Ecological Evaluation of Plant Resources and Vegetation Pattern of Jelar Valley, Dir Upper, Pakistan

ECOLOGICAL EVALUATION OF PLANT RESOURCES AND VEGETATION PATTERN OF JELAR VALLEY, DIR UPPER, PAKISTAN

SHARIAT ULLAH

DEPARTMENT OF BOTANY UNIVERSITY OF PESHAWAR 2018

In the name of Allah, the Compassionate, the Merciful

Auther,s Declaration

I Shariat Ullah hereby state that my Ph.D thesis titled” Ecological Evaluation of Plant Resources and Vegetation Pattern of Jelar Valley, Dir Upper, Pakistan” is my own work and has not been submitted to previously by me for taking degree from this University University of Peshawar or anywhere in the country/world.

At any time if my statement is found to be incorrect even after my graduation the university has the right to withdraw my Ph.D degree.

Shariat Ullah

Date______

Plagiarism Undertaking

I solemnly declare that research work presented in the thesis titled “Ecological Evaluation of Plant Resources and Vegetation Pattern of Jelar Valley, Dir Upper, Pakistan” is solely my research work with no significant contribution from any other person. Small contribution/help wherever taken has been duly acknowledged and that complete thesis has been written by me. I understand the zero tolerance policy of the HEC and University of Peshawar towards plagiarism. Therefore I as an Author of the above titled thesis declare that no portion of my thesis has been plagiarized and any material used as reference is properly referred/cited. I undertake that if I am found guilty of any formal plagiarism in the above titled thesis even after award of PhD degree, the University reserves the rights to withdraw/revoke my PhD degree and that HEC and the University has the right to publish my name on the HEC/University Website on which names of students are placed who submitted plagiarized thesis.

Student /Author Signature: ______

Name: Shariat Ullah

DEDICATION

This thesis is dedicated to our parents, teachers and friends.

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University of Peshawar

Peshawar

ECOLOGICAL EVALUATION OF PLANT RESOURCES AND VEGETATION PATTERN OF JELAR VALLEY, DIR UPPER, PAKISTAN

A dissertation submitted in partial completion

of the requirement for the degree of

Doctor of Philosophy

Botany

Shariat Ullah

Graduate Study Committee

1. Prof. Dr. Ghulam Dastagir Convener 2. Prof. Dr. Sirajud Din Member 3. Dr. Zahir Muhammad Member 4. Dr. Tanvir Burni Member 5. Dr. Rasool Khan Member

PUBLICATION OPTION

I hereby reserve the right of publication, including right to reproduce this thesis in any form for a period of 5 years from the date of submission

Shariat Ullah

Acknowledgement

The spirit behind this task of mine goes to “All mighty Allah who gave me the power to complete this assignment. I need his help at every turn and every moment of my life. I offer my humble words of gratitude to the Holy Prophet of mercy, Muhammad (S.A.W) the most perfect and dignified among and of ever born on the surface of the earth who lit the candle of Islam and removed all darkness of our life. I have a special debt of gratitude to wise guidance of research supervisor, Dr. Lal Badshah for sincere encouragement, advice and over all support, which stimulated me while completing the course of my research work. I feel great pleasure and honor to express sincere appreciation to Prof. Dr. Muhammad Ibrar, Chairman, Department of Botany, University of Peshawar, Prof. Dr. Sirajud Din, Prof. Dr. Ghulam Dastagir, Dr. Nadeem Ahmad, Dr. Sami Ullah, Mr. Rehmanullah and Mr. Ghulam Jelani Sahib for their help and moral support. I would like to extend a sincere thanks to Prof. Mehboob-ur-Rehman, Prof. Shad Ayaz and Prof. Muhmmad Yousaf for his sincere cooperation and moral support throughout my research work. I offer my cordial and profound thanks to my affectionate parents and dear brothers and sisters for their encouragement, keen interest and for decorating my life with the ornament of knowledge.

Shariat Ullah

VITAE

Jan 25, 1979- Born. District Lakki Marwat, Khyber Pakhtunkhwa.

2000- B.Sc. Gomal University D.I. Khan.

2003- M.Sc. Gomal University D.I. Khan.

2013- M.Phil. Malakand University Chakdara, Dir Lower.

August 31, 2004- Lecturer, Govt. Degree College Habib Ullah Domel, District Bannu.

Nov 12, 2005- Lecturer, Govt. Degree College Ahmad Abad Karak.

Sep 01, 2007- Lecturer, Malakand University Chakdara, Dir Lower.

Major Field: Botany Field of Specialization: Vegetation Ecology

Courses Studied Teacher

1. Soil Algae Prof. Dr. Nadeem Ahmad 2. Fresh Water Algae Prof. Dr. Nadeem Ahmad 3. Vegetation Ecology Prof. Dr. Lal Badshah 4. Intensive Study In Ecology Prof. Dr. Lal Badshah 5. Limnology Prof. Dr. Barkat Ullah

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ABSTRACT

The present study aimed to explore ecological evaluation of plant resources and vegetation pattern of Jelar valley, Dir Upper during 2014-2017. Floristic list of the study area revealed that flora of Jelar valley is diverse and comprised of 250 species belonging to 177 genera and 77 families. The dominant families in term of species richness were Asteraceae and Lamiaceae, (each with 20 species, 8%), Rosaceae (19 species, 7.6%) and Papilionaceae (16 species, 6.4%), while the dominant genera were Polygonum and Rosa (each with 5 species). Due to harsh climatic conditions in winter, maximum numbers of species were found in summer and autumn. Biological spectrum showed that therophytes (101 species, 40.4%) were dominant followed by hemicryptophytes (43 species, 17.2%), while microphylls (32%) and nanophylls (30%) respectively dominating the leaf spectrum. The quantitative analysis of trees species in six study sites were subjected to Pc-Ord for cluster analysis, could establish four vegetation groups. Ailanthus altissima-Quercus incana community was distributed in Gumbad and Gul Dherai at 1967±130 (Mean± SE) m altitude with 20.1±2.3 slope angle. This group was more diverse (27 trees) as compared to others. Pinus wallichiana-Quercus incana community was distributed in Sore Pao at 1808 m altitude with 20.1±2.3 slope angle. This community consisted at total of 14 trees species. Pinus wallichiana- Prunus armeniaca community with fewer numbers of species recognized in Shao at 2058.6 m mean altitude with 15.6 slope angle. Similarly, Pinus wallichiana-Ailanthus altissima association was found in Tangi Awar and Danda at 2070.8 m altitude with 12.7 slope angle. Wards cluster and NMS ordination of 88 understory vegetation from six different zones constituted a total of four groups as; Sarcococca saligna-Isodon rugosus community at Gumbad, Wikstroemia canescens-Berberis lycium community at Sore Pao and Gul Dherai, Berberis lycium-Indigofera heterantha community at Shao and Danda and Berberis lycium-Indigofera heterantha community at Tangai Awar. NMS and PCA ordination were used to explore the relation of edaphic and environmental variables with trees species. Correlation of NMS ordination axis 1, 2 revealed that the NMS ordination axis 1 was only significantly correlated with nitrogen (P<0.05) while axis 2 was significantly correlated with altitude (P<0.001), organic matter % (P<0.05), Pb (mg/kg) (r= 0.83695, P<0.05) and Ca (mg/kg) (r= 0.947312, P<0.01) while PCA ordination axis 2 was significantly correlated with altitude and organic matter and axis 1 with slope angle. The relationship of NMS ordination axis with environmental variable

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associated with understory vegetation revealed that altitude and organic matter were found in significant correlation (r= 0.997, P<0.001) with axis 1 and lime % with axis 2. Lead (r= 0.752, P<0.05) and Ca (r= 0.947, P<0.01) with Axis 1. NMS ordination axis 2 was significantly correlated with nitrogen (r= 0.787, P<0.05) and Cu (r= 0.939, P<0.01). The soil was generally loamy sand, acidic in nature and slightly calcareous. Contents of organic matter ranged from 0.69% to 1.932%. The nitrogen contents were 0.966 to 0.0345 (mg/kg) while potassium 110 to 240 (mg/kg) and Cu 0.245 to 0.327 (mg/kg). Similarly, Zn 0.138 to 0.573 (mg/kg), Fe 0.879 to1.305 (mg/kg), Mn 1.885 to 6.179 (mg/kg) and Pb 1.0765 to 1.88 (mg/kg) were recorded. The concentration of Ca, Mg and sodium ranged respectively from 9.126 to 9.948, 2.2835 to 2.4545 and 16.9 to 19.45 (mg/kg). ANOVA showed significant variation at P<0.001 for all physicochemical parameters except soil texture. The palatability results revealed of the 250 plants species 55 (22%) were non-palatable and 195 (78%) were palatable which shows the grazing pressure. Among them 99 (39.6%) species were highly palatable, 51 (20.4%) species less palatable and 45 (18%) species rarely palatable. Livestock preferences showed that goats and sheep preferred 172 species while buffalo 71 species. Based on part used 98 (49%) species were consumed as whole plants and in 89 (44.55%) species only leaves were utilized, while in 13 (6.5%) species inflorescence was consumed by livestock. Similarly, some 116 (59.5%) species were found to be grazed in fresh condition, 2 species when it is dried and 77 (39.5%) species both in fresh and dried condition. In addition, the elemental composition of Impatiens bicolor, Myrsine africana, Themeda anathera, Sarcococca saligna and Quercus dilatata were evaluated at pre-reproductive and post- reproductive stages. The results revealved that Ca, Zn and Fe concentration were found high at pre-reproductive in all the selected species, while Mg contents were noted higher only in Sarcococca saligna and Myrsine africana at pre-reproductive stage. Phosphorus contents were found higher at pre-reproductive stage in Themeda anathera and Quercus dilatata, while Cu concentration was high at pre-reproductive stage only in Sarcococca saligna. Similarly K, Mn and Pb contents were found higher at post-reproductive stage in all the selected plants, while P were higher at post-reproductive stages only in Impatiens bicolor, Myrsine africana and Sarcococca saligna. Copper concentration was maximum at post-reproductive stages in all the species except Sarcococca saligna which was more at pre-reproductive stage. Magnesium

concentration was found more only in Impatiens bicolor, Themeda anathera and Quercus dilatata at post-reproductive stages. Ethnomedicinal study of the plants depicted that almost all parts of plants (21.7%), followed by leaves only (25.3%) were used in curing diseases, while the common mode of administration was usually decoction. Most of these species were multipurpose in their medicinal uses. Based on FIV the best represented used family was Lamiaceae (91.11), followed by Asteraceae, while the highest RFC was recorded for Mentha longifolia (0.266) followed by Olea ferruginea (0.259). The conservation status of medicinal flora revealed that Melia azedarach was found endanger, 35 (42%) species were rare, 15 (18%) species infrequent and 32 (39%) species were recorded as vulnerable in the area. Following the IUCN criteria for conservation none of the population was declared in the dominant category.

List of Contents

Page 1. INTRODUCTION...... 1 1.1 Area 1 1.2 Flora 1 1.3 Vegetation 1 1.4 Soil 1 1.5 Palatability and elemental analysis 2 1.6 Ethnomedicine 2 1.7 AIMS AND OBJECTIVES 4 2. REVIEW OF LITERATURE ...... 5 3. MATERIALS AND METHODS ...... 22 3.1 Floristic structure 22 3.1.1 Biological spectra of vegetation 22 3.1.2 Leaf size spectra 23 3.2 Vegetation structure 24 3.2.1 Data collection 24 3.2.2 Quadrats size and number 24 3.2.3 Vegetation data analysis 24 3.2.4 Frequency 24 3.2.5 Density 24 3.2.6 Herbage cover 25 3.2.7 Importance value index (IVI) 26 3.2.8 Density/ha and cover/ha 26 3.2.9 Statistical analysis 26 3.2.9.1 Cluster analysis and ordination 26 3.3 Ethnomedicine and conservation 27 3.4 Edaphology 28 3.4.1 Collection of soil samples 28 3.4.2 Laboratory procedure 28 3.5 Palatability 28 3.5.1 Phenological behavior 29 3.6 Chemical evaluation 29 3.6.1 Mineral composition 29 4. RESULTS AND DISCUSSION ...... 30 4.1 Floristic composition 30 4.1.1 Seasonal variation 31 4.1.2 Life form 31 4.1.3 Leaf size spectrum 32 4.2a Quantitative analysis of vegetation /Phytosociology 50 4.2.1a Classification of trees species through Ward‟s cluster analysis 50 4.2.2a Ordination of trees vegetation data 60 4.2.2.1a NMS ordination of trees vegetation 60 4.2.2.2a PCA ordination of trees vegetation 61 4.2b Classification of understory vegetation (Ward‟s cluster analysis and ordination) 67 4.2.1b Ward‟s cluster analysis of understory vegetation 67

4.2.2b Ordination of understory vegetation data 77 4.2.2.1b NMS ordination of understory vegetation 77 4.2.3 Density/ha and cover/ha of understory vegetation 80 4.3 Edaphology 88 4.3.1 Univariate analysis of variance (ANOVA) of different edaphic parameters 89 4.4 Palatability of vegetation 97 4.4.1 Degree of palatability 97 4.4.2 Classification based on livestock preferences 98 4.4.3 Classification of palatable plants species by part used 98 4.4.4 Classification of palatable plants species by condition 99 4.5 Chemical evaluation of some selected plants species 112 4.5.1 Macronutrients 112 4.5.2 Micronutrients 114 4.6 Medicinal plants and their conservation status 124 4.6.1 Family importance value (FIV) 125 4.6.2 Relative frequency of citation (RFC) 125 4.6.3 Conservation status of medicinal flora 126 Conclusions ...... 145 Recommendations 146 References ...... 147

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List of Figures

Fig. Titles Page.No 1. Mape of the study area 03 2. Percentage of species based on their habitat 47 3. Percentage no. of species in different seasons 47 4. Life form spectra of vegetation of Jelar valley 48 5. Seasonal variation in life form of vegetation 48 6. Leaf size spectra of vegetation of Jelar valley 49 7. Seasonal variation in leaf spectra of vegetation 49 8. Cluster analysis dendrogram of trees species obtained through Ward‟s cluster analysis 59 9. Two-way cluster dendrogram of trees species 59 10. NMS ordination plot showing the distribution of trees species between Axis 1, axis 2 65 11. PCA ordination Axis 1 and 2 of tree species 65 12. PCA ordination Axis 2 and 3 of tree species 66 13. PCA ordination Axis 1 and 3 of tree species 66 14. Cluster analysis dendrogram based on IVI of understory species 76 15. Two-way cluster dendrogram representing stands and species distribution in different groups 76 16. NMS ordination plot showing the distribution of stands of understory vegetation 80 17. Difference in clay particles in different sites 92 18. Difference in silt particles found in different sites 92 19. Difference in sand particles in different sites 92 20. Difference in pH values in different sites 92 21. Difference in organic matter in different sites 93 22. Difference in lime contents in different sites 93 23. Difference in nitrogen contents in different sites 93 24. Difference in phosphorus contents in different sites 93 25. Difference in potassium contents in different sites 94 26. Difference in Cu contents in different sites 94 27. Difference in Zn contents in different sites 94 28. Difference in Fe contents in different sites 94 29. Difference in Mn contents in different sites 95 30. Difference in Pb contents in different sites 95 31. Difference in Ca contents in different sites 95 32. Difference in Na contents in different sites 95 33. Difference in Mg contents in different sites 96 34. Differential palatability in each stratum of plant species in Jelar valley 109 35. Classification of palatable plants species based on preference of grazing animals 110 36. Classification of plants species based on parts used 110 37. Classification of various types of plants species based on livestock preference 111 38. Classification of plants species by condition used 111 39. Mean values of calcium contents (mg/kg) in different plants species 119 40. Mean values of magnesium contents (mg/kg) in different plants species 119 41. Mean values of phosphorus contents (mg/kg) in different plants species 120

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42. Mean values of potassium contents (mg/kg) in different plants species 120 43. Mean values of Cu contents (mg/kg) in different plants species 121 44. Mean values of Zn contents (mg/kg) in different plants species 121 45. Mean values of Fe contents (mg/kg) in different plants species 122 46. Mean values of Mn contents (mg/kg) in different plants species 122 47. Mean values of Pb contents (mg/kg) in different plants species 123 48. Classification of medicinal plants based on their habits 142 49. Classification of medicinal plants species based on their parts used 142 50. FIV of the top ten families found in the area 143 51. Species with highest relative frequency of citation 143 52. Conservation status of plants species in Jelar valley 144

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List of Tables Table Titles Page.No 3.1. Leaf type and leaf area 23 3.2. Density classes and their mid-point values 25 3.3. Cover size classes of herbs and their mid-point values 26 3.4. Classes of phenological behavior of species 29 4.1. Floristic composition, life form and leaf size spectrum, habitat condition and seasonal variation of vegetation in Jelar valley Dir Upper 34 4.2. Ecological characteristics of vegetation 45 4.3. Seasonal variation of life form spectrum 46 4.4. Seasonal variation of leaf size spectrum 46 4.5. IVI means values of trees species in different communities results from Wards cluster analysis 55 4.6. Density/ha of trees species in different communities obtained through cluster analysis 56 4.7. Basal area/ha of trees species in different communities obtained through cluster analysis 57 4.8. Topographic and edaphic variables associated with trees species 58 4.9. Correlation of NMS ordination axis 1, 2 with environmental and soil variables 63 4.10. Correlation of PCA ordination axis 1, 2, 3 of trees with environmental and soil variables 64 4.11. IVI mean values of understory vegetation in different communities groups obtained through Ward‟s cluster analysis 72 4.12. Topographic, edaphic and soil nutrients elements associated with different groups of understory vegetation 75 4.13. Relationship of environmental variables and soil nutrient elements with NMS ordination axes (1, 2) based on IVI of understory species 79 4.14. Density/ha and cover/ha of understory vegetation in different groups obtained through Ward‟s cluster analysis 83 4.15. Mean values of edaphic variable of different sampling sites 90 4.16. (ANOVA) of individual edaphic variables in six sampling sites 90 4.17. Palatability, part used, condition and animal preferences of plants species 100 4.18. Grazing percentage of palatable species by life form 109 4.19. Classification of palatable plants by browsed preferred parts by livestock 109 4. 20. Forage plants selected for chemical evaluation 112 4.21. Concentration of macro elements at various phenological stages 117 4.22. Concentration of micro elements at various phenological stages 118 4.23. Medicinal plants, RFC, FIV and their conservation status 128

INTRODUCTION

Chapter 1 INTRODUCTION

1.1 Area Jelar valley is located between 71o 56' 9" to 71o56' 4" longitude and 34o 5' 87" to 34o 58' 54" latitude in Dir Upper. "Jelar" is the combination of two words “Je” means mountain and “Lar” means track or way. Phytogeographically, it can be counted in Sinojapanese region (Ali & Qaiser, 1986). Jelar valley is situated at a distance of 16 km from Tehsil headquarter, Wari. It is surrounded by Maidan in West, Wari in the East, Molavi hills in the North and Luqman Banda in South (Fig. 1). Different topographic and ecological factors influence the climate of the valley. Annually, four distinct seasons remain the feature of the valley. Winter is harsh while summer is pleasant and short. The valley receives sufficient rain and snowfall during December to mid- March. July and August are the hottest while January and February are the coldest months during the year. The valley is divided into upper Jelar and lower Jelar. 1.2 Flora Floristic diversity projects physiognomy, ecological interactions in various territories (Catarino et al., 2002). The valley is flourished in wild medicinal flora local inhabitants and Hakeem‟s collect them and sold them in the market to earn their livelihood. Due to improper collection methods and poor literacy rate the pressure on the flora increases day by day. Several varieties of mushrooms are also grown wildly in the valley. Besides the wild medicinal flora, the valley is also rich in valuable timber and fuels plants species such as Pinus wallichiana, Pinus roxburghii and Quercus species. 1.3 Vegetation Species composition and structure of plant communities are regulated by environmental conditions and by spatial and anthropogenic factors (Cousins & Eriksson, 2002). Structure, role and composition are three noteworthy attributes of forest ecosystem that vary in response to topography, climate, soil and disturbances (Timilsina et al., 2007). 1.4 Soil The soil of the area is developed on residual and colluvial slopes of igneous rocks. Major types of rocks are metamorphic, igneous and sedimentary. The soil of the study area is acidic in nature and slightly calcareous and sand loamy in texture. Soil erosion and land sliding are common phenomenon due the removal of v egetation cover which greatly modifies the top soil and its effect is seen in the valley.

1.5 Palatability and elemental analysis Throughout the process of evolution, rangeland vegetation and grazing are co-adopted. However, undesirable plants result in growth of both overgrazing and under-grazing (Jones & Martin, 1994). Due to free grazing, palatable species has been reduced and are replaced by unpalatable grasses. Plant palatability and vegetation structure of an area depends on its morphology, chemical components, grazing animals and forage plants (Dalle et al., 2006; Chocarro et al., 2005 and Wang, 2004). The livestock owned by landless farmers in hilly areas subsist entirely on the rangeland. Due to inadequate management of the rangeland in Khyber Pakhtunkhwa, it has been severely overgrazed, as a result the palatable nutritious species of grasses have vanished and replaced by low quality vegetation with less preferences (Ali et al., 2007). Productivity of grazing animal is not only influenced by the forage plants but also depends on nutritional value of plants. In the ecosystem, the grazing pressure decides dietary value and plentiful of forage plants (Badshah & Hussain, 2011; Hussain & Durrani, 2008). Majority of the rangelands in Pakistan contain low palatable forage with deprived nutritive rate. Ecosystem also concerns with the chemical constituents and nourishing value of forages. 1.6 Ethnomedicine Moreover, medicinal plants have an ancient history of manhood itself; therefore, human beings are involved in utilization of plants resources since time immemorial. Studies at global level conducted from time to time i.e. Gilani et al. (2003); Khan & Khatoon (2008); Kala (2005); Olsen & Larsen, (2003); Wazir et al. (2007) have emphasized on the importance of medicinal plants in various medicine systems.

Fig. 1. Map of the study area

1.7 AIMS AND OBJECTIVES 1. To explore flora 2. To enumerate the vegetation dynamics 3. To explore the edaphology 4. To explore the palatability and grazing pressure 5. To explore the elemental and chemical profile of some selected species at different phenological stages 6. To explore the ethnobotany

REVIEW OF LITERATURE

Chapter 2 REVIEW OF LITERATURE

A. Flora Floristic composition such as life form and leaf size spectra are the most important physiognomic characteristics widely used for the exploration of vegetation. Life form spectra tells us about the micro and macro climatic condition of an area (Shimwell, 1971) while leaf size spectra is useful for the determination of association as well as for the understanding of physiological process of plants communities (Oosting, 1956). Some of the work done on floristic composition and its ecological attributes of vegetation is reviewed below: A1. International Ssegawa & Nkuutu (2006) recorded 179 species belonging to 146 genera and 70 families from Lake Victoria Central Uganda. They found Rubiaceae as the richest family with (14 species) followed by Euphorbiaceae (13 species), Apocynaceae (10 species) and Moraceae (9 species) while among the remaining majority of the families were monospecific. They further classified the plants based on the habit and stated that the area comprised of 10 shrubs, 39 lianas, 58 herbs and 72 trees species. Costa et al. (2007) worked on the floristic composition and life form of vegetation and reported 133 plants belonging to 47 families. Based on the Raunkiarian life form classification they reported therophytes the dominant life form class followed by phanerophytes, chamaephytes, hemicryptophytes and cryptophytes. Sarwar et al. (2008) studied the vegetation of campus of Bangladesh tea research institute and reported 199 plants with 155 genera and 69 families in which 168 species were dicotyledonous with 127 genera and 57 families. He found Leguminosae as the richest family in the area both in term of genera (20) and number of species (29), followed by Gramineae comprised of 11 species and 9 genera while among the remaining 38 families were monogeneric and 35 families were found to be comprised of single species. Francisco et al. (2009) worked on Commelinaceae of Equatorial Guinea and reported 46 plants with 12 genera in which the richest genus was Palisota (11 species). Malaker et al. (2010) reported the floristic composition of angiosperm of Lawachara forest in Bangladesh and found 159 species with 123 genera and 60 families in which Leguminosae was found the largest family in term of genera (12) and species (13) followed by Compositae comprised of seven genera and seven species. The other families which contributed more species were Euphorbiaceae, Anacardiaceae, Gramineae, Rubiaceae, Apocynaceae and verbanaceae. He further classified the vegetation based on growth habit and found 78 species as trees, 14 species

of shrubs, 42 herbs and 25 species as climbers. Tajali & Khazaeipool (2012) reported 205 species while studying the floristic composition of Kojur (Iran). Among the 36 families, Poaceae (37) was found the richest family followed be Asteraceae (27) and Lamiaceae (20). Alsherif et al. (2013) studied the life form chorology and floristic composition of vegetation of Khulais, Western Saudi Arabia and reported 251 species with 160 genera and 50 families in which Poaceae (42 species) was the richest family followed by Papilionaceae (20 species), Euphorbiaceae and Asteraceae with 18 and 15 species, respectively. Among the life form classes, therophytes (41.2%) were found dominant followed by chameophytes (31.4%), hemicryptophytes (13.7%) and phanerophytes (10%) while geophytes species were found in very low percentage in the study area. Ravanbakhsh & Amini (2014) conducted research on the floristic composition, ecological structure of forest reserve and chorology of Talesh, Iran and reported 76 species with 66 genera belonging to 45 families in which Rosaceae and Asteraceae were found the dominant families in term of number of species (5). Transect-quadrate method was used for sampling while, for the determination of life form, Raunkiaer method of classification was used. Erenso et al. (2014) reported 95 species with 76 genera and 58 families while studying the vegetation structure, diversity and floristic composition of woody plants communities in Boda dry evergreen Montane Forest of Ethiopia. They further reported the collected species were comprised of trees 34%, shrubs 45.2%, liana 13.8%, epiphytes 3%, trees/shrubs 1% and the remaining were trees/liana 1%. Seraj et al. (2014) reported vegetation chorology, floristic composition and life form of three major Wadis of South-Western Saudi Arabia and found 103 species 40 families in which more species were found in Asteraceae (23%) followed by Papilionaceae (8.7%) and Poaceae (6.7%). Based on the biological spectrum therophytes (32%) were found dominant life form followed by hemicryptophytes (15%) which showed a temperate climatic condition while, based on chorology the vegetation showed Saharo-Arabian and Sudanian element. Salama et al. (2014) studied the vegetation of Wadi Al-Assiuty and Wadi Habib in the Eastern desert of Egypt and reported 66 plants belonging to 53 genera and 22 families. Based on the life form therophytes (50%) were found dominant followed by chamaephytes, phanerophytes, hemicryptophytes and geophytes. Zhu et al. (2015) conducted research on the floristic composition and vegetation surveys on a tropical mountain in Southern Yunnan and reported 1657 species of seed plants with 146 families and 758 genera in which the dominant family was Fabaceae followed by

Euphorbiaceae, Rubiaceae and Lauraceae. Based on altitude he recognized three vegetation types such as tropical seasonal rain forest, lower montane evergreen broad-leaved forest and a montane rain forest and found the higher tree species diversity, number of genera and families in the low land and middle zones while lower diversity in the lower montane zone. He argued that lower diversity in the lower montane zone is due to the smaller amount of precipitation and repeated fires in the past historical period. Ganji (2016) explored the floristic composition and geographical distribution of vegetation in mining (West of Iran) and found 147 species and subspecies belonging to 116 genera and 36 families. Among the reported 36 families they found Asteraceae as the dominant family based on number of species followed by Brassicaceae, Poaceae, Fabaceae and Lamiaceae. Based on the biological spectrum of vegetation they found cryptophytes (49%) the dominant followed by therophytes (39%), chamaephytes (9.6%) and hemicryptophytes (5%) while based on the geographical distribution of species the vegetation belongs to Iran–Trainman area. A2. National Qureshi & Bhatti (2006) studied the floristic composition of vegetation of Nara desert, Sindh and reported 25 plants including three monocot families. Similarly, Malik et al. (2007) reported the biological spectrum of different plant communities Harbouring Ganga Chotti and Bedori Hills in the spring and monsoon season. Based on Raunkiarian classification of life form, the communities were grouped into four plants association in which hemicryptophytes and therophytes were found the dominant life forms both in spring and monsoon season while in the leaf size spectrum of vegetation, microphyllous were found dominant followed by nanophyllous species during both the seasons in the study area. Similarly, Ajaib et al. (2008) explored biological spectra of vegetation of Kotli (Pakistan). Hussain & Ishtiaq (2009) conducted floristic study on Samahni valley (A.K.) Pakistan, while Qureshi & Bhatti (2010) conducted similar study on Nawab Shah and reported 93 plants. Khan et al. (2011), Amjad (2012) and Shah et al. (2013) conducted research on life form and leaf size spectra of vegetation. Shaheen et al. (2015) explored species composition and community structure of subtropical forest of Kashmir and reported 65 species while, Amjad et al. (2016) reported conservation status, floristic composition and biological spectrum of vegetation of Nikyal valley, Kashmir and reported 110 species, 98 genera and 51 families.

Based on life form classification of vegetation they found hemicryptophytes the dominant life form class followed by therophytes and nanophanerophytes while based on leaf size spectrum of vegetation, nanophyllous were dominant followed by microphyllous. Based on the study of conservation status of vegetation they concluded that mostly the species in the area are critically endangered and require proper attention for the preservation of resources. A3. Regional Sher & Khan (2007) conducted research on the floristic composition of vegetation of Chagharzai valley (Buner), Shah & Hussain (2008) on Nowshera, Saima et al. (2010) on Ayubia National park, Haq et al. (2010) on Nandiar valley while, Khan et al. (2011) studied the biological spectrum of vegetation of Darra Adam Khel in summer and monsoon season and reported 30 families in which the leading families were Lamiaceae, Asteraceae and Solanaceae followed by Zygophyllaceae, Mimosaceae and Moraceae. Based on the biological spectrum of vegetation the dominant life form was therophytes followed by megaphanerophytes and nanophanerophytes while chamaephytes, hemicryptophytes and geophytes were found in low contribution in the area. From the study they concluded that the high percentage of therophytes were due to the heavy anthropogenic disturbance in the study area. In the leaf size spectrum of vegetation, microphylls were found dominant followed by mesophylls, leptophylls and nanophylls while, megaphylls were found in low proportion. Rashid et al. (2011) explored the floristic composition of vegetation of Malam Jaba (Swat) and reported 200 species belong to 75 families in which Asteraceae was dominant followed by Lamiaceae and Poaceae. Among the recorded 200 species therophytes (39.5%) were dominant followed by hemicryptophytes (17%) and geophytes (12.5%), while based on the leaf size spectra, macrophylls (41.5%) were dominant followed by nanophylls (32%) and leptophylls (13.5%). Shaheen & Shinwari (2012) explored the endemic richness and phytodiversity of vegetation of Karambar Lake and found 108 plant belong to 27 families in which Asteraceae was dominant followed by Leguminosae, Caprifoliaceae, Rosaceae, Primulaceae and Poaceae. Rafay et al. (2013) conducted research on the floristic composition of grasses in Cholistan and reported 27 species belong to 16 genera. Based on species abundance, they found therophyte as the dominant life form class (59.2%) followed by hemicryptophytes (33.3%) and phanerophytes (7.4%). Badshah et al. (2013) reported the floristic composition, ecological characteristics and biological spectrum of vegetation of district Tank and found 205 species with sixty-five families in which Poaceae was

found the dominant family followed by Papilionaceae and Asteraceae. Based on Raunkiarian classification of life form, therophytes (47.8%) were found dominant followed by hemicryptophytes (14.6%) and concluded that biological spectrum of vegetation changes not only due to the climatic variation but anthropogenic disturbance such as grazing; deforestation trampling and agricultural practice also play a major role. He also studied the leaf size spectra of vegetation and reported that nanophylls, leptophylls, microphylls and mesophylls were the most prevalent leaf sizes in the study area. Qureshi et al. (2014) studied floristic diversity and life form of vegetation of Khanpur Dam, Khyber Pakhtunkhwa, Pakistan and reported 221 species in 169 genera belong to 66 families comprised of 179 dicots, 39 monocots, one gymnosperm and two ferns. In the study area the leading dominant family was Poaceae (33 species) followed by Asteraceae (26 species) and Fabaceae (13 species). Based on the life span of the species, perennials were found dominant followed by annuals and biennial while on the basis of their habits herbaceous were found dominant, followed by shrubs, grasses and trees were found in less proportion. Therophytes (42.53%) were found dominant in the area followed by phanerophytes (27.15%). Mehmood et al. (2015) conducted research on the floristic composition of vegetation of district Torghar and reported 331 species of vascular plants with 246 genera and 101 families. Asteraceae was found dominant followed by Leguminosae. They further classified the vegetation into pteridophytes (12 species), gymnosperms (6) and angiosperm (313 species including 46 monocotyledons and 267 dicotyledons). Samreen et al. (2016) reported the floristic composition and ecological attributes of vegetation of Darazinda (D. I. Khan) and reported 213 species with in 68 families. Among the reported species 46 were monocots and 163 were dicots while the remaining species were pteridophytes (2) and fungi (2). Among the reported families they found Poaceae (37 species) the dominant followed by Asteraceae (19 species), Solanaceae (12 species), Brassicaceae (10 species) and Papilionaceae (9 species). Based on habitat classification they reported that wet were 41, dry and wet 24, cultivated plants 21, and dry species were 127 in number. They further classified the plants species based on their life form and reported that therophytes (49.2%) were dominant followed by hemicryptophytes (12.2%), geophytes (10.7%), chamaephytes (8.9%), nanophanerophytes (6.5%) and microphanerophytes (11.2%) while two species were parasites. Their results of leaf size spectrum shows that the dominant leaf size spectrum was nanophylls (34.7%), followed by leptophylls (21.5%), microphylls (20.1%), mesophylls (19.2%) and macrophylls 2 (1%) while aphyllus were 3.2%. Ullah et al. (2016)

conducted research on the floristic composition biological spectrum and ecological characteristics of vegetation of Bannu and reported 193 species with 154 genera belonging to 54 families. They classified them into monocotyledons (48 species) and dicotyledons (145 species). The most dominant family in the area was Poaceae comprised of 37 species. Among the reported 193 species therophytes (60.62%) was reported as dominant life form followed by hemicryptophytes and geophytes (9.84 for each one) while based on leaf size spectra, nanophyll (48.18%) were dominant. Based on the dominant life form (therophytes), they concluded that the area is falling in the semiarid zone of Khyber Pakhtunkhwa. The literature review showed that there is no information on the flora of Jelar valley. So, there is a dire need of floristic composition and ecological attributes of the area. B. Vegetation Phytosociology is an important tool for the evaluation of plants communities and vegetation data analysis (Rieley & Page, 1990). Plants communities‟ forms as results of kind of vegetation as well as climatic condition of a particular area. Plants communities structure gives information for the prediction of future and fast trends of vegetation in as area (Malik et al., 2007). B1. International Oswalt et al. (2006) reported the phytosociology of vascular plants in relation to environmental variables in St. John, US Virgin Islands. They used multivariate techniques (cluster analysis and NMS ordination) for data analysis and found four plants communities. Hirst & Jackson (2007) used ordination and gradient analysis for the analysis of plants community, Liu (2008) reported vegetation–environment relationships and dynamics in subtropical forests of china, Tavili et al. (2009) used CCA ordination for the exploration of vegetation environmental relationships in Khorasan rangelands while; Gui et al. (2010) applied ordination for vegetation environmental relationships (Kunlun Mountains). Zhang & Zhang (2011) studied the relationships between environmental factors and forest communities in the Lishan Mountain Nature Reserve, China using quadrat method. They used DCCA and TWINSPAN, for analysis and reported 9 plants communities and found that altitude and organic matter of the soil were important factors for the distribution of forest communities in the area. Mishra et al. (2012) conducted research on the phytosociology of three commonly occurring genera of family Asteraceae in Anapara (India). They studied different phytosociological attributes like relative

density, relative frequency, relative dominance and importance value index in order to know about annual variation in phytosociological status and population dynamics of the target generas (Vernonia, Tridax and Parthenium). Burju et al. (2013) studied the floristic composition, structure and community types of Jibat Humid Afromontane forest, West Shewa Zone Ethiopia and found 123 species in 161 genera and 73 families. For sampling of vegetation quadrat method was used and 20 x 20 m quadrat was placed for woody and shrubs species and 1 x1 m for herbaceous plants. Gandhi & Sundarapandian (2014) studied the species diversity and distribution pattern in tropical dry forest of Eastern Ghats (India) using quadrat method for data collection and a total of 20 plots were taken randomly. Based on density and IVI values, Lantana camara and Tarenna asiatica were found dominant shrub while in herbaceous plants Sida cardifolia and Ageratum conyzoides were dominant. Srivastava et al. (2016) conducted research on the phytosociology of 30 medicinal plants in Awarpur (M.S.) and reported that difference in vegetation in a site was due to the interaction of climatic condition and soil factor of the area and the predominance of a particular species showing its adaptive capacity to a particular site. B2. National Ahmed et al. (2006) conducted phytosociological study in different climatic zones of Himalayan forests. They reported 24 plants communities and four monospecific vegetation. The communities were made based on IVI and floristic composition of vegetation in which most of the community‟s shows similar floristic composition but difference was found in the quantitative data of different species. Malik et al. (2007) work on the vegetation of Pir Chinasi hills (Kashmir) and recognized 13 plants communities of 77 species. Wazir et al. (2008) studied the vegetation of Chapursan valley (Gilgit) and reported five plants communities in relation to topographic and edaphic factors. Ahmed et al. (2009) explored vegetation structure of Olea ferruginea forests of Dir, Badshah et al. (2010) conducted research on subtropical forests of Tabai, South Waziristan, Pakistan, Ahmad (2011) studied the vegetation and soil relationship along Lahore-Islamabad motorway (M-2) using CCA ordination and reported that lead, nickel, zinc, potassium and sodium were the important variables effecting the distribution of vegetation. Ahmad & Quratulann (2011) studied the vegetation of Ayubia National Park using TWINSPAN, NMS ordination and Monte-Carlo test for analysis and reported two major communities such as Hedera nepalensis-Adiantum caudatum and Plantago major-Rumex nepalensis community. Akbar et al. (2011) conducted research on the phytosociology of vegetation of three districts of

Gilgit Baltistan. Based on IVI the vegetation was classified into five mixed communities and five pure stands. Some saplings were also observed during research. Shaheen et al. (2011) studied the vegetation environmental relation and anthropogenic disturbance in subtropical forests of Kashmir. Species diversity, species evenness, richness and maturity index were also carried out. Saeed et al. (2012) conducted data on phytosociology of chasmophytes and epiphytes of Lahore city using quadrat method. Based on Ward‟s cluster analysis five plants communities (Dactyloctenium-Setaria community, Tribulus-Polygonum community, Malvastrum-Calotropis- Ficus community, Boerhavia-Amaranthus-Morus community, Alternanthera–Xanthium- Portulaca community) could have established. Nazir et al. (2012) study the phytosociology of vegetation in Sarsawa hills Kashmir in relation to environmental variables using quadrat method for data collection and 10 x 10 m quadrat was used for trees, 5 x 5 m for shrubs and 1 x 1 m for herbaceous plants. Some nine communities were established in all. Noor & Khatoon (2013) studied the vegetation patterns and soil characteristics of Astore valley (Gilgit) at different elevation and found the herbaceous plants dominant in the natural habitat while at low altitude halophytic and xerophytes species were found. Shabbir et al. (2014) and Haq et al. (2015) explored vegetation environmental relationships while Amjad et al. (2016) conducted study on the phytosociology of vegetation of Nikyal valley, Azad Jammu and Kashmir using quadrat method. B3. Regional Ahmed et al. (2006) conducted research on various climatic zones of Himalayan forests and reported 24 communities and four monospecific forests vegetation. Ali et al. (2007) reported the vegetation capacity and physical characters of different rangeland of Dir Lower, while Siddiqui et al. (2009) reported vegetation environment relation of conifer dominated forests of temperate (Himalayan and Hindukush) areas of Pakistan. Hussain et al. (2010) studied phytosociology and structure of Central Karakoram National Park using PCQ method and reported six communities such as Picea-Pinus community, Picea-Smithiana pure stand, Juniperus-excelsa pure stand, Rosa-Hippophae community, Rosa-Ribes community and Hippophae-Berberis community. Khan et al. (2010) conducted research on the ecological status of Monotheca buxifolia forests in Dir Lower at different altitude and found six tree species in association with Monotheca buxifolia. Ahmed et al. (2011) reported Cedrus deodara dominated forests of Hindukush and Himalayan region. Rashid et al. (2011) reported phytosociology of

vegetation of Malam Jabba valley. Khan et al. (2012) reported the phytosociology of forested and non-forested areas of Chitral. Khan (2012) worked on communities of Quercus baloot dominated forests in district Dir, Upper. They used PCQ method for data collection and cluster analysis for classification as well as DCA for ordination of environmental and edaphic factors. They get three major vegetation groups dominated by Quercus baloot. Khan et al. (2013) studied the vegetation-environment relationships in the forests of Chitral using Point Centered Quarter (PCQ) method. They used cluster analysis and DCA ordination for the analysis of vegetation and reported six plants communities in which Cedrus deodara was found the dominant species. Shah & Rozina (2013) conducted work on the phytosociology of vegetation of Dheri baba hill and Peer Taab graveyard (Swabi) while, Shah et al. (2014) reported communities structure and dynamics of vegetation of Farash hills, Mardan. Ali et al. (2015) applied multivariate analysis to evaluate interaction between plants and plants-environmental variables while exploring the vegetation of Hindukush mountain of Pakistan and Ilyas et al. (2015) conducted research on the quantitative study of vegetation of Kabal valley and reported 9 plants communities. Similarly, Muhammad et al. (2015) studied the population structure and phytosociology of Acacia modesta at different altitude in Malakand division. Rahman et al. (2016) reported the phytosociology of Isodon rugosus dominated communities in Khwazakhela (Swat). Khan et al. (2016) reported the phytosociology of pine forest of Indus Kohistan and recognized six communities and four monospecific stands of Cedrus deodara. Irshad et al. (2016) reported the impact of environmental factors on the distribution of Punica granatum communities in district Dir (Lower). However, there is no such information on the vegetation of Jelar valley Dir Upper. Therefore, phytosociology is needed to be worked out. C. Edapholpgy Soil is the most important component of the universe for the survival of living organism, because all the production of agriculture, forests development depends upon the physiochemical properties of the soil (Kekane et al., 2015). It is a medium of unconsolidated nutrients and materials which forming the life layer of plants. The physicochemical parameters of soil determine their adaptability to vegetation and level of biological activities that can be supported by the soil (Borkar, 2015). Physicochemical properties of the forests soil vary in time and space due to climate of the area, topography, weathering processes, microbial activities and abiotic factors (Shrivastava & Kanungo, 2014; Champan & Reiss, 1992).

