Sci Nat (2017) 104:24 DOI 10.1007/s00114-017-1431-2
ORIGINAL PAPER
Classification and ordination of understory vegetation using multivariate techniques in the Pinus wallichiana forests of Swat Valley, northern Pakistan Inayat Ur Rahman 1 & Nasrullah Khan 1 & Kishwar Ali 1
Received: 24 September 2016 / Revised: 11 January 2017 / Accepted: 16 January 2017 # Springer-Verlag Berlin Heidelberg 2017
Abstract An understory vegetation survey of the Pinus wallichiana-dominated temperate forests of Swat District was carried out to inspect the structure, composition and ecological associations of the forest vegetation. A quadrat method of sampling was used to record the floristic and phytosociological data necessary for the analysis using 300 quadrats of 10 × 10 m each. Some vegetation parameters viz. frequency and density for trees (overstory vegetation) as well as for the understory vegetation were recorded. The results revealed that in total, 92 species belonging to 77 different genera and 45 families existed in the area. The largest families were Asteraceae, Rosaceae and Lamiaceae with 12, ten and nine species, respectively. Ward’s agglomerative cluster analysis for tree species resulted in three floristically and ecologically distinct community types along different topographic and soil variables. Importance value indices (IVI) were also calculated for understory vegetation and were subjected to ordination techniques, i.e. canonical correspondence analysis (CCA) and detrended correspondence analysis (DCA). DCA biplots for stands show that most of the stands were scattered around the centre of the DCA bi-plot, identified by two slightly scattered clusters. DCA for species bi-plot clearly identified three clusters of species revealing three types of understory communities in the study area. Results of the CCA were somewhat different from the DCA showing the impact of environmental variables on the understory species. CCA results reveal that three environmental variables, i.e. altitude, slope and P Communicated by: Sven Thatje * Inayat Ur Rahman
[email protected]
1
Laboratory of Plant Ecology, Department of Botany, University of Malakand, Chakdara, LowerDir, Khyber Pakhtunkhwa, Pakistan
(mg/kg), have a strong influence on distribution of stands and species. Impact of tree species on the understory vegetation was also tested by CCA which showed that four tree species, i.e. P. wallichiana A.B. Jackson, Juglans regia Linn., Quercus dilatata Lindl. ex Royle and Cedrus deodara (Roxb. ex Lamb.) G. Don, have strong influences on associated understory vegetation. It is therefore concluded that Swat District has various microclimatic zones with suitable environmental variables to support distinct flora. Keywords Pinus wallichiana . Understory vegetation . DCA . CCA . Floristic composition . Ecological structure
Introduction Understory vegetation plays a critical role in maintaining forest ecosystem structure and function, facilitating energy flow and nutrient cycling and affecting canopy succession as a forest ecosystem driver (Huo et al. 2014). Although the understory contributes relatively little to the total forest plant biomass, it accounts for the largest proportion of floristic diversity (Huo et al. 2014). Moreover, diverse understory vegetation increases forest structural complexity and provides habitats and food for other biotic groups, increasing their diversity (Whigham 2004; Dauber et al. 2003). Changes in the understory vegetation impose long-term shifts in forest communities and landscapes, but unfortunately, it is one of the least studied areas of forest ecology (Rees and Juday 2002; Chaping et al. 2004). Numerous studies demonstrated that dynamic understory communities change considerably with the overstory species (Hart and Chen 2006; Yu and Sun 2013; Qian et al. 2003; Macdonald and Fenniak 2007), stand management (Barbier et al. 2008), ground
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disturbances (Roberts and Zhu 2002; Aikens et al. 2007), light resources (Hart and Chen 2006; Lefrancois et al. 2008; Ameztegui et al. 2012), litter properties (Yu and Sun; Ellsworth et al. 2004: North et al. 2005), topography (Qian et al. 2003; Hart and Chen 2006; Thomsen et al. 2005; Koorem and Moora 2010) and soil nutrients and pH (Molder et al. 2008; Chavez and Macdonald 2010; Hart and Chen 2006). Due to the dominant position of trees in forests, the composition and structure of overstory species can be expected to influence the understory composition and diversity (Bratton 1976; Palik and Engstrom 1999). It is imperative to study the effect of overstory species on the understory vegetation because ground flora plays an important role in the functioning of forest