Vegetation mapping and multivariate approach to indicator species of a forest ecosystem a case study from the thandiani sub forests division (ts fd) in the western himalayas

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Ecological Indicators 71 (2016) 336–351

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Ecological Indicators

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egetation mapping and multivariate approach to indicator species of forest ecosystem: A case study from the Thandiani sub Forestsivision (TsFD) in the Western Himalayas

aqas Khan a, Shujaul Mulk Khan b,∗, Habib Ahmad c, Zeeshan Ahmad b, Sue Page d

Department of Botany, Hazara University, Mansehra, PakistanDepartment of Plant Sciences, Quaid-i-Azam University, Islamabad, PakistanDepartment of Genetics, Hazara University, Mansehra, PakistanDepartment of Geography, University of Leicester, UK

r t i c l e i n f o

rticle history:eceived 25 April 2016eceived in revised form 23 June 2016ccepted 29 June 2016

eywords:luster analysis

ndicator species analysislant communitypecies compositionwo way cluster analysisegetation mappinghandiani sub Forests Division (TsFD)

a b s t r a c t

Questions: Does the plant species composition of Thandiani sub Forests Division (TsFD) correlate withedaphic, topographic and climatic variables? Is it possible to identify different plant communities inrelation to environmental gradients with special emphasis on indicator species? Can this approach tovegetation classification support conservation planning?Location: Thandiani sub Forests Division, Western Himalayas.Methods: Quantitative and qualitative characteristics of species along with environmental variables weremeasured using a randomly stratified design to identify the major plant communities and indicatorspecies of the Thandiani sub Forests Division. Species composition was recorded in 10 × 2.5 × 2 and0.5 × 0.5 m square plots for trees, shrubs and herbs, respectively. GPS, edaphic and topographic data werealso recorded for each sample plot. A total of 1500 quadrats were established in 50 sampling stations alongeight altitudinal transects encompassing eastern, western, northern and southern aspects (slopes). Thealtitudinal range of the study area was 1290 m to 2626 m above sea level using. The relationships betweenspecies composition and environmental variables were analyzed using Two Way Cluster Analysis (TWCA)and Indicator Species Analysis (ISA) via PCORD version 5.Results: A total of 252 plant species belonging to 97 families were identified. TWCA and ISA recognizedfive plant communities. ISA additionally revealed that mountain slope aspect, soil pH and soil electricalconductivity were the strongest environmental factors (p ≤ 0.05) determining plant community compo-sition and indicator species in each habitat. The results also show the strength of the environment-speciesrelationship using Monte Carlo procedures.
Conclusions: An analysis of vegetation along an environmental gradient in the Thandiani sub ForestsDivision using the Braun-Blanquet approach confirmed by robust tools of multivariate statistics identifiedindicators of each sort of microclimatic zones/vegetation communities which could further be used inconservation planning and management not only in the area studied but in the adjacent regions exhibitsimilar sort of environmental conditions.
© 2016 Elsevier Ltd. All rights reserved.

. Introduction

Across a range of different scales, vegetation structure is
ontrolled by environmental gradients (Leonard-Barton, 1988).iscovering and understanding the association between the bioticnd environmental components of an ecosystem and particularly
∗ Corresponding author.E-mail addresses: [email protected], [email protected],

[email protected] (S.M. Khan).

ttp://dx.doi.org/10.1016/j.ecolind.2016.06.059470-160X/© 2016 Elsevier Ltd. All rights reserved.

the variation in species diversity and abundance along envi-ronmental gradients, are critical branches of ecological research(Daubenmire, 1968; Grytnes and Vetaas, 2002; Tavili and Jafari,2009). For example, the effect of soil pH on the species composi-tion and richness of plant communities is a well-known ecologicalphenomenon (Ellenberg 1988 Moldan et al., 2012; Haberl et al.,2012; Ullah et al., 2015), while in mountainous regions, aspect and
altitude show the greatest effects in limiting plant species and com-munity types (Chawla et al., 2008; Khan and Ahmad, 2015). In termsof identifying the effects of environmental gradients on vegetation,
dx.doi.org/10.1016/j.ecolind.2016.06.059

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W. Khan et al. / Ecologica

he use of computer-based statistical and multivariate analyticalrograms can help ecologists to discover structure in vegetationata sets and enable them to analyze the effects of environmen-al gradients on whole groups of species in a more efficient wayMassberg et al., 2002; Hair et al., 2006). Statistical programs reducehe complexity of data by classifying vegetation data and relat-ng it to environmental components (Dufrêne and Legendre, 1997;

cCune and Mefford, 1999 Khan et al., 2011a,b Haq et al., 2015;hahouki et al., 2010). Classification also overcomes problems ofomprehension by summarizing field data in a low-dimensionalpace by bringing species with similar requirements together inarious groups (Khan et al., 2013a,b). Such approaches have, how-ver, rarely been used in vegetation studies in Pakistan (Malik andalik 2004; Malik and Husain, 2006; Saima et al., 2009; Wazir

t al., 2008; Malik and Husain, 2008 Khan et al., 2011a,b). Eco-ogical groups can be defined on the basis of indicator values forifferent environmental gradients like light, moisture, soil reac-ion and nitrogen content (Anderson et al., 1992). In addition, theccurrence of certain associated vascular plant species may indi-ate vegetation history, illustrated, for example, by those speciesermed “ancient woodland indicator plants” that are recognized ashe species elements denoting continuity of woodland cover in thenited Kingdom (Glaves et al., 2009). Species can be grouped on theasis of their indicator values and the nature of the assemblage;uch assemblages are usually a mixture of eurytopic (wide eco-ogical tolerance) and stenotopic (restricted ecological tolerance)pecies (Kremen et al., 1993; Shah et al., 2015). In support of thispproach, a large data set on the distribution of species in openabitats in Belgium was used as a case study to illustrate the utilityf a new method of identifying species assemblages and indica-or species (Dufrêne and Legendre, 1997), which may be useful forlanning of regional conservation priorities.

The aim of this study is to achieve an empirical model of vege-ation using plant species combinations to characterize vegetationypes in the study area (Weber et al., 2000). Most of the West-rn Himalayan Forests, such as those in the Thandiani sub Forestsivision (TsFD) area, have not been investigated using recentlyeveloped analytical methods for vegetation characterization. Inart this is because these forests are located in remote areas withoor access, uneven terrain and adverse geopolitics. But, in addi-ion, previous accounts of montane vegetation in this region haveended to be descriptive with a lack of quantitative approaches,ncluding computer-based vegetation data analysis. This study wasesigned, therefore, to quantify the abundance of plant species,nalyze and define the communities and place them in an ecologicalnd vegetation framework in order to better understand indicatorroups for different microclimatic conditions within this moun-ainous region. The specific research objectives were to explore thenfluence of aspect, elevation and soil chemistry on the vegetationssemblages of TsFD and to identify indicator species for each habi-at using multivariate statistical analyses. The study contributeso wider efforts to systematically describe the plant communi-ies of the mountainous regions of north-western Pakistan using

phytosociological approach supported by robust statistical anal-ses (Khan et al., 2011a,b) which will form the basis for strategiconservation planning.

. Study area

The “Thandiani sub Forests Division” (TsFD) encompasses thealis Forest Division of Abbottabad, the east Siran Forests Division,

he north Muzaffarabad & Garhi Habibullah in the south Abbottabadub forests division and the east Berangali forests range, between329◦ to 3421◦ North latitude and 7255◦ to 7329◦ East longitudeFig. 1).

ators 71 (2016) 336–351 337

The TsFD covers an area of 24987 ha in which 2484 ha are clas-sified as Reserve Forests and 947 ha as Guzara Forests (Khan et al.,2012a,b). The whole area is protected under the Guzara ForestsDivision of the Khyber Pakhtunkhwa government in order to pre-serve the valuable flora and fauna of the area. The highest point isThandiani top (Sikher) having an elevation of 2626 m. The dominantvegetation cover is pine forest which may be divided into three ele-vation ranges namely upper range (2200–2600 m), medium range(1700 m–2200 m) and lower range (1200 m–1700 m). This studywas designed to record species composition pattern, quantify theabundance of plant species across this elevation range and to estab-lish the plant communities based on robust statistical approachesin order to understand the environmental factors responsible fordetermining the distribution of both species and communities withspecial focus on indicator species. The research hypothesis was thataltitude, aspect, soil electrical conductivity and soil pH all have asignificant impact on species and community diversity of vascularplants in the TsFD of the western Himalayas, Pakistan.

3. Materials and methods

In order to test the hypothesis, a phytosociological approach(Rieley and Page, 1990; Kent and Coker, 1994 Khan et al., 2011a,b)was used to record quantitative and qualitative attributes of vas-cular plants in quadrats along edaphic, topographic and climaticgradients during the summer months of 2012 and 2013. The studyarea was divided into eight altitudinal transects covering a range of1290–2626 m, along each of transects, sampling commenced fromthe lowest elevation (forest bottom) and continued to the mountainsummit. Data collection stations were established at 100 m inter-vals (total of 50 stations) along each transect with the help of aGPS. At each station, 30 quadrats were enumerated: 5 for record-ing trees, 10 for shrubs and 15 for herbs, each having an area of10 × 2.5 × 2 and 0.5 × 0.5 m square, respectively. The quadrats werepositioned randomly at each station (Cox 1985; Malik 1990 Khanet al., 2013a,b). Species composition and abundance in each quadratwere recorded onto Excel data sheets. Absolute and relative density,cover and frequency of each vascular plant species at each stationwere subsequently calculated through the formulae designed byCurtis and McIntosh (1950) using Microsoft Excel on an Asus palm-top computer. The plant specimens were mostly identified withthe help of the Flora of Pakistan (Nasir and Ali, 1970 Nasir andAli, 1970–1989; Khan et al., 2014; Ali and Qaiser, 1993–2009) andpreserved in the Herbarium of Hazara University Pakistan (HUP).Altitude was measured by GPS and slope aspect i.e., East (E), West(W), South (S) and North (N), was determined with the help of adigital compass. The soil was collected from each site up to a depthof 15 cm and thoroughly mixed to make a composite sample. Thesoil samples were kept in polythene bags and labeled appropriatelyprior to analysis for a range of physical and chemical characteristics.Particle-size analysis was determined following the destruction ordispersion of soil aggregates into discrete units by mechanical orchemical means, and then the separation of the soil particles bysieving or sedimentation methods (Gee et al., 1986). Chemical dis-persion was accomplished by first removing cementing substances,such as organic matter and iron oxides, and then replacing calciumand magnesium ions (which tend to bind soil particles togetherinto aggregates) with sodium ions (which surround each soil parti-cle with a film of hydrated ions). The calcium and magnesium ionswere removed from solution by complexion with oxalate or hexa-metaphosphate (Calgon) anions (Baver et al., 1972; Sheldrick and
Wang 1993; Monteith et al., 2014). Soil texture was determined bythe hydrometer method (Sarir et al., 2006; Bergeron et al., 2013;the texture class was determined with the help of a textural trian-gle (Adamu and Aliyu, 2012). For determination of pH, soil samples

338 W. Khan et al. / Ecological Indicators 71 (2016) 336–351

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ere mixed with an equal volume of deionized water, allowed toquilibrate for at least an hour, and then the electrode of the pHeter was immersed into the soil suspension and a reading was

irectly recorded (Jackson, 1963). Electrical conductivity (EC) of soil extract was used to estimate the level of soluble salts. Thetandard method is to saturate the soil sample with water, vacuumlter to separate water from soil, and then measure EC of the satu-ated paste extract (Hussain et al., 1999a,b; Jackson, 1963; Wilsonnd Bayley, 2012). The soluble P was extracted from N mineral-zation samples with hydrochloric-ammonium fluoride solution,nd determined calorimetrically (Kitayama and Aiba, 2002). Therganic matter was determined using the Walkley and Black’s titra-ion method (Jackson, 1963; Hussain et al., 1999a,b).

rganic Matter% = S − TS

× 6.7

here S = Blank reading, T = Volume used of FeSO4.

