Characteristics of modern biotic data and their relationship to vegetation of the Alpine zone of Chopta valley,North Sikkim,India: Implications for palaeovegetation reconstruction

Abstract

We examined the modern pollen palynomorphs (PP) distribution complemented with non-pollen palynomorphs (NPP) and stable carbon isotopic data of soil organic matter (SOM) to explore relationships of these proxies to vegetation communities in the Chopta valley, a closed valley in alpine zone of the North Sikkim, India, in an attempt to check the efficiency for reconstructing past vegetation and climate. A total of 24 surface soil samples were collected from both the windward and leeward sides of the valley and they did not show any significant difference in the palynoassemblages. The average value of δ¹³C is −26.6%, which clearly indicates a C₃-dominated vegetation in this valley which is also corroborated by the palynological data. However, signature of upthermic wind transport was evident by the significant presence of extra-local and regional forest elements in the palynoassemblages. NPP data indicated grazing activity in the valley and is in conformity with the present-day scenario. Furthermore, cluster analysis (CA) and principal component analysis (PCA) done on the PP and NPP data broadly grouped the samples according to the location of collection to some extent and reflected the relationships among the taxa with the extant vegetation. This study provides a basis for future palaeovegetation and palaeoclimate reconstruction from the region.

Keywords

Himalaya North Sikkim NPP palaeovegetation reconstruction pollen stable carbon isotope

Introduction

As climate exerts dominant control on spatial distribution of vegetation, characterization of past pollen distribution in relation to the vegetation features has been recognized as an essential step for studies related to past climate history (Birks and Birks, 1980; Gaillard et al., 1992; Gosling et al., 2005; Jackson and Williams, 2004). However, relationship between modern pollen rain and vegetation is not always straightforward. In most of the cases, a non-linear relationship exists between pollen production, dispersal and preservation in the sediments (Birks and Gordon, 1985). Owing to this complexity, some taxa are under-represented, over-represented or even not represented at all in the fossil palynoassemblages (Jackson and Lyford, 1999; Prentice, 1985; Prentice et al., 1987; Sugita, 2007; Tauber, 1965). For example, the anemophilous species producing high quantities of pollen grains are generally over-represented, whereas species with entomophilous mode of pollination produce lower number of pollen grains and are under-represented in pollen assemblages (Faegri and Iversen, 1964). Although the pollen–vegetation relationship requires a detailed study and is very complex, the palaeoenvironmental/palaeoclimatic information is often extracted from pollen records using the modern analogue technique (Flenley, 1973; Miehe, 1996; Overpeck et al., 1985; Räsänen, 2001; Wright, 1967). To minimize the bias and for more precise palaeoclimate reconstruction, a sound knowledge of the modern pollen–vegetation relationship of the area under investigation is an essential prerequisite that helps in the interpretation of the fossil palynoassemblages more accurately (Barboni and Bonnefille, 2001; Barboni et al., 2003; Basumatary and Bera, 2007; Broström et al., 1998; Caseldine and Pardoe, 1994; Gosling et al., 2005; Jackson and Williams, 2004; Janssen, 1970; Quamar and Bera, 2014; Seppä and Hicks, 2006).

Non-pollen palynomorphs (NPPs), the microfossils other than pollen and spores that are frequently encountered in palynological slides, may also provide useful information on local ecological characteristics of a site. These NPPs have definite ecological preferences and are often linked with vegetation dynamics, land-use and hydrological changes (Barthelmes et al., 2012; Cugny et al., 2010; Dietre et al., 2012; Feeser and O’Connell, 2010; Ghosh et al., 2017; Wünnemann et al., 2010). When combined with pollen data during palaeoenvironmental reconstructions, NPPs may provide insights into long-term changes in vegetation, land-use and soil erosion properties and so on (Feeser and O’Connell, 2009). For more precise palaeoecological reconstructions, modern analogue studies of NPPs have been proved very useful, and were attempted from many parts of the globe but still wanting from the Sikkim Himalaya (see Ghosh et al. (2017) and references therein).

In reconstruction of the past ecologic and climate changes, stable carbon isotopic signatures of organic matter associated with soil (SOM) is commonly used (Meyers, 1994). To understand terrestrial ecosystem, stable carbon isotopes have been proved as reliable tool, as it focuses on the C₃ versus C₄ plant dynamics because of substantial difference in ¹³C discrimination during the photosynthesis. The carbon isotopic fractionation in both C₃ and C₄ plants can be affected by different environmental factors during the photosynthetic processes, in which the amount of rainfall and temperature are the most significant climatic factors controlling the δ¹³C values of these plants. C₃ plants are characterized by large range of δ¹³C value (−20‰ to −34‰, VPDB), where the less negative δ¹³C values reflect a physiological response to aridity and more negative δ¹³C values normally occurred under relatively humid condition (Rao et al. (2017) and reference therein). On the other hand, C₄ plants adapt to the environmental factors like high temperature, aridity and low atmospheric CO₂ concentration. The δ¹³C values of modern C₄ plants range from −9‰ to −19‰, with an average value of −13‰ (Agrawal et al., 2012; Ehleringer et al., 2015; Deines, 1980; Farquhar et al., 1989; O’Leary, 1988; O’Leary et al., 1981; Sage et al., 1999). A minor change in humidity–temperature gradient can result in a significant change in δ¹³C values of C₃ and C₄ plants which can be reflected by δ¹³C value of SOM (Cerling et al., 1989). Therefore, δ¹³C value of SOM is widely used to reconstruct palaeovegetation history as well as palaeoclimate. When combined with the other biotic proxies, it not only strengthens the past environmental reconstructions but also helps to explore the most influential climatic factors responsible for the change. However, for strengthening palaeoclimatic reconstructions, it is important to characterize the δ¹³C values of surface soils which may serve as analogues while interpreting past climate changes. Despite this important fact, the δ¹³C values of the modern surface soil samples are also lacking from the Indian Himalaya.

As far as the Indian Himalayan region is concerned, there is a paucity of both instrumental/historical as well as proxy climatic data. Although there are a few metrological stations installed in the Himalayan states, the locations are restricted to the lower altitudes only (Bhutiyani et al., 2010; Dimri and Dash, 2012; Fujita et al., 2001a, 2001b; Gusain et al., 2014; Immerzeel, 2008; Shrestha et al., 1999). Therefore, proxy data are the only means for climate reconstructions in high altitude sites, yet this seems to have been largely overlooked so far. Similarly, the palaeovegetation and palaeoclimatic reconstructions from the entire Indian Himalayan region are very sparse and are mostly limited to lower elevations (Agrawal et al., 2015; Bali et al., 2017; Bera and Gupta, 1989; Bera et al., 2011; Bhattacharyya, 1989a, 1989b; Chauhan and Sharma, 1993, 1996; Chauhan et al., 2000; Ghosh et al., 2014, 2015; Gupta and Yadav, 1992; Ranhotra and Bhattacharyya, 2013; Rawat et al., 2012, 2015a, 2015b; Sharma, 1973, 1985). As far as the Sikkim Himalaya is concerned, only study related to the late-Holocene palaeoclimate reconstruction supplemented with modern pollen data is from the eastern part of Sikkim (Sharma and Chauhan, 2001); however, the sampling resolution is not sufficient for characterizing modern pollen–vegetation relationship precisely. The importance of the present study lies in the fact that (1) the pollen–vegetation relationship in eastern Himalayas, considered to be the hotspot of biodiversity, is almost lacking or poorly studied; (2) this is a pioneering attempt to understand the pollen deposition pattern in the transitional zone (just above the tree line) between fairly vegetated low altitudinal zone and the high altitude arid zone of the Thangu valley; (3) the study attempts to reconstruct isotopic analogue of the modern surface samples for the first time from the Himalaya that will provide a baseline data for palaeoclimatic reconstructions.

Study area

The state of Sikkim lying towards the Northeast of India was ruled by monarchy prior to its merger with India in 1975. This small state with an area of approximately 7299 km² is one of the places in the eastern Himalayas that have been considered as ‘biodiversity hotspots’ (Brooks et al., 2006). The Sikkim Himalaya, that extends between 27°03′41″ to 28°7′34″ North and 88°3′40″ to 88°57′19″ East, is drained by the Tista river. Moreover, the state is strategically very important as it shares the international borders with the neighbouring countries like Bhutan, China and Nepal, and in the south, it is delimited by West Darjeeling Himalaya (Sikkim SAPCC, 2011). Geologically, the state of Sikkim comprises the rocks of Lesser, Central and the Tethys Himalaya (Gansser, 1964). The altitudinal gradient of the state is the steepest (average steepness of about 45°; as low as 250 m and as high as 8500 m a.s.l.) in the country as the N-S width of the Himalaya (from West Bengal to the Tibet) in this region is narrowest (Schaller, 1977). This geographic complexity of steep altitudinal gradient exerts a significant influence on the local weather patterns of the state from south to north and forms very different microclimatic conditions that have resulted into the existence of some exceptional assemblages of vegetation and wildlife (Chettri et al., 2001). Because of the wide range of topography, diverse climatic conditions and wide range in the annual precipitation, the state shelters one of the richest phyto-geographic regions of the Himalaya and is considered as the treasure houses of plant diversity in our country (Hajra et al., 1996; Rao, 1974; Singh and Chauhan, 1997). The vegetation complex of the state is represented by the sal (Shorea robusta) forest (300−900 m a.s.l.), chir pine (Pinus roxburghii) forest (500−900 m a.s.l.), subtropical forest (300−900 m a.s.l.), warm broad-leaved forest (900−1700 m a.s.l.), alder forest (1500−2000 m a.s.l.), evergreen oak forest (1700−2800 m a.s.l.), dwarf bamboo thicket (2600−3100 m a.s.l.), mixed conifer forest (2700−3100 m a.s.l.), conifer forest (2800−3700 m a.s.l.), alpine thicket (3500− 4500 m a.s.l.), alpine scrub (4000−4500 m a.s.l.) and alpine meadow (4500−5500 m a.s.l.) (Champion and Seth, 1968; Grierson and Long, 1991 [1983]; Figure 1).

