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Spatial Analysis of Vascular Flora of Ayubia National Park, Kpk, Pakistan: a Classical Example of Moist Temperate Himalaya

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Spatial Analysis of Vascular Flora of Ayubia National Park, Kpk, Pakistan: a Classical Example of Moist Temperate Himalaya SPATIAL ANALYSIS OF VASCULAR FLORA OF AYUBIA NATIONAL PARK, KPK, PAKISTAN: A CLASSICAL EXAMPLE OF MOIST TEMPERATE HIMALAYA 1 Rabia Afza , Habib Ahmad2, Zafeer Saqib, Khan Bahadar Marwat3, Jawad Khan4, Department of Botany, Hazara University Mansehra, Pakistan1, Department of Genetics, Hazara University Mansehra, Pakistan2 Department of Environmental Sciences, IIUI, Islamabad Shaheed Benazir Bhutto (SBB) University, Sheringal, Dir Upper3, Pakistan Govt. Degree collage, Zaida, Swabi, KPK, Pakistan4 *E-mail of the corresponding author: [email protected] Abstract The current study analyzed the diversity of vascular flora in relation to the prevailing environmental gradients of Ayubia National Park (ANP) of 33km2 area. The phyto- environmental physiognomies of ANP were analyzed by multivariate techniques. The data analysis was based on indicator species concept and presence only data to classify and ordinate species distribution. The hierarchical clustering by Bray-Curtis method and ordination by Nonmetric multidimensional scaling (NMDS) identified major plant communities in the Park. The study revealed that some environmental factors have a determining role in defining and shaping the key vegetation classes and species richness in the area. NMDS-Ordination indicated elevation (Pr› 0.001) as highly significant environmental gradient followed by stream power index (Pr› 0.012) and slope length factor (Pr› 0.025) in plant species distribution. The study recommends important phytosociological parameters for species distribution that may facilitate conservation of biodiversity and developing future strategies for mountain ecosystems. Key words: Ayubia National Park; vascular flora; multivariate analysis; biodiversity conservation. Introduction The Himalayan region is the world’s highest and geologically youngest mountainous province (Burchfiel & Royeden, 1985) with distinct biodiversity and is therefore consequently important for ecologiests and biodiversity conservationists of the world (Mool et al., 2001). Ecologists and biologists are interested to ascertain and determine the biological alteration among species 1 diversity by different environmental factors in an ecosystem (Vetaas & Grytnes, 2002; Grytnes, 2003). Ascertaining and establishment of correlation between biological and physical elements of an ecosystem is very important branch of applied ecological study (Mofidi et al., 2013) particularly in mountainous regions, physical factors shows the greatest effect in limiting plant species and community types (Chawla et al., 2008). Classification and categorization of forest’s ecosystem into different assemblages and habitat categories is an imperative tool in natural resource conservation and management. Ayubia National Park (ANP), a classical example of moist temperate region of Pakistan, is a protected area spreads with 33km2 cover. Approximately 50,000 inhabitants are residing around the Park in seven major villages (Afza et al., 2004). The park is a part of Lesser ;to 73° 27.1' E ׳N and 73° 22.8׳ Himalaya extending from North to South at 34°1' to 34° 3.8 spreading between an elevation range of approximately ±1450 - 3,033m of Galliat region, District Abbottabad, Pakistan (Fig.1). The floristic resemblance is with Saharo-Japanese phytogeographic region of the world (Mani 1974) with mean 1500 mm annual rainfall and Fig.1. Location map of Ayubia National Park. 2 10°C temperature (Ahmad & Afza, 2014; Afza, 2016). The most of the precipitation is received in the form of snow (December to February) which characterised the vegetation as moist temperate and having variable degree of coniferous species including Pinus wallichiana, Pinus roxburghii, Abies pindrow, and Cedrus deodara. Taxus wallichiana is also very common tree of the area. Geologically this zone is molded by precipitous and steep rocks (40 - 170 million years old) constituting shale, sand and limestone particles (Calkins et al., 1975; Latif 1976) with very shallow topsoil to sustain plant flora on steep slopes. The common broad leaves are Acer caesium, Prunus padus, Aesculus Indica and Quercus Species. The forests fluctuating from canopy to open lush grassy meadows with a high variety of ferns and perennial herbs; lichens on the trees trunks and an assortment of mosses. The bio-ecological habitats of the area by describing 5 major zones including (i) Coniferous Forests (49.2 %) (ii) Shadow Coniferous Forests (32.2%), (iii) Coniferous Forest, Shrubs and Grasses (4.03%), (iv) Broadleaved Mix Forests (11.18%), (v) Pastures and Grasses (0.14%). The vegetation of the study area was first described by Champion et