Modern pollen–vegetation relationships along an altitudinal transect in the Western Higher Himalaya,India: Palaeoclimatic and anthropogenic implications

Abstract

Palynology is one of the most reliable tools for the reconstruction of past vegetation and climate and modern pollen analogues are important for the calibration of fossil pollen assemblages. The present study analyses the pollen–vegetation relationships along a steep altitudinal gradient (2700–3680 m), in the western Higher Himalayan region. On the basis of altitude, three vegetation zones were demarcated: Zone I (2700–3100 m) is composed of mixed-temperate forest vegetation, dominated by Quercus semecarpifolia and Rhododendron arboreum; Zone II (3100–3250 m) is marked by sub-alpine forest vegetation, characterised by R. campanulatum and R. barbatum, along with Abies spectabilis and Q. semecarpifolia; Zone III (3250–3680 m) is above the tree-line (3250 m) and represented by alpine-scrub and meadows. Thirty-five surface soil samples (twenty, seven and eight from each zone, respectively) were analysed along the altitudinal transect to decode the representation of the extant vegetation in the pollen-rain. The pollen–vegetation relationship is non-linear due to the over-representation of extra-local Pinus pollen in each zone. Nonetheless, the modern pollen assemblages show a general correlation with the local broad-leaved taxa and the herbaceous elements; with the exception of Rhododendron pollen, which is under-represented. Among the non-pollen palynomorphs (NPPs), the presence of coprophilous fungal spores is compatible with the grazing activities in the area. Multivariate statistical analyses performed on the surface pollen data indicate that the dataset can efficiently distinguish the different vegetation zones across the altitudinal gradient. This work provides the modern analogues for pollen-based palaeoclimatic reconstructions for the Western-Higher Himalayan region, and would also help to decipher the inception and intensification of anthropogenic activities in the region.

Keywords

alpine vegetation anthropogenic influence Himalaya NPPs palaeoclimate palynology

Introduction

Investigation of palynological assemblages is one of the most time-tested and proven methods for the reconstruction of palaeoclimate and is also useful for the comparative study of the past and present vegetational changes (Birks and Birks, 1980; Kar and Quamar, 2019; Liu and Lam, 1985; Overpeck et al., 1985; Quamar et al., 2021). However, the relationship between the modern pollen assemblages and the extant vegetation is not always easy to interpret. Since plants have different magnitudes of pollen production and dispersal behaviour, therefore, in most of the cases the relationship between the modern pollen assemblages and the surrounding vegetation is not proportional. A non-linear relationship (Fagerland effect: Fagerland, 1952) is often observed between the pollen assemblages recorded in the sediments and the surrounding vegetation that contributes the pollen load (Birks and Berglund, 2018; Birks and Gordon, 1985; Kar and Quamar, 2019; Quamar and Kar, 2020). Because of these complications, some pollen taxa are over-represented, under-represented or not represented at all, in the pollen assemblages (Jackson and Lyford, 1999; Prentice et al., 2008; Sugita, 2007). Generally, wind pollinated (anemophilous) plants have higher pollen production and better pollen dispersal, leading to the over-representation of pollen taxa, whereas entomophilous (insect pollinated) plants have lesser pollen production and are relatively poorly represented in the pollen assemblages (Faegri and Iversen, 1964; Quamar and Kar, 2020). Hence, analysing and establishing the pollen–vegetation relationship and developing the ‘modern analogues’ are imperative to correctly interpret the fossil pollen data (Calcote, 1998; Kar and Quamar, 2019; Webb et al., 1981).

There are some good published records on pollen–vegetation relationship along altitudinal transects from the different parts of the world, mainly from Africa: Burundi (Bonnefille and Riollet, 1988), Ethiopia (Bonnefille et al., 1993), Uganda (Vincens et al., 1997), Tanzania (Schüler et al., 2014), and also from South America (Weng et al., 2004), south-western Europe (Cañellas-Boltà et al., 2009) and Iran (Dehghani et al., 2017). Comprehensive studies using pollen traps to estimate the influence of climate on pollen productivity have also been undertaken in different parts of Europe (Filipova-Marinova et al., 2010; van der Knaap et al., 2010). From India, a number of studies on pollen–vegetation relationship have been undertaken across the different physiographic regions of the vast country, such as the Himalayas, Northern Plains, Peninsular and the coastal areas (Quamar and Kar, 2020 and the references cited therein). From the Indian Himalayan region as well, pollen dispersal studies have been undertaken ranging from the foothills to the Higher and Trans Himalaya (Kar and Quamar, 2020 and the references cited therein). However, the great Himalayan range has remained largely under-studied in the context of pollen–vegetation relationship studies along altitudinal gradients (Ali et al., 2020; Roy et al., 2021). In this perspective, the Chopta-Tungnath region of alpine meadows and temperate forests in the Western-Higher Himalaya, is a suitable site to study the pollen–vegetation relationship along an altitudinal transect (2700–3680 m), which can be related to sharp vegetational changes due to the steep gradient. Moreover, the area of study is also conducive to address problems about Holocene climate variability and anthropogenic activities in the high-altitude Himalayan regions. The objective of the study is to observe the changes in the pollen assemblages, across the different vegetation zones, along the altitudinal transect in a high-altitude region. Besides, palynological studies related to Holocene climatic changes have been initiated from sub-surface sediment archives in the same area (Mishra, 2020). Hence, the data generated on pollen–vegetation relationship from the surface sediments would provide the much needed modern analogues for the calibration and correct interpretation of the sub-surface fossil pollen records. This work is the first attempt to study the pollen–vegetation relationship along an altitudinal transect, encompassing different vegetation zones (temperate, sub-alpine and alpine), in the Western-Higher Himalaya, India.

Regional setting

The hamlet of Chopta is a region of high-altitude temperate forests and alpine meadows, located in the Rudraprayag District, Uttarakhand State, at an elevation of 2700 masl. The area falls under the Kedarnath Wildlife Sanctuary and is relatively well preserved. It is the base for trekking to Tungnath (a well-known and highly revered Shiva temple), which lies approximately 4 km away at an elevation of 3500 masl. Chopta-Tungnath region is situated between 30°29″ to 30°30″N latitude and 79°12 to 79°13″E longitude and covers a large area of the upper catchments of Alaknanda River, a major tributary of the river Ganga (Figure 1). The tree-line lies at about an altitude of 3250 masl (Semwal et al., 1981). In this region, permanent snow-line is lacking. The highest peak of the region, Chandrasila, is situated at an elevation of 3680 masl (Figure 2).

Figure 1.

(a) Location of Uttarakhand State on the map of India. (b) Rudraprayag District in Uttarakhand State. (c) Shutter Radar Topographic Mission (SRTM) Digital Elevation Map of Rudraprayag District (figure has been made by using ArcGIS 10.3), the black dot indicates the study area. (d) Enlarged view of the study area (orange coloured trekking path denotes the sampling transect).

Figure 2.

(a) A view of the Chopta hamlet with mixed-temperate forests in the background. (b) Rhododendron arboreum in bloom during spring. (c) Anthropogenic impact in the form of grazing, mule track, hutments and forest clearings. (d) View of the Tungnath temple and lodges above the tree-line. (e and f) View of the area around Tungnath temple and Chandrasila peak, with stunted trees of Rhododendron campanulatum in the foreground forming the Krummholz Zone, in summer and winter, respectively. (g) Close-up of Tungnath temple during summer and winter. (h) Alpine-scrub vegetation and a panoramic view of the Chandrasila peak.

The area is approachable by motorable road till Chopta (2700 masl). During the recent times, the Chopta-Tungnath region has become a favourite place for trekkers and campers due to its scenic locale. Religious tourism has also witnessed a manifold increase for those visiting the Tungnath shrine. Anthropogenic pressure is evident in the form of construction activities for accommodating the tourists (Rai et al., 2012a). Deforestation for timber and fuel, lopping and grazing by domestic animals such as sheep, goats, mules and cattle are also common during the entire summer season in the area (Hajra and Rao, 1990).