Figure 1.

Land-use land cover (LULC) map of Sikkim, derived by supervised classification of Landsat 8 imagery of November 2014. The LULC map has been derived from the satellite data with minimum snow cover and minimum cloud cover.

Geomorphological setup of the study site

The present study has been carried out in the alpine zone of Chopta valley located in North Sikkim. The valley, lying just above the tree line, is a broad pro-glacial, U-shaped valley in the north Sikkim and is being used as a pasture land for grazing animals during the summers. Geomorphogically, the valley is bound by the late Quaternary recessional moraines on the downstream side that must have blocked the river flow in the past giving rise to this flat outwash plain that is filled with finer sediments. The sediment composition is mostly sandy and silty; however, it is mixed with a lot of organic matter derived from the grasses growing in the area. Other than this recessional moraine, a well-preserved lateral moraine is present on the left flank of the valley that emanates from the upstream valley and terminates at the Tista river (Figure 2a and b). The Chopta valley shelters earth Hummocks which are one of the most prominent features present in the study area (Figure 3a–c). These are miniature cryogenic mounds that are formed in the seasonally frozen ground in periglacial environments. These mounds generally ranging from few centimetres to around a metre in height are dome shaped, circular or of oval shape (Schunke, 1977; Schunke and Zoltai, 1988).

Figure 2.

(a) Detailed geomorphological map of the Chopta valley showing the distribution of glacial and paraglacial landforms. (b) Google earth Image showing the major drainages and moraines with sample locations.

Figure 3.

(a) Field photograph showing the synoptic view of the Chopta valley. (b) The most prominent earth hummocks present in the study area. (c) Close-up of the earth hummocks.

Climate

The complex topography and steep altitudinal gradient of Sikkim has resulted in wide climatic contrasts within short distances that range from subtropical in the south to tundra in the north. The low altitudinal area of the state experiences a humid climate with plenty of summer precipitation brought by the Bay of Bengal branch of the Indian Summer Monsoon (ISM), whereas the amount of precipitation keeps on decreasing towards the high altitudinal northern region which experiences low to very low precipitation. The area under investigation falls in the alpine zone and receives less than 800 mm precipitation (ENVIS, 2016) during the monsoonal months, while in the winter season, the precipitation occurs in the form of snowfall. Rainfall data from 18 stations in Sikkim show that the mean annual rainfall is minimum at Thangu (821 mm) and maximum at Gangtok (3493 mm) (ENVIS, 2016). Most of the inhabited regions of Sikkim experience a temperate climate, with temperatures seldom exceeding 28°C in summer. The average annual temperature for most of Sikkim is around 18°C. The average temperature in the Chopta valley is below 10°C throughout the year and below freezing point in winters.

Vegetation

The study area lying just above the tree line in the north Sikkim shelters the alpine vegetation. Previous studies on the alpine vegetation of the Sikkim Himalaya have demonstrated that the region shows a great variety of plant diversity and represents nearly 30% of the total flora of Sikkim. In total, alpine flora belonged to 60 families and 297 genera which contribute 60% of the total alpine plant families and 10% of all the alpine genera known worldwide (Körner, 1999). The vegetation complex of the alpine zone of the Sikkim Himalaya can be broadly classified into three categories: (1) the low altitudinal alpine zone (Shrubland) dominated by phanerophytes and chaemophytes; (2) the intermediate altitudinal alpine zone represented by the alpine meadows, dominated by geophytes, hemicryptophytes, and cryptophytes; and (3) the high altitudinal alpine zone (trans Himalayan alpine steppe) dominated by hemicryptophytes (Telwala, 2012). The documented plant life forms in the region include cushion forming communities such as Arenaria polytrichoides, Anaphalis cavei, Leontopodium monocephalum, Leontopodium brachyactis and Arenaria bryophylla; Poaceae such as Agrostis sp., Stipa purpurea and Calamagrostis sp.; sedges like Kobresia royleana, Kobresia nepalensis, Kobresia cappilifolia, Kobresia schoenoidesa and Carex parva (Miehe, 1996) adapted to unstable scree with long roots and stems trailing along the snow and debris (e.g. Gentiana urnula, Eriophytum wallichii and Veronica lanuginosa); herbaceous perennials or geophytes and therophytes (e.g. Aconitum heterophyllum, Aletris pauciflora, Bistorta macrophylla, Cortia depressa and Cyananthus incanus); low-growing creeping prostrate woody shrubs or dwarf-shrubs or chamaephytes (e.g. Cotoneaster sp., Lonicera spp., Spiraea arcuata, Hippophae tibetana and Potentilla fruticosa); and dense wooly forms (e.g. Saussurea graminifolia, Saussurea sericea, Scabiosa graminifolia, Onosma hookeri and Glechoma nivalis).

Materials and methods

Samples: Collection and extraction of pollen and NPPs

A total of 24 surface samples were collected in a pre-decided transect from the Chopta valley by hand-pick method using sterilized spatula/knife and zip polythene pouches to carry out the pollen–vegetation relationship (Figure 2a and b). Samples CH-1 to CH-8 are lying close to hill slope (windward side) of the Chopta valley, whereas samples CH-10 to CH-20 are located in an area close to river and CH-21 to Ch-24 are from the central region of the valley (Table 1).

Table 1.

Details of latitude, longitude and elevation of the samples collected from the alpine zone of Chopta valley, north Sikkim.

S. No.	Sample No.	Latitude (N)	Longitude (E)	Elevation (~m a.s.l.)
1	CH-1	27°54′07.89″	88°31′40.53″	3977
2	CH-2	27°54′11.50″	88°31′38.20″	3974
3	CH-3	27°54′14.97″	88°31′34.92″	3999
4	CH-4	27°54′17.49″	88°31′29.51″	4007
5	CH-5	27°54′15.51″	88°31′22.74″	4008
6	CH-6	27°54′12.50″	88°31′12.13″	4007
7	CH-7	27°54′11.11″	88°31′00.40″	4023
8	CH-8	27°54′11.86″	88°30′47.64″	4070
9	CH-9	27°54′12.19″	88°30′35.51″	4092
10	CH-10	27°54′15.08″	88°30′20.92″	4093
11	CH-11	27°54′10.11″	88°30′27.37″	4081
12	CH-12	27°54′06.43″	88°30′43.34″	4036
13	CH-13	27°54′04.92″	88°30′51.03″	4028
14	CH-14	27°54′08.40″	88°30′59.30″	4006
15	CH-15	27°54′08.37″	88°31′08.83″	3999
16	CH-16	27°54′09.27″	88°31′18.36″	3990
17	CH-17	27°54′08.83″	88°31′23.69″	3986
18	CH-18	27°54′07.70″	88°31′31.19″	3990
19	CH-19	27°54′06.67″	88°31′35.62″	3993
20	CH-20	27°54′05.30″	88°31′40.30″	3995
21	CH-21	27°54′13.12″	88°31′34.57″	3988
22	CH-22	27°54′12.71″	88°31′22.88″	3995
23	CH-23	27°54′11.38″	88°31′15.05″	3997
24	CH-24	27°54′09.86″	88°31′03.47″	4008

In order to extract the pollen, spores and NPPs from the sediment sample, maceration technique including acetolysis was followed (Erdtman, 1943). Ten grams of the sample was boiled with 10% aqueous solution of potassium hydroxide (KOH) to deflocculate pollen and spores from the sediments and to dissolve the humus. Furthermore, the samples were treated with 40% hydrofluoric acid (HF) to remove the silica. This chemical treatment was followed by the process of acetolysis (Erdtman, 1943) using a mixture of acetic anhydride and concentrated sulphuric acid in the ratio of 9:1. The extracts were finally kept in 50% glycerine solution for microscopic study and few drops of phenol were also added to make the mixture homogeneous and also to avoid any microbial/fungal growth.

The extracted pollen, spores and NPPs were studied under the Olympus microscope. Conventionally, about 250–350 pollens/spores per sample were counted that are considered as total palynomorph count (TPC). Identification of the palynomorphs was achieved by comparison with reference slides available from the herbarium of Birbal Sahni Institute of Palaeosciences as well as the pollen photographs from various published literature (Moore and Webb, 1978). TPC includes the representation of the ground vegetation growing in the study area and a considerable amount of pollen grains of the extra-local plants which presently do not grow around the sampling sites. However, total pollen sum was also calculated for every sample excluding the spores and the marshy and aquatic taxa from the TPC. NPPs were counted (excluding pollen grains but including pteridophytic spores as fern allies) and their values were expressed as percentages of the total sum of the NPPs. The pollen and NPP spectra were constructed using the TILIA and TILIA graph software (Grimm, 1990). The taxa were grouped in the pollen spectra as arboreal and non-arboreals, whereas aquatic and marshy were grouped together and are represented in a separate diagram. Similarly, NPPs and fern allies are represented separately (Figures 4 –6).