al. (1965) and Beg (1975) before the inception of the Park in 1984. After the establishment of the Park, the area was described by a number of ecologists like Hussain and Ilahi (1991); Saima et al. (2009) and Ahmad (2012) and the floristic composition of the area was analysed by using multivariant approaches in selected compartments of the Park due to rugged terrains and steep slopes the whole area of the park was not covered till now with recently developed analytical tools. This study was designed therefore, to compute the richness of species in plant communities and place them in such an ecological and vegetation framework acceptable in international terms, for identification of key environmental factors for distribution and classification of vegetation. The recent developments in multivariate statistical techniques have helped improve baseline knowledge of the ecological communities and are becoming increasingly popular in Pakistan for the same (Khan et al., 2011; Afza et al., 2016). The use of computer-based statistical and multivariate analytical programs assists ecologists to find out proper configuration to analyse the outcomes of environmental gradients on entire sets of plant species (Phillips et al., 2006). Statistical programs reduce the intricacy of data sets by clustering the vegetation types and correlating the results with abiotic (environmental) factors (McCune et al., 2004; Terbraak & Prentice, 2004, Zhang & Dong, 2010). Such multivariate tools have infrequently been applied in vegetation studies of Pakistan (Malik & Husain, 2008; Wazir et al., 2008; Saima et al., 2009; Shaheen et al., 2011; Khan et al., 2013, Afza, 3 2016). Materials and Methods Field data collection: In order to understand the broader ecological patterns in ANP, field data was collected in the study area during the spring and summer along different environmental gradients during year 2012 to 2014. A phytosociological approach (Rieley & Page, 1990; Malik & Hussain, 2006) was used to measure quantitative and qualitative attributes of vascular plants in quadrats. The vegetation pattern was studied in systematically laid plots at a grid spaced at 100 m altitudinal and at least 250m horizontal intervals to cover the whole extent of study area (33 km2). The grid points were predetermined and located in field using handheld Global Positioning System (GPS) receiver. A circular plot of 18 x18 m2 was used for trees, 4 x 4 m2 for shrubby vegetation and 1 x 1 m2 for the plots were chosen in a nested techniques for ground vegetation (Pfister et al., 1977). The overall data consisted of 160 nested data plots (0.1 hector/plot) representing 250 species. The current study calculated frequency, cover density (absolute and relative) of all recorded vascular plant species using the formulae designed. The data collected within the plots included the occurrence record of plant species. The unidentified plants were duly labelled and collected for identification at herbarium of Hazara University Mansehra. The nomenclature follows Flora of Pakistan (Nasir et al., 1972). Statistical analyses: The recoded data was analysed through classification and ordination tools of multivariate statistical software package (R-software3.1) (McCune et al., 2002). Classification of vegetation plot data: Hierarchical clustering was performed by Bray-Curtis (1957) and Wards (1963) methods of classification, based on applied distance matrix. The broader communities were thus defined and presented as dendrogram. The communities were characterised based on the concepts of fidelity and constancy and the frequency of each of the species in respective community was also determined (Kent & Coker, 1992). Constancy was used in this analysis to name the vegetation communities (ecological zones). Species with constancy between 20% and 75% and degree of fidelity between 3 and 5 were considered ‘characteristic species’ (Kent & Coker, 1992). Following quantitative attributes for each of the 4 community were also determined: Species diversity: Shanon-Weaver Index H' (Shannon & Weaver, 1948) was calculated as: Diversity H ′ = − p ln p ∑ i i ……………………… (Eq. 1) Species richness: Species richness means a count of the number of the plant species in a community. Evenness or equitability: Shannon’s-evenness index (E1) to quantify the evenness component of species diversity as: E = H ′/ ln s 1 ……………………………..…….... (Eq. 2) Where H' = Shannon’s diversity; ln = natural logarithm and s = the total number of species in a community Ordination of vegetation plot data: To support the Bray-Curtis hierarchal clustering analyses and describe the influence of environmental gradients in vegetation pattern, Non- metric multidimensional scaling (NMDS) o f vegan package (R-software), a PC- ORD Software was applied for ordination of sampling plots. Ordination of vegetation plot is used to assess the arrangement of species or samples along gradients and show their
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