Ethno-ecological importance of plant biodiversity in mountain ecosystems with special emphasis on indicator species of a Himalayan Valley in the northern Pakistan

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Ecological Indicators 37 (2014) 175–185

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Ecological Indicators
journal homepage: www.elsevier.com/locate/ecolind

Ethno-ecological importance of plant biodiversity in mountain
ecosystems with special emphasis on indicator species of a Himalayan
Valley in the northern Pakistan
Shujaul Mulk Khan a,d,∗ , Sue Page b , Habib Ahmad c , David Harper d
a

Department of Botany, Hazara University, Mansehra, Pakistan
Department of Geography University of Leicester, UK
c
Department Genetics, Hazara University, Mansehra, Pakistan
d
Department of Biology University of Leicester, UK
b

a r t i c l e

i n f o

Article history:
Received 17 April 2012
Received in revised form 4 September 2013
Accepted 10 September 2013
Keywords:
Indicator species
Conservation
Environmental gradient
Social perception
Himalaya

a b s t r a c t
Mountain ecosystems support a high biological diversity and a large number of endangered plant species
many of which are ecological indicators of those specific habitats. The Himalayas are the world’s youngest,
highest and largest mountain range and support a high plant biodiversity. People living in this region
use their traditional ecological knowledge to utilize local natural resources and hence have valuable
understanding about their surroundings. Many areas within this region still remain poorly known for
their floristic diversity, plant species distribution and vegetation ecosystem services, yet the indigenous people depend heavily upon local plant resources and, through unsustainable use, can cause an
irreversible loss of plant species. The valley used in this study is typical of such areas and occupies
a distinctive geographical location on the edge of the western Himalayan range, close to the Hindu
Kush range to the west and the Karakorum Mountains to the north. It is also located on geological
and climatic divides, which further add to its ecological interest. This paper focuses on (i) identification of ecological indicators at various elevation zones across an altitudinal range of 2450–4100 m and
(ii) recognition of social perceptions of plant species populations based on the ecosystem services that
they provide. We used robust approaches to identify the plant indicator species of various elevation
zones. Using phytosociological techniques, Importance Values (IVs) for each plant species were calculated. The statistical package PCORDS was used to evaluate the species area curves and indicator species
for each elevation zone. Data attribute plots derived from Canonical Correspondence Analysis (CCA) using
CANOCO were deployed to illustrate the location of indicator species in each habitat type. Furthermore,
the social perceptions of the local inhabitants as to whether the populations of the recorded species
were increasing or decreasing over the recent past were recorded. We argue that the assessment of
ecological indicators combined with the ecological knowledge of the indigenous population can assist
in developing priorities for local and regional conservation strategies, especially for fragile mountain
ecosystems.
© 2013 Elsevier Ltd. All rights reserved.

1. Introduction
Mountain ecosystems all over the world usually have diverse
biological communities due to their rapidly changing landscape,
climate and geo-climatic history (Fosaa, 2004; Herben et al., 2003).
The distribution of individuals of the same and different plant
species in a community is a function of micro environmental
differences, time and biotic relationships. Plant species assemble

∗ Corresponding author at: Department of Botany, Hazara University, Mansehra,
Pakistan.
E-mail addresses: shuja60@gmail.com, smulkkhan@gmail.com (S.M. Khan).
1470-160X/$ – see front matter © 2013 Elsevier Ltd. All rights reserved.
http://dx.doi.org/10.1016/j.ecolind.2013.09.012

in a definite fashion to form community and hence helps in identification of indicator vegetation of each zone. Plant biodiversity
provides the first trophic level in mountain ecosystems and hence
requires proper documentation and quantification in relation to
abiotic environmental variables both at individual and aggregate
levels (Jackson, 2006). Classification of natural ecosystems into
potential plant communities and habitat types is important for
the long-term management of natural resources (Ewald, 2003;
Mucina, 1997). Phytosociological techniques are increasingly being
used for conservation planning in natural ecosystems by identifying species of high conservation priority. Apart from the ecological
indicators, social indicators and perceptions can also be identified
and, when employed together with knowledge of traditional and

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S.M. Khan et al. / Ecological Indicators 37 (2014) 175–185

