 0.01 -4.53 -0.05



22 Cissampelos pareira 2 0.00 -6.48 -0.01

23 Conyza stricta 13 0.01 -4.60 -0.05

24 Conyza canadensis 10 0.01 -4.87 -0.04


26 Cynoglossum lanceolatum 12 0.01 -4.68 -0.04

27 Daphne oleoides 2 0.00 -6.48 -0.01

28 Debregeasia saeneb 6 0.00 -5.38 -0.02

29 Desmodium elegans 2 0.00 -6.48 -0.01






35 Euphorbia granulata 21 0.02 -4.12 -0.07

36 Euphorbia hirta 4 0.00 -5.78 -0.02

37 Euphorbia indica 16 0.01 -4.40 -0.05

143

38 Ficus palmata 21 0.02 -4.12 -0.07

39 Ficus racemosa 13 0.01 -4.60 -0.05

40 Fumaria indica 14 0.01 -4.53 -0.05



43 Imperata cylindrica 8 0.01 -5.09 -0.03


45 Kickxia ramosissima 7 0.01 -5.22 -0.03



48 Medicago minima 4 0.00 -5.78 -0.02

49 Micromeria biflora 10 0.01 -4.87 -0.04

50 Mimosa himalayana 4 0.00 -5.78 -0.02

51 Morus nigra 8 0.01 -5.09 -0.03

52 Nannorrhops ritchiana 3 0.00 -6.07 -0.01

53 Nepeta griffithii 10 0.01 -4.87 -0.04

54 Olea ferruginea 40 0.03 -3.48 -0.11

55 Origanum vulgare 11 0.01 -4.77 -0.04

56 Otostegia limbata 11 0.01 -4.77 -0.04

57 Oxalis corniculata 4 0.00 -5.78 -0.02

58 Periploca aphylla 1 0.00 -7.17 -0.01

59 Phyllanthus niruri 4 0.00 -5.78 -0.02

60 Physalis divaricata 4 0.00 -5.78 -0.02


62 Piptatherum aequiglume 9 0.01 -4.97 -0.03

63 Pistacia chinensis 9 0.01 -4.97 -0.03

64 Plantago lanceolata 14 0.01 -4.53 -0.05

65 Polygala erioptera 4 0.00 -5.78 -0.02

66 poa annua 32 0.02 -3.70 -0.09

67 Punica granatum 2 0.00 -6.48 -0.01

68 Quercus incana 1 0.00 -7.17 -0.01

69 Rhynchosia minima 5 0.00 -5.56 -0.02

70 Rubus fruticosus 12 0.01 -4.68 -0.04

71 Rumex hastatus 14 0.01 -4.53 -0.05


73 Sageretia thea 3 0.00 -6.07 -0.01

74 Setaria pumila 29 0.02 -3.80 -0.08

75 Sida cordata 7 0.01 -5.22 -0.03

76 Stipagrostis hirtigluma 10 0.01 -4.87 -0.04

77 Taraxacum officinale 10 0.01 -4.87 -0.04

78 Tribulus terestris 8 0.01 -5.09 -0.03

79 Urtica dioica 4 0.00 -5.78 -0.02

144

80 Verbascum Thapsus 16 0.01 -4.40 -0.05

81 Vitis jacquemontii 12 0.01 -4.68 -0.04

82 Woodfordia fruiticosa 10 0.01 -4.87 -0.04


1299 -3.95

145

Appendix-6.3 Shannon-Wiener diversity index (H) values considering all undergrowth

plant species recorded from Pinus roxburghii plots during winter season.

S. No Species name

Total


Shannon-

Wiener

index

(H)

1 Acacia modesta 19 0.0 -3.9 -0.1 3.6






7 Ammi visnaga 0 0.0 0.0 0.0

8 Anisomeles indica 5 0.0 -5.3 0.0


10 Asparagus adscendens 5 0.0 -5.3 0.0

11 Bauhinia variegata 9 0.0 -4.7 0.0


13 Bidens pilosa 0 0.0 0.0 0.0


15 Brachiaria ramosa 0 0.0 0.0 0.0

17 Cassia occidentalis 0 0.0 0.0 0.0


19 Chenopodium ambrosioides 0 0.0 0.0 0.0



22 Cissampelos pareira 2 0.0 -6.2 0.0

23 Conyza stricta 0 0.0 0.0 0.0

24 Conyza canadensis 0 0.0 0.0 0.0





29 Desmodium elegans 2 0.0 -6.2 0.0






35 Euphorbia granulata 0 0.0 0.0 0.0

36 Euphorbia hirta 0 0.0 0.0 0.0

146

37 Euphorbia indica 0 0.0 0.0 0.0

38 Ficus palmata 19 0.0 -3.9 -0.1

39 Ficus racemosa 12 0.0 -4.4 -0.1

40 Fumaria indica 0 0.0 0.0 0.0



43 Imperata cylindrica 8 0.0 -4.8 0.0





48 Medicago minima 0 0.0 0.0 0.0


50 Mimosa himalayana 4 0.0 -5.5 0.0

51 Morus nigra 7 0.0 -4.9 0.0


53 Nepeta griffithii 0 0.0 0.0 0.0


55 Origanum vulgare 11 0.0 -4.5 -0.1


57 Oxalis corniculata 0 0.0 0.0 0.0



60 Physalis divaricata 0 0.0 0.0 0.0


62 Piptatherum aequiglume 9 0.0 -4.7 0.0

63 Pistacia chinensis 9 0.0 -4.7 0.0

64 Plantago lanceolata 0 0.0 0.0 0.0


66 poa annua 0 0.0 0.0 0.0

67 Punica granatum 2 0.0 -6.2 0.0


69 Rhynchosia minima 5 0.0 -5.3 0.0

70 Rubus fruticosus 12 0.0 -4.4 -0.1

71 Rumex hastatus 0 0.0 0.0 0.0



74 Setaria pumila 0 0.0 0.0 0.0

75 Sida cordata 7 0.0 -4.9 0.0

76 Stipagrostis hirtigluma 5 0.0 -5.3 0.0

77 Taraxacum officinale 0 0.0 0.0 0.0


147

79 Urtica dioica 4 0.0 -5.5 0.0

80 Verbascum Thapsus 10 0.0 -4.6 0.0

81 Vitis jacquemontii 12 0.0 -4.4 -0.1

82 Woodfordia fruiticosa 10 0.0 -4.6 0.0


968 -3.6

148

Appendix-6.4 Shannon-Wiener diversity index (H) values considering undergrowth

tree species only recorded from Pinus roxburghii plots during summer season.

S. No Species name

Total


Shannon-

Wiener

index

(H)

1 Acacia modesta 19 0.06 -2.86 -0.16 2.01




5 Ficus palmata 19 0.06 -2.86 -0.16

6 Ficus racemosa 12 0.04 -3.32 -0.12



9 Morus nigra 7 0.02 -3.86 -0.08

10 Olea ferruginea 36 0.11 -2.22 -0.24



13 Punica granatum 2 0.01 -5.11 -0.03

14 Quercus incana 1 0.00 -5.80 -0.02


331 -2.01

149

Appendix-6.5. Shannon-Wiener diversity index (H) values considering undergrowth

tree species only recorded from Pinus roxburghii plots during monsoon season.

S. No Species name

Total

individuals Pi Log Pi*log

Shannon-

Wiener

index

(H)

1 Acacia modesta 23 0.06 -2.76 -0.17 2.01




5 Ficus palmata 21 0.06 -2.85 -0.16

6 Ficus racemosa 13 0.04 -3.33 -0.12



9 Morus nigra 8 0.02 -3.82 -0.08

10 Olea ferruginea 40 0.11 -2.21 -0.24



13 Punica granatum 2 0.01 -5.20 -0.03

14 Quercus incana 1 0.00 -5.90 -0.02


364 -2.01

150


tree species only recorded from Pinus roxburghii plots during winter season.

S. No Species name

Total


Shannon-

Wiener

index

(H)

1 Acacia modesta 19 0.06 -2.86 -0.16 2.01




5 Ficus palmata 19 0.06 -2.86 -0.16

6 Ficus racemosa 12 0.04 -3.32 -0.12



9 Morus nigra 7 0.02 -3.86 -0.08

10 Olea ferruginea 36 0.11 -2.22 -0.24



13 Punica granatum 2 0.01 -5.11 -0.03

14 Quercus incana 1 0.00 -5.80 -0.02


331 -2.01

151


undergrowth plant species recorded from E. camaldulensis plots during spring season.

S.no Species name Total

indivi.

Pi log

Pi*log

Shannon-

Wiener

index

(H)