Climate

The climate of the area is typical moist-temperate type (Köppen, 1936). At the study site, the year is represented by the three main seasons; the cold and relatively dry winter (December–February); the warm and dry summer (May–June); and the warm and wet period (July–September), known as the monsoon or rainy season (Gairola et al., 2010). Besides these main seasons, the transitional periods between the rainy and winter, and winter and summer respectively, referred to as autumn (October–November) and spring (March–April) are also observed.

The area is under the influence of both the Indian Summer Monsoon (ISM) and the Western Disturbances (WDs). The bulk of the precipitation occurs during the rainy season (JAS) due to the ISM. During the winters (DJF) heavy snowfall occurs in the area due to the WDs, followed by frequent hail storms during April to May. The area remains covered with snow for about 3–4 months; the snow melts during May to June, resulting in high soil moisture that supports luxuriant plant growth. The average temperature ranges from a minimum of −8.0°C to a maximum of 25°C at the timberline ecotone (3250 masl), while it has higher variation in the alpine area (−11.0°C to 27°C) at 3600 masl (Rai et al., 2012b). The nearest Climate Research Unit Time Series (CRU TS) 4.04, 0.5 × 0.5 gridded climate data points, 1901–2019, showing the mean monthly precipitation and temperature around the site of investigation is shown in Figure 3 (Harris et al., 2014). The mean annual temperature (MAT) is 13.82°C and the mean annual precipitation (MAP) is 1110.6 mm.

Figure 3.

Nearest Climate Research Unit Time Series (CRU TS) 4.04, 0.5 × 0.5 gridded climate data point, 1901–2019, showing the mean monthly precipitation and temperature around the Chopta-Tungnath region, Western Higher Himalaya, India.

Vegetation

The area around Chopta-Tungnath is basically a region of meadows and temperate evergreen forests (Hajra and Rao, 1990). According to Champion and Seth’s (1968) classification of the vegetation zones of India, the study area falls under sub-alpine forest and alpine-scrub. Previous studies on the vegetation of the Chopta-Tungnath region of Garhwal Himalaya have indicated that the area shows a great variety of plant diversity, comprising of 71 families and 234 genera, across the sub-alpine and alpine region (Rai et al., 2012b). The forests in the study area are dominated by different species of Rhododendron and Quercus, which form the climax vegetation. These forests are not only intricately associated with the hydrological balance but also deal with the life support system for the local inhabitants. This vegetation has experienced a great deal of changes due to natural as well as anthropogenic factors.

The tree-line varies from place to place across the whole Himalayan range depending upon the climate, edaphic factors and the particular species. In the area of the present study, the upper limit of the tree-line is observed at 3250 masl, which is constituted by Rhododendron campanulatum and Abies spectabilis. These species form the ‘Krummholz Zone’, which is a type of stunted, deformed vegetation, encountered in the sub-alpine tree-line landscape, shaped by continual exposure to freezing winds. In general, the sub-alpine zone (3100–3250 m) is characterised by, more or less, equal dominance of Rhododendron arboreum, R. barbatum, Abies spectabilis, Quercus semecarpifolia, Betula utilis, Acer caesium, A. acuminatum, Prunus cornuta, Viburnum grandiflorum and Taxus baccata sub sp. wallichiana, etc. The herbaceous taxa of this region are represented by Potentilla atrosanguinea, Geranium wallichianum, Primula denticulata, Epilobium royleanum, Ranunculus hirtellus, Impatiens sulcata, Bistorta affinis, Fritillaria roylei and Satyrium nepalense. Danthonia cachemyriana, Agrostis pilosula and Trisetum spicatum are the common grasses and Kobresia royleana and Carex nubigena are the major sedges in the region.

Above the sub-alpine forests, alpine-scrub and meadows dominate the landscape. This alpine zone differs from other alpine regions of Western Himalaya, due to higher humidity and soil moisture. This is evident floristically by the absence or poor representation of xeric plants like Juniperus spp., Berberis spp., Ephedra gerardiana, Acantholimon lucopodioides, Thylacospermum rupifragrum, Astragalus strobilifera, etc. (Rau, 1974). The alpine zone has peculiar distribution of plant species, in response to specific environmental factors. Some important trees are Rhododendron companulatum, R. anthopogon, R. lepidotum and Cotoneaster microphyllus. The herbaceous flora is represented by Impatiens sulcata, Geranium wallichianum, Potentilla atrosanguinea, Circium verutum, Rumex nepalensis, Persicaria wallichii, Trachydium roylei, Cypripedium himalaicum and Epilobium royleanum etc., along with the members of Poaceae, Asteraceae, Ranunculaceae, Brassicaceae, Chenopodiaceae and Caryophyllaceae. (Gairola et al., 2010; Rai et al., 2012b; Table 1).

Table 1.

Showing the vertical belt of vegetation with altitude.

Forest type	Altitude (m)	Important elements of the vegetation
Alpine scrub and meadows (Zone III)	3250–3680	Rhododendron anthopogon, R. lepidotum; herbaceous taxa represented by families: Poaceae, Asteraceae, Ranunculaceae, Rosaceae, Caryophyllaceae, Euphorbiaceae, Amaranthaceae, Papaveraceae, Apiaceae, Lamiaceae, Polygonaceae, Brassicaceae, Balsaminaceae, Saxifragaceae, Liliaceae, Convolvulaceae, Solanaceae, Geraniaceae and Cyperaceae.
Sub-alpine (Zone II)	3100–3250	Rhododendron campanulatum, R. barbatum, Abies spectabilis, Quercus semecarpifolia, Acer caesium, A. acuminatum, Ulmus wallichiana, Myrica esculenta, Betula utilis, Prunus cornuta, Viburnum grandiflorum, Taxus baccata and herbaceous taxa mentioned above.
Mixed-temperate (Zone I)	2700–3100	Rhododendron arboreum, Quercus semecarpifolia, Q. leucotrichophora, Q. floribunda and herbaceous taxa mentioned above.

Material and methods

Field work and sampling

Thirty-five surface soil samples were collected along the altitudinal transect (2700–3680 m) from Chopta hamlet to Chandrasila peak. Based on variations in the vegetation due to changes in the altitude, three vegetation zones were demarcated along the transect: Zone I (2700–3100 m) is composed of mixed-temperate forests; Zone II (3100–3250 m) constitutes the Krummholz Zone and consists of a mosaic vegetation of stunted trees; Zone III (3250–3680 m) lies above the tree-line and is represented by alpine-scrub vegetation. The lower most zone (Zone I), comprising of mixed-temperate forests is the largest zone and also the most diverse, so more samples (20) were collected from this zone. As Zone II and Zone III are smaller, and the vegetation diversity is also much lesser as compared to Zone I, therefore, lesser number of samples were collected from these two zones (7 and 8, respectively) (Figure 4).

Figure 4.

Sketch representing the vegetational zones along the altitudinal transect. Numbers denote the surface sampling points and arrows denote the sub-surface sampling locations. (a) Alpine-scrub vegetation. (b) Sub-alpine vegetation forming the tree-line. (c) Mixed-temperate vegetation.

Sampling was done in the open spaces and not below the canopy, so as to avoid a bias of pollen representation of a particular species, in the overall palynological assemblage. Moreover, our main objective of undertaking the present study was to develop the modern-analogues for palaeoecological reconstructions; and as the subsurface sampling points are also located on similar open spaces, the comparison between the modern and fossil assemblages would thereby be proper. Samples were collected by hand-pick method, using a spatula by skimming the soil surface. All the samples were put in zip-lock polythene bags, labelled with details noted in the field diary and registered in the museum of the Birbal Sahni Institute of Palaeosciences, Lucknow, India (Table 2).

Table 2.

Latitude, longitude, altitude, dominant vegetation and characteristic pollen assemblage of the samples collected along the altitudinal transect.