economic drivers, can play a vital role in designing conservation
strategies (Khan et al., 2012a; Tarrasón et al., 2010; Zou et al., 2007).
Conservation management, therefore, also requires an understanding of anthropogenic impacts on vegetation and their likely social
indicators, including poverty, lack of awareness and education, and
uncontrolled utilization of vegetation resulting in overexploitation
of plant resources. In the scenario of anthropogenic impacts on
vegetation ecosystem services, extensive assessment of plant biodiversity at both regional and national levels is needed (Zobel and
Singh, 1997).
Researchers from the natural and social sciences have studied
the natural system and human culture separately. Limited consideration has been made to link these disciplines together for
the better assessment of human impact on plant resources in
the Hindu-Himalayan region. Recently interest in such issues has
developed in different parts of the world as an attempt to integrate
traditional knowledge with ecosystem management (Chowdhury
et al., 2009; Dong et al., 2010; Mutenje et al., 2011; Sharma et al.,
c r
2010; Vaˇ káˇ et al., 2012). In this regard assessment of vegetation quality and quantity is as important as its floristic evaluation.
Through the Convention on Biodiversity (CBD), countries are making efforts to elaborate not only on the quantity of plant biodiversity
but also on the quality by identifying indicator species and measuring their abundance (Normander et al., 2012). This is not only
imperative for the conservation of biodiversity itself but also for
environmental sustainability against the scenario of changing climate, global warming and economic crises (Moldan et al., 2011;
Müller and Lenz, 2006). People’s observations about the trends in
plant populations can also be taken into consideration in conservation as they have long established associations with those plants
(Tarrasón et al., 2010). Conservation and management strategies
are necessary to be planned for vegetation of these ecosystem as
they give food security, not only to the people within these mountains but also for the people of the lowlands that depend on these
highlands (Manandhar and Rasul, 2009; Rasul, 2010; Sharma et al.,
2010).
In addition to the most accepted biodiversity conservation
criteria, namely rarity, endangerment and endemism, there are
other significant criteria relating to historical, traditional or educational values. Traditional knowledge in Asia in general and in
the intact valleys of the Himalayas and Hindu Kush in particular
can play a key role in formulating conservation strategies. Such
knowledge is wrought from a life time’s experience and is based
on the relationship between natural environments and cultures.
Indigenous people get benefits from nature using their traditional
knowledge but it may cause harm to the natural resources if carried out unwisely and unchecked. Ethnoecological knowledge is
a cultural asset that provides a base for synthesis of conservation
planning. Traditional knowledge can be used for the recognition
and preservation of valuable species as well as habitats in long
term management (Dung and Webb, 2008; Gaikwad et al., 2011;
Jules et al., 2008; Pieroni et al., 2007). The prevailing poverty and
expansion of agricultural land are the main causes of habitat and
biodiversity loss and must be addressed when designing policies
(Gorenflo and Brandon, 2005). Achieving the above mentioned conservation goals, needs collaboration of various governmental and
non governmental agencies involved in natural resources management (Fosaa, 2004; Mucina, 1997).
In north-western Pakistan, three of the world’s highest
mountain systems i.e., the Himalayas, Hindu Kush and Karakoram ranges, come together exhibiting high floral diversity and
phyto-geographic interests. Unlike the eastern Himalayas, where
monsoon driven vegetation predominates under higher rainfall and
humid conditions (Anthwal et al., 2008; Behera et al., 2002), the
vegetation in the western Himalayas in general (Ahmad et al., 2009;
Shaheen et al., 2011, 2012) and in the Naran Valley (Khan et al.,

2011b, 2013a) in particular has closer affinities with that of the
Hindu Kush mountains which have drier and cooler climate (Khan
et al., 2012c; Noroozi et al., 2008; Wazir et al., 2008). Nevertheless,
the vegetation in both these mountain systems as well as in the
Karakorum (Eberhardt et al., 2007; Miehe et al., 1996) exhibits great
similarity above the tree line (Miehe et al., 2009), where climatic
conditions are more comparable. The complex and dynamic range
of the Himalayan Mountains exhibit diverse vegetation which the
inhabitants use for various purposes and subsequently exert high
anthropogenic pressures on it. Plant biodiversity provide services
in the form of food, grazing land and fodder for livestock, fuel wood,
timber wood, and medicinal products. These ultimately contribute
to agricultural, socio economic and industrial activities. The species
providing multiple services and having more economic importance
are generally chosen by indigenous people which in turn increases
rarity of these species and habitat fragmentation. This paper aims
to provide a firm basis for identification of indicator plant biodiversity. We also aim to develop a methodology that can be reproduced
in vegetation studies of adjacent mountain systems. Our main
objectives were (i) to identify indicator plant species in different
habitat types using robust multivariate approaches such as indicator species analyses, canonical correspondence analyses and data
attribute plots, (ii) to assess the social perceptions on the trends of
vegetation populations of different species and the services people
obtain from them and (iii) to determine anthropogenic impacts on
plant biodiversity by valuating social indicators. The quantitative
approach to vegetation description and analyses deployed in this
study are special as they focus on vegetation abundance from the
perspective of environmental as well as cultural drivers.

2. Study area
The Naran Valley, which is floristically situated in the Western
Himalayan Province of the Irano-Turanian region, forms a botanical transition zone between the moist temperate (from the South
East) and dry temperate (from the North West) vegetation zones of
the Hindu Kush and Himalayan mountain ranges, respectively (Ali
and Qaiser, 1986; Khan, 2012). It is a mountainous valley in North
West Pakistan (34◦ 54.26 N to 35◦ 08.76 N latitude and 73◦ 38.90 E to
74◦ 01.30 E longitude; elevation between 2450 and 5000 m above
mean sea level). The entire area is formed by rugged mountains
on either side of the River Kunhar which flows in a northeast to
southwest direction down the valley to the town of Naran. Geographically the valley is located on the extreme western boundary
of the Himalayan range, after which the Hindu Kush range of mountains start to the west of the River Indus. Geologically, the valley is
located where the Eurasian and Indian tectonic plates meet and
where the arid climate of the western Eurasian mountains gives
way to the moister monsoon climate of the Sino-Japanese region
(Kuhle, 2007; Qaiser and Abid, 2005; Takhtadzhian and Cronquist,
1986) (Fig. 1). As far as we know, there is no previous ethnoecological study in this remote mountainous valley, due to the
complexity of the ecosystem, its inaccessibility and cost and time
factors.
Severe winter weather compels the inhabitants of the Naran
Valley to follow a nomadic lifestyle, with many people making
temporary arrangements to reside at high elevations in the valley during the summer months and returning to lower elevations
during winter. The population of the Naran Valley is exclusively
rural and people mostly live in temporary settlements and even in
tents in the upper parts of the valley (20 different villages in total).
The local economy is mainly based on farming and rearing of live
stock. Various tribes including the Gujars, Syeds, Swati and Kashmiri inhabit the valley among these are the Gujars (descendents of
the Indian Arians) who are famous for their unique culture, rituals