. Data analysis

Vegetation and environmental data sets were processed in MSxcel in accordance with the PCORD V.5 requirements. The dataollected from the 50 sampling stations (1500 quadrats) revealedhe presence of 252 plant species. These species data along withnformation on the six environmental variables (namely, altitude,spect, soil organic matter, soil pH, soil electrical conductivity, soilhosphorous content and soil texture) were analyzed using PC-RD version 5 (McCune and Mefford, 1999). The Cluster Analysis

CA) and the Two Way Cluster Analyses (TWCA) identified signifi-ant habitat and plant community types using Sorensen measures,ased on presence/absence data (Greig-Smith, 1983) and were car-ied out to identify pattern similarity in the species and station data.ndicator Species Analysis (ISA) was subsequently used to link theoristic composition and abundance data with the environmen-al variables. This combined information provided knowledge of
he concentration of species abundance in a particular group andhe faithfulness (fidelity) of occurrence of a species in that group.ndicator values for each species in each group were obtained andested for statistical significance using the Monte Carlo test. Indi-
with reference to the Western Himalayas of Pakistan.

cator Species Analysis evaluated each species for the strength of itsresponse to the environmental variables, from the environmentalmatrix (50 stations × 7 environmental gradients). A threshold levelof indicator value of 30% with 95% significance (p value ≤ 0.05) waschosen as the cut off for identifying indicator species (Dufrene andLegendre, 1997; Ter Braak and Prentice 1988) and the identifiedindicator species were used for naming the communities.

5. Results

In total, 252 plant species belonging to 97 families were iden-tified, comprising 51 trees, 48 shrubs and 153 herbs. Cluster andTwo Way Cluster Analyses broadly divided the plant species into 5habitat types/communities which could be clearly seen in two mainbranches of the dendrogram; (i) a lower altitude (1290 m–1900 m)cluster including 3 communities/habitat types dominated by sub-tropical vegetation and (ii) a higher altitude (1900 m–2626 m)cluster including 2 communities/habitat types dominated by moisttemperate elements (Figs. 3 and 4 ).

Indicator Species Analysis (ISA) identified indicator species foreach habitat type under the influence of variables responsiblefor those communities. The ISA results show that aspect, soilpH and soil electrical conductivity have the strongest influenceon species occurrence. The results also show the strength of theenvironment-species relationship using Monte Carlo procedures.The five plant communities/habitat types established in TsFD aredescribed below, along with respective environmental variables.

5.1. Melia azedarach, Punica granatum and Euphorbiahelioscopia community

This community occurred at 12 stations (360 quadrats/releves)at the lowest elevations (1299–1591 m asl). The tree, shrub andherb layers were characterized by Melia azedarach, Punica granatumand Euphorbia helioscopia respectively, which are the top diagnostic
(indicator) species (Table 1). Other indicator species of this commu-nity are Ziziphus vulgaris Lam. Euclaptus globulus, Rosa moschata,Zanthoxylum alatum, Cnicus argyracanthus, Medicago denticulata,Poa annua, Themeda anathera, Rumex hastatus, Taraxacum officinale

W. Khan et al. / Ecological Indicators 71 (2016) 336–351 339

Fig. 2. Cluster Dendrogram of 50 stations based on Sorensen measures showing 5 plant communities/habitat types (For more details see Table 8).

Table 1The indicator species of the Melia azedarach, Punica granatum and Euphorbia helio-scopia Community with their indicator values.

Top indicator of the community IV P* IVI TIVI

Melia azedarach L. 85.7 0.0406 36.53 61.11Punica granatum L. 58.9 0.0008 80.1 69.5Euphorbia helioscopia L. 40.3 0.0222 103.98 72.14

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Table 2The indicator species of the Ziziphus vulgaris, Zanthoxylum alatum and Rumexnepalensis Community with their indicator values.

Top Indicator of the community IV P* IVI TIVI

Ziziphus vulgaris Lam. 40.4 0.0126 43.4 41.9Zanthoxylum alatum Roxb. 60.9 0.0006 63.26 62.08Rumex nepalensis Spreng. 52.2 0.0188 97.52 74.86

V = Indicator Value, P = Probability, IVI = Importance Value Index in the community.IVI = Total Importance Value Index (Average Importance Value).

nd Cynodon dactylon (Figs. 2–4 and Tables 7 and 8). The mostmportant environmental variables determining the gradient of thisommunity were low electrical conductivity (0.26–1.03dsm−1), lowoil organic matter content (0.5%–1.24%) and low soil pH (4.8–5.5),oupled with associated co-variables of aspect (W-S), soil phospho-ous content (5–8 ppm) and soil texture (silty loam) (Figs. 2–4 andables 6–7).

Being located at lower elevations this community occurs in theicinity of human settlement and is therefore under pressure from

range of anthropogenic activities, i.e., deforestation for fuel woodnd timber, expansion of agricultural land, grazing and multipur-ose plant collection.

.2. Ziziphus vulgaris, Zanthoxylum alatum and Rumexepalensis community

This community was found at the altitudinal range of600–1900 m asl and was represented by 16 different stations (480uadrats). The tree, shrub and herb layers are characterized by the

ndicator species Ziziphus vulgaris, Zanthoxylum alatum and Rumexepalensis (Table 2).

Other indicator species of this community are Abies pindrow,unica granatum, Rosa moschata, Rubus fruticosus, Achillea mille-olium, Cnicus argyracanthus, Poa annua, Rumex hastatus, Nepetarecta, Taraxacum officinale, Medicago denticulata, Senecio chrysan-

IV = Indicator value, P = Probability, IVI = Importance value Index.TIVI = Total Importance Value Index (Average Importance Value).

themoides, Cynodon dactylon, Chenopodium album and Capsellabursa pastoris (Figs. 2–4 and Tables 7 and 8). North-West aspect wasone of the main environmental determinants of this communityindicating that this community receives comparatively less directsunlight. Other strong environmental variables were low soil pH(4.9–6.6) and only trace amounts of organic matter (0.5%–1.24%)coupled with low soil electrical conductivity (0.24–0.62dsm−1),sandy loam and clay loam soil textures (Figs. 2–4 Tables 6–8).

5.3. Quercus incana, Cornus macrophylla and Viola bifloraplant community

This community occurs at mid-altitude elevations(1900–2150 m asl) and was present at 11 stations and 330quadrats (Table 3). In addition to the three main indicator species,the additional characteristic species of this community are Abiespindrow, Viburnum grandiflorum, Chrysanthemums cinerariifolium,Euphorbia wallichii, Plantago lanceolata, Actaea spicata, Nepetaerecta, Rumex nepalensis, Viola biflora and Achillea millefolium(Figs. 2–4 and Tables 7 and 8). This community shows its bestdevelopment on south-east facing slopes where it is exposed to
direct solar radiation. Other strong influencing factors were highersoil phosphorous content (5–7 ppm), moderate soil organic matter(0.6%–1.18%), a weakly acidic soil pH (4.0), low soil electrical con-


Fig. 3. GIS map showing the 3D-DEM View (SRTM) of project area—Thandiani sub forests division with sampling localities (GIS based, stations distribution), graph andelevation profile for the stations of all altitudinal transacts.

Table 3The indicator species of the Quercus incana, Cornus macrophylla and Viola bifloraCommunity With their indicator values.


Quercus incana Roxb. 42.7 0.018 36.78 39.74Cornus macrophylla Wall. Ex Roxb. 48.6 0.021 41.38 44.99Viola biflora L. 54.4 0.008 47.17 50.79

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Table 4The indicator species of the Cedrus deodara, Viburnum grandiflorum and Achilleamillefolium Community with their indicator values.


Cedrus deodara Rox ex Lamb. 34.5 0.0574 88.2 61.35Viburnum grandiflorum Wallich. 49.9 0.0016 31.44 40.67Achillea millefolium L. 47.2 0.019 47.43 47.315

IV = Indicator Value, P = Probability, IVI = Importance Value Index.TIVI = Total Importance Value Index (Average Importance Value).

V = Indicator value, P = Probability, IVI = Importance Value Index.IVI = Total Importance Value Index (Average Importance Value).

uctivity (0.2–0.62dsm−1) and a sandy loam soil texture (Figs. 2–4nd Tables 6–8).

.4. Cedrus deodara, Viburnum grandiflorum and Achilleaillefolium community

This community can be found at relatively high elevations
2150–2400 m asl) occurring at six stations (180 quadrats). This is
tree-dominated community comprising of moist temperate veg-tation including the principal indicator species Cedrus deodara,iburnum grandiflorum and Achillea millefolium from the tree, shrub

and herb layers, respectively (Table 4). Abies pindrow was the othernotable indicator tree found in this community. The most importantenvironmental variables responsible for the formation of this com-munity are mildly acidic soil pH (6.3–6.8), high soil organic matter(1.07%–1.25%), low soil electrical conductivity (0.26–0.73dsm−1),moderate soil phosphorous contents (5–6 ppm) and a sandy loamsoil texture (Figs. 2–4 and Tables 6–8).

The main anthropogenic pressure observed on this communitywas the collection of medicinal and fodder plants.


