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Variation of phytochemistry, morphology and population structure in Trillium govanianum (Melanthiaceae)

Journal: Botany

Manuscript ID cjb-2020-0140.R1

Manuscript Type: Article

Date Submitted by the Author: 19-May-2021

Complete List of Authors: Chauhan, Harsh; Kumaun University, Department of BotanyGallacher, David ; The University of Sydney, School of Life and Environmental SciencesBisht, Anil; Kumaun University, Department of BotanyBhatt, Indra; G.B. Pant National Institute of Himalayan EnvironmentBhatt, Arvind; Chinese Academy of Science, Lushan Botanical GardenDhyani, Praveen; G.B. Pant National Institute of Himalayan EnvironmentKewlani, Pushpa; G.B. Pant National Institute of Himalayan Environment

Keyword: Adaptation, Anthropogenic pressure, Conservation, High altitude medicinal plant, Natural variations

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Issue? :Not applicable (regular submission)

© The Author(s) or their Institution(s)

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1 Variation of phytochemistry, morphology and population structure in Trillium govanianum 2 (Melanthiaceae)

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7 Harsh Kumar Chauhan1,2*, David Gallacher3, Anil Kumar Bisht1, Indra Dutt Bhatt2, Arvind 8 Bhatt4, Praveen Dhyani2ψ, Pushpa Kewlani2

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14 1Department of Botany, D.S.B. Campus, Kumaun University, Nainital, India-263001

15 2G.B. Pant National Institute of Himalayan Environment, Kosi-Katarmal, Almora, India-263643

16 3School of Life and Environmental Sciences, The University of Sydney, Narrabri, NSW,

17 Australia-2390

18 4Lushan Botanical Garden, Chinese Academy of Science, Lushan, Jiujiang, Jiangxi, China-

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20 ψPresent Address: Department of Biotechnology, Kumaun University, Bhimtal-Nainital, India-

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24 *Corresponding author. Tel.: +91 9557916395; E-mail addresses:

25 [email protected]

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26 Abstract

27 As habitats change, species with higher intraspecific variation have more resources to adapt.

28 Medicinal plants of the Himalayas are increasingly threatened by climate change and other

29 anthropogenic influences. Intraspecific variation within and among 17 populations of the high-

30 altitude herb Trillium govanianum was studied as an indicator of adaptability. Variation in

31 nineteen traits of population structure, morphology and phytochemistry were assessed across

32 habitats that varied in altitude (2452-3432 m), aspect, latitude (30.1-31.7 N) and arboreal

33 community. Morphology and population structure were conserved among populations but varied

34 among regions. Populations in the lower altitude mixed forests of Tirthan Valley produced

35 smaller rhizomes but larger plant densities, such that plant biomass per m2 was conserved.

36 Phytochemistry varied among regions and populations within regions, indicating significant

37 variation among habitats. Above-ground morphology of the species masks considerable

38 variations in below-ground morphology and phytochemistry. The observed variations can help

39 the species to adapt the changing environmental conditions by provoking a functional response.

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41 Keywords: Adaptation; Anthropogenic pressure; Conservation; High altitude medicinal plant;

42 Natural variations

43 1. Introduction

44 The rate at which species adapt to new or changing environments is dependent on their

45 phenotypic plasticity and genetic variation (Fox et al. 2019). Species with a more flexible

46 phenotype and a broad genetic base have more resources to adapt, and therefore more resilience

47 to changing conditions (Forsman 2015). The heterogeneous topography of the Himalayan region

48 provides microenvironments of temperature, humidity and exposure (Sigdel et al. 2018) which

49 have produced enormous plant diversity (Salick et al. 2009). The Indian Himalayas harbors more

50 than 8,000 angiosperm species, of which 1,748 are sufficiently novel to be valued in traditional

51 medicine (Samant et al. 1998, Singh and Hajra 1996). Many microhabitats are geographically

52 separated from similar microhabitats, which facilitate the emergence of distinctive populations

53 within the species adapted to them (Pescador et al. 2015). These populations might have

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54 developed distinct gene pools, or may exhibit phenotypic variation in response to differences in

55 habitat.

56 Morphological variation may be linked to differences in season, altitude, species

57 association, nutrients, and anthropogenic pressures (Albert et al. 2010, Parmesan and Hanley

58 2015, Pescador et al. 2015). Polygonatum verticillatum exhibits declining leaf number, above-

59 and below-ground fresh weight, and below ground dry weight with increasing altitude (Suyal et

60 al. 2020). Synthesis of phenols, flavonoids, tannins, and antioxidants may also be related to

61 specific environment gradients (Penuelas and Llusia 1997, Kefeli et al. 2003, Bhatt et al. 2013).

62 Adverse conditions stimulate the synthesis of free radicals, which cause oxidative stress and

63 impact plant structure and function. The association between phytochemistry and environment

64 has been reported for several medicinal plants. For example, podophyllotoxin variation

65 in Podophyllum hexandrum was associated with altitude, temperature, rainfall, humidity and soil

66 pH (Alam et al. 2008, 2009). Chlorogenic acid of Eucommia ulmoides increased with sunshine

67 and altitude, and decreased with temperature (Dong et al. 2011). Antioxidant activity

68 in Polygonatum verticillatum increased with altitude (Suyal et al. 2020).