177

Fig. 1. Physiographic map showing the position of the Naran Valley (research area). Also shown are the elevation zones, location of main settlements namely A. Naran, B.
Damdama, C. Soach, D. Lower Batakundi, E. Upper Batakundi, F. Khora, G. Dabukan, H. Bans, I. Barrawae, J. Serrian, K. Jalkhad, L. Baiser, the River Kunhar, the river’s source
(Lake Lulusar) and tributary streams.

and bravery. They are also considered as the pioneering inhabitants
of the Hindustan sub-continent (Chauhan, 1998).
Extensive use of natural vegetation in the valley in the past has
decreased the provisioning of ecosystem services (Dobson et al.,
2006; Giam et al., 2010; Stewart and Pullin, 2008). This reduction
is quite prominent in the categories of food, fodder, timber fuel
and medicines provided by local species. The consequence of the
imbalance in supply of these services and the increasing human
demands have been deteriorating the condition of natural systems
and making several plant species more rare (Díaz et al., 2006; Giam
et al., 2010).
3. Materials and methods
Two types of data were recorded during two field data collection
campaigns, namely vegetation abundance data, collected during
the summer of 2009, and social perception data, collected during
the summer of 2010.

whole valley (about 60 km long) was divided into 12 sampling
localities (A–L) at about 5 km intervals (Figs. 1 and 2). To study
the vegetation of both northern and southern aspect slopes, 12
elevational transects were established on each of the aspects perpendicular to the River Kunhar at each locality (site), covering an
altitudinal elevation range of 2450–4100 m for the whole valley.
At each study site, each transect was started from the bed of the
river and was continued along the full altitudinal gradient (from
the valley bottom to the ridge of the mountain). Along each transect, stations (each with 9 quadrats) were established at 200 m
elevation intervals (144 stations in total) and the vegetation was
sampled in three layers i.e., tree, shrub and herb layers. In total,
1296 releves/quadrats were recorded (432 each for tree, shrub and
herb layers) using the methods proposed by (McIntosh, 1978). DBH
(diameter at breast height) of tree species in the quadrats were
measured to evaluate cover values of tree layers while for shrub
and herb layers the cover values were visually estimated.

3.1. Vegetation abundance data using quadrats
The use of quadrats along transects is the best way to assess
vegetation in varying landscapes (Cox, 1996; Goldsmith et al.,
1986; Everson and Clarke, 1987). A stratified random method
was used to sample the area with rectangular quadrats of varied sizes for trees (10 m × 5 m), shrubs (5 m × 2 m) and herbaceous
(1 m × 0.5 m) vegetation respectively. Changes to quadrat sizes,
based on = minimal area methods, were implemented where necessary. Minimal area method is a standard method through which
quadrat size is increased if surveyor feels that the plot/quadrat
size is inadequate due to more rich vegetation in a specific location. Quadrats were used along altitudinal transects to measure
the phytosociological attributes of vascular plant species following standard methods where randomization of sampling stations,
standardization of quadrat sizes and quantification of vegetation
were fully considered (Mueller-Dombois and Ellenberg, 1974). The

Fig. 2. Species area and compositional curves based on IVI data for all 198 plant
species and 144 stations.

178


3.2. Measurements and estimation of environmental variables
At each of the 144 releves stations the following environmental
data were also collected. Elevation data for each station at each
of the 200 m elevations along transects was obtained using a GPS
(Garmin eTrex. HC series, vista HCx); Measurement of longitude
and latitude were also recorded. Aspect was recorded using the
compass in the GPS. Soil pH was measured using a pH kit (Merck
KGaA Germany). An iron rod of 1 m length with pointed head was
used to measure soil depth in three classes. Grazing pressure (low
to high) was recorded on a scale of 1–5 by noticing the recent signs,
intensity and trampling effects of grazing cattle.
3.3. Social perception data using questionnaires
Local names of the 198 plant species recorded during the phytosociological survey were listed along with their botanical names.
Each of the main 12 settlements (villages) in the project area (Fig. 1),
were visited and meetings were arranged with village heads or
councillors – guidance and permissions were obtained. A local community member was taken as a guide who knew the norms and
traditions of the indigenous society as suggested by Da Cunha and
De Albuquerque (2006) and Martin (2004). Selection of a guide from
local people was important as they knew much better about the
social norms and ethics of the culture. Ten houses at each locality (a
total of 120) were selected randomly for the interviews, using a random number table method. Each village was visited from one side;
an interview was requested from each 5th house from that family
following (Cunningham, 2001; Martin, 2004) as it was important for
randomization and unbiased execution of social surveys. If willing,
one member in the household was interviewed about their perception of trends in the populations of plant species growing in the
valley. Photographs of plants obtained from the first field campaign
were shown to the interviewee where and when it was felt necessary. The trends in plant populations mentioned by the respondents
were grouped into three categories i.e., increase (I), decrease (D)
or no visible change (NC). Questionnaire can be traced via the
link http://www.scribd.com/doc/123606601/Questionnaire. Interviewees were also asked about various uses especially medicinal
uses of plant biodiversity of the region (Khan et al., 2013b)
4. Data analysis