ecosystems. The understory vegetation stores a significant amount of nutrients of forests during stand development (Perala and Alban 1982; Switzer et al. 1968) and may influence changes in the nutrients of the forest ecosystem during through falls (Hornung et al. 1990), mineralisation (Lemée, 1975), nitrification (Wedraogo et al. 1993) and after clear-felling (Dahlgren and Driscoll 1994). It can also influence the soil microbiota (Leyval and Berthelin 1983) and weathering of soil minerals (Hinsinger et al. 1993). On the other hand, understory can cause difficulty in planting operations, as well as a competitor with trees for light, water and nutrients (Warren et al. 1987). Finally, a natural and diverse understory vegetation may be very important to plant communities beyond any effect on growth or nutrients. Various studies showed the impact of tree species on the composition of understory vegetation yet cannot be generalized as it involved very few sites (e.g. (Knapp 1958)), mixedspecies stands (Berger and Puettmann 2000; Crozier and Boerner 1984), young stands (Ovington 1955) or a vegetation specific to a region. Studies conducted on understory vegetation in coniferous forests (e.g. Koorem and Moora 2010), hardwood forests and mixed-wood forests (Chavez and Macdonald 2010; Yu and Sun 2013) suggest that coniferous forests are less favourable to biodiversity than mixed- or hardwood forests (Barbier et al.). However, few studies have compared understory vegetation among coniferous species (Barbier et al. 2008; McKenzieand and Halpern 1999). Natural forest patches that are dominated by Pinus wallichiana are widely distributed in the Hindu KushHimalayan mountains of northern Pakistan. These forests are important for timber and firewood, water conservation and preventing soil erosion in this region. In this study, we investigated the understory flora and associated topographic variables in different forest stands representing the entire range of P. wallichiana forests in the Swat District. The objectives of this study were to (i) document the floristic composition of the P. wallichiana understory vegetation, (ii) compare understory vegetation in pure and mixed conifer forests and (iii) determine the extent to which topographic variables and site
conditions could explain the variation in the understory species composition.
Material and methods Study area Swat District is in the northwestern region of Pakistan in Khyber Pakhtunkhwa (KPK) Province. It is a well-known summer resort for national and international tourists and visitors and lies between 34° 34″ and 35° 55″ north latitudes and 72° 08″ and 72° 50″ east longitudes. Most of the area consists of mountains belonging to the Hindu Kush mountain ranges. The weather of the valley is mild. However, upper regions have longer and lower regions have shorter winters. Summers are short and pleasant with temperatures rarely reaching to 35 °C. Yearly rainfall ranges from 80 to 90 cm, while upper parts of the valley experience regular snowfall in winter (Ilahi and Suleman 2013). Fieldwork methodology Systematic floral surveys were carried out during 2013–2014 to investigate the understory species diversity of P. wallichiana forests of Swat, Pakistan. Specimens obtained from the field were preserved using techniques described in Jain and Rao (1977) and labeled for permanent storage as herbarium collections. These specimens were properly identified using keys in the Flora of Pakistan (Nasir and Ali (1971–1995) and Ali and Qaisar (1995–2011)). Sampling procedure and data collection The quadrat method of vegetation sampling (Hussain 1989) was used to record data regarding the vegetation of the study area. At 30 different sites, a total of 300 quadrats each for trees (10 × 10 m), shrubs (5 × 5 m) and herbs (1 × 1 m) were established (Cox 1967). Frequency, density and cover of each species were recorded per Hussain (1989). The investigated values were entered in an Excel spreadsheet (Microsoft Office 2016) and relativized which in turn were summed up to obtain importance value index (IVI) (Hussain 1989). Soil analysis Soil samples were collected at randomly selected locations within each stand. Soil samples were obtained by digging out soil from 0 to 30 cm depths using a soil auger. The litter from the surface of the samples was removed, and the samples were mixed before further analyses. About 500 g of soil from each sample was placed in a polyethylene bag, labeled and brought to the soil laboratory of the Agriculture Research Institute (Mingora North). Air dried (25–30 °C) soil samples were passed through a 2-mm sieve, and their physicochemical characteristics were recorded. The soil sample pH values were measured in a 1:5 soil:water paste using a Dynamic digital pH