Fig. 4. Two Way Cluster Dendrogram generated through PC-ORD Version 5 based on Sorecommunities (associations).

Table 5The indicator species of the Abies pindrow, Daphne mucronata and Potentilla fruticosaCommunity with their indicator values.


Abies pindrow Royle. 40.5 0.007 179.18 109.84Daphne mucronata Royle. 75 0.0002 31.43 53.215Potentilla fruticosa L. 44.4 0.0102 89.27 66.835

IV = Indicator Value, P = Probability, IVI = Importance Value Index.TIVI = Total Importance Value Index (Average Importance Value).

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tainous ecosystems (Anderson et al., 1992; Ahmad et al., 2015).Moreover an increase in herbaceous vegetation is positively cor-related to increase in elevation which seems to be a function of

.5. Abies pindrow, Daphne mucronata and Potentillaruticosa plant community

This was the highest elevation community described in TsFD atltitudes of 2400–2626 m asl. It was described from five stations150 quadrats). Abies pindrow, Daphne mucronata and Potentillaruticosa are the characteristic indicator species of this commu-ity (Table 5). Other diagnostic indicator species are Berberisrthobotrys, Viburnum grandiflorum, Rumex nepalensis, Drypterispp., Euphorbia wallichii, Plantago major and Pteris vittata (Figs. 2–4nd Tables 7 and 8). Due to the high altitude, low temperaturesrevail throughout the growing season. The important environ-ental variables were soil pH (6.6–7.2), soil phosphorous content

6–8 ppm), soil electrical conductivity (0.2–0.39dsm−1) and soilrganic matter (0.55%–0.75%).

This high altitude plant community has low species richness ( ´iversity) with fewer plant species in comparison with the other

our communities. The near neutral soil pH in the range 6.6–7.0 wasne of most important environmental variables for this community.ther associated variables were slightly higher soil phosphorous
ontents, lower soil organic matter, lower soil electrical conductiv-ty and sand dominated soil (Figs. 2–4 and Tables 6–8 ).
nsen measures, showing distribution of 252 plant species in 50 stations and 5 plant

6. Discussion

The multivariate analyses carried out as part of this study estab-lished five distinct plant communities in the TsFD study area. Beinglocated in the Western Himalayan Province, the vegetation wasmainly Sino-Japanese in nature and the communities were clas-sified on the basis of environmental factors/gradients i.e., soil pH,soil organic matter, soil phosphorous contents, soil texture, aspect,altitude and soil electrical conductivity. This allows our results tobe compared with the studies already undertaken in other adja-cent locations in the Sino Japanese Region (Takhtadzhian, 1997; Aliand Qaiser 1986; Champion et al., 1965 Khan et al., 2011a,b, 2014;Mehmood et al., 2015; Shaheen et al., 2015). At lower elevationranges the vegetation was of a sub-tropical nature with indica-tor species including Dodonea viscosa, Punica granatum, Berberislyceum and Pinus roxburghii. A similar community was described bySiddiqui et al. (2009) during a phytosociological survey of the lesserHimalayan and Hindu Kush ranges of Pakistan. At upper altitudi-nal ranges, the vegetation contains characteristic species of moisttemperate types of forests, e.g., Pinus wallichiana, Abies pindrow,Aesculus indica, Prunus padus, Indigofira heterantha, Viburnum gran-diflorum, Paeonia emodi, Bistorta amplexicaule, Euphorbia wallichiiand Trifolium repens; which could be compared with the assem-blage reported in the moist temperate Himalaya by Saima et al.,2009 and Ahmed et al., (2006). Species diversity reached an opti-mum at middle elevations (1700 m–2200 m), as compared to thelower locations where there was greater impact of anthropogenicactivities, while at high elevations (2200 m–2626 m) diversity waslowest mainly due to extreme conditions. Such kinds of speciesdistributional phenomena have also been observed in other moun-

eco-physiological processes associated with these higher eleva-


Table 6Influence of various environmental variables on top indicator species of each community.

1st CommunitySNO BN (IV) P* I.V.I-1 T.I.V.IAspect1 Ziziphus vulgaris Lam. 40.4 0.0126 40.66 40.532 Cnicus argyracanthus (DC) Hk.f. 35.5 0.0488 71.49 53.503 Euphorbia helioscopia L. 40.3 0.0222 103.98 72.144 Poa annua L. 43.3 0.014 91.00 67.15Soil Electrical Conductivity1 Melia azedarach L. 85.7 0.0406 36.53 61.112 Themeda anathera (Ness) Hack. 85.7 0.0358 114.72 100.21Soil organic matter Content1 Punica granatum L. 38.7 0.039 80.11 59.402 Rumex nepalensis Spreng. 52.2 0.0188 125.71 88.96Soil Phosphorous1 Cnicus argyracanthus (DC) Hk.f. 34.6 0.0324 71.49 53.052 Taraxacum officinale Weber. 39 0.047 127.33 83.16Soil pH1 Euclaptus globulus L. 51.3 0.006 44.41 47.852 Punica granatum L. 58.9 0.0008 80.11 69.503 Rosa moschata non J. Herrm. 53 0.001 51.86 52.434 Zanthoxylum alatum Roxb. 60.9 0.0006 33.29 47.095 Capsella bursa pastoris Moench. 54.7 0.017 48.63 51.666 Cynodon dactylon L. 60.8 0.0008 115.76 88.287 Euphorbia helioscopia L. 50.2 0.0316 103.98 77.098 Medicago denticulata Willd. 55.8 0.0006 92.86 74.339 Poa annua L. 54.1 0.0158 91.00 72.5510 Rumex hastatus D.Don. 48.6 0.0348 73.75 61.172nd CommunityAspect1 Ziziphus vulgaris Lam. 40.4 0.0126 43.4 41.92 Chenopodium album L. 37.9 0.0328 82.08 59.993 Cnicus argyracanthus (DC) Hk.f. 35.5 0.0488 62.66 49.084 Poa annua L. 43.3 0.014 47.63 45.465Soil Electrical Conductivity1 Themeda anathera (Ness) Hack. 85.7 0.0358 36.5 61.1Soil Organic matter contents1 Punica granatum L. 38.7 0.039 54.04 46.372 Rumex nepalensis Spreng. 52.2 0.0188 97.52 74.86Soil Phosphorous1 Cnicus argyracanthus (DC) Hk.f. 34.6 0.0324 62.66 48.632 Taraxacum officinale Weber. 39 0.047 83.28 61.14Soil pH1 Abies pindrow Royle. 40.5 0.007 98.94 69.722 Punica granatum L. 58.9 0.0008 54.04 56.473 Rosa moschata non J. Herrm. 53 0.001 56.38 54.694 Rubus fruticosus Hk.f. 41.9 0.0364 42.54 42.225 Zanthoxylum alatum Roxb. 60.9 0.0006 63.26 62.086 Achillea millefolium L. 47.2 0.019 58.45 52.8257 Capsella bursa pastoris Moench. 54.7 0.017 56.95 55.8258 Cynodon dactylon L. 60.8 0.0008 55.92 58.369 Medicago denticulata Willd. 55.8 0.0006 83.36 69.5810 Poa annua L. 54.1 0.0158 47.63 50.86511 Rumex hastatus D.Don. 48.6 0.0348 81.3 64.95Soil texture1 Achillea millefolium L. 44.9 0.0276 58.45 51.6752 Nepeta erecta Bh Bth. 45.4 0.0196 68.16 56.783 Senecio chrysenthemoides DC. 36.8 0.0428 50.25 43.5253rd CommunityAspect1 Quercus incana Roxb. 35 0.0306 36.79 35.89Soil organic matter contents1 Rumex nepalensis Spreng. 52.2 0.0188 40.41 46.31Soil phosphorous1 Quercus incana Roxb. 37.3 0.0392 36.79 37.04Soil pH1 Abies pindrow Royle. 40.5 0.007 133.84 87.172 Cornus macrophylla Wall. Ex Roxb. 48.6 0.021 41.38 44.993 Viburnum grandiflorum Wallich. 49.9 0.0016 52.64 51.274 Achillea millefolium L. 47.2 0.019 92.76 69.985 Actaea spicata L. 42.9 0.0362 46.94 44.926 Chrysanthimum cenarifolium Trey 60.9 0.0044 35.00 47.957 Euphorbia wallichii Hk.f. 58.3 0.0006 89.31 73.808 Plantago lanceolata Linn. 44.2 0.0186 36.74 40.479 Viola biflora L. 42.9 0.0384 47.17 45.04


Table 6 (Continued)

Soil texture1 Quercus incana Roxb. 42.7 0.018 36.79 39.742 Viburnum grandiflorum Wallich. 44.1 0.0288 52.64 48.373 Achillea millefolium L. 44.9 0.0276 92.76 68.834 Actaea spicata L. 54.4 0.0078 46.94 50.675 Nepeta erecta Bh Bth. 45.4 0.0196 38.40 41.906 Plantago lanceolata Linn. 54.4 0.0082 36.74 45.577 Viola biflora L. 54.4 0.008 47.17 50.794th CommunitySoil pH1 Abies pindrow Royle. 40.5 0.007 66.64 53.572 Viburnum grandiflorum Wallich. 49.9 0.0016 31.44 40.673 Achillea millefolium L. 47.2 0.019 47.44 47.324 Cedrus deodara Rox ex Lamb. 34.5 0.0574 88.20 61.35Soil texture1 Viburnum grandiflorum Wallich. 44.1 0.0288 31.44 37.772 Achillea millefolium L. 44.9 0.0276 47.44 46.175th CommunitySoil organic matter contents1 Rumex nepalensis Spreng. 52.2 0.0188 61.95 57.07Soil phosphorous1 Drypteris spp. 43.5 0.0184 40.70 42.10Soil pH1 Abies pindrow Royle. 40.5 0.007 179.19 109.842 Acacia arabica (Lam.) Willd. 29 0.0352 89.07 59.033 Berberis orthobotyrus Bien. Ex Aitch. 69.5 0.0016 33.83 51.674 Daphne mucronata Royle. 75 0.0002 31.44 53.225 Viburnum grandiflorum Wallich. 49.9 0.0016 30.60 40.256 Drypteris spp. 69.7 0.0012 40.70 55.207 Euphorbia wallichii Hk.f. 58.3 0.0006 36.05 47.188 Plantago major L. 38.7 0.0308 42.10 40.409 Potentilla fruticosa L. 44.4 0.0102 89.28 66.84

2

4.1

tegutg

ptotetpdceiacttVesodch

vVsc

10 Pteris vittata L. 7Soil texture1 Viburnum grandiflorum Wallich. 4

ions. The findings of this study clearly indicate that the lowerlevational ranges exhibit sub-tropical floristic elements whichradually change on the one hand to moist temperate types in thepper ranges, i.e. along the latitudinal gradient, and to subalpineypes near the peaks of the mountains in response to the altitudinalradient.

