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1 August 2016 Ecological Assessment of Plant Communities and Associated Edaphic and Topographic Variables in the Peochar Valley of the Hindu Kush Mountains
Aziz Ur Rahman, Shujaul Mulk Khan, Salman Khan, Ahmad Hussain, Inayat Ur Rahman, Zafar Iqbal, Farhana Ijaz
Author Affiliations +
Abstract

This study quantified the effect of environmental variables on plant species composition in the Peochar Valley, located in the Hindu Raj mountains of the Hindu Kush. A mixture of quadrat and transect methods were used. Quadrat sizes were 10 × 10 m, 2 × 5 m, and 1 m2 for trees, shrubs, and herbs, respectively, determined using the minimal area method. Twenty-seven stations were established along 6 elevation transects on slopes with various aspects. Density, cover, and frequency were recorded for all species in each quadrat. Aspect, elevation, rock types, soil nature, and grazing pressure were also considered as edaphic and topographic variables. Preliminary results showed that the Peochar Valley hosts 120 species. Presence/absence data for these species were analyzed with cluster and 2-way cluster techniques to elaborate species composition in the study area; this resulted in 4 plant communities. Species abundance and environmental data matrices were developed to evaluate the ecological gradient of vegetation through canonical correspondence analysis. Of the environmental variables, elevation, aspect, grazing pressure, soil depth, and rock type showed a significant effect on species composition and diversity. We also identified the dominant and rare plant species in each plant community based on their low importance value indexes. Conservation measures are recommended for all flora of this valley and for rare species in particular.

Introduction

There is a growing trend in ecological research to study the relationships between abiotic and biotic components of an ecosystem (Tavili and Jafari 2009; Khan et al 2016). Vegetation is the expression of environment in a specific habitat at a specific time and hence needs to be properly studied in relation to its surroundings at both species and community levels (Khan et al 2012). Vegetation composition and structure are influenced by various natural and anthropogenic disturbances on both local and broader scales (Ribichich and Protomastro 1998). It is thus imperative to understand the patterns of distribution of plant species and the influencing factors at these different scales (Bai et al 2004).

Plant species in forest ecosystems have faced various environmental changes over their long ecological and evolutionary histories. Some of these changes have been slow, but others have occurred quite rapidly in the recent past (Bryson et al 1970). The tremendous increase in research on environment-related subjects in recent decades explains the impacts of rapid changes in the environment in general and vegetation in particular. The most important factors influencing the future of plant species are the degree and rate of changes in the surrounding environment. Such changes may have serious consequences for the ability of plant species, especially those with less genetic diversity and narrow ecological amplitude, to adjust to changing conditions (Critchfield 1984; Davis and Zabinski 1992). Moreover, the rate of environmental change is so rapid that plant species with long generation times may be unable to adapt rapidly enough to keep pace (Davis and Shaw 2001).

Some species adapt to changing conditions by changing their growth forms, development, and life cycles. Changes in species life cycle ultimately bring changes in the formation of plant communities and hence ease the way for invasive species. In such scenarios, it becomes imperative for plant researchers to study environmental variations in terms of how these affect species composition and community structure (Økland and Eilertsen 1993; Guisan and Zimmermann 2000). Abiotic, biotic, historical, and human factors contribute diversity and variation in the distribution of plant species and communities (Brown 1984). The nature of these variations in temperate forests of developing countries is still insufficiently documented and analyzed (Benzing 1998).

Northern Pakistan is one such example, with mountainous temperate forests, mostly coniferous (Ilyas et al 2012), that cover an area of approximately 5% of the forest ecosystem in the country. The natural forest cover is decreasing at the rate 0.75% annually (FAO 2009). In certain regions that are difficult to study (eg Chitral, Nanga Parbat, and Naran), plant researchers have sought to elaborate the altitudinal gradient complex of the vegetation. These authors have also focused on other climatic factors, such as rainfall in relation to plant distribution, in these fragile ecosystems (Dickoré and Nüsser 2000; Nüsser and Dickoré 2002). In addition to natural hazards and other factors responsible for deterioration of natural ecosystems, anthropogenic and edaphic drivers play a vital role in vegetation dynamics. This project was initiated to better understand the role of such factors in the establishment of plant communities.