69 Wild populations of Trillium govanianum Wall. ex D. Don appear in temperate and

70 subalpine regions of the Himalayas, in shady, cold, moist habitats with thick humus (Chauhan et

71 al. 2018). Wild populations have declined from unregulated gathering (Ahmed and Akhtar 2016,

72 Chauhan et al. 2020a), which is an economically important activity for Himalayan residents

73 (Chauhan et al. 2018). Populations may also be affected by climate change, deforestation, and

74 livestock grazing or trampling (Chauhan et al. 2019). Several changes such as phenological shift,

75 change in distribution, range shift, physiology and growth in wild species have been linked to

76 increased CO2 concentration, warming climate and changing precipitation (Parmesan and Hanley

77 2015).

78 The aim of the present study was to evaluate phenotypic variation of phytochemistry,

79 morphology, and population structure within and among populations of three Indian Himalayan

80 regions. This research will provide insight into the potential resilience of the species to continued

81 habitat changes. It will also provide baseline data for future studies that may look at changes in

82 phenotypic expression over time, or of gene pool variation among populations. Knowledge of

83 phenotypic variation by population will also inform germplasm collection if ex situ propagation

84 becomes viable.

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85 2. Material and methods

86 2.1. Species description

87 The centre of Trillium govanianum diversity is North-West Himalaya (Chauhan and Bisht 2020),

88 and its natural range extends across the Himalayan range of Afghanistan, Bhutan, China (Tibet),

89 India, Nepal and Pakistan (Fukuda 2001, Roskov et al. 2018). Populations are restricted to cold,

90 shady habitats within temperate and sub-alpine forests at altitudes of 2400-3500 m (Polunin and

91 Stainton 1984). The species is listed as endangered by the IUCN (Chauhan and Bisht 2020).

92 Trillium govanianum is a perennial rhizomatous herb with a 15-20 cm tall stem that bears

93 one or three broadly ovate, acute, stalked leaves. Like other Trillium species, it passes through

94 three distinct phenophases, 1-leaf vegetative, 3-leaf vegetative and 3-leaf reproductive (see

95 Chauhan et al. 2018). Flowers are small with six yellow basifixed stamens and a whorl of each

96 petal and sepals. Fruit is a red berry containing multiple seeds. The voucher specimen is

97 deposited to the Botanical Survey of India, Dehradun (Accession No. 115223). Individuals

98 emerge annually in early spring following snowmelt and flower from May to June. Berries

99 mature in July-August at low altitude and September-October at higher altitudes. Asexual

100 reproduction is rare in the genus (Ohara 1989, Kubota et al. 2008), and there has been little

101 success in ex-situ propagation (Chauhan et al. 2020b).

102 The species is a rich source of antioxidants (Kundra et al. 2020) and is among the most

103 traded species of the region (Khan et al. 2016). Rhizomes are gathered for the steroidal

104 compounds Govanoside A, Borassoside E, Pennogenin, Diosgenin, 20-hydroxyecysone, 5, 20-

105 dihydroxyecdysone and govanic acid (Rahman et al. 2017), and used to treat dysentery, wounds,

106 skin boils, inflammation, sepsis, menstrual and sexual disorders (Pant and Samant 2010,

107 Chauhan and Bisht 2020, Chauhan et al 2020a, 2020b).

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109 2.2. Study area

110 Within the Indian Himalayas, the species is most common in Jammu and Kashmir, Himachal

111 Pradesh, and Uttarakhand (Chauhan et al. 2018). A total of 17 populations of T.

112 govanianum were studied from three regions of Himachal Pradesh and Uttarakhand (Table 1),

113 selected with assistance from local plant gatherers to represent the range of habitats. Among the

114 three regions, Tunghnath and Munsiyari were selected from Uttarakhand and Tirthan Valley

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115 from Himachal Pradesh (Figure 1). Populations varied in altitude, latitude, arboreal community,

116 and aspect but the influence of these variables could not be assessed in isolation.

117 Aspect significantly affects habitats since all regions are north of the Tropic of Cancer.

118 Thus, north-facing slopes have lower average sunlight penetration throughout the year. Tirthan

119 Valley (Himachal Pradesh; high latitude, low altitude) has temperate mixed-species forest

120 habitats, and T. govanianum populations occur on aspects facing all cardinal points. Both

121 Munsiyari and Tunghnath (Uttarakhand) have Rhododendron forest habitats with T.

122 govanianum populations on north-facing aspects only. Munsiyari is low latitude, mid to high

123 altitude, while Tunghnath is mid-latitude, high altitude. Selected T. govanianum populations

124 were separated by at least 500 m and usually also by a geographic boundary, and thus were

125 considered distinct populations (Osunkoya 1999). Commercial gathering is affecting population

126 distributions in Munsiyari and Tirthan Valley but is not reported from Tunghnath (Chauhan et al.