Sample no.	Latitude (N)	Longitude (E)	Altitude (masl)	Dominant vegetation	Characteristic pollen assemblage
Zone I
TCS-1	30°29.138′N	79°12.063′E	2704	Rhododendron arboreum, Quercus semecarpifolia	Pinus, Quercus, Rhododendron, Alnus
TCS-2	30°29.251′N	79°12.126′E	2716	R. arboreum, Q. semecarpifolia	Pinus, Quercus, Rhododendron, Alnus
TCS-3	30°29.295′N	79°12.160′E	2734	R. arboreum, Q. semecarpifolia	Pinus, Quercus, Alnus, Abies
TCS-4	30°29.342′N	79°12.203′E	2748	R. arboreum, Q. semecarpifolia, Acer caesium	Pinus, Abies, Alnus
TCS-5	30°29.366′N	79°12.205′E	2761	R. arboreum, Q. semecarpifolia	Pinus, Abies, Quercus
TCS-6	30°29.384′N	79°12.207′E	2783	R. arboreum, Q. semecarpifolia	Pinus, Quercus, Rhododendron
TCS-7	30°29.424′N	79°12.208′E	2806	R. arboreum, Q. semecarpifolia	Pinus, Quercus, Alnus, Abies
TCS-8	30°29.511′N	79°12.209′E	2822	R. arboreum, Q. semecarpifolia	Pinus, Quercus, Alnus, Abies
TCS-9	30°29.555′N	79°12.334′E	2846	R. arboreum, Q. semecarpifolia	Pinus, Quercus, Alnus, Abies
TCS-10	30°29.557′N	79°12.363′E	2876	R. arboreum, Q. semecarpifolia	Pinus, Quercus, Alnus, Abies
TCS-11	30°29.601′N	79°12.266′E	2905	R. arboreum, Q. semecarpifolia	Pinus, Quercus, Alnus, Abies
TCS-12	30°29.604′N	79°12.289′E	2921	R. arboreum, Q. semecarpifolia	Pinus, Abies
TCS-13	30°29.601′N	79°12.324′E	2934	R. arboreum, Q. semecarpifolia	Pinus, Abies, Quercus
TCS-14	30°29.596′N	79°12.404′E	2958	R. arboreum, Q. semecarpifolia	Pinus, Abies, Quercus
TCS-15	30°29.655′N	79°12.465′E	2987	R. arboreum, Q. semecarpifolia	Pinus, Abies, Quercus
TCS-16	30°29.475′N	79°12.368′E	3011	R. arboreum, Q. semecarpifolia	Pinus, Alnus
TCS-17	30°29.466′N	79°12.372′E	3032	R. arboreum, Q. semecarpifolia	Pinus, Alnus, Quercus
TCS-18	30°29.470′N	79°12.362′E	3054	R. arboreum, Q. semecarpifolia	Pinus, Abies, Alnus
TCS-19	30°29.485′N	79°12.367′E	3080	R. arboreum, Q. semecarpifolia	Pinus, Quercus
TCS-20	30°29.410′N	79°12.339′E	3097	R. arboreum, Q. semecarpifolia	Pinus, Quercus, Abies
Zone II
TCS-21	30°29.437′N	79°12.452′E	3109	Q. semecarpifolia, R. campanulatum, Abies spectabilis	Pinus, Quercus, Abies, Alnus
TCS-22	30°29.448′N	79°12.466′E	3135	Q. semecarpifolia, R. campanulatum, A. spectabilis	Pinus, Abies
TCS-23	30°29.377′N	79°12.462′E	3156	Q. semecarpifolia, R. campanulatum, R. barbatum, A. spectabilis	Pinus, Abies, Quercus, Alnus
TCS-24	30°29.375′N	79°12.504′E	3202	R. campanulatum, R. barbatum, A. spectabilis	Pinus, Abies, Alnus, Betula
TCS-25	30°29.307′N	79°12.521′E	3220	R. campanulatum, R. barbatum, A. spectabilis	Pinus, Quercus, Alnus
TCS-26	30°29.306′N	79°12.561′E	3232	R. campanulatum, R. barbatum, A. spectabilis	Pinus, Abies,
TCS-27	30°29.302′N	79°12.701′E	3248	R. campanulatum, R. barbatum, A. spectabilis	Pinus, Alnus
Zone III
TCS-28	30°29.342′N	79°12.861′E	3308	R. anthopogon, R. lepidotum, ground taxa (such as Poaceae, Astreraceae, etc.)	Pinus, Alnus, Quercus, Poaceae
TCS-29	30°29.363′N	79°12.965′E	3398	R. anthopogon, R. lepidotum, ground taxa	Pinus, Alnus, Abies, Poaceae
TCS-30	30°29.323′N	79°12.032′E	3450	R. anthopogon, R. lepidotum, ground taxa	Pinus, Alnus, Poaceae
TCS-31	30°29.353′N	79°12.038′E	3508	R. anthopogon, R. lepidotum, ground taxa	Pinus, Alnus, Poaceae, Polygonaceae
TCS-32	30°29.341′N	79°12.081′E	3532	R. anthopogon, R. lepidotum, ground taxa	Pinus, Alnus, Poaceae
TCS-33	30°29.340′N	79°12.092′E	3588	R. anthopogon, R. lepidotum, ground taxa	Pinus, Alnus, Poaceae, Asteroideae
TCS-34	30°29.210′N	79°12.202′E	3625	R. anthopogon, R. lepidotum, ground taxa	Pinus, Alnus, Poaceae, Asteroideae
TCS-35	30°29.179′N	79°12.285′E	3677	R. anthopogon, R. lepidotum, ground taxa	Pinus, Alnus, Quercus, Poaceae

Maceration

In order to extract the pollen-spores from the soil samples, 10 g of each sample was boiled in 10% Potassium Hydroxide (KOH) solution for 15 min to deflocculate the palynomorphs from the soil and to dissolve the humus. This was followed by the treatment of the samples with 40% Hydrofluoric Acid (HF) in order to remove the silica. Subsequently, the samples were acetolysed (Erdtman, 1953), using acetolysis mixture (ratio of 9:1 of acetic anhydride and concentrated sulphuric acid, respectively). Acetolysis dissolves most of the tissues and organic debris, and removes the proteins, lipids and carbohydrates from the surface of the palynomorphs (Erdtman, 1960). This gives the pollen-spores more clarity and easier to identify. The samples were finally prepared in 50% glycerine solution for microscopic examination. Two drops of Phenol were also added to the macerates to avoid any kind of fungal or microbial growth in the macerated samples.

Microscopic study

The extracted pollen-spores were studied under an Olympus CX41 light microscope, with 40× magnification, by making temporary slides mounted on glycerine. For the proper identification of palynomorphs, the reference pollen slides available at the museum of Birbal Sahni Institute of Palaeosciences were consulted. Some published sources related to pollen and NPPs were also referred (Basumatary et al., 2019; Gupta and Sharma, 1986; Moore and Webb, 1978). Normally, more than 400 pollen-spores per sample were counted, which was taken as the Total Palynomorph Count (TPC). To calculate the arboreal pollen/non-arboreal pollen ratio (AP/NAP), the Total Pollen Sum (TPS) was taken into account, where the spores of the lower plants (ferns, algae and fungi) were excluded from the TPC, due to their origin from local sources. However, for depicting the total palynomorph assemblage (pollen and NPPs), the TPC was taken into consideration. The pollen diagram was constructed using TILIA and TG View Software (Grimm, 1990). The pollen were grouped as arboreals (conifers and broad-leaved taxa) and non-arboreals (herbaceous taxa) in the pollen diagram (Figure 5). The local taxa (NPPs) were grouped as fern allies, algal and fungal remains (including coprophilous fungi) and represented in a separate percentage diagram (Figure 6).

Figure 5.

Pollen diagram showing the frequency distribution of palynomorphs recovered from the surface samples.

Figure 6.

Frequency distribution of the non-pollen palynomorphs (NPPs) recovered from the surface samples.