Little effort has been made to undertake quantitative analysis of the plant communities along geoclimatic environmental gradients in Hindu Kush valleys. To identify the effective determinants of local or regional vegetation and biodiversity patterns, such studies are imperative. This study seeks to help fill this knowledge gap. Moreover, there have been no previous quantitative studies of the vegetation in this valley. This study was designed to test the hypothesis that elevation, aspect, and edaphic factors are the main determinants of the vegetation of the Peochar Valley, with the following specific research objectives:

  • 1.  Use phytosociological and quantitative statistical methods to describe and analyze plant species and community diversity in the Peochar Valley, Hindu Kush.

  • 2.  Identify the edaphic and topographic factors responsible for plant community and distribution patterns along the gradients of elevation, aspect, and rock type.

Material and methods

Study area

The Peochar Valley is located in Tehsil Matta of the famous Swat District (Figure 1), in the Hindu Raj Mountains of the greater Hindu Kush range. It is located at 35°07′ to 35°22′N and 72°29′ to 72°39′E and has a total area of 4877 ha. About half (2450 ha) of the total area is cultivated, and the rest (2427 ha) is forest range land. The valley is bounded by the valley of Nihak Dara on the west, the Beha Valley on the north, the valley of Tehsil Kabal on the south, and the Shawar Valley on the east (Figure 1) (Islam et al 2006; Khan et al 2007). Most residents are Gujjars, descendants of the ancient Kushan dynasty (Lyon 2002), Yousafzai Afghans, and a few Sayed families. Pushto and Gujri are the main languages (Ahmad and Ahmad 2003; Islam et al 2006).

FIGURE 1 

Map of the Peochar Valley. (Map by Aziz Ur Rahman and Shujaul Mulk Khan)

i0276-4741-36-3-332-f01.tif

The area comprises moist temperate forests (Beg and Khan 1974); the valley is in the monsoon belt. The upper part of the valley has moist temperate and alpine ecosystems with coniferous forests. Because of its varied climate, the valley is home to a variety of plant species, a number of which are edible, aromatic, or medicinal (Sher et al 2007; Ahmad et al 2015).

Methodology

Quantitative ecological techniques were applied to evaluate species composition, distribution pattern, and abundance under the influence of edaphic and topographic variability in the targeted region. This study was conducted in summer 2013. Elevation transects were established at sites with various mountain aspects—north, south, west, and east faces. Stations were established at 200-m elevation along each transect, resulting in 27 stations. Quadrats were placed systematically along each transect at 200-m intervals using global positioning system (GPS) technology (Khan et al 2013). Quadrat sizes, determined using the minimal area method, were 10 × 10 m for trees, 2 × 5 m for shrubs, and 1 m2 for herbs (Salzer and Willoughby 2004). Three quadrats were placed at the same elevation (Khan et al 2011, 2013). Edaphic and topographic factors such as aspect, elevation, and soil physical and chemical features were recorded, while recent anthropogenic impacts like grazing pressure were estimated, based on observations, on a scale of 1–5 (low to high). Plant specimens were collected from each quadrat and labeled. Specimens were identified using Flora of Pakistan and other literature (Ali and Qaiser 1993–2007). The collected specimens were mounted on standard sheets and kept in the herbarium of the University of Haripur.

Analyses

Floristic composition (presence or absence), density, and cover for all higher plant species were recorded in each quadrat. Diameter at breast height (Dbh) was measured for tree species. Stem basal area of each tree species was calculated as πr2 or (Dbh/2)2 × 3.143. Relative values of density, cover, and frequency of species in each transect were also calculated and summed to get the importance value index (IVI). Based on IVI, rare species were identified for the region and for each plant community.

Soil samples up to 30 cm in depth were collected in soil sampling tubes from each quadrat. The collected samples were brought to the laboratory and dried at room temperature, ground, thoroughly mixed, and sieved through 2-mm mesh to form 1 composite sample. Physiochemical analysis of these soil samples was done in the soil science laboratory of the Agricultural Research Institute, Tarnab Farm, Peshawar.

Soil samples were analyzed using standard methods for various physical and chemical properties. Soil texture was determined using a hydrometer (Page 1982), lime content was determined using acid neutralization (Cottenie 1980), organic matter was determined using the Walky-Black procedure (Nelson and Sommers 1982), soil nitrogen was determined using the Kjeldhal method (Bremner and Mulvaney 1982), soil pH was determined by testing a 1:5 soil:water suspension with a pH meter, electrical conductivity was determined by testing a 1:5 soil:water suspension with a conductivity meter (Rhoades 1990), and extractable phosphorus and potassium were determined using the method described by Soltanpour (1985).

