Kahuta National Park

PHYTOSOCIOLOGY, FLORAL DIVERSITY AND CONSERVATION STATUS OF MURREE-KOTLI SATTIAN- KAHUTA NATIONAL PARK

WASIM AHMED 07-arid-1320

Department of Botany Faculty of Sciences PirMehr Ali Shah Arid Agriculture University Rawalpindi Pakistan 2019

PHYTOSOCIOLOGY, FLORAL DIVERSITY AND CONSERVATION STATUS OF MURREE-KOTLI SATTIAN- KAHUTA NATIONAL PARK

WASIM AHMED (07-arid-1320)

A thesis submitted in the partial fulfillment of the requirements for the degree of

Doctor of Philosophy in Botany

Department of Botany Faculty of Sciences PirMehr Ali Shah Arid Agriculture University Rawalpindi Pakistan 2019

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DEDICATED

MY LOVING PARENTS

CONTENTS Page

List of Tables ix

List of Figures x

List of Abbreviations xii

Acknowledgement xiii

ABSTRACT 1

1 GENERAL INTRODUCTION 3

1.1 THE STUDY AREA 3

1.1.1 Location and Description 3

1.1.2 Geology 4

1.1.3 Soil 5

1.1.4 Climate 5

1.1.4.1 Temperature 7

1.1.4.2 Rain fall 7

1.1.4.3 Snow fall 7

1.1.4.4 Relative humidity 8

1.1.5 Hydrography 8

1.1.6 Natural Vegetation 13

1.1.7 Wild Life 13

1.1.8 Brief History 14

1.1.9 People 15

1.1.10 Agro Ecology 16

1.1.11 Biotic Factors 16

1.2 PHYTOSOCIOLOGY AND VEGETATION 18

1.3 BIODIVERSITY AND CONSERVATION 20

2 FLORISTIC ENUMURATION AND PHYTOSOCIOLOGY 22

2.1 INTRODUCIOTN 22

2.2 REVIEW OF LITERATURE 31

2.3 MATERIAL AND METHODS 37

2.3.1 Physiognomy 37

2.3.2 Plant Collection and Identification 38

2.3.3 Phtosociological Studies 38

2.3.3.1 Sampling procedure 38

2.3.3.2 Cover scale 39

2.3.3.3 Frequency 39

2.3.3.4 Density 40

2.3.3.5 Coverage 40

2.3.3.6 Change to relative values 40

2.3.3.7 Importance value Index 40

2.3.3.8 Soil analysis 41

2.3.3.9 Diversity indices 41

2.3.3.9.1 Species richness 41

2.3.3.9.2 Margalef richness 41

2.3.3.9.3 Menhinick richness 42

2.3.3.9.4 Simpson Diversity Index 42

2.3.3.9.5 Shannon-Wiener Diversity Index 42

2.3.3.9.6 Pielou evenness Pielou 44

2.3.3.10 Iindicator value 44

2.3.3.11 Life form (biological spectrum) 44

2.3.3.12 Leaf spectra 46

2.3.4 Data Analysis 45

2.3.4.1 Data organization 45

2.3.4.2 Vegetation analysis 46

2.3.4.2.1 Cluster analysis 46

2.3.4.2.2 Indicator species analysis 46

2.3.4.2.3 Ordination analyses 47

2.4 RESULTS 47

2.4.1 Florestic Enumeration 47

2.4.2 Phytosociology 76

2.4.2.1 Plant communities 77

2.4.2.1.1. Themeda-Galium-Gerbera (TGG) 77

2.4.2.1.2 Dodonaea-Carissa-Dalbergia (DCD) community 80

2.4.2.1.3 Adiantum-Olea-Xylosma (AOX) community 82

2.4.2.1.4 Justicia-Mallotus-Asplenium (JMA) community 84

2.4.2.1.5 Micromeria-Taraxacum-Dichanthium (MTD) 86

community

2.4.2.1.6 Myrsine-Oplismenus-Pinus (MOP) community 105

2.4.2.1.7 Pinus-Viburnum-Daphne (PVD) community 111

2.4.2.2 Ordination of plant communities 113

2.4.2.2.1 Detrended correspondence analysis 113

2.4.2.2.2 Canonical correspondence analysis 114

2.5 DISCUSSION 121

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2.6 CONCLUSION 133

3 PLANT BIODIVERSITY AND CONSERVATION 135

3.1 INTRODUCTION 135

3.2 REVIEW OF LITERATURE 137

3.3 MATERIAL AND METHODS 141

3.3.1 Impotence Value Index 141

3.3.2 Ethnoecological Perception 141

3.3.3 I.U.C.N Categorization 141

3.4 RESULTS 142

3.5 DISCUSSION 142

3.6 CONCLUSION OF BIODIVERSITY 144

4 GENERAL DISCUSSION 156

CONCLUSION AND RECOMMENDATION 165

SUMMARY 168

LITERATURE CITED 170

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List of Tables

Table Page

1.1 Average Climatic Data Pakistan Meteorological 9

Department, Islamabad.

2.1 Comparision of flora of Murree-KotliSattian-Kahuta 50

National Park with flora of Pakistan.

2.2 Floristic list of vascular plants of Murree-KotliSattian- 51

Kahuta National Park, Pakistan.

2.3 Pairwise comparison (MRPP) of seven plant 75

communities MurreeKotliSattian

2.4 Indicator species analysis (ISA) of the plant 87

communities of the study area

2.5 Environmental variable and cover percentage of 103

vegetation layers in the seven communities of

MureeKotli-SattianKahuta National Park.

2.6 Diversity indicies of communiite from MureeKotli- 108

SattianKahuta National Park

2.7 Statistis of detrended correspondence analysis. 118

2.8 Statistis of canonical correspondence analysis. 119

2.9 Testing of individual constrained axes of constrained 120

analysis (Permutation test on all axes).

2.10 Ranking and Contribution of studied variables in 121 explaining variation in species data.

2.11 Conservation status of plant specis of Murree- 145 KotliSattian-Kahuta National Park

List of Figures

Figure Page

1.1 Map of MureeKotli-SattianKahuta National 6

Park(MKSKNP)

1.2 Monthly average minimum and maximum 11

temperatures, raletive humidity and rainfall for the

years 1910 – 2016 (Source; Department of Metrology

Islamabad, Pakistan)

1.3 Average climatic data of district Rawalpindi 12

2.1 Distribution of samples in the study area 41

2.2 Floristic composition of vascular flora of Murree- 49

KotliSattian-Kahuta National Park with flora of

Pakistan

2.3 Top 10 families of vascular flora of Murree- 69

KotliSattian-Kahuta National Park,

2.4 Habit form of the flora of Murree-KotliSattian-Kahuta 70

National Park

2.5 Regional status of the flora of Murree-KotliSattian- 71

Kahuta National Park

2.6 Determination of the number of ecologically 73

meaningful communities in MurreeKotliSattianKahuta

national park, Pakistan

2.7 Cluster dendrogram of 246 samples based on 74

Sorensen measures showing 7 plant communitie

2.8 Biological spectrum (Life form) of MureeKotli- 109

SattianKahuta National Park

2.9 Leaf spectra of the flora of MureeKotli-SattianKahuta 110

National Park

2.10 DCA biplot showing distribution of vegetation 115

samples and their possible relationship with the

supplementary variables

2.11 DCA biplot of specis and environmental variables 116

2.12 CCA species biplot 117

2.13 Summary of conservation status of the flora of 154

Murree-KotliSattian-Kahuta National Park

List of Abbreviations

AH Annual herb

C Climber

Co. St Conservation staus

C Constent

D Decreasing

DS Diciduous shrub

DT Diciduous tree

ES Evergreen shrub

ET Evergreen tree

Ha Habit

HKH Himalaya Hindokush

IVI Importence value index

I Increasing

IV Indicator value

MKSKNP Murree-KotliSattian-Kahuta national park

P Parasite

PH Perennial herb

TIV Total Indicator value

T Trend

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ACKNOWLEDGMENTS

All praise and glory to theAlmighty Allah, the most benevolent and merciful and whose blessing enabled me to complete this task.My heartiest tributes are also due to Holy Prophet, Hazrat Muhammad (P.B.U.H), who is a beacon of light and acme of knowledge.

I feel great pleasure in expressing my sincerest thanks to ever affectionatesupervisor Dr. Rahmatullah Qureshi, Associate Professor,

Department of Botany, PMAS Arid Agriculture University Rawalpindi, for his skillful supervision, sincere support and inspiring guidance throughout this study.

This thesis would not have been possible to finish in time without his input and encouragement. I would like to express my appreciation for providing necessary facilities and dynamic guidance in the planning, execution and write up stages of the effort.

I have honor to offer my deep sense of gratitude to member of my supervisory committee, Prof. Dr. Muhammad Arshad Chairman Department of

Botany, PMAS Arid Agriculture University Rawalpindi, and for his kind supervision and skilled dvises, generous support and guidance.

My sweet and loving parents worthy to be given the credit of decorating my life with ornament of knowledge. Their keen interst, financial support and whole

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hearted prayers are the source of my success.

I feel profound sense of gratitude for Dr. Muhammad Ilyas whos generous quidence, help and inspiration enabled me to accomplish this great task.My special thanks go to Dr. Zafeer Saqib and Mr. Muhammad Arshad Khan, whose assistance, cooperation and healthy suggestions helped me a lot in carring out this task in general and understanding computer softwares and interpretation of data in particular. I am very thankfull to Dr. Zahidullah and Dr. Tanveer for their help in plant identification.

I can not forget the help of my lab fellows, Mirza Faisal Qaseem, Ms.

Rehana Kouser, Mr. Muhammad Maqsood.

My deepest gratitude goes to my brother Mr. Nadeem Ahmed Awan who has always accompanied me to the rigorous field trips. and my sisters for whole hearted prayars. I am thankful to my wifefor her support and help.

May all live long & be happy forever.

(Wasim Ahmed)

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ABSTRACT

To understand the ecosystem dynamics with respect to plant ecology it is inevitable to understand floristic composition, spatial and temporal distribution and all the related phytosociological aspects of plants in an ecosystem. Murree-Kotli

Sattian-Kahuta national park (MKSKNP) is located on the lateral spur of the sub-

Himalayan Mountains and declared as a national park in 2009. MKSKNP is rich in plant biodiversity but have not been previously subjected to quantitative ecological studies through statistical tools and techniques. The present study was conducted from August, 2013 till September, 2015 to fill the research gap. Species attributes were measured by stratified random sampling design. Three hundred and fifty two plant species were recorded from 246 samples using the quadrat method. There were seven plant communities, identified by using classification and ordination techniques (PC-ORD and CANOCO) viz., 1) Themeda-Galium-Gerbera community, 2) Dodonaea-Carissa-Dalbergia community, 3) Adiantum-Olea-Xylosma community, 4) Justicia-Mallotus-Asplenium community, 5) Micromeria-

Taraxacum-Dichanthium community, 6) Myrsine-Oplismenus-Pinus community and 7) Pinus-Viburnum-Daphne community. Indicator species of each community were determined by Indicator species analysis. Multi-Response Permutation

Procedure detected a significant difference (p 0.05) in species composition of plant communities. Biodiversity of the communities were established by different diversity and evenness indices, while the conservation status was ascertained according to the categories of IUCN. Plant species composition and distribution dynamics were mainly determined by al-

itude, latitude and soil texture, as shown by Detrended correspondence analysis

(DCA) and canonical correspondence analysis (CCA). CCA detected nine significant [p (adj) < 0.5] environmental variables which cumulatively explain

13.10% of variation in species data the species composition

The dominant life forms were the Hemicryptophytes (28.89%) and

Therophytes (27.98%), whereas Microphylls (35.41%) and Nanophylls (35.41%) were the prevailing leaf spectra of the study area. Overall, 624 plant species comprised of 361 genera and 106 families. (Including 24 ferns species, 4 species of gymnosperms, 144 monocots and 452 dicots), were recorded from the study area.

Comparing with regional floras, most of the species were native to the area (508

Spp.). The individuality of the region is depicted by the endemic flora, which is quite significant because of limited distribution (Ali, 2008), are of great interest for taxonomists and ecologist (Khan, 2013). The Western Himalayas is endowed with rich endemic flora (300 species), (Ali et al.,1972–2009), of which five plant species viz. Viola makranica, Buxus papillosa, Rydingia limbata, and Gentiana argentea which are endemic to Pakistan were also reported from the study area. There were

16 plant species recorded for the first time from MKSKNP, Rawalpindi.

The study helps understanding the plant diversity and related biodiversity issues of the MKSKNP. The finding of the study will help the ecologist, conservationist and foresters to tackle biodiversity crises and improving the bioresource basis of the study area.

Chapter 1

GENERAL INTRODUCTION

1.1 THE STUDY AREA

1.1.1 Location and Description

Murree-Kotli Sattian-Kahuta National Park (MKSKNP) lies at 33º 21´ to

34º 01ʹ N latitudes and 73º 11ʹ to 73° 38ʹ E longitude in district Rawalpindi,

Pakistan. The total area of the park is 934 Km2. The average elevation varies from

500 to 2270 meters. The study area is located on the lateral spur of the sub-

Himalayan Mountains (Abbasi et al., 2002) bounded by river Jhelum in the east,

Islamabad in west, khyber Pakhtunkhwain in the north and Gujar Khan in the south. The topography of the study area, at higher altitude is mainly composed of rugged terrain with narrow valleys whereas relatively flat topography is predominant in the lower elevation. The hilly area contains valleys created by fast flowing running water of streams and rivers. The water courses are gradually made deeper by the fast flow of water which erodes the soil and carries valuable mineral to low lying downstream areas, resulting in alluvial deposits making these areas most fertile then hilly areas for cultivation.River Soan flow from the northwest to southwest of the Murree-Kotli Sattian-Kahuta national park, whereas River Jhelum runs through the eastern region of the study area and separates the area from

Kashmir regions in the east (Hussain et al., 2014). Along with the rivers, the study area contains many streams which cut the area into narrow and deep gorges. These streams flow with great speed particularly in the monsoon season, resulting in seasonal floods which cause soil erosion at a very high rate. The fast flowing water

of these streams is ladened with silt and boulders which is deposited in a low lying area, making these lands even more fertile.

1.1.2 Geology

The 2500 km long Himalayan range was created during Eocene time by the collision of the Indian plate with the Eurasian plate along a suture zone about 20 million year ago creating rapidly uplifting region (Abbasi et al., 2002; Khan et al.,

2011) and producing the complex geological stratifications (Sheikh et al.,

2008).The Murree-Kotli Sattian-Kahuta national park is located on a lateral spur of the sub-Himalayan Mountains (Khan et al., 2011) also known as The Himalayan foothills (Gansser, 1964), towards the southwest margin of Himalaya (Ellis et al.,

1994) It is the part of Shiwalik terrains formed of anticline. The area fall in the climatic division of the subtropical continental highlands (Khan et al., 2011) tertiary and quaternary sediments predominate the area (Ahmad, 2011) with widespread rock formation of Shiwalik type (Gansser, 1964).

Area is geologically immature (Khan et al., 2011) and made up of Miocene sandstone and Eocene Mummulitic limestone. Lithologically, area consists of limestone, clay stone hard gray to reddish and even white sandstone inter-bedded with soft red calcareous shale and alluvial deposits belonging to Sirmar and

Shiwalik series of sub Himalayas system (Khan et al., 2011; Saqib et al.; 2014).

Geologically the study area is predominantly comprised of Cretaceous and Tertiary sedimentary strata and the relief is characterized by deeply incised valleys.

These valleys were created due to rapid tectonic uplift duringand since the

Tertiary period (Ellis et al., 1994).

1.1.3 Soil

The soil of Murree-Kotli Sattian-Kahuta national park can be classified as

Entisol (very poorly developed, recent soils) and Inceptisol (soils in an early stage of formation) orders with non-calcareous form at higher altitude and calcareous forms at lower altitudes (Ellis et al., 1994; Ullah, 2009). The soils are typically loamy and very shallow. Their development being restricted by the steepness of slopes (Ellis et al., 1994). The soil of the study area is residual as well as of transported. The soil of the mountains is residual derived from shale and sandstone, whereas the soil of steep slope regions is colluvial with very low soil thickness

(Saqib et al.; 2014). In the valleys, soil is of alluvial type. The soil is calcareous, varies from moderately coarse to moderately fine in texture having silt, sand than clay content (Ullah, 2009). The soil of open places has low organic matter compare to the soil under vegetation cover which has a high organic content. The soil is slightly acidic and the soil of the area is mostly clayey and clay loam type with few areas having loamy soil whereas the river banks contain sandy loam.

1.1.4 Climate

Climatically the study area declines in subtropical to temperate zone. Such a vast variation within a small geographical region can be ascribed to differences in altitude, to diverse topography amount and duration of winter snowfall and varying vegetation. The weather has distinct seasons. Generally, the climate is cooler at higher altitude and warmer at lower one with a short spring and autumn seasons

Monsoon winds are the main source of precipitation and also a primary force controlling erosion and climatology and hence the topography and vegetation of the

Fig. 1.1.Map of Murree Kotli-Sattian Kahuta National Park.

Himalayas. Metrological data from 2010-2016 is given in (Table 1.1a-d).

1.1.4.1 Temperature

Owing to considerable topographic and altitudinal variations, the study area shows a wide variation in temperature. The area has a distinct pattern of four seasons viz. Summer, Autumn, Winter and Spring. Based on temperature data of the last seven years (2010-2016) the mean monthly maximum and minimum temperature are 32.09°C and 1.22°C respectively. The hottest month of the year is

July with an average maximum temperature of 32.09°C. Winter season at the higher elevation of Murree-Kotli Sattian-Kahuta national park is relatively long and severe compare to the low elevation areas where conditions are vice versa. January being the coldest month of the year has a mean monthly maximum and minimum temperature of 14.12°C and 1.2°C respectively.

1.1.4.2 Rain fall

The mean annual rainfall is 1484mm of which 62% rainfall occurs in summer (Monsoon season) with the rainfall of 326.55mm and 273.75mm in the months of July and August respectively. The other months in which maximum winter rainfall occurs are February and March with the average rainfall of

142.13mm and 154.41mm respectively. May (61.97mm) and June (108.28mm) are the driest months of the summer while October and November and are the driest months of the autumn season with the average rainfall of 57.30mm and 15.79mm.

1.1.4.3 Snow fall

Snowfall occurs at the higher elevation of MKSKNP during the winter

season from November to April, reaching the peak in the month of February. The higher elevation of the study area receives about two meters of snow in the winter season (Ahmed et al., 2006). The gradual melting of the snow ensures the moisture provision to the plant for short growing summer season.

1.1.4.4 Relative humidity

There is a wide variation in relative humidity values with respect to difference in altitude, aspect and vegetation cover. Generally July, August and

September are more wet months due to heavy monsoon rainfall with the relative humidity of 77.05%, 81.67% and 76.05% respectively. The second most humid season is winter season with January and February is the most humid months with relative humidity values of 70.99% and 74.64% respectively (Table 1.1.d)

1.1.5 Hydrography

The area contains two main rivers the eastern edge of the park is separated from Kashmir by river Jhelum; whereas the western areas of the park contain Soan

River which has the Simly dam, built in 1983 on the river to meet the water requirements of capital city Islamabad (Hussain et al., 2014) whereas the Mangla

Dam was constructed between 1961 and 1967 across the Jhelum River which is generating about 1000 megawatt electricity. Along with the rivers, the study area contains certain main streams which are locally called Khad and Kas. Kas Kohati,

Khad Chajana and Khad Thoon flow eastward from the top of the park and fall in river Jhelum near Kohati village, Koonal village and Thoon. Khad Baiga and

Lehtrar Kas flow westward and meet the Soan River near Dalla Chapar. Ling nullah arises from Lehtrar hills and joins the Soan River, whereas Knshi stream

Table 1.1. (a-d) AverageClimatic Data collected by Pakistan Meteorological Department, Islamabad.

a. Mean Monthly Rainfall (mm) values of Murree-Kotli Sattian-Kahuta National Park, Pakistan YEAR JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC Sum 2010.00 23.05 184.75 63.20 63.80 73.70 78.75 462.35 240.70 100.00 34.10 2.00 23.35 1349.75 2011.00 12.85 156.85 79.75 153.95 24.10 136.25 278.50 220.35 133.50 47.80 15.50 1.00 1260.40 2012.00 67.80 85.00 33.20 82.10 28.85 36.25 145.65 375.95 318.60 13.15 6.00 103.15 1295.70 2013.00 17.90 261.05 72.30 70.20 26.65 198.60 264.05 550.85 188.55 36.15 10.65 7.10 1704.05 2014.00 19.90 87.85 320.20 28.95 123.05 78.00 298.65 174.30 373.20 32.00 13.50 0.00 1549.60 2015.00 36.20 135.05 266.95 229.75 72.90 134.05 507.50 200.75 171.60 221.4 62.85 30.70 2069.70 0 2016.00 52.00 84.35 245.25 28.45 84.55 96.05 329.15 153.35 68.60 16.50 1.00 0.50 1159.75 Average 32.81 142.13 154.41 93.89 61.97 108.28 326.55 273.75 193.44 57.30 15.93 23.69

b. Mean Maximum temperature (°C ) values of Murree-Kotli Sattian-Kahuta National Park, Pakistan YEAR JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC Average 2010 16.95 14.40 23.55 27.80 29.65 31.70 29.70 27.25 27.30 25.65 22.20 16.80 24.41 2011 13.50 13.20 20.50 23.25 31.60 31.50 28.40 27.95 27.80 25.55 21.90 17.35 23.54 2012 11.50 12.25 19.25 24.35 29.05 33.90 31.70 28.15 26.70 24.65 20.45 15.50 23.12 2013 13.65 13.60 20.45 23.85 30.10 31.75 29.05 27.00 26.90 25.35 19.95 16.40 23.17 2014 14.20 13.70 16.05 22.75 27.25 32.75 29.25 28.85 26.80 24.05 21.05 16.80 22.79 2015 14.43 15.61 17.56 23.56 29.09 30.28 27.75 28.77 28.55 25.35 19.51 17.33 23.15 2016 14.61 17.78 19.34 25.30 31.51 32.77 29.38 28.80 28.58 26.65 21.82 20.32 24.74 Average 14.12 14.36 19.53 24.41 29.75 32.09 29.32 28.11 27.52 25.32 20.98 17.21

Table 1.1. (a-d) Average Climatic Data collected by Pakistan Meteorological Department, Islamabad.

c. Mean Monthly MinimumTemperature (°C ) values of Murree-Kotli Sattian-Kahuta National Park, Pakistan YEAR JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC Average 2010 2.35 4.10 11.00 14.65 16.85 18.60 20.20 20.40 17.35 12.70 7.85 1.85 12.33 2011 -0.10 3.25 8.55 11.20 18.60 20.20 19.70 19.85 18.10 12.55 9.00 1.80 11.89 2012 -1.00 0.95 7.00 12.30 16.30 20.45 21.35 20.35 17.65 11.95 6.90 2.60 11.40 2013 1.10 3.75 8.65 11.70 16.60 20.10 20.50 19.80 17.95 14.35 6.05 2.50 11.92 2014 0.50 3.00 5.90 11.25 15.05 19.80 20.85 19.40 17.10 13.15 7.00 2.30 11.28 2015 2.32 5.23 8.14 13.23 17.54 19.21 20.73 20.03 17.23 13.76 8.56 3.83 12.48 2016 3.36 4.53 9.66 13.46 18.96 21.05 20.24 19.88 18.66 14.16 8.63 5.64 13.19 Average 1.22 3.54 8.41 12.54 17.13 19.92 20.51 19.96 17.72 13.23 7.71 2.93

d. Relative humidity (%), values of Murree-Kotli Sattian-Kahuta National Park, Pakistan YEAR JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC Average 2010 60.34 78.00 57.50 53.00 48.50 49.50 73.50 85.00 76.50 67.00 66.50 63.50 64.90 2011 71.37 77.27 27.00 59.65 46.32 60.93 79.60 80.81 77.63 64.31 65.68 66.97 64.79 2012 80.48 78.95 59.21 61.27 46.53 39.18 65.76 83.26 77.47 62.26 66.78 66.50 65.64 2013 72.76 75.29 62.26 59.95 43.11 58.67 80.35 88.00 79.22 74.71 64.02 73.31 69.30 2014 69.97 75.39 73.94 58.75 55.94 48.68 74.77 76.90 78.25 68.37 61.00 58.76 66.73 2015 71.10 71.59 69.39 66.03 50.55 53.88 84.02 79.84 66.58 66.11 67.63 68.69 67.95 2016 70.89 66.00 69.39 56.00 51.58 59.32 81.37 77.85 76.72 63.05 59.07 61.81 66.09 Average 70.99 74.64 59.81 59.24 48.93 52.88 77.05 81.67 76.05 66.54 64.38 65.65

350.00

300.00

250.00

200.00 Max. T Min. T 150.00 RF. RH. 100.00

50.00

0.00 JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC

Fig. 1.2.Fig Monthly average minimum and maximum temperatures, relative humidity and rainfall for the years 2010–2016 (Source; Department of Metrology Islamabad, Pakistan).

11 11

200.00 Min. T Max. T RH RF 180.00 160.00 140.00 120.00 100.00 80.00 60.00 40.00 20.00 0.00 2010 2011 2012 2013 2014 2015 2016

Fig. 1.3.Average climatic data of district Rawalpindi.

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rises from Kahuta hills and joins river Jehlum. Most of the cultivated land is rain fed. The principal source of precipitation is monsoon rainfall and winter snowfall.

1.1.6 Natural Vegetation

Champion et al. (1965) classified the vegetation types of the area into following forest types.

1. Subtropical broad leaved forests: The forest type is found in lower dryer part of the area containing some characteristic tree species like Olea ferruginea, Cassia fistula, Pistacia integerrima, Bauhinia veriegata, Flacortia indica and Acacia modesta. The shrub layer contains Sageretia thea, Carissa oppaca, Justicia adhatoda and Woodfordia fruiticosa etc.

2. Siwalik Chir Pine forest: the forest occupy the middle elevation of the park which contain the following plant species, Pinus roxberghii, Pyrus patia, Quercus incana, Xylosma longifolia, Myrsine Africana, Berberis lyceum, Rubus ellipticus,

R. niveus, R. ulmifolius, Punica granatum, Rosa mashcata and Indigofera heterantha etc.

3. Himalaya Moist Temperate Forest: The characteristic species of this part arePinus Wallichiana, Aesculus indica, Quercus dilatata, Viburnum cotinifolium,

V. grandiflorum, Lonicera quinquelocularis, Berberis lyceum, Daphne papyracea,

Viola cancescens, Clematis montana, Dioscorea deltoidesand Polygonatum spp.

1.1.7 Wild Life

The study area is rich in biodiversity, which is decreasing at alarming rate

due to human activities particularly in the form of habitat destruction. The study area contains a variety of mammals, including Panthera pardus (Leopard; local name, Seehn), which has been brought to the brink of extinction due to habitat destruction and habitat fragmentation. The other animal include Vulpes vulpes (Red fox; Local name Gethor), Muntiacus muntjak (Barking dear; Local name,

Kaker),Macaca mulatta (Rhesus Macaque; Local name, Buja), Sus scrofa (wild boar; Local name Soar), Hystrix indica (porcupines; Local name, Segh) and

Pipistrellus tenuis (Indian Pygmy Bat; Local name, Chamgither).The area hosts a large number of birds of prey include Accipiter nisus melaschistos(Eurasian

Sparrow Hawk; Local name, Basha), Accipiter badius cenchroides (Indian sparrow

Hawk; Local name, Shikra/Basha)Aquila rapax nipalensis (Steppe Eagle; Local name, Hill) Aquila pomarina (Lesser Spotted Eagle), Circus aeruginosus (Marsh

Harrier) Falco tinnunculus (Eurasian kestrel; Local name, Basha), Gyps himalayensis (Himalayan Griffon Vulture; Local name Hillor), Gyps fulvus

(Eurasian Griffon Vulture; Local name Hillor), Milvus migrans migrans (Black kite), Milvus migrans lineatus (Eared or large Indian kite), Milvus migrans govinda

(Indian kite) and Pernis ptilorhynchus (Crested Honey Buzzard).

A variety of reptile such as snakes, lizards and varanus are also present in the study area. Along with these animals the area hosts a number of amphibians species such as Murree Hill frog. The area also hosts a large number of insect spices as also (Masroor, 2011; Rais et al., 2014; Yousaf and Manzoor, 2014).

1.1.8 Brief History

The area had been occupied by different tribes and religions in the past.

Toward the end of 10th century Islam came to this region. Muhammad Ghaznavi bestowed the district of Ghakkar shah, whosThe descendent remain in the district for about 8 centuries. In 1765, the Ghakkar chief was slain in battle and the district became under the Shik rule which could not stand their grounds for very long and the country was past to the British government in 1849. During the time of Akbar

Ghakkar territory was distributed between rival chiefs. Pharwala fort was the head quarter of the mountainous region; the last chief of Pharwala was Sultan Muqarrab whose successors were defeated by Sardar Gojar sigh. Then these hills were granted to Gulab Singh who ruled the area for quite some time, and the area finally become under British rule. After the annexation of the area to British dominions, this region was assessed by Major Abbott. Murree was then called was first identified as a potential hill station by Major James Abbott (Indian Army officer) in

1847. The town's early development was done in 1851 by President of the Punjab

Administrative Board, Sir Henry Lawrence (Saqib et al.; 2014; DCR, 2017).

1.1.9 People

The projected human population calculated for district census report (DCR.,

2017) is about0.38 million. The population density is 374 persons per square kilometer. The average annual growth rate is 2.7 percent. The predominant population is the rural population. There are different ethnic groups inhabiting the area like Ghaghar, Satti, Abbasi (dhoond), Sayad, Awan, Alvi, Mughal, Chauhans

Qureshi, Gujjars, Rajput, janjuha and kethwal etc. (Saqib et al.,2014).

Pothowari is the main language which predominate the lower elevation of the Murree-Kotli Sattian-Kahuta national park and a muchrelated accent called

Pahari is spoken in the upper elevation. Average literacy rate is 63.9 percent.

1.1.10 Agro Ecology

As the area is mainly rain fed the agricultural economy depends on rainfall and to some extent on water provided by mountain streams. The area is cultivated up to around 2000 m, with cereals and fruit usually on terraced slopes, although there are also large areas which are uncultivated and possess thin soil with little vegetation cover (Ellis et al., 1994). The crops commonly grown in the study area are wheat, maize, Barlay, Millet, Musterd, Sunflower, Gram, Pulses Potato,

Tomato,Turnip, Radish, Cucumber, Squash, Pumpkins, Bringle, Lady finger, etc.

Fruit trees like Citrus, Apple, pear, Plum, Mango, Banana, Guava, Appricot, Peach and walnut are grown in the area (Ullah, 2009: Asghar et al., 2012).

In most of the remote areas of the MKSKNP, old mean of agriculture are still practiced where the field are plowed with bullocks. Grass is harvested and stored to be used as dry fodder which is fed to cattle during the winter months.

Most of the household keeps goats, cow or buffalo. The livestock provides the livelihood to the local people because the rangelands of the area are full of nutritious and palatable species of grass, herbs, shrubs and trees (Shaheen et al

2011b; Shaheen et al., 2014). Similarly, every year more than 1 million tourists visit Murree and this figure is growing by 5% per year during periods of political calm (Khan et al., 2011).

1.1.11 Biotic Factors

The vegetation of the study area is severely exploited for medicinal

plantcollection, timber collection and fuel wood extraction hence the area is under extreme pressure of deforestation. In addition to these factors overgrazing by domestic animals is another major factor causing the deterioration of the vegetation of the study area.

Pinus wallichiana and Pinus roxburghii area frequently dislodged for house construction whereas Quercus incana, Quercus dilatata, Pyrus patia, Acacia nilotica, Acacia modesta, Olea ferrogenia are the tree species which are preferably cut for fuel likewise Dodonia viscose and Vibernum grandiflorum are preferred shrubs for the same purpose. The medicinal plant under higher exploitation isViola canasense, Bergenia ciliata, Berbaris lyceum and Swertiawhich are a few of the most frequently used medicinal plants species in the study area.

Extensive cutting of fuel wood, timber and medicinal plant along with unchecked over grazing resulted in a decline of vegetation cover in the area. The rate of regeneration is very slow compare to the removal of vegetation, which not only resulted in the decline of the aesthetic sense of the study area but also caused other serious problems like soil erosion. The shrub density is significantly low in pine forest region and particularly in south facing slopes which can be attributed to the fact that local people deliberately remove the shrubby plant from certain areas to ensure the extensive growth of grasses which they harvest before the winter months to support the cattle during winter season.

The forest at lower elevation (Subtropical broad leaved forests) has high number of shrubs, predominantly of none palatable species like Dodonaea viscosa and Justicia adhatoda. This forest type is the most devastated forest by human

activities like deforestation for fuel wood collection and very high grazing pressure.

The pine forest dominated by the Pinus roxburghii is also under high grazing pressure and selective pressure of human particularly for grass, which reduces the plant biodiversity. Forest fire intentional and natural one is very common in Chir pine forest, which is a contributing factor in low species diversity in the forest type.

Himalayan moist temperate forest at the higher elevation is the most diverse forest type of the park with maximum species diversity compare to other forest types in the study area.

1.2 PHYTOSOCIOLOGY AND VEGETATION

Vegetation is the plant composition of any given area (Arora, 1987) which possesses characteristic physiognomy (Hussain and Ilahi, 1991) including all plant forms present on the earth (Hargreaves, 2008). Plant community is the characteristic assemblage of plant species which is determined by the interaction of vegetation with other biotic and abiotic component and can easily be recognized from a nearby community (Malik and Husain, 2006).

The unique species aggregation of an area reflects the effect of environment on vegetation. Vegetation complex fluctuates in correspondence with the environmental fluctuation, which might be a seasonal or long term fluctuations

(Mandal and Joshi, 2014). The vegetation is strongly depended on climate and soil, disturbance in any of the factors indeed affects the other factors (Ilyas et al., 2015).

Vegetation thus provides valuable information about the health of an ecosystem.

The information can be used to manage an ecosystem, indicate habitat of animal and productivity of the area. Different environmental variables have different

effects on the vegetation but all the environmental variables have a cumulative dynamic effect on plant species composition of an area (Billings,

1952).Phytosociological study deals with plant communities based on composition, development and co-occurrence of species (Ilyas et al., 2015) which is an extremely important issue in ecological research (Zhao et al., 2010). It deals with the species composition of plant communities, their evolution and the relationships between the species present. Gradient analysis and classification are its complementary tools (Ewald and Díaz, 2003). The phytosociological study mainly focuses on functioning and description of vegetation, by providing detail information about the composition of plant species particularly the indicator species which control the composition of a community (Rawat and Chandra, 2014).

Study of vegetation has long been given the importance not merely because of its fundamental role in understanding of an ecosystem but because of the fact that it modifies the ecosystem and determines the vegetation composition and functioning (Ferreira et al., 2015). Different tools and techniques have been proposed to study the plant ecology and phytosociology with respect to vegetation type and objective of the study (Dufrene and Legendre, 1997; Kent, 2011). No aspect of phytosociology hasbeen granted more importance than the classification of the communities (Whittaker, 1962). With the passage of time enormous literature has been published encompassing may aspect of phytosociology. Now a day’s phytosociology attempts to explain vegetation patterns and the processes governing vegetation assembly and dynamics in all temporal and spatial scales

(Pott, 2011). During an early stage of development, the characteristics of vegetation were studied by ocular estimation in many studies rather than by exact numerical

measurements, which could not explain the potential ecological phenomenon. To resolve the problems related to this rough estimation approach in plant ecology, different methods have been proposed to accelerate the collection of field data that could be used in statistical and mathematical operations to draw an accurate picture of vegetation (Curtis and McIntosh, 1950). Now phytosociological studies are assisted by computer based program like Two Way Indicator Species Analysis

(TWINSPAN) (Hill, 1979) and multivariate analysis like Principal Component

Analysis (PCA) have considerably increased in vegetation delineation and ordination (Kent, 2011).