Figure 4.

(a) Frequency distribution of the terrestrial pollen taxa in the surface samples from the Chopta valley (pollen sum is also represented in the right) and (b) results of cluster analysis on the pollen data based on squared Euclidean distance and minimum value.

Figure 5.

(a) Frequency distribution of the marshy and aquatic taxa and (b) results of cluster analysis on the pollen data based on squared Euclidean distance and minimum value.

Figure 6.

(a) Frequency distribution of the Fern allies, Algae, Brhophytic spores as well as Fungal spores; and (b) results of cluster analysis based on squared Euclidean distance and minimum value.

Isotopic sample preparation

The samples that were collected for the pollen analysis were used for the isotopic analysis as well. Around 1 gm of the sediment sample was taken after coning and quartering and was finely powdered to clay size particles and poured into 50 mL centrifuge tubes. The samples were treated with 5% HCl solution (three times) for the removal of carbonates and were washed with milli-Q water using a centrifuge machine (~3000 r/min) to remove acid and soluble salts. The de-carbonated samples were then dried in a hot-air oven with temperature fixed at 45°C. The oven-dried samples were again powdered with an agate mortar to loose clumps that might have formed during drying. All the acid-treated powdered samples were individually packed into tin capsules and introduced into the pre-filled and conditioned reactor of Elemental Analyser (Flash EA 2000 HT) through an auto sampler. The CO₂ gas produced through the combustion was introduced into the Continuous Flow Isotope Ratio Mass Spectrometer (CFIRMS, MAT 253) coupled with Con-Flow IV interface for isotopic analysis. The reproducibility of samples was checked by repeat measurements. References gas was calibrated using IAEA CH-3 and carbon isotopic data is reported against VPDB. International standards (CH-3 and CH-6) as well as internal standards (sulphanilamide) were run to check the accuracy for the CO₂ measurements with an external precision of ±0.1‰ (1σ). All samples were analysed in the Stable Isotope Laboratory, Birbal Sahni Institute of Palaeosciences (BSIP), Lucknow.

Sample preparation for loss on ignition

The weight percent of the organic matter and the carbonate content of the sediments were determined by the measurement of loss on ignition (LOI) by the sequential heating of the samples in a muffle furnace (Bengtsson and Enell, 1986; Dean, 1974; Heiri et al., 2001). The same sediment samples were dried in a hot-air oven with temperature fixed at 45°C for 10 days. The quartering and coning methods were used to homogenize these samples that were crushed in a disc mill grinder to a fine powder. Five grams of this homogenized sample was taken in a quartz crucible that was oven-dried at a temperature of 110°C for 12 hours. Thereafter, the samples were weighed to estimate the percentage of moisture that has been lost from the samples at 110°C temperature. Organic matter was combusted in next step to ash and carbon dioxide at a temperature of 550°C and weighed further. During the last step, carbon dioxide was evolved from carbonate at 950°C followed by weighing.

Multivariate analyses

To test the classification potential of the palynomorphs and NPPs, cluster analysis (CA) was performed on the pollen (for azonal taxa and terrestrial pollen taxa separately) and NPP data set. On the basis of the selected characteristics, CA identifies groups of individual (here samples) that are similar to each other but different from individuals in other groups. Here, we used Ward’s method and the squared Euclidean distance with the variables rescaled to 0–1.

Ordination analysis was performed to understand the variation in the pollen and NPP data separately and to figure out how many possible explanatory variables could account for the observed variance in pollen palynomorphs (PP) and NPP. Environmental gradient lengths using both the pollen taxa and NPP were calculated from the detrended correspondence analysis (DCA) and found that the DCA axis 1 scores are 1.34 SD (standard deviation scale) and 2.65 SD for PP and NPP, respectively. This indicate that environmental gradient is small (less than 3 SD) and suggests to employ linear model of ordination analysis. Principal component analysis (PCA), an unconstrained ordination analysis was used to see the independent explanatory components to account for variabilities observed in the biotic data set (both PP and NPP). All the taxa were used in the analyses with Hellinger transformation which reduced the impact of the taxa with 0 values (Legendre and Gallagher, 2001; Poos and Jackson, 2012). The bi-plots (site scores and species scores) can be shown with Hill’s scaling (scaling = −3) so that both the sites (samples) and species can be better distinguished among themselves. All the analyses were done in R platform (R Core Team, 2014) using vegan package from CRAN project (Oksanen et al., 2015).

Results

Palynoassemblages

The palynological analysis of 24 surface sediment samples (CH-1 to CH-24) from Chopta valley, north Sikkim, reveals relatively high frequencies of arboreals (trees and shrubs) over the non-arboreals (herbaceous taxa) (Figure 4a; Supplementary Figure S3, available online). The arboreal taxa include conifers and broad-leaved taxa which show an average pollen frequency of 12.3% and 33.6%, respectively. Among the conifers, Pinus sp. represents the highest pollen frequency and the value ranges from 0.7% to 13.5%, Tsuga sp. (1–6.8%), Abies (0.7–4.4%), Juniperus (0.3–2.2%), Picea (0.3–1%) and Podocarpus (0.3–1.1%). Among the broad-leaved taxa, Alnus sp. and Betula sp. represent comparatively higher values ranging between 5.6–13.2% and 2.5–12.8%, respectively. Rhododendron (1.8–18.4%) is also well represented in good amounts. However, other broad-leaved taxa, that is, Quercus sp. (0.8–10.2%), Ulmus sp. (0.3–2.8%), Salix (0.3–1.4%), Carpinus sp. (0.4–6.%), Aesculus sp. (0.6–2.3%), Corylus sp. (0.3–2.6%), Tiliaceae (0.3–3.3%), Elaeocarpus sp. (0.3–1.5%), Juglans sp. (0.3–1.2%), Fraxinus sp. (0.2–3.2%), Triumfetta sp. (0.3–0.8%), Ehretia sp. (0.3–0.4%), Ilex sp. (0.7%) and Fagaceae (0.3–0.4%) have comparatively less values and are sporadically recorded. Among the non-arboreal taxa, Poaceae is highly represented in the pollen rain (3.5–21.6%) followed by Polygonum sp. (0.4–15.3%), Caryophyllaceae (0.3–12.4%) and Tubuliflorae (0.3–15.1%), whereas pollen percentages in Dodonea (0.7–3.8%), Brassicaceae (0.4–5%), Spiraea sp. (1.1–3.8%), Ranunculaceae (0.5–6%), Artemisia (0.2–5.3%), Apiaceae (0.4–2.5%), Skimmia (0.3–2.7%), Myricaria sp. (0.3–0.7%), Oleaceae (0.3–3.5%), Amaranthaceae (0.3–3.5%), Liguliflorae (1.2–3.4%), Malvaceae (0.4–4%), Liliaceae (0.4–1.6%), Anemone (0.3–2.1%), Clematis (0.3–1.8%), Aconitum (0.3–1.1%), Ranunculus (0.5–1.2%), Oldenlandia (2.3–1.3%), Saxifraga (0.3–0.7%), Chrysosplenium (0.3–1.1%), Dioscorea (0.2–1.1%), Aceraceae (0.3–4.1%), Crotalaria albida (0.3–0.4%), Fabaceae (0.3–3.8%), Arenaria sp.(0.3–0.8%), Desmodium (0.3–1.5%), Prunus sp. (1.3%), Euphorbiaceae (1%), Caricaceae (0.3%), Indigofera (0.2%), Trichodesma sp. (0.4%) and Jussieua sp. (0.6%) show variable pollen percentages during the analysis of the samples (Figure 4a).

The CA done on the pollen data has broadly defined two main groups within the samples (Figure 4b). Samples of group 1 (no. CH-3, 4, 6, 12 and 13) show dominance of Pinus, Alnus, Betula, Quercus and so on. However, group 2 can be further divided into two sub-groups, that is, group 2A, consisting of samples (no. CH-1, 7, 23 and 24) collected from the windward side of the slope exhibited Pinus, Abies, Picea, Podocarpus, Juniperus, Alnus, Betula, Ulmus, Carpinus, Quercus and Tsuga, all in moderate frequencies. Among the non-arboreals, Tubuliflorae and Poaceae are also co-dominantly recovered in these samples. Samples of group 2B (rest of the samples collected mostly from the leeward side of the slope) show co-dominance of Alnus, Betula, Tsuga and Poaceae followed by Amaranthaceae, Artemisia, Caryophyllaceae and Tubuliflorae (Figure 4b). Among the marshy elements, Cyperaceae shows consistent representation in the samples with high pollen frequency (0.9–24%), while Lemna (0.3–10.2%), Utricularia (0.3–0.7%) and Potamogeton of 0.3% are recorded meagrely (Figure 5a). To assess whether the aquatics and marshy taxa – the azonal elements that are influenced more by the edaphic factors than by the climate – could discriminate the samples with the changes in the microenvironment, CA was done. The results show two distinct groups. Samples of group 1 (Figure 5b), despite being rich in organic carbon content and with high soil moisture, show low to moderate percentages of Cyperaceae. However, samples of group 2 (Figure 5b) with comparatively low organic carbon and low soil moisture show higher frequencies of Cyperaceae.