The methods applied in this study allow users to compare multi-le classification procedures of the same sites, for authentication ofhe information resulting from the analysis. However, in mountain-us regions, which are difficult to access, vegetation surveys needo be conducted rapidly and with limited resources, such as for veg-tation mapping. In such situations, it may be desirable to surveyhe largest possible number of localities, but simplify the fieldworkrotocol by focusing on a small subset of species that have high pre-ictive value. The use of indicator species to monitor environmentalonditions or to determine habitat or community types is a firmlystablished technique for both theoretical and applied purposesn vegetation ecology in the recent past. Such indicators are useds indicative of a specific microclimatic condition or environmentalhange. The use of a suite of multispecies ecological or environmen-al indicators rather than single indicators has been recommendedo increase the reliability of bio-indication systems (Carignan andillard 2002; McGEOCH, 1998; Niemi and McDonald 2004; Butlert al., 2012; Mouillot et al., 2013). In order to determine indicatorpecies, the characteristic to be predicted is represented in the formf a classification of the sites, which is compared to the patterns ofistribution of the species found at the sites. For this purpose, Indi-ator Species Analysis (ISA) takes into account the fact that speciesave different niche breadths.

Another important application, of this paper is illustration of
egetation classification schemes according to the modern rules.egetation types are often defined using the complete compo-ition of vascular plants (Cáceres et al., 2012). When completeomposition is available, there are several alternatives for assign-
0.0006 37.93 54.97

0.0288 30.60 37.35

ing vegetation plot records to predefined vegetation types (VanTongeren et al., 2008; Tongren and Hennekens 2008; Cáceres andLegendre, 2009), which are preferable to the approach presentedhere. When an indicator value index is used, the method providesthe set of site-groups that best matches the observed distribu-tion pattern of the species. When applied to community types, itallows one to distinguish those species that characterize individ-ual types from those that characterize the relationships betweenthem. This distinction is useful to determine the number of typesthat maximizes the number of indicator species. Consideration ofcombinations of groups of sites provides an extra flexibility to qual-itatively model the habitat preferences of the species of interest(Acker, 1990). If at a given site, one finds a species combinationwith high predictive value, the site can be assigned with confi-dence to the indicated type. If none of the valid indicators is found,then a full vegetation plot may need to be established. Users ofthe method should bear in mind that when site groups have beendefined using species composition data, they are by definition nonindependent from species. In these cases, the indicator value statis-tic will be larger than the value expected under the null hypothesisof independence, leading to a high rate of rejection in inferentialtests (De Cáceres et al., 2010). When confidence intervals are beingused to assess the uncertainty of the estimation, however, theyare still valid. A variety of environmental gradients determines theboundaries of altitudinal zones found on mountains, ranging fromdirect effects of temperature and precipitation to indirect charac-teristics of the mountain itself, as well as biological interactionsof the species. Zonation produces distinct communities along anelevation gradient (Haq et al., 2015; Khan et al., 2015). In additionto environmental factors, other factors related to historical plant
geography may also be responsible for the determination of a plantcommunity (Poore, 1955).
The Western Himalayan TsFD in Pakistan is a highly diverseregion, particularly in terms of the wide range of natural for-

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Table 7Results of Indicator Species Analysis (ISA) through PC-ORD, showing top Indicator plant species (with bold font) of each of the five plant communities (1–5) at a threshold level of Indicator 30% and Monte Carlo tests of significancefor observed maximum indicator value of species (P value ≤ 0.05).

S NO BOTANICAL NAME Melia, Punica and EuphorbiaCommunity

Ziziphus, Zanthoxylum andRumex Community

Quercus, Cornus and ViolaCommunity

Cedrus, Viburnum andAchillea Community

Abies, Daphne and PotentillaCommunity

Group was defined byvalue of ElectricalConductivity

Group was defined byvalue of Aspect

Group was defined byvalue of Texture Classes

Group was defined byvalue of Soil pH


Max val (IV) P* Max val (IV) P* Max val (IV) P* Max val (IV) P* Max val (IV) P*

1 5Abies pindrow Royle. 0 64.6 0.1394 3 21.4 0.8276 3 38 0.0614 7 40.5 0.007 7 40.5 0.0072 Acacia arabica (Lam.) Willd. 1 46.2 0.1212 2 12 0.3653 1 8.7 0.7578 4 29 0.0352 4 29 0.03523 Acacia nilotica (Linn.) Delile 1 38.7 0.2861 2 19.6 0.2094 4 17 0.3651 4 17.6 0.2747 4 17.6 0.27474 Acer caesium Wall. Ex Brandis 0 29.2 1 3 19.5 0.3041 2 23.6 0.2364 6 33.5 0.0696 6 33.5 0.06965 Aesculus indica (Comb) Hook. 0 18.7 1 4 9.8 0.7197 3 25.4 0.1576 7 44.3 0.0082 7 44.3 0.00826 Ailanthus altissima (Mill.) Swingle 1 75 0.1292 2 23 0.2805 1 14.3 0.8458 4 32.7 0.0912 4 32.7 0.09127 Broussonetia papyrifera Vent. 1 38.7 0.2907 1 8.7 0.7584 4 8.3 0.9144 5 17.5 0.2833 5 17.5 0.28338 Cedrela serrata Royle 0 14.6 1 4 7.5 0.8522 2 8 1 6 33.3 0.0728 6 33.3 0.07289 Cedrela toona Roxb. Ex Rottl. & Willd. 0 8.3 1 4 16.3 0.2222 4 8.5 0.8486 6 10.6 0.5415 6 10.6 0.541510 4Cedrus deodara Rox ex Lamb. 0 72.9 0.0828 1 30.4 0.2208 3 33.4 0.1732 6 34.5 0.0574 6 34.5 0.057411 Celtus australis L. 0 22.9 1 3 9.3 0.8506 3 23.8 0.173 6 34.7 0.0954 6 34.7 0.095412 3Cornus macrophylla Wall. Ex Roxb. 0 29.2 1 4 17.4 0.3559 6 48.6 0.021 6 48.6 0.021 6 48.6 0.02113 Cotoneaster minuta Klotz. 0 27.1 1 4 11.9 0.8758 3 36.2 0.0592 6 20.1 0.3229 6 20.1 0.322914 Dalbergia sissoo Roxb. 0 6.2 1 1 6.6 0.8262 4 4.9 1 6 6.2 1 6 6.2 115 1Diospyros kaki L. 1 87.3 0.0364 3 7.5 0.9474 2 21.5 0.2539 4 16.3 0.3527 4 16.3 0.352716 Diospyros lotus L. 0 29.2 1 2 13.5 0.6741 2 31 0.1158 4 23.9 0.3055 4 23.9 0.305517 Eucalyptus globulus L. 0 16.7 1 2 20.1 0.2034 1 28.6 0.1006 4 51.3 0.006 4 51.3 0.00618 Ficus carica L. 1 64 0.3373 2 28.5 0.1582 3 22.8 0.6981 5 38.1 0.1156 5 38.1 0.115619 Ficus palmata Forssk. 1 51 0.2373 2 28.5 0.1482 5 4.9 1 3 21.9 0.3052 3 21.9 0.305220 Grewia optiva Drum. ex. Burret 0 14.6 1 2 6.7 0.957 1 10.7 0.6019 6 10.7 0.776 6 10.7 0.77621 Ilex dipyrena Walld. 0 12.5 1 3 10.5 0.4767 3 13.6 0.2869 6 28.6 0.0556 6 28.6 0.055622 Jacaranda mimosifolia D. Don. 0 16.7 1 3 8.3 0.808 2 17.6 0.3257 5 7.9 0.9198 5 7.9 0.919823 Juglans regia L. 0 25 1 1 13.7 0.6839 1 20.5 0.3115 6 10.1 0.8922 6 10.1 0.892224 1Melia azedarach L. 1 85.7 0.0406 1 9.2 0.796 1 8.6 0.8574 5 32.8 0.1062 5 32.8 0.106225 Morus alba L. 1 81.4 0.0686 3 14.9 0.4901 4 14.5 0.6681 4 25.1 0.2753 4 25.1 0.275326 Morus nigra L. 0 33.3 0.5541 2 23.8 0.225 2 28.5 0.1678 5 21.9 0.4245 5 21.9 0.424527 Olea ferruginea Royle. 0 18.7 1 2 21 0.1094 2 21 0.2803 5 21.7 0.15 5 21.7 0.1528 Pinus roxburghii Sargent. 1 37.5 0.3279 2 18.6 0.2729 4 14.7 0.4597 5 17.9 0.211 5 17.9 0.21129 Pinus wallichiana A.B.Jackson. 0 52.1 1 1 24.4 0.7209 2 28 0.6961 6 30.2 0.1942 6 30.2 0.194230 Pistacia integerrima J.L. 1 38.7 0.2917 2 40.4 0.0086 1 13.8 0.4455 4 17.7 0.2623 4 17.7 0.262331 Platanus orientalis L. 0 6.2 1 1 19.7 0.102 4 4.9 1 4 10.5 0.5263 4 10.5 0.526332 Populus ciliata Wall. Ex Royle 1 38.7 0.2971 3 10.6 0.6185 1 13.8 0.4461 7 13.9 0.6587 7 13.9 0.658733 Populus nigra L. 0 20.8 1 3 6.9 1 3 24 0.207 6 47.6 0.0056 6 47.6 0.005634 Prunus armeniaca L. 1 36.4 0.3627 3 10.2 0.7532 1 18.4 0.3643 5 21.8 0.2156 5 21.8 0.215635 Prunus domestica L. 1 33.3 0.4585 2 13.5 0.6791 2 16.9 0.5319 5 18.3 0.4079 5 18.3 0.407936 Prunus padus (Hk) f. 0 35.4 0.5445 4 21.3 0.3533 4 11.9 1 7 60 0.0008 7 60 0.000837 Prunus persica (Linn.) Batsch 0 10.4 1 2 8.3 0.6843 4 6.4 1 7 17.1 0.3649 7 17.1 0.364938 Pyrus pashia D.Don. 0 43.7 0.4931 2 20.9 0.3993 2 21.2 0.4907 5 21.9 0.5643 5 21.9 0.564339 Quercus dilatata Lindl. Ex Royle 0 10.4 1 1 15.3 0.1896 2 10.4 0.6963 6 10.2 0.5075 6 10.2 0.507540 3Quercus incana Roxb. 0 31.2 1 4 35 0.0306 3 42.7 0.018 6 27.2 0.2402 6 27.2 0.240241 Robinia pseudoacacia L. 1 65.8 0.2861 1 26.3 0.3315 2 16.7 0.933 5 18.4 0.9662 5 18.4 0.966242 Salix alba L. 0 4.2 1 1 9.2 0.4423 1 3.4 1 4 12.8 0.3253 4 12.8 0.325343 Salix angustifolia Willd. 0 29.2 1 3 13.8 0.6169 2 27.7 0.1248 6 40.7 0.0266 6 40.7 0.026644 Salix denticulata N.J. Anderss. 1 38.7 0.2901 2 21.7 0.1264 3 8.3 0.8554 7 14 0.6089 7 14 0.608945 Sarcococca saligna (Don) Muell. 0 10.4 1 3 6.9 0.829 2 10 0.8286 6 15.1 0.4537 6 15.1 0.453746 Sorbaria tomentosa (Lindl.) 0 31.2 1 4 20.5 0.2977 3 37.6 0.056 6 32.5 0.0796 6 32.5 0.079647 Staphylea emodi Wall. Ex Brandis. 0 4.2 1 2 12.3 0.3013 2 16.6 0.2394 5 2.6 1 5 2.6 148 Taxus wallichiana (Zucc.) 0 2.1 1 1 12.5 0.2565 1 5.9 0.5203 7 33.3 0.0608 7 33.3 0.060849 Ulmus wallichiana Planch. 0 14.6 1 4 8.7 0.7199 3 11.7 0.4947 7 17.9 0.2627 7 17.9 0.2627