C1. International Joel & Amajuoyi (2009) determined the physical and chemical properties of the soil of dump sites Ezeogwu (Nigeria). Dengiz (2010) reported the physiochemical properties, classification and morphology of soil from Tigris River (Turkey). Similar work was also done by Zaiad (2010) in Al-Khums city, Libya. Fonge et al. (2011) reported the soil properties and their effect on plants communities on Cameroon mount. Raut & Ekbote (2012) worked on the physiochemical properties of the soil in Babhulgaon (Yavatmal). Chaudhari (2013) from India, Shrivastava & Kanungo (2014) reported the physico-chemical characteristics of soil of Surguja (India), Fauzie et al. (2015) reported the properties of soil in different sites at Yamuna Biodiversity Park in India. Asema et al. (2015) analyzed the soil of Aurangabad city (India) for their physiochemical characteristics. Rahal & Shamkhi (2015) reported the spatial variation of physical and chemical characteristics of soil of Mesopotamian plain (Iraq). Geetha et al. (2017) reported the physiochemical properties of agricultural soil in Kommangi, Visakhapatnam. C2. National Ashraf et al. (1999) reported the physical and chemical analysis of the soil of Cholistan desert. Khan et al. (2004) analyzed the soil of semi arid areas of Pakistan for concentration of various micro and macro nutrients. Khan et al. (2005) reported the difference in concentration of various elements in the soil in different seasons of the year. Hamid et al. (2006) reported the impact of soil pH on the growth and rooting on Camellia sinensis, while Ashraf & Ali (2007) reported the effect of different metal elements on the germination of bean seed as well as on the microorganisms of the soil. Malik et al. (2010) studied the contamination of heavy metals in soil and few wild plants from the industrial area of Islamabad. Arshad et al. (2011) explored the correlation of soil texture with the availability of Zn and Cu. Amjad et al. (2013) reported the physiochemical properties of Pinus and Quercus dominated sites in Nikyal hills (Azad Kashmir). Rafay et al. (2015) reported the physiochemical analysis and its impact on grasses diversity of Cholistan desert. Khan & Zafar (2015) worked on the physiochemical properties of soil and water of Kasur region. Ahmad et al. (2016) reported the impact of soil on the distribution of vegetation of temperate Himalayan.

C3. Regional Babar et al. (2004) conducted research on the soil properties of Gilgit. Wasiullah & Bhatti (2007) reported the soil properties of Kohat and Bannu, Wazir et al. (2008) reported the impact of soil physiochemical properties on the vegetation of Chapursan valley (Gilgit), Khan et al. (2010) from Chitral. Khan et al. (2011) from Dir Lower. Rehman et al. (2015) conducted similar research from North of Kohat. Azeem et al. (2016) from Goal Dam (Karak) Khyber Pakhtunkhwa, Irshad et al. (2016) reported the soil characteristics of Punica granatum dominated sites of Dir Lower. Younas et al. (2017) reported the physiochemical properties of soil and water of three dames in Karak, Khyber Pakhtunkhwa, Pakistan, while focusing on the physiochemical properties of the soil there is not found any information on the soil of Jelar valley. D. Palatability Palatability may be defined as the relationship between foods nutrient‟s flavor and its toxin contents. When a food is eaten by an animal it is digested and releasing nutrients or toxins because all plants contain some level of toxic material. After digestion these toxins and nutrients materials are absorbs and travel to different cells of the body. The cells or different organs of the body then sent the message to the brains and tell it how well a food fulfils the animal‟s dietary demand. The brain then pairs the flavor of foods with its nutritional benefits or toxicity. This information is stores in the brains for the future experience. The smell and taste also enable animals to discriminate among foods and provide pleasant or unpleasant feelings associated with eating. So the taste, smell flavor and past experience associated with eating the foods determined the degree of palatability of plants for the livestock (Provenza, 1995). Preference of plants by alivestock is determined by plant palatability. The palatability of plants is determined by various factors such as secondry metabolites, morphology and phenology (Hussain & Durrani, 2009b). In addition to this some grazing animals prefer to consume a plant in its fresh condition while others eat it in dry form or in both dry and fresh condition. Some of the work conducted on the palatability of vegetation is given below: D1. International Vesk & Westoby (2001) reported the prediction of plant responses to grazing animals. Brits et al. (2002) reported that by large herbivores congregating around artificial watering points has affected an average of 3% of the total area of the Kruger National Park (KNP). Schadler et

al. (2003) reported the palatability, composition and insect herbivory and found that due to the reduction of herbivory the ranking of plants based on palatability showed no relationship with the specific change of cover abundance. Lucas et al. (2004) conducted study on the grazing pressure on cottonwood population and stated that increased grazing pressure did not have significant impact on cottonwood populations while the effect of seasonal use were significant on species diversity and richness of herbaceous flora while Chocarro et al. (2005) reported the effects of one severe winter-grazing of lucerne over three years in the Ebro valley (Spain). Ebro et al. (2007) worked on the rangeland of Middle Awash valley of Ethiopia. Beyene (2009) reported the fed resources and rangland condition of livestock in Assosa Zone, Benishangul- Gumuz Region. Auda (2010) reported the ecology and palatability of plants in Gaza Strip (Palestine), Shenkute et al. (2012) reported the nutritional value of fodder plants in Ethiopia. El- hag et al. (2013) reported the effect of plant maturity stage on digestibility and distance walked for diet selection by goat at North Kordofan State, Sudan. Raufirad et al. (2015) conducted research on the relationship of animal preference and external attributes of plants of Karsanak rangelands (Iran). Fleming et al. (2016) conducted an experimental study on diet preferences of goats in a subtropical dry forest and implications for habitat management in U.S.A. D2. National Sultan et al. (2008) conducted research on palatability, digestibility and mineral composition of free rangeland grasses of Northern Grasslands of Pakistan. Hussain & Durrani (2009a) worked on the palatability of plants in Harboi arid rangeland of Kalat. Similarly, Gulshan & Dasti (2012) conducted study on grazing behavior of different animals in Thal and Cholistan deserts of Punjab (Pakistan) and reported that 39 wild plants were frequently grazed by animals in the area. They also reported that the level of grazing pressure was high on herb and grasses followed by shrubs, under-shrub and trees by the different categories of animals. Amjad et al. (2014) conducted research on the palatability of vegetation in Nikyal rangeland (AJK) while, Abdullah et al. (2017) reported the palatability of plants in arid rangelands of Cholistan desert (Pakistan). D3. Regional Ali et al. (2007) work on the vegetation capacity and physical characteristics of open and protected rangeland in Dir Lower and reported higher number of palatable plants in the protected rangeland. Similar study was also reported by Badshah (2011) from district Tank. Khan &

Hussain (2012) conducted reaserch on plants palatability and animal preferences in Takht-e- Nasrati, (Karak). Ali (2016) conducted research on the palatability of vegetation in Chail valley (Swat). Focusing on the vegetation of Jelar valley there is not found any information on palatability. Therefore, the present study aims to explore the palatability of plants of Jelar valley. E. Chemical evaluation Bioelements are those required by our body for numerous physiological and biological functions necessary for the health maintenance of an organism (Bahadur et al., 2011). The richest sources of these elements required for animals are plants. There is a direct relationship of the nutritional status and elemental composition of plants (Newall et al., 1996). The following work has been done on the elemental analysis of plants. E1. International Storeheier et al. (2002) evaluate the elemental profile of the species of Poaceae. Starks et al. (2004) worked on the concentration of nitrogen, neutral and acid detergent fibers in live standing forages species. Dairo & adanlawo (2007) reported the nutritional potential of three plants, while Gutierrez et al. (2008) reported the chemical composition of fourteen weed in Mexico. Kumar et al. (2011) reported the elemental profile of some medicinal plants collected from Jaunpur (India). Ragavendran et al. (2012) reported the elemental profile of Aerva lanata. Yagi et al. (2013) reported the elemental composition of Sudani medicinal plants. Andualem & Gessesse (2014) worked on the elemental composition of Millettia ferruginea. Hannah & Krishnakumari (2015) reported the elemental composition and nutritive value of Citrullus vulgaris. Kachiguma et al. (2015) reported the mineral composition of Amaranthus species collected from central Malawia. Parab & Vaidya (2016) reported the mineral contents of Sesbania bispinosa from India. E2. National Khan et al. (2004) reported the mineral composition of forage plants in semiarid region of Pakistan. Shaheen (2005) reported the nutritional value of some selected shrubs and trees species collected from Chiltan National Park. Khan et al. (2006a) reported that seasonal changes of elemental profile of forage plants and stated that iron, zinc and selenium in forage plants were affected by seasonal variation. Khan et al. (2007) reported seasonal variation of micro and macro nutrients contents of forages plants. Rahim et al. (2008) determined the elemental composition of

some grasses plants from Himalayan grasslands. Abbasi et al. (2009) conducted a comparative study on elemental composition and nutritive value of legumes and grasses and found that white clover forage had high concentration of P, K, Ca and Mg as compared to grasses species. Bano et al. (2009) reported the seasonal variation in nutritive value of two plants collected from Balochistan. Shirin et al. (2010) reported the elemental profile of Withania somnifera. Zaidi et al. (2010) reported the elemental composition of six plants from Quetta valley Balochistan. Ata et al. (2011) reported the elemental profile of 24 medicinal plants. Ghani et al. (2012) reported the elemental composition of some selected medicinal plants collected from Soon valley Khushab, Pakistan. Similar study was also condected by Rahim et al. (2013). Ghani et al. (2016) reported the difference in the elemental profile of Solanum nigrum collected from different areas of Mianwali. Abdullah et al. (2017) reported palatability and nutritional potential of plants of Cholistan deserts. E3. Regional Hameed et al. (2008) worked on the elemental composition of selected medicinal plants from Pakistan. Hussain et al. (2011) reported the elemental composition of six vegetable species of Mardan district, Pakistan. Similar study was also conducted by Mushtaq et al. (2012) from Swabi. Khan et al. (2013) reported the elemental profile of ten plants at different phenological stages collected from Takht-e-Nasrati (Karak). Shad et al. (2014) worked on the phytochemical analysis of four wild medicinal plants collected from different areas of Khyber Pakhtunkhwa, Pakistan. Ullah et al. (2015) conducted research on the heavy metal profile of some selected medicinal plants from Karak Khyber Pakhtunkhwa, Pakistan. Salman et al. (2015) reported the elemental profile of Mirabilis jalapa. Samreen et al. (2016) conducted similar work on some fodder plants of Darazinda (D. I. Khan). F. Ethnomedicine Ethnobotany may be defined as the study of how the peoples of a particular region make the use of indigenous flora for medicinal purposes. Ethnobotany is the relation of a society with plants (Aumeeruddy, 1996). The field of ethnobotany is old as human civilization. It is a branch of botany originates in part from an interest in finding plants to help fight illness (Qureshi et al., 2007). The interaction of human society with plants varies due to their uses, social, cultural and ethenic factors (Shinwari et al., 2011). A lot of research has been conducted on ethnobotany in

different parts of the world as well as in Pakistan. Some of the work done on ethnobotany is reviewed below: F1. International Hanazaki et al. (2006) reported the ethno-botanical uses of 248 plants from Carlos Botelho State Park, São Paulo State, Brazil. Informations from 58 inhabitants (male and female) were collected through interview about the local uses of these plants. Okello & Ssegawa (2007) from Ngai subcounty in Apac district and found that mostly the roots of the plants are used as medicines which directly affect the regeneration status of the flora especially medicinal plants in the area. Wyk et al. (2008) conducted research on the ethnobotany of medicinal plants in Southeastern Karoo, South Africa and reported that 86 plants included Metria medica are still used by the people for curing of different ailments like kidneys, bladder, colds, back and stomach. Similarly, Mao et al. (2009) reported the ethno-botanical uses and status of the wild plants of Northeast India. Amusa et al. (2010) conducted research on the conservation status and ethnobotany of medicinal plants resources of Kainji Lake National Park, Nigeria. Similar study was also reported by Oladele et al. (2011) and Rajaei & Mohamadi (2012) from Nigeria and Iran respectively. Mesfin et al. (2013) recorded the ethno-botanical uses of traditional medicinal plants from Gemad, Northern Ethiopia. The information collected on medicinal plants were mainly based on parts used, preparation method, route of administration and diseases for which the plants were used. Parul & Vashistha (2015) reported the ethno-botanical uses of 73 plants from Yamuna Nagar (India) and classified them based on parts used and type of disease. Jadhav (2016) conducted research on the ethnobotany and ethno-medicine of Kadegaon (India) and reported the local uses of 21 plants belonged to 15 families. Mengesha (2016) conducted research on ethno-botanical survey of medicinal plants used for the curing of different human and livestock disorders in Mandura Woreda, Ethiopia. F2. National Qureshi et al. (2006) reported the ethno-botanical uses of plants resources of Gujar Khan (Rawalpindi) while, Qureshi et al. (2007) conducted research on the ethno-botanical uses of medicinal plants of Mianwali Pakistan and reported 26 vascular plants used for different purposes in the area. Ahmad & Hussain (2008) conducted research on the ethno-botanical uses of medicinal plants of Kalar-Kahar and reported 29 medicinal plants belong to 18 families. Similar study was also conducted by Qureshi et al. (2009) tehsil Chakwal, Pakistan and reported

the ethno-botanical uses of 29 plants. Tareen et al. (2010) conducted research on the ethno- botanical uses of medicinal plants in Kalat and Khuzdar (Balochistan). They reported the local uses of 61 plants belong to 34 families and 56 genera. Mahmood et al. (2011) reported the medicinal uses of 38 plants from Azad Kashmir, Khan et al. (2012) conducted research on the ethno-botanical uses of medicinal plants of Ponch valley, Azad Kashmir and reported the local uses of 56 species belong to 36 families. Ajaib et al. (2013) conducted research on the ethno- botanical study in Loralai district, Balochistan and reported the local names, botanical name, part used and purpose of uses of 28 plants belong to 39 families. Ajaib et al. (2014) also documented the ethno-botanical uses of medicinal plants of Kotli, Azad Kashmir and reported 93 herbaceous plants belong to 46 angiosperm families. Beside the vegetable and fodder uses of these plants the people of the area uses these plants for different human diseases such as eczema, jaundice, hypertension, impotency, rheumatism and gonorrhea. Wariss et al. (2014) reported the ethno- botanical uses of 212 plants from Lal Suhanra National Park, Bahawalpur. Jabeen et al. (2015) and Ajaib et al. (2016) explored the ethno-botanical uses of plants from Gilgit and Azad Kashmir respectively. F3. Regional Wazir et al. (2004) conducted research on the ethno-botanical uses of 41 plants belong to 29 families from Chapursan valley Gilgit–Baltistan while Ahmad et al. (2006) from Booni (Chitral). Hussain et al. (2006) conducted research on the ethno-botanical uses of plants of Ghalegay, Swat Pakistan and reported 126 plants of various economic uses. Ibrar et al. (2007) reported the ethno-botanical uses of 97 medicinal plants from Ranyal hill district Shangla and classified them based on local uses. Hazrat et al. (2007) reported the medicinal plants of family Ranunculaceae in Dir valley and reported 39 species with 14 genera. Jan et al. (2008) reported the local uses of 43 medicinal plants from Kaghan valley. They stated that out of 43 species 27 species are used as poly herbal recepies while the remaining fifteen are used as minor component. Zahoor et al. (2009) conducted research on the ethno-botanical uses of medicinal of Darra‟e Pezo, (Lakki Marwat). They reported 52 plants with 45 genera and 30 families in which 47 medicinal plants used by the people for curing of different diseases. Ali & Qaiser (2009) worked on the ethno-botanical uses of plants of Chitral district and reported 83 species. They stated that mostly the people of the area use roots of the plants as recipes and taken them orally. Similarly, Akhtar & Begum (2009) conducted research on the local uses of 55 medicinal plants

in Jalala (Mardan) and stated that the inhabitants of the area use these plants for the treatments of forty-two different types of diseases. Ullah et al. (2009) conducted ethno-botanical study on vascular plants of Jandool valley (Dir Lower) and reported the medicinal uses of 60 plants. Jan et al. (2010) reported the ethno-botanical uses of weeds from Dir Kohistan valley. Shinwari et al. (2011) conducted research on the ethno-botanical survey on Kohat Pass, Khyber Pakhtunkhwa, Pakistan and reported the local uses of 60 plants belong to 49 genera and 30 families. Ahmad et al. (2011) conducted research on the ethno-botanical uses of medicinal plants of tehsil Kabal Swat, Pakistan and reported the local uses of 140 plants. Badshah et al. (2012) conducted research on the flora of rangeland of district Tank, Pakistan and reported 205 plants, classified them based on the utility of plant such as medeicinal species (22.4%), fuel wood species (36%) etc. Nasrullah et al. (2012) on Jandool valley Dir Lower and reported the ethno-botanical information on 67 plants. Khan et al. (2013) reported the ethno-botanical uses of 27 commonly used plants from Bannu. The data on ethno-botanical uses was collected from pansaries, herbalists and local inhabitants through questionnaire from more than eighty interviewers. Qaisar et al. (2013) conducted research on the ethnobotany of medicinal plants of North Waziristan and collected 88 medicinal and aromatic species. These species were classified based on the type of disease cured. Ahmad et al. (2014) reported the ethno-botanical uses of flora of Chail (Swat) while Khan et al. (2015) reported the ethnomedicinal plants of Kabal valley. Shah et al. (2015) reported the medicinal uses of flora of Torghar, Begum et al. (2016) reported the ethno-botanical uses of flora of Harichand (Charsada) and Shuaib et al. (2016) conducted similar study on the ethnobotany of plants of district Dir Upper. The review shows that there is no information on the ethnomedicinal flora of Jelar valley Dir Upper. Therefore, it is needed to explore the ethnomedicine.

MATERIALS AND METHODS

Chapter 3 MATERIALS AND METHODS

3.1 Floristic structure Regular trips were arranged for the preparation of floristic checklist of Jelar valley, Dir Upper, Pakistan in the year 2014-2017. The research area was thoroughly searched for the collection of plants. The collected plants specimens were preserved, identified with the help of Flora of Pakistan, (Nasir & Ali, 1971-1995; Ali & Qaisar, 1995-2015) arranged in alphabetical order. Voucher specimens were properly numbered in alphabetical order and deposited in Herbarium, Department of Botany University of Peshawar. 3.1.1 Biological spectra of vegetation In order to know the biological spectrum and ecological characters of the study area, Raunkiaer (1934) and Hussain (1989) methods were followed. The plants were classified into different life-form classes which are described as under: i. Therophytes (The) Therophytes were the seed bearing annual plants which complete their life cycle in a single year and spend the unfavorable period in the form of spores and seeds. ii. Geophytes (Ge) Geophytes were the plants whose perennating buds were located below soil surface. This life-form includes plants having deep rhizomes, tubers, corms and bulbs etc. iii. Hemicryptophytes (Hem) Hemicryptophytes were herbaceous perennial plants whose perennating buds were located just near to the surface. The aerial parts of these plants died at the end of growing season, at the surface of the earth or below the ground. iv. Chamaephytes (Cha) Chameophytes were herbaceous, low stem succulents; low woody trailing and cushion plants whose perennating buds were located near the surface of ground upto 0.25 m height. v. Phanerophytes (Pha) They were shrubs and trees whose perennating buds were borne on aerial shoots. These were further classified into nanophanerophytes, microphanerophytes, mesophanerophytes and megaphanerophytes.

a. Nanophanerophytes (Np) The plants whose perennating buds were bear on aerial shoots from 0.25 to 2 m above the surface of ground. b. Microphanerophytes (MicP) Microphanerophytes were shrubby plant with perennating buds located above 1.8 to 7.6 m. c. Mesophanerophytes (MesP) Mesophanerophytes were small trees whose perennating buds were located at 7.5 to 30 m above the ground surface. d. Megaphanerophytes (MgP) Tall tree whose perennating buds were found at a height of 30 m above the surface of earth. The following formula was used for the calculation of biological spectrum.

3.1.2 Leaf size spectra The leaf size knowledge of plants is helpful for the understanding of physiological process of plants as well as classification of vegetation communities. Plants found in the study area were also classified into various leaf size classes following Raunkiarian leaf sizes spectrum (Raunkiaer, 1934) as given below: Table 3.1. Leaf type and leaf area Leaf type Leaf area (mm2) Leaf type Leaf area (mm2) Leptophyll (L). up to 25 Mesophyll (Mes). 2025-18225 Nanophyll (N). from 25 to 225 Macrophyll (Mac). 18225-164025 Microphyll (Mic). from 225 to 2025 Megaphyll (Meg). Above 164025

The formula used for calculation of Raunkiaerian leaf size spectrum is given as:

Importance value indices of plants were used for the calculation of quantitative leaf size spectra of species following Cain & Castro (1959). The following formula was used for the calculation of quantitative leaf size spectrum:

3.2 Vegetation Structure 3.2.1 Data collection Regular trips were arranged for the collection of data in Jelar valley during the years 2014-2017. Based on physiognomy, species composition and habitats difference the whole area of Jelar valley was divided into six ecological zones (Shao, Danda, Tangai Awar, Sore Pao, Gumbad and Gul Dherai) for quantitative analysis. For sampling of vegetation different quantitative methods were applied following standard procedures (Cottam & Curtis, 1956; Mueller-Dumbois & Ellenburg, 1974). 3.2.2 Quadrats size and number Phytosociological attributes were measured by 1×1 m2 (herbs), 5×5 m2 (shrubs) and 10×10 m2 (trees). A total of 15 quadrats were laid for herbs, 10 for shrubs and 5 quadrats for trees species in each study site (Badshah, 2011). The frequency, density and cover of species were measured. Plants were identified with the help of Flora of Pakistan (Nasir & Ali, 1970- 1989; Ali & Qaisar, 1995-2015). 3.2.3 Vegetation data analysis Phytosociological data was calculated following Curtis & Mclntosh (1950) and Hussain (1984). The data of all of the reported trees species and understory vegetation found in the six sampling sites was inputted to Microsoft Office Excel 2007 for analysis. The formulas used for the initial data of vegetation analysis are given as under: 3.2.4 Frequency Frequency is the percentage occurrence of a species in an area and is calculated by using the following formula: Number of quadrats in which a species occured Frequency (F1) 100 Total number of quadrats Frequency of a species Relative Frequency (F3) 100 Frequency of all species 3.2.5 Density Density is the average number of individuals of a species in a unit area and is calculated using the formula as:

Number of individuals of a species in all quadrats Density (D1) Total number of quadrats Number of individuals of a species in all quadrats Relative Density (D3) 100 Number of individuals of all species in all quadrats The following ten classes of density were made and their mid-point values were used for statistical analysis (Table. 3.2). Table 3.2. Density classes and their mid-point values Classes Density range Mid-point values 1. Up to 10 5 2. 11-20 15 3. 21-30 25 4. 31-40 35 5. 41-50 45 6. 51 – 60 55 7. 61 – 70 65 8. 71 – 80 75 9. 81- 90 85 10. 91 -100 95

3.2.6 Herbage cover The cover of species was calculated as follow: Sum of Cover of a species in a quadrat Cover (C1) Number of individual of a species in a quadrat Cover of a species in quadrat Relative Cover (C3) 100 Sum of cover of a species in all quadrat

Table 3.3. Cover size classes of herbs and their mid-point values

Classes Range of cover size classes Mid-point values 1. Up to 10 5 2. 11-20 15 3. 21-30 25 4. 31-40 35 5. 41-50 45 6. 51 – 60 55 7. 61 – 70 65 8. 71 – 80 75 9. 81- 90 85 10. 91 -100 95

3.2.7 Importance value index (IVI) For the calculation of importance value index of the species, relative values of density, frequency and cover were added and then divided by 3 and communities were made based on the highest values of species in each community. The formula used for the calculation of IVI is given as under: D3+ C3 + F3 Importance value index (IVI) 3 3.2.8 Density/ha and cover/ha The following formulas were used for the calculation of density/ha and cover/ha: Density of a species Density/ha (D2) 10,000 Area of quadrat No. of Quadrats

Cover of a species Cover/ha (C2) 10,000 Area of quadrat No. of Quadrats 3.2.9 Statistical analysis 3.2.9.1 Cluster analysis and ordination PC-Ord (Window Version 5.10) software was used for the data analysis. The quantitative data of trees species and understory vegetation corresponding to environmental variables and soil nutrients elements was subjected to PC-Ord software for the exposition of underlying group

structure and the major gradients that existed in the composition of vegetation (McCune & Mefford, 2005). Ward‟s cluster analysis was used for the classification while PCA and NMS were used for ordination (Gauch & Whittaker, 1981). First the IVI data of 30 trees species and a total of 20 environmental parameters and nutrients elements was subjected to cluster analysis and ordination (NMS and PCA ordination) which results to the formation of four communities at 75% remaining information in the abundance of species retained. After that, the IVI data of understory vegetation was subjected to PC-Ord for cluster analysis, PCA and NMS ordination which results to the formation of four groups of understory vegetation at 75% remaining information of the species. Then the IVI data of different groups of trees species, understory vegetation and associated soil was subjected to descriptive statistics for the calculation of mean and standard error. The soil data of the sampling sites was correlated with the score of PCA and NMS axis (Gupta et al., 2008). 3.3 Ethnomedicine and conservation In order to collect information on ethno-btanical uses of plants species, a questionnaire was prepared and information were collected from local knowledgeable peoples of the area including male, female as well from local hakeems following Badshah (2011). A total of 135 informants were interviewed for the information regarding ethnomedicinal uses of the plants found in the area. The collected plants were classified into various used categories on the basis of information on their ethno-botanical uses. The relative frequency of citation and family importance values were calculated using the following formulas: Relative frequency of citation (RFC) was calculated as per following formula: (0 ˂ RFC ˂ 1)

Where RFC stands for relative frequency of citation and its value is less than one and greater than zero, FC is the number of informants who mentioned the plant species and N is the total number of informants.

FC is frequency of citation of the family while N is the total number of informants. Conservation status of the medicinal plants was enumerated according the IUCN standard (IUCN, 2001). 3.4 Edaphology 3.4.1 Collection of soil samples Soil samples were collected from three locations from each of the six sampling sites upto a depth of 0.15 m. One-kg soil was collected from each site. The collected samples of each site were thoroughly mixed (Khan et al., 2013) to get a composite sample and packed in polythene bags, labeled properly and analysed in the laboratory. 3.4.2 Laboratory procedure The collected soil samples were taken to the laboratory of Agriculture University of Peshawar for the different physical and chemical analysis. Soil texture was determined following Bouyoucos (1936) while texture triangle was used for the determination of texture class (Brady, 1990) while soil PH was calculated by 1:5 soil water suspension (Black, 1965). Walkley (1947) was followed for the determination of organic matter in the soil while Lime % (CaCo3) was calculated by acid base neutralization following Rayan et al. (1997). For the determination of nitrogen Kjeldahl (1983) method was followed. Olsen & Sommers (1982) were followed for the determination of phosphorus in the soil while, Rhoades (1982) was followed for the potassium determination. For the determination of magnesium and calcium, Richards (1954) was followed. Similarly, the amount of sodium was determined using flame photometer method. Zn, Fe, Mn, Pb and Cu in the soil were determined following Shriadah (1999). 3.5 Palatability Palatability of plants depends upon the choice of grazing animals. It was recorded by visual observation of grazing animals (goats, sheep‟s and other animals) in the field. Information of plants palatability was also gathered from the local herdman of the area. Plants were classified based on their degree of palatability following Hussain & Durani (2009). 1. Non-Palatable (NP): Plants species not grazed by livestock. 2. Palatable: Plants species preferred by the animals for grazing. 3. Highly Palatable (HP): Highly preferred by the livestock.

4. Less Palatable (LP): Plant species which were less preferred by grazing animals. 5. Rarely Palatable (RP): Those species which were rarely grazed. 3.5.1 Phenological behavior For the determination of phenological behavior, plants were classified into following phenological classes (Table. 3.4). Table 3.4. Classes of phenological behavior of species 1. S1. Pre-reproductive/ Flowering stage 2. S2. Post-reproductive stage/Drying stage

3.6 Chemical evaluation Five plants including four palatable and one non-palatable were selected for chemical evaluation. The collected species were dried, powdered, and stored in plastic bags till chemical analysis in the laboratory. The detailed of the laboratory analysis for the species are described as under: 3.6.1 Mineral composition For determination of mineral composition, the samples were dried in a forced air oven at a temperature of 70 C for 48 hours and grounded to pass through a sieve (0.001 m) and then subjected to wet acid digestion following AOAC (1990). Sodium and potassium were determined by flame photometer (corning flame photometer 410), while P was determined by using UV/ visible Spectro Photometer (Shimadzu UV-1601PC). Ca, Mg, Fe, Mn, Zn, Cu and Pb were determined using atomic absorption spectrometer (GBC, 908AA.Victoria Australia).

RESULTS AND DISCUSSION

FLORA

Chapter 4 RESULTS AND DISCUSSION

4.1 Floristic composition The flora of Jelar valley is comprised of 250 species with 177 genera in 77 families. Among them, 41 (16.4%) were trees, 32 (12.8%) shrubs, 156 (62.4%) herbs and 21 (8.4%) were pteridophytes. The dominant families in term of species richness were Asteraceae and Lamiaceae, (20 species, 8% each), followed by Rosaceae (19 species, 7.6%), Papilionaceae (16 species, 6.4%), Poaceae, Solanaceae (each with 9 species, 3.6%) and Apiaceae (8 species, 3.2%). Dryopteridaceae, Polygonaceae had (7 species, 2.8% each). Similarly, Cucurbitaceae, Moraceae contributed 6 species (2.4% each), Chenopodiaceae, Ranunculaceae with 5 species (2.0% each), Aspleniaceae, Euphorbiaceae, Rhamnaceae and Salicaceae each had (4 species, 1.6%). The other families shared fewer numbers of species (Table. 4.1). Of the 77 genera, Polygonum and Rosa were the richest genera with 5 species each. Shah et al. (2006) reported 63 plant families with 218 species from the summer vegetation of Mastuj (Chitral), Saima et al. (2010) reported 167 species and 65 plants families from Ayubia National park (Abbottabad). Al-Yemeni & Sher (2010) reported 189 species and 74 families from Asir Mountain (Saudi Arabia) in which the leading families were Asteraceae, Lamiaceae and Poaceae. These families were also reported dominant by Khan et al. (2011) from Dara Adam Khel, Perveen et al. (2008) from Dureji. Hussain et al. (2015) reported 571 species, with 104 families from Mastuj valley and found Asteraceae, Poaceae, Papilionaceae, Rosaceae and Lamiaceae as dominant families in the locality. Ali et al. (2016) reported 463 species from Chail valley in which the richest families were Asteraceae, Rosaceae, Lamiaceae, Apiaceae and Papilionaceae. Variation in floristic list of the present area is due to the difference in habitat, climatic condition and altitude; however the dominance of the similar families may be due to a wide range of ecological amplitude of their species. Plants with simple lamina (155 species, 62%) followed by compound (63 species, 25.2%) were major adaptation. While 24 species (9.6%) had dissected lamina, (2 species, 0.8%) had needles like while (3 species, 1.2%) had spiny in nature (Table. 4.2). The lamina shapes of most of these species were also reported by Ali et al. (2016) from Chail valley (Swat) and Samreen et al. (2016) from Darazinda. Based on habitat (70 species, 21.21%) were found in dry mountain slope, (68 species, 20.61%) in wet places, (65 species, 19.70%) in forest, (44 species, 13.33%) in cultivated while (38 species, 11.52 %) were found in moist shady places. The others species were found in

agricultural fields, rock crevices and graveyards. In addition, there were found 2 introduced and one epiphytic species (Table. 4.2, Fig. 2). Ali et al. (2016) reported 37% species from dry mountain slope, 16.84% from cultivated fields, 16.63% from forest, 9.28% from waste places and 6% from wet places in Chail valley. Similar study was also conducted by Samreen et al. (2016) while exploring the vegetation of Darazinda (D. I. Khan). They found 41 species in wet places, 21 cultivated, 127 species in dry habitat and 24 species in dry and wet habitat. The present findings are in correlation with the above observations while differences are found in the abundance values of species which is due to the difference in altitude and biotic pressures (Hussain et al., 2015) and (Ali et al., 2016). 4.1.1 Seasonal variation Seasonal variation of vegetation shows that highest numbers of species (241, 33%) were found in summer followed by autumn (202, 28%) and spring (161, 22%) (Table. 4.2, Fig. 3) which showing various distribution of annual in different seasons of the year. Samreen et al. (2016) reported highest number of species in spring season in Darazinda (D. I. Khan). However, my findings are supported by Durrani et al. (2010), Badshah et al. (2013) and Ali et al. (2016) who reported highest number of species in summer. 4.1.2 Life form Life form determining the macro and microclimatic conditions of the area, (Shimwell, 1971; Raunkiaer, 1934) and its biological spectrum is useful for the comparison of geographically distant vegetation communities and indicator for existing environment of the area (Khan et al., 2014) which may be altered due to grazing and human disturbance (Cain & Castro, 1959). In the present study, therophytes (101 species, 40.4%) were dominant followed by hemicryptophytes (43 species, 17.2%) and nanophanerophyte (38 species, 15.2%) while, megaphanerophytes, chamaephytes and geophytes (16 species, 6.4%) each were next in abundance. Mesophanerophytes were less distributed life forms (Table. 4.3, Fig. 4). Al-Yemeni & Sher (2010) reported the same life form classes dominant in Asir Mountain (Saudi Arabia), Samreen et al. (2016) also reported therophytes and hemicryptophytes the dominant life form while; Sharma et al. (2014) reported therophytes and microphanerophytes were dominant. It is justified that similar biological spectra in different regions indicates similar climatic conditions and vice versa. However, in the present study the dominancy of therophytes indicate the disturbed environmental conditions in the area. It is also reported that the predominance of

therophytes is the indicator of disturb environmental condition in which phanerophytes cannot establish themselves therefore therophytes has emerged as a life form which is capable to cope with unfavorable environmental conditions. The environmental conditions of the area are greatly disturbed by biotic pressures on vegetation which increasing the number of short lived species in the area. My findings are also supported by Saxena et al. (1982), Al-Yemeni & Sher (2010), Naqinezhad & Zarezadeh (2012), Ilyas et al. (2012), Alsherif et al. (2013) and Farag (2014) that biotic pressures on vegetation greatly affect environmental conditions. The results of seasonal variation in different life form classes revealed that in spring , therophytes (40 species, 24.8%) were dominant followed by nanophanerophytes (38 species, 23.6%), megaphanerophytes (16 species, 9.9%) microphanerophytes (11 species, 6.8%) and mesophanerophytes (9 species, 5.6%) while, in summer therophytes (95 species, 39.4%) were dominant followed by hemicryptophytes (43 species, 17.8%), nanophanerophytes (38 species, 15.8%), chamaephytes, megaphanerophytes each with (16 species, 6.6%). In autumn, the maximum numbers of species (70 species, 34.7%) were therophytes followed by nanophanerophytes while hemicryptophytes and megaphanerophytes were the third and fourth dominant life form. In winter season, nanophanerophytes (38 species, 30.9%) were abundant followed by hemicryptophytes, therophytes, megaphanerophytes, microphanerophytes, mesophanerophytes and chamaephytes while geophytes were infrequent (Table. 4.3, Fig. 5). Similar study was conducted by Ali et al. (2016), in Chail valley (Swat), and reported therophytes as the dominant life form in spring, summer and nanophanerophytes during autumn and winter season. The seasonal variation in life form was also reported by Al-Yemeni & Sher (2010) from Asir Mountains (Saudi Arabia), Durrani et al. (2010) from Balochistan, Samreen et al. (2016) from Darazinda (D. I. Khan), Badshah et al. (2016) from Kuram Agency (Parachinar) and Ullah et al. (2016) from Bannu (Pakistan). 4.1.3 Leaf size spectrum The knowledge of leaf size is helpful for the understanding of physiological processes of plants and their communities (Oosting, 1956). In the present study the leaf size spectra indicated that the leading dominant leaf size class was microphylls (80 species, 32%) followed by nanophylls (75 species, 30%), mesophylls (57 species, 22.8%), leptophylls (27 species, 10.8%), macrophylls (6 species, 2.4%), megaphylls (3 species, 1.2%) while, aphyllous were represented by only 2 species (Table. 4.4, Fig. 6).

The result of seasonal variation in leaf size spectra showed a same pattern of dominancy in all seasons of the year. Microphylls were dominant followed by nanophylls, mesophyll, leptophyll and macrophyll. While the differences were found in the percentage contribution of species in different seasons as microphylls were 34% in spring, 31.5% in winter, 30% in autumn and 31% during winter (Table. 4.4, Fig. 7). Seasonal variation occurs in leaf size spectra due to annuals herbaceous species in the area as reported by different authors Ali et al. (2016), Al- Yemeni & Sher (2010). Khan et al. (2011) reported the leaf spectrum of vegetation of Dara Adam Khel and found microphyllus and mesophyllus species dominating during spring and monsoon seasons. Amjad et al. (2012) reported leptophylls and microphylls as the dominant leaf size classes from Sub-Tropical to Alpine and Subalpine vegetation of Basu hills. Malik & Hussain (1990) studied the vegetation of dry subtropical area of Kotli (Kashmir). My results are also agreed with Qadir & Tareen (1987) who reported the same leaf size with high percentage from dry temperate areas of Quetta. The percentage of different leaf size classes varied with change in altitude Saxena et al. (1985). Dolph & Dilcher (1980) reported megaphyll as a dominant leaf spectrum as the moisture increases. My results are also strongly supported by Amjad et al. (2012) who stated that the dominancy of microphylls are the characteristic features of cold, dry climates and degraded habitat. However, leaves alone could not be used for the recognition of a definite climate, but in combination with other characteristics i.e morphological and anatomical) provide more perfect results to establish a climate.

Table 4.1. Floristic composition, life form and leaf size spectrum, habitat condition and seasonal variation of vegetation in Jelar valley

Dir Upper

Seasonality

Division/ Family/ Species

S. S. No

Habitat

Life Life form

Lamina shape

Leaf size spectra

Spring

Voucher number

Winter

Autumn Summer

A. Pteridophytes 1. Adiantaceae 1. Adiantum venustum D. Don. Shariatullah Bot. 1 (PUP) Comp M-F + + + + H N 2. Adiantum incisum Forssk. Shariatullah Bot. 2 (PUP) Comp M-R + + + + H L 3. Adiantum capillus-veneris L. Shariatullah Bot. 3 (PUP) Comp M-R + + + + H N 2. Aspleniaceae 4. Asplenium adiantum-nigrum L. Shariatullah Bot. 4 (PUP) Comp M-R + + + + H N 5. Asplenium trichomanes L. Shariatullah Bot. 5 (PUP) Comp M-R + + + + H L 6. Asplenium septentrionale (L.) Hoffm. Shariatullah Bot. 6 (PUP) Comp W-R + + + H L

7. Ceterach dalhousiae (Hook.) C. Chr. Shariatullah Bot. 7 (PUP) Comp M-F + + + + H N 3. Dryopteridaceae 8. Hypodematium crenatum (Forssk.) Kuhn. Shariatullah Bot. 8 (PUP) Comp M + + + H L

9. Dryopteris serrato-dentata Hayata. Shariatullah Bot. 9 (PUP) Comp M-R + + + + H L 10. Dryopteris sieboldii (T. Moore.) Kuntze. Shariatullah Bot. 10 (PUP) Comp W + + + H L

11. Dryopteris juxtaposita Christ. Shariatullah Bot. 11 (PUP) Comp M-F + + + + H L 12. Polystichum discretum (D. Don.) J. Sm. Shariatullah Bot. 12 (PUP) Comp M-R + + + + H N 13. Polystichum wilsonii Christ. Shariatullah Bot. 13 (PUP) Comp W-R + + + + H N 14. Polystichum lonchitis (L.) Roth. Shariatullah Bot. 14 (PUP) Comp W-R + + + + H N 4. Cystopteridaceae 15. Cystopteris fragilis (L.) Bernh. Shariatullah Bot. 15 (PUP) Comp W + + + + G Mic 5. Equisetaceae 16. Equisetum ramosissimum Desf. Shariatullah Bot. 16 (PUP) Abs M + + + G Aph

17. Equisetum arvense L. Shariatullah Bot. 17 (PUP) Abs W + + + H L

6. Pteridaceae 18. Pteridium aquilinum (L.) Kuhn. Shariatullah Bot. 18 (PUP) Comp W-F + + + + G Mic 19. Pteris cretica L. Shariatullah Bot. 19 (PUP) Comp M + + + + H Mic 20. Pteris vittata L. Shariatullah Bot. 20 (PUP) Comp M-R + + + + H Mic 7. Sinooteridaceae 21. Cheilanthes pteridioides C. Chr. Shariatullah Bot. 21 (PUP) Comp W + + + + H N B. Gymnosperms 8. Pinaceae 22. Pinus roxburghii Sarg. Shariatullah Bot. 22 (PUP) N F + + + + Mesp L 23. Pinus wallichiana A.B. Jacks. Shariatullah Bot. 23 (PUP) N F + + + + Megp L C. Angiosperms 9. Acanthaceae 24. Dicliptera roxburghiana Nees. Shariatullah Bot. 24 (PUP) S CU-F + + + Ch Mic

25. Pteracanthus urticifolius (Wall. ex Kuntze) Bremek. Shariatullah Bot. 25 (PUP) S F + + Th Mic

10. Alliaceae 26. Allium sativum L. Shariatullah Bot. 26 (PUP) S CU + G Mes

27. Allium cepa L. Shariatullah Bot. 27 (PUP) S CU + G

11. Amaranthaceae 28. Amaranthus spinosus L. Shariatullah Bot. 28 (PUP) S W + Th Mic

29. Achyranthes aspera L. var. pubescens (Moq.) M. Gomez. Shariatullah Bot. 29 (PUP) S W-CU + + + Th N

30. Amaranthus caudastus L. Shariatullah Bot. 30 (PUP) S W + + Th Mic

12. Anacardiaceae Pistacia chinensis Bunge subsp. integerrima (J.L. Stewart ex Brandis.) 31. Shariatullah Bot. 31 (PUP) Comp F-GY + + + + Micp Mic Rech. f. 32. Cotinus coggygria Scop. Shariatullah Bot. 32 (PUP) S CU + + + + Np Mic 13. Apiaceae 33. Ammi visnaga (L.) Lam. Shariatullah Bot. 33 (PUP) Comp A-D + + + Ch L

34. Daucus carota L. Shariatullah Bot. 34 (PUP) Comp CU + + G Mes

35. Trachydium roylei Lindl. Shariatullah Bot. 35 (PUP) Comp W + + + H Mic

36. Chaerophyllum reflexum Aitch. Shariatullah Bot. 36 (PUP) Comp R + + + + H Mic 37. Foeniculum vulgare Mill. Shariatullah Bot. 37 (PUP) Dis CU + + Th N

38. Coriandrum sativum L. Shariatullah Bot. 38 (PUP) Dis CU + + Th L

39. Trachyspermum ammi (L.) Sprague. Shariatullah Bot. 39 (PUP) Comp D + + Th L

40. Seseli libanotis (L.) W. D. J. Koch. Shariatullah Bot. 40 (PUP) Comp M-F + + Th L

14. Araceae 41. Arisaema flavum (Forssk.) Schott. Shariatullah Bot. 41 (PUP) Comp W-F + + G Mes

42. Arisaema jacquemontii Blume. Shariatullah Bot. 42 (PUP) Comp W-F + + G Mes

15. Araliaceae 43. Hedera nepalensis K. Koch. Shariatullah Bot. 43 (PUP) S F-GY + + + + Np Mes 16. Asclepiadaceae 44. Periploca aphylla Decne. Shariatullah Bot. 44 (PUP) Abs D + + + + Np Aph 17. Asteraceae 45. Conyza bonariensis (L.) Cronquist. Shariatullah Bot. 45 (PUP) S W + + Th N

46. Phagnalon niveum Edgew. Shariatullah Bot. 46 (PUP) S W + + Ch N

47. Cirsium falconeri (Hook. f.) Petr. Shariatullah Bot. 47 (PUP) Sp D + + + H Mes

48. Gnaphalium affine D. Don. Shariatullah Bot. 48 (PUP) S F + + H Mes

49. Leontopodium leontopodinum (DC.) Hand.-Mazz. Shariatullah Bot. 49 (PUP) S W + + H N

50. Artemisia biennis Willd. Shariatullah Bot. 50 (PUP) Dis W + + + He Mic

51. Bidens cernua L. Shariatullah Bot. 51 (PUP) S W + + Th Mic

52. Bidens chinensis (L.) Willd. Shariatullah Bot. 52 (PUP) S CU + + Th Mic

53. Taraxacum campylodes G. E. Haglund. Shariatullah Bot. 53 (PUP) S D + + + Th Mic

54. Artemisia scoparia Waldst. & Kitam. Shariatullah Bot. 54 (PUP) Dis W + + Th N

55. Cosmos bipinnatus Cav. Shariatullah Bot. 55 (PUP) Comp GY + + Th N

56. Xanthium strumarium L. Shariatullah Bot. 56 (PUP) S W + + Th Mes

57. Myriactis wallichii Less. Shariatullah Bot. 57 (PUP) S F + + Th Mic

58. Sonchus asper (L.) Hill. Shariatullah Bot. 58 (PUP) Dis W + Th Mes

59. Sonchus arvensis L. Shariatullah Bot. 59 (PUP) Dis A-D + Th Mes

60. Conyza canadensis (L.) Cronquist. Shariatullah Bot. 60 (PUP) S W + + Th N

61. Tagetes minuta L. Shariatullah Bot. 61 (PUP) Dis D-F + + + Th N

62. Galinsoga parviflora Cav. Shariatullah Bot. 62 (PUP) S CU + + Th L

63. Onopordum acanthium L. Shariatullah Bot. 63 (PUP) Dis A-D + + Th Mes

64. Filago hurdwarica (Wall. ex DC.) Wagenitz. Shariatullah Bot. 64 (PUP) S F + + + Th L

18. Balsaminaceae Impatiens bicolor Royle subsp. pseudobicolor (Grey-Wilson & Rech. f.) Y. 65. Shariatullah Bot. 65 (PUP) S W + + Th Mes J. Nasir. 66. Impatiens brachycentra Kar. & Kir. Shariatullah Bot. 66 (PUP) S M + Th Mic

19. Berberidaceae 67. Berberis lycium Royle. Shariatullah Bot. 67 (PUP) Sp F + + + + Np Mic 20. Betulaceae 68. Alnus nitida (Spach.) Endl. Shariatullah Bot. 68 (PUP) S W-F + + + + Mesp Mes 20. Boraginaceae 69. Heliotropium undulatum Vahl. var. suberosa Clarke. Shariatullah Bot. 69 (PUP) S D + + G L

70. Myosotis alpestris F.W. Schmidt var. albicans (Riedl.) Y. J. Nasir. Shariatullah Bot. 70 (PUP) S F + H Mic

71. Cynoglossum lanceolatum Forssk. Shariatullah Bot. 71 (PUP) S D + + Th Mic

21. Brassicaceae 72. Brassica campestris L. Shariatullah Bot. 72 (PUP) Dis CU + + Th Mic

73. Raphanus sativus L. var. sativus Shariatullah Bot. 73 (PUP) S CU + + Th Mac

74. Nasturtium officinale R. Br. Shariatullah Bot. 74 (PUP) Comp W + + + + Th N 22. Buxaceae 75. Sarcococca saligna Muell. Arg. Shariatullah Bot. 75 (PUP) S D-F + + + + Ch Mic 23. Cannabaceae 76. Cannabis sativa L. Shariatullah Bot. 76 (PUP) S W-F + + + Th Mic

24. Caprifoliaceae 77. Lonicera asperifolia Hook. f. & Thomson. Shariatullah Bot. 77 (PUP) S D + + + + Ch N 78. Viburnum cotinifolium D. Don. Shariatullah Bot. 78 (PUP) S M + + + + Np Mic 25. Caryophyllaceae 79. Silene vulgaris (Moench.) Garcke. Shariatullah Bot. 79 (PUP) S M + + Th N

80. Cerastium fontanum Baumg. Shariatullah Bot. 80 (PUP) S M + + Th N

81. Silene conoidea L. Shariatullah Bot. 81 (PUP) S W + + Th N

26. Chenopodiaceae 82. Chenopodium album L. Shariatullah Bot. 82 (PUP) S F-A + + Th Mic

83. Spinacia oleracea L. Shariatullah Bot. 83 (PUP) S CU + + Th Mic

84. Chenopodium foliosum Asch. Shariatullah Bot. 84 (PUP) S D + + Th N

85. Chenopodium ambrosioides L. Shariatullah Bot. 85 (PUP) S W + + Th Mes

86. Dysphania botrys (L.) Mosyakin & Clemants. Shariatullah Bot. 86 (PUP) S A + + Th Mic

27. Commelinaceae 87. Commelina benghalensis L. Shariatullah Bot. 87 (PUP) S M-A + + Th Mic

28. Cucurbitaceae 88. Cucurbita pepo L. Shariatullah Bot. 88 (PUP) Dis CU + + Th Meg

89. Momordica charantia L. Shariatullah Bot. 89 (PUP) Dis CU + + Th Mes

90. Cucumis melo L. Shariatullah Bot. 90 (PUP) S CU + + Th Mac

91. Cucumis sativus L. Shariatullah Bot. 91 (PUP) Dis CU + + Th Mac

92. Cucurbita maxima Duchesne. Shariatullah Bot. 92 (PUP) Dis CU + + Th Meg

93. Luffa cylindrica (L.) M. Roem. Shariatullah Bot. 93 (PUP) Dis CU + + Th Mac

29. Cyperaceae 94. Cyperus niveus Retz. Shariatullah Bot. 94 (PUP) S W-CU + H N

95. Cyperus rotundus L. Shariatullah Bot. 95 (PUP) S W + Th N

30. Ebenaceae 96. Diospyros kaki L.f. Shariatullah Bot. 96 (PUP) S W-I + + + + Mesp Mes 97. Diospyros lotus L. Shariatullah Bot. 97 (PUP) S D-F + + + + Megp Mic 31. Elaeagnaceae 98. Elaeagnus umbellata Thunb. Shariatullah Bot. 98 (PUP) S D-F + + + + Np Mic 32. Euphorbiaceae 99. Euphorbia pilulifera L. Shariatullah Bot. 99 (PUP) S CU + + + Th L

100. Euphorbia helioscopia L. Shariatullah Bot. 100 (PUP) S A-D + + + Th N

101. Euphorbia peplus L. Shariatullah Bot. 101 (PUP) S A-D + + + Th L

102. Andrachne cordifolia (Decne.) Mull. Arg. Shariatullah Bot. 102 (PUP) S CU + + + + Np Mic 33. Fagaceae 103. Quercus incana Bartram. Shariatullah Bot. 103 (PUP) S D-F + + + + Mesp Mic 104. Quercus dilatata Royle. Shariatullah Bot. 104 (PUP) S D-F + + + + Mesp Mic 34. Gentianaceae 105. Swertia petiolata D. Don. Shariatullah Bot. 105 (PUP) S F + + Th Mic

106. Swertia ciliata (D. Don ex G. Don.) B.L. Burtt. Shariatullah Bot. 106 (PUP) S D-F + + Th Mes

35. Geraniaceae 107. Geranium wallichianum D. Don. ex Sweet. Shariatullah Bot. 107 (PUP) Dis F + + + Th Mic

108. Geranium collinum Stephan ex Willd. Shariatullah Bot. 108 (PUP) Comp F + H Mic

36. Hamamelidaceae 109. Parrotiopsis jacquemontiana (Decne.) Rehder. Shariatullah Bot. 109 (PUP) S D + + + + Np Mes 37. Hypericaceae 110. Hypericum perforatum L. Shariatullah Bot. 110 (PUP) S D + + Ch N

38. Juglandaceae 111. Juglans regia L. Shariatullah Bot. 111 (PUP) Comp D + + + + Mesp Mic 39. Lamiaceae 112. Otostegia fruticosa (Forssk.) Schweinf. ex Penzig. Shariatullah Bot. 112 (PUP) S W + Ch Mic

113. Mentha arvensis L. Shariatullah Bot. 113 (PUP) S W + + + G N

114. Thymus linearis Benth. subsp. linearis Jalas. Shariatullah Bot. 114 (PUP) S D + + H L

115. Ajuga bracteosa Wall. ex Benth. Shariatullah Bot. 115 (PUP) S D + + + H Mic

116. Isodon rugosus (Wall. ex Benth.) Codd. Shariatullah Bot. 116 (PUP) S D + + + + Np Mes 117. Rabdosia rugosa (Wall. ex Benth.) H. Hara. Shariatullah Bot. 117 (PUP) S D-F + + + + Np Mes 118. Salvia lanata Roxb. Shariatullah Bot. 118 (PUP) S D-F + + + Th Mes

119. Salvia moorcroftiana Wall. ex Benth. Shariatullah Bot. 119 (PUP) S D-F + + Th Mac

120. Salvia nubicola Wall. ex Sweet. Shariatullah Bot. 120 (PUP) S D + + + Th Mes

121. Ajuga parviflora Benth. Shariatullah Bot. 121 (PUP) S W + + + Th Mes

122. Micromeria biflora (Duch.-Ham ex D.Don.) Benth. Shariatullah Bot. 122 (PUP) S W + + + Ch L

123. Plectranthus rugosus Wall. ex Benth. Shariatullah Bot. 123 (PUP) S D + + Ch N

124. Ocimum basilicum L. Shariatullah Bot. 124 (PUP) S D + + + + Ch N 125. Origanum vulgare L. Shariatullah Bot. 125 (PUP) S M-F + + H N

126. Mentha longifolia (L.) L. Shariatullah Bot. 126 (PUP) S W + + + H N

127. Scutellaria chamaedrifolia Hedge & A.J. Paton. Shariatullah Bot. 127 (PUP) S F + + + + H N 128. Thymus serpyllum L. Shariatullah Bot. 128 (PUP) S D + + H L

129. Calamintha umbrosa (M. Bieb.) Fisch. & C.A. Mey. Shariatullah Bot. 129 (PUP) S M-F + + + Th N

130. Teucrium stocksianum Boiss. Shariatullah Bot. 130 (PUP) S D-W + Th Mic

131. Teucrium royleanum Wall. ex Benth. Shariatullah Bot. 131 (PUP) S D-W + + Th Mic

40. Loganiaceae 132. Buddleja crispa Benth. Shariatullah Bot. 132 (PUP) S A-D + + + + Np N 41. Malvaceae 133. Abelmoschus esculentus (L.) Moench. Shariatullah Bot. 133 (PUP) Sp CU + + + + Th Mes 134. Malva neglecta Wallr. Shariatullah Bot. 134 (PUP) S A + + Th Mic

42. Meliaceae 135. Melia azedarach L. Shariatullah Bot. 135 (PUP) Comp GY-W + + + + Megp Mic 43. Moraceae 136. Broussonetia papyrifera (L.) L „Her. ex Vent. Shariatullah Bot. 136 (PUP) S M + + + + Megp Mes 39

137. Ficus foveolata (Wall. ex Miq.) Miq. Shariatullah Bot. 137 (PUP) S M + + + + H Mic 138. Morus nigra L. Shariatullah Bot. 138 (PUP) S A + + + + Megp Mes 139. Morus alba L. Shariatullah Bot. 139 (PUP) S A + + + + Megp Mes 140. Ficus carica L. Shariatullah Bot. 140 (PUP) S D-F + + + + Megp Mes 141. Ficus serrata L. Shariatullah Bot. 141 (PUP) Dis D + + + + Megp Mes 44. Myrsinaceae 142. Myrsine africana L. Shariatullah Bot. 142 (PUP) S M-F + + + + Np N 45. Nyctaginaceae 143. Mirabilis jalapa L. Shariatullah Bot. 143 (PUP) S M-I + + + + Th Mes 46. Oleaceae 144. Jasminum humile L. Shariatullah Bot. 144 (PUP) Comp M-F + + + + Np Mic 145. Olea ferruginea Royle. Shariatullah Bot. 145 (PUP) S D-GY + + + + Mesp Mic 146. Jasminum officinale L. Shariatullah Bot. 146 (PUP) Comp D-F + + + + Np N 47. Onagraceae 147. Epilobium hirsutum L. Shariatullah Bot. 147 (PUP) S W + + + H N

148. Oenothera speciosa Nutt. Shariatullah Bot. 148 (PUP) S W + + Th N

48. Oxalidaceae 149. Oxalis corniculata L. Shariatullah Bot. 149 (PUP) Comp M-A + + + Th N

49. Papaveraceae 150. Papaver somniferum L. Shariatullah Bot. 150 (PUP) Dis D + + Th Mes

50. Papilionaceae 151. Phaseolus vulgaris L. Shariatullah Bot. 151 (PUP) Comp CU + Ch Mes

152. Medicago denticulata Willd. Shariatullah Bot. 152 (PUP) Comp A + + Th N

153. Astragalus affghanus Boiss. Shariatullah Bot. 153 (PUP) Comp M + + + Th N

154. Indigofera heterantha Brandis. var. gerardiana (Baker) Ali. Shariatullah Bot. 154 (PUP) Comp D-F + + + + Np L 155. Robinia pseudo-acacia L. Shariatullah Bot. 155 (PUP) S D-F + + + + Megp Mic 156. Astragalus grahamianus Benth. Shariatullah Bot. 156 (PUP) Comp M-F + + + Ch L

157. Medicago lupulina L. Shariatullah Bot. 157 (PUP) Comp M-F + + Th N

158. Medicago minima (L.) L. Shariatullah Bot. 158 (PUP) Comp A + + Th N

159. Trigonella gracilis Benth. Shariatullah Bot. 159 (PUP) Comp M-A + + Th N

160. Pisum sativum L. Shariatullah Bot. 160 (PUP) Comp CU + Th Mic

161. Lathyrus aphaca L. Shariatullah Bot. 161 (PUP) Comp A + Th Mic

162. Melilotus officinalis (L.) Pall. Shariatullah Bot. 162 (PUP) S M-F + + Th N

163. Desmodium elegans DC. Shariatullah Bot. 163 (PUP) Comp D-F + + + + Np Mic 164. Indigofera heterantha Brandis. var. heterantha. Shariatullah Bot. 164 (PUP) Comp D-F + + + + Np L 165. Lespedeza juncea (L. f.) Pers. Shariatullah Bot. 165 (PUP) Comp D + + + + Th L 166. Trifolium repens L. Shariatullah Bot. 166 (PUP) Comp F + + Th N

51. Philadelphaceae 167. Deutzia staminea R. Br. ex Wall. Shariatullah Bot. 167 (PUP) S D + + + + Micp Mic 52. Plantaginaceae 168. Plantago major L. Shariatullah Bot. 168 (PUP) S W + + Th Mes

169. Plantago lanceolata L. Shariatullah Bot. 169 (PUP) S W + + Th Mic

170. Plantago ovata Forssk. Shariatullah Bot. 170 (PUP) S W + + Th Mic

53. Platanaceae 171. Platanus orientalis L. Shariatullah Bot. 171 (PUP) Dis F + + + + Megp Mes 54. Plumbaginaceae 172. Limonium cabulicum (Boiss.) Kuntze. Shariatullah Bot. 172 (PUP) S D + + + + Np Mes 55. Poaceae 173. Oryza sativa L. Shariatullah Bot. 173 (PUP) S CU + + G Mic

174. Themeda anathera (Nees ex Steud.) Hack. Shariatullah Bot. 174 (PUP) S D + + + H N

175. Dichanthium annulatum (Forssk.) Stapf. Shariatullah Bot. 175 (PUP) S GY-A + + + H N

176. Cynodon dactylon (L.) Pers. Shariatullah Bot. 176 (PUP) S A-D + + H Mic

177. Zea mays L. Shariatullah Bot. 177 (PUP) S CU + + Th Mes

178. Triticum aestivum L. Shariatullah Bot. 178 (PUP) S CU + + Th Mic

179. Apluda mutica L. Shariatullah Bot. 179 (PUP) S A-D + H N

180. Hordeum vulgare L. Shariatullah Bot. 180 (PUP) S CU + + H Mic

181. Setaria viridis (L.) P. Beauv. Shariatullah Bot. 181 (PUP) S D + + Th N

56. Polygonaceae 182. Rumex hastatus D. Don. Shariatullah Bot. 182 (PUP) S W + + + Ch N

183. Bistorta amplexicaulis (D. Don.) Greene. Shariatullah Bot. 183 (PUP) S W-F + + + H Mes

184. Polygonum aviculare L. Shariatullah Bot. 184 (PUP) S W + + Th N

185. Polygonum posumbu Buch. -Ham. ex D. Don. Shariatullah Bot. 185 (PUP) S W + + Th N

186. Polygonum capitatum Buch.-Ham. ex D. Don. Shariatullah Bot. 186 (PUP) S W + + Th N

187. Rumex dentatus L. Shariatullah Bot. 187 (PUP) S W + + Ch Mes

188. Polygonum maculosa L. Shariatullah Bot. 188 (PUP) S W + + Th Mic

57. Primulaceae 189. Androsace rotundifolia Hardw. subsp. glandulosa (Hook. f.) Y.J. Nasir. Shariatullah Bot. 189 (PUP) S D-F + + Th Mic

58. Punicaceae 190. Punica granatum L. Shariatullah Bot. 190 (PUP) S D + + + + Micp Mic 59. Ranunculaceae 191. Clematis graveolens Lindl. Shariatullah Bot. 191 (PUP) Comp D + + + G Mic

192. Ranunculus laetus Wall. ex Hook. f. & J.W. Thomson. Shariatullah Bot. 192 (PUP) Dis W + + G N

193. Ranunculus muricatus L. Shariatullah Bot. 193 (PUP) Dis W + + G Mic

194. Delphinium ajacis L. Shariatullah Bot. 194 (PUP) Dis M + + H N

195. Ranunculus hirtellus Royle. Shariatullah Bot. 195 (PUP) Dis W + Th N

60. Rhamnaceae 196. Sageretia thea (Osbeck.) M. C. Johnst. Shariatullah Bot. 196 (PUP) S D + + + + Np N 197. Rhamnus pentapomica R. Parker. Shariatullah Bot. 197 (PUP) S D-F + + + + Micp N 198. Ziziphus sativa Gaertn. Shariatullah Bot. 198 (PUP) S D-F + + + + Megp N 199. Ziziphus oxyphylla Edgew. Shariatullah Bot. 199 (PUP) S D + + + + Np N 61. Rosaceae 200. Prunus persica (L.) Batsch. Shariatullah Bot. 200 (PUP) S CU + + + + Micp Mes 201. Prunus domestica L. Shariatullah Bot. 201 (PUP) S CU + + + + Micp Mes 202. Prunus armeniaca L. Shariatullah Bot. 202 (PUP) S Cu + + + + Micp Mes 203. Pyrus pyrifolia (Burm. f.) Nakai. Shariatullah Bot. 203 (PUP) S CU + + + + Micp Mes 204. Pyrus communis L. Shariatullah Bot. 204 (PUP) S CU + + + + MegP Mac 205. Rosa moschata Herrm. Shariatullah Bot. 205 (PUP) Comp CU + + + + Np Mic 206. Spiraea canescens D. Don. Shariatullah Bot. 206 (PUP) S F + + + + Np Mic 207. Rosa webbiana Wall. ex Royle. Shariatullah Bot. 207 (PUP) Comp F + + + + Np N 208. Rosa alba L. Shariatullah Bot. 208 (PUP) Comp CU + + + + Np N 209. Rubus ulmifolius Schott. Shariatullah Bot. 209 (PUP) Comp W + + + + Np Mes 210. Rubus ellipticuss Sm. Shariatullah Bot. 210 (PUP) Comp W-F + + + + Np N 211. Duchesnea indica (Jacks.) Focke. Shariatullah Bot. 211 (PUP) Comp W + + + + Th Mic 42

212. Rosa brunonii Lindl. Shariatullah Bot. 212 (PUP) Comp F + + + + Np N 213. Pyrus malus L. Shariatullah Bot. 213 (PUP) S M-A + + + + Micp Mes 214. Pyrus pashia Buch. -Ham. ex D. Don. Shariatullah Bot. 214 (PUP) S CU + + + + Micp Mes 215. Sorbaria tomentosa (Lindl.) Rehder. Shariatullah Bot. 215 (PUP) Comp W + + + + Np Mic 216. Cotoneaster nummularia Fisch. & Mey. Shariatullah Bot. 216 (PUP) S F + + + + Np N 217. Rosa canina L. Shariatullah Bot. 217 (PUP) Comp M-F + + + + Np N 218. Poterium sanguisorba L. Shariatullah Bot. 218 (PUP) Dis W + + + Th N

62. Rubiaceae 219. Galium stewartii Nazim. Shariatullah Bot. 219 (PUP) S M-R + + + Th L

63. Rutaceae 220. Zanthoxylum armatum DC. Shariatullah Bot. 220 (PUP) Comp CU + + + + Np Mic 221. Citrus sinensis (L.) Osbeck. Shariatullah Bot. 221 (PUP) S CU + + + + Np Mes 64. Salicaceae 222. Populus alba L. Shariatullah Bot. 222 (PUP) S W + + + + Mesp Mes 223. Salix tetrasperma Roxb. Shariatullah Bot. 223 (PUP) S W + + + + Micp Mic 224. Salix alba L. Shariatullah Bot. 224 (PUP) S W + + + + Megp Mic 225. Populus nigra L. Shariatullah Bot. 225 (PUP) S W + + + + Megp Mic 65. Sapindaceae 226. Dodonaea viscosa (L.) Jacq. Shariatullah Bot. 226 (PUP) S D + + + + Np N 66. Saxifragaceae 227. Bergenia ciliata (Haw.) Sternb. Shariatullah Bot. 227 (PUP) S W + + + G Mes

67. Scrophulariaceae 228. Scrophularia umbrosa Dumort. Shariatullah Bot. 228 (PUP) S D + + Ch N

229. Verbascum thapsus L. Shariatullah Bot. 229 (PUP) S W + + Th Meg

230. Scrophularia nodosa L. Shariatullah Bot. 230 (PUP) S D + Th N

68. Simaroubaceae 231. Ailanthus altissima (Mill.) Swingle. Shariatullah Bot. 231 (PUP) Comp A-I + + + + Megp Mic 69. Smilacaceae 232. Smilax glaucophylla Klotzsch. Shariatullah Bot. 232 (PUP) S EPI + + + + Np Mes 70. Solanaceae 233. Solanum tuberosum L. Shariatullah Bot. 233 (PUP) Comp CU + G Mes

234. Capsicum frutescens L. Shariatullah Bot. 234 (PUP) S CU + + + + Np Mes 235. Datura innoxia Mill. Shariatullah Bot. 235 (PUP) S D + + Th Mes

236. Hyoscyamus niger L. Shariatullah Bot. 236 (PUP) S F + Th Mes

237. Solanum nigrum L. var. villosum L. Shariatullah Bot. 237 (PUP) S D-W + + Th Mes

238. Lycopersicon esculentum Mill. Shariatullah Bot. 238 (PUP) S CU + + + + Th Mic 239. Capsicum annuum L. Shariatullah Bot. 239 (PUP) S CU + + Th Mic

240. Solanum nigrum L. var. nigrum. Shariatullah Bot. 240 (PUP) S D-W + Th Mic

241. Datura stramonium L. Shariatullah Bot. 241 (PUP) S D-F + + + Ch Mes

71. Thymelaeaceae 242. Daphne mucronata Royle. Shariatullah Bot. 242 (PUP) S D-F + + + + Np N 243. Wikstroemia canescens Wall. ex Meisn. Shariatullah Bot. 243 (PUP) S F + + + + Np N 72. Ulmaceae 244. Celtis caucasica Willd. Shariatullah Bot. 244 (PUP) S GY + + + + Megp Mic 245. Celtis australis L. Shariatullah Bot. 245 (PUP) S D + + + + Mesp Mic 73. Urticaceae 246. Urtica dioica L. Shariatullah Bot. 246 (PUP) S D + + + Th Mic

247. Girardinia palmata (Forssk.) Gaudich. Shariatullah Bot. 247 (PUP) Dis D + + + Th N

74. Valerianaceae 248. Valeriana wallichii DC. Shariatullah Bot. 248 (PUP) S M-F + + + Th Mic

75. Violaceae 249. Viola canescens Wall. Shariatullah Bot. 249 (PUP) S M-R + + H Mic

76. Vitaceae 250. Vitis vinifera L. Shariatullah Bot. 250 (PUP) S CU + + + Np Mes

Key: Life form: H= Hemicryptophyte, Th= Therophyte, Np= Nanophenarophytes, Ch= Chamaephyte, Mesp= Mesophanerophyte, Megp= Megaphanerophytes, Micp= Microphanerophyte, G= Geophytes. Leaf form: N= Nanophyll, L= Leptophyll, Aph= Aphyllous, Mic= Microphyll, Mes= Mesophyll, Meg= Megaphyll, Mac= Macrophyll. Lamina shape: S= Simple, Comp= Compound, Abs= Absent, N= Needle, Dis= Dissected, Sp= Spiny. Habitat: A= Agricultural fields, W= Wet places, F= Forest, M= Moist shady places, I= Introduced, CU= Cultivated, R= Rock crevices, GY= Graveyards, WP= Waste places, EPI= Epiphyte

Table 4.2. Ecological characteristics of vegetation

S.No Characteristics 1. Vegetation Number %age i. Families 77 - ii. Genera 177 - iii. Species 250 - 2. Habitat type No. of species %age of species i. Dry mountain slope 70 21.21 ii. Wet places 68 20.61 iii. Forest 65 19.70 iv. Cultivated 44 13.33 v. Moist shady places 38 11.52 vi. Agricultural fields 22 6.67 vii. Rock crevices 13 3.94 viii. Graveyards 7 2.12 ix. Introduced 2 0.61 x. Epiphyte 1 0.30 3. Seasonality No. of species %age of species i. Spring 161 22 ii. Summer 241 33 iii. Autumn 202 28 iv. Winter 123 17 4. Life form classes No. of species %age of species i. Therophytes 101 40.4 ii. Hemicryptophytes 43 17.2 iii. Nanophanerophytes 38 15.2 iv. Megaphanerophytes 16 6.4 v. Chamaephytes 16 6.4 vi. Geophytes 16 6.4 vii. Microphanerophytes 11 4.4 viii. Mesophanerophytes 9 3.6 5. Leaf size spectra No. of species %age of species i. Microphyll 80 32.0 ii. Nanophyll 75 30.0 iii. Mesophyll 57 22.8 iv. Leptophyll 27 10.8

v. Macrophyll 6 2.4 vi. Aphyllous 2 0.8 vii. Megaphyll 3 1.2 6. Lamina shape No. of species %age of species i. Simple 155.0 62.00 ii. Compound 63.0 25.20 iii. Dissected 24.0 9.60 iv. Needles 2.0 0.80 v. Absent 3 1.20 vi. Spiny 3 1.20

Table 4.3. Seasonal variation of life form spectrum

S.No Life form classes Spring Summer Autumn Winter No. %age No. %age No. %age No. %age i. Therophytes 40 24.8 95 39.4 70 34.7 17 13.8 ii. Hemicryptophytes 29 18.0 43 17.8 37 18.3 20 16.3 iii. Nanophanerophytes 38 23.6 38 15.8 38 18.8 38 30.9 iv. Chamaephytes 7 4.3 16 6.6 12 5.9 8 6.5 v. Geophytes 11 6.8 13 5.4 9 4.5 4 3.3 vi. Megaphanerophytes 16 9.9 16 6.6 16 7.9 16 13.0 vii. Microphanerophytes 11 6.8 11 4.6 11 5.4 11 8.9 viii. Mesophanerophytes 9 5.6 9 3.7 9 4.5 9 7.3 Total 161 100 241 100 202 100 123 100

Table 4.4. Seasonal variation of leaf size spectrum

Spring Summer Autumn Winter Leaf size spectrum No. %age No. %age No. %age No. %age S.No Leaf type Spring % Summer % Autumn % Winter % i. Microphyll 56 34.8 76 31.5 62 30.7 39 31.7 ii. Nanophyll 48 29.8 76 31.5 61 30.2 34 27.6 iii. Mesophyll 33 20.5 53 22.0 47 23.3 35 28.5 iv. Leptophyll 18 11.2 26 10.8 24 11.9 12 9.8 v. Macrophyll 3 1.9 5 2.1 4 2.0 2 1.6 vi. Aphyllous 2 1.2 2 0.8 2 1.0 1 0.8 vii. Megaphyll 1 0.6 3 1.2 2 1.0 0 0 Total 161 100 241 100 202 100 123 100

Fig. 2. Percentage of species based on their habitat

Fig. 3. Percentage no. of species in different seasons

%of Species

Fig. 4. Life form spectra of vegetation of Jelar valley

%of Species

Fig. 5. Seasonal variation in life form of vegetation

%of Species

Fig. 6. Leaf size spectra of vegetation of Jelar valley

%of Species

Fig. 7. Seasonal variation in leaf spectra of vegetation

VEGETATION PATTERN

4.2a Quantitative analysis of vegetation /Phytosociology 4.2.1a Classification of trees species through Ward’s cluster analysis Phytosociological studies can be an essential tool to distinguish temporal changes in vegetation in reaction to global climate change (Felde et al., 2012). In the present study the IVI of 30 trees species were subjected to Pc-Ord software (Version 5.2) for cluster analysis. The data was separated into four vegetation groups at 75% remaining information of the species individuals. (Fig. 8) represent cluster dendrogram of trees species while the two-ways cluster dendrogram represents the stand as well as the presence and absence of species in different communities (Fig. 9). The communities were made based on IVI of the dominant species. Details of communities obtained through Ward‟s cluster analysis are summarized below. Group 1. Ailanthus altissima-Quercus incana community This community is distributed in Gumbad and Gul Dherai at 1967±130 (Mean± SE) m altitude with 20.1±2.3 slope angle. A total of 27 trees species were found in this community. This community is more diverse as compared to other community. Based on IVI, the dominant species of this community was Ailanthus altissima with 9.70% IVI, 100 individuals/ha and 465.6 cm2 mean basal area/ha followed by Quercus incana (8.49±1.99% IVI, 60±32 trees/ha, 1636.3±2 cm2 basal area/ha), Pinus wallichiana (IVI. 8.14±2.30, density/ha,70±42, basal area/ha 1360.4 ±357.5 cm2), Quercus dilatata (6.77±3.22% IVI, density/ha 22, basal area 1128.3 cm2/ha), Juglans regia (IVI. 5.26±2.68, 18 density/ha, 1436.3 cm2/ha basal area), Pinus roxburghii (5.24±5.24 IVI, density/ha 66, 443 cm2 /ha basal area), Prunus armeniaca (5.00±1.28 IVI, density/ha 12, basal area 2198 cm2/ha). Quercus incana was also reported by Ali (2016) as a co- dominant species with Abies pindrow from Chail valley (Swat) while, Ilyas et al. (2015) reported Quercus incana as a co-dominant species with Pinus wallichiana from Kabal valley. Some of the other species of this community with different IVI mean values were also reported by Khan et al. (2016). Similarly, Ahmed et al. (2011) and Siddiqui et al. (2011) while working on the vegetation of Himalayan moist temperate and Hindukush ranges reported Pinus wallichiana with 56-81% IVI. Among the recorded species of this community Khan et al. (2015) reported the composition, structure and regeneration status of Olea ferruginea from Hindukush range of Pakistan while, the quantitative data of Quercus baloot is reported by Khan et al. (2010) from Chitral. So, my results are agreed with the above authors. Morus alba, Diospyros kaki, Populus nigra, Pyrus pashia, Ficus carica, Olea ferruginea and Prunus persica are other species of this

community their IVI mean values ranged from 4.96 to 3.38%. Among the remaining thirteen species of this community Celtis australis shared 2.59% IVI, 2 trees/ha and 1780 cm2/ha basal area, Salix alba (2.54% IVI, density/h 4, 1650 cm2/ha basal area), Platanus orientalis (2.28% IVI, density/ha 4, 1415 cm2/ha cover, Punica granatum 2.22% IVI with 4 trees/ha and 1240 cm2/ha basal area. Alnus nitida, Pyrus pyrifolia and Morus nigra shared 1.87% IVI with 6 to 2 tress/ha and 860 to 120 cm2 /ha basal area respectively. Pyrus malus, Citrus sinensis, Melia azedarach, Prunus domestica, Vitis vinifera and Pistacia chinensis are the low contributed species in term of IVI, density/ha and basal area/ha (Table. 4.5, 4.6, 4.7). Most of the wild species of this community contributed less IVI, these species required proper care otherwise they will be loss in the future. Soil is the main factor which determined the characteristics of vegetation species in aparticular area (Khan et al., 2010). The physiochemical properties of the soil revealed that the soil associated with community I, contain 2.4% clay particle which is lower than community IV, but higher than the soil of community II. Silt particles (42%) were found similar to community III but higher than the other communities. The quantities of sand particles (55.6%) were also similar to community III but lower than the other communities. The results also revealed that like other communities, the soil of this community was loamy sand (coarse), acidic in nature with a pH value 5.9. The lime content showed that the soil was slightly calcareous, organic matter (1.656%) were high, nitrogen contents low, phosphorus medium, while potassium was found in adequate amount. Similarly, Mg (2.4545 mg/kg) was also found high as compared to the soil of other communities while Na (19.45 mg/kg) was higher than the soil of communities II and IV. Among the other nutrient elements found in the soil of this community the mean value of Cu (mg/kg) was 0.5915, Zn (mg/kg) 0.5915, Fe (mg/kg) 1.0165, Mn (mg/kg) 3.4765, Pb (mg/kg) 1.0765 and Ca (mg/kg) was 9.696 (Table. 4.8). Group II. Pinus wallichiana-Quercus incana community This community is situated in Sore Pao at low altitude (1808 m) as compared to other communities while slope angle was similar to community group I. Fourteen trees species were found in this community in which the leading dominant species was Pinus wallichiana with 18.91% means IVI, 168 density/ha and 1728.1 cm2 basal area/ha. Similar to community I, the co- dominant species of this community was also Quercus incana with 13.54% average importance value. The density/ha and basal area/ha of this species was recorded 92 and 1698.3 cm2 respectively. Similar study was conducted by Wahab et al. (2010) and reported Picea smithiana-

Pinus wallichiana community on 2645 m altitude from Danair valley (Dir.). Pinus wallichiana was also reported previously in the form of pure communities as well as in association with other trees species in different areas at different altitudinal gradient which indicating the wide ecological amplitude of this species (Ahmed et al., 2010; Wahab et al., 2010; Khan et al., 2013; Akbar, 2013). However, my results are strongly supported by Ilyas et al. (2015) who reported Pinus wallichiana-Quercus incana community from Kabal valley. They also reported the presence of some of the other species of this community with different IVI mean values. The presence of similar communities in different areas may be the reason of same climatic conditions. Among the remaining species of this community the IVI of Diospyros kaki was 9.25%, density/ha 80 and basal area 566 cm2/ha, Juglans regia was represented with 8.87% IVI, 32 density/ha and 1457.5 cm2 basal area/ha. Among the other species, Quercus dilatata shared 8.45% IVI, 28 density/ha and 1382 cm2 basal area/ha, Populus nigra 6.58% IVI, 20 density/ha and 1386 cm2 basal area/ha, Ailanthus altissima 6.52 % IVI, 20 density/ha, 1336 cm2 basal area/ha. Other less contributing species found in association with this community were Robinia pseudo-acacia (5.84%), Olea ferruginea (5.54%), Prunus persica (4.23%), Sorbaria tomentosa (4.05%), Salix alba (3.78%), Morus alba (2.38%) and Punica granatum (2.06%). Their mean values of density/ha and basal area/ha are represented in (Table. 4.6, 4.7). The results of edaphic variables associated with this community showed that clay (0.4%) and silt (34%) contents were low while, sand (55.6%) particles were high as compared to other communities. Similar to community I, the soil associated with this community was loamy sand, acidic in nature (pH 6.2), slightly calcareous, phosphorus medium, potassium adequate while, organic matter and nitrogen were found low in the soil. Among the other nutrient elements, the amount of calcium (9.126 mg/kg) was lower than the soil of other communities, magnesium and sodium (mg/kg) was found higher only than community IV. Cu (0.327 mg/kg), Fe (1.33 mg/kg) and Pb (1.88 mg/kg) contents were found high, Zn (0.288 mg/kg) and Mn was found 2.177 (mg/kg) in the soil associated with community II. Group III. Pinus wallichiana-Prunus armeniaca community This community was found in Shao at 2058.6 m mean altitude with 15.6 slope angle. This community is less diverse in term of number of species (10 trees species). This community was also dominated by Pinus wallichiana while the co-dominant species was Prunus armeniaca. The IVI mean values of these species were 37.52%, 10.16%, density/ha 232, 4 and basal area/ha was

recorded as 1651.7 cm2 and 3340 cm2 respectively. Similar study was conducted by Akbar (2013) while working on the vegetation of Northern areas of Pakistan and reported five plants communities. He reported Pinus wallichiana as a dominant species with Betula utilis, Pinus gerardiana as well as in the form of pure stand. Pinus wallichiana communities were also reported by Chaghtai et al. (1989) from Nathia Gali at 2133 m altitude, Ahmed et al. (2006) from Himalayan forest of Pakistan, Chaudhri (1960), Hussain & Illahi (1991) also reported this species from different areas of Pakistan which indicating the wide ecological amplitude due to which they survive in different climatic zones in the form of monospecic stand as well as in association with other species. Khan et al. (2012) reported Pinus wallichiana as a dominant species in dry temperate area of Chitral. The second leading dominant species (Prunus armeniaca) of this community is a fruit yielding cultivated species as the inhabitants of the area degraded the natural forests for the plantation of edible plants due to which the species has become dominant in the area. Ailanthus altissima was present with 8.15% IVI, 28 trees/ha, and 577 cm2 basal area/ha, Juglans regia with I8.01% IVI, 8 trees/ha and 1400 cm2 basal area/ha while the remaining less contributing species of this community were Salix alba (IVI. 7.16%), Pyrus pashia (IVI. 6.85%), Morus nigra (IVI. 6.8%), Diospyros kaki (IVI. 6.68%), Robinia pseudo-acacia (IVI. 5. 23%) and Morus alba (IVI. 3.44%). The density and basal area/ha mean values of these species are presented in (Table. 4.6, 4.7). Mostly the species of this community are cultivated which indicating the past degradation of natural forests therefore most of the area was brought under cultivation. The physiochemical properties of the soil associated with this community revealed that clay particles were (2.4%), silt (42%) and sand (55.6%). Like other community the soil was loamy sand, and acidic in nature while organic matter were high. Lime contents shows that the soil of this community was slightly calcareous. Similarly, nitrogen was found in adequate amount, potassium medium phosphorus low while, Na was found 19.6 mg/kg. Among the other soil nutrients found in the soil associated with community the amount of Cu was found (0.245) mg/kg, Zn (0.138) mg/kg, Fe (0.879) mg/kg, Mn (1.885) mg/kg, Pb (1.13) mg/kg, Ca (9.948) mg/kg and Mg (2.372) mg/kg. My results are an agreement with Chaghtai et al. (1983), Khan (2011), Akbar (2013), Khan et al. (2013), Siddiqui (2011) and Shah et al. (2013) who also reported the impact of topographic, edaphic factors and soil nutrients on the distribution of vegetation communities.

Group IV. Pinus wallichiana-Ailanthus altissima community Pinus wallichiana and Ailanthus altissima community was recorded in two stands namely Tangi Awar and Danda which are situated at 2070.8 m altitude with 12.7 slope angle. This community was found the second diverse community in term of trees species. Seventeen trees species were recorded in this community in which the IVI of the dominant species Pinus wallichiana was (24.76%), density/ha 138 and basal area/ha 1626 cm2 followed by Ailanthus altissima (10.56% IVI, 42 density/ha, 1206.3 cm2 basal area/ha), Juglans regia (8.92%) IVI, 20 density/ha, 1738.3 cm2 basal area), Morus alba (8.63% IVI, 8 density/ha, 2990 cm2 basal area), Ficus carica (7.46% IVI, 16 density/ha, 1177 cm2 basal area), Prunus armeniaca (7.24% IVI, 10 density/ha, 1988 cm2basal area) and Pyrus pashia (6.68% IVI, 6 density/ha, 2510 cm2 basal area/ha). Other low contributing trees species found in this community are Prunus domestica, Salix alba, Quercus dilatata, Pistacia chinensis, Populus nigra, Prunus persica, Ziziphus oxyphylla, Vitis vinifera, Diospyros kaki and Platanus orientalis (Table. 4.5, 4.6, 4.7). Similar study was conducted by Akbar (2013) and recorded Piuns wallichiana as a dominant species in 14 sampled stands and argued the wide spread distribution of this species as reported by others (Ahmed, 1988; Wahab et al., 2008; Wahab, 2011). Some of the species found in this community were also reported by Khan (2012) in Quercus baloot dominated communities in Dir. The physiochemical properties of the soil of this community show that clay (2.3%) contents were lower than the soil of group III, while higher than the soil of group I and II. Silt was found (38%). Sand particles were found higher than the soil associated with other communities. The soil texture shows that the soil was loamy sand and acidic in nature as the soil of other communities. The soil was slightly calcareous with high organic matter; phosphorus contents were medium while potassium was found in adequate amount. Among the other soil nutrients, the quantity of Cu was found (0.2775) mg/kg, Zn (0.573) mg/kg, Fe (1.305) mg/kg, Mn (6.179) mg/kg, Pb (1.1) mg/kg, Ca (9.8905) mg/kg, Mg (2.2835) mg/kg while Na was found (16.9) mg/kg.

Table 4.5. IVI means values of trees species in different communities results from Wards cluster analysis

S.No Species Voucher number Group I Group II Group III Group IV Mean ± SE Mean ± SE Mean ± SE Mean ± SE 1. Salix alba L. Shariatullah Bot. 224 (PUP) 2.54 ± 2.54 3.78 ± 0 7.16 ± 0 3.33 ± 3.33 2. Juglans regia L. Shariatullah Bot. 111 (PUP) 5.26 ± 2.68 8.87 ± 0 8.01 ± 0 8.92 ± 0.65 3. Platanus orientalis L. Shariatullah Bot. 171 (PUP) 2.28 ± 2.28 0.00 ± 0 0.00 ± 0 1.17 ± 1.17 4. Alnus nitida (Spach.) Endl. Shariatullah Bot. 68 (PUP) 1.87 ± 1.87 0.00 ± 0 0.00 ± 0 0.00 ± 0.00 5. Ficus carica L. Shariatullah Bot. 140 (PUP) 3.90 ± 0.06 0.00 ± 0 0.00 ± 0 7.46 ± 0.01 6. Ailanthus altissima (Mill.) Swingle. Shariatullah Bot. 231 (PUP) 9.70 ± 1.01 6.52 ± 0 8.15 ± 0 10.56 ± 0.00 7. Diospyros kaki L. f. Shariatullah Bot. 96 (PUP) 4.59 ± 1.75 9.25 ± 0 6.68 ± 0 1.19 ± 1.19 8. Quercus incana Bartram. Shariatullah Bot. 103 (PUP) 8.49 ± 1.99 13.54 ± 0 0.00 ± 0 0.00 ± 0.00 9. Pinus roxburghii Sarg. Shariatullah Bot. 22 (PUP) 5.24 ± 5.24 0.00 ± 0 0.00 ± 0 0.00 ± 0.00 10. Pinus wallichiana A. B. Jacks. Shariatullah Bot. 23 (PUP) 8.14 ± 2.30 18.91 ± 0 37.52 ± 0 24.76 ± 4.31 11. Populus nigra L. Shariatullah Bot. 225 (PUP) 4.21 ± 0.93 6.58 ± 0 0.00 ± 0 2.47 ± 2.47 12. Pyrus pashia Buch. -Ham. ex D. Don. Shariatullah Bot. 214 (PUP) 3.92 ± 0.46 0.00 ± 0 6.85 ± 0 6.68 ± 0.01 13. Citrus sinensis (L.) Osbeck. Shariatullah Bot. 221 (PUP) 1.42 ± 1.42 0.00 ± 0 0.00 ± 0 0.00 ± 0.00 14. Prunus persica (L.) Batsch. Shariatullah Bot. 200 (PUP) 3.38 ± 0.59 4.23 ± 0 0.00 ± 0 2.32 ± 2.32 15. Quercus dilatata Royle. Shariatullah Bot. 104 (PUP) 6.77 ± 3.22 8.45 ± 0 0.00 ± 0 3.19 ± 3.19 16. Pistacia chinensis Bunge subsp. integerrima Shariatullah Bot. 31 (PUP) 0.76 ± 0.76 0.00 ± 0 0.00 ± 0 2.99 ± 2.99 (J. L. Stewart ex Brandis.) Rech. f. 17. Vitis vinifera L. Shariatullah Bot. 250 (PUP) 1.03 ± 1.03 0.00 ± 0 0.00 ± 0 1.98 ± 1.98 18. Olea ferruginea Royle. Shariatullah Bot. 145 (PUP) 3.75 ± 0.92 5.54 ± 0 0.00 ± 0 0.00 ± 0.00 19. Prunus armeniaca L. Shariatullah Bot. 202 (PUP) 5.00 ± 1.28 0.00 ± 0 10.16 ± 0 7.24 ± 0.84 20. Morus alba L. Shariatullah Bot. 139 (PUP) 4.96 ± 0.63 2.38 ± 0 3.44 ± 0 8.63 ± 0.40 21. Punica granatum L. Shariatullah Bot. 190 (PUP) 2.22 ± 2.22 2.06 ± 0 0.00 ± 0 0.00 ± 0.00 22. Robinia pseudo-acacia L. Shariatullah Bot. 155 (PUP) 0.00 ± 0.00 5.84 ± 0 5.23 ± 0 0.00 ± 0.00 23. Sorbaria tomentosa (Lindl.) Rehder. Shariatullah Bot. 215 (PUP) 0.00 ± 0.00 4.05 ± 0 0.00 ± 0 0.00 ± 0.00 24. Pyrus pyrifolia (Burm.f.) Nakai. Shariatullah Bot. 203 (PUP) 1.87 ± 1.87 0.00 ± 0 0.00 ± 0 0.00 ± 0.00 25. Celtis australis L. Shariatullah Bot. 245 (PUP) 2.59 ± 2.59 0.00 ± 0 0.00 ± 0 0.00 ± 0.00 26. Melia azedarach L. Shariatullah Bot. 135 (PUP) 1.40 ± 1.40 0.00 ± 0 0.00 ± 0 0.00 ± 0.00 27. Morus nigra L. Shariatullah Bot. 138 (PUP) 1.87 ± 1.87 0.00 ± 0 6.80 ± 0 0.00 ± 0.00 28. Pyrus malus L. Shariatullah Bot. 213 (PUP) 1.62 ± 1.62 0.00 ± 0 0.00 ± 0 0.00 ± 0.00 29. Prunus domestica L. Shariatullah Bot. 201 (PUP) 1.23 ± 1.23 0.00 ± 0 0.00 ± 0 4.93 ± 0.67 30. Ziziphus oxyphylla Edgew. Shariatullah Bot. 199 (PUP) 0.00 ± 0.00 0.00 ± 0 0.00 ± 0 2.19 ± 2.19

Table 4.6. Density/ha of trees species in different communities obtained through cluster analysis

S.No Species Voucher number Group I Group II Group III Group IV Mean ± SE Mean ± SE Mean ± SE Mean ± SE 1. Salix alba L. Shariatullah Bot. 224 (PUP) 4 ± 4 4 ± 0 12 ± 0 2 ± 2 2. Juglans regia L. Shariatullah Bot. 111 (PUP) 18 ± 14 32 ± 0 8 ± 0 20 ± 4 3. Platanus orientalis L. Shariatullah Bot. 171 (PUP) 4 ± 4 0 ± 0 0 ± 0 2 ± 2 4. Alnus nitida (Spach.) Endl. Shariatullah Bot. 68 (PUP) 6 ± 6 0 ± 0 0 ± 0 0 ± 0 5. Ficus carica L. Shariatullah Bot. 140 (PUP) 18 ± 2 0 ± 0 0 ± 0 16 ± 0 6. Ailanthus altissima (Mill.) Swingle. Shariatullah Bot. 231 (PUP) 100 ± 48 20 ± 0 28 ± 0 42 ± 10 7. Diospyros kaki L. f. Shariatullah Bot. 96 (PUP) 44 ± 32 80 ± 0 12 ± 0 2 ± 2 8. Quercus incana Bartram. Shariatullah Bot. 103 (PUP) 60 ± 32 92 ± 0 0 ± 0 0 ± 0 9. Pinus roxburghii Sarg. Shariatullah Bot. 22 (PUP) 66 ± 66 0 ± 0 0 ± 0 0 ± 0 10. Pinus wallichiana A. B. Jacks. Shariatullah Bot. 23 (PUP) 70 ± 42 168 ± 0 232 ± 0 138 ± 14 11. Populus nigra L. Shariatullah Bot. 225 (PUP) 18 ± 2 20 ± 0 0 ± 0 14 ± 14 12. Pyrus pashia Buch. -Ham. ex D. Don. Shariatullah Bot. 214 (PUP) 10 ± 6 0 ± 0 4 ± 0 6 ± 2 13. Citrus sinensis (L.) Osbeck. Shariatullah Bot. 221 (PUP) 10 ± 10 0 ± 0 0 ± 0 0 ± 0 14. Prunus persica (L.) Batsch. Shariatullah Bot. 200 (PUP) 12 ± 0 8 ± 0 0 ± 0 2 ± 2 15. Quercus dilatata Royle. Shariatullah Bot. 104 (PUP) 22 ± 14 28 ± 0 0 ± 0 10 ± 10 16. Pistacia chinensis Bunge subsp. Shariatullah Bot. 31 (PUP) 2 ± 2 0 ± 0 0 ± 0 2 ± 2 integerrima (J. L. Stewart ex Brandis.) Rech. f. 17. Vitis vinifera L. Shariatullah Bot. 250 (PUP) 2 ± 2 0 ± 0 0 ± 0 2 ± 2 18. Olea ferruginea Royle. Shariatullah Bot. 145 (PUP) 14 ± 2 4 ± 0 0 ± 0 0 ± 0 19. Prunus armeniaca L. Shariatullah Bot. 202 (PUP) 12 ± 8 0 ± 0 4 ± 0 10 ± 2 20. Morus alba L. Shariatullah Bot. 139 (PUP) 10 ± 2 8 ± 0 4 ± 0 8 ± 0 21. Punica granatum L. Shariatullah Bot. 190 (PUP) 4 ± 4 4 ± 0 0 ± 0 0 ± 0 22. Robinia pseudo-acacia L. Shariatullah Bot. 155 (PUP) 0 ± 0 4 ± 0 16 ± 0 0 ± 0 23. Sorbaria tomentosa (Lindl.) Rehder. Shariatullah Bot. 215 (PUP) 0 ± 0 4 ± 0 0 ± 0 0 ± 0 24. Pyrus pyrifolia (Burm.f.) Nakai. Shariatullah Bot. 203 (PUP) 2 ± 2 0 ± 0 0 ± 0 0 ± 0 25. Celtis australis L. Shariatullah Bot. 245 (PUP) 2 ± 2 0 ± 0 0 ± 0 0 ± 0 26. Melia azedarach L. Shariatullah Bot. 135 (PUP) 2 ± 2 0 ± 0 0 ± 0 0 ± 0 27. Morus nigra L. Shariatullah Bot. 138 (PUP) 2 ± 2 0 ± 0 4 ± 0 0 ± 0 28. Pyrus malus L. Shariatullah Bot. 213 (PUP) 2 ± 2 0 ± 0 0 ± 0 0 ± 0 29. Prunus domestica L. Shariatullah Bot. 201 (PUP) 4 ± 4 0 ± 0 0 ± 0 6 ± 2 30. Ziziphus oxyphylla Edgew. Shariatullah Bot. 199 (PUP) 0 ± 0 0 ± 0 0 ± 0 2 ± 2

Table 4.7. Basal area/ha of trees species in different communities obtained through cluster analysis

S.No Species Voucher number Group I Group II Group III Group IV Mean ± SE Mean ± SE Mean ± SE Mean ± SE 1. Salix alba L. Shariatullah Bot. 224 (PUP) 1650.0 ± 1650.0 1160.0 ± 0 1700.0 ± 0 1100.0 ± 1100.0 2. Juglans regia L. Shariatullah Bot. 111 (PUP) 1436.3 ± 236.3 1457.5 ± 0 1400.0 ± 0 1738.3 ± 61.7 3. Platanus orientalis L. Shariatullah Bot. 171 (PUP) 1415.0 ± 1415.0 0.0 ± 0 0.0 ± 0 110.0 ± 110.0 4. Alnus nitida (Spach.) Endl. Shariatullah Bot. 68 (PUP) 956.7 ± 956.7 0.0 ± 0 0.0 ± 0 0.0 ± 0.0 5. Ficus carica L. Shariatullah Bot. 140 (PUP) 886.0 ± 74.0 0.0 ± 0 0.0 ± 0 1177.5 ± 517.5 6. Ailanthus altissima (Mill.) Swingle. Shariatullah Bot. 231 (PUP) 465.6 ± 66.7 1336.0 ± 0 577.1 ± 0 1206.3 ± 1.3 7. Diospyros kaki L. f. Shariatullah Bot. 96 (PUP) 563.9 ± 42.8 566.0 ± 0 653.3 ± 0 120.0 ± 120.0 8. Quercus incana Bartram. Shariatullah Bot. 103 (PUP) 1636.3 ± 2.0 1698.3 ± 0 0.0 ± 0 0.0 ± 0.0 9. Pinus roxburghii Sarg. Shariatullah Bot. 22 (PUP) 443.0 ± 443.0 0.0 ± 0 0.0 ± 0 0.0 ± 0.0 10. Pinus wallichiana A. B. Jacks. Shariatullah Bot. 23 (PUP) 1360.4 ± 357.5 1728.1 ± 0 1651.7 ± 0 1626.0 ± 12.4 11. Populus nigra L. Shariatullah Bot. 225 (PUP) 1205.5 ± 109.5 1368.0 ± 0 0.0 ± 0 120.0 ± 120.0 12. Pyrus pashia Buch. -Ham. ex D. Don. Shariatullah Bot. 214 (PUP) 1372.5 ± 627.5 0.0 ± 0 1920.0 ± 0 2510.0 ± 290.0 13. Citrus sinensis (L.) Osbeck. Shariatullah Bot. 221 (PUP) 368.0 ± 368.0 0.0 ± 0 0.0 ± 0 0.0 ± 0.0 14. Prunus persica (L.) Batsch. Shariatullah Bot. 200 (PUP) 883.3 ± 156.7 580.0 ± 0 0.0 ± 0 550.0 ± 550.0 15. Quercus dilatata Royle. Shariatullah Bot. 104 (PUP) 3038.3 ± 1128.3 1382.9 ± 0 0.0 ± 0 880.0 ± 880.0 16. Pistacia chinensis Bunge subsp. integerrima (J. Shariatullah Bot. 31 (PUP) 120.0 ± 120.0 0.0 ± 0 0.0 ± 0 1310.0 ± 1310.0 L. Stewart ex Brandis.) Rech. f. 17. Vitis vinifera L. Shariatullah Bot. 250 (PUP) 360.0 ± 360.0 0.0 ± 0 0.0 ± 0 370.0 ± 370.0 18. Olea ferruginea Royle. Shariatullah Bot. 145 (PUP) 1050.8 ± 35.8 2080.0 ± 0 0.0 ± 0 0.0 ± 0.0 19. Prunus armeniaca L. Shariatullah Bot. 202 (PUP) 2198.0 ± 42.0 0.0 ± 0 3340.0 ± 0 1988.3 ± 418.3 20. Morus alba L. Shariatullah Bot. 139 (PUP) 2418.3 ± 1351.7 280.0 ± 0 460.0 ± 0 2990.0 ± 210.0 21. Punica granatum L. Shariatullah Bot. 190 (PUP) 1240.0 ± 1240.0 260.0 ± 0 0.0 ± 0 0.0 ± 0.0 22. Robinia pseudo-acacia L. Shariatullah Bot. 155 (PUP) 0.0 ± 0.0 2240.0 ± 0 695.0 ± 0 0.0 ± 0.0 23. Sorbaria tomentosa (Lindl.) Rehder. Shariatullah Bot. 215 (PUP) 0.0 ± 0.0 1300.0 ± 0 0.0 ± 0 0.0 ± 0.0 24. Pyrus pyrifolia (Burm.f.) Nakai. Shariatullah Bot. 203 (PUP) 1100.0 ± 1100.0 0.0 ± 0 0.0 ± 0 0.0 ± 0.0 25. Celtis australis L. Shariatullah Bot. 245 (PUP) 1780.0 ± 1780.0 0.0 ± 0 0.0 ± 0 0.0 ± 0.0 26. Melia azedarach L. Shariatullah Bot. 135 (PUP) 660.0 ± 660.0 0.0 ± 0 0.0 ± 0 0.0 ± 0.0 27. Morus nigra L. Shariatullah Bot. 138 (PUP) 1100.0 ± 1100.0 0.0 ± 0 1900.0 ± 0 0.0 ± 0.0 28. Pyrus malus L. Shariatullah Bot. 213 (PUP) 860.0 ± 860.0 0.0 ± 0 0.0 ± 0 0.0 ± 0.0 29. Prunus domestica L. Shariatullah Bot. 201 (PUP) 310.0 ± 310.0 0.0 ± 0 0.0 ± 0 1495.0 ± 595.0 30. Ziziphus oxyphylla Edgew. Shariatullah Bot. 199 (PUP) 0.0 ± 0.0 0.0 ± 0 0.0 ± 0 780.0 ± 780.0

Table 4.8. Topographic and edaphic variables associated with trees species in Jelar valley

Parameters Group I Group II Group III Group IV Mean±SE Mean±SE Mean±SE Mean±SE Altitude 1967 ± 130.0 1808 ± 0 2058.6 ± 0 2070.8 ± 35.20 Slope 20.1 ± 2.3 20.2 ± 0 15.6 ± 0 12.7 ± 0.90 Clay% 2.4 ± 2.0 0.4 ± 0 2.4 ± 0 2.3 ± 0.10 Silt% 42 ± 2.0 34 ± 0 42 ± 0 38 ± 2.00 Sand % 55.6 ± 4.0 65.6 ± 0 55.6 ± 0 59.6 ± 2.00 Texture class Loamy ± 0.0 Loamy ± 0 Loamy ± 0 Loamy ± 0.00 sand sand sand sand PH 1:5 5.9 ± 0.3 6.2 ± 0 5.4 ± 0 5.8 ± 0.00 O-M% 1.656 ± 1.0 0.69 ± 0 1.932 ± 0 1.242 ± 0.14 Lime% 1.75 ± 0.8 0.5 ± 0 2 ± 0 1.75 ± 0.75 N% 0.0828 ± 0.0 0.0345 ± 0 0.966 ± 0 0.3105 ± 0.24 P (mg/kg) 27.69 ± 27.7 20.04 ± 0 0.03 ± 0 5.375 ± 2.26 K (mg/kg) 240 ± 120 130 ± 0 110 ± 0 135 ± 45.00 Cu (mg/kg) 0.302 ± 0.0 0.327 ± 0 0.245 ± 0 0.2775 ± 0.04 Zn (mg/kg) 0.5915 ± 0.3 0.288 ± 0 0.138 ± 0 0.573 ± 0.41 Fe (mg/kg) 1.0165 ± 0.1 1.33 ± 0 0.879 ± 0 1.305 ± 0.31 Mn (mg/kg) 3.4765 ± 1.1 2.177 ± 0 1.885 ± 0 6.179 ± 0.64 Pb (mg/kg) 1.0765 ± 0.2 1.88 ± 0 1.13 ± 0 1.1 ± 0.52 Ca (mg/kg) 9.696 ± 0.3 9.126 ± 0 9.948 ± 0 9.8905 ± 0.01 Mg (mg/kg) 2.4545 ± 0.0 2.347 ± 0 2.372 ± 0 2.2835 ± 0.09 Na (mg/kg) 19.45 ± 1.0 17.9 ± 0 19.6 ± 0 16.9 ± 0.30

Fig. 8. Cluster analysis dendrogram of trees species obtained through Ward‟s cluster analysis

Fig. 9. Two-way cluster dendrogram of trees species

4.2.2a Ordination of trees vegetation data 4.2.2.1a NMS ordination of trees vegetation NMS and PCA ordination were used to explore the relation of environmental variables, edaphic factors, macro and micro nutrients with trees species. The results revealed that the groups of trees species (based on IVI) obtained through Ward‟s cluster analysis were also super imposed on the NMS and PCA ordination axis. In NMS ordination plot group 1 is overlapped on axis 1, 2 while group 2 is situated in the lower end of the plot toward axis 1. Similarly, group 3 and group 4 are situated at the left side toward axis 2. The overall pattern of distribution of stands in NMS ordination plot shows an almost clock wise rotation (Fig. 10). Similar study was also conducted by Tavili et al. (2009) while studying the vegetation environment relation in Southern Khorasan rangelands. They used cluster analysis for classification and CCA ordination. Gui et al. (2010) also used CCA ordination while exploring the vegetation of Middle Kunlun Mountains. Khan (2012) used DCA ordination and cluster analysis for the classification and ordination of Quercus baloot dominated forest of Dir Upper and reported three communities. Haq et al. (2015) used TWINSPAN for classification and DCA, CCA ordination for exploration of vegetation of Nandiar Khuwar (Pakistan) and reported four communities. Irshad et al. (2016) used cluster analysis and NMS ordination and reported four communities. Rahman et al. (2016) used cluster analysis and NMS ordination while exploring Isodon rugosus dominated communities in Khwazakhela (Pakistan) and reported four communities. Similarly, Akbar (2013) applied cluster analysis and PCA ordination of trees species while exploring trees vegetation of Northern areas of Pakistan. So, my finding is an agreement with the above authors. Correlation of NMS ordination axis with environmental and soil variables The correlation of NMS ordination axis 1, 2 with various topographic, edaphic variables and soil nutrients are presented in (Table. 4.9). The results revealed that the NMS ordination axis 1 was only significantly correlated with nitrogen (P<0.05) while, axis 2 of NMS ordination was found in significant correlation with altitude (P<0.001), organic matter % (P<0.05), Pb (mg/kg) (r= 0.83695, P<0.05) and Ca (mg/kg) (r= 0.947312, P<0.01). The correlation of NMS ordination axis 1, 2 were found non-significant with the remaining studied parameters. Hill & Gauch (1980), McCune & Grace (2002) stated that ordination is capable to give up at least one basic gradient linked with community‟s distribution of vegetation. In the present study the results show that nitrogen, altitude, organic matter contents in the soil, Pb and Ca are the main variables

responsible for the distribution of trees species while the remaining parameters moving along. Similar study was conducted by Khan (2012) and not found any significant correlation of DCA ordination axes environmental variables and urged that past disturbance and chance factors are responsible for the alteration of vegetation which is a deviation from my results. However, my findings are strongly supported by Rahman et al. (2016) who found significant correlation of CCA ordination axes with altitude, aspect, pH, organic matter, potassium and phosphorus contents of the soil. Khan et al. (2011) found significant correlation of DCA ordination axes with elevation, conductivity, nitrogen and phosphorus. My findings are also an agreement with Oswalt et al. (2006) who found significant correlation of NMS ordination axes with different edaphic and environmental variables while exploring the phytosociology of vascular plants Vergen Islands (US). 4.2.2.2a PCA ordination of trees vegetation The relationship of trees vegetation with topographic, edaphic factors, soil macro and micro nutrients was explored using PCA ordination. The four groups of trees species separated through Ward‟s cluster analysis were also superimposed on the PCA ordination axis I, 2; 1, 3 and 2, 3. The results revealed that Ward‟s cluster analysis and ordination are different techniques though use for the same purposes. The pattern of rotation of various groups in PCA ordination (axis 1, 2) is irregular. Community group 1 and group 2 are separated toward (axis 2) the left side, group 2 is situated at the right side (axis 1) while one stand of group 4 is situated at the upper end of axis 1 (right side) and the second stand of this group is situated at the lower end toward axis 2 (Fig. 11). PCA ordination plots of axis 2, 3 and 1, 3 are represented in (Fig. 12). The rotation of various vegetation groups of trees data set is clock wise at ordination plane (axis 2,3) while that of axis 2, 3 is anti clock wise (Fig. 13). Similar study was conducted by Akbar et al. (2011) and used PCA ordination for the exploration of trees vegetation data in Gilgit- Baltistan. Ilyas et al. (2015) applied DCA for the exploration of vegetation of Kabal valley (Pakistan). Relationship of PCA ordination axes (1-3) with edaphic, topographic and soil nutrients associated with trees vegetation Table. 4.10 represent the relationship of PCA ordination axis (1-3) of trees vegetation data set with topographic, edaphic factors and soil nutrients elements. The results revealed that both the topographic factors (altitude and slope) were significantly correlated with PCA

ordination axis. Altitude was found in significant correlation with PCA axis 2 while slope was significantly correlated with axis 1. Among the other observed parameters only organic matter was found in significant correlation with axis 2 (r= 0.756, P<0.05) of PCA ordination while, the correlation of the remaining factors was non-significant. The results also revealed that PCA ordination axis 3 was not found in significant correlation with any one of the topographic, edaphic factors and nutrient elements associated with trees vegetation data. Hill & Gauch (1980) and McCune & Grace (2002) stated that the ordination is capable of yielding at least one basic gradient associated with the vegetation. However, i found significant relationships of PCA ordination axes with more than one gradient which indicating that the distribution of vegetation is governed by more than one factor. Therefore, my findings are an agreement with Ahmed et al. (2011) who found correlation of ordination axes with several environmental variables (altitude, organic matter, soil pH, nitrogen and magnesium contents). My findings are also supported by Akbar et al. (2011) who found significant correlation of PCA axis with nitrogen, magnesium, zinc, iron and manganese contents in the soil associated with trees vegetation. In the present finding most of the studied parameters were found non-significant in correlation with PCA ordination which may be the severe anthropogenic disturbance which altered the natural phenomenon as reported by Chaghtai et al. (1983), Gui et al. (2010), Wahab (2011), Rahman et al. (2016) and Khan et al. (2013).

Table 4.9. Correlation of NMS ordination axis 1, 2 with environmental and soil variables

Parameters Axis 1 Axis 2 Multiple R Probability level Multiple R Probability level Altitude 0.340 Non-significant 0.982066 p<0.001 Slope 0.257 Non-significant 0.317879 Non-significant Clay% 0.375 Non-significant 0.112633 Non-significant Silt% 0.375 Non-significant 0.273592 Non-significant Sand% 0.399 Non-significant 0.176231 Non-significant Texture class 0.0 Non-significant 0.0 Non-significant PH 1:5 0.210 Non-significant 0.088266 Non-significant O-M% 0.250 Non-significant 0.779259 P<0.05 Lime% 0.325 Non-significant 0.624545 Non-significant N% 0.813 P<0.05 0.253115 Non-significant P (mg/kg) 0.183 Non-significant 0.291764 Non-significant K (mg/kg) 0.301 Non-significant 0.529645 Non-significant Cu (mg/kg) 0.494 Non-significant 0.089715 Non-significant Zn (mg/kg) 0.039 Non-significant 0.281935 Non-significant Fe (mg/kg) 0.100 Non-significant 0.2211 Non-significant Mn (mg/kg) 0.030 Non-significant 0.585963 Non-significant Pb (mg/kg) 0.187 Non-significant 0.83695 P<0.05 Ca (mg/kg) 0.313 Non-significant 0.947312 P<0.01 Mg (mg/kg) 0.434 Non-significant 0.190185 Non-significant Na (mg/kg) 0.295 Non-significant 0.294686 Non-significant

Table 4.10. Correlation of PCA ordination axis 1, 2, 3 of trees with environmental and soil variables

Parameters Axis 1 Axis 2 Axis 3 Multiple R Prob. level Multiple R Prob. Level Multiple R Prob. Level Altitude 0.482 Non-significant 0.781* P<0.05 0.266 Non-significant Slope 0.943** P<0.01 0.094 Non-significant 0.176 Non-significant Clay% 0.638 Non-significant 0.583 Non-significant 0.383 Non-significant Silt% 0.315 Non-significant 0.233 Non-significant 0.200 Non-significant Sand% 0.445 Non-significant 0.353 Non-significant 0.275 Non-significant Texture class Non-significant Non-significant Non-significant PH 1:5 0.702 Non-significant 0.455 Non-significant 0.178 Non-significant O-M% 0.106 Non-significant 0.756* P<0.05 0.265 Non-significant Lime% 0.196 Non-significant 0.731 Non-significant 0.043 Non-significant N% 0.386 Non-significant 0.072 Non-significant 0.580 Non-significant P (mg/kg) 0.682 Non-significant 0.678 Non-significant 0.119 Non-significant K (mg/kg) 0.446 Non-significant 0.702 Non-significant 0.166 Non-significant Cu (mg/kg) 0.538 Non-significant 0.025 Non-significant 0.091 Non-significant Zn (mg/kg) 0.115 Non-significant 0.729 Non-significant 0.452 Non-significant Fe (mg/kg) 0.003 Non-significant 0.224 Non-significant 0.176 Non-significant Mn (mg/kg) 0.504 Non-significant 0.690 Non-significant 0.318 Non-significant Pb (mg/kg) 0.364 Non-significant 0.431 Non-significant 0.052 Non-significant Ca (mg/kg) 0.532 Non-significant 0.720 Non-significant 0.170 Non-significant Mg (mg/kg) 0.490 Non-significant 0.088 Non-significant 0.061 Non-significant Na (mg/kg) 0.231 Non-significant 0.553 Non-significant 0.093 Non-significant

Fig. 10. NMS ordination plot showing the distribution of trees species between axis 1, axis 2

Fig. 11. PCA ordination axis 1 and 2 of tree species

Fig. 12. PCA ordination axis 2 and 3 of tree species

Fig. 13. PCA ordination axis 1 and 3 of tree species

4.2b Classification of understory vegetation (Ward’s cluster analysis and ordination) 4.2.1b Ward’s cluster analysis of understory vegetation Understory vegetation plays a significant role in sustainability of structure and function of forest ecosystem, facilitating nutrient cycling, flow of energy as well as affecting canopy succession (Huo et al., 2014). Any changes in the understory vegetation impose long-term shifts in forest communities; however, unfortunately it is one of the least considered areas of forest ecology (Chapin et al., 2004). Numerous studies demonstrated that dynamic understory communities change considerably with the overstory species (Yu & Sun, 2013). In the present study the IVI of 88 understory species and six sampling stands was subjected to Pc-Ord software for Ward‟s cluster analysis and NMS ordination which results into the formation of four communities (Fig.14, 15). The communities were made based on the top IVI of the dominant species found in the area. Rahman et al. (2017) explored the understory vegetation and associated topographic variables of Pinus wallichiana-dominated forests of Swat (Pakistan). They reported three communities of 92 understory species. Nisar (2013) reported the composition of understory vegetation of Cholistan desert, Pakistan. Similarly, Akbar (2013) reported five communities of understory species from Northern areas of Pakistan. Group I. Sarcococca saligna-Isodon rugosus community This community was found in Gumbad at 1837 m altitude and 17.8 slope angle. This community was comprised of 57 understory species (14 shrubs and 43 herbs). This community was dominated by shrubs species in which the IVI of the leading species (Sarcococca saligna) was recorded as 12.18%. The co-dominant species of this community was Isodon rugosus with IVI 11.6% followed by Berberis lycium (IVI. 10.77%), Wikstroemia canescens (IVI. 10.21%), Spiraea canescens (IVI. 9.73%) and Parrotiopsis jacquemontiana (IVI. 9.32%). Many of the species found in this community were also reported by Rahman et al. (2016) while exploring the Isodon rugosus dominated communities in Khwazakhela Swat. Among the other understory species of this community the IVI of Galium stewartii and Viola canescens was 7.22 to 7.18%, while that of Cotinus coggygria, Cotoneaster nummularia, Duchesnea indica, Calamintha umbrosa, Indigofera heterantha, Foeniculum vulgare, Oxalis corniculata and Rabdosia rugosa was recorded as 6.92 to 5.3% respectively. The IVI of Themeda anathera, Dysphania botrys, Xanthium strumarium, Cyperus rotundus, Jasminum officinale, Cynodon dactylon, Amaranthus caudatus, Chenopodium album, Impatiens bicolor, Lonicera asperifolia, Andrachne cordifolia,

Conyza canadensis and Myrsine africana ranged from 3.77 to 2.32% respectively. All of the remaining 28 species of this community were herbaceous and they contributed less IVI (less than 2%) to this community (Table. 4.11). Most of the understory species found in this community are also found in the other communities groups as well as previously reported by Rahman et al. (2017) from Swat, Akbar (2013) from (Gilgit, Astor and Skardu) dry temperate while Wahab (2011) reported some of these species form district Dir. Jelar valley falls under dry temperate areas. So, my findings are an agreement with the above authors. Some of the species (Mentha longifolia, Urtica dioica and Berberis lycium) found in this community were reported by Hussain (2013) as common species from Gilgit. Environmental variables (slope, elevation) and edaphic factors can strongly influence the composition of species at a microclimatic level (Rahman et al., 2017). The physiochemical properties associated with this community shows that clay and silt (%) were high while sand (%) contents were lower as compared to the soil of other communities. The soil associated with this community was loamy sand, acidic in nature and slightly calcareous while difference was found in the pH value, organic matter and lime (%) in the soil. The similar edaphic characters of the soil associated with different communities groups may be the less difference in the altitude and distance of these sites from each other. Nitrogen and phosphorus contents were low while potassium was found in adequate amount. Among the other nutrients elements of the soil, Cu was found (0.288 mg/kg), Zn (0.272 mg/kg), Fe (0.893 mg/kg), Mn (2.407 mg/kg), Pb (1.32 mg/kg), Ca (9.407 mg/kg), Mg (2.411 mg/kg) and Na was found (20.4 mg/kg) (Table. 4.12). The impact of topographic and edaphic variables on the distribution and composition of understory vegetation is also reported by others from different areas of the country as well as abroad (Akbar, 2013; Veldman et al., 2013; Ummara et al., 2015 and Rahman et al., 2017). Group II. Wikstroemia canescens-Berberis lycium community This community was found in Sore Pao and Gul Dherai at 1952.5 m mean altitude and 21.3 slope angle. This community is more diverse and comprised of 64 species (18 shrubs and 46 herbs). Diversity of understory species may be due to different environmental variables (Huebner et al., 1995) associated with different communities. Diversity of understory species may be affected by trees species in an area as the death of the canopy trees produced gapes, increase resources which frequently results in greatly increase total abundance and composition of understory species (Brunet & Oheimb, 1998). The dominant species of this community was

Wikstroemia canescens with an IVI mean value 10.19±2.98% followed by Berberis lycium, Isodon rugosus, Andrachne cordifolia, Cotoneaster nummularia, Oxalis corniculata, Rabdosia rugosa, Tagetes minuta, Cotinus coggygria, Indigofera heterantha, Cynodon dactylon, Dicliptera roxburghiana and Lonicera asperifolia. Their IVI ranged from 10.11±1.32 to 4.23±1.31 respectively. Among the other species of this community Sarcococca saligna shared 3.98±2.75 mean IVI, Cannabis sativa, Medicago minima, Duchesnea indica, Rumex dentatus, Daphne mucronata, Jasminum officinale, Conyza canadensis, Rumex hastatus, Malva neglecta and Amaranthus caudatus shared 3.93 to 3.03% IVI respectively. The IVI mean values of Myrsine africana, Galinsoga parviflora, Rosa webbiana, Impatiens bicolor, Rosa moschata, Urtica dioica, Chenopodium ambrosioides, Desmodium elegans, Cirsium falconeri, Xanthium strumarium, Calamintha umbrosa, Viola canescens and Spiraea canescens ranged from 2.95 to 2.07 respectively while, the IVI of the remaining 27 species such as Clematis graveolens, Polygonum aviculare, Mentha longifolia, Datura stramonium, Nasturtium officinale, Foeniculum vulgare, Themeda anathera, Bidens chinensis, Ranunculus laetus, Euphorbia helioscopia, Micromeria biflora, Polygonum maculosa, Taraxacum campylodes, Hedera nepalensis, Plantago lanceolata, Arisaema flavum, Oenothera speciosa, Girardinia palmata, Chenopodium album, Filago hurdwarica, Galium stewartii, Amaranthus spinosus, Solanum nigrum, Commelina benghalensis, Conyza bonariensis, Ocimum basilicum and Viburnum cotinifolium ranged from 1.93 to 0.53 respectively (Table. 4.11). Similar study was conducted by Ummara et al. (2015) from Shogran vally (Pakistan) and reported fifty-four understorey species. My results are also agreed with Siddiqui (2011) and Ahmed et al. (2010) who reported some of these species from Himalayan range of Pakistan. The results of edaphic and soil nutrients showed that clay particles were 0.4%, silt 37% while sand were found 62.6%. Like the other communities the soil of this community was also loamy sand in texture, acidic and slightly calcareous. Organic matter and nitrogen (%) were low, phosphorus (mg/kg) medium while, potassium (mg/kg) was found in adequate amount. Among the other nutrients elements associated with community group II, Cu was found (0.322 mg/kg), Zn (0.600 mg/kg), Fe (1.235 mg/kg), Mn (3.362 mg/kg), Pb (1.357 mg/kg), Ca (9.556 mg/kg), Mg (2.423 mg/kg) while, sodium was found (18.2 mg/kg) in the soil. The effect of topographic, edaphic and environmental variables on the distribution, diversity and composition of understory vegetation is also reported by Rahman et al. (2017), Adam et al. (2013) and Nisar et al. (2013).

Group III. Berberis lycium- Indigofera heterantha community This community was distributed in Shao and Danda at high altitude 2082.3 m and low slope angle 13.7. This community was comprised of a total of 58 species (15 shrubs and 43 herbs). The IVI of the leading dominant species (Berberis lycium) of this community was 18.05 while that of the co-dominant species (Indigofera heterantha) was 12.36. Similarly, the IVI of Sarcococca saligna was 10.52±1.39, Wikstroemia canescens and Isodon rugosus 9.29 to 9.1, Oxalis corniculata (7.31±0.93), Rosa moschata and Spiraea canescens 6.68 to 6, Cynodon dactylon, Cotinus coggygria and Andrachne cordifolia was found as 5.72 to 5.04 respectively. Among the remaining species the IVI of Plantago lanceolata, Duchesnea indica, Rumex hastatus and Rosa webbiana ranged from 4.86 to 4.11, while that of Cirsium falconeri, Myriactis wallichii, Jasminum officinale, Medicago minima, Dicliptera roxburghiana, Rumex dentatus, Scutellaria chamaedrifolia, Tagetes minuta, Impatiens bicolor and Thymus linearis was 3.87 to 3.02 respectively. Among the remaining 34 species the IVI of Viburnum cotinifolium, Conyza canadensis, Urtica dioica, Commelina benghalensis, Rabdosia rugosa, Cotoneaster nummularia, Chenopodium album, Filago hurdwarica, Polygonum aviculare, Micromeria biflora, Polygonum capitatum and Desmodium elegans ranged from 2.85 to 2.06 while the remaining 21 species less contributed (Table. 4.11). In the present work the distribution of species is almost similar and less difference is found in species diversity which may be the short distance between different study sites as scientists‟ select large area (Wahab, 2011; Akbar, 2013) or the similarity in species in different sites may be the wide ecological amplitude of these species (Khan et al., 2013; Ahmad, 2011 and Ali et al., 2016). Edaphic variables associated with community III showed that clay particles were (2.4%) silt (41%) and sand (56.6%). Soil was loamy sand in texture, slightly calcareous while organic matter was high. The results of soil nutrient elements showed that nitrogen contents were medium (0.5175%), phosphorus was low (3.81 mg/kg) while potassium was found in adequate amount (145 mg/kg). Among the other nutrients elements found in the soil of this community Cu was found (0.284±0.039 mg/kg), Zn (0.149±0.010 mg/kg), Fe (1.246±0.367 mg/kg), Mn (3.712±1.827 mg/kg), Pb (0.855±0.275 mg/kg), Ca (9.923±0.025 mg/kg), Mg (2.373±0.001 mg/kg) and Na (18.4±1.2 mg/kg) in the soil.

Group IV. Berberis lycium-Indigofera heterantha community This community was reported from Tangai Awar at 2035.6 m mean altitude and 13.6 slope angle. This community is less diverse in term of number of species (49) the dominant and co-dominant species of this community is similar to community group III but the difference is found in the IVI mean values of the dominant species. Berberis lycium (IVI. 21.28) was the dominant species of this community followed by Indigofera heterantha, Wikstroemia canescens, Medicago minima, Lonicera asperifolia, Calamintha umbrosa, Andrachne cordifolia, Rosa moschata, Isodon rugosus, Viburnum cotinifolium, Cotinus coggygria, Viola canescens, Impatiens bicolor, Oxalis corniculata, Sarcococca saligna, Duchesnea indica and Desmodium elegans with IVI mean values 15.75 to 4.81 respectively. Berberis lycium is an important medicinal plant used for the curing of different ailments (Rahman et al., 2016). Other species such as Indigofera gerardiana, Medicago minima, Lonicera asperifolia and Tagetes minuta are other important species used by the people of the area for fuels and other purposes (Khan et al., 2011). These species were also previously reported by Rahman et al. (2016) from Khwazakhela (swat) in Isodon rugosus dominated communities. The IVI of Rumex dentatus, Cannabis sativa, Polygonum maculosa, Polygonum aviculare and Amaranthus caudatus was found as 3.74 to 3.12 respectively. Among the remaining low contributing species, the IVI mean value of Chenopodium album, Setaria viridis, Urtica dioica, Rumex hastatus, Valeriana wallichii, Clematis graveolens, Myrsine africana, Mentha arvensis, Plantago lanceolata and Conyza canadensis range from 2.84 to 2.13 respectively while, that of the remaining species (IVI) was less than 2% (Table. 4.11). These species require proper management otherwise they will be loss in the future from this area. The results of soil associated with this community showed that like the soil of other communities the soil was loamy sand acidic (pH 5.8) in nature and slightly calcareous. Organic matter (1.10%), nitrogen (0.552%) and potassium (90 mg/kg) contents were medium while phosphorus (3.12 mg/kg) was low. Among the other nutrients, Cu (0.233 mg/kg), Mg (2.193 mg/kg) and Na (16.6 mg/kg) contents were lower while, Zn (0.987 mg/kg), Mn (6.82 mg/kg) and Pb (1.62 mg/kg) contents were high as compared to the soil of other communities. Fe contents were found (0.998 mg/kg) while calcium was found (9.883 mg/kg) in the soil associated with this community.

Table 4.11. IVI mean values of understory vegetation in different communities obtained through Ward‟s cluster analysis

S.NO Species Voucher number Group I Group II Group III Group IV

Mean±SE Mean±SE Mean±SE Mean±SE 1. Wikstroemia canescens Wall. ex Meisn. Shariatullah Bot. 243 (PUP) 10.21 ± 0 10.19 ± 2.98 9.29 ± 0.22 12.57 ± 0 2. Berberis lycium Royle. Shariatullah Bot. 67 (PUP) 10.77 ± 0 10.11 ± 1.32 18.05 ± 2.64 21.28 ± 0 3. Indigofera heterantha Brandis. var. heterantha Shariatullah Bot. 164 (PUP) 6.07 ± 0 5.35 ± 1.77 12.36 ± 1.05 15.75 ± 0 4. Cotinus coggygria Scop. Shariatullah Bot. 32 (PUP) 6.92 ± 0 5.98 ± 0.47 5.3 ± 0.38 5.82 ± 0 5. Cotoneaster nummularia Fisch. & Mey Shariatullah Bot. 216 (PUP) 6.73 ± 0 9.31 ± 1.44 2.48 ± 2.48 0 ± 0 6. Sarcococca saligna Muell. Arg. Shariatullah Bot. 75 (PUP) 12.18 ± 0 3.98 ± 2.75 10.52 ± 1.39 4.96 ± 0 7. Lonicera asperifolia Hook. f. & Thomson. Shariatullah Bot. 77 (PUP) 2.73 ± 0 4.23 ± 1.31 0 ± 0 7.5 ± 0 8. Spiraea canescens D. Don. Shariatullah Bot. 206 (PUP) 9.73 ± 0 2.07 ± 0.1 6 ± 1.76 0 ± 0 9. Jasminum officinale L. Shariatullah Bot. 146 (PUP) 3.41 ± 0 3.39 ± 0.61 3.67 ± 1.43 0 ± 0 10. Rabdosia rugosa (Wall. ex Benth.) H. Hara. Shariatullah Bot. 117 (PUP) 5.3 ± 0 6.64 ± 0.07 2.49 ± 2.49 0 ± 0 11. Isodon rugosus (Wall. ex Benth.) Codd. Shariatullah Bot. 116 (PUP) 11.6 ± 0 10.1 ± 0.09 9.1 ± 0.53 5.99 ± 0 12. Myrsine africana L. Shariatullah Bot. 142 (PUP) 2.32 ± 0 2.95 ± 2.95 0 ± 0 2.28 ± 0 13. Andrachne cordifolia (Decne.) Mull.Arg. Shariatullah Bot. 102 (PUP) 2.72 ± 0 9.97 ± 0.58 5.04 ± 0.21 6.66 ± 0 14. Parrotiopsis jacquemontiana (Decne.) Rehder. Shariatullah Bot. 109 (PUP) 9.32 ± 0 0 ± 0 0 ± 0 0 ± 0 15. Rosa webbiana Wall. ex Royle. Shariatullah Bot. 207 (PUP) 0 ± 0 2.79 ± 0.54 4.11 ± 1.07 0 ± 0 16. Desmodium elegans DC. Shariatullah Bot. 163 (PUP) 0 ± 0 2.54 ± 0.42 2.06 ± 2.06 4.81 ± 0 17. Viburnum cotinifolium D. Don. Shariatullah Bot. 78 (PUP) 0 ± 0 0.53 ± 0.53 2.85 ± 0.3 5.84 ± 0 18. Rosa moschata Herrm. Shariatullah Bot. 205 (PUP) 0 ± 0 2.63 ± 2.63 6.68 ± 0.73 6.56 ± 0 19. Daphne mucronata Royle. Shariatullah Bot. 242 (PUP) 0 ± 0 3.44 ± 3.44 0 ± 0 0 ± 0 20. Duchesnea indica (Jacks.) Focke. Shariatullah Bot. 211 (PUP) 6.32 ± 0 3.51 ± 1.13 4.79 ± 1.76 4.94 ± 0 21. Ocimum basilicum L. Shariatullah Bot. 124 (PUP) 1.83 ± 0 0.57 ± 0.57 0.61 ± 0.61 1.12 ± 0 22. Calamintha umbrosa (M. Bieb.) Fisch. & C. A. Mey. Shariatullah Bot. 129 (PUP) 6.21 ± 0 2.26 ± 2.26 0 ± 0 7.45 ± 0 23. Galium stewartii Nazim. Shariatullah Bot. 219 (PUP 7.22 ± 0 0.79 ± 0.79 0 ± 0 1.3 ± 0 24. Oxalis corniculata L. Shariatullah Bot. 149 (PUP) 5.36 ± 0 8.29 ± 0.79 7.31 ± 0.93 4.99 ± 0 25. Androsace rotundifolia Hardw. subsp. glandulosa (Hook. f.) Shariatullah Bot. 189 (PUP) 1.35 ± 0 0 ± 0 0 ± 0 0 ± 0 Y.J. Nasir. 26. Cynodon dactylon (L.) Pers. Shariatullah Bot. 176 (PUP) 2.96 ± 0 4.82 ± 0.03 5.72 ± 1.86 1.39 ± 0 27. Cyperus rotundus L. Shariatullah Bot. 95 (PUP) 3.42 ± 0 0 ± 0 0 ± 0 0 ± 0 28. Themeda anathera (Nees ex Steud.) Hack. Shariatullah Bot. 174 (PUP) 3.77 ± 0 1.34 ± 1.34 0 ± 0 0 ± 0 29. Cannabis sativa L. Shariatullah Bot. 76 (PUP) 1.47 ± 0 3.93 ± 0.41 0 ± 0 3.62 ± 0 30. Conyza Canadensis (L.) Cronquist Shariatullah Bot. 60 (PUP) 2.49 ± 0 3.24 ± 0.23 2.78 ± 0.99 2.13 ± 0 31. Tagetes minuta L. Shariatullah Bot. 61 (PUP) 0.99 ± 0 6.03 ± 0.5 3.15 ± 0.17 1.29 ± 0 32. Mentha longifolia (L.) L. Shariatullah Bot. 126 (PUP) 1.11 ± 0 1.5 ± 0.51 1.12 ± 1.12 0 ± 0 33. Rumex hastatus D. Don. Shariatullah Bot. 182 (PUP) 1.24 ± 0 3.24 ± 0.09 4.22 ± 0.73 2.58 ± 0

34. Viola canescens Wall. Shariatullah Bot. 249 (PUP) 7.18 ± 0 2.23 ± 0.48 1.51 ± 0.14 5.53 ± 0 35. Conyza bonariensis (L.) Cronquist. Shariatullah Bot. 45 (PUP) 0.81 ± 0 0.58 ± 0.58 0 ± 0 1.44 ± 0 36. Setaria viridis (L.) P. Beauv. Shariatullah Bot. 181 (PUP) 1.23 ± 0 0 ± 0 0 ± 0 2.73 ± 0 37. Micromeria biflora (Duch.-Ham ex D. Don.) Benth. Shariatullah Bot. 122 (PUP) 1.73 ± 0 1.24 ± 0.06 2.14 ± 0.7 0 ± 0 38. Plantago lanceolata L. Shariatullah Bot. 169 (PUP) 1.39 ± 0 1.05 ± 1.05 4.86 ± 2.24 2.17 ± 0 39. Rumex dentatus L. Shariatullah Bot. 187 (PUP) 1.54 ± 0 3.47 ± 0.35 3.2 ± 0.45 3.74 ± 0 40. Impatiens bicolor Royle subsp. pseudobicolor Shariatullah Bot. 65 (PUP) 2.74 ± 0 2.66 ± 2.66 3.05 ± 0.21 5.27 ± 0 (Grey-Wilson & Rech. f.) Y. J. Nasir. 41. Arisaema flavum (Forssk.) Schott. Shariatullah Bot. 41 (PUP) 1.6 ± 0 1.05 ± 1.05 0.63 ± 0.63 0 ± 0 42. Swertia petiolata D. Don. Shariatullah Bot. 105 (PUP) 0.86 ± 0 0 ± 0 0 ± 0 0 ± 0 43. Melilotus officinalis (L.) Pall. Shariatullah Bot. 162 (PUP) 0.64 ± 0 0 ± 0 0 ± 0 0 ± 0 44. Valeriana wallichii DC. Shariatullah Bot. 248 (PUP) 1.66 ± 0 0 ± 0 0 ± 0 2.52 ± 0 45. Seseli libanotis (L.) Koch. Shariatullah Bot. 40 (PUP) 1.28 ± 0 0 ± 0 0 ± 0 0 ± 0 46. Bergenia ciliata (Haw.) Sternb. Shariatullah Bot. 227 (PUP) 0.9 ± 0 0 ± 0 0 ± 0 0 ± 0 47. Heliotropium undulatum Vahl. var. suberosa Clarke. Shariatullah Bot. 69 (PUP) 1.35 ± 0 0 ± 0 0 ± 0 0 ± 0 48. Ajuga bracteosa Wall. ex Benth. Shariatullah Bot. 115 (PUP) 1.35 ± 0 0 ± 0 0 ± 0 0 ± 0 49. Foeniculum vulgare Mill. Shariatullah Bot. 37 (PUP) 5.54 ± 0 1.41 ± 1.41 0 ± 0 0 ± 0 50. Chenopodium album L. Shariatullah Bot. 82 (PUP) 2.8 ± 0 0.96 ± 0.96 2.43 ± 0.37 2.84 ± 0 51. Amaranthus caudatus L. Shariatullah Bot. 30 (PUP) 2.92 ± 0 3.03 ± 0.24 1.65 ± 0.09 3.12 ± 0 52. Amaranthus spinosus L. Shariatullah Bot. 28 (PUP) 1.42 ± 0 0.73 ± 0.73 0 ± 0 0 ± 0 53. Dysphania botrys (L.) Mosyakin & Clemants. Shariatullah Bot. 86 (PUP) 3.45 ± 0 0 ± 0 0 ± 0 0 ± 0 54. Polygonum aviculare L. Shariatullah Bot. 184 (PUP) 1.73 ± 0 1.68 ± 0.86 2.25 ± 0.55 3.33 ± 0 55. Solanum nigrum L. var. nigrum. Shariatullah Bot. 240 (PUP) 1.35 ± 0 0.67 ± 0.67 0.45 ± 0.45 1.19 ± 0 56. Xanthium strumarium L. Shariatullah Bot. 56 (PUP) 3.45 ± 0 2.39 ± 2.39 0 ± 0 0 ± 0 57. Datura stramonium L. Shariatullah Bot. 241 (PUP) 1.19 ± 0 1.5 ± 1.5 1.03 ± 1.03 0 ± 0 58. Artemisia scoparia Waldst. & Kitam. Shariatullah Bot. 54 (PUP) 0.72 ± 0 0 ± 0 0 ± 0 0 ± 0 59. Malva neglecta Wallr. Shariatullah Bot. 134 (PUP) 1.35 ± 0 3.06 ± 0.93 1.48 ± 1.48 1.96 ± 0 60. Polygonum maculosa L. Shariatullah Bot. 188 (PUP) 1.18 ± 0 1.18 ± 0.39 1.49 ± 1.49 3.34 ± 0 61. Dicliptera roxburghiana Nees. Shariatullah Bot. 24 (PUP) 0.92 ± 0 4.32 ± 0.1 3.23 ± 0.21 1.39 ± 0 62. Urtica dioica L. Shariatullah Bot. 246 (PUP) 0 ± 0 2.63 ± 0.19 2.58 ± 0.66 2.7 ± 0 63. Galinsoga parviflora Cav. Shariatullah Bot. 62 (PUP) 0 ± 0 2.8 ± 0.91 1.9 ± 0.35 0 ± 0 64. Taraxacum campylodes G.E.Haglund. Shariatullah Bot. 53 (PUP) 0 ± 0 1.16 ± 0.01 0.85 ± 0.08 1.36 ± 0 65. Oenothera speciosa Nutt. Shariatullah Bot. 148 (PUP) 0 ± 0 1.05 ± 1.05 0 ± 0 0 ± 0 66. Clematis graveolens Lindl. Shariatullah Bot. 191 (PUP) 0 ± 0 1.93 ± 0.09 1.54 ± 0.61 2.47 ± 0 67. Cirsium falconeri (Hook. f.) Petr. Shariatullah Bot. 47 (PUP) 0 ± 0 2.51 ± 0.5 3.87 ± 0.24 0 ± 0 68. Medicago minima (L.) L. Shariatullah Bot. 158 (PUP) 0 ± 0 3.65 ± 2.05 3.42 ± 1.2 8.66 ± 0 69. Ranunculus laetus Wall. ex Hook. f. & J.W. Thomson. Shariatullah Bot. 192 (PUP) 0 ± 0 1.31 ± 1.31 0 ± 0 1.29 ± 0 70. Nasturtium officinale R. Br. Shariatullah Bot. 74 (PUP) 0 ± 0 1.42 ± 1.42 0 ± 0 0 ± 0 71. Chenopodium ambrosioides L. Shariatullah Bot. 85 (PUP) 0 ± 0 2.55 ± 0.88 0 ± 0 0 ± 0

72. Bidens chinensis (L.) Willd. Shariatullah Bot. 52 (PUP) 0 ± 0 1.32 ± 0.06 1.39 ± 0.16 1.07 ± 0 73. Filago hurdwarica (Wall. ex DC.) Wagenitz. Shariatullah Bot. 64 (PUP) 0 ± 0 0.87 ± 0.87 2.41 ± 0.09 1.45 ± 0 74. Mentha arvensis L. Shariatullah Bot. 113 (PUP) 0 ± 0 0 ± 0 0.59 ± 0.59 2.23 ± 0 75. Myriactis wallichii Less. Shariatullah Bot. 57 (PUP) 0 ± 0 0 ± 0 3.85 ± 1.8 1.69 ± 0 76. Euphorbia helioscopia L. Shariatullah Bot. 100 (PUP) 0 ± 0 1.26 ± 1.26 1.55 ± 1.55 1.39 ± 0 77. Polygonum capitatum Buch.-Ham. ex D. Don. Shariatullah Bot. 186 (PUP) 0 ± 0 0 ± 0 2.08 ± 0.42 1.39 ± 0 78. Achyranthes aspera L. var. pubescens (Moq.) M. Gomez. Shariatullah Bot. 29 (PUP) 0 ± 0 0 ± 0 0 ± 0 1.39 ± 0 79. Epilobium hirsutum L. Shariatullah Bot. 147 (PUP) 0 ± 0 0 ± 0 0.98 ± 0.37 1.5 ± 0 80. Commelina benghalensis L. Shariatullah Bot. 87 (PUP) 0 ± 0 0.6 ± 0.6 2.58 ± 2.58 0 ± 0 81. Hedera nepalensis K. Koch. Shariatullah Bot. 43 (PUP) 0 ± 0 1.14 ± 1.14 0 ± 0 0 ± 0 82. Girardinia palmata (Forssk.) Gaudich. Shariatullah Bot. 247 (PUP) 0 ± 0 1.03 ± 1.03 1.33 ± 1.33 0 ± 0 83. Scutellaria chamaedrifolia Hedge & A.J. Paton. Shariatullah Bot. 127 (PUP) 0 ± 0 0 ± 0 3.16 ± 1.39 0 ± 0 84. Ranunculus muricatus L. Shariatullah Bot. 193 (PUP) 0 ± 0 0 ± 0 1.4 ± 0.64 0 ± 0 85. Poterium sanguisorba L. Shariatullah Bot. 218 (PUP) 0 ± 0 0 ± 0 0.69 ± 0.69 0 ± 0 86. Thymus linearis Benth. subsp. linearis Jalas. Shariatullah Bot. 114 (PUP) 0 ± 0 0 ± 0 3.02 ± 3.02 0 ± 0 87. Hypericum perforatum L. Shariatullah Bot. 110 (PUP) 0 ± 0 0 ± 0 1.03 ± 1.03 0 ± 0 88. Salvia lanata Roxb. Shariatullah Bot. 118 (PUP) 1 ± 1 0 ± 0 1.03 ± 1.03 0 ± 0

Table 4.12. Topographic, edaphic and soil nutrients associated with different groups of understory vegetation

Parameters Group I Group II Group III Group IV Mean ± SE Mean ± SE Mean ± SE Mean ± SE I. Topographic variables

Altitude 1837 ± 0 1952.5 ± 144.5 2082.3 ± 23.7 2035.6 ± 0 Slope 17.8 ± 0 21.3 ± 1.1 13.7 ± 1.9 13.6 ± 0 II. Edaphic variables Clay% 4.4 ± 0 0.4 ± 0 2.4 ± 0 2.2 ± 0 Silt% 44 ± 0 37 ± 3 41 ± 1 36 ± 0 Sand% 51.6 ± 0 62.6 ± 3 56.6 ± 1 61.6 ± 0 Texture class 1 ± 0 1 ± 0 1 ± 0 1 ± 0 PH 1:5 5.6 ± 0 6.2 ± 0 5.6 ± 0.2 5.8 ± 0 O-M% 0.69 ± 0 1.656 ± 0.966 1.656 ± 0.276 1.104 ± 0 Lime% 1 ± 0 1.5 ± 1 1.5 ± 0.5 2.5 ± 0 III. Soil nutrients

N% 0.035 ± 0 0.083 ± 0.048 0.5175 ± 0.449 0.552 ± 0 P (mg/kg) 0.7044 ± 0 37.71 ± 17.67 3.83 ± 3.8 3.12 ± 0 K (mg/kg) 120 ± 0 245 ± 115 145 ± 35 90 ± 0 Cu (mg/kg) 0.288 ± 0 0.322 ± 0.006 0.284 ± 0.039 0.233 ± 0 Zn (mg/kg) 0.272 ± 0 0.600 ± 0.312 0.149 ± 0.010 0.987 ± 0 Fe (mg/kg) 0.893 ± 0 1.235 ± 0.095 1.246 ± 0.367 0.998 ± 0 Mn (mg/kg) 2.407 ± 0 3.362 ± 1.185 3.712 ± 1.827 6.82 ± 0 Pb (mg/kg) 1.32 ± 0 1.357 ± 0.524 0.855 ± 0.275 1.62 ± 0 Ca (mg/kg) 9.407 ± 0 9.556 ± 0.430 9.923 ± 0.025 9.883 ± 0 Mg (mg/kg) 2.411 ± 0 2.423 ± 0.075 2.373 ± 0.001 2.193 ± 0 Na (mg/kg) 20.4 ± 0 18.2 ± 0.3 18.4 ± 1.2 16.6 ± 0

Fig. 14. Cluster analysis dendrogram based on IVI of understory species

Fig. 15. Two-way cluster dendrogram representing stands and species distribution in different groups

4.2.2b Ordination of understory vegetation data 4.2.2.1b NMS ordination of understory vegetation The results of NMS ordination of understory vegetation show that the four groups of understory vegetation obtained through Ward‟s cluster analysis are also superimposed on NMS ordination axis 1 and axis 2. Greig-Smith (1983) reported that cluster analysis and ordination are two basic techniques complementary to each other, though fundamentally used for different purposes. Group 1 is placed at the lower end at axis 1 while group 2 is overlapped on both axis of NMS ordination plot. Similarly, group 2 of understory vegetation is placed at axis 2 (upper end) while group 4 is situated at the upper end toward right side. (Fig. 16) shows that the rotation of stand between the two axes of NMS ordination is almost clock wise. There is not found any overlapping of groups of understory vegetation in NMS ordination axis 1, 2. Similar study was conducted by Rahman et al. (2017) while exploring the understory species of Pinus wallichiana dominated forests of Swat. They used DCA and CCA ordination and found three communities of understory species. Akbar (2013) used PCA ordination for soil and understory vegetation relationship. Similarly, Adam et al. (2013) reported the effect of stands characteristics on understory species using PCA and DCA ordination. Relationship of topographic, edaphic factors and nutrients of the soil with NMS ordination axis of understory vegetation The relationship of NMS ordination axis with environmental variable associated with understory vegetation is presented in Table. 4.13. The results revealed that between the two studied topographic factors only altitude is found in significant correlation (r=0.997, P<0.001) with axis 1 of NMS ordination. Among the edaphic factors organic matter significantly correlate with axis 1, lime % was significantly correlated with axis 2 while, the remaining factors not showed any significant relation with NMS ordination axis (1, 2). Among the nutrient elements of the soil NMS axis 1 was significantly correlated with Pb (r=0.752, P<0.05) and Ca (r=0.947, P<0.01). The axis 2 of NMS ordination was found in significant correlation with nitrogen (r= 0.787, P<0.05) and Cu (r=0.939, P<0.01) while, the remaining nutrient element not showed any significant correlation with axis 2 of NMS ordination of understory vegetation. Akbar (2013) documented the effect of environmental variables on the distribution of understory vegetation in Gilgit, Astor and Skardu district and found significant correlation of PCA ordination axis with altitude, pH, organic matter, electrical conductivity, calcium, magnesium, iron, phosphorus,

cobalt and manganese. Ahmed (1984) reported that ordination and classification both are important techniques to understand vegetation ecology. Khan (2011) studied the effect of environmental variables on the distribution of vegetation using DCA ordination while not found any significant correlations and argued that anthropogenic effect is responsible for the differences in distribution of species. Rahman et al. (2016) documented the effect of altitude and aspect on the distribution of Isodon rugosus in Khwazakhela while did not found any significant relationship with the NMS ordination axis. However, my results are strongly supported by McCune & Grace (2002) who stated that ordination is capable of yielding at least one basic gradient associated with the vegetation. Similar study was conducted by Rahman (2013) and found significant relation of DCA ordination axis 1 with altitude, my finding is also an agreement with them. From the above discussion it is concluded that the distribution of understory vegetation in different sampling stands is the combine effect of those variables which were found in significant correlation with NMS ordination axis while the remaining topographic, edaphic factors and nutrients elements moving alone.

Table 4.13. Relationship of environmental variables and soil nutrients with NMS ordination axes (1, 2) based on IVI of understory species

Parameters Axis 1 Axis 2 Multiple R Probability level Multiple R Probability level Altitude 0.997 P<0.001 0.497 Non-significant Slope 0.347 Non-significant 0.491 Non-significant Clay% 0.217 Non-significant 0.354 Non-significant Silt% 0.139 Non-significant 0.198 Non-significant Sand% 0.042 Non-significant 0.273 Non-significant Texture class 0.000 Non-significant 0.000 Non-significant PH 1:5 0.068 Non-significant 0.608 Non-significant O-M% 0.777 P<0.05 0.227 Non-significant Lime% 0.644 Non-significant 0.764 P<0.05 N% 0.353 Non-significant 0.787 P<0.05 P (mg/kg) 0.271 Non-significant 0.387 Non-significant K (mg/kg) 0.171 Non-significant 0.309 Non-significant Cu (mg/kg) 0.143 Non-significant 0.939 P<0.01 Zn (mg/kg) 0.288 Non-significant 0.390 Non-significant Fe (mg/kg) 0.240 Non-significant 0.594 Non-significant Mn (mg/kg) 0.590 Non-significant 0.410 Non-significant Pb (mg/kg) 0.752 P<0.05 0.032 Non-significant Ca (mg/kg) 0.947 P<0.01 0.661 Non-significant Mg (mg/kg) 0.085 Non-significant 0.521 Non-significant Na (mg/kg) 0.390 Non-significant 0.097 Non-significant

Fig. 16. NMS ordination plot showing the distribution of stands of understory vegetation

4.2.3 Density/ha and cover/ha of understory vegetation The density/ha and cover/ha of understory species are presented in (Table. 4.14). The results revealed that a large difference was observed in the overall density/ha and cover/ha in different communities. The overall density/ha (70971 individual) was found high in community group 3, followed by group 4 (56332 individuals /ha). These stands were situated at high altitude while lowest overall density/ha (44467) of species were recorded in community group 2. These groups were situated comparatively at low elevation. Similarly, the overall cover/ha (145697 cm2/ha) was found high in group 1 followed by group 3 (97620 cm2/ha) while lowest cover/ha was found in community group 2 (68621 cm2/ha). Similar study was conducted by Ahmed et al. (2009) and Rahman (2013). They reported highest density/ha and cover/ha at medium elevation. My findings are a deviation from the above authors the reason may be the difference in other environmental factors such as slope angle, aspect, organic matter, moisture contents, soil texture as well as macro and micro nutrients of the soil which greatly affect the vegetation cover, density and distribution pattern of species (Titshall et al., 2000; Zare et al., 2011 and Khan et al., 2013). Beside these parameters, density and cover of overstory species as well as anthropogenic disturbance (grazing. browsing, fuels demand and medicinal values) also greatly affect the density and cover of understory species (Khan et al., 2013; Wahab et al., 2010 and Rahman et al., 2016). The individual density/ha and cover/ha is also different in different communities which indicating the difference in microclimate and habitat condition of different sites which effecting the absolute values of species (Khan et al., 2011; Ahmad et al., 2016 and Rahman et

al., 2016). A species dominant in one community may be rare in the other communities. There are so many factors responsible for the differences in cover and density of species these factors are aspect, slope angle, altitude, soil physiochemical properties and topography of the area (Ahmed et al., 2006; Wahab, 2011). The individual density/ha of the understory species revealed that the dominant species in community group I was Viola canescens (6489 individuals/ha) followed by Galium stewartii (6178 individuals/ha), Duchesnea indica (5644 individuals/ha), Calamintha umbrosa (4356 individuals/ha), Oxalis corniculata (3911 individuals/ha), Cyperus rotundus (2622 individuals/ha), Cynodon dactylon (2356 individuals/ha), Themeda anathera (1333 individuals/ha), Impatiens bicolor (1244 individuals/ha), Conyza canadensis (1200 individuals/ha), Micromeria biflora (1111 individuals/ha) and Plantago lanceolata (1067 individuals/ha). The individual cover/ha of these species ranged from 278 to 2000 cm2 (Table. 4.14). Among the shruby species of community group I Sarcococca saligna was found the leading dominant species with 556 individual/ha with 2119 cm2 mean cover /ha followed by Isodon rugosus (460 density/ha and 2838 cm2 cover/ha), Spiraea canescens (456 density/ha, 678 cm2 cover/ha), while Rabdosia rugosa (16 density/ha, 5450 cm2 cover/ha) and Myrsine africana (12 individuals/ha, 1973 cm2 cover/ha) were less contributing species. In community II the leading dominant species was Oxalis corniculata followed by Cynodon dactylon, Tagetes minuta, Duchesnea indica, Medicago minima, Dicliptera roxburghiana, Impatiens bicolor, Calamintha umbrosa, Conyza canadensis and Rumex hastatus. Their individual mean density/ha ranged from 6311 to 1356 respectively while their mean cover/ha ranged from 178 to 1912 (cm2/ha). In case of shrub species, the highest density/ha was contributed by Wikstroemia canescens (408 individual/ha) followed by Andrachne cordifolia, Isodon rugosus (256) and Berberis lycium while Rosa moschata, Rosa webbiana and Viburnum cotinifolium were less contributing species. Similar to community II group III was also dominated by Oxalis corniculata and Cynodon dactylon while difference was found in quantitative (density/ha and cover/ha) values of these species. In this community the leading dominant shrub species was Berberis lycium (586 individuals/ha, 4538 cm2 cover/ha) followed by Sarcococca saligna (404586 individuals/ha, 2022 cm2 cover/ha), Wikstroemia canescens (338 individuals/ha, 1863 cm2 cover/ha) while the remaining species of this community such as Rosa webbiana, Viburnum cotinifolium, Rabdosia rugosa, Desmodium elegans and Cotoneaster nummularia contributed less density/ha and cover/ha. In community IV the highest density/ha was contributed by

Medicago minima (9111 individuals/ha) followed by Calamintha umbrosa, Viola canescens, Duchesnea indica and Oxalis corniculata. Their individuals cover/ha ranged from 567 cm2 to 284 cm2. Similar to community III the dominant shrub of this community was Berberis lycium while difference was found in density/ha and cover/ha. The second leading dominant shrub of this community was Wikstromia canesencs followed by Indigofera heterantha, Andrachne cordifolia and Isodon rugosus while, less contributing species were Sarcococca saligna, Viburnum cotinifolium, Myrsine africana and Lonicera asperifolia. Their density /ha and cover/ha mean values are presented in (Table. 4.14). The distribution of species is a dynamic phenomenon and it changes over time as a result of climatic change, anthropogenic disturbance, habitat preferences, and dispersal mechanisms of the species (Nkoa et al., 2015). Grubb et al. (1963) reported that in an undisturbed area density is closely related to slope while beside this slope angle, soil texture, available potassium, organic matter, nitrogen, lime and soil moisture differences are also responsible for the differences in density and distribution of vegetation (Barnes et al., 1997; Zare et al., 2011 and Block & Treter, 2001). Beside these factors the stem density of understory species is also altered by the presence of overstory species. A thick layer of overstory species reduced the density and cover of understory species. In the present finding, the density/ha and cover/ha showed a large variation from community to community, and it is assumed that density and cover not only depend upon various historical and environmental factors however, anthropogenic disturbance could be an overriding factor for their alteration as reported by others (Ahmed, 1984; Gairola et al., 2008).

Table 4.14. Density/ha and cover/ha of understory vegetation in different groups obtained through Ward‟s cluster analysis

S.No Species Voucher number Group I Group II Group III Group IV Mean±SE Mean±SE Mean±SE Mean±SE Density/ha Cover/ha Density/ha Cover/ha Density/ha Cover/ha Density/ha Cover/ha 1. Wikstroemia canescens Shariatullah Bot. 400±0 2062±0 408±144 1820±257 338±50 1863±52 272±0 1782±0 Wall. ex Meisn. 243 (PUP) 2. Berberis lyceum Royle. Shariatullah Bot. 67 316±0 2758±0 214±46 3985±1289 586±134 4538±223 428±0 3437±0 (PUP) 3. Indigofera heterantha Shariatullah Bot. 68±0 3800±0 44±32 4222±2382 246±18 5288±314 240±0 4256±0 Brandis. var. heterantha. 164 (PUP) 4. Cotinus coggygria Scop. Shariatullah Bot. 32 152±0 1784±0 44±4 3970±894 30±10 4026±298 40±0 1724±0 (PUP) 5. Cotoneaster nummularia Shariatullah Bot. 56±0 3563±0 168±56 3979±497 8±8 2455±2455 - - Fisch. & Mey. 216 (PUP) 6. Sarcococca saligna Muell. Shariatullah Bot. 75 556±0 2119±0 62±54 1605±405 404±80 2022±28 24±0 2833±0 Arg. (PUP) 7. Lonicera asperifolia Hook. Shariatullah Bot. 77 44±0 1400±0 96±56 1518±934 - - 8±0 6600±0 f. & Thomson. (PUP) 8. Spiraea canescens D. Don. Shariatullah Bot. 456±0 678±0 44±28 1047±235 144±48 1300±185 - - 206 (PUP) 9. Jasminum officinale L. Shariatullah Bot. 48±0 943±0 36±8 1258±39 84±48 1371±224 - - 146 (PUP) 10. Rabdosia rugosa (Wall. ex Shariatullah Bot. 16±0 5450±0 54±42 5648±148 10±10 2092±2092 - - Benth.) H. Hara. 117 (PUP) 11. Isodon rugosus (Wall. ex Shariatullah Bot. 460±0 2838±0 256±4 2730±242 208±12 2020±226 80±0 1644±0 Benth.) Codd. 116 (PUP) 12. Myrsine africana L. Shariatullah Bot. 12±0 1973±0 48±48 1087±1087 - - 16±0 1110±0 142 (PUP) 13. Andrachne cordifolia Shariatullah Bot. 44±0 1385±0 298±18 2091±429 120±8 2484±440 88±0 2116±0 (Decne.) Mull. Arg. 102 (PUP) 14. Parrotiopsis Shariatullah Bot. 76±0 8739±0 ------jacquemontiana (Decne.) 109 (PUP) Rehder. 15. Rosa webbiana Wall. ex Shariatullah Bot. - - 6±2 2750±450 18±10 3900±2100 - - Royle. 207 (PUP) 16. Desmodium elegans DC. Shariatullah Bot. - - 44±16 1750±116 10±10 1792±1792 56±0 1851±0 163 (PUP)

17. Viburnum cotinifolium D. Shariatullah Bot. 78 - - 4±4 450±450 14±2 2133±333 20±0 3040±0 Don. (PUP) 18. Rosa moschata Herrm Shariatullah Bot. - - 18±18 3040±304 38±18 4216±1348 36±0 3356±0 205 (PUP) 19. Daphne mucronata Royle. Shariatullah Bot. - - 42±42 2950±2950 - - - - 242 (PUP) 20. Duchesnea indica (Jacks.) Shariatullah Bot. 5644±0 472±0 2844±124 511±141 5422±1600 403±23 4889±0 424±0 Focke. 211 (PUP) 21. Ocimum basilicum L. Shariatullah Bot. 933 1111±0 289±289 385±385 311±311 238±238 578±0 769±0 124 (PUP) 22. Calamintha umbrosa (M. Shariatullah Bot. 4356±0 374±0 1667±1667 178±178 - - 6533±0 567±0 Bieb.) Fisch. & C.A. Mey. 129 (PUP) 23. Galium stewartii Nazim. Shariatullah Bot. 6178 384±0 556±556 133±133 - - 1333±0 333±0 219 (PUP 24. Oxalis corniculata L. Shariatullah Bot. 3911±0 417±0 6311±711 512±36 9400±378 309±52 4178±0 284±0 149 (PUP) 25. Androsace rotundifolia Shariatullah Bot. 44±0 3333±0 ------Hardw. subsp. glandulosa 189 (PUP) (Hook. f.) Y. J. Nasir. 26. Cynodon dactylon (L.) Shariatullah Bot. 2356±0 629±0 4378±67 709±91 9311±4733 549±1 667±0 1111±0 Pers. 176 (PUP) 27. Cyperus rotundus L. Shariatullah Bot. 95 2622±0 621±0 ------(PUP) 28. Themeda anathera (Nees Shariatullah Bot. 1333±0 2000±0 311±311 952±952 - - - - ex Steud.) Hack. 174 (PUP) 29. Cannabis sativa L. Shariatullah Bot. 76 489±0 1818±0 800±533 3944±1056 - - 400±0 4444±0 (PUP) 30. Conyza Canadensis (L.) Shariatullah Bot. 60 1200±0 864±0 1400±511 1043±43 1422±1022 859±253 889±0 1167±0 Cronquist. (PUP) 31. Tagetes minuta L. Shariatullah Bot. 61 267±0 1667±0 3800±244 1044±165 956±733 1728±939 356±0 1250±0 (PUP) 32. Mentha longifolia (L.) L. Shariatullah Bot. 444±0 1667±0 89±44 2222±111 578±578 769±769 - - 126 (PUP) 33. Rumex hastatus D. Don. Shariatullah Bot. 311±0 2381±0 1356±111 1912±7 3867±1733 1295±25 311±0 3333±0 182 (PUP) 34. Viola canescens Wall. Shariatullah Bot. 6489±0 434±0 1178±644 742±91 711±44 627±39 5822±0 458±0 249 (PUP) 35. Conyza bonariensis (L.) Shariatullah Bot. 45 667±0 222±0 356±356 313±313 - - 1333±0 556±0 Cronquist. (PUP)

36. Setaria viridis (L.) P. Shariatullah Bot. 800±0 370±0 - - - - 89±0 3333±0 Beauv. 181 (PUP) 37. Micromeria biflora Shariatullah Bot. 1111±0 400±0 378±22 787±46 1178±911 804±307 - - (Duch.-Ham ex D. Don.) 122 (PUP) Benth. 38. Plantago lanceolata L. Shariatullah Bot. 1067±0 278±0 22±22 1667±166 6667±4044 405±10 2222±0 400±0 169 (PUP) 39. Rumex dentatus L. Shariatullah Bot. 311±0 3333±0 756±89 2561±105 1022±133 2301±135 1067±0 2639±0 187 (PUP) 40. Impatiens bicolor Royle Shariatullah Bot. 65 1244±0 1548±0 1800±180 473±473 933±311 2024±357 1467±0 2424±0 subsp. pseudobicolor (PUP) (Grey-Wilson & Rech. f.) Y. J. Nasir. 41. Arisaema flavum (Forssk.) Shariatullah Bot. 41 578±0 2051±0 22±22 1667±1667 200±200 370±370 - - Schott. (PUP) 42. Swertia petiolata D. Don. Shariatullah Bot. 89±0 1667±0 ------105 (PUP) 43. Melilotus officinalis (L.) Shariatullah Bot. 311±0 476±0 ------Pall. 162 (PUP) 44. Valeriana wallichii DC. Shariatullah Bot. 89±0 3333±0 - - - - 756±0 2353±0 248 (PUP) 45. Seseli libanotis (L.) Koch. Shariatullah Bot. 40 578±0 1026±0 ------(PUP) 46. Bergenia ciliata (Haw.) Shariatullah Bot. 444±0 1000±0 ------Sternb. 227 (PUP) 47. Heliotropium undulatum Shariatullah Bot. 69 44±0 3333±0 ------Vahl. var. suberosa Clarke. (PUP) 48. Ajuga bracteosa Wall. ex Shariatullah Bot. 44±0 3333±0 ------Benth. 115 (PUP) 49. Foeniculum vulgare Mill. Shariatullah Bot. 37 44±0 16667±0 244±244 1667±166 - - - - (PUP) 50. Chenopodium album L. Shariatullah Bot. 82 222±0 6667±0 111±111 1000±1000 67±22 3333±0 267±0 3333±0 (PUP) 51. Amaranthus caudatus L. Shariatullah Bot. 30 444±0 5667±0 756±356 1659±193 178±44 1778±444 889±0 1833±0 (PUP) 52. Amaranthus spinosus L. Shariatullah Bot. 28 133±0 3333±0 267±267 556±556 - - - - (PUP) 53. Dysphania botrys (L.) Shariatullah Bot. 86 44±0 10000±0 ------Mosyakin & Clemants. (PUP)

54. Polygonum aviculare L. Shariatullah Bot. 356±0 2083±0 289±67 1375±708 1311±467 643±59 2444±0 667±0 184 (PUP) 55. Solanum nigrum L. var. Shariatullah Bot. 44±0 3333±0 111±111 667±667 67±67 556±556 444±0 1000±0 nigrum. 240 (PUP) 56. Xanthium strumarium L. Shariatullah Bot. 56 44±0 10000±0 44±44 4167±4167 - - - - (PUP) 57. Datura stramonium L. Shariatullah Bot. 178±0 2500±0 133±133 2222±222 22±22 1667±1667 - - 241 (PUP) 58. Artemisia scoparia Waldst. Shariatullah Bot. 54 133±0 1111±0 ------& Kitam. (PUP) 59. Malva neglecta Wallr. Shariatullah Bot. 44±0 3333±0 911±689 1833±167 178±178 1250±1250 311±0 1905±0 134 (PUP) 60. Polygonum maculosa L. Shariatullah Bot. 933±0 794±0 844±489 486±69 44±44 2500±2500 1156±0 1923±0 188 (PUP) 61. Dicliptera roxburghiana Shariatullah Bot. 24 844±0 175±0 2578±133 1234±22 1956±578 1221±285 667±0 1111±0 Nees. (PUP) 62. Urtica dioica L. Shariatullah Bot. - - 756±444 1631±273 1667±156 1107±519 1200±0 864±0 246 (PUP) 63. Galinsoga parviflora Cav. Shariatullah Bot. 62 - - 956±644 1270±159 1067±711 917±333 - - (PUP) 64. Taraxacum campylodes G. Shariatullah Bot. 53 - - 311±222 1250±417 178±0 833±0 311±0 952±0 E. Haglund. (PUP) 65. Oenothera speciosa Nutt. Shariatullah Bot. - - 22±22 1667±1667 - - - - 148 (PUP) 66. Clematis graveolens Lindl. Shariatullah Bot. - - 400±133 2361±139 333±156 1326±492 1067±0 1528±0 191 (PUP) 67. Cirsium falconeri (Hook. Shariatullah Bot. 47 - - 67±22 4167±833 89±0 5833±833 - - f.) Petr. (PUP) 68. Medicago minima (L.) L. Shariatullah Bot. - - 2667±133 704±148 3911±889 344±97 9111±0 455±0 158 (PUP) 69. Ranunculus laetus Wall. ex Shariatullah Bot. - - 378±378 1373±1373 - - 356±0 1250±0 Hook. f. & J.W. Thomson. 192 (PUP) 70. Nasturtium officinale R. Br. Shariatullah Bot. 74 - - 1111±1111 533±533 - - - - (PUP) 71. Chenopodium Shariatullah Bot. 85 - - 267±89 3958±1875 - - - - ambrosioides L. (PUP) 72. Bidens chinensis (L.) Shariatullah Bot. 52 - - 267±0 1389±278 444±89 903±347 133±0 1111±0 Willd. (PUP)

73. Filago hurdwarica (Wall. Shariatullah Bot. 64 - - 67±67 1111±1111 67±22 3333±0 1200±0 247±0 ex DC.) Wagenitz. (PUP) 74. Mentha arvensis L. Shariatullah Bot. - - - - 556±556 200±200 1244±0 1429±0 113 (PUP) 75. Myriactis wallichii Less. Shariatullah Bot. 57 - - - - 422±378 5370±4630 800±0 556±0 (PUP) 76. Euphorbia helioscopia L. Shariatullah Bot. - - 556±556 467±467 67±67 1667±1667 89±0 1667±0 100 (PUP) 77. Polygonum capitatum Shariatullah Bot. - - - - 111±67 2917±417 89±0 1667±0 Buch.-Ham. ex D. Don. 186 (PUP) 78. Achyranthes aspera L. var. Shariatullah Bot. 29 ------89±0 1667±0 pubescens (Moq.) M. (PUP) Gomez. 79. Epilobium hirsutum L. Shariatullah Bot. - - - - 400±89 628±325 267±0 1667±0 147 (PUP) 80. Commelina benghalensis L. Shariatullah Bot. 87 - - 311±311 238±238 2444±2444 288±288 - - (PUP) 81. Hedera nepalensis K. Shariatullah Bot. 43 - - 44±44 1667±1667 - - - - Koch. (PUP) 82. Girardinia palmata Shariatullah Bot. - - 400±400 926±926 422±422 1228±1228 - - (Forssk.) Gaudich. 247 (PUP) 83. Scutellaria chamaedrifolia Shariatullah Bot. - - - - 2867±1489 487±57 - - Hedge & A. J. Paton. 127 (PUP) 84. Ranunculus muricatus L. Shariatullah Bot. - - - - 1511±1156 403±14 - - 193 (PUP) 85. Poterium sanguisorba L. Shariatullah Bot. - - - - 311±311 357±357 - - 218 (PUP) 86. Thymus linearis Benth. Shariatullah Bot. - - - - 5556±5556 207±207 - - subsp. linearis Jalas 114 (PUP) 87. Hypericum perforatum L. Shariatullah Bot. - - - - 22±22 1667±1667 - - 110 (PUP) 88. Salvia lanata Roxb. Shariatullah Bot. - - - - 467±467 476±476 - - 118 (PUP) Total 50121 1.00E+05 45067 1.00E 70971 97620 56332 86426

EDAPHOLOGY

4.3 Edaphology Soil analysis is the only way for the determination of various available micro and macro nutrients status in the soil (Geetha et al., 2017). In the present study the soil was analyzed for various physiochemical properties. The results revealed that the clay % were (4.4%), silt (44%) and sand were found (51.6%). The soil was basic in nature, organic matter were (0.69%), while lime contents were (1%). Among the other nutrients, nitrogen contents were found (0.0345%), K (120 mg/kg), Cu (0.288 mg/kg), Zn (0.272 mg/kg), Fe (0.893 mg/kg), Mn (2.407 mg/kg), Pb (1.32 mg/kg), Ca (9.407 mg/kg), Mg (2.411 mg/kg) and Na (20.4 mg/kg). Similarly, the clay particles in the soil of Gul Dherai site were similar to Sore Pao but less than other sites. Sand particles were more than the soil of Gumbad but less than Sore Pao and Tangai Awar. The results also revealed that the soil of all the sites was acidic in nature while the difference was found in the pH values. The % of organic matter was higher in the soil of Gul Dherai, followed by Shao, Tangai Awar and Danda. Lime contents were recorded as 2.5% in Gul Dherai which were higher as compared to other sites. Among the other macro and micro nutrients in the soil of Gul Dherai nitrogen contents were (0.0345%), P (20.04 mg/kg), K (130 mg/kg), Cu (0.327 mg/kg), Zn (0.288 mg/kg), Fe (1.33 mg/kg), Mn (2.177 mg/kg), Pb (1.88 mg/kg), Ca (9.126 mg/kg), Mg (2.347 mg/kg) and Na (17.9 mg/kg). In Sore poa the clay particles (0.4%), silt (34%), sand (65.6%), organic matter (0.69%), lime (0.5%), N (0.0345%), P (20.04 mg/kg), K (130 mg/kg), Cu (0.327 mg/kg), Zn (0.288 mg/kg), Fe (1.33 mg/kg), Mn (2.177 mg/kg), Ca (9.126 mg/kg), Mg (2.347 mg/kg), Na (17.9 mg/kg) and Pb contents were found (1.88 mg/kg). In the soil of Shao, the clay particles were same in percentage to that of Danda while more than other sites, silt % were second highest while sand contents were low as compared to other sites. The soil of this site was also acidic while organic matter was more than the other sites. Lime contents were 2%, nitrogen contents were similar to the soil of Gumbad and phosphorus contents were maximum as compared to other while potassium contents were less than the soil of Gul Dherai and Danda. Among the other macro and micro nutrients the Cu contents in the soil of Shao were (0.245 mg/kg), Zn (0.138 mg/kg), Fe (0.879 mg/kg), Mn (1.885 mg/kg), Pb (1.13 mg/kg), Ca (9.948 mg/kg), Mg (2.372 mg/kg) and Na were (19.6 mg/kg). In the soil of Tangai Awar the clay particles were (2.2%), silt particles were minimum while sand particles contents were maximum as compared to other sites. The soil of this site was also acidic in nature, organic matter was (1.014%) and lime contents were similar to Gul Dherai soil while maximum than the soils of

other sites. Nitrogen contents were (0.552%), while the phosphorus contents were maximum as compared to Shao while minimum than the soil of other sites. Similarly, K contents were minimum than other sites, Cu contents were (0.233 mg/kg), while Zn contents were maximum as compared to others sites. Similarly, the Fe contents were found (0.998 mg/kg), Mn (6.82 mg/kg), Pb (1.62 mg/kg), Ca (9.883 mg/kg), Mg (2.193 mg/kg) and Na were found (16.6 mg/kg). The soil analysis of Danda revealed that the percentage of clay particles was maximum, silt contents were 3rd highest, sand were (57.6%) while pH value was recorded as (5.8) which also showing the acidic nature. Lime contents were found (1%), nitrogen (0.069%), P (7.63 mg/kg), Cu (0.322 mg/kg) while, the K contents were maximum as compared to the soil of other sites. Among the other macro and micro elements in the soil of Danda Zn were found (0.159 mg/kg), Fe (1.612 mg/kg), Mn (5.538 mg/kg), Pb (0.58 mg/kg), Ca (9.898 mg/kg), Mg (2.374 mg/kg) and Na was found (17.2 mg/kg) (Table. 4.15). 4.3.1 Univariate analysis of variance (ANOVA) of different edaphic parameters The soil corresponds to various study sites such as (Shao, Danda, Tangi Awar, Sore Pao, Gul Dherai and Gumbad) of Jelar valley were analyzed using one-way analysis of variance (ANOVA). The results revealed that all the physiochemical parameters in different sites showed significant variation at P<0.0001 (Table. 4.16, Fig. 17-33) except soil texture class which was found to be loamy sand in all study sites. The significant difference in various factors among different study sites may be due to the difference in altitude, slope angle and difference in plants communities. My findings were supported by Shrivastava & Kanungo (2014) who stated that the physico-chemical properties of the forests soil varied in space and time because variation in climate, topography, weathering processes, microbial activities and vegetation cover several other abiotic and biotic factors. My findings were also supported by Akbar (2013), Wani et al. (2014) who conducted similar study.

Table 4.15. Mean values of edaphic variables of different sampling sites

Parameters Gumbad Gul Dherai Sore Poa Shao Tangai Awar Danda Clay% 4.4 0.4 0.4 2.4 2.2 2.4 Silt% 44 40 34 42 36 40 Sand% 51.6 59.6 65.6 55.6 61.6 57.6 Texture class Loamy sand Loamy sand Loamy sand Loamy sand Loamy sand Loamy sand PH 1:5 5.6 6.2 6.2 5.4 5.8 5.8 O-M% 0.69 2.622 0.69 1.932 1.104 1.38 Lime% 1 2.5 0.5 2 2.5 1 N% 0.0345 0.1311 0.0345 0.966 0.552 0.069 P (mg/kg) 0 55.38 20.04 0.03 3.12 7.63 K (mg/kg) 120 360 130 110 90 180 Cu (mg/kg) 0.288 0.316 0.327 0.245 0.233 0.322 Zn (mg/kg) 0.272 0.911 0.288 0.138 0.987 0.159 Fe (mg/kg) 0.893 1.14 1.33 0.879 0.998 1.612 Mn (mg/kg) 2.407 4.546 2.177 1.885 6.82 5.538 Pb (mg/kg) 1.32 0.833 1.88 1.13 1.62 0.58 Ca (mg/kg) 9.407 9.985 9.126 9.948 9.883 9.898 Mg (mg/kg) 2.411 2.498 2.347 2.372 2.193 2.374 Na (mg/kg) 20.4 18.5 17.9 19.6 16.6 17.2

Table 4.16. (ANOVA) of individual edaphic variables in six sampling sites

Source of variation SS DF MS F P value Between Sites 21.82 5 4.364 1309 P<0.0001 1. Clay Within Site 0.02 12 0.003333 Total 21.84 17 Between Sites 240 5 48 48 P<0.0001 2. Silt Within Site 12 12 1 Total 252 17 Between Sites 365.2 5 73.04 1206 P<0.0001 3. Sand Within Site 0.7267 12 0.06056 Total 365.9 17 Between Sites 3.28 5 0.656 4.686 P<0.0001 4. pH Within Site 1.68 12 0.14 Total 4.96 17

Between Sites 8.795 5 1.159 1397 P<0.0001 5. O.M Within Site 0.01511 12 0.00126 Total 8.81 17 Between Sites 7.147 5 1.429 238.2 P<0.0001 6. Lime Within Site 3 12 0 Total 7.177 17 Between Sites 2.081 5 0.4161 1018 P<0.0001 7. N Within Site 0.004903 12 0.000409 Total 2.085 17 Between Sites 4540 5 907.9 557585 P<0.0001 8. P Within Site 0.007008 12 0.007008 Total 4543 17 Between Sites 100300 5 20060 40120 P<0.0001 9. K Within Site 3 12 0.5 Total 100303 17 Between Sites 0.04188 5 0.008375 7.922 P<0.0001 10. Cu Within Site 0.01269 12 0.991075 Total 0.05456 17 Between Sites 2.194 5 0.4388 1646 P<0.0001 11. Zn Within Site 0.003199 12 0.000267 Total 2.197 17 Between Sites 1.317 5 0.2634 188.5 P<0.0001 12. Fe Within Site 0.01677 12 0.001398 Total 1.334 17 Between Sites 63.04 5 8.371 8708 P<0.0001 13. Mn Within Site 0.01738 12 0.001448 Total 63.06 17 Between Sites 3.558 5 0.7115 587.3 P<0.0001 14. Pb Within Site 0.01454 12 0.001212 Total 3.572 17 Between Sites 1.261 5 0.2522 5043003 P<0.0001 15. Ca Within Site 3e-.006 12 5.00E-07 Total 1.261 17 Between Sites 0.1564 5 0.03129 18.24 P<0.0001 16. Mg Within Site 0.02058 12 0.001715 Total 0.177 17 Between Sites 30.78 5 6.155 86.62 P<0.0001 17. Na Within Site 0.8527 12 0.07106 Total 31.63 17

S ilt C la y 5 0 5

4 5

3 %

4 0 Silt Clay% 2 3 5 1

0 3 0 i d e l o a a r u a a g d l t b o G h n G s u o d S n a a m s a g h u t d s G

Fig. 17. Difference in clay particles in different sites Fig. 18. Difference in silt particles found in different sites

S a n d P h

8 0 7 .0

6 0 6 .5

values

4 0 6 .0

pH Sand 2 0 5 .5

0 5 .0

l t l t g s o d g s u o d u h h g s g s

Fig. 19. Difference in sand particles in different sites Fig. 20. Difference in pH values in different sites

L im e O . M

3 3

% 2

% 2 Lime

matter matter 1

- 1 O

0 0 l l t g s o t d g s u o d u h h g s g s

Fig. 21. Difference in organic matter in different sites Fig. 22. Difference in lime contents in different sites

P N 6 0

1 .5

4 0

1 .0

mg/kg

N P

0 .5 2 0

0 .0 0

l t g s l o t d g s u o d u h g h g s s

Fig. 23. Difference in nitrogen contents in different sites Fig. 24. Difference in phosphorus contents in different sites

K C u

4 0 0 0 .3 5

3 0 0

0 .3 0 mg/kg

2 0 0

mg/kg

Cu K 0 .2 5 1 0 0

0 0 .2 0

l t l t g s u o d g s o d h u h g s g s

Fig. 25. Difference in potassium contents in different sites Fig. 26. Difference in Cu contents in different sites

F e Z n

2 .0

1 .5

1 .0

mg/kg

mg/kg 1 .0

Zn 0 .5 0 .5

0 .0 0 .0 l l t g s o t d g s u o d u h g h g s s

Fig. 27. Difference in Zn contents in different sites Fig. 28. Difference in Fe contents in different sites

M n P b

8 2 .0

1 .5

4 1 .0

mg/kg

2 0 .5 Mn

0 0 .0 l l g s o t d g s o t d u h u h g s g s

Fig. 29. Difference in Mn contents in different sites Fig. 30. Difference in Pb contents in different sites

N a C a 2 2 1 0 .5

2 0

1 0 .0

1 8

9 .5 mg/kg

mg/kg

Na 1 6 Ca 9 .0

8 .5 1 4 l t g s l o t d g s u o d u h g h g s s

Fig. 31. Difference in Ca contents in different sites Fig. 32. Difference in Na contents in different sites

M g

2 .8

2 .6

2 .4

mg/kg

Mg 2 .2

2 .0

g s l o t d u h g s

Fig. 33. Difference in Mg contents in different sites

PALATABILITY

4.4 Palatability of vegetation 4.4.1 Degree of palatability Palatability is defined as the acceptability or the relative preference of plants by grazing animals. The acceptability of species may be affected by different attributes of species such as their types, growth stages and chemical composition as well as selective responses by grazing animals (Heady, 1964). In the present study the plants were classified on the basis of their palatability. The results revealed that out of 250 species, 55 (22%) were found as non-palatable. Some of the non-palatable species are Pinus roxburghii, Pinus wallichiana, Sarcococca saligna, Daphne mucronata, Wikstroemia canescens, Dodonaea viscosa, Ranunculus laetus, Artemisia scoparia, Leontopodium leontopodinum, Polygonum maculosa, Xanthium strumarium, Mirabilis jalapa, Euphorbia helioscopia, Nasturtium officinale, Datura stramonium, Teucrium stocksianum, Dysphania botrys, Polygonum posumbu, Onopordum acanthium, Cannabis sativa and Datura innoxia (Table. 4.17). The non-palatable nature of these species was due to unpleasant odour, chemical composition and some textural morphology as reported by (Badshah & Hussain, 2011; Amjad et al., 2014 and Abdullah et al., 2017). A total of 195 (78%) species were recorded as palatable. Among them, trees were 38, shrubs 26, herbs 111 and pteridophytes were 19 in numbers (Table. 4.17). Gorade & Datar (2014) reported that severe grazing pressure of livestock‟s increase the number of non-palatable species in the area. My finding is a deviation from the above finding as the numbers of palatable species are found high in the area as compared to non-palatable species. The reason may be other demand of these non-palatable species such as fuels demand, fences, and medicinal uses. The palatable species were further classified into three categories based on the preference of livestock‟s and found that 99 (39.6%) species were highly palatable. Some of these highly palatable plants were Robinia pseudo-acacia, Ziziphus oxyphylla, Ailanthus altissima, Ziziphus sativa, Celtis australis, Indigofera heterantha, Parrotiopsis jacquemontiana, Myrsine africana, Rosa moschata, Chenopodium album, Bidens chinensis, Cyperus rotundus, Cynodon dactylon, Zea mays, Triticum aestivum, Medicago minima, Phaseolus vulgaris, Brassica campestris, Cucumis sativus, Trifolium repens, Hordeum vulgare, Spinacia oleracea, Oryza sativa, Pisum sativum and Lathyrus aphaca. Fifty-one (20.4%) species were found less palatable while only 45 (18%) species were recorded as rarely palatable (Fig. 34). Similar study was conducted by Badshah (2011) from district Tank and reported 205 plants including 56 non-palatable and 149

palatable species. Amjad et al. (2014) reported 110 plants while working on the palatability of vegetation of Nikyal (Azad Kashmir) and found 45% non-palatable and 55% palatable. Many of these species are also reported by them as highly palatable. 4.4.2 Classification based on livestock preferences Palatability of plants depends upon nutritional need of animals and declines as need are met (Provenza, 1995). The results revealed that all the palatable species found in the area were browsed by goats while sheep preferred to graze 172 species. These species include 18% trees, 13.4% shrubs, 57.6% herbs and 11% pteridophytes. Cow prefers 110 plants species including 13.6% trees, 10.9% shrubs, 61.8% herbs and 13% pteridophytes while buffalo prefered 71 species in which 14.1% were trees, 12.7% shrubs 60.6% herbs and 12.7% pteridophytes (Table. 4.18, Fig. 35). The present study also revealed that the livestock mostly prefers herbaceous flora followed by trees species. Similar study was conducted by Angassa & Baars (2001), Husain & Durrani (2007), Badshah (2011) and Ali (2016) stated that goat and sheep usually preferred shrub and herbaceous flora while other cattle preferred grasses. 4.4.3 Classification of palatable plants by part used The palatability of species is reduced by various characteristics adopted by plants. These may be morphological such as the presence of hair, spines, thorns, rigidity, unpleasant odor or chemical compounds such as poisons or other indigestible materials, mineral contents and nutritive value which cause variation in selection of different plants parts by grazing animals (Wahid, 1990; Milewski & Madden, 2006; Khan et al., 2012 and Amjad et al., 2014). Plants were also classified based on their part consumed by the livestock. The results showed that 98 (49%) species were consumed by the animals as whole. Some of these are Setaria viridis, Valeriana wallichii, Chenopodium album, Commelina benghalensis, Galium stewartii, Cyperus rotundus, Oxalis corniculata, Viola canescens, Amaranthus spinosus, Amaranthus caudatus, Malva neglecta, Solanum nigrum, var. villosum, Dicliptera roxburghiana, Clematis graveolens, Solanum nigrum, var. nigrum, Rumex hastatus, Cynodon dactylon, Medicago minima, Brassica campestris, Lathyrus aphaca, Origanum vulgare, Geranium collinum, Astragalus affghanus, Plantago lanceolata and Mentha arvensis. In 89 (44.55%) species leaves were used while in 13 (6.5%) species inflorescence was consumed by livestock (Table. 4.19, Fig. 36). The present study is in line with Abdullah et al. (2017) and Hussain & Durani (2009a) who conducted similar

studies. My finding is also in agreement with Hussain et al. (2009) who reported that whole plants preferred mostly followed by leaves and inflorescence. 4.4.4 Classification of palatable plants species by condition In the present study 116 (59.5%) species were used by the livestock in fresh condition like Pistacia chinensis, Quercus incana, Melia azedarach, Ailanthus altissima, Punica granatum and Ziziphus sativa, while Ficus carica and Cosmos bipinnatus were consumed in dried condition and 77 (39.5%) species were used both in fresh and dried condition. Sorbaria tomentosa, Ranunculus muricatus, Impatiens bicolor, Viburnum cotinifolium, Conyza bonariensis, Cyperus rotundus and Oxalis corniculata were mainly utilized both in fresh and dried (Table. 4.17, Fig. 38). In general livestock mostly prefer green foliage of species because they are easily digestible as compared to dried plants materials while, the choice of dried plants material decline due to the loss of taste, feel and nutrition value of the materials ((Holechek & Galt, 2000; Amjad et al., 2014). In drought and winter seasons, dried fodder and trees become the only supply of fodder to the livestock.