1 Aerva javanica 21 0.0 -3.9 -0.1 1

2 Acacia modesta 39 0.0 -3.2 -0.1 2

3 Adiantum caudatum 37 0.0 -3.3 -0.1 3

4 Ajuga bracteosa 11 0.0 -4.5 0.0 4

5 Ajuga parviflora 5 0.0 -5.3 0.0 5

6 Aristida cyanantha 29 0.0 -3.5 -0.1 6

7 Barleria cristata 1 0.0 -6.9 0.0 7

8 Bidens pilosa 15 0.0 -4.2 -0.1 8

9 Boerhavia procumbens 6 0.0 -5.1 0.0 9

10 Cannabis sativa 16 0.0 -4.1 -0.1 10

11 Caralluma tuberculata 1 0.0 -6.9 0.0 11

12 Celtis caucasica 8 0.0 -4.8 0.0 12

13 Chenopodium album 20 0.0 -3.9 -0.1 13

14 Chenopodium botrys 23 0.0 -3.8 -0.1 14

15 Chrysopogon aucheri 31 0.0 -3.5 -0.1 15

16 Colebrookea oppositifolia 1 0.0 -6.9 0.0 16

17 Cymbopogon jwarancusa 28 0.0 -3.6 -0.1 17

18 Cynoglossum lanceolatum 11 0.0 -4.5 0.0 18

19 Cyperus rotundus 21 0.0 -3.9 -0.1 19

20 Daphne oleoides 1 0.0 -6.9 0.0 20

21 Datura innoxia 2 0.0 -6.2 0.0 21

22 Debregeasia saeneb 6 0.0 -5.1 0.0 22

23 Desmostachya bipinnata 3 0.0 -5.8 0.0 23

24 Dichanthium annulatum 8 0.0 -4.8 0.0 24

25 Dodonea viscosa 123 0.1 -2.1 -0.3 25

26 Dryopteris crenata 37 0.0 -3.3 -0.1 26

27 Dryopteris jaxtaposta 16 0.0 -4.1 -0.1 27

28 Duchesnea indica 2 0.0 -6.2 0.0 28

29 Eucalyptus camaldulensis 139 0.1 -2.0 -0.3 29

30 Euphorbia granulate 2 0.0 -6.2 0.0 30

31 Euphorbia hirta 14 0.0 -4.3 -0.1 31

32 Euphorbia indica 12 0.0 -4.4 -0.1 32

33 Ficus palmata 8 0.0 -4.8 0.0 33

34 Grevia optiva 10 0.0 -4.6 0.0 34

35 Heteropogan contortus 14 0.0 -4.3 -0.1 35

36 Justicia adhatoda 21 0.0 -3.9 -0.1 36

37 Kickxia ramosissima 2 0.0 -6.2 0.0 37

38 Launaea procumbens 5 0.0 -5.3 0.0 38

39 Mallotus philippensis 36 0.0 -3.3 -0.1 39

40 Maytenus royaleanus 2 0.0 -6.2 0.0 40

41 Mentha longifolia 1 0.0 -6.9 0.0 41

152

42 Micromeria biflora 3 0.0 -5.8 0.0 42

43 Nannorrhops ritchiana 2 0.0 -6.2 0.0 43

44 Olea ferruginea 35 0.0 -3.4 -0.1 44

45 Onosma hispida 6 0.0 -5.1 0.0 45

46 Opuntia dilleni 8 0.0 -4.8 0.0 46

47 Opuntia monacantha 2 0.0 -6.2 0.0 47

48 Otostegia limbata 18 0.0 -4.0 -0.1 48

49 Parthenium hysterophorus 12 0.0 -4.4 -0.1 49

50 Peganum harmala 1 0.0 -6.9 0.0 50

51 Periploca aphylla 3 0.0 -5.8 0.0 51

52 Phyllanthus niruri 2 0.0 -6.2 0.0 52

53 Pinus roxburghii 27 0.0 -3.6 -0.1 53

54 Plantago lanceolata 1 0.0 -6.9 0.0 54

55 Plantago major 1 0.0 -6.9 0.0 55

56 Isodon rugosus 1 0.0 -6.9 0.0 56

57 Polygonum barbatum 10 0.0 -4.6 0.0 57

58 Quercus incana 1 0.0 -6.9 0.0 58

59 Rhazya stricta 1 0.0 -6.9 0.0 59

60 Ricinus communis 2 0.0 -6.2 0.0 60

61 Rubus fruticosus 4 0.0 -5.5 0.0 61

62 Rumex hastatus 4 0.0 -5.5 0.0 62

63 Saccharum griffthii 13 0.0 -4.3 -0.1 63

64 Saccharum filifolium 16 0.0 -4.1 -0.1 64

65 Sageretia thea 3 0.0 -5.8 0.0 65

66 Solanum surattense 2 0.0 -6.2 0.0 66

67 Symphyotrichum graminifolium 18 0.0 -4.0 -0.1 67

68 Verbascum Thapsus 9 0.0 -4.7 0.0 68

69 Vitis jacquemontii 8 0.0 -4.8 0.0 69

70 Withania coagulans 3 0.0 -5.8 0.0 70

1004 -3.5

153

Appendix- 6.8. Shannon-Wiener diversity index (H) values considering all

undergrowth plant species recorded from E. camaldulensis plots during monsoon

season.

S. No Species name

Total


Shannon-

Wiener

index

(H)

1 Aerva javanica 21 0.0 -4.0 -0.1 3.4

2 Acacia modesta 41 0.0 -3.3 -0.1






8 Bidens pilosa 19 0.0 -4.1 -0.1


10 Cannabis sativa 16 0.0 -4.3 -0.1

11 Caralluma tuberculata 1 0.0 -7.0 0.0

12 Celtis caucasica 10 0.0 -4.7 0.0

13 Chenopodium album 34 0.0 -3.5 -0.1

14 Chenopodium botrys 23 0.0 -3.9 -0.1


16 Colebrookea oppositifolia 1 0.0 -7.0 0.0

17 Cymbopogon jwarancusa 28 0.0 -3.7 -0.1


19 Cyperus rotundus 21 0.0 -4.0 -0.1


21 Datura innoxia 2 0.0 -6.3 0.0


23 Desmostachya bipinnata 3 0.0 -5.9 0.0

24 Dichanthium annulatum 8 0.0 -4.9 0.0

25 Dodonea viscosa 123 0.1 -2.2 -0.2



28 Duchesnea indica 2 0.0 -6.3 0.0

29 Eucalyptus camaldulensis 143 0.1 -2.1 -0.3

30 Euphorbia granulate 4 0.0 -5.6 0.0

31 Euphorbia hirta 23 0.0 -3.9 -0.1


33 Ficus palmata 10 0.0 -4.7 0.0

34 Grevia optiva 10 0.0 -4.7 0.0

35 Heteropogan contortus 14 0.0 -4.4 -0.1

154

36 Justicia adhatoda 21 0.0 -4.0 -0.1


38 Launaea procumbens 5 0.0 -5.4 0.0


40 Maytenus royaleanus 2 0.0 -6.3 0.0

41 Mentha longifolia 1 0.0 -7.0 0.0




45 Onosma hispida 6 0.0 -5.2 0.0

46 Opuntia dilleni 8 0.0 -4.9 0.0

47 Opuntia monacantha 2 0.0 -6.3 0.0


49 Parthenium hysterophorus 12 0.0 -4.5 0.0

50 Peganum harmala 2 0.0 -6.3 0.0





55 Plantago major 2 0.0 -6.3 0.0

56 Isodon rugosus 1 0.0 -7.0 0.0

57 Polygonum barbatum 21 0.0 -4.0 -0.1


59 Rhazya stricta 1 0.0 -7.0 0.0

60 Ricinus communis 2 0.0 -6.3 0.0



63 Saccharum griffthii 13 0.0 -4.5 -0.1

64 Saccharum filifolium 16 0.0 -4.3 -0.1


66 Solanum surattense 2 0.0 -6.3 0.0

67 Symphyotrichum graminifolium 34 0.0 -3.5 -0.1

68 Verbascum Thapsus 18 0.0 -4.1 -0.1


70 Withania coagulans 3 0.0 -5.9 0.0

1122 -3.4

155

Appendix-6.9. Shannon-Wiener diversity index (H) values considering all undergrowth

plant species recorded from E. camaldulensis plots during winter season.

S. No Species name

Total


Shannon-

Wiener

index (H)

1 Aerva javanica 21 0.0 -3.8 -0.1 3.3

2 Acacia modesta 39 0.0 -3.1 -0.1


4 Ajuga bracteosa 11 0.0 -4.4 -0.1








12 Celtis caucasica 8 0.0 -4.7 0.0

13 Chenopodium album 0 0.0 0.0 0.0










23 Desmostachya bipinnata 3 0.0 -5.7 0.0

24 Dichanthium annulatum 8 0.0 -4.7 0.0

25 Dodonea viscosa 123 0.1 -2.0 -0.3








33 Ficus palmata 8 0.0 -4.7 0.0

34 Grevia optiva 10 0.0 -4.5 -0.1



156




40 Maytenus royaleanus 2 0.0 -6.1 0.0





45 Onosma hispida 6 0.0 -5.0 0.0

46 Opuntia dilleni 8 0.0 -4.7 0.0

47 Opuntia monacantha 2 0.0 -6.1 0.0


49 Parthenium hysterophorus 12 0.0 -4.3 -0.1

50 Peganum harmala 0 0.0 0.0 0.0





55 Plantago major 0 0.0 0.0 0.0


57 Polygonum barbatum 0 0.0 0.0 0.0





62 Rumex hastatus 0 0.0 0.0 0.0





67 Symphyotrichum graminifolium 0 0.0 0.0 0.0

68 Verbascum Thapsus 0 0.0 0.0 0.0



897 -3.3

157


tree species only recorded from E. camaldulensis plots during spring season.

S. No Species name

Total


Shannon-

Wiener

index

(H)

1 Acacia modesta 39 0.13 -2.07 -0.26 1.72




5 Ficus palmata 8 0.03 -3.65 -0.09

6 Grevia optiva 10 0.03 -3.43 -0.11


8 Olea ferruginea 35 0.11 -2.18 -0.25


10 Quercus incana 1 0.00 -5.73 -0.02

309 -1.72

158


tree species only recorded from E. camaldulensis plots during monsoon season.

S. No Species name

Total


Shannon-

Wiener

index (H)

1 Acacia modesta 41 0.1 -2.1 -0.3 1.76




5 Ficus palmata 10 0.0 -3.5 -0.1

6 Grevia optiva 10 0.0 -3.5 -0.1





329 -1.76

159


tree species only recorded from E. camaldulensis plots during winter season.

S. No Species name

Total


Shannon-

Wiener

index

(H)

1 Acacia modesta 39 0.13 -2.07 -0.26 1.72




5 Ficus palmata 8 0.03 -3.65 -0.09

6 Grevia optiva 10 0.03 -3.43 -0.11


8 Olea ferruginea 35 0.11 -2.18 -0.25


10 Quercus incana 1 0.00 -5.73 -0.02

309 -1.72

160


undergrowth plant species recorded from Acacia modesta plots during spring season.

S. No Species name

Total


Shannon-

Wiener

index

(H)