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meter (model sension, TM 105). Soil organic matter (SOM) was determined by the method of Jackson (1958). Total nitrogen (N) was determined per Bremner (1965) using the Kjeldahl method, and total phosphorus (P) was estimated following the method of Bingham (1949). Multivariate methods Ward’s agglomerative clustering was used to classify the plant community types based on the overstory tree species, while detrended correspondence analysis (DCA) and canonical correspondence analysis (CCA) were used to investigate vegetation patterns and distributions of species with regard to their environmental variables, using PC-ORD software (McCune and Mefford 2005). IVI was used as species abundance input data (Baruch 2005). The importance value indices were calculated by summing the relative frequencies and densities of the species. We could not use commonly used cover estimates for IVI calculation due to inadequate species cover data. Edaphic and topographic variables used for the CCA analysis were the elevation, slope, aspect, clay, silt, sand, pH, organic matter %, lime %, N %, P (mg/kg) and K (mg/kg).
Results Floristic composition A total of 92 understory species of 77 genera related to 45 families were recorded in 300 quadrats at 30 sampled locations in the Hindu Kush ranges of Swat Valley. Asteraceae, Rosaceae and Lamiaceae with 12, ten and nine species, respectively, were the dominant families. Six families were represented by three species, seven families by two species and 29 families were represented by one species each (Fig. 1). Classification of P. wallichiana-dominated forests The Ward’s agglomerative cluster analysis segregated 30 forest stands comprised of 12 tree species dominated by P. wallichiana into three distinct vegetation types (Fig. 2). Two of these communities represented P. wallichiana and its co-dominant species, while one of them is formed by pure P. wallichiana stands. These vegetation types show more distinct classification for species composition in the three clusters linked with their specific topographic and soil regimes as described below. Cluster I- P. wallichiana and Quercus dilatata community
Cluster I consists of P. wallichiana-Q. dilatata-dominated forests and is represented by 11 stands of the study area. This
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cluster was more diverse and heterogeneous both floristically and environmentally in P. wallichiana-dominated forests of Swat, comprising 12 trees and 66 understory species. P. wallichiana led with an average of 76 ± 2.73 and Q. dilatata with 6.41 ± 2.45% importance values. Picea smithiana, Abies pindrow and Quercus incana were cooccurring species in minor amounts in the community. The understory plant community was comprised of 66 species, of which Fragaria nubicola was the most abundant, while Dryopteris stewartii was the most frequent species. Rabdosia rugosa, Viola canescens, Viburnum grandiflorum, Indigofera heterantha, Rubia cordifolia, Arisaema flavum, Bistorta amplexicaulis and Berberis lycium were occasional species with average frequencies ranging from 20 to 40%. The remaining 56 species were rare, having average frequency ranges of 0.4–20% of the total floristic community. Cluster II- Pure P. wallichiana community Cluster II can be declared as a monospecific (dominated) community of P. wallichiana with a mean importance value of 95%. The co-dominant species each contributed less than 2% of the importance value. This community constitutes a singlecohort stand structure so that it was solely dominated by P. wallichiana in the entire layers, and it generally formed mature stands in the region. Co-dominants did contribute to two-layered structure, but in minor amounts, and hence were insignificant in the population. This group comprised 12 stands with a total of seven tree species. The understory vegetation of this community was floristically rich, having 80 associated species. The most important species based on frequency was F. nubicola, with a relative frequency of 70%. D. stewartii (52%) was frequent, while Artemisia vulgaris, I. heterantha, R. cordifolia, Valeriana jatamansi, V. canescens, A. flavum, B. amplexicaulis, B. lycium and Festuca gigantea occurred occasionally with average frequencies ranging from 20 to 40%. The remaining 69 species were rare for this community type. Cluster III- P. wallichiana and Cedrus deodara community Cluster III represents P. wallichiana-C. deodara community having importance values of 52.77 ± 3.7 and 24.5 ± 1.77% for P. wallichiana and C. deodara, respectively. P. smithiana locally joins the population with 8.71 ± 2.5%, Q. dilatata with 7.69 ± 4.32% and A. pindrow (IV = 6.29 ± 2.52%) with comparatively lesser importance values. Because of the occurrence of the co-dominant and subordinate species, this community, generally formed by mature stands, constitutes multicohort stand structures. This community was relatively less diverse among three community types. The understory vegetation comprised 28 species, of which F. nubicola was abundant, while Rumex dentatus was a