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50 Vincetoxicum arnottianum Wight. 0 2.1 1 3 4.5 1 1 5.9 0.5067 5 5 0.5763 5 5 0.576351 2Ziziphus vulgaris Lam. 1 38.7 0.2951 2 40.4 0.0126 2 7.4 1 4 33.3 0.0962 4 33.3 0.096252 Abelia triflora R. Br. 0 22.9 1 4 25.5 0.1018 4 9.9 0.7802 6 27.3 0.2022 6 27.3 0.202253 Andrachne cordifolia (Don) Muell 0 45.8 0.5013 3 19.6 0.5621 3 30.1 0.189 6 37.6 0.098 6 37.6 0.09854 Arundo donaxL. 0 16.7 1 3 13.8 0.3895 2 22.8 0.2224 4 17.7 0.2621 4 17.7 0.262155 Astragalus flaccidum (Royle) 0 29.2 1 4 10.5 0.9616 3 23 0.2623 6 23.1 0.3347 6 23.1 0.334756 Berberis lycium Royle. 1 63.2 0.3557 2 25.1 0.4101 2 25.9 0.3625 5 28.7 0.3465 5 28.7 0.346557 Berberis orthobotrys Bien. Ex Aitch. 0 25 1 1 16.2 0.3685 2 18.1 0.4527 7 69.5 0.0016 7 69.5 0.001658 Berberis pachyacantha Koehne, Deutsche Dender. 0 12.5 1 2 8.9 0.6181 3 61.9 0.0026 6 28.6 0.058 6 28.6 0.05859 Berberis parkeriana C.K.Schn. 0 10.4 1 4 5.1 1 2 10.4 0.6967 6 23.8 0.0546 6 23.8 0.054660 Buddleja asiatica Lour. 0 10.4 1 4 9 0.5985 3 10.3 0.7341 7 21 0.239 7 21 0.23961 Buddleja crispa Bth., 0 25 1 3 11.2 0.8686 3 22.2 0.243 6 20.8 0.2753 6 20.8 0.275362 Buxus papillosa C.K.Schn. 1 38.7 0.3043 3 18.3 0.2611 2 18.3 0.2869 6 14.6 0.4987 6 14.6 0.498763 Clematis amplexicaulis Edgew. 0 16.7 1 3 9.2 0.6717 2 34.3 0.033 5 10.2 0.8562 5 10.2 0.856264 Clematis montana Buch.- 0 20.8 1 3 15.9 0.4223 3 52.3 0.0072 6 30.2 0.1184 6 30.2 0.118465 Cuscuta reflexa Roxb Amar. 0 14.6 1 2 6.7 0.9576 2 24.2 0.18 4 19.2 0.1854 4 19.2 0.185466 5Daphne mucronata Royle. 0 20.8 1 4 17.9 0.2631 1 24 0.1772 7 75 0.0002 7 75 0.000267 Debregeasia salicifolia (D. Don) Rendle, 0 8.3 1 4 7.9 0.7516 1 6.9 1 5 5.1 1 5 5.1 168 Desmodium gangeticum (Linn) DC. 0 16.7 1 4 6.9 0.8824 3 23.1 0.1912 6 11.2 0.8064 6 11.2 0.806469 Desmodium podocarpum DC. 1 35.3 0.4151 3 10.3 0.7688 2 30.6 0.0726 6 20.8 0.2753 6 20.8 0.275370 Dodonea viscosa Jack 1 36.4 0.3637 2 17.2 0.3503 4 10 0.7027 5 21.8 0.2128 5 21.8 0.212871 Euonymus hamiltonianus Wall. 0 8.3 1 3 9.2 0.5683 2 12.3 0.4141 6 19 0.2555 6 19 0.255572 Hedera nepalensis K. Koch., 0 22.9 1 3 19.4 0.1806 2 35.9 0.0594 4 28 0.1786 4 28 0.178673 Indigofera gerardiana Wall. 1 67.6 0.2498 2 29.1 0.1618 2 17.4 0.8532 5 28.8 0.23 5 28.8 0.2374 Indigofera heterantha Wall. Ex Brandis. 0 35.4 0.5485 4 17.6 0.5315 3 17.6 0.5917 7 32 0.0844 7 32 0.084475 Isodon coetsa (Spr.) 0 10.4 1 1 16.2 0.1512 1 20 0.1654 4 7.6 1 4 7.6 176 Lonicera hispida Pall. Loony 1 35.3 0.3987 4 7.9 0.9562 3 7 1 5 13 0.6315 5 13 0.631577 Lonicerar bicolor KI. & Garcke., 0 33.3 0.5533 4 14.7 0.6105 2 24.8 0.229 4 22.1 0.3799 4 22.1 0.379978 Lonicerar quinquelocularis Hardw. 0 22.9 1 3 17.5 0.2609 4 7.1 0.9468 6 17.1 0.3257 6 17.1 0.325779 Parrotiopsis jacquemontiana (Dcne.) 0 4.2 1 4 4 1 4 8.3 0.6773 6 9.5 0.6573 6 9.5 0.657380 Paeonia emodi Wall. 0 12.5 1 3 4.7 1 2 9.4 0.8308 6 28.6 0.0584 6 28.6 0.058481 1Punica granatum L. 0 38.7 0.039 1 20.8 0.4205 1 29.7 0.1894 4 58.9 0.0008 4 58.9 0.000882 Rhamnus purpurea Edgew. 0 12.5 1 4 8.1 0.7493 3 12.7 0.3991 6 28.6 0.0576 6 28.6 0.057683 Rhus punjabensis Stewart ex Brandis., 0 10.4 1 3 13.3 0.3341 3 26.1 0.1036 6 23.8 0.0516 6 23.8 0.051684 Rosa moschata non J. Herrm. 1 68.6 0.2296 2 28.9 0.183 4 17.7 0.8222 4 53 0.001 4 53 0.00185 Rosa webbiana Wall. Ex. Royle., 0 25 1 3 12.9 0.7676 3 19 0.3845 6 25 0.2412 6 25 0.241286 Rubus ellipticus Smith in Rees., 0 29.2 1 4 13.9 0.6003 2 13.4 0.8316 6 18.2 0.4655 6 18.2 0.465587 Rubus fruticosus Hk.f. 1 30.8 1 2 22.9 0.2585 1 16.7 0.6253 4 41.9 0.0364 4 41.9 0.036488 Rubus macilentus Camb. In Jacq. 0 18.7 1 4 14.4 0.4645 3 55.3 0.005 7 15.5 0.3913 7 15.5 0.391389 Rubus ulmifolius Schott in Oken., 0 8.3 1 3 9.2 0.5689 2 11.7 0.5573 6 10.6 0.5459 6 10.6 0.545990 Sageretia brandrethiana Aitch., J.L.S. 0 12.5 1 3 10.5 0.4841 2 9.4 0.8312 5 7.7 0.8068 5 7.7 0.806891 Skimmia laureola D.C. 0 10.4 1 1 14.6 0.2252 2 10 0.8306 7 91.3 0.0004 7 91.3 0.000492 Solanum pseudocapsicum L. 0 12.5 1 2 7.3 0.8886 2 9.4 0.8406 4 38.6 0.0488 4 38.6 0.048893 Spiraea gracilis Maxim., 0 16.7 1 1 11.1 0.5403 4 11.2 0.5235 6 16.7 0.2883 6 16.7 0.288394 Syringa emodi Wall. Ex G. Don., 0 12.5 1 2 8.5 0.7175 4 9.8 0.7273 6 28.6 0.059 6 28.6 0.05995 Viburnum cotinifolium D.Don. 0 22.9 1 1 7.1 1 3 20.1 0.3045 6 11.9 0.6743 6 11.9 0.674396 4Viburnum grandiflorum Wallich. 0 50 0.4963 4 20.5 0.4685 3 44.1 0.0288 7 49.9 0.0016 7 49.9 0.001697 Vitex negundo Linn. 0 18.7 1 1 16.2 0.4049 2 21 0.2781 7 44.1 0.0242 7 44.1 0.024298 2Zanthoxylum alatum Roxb. 1 28.6 1 4 60.9 0.0006 1 22.2 0.3861 4 60.9 0.0006 4 60.9 0.000699 Ziziphus jujuba Lam. 1 40 0.2561 2 24.7 0.055 1 9.1 0.7568 5 19.3 0.1232 5 19.3 0.1232

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Table 7 (Continued)