1 Aerva javanica 26 0.0 -3.8 -0.1 3.7

2 Acacia modesta 161 0.1 -2.0 -0.3

3 Acacia nilotica 13 0.0 -4.5 0.0


5 Ailanthus altissima 10 0.0 -4.8 0.0


7 Albizia lebbeck 2 0.0 -6.4 0.0

8 Allium griffithianum 20 0.0 -4.1 -0.1

9 Amaranthus spinosus 6 0.0 -5.3 0.0

10 Amaranthus viridis 11 0.0 -4.7 0.0

11 Apluda mutica 17 0.0 -4.2 -0.1


13 Berberis lycium 3 0.0 -6.0 0.0

14 Bidens pilosa 6 0.0 -5.3 0.0


17 Buddleja crispa 5 0.0 -5.5 0.0

18 Cannabis sativa 5 0.0 -5.5 0.0




22 Cenchrus ciliaris 20 0.0 -4.1 -0.1


24 Chenopodium botrys 10 0.0 -4.8 0.0


26 Chrysopogon serrulatus 18 0.0 -4.2 -0.1

27 Cleome viscosa 4 0.0 -5.7 0.0


29

Cucumis melo

subsp. agrestis 4

0.0 -5.7 0.0


31 Cyperus rotundus 8 0.0 -5.0 0.0


33 Dodonea viscosa 129 0.1 -2.2 -0.2


35 Ehretia obtusifolia 1 0.0 -7.1 0.0

36 Eryngium biebersteinianum 2 0.0 -6.4 0.0

161

37 Euphorbia hirta 4 0.0 -5.7 0.0

38 Ficus palmata 22 0.0 -4.0 -0.1

39 Grevia optiva 26 0.0 -3.8 -0.1

40 Heliotropium strigosum 14 0.0 -4.4 -0.1

41 Herniaria hirsuta 11 0.0 -4.7 0.0

42 Hyoscyamus niger 2 0.0 -6.4 0.0



45 Lamarckia aurea 18 0.0 -4.2 -0.1

46 Coronopus didymus 9 0.0 -4.9 0.0

47 Lotus corniculatus 2 0.0 -6.4 0.0

48 Mallotus philippensis 3 0.0 -6.0 0.0

49 Martynia annua 2 0.0 -6.4 0.0

50 Maytenus royleana 8 0.0 -5.0 0.0

51 Melia azedarach 10 0.0 -4.8 0.0

52 Melothria heterophylla 1 0.0 -7.1 0.0



55 Monotheca buxifolia 1 0.0 -7.1 0.0

56 Morus nigra 7 0.0 -5.1 0.0

57 Myrsine africana 1 0.0 -7.1 0.0


59 Nerium odorum 2 0.0 -6.4 0.0


61 Onosma hispida 14 0.0 -4.4 -0.1


63 Papaver pavoninum 2 0.0 -6.4 0.0

64 Parthenium hysterophorus 13 0.0 -4.5 0.0

65 Peganum harmala 2 0.0 -6.4 0.0

66 Pennisetum flaccidum 8 0.0 -5.0 0.0

67 Pentanema vestitum 23 0.0 -3.9 -0.1




71 Polygonum barbatum 10 0.0 -4.8 0.0

72 Pupalia lappaceae 7 0.0 -5.1 0.0





77 Salvia lanata 5 0.0 -5.5 0.0

78 salvia moorcroftiana 16 0.0 -4.3 -0.1

162

79 Salvia plebia 4 0.0 -5.7 0.0

80 Sida cordata 6 0.0 -5.3 0.0


82 Tecomella undulata 1 0.0 -7.1 0.0

83 Teucrium stocksianum 1 0.0 -7.1 0.0

84 Tithonia sp. 8 0.0 -5.0 0.0

85 Trichodesma indica 8 0.0 -5.0 0.0

86 Vitex negundo 2 0.0 -6.4 0.0


88 Zizyphus mauritiana 13 0.0 -4.5 0.0

89 Zizyphus nummularia 1 0.0 -7.1 0.0

1183 -3.7

163


undergrowth plant species recorded from Acacia modesta plots during monsoon

season.

S. No Species name

Total


Shannon-

Wiener

index

(H)

1 Aerva javanica 26 0.02 -3.96 -0.08 3.80

2 Acacia modesta 181 0.13 -2.02 -0.27

3 Acacia nilotica 16 0.01 -4.44 -0.05


5 Ailanthus altissima 12 0.01 -4.73 -0.04

6 Ajuga bracteosa 15 0.01 -4.51 -0.05

7 Albizia lebbeck 2 0.00 -6.52 -0.01


9 Amaranthus spinosus 12 0.01 -4.73 -0.04

10 Amaranthus viridis 22 0.02 -4.13 -0.07

11 Apluda mutica 17 0.01 -4.38 -0.05


13 Berberis lycium Royle 3 0.00 -6.12 -0.01

14 Bidens pilosa 12 0.01 -4.73 -0.04

15 Boerhavia procumbens 7 0.01 -5.27 -0.03

17 Buddleja crispa 5 0.00 -5.61 -0.02

18 Cannabis sativa 5 0.00 -5.61 -0.02

19 Caralluma tuberculata 2 0.00 -6.52 -0.01

20 Cassia occidentalis 4 0.00 -5.83 -0.02







27 Cleome viscosa 8 0.01 -5.14 -0.03

28 Colebrookea oppositifolia 1 0.00 -7.22 -0.01

29

Cucumis melo

subsp. agrestis 8

0.01 -5.14 -0.03



32 Datura innoxia 2 0.00 -6.52 -0.01

33 Dodonea viscosa 129 0.09 -2.36 -0.22

34 Duchesnea indica 6 0.00 -5.43 -0.02

35 Ehretia obtusifolia 1 0.00 -7.22 -0.01

164

36 Eryngium biebersteinianum 2 0.00 -6.52 -0.01

37 Euphorbia hirta 8 0.01 -5.14 -0.03

38 Ficus palmata 26 0.02 -3.96 -0.08

39 Grevia optiva 28 0.02 -3.89 -0.08

40 Heliotropium strigosum 27 0.02 -3.92 -0.08

41 Herniaria hirsuta 17 0.01 -4.38 -0.05

42 Hyoscyamus niger 2 0.00 -6.52 -0.01



45 Lamarckia aurea 29 0.02 -3.85 -0.08

46 Coronopus didymus 14 0.01 -4.58 -0.05

47 Lotus corniculatus 2 0.00 -6.52 -0.01


49 Martynia annua 4 0.00 -5.83 -0.02

50 Maytenus royleana 8 0.01 -5.14 -0.03

51 Melia azedarach 11 0.01 -4.82 -0.04

52 Melothria heterophylla 1 0.00 -7.22 -0.01

53 Mentha longifolia 1 0.00 -7.22 -0.01

54 Micromeria biflora 2 0.00 -6.52 -0.01

55 Monotheca buxifolia 1 0.00 -7.22 -0.01

56 Morus nigra 9 0.01 -5.02 -0.03

57 Myrsine africana 1 0.00 -7.22 -0.01

58 Nannorrhops ritchiana 2 0.00 -6.52 -0.01

59 Nerium odorum 2 0.00 -6.52 -0.01

60 Olea ferruginea 62 0.05 -3.09 -0.14

61 Onosma hispida 14 0.01 -4.58 -0.05


63 Papaver pavoninum 4 0.00 -5.83 -0.02


65 Peganum harmala 4 0.00 -5.83 -0.02

66 Pennisetum flaccidum 8 0.01 -5.14 -0.03

67 Pentanema vestitum 25 0.02 -4.00 -0.07

68 Physalis divaricata 8 0.01 -5.14 -0.03

69 Plantago major 4 0.00 -5.83 -0.02

70 Isodon rugosus 2 0.00 -6.52 -0.01

71 Polygonum barbatum 14 0.01 -4.58 -0.05

72 Pupalia lappaceae 7 0.01 -5.27 -0.03

73 Rhazya stricta 2 0.00 -6.52 -0.01

74 Ricinus communis 3 0.00 -6.12 -0.01



77 Salvia lanata 5 0.00 -5.61 -0.02

165


79 Salvia plebia 8 0.01 -5.14 -0.03

80 Sida cordata 6 0.00 -5.43 -0.02

81 Solanum surattense 1 0.00 -7.22 -0.01

82 Tecomella undulata 1 0.00 -7.22 -0.01

83 Teucrium stocksianum 1 0.00 -7.22 -0.01

84 Tithonia sp. 16 0.01 -4.44 -0.05

85 Trichodesma indica 16 0.01 -4.44 -0.05

86 Vitex negundo 4 0.00 -5.83 -0.02

87 Withania coagulans 5 0.00 -5.61 -0.02

88 Zizyphus mauritiana 16 0.01 -4.44 -0.05

89 Zizyphus nummularia 2 0.00 -6.52 -0.01

1363 -3.80

166


undergrowth plant species recorded from Acacia modesta plots during winter season.

S. No Species name

Total


Shannon-

Wiener

index (H)

1 Aerva javanica 26 0.0 -3.7 -0.1 3.4

2 Acacia modesta 161 0.2 -1.8 -0.3

3 Acacia nilotica 13 0.0 -4.3 -0.1




7 Albizia lebbeck 2 0.0 -6.2 0.0


9 Amaranthus spinosus 0 0.0 0.0 0.0

10 Amaranthus viridis 0 0.0 0.0 0.0

11 Apluda mutica 17 0.0 -4.1 -0.1


13 Berberis lycium 3 0.0 -5.8 0.0



17 Buddleja crispa 5 0.0 -5.3 0.0

18 Cannabis sativa 5 0.0 -5.3 0.0






24 Chenopodium botrys 10 0.0 -4.6 0.0



27 Cleome viscosa 0 0.0 0.0 0.0


29

Cucumis melo

subsp. agrestis 4

0.0 -5.5 0.0


31 Cyperus rotundus 8 0.0 -4.8 0.0


33 Dodonea viscosa 129 0.1 -2.1 -0.3


35 Ehretia obtusifolia 1 0.0 -6.9 0.0

36 Eryngium biebersteinianum 2 0.0 -6.2 0.0

167


38 Ficus palmata 22 0.0 -3.8 -0.1

39 Grevia optiva 26 0.0 -3.7 -0.1

40 Heliotropium strigosum 0 0.0 0.0 0.0

41 Herniaria hirsuta 0 0.0 0.0 0.0

42 Hyoscyamus niger 2 0.0 -6.2 0.0



45 Lamarckia aurea 0 0.0 0.0 0.0

46 Coronopus didymus 0 0.0 0.0 0.0


48 Mallotus philippensis 3 0.0 -5.8 0.0

49 Martynia annua 0 0.0 0.0 0.0

50 Maytenus royleana 8 0.0 -4.8 0.0

51 Melia azedarach 10 0.0 -4.6 0.0




55 Monotheca buxifolia 1 0.0 -6.9 0.0

56 Morus nigra 7 0.0 -5.0 0.0

57 Myrsine africana 1 0.0 -6.9 0.0


59 Nerium odorum 2 0.0 -6.2 0.0


61 Onosma hispida 14 0.0 -4.3 -0.1


63 Papaver pavoninum 0 0.0 0.0 0.0


65 Peganum harmala 0 0.0 0.0 0.0

66 Pennisetum flaccidum 8 0.0 -4.8 0.0

67 Pentanema vestitum 0 0.0 0.0 0.0




71 Polygonum barbatum 0 0.0 0.0 0.0

72 Pupalia lappaceae 7 0.0 -5.0 0.0





77 Salvia lanata 5 0.0 -5.3 0.0


168

79 Salvia plebia 0 0.0 0.0 0.0

80 Sida cordata 6 0.0 -5.1 0.0


82 Tecomella undulata 1 0.0 -6.9 0.0

83 Teucrium stocksianum 1 0.0 -6.9 0.0

84 Tithonia sp. 0 0.0 0.0 0.0

85 Trichodesma indica 0 0.0 0.0 0.0

86 Vitex negundo 2 0.0 -6.2 0.0



89 Zizyphus nummularia 1 0.0 -6.9 0.0

1007 -3.4

169


tree species only recorded from Acacia modesta plots during spring season.

S. No Species name

Total


Shannon-

Wiener

index (H)

1 Acacia modesta 161 0.48 -0.74 -0.35 1.77

2 Acacia nilotica 13 0.04 -3.26 -0.13


4 Albizia lebbeck 2 0.01 -5.13 -0.03


6 Ficus palmata 22 0.07 -2.73 -0.18

7 Grevia optiva 26 0.08 -2.56 -0.20

8 Melia azedarach 10 0.03 -3.52 -0.10


10 Morus nigra 7 0.02 -3.88 -0.08

11 Olea ferruginea 57 0.17 -1.78 -0.30



338 -1.77

170


tree species only recorded from Acacia modesta plots during monsoon season.

S. No Species name

Total


Shannon-

Wiener

index

(H)

1 Acacia modesta 181 0.47 -0.76 -0.36 1.80

2 Acacia nilotica 16 0.04 -3.18 -0.13


4 Albizia lebbeck 2 0.01 -5.26 -0.03


6 Ficus palmata 26 0.07 -2.70 -0.18

7 Grevia optiva 28 0.07 -2.62 -0.19

8 Melia azedarach 11 0.03 -3.56 -0.10


10 Morus nigra 9 0.02 -3.76 -0.09

11 Olea ferruginea 62 0.16 -1.83 -0.29



386 -1.80

171


tree species only recorded from Acacia modesta plots during winter season.