1.3 BIODIVERSITY AND CONSERVATION

Biodiversity refers to all the aspect of life on planet earth, which provide countless services to human (Delong, 1996; Rands et al., 2010) Millions of peoples throughout the world are provided with the basic necessities by plant biodiversity, which is facing a gradual decline at a rate much faster due to the interference of human activities then would be by natural means (Haq, 2011). Effective biodiversity conservation at species and ecosystem level makes the requirement of sufficient reliable data about the status and distribution of biodiversity, inevitable

(Ahrends et al., 2011). Because of diverse climate and geography Pakistan has been provided with rich plant diversity, containing about 6000 species of flowering plant 128 species of Pteridophytes, 23 species of Gymnosperm, 1140 Monocot and

4492 dicot species (Steward, 1972).

Plant provide countless benefits to human beings like, food, timber, medicines, and fiber, control nutrient cycling, regulate climate and flood, provide

recreation and buffers the ecosystem against environmental changes (Rai et al.,

2000; Singh and Kushwaha, 2008; Ahrends et al., 2011). Biodiversity not only reduces the impact of global warming but also minimize the effects of climate change (Feehan et al., 2009).These natural resources are unwisely exploited throughout the world. These natural resources are unwisely exploited throughout the world.

There are numerous plant species which have the core habitat in the mountain ecosystem, because of their low ecological amplitude, are on the brink of local extinction (Khan, 2012). Lake of sustainable uses of plant resources particularly the medicinal one and poor management of ecosystems in the

Himalayas is the worst case scenario, causing the rarity of medicinal plants in these regions (Rai et al., 2000, Ghimire et al., 2005).Realizing the unprecedented potential problem which might be caused by biodiversity loss, principally due to anthropogenic causes (Ahrends et al., 2011), biodiversity conservation gained worldwide recognition. Assessment of plant biodiversity and related threats is the main focus of international communities like the International Union for

Conservation of Nature (IUCN) (Rands et al., 2010) and many other non government organizations. As a worldwide recognition, UNO declared the decade

2011-2020 as the decade of biodiversity.

Chapter 2

FLORISTIC ENUMURATION AND PHYTOSOCIOLOGY

2.1 INTRODUCTION

The very survival of mankind and socio-economic activities is dependent on biological resources (Khan, 2012) and ecosystem has always been providing all the necessities fulfilling the requirement of mountain ecosystem (MA, 2005). Due to their diverse environmental conditions and microhabitat variation mountain ecosystem harbor diverse floral diversity (Kharkwal and Rawat, 2010) which not only equipped the locals with all the basic survival skills, bless the man far from their physical reaches in controlling the chemistry of environment and acting as catchment areas for sustaining the agriculture in low land (Khan et al., 2012), particularly in the arid regions of the world. in addition to regulating the chemistry of environment and maintaining the ecosystem plant not only provide direct services to human in the form of food, fodder, timber and medicinal plants but also prevent soil erosion and land sliding (Abbasi et al., 2002; Saqib et al., 2014). In the last century ecosystem all over the world because of human activities has faced the huge loss of biodiversity at a scale that has never been experienced in the previous history. The evaluation of ecosystem services in economic terms became an increasingly popular approach to demonstrate and justify the need for the conservation of an ecosystem (Schneiders et al., 2012; Vackaret al., 2012).

Scientific research confirmed the positive correlation between biodiversity and ecosystem services. Scientific community concluded that the species with different ecological niche and different spatial and temporal distribution act as a buffer to

2222

ecosystem processes, services and making the ecosystem more resilient (Schneiders et al., 2012).

Many of the services provided by the ecosystem come directly from vegetation. Due to the complexity and dynamicity the ecosystem system cannot be subjected to the routine experimental study, though certain method and techniques have been developed to study the individual components which help assessing the functioning and health of ecosystem (Kent, 2011; Khan et al., 2012). To understand the ecosystem dynamics with respect to plant ecology it is inevitable to understand floristic composition, spatial and temporal distribution and all the related phytosociological aspect of plants in an ecosystem (Ferreira et al., 2015).

Vegetation Science is a scientific discipline devoted to the study of vegetation at all levels of complexity spanning populations, plant communities and biomes. It attempts to explain vegetation patterns and the processes governing vegetation assembly and dynamics in all temporal and spatial scales (Pott, 2011). Study of vegetation has long been given the importance not merely because of its fundamental role in understanding of an ecosystem but because of the fact that it modifies the ecosystem and determines the vegetation composition and functioning of ecosystems as well (Braun-Blanquet, 1932; Ferreira et al., 2015). Different tools and techniques have been proposed to study the plant ecology and phytosociology with respect to vegetation type and objective of the study (Hussein, 1989; Braun-

Blanquet, 1932; Dufrene and Legendre, 1997; Kent, 2011). Floristic composition is the aggregation of individual species that are present in a strand or a region (Kent,

2011). The knowledge of the floristic composition of an area is a prerequisite for any ecological, phytogeographical studies, and conservation management activities

(Khan et al., 2012). To study particular vegetation from an ecological point of view, the first step must be to determine the facts as they exist on the ground e.g.

“who lives with whom and why” (McCune et al., 2002). The floristic composition of vegetation is more susceptible to direct study and exact characterization (Barakat et al., 2014). The only source of botanical information in many cases, for a particular area is the floristic checklists which may serve as a platform for more detailed study (Kent, 2011) and provide baseline for further future taxonomic, ecological, ethnobotanical, conservation and forest management projects (Khan et al., 2015). Because of their conciseness, the listing of species is easy approach in vegetation study because it can be done in a relatively small time frame, is easy to handle, and provide fundamental information for understanding the biodiversity issues (Ilyas et al., 2012).

Despite its importance the mere listing of plants species cannot describe structural characteristics of the community such as number, size, distribution and spacing of individuals between or within a community in relation to the physical environment. On the basis of such quantitative data, composition and community structure can be readily understood (Hussain, 1989). Phytosociology established by

Swiss ecologist Josias Braun-Blanquet (Braun-Blanquet, 1932) deals with plant communities, their composition, evolution and the relationships between the constituent species, gradient analysis and classification are its complementary tools

(Ewald and Díaz, 2003). No aspect of phytosociology has been extensively discussed than the classification of plant communities (Whittaker, 1962) because of the fact that understanding plant communities is the prerequisite for understanding the ecological niche of plant species, natural resources management and providing

guidelines for conservation strategies and plans (Khan et al., 2013c).

Plant community is a natural combination of plant species within a designated geographical unit, which is established by certain environmental variables such as soil type, topography, climate and human impact. The quantitative and qualitative variable of plant communities can be examined by tools and technique of phytosociology (Hussain 1989).To analyze and understand vegetation more objectively different diversity indices have been developed which help understand different aspects of floral diversity in a more realistic way. The term beta diversity has also recently been applied in a different way as a rate of decay in species similarity with increasing distance without respect to explicit environmental gradients (McCuneet al., 2002; Ilyas et al., 2015). Phytosociological field methods have helped ecologist to calculate diversity indices and find the indicator value of species in a particular plant community type (Dufrene and

Legendre, 1997), which not only help to demark the plant communities but also give insight to the composition dynamics of vegetation (Zou et al., 2007).

Phytosociology has been preoccupied with vegetation description, contributing to the outlier position phytosociologists have in the scientific community but as the new task emergesphytosociologists contributed a lot in nature conservation and landscape management (Fischer and Bemmerlein, 1989). Modern phytosociology is a relatively young branch of science which has been developed since the turn of the 20th century; it has its roots in classical plant geography (Pott, 2011). Plant species composition is not by chance or random selection of species but is a intricate well defined geographical unite which is in absolute harmony, governed by both biotic and abiotic factors like physical environment, climatic factor,

evolutionary history, migration of plant species and geological history of area along with anthropogenic pressure as well. Analysis of the distribution patterns of plants helps understand the ecological nature of a regional ecosystem functioning and process (Ferreira et al., 2015; Ullah et al., 2015).These plant communities consist of recognizable and reproducible associations of plant types which are subject to natural laws under the same ecological conditions (Pott, 2011).

The need for classification has long been recognized as according to

Ferguson “Without classification there can be no science of vegetation” (Ferguson et al., 1989).The vegetation has been classified by different approaches in the past.

In the physiognomic approach, earth vegetation was classified based on physiognomic characters, later individual species were given the more importance to understand vegetation leading to the use of floristic approach in vegetation science. Since the early suggestion of vegetation units by Humboldt and Grisebach, approaches to classification of vegetation have diverged into several major traditions and numerous schools (Whittaker, 1962) each school of thought not only helped in understanding the dynamics of vegetation but also equipped the ecologist to calculate different indices which help them to decide conservation priorities and understanding the ecosystem (Whittaker et al., 2001; Kent, 2011). Many systems have categorized units of land based on a few, and often one, important ecosystem components, e.g., based on climate or soils (Pojar et al., 1987) the habitat types community as well as the potential natural vegetation classifications based strictly on vegetation (Kusbach, 2010). Therefore, no environmental understanding of vegetation units could evolve without classification and hence no conceptual framework for conservation purposes and for more specific ecological research

could be developed (Juergens et al., 2013), so to have the fine scale understanding of vegetation composition there is need to organize vegetation based on fundamental spatial and functional differences.

The comprehensive ecosystem classification can provide insight into a number of fundamental ecological questions, for example: (1) are there identifiable vegetation climatic zones as firm altitudinal belts (Daubenmire, 1943) in the study area (2) What are patterns of vegetation species assemblages in the study area? and what environmental factor is responsible for a characteristic assemblage of species

(Kusbach, 2010; Tsheboeng et al., 2016). As a distinctive landscape feature, vegetation has been a fundamental component of land classifications recently; vegetation classification has been emphasized as a communication tool in ecological research and in the application of ecological information in planning, monitoring, conservation, and management (Ferguson et al., 1989).

Like any other biological phenomenon, for vegetation study it is inevitable to create order to identify small units which are possible to study Different method have been developed to classify vegetation and form groups (Dufrene and

Legendre, 1997; McCune et al., 2002; Kusbach, 2010; Kent, 2011) like hierarchical clustering, nonhierarchical, monothetic and polythetic methods.

Increasingly, society has to deal with complex challenges in management of natural resources including changes in land use and climate. A particular challenge is that management of natural resources has to be sustainable. In light of these challenges, it is appropriate to adopt an ecosystem approach to natural resource management rather than attempting to manage individual resources. This approach

requires the classification of units of land into ecologically meaningful and relatively uniform segments. One of the tests of ecosystem classification usefulness is the degree to which it provides insight into factors influencing the distribution of vegetation. In addition to disturbances and biotic interactions (e.g., competition); the physical environment, conceptually represented by climate, soil moisture and soil nutrients, exerts considerable influence on vegetation distribution (Kusbach,

2010).

As vegetation science develops, its formalized methodology increased in importance. At the beginning of the twentieth century traditional European schools of phytosociology applied an intuitive classification and ordering scheme to establish vegetation units. The introduction of computer-supported data analysis into vegetation science accelerated the formalization (Fischer and Bemmerlein,

1989). Identification of characteristic or indicator species is a traditional activity in ecology and biogeography. There is obviously a need for the identification of characteristic or indicator species in the fields of nature monitoring, conservation, and management (Dufrene and Legendre, 1997). No aspect of synecological science has been the subject of more discussion and argument than the classification of natural communities (Whittaker, 1962). The thorough

Understanding of the ecosystem dynamics requires the quantitative measurement after observation and description of vegetation. On the basis of such quantitative data, composition and community structure can easily be understood due to interaction and association of a community or between communities (Hussain,

1989). The most common method in quantitative analysis of vegetation is quadrate method (Ilyas, 2015), which has been used for plant community ecology and

element ecology and have been proven to be compendious and accurate in revealing the nature and characteristic of the flora or vegetation in plant communities (Jianet al., 2008).

At the beginning of the previous century European school of hytosociology applied intuitive approach and methodology to classify vegetation. The erosion of traditional schools in the Anglo American world started at the beginning of the fifties, which is very much matrix-orientated. In Central European Phytosociology, the releve tables can be understood as matrices. The traditional releve table can be seen as a convenient way to display data rather than an analytical tool. But with the emergence of matrix oriented approaches the data can be interpreted and analyzed in a more explicit way (Fischer and Bemmerlein, 1989). The association has been asserted to be the fundamental units of ecological science (Whittaker, 1962).

Various quantitative methods have been proposed for understanding the dynamics of an ecosystem (Hussain, 1989) and finding the plant associations.

Vegetation data collected is now subjected to Multivariate statistical techniques which help in extracting useful information and patterns from multivariate data and for understanding the structure of random phenomena

(Hettrich. and Rosenzweig, 2003; Chatfied and Collins, 2013) the Techniques which may contribute to a 'new look' in phytosociology, were neither developed for use in community ecology nor generally accepted by most Central European phytosociologists. At any scale of analysis, any single environmental variable has no explanatory power across all scales of analysis (Whittaker et al., 2001).

The advent of Multivariate statics helped to visualise multivariate high

dimensional data into low dimensions by dimensional compression with minimum loss of information in the original data (Chatfied and Collins, 2013). Reduction of multivariate data involves extracting a small number of composite variables or dimensions or PC axis that express much of variation in the original data set

(McCune et al., 2002). Multivariate techniques have become an option, which might provide a further dimension to Phytosociology. The application of automatic data processing and multivariate methods has promoted the development of new approaches to understanding the vegetation structure and dynamics notably ordination methods have now become a standard tool in Anglo-American ecology

(Fischer and Bemmerlein, 1989).

In particular phytosociologists expected that if all associations were described it would be possible to contribute significantly to the solution of agricultural problems and landscape planning and to have a solid basis for further ecological research. It was not before the resources of multivariate statistics and automatic data processing came into existence that multidimensional phenomena could be easily described and analyzed on all levels of integration and with different spatial and temporal scales (Fischer and Bemmerlein, 1989).Use of the computer has made it possible to analyze large complex multidimensional data and to present the result in more simplified form in low dimensions. Different ordination techniques have been found to be the effective technique to understand the vegetation pattern (Kusbach, 2010) involvement of software packages e.g.

PCA, DCA TWINSPAIN, CONOCO (Hill, 1979; Hill and Gauch, 1980; Dufrene and Legendre, 1997) played important role in analyzing and interpreting the multidimensional data.

2.2 REVIEW OF LITERATURE

The thorough understanding of ecosystem dynamics requires the information on floral composition, diversity (Reddy et al., 2011) and quantitative measurement after observation and description of vegetation. On the basis of such quantitative data, composition and community structure can be readily understood

(Hussain, 1989). Conservation and management of an ecosystem also make the requirement of such data inevitable to highlight the important issues (Reddy et al.,

2011).Various quantitative methods have been proposed for understanding the dynamics of an ecosystem (Braun-Blanquet, 1932; Dufrene and Legendre, 1997).

At the beginning of the 20th century a number of schools of thoughts developed on phytosociology, of which the Zurich-Montpellier and the Uppsala school of thought got much popularity (Khan, 2012). European school of phytosociology applied intuitive approach and methodology to classify vegetation (Braun-

Blanquet, 1932) but the use of common methods for vegetation analysis has been the problem in the field of phytosociology. With the advent of multivariate statistical techniques ecologist has been better equipped with modern tool and techniques, which might provide a new dimension to phytosociology for understanding and solving problems of ecosystems (Fischer and Bemmerlein,

1989). The use of computer assisted analysis in vegetation dynamics along environmental gradients is an established theme (Khan et al., 2013). The application of automatic data processing and multivariate methods has promoted the development of new approaches to understanding the vegetation structure and dynamics. Notably ordination methods have now become a standard tool in Anglo-

American ecology (Fischer and Bemmerlein, 1989). Using the tools and techniques

of phytosociology vegetation is being studed throughut the world. Ullah et al.

(2015) carried out the phytogeographical analysis and diversity of grasses and sedges in northern Pakistan and reported 117 species belonging to 30 genera in three families of the order Poales. Based on environmental gradients they divided sixteen districts into groups, and subgroups. Climate was found to be the significant factor in controling the species association. Vegetation dynamics were studies in the Western Himalayas by Khan et al. (2012). They identified five plant communities and found that biodiversity decreased along the altitude. Plant diversity was found to be highest at middle altitudes facing the north site, which was associated with the long snow cover and dense tree cover which result in high moisture, cumulatively supporting high biodiversity.

Phytosociological attributes along environmental gradients in the Naran

Valley were studied to identify and understand the plant communities and priorities the conservation plan in the region. A total of 198 plant species were identified distributed over 68 families using the transect method. Canonical correspondence analysis determined that the main ecological variable determining the vegetation is altitude. Diversity was highest at middle altitude and low at both high altitude and lower altitude due to high summer grazing pressure coupled with shallow soil and high anthropogenic pressure respectively (Khan et al., 2013).The vegetation of

Thandiani forests, district Abbottabad, Pakistan was studies by Khan et al. (2016).

The area was dominated by Hemicryptophytes being the indicator of cold climate.

Phytosociological study of the vegetation of Kabal valley, district Swat, Pakistan was conducted by Ilyas et al. (2015). Vegetation was classified into nine communities using Way Indicator Species Analysis (TWINSPAN) and data was

subjected to Detrenched Correspondence Analysis to correlate the vegetation with environmental variables. The results indicated the significant degradation of vegetarian owing to poverty, high livestock population and overexploitation of natural resources.

Ilyas et al. (2012) determined the composition of Qalagai hills vegetation of

Swat, Khyber Pakhtunkhwa along with threats to the ecosystems, using quadrate method by taking 160 stands from the study area. The vegetation was classified in to eight communities based on importance values, similarity index, and physiognomy and adaphic factors. A total of 209 plant species distributed over 167 genera were reported from the area. The degradation of vegetation was attributed to improper land use, terrace cultivation and over grazing. Phytosociological survey of Himalayan forests of Pakistan was conducted by Ahmed et al. (2006). They analyzed 184 samples taken from representative areas, and defined 24 different plant communities based on importance value. Rawat and Chandra, (2014) studied the vegetation diversity along the altitudinal range from 2200 and 2500 m in

Garhwal Himalaya and found diverse plant communities along the altitudinal gradient but with overlapping species composition. A total of 413 plants species were identified from the area. The result indicates the increase in species richness with more open canopy. To analyse the effect of an altitudinal gradient on species richness and diversity the vegetation in the temperate forest of Garhwali Himalaya was studies along the altitudinal gradient. A negative correlation was observed between density, species richness and altitude. The distribution pattern and species richness particularly of tree species was seemes to be regulated by the climatic and

(Sharma et al., 2009).

The vegetation of Western Ghats in southern India was classified into five groups using different multivariate techniques. Altitude was found to be the most important factor which determines the vegetation in Western Gates (Pascal et al.,

2004). To understand the effect of interspecific competition and environmental factors on spatiotemporal pattern of vegetation the plant communities were investigated in Brazil. The result indicated that the composition of plant species is determined by antagonistic action of biotic and ecological parameters (Ferreira et al., 2015). The vegetation of Eastern Alps was studied by Lüth et al. (2011) to examine the extent of land use influence and site factors in determining the plant communities in the area. They identified 39 plant communities and found altitude as the decisive factor in determining specific plant communities.

Barakat et al. (2014) carried out the ecological studies of vegetation in the

Sinai Peninsula, Egypt and recorded 75 plant species distributed over 65 genera and 29 families with the high percentage of chamaephytes. The vegetation has been classified in to four communities’ viz. Retama raetam, Cornulaca monacantha,

Atriplex halimus, and Nitraria retusa.based on heterogeneity in local topography, microclimatic conditions and edaphic factors. The vegetation in central the Namib

Desert was studied by Juergens et al. (2013).They reported 806 seed plants belong to 93 families of which 103 species were found to be endemic to the Namibia and classifying the vegetation into 21 large-scale classes.

The vegetation in the Okavango Delta, Botswana was classified into four vegetation communities based on Hierarchical cluster analysis. Indicator species analysis was used to determine the number of significant communities, which were

subjected to Multi-response permutation procedures (MRPP) showing a significant difference in all the four communities (Tsheboeng et al., 2016). Vegetation of

Umkhanyakude Node has been studies and divided into two major plant communities and eight vegetation types using TWNSPAN classification. The most important factor determines the vegetation type was found to be percentage sand/clay content by PCA analysis. The result was confirmed by DCA ordination

Ecological studies of the relic tree Zelkova sicula, a species endemic to

Sicily, were conducted in order to check niche and eco-geographic range of species. The abiotic and biotic features of 30 plots from the populations were investigated using the method of Zurich-Montpellier school in order to contribute and clarifying the actual and potential eco-geographic range of this species. The result showed that micro-habitat differences and the size of the tree are responsible for compositional differences among the sampled plots (Garfì et al., 2011).

Vegetation of Malilangwe Wildlife Reserve in Zimbabwe has been classified into

38 vegetation types using TWINSPAN. Soil textural gradient was the primary gradient separating the communities along with some secondary gradient like slope, rockiness, and topographical position (Clegg and O'connor, 2012).The phytosociological studies in Bagh district, Kashmir were carried out using

Quadrate method showing the complete dominance of Abies pindrow and Pinus wallichiana. Canonical correspondence analysis revealed a negative correlation between diversity and richness with slope and altitudinal gradient. Low tree density and seedling count were related to high degradation status of this part of Himalaya being under the siege of the human population (Shaheen et al., 2012). Galal, (2011) studied the vegetation of in Wadi Gimal, Egypt in order to assess the effect of

elevation on the distribution pattern, number and size of perennial woody plant species in the area. Except Balanites aegyptiaca the number of most of other species decreases with increase in elevation which was also strongly correlated with soil characteristics. High species diversity in the low elevation is attributed to the fact that low land receives more runoff water than high elevations.

Qureshi, (2008) defined five plant communities’ viz., 1) Phragmites-Typha-

Saccharum in wetland; 2) Callligonum-Dipterygum-Salvadora in desert; 3)

Saccharum-Pluchea-Typha in marshland; 4) Desmostachya-Brachiaria-Cynodon in agricultural habitat and 5) Salvadora-Desmostachya-Posopis in protected forest, on the basis of Importance value index (IVI) in Sawan Wari of Nara Desert, Pakistan.

Furthermore, a total of 136 plant species belonging to 73 genera and 44 families have been identified.The vegetation in the Chapursan Valley, Gilgit was subjected to multivariate analysis by Wazir et al. (2008) and five vegetation types were identified include crasulescent steppes, chamophytic steppes, erme, moist sub- alpine pastures and pseudo-steppes with the help of cluster analysis. Ahmed et al.

(2009) studied the vegetation structure of Olea ferruginea forest in lower Dir,

Pakistan. Based on IVI the vegetation was classified into ten plant communities viz., 1) Olea- Punica, 2) Olea- Ficus 3) Platanus-Morus, 4) Olea-Ailanthus, 5)

Morus-Celtis 6) Olea-Acacia, 7) Olea-Morus, 8) Olea-Monotheca, 9) Olea-

Quercus and 10) Olea community. Haq, (2011) determined the conservation status of the critically endangered and endangered species in the Nandiar Khuwar catchment district Battagram, reporting a total of 37 taxa which includes 14 critically endangered and 23 endangered species. Deforestation, over grazing, unplanned collection, erosion and introduced of alian taxa was the main culprit

responsible for the loss of local diversity. Reddy et al. (2011) studied the species composition and diversity change in response to altitudinal gradient and positively correlated the altitude with differential species composition. The major threats in the area were fuel wood extraction, medicinal plants collection, over grazing and intentional forest fire. Khan et al. (2013) determined plant communities in Naran

Valley, Himalayas with respect to different environmental gradients, describing the vegetation using ordination technique like Detrended correspondence analysis

(DCA) and canonical correspondence analysis (CCA). They also assessed the effect of anthropogenic pressure on vegetation. They identified a total of 198 species from 68 families were identified at 144 stations along 24 transects across an elevation range of 2450–4100 m. A number of plant species of conservational interests were identified in and their main threats were also assessed.

2.3. MATERIAL AND METHODS

2.3.1 Physiognomy

Before the phytosociological field data collection, several preliminary trips were made to have the familiarity with the study area. Before the data collection topography, physiognomy and different other aspect of vegetation was visualised in these preliminary trips. On the basis of altitude, physiognomy, aspect and topography study area was divided into separate zones for vegetation analysis.

Vegetation was survived using stratified random design.

2.3.2 Plant Collection and Identification

Plant specimens were collected from the whole area from August, 2013 till

September, 2015 in triplicate, pressed, dried and mounted on standard herbarium sheets. Gymnosperm and Angiosperm were identified with the help of Flora of

Pakistan, (Steward, 1972; Nasir and Ali, 1970-1996; Ali and Nasir, 1989-1991; Ali and Qaiser, 1993-2007). Where as the Cryptogamic Flora of Pakistan (Nakaike and

Malik, 1992) was used to identify the Pteridophytes. Nomenclature of the taxa followed above mentioned flora but the accepted names were validated from The

Plant List (TPL, 2013). Voucher number was allocated to plant specimens and specimens were deposited in the herbarium of Pir Mehr Ali Shah, Arid Agriculture

University Rawalpindi, Pakistan.

2.3.3. Phytosociological Studies

2.3.3.1 Sampling procedure

The study area was surveyed from August, 2013 till September, 2015. A stratified (based on vegetation physiognomy) random (objective selection) sampling design was used to sample the area. Different sampling sites was marked keeping in view the maximum possible heterogeneity in vegetation after orientation survey of the study area. Sampling was intensive enough to capture as much ecosystem variation as possible. A total of 246 samples were selected, each sample having seven quadrats, one quadrat for trees, two for shrubs and four for herbs each measuring 10m2, 4m2 and 1m2, respectively (Hussain, 1989). A total of 1722 quadrats (245*7) were studied, distribution of which is shown in fig (2.1). For each sample, geographical coordinates altitude, exposure and slope gradient was recorded using Geographical Positioning System (GPS). Fallowing parameters, from each quadrate were measured.

2.3.3.2 Cover scale

In order to record cover value, modified method of Braun-Blanquet

(Barkman et al., 1964) was used as fallow;

Score Cover

0 Taxa absent from quadrate

0.1 Taxa represented by a solitary shoot, <5% cover

0.5 Taxa represented by a few (<5) shoots, <5% cover

1 Taxa represented by many (>5) shoots, <5% cover

2 Taxa represented by many (>5) shoots, 5 - 25% cover

3 Taxa represented by many (>5) shoots, 25 - 50% cover

4 Taxa represented by many (>5) shoots, 50 - 75% cover

5 Taxa represented by many (>5) shoots, 75 - 100% cover

2.3.3.3 Frequency (F)

It is calculated by fallowing formula (Hussain 1989).

2.3.3.4 Density (D)

Density was calculated using fallowing formula (Hussain, 1989).

2.3.3.5 Coverage (C)

2.3.3.6 Change to relative values

The average values of frequency, density and coverage was converted to relative values according to the following formulae (Hussain, 1989).

2.3.3.7 Importance value index (I.V.I)

Importance value index was obtained by summing up the relative values of each species in a stand according to the following formula (Hussain, 1989).

I.V.I = RF + RD+ RC

Fig.2.1. Samples distribution in the study area.

2.3.3.8. Soil analysis

Soil was collected from three randomly selected points in each sample up to a depth of 15cms and thoroughly mixed to make a composite mixture. About one kilogram from the mixture as packed in polythen bags and labeled. The physical and chemical analysis of soils was following that of Koehler et al. (1984),

(McLean, 1982), Hussain (1989) and (Black et al., 1965). The studying parameters include: 1) Textural analysis, 2) Electrical conductivity, 3) pH,4) Organic matter,

5) Phosphorus, 6) Potassium and 7) Nitrogen.

2.3.3.9 Diversity indices

The following species richness, diversity indices and evenness indices were calculated;

2.3.3.9.1 Species richness

Species richness is calculated as the total number of species in the community, denoted by S.

2.3.3.9.2 Margalef richness

It was calculated by the following formula (Margalef, 1958).

R = S - 1/ ln (n)

Wareas R is Margalef richness; S is total number of species in a sample and ln (n) is natural log of total number of individual of all species in a sample.

2.3.3.9.3 Menhinick richness

It was calculated by the following formula (Menhinick, 1964).

R2 = S/√N

Wheras R2 is Menhinick richness; S is Total number of different species in a sample and N is total number of individuals of all species in the same sample.

2.3.3.9.4 Simpson diversity index

Simpson Diversity Index has been calculated by following formula

(Hussain, 1989).

Where D is Simpson Diversity index n is Number of individuals of a species in sample and N is the total number of individuals of all species. For better presentation D1 was calculated as 1-D also called Simpson Diversity Index

2.3.3.9.5 Shannon-Wiener diversity index

It was calculated by the following formula (Sher et al., 2013).

Where H'is Shannon-Wiener Diversity Index; piis decimal fraction of individuals belonging to i-th species

2.3.3.9.6 Pielou evenness

E= e H'/ln S

Where E is Pielou evenness; e H'is the expected value from Shannon-

Wiener index for and S is the total species in a sample.

2.3.3.9.10 Iindicator value

INDVAL ij = A ij× B ij × 100,

Wereas A ij = Nindividuals ij /Nindividuals i.and B ij= Nsites ij /Nsitesj

2.3.3.9.11 Life form (biological spectrum)

The life form classes and their percentage in each community were marked by following the work of (Raunkiaer 1934; Hussain and Tajul-Malook, 1984) and

(Hussain 1989). The major life form classes are as follows:

1. Macrophanerophytes (MP).

2. Nanophanerophytes (NP).

3. Chamaephytes (Ch).

4. Hemicryphotophytes (H).

5. Geo phytes (G).

6. Lianas (L).

7. Therophytes (Th).

2.3.3.9.12 Leaf spectra

The leaf size was calculated according to Cain and Castro (1959) which is:

Leaf area = length x breadth x 2/3

The leaves weregrouped into the followings classes:-

Class-I Leptophyll (L) = 25mm2

Class-II Nanophyll (N) = 25 x 9 = 225mm2

Class-III Microphyll (Mi) = 25 x 9 x 9 = 2025 mm2

Class-IV Mesophyll (Me) = 25 x 9 x 9 x 9 = 18225mm2

2.3.4 Data Analysis

Data for 352 vascular plant species, from 246 samples (1722 quadrats) along with 13 environmental variables were analysed in computer programmes i.e.,

MS EXCEL 2007, PC-ORD version 5 (McCune, 1986, McCune & Mefford, 1999),

CANOCO version 4.5 (ter Braak, 1988, ter Braak, 1989, ter Braak & Smilauer,

2002) and R software package.

2.3.4.1 Data organization

Followed by calculation of quantitative and qualitative attributes for each of the 246 samples in MS EXCEL 2007, using the respective formulae given above, absolute and relative values of vascular plants studied in 246 samples were calculated.

After that the data was organized according to the requirement of the requirement of

PC-ORD (McCune and Mefford, 2006), R-statistical package (R Core Team, 2015)

(Team, 2015) and CANOCO (Ter Braak and Šmilauer, 2012) for different multivariate analysis. As a result two groups of data matrices were obtained. The first group composed of species data matrices (qualitative and quantitative characters of species) and the second one include environmental variable

(considered as independent variables) for each sample.

2.3.4.2 Vegetation analysis

In order to understand distribution of plant communities and to explain the distribution pattern, data was analyzed using the classification and ordination techniques. This was done to bring the multidimensional data set to low dimensional space in order to identify the plant communities, their respective indicator species, habitat types and the important environmental variables controlling the vegetation distributional pattern and composition.

2.3.4.2.1 Cluster analysis

Hierarchical agglomerative clustering of 246 samples and 352 plant species was done based on qualitative data (presence/absence) by using Sorensen distance.

2.3.4.2.2 Indicator species analysis

Indicator species analysis (Dufrêne and Legendre 1997) was done with the help of PC-ORD version 5 (McCune, 1986, McCune & Mefford, 1999), in order to calculate indicator values (IV) of species in groups defined from the cluster analysis. The statistical significance of indicator values for species was tested using

Monte Carlo technique. Indicator species analysis was also used to determine an ecologically meaningful number of vegetation communities. This was determined

where mean p is minimized or the number of ecologically significant species maximized (McCune and Grace 2000). To find if the different vegetation communities were significantly different or not, Multi-response permutation procedures (MRPP) (McCune and Grace 2000), was used, which was conducted with PC-ORD using the Sorensen distance measure.

2.3.4.2.3 Ordination analyses

Ordination, a multivariate statistical method, summarizes the multidimensional interaction to low dimensional space in which dissimilar sample/species goes further apart and similar ones come closer together. Relationships of samples, plant species and environmental variables were determined by Detrended Correspondence

Analysis (Indirect method) and Canonical Component Analysis (Direct method) using CANOCO software to find species-environment correlation, samples relationship and grouping, order and significance of different variables in controlling the species composition in study area. To have the better visual presentation of biplot the number of displayed species was reduced using the joint criteria of ≥15% best fit and ≥15% largest species weightage was used.

2.4. RESULTS

2.4.1. Floristic Enumeration

The vascular flora of Murree Kotli Sattian Kahuta national park in district

Rawalpindi comprised of 624 plant species belonging to 106 families and 361 genera, which include 24 ferns species, 4 species of gymnosperms and 596 angiosperms species (i.e. 144 monocotyledon and 452 dicotyledons) (Fig 2.2). As

the area is located in lateral spur of Himalaya (Abbasi et al., 2002) distributed from the elevation of about 400 to 2155 meters above sea levels, there was a good deal of floral diversity under the park area compared to the area of whole country (Table

2.1). The total park area contributed only 0.12% compare to the whole area country but contain significantly high flora diversity (10.79%). The study area was found to be rich in Pteridophytes (18.75%) and Gymnosperms (17.39%) compared with the flora of Pakistan, followed by Monocotyledons (12.63%) and Dicotyledons

(10.06%) (Fig. 2.2).

The most abundant plant family in the study area was poaceae with 12.82% plant species share (80, spp.). The second most abundant family, represented by 60 plant species (9.62%) was Fabaceae followed by Asteraceae (55 spp., 8.81%),

Cyperaceae (30 spp., 4.81%), Lamiaceae (27 spp., 4.33%), Rosaceae (19 spp.,

3.04%), Apiaceae, Brassicaceae and Euphorbiaceae (12 spp1.92% each),

Convolvulaceae and Ranunculaceae (11 spp., 1.76% each), Acanthaceae,

Amaranthaceae and Polygonaceae (10 spp., 1.60% each), where as the remaining families were represented by less than 10 species (Fig. 2.3). The largest genus was

Euphorbia (10 spp., 2.67%) followed by Carex (9 spp., 2.4%), Cyperus (8 spp.,

2.13%), Eragrostis, Poa, Ficus, Medicago, Rubus and Swertia (6 spp., 1.6% each), while rest of genera shared less than five plant species. Eight life forms of the flora were determined in which perennial herbs were dominating the area with contribution of 241 species sharing 38.62% of the flora. It was followed by annual herbs (199 spp., 31.89%), deciduous shrubs (62 spp., 9.94%), deciduous trees (46

500 452 450

400 350 269 300 250

No. ofspecies No. 200 144 150 77 82 100 7 12 24 1 3 4 16 50 0 Pteridophytes Gymnosperms Monocotyledons Dicotyledons Families Genera Species

Fig. 2.2.Floristic composition of vascular flora of Murree-Kotli Sattian-Kahuta National Park with flora of Pakistan.