100 4Acmountainea millefolium L. 0 47.9 0.4871 3 22.3 0.3395 3 44.9 0.0276 6 47.2 0.019 6 47.2 0.019101 Achyranthus spp 0 20.8 1 1 7.7 0.911 2 15.6 0.5213 7 12.4 0.7686 7 12.4 0.7686102 Aconitum violaceum Jacq. ex Stapf 1 31.6 0.5137 3 12.9 0.7417 2 25.5 0.1904 5 14.4 0.6675 5 14.4 0.6675103 Actaea spicata L. 0 18.7 1 3 8.2 0.826 3 54.4 0.0078 6 42.9 0.0362 6 42.9 0.0362104 Adiantum venustum Linn. Sraj, 0 14.6 1 1 12.5 0.3813 2 8 1 5 8.7 0.841 5 8.7 0.841105 Aegopodium burttii E. 0 2.1 1 3 4.5 1 4 4.2 1 6 4.8 1 6 4.8 1106 Ainsliaea aptera DC., 0 16.7 1 4 7.9 0.8616 3 8.7 0.7536 6 29 0.1094 6 29 0.1094107 Ajuga bracteosa L. 0 39.6 0.5121 2 20.3 0.4591 1 17.8 0.5785 4 31.6 0.109 4 31.6 0.109108 Anemone falconeri T. T. in Hk., 1 34.3 0.4315 3 12 0.8062 2 34.5 0.071 5 20.8 0.2643 5 20.8 0.2643109 Anemone tetrasepaqla Royle. 0 27.1 1 3 14.9 0.4967 3 19.1 0.3817 6 23 0.3027 6 23 0.3027110 Anemone vitifolia Ham. DC. 0 18.7 1 4 12.4 0.5475 3 29.1 0.1042 6 18.7 0.2132 6 18.7 0.2132111 Aquilegia missouriensis Royle. 0 10.4 1 3 6.9 0.8228 3 13.9 0.3295 6 15.1 0.4635 6 15.1 0.4635112 Aquilegia pubiflora Wall ex Royle 0 20.8 1 4 14 0.5655 3 7.3 1 6 30.2 0.1156 6 30.2 0.1156113 Argemone mexicana L. 0 10.4 1 3 22.7 0.1182 2 39.6 0.0116 4 7.7 0.8108 4 7.7 0.8108114 Arisaema flavum Forrsk. 0 18.7 1 1 9.9 0.6905 3 30.3 0.0714 7 15.5 0.3897 7 15.5 0.3897115 Arisaema jacquemontii Blume. 0 16.7 1 1 8.4 0.7846 3 8.3 0.8468 6 16.7 0.2875 6 16.7 0.2875116 Arisaema utile Hk.f., 0 4.2 1 3 9.1 0.6235 4 8.3 0.6669 6 9.5 0.6489 6 9.5 0.6489117 Artemisia absinthium L. 1 80 0.0772 2 14.4 0.5495 4 13.4 0.8054 5 32.5 0.0922 5 32.5 0.0922118 Aster molliusculus (DC.) 0 16.7 1 3 9.2 0.6837 3 8.5 0.803 6 29 0.1038 6 29 0.1038119 Atropa acuminata Royle., 0 4.2 1 4 13.3 0.2693 4 8.3 0.6591 6 9.5 0.6601 6 9.5 0.6601120 Bergenia ciliata (Haw) Sternb. 0 18.7 1 4 16.5 0.3785 4 7.4 1 6 20.3 0.1814 6 20.3 0.1814121 Bistorta amplexicaule (D.Don) Greene. 0 25 1 1 17 0.2999 3 19.5 0.3529 7 35.1 0.0624 7 35.1 0.0624122 Bupleurum candollei Wall. Ex DC., 1 38.7 0.3021 1 8.4 0.7776 3 8.3 0.8526 5 15.9 0.4691 5 15.9 0.4691123 Bupleurum falcatum L. 0 14.6 1 3 9.4 0.6151 3 28.3 0.0924 6 33.3 0.0764 6 33.3 0.0764124 Bupleurum jacundum Kurz., 0 18.7 1 1 9.9 0.6775 2 16.5 0.4129 6 14.8 0.5059 6 14.8 0.5059125 Bupleurum lanceolatum Wall. Ex DC., 0 12.5 1 3 8.9 0.6757 3 9.9 0.6347 6 19.7 0.2068 6 19.7 0.2068126 Calamintha vulgaris (L.) 0 10.4 1 3 13.3 0.3453 3 10.3 0.7329 6 8.4 0.7457 6 8.4 0.7457127 Cannabis sativa L. 1 80 0.0742 2 26.8 0.1288 4 17.4 0.5403 5 28.8 0.1992 5 28.8 0.1992128 Capsella bursa pastoris Moench. 1 30 1 1 23 0.2625 1 32.5 0.1162 4 54.7 0.017 4 54.7 0.017129 Capsicum annuum L. 0 10.4 1 2 28.7 0.0528 2 51.4 0.0052 4 23.1 0.1236 4 23.1 0.1236130 Caryopteris odorata (Ham) B. L 0 12.5 1 4 11.9 0.4107 2 9.4 0.8358 6 12.5 0.6353 6 12.5 0.6353131 Chenopodium album L. 0 50 0.4993 1 37.9 0.0328 2 35.8 0.086 5 23.3 0.3339 5 23.3 0.3339132 Chrysanthemum cinerariifolium Trey 0 29.2 1 1 20.6 0.2851 3 23.4 0.2216 7 60.9 0.0044 7 60.9 0.0044133 Cichorium intybus Linn. 0 8.3 1 1 5.5 1 2 12.3 0.4313 6 10.6 0.5469 6 10.6 0.5469134 Cirsium argyracanthum DC. 0 8.3 1 3 9.2 0.5719 3 11.7 0.4487 6 19 0.2639 6 19 0.2639135 Cnicus argyracanthus (DC) Hk.f. 1 73.8 0.135 2 35.5 0.0488 4 17.3 0.6019 4 31.6 0.1054 4 31.6 0.1054136 Colchicum luteum Baker 0 14.6 1 3 7.5 0.8028 3 8.8 0.85 5 11.7 0.7119 5 11.7 0.7119137 Convolvulus prostratus Forssk 0 4.2 1 4 13.3 0.2767 1 3.4 1 5 2.6 1 5 2.6 1138 Conyza canadensis (L.) 0 14.6 1 3 12.3 0.4241 2 24.9 0.1574 6 7.9 0.9102 6 7.9 0.9102139 Coriandrum sativum Linn. 0 6.2 1 2 13.7 0.1622 4 4.9 1 6 6.2 1 6 6.2 1140 Corydalis diphylla Wall., 0 4.2 1 4 4 1 4 8.3 0.6663 6 9.5 0.6507 6 9.5 0.6507141 Corydalis stewartii Fedde, 0 16.7 1 3 18.3 0.2691 2 34.8 0.0284 6 29 0.1076 6 29 0.1076142 Cynodon dactylon L. 1 73.8 0.1414 2 34 0.0756 2 22.8 0.3449 4 60.8 0.0008 4 60.8 0.0008143 Cyperus rotundusL. 0 20.8 1 2 17.6 0.2937 4 9.2 0.7634 7 14.4 0.4945 7 14.4 0.4945144 Datura stramonium L. 0 10.4 1 4 18.2 0.1282 4 6.4 1 6 15.1 0.4707 6 15.1 0.4707145 Dicliptera roxburghiana Nees in Wall., 0 11.4 1 4 17.2 0.1182 5 9.2 0.8634 6 14.4 0.4945 6 14.4 0.4945146 Dioscorea bulbifera Linn. 0 4.2 1 4 4 1 1 3.4 1 5 2.6 1 5 2.6 1147 Dipsacus sativus (Linn.) Honck. 0 6.2 1 4 9.9 0.5557 2 14.1 0.3019 6 14.3 0.3277 6 14.3 0.3277148 Dipsacus strictus D.Don., 1 44.4 0.1632 4 7.9 0.7455 4 16.7 0.1658 5 11.4 0.4325 5 11.4 0.4325149 Dryopteris spp 0 25 1 1 16.6 0.3279 3 20.9 0.3021 7 69.7 0.0012 7 69.7 0.0012

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Table 7 (Continued)