127 2018).

128

129 2.3. Population and morphology

130 Number of 1- and 3-leaf plants was counted in twenty 1m2 plots in each of three 100 m2

131 replicates of each population. Replicate were selected visually within the natural growing area of

132 each selected population. In four study sites (Taati, Base Khalli, Tunghnath 2 and Tunghnath 3)

133 just one replicate was assessed due to the small size of these populations. From these data,

134 density (number of 1-leaf and number of 3-leaf plants per plot), age ratio (number of 1-leaf

135 plants/number of 3-leaf plants) and frequency (proportion of plots with at least one 1-leaf plant,

136 repeated for 3-leaf plants) were calculated. These data have been presented previously (Chauhan

137 et al. 2018).

138 Five 3-leaf vegetative plants aged 11-15 years were removed from each population for

139 morphological analysis. Age was estimated from the number of internodes on the rhizome

140 (Hanzawa and Kalisz 1993) and rejected individuals were replanted in situ. This age range was

141 chosen to enable comparison among populations while minimizing disturbance to natural

142 populations. Plants at the reproductive stage were not used because they were unavailable at

143 some of the more disturbed populations of Tirthan Valley. Each plant was washed by immersing

144 in water and stirring thoroughly and then placed in the shade until dry. Morphological

145 measurements included shoot length from plant base to a leaf node, leaf area (graph paper

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146 method; Jugran et al. 2013), fresh biomass of aboveground (shoot, leaf) and belowground (root,

147 rhizome) components, number of roots, length of the longest root, and rhizome maximum length

148 and diameter. Morphological measurements including fresh biomass were made in the field. Dry

149 biomass was not included because fungal contamination could not be prevented from samples

150 that were collected several days’ travel from a laboratory. Species’ biomass per square meter was

151 estimated for each population by multiplying the average plant biomass for each population by

152 the average plant (1- and 3-leaf) density.

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154 2.4. Phytochemistry

155 Five rhizomes were collected from each population, washed in distilled water, dried in a hot-air

156 oven at 40°C until they reached a constant mass, then ground to a fine powder. Solutions of 0.5 g

157 rhizome powder and 50 ml 80% (v/v) methanol were gently stirred for 12 hours, sonicated at

158 22°C for 10 minutes, and centrifuged at 10000 rpm for 15 minutes. The supernatant was filtered

159 and stored at -20°C until analysis.

160 Phenolic content was determined using Folin–Ciocalteu’s colorimetric method (Singleton

161 and Rossi 1965, Rawat et al. 2016). The extract (0.5 ml) diluted with distilled water (4.5 ml) was

162 mixed with Folin Ciocalteu’s reagent (0.5 ml) and allowed to stand for reaction (5 min). The

163 mixture was neutralized by 1% sodium carbonate (5 ml) and incubated in dark for 90 min at

164 22±1°C. The absorbance of the resultant blue color was measured at 765 nm using UV–Vis

165 spectrophotometer (U-2001, Hitachi, Japan). Quantification of total phenols was based on the

166 standard curve of gallic acid prepared in 80% (v/v) methanol and results were expressed in mg

167 gallic acid equivalent (GAE) per 100 grams dry weight (GAE/100g).

168 Flavonoids in the extract were determined by aluminium chloride calorimetric method

169 (Chang et al. 2002). 0.50 ml of methanolic extract of the sample was diluted with 1.50 ml of

170 distilled water and 0.50 ml of 10% (w/v) aluminium chloride added along with 0.10 ml of 1M

171 potassium acetate and 2.80 ml of distilled water. This mixture was incubated at room

172 temperature for 30 min. The absorbance of the resulting reaction mixture was measured at 415

173 nm UV-VIS spectrophotometer. Quantification was based on the standard curve of quercetin

174 prepared in 80% methanol, results were expressed in mg quercetin equivalent per 100 gram of

175 dry weight (QE/100g).

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176 Tannin content was estimated following Nwinuka et al. (2005). The methanol extract of

177 the rhizomes was added to Folin-Dennis reagent (0.5 ml) and saturated with Sodium carbonate

178 (1ml). The solution was diluted up to 10 ml with distilled water. The solution was kept at room

179 temperature (25 °C) for 20 minutes. The absorbance by solution was measured at 700 nm. The

180 quantification of tannin content was based on the standard curve of tannic acid prepared in 80%

181 (v/v) methanol and results were expressed in mg tannic acid equivalent (TAE) per 100 grams dry

182 weight (TAE/100g).

183 Antioxidant activity was determined using three in vitro methods: ABTS (2,2'-azino-bis

184 3-ethylbenzothiazoline-6-sulfonic acid) radical scavenging activity assay (Cai et al., 2004),

185 DPPH (2,2-diphenyl-1-picryl-hydrazyl-hydrate) free radical scavenging assay (Brand-Williams

186 et al. 1995), and FRAP (ferric reducing antioxidant power) assay (Faria et al. 2005). ABTS assay

187 as described by Cai et al. (2004) was used for the measurement of the antioxidant activity. ABTS

188 (7.0 μM) and potassium persulphate (2.45 μM) were added for the production of ABTS cation in

189 an amber-colored bottle. The bottle was kept in dark for (16 h, 22±1ºC). The solution was diluted

190 with 80% (v/v) ethanol till an absorbance of 0.700± 0.05 at 734 nm is obtained. Sample analysis

191 was performed by adding 0.10 ml of methanolic extract with 3.90 ml of this diluted ABTS

192 solution. The resulted solution was mixed and allowed to stand for 6 min in dark at 23ºC.

