Journal of Threatened Taxa | www.threatenedtaxa.org | 26 March 2026 | 18(3): 28495–28509

ISSN 0974-7907 (Online) | ISSN 0974-7893 (Print)

https://doi.org/10.11609/jott.9730.18.3.28495-28509

#9730 | Received 04 March 2025 | Final received 23 February 2026| Finally accepted 09 March 2026

Diversity and distribution pattern of geometrid moths (Insecta: Lepidoptera: Geometridae) along the altitudinal gradient, Kumaun Himalaya, India

Narendra Singh Lotani ¹ & Chandra Singh Negi ²

^1,2 Ecology & Biodiversity Laboratory, Department of Zoology, Motiram Baburam Government Postgraduate College, Haldwani (Nainital), Uttarakhand 263139, India.

¹ nsleco25@gmail.com, ² csnsacred1@gmail.com (corresponding author)

Abstract: Altitudinal gradients are frequently used to study Lepidoptera diversity. The study site, situated in the Munsiari Subdivision of Pithoragarh District, Kumaun Himalaya, was divided into transects along the altitudinal gradient, each 200 m wide, spanning elevations from 1,200–4,000 m. In each transect, a minimum of five sampling plots were established. Furthermore, the study area was divided into five broad zones based on vegetational cover. Moths were collected using automated light traps between 1900 h and 2300 h. The specimens were identified using the available literature and following standard protocols. Indicator species analysis was carried out as per Dufrêne & Legendre. The present paper deals exclusively with the status and altitudinal distribution pattern of the Geometridae moths. Zone II, lying between 1,800–2,600 m, harboured highest species richness (98 species), as well as abundance (4,686 individuals), while the least species richness was encountered in Zone III. In terms of species diversity across the subfamilies, Ennominae comprised 93 species, followed by Larentiinae (49), Geometrinae (14), Sterrhinae (4), and Desmobathrinae (1). In terms of distribution, 23 species, restricted to just one transect and exhibiting distribution for one month, could be categorised as highly specialized, while two species—Euphyia subangulata and Eustroma melancholicum venipicta (Larentiinae)—exhibiting distribution throughout the altitudinal gradient, along with an additional 23 species (all Ennominae) exhibiting presence across five or more transects, could be defined as generalists. Both categories are considered ‘indicator species.’

Keywords: Alpine, ecotone, environmental factor, habitat, indicator species, light trap, specialists, species richness, transects, western Himalaya.

Editor: Jatishwor Singh Irungbam, Centrum Algatech, Třeboň, Czech Republic. Date of publication: 26 March 2026 (online & print)

Citation: Lotani, N.S. & C.S. Negi (2026). Diversity and distribution pattern of geometrid moths (Insecta: Lepidoptera: Geometridae) along the altitudinal gradient, Kumaun Himalaya, India. Journal of Threatened Taxa 18(3): 28495–28509. https://doi.org/10.11609/jott.9730.18.3.28495-28509

Copyright: © Lotani & Negi 2026. Creative Commons Attribution 4.0 International License. JoTT allows unrestricted use, reproduction, and distribution of this article in any medium by providing adequate credit to the author(s) and the source of publication.

Funding: The research received no external funding.

Competing interests: The authors declare no competing interests.

Author details: Narendra Singh Lotani is a research scholar in the Ecology & Biodiversity Laboratory, M B Government Postgraduate College, pursuing an interest in lepidoptera, more specifically, the habitat ecology of moths. Chandra Singh Negi, PhD, is a professor at the MB Government Postgraduate College, with a wide interest in ecology, conservation biology, and traditional knowledge-based systems, and is an expert on the habitat ecology of the caterpillar mushroom and the Institution of sacred.

Author contributions: Both authors contributed to the study. NSL: Field work, formal analysis of the raw data, review, and manuscript writing (original draft). CSN: Conceptualization, methodology, formal analysis, supervision, and editing of the draft.

Acknowledgements: The authors gratefully acknowledge the principal, MB Government Postgraduate College, Haldwani (Nainital), for extending the infrastructural support. To Pardeep Kumar Sharma, Ms. Priya Bisht, Ms. Ranjana Goswami, and Ms. Divya Rawat, our colleagues in the laboratory, for extending help from time to time. To the residents of Kultham and Dheelam villages for their help with the fieldwork.

Introduction

Moths and butterflies belong to the insect order Lepidoptera, characterized by two pairs of scale-covered wings, and, in most groups, reduced mandibles. Butterflies are primarily day-flying and usually brightly coloured, while most moths are nocturnal and tend to be more cryptically coloured. Currently, approximately 158,000 Lepidoptera species have been reported worldwide; new discoveries are made each year, and the actual total is estimated to range 300,000–400,000 (Kristensen et al. 2007). Even though butterflies are relatively better known than moths, the latter, outnumber the butterflies by at least 10 to one (Hill et al. 2021). Moths are a significant component of terrestrial ecosystems as herbivores and pollinators, and they also play a role in nutrient cycling; therefore, disturbances to their natural habitats, primarily due to anthropogenic activities, affect their population dynamics (Lomov et al. 2006). In fact, on account of their sensitivity towards habitat change, moths have been recently targeted as ‘indicator species’ that reflect upon habitat changes, such as forest fragmentation, land-use patterns, deforestation, and regeneration (Ricketts et al. 2001; Enkhtur et al. 2017). In terms of distribution and habitat preferences, moths exhibit both narrow and wide distributions. Both narrow, highly niche specialized (confined to 200–400 m breadth segments), and widely distributed – the generalists, could act as ecological indicators; for any change in their availability or numbers would relate to habitat change or its quality. The distribution of moths across an altitudinal gradient, thus, provides an opportunity to study the range of their distribution pattern, the diversity – both richness and abundance, and relate these with the above-ground vegetation profile, as well as the anthropogenic disturbance. Moreover, any depletion in numbers, as well as the availability of specialist moths in particular, could be monitored, since moths exhibit ‘assemblages’ that are easy to monitor.

Variation in moth diversity along altitudinal gradients can be an effective way to study the effects of climate change on ecological communities (Kitching et al. 2011). Forested elevational gradients representing sets of adjacent climates are excellent tools for such studies; encompassing, in a small geographical area, a range of environmental factors that shift predictably (Rahbek 2005; Fiedler & Beck 2008; Fischer et al. 2011; Kitching et al. 2011). For example, it is well established that for every 100 m increase in elevation, the temperature decreases by approximately 0.6 °C (Jacobson 2005). Concomitantly, a set of other biotic-abiotic factors, for example, mean annual temperature, precipitation change, and others, too, shift in concert, inclusive of soil physico-chemical properties (Strong et al. 2011), along elevational gradients (Stevens 1992; Kessler et al. 2001; Lomolino 2001; Foster 2010).

Understanding how moth assemblages change along the altitudinal gradient is therefore important for assessing likely future changes in diversity, for example, climate change (Doran et al. 2003). It will also allow us to observe the current distributions of different species, and make predictions about how they would respond to climate change based on their current climatic envelopes, thereby leading us to identify species (indicator species), which would then be used to monitor future range shifts (Kitching & Ashton 2014; Nakamura et al. 2016). Moths are ideal as ‘Indicator species’ for use in climate monitoring, since (i) they are sensitive to environmental variables, and (ii) their herbivorous life histories bind them invariably to larger community-level shifts (Schulze et al. 2001). Other features, like their being easy to sample in large numbers (principally, making use of automated light traps), giving strong statistical power, and their being relatively well known taxonomically (Holloway 1985ab–1997) make them ideal species to monitor climate change.

An elevational change of just 200 m drives significant changes in moth assemblage composition, particularly for forest-inhabiting moths (Ashton et al. 2016); these changes have considerable implications for conservation under climate change scenarios. Because moths, as herbivores, are closely linked to the availability of appropriate larval host plants, this could lead to a mismatch between the upward movement of herbivores and their host plants when host plants respond more slowly and track climatic envelopes (Rehm 2014). To understand how species respond to climate change, we need to generate baseline data on their current distributions. By examining species distributions and investigating how their altitudinal ranges are driven by environmental variables across altitudes, we will be better able to predict how these species may respond to further climate warming.

Many recent studies on altitude-diversity patterns have been conducted in tropical systems, including studies of moths (e.g., Axmacher et al. 2004; Brehm et al. 2007; Beck & Chey 2008; Fiedler et al. 2008; Beck & Kitching 2009). Comparable data regarding methods and studies are conspicuously lacking for the temperate moths. Consequently, little is known about the altitudinal diversity patterns of temperate taxa, and information on the seasonal variation in these patterns is scarce (Summerville & Crist 2003). Also, as concerns India, most studies related to the diversity and distribution of moths along the altitudinal gradient are restricted to tropical or sub-temperate regions (Axmacher et al. 2004; Beck & Chey 2008; Beck & Kitching 2009; Ashton et al. 2016), with an exception (Dey et al. 2015) conducted across four protected areas within the state of Uttarakhand. Further, only one single attempt (Sanyal et al. 2017) has addressed the ‘indicator properties’ of moth assemblages in assessing habitat quality. The present study aims to address this gap. Further, most, if not all, studies on moths are relegated to macromoths, and micromoths, if any, remain mostly unexplored. This fact becomes all the more obvious when it concerns studies in the sub-alpine and alpine zones of the Himalaya, which remain unexplored. However, one positive outcome of such a scenario is that the likelihood of discovering entirely new species or documenting their presence increases, as evidenced by the present study.

Geometrid moths occur in large numbers and have a wide elevational distribution, making them an ideal group for studies along elevational transects (Toko et al. 2023). Their sensitivity to habitat alteration and climate variation, as reflected in their distribution patterns, makes them a valuable bioindicator of environmental change (Scoble 1992; Choi 2006; Ashton et al. 2011; Alonso-Rodrigue et al. 2017; Enkhtur et al. 2020). Approximately 24,000 species of Geometridae have been described worldwide (Brehm et al. 2005). The present study thus examines (i) the diversity of the family Geometridae, and (ii) indicator species vis-à-vis the spatial distribution of each individual species, along the elevational gradient.

Materials & Methods

The study site (Figure 1), situated in Munsiari Subdivision, Pithoragarh District, Kumaun Himalaya, between 30.111^o–30.144^o N and 80.254^o–80.304^o E, extending from base 1,200 m to 4,000 m, was divided along the altitudinal gradient into transects, measuring 200 m in breadth. In each transect, a minimum of five sampling plots were established, spaced at least 20 m apart, ensuring that a light device (UV light source) did not impede the other light device. Light traps were set using a light-sensitive solar-powered lantern. Solar light traps remained an effective tool for insect collection; they are fully automatic, switch on at night, and are absolutely safe to handle. The solar light trap was positioned at a right angle in relation to the direction of movement of the sun during daytime, for charging the battery to a maximum, so that it lasts for the complete duration (4 h) of the insect trap. Since temporal distribution remained one component of the study (though not included in the present manuscript), moth collections, in each transect, were carried out on average between 2–3 days per month, compounding to 10–15 days for the complete duration of the study of five months, annually, and replicated for two years.

The study area was further divided into five zones (I–V) based on vegetational cover and other features, such as interspersed habitat types and anthropogenic disturbance. Moths were collected using automated light traps, between 1900 h and 2300 h. The collected specimens were then pinned and partially spread according to standard techniques (Krogmann et al. 2010). The specimens were sorted into morphospecies and identified using the available literature, following standard protocols (Haruta 2000; Scoble & Hausmann 2007). The identification of moth specimens was based entirely on morphological features, following the BOLD system of taxonomy for moths of India, Nepal, and Borneo (Ratnasingham & Hebert 2007). The identified species were further classified into families, subfamilies, and genera.

Characteristic moth species restricted to specific transect/s were identified across the altitudinal gradient using the indicator species analysis (Dufrêne & Legendre 1997). For the calculation of the indicator value, abundance figures of each species confined either to a single or two belt transects were selected (since species spread out across more than two transects had a p-value greater than 0.01). Species with indicator values greater than 70% produced from ISA were regarded as good indicators for each habitat, while those with the Indicator Value lying between 50–70 % were regarded as detector species, i.e., as a detector of a change in habitat (McGeoch et al. 2002). At each level of cluster (species group), indicator values (Ind. Val.) and their associated p-values for all moth species were calculated. We selected species with an indicator value greater than 70%. The Bray-Curtis similarity index was calculated as per Bray & Curtis (1957). Lastly, the data analysis was conducted using Past 4.17 and Excel Stat. The correlation coefficient between species richness and the altitudinal gradient was calculated using Pearson’s (1895) method.

While Zone I can be classified as sub-temperate or warm-temperate, the subsequent zones are classified as temperate or cool-temperate, sub-alpine, timberline, and alpine, respectively. Because the altitudinal range was extensive, changes in vegetation profiles across the altitudinal gradient were also observed, as were ecotones. The dominant plant species were Quercus spp., Rhododendron spp., Alnus nepalensis, Neolitsea umbrosa, and Acer; the was characterized by Betula utilis, while the alpine meadow was dominated by herbaceous species.

Results

A total of five subfamilies, representing 99 genera, and 161 species were collected. The maximum species richness (98) and abundance (4,686 ind.) were encountered in zone II (1,800–2,600 m), followed by zone I (68 species and abundance 2,586 ind.) (Table 1). Species abundance declined with altitude; it increased rapidly in zone V (Table 1). The subfamily Ennominae exhibits the highest species richness, represented by 93 species (58% of the total, Figure 2), with the highest diversity encountered in the mid-altitudinal zone (1,800–2,400 m), and with transects at 2,200–2,400 m exhibiting the maximum diversity (58 species), followed by steady decline with an increase in altitude (Figure 3). The most dominant genera include Arichanna (7 spp.), followed by Cleora (4 spp.), Opisthograptis (4 spp.), and Psyra (4 spp.). The genera, Abraxas, Alcis, Biston, Dalima, Medasina, and Ourapterix, are represented by three species each. Ennominae is followed by Larentiinae (49 species, and 31.05% dominance, Figure 2); exhibiting dominancy in the high-altitudinal zone (2,800–4,000m, Figure 3). Important genera include Euphyia (6 spp.), Photoscotosia (5 spp.), Entipheria (5 spp.), Eustroma (4 spp.), and Eupithecia (2 spp.). The subfamily Geometrinae did not exhibit a consistent altitudinal gradient pattern, although it comprises 14 species (9% dominance, Figure 2) and is restricted to 2,800 m in distribution (Figure 3). Pachyodes was the dominant genus, with three species. The subfamily Sterrhinae was confined to the lower and mid-altitudinal zones (1,200–2,600 m) and comprised four species (Genera 3, Figure 2). Desmobathrinae was represented by a single species, distributed across three transects (2,000–2,600 m, Figure 3).

The Bray-Curtis Similarity Index (Bray & Curtis 1957) between the distribution pattern and species richness, along the altitudinal gradient, shows that the subfamily Ennominae exhibits maximum diversity at 1,600–2,400 m, and is represented throughout the altitudinal gradient; while Larentiinae exhibits maximum diversity at 3,400–3,600 m, as well as reciprocates Ennominae in its wide distribution, while the rest of the three subfamilies- Desmobathrinae, Geometrinae, and Sterrhinae, are restricted in distribution (Figure 4). Pearson correlation analysis revealed a significant negative relationship between altitude and the species richness of Ennominae (r = −0.597, p = 0.024), Geometrinae (r = −0.545, p = 0.044), and Sterrhinae (r = −0.684, p = 0.007). In contrast, Larentiinae exhibits a strong positive correlation with altitude (r = 0.730, p = 0.003), indicating an increase in species richness with elevation (Brehm et al. 2007). Desmobathrinae show no significant correlation with altitude (r = 0.290, p = 0.320), likely due to their extremely low and rare occurrence across the altitudinal gradient (Table 3).

Across transects and the altitudinal gradient, many species exhibit restricted distributions or highly specialized niches. These include 17 species restricted to just one transect, 37 species restricted to just two transects, totalling 54 species, which could be categorised as highly specialized, while two species—Euphyia subangulata and Eustroma melancolicum venipicta (Larentiinae)—exhibited distribution throughout the altitudinal gradient. However, in terms of relative distribution, the subfamily Ennominae, represented by 23 species and present across five or more transects, outperforms other families, principally Larentiinae. This is because these species are mostly polyphagous and hence relatively more widely distributed (Lindström et al. 1994).

The indicator values range 53.33–100 %. However, the indicator value of a species was compounded with the p-value, which in the present study, should be less than 0.01. Of the 23 species analyzed, 13 exhibited high indicator values (70–100 %) and were therefore categorized as good indicator species, indicating a strong association with specific habitat conditions. The remaining 10 species, exhibiting moderate indicator values of 50–70 %, were classified as detector or early-warning species (Table 4). Both these categories of indicator species, however, reflect upon the habitat changes, habitat modification, environmental stress, or successional shifts (Bandyopadhyay 2021).

The highest number of indicator species were recorded from Ennominae subfamily (14 spp.), followed by Larentiinae (7 spp.), Sterrhinae (1 sp.), and Geometrinae (1 sp.) (Table 4). In terms of distribution profiles, a significant number of species (5) were confined to transects, ranging 2,200–2,400 m, followed by four species confined to the transects lying at 1,800–2,000 m; in three transects (1,200–1,400 m, 2,400–2,600 m, and 3,600–3,800 m) each have three spp.; in transects at altitudes of 1,600–1,800 m and 2,600–2,800 m two spp. were recorded from each; and the transect 2,800–3,000 m contain only a single indicator species (Table 4). In terms of the distribution of representative indicator species across the families Geometridae exhibiting species distribution across the whole transect area, from 1,200 m at the bottom to 4,000 m, characteristically is marked by the absence of any indicator species between the six transects lying between 1,400–1,600 m, 2,000–2,200 m, 3,000–3,600 m, and 3,800–4,000 m (Table 4).

Several species (Images 1–7) are reported for the first time from Uttarakhand, most of which belong to the subfamily Ennominae. These include- Chiasmia cymatodes Wehrli, 1932, Cleora alienaria Walker, 1860, Dalima apicata Moore, 1868, Harutalcis vialis Moore, 1888, and Micronidia simpliciata Moore, 1868; while two species- Agnibesa pictaria brevibasis Prout, 1938 and Physetobasis dentifascia Hampson, 1895, belong to the Larentiinae. Of greater importance are the two species, Euclidiodes meridionalis Wallengren, 1860, and Hypochrosis amaurospila Yazaki, 1995 (Ennominae, Images 8 & 9), reported for the first time from the country.

Discussion

Changes in subfamily composition of geometrid moths along elevational transects show different patterns of distribution (Brehm & Fiedler 2003). The maximum diversity encountered in zones I and II (altitude 1,200–2,600 m), reflects the findings of Brehm et al. (2003). Also, the finding that Ennominae accounts for the highest proportions at low elevations (1,200–2,800 m), while Larentiinae dominates at higher elevations (2,800–4,000 m), is consistent with Brehm & Fiedler’s (2003) findings in the Ecuadorian Andes.

The declining trend in species diversity, along the altitudinal gradient, could be ascribed to open patches and anthropogenic disturbance, principally in zone III, while the other factors could be declining temperature (21.19 ± 0.26 to 11.69 ± 0.95) and concomitant increase in humidity (63.81 ± 1.12 to 78.02 ± 0.75), with altitude (Table 1). The subfamily Ennominae exhibits a strong positive correlation with ambient temperature (r = 0.61) and a negative correlation with humidity (r = -0.57). In contrast, Larentiinae exhibits a strong negative correlation with temperature (r = -0.78), but a strong positive correlation with humidity (r = 0.74). This contrasts with the findings of Colwell & Lees (2000) and Colwell et al. (2004), which indicate that Ennominae exhibits a positive relationship with both humidity and temperature. With respect to Larentiinae, our findings further support those of Colwell & Lees (2000) and Colwell et al. (2004), namely that species diversity within Larentiinae is positively correlated with humidity.

Overall, for Geometridae, a positive correlation with temperature (r = 0.35) and a negative correlation with humidity (r = -0.32) were observed. It would thus be safe to conclude that changes in species diversity, along the altitudinal gradient, are influenced principally by the vegetation cover—tree species as host plants for Ennominae, and subsequently, herbaceous species in the case of Larentiinae. This feature is exemplified by a positive correlation (r = 0.59) between Ennominae and tree diversity, and a negative correlation (r = -0.74) between Larentiinae and tree diversity. The latter exhibit increased diversity with decreased forest cover and increased herbaceous diversity, as also indicated by their distribution pattern (Figure 3).

The marked increase in species richness in zone 2 relative to zone 1 could be attributed to the ecotonal effect between forest cover and species diversity. In zone 1 the ecotonal effect is between forest cover and agricultural patches. This ecotone effect on species diversity across zones III and IV is presumably offset by anthropogenic disturbance, primarily tree lopping and grass removal. On the other hand, the marked increase in species abundance in the alpine zone could be attributed to greater host plant diversity.

Various biotic and abiotic factors shape the diversity and distribution of Geometrid moths, governing species assemblages along elevational and vegetational gradients (Webb et al. 2002; Graham et al. 2009). One of the major factors determining the distribution pattern of moths is the availability of larval host plants. This is especially true for highly specialized species, as exemplified by 54 species restricted to one or two transects (Brehm et al. 2013). At the same time, 32 species, mostly belonging to Ennominae (23 species), exhibiting relatively wider distribution (more than 5 transects, which equals a significant distance of 1 km altitudinally), could be defined as ‘polyphagous’ and ‘generalists.’

The relative greater species richness as well as abundance of moths, predominantly belonging to the subfamily Larentiinae, in the alpine (zone V), compared to immediate sub-alpine zones III and IV, could be ascribed to the fact that species occupying higher elevations have a larger range of tolerances (Brehm et al. 2007), and possess physiological characteristics to comply with the cooler temperatures and affiliation with the host plants that have colonized the upper areas (Brehm et al. 2013). It could be presumed that the Larentiinae moths are better suited to cooler environments than the members of other subfamilies, especially Sterrhinae and Geometrinae (Brehm et al. 2013). The physiological properties, which allow moths of this subfamily to be unusually tolerant of unfavourable conditions, however, remain unknown (Brehm & Fiedler 2003). Furthermore, Larentiinae moths, owing to their relatively weaker body structure compared with other subfamilies, are weak flyers, which might benefit them in predator-free environments (Brehm & Fiedler 2003). Moderate host-plant specificity, as exhibited primarily by Ennominae, coupled with adaptability to cooler temperatures, as exhibited by Larentiinae, broadly describes patterns in species distribution across the altitudinal gradient (Brehm et al. 2013).

The indicator species were confined to a single transect, i.e., within an altitudinal breadth of just 200 m, which makes them not just highly specialized species (in terms of distribution), but more importantly, their niche specificity, relegated to biotic (mostly) and abiotic factors, would necessitate their greater monitoring. Any degradation of the habitat would invariably result in population decline and the loss of these species.

Table 1. A brief statement of the five different zones, and their habitat description.

Altitudinal zone	Altitude (m)	Species	Species abundance	Temperature (°C)	Humidity (%)	Habitat description
Zone- I (warm temperate forest)	1200–1800	68	2586	21.19 ± 0.26	63.81 ± 1.12	Mixed forest, dominated by Engelhardtia spicata Lesch. ex-Blume and Quercus leucotrichophora A.Camus, with interspersed Rhus punjabensis. J.L.Stewart ex Brandis; and characterized by riverine ecosystem on its lower end, and interspersed grass-dominant patches.
Zone- II (Cool temperate forest)	1800–2600	98	4686	19.99 ± 0.19	67.22 ± 0.90	Mixed forest, dominated by Quercus leucotrichophora A. Camus and Rhododendron arboreum Sm., with interspersed Alnus nepalensis D.Don, Neolitsea umbrosa (Nees) Gamble., Acer pseudoplatanus L., and Q. semecarpifolia Sm. towards the upper reaches. The forest is marked by interspersed grass habitats and agricultural land
Zone- III (Timberline Forest)	2600–3000	35	1098	18.08 ± 0.27	70.33 ± 0.25	Mixed forest, dominated by Q. semecarpifolia and R. arboreum Sm., and further marked by R. barbatum. and Acer acuminatum Wall. ex D.Don, towards upper reaches. This zone is disturbed, characterized by lopping and removal of grass cover.
Zone- IV (Sub-alpine forest)	3000–3400	41	606	15.70 ± 0.85	72.81 ± 0.27	Ecotone, marked out by treeline and alpine meadow. The treeline is dominated by Acer acuminatum Wall. ex D.Don., R. barbatum, R. campanulatum D.Don. The tree line is marked by a steep slope and is dominated by grass cover
Zone- V (Alpine meadow)	3400–4000	46	1118	11.69 ± 0.95	78.02 ± 0.75	Alpine meadow, characterized by herbaceous vegetation, with few individuals of R. campanulatum.

Table 2. Distribution profile of individual species along the altitudinal gradient.

	Species	Distribution of species across the transects*
		1	2	3	4	5	6	7	8	9	10	11	12	13	14
Subfamily Desmobathrinae (01)
1	Ozola sp.
Subfamily Ennominae (93)
2	Abaciscus tristis Butler, 1889
3	Abraxas permutans Wehrli, 1931
4	Abraxas praepiperata Wehrli, 1935
5	Abraxas sp.
6	Alcis paraclarata Sato, 1993
7	Alcis praevariegata Prout, 1929
8	Alcis variegata Moore, 1888
9	Anonychia grisea Butler, 1883
10	Anonychia lativitta Moore, 1888
11	Arichanna furcifera Moore, 1888
12	Arichanna flavinigra Hampson, 1907
13	Arichanna interplagata Guenee, 1857
14	Arichanna sparsa Butler, 1890
15	Arichanna tramesata Moore, 1867
16	Arichanna sp. 1
17	Arichanna sp. 2
18	Blepharoctenucha virescens Butler, 1880
19	Biston bengaliaria Guenee, 1858
20	Biston falcata Warren, 1893
21	Biston sionitibetica Warren, 1941
22	Cabera quadrifasciaria Packard, 1873
23	Cassyma deletaria Moore, 1888
24	Chiasmia cymatodes Wehrli, 1932
25	Chiasmia sp.
26	Chorodna vulpinaria Moore, 1867
27	Cleora alienaria Walker, 1860
28	Cleora fraternal Moore, 1888
29	Cleora sp. 1
30	Cleora sp. 2
31	Corymica pryeri Butler, 1878
32	Corymica spatiosa Prout, 1925
33	Dalima apicata Moore, 1868
34	Dalima schistacearia Moore, 1868
35	Dalima truncataria Moore, 1868
36	Deinotrichia scotosiaria Warren, 1893
37	Euclidiodes meridionalis Wallengren, 1860
38	Epigynopteryx sp.
39	Erebabraxas metachromata Walker, 1862
40	Erebomorpha fulgurita Walker, 1860
41	Eutoea heteroneurata Guenee, 1858
42	Fascellina plagiata Walker, 1866
43	Gareus sp.
44	Harutalcis vialis Moore, 1888
45	Hirasa scripturaria Walker, 1866
46	Hyalinetta circumflexa Kollar, 1848
47	Hypephyra cyanargentea Wehrli, 1925
48	Hypochrosis amaurospila Yazaki, 1995
49	Lassaba albidaria Walker, 1866
50	Lomographa vestaliata Guenee, 1857
51	Loxaspilates hastigera Butler, 1889
52	Luxiaria amasa Butler, 1878
53	Medasina albidaria Walker, 1866
54	Medasina combustaria Walker, 1866
55	Medasina sp.
56	Micronidia simpliciata Moore, 1868
57	Mimomiza cruentaria Moore, 1867
58	Menophra nigrifasciata Hampson, 1891
59	Menophra sp.
60	Odontopera kanchia Moore, 1883
61	Odontopera sp.
62	Ophthalmitis cordularia Swinhoe, 1893
63	Opisthograptis luteolata L., 1758
64	Opisthograptis tridentifera Moore, 1888
65	Opisthograptis rumiformis Hampson, 1902
66	Opisthograptis sulphurea Butler, 1880
67	Orthofodonia sp. 1
68	Orthofodonia sp. 2
69	Ourapteryx clara Butler, 1880
70	Ourapteryx consociata Inoue, 1993
71	Ourapteryx sambucaria L. 1758
72	Oxymacaria penumbrata Warren, 1896
73	Paradarisa consonaria Hübner, 1799
74	Paraleptomiza bilinearia Leech, 1897
75	Parectropis subflava Bastelberger, 1909
76	Percnia belluaria Guenee, 1858
77	Percnia foraria Guenee, 1858
78	Plagodis inustaria Moore, 1868
79	Plutodes costatus Butler, 1886
80	Pseudomiza cruentaria Moore, 1867
81	Pseudopanthera himalayica Kollar, 1848
82	Psilalcis conspicuata Moore, 1888
83	Psyra angulifera Walker, 1867
84	Psyra cuneata Walker, 1860
85	Psyra falcipennis Yazaki, 1994
86	Psyra spurcataria Walker, 1863
87	Racotis petrosa Butler, 1879
88	Scioglyptis externaria Walker, 1866
89	Sirinopteryx rufivinctata Walker, 1862
90	Stenorumia ablunata Guenee, 1858
91	Stenorumia duplicilinea Hampson, 1895
92	Tanaoctenia haliaria Walker, 1861
93	Thinopteryx crocoptera Kollar, 1844
94	Xandrames albofasciata Moore, 1868
Subfamily Geometrinae (14)
95	Chloroglyphica variegata Butler, 1889
96	Chlororithra fea Butler, 1889
97	Comostola minutata Druce, 1893
98	Dichorda sp.
99	Gelasma inaptaria Walker, 1863
100	Idiochlora approximans Warren, 1897
101	Lotaphora iridiocolor Butler, 1880
102	Orothalassodes falsaria Prout, 1912
103	Pachyodes erionoma Swinhoe, 1893
104	Pachyodes moelleri Warren, 1893
105	Pachyodes ornataria Moore, 1888
106	Pelagodes sp. 1
107	Pelagodes sp. 2
108	Tanaorhinus formosanus Okano, 1959
Subfamily Larentiinae (49)
109	Agnibesa pictaria brevibasis Prout, 1938
110	Amnesicoma bicolor Oberthur, 1893
111	Amnesicoma sp.
112	Baynia odontata Prout, 1910
113	Colostygia sp.
114	Dysstroma sp. 1
115	Dysstroma sp. 2
116	Ecliptopera postpallida Prout, 1940
117	Ecliptopera umbrosaria Motschulsky, 1861
118	Elophos sp.
119	Entephria caesiata Denis & Schiffermuller, 1775
120	Entephria nobiliaria Herrich-Schaffer, 1852
121	Entephria sp. 1
122	Entephria sp. 2
123	Entephria sp. 3
124	Epirrita dilutata Schiffermuller, 1775
125	Epirrita sp.
126	Epirrhoe galiata Denis & Schