i

FLORISTIC DIVERSITY ALONG ENVIRONMENTAL GRADIENTS IN DISTRICT TOR GHAR

AZHAR MEHMOOD

DEPARTMENT OF BOTANY HAZARA UNIVERSITY MANSEHRA

2016

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HAZARA UNIVERSITY, MANSEHRA

Department of Botany

FLORISTIC DIVERSITY ALONG ENVIRONMENTAL GRADIENTS IN DISTRICT TOR GHAR

By

AZHAR MEHMOOD

This research study has been conducted and reported as partial fulfilment of requirement of Ph.D degree in Botany awarded by Hazara University, Mansehra, Pakistan

Mansehra, June 17, 2015

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ABSTRACT

The Tor Ghar (Black Mountain) a newly established district lies on the extreme

western edge of the Himalayas where the Indus River separates it from the Hindu

Kush. This area of Pakistani Himalayas has remained botanically unexplored in the

history. In spite of number of social, administrative, communication problems and

rough terrain, it was felt necessary to document flora, ecology and syn-taxonomy of

this region. In view of the utmost importance of first ever exploration, study was

planned with the objectives to explore, identify and document vascular plant species

to provide a scientific basis for future research, evaluate species distributions and

plant communities using modern phytosociological techniques and to identify

environmental gradients responsible for species distribution. Extensive field work

was carried out during the summers of 2012 and 2013. Quadrats were randomly

used along the elevation gradient to measure various phytosociological attributes of

higher plants. A total of 331 vascular plant species belonging to 246 genera and 101

families were recorded in 320 quadrats each for herbs, shrubs and trees at 64 stations

of 12 different localities at a distance of about 5 km. Primary results showed that

vascular plants of To Ghar include 12 species of Pteridophytes, 6 Gymnosperms, and

313 Angiosperms. The dicotyledons dominate the flora of the study area that is

represented by 80 families, 199 genera and 270 species followed by monocotyledons

represented by 13 families, 36 genera and 43 species. Based on Raunkiaer System of

life form classification, all the recorded plant species were divided into eight classes.

The hemicryptophytes was dominant life form class represented by 108 species (32.6

%) followed by Therophytes with 73 plant species (22 %) of the total flora.

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Nanophanerophytes consist of 42 plant species (12.7%), Microphanerophytes 41

species (12.4 %), Chamaephytes 28 species (8.4%), Mesophanerophytes 12 plant

species (3.6%) and Mega phanerophytes 09 species. Similarly, class Geophytes

(Cryptophytes) was represented by 18 plant species.

For extensive results and vegetation modeling, presence, absence (1,0) data on 331

species and 64 stations were analyzed in PCORD version 5 to classify habitat types

and plant communities via Cluster and Two Way Cluster Analyses. Two major

habitat types and 6 plant communities were established. Species area curves were

drawn to prove the adequacy of sampling size. Indicator Species Analyses (ISA)

were used to identify indicator of each microenvironment and habitat type. Plant

abundance data were treated in CANOCO version 4.5 to measure the ecological

gradient of plant species and communities of the region. Detrended Correspondence

Analysis (DCA) a type of indirect gradient analyses reconfirms the results of Cluster

and Two way Cluster Analyses. Moreover, direct gradient analysis procedures were

adapted using Canonical Correspondence Analysis (CCA) to measure the effect of

environmental variables on vegetation structure, composition and diversity.

Variables like elevation, soil depth, soil erosion, grazing pressure and slope aspect

were significant in determining vegetation dynamics.The study furnishes baseline

data and useful information for taxonomic, bio-geographic, floristic and

conservation studies. This study will help botanists, conservationists, ecologists,

managers and policy makers to improve, protect and manage the present vegetation

status and sustainably for future generations.

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Chapter 1 INTRODUCTION

1.1 Plant Biodiversity

The term Biodiversity was recently introduced by Walter Rosen in 1985, although

the origin of this concept can be observed in the past botanical studies (Jenkins,

2003). Biodiversity includes the diversity of all species of plants, animals and other

microorganisms. Wilcox, (1984) defined biodiversity as “the diversity of life form in

given region, the ecological role they perform and genetic diversity they comprise”.

Biodiversity positively affects ecosystem functioning (Hooper et al., 2005). It is of

great importance for human life, as most of the materials for food, fuel, clothing and

shelter are obtained from living organisms. Biodiversity also provides different

things indirectly, like water, air and fertile soil. Only 1.75 million living species of the

world are described out of approximately 30 million living species (Hawksworth &

Kalin-Arroyo, 1995). A large number of species are yet to be known to science.

1.1.1 Importance of Plant Diversity

Plants are vital part of biodiversity. Plants provide food, firewood, cover, medicines

and protection to other organisms. Biodiversity plays asignificant role in stoppage of

flood, landslides, soil degradation, wind erosion, siltation of water reservoir, global

warming and raising of the sea level. Plants play a vital role in protecting the

environment, and maintaining ecosystem constancy and provide habitats for other

living organisms. Most of the things we eat directly or indirectly obtained from

plants. Most of the people of the developing countries cannot afford medicines and

depend on natural medicines which are mainly obtained from plants. It is estimated

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that 80% of the world’s population are dependent on traditional medicines (Akerele

1993). The World Heath organization estimates that 70-90% of the people living in

developing countries rely on medicinal plants for their primary health care (WHO,

2011). Several modern medicines contain active constituents that are directly

obtained from living organisms (Akerele et al., 1991). In Pakistan, about 50 % of the

drug currently used in modern medicine is prepared synthetically from

petrochemical-based raw materials (Hussain, 1987). Hocking (1958) estimated that in

early 1950 up to 84% of the Pakistani population was dependent on traditional

medicine for all or the majority of their medicinal requirements. Herbal medicins are

becoming more popular in the cure of minor ailments and there is great risk that

many medicinal plants today, face either extinction or loss of genetic diversity

(Hoareau and Silva, 1999).

1.1.2 Threats to Biodiversity

Plant biodiversity is changing rapidly due to a number of natural as well as

anthropogenic influences, e.g., climatic change, invasive species, over exploitation of

human and pollution. Climatic change may results the change in the timing of

seasonal activities of species. Species may not obtain suitable habitat and food for

survival due to local climatic changes. The high concentration of CO2 and reduction

of wind speed may result in the extinction of plant species which are dependent on

the wind for dispersal of their seeds (Nathan, et al., 2011). Another important threat

to biodiversity is rapid increase in population. With the increase of population,

natural habitats are being damaged and plant communities are disturbed. A number

of plant species are rapidly vanishing due to tremendous increase in human

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population, urbanization and overuse of natural resources (Heywood, 1995;

Western, 2001). It is recognized that extinction of a species results due to human

activities who have transformed the natural habitat in agriculture and livestock

fields (Vitousek et al., 1997; Lambin et al., 2003). Habitat loss or degradation for one

species will certainly constitute habitat gain or enhancement for some other species

(Probst & Weinrich, 1993). Loss of species results in the change in diversity and it has

a significant impact on other vegetation. Woody plants affect the diversity and

richness of ground flora. Modifications in the forest structure may result in the

extinction of certain species. (Vellend et al., 2006). Nearly 380 plant species are

known to have become recently extinct globally (Walter & Gillet, 1998; Mishra et al.,

2004). Anthropogenic interference remained one of the major threat to the species

extinction during last 100 years. It is assessed that, this trend will result in the

elimination of about one million species, by the end of the 20th century (Meyers &

Ayensu, 1983).

Grazing is another important determinant of biodiversity loss (Sher et al., 2010)

investigated that grazing can reduce the diversity up to 60%. It has

a direct influence on the plant biodiversity of an area (Vallentine, 2001).

Overgrazing results in the decrease soil depth and organic matter and potential land

productivity.

Conservation of biodiversity is needed for survival and development of the human

being. The sustainable use of biological resources is the most effective conservation

method for biodiversity. The biodiversity can be conserved through the involvement

of local people who are the beneficiaries of natural resources. By conservation of

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biodiversity, we can provide fuel wood, fiber, natural medicines and other

requirements for future generation and we can prevent land sliding, siltation in

dams, protect our water reservoir and maintain ecological balance.

1.1.3 Biodiversity of Pakistan

Pakistan has an important geographical location with rich floral diversity. The three

great mountains Karakoram, Hindukash and Himalaya are the important reservoirs

of biological diversity. Five of the fourteen highest mountains in the world are found

in Pakistan. There are four phytogeographical regions, i.e. Iranoturanian, Sino

Japanese, Soharo Sindian and Indian. Annual rainfalls in the country, ranging from

30-1350 mm. Some of the rarest animals and plants are found in Pakistan. There are

six endemic mammal species in Pakistan. More than 6000 vascular plants have been

reported in the region (Stewart, 1972). About 7.1% of the total flora is endemic.

About 80% of the endemic flowering plants of Pakistan are restricted to the northern

and western mountains (Ali & Qaiser, 1986).

About 4.8% of the total area in Pakistan consists of forest (Anonymous, 2005) and

40% of total forests comprise of coniferous forests (Aftab & Hickey, 2010). The most

familiar species found in these forests are Abies pindrow, Aesculus indica, Acacia

modesta, Juglans regia, Picea smithiana, Pinus roxburghii, Pinus wallichiana, and Taxus

wallichiana (Haq et al., 2010 & Awan et al., 2013).These forests are the important

source of timber, fuel wood, medicinal plants, and food for grazing animals and

protect soil from erosion. Similarly, they provide habitat for wildlife (Khan, 2009).

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The study of biodiversity in our area was initiated in 1820-1822 by Moorcroft. He

documented the vegetation of Ladakh and Kashmir, followed by V. Jacquemont in

1828-1832 who described the flora of Punjab and Kashmir. The first extensive

exploration record in Pakistan is available in J. D Hooker’s “Flora of British India”

(1872-1997). It provided comprehensive information about the flora of the region.

Later on R. R. Stewart conducted extensive survey in almost all parts of the country

and deposited about 6000 species at Gorden College Herbarium, Rawalpindi. He

published“An Annotated Catalogue of the Vascular Plants of Pakistan and Kashmir”

(Stewart, 1972) providing a base for the flora of Pakistan. The Flora of Pakistan is a

comprehensive inventory of plants of Pakistan. About 47 Botanists have contributed

to the Flora of Pakistan. The floristic diversity of many regions has recently been

introduced by different botanists, Haq et al ., (2010); Khan et al .,(2013a); Ilyas et al .,

(2013); Badshah et al .,(2013); Shah & Rozina (2013) Qureshi et al ., (2014) and

Shaheen et al ., (2014).

1.2 Phytosociological approach to Plant Biodiversity

Information regarding vegetation provides basis for estimation of forthcoming

changes and help in biological conservation (Kent & Coker, 1994). Phytosociology is

study that attempts to describe the variation in plant communities.

Phytosociological procedures are used to classify plant species, quantify vegetation

and assess its relationships with the surrounding environment. It is involved in

quantitative calculation of various parameters like, density, frequency, cover and

abundance etc. The variation in the total number of species is a result of species

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interaction of specific environmental setting (Ricklefs, 2006). Many factors are

considered to be important for exploring environmental gradients of vegetation

diversity (Lomolino, 2001). In mountainous landscape elevation is an important

factor for determination of vegetation types. Elevation from sea level represents a

complex gradient along which many environmental variables change concurrently.

The change in altitude is reflected by change in floristic composition (Sakya & Bania,

1998). It performs in the way as latitudinal gradient does; in both such cases a

decrease in species richness from equator to pole and sea level to mountain peaks

has been observed (Gaston, 2000; Willig et al., 2003; Rahbek, 1995; Brown &

Lomolino 1998). Generally temperature decreases with increasing altitude, which

further specifies the boundaries of prominent vegetation types (Komer, 2000).

Change in floristic diversity along different environmental variables is a key topic of

ecological study and has been described by different authors in different regions

with reference to meteorological conditions, yield, biotic interaction, environmental

variations and history (Givnish, 1999).

1.2.1 Phytosociological study in Pakistan

Pakistan is divided into nine ecological zones on the basis of temperature, moisture

availability, elevation and soil conditions. Due to these diverse climatic conditions;

Pakistan is rich in biodiversity of fauna and flora. Each ecological zone inhabits

particular trees and plant species. Himalaya is one of the mountainous regions

where most of the natural forest resources of Pakistan are found. Pakistan has an

altitude ranging from 0-8611m and is gifted with deserts, forest valleys, snow bound

mountains, rivers and lakes, estuaries and oceans.Due to important geographical

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position it has rich floral diversity. A lot of research is reported in the area of

phytosociology on different scales in the world and Pakistan.

The phytosociological study in Pakistan was initiated by by D.M. Currie, under a

research project of FAO. The vegetation of Thal was investigated by Monsi and Khan

(1960) and it was compared with the flora of other areas of Pakistan. The

phytosociological research in Northern areas of Pakistan, was conducted by Ahmed,

(1976, 1986, and 1988). Ahmed (1986) studied the vegetation of some foot hills of

Himalaya range in Pakistan. He described many phytosociological attributes in the

area. Whittaker (1965) observed that the distribution of tree, shrub and herb

diversities has been found to be affected by the presence of different soil moisture

regimes. Malik et al., (1990a) described three plant communities in Sund Gali

Muzzafarabad Azad Jummu and Kashmir. They reported that in the study area

Therophytes and Nanophytes vegetation was dominant. Ahmed et al., (2006)

conducted phytosociological survey in 184 sampling stands in different climatic

zones of Himalayan forests of Pakistan. Based on floristic composition and

importance value, 24 different communities and 4 monospecific forest vegetations

were recognized. They described that many communities are similar in floristic

composition, but differ quantitatively. The phytosociology of Pir Chinasi Hills of

AJK Pakistan was described by Malik et al., (2007). They studied vegetation structure

in relation to ecological factors and documented thirteen plant communities in the

region. Many other workers have presented their research work in different regions

of the country i.e., Malik et al., (2001), Malik and Malik (2004), Malik (2005), Ahmed

et al., (2006) Ahmad et al. (2008), Choudhary (2001), Choudhary et al., (2005), Sher

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and Khan (2007), Badshah et. al. (2010), Ahmed et al ., (2012), Saima et al ., (2010),

Qureshi et al ., (2014), Khan et al ., (2014) and Zareen et al., (2015) (Fig:1.1a).

In spite of many floristic explorations still certain areas in the northern Pakistan have

not been undergone detailed quantitative floristic studies. One of such regions is

district Tor Ghar Kyber Pakhtunkhwa, Pakistan situated on the western boundary of

lesser Himalayas. In these scenarios, it is important to quantify vegetation in relation

to its surroundings (Khan et al., 2011).

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Fig:1.1a Map indicating the site where previous studies have been undertaken.

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1.3 Study Area

1.3.1 Location

The study area Tor Ghar is situated at the western edge of the lesser Himalayas at

the bank of Indus (Hazara division Khyber Pakhtunkhwa province of Pakistan). It is

a rugged mountainous region, shares its borders with Tanawal on south, Agror,

Tikuari and Nandiar on the east, Indus River and Thakot on the north and District

Buner to the west. The only road transverse Tor Ghar from Darband to Thakot is 85

km. Floristically, it is part of the Western Himalayan Province (Takhtadzhian &

Cronquist, 1986).It can be located on 34º 32' - 34º 50' N, and 72º 48' - 72º58' E. The

altitude of District ranges from 450 masl to 3,500 masl.

1.3.2 Topography and Soil

Tor Ghar is largely dominated by mountains and hills. The lowest point of the

district is the Indus River while the highest peak is Machesar (2950 masl). Soil

erosion and land slides are common due to steep slopes. According to observations

of Divisional Forest Officer, Battagram, in 1976 the parent rocks are composed of

genesis, schists, granite and micaschists. The soil is loose, friable with a reasonable

amount of clay and is suitable for agriculture. Overgrazing and deforestation are the

major causes of soil erosion in the region. The soil in the sub alpine forest is rich in

humus. During construction of the Tarbela dam some of the best agricultural land

was damaged.

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Figure 1.1b: Map indicating the location of study area

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Figure 1.2 Scenic view of village Soral (Near Station 10, Zizari 2 above 800msl)

1.3.3 Geology

Geology of the area is not investigated in detail. Preliminary field visits by officers

from the geological survey of Pakistan indicates the occurrence of different minerals

like white marble, lead, zinc, magnetite, soap stone, mica and Bauxite.

1.3.4 Climate

The climate of the area is subtropical in the lower region and moist temperate and

sub alpine type in the higher elevations. In the district there is no meteorological

station, therefore, climatic data was got from nearest meteorological station at Oghi

which is situated on the eastern boundary. Total annual rain fall during the year

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2013 was 38.9 inches. The maximum rain fall occurs during the month of February

and July. The climate of Tor Ghar is pleasant in spring and autumn but winter are

very harsh because of heavy snow fall. Heavy rainfall occurs in spring and early

autumn. The snow fall occurs generally between 15 December to the end of February

each year. During this period the area remains cut off from other parts of the

province and the life of the people living at high altitude becomes troublesome and

inactive. Snow fall is up to 8 feet at 3000 m elevation and decreases with the

descending altitude. The average rainfall data (inches) for the period of three years

(2012 to 2014) are given below:

Table-1.1 Monthly total precipitation of three years from 2012 to 2014 (Data rounded to 1 decimal unit)

Year 2014 2013 2012

January 1.3 0.7 0.5

February 5.8 8.7 8.5

March 4.1 3.3 3.3

April 3 2 3.5

May 1.8 3.2 0.5

June 3.1 5.8 0.6

July 5 6.7 1.5

August 3.2 5.1 8.9

September 2 0.7 7.2

October 0.5 0.5 0.6

November 1.7 1.5 0.6

December 3 0.2 4.2

Total rain (Inch)

34.5 38.7 39.9

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Figure 1.3 Monthly Rain fall (inches) during the year 2012

Figure 1.4 Monthly Rain Fall (inches) during the year 2013

-2

0

2

4

6

8

10

Jan Feb March April May june July August Sept. Oct. Nov. Dec.

Rain FallJan Feb March April May june

July August Sept. Oct. Nov. Dec.

0

1

2

3

4

5

6

7

8

9

10

Jan Feb March April May june July August Sept. Oct. Nov. Dec.

Rain Fall Jan Feb March April May june

July August Sept. Oct. Nov. Dec.

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Fig: 1.5 Monthly Rain Fall (inches) during the year 2014

The monthly mean maximum and mean minimum temperature (Fahrenheit) of three

last years from 2012 to 2014 is given below:

Table1.2 Mean maximum and minimum temperature (Fahrenheit) of three year

Year Jan. Feb. March April May June July Aug. Sep. Oct. Nov. Dec.

2012 Max. 53.6 59.6 60.2 66.5 76.3 90.8 91.5 82.6 80.3 76 61 54.7

Min. 36.9 41.5 42.2 40.7 56.5 67.1 68.4 66 50 54 45 39.2

2013 Max. 42.7 51.9 63.8 68.5 77.5 92.1 83.3 82.9 78.1 80 65 49.1

Min. 32.4 35.2 39.3 42.1 57.2 69.5 65.9 67.3 48.2 53 40 34

2014 Max. 49.8 55.3 64.1 70.2 78.8 94.1 88.7 83.1 79.3 81 64.1 50.2

Min. 34.2 37.3 40.1 39.7 58.1 68.9 70.2 68.1 49.2 52 43 36

0

1

2

3

4

5

6

7

Jan Feb March April May june July August Sept. Oct. Nov. Dec.

Rain Fall

Jan Feb March April May june

July August Sept. Oct. Nov. Dec.

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1.3.5 Population

According to the 1998 population census the population of Tor Ghar was 1,74,862.

Total area is 454 sq. km. The majority of the population depends on forestry,

livestock, agriculture, etc. More than half of the population is settled in the highland

zone. Tor Ghar is a neglected side valley and lacks the facilities of education and

health. The society is tribal and attached to old tribal traditions. Conflicts are

resolved through jirga (a local jury of elders).

The major profession of the people is small scale agriculture. Only 25% land is

cultivable with maize and wheat as a major crop. There was a strong inclination

among the people to cultivate poppy or inclined toward deforestation. The other

source of income includes small scale business in the big cities of the country. A

large portion of the male population is working in Karachi. The most population is

below the poverty line and women are given low social status.

Fig: 1.6 Main tribes and percentage of Population in district Tor Ghar

Population %, Madakhel, 15.36, 15% Population %,

HassanZai, 18.38, 19%

Population %, AkaZai, 17.09,

17%

Population %, Basikhel,

43.02, 43%

Population %, Nusratkhel,

6.13, 6%

Population %

Madakhel HassanZai AkaZai Basikhel Nusratkhel

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1.3.6. Livestock

There are vast and fertile grazing fields in the district Tor Ghar. Cattle and goats are

raised by the people living at higher altitudes for milk and meat. Due to overgrazing

significant degradation of certain slopes has taken place. The nomadic Gujars also

bring large number of sheep, cattle and goats during summer to grasslands.

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1.3.7 Forests

The higher altitude is covered with blue pine forests which are described as

Himalayan moist temperate and are the best habitats of wild birds and animals.

These forests are owned by the inhabitant of the area who are not aware about the

significance of these forest resources. These forests are composed of Kail (Pinus

wallichiana), Fir (Abies pindrow) and spruce (Picea smithiana). Legal and illegal cuttings

had badly destroyed these forests. Management of forest resources is needed to save

this treasure of nature.

Figure. 1.7 Heavy snow fall during December 2012 at Manasar, 2650 msl (Station

Dni 11)

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Figure 1.8 Highest peak of the district, Machasar 2950msl (Station Dni13)

1.3.8 Agriculture and Land Use

Agriculture land is less but there are abundant grassland and pastures which

support a large number of livestock, including goat, sheep, buffalo and cows.

Agriculture crops grown in the region are wheat, maize and rice. All the cereals are

inter-cropped with variety of vegetables. This region was also popular for poppy

cultivation. Kala Dhaka Area Development Project (KDADP) was started in 1990

through US Agency for international development in Pakistan to decrease the

Opium (Poppy) cultivation in the Tor Ghar. The project achieved the target of

eliminating the poppy from the region.

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Figure 1.9 Ruin of oldest mosque near the transect 2, (Station Kk1).

1.3.9 Vegetation and Agro climatic Zones in the Study Area

The district can be divided into three general ecological zones viz. River valley,

evergreen forest and sub alpine pastures. The upper part of the district is covered

with thick forest of pine, oak, horse chestnut and wild cherry, but most of the slopes

are stony and barren.

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Figure. 1.10 Humid subtropical habitat near Judbah tasect 5 (station Jdbh1)

Figure 1.11 Moist temperate Forest near Torban (station Dni13)

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1.4 Justification of Study /Rationale for Choice of Study location

The Himalaya is highest mountain of the world, having diverse vegetation therefore,

very important for biodiversity and ecological research (Sheng, 2001). More than

18,500 plant species were reported from these mountains (Sheng, 1998). The

Himalayas are the birth place of ten of the largest rivers in Asia. Economy of south

Asian countries is mainly based on the flow of these rivers from the Himalayas.

These rivers ensure food security by providing irrigation water for rice and wheat

crops which are the major staple food (Rasul, 2010). High mountains all over the

world are important hot spots for endemic floras (Nowak et al., 2011) and are the

ecosystem where climatic change is more visible and species extinction is very

rapid (Kullman, 2010). There is a dire need to study, document and map the

vegetation of diverse areas of Himalaya, according to international standards, to

provide a baseline for effective plant conservation strategies and sustainable

development.

Plants are the important source of food, shelter, medicines, fodder and are

contributing economic and social well being of the country and playing important

role in protecting environment, regulating climatic changes and preventing soil

erosion.

One major component of phytodiversity of the region are forests which act as a store

house of plant and animal genetic resources and contribute to genetic diversity.

Demand of the forests protection is increasing worldwide while forest area is

continuously decreasing. Preservation and sustainable management of forest

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ecosystem is important. Anthropogenic pressure due to heavy deforestation, grazing

and soil erosion have destructed the vegetation. This situation will become worse if

present rate of deforestation and other anthropogenic influences continued and

reforestation on large scale are not made. It is dire need to protect, preserve and

maintain the plant resources of the area.

Floristic surveys are useful in proper identification of plant-wealth for their

utilization on a scientific and systematic basis. Inventorying of biodiversity is the

fundamental starting point of any phytosocialogical study needed for its

conservation, sustainable use and management. Similarly collections of Voucher

specimens from a region help to measure biodiversity and vegetation structure of

particular area. This data tells us changes occurring in the vegetation structure in

response to disturbances. Inventory of plants also play asignificant role in increasing

our understanding and information on availability of resources and its relationship

with the inhabitants. To develop conservation strategies and estimate the changes

taking place in the vegetation patterns of any area, it is required to have a detailed

floristic description of that area based on floristic surveys, collections and accurate

identification. A number of research workers prepared inventories based on plant

data collected from different parts of Himalaya and adjacent mountain ranges of

Pakistan.(e.g., Hussain et al., 2007, Khan et al., 2007, Khan & Khatoon, 2007,

Qureshi et al., 2009, Ahmad et al., 2009, Ali & Qaiser, 2009). Some areas of the

country including study area (District Tor Ghar) are still unexplored till this

study.

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District Tor Ghar is the area lies in the western Himalya, which is neglected by

botanist and ecologists. A number of social, administrative and communication

problems were the main hurdles in the exploration of such a remote area.There is no

previous record of floristic or ecological study in the area. The area is unexplored in

all aspects of plants and no work has been done regarding plant phytosociolgy,

phytodiversity, conservation and restoration. Extensive review of literature revealed

that there is not a single record of collected specimens from District Torghar. The

indigenous peoples of Tor Ghar are continousely destroying plants wealth even

after establishment of the new district. People of the area are mostly illiterate and

not aware of loss of biodiversity and its impact on human life. They are using

natural resources ruthlessly. They use live stocks for milk, meat, transportation and

farming. Seasonal nomads with large number of cattle’s also stay in this area.

The large numbers of live stocks result in the overgrazing of natural vegetation. The

study area lies in the catchment area of Indus River. Over grazing, expansion of

agriculture land and recent development after creation of new district resulted in the

deforestration and enhanced rate of soil erosion which may increase siltation in the

Indus River. In this scenario, proper inventorying and monitoring of plant

biodiversity of the area is utmost important.

Keeping in view the utmost importance of first ever exploration of the western

most part of the Himalaya the present study was planned not only to explore,

identify and document vascular plant species to provide scientific basis for

future research but also mention the environmental gradients changing the

vegetation structure, species composition and even conservation stata of the plant

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biodiversity. Phenological behavior of plants documented in the research project will

be helpful to study the relationship between climate and growing period.

In case of most of the phytosociological studies, researchers have studied either

qualitative characteristics of the vegetation or have recorded species importance

value indices. A very limited number of studies have used modern

numerical/statistical techniques to quantify vegetation particularly in the

distant and least accessible parts of these mountains. In addition, research on

plant community identification and classification (using modern techniques) has so

far been restricted to the plains and low altitude areas (eg., Malik & Husain, 2006,

Dasti et al., 2007, Malik et al., 2007, Saima et al., 2009, Siddiqui et al., 2009). Most

of the remote mountainous areas are the hotspots for vegetation due to their

important phytogeographical location. This research project not only resulted the

scientific exploration of plant resources but also also contributed to the literature,

information about the biodiversity, natural resources of the country, climate change,

habitat destruction, anthropogenic influences on plant species and understanding

the environmental gradients responsible for the distribution of species and

communities.

The quantitative and qualitative assessment of the results will be used to evaluate

the past, present and future of biodiversity and conservation status of the plant

resources of the area. In this study, modern statistical approaches were applied for

the first time in this region. This study will also provide a baseline for effective plant

conservation strategies and sustainable development. It provides a set of valuable

recommendations for improvement of socioeconomic conditions of the people.

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The present study was, therefore, formulated to collect information about the plant

biodiversity of this region with a target to quantify plant communities at varying

landscape with following objectives.

1.4.1 Aims and Objectives

To explore, identify and document vascular plant species of the district.

To prepare checklist of vascular plant species of the area under study.

To evaluate species distributions and plant communities using modern

phytosociological techniques.

To identify environmental gradients responsible for species distribution.

To suggest possible measures for improvement of plant resources and

socioeconomic status of the area.

To furnish baseline data and useful informations to protect local flora for the

future generation.

Voucher specimen of valuable plant collection will be added to Herbarium of

Hazara University will serve as refrence for future research.

27

Chapter 2

MATERIAL AND METHODS

2.1 Study Area

Present study was designed to analyze floristic diversity along environmental

gradients in district Tor Ghar during 2012-13. Tor Ghar is situated at the bank of

Indus (Hazara division Khyber Pakhtunkhwa province of Pakistan) within latitude

on 34º 32' to 34º 50' north and between longitudes 72º 48' - 72º58' E. It has been given

a status of District of Khyber Pakhtunkhwa on 28 January, 2011. The altitudinal

variation of District Tor Ghar ranges between 450 to 2,950 masl.

2.2 Preparation for the field Study

Map of the district was obtained from forest department. Climatic data of study site

was obtained from Pakistan metrological department and general information about

the area was collected.

2.3 Field Survey

The research area was extensively visited throughout flowering and fruiting seasons

during 2012-13. Specimens were collected from various localities of the district,

properly tagged and given voucher number along field notes. The herbaceous

specimen always included enough of underground parts to show their

characteristics. Most of the plants were pressed on spot and data related to their

locality, scientific/ local names, habit, habitat and family was immediately recorded.

The plants were arranged in such a way that there were no overlapping parts. The

large size specimens were folded in the “V”, “Z”, “W” and “C” shapes. The

28

specimens were pressed in blotting paper or old newspapers for about 24 to 48

hours. Newspapers were changed regularly for 15 to 20 days till specimen get

properly dried.Dried plants were poisoned in aqueous solution of mercuric chloride

and mounted in triplicate on standard herbarium sheets (42 x 28cm) with the help of

glue. Field data was transferred to the herbarium sheets. The plant specimens were

identified with the help of flora of Pakistan (Stewart, 1972; Nasir and Ali 1971-1995;

Ali and Qaiser 1991-2012). The identified and mounted copies of voucher specimens

were deposited in the Herbarium of Hazara University Mansehra. Data obtained

from field work in selected sites was used to prepare a complete floristic list of plant

species along with families.

2.4 Phytosociological Study Design

In order to collect information about floristic diversity along environmental

gradients, the entire area was divided into 12 transects (Fig. 2.1). Base line was

established at Indus River. Transects were made perpendicular to the base line.

These transects were selected randomly to get accurate statistical inferences. Each

transect was approximately located at a distance of 5Km. These selected sites were

divided into altitudinal belts of 200 masl. Samplings were started from Indus River.

The selection of starting point for systematic sampling was random; the remaining

sampling was carried out at the interval of 200msl from this starting point. Three

quadrats (each having an area of 10 × 10m, 5 × 5 m and 1 × 1m) were placed

randomly for determining the community structure of tree, herbs and shrubs

respectively following the protocol of Misra, (1968) and Khan et al., (2012). There

29

were 5 replicate in each stand. In each quadrat, trees were recorded with >31.5cm

cbh (circumference at breast height i.e., 1.37m above ground). Individuals within the

cbh range of 10.5 to 31.4cm were considered as shrub and <10.5cm cbh as herb. The

data was collected during 2012 and 2013.

Coordinate including altitude, longitude and latitude of selected site was recorded

using GPS of Garmin e trex Hc series, vista HCx, while aspects were recorded by

compass (Table-2.1).

30

Fig:2.1 Map indicating location of the Transects in study area

31

Table 2.1 Detail of study sites: Localities, altitudinal range (msl), longitude N0,

latitude E0, aspect, number of stations and number of quadrates at each of 64 stations S

. N

o.

Lo

cali

tie

s

Alt

itu

din

al

ran

ge (

msl

)

L

on

git

ud

e N

0

Lati

tud

e E

0

Asp

ect

No

. o

f st

ati

on

No

. o

f q

uad

rate

1 Tor Kandow 640-1040 34025. 953” 0720 49.424” South 03 15

2 Kotkay 467-1260 340 27. 839” 0720 50.555” East 05 25

3a Dadam (E) 506-900 340 31. 335” 0720 49.312” East 03 15

3b Dadam (N) 600-950 340 31. 380" 0720 49.636" North 03 15

4 Toot banda 550-935 340 31. 222” 0720 49.534” East 03 15

5 Dar bani 650-2950 340 33. 576” 0720 49.262” East 10 30

6 Kotley 540-940 340 36. 717” 0720 49.8121” East 03 15

7 Judbah 530-2660 340 36. 6895” 0720 47.410” East 12 60

8 Shagahi 540-1600 340 40. 542” 0720 48.250” East 06 30

9 Shadock 550-1100 340 41 .590” 0720 47.628” East 04 20

10 Zizari 650-1450 340 44. 547” 0720 49.814” East 05 25

11 Dheri 600-1210 340 45. 666” 0720 50.766” East 04 20

12 Gorial 600-1000 340 45 .476” 0720 53.360” East 03 15

Total 64 320

32

Figure 2.2 Field data collection in Study area

2.4.1 Parameter Studied

Following parameters were recorded within each quadrat

2.4.1.1 Density

Density was recorded after Malik and Hussain (1987) by following formula.

𝐷𝑒𝑛𝑠𝑖𝑡𝑦 = Total number of individual of a species in all quadrats

total number of quadrats

Relative Density =Density value of a species in all quadrats x 100

Total density of all species

33

2.4.1.2 Frequency

Frequency was calculated after Brower and Zar (1977) and expressed as a

percentage.

Frequecny

=Density value of a species Number of time in which a species occur x 100

Total number of quadrats

Relative Frequecny =Frequency value of a species x 100

Total frequency of all species

2.4.1.3 Canopy Cover

Canopy Cover was calculated after Daubenmire (1959) using following scale.

Class Range of Coverage Midpoint %

1 Cover up to 5% of ground 2.5%

2 Cover 5% to 25% of ground 15.0%

3 Cover 25% to 50% of ground 37.5%

4 Cover 50% to 75% of ground 62.5%

5 Cover 75% to 95% of ground 85.0%

6 Cover 95% to 100% 0f ground 97.5%

2.4.1.4 Basal Area

Basal area was measured by dbh method. For trees including lianas the diameter or

circumference of the trunks was measured with the help of measuring tape at a

breast height (dbh) i.e. 1.5 metres above the ground. The diameter was converted to

basal area by the formula r2 where r equals to 1/2dbh.

34

Relative basal area was measured by following formula

Relative basal area = Basal area of a species × 100

Total basal area of all species

The relative values were summed up to represent important value index, IVI as per

Curtis, (1959).

2.4.1.5 Importance Value Index (IVI)

Importance Value Index (IVI) was calculated by the method of Curtis, (1959).

IVI = R.D + R.F + R.C

Where IVI; importance value index, R.D; relative density, R.F; relative frequency and

R.C; relative cover.

2.4.1.6 Physiognomic features analyses

Aspect was measured using compass, slope was measured at each quadrate,

however, slope values for whole site was calculated by taking average of all the

values at that site.

Classes Class-1 Class-2 Class-3 Class-4

Degree of Slope Flate Gentle Slope Moderate Slope Steep Slope

Soil depth in the study sites was estimated with an iron rod of 1m length. The

following 03 classes were recorded for the soil depth in the study area.

Classes Class-1 Class-2 Class-3

Range of soil depth (cm) 01-50 50-200 >200

35

2.4.1.7 Habitat degradation analyses

Grazing intensity was determined by observations like, hoof marks, browsed foliage,

trampling and animal dung using following scale.

Class-1 Class-2 Class-3 Class-4

Un-grazed Moderately grazed

High grazing pressure

Severely grazed and degraded vegetation

While three erosion classes were recorded by direct observations in the study sites.

Class-I No noticeable effects of erosion

Class-II Moderately eroded, showing significant erosion

Class-III Severely eroded, indicating heavy soil erosion and land

degradation

2.4.1.8 Biological Spectrum (Life Form Classes)

The plants were divided into different life form classes (Phanerophytes,

Chamaephytes, Hemicryptophytes, Geophytes, Therophytes) and each life form

class was further subdivided on the basis of habitat, persistence of foliage and other

features after Raunkiaer (1934).

All species were listed from the localities with their habitat, ecological zone or forest

type and were classified into their respective life form class as follows:

Life form spectrum (%)

=Number of species falling in a particular life form class × 100

Total number of species

36

2.4.1.9 Species richness

Species richness in different localities of the area was calculated after Margalef (1958)

as follows.

R= S-1/In (n)

Where S; total number of species in a community, In; natural log, n; total number of

individual of all species in a community.

2.5 Statistical Analysis

Modern multivariate techniques were used to study the degree of variation found in

vegetation composition of a region.The use of these techniques make large data sets

mentally accessible, structurally recognizable and patterns explainable.

MS EXCEL 2013 was used for basic calculations like frequency, density, cover and

their relative values and to present different results graphically.

Modern statistical packages PC-ORD version 5 (McCune, 1986, McCune & Mefford,

1999) and CANOCO version 4.5 (ter Braak, 1988, ter Braak, 1989, ter Braak &

Smilauer, 2002) were used to analysed the data.

The data obtained for 331 vascular plant species 320 quadrats each for herbs, shrubs

and trees (total 960 quadrats) from 64 stations was subjected to statistical analysis to

find out relation between environmental factor, structure and composition of

vegetation. It includes qualitative data for all plant species i.e Presence/ absence

data and quantitative data consists of density, cover, frequency, relative density,

relative cover, relative frequency and Importance Values. For classification and

37

ordination qualitative data (presence/absence) was used as, it gives clear picture

than quatitative data.

The environmental data including altitude, soil erosion, slope, soil depth, grazing

pressure, for each station was also recorded. All the environmental variables were

treated as independent variables while quantitative attributes of plant species were

considered as dependent variables.

In present study different multivariate methods were used for community data.

These techniques are of two types: classification and ordination.

2.5.1 PC-ORD Analysis

To classify vegetation of the study area and identify different plant communities PC-

ORD version 5 was used. Different classification methods were used i.e., Cluster

Analysis (CA), Two Way Cluster Analysis (TWCA) and Indicator Species Analysis

(ISA), (Dufrene & Legendre, 1997).

2.5.1.1.Two Way Cluster Analyses (TWCA)

The (TWCA) is an important classification program used by plant ecologist. This

program results in the different communities. It was used for clusterization of

species and different localities in smaller groups which showed close

similarities. In this method results are presented in graphical form called a two-way

cluster dendrogram which explained the results more meaningfully and predictably

in the form of clusters. Dendrogram shows different groups or clusters in which the

degree of resemblance is reflected by size of branch. The vegetation

(presence/absence) data collected from district Tor Ghar was analyzed by two Way

38

Cluster Analysis (TWCA) to classify the vegetation into different plant communities.

The species are arranged in rows and samples in columns. A number of studies have

proved that TWCA is best method for the classification of the vegetation. Although a

great number of clustering systems for plant community classification are available

(Legendre & Legenrde, 1998) these techniques produce different outcomes on the

same data set. But the best technique is the one which provides a clear ecological

description for a specific purpose (Kent & Coker, 1992).

2.5.1.2 Cluster Analysis

Cluster analysis was used to describe the vegetation pattern in district Tor Ghar. The

data include 64 stations (samples) for 331 vascular plant species based on qualitative

data (presence/absence). It was used to identify different plant communities based

on Sorensen‘s (Bray Curtis) distance.

2.5.2 Indicator Species Analysis (ISA).

Informations about abundance of a species and fidelity in that group results in the

indicator value for each species. Each of the 331 species was evaluated to classify for

different environmental variables.

2.5.2 CANOCO Analysis

Indirect and direct environmental gradient analyses were performed using

CANOCO version 4.5 (Ter Braak &Barendregt, 1986, Ter Braak and Šmilauer. 1998).

It was used to investigate environmental gradients indirectly using a species matrix

or directly using both species and environmental data matrices.

2.5.2.1 InDirect gradient ordination

39

Indirect Ordination method includes Correspondence Analyses (CA), Principal

Component Analyses (PCA) and Detrended Correspondence Analysis (DCA).

Indirect gradient analysis involves the Ordination resulting only from species data.

These techniques have rarely been used in the phytosociological studies of Pakistani

terretories and can be found in the literature; For example the vegetation of Ayub

National Park was analysed by Jabeen and Ahmed (2009) using PCOrd version 5

and CANOCO 4.5 for the classification and ordination of vegetation. They used

TWINSPAN, DCA and CCA for analyses giving four plant communities and

correlations of association with different environmental variables.

Detrended Correspondence Analysis (DCA):

DCA is one of the important and efficient methods of indirect gradient analysis and

is used when there is no environmental data. The axes in DCA are measured by the

average standard deviation of species turnover (sd units). A 50% change in species

composition occurs in a distance of about 1 SD unit. A species disappear over a

distance of about 4 SD units. The more SD units that occur along the axis the more

change in species composition is revealed. Thus, the sd units of DCA are a helpful to

measure the beta diversity. Species have, on average, a habitat breadth (as measure

by standard deviations) of 1. Detrended Correspondence Analysis (DCA) was used

to avoid the distortion from results as described by Hill & Gauch Jr., (1980), and ter

Braak, (1988). DCA provide more efficient and interpretable results than CA and

PCA and hence was used in present study for ordination analysis. CANODRAW a

utility of CANOCO was used to plot the data as an ordination plot. Environmental

data are used after that to interpret the ordination. Data is initially arranged

40

according to their floristic resemblance without the addition of environmental

variables and then correlated the axes with environmental data. The axes formed

during the ordination analysis are in descending order of importance. The first axis

is most significant and describes the most variation in the floristic data

2.5.2.2 Direct gradient ordination

In direct gradient analysis we study the florostic changes along known

environmental gradients.

Canonical Correspondence Analysis (CCA)

Canonical Correspondence Analysis (CCA is a direct ordination method used to

study correlation and regression between the floristic data and environmental data.

It is widely used and most robust direct gradient exploration technique, therefore

selected for present research project. In this method species and environmental

factors are plotted on the same graph but using different scales. The Arrows are

strained from the joint centered ordination axes to the points showing environmental

variables and the directions of the arrows indicate the direction in which the

abundance of a variable increases most rapidly. The length of the arrow indicates the

rate of change in abundance in that direction. Occurrence of plant species at the end

or away from the tip of the arrows display positive correlation and the species which

occur at the opposite end reflect negative correlation.

These analyses were used to investigate different plant communities found in the

district Tor Ghar and to study the effect of different environmental variables in plant

distribution in the study area.

41

Chapter 3 RESULTS

3.1 Floristic Diversity

3.1.1 Diversity among Vascular Plant Groups

A total of 331 vascular plant species belonging to 246 genera and 101 families were

recorded including 12 species of Pteridophytes (3.61%) and 6 species of

gymnosperms (1.8%). Angiospermic flora consists of 313 species (94.5%) belonging

235 genera and 93 families. Among angiosperms, the dicotyledons dominated the

flora and were represented by 79 families, 197 genera and 267 species (80.66%), while

monocotyledons were composed of 14 families, 38 genera and 46 species (13.89%),

(Figure 3.1).

Figure 3.1: Pi chart representing floristic diversity

42

3.1.2 Species richness within families:

The highest number of species were recorded for Asteraceae (25., 7.53%) followed by

Leguminosae (Fabaceae) (24species., 7.22%), Poaceae (21 species.,6.32%), Lamiaceae

(17, 5.1%) Rosaceae and Polygonaceae (14 each, 4.2%).

Among Pteridophytes Adiantaceae and Dryopteridaceae were largest families

represented by 4 species each. Equisetaceae, Pteridaceae and Sinopteridaceae were

having one species each. Among Gymnosperms Pinaceae was the largest family (5

spp.) followed by Taxaceae (1 spp.).

Among Angiosperms, dicots were represented by forty two families having a single

species each, another twenty one families were represented by 2 species, whereas

thirteen families possessed 3 species each. Six families were composed of 4 species

and only one family containg 5 species (table 3.1).

Figure 3.2 Percentage of different plant families in District Tor Ghar

43

3.1.3 Diversity within plant habit:

Based on plant growth habit, 55 tree species, 48 species of shrubs and 240 herbs were

reported from the area. All the reported gymnosperms were represented by tree

habit only, while angiosperms were represented by 50 tree and 48 shrubs. Majority

of the flora was represented by herbs (240 species)

Figure 3.3: Diagramatic representation of plant habit (percent) diversity

3.1.4 Life Form diversity

Among Ruankiaer lifeform classes, hemicryptophyte was dominant life form class

represented by 108 species (32.6 %) followed by Therophytes (73 species, 22%),

Nanophanerophytes (42.species.12.7%), Microphanerophytes(41 species 12.4%),

Chamaephytes, 28 species (8.4%), Mesophanerophytes, 12 plant species (3.6%) and

Megaphanerophytes, (9 species, 2.7%). Geophytes were represented by 18 species

(5.4%) (Fig: 3.4).

Herbs70%

Shrubs14%

trees16%

44

Fig:3.4 Representation of Raunkiaer life form classes within flora

0

20

40

60

80

100

120

45

Table 3.1(a) Inventory of Vascular plants collected during first exploration of District Torghar

S. No

Family S.No

Botanical Name

Life form class

Local Name Habit Flowering period

Locality Altitude

Pteridophytes

1 Adiantaceae 1 Adiantum caudatum Linnaeus G Herb _______ Soral 1200

2 Adiantum incisum Forssk. G Sumbel Herb _____ Soral 1300

3 Adiantum venustum D. Don. G Babozai Herb ______ Soral 1200

4 Adiantum capillus - veneris Linn. G Sumbel Herb _______ Haleema 1400

2 Aspleniaceae 5 Asplenium septentrionL.) Hoffmann, CH

Wakha rangaey Herb ________ Haleema 2000

3 Dryoteridaceae 6 Polystichum lonchitis L G Herb ______ Shagae 800

7 Polystichum munitum (Kaulf.) C.Presl

G Herb Shagae 800

8 Polystichum squarrosum (D. Don) Fée,

G Herb Behrhi 1800

9 Polystichum tsussimense (Hook.) J.Sm.

G Herb Behrhi 1800

4 Equisetaceae 10 Equisetum ramosissimum Desf. H Bandakay Herb Kotkay 800

5 Pteridaceae 11 Pteris cretica Linnaeus, H Qinchi panra Herb ________ Soral 1200

6 Sinopteridaceae 12 Onychium contiguum Wall. Ex Hope H Herb Soral 1200

Dicotyledons

46

7 Acanthaceae 13 Barleria cristata L. H

Tadrelu Herb June- August

Kunhar 800

14 Dicliptera bupleuroides Nees. CH Herb April-june Kandar 800

15 Justicia adhatoda L. NP Baikar Shrub May-July Kotkay 700

8 Amaranthaceae 16 Achyranthes bidentata Blume Th Geshay/

Spay boty Herb Nov –Jan Kotkay 1800

17 Achyranthus aspera L. TH Puth Kanda Herb March-May Kotkay 1800

18 Aerva javanica (Burm.f) Juss. H Spin booti Herb April-June Dadam 500

19 Aerva sanguinolenta (Linn.) Blume H Spin Botee Herb March-June Kunhar 700

20 Amaranthus caudatus Linn. TH

Chaleray Herb June-August

Judbah 700

21 Amaranthus spinesus L. TH Karsusa Herb May-Agust Judbah 700

22 Amaranthus viridis Linn. Th Ganhar Herb April-June Kalash 1400

9 Anacardiaceae 23 Pistacia integerrima J.L.Stewart. Brandis

Ms Shanae Tree April –June Kotkay 1500

24 Cotinus coggyria Scop. Mc Chamy-arlakhta

/ Paan Shrub March-May Soral 1200

10 Apiaceae (Umbelifererae)

25 Aethusa cynapium L. H

Herb March-May Soral 1000

26 Bupleurum falcatum L. H

Herb

May-August

Shatal 2000

27 Eryngium Sp.L. H Herb May-July Dadam 1000

28 Foeniculum vulgare Mill. TH Sounf Herb April-June Shatal 1600

29 Oenanthe crocata L CH Herb March-May Bartuni 2300

30 Oenanthe javanica (Bllume) DC. CH Herb March-May Bartuni 2300

47

31 Scandix pectin-veneris L. Th Herb March-May Bartuni 2000

32 Torilis leptophylla (L.) Reichb Th

Herb March –May

Kotkay 600

11 Apocynaceae 33 Nerium indicum Mill. NP Gandirey Shrub May-July Maira 800

34 Nerium oleander L. NP

Kaneer Shrub March-August

Maira 900

35 Carissa opaca Stapf. en Haines NP Granda Shrub Kotkay 700

12 Aquifoliaceae 36 Ilex dipyrena Wall Ms Tree April-June Machasar 3000

13 Araliaceae 37 Hedra nepalensis K.Koch. NP

Parweta Shrub June-August

Gantharh 2600

14 Asclepiadaceae 38 Calotropis procera (Ait.) Ait. F NP

Spulmay Shrub Jan-December

Darbani 800

39 Caralluma tuberculata N.E. Brown H

Choung Herb June-July Machra Akazai

800

40 Periploca aphylla Dcne. H Bata/Barara Herb March-May Darbani 700

15 Asteraceae (Compositae)

41 Achillea millifolium L. H

Karkarah Herb April-June Soral 1000

42 Artemisia absinthium L H

Tarkha Herb April-August

Kandar 800

43 Artemisia scoparia Waldst. & Kit H Gandi booti/

Jaokae Herb April-July Kandar 900

44 Artemisia vulgaris L. H Joakay Herb April-June Haleema 1500

45 Calendula arvensis L. H Ziar Guley Herb April-July Maira 710

46 Carthmus oxycantha M.Bieb H Kareza Herb April-July Asharay 1150

47 Centaurea iberica Trevir & Spreng H

Herb May-July Dadam 800

48 Chamaemelum nobile (L.) All. H Herb June-July Machasar 2500

48

49 Cichorium intybus L CH Hanshamakey/

Kasny Herb April-June Shagai 800

50 Circium falconeri (Hook. F) Petr. Th

Herb Dada banda

1200

51 Cirsium arvense (L.) Scop. Th

Herb May-August

Soral 1250

52 Conyza canadensis (L.) Corgn. TH Maloocheii Herb April-June Balkot 1000

53 Galinsoga parviflora Cavanilles H

Herb March- May

Balkot 1000

54 Lactuca serriola L. Th Herb Shadak 730

55 Parthenium hysterophorus L. Th

Herb Through out the year

Maira 700

56 Pulicaria crispa (Forssk.) Oliv. TH

Herb November-March

Shatal 1000

57 Sassurea heteromalla (D.Don) Hand H

Herb May-June Shatal 1500

58 Senesio chrysanthemoides DC. G Ghopga Herb June-Sept Kamesar 2670

59 Silybum marianum (L) Gaertn Th

Karizaghena Herb Marc-June Gave bazar

800

60 Solidago virgaurea L. H Bangira Herb May-July Ganthar 1800

61 Sonchus asper (L) Hill. Th Shodapae Herb April-July Sargay 900

62 Taraxicum officinale Webb. H Ziar guley Herb April-July Sabe hill 1200

63 Tegetes erecta L Th Herb April –June Shah dak 700

64 Vernonia Sinerea (L.)Lees. Th Tor Zeera Herb May-July Sorban 2000

65 Xanthium strumarium Linn. NP Ghishkey Herb May-July Kotley 1510

49

16 Balsaminaceae 66 Impatiens bicolor Royle. Th writh athrang Herb June- Sept. Machasar 3000

67 Impatiens edgeworthii Hk. F. Th Ziar athreng Herb June- Sept. Machasar 2900

17 Berberidaceae 68 Berberis lycium Royle. NP Kwaray

/Sumbal Shrub

April- Agust

Soral 1200

18 Betulaceae 69 Alnus nitida (Spach.) Endl. MC

Girae/ Sharol Tree Agust- Nov.

Soral 1250

19 Bombacaceae 70 Bombax ceiba L. MG

Simble Tree December-March

Kotkay 1820

20 Boraginaceae 71 Cynoglossum lanceolatum Forssk. Th Pachy Herb May-June Surmal 800

72 Lithospermum officinale L. H

Herb April- August

Kotkay 1500

73 Onosma hispida Wall.Ex G. Don H Kairry Herb March-June Shagai 820

74 Trichodesma indicum (L.) R. Br., Prodr.

H Herb

Through out the year

Soral 1230

21 Brasicaceae (Cruciferae)

75 Alliaria petiolata (M.Bieb)Cavara & Grande

H Gangli thom/ Balu

Herb May-July Nawagae 730

76 Capsella bursa-pestoris L. Th Bambaesa Herb March-June Haleema 1300

77 Cardamine hirsuta L. H Chargh butay Herb March-May Aarekh 1070

78 Erophila verna L. Th

Herb March – June

Tot Banda

800

79 Lepidium aucheri Boiss Th Halam Herb Marh-June Berhi 1350

80 Nasturtium officinale R. Br. CH Tarmera Herb April-July Shagae 670

81 Neslia apiculata Fisch TH Herb April-June Shatal 1000

82 Sisymbrium irrio L. Th Oorae Herb April-June Darbani 790

50

83 Arabidopsis thaliana (Linn.) Heynh. H

Herb April-July Judbah 900

84 Coronopus didymus (L.) Sm.

TH Hazar dani Herb

April-August

Soral 1650

22 Buddlejaceae 85 Buddleja crispa Bth. NP Booe Shrub March-May Ganthar 2300

23 Buxaceae 86 Buxus wallichiana Bill. NP Shrub March-May Ganthar 2600

87 Sarcococca saligna (D.Don) Muell. NP Ladan Shrub April-Sept Brathoo 2600

24 Cactaceae 88 Opuntia dillenii Haw. CH

Zakoom Herb June-August

Tot banda 800

25 Campanulaceae 89 Campanula benthamii Wall. H Herb March-July Soral 1200

90 Codonopsis clematidea (Schrenk) C.B.Clarke.

H Herb

July – august

Soral 1000

26 Cannabaceae 91 Cannabis sativa L. TH Bhang Herb April-July Kandar 800

27 Capparidaceae 92 Cleome scaposa DC., Prodr H

Herb May-August

Shatal 840

28 Caprifoliaceae 93 Viburnum grandiflorum Wall. ex DC. NP

Chamiaray Shrub March-July Kandow/ Manasar

2400

94 Viburnum cotinifolium D. Don NP

Ghanpmzewa Shrub March- May

Mana sar 2600

29 Caryophyllaceae 95 Silene conidea L. Th

Babrai Herb May-July Sarbago 1580

96 Sillene vulgaris (Moench) Garcke Th

Matranga Herb May- Agugust

Sarbago 730

97 Stellaria media (L.) Vill. Th

Laroley Herb April-August

Aarakh 1200

30 Celastraceae 98 Maytenus royleanus (Wall. ex Lawson) Cufodontis

NP Patakhi / Azghakay

Shrub March-July Kotkay 1150

51

31 Chenopodiaceae 99 Chenopodium album L. Th

Larmay Sarmea Herb March-May Dadam 700

100 Chenopodium ambrosioides L Th Benakai Herb Mach-May Dadam 756

101 Chenopodium botrys L. Th Skha Khawra Herb April-June Kotley 1050

102 Chenopodium murale L. Th Skha Botey Herb April-June Gut 1100

32 Convolvulaceae 103 Convolvulus arvensis L. H Pirwathai Herb April-July Jegal 840

104 Evolvulus alsinoides (L.) Th Sargulay Herb April-June Jegal 1100

33 Cornaceae 105 Cornus macrophylla Wall. ex Roxb MS

Kandara Tree April - june Soral 1300

34 Cucurbitaceae 106 Citrullus colocynthis (Linn.) Schrad

H Tumba / Manzil/ Markundai

Herb May-July Dadam 800

107 Solena amplexicaulis (Lam.)Gandhi Th

Kakora Herb April-June Soral Village

1240

35 Cuscutaceae 108 Cuscuta reflexa Roxb TH Zeara Zeelai Herb April-July Berrhi 1100

109 Cuscuta gigantea Griff. TH Ooloe Herb April-July Soral 1100

36 Dioscoraceae 110 Dioscorea deltoidea Wall.ex Kunth H

Konel Herb April-July Chor kalan

2300

37 Ebenaceae 111 Diospyrus lotus L. MC

Tor Amlok Tree June-Agugust

Manasar 2800

38 Euphorbiaceae 112 Andrachne cordifolia (Wall. ex Decne.) Muell.

H Kurkun Shrub June-Oct. Shahtal 1500

113 Euphorbia helioscopia L. H Mandro Herb April-June Kalash 1650

114 Euphorbia hirta L. H

Skha Botay Herb June-August

Kalash 1650

52

115 Euphorbia hispida Boiss. H Herb May-July Soral 1100

116 Euphorbia peplus L. H Herb Nawagae 650

117 Euphorbia prostrata Aiton CH Herb Nawagae 700

118 Euphorbia Wallichii Hk. H Zangly

Mandaro Herb June-Sept. Larhsar 2650

119 Mallotus philippensis (Lam.)Muess. NP

Kambella Shrub July-Sept. Kandar 900

120 Ricinus communis L. NP Arharhanda Herb March-July Judbah 700

39 Fagaceae 121 Quercus dilatata Lindle. ex Royle MC

Tor banj Tree April – May

Manasar 2500

122 Quercus baloot Griff. MC

Brungi Tree April –May Chor kalan

2300

123 Quercus leucotrichophora A. Camus MC

Rin Tree Manasar 2400

124 Quercus incana Roxb MC Spin banj Tree April-May Doda 1100

40 Fumariaceae 125 Fumaria indica (Hausskn) Pusley TH Papra Herb April-June Soral 1230

126 Fumaria officinalis L. TH Herb March-July Soral 1200

41 Gentianaceae 127 Gentiana kurroo Royle TH

Nilkant Herb Agust-Oct. Chota Kandow

2700

128 Swertia ciliata (G. Don) B.L. Burtt

Th Chirata/ Momera

Herb June-August

Loto Banda

1800

42 Geraniaceae 129 Geranium lucidum L. TH

Herb April-June Danda Banda

1300

130 Geranium ocellatum Camb. TH

Herb April-July Shangaldarh

1500

53

131 Geranium wallichianum D.Don ex Sweet

H Sargrrai Herb

June-August

Shangaldarh

2600

43 Guttiferae 132 Hypericum oblongifolium L. Np Shin Chai Shrub Mach-July Soral 1300

133 Hypericum perforatum L. H

Warmang Booty Herb June-September

Soral 1200

44 Hippocastanaceae 134 Aesculus indica (Wall.ex Camb.)Hk. MG

Ashanr Tree Jabara 2300

45 Juglandaceae 135 Juglans regia Linn MG Ghuz Tree April- July Soral 1240

46 Lamiaceae (Labiateae)

136 Ajuga bracteosa Wall., Benth. H

Guti Herb April-June Shagae 800

137 Ajuga reptan L. H Guti Herb April-June Nawagae 1800

138 Anisomeles indica (L.) O. Kuntze Th

Herb April-Sept

Shangaldarh

2400

139 Colebrookia oppositifolia Smith NP Balbadarh/

Benda Shrub Jan.- April Kotkay 700

140 Isodon rugosus (Wall. ex Benth.) Codd

MC Khangere/ Salasla

Shrub July-Sept Larsar 2300

141 Lamium amplexicaule L. Th Herb March-June Shatal 1450

142 Marrubium vulgare L. H

Gandana Herb May-August

Shatal 2000

143 Mentha arvensis L. H

Podina Herb July-August

Shagae 800

144 Mentha longifolia (L.) Huds H

Vanaley Herb June-August

Shagae 760

145 Mentha spicata L. H Zangli Podina Herb May-July Soral 1200

146 Nepeta cataria L. CH Jalbang Herb April-June Guth 1400

54

147 Otostegia limbata (Bth) Boiss NP

Spinaghzai Shrub March-June Tor Kandow

825

148 Salvia lanata Roxburgh CH Khathriki Herb April- july Soral 1200

149 Salvia moorcroftiana Wall. ex Benth. H Kali jarhi / Khar

ghoagh Herb April-June Soral 1200

150 Stachys parviflora Benth. H Spera Botay Herb March-July Larhsar 2300

151 Thymus linearis Benth NP Da Ghar sper

kay Herb Jun-August Manasar 2500

152 Salvia aethiopis L. Th Kali jarhi Herb March-July Kamesar 2300

47 Leguminosae (Caesalpinioideae)

153 Caesalpinia decapitala (Roth) Alston. MC

Jara Shrub March- April

Shagae 800

154 Bauhinia variegata Linn Np Kulhar Tree April-July Kotkay 750

47 Leguminosae (Mimosoideae)

155 Acacia modesta Wall. MS

Palosa Tree March- July

Kotkay 800

156 Acacia nilotica Linn. MC

Kikar Tree June- August

Kandar 700

157 Albezzia lebbek (L) Benth. MS Srikh Tree April –July Berhi 1200

158 Albezzia procera (Roxb) Benth. MC Tree April- june Berhi 900

47 Leguminosae (Papilionoideae)

159 Robinia pseudoacacia Linn.

CH

Toor kiker Tree April-June Kotkay 900

160 Butea monosperma (Lam.) O. Kuntz. H

Badar Tree Kotkay 680

161 Crotolaria mediginea Lamk H Herb Shagae 700

55

162 Delbergia sisso Roxb. H Shaewa Tree May-July Kandar 700

163 Indigofera heterantha Wall.ex rand. H

Ghoraja Shrub May-July Soral 1260

164 Trifolium repens L. MC Shaotal Herb April-June Judbah 800

165 Argyrolobium roseum (Comb) Janb & spach

H Makana Herb

February-April

Banda 1500

166 Astragalus amherstianus Royle ex Benth.

NP Asli Batawach Herb Soral 1300

167 Astragalus graveolens Buch.-Ham.ex Benth.

NP Bitawach E Naqli/Azghakay

Herb April-June Soral 1250

168 Astragalus macropterus DC Th

Herb June-July Danda Banda

1600

169 Astragalus neomonodelphus H. T. Tsai & T. T. Yu

Th Herb Soral 1300

170 Lathyrus aphaca L Th Korkamani Herb March-May Maira 600

171 Lathyrus emodii (Wall.ex Fritsch) Ali Th

Herb Maira 600

172 Lotus corniculatus L. Th Herb March-May Dheri 580

173 Medicago polymorpha L. MC

Shpeshtiary Herb March-April

Dheri 800

174 Melilotus officinalis (L.)Desr. H Lewanay Herb April-June Shadak 700

175 Trifolium pratense Linn. H

Herb

July – august

Judbah 720

176 Vicia hirsuta (Linn.) S.F.Gray Th Marghaikhpa Herb March-June Shadak 600

56

48 Loranthaceae 177 Viscum album Linn. NP

Prewatai Shrub July-September

Manasar 2360

49 Lythraceae 178 Woodfordia fruticosa (L.)S.Kurz NP Thawi Shrub March-May Soral 1230

50 Malvaceae 179 Malva neglecta Wall. Th

Panerak Herb April-July Dhera kahu

530

180 Malva sylvestris Linn Th

Samchal Herb May- Agugust

Dhera kahu

530

51 Meliaceae 181 Azadiracha indica L. MC Neem Tree April-May Soral 1200

182 Cedrella serrata Royle MC Daravi Tree May-June Shatal 1700

183 Melia azedarach Linn. MC

Bakaina/Lagan Tree April- July Daur Maira

680

52 Menispermaceae 184 Cissampelos pareira Linn Th

Katoon Herb March-july Macahasar

2200

53 Moraceae 185 Broussonetia papyrifera (L.)L’ Herit ex Vent

MC Kaghazi toot Tree June-July Kotkay 1100

186 Ficus benghalensis L. MS

Barh Tree Through out the year

Judbah 600

187 Ficus carica Forsk. MS

Inzar Tree April-June Dorh Mera

600

188 Ficus elastica Roxb. MS

Rubber Tree March-April

Dadam 700

189 Ficus palmata Forsk. MS

Inzar Tree March-June Daur Maira

600

190 Ficus racemosa L. MS

Armol Tree July-August

Berhi 1800

191 Moras nigra L. MC Tor toot Tree March-may Kotkay 730

192 Morus alba L. MC Spin Toot Tree May-June Kandar 680

57

54 Myrsinaceae 193 Myrsine africana Linn Np

Khukhar Shrub Kotkay 638

55 Myrtaceae 194 Eucalyptus spp. MS Leichi Tree April-June Kandar 700

56 Nyctaginaceae 195 Mirabilis jalapa L. G

Gul e badam Herb June-August

Balkot 950

57 Oleaceae 196 Jasminum humile Linn NP Konkoni Shrub April-July Soral 1200

197 Jasminum nudiflorum Lindl.

NP Zangli Chambeli Shrub March-May Soral 1200

198 Olea ferruginea Royle NP Khoona Tree April-June Arnil 1800

58 Onagraceae 199 Oenthera rosea L. CH Herb march-July Soral 1100

59 Oxalidaceae 200 Oxalis carniculatus L. H Threwakey Herb March-June Shagae 700

60 Plantaginaceae 201 Plantago lanceolata L. Th Shalet Herb March-May Guth 1000

202 Plantago major L. Th Baltanga jabai Herb March-May Guth 1100

61 Platanaceae 203 Platanus orientalis L. Mg Chinar Tree May-June Soral 1250

62 Podophyllaceae 204 Podophyllum emodi Wall. ex Royle, H Ban kakri /

Banwangun Herb April-May Tor band 2000

63 Polygonaceae 205 Persicaria hydropiper (L.) Spach, H Herb April-Sept Maira 500

206 Polygonum aviculare Linnaeus H Pal poluk Herb April-May Shagae 770

207 Polygonum plebejum R. Br. G Herb Shagae 680

208 Rumex acetosa L. CH Tarokey Herb May-Sept. Zizari 600

209 Rumex dentatus L. CH Shalkhay Herb May-June Zizari 620

210 Rumex hastatus D. Don, Prodr. CH Tarokai Herb April-June Soral 1100

58

211 Rumex vesicarius L. CH

Herb April-June

Tor Kandow

700

212 Bistorta amplexicaulis (D.Don) Greene

H Rain Herb March-June Soral 1200

64 Portulacaceae 213 Portulaca oleracea L. H

Warkharay Herb July-September

Shatal 1600

65 Primulaceae 214 Anagalus arvensis L. Th

Ghutyalai Herb Feb.-April Tot Banda

800

66 Punicaceae 215 Punica granatum Linn MC Narsaw-ay/

Anunghoray Tree March-May

Dorh mera

600

67 Ranunculaceae 216 Aconitum napellus L. G Herb Agust-Sept. Haleema 1200

217 Aconitum Sp G

Sarbawali Herb July-September

Soral 1200

218 Aquilegia Sp. L H

Oudi Guley Herb April-August

Soral 1260

219 Caltha alba Camb. TH Makhanr Path Herb May-July Kalash 2300

220 Clematis grata Wall. CH

Chenjan Wala Herb June-August

Kotkay 600

221 Clematis montana Buch CH Herb Kalash 1800

222 Clematis orientalis L. CH

Zelay Herb June-August

Kandar 800

223 Ranunculus arvensis L. CH Chaghchejakai Herb May-July Shadak 600

224 Ranunculus muricatus L. CH Ziar guley Herb April-June Shadak 6210

225 Ranunculus scleratus L. CH Jashaghai Herb April-June Gazagat 1600

68 Rhamnaceae 226 Ziziphus jujuba Mill. MC

Sezen Tree May-June Tot Banda

740

227

Ziziphus nummularia (Burm. f.) Wight & Arn.

MC Karkanda Shrub May-July

Gawe Bazar

600

228 Ziziphus oxyphylla Edgew. MC Elanai Shrub June- Tot 800

59

September Banda

69 Rosaceae 229 Cotoneaster bacillaris Wall. ex Lindl Mc

Looni Shrub May-August

Berhi 1100

230 Cotoneaster frigidusWall. ex Lindl Mc

Shrub May-August

Guth 1300

231 Cotoneaster nummularia Fish & Mey Mc Mamana Shrub May-July Berhi 1000

232 Cydonia oblonga Miller MC Pub Tree March-May Soral 1400

233 Duchesnea indica (Andr.)Focke H Mewa Herb March-May Shagae 800

234 Fragaria nubicola (Hook.f.) Lindl. ex Lacaita

TH Da zimakaytoot Herb

May-August

Shagae 800

235 Potentilla nepalensis Hook. f. TH

Kunacy Herb June-August

Kamesar 2500

236 Prunus armeniaca L. MC Khubanai Tree Feb.-March Shatal 1100

237 Pyrus communis L. MC

Nashpati Tree Feb.-April Shangaldarh

2300

238 Pyrus pashia Ham ex D. Don. MC

Tangai Tree March-May Shangaldarh

2300

239 Rosa indica L. NP Sor gulab Shrub April-June Shagae 700

240 Rosa moschata J. Herm NP Shrub Barhi 1000

241 Rubus ellipticus Smith. NP Karwara Shrub May-July Guth 1300

242 Rubus fructicosus Hook .f NP Karwara Shrub March-May Berhi 1040

70 Rubiaceae 243 Borreria articularis (L.F.) FN . Will. H Herb Guth 1040

244 Galium aparine L. H Herb March-July Gantharh 2500

245 Galium elegans Wall. In Roxb H

Herb June-August

Gantharh 2500

60

246 Galium tenuissimum M. Bieb H

Herb June-August

Kara Kandow

2600

71 Rutaceae 247 Boenninghausenia albiflora (Hook.) Reichb.

H Pissu mar Herb

July-August

Bartuni Machaser

3000

248 Skimmia laureola (DC.) Sieb. & Zucc. ex Walp

NP Nameer/ Nazar pana

Shrub June- September

Machasar 3000

249 Zanthoxylum armatum DC. MC

Dambara Shrub April-June Dhorh Maira

600

72 Salicaceae 250 Populus alba Linnaeus MS Watani sperdar Tree April-June Soral 1300

251 Salix tetrasperma Roxb. MC Walla Tree April-June Soral 1200

73 Sapindaceae 252 Cardiospermum halicacabum L. H

Khubara plt Herb Oct.- Nov. Shangal darh

2500

253 Dodonaea vescosa (L.) Jacq NP Ghoraskai Shrub May-june Kunhar 700

254 Sapindus mukorossi Gaertn., MC Ritha Tree May-June Kalash 1300

74 Saxifragaceae 255 Bergenia ciliata Sternb. G Koerat Herb May-july Kamesar 2500

75 Scrophulariaceae 256 Verbascum thapsus L. H Kharghwagh Herb March-May Kotkay 700

257 Mazus pumilus (N. L. Burman) Steenis

Th Herb March-May Kotkey 700

258 Veronica persica Poiret Th Herb March-July Shadak 700

259 Veronica polita Fr. Th Herb March-May Asharhe 900

76 Simarubaceae 260 Ailanthus altissima (Mill.) Swingle MC Lagan Tree March-June Sorban 2100

77 Solanaceae 261 Datura stramonium L. H Batoora Herb June-Sept. Dadam 690

262 Solanum incanum L. H

Herb Through out the year

Kotkay 700

61

263 Solanum nigrum L. Th Karmacho Herb April-June Dadam 700

264 Solanum pseudocapsicum L. NP

Mirchola Shrub May- June Machra Akazai

600

265 Solanum virginianum L. H

Herb Tor Kandow

800

266 Withania somnifera (L.) Dunal NP Shrub March-July Kalash 1800

78 Thymeliaceae 267 Daphne mucronata Royle H Laighonai/

Kutilal Shrub April-June Sorban 2300

79 Tiliaceae 268 Corchorus trilocularis Linn H Herb June-Sept. Shatal 1000

269 Grewia optiva Drummond .ex Burret MC Pastaw-oney Tree April- Sept. Shadak 500

80 Ulmaceae 270 Celtis australis Linn. MC Taghagaha /

Batkar Tree March-May

Charh/ Shagae

1100

81 Urticaceae 271 Urtica dioica L. H Jelbung Herb May-July Bartuni 2500

272 Urtica pilulifera Linn H Herb May-July Bartuni 2500

273 Debregeasia salicifolia (D.Don) Rendle

NP Chewr Shrub March-May Arekh 1800

82 Valerianaceae 274 Valeriana jatamansi Jones H

Mushk bala Herb March- May

Arekh 1800

83 Verbenaceae 275 Vitex negundo Linn NP Marghondai Shrub May-July Kalash 1700

276 Verbena officinalis Linn. Th Shmoakai Herb May-Sept. Palosa 800

84 Violaceae 277 Viola canescens Wall. ex Roxb Th

Herb April-July Shangal darh

2500

278 Viola odorata L. Th

Banafsha Herb May-August

Mana sar 2500

85 Vitaceae 279 Vitis vinifera L. NP Kwar Shrub May-June Soral 1400

Gymnosperms

62

86 Pinaceae 280 Cedrus deodara (Roxb. ex D. Don), G. Don

H Lamb. / Ranzhra

Tree ______ Machasar 3000

281 Picea smithiana (Wall.) Boiss, MG Nakhtar Tree ________ Machasar 3000

282 Pinus roxburghii Sargent MG Nakhtar Tree Guth 1240

283 Pinus wallichiana A. B. Jackson MG Pewach Tree ________ Manasar 2500

284 Abies pindrow Royle. MG Achal Tree Machasar 3000

87 Taxaceae 285 Taxus wallichiana (Zucc.)Pilger MG Bunya Tree __________ Arekh 2000

Monocotyledons

88 Agavaceae 286 Agave sisalana Perrine ex Engelm. Mc Herb April-June Darbani 600

287 Yucca aloifolia L NP Shrub Jun Darbani 600

89 Alliaceae 288 Allium griffithianum Boiss G Herb March-June Tot Banda 800

90 Amaryllidaceae 289 Narcissus tazetta L. TH

NargisGulae Herb December-March

Aararkh 2450

91 Araceae 390 Acorus calamus L. H Skhaweja Herb April-July Shatal 1625

291 Arisaema flavum (Forssk.)Schott. G Marjaarei Herb May-July Gantharh 2550

292 Arisaema jacquemontii Blume. G Marjaarei Herb May-July Manasar 2400

293 Arisaema utile Hook.f.ex. Schott G Tora marjarai Herb May-July Gantharh 2050

294 Colocasia esculenta (Linn.) Schott G

Karchalo Herb June-August

Judbah 700

92 Asparagaceae 295 Asparagus adscandens Roixb. CH Spin tindoray Herb March-July Totbanda 800

296 Asparagus capitatus Baker CH

Tindoray Herb March-July Machra Akazai

700

297 Asparagus officinalis L. CH

Tindoray Herb March-June Toot banda

830

63

93 Asphodelaceae 298 Aloe vera (L.) Burm. MC

Zaqam botay Herb May-August

Deheri 700

94 Cannaceae 299 Canna indica L. H Herb March-June Dehri 700

95 Colchicaceae 300 Colchicum luteum Baker. Th Herb Feb-May Pyan 2300

96 Commelinaceae 301 Commelina benghalensis L. CH

Kanchara Herb May-August

Shatal 1450

302 Commelina poludosa Blume CH Kanjuna Herb May-june Shatal 1400

97 Convallariaceae 303 Polygonatum multiforum (L.) All. H Noor e Alam Herb April-July Shagae 600

304 Polygonatum Verticillatum H

Noor e Alam Herb June-August

Shagae 600

98 Cyperaceae 305 Cyperus cyperoides L. H Della Herb May-June Berhi 1200

99 Liliaceae 306 Gagea lutea (L) Ker-Gawl H

Qaimat Gulay Herb June-August

Mahtorh 1100

307 Tulipa clusiana (Hook.) Regel H Gantul Herb March-May Banda 1100

100 Palmae 308 Nannorrhops ritchieana (Griff.) Aitchison

Np Mazri palm Shrub

Tot Banda

700

309 Phoenix dactylifera L. MC

Khajoor Tree March-April

Darbani 600

310 Phoenix sylvestris (L.) Roxb MC

Jangli khajur Tree March-April

Darbani 600

101 Poaceae (Gramineae)

311 Agrostis stolonifera L. H

Herb March-June Shatal 1500

312 Apluta aristata L. H Herb Kamesar 2400

313 Aristida depressa Retz H Herb March-July Nawagae 800

314 Arundo donax L. H Nara Herb April-June Kotkay 760

315 Avena fetua L. Th Jawdar Herb April-July Judbah 800

64

316 Bambusa glaucescens (Willd.) Sieb. H Bans Shrub Kunhar 700

317 Brachiaria ramosa (Linn.) Stap H Herb July – Oct Kandar 700

318 Calamagrostis decora Hook. f., Fl. Bri

H Herb Berhi 1000

319 Chrysopogon serrulatus Trin H Herb Jun-sep Arnil 730

320 Cynodon dactylon ( L) Pers H

Kabal Herb May-August

Arnil 730

321 Dactylotenium aegyptium (L) P.Beauv H Herb Shahtal 1530

322 Deschampsia caespitosa L H Broom grass Herb Kotkay 700

323 Desmostachya bipinnata (L) Stapf H

Drab Herb May-August

Kotley 700

324 Dichanthium annulatum (Forssk)Stapf.

H Herb Gigani 1600

325 Digitaria nodosa Perl. H Herb Berhi 1000

326 Imperata cylindrica (L)P. Beauv H

Herb Dehra kahu

570

327 Phalaris minor Retz Th Herb Shadak 600

328 Phragmites australis (Cay.) Trin. H Herb July- Oct Sorban 1200

329 Poa bulbosa L. H

Herb April-October

Larhsar 2000

330 Poa alpina Linn. H Herb June-Sept. Gantharh 2550

331 Sorghum haleeparse (L) Pers. H Dadam Herb May-Sept. Danda 1200

65

3.2 Phytosociological Aspects

Phytosocilogical features were studied in two sections i.e. classification and

ordination.

3.2.1 Classification: (Cluster Analysis)

Cluster analysis revealed that software divided all the 64 stations into two broad

groups. Upper arm again divided into subgroups at 30% cutoff level. The upper sub

group was composed of 5 stations representing Community 1. Lower subgroup was

further divided into two associations at 37% cutoff level depicting community 2 (13

stations) and 3 (8 stations).

Second major arm was divided at level of 20%. Upper subgroup again divided into

two associations representing Community 4 (14 stations) and 5 (12 stations), while

the lower subgroup represented Community 6 (8 stations).

Community 1 included Kotkay, Behri and Gut, while Community 2 was represented

by parts of Kotley, Judba, Shagai, Gorial and Zizari. Community 3 was located at

Toot banda Akazai, Darbani and Sabah Top. Important localities of community 4

were Dadabanda, Haleema, Nawagai and Pian hills. Community 5 was at South of

the Sahbah hill, Arnil, Shatal and lower part of Shangal Dar area. Community 6

represented the localities of Bakain, Bratho, Cando Gali, Mana Sar, Doda Gata,

Torban and Macahisar (Fig.3.5a & b).

3.2.1.1 Communities structure

The following communities were identified based on cluster analyses.

66

3.2.1.1.1 Community I: Delbergia sisso- Mallotus philippensis -Cyperus cyperoides

The community was located at altitude ranging from 467 -1260 masl (Table 3.1b).

Important localities of this community were Kotkay, Behrhi and Gut area. A total of

101 plants species were reported in this community including 22 tree, 19 shrub and

60 herb species.The tree, shrub and herb layers were characterized by Delbergia sisso,

Mallotus philippensis and Cyperus cyperoides as dominant species on the basis of

abundance. The other important tree species were represented by Pinus roxburghii,

Delbergia sisso, Ailanthus altissima and Acacia nilotica. The shrub layer consisted of

Mallotus philippensis, Dodonaea vescosa, Rubus spp, Colebrookia oppositifolia, Maytenus

royleanus, Berberis lycium, Cotinus coggyria and Carissa opaca. Important herbs

included Cynodon dactylon, Chrysopogon serrulatus, Digitaria nodosa, Verbena officinalis,

Erophila Verna, Trichodesma indicum, Torilis leptophylla.

Rare trees of this community included Bombax ceiba, Butea monosperma, Pyrus pashia,

Quercus incana and Alnus nitida. Among rare shrubs are Hypericum oblongifolium,

Rubus ellipticus, Justicia adhatoda, and Xanthoxylum armatum species. The rare herbs

comprised of Bergenia ciliata, Aerva sp. and Verbascum Thapsus (Fig 3.7-3.10).

67

Fig. 3.5 (a): Cluster dendrograms describing association among all six communities.

68

Figure 3.5 (b) Sketch Map Showing the location of different Plant communities in the study area

69

Fig.3.6 Habitat representation of community 1. (A Bheri, B: Kotkey)

A

B

70

The major life form was Hemicryptophytes (26.5%) followed by Nanophytes and

therophytes (18.2 and 17.3%). The microphanerophytes were 14.5%,

megaphanerophytes were 2.88% and mesophyte and chamaephytes were 6.7%

each.The share of geophytes was 8.6%.

Fig.3.7: Top 10 trees of the community 1 based on IVI in Delbergia-Mallotus-Cyperus

community. (Note:Pinus rox- Pinus roxburghii, Delbergia- Delbergia sisso, Acaci mod- Acacia

modesta, Acaci nil- Acacia nilotica Brousnetia- Broussonetia papyrifera, Celtis a- Celtis australis,

Ficus rac- Ficus racemosa, Alnthus alt- Ailanthus altissima, Albeza lb- Albezzia lebbek, Olea f- Olea

ferruginea).

0

50

100

150

200

250

300

IVI

71

Table: 3.1(b) Characteristic features of different Plant communities documented from

District Tor Ghar

Plant Community

CommunityI CommunityII Community III Community IV Community V Community VI

Elevation 467-1260 506-840 550-950 740-1400 900-2050 1930-2950

No of localities 5 15 8 16 12 8

Total No. of Species 101 160 121 229 220 149

Life form %

MC 14.5 14.9 16.5 15.15 6.5 12.4

MG 2.88 1.86 1.6 2.59 3.7 5.3

MS 6.7 5.59 2.47 3.03 3.7 3.35

Total ph 24.08 22.35 20.57 20.77 13.9 21.05

NP 18.2 14.28 20.66 15.5 17.4 13.5

TH 17.3 20.4 21.48 19.9 20 16.7

CH 6.7 7.4 6.6 6.6 8.9 6.77

G 8.6 3.72 1.65 5.6 6.3 7.3

H 26.5 31.6 28.9 32.03 32.8 32.0

No of Tree spp. 22 32 24 42 40 36

No. of Shrub spp. 19 23 24 38 38 26

No. of Herb spp. 60 105 73 149 142 86

Total spp. 101 160 121 229 220 148

Total IVI of 3 dominant tree species

954.0198

1778.78

917.2872

1431.006

1498.439

1104.649

Total IVI of 3 dominant Shrub species

531.6613

2000.198

1190.783

1021.539

1044.821

831.9647

Total IVI of 3 dominant Herb species

317.3438

1284.774

651.0351

597.3424

821.54

392.7304

Total IVI By tree species 1486.986 4272.181 300.8186 4110.033 3600.001 2300.402

Total IVI By Shrub species 1500 4302.49 292.9348 4200 3374.708 2230.089

Total IVI By Herb species 1500 4297.013 294.5652 4200 3481.292 2478.6

72

Fig. 3.8. Top 10 Shrub species of community 1 (Note: Malotus- Mallotus philippensis,

Ddonaea- Dodonaea vescosa, Rubus el- Rubus ellipticus, Maytenus- Maytenus royleanus, Colbrkia-

Colebrookia oppositifolia, Berbers l- Berberis lycium, Nerim ind- Nerium indicum, Myrsine- Myrsine

africana, Cotinus- Cotinus coggyria, Carissa- Carissa opaca)

Fig. 3.9. Top 10 Herbs of community 1 (Note: Cynodon- Cynodon dactylon, Cyperus- Cyperus

cyperoides , Dgitaria- Digitaria nodosa, Chryspgn- Chrysopogon serrulatus,Verbena of- Verbena officinalis,

Erophila-,Trchodsm- Trichodesma indicum,Torilis-Torilis leptophylla, Mrabilis- Mirabilis jalapa, Slanm

vir- Solanum virginianum)

0

20

40

60

80

100

120

140

160

180

200

IVI

0

20

40

60

80

100

120

140

IVI

73

Fig.3.10 Rare tree species of community 1 (Note Populus a- Populus alba, Ficus car- Ficus

carica, Melia az- Melia azedarach, Butea m- Butea monosperma, Pistacia- Pistacia integerrima, Bombax c-

Bombax ceiba, Pyrus pas- Pyrus pashia ,Qurcus fr- Quercus baloot Alnus nit- Alnus nitida, Tasy-

Unidentified)

Fig. 3.11 Total IVI of Rare herbs of the community 1(Note: Traxicum- Taraxicum officinale,

Adintm cp- Adiantum capillus- veneris, Acontm np- Aconitum napellus, Aerva san- Aerva sanguinolenta,

Bergenia- Bergenia ciliata, Acrnths b- Achyranthes bidentata, Verbascum- Verbascum thapsus, Ephrba hl-

Euphorbia helioscopia, Asplenium- Asplenium septentrionale, Acrnts as- Achyranthus aspera)

0

5

10

15

20

25

IVI

0

1

2

3

4

5

6

IVI

74

3.2.1.1.2 Community II Acacia modesta- Dodonaea viscosa - Cynodon dactylon

The second community is located at altitude ranging from 506-840 masl. Important

localities of this community were Kotley, Judbah, Sarbago, Shagai, Shadak, Gorial

and Zizari. A total of reported species from this community were 161.The dominant

tree species was Acacia modesta while other species with high IVI value were

Delbergia sisso, Ailanthus altissima, Broussonetia papyrifera, Acacia nilotica and Ficus

palmata. Characteristic species of shrub layer consists of Dodonaea vescosa, Mallotus

philippensis, Otostegia limbata, Justicia adhatoda, Colebrookia oppositifolia, Calotropis

procera, and Myrsine africana.

The dominant species of herb layer was Cynodon dactylon and other important herb

species include Chrysopogon, Digitaria nodosa, Agrostis stolonifera, Cannabis sativa,

Rumex hastatus and Aerva javanica.

Rare trees of the community include Cedrella serrata, Butea monosperma, Pyrus spp.and

Pistacia integerrima. Among rare shrubs Cotinus coggyria, Viburnum and Andrachne

cordifolia were documented, while the rare herbs consisted of Potentilla nepalensis,

Malva neglecta, Anagalus arvensis, and Melilotus officinalis (Fig. 3.12-3.18).

The dominant life form was Hemicryptophytes (31.6%) followed by therophytes

(20.4%). The Nanophytes and microphanerophytes were 14.28% and 14.9%

respectively while megaphanerophytes contributed 1.86% and Mesophytes were

5.59% and chamaephytes were 7.4% where as the share of Geophyteswas 3.72%.

75

Fig.3.12. Habitats and characteristic species of Community II (A Tor Kando:B: Kotley)

B

A

76

Fig: 3.13: IVI of top 10 tree species of community II (Note: Acaci mod- Acacia modesta,

Delbergia- Delbergia sisso, Alnthus alt- Ailanthus altissima, Brousnetia- Broussonetia papyrifera, Ficus pa-

Ficus palmate, Grewia op- Grewia optiva, Acaci nil- Acacia nilotica, Euclaptus- Euclaptus spp. ,Melia az-

Melia azedarach, Ficus car- Ficus carica)

Fig. 3.14: Top 10 Shrubs species of community II (Note: Ddonaea- Dodonaea vescosa,

Malotus- Mallotus philippensis, Otostgia- Otostegia limbata, Justicia- Justicia adhatoda, Myrsine- Myrsine

africana, Colbrkia- Colebrookia oppositifolia, Caltrops- Calotropis procera, Maytenus- Maytenus royleanus,

Carissa - Carissa opaca, Znthxylm- Zanthoxylum armatum)

0100200300400500600700800900

1000

IVI

0

200

400

600

800

1000

1200

IVI

77

Fig. 3.15 IVI of top 10 herbs species of community II (Note: Cynodon- Cynodon dactylon,

Chryspgn-Chrysopogon, Dgitaria- Digitaria nodosa, Agrostis- Agrostis stolonifera, Rumex has- Rumex

hastatus, Cannabis- Cannabis sativa, Phalaris- Phalaris minor, Aerva jav- Aerva javanica, Oxalis, Oxalis

carniculatus, Conyza- Conyza canadensis

Fig. 3.16 Rare tree species of community II (Note: Cedrella- Cedrella serrata, Butea-Butea

monosperma, Zzphs j- Ziziphus jujube, Pistacia- Pistacia integerrima, Bauhinia- Bauhinia variegate, Salix

tt- Salix tetrasperma, Populus a- Populus alba, Pyrus com- Pyrus communis, Pinus rox- Pinus roxburghii

Juglans- Juglans regia)

0

100

200

300

400

500

600

700

IVI

0

5

10

15

20

25

30

IVI

78

Fig.3.17: Total IVI of rare shrub species of community II (Note: Nanrhops- Nannorrhops

ritchieana, Yucca- Yucca aloifolia, Berbers l- Berberis lycium, Rosa ind- Rosa indica, Indgofra Vitis- Vitis

vinifera, Jsmnum hm- Jasminum humile, Andrchne- Andrachne cordifolia, Vburnm gr- Viburnum

grandiflorum, Cotinus- Cotinus coggyria)

Fig. 3.18 Total IVI of rare herbs species of the community II (Astrgls am- Astragalus

amherstianus, Ephrba hr- Euphorbia hirta, Evlvulus- Evolvulus alsinoides, Scandix p- Scandix pectin-

veneris, Lthosprmm- Lithospermum officinale, Melilotus- Melilotus officinalis, Anagalus- Anagalus

arvensis Clocasia- Colocasia esculenta, Malva neg- Malva neglecta, Potentla- Potentilla nepalensis)

0

10

20

30

40

50

60

70

0

0.5

1

1.5

2

2.5

3

3.5

4

IVI

79

3.2.1.1.3 Commuity III: Ailanthus altisima- Justicia adhatoda- Digitaria nodosa

Ailanthus altissima was the dominant species of tree layer. Other codominant tree

species of the community included, Acacia modesta, Delbergia sisso, Pinus roxburghii,

Ficus palmata, Olea ferruginea, Acacia nilotica, Broussonetia papyrifera and Phoenix

dactylifera. Characteristic shrubs species of this communities included Dodonaea

vescosa, Justicia adhatoda, Yucca aloifolia, Carissa opaca, Otostegia limbata and Calotropis

procera. Herb species of the community were represented by Cynodon dactylon,

Digitaria nodosa, Cannabis sativa, Phalaris minor, Aristida depressa, Imperata cylindrica,

Periploca aphylla and Arundo donax. Rare tree species of the community were

Diospyrus lotus, Quercus spp., Pyrus pashia and Morus spp. Among rare shrubs

species Maytenus royleanus, Colebrookia oppositifolia, Rubus fructicosus, Viburnum spp.,

Mallotus philippensis and Cotoneaster bacillaris, were included.The rare herbaceous

flora of this plant community include Argyrolobium roseum and Sisymbrium irrio.

The life form classification indicated that dominant life form was Hemicryptophytes

(28.9%) followed by therophytes (21.48%). The Nanophytes and microphanerophytes

were 20.66 and 16.5% respectively followed by megaphanerophytes (1.66%),

Mesophytes (2.47%), chamaephytes (,6.6%) where as the Geophytes were1.65%.

(Figure 3.19).

80

Fig.3.19: Habitats representing Community III (A: Akazai area B:Toot banda)

A

B

81

Fig: 3.20: Top 10 tree species of the community III (Note: Acaci mod- Acacia modesta,

Alnthus alt- Ailanthus altissima, Delbergia- Delbergia sisso, Pinus rox- Pinus roxburghii, Ficus pa-

Ficus palmata, Olea f- Olea ferruginea, Acaci nil- Acacia nilotica, Brousnetia- Broussonetia papyrifera

Phonx da- Phoenix dactylifera, Albeza pr- Albezzia procera).

Fig 3.21: Top 10 shrubs species of community III (Note: Ddonaea- Dodonaea vescosa, Justicia-

Justicia adhatoda, Yucca- Yucca aloifolia, Carissa- Carissa opaca, Otostgia- Otostegia limbata Caltrops-

Calotropis procera, Myrsine- Myrsine africana, Hyprcm ob- Hypericum oblongifolium Solnm ps- Solanum

pseudocapsicum, Nanrhops- Nannorrhops ritchieana)

0

50

100

150

200

250

300

IVI

0

50

100

150

200

250

300

IVI

Axis Title

82

Fig: 3.22: Important herb species of community III (Note: Cynodon- Cynodon dactylon,

Dgitaria- Digitaria nodosa, Cannabis-, Cannabis sativa, Phalaris- Phalaris minor, Aristida- Aristida

depressa, Imperata- Imperata cylindrical, Priploca- Periploca aphylla, Arundo d- Arundo donax

Lamium- Lamium amplexicaule, Poa blb- Poa bulbosa, Lthosprmm- Lithospermum officinale, Mntha ln-

Mentha longifolia, Plntgo mj- Plantago major, Acrnths b- Achyranthes bidentata Chnpodm al-

Chenopodium album)

Fig:3.23: Rare herbs of community III (Note: Sonchus-Sonchus asper, Swerti-Swertia ciliate, Slvia

mor- Salvia moorcroftiana, Duchsnea- Duchesnea indica, Crsum ar-Cirsium arvense, Ajuga br- Ajuga

bracteosa, Eryngium-Eryngium Sp., Cnvolvls-Convolvulus arvensis, Marubium- Clchcm lu- Colchicum

luteum, Oxalis-Oxalis carniculatus, Allium gr-Allium griffithianum, Impatin b- Impatiens bicolor,

Slybum ma- Silybum marianum, Agrlobum- Argyrolobium roseum)

050

100150200250300350

Cyn

odon

Dg

itar

ia

Can

nab

is

Ph

alar

is

Ari

stid

a

Impe

rata

Pri

ploc

a

Aru

nd

o d

Lam

ium

Poa

blb

Lth

osp

rmm

.

Mn

tha

ln

Pln

tgo

mj

Acr

nth

s b

Chn

pod

m a

l

IVI

01234567

Son

chu

s

Sw

erti

Slv

ia m

or

Du

chsn

ea

Crs

um

ar

Aju

ga b

r

Ery

ng

ium

Cn

vol

vls

Mar

ubi

um

Clc

hcm

lu

Ox

alis

All

ium

gr

Impa

tin

b

Sly

bum

ma

Ag

rlob

um

IVI

83

Fig.3.24: Rare shrub species of community III (Note: Rosa mos- Rosa moschata, Debrgsia-

Debregeasia salicifolia, Znthxylm- Zanthoxylum armatum, Cotnstr b- Cotoneaster bacillaris, Nerim ol-

Nerium oleander, Malotus- Mallotus philippensis, Vburnm gr- Viburnum grandiflorum, Rubus el- Rubus

ellipticus, Colbrkia- Colebrookia oppositifolia, Maytenus- Maytenus royleanus)

Fig. 3.25: Total IVI of rare tree species of community III (Note: Pistacia- Pistacia integerrima,

Grewia op- Grewia optiva, Phonx sy- Phoenix sylvestris, Qurcus dl- Quercus dilatata, Morus al- Morus

alba, Moras ni- Moras nigra, Qurcus fr- Quercus baloot, Pyrus pas- Pyrus pashia, Qurcs in- Quercus

incana, Diospyrus- Diospyrus lotus)

0

5

10

15

20

25

IVI

0

10

20

30

40

50

60

IVI

84

3.2.1.1.4 Community IV: Pinus roxburghii-Rubus ellipticus-Agrostis stolonifera

The Pinus roxburghii is the dominant texa of tree layer. Other companion species of

tree layer are Acacia modesta, Ailanthus altissima, Pinus wallichiana, Delbergia sisso and

Olea sp. The shrub layer consisted of Rubus ellipticus as a dominant species, Indigofera

heterantha, Dodonaea viscosa, Berberis lycium, Cotinus coggyria, Justicia adhatoda and

Otostegia limbata are the other important species of shrub layer. Important herbs of

the community were Cynodon dactylon, Agrostis stolonifera, Apluda aristata, Oxalis

carniculatus, Alliaria petiolata, Duchesnea indica, Taraxacum officinaleand

Partheniumhysterophorus. Among rare tree species of the community included

Quercus incana, Grewia optiva, Butea monospermum, and Bombax ceiba (Fig. 3.26-3.29).

The rare tree species of the community were Quercus incana, Bombax ceiba, Butea

monosperma, Cydonia oblonga, Grewia optiva, Moras nigra, Plantanus orientalis, Albezzia

procera, Aesculus indica, Sapindus mukorossi and Platanus orientaliswhile rare shrub

flora of the community consists of Caesalpinia decapitate, Rosa moschata, Calotropis

procera, Nerium indicum, Hedra nepalensis,Sarcococca saligna, Withania somnifera,

Jasminum humile, Cotoneaster nummularia andViscum album.

Among rare shrubs Equisetum, Plystichum lonchitis, Colchicum luteum, Arisaema

jacquemontii, Cordiospermum helicacabum, Impatiens bicolor, Priploca Aquilegia,

Astragalus macropterus are included.

The life form classification reflected that hemicryptophytes were dominant in the

community with 74 plant species and 32.03% of the total plant species followed by

therophytes with 19.9%. The contribution by Nanophytes was 15.5%, followed by

85

microphytes (15.15%), Chamaeophytes (6.06%), Geophytes (5.6%), Mesophytes

(3.03%) and megaphytes (2.59%).

Fig.3.26 Chir pine forest habitat (A: Bandan, B: Nawagae)

B

A

86

Fig. 3.27: Total IVI of top 10 tree species of community IV (Note: Pinus rox- Pinus

roxburghii, Acaci mod- Acacia modesta, Alnthus alt- Ailanthus altissima, Pinus wa- Pinus wallichiana,

Delbergia- Delbergia sisso, Juglans- Juglans regia, Olea f- Olea ferruginea, Punica g- Punica granatum,

Pyrus pas- Pyrus pashia, Qurcus dl- Quercus dilatata)

Fig. 3.28: IVI of Top 10 Herbs from community IV (Note: Cynodon- Cynodon dactylon,

Agrostis- Agrostis stolonifera, Apluta ar-Apluda aristata, Oxalis- Oxalis carniculatus, Aliaria pet -Alliaria

petiolata, Duchsnea-Duchesnea indica, Traxicum- Taraxacum officinale, and Prthenum-Parthenium

hysterophorus, Cardamin- Cardamine hirsute, Astrgls gr- Astragalus graveolens)

0100200300400500600700800900

1000

IVI

0

50

100

150

200

250

IVI

87

Fig. 3.29: IVI of Top 10 shrubs from community IV (Note: Rubus el- Rubus ellipticus, Indgofra-

Indigofera heterantha, Ddonaea- Dodonaea viscosa, Berbers l-Berberis lycium, Cotinus-Cotinus coggyria,

Otostgia-Otostegia limbata, Isodon- Isodon rugosus, Malotus- Mallotus philippensis, Carissa- Carissa

opaca, Justicia- Justicia adhatoda)

3.2.1.1.5 Community V: Pinus roxburghii- Berberis lycium–Chrysopogon

The community is located at North and South of Sahbah hill, Arnil, Shatal area,

Shangal Dar area and Haleema. Dominant tree species of this plant community was

Pinus roxburghii with total IVI 1015.2. Other Important tree species are Acacia modesta,

Pyrus pashia, Olea ferrugenia, Delbergia sisso, Ailanthus altissima and Juglans regia.

Prominent shrubs species in this community are represented by Indigofera heterantha,

Berberis lycium, Debregeasia salicifolia, Rubus ellipticus, Rosa moschata, Carissa opaca,

Dodonaea vescosa, Isodon rugosus, Zanthoxylum armatum and Cotinus coggyria.

0

50

100

150

200

250

300

350

400

IVI

88

Fig.3.30: Habitat representing Community V ( A: Gut Hill, B:Haleema Top)

Among important herbs Cynodon dactylon, Chrysopogonsp, Poa alpina, Digitaria nodosa,

Xanthium strumarium, Agrostis stolonifera and Taraxicum officinale are found (Fig. 3.31-

3.33).

B

B

89

Rare tree species of the community consist of Taxus wallichiana, Qercus

leucotrichophora, Sapindus mukorossi, Bombax ceiba, Plantanus orientalis, Bauhinia

variegate, Albezzia procera and Picea smithiana. Among rare shrubs are Vitex negundo,

Caesalpinia decapitate, Rosa moschata, Calotropis procera Cotoneaster frigidus, Buxus

Wallichiana, Viscum album andWithania somnifera. Rare herbaceous flora of this

community consists ofViola canescens, Urtica diocia, Arisaema jacquemontii, Asparagus

officinalis and Carthmus oxycantha.

The study of life form clsssification of this plant community revealed that

Hemicryptophytes with 62 plant species (32.8%) were dominant followed by

therophytes 20.0%) Nanophytes were represented by 33 plant species (17.4%).The

microphanerophytes were 6.5% followed by equal share of megaphanerophytes and

Mesophytes (3.7%) where as chamaephytes were 8.9% and Geophytes were 6.3%.

Fig. 3.31: Total IVI of Important tree species of community V (Note: Pinus rox- Pinus roxburghii,

Pinus wa- -- Pinus wallichiana, Acaci mod- Acacia modesta, Pyrus pas- Pyrus pashia, Qurcs in- Quercus

incana, Olea f- Olea ferrugenia, Alnthus alt- Ailanthus altissima, Delbergia- Delbergia sisso, Juglans-

Juglans regia Pistacia- Pistacia integerrima )

0

200

400

600

800

1000

1200

IVI

90

Fig. 3.32 Total IVI of top 10 shrub species of community V (Note: Berbers l- Berberis lycium,

Indgofra- Indigofera heterantha, Debrgsia - Debregeasia salicifolia, Rubus el- Rubus ellipticus, Rosa mos- Rosa

moschata, Carissa- Carissa opaca, Ddonaea- Dodonaea vescosa, Isodon- Isodon rugosus, Znthxylm-

Zanthoxylum armatum, Cotinus- Cotinus coggyria)

Fig. 3.33 Important herbs of community V (Note: Cynodon- Cynodon dactylon,

Chryspgn-Chrysopogonsp, Poa alp- Poa alpina, Dgitaria- Digitaria nodosa, Duchsnea- Duchesnea indica,

Xanthium- Xanthium strumarium, Cyperus- Cyperus cyperoides, Agrostis- Agrostis stolonifera, Rumx ac-

Rumex acetosa, Traxicum- Taraxicum officinale )

0

100

200

300

400

500

IVI

050

100150200250300350400450

IVI

91

3.2.1.1.6 Community VI: Pinus wallichiana -Viburnum grandiflorum- Poa alpine

The total documented species among this community were 36 trees, 26 shrubs and

86 herbs species. The dominant tree pecies of this community was Pinus wallichiana

with total IVI= 714. Other important trees of the community included Abies, Pinus

roxburghii, Quercus incana, Pyrus pashia, Quercus dilatata, Taxus wallichiana, Diospyrus

lotus, Cedrus deodara and Juglans regia.

Viburnum grandiflorum is represented as a dominat species while, Berberis lycium,

Indigofera heterantha, Sarcococca saligna, Hedra nepalensis, Viburnum cotinifolium, Rubus

ellipticus, Skimmia laureola, Isodon rugosus, and Cotoneaster bacillaris are the companion

species of shrub layer.

Among rare trees of this community are included Celtis australus, Sapindus mukorossi,

Broussnetia papyrifera, Ficus carica, Melia azedarach, Prunus armeniaca, Morus alba,

Delbergia sisso, Grewia optiva and Olea ferruginea. The rare shrubs are Cotinus coggyria,

Cotoneaster nummularia, Viscum album, Andrachne cordifolia, Cotoneaster frigidus,

Daphne mucronata, Zanthoxylum armatum, Debregeasia salicifolia, Buddleja crispa and

Vitex negundo. Among rare herbs, Chenopodium album, Crdiospermum helicacabum,

Cichorium intybus, Lactuca serriola, Malva sylvestris, Urtica pilulifera, Clematis montana,

Neslia apiculata, Plantago lanceolata are documented.

92

Fig.3.34(a) Habitats representing Community VI

B

A

93

Fig. 3.34 (b): Deforestation at different localities of community VI (A: Machasar, B:

Manasar, C: Shalangal dar, D: Kando Gali)

The life form classification described that hemicryptophytes were (32%) followed by

microphyte with 12.4% share and therophytes (16.7%). Nanophytes included 20

plant species (13.5%) of the total plant species in the community. The

megaphanerophytes and mesophytes were 5.3 and 3.35% where as chamaephytes

and geophytes were were 6.7%and 7.3% respectively.

C

B A

D

94

Fig: 3.35 Total IVI of top 10 tree species of community VI ( Note: Pinus wa- Pinus wallichiana,

Abie pind- Abies pindrow, Pinus rox- Pinus roxburghii, Qurcs in- Quercus incana, Pyrus pas- Pyrus

pashia, Qurcus dl- Quercus dilatata, Taxus w- Taxus wallichiana, Diospyrus- Diospyrus lotus, Cedrus

d- Cedrus deodara, Juglans- Juglans regia)

Fig. 3.36 Total IVI of Important shrubs of the community VI (Note: Vburnm gr- Viburnum

grandiflorum, Berbers l- Berberis lycium, Indgofra- Indigofera heterantha, Srcoca s- Sarcococca saligna,

Hedra nep- Hedra nepalensis, Vburnm ct- Viburnum cotinifolium, Rubus el- Rubus ellipticus, Skimia-

Skimmia laureola, Isodon- Isodon rugosus, Cotnstr b- Cotoneaster bacillaris).

0

100

200

300

400

500

600

700

800

IVI

0

50

100

150

200

250

300

350

IVI

95

Fig. 3.37 Total IVI of important herb species of the community VI (Note: Poa alp- Poa alpine,

Cyperus- Cyperus cyperoides, Dgitaria- Digitaria nodosa, Vleriana- Valeriana jatamansi, Poa blb- Poa

bulbosa, Fragaria- Fragaria nubicola, Pteris cr- Pteris cretica, Slvia lan- Salvia lanata, Ephrba Wl-

Euphorbia Wallichii, Urtica di- Urtica dioica, Oxalis- Oxalis carniculatus Duchsnea- Duchesnea indica,

Viola can- Viola canescens, Impatin b- Impatiens bicolor, Cynodon Cynodon dactylon)

Fig. 3.38 Total IVI of Rare tree species of the community VI (Note: Celtis a- Celtis australus,

Spnds muk- Sapindus mukorossi, Brousnetia- Broussnetia papyrifera, Ficus car- Ficus carica, Melia az-

Melia azedarach, Prunus ar- Prunus armeniaca, Morus al- Morus alba, Delbergia- Delbergia sisso, Grewia

op- Grewia optiva, Olea f- Olea ferruginea)

0

2

4

6

8

10

12

IVI

020406080

100120140160180

Po

a al

p

Cyp

eru

s

Dgi

tari

a

Vle

rian

a

Po

a b

lb

Frag

aria

Pte

ris

cr

Slvi

a la

n

Eph

rba

Wl

Urt

ica

di

Oxa

lis

Du

chsn

ea

Vio

la c

an

Imp

atin

b

Cyn

od

on

IVI

96

Fig. 3.39 Total IVI of Rare shrub species of the community VI (Note: Cotinus-Cotinus coggyria,

Cotnstr n- Cotoneaster nummularia, Viscum- Viscum album, Andrchne- Andrachne cordifolia, Ctnstr fr-

Cotoneaster frigidus, Daphne m- Daphne mucronata, Znthxylm- Zanthoxylum armatum, Debrgsia-

Debregeasia salicifolia Buddleja- Buddleja crispa, Vitex n- Vitex negundo)

Fig. 3.40 Total IVI of Rare herb species of the community VI (Note: Chnpodm al- Chenopodium album, Crdosprm-

Cordiospermum helicacabum, Cichorum- Cichorium intybus, Lactuca- Lactuca serriola, Malva syl- Malva sylvestris, Acrnths b- Achyranthes bidentata, Urtica pi-

Urtica pilulifera, Clmats mn- Clematis montana, Neslia a- Neslia apiculata, Plntgo ln- Plantago lanceolata)

0

5

10

15

20

25

30

IVI

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5

IVI

97

3.2.2 Two Way Cluster Analysis (TWCA) Classification

TWCA and cluster analysis divided the samples into two main groups, which were

further divided into six plant associations.TWCA also describes species distribution

at different localities. The subtropical species were dominant in the investigated area

as shown in the two way cluster dendrogram. TWCA dendrogram show that plant

species like Abies pindrow, Taxus wallichiana, Skimmia laureola, Phoenix spp. and Cedrus

deodara were present in one plant association and were documented from few

stations i.e Abies pindrow and Cedrus deodara were recorded from 5 localitiesTaxus

wallichiana from 6 stations, Skimmia laureola was reported from 4 stations, while

species likePicea smithiana and Rumex vesicarius were reported from two localities

only, Dioscorea deltoidea from 4 stations, Viscum album, Cardiospermum halicacabum,

Aquilegia Sp.and Arisaema flavum were documented from 5 localities and Ficus

elasticawas found at 3 localities, representing rare plant species of the study area.

Similarly Aerva javanica, Phoenix spp. Artemisiaspp., Aconitum, sp Nannorrhops

ritchieanawere reported from two plant associations showing a narrow range of

distribution limit. Whereas the species, Acacia modesta, Delbergia sisso, Mallotus

philippensis, Dodonaea viscosa, Justacia, Otostegia limbata, chrysopogon, Cynodon,

digitariaand Rubus sp. having wide range were present in five out of six plant

communities recorded from study area (figure 3.41).

98

Fig. 3.41 TWCA dendrogram of 331 plant species and 64 stations based on Sorensor measures showing 6 plant communities.

99

3.3 Floristic Diversity along Environmental Gradients

In order to analyse effects of environmental varibales on the floristic diversity and

correlation among species, communities and localities, following two approaches

were adopted.

3.3.1 Indirect gradient analysis

DCA diagram (Figure 3.42) show the distribution of tree species and habitat type in

64 stations. The localities Jdbh I, Shagi I, Shdk 1, Zzari 1 and Ktky I are present at the

upper right side of the DCA diagram and are showing no correlation with most of

the stations. These stations show strong negative correlation with Dni2, Ddme 1,

Ttbda 3, Dni 10, Dni 9 and Ttbda. The stations Jdbh 12, Jdbh 11, Dni 13, Dni 12, Jdbh

10 and Jdbh 9 are located at the right side showing strong correlation with Axis Ist

and 2nd and negative correlation with certain stations like Tk2, Tkec1 and Dmn1. The

DCA diagram also reflected that the stations Ddme 1, Tk2 and Tk1 are locted at

negative side of the diagram showing negative correlation with other localities.

Table 3.2 Detail of the four axes of the DCA for 54 tree species and 64 stations data

Axes 1 2 3 4 Total

Inertia

Eigenvalues 0.630 0.212 0.103 0.083 3.543

Lengths of gradient 6.325 5.043 3.902 3.570

Cumulative percentage

variance of species data

17.8 23.8 26.7 29.0

100

Fig.3.42 DCA diagram displaying distribution of tree species and habitat types among 64 stations. (Codes in diagram indicates stations names refer to appendix 4)

101

Fig. 3.43 DCA diagram presenting the distribution of tree species in the district Tor ghar along the gradient (Codes in diagram indicates names of species refer to appendix 5)

102

The DCA diagram (Figure 3.43) revealed that most of tree species like Acacia

modesta, Delbergia sisso, Pinus roxburghii, Olea ferruginea and Acacia nilotica are

present in the centre of the diagram presenting strong correlation. Whereas tree

species Abies pindrow, Cedrus deodara, Picea, Aesculus and Taxus sp.are present at right

side of DCA diagram (Fig. 3.43) showing strong correlation with Ist axis and are

negatively correlated with species like Euclaptus, Delbergia sisso, Ficus elstica.

Similarly the species, Ficus benghalensis, Poplus, Butea monosperma and Bombax ceiba

are present at the upper right side of the DCA diagram show no correlation with

most of the tree species and are negatively correlated with the species Albezzia

proceraand Phoenix spp.

DCA diagram (Figure 3.44) produced through CANOCO revealed that majority of

shrub species stations were strongly correlated with 1st and 2nd axis (Eigen

value=0.64 and 0.189 respectively), while less correlation with 3rd and 4th axis (Eign

value=0.132, 0.099) (table 3.3).

The localities distributed at margins of the diagram represent habitat specificity

while the stations located in centre were showing similarity among each other. Jdbh

12, Dni13, Jdbh 11, jdbh 9 and Jdbh 10 are positively correlated with axis while

showing negative correlation with Kotly1, Kotly 2 and Tk 1. Locality shagai had

negative correlation most of the localities. The localities, Zizari3, Zizari 4, Shagai 6,

Gorl 3 and Shdk 4 are located at the center of diagram showing strong correlation.

103

Fig.3.44 DCA diagram presenting the distribution of shrub species and habitat types among 64 stations. (Codes in diagram indicates station’s names refer to appendix 4)

104

Fig. 3.45 DCA diagram presenting distribution of shrub species in district Tor ghar along the gradient (Codes in diagram indicates names of species refer to appendix 5)

105

Table 3.3 Detail of four axes of DCA for 48 shrub species and 64 stations data

Table 3.4 Description of four axes of the DCA for 420 herb species (using IVI data) for all 64 stations.

Detrended Correspondence Analysis (DCA) diagram Fig 3.45 revealed that the 1st

and 2nd DCA axis show strong correlation with shrub species. In the middle of the

DCA diagram, there are many shrubs which shared many vegetation types such as

Carissa opaca, Cotinus coggyria, Otostegia limbata and Zanthoxylum. Some shrubs show

no correlation with other plants like Bambusa, Yucca aloifolia and Nannorrhops

ritchieana. The species distribution along the first axis of DCA reflected altitudinal

gradient. While the shrub species like Skimmia laureola,Sarcococca saligna, Hedra

nepalensis are present on the right side of the diagram showing strong correlation

with axis and are negatively correlated with species like Yucca aloifolia, Calotropis

Axes 1 2 3 4 Total Inertia

Eigenvalues .508 .360 .270 .208 7.232

Lengths of gradient 6.723 5.074 6.242 5.231

Cumulative percentage

Variance of species data

7.0 12.0 15.7 18.6

Axes 1 2 3 4 Total

inertia

Eigenvalues 0.641 0.189 0.132 .099 3.299

Lengths of gradient 5.627 5.248 2.431 2.114

Cumulative percentage

variance of species data

19.4 25.1 29.1 32.1

106

procera,. The shrub species Vitis and Nannorrhops ritchieana showed negative

correlation with most of the species and axis.

Results of Detrended Correspondence Analysis (DCA) for all 240 herbaceous flora

and habitat types among 64 stations are represented in the Fig 3.46. Results revealed

that most of the sites are located in the center of DCA diagram.

The table 3.4 show that the Eigen value from Ist two axis were 0.58 and 0.360 while

the Eigen values from 3rd and 4rth axis were 0.270 and 0.208. Some localities like TK

EC1, Ttbda 3, Ttbda and Tk2 are located at the upper half showing negative

correlation with Dmn 1 Ddme 2, Dmn 2 and Ddme 3.

The habitats Ktky1, Ktky 2, Ktky3, Ktky 4 and Ktky 5 were located at lower left half

of the DCA diagram which show negative correlation with habitats; Dni 13, Dni 12,

Jdbh 12, jdbh 9, Jdbh 10 and Dni 11.

DCA diagram (Fig. 3.47) for herb species reflected that most of the herb species are

strongly correlated and are group together in the centre. While the species located at

the margin of the DCA diagram are showing less correlation. Herbaceous flora

located at the extreme right side of the diagram, Boenninghausenia albiflora, Impatiens

bicolor, Valeriana and Arisaema utileshowing strong correlation with axis 1 and 2.

These species are showing negative correlation with species located at the left side

i.eOpuntia, Canna, Solanum virginianum.

107

Fig. 3.46 Detrended Correspondence Analysis (DCA) diagram showing distribution of herbaceous flora and habitat types among 64 stations. (Codes in diagram indicates stations names refer to appendix 4)

108

Fig. 3.47 DCA diagram presenting the distribution of total herbs species among six plant communities along the gradient (Codes in diagram indicates names of species refer to appendix 5)

109

3.3.2 Direct Gradient Ordination

In direct gradient ordination the effect of different environmental variables e.g. soil

depth, slope, grazing pressure and elevation gradient were analysed using CCA.

CCA diagram (Fig 3.48- 3.49) reflected that among six environmental variables,

elevations was the most influential factor in tree species distribution followed by

slope and soil depth. Among climatic gradients, slope and soil depth were stongly

correlated with each while grazing pressure and soil erosion were positively

correlated. Elevation had least correlated with remaing factors.

Among stations Dni 12, Dni 13, Jdbh 11, Dni 11, Dni 12 and Dni 10 were showing

positive correlation and were more effected by altitude while Jdbh 1, Shadk 1, Ktky

1, Shagi 1were showing negative correlation. Dni 6 was positively correlated with

slope, Dri4, Ktky5 and Dni 4 were showing correlation with soil depth. Grazing

pressure was more evident at Jdbh4 and Dni2. Dri, Tk1, Dmn 1, Dmn2, Tk2 were

negatively correlated with soil depth and slope.

Table.3.5 (a) Detail of four axes of the CCA using IVI data for 55 tree species, 64 stations and 6 environmental variables.

Axes

1 2 3 4 Total inertia

Eigenvalues .481 .165 .097 .049 3.543

Species-environment correlations

0.894 0.703 0.688 0.618

Cumulative percentage variance of species data

13.6 18.3 21.0 22.4

species-environment relation:

56.6 76.1 87.5 93.2

110

Table. 3.5(b) Summary of Monte Carlo test (499 permutations under reduced

model)

The Pinus wallichiana, Abies, Quercus incana, Pyrus pashia, Taxus wallichiana and Cedrus

deodara showed strong positive correlation with altitude. On the other hand plant

species like Bombax, Butea and Acacia modestawere negatively correlated with tree

species and were found at lower altitude. Soil erosion and grazing pressure show

less effect in the plant distribution. Quercus sp., Juglans regia, and Cornus macrophyla

show positive coorelation with slope and Acacia modesta, Phoenix, Eucalyptus sp and

Delbergia sisso showed less correlation to slope.

Test of significance

of first canonical

axis:

Test of

significance of all

canonical axes

eigenvalue

0.481 Trace

0.850

F-ratio 8.963

F-ratio 3.000

P-value 0.0020 P-value 0.0020

111

Fig:3.48 CCA diagram showing distribution of tree species among 64 stations in relation to various measured environmental variables (Codes in diagram indicates stations names refer to appendix 4)

112

Fig: 3.49 CCA diagram showing distribution of tree species in District Tor Ghar and the measured environmental gradients. (Codes in diagram indicates names of species refer to appendix 5)

113

Table. 3.6 (a) Description of four axes of the CCA using IVI data for 48 shrub species, 64 stations and 6 environmental variables.

Axes 1 2 3 4 Total

Inertia

Eigenvalues 0.422 0.120 .051 .043 3.299

Species-environment

correlations

0.848 0.660 0.617 0.559

Cumulative percentage variance of species data

12.8 16.4 18.0 19.3

species-environment

relation:

61.2 78.7 86.1 92.2

Table.3.6 (b) Summary of Monte Carlo test (499 permutations under reduced model)

Test of significance of

first canonical axis:

Test of significance

of all canonical axes

eigenvalue 0.422 Trace

0.689

F-ratio 8.365 F-ratio 2.509

P-value 0.0020 P-value 0.0020

The biplot diagram for shrubs species such as Sarcococca saligna, Hedera nepalensis,

Viburnum cotonifoliu, Rubus ellipticus, Skimmia laureola, and Cotoneaster bacillaris

showed positive correlation with slope and altitude while Dodonaea viscosa, Mallotus

philippensis, Otostegia limbata, Justicia adhatoda, Colebrookia oppositifolia, Calotropis

procera, and Myrsine africana were showing negative correlations. Other important

environmental factors affecting distribution of shrub species are slope and grazing

pressure. The plant species like Andrachne cordifolia, Xanthium sp. and Melilotus

officinalis were positively correlated with soil depth. Grazing pressure and soil

erosion was positively correlated with Yucca, Nannorops and Vitex while negatively

correlated with Caesalpinia, Zanthoxylum and Zizyphus.

114

Fig.3.50 CCA diagram showing distribution of shrub species among 64 stations in relation to different environmental variables (Codes in diagram indicates stations names refer to appendix 4)

115

Fig.3.51 Canonical Correspondence Analysis (CCA) diagram showing distribution of shrub species in relation to various measured environmental variables. (Codes in diagram indicates names of species refer to appendix 5)

116

The CCA diagram for herb localities (Fig 3.52) indicated that Dn12, Dn13 and Jdbh11

were positively coorelated with altitude whereas the stations Ktly1, Dri1, Shdk1,

Zzari and Ktky1 showed negative correlation with elevation. Jdbh7 was more

effected with slope. Zzari4, Dri4 and Zzari5 were positively correlated with soil

depth. Tk1, Tdbda1, Dmn1 and Ttbda2 were negatively correlated with soil depth.

CCA diagram for herb species (fig 3.53) showed that elevation was negatively

correlated with Ricinis communis, Opuntia and Sisymbrium while strongly correlated

with Poa alpina, Valeriana jatamansi, Viola odorata, Euphorbia wallichii, Impatiens bicolor,

Duchesnea indica, Boenninghausenia albiflora and Aquilegia sp.Swertia, Salvia, Bergenia

and Gernium were positively correlated with slope. Euphorbia, Astagalus and

Achyranthus showed positive correlation with grazing and soil erosion.

117

Fig.3.52 CCA diagram showing distribution of herb species among 64 stations in relation to different environmental variables. (Codes in diagram indicates stations names refer to appendix 4)

118

Fig. 3.53 CCA diagram showing distribution of herbs species in District Tor Ghar and different environmental gradients. (Codes in diagram indicates names of species refer to appendix 5)

119

3.4 Species Area Curve.

In present study species area curve was used to calculate the proper sampling size

for the collection of phytosociological data. PCORD was used to calculate species

area curve for tree, shrubs and herbs. The Fig 3.51 shows the species area curve for

tree species. It indicates that the number of species increases with an increase in the

number of sampling plotsand species curves reach to the region of constancy,

whereas the distance curves become zero. The diagram show that after 24 sub plot

the sample size become suitable and give constant species composition.

Fig. 3.54 Species area curves based on IVI data tree species and 64 stations

The relationship between area and number of shrub species is shown in the figure

3.55 and for herb species is presented in Fig. 3.56. These figures indicate that the

number of species increases with an increase in the number of sampling plots and

species curves reach to the region of constancy, whereas the distance curves become

zero. The diagram shows that after 20 sub plot the sample size for shrubs become

120

suitable and give constant species composition. The relationship of sample area and

number of species is shown in the figure 3.56.

Fig 3.55 Species area curves based on IVI data for all shrub species and 64 stations

Fig. 3.56 Species area curves based on IVI data for herb species

121

Chapter 4

DISCUSSION

Plants are the most expensive gift of Nature to mankind. It is the most important

treasure, much superior to other blessings because not only it is renewable but also

makes a very healthy contribution towards the development of environment. Plants

are imperative for the continuation of ecosystem services that is water, air and fertile

soil. Over 230,000 species of higher plants have been recorded in the world (Thorne,

1992). A large number of plant species are yet to be discovered.There has been much

research attempting to describe and explain this vast diversity and discover the

mechanisms which maintain it (Pitman et al., 1999).

Surveying of vegetation of an area is important because effective conservation

measures cannot be obtained without extensive knowledge of the flora of the region.

Plant checklist provides basic information about the vegetation of an area and serves

as a baseline for detailed study (Keith, 1988). Floristic listing helps in identification

and nomenclature of species (Ilyas et al., 2013).To develop conservation strategies

and estimate the changes taking place in the vegetation patterns of any area, it is

required to have a detailed floristic account of that area based on collections and

correct identification (Manikandan & Lakshminarasimhan, 2012).

Himalayas is one of the most complex and diverse mountain ecosystems on the

planet earth, possessing a unique climate, a strong degree of seasonality and diverse

plant communities and species due to wider elevation range, summer winter

precipitation, microclimatic variations, edaphic factors and landscape. It is one of the

mountain range where exist most of the natural forest resources of the subcontinent.

122

Pakistan is among one of few places on the earth with rich plant diversity, because of

varying geoclimatic zones in five significant mountain systems i.e. Western

Himalayas, Karakoram, Hindukush, Suleiman and Khirthar range (Perveen and

Hussain, 2007). Various floristic studies are reported from Pakistan and contributed

in term of ecological studies. The Flora of Pakistan is comprehensive inventory of

plants of Pakistan. About 47 Botanists have contributed to the Flora of Pakistan.

Litrature shows no available evidence of study from my project area although a

number of the studies were reported from adjacent area, for example Fazal et al.,

(2010) documented 211 species of 170 genera and 66 families from District Haripur.

Shah and Khan (2006) recorded 80 medicinal plants belong to 49 families from Sirin

Valley Mansehra. Haq et al., (2010) documented 402 vascular plants species

belonging to 110 families from Nandiar Valley western Himalaya, Pakistan. A

research project was conducted by Khan et al., (2013a) to study ecosystem services

provided by plants in the Naran Valley. They reported 101 plants belonging to 52

families used by the inhabitants for different medicinal purposes. Tor Ghar (Black

mountain) was explored for the first time in the history of plant sciences and

disclosed a diversity of flora.

4.1 Plant Diversity of District Tor Ghar

The study area, Tor Ghar (Black Mountain) can be located on the extreme western

edge of the Himalayas. Diversity in vegetation of the region is representative of Sub

tropical, Moist temperate and Sub alpine types of forests. Our findings showed that

the study area is blessed with diverse ecological habitats that host high floral

123

diversity. A total of 331 vascular plant species belonging to 246 genera and 101

families were recorded. Hosting 331 vascular plants species is evidence of a rich

diversity inspite of relatively harsh climate. The total area of district Tor Ghar is 454

Km2 which constitute .05% of the total area of Pakistan (796095 Km2) (Anon.,1999).

The present list of vascular plant species reported from district Tor Ghar has 331

plant species which constitute about 6% of the total 5783 species as reported by

Stewart, (1972). Most of these plants are important from ecosystem services point of

view such as medicinal plants, wild vegetables and timber plants. Besides providing

the first ever checklist of higher plant species of the region our study also fulfill

methodological gaps and use modern techniques for vegetation classification and

ordination. Preparation of inventories/checklists for unexplored regions can be seen

in previously published literature by various authors but most of them are on

smaller geographical units, like a valley and mountain etc. For example Perveen and

Hussain (2007) explored the flora of Gorakh hill (Khirthar range), Sindh, Pakistan

and reported 74 plant species belonging to 62 genera and 34 families. Shaheen et al .,

(2014) recorded the flora of Santh Saroola, Kotli Sattian, Pakistan and identified 186

plants species belonging to 148 genera and 63 families. Khan and Sardar, (2008)

described natural flora of Shakargarh District Narowal, Pakistan. It includes 83

families, 245 genera and 317 species. Similarly Fazal et al., (2010) documented a total

of 211 vascular plant species belonging to 170 genera and 66 families from District

Haripur. It includes 5 species of Gymnosperms of 5 genera and 4 families. Rafay et

al., (2013) studied life form, life trend and abundance of grass species in Cholistan

desert and described twenty seven grass species belonged to 16 genera from

124

Cholistan desert. Ilyas et al., (2013) surveyed the Kabal Valley Swat and reported 593

species of 408 genera and 130 families. Waris et al., (2013) documented the flora of

Cholistan desert and recorded 154 plant species, 106 genera and 38 families from 38

families, 106 genera and 154 species from the region. Qureshi et al., (2014) recorded

the flora of Khanpur Dam, Khyber Pakhtunkhwa, Pakistan. They documented 221

plant species of 169 genera and 66 families consisting of two ferns, one gymnosperm,

39 monocots and 179 dicots. Herbs were dominant in the floristic composition

followed by shrubs, grasses and trees. Khan et al., (2015) reported 252 species of

vascular plants belonging to 97 families from Thandiani sub forests division,

Abbottabad, Pakistan. I have tried to document higher vascular plants of a whole

district in my Ph.D project and hence cover comparatively a broader geopraphic unit

that is also a whole administrative unit.

In our project area the dicotyledons were dominating the flora and were represented

by 267 species (80.66%), while monocotyledons were composed of 46 species

(13.89%) and there were 6 species of gymnosperms (1.8%). Similar results were

presented in the previous study in the adjacent regions like, Qureshi et al., (2014)

reported one (0.5%) gymnosperm, 39 (17.64%) monocots and 179 (80%) dicots in the

flora of Khanpur Dam, Khyber Pakhtunkhwa, Pakistan. Ilyas et al., (2013) recorded 8

(1.3%) gymnosperms, 128 (21.58%) monocotyledons species and dicotyledons were

composed of 437 (73.69%) species from Kabal valley Swat. Khan et al., (2014) repoted

4 species of Gymnosperms, 56 species of Monocots and 357 plant species of Dicots

from Himalayan region of Poonch Valley, Azad Kashmir, Pakistan.

125

Our findings also show that the most prominent families in the District Tor Ghar

were Asteraceae, Leguminosae, Poaceae, Lamiaceae, Rosaceae, Ranunculaceae,

Brasicaceae, Euphorbiaceae, Moraceae and Apiaceae. These families all together

cover 43.82% of total number of species of the study area. Flora of the region showed

close affinities with the flora of adjacent areas in term of families. i.e., in the western

Himalayan region, the dominant angiospermic families are Asteraceae, Rosaceae,

Poaceae, Ranunculaceae and Brassicaceae (Rau, 1975). Many other studies have also

indicated the dominance of Asteraceae and Poaceae and can be seen in the literature

published. Fazal et al., (2010) reported that Family Asteraceae with 18 species was

the largest family in District Haripur and the Poaeae was the second largest family

with 16 species. Haq et al., (2010) also reported the dominance of family Asteraceae

with 36 species from the Nandyar Valley Western Himalaya, Pakistan. The family

Asteraceae was most species rich family from Kinnaur, Himachal Pradesh, India,

with 122 species, followed by Poaceae with 69 (Chawla et al., 2012). Qureshi et al .,

(2014) described that family Poaceae with 33 (14. 86%) species a dominant family

while documenting flora of the Khanpur Dam, Khyber Pakhtunkhwa, Pakistan.

Badshah et al., (2013) reported that Poaceae, Paplionaceae and Asteraceae are the

larger plant families of the District Tank, Pakistan. Ilyas et al., (2013) also indicated

that Poaceae was the largest family represented by 65 species, followed by

Asteraceae (44 spp), Rosaceae (33 spp), Papilionaceae (32 spp.,) and Lamiaceae (30

spp) from Kabal Valley Swat. Shaheen et al ., (2014) described the family Poaceae as

a largest family with (24 spp., 12.90%), followed by Asteraceae with 20 species

(10.75%) and Fabaceae having 16 spp., (8.60%) in the flora of Santh Saroola, Kotli

126

Sattian, Pakistan. Khan & Khatoon, (2008) also reported that the most important

plant family was Asteraceae with 14 plant species in Haramosh and Bugrote Valleys

in Gilgit, Northern areas of Pakistan. Similar results were obtained by many other

botanists like Marwat and Qureshi (2000), Saima et al., (2010), Khan et al., (2014) and

Durrani et al., (2005) in their respective study areas.

As a whole the family Asteraceae, the most prominent family in our study area, is

the largest plant family in Pakistan, ranks second, fourth, and seventh in the

western Himalaya, eastern Himalaya, and the Flora of British India, respectively

(Hooker, 1904; Hara and Hohashi, 1966- 1974; Rau 1975).Poaceae was another

prominent family in our study area.

Family to genera ratio in our study area was 1:2.44 and genera to species ratio was

1:3.4 which is similar to other reports from different region of Himalaya range, for

example the check list of Phanerogames presented by Fazal et al.,(2010) revealed that

genera to species ratio was 1:1.24 and genera to family ratio was 1:2.54 from district

Haripur, the study of Shaheen et al., (2014) from Santh Saroola, Kotli Sattian,

Pakistan indicated that family to genera ratio was 1:2.34 and genera to species ratio

was 1:1.25. Preliminarly check list reported by Ilyas et al., (2013) from Kabal Valley

Swat, Pakistan indicated that family to genera ratio was 1:3.1 and species to genera

ratio was 1:1.45 and Qureshi et al., (2014) rported family to genera ratio 1:2.56 and

genera to species ratio 1:1.30 in flora of Khanpur Dam, Khyber Pakhtunkhwa,

Pakistan.

Most part of our study area fall in subtropical and moist temperate habitat. In

present study most of the plant species collected from lower elevations of the district

127

were representing subtropical vegetation, for example, Acacia modesta, Calotropis

procera, Ficus palmata, Acacia nilotica Dalbergia sissoo, Justiceae adhatoda, Otostegia

limbataCarissa opaca,Dodonaea viscosa and Maytenus royleanus. These plant species

were reported from many other regions. Nazir et al., (2012) studied the subtropical

forests of Sarsawa Hills District Kotli, Azad Jammu & Kashmir, western Himalaya

and reported Pinus roxburghii,Ficus palmata, Acacia nilotica Dalbergia sissoo, Adhatoda

zeylonica, Carissa opaca, Dodonaea viscosa, Maytenus royleanus, Punica granatum,

Otostegia limbata, Themeda anathera, and Poa annua as indicator species of sub-tropical

vegetation. Hameed et al., (2012) indicated that Dodonaea viscosa, Justiceae adhatoda,

Otostegia limbataCarissa opacaChrysopogon serrulatus, Dichanthium foveolatum and

Cymbopogon spp.as indicator of lower altitudes. Shah & Rozina (2013) documenteda

total of 72 plant species belonging to 23 families from Dheri Baba hill Gohati and

Peer Taab graveyard District Swabi, Khyber Pakhtunkhwa, Pakistan. It includes

Zizyphus mauritiana, Acacia modesta, Calotropis procera, Carthamus oxycantha, Centaurea

calcitrapa, Eryngium bourgatii, Eucalyptus lanceolatus, Euphorbia prostrate, Solanum

surattense and Opuntia. Most of these plant species are similar to the species reported

from our research area.

The characteristic species of moist temperate sort of habitats were collected relatively

from higher elevations of the study area which include Abies pindrow, Quercus incana,

Pyrus pashia, Quercus dilata, Taxus wallichiana, Pinus roxburghii, Diospyrus lotus, Cedrus

deodara, Juglans regia, Viburnum grandiflorum, Berberis lycium, Indigofera heterantha,

Sarcococca saligna, Hedra nepalensis, Viburnum cotinifolium, Rubus ellipticus, Skimmia

laureola, Isodon rugosus and Cotoneaster bacillaris. Different authors from other parts

128

of Himalaya documented such species e.g. Pinus wallichiana, Aesculus indica,

Viburnum grandiflorum, Prunus cerasoides, Indigofera heterantha, , Viburnum cotinifolium,

Trifolium repens Paeonia emodi, and Bistorta amplexicaulis were documented from moist

temperate Himalaya of Pakistan by Saima et al., (2010). Hameed et al., (2012)

recorded Pinus wallichiana and Cedrus deodara from higher altitude of Himalayan

foothill region of Punjab.

4.2 Phytosociological classification

Scientific advances in ecology led towards the sciences of phytosociology, phyto-

geography and synecology (Leveque, 2001). Phytosociology is the study of plant

communities and associations. A community is assemblage of plant population

established in one habitat type in specific area and show mutual competition and

dependence. Certain plant species perform well in wide range of environmental

conditions while it is impossible for some plant species to perform well in different

environmental conditions (Atri et al., 2007). Different plant species are assembled in

different associations due to variations in habitat, environmental factors and biotic

relationships. Study of plant communities provides informations about plant species

distribution in relation to different ecological factors. This information gives basis for

estimation of probable future changes (Mueller and Ellenberg, 1974). Elevations,

aspect, degree of slope and precipitations phenomena are most important variables

affecting the distribution of vegetation in mountainous areas (Titshal et al., 2000).

Elevation from sea level is an important environmental variable for determination of

vegetation type (Day and Monk 1974; Busing et al., 1992). With change in altitude

floristic composition and community structure is changed (Sakya & Bania 1998;

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Ayube et al., 2004). Ecological diversity of a community is considered to be a

measure of the health of its ecosystem (Mc Grady-Steed and Morin, 2000). Modern

phytosociological techniques are important tools to study the distribution of

vegetation of an area.

Champion et al., (1965) and Beg (1975) recognized various types of forests and

different vegetational zones in Pakistan and India, based on variation of temperature

and altitude. Rafi (1965) presented similar studies from Balochistan Province.

Hussain & Illahi (1991) described ecology and vegetation types of Lesser Himalaya

of Pakistan. Hussain (1984) documented vegetation of Karachi and Pakistan.

Number of phytosociological studies has been done in Pakistan on various scales.

Hussain (1964) surveyed the vegetation of Nagarparker. Hussain (1969) and Naqvi

(1974) conducted phytosociological study at Wah Garden and Murree Hazara Hills,

respectively. Phytosociological study of Sundangali, was carried out by Malik et al.,

(1990a). They described three plant communities (i) Malvestrum- Cymbopogon-

Adiantum (ii) Medicago-Cynodon-Euphorbia and (iii) Cynodon-Reinwardtia-Micromeria in

Sund Gali Muzzafarabad Azad Jummu and Kashmir. Shah et al., (2014) conducted

Phytosociological study of Farash hills Katlang, District Mardan. They identified 15

plant communities in the study area. Ahmad (2009) documented 52 herbs belonging

to 26 families from Margalla Hills National Park, Islamabad, Pakistan and classified

them into four plant communities by using TWINSPAN. Many other ecologists

carried out phytosociological studies from different areas of Pakistan. Most of these

studies were on small scale and there are only few studies about the phytosociology

of tropical and sub tropical regions involving the use of modern techniques like

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TWCA, DCA and CCA. There is no previous record of phytosociological study in

District Tor Ghar. We have used modern phytosociological approaches in rugged

mountains which were rarely used in vegetation analysis in such remote areas in

developing world. We have used mixed methods of quadrat along transect to get

maximum diversity and enough data for vegetation maping. We have used modern

phytosociological techniques like TWCA, Cluster Analysis, and Indicator Species

Analysis etc. During the present research work phytosociological investigation was

carried out to explore the ecosystem and floristic biodiversity of the region. The

phytosociological attributes were recorded in three vegetational zones. In the

investigated area 64 stands were selected for phytosociological attributes. IVI data

obtained from these stands were further analyzed for classification and ordination.

The data from the study area revealed that plant communities confined in one region

are not available at the other sites due to differencesin altitude, soil depth, and other

environmental variables.

The present Phytosociological analyses have revealed different climatic zones in the

study area by applying TWCA, and CCA. Major vegetation zones were subtropical,

moist temperate and sub alpine region. During the research work in different sites

of the study area it was noticed that soil erosion due to deforestation and

constructions of roads were important factors causing a reduction in vegetation

abundance and species diversity of the region. Losses of soil due to soil erosion have

resulted in the loss of fauna and flora. In present research project vegetation of

district Tor Ghar was analysed. A total of 320 quadrats were used each for herb,

shrub and tree species at 12 different localities and 64 stations. A total of 331 vascular

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plant species were recorded in these sites. The data collected from these sites was

analysed by cluster analysis and Two Way Cluster Analysis which give rise to six

different plant associations.

4.2.1 Cluster Analysis of Vegetation

Classification is used by ecologists for grouping the species or stands into groups on

the basis of similarity. In cluster analysis the samples or species are classified into

smaller number of interpretable groups or clusters that are meaningful and useful

and helps in understanding relationships between and within the community. In this

study we explored vegetation structure and composition from different vegetational

zone in the district. Using cluster analysis six plant communities were reported

which can be seen in the cluster dendrogram.In the dendrogram there were two

main branches indicating two different habitat types i.e. humid subtropical habitat

and the second half of the dendrogram includes the plant communities representing

chir pine forest type, moist temperate forests and subalpine type. Three plants

communities can be seen in first half of the dendrogram and three plant associations

are present in the second half of dendrogram.The presence of a species is important

in vegetation classification rather than its abundance (Greig-Smith, 1983). Therefore,

the analysis is done by cluster analysis and Two Way Cluster analysis using

presence/absence data.

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4.2.2 Two Way Cluster Analysis (TWCA)

In present study TWCA was used for classification of plant species resulted in a two

way cluster Dendrogram. TWCA divided the samples into two main groups, which

were further separated into smaller groups.

The six plant communities were documented as a result of cluster analysis and Two

Way Cluster Analysis. In the investigated area altitude is the main factor change the

species diversity from Indus River to the top of altitude the study area. In the study

area communities located at low altitude indicated low species diversity while the

plant communities present at higher altitude were showing high diversity. Similar

results were reported by Malik et al., (1990b), Kharwal et al., (2005) and Khan et al.,

(2015). In contrast the diversity decreases with increase in elevation in subalpine and

alpine ecosystems as reported by Khan et al., (2012). They quantify the vegetation of

Naran Valley by using modern statistical techniques and reported that plant

biodiversity decreased along the altitude. The diversity decreased at higher altitude

due to steep slope, low temperature and high wind velocity. The six plant

communities on the basis of available indicator species can further be classified into

three categories (Haq et al., 2010; Champion et al., 1965); which are Tropical sub

humid forests, sub-tropical chir-pine forests and mixed coniferous forests.

4.2.2.1 Tropical Sub Humid Forest

Most of the sites included in this zone were located near the River Indus, near to

human settlements and are exposed to human disturbances. The study of plant

communities in the region shows that at lower altitude along the Indus River

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Tropical sub humid vegetation is found which changes with changing altitude. At

lower altitude temperature was hot with poor rainfall while at higher altitude low

temperature prevails with significant precipitation. Primarily, community I, II and

III include the species of tropical sub humid and sub tropical vegetation. Community

I Delbergia sisso- Mallotus philippensis -Cyperus cyperoides was reported from five

localities at altitude 467-1260 msl. The biological spectrum was dominated by

Hemicryptophytes and therophytes. A total of 101 species were recorded in the

community. Total IVI of three dominant species was 954. Dalbergia sissoo was

reported from most of the localities and was dominant tree species in community I.

It is a deciduous tree and propagates by root suckers and seeds. Most of the sites in

this community provide suitable environment for the growth of Delbergia sisso,

Acacia modesta and Acacia nilotica. Pinus roxburghii was found above 900 masl at the

localities like Guth area. Mallotus philippensis is a large genus of trees and shrubs

distributed chiefly in the tropical and subtropical regions of the Himalayas

ascending to 1500 meters. It is frost-hardy and resistant to drought (Gangwar et al

.,2014) Under the pressure of regular human disturbance, M. philippensis is able to

show its constant presence in different forest communities. In addition to

recruitment by seeds, it exhibits efficient vegetative propagation and provides

enough and essential understorey cover for the ecosystem attributes of forests. Its

bushy sprouts and evergreen nature provide niches for other herbs, climbers and

wild fauna even in the presence of recurrent disturbance (Pandey & Shukla 2003).

The important grasses found in this zone were Cyperus cyperoides, Cynodon dactylon,

Chrysopogon serrulatus and Digitaria nodosa. These grasses were found in most of the

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communities. Cyperus is a very noxious weed. It occurs in waste lands, along

pavements and farms. Cyperus is allelopathic to many plant species growing in the

locality and can reduce yield of crop to a great extent as it compete for mineral

resources with crop plant (Zareen et al., 2015)

The community II: Acacia modesta- Dodonaea viscosa - Cynodon dactylon was

established at lower altitude of the study region at altitude 506-840msl. It was

reported from 15 localities in the study area. Hemicryptophytes and therophytes

were the dominant life form classes from this community.

Important localities of this community were Kotley, Judbah, Sarbago, Shagai,

Shadak, Gorial and Zizari. All these localities were present near the Indus River. A

total of 161 species were reported from this community. The tree species were

represented by Acacia modesta as adominant species. Acacia modesta is a medium

sized tree dominant in community II and found abundantly in this vegetation zone

because it grows in different types of habitats. It is very drought resistant and can

easily be grown from seed. Pinus and Acacia spp. are commercially important plants

which provide gum, resin and wood which are important source of income for the

inhabitants who sell these products in nearby market.

Indicator species analysis identified Acacia modesta and Mallotus philippensis as

indicator species on the basis of degree of slope and low soil depth (appendix 8).

Other important tree species with high IVI value were Delbergia sisso, Ailanthus

altissima, Broussonetia papyrifera, Acacia nilotica and Ficus palmata. Characteristic

species of shrub layer consists of Dodonaea vescosa, Mallotus philippensis, Otostegia

limbata, Justicia adhatoda, Colebrookia oppositifolia, Calotropis procera, and Myrsine

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africana. The dominant species of herb layer were Cynodon dactylon, Chrysopogon,

Digitaria nodosa, Agrostis stolonifera, Cannabis sativa, Rumex hastatus and Aerva javanica

(Appendix 3). Most of these species are the indicator species of the subtropical

habitats (Haq et al., 2010). Cynodon dactylon propagates by seeds and due to this

reason it flourishes in all type of habitat (Nasir and Rafique, 1995). Their seeds are

disbursed by wind to long distances and show good percent cover values. Cynodon is

considered as an important fodder grass (Cope, 1982.). Due to high grazing pressure

most of the dicot species are eradicated. Only less palatable and non palatable

species were present. Cynodon dactylon was dominant because it occurs on almost all

types of soils and was common in the habitat disturbed by man and under severe

grazing pressure, unused lands etc. (Martin et al., 1951). It has capability to resist the

drought and high temperature and can survive in the area where only few grasses

are found (Shah & Rozina, 2013).

Similar to community II, Acacia modesta community was recorded by Khan et al.,

(2014) from Poonch valley, Azad Kashmir Himalaya region at altitude of 3500 feet.

Ahmed et al., (2006) documented the dominance of Acacia modesta and Olea

ferruginaea community on the southern aspects of lower hills of Murree.

The community III: Ailanthus altisima- Justicia adhatoda- Digitaria nodosa represents the

degraded sites of the study area. It was reported from 8 localities. In the degraded

sites organic matter is reduced and species requiring low moisture and low fertility

will survive. Less number of species was recorded from this community (121). Total

IVI of three dominant tree species was 917.28. It is less than the rest of plant

communities. Due to degradation of habiatat and other human activities growth of

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tree and shrubs is affected. This community represents highest number of

therophytes (21.48%) which is indication of habitate destruction, overgrazing and

other human interference. Therophytes are experts of occupying vacant niches as a

result of disturbances like deforestation and overgrazing (Pysek et al., 2005). The

localilities Dni 8 (Chor Kalan 1) and Dni 9 (Chor kalan 2) were present at higher

altitude, but due sever conditions like steep slope, habitat destruction and heavy

grazing pressure (Appendix 4) represent disturbed habitat. In degraded sites sun

tolerant or loving species which require low moisture and low humidity grow better.

This causes the reduction of species diversity as number of sciophytes reduced.

These findings are similar to the results of Malik et al., (1990). Important plant

species found in this community were Dodonaea vescosa, Acacia modesta, Justicia

adhatoda, Ailanthus altissima, Pinus roxburghii, Digitaria nodosa, Yucca aloifolia,

Calotropis procera, Broussonetia papyrifera, Myrsine Africana, Phoenix dactylifera,

Nannorrhops ritchieana. Ailanthus altissima is an introduced species and is mostly used

for fuel wood.

The dominance of Ailanthus altissima in community III indicates the anthropogenic

influence on the community structure. At lower elevation human interference results

in introduction of non-native species (Rawal & Pangtey, 1994). Broussonetia papyrifera

is an invasive species of this zone. Occurrence of non-native species like Broussonetia

papyrifera and Ailanthus altissima in this community were due to human caused

alterations in natural ecosystems. In this community original habitat was altered by

the removal of vegetation. Human influence on the natural flora has been studied by

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different researchers in adjacent regions and found in accordance with our findings

(Peer et al., 2001; Kukshal et al., 2009; Malik & Hussain, 2006).

Characteristic species of this zone include Acacia modesta, Delbergia sisso, Broussonetia

papyrifera and Phoenix dactylifera, Acacia nilotica, Butea monosperma, Pistacia integerrima

Bombax ceiba, Aerva sp, Mallotus philippensis, Dodonaea vescosa, Colebrookia oppositifolia,

Maytenus royleanus, Carissa opaca, Otostegia limbata, Justicia adhatoda, Colebrookia

oppositifolia, Calotropis procera, Myrsine africana and Verbascum Thapsus. Important

factors affecting plants distributions in this zone were elevation from sea level, soil

depth and grazing pressure. Most of the localities are found on Gentle slope and at

low altitude.

The dominant life form was Hemicryptophytes and therophytes. Malik (2005)

reported high proportion of Hemicryptophytes and therophytes from Ganga Choti

Bedori hills due to deforestation and other anthropogenic influences. Higher

proportion of therophyte in this zone indicate harsh climate. Anthropogenic

influence is the main cause of change in biological spectra in given vegetational zone

(Zahid, 2007).

4.2.2.2 Sub-Tropical Chir-Pine Forests

The important localities in Sub tropical Chir pine forests were Dada Banda,

Haleema, Nawagae, North and South of Sahbah hill, Arnil, Shatal area, Shangal Dar

area and Pian hill. The altitude ranges from 740-1730 masl. Indicator species

identified by high soil depth indicated the Quercus and Pinus roxburghii as

characteristic species for tree layer. Community IV and V were representing this

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vegetation zone. This zone of vegetation in study area is characterised by medium

slope, high soil depth and low grazing pressure (Appendix 4).

Important tree species were Pinus roxburghii, Acacia modesta, Ailanthus altissima,

Pinus wallichiana, Delbergia sisso, Quercus incana, Olea spp., Pyrus pashia, and Juglans

regia. Prominent shrubs species were Indigofera heterantha, Berberis lycium,

Debregeasia salicifolia, Rubus ellipticus, Rosa moschata, Carissa opaca, Dodonaea vescosa,

Isodon, Zanthoxylum armatum and Cotinus coggyria, Justicia adhatoda and Otostegia

limbata. Important herbs consist of Cynodon dactylon, Agrostis stolonifera, Apluta

aristata, Oxalis carniculatus, Alliaria petiolata, Duchesnea indica, Taraxicum officinale,

Parthenium hysterophorus, Poa alpina, Digitaria nodosa, and Taraxicum officinale. These

plant species are the characteristic of subtropical chir pine forest. Number of plant

species was highest in these two plant communities. It was due to similar elevation

from sea level, edaphic factors and habitat type. As habitat, elevation and edaphic

conditions are changed diversity is changed.

Community IV: Pinus roxburghii-Rubus ellipticus-Agrostis stolonifera was reported

from 16 localities in the study area at altitude 740-1400msl. The tree layer was

characterized by Pinus roxburghii as a dominat plant species. The dominant texa of

shrub layer is Rubus ellipticus and Agrostis stolonifera represents the dominant herb

of the community. The most effective environmental variable responsible for the

formation of this group was high soil depth associated with low grazing pressure. It

was most diverse community in the investigated area. A total of 229 vascular plant

species were documented from this community. Soil moisture and organic matter

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due to deposition of litter was high under Pinus roxbergii community. Species

diversity increase with increasing the humidity (Danin,1999).

Community V:Pinus roxburghii- Berberis lycium–Chrysopogon was recorded from 12

localities at altitude 900-2050msl. Pinus roxburghii was the dominant tree species.

Berberis lycium emerged as dominant species in the shrub layer and Chrysopogon was

dominant herb species in this community. Total IVI of the tree layer was 3600 while

shrub layer represents 3374. A total of 220 vascular plant species were reported

showing rich plant diversity in the community.

The dominance of Pinus roxbergii in subtropical forests is reported in previous study

from Himalaya by Champion et al., (1965). In ideal conditions, the Pinus is dominant

due to its wide ecological amplitude and specific niche in this zone (Ahmad et al.,

2010). The study of life form classification of this plant community revealed that

Hemicryptophytes with 62 plant species (32.8%) were dominant followed by

therophytes (26.4%). Higher proportion of Hemicryptophytes than the tropical sub

humid forest vegetation zone reflects climatic condition of this zone. Many

ecologists documented similar vegetation from different part of the Himalaya and

our results are in agreement with them like Ahmed et al., (2006) reported Sub-

Tropical Chir Pine- Blue Pine Ecotonal Forests from Ghoragali Murree at an altitude

1570 msl and indicated that that Pinus roxburghii was dominant and Quercus incana

was in low density and other species include, Myrsine africana, Viburnum

cotinifolium, Berberis lyceum, Hedera nepalensis, Indigofera heterantha and

Chrysanthemum leucanthemum. It seems that due to anthropogenic influence these

plant communities might eventually modified to degraded scrub-land with

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dominant species Maytenus royleanus, Justicia adhatoda, Dodonaea viscosa and other

related species (Malik et al., 1994).

4.2.2.3 Mixed Coniferous Forests

Pinus wallichiana - Viburnum grandiflorum - Poa alpina community (Community VI)

was reported in this vegetation zone. This zone can be established at 2130-2950 masl

hosting moist temperate reaching to subalpine ecosystem. The important stations at

this elevation range were Bakain, Bratho, Kando Gali, Mana Sar, Doda Gata, Tor Ban

and Machasar. Important environmental variable responsible for grouping the plant

species was altitude associated with low soil depth and grazing pressure. Severe

deforestation, over grazing, steep slope and soil erosion (appendix 4) have changed

the community structure. Some important plants such as Abies, Cedrus deodara, Picea

smithiana, Pyrus pashia and Taxus wallichiana are destroyed. Due to unavailability of

alternate source, people are dependent on these forests for fuelwood. The local

inhabitants use these plants for different benefits, causing degradation of plant

community. The plant species - Abies pindrow, Pinus roxburghii, Quercu dilata, Taxus

wallichiana, Diospyrus lotus, Cedrus deodara, Juglans regia, Viburnum grandiflorum,

Berberis lycium, Sarcococca saligna, Hedra nepalensis, Viburnum cotinifolium, Rubus

ellipticus, Skimmia laureola, Isodon rugosus and Cotoneaster bacillaris are the

characterictic plant species of moist temperate forests. Sarcococca saligna, Hedra

nepalensis, Viburnum cotinifolium, Skimmia laureola and Isodon rugosus are dominant

due to moist soil condition and are mostly unpalatable. These plants multiply under

grazing pressure. Viburnum grandiflorum was dominant shrub having highest IV.

Important herbs consist of Poa alpina, Cyperus cyperoides, Digitaria nodosa, Valeriana

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jatamansi, Viola odorata, Euphorbia wallichii, Impatiens bicolor, Duchesnea indica. Pinus

wallichiana was characteristic tree species of this community. The community is

named on grass species i.e, poa due to highest presence of this species. It is group of

grasses with smooth and hollow stem and grows in clusters. It can compete with

other grasses. The dominance of hemicryptophytes is indication of temperate zone

(Cain and Castro 1959, and Shimwell, 1971). This community shows antrhropogenic

influence on the vegetation. Abies pindrow and Quercus spp. is the climax community

for western Himalaya (Champion & Seth, 1968). The change in this community is

due to destruction of these forests by deforestation and overgrazing. Quercus spp.

are widely used for fuel and fodder. These activities have resulted in the reduction

of vigour and seed production (Saxena & singh, 1984). Heavy browsing also causes

reduction in plant species. Large scale removal of certain species also produced

structural change of plant community (Spurr & Barnes, 1980). Similar vegetation

type was reported by Malik et al., (2007) from Pir Chinasi Hills. They reported Pinus-

Viburnum-Poa community as degraded vegetation at an altitude of 2000-2600 masl

and Pinus-Viburnum-Plantago community at an altitude of 2800m. Our results are

supporting them. Abies pindrow community was reported by Khan et al., (2013a) from

Naran valley at altitude of 2800-3400 and Ahmed et al., (2006) from Miandam,

Dungagali, Ayubia and Murree hills from 2245 to 2350 masl. In our study area due to

anthropogenic influence, like severe deforestation, over grazing and soil erosion, the

community structure has been changed and important woody plants Abies pindrow,

Cedrus deodara, Picea smithiana and Taxus wallichiana were destroyed.

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Ahmed et al., (2006) reported Pinus wallichiana community from Murree, lower Topa,

and Jhikagali at altitude of 1970 - 2250 msl with Quercus incana as a codominant

species. Other species were Hedera nepalensis Lolium perenne Chrysanthemum

leuconthemum, Berberis lyceum, Myrsine Africana, Viburnum contifolium. Chaudhri,

(1960) indicated that Pinus wallichiana is a pioneer species present on all aspects

having wide altitudinal range.

Indicator species for each of the vegetation zone were identified by indicator species

analysis using PCORD. These species were Acacia modesta, Delbergia sisso, Euclaptus,

Bombax ceiba, Mallotus philippensis, Dodonaea vescosa, Otostegia limbata, Pinus

roxburghii, Cynodon dactylon, Quercus incana, Indigofera heterantha, Carissa opaca,

Duchesnea indica, Maytenus royleanus, Viburnum spp., Juglan regea, Ficus elastic and

Pinus wallichiana. Unlike the indicator species analysed by Khan et al., (2011) from

Naran valley which include, Aster falconeri, Iris hookeriana and Ranunculus hirtellu,

Achillea millfollium, Sambucus wightiana, Pinus wallichiana, Betula utilis, Abies pindrow,

Rheum austral, Poa alpina, plantago lanceolata, Impatiens bicolor, Fragariab nubicola,

Taraxicum officinale, Trifolium repens, Juniperus excels, Artemisia brervifolia, Onopordum

acanthium and Eremurus himalaicus. Hussain, (2014) identified indicator species

during the vegetation analysis of Deosai National Park, Gilgit Baltistan. Indicator

species were Saxifraga flagellari, Androsace mucronifolia, Agropyron longearistatum,

Carex cruenta, Agropyron longearistatum, Bromus oxydon Allium semenovii and Aster

flaccidus. Most of the study area falls in sub tropical habitat therefore, indicator

species are mostly subtropical.

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Biodiversity of a region can be understood in a better way if certain systematic tools

are taken into consideration. Phytosociology is one of the branch of ecology having

such tools equipped with modern statistical approaches.

4.2.3 Environmental Gradient Analysis via Ordination Techniques

Environmental gradient or ordination analyses are analytical procedures used to

study species relationship with responsible ecological factors using statistical

approaches. These techniques using CANOCO version 4.5 showed that

environmental variables, like soil, light, water, temperature, elevation etc., play

important roles in species distributions. In present study indirect and direct

environmental gradient analyses were performed. Indirect method Detrended

Correspondence Analysis (DCA) was used for ordination analyses. Khan et al.,

(2012) used modern techniques like CANOCO to quantify the diversity Indices of

plant communities and habitat types. Ahmed et al., (2009) studied the vegetation

from Abbottabad road side using Detrended Correspondence Analysis (DCA) and

Canonical Correspondence Analyses (CCA). They identified 5 plant communities

along roadsides. TWINSPAN and DECORANA techniques were used by Ahmed

and Yasmin (2011) to analyze the vegetation along Hanna Lake, Baluchistan. They

described 2 main communities and 4 sub-communities. But all of these studies are at

smaller scales. For the first time we have used these techniques on a whole district

level.

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4.2.3.1 Detrended Correspondence Analysis (DCA)

In Detrended Correspondence Analysis (DCA), only species data was used (Sagers

& Lyon, 1997). Detrended Correspondence Analysis was used to study the pattern of

species distribution among the major plant communities with in research area and to

confirm the outcomes of Cluster analysis and Two Way Cluster Analysis (TWCA).

Default sitting of CANOCO was adapted using DCA that resulted in AX1 and AX2

from which ordination diagram was constructed. Every point on the graph

corresponded to species. The different species which occur with same abundances in

the same site would occupy the same point. The distances among the points on the

graph represent the distribution of a plant species.

Ordination of the site and tree species reported from the district Tor Ghar by DCA

revealed that the Ist two axes have given useful information about the distribution of

species. Maximum gradient length 6.32 with Eigen value 0.63 were recorded for axis

1 and gradient length 5.0 with Eigen value 0.212 from 2nd axis of DCA reflected that

habitat and species were showing strong correlation with first and second axes while

the Eigen values 0.13 and 0.83 from 3rd and 4rth axis indicated that there was less

correlation with these axis. The localities Judbah (Jdbh I), Shagai Basi khel (Shagi I),

and Kotkey Hasan zai (Ktky I), Shadak (Shdk 1) and Zizari Basi Khel (ZZari 1)

(representing community 1 & 2) are present at the upper right side of the DCA

diagram. These sites occur near the Indus River showing negative correlation with

Darbani Akazai (Dni2), Dadam Hasan Zai (Ddme 1), Toot banda (tbda), Ttbda 3,

Dmn2, Darbani Dni 1 (community 3) most of these sites are also located at lower

altitude but representing the degraded localites. The DCA diagram reflected that the

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vegetation of these habitats were different from rest of the region due to the presence

of these localities near the human settlements and are exposed to anthropogenic

disturbances. Some of the stations like Chor kalan and Chota kandow are present at

higher altitude but due to heavy human interference and sever climatic condition

showing resemblance with subtropical habitat. The stations Kando Gali (Jdbh 12),

Bratho (Jdbh 11), Tor Ban (Dni 13), Doda Gatta (Dni 12), Arekh (Jdbh 10) and Jdbh 9

(Community No. 6) are located at the right side of the diagram. These localities were

indicating moist temperate type of habitat and the sites present at the left side

reflecting subtropical habitat.

The DCA diagram for tree revealed that most of tree species like Acacia modesta,

Delbergia sisso, Pinus roxburghii, Olea ferruginea and Acacia nilotica are present in the

centre of the diagram, share more than one community. Whereas tree species Abies

pindrow, Cedrus deodara, Picea, Aesculus and Taxus wallichiana are present at right side

of DCA diagram showing strong correlation with Ist axis and are found in one plant

association (Community VI). These species were representing moist temperate and

subalpine vegetation. Similarly the species, Ficus benghalensis, Poplus, Butea

monosperma and Bombax ceiba were present at the upper right side of the DCA

diagram showing no correlation with most of the tree species and are negatively

correlated with the species Albezzia procera and Phoenix spp. These species were found

in different topographic conditions. The results also revealed that most of the plant

species followed arrangement similar to sites indicating that distribution of these

species is influenced by topographic factors.

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DCA diagram representing shrubs species and habitat types reflected that majority

of shrub species stations were strongly correlated with 1st and 2nd axis.The localities

distributed at margins of the diagram represent habitat specificity while the stations

located in centre were showing similarity among each other. The site Kando Gali

(Jdbh 12), Torban (Dni13), Bratho (Jdbh 11), Arekh (jdbh 9) and Jdbh 10 are higher

altitude of the study area representing moist temperate and sub alpine habitate and

showing different vegetation from rest of the sites. The localities like Kotkey Hasan

Zai (Kotly1), Kotly 2 and Tor kandow (Tk 1), Kotley Nusrat Khel (Ktly 1), Gorial Basi

Khel (Gorl 1), Dheri (Dri 1) and Shadak (Shdk 1) are present at low altitude near the

Indus River representing Tropical Sub Humid climate. The stations Shagai and

Judbah showing different shrub vegetation due to occurrence near human

settlements.

The localities, Dada Banda (Zizari3), Banda (Zizari 4), Shangal Dar (Shagai 6), Danda

(Gorl 3) and Shatal (Shdk 4) are located at the center of diagram showing similarities.

Most of these localities are found at same altitude, share similar climatic condition

therefore, hosting similar shrub vegetation. Ordination of the site and shrub species

reported from the district Tor Ghar by DCA is depicted in DCA diagrams. The Ist

axis has given a best summary of original data (Eigen value 0.64 and for 2nd axes it is

0.189) Ordination diagram for sample of shrub species indicated a strong correlation

with 1st axes.

The plant species located at left side of the DCA diagram is the indication of sub

humid tropical habitat and shrub species present on right side of the DCA diagram

showing moist temperate and sub alpine habitat. Species like Skimmia laureola,

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Sarcococca saligna and Hedra nepalensis are present on the right side of the diagram

and are found on high altitude and low soil depth conditions. Similar altitude is the

main environmental variable responsible for grouping these plant species and

representing moist temperate coniferous type of habitat. Comparison of localities

and species DCA diagram showed that these shrubs are absent from rest of localities

due altitudinal differences. The species like Yucca aloifolia, Calotropis procera and

Nannorrhops ritchieana were present at the right side of the diagrm indicated sub-

tropical habitat.

The occurrence of shrub species Vitis and Nannorrhops ritchieana on negative axis is

indication of habitat specificity of these species in study area. Where as many shrub

species are located at the center of diagram which shared many vegetation types

such as Carissa opaca, Cotinus coggyria, Otostegia limbata and Zanthoxylum. Some

shrubs show no correlation with other plants like Bambusa, Yucca aloifolia and

Nannorrhops ritchieana which is indication of specific locality. The species

distribution along the first axis of DCA reflected altitudinal gradient. In hilly

regions, elevation shows the greatest influence in controlling plant species and

community classification (Chawla et al., 2008).

The second axis represented the distribution of species along degree of slope and

soil depth. The results of the study revealed that elevation, soil depth and slope are

the main factor affecting the distribution of plant species.

Results of Detrended Correspondence Analysis (DCA) for all 240 herbaceous plant

species revealed that most of the sites are located in the center of DCA diagram

showing similarities and are found in many plant communities. The Eigen value 0.58

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and 0.360 from Ist two axis of DCA indicating that habitat and species show strong

correlation while the Eigen values 0.270 and 0.208 from 3rd and 4rth axis indicated

that there was less correlation with these axis.

Some localities like Tor Kandow (TK EC1), Tk2, and Toot Banda (Ttbda 3), Ttbda

located at the left upper half of the DCA diagram showing different habitat than rest

of the locations. The Localities like Kotkey (Ktky 1), Ktky 2, Behri (Kt ky 3), Guth

hill (Ktky 4, Ktky 5) present at the lower left half of the DCA diagram are the sites

reflecting lower altitude. The vegetation of these habitats differs due to more

anthropogenic interference. Anthropogenic interferences are the major controlling

factors regulating species distribution (Mueller & Ellenberg, 1974). The herbaceous

habitats; Kandow gali (Jdbh 12), Tor ban (Dni 13), Doda gatta (Dni 12), Mana Sar

(Dni 11), Arekh (Jdbh 10) are the moist temperate habitat located at higher altitude.

DCA diagram for herb species revealed the distribution of herbaceous species in the

study area. Most of the herbs are present in more than one association showing

similarities. Where as, many plant species were showing specific localities in the

research area. Rumex vesicarius does not show correlation with rest of the herbs

showing specific locality. It was found in one association only. Herbaceous flora

located at the extreme right side of the diagram, Boenninghausenia albiflora, Impatiens

bicolor, Valeriana, Urtica pilulifera and Arisaema utile showing strong correlation with

axis 1 (representing community VI). The first axis represents altitudinal gradient.

Comparison of herb species and habitat revealed that these species are chacteristic of

moist temperate forest type habitat and are absent from rest of the habitats. The

dominance of these plant species decreased from higher altitude to lower

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altitude.These species are showing negative correlation with species located at the

left side i.e Opuntia, Canna, Solanum virginianum which are located at low altitude

and poor soil condition.

In DCA diagram the position of some species is not similar to site indicated that the

distribution of thses species is not affected by topographic and edaphic factors.

Species distribution is controlled by a combination of environmental and

anthropogenic influence (Dolezol & Srutek, 2002).

Similar results were reported by Jabeen and Ahmad (2009). They conducted a

research project to study the vegetation and environment data of Ayub National

Park, Rawalpindi. Khan et al., (2011) studied 5 plant communities of Naran valley,

Pakistan by using TWCA and indicator species analysis and reported that aspect,

altitude and soil depth were important variables responsible for species distribution

in study area.

4.2.3.2 CCA Canonical Correspondence Analysis

Canonical Correspondence (CCA) has proved to be superior to others techniques

such as PCA (Gauch, 1982). When data sets are heterogeneous the results of CCA

are generally better than PCA and CA. However, when the data is relatively

homogenous with short gradients, PCA may be better option for ordination

procedures (Palmer, 1993). Species distribution pattern depend on various

environmental variables. Correlation between vegetation and different

environmental variables using CCA confirmed altitude, soil depth, degree of slope,

grazing pressure and soil erosion as more determinant environmental

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variables.Biplots showed point locations as representative of individual species

whereas arrows indicate change in environmental factor. Length of arrow shows

strength of that particular variable.

CCA diagram for tree species reflected that among five environmental varibales

elevation was the most influential factor in tree species distribution followed by

slope and soil depth. Among climatic gradients, slope and soil depth were strongly

correlated with each while grazing pressure and soil erosion were positively

correlated. Among 4 CCA axes, the first and second axes (Eigen value 0.481, 0.165)

had strong correlation with environmental gradients. The stations Doda Gatta (Dni

12, Tor ban (Dni 13), Bratho (Jdbh 11), Manasar (Dni 11) and Chota Kandow (Dni 10)

were located at high altitude and represented the moist temperate and sub alpine

type of habitat.These stations are different from rest of localities due to altitude,

because with change of altitude,the vegetation also changes. Stations, Darbani

(Dni2). Dehri (Dri), TorKandow (Tk1), Dadam (Dmn 1, Dmn2) Tor Kandow 2 (Tk2)

were representing community II. Low soil depth and gentle slope was seemed to be

the effective variable responsible for grouping these sites. The altitude, soil depth

and slope were more effective variables responsible for distribution of tree species.

The Pinus wallichiana, Abies, Quercus incana, Pyrus pashia, Taxus wallichiana and Cedrus

deodara were found on high altitude and these species were separated from other

species.These tree species were present in one plant association (community VI) and

were absent from rest of the associations due to difference in elevation on the other

hand plant species like Bombax, Butea and Acacia modesta were present at low

altitude. Soil erosion and grazing pressure were less effectivein plant distribution.

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Quercus sp., Pyrus sp., Juglans regia and Cornus macrophylawere present at steep slope.

Acacia modesta, Phoenix, Eucalyptus sp and Delbergia sisso were closely associated and

were found in gentle slope and low soil depth.

Vegetation association cannot be described on the basis of single process, altitude is

considered as a primary factor in community development (Billings, 1952; Whittaker

and Niering, 1975, Barbour et al., 1991). Altitude helps in representation for several

interrelated and biologically important environmental variables e.g. rainfall and

temperature, and is helpful in determining vegetation composition (Lookingbill &

Urban, 2005).

The biplot diagram for shrub species show that the distribution of species such as

Sarcococca saligna, Hedera nepalensis, Viburnum cotonifolium, Rubus ellipticus, Skimmia

laureola, and Cotoneaster bacillaris (representing Community VI) was more affected by

slope and altitude while Dodonaea viscosa, Mallotus philippensis, Otostegia limbata,

Justicia adhatoda, Colebrookia oppositifolia, Calotropis procera, and Myrsine Africana

(representing community I & II) were less affected and were found at lower altitude

of the district. Other important environmental factors affecting distribution of shrub

species were slope and grazing pressure. The plant species like Andrachne cordifolia,

Xanthium sp. and Melilotus officinalis were found in the location with high soil depth.

The plant species like Caesalpinia, Zanthoxylum and Zizyphus, which are palatable

species, were affected by grazing pressure while plant species Yucca, Nannorops and

Vitex were found more under high grazing pressure. The species richness of many of

the palatable plant species decreased due to grazing pressure while proportion of

non-palatable plant species will increase (Malik et al., 2007).

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CCA diagram for herb localities indicated that the stations like Doda Gatta (Dn12),

Torban (Dn13) andBratho (Jdbh11) were located at higher altitude of the investigated

area whereas the stations Kotkey (Ktly1), Dehri (Dri1), Shadak (Shdk1) and Zizari

were the sub tropical habitat located at lower altitude. The soil depth was maximum

at location Banda (Zzari4), Matorh (Dri4) and Haleema (Zzari5).

CCA diagram for herb species and stations showed that herb species like Ricinis

communis, Opuntia and Sisymbrium were located at lower altitude and the species Poa

alpina, Valeriana jatamansi, Viola odorata, Euphorbia wallichii, Impatiens bicolor,

Duchesnea indica, Boenninghausenia albiflora and Aquilegia sp. were found at higher

altitude in study area. These species were more closely associated and were present

in one plant community only due similar altitude. Most of these species were absent

from other plant associations. Plant species; Swertia, Salvia, Bergenia and Gernium

were found on steep slope. Euphorbia, Astragalus and Achyranthus showed positive

correlation with grazing pressure and soil erosion. These species are unpalatable or

less palatable and were present in high grazing pressure.

The change in vegetation type along altitude gradient is investigated by many

studies. It was reported in CCA results of Jiang et al., (2007) that the change in flora

along the altitudinal gradient was more than that along the north-south latitudinal

gradient. Altitude is most effective variable describing the distribution of species

indirectly, by interacting with topography, light, soil, moisture, snow period and

temperature (Korner, 1999; Holten, 1998). Normal vegetation gradients in an area are

dependent on joint impact of historic, climatic variation, human interference and

comparative species performance (Jenik, 1990).

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4.3 Life Form classification a reflection of microclimatic variation in Tor Ghar

Life form is the indicator of climate and can be used to compare plant communities.

Life form is characterized by plants to certain ecological conditions (Mera et al.,

1999). Raunkiaer (1934) proposed a system to classify plant life form based on

position and degree of protection of renewing buds.

Base on life forms, plant species reported from District Tor Ghar were grouped into

eight classes. Life form classes reflect the existing environment and are helpful in

comparing different plant communities and habitat types. Occurrence of similar life

form spectrum in different regions shows similar climatic conditions. According to

Raunkiaer (1934) the climate of a region, can be categorized by life form.

Anthropogenic disruption can change the life form of a region. Phyto-climatic

gradient and environmental indicators can help in policies related to long term

management and conservation of species and habitats (Khan et al., 2013b). The

biological spectra of flora and different plant communities in the present study

indicated that Hemicryptophytes and Therophytes were dominant in the study area.

At lower elevations high temperature, low precipitation and more anthropogenic

disturbance were reported. In Humid subtropical habitat high proportion

Phanerophytes and therophytes which are the elements of tropical region and

decreases in sub-tropical and subalpine region, reflecting climatic conditions. Life

form of a species changes with change in altitude from sea level. It reflects

adaptation of a species to different climatic conditions (Patel et al., 2010). The life

form of species in an area is always revealing plant-environment relations. Shimwell

(1971) reported that hemicryptophyte is the dominant life form of temperate zone

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and therophytes are characteristic life form of desert climate and geophytes are the

indicator of Mediterranean climate. It confirms that climate of the study area vary

from subtropical to moist temperate and subalpine at different localities. The

vegetation of study area was predominantly Western Himalaya with SinoJapanese

and Irano-Turanians elements. The biological spectrum obtained in the present

study reflects the existing environmental conditions. Similar results were obtained

by different workers. Khan et al., (2013b) investigated the phyto-climatic gradient of

the flora in Naran valley by using Detrended Correspondence Analysis (DCA) and

Canonical Correspondence Analysis (CCA). They reported that hemicryptophyte

was the dominant life form in Naran Valley followed by Phanerophytes. Similar

observations were made by Malik et al., (1994) and Malik, (2005).

4.4 Plants in the Socioeconomics of the Region

Plants are precious resource and have vast impact on ecosystem and play important

role in socioeconomic conditions of the people. It was observed that most of the

plants reported in our project provide number of ecosystem services in the

region.These include traditional uses of plants as medicine, wild vegetables and

timber wood. Such plants have been reported in various studies.WHO highlighted

the need to use herbal medicines for treatment for different ailments. The medicinal

plants exhibit significant efficacy in curing various diseases without any side

effects. Plant based medicines are more effective, harmless and low-cost (Shinwari et

al., 2015). Over 21,000 plant species are used for medicinal purposes around the

world (Sultan et al., 2013).

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Berberis lycium, Cyperus rotundus, Acacia modesta, Colchicum luteum, Ajuga bracteosa,

Cichorium intybus, Mentha longifolia, Hypericum oblongatum, Punica granatum, Ficus

carica, Podophyllum emodi, Valeriana jatamansi, Lactuca serriola, Viola canescens, Justicia

adhatoda, Skimmia laureola, Otostegia limbata, Dodonaea viscosa and Zanthoxylum

armatum are common medicinal plants found in our study area and are used by the

inhabitants for different ailments as reported by different authors from adjacent

areas (Haq et al., 2010; Qureshi et al., 2008; Hussain et al., 1996; Hamayun et al., 2003;

Adnan et al., 2015). Plant species like Acacia modesta, Acorus calamus, Amaranthus

spinosus, Chenopodium ambrosoides, Medicago sativa, Cyperus rotundus, Ficus religiosa,

Plantago ovata, Tagetes erecta, Ajuga bracteosa, Taxus wallichiana, Geranium

wallichianum, Achyranthes aspera andChenopodium ambrosoides, are frequently used by

women for treatment of their diseases. Similarly plant species such as, Dalbergia

sissoo, Adiantum capillusveneris, Melia azedarach, Datura stramonium, Valeriana

jatamansi, Sapindus mukorossi, and Vitex negundo are used for the treatment of hair fall,

anti-dandruff and antilice (Shah et al., 2013).

Punica granatum, Coriandrum sativum, Adiantum capillus-veneris, Lepidium sativum,

Foeniculum vulgare, Mentha longifoliaand and Paeonia emodi are used for number of

diseases to kill the harmful bacteria or stop their growth (Khan 2011). Important

timber yielding plants include Abies pindrow, Aesculus indica, Acacia modesta, Juglans

regia, Picea smithiana, Pinus roxburghii, Pinus wallichiana, and Taxus wallichiana (Haq et

al., 2010 & Awan et al., 2013, Hamayun et al., 2003). Taraxiacum officinale, Salvia lanata,

Oxalis corniculata, Trifolium repens, Rumex dentatus, Rumex hastatus, Caltha alba, Urtica

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dioica, Dryopteris spp.and Caralluma tuberculata are the plant species used as wild

vegetables (Khan & Khatoon 2008; Haq et al., 2010; Khan, 2012).

A large area of the district is a grass land, serving as an important source of fodder

for animals. Important palatable grass species were Brachiaria ramose, Bromus

japonica, cenchrus bifloris, Cynodon dactylon, Desmostachya bipinnata, Dichanthium

annulatum, Poa alpina (Zahid, 2007). Other palatable species are Bistorta

amplexicaulis, Bromus hordeaceus, Eragrostis cilianensis, Lathyrus pratensis, Pimpinella

acuminata, Pimpinella diversifolia, Silene vulgaris and Chenopodium album (Khan, 2012).

Berberis lycium, Rosa moschata, Viburnum grandiflorum, Zanthoxylum armatum, are the

most preferred shrubs by cattle, goat and sheep (Zahid, 2007). Many plant species

reported from the study area are poisonous to the cattle, goat and sheep. Most of the

plants are poisonous to the animals only if taken in large amount (Vallentine, 1990).

Some plants are poisonous at particular stage of growth (Huston and Pinchak, 1993).

Astragulis, Solanum, Senecio and Cynoglossum containing a poisonous alkaloid

Pyrolizadin, which toxic to live stock. Similarly other poisonous plant species are

Andrachne cordifolia, Arisaema flavum, Datura innoxia, Nerium indicum, Datura

stramonium, and Urtica dioica (Haq et al., 2010).

The important plant species reported by different authors which are used as fuel

include Indigofera heterantha, Aesculus indica, Prunus spp., Viburnum cotinifolium Pinus

wallichiana, Pinus roxbergii, Abies pindrow, Picea smithiana and Cedrus deodara (Khan,

2012). Cedrus deodara and Pinus wallichiana which are native trees of the Himalayas

and the Hindu Kush, provide the best timber woods. Species of Abies pindrow, Picea

smithiana and Populus glauca also provide good quality timber, used in ceilings,

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making doors and windows, utensils etc. Timber from species of Aesculus indica, Acer

caesium, Juglans regia and Prunus cerasoides is considered the best for agricultural

tools. Coniferous trees like Cedrus deodara, Pinus wallichiana, Abies pindrow, Picea

smithiana and Aesculus indica, have high aesthetic values for tourists as well as

inhabitants (Khan et al., 2012). Over exploitation of these plant species is major threat

to biodiversity in the area. Alam & Ali, (2010) presented the conservation status of 19

plant species and their study revealed that due to anthropogenic activities one

species is becoming extinct every day and this rate of species extinction is much

faster than that should occur naturally (Hilton-Taylor, 2000; Akeroyd, 2002). This

rate of plant extinction will result in the extinction of large number of species in near

future (Akeroyd, 2002).

4.5 Rare and Endemic Plant Species of District Tor Ghar

Rare plant species are applied to plant species which are uncommon and are

represented by small number of species in the study area. In this study IVI data or

abundance data (appendix 3) collected during field survey is used to designate

species as rare or common.

The present investigation is the first phytosociological study involving the use of

modern software to analyze the vegetation of the region. The species abundance

data and the data obtained from Indicator species analysis can be used to assess the

status of different plant species in the area. This data will be helpful to find out the

conservation status of the plant species documented from the study area. The plant

species having lower abundance and important values were used to asses the

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conservation criterian. Identification of rare species is important for local and global

biodiversity. Plants used for the treatment of different diseases, fuel wood and for

other purposes, are valuable resource of the area. This information will be helpful to

develop awareness about these species among the people of the area. Indigenous

people can play major role in conservation of biodiversity of an area (Smith, 2004).

Local conservation exercise of the inhabitants can play significant role in biodiversity

management.

In the investigated area the rare tree species were found Bombax ceiba, Butea

monosperma, Quercus incana, Alnus nitida, Cedrella serrata, Pistacia integerrima,

Diospyrus lotus, Cydonia oblonga, Grewia optiva, Moras nigra, Albezzia procera, Aesculus

indica, Sapindus mukorossi, Platanus orientalis, Taxus wallichiana, Cedrus deodara,

Quercus leucotrichophora, Bauhinia variegate, Albezzia procera, Picea smithiana, Celtis

australus, Prunus armeniaca, Grewia optiva, Morus alba and Olea ferruginea.

Among rare shrubs were Hypericum oblongifolium, Xanthoxylum armatum, Cotinus

coggyria, Viburnum, Andrachne cordifolia, Cotoneaster bacillaris, Caesalpinia decapitate,

Rosa moschata, Calotropis procera, Nerium indicum, Hedra nepalensis, Sarcococca saligna,

Withania somnifera, Jasminum humile, Cotoneaster nummularia, Viscum album,

Cotoneaster frigidus, Buxus Wallichiana, Cotinus coggyria, Andrachne cordifolia, Daphne

mucronata, Zanthoxylum armatum, Debregeasia salicifolia, Buddleja crispa and Vitex

negundo.

The rare herbs included Bergenia ciliata, Aerva sp. and Verbascum thapsus, Potentilla

nepalensis, Malva neglecta, Anagalus arvensis, Melilotus officinalis, Argyrolobium roseum,

Sisymbrium irrio, Equisetum, Polystichum lonchitis, Colchicum luteum, Arisaema

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jacquemontii, Cordiospermum helicacabum, Impatiens bicolor, Priploca, Aquilegia, Astragals

macropterus, Viola canescens, Urtica diocia, Asparagus officinalis, Carthmus oxycantha,

Chenopodium album, Crdiospermum helicacabum, Cichorium intybus, Lactuca serriola,

Malva sylvestris, Urtica pilulifera, Clematis montana, Neslia apiculata, and Plantago

lanceolata.

All these plant species having low abundance and importance values are considered

as rare species of the study area (appendix 3). The findings of present study revealed

that depence on these plants for the fuel wood, overgrazing, habitat degradation and

over exploitation for different purposes is resulting reduction in the population of

these species. Most of these plants were included in the list of globally or regionally

endangererd species by various authors in previous studies from the adjoining areas.

Aconitum heterophyllum, Colchicum luteum, Bistorta amplexicaulis, Geranium

wallichianum, Cedrus deodara, Juglans regia, Viola canescens Plantago major and

Polygonatum verticillatum are nearly threatened or vulnerable at a country level

(Khan, 2012).

The rare species documented from our study area like Taxus wallichiana, Cedrus

deodara, Poplus alba, Potentilla, Opuntia and Viscum album were reported as critically

endangered plant species from Nandiar valley, Battagram, KPK, Pakistan by Haq,

(2011). Whereas endangered flora of the area included Viola canescens, Salix spp.,

Withania somnifera, Grewia optiva, Aesculus indica, Quercus spp. Bauhinia variegate and

Podophyllum spp. They also described that these plants are used as fuel wood,

medicines and as a timber wood. In addition habitat loss, overgrazing and other

human interventions were the main causes of the reduction in the population of

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these plant species. According to Shah and Hussain, (2012) rare plant species in

Chakesar valley, district Shangla, KPK, Pakistan were Acorus calamus, Arisaema

flavum, Artemisia vulgare, Clematis grata, Euphorbia wallichii, Geranium wallichianum,

Hypericum-perforatum, Urtica dioica. Vulnerable species of the valley included Bergenia

ciliate, Aconitum spp, Gerardiana palmate, Thymus serphylum, Indigofera hetrantha,

Podophylum emodi, Rubus fruticosus, Salvia lanata, Salvia nubicola and Valeriana

jacomontii.

According to Hamayun et al., (2006) about 50% medicinal plants are threatened due

to over exploitation and inappropriate harvesting. Destruction of Himalayan forest

in past is caused by different anthropogenic activities like increased population,

agriculture, expansion in human settlements (Shaheen et al., 2011; Ahmed et al.,

2006). Sheikh et al., (2002) studied the biodiversity of Naltar Valley, Gilgit and

reported that Gentiana kurroo, Stellaria media, Geranium wallichianum and Capparis sp.

having high demand as medicinal plants lead to overexploitation. Khan, (2003)

stated that in the recent years Anthropogenic activities by way of destruction of

biota, the natural habitats have accelerated the process of extinction to an alarmingly

faster rate. Shinwari et al., (2000) conducted studies to calculate the approximate

number of endangered plants which indicated that more than 10% flora is

endangered while another 10% is threatened or vulnerable. The Himalaya

experiences the worst position where 90 percent of the natural forest habitats have

already been lost.

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Malla et al., (2015) reported that anthropogenic influence on the ecosystem like

unsystematic development works, habitat degradation, unsustainable use of

medicinal plants were the main causes of reduction of important medicinal plants.

Many plant species documented from our study area were reported as endemic to

Himalayas and Hindukush. Gentiana kurroo, Geranium wallichianum, Bergenia ciliata,

Aconitum spp, Podophylum emodi, Viola canescens, Cedrus deodara, Picea smithiana, Salvia

moorcroftiana, Bistorta amplexicaulis, Otostegia limbata, Impatiens bicolor (Khan, 2012;

Majid et al., 2015).

4.6 Threat to plant biodiversity of the study area

The present project also revealed that the people of the District Tor Ghar are

illiterate. They are unaware from the importance of biodiversity. They cut the

important plants for timber, fuel, fodder, fiber and wood. There is no influence of

forest department. Heavy deforestation can be seen at the higher altitudes of the

district especially in the Machasar, Manasar, Ganther and Shangaldar area, where

immature and large sized cut stem can be seen which are being destroyed ruthlessly

by the inhabitants. In these areas the forests of Picea smithiana, Pinus wallichiana,

Quercus incana, Quercus dilatata, Cedrus deodara and Abies pindrow are being destroyed

at large scale. It is great threat to biodiversity. There is no alternative fuel and

people are heavily depending on these species for fuel wood. These species are used

for construction, timber and formation of agriculture tools.

Overgrazing is another important threat to biodiversity. The heavily grazed

community results in the change in the species diversity. It was investigated that

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protection of grazing had increased biodiversity and biomass in Kanak valley

Baluchistan (Mori & Rehman, 1997). Palatability of a plant species and preference for

grazing by a particular animal is dependent on certain characteristics such as

external plant form, chemical composition, kind of plant and growth stage of a plant

(Heady, 1964). Traditional grazing without any management practices is seen in

many parts of the study area. Overgrazing not only causes soil destruction but also

remove palatable species resulting soil erosion, this is seen at various places in the

investigated area. eg. Severe grazing effect and vegetation degradation is recorded in

the Dadem, Kotley, Sarbago, Tor kando, Toot banda, Arnil, Gut hill, Shatal, Chor

Kalan, Chota Kando, Doda Gata and Torban (appendix 4). Vegetation of these sites is

destroyed and soils of these locations were eroded by soil erosion. These sites show

low species diversity. Most of the locations are considered as degraded habitate of

the district. At the higher altitude of the study area like Torban (Machasar), Kando

gali, Chota kando and Chorkalan area seasonal nomads with large number of cattle’s

also stay. Large number of livestocks results in the overgrazing of natural

vegetation.

Soil erosion is also one of the threats to plant biodiversity. Degradation of land by

soil erosion not only decreases production capacity but also reduces the number of

palatable species. In degraded habitats only few plant species can survive and

complete their life cycle whereas, those species, which need better habitat in term of

soil, light, moisture and shade are generally eliminated. In our study area at higher

altitude the stations like Arekh1 and Arekh2 are located at steep slopes and the

stations: Manasar, Chota Kondo, Doda Gata, Machasar, Chor Kalan, Sargae, Toot

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Banda and Dar Bani are representing moderate slopes. Due to steep slope soil

erosion habitat degradation was observed at these locations (Appendix 4). In newly

created district, developmental works like construction of roads and infrastructure is

in progress, which is another important cause of soil erosion in the area. Study site is

the catchment area of one of the largest water reservoir of the country (Tarbella

dam). Its storage capacity is rapidly reducing due to heavy siltation caused by soil

erosion. It is also major threat to biodiversity and agricultural land of the area. Haq

et al., (2011) conducted field survey in Nandiar valley District Battagram, KPK,

Western Himalaya and reported similar observations. They observed that major

threat to the biodiversity in the area was unawareness of local communities,

deforestation, population expansion, overgrazing, urbanization, deforestation,

habitat destruction and unsustainable use of natural vegetation.

4.7 Limitations of the present research project

The study area has never been surveyed in history because it is one of the farflung

and backward area of the Pakistani Himalaya region consisting of steep slope and in

accessable sites. The present study explored in detail the biodiversity and

phytosociology of the area. The research study was well planned to achieve almost

all aims and objectives. However it is not possible to achieve 100% perfection

especially in survey based studies in such remote, inaccessible area with strong tribal

cultural constraints which do not allow frequent visits of some localities.

I think few plant species might have been missed which were present at steep slopes

or at inaccessable sites. Due to accessability and transportation problem complete

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soil analysis could not be done. A few plant species with short growing season may

have not been reported during the survey. The study provides information about the

important plant species used in different ecosystem survices and species abundance

but detailed study is needed. However, the study with a few limitations is first ever

attempt of exploration of a hard and tough western Himalayan region, which opens

the way for future researches.

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CONCLUSIONS

Exploration of District Tor Ghar results in the documentation of 331 plant species

from 960 quadrats and 64 stations. District Tor Ghar represented rich plant

biodiversity. The study showed that the area is blessed with diverse ecological

habitat and inhabit high floral diversity. Our findings clearly show that vegetation of

the region is representative of humid subtropical and Subtropical Chir Pine Forest

type in lower region of district which gradually changes to Moist temperate and sub

alpine type of habitats at higher elevation. Hosting high number of vascular plants

species (331) is evidence of rich diversity of the region though most of the region

exhibit harsh climate. Most of reported plants are important from ecosystem services

point of view such as medicinal plants, wild vegetables and timber plants. This

study also provides first ever phytosociological classification based on robust

multivariate classification and ordination procedure via Canoco and PCORD

softwares. Six plant communites were reported in 3 vegetation zones i.e. Humid sub-

tropical, Sub tropical Chir pine and Moist temperate and sub alpine. Finding of this

project confirmed elevation from sea level, slope and soil depth as significant

environmental variables responsible for distribution of plant species. As for as

preservation of the natural plants and habitats are concerned, it was observed that

people of the area were mostly illiterate and were not aware of the biodiversity loss

and its impact on human life. They are using natural resources ruthlessly that

resulting disappearance of certain plants and habitats from the region. The study

also revealed that area is suitable for rangeland as grasses are dominant in the

region, which are mostly palatable. The study furnishes baseline data and useful

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information to protect local flora for the future generation. The findings of the study

will be useful to rangeland managers, ecologist, medicinal plant growers, foresters,

collectors and conservationists to improve the bioresource base and socioeconomic

conditions of the people of the area under investigation.

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RECOMMENDATIONS

Based on the finding of the present study following recommendations were made.

Law enforcement is essential to protect floristic diversity which is the treasure

of nature and in this regard proper legislation should be made for the

protection of threatened species.

Compilation of complete flora is essential.

Extensive reforestation in the study area is urgently needed

To launch awareness campaign among locals to stop over exploitation and

protect plant resources.

The higher altitudes dominated by moist temperate forests inhabiting

threatened species should be given the status of a protected area.

Proper rangeland management in the region can improve the socioeconomic

condition of the inhabitants.

The documentation and preservation of indigenous knowledge is needed for

conservation and sustainable utilization of plant resources.

Plant bio-resources of the area also need proper in-situ conservation measures.

Eco-tourism should be established which will be the good source of income for

the inhabitants.

Application of remote sensing is needed.