Numerical analyses

To assess if our pollen data can distinguish the different vegetation zones, we applied discriminant analysis (DA) on the pollen abundance data of the 35 surface samples, collected from the three vegetation zones, along the altitudinal gradient. DA demonstrates that how well linear functions could classify pollen assemblages into their predefined vegetation zones. This analysis also identifies the important pollen taxa, which have the potential to distinguish between the different vegetation types (Liu and Lam, 1985; Lynch, 1996). DA has been done using SPSS 16 (SPSS Inc Released, 2007).

We also applied detrended correspondence analysis (DCA) on our surface pollen data to estimate the ecological/environmental gradient length of the region under study. DCA also helps to understand whether a linearity-based or unimodal-based ordination method is appropriate to understand the similarity/dissimilarity between the samples and their associations with the species. We performed DCA (Hill and Gauch, 1980) by detrending the linear segments, and down-weighting the rare species to estimate the compositional gradient lengths along the first few DCA axes. The gradient length of the first DCA axis >2 SD (standard deviation) suggests that uni-modal based method (CA/CCA) is appropriate; however, a < 2 SD gradient length of DCA axis 1 indicates that a linearity-based method (PCA/RDA) would be appropriate to visualise the distribution of pollen species and samples along the vegetation/altitudinal gradients (Ter Braak and Verdonschot, 1995). Considering the results of DCA, we performed principal component analysis (PCA) on the pollen abundance data.

Results

Palynological analysis

To estimate the representation of various taxa of the present vegetation prevailing in the pollen-rain, palynological analysis of 35 surface sediment samples was undertaken along the altitudinal transect (2700–3680 m), in the Chopta-Tungnath region. On the basis of the altitudinal variations, three vegetation zones were demarcated. Zone I (2700–3100 m) shows a mixed-temperate type of vegetation and is dominated by Quercus semecarpifolia and Rhododendron arboreum. Zone II (3100–3250 m) is characterised by sub-alpine vegetation, comprising of Rhododendron campanulatum, along with Abies spectabilis and Quercus semecarpifolia. Zone III is above the tree-line (3250 masl) and is characterised by alpine-scrub and meadows. 20, 7 and eight samples each were analysed from the above three zones, respectively (Figure 4). The location of the samples and the dominant vegetation with characteristic pollen assemblages are listed in Table 2. The pattern of occurrence of palynomorphs in each zone is described below (Figure 5; Supplemental File 1).

Zone I (2700 m to 3100 masl): Mixed-temperate forests

Palynological analysis of samples from Zone I (Sample No. TCS-1 to TCS-20) revealed relatively high frequencies of arboreal (trees) pollen (especially conifer pollen), over the non-arboreal (herbaceous taxa) components. The different conifer pollen are all bisaccate, but can be differentiated from each other by distinct morphological features specific to each genus, such as overall size, corpus (central body), saccus size, pattern of attachment of the saccus with the corpus, etc. Pinus pollen is of 60–90 µm, sacci relatively large, attached along the full width of the corpus, forming poorly developed re-entrant angles. Picea pollen is 80–110 µm in size, sacci attached almost along the full length and width of the corpus, forming no re-entrant angles. Abies pollen is 100–130 µm in size, sacci relatively large, it is distinguished from Pinus by its larger size (>80 µm) and from Picea by the angular transition between the sacci and corpus. Cedrus pollen is of 60–90 µm, the most distinguishing feature is that the sacci are smaller than the corpus, and marginal crest is well developed with deep undulations (Figure 7).

Figure 7.

Some representative pollen and spores from the surface soil samples. (1 and 2) Pinus. (3 and 4) Abies. (5 and 6) Cedrus. (7 and 8) Picea. (9) Alnus. (10) Quercus. (11) Rhododendron. (12) Betula. (13) Juglans. (14) Corylus. (15) Asteroideae (Tubuliflorae). (16) Cichorioideae (Liguliflorae). (17) Caryophyllaceae. (18) Amaranthaceae. (19) Artemisia. (20 and 21) Poaceae. (22) Ranunculaceae. (23) Saxifragaceae. (24) Cyperaceae. (25) Rosaceae. (26) Apiaceae. (27) Solanaceae. (28) Balsaminaceae. (29) Polygonaceae. (30) Geraniaceae. (31) Monolete fern spore. (32) Trilete fern spore. (33) Tetraploa. (34) Glomus. (35) Microthyriaceae. (36) Podospora. (37) Sporormiella. (38) Sordaria. (39) Cercophora. (40) Ascodesmis. (41) Nigrospora.

Among the conifers, Pinus shows the highest pollen frequency and ranges between 29% and 77%. Other conifers, like Abies are also well represented (2–16%), while pollen of Cedrus (1–6.5%) occur in lower amounts. Picea and Juniperus pollen are found only in one sample with extremely low values. The temperate broad-leaved taxa are observed in variable amounts, of which Quercus is represented with highest numbers (2–21%), while Alnus is also fairly represented (1.5–10%), Rhododendron (0.5–7%) is also well represented. Other broad-leaved taxa, Betula (0.5–3%), Corylus (0.5–1%), Ulmus (0.5–1.5%), Myrica (0.5–1%) and Acer (0.5–2%) occur sporadically and Juglans is encountered only in one sample.

Non-arboreals are mostly identified up to the family level. Most frequently occurring non-arboreals are the members of Poaceae (1–12%), Polygonaceae (0.5–9%), Solanaceae (0.5–5%), Rosaceae (0.5–4%), Ranunculaceae (0.5–3%), Apiaceae (0.5–2%), Saxifragaceae (0.5–2%), Euphorbiaceae (0.5–2.5%), Cyperaceae (0.5–2%) and Brassicaceae (0.5–1%). The representation of the members of Balsaminaceae, Acanthaceae, Geraniaceae, Lamiaceae, Papaveraceae, Liliaceae, Malvaceae, Convolvulaceae, Caprifoliaceae, Fabaceae, Rutaceae, Oleaceae and Potamogetanaceae are sporadic and low. Among the steppe elements, Artemisia (0.5–3.5%), Amaranthaceae (0.5–2%) and Caryophyllaceae (0.5–1%) are represented in low amounts in the pollen assemblage. Members of sub-families of Asteraceae: Asteroideae (0.5–13.5%) and Cichorioideae (0.5–1.5%) are well recorded.

Zone II (3100 m to 3250 masl): Sub-alpine forests

The pollen records from Zone II (Sample No. TCS-21 to TCS-27) clearly indicate that as the altitude increases, herbaceous pollen become more abundant (especially above 3000 m), while the trees and shrubs experience a small decline. Amongst the conifers, Pinus maintains its predominance, with 33–64%. Abies (3–10%) and Cedrus (0.5–12%) are also represented in good amounts. Picea (0.5–1%) and Juniperus (<0.5%) are sporadically recorded. Among the broad-leaved taxa, Alnus (2.5–11%) and Quercus (0.5–15%) are represented in good amounts. Betula (1–2%), Rhododendron (0.5–1%), Ulmus (1–1.5%) and Corylus (0.5–1%) are comparatively lesser. Acer and Syzygium are rare and found in only one sample of this zone.

Among the non-arboreals, the prominent taxa are Asteroideae (2.5–7%), Poaceae (2–7%), Polygonaceae (0.5–7%), Solanaceae (0.5–6%), Rosaceae (1–2%) and Artemisia (0.5–2.5%). Other taxa, such as Ranunculaceae (0.5–2%), Euphorbiaceae (0.5–1.5%), Cichorioideae (0.5–1.5%), Amaranthaceae (0.5–3.5%), Geraniaceae (0.5–1%), Lamiaceae (1–1.5%), Cyperaceae (0.5–1%), Apiaceae (0.5–2%) and Papaveraceae (0.5–1%) are infrequent. Pollen of Caryophyllaceae, Malvaceae, Convolvulaceae, Balsaminaceae, Lentibulariaceae, Rutaceae, Saxifragaceae and Liliaceae are encountered in only one or two samples of this zone.