S. No Species name

Total


Shannon-

Wiener

index (H)

1 Acacia modesta 161 0.48 -0.74 -0.35 1.77

2 Acacia nilotica 13 0.04 -3.26 -0.13


4 Albizia lebbeck 2 0.01 -5.13 -0.03


6 Ficus palmata 22 0.07 -2.73 -0.18

7 Grevia optiva 26 0.08 -2.56 -0.20

8 Melia azedarach 10 0.03 -3.52 -0.10


10 Morus nigra 7 0.02 -3.88 -0.08

11 Olea ferruginea 57 0.17 -1.78 -0.30



338 -1.77

172

Appendix-6.19. Shannon-Wiener diversity index (H) value considering all

undergrowth plant species recorded from R. pseudoacacia plots during spring season.

S. No Species name

Total


Shannon-

Wiener

index

(H)

1 Aerva sanguinolenta 34 0.0 -3.5 -0.1 3.6



4 Alternanthera pungens 25 0.0 -3.8 -0.1

5 Ammi visnaga 2 0.0 -6.3 0.0

6 Apluda mutica 20 0.0 -4.0 -0.1

7 Artemisia scoparia 13 0.0 -4.4 -0.1

8 Avena fatua 18 0.0 -4.1 -0.1

9 Bidens pilosa 5 0.0 -5.4 0.0

10 Broussonetia papyrifera 29 0.0 -3.6 -0.1

11 Calistemin lanceolatus 1 0.0 -7.0 0.0

12 Commelina paludosa 23 0.0 -3.9 -0.1


14 Carthamus lanatus 40 0.0 -3.3 -0.1

15 Carthamus oxycantha 15 0.0 -4.3 -0.1



18 Chenopodium ambrosioides 12 0.0 -4.5 0.0


20 Convolvulus arvense 3 0.0 -5.9 0.0

21 Conyza Canadensis 18 0.0 -4.1 -0.1

22 Cucumis melo subsp. agrestis 2 0.0 -6.3 0.0



25 Dalbergia sissoo 2 0.0 -6.3 0.0

26 Dodonea viscosa 92 0.1 -2.5 -0.2

27 Euphorbia granulate 15 0.0 -4.3 -0.1



30 Ficus palmata 16 0.0 -4.2 -0.1

31 Heliotropium strigosum 4 0.0 -5.6 0.0



34 Lathyrus cicera 5 0.0 -5.4 0.0


173


37 Malva neglecta 2 0.0 -6.3 0.0



40 Morus alba 9 0.0 -4.8 0.0

41 Morus nigra 14 0.0 -4.4 -0.1









50 Polygonam barbatum 9 0.0 -4.8 0.0

51 Portulaca olearaceae 4 0.0 -5.6 0.0


53 Robinia pseudoacacia 146 0.1 -2.0 -0.3



56 Salix Babylonica 1 0.0 -7.0 0.0

57 Setaria pumila 13 0.0 -4.4 -0.1

58 Solanum nigrum 3 0.0 -5.9 0.0


60 Sonchus asper 10 0.0 -4.7 0.0




64 Vicia sativa 6 0.0 -5.2 0.0


66 Xanthium sibiricum 1 0.0 -7.0 0.0

67 Xanthium strumarium 3 0.0 -5.9 0.0

1093 -3.6

174

Appendix-6.20. Shannon-Wiener diversity index (H) value considering all undergrowth

plant species recorded from R. pseudoacacia plots during monsoon season.

S. No Species name

Total


Shannon-

Wiener

index (H)





5 Ammi visnaga 4 0.0 -5.8 0.0

6 Apluda mutica L. 20 0.0 -4.2 -0.1

7 Artemisia scoparia 13 0.0 -4.6 0.0

8 Avena fatua 24 0.0 -4.0 -0.1

9 Bidens pilosa 9 0.0 -5.0 0.0



12 Commelina paludosa 32 0.0 -3.7 -0.1


14 Carthamus lanatus 57 0.0 -3.2 -0.1

15 Carthamus oxycantha 29 0.0 -3.8 -0.1



18 Chenopodium ambrosioides 24 0.0 -4.0 -0.1


20 Convolvulus arvense 6 0.0 -5.4 0.0

21 Conyza Canadensis 34 0.0 -3.7 -0.1

22 Cucumis melo subsp. agrestis 4 0.0 -5.8 0.0





27 Euphorbia granulate 23 0.0 -4.1 -0.1


29 Euphorbia indica 14 0.0 -4.6 0.0

30 Ficus palmata 20 0.0 -4.2 -0.1

31 Heliotropium strigosum 6 0.0 -5.4 0.0

32 Heteropogan contortus 14 0.0 -4.6 0.0


34 Lathyrus cicera 8 0.0 -5.1 0.0



175

37 Malva neglecta 4 0.0 -5.8 0.0



40 Morus alba 9 0.0 -5.0 0.0

41 Morus nigra 16 0.0 -4.4 -0.1







48 Plantago major 15 0.0 -4.5 -0.1


50 Polygonam barbatum 17 0.0 -4.4 -0.1

51 Portulaca olearaceae 8 0.0 -5.1 0.0



54 Rumex hastatus 13 0.0 -4.6 0.0



57 Setaria pumila 25 0.0 -4.0 -0.1

58 Solanum nigrum 5 0.0 -5.6 0.0


60 Sonchus asper 10 0.0 -4.9 0.0




64 Vicia sativa 12 0.0 -4.7 0.0


66 Xanthium sibiricum 4 0.0 -5.8 0.0

67 Xanthium strumarium 6 0.0 -5.4 0.0

1331 -3.7

176

Appendix-6.21. Shannon-Wiener diversity index (H) value considering all

undergrowth plant species recorded from R. pseudoacacia plots during winter season.

S. No Species name

Total


Shannon-

Wiener

index (H)





5 Ammi visnaga 0 0.0 0.0 0.0

6 Apluda mutica 20 0.0 -3.6 -0.1

7 Artemisia scoparia 13 0.0 -4.0 -0.1

8 Avena fatua 0 0.0 0.0 0.0




12 Commelina paludosa 0 0.0 0.0 0.0


14 Carthamus lanatus 0 0.0 0.0 0.0

15 Carthamus oxycantha 0 0.0 0.0 0.0



18 Chenopodium ambrosioides 0 0.0 0.0 0.0


20 Convolvulus arvense 0 0.0 0.0 0.0

21 Conyza Canadensis 0 0.0 0.0 0.0

22 Cucumis melo subsp. agrestis 0 0.0 0.0 0.0








30 Ficus palmata 16 0.0 -3.8 -0.1

31 Heliotropium strigosum 0 0.0 0.0 0.0



34 Lathyrus cicera 0 0.0 0.0 0.0


36 Lotus corniculatus 11 0.0 -4.2 -0.1

177

37 Malva neglecta 0 0.0 0.0 0.0

38 Medicago minima 0 0.0 0.0 0.0


40 Morus alba 9 0.0 -4.4 -0.1

41 Morus nigra 14 0.0 -4.0 -0.1


43 Papaver pavoninum 0 0.0 0.0 0.0






49 Polygala erioptera 12 0.0 -4.1 -0.1

50 Polygonam barbatum 0 0.0 0.0 0.0

51 Portulaca olearaceae 0 0.0 0.0 0.0






57 Setaria pumila 0 0.0 0.0 0.0

58 Solanum nigrum 0 0.0 0.0 0.0


60 Sonchus asper 10 0.0 -4.3 -0.1

61 Symphyotrichum graminifolium 0 0.0 0.0 0.0

62 Trichodesma indica 0 0.0 0.0 0.0

63 Tribulus terestris 0 0.0 0.0 0.0

64 Vicia sativa 0 0.0 0.0 0.0


66 Xanthium sibiricum 0 0.0 0.0 0.0

67 Xanthium strumarium 0 0.0 0.0 0.0

736 -3.0

178


tree species only recorded from R. pseudoacacia plots during spring season.

S. No Species name

Total


Shannon-

Wiener

index (H)

1 Ailanthus altissima 12 0.0 -3.1 -0.1 1.5




5 Ficus palmata 16 0.1 -2.8 -0.2

6 Morus alba 9 0.0 -3.4 -0.1

7 Morus nigra 14 0.1 -3.0 -0.2




272 -1.5

179

Appendix- 6.23. Shannon-Wiener diversity index (H) values considering undergrowth

tree species only recorded from R. pseudoacacia plots during monsoon season.

S. No Species name

Total


Shannon-

Wiener

index (H)



3 Calistemin lanceolatus 1 0.00 -5.68 -0.02

4 Dalbergia sissoo 2 0.01 -4.99 -0.03

5 Ficus palmata 20 0.07 -2.69 -0.18

6 Morus alba 9 0.03 -3.49 -0.11

7 Morus nigra 16 0.05 -2.91 -0.16

8 Olea ferruginea 47 0.16 -1.83 -0.29


10 Salix Babylonica 1 0.00 -5.68 -0.02

294 -1.55

180


tree species only recorded from R. pseudoacacia plots during winter season.

S. No Species name

Total


Shannon-

Wiener

index

(H)





5 Ficus palmata 16 0.1 -2.8 -0.2

6 Morus alba 9 0.0 -3.4 -0.1

7 Morus nigra 14 0.1 -3.0 -0.2




272 -1.5

181

Appendix-6.25 Anova results for comparison of SWDI (H) values of all research plots

considering all undergrowth.

Statistix 8.1

Analysis of Variance Table for Data

Source DF SS MS F P

Plants 3 0.36250 0.12083 7.25 0.0202

Season 2 0.38000 0.19000 11.40 0.0090

Error 6 0.10000 0.01667

Total 11 0.84250

Grand Mean 3.5750 CV 3.61

Tukey's 1 Degree of Freedom Test for Nonadditivity

Source DF SS MS F P

Nonadditivity 1 0.00009 0.00009 0.00 0.9499

Remainder 5 0.09991 0.01998

Statistix 8.1

LSD All-Pairwise Comparisons Test of Data for Plants

Plants Mean Homogeneous Groups

1 3.8333 A

2 3.6333 AB

4 3.4333 B

3 3.4000 B

Alpha 0.05 Standard Error for Comparison 0.1054

Critical T Value 2.447 Critical Value for Comparison 0.2579

Error term used: Plants*Season, 6 DF

There are 2 groups (A and B) in which the means

are not significantly different from one another.

LSD All-Pairwise Comparisons Test of Data for Season

Season Mean Homogeneous Groups

2 3.7250 A

1 3.6750 A

3 3.3250 B






182

Appendix-6.26 Anova results for comparison of SWDI (H) values of all research plots

considering only trees species as undergrowth.