150 Duchesnea indica (Andr.) Focke. 1 66.7 0.2735 2 27.5 0.2392 2 33.6 0.1124 4 39.1 0.0944 4 39.1 0.0944151 Echinops niveus Wall. Ex DC., 0 10.4 1 4 5.1 1 2 10.9 0.5645 6 23.8 0.0562 6 23.8 0.0562152 Elaeagnus parvifolia Wall 0 6.2 1 3 5.2 1 3 17.8 0.1696 6 14.3 0.3287 6 14.3 0.3287153 Ephedra gerardiana Wall. ex Stapf 0 8.3 1 4 16.3 0.2104 2 11.7 0.5537 6 19 0.2643 6 19 0.2643154 Epilobium royleanumHausskn., 0 2.1 1 3 4.5 1 4 4.2 1 6 4.8 1 6 4.8 1155 Epipactis helleborine (L.) 0 4.2 1 4 13.3 0.2693 4 8.3 0.6591 6 9.5 0.6601 6 9.5 0.6601156 ErIgeron roylei DC., 0 6.2 1 1 6.6 0.8248 4 12.5 0.5849 6 14.3 0.3333 6 14.3 0.3333157 Eulophia hormusji Du. 1 42.9 0.198 3 6.9 0.8234 3 66.1 0.0012 6 8.4 0.7469 6 8.4 0.7469158 1Euphorbia helioscopia L., 2 40.3 0.0222 2 40.3 0.0222 4 15.2 0.7281 4 50.2 0.0316 4 50.2 0.0316159 Euphorbia hirta L., 0 10.4 1 1 16.2 0.1448 2 10.4 0.7003 4 7.6 1 4 7.6 1160 Euphorbia wallichii Hk.f., 0 37.5 0.5433 4 21.9 0.3387 3 31.3 0.1468 7 58.3 0.0006 7 58.3 0.0006161 Foeniculum vulgare Mill. 0 8.3 1 1 5.5 1 4 8.5 0.8264 4 25.8 0.0612 4 25.8 0.0612162 Fragaria nubicola L. 0 27.1 1 1 15 0.4825 3 21.1 0.3017 6 20.1 0.3107 6 20.1 0.3107163 Galium aparine L. 1 31.6 0.5245 2 27.5 0.0882 2 15.3 0.6819 5 32.7 0.0804 5 32.7 0.0804164 Galium asperifolium Wall., 0 12.5 1 1 27.5 0.0236 3 9.4 0.8522 6 8.9 0.7117 6 8.9 0.7117165 Galium elegans Wall. In Roxb., 0 8.3 1 4 5.9 0.8762 1 6.9 1 6 10.6 0.5383 6 10.6 0.5383166 Galium hirtiflorum DC., 0 2.1 1 3 4.5 1 3 25 0.0856 6 4.8 1 6 4.8 1167 Geranium wallichianum D. Don ex Sweet, 0 16.7 1 3 22.8 0.077 2 17.9 0.3011 5 15.9 0.4655 5 15.9 0.4655168 Girardinia palmata (Forssk.) 0 6.2 1 3 5.2 1 4 4.9 1 4 10.4 0.5833 4 10.4 0.5833169 Gnaphalium affine D. Don., 0 4.2 1 4 4 1 4 8.3 0.6773 6 9.5 0.6573 6 9.5 0.6573170 Heliotropium paniculatum (R.Br.) 0 4.2 1 4 4 1 4 8.3 0.6613 6 9.5 0.6503 6 9.5 0.6503171 Heracleum candicans Wall. ex. DC., 0 6.2 1 3 13.6 0.2442 2 14.1 0.3179 6 14.3 0.3277 6 14.3 0.3277172 Hyoscyamus niger L. 0 4.2 1 4 4 1 2 15.5 0.3165 5 10 0.4787 5 10 0.4787173 Hypericum oblongifolium Choisy., 0 2.1 1 4 6.7 0.5607 4 4.2 1 6 4.8 1 6 4.8 1174 Hypericum perforatum L. 0 2.1 1 1 12.5 0.2669 4 4.2 1 6 4.8 1 6 4.8 1175 Impatiens balsamina L. 0 10.4 1 2 9.9 0.5267 3 13.9 0.3377 6 23.8 0.0538 6 23.8 0.0538176 Impatiens bicolor Royle. 0 8.3 1 4 7.9 0.7518 2 11.7 0.5535 6 19 0.2563 6 19 0.2563177 Impatiens edgworthii Hk.f., 0 4.2 1 1 9.2 0.4437 4 8.3 0.6679 6 9.5 0.6635 6 9.5 0.6635178 Impatiens flemingii Hk.f., 0 12.5 1 4 11.9 0.4019 3 36.6 0.0266 6 28.6 0.0522 6 28.6 0.0522179 Jasminum officinale Linn 0 8.3 1 1 17.3 0.1608 3 16.7 0.162 4 9 0.5709 4 9 0.5709180 Gerbera gossypina (Royle.) 0 16.7 1 2 6.2 0.9486 4 11.3 0.5151 4 17.5 0.2795 4 17.5 0.2795181 Lactuca brunoniana (Wall. ex DC.) 0 2.1 1 3 4.5 1 2 20 0.1836 6 4.8 1 6 4.8 1182 Lavatera Cashmeriana Camb., 0 4.2 1 3 9.1 0.6281 3 13.9 0.3299 6 9.5 0.6633 6 9.5 0.6633183 Lecanthus peduncularis (Royle.) 0 3.2 1 3 8.1 0.5281 3 21 0.1936 5 9.2 0.5709 5 9.2 0.5709184 Lepidium sativum L. 0 16.7 1 2 6.2 0.9432 3 10.2 0.6793 6 7.2 1 6 7.2 1185 Lyonia ovalifolia (Wall.) 0 4.2 1 1 8.2 0.7357 1 3.4 1 6 9.5 0.6603 6 9.5 0.6603186 Malcolmia africana (L.) 0 6.2 1 4 9.9 0.5499 3 18.7 0.0976 7 25.9 0.0778 7 25.9 0.0778187 Malva neglecta Wallr. 0 25 1 1 17 0.2963 2 14.4 0.6871 4 13.5 0.5689 4 13.5 0.5689188 Malva sylvestris L. 0 12.5 1 3 10.5 0.4733 3 9.4 0.8428 6 12.5 0.6399 6 12.5 0.6399189 Medicago denticulata Willd. 1 70.6 0.188 2 30.5 0.136 2 23.8 0.3863 4 55.8 0.0006 4 55.8 0.0006190 Mentha longifolia (Linn.), Huds 1 42.9 0.1886 2 9.4 0.5883 4 6.4 1 4 23.1 0.116 4 23.1 0.116191 Micromeria biflora Benth. 0 2.1 1 4 6.7 0.5475 4 4.2 1 5 5 0.5753 5 5 0.5753192 Myosotis asiatica Schischk. 0 10.4 1 4 5.1 1 2 10.9 0.5533 6 15.1 0.4595 6 15.1 0.4595193 Myrsine africana Linn. 0 2.1 1 3 4.5 1 4 4.2 1 6 4.8 1 6 4.8 1194 Nepeta erecta Bh Bth. 1 28.6 1 3 16.9 0.6419 3 45.4 0.0196 5 19.4 0.6119 5 19.4 0.6119195 Nerium oleander Linn. 0 2.1 1 4 6.7 0.5607 4 4.2 1 6 4.8 1 6 4.8 1196 Oenothera rosea Soland., 0 47.9 0.4927 1 23.2 0.2975 3 25.2 0.4055 6 18.6 0.7864 6 18.6 0.7864197 Onychium contiguum Wall. ex Hope., 0 8.3 1 4 16.3 0.2204 4 8.5 0.8464 6 19 0.2549 6 19 0.2549198 Orchid sp. 0 7.3 1 4 15.3 0.2104 3 4.5 1 6 4.8 1 6 4.8 1199 Otostegia limbata (Benth.) Boiss. 0 4.2 1 3 9.1 0.6299 3 50 0.0052 6 9.5 0.6529 6 9.5 0.6529

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Table 7 (Continued)












200 Oxalis corniculata L. 1 27.9 1 2 21 0.4087 3 14.7 0.9402 5 34.6 0.0896 5 34.6 0.0896201 Papaver somniferum.Linn 0 2.1 1 3 4.5 1 2 20 0.1836 6 4.8 1 6 4.8 1202 Phalaris minor Retz., 0 6.2 1 3 5.2 1 2 14.1 0.3103 6 14.3 0.3355 6 14.3 0.3355203 Phytolacca latbenia (Moq.) 0 6.2 1 1 7.2 0.6429 4 12.5 0.5735 6 14.3 0.3259 6 14.3 0.3259204 Pimpinella acuminata (Edgew.) 0 2.1 1 1 6.2 0.5429 4 4.5 1 7 4.8 1 7 4.8 1205 Plectranthus rugosus Wall. 0 2.1 1 4 6.7 0.5553 1 5.9 0.5141 6 4.8 1 6 4.8 1206 Plantago lanceolata Linn. 0 18.7 1 3 7.5 0.9476 3 54.4 0.0082 7 44.2 0.0186 7 44.2 0.0186207 Plantago major L. 0 25 1 4 25.5 0.1282 1 9.1 0.946 7 38.7 0.0308 7 38.7 0.0308208 Poa annua L. 1 80 0.0778 2 43.3 0.014 2 16.2 0.6035 4 54.1 0.0158 4 54.1 0.0158209 Podophyllum emodi Wall. Ex Royle. 0 6.2 1 1 7.2 0.6343 3 12.7 0.4313 6 14.3 0.3287 6 14.3 0.3287210 Podophyllum hexandrum Royle. 0 18.7 1 1 7.9 0.9032 1 9.2 0.784 7 13.3 0.5573 7 13.3 0.5573211 Polygonatum verticillatum All., 0 8.3 1 3 9.2 0.5653 3 15.3 0.3045 4 8.8 0.7936 4 8.8 0.7936212 Polygonum amplexicaule D. Don 1 36.4 0.3615 1 29.9 0.0718 4 12.9 0.6283 7 74.3 0.0012 7 74.3 0.0012213 5Potentilla fruticosa L. 0 18.7 1 4 12.4 0.5305 3 29.7 0.0908 7 44.4 0.0102 7 44.4 0.0102214 Potentilla nepalensis Hk. f. 0 16.7 1 1 8.7 0.7441 2 17.6 0.3191 7 14.1 0.5227 7 14.1 0.5227215 Primula veris L. 0 4.2 1 4 4 1 4 8.3 0.6663 6 9.5 0.6507 6 9.5 0.6507216 Prunella vulgaris L. 0 10.4 1 1 14.6 0.2318 1 20 0.1768 7 17.2 0.3399 7 17.2 0.3399217 Pseudomertensia parviflora (Decne.) 0 4.2 1 3 9.1 0.6423 2 16.6 0.2476 6 9.5 0.6557 6 9.5 0.6557218 Pteris vittata L. 0 22.9 1 4 14.5 0.6075 2 18.2 0.4131 7 72 0.0006 7 72 0.0006219 Ranunculus laetus Wall. ex H. 1 35.3 0.3951 3 15.7 0.4507 2 19.4 0.3667 7 40 0.0514 7 40 0.0514220 Ranunculus muricatus L. 0 22.9 1 2 29.4 0.0724 3 22.3 0.2484 4 28 0.188 4 28 0.188221 Reinwardtia indica Dumort. 0 6.2 1 3 13.6 0.2547 3 18.7 0.087 6 6.2 1 6 6.2 1222 Rochelia stylaris Bioss. 0 6.2 1 4 9.9 0.5593 1 8.7 0.7558 4 10.6 0.4023 4 10.6 0.4023223 Rumex dentatus L. 1 42.9 0.1928 2 25.1 0.082 2 28.6 0.1042 7 20.9 0.2581 7 20.9 0.2581224 Rumex hastatus D.Don., 1 30 1 2 22.5 0.3023 1 32.5 0.1152 4 48.6 0.0348 4 48.6 0.0348225 2Rumex nepalensis Spreng. 0 36.4 1 0 52.2 0.0188 1 23.4 0.5779 4 32 0.3243 4 32 0.3243226 Salvia Moorcroftiana Wall.ex Benth 0 6.2 1 4 9.9 0.5509 3 18.7 0.0936 6 6.2 1 6 6.2 1227 Sauromatum venosum (Ait.) Schott., 0 2.1 1 4 6.7 0.5607 4 4.2 1 6 4.8 1 6 4.8 1228 Scrophularia robusta Penn. 0 2.1 1 4 6.7 0.5649 1 5.9 0.5239 6 4.8 1 6 4.8 1229 Scutellaria linearis Bth., 0 2.1 1 4 6.7 0.5645 4 4.2 1 6 4.8 1 6 4.8 1230 Senecio chrysanthemoides DC. 0 20.8 1 3 15.5 0.4733 2 36.8 0.0428 5 24.9 0.1696 5 24.9 0.1696231 Sibbaldia cuneata Kunze., 0 2.1 1 3 4.5 1 4 4.2 1 6 4.8 1 6 4.8 1232 Silene vulgaris (Moench.) 0 10.4 1 3 10.8 0.4425 3 31.2 0.0462 6 15.1 0.4685 6 15.1 0.4685233 Silybum marianum Gaertn., 0 7.3 1 1 11.8 0.5425 3 4.2 1 5 21.9 0.1491 5 21.9 0.1491234 Solanum nigrumL. 0 10.4 1 2 50.6 0.003 4 6.4 1 4 41.7 0.0322 4 41.7 0.0322235 Sonchus arvensis (DC.) 0 8.3 1 3 18.2 0.1228 3 42.9 0.0116 6 10.6 0.5551 6 10.6 0.5551236 Strobilanthes alatus Nees non Blume 0 6.2 1 4 9.9 0.5527 2 12.6 0.4659 6 14.3 0.3253 6 14.3 0.3253237 Swertia alata (D.Don) 0 6.2 1 1 6.6 0.8248 3 17.8 0.1764 7 25.8 0.1372 7 25.8 0.1372238 Swertia angustifolia Ham. Ex. D.Don., 0 8.3 1 3 9.2 0.5645 3 11.7 0.4435 6 19 0.2591 6 19 0.2591239 Swertia ciliata (G. Don) B. L. Burtt 0 12.5 1 2 8.9 0.6135 2 9 0.9432 5 7.7 0.817 5 7.7 0.817240 Tagetes minuta L. 1 38.7 0.2985 2 21.7 0.1328 1 9.9 0.7149 4 17.5 0.2807 4 17.5 0.2807241 Taraxacum officinale Weber. 1 64.9 0.2995 2 25.2 0.4297 1 22.3 0.7087 4 37.7 0.1164 4 37.7 0.1164242 Thalictrum cultratum Bl 0 8.3 1 1 17.3 0.1592 2 11.1 0.6589 7 23.1 0.1944 7 23.1 0.1944243 1Themeda anathera (Ness) Hack. 1 85.7 0.0358 2 18.1 0.2639 2 20.4 0.3031 4 29.5 0.1566 4 29.5 0.1566244 Trifolium repens L. 0 6.2 1 3 5.2 1 3 12.7 0.4303 6 14.3 0.3449 6 14.3 0.3449245 Tussilago farfara L. 0 8.3 1 3 9.2 0.5575 3 15.9 0.2523 5 11.4 0.4227 5 11.4 0.4227246 Urtica ardens Link, Hort., 0 6.2 1 3 5.2 1 4 12.5 0.5765 6 14.3 0.3241 6 14.3 0.3241247 Valeriana jatamansi Jones. 0 12.5 1 3 17.6 0.2034 3 63 0.003 6 8.9 0.7185 6 8.9 0.7185248 Valeriana officinalis (non L.) Hk. F. 0 35.4 0.5497 1 25 0.1576 1 23.8 0.2891 7 27.1 0.2851 7 27.1 0.2851249 Verbescum thapsis L. 1 36.4 0.3611 2 32.2 0.0528 4 12.9 0.6231 4 35.6 0.0854 4 35.6 0.0854250 Verbena bonariensis L. 0 10.4 1 3 6.9 0.821 3 38.9 0.0242 6 15.1 0.4663 6 15.1 0.4663251 3Viola biflora L. 0 18.7 1 3 11.2 0.5637 3 54.4 0.008 6 42.9 0.0384 6 42.9 0.0384252 Viola canescens Wall ex Roxb. 0 20.8 1 4 12.7 0.5969 2 21.3 0.2272 6 16.8 0.2841 6 16.8 0.2841