Zone III (3250 m to 3680 masl): Alpine-scrub and meadows

From this zone, eight surface samples (TCS-28 to TCS-35) were analysed, starting from the tree-line up to the highest point in the region, the Chandrasila peak. Pinus (35–67%) maintains its high abundance among all the pollen taxa, similar to the samples of Zone I and Zone II. A slight decrease in the percentage of Abies (1–5%) and Cedrus (0.5–3%) is observed as compared to the other two zones. Picea and Juniperus are very less in amount and recorded sporadically as in the previous zones. Among the broad-leaved taxa, Alnus (6.5–16%), Quercus (0.5–6%), Rhododendron (0.5–3%) and Betula (0.5–3.5%) are better represented; Myrica (0.5–2%) and Corylus (0.5–2%) are also common, whereas, Acer and Juglans are quite sparse.

The prominent taxa among the non-arboreals are Poaceae (1.5–22%), Asteroideae (0.5–4.5%), Solanaceae (0.5–5.5%), Artemisia (0.5–2.5%) and Polygonaceae (0.5–4.5%). Other taxa, such as Amaranthaceae (0.5–2%), Brassicaceae (0.5–2%), Cichorioideae (0.5–2.5%), Apiaceae (0.5–1%) and Saxifragaceae (0.5–2%) are represented in low frequencies. Pollen remains of Caryophyllaceae, Cyperaceae, Geraniaceae, Ranunculaceae, Euphorbiaceae, Liliaceae, Malvaceae, Convolvulaceae, Rosaceae, Lentibulariaceae, Rutaceae and Potamogetonaceae are quite low and infrequent.

Non-pollen palynomorphs (NPPs)

In Zone I, among the NPPs, fern allies (Davallia, other monolete and trilete spores) are present in all the samples with variable frequencies (5.5–11.5). The coprophilous fungal spores, such as Sporormiella (1–1.5%) and Sordaria (1.5–2.5%) are common in all the samples, while Podospora, Cercophora and Ascodesmis occur sporadically. Other fungal elements, such as Glomus, Nigrospora, Tetraploa and Microthyriaceae are also encountered. Algal elements along with Spirogyra and Botryococcus are recorded in lesser amounts.

In Zone II, both the monolete and trilete spores are well recorded, with values of 5–9%. Amongst the coprophilous fungi, Sporormiella (1–1.5%) and Sordaria (2–3%) are common. Podospora, Cercophora and Ascodesmis are less in value. The other fungal remains such as Glomus, Nigrospora and Microthyriaceae are represented in lesser amounts. The prominent algal elements are Spirogyra and Botryococcus, which are also recorded in low frequencies along with other algal elements.

Above the tree-line in Zone III, the remains of NPPs show a small decrease in their frequencies, as compared to the previous two vegetation zones, except the slight increase in the amount of coprophilous fungal spores. Among the fern allies, monolete and trilete spores are common, with values ranging between 3.5% and 7%. Coprophilous fungal components are represented by Sporormiella (1–1.5%) and Sordaria (1.5–2%), whereas Podospora, Cercophora and Ascodesmis are very less in number. Among the other fungal remains, Glomus, Nigrospora, Cookeina and Microthyriaceae maintain their presence, however, with low values. The algal remains are also lesser in numbers (Figure 6; Supplemental File 2).

Multivariate analysis

Abundance (%) data of all the 45 pollen taxa, recovered from the 35 surface samples from the three vegetation zones were subjected to DA and PCA. Summary results for DA are represented in Figure 8a (Supplemental File 3). Linear discriminant functions have successfully classified 91.4% of the surface samples into their original vegetation zones. Of the 35 samples, only three are misclassified. One sample from the mixed-temperate forests is grouped with the samples from the sub-alpine zone. Similarly, one sample from the sub-alpine zone is found to be associated with the samples collected from the mixed-temperate forests. However, one sample collected from the alpine-scrub vegetation is grouped with those collected from the mixed-temperate forests. The eigenvalues explain the proportion of variance in the dataset. Here, the larger eigenvalue indicates a strong function as in DA function 1 (Table 3). The canonical correlation indicates a correlation between the discriminant scores and the dependant variables. Here, the high correlation suggests a function that discriminate well (Table 3). In this analysis, the first two canonical discriminant functions are used, and a small Wilks’ Lambda (0.091) associated with discriminant function 1 (with Sig. = 0) indicates that the group means differ significantly (Figure 8a). A high Wilks’ Lambda nearing to 1.00 suggests that the group means are equal, and a small value indicates that within-groups similarity is small, as is the case here. Hence, the discriminant function 1 is most significant here. From the correlation of pollen taxa with discriminant function 1, it appears that plants like Abies, Brassicaceae, Juglans, Juniperus, Myrica, Caprifoliaceae, Fabaceae, Quercus, Artemisia, Oleaceae and Saxifragaceae show a strong correlation with discriminant function 1 (Supplemental File 3).

Table 3.

Summary of discriminant analysis (DA) results for modern pollen data from the three different vegetation zones.

Total no. of surface samples: 35Number of misclassified samples: 3Percentage of samples correctly classified: 91.4
Vegetation zones	Predicted group
Actual group	No. of samples	Mixed-temperate forests	Sub-alpine vegetation	Alpine-scrub vegetation
Mixed-temperate forests	20	19 (95%)	1 (5%)	0 (0%)
Sub-alpine vegetation	7	1 (14.3%)	6 (85.7%)	0 (0%)
Alpine-scrub vegetation	8	1(12.5%)	0 (0%)	7 (87.5%)
Summary of canonical discriminant functions	Eigenvalue	Percentage of variance of dependent variable	Cumulative percentage of variance of dependent variable	Canonical correlation	Significance
	3.446^a	69.9	69.9	0.880	0
	1.484^a	30.1	100	0.773	0

The first two canonical discriminant functions were used in the analysis.

Figure 8.

Showing summary results of (a) DA and (b) PCA done on the surface pollen data (Pin – Pinus, Abi– Abies, Pic– Picea, Ced – Cedrus, Juni – Juniperus, Que– Quercus, Bet– Betula, Cory– Corylus, Ulm– Ulmus, Aln– Alnus, Rhodo– Rhododendron, Myri– Myrica, Ace– Acer, Jugl– Juglans, Syzyg– Syzygium, Tubuliflo– Tubuliflorae (Asteroideae), Liguliflo– Liguliflorae (Cichorioideae), Artem– Artemisia, Caryophyll– Caryophyllaceae, Amaran– Amaranthaceae, Balsa– Balsaminaceae, Cyper– Cyperaceae, Acanth– Acanthaceae, Brass– Brassicaceae, Geran– Geraniaceae, Lamia– Lamiaceae, Ranuncula– Ranunculaceae, Polygona– Polygonaceae, Papav– Papaveraceae, Euphor– Euphorbiaceae, Lilia– Liliaceae, Mal– Malvaceae, Convo– Convolvulaceae, Rosa– Rosaceae, Capri– Caprifoliaceae, Poa– Poaceae, Faba– Fabaceae, Lenti– Lentibulariaceae, Ruta– Rutaceae, Solana– Solanaceae, Saxifra– Saxifragaceae, Apia– Apiaceae, Olea– Oleaceae, Potam– Potamogetonaceae, UNA– unidentified non-arboreals).

DCA estimates the indirect environmental gradients implied by the pollen data (ter Braak and Verdonschot, 1995). All the DCA axes show <2 SD gradient lengths and thus indicate a short ecological gradient (Table 4). Hence, we applied PCA on the pollen data to understand the environmental variability, explained by the pollen data indirectly. The results of the DCA and PCA are represented in Table 4. The PCA ordination plot showing distribution of pollen taxa and surface samples from the three vegetation zones is represented in Figure 8b. The first two axes of PCA explain about 37.8% of the pollen data, of which axis 1 represents 19.4%. The first PCA axis represents the highest eigenvalue, suggesting that the PCA 1 is the strongest axis (Table 4). From the scores of the surface samples on PCA 1 and the ordination plot, it is apparent that the samples collected from the alpine-scrub vegetation have loadings between 0 and −0.5; whereas, samples collected from the sub-alpine zone show loadings between 0 and 1.0. However, samples collected from the mixed-temperate forests show considerable mixing with those collected from the sub-alpine zone and show loadings between 1.0 and −0.5 (Supplemental File 4). Among the pollen taxa, Tubuliflorae, Solanaceae, Betula, Ranunculaceae, Convolvulaceae and Polygonaceae, etc. show highest positive loadings on axis 1, while Pinus, Myrica, Acer and Brassicaceae, etc. show negative loadings on axis 1 (Supplemental File 5).