Statistix 8.1


Source DF SS MS F P

Plants 3 0.37792 0.12597 848.74 0.0000

Season 2 0.00241 0.00121 8.13 0.0196

Error 6 0.00089 0.00015

Total 11 0.38123



Source DF SS MS F P

Nonadditivity 1 8.341E-04 8.341E-04 73.92 0.0004

Remainder 5 5.642E-05 1.128E-05

Statistix 8.1 SWDI Considering Tree species



1 2.0162 A

2 1.7805 B

3 1.7333 C

4 1.5167 D

Alpha 0.05 Standard Error for Comparison 9.947E-03



All 4 means are significantly different from one another.



2 1.7817 A

1 1.7517 B

3 1.7517 B






183

Appendix-6.27 Anova results for comparison of SWDI (H) values B/w exotic and

indigenous research plots considering all undergrowth.

Statistix 8.1


Source DF SS MS F P

Plants 1 0.15042 0.15042 90.25 0.0109

Season 2 0.19000 0.09500 57.00 0.0172

Error 2 0.00333 0.00167

Total 5 0.34375



Source DF SS MS F P

Nonadditivity 1 0.00053 0.00053 0.19 0.7399

Remainder 1 0.00281 0.00281

Statistix 8.1 , 31/12/2018, 21:56:58



Indigenous 3.7333 A

Exotic 3.4167 B







Monsoon 3.7250 A

Spring 3.6750 A

Winter 3.3250 B






184

Appendix 6.28 Anova results for comparison of SWDI (H) values B/w exotic and

indigenous research plots considering only tree species as undergrowth.

Statistix 8.1


Source DF SS MS F P

Plants 1 0.11207 0.11207 517.23 0.0019

Season 2 0.00070 0.00035 1.62 0.3824

Error 2 0.00043 0.00022

Total 5 0.11320



Source DF SS MS F P

Nonadditivity 1 3.571E-04 3.571E-04 4.69 0.2755

Remainder 1 7.619E-05 7.619E-05

Statistix 8.1 SWDI for only trees species



Indigenous plots 1.8967 A

Exotic Plots 1.6233 B







Monsoon 1.7750 A

Spring 1.7550 B

Winter 1.7500 A




There are no significant pairwise differences among the means.

185

Appendix-7.1 Different soil parameters recorded from exotic and indigenous tree plots during winter season 2017.

Plot Type Location Replication Organic

matter (%)

pH EC

dS/m

Organic

Carbon

(%)

Total

Nitrogen

(%)

Phosphorus

(ppm)

Potassium

(ppm)

CaCO3

(mmole/meter)

R. pseudoacacia 1 1 1.18 7.1 0.2 0.68 0.07 6.84 82.06 5.4

R. pseudoacacia 1 2 1.19 7.05 0.2 0.69 0.07 6.9 82.75 4.9

R. pseudoacacia 1 3 1.19 7.03 0.9 0.69 0.07 6.88 82.55 5.4

R. pseudoacacia 2 1 1.28 6.95 0.2 0.74 0.07 7.44 89.23 4.5

R. pseudoacacia 2 2 1.27 6.97 0.2 0.74 0.07 7.36 88.32 4.2

R. pseudoacacia 2 3 1.28 6.94 0.2 0.74 0.07 7.42 89.02 3.9

R. pseudoacacia 3 1 1.37 6.9 0.2 0.79 0.08 7.94 95.28 3.6

R. pseudoacacia 3 2 1.39 6.87 0.2 0.81 0.08 8.06 96.67 3.8

R. pseudoacacia 3 3 1.37 6.86 0.2 0.8 0.08 7.96 95.49 3.5

E. camaldulensis 1 1 1.16 7.2 0.2 0.67 0.07 6.73 80.74 6.1

E. camaldulensis 1 2 1.17 7.19 0.2 0.68 0.07 6.8 81.57 6.2

E. camaldulensis 1 3 1.15 7.1 0.2 0.67 0.07 6.68 80.18 6.1

E. camaldulensis 2 1 1.19 7.03 0.2 0.69 0.07 6.88 82.55 5.7

E. camaldulensis 2 2 1.19 7.05 0.1 0.69 0.07 6.9 82.82 5.7

E. camaldulensis 2 3 1.27 7.01 0.1 0.74 0.07 7.36 88.32 5.8

E. camaldulensis 3 1 1.29 6.99 0.1 0.75 0.07 7.48 89.71 3.8

E. camaldulensis 3 2 1.28 6.98 0.1 0.74 0.07 7.44 89.23 3.6

E. camaldulensis 3 3 1.29 6.96 0.1 0.75 0.07 7.48 89.71 3.6

Acacia modesta 1 1 1.17 6.99 0.2 0.68 0.07 6.8 81.57 5.9

Acacia modesta 1 2 1.19 6.96 0.1 0.69 0.07 6.88 82.55 5.9

Acacia modesta 1 3 1.2 6.97 0.2 0.69 0.07 6.94 83.33 5.7

Acacia modesta 2 1 1.38 6.94 0.1 0.8 0.08 8.02 96.19 4.7

186

Acacia modesta 2 2 1.39 6.94 0.1 0.81 0.08 8.05 96.6 5.1

Acacia modesta 2 3 1.38 6.92 0.1 0.8 0.08 8 95.98 5.1

Acacia modesta 3 1 1.47 6.87 0.1 0.85 0.09 8.54 102.45 3.1

Acacia modesta 3 2 1.49 6.89 0.1 0.86 0.09 8.64 103.63 3.3

Acacia modesta 3 3 1.48 6.85 0.1 0.86 0.09 8.58 102.94 3.3

Pinus roxburghii 1 1 1.75 6.87 0.1 1.02 0.1 10.15 121.8 3.4









187

Appendix 7.2. Different soil parameters recorded from exotic and indigenous tree plots during spring season 2018.


matter (%)

pH EC

dS/m

Organic

Carbon

(%)

Total

Nitrogen

(%)

Phosphorus

(ppm)

Potassium

(ppm)

CaCO3

(mmole/meter)

R. pseudoacacia 1 1 1.08 7.15 0.12 0.58 0.05 5.09 75.06 7.7

R. pseudoacacia 1 2 1.09 7.1 0.11 0.59 0.05 5.15 75.75 7.2

R. pseudoacacia 1 3 1.09 7.08 0.79 0.59 0.05 5.13 75.55 7.7

R. pseudoacacia 2 1 1.18 7 0.12 0.64 0.05 5.69 82.23 6.8

R. pseudoacacia 2 2 1.17 7.02 0.11 0.64 0.05 5.61 81.32 6.5

R. pseudoacacia 2 3 1.18 6.99 0.11 0.64 0.05 5.67 82.02 6.2

R. pseudoacacia 3 1 1.27 6.95 0.1 0.69 0.06 6.19 88.28 5.9

R. pseudoacacia 3 2 1.29 6.92 0.2 0.71 0.06 6.31 89.67 6.1

R. pseudoacacia 3 3 1.27 6.91 0.2 0.70 0.06 6.21 88.49 5.8

E. camaldulensis 1 1 1.06 7.25 0.19 0.57 0.05 4.98 73.74 8.4

E. camaldulensis 1 2 1.07 7.24 0.2 0.58 0.05 5.05 74.57 8.5

E. camaldulensis 1 3 1.05 7.15 0.19 0.57 0.05 4.93 73.18 8.4

E. camaldulensis 2 1 1.09 7.08 0.19 0.59 0.05 5.13 75.55 8

E. camaldulensis 2 2 1.09 7.1 0.19 0.59 0.05 5.15 75.82 8

E. camaldulensis 2 3 1.17 7.06 0.19 0.64 0.05 5.61 81.32 8.1

E. camaldulensis 3 1 1.19 7.04 0.19 0.65 0.05 5.73 82.71 6.1

E. camaldulensis 3 2 1.18 7.03 0.19 0.64 0.05 5.69 82.23 5.9

E. camaldulensis 3 3 1.19 7.01 0.19 0.65 0.05 5.73 82.71 5.9

Acacia modesta 1 1 1.07 7.04 0.19 0.58 0.05 5.05 74.57 8.2

Acacia modesta 1 2 1.09 7.01 0.19 0.59 0.05 5.13 75.55 8.2

188

Acacia modesta 1 3 1.1 7.02 0.19 0.59 0.05 5.19 76.33 8

Acacia modesta 2 1 1.28 6.99 0.19 0.70 0.06 6.27 89.19 7

Acacia modesta 2 2 1.29 6.99 0.19 0.71 0.06 6.3 89.6 7.4

Acacia modesta 2 3 1.28 6.97 0.19 0.70 0.06 6.25 88.98 7.4

Acacia modesta 3 1 1.37 6.92 0.18 0.75 0.07 6.79 95.45 5.4

Acacia modesta 3 2 1.39 6.94 0.19 0.76 0.07 6.89 96.63 5.6

Acacia modesta 3 3 1.38 6.9 0.18 0.76 0.07 6.83 95.94 5.6


Pinus roxburghii 1 2 1.69 6.88 0.19 0.94 0.08 8.62 117.44 6








189

Appendix 7.3. Different soil parameters recorded from exotic and indigenous tree plots during monsoon season 2018.


matter (%)

pH EC

dS/m

Organic

Carbon

(%)

Total

Nitrogen

(%)

Phosphorus

(ppm)

Potassium

(ppm)

CaCO3

(mmole/meter)

R. pseudoacacia 1 1 1.48 7.07 0.16 0.76 0.1 8.79 93.06 4.7 R. pseudoacacia 1 2 1.49 7.02 0.15 0.77 0.1 8.85 93.75 4.2 R. pseudoacacia 1 3 1.49 7 0.83 0.77 0.1 8.83 93.55 4.7 R. pseudoacacia 2 1 1.58 6.92 0.16 0.82 0.1 9.39 100.23 3.8 R. pseudoacacia 2 2 1.57 6.94 0.15 0.82 0.1 9.31 99.32 3.5 R. pseudoacacia 2 3 1.58 6.91 0.15 0.82 0.1 9.37 100.02 3.2 R. pseudoacacia 3 1 1.67 6.87 0.14 0.87 0.11 9.89 106.28 2.9 R. pseudoacacia 3 2 1.69 6.84 0.14 0.89 0.11 10.01 107.67 3.1 R. pseudoacacia 3 3 1.67 6.83 0.14 0.88 0.11 9.91 106.49 2.8 E. camaldulensis 1 1 1.46 7.17 0.13 0.75 0.1 8.68 91.74 5.4 E. camaldulensis 1 2 1.47 7.16 0.14 0.76 0.1 8.75 92.57 5.5 E. camaldulensis 1 3 1.45 7.07 0.13 0.76 0.1 8.63 91.18 5.4 E. camaldulensis 2 1 1.49 7 0.13 0.77 0.1 8.83 93.55 5 E. camaldulensis 2 2 1.49 7.02 0.13 0.77 0.1 8.85 93.82 5 E. camaldulensis 2 3 1.47 6.98 0.13 0.82 0.1 9.31 99.32 5.1 E. camaldulensis 3 1 1.59 6.96 0.13 0.83 0.1 9.43 100.71 3.1 E. camaldulensis 3 2 1.58 6.95 0.13 0.82 0.1 9.39 100.23 2.9 E. camaldulensis 3 3 1.59 6.93 0.13 0.83 0.1 9.43 100.71 2.9 Acacia modesta 1 1 1.47 6.96 0.13 0.76 0.1 8.75 92.57 5.2 Acacia modesta 1 2 1.49 6.93 0.13 0.77 0.1 8.83 93.55 5.2 Acacia modesta 1 3 1.5 6.94 0.13 0.77 0.1 8.89 94.33 5 Acacia modesta 2 1 1.68 6.91 0.13 0.88 0.11 9.97 107.19 4