distance matrices. To run a Mantel test one must have both a main
and a second matrix. Both matrices must have the same number
of rows. The value of the Mantel statistic can vary from −1 to +l
and can be used to illustrate the extent of correlation of quantitative attributes of vegetation under the influence of environmental
variables at various stations (Lamb et al., 2009; Legendre and Fortin,
1989; Mantel, 1967). Nevertheless, two variables may be correlated
due to a third, common variable, thus before the ultimate decision
is made whether the original two variables are significantly correlated, the third variable must be removed. The species data matrix
was therefore, also examined in relation to one environmental variable at a time.
4.3. Identification of indicator species
Abundance data of all the species and quadrats were analyzed
with the objectives of (i) evaluating the significance of the relationships among species and environmental variables, and (ii)
authenticating the habitat specificity of indicator species. Using
PCORD version 5, Indicator Species Analysis (ISA) (Dufrêne and
Legendre, 1997; Khan et al., 2011b) was employed to identify faithful indicators of each habitat type. These analyses categorize and
illustrate the value of different species as representative of environmental conditions and combine information on the concentration
of species abundance in a particular group with the faithfulness
(fidelity) of occurrence of a species in that particular group (defined
by an environmental variable). Using ISA, the species matrix for all
stations was defined five times for each environmental variable
i.e., aspect, elevation, soil depth, grazing pressure and soil pH, from
the environmental data matrix. This enabled construction of indicator values for each species in each group which were tested for
statistical significance using a Monte Carlo technique (Dufrêne and
Legendre, 1997; Khan et al., 2011b). Fidelity of indicator species was
also tested by their categorization in the fidelity classes (Malik and
Husain, 2006; Kent and Coker, 2002). Data attribute plots were produced using a utility in CANOCO that summarizes community data
by constructing a low dimensional space in which similar species
come closer together whilst dissimilar ones go further apart under
the influence of specific environmental factor(s). These plots were
used to re-assess the indicator species of each habitat type and
show them diagrammatically (Khan et al., 2011b; ter Braak and
Smilauer, 2002; ter Braak, 1989).

4.1. Species area curves
Species Area Curves (SAC) are widely used in vegetation ecology
to approximate the adequate sample size, understand the biodiversity and associated environmental and human factors (He and
Legendre, 1996,Legendre et al., 2005). We used species area and
compositional curves in order to evaluate whether the sample size
was sufficient to achieve species composition in relation to the full
sample (the study area). Using the abundance data combined with
Sørensen distance values, Species Area Curves were constructed
for all 144 stations (sampling plots) using PCORD (Grandin, 2006;
McCune and Mefford, 1999; Turner and Tjørve, 2005).
4.2. Mantel test
PCORD was used to perform mantel test for estimating the
strength of the relationship between species and environmental
data matrices. The Mantel method tests the significance of the correlation by a permutation method: the rows and columns of one
of the two matrices are permuted. After each permutation the Z
statistic is calculated and the resulting values provide an empirical distribution that is used for the significance test. It was run to
quantify the correlations between the floristic and environmental

4.4. Quantification of social perception (trend) mentioned by
people
Analysis of the questionnaires on the plant population trends
(perceptions) observed by the indigenous communities were analyzed following the methodologies adopted by Chowdhury and
Koike, 2010; Kassam et al., 2011; Uprety et al., 2010. In these methods they have used random sampling method for data collection.
Voucher specimens and pictures were shown to the interviewees where they felt doubt in identification of species. Qualitative
approach was adapted while asking about the trend in species population whether it increased, decreased or maintained over the past
decades. These analyses also allow for comparison of current trends
with the indicator species to evaluate the potential for sustainable
utilization and management of the regions’ vegetation.

5. Results
A total of 198 plant species belonging to 150 genera and 68 families were recorded at 144 stations (1296 releves) during the first
field survey. During the second field survey, 92.4% of these plants