NPP

Among the NPPs, fern allies are recovered from all the samples but with varying frequencies. Of the algal morphs, considerably high values of Botryococcus (0.1–41%) are noticed, while Spirogyra sp. has been recovered in negligible frequencies. The coprophilous fungal spores are represented by Podospora, Sordaria and Delitschia sp. Among these, Podospora is found to dominate the assemblages followed by Sordaria and Delitschia sp. NPP assemblages also include two thecamoebian taxa, that is, Assulina sp. and Centropyxis sp. (Figure 6a). CA done on the NPP data reveals two broad groups (Figure 6b). Group 1 consisting of two samples (i.e. CH-3 and CH-4) shows high percentages of Botryococcus. While among the samples in group 2, CH-1 shows high amount of Glomus, and rest of the samples show co-dominance of Podospora, Sordaria, Assulina and Centropyxis (Figure 6b; Supplementary Figure 1, available online).

LOI and δ¹³C

In the present study, LOI is the sum of moisture content, organic carbon and carbonate content of the sample. It is clearly visible from the graph (Figure 7) that the moisture content and organic carbon in the samples are showing more or less a similar trend. Moisture percentage of samples CH-1 to CH-13 broadly ranges from 4.5% to 7.2%, whereas sample CH-14 shows the lowest value of 0.89%. The average minimum and maximum value for all the 24 samples is 0.9% and 7.3%, respectively. However, the organic carbon value of sample CH-14 shows the least value among the other samples with a value of 5.8, while the average minimum values of all the samples are 5.73 and maximum average values of 44.8%. From the graph of the CO₃%, it is clear that samples 5 and 6 show maximum values of 21% and 25.3%, respectively, followed by sample number 12 showing a value of 16.9%. Thus, the average minimum and maximum values of the carbonate content in the samples are 0.7–25.3%. The graph clearly depicts that the trend of carbonate content is showing a considerable variation with values of organic carbon and moisture content among all the samples. The δ¹³C values of organic matter associated with the surface soil are ranging from −25.8 and −27.7‰ with average value of −26.6‰. In contrast to LOI, the δ¹³C values do not show any specific spatial variation within the Chopta valley.

Figure 7.

Loss on ignition (LOI) and δ¹³C values of the samples.

Scree plot (eigenvalues vs PCA components) could not ambiguously suggest the number of components which can account for most of the variation in PP (Figure S1). PCA shows that first three components could only account for 40.2% (17.8%, 12.3% and 10.1% for first three axes, respectively) of total variations in the species data as suggested by the scree plot. Hellinger transformed data (to be compared with the species data) of δ¹³C (δ¹³C_i − δ¹³C_min) and organic content (OC) were fit onto the ordination plot (PCA plot). Using the permutation test (999 times), neither δ¹³C (p-value = .43) nor OC was found to be significant (Figure 8a).

Figure 8.

PCA using (a) pollen taxa, PP, and (b) non-pollen taxa, NPP as response variable and organic content, OC (%) and δ¹³C as explanatory variables. Numerics are the sample number (CH-n, where n vary from 1 to 24) and capital texts (first three letters of the taxa) are the first three letter code of the (a) pollen and (b) non-pollen taxa. Taxa used in (a) PP: PIN – Pinus; ABI – Abies; PIC – Picea; POD – Podocarpus; JUN – Juniperus; ALN – Alnus; BET – Betula; ULM – Ulmus; CAR – Carpinus; COR – Corylus; QUR – Quercus; TSU – Tsuga; SAL – Salix; JUG – Juglans; AES – Aesculus; ILE – Ilex; PRU – Prunus; EHR – Ehretia; ELE – Elaeocarpus; TRI – Triumfetta sp.; TIL – Tiliaceae; FRA – Fraxinus; CAR – Caricaceae; FAG – Fagaceae; EPH – Ephedra spp.; RHO – Rhododendron; DOD – Dodonea; UNI – Unidentified; API – Apiaceae; SKI – Skimmia; MYR – Myricaria sp.; IND – Indigofera; OLE – Oleaceae; POA – Poaceae; AMA – Amaranthaceae; CAR – Caryophyllaceae; BRA – Brassicaceae; ART – Artemisia; TUB – Tubuliflorae; LIG – Liguliflorae; MAL – Malvaceae; LIL – Liliaceae; RAN – Ranunculaceae; ANE – Anemone; CLE – Clematis; ACO – Aconitum; RAN.1 – Ranunculus spp.; EUP – Euphorbiaceae; OLD – Oldenlandia; SAX – Saxifraga; CHR – Chrysosplenium spp.; DIO – Dioscorea; ACE – Aceraceae; CRO – Crotalaria albida; FAB – Fabaceae; POL – Polygonum spp.; POL.1 – Polygonum recumbens; ARE – Arenaria; SPI – Spiraea; TRI – Trichodesma sp.; DES – Desmodium; JUS – Jussieua; CYP – Cyperaceae; UTR – Utricularia; LEM – Lemna; POT – Potamogeton; and in (b) NPP: FA – Fern allies; SPI – Spirogyra; BOT – Botryococcus; GLO – Glomus; CUR – Curvularia; DIP – Diploidea; NIG – Nigrospora; POD – Podospora; ALT – Alternaria; DEL – Delitchia spp.; SOR – Sordaria; END – Endofragmiella; UNI – Unidentified; ASS – Assulina; CEN – Centropyxis; CYP – Cyperaceae; UTR – Utricularia; LEM – Lemna.

The scree plot, using NPP, suggests three significant components can account for most of the variability in the data set (Figure S2). PCA shows that first three components could account for 66.8% (43.2%, 13.0% and 10.7% for first three axes, respectively). Using the permutation test, δ¹³C (0.15) was found to be slightly significant than OC (p-value = .26), and this is shown in Figure 8b.

Discussion

Pollen rain–vegetation relationship

In general, it is conventional in palynology that the surface sediments and moss polsters yield the pollen assemblages that have been deposited there in the past decades and are dominated by the pollen grains with the most decay-resistant pollen walls (Wilmshurst and McGlone, 2005; Xu et al., 2009). It has been recognized that the zoophilous taxa show meagre representation in the pollen assemblages as compared with the anemophilous taxa. The reason behind the difference in representation is attributed to the lower pollen production of the zoophilous taxa (Faegri and Iversen, 1964). Moreover, because of the differences in pollen production, dispersal and preservation between different taxa, pollen percentages do not always reflect the vegetation scenario around the sampling site (Prentice, 1985; Prentice et al., 1987). Hence, establishing the modern pollen–vegetation relationship from the surface samples/moss polsters is inevitable and prerequisite in order to better understand and develop a quality reconstruction and interpretation of past vegetation, landscape and climate as well (Bradshaw and Webb, 1985; Calcote, 1998; Court-Picon et al., 2006; Fall, 1992; Webb et al., 1981).

Despite the fact that the valley under consideration is an open meadow, the pollen assemblages have demonstrated the dominance of the arboreals over non-arboreals. Hence, this study portrays the distribution pattern of pollen taxa deposited over the elevation gradient of the Sikkim Himalaya in relation to vegetation. Although the samples have been collected from an open area above the tree line, presence of significantly higher amount of anemophilous pollen grains suggests their active transport towards higher elevations through the upthermic winds blowing through the valleys. As per the categorization of Janssen (1966), pollen taxa that do not reflect the local vegetation in and around the sampling sites may be grouped under extra-local, regional or extra-regional categories. The extra-local palynotaxa coming within a few hundred metres from the sampling sites are represented in comparatively higher frequencies in palynoassemblages than those coming from regional sources. Regional palynoassemblages may reflect the vegetation beyond a few hundred metres of specific pollen sources. On the other hand, the extra-regional pollen deposition includes the pollen grains those are capturing the signal beyond the area of the vegetation formation where the samples have been collected. In this study, Pinus cf. wallichiana, Abies, Picea, Juniperus, Betula, Quercus and Salix representing the extra-local arboreal taxa might be coming from the nearby sub-alpine or dry temperate forests located within a few hundred metre distance from the valley. However, differences in their abundance in the pollen spectra may reflect their difference in pollen production, weight of the pollen grain and preservation potential. Such as, among the conifers, Pinus sp. is the major element of the pollen rain which could be attributed to its high pollen productivity as well as excellent dispersal efficiency and preservation (Andersen, 1970; Bera et al., 2011; Bhattacharyya, 1989a, 1989b, 1989c; Ertl et al., 2012; Kar et al., 2015, 2016; Pidek et al., 2010; Sharma et al., 2001; Vishnu-Mittre and Robert, 1971). Moreover, the Pinus pollen showing relatively higher percentages may be attributed to the highly resistant pollen exine (high in sporopollenin) towards oxidation and microbial attacks (Havinga, 1964, 1984). However, Abies sp., Tsuga sp., Picea sp., Podocarpus sp. and Juniperus sp. are other conifers that have been recorded in comparatively less values which may be because of their larger pollen size and low pollen productivity than that of Pinus (Vishnu-Mittre and Robert, 1971). Some other arboreal taxa retrieved in significant percentages, that is, Alnus, Ulmus, Juglans, Carpinus, Podocarpus and Prunus might be reflecting the regional vegetation of comparatively lower elevation temperate and subtropical zones (Hicks, 2001). CA shows that terrestrial palynoassemblages can differentiate the samples as per their sampling locations (i.e. some are collected from windward and some are from the leeward sides of the valley) to some extent only when the extreme windward or leeward locations are concerned. However, a considerable mixed signal has been observed for the samples collected from the central zone.