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Fig. 1 Family-wise distribution of P. wallichiana understory species
12
No. of species
10 8 6 4 2 0
Family
frequent species. V. canescens and I. heterantha were occasional species. The remaining 24 species were rare, with an average frequency range of 0.4–20%. Vegetation analysis DCA for stands only A DCA ordination plot (Fig. 3) for stands reveals that about 80% of the variations in vegetation composition were displayed in two (of four total) DCA ordination axes.
Although most of the stands are located at the centre, suggesting similarities in species composition among the stands, we can distinguish two main clusters of stands. The first cluster containing most of the stands lies in the centre of the graph represented by most of the stands between 14 to 30 including stand 8. The proximity of these stands shows clear similarities in the vegetation structure and composition. The second cluster located at the lower left hand of the graph consists of stands 1, 2, 3, 9, 10, 12 and 21 also shows similarities in species composition of these stands. On the extreme left side, somewhat away from the main cluster, three stands (i.e. 5, 6 and 24) are grouped together, suggesting similarities among them and differences from the main cluster. Stand 4 (Sangar) plotted at the top left, stand 13 (Sulatanr) at the bottom left and stand 27 (Mankyal) at the centre right of the ordination diagram suggest that each of these locations has a unique floristic composition. Similarly, stands 11 and 7 located in the top left were also peculiar stands regarding their species composition. DCA for the understory species
Fig. 2 Classification of 30 sample stands (St. stand) dominated by Pinus wallichiana into three groups (vegetation types) using Ward’s agglomerative clustering procedure. Groups are extracted at 70% information and arranged from top (Group I) to bottom (Group III) on the dendrogram
A DCA scattered diagram of species (based on the species score) revealed the position of different species along the two axes and their association with the gradients (Fig. 4). The existence of F. nubicola, Chenopodium album, Anaphalis triplinervis, Polygonum aviculare and Polygonatum verticillatum on the extreme upper left side of the ordination diagram indicates their high axis 2 scores and low axis 1 scores. The high scores on axis 2 depict the affinity of these species to moist and hot habitats occurring at middle elevations. The clustering together of the large shrub Parrotiopsis jacquemontiana, a woody evergreen climber Hedera nepalensis and small herbs, i.e. A. vulgaris, Achyranthes aspera, Duchesnea indica and Pilea umbrosa shows that they all to some extent were grouped together due to their same ecological amplitude.
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Fig. 3 DCA ordination plot of stands only for P. wallichianadominated forests of the Swat Valley
The occurrence of R. dentatus, F. gigantea, V. canescens, Anemone falconeri, Ajuga bracteosa, Aquilegia pubiflora, Andrachne cordifolia, Tagetes minuta, Thalictrum pedunculatum, Rosa brunonii and Swertia ciliata in the centre towards the upper right side of the ordination diagram indicates their high axes 1 and 2 scores. These high scores disclose the affinity of these species to relatively dry and cold habitats occurring at high elevation. These species lie slightly apart from each other indicating some differences in microclimatic conditions. The occurrence of Bergenia ciliata, Rubus fruticosus and Viburnum cotinifolium on the lower left side of axis 2 shows their preferences for relatively cold areas with higher precipitation. Two of the species, i.e. Podophyllum hexandrum and Chenopodium botrys occur at the lower right side of the diagram having the least value of axis 2 showing their preference for low temperature. The occurrence of Salvia lanata, Sorbaria tomentosa, Delphinium denudatum, Pteris cretica, and Plantago lanceolata in the centre of the diagram shows that these species have no apparent affinity for specific habitats and that these species are omnipresent in nature in many communities. Scattered diagram revealed that these species were present at some distance from each other, but due to ecological amplitude, they were grouped together in communities.