190

Acacia modesta 2 2 1.69 6.91 0.13 0.89 0.11 10 107.6 4.4 Acacia modesta 2 3 1.68 6.89 0.13 0.88 0.11 9.95 106.98 4.4 Acacia modesta 3 1 1.77 6.84 0.12 0.93 0.12 10.49 113.45 2.4 Acacia modesta 3 2 1.79 6.86 0.13 0.94 0.12 10.59 114.63 2.6 Acacia modesta 3 3 1.78 6.82 0.12 0.94 0.12 10.53 113.94 2.6 Pinus roxburghii 1 1 2.05 6.84 0.12 1.1 0.13 12.1 132.8 2.7 Pinus roxburghii 1 2 2.09 6.8 0.13 1.12 0.13 12.32 135.44 3 Pinus roxburghii 1 3 2.08 6.77 0.12 1.11 0.13 12.29 135.03 2.7 Pinus roxburghii 2 1 2.09 6.75 0.12 1.12 0.13 12.33 135.58 2.1 Pinus roxburghii 2 2 2.12 6.77 0.12 1.14 0.14 12.51 137.67 2.2 Pinus roxburghii 2 3 2.12 6.73 0.12 1.14 0.14 12.51 137.67 2.2 Pinus roxburghii 3 1 2.28 6.7 0.11 1.23 0.14 13.41 148.46 1.6 Pinus roxburghii 3 2 2.27 6.7 0.11 1.22 0.14 13.39 148.25 1.5 Pinus roxburghii 3 3 2.28 6.67 0.11 1.23 0.14 13.45 148.95 1.8

191

Appendix-8.

Statistix 8.1 Soil pH Analysis of Variance Table for Data

Source DF SS MS F P

Plants 3 1.08929 0.36310 522.86 0.0000

Location 2 0.38960 0.19480 280.51 0.0000

Season 2 0.11760 0.05880 84.67 0.0000

Plants*Location 6 0.03613 0.00602 8.67 0.0000

Plants*Season 6 9.324E-31 1.554E-31 0.00 1.0000

Location*Season 4 1.919E-30 4.798E-31 0.00 1.0000

Plants*Location*Season 12 2.465E-30 2.054E-31 0.00 1.0000

Error 72 0.05000 6.944E-04

Total 107 1.68263


Statistix 8.1 Soil pH



2 7.0633 A

1 6.9700 B

3 6.9322 C

4 6.7844 D



Error term used: Error, 72 DF


LSD All-Pairwise Comparisons Test of Data for Location

Location Mean Homogeneous Groups

1 7.0142 A

2 6.9308 B

3 6.8675 C







2 6.9808 A

1 6.9308 B

3 6.9008 C





LSD All-Pairwise Comparisons Test of Data for Plants*Location

Plants Location Mean Homogeneous Groups

2 1 7.1700 A

1 1 7.0667 B

2 2 7.0367 C

2 3 6.9833 D

3 1 6.9800 D

1 2 6.9600 DE

3 2 6.9400 E

192

1 3 6.8833 F

3 3 6.8767 F

4 1 6.8400 G

4 2 6.7867 H

4 3 6.7267 I




There are 9 groups (A, B, etc.) in which the means


LSD All-Pairwise Comparisons Test of Data for Plants*Season

Plants Season Mean Homogeneous Groups

2 2 7.1067 A

2 1 7.0567 B

2 3 7.0267 C

1 2 7.0133 C

3 2 6.9756 D

1 1 6.9633 D

1 3 6.9333 E

3 1 6.9256 E

3 3 6.8956 F

4 2 6.8278 G

4 1 6.7778 H

4 3 6.7478 I






LSD All-Pairwise Comparisons Test of Data for Location*Season

Location Season Mean Homogeneous Groups

1 2 7.0575 A

1 1 7.0075 B

1 3 6.9775 C

2 2 6.9742 C

2 1 6.9242 D

3 2 6.9108 DE

2 3 6.8942 E

3 1 6.8608 F

3 3 6.8308 G






LSD All-Pairwise Comparisons Test of Data for Plants*Location*Season

Plants Location Season Mean Homogeneous Groups

2 1 2 7.2133 A

2 1 1 7.1633 B

2 1 3 7.1333 BC

1 1 2 7.1100 CD

2 2 2 7.0800 DE

1 1 1 7.0600 EF

1 1 3 7.0300 FG

2 2 1 7.0300 FG

2 3 2 7.0267 FG

3 1 2 7.0233 FGH

1 2 2 7.0033 GHI

2 2 3 7.0000 GHI

193

3 2 2 6.9833 HIJ

2 3 1 6.9767 IJ

3 1 1 6.9733 IJK

1 2 1 6.9533 JKL

2 3 3 6.9467 JKL

3 1 3 6.9433 JKLM

3 2 1 6.9333 KLM

1 3 2 6.9267 LM

1 2 3 6.9233 LMN

3 3 2 6.9200 LMN

3 2 3 6.9033 MNO

4 1 2 6.8833 NOP

1 3 1 6.8767 OPQ

3 3 1 6.8700 OPQR

1 3 3 6.8467 PQR

3 3 3 6.8400 QRS

4 1 1 6.8333 RS

4 2 2 6.8300 RS

4 1 3 6.8033 ST

4 2 1 6.7800 TU

4 3 2 6.7700 TU

4 2 3 6.7500 UV

4 3 1 6.7200 VW

4 3 3 6.6900 W






194

Appendix-9.