193 Absorbance was recorded at 734 nm using UV-VIS spectrophotometer. Samples were diluted

194 with 80% (v/v) methanol to obtain 20-80% reduction in absorbance at 734 nm with respect to the

195 blank.

196 Antioxidant activity by DPPH assay was analysed following Brand-William et al. (1995)

197 with minor modifications. 400 μM DPPH, 0.2M MES buffer (pH 6.0) and 20% (v/v) ethanol was

198 added for the DPPH cation preparation. The prepared DPPH cation solution (2.7 ml) was mixed

199 with 0.9 ml sample extract and kept in dark at room temperature for 20 minutes. Absorbance was

200 taken at 520 nm by UV-VIS spectrophotometer. Results were expressed in millimole (mM)

201 ascorbic acid equivalent (AAE)/100g of the sample on a dry weight basis.

202 FRAP assay was performed following Faria et al. (2005) with few modifications. FRAP

203 reagent was prepared by adding 300 mM acetate buffer (10 vol); 10 mM 2, 4, 6-tri-2-pyridyl-1,

204 3, 5-triazin (TPTZ) in 40 mM HCl (1 vol); 20 mM ferric chloride (1 vol). The mixture was pre-

205 warmed at 37 °C and 3.0 ml of the mixture was added to 0.1 ml methanolic extract and kept at

206 37 °C for 8 minutes. Absorbance was recorded at 593 nm. A blank sample was prepared by

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207 ascorbic acid and results were expressed in mM ascorbic acid equivalent (AAE)/100 g dry

208 weight.

209

210 2.5. Data analysis

211 Variability in phytochemistry, morphology and population structure of T. govanianum across

212 populations located in different altitudes, latitude and habitat factors of region, arboreal

213 community and aspect was assessed using analysis of variance in which populations were nested

214 within the factor, using IBM SPSS v23. Means and pairwise comparisons of significance were

215 recorded for significant factors. Altitude was assessed using Pearson’s correlation coefficient for

216 each region individually and combined. The Bonferroni correction was applied across inter-and

217 intra-factor effects for each factor, and across pairwise comparisons for each factor. Hence

218 α=0.05/x, where x=38 for region, arboreal community and aspect and their nested populations,

219 x=19 for altitude (all regions); for pairwise comparisons among regions, x = 42, arboreal

220 communities, x = 39, and aspect groups, x = 30; for correlations of altitude within each region, x

221 = 57.

222 3. Results

223 Most phytochemical variables exhibited strong differences between the high altitude regions of

224 Munsiyari and Tunghnath and between Rhododendron dominant and pure Rhododendron forests

225 (Figure 2 and 3). Almost all variables exhibited spatial influences on phytochemistry at both the

226 intra- and interregional scales. Altitude did not affect the phytochemistry within regions (Table

227 5).

228 Phenol concentration was higher in Tirthan Valley than the other regions and was not

229 significantly affected by factors separating the higher altitude populations (Figure 2). Flavonoid

230 concentration was highest in the partially north-facing pure Rhododendron forests of Munsiyari

231 (Figure 3 and 4), and lowest in the south-facing populations of Tirthan Valley (Figure 2 and 4).

232 Tannin concentration was highest in the partially north-facing populations of Munsiyari (Figure

233 2 and 4), and lowest in the mostly north-facing Rhododendron dominant forests of Tunghnath.

234 ABTS concentration was lowest in the Rhododendron dominant forests (Figure 3). DPPH

235 concentration was highest in the south-facing populations of Tirthan Valley and lowest in

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236 Munsiyari (Figure 2 and 4). FRAP concentration was substantially lower in the mostly north-

237 facing Rhododendron dominant forests of Tunghnath.

238 All root morphology variables other than fresh biomass were smaller in Tirthan Valley

239 but there was no difference among populations (Figure 2). Hence, roots were shorter and fewer

240 and rhizomes were smaller, but root mass was constant (Table 2). In the other regions, there was

241 no difference among Rhododendron dominant and pure Rhododendron forests (Table 3) nor

242 between populations of different aspects (Table 4). Leaf area, population age ratio, and fresh

243 biomass of both shoots and roots were strongly conserved across all factors (Tables 2-5). Shoot

244 length was also highly conserved, differing among the regions of Tirthan Valley and Munsiyari

245 but not among any other factors. Plant biomass per square meter was also strongly conserved

246 across all factors, although the power of this test was much lower. Therefore a non-destructive

247 observation of above-ground morphology of individual plants would suggest the minimal

248 variation among populations.

249 Density of both 1- and 3-leaf plants was lower in Munsiyari than other regions, though

250 the age ratio of populations was constant (Figure 2). Regions differentiated populations by plant

251 density variables more than arboreal community (Table 3) or aspect (Table 4), but altitude was

252 positively correlated with plant density within the lower altitude region of Tirthan Valley (Table

253 5). Frequency was greatest in the mixed species forests of Tirthan Valley for both 1- and 3- leaf

254 plants (Table 2, 3).

255 4. Discussion

256 Plant species demonstrate enormous diversity in eco-physiological and functional traits at local,

257 regional and global scales, linked to climatic and environmental variation (Ackerly et al. 2000).

258 The present study revealed significant phytochemical variation among regions and populations

259 within regions. This type of variation is to be expected, due to different habitats causing different

260 phenotypic expression, or of isolated populations developing distinct gene pools. Such variation

261 among populations has been observed in other Himalayan medicinal plants (Suyal et al. 2020).

262 Phenols are normally produced in response to environmental stress (Klepacka et al. 2011)

263 indicating that populations varied in their exposure to stresses such as pathogens, insect or

264 vertebrate herbivory, or sunlight exposure. Flavonoids also are produced in response to

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265 environmental cues (Kefeli et al. 2003). T. govanianum has a patchy distribution, limited to cold,

266 shaded and moist habitat (Chauhan et al. 2018). Patchy distribution and geographical barriers

267 accelerate genetic differences increasing the adaptability to specific habitat (Rawat et al. 2018).

268 Differences in root morphology and population structure are likely attributable to

269 regional characteristics other than those investigated. Above-ground morphology and biomass

270 per square meter were highly conserved among populations both within and among regions. Root

271 morphology and population structure varied among regions but not within them, other than a

272 decline in plant density at the lower range of altitudes. The similar root morphology and

273 population structure among populations of a region might indicate gene flow among populations

274 is much stronger than among regions. Thus, we speculate that the species might exhibit adaptive

275 genetic diversity among regions (Buckley et al. 2010, Ishizuka et al. 2020). The spatially

276 separated populations among regions differ climatically and edaphically, which could promote

277 variation in these traits.

278 The shorter roots and smaller rhizomes of Tirthan Valley had the same fresh biomass as

279 roots from other regions. These lower-altitude mixed forests contained an abundant layer of

280 humus and leaf litter due to the higher proportion of broad-leaved trees. T. govanianum roots

281 may have been shallower and thicker because nutrients were closer to the surface. Higher

282 humus/carbon and root associations normally result in increased biomass and growth of sub-

283 alpine and alpine species (Callaway et al. 2002, North et al. 2005). It is not known why plants

284 put resources into thicker, shorter roots rather than rhizomes in this region, but this may be

285 related to a longer growing season at these lower altitudes. Higher altitude was correlated with

286 greater resource allocation to roots, and particularly rhizomes (Ma et al. 2010). Species’ fitness

287 generally declines with altitude, correlating with lower temperature and a shorter growing season

288 (Korner 2003). Rhizome size is significant for the regional economy since gathered rhizomes are

289 sold on a dry-weight basis (Chauhan et al. 2018, 2020a) and the amount of active constituents is

290 assumed to be proportional to weight (Jugran et al. 2013). The larger rhizomes of Munsiyari and

291 Tunghnath could reflect that these regions are more suitable for T. govanianum. Tirthan valley

292 populations have been more heavily disturbed by medicinal plant gatherers (Chauhan et al. 2018)

293 hence morphological differences may also reflect a recovering population. Selective removal by

294 gatherers can also reduce genetic diversity (Cruse-Sanders et al. 2005).

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295 Results of this study indicate that there were sufficient environmental differences among

296 populations to invoke a population-specific phytochemical response. Causes of such variations

297 can be attributed either to the genetic character of source populations, growing season,

298 developmental stages of plants, light intensity, altitude of plant origin or microclimatic condition

299 of the area (Jugran et al. 2016a). Plant secondary metabolite accumulation is usually greater at

300 higher altitudes (Spitaler et al. 2008, Rawat et al. 2011, Jugran et al. 2013) where plants are

301 exposed to more extreme environmental stresses, such as ultraviolet light and temperature

302 (Rainwater et al. 1996). Increasing light intensity in glass house is reported to increase total

303 phenols, flavonoids and antioxidant activities in Zingiber officinale (Ghasemzadeh et al. 2010).

304 Latitude of the plant origin is found to influence the tannin and glycyrrhizin content in

305 Glycyrrhiza glabra (Oloumi and Hassibi 2011). Growth stages in Hedycium spicatum were

306 found to influence phenolic and antioxidant activities (Rawat et al. 2011). Phytochemical

307 diversity in Valeriana jatamansi was found to vary across altitude and among different habitat

308 (Jugran et al. 2016a). Moreover, several other Himalayans medicinal plants such as Habenaria

309 intermedia, Roscoea procera, Valeriana jatamansi (Rawat et al. 2016) and Paeonia emodi

310 (Jugran et al. 2016b) and many more have shown considerable variations in the phytochemical

311 diversity among different environmental gradient. This study did not find a relationship with

312 altitude when regional differences were considered, but found significant variation among

313 arboreal communities and aspects within regions.

314 The present study demonstrated that in T. govanianum above-ground morphology masks

315 considerable variations in below-ground morphology and phytochemistry. It is difficult to predict

316 whether the observed variations are due to genetic adaptation or phenotypic plasticity. Although

317 the species is limited to a very specific habitat class, it does appear that the observed variations

318 can provoke a functional response to changing environmental conditions for adaptation.

319

320 Acknowledgements

321 We are thankful to the Head of the Department of Botany, D.S.B. Campus, Kumaun University,

322 Nainital and the Director of G.B. Pant National Institute of Himalayan Environment, Kosi-

323 Katarmal, Almora for providing the necessary facilities to complete this work. This work was

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324 financially supported by the University Grants Commission, New Delhi, India under the UGC-

325 BSR scheme to H.K. Chauhan (Grant No. F.7-318/2011 BSR).

326

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505 Figure legends

506 Figure 1 Location map of selected sites {Figure was created using OpenStreetMap, 507 (https://www.openstreetmap.org/about), accessed July 2021}

508 Figure 2 Influence of region on populations of Trillium govanianum in the Indian Himalayas

509 Figure 3 Influence of arboreal community on Trillium govanianum in the Indian Himalayas

510 Figure 4 Influence of aspect on Trillium govanianum in the Indian Himalayas

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https://www.openstreetmap.org/about

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Figure 1. Location map of selected sites {Figure was created using OpenStreetMap, (https://www.openstreetmap.org/about), accessed July 2021}

50x36mm (300 x 300 DPI)

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Figure 2. Influence of region on populations of Trillium govanianum in the Indian Himalayas

100x108mm (300 x 300 DPI)

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Figure 3. Influence of arboreal community on Trillium govanianum in the Indian Himalayas

100x108mm (300 x 300 DPI)

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Figure 4. Influence of aspect on Trillium govanianum in the Indian Himalayas

108x110mm (300 x 300 DPI)

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Table 1. Classification of studied Trillium govanianum populations

Region Population Altitude (m above sea level)

Aspect Aspect group

Arboreal community Tree species other than Rhododendron spp.

Devri 2452 NW N facingGaraha Thach 2465 NE N facingPurcha 2550 SW S facingTalai 2585 NW N facingGurku Thach 2623 WNW N facingBasu 2625 SE S facingMiruti Bahal 2648 ESE S facing

Tirthan Valley

Northernlatitude

HimachalPradesh

Kamarat Thach 2655 NW N facing

Mixed species Quercus spp., Abies pindrow, Juglans regia, Cedrus deodara, Picea smithiana, Betula utilis, Juniperus indica, Salix spp.

Martoli Thor 2924 NW N most Qurecus spp., BambusoideaeTaati 3068 W N part Qurecus spp., Betula spp. Base Khalli 3340 NNE N most

Rhododendron dominant

Betula spp.Bhujani 3371 ENE N part

Munsiyari

Southernlatitude

UttarakhandKhaliya Top 3432 ENE N part

Pure Rhododendron None

Tunghnath 1 3250 NW N mostTunghnath 2 3266 WNW N partTunghnath 3 3306 NE N most


Abies spp.Tunghnath

Central latitude

Uttarakhand Tunghnath 4 3319 NE N most Pure Rhododendron None

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Table 2. Influence of region on observations of 17 populations of Trillium govanianum in the Indian Himalayas, using analysis of variance with populations nested within regions. ns denotes P>0.05, ns* denotes 0.05>P> α, where α=0.0013 for the variation source and 0.0012 for pairwise comparisons.

Variation source (P) Region(Mean ± SE) Pairwise comparisons (P)

Variable Region PopulationTirthan Valley Munsiyari Tunghnath

Tir Valley / Muns.

Munsiyari / Tunghnath

Tir Valley / Tunghnath

Population structure1-leaf density (plants m-2) 1.2x10-12 1.3x10-10 4.0 ± 0.1 2.2 ± 0.2 3.1 ± 0.2 1.6x10-12 ns* ns*3-leaf density (plants m-2) 2.1x10-20 ns* 2.9 ± 0.1 2.0 ± 0.2 3.0 ± 0.2 4.7x10-05 3.3x10-04 nsAge ratio ns ns1-leaf frequency (%1m2 plots) 1.7x10-07 ns 83.5 ± 2.5 55.3 ± 4.2 49.0 ± 4.9 1.2x10-05 ns 3.1x10-06

3-leaf frequency (%1m2 plots) 4.3x10-07 ns* 81.9 ± 2.4 57.3 ± 4.1 48.3 ± 4.8 6.0x10-05 ns 3.8x10-06

Shoot morphologyShoot length (mm) 1.2x10-03 ns* 147.3 ± 4.5 119.2 ± 5.7 139.3 ± 6.4 8.3x10-04 ns nsLeaf area (mm2) ns nsFresh biomass (g) ns ns

Root morphologyRoot length (mm) 9.0x10-10 ns 75.9 ± 3.5 101.9 ± 4.5 120.4 ± 5 6.1x10-05 ns* 1.3x10-09

Root number per plant 4.2x10-05 ns 11.7 ± 0.6 14.9 ± 0.8 16.9 ± 0.9 ns* ns 5.8x10-05

Rhizome length (mm) 2.6x10-06 ns 18.4 ± 1.1 27.6 ± 1.3 24.3 ± 1.5 2.5x10-06 ns ns*Rhizome diameter (mm) 1.4x10-04 ns 7.0 ± 0.2 8.7 ± 0.3 8.0 ± 0.3 1.0x10-04 ns nsFresh biomass (g) ns ns

PhytochemistryPhenols (mg / 100g DW) 1.1 x10-12 5.9 x10-08 235.6 ± 4.0 175.4 ± 5.0 167.8 ± 5.6 1.5 x10-10 ns 4.4 x10-11

Flavonoids (mg / 100g DW) 1.6 x10-21 2.2 x10-13 233.6 ± 5.5 438.3 ± 6.9 312.7 ± 7.8 6.7 x10-22 2.4 x10-13 3.1 x10-09

Tannins (mg / 100g DW) 1.8 x10-17 9.4 x10-14 355.9 ± 5.3 422.2 ± 6.7 249.7 ± 7.5 1.6 x10-08 8.6 x10-18 8.0 x10-13

Antioxidants (mM / 100g DW) – ABTS ns 9.1 x10-04

– DPPH 1.8E x10-

104.4 x10-12 2.85 ± 0.01 2.73 ± 0.01 2.79 ± 0.01 1.0 x10-10 1.1 x10-03 1.8 x10-04

– FRAP 7.8E x10-

131.4 x10-13 9.6 ± 0.3 9.9 ± 0.3 4.5 ± 0.4 ns 1.1 x10-11 4.2 x10-12

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Table 3. Influence of arboreal community on observations of 17 populations of Trillium govanianum in the Indian Himalayas, using analysis of variance with populations nested within arboreal community types. ns denotes P>0.05, ns* denotes 0.05>P>0.0013.

Variation source (P) Arboreal community (Mean ± SE) Pairwise comparisons (P)

VariableArboreal

community PopulationMixed species


Pure Rhododendron

Mixed / dominant

Dominant / pure

Mixed / pure

Population structure1-leaf density (plants m-2) 2.1x10-11 3.6x10-12 4.0 ± 0.1 2.7 ± 0.2 2.5 ± 0.2 2.4x10-06 ns 4.4x10-09

3-leaf density (plants m-2) ns* 8.0x10-21

Age ratio ns ns1-leaf frequency (% 1m2 plots) 1.5x10-07 ns 83.5 ± 2.5 52.0 ± 4.6 52.9 ± 4.3 6.7x10-06 ns 4.1x10-06

3-leaf frequency (% 1m2 plots) 4.6x10-07 ns* 81.9 ± 2.4 53.0 ± 4.5 53.7 ± 4.2 1.7x10-05 ns 1.0x10-05

Shoot morphologyShoot length (mm) ns* ns*Leaf area (mm2) ns nsFresh biomass (g) ns* ns

Root morphologyRoot length (mm) 7.4x10-09 ns* 75.9 ± 3.5 109.3 ± 4.5 111.1 ± 5 4.1x10-07 ns 6.5x10-07

Root number per plant 7.7x10-05 ns 11.7 ± 0.6 15.3 ± 0.8 16.4 ± 0.9 ns* ns 2.5x10-04

Rhizome length (mm) 6.6x10-06 ns* 18.4 ± 1.1 25.8 ± 1.3 26.6 ± 1.5 1.5x10-04 ns 8.8x10-05

Rhizome diameter (mm) 2.3x10-04 ns 7.0 ± 0.2 8.6 ± 0.3 8.1 ± 0.3 2.6x10-04 ns ns*Fresh biomass (g) ns* ns

PhytochemistryPhenols (mg / 100g DW) 6.6 x10-13 9.4 x10-08 235.6 ± 4.0 164.0 ± 5.0 182.1 ± 5.6 1.6 x10-12 ns 1.3 x10-08

Flavonoids (mg / 100g DW) 7.2 x10-20 2.4 x10-15 233.6 ± 5.5 356.6 ± 6.9 414.9 ± 7.8 4.2 x10-15 8.7 x10-06 3.0 x10-19

Tannins (mg / 100g DW) 7.6 x10-08 2.8 x10-17 355.9 ± 5.3 312.8 ± 6.7 386.4 ± 7.5 4.8 x10-05 5.8 x10-08 ns*Antioxidants (mM / 100g DW) – ABTS 4.4 x10-04 ns* 41.7 ± 1.8 32.1 ± 2.3 46.4 ± 2.5 ns* 5.1 x10-04 ns – DPPH 3.3 x10-10 3.4 x10-12 2.85 ± 0.01 2.74 ± 0.01 2.79 ± 0.01 2.4 x10-10 ns* 6.1 x10-05

– FRAP 6.0 x10-13 1.6 x10-13 9.6 ± 0.3 5.1 ± 0.3 10.5 ± 0.4 1.4 x10-11 7.9 x10-12 ns

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Table 4. Influence of aspect on observations of 17 populations of Trillium govanianum in the Indian Himalayas, using analysis of variance with populations nested within aspect groups. ns denotes P>0.05, ns* denotes 0.05>P> α, where α=0.0013 for the variation source and 0.0017 for pairwise comparisons.

Variation source (P) Aspect groups(Mean ± SE) Pairwise comparisons (P)Low altitude High altitude

VariableAspect group Population S facing N facing N part N most

Low : High altitude

S : N facing

N part : N most

Population structure1-leaf density (plants m-2) 4.3 x10-12 9.9 x10-11 4.48 ± 0.20 3.70 ± 0.16 2.39 ± 0.25 2.75 ± 0.21 4.9 x10-04 ns* ns3-leaf density (plants m-2) ns* 6.8 x10-21

Age ratio ns ns1-leaf frequency (% 1m2 plots) 1.6 x10-07 ns 86.0 ± 4.0 82 ± 3.0 62 ± 5.0 45 ± 4.0 ns* ns ns3-leaf frequency (% 1m2 plots) 2.4 x10-07 ns* 86.0 ± 4.0 80 ± 3.0 65 ± 5.0 44 ± 4.0 ns* ns ns*

Shoot morphologyShoot length (mm) ns ns*Leaf area (mm2) ns nsFresh biomass (g) ns ns

Root morphologyRoot length (mm) 1.6 x10-08 ns* 75.3 ± 5.6 70.6 ± 5.1 105.8 ± 5.9 111.9 ± 4.3 5.6 x10-04 ns nsRoot number per plant ns* nsRhizome length (mm) 7.8 x10-04 ns 18.1 ± 1.7 18.9 ± 1.6 26.2 ± 1.8 24.9 ± 1.3 ns* ns nsRhizome diameter (mm) ns* nsFresh biomass (g) ns ns

PhytochemistryPhenols (mg / 100g DW) 4.0 x10-13 5.3 x10-07 255.6 ± 6.5 223.6 ± 5.0 186.6 ± 5.6 160.4 ± 5.0 3.2 x10-05 ns* ns*Flavonoids (mg / 100g DW) 2.3 x10-20 2.4 x10-14 183.2 ± 9.0 263.9 ± 6.9 426.4 ± 7.8 347.4 ± 6.9 9.3 x10-10 1.9 x10-07 4.9 x10-08

Tannins (mg / 100g DW) 1.1 x10-12 2.6 x10-16 378.1 ± 8.7 342.6 ± 6.7 411.9 ± 7.5 292.4 ± 6.7 ns* ns* 7.7 x10-13

Antioxidants (mM / 100g DW) – ABTS ns* ns* – DPPH 9.1 x10-12 2.2 x10-11 2.93 ± 0.01 2.81 ± 0.01 2.76 ± 0.01 2.76 ± 0.01 ns* 1.1 x10-07 ns – FRAP 4.5 x10-12 6.6 x10-14 10.8 ± 0.4 8.83 ± 0.34 10.2 ± 0.4 5.31 ± 0.34 ns ns* 1.7 x10-10

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Table 5. Influence of altitude on observations of 17 populations of Trillium govanianum in the Indian Himalayas, using Pearson’s Correlation Coefficient (r) for each region separately and combined. ns denotes P>0.05, ns* denotes 0.05>P> α, where α=0.0013 for all regions, and 0.0009 for within regions.

All regions Tirthan Valley Munsiyari TunghnathVariable P r P r P PPopulation structure

1-leaf density (plants m-2) 2.7 x10-07 -0.17 5.9 x10-07 0.23 ns ns3-leaf density (plants m-2) ns 2.7 x10-12 0.31 ns* ns*Age ratio ns ns ns ns1-leaf frequency (% 1m2 plots) 2.4 x10-06 -0.65 ns ns ns3-leaf frequency (% 1m2 plots) ns* ns* ns* ns

Shoot morphology Shoot length (mm) ns* ns ns nsLeaf area (mm2) ns ns ns* nsFresh biomass (g) ns ns ns ns

Root morphology Root length (mm) 6.4 x10-08 0.55 ns ns nsRoot number per plant 4.1 x10-05 0.43 ns ns nsRhizome length (mm) 9.8 x10-06 0.46 ns ns nsRhizome diameter (mm) ns* ns ns nsFresh biomass (g) ns ns ns ns

Phytochemistry Phenols (mg / 100g DW) 3.8 x10-07 -0.64 ns ns nsFlavonoids (mg / 100g DW) 3.9 x10-06 0.60 ns* ns nsTannins (mg / 100g DW) ns ns ns nsAntioxidants (mM / 100g DW) – ABTS ns ns ns ns – DPPH 1.2 x10-03 -0.44 ns* ns ns – FRAP ns ns ns ns

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