Results

Species composition in the Peochar Valley

A total of 120 species belonging to 57 families were collected along 5 elevation transects from the Peochar Valley, including 12 (10%) tree, 25 (21%) shrub, and 83 (69%) herb (Figure 2). The most dominant family was Poaceae, with 14 species (12% of all species), followed by Rosaceae, with 13 species (11%). Other dominant families were Lamiaceae, with 10 species, and Asteraceae, with 5 species.

FIGURE 2 

Proportion of trees, shrubs, and herbs in Peochar Valley vegetation, summer 2013.

i0276-4741-36-3-332-f02.tif

Plant communities and habitat types

Presence/absence (1/0) data were analyzed using cluster and 2-way cluster analyses via PCORD version 5 (Leps and Smilauer 2003). Cluster analysis placed the 27 stations (representing different elevations) in 4 groups (plant communities) (Figure 3). These 4 groups are described later. Rare herb species in the region, from all plant communities, are shown in Supplemental material, Table S1 ( http://dx.doi.org/10.1659/MRD-JOURNAL-D-14-00100.S1).

FIGURE 3 

Results of cluster analysis showing 4 plant communities. T, transect; El C, elevation class; El C1 = 1950–2200 masl; El C2 = 2200–2400 masl; El C3 = 2400–2600 masl; El C4 = 2600–2800 masl; El C5 = 2800–3000 masl.

i0276-4741-36-3-332-f03.tif

Pinus–Sarcococca–Dryopteris community: This community was established at lower elevations (1975–2297 m above sea level [masl]). Pinus wallichiana, Sarcococca saligna, and Dryopteris stewartii, on which the community name is based, were the characteristic species of the tree, shrub, and herb layers, respectively. Other dominant tree species were Quercus dilatata and Taxus baccata. The rare tree species in this community were Picea smithiana, Ilex dipyrena, and Quercus incana. The shrub layer was dominated by Berberis lyceum and Wikstroemia canescens; rare species were Sorbaria tomentosa, Rosa moschata, and Rubus ulmifolius. Dominant species of the herb layer were Eleusine indica, Themeda anathera, Brachiaria ramosa, and Fragaria vesca. Rare herbs were Epipactis veratrifolia, Geranium wallichianum, Cerastium fontanum, Podophyllum emodi, and Myosotis caespitosa. Data-attribute plots of indicator species of this community show that grazing pressure has had less effect on these species than on other communities. This community was mainly observed on rocky steep slopes with shallow soil.

Picea–Parrotiopsis–Fragaria community: This community was found at midelevations (2296–2658 masl). P. smithiana characterized the tree layer. Other dominant species in the tree layer included Abies pindrow and P. wallichiana; rare tree species were Acer cappadocicum, Celtis australis, and T. baccata. In the shrub layer, Parrotiopsis jacquemontiana was the indicator or dominant species; codominant species were Viburnum grandiflorum and W. canescens. Parrotiopsis is monotypic genus endemic to the Hindu Kush–Himalayas. Rare species of the shrub layer were Rubus sanctus, R. ulmifolius, and R. moschata. The characteristic species of the herb layer was F. vesca; other dominant species included Trifolium repens, Dryopteris filix-mas, Viola canescens, and Artemisia vulgaris. Rare species were Solanum nigrum, Bergenia ciliata, Phytolacca acinosa, Bistorta amplexicaulis, and Polygonatum verticillatum. Of the characteristic species for each layer, the IVI was 1.15 for P. smithiana, 0.727 for P. jacquemontiana, and 11.47 for F. vesca. This community was present mostly on northern slopes.

Abies–Viburnum–Carex community: This community was found at higher elevations (2536–2708 masl). Characteristic species of tree and shrub layers were A. pindrow and V. grandiflorum (IV = 1.53). The other dominant species of the tree layer were P. wallichiana and P. smithiana and of the shrub layer were R. moschata and Indigofera heterantha. Rare tree species were A. cappadocicum, I. dipyrena, and Aesculus indica; rare shrub species were Cotoneaster nummularius, Plectranthus rugosus, and S. tomentosa. The characteristic species of the herb layer was Carex schlagintweitiana (IV = 22.71). The dominant species of this community were Sibbaldia cuneata, Thymus linearis, Poa annua, and B. amplexicaulis; rare species were Skimmia laureola, Trillium govanianum, Ajuga parviflora, G. wallichianum, and Agrimonia eupatoria. This community was mainly established on southern slopes.