Among the non-arboreals, Poaceae shows the highest frequency in the pollen rain which could be because of its wind-pollinated character as well as its gregarious presence in the extant vegetation. However, some other anemophilous taxa such as Amaranthaceae which is suggested to be a low pollen producer typically in wind-pollinated groups show sparse representation in the modern pollen rain, which could be ascertained to its poor pollen dispersal and preservation (McMullen and Close, 1993). It has been well established that the rate of pollen production is not only phylogenetically controlled but also by the prevailing environmental settings of the habitat (Cariñanos et al., 2014). Decrease in the pollen production in the present study area may be because of the shortening of the flowering season which is attributed to the location of the study area that experiences a temperate climatic condition. Besides, earlier studies regarding the reduced pollen production have been attributed to the frost damage during budburst because of a sharp drop in temperatures (Cannel and Smith, 1984). Except the higher frequency of grasses, other herbaceous taxa such as Tubuliflorae (Asteraceae), Caryophyllaceae and Artemisia are also recorded in relatively good frequencies in the pollen rain. Presence of these taxa in the present study area points towards their local presence as well as an extensive grazing because of availability of open landscape (van Geel et al., 2003). The entomophilous families show relatively low pollen frequencies nevertheless; Brassicaceae, Ranunculaceae and Fabaceae are encountered in significant frequencies, which indicate towards their local presence. The low pollen production can be ascribed to the low temperatures in the glaciated regions which reduce activities of potential pollinators (Duan et al., 2009). Other herbaceous taxa, such as Malvaceae, Liguliflorae, Liliaceae, Skimmia, Oleaceae, Apiaceae, Anemone, Clematis, Aconitum, Ranunculus spp., Euphorbiaceae, Oldenlandia, Saxifraga, Chrysosplenium spp., Dioscorea, Aceraceae, C. albida, Arenaria sp., Trichodesma sp., Desmodium, Jussieua, Spiraea sp., Myricaria sp. and Indigofera are also encountered sporadically in the pollen rain. Despite presence in the local flora, their low presence in the pollen assemblages may be attributed to their low pollen production and entomophilous nature. Considerable presence of Polygonaceae pollen (cf. Polygonum recumbens and Polygonum spp.) is also suggestive of the anthropogenic activity in the valley, might be during pasturage (Yao et al., 2015).

Occurrence of Cyperaceae, Lemna, Utricularia and Potamogeton indicates marshy condition in general (Pišút et al., 2010). CA done on the aquatics and marshy data revealed an interesting phenomenon: samples with high organic carbon and high moisture content show low to moderate percentages of Cyperaceae in contrast to those with low organic carbon and low moisture contents. Cyperaceae or ‘sedges’ are a major component of most wetland vegetation with cosmopolitan distribution (Simpson and Inglis, 2001). Although most of the species of Cyperaceae are linked to wetland conditions, some are also adapted to comparatively dry land habitats (Goetghebeur, 1998). In an earlier study by Vellend et al. (2000), it was observed that even within a single genus Carex (which is also a significant member of the local vegetation), environmental heterogeneity because of differences in soil moisture regime and nutrient availability created interspecific microhabitat and proved to be important for the maintenance of local species diversity. Hence, differing behaviour of the sedges in the samples of this closed valley may be attributed to different microhabitats and the moisture preference of the taxa.

NPP and their ecological indicative values

The fern and fern allies that disperse via spores (Taylor et al., 2005) show a steady occurrence in all the samples, suggesting a moist and shady environment (Bera et al., 2011). Presence of the ferns in the study area is attributed to the water availability (Aldasoro et al., 2004; Kessler et al., 2011; Schuettpelz et al., 2007). It is suggested that dominance of the ferns reflects high water availability and a preference for mesic habitats (Kato, 1993). Although the present study area receives a moderate annual rainfall (~800 mm), significant presence of fern allies indicating high soil moisture might be because of low rate of evapo-transpiration or melt water availability or nearness to the river channel which is also evident in LOI results.

Botryococcus shows a considerable frequency in samples that have been collected towards the valley slope (CH-1 to CH-8); however, sample numbers CH-3 and CH-4 represent maximum frequency that can be attributed to its local abundance, good preservation or enhanced limnic condition. Delitschia spp., Podospora and Sordaria spp. are regarded as the coprophilous fungi and are represented well in the data set. In an earlier study by Ghosh et al. (2017) from the Darjeeling Himalaya, it has been noticed that the Podospora sp. and Sordaria spp. are the most reliable indicators of grazing activity. However, abundance of Delitschia sp. may also provide additional information on intensively grazed conditions when recovered with Podospora and Sordaria. Hence, these fungal NPPs may be used as intensive grazing indicators when recovered together. Other NPPs such as Glomus sp., Nigrospora sp. and Alternaria sp. indicate humid climate in the area of study. High percentage of Glomus in one sample (CH-1) might also indicate local soil erosion. Bryophyte spore is represented only in sample CH-1 which is indicative of moist and shady environment (Cook et al., 2011). CA done on the data categorized the samples into two groups. Samples of group 2 are rich in fungal spores, especially the coprophilous taxa and those of group 1 show abundances of Botryococcus, somewhat establishing a gradient of increasing limnic condition.

LOI and δ¹³C: Relationships to vegetation

Samples CH-1 to CH-8 that are lying close to hill slope (windward side) of the Chopta valley show highest OC, samples CH-10 to CH-20 are located in an area close to river, and CH-21 to Ch-24 are from the central region of the valley. The samples taken in close vicinity of the river depicts a high content in the organic carbon, while it decreases fairly in the samples that are from the central part of the valley. An exception is observed with sample CH-14 which though lies close to the river shows the lesser value of organic carbon and moisture content that can be attributed to local difference in the sediment texture. The trend of moisture content and organic carbon is similar among the samples which may be because of the reason that the area containing more organic matter would surely have high moisture-retaining capability.

δ¹³C in SOM provides useful information regarding the dominant photosynthetic pathway of the watershed vegetation. As the photosynthetic pathway of vegetation is largely dictated by environmental conditions like temperature, aridity and atmospheric CO₂ concentration (Boom et al., 2001; Ehleringer et al., 1997), the δ¹³C values can also provide useful information regarding environmental conditions. Modern pollen–vegetation relationship is non-linear and a complex process which is governed by a number of factors such as pollen production, dispersal, deposition and preservation and related biases. Unlike pollen, the SOM has a less complex origin that involves the decomposition of overlying plants because of the interaction of the physical, chemical and biological processes within soils; hence, SOM is assumed to preserve mean δ¹³C values of the contemporary vegetation with little or no fractionation (Cerling et al., 1997; Whitbread, 1995).

The Chopta valley is a close basin and it is above the tree line. Therefore, it gets sediments and organic matter from the surrounding hills which are mainly covered by the grass and mosses. The same grasses and mosses are also found in the Chopta valley. In the present study, the soil samples collected from the hill slope and the valley show very narrow range of δ¹³C values which vary between −25.8‰ and −27.7‰ with average value of −26.6‰. Considering the typical stable carbon isotope ratios (about −26‰ to −27‰) of C₃ plant organic matter, the δ¹³C values of SOM in the Chopta valley suggest C₃-dominated vegetation.

Modern isotopic analogues from the Indian subcontinent are lacking except for a few from the Gangetic Plain (Agrawal et al., 2012; Basu et al., 2015). However, there is no available information on the modern isotopic values from the entire India Himalayan region. Therefore, we have compared the average isotopic values of SOM from the Chopta valley to the available carbon isotopic records both with regional as well as global data. Rao et al. (2017) integrated δ¹³C values of modern plants and soil samples and they found most frequent δ¹³C values are around −28‰ to −26‰ for the modern plants and −27‰ to −25‰ for surface soils. These values are well correlated with the data set generated in the present study. In contrast, Kohn (2010) included the δ¹³C values of mid-latitude equatorial vegetation to the global δ¹³C data set which lower the end-member value of C₃ plants by 2‰ (−28.5‰). Such lowered δ¹³C values of modern C₃ plants (−29.5‰ ± 2.2‰) were also observed in the low-latitude area (south central Gangetic Plain, India; Agrawal et al., 2012; Basu et al., 2015). Our results contrast sharply with these available data set from the Gangetic Plain. Therefore, the present data highlight requirement of the modern analogues of δ¹³C values of modern plants and SOM from ecologically diverse regions of Indian subcontinent that encompass very humid regions, both hot and cold deserts, as well as mean elevations ranging from sea level to around 8500 m a.s.l. with a very sharp gradient in annual precipitation prior to the palaeovegetation/palaeoclimate reconstruction.