Table 2.1.Comparision of flora of Murree-Kotli Sattian-Kahuta National Park with flora of Pakistan. Plant Group Number of Species Species Percentage Study Area Pakistan compared to (Steward, 1967) (Steward, 1967) Pakistan (Area: 934 Km2) (Area: 796095 Km2) Pteridophytes 24 128 18.75 Gymnosperms 4 23 17.39 Monocotyledons 144 1140 12.63 Dicotyledons 452 4492 10.06 Total 624 5783 10.79

Table 2.2.Floristic list of vascular plants of Murree-Kotli Sattian-Kahuta National Park, Pakistan. Group/Family Sr. Plant Species Voucher Ha. Status # # Pteridophytes 1. Adiantaceae 1 Adiantum capillus-veneris L. WA-251 PH Native 2 A. caudatum L. WA-95 PH Native 3 A. incisum Forssk. WA-252 PH Native 4 A. venustum D. Don WA-253 PH Native 5 Onychium contiguum Wall. ex WA-96 PH Native C. Hope 2. Aspleniaceae 6 Asplenium adiantum-nigrum L. WA-254 PH Native 7 A. trichomanes L. WA-256 PH Native 8 A. dalhousiae Hook. WA-255 PH Native 3. Dennstaedtiaceae 9 Pteridium aquilinum (L.) Kuhn WA-381 PH Native 4. Dryopteridaceae 10 Dryopteris filix-mas (L.) Schott WA-382 PH Native 11 D. ramosa (C. Hope) C. Chr. WA-241 PH Native 12 D. stewartii Fraser-Jenk. WA-190 PH New to area 13 Polystichum aculeatum (L.) WA-383 PH Native Roth ex Mert. 5. Equisetaceae 14 Equisetum arvense L. WA-615 PH Native 15 E. hyemale L. WA-224 PH Native 16 E. ramosissimum (Desf.) WA-384 PH Native 17 Hippochaete debilis (Roxb. ex WA-385 PH Native Vaucher) Ching 6. Pteridaceae 18 Allantodia squamigera (Mett.) WA-586 PH Native Ching 19 Cheilanthes argentea (S.G. WA-387 PH Native Gmel.) Kunze 20 C. farinosa (Forssk.) Kaulf. WA-585 PH Native 21 Coniogramme rosthornii WA-386 PH Native Hieron. 22 Pteris cretica L. WA-189 PH Native 23 P. vittata L. WA-257 PH Native 7. Hypodematiaceae 24 Hypodematium crenatum WA-591 PH Native (Forssk.) Kuhn Gymnosperms 8. Pinaceae 25 Abies pindrow (Royle ex WA-258 ET Native D.Don) Royle 26 Cedrus deodara (Roxb. ex D. WA-172 ET Native Don) G. Don 27 Pinus roxburghii Sarg. WA-203 ET Native 28 P. wallichiana A.B. Jacks. WA-99 ET Native Monocotyledons 9. Alismataceae 29 WA-617 PH New to Alisma plantago-aquatica L. Punjab 10. Amaryllidaceae 30 Allium cepa L WA-225 PH Cultivated

Group/Family Sr. Plant Species Voucher Ha. Status # # 31 A. sativum L. WA-100 AH Cultivated 11. Araceae 32 Aralia cachemirica Decne. WA-388 PH Native 33 Arisaema flavum (Forssk.) WA-259 PH Native Schott 34 A. jacquemontii Blume WA-97 PH Native 35 Sauromatum venosum (Dryand. WA-226 PH Native ex Aiton) Kunth 12. Asparagaceae 36 Agave americana L. WA-227 PH Cultivated 37 Asparagus adscendens Roxb. WA-378 PH Native 38 A. capitatus Baker WA-379 PH Native 39 A. filicinus Buch.-Ham. ex WA-380 PH Native D.Don 40 A. racemosus Willd. WA-98 PH Native 41 Ophiopogon intermedius D. WA-377 PH New to Don Punjab 13. Commelinaceae 42 Commelina paludosa Blume WA-103 PH Native 14. Convallariaceae 43 Polygonatum verticillatum (L.) WA-260 PH Native All. 44 P. multiflorum (L.) All. WA-261 PH Native 15. Cyperaceae 45 Bolboschoenus maritimus subsp WA-101 PH Native . affinis (Roth) T.Koyama 46 Carex canescens L WA-182 PH Native 47 C. cardiolepis Nees WA-262 PH Native 48 C. cuprina (Sándor ex Heuff.) WA-609 PH Native Nendtv. ex A.Kern. 49 C. fedia Nees WA-183 PH Native 50 C. filicina Nees WA-104 PH Native 51 C. hebecarpa C.A. Mey. WA-181 PH Native 52 C. schlagintweitiana Boeck. WA-180 PH Native 53 C. foliosa D. Don WA-263 PH Native 54 C. psychrophila Nees WA-264 PH Native 55 Cyperus compressus L. WA-102 AH Native 56 C. difformis L. WA-376 AH Native 57 C. iria L. WA-265 AH Weed 58 C. laevigatus L. WA-375 PH Native 59 C. niveus Retz. WA-389 PH Native 60 C. rotundus L. WA-431 PH Weed 61 C. squarrosus L. WA-390 AH Native 62 C. alopecuroides Rottb. WA-391 PH Native 63 Eleocharis uniglumis (Link) WA-432 PH Native Schult. 64 Eriophorum comosum (Wall.) WA-392 PH New to area Nees 65 Fimbristylis dichotoma (L.) WA-266 PH Native Vahl 66 F. rigidula Nees WA-267 PH Native

Group/Family Sr. Plant Species Voucher Ha. Status # # 67 F. schoenoides (Retz.) Vahl WA-393 PH Native 68 F. squarrosa Vahl WA-607 AH Native 69 Kobresia laxa Nees WA-599 PH Native 70 Kobresia sanguinea (Boott) WA-370 PH Native Raymond 71 Kyllinga squamulata Vahl WA-371 PH Native 72 Pycreus pumilus (L.) Nees WA-374 AH Native 73 P. flavidus (Retz.) T.Koyama WA-373 AH Native 74 Schoenoplectus litoralis (Schrad WA-372 PH Native .) Palla 16. Hypoxidaceae 75 Curculigo orchioides Gaertn. WA-229 PH Native 17. Hydrocharitaceae 76 Hydrilla verticillata (L.f.) Royle WA-228 PH Native 18. Juncaceae 77 Juncus articulatus L. WA-394 PH Native 78 J. inflexus L. WA-268 PH Native 79 Juncus maritimus Lam. WA-608 PH Native 19. Liliaceae 80 Tulipa clusiana DC. WA-230 PH Native 20. Orchidaceae 81 Calanthe tricarinata Lindl. WA-604 PH Native 82 Cephalanthera longifolia (L.) WA-395 PH Native Fritsch 83 Epipactis gigantea Douglas ex WA-269 PH Native Hook.//Epipactis veratrifolia Boiss. & Hohen. 84 E. helleborine (L.) Crantz WA-270 PH Native 85 E. persica (Soó) Hausskn. ex WA-272 PH Native Nannf. 86 Habenaria furcifera Lindl. WA-587 PH Native 87 Malaxis muscifera (Lindl.) WA-588 PH Native Kuntze 88 Spiranthes sinensis (Pers.) WA-271 PH Native Ames 21. Poaceae 89 Agrostis gigantea Roth WA-396 PH Native 90 A. stolonifera L. WA-398 PH Native 91 Apluda mutica L. WA-397 PH Native 92 Aristida cyanantha Steud. WA-231 PH Native 93 Arthraxon lancifolius (Trin.) WA-369 PH Native Hochst. 94 A. prionodes (Steud.) Dandy WA-367 PH Native 95 Arundinella nepalensis Trin. WA-368 PH Native 96 Arundo donax L. WA-453 PH Naturalised 97 Avenafatua L. WA-364 PH Weed 98 Bothriochloa bladhii (Retz.) WA-365 PH Native S.T.Blake 99 Brachiaria eruciformis (Sm.) WA-366 AH Native Griseb. 100 B. ramosa (L.) Stapf WA-597 AH Native 101 B. reptans (L.) C.A. Gardner WA-200 AH Weed &C.E. Hubb.

Group/Family Sr. Plant Species Voucher Ha. Status # # 102 Bromus hordeaceus L. WA-399 PH Native 103 B. pectinatus Thunb. WA-361 AH Native 104 B. catharticus Vahl WA-362 PH Naturalised 105 B. ramosus Huds. WA-363 PH Native 106 Brachypodium sylvaticum (Hud WA-598 AH Native s.) P.Beauv. 107 Capillipedium parviflorum (R.B WA-400 PH Native r.) Stapf 108 Cenchrus ciliaris L. WA-133 PH Native 109 C. pennisetiformis Steud. WA-356 PH Native 110 C. setiger Vahl WA-357 PH Native 111 Chrysopogon aucheri (Boiss.) WA-354 PH Native Stapf. 112 C. serrulatus Trin. WA-355 PH Native 113 C. gryllus (L.) Trin. WA-401 PH Native 114 Cymbopogon martini (Roxb.) WA-433 PH Native Will. Watson 115 Cynodon dactylon (Linn.) Pers. WA-353 PH Native 116 Dactylis glomerata L. WA-434 PH Native 117 Dactyloctenium aegyptium (L.) WA-402 PH Weed Willd. 118 Desmostachya bipinnata (L.) WA-360 PH Native Stapf 119 Dichanthium WA-232 PH Native annulatum (Forssk.) Stapf 120 D. foveolatum (Delile) Roberty WA-107 PH Native 121 Digitaria sanguinalis (L.) Scop. WA-352 AH Native 122 Echinochloa crus-galli (L.) P. WA-403 AH Weed Beauv. 123 Eragrostis curvula (Schrad.) WA-358 AH Native Nees 124 E. amabilis (L.) Wight & Arn. WA-350 AH Native 125 E. cilianensis (All.) Janch. WA-596 AH Native 126 E. minor Host. WA-359 AH Native 127 E. papposa (Desf. ex Roem. & WA-351 PH Native Schult.) Steud. 128 E. pilosa (L.) P.Beauv. WA-105 AH Native 129 Eulaliopsis binata (Retz.) C.E. WA-404 PH Native Hubb. 130 Festuca gigantea (L.) Vill. WA-600 PH New to area 131 WA-610 PH New to Festuca kashmiriana Stapf Punjab 132 Heteropogon contortus (Linn.) WA-454 PH Native P. Beauv. ex Roem. & Schult. 133 Imperata cylindrica (L.) WA-405 PH Native Raeuschel 134 Lolium perenne L. WA-187 PH Native 135 L. persicum Boiss. & Hohen. WA-108 AH Native

Group/Family Sr. Plant Species Voucher Ha. Status # # 136 L. temulentum L. WA-188 AH Weed 137 Oplismenus compositus (L.) P. WA-191 PH Native Beauv. 138 Panicum antidotale Retz WA-595 PH Naturalised 139 Paspalidium flavidum (Retz.) WA-427 PH Naturalised A.Camus 140 Paspalum dilatatum Poir. WA-457 PH Naturalised 141 P. distichum L. WA-544 PH Native 142 Pennisetum glaucum (L.) R.Br. WA-455 AH Cultivated 143 P. orientale Rich. WA-503 PH Native 144 Phalaris minor Retz. WA-106 AH Native 145 Piptatherum WA-406 PH Native aequiglume (Duthie ex Hook. f.) Roshev. 146 P. hilariae Pazij WA-435 PH Native 147 P. gracile Mez WA-602 PH Native 148 Poa alpina L WA-273 PH Native 149 P. annua L. WA-274 AH Weed 150 P. nemoralis L. WA-603 PH Native 151 P. polycolea Stapf WA-533 PH Native 152 P. pratensis L WA-407 PH Native 153 P. infirma Kunth WA-275 AH Weed 154 Polypogon fugax Nees ex Steud. WA-436 AH Weed 155 P. monspeliensis (Linn.) Desf. WA-408 AH Weed 156 P. viridis (Gouan) Breistr. WA-601 PH Native 157 Rostraria cristata (L.) Tzvelev WA-545 AH Weed 158 Saccharum bengalense Retz. WA-409 PH Native 159 S. ravennae (L.) L. WA-411 PH Native 160 S. spontaneum L. WA-527 PH Native 161 Setaria pumila (Poir.) Roem. & WA-276 AH Weed Schult. 162 S. verticillata (L.) P.Beauv. WA-412 AH Invasive 163 S. viridis (L.) P. Beauv. WA-234 AH Weed 164 Sorghum bicolor (Linn.) WA-413 AH Cultivated Moench. 165 S. halepense (L.) Pers. WA-235 PH Native 166 Tetrapogon villosus Desf. WA-414 PH Native 167 Themeda anathera (Nees ex WA-201 PH Native Steud.) Hack. 168 Zea mays L. WA-277 AH Cultivated 22. 169 WA-592 PH Native Potamogetonaceae Potamogeton perfoliatus L. 23. Smilacaceae 170 Smilax aspera L. WA-111 C Native 171 S. glaucophylla Klotzsch WA-112 C Native 24. Xanthorrhoeaceae 172 Asphodelus tenuifolius Cav. WA-543 AH Native

Group/Family Sr. Plant Species Voucher Ha. Status # # Dicotyledons 25. Acanthaceae 173 Barleria cristata L. WA-236 DS Native 174 B. acanthoides Vahl WA-109 DS Native 175 Dicliptera bupleuroides Nees WA-415 PH Native 176 Eranthemum WA-605 ES Native pulchellum Andrews 177 Justicia adhatoda L. WA-237 ES Native 178 J. japonica Thunb. WA-349 ES Weed 179 J. quinqueangularis K.D.Koeni WA-346 PH Native g ex Roxb. 180 Strobilanthes WA-177 DS Native dalhousieanus (Nees) C.B. Clarke 181 S. urticifolia Wall. ex Kuntze WA-110 DS Native 182 S. glutinosa J.Graham WA-345 DS Native 26. Adoxaceae 183 Viburnum cotinifolium D. Don WA-205 ES Native 184 V. grandiflorum Wall. ex DC. WA-278 ES Native 185 V. mullaha Buch.-Ham. ex D. WA-344 ES Native Don 27. Aizoaceae 186 Trianthema portulacastrum L. WA-343 AH Weed 28. Amaranthaceae 187 Achyranthes aspera L. WA-114 PH Weed 188 A. bidentata Blume WA-238 PH Weed 189 Aerva javanica (Burm.f.) Juss. WA-115 PH Native ex Schult. 190 Alternanthera pungens Kunth WA-341 PH Naturalised 191 Amaranthus spinosus L. WA-340 AH Native 192 A. viridis L. WA-437 AH Native 193 Chenopodium album L. WA-314 AH Native 194 Digera muricata (L.) Mart. WA-342 AH Weed 195 Dysphania ambrosioides (L.) WA-546 AH Naturalised Mosyakin & Clemants 196 Pupalia lappacea (L.) Juss. WA-542 PH Weed 29. Anacardiaceae 197 Cotinus coggygria Scop. WA-279 DS Native 198 Lannea coromandelica (Houtt.) WA-339 DS Native Merr. 199 Pistacia chinensis Bunge WA-239 DT Native 200 P. chinensis subsp. integerrima WA-240 DT Native (J. L. Stewart ex Brandis) Rech. f. 30. Apiaceae 201 Aegopodium burttii Nasir WA-416 PH New to area 202 Bupleurum marginatum Wall. WA-418 PH Native ex DC. 203 Carissa opaca Stapf ex. Haines WA-199 ES Native 204 Centella asiatica (L.) Urb. WA-336 PH Native 205 Coriandrum sativum L. WA-505 AH Cultivated 206 Eryngium caeruleum M.Bieb. WA-299 AH New to area

Group/Family Sr. Plant Species Voucher Ha. Status # # 207 Foeniculum vulgare Miller. WA-337 PH Cultivated 208 H. cachemiricum C.B. Clarke WA-338 PH Native 209 Heracleum candicans Wall. ex WA-280 PH Native DC. 210 Psammogeton biternatum WA-547 PH Native Edgew. 211 Scandix pecten-veneris L. WA-223 AH Weed 212 Torilis japonica (Houtt.) DC. WA-623 AH Weed 31. Apocynaceae 213 Dregea volubilis (L.f.) Benth. WA-119 C Native ex Hook.f. 214 Nerium oleander L. WA-335 ES Native 215 Tylophora hirsuta Wight WA-594 C Native 32. Aquifoliaceae 216 Ilex dipyrena Wall. WA-117 ET Native 33. Araliaceae 217 Hedera nepallensis K. Koch WA-116 C Native 34. Aristolochiaceae 218 Aristolochia punjabensis Lace WA-532 C Native 35. Asclepiadaceae 219 Calotropis procera (Aiton) WA-333 ES Native Dryand. 220 Periploca aphylla Decne. WA-334 ES Native 221 Vincetoxicum canescens (Willd. WA-118 PH Native ) Decne. 222 V. hirundinaria Medik. WA-565 PH Native 36. Asteraceae 223 Achillea millefolium L. WA-523 PH Native 224 Adenostemma lavenia (L.) WA-573 AH Native Kuntze 225 Ageratum conyzoides (L.) L. WA-550 AH Native 226 Ainsliaea latifolia (D.Don) WA-548 PH Native Sch.Bip. 227 Anaphalis adnata DC. WA-120 AH Native 228 A. busua (Buch.-Ham.) DC. WA-570 AH Native 229 A. margaritacea (L.) Benth. & WA-281 AH Native Hook. f. 230 Artemisia dubia Wall. ex Besser WA-529 AH Native 231 A. scoparia Waldst. & Kitam. WA-551 DS Native 232 A. vulgaris L. WA-552 PH Native 233 Aster flaccidus Bunge WA-124 PH Native 234 A. aitchisonii Boiss. WA-282 PH Native 235 A. himalaicus C.B.Clarke WA-549 PH Native 236 Bidens biternata (Lour.) Merr. WA-298 AH Native & Sherff 237 Calendula officinalis L. WA-553 AH Native 238 Carpesium abrotanoides L. WA-530 AH Native 239 C. cernuum L. WA-572 AH Weed 240 Carthamus oxycantha M. Bieb WA-554 AH Weed 241 Cichorium intybus L. WA-614 PH Weed 242 Cirsium arvense (L.) Scope. WA-555 PH Native 243 Conium maculatum L. WA-606 PH Native

Group/Family Sr. Plant Species Voucher Ha. Status # # 244 Conyza canadensis (L.) Cronq. WA-122 AH Native 245 Cousinia thomsonii C.B.Clarke WA-283 PH Native 246 Crepis multicaulis Ledeb. WA-534 PH Native 247 Eclipta prostrata (L.) L. WA-439 AH Native 248 Erigeron canadensis L. WA-556 AH Native 249 E. multiradiatus (Lindl. ex DC.) WA-536 PH Native Benth. ex C.B. Clarke 250 E. aegyptiacus L. WA-123 AH Native 251 E. bonariensis L. WA-440 AH Native 252 E. trilobus (Decne.) Boiss. WA-125 AH Native 253 Gerbera gossypina (Royle) WA-284 PH Native Beauverd 254 Inula cappa (Buch.-Ham. ex D. WA-575 DS Native Don) DC. 255 Lactuca serriola L. WA-577 AH Native 256 L. brunoniana (DC.) Wall. ex WA-178 AH Native C.B.Clarke 257 L. dissecta D.Don WA-285 PH Native 258 L.secunda (C.B.Clarke) Hook.f. WA-426 PH Native 259 Launaea procumbens (Roxb.) WA-574 PH Native Ram. & Rajgo. 260 Leucanthemum vulgare (Vaill.) WA-580 PH Native Lam 261 Myriactis nepalensis Less. WA-287 PH Native 262 M. wightii DC. WA-286 AH New to area 263 Parthenium hysterophorus L. WA-537 AH Invasive 264 Saussurea heteromalla (D.Don) WA-441 AH Invasive Hand.-Mazz. 265 S. atkinsonii C.B.Clarke WA-417 AH Native 266 Senecio nudicaulis Buch.-Ham. WA-578 AH Native ex D.Don 267 WA-442 AH New to Siegesbeckia orientalis L. Punjab 268 Silybum marianum (L.) Gaertin WA-443 PH Native 269 Sonchus arvensis L. WA-526 AH Native 270 S. asper (L.) Hill WA-571 AH Native 271 S. oleraceus L. WA-569 AH Native 272 Tagetes minuta L. WA-425 AH Invasive 273 Taraxacum campylodes G.E.Ha WA-624 PH Native glund 274 T. wallichii DC. WA-70 PH Native 275 Tridax procumbens (L.) L. WA-242 PH Native 276 Xanthium strumarium L. WA-581 AH Native 277 Youngia japonica (L.) DC. WA-583 AH Native 37. Balsaminaceae 278 Impatiens bicolor Royle WA-290 AH Native 279 I. brachycentra Kar. & Kir WA-288 AH Native

Group/Family Sr. Plant Species Voucher Ha. Status # # 280 I. edgeworthii Hook. f. WA-289 AH Native 281 Sinopodophyllum hexandrum (R WA-144 PH Native oyle) T.S.Ying 38. Berberidaceae 282 Berberis lycium Royle. WA-174 DS Native 283 B. parkeriana C.K.Schneid. WA-291 DS Native 39. Boraginaceae 284 Buglossoides tenuiflora (L.f.) WA-541 AH Native I.M.Johnst. 285 Cynoglossum glochidiatum WA-444 AH Native Wall. ex Benth. 286 C. lanceolatum Forssk. WA-445 AH Native 287 Ehretia acuminata R.Br. WA-563 DT Native 288 E. obtusifolia Hochst. ex A.DC. WA-528 DS Native 289 Heliotropium strigosum Willd. WA-566 AH Native 290 H. crispum Desf. WA-447 AH Native 291 H. europaeum L. WA-524 AH Native 292 Trichodesma indicum (L.) WA-446 PH Native Lehm. 40. Brassicaceae 293 Alliaria petiolata (M.Bieb.) WA-510 AH Native Cavara & Grande 294 Arabis amplexicaulis Edgew. WA-557 PH Native 295 A. nova Vill. WA-616 AH Native 296 Brassica napus L. WA-522 AH Cultivated 297 Capsella bursa-pastoris (L.) WA-576 AH Weed Medik 298 Cardamine impatiens L. WA-562 AH Weed 299 Crucihimalaya himalaica (Edge WA-521 AH Native w.) Al-Shehbaz, O'Kane & R.A.Price 300 Lepidium sativum L. WA-448 AH Cultivated 301 L. didymum L WA-558 AH Native 302 Nasturtium officinale R.Br. WA-559 PH Native 303 Raphanus sativus L. WA-568 AH Cultivated 304 Sisymbrium irio L. WA-449 AH Native 41. Buxaceae 305 WA-564 ES Endamic to Buxus papillosa C.K. Schneid. pakistan 306 Sarcococca saligna (D.Don) WA-292 ES Native Muell.-Arg. 42. Cactaceae 307 Opuntia monacantha (Willd.) WA-561 ES Native Haw. 43. Campanulaceae 308 Campanula pallida Wall WA-438 AH Native 44. Cannabaceae 309 Cannabis sativa L. WA-331 AH Native 45. Caprifoliaceae 310 Lonicera hispida Pall. ex WA-612 ES Native Schult. 311 L. myrtillus Hook. f. & WA-560 ES Native Thomson 312 L. quinquelocularis Hard. WA-206 DS Native 313 L. webbiana Wall. ex DC WA-520 DS Native

Group/Family Sr. Plant Species Voucher Ha. Status # # 46. Caryophyllaceae 314 Cerastium glomeratum Thuill. WA-567 AH Native 315 Silene conoidea L. WA-525 AH Weed 316 Stellaria media (L.) Vill. WA-579 PH Weed 317 Vaccaria hispanica (Mill.) WA-471 AH Native Rauschert 47. Celastraceae 318 Cassine glauca (Rottb.) Kuntze WA-519 DT Native 319 Euonymus fimbriatus Wall. WA-10 DT Native 320 E. hamiltonianus Wall. WA-330 DS Native 321 Maytenus royleanus (Wall. ex WA-329 ES Native Lawson) Cufodontis 48. Convolvulaceae 322 Convolvulus arvensis L. WA-500 C Native 323 C. prostratus Forssk. WA-499 C Native 324 Cuscuta europaea L. WA-498 P Native 325 C. reflexa Roxb. WA-94 P Native 326 C.gigantea Griff. WA-328 P Native 327 Evolvulus alsinoides (L.) L. WA-327 AH Native 328 Ipomoea carnea Jacq. WA-293 C Native 329 I. eriocarpa R. Br. WA-496 C Native 330 I. hederacea (L.) Jacq. WA-497 C Native 331 I. nil (L.) Roth WA-294 C Naturalised 332 I. purpurea (L.) Roth WA-517 C Native 49. Cornaceae 333 Cornus macrophulla Wall. WA-295 ET Native 50. Cucurbitaceae 334 Solena amplexicaulis (Lam.) WA-296 C Native Gandhi 51. Dioscoreaceae 335 Dioscorea belophylla (Prain) WA-494 C Native Voigt ex Haines 336 D. bulbifera L. WA-518 C Native 337 D. deltoidea Wall. ex Griseb. WA-495 C Native 52. Ebenaceae 338 Diospyros lotus L. WA-493 ET Cultivated 53. Elaeagnaceae 339 Elaeagnus angustifolia L. WA-489 ET Native 54. Ericaceae 340 Rhododendron arboreum Sm WA-490 ET Native 55. Euphorbiaceae 341 Euphorbia clarkeana Hook. f. WA-492 AH Native 342 E. granulata Forssk. WA-540 AH Weed 343 E. helioscopia L. WA-491 AH Weed 344 E. heterophylla L. WA-620 AH Native 345 E. hirta L. WA-515 AH Native 346 E. indica Lam. WA-539 AH Native 347 E. prolifera Buch.-Ham. ex WA-621 AH Native D.Don 348 E. prostrata Aiton WA-516 AH Weed 349 E. royleana Boiss WA-618 AH Native 350 E. wallichii Hook.f. WA-619 AH Native 351 Mallotus philippensis (Lam.) WA-210 DS Native Müll. Arg.

Group/Family Sr. Plant Species Voucher Ha. Status # # 352 Ricinus communis L. WA-211 ES Native 56. Fabaceae 353 Acacia catechu (Linn. f.) Willd WA-501 DS Native 354 A. modesta Wall. WA-197 DS Native 355 A. nilotica (L.) Delile WA-196 DS Native 356 Albizzia lebbeck Benth. WA-90 DS Native 357 Alysicarpus bupleurifolius (L.) WA-535 AH Native DC. 358 A. rugosus (Willd.) DC. WA-93 AH Native 359 A. monilifer (L.) DC. WA-218 AH New to area 360 A. ovalifolius (Schum.) Leonard WA-511 AH Native 361 Argyrolobium roseum (Cambess WA-512 AH Native .) Jaub. & Spach 362 Astragalus leucocephalus Bung WA-92 PH Native e 363 Atylosia mollis "Benth., p.p.A" WA-250 AH Native 364 A. platycarpa Benth. WA-249 AH Native 365 A. scarabaeoides (L.) Benth. WA-217 AH Native 366 Bauhinia variegata L. WA-243 DT Native 367 Butea monosperma (Lam.) WA-514 DT Native Taub. 368 Cassia fistula L. WA-216 DT Native 369 Crotalaria prostrata Willd. WA-91 PH Native 370 WA-213 PH New to C. retusa L. punjab 371 WA-214 PH New to C. calycina Schrank punjab 372 C. medicaginea Lam. WA-215 PH Native 373 Dalbergia sissoo DC. WA-209 DT Cultivated 374 Desmodium elegans DC WA-89 DS Native 375 D. gangeticum (L.) DC. WA-297 DS Native 376 D. laxiflorum DC. WA-508 DS Native 377 Hylodesmum podocarpum (DC.) WA-57 DS New to H.Ohashi & R.R.Mill Pakistan 378 Indigofera linifolia (L. f.) Retz. WA-538 AH Native 379 I. cordifolia Roth WA-219 AH Native 380 I. hebepetala Baker WA-509 AH Native 381 I. heterantha Brandis WA-506 DS Native 382 Lathyrus aphaca L. WA-507 AH Weed 383 L. sphaericus Retz. WA-590 AH Native 384 Lespedeza juncea (L.f.) Pers. WA-87 PH Native 385 Leucaena leucocephala (Lam.) WA-484 ET Cultivated de Wit 386 Lotus corniculatus L. WA-504 PH Native 387 Medicago edgeworthii Sirj. WA-221 AH Native 388 M. lupulina L. WA-2 AH Native

Group/Family Sr. Plant Species Voucher Ha. Status # # 389 M. laciniata (L.) Mill WA-483 AH Native 390 M. orbicularis (L.) Bartal. WA-220 AH Native 391 M. polymorpha L. WA-481 AH Weed 392 M. sativa L. WA-482 AH Native 393 Melilotus indicus (L.) All. WA-88 AH Native 394 Mimosa himalayana Gamble WA-488 DT Native 395 Oxytropis mollis Benth. WA-313 PH Native 396 Pongamia pinnata (L.) Pierre WA-502 ET Native 397 Pueraria tuberosa (Willd.) DC. WA-479 C Native 398 Rhynchosia capitata (Roth) DC. WA-476 C Native 399 R. himalensis Baker WA-477 C Native 400 R. minima (L.) DC WA-480 PH Native 401 R. pseudo-cajan Cambess WA-486 DS Native 402 Robinia pseudoacacia L. WA-3 DT Naturalised 403 Taverniera cuneifolia (Roth) Ali WA-487 DT Native 404 Tephrosia strigosa (Dalzell) WA-584 AH Native Santapau & Maheshw. 405 Trifolium dubium Sibth. WA-301 PH introduced 406 T. repens L. WA-300 PH Native 407 T. pratense L. WA-478 PH New to area 408 Trigonella emodi Benth. WA-171 AH Native 409 T. gracilis Benth. WA-170 AH Native 410 Uraria picta (Jacq.) DC. WA-611 AH Native 411 Vicia sativa L. WA-128 AH Weed 412 V. monantha Retz. WA-129 AH Native 57. Fagaceae 413 Quercus dilatata Royle WA-126 ET Native 414 Q. glauca Thunb. WA-173 ET Native 415 Q. incana Bartram WA-86 ET Native 416 Q. oblongata D.Don WA-127 ET Native 58. Gentianaceae 417 Gentiana argentea (Royle ex WA-83 AH Native D.Don) Royle ex D.Don 418 G.olivieri Griseb. WA-302 PH New to area 419 Swertia alata C.B. Clarke WA-4 AH Native 420 S. angustifolia Buch.-Ham. ex WA-131 AH Native D. Don 421 S. ciliata (D. Don ex G. Don) WA-85 AH Native B.L. Burtt 422 S. cordata (Wall. ex G. Don) WA-132 AH Native C.B. Clarke 423 S. paniculata Wall. WA-84 AH Native 424 S. tetragona R.H. Miao WA-130 AH Native 59. Geraniaceae 425 Geranium lucidum L. WA-1 AH Native 426 G. mascatense Boiss. WA-138 AH Native

Group/Family Sr. Plant Species Voucher Ha. Status # # 427 G. nepalense Sweet WA-303 AH Native 428 G. rotundifolium L. WA-137 AH Native 429 G. wallichianum D. Don ex WA-136 AH Native Sweet 60. Grossulariaceae 430 WA-589 DS New to Ribes alpestre Wall. ex Decne. punjab 61. Hamamelidaceae 431 Parrotiopsis jacquemontiana (D WA-5 DS Native ecne.) Rehder 62. Hypericaceae 432 WA-347 DS New to Hypericum dyeri Rehder Punjab 433 H. oblongifolium Choisy WA-135 DS Native 434 H. perforatum L. WA-134 PH Native 63. Juglandaceae 435 Juglans regia L. WA-169 ET Naturalised 64. Lamiaceae 436 Ajuga bracteosa Wall. ex WA-165 PH Native Benth. 437 A. parviflora Benth. WA-166 AH Native 438 Anisomeles indica (L.) Kuntze WA-222 PH Native 439 Callicarpa macrophylla Vahl WA-32 DS Native 440 Clinopodium umbrosum (M.Bie WA-474 PH Native b.) Kuntze 441 Colebrookea oppositifolia Sm. WA-49 DS Native 442 Isodon coetsa (Buch.-Ham. ex WA-473 PH Native D. Don) Kudô 443 I. lophanthoides (Buch.-Ham. WA-475 AH Native ex D. Don) H. Hara 444 I. rugosus (Wall. ex Benth.) WA-304 DS Native Codd 445 Lamium album L. WA-168 PH Native 446 L. cephalotes (Roth) Spreng. WA-246 AH Native 447 Leucas lanata Baker WA-167 PH Native 448 L. decemdentata (Willd.) Sm WA-245 PH Native 449 L. nutans (Roth) Spreng. WA-50 PH Native 450 Mentha longifolia (L.) L. WA-44 PH Native 451 M. royleana Wall. ex Bth. WA-43 PH Native 452 Micromeria biflora (Buch.- WA-244 PH Native Ham. ex D.Don) Benth. 453 Origanum vulgare L. WA-305 PH Native 454 Prunella vulgaris L WA-6 PH Native 455 Pseudocaryopteris bicolor (Rox WA-531 DS Native b. ex Hardw.) P.D.Cantino 456 Pseudocaryopteris foetida (D.D WA-582 DS Native on) P.D.Cantino 457 Rydingia limbata (Benth.) WA-31 DS Native Scheen & V.A.Albert 458 Salvia moorcroftiana Wall. ex WA-26 PH Native Benth. 459 S. plebeia R. Br. WA-46 PH Weed 460 Teucrium quadrifarium Buch.- WA-622 PH Native

Group/Family Sr. Plant Species Voucher Ha. Status # # Ham. 461 T. royleanum Wall. ex Benth. WA-40 PH Native 462 Vitex negundo L. WA-472 DS Native 65. Lauraceae 463 Neolitsea pallens (D. Don) WA-139 ET Native Momiy. & H. Hara 464 Machilus duthiei King WA-140 ET Native 66.Linaceae 465 Reinwardtia indica Dumort. WA-29 DS Native 67.Loranthaceae 466 Scurrula pulverulenta (Wall.) WA-45 P New to G. Don Punjab 68. Lythraceae 467 Woodfordia fruticosa (L.) Kurz WA-7 DS Native 69. Malvaceae 468 Abutilon bidentatum Hochst. ex WA-47 DT Native Rich. 469 Bombax ceiba L. WA-30 DT Cultivated 470 Corchorus aestuans L. WA-430 DS Native 471 Kydia calycina Roxb. WA-48 DT Native 472 Malva neglecta Waller. WA-28 AH Weed 473 Malvastrum aboriginum B.L. WA-202 AH Native Rob. 474 Sida cordifolia L. WA-207 AH Native 475 S. cordata (Burm.f.) WA-51 AH Native Borss.Waalk. 70. Mazaceae 476 Mazus alpinus Masam. WA-458 AH Native 71. Meliaceae 477 Melia azedarach L. WA-42 DT Native 72. Menispermaceae 478 Cissampelos pareira L. WA-247 C Native 73. Molluginaceae 479 Mollugo nudicaulis Lam. WA-27 AH Native 74. Moraceae 480 Broussonetia papyrifera (L.) WA-429 DT Naturalised L'Hér. ex Vent. 481 Ficus auriculata Lour. WA-428 DT Native 482 F. benghalensis L. WA-248 ET Native 483 F. carica L. WA-8 DT Cultivated 484 F. palmata Forssk. WA-306 DT Native 485 F. religiosa L. WA-141 ET Native 486 F. sarmentosa Buch.-Ham. ex WA-33 C Native Sm. 487 Morus alba L. WA-142 DT Native 488 M. nigra L. WA-143 DT Native 75. Myrtaceae 489 Eucalyptus WA-456 DT Introduced camaldulensis Dehnh. 76. Nitrariaceae 490 Peganum harmala L. WA-39 AH Native 77. Nyctaginaceae 491 Boerhavia procumbens Banks WA-9 PH Native ex Roxb. 492 Mirabilis jalapa L. WA-233 AH Naturalised 78. Oleaceae 493 Jasminum humile L. WA-307 DS Native 494 J. officinale L. WA-470 DS Native 495 Olea ferruginea Royle WA-195 ET Native 79. Orobanchaceae 496 Oenothera rosea L'Hér. ex WA-34 PH Native