Statistix 8.1 Organic Matter


Source DF SS MS F P

Plants 3 6.8441 2.28138 9733.80 0.0000

Location 2 0.7504 0.37518 1600.75 0.0000

Season 2 3.0742 1.53709 6558.20 0.0000

Plants*Location 6 0.1063 0.01772 75.62 0.0000

Plants*Season 6 0.0005 0.00009 0.39 0.8849

Location*Season 4 0.0004 0.00009 0.40 0.8086

Plants*Location*Season 12 0.0011 0.00009 0.40 0.9595

Error 72 0.0169 0.00023

Total 107 10.7939


Statistix 8.1 Organic Matter



4 1.9199 A

3 1.4160 B

1 1.3460 C

2 1.2839 D


Critical T Value 1.993 Critical Value for Comparison 8.306E-03





3 1.5966 A

2 1.4851 B

1 1.3927 C







3 1.7230 A

1 1.4257 B

2 1.3257 C







4 3 2.0430 A

4 2 1.8767 B

4 1 1.8400 C

3 3 1.5467 D

3 2 1.4497 E

1 3 1.4433 E

2 3 1.3533 F

195

1 2 1.3433 F

2 2 1.2706 G

3 1 1.2517 H

1 1 1.2513 H

2 1 1.2278 I








4 3 2.1532 A

4 1 1.8532 B

4 2 1.7532 C

3 3 1.6494 D

1 3 1.5793 E

2 3 1.5099 F

3 1 1.3494 G

1 1 1.2793 H

3 2 1.2494 I

2 1 1.2210 J

1 2 1.1793 K

2 2 1.1208 L







3 3 1.8299 A

2 3 1.7128 B

1 3 1.6261 C

3 1 1.5299 D

3 2 1.4299 E

2 1 1.4212 E

1 1 1.3261 F

2 2 1.3212 F

1 2 1.2259 G








4 3 3 2.2763 A

4 2 3 2.1100 B

4 1 3 2.0733 C

4 3 1 1.9763 D

4 3 2 1.8763 E

4 2 1 1.8100 F

3 3 3 1.7800 G

4 1 1 1.7733 G

4 2 2 1.7100 H

3 2 3 1.6830 I

1 3 3 1.6767 I

4 1 2 1.6733 I

2 3 3 1.5867 J

196

1 2 3 1.5767 J

3 1 3 1.4851 K

1 1 3 1.4847 K

2 2 3 1.4817 K

3 3 1 1.4800 K

2 1 3 1.4613 K

3 2 1 1.3830 L

3 3 2 1.3800 L

1 3 1 1.3767 L

2 3 1 1.2867 M

3 2 2 1.2830 M

1 2 1 1.2767 M

1 3 2 1.2767 M

2 2 1 1.2150 N

2 3 2 1.1867 O

3 1 1 1.1851 OP

1 1 1 1.1847 OP

1 2 2 1.1767 OP

2 1 1 1.1613 P

2 2 2 1.1150 Q

3 1 2 1.0851 R

1 1 2 1.0847 R

2 1 2 1.0607 R






197

Appendix-10

Statistix 8.1 Organic carbon


Source DF SS MS F P

Plants 3 2.29942 0.76647 6979.06 0.0000

Location 2 0.25118 0.12559 1143.57 0.0000

Season 2 0.58336 0.29168 2655.86 0.0000

Plants*Location 6 0.03526 0.00588 53.51 0.0000

Plants*Season 6 0.00002 2.946E-06 0.03 0.9999

Location*Season 4 0.00002 4.893E-06 0.04 0.9962

Plants*Location*Season 12 0.00003 2.404E-06 0.02 1.0000

Error 72 0.00791 1.098E-04

Total 107 3.17719


Statistix 8.1 Organic carbon



4 1.0694 A

3 0.7757 B

1 0.7355 C

2 0.7023 D







3 0.8808 A

2 0.8186 B

1 0.7627 C







3 0.9071 A

1 0.8275 B

2 0.7275 C







4 3 1.1399 A

4 2 1.0455 B

4 1 1.0228 C

3 3 0.8506 D

3 2 0.7963 E

1 3 0.7928 E

2 3 0.7399 F

198

1 2 0.7335 F

2 2 0.6993 G

3 1 0.6802 H

1 1 0.6801 H

2 1 0.6676 I








4 3 1.1549 A

4 1 1.0767 B

4 2 0.9767 C

3 3 0.8626 D

1 3 0.8220 E

2 3 0.7891 F

3 1 0.7822 F

1 1 0.7422 G

2 1 0.7089 H

3 2 0.6822 I

1 2 0.6422 J

2 2 0.6089 K








3 3 0.9674 A

2 3 0.9043 B

3 1 0.8875 C

1 3 0.8498 D

2 1 0.8258 E

3 2 0.7875 F

1 1 0.7692 G

2 2 0.7258 H

1 2 0.6692 I







4 3 3 1.2263 A

4 3 1 1.1467 B

4 2 3 1.1298 B

4 1 3 1.1085 C

4 2 1 1.0533 D

4 3 2 1.0467 DE

4 1 1 1.0300 E

4 2 2 0.9533 F

3 3 3 0.9384 FG

4 1 2 0.9300 G

3 2 3 0.8821 H

1 3 3 0.8785 H

3 3 1 0.8567 I

199

2 3 3 0.8263 J

1 2 3 0.8205 J

3 2 1 0.8033 K

1 3 1 0.8000 KL

2 2 3 0.7847 L

3 1 3 0.7673 M

1 1 3 0.7671 M

3 3 2 0.7567 MN

2 1 3 0.7562 MN

2 3 1 0.7467 N

1 2 1 0.7400 N

2 2 1 0.7067 O

3 2 2 0.7033 OP

1 3 2 0.7000 OP

1 1 1 0.6867 PQ

3 1 1 0.6867 PQ

2 1 1 0.6733 Q

2 3 2 0.6467 R

1 2 2 0.6400 R

2 2 2 0.6067 S

1 1 2 0.5867 T

3 1 2 0.5867 T

2 1 2 0.5733 T






200

Appendix-11

Statistix 8.1 Electric conductivity


Source DF SS MS F P

Plants 3 0.10803 0.03601 2.82 0.0447

Location 2 0.09022 0.04511 3.54 0.0342

Season 2 0.02961 0.01480 1.16 0.3189

Plants*Location 6 0.21527 0.03588 2.81 0.0162

Plants*Season 6 0.02722 0.00454 0.36 0.9042

Location*Season 4 0.00148 0.00037 0.03 0.9983

Plants*Location*Season 12 0.00444 0.00037 0.03 1.0000

Error 72 0.91793 0.01275

Total 107 1.39421


Statistix 8.1 Electric conductivity



1 0.2233 A

2 0.1569 B

3 0.1534 B

4 0.1432 B








1 0.2101 A

2 0.1493 B

3 0.1483 B








2 0.1896 A

1 0.1690 A

3 0.1490 A




There are no significant pairwise differences among the means.



1 1 0.3733 A

2 1 0.1613 B

3 1 0.1567 B

2 2 0.1563 B

201

3 2 0.1543 B

1 3 0.1532 B

2 3 0.1530 B

3 3 0.1493 B

4 1 0.1490 B

1 2 0.1433 B

4 2 0.1430 B

4 3 0.1377 B








1 1 0.2426 A

1 3 0.2226 AB

1 2 0.2048 AB

2 2 0.1902 AB

3 2 0.1868 AB

4 2 0.1766 AB

2 1 0.1502 AB

3 1 0.1468 AB

4 1 0.1366 AB

2 3 0.1302 B

3 3 0.1268 B

4 3 0.1166 B








1 2 0.2268 A

1 1 0.2117 AB

1 3 0.1918 AB

3 2 0.1761 AB

2 2 0.1659 AB

2 1 0.1509 AB

3 1 0.1444 AB

2 3 0.1309 B

3 3 0.1244 B








1 1 1 0.4000 A

1 1 3 0.3800 A

1 1 2 0.3400 AB

2 1 2 0.1947 BC

3 1 2 0.1900 BC

2 2 2 0.1897 BC

3 2 2 0.1877 BC

2 3 2 0.1863 BC

3 3 2 0.1827 BC

202

4 1 2 0.1823 BC

4 2 2 0.1763 BC

4 3 2 0.1710 BC

1 2 1 0.1700 BC

1 3 2 0.1643 BC

1 3 1 0.1577 BC

2 1 1 0.1547 C

1 2 3 0.1500 C

3 1 1 0.1500 C

2 2 1 0.1497 C

3 2 1 0.1477 C

2 3 1 0.1463 C

3 3 1 0.1427 C

4 1 1 0.1423 C

1 3 3 0.1377 C

4 2 1 0.1363 C

2 1 3 0.1347 C

4 3 1 0.1310 C

3 1 3 0.1300 C

2 2 3 0.1297 C

3 2 3 0.1277 C

2 3 3 0.1263 C

3 3 3 0.1227 C

4 1 3 0.1223 C

4 2 3 0.1163 C

4 3 3 0.1110 C

1 2 2 0.1100 C






203

Appendix-12

Statistix 8.1 Total Nitrogen


Source DF SS MS F P

Plants 3 0.02289 0.00763 7733.07 0.0000

Location 2 0.00253 0.00126 1279.73 0.0000

Season 2 0.04556 0.02278 23090.3 0.0000

Plants*Location 6 3.558E-04 5.930E-05 60.10 0.0000

Plants*Season 6 2.923E-10 4.871E-11 0.00 1.0000



Error 72 7.104E-05 9.866E-07

Total 107 0.07140


Statistix 8.1 Total Nitrogen



4 0.1108 A

3 0.0816 B

1 0.0775 C

2 0.0742 D







3 0.0921 A

2 0.0858 B

1 0.0803 C







3 0.1127 A

1 0.0827 B

2 0.0627 C







4 3 0.1180 A

4 2 0.1083 B

4 1 0.1062 C

3 3 0.0892 D

3 2 0.0836 E

1 3 0.0832 E

204

2 3 0.0780 F

1 2 0.0774 F

2 2 0.0738 G

3 1 0.0721 H

1 1 0.0721 H

2 1 0.0707 I








4 3 0.1375 A

3 3 0.1083 B

4 1 0.1075 B

1 3 0.1042 C

2 3 0.1008 D

4 2 0.0875 E

3 1 0.0783 F

1 1 0.0742 G

2 1 0.0708 H

3 2 0.0583 I

1 2 0.0542 J

2 2 0.0508 K








3 3 0.1187 A

2 3 0.1124 B

1 3 0.1069 C

3 1 0.0888 D

2 1 0.0824 E

1 1 0.0769 F

3 2 0.0688 G

2 2 0.0624 H

1 2 0.0569 I







4 3 3 0.1446 A

4 2 3 0.1350 B

4 1 3 0.1329 C

3 3 3 0.1158 D

4 3 1 0.1147 D

3 2 3 0.1102 E

1 3 3 0.1098 E

4 2 1 0.1050 F

2 3 3 0.1046 F

1 2 3 0.1040 FG

4 1 1 0.1029 G

2 2 3 0.1005 H

205

3 1 3 0.0987 I

1 1 3 0.0987 I

2 1 3 0.0974 I

4 3 2 0.0947 J

3 3 1 0.0859 K

4 2 2 0.0850 K

4 1 2 0.0829 L

3 2 1 0.0802 M

1 3 1 0.0799 M

2 3 1 0.0747 N

1 2 1 0.0741 N

2 2 1 0.0705 O

1 1 1 0.0687 P

3 1 1 0.0687 P

2 1 1 0.0674 PQ

3 3 2 0.0659 Q

3 2 2 0.0602 R

1 3 2 0.0599 R

2 3 2 0.0547 S

1 2 2 0.0541 S

2 2 2 0.0505 T

1 1 2 0.0487 U

3 1 2 0.0487 U

2 1 2 0.0474 U






206

Appendix-13

Statistix 8.1 Phosphorus


Source DF SS MS F P

Plants 3 228.822 76.2740 7785.50 0.0000

Location 2 25.1918 12.5959 1285.70 0.0000

Season 2 246.660 123.330 12588.6 0.0000

Plants*Location 6 3.55473 0.59246 60.47 0.0000

Plants*Season 6 1.020E-30 1.701E-31 0.00 1.0000



Error 72 0.70538 0.00980

Total 107 504.934


Statistix 8.1 Phosphorus



4 10.815 A

3 7.893 B

1 7.487 C

2 7.148 D







3 8.9402 A

2 8.3094 B

1 7.7580 C







3 10.219 A

1 8.269 B

2 6.519 C







4 3 11.529 A

4 2 10.565 B

4 1 10.352 C

3 3 8.651 D

3 2 8.088 E

1 3 8.051 E

207

2 3 7.529 F

1 2 7.471 F

2 2 7.114 G

3 1 6.940 H

1 1 6.938 H

2 1 6.802 I








4 3 12.699 A

4 1 10.749 B

3 3 9.776 C

1 3 9.370 D

2 3 9.032 E

4 2 8.999 E

3 1 7.826 F

1 1 7.420 G

2 1 7.082 H

3 2 6.076 I

1 2 5.670 J

2 2 5.332 K








3 3 10.824 A

2 3 10.193 B

1 3 9.641 C

3 1 8.874 D

2 1 8.243 E

1 1 7.691 F

3 2 7.124 G

2 2 6.493 H

1 2 5.941 I







4 3 3 13.413 A

4 2 3 12.448 B

4 1 3 12.235 C

4 3 1 11.463 D

3 3 3 10.534 E

4 2 1 10.498 E

4 1 1 10.285 F

3 2 3 9.971 G

1 3 3 9.935 G

4 3 2 9.713 H

2 3 3 9.413 I

1 2 3 9.355 I

208

2 2 3 8.997 J

3 1 3 8.823 K

1 1 3 8.821 K

4 2 2 8.748 K

2 1 3 8.686 KL

3 3 1 8.584 L

4 1 2 8.535 L

3 2 1 8.021 M

1 3 1 7.985 M

2 3 1 7.463 N

1 2 1 7.405 N

2 2 1 7.047 O

3 1 1 6.873 P

1 1 1 6.871 P

3 3 2 6.834 P

2 1 1 6.736 P

3 2 2 6.271 Q

1 3 2 6.235 Q

2 3 2 5.713 R

1 2 2 5.655 R

2 2 2 5.297 S

3 1 2 5.123 T

1 1 2 5.121 T

2 1 2 4.986 T






209

Appendix-14

Statistix 8.1 Potassium


Source DF SS MS F P

Plants 3 32950.4 10983.5 7785.48 0.0000

Location 2 3627.63 1813.81 1285.70 0.0000

Season 2 5928.00 2964.00 2100.99 0.0000

Plants*Location 6 511.881 85.3135 60.47 0.0000

Plants*Season 6 2.222E-09 3.704E-10 0.00 1.0000



Error 72 101.575 1.41076

Total 107 43119.5


Statistix 8.1 Potassium



4 130.32 A

3 95.25 B

1 90.37 C

2 86.31 D







3 107.82 A

2 100.25 B

1 93.63 C







3 110.23 A

1 99.23 B

2 92.23 C







4 3 138.89 A

4 2 127.31 B

4 1 124.76 C

3 3 104.34 D

3 2 97.59 E

1 3 97.15 E

210

2 3 90.89 F

1 2 90.19 F

2 2 85.90 G

3 1 83.81 H

1 1 83.79 H

2 1 82.16 I








4 3 139.98 A

4 1 128.98 B

4 2 121.98 C

3 3 104.92 D

1 3 100.04 E

2 3 95.98 F

3 1 93.92 G

1 1 89.04 H

3 2 86.92 I

2 1 84.98 J

1 2 82.04 K

2 2 77.98 L







3 3 117.48 A

2 3 109.91 B

3 1 106.48 C

1 3 103.30 D

3 2 99.48 E

2 1 98.91 E

1 1 92.30 F

2 2 91.91 F

1 2 85.30 G








4 3 3 148.55 A

4 3 1 137.55 B

4 2 3 136.98 B

4 1 3 134.42 C

4 3 2 130.55 D

4 2 1 125.98 E

4 1 1 123.42 F

4 2 2 118.98 G

4 1 2 116.42 H

3 3 3 114.01 I

3 2 3 107.26 J

1 3 3 106.82 J

211

3 3 1 103.01 K

2 3 3 100.55 L

1 2 3 99.86 L

3 2 1 96.26 M

3 3 2 96.01 M

1 3 1 95.82 M

2 2 3 95.56 M

3 1 3 93.48 N

1 1 3 93.45 N

2 1 3 91.83 N

2 3 1 89.55 O

3 2 2 89.26 O

1 2 1 88.86 O

1 3 2 88.82 O

2 2 1 84.56 P

2 3 2 82.55 Q

3 1 1 82.48 Q

1 1 1 82.45 Q

1 2 2 81.86 Q

2 1 1 80.83 Q

2 2 2 77.56 R

3 1 2 75.48 S

1 1 2 75.45 S

2 1 2 73.83 S






212

Appendix-15

Statistix 8.1 Calcium carbonate (CaCO3)