Table 4.17. Palatability, part used, condition and animal preferences of plants

Species Voucher number Palatability classes Part used Condition Livestock NP P HP LP RP W L I F D B G S C B S.No A. Trees 1. Pinus roxburghii Sarg. Shariatullah Bot. 22 (PUP) + ------2. Populus nigra L. Shariatullah Bot. 225 (PUP) - + + - - - + - - - + + + + + 3. Pistacia chinensis Bunge subsp. integerrima Shariatullah Bot. 31 (PUP) - + - + - - + - + - - + + - - (J. L. Stewart ex Brandis.) Rech. f. 4. Quercus incana Bartram. Shariatullah Bot. 103 (PUP) - + - + - - + - + - - + + - - 5. Ficus serrata L. Shariatullah Bot. 141 (PUP) - + - - + - + - + - - + + + + 6. Salix tetrasperma Roxb. Shariatullah Bot. 223 (PUP) - + - + - - + - + - - + + - - 7. Pinus wallichiana A.B. Jacks. Shariatullah Bot. 23 (PUP) + ------8. Robinia pseudo-acacia L. Shariatullah Bot. 155 (PUP) - + + - - - + + + - - + + + - 9. Broussonetia papyrifera (L.) L „Her. ex Vent. Shariatullah Bot. 136 (PUP) - + - + - - + - + - - + + - - 10. Melia azedarach L. Shariatullah Bot. 135 (PUP) - + - + - - + - + - - + + - - 11. Alnus nitida (Spach.) Endl. Shariatullah Bot. 68 (PUP) - + - + - - + - + - - + + - - 12. Sorbaria tomentosa (Lindl.) Rehder. Shariatullah Bot. 215 (PUP) - + + - - - + + - - + + + - - 13. Ziziphus oxyphylla Edgew. Shariatullah Bot. 199 (PUP) - + + - - - + - - - + + + - - 14. Quercus dilatata Royle. Shariatullah Bot. 104 (PUP) - + - + - - + + - - + + + - - 15. Ailanthus altissima (Mill.) Swingle. Shariatullah Bot. 231 (PUP) - + + - - - + - + - - + + - - 16. Punica granatum L. Shariatullah Bot. 190 (PUP) - + - - + - + - + - - + - - - 17. Celtis caucasica Willd. Shariatullah Bot. 244 (PUP) - + + - - - + - + - - + + + + 18. Ficus carica L. Shariatullah Bot. 140 (PUP) - + - - + - + - - + - + + - - 19. Prunus persica (L.) Batsch. Shariatullah Bot. 200 (PUP) - + - - + - + - + - - + + - - 20. Prunus domestica L. Shariatullah Bot. 201 (PUP) - + + - - - + - - - + + + + + 21. Diospyros lotus L. Shariatullah Bot. 97 (PUP) - + - - + - + - + - - + + + + 22. Diospyros kaki L. f. Shariatullah Bot. 96 (PUP) - + - - + - + - + - - + + + + 23. Morus nigra L. Shariatullah Bot. 138 (PUP) - + + - - - + + - - + + - - 24. Olea ferruginea Royle. Shariatullah Bot. 145 (PUP) - + + - - - + + - - + + + - - 25. Pyrus pashia Buch. -Ham. ex D. Don. Shariatullah Bot. 214 (PUP) - + + - - - + - - - + + + + + 26. Zanthoxylum armatum DC. Shariatullah Bot. 220 (PUP) - + - + - - + - + - - + + - - 100

27. Celtis australis L. Shariatullah Bot. 245 (PUP) - + + - - - + - - - + + - - - 28. Morus alba L. Shariatullah Bot. 139 (PUP) - + + - - - + - + - - + + - - 29. Pyrus malus L. Shariatullah Bot. 213 (PUP) - + - - + - + - + - - + + + - 30. Prunus armeniaca L. Shariatullah Bot. 202 (PUP) - + - + - - + - + - - + + - - 31. Pyrus communis L. Shariatullah Bot. 204 (PUP) - + - - + - + - + - - + + - - 32. Salix alba L. Shariatullah Bot. 224 (PUP) - + + - - - + - - - + + + + + 33. Juglans regia L. Shariatullah Bot. 111 (PUP) - + - - + - + - + - - + - - - 34. Platanus orientalis L. Shariatullah Bot. 171 (PUP) - + - + - - + - + - - + - + - 35. Vitis vinifera L. Shariatullah Bot. 250 (PUP) - + + - - + - - + - - + - + + 36. Ziziphus sativa Gaertn. Shariatullah Bot. 198 (PUP) - + + - - - + + + - - + - + - 37. Ficus foveolata (Wall. ex Miq.) Miq. Shariatullah Bot. 137 (PUP) - + - - + - + - - - + + + - - 38. Capsicum frutescens L. Shariatullah Bot. 234 (PUP) + ------39. Citrus sinensis (L.) Osbeck. Shariatullah Bot. 221 (PUP) - + - - + - + - + - - + - + - 40. Pyrus pyrifolia (Burm. f.) Nakai. Shariatullah Bot. 203 (PUP) - + - + - - + - + - - + + - - 41. Populus alba L. Shariatullah Bot. 222 (PUP) - + + - - - + - - - + + + + + B. Shrubs 42. Rosa webbiana Wall. ex Royle. Shariatullah Bot. 207 (PUP) - + - + - - + - + - - + + - - 43. Parrotiopsis jacquemontiana (Decne.) Shariatullah Bot. 109 (PUP) - + + - - + - - - - + + + + + Rehder. 44. Buddleja crispa Benth. Shariatullah Bot. 132 (PUP) + ------45. Rosa canina L. Shariatullah Bot. 217 (PUP) - + - - + - + - + - - + + - - 46. Rubus ellipticus Sm. Shariatullah Bot. 210 (PUP) - + - + - + - - + - - + + - - 47. Isodon rugosus (Wall. ex Benth.) Codd. Shariatullah Bot. 116 (PUP) - + - + - - + - + - - + + + + 48. Andrachne cordifolia (Decne.) Mull. Arg. Shariatullah Bot. 102 (PUP) + ------49. Desmodium elegans DC. Shariatullah Bot. 163 (PUP) - + + - - + - - - - + + + + + 50. Sarcococca saligna Muell. Arg. Shariatullah Bot. 75 (PUP) + ------51. Daphne mucronata Royle. Shariatullah Bot. 242 (PUP) + ------52. Sageretia thea (Osbeck) M.C. Johnst. Shariatullah Bot. 196 (PUP) - + - + - - + - - - + + + - - 53. Rhamnus pentapomica R. Parker. Shariatullah Bot. 197 (PUP) - + + - - - + - - - + + + - - 54. Viburnum cotinifolium D. Don. Shariatullah Bot. 78 (PUP) - + + - - + - - - - + + - - - 55. Cotinus coggygria Scop. Shariatullah Bot. 32 (PUP) - + - + - - + - - - + + + - - 56. Rosa moschata Herrm. Shariatullah Bot. 205 (PUP) - + + - - + - - - - + + + - -

101

57. Wikstroemia canescens Wall. ex Meisn. Shariatullah Bot. 243 (PUP) + ------58. Berberis lycium Royle. Shariatullah Bot. 67 (PUP) - + - + - + - - - - + + - - - 59. Spiraea canescens D. Don. Shariatullah Bot. 206 (PUP) - + - + - - + - + - - + + + + 60. Cotoneaster nummularia Fisch. & Mey. Shariatullah Bot. 216 (PUP) - + - + - - + - + - - + + - - 61. Lonicera asperifolia Hook. f. & Thomson. Shariatullah Bot. 77 (PUP) - + + - - - + - - - + + + - - 62. Indigofera heterantha Brandis. var. Shariatullah Bot. 164 (PUP) - + + - - + - - + - - + + + + heterantha. 63. Myrsine africana L. Shariatullah Bot. 142 (PUP) - + + - - - + - - - + + + - - 64. Jasminum humile L. Shariatullah Bot. 144 (PUP) - + + - - - + - - - + + + + + 65. Jasminum officinale L. Shariatullah Bot. 146 (PUP) - + + - - + - - + - - + + + + 66. Rubus ulmifolius Schott. Shariatullah Bot. 209 (PUP) - + - - + - + - + - - + + - - 67. Elaeagnus umbellata Thunb. Shariatullah Bot. 98 (PUP) - + - + - + - - - - + + + - - 68. Rabdosia rugosa (Wall. ex Benth.) H. Hara. Shariatullah Bot. 117 (PUP) - + - + - - + - + - - + + + + 69. Dodonaea viscosa (L.) Jacq. Shariatullah Bot. 226 (PUP) + ------70. Periploca aphylla Decne. Shariatullah Bot. 44 (PUP) - + - - + + - - + - - + - + - 71. Rosa brunonii Lindl. Shariatullah Bot. 212 (PUP) - + - + - - + - + - - + + + - 72. Rosa alba L. Shariatullah Bot. 208 (PUP) - + - + - - + - + - - + + + - 73. Indigofera heterantha Brandis var. Shariatullah Bot. 154 (PUP) - + + - - + - - + - - + + + + gerardiana (Baker) Ali. C. Herbs 74. Conyza bonariensis (L.) Cronquist. Shariatullah Bot. 45 (PUP) - + + - - + - - - - + + + + + 75. Ranunculus laetus Wall. ex Hook. f. & J.W. Shariatullah Bot. 192 (PUP) + ------Thomson. 76. Artemisia scoparia Waldst. & Kitam. Shariatullah Bot. 54 (PUP) + ------77. Artemisia biennis Willd. Shariatullah Bot. 50 (PUP) - + - - + + - - + - - + + + - 78. Cosmos bipinnatus Cav. Shariatullah Bot. 55 (PUP) - + - - + - + - - + - + + - - 79. Tagetes minuta L. Shariatullah Bot. 61 (PUP) - + - + - + - - - - + + + - - 80. Leontopodium leontopodinum (DC.) Hand.- Shariatullah Bot. 49 (PUP) + ------Mazz. 81. Melilotus officinalis (L.) Pall. Shariatullah Bot. 162 (PUP) - + + - - - + - - - + + + - - 82. Setaria viridis (L.) P. Beauv. Shariatullah Bot. 181 (PUP) - + + - - + - - - - + + + + + 83. Valeriana wallichii DC. Shariatullah Bot. 248 (PUP) - + + - - + - - - - + + + + - 84. Limonium cabulicum (Boiss.) Kuntze. Shariatullah Bot. 172 (PUP) - + - - + + - - - - + + + + +

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85. Bidens chinensis (L.) Willd. Shariatullah Bot. 52 (PUP) - + + - - - + - + - - + + + + 86. Polygonum maculosa L. Shariatullah Bot. 188 (PUP) + ------87. Cirsium falconeri (Hook. f.) Petr. Shariatullah Bot. 47 (PUP) - + - + - - + - + - - - - + + 88. Xanthium strumarium L. Shariatullah Bot. 56 (PUP) + ------89. Oenothera speciosa Nutt. Shariatullah Bot. 148 (PUP) - + - + - + - - - - + + + + + 90. Scutellaria chamaedrifolia Hedge & A. J. Shariatullah Bot. 127 (PUP) - + - - + + - - + - - + + - - Paton. 91. Gnaphalium affine D. Don. Shariatullah Bot. 48 (PUP) + ------92. Chenopodium album L. Shariatullah Bot. 82 (PUP) - + + - - + - - + - - + + + - 93. Commelina benghalensis L. Shariatullah Bot. 87 (PUP) - + + - - + - - + - - + + + + 94. Swertia petiolata D. Don. Shariatullah Bot. 105 (PUP) - + - - + + - - + - - + + - - 95. Galium stewartii Nazim. Shariatullah Bot. 219 (PUP - + + - - + - - - - + + + + + 96. Myriactis wallichii Less. Shariatullah Bot. 57 (PUP) - + + - - + - - + - - + + - - 97. Seseli libanotis (L.) Koch. Shariatullah Bot. 40 (PUP) + ------98. Polygonum capitatum Buch.-Ham. ex D. Shariatullah Bot. 186 (PUP) - + - - + + - - + - - + + + + Don. 99. Cyperus niveus Retz. Shariatullah Bot. 94 (PUP) - + + - - + - - - - + + + + + 100. Delphinium ajacis L. Shariatullah Bot. 194 (PUP) - + - + - + - - - - + + + + + 101. Mirabilis jalapa L. Shariatullah Bot. 143 (PUP) + ------102. Achyranthes aspera L. var. pubescens (Moq.) Shariatullah Bot. 29 (PUP) - + - + - + - - + - - + + - - M. Gomez. 103. Swertia ciliata (D. Don ex G. Don.) B.L. Shariatullah Bot. 106 (PUP) - + + - - + - - + - - + - - - Burtt. 104. Ranunculus muricatus L. Shariatullah Bot. 193 (PUP) - + - + - - - + - - + + + - - 105. Epilobium hirsutum L. Shariatullah Bot. 147 (PUP) - + - - + - + - + - - + + - - 106. Calamintha umbrosa (M. Bieb.) Fisch & Shariatullah Bot. 129 (PUP) - + - - + + - - - - + + + - - C.A. Mey. 107. Heliotropium undulatum Vahl. var. suberosa Shariatullah Bot. 69 (PUP) - + + - - - + - + - - + + - - Clarke. 108. Scrophularia umbrosa Dumort. Shariatullah Bot. 228 (PUP) - + - + - + - - - - + + + - - 109. Duchesnea indica (Jacks.) Focke. Shariatullah Bot. 211 (PUP) - + + - - + - - - - + + + + - 110. Geranium wallichianum D. Don. ex Sweet. Shariatullah Bot. 107 (PUP) - + + - - + - - + - - + + + + 111. Ajuga bracteosa Wall. ex Benth. Shariatullah Bot. 115 (PUP) - + - + - - + - + - - + + + + 112. Scrophularia nodosa L. Shariatullah Bot. 230 (PUP) - + - + - + - - - - + + + - -

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113. Cyperus rotundus L. Shariatullah Bot. 95 (PUP) - + + - - + - - - - + + + + + 114. Bergenia ciliata (Haw.) Sternb. Shariatullah Bot. 227 (PUP) - + + - - - + - - - + + + + - 115. Poterium sanguisorba L. Shariatullah Bot. 218 (PUP) - + - - + - + - + - - + + - - 116. Euphorbia helioscopia L. Shariatullah Bot. 100 (PUP) + ------117. Oxalis corniculata L. Shariatullah Bot. 149 (PUP) - + + - - + - - - - + + + + + 118. Nasturtium officinale R. Br. Shariatullah Bot. 74 (PUP) + ------119. Salvia moorcroftiana Wall. ex Benth. Shariatullah Bot. 119 (PUP) - + + - - - + - - - + + + + - 120. Viola canescens Wall. Shariatullah Bot. 249 (PUP) - + + - - + - - - - + + + + + 121. Hedera nepalensis K. Koch. Shariatullah Bot. 43 (PUP) - + - + - + - - - - + + + + - 122. Datura stramonium L. Shariatullah Bot. 241 (PUP) + ------123. Conyza canadensis (L.) Cronquist. Shariatullah Bot. 60 (PUP) - + - - + - + - + - - + + - - 124. Teucrium stocksianum Boiss. Shariatullah Bot. 130 (PUP) + ------125. Dysphania botrys (L.) Mosyakin & Shariatullah Bot. 86 (PUP) + ------Clemants. 126. Cerastium fontanum Baumg. Shariatullah Bot. 80 (PUP) - + - - + + - - - - + + + - - 127. Micromeria biflora (Duch.-Ham ex D.Don.) Shariatullah Bot. 122 (PUP) + ------Benth. 128. Phagnalon niveum Edgew. Shariatullah Bot. 46 (PUP) + ------129. Amaranthus spinosus L. Shariatullah Bot. 28 (PUP) - + + - - + - - - - + + + + - 130. Amaranthus caudatus L. Shariatullah Bot. 30 (PUP) - + + - - + - - - - + + + + - 131. Girardinia palmata (Forssk.) Gaudich. Shariatullah Bot. 247 (PUP) + ------132. Smilax glaucophylla Klotzsch. Shariatullah Bot. 232 (PUP) + ------133. Deutzia staminea R. Br. ex Wall. Shariatullah Bot. 167 (PUP) - + - + - - + - + - - + + - - 134. Euphorbia peplus L. Shariatullah Bot. 101 (PUP) + ------135. Bidens cernua L. Shariatullah Bot. 51 (PUP) + ------136. Medicago lupulina L. Shariatullah Bot. 157 (PUP) - + + - - - + - + - - + + + + 137. Malva neglecta Wallr. Shariatullah Bot. 134 (PUP) - + + - - + - - + - - + + - - 138. Urtica dioica L. Shariatullah Bot. 246 (PUP) + ------139. Androsace rotundifolia Hardw. subsp. Shariatullah Bot. 189 (PUP) - + + - - + - - + - - + + + - glandulosa (Hook. f.) Y. J. Nasir. 140. Pteracanthus urticifolius (Wall. ex Kuntze.) Shariatullah Bot. 25 (PUP) + ------Bremek. 141. Origanum vulgare L. Shariatullah Bot. 125 (PUP) - + - - + + - - + - - + + - -

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142. Salvia nubicola Wall. ex Sweet. Shariatullah Bot. 120 (PUP) - + + - - - + - + - - + + + + 143. Solanum nigrum L. var. villosum L. Shariatullah Bot. 237 (PUP) - + + - - + - - + - - + + + + 144. Dicliptera roxburghiana Nees. Shariatullah Bot. 24 (PUP) - + + - - + - - + - - + + + + 145. Taraxacum campylodes G. E. Haglund. Shariatullah Bot. 53 (PUP) - + - - + - + - + - - + + - - 146. Clematis graveolens Lindl. Shariatullah Bot. 191 (PUP) - + + - - + - - + - - + + + - 147. Filago hurdwarica (Wall. ex DC.) Wagenitz. Shariatullah Bot. 64 (PUP) + ------148. Foeniculum vulgare Mill. Shariatullah Bot. 37 (PUP) + ------149. Bistorta amplexicaulis (D. Don.) Greene. Shariatullah Bot. 183 (PUP) + ------150. Trachydium roylei Lindl. Shariatullah Bot. 35 (PUP) - + - - + + - - + - - + + - - 151. Impatiens bicolor Royle subsp. pseudo- Shariatullah Bot. 65 (PUP) - + - - + - - + - - + + + + + bicolor (Grey-Wilson & Rech. f.) Y.J. Nasir. 152. Thymus linearis Benth. subsp. linearis jalas. Shariatullah Bot. 114 (PUP) - + - + - + - - - - + + + + - 153. Dichanthium annulatum (Forssk.) Stapf. Shariatullah Bot. 175 (PUP) - + + - - + - - - - + + + + + 154. Euphorbia pilulifera L. Shariatullah Bot. 99 (PUP) + ------155. Chaerophyllum reflexum Aitch. Shariatullah Bot. 36 (PUP) - + + - - + - - - - + + + + + 156. Astragalus grahamianus Benth. Shariatullah Bot. 156 (PUP) - + - + - - + - + - - + - - - 157. Geranium collinum Stephan ex Willd. Shariatullah Bot. 108 (PUP) - + - + - + - - - - + + + - - 158. Trigonella gracilis Benth. Shariatullah Bot. 159 (PUP) - + - + - - + - + - - + + - - 159. Astragalus affghanus Boiss. Shariatullah Bot. 153 (PUP) - + - + - + - - + - - + + - - 160. Hyoscyamus niger L. Shariatullah Bot. 236 (PUP) + ------161. Polygonum posumbu Buch. -Ham. ex D. Shariatullah Bot. 185 (PUP) + ------Don. 162. Cynoglossum lanceolatum Forssk. Shariatullah Bot. 71 (PUP) - + - - + - + - - - + + + + + 163. Chenopodium ambrosioides L. Shariatullah Bot. 85 (PUP) + ------164. Onopordum acanthium L. Shariatullah Bot. 63 (PUP) + ------165. Cannabis sativa L. Shariatullah Bot. 76 (PUP) + ------166. Myosotis alpestris F.W. Schmidt var. Shariatullah Bot. 70 (PUP) - + + - - - + - + - - + + - - albicans (Riedl.) Y. J. Nasir. 167. Silene conoidea L. Shariatullah Bot. 81 (PUP) - + - + - - + - + - - + + - - 168. Silene vulgaris (Moench.) Garcke. Shariatullah Bot. 79 (PUP) - + - + - - + - + - - + + - - 169. Impatiens brachycentra Kar. & Kir. Shariatullah Bot. 66 (PUP) - + - - + + - - + - - + + - - 170. Galinsoga parviflora Cav. Shariatullah Bot. 62 (PUP) - + + - - + - - - - + + + + + 171. Datura innoxia Mill. Shariatullah Bot. 235 (PUP) + ------

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172. Chenopodium foliosum Asch. Shariatullah Bot. 84 (PUP) + ------173. Rumex dentatus L. Shariatullah Bot. 187 (PUP) - + + - - - + - + - - + + + + 174. Teucrium royleanum Wall. ex Benth. Shariatullah Bot. 131 (PUP) + ------175. Verbascum thapsus L. Shariatullah Bot. 229 (PUP) - + - - + + - - - - + + + + + 176. Solanum nigrum L. var. nigrum. Shariatullah Bot. 240 (PUP) - + + - - + - - + - - + + + + 177. Mentha longifolia (L.) L. Shariatullah Bot. 126 (PUP) + ------178. Arisaema flavum (Forssk.) Schott. Shariatullah Bot. 41 (PUP) + ------179. Lespedeza juncea (L. f.) Pers. Shariatullah Bot. 165 (PUP) - + - + - + - - + - - + + - - 180. Polygonum aviculare L. Shariatullah Bot. 184 (PUP) + ------181. Rumex hastatus D. Don. Shariatullah Bot. 182 (PUP) - + + - - + - - - - + + + + + 182. Plantago lanceolata L. Shariatullah Bot. 169 (PUP) - + - + - + - - - - + + + - - 183. Plantago major L. Shariatullah Bot. 168 (PUP) - + - + - + - - - - + + + - - 184. Plantago ovata Forssk. Shariatullah Bot. 170 (PUP) - + - + - + - - - - + + + - - 185. Hypericum perforatum L. Shariatullah Bot. 110 (PUP) - + - - + - - + + - - + + - - 186. Salvia lanata Roxb. Shariatullah Bot. 118 (PUP) - + + - - - + - + - - + + + + 187. Cynodon dactylon (L.) Pers. Shariatullah Bot. 176 (PUP) - + + - - + - - + - - + + + + 188. Mentha arvensis L. Shariatullah Bot. 113 (PUP) - + - - + + - - + - - + + - - 189. Zea mays L. Shariatullah Bot. 177 (PUP) - + + - - + - - - - + + + + + 190. Triticum aestivum L. Shariatullah Bot. 178 (PUP) - + + - - + - - - - + + + + + 191. Allium sativum L. Shariatullah Bot. 26 (PUP) - + - - + - + - + - - + + + + 192. Allium cepa L. Shariatullah Bot. 27 (PUP) - + - - + - + - + - - + + + + 193. Medicago minima (L.) L. Shariatullah Bot. 158 (PUP) - + + - - + - - - - + + + - - 194. Phaseolus vulgaris L. Shariatullah Bot. 151 (PUP) - + + - - - + - + - - + + + - 195. Ocimum basilicum L. Shariatullah Bot. 124 (PUP) + ------196. Brassica campestris L. Shariatullah Bot. 72 (PUP) - + + - - + - - + - - + - + + 197. Solanum tuberosum L. Shariatullah Bot. 233 (PUP) - + - - + - + - + - - + + - - 198. Lycopersicon esculentum Mill. Shariatullah Bot. 238 (PUP) - + - - + - + - + - - + + - - 199. Abelmoschus esculentus (L.) Moench. Shariatullah Bot. 133 (PUP) - + - + - - - + + - - + - + - 200. Cucumis sativus L. Shariatullah Bot. 91 (PUP) - + + - - - - + + - - + - + - 201. Cucurbita maxima Duchesne. Shariatullah Bot. 92 (PUP) - + - - + - + - + - - + - + - 202. Capsicum annuum L. Shariatullah Bot. 239 (PUP) - + - - + - + - - - + + + + + 203. Coriandrum sativum L. Shariatullah Bot. 38 (PUP) + ------

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204. Trachyspermum ammi (L.) Sprague. Shariatullah Bot. 39 (PUP) + ------205. Ammi visnaga (L.) Lam. Shariatullah Bot. 33 (PUP) + ------206. Trifolium repens L. Shariatullah Bot. 166 (PUP) - + + - - + - - + - - + + + + 207. Arisaema jacquemontii Blume. Shariatullah Bot. 42 (PUP) + ------208. Cucurbita pepo L. Shariatullah Bot. 88 (PUP) - + - - + - + - + - - + - + - 209. Luffa cylindrica (L.) M. Roem. Shariatullah Bot. 93 (PUP) - + - + - - - + + - - + - + - 210. Hordeum vulgare L. Shariatullah Bot. 180 (PUP) - + + - - + - - - - + + + + + 211. Momordica charantia L. Shariatullah Bot. 89 (PUP) - + - + - - - + + - - + - + - 212. Spinacia oleracea L. Shariatullah Bot. 83 (PUP) - + + - - + - - + - - + + + + 213. Daucus carota L. Shariatullah Bot. 35 (PUP) - + - - + - + - + - - + + + - 214. Raphanus sativus L. var. sativus Shariatullah Bot. 73 (PUP) - + - - + - + - + - - + + + - 215. Oryza sativa L. Shariatullah Bot. 173 (PUP) - + + - - + - - - - + + + + + 216. Pisum sativum L. Shariatullah Bot. 160 (PUP) - + + - - + - - + - - + - - - 217. Lathyrus aphaca L. Shariatullah Bot. 161 (PUP) - + + - - + - - + - - + - - - 218. Otostegia fruticosa (Forssk.) Schweinf. ex Shariatullah Bot. 112 (PUP) + ------Penzig. 219. Themeda anathera (Nees ex Steud.) Hack. Shariatullah Bot. 174 (PUP) - + + - - + - - - - + + + + + 220. Medicago denticulata Willd. Shariatullah Bot. 152 (PUP) - + + - - - + - + - - + + + - 221. Papaver somniferum L. Shariatullah Bot. 150 (PUP) + ------222. Sonchus asper (L.) Hill. Shariatullah Bot. 58 (PUP) - + + - - + - - + - - + + - - 223. Ranunculus hirtellus Royle. Shariatullah Bot. 195 (PUP) + ------224. Thymus serpyllum L. Shariatullah Bot. 128 (PUP) - + + - - + - - - - + + + + - 225. Plectranthus rugosus Wall. ex Benth. Shariatullah Bot. 123 (PUP) - + - + - - + - + - - + + + - 226. Apluda mutica L. Shariatullah Bot. 179 (PUP) - + - - + - + - + - - + + - - 227. Ajuga parviflora Benth. Shariatullah Bot. 121 (PUP) - + - + - - + - + - - + + + + 228. Sonchus arvensis L. Shariatullah Bot. 59 (PUP) - + + - - + - - + - - + + - - 229. Cucumis melo L. Shariatullah Bot. 90 (PUP) - + + - - - - + + - - + - + - D. Pteridophytes 230. Dryopteris sieboldii (T. Moore.) Kuntze. Shariatullah Bot. 10 (PUP) - + + - - + - - + - - + + - - 231. Polystichum wilsonii Christ. Shariatullah Bot. 13 (PUP) - + + - - + - - + - - + + - - 232. Polystichum lonchitis (L.) Roth. Shariatullah Bot. 14 (PUP) - + + - - + - - + - - + + - - 233. Asplenium septentrionale (L.) Hoffm. Shariatullah Bot. 6 (PUP) - + + - - + - - - - + + + + +

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234. Cystopteris fragilis (L.) Bernh. Shariatullah Bot. 15 (PUP) - + - - + + - - + - - + + + - 235. Adiantum incisum Forssk. Shariatullah Bot. 2 (PUP) - + + - - + - - - - + + + + - 236. Adiantum venustum D. Don. Shariatullah Bot. 1 (PUP) - + + - - + - - - - + + + + - 237. Ceterach dalhousiae (Hook.) C. Chr. Shariatullah Bot. 7 (PUP) - + + - - + - - - - + + + + - 238. Equisetum arvense L. Shariatullah Bot. 17 (PUP) + ------239. Cheilanthes pteridioides C. Chr. Shariatullah Bot. 21 (PUP) - + + - - + - - - - + + + + + 240. Pteris cretica L. Shariatullah Bot. 19 (PUP) - + + - - + - - - - + + + + - 241. Pteridium aquilinum (L.) Kuhn. Shariatullah Bot. 18 (PUP) - + + - - + - - + - - + + + - 242. Hypodematium crenatum (Forssk.) Kuhn. Shariatullah Bot. 8 (PUP) - + - + - + - - + - - + + - - 243. Asplenium adiantum-nigrum L. Shariatullah Bot. 4 (PUP) - + + - - + - - - - + + + + + 244. Dryopteris juxtaposita Christ. Shariatullah Bot. 11 (PUP) - + + - - + - - - - + + + + + 245. Pteris vittata L. Shariatullah Bot. 20 (PUP) - + + - - + - - - - + + + + + 246. Asplenium trichomanes L. Shariatullah Bot. 5 (PUP) - + + - - + - - - - + + + + + 247. Polystichum discretum (D. Don.) J. Sm. Shariatullah Bot. 12 (PUP) - + + - - + - - + - - + + + + 248. Dryopteris serrato-dentata Hayata. Shariatullah Bot. 9 (PUP) - + + - - + - - + - - + + + + 249. Adiantum capillus-veneris L. Shariatullah Bot. 3 (PUP) - + + - - + - - + - - + + + + 250. Equisetum ramosissimum Desf. Shariatullah Bot. 16 (PUP) + ------Total 55 195 99 51 45 98 89 13 116 2 77 194 172 110 71

Key: NP-Non-palatable, P-Palatable, HP-Highly palatable, LP-Less palatable, RP-Rarely palatable, W-Whole plant, L-Leaves, I- Inflorescence, F-Fresh, D-Dry, B-Both, G-Goat, S-Sheep, C-Cow, B-Buffalo

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Table 4.18. Grazing percentage of palatable species by life form

Life form Goat Sheep Cow Buffalo Total species browsed 194 172 110 71 Trees (%) 19.6 18.0 13.6 14.1 Shrubs (%) 13.4 13.4 10.9 12.7 Herbs (%) 57.2 57.6 61.8 60.6 Pteridophytes (%) 9.8 11.0 13.6 12.7 Total 100.0 100.0 100.0 100.0

Table 4.19. Classification of palatable plants by browsed preferred parts by livestock

Part used by grazing animals Species Number % age Whole plant 98 49 Leaves 89 44.5 Inflorescences 13 6.5 Total 200 100

Fig. 34. Differential palatability in each stratum of plant

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Fig. 35. Classification of palatable plants based on preference of grazing animals

Fig. 36. Classification of plants based on parts used

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Fig. 37. Classification of various types of plants based on livestock preference

Fig. 38. Classification of plants by condition used

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CHEMISTRY OF PLANTS

4.5 Chemical evaluation of some selected plants Plants are the rich sources of the essential elements needed for animals. A strong relationship is present between the elemental content and nutrition values of plants (Newall et al., 1996). In the present study the elemental composition (macro and micro elements) of some selected plants viz. Impatiens bicolor, Myrsine africana, Themeda anathera, Sarcococca saligna and Quercus dilatata were evaluated (Table. 4.20). Table 4.20. Forage plants selected for chemical evaluation S.No Species Voucher number Habit Family Palatability Distribution classes 1. Impatiens bicolor Royle. Shariatullah Bot. 65 H Balsaminaceae Rare palatable Common subsp. pseudo-bicolor (PUP) (Grey-Wilson & Rech. f.) Y.J. Nasir. 2. Myrsine africana L. Shariatullah Bot. 142 S Myrsinaceae High palatable Occasional (PUP) 3. Themeda anathera (Nees Shariatullah Bot. 174 H Poaceae High palatable Common ex Steud.) Hack. (PUP) 4. Sarcococca saligna Shariatullah Bot. 75 S Buxaceae Non-palatable Common Muell. Arg. (PUP) 5. Quercus dilatata Royle. Shariatullah Bot. 104 T Fagaceae Less palatable Uncommon (PUP)

4.5.1 Macronutrients Macronutrients are the structural components of the body organs and tissues of organisms. Macronutrients also playing an important role in reproduction, growth and proper function of the animal body (Anon, 2006). 1. Calcium Calcium is a necessary constituent of cell wall and it provides strength and rigidity to cell wall. It is an essential element in animal nutrition. In the present study a significant difference was found in the mean values of Ca content in different species at different phenological stages (Table. 4.21). The calcium contents were found highest in Quercus dilatata (4250 mg/kg) and lowest in Impatiens bicolor (2023 mg/kg). Overall the Ca contents were found higher at pre- reproductive stage as compared to the post-reproductive stage (Fig. 39). Similar, study was conducted by Badshah (2011) and found high content of Ca in flowering stage. Similar, findings were reported by Ashraf et al. (2005) and Khan et al. (2005), where Ca contents increased with maturity in herbaceous forages while, enhanced at maturity in trees species. However, my findings are in line with Hussain & Durani (2008) who reported that certain elements decreased with maturity of forages.

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2. Magnesium Magnesium is a component of the cell and skeletal system. It catalyses different enzymes reactions taking part in ion transport in the nerve cell. Magnesium maintains neuromuscular excitation both in animal and human being. In the present study the highest contents (2007.5 mg/kg) of Mg were found in the non-palatable species Sarcococca saligna followed by less palatable of tree species Quercus dilatata and highly palatable shrub Myrsine africana while less Mg contents were found in Impatiens bicolor. At pre-reproductive stage the more Mg contents were found in non-palatable species Sarcococca saligna (3026 mg/kg) followed by Myrsine africana (478.1 mg/kg), while at post-reproductive stage the more Mg contents were found in rare palatable species Impatiens bicolor (178.8 mg/kg), followed by high palatable species Themeda anathera (279 mg/kg) (Table. 4.21, Fig. 40). This is in accordance to Badshah (2011) who reported the highest Mg contents in woody plants. However, my results are also in line to Canali et al. (2005) who reported more concentration of Mg in a number of forages species. Kallah et al. (2000) observed that Mg contents were sufficient in the forages for ruminant production in tropics further strengthen my observation. 3. Phosphorus Phosphorus is an essential element providing strength to teeth and skeleton as well as improving blood plasma level. It is also necessary for the activation of some enzymes activation. It also a limiting factor to productivity of grazing live stocks (Hussain & Durrani, 2008). The present study revealed a significant difference in the mean values of P contents in different species at different phenological stages. Phosphorus was found in high concentration in Quercus dilatata, followed by Sarcococca saligna, while less concentration of phosphorus was noted in Myrsine africana (Fig. 41). Phosphorus was high in post-reproductive stage in Impatiens bicolor, Myrsine africana and Sarcococca saligna while the phosphorus contents were found more at pre-reproductive stage in Themeda anathera and Quercus dilatata (Table. 4.21). However, my findings are strongly supported by Samreen et al., (2016) who noted high P concentration at pre- reproductive stages in all the forages species. Dave & Dave (2003) reported the high concentration of P in some plants at early growing stages while in less concentration at mature stages. 4. Potassium Potassium is an essential macronutrient that activates many enzyme systems. The deficiency of K adversely affects the growh and metabolism of plants (Rahim et al., 2008). It is

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also a necessary element in livestock nutrition and at least 0.5 ppm K is required for their normal physiological function (Anon, 1985). The present results showed that a little significant difference was found in K concentration in different studied species. Mean value of K concentration was found higher for Sarcococca saligna as compared to other species (Table 4.21). In the present study, it was also observed that potassium contents were high at post- reproductive stages. The reason may be due to the difference in the accumulation potential of the species. This is in accordance to Khan et al., (2013) who reported highest concentration of potassium at post-reproductive stages. Ahmad et al. (2008) stated that different plants parts and phenological stages varied in K concentration. 4.5.2 Micronutrients The elements which are required in small quantity are called micronutrients. These micro elements play an important role in the metabolism and growth of organisms. If taken in excess amount these elements can cause severe physiological disturbances (Sobukola et al., 2010). Heavy metals influence the nutritive values of foods and also have hurtful effect on human beings (Radwan & Salama, 2006). In the present study, five micronutrients (zinc, manganese, iron, copper and lead) were analyzed in selected species (Table. 4.20). 1. Copper Copper is important micronutrient for normal bone formation as well as along with Fe it is also necessary for red cell maturation. Copper deficiency causes some abnormalities of bones and growth as well as anemia in organisms (Gonzalez et al., 2005). In the present study, high concentration of Cu was noted for Impatiens bicolor while less concentration was reported for Quercus dilatata. Copper concentration was high at pre-reproductive stage only in Sarcococca saligna while in the other species the concentration was higher at post-reproductive stages (Table. 4.22). Similar, study was conducted by Badshah (2011) and reported high range of fluctuation in Cu concentration in forages species during different phenological stages. 2. Zinc Zinc is present in carbonic anhydrase enzyme found in red blood cells and plays a key role in eliminating CO2. Zinc is also an activator of many enzymes. Reduction in reproductive capacity of animals, absence of sexual maturation and dwarfism are main symptoms in severe Zn deficiencies. In the present study, the Zn concentration was found higher in Impatiens bicolor followed by Themeda anathera while low concentration was found in trees and shrubs (Fig. 44)

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which agreed with (Malik et al., 2010; Badshah, 2011) who reported the highest concentration of Zn in forages species as compared to woody species. In all the species the Zn concentration was found maximum at pre-reproductive stage. My finding is also in line with Khan et al. (2006) who found high concentration of Zn at pre-reproductive stage in different species. 3. Iron Iron is important constituent of muscle protein, blood pigment, myoglobbulin, hemoglobin and different enzymes. Its deficiency causes anemia and decreases diseases resistance. Over intake of iron decreasing phosphate absorption and may cause dietary problems. The present study revealed that maximum concentration of Fe was found in Impatiens bicolor while minimum was reported for Themeda anathera. Iron concentration was also maximum at pre-reproductive stages in all the species (Table. 4.22). The present findings are in agreement with previous research (Gonzalez et al., 2005; Akhtar et al., 2007; Hussain & Durrani, 2008) that Fe contents decrease at maturity in species. 4. Manganese Manganese is a stimulant for some enzymes such as thiaminase and arginase. Its deficiency causes infant abnormalities, skeletal abnormalities and weakens growth. Manganese is least toxic of the trace elements to birds and mammals. Manganese between 50 and 125 ppm affected haemoglobin formation in mature rabbits and lambs (Hartman et al., 1955). The present study showed that Mn contents were high at post reproductive stages. The maximum mean Mn contents were found in Themeda anathera while minimum Mn contents were found in Sarcococca saligna (Fig. 46). My findings are in line with Hussain & Durrani (2008) who reported high concentration of Mn in herbaceous as compared to woody plants. 5. Lead Lead is a heavy metal causing accidental poisoning in domestic animals and human being. Its concentration of 80 ppm in forages could be toxic to horses but cattle could tolerate 200 ppm or more concentration. (Sobukola et al., 2010). In the present study, the mean lead contents were found higher in Quercus dilatata and Themeda anathera while the low contents were noted in Myrsine africana (Fig. 47). The results also revealed that Pb contents were found maximum at post-reproductive stages. A large significant difference was found in Pb contents in pre-reproductive and post-reproductive stages. The present findings are strongly supported by

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Badshah (2011) who reported the high concentration of Pb at post-reproductive stages. The present research is also in line with Malik et al. (2010) who conducted similar study.