CCA understory vegetation with environmental variables (stand only data) The CCA stand ordination results were significantly different from the DCA results. Figure 5 shows that most of the stands are scattered in four CCA ordination axes except stands 7, 10, 11, 12, 13 and 21, which are clustered at the top left hand of the plot suggesting their similarities in terms of environmental variables. The CCA also reveals that elevation, slope and P (mg/kg) were the most vital variables affecting the stand distribution. Towards the positive side of axis 1, seven of the stands were scattered and elevation seems to have a pronounced effect upon them (stands 27 and 28 have the highest value for elevation), while towards the negative side of axis 1, six out of 30 stands are clustered under the influence of elevation, whereas towards axis 2, most of the quadrats are scattered along the negative side of the axis, indicating the strong influence of P (mg/kg) and slope upon them. Some of the stands occurring on the positive side of axis 2 indicate the influence of elevation. CCA of understory vegetation and environmental variables (species only) By analysing the pattern of species distribution and relating them with ecological characteristics of the habitats supporting
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Fig. 4 DCA ordination plot of P. wallichiana understory vegetation
them, a general pattern of variation was evident in the P. wallichiana understory vegetation. Elevation, slope and P (mg/kg) had played an apparent significant role in the grouping of most of the species. Species showing correlation responses with elevation are plotted towards the upper left of the plot, while slope and P (mg/ kg) association is plotted on the lower left of the plot (Fig. 6). Elevation showed a strong correlation with P. hexandrum, C. botrys, Trillidium govanianum, T. minuta, Euphorbia wallichii, V. canescens and A. bracteosa while A. flavum, Hypericum perforatum, Sarcococca saligna, Viola betonicifolia, Impatiens brachycentra, Verbascum thapsus, V. cotinifolium and Adiantum capillus-veneris showed a correlation with slope and P (mg/kg). CCA of understory using tree species as environmental variable To investigate the influence of overstory tree species on understory vegetation, CCA was applied considering overstory as environmental variables. Among 12 tree species, four species, i.e. P. wallichiana, Juglans regia, Q. dilatata and C. deodara were found to be associated with distinct subfloras. P. wallichiana and J. regia shared the associated flora
having 50% of the understory species associated with them. Q. dilatata is the second most important tree species, having a strong association with approximately 30% of the understory vegetation. C. deodara was also associated with R. dentatus, Jasminum humile and F. gigantea. Some of the understory species such as V. thapsus, S. lanata and S. ciliata appear to have no associated overstory species (Fig. 7).