Table 4.

Summary results of detrended correspondence analysis (DCA) and principal component analysis (PCA) on the pollen data.

	DCA
	Axis 1	Axis 2	Axis 3	Axis 4
Eigenvalue	0.118	0.059	0.031	0.019
Gradient length (SD)	1.189	1.023	0.957	0.635
Cumulative percentage variance of pollen data (%)	20.3	30.4	35.8	39.0
	PCA
	Axis 1	Axis 2	Axis 3	Axis 4
Eigenvalue	0.194	0.184	0.128	0.061
Cumulative percentage variance of species–environment relation	19.4	37.8	50.6	56.7

SD: standard deviation units for DCA.

Discussion

Comparison of palynological assemblages among the three vegetation zones

The comparative study of the palynological data recorded from the three vegetational zones at different altitudes, have brought out the broad similarities, as well as the differences amongst them. The pollen-rain in each zone reveals high frequencies of arboreals over the non-arboreal pollen taxa (Figure 9).

Figure 9.

Composite pie diagrams showing the frequency distribution of Pinus and other groups of taxa from (a) Zone I. (b) Zone II. (c) Zone III. These have been constructed on the basis of Total Palynomorph Count (TPC).

The palynological assemblage from Zone I (2700–3100 m), reflects an overall dominance of arboreals, especially conifers, over the non-arboreals. Amongst the conifers, Pinus is the predominant taxa (44%). Other conifers (Abies, Cedrus, Picea and Juniperus) constitute 7%, and the broad-leaved elements account for 16% of the assemblage. The average value of non-arboreal herbaceous vegetation is 19%. Amongst the NPPs, fern spores show an average frequency of 7%. Algal elements (1%) and coprophilous fungi (4%), along with other fungal elements (2%), are also common. The palynological assemblages from Zone II (3100–3250 m), similarly show the high frequencies of arboreal pollen taxa over the non-arboreals in most of the samples. Pinus (36%) is the most abundant among the conifers. Other coniferous taxa account for 9% and the broad-leaved taxa are 14% of the total assemblage. The average value of non-arboreal pollen taxa is 27%. Fern allies (6%), algal elements (2%) and coprophilous fungi (3%), along with other fungal elements (3%), are almost similar in frequencies, as in the previous Zone. The palynological assemblages from Zone III (3250–3680 m) are also characterised by the abundance of arboreal taxa over the non-arboreal taxa. Pinus, as usual, represents the maximum abundance having an average frequency of 45%. The other conifers constitute an average value of 5%, while the temperate broad-leaved taxa are 13% of the pollen assemblage. The average value of non-arboreal herbaceous elements is 26%. NPPs are represented by fern allies (5%), algal spores (1%), coprophilous fungal spores (4%) and other fungal elements (1%).

So, the common point in all the three vegetation zones is the absolute dominance of Pinus pollen across the altitudinal divide. Here, the most noticeable feature is that the frequencies of temperate broad-leaved taxa show a subtle decreasing trend from the lower to the higher altitudes. This representation of broad-leaved pollen, is compatible to its actual presence along the altitudinal transect. The broad-leaved trees are more common at lower altitudes (Zone I) and gradually show a decreasing trend towards the higher altitudes (Zone II and Zone III), which is well manifested in the respective pollen assemblages. This variation in the frequencies of temperate broad-leaved taxa is because of their relative lack of buoyancy and low pollen dispersal capacity, as compared to conifer pollen. The pollen of the broad-leaved taxa are unable to be transported to long distances in large amounts, and thus have got deposited more in the lower reaches than that in the higher altitudes. Another differing feature is that the remains of NPPs in the higher altitudes (above the tree-line) show a decrease in their frequencies. This is probably because of the decrease in temperature at higher altitudes, which is not favourable for the growth of fungal and fern allies.

Over-representation of extra-local vegetation

The dominant vegetation across the sampling transect, at the study site, and the dominant pollen taxa recovered from the surface samples are rather different. The palynological data show that Pinus is the major element of the pollen-rain and the pollen assemblages of all the three vegetation zones show an overwhelming dominance of Pinus pollen over all the other arboreal and non-arboreal taxa. The primary reason for the abundance of Pinus is its bountiful pollen production, excellent pollen dispersal efficiency and good preservation potential in the sediments (Andersen, 1970; Bajpai and Kar, 2018; Ertl et al., 2012; Kar et al., 2015; Pidek et al., 2010; Quamar et al., 2018). The high concentration of sporopollenin, the most chemically inert biological polymer, in the outer wall (exine) of Pinus pollen, makes it resistant towards oxidation and degradation (Havinga, 1984), facilitating the good preservation of Pinus pollen in the sediments. Moreover, pollen of Pinus are lighter in weight and have good buoyancy character; therefore, they are transported over long distances (55–60 km and even more), by the action of upthermal winds (Bajpai and Kar, 2018; Richardson, 1998). All the above attributes of profuse pollen production, efficient dispersal and preservation, have aided in the abundant representation of Pinus pollen in the sediments, though Pinus is not part of the vegetation in the vicinity of the study area. Besides Pinus, other conifers like Abies, Cedrus, Picea and Juniperus are represented in lower frequencies in the sediments, which is primarily due to lower pollen productivity and poor preservation, coupled with their larger size of pollen grains that inhibit their far-off dispersal, as compared to Pinus pollen. Though Abies is the third most dominant tree after Quercus and Rhododendron and is a component of the tree-line, its pollen is not as abundantly represented as that of Pinus.

The transportation of air-borne pollen over large areas, depends on the weather conditions like wind direction and velocity, temperature, atmospheric pressure, relative humidity and precipitation (Hjelmroos, 1991). In the present study, wind velocity and direction seems to have played an important role in transporting the pollen from the lower reaches to the higher altitudes. A comprehensive study conducted over a period of 7 years to monitor the influx of pollen in the Swiss Alps, found an abundance of Pinus and Alnus pollen in the upper forest limit, though these trees were not present in the near vicinity of the pollen traps (van der Knaap et al., 2001). It has also been observed in the Andes that the strength and regularity of upslope winds have played an important role in the deposition of Alnus pollen from the low-lying forest areas to the higher altitudes (Weng et al., 2004). In our present study also, Alnus is the most abundant extra-local pollen after Pinus, and shows high frequencies throughout all the three zones in increasing order (1.5–10%, 2.5–11% and 6.5–16% in Zone I, Zone II and Zone III, respectively).

Representation of broad-leaved arboreal vegetation

Among the broad-leaved trees, Quercus shows the highest frequencies, but its numbers continuously decrease from the lower to the higher altitudes (2–21%, 0.5–15% and 0.5–6% in Zone I, II and III, respectively). This is compatible with the actual presence of Quercus in the area. Quercus is one of the dominant taxa of the temperate forests in Zone I and accordingly, it is represented in the pollen assemblage in Zone I. In the higher altitudes, the frequency of Quercus decreases, which is manifested in the lesser amounts of Quercus pollen in the upper vegetation zones (Zone II and III). Nonetheless, Quercus pollen is present above the tree-line, which has been dispersed from the Quercus trees in the lower altitude and deposited in the sediments above the tree-line. However, it is not as abundant as Pinus pollen, because Quercus is a much lesser pollen producer, as compared to Pinus. Other broad-leaved taxa, such as Rhododendron, Betula, Corylus, Ulmus, Myrica, Acer, Juglans and Syzygium are encountered in low frequencies. This can be mainly ascribed to their low pollen productivity. Of the above taxa, Rhododendron is one of the dominant components of the temperate forests and alpine-scrub vegetation. Different species of Rhododendron are present throughout the sampling transect, depending upon their respective altitudinal niche. However, the scarcity of Rhododendron pollen is quite striking, despite its luxuriant presence in the vegetation, which is primarily due to it being an extremely low pollen producer, probably due to its entomophilous nature. The average frequencies of Rhododendron in Zone I, Zone II and Zone III are 1.8%, 0.65% and 0.80% respectively. So, among the two dominant broad-leaved taxa, the representation of Quercus pollen is compatible to its actual presence in the area, whereas Rhododendron is under-represented.