Indigofera–Plectranthus–Viola community: This community was located at 2485–2937 masl. There is no dominant tree species, though a few rare trees were present, including P. wallichiana, P. smithiana, I. dipyrena, and Prunus cornuta. The characteristic shrub species were I. heterantha and P. rugosus. The dominant shrub species was V. grandiflorum, and rare shrubs were B. lyceum and R. moschata. The characteristic species of the herb layer was Viola bicolor, with codominant species such as C. schlagintweitiana, T. govanianum, T. linearis, and Galium aparine. Rare herbs in this community were Hypericum perforatum, Leonurus cardiaca, Origanum vulgare, Oxalis corniculata, and Desmodium laxiflorum. The characteristic tree, shrub, and herb species in this community were I. heterantha, P. rugosus, and V. bicolor, with IVIs of 1.37, 1.06, and 11.15, respectively. This community had a wider range of occurrence in varying habitats.

Environmental gradient

Species and environmental data matrices were analyzed together in CANOCO software version 4.5. Results showed that environmental (edaphic, topographic, and anthropogenic) variables had significant effects on species composition and diversity. Significant environmental variables were elevation, aspect, grazing pressure, pH, soil depth, and presence of organic matter, phosphorus, potassium, silt, and rocky soil. It was hypothesized that aspect and elevation could be the main driving forces of vegetation variation in the valley, and the low P value (≤0.012) showed that the results were highly significant in terms of test statistics. Canonical correspondence analysis (CCA) of environmental data identifies the main driving environmental variable for the constitution of a specific community type. CCA results showed that both the composition and the abundance of plant species were a reflection of differences in these environmental variables.

The CCA ordination procedures for samples and species indicated that the first axis was primarily correlated with elevation and aspect, the second axis was correlated with soil depth and grazing, and the third axis was correlated partially with grazing pressure, soil depth, and rock types. The fundamental ecological gradient of the first axis can be clearly recognized from the biplots, relating key environmental variables to plant species distribution (Figure 4) and elevation-based stations (Figure 5), which confirm each other. Pearson's correlation with ordination axes for the CCA plot pointed out a significant correlation of axis with the geoclimatic variables (elevation and soil depth). Data attribute plots strengthened the position of the indicator or characteristic species of each community (the species from which the communities' names were derived).

FIGURE 4 

Results of CCA showing the biplot distribution of 120 plant species and 10 environmental variables.

i0276-4741-36-3-332-f04.tif

FIGURE 5 

Results of CCA showing the biplot distribution of 27 elevation classes in relation to 10 environmental variables. T, transect; El C, elevation class. El C1 = 1950–2200 masl; El C2 = 2200–2400 masl; El C3 = 2400–2600 masl; El C4 = 2600–2800 masl; El C5 = 2800–3000 masl.

i0276-4741-36-3-332-f05.tif

Discussion

During the last several decades, studies of environmental changes have emerged more rapidly than other studies in the life sciences. The effects of these environmental changes have been intensified by recent anthropogenic activities (Davis and Zabinski 1992; Ali et al 2002). In mountain ecosystems, the initial trophic level is made up of vegetation; therefore, proper quantification and documentation of vegetation in relation to the abiotic environment is required (Khan et al 2012).

In terms of floristic groups, our findings can be compared with those of other studies from mountain valleys in the Himalayas, where plant families like Poaceae, Asteraceae, Lamiaceae, and Rosaceae were the most representative of the vegetation (Khan et al 2011, 2015; Shaheen et al 2011). Our study confirms Poaceae with 14 plant species (12% of all species), Rosaceae with 13 species (11%), Lamiaceae with 10 species (9%), and Asteraceae with 5 species (4%).

Plant species are successively replaced as a function of variation in the environment; hence, composition and distribution of plant species in communities vary along ecological gradients. The 4 plant communities were determined through way cluster analysis and the IVI (Figure 6). Influencing edaphic factors and their strength are shown in Table 1.

FIGURE 6 

The 20 rare herb species with the lowest IVIs in the study area.

i0276-4741-36-3-332-f06.tif

TABLE 1 

Key environmental variables in the 4 plant communities.

i0276-4741-36-3-332-t01.tif

Other studies (Desalegn 2002; Shaheen et al 2011; Khan et al 2012) have also found a relationship between plant communities and environmental gradients. The dominant tree species in most of the study area (communities 1–3) are P. wallichiana, P. smithiana, and A. pindrow; a similar pattern was reported for the Naran Valley of the western Himalayas (Khan et al 2011).

CCA was used to evaluate the distribution pattern of 120 plant species in 27 elevational stations under the influence of various environmental variables. Of the environmental variables, elevation, aspect, grazing pressure, pH, depth of soil, and presence of organic matter, phosphorus, potassium, silt, and rocky soil significantly (P ≥ 0.0120) affect species composition and community classification (Table 2). Similar impacts on species composition were reported for adjacent temperate regions of Pakistan (Khan et al 2012).