Group/Family Sr. Plant Species Voucher Ha. Status # # Aiton 80. Oxalidaceae 497 Oxalis corniculata L. WA-192 AH Native 498 O. pes-caprae L. WA-208 PH Native 81. Papaveraceae 499 Corydalis murreeana Jafri WA-41 AH Native 500 Fumaria indica (Hausskn.) WA-450 AH Native Pugsley 82. Phyllanthaceae 501 Andrachne cordifolia (Decne.) WA-176 DS Native Müll.Arg. 502 Bridelia verrucosa Haines WA-52 DS Native 503 Glochidion heyneanum (Wight WA-25 ET Native & Arn.) Wight 504 Phyllanthus emblica L. WA-38 DT Native 505 P. niruri L. WA-451 AH Native 506 P. urinaria L. WA-53 AH Native 507 P. virgatus G.Forst. WA-24 AH Native 83. Plantaginaceae 508 Bacopa monnieri (L.) Wettst. WA-35 AH Native 509 Nanorrhinum ramosissimum (W WA-54 AH Native all.) Betsche 510 Plantago lanceolata L. WA-452 PH Weed 511 P. major L. WA-185 PH Native 512 P. ovata Forssk. WA-184 PH Native 513 Veronica anagallis-aquatica L. WA-460 PH Native 514 V. arvensis L WA-308 AH Native 84. Polygalaceae 515 Polygala abyssinica R.Br. ex WA-81 PH Native Fresen 516 P. arvensis Willd. WA-459 PH Native 517 P. erioptera DC. WA-55 PH Native 85. Polygonaceae 518 Persicaria amplexicaulis (D. WA-80 PH Native Don) Ronse Decr. 519 P. barbata (L.) H.Hara WA-309 AH Native 520 P. hydropiper (L.) Delarbre WA-79 AH Native 521 P. mitis (Schrank) Holub WA-11 AH Native 522 P. nepalensis (Meisn.) Miyabe WA-56 AH Native 523 Polygonum aviculare L. WA-310 AH Native 524 P. plebeium R.Br. WA-37 AH Native 525 Rumex dentatus L. WA-61 AH Weed 526 R. hastatus D. Don WA-82 PH Native 527 R. nepalensis Spreng. WA-36 PH Native 86. Primulaceae 528 Anagallis arvensis L. WA-78 AH Weed 529 Androsace foliosa Duby WA-158 PH Native 530 A. rotundifolia Hardw. WA-75 PH Native 531 A. umbellata (Lour.) Merr. WA-60 AH Native 532 Embelia robusta Roxb. WA-23 DS Native 533 Lysimachia pyramidalis Wall. WA-62 AH Native

Group/Family Sr. Plant Species Voucher Ha. Status # # 534 Myrsine africana L WA-194 ES Native 535 M. semiserrata Wall. WA-12 DS Native 536 Primula denticulata Sm. WA-145 PH Native 87. Punicaceae 537 Punica granatum L. WA-64 DS Native 88. Ranunculaceae 538 Aconitum laeve Royle WA-59 PH Native 539 Anemone tetrasepala Royle WA-146 PH Native 540 A. vitifolia Buch.-Ham. ex DC. WA-76 PH Native 541 Aquilegia pubiflora Wall. ex WA-63 PH Native Royle 542 Clematis barbellata Edgew. WA-311 C Native 543 C. grata Wall. WA-147 C Native 544 C. montana Buch.-Ham. ex DC. WA-58 C Native 545 Ranunculus arvensis L. WA-312 AH Weed 546 R.laetus Wall. ex Hook. f. & WA-157 PH Native J.W. Thomson 547 R. muricatus L. WA-148 AH Weed 548 R. sceleratus L. WA-149 AH Native 89. Rhamnaceae 549 Rhamnus purpurea Edgew. WA-77 DT Native 550 R. triquetra (Wall.) Brandis WA-22 DT Native 551 R.virgata Roxb. WA-13 DT Native 552 Sageretia thea (Osbeck) M.C. WA-461 DS Native Johnston 553 Ziziphus jujuba Mill. WA-462 DT Cultivated 554 Z. mauritiana Lam. WA-155 DT Native 555 Z. oxyphylla Edgew. WA-156 DS Native 90. Rosaceae 556 Agrimonia eupatoria L. WA-463 AH Native 557 Cotoneaster affinis Lindl. WA-464 DS Native 558 Duchesnea indica (Jacks.) WA-186 PH Native Focke 559 Fragaria nubicola (Hook. f.) WA-465 PH Native Lindl. ex Lacaita 560 Malus domestica Borkh. WA-466 DT Cultivated 561 Potentilla reptans L. WA-320 PH Native 562 Prunus armeniaca L. WA-113 DT Cultivated 563 P. domestica L. WA-315 DT Cultivated 564 P. persica (L.) Batsch WA-121 DT Cultivated 565 Pyrus pashia Buch.-Ham. ex D. WA-204 DT Native Don 566 Rosa moschata Herrm. WA-316 DS Native 567 Rosa multiflora Thunb. WA-513 DS Native 568 Rubus ellipticus Sm. WA-469 DS Native 569 R. anatolicus Focke WA-593 DS Native 570 R. fruticosus L. WA-14 DS Native 571 R. niveus Thunb. WA-179 DS Native

Group/Family Sr. Plant Species Voucher Ha. Status # # 572 R. sanctus Schreb. WA-317 DS Native 573 R. ulmifolius Schott WA-410 DS Native 574 Spiraea canescens D. Don WA-21 DS Native 91. Rubiaceae 575 Galium acutum Edgew. WA-159 AH Native 576 G. aparine L. WA-424 AH Native 577 G. asperifolium Wall. WA-161 AH Native 578 G. elegans Wall. ex Roxb. WA-160 PH Native 579 G. rotundifolium L. WA-193 PH Native 580 Himalrandia tetrasperma (Wall. WA-423 DS Native ex Roxb.) T.Yamaz. 581 Pavetta tomentosa Roxb. ex WA-318 DS Native Sm. 582 Rubia cordifolia L. WA-162 C Native 583 Wendlandia heynei (Schult.) WA-20 DT Native Santapau & Merchant 92. Rutaceae 584 Zanthoxylum armatum DC. WA-422 DS Native 93. Salicaceae 585 Flacourtia indica (Burm. f.) WA-152 DT Native Merr. 586 Populus deltoides Marshall WA-421 DT Naturalised 587 Salix acmophylla Boiss. WA-15 DT Native 588 S. tetrasperma Roxb. WA-485 DT Naturalised 589 Xylosma longifolia Clos WA-150 DT Native 94. Sapindaceae 590 Aesculus indica (Wall. ex WA-468 DT Native Cambess.) Hook. 591 Cardiospermum halicacabum L. WA-151 AH Native 592 Dodonaea viscosa (L.) Jacq. WA-198 ES Native 95. Saxifragaceae 593 Bergenia ciliata (Haw.) Sternb. WA-19 PH Native 96. Scrophulariaceae 594 Verbascum thapsus L. WA-319 PH Native 97. Simaroubaceae 595 Ailanthus altissima (Mill.) WA-16 DT Naturalised Swingle 98. Solanaceae 596 Datura innoxia Mill. WA-17 AH Naturalised 597 D. stramonium L. WA-68 AH Native 598 Physalis divaricata D. Don WA-326 AH Weed 599 Solanum americanum Mill. WA-163 AH Weed 600 S. erianthum D. Don WA-325 AH Native 601 S. incanum L. WA-324 AH Weed 602 S. surattense Burm. f WA-67 AH Native 603 S. villosum Mill. WA-164 AH Weed 604 Withania somnifera (L.) Dunal. WA-74 PH Native 99. Thymelaeaceae 605 Daphne papyracea Wall. ex G. WA-175 ES Native Don 100. Tiliaceae 606 Grewia asiatica L. WA-69 DT Native 607 G. eriocarpa Juss. WA-613 DT New to area 608 G. optiva J.R.Drumm. ex Burret WA-153 DT Native

Group/Family Sr. Plant Species Voucher Ha. Status # # 609 G. tenax (Forssk.) Fiori WA-71 DT Native 101. Ulmaceae 610 Celtis australis subsp. caucasic WA-154 ET Native a (Willd.) C.C.Towns. 102. Urticaceae 611 Debregeasia saeneb (Forssk.) WA-72 ES Native Hepper & J.R.I.Wood 612 Urtica dioica L. WA-18 PH Native 613 U. pilulifera L. WA-73 PH Native 103. Valerianaceae 614 Valeriana hardwickii Wall. WA-420 PH New to area 615 V. jatamansi Jones WA-348 PH Native 104. Verbenaceae 616 Glandularia aristigera (S.Moor WA-332 AH Introduced e) Tronc. 617 Lantana camara L. WA-323 ES Naturalised 618 L. indica Roxb. WA-322 ES Naturalised 619 Phyla nodiflora (L.) Greene WA-419 AH Native 620 Verbena officinalis L. WA-321 AH Weed 105. Violaceae 621 Viola cancescens Wall. WA-467 PH Native 622 WA-212 PH Endamic to Pakistan/Ne V. makranica Omer & Qaiser w to Punjab 623 V. pilosa Blume WA-66 PH Native 106. Zygophyllaceae 624 Tribulus terrestris L. WA-65 AH Weed

90 80 70 60 50 40 30 Spp# 20 Percentage 10 0

Fig. 2.3.Top 10 families of vascular flora of Murree-Kotli Sattian-Kahuta National Park.

4% 4% 4% Parasites 7% Evergreen 38% shrubs Evergreen trees 10% Climbers

Deciduous trees

32%

Fig 2.4.Habit form of the flora of Murree-Kotli Sattian-Kahuta National Park.

600

500

400

300

200

100

0 Endamic Cultivate Naturalis New to Introduc Native Weed Invasive to d ed Area ed Pakistan No. 511 48 21 18 16 4 4 2 %age 81.89 7.69 3.37 2.88 2.56 0.64 0.64 0.32

Fig. 2.5.Regional status of the flora of Murree-Kotli Sattian-Kahuta National Park.

spp., 7.37%), climbers (26 spp., 4.17%), evergreen shrubs (23 spp., 3.69%), evergreen trees (23 spp., 3.69%) while parasites were almost in negligible proportion (i.e. 4 spp., 0.64%), (Fig. 2.4). As a whole the vegetation of Murree-

Kotli Sattian-Kahuta National Park is dominated by the hemicryptophytes with

28.75% contribution to the flora, followed by Therophytes with 27.92% contribution. Other life form with decreasing order of percentage contribution was nanophanerophytes (17.22%), macrophanerophytes (13.29 %), chamaephytes

(5.70%), geophytes (3.93%) and lianas (3.18%). Overall the vegetation was of

Hemi-therophyte type. With respect to leaf spectra the MKSKNP is dominated by

Microphylls with 31.82% contribution. Nanophylls were (30.40%) the next most important leaf spectra class followed by Leptophylls (24.72%) and Mesophylls

(13.07%) contribution. Hence the area is of Micr-Nano-Leptophyllous type.

Comparing the plant species with related floras, most of the species (511 spp.,

81.89%) were found to be the native species of the area, followed by 48 weed species (7.69%). Cultivated species were 21 (3.37%), 18 species (2.88%) were naturalized, 16 species (2.56%) were new to area, 3 species were introduced to the area. While two species viz., Viola makranica and Buxus papillosa are endemic to the Pakistan (Table 2.2).

This floristic checklist provides baseline information to be used for further taxonomic and ecological research in future. As for as the contribution to the flora of Murree Kotli Sattian Kahuta national park is concerned, following species are reported for the first time from the study area viz.Ophiopogon intermedius, Festuca kashmiriana, Crotalaria retusa, Crotalaria calycina, Ribes alpestre, Viola makranica, Hypericum dyeri, Scurrula pulverulenta, Festuca gigantea, Myriactis

120 0.370

0.360 0.360

100 0.355 95 96 89 0.350 95 93 80 80

72 74 0.340 Value

0.334 72 - 0.331 0.337 60 0.3340.330 0.323 0.321 0.320

40 0.316 P Average 0.310

Number of Significant species Significantof Number 20 0.300

0 0.290

Significant species Average P-value

Fig.2.6. Determination of the number of ecologically meaningful communities in Murree Kotli Sattian Kahuta national park, Pakistan.

Fig. 2.7. Cluster dendrogram of 246 samples based on Sorensen measures showing 7 plant communities

74 74 75

Table 2.3. Pairwise comparison (MRPP) of seven plant communities Murree Kotli Sattian Kahuta national park, Pakistan.

Species groups compared T-value A-value p-value 1. TGG vs. 2. DCD -25.39442661 0.18243753 0.00000000 1. TGG vs. 3. AOX -31.05069093 0.18220546 0.00000000 1. TGG vs. 4. JMA -26.67223293 0.16132233 0.00000000 1. TGG vs. 5. MTD -26.80194792 0.07465266 0.00000000 1. TGG vs. 6. MOP -32.16523408 0.12683917 0.00000000 1. TGG vs. 7. PVD -45.90722034 0.14877765 0.00000000 2. DCD vs. 3. AOX -14.96841461 0.05571134 0.00000000 2. DCD vs. 4. JMA -14.62000135 0.05522311 0.00000000 2. DCD vs. 5. MTD -20.84535713 0.05614998 0.00000000 2. DCD vs. 6. MOP -32.60144239 0.11679666 0.00000000 2. DCD vs. 7. PVD -41.24665087 0.10731748 0.00000000 3. AOX vs. 4. JMA -18.70918204 0.06414353 0.00000000 3. AOX vs. 5. MTD -26.19438868 0.06139754 0.00000000 3. AOX vs. 6. MOP -34.09482821 0.10308181 0.00000000 3. AOX vs. 7. PVD -45.63444168 0.11041793 0.00000000 4. JMA vs. 5. MTD -20.94110778 0.04906582 0.00000000 4. JMA vs. 6. MOP -29.15421545 0.08488454 0.00000000 4. JMA vs. 7. PVD -27.90371457 0.05587425 0.00000000 5. MTD vs. 6. MOP -25.47303793 0.04894967 0.00000000 5. MTD vs. 7. PVD -48.41666781 0.08507354 0.00000000 6. MOP vs. 7. PVD -35.02655218 0.06525562 0.00000000

wightii, Viola makranica, Aegopodium burttii, Eryngium caeruleum, Alysicarpus monilifer, Gentianaolivieri, Grewia eriocarpa, and Valeriana hardwickii (Table

2.2).

2.4.2 Phytosociology

The delineation of vegetation groups were done based on similarity in species composition. Hierarchical clustering classified the samples into seven groups of vegetation communities. The maximum number of significant (p ≤ 0.05) species with minimum average p value criteria was used to demined the number of biologically significant communities. The minimum mean p-value (0.32) and maximum number of significant indicator species (96) were recorded at 7th level of division of dendrogram (Fig.2.5). Thus we detected seven ecologically meaningful

(significant) vegetation clusters. The two main branches of the dendrogram separated the lower altitude vegetation with the average elevation of 1055m comprising five communities, characterized by temperate vegetation from the higher altitude (average elevation of (1693m) vegetation comprising two communities dominated by Pinus roxbughii and Pinus wallichiana.

Thus accordingly all the 246 vegetation samples were categorized into 7 vegetation groups/community types viz. group 1 (n = 23), group 2 (n = 21), group 3

(n = 31) and group 4 (n = 22), group 5 (n = 49), group 6 (n = 45), group7 (n = 55), where n represent the number of samples (Fig. 2.6). Introduction of associated grouping variable (1-7) for 246 samples and subsequent indicator species analysis enables us to detect the leading indicator species of each group on the basis of their indicator value, which were subjected to Monte Carlo test for testing their

statistical significance. Three leading significant indicator species (p ≤ 0.5) of each vegetation community was used to name the respective community type (1-7) i.e.

1. Themeda-Galium-Gerbera (TGG) community, 2.Dodonaea-Carissa-Dalbergia

(DCD) community, 3.Adiantum-Olea-Xylosma, (AOX) community, 4.Justicia-

Mallotus-Asplenium (JMA) community, 5.Micromeria-Taraxacum-Dichanthium

(MTD) community, 6.Myrsine-Oplismenus-Pinus (MOP) community, 7.Pinus-

Viburnum-Daphne (PVD) community (Table 2.3). Pairwise MRPP comparison of all the seven plant communities showed that they are significantly (p < 0.00004) different with respect to their species composition. They also showed negative T values, as more negative T value indicates stronger separation of the two communities thus depicting maximum heterogenicity between all communities.

Pairwise MRPP analyses also gave A-values (within-group agreement) in the range of 0.05 to 0.18 for all the pair wise comparisons of the plant communities. This proves that within groups heterogeneity equals expectation by chance. As A-value of A max = 1 means all items/samples within groups are identical, A = 0 means that within groups heterogeneity equals expectation by chance and A < 0 means that within groups heterogeneity is higher than expected by chance (Table.2.4)

2.4.2.1 Plant communities

2.4.2.1.1. Themeda-Galium-Gerbera (TGG) community

The vegetation community was found at middle elevation 976 -1776 m comprised of hilly terrain, represented by 23 samples and was distributed in belt between 33°41'-33°59"N latitude and 73°14'-73°31E longitude. The community is represented in Dhar, Ocha, Nar, low elevation of Parinola Reserve Forest, Kohati,

Dewal Reserve Forest, Nankot, Angori village, Lehtrar, Blawra, Kotli Sattian and

Broa. The inclination varied between 17-40°.

The soil of this community type is clayey-clay loam type with almost neutral pH (i.e 6.79±0.19) and the moisture content of 55.52±9.62%. The organic matter content in the soil of the community was 1.19±0.53%, Nitrogen was

0.06±0.03mg/ Kg, Phosphorus was 9.24±4.26 mg/ Kg and Potassium was

120.91±48.04 mg/ Kg (Table 2.5). The area covered with vegetation was

48±10.9%, of which tree layer covered 42.74±21.64% of the area, 20.91±15.83% area was covered by shrubs and herbs covered 80.35±21.93 % of the area (Table

2.5). The number of recorded plant species from the community was 129, of which

43 species were the indicator species of the community. Shannon index was

1.71±0.28, Inversion Simpson index was 3.16±0.82, Simpson index was 0.66±0.09,

Pielou evenness was 0.62±0.08 whereas Margalrf Richness and Menhinick

Richness were 3.13±0.62 and 1.52±0.34 respectively (Table 2.6).

The community was given the name after Themeda anathera (64.1),

Galium aparine (11.9) and Gerbera gossypina (11.2) because of having high indicator value and low p value <0.5. The whole area was represented by 129 plant species of which the species found to be the indicator of the community were 43.

The significant indicator species of the association (SIS) having p value <0.5 were,

T. anathera , G. aparine, G. gossypina, Sonchus arvensis and Myriactis nepalensis

( Table 2.4).

The indicator species of the community with dominant indicator value were Themeda anathera (64.1), Galium aparine (11.9), Gerbera gossypina (11.2),

Sonchus arvensis (10.6), Viola cancescens (9.4), Arthraxon prionodes (7.6), Ficus carica (7.5), Myriactis nepalensis (7.2), Debregeasia saeneb (6.2), Cousinia thomsonii (5.9), Ageratum conyzoides (5.8), Bromus oxyodon (5.7), Polygala abyssinica (5.6), Lactuca dissecta (5.4), Adiantum incisum (4.3), Agrostis gigantea

(4.3), Capillipedium parviflorum (4.3), Carpesium abrotanoides (4.3), Euphorbia prolifera (4.3), Inula conyza (4.3), Isodon rugosus (4.3), Juncus articulatus (4.3),

Medicago orbicularis (4.3), Phyllanthus niruri (4.3), Spiranthes sinensis (4.3)and

Swertia tetragona (4.3) whereasthe plent species with least indicator value were

Bupleurum marginatum (2.3), Rumex hastatus (2.2), Cornus oblonga (1.9) and

Anaphalis adnata (1.6).

The more consistent species of the communities were Themeda anathera with the frequency valueof 100%, followed by Viola cancescens (39%), Galium aparine (35%), Gerbera gossypina (35%), Sonchus arvensis (22%), Arthraxon prionodes (17%), Ficus carica (17%), Lactuca dissecta (17%), Cousinia thomsonii

(13%), Indigofera heterantha (13%) and Polygala abyssinica (13%).The Exclusive species species of the community were Adiantum incisum, Agrostis gigantean,

Capillipedium parviflorum, Carpesium abrotanoides, Euphorbia prolifera, Inula conyza, Isodon rugosus, Juncus articulates, Medicago orbicularis, Phyllanthus niruri, Spiranthes sinensis and Swertia tetragona. The community is dominated by herbs which contribute to 68.99% of the total flora followed by herbs (22.48%) and trees contributed 8.85%. the Therophytes was the dominant life form of the community with the share of 30.23%, followed by hemicryptophytes (27.13%).

Other life form with decreasing order was nanophanerophytes (19.38%), chamaephytes (8.53%), macrophanerophytes (7.75%), lianas (3.88%) and

geophytes (3.10%). The dominant leaf spectra class was Microphylls with 33.33% contribution. Nanophylls were (31.78%), whereas Leptophylls and Mesophylls

(24.03%) and (10.85%) respectively. The community was designated as Micr-

Nano-Leptophyllous community.

2.4.2.1.2. Dodonaea-Carissa-Dalbergia (DCD) community

The community is represented by 21 samples present between 33°30'-

33°57'N latitude and 73°14'-73°35' E longitude. The community is confined to lowest elevation (436-1128m) with the mean elevation of 794.81±187.31 m. The community is represented in Krot, Near Simli Dam, Broa, Kohati, Azad Patan and

Nara areas. The area is having the low inclination 24.24°±13.79°.

The soil of the association is mostly clayey with few sites having loam with the pH value of 78±0.37 with the moisture content of 52.43±16.16%. The organic matter content in the soil of the community is 0.98±0.54% which is lowest compare to all other communities. The soil contains 0.05±0.03mg/ Kg Nitrogen,

7.41±4.62mg/ Kg Phosphorus, 108.57±57.82 mg/ Kg Potassium. Electric conductivity of soil was 0.81±0.18 and total soluble salt content was

517.49±113.50 mg/ Kg. The area of the community, covered with vegetation was

42.33±9.67%. Most of the area (55.45±30.37%) was covered by shrubs followed by tree layer, covering 39.02±21.183% of the area and herbs have the least cover contribution 32.53±21.14% of the area. The total number of species present in the community was 99, of which 44 species were the indicator species of the community. Margalrf Richness was 3.23±0.78 and Menhinick Richness was

2.04±0.56, Simpson index was 0.85±0.05, Shannon index was 2.25±0.32, Inversion

Simpson index was 7.65±2.90, Pielou evenness was 0.85±0.06, (Table 2.6).

The community was given the name after Dodonaea viscose, Carissa opaca and Dalbergia sissoo because of having high significant (p value <0.5) indicator value. The community was represented by 99 plant species. There were 42 species as indicator species of the community determined. The diagnostic species of the communities with dominant indicator value were Dodonaea viscosa (49.6), Carissa opaca (29.2), Dalbergia sissoo (22.3), Sida cordata (22.2), Cassia fistula (16.6),

Flacourtia indica (16.4), Indigofera linifolia (15), Atylosia scarabaeoides (14.3),

Acacia modesta (13.5), Dicliptera bupleuroides (13), Bidens biternata (12.4),

Grewia optiva (11.6), Celtis australis.(10.1), Boerhavia procumbens (9.9) and

Alysicarpus monilifer (9.5).

The most frequent species of the association were Dodonaea viscosa (95%),

Carissa opaca (76%), Flacourtia indica (43%), Dicliptera bupleuroides (43%),

Cassia fistula (33%), Dalbergia sissoo (29%), Celtis australis (24%), Acacia modesta (24%), Bidens biternata (19%), Atylosia scarabaeoides (14%), Apluda mutica (14%), and Boerhavia procumbens (14%).Saussurea heteromalla, Launaea procumbens, Brachiaria ramosa, Conyza canadensis, Leucas decemdentata,

Leucas decemdentata and Cynoglossum lanceolatum, are the rare species of the community.

The exclusive species of the community were Alysicarpus monilifer,

Atylosia scarabaeoides, Commelina paludosa, Curculigo orchioides, Cyperus alopecuroides, Cyperus iria, Eragrostis amabilis, Grewia eriocarpa, Pueraria tuberosa and Tribulus terrestris.The community is dominated by herbs which

contribute to 66.67% of the total flora followed by trees (17.17%) and herbs

(16.67%). The Therophytes was the dominant life form of the community with the share of 30.30%, followed by hemicryptophytes (25.25%). macrophanerophytes

(17.17%) nanophanerophytes (14.14%) chamaephytes (6.06%), geophytes (4.04%) and lianas (3.03%). Microphylls had the highest share of 30.30% in the community. Nanophylls and Leptophylls had the contribution of 28.27% 27.27% respectively, where as Mesophylls contributed 14.14%. The community was designated as Micr-Nano-Leptophyllous.

2.4.2.1.3. Adiantum-Olea-Xylosma (AOX) community

The community is distributed in north west of the park between

33°41'05.32"N"-33°50'37.07"N latitude and 73°20'06.07"E-73°28'44.02"E longitude, and determined on the basis of 31 samples. The community is confined relatively to low elevation between 700 to 1208 m with the mean elevation of

990.86±116.54m with the average inclination of of 27.58°±12.10°. The community is represented in Angori, Bhang reserve forest, Karor, Lehtrar, Manga Reserve forest, Nandkot Reserve forest, Sain and Sneo areas.

The soil of the association is mostly clay Loam with few sites having

Clayey soil having the pH value of 6.73±0.26) with the moisture content of

53.95±8.29%. The soil of the community contains relatively high organic matter content (1.25±0.52%). The soil contains 0.06±0.03mg/ Kg Nitrogen, 9.85±3.41mg/

Kg Phosphorus and 130.65±34.15mg/ Kg Potassium. Electric conductivity of soil was 1.03±0.29 and total soluble salt content was 662.19±184.81 mg/ Kg.

The total area of the community covered with vegetation was

44.13±38.25%. Most of the area was covered by trees and shrubs with

51.39±28.65% and 50.42±27.86% cover contribution respectively followed by herbs which covered 30.57±18.86 of the area (Table 2.5). Simpson index was

0.85±0.05, Pielou evenness was 0.85±0.06, Shannon index was 2.25±0.32,

Inversion Simpson index was 7.65±2.90, Margalrf Richness and Menhinick

Richness have the value of 2.81±0.91 and 1.78±0.56 respectively (Table 2.6).The community was given the name after Adiantum caudatum (37.7), Olea ferruginea

(33.4) and Xylosma longifolium (26.7) because of having high indicator value and low p value <0.5 (Table 2.4). The community was ihibited by 92 plant species of which 17 species were the indicator species of the community type The significant indicator species of the association (SIS) having p value <0.05 were Adiantum caudatum, Olea ferruginea, Xylosma longifolium, Sageretia thea, Cissampelos pareiraand Brachiaria reptans.

The diagnostic species of the communities with dominant indicator value were Adiantum caudatum (37.7), Olea ferruginea (33.4), Xylosma longifolium

(26.7), Brachiaria reptans (17.6), Sageretia thea (12.3), Cissampelos pareira

(12.2) and Maytenus royleanus (9).The rare species of the community were

Broussonetia papyrifera, Indigofera cordifolia, Phyllanthus emblica, Solanum surattense, Siegesbeckia orientalis, Ficus auriculata and Callicarpa macrophylla.The most frequent species of the association wereOlea ferruginea,

Xylosma longifolium, Maytenus royleanus, Adiantum caudatum,Sageretia thea,

Cissampelos pareira and Zanthoxylum armatum. Ware as the exclusive species of the community were Broussonetia papyrifera, Indigofera cordifolia, Phyllanthus

emblica and Solanum surattense.The community is dominated by herbs which contribute to 61.96% of the total flora followed by shrub (19.56%) and tree

(18.49%). Hemicryptophytes was the dominant life form of the community with the share of (30.43%), followed by Therophytes (23.91%), nanophanerophytes

(19.57%), macrophanerophytes (17.39%), chamaephytes and lianas (3.26% each), and geophytes (2.17%). Microphylls had the highest share of 34.78% in the community. Nanophylls and Leptophylls had the contribution and 29.35% and

19.57% respectively. Mesophylls had the least contributed (16.30%). The community was designated as Micr-Nano-Leptophyllous.

2.4.2.1.4. Justicia-Mallotus-Asplenium (JMA) community

The vegetation community was found in at an average elevation of

864.14±495.45 m. The community is presented by 22 samples distributed in

33°29'N-34°00'N latitude and 73°17' E-73°36'E longitude. The community is represented in Azad Patan, Burban Reserve Forest, Dewal, Gianthal Reserve

Forest, Gura Reserve Forest, Krot, Nara, Ocha, Burban, Pail, Sain and Thuther areas. The soil of the association is Loamy with lowest moisture content

(44.27±14.52%) having the pH value of 6.53±1.29. The organic matter content in the soil of the community is 1.06±0.50% with Nitrogen content of 0.05±0.02mg/

Kg and contains 7.05±4.32 mg/ Kg Phosphorus, 121.82±48.05 mg/ Kg Potassium.

The electric conductivity of the soil was 0.81±0.19 whereas total soluble salt were

521.31±124.38 mg/ Kg.

The total area of the community covered with vegetation was

43.29±37.86%, of which tree layer covered 52.81±32.23% of the area, whereas

43.56±25.84% area was covered by herbs and shrubs covered 33.51±20.71% of the area (Table 2.5). Margalrf Richness was 2.96±0.84 and Menhinick Richness was found to be 1.77±0.49, Pielou evenness was 0.78±0.15, Simpson index was

0.77±0.15, Shannon index was 2.00±0.47, Inversion Simpson index was 5.93±3.13,

(Table 2.6).

The community was given the name after Justicia adhatoda, Mallotus philippensis and Asplenium trichomanes because of having high indicator value and low p value <0.05. The community was represented by 137 plant species containg 51 indicator species. Seventeen species were the significant indicator species (p <0.05.) of the community (SIS). The diagnostic species of the association with dominant indicator value were Justicia adhatoda (37.1), Mallotus philippensis (28.9), Asplenium trichomanes (26.3), Duchesnea indica (21.3),

Pennisetum orientale (13.6), Lolium temulentum (13), Nerium oleander (12.4),

Cynodon dactylon (11.7), Saccharum spontaneum (10.8), Acacia nilotica (10.7) and Cannabis sativa (9.1).The rare plant species of the community were Verbena officinalis, Lantana camara, Cassine glauca, Aesculus indica, Cynoglossum glochidiatum, Erigeron bonariensis, Justicia japonica, Swertia paniculata, Setaria pumila and Ziziphus mauritiana. The more consistent species of the communities were Mallotus philippensis, Justicia adhatoda, Lespedeza juncea, Asplenium trichomanes, Crotolaria medicagnea, Setaria viridis, Acacia nilotica, Aristida cyanantha, Cynodon dactylon, Saccharum spontaneum, Lolium temulentum and

Pennisetum orientale.The Exclusive species of the community were Cannabis sativa, Chenopodium album, Cymbopogon martini, Datura stramonium, Dryopteris filix-mas, Embelia robusta, Equisetum ramosissimum, Eryngium caeruleum,

Festuca gigantea, Fimbristylis squarrosa, Hippochaete debilis, Kydia calycina,

Leucas nutans, Paspalum distichum, Pennisetum orientale, Phyla nodiflora,

Pupalia lappacea, Sauromatum venosum, Solanum americanum, Solanum erianthum, Vitex negundo.

The community is dominated by herbs which contribute to 65.69% of the total flora followed by trees (18.25% and shrubs (16.06%). The hemicryptophytes was the dominant life form of the community with the share of (30.66%), followed by Therophytes (27.74%) other life form with decreasing order were macrophanerophytes (17.52%), nanophanerophytes (16.06%), chamaephytes

(4.38%), Geophytes (2.92%). Whereas lianas (0.73%) have the least contribution which is lowest compared to any other community. The dominant leaf spectra class was Microphylls with 33.58% contribution followed by Nanophylls (28.82%),

Leptophylls (24.09%) and Mesophylls (17.52%). The community was designated as Micr-Nano- Leptophyllous.

2.4.2.1.5. Micromeria-Taraxacum-Dichanthium (MTD) community

The community is determined on the basis of 49 samples, located between

33°05'N-33°56'N latitude and 73°14'E-73°35'E longitude. The community has the mean elevation of 1170.53±310.94m and the average inclination of 26.45°±13.45°.

The community is represented in Kalla Bsand Reserve Forest, Angori, Bagga

Reserve Forest, Kamra Reserve Forest, Chalawra, Kohati, Kror, Lehtrar, Trait,

Simli Dam, Sain, Nara, Paija, and Nar regions. The soil analysis of the association of MKSKNP was found to be mostly clay Loam and Clayey and have the pH value of 6.77±0.25 and moisture content of 54.90±10.31%. The soil of the

Table. 2.4.Indicator species analysis (ISA) of the plant communities of the study area.