Conclusion

The pollen assemblages in the surface samples collected from the small glaciated Chopta valley, sharing its boundary with the tree line, fundamentally reflect the alpine vegetation patterns. This also helps in understanding the pollen transport, preservation and its relation to the extant vegetation. The results show the dominance of wind-pollinated arboreals in higher frequencies suggesting their upthermic transport from the lower altitudes. The higher frequency of non-arboreals such as grasses completely reflects the extant vegetation, and their significant presence in the samples points to an extensive grazing and anthropogenic activities. The record of anthropogenic activity in the region can also be inferred from the substantial presence of some anthropogenic marker pollen grains such as Polygonaceae pollen, as well as recovery of coprophilous fungal spores in significant frequencies. A typical value of −26.6‰ of δ¹³C indicates a dominant C₃ vegetation type, suggesting a high moisture availability (not the retention capacity, except CH-14) in the soil. Thus, the present study provides a basis for future palaeovegetation and palaeoclimate reconstruction from the region using pollen and stable isotope analogues.

Footnotes

Acknowledgements

The authors are thankful to the Director, Birbal Sahni Institute of Palaeosciences, Lucknow, India, for providing infrastructural facilities. Special thanks are addressed to Dr U. Lachungpa, Department of Forest, Government of Sikkim; Department of Home, Government of Sikkim; and the Indian Army for their help and support for providing the necessary permissions during the field work. Thanks are also due to the field staffs who have worked tirelessly in the harsh conditions during the field work. Thanks are due to the editor and the two anonymous reviewers for constructive suggestions.

Funding

This work was carried out under project no. SR/DGH-89/2014 with financial support from the Department of Science and Technology (DST), Government of India, India.

References

Agrawal

Sanyal

Sarkar

et al . (2012) Variability of Indian monsoonal rainfall over the past 100 ka and its implication for C₃–C₄ vegetational change. Quaternary Research 77: 159–170.

Agrawal

Srivastava

Sonam et al . (2015) Stable (δ¹³C and δ¹⁵N) isotopes and Magnetic Susceptibility record of late Holocene climate change from a lake profile of the northeast Himalaya. Journal of Geological Society of India 86: 696–705.

Aldasoro

Cabezas

Aedo

(2004) Diversity and distribution of ferns in sub-Saharan Africa, Madagascar and some islands of the South Atlantic. Journal of Biogeography 31: 1579–1604.

Andersen

STH

(1970) The relative pollen productivity and pollen representation of north European trees: and correction factors for tree pollen spectra. Determined by surface pollen analyses from forests. Danmarks geologiske Undersøgelse; Raekke 2, 96: 1–99.

Bali

Chauhan

Mishra

et al . (2017) Vegetation and climate change in the temperate-subalpine belt of Himachal Pradesh since 6300 cal. yrs. BP, inferred from pollen evidence of Triloknath palaeolake. Quaternary International 444: 11–23.

Barboni

Bonnefille

(2001) Precipitation signal in pollen rain from tropical forests, South India. Review of Palaeobotany and Palynology 114: 239–258.

Barboni

Bonnefille

Prasad

et al . (2003) Variation in modern pollen from tropical evergreen forests and the monsoon seasonality gradient in SW India. Journal of Vegetation Science 14: 551–562.

Barthelmes

de Klerk

Prager

et al . (2012) Expanding NPP analysis to eutrophic and forested sites: Significance of NPPs in a Holocene wood peat section (NE Germany). Review of Palaeobotany and Palynology 186: 22–37.

Basu

Agrawal

Sanyal

et al . (2015) Carbon isotopic ratios of modern C₃-C₄ plants from the Gangetic plain, India and its implications to paleovegetational reconstruction. Palaeogeography, Palaeoclimatology, Palaeoecology 440: 22–32.

10.

Basumatary

Bera

(2007) Modern pollen-spore assemblage from sediment of tropical moist deciduous forest, East Garo Hills, Meghalaya. Journal of Palynology 43: 111–118.

11.

Bengtsson

Enell

(1986) Chemical analysis. In: Berglund

(ed.) Handbook of Holocene Palaeoecology and Palaeohydrology. Chichester: John Wiley & Sons, pp. 423–451.

12.

Bera

Gupta

(1989) Correlation between pollen spectra and vegetation of Chota Shigri Glacier in Himachal Pradesh, India. Palaeobotanist 38: 404–410.

13.

Bera

Ali

Bali

et al . (2011) Impact of pollen rain from the vegetation of alpine-subalpine belt as a reliable measure for palaeoclimatic interpretation: a case study from Pindari Glacier, Kumaun Himalaya, India. International Journal of Earth Sciences Engineering 4: 101.

14.

Bhattacharyya

(1989a) Modern pollen spectra from Rohtang range, Himachal Pradesh. Journal Palynology 25: 121–131.

15.

Bhattacharyya

(1989b) Modern pollen spectra of Bada Shigri Glacier, Greater Himalayan Range, Lahaul-Spiti District, Himachal Pradesh. Scientific Culture 55: 246–248.

16.

Bhattacharyya

(1989c) Vegetation and climate during the last 30,000 years in Ladakh. Palaeogeography, Palaeoclimatology, Palaeoecology 73: 25–38.

17.

Bhutiyani

Kale

Pawar

(2010) Climate change and the precipitation variations in the northwestern Himalaya: 1866–2006. International Journal of Climatology 30: 535–548.

18.

Birks

HJB

Birks

(1980) Quaternary Palaeoecology. London: Edward Arnold Publishers, p. 289.

19.

Birks

HJB

Gordon

(1985) Numerical Methods in Quaternary Pollen Analysis. London: Academic Press, p. 317.

20.

Boom

Mora

Cleef

et al . (2001) High altitude C₄ grasslands in the northern Andes: relicts from glacial conditions? Review of Palaeobotany and Palynology 115: 147–160.

21.

Bradshaw

RHW

Webb

III (1985) Relationships between contemporary pollen and vegetation data from Wisconsin and Michigan, USA. Ecology 66: 721–737.

22.

Brooks

Mittermeier

da Fonseca et al . (2006) Global biodiversity conservation priorities. Science 313: 58–61.

23.

Broström

Gaillard

Ihse

et al . (1998) Pollen-landscape relationships in modern analogues of ancient cultural landscapes in southern Sweden: A first step towards quantification of vegetation openness in the past. Vegetation History and Archaeobotany 7: 189–201.

24.

Calcote

(1998) Identifying forest stand types using pollen from forest hollows. The Holocene 8: 423–32.

25.

Cannel

Smith

(1984) Spring frost damage on young Picea sitchensis. Predicted dates of budburst and probability of frost damage. Forestry 57: 177–95.

26.

Cariñanos

Casares-Porcel

Quesada-Rubio

(2014) Estimating the allergenic potential of urban Green spaces: A case-study in Granada, Spain. Landscape and Urban Planning 123: 134–144.

27.

Caseldine

Pardoe

(1994) Surface pollen studies from alpine/sub-alpine southern Norway: Applications to Holocene data. Review of Palaeobotany Palynology 82: 1–15.

28.

Cerling

Harris

MacFadden

et al . (1997) Global vegetation change through the Miocene/Pliocene boundary. Nature 389: 153–158.

29.

Cerling

Quade

Wang

et al . (1989) Carbon isotopes in soils and palaeosols as ecology and palaeoecology indicators. Nature 34: 138–139.

30.

Champion

Seth

S K

(1968) A Revised Survey of Forest Types of India. New Delhi: Government of India Press, p. 404.

31.

Chauhan

Sharma

(1993) Modern pollen deposition in Subtropical zone of Kumaon Himalaya. Geophytology 3: 147–153.

32.

Chauhan

Sharma

(1996) Late-Holocene vegetation of Darjeeling (Jore-Pokhari), eastern Himalaya. Palaeobotanist 45: 125–129.

33.

Chauhan

Mazari

Rajagopalan

(2000) Vegetation and climate in upper Spiti region, Himachal Pradesh during late Holocene. Current Science 79: 373–377.

34.

Chettri

Sharma

Deb

(2001) Bird community structure along a trekking corridor of Sikkim Himalaya: A conservation perspective. Biological Conservation 102: 1–16.

35.

Cook

van

van der

et al . (2011) A review of the use of non-pollen palynomorphs in palaeoecology with examples from Australia. Palynology 35: 155–178.

36.

Court-Picon

Buttler

de Beaulieu

(2006) Modern pollen/vegetation/land-use relationships in mountain environments: An example from the Champsaur valley (French Alps). Vegetation History and Archaeobotany 15: 151–168.

37.

Cugny

Mazier Galop

(2010) Modern and fossil non-pollen palynomorphs from the Basque mountains (western Pyrenees, France): The use of coprophilous fungi to reconstruct pastoral activity. Vegetation History and Archaeobotany 19: 391–408.

38.

Dean

Jr (1974) Determination of carbonate and organic matter in calcareous sediments and sedimentary rocks by loss on ignition: Comparison with other methods. Journal of Sedimentary Petrology 44: 242–248.

39.

Deines

(1980) The isotopic composition of reduced organic carbon. In: Fritz

Fontes

(eds) Handbook of Environmental Isotope Geochemistry. Amsterdam: Elsevier, pp. 329–406.

40.

Dietre

Gauthier

Gillet

(2012) Modern pollen rain and fungal spore assemblages from pasture woodlands around Lake Saint-Point (France). Review of Palaeobotany and Palynology 186: 69−89.

41.

Dimri

Dash

(2012) Wintertime climatic trends in the western Himalayas. Climatic Change 111(3–4): 775–800.

42.

Duan

Zhang

et al . (2009). Insect and wind pollination of an alpine biennial Aconitum gymnrum (Ranunculaceae). Plant Biology 11: 796–802.

43.

Ehleringer

Cerling

Helliker

(1997) C₄ photosynthesis, atmospheric CO₂ and climate. Oecologia 112: 285–299.

44.

ENVIS (2016) Environmental Information System (ENVIS) Centre, Ministry of Environment and Forest, Govt. of India. Available at: http://www.sikenvis.nic.in/database/naturalresources_790.aspx?format=print.

45.

Erdtman

(1943) An Introduction to Pollen Analysis. Waltham, MA: Chronica Botanica, p. 239.

46.

Ertl

Pessi

Huusko

et al . (2012) Assessing the proportion of ‘extra local’ pollen by means of modern aerobiological phonological records – An example from Scots pine (Pinus sylvestris L.) in northern Finland. Review of Palaeobotany and Palynology 185: 1–12.

47.

Faegri

Iversen

(1964) Textbook of Pollen Analysis. Hoboken, NJ: John Wiley & Sons.

48.

Fall

(1992) Pollen accumulation in a montane region of Colorado, USA. Review of Palaeobotany Palynology 72: 169–197.

49.

Farquhar

Ehleringer

Hubick

(1989) Carbon isotope discrimination in photosynthesis. Annual Review of Plant Physiology and Plant Molecular Biology 40: 503–537.

50.

Feeser

O’Connell

(2009) Fresh insights into long-term changes in flora, vegetation, land use and soil erosion in the karstic environment of the Burren, western Ireland. Journal of Ecology 97: 1083–1100.

51.

Feeser

O’Connell

(2010) Late Holocene land-use and vegetation dynamics in an upland karst region based on pollen and coprophilous fungal spore analyses: An example from the Burren, western Ireland. Vegetation History and Archaeobotany 19: 409–426.

52.

Flenley

(1973) The use of modern pollen rain samples in the study of the vegetational history of tropical regions. In: Birks

West

(eds) Quaternary Plant Ecology: The 14th Symposium of the British Ecological Society. Oxford: Blackwell Scientific, pp. 131–141.

53.

Fujita

Kadota

Rana

et al . (2001a) Shrinkage of Glacier AX010 in Shorong region, Nepal Himalayas in the 1990s. Bulletin of Glaciological Research 18: 51–54.

54.

Fujita

Nakazawa

Rana

(2001b) Glaciological observations on Rikha Samba Glacier in Hidden Valley, Nepal Himalayas, 1998 and 1999. Bulletin of Glaciological Research 18: 31–35.

55.

Gaillard

Birks

HJB

Emanuelsson

et al . (1992) Modern pollen/land-use relationships as an aid in the reconstruction of past land-uses and cultural landscapes: An example from south Sweden. Vegetation History and Archaeobotany 1: 3–17.

56.

Gansser

(1964) The Geology of the Himalayas. New York: Wiley Interscience, p. 289.

57.

Grierson

AJC

Long

(1991 [1983]) Flora of Bhutan, vols 1–3. Edinburgh: Royal Botanical Garden.

58.

Ghosh

Bera

Sarkar

et al . (2015) A ~50 ka record of monsoonal variability in the Darjeeling foothill region, eastern Himalayas. Quaternary Science Reviews 114: 100–115.

59.

Ghosh

Paruya

Khan

et al . (2014) Late Quaternary climate variability and vegetation response in Ziro Lake Basin, Eastern Himalaya: a multiproxy approach. Quaternary International 325: 13–29.

60.

Ghosh

Paruya

Acharya

et al . (2017) How reliable are non-pollen palynomorphs in tracing vegetation changes and grazing activities? Study from the Darjeeling Himalaya, India. Palaeogeography, Palaeoclimatology, Palaeoecology 475: 23–40.

61.

Goetghebeur

(1998) Cyperaceae. In: Kubitzki

Huber

Rudall

al.

(eds) The Families Genera of Vascular Plants. Berlin: Springer-Verlag, pp. 141–190.

62.

Gosling

Mayle

Tate

et al . (2005) Modern pollen-rain characteristics of tall terra firme moist evergreen forest, southern Amazonia. Quaternary Research 64: 284–97.

63.

Grimm

(1990) TILIA TILIA.GRAPH: PC spreadsheet graphics software for pollen data (Newsletter 4). INQUA, Working Group on Data-Handling Methods, July, pp. 5–7.

64.

Gupta

Yadav

(1992) Interplay between pollen rain and vegetation of Tarai-Bhabar in Kumaon Division, U.P., India. Geophytology 21: 183–189.

65.

Gusain

Mishra

Bhutiyani

(2014) Winter temperature and snowfall trends in the cryospheric region of north-west Himalaya. Mausam 65: 425–432.

66.

Hajra

Verma

Giri

(eds) (1996) Materials for the Flora of Arunachal Pradesh, vol. I. Calcutta: Botanical Survey of India.

67.

Havinga

(1964) Investigation into the differential corrosion susceptibility of pollen and spores. Pollen et Spores 6: 621–635.

68.

Havinga

(1984) A 20-year experimental investigation into the differential corrosion susceptibility of pollen and spores in various soil types. Pollen et Spores 26: 541–558.

69.

Heiri

Lotter

Lemcke

(2001) Loss on ignition as a method for estimating organic carbonate content in sediments: Reproducibility and comparability of results. Journal of Paleolimnology 25: 101–110.

70.

Hicks

(2001) The use of annual arboreal pollen deposition values for delimiting tree-lines in the landscape and exploring models of pollen dispersal. Review of Palaeobotany and Palynology 117: 1–29.

71.

Immerzeel

(2008) Historical trends and future predictions of climate variability in the Brahmaputra basin. International Journal of Climatology 28: 243–254.

72.

Jackson

Lyford

(1999) Pollen dispersal models in quaternary plant ecology: assumptions, parameters, and prescriptions. Botanical Review 65: 39–75.

73.

Jackson

Williams

(2004) Modern analogs in Quaternary paleoecology: here today, gone yesterday, gone tomorrow? Annual Reviews of Earth Planetary Sciences 32: 495–537.

74.

Janssen

(1966) Recent pollen spectra from the deciduous and coniferous-deciduous forests of northeastern Minnesota: A study in pollen dispersal. Ecology 47: 804–825.

75.

Janssen

(1970) Problems in the recognition of plant communities in pollen diagrams. Vegetation 20: 187–198.

76.

Kar

Bajpai

Mishra

(2016) Modern pollen rain in Kedarnath: implications for past vegetation and climate. Current Science 110: 296–298.

77.

Kar

Bajpai

Singh

(2015) Modern pollen assemblages from Hamtah and Chhatru glaciers, Lahaul-Spiti, India: Implications for pollen-vegetation relationship in an alpine arid region of western Himalaya. Quaternary International 371: 102–110.

78.

Kato

(1993) Biogeography of ferns: dispersal variance. Journal of Biogeography 20: 265–274.

79.

Kessler

Kluge

Hemp

et al . (2011) A global comparative analysis of elevational species richness patterns of ferns. Global Ecology Biogeography 20: 868–880.

80.

Kohn

(2010) Carbon isotope compositions of terrestrial C3 plants as indicators of (paleo)ecology and (paleo)climate. Proceedings of the National Academy of Sciences of the United States of America 107: 19691–19695.

81.

Körner

(1999) Alpine Plant Life: Functional Plant Ecology of High Mountain Ecosystems. Berlin: Springer-Verlag, p. 343.

82.

Legendre

Gallagher

(2001) Ecologically meaningful transformations for ordination of species data. Oceaologia 129: 271–280.

83.

McMullen

(1993) Wind pollination in the Galápagos Island. Noticias de Calápagos 52: 12–17.

84.

Meyers

(1994) Preservation of elemental and isotopic source identification of sedimentary organic matter. Chemical Geology 114: 289–302.

85.

Miehe

(1996) On the connexion of vegetation dynamics with climatic changes in high Asia. Palaeogeography, Palaeoclimatology, Palaeoecology 120: 5–24.

86.

Moore

Webb

(1978) An Illustrated Guide to Pollen Analysis. London: Hodder Stoughton.

87.

Oksanen

Blanchet

Kindt

et al . (2015) Vegan: Community ecology package (R package version 2.2–1). Available at: http://CRAN.R-project.org/package=vegan.

88.

O’Leary

(1988) Carbon isotopes in photosynthesis. Bioscience 38: 328–336.

89.

O’Leary

Rife

Slater

(1981) Kinetic and isotope effect studies of maize phosphoenolpyruvate carboxylase. Biochemistry 20: 7308–7314.

90.

Overpeck

Webb

III Prentice

(1985) Quantitative interpretation of fossil pollen spectra: dissimilarity coefficients and the method of modern analogs. Quaternary Research 23: 87–108.

91.

Pidek

Piotrowska

Kasprzyk

(2010) Pollen-vegetation relationships for pine and spruce in southeast. Poland on the basis of volumetric and Tauber trap records. Grana 49: 215–226.

92.

Pišút

Břízová

Čejka

et al . (2010) Paleofloristic and paleofaunistic analysis of Dudváh River oxbow and implication for Late Holocene paleoenvironmental development of the Žitný ostrov Island (SW Slovakia). Geologica Carpathica 61: 513–533.

93.

Poos

Jackson

(2012) Addressing the removal of rare species in multivariate bioassessments: The impact of methodological choices. Ecological Indicators 18: 82–90.

94.

Prentice

(1985) Pollen representation, source area, and basin size: toward a unified theory of pollen analysis. Quaternary Research 23: 76–86.

95.

Prentice

Berglund

Olssen

(1987) Quantitative forest-composition sensing characteristics of pollen samples from Swedish lakes. Boreas 16: 43–54.

96.

Quamar

Bera

(2014) Surface pollen and its relationship with modern vegetation in tropical deciduous forests of southwestern Madhya Pradesh, India: A review. Palynology 38: 147–161.

97.

R Core Team (2014) R: A Language Environment for Statistical Computing. Vienna: R Foundation for Statistical Computing. Available at: http://www.R-project.org/.

98.

Ranhotra

Bhattacharyya

(2013) Modern vegetational distribution and pollen dispersal study within Gangotri Glacier Valley, Garhwal Himalaya. Journal of Geological Society of India 82: 133–142.

99.

Rao

(1974) Vegetation phytogeography of Assam–Burma. In: Mani

(ed.) Ecology Biogeography of India. The Hague: Dr. W. Junk B.V. Publishers, pp. 204–246.

100.

Rao

Guo

Cao

et al . (2017) Relationship between the stable carbon isotopic composition of modern plants and surface soils and climate: A global review. Earth-Science Reviews 165: 110–119.

101.

Räsänen

(2001) Tracing interpreting fine-scale human impact in northern Fennoscandia with the aid of modern pollen analogues. Vegetation History and Archaeobotany 10: 211–218.

102.

Rawat

Gupta

Srivastava

et al . (2015a) A 13,000 year record of environmental magnetic variations in the lake and peat deposits from the Chandra valley, Lahaul: Implications to Holocene monsoonal variability in the NW Himalaya. Palaeogeography, Palaeoclimatology, Palaeoecology 440: 116–127.

103.

Rawat

Gupta

Sangode

et al . (2015b) Late Pleistocene–Holocene vegetation and Indian summer monsoon record from the Lahaul, Northwest Himalaya, India. Quaternary Science Reviews 114: 167–181.

104.

Rawat

Phadtare

Sangode

(2012) The Younger Dryas cold event in NW Himalaya based on pollen record from the Chandra Tal area in Himachal Pradesh, India. Current Science 102: 1193–1198.

105.

Sage

(1999) Why C₄ photosynthesis? In: Sage

Monson

(eds) C₄ plant biology. San Diego, CA: Academic Press, pp. 3–16.

106.

Schaller

(1977) Mountain Monarchs: Wild Goat Sheep of the Himalaya. Chicago, IL: University of Chicago Press.

107.

Schuettpelz

Schneider

Huiet

et al . (2007) A molecular phylogeny of the fern family Pteridaceae: Assessing overall relationships and the affinities of previously unsampled genera. Molecular Phylogenetics and Evolution 44: 1171–1185.

108.

Schunke

(1977) Zur genese der thufur Isls und Ost-Grönls. Erdkunde 31: 279–87.

109.

Schunke

Zoltai

(1988) Earth hummocks. In: Clark

(ed.) Advances in Periglacial Geomorphology. Chichester: John Wiley & Sons, pp. 231–45.

110.

Seppä

Hicks

(2006) Integration of modern and past pollen accumulation rate (PAR) records across the arctic tree-line: A method for more precise vegetation reconstructions. Quaternary Science Reviews 25: 1501–1516.

111.

Sharma

(1973) Recent pollen spectra from Himachal Pradesh. Geophytology 3: 5–144.

112.

Sharma

(1985) Recent pollen spectra from Garhwal Himalaya. Geophytology 15: 87–97.

113.

Sharma

Chauhan

(2001) Late-Holocene vegetation climate of Kupup (Sikkim), eastern Himalaya, India. Journal of the Palaeontological Society of India 46: 51–58.

114.

Sharma

Trivedi

Malik

(2001) Modern pollen/spore rain in Surinsar and Mansar lakes, Jammu. Geophytology 3: 9–17.

115.

Shrestha

Wake

Mayewski

et al . (1999) Maximum temperature trends in the Himalaya and its vicinity: An analysis based on temperature records from Nepal for the period 1971–94. Journal of Climate 12: 2775–2786.

116.

Sikkim SAPCC (2011) Sikkim Action Plan on Climate Change (2012–2030). Available at: http://www.moef.nic.in/sites/default/files/sapcc/Sikkim.pdf.

117.

Simpson

Inglis

(2001) Cyperaceae of economic, ethnobotanical and horticultural importance: A checklist. Kew Bulletin 56: 257–360.

118.

Singh

Chauhan

(1997) Plant diversity in Sikkim Himalaya. In: Hajra

Mudgal

(eds) Plant Diversity Hotspots of India: An Overview. Kolkata: Botanical Survey of India, pp. 137–158.

119.

Sugita

(2007) Theory of quantitative reconstruction of vegetation I: Pollen from large sites REVEALS regional vegetation. The Holocene 17: 229–241.

120.

Tauber

(1965) Differential pollen dispersal and the interpretation of pollen diagrams. Danmarks Geologiske Undersøgelse (Afhlinger), Række II 89: 1–69.

121.

Taylor

Kerp

Hass

(2005) Life history biology of early land plants: deciphering the gametophyte phase. Proceedings of the National Academy of Sciences of the United States of America 102: 5892–5897.

122.

Telwala

(2012) Climate change alpine flora in Sikkim Himalaya. In: Arrawatia

Tambe

(eds) Climate Change in Sikkim-Patterns, Impacts and Initiatives. Sikkim, India: Information and Public Relations Department, Government of Sikkim, pp. 103–124.

123.

van Geel

Buurman

Brinkkemper

et al . (2003) Environmental reconstruction of a Roman Period settlement site in Uitgeest (The Netherlands), with special reference to coprophilous fungi. Journal of Archaeological Science 30: 873–883.

124.

Vellend

Lechowicz

Waterway

(2000) Environmental distribution of four carex species (cyperaceae) in an old-growth forest. American Journal of Botany 87: 1507–1516.

125.

Vishnu-Mittre Robert

(1971) Studies of pollen content of moss cushions in relation to forest composition in the Kashmir valley. Geophytology 1: 84–96.

126.

Webb

III Howe

Bradshaw

RHW

et al . (1981) Estimating plant abundances from pollen percentages: the use of regression analysis. Review of Palaeobotany Palynology 34: 269–300.

127.

Whitbread

(1995) Soil organic matter: Its fractionation and role in soil structure. In: Lefroy

RDB

Blair

Craswell

(eds) Soil Organic Matter Management for Sustainable Agriculture. Queensland: The Australian Society of Agronomy, pp. 124–130.

128.

Wilmshurst

McGlone

(2005) Origin of pollen and spores in surface lake sediments: Comparison of modern palynomorph assemblages in moss cushions, surface soils and surface lake sediments. Review of Palaeobotany Palynology 136: 1–15.

129.

Wright

Jr (1967) The use of surface samples in Quaternary pollen analysis. Review of Palaeobotany and Palynology 2: 321–330.

130.

Wünnemann

Demsk

Tarasov

et al . (2010) Hydrological evolution during the last 15 kyr in the Tso Kar lake basin (Ladakh, India), derived from geomorphological, sedimentological and palynological records. Quaternary Science Reviews 29: 1138−1155.

131.

Tian

et al . (2009) Pollen assemblages of tauber traps and surface soil samples in steppe areas of China their relationships with vegetation climate. Review of Palaeobotany and Palynology 153: 86–101.

132.

Yao

Song

Wortley

et al . (2015) A 22 570-year record of vegetational and climatic change from Wenhai Lake in the Hengduan Mountains biodiversity hotspot, Yunnan, Southwest China. Biogeosciences 12: 1525–1535.

Supplementary Material

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Characteristics of modern biotic data and their relationship to vegetation of the Alpine zone of Chopta valley,North Sikkim,India: Implications for palaeovegetation reconstruction

Abstract

Keywords

Introduction

Study area

Geomorphological setup of the study site

Climate

Vegetation

Materials and methods

Samples: Collection and extraction of pollen and NPPs

Isotopic sample preparation

Sample preparation for loss on ignition

Multivariate analyses

Results

Palynoassemblages

NPP

LOI and δ13C

Discussion

Pollen rain–vegetation relationship

NPP and their ecological indicative values

LOI and δ13C: Relationships to vegetation

Conclusion

Footnotes

Acknowledgements

Funding

References

Supplementary Material

LOI and δ¹³C

LOI and δ¹³C: Relationships to vegetation