TABLE 2 

Results of CCA.

i0276-4741-36-3-332-t02.tif

The environment has been changing on local and global scales because of anthropogenic activities coupled with climate change (Schwartz et al 2000; Sax and Gaines 2003). Grazing pressure can create a severe threat to plant biodiversity (Mayer et al 2009) and species composition. Major palatable species in the Peochar Valley are R. moschata, R. ulmifolius, C. fontanum, and G. wallichianum. T. govanianum was scarcely present in the area at high elevations. Because of its high medicinal value, this species has been greatly affected by anthropogenic pressure. In the tree layer, Q. dilatata and Q. incana were rare and found in lower altitudes, which makes it easy for inhabitants of the area to use them for animal fodder and fuel.

Soil in the Peochar Valley is mostly sandy loam. Similar soil was reported in vegetation studies of the adjacent Girbanr Hills, Swat District, Pakistan (Hussain et al 1995). The amount of calcium carbonate increases with elevation from 8.55 to 9.18%. Phosphorus also increases in area from 11.73 to 29.42 mg kg−1. Potassium ranged from 113.4 to 171 mg kg−1. Organic matter showed less difference, ranging from 1.3 to 1.7%. The area has mostly rocky soil, with 60.5 to 66.73% sand. Soil was weakly acidic, with pH ranging from 6.5 to 6.8.

In mountainous regions, elevation shows the greatest effect in limiting plant species and community types (Chawla et al 2008). Numerous studies have concentrated on variations of species richness and diversity along elevation gradients in hilly areas to find the patterns of distribution (Lomolino 2001). We found a range of occurrences of various indicator species as well. For example, P. wallichiana was found at elevations of 1990 to 2870 masl but most abundantly at 1990 to 2297 masl. A. pindrow was distributed dominantly at high elevations, from 2296 to 2708 masl. P. smithiana ranged from 2085 to 2937 masl and was dominant at 2296 to 2658 masl. Q. dilatata was found at lower elevations, from 1975 to 2205 masl, with Q. incana at 2085 masl. Other studies in the Hindu Kush–Himalayas have documented similar elevation ranges for these characteristic species of temperate ecosystems (Dickoré 1995; Shaheen et al 2012).

Most of the species are related to a particular habitat and found to be richer around their particular environmental optimum. P. jacquemontiana and Buxus wallichiana were also recorded in the region at lower elevations of 1990 to 2296 masl. These species are endemic to the western Himalaya, especially Kashmir, Murree, Hazara, and Swat, at elevations from 1200 to 2800 masl (Takhtajan et al 1986). Three species of the Buxaceae family have been reported from Pakistan; 2 of them were recorded during this study in the Peochar Valley: B. wallichiana and S. saligna. Parrotiopsis is the only species in the genus (mono-specific). Therefore, proper measures for conservation of these rarely occurring endemic species must be given high priority.

These findings can be used for conservation of rare species—that is, species that have restricted distribution and special or fragmented habitats, are endemic, and decrease more quickly in population. These results also open new ways to study and manage ecosystem services and environmental sustainability. Our findings, based on ecological approaches, can be used as one of the criteria for prioritization of protected areas, special habitats, and species of conservation importance.

Although the Hindu Kush region is famous for its indicator and endemic flora and unique ecosystems, there has been limited research on the region's endangered plant species. One of the reasons for this is the political conflict of the last few decades, which has prevented detailed work for environment sustainability. Few comparators exist to evaluate endangered and critical species at the national level, but new efforts have emerged in recent years (Ali and Qaiser 1986; Ali 2008; Alam et al 2011; Shinwari and Qaiser 2011), though these described few species.

The quantitative description of plant abundance in our findings is distinctive, like the one described by Nüsser and Dickoré (2002) for Chitral Valley, and can be used for comparison, confirmation, and assessment of anthropogenic pressures while planning conservation strategies, as suggested by a number of people. Nevertheless, our study can be compared to other regions of the Himalaya in terms of potential for endemism and ecosystem services.

Documentation that critically evaluates plant biodiversity and the factors driving it at regional and national levels is mandated by law in the developed world. This approach can be adopted in the developing world as well for long-term management and sustainability of the natural environment.

ACKNOWLEDGMENTS

We are thankful to the local inhabitants and to members of the Pakistan Army, who helped us to complete our research in a geopolitically tense region, the Peochar Valley Mountains. We are also thankful to 2 anonymous reviewers for their insightful comments.

Supplemental material

TABLE S1 Detailed list of species of the Peochar Valley.

b) D, total density; C, cover; F, frequency; RD, relative density; RC, relative cover; RF, relative frequency.

Found at DOI:  10.1659/MRD-JOURNAL-D-14-00100.S1 (117 KB PDF).

REFERENCES

1.

Ahmad H, Ahmad R. 2003. Agroecology and biodiversity of the catchments area of Swat River. Nucleus 40:67–75. Google Scholar

2.

Ahmad H, Turk MO, Ahmad W, Khan SM. 2015. Status of natural resources in the uplands of the Swat Valley, Pakistan. In: Ozturk M, Hakeem KR, Faridah-Hanum I, Efe R, editors. Climate Change Impacts on High-Altitude Ecosystems. Cham, Switzerland: Springer International Switzerland, pp 49–98. Google Scholar

3.

Alam N, Khan SM, Ullah Z. 2011. Present Status of Sub Tropical Dry Deciduous Forests of Pakistan. Saarbrücken, Germany: Lambert Academic Publishing. Google Scholar

4.

Ali RJ, Adams DM, McCarl BA. 2002. Projecting impacts of global climate change on the US forest and agriculture sectors and carbon budgets. Forest Ecology and Management 169:3–14. Google Scholar

5.

Ali SI. 2008. Significance of flora with special reference to Pakistan. Pakistan Journal of Botany 40:967–971. Google Scholar

6.

Ali SI, Qaiser M., editors1986. A phyto-geographical analysis of the phanerogams of Pakistan and Kashmir. Proceedings of the Royal Society of Edinburgh. Section B. Biological Sciences 89:89–101. Google Scholar

7.

Ali SI, Qaiser M. 1993–2007. Flora of Pakistan. Vol194–215. Islamabad and Karachi, Pakistan. Google Scholar

8.

Bai Y, Broersma K, Thompson D, Ross TJ. 2004. Landscape-level dynamics of grassland-forest transitions in British Columbia. Rangeland Ecology & Management 57:66–75. Google Scholar

9.

Beg A, Khan A. 1974. Flora of Malakand Division, part 1 (A). Pakistan Journal of Forest 24:171–185. Google Scholar

10.

Benzing DH. 1998. Vulnerabilities of tropical forests to climate change: The significance of resident epiphytes. Climatic Change 39:519–540. Google Scholar

11.

Bremner J, Mulvaney C. 1982. Nitrogen—total. In: Page AL, editor. Agronomy Monograph, Methods of Soil Analysis. Part 2. Chemical and Microbiological Properties. Madison, WI: American Society of Agronomy, Soil Science Society of America, pp 595–624. Google Scholar

12.

Brown JH. 1984. On the relationship between abundance and distribution of species. American Naturalist 124(2):255–279. Google Scholar

13.

Bryson RA, Baerreis DA, Wendland WM. 1970. The character of late-glacial and post-glacial climatic changes. In: Wakefield D, Knox, J, editors. Pleistocene and Recent Environments of the Central Great Plains. Lawrence, KS: University Press of Kansas, pp 53–74. Google Scholar

14.

Chawla A, Rajkumar S, Singh K, Lal B, Singh R, Thukral A. 2008. Plant species diversity along an altitudinal gradient of Bhabha Valley in western Himalaya. Journal of Mountain Science 5:157–177. Google Scholar

15.

Cottenie A. 1980. Soil and Plant Testing as a Basis of Fertilizer Recommendations. FAO Soils Bulletin 38/2. Rome, Italy: Food and Agriculture Organization. Google Scholar

16.

Critchfield WB. 1984. Impact of the Pleistocene on the genetic structure of North American conifers. In: Lanner RM, editor. Proceedings of the 8th North American Forest Biology Workshop, Logan, UT, 30 Jul–1 Aug 1984. Bethesda, MD: Society of American Foresters, pp 70–118. Google Scholar

17.

Davis MB, Shaw RG. 2001. Range shifts and adaptive responses to Quaternary climate change. Science 292:673–679. Google Scholar

18.

Davis MB, Zabinski C. 1992. Changes in geographical range resulting from greenhouse warming: Effects on biodiversity in forests. In: Peters RL, Lovejoy TE, editors. Global Warming and Biological Diversity. New Haven, CT: Yale University Press, pp 297–308. Google Scholar

19.

Desalegn W. 2002. Plant Communities and Diversity Along Altitudinal Gradients from Lake Abaya to Chencha Highland[PhD thesis]. Addis Abababa, Ethiopia: Addis Ababa University. Google Scholar

20.

Dickoré WB. 1995. Systematische Revision und Chorologische Analyse der Monocotyledoneae des Karakorum (Zentralasien, West-Tibet). Flora Karakorumensis: 1. Angiospermae, Monocotyledoneae [Flora of the Karakorum, Including a Record of Species from Adjacent Mountains of High Asia (East Pamir, West Kunlun, Northeast Hindukush, Northwest Himalaya, West Tibet): 1. Angiospermae, Monocotyledoneae.]Stapfia Reports 39. Linz, Austria: Oberösterreichisches Landesmuseum, Biologiezentrum. Google Scholar

21.

Dickoré WB, Nüsser M. 2000. Flora of Nanga Parbat (NW Himalaya, Pakistan): An Annotated Inventory of Vascular Plants With Remarks on Vegetation Dynamics. Englera No 19. Berlin-Dahlem, Germany: Botanischer Garten und Botanisches Museum. Google Scholar

22.

FAO [Food and Agriculture Organization of the United Nations]. 2009. Pakistan Forestry Outlook Study. Working Paper No.APFSOS II/WP/2009/28. Bangkok, Thailand: FAO Regional Office for Asia and the Pacific. Google Scholar

23.

Guisan A, Zimmermann NE. 2000. Predictive habitat distribution models in ecology. Ecological Modelling 135:147–186. Google Scholar

24.

Hussain F, Ilyas M, Gil K. 1995. Vegetation studies of Girbanr Hills District Swat, Pakistan. Korean Journal of Ecology 18:207–218. Google Scholar

25.

Ilyas M, Shinwari ZK, Qureshi R. 2012. Vegetation composition and threats to the montane temperate forest ecosystem of Qalagai hills, Swat, Khyber Pakhtunkhwa, Pakistan. Pakistan Journal of Botany 44:113–122. Google Scholar

26.

Islam M, Ahmad H, Rashid A, Razzaq A, Akhtar N, Khan I. 2006. Weeds and medicinal plants of Shawar valley, District Swat. Pakistan Journal of Weed Science Research 12(1/2):83–88. Google Scholar

27.

Khan SM, Ahmad H, Ramzan M, Jan MM. 2007. Ethnomedicinal plant resources of Shawar Valley. Pakistan Journal of Biological Sciences 10(10):1743–1746. Google Scholar

28.

Khan SM, Harper D, Page S, Ahmad H. 2011. Species and community diversity of vascular Flora along environmental gradient in Naran Valley: A multivariate approach through indicator species analysis. Pakistan Journal of Botany 43:2337–2346. Google Scholar

29.

Khan SM, Page S, Ahmad H, Shaheen H, Harper D. 2012. Vegetation dynamics in the Western Himalayas, diversity indices and climate change. Science, Technology and Development 31:232–243. Google Scholar

30.

Khan SM, Page S, Ahmad H, Ullah Z, Shaheen H, Ahmad M, Harper D. 2013. Phyto-climatic gradient of vegetation and habitat specificity in the high elevation Western Himalayas. Pakistan Journal of Botany 45:223–230. Google Scholar

31.

Khan W, Khan SM, Ahmad H. 2015. Altitudinal variation in plant species richness and diversity at Thandiani sub forests division, Abbottabad, Pakistan. Journal of Biodiversity and Environmental Sciences 7:46–53. Google Scholar

32.

Khan W, Khan SM, Ahmad H, Ahmad Z, Page S. 2016. Vegetation mapping and multivariate approach to indicator species of a forest ecosystem: A case study from the Thandiani sub Forests Division (TsFD) in the Western Himalayas. Ecological Indicators 71:336–351. Google Scholar

33.

Leps J, Smilauer P. 2003. Multivariate Analysis of Ecological Data Using CANOCO. Cambridge, United Kingdom: Cambridge University Press. Google Scholar

34.

Lomolino M. 2001. Elevation gradients of species-density: Historical and prospective views. Global Ecology and Biogeography 10:3–13. Google Scholar

35.

Lyon SM. 2002. Power and Patronage in Pakistan [PhD thesis]. Canterbury, United Kingdom: University of Kent. Google Scholar

36.

Mayer R, Kaufmann R, Vorhauser K, Erschbamer B. 2009. Effects of grazing exclusion on species composition in high-altitude grasslands of the Central Alps. Basic and Applied Ecology 10:447–455. Google Scholar

37.