Representation of non-arboreal vegetation

Among the herbaceous taxa, Poaceae represents maximum frequencies in the modern pollen-rain, which is because of its dominant presence in the ground vegetation. The average frequency of Poaceae continuously increases from the lower reaches to the higher altitudes (3%%, 4.5% and 8.7% in Zone I, Zone II and Zone III, respectively). Cichorioideae have meagre representation, whereas Asteroideae is recorded with high values in the pollen assemblages. Pollen grains of Rosaceae, Solanaceae, Ranunculaceae and Apiaceae are encountered in low frequencies, which, nonetheless, indicate their presence in the ground vegetation. The non-arboreal pollen taxa, largely represent the ground vegetation. They seem to be apparently lesser than the arboreals, but that is because of the overwhelming presence of Pinus pollen. Low temperature can also be a factor for the poor pollen production of these families, which reduces the activities of pollinators. Other non-arboreal taxa like Balsaminaceae, Acanthaceae, Geraniaceae, Lamiaceae, Papaveraceae, Euphorbiaceae, Liliaceae, Malvaceae, Convolvulaceae, Caprifoliaceae, Fabaceae, Lentibulariaceae, Rutaceae, Saxifragaceae and Oleaceae are also recovered sporadically in the modern pollen-rain. Because of the presence of alpine-scrubs and meadows at the higher altitudes, and in the absence of arboreals, the average frequency of non-arboreal taxa is showing an increasing trend from the lower reaches (19% in Zone I) to the higher altitudes (27% and 26% in Zone II and Zone III, respectively).

Evidences of anthropogenic impact

The area is witnessing a steady increase in anthropogenic activities over the last two decades or so, due to the ever increasing footfall of tourists. This has led to construction activities around the hamlet and also along the entire trekking path, from Chopta to the Tungnath temple. Moreover, lopping and over-grazing for fodder by sheep, goats, mules and cattle are common during the entire growing season (Hajra and Rao, 1990; Rai et al., 2012a). At the study site, anthropogenic impact is clearly evident in the form of grazing by domestic animals. This is inferred by the increased frequencies of Asteraceae pollen in the palynological records, as these plants are generally avoided by the grazers due to the presence of thorns and sap in their flowers (Mazier et al., 2006). Caryophyllaceae and Artemisia are also encountered in the modern pollen assemblages. Presence of these taxa in the study area further indicates the intense grazing activities because of the availability of open terrain (alpine meadows) (van Geel et al., 2003). The presence of families related to cultural pollen taxa, such as Amaranthaceae, Brassicaceae, Caryophyllaceae and Artemisia signifies the anthropogenic activities in the area. Significant presence of Polygonaceae pollen is also indicative of the anthropogenic activities in the vicinity in the lower reaches, and might be related to pasturage (Yao et al., 2015).

The presence of coprophilous fungi (dung-loving fungi), such as Sporormiella, Sordaria, Podospora, Cercophora and Ascodesmis in higher numbers, throughout the altitudinal transect further validates the presence of grazers in the region. It is evident in the percentage diagram (Figure 6) that around the grassy meadows (in Zone I) and near to the Tungnath temple in Zone III, the concentration of coprophilous fungi is more, as compared to the other samples. Mules are quite commonly used to ferry religious tourists from the road head (Chopta) up to the Tungnath temple, and also for carrying goods, eatables, etc. to the lodges and food joints along the trekking track. The final resting place and halt of the mules is at the temple, and these are left to graze in the meadows located in the forest clearings, and hence the percentage of coprophilous fungi is more at these sites.

Calibration of the fossil records

The primary objective of undertaking palynological studies in the area is for deciphering the Holocene climatic changes and vegetation dynamics in the region. In this context, sub-surface sediment sampling has been done by digging trial-trenches along the altitudinal transect and pollen-based palaeoclimatic studies have been initiated (Mishra, 2020). A trench of 105 cm depth, from the mixed-temperate forests (2700 masl), has given a chronology of ca. 4.8 kyr BP, in which an abundance of Pinus pollen is observed across the profile (Figure 10). Another trench at the transition of mixed-temperate forests and the Krummholz Zone (3050 masl), having a depth of 150 cm and a chronology of ca. 11.5 kyr, is also characterised by the dominance of Pinus pollen throughout the sequence (Figure 11). This is indeed quite a noteworthy feature and is completely comparable with the surface pollen assemblages. This overwhelming dominance of Pinus pollen in the sub-surface profiles, across the Holocene, could have created confusion in the interpretation of the fossil pollen records, had it not been correlated and found to be similar to that of the modern pollen data.

Figure 10.

Pollen diagram of fossil pollen assemblages showing the major groups of taxa from a trench having a chronology of ca. 4.8 kyr BP. Note the abundance of Pinus pollen throughout the sequence.

Figure 11.

Pollen diagram of fossil pollen assemblages showing the major groups of taxa from a trench having a chronology of ca. 11.5 kyr BP. Note the abundance of Pinus pollen throughout the sequence.

Another important feature is the poor representation of Rhododendron in the fossil pollen assemblages of both the trenches (Figures 10 and 11). Different species of Rhododendron are abundant elements of the extant vegetation; however, these are under-represented in the modern pollen assemblages as well (Figure 5), which is similar to that in the sub-surface samples. The frequencies of Quercus, another dominant component of the present arboreal vegetation, in the fossil records, are similar to that of the modern pollen assemblages. Subtle changes across the sub-surface profiles are observed in the percentages of Quercus pollen, which would be useful for palaeoclimatic inferences. Quercus is an important indicator taxon in the temperate Himalayan region and changes in its pollen frequencies have been widely used for palaeoclimatic interpretations (Kar and Quamar, 2019 and the references cited therein). The changing frequencies of Quercus and Pinus pollen (Q/P ratio) have also been used to decipher the Late-Holocene climatic fluctuations in the Higher Himalayas (Phadtare, 2000). Besides the above, other arboreal taxa are found to be of similar frequencies in both the surface and sub-surface samples. The frequencies of herbaceous taxa also show a broad compatibility in the surface and sub-surface samples. Based on the changing frequencies of the arboreal and non-arboreal pollen (AP/NAP ratio), different ‘Pollen Zones’ have been demarcated, which distinguish the warmer/colder phases (Figures 10 and 11). The data on pollen–vegetation relationship generated in the present study have immensely helped in developing the modern-analogues. The compatibility of the modern surface pollen assemblages with that of the subsurface fossil pollen records have helped in calibrating the fossil pollen assemblages, for reconstructing the vegetation and concurrent climatic changes during the Holocene.

Non-pollen palynomorphs (NPPs): Environmental and anthropogenic implications

In the present study, various types of NPPs, organic-walled microfossils of dissimilar origin and nature, were recovered. The fern allies that are mainly represented in the form of spores (Taylor et al., 2005) occur in all the surface sediment samples. As the fern allies are present in considerable amounts in the pollen assemblages, it reflects the mesic type of habitat around the study area, which is characterised by a high and well-balanced supply of moisture (Kato, 1993; Kessler et al., 2011).

Some algal spores, represented by the zygospores of green algae, Spirogyra (Zygnemetaceae), are observed. These reflect shallow water conditions and small ephemeral pools or waterlogged conditions in the area. In the pollen assemblages, Botryococcus is present in an uneven way, which indicates seasonal warmer conditions (Salgado-Labourian and Schubert, 1977).