Sr.No. Species name Abbrev. Max IV Max Grp IV Within Groups T IV IV from randomized groups 1 2 3 4 5 6 7 Obs. IV Mean SD p- value 1 Themeda anathera The.ana 64 1 64 5 3 0 11 6 0 89 64.1 13.2 2.57 0.001 2 Galium aparine Gal.apa 12 1 12 0 0 0 2 11 5 30 11.9 7.2 2.2 0.041 3 Gerbera gossypina Ger.gos 11 1 11 0 0 0 4 2 4 21 11.2 5.9 2.36 0.04 4 Sonchus arvensis Son.arv 11 1 11 1 0 1 0 1 0 14 10.6 3.5 1.89 0.012 5 Viola cancescens Vio.can 9 1 9 0 0 0 7 6 5 27 9.4 7.4 2.45 0.1812 6 Arthraxon prionodes Art.pri 8 1 8 0 0 0 0 0 4 12 7.6 4.6 2.25 0.0941 7 Ficus carica Fic.car 8 1 8 0 1 0 1 1 0 11 7.5 3.9 2.06 0.0541 8 Myriactis nepalensis Myr.nep 7 1 7 0 0 0 0 0 0 7 7.2 2.6 1.48 0.038 9 Debregeasia saeneb Deb.sae 6 1 6 0 0 2 0 0 0 8 6.2 3.7 2.14 0.1321 10 Cousinia thomsonii Cou.tho 6 1 6 0 0 0 0 1 2 9 5.9 3.7 1.84 0.0941 11 Ageratum conyzoides Age.con 6 1 6 0 0 0 0 2 0 8 5.8 2.8 1.78 0.0691 12 Bromus oxyodon Bro.oxy 6 1 6 0 0 0 0 0 0 6 5.7 2.7 1.66 0.0761 13 Polygala abyssinica Pol.aby 6 1 6 0 0 0 5 0 0 11 5.6 3.5 2.01 0.1201 14 Lactuca dissecta Lac.dis 5 1 5 0 2 0 2 4 0 13 5.4 4.7 1.97 0.2703 15 Adiantum incisum Adi.inc 4 1 4 0 0 0 0 0 0 4 4.3 2.9 1.12 0.2743 16 Agrostis gigantean Agr.gig 4 1 4 0 0 0 0 0 0 4 4.3 2.9 1.13 0.2873 17 Capillipedium parviflorum Cap.par 4 1 4 0 0 0 0 0 0 4 4.3 2.8 1.11 0.2663 18 Carpesium abrotanoides Car.abr 4 1 4 0 0 0 0 0 0 4 4.3 2.8 1.1 0.2603 19 Euphorbia prolifera Eup.pro1 4 1 4 0 0 0 0 0 0 4 4.3 2.8 1.09 0.2563 20 Inula conyza Inu.con 4 1 4 0 0 0 0 0 0 4 4.3 2.8 1.1 0.2593 21 Isodon rugosus Iso.rug 4 1 4 0 0 0 0 0 0 4 4.3 2.9 1.12 0.2723

Sr.No. Species name Abbrev. Max IV Max Grp IV Within Groups T IV IV from randomized groups 1 2 3 4 5 6 7 Obs. IV Mean SD p- value 22 Juncus articulates Jun.art 4 1 4 0 0 0 0 0 0 4 4.3 2.8 1.1 0.2603 23 Medicago orbicularis Med.orb 4 1 4 0 0 0 0 0 0 4 4.3 2.9 1.13 0.2873 24 Phyllanthus niruri Phy.nir 4 1 4 0 0 0 0 0 0 4 4.3 2.8 1.11 0.2663 25 Spiranthes sinensis Spi.sin 4 1 4 0 0 0 0 0 0 4 4.3 2.8 1.1 0.2603 26 Swertia tetragona Swe.tet 4 1 4 0 0 0 0 0 0 4 4.3 2.8 1.11 0.2653 27 Trichodesma indicum Tri.ind 4 1 4 3 0 1 0 0 0 8 4.2 2.8 1.75 0.1772 28 Clematis grata Cle.gra 4 1 4 1 1 0 0 0 1 7 4 3.4 1.83 0.2833 29 Isodon coetsa Iso.coe 4 1 4 0 0 0 1 1 2 8 4 4.1 2.27 0.4044 30 Viola pilosa Vio.pil 4 1 4 0 0 0 0 2 1 7 4 3 1.75 0.2292 31 Cotinus coggygria Cot.cog 4 1 4 0 0 0 0 0 0 4 3.6 2.8 1.48 0.2903 32 Indigofera heterantha Ind.het 3 1 3 0 0 1 0 0 3 7 3.4 4 2.19 0.4975 33 Jasminum officinale Jas.off 3 1 3 0 0 0 0 1 0 4 3.2 2.8 1.55 0.3473 34 Senecio nudicaulis Sen.nud 3 1 3 1 1 0 2 0 0 7 3.1 3.5 1.76 0.4905 35 Rubus ulmifolius Rub.ulm 3 1 3 0 0 0 2 0 0 5 2.6 2.7 1.61 0.3183 36 Argyrolobium roseum Arg.ros 3 1 3 1 0 1 0 0 0 5 2.5 2.9 1.65 0.5165 37 Geranium mascatense Ger.mas 2 1 2 0 0 0 1 2 0 5 2.4 3 1.69 0.5516 38 Rydingia limbata Ryd.lim 2 1 2 1 0 0 0 0 0 3 2.4 2.7 1.65 0.4775 39 Trigonella emodi Tri.emo 2 1 2 0 0 0 0 0 1 3 2.4 2.8 1.44 0.5976 40 Bupleurum marginatum Bup.mar 2 1 2 0 0 0 1 0 0 3 2.3 2.7 1.61 0.5225 41 Rumex hastatus Rum.has 2 1 2 0 0 0 1 0 0 3 2.2 2.7 1.42 0.6376 42 Cornus oblonga Cor.obl 2 1 2 0 0 0 0 0 1 3 1.9 2.8 1.49 0.6366 43 Anaphalis adnata Ana.adn 2 1 2 0 1 0 0 0 0 3 1.6 2.6 1.76 0.8729 44 Dodonaea viscose Dod.vis 50 2 1 50 14 3 2 0 0 70 49.6 8.7 2.31 0.001

Sr.No. Species name Abbrev. Max IV Max Grp IV Within Groups T IV IV from randomized groups 1 2 3 4 5 6 7 Obs. IV Mean SD p- value 45 Carissa opaca Car.opa 29 2 2 29 20 5 5 1 0 62 29.2 9.1 2.02 0.001 46 Dalbergia sissoo Dal.sis 22 2 0 22 0 0 1 0 0 23 22.3 3.7 1.97 0.001 47 Sida cordata Sid.cor1 22 2 2 22 2 0 2 0 0 28 22.2 4.9 1.88 0.001 48 Cassia fistula Cas.fis 17 2 0 17 3 3 0 0 0 23 16.6 3.9 1.89 0.001 49 Flacourtia indica Fla.ndi 16 2 0 16 4 4 0 0 0 24 16.4 4.5 1.97 0.001 50 Indigofera linifolia Ind.lin 15 2 0 15 0 0 1 0 0 16 15 3.3 1.87 0.002 51 Atylosia scarabaeoides Aty.sca 14 2 0 14 0 0 0 0 0 14 14.3 2.7 1.53 0.001 52 Acacia modesta Aca.mod 13 2 1 13 6 1 0 0 0 21 13.5 4.6 2.31 0.007 53 Dicliptera bupleuroides Dic.bup 13 2 4 13 10 2 3 1 0 33 13 7.3 2.36 0.027 54 Bidens biternata Bid.bit 12 2 0 12 0 0 1 0 0 13 12.4 3 1.88 0.004 55 Grewia optiva Gre.opt 12 2 0 12 0 0 0 0 0 12 11.6 3.1 1.86 0.004 56 Celtis australis Cel.aus 10 2 0 10 1 10 0 0 0 21 10.1 4.1 2.12 0.025 57 Boerhavia procumbens Boe.pro 10 2 1 10 0 0 1 0 0 12 9.9 3.2 1.85 0.007 58 Alysicarpus monilifer Aly.mon 10 2 0 10 0 0 0 0 0 10 9.5 2.7 1.42 0.008 59 Polygala arvensis Pol.arv 7 2 0 7 0 0 3 0 0 10 7.3 3.4 1.86 0.036 60 Euphorbia hirta Eup.hir 7 2 2 7 0 0 0 0 0 9 6.9 3.2 1.93 0.0631 61 Woodfordia fruticosa Woo.fru 7 2 1 7 5 1 1 0 0 15 6.8 4.4 2.09 0.1081 62 Viola makranica Vio.mak 7 2 0 7 0 0 1 0 0 8 6.7 2.9 1.7 0.0531 63 Dregea volubilis Dre.vol 7 2 1 7 0 0 0 0 0 8 6.5 2.6 1.44 0.0531 64 Eriophorum comosum Eri.com 5 2 0 5 0 0 1 0 0 6 5.1 3 1.75 0.1011 65 Arthraxon lancifolius Art.lan 5 2 0 5 0 0 0 2 0 7 5 3.4 2 0.1802 66 Sida cordifolia Sid.cor2 5 2 0 5 1 2 2 0 0 10 4.9 3.4 1.87 0.1572 67 Commelina paludosa Com.pal 5 2 0 5 0 0 0 0 0 5 4.8 2.8 1.09 0.0841

Sr.No. Species name Abbrev. Max IV Max Grp IV Within Groups T IV IV from randomized groups 1 2 3 4 5 6 7 Obs. IV Mean SD p- value 68 Curculigo orchioides Cur.orc 5 2 0 5 0 0 0 0 0 5 4.8 2.8 1.08 0.0731 69 Cyperus alopecuroides Cyp.alo 5 2 0 5 0 0 0 0 0 5 4.8 2.8 1.12 0.0831 70 Cyperus iria Cyp.iri 5 2 0 5 0 0 0 0 0 5 4.8 2.8 1.12 0.0831 71 Dichanthium foveolatum Dic.fov 5 2 0 5 0 0 0 0 0 5 4.8 2.8 1.08 0.0731 72 Eragrostis amabilis Era.ama 5 2 0 5 0 0 0 0 0 5 4.8 2.8 1.08 0.0731 73 Grewia eriocarpa Gre.eri 5 2 0 5 0 0 0 0 0 5 4.8 2.8 1.11 0.0741 74 Pueraria tuberosa Pue.tub 5 2 0 5 0 0 0 0 0 5 4.8 2.8 1.08 0.0731 75 Tribulus terrestris Tri.ter 5 2 0 5 0 0 0 0 0 5 4.8 2.8 1.12 0.0891 76 Chrysopogon aucheri Chr.auc 5 2 1 5 0 0 0 0 0 6 4.7 3 1.84 0.1672 77 Cheilanthes argentea Che.arg 4 2 0 4 1 0 1 1 0 7 4.1 3.3 1.84 0.2222 78 Mimosa himalayana Mim.him 4 2 0 4 0 0 0 0 0 4 3.9 2.8 1.53 0.1572 79 Apluda mutica Apl.mut 4 2 1 4 0 0 2 3 3 13 3.6 5.3 2.02 0.8198 80 Cyperus niveus Cyp.niv 3 2 0 3 0 0 1 0 1 5 3.4 3.1 1.79 0.2813 81 Saussurea heteromalla Sau.het 3 2 0 3 0 0 1 0 0 4 3.3 2.7 1.5 0.2452 82 Launaea procumbens Lau.pro 3 2 3 3 0 1 0 0 0 7 3.1 2.9 1.7 0.3844 83 Brachiaria ramosa Bra.ram 3 2 0 3 0 2 0 0 0 5 2.9 2.7 1.35 0.3974 84 Conyza canadensis Con.can 3 2 0 3 1 0 0 0 0 4 2.8 2.7 1.44 0.5145 85 Colebrookea oppositifolia Col.opp 3 2 0 3 0 0 2 0 0 5 2.7 3.1 1.91 0.4014 86 Leucas decemdentata Leu.dec 2 2 0 2 0 1 0 0 0 3 2.2 2.7 1.65 0.4515 87 Cynoglossum lanceolatum Cyn.lan 2 2 1 2 0 0 0 1 0 4 1.9 2.9 1.72 0.6316 88 Adiantum caudatum Adi.cau 38 3 2 0 38 2 1 1 0 44 37.7 8.3 2.89 0.001 89 Olea ferruginea Ole.fer 33 3 0 9 33 0 1 0 0 43 33.4 6.4 2.23 0.001 90 Xylosma longifolium Xyl.lon 27 3 0 0 27 2 3 1 0 33 26.7 5.9 2.34 0.001

Sr.No. Species name Abbrev. Max IV Max Grp IV Within Groups T IV IV from randomized groups 1 2 3 4 5 6 7 Obs. IV Mean SD p- value 91 Brachiaria reptans Bra.rep 18 3 0 0 18 2 15 2 4 41 17.6 9.5 2.64 0.021 92 Sageretia thea Sag.the 12 3 0 1 12 0 1 0 0 14 12.3 3.6 1.93 0.005 93 Cissampelos pareira Cis.par 12 3 0 0 12 0 0 0 0 12 12.2 3.2 1.9 0.005 94 Maytenus royleanus May.roy 9 3 2 4 9 1 3 0 0 19 9 5.8 2.4 0.0951 95 Glochidion heyneanum Glo.hey 6 3 0 0 6 0 2 0 0 8 5.7 3.1 1.87 0.1091 96 Zanthoxylum armatum Zan.arm 5 3 2 0 5 3 1 2 0 13 4.7 4.5 1.9 0.3714 97 Lamium album Lam.alb 4 3 2 0 4 0 0 0 0 6 3.9 2.7 1.45 0.1281 98 Broussonetia papyrifera Bro.pap 3 3 0 0 3 0 0 0 0 3 3.2 2.9 1.12 0.4094 99 Indigofera cordifolia Ind.cor 3 3 0 0 3 0 0 0 0 3 3.2 2.9 1.12 0.4094 100 Phyllanthus emblica Phy.emb 3 3 0 0 3 0 0 0 0 3 3.2 2.8 1.11 0.3954 101 Solanum surattense Sol.sur 3 3 0 0 3 0 0 0 0 3 3.2 2.8 1.1 0.3704 102 Siegesbeckia orientalis Sie.ori 3 3 0 2 3 0 0 0 0 5 3.1 2.7 1.63 0.2533 103 Ficus auriculata Fic.aur 3 3 0 0 3 0 0 3 0 6 2.7 2.9 1.8 0.4655 104 Callicarpa macrophylla Cal.mac 3 3 0 0 3 0 0 0 0 3 2.6 2.7 1.46 0.4715 105 Justicia adhatoda Jus.adh 37 4 0 12 2 37 0 0 0 51 37.1 5.3 2.04 0.001 106 Mallotus philippensis Mal.phi 29 4 0 13 7 29 2 0 0 51 28.9 6.9 2.16 0.001 107 Asplenium trichomanes Asp.tri 26 4 0 0 0 26 0 0 0 26 26.3 3.9 2.26 0.001 108 Duchesnea indica Duc.ind 21 4 0 0 0 21 2 6 15 44 21.3 12 3.39 0.021 109 Pennisetum orientale Pen.ori 14 4 0 0 0 14 0 0 0 14 13.6 2.7 1.55 0.001 110 Lolium temulentum Lol.tem 13 4 0 0 0 13 0 0 0 13 13 3.2 1.89 0.003 111 Nerium oleander Ner.ole 12 4 0 0 0 12 0 0 0 12 12.4 2.9 1.79 0.003 112 Cynodon dactylon Cyn.dac 12 4 0 0 0 12 1 0 0 13 11.7 4 2.18 0.008 113 Saccharum spontaneum Sac.spo 11 4 0 1 0 11 0 0 0 12 10.8 2.7 1.71 0.009

Sr.No. Species name Abbrev. Max IV Max Grp IV Within Groups T IV IV from randomized groups 1 2 3 4 5 6 7 Obs. IV Mean SD p- value 114 Acacia nilotica Aca.nil 11 4 0 1 0 11 0 0 0 12 10.7 2.9 1.85 0.01 115 Cannabis sativa Can.sat 9 4 0 0 0 9 0 0 0 9 9.1 3.1 1.63 0.027 116 Fimbristylis squarrosa Fim.squ 9 4 0 0 0 9 0 0 0 9 9.1 2.9 1.52 0.014 117 Leucas nutans Leu.nut 9 4 0 0 0 9 0 0 0 9 9.1 2.7 1.46 0.012 118 Pupalia lappacea Pup.lap 9 4 0 0 0 9 0 0 0 9 9.1 2.7 1.47 0.015 119 Solanum erianthum Sol.eri 9 4 0 0 0 9 0 0 0 9 9.1 2.8 1.53 0.016 120 Vitex negundo Vit.neg 9 4 0 0 0 9 0 0 0 9 9.1 2.7 1.48 0.015 121 Xanthium strumarium Xan.str 9 4 0 5 0 9 0 0 0 14 8.9 2.9 1.69 0.017 122 Lespedeza juncea Les.jun 9 4 5 2 1 9 4 0 1 22 8.7 6.6 2.38 0.1391 123 Malvastrum aboriginum Mal.abo 8 4 0 3 0 8 1 0 0 12 7.6 4.2 2.3 0.0811 124 Crotolaria medicagnea Cro.med 7 4 2 2 0 7 4 0 0 15 6.9 4.3 2.2 0.1041 125 Carpesium cernuum Car.cer 6 4 3 3 0 6 1 1 3 17 6.4 5.9 2.21 0.3053 126 Aristida cyanantha Ari.cya 5 4 3 0 1 5 1 0 0 10 4.6 3.9 2.04 0.2673 127 Chenopodium album Che.alb 5 4 0 0 0 5 0 0 0 5 4.5 2.8 1.11 0.1852 128 Cymbopogon martini Cym.mar 5 4 0 0 0 5 0 0 0 5 4.5 2.8 1.12 0.1812 129 Datura stramonium Dat.str 5 4 0 0 0 5 0 0 0 5 4.5 2.8 1.11 0.1852 130 Dryopteris filix-mas Dry.fil 5 4 0 0 0 5 0 0 0 5 4.5 2.9 1.13 0.1952 131 Embelia robusta Emb.rob 5 4 0 0 0 5 0 0 0 5 4.5 2.9 1.11 0.1742 132 Equisetum ramosissimum Equ.ram 5 4 0 0 0 5 0 0 0 5 4.5 2.9 1.13 0.1912 133 Eryngium caeruleum Ery.cae 5 4 0 0 0 5 0 0 0 5 4.5 2.9 1.13 0.1892 134 Festuca gigantea Fes.gig 5 4 0 0 0 5 0 0 0 5 4.5 2.9 1.13 0.1892 135 Hippochaete debilis Hip.deb 5 4 0 0 0 5 0 0 0 5 4.5 2.8 1.12 0.1822 136 Kydia calycina Kyd.cal 5 4 0 0 0 5 0 0 0 5 4.5 2.9 1.11 0.1742

Sr.No. Species name Abbrev. Max IV Max Grp IV Within Groups T IV IV from randomized groups 1 2 3 4 5 6 7 Obs. IV Mean SD p- value 137 Paspalum distichum Pas.dis 5 4 0 0 0 5 0 0 0 5 4.5 2.8 1.12 0.1822 138 Phyla nodiflora Phy.nod 5 4 0 0 0 5 0 0 0 5 4.5 2.8 1.12 0.1822 139 Sauromatum venosum Sau.ven 5 4 0 0 0 5 0 0 0 5 4.5 2.8 1.08 0.1512 140 Solanum americanum Sol.ame 5 4 0 0 0 5 0 0 0 5 4.5 2.8 1.08 0.1512 141 Setaria viridis Set.vir 4 4 0 3 0 4 2 0 0 9 4 3.9 1.93 0.3534 142 Carex cardiolepis Car.car 3 4 0 0 0 3 0 0 0 3 3.1 2.8 1.69 0.2182 143 Carex fedia Car.fed 3 4 0 0 0 3 0 0 1 4 3.1 2.9 1.88 0.2833 144 Crotalaria calycina Cro.cal 3 4 0 0 0 3 1 0 0 4 3.1 2.7 1.38 0.3313 145 Galium asperifolium Gal.asp 3 4 0 0 0 3 1 0 0 4 3.1 2.7 1.35 0.3483 146 Verbena officinalis Ver.off 3 4 1 0 0 3 0 0 0 4 2.9 2.8 1.67 0.3383 147 Lantana camara Lan.cam 3 4 0 1 0 3 0 0 0 4 2.8 2.8 1.62 0.3954 148 Cassine glauca Cas.gla 3 4 0 0 1 3 0 0 0 4 2.7 2.6 1.39 0.5135 149 Aesculus indica Aes.ind 3 4 0 0 0 3 0 0 1 4 2.5 2.7 1.54 0.4304 150 Cynoglossum glochidiatum Cyn.glo 3 4 1 1 1 3 1 0 0 7 2.5 3.3 1.66 0.7367 151 Erigeron bonariensis Eri.bon 2 4 0 0 1 2 1 0 0 4 2.4 2.8 1.67 0.4154 152 Justicia japonica Jus.jap 2 4 0 0 2 2 1 0 0 5 2.4 3.2 2.03 0.5816 153 Swertia paniculata Swe.pan 2 4 2 0 0 2 0 0 0 4 2.3 2.7 1.47 0.5916 154 Setaria pumila Set.pum 2 4 0 0 0 2 1 1 0 4 2.1 3.3 1.98 0.7477 155 Ziziphus mauritiana Ziz.mau 2 4 0 1 0 2 2 0 0 5 2.1 2.8 1.78 0.5636 156 Micromeria biflora Mic.bif 22 5 17 2 2 3 22 11 0 57 21.8 10.6 2.22 0.002 157 Taraxacum officinale Tar.off 18 5 7 0 0 0 18 2 1 28 18.3 8.3 3.11 0.009 158 Dichanthium annulatum Dic.ann 14 5 0 3 0 1 14 0 0 18 13.9 5.1 2.44 0.011 159 Rubus ellipticus Rub.ell 14 5 8 0 0 0 14 7 0 29 13.8 7.1 2.38 0.023

Sr.No. Species name Abbrev. Max IV Max Grp IV Within Groups T IV IV from randomized groups 1 2 3 4 5 6 7 Obs. IV Mean SD p- value 160 Heteropogon contortus Het.con 13 5 1 7 0 0 13 0 0 21 12.8 4.8 2.16 0.011 161 Imperata cylindrica Imp.cyl 12 5 5 0 0 0 12 1 0 18 12.1 5.7 2.64 0.033 162 Oenothera rosea Oen.ros 10 5 3 0 1 1 10 3 1 19 10.1 5.9 2.12 0.0511 163 Barleria cristata Bar.cri 8 5 5 6 0 0 8 0 0 19 8.1 4.9 2.28 0.0791 164 Pseudocaryopteris foetida Pse.foe 8 5 4 0 0 0 8 0 0 12 8.1 4.3 2 0.0531 165 Reinwardtia indica Rei.ind 6 5 4 1 0 0 6 3 1 15 6.5 5.9 2.36 0.3103 166 Launaea secunda Lau.sec 6 5 6 0 1 0 6 1 0 14 6.4 4.5 1.79 0.1231 167 Androsace rotundifolia And.rot 6 5 3 0 0 0 6 0 3 12 6.3 4.5 1.94 0.1542 168 Himalrandia tetrasperma Him.tet 6 5 4 0 1 0 6 0 0 11 6.3 4.3 2.07 0.1411 169 Campanula pallida Cam.pal 6 5 0 0 0 0 6 0 0 6 6.1 2.7 1.65 0.0881 170 Saccharum ravennae Sac.rav 6 5 0 0 0 0 6 0 0 6 6.1 2.9 1.71 0.0511 171 Sonchus asper Son.asp 6 5 4 2 0 0 6 1 0 13 5.7 4.9 2 0.2683 172 Ajuga parviflora Aju.par 4 5 1 0 0 0 4 0 1 6 4.4 3.4 1.93 0.2092 173 Inula cappa Inu.cap 4 5 0 0 0 0 4 0 0 4 4.1 2.7 1.44 0.1061 174 Plantago lanceolata Pla.lan 4 5 0 0 0 0 4 2 3 9 3.7 6.1 2.95 0.7788 175 Eulaliopsis binata Eul.bin 3 5 0 1 0 0 3 0 0 4 3.1 2.8 1.62 0.4004 176 Ailanthus altissima Ail.alt 3 5 0 3 0 0 3 0 0 6 2.8 3 1.77 0.4144 177 Rubus sanctus Rub.san 2 5 0 0 0 0 2 2 0 4 2.5 3.2 1.93 0.5686 178 Wendlandia heynei Wen.hey 2 5 0 0 0 1 2 1 0 4 2.3 3 1.82 0.5776 179 Agrostis stolonifera Agr.sto 2 5 0 0 0 0 2 0 0 2 2 2.8 1.1 0.7698 180 Alysicarpus bupleurifolius Aly.bup 2 5 0 0 0 0 2 0 0 2 2 2.8 1.1 0.7708 181 Alysicarpus ovalifolius Aly.ova 2 5 0 0 0 0 2 0 0 2 2 2.9 1.14 0.7838 182 Asparagus racemosus Asp.rac 2 5 0 0 0 0 2 0 0 2 2 2.9 1.13 0.7878

Sr.No. Species name Abbrev. Max IV Max Grp IV Within Groups T IV IV from randomized groups 1 2 3 4 5 6 7 Obs. IV Mean SD p- value 183 Bauhinia variegata Bau.var 2 5 0 0 0 0 2 0 0 2 2 2.8 1.13 0.7678 184 Bothriochloa bladhii Bot.bla 2 5 0 0 0 0 2 0 0 2 2 2.8 1.11 0.7578 185 Chrysopogon serrulatus Chr.ser 2 5 0 0 0 0 2 0 0 2 2 2.9 1.11 0.7798 186 Erigeron trilobus Eri.tri 2 5 0 0 0 0 2 0 0 2 2 2.9 1.14 0.7768 187 Euphorbia prostrata Eup.pro2 2 5 0 0 0 0 2 0 0 2 2 2.8 1.08 0.7768 188 Fimbristylis dichotoma Fim.dic 2 5 0 0 0 0 2 0 0 2 2 2.8 1.11 0.7718 189 Hypericum perforatum Hyp.per 2 5 0 0 0 0 2 0 0 2 2 2.8 1.11 0.7738 190 Medicago edgeworthii Med.edg 2 5 0 0 0 0 2 0 0 2 2 2.8 1.1 0.7768 191 Mentha longifolia Men.lon 2 5 0 0 0 0 2 0 0 2 2 2.8 1.1 0.7698 192 Physalis divaricata Phy.div 2 5 0 0 0 0 2 0 0 2 2 2.9 1.13 0.7918 193 Phyllanthus virgatus Phy.vir 2 5 0 0 0 0 2 0 0 2 2 2.9 1.12 0.7798 194 Hylodesmum podocarpum Hyl.pod 2 5 0 0 0 0 2 0 0 2 1.6 2.9 1.53 0.8178 195 Clematis barbellata Cle.bar 1 5 0 0 0 0 1 1 0 2 1.3 2.7 1.44 0.9179 196 Hypodematium crenatum Hyp.cre 1 5 0 0 0 0 1 1 0 2 1.3 2.7 1.4 0.9159 197 Quercus glauca Que.gla 1 5 0 0 0 0 1 1 0 2 1.3 2.7 1.43 0.9249 198 Anaphalis margaritacea Ana.mar 1 5 0 0 0 0 1 0 1 2 1.1 2.7 1.53 1 199 Berberis parkeriana Ber.par 1 5 0 0 0 0 1 0 1 2 1.1 2.7 1.51 1 200 Polygala erioptera Pol.eri 1 5 1 1 0 0 1 1 0 4 1.1 2.8 1.66 0.9419 201 Kobresia laxa Kob.lax 1 5 0 0 0 0 1 0 1 2 1 2.8 1.63 0.959 202 Myrsine africana Myr.afr 51 6 8 0 6 0 8 51 6 79 51.3 12.7 2.19 0.001 203 Oplismenus compositus Opl.com 27 6 0 0 0 0 0 27 27 54 27.4 8.4 2.45 0.001 204 Pinus roxburghii Pin.rox 25 6 19 1 2 1 21 25 2 71 24.6 12.6 2.43 0.001 205 Pyrus pashia Pyr.pas 15 6 2 0 3 1 0 15 13 34 15.3 7.8 2.27 0.016

Sr.No. Species name Abbrev. Max IV Max Grp IV Within Groups T IV IV from randomized groups 1 2 3 4 5 6 7 Obs. IV Mean SD p- value 206 Quercus incana Que.inc 12 6 1 0 4 1 0 12 4 22 11.8 6.4 2.24 0.034 207 Bridelia verrucosa Bri.ver 9 6 1 0 2 1 1 9 0 14 8.6 5.3 2.51 0.0971 208 Clinopodium umbrosum Cli.umb 8 6 1 0 0 0 4 8 2 15 8.1 5.1 2.22 0.0921 209 Diospyros lotus Dio.lot 7 6 0 0 0 0 0 7 4 11 6.8 3.6 1.88 0.0631 210 Rubus fruticosus Rub.fru 7 6 0 0 0 0 0 7 0 7 6.7 2.8 1.72 0.0591 211 Trigonella gracilis Tri.gra 5 6 0 0 0 0 0 5 1 6 5.4 4.3 2.48 0.2563 212 Impatiens edgeworthii Imp.edg 4 6 0 0 0 0 0 4 0 4 4.4 2.8 1.6 0.0871 213 Phlomoides spectabilis Phl.spe 4 6 0 0 0 0 0 4 0 4 4.4 2.8 1.54 0.0771 214 Punica granatum Pun.gra 4 6 1 0 4 1 1 4 0 11 4.4 4.7 2.15 0.4494 215 Elaeagnus angustifolia Ela.ang 4 6 0 0 0 1 1 4 1 7 3.9 3.7 1.88 0.3453 216 Impatiens brachycentra Imp.bra 4 6 0 0 0 0 0 4 0 4 3.7 2.8 1.71 0.1582 217 Cornus macrophulla Cor.mac 3 6 0 0 0 0 0 3 3 6 3.4 3.1 1.85 0.3183 218 Ajuga bracteosa Aju.bra 3 6 2 1 0 1 0 3 0 7 3.2 3.6 1.94 0.4575 219 Oxalis pes-caprae Oxa.pes 3 6 3 0 1 3 1 3 0 11 3 4.1 1.86 0.6547 220 Aquilegia pubiflora Aqu.pub 3 6 0 0 0 2 0 3 0 5 2.9 2.7 1.65 0.1902 221 Youngia japonica You.jap 3 6 0 0 0 0 2 3 0 5 2.8 2.8 1.75 0.3053 222 Adiantum venustum Adi.ven 3 6 0 0 0 0 1 3 0 4 2.7 3.4 1.92 0.5626 223 Lotus corniculatus Lot.cor 3 6 2 0 0 0 0 3 0 5 2.5 3.8 2.17 0.6937 224 Asplenium dalhousiae Asp.dal 2 6 0 0 0 0 0 2 2 4 2.4 2.8 1.82 0.3033 225 Hypericum obongifolium Hyp.obo 2 6 1 0 0 0 1 2 2 6 2.4 3.6 1.96 0.6376 226 Origanum vulgare Ori.vul 2 6 2 0 0 0 2 2 1 7 2.3 4.3 2.15 0.8869 227 Achyranthes aspera Ach.asp 2 6 0 0 0 0 0 2 0 2 2.2 2.9 1.12 0.5956 228 Ainsliaea latifolia Ain.lat 2 6 0 0 0 0 0 2 0 2 2.2 2.9 1.12 0.5706

Sr.No. Species name Abbrev. Max IV Max Grp IV Within Groups T IV IV from randomized groups 1 2 3 4 5 6 7 Obs. IV Mean SD p- value 229 Aristolochia punjabensis Ari.pun 2 6 0 0 0 0 0 2 0 2 2.2 2.9 1.12 0.5956 230 Astragalus leucocephalus Ast.leu 2 6 0 0 0 0 0 2 0 2 2.2 2.8 1.07 0.5566 231 Bergenia ciliata Ber.cil 2 6 0 0 0 0 0 2 0 2 2.2 2.9 1.13 0.5656 232 Cuscuta gigantea Cus.gig 2 6 0 0 0 0 0 2 0 2 2.2 2.9 1.12 0.5706 233 Ficus sarmentosa Fic.sar 2 6 0 0 0 0 0 2 0 2 2.2 2.9 1.13 0.5646 234 Gentiana argentea Gen.arg 2 6 0 0 0 0 0 2 0 2 2.2 2.8 1.11 0.5696 235 Geranium lucidum Ger.luc 2 6 0 0 0 0 0 2 0 2 2.2 2.8 1.11 0.5746 236 Heracleum candicans Her.can 2 6 0 0 0 0 0 2 0 2 2.2 2.9 1.14 0.5846 237 Polypogon viridis Pol.vir 2 6 0 0 0 0 0 2 0 2 2.2 2.9 1.13 0.5646 238 Potentilla reptans Pot.rep 2 6 0 0 0 0 0 2 0 2 2.2 2.9 1.14 0.5846 239 Salix acmophylla Sal.acm 2 6 0 0 0 0 0 2 0 2 2.2 2.9 1.14 0.5736 240 Teucrium royleanum Teu.roy 2 6 0 0 0 0 0 2 2 4 2.2 3.6 2.12 0.7487 241 Trifolium dubium Tri.dub 2 6 0 0 0 0 0 2 0 2 2.2 2.8 1.11 0.5826 242 Uraria picta Ura.pic 2 6 0 0 0 0 0 2 0 2 2.2 2.9 1.15 0.6076 243 Vicia hirsuta Vic.hir 2 6 0 0 0 0 0 2 0 2 2.2 2.9 1.15 0.6076 244 Polypogon fugax Pol.fug 2 6 0 0 0 0 0 2 0 2 1.9 2.8 1.55 0.5526 245 Cedrus deodar Ced.deo 1 6 0 0 0 0 1 1 0 2 1.5 3.1 1.79 0.7858 246 Asplenium adiantum-nigrum Asp.adi 1 6 0 0 0 0 0 1 1 2 1.2 2.7 1.5 0.8378 247 Dysphania ambrosioides Dys.amb 1 6 0 0 0 0 1 1 0 2 1.2 2.7 1.48 0.9249 248 Myriactis wightii Myr.wig 1 6 0 0 0 0 0 1 1 2 1.2 2.7 1.37 0.8188 249 Sinopodophyllum hexandrum Sin.hex 1 6 0 0 0 0 0 1 1 2 1.2 2.7 1.43 0.8338 250 Lolium perenne Lol.per1 1 6 0 0 0 0 1 1 1 3 1.1 3.2 1.94 0.9479 251 Pinus wallichiana Pin.wal 66 7 0 0 0 0 0 2 66 68 66.2 7.3 2.12 0.001

Sr.No. Species name Abbrev. Max IV Max Grp IV Within Groups T IV IV from randomized groups 1 2 3 4 5 6 7 Obs. IV Mean SD p- value 252 Viburnum grandiflorum Vib.gra 48 7 0 0 0 1 0 0 48 49 47.7 6.7 2.38 0.001 253 Daphne papyracea Dap.pap 43 7 0 0 0 1 0 3 43 47 43.5 6.7 2.37 0.001 254 Carex schlagintweitiana Car.sch 40 7 0 0 0 0 1 13 40 54 40.3 8.7 2.67 0.001 255 Strobilanthes urticifolia Str.urt 36 7 0 0 0 1 0 5 36 42 36.3 6.9 2.38 0.001 256 Sarcococca saligna Sar.sal 34 7 0 0 0 0 0 2 34 36 34.3 5.5 2.28 0.001 257 Dryopteris stewartii Dry.ste 31 7 0 0 0 0 0 9 31 40 30.9 6.7 2.2 0.001 258 Brachiaria eruciformis Bra.eru 26 7 0 0 0 0 0 0 26 26 26.4 5.6 2.56 0.001 259 Berberis lycium Ber.lyc 25 7 12 0 0 0 1 10 25 48 24.6 9.2 2.4 0.001 260 Neolitsea pallens Neo.pal 24 7 0 0 0 0 0 2 24 26 23.7 4.9 2.2 0.001 261 Lactuca brunoniana Lac.bru 23 7 0 0 0 0 0 6 23 29 22.9 5.1 2.05 0.001 262 Lonicera quinquelocularis Lon.qui 21 7 0 0 0 0 1 4 21 26 21.5 5.9 2.09 0.001 263 Pteris vittata Pte.vit 20 7 0 0 0 1 0 3 20 24 19.7 5.4 2.31 0.003 264 Smilax glaucophylla Smi.gla 19 7 0 0 0 0 0 3 19 22 19.4 4.9 2.21 0.001 265 Geranium rotundifolium Ger.rot 18 7 6 0 0 2 0 2 18 28 18.3 6.3 2.11 0.001 266 Trifolium repens Tri.rep 18 7 0 0 0 0 0 0 18 18 18.2 3.8 2.04 0.001 267 Carex filicina Car.fil 17 7 0 0 0 0 0 1 17 18 16.9 4.3 2.2 0.001 268 Spiraea canescens Spi.can 16 7 0 0 0 0 0 0 16 16 16.5 4 2.08 0.001 269 Andrachne cordifolia And.cor 14 7 0 0 0 0 0 2 14 16 14.2 4.9 2.21 0.005 270 Fragaria nubicola Fra.nub 14 7 0 0 0 1 0 0 14 15 13.6 4 1.97 0.003 271 Bromus hordeaceus Bro.hor 13 7 0 0 0 0 1 0 13 14 12.8 4.7 2.69 0.021 272 Plantago major Pla.maj 13 7 0 0 0 0 0 0 13 13 12.7 3 1.74 0.003 273 Rumex nepalensis Rum.nep 13 7 0 0 0 0 0 0 13 13 12.7 3.1 1.93 0.005 274 Galium rotundifolium Gal.rot 12 7 1 0 0 0 1 2 12 16 11.9 5.7 2.79 0.038