were reported to be important in terms of provisioning services to
the local people under various use categories.
5.1. Species area curves
To ensure the adequacy of the sample size used in the community data, species area curves were calculated using PCORD.
The curve of average distance integrated the statistics on species
presence-absence and abundance to determine a subsample size
that gave a constant species composition. It shows species curves
climbs to the region of stability, whereas the distance curves goes
down to zero (Fig. 2). For our data set the average number of species
started from 20 at station 1 (with average distance 0.7651) to 197 in
station 143 (with average distance 0.0054). The average Sørensen
distance was reduced to around 10% after about 12 stations had
been sampled, indicating that a stable community composition had
been approximated.
5.2. Correlation between floristic attributes and environmental
variables
Examining the correlation between species data matrices and
environmental data matrices through the Mantel test resulted in
a highly significant correlation (p = 0.00000) between species and
environmental data. In the first step the species data matrix was
checked alongside the environmental variable data matrix. Treating
floristic matrix one by one with each of the environmental matrices showed the highest correlations with elevation, aspect and soil
depth. The correlation with grazing pressure was also significant
but with soil pH there was non-significant relation (Table 1).
5.3. Indicator species and habitat specificity
Three top indicator species were recognized for five vegetation
zones mainly based on elevation. Indicator Species Analysis (ISA)
identified indicator species for each of the elevation zones at a
threshold level of 20% (p value ≤ 0.05). Indicator species were also
identified if they had a constancy of 30% and fidelity between 3 and
5 from fidelity classes 1–5. Indicators of the lower elevation habitats (2450–2800 m) were dominated by temperate phanerophytes.
Top 3 indicator species of this habitat type are Pinus wallichiana;
Sambucus weightiana and Impatiens bicolour. The middle elevation
zone (2900–3300 m) were dominated by subalpine chamaephytes,
hemi-cryptophytic and therophytic species with its indicators i.e.,
Abies pindrow, Betula utilis and Achillea millefolium. Higher elevations (above 3400 m) were dominated by herbaceous vegetation
of mainly hemi-cryptophytic or cryptophytic nature – top indicators were Rheum austral, Sibbaldia cuneata, Bergenia strachyei, Aster
falconeri, Iris hookeriana and Ranunculus hirtellus (Figs. 3–7). These
indicators were highly habitat specific in relation to the altitudinal
zones (Table 2, Appendix 1).
5.4. Results of canonical correspondence analysis (CCA)
After finding the general vegetation environmental relationship,
and identification of indicator species, Canonical Correspondence
Analysis (CCA) was carried out to classify the species matrices for
the faithfulness (fidelity) of species to a particular habitat type
and community (defined by an environmental variable). These values were tested for statistical significance using a Monte Carlo
method (p value ≤ 0.002). Data attribute plots reconfirmed that
elevation was the most important environmental variable in determining indicator species. Indicators of the lower elevation habitats
were of a temperate nature e.g., P. wallichiana; S. weightiana and I.
bicolour. There were some microclimatic variations in that slopes
with a northern aspect had different indicator species (A. pindrow,

179

B. utilis and A. millefolium) from those with a southern aspect
(Juniperus excels, Artemisia brevifolia and Eremurus himalaicus) at
middle elevations. Higher elevations (3300–3900 m) were dominated by subalpine species e.g., R. austral, S. cuneata and B. strachyei,
while the highest elevations (above 3900 m) exhibited a dominance of herbaceous vegetation e.g., A. falconeri, I. hookeriana and
R. hirtellus. At the same same time aspect (slope orientation) and
soil depth also had an influence on the vegetation pattern. The
CCA ordination procedures indicated that the first axis was primarily correlated with elevation and soil depth; the second axis
was correlated mainly with aspect; while the third axis was correlated partially with aspect, elevation, soil depth and grazing
pressure. Indicator species were highly habitat specific in relation to elevation zones. Such indicator could be studied in further
detail to understand the requirements of specific habitat types and
vegetation and to devise conservation plans (Figs. 3–7, Table 3
& Appendix 1).
5.5. Results of the social interviews
Findings of the ethnoecological questionnaire analyses show
that the respondents represented a diverse array of people including farmers, women, literate, illiterate, young and old. Among the
120 informants, 87 were male and 33 were female. The largest proportions of the respondents were above 40 years old (81.6%). More
than half of the respondents were illiterate (51.7%), whilst, most
of those with an education had merely primary which reflect the
unavailability of educational institution in the area (30%). These
very basic informations also reflect the legitimacy that indigenous
knowledge is well established in older generations as compare to
the younger one.
Due to high elevation of the study area, vegetation is mainly
herbaceous and shrubby and hence mostly used in the form of nontimber forest products (NTFPs). The questionnaire analyses show
that 183 plant species (92.4% of the surveyed species) provided services to the local people in the form of fuel, food, fodder, medicinal,
grazing, aesthetics and other services. Many of the species offered
more than one service. The high number of uses has resulted in
an enormous pressure being placed on the plant biodiversity. It
also indicates the long and well established traditional ethnobotanical knowledge that exists in this area. Prevailing poverty, lack of
resources and harsh climate compel the local people for unmanaged utilization of plant resources which is a frightening sign for
future resource sustainability.
5.6. Overview of the social perceptions on plant population trends
The results of the analysis of local people’s perception on vegetation abundance at a species level shows that they believe there
has been a decrease in more than 50% of the plant species growing
in the region. Only 34% of the species were reported to have maintained their populations with no visible change whilst an increase
in population size was reported only in 10% of the species. Furthermore, when those species exhibiting a decreasing trend in
population size were examined from species abundance, fidelity
and endemism perspectives, we found out that most of these were
either rare, habitat specific or endemic to the region. Some of
the species are listed here as examples which provide provisioning services to the local people and their population is decreasing
at alarmingly rapid rate – Aesculus indica (timber and furniture
wood), Crataegus oxycantha (Fruit and medicine), Euphorbia wallichii (ethnomedicine), Indigofera heterantha (ethnomedicine and
grazing), Prunus cerosioides (furniture wood, fuel wood, fruit and
ethnomedicine), Hypericum perforatum (Ethnomedicine), Geranium
nepalense (Ethnomedicine), Juniperus squamata (fuel wood and