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Table 4.21. Concentration of macro elements at various phenological stages

S.No Species Voucher number Macronutrients 1. Impatiens bicolor Royle. subsp. Shariatullah Bot. 65 Ca Mg P K pseudobicolor (PUP) (mg/kg) (mg/kg) (mg/kg) (mg/kg) (Grey-Wilson & Rech. f.) Y.J. Nasir. Pre-reproductive stage 3557 112.3 318.92 1042 Post-reproductive stage 489.7 178.8 192.7 2150 Mean value 2023.35 145.55 255.81 1596 2. Myrsine africana L. Shariatullah Bot. Ca Mg P K 142 (PUP) Pre-reproductive stage 4863 478.1 50 1025 Post-reproductive stage 497.5 186.9 66 1990 Mean value 2680.25 332.5 58 1507.5 3. Themeda anathera (Nees ex Shariatullah Bot. Ca Mg P K Steud.) Hack. 174 (PUP) Pre-reproductive stage 3054 72.5 271 1423 Post-reproductive stage 1093 279 99 2240 Mean value 2074 175.75 185 1831.5 4. Sarcococca saligna Muell. Arg. Shariatullah Bot. 75 Ca Mg P K (PUP) Pre-reproductive stage 5088 3026 220 1137 Post-reproductive stage 1098 989 465 2660 Mean value 3093 2007.5 342.5 1898.5 5. Quercus dilatata Royle. Shariatullah Bot. Ca Mg P K 104 (PUP) Pre-reproductive stage 6576 897 220 1323 Post-reproductive stage 1924 1334 742 1880 Mean value 4250 1115.5 481 1601.5

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Table 4.22. Concentration of micro elements at various phenological stages

S.No Species Voucher Micronutrients number 1. Impatiens bicolor Shariatullah Cu Zn Fe Mn Pb Royle. subsp. pseudo- Bot. 65 (PUP) (mg/kg) (mg/kg) (mg/kg) (mg/kg) (mg/kg) bicolor (Grey-Wilson & Rech. f.) Y. J. Nasir. Pre-reproductive 10.7 84 2584 55.2 2.2 stage Post-reproductive 19.5 47.8 98.7 175.6 49 stage Mean value 15.1 65.9 1341.35 115.4 25.6 2. Myrsine africana L. Shariatullah Cu Zn Fe Mn Pb Bot. 142 (PUP) Pre-reproductive 6.9 64.2 584.7 30 1.2 stage Post-reproductive 20.6 30.4 98.3 198 28 stage Mean value 13.75 47.3 341.5 114 14.6 3. Themeda anathera Shariatullah Cu Zn Fe Mn Pb (Nees ex Steud.) Bot. 174 Hack. (PUP) Pre-reproductive 5.1 86 250 15 0 stage Post-reproductive 10.4 41 99 273 98 stage Mean value 7.75 63.5 174.5 144 49 4. Sarcococca saligna Shariatullah Cu Zn Fe Mn Pb Muell. Arg. Bot. 75 (PUP) Pre-reproductive 12 66 378 39 1.2 stage Post-reproductive 10 31 97 121 78 stage Mean value 11 48.5 237.5 80 39.6 5. Quercus dilatata Shariatullah Cu Zn Fe Mn Pb Royle. Bot. 104 (PUP) Pre-reproductive 4 58 353 72 3 stage Post-reproductive 11 30 88 112 95 stage Mean value 7.5 44 220.5 92 49

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Fig. 39. Mean values of calcium contents (mg/kg) in different plants

Fig. 40. Mean values of magnesium contents (mg/kg) in different plants

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Fig. 41. Mean values of phosphorus contents (mg/kg) in different plants

Fig. 42. Mean values of potassium contents (mg/kg) in different plants

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Fig. 43. Mean values of Cu contents (mg/kg) in different plants

Fig. 44. Mean values of Zn contents (mg/kg) in different plants

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Fig. 45. Mean values of Fe contents (mg/kg) in different plants

Fig. 46. Mean values of Mn contents (mg/kg) in different plants

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Fig. 47. Mean values of Pb contents (mg/kg) in different plants

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ETHNOMEDICINE AND CONSERVATION

4.6 Medicinal plants and their conservation status Plants are the major source of medicine and nutrition in the world (Ajaib et al., 2016). In the present study, the medicinal uses and conservation status of 83 plants were determined. Plants are classified based on their habits; parts used, family‟s important values (FIV), frequency of citation (FC), relative frequency of citation (RFC), ethnomedicinal uses and their conservation status in the area. Data on medicinal uses and conservation status was collected through a questionnaire from local Hakeems and other knowledgeable people in the area. A total of 135 individuals were interviewed for the ethno-botanical information. The results revealed that of the 83 medicinal species (62.7%) were herbs, (21.7%) trees and the remaining (15.7%) species belonged to shrubs (Fig. 48). The plants were also classified based on their part used. The results showed that mostly the species were used as a whole plant (21.7%), followed by leaves (25.3%), leaves & fruit (9.6%), leaves & seed (6.0%), flower (4.8%), leaves & root 4.8% (Table. 4.23, Fig. 49). Wariss et al. (2014) documented 84 medicinal plants from Lal Suhanra national park, Bahawalpur while, Ahmad & Pieroni (2016) reported 51 plants of medicinal uses from Thakht-e- Sulaiman hills North-West Pakistan. Similar study was conducted by Barkatullah & Ibrar (2011) and explored the ethno-botanical uses of 169 plants from Malakand Pass hill and stated that shoots were the most frequently used part (34.91%) in the area followed by leaves (27.21%) and whole plant (21.89%). However, my results are in agreement with Adnan et al. (2015) who documented the ethno-botanical uses of medicinal plants in Pashtun tribal areas and found that the inhabitants of the area mostly used whole plants (33%) and leaves (31%) for the treatment of various diseases. Most common mode of administration was found to be decoction. Some medicinal plants or their effective parts are powdered while in few cases fresh plants were used as crude drug (Table. 4.23). The results show that most of these species were multipurpose in their medicinal uses while, others were used for single type of diseases such as the latex of Euphorbia peplus were reported to be effective in scabies, Taraxacum campylodes in antidiabetic, Melilotus officinalis leaves decoction as anticoagulant, Malva neglecta as purgative, Medicago lupulina as laxative and Daphne mucronata was reported to be useful in treatment of fertility. Some species were administered in the form of decoction or their effective part was used in powdered form while others were used directly in fresh form as a crud drug. Allium cepa, Tagetes minuta, Dysphania botrys, Micromeria biflora, Ajuga bracteosa, Mentha longifolia, Datura stramonium,

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Geranium wallichianum, Gerardinia palmata, Berberis lycium, Quercus dilatata, Ziziphus oxyphylla and Pinus wallichiana were reported to be used for multi types of disorders like skin irritation, cough and asthma, stomachache, expectorant, hepatic disorders, jaundice, hepatitis, antidiuretic, diarrhea, carminative, hepatitis, dog bite, wound healing, abdominal pain, blood pressure, throat sore, constipation, swollen joint, headache and backbone pain. Similar study was conducted by Aziz et al. (2016) in Ladha subdivision, South Waziristan agency, Pakistan and reported the medicinal uses of 82 plants for different types of diseases. The ethnomedicinal uses of flora are also reported by other researchers in different parts of the country (Hussain et al., 2006; Ibrar et al., 2007; Qureshi et al., 2008) and abroad (Jain, 2001; Mahishi et al., 2005; Jeruto et al., 2008). So, my findings are in line with these findings. As an increase in human population, the stress on the collection of medicinal flora increases and the unsustainable collection of these medicinally important species leads to be declining in the area. Beside their collection for medicinal purposes the inhabitants clearing the forests vegetation for agriculture purposes, fuels demand and houses construction. 4.6.1 Family importance value (FIV) Family importance values reflects the number of locally important species belong to that particular plants family, while RFC index tells us the local importance of that particular plants found in the area. The results revealed that the best represented used family based on number of species was Lamiaceae with 8 (91.11%) species, followed by Asteraceae with 7 (71.11%) species, Rosaceae with 6 (54.07%) species, Apiaceae with 5 (47.4%) species, Solanceae & Moraceae each with 3 (31.11%) species, Chenopodiaceae with 2 (28.14%) species and Oleaceae with 1 (25.92%) species (Table. 4.23, Fig. 50). My findings agreed with Ahmad et al. (2014) who found Lamiaceae, Polygonaceae, Amaranthaceae, Apiaceae and Ranunculaceae the best represented families in terms of FIV in Chail valley. My findings are also in accordance with the previous studies on ethno flora reported by Giday et al. (2003), Guarrera et al. (2005), Hamayun (2007) and Hong et al. (2015) in different areas of the world. 4.6.2 Relative frequency of citation (RFC) Relative frequency of citation tells us about the local importance of the particular plant species for the treatment of various types of diseases. The RFC values also indicate the importance of species relative to the number of local informants taking part in this study as well as reflecting the strong and long-term association of inhabitants with local plants (Ahmad et al.,

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2014). The present study revealed that the highest RFC was recorded for Mentha longifolia (0.266) followed by Olea ferruginea (0.259), Myrsine africana (0.244), Artemisia biennis (0.229), Quercus dilatata (0.222), Isodon rugosus (0.207), Punica granatum and Equisetum arvense (0.214) each, Cotoneaster nummularia (0.195) while that of Viola canescens was (0.192) RFC value (Table. 4.23, Fig. 51). Ahmad et al. (2014) conducted study on the ethno- botanical information of Chail valley and found the highest RFC values for Origanum vulgare, Geranium wallichianum and Skimmia laureola. Similarly, Ali (2016) reported the highest RFC for Skimmia laureola (0.321), Juglans regia, Olea ferruginea and Papaver somniferum in Chail valley (Swat). These species were used for different disorders like expectorant, emetic, for scorpion bites, laxative, purgative, carminative, jaundice, hepatitis. The uses of these species were also reported by other researchers from different parts of the country (Barkatullah & Ibrar, 2011; Khan et al., 2013; Hussain et al., 2014; Ahmad et al., 2014; Begum et al., 2016; Ajaib et al., 2016 and Ali et al., 2017) for the treatment of these disorders however, a little difference was found in the method of administration and recepies preparation. 4.6.3 Conservation status of medicinal flora In the present study, a total of 83 medicinal plants were analyzed for its conservation following IUCN (2001). The results revealed that only Melia azedarach was found endanger, 35 (42%) species were rare, 15 (18%) species infrequent, and 32 (39%) species were recorded as vulnerable in the area (Fig. 52). The result also showed that no species fulfilled the IUCN criteria of dominance. Some of the rare were Micromeria biflora, Thymus linearis, Mentha arvensis, Bergenia ciliata, Mentha longifolia, Plantago major, Plantago lanceolata, Verbascum thapsus, Teucrium stocksianum, Galium stewartii, Tagetes minuta, Foeniculum vulgare, Isodon rugosus, Daphne mucronata, Sarcococca saligna, Pinus roxburghii and Ficus carica (Table. 4.23). Many of the rare species indentified were extensively collected for medicinal purposes, while the trees species such as Pinus roxburghii was utilized for timber purposes. The rare species need special attention for their conservation otherwise; they will be endangered in the near future. Some of the vulnerable species found in the area were Geranium wallichianum, Cirsium falconeri, Myrsine africana, Berberis lycium, Quercus dilatata, Diospyros lotus, Olea ferruginea, Salix tetrasperma, Ziziphus oxyphylla, Juglans regia, Punica granatum and Morus nigra. The local community depends on these species for fuel wood and timber purposes. The anthropogenic activities were found to be at peak and threatening the biodiversity to alarming level. Several

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factors are involved to threaten biodiversity such as habitat loss, habitat fragmentation (Corlett & Westcott, 2013; Steege et al., 2015; Kettle & Koh, 2014 and Corlett, 2016) fuels demand, over collection, over grazing and abiotic stress. While in the present observation the major threat to biodiversity was fuels demand, marketed values of medicinal plants and conversion of land to farming and agriculture.

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Table 4.23. Medicinal plants, RFC, FIV and their conservation status

S.No Taxon Voucher number Local name Habit Part C RFC FIV 1 2 3 4 5 Conservation Uses and used Status Remedies A. Pteridophytes 1. Adiantaceae 10.37 1. Adiantum capillus- Shariatullah Bot. 3 Sumbal H Leaflet 5 0.037 3 3 4 4 14 Infrequent Febrifuge, veneris L. (PUP) expectorant and diuretic. 2. Adiantum venustum D. Shariatullah Bot. 1 Babozay H Frond 9 0.066 2 2 4 4 12 Rare The fronds crushed Don. (PUP) and squeezed used as expectorant, emetic and in scorpion bites. 2. Equisetaceae 21.48 3. Equisetum arvense L. Shariatullah Bot. 17 Bandakay H Whole 29 0.214 0 2 4 0 6 Vulnerable Plant extracts (PUP) Plant effective against renal calculi and antilice. 3. Pteridaceae 2.96 4. Pteris vittata L. Shariatullah Bot. 20 Babozai H Rhizom 4 0.029 0 3 4 0 7 Vulnerable Rhizome used to (PUP) e & treat hysteria. Leaves Fresh leaves cooked as vegetable. 4. Dryopteridaceae 0.74 5. Dryopteris serrato- Shariatullah Bot. 9 Kwanjay H Leaves/ 1 0.007 3 2 4 4 13 Infrequent Poisonous both to dentata Hayata. (PUP) Pinnae humen and animals. B. Gymnosperm 5. Pinnaceae 12.59 6. Pinus roxburghii Sarg. Shariatullah Bot. 22 Nakhtar, Chir T Resin 10 0.074 3 2 0 4 9 Rare Used for the (PUP) Pine treatment of abses on body and acne on face, asterigent and effective against measles.

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7. Pinus wallichiana A.B. Shariatullah Bot. 23 Sraf, Blue T Wood, 7 0.051 3 3 0 1 7 Vulnerable Wood bark Jaks. (PUP) Pine Resin effective against skin irritation, cough and asthma. Resin is used to treat stomachache. C. Monocotyledonae 6. Poaceae 2.22 8. Cynodon dactylon (L.) Shariatullah Bot. Kabal H Whole 3 0.022 2 2 4 0 8 Vulnerable Decoction used for Pers. 176 (PUP) plant abdominal pain, leg pain, dysentry and as asterigent. 7. Alliaceae 12.59 9. Allium cepa L. Shariatullah Bot. 27 Piyaz H Bulb 6 0.044 3 0 4 0 7 Vulnerable Good for gum, (PUP) teeth disorders and high blood pressure, expectorant and diuretic. 10. Allium sativum L. Shariatullah Bot. 26 Oga H Cloves 11 0.081 3 1 4 0 8 Vulnerable Aphrodisiac, (PUP) diuretic, effective against diabetic and high blood pressure. 8. Araceae 3.7 11. Arisaema flavum Shariatullah Bot. 41 Marjarai H Seed & 5 0.037 2 2 4 2 10 Rare Seeds are used to (Forssk.) Schott. (PUP) Root treat infertility and digestive problems of livestock. Root is anthelmintic. D. Dicotyledonae 9. Solanaceae 31.11 12. Solanum nigrum L. Shariatullah Bot. Karmachu H Whole 17 0.125 3 2 4 0 9 Rare Exract of fresh var. nigram. 240 (PUP) Plant leaves are applied to treat odema, hapetitis and abdominal pain. Root decoction is effective against urticaria and abses. 129

13. Datura stramonium L. Shariatullah Bot. Batura H Leaves 9 0.066 2 3 4 4 13 Infrequent Fresh leaves are 241 (PUP) & Seed used as bandages on abses; seeds antispasmodic. 14. Datura innoxia Mill. Shariatullah Bot. Batura H Seed & 16 0.118 2 3 4 2 11 Rare Seeds anodyne and 235 (PUP) Leaves sedative in nature. Leaf juice is used to cure gonorrhoea. 10. Brassicaceae 9.62 15. Raphanus sativus L. Shariatullah Bot. 73 Mouli H Whole 13 0.096 2 1 4 0 7 Vulnerable Aqueous extact of var. sativus. (PUP) Plant fresh leaves used against juandice; laxative and diuretic. Roots effective in dissolving uninary tract stones. 11. Urticaceae 25.18 16. Urti ca dioica L. Shariatullah Bot. Sezunkai H Whole 14 0.103 3 2 4 0 9 Rare Asterigent, diuretic 246 (PUP) Plant and its decoction is used for juandice and scabes. 17. Girardinia palmata Shariatullah Bot. Sezunkai H Whole 20 0.148 2 2 4 0 8 Vulnerable Leaves decoction (Forssk.) Gaudich. 247 (PUP) Plant commonly used for constipation, on swollen joint and headache. 12. Chenopodiaceae 28.14 18. Chenopodium album Shariatullah Bot. 82 Sakh Botay H Leaves 15 0.111 2 3 4 4 13 Infrequent Carminative, L. (PUP) diuretic; dried powdered leaves are used to treat dysentry, vomiting and piles. 19. Dysphania botrys (L.) Shariatullah Bot. 86 Gouti H Leaves 23 0.170 3 3 4 4 14 Infrequent Latex of leaves Mosyakin & Clemants. (PUP) mixed with the mother milk is considered effective in controlling

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childeren constipation. Anthelmintic and dried leaves used to cure dysentry, odema, diarrhea and hepatitis. 13. Meliaceae 5.18 20. Melia azedarach L. Shariatullah Bot. Tora Shandai T Bark 7 0.051 1 2 0 1 4 Endangered Carminative, 135 (PUP) decoction of bark is used to treat fever (pyrexia), body ache, leaf extracts used against typhoid. 14. Simarubaceae 15.55 21. Ailanthus altissima Shariatullah Bot. Watani T Leaves 21 0.155 3 2 0 4 9 Rare Extract of fresh (Mill.) Swingle. 231 (PUP) Shandai leaves is used for blood purification and scabes. 15. Rosaceae 54.07 22. Cotoneaster Shariatullah Bot. Mamanra S Root & 27 0.195 3 1 3 0 7 Vulnerable Fresh roots boiled nummularia Fish. & 216 (PUP) Fruits in water then Mey. filtered the water through cloth; the filterate is used for diabetic patients, dysentery, vomiting, cholera and calculis of kidney. Fruit is expectorant and antidiabetic. 23. Rosa canina L. Shariatullah Bot. Gulab S Flower 5 0.037 3 2 3 3 11 Rare Flower is 217 (PUP) anthelmintic and purgative. And good for abdominal pain.

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24. Rosa webbiana Wall. Shariatullah Bot. Khwarach S Seed & 12 0.088 2 2 3 2 9 Rare Seeds throughly ex Royle. 207 (PUP) Fruit boiled in tea are considered effective against chest infection, cough, asthma, hapatitis and vartigo goiter. 25. Prunus persica (L.) Shariatullah Bot. Shaltalu T Flower 11 0.081 2 3 0 3 8 Vulnerable Diuretic, purgative Batsch. 200 (PUP) and anthelmintic 26. Sorbaria tomentosa Shariatullah Bot. Jalbhang T Leaves 10 0.074 0 3 0 4 7 Vulnerable Fresh leaves are (Lindl.) Rehdr. 215 (PUP) & Fruit boiled in water and the decoction is used against diabetic patients, abses and hapatitis. Fruit is aneasthetic 27. Rubus ulmifolius Shariatullah Bot. Karwara S Fruit & 8 0.059 3 2 3 2 10 Rare Fresh fruit used to Schott. 209 (PUP) Leaves cure cold and sore throat. Leaves decoction effective in the treatment of diarrhea, urticaria, and also diuretic. 16. Rutaceae 3.7 28. Z anthoxylum armatum Shariatullah Bot. Dambara T Fruit & 5 0.037 1 3 0 2 5 Vulnerable Dried and DC. 220 (PUP) Seed powdered fruit is used for dry cough; also good carminative. 17. Moraceae 31.11 29. Morus nigra L. Shariatullah Bot. Tor Toot T Fruit & 16 0.118 1 3 0 2 6 Vulnerable Fruit is 138 (PUP) leaves anthelmintic, refrigerant, expectorant and diuretic. Extract of leaves are useful for high blood pressure.

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30. Morus alba L. Shariatullah Bot. Spin Toot T Fruit & 22 0.162 3 2 0 2 7 Vulnerable Fruit is a good 139 (PUP) Bark remedy for sore throat, overdose cause diarrhea. Bark as anthelmintic and purgative. 31. Ficus carica L. Shariatullah Bot. Inzar T Leaves 4 0.029 2 3 0 4 9 Rare Milkey latex from 140 (PUP) fresh leaves are used to expell thorn from skin, arthriotis and wound healing. 18. Apiaceae 47.4 32. Foeniculum vulgare Shariatullah Bot. 37 Kaga H Seed & 20 0.148 3 1 4 2 10 Rare Dried, powdered Mill. (PUP) Leaves seeds mix with sugar used against abdominal pain, digestive problems, dry cough, vomiting and chest infection. Leaves carminative and diuretic. 33. Coriandrum sativum L. Shariatullah Bot. 38 Dhania H Leaves 17 0.125 1 1 4 4 10 Rare Roasted seeds are (PUP) & Fruit good remedy for vomiting and diarrhea. 34. Seseli libanotis (L.) Shariatullah Bot. 40 Kali Zeeri H Leaves 6 0.044 0 3 4 4 11 Rare Decoction of Koch. (PUP) & Seeds leaves is used to treat urticaria, dry cough and asthma. Fruit as carminative. 35. Trachydium roylei Shariatullah Bot. 35 Zankai H Whole 2 0.014 1 2 4 0 7 Vulnerable Crushed whole Lindl. (PUP) Plant plant and paste applied to cure odema. Fruit is laxative.

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36. Ammi visnaga (L.) Shariatullah Bot. 33 Spairkai H Fruit 19 0.14 3 2 4 2 11 Rare Dried and Lam. (PUP) powdered fruits are used to treat asthma, whooping cough and angina pectoris. 19. Polygonaceae 14.81 37. Polygonum aviculare Shariatullah Bot. Bandakai H Whole 3 0.022 1 2 4 0 7 Vulnerable Grinded the whole L. 184 (PUP) Plant plant in a mortar, then filter through cloth, is a good agent for hapatitis and kidney calculies. Root as anodyne. 38. Rumex hastatus D. Shariatullah Bot. Taruky H Root & 8 0.059 3 3 4 0 10 Rare Quite effective in Don. 182 (PUP) Leaves diarrhea, bleeding of wound. Refrigerant and diuretic. 39. Rumex dentatus L. Shariatullah Bot. Shalkhay H Leaves 9 0.066 3 3 4 4 14 Infrequent Poultice of leaves 187 (PUP) & Bark used for wound healing and abses. Decoction of the bark is used against arthriotis. 20. Asteraceae 71.11 40. Tagetes minuta L. Shariatullah Bot. 61 Malooch H Flower 11 0.081 1 2 4 3 10 Rare Flowers used to (PUP) cure juandice and hapatitis. 41. Filago hurdwarica Shariatullah Bot. 64 Warkharay H Whole 18 0.133 3 1 4 0 8 Vulnerable Decoction in (Wall. ex DC.) (PUP) Plant dysentry, abses and Wagenitz. body cooling. 42. Artemisia biennis Shariatullah Bot. 50 Tarkha H Leaves 31 0.229 3 2 4 4 13 Infrequent Anthelmintic, Willd. (PUP) vomiting, diarrhea and in snake bite. 43. Taraxacum Shariatullah Bot. 53 Ziar Gulay H Leaves 14 0.103 3 3 4 4 14 Infrequent Antidiabetic. campylodes G. E. (PUP) Haglund.

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44. Myriactis wallichii Shariatullah Bot. 57 Spera Botay H Whole 7 0.051 2 3 4 0 9 Rare Decoction of Less. (PUP) Plant whole plant is very effective for abdominal pain, hepatitis and high blood pressure. 45. Cirsium falconeri Shariatullah Bot. 47 Azghaky H Whole 9 0.066 1 3 4 0 8 Vulnerable Quite effective in (Hook. f.) Petr. (PUP) Plant hepatitis and high blood pressure. 46. Sonchus asper (L.) Shariatullah Bot. 58 Shuada Pai H Flower 6 0.044 3 3 4 3 13 Infrequent Decoction of Hill. (PUP) flower is used to treat constipation and jaundice. 21. Buxaceae 13.33 47. Sarcococca saligna Shariatullah Bot. 75 Shenolay S Leaves 18 0.133 3 1 2 4 10 Rare Refrigerant and Muell. Arg. (PUP) & Fruit carminative. Decoction used against jaundice, hepatitis, odema, skin disorders, mouth ulcers and sore throat. 22. Lamiaceae 91.11 48. Isodon rugosus (Wall. Shariatullah Bot. Karachai S Leaves 28 0.207 3 2 3 4 12 Rare Fresh leaves are ex Benth.) Codd. 116 (PUP) chewed effective in sore throat, hapatitis, high blood pressure, abdominal pain, diarrhea and dsentry. Extract of leaf is used against eye infection. 49. Micromeria biflora Shariatullah Bot. Shumakay H Leaves 15 0.111 2 1 4 4 11 Rare Laxative, (Duch.-Ham ex 122 (PUP) purgative, D.Don.) Benth. carminative and analgesic. Leaf extract is recommended for body pain.

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50. Thymus linearis Benth. Shariatullah Bot. Ghar Sperkai H Leaves 10 0.074 2 0 4 4 10 Rare Antispasmodic, subsp. linearis Jalas. 114 (PUP) carminative and analgesic. Decoction of leaves is considered useful in abdominal pain and to warm up mammals‟ body after delivery to expel umbilical cord. 51. Ajuga bracteosa Wall. Shariatullah Bot. Gooti H Leaves 5 0.037 3 3 4 4 14 Infrequent Decoction is used to ex Benth. 115 (PUP) treat articaria, abses, abdominal pain and erythema. Also used as carminative. 52. Teucrium stocksianum Shariatullah Bot. Spera Botay H Whole 11 0.081 2 3 4 0 9 Rare Diphoretic and Boiss. 130 (PUP) Plant stimulant. Effective remedy for jaundice. 53. Mentha arvensis L. Shariatullah Bot. Podina H Leaves 16 0.118 3 0 4 4 11 Rare Used as stimulant; 113 (PUP) carminative and diuretic. Effective against constipation. 54. Mentha longifolia (L.) Shariatullah Bot. Enalay H Leaves 36 0.266 3 0 4 4 11 Rare Laxative, purgative L. 126 (PUP) & Root and carminative. Decoction of leaves used to treat vomiting, jaundice, hepatitis and cholera. 55. Scutellaria Shariatullah Bot. Zagli Sparkai H Whole 2 0.014 1 2 4 0 7 Vulnerable Nerve tonic and chamaedrifolia Hedge 127 (PUP) Plant antispasmodic. & A. J. Paton. 23. Rhamnaceae 5.18 56. Ziziphus oxyphylla Shariatullah Bot. Markhanay T Fruit & 7 0.051 2 2 0 2 6 Vulnerable Fruit is used as Edgew. 199 (PUP) Leaves effective expectorant and emollient and also 136

helpful in hepatic disorders. Leaves decoction used against jaundice and hepatitis. 24. Berberidaceae 17.77 57. Berberis lycium Royle. Shariatullah Bot. 67 Kwaray S Root & 24 0.177 3 1 3 0 7 Vulnerable Refrigerant and (PUP) Bark carminative. Decoction of dry root bark advised for hepatitis, dog bite, wound healing, jaundice, abdominal pain and high blood pressure. Also used to relieve toothache and throat sore. 25. Thymelaceae 1.48 58. Daphne mucronata Shariatullah Bot. Laighunai S Leaves 2 0.014 2 3 3 4 12 Rare Decoction is Royle. 242 (PUP) considered useful in infertility. 26. Geraniaceae 5.92 59. Geranium Shariatullah Bot. Sara Zeela H Root 8 0.059 1 1 4 0 6 Vulnerable Dried and wallichianum D. Don. 107 (PUP) powdered form of ex Sweet. root mixed with halwa recommended for backbone pain, wound healing and arthritis; good aphrodisiac. 27. Juglandaceae 16.29 60. Juglans regia L. Shariatullah Bot. Ghuz T Leaves 22 0.162 3 1 0 2 6 Vulnerable Honey plus dried 111 (PUP) & Fruit fruit used as a brain tonic. Decoction of leaves useful against diabetic.

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28. Loganaceae 2.96 61. Buddleja crispa Benth. Shariatullah Bot. Banroo S Whole 4 0.029 2 3 4 0 9 Rare Carminative and 132 (PUP) Karachai Plant purgative. Decoction used for blood purification and BP. 29. Cannabaceae 14.07 62. Cannabis sativa L. Shariatullah Bot. 76 Bhang H Leaves 19 0.140 3 3 4 4 14 Infrequent Powdered leaves (PUP) used as narcotic and sedative. Charas is also prepared from it and is valuable appetizer. 30. Elaeagnaceae 18.51 63. Elaeagnus umbellata Shariatullah Bot. 98 Katanr S Leaves 25 0.185 3 3 3 4 13 Infrequent Leaves decoction Thunb. (PUP) is used to treat cold and flu. 31. Myrsinaceae 24.44 64. Myrsine africana L. Shariatullah Bot. Marogaya S Fruit & 33 0.244 2 1 1 2 6 Vulnerable Fruit is 142 (PUP) Leaves anthelmintic. Decoction of leaves used to cure abdominal pain, digestive disorders and vomiting. 32. Ebanaceae 8.14 65. Diospyros lotus L. Shariatullah Bot. 97 Amlook T Seed & 11 0.081 3 3 0 2 8 Vulnerable Diuretic and (PUP) Fruit sedative. Also used against diarrhea and constipation. 33. Saxifragaceae 4.44 66. Bergenia ciliata Shariatullah Bot. Pararwali H Leaves 6 0.044 1 3 4 4 12 Rare Demulcent and (Haw.) Sternb. 227 (PUP) astringent. 34. Malvaceae 2.22 67. Malva neglecta Wallr. Shariatullah Bot. Paneerak H Whole 3 0.022 1 3 4 0 8 Vulnerable Purgative in nature. 134 (PUP) Plant Leaves used as vegetable.

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35. Rubiaceae 11.11 68. Galium stewartii Shariatullah Bot. Naray Botay H Whole 15 0.111 3 2 4 0 9 Rare Aphrodisiac and Nazim. 219 (PUP) Plant refrigerant. Dried and powdered form is used for diarrhea, hair fall, dysentery, abdominal pain, and chest infection. 36. Fagaceae 22.22 69. Quercus dilatata Shariatullah Bot. Zareen T Fruit 30 0.222 1 2 0 2 5 Vulnerable Dried roasted fruit Royle. 104 (PUP) is anti diuretic; effective in diarrhea. 37. Scrophulariaceae 8.88 70. Verbascum thapsus L. Shariatullah Bot. Kharghawag H Leaves 12 0.088 2 2 4 4 12 Rare Leaves poultice 229 (PUP) & Seeds against boils. Seed as aphrodisiac. 38. Euphorbiaceae 12.59 71. Euphorbia peplus L. Shariatullah Bot. Mandaro H Latex 17 0.125 3 3 4 4 14 Infrequent Latex effective in 101 (PUP) scabies. 39. Plantaginaceae 22.96 72. Plantago lanceolata L. Shariatullah Bot. Ghawajabai H Root & 18 0.133 3 2 4 0 9 Rare Leaves used to 169 (PUP) Leaves cure asthma, candidacies and also mild purgative. 73. Plantago major L. Shariatullah Bot. Ghawajabai H Leaves 13 0.096 2 2 4 4 12 Rare Leaves used to 168 (PUP) & Root treat candidacies and inflamed surface. 40. Anacardiaceae 1.48 74. Pistacia chinensis Shariatullah Bot. 31 Sheenawar T Fruit & 2 0.014 1 3 0 2 6 Vulnerable Decoction used in Bunge subsp. (PUP) Leaves dry cough and integrrima (J. L. tuberculosis; also, Stewart ex Brandis.) antiseptic. Rech. f.

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41. Salicaceae 10.37 75. Salix tetrasperma Shariatullah Bot. Wala T Bark & 14 0.103 2 2 0 1 5 Vulnerable Decoction of Roxb. 223 (PUP) Leaves leaves is used for diabetic and infertility. Bark used in erythema. 42. Oleaceae 25.92 76. Olea ferruginea Royle. Shariatullah Bot. Khona T Leaves 35 0.259 3 1 0 4 8 Vulnerable Decoction used to 145 (PUP) treat sore throat, jaundice and diabetes; good anodyne. 43. Caprifoliaceae 11.85 77. Viburnum cotinifolium Shariatullah Bot. 78 Khapyanga S Leaves 16 0.118 0 2 3 4 9 Rare Dried and D. Don. (PUP) & Bark powdered form of leaves and bark used against healing of wound and constipation; also, a good anthelmintic. 44. Oxalidaceae 6.66 78. Oxalis corniculata L. Shariatullah Bot. Garday H Leaves 9 0.066 3 3 4 4 14 Infrequent Leaves decoction 149 (PUP) Taruky effective against jaundice and hepatitis, while poultice used for boils and blood clothing. 45. Punicaceae 21.48 79. Punica granatum L. Shariatullah Bot. Anar T Fruit & 29 0.214 2 3 0 2 7 Vulnerable Powdered fruit mix 190 (PUP) Bark with egg taken orally to control abdominal pain. 46. Violaceae 19.25 80. Viola canescens Wall. Shariatullah Bot. Tora Panra H Whole 26 0.192 3 1 4 0 8 Vulnerable Dried and 249 (PUP) Plant powdered leaves boiled in green tea used for chest infection, 140

abdominal pain and flue. 47. Papilionaceae 16.29 81. Desmodium elegans Shariatullah Bot. Aday S Root 7 0.051 3 3 3 0 9 Rare Diuretic and DC. 163 (PUP) carminative. 82. Medicago lupulina L. Shariatullah Bot. Shpeshtarlay H Whole 10 0.074 3 2 4 0 9 Rare Laxative/ vegetable 157 (PUP) Plant food. 83. Melilotus officinalis Shariatullah Bot. Lewanai H Leaves 5 0.037 2 3 4 4 13 Infrequent Decoction is used (L.) Desr. 162 (PUP) as anticoagulant.

Key: C- Number of respondents citing the plant RFC- Relative frequency of citation FIV- Family importance value 1. Availability class 2. Collection status 0 = Uncommon or very rare 0 = More than 1000 kg/yr 1 = Less common or rare 1 = Consumed from 500-1000 kg/yr 2 = Occasional 2 = Consumed from 300-500 kg/yr 3 = Abundant 3 = Consumed from 100-200 kg/yr 3. Growth behavior 4. Part used 0 = Regrowth in more 3 years 0 = Root/whole plant 1 = Regrowth within 3 years 1 = Bark 2 = Regrowth within 2 years 2 = Seeds, fruits 3 = Regrowth within 1 year 3 = Flowers 4 = Regrowth in a season 4= Leaves/gum/latex 5. Total score: 1. 0 - 4 Endangered 2. 5 - 8 Vulnerable 3. 9 - 12 Rare: 4. 13 - 14 Infrequent 5. 15 - 16 Dominant

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Fig. 48. Classification of medicinal plants based on their habits

%of Species

Fig. 49. Classification of medicinal plants based on their parts used

142

%of Species

Fig. 50. FIV of the top ten families found in the area

RFC Values RFC

Fig. 51. Species with highest relative frequency of citation

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Fig. 52. Conservation status of plants in Jelar valley

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Conclusions

1. Flora of Jelar valley was diverse and comprised of 250 species belonging to177 genera and 77 families. 2. The dominant families in term of species richness were Asteraceae and Lamiaceae, followed by Rosaceae while dominant genera were Polygonum and Rosa. 3. Therophytes were dominant followed by hemicryptophytes, while in leaf size classes microphylls and nanophylls were dominant. 4. The major threat to biodiversity in the area is fuels demand, uprooting of medicinal plants and low agriculture land which contributing to the removal of vegetation covers. 5. Based on FIV the best represented used family was Lamiaceae followed by Asteraceae, while the highest RFC was recorded for Mentha longifolia followed by Olea ferruginea. 6. The conservation status of medicinal flora revealed that Melia azedarach was found endanger, 35 species were rare, 15 species infrequent and 32 species were recorded as vulnerable with no dominant category. 7. Pc-Ord analysis (cluster analysis and ordination) results into the formation of eight vegetation groups, four each for trees and understory species. 8. The difference in physiognomy of plants communities was mainly due to the difference in environmental, topographic and edaphic characteristics. 9. The difference in the IVI, density/ha and covers/ha of species in different communities indicating the difference in microclimate and habitat condition at different sites and anthropogenic disturbance. 10. The soil of the study area was loamy sand, acidic in nature and slightly calcareous with variable amount of organic matter and other macro and micronutrients. 11. The palatability results revealed that the flora is facing grazing and browsing pressure. 12. Though the area has dominated by palatable plants but due to deforestation and severe grazing pressure the vegetation is threatened. 13. Elemental analysis of selected plants revealed that sufficient level of macro and micro nutrients were presents in the plants, however difference was observed in the phenological stages as well as in the palatability of the species.

Recommendations

1. The local inhabitants are exclusively dependent upon natural forest for fuel, fodder and timber, so the government should provide alternate sources to turn their direction from the degradation of vegetation. 2. BTAT (Bilion tree aforest programme) is recommended to reforest the native trees and to establish nurseries on large scale in the area to ensure the propagation of high valued species Pinus wallichiana, Pinus roxburghii and Olea ferruginea. 3. Overgrazing should be managed to ensure the regeneration capacity of the important tress species in the area. Moderate and rotational grazing routines should be enforced which is indentified in the research. 4. Reforestation programs should be initiated in the area for the protection and conservation of indigenous flora which is indentified in the research. 5. Alternative sources of energy should be provided to reduce pressure on fuels demand. 6. Insitu conservation should be own on urgent basis. 7. Ecotourism could be eager in the area for the additional sources of economy to strengthen the socioeconomic condition of the area. 8. Forestry and horticulture departments should arranged timely programs to inspire and trained the local interested people as not such activities observed during research.

146

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