Nelson DW, Sommers LE. 1982. Total carbon, organic carbon, and organic matter. In: Page AL, editor. Agronomy Monograph: Methods of Soil Analysis. Part 2. Chemical and Microbiological Properties. Madison, WI: American Society of Agronomy, Soil Science Society of America, pp 539–579. Google Scholar

38.

Nüsser M, Dickoré WB. 2002. A tangle in the triangle: Vegetation map of the eastern Hindukush (Chitral, Northern Pakistan). Erdkunde 56(1):37–59. Google Scholar

39.

Økland RH, Eilertsen O. 1993. Vegetation–Environment Relationships of Boreal Coniferous Forests in the Solhomfjell Area, Gjerstad, S Norway. Sommerfeltia 16. Oslo, Norway: Botanical Garden and Museum, University of Oslo. Google Scholar

40.

Page AL. 1982. Methods of Soil Analysis. Part 2. Chemical and Microbiological Properties. Madison, WI: American Society of Agronomy, Soil Science Society of America. Google Scholar

41.

Rhoades JD, Miyamoto S. 1990. Testing soils for salinity and sodicity. In: Westerman RL, editor. Soil Testing and Plant Analysis. Madison, WI: Soil Science Society of America, pp 299–336. Google Scholar

42.

Ribichich AM, Protomastro J. 1998. Woody vegetation structure of xeric forest stands under different edaphic site conditions and disturbance histories in the Biosphere Reserve “Parque Costero del Sur,” Argentina. Plant Ecology 139:189–201. Google Scholar

43.

Salzer DW, Willoughby J. 2004. Standardize this! The futility of attempting to apply a standard quadrat size and shape to rare plant monitoring. In: Brooks MB, Carothers SK, LaBanca T, editors. The Ecology and Management of Rare Plants of Northwestern California. Proceedings of the Symposium of the North Coast Chapter of the California Native Plant Society. Arcata, CA. Sacramento, CA: The California Native Plant Society,pp 87–99. Google Scholar

44.

Sax DF, Gaines SD. 2003. Species diversity: From global decreases to local increases. Trends in Ecology & Evolution 18:561–566. Google Scholar

45.

Schwartz M, Brigham C, Hoeksema J, Lyons K, Mills M, Van Mantgem P. 2000. Linking biodiversity to ecosystem function: Implications for conservation ecology. Oecologia 122:297–305. Google Scholar

46.

Shaheen H, Khan SM, Harper DM, Ullah Z, Allem Qureshi R . 2011. Species diversity, community structure, and distribution patterns in western Himalayan alpine pastures of Kashmir, Pakistan. Mountain Research and Development 31:153–159. Google Scholar

47.

Shaheen H, Ullah Z, Khan SM, Harper DM. 2012. Species composition and community structure of western Himalayan moist temperate forests in Kashmir. Forest Ecology and Management 278:138–145. Google Scholar

48.

Sher H, Ajaz M, Sher H. 2007. Sustainable utilization and economic development of some plant resources in Northern Pakistan. Acta Botanica Yunnanica 29(2):207–214. Google Scholar

49.

Shinwari ZK, Qaiser M. 2011. Efforts on conservation and sustainable use of medicinal plants of Pakistan. Pakistan Journal of Botany 43:5–10. Google Scholar

50.

Soltanpour P. 1985. Use of ammonium bicarbonate DTPA soil test to evaluate elemental availability and toxicity 1. Communications in Soil Science & Plant Analysis 16:323–338. Google Scholar

51.

Takhtajan A, Crovello TJ, Cronquist A, translators.1986. Floristic Regions of the World. Berkeley, CA: University of California Press. Google Scholar

52.

Tavili A, Jafari M. 2009. Interrelations between plants and environmental variables. International Journal of Environmental Research 3:239–246. Google Scholar
© 2016. Rahman et al. This open access article is licensed under a Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/). Please credit the authors and the full source.
Aziz Ur Rahman, Shujaul Mulk Khan, Salman Khan, Ahmad Hussain, Inayat Ur Rahman, Zafar Iqbal, and Farhana Ijaz "Ecological Assessment of Plant Communities and Associated Edaphic and Topographic Variables in the Peochar Valley of the Hindu Kush Mountains," Mountain Research and Development 36(3), 332-341, (1 August 2016). https://doi.org/10.1659/MRD-JOURNAL-D-14-00100.1
Received: 1 September 2015; Accepted: 1 May 2016; Published: 1 August 2016
KEYWORDS
Canonical correspondence analysis
cluster analysis
conservation
Hindu Kush Mountains
Peochar Valley
plant composition
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