Discussion Floristic composition P. wallichiana-dominated forests of Swat showed floristic and ecological diversity both in the over- and understory levels. The presence of 92 understory plant species in P. wallichiana forests of Swat District indicates that P. wallichiana has associations with a considerable variety of understory species. It is suggested that high plant diversity under the single tree species is possibly due to varied topographic and physiographic conditions. Asteraceae was the most dominant family in P. wallichiana understory vegetation, followed by Rosaceae and Lamiaceae. Behera et al. (2002), Paul (2008) and Bharali et al. (2011) have also reported similar trends of family dominance (Asteraceae,
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Fig. 5 CCA ordination plot of the stands only using environmental factors
Ericaceae and Rosaceae) from temperate/subalpine forest of Arunachal Pradesh. Fig. 6 CCA ordination plot for understory species and environmental variables
As per our results, the overstory stands were clustered into three groups (communities) using Ward’s clustering
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Fig. 7 CCA ordination plot of herbs; tree species were used as environmental variables
technique. One of the clusters (cluster II) resulted from this classification contained P. wallichiana as the only overstory plant. We can precisely report that this community has the potential of supporting the maximum number (80 species) of understory flora, indicating broad sociability of the species in the studied forests. Another group (cluster I) resulting from the Ward’s cluster diagram, P. wallichiana-Q. dilatata community, was more heterogeneous in terms of the overstory species consisting of 12 trees and 66 understory species. This reveals that as the overstory species diversity has increased, the understory has correspondingly decreased. The third one group consisted C. deodara as co-dominant species along with P. wallichiana. This group was less diverse in terms of understory species containing only 28 species. These findings suggested that P. wallichiana alone supports more understory species than in association with Q. dilatata or C. deodara or we can say that these species. Species-environment relationship was investigated through multivariate techniques of DCA and CCA. Jongman et al. (1995) preferred the use of regression models for such correlation analysis, on the condition that sufficient data must be available, but some favoured other multivariate techniques such as ordination (Palmer 1993). DCA results of understory vegetation also indicated three major communities or groups which follow the groups sorted by Ward’s clustering of tree species. The vegetation groups from DCA were F. nubicola and C. album (group 1), B. ciliata and R. fruticosus (group 2) and R. dentatus and F. gigantea (group 3). Some of the species like P. cretica and P. lanceolata, occurring in the centre of the diagram, showed no preference for a certain plant community
type and were distributed evenly throughout the studied forests. Similarly, Jabeen and Ahmed (2009) reported four groups from a DCA of temperate forests of Ayub National Park Rawalpindi and Naqinezhad et al. (2008) obtained five vegetation groups by DCA and interpreted these groups with major environmental gradients, i.e. organic matter and nitrogen contents. The DCA ordination analysis for locations has revealed that most locations were clustered in the centre of the plot, indicating similarities among stands; this is since all the plots have P. wallichiana in common as the overstory tree species. Moreover, some stands were located separately on the plot showing very peculiar vegetation and indicator species. These include stand 4 (Sangar), stand 7 (Manrai), stand 11 (Lalku), stand 13 (Sulatanr), stand 20 (Miandam), stand 22 (Bishegram) and stand 27 (Mankyal). These temperate coniferous forests are rich in terms of biodiversity having ecologically and commercially important plant species (Ali 2011). The impact of environmental factors on vegetation distribution was also measured through CCA. Most of the understory species showed strong responses to changes in elevation, slope and P (mg/kg); however, these factors played little role in the grouping of stands (locations). Many studies have shown that elevation has a greater impact on vegetation type than latitudinal gradient (Jiang et al. 2007; Jabeen and Ahmed 2009). Moreover, the structure and composition of prevailing vegetation type are more adapted to climatic conditions which are better reflected along altitudinal gradients. Ali (2011) analysed the impact of altitude on tree species and concluded a strong response of trees toward altitude. Jabeen
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and Ahmed (2009) also reported strong correlations of Geranium rotundifolium and Rumex chalepensis with pH. The significance of the study can be determined from the research question viz. to understand the relationship between the overstory and understory vegetation in connection with the prevailing environmental regime of the area. It is evident from the results that the overstory tree species have strong affinity with the associated understory plant species in the study area, as shown in the CCA analysis. It can undoubtedly be reported that the P. wallichiana-J. regia communities support most of the understory species, while Q. dilatata supports fewer understory species. The smallest number of species was recorded for the C. deodara forest communities. It could be due to the allelopathic or other limiting factors, i.e. sunlight penetration through the foliage of the trees etc.
Conclusion As a general conclusion, Swat Valley has the major forest type dominated by P. wallichiana. Most of these forest stands have P. wallichiana as the only overstory species while others form an association with other tree species such as C. deodara and Q. dilatata. These forests support a variety of understory vegetation playing a distinct role in the forest ecosystem of the area. The study also concludes that the environmental variables such as slope, elevation and edaphic factors can strongly influence the composition of species at a microclimatic level. We recommend similar studies at a broader level, expanding it to the neighbouring districts of Swat and possibly to the entire area under the Hindu Kush-Himalayan ranges of the country.
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