Sr.No. Species name Abbrev. Max IV Max Grp IV Within Groups T IV IV from randomized groups 1 2 3 4 5 6 7 Obs. IV Mean SD p- value 275 Jasminum humile Jas.hum 12 7 0 0 0 0 0 3 12 15 11.8 4.8 2.48 0.02 276 Desmodium elegans Des.ele 11 7 0 0 0 0 0 1 11 12 11 4.2 2 0.013 277 Arisaema flavum Ari.fla 11 7 1 0 0 0 0 0 11 12 10.7 3.4 1.97 0.005 278 Rosa moschata Ros.mos 10 7 0 0 0 0 1 7 10 18 10.5 4.9 2.16 0.021 279 Ranunculus laetus Ran.lae 10 7 0 0 0 1 0 0 10 11 10.3 3.9 2 0.016 280 Oxalis corniculata Oxa.cor 10 7 4 9 0 9 4 7 10 43 9.9 10.9 2.56 0.6056 281 Poa annua Poa.ann 9 7 0 0 0 0 0 0 9 9 9.1 3.2 1.88 0.014 282 Hedera nepallensis Hed.nep 9 7 0 0 0 0 0 6 9 15 8.8 4.4 1.99 0.04 283 Quercus dilatata Que.dil 9 7 0 0 0 1 0 1 9 11 8.8 3.9 2.19 0.036 284 Persicaria amplexicaulis Per.amp 9 7 0 0 0 1 0 0 9 10 8.7 3.1 1.77 0.017 285 Poa alpina Poa.alp 9 7 0 0 0 0 0 0 9 9 8.6 3.6 1.96 0.025 286 Valeriana jatamansi Val.jat 9 7 3 0 0 0 1 1 9 14 8.6 4.7 2.09 0.0561 287 Galium elegans Gal.ele 8 7 0 0 0 0 0 1 8 9 8.2 3.4 1.74 0.025 288 Medicago laciniata Med.lac 8 7 0 0 0 0 0 0 8 8 8.2 3.5 2.19 0.036 289 Galium acutum Gal.acu 8 7 0 0 0 3 0 0 8 11 7.9 3.6 1.87 0.043 290 Coniogramme rosthornii Con.ros 8 7 0 0 0 1 0 1 8 10 7.8 4.3 2.2 0.0761 291 Cotoneaster affinis Cot.aff 8 7 0 0 0 0 0 1 8 9 7.8 3.6 2 0.028 292 Polystichum aculeatum Pol.acu 8 7 0 0 0 0 0 1 8 9 7.8 3.3 1.87 0.038 293 Plantago ovata Pla.ova 8 7 0 0 0 1 0 0 8 9 7.6 3.4 1.97 0.046 294 Rubia cordifolia Rub.cor 7 7 4 0 0 0 0 4 7 15 7.4 4.4 2 0.0811 295 Abies pindrow Abi.pin 7 7 0 0 0 0 0 0 7 7 7.3 2.8 1.71 0.024 296 Leucanthemum vulgare Leu.vul 7 7 0 0 0 2 0 0 7 9 6.7 3.3 1.98 0.0691 297 Smilax aspera Smi.asp 7 7 0 0 0 0 0 4 7 11 6.5 3.9 1.99 0.0981

100

Sr.No. Species name Abbrev. Max IV Max Grp IV Within Groups T IV IV from randomized groups 1 2 3 4 5 6 7 Obs. IV Mean SD p- value 298 Adiantum capillus-veneris Adi.cap 6 7 0 0 0 1 0 1 6 8 6.2 4 2.04 0.1301 299 Lolium persicum Lol.per2 5 7 0 0 0 0 0 0 5 5 5.5 3.1 1.68 0.0921 300 Machilus duthiei Mac.dut 5 7 0 0 0 0 0 0 5 5 5.5 3.1 1.82 0.1021 301 Onychium contiguum Ony.con 5 7 0 0 0 0 0 0 5 5 5.5 3.1 1.7 0.0951 302 Ophiopogon intermedius Oph.int 5 7 0 0 0 0 0 0 5 5 5.5 2.9 1.7 0.1071 303 Persicaria hydropiper Per.hyd 5 7 0 0 0 0 0 0 5 5 5.5 2.7 1.52 0.0931 304 Poa pratensis Poa.pra 5 7 0 0 0 0 0 0 5 5 5.5 3 1.8 0.0921 305 Rhamnus virgata Rha.vir 5 7 0 0 0 0 0 0 5 5 5.5 2.7 1.61 0.1001 306 Erigeron multiradiatus Eri.mul 5 7 0 0 0 0 0 0 5 5 5.2 3 1.85 0.0971 307 Ranunculus muricatus Ran.mur 5 7 0 0 1 0 0 1 5 7 5.2 3.4 2.07 0.1722 308 Clematis montana Cle.mon 5 7 1 0 1 0 0 0 5 7 4.9 4.1 2.03 0.2442 309 Rosa multiflora Ros.mul 5 7 0 0 0 0 0 1 5 6 4.9 3 1.85 0.1381 310 Geranium wallichianum Ger.wal 5 7 0 0 0 0 0 1 5 6 4.5 3.1 1.82 0.1642 311 Medicago lupulina Med.lup 5 7 0 0 0 1 4 0 5 10 4.5 4.3 2.2 0.3744 312 Viburnum cotinifolium Vib.cot 4 7 0 0 0 0 0 3 4 7 4.3 3.3 2.01 0.2262 313 Carex foliosa Car.fol 4 7 0 0 0 0 0 0 4 4 3.6 2.7 1.39 0.3223 314 Cuscuta reflexa Cus.ref 4 7 0 0 0 0 0 0 4 4 3.6 2.7 1.39 0.1622 315 Habenaria furcifera Hab.fur 4 7 0 0 0 0 0 0 4 4 3.6 2.7 1.49 0.2593 316 Poa polycolea Poa.pol 4 7 0 0 0 0 0 0 4 4 3.6 2.9 1.49 0.3774 317 Prunella vulgaris Pru.vul 4 7 0 0 0 0 0 0 4 4 3.6 2.7 1.45 0.1662 318 Pteris cretica Pte.cre 4 7 0 0 0 0 0 0 4 4 3.6 2.9 1.57 0.4084 319 Swertia cordata Swe.cor 4 7 0 0 0 0 0 0 4 4 3.6 2.7 1.41 0.1612 320 Dryopteris ramosa Dry.ram 4 7 0 0 1 1 0 0 4 6 3.5 3.1 1.85 0.3183

100

101

Sr.No. Species name Abbrev. Max IV Max Grp IV Within Groups T IV IV from randomized groups 1 2 3 4 5 6 7 Obs. IV Mean SD p- value 321 Rubus niveus Rub.niv 3 7 0 0 0 2 0 0 3 5 3 2.9 1.82 0.2863 322 Pistacia integerrima Pis.int 3 7 0 0 0 0 0 0 3 3 2.9 3.1 1.87 0.3784 323 Teucrium quadrifarium Teu.qua 2 7 0 0 0 0 0 2 2 4 2.3 2.8 1.69 0.6046 324 Valeriana hardwickii Val.har 2 7 0 0 0 0 0 1 2 3 2.3 2.7 1.49 0.5656 325 Achillea millefolium Ach.mil 2 7 0 0 0 0 0 0 2 2 1.8 2.9 1.13 1 326 Anaphalis busua Ana.bus 2 7 0 0 0 0 0 0 2 2 1.8 2.8 1.11 1 327 Anemone vitifolia Ane.vit 2 7 0 0 0 0 0 0 2 2 1.8 2.9 1.13 1 328 Arabis nova Ara.nov 2 7 0 0 0 0 0 0 2 2 1.8 2.9 1.13 1 329 Artemisia dubia Art.dub 2 7 0 0 0 0 0 0 2 2 1.8 2.8 1.1 1 330 Bromus pectinatus Bro.pec 2 7 0 0 0 0 0 0 2 2 1.8 2.9 1.14 1 331 Bromus ramosus Bro.ram 2 7 0 0 0 0 0 0 2 2 1.8 2.8 1.11 1 332 Cephalanthera longifolia Cep.lon 2 7 0 0 0 0 0 0 2 2 1.8 2.8 1.11 1 333 Chrysopogon gryllus Chr.gry 2 7 0 0 0 0 0 0 2 2 1.8 2.8 1.1 1 334 Dactylis glomerata Dac.glo 2 7 0 0 0 0 0 0 2 2 1.8 2.9 1.12 1 335 Dioscorea deltoidea Dio.del 2 7 0 0 0 0 0 0 2 2 1.8 2.9 1.14 1 336 Epipactis helleborine Epi.hel 2 7 0 0 0 0 0 0 2 2 1.8 2.9 1.14 1 337 Epipactis persica Epi.per 2 7 0 0 0 0 0 0 2 2 1.8 2.9 1.12 1 338 Gentiana olivieri Gen.oli 2 7 0 0 0 0 0 0 2 2 1.8 2.9 1.15 1 339 Hypericum dyeri Hyp.dye 2 7 0 0 0 0 0 0 2 2 1.8 2.9 1.1 1 340 Kyllinga squamulata Kyl.squ 2 7 0 0 0 0 0 0 2 2 1.8 2.9 1.12 1 341 Lonicera hispida Lon.his 2 7 0 0 0 0 0 0 2 2 1.8 2.9 1.12 1 342 Persicaria nepalensis Per.nep 2 7 0 0 0 0 0 0 2 2 1.8 2.9 1.16 1 343 Poa nemoralis Poa.nem 2 7 0 0 0 0 0 0 2 2 1.8 2.9 1.12 1

101

102

Sr.No. Species name Abbrev. Max IV Max Grp IV Within Groups T IV IV from randomized groups 1 2 3 4 5 6 7 Obs. IV Mean SD p- value 344 Polygonatum multiflorum Pol.mul 2 7 0 0 0 0 0 0 2 2 1.8 2.8 1.11 1 345 Pycreus flavidus Pyc.fla 2 7 0 0 0 0 0 0 2 2 1.8 2.8 1.1 1 346 Pycreus pumilus Pyc.pum 2 7 0 0 0 0 0 0 2 2 1.8 2.8 1.11 1 347 Solena amplexicaulis Sol.amp 2 7 0 0 0 0 0 0 2 2 1.8 2.8 1.09 1 348 Trifolium pratense Tri.pra 2 7 0 0 0 0 0 0 2 2 1.8 2.8 1.1 1 349 Medicago polymorpha Med.pol 2 7 0 0 0 1 1 1 2 5 1.7 3.2 1.93 0.7678 350 Arisaema jacquemontii Ari.jac 2 7 0 0 0 0 0 1 2 3 1.6 2.7 1.67 0.8388 351 Aster flaccidus Ast.fla 1 7 0 0 0 0 0 1 1 2 1.4 2.8 1.63 0.8148 352 Myrsine semiserrata Myr.sem 1 7 1 0 0 0 0 0 1 2 1.1 2.9 1.75 0.979

102

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Table. 2.5: Environmental variable and vegetation cover in the seven communities of Muree Kotli-Sattian Kahuta National Park.

Parameters Communities 1. TGG 2. DCD 3. AOX 4. JMA 5. MTD 6. MOP 7. PVD 1858.62±173.1 Altitude (m) 1316.98±190.42 794.81±187.31 970.54±196.47 864.14±495.45 1170.53±310.94 1490.64±317.3 8 Slope (degrees) 33.17±12.47 24.24±13.79 27.58±12.1 28.36±15.72 26.45±13.06 27.96±12.63 34.42±15.05 Total Cover (%) 48±10.9 42.33±9.67 44.13±38.25 43.29±37.86 41.04±13.86 60.01±7 55.53±38.03 Cover tree layer (%) 42.74±21.64 39.02±21.18 51.39±28.65 52.81±32.23 40.79±21.45 67.85±42.35 67.25±24 Cover shrub layer (%) 20.91±15.83 55.45±30.37 50.42±27.86 33.51±20.71 27.31±24.73 54.39±35.3 37.15±20.85 Cover herb layer ( %) 80.35±21.93 32.53±21.14 30.57±18.86 43.56±25.84 55.03±24.46 57.8±53.51 62.18±26.48 Longitude 73.4589±0.07 73.4377±0.13 73.3804±0.06 73.5199±0.09 73.4502±0.08 73.4422±0.06 73.4658±0.04 Latitude 33.8476±0.1 33.7256±0.15 33.7731±0.06 33.7391±0.19 33.7617±0.15 33.8318±0.06 33.8916±0.04 Moisture 55.52±9.62 52.43±16.16 53.95±8.29 44.27±14.52 54.9±10.31 58.98±9.53 56.58±9.78 Ph 6.79±0.19 6.78±0.37 6.73±0.26 6.53±1.29 6.77±0.25 6.73±0.27 6.78±0.21 K 120.91±48.04 108.57±57.82 130.65±34.15 121.82±48.95 117.76±36.01 129.33±37.32 125.64±46.1 P mg/kg 9.24±4.26 7.41±4.62 9.85±3.41 7.05±4.32 8.72±4.38 8.45±3.19 8.13±2.34 O.M% 1.19±0.53 0.98±0.54 1.25±0.52 1.06±0.5 1.04±0.53 1.15±0.53 1.33±0.45 N mg/ Kg 0.06±0.03 0.05±0.03 0.06±0.03 0.05±0.02 0.05±0.03 0.06±0.03 0.07±0.02 EC 1.03±0.33 0.81±0.18 1.03±0.29 0.81±0.19 0.96±0.22 1.07±0.32 0.9±0.23 TSS mg/ Kg 658.09±211.59 517.49±113.5 662.19±184.81 521.31±124.38 614.66±143.42 681.67±206.27 574.6±144.55

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community contain relatively low amount of organic matter 1.04±0.53%.

The soil contains 0.05±0.03mg/ Kg Nitrogen, 8.72±4.38mg/ Kg

Phosphorus, and 117.76±36.01mg/ Kg Potassium. Electric conductivity of soil was

0.96±0.22 and total soluble salt content was 614.66±143.42 mg/ Kg. The total area of the community covered with vegetation was 41.04±13.86%. Most of the area was covered with Herbs (55.03±24.46%) followed by trees (40.79±21.45%), shrubs has the least cover value (27.31±24.7322.18%). Shannon index was 2.15±0.40,

Simpson index was 0.81±0.10, Margalrf Richness and Menhinick Richness

3.29±0.9 and 1.79±0.55 respectively, Inversion Simpson index was 6.50±2.98,

Pielou evenness was 0.78±0.10, (Table 2.6).

The community was given the name after Micromeria biflora, Taraxacum officinale and Dichanthium annulatum because plant species have high indicator value. The community was represented by 171 plant species. The total number of plant species, found to be the indicator species of the community were fourtysix.

Micromeria biflora, Taraxacum officinale, Dichanthium annulatum, Heteropogon contortus, Rubus ellipticus and Imperata cylindrical were the significant (p <0.05) indicator species of this community.The diagnostic species of the communities with dominant indicator value were Micromeria biflora(21.8), Taraxacum officinale (18.3), Dichanthium annulatum (13.9), Rubus ellipticus (13.8),

Heteropogon contortus (12.8), Imperata cylindrica (12.1), Oenothera rosea (10.1),

Barleria cristata (8.1),Pseudocaryopteris foetida (8.1), Reinwardtia indica (6.5) and Launaea secunda (6.4).

The rare species of the community were Hylodesmum podocarpum,

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Clematis barbellata, Hypodematium crenatum, Quercus glauca, Anaphalis margaritacea, Berberis parkeriana and Kobresia laxa.The most frequent species of the association were Micromeria biflora,Taraxacum officinale, Pinus roxburghi,

Rubus ellipticus, Oenothera rosea, Reinwardtia indica, Dichanthium annulatum,

Sonchus asper, Launaea secunda, Androsace rotundifolia and Pseudocaryopteris foetida.The exclusive species of the community were Agrostis stolonifera,

Alysicarpus bupleurifolius, Alysicarpus ovalifolius, Asparagus racemosus,

Bauhinia variegata, Bothriochloa bladhii, Campanula pallida, Chrysopogon serrulatus, Erigeron trilobus, Euphorbia prostrata, Hypericum perforatum,

Fimbristylis dichotoma, Inula cappa, Medicago edgeworthii, Mentha longifolia,

Physalis divaricata, Phyllanthus virgatus and Saccharum ravennae.

The community is dominated by herbs which contribute to 66.67% of the total flora followed by shrubs (20.47%) and trees contributed 12.87%.

Hemicryptophytes was the dominant life form of the community with the share of

29.24%, followed by Therophytes (28.07%).Nanophanerophytes contributed

(18.71%) followed by macrophanerophytes (12.87%), chamaephytes (5.85%), geophytes (2.92% and lianas (2.34%). Nanophylls dominated the community with the share of 33.92% followed by Microphylls 31.58. Leptophylls had the contribution of 26.32% and Mesophylls contributed 8.19%. The community was designated as Nano-Micr-Leptophyllous.

2.4.2.1.6. Myrsine-Oplismenus-Pinus (MOP) community

The community is represented by the swalik chir pine forest and it is determined on the basis of 45 samples. The community is located between

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33°41'N-33°56'N latitude and 73°26'E-73°26'E longitude, confined to the area with the mean elevation of 1490.64±317.30m and the average inclination of

27.96°±12.63°. The community is represented in Blawra, Phaphrel, Sain, Ratta

Jabbar, Upper Sain, Phaghwari reserve forest, Borban Reserve Forest, Chajana,

Gharihan, Seri Bari Reserve Forest, Kotli Sattin, Ksairi Reserve Forest,Mangal

Reserve Forest, New Muree, Parinola Reserve Forest, Dnoi and Patriata.The soil of the association is mostly Clayey and clay Loam type with the pH value of

6.73±0.27 with the highest moisture content (58.98±9.53%) compare to any other community typ and having relatively organic matter content 1.15±0.53%. The soil contains 0.06±0.03mg/ Kg Nitrogen, 8.45±3.19mg/ Kg Phosphorus and

129.33±37.32mg/ Kg Potassium. Electric conductivity of soil was 1.07±0.32 and total soluble salt content was 681.67±206.27 mg/ Kg.

The community has the highest vegetation coverage (60.01±7%). Most of the area was covered by trees (67.85±42.35%) followed by Herbs (57.8±53.51%) and shrubs (54.39±35.3%). Margalrf Richness was calculated as 3.45±0.81 and

Menhinick Richness was found to be 1.77±0.3. Pielou evenness was 0.79±0.07,

Simpson index was 0.83±0.07, Shannon index was 2.21±0.30 and Inversion

Simpson index was 6.60±2.10, (Table 2.6).The community was given the name after Myrsine africana (IV, 51.3), Oplismenus compositus (IV, 27.4) and Pinus roxburghii (IV, 24.6).The community was represented by 176 plant species of which 49 species were found to be the indicator of the community. The significant indicator species of the association (SIS) having p value <0.05 were Myrsine africana, Oplismenus compositus, Pinus roxburghii, Pyrus pashia and Quercus incana (Table 2.4).

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The diagnostic species of the communities with dominant indicator value were Myrsine africana (51.3), Oplismenus compositus (27.4), Pinus roxburghii

(24.6), Pyrus pashia (15.3), Quercus incana (11.8), Bridelia verrucosa (8.6),

Clinopodium umbrosum (8.1) and Rubus fruticosus (6.7).The most frequent species of the association were Myrsine africana, Pinus roxburghii, Oplismenus composites. Themeda anathera, Duchesnea indica, Oxalis corniculata, Pyrus pashia, Carex schlagintweitiana and Elaeagnus angustifolia.The rare species of the community were Lolium perenne, Sinopodophyllum hexandrum, Myriactis wightii,

Dysphania ambrosioides, Asplenium adiantum-nigrum and Cedrus deodar.The exclusive species of the community were Achyranthes aspera, Ainsliaea latifolia,

Aristolochia punjabensis, Astragalus leucocephalus, Bergenia ciliata, Cuscuta gigantea, Ficus sarmentosa, Gentiana argentea, Geranium lucidum, Heracleum candicans, Impatiens edgeworthii, Phlomoides spectabilis, Polypogon viridis,

Potentilla reptans, Rubus fruticosus, Salix acmophylla, Trifolium dubium, Uraria picta, and Vicia hirsuta.

The community is dominated by herbs which contribute to 65.91% of the total flora followed by shrubs (21.59%) whereas trees contributed least to the flora of study area (12.50%). Hemicryptophytes and Therophytes were the dominant life form (27.27% each) in the association followed by nanophanerophytes (17.05%), macrophanerophytes (11.93%), chamaephytes (6.82%), lianas (5.11%) and geophytes (4.55%). Microphylls had the highest share of 39.20% in the community, followed by Nanophylls (28.41%), Leptophylls (21.02%) and

Mesophylls (11.36%). The community was designated as Micr-Nano-

Leptophyllous.

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Table 2.6. Diversity indicies of communiite from Muree Kotli-Sattian Kahuta National Park

Associations No. of Species Diversity indices Evenness Relves # Margalrf Menhinick Simpson Shanon Inversion Pielou Richness Richness index index simpson evenness 1.Themeda-Galium-Gerbera 23 129 3.13±0.62 1.52±0.34 0.66±0.09 1.71±0.28 3.16±0.82 0.62±0.08 2. Dodonaea-Carissa- Dalbergia 21 99 3.23±0.78 2.04±0.56 0.85±0.05 2.25±0.32 7.65±2.9 0.85±0.06 3. Adiantum-Olea-Xylosma 31 92 2.81±0.91 1.78±0.56 0.82±0.12 2.11±0.4 6.8±2.34 0.85±0.12 4. Justicia-Mallotus- Asplenium 22 139 2.96±0.84 1.77±0.49 0.77±0.15 2±0.47 5.93±3.11 0.78±0.15 5. Micromeria-Taraxacum- Dichanthium 49 171 3.29±0.9 1.79±0.55 0.81±0.1 2.15±0.4 6.5±2.98 0.78±0.1 6. Myrsine-Oplismenus-Pinus 45 176 3.45±0.81 1.77±0.31 0.83±0.07 2.21±0.3 6.6±2.1 0.79±0.07 7. Pinus-Viburnum-Daphne 55 179 4.15±0.66 2.06±0.41 0.87±0.06 2.49±0.26 8.77±2.73 0.82±0.07

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35.00

30.00 Hemicryptophytes 25.00 Therophytes 20.00 Nanophanerophytes 15.00 Macrophanerophytes

10.00 Chamaephytes Geophytes 5.00 Lianas 0.00 1. TGG 2. DCD 3. AOX 4. JMA 5. MTD 6. 7. PVD Total MOP

Fig. 2.8.Life form classis (Biological spectrum) of Muree Kotli-Sattian Kahuta National Park.

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45.00

40.00

35.00

30.00 Leptophylls 25.00 Mesophylls 20.00 Microphylls 15.00 Nanophylls 10.00

5.00

0.00 1. TGG 2. DCD 3. AOX 4. JMA 5. MTD 6. MOP 7. PVD Fig. 2.9. Leaf spectra of the flora of Murree Kotli-Sattian Kahuta National Park

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2.4.2.1.7. Pinus-Viburnum-Daphne (PVD) community

The community is confined to higher elevation with the average elevation of 1858.62±173.18m having the average inclination of 34.42°±15.05°. The community is determined on the basis of 55 releves distributed between 33°49'N-

33°57'N latitude and 73°19'-73°31'E longitude. The releves were distributed in

Darnoian, Deerkot, Deerkot Reserve Forest, Kaity, Kohati, Ksairi Reserve Forest,

Patita Reserve and Forest. The slopes were very steep with the inclination reaching up to 34.42±15.05°.

The soil type of the association was clay Loam and Clayey soil with the pH value of 6.78±0.21 and the moisture content of 56.58±9.78%. The soil contain the highest amount of organic matter (1.33±0.45%), compared to any other community. The was 0.07±0.02mg/ Kg Nitrogen, 8.13±2.34mg/ Kg Phosphorus,

125.64±46.10mg/ Kg Potassium in the soil. Electric conductivity of soil was

0.90±0.23 and total soluble salt content was 574.60±144.55 mg/ Kg. The total community has the high vegetation cover (55.53±38.03%). Most of the area was covered by trees (67.25±24%) followed by herbaceous cover (62.18±26.48%) and least cover was contribute by shrubs (37.15±20.85%). Pielou evenness was

0.82±0.07, Simpson index was 0.87±0.06, Shannon-Wiener index was

2.49±0.26,Inversion Simpson index was 8.77±2.73, The community has the highest species richness compare to any other community in the study area as delectated by

Margalrf Richness (4.15±0.66) and Menhinick Richness (2.06±0.41).

The community was named after Pinus wallichiana, Viburnum grandiflorum and Daphne papyracea based on highest indicator value and low p

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value <0.05. The community was represented by 179 plant species including 41 significant indicator species (p <0.05) of the association (Table 2.4).

The diagnostic species of the communities with dominant indicator value were Pinus wallichiana (66.2), Viburnum grandiflorum (47.7), Daphne papyracea

(43.5), Carex schlagintweitiana (40.3), Strobilanthes urticifolia (36.3), Sarcococca saligna (34.3), Dryopteris stewartii (30.9), Brachiaria eruciformis (26.4), Berberis lycium (24.6), Neolitsea pallens (23.7), Lactuca brunoniana (22.9), Lonicera quinquelocularis (21.5), Pteris vittata (19.7), Geranium rotundifolium (18.3),

Trifolium repens (18.2), Carex filicina (16.9), Spiraea canescens (16.5)and

Andrachne cordifolia (14.2).

The rare species of the community Myrsine semiserrata, Aster flaccidus,

Arisaema jacquemontii, Pycreus pumilus, Pycreus flavidus, Polygonatum multiflorum, Poa nemoralis, Lonicera hispida, Kyllinga squamulata, Hypericum dyeri, Gentiana olivieri, Epipactis persica, Epipactis helleborine, Anaphalis busua,

Anemone vitifolia and Artemisia dubia.The most frequent species of the association

Pinus wallichiana, Duchesnea indica, Carex schlagintweitiana, Daphne papyracea, Viburnum grandiflorum, Strobilanthes urticifolia, Sarcococca saligna,

Oplismenus compositus, and Geranium rotundifolium.

The exclusive species of the community were Abies pindrow, Achillea millefolium, Anaphalis busua, Anemone vitifolia, Arabis nova, Artemisia dubia,

Bromus pectinatus, Bromus ramosus, Carex foliosa, Cephalanthera longifolia,

Chrysopogon gryllus, Cuscuta reflexa, Dactylis glomerata, Dioscorea deltoidea,

Epipactis helleborine, Epipactis persica, Gentiana olivieri, Habenaria furcifera,

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Hypericum dyeri, Kyllinga squamulata, Lonicera hispida, Lolium persicum,

Machilus duthiei, Ophiopogon intermedius, Onychium contiguum, Persicaria hydropiper, Persicaria nepalensis, Plantago major, Poa annua, Poa nemoralis,

Poa polycolea, Poa pratensis, Polygonatum multiflorum, Prunella vulgaris, Pteris cretica, Pycreus flavidus, Pycreus pumilus, Rhamnus virgata, Rumex nepalensis,

Solena amplexicaulis, Swertia cordata and Trifolium pratense.

2.4.2.2 Ordination of plant communities

Ordination is a multivariate statistical approach which equips the scientists to visualize multidimensional interactions in low dimensional space to have the better and easy understanding and interpretation of high dimensional processes and phenomenons which would otherwise be very much difficult to talk about.

Ecologists are provided with choice by CANOCO, to carry out (DCA), using a species matrix or direct gradients analysis (CCA), using both species and environmental data matrices (CCA). Direct gradients analysis (DCA) was used to have the groups of samples in ordination space, showing the separation and arrangement of the ordinate samples. Canonical correspondence analysis (CCA) was performed to find the contribution, extent and importance of studied environmental variable in explaining the variation in species data.

2.4.2.2.1 Detrended correspondence analysis

In the Detrended correspondence analysis the environmental variables were used as supplementary variables. The total inertia of 7.323 was recorded in the species data whereas the eigenvalues of DCA axis-1, DCA axis-2, DCA axis-3 and

DCA axis-4 have the eigenvalues of 0.631, 0.212, 0.1496 and 0.1392 respectively.

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These four DCA axes explained 15.46% of variation in species data with the cumulative explained variations of 8.62%, 11.51%, 13.56% and 15.46% respectively. Whereas the adjusted explained variation is 9.9%. The strength of psudo-canonical correlation of supplementary variables of DCA axis-1to DCA axis-4 was 0.9401, 0.3237, 0.3251 and 0.4532 respectively (Table 2.7). The DCA biplot shows that the altitude is most important variable in determining the species composition variation in the study area followed by latitudinal gradient, soil pH and soil texture (Fig. 2.9).

Pinus-Viburnum-Daphne and Dodonaea-Carissa-Dalbergia community are far apart in ordination space showing maximum heterogeneity between these communities (Fig. 2.9). The DCA biplot of species and environmental variables show that Pinus-Viburnum-Daphne community is strongly correlated with Altitude, slope, soil saturation, and organic matter and Latitudinal variations along Axis-1 of

DCA biplot. Whereas Dodonaea-Carissa-Dalbergia community is mainly determined by texture of soil.

2.4.2.2.2 Canonical correspondence analysis

The effect of environmental variables in determing the vegetation distribution pattern and variation in species composition was analyzed using CCA.

Of the total variation in species data 14.7% was explained by the studied environmental variables. The canonical eigenvalues of the first four axis i.e axis-1, axis-2, axis-3 and axis-4, were 00.5649, 0.1051, 0.0773 and 0.057 with cumulative explained variations (%) of 7.71%, 9.15%, 10.21% and 10.98% respectively. the pseudo-canonical correlation values of the first four CCA axes were 0.9512%,

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Fig. 2.10. DCA biplot showing distribution of vegetation samples and their possible relationship with the supplementary variables.

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Fig. 2.11. DCA biplot of species and environmental variables.

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Fig. 2.12. CCA species biplot.

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Table 2.7.Statistis of detrended correspondence analysis.

Axis Axis 1 Axis 2 Axis 3 Axis 4 Eigenvalues 0.631 0.212 0.1496 0.1392 Explained variation (cumulative) 8.62 11.51 13.56 15.46 Gradient length 5.19 3.79 3.15 2.05 Pseudo-canonical correlation (suppl.) 0.9401 0.3237 0.3251 0.4532

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Table 2.8.Statistis of canonical correspondence analysis.

Statistic Axis 1 Axis 2 Axis 3 Axis 4 Eigenvalues 0.5649 0.1051 0.0773 0.057 Explained variation (cumulative) 7.71 9.15 10.21 10.98 Pseudo-canonical correlation 0.9512 0.6723 0.7113 0.685 Explained fitted variation (cumulative) 52.47 62.23 69.41 74.71

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Table 2.9.Testing of individual constrained axes of constrained analysis (Permutation test on all axes).

Statistic 1 2 3 4 5 6 7 8 9 10 11 12 13 Explained by constrained axis [%] 7.71 1.43 1.06 0.78 0.69 0.65 0.47 0.42 0.37 0.34 0.3 0.24 0.23 Pseudo-F value 19.4 3.7 2.7 2 1.8 1.7 1.3 1.1 1 0.9 0.8 0.7 0.6 P value 0.001 0.001 0.001 0.017 0.075 0.094 0.888 0.976 0.999 0.998 0.999 1 1

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Table 2.10: Ranking and Contribution of studied variables in explaining variation in species data.

Simple term (marginal) effects % explained Conditional term (Net) effects % explained

Variable Explains % pseudo-F P P(adj) Variable Explains % pseudo-F P P(adj)

Altitude 7.4 19.6 0.001 0.00233 Altitude 7.4 19.6 0.001 0.00233

Longitude 3.2 8 0.001 0.00233 Latitude 1.2 3.2 0.001 0.00233

Loam 1.8 4.6 0.001 0.00233 Loam 0.9 2.3 0.001 0.00233

Latitude 1.3 3.2 0.001 0.00233 Slope 0.7 2 0.001 0.00233

Saturation 1.2 3.1 0.001 0.00233 Longitude 0.7 2 0.001 0.00233

Slope 1.1 2.8 0.001 0.00233 Sandy.Loam 0.6 1.6 0.025 0.03889

Ogamic Matter 0.8 2 0.002 0.004 Soil pH 0.6 1.6 0.021 0.03675

Clay 0.7 1.8 0.003 0.00525 Potassium 0.5 1.4 0.012 0.024

Phosphorus 0.7 1.8 0.004 0.00622 Saturation 0.5 1.4 0.001 0.00233

Soil EC 0.7 1.6 0.008 0.0112 OM 0.4 1.2 0.123 0.1722

Soil pH 0.6 1.5 0.038 0.04433 Soil EC 0.4 1.2 0.154 0.196

Sandy.Loam 0.6 1.5 0.05 0.05385 Phosphorus 0.3 0.8 0.785 0.91583

Potassium 0.5 1.2 0.09 0.09 Clay 0.3 0.9 0.891 0.95954

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0.6723%, 0.7113% and 0.685% respectively (Table 2.8). There were 13 constrained axes which were tested for their significance and the result showed that first four axes were significant with the p-value ranging from 0.001 to 0.017 (Table 2.9).

Twelve of the explanatory variables were found to be the significant [p(adj)

<0.05] in explaining variation in species data via testing simple term effects, of which altitude, longitude, loamy texture, latitude, soil saturation and slope were the most important variable in controlling the distribution and composition patterns of plant species. There were nine significant variables [p (adj) <0.05] detected based on conditional term effects. The most important variable was altitudinal, followed by latitude, loamy texture, slope, longitude, sandy loam, soil pH, potassium content and soil moisture (Table 2.9). The species biplot of CCA shows that diagnostic species of DCD and JMA community have a strong but negative correlation altitude, soil moisture and organic matter content. Whereas CCA biplot showed a strong positive correlation of MOP and PVD (High elevation communities) with altitude, soil moisture, organic matter content and high inclination.

2.5 DISCUSSION

Mountain ecosystems, because of their rapidly varying landscape within a brief spatial and temporal frame, have diverse environmental conditions and microhabitat variation, the factor responsible for rich floral diversity and usually various plant communities in such ecosystems (Kharkwal and Rawat, 2010; Khan,

2012b). To understand the ecosystem dynamics with respect to plant ecology, it is inevitable to understand floristic composition, special and temporal distribution and all the related phytosociological aspect of plant species of an ecosystem (Ferreira et

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al., 2015). Identification of plant communities by vegetation classification help understanding the issues and consequently long term management of ecosystem

(Mucina, 1997; Ewald and Diaz, 2003). Ordination brings the multidimensional aspects of ecosystem and vegetation to a low dimensional space to showcase the multivariate and complication phenomenon in an easy way (Kusbach, 2010).

A check list of flora provides base line for further studies related to botanical aspects (Ilyas et al., 2015; Ilyas, 2015). Data on plant species diversity and the forest community structure provides a baseline not only for conservation,

(Reddy et al., 2011) but also help to highlight necessary actions for managing the natural resources in a sustainable way (Khan, 2012). Murree Kotli-Sattian Kahuta

National Park is endowed with rich plant diversity, containing 624 plant species

(Table 2.2). With respect to vascular plant species, the study area is one of the rich areas of the country. The MKSKNP occupy 0.12% area of the country and contain significantly high floral diversity (10.79%) relative to the total flora of Pakistan. A total of 16 plant species were recorded for the first time from the MKSKNP, district Rawalpindi, (Table 2.2) a few of endemic species have also been recorded from the study area. Majority of these species are rare as represented in only few of the samples studied in phytosociological work. The species like Viola. makranica has only been reported form Makran region of Balochistan Province, Pakistan. The floristic list of the study area might provide a little insight in understanding the ecosystem dynamics, along with physiological and reproductive aspect of vegetation. The floristic list of the study area could be the potential source for ethno-pharmacological studies, because many of the plant species reported in this study are medicinal one (Abbasi et al., 2013; Saqib et al., 2014).

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To understand the nature and distribution of plant species in the landscape, there is need to have an accurate surface area inventory, a species composition list, and the identification and classification of the communities (Lotter and Beck,

2004). Therefore, information on floral composition, diversity is an essential aspect of ecological studies which help in understanding the ecosystem dynamics.