Among the fungal elements, Glomus (symbiotic nature), Nigrospora and Tetraploa (parasitic nature), Cookeina (saprophytic nature) and Microthyriaceae were recorded, which indicate the humid environment of the study area (Quamar and Bera, 2015). It has been observed that the presence of Glomus is indicative of active soil erosion processes in the catchment area (Anderson et al., 1984; Medeanic and Silva, 2010). Spores of Glomus and Tetraploa can also be the indicators of drier climatic conditions (Musotto et al., 2012), which may be seasonal (summer) in the area of study. Nigrospora is pathogenic to grasses and some angiosperms, and can be an indicator of warm climatic conditions (Esposito et al., 1962; Wright et al., 2008).

Another important feature is the presence of several types of coprophilous fungi that flourish on animal dung. Sporormiella, is found only on the dung of herbivores, such as cattle, sheep, goats, horses, etc. (Bell, 1993; Davis and Shafer, 2006; Pirozynski et al., 1988; Raper and Bush, 2009). Almeida-Lenero et al. (2005) suggested that Sporormiella and Sordaria are generally associated with grazing activities and also show their link with herbaceous vegetation. Factually, Sporormiella, Podospora and Sordaria are coprophilous in nature (Blackford and Innes, 2006; Davis and Shafer, 2006; Ghosh et al., 2017; van Geel and Aptroot, 2006), whereas Cercophora, Ascodesmis and Sordariaceous ascospores are not only coprophilous, but also occur on dead plant materials and other decaying substrates (van Geel and Aptroot, 2006). So, among the NPPs, the records of these coprophilous fungal spores in the modern pollen assemblages, may be useful as one of the most reliable indicators for the inception of grazing activities and for a better understanding of the intensification of anthropogenic pressure in the area, by correlating the modern data with that of the fossil records.

Statistical analysis

Linear discriminant analysis (DA) performed on the surface pollen data from the Chopta-Tungnath area, Western-Higher Himalaya indicates that the dataset can efficiently distinguish different vegetation zones along the temperate-alpine elevation gradient (Figure 8a). Misclassification of a low number of samples may be due to their sampling from the transition zone of two vegetation types, or over representation of Pinus pollen grains in all the samples from the three different vegetation zones. It is to be noted that Pinus is not among the components of the studied vegetation zones. Perhaps its high pollen production than the broad-leaved taxa and transport through winds have created this bias. This is also reflected in the DA results, where Pinus does not show any strong correlation to discriminant function 1. Whereas, taxa such as, Abies, Brassicaceae, Juglans, Juniperus, Myrica, Caprifoliaceae, Fabaceae, Quercus, Artemisia, Oleaceae and Saxifragaceae show potential to distinguish the different vegetation zones.

PCA results also show that most of the surface samples are grouped separately, except a few, especially the samples from the mixed-temperate and sub-alpine zones (Figure 8b). Here, taxa like Quercus, Rhododendron, Ulmus, Alnus, Corylus and Betula show close associations to the samples collected from the mixed-temperate forests. Samples on the right side of the PCA biplot, from both the mixed-temperate and sub-alpine zones, show dominance of Abies, Juniperus, Rosaceae, Solanaceae, Tubuliflorae, Polygonaceae and Ranunculaceae, etc. Whereas, Poaceae shows close associations with the samples from the alpine-scrub zone. Hence, it may be inferred that the dominance of the above-mentioned pollen taxa in the regional fossil pollen spectra may be indicative of the respective vegetation zones.

Conclusion

The present work is the first approach towards establishing the modern pollen–vegetation relationship along an altitudinal transect from the Western-Higher Himalaya. This study has revealed relatively high frequencies of arboreal (trees and shrubs) pollen over the non-arboreals (herbaceous taxa) in each vegetation zone, along the altitudinal transect.

The pollen–vegetation relation shows a correlation on the basis of changes in the vegetation along the altitudinal transect. However, it is marked by the over-representation of extra-local Pinus pollen in the palynological assemblages, across all the vegetation zones.

The pollen–vegetation relation is basically non-linear, that is incompatible to the surrounding vegetation, due to the overwhelming dominance of Pinus pollen in all the samples. The over-representation of Pinus pollen is due to its prolific production, efficient wind dispersal (light and buoyant) and good preservation potential in the sediments.

Among the broad-leaved taxa, Quercus, which is one of the dominant elements in the present vegetation, is properly represented in the pollen-rain. On the other hand Rhododendron, though abundantly present in the extant vegetation, is under-represented in the pollen records, which is mainly because of its low pollen productivity.

The herbaceous ground vegetation is broadly compatible in the pollen records. High frequencies of Asteraceae pollen in the samples indicate the presence of extensive grazing and anthropogenic activities in the area. The records of other cultural markers, like Amaranthaceae, Brassicaceae, Polygonaceae and Solanaceae also reflect the human activities in the vicinity.

NPPs (pteridophytic spores, algal and fungal remains) are represented according to their presence in the vegetation and show a general decrease towards the higher altitudes. Good percentage of coprophilous fungi in the pollen records is due to the presence of grazers in the area.

Statistical analyses (DA, PCA) indicate that the pollen dataset can clearly distinguish the different vegetation zones across the altitudinal gradient.

This work would provide the modern analogues for pollen-based palaeoclimatic reconstructions for the Western-Higher Himalayan region, having similar temperate vegetation. The modern pollen data on cultural pollen and NPPs, especially the coprophilous fungi, would also help to interpret the inception and intensification of anthropogenic activities in this Higher Himalayan region.

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Supplemental material, sj-doc-4-hol-10.1177_09596836221096006 for Modern pollen–vegetation relationships along an altitudinal transect in the Western Higher Himalaya, India: Palaeoclimatic and anthropogenic implications by Amit Kumar Mishra, Ruchika Bajpai Mohanty, Ruby Ghosh, Kriti Mishra, Uma Kant Shukla and Ratan Kar in The Holocene

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Supplemental material, sj-doc-5-hol-10.1177_09596836221096006 for Modern pollen–vegetation relationships along an altitudinal transect in the Western Higher Himalaya, India: Palaeoclimatic and anthropogenic implications by Amit Kumar Mishra, Ruchika Bajpai Mohanty, Ruby Ghosh, Kriti Mishra, Uma Kant Shukla and Ratan Kar in The Holocene

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Supplemental material, sj-xlsx-1-hol-10.1177_09596836221096006 for Modern pollen–vegetation relationships along an altitudinal transect in the Western Higher Himalaya, India: Palaeoclimatic and anthropogenic implications by Amit Kumar Mishra, Ruchika Bajpai Mohanty, Ruby Ghosh, Kriti Mishra, Uma Kant Shukla and Ratan Kar in The Holocene

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Supplemental material, sj-xlsx-2-hol-10.1177_09596836221096006 for Modern pollen–vegetation relationships along an altitudinal transect in the Western Higher Himalaya, India: Palaeoclimatic and anthropogenic implications by Amit Kumar Mishra, Ruchika Bajpai Mohanty, Ruby Ghosh, Kriti Mishra, Uma Kant Shukla and Ratan Kar in The Holocene

Footnotes

Acknowledgements

We thank the Director, Birbal Sahni Institute of Palaeosciences, for providing the necessary facilities to carry out this work and the permission to publish. AKM is grateful to the Council of Scientific & Industrial Research (CSIR) and University Grants Commission (UGC), New Delhi, for the award of CSIR-UGC NET Fellowship (Grant No. 19/06/2016(i) EU-V-205247). RBM thanks the Department of Science & Technology (DST), New Delhi for sponsoring a project under the Women Scientist Scheme (SR/WOS-A/EA-15/2019). RK is grateful to the DST, for sponsoring a project under the Climate Change Programme (DST/CCP/PR/07/2011/G), under which field work and sampling were done.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship and/or publication of this article: The Birbal Sahni Institute of Palaeosciences (BSIP), Lucknow, India – an autonomous Institute under the Department of Science and Technology (DST), Government of India, New Delhi, has provided the financial assistance to conduct the study. The present research is an outcome of the Institute Project (Project Component No. 5.1/6).

ORCID iD

Ratan Kar

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