Source DF SS MS F P

Plants 3 77.6067 25.8689 878.57 0.0000

Location 2 70.4817 35.2408 1196.86 0.0000

Season 2 177.360 88.6800 3011.77 0.0000

Plants*Location 6 10.5983 1.76639 59.99 0.0000

Plants*Season 6 3.845E-30 6.408E-31 0.00 1.0000



Error 72 2.12000 0.02944

Total 107 338.167


Statistix 8.1 Calcium carbonate (CaCO3)



2 5.7111 A

3 5.2111 B

1 4.8889 C

4 3.4333 D







1 5.7083 A

2 4.9750 B

3 3.7500 C







2 6.5778 A

1 4.2778 B

3 3.5778 C







2 1 6.6667 A

3 1 6.3667 B

2 2 6.2667 B

1 1 5.7667 C

3 2 5.5000 D

1 2 4.7333 E

213

2 3 4.2000 F

1 3 4.1667 FG

4 1 4.0333 G

3 3 3.7667 H

4 2 3.4000 I

4 3 2.8667 J








2 2 7.4778 A

3 2 6.9778 B

1 2 6.6556 C

4 2 5.2000 D

2 1 5.1778 D

3 1 4.6778 E

2 3 4.4778 F

1 1 4.3556 F

3 3 3.9778 G

1 3 3.6556 H

4 1 2.9000 I

4 3 2.2000 J








1 2 7.4750 A

2 2 6.7417 B

3 2 5.5167 C

1 1 5.1750 D

1 3 4.4750 E

2 1 4.4417 E

2 3 3.7417 F

3 1 3.2167 G

3 3 2.5167 H








2 1 2 8.4333 A

3 1 2 8.1333 B

2 2 2 8.0333 B

1 1 2 7.5333 C

3 2 2 7.2667 C

1 2 2 6.5000 D

2 1 1 6.1333 E

2 3 2 5.9667 EF

1 3 2 5.9333 EF

3 1 1 5.8333 F

4 1 2 5.8000 FG

214

2 2 1 5.7333 FG

3 3 2 5.5333 GH

2 1 3 5.4333 HI

1 1 1 5.2333 IJ

4 2 2 5.1667 IJ

3 1 3 5.1333 J

2 2 3 5.0333 J

3 2 1 4.9667 J

4 3 2 4.6333 K

1 1 3 4.5333 KL

3 2 3 4.2667 LM

1 2 1 4.2000 M

2 3 1 3.6667 N

1 3 1 3.6333 N

1 2 3 3.5000 NO

4 1 1 3.5000 NO

3 3 1 3.2333 OP

2 3 3 2.9667 PQ

1 3 3 2.9333 Q

4 2 1 2.8667 Q

4 1 3 2.8000 QR

3 3 3 2.5333 RS

4 3 1 2.3333 ST

4 2 3 2.1667 T

4 3 3 1.6333 U






215

Appendix 16. Calculation of Internal Rate of Return (IRR)

Discount rate for capital loan in Pakistan @10%

Year Total Annual cost

(C)

Discounted cost Total Annual benefit (B) Discounted benefits

C*(1+r)^(-t) B*(1+r)^(-t)

1 158299 138459 0 0

2 133695 102282 0 0

3 109236 73096 0 0

4 90583 53017 9519 5571

5 86000 44026 3336 1708

6 90965 40731 32726 14654

7 87273 34180 0 0

8 87592 30006 5837 2000

9 87719 26283 6671 1999

10 87782 23005 2057261 539155

1019144 565086 2115350 565086

Sum= Total Discounted Cost

(TDC)

Sum = Total Discounted Benefit

(TDB)

NPV = TDB – TDC IRR 14.33%

BCR = TDB/TDC NPV 0

IRR = r when NPV =0, that is, TDB =

TDC

BCR 1

C = Cost

B = Benefit

t = time (year)

Net Present Value (NPV), Benefit Cost Ratio (BCR), Internal Rate of Return (IRR)

216

Appendix 17. Calculation of Net present value (NPV) and Benefit cost Ratio (BCR)

Year Total cost Discounted cost C*(1+r)^(-t) Total benefit Discounted benefit B*(1+r)^(-t)

1 158299 143908 0 0

2 133695 110492 0 0

3 109236 82071 0 0

4 90583 61869 9519 6502

5 86000 53399 3336 2071

6 90965 51347 32726 18473

7 87273 44785 0 0

8 87592 40862 5837 2723

9 87719 37201 6671 2829

10 87782 33844 2057261 793163

1019144 659779

Sum = Total Discounted Cost (TDC)

2115350 825761

Sum = Total Discounted Benefit (TDB)

NPV = TDB – TDC NPV 165982

BCR = TDB/TDC BCR 1.25

IRR = r when NPV =0, that is, TDB = TDC Interest rate (base

case)

10%

C = Cost

B = Benefit

t = time (year)

217

Appendix-18 Average benefit cost analysis for one-hectare woodlot plantations in District Malakand

Investment and maintenance cost (Rs.) Benefit (Rs.)

Year Seedling

purchase

Transport

carrying

Labour/watch

and ward

Fencing Stacking Watering Thinning Pruning Opportunity

cost

Total cost Thinning Pruning Tree sale Total

benefit

1 8933 4157 44329 4297 4138 6445 86000 158299 0

2 778 617 36448 2960 1592 5300 86000 133695 0

3 17731 2291 636 2578 86000 109236 0

4 4583 86000 90583 9519 9519

5 86000 86000 3336 3336

6 4965 86000 90965 28557 4169 32726

7 1273 86000 87273 0

8 1592 86000 87592 5837 5837

9 1719 86000 87719 6671 6671

10 1782 86000 87782 7783 2049478 2057261

Total 9711 4774 98508 9548 6366 14323 9548 6366 86000 1019144 38076 27796 2049478 2115350

*Opportunity Cost: It was discussed with the tree growers of the research area. The average wheat production (yield) rate was 1655 kg per

hectare in 2017-18 and the average sale price was Rs. 52 per kg, so the wheat price for one year was approximately Rs. 86000 per hectare.

218

Appendix- 19 Questionnaire

1. Name of respondent: ___________________________

Age: ______________ Education ___________________

2. Occupation of the Respondent/Stake Holder

a) Farmer b) Business person c) Researcher d) Govt. Policy Maker

e) Common Person

3. Category of farmer: Small / Medium / Large

4. Specification of farmer’s land:

5. Income sources other than tree plantation/ year (Rs):

a) Business b) Job c) others

6. Willingness for plantation (Exotic/Indiginous)

a) Yes b) No

7. Purpose of plantation?

8. Type of block / woodlot plantation: exotic / indigenous

Name of species:

9. Size of block/woodlot and (Hectare):

10. Block/woodlot plantation spacing (ft.):

11. Previous land use pattern:

12. Description of timber tree species of block / woodlot plantation (Over storey

trees):

13. List of tree species newly introduced in the woodlot/block plantation:

14. Preferred size and age of exotic and indigenous tree seedlings for plantation in the

block / woodlot plantation:

15. Causes of damage of planted seedlings/saplings/poles/trees for raising tree

Plantation in the block / woodlot plantation:

16. Expenditure for raising woodlot/block plantation: (exotic / indigenous)

17. Valuation of woodlot/block plantation: (exotic / indigenous)

Name

of Tree

Species

No. of

trees

Average

height

(ft)

Average

diameter

(ft)

Present valuation/

Price

Future

rotation

valuation/

Price

Remarks

18. Economic return (net profit) from woodlot/block plantation considering time

frame:

Net Profit (Rs.) = Total Sale/Uses (Rs.) – Expenditure of plantation raising (Rs.)

19. Social and environmental benefits/losses from the monoculture woodlot/block

plantation of timber trees.

20. Economic, social and environmental benefits/losses from the undergrowths of the

woodlot/block plantation:

219

21. Is there any dispute about plantation between different tribe/institution in the

village?

If yes, what is the reason of the dispute?

a) Income distribution b) Boundary not marked c) Any other

22. Has exotic plantation effect on underground water table?

a) Yes b) No

23. Is exotic plantation increasing underground water table?

a) Yes b) No

24. Is exotic plantation decreasing underground water table?

a) Yes b) No

24. What was the depth of water table before plantation?

25. What is the depth of water table after plantation?

26. How many springs were there in the village before plantation?

27. How many springs are there in the village now?

28. What impact has plantation on stream discharge rate?

29. List of wild fauna found in woodlot/block plantations: (exotic / indigenous)

30. Potential timber tree species for monoculture/commercial block (woodlot)

plantations:

31. Comments on monoculture woodlot/block tree plantation: (exotic / indigenous)

Considering socio-economic aspect:

Considering environmental aspect:

32. Which sources of energy are used for fulfilling domestic/ commercial needs of

people in the area?

a) Fuel wood b) LPG c) Animal dungs d) others

33. Which species are used as fuel wood in the area?

a) Dodonea viscosa b) Eucalyptus c) Morus alba d) Populus e) other

34. What are the rates /mound in the nearby market of the village?


35. How many mound/ month of these species are sold in the market?


36. Present marketing condition of trees:

A. Market demand for timber: (High / Medium / Low)

B. Name of demanded timber species.

C. Market demand for fuel wood: (High / Medium / Low)

D. Name of demanded fuel wood species:

E. Timber/fuel wood sold by:

220

Appendix-20 Photographic Presentation

Photograph 1: Collection of undergrowth plants specimen

Photograph 2: Collection of data by using GPS in Pinus roxburghii plot

221

Photograph 3: Informal interview with local people during questionnaire survey

Photograph 4: Collecting informations from the local people through questionnaire

222

Photograph 5: Extraction of soil through supporters from the research plots

Photograph 6: Drying of soil sample in shade

223

Photograph 7: Woodlot plantations of Eucalyptus camaldulensis.

Photograph 8: Eucalyptus camaldulensis research plot

224

Photograph 9: Measurement of discharge rate of spring in the research area

Photograph 10: Acacia modesta research plot

225

Photograph 11: Robinia pseudoacacia

Photograph 12: Robinia pseudoacacia research plot

ph.d. thesis by kamran khan

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