Ecological studies help understand the characteristic species of microhabitat along with their ecological niche (Mandal and Joshi, 2014) and provide the initial clues to understand and solve the problems of ever disturbing vegetation particularly in the study area due to growing anthropogenic pressure (Zhao et al.,

2010), especially in the form of overgrazing, fuel wood extraction and overexploitation of medicinal plant. Similar stresses are also reported from other

Himalayan regions (Malik et al., 2007a; Shaheen et al. 2011a; Khan, 2012a; Ilyas,

2015a).

The deforestation in the study area can be correlation to poverty of the local inhabitant, the fact reported in certain other studies in Himalayan regions as well (Saeeda and Zakir 2012).Vegetation and the environmental variable are interpedently phenomenon, in fact the environment and plant system is a single dynamic unite (Billings, 1952), the intricate harmonical balance of which is the very essence of vegetation composition of an area and the very survival of the life depends on it. Vegetation is an important part of the ecosystem that reflects the effects of the environmental variables (Mandal and Joshi, 2014) and the variation of these variables in microhabitat make characteristic vegetation composition; therefore it is important to correlate the vegetation with its corresponding

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topographic and environmental constrains to better understand the dynamics of plant community (Kokaly et al., 2003; Kent, 2011; Mandal and Joshi, 2014).

Champion et al. (1965), classified the vegetation of Murree-Kotli Sattian-Kahuta national park into subtropical and temperate type but due to significant difference in microhabitat with respect to topography, slope, edaphic and climatic condition along with anthropogenic activities (Billings, 1952), different areas of the Murree-

Kotli Sattian-Kahuta national park harbor different plant species composition.

Vegetation classification and species composition show that there is a gradual variation in vegetation from Subtropical broad leaved vegetation at the lower elevation along the Jhelum River in south and in the south western part of

Murree-Kotli Sattian-Kahuta national park to the Siwalik Chir Pine vegetation in the middle elevation of the study area. The vegetation then mingles with Himalaya

Moist Temperate Forest at the upper elevation. At the lower elevation species, characteristic of Subtropical broad leaved forests can be identified like Olea ferruginea, Cassia fistula, Pistacia integerrima, Bauhinia veriegata, Flacortia indica and Acacia modesta. The shrub layer contains Sageretia thea, Carissa oppaca, Justicia adhatoda and Woodfordia fruiticosa etc. (Champion et al., 1965;

Hussain and Ilahi, 1991; Malik and Husain, 2006; Ahmed et al., 2009; Khan et al.,

2015). As the altitude increases the element of subtropical type vanish and plant species typical of Siwalik Chir Pine forest dominate the middle elevation (Nafeesa et al., 2007; Ahmad et al., 2009; Shaheen et al., 2011a) i.e. Pinus roxberghii, Pyrus patia, Quercus incana, Xylosma longifolia, Myrsine Africana, Berberis lyceum,

Rubus ellipticus, R. niveus, R. ulmifolius, Punica granatum, Rosa mashcata and

Indigofera heterantha etc etc. Moving further up the elevation Himalaya Moist

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Temperate Forest dominates the area with the characteristic species of eastern

Kashmir Hills like Pinus Wallichiana, Aesculus indica, Quercus dilatata,

Viburnumcotinifolium, V.grandiflorum, Lonicera quinquelocularis, Berberis lyceum, Daphnepapyracea, Viola cancescens, Clematis Montana, Dioscorea deltoides and Polygonatum spp. etc (Nafessa et al., 2007; Shaheen, 2011b; Khan,

2012a). The main variable controlling the vegetation variability was the altitude, which was found to be the main determining factor in species composition in Naran valley and swat valley of the western Himalaya regions (Shaheen, 2011a; Khan,

2012; Dar et al., 2013; Khan, 2015). Community 2, 3 and 4 are dominated by subtropical broad leaved plant species, whereas to some extent community 1 and exclusively the elements of community 5 and 6 are the representative of Siwalik

Chir Pine forest type (Champion et al., 1965).

The community 7 is dominated by the elements of Himalaya moist temperate vegetation, though appear exclusively dominated by Pinus wallichiana but with small admixture of Neolitsea pallens, Quercus dilatata, Abies pindrow and

Machtilus duthiei etc. (Sher et al., 2013; Khan, 2013c). The community is under human pressure but the forest type is thought to be the stable one (Champion et al.,

1965). The vegetation type is transition from lower Chir pine community Myrsine-

Oplismenus-Pinus, fire being the most detrimental factor in this transitional zone.

There was a strong similarity reduction in plant species composition between open tree canopy area and under canopy (Soliveres et al., 2015) due to moisture and light perception differences. Species diversity and richness are the direct measures of anthropogenic and livestock pressure on the ecosystems (Buntaine et al., 2007).

We found that species diversity and richness was highest at the upper elevation and

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lower elevation (comparatively low then the upper elevation) due to the remoteness of areas from the network of roads and human settlements. Whereas the vegetation at the middle elevation have low species diversity and richness due to high anthropogenic pressure in the form of deforestation and overgrazing along with forest fire and high number of human settlements at this elevation, a similar trends were reported from other studies of Himalayan region as well (Khan, 2012) . The considerably high number of humen settlements and consequently more inhabitants at middle elevation can be attributed to moderate temperature at this elevation

(1316 m) and easy access to the roads, which predominantly run through the middle elevation of the mountainous region of the study area. Pinus-Viburnum-

Daphne community is the most diverse and species rich community (as shown by

Menhinick Richness (2.06±0.41) and Shanon index (2.49±0.26)) which is present at the highest elevation of the study area, Dodonaea-Carissa-Dalbergia second most diverse community present at the lowest elevation. The high diversity of both these community can be the function of remoteness of area in both cases and domination of impenetrable thorny shrubs like Carissa oppaca to some extent in later case.

The study area is rich in plant biodiversity as depicted by the different diversity indices (Ahmad et al., 2008; Sharma et al., 2009; Shaheen et al., 2011a;

Qureshi et al., 2014). Themeda-Galium-Gerbera has the least value of species richness and diversity (Menhinick Richness (1.52±0.34) and Shanon index

(0.66±0.09)) due to high anthropogenic pressure, because of its presence at middle elevation (1316.98±190.42m) (Consiglio et al., 2006; Ilyas et al., 2012) (Table

2.6).The wide difference in plant species composition in small special scale can be

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attributed to the considerable variation in elevation, topographic, adaphic variation and indeed anthropogenic effect had a major influence in controlling the vegetation composition of microhabitat in the study area (Gunatilleke and Gunatilleke, 1985).

Themeda-Galium-Gerbera has the highest herbaceous cover (80.35±21.93) and least coverage by shrubs (20.91±15.83) which can be attributed to the intentional removal of shrubs by local inhabitants to promote the growth of grasses and other herbs which they collect as winter fodder. There was a general increase in the herbaceous vegetation from lower to upper elevation, a common trend found in the temperate region of Himalaya (Ren et al., 2006; Zhang et al., 2009, Khan, 2012;

Ilyas, 2015; Ilyas et al., 2015).

The understanding of vegetation dynamics demands the understanding of species-environmental correlation (Kent, 2011), as the spatial and temporal heterogeneity from microhabitat to landscape level is the function of climatic, topographic and environmental variables (Mandal and Joshi, 2014). Climate has pronounce effect on the species composition, in response to recent climatic change species are already shifting their ranges (Hijmans and Graham, 2006; Thuiller et al., 2008), with changes in phenology, and species composition and ranges expanding towards higher latitudes and altitudes. The understanding of how species respond to climate change is of fundamental importance for understanding potential species distribution in geographical region and for effective management and conservation of local biodiversity (Hijmans and Graham, 2006). Other factors i.e. soil also play important role for determining species aggregation at least on small regional scale. The physical environment (site), represented by climate, soil moisture and soil nutrients, considerably contributes to vegetation distribution

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(Wohlgemuth, 1998) altitude, slope angle and soil pH (Lüth et al., 2011; Khan,

2012a) are very important factors in determining vegetation pattern. The combine effect of all these factors make it difficult to delineate distinct vegetation communities but using appropriate tools and techniques of phytosociology vegetation pattern can be understood and vegetation can be classified into so called separate communities (Kent, 2011; Ilyas, 2015).

The significant difference in species composition along with species richness and diversity among different communities determined in Murree-Kotli

Sattian-Kahuta national park is predominantly determined by altitudinal variation which is the main limiting factor for zonal localization of different species in

Himalayan region (Khan et al., 2013c; Khan et al., 2017). Latitudinal variation along with loamy texture was the second most important variables determining the species composition in the study area, the results reported in different other

Himalayan studies (Kharkwal and Rawat, 2010; Shaheen and Shinwari, 2012; Ilyas et al., 2015; Khan et al., 2017). Topographic effects is the most important factors controlling microclimate and the characteristic vegetation makeup of plant community, (Ilyas, 2015) which is influenced indeed by many other factors

(Kusbach, 2010; Reddy et al., 2011; Rawat and Chandra, 2014).The ordination shows that the altitude is most important variable in determining the species compositional variation in the study area followed by latitudinal gradient, loamy texture, slope, longitudinal variation and soil pH (Fig. 2.9). Altitude has been reported to be the most important factor controlling the vegetation pattern and species composition in Himalayan regions (Khan, 2012; Khan et al., 2012; Ilyas,

2015). Three plant communities viz. community 1, 5, 6 and 7 can be separated

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mainly by altitude. Whereas the community number 2 is determined mainly by low altitude, less organic matter and loamy texture of the soil. Community 7 is dominated by the element of moist temperate forest; a similar community was reported from Naran valley (Khan, 2012a), and Ayubia national park by Saima et al. (2009), but with different species composition. A community dominated by

Pinus wallichiana was also reported from Pir Chanasi Hills; Kashmir by Nafeesa et al. (2007), using classical approach of indicator value index. Commnity 6 contains the elements of Shiwalik chir pine forest (Champion et al., 1965).

The dynamic and self sustaining ecosystem is the success of plant species against all the odds of time, which is not only determined temporally but topographic and edaphic variation like altitude, slope, latitude, aspect,, and soil pH play a key role in controlling the species composition, richness and diversity of any community (Kusbach, 2010; Luth et al., 2011; Khan, 2012; Khan et al., 2013;

Khan et al., 2017).Variations in aspects also enhance habitat heterogeneity and bring micro-environmental variation in vegetation pattern (Lüth et al., 2011). High species diversity were found in north facing slopes compare to the southern aspect which harbor less species diversity (Hussain et al., 1997; Shaheen et al., 2012a;

Ilyas et al., 2015). The ultimate outcome of the topographic variation is the variation in the microhabitat and vegetation by modifying the other environmental variables. The moist northern slope with low temperature, with less solar exposure contain sciophytes like Quercus dilatata, Viburnum cotinifolium, V.grandiflorum,

Strobilanthes dalhousieanus, Daphne papyracea, Sarcococca saligna, Dryopteris filix-mas, D. stewartii, Polystichum aculeatum, Arisaema flavum, Carex schlagintweitiana, Epipactis gigantea, Cephalantheralongifoliaand Spiranthes

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sinensisetc as reported from other area of Himalaya (Shaheen et al., 2012b).

Sothern aspect is drier and contains heliophytes like Pinus roxburghii, Dodonaea viscosa, Sageretia thea and Micromeriabiflora etc. There was a wide variation in species composition in northern and southern aspect in the study area, the variation also reported form Naran valley of south western Himalaya (Khan, 2012b).

The species assemblage particularly at small spatial scale is very much influence by the edaphic factors (Shaltout et al., 2003) which control the species diversity (Reddy et al., 2011) vegetation pattern in different special and temporal scale (Ferreira, 1997). Some of the vegetation communities are control by the soil depth (Khan et al., 2013) and texture (Ilyas et al., 2012) in Himalayan regions. In the present study, Loamy texture primarily determined the Dodonaea-Carissa-

Dalbergia community (Fig 2.11) similar findings reported by Malik and Hussain

(2016) from Lohi bir Rawalpindi, where as soil moisture is positively correlated with Pinus-Viburnum-Daphne community which is mainly determined by altitude and slope. The most important key edaphic factor in deterring the Micromeria-

Taraxacum-Dichanthium association is pH, the trends also found in Doon valley

Himalaya, India (Manhas et al., 2009). Apart from other environmental and edaphic variable human has strong influence on the vegetation type in the study area particularly in the case of Themeda-Galium-Gerbera community with the least value of Shannon diversity index, because the more the human influence less diverse the vegetation is with fewer selective species (Lüth et al., 2011). The life form of vegetation reflects the species adaptation to the given set of environmental constrains and this physiognomic attribute is given the much needed attention in vegetation science (Phillips, 1929; Braun-Blanquet, 1932; Thakur et al., 2012;

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Khan et al., 2016). The evident phyto-climatic gradient in the study area from lower hot climate with subtropical vegetation to moist temperate vegetation at higher elevation is reported in other studies as well (Malik et al., 2007; Shaheen et al., 2011; Khan, 2012b; Sher et al., 2013). Life form and physiognomy not only show the competitive ability and social capacity (Cain, 1950) but also the morphological adjustment that have evolutionary basis and adaptation to the environmental constrains and the survival of species (Khan et al., 2016). The life form studies is useful for understanding climatic variation (Badshah et al., 2016) and is the indicator of phyto-climatic conditions under which certain life form prevails (Batalha and Martins, 2004). The vegetation of the Murree-Kotli Sattian-

Kahuta national park is dominated by hemicryptophytes, the life form characteristic of temperate climate with cold temperature and humid conditions (Ilyas, 2015;

Ilyas et al., 2015), followed by Therophytes. The similar life form and physiognomy show the related niche requirement of plant species present in a particular habitat (Batalha and Martins, 2004). The climate though supports phanerophytes, but the domination of Therophytes particularly in the case of

Themeda-Galium-Gerbera and Dodonaea-Carissa-Dalbergia communities the indicator of harsh climate (Badshah et al., 2016; Khan et al., 2016) which in this case is the biotic stress in the form of overgrazing, wood extraction (Ilyas et al.,

2013; Ullah et al., 2015; Badshah et al., 2016).

The analysis of vegetation with respect to leaf size can help understand the physiological and ecological process and also the niche of plant species. The vegetation of Murree-Kotli Sattian-Kahuta national park is dominated by

Microphylls the representative of steppes and Nanophylls followed by

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leptophyllous plants the representative of hot climate (Champion et al., 1965; Khan et al., 2016). The higher elevation of the park is dominated by Microphylls and lower elevation of park was dominated by Nanophylls and leptophyllous plant species, similar result also found in Thandiani forests of Pakistan (Khan et al.,

2016).

As the study area fall in temperate zone (Champion et al., 1965)

Microphylls and Nanophylls which is the characteristic life form of temperate zone

(Cain and Castro, 1959) dominates the study area, the results coincides with other studies carried out in Himalayan regions (Shehzad et al., 1999; Ilyas et al., 2012;

Mohammad et al., 2013; Khan et al., 2016).

2.6 CONCLUSION

Murree-Kotli Sattian-Kahuta has not been previously explored botanically using statistical tools and techniques, so the area was studied extensively to bridge this gape. The Murree-Kotli Sattian-Kahuta national park posses a variety of rare species and a couple of endemic species as well. Thus the present study, which is quite comprehensive, proves to be the worthwhile contribution to the floristic and ecological knowledge of the study area in particular and to the botanical knowledge of Pakistan in general. The ecosystem of the area is under continuous and ever increasing human pressure in the form of deforestation, overgrazing and human settlement construction, which resulted in sever degradation the natural vegetation of the study area. The overgrazing in some area of the park has resulted in the pure domination of non palatable species like Dodonea viscosa. The current study reports the number of medicinal plant, the aspect very important for further

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investigation in ethno-pharmacological field (Abbasi et al., 2013; Saqib et al.,

2014). The ecosystem of the area must be studies in more detail to find the wealth of local flora, ecological functions of species composition which will help in understanding and the conservation of rare and endangered species. Te results of current study will help ecologist, economic botanist, medicinal plants collectors, rangeland managers, physiologist, foresters and planers for long term conservation and improving the social and economical conditions of the local inhabitants.

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Chapter 3

PLANT BIODIVERSITY AND CONSERVATION

3.1 INTRODUCTION

Definitions of biodiversity range in scope from the number of different species occurring in some location to all of the diversity and variability in nature and the variety of life and its processes (DeLong, 1996) which is important for aesthetic and economic reasons, as well as for providing services to the local people (West, 1993). The study of biodiversity is of fundamental importance not only to understand the cause and effects of life disturbance on Earth but to address some of the problems related to biodiversity particularly caused by human activities (Raven et al., 2011). Biodiversity is the source of shelter, fuel food, ethno-medicines, timber, for millions of indigenous people (Kunwar and

Bussmann, 2008). Plant resources being easily and readily accessible fulfill the fundamental needs of peoples particularly poor societies (Qureshi et al., 2012) are under extensive pressure (Ilyas, 2015). Collection of medicinal plant by untrained collectors in unwise manner posed even a serious threat to the plant of medicinal importance (Rai et al., 2000). The conservation of biodiversity is the global concerns (Koellner and Schmitz, 2006) as the biodiversity of any nation is critically important to very survival of that nation and must be given the importance for any national or regional development strategy (Mittermeier et al., 1998). More than a billion people living in extreme poverty are supported by ecosystem services directly (Turner et al., 2007). Human are dependent on ecosystems for services provision but the demand exceed then what ecosystem can provide thus

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diminishing the diversity of ecosystem (Schneiders 2012) reducing the Plant biomass, accelerating soil erosion and disturbing the hydrological cycles become

(Feoli et al., 2003). Biodiversity is diminishing at even a faster rate compare to the mass extinction about, 65 million years ago. By the end of this century a large number of known and even unknown species would be vanished from the face of earth (Raven et al., 2011), which might threatened the very survival of people living in remote area. To address different biodiversity issue it is utmost important to assess the conservation status of plant of any area.

Along with ecological quantitative data about plant species the people perception about the trends of vegetation can be very crucial in assessing the conservation status and making decision and strategies related to biodiversity

(Ilyas. 2015). Biodiversity make the ecosystem Resilience, and also reduces the effect of climate change and global warming (Feehan et al., 2009) recovery of ecosystem from sudden disturbance and shocks largely depend on the diversity of ecosystem the more diverse the ecosystem the more buffering ability it has

Indigenous people having direct interaction with nature and their ethnobotanical knowledge can be used to solve biodiversity conservation problems (Gadgil et al.,

1993). Biodiversity conservation is getting pronounced importance throughout the world and target has been set to reduce biodiversity loss by 2020 (Normander et al., 2012). Despite the fact that study area is rich in biodiversity, there is no Red

Data Book on endangered plant species of Himalayan region of Pakistan though very limited work only on few IUCN Red list plant has been done by (Ali, 2008;

Alam and Ali, 2009; Ali and Qaiser, 2010). Due to lake of list of endemic plant it is impossible to apply strict IUCN criteria for determining the conservation status to

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the plants however phytosociological field data along with people perception is used to assign conservation status to the flora of study area.

3.2 REVIEW OF LITERATURE

Conservation of biodiversity and sustainable use ensure the resilience and continuation of ecosystem (Kienast et al., 2009). Biodiversity is the soul of ecosystem services, (Singh and Kushwaha, 2008) studies have found coincidence of biodiversity with ecosystem service value bundling biodiversity and ecosystem service objectives is now a common conservation strategy (Turner et al., 2007).

The insurance of continuous services provision to the peoples need the healthy sustainable and resilience ecosystem, which demand the conservation of ecosystem resources particularly vegetation.

Ecosystem degradation harms the people particularly those living in or near forest having the devastating effect on poor people (MA, 2005). The unlimited demand of ecosystem services and extensive use of plant resources caused the deterioration of ecosystem by reducing the species richness and diversity of vegetation of area (Khan, 2012; Ilyas 2015). However plant biodiversity can be restored by proper mitigation measures (Turner et al., 2007) and the knowledge of indigenous people can be helpful in solving biodiversity issues (Gadgil et al.,

1993). One of the effort at global level is IUCN Red list, but with reference to study area no such work has yet been done, with the exception of sporadic work only on few species in nearby areas (Alam and Ali, 2009; Ali and Qaiser, 2010).

Irwin and Narasimhan, (2011) reviewed the endemic angiospermic pant and

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found 41 genera endemic to India. The Dolpo and Mustang region of Nepal has been found to contain 155 endemic species of Himalayan region and 18 species endemic to Nepal (Shrestha et al., 2006). In the Indian Himalaya endemic plant diversity with spatial reference to Ranunculaceae and Paeoniaceae was carries out by (Dhar and Samant, 1993).They found 76 species endemic to Indian Himalaya most of which confined to

Dar et al. (2013) and recorded 153 endemic taxa of the region most of which were found to be present in sub alpine and alpine zone many of them were considered threatened with some critically endangered taxa.(Singh and Kushwaha,

2008) analyzed the Forest biodiversity and its conservation in India and emphasize on the conservation of biodiversity hotspot by providing Education, and capacity building of the people (Gadgil et al., 1993) is of the view that indigenous knowledge of people may be used to address biodiversity issues. They might be help full in restoring the biodiversity in depleted areas. Feoli et al. (2003) studied the effects of human impact on vegetation using remote sensing and phytosociological approaches, and found that human pressure along with other factor determine the vegetation composition of area. Kala (2000) studied the phytosociological aspect and conservation status of rare and endangered medicinal plant species in Himachal Pradesh in the Indian trans-Himalaya describing 23 endangered and rare medicinal plants, recommending the establishment of conservation area for such plant species. Kumar and Bhatt (2006) studied the

Biodiversity and Conservation of Forests of Garhwal Himalaya and analyzed the diversity dominance and abundance of plant in the study area.

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Pandit et al. (2007) describe the biodiversity status of endemic plants of

Indian Himalaya and report the alarming trend of deforestation and also suggested extinctions of endemic taxa by 2100 predicting the extinction 366 endemic vascular plant taxa. Hobbs and Huenneke, (1992) review the disturbance regime on plant diversity and concluded that disturbance specifically of anthropogenic nature reduces the biodiversity. Khan et al. (2013b) studied the plant communities in western Himalaya and recorded a number of endemic species, which were though rare were over exploited causing the decline of biodiversity. Irwin and Narasimhan,

(2011) reported 49 endemic genera of angiosperms in India, 40 of which were found in peninsular India. They stressed the need of detail assessment of these genera based on IUCN criteria.

To reduce the biodiversity loss, different counties of the world made the commitment through the Convention on Biological Diversity. Different indices like

Biodiversity Change Index have been proposed to help measure progress towards reduction in biodiversity loss. These indices use the quantitative and qualitative data viz the abundance of indicator species and proportion of old trees with different age group or dead wood in forests. The index made it easy to compare the change in biodiversity in different habitat type (Normander et al., 2012). The sustainable development need different other indicators to assess the sustainability of environment which requires the use of resources within the limits of what an ecosystem can provide (Moldan et al., 2012). Androsace russellii, a critically endangered species has been analyzed by (Alam and Ali, 2010), the species is endemic to the Gilgit region of Pakistan. The species has been reported only from two localities of Hunza valley with the overall population of 69 individuals limited

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to 0.4Km2 geographical rang of occupancy. The species has been declared as critically endangered. Haq (2011) reported the conservation status of plants for the

Batagram district of Pakistan. Author reported a total of 37 taxa with 23 endangered taxa and also14 critically endangered. Loss of habitat and uncontrolled collection of plants are the main threats to the local vegetation.

Ali et al. (2012) studied the conservation status of Delphinium nordhagenii from Chitral region of Pakistan. The species is endemic to Chitral, the author reported 624 individuals from five localities of Chitral regions, with main treat of habitat destruction. According to the IUCN criteria species was placed in critically endangered category. Haq (2011) discussed the status of some treated and endangers species of Paksitan, and declared Aconitum violaceum and Rhodiola saxifragoides as vulnerable and Androsace russellii, Asperula oppositifolia subsp.

Baltistanica, Astragalus clarkeanus, Berberis pseudumbellata subsp. gilgitica,

Haplophyllum gilesii and Tanacetum baltistanicum as critically endangered. The floristic studies of Chitral have been dong to assess the conservation status of different species. the study reports 17 endangered taxa viz Allium barszczewskiim

A, chitralicum, Androsace harrissii, Arnebia grandiflora, Astragalus affghanus, A. chitralense, Astragalus gahiratensis, A. stantonianus, Campanula tristis,

Delphinium mordhagenii, Gaillonia chitralensis and Oxytropis gloriosa were critically endangered. Five taxa, i.e. Anaphalis chitralensis, Delphinium chitralensis, Galium chitralensis, Polygonum cognatum subsp. Chitralicum and Silene longisepala (Alam and Ali, 2010). Throughout the word efforts are made to conserve biodiversity, for which not only the quantitative but also the qualitative aspects of plant biodiversity are studied by measuring the abundance of plant

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species and identifying indicator species Normander et al. (2012) which is not only necessary for the biodiversity conservation itself but also for prediction of upcoming environmental challenges which we might encounter in the very next future (Moldan et al., 2011).

3.3 MATERIAL AND METHODS

The study was conducted in MKSKNP, from august, 2013 till September,

2015. A total of 245 releves were recorded by random stratified method. For determining the conservation status of the local flora following parameter were used.

3.3.1 Impotence Value Index (IVI)

3.3.2 Ethnoecological Perception

Based on questionnaire the local people were interviewed to reveal the trend of population dynamic of species and extend of anthropogenic pressure. The plant species were assigned the endemic status, base on literature review (Table

2.11). Furthermore individuals were also asked their opinion about the trend of the species that they observed their lifetimes. Trend was recorded using a scale with three categories i.e., decreasing (D), increasing (I) and constant (C) (Khan, 2o12;

Ilyas, 2015).

3.3.3 I.U.C.N Categorization

The conservation status of plant species was determined based on phytosociological data and people perception according to I.U.C.N. categorization

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(version 3.1, IUCN 2001) up to the level of Critically Endangered (CR),

Endangered (E), Vulnerable (VU), Near Threatened (NT) and Lest Concern (LC).

3.4 RESULTS

With respect to biodiversity and conservation many of the species (279 spp., 79.26%) were categorized as least concern (LC) because of low use value, larger ecological amplitude, less biotic pressure and larger community size. Narrow ecological amplitude, extreme biotic pressure and overexploitation might be the cause of Vulnerable (VU) status of 22 plant species (6.25%), followed by near threatened (20 spp., 5.68%), endangered (14spp., 3.98%) and 17 plant species

(4.83%) were categorized in critically endangered status.

The critically endangered species are Cedrus deodar, Crotalaria calycina,

Habenaria furcifera, Polygonatum multiflorum, Sauromatum venosum,

Sinopodophyllum hexandrum, Epipactis helleborine, Eryngium caeruleum,

Hylodesmum podocarpum, Hypericum dyeri, Myrsine semiserrata, Uraria pictaViola pilosa and Viola makranica. Endangered species in the area include

Ajuga bracteosa, Aquilegia pubiflora, Aristolochia punjabensis, Aristolochia punjabensis, Berberis parkeriana, Bergenia ciliata, Cheilanthes argentea,Cornus oblonga, Cotoneaster affinis,Equisetum ramosissimum, Geranium wallichianum,

Plantago major, Prunella vulgaris and Swertia cordata.

3.5 DISCUSSION

Despite more awareness and increasing conservation efforts there is a general decreasing trend in plant biodiversity (Rands et al., 2010) particularly in

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developing countries due to geo-political crises and population growth (Feoli et al.,

2003). Species losses, at unprecedented levels and the conservation of plant species and ecosystem needs appropriate information on biodiversity distribution (Ahrends et al., 2011). Along with the most accepted criteria like endemism, rarity and endearment (Khan, 2012) the indigenous knowledge of the local people can play a vital role in assessing the conservation status of the local flora and them paining the conservation strategy (Ilyas, 2015). According to literature, 43 plant species

(12.21%) were found to be the endemic to Hindu Kush-Himalayan region (Ali et al., 1972-2009) (Shrestha et al., 2006; Singh and Samant, 2010; Kumar et al.,

2011; Khan, 2012; Sharma and Sharma 2014; Ilyas, 2015) and three species were endemic to Pakistan (Ali et al., 1972-2009). Majority of the species (279 spp.,

79.26%) were categorized as least concern (LC) because of low use value, larger ecological amplitude, less biotic pressure and larger community size. Narrow ecological amplitude, extreme biotic pressure and overexploitation might be the cause of critically endangered status of (17 spp., 4.83%) (Ilyas, 2015).

The critically endangered species are Cedrus deodar, Crotalaria calycina,

Eryngium caeruleum, Hylodesmum podocarpum, Hypericum dyeri, Myrsine semiserrata, Uraria picta and Viola makranica.Cedrus deodar has also been given the critically endangered status from other area of Pakistan as well (Khan, 2012;

Khan et al., 2013; Ilyas, 2015) Endangered species in the area include, Ajuga bracteosa, Ajuga parviflora, Aristolochia punjabensis, Berberis parkeriana,

Bergenia ciliata, Cornus oblonga, Cotoneaster affinis and Equisetum ramosissimum. Amongst them Abies pindrow was reported as near threatened and

Bergenia ciliate as vulnerable form Naran valley of Pakistan (Khan, 2012) whereas

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Ajuga bracteosa, Ajuga parviflora, Abies pindrow, Berberis parkeriana, has been assign the vulnerable status from other areas (Ilyas, 2015). Most of the plant species are under the immense pressure of overexploitation, one of the major causes of the threatened status of species in the area (Saqib et al., 2014; Shaheen et al., 2014). The perspectives of local people and contributions in ecology and conservation have been given the importance (Gadgil et al., 1993; Khan, 2012) to solve the problems related to ecosystem in general and conservation in particular

(Sheil and Lawrence, 2004). As the local communities extract the necessities of livelihood from the available natural resources, they not only conserve local biodiversity, but modify it according to need by manipulating the landscape

(Gadgil et al., 1993; Pei et al., 2009).

Any suitable conservation plane cannot work without the involvement of local inhabitant as they understand the nature, know the trends in species degradation and perceive the forthcoming change in ecosystem in realistic manner

(Kumar and Bhatt, 2006; Rands et al., 2010; Ilyas et al., 2012). There is dire need of biodiversity conservation not because it causes problem in the local area but can be felt in different time and space (Rands et al., 2010). If not given, the much demanded attention, the area might see many species at the verge of extinction along with ecosystem degradation which might create many other socio economic and environmental problems in the area as reported in many other area of Pakistan

(Ilyas et al., 2012; Khan et al., 2012; Khan et al., 2013; Ilyas, 2015).