Table 8Soil (Edaphic) factor analyses of all the sampling sites (stations) of Thandiani Sub Forests Division, Abbottabad—quantification in each of the five different plant communities.

S.No Stations PH EC (dsm-1) % O.M % CaCO3 % Sand % Silt % Clay T.Classes P (ppm) K (ppm)

Melia-Punica-Euphorbia Community1 Mandroch 5.2 0.63 0.55 11 25.8 52 22.2 1 8 1552 Battanga 5.3 0.29 1.04 6.5 49.8 36 14.2 4 6 1253 Neelor 5 0.31 1.24 9.7 37.8 46 16.2 4 6 1454 Bari Bak 5.3 0.28 0.85 12 39.4 42 16.2 4 7 1405 Mand Dar 5.2 1.02 1.06 6.3 47.8 36 16.2 4 5 1306 Pkhr Bnd 5.4 0.52 0.57 8.6 26.3 49.5 24.1 4 5 1107 Lowr Dna 5.4 0.26 1.32 8 51.8 36 12.2 4 6 1308 Bandi TC 4.9 0.92 0.5 12.5 15.8 64 20.2 1 6 1359 Qalndrbd 4.8 0.54 0.65 13.7 17.8 64 18.2 1 7 14510 Riala 4.8 0.54 0.55 8.5 26.4 49.4 24.2 4 5 11011 Malch Lw 5.5 1.03 1.08 8.7 45.8 30 24.2 4 5 12512 Malch Up 5.5 0.41 1.1 7.5 35.2 34 30.2 2 6 135Ziziphus-Zanthoxylum-Rumex Community1 Danna 5.5 0.62 1.15 8.3 33.8 48 18.2 4 6 1352 Uper Dna 5.7 0.35 0.72 1.3 29.2 60 10.2 1 6 1203 Pejjo 5.5 0.48 1.05 8.2 27.8 52 20.2 1 5 1154 Lowr Bal 5.9 0.4 1.07 7.7 45.8 28 26.2 2 7 1455 Upr Balo 6.4 0.36 1.1 6.6 29.9 40 32.1 2 6 1206 Mera Bun 4.9 0.28 0.75 13 39.8 44 16.2 4 7 1407 Lonr Pat 5.2 0.34 0.65 8 35.8 52 12.2 1 8 1508 Gali Ban 5.8 0.27 1.2 8 41.8 44 14.2 4 6 1059 Riala Ca 4.9 0.61 0.5 12.7 21.8 54 24.2 1 6 10510 Resrv FC 6.6 0.41 1.15 6.8 37.8 44 18.2 4 6 11011 Upper GB 6.2 0.24 1.06 8.4 35.8 40 24.2 4 6 12012 Chatrri 6.4 0.43 1.1 9.2 21.8 58 20.2 1 6 11513 Terarri 5.1 0.37 0.7 9.5 40.4 45.4 14.2 1 7 13514 Upr Rial 4.9 0.31 0.72 1.1 29.8 60 10.2 1 6 12515 Terari C 5.4 0.6 0.56 11 33.8 46 20.2 4 7 13016 Mathrika 5.9 0.45 1.24 6.7 29.8 56 14.2 1 6 135Quercus-Cornus-Viola Community1 Mthrka T 6.2 0.22 1.2 7.4 55.8 34 10.2 3 7 1452 Jabbra 6.3 0.49 1.07 7.3 69.6 20.1 10.1 3 5 1203 Darral 5.5 0.2 0.6 13 41.8 42 16.2 4 5 1104 Makali 6.5 0.25 0.55 10.5 35.8 50 14.2 4 6 1205 Ladrri 6.1 0.62 0.6 9.5 16.8 58 26.2 1 7 1306 Upper KP 6.5 0.53 1.05 7.2 69.2 20.6 10.2 3 5 907 Kakl RFC 5.8 0.51 1.18 5.8 29.2 44.6 26.2 4 5 1408 Parringa 6.6 0.44 0.8 7.8 21.8 56 22.2 1 6 1209 Satu Top 6.8 0.45 0.55 12 31.8 58 10.2 1 5 11510 Lower KP 6.4 0.33 1.08 6.5 29.8 38 32.2 2 6 11511 Larri 6.5 0.55 1.15 8 35.8 50 14.2 4 5 110Cedrus-Viburnum-Achillea Community1 Pallu Zr 6.7 0.41 1.2 6.9 37.1 43 18.1 4 6 1152 Lari Tra 6.3 0.26 1.25 7 57.2 26.2 16.2 3 5 1103 Lari Top 6.8 0.73 1.07 7.4 45.8 42 12.2 4 6 1254 Sawan Gl 6.7 0.38 1.2 6 49.2 28.6 22.2 2 6 1155 Lower Th 6.6 0.39 1.1 9.2 53.2 32 14.8 4 5 1106 Upper TC 6.7 0.57 1.15 9 45.2 44.2 10.2 4 5 105Abies-Daphne-Potentilla Community1 Mera RKC 6.6 0.22 0.7 10 29.8 44 26.2 4 8 1402 Mera RKT 6.8 0.34 0.65 8 21.8 54 24.2 1 8 145

ecessiiscaphdt

3 Lwr Nmal 7.1 0.2 0.6 8

4 Upr Nmal 7.2 0.36 0.55 6

5 Sikher 7.2 0.39 0.75 9

st types that occur there. These forests are, however, underonsiderable conversion pressure as land use intensifies withxpanding human population and economic development. Con-ervation strategies based on the geographic patterns of botanicalpecies richness and diversity, including the identification of mean-ngful floristic regions and priority areas for conservation, couldmprove the effectiveness of forest policy and management. Thesetrategies should also include current threats of loss due to forestonversion to address the more urgent challenges for sustain-ble development. Here, we produce distribution models for 252lant species using multivariate analysis, collecting geo-referencederbarium specimens. Our findings provide clear priorities for the
evelopment of a sustainable and feasible biodiversity conserva-ion strategy for TsFD through indicator species approach.
35.8 44 20.2 4 6 12033.8 60.6 15.6 1 6 12546.8 35.2 18.2 1 7 135

7. Conclusions

Plant ecologists have commonly been conscious that vegetationshows a discrepancy over a broad variety of particular factors andareas. We have demonstrated that both species composition andspecies pattern of vegetation in the TsFD depend more strongly onsoil pH, aspect and soil electrical conductivity than on any other soilor climatic variables. This relationship even exists across a narrowrange of near-neutral pH values; slopes with north-west and south-east aspects and low electrical conductivity. This study indicatesthat environmental factors have a strong influence on vegetationgradients and that the association of plant species changed in
response to edaphic, topographic and climatic gradients. There arethree major implications of the current study: (1) How to documentspecies composition, pattern and abundance at peak growing sea-

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50 W. Khan et al. / Ecologica

on and classify vegetation to potential plant communities usingluster Analyses (CA) through PCORD. (2) How to use samplingethods for finding relationships between plant communities and

omplex set of environmental variables using robust statisticalpproaches via Two Way Cluster (TWCA) and Indicator Speciesnalyses (ISA). (3) These techniques give a way to identify indicatoregetation of specific habitats and hence directly or indirectly con-ribute to biodiversity and habitat conservation and managementlans.

cknowledgements

We are thankful to the curator,Herbarium of Hazara Univer-ity Mansehra Pakistan, for providing help in identification of allhe plant specimens. We are also thankful to Directorate of Higherducation Khyber Pakhtun Khwah, Pakistan for financial assistanceowards this project.

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