180


Table 1
Results of the Mantel statistics executed between floristic and environmental data matrices.
S.No

Main matrix i.e., {144 samples (rows) × 198 species
(columns)} examined with second matrix of;

t

r

p value

1
2
3
4
5
6

144 Samples (rows) × 5 Env. variables (columns)
144 samples (rows) × 1 env. variable (Elevation)
144 Samples (rows) × 1 Env. variable (Aspect)
144 Samples (rows) × 1 Env. variable (Soil depth)
144 Samples (rows) × 1 Env. variable (Graz. pressure)
144 Samples (rows) × 1 Env. variable (Soil pH)

22.7673
22.7260
17.2970
13.2412
2.2217
1.6440

0.4828
0.4821
0.1632
0.3061
0.0619
0.0383

0.0000
0.0000
0.0000
0.0000
0.0265
0.1005

Fig. 3. CCA, data attribute plots of Pinus wallichiana; Sambucus weightiana and I. bicolour (left to right) the top three indicator species of the valley bottom or lower elevation
(2400–2800 m) habitats (Association 1). Blue circles show the locations and abundance of the indicator species of association – 1, with respect to associated environmental
variables. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of the article.)

Fig. 4. CCA, Data attribute plot of Abies pindrow, Betula utilis and Achillea millefolium (left to right) the top three indicator species of the middle elevation (2800–3300 m)
Northern aspect habitats (Association 2). Red triangles show the locations and abundance of the indicator species of association – 2, with respect to associated environmental
variables. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of the article.)

Fig. 5. CCA, Data attribute plot of Juniperus excels, Artemisia brevifolia and Eremurus himalaicus (left to right), the top three indicator species of the middle elevation
(2800–3300 m) Southern aspect habitats (Association 3). Green square boxes show the locations and abundance of the indicator species of association–3, with respect to
associated environmental variables. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of the article.)


181

Fig. 6. CCA, Data attribute plot of R. austral, S. cuneata and B. strachyei (left to right), the top three indicator species of the high elevation (3300–3900 m) timber line (subalpine)
habitats (Association 4). Brown boxes show the locations and abundance of the indicator species of association – 4, with respect to associated environmental variables. (For
interpretation of the references to color in this figure legend, the reader is referred to the web version of the article.)

Fig. 7. CCA, Data attribute plot of A. falconeri, Iris hookeriana and R. hirtellus (left to right), the top three indicator species of the highest elevations (above 3900 m), alpine
habitats (Association 5). Purple stars show the locations and abundance of the indicator species of association – 5, with respect to associated environmental variables. (For
interpretation of the references to color in this figure legend, the reader is referred to the web version of the article.)

ethnomedicine), and Viburnum grandiflorum (fuel wood, fruit and
ethnomedicine).
6. Discussion
6.1. Role of native vegetation in supporting human livelihoods
Our findings confirm that vegetation offer valuable ecosystem
services to inhabitants of the region. The questionnaire analyses
indicate that people of the Naran Valley possess precious knowledge of local plant biodiversity and the services it can provide
are immensely important to them. These traditional human communities utilize the plant species according to their indigenous
knowledge. In the Naran Valley various anthropogenic activities
have an influence on the vegetation. These include multipurpose
plant collection, forest cutting, grazing pressure and expansion of
agricultural land. Vegetation zones 1–3 were influenced by all of
these factors, while 4 and 5 were mainly affected by grazing and
plant collection. More detailed information on the utilization of
plant species were discussed in our recent paper (Khan et al., 2013b)
but it is evident that grazing pressure was most severe on herb and
shrub species especially at higher elevation during the short summer. Anthropogenic pressure on the natural vegetation has been
observed in adjacent hilly areas of the Hindu Kush and the Karakorum mountain ranges (Inam-ur-Rahim Maselli, 2004; Kukshal et al.,
2009; Peer et al., 2001). It is noteworthy to mention those grazers in
particular and other indigenous people of this region in general who
collect and utilize medicinal plant species, some of which they sell
in the local markets. A similar land use pattern has been reported in
other studies from adjacent mountain valleys (Khan et al., 2011a;

Kassam et al., 2011) and also other parts of the world (Chowdhury
and Koike, 2010; Jones, 2000; Maurer et al., 2006). In the Himalayas,
there is long-established ethnoecological knowledge of plant use
for human well-being; however, this is at risk of loss together with
the rising pressure to the species themselves as a consequence of a
series of anthropogenic influences (Khan et al., 2013a). Ecological
Indicators mentioned in our findings are also of great importance
from indigenous knowledge point of view that is also an alarming
signal for species and habitat conservation.
6.2. Mountain vegetation, indigenous people and provisioning
services
Landscape dynamics associated with anthropogenic activities
and global climate change will likely reduce the ecosystem services
associated with natural biodiversity. Sustainable utilization and
conservation of biodiversity are essential for the continuation of
ecosystem functioning (Srivastava and Vellend, 2005). Organizations and ecosystem managers should pay attention to these issues
in order to minimize the present losses in natural ecosystems
and to plan for their sustainable future (Prato, 2007; Stewart and
Pullin, 2008; Whaley et al., 2010; Zavaleta and Hulvey, 2004). The
indigenous people in the study area gave less attention to long term
ecosystem services (i.e., regulating and supporting services) since
they were focused on their marginal and short time benefits (i.e.,
provisioning services). They illicitly utilized plants for a number
of purposes including timber, fuel, medicines, food, grazing and
fodder. Law enforcement agencies cannot access fully this remote
valley due to low budgets, harsh terrain and climate and institutional dishonesty (Khan et al., 2013c). Local residents, especially of

182


Table 2
Top 3 indicator (characteristic) plant species of each of the 5 habitat types (vegetation zones) based on constancy, fidelity and indicator species analysis (ISA).
Com. 1

Com. 2

Com. 3

Com. 4

Com. 5

Valley bottom, lower elevations
(2400–2800 m) habitats
(Pinus-Sambucus-Impatiens
association) Total number of
stations = 24
Indicator (characteristic) species of the
community
Pinus wallichiana Jackson
Sambucus weightiana Wall. Ex Wight &
Arn
Impatiens bicolor Royle
Northern aspect, middle elevations
(2800–3300 m) habitats (Abies-Betula
Achillea association) Total number of
stations = 34
Abies pindrow Royle
Betula utilis D. Don
Achillea millefolium L.
Southern aspect, middle elevations
(Juniperus-Artemisia-Eremurus
stations = 28
Juniperus excelsa M.Bieb
Artemesia brevifolia L.
Eremurus himalaicus Baker
Tree line line, higher elevations
(Rheum-Sibbaldia-Bergenia
stations = 31
Rheum australe D.Don
Sibbaldia cuneata O. Kuntze
Bergenia strachyei (Hook. f. & Thoms)
Engl
Alpine, highest elevations
(Aster-Iris-Ranunculs association)
Total number of stations = 27
Aster falconeri (C. B. Clarke) Hutch
Iris hookeriana Foster
Ranunculus hirtellus Royle ex D. Don

Monte Carlo test of significance of observed maximum indicator value for Species based on 4999
permutations. Random number seed: 2324 (Groups were defined by values of Soil depth classes; Max
grp = 3 = maximum soil depth)

Const

Fid. class

46
96

11
23

% const

4
3

Max grp

Mean

S. Dev

p * value

32
59

3
3

Obs IV

9.7
16.4

3.31
3.79

0.0004
0.0002

14
58
3
3
50
15.3
4.06
0.0002
permutations. Random number seed: 527 (Groups were defined by values of Aspect; Max grp = 1 = Northern
aspect)
14
41
3
1
34
12.0
2.5
0.0002
10
29
4
1
24
8.8
2.1
0.0002
15
44
4
1
25
11.6
2.5
0.0006
permutations. Random number seed: 527 (Groups were defined by values of Aspect; Max grp = 0 = Southern
aspect)

19
68
4
0
35
13.1
2.5
0.0002
27
96
3
0
50
23.0
3.1
0.0002
22
79
4
0
35
12.8
2.6
0.0002
permutations. Random number seed: 2673 (Groups were defined by values of Elevation m.a.s.l; Max
grp = 33–39 = 3300–3900 m i.e., higher elevations)

13
16
13

42
52
42

4
3
4

39.5
38.5
39

20.3
19.7
14.7

10.7
10.4
10.6

5.05
4.56
5.91

0.0508
0.0504
0.0504

permutations. Random number seed: 2673 (Groups were defined by values of Elevation m.a.s.l; Max
grp = 39–44 = above 3900 m i.e., highest elevations)
13
25
6

48
93
22

the older generation, preferred to live in the valley because of the
existing provisioning ecosystem services. However, members of
the younger generation tend to leave these rural spaces in search
of education, facilities and an easy modern life thus they were less
aware of or dependent on ecosystem services but human population pressure is till maintained as nomads and seasonal grazers
from other regions visit the area quite regularly. These effects are
becoming worse as the indigenous people neither have sufficient
facilities locally nor can they compete in the urban societies. The
traditional indigenous knowledge of the people is decreasing day by
day and the younger generation do not know about the importance
of that knowledge. These problems threaten the sustainability of
the mountain ecosystem. Plant biodiversity can be restored and
the risks of degradation may be combated, if measures like reforestation, establishment of protected areas, improved awareness by
the people to use resources sustainably and ex situ conservation

5
4
1

41
41
41

43.2
20
67.1

10.4
10.9
11.5

6.31
5.4
8.39

0.0056
0.0502
0.0022

of rare species are initiated (Brown and Shogren, 1998; Muzaffar
et al., 2011; Niemi and McDonald, 2004; Parody et al., 2001;
Pereira et al., 2005). Long term management and conservation
strategies might, therefore, have optimistic outcomes for the
maintenance and increase in mountain biodiversity and ecosystem
services which will also have a positive impact on the lowland
ecosystems which depend on the sustainability of these mountainous ecosystems. Analyses showed that indicator and endemic
species with higher fidelity values are depleting rapidly in the
region.
6.3. Ecological indicators, traditional perception and
conservation efforts
Assessment of conservation status cannot be absolute and
requires periodic revision but taking various criteria at a time

Table 3
Summary of the first four axes of the CCA for the species data (using importance value (IV) data).
Axes

1

Eigen values
0.410
0.870
Species-environment correlations
3.820
Cumulative percentage variance of species data
48.50
Species-environment relation
Summary of Monte Carlo test (499 permutations under reduced model)
Test of significance of first canonical axis
0.412
Eigen value
5.460
F-ratio
0.002
P-value

2

3

4

Total inertia

0.190
0.80
5.50
70.40

0.12
0.70
6.60
84.30

0.08
0.70
7.40
94.20

10.960

Test of significance of all canonical axes
Trace
F-ratio
P-value

0.858
2.355
0.002


validate the conclusion for a considerable period of time or specific
geographic locality (Broennimann et al., 2005; Domínguez Lozano
et al., 2003). Based on definite ecological criteria, prioritizing certain communities, habitat types and ecosystems is useful in long
term management planning nevertheless each species should keep
its own individual importance (Vellak et al., 2009). In the first part of
the study the objective was quantification of plant species and communities with the crucial target of assessing the conservation value
of the species using the criteria of indicators and fidelity. This vegetation study is distinctive as it identified the indicator species based
on their fidelity and abundance. Such ecological indicators can be
used to understand the requirements of various natural habitats
(Khan et al., 2012b; Kati et al., 2009; Tarrasón et al., 2010). Indicator species (statistically significant) were selected from each of the
tree, shrub and herb layers. Short summers, deep snow, low temperatures, intense solar radiation and cold strong winds result in
xeric conditions for plant growth and hence the ␤-diversity gradually decreases both along the altitudinal and latitudinal gradients
in high mountain valleys such as the Naran. Although drawing a
sharp line in any natural mountain ecosystem is difficult as there are
rapid changes in micro climatic and edaphic conditions but based
on such indicators, it is possible to delimit vegetation zones and
associations. In the western Himalayas, both at station and community levels the plant species richness and diversity is strongly
influenced by elevation, aspect and soil depth, with similar patterns
of diversity across altitudinal gradients observed in other studies in
the Himalayan regions (Kharkwal et al., 2005; Tanner et al., 1998;
Vázquez and Givnish, 1998).
In the second part the same vegetation was evaluated from the
perspective of its traditional utilization. In the remote valleys of the
Himalayas people exploit natural resources and vegetation during
their seasonal movements. Due to this extensive interaction with
plant biodiversity these indigenous people have valuable knowledge of provisioning ecosystem services both in the recent past
and at present. Trends of either increase or decrease in the population and abundance of various plant species based on people’s
indigenous knowledge reconfirm our findings based on abundance,
fidelity, constancy and IUCN criteria. In addition this is the first
ever vegetation study of the Naran region that is combined with
an assessment of social perception about that plant biodiversity. To
date there has been very limited and fragmented published work on
IUCN red list of plant species from the Pakistani part of the Himalaya
and Hindu Kush mountain ranges (and only for few species) (Alam
and Ali, 2010, 2009; Ali, 2008; Ali and Qaiser, 2011). Indicator
species identified in this study can be used as a basis for extensive
conservation studies on biodiversity at a regional and even country level in the fashion of most European and some Asian countries
where the vegetation has thoroughly been mapped by ecologists
(Giam et al., 2010; Noroozi et al., 2008; Odland, 2009; Roy et al.,
2000; Rodwell et al., 1997, 1995; Brown et al., 1993; Sutherland
et al., 2008). Notably several plant species were found that are
endangered either globally or regionally. Four (4) of the recorded
species were listed by CITES i.e., Dioscorea deltoidia, Podophyllum hexandrum, Cypripedium cordigerum and Dactylorhiza hatagirea.
Other species such as Acer caesium, B. utilis, Ephedra gerardiana,
Fritillaria roylei, Gentiana kurro, Hyoscyamus niger, Inula grandiflora,
R. australe and Rhododendron hypenanthum are endangered in the
region. In addition, species such as Aconitum heterophyllum, Bistorta
amplexicaulis, Cedrus deodara, Colchicum luteum, Geranium wallichianum, I. hookeriana, Juglans regia, Paeonia emodi, Plantago major,
Polygonatum verticillatum and Viola canescens, are nearly threatened or vulnerable at a country level.
An awareness culture should be promoted among the locals
so that they value and own the biodiversity and ecosystem
services around them. This can be done by arranging workshops, lectures and seminars. The people can only own plant

183

biodiversity and their associated ecosystem services if they are
involved in the regeneration and conservation processes. Recent
use of indigenous knowledge in conservation led to the new idea of
‘ethno-conservation’ in the late 1990s which is now a popular conservation approach around the globe (Jules et al., 2008; Khan et al.,
2013c; Negi, 2010; Rajeswar, 2001). Future work should address
the long lasting consequences of the loss of plant biodiversity for the
sustainability of ecosystem services other than just provisioning
services i.e., also regulatory, supporting and cultural services.
Acknowledgements
Higher Education Commission of Pakistan and Hazara University Mansehra are very much acknowledged for their financial
support to this study under the Post Quake Faculty Development
Research Plan (PQDRP).
Appendix A. Supplementary data
Supplementary data associated with this article can be
found, in the online version, at http://dx.doi.org/10.1016/
j.ecolind.2013.09.012.
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