3.6 CONCLUSION OF BIODIVERSITY

The results of an analysis of local people‘s views on vegetation abundance

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Table 2.11 Conservation status of plant species of Murree-Kotli Sattian-Kahuta National Park

Species IVI Prassure T. Co. Endemic status level St. Abies pindrow 0.50 Moderate C LC Endemic to HKK (Ali et al., 1972-2009) Acacia modesta 1.59 Moderate D LC Endemic to HKK (Ali et al., 1972-2009) Acacia nilotica 0.42 High C LC Endemic to HKK (Ali et al., 1972-2009) Achillea millefolium 0.04 Low C LC Achyranthes aspera 0.01 Low C LC Adiantum capillus- veneris 0.39 Low C LC Adiantum caudatum 5.74 Low C LC Adiantum incisum 0.07 Low C LC Adiantum venustum 0.28 Low C LC Aesculus indica 0.12 High D NT Endemic to HKH (Ali et al., 1972-2009) Ageratum conyzoides 0.09 Moderate D NT Agrostis gigantea 0.09 Low C LC Agrostis stolonifera 0.03 Low C LC Ailanthus altissima 0.45 Low C LC Ainsliaea latifolia 0.01 High D NT Ajuga bracteosa 0.24 Low D LC Ajuga parviflora 0.17 Low D LC Alysicarpus bupleurifolius 0.03 Moderate D LC Alysicarpus monilifer 0.05 Low C LC Alysicarpus ovalifolius 0.02 Low C LC Anaphalis adnata 0.06 Low C LC Anaphalis busua 0.02 Low C LC Anaphalis margaritacea 0.03 Low C LC Andrachne cordifolia 0.98 Moderate C LC Endemic to HKH (Ali et al., 1972-2009) Androsace rotundifolia 0.47 Low C LC Endemic to HKH (Ali et al., 1972-2009) Anemone vitifolia 0.02 Moderate D NT Apluda mutica 1.58 High C LC Aquilegia pubiflora 0.10 Moderate D EN Arabis nova 0.01 NIL C LC Argyrolobium roseum 0.07 Low C LC Arisaema flavum 0.22 Low C LC Arisaema jacquemontii 0.09 High D NT Endemic to HKH (Ali et al., 1972-2009) Aristida cyanantha 0.87 Moderate C LC Aristolochia punjabensis 0.03 High D EN Artemisia dubia 0.02 High C LC Arthraxon lancifolius 0.31 Low C LC Arthraxon prionodes 1.71 Low C LC Asparagus racemosus 0.02 High D NT Asplenium adiantum- nigrum 0.04 NIL C LC

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Species IVI Prassure T. Co. Endemic status level St. Asplenium dalhousiae 0.06 NIL C LC Asplenium trichomanes 0.90 NIL C LC Aster flaccidus 0.06 NIL C LC Astragalus leucocephalus 0.01 NIL C LC Atylosia scarabaeoides 0.12 Low C LC Barleria cristata 0.71 Low C LC Bauhinia variegata 0.11 Moderate C LC Endamic to HKH (Sharma and Sharma, Berberis lycium 3.87 High D NT 2014) Berberis parkeriana 0.16 High D EN Bergenia ciliata 0.02 High D EN Endamic to HKH (Khan et al., 2013b) Bidens biternata 0.15 Low C LC Boerhavia procumbens 0.19 Moderate C LC Bothriochloa bladhii 0.06 Moderate C LC Brachiaria eruciformis 1.92 Moderate C LC Brachiaria ramosa 0.07 High C LC Brachiaria reptans 7.31 High C LC Bridelia verrucosa 1.29 Moderate C LC Endemic to HKH (Ali et al., 1972-2009) Bromus hordeaceus 0.54 NIL C LC Bromus oxyodon 0.15 NIL C LC Bromus pectinatus 0.02 NIL C LC Bromus ramosus 0.08 NIL C LC Broussonetia papyrifera 0.05 Low I LC Bupleurum marginatum 0.04 NIL C LC Callicarpa macrophylla 0.12 Moderate C LC Endemic to HKH (Ali et al., 1972-2009) Campanula pallida 0.05 Low C LC Cannabis sativa 0.34 Low I LC Capillipedium parviflorum 0.09 Moderate C LC Carex cardiolepis 0.32 Low C LC Carex fedia 0.22 Low C LC Carex filicina 0.57 Low C LC Carex foliosa 0.05 Low C LC Carex schlagintweitiana 4.82 Low C LC Endemic to HKH (Ali et al., 1972-2009) 12.5 Carissa opaca 3 Moderate D LC Carpesium abrotanoides 0.02 Moderate D EN Carpesium cernuum 0.87 NIL C LC Cassia fistula 1.27 Moderate D LC Cassine glauca 0.34 Moderate C LC Endemic to HKH (Ali et al., 1972-2009) Cedrus deodar 0.39 High D CR Endamic to HKH (Sharma and Sharma,

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Species IVI Prassure T. Co. Endemic status level St. 2014; Khan, 2012) Celtis australis 1.22 Low D LC Cephalanthera longifolia 0.03 Moderate D VU Cheilanthes argentea 0.17 Moderate D EN Chenopodium album 0.06 Low C LC Chrysopogon aucheri 0.25 Low C LC Chrysopogon gryllus 0.02 Low C LC Endemic to HKH (Ali et al., 1972-2009) Chrysopogon serrulatus 0.03 Low C LC Cissampelos pareira 0.15 Moderate D NT Clematis barbellata 0.07 Low C LC Clematis grata 0.24 Low C LC Clematis montana 0.42 Moderate C LC Clinopodium umbrosum 0.90 NIL C LC Colebrookea oppositifolia 0.24 Moderate C LC Commelina paludosa 0.03 NIL C LC Coniogramme rosthornii 0.68 NIL C LC Conyza canadensis 0.04 Low C LC Cornus macrophulla 0.26 Moderate D VU Cornus oblonga 0.09 High D EN Cotinus coggygria 0.07 Moderate D NT Cotoneaster affinis 0.26 High D EN Cousinia thomsonii 0.35 Low C LC Crotalaria calycina 0.08 High D CR Crotolaria medicagnea 0.69 Low C LC Curculigo orchioides 0.04 High D NT Cuscuta gigantea 0.01 Moderate D VU Cuscuta reflexa 0.02 Moderate C LC Cymbopogon martini 0.03 High D NT Cynodon dactylon 1.08 Moderate C LC Cynoglossum glochidiatum 0.22 Low C LC Endemic to HKH (Ali et al., 1972-2009) Cynoglossum lanceolatum 0.13 Low C LC Cyperus alopecuroides 0.04 NIL C LC Cyperus iria 0.04 NIL C LC Cyperus niveus 0.12 NIL C LC Dactylis glomerata 0.01 NIL C LC Dalbergia sissoo 1.79 High C LC Endamic to HKH (Sharma and Sharma, Daphne papyracea 1.55 Low C LC 2014) Datura stramonium 0.03 High D VU Debregeasia saeneb 0.68 Moderate C LC Desmodium elegans 0.63 Moderate C LC Endemic to HKH (Ali et al., 1972-2009) Dichanthium 2.28 Low C LC

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Species IVI Prassure T. Co. Endemic status level St. annulatum Dichanthium foveolatum 0.08 Low C LC Dicliptera bupleuroides 2.24 NIL C LC Dioscorea deltoidea 0.02 Moderate D VU Vulnerable/ on CITES list Diospyros lotus 0.53 Low C LC Dodonaea viscosa 9.41 Moderate C LC Dregea volubilis 0.06 Moderate D NT Endemic to HKH (Ali et al., 1972-2009) Dryopteris filix-mas 0.03 NIL C LC Dryopteris ramosa 0.27 NIL C LC Endemic to Pakistan (Ali et al., 1972- Dryopteris stewartii 1.94 NIL C LC 2009) Duchesnea indica 6.05 NIL C LC Dysphania ambrosioides 0.04 Low C LC Elaeagnus angustifolia 0.69 Moderate C LC Embelia robusta 0.08 Moderate D NT Epipactis helleborine 0.01 High D CR Epipactis persica 0.02 Low C LC Equisetum ramosissimum 0.03 Moderate D EN Eragrostis amabilis 0.02 Low C LC Erigeron bonariensis 0.37 Low C LC Erigeron multiradiatus 0.11 Low C LC Erigeron trilobus 0.02 Low C LC Eriophorum comosum 0.31 Low C LC Eryngium caeruleum 0.03 Moderate D CR Eulaliopsis binata 0.26 NIL C LC Euphorbia hirta 0.11 Low C LC Euphorbia prolifera 0.01 Low C LC Euphorbia prostrata 0.07 Low C LC Festuca gigantea 0.03 Moderate C LC Ficus auriculata 0.26 High C LC Ficus carica 0.82 High D LC Ficus sarmentosa 0.02 Moderate C LC Fimbristylis dichotoma 0.01 Low C LC Fimbristylis squarrosa 0.27 Low C LC Flacourtia indica 1.69 High D VU Fragaria nubicola 0.69 Low C LC Endemic to HKH (Ali et al., 1972-2009) Galium acutum 0.37 Low C LC Galium aparine 2.39 Low C LC Galium asperifolium 0.07 Low C LC Galium elegans 0.29 Low C LC Galium rotundifolium 0.63 Low C LC Gentiana argentea 0.03 NIL C LC Endemic to Pakistan (Ali et al., 1972-

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Species IVI Prassure T. Co. Endemic status level St. 2009) Gentiana olivieri 0.02 NIL C LC Geranium lucidum 0.03 NIL C LC Geranium mascatense 0.23 High D EN Geranium rotundifolium 0.87 NIL C LC Geranium Endemic to HKH (Khan, 2012)/ wallichianum 0.19 High D EN Vulnerable species of the Pakistan Gerbera gossypina 1.62 Low C LC Glochidion heyneanum 0.50 Moderate D LC Grewia eriocarpa 0.06 High D LC Grewia optiva 0.33 High D LC Endemic to HKH (Ali et al., 1972-2009) Habenaria furcifera 0.03 Moderate D CR Hedera nepallensis 0.71 Moderate C LC Heracleum candicans 0.03 Low C LC Endamic to HKH (Khan et al., 2013b) Heteropogon contortus 2.38 High C LC Himalrandia tetrasperma 0.67 High C LC Hippochaete debilis 0.01 High D NT Hylodesmum podocarpum 0.09 High D CR Hypericum dyeri 0.02 High D CR Hypericum obongifolium 0.35 Moderate C LC Hypericum perforatum 0.02 Moderate D NT Hypodematium crenatum 0.07 NIL C LC Impatiens brachycentra 0.08 NIL C LC Impatiens edgeworthii 0.04 NIL C LC Endemic to HKH (Ali et al., 1972-2009) Imperata cylindrica 3.20 Low C LC Indigofera cordifolia 0.02 High D VU Indigofera heterantha 0.55 Moderate C LC Endemic to HKH (Ali et al., 1972-2009) Indigofera linifolia 0.36 Moderate C LC Inula cappa 0.15 Moderate C LC Inula conyza 0.02 Low C LC Isodon coetsa 0.37 Moderate C LC Isodon rugosus 0.02 High D VU Jasminum humile 0.51 Low C LC Jasminum officinale 0.09 Low C LC Juncus articulatus 0.02 Low C LC Justicia adhatoda 3.00 High D LC Justicia japonica 0.17 Low C LC Kobresia laxa 0.11 Low C LC Kydia calycina 0.12 High D VU Kyllinga squamulata 0.02 Low C LC

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Species IVI Prassure T. Co. Endemic status level St. Lactuca brunoniana 0.79 Moderate C LC Lactuca dissecta 0.57 Moderate C LC Lamium album 0.05 Low C LC Lantana camara 0.11 Low I LC Launaea procumbens 0.14 Moderate C LC Launaea secunda 0.79 Low C LC Lespedeza juncea 2.09 Low C LC Endemic to HKH (Ali et al., 1972-2009) Leucanthemum vulgare 0.53 Low C LC Leucas decemdentata 0.17 Low C LC Leucas nutans 0.08 Low C LC Lolium perenne 0.16 Low C LC Lolium persicum 0.15 Low C LC Lolium temulentum 0.50 Low C LC Lonicera hispida 0.02 Moderate D NT Lonicera quinquelocularis 1.12 Moderate C LC Lotus corniculatus 0.22 Low C LC Machilus duthiei 0.23 Low C LC Mallotus philippensis 6.44 High D LC Malvastrum aboriginum 0.49 Low C LC Maytenus royleanus 1.37 Moderate C LC Endemic to HKH (Ali et al., 1972-2009) Medicago edgeworthii 0.04 Low C LC Medicago laciniata 0.32 Low C LC Medicago lupulina 0.46 Low C LC Medicago orbicularis 0.02 Low C LC Medicago polymorpha 0.17 Low C LC Mentha longifolia 0.02 High D NT Micromeria biflora 5.97 NIL C LC Mimosa himalayana 0.14 Moderate D VU Myriactis nepalensis 0.05 Moderate D VU Myriactis wightii 0.02 Low C LC 18.7 Myrsine africana 6 High C LC Myrsine semiserrata 0.13 Moderate D CR Neolitsea pallens 1.67 High D LC Nerium oleander 0.23 Low I LC Oenothera rosea 0.87 Low C LC Olea ferruginea 5.68 High D LC Onychium contiguum 0.13 NIL C LC Ophiopogon intermedius 0.06 Low C LC Oplismenus compositus 5.36 Moderate C LC Origanum vulgare 0.76 Low C LC Oxalis corniculata 3.27 Low C LC Oxalis pes-caprae 0.43 Low C LC

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Species IVI Prassure T. Co. Endemic status level St. Paspalum distichum 0.06 Low C LC Pennisetum orientale 0.11 Low C LC Endamic to HKH (Khan et al., 2013b; Persicaria Khan, 2012)/Endangerd species of amplexicaulis 0.17 Low C LC Pakistan Persicaria hydropiper 0.09 Low C LC Persicaria nepalensis 0.02 Low C LC Phlomoides spectabilis 0.03 Low C LC Phyla nodiflora 0.10 Low C LC Phyllanthus emblica 0.12 High D VU Phyllanthus niruri 0.02 Low C LC Phyllanthus virgatus 0.04 Low C LC Physalis divaricata 0.04 Low C LC 23.2 Endamic to HKH (Sharma and Sharma, Pinus roxburghii 5 High D LC 2014) 11.6 Endamic to HKH (Sharma and Sharma, Pinus wallichiana 3 High D LC 2014) Endamic to HKH (Sharma and Sharma, Pistacia integerrima 0.41 High D VU 2014) Plantago lanceolata 0.64 Moderate C LC Plantago major 0.10 Moderate D EN Rare species of Paksitan (Khan, 2012) Plantago ovata 0.29 Moderate C LC Poa alpina 0.67 Low C LC Poa annua 0.50 Low C LC Poa nemoralis 0.01 Low C LC Poa polycolea 0.05 Low C LC Poa pratensis 0.53 Low C LC Polygala abyssinica 0.34 Low C LC Polygala arvensis 0.36 Low C LC Polygala erioptera 0.19 Low C LC Polygonatum multiflorum 0.02 Moderate D CR Polypogon fugax 0.07 Low C LC Polypogon viridis 0.06 Low C LC Polystichum aculeatum 0.21 Low C LC Potentilla reptans 0.03 Low C LC Prunella vulgaris 0.03 Moderate D EN Pseudocaryopteris foetida 1.01 Moderate C LC Pteris cretica 0.10 Low C LC Pteris vittata 1.42 Low C LC Endamic to HKH (Khan et al., 2013b) Pueraria tuberosa 0.04 High D VU Punica granatum 0.84 Low D LC Pupalia lappacea 0.12 Low C LC Pycreus flavidus 0.02 Low C LC Pycreus pumilus 0.01 Low D LC Pyrus pashia 3.84 High C LC Quercus dilatata 0.70 High D CR Endemic to HKH (Ali et al., 1972-2009)

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Species IVI Prassure T. Co. Endemic status level St. Quercus glauca 0.08 High D NT Endemic to HKH (Ali et al., 1972-2009) Quercus incana 1.45 High D NT Endemic to HKH (Ali et al., 1972-2009) Ranunculus laetus 0.30 Low C LC Ranunculus muricatus 0.18 Low C LC Endamic to HKH (Sharma and Sharma, Reinwardtia indica 1.79 Low I LC 2014) Rhamnus virgata 0.06 Low C LC Rosa moschata 0.69 Low C LC Rosa multiflora 0.17 Low C LC Rubia cordifolia 0.32 Moderate D VU Endamic to HKH (Srestha et al., 2006) Rubus ellipticus 4.03 Low C LC Rubus fruticosus 0.13 Low C LC Rubus niveus 0.19 Low C LC Rubus sanctus 0.49 Low C LC Rubus ulmifolius 0.13 Low C LC Rumex hastatus 0.07 Low C LC Rumex nepalensis 0.16 Low C LC Endamic to Pakistan (Ali et al., 1972- Rydingia limbata 0.10 Low C LC 2009) Saccharum ravennae 0.26 Moderate C LC Saccharum spontaneum 0.22 Moderate C LC Sageretia thea 0.53 Moderate C LC Salix acmophylla 0.04 Moderate D LC Sarcococca saligna 2.21 Low C LC Endemic to HKH (Ali et al., 1972-2009) Sauromatum venosum 0.02 Moderate D CR Saussurea heteromalla 0.03 Low C LC Senecio nudicaulis 0.39 Low C LC Setaria pumila 0.46 Low C LC Setaria viridis 0.59 Low C LC Sida cordata 0.85 Low C LC Sida cordifolia 0.39 Low C LC Siegesbeckia orientalis 0.07 Moderate D VU Sinopodophyllum hexandrum 0.03 High D CR Endamic to HKH (Khan et al., 2013b) Smilax aspera 0.38 High C LC Smilax glaucophylla 0.73 High C LC Solanum americanum 0.02 Moderate C LC Solanum erianthum 0.13 High D VU Solanum surattense 0.02 High D NT Solena amplexicaulis 0.02 High D CR Sonchus arvensis 0.34 Low C LC Sonchus asper 0.65 Low C LC Endamic to HKH (Sing and Smant, Spiraea canescens 0.76 Low C LC 2010) Spiranthes sinensis 0.01 Moderate D VU

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Species IVI Prassure T. Co. Endemic status level St. Strobilanthes urticifolia 3.53 Low C LC Swertia cordata 0.07 High D EN Swertia paniculata 0.04 Low D LC Swertia tetragona 0.02 Low D LC Taraxacum officinale 2.00 Low C LC Teucrium quadrifarium 0.07 Low C LC Teucrium royleanum 0.54 Low C LC 27.7 Themeda anathera 7 High C LC Endemic to HKH (Ali et al., 1972-2009) Tribulus terrestris 0.02 High D VU Trichodesma indicum 0.12 Low C LC Trifolium dubium 0.04 Low C LC Trifolium pratense 0.06 Low C LC Trifolium repens 0.56 Low C LC Trigonella emodi 0.04 Low C LC Trigonella gracilis 0.90 Low C LC Uraria picta 0.01 High D CR Valeriana hardwickii 0.04 Moderate D VU Valeriana jatamansi 0.71 Moderate C LC Verbena officinalis 0.09 Low C LC Viburnum cotinifolium 0.58 High D VU Endamic to HKH (Khan et al., 2013b) Viburnum grandiflorum 3.15 Low C LC Endemic to HKH (Ali et al., 1972-2009) Vicia hirsuta 0.01 Low C LC Endamic to HKH (Rana & Samant, Viola cancescens 1.66 High D EN 2009;Khan et al., 2013b) Viola makranica 0.20 High D CR Viola pilosa 0.10 High D EN Vitex negundo 0.07 Low C LC Wendlandia heynei 0.49 Low C LC Woodfordia fruticosa 1.64 Low C LC Xanthium strumarium 0.17 Low C LC Xylosma longifolium 3.28 Low C LC Youngia japonica 0.12 Low C LC Zanthoxylum armatum 0.77 High D VU Ziziphus mauritiana 0.30 Low C LC

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0 Least Vulnerable Near Endangered Cretically concern threatened endangered Number 279 22 20 16 15 Percentage 79.26 6.25 5.68 4.55 4.26

Fig. 2.13: Summary of conservation status of the flora of Murree-Kotli Sattian- Kahuta National Park.

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at a species level shows that there is a continuous decrease 26.99% of the species, while 71.59% species were reported to maintain their population with no visible change, where as an increase was reported only in 1.42% of the species (Table

2.11). The people in study area, as in the other remote area of Himalayas have deep understanding of natural resources and vegetation, to which they depend for most of their requirement like medicine, fodder, forage, fuel wood, timber etc. Due to geopolitical situation along with many other factors, the ever increasing demands of natural resources, particularly vegetation, posses a significant threat to the biodiversity of the area. Indigenous people not only utilize the plant bio resources but they have very deep and intricate understanding of trends in biodiversity, whether a species is decreasing increasing or is constant in ecosystem.

In present studies the perception of local people about the biodiversity

Trend was coupled with the field phytosociological data was used to evaluate the conservation status of plant species of the area. Both the data set indicate close coincidence, showing that the species which are more valued have high extinction rick. Many of the species are reported to be decreasing with the passage of time and fall under threaten status of IUCN categories, which demand the conservation by using in-situ and ex-situ approaches, so that the species might be protected from the risk of extinction. Biodiversity conservation is intricate and dynamic processes which not only require the modern scientific research and theories but also require the wisdom and perception of local people indeed. Perception and wisdom of local people must be appreciated in understanding and solving the biodiversity crises, they are the real custodian of regional biodiversity, which demand their active involvement and any plane or strategy regarding biodiversity conservation.

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Chapter 4

GENERAL DISCUSSION

The vascular flora of Murree Kotli Sattian Kahuta national park in district

Rawalpindi comprised of 624 plant species belonging to 106 families and 375 genera, which include 24 ferns species, 4 species of gymnosperms and 596 angiosperms species (i.e. 144 monocotyledon and 452 dicotyledons) (Table 2.1).

As the area is located in lateral spur of Himalaya (Abbasi et al., 2002) distributed from the elevation of 400 to 2155 meters above sea levels, there was a good deal of floral diversity under the park area compared to the area of whole country (Table

2.1). The total park area contributed only 0.12% compare to the whole country but contain significantly high flora diversity (10.79%). The study area was found to be rich in Pteridophytes (18.75%) and Gymnosperms (17.39%) compared with the flora of Pakistan, followed by Monocotyledons (12.63%) and Dicotyledons

(10.06%).

Poaceae family contributed maximum species (80 spp., 12.82%), followed by Fabaceae (60 spp., 9.62%) and Asteraceae (55 spp., 8.81%), Cyperaceae (30 spp., 4.81%), Lamiaceae (27 spp., 4.33%) Rosaceae193.04% Apiaceae,

Brassicaceae and Euphorbiaceae (12 spp., 1.92% each), Convolvulaceae

Ranunculaceae (11 spp., 1.76%), Acanthaceae, Amaranthaceae and Polygonaceae

(10 spp., 1.60% each), Boraginaceae, Moraceae, Primulaceae, Rubiaceae and

Solanaceae (9 spp., 1.44% each), Orchidaceae, Gentianaceae and Malvaceae (8 spp., 1.28% each), Phyllanthaceae, Plantaginaceae and Rhamnaceae (7 spp., 1.12% each) whereas the remaining families, contain fever than 6 species (Table 2.2).

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Euphorbiais the major genus (10 spp., 2.67%) followed by Carex (9 spp., 2.4%),

Cyperus (8 spp., 2.13%), whereas Eragrostis, Poa, Ficus, Medicago, Rubus and

Swertia (6 spp., 1.6% each), Erigeron, Galium, Ipomoea, Geranium, Persicaria and Solanum, (5 spp., 1.3% each) where as the other genera contain less than five species.

Eight life forms of the flora were determined in which perennial herbs were dominating in the area with 241 species sharing 38.62% in the flora. It was followed by annual herbs 199 species (31.89%), deciduous shrubs 62 species

(9.94%), deciduous trees (46 spp., 7.37%), climbers (26 spp., 4.17%), evergreen shrubs (23 spp., 3.69%), evergreen trees (23 spp., 3.69%) while parasites were almost in negligible proportion (i.e. 4 spp., 0.64%) (Fig. 2.4).

Comparing with related floras, most of the species (511 spp., 81.89%) were native to the area, followed by 48 weed species (7.69%), Cultivated species were

21 (3.37%), 18 species (2.88%) were naturalized, 16 species (2.56%) were new to area, 3 species were introduced to the area. While two species viz., Viola makranica and Buxus papillosa are endemic to the Pakistan (Table 2.2). This floristic checklist provides baseline information to be used for further taxonomic and ecological research in future.

As for as the contribution to the flora Murree Kotli Sattian Kahuta national park is concerned, following species are reported for the first time from the study area viz. Ophiopogon intermedius, Festuca kashmiriana, Crotalaria retusa,

Crotalaria calycina, Ribes alpestre, Viola makranica, Hypericum dyeri, Scurrula pulverulenta, Festuca gigantea, Aegopodium burttii, Eryngium caeruleum,

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Myriactis wightii, Viola makranica, Alysicarpus monilifer, Gentiana olivieri,

Grewia eriocarpa and Valeriana hardwickii. (Table 2.2). Seven significantly different communities were established (Dufrene and Legendre, 1997) viz, 1)

Themeda-Galium-Gerbera community, 2) Dodonaea-Carissa-Dalbergia comm.- unity, 3) Adiantum-Olea-Xylosma community, 4) Justicia-Mallotus-Asplenium community, 5) Micromeria-Taraxacum-Dichanthium community, 6) Myrsine-

Oplismenus-Pinus community, 7) Pinus-Viburnum-Daphne community (Table

2.4). Species compositional and distributional differences were strongly determined by the altitude, latitude, soil moisture, soil texture, pH and slope as indicated by

CCA and DCA biplots (Fig. 2.11& 2.12).

Vegetation distribution, spatial or temporal distribution of plant species reflects the effects of environmental variable under which species adapts accordingly and wins against the odd of time and space (Feehan et al., 2009;

Kusbach, 2010; Rawat and Chandra, 2014). The current study defined seven plant communities based on indicator value (Dufrene and Legendre, 1997; Tsheboeng et al., 2016) which were significantly different as indicated by MRPP test (McCune et. al., 2002). The difference in floristic composition and special distribution is controlled by dynamic complex of topography, edaphic factors and climatic variations, coupled with anthropogenic influences which is very evident at microhabitat level (Hijmans and Graham, 2006; Thuiller et. al., 2008; Lüth et. al., 2011).

Factors affecting the spatial distribution of species include both abiotic and biotic factors, such as soil, topography, geology, tectonic movements, mountain uplifting, climate change and species evolution and migration (Ullah et al., 2015). The large scale physiognomic and phonological differences are determined by the climate

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(Ilyas et al., 2012; Ilyas et al., 2015) but the variation among different vegetation association at small scale are principally determined by edaphic factors, topographic differences, altitudinal variation and anthropogenic influences (Barakat et al., 2014). As a whole subtropical and temperate climate persist in area

(Champion et al., 1965), though significant variation in microhabitat with respect to topography, slope, edaphic and climatic condition along with anthropogenic activities, different areas of the park harbor differ plant species composition

(Billings, 1952; Clegg and O'connor, 2012).

Wide difference in plant species composition in small special scale can be attributed to the considerable elevational variation, topographic, adaphic variation and indeed anthropogenic effect had a major influence in controlling the vegetation composition of microhabitat (Gunatilleke and Gunatilleke, 1985). The gradual variation in vegetation from Subtropical broad leaved forests at the lower elevation along the Jhelum river in south and in the south western part of Murree-Kotli

Sattian-Kahuta national park to the Siwalik Chir Pine forest in the middle elevation of the study area and Himalaya Moist Temperate Forest at the upper elevation is controlled by altitude, consistent fact with other Himalayan regions (Dhar and

Samant, 1993; Khan, 2012; Ilyas et al., 2015; Khan et al., 2015; Badshah et al.,

2016). Community characters differ among aspect, slope, and altitude even in the same vegetation type (Rawat and Chandra, 2014). Different aspect and slopes are inhibited by different set of plant species (Lüth et al., 2011; Khan, 2012) as the current study revile the domination of northern moist aspect by sciophytes with alpha diversity compare to southern more drier aspect which contain less diversity with the domination helophytes.

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Soil play a key role in signature composition and the species assemblage particularly at small spatial (Shaltout et. al., 2003; Ullah, 2009) which control the species diversity pattern (Reddy et al., 2011). The differences in vegetation pattern in different special and temporal scale can be explained by soil parameters

(Ferreira, 1997). Some of the vegetation communities are control by the soil depth

(Khan et al., 2013) and texture (Ilyas et al., 2012) in Himalaya. Loamy texture primarily determined the Dodonaea-Carissa-Dalbergia community (Fig. 2.11), where as soil moisture is positively correlated with Pinus-Viburnum-Daphne community which is mainly determined by altitude and slope. The most important key edaphic factor in deterring the Micromeria-Taraxacum-Dichanthium association is Ph, the trends also found in Doon valley Himalaya India (Manhas et. al., 2009).

The adoption and success of plant species to a given environment is shown by it Life form, a crucial physiognomic attribute which has long been given attention to better understand the species response to the environmental constrains

(Phillips, 1929; Braun-Blanquet, 1932; Thakur et al., 2012; Khan et al., 2016). Life form and physiognomy not only show the competitive ability and social capacity

(Cain, 1950) but also the morphological adjustment that have evolutionary basis and adaptation to the environmental constrains and the survival of species (Khan et. al., 2016). Life form helps to understand the effects of climatic variation (Badshah

2016) and phytoclimatic conditions, under which certain life form prevails (Batalha and Martins, 2004). The vegetation of the Murree-Kotli Sattian-Kahuta national park is dominated by hemicryptophytes, the life form characteristic of temperate climate with cold temperature and humid conditions (Ilyas, 2015) followed by

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Therophytes. The similar life form and physiognomy show the related niche requirement of plant species (Batalha and Martins, 2004). The climate though supports phanerophytes, but the domination of Therophytes is the indicator of harsh climate (Badshah et al., 2016; Khan et al., 2016) biotic stress like overgrazing, wood extraction and deforestation make it difficult for other life forms to be in dominant position (Ullah et al., 2015; Badshah et al., 2016).

The analysis of leaf size has been another physiognomic character which helped the scientist to understand the physiological and ecological process (Malik et al., 2007; Khan et al., 2016) and also the niche of plant species. The vegetation of Murree-Kotli Sattian-Kahuta national park is dominated by Microphylls the representative of steppes and Nanophylls followed by leptophyllous plants the representative of hot climate (Khan et al., 2016). The higher elevation of the park is dominated by Microphylls and lower elevation of park was dominated by

Nanophylls and leptophyllous plant species, similar result found in Thandiani forests of Pakistan (Khan et al., 2016). As the study area fall in temperate zone

(Champion et al., 1965) Microphylls and Nanophylls which is the characteristic life form of temperate zone (Cain and Castro, 1959) dominates the study area, the results coincides with other studies like (Shehzad et al., 1999; Ilyas et al., 2012;

Mohammad et al., 2013; Khan et al., 2016). Many of the plant species (279 spp.,

79.26%) were categorized as least concern (LC) because of low use value, larger ecological amplitude, less biotic pressure and larger community size. Narrow ecological amplitude, extreme biotic pressure and overexploitation might be the cause of Vulnerable (VU) status of 22 plant species (6.25%), followed by near threatened (20 spp., 5.68%), endangered (14 spp., 3.98%) and 17 plant species

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(4.83%) were categorized in critically endangered status (Fig. 2.13).

The most important anthropogenic factors responsible for the deterioration of the vegetation of Murree Kotli Sattian Kahuta national park are unwise land use practices, deforestation, overgrazing, overexploitation of medicinal plants and introduction of alien species, firewood collection, similar problems are also reported in many other part of Himalaya (Kala, 2000; Kumar and Bhatt, 2006;

Khan et al., 2012). Biodiversity is important for many reasons like aesthetics value, economics values and for countless services provision to society (West, 1993;

Khan et al., 2013). Biodiversity also contribute to the ecotourism. Biodiversity degradation drastically reduces the benefits the man can get from ecosystem

(Kienast et al., 2009).

Human activities are responsible for the deterioration of forest ecosystems.

The main threats to the biodiversity loss in the Murree-Kotli Sattian-Kahuta national park is deforestation, overgrazing, land clearing for agriculture and house construction and fuel wood collection as reported in different other studies (Mishra et al., 2001; Ilyas et al., 2012) Controlled grazing can improve conditions for high plant diversity (Mitchell and Kirby, 1990) but overgrazing in the area not only resulted in decline of plant species but makes the area susceptible to other threat in the form of land sliding and erosion (Mishra et al., 2001; Abbasi et al., 2002), the problem very common due to the immature geology of area (Gansser, 1964;

Ahmad, 2011).

Plant species composition of an ecosystem is altered by grazing pressure, changing the ecosystem processes and functions (Adler et al., 2001). There is

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significant change in the vegetation composition of the study area particularly in the middle elevation of the park because of over grazing. There is also general increase in non-palatable species like Dodonia viscosa in heavily overgrazed area of the park and reduction in palatable plant species like Carissa oppaca.

Anthropogenic pressure drastically reduces the plant biodiversity and changes the compositional dynamics of plant species of a vegetation type (Shaheen et al., 2011; Khan et al., 2013). Another very important factor for loss of shrub and tree diversity in southern slope at middle elevation of park as evident in Themeda-

Galium-Gerbera community is intentional removal of shrubs by local inhabitants to promote the growth of grasses and other herbs which they collect as winter fodder.

The community has the highest herbaceous cover (80.35±21.93) and least cover by shrubs (20.91±15.83). The introduction of some alien species like Lantana camara and L. indica are not only destroying the natural vegetation and causing biodiversity loss in some part of the park at lower elevation but expending their frontier to the higher elevation. The overwhelming spread of these invaders is posing considerable threat to the natural vegetation (Dukes and Mooney, 1999).

Deforestation is one of the major factors severely devastating the vegetation of national park. Due to the uncertain geopolitical situation coupled with the poverty, the Pakistan is facing tremendous decrease in vegetation cover. Different studies showed the general trend in deforestation i.e. the decrease of coniferous forests at a rate of 1.27% per annum since 1992 has been reported by (Ahmad et al., 2012).

Deforestation reduces not only the buffering ability of forest ecosystem to external change but also reduces the quality of forest, soil, alter the functioning and services it provide to the people and ecosystem (Islam and Weil, 2000). The main

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cause of deforestation in the area are fuel wood collection, timber, forage collection and forest cutting for house construction and agriculture along with overgrazing

(Nagothu, 2001; Khan et al., 2013; Shaheen et al., 2014). Deforestation has decreased in some part of park at higher altitude with severe winter with might be attributed to significant winter migration of inhabitant. Deforestation is associated with many ecological problems like change in rainfall regime, climate change which ultimately merge with socio economical problems of local people in particular compromising the quality of inhabitant (Reddy et al., 2013). Different problem of local community related to social issues like lake of education and awareness, poverty in the study area are the main causes of high anthropogenic pressure and ultimate degradation of local vegetation (Ilyas et al., 2015).

The study on the National park reveals that the study area posse’s great deal of plant biodiversity and has great potential for biodiversity conservation. The area hosts a variety of rare and endangered plants which demand a proper and serious attention to conserve such plant species in particular and over all floral diversity in general. If the plant resources of the area has not been given the very demanded attention the area might see many species at the verge of extinction along with ecosystem degradation which might create many other socio economic and environmental problems in the area as reported in many other area of Pakistan

(Ilyas et al., 2012; Khan et al., 2012; Khan et al., 2013). Any appropriate conservation plane may not work without the involvement of local inhabitant as they understand the nature, know the trends in species degradation and perceive the forthcoming change in ecosystem in realistic manner.(Kumar and Bhatt, 2006;

Rands et al., 2010; Ilyas et al., 2012). There is dire need of biodiversity

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conservation, not because it causes problem in the local area but can be felt in different time and space (Rands et al., 2010).

CONCLUSION AND RECOMMENDATIONS

The present study accentuate the enrichment of the study area with a significantly high plant biodiversity which not only provide services to local people in the form of food, fuel, timber, ethno medicine etc., but also contribute to the wellbeing of human in different time and space. The study reports certain endemic species as well as few alien species which are slowly and progressively domination the local plant species. The native plant species play a very crucial role in controlling the dynamics of the ecosystem. The local vegetation play significant ecological role in controlling soil erosion, regulating the chemistry of environment and providing other ecological services. Following are the some suggestions to improve plant resources of study area

1. The current study reveals the great diversity of plant taxa along with certain

new and endemic elements with characteristic associations, hence related

studies must be carries out from other regions of Punjab and related areas to

compile the flora and to fill the ecological gapes which was help full in

future studies.

2. The conservation of taxa must be entertained with the help local people

which posses a century old knowledge to make the consecration efforts

even more productive.

3. The local inhabitants must be trained to collect the medicinal plants in

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proper way to minimize the drastic loss of medicinal plants.

4. Plant conservation by in situ conservation procedures must be adopted for

plants the plant species which are restricted to particular habitat and pose

difficulties in their grouth away from their natural habitat like Bergenia

ciliata, Viola cancescens, Viola akranica, Hylodesmum podocarpum,

Sinopodophyllum hexandrum to save them from risk of extinction from the

study area.

5. The conservation of critical taxa, (endangered and critically endangered)

must be done using ex-situ approaches.

6. Seed and gene bank of threatened taxa must be developed.

7. The alien species must be eradicated to protect natural vegetation law must

be very clear to bane the growth of alien species and even import of such

species.

8. The local inhabitant should be provided with alternative energy sources like

solar energy, wind energy, natural gas, to minimize the anthropogenic

pressure in the form of fuel wood extraction.

9. Public awareness about the importance of plant biodiversity and the

negative consequence of loss of biodiversity should be created to directly

involve the local people in conservation efforts

10. The boundaries of the park must be clearly defined as the disputed

territories create problem in protection of bio-resources of the park.

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11. Deforestation, overgrazing, overexploitation along with human population

growth are the factors causing habitat destruction, soil erosion and

ultimately ecosystem degradation as whole. These issues must be given the

much demanded attention to solve some of the problems and to conserve

bioresources of area.

12. There is dire need of implementation of protection law in true spirit and

even new legislations are required to solve some unprecedented problems

which create hindrance in conservation efforts.

13. Extensive reforestation is required especially in severely deforested area

with the local plants.

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SUMMARY

Murree-Kotli Sattian-Kahuta national is endowed with rich plant biodiversity, but the scientific evaluation of the vegetation has not previously been attempted so far. To fill this research gap present study was conducted to evaluate the floristic wealth along with phytosociological attributes of local vegetation. The vascular flora of Murree Kotli Sattian Kahuta national park in district Rawalpindi comprised of 624 plant species belonging to 106 families and 375 genera, which include 24 ferns species, 4 species of gymnosperms and 596 angiosperms species

(i.e. 144 monocotyledon and 452 dicotyledons). Among them 508 plant species were native to the area, two species viz., Viola makranica and Buxus papillosa were recorded endemic to Pakistan. There were 16 plant species recorded for the first time from District Rawalpindi.

The phytosociological studies reveal seven plant communities which are, 1)

Oplismenus-Pinus community, 7) Pinus-Viburnum-Daphne community. The associations are determined by environmental variables like topographic and edaphic factor as depicted by Detrended correspondence analysis and canonical correspondence analysis

As a whole the vegetation of Murree-Kotli Sattian-Kahuta national park is dominated by the hemicryptophytes with 28.75% contribution to the flora followed by Therophytes with 27.92% contribution. The life form contribution with

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decreasing order was nanophanerophytes (17.22%), macrophanerophytes (13.29

%), chamaephytes (5.70%), geophytes (3.93%) and lianas (3.18%). Overall vegetation can be designated as Hemi-therophytes. Microphylls, with 31.82% contribution dominate the area. Nanophylls was (30.40%) the next most important leaf spectra class followed by where Leptophylls (24.72%) and Mesophylls

(13.07%) contribution. Hence the area is of Micr-Nano-Leptophyllous type.

Majority of plant species (279 spp., 79.26%), with respect to biodiversity and conservation, were categorized as least concern (LC) because of low use value, larger ecological amplitude, less biotic pressure and larger community size. This category was followed by Vulnerable (VU) status of 22 plant species (6.25%), followed by near threatened (20 spp., 5.68%), endangered (14 spp., 3.98%) and 17 plant species (4.83%) were categorized in critically endangered status. Beside natural calamities like land sliding forest fire, the major degradation of the vegetation is due to anthropogenic causes in the form of deforestation, overgrazing overexploitation of vegetation resources.

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Appendix-1

Community 1 Community 2

Community 3 Community 4

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Community 5 Community 6

Community 7

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Appendix-2

Gerbera gossypina Sarcococca saligna

Pseudocaryopteris foetida Pseudocaryopteris bicolor

Myrsine semiserrata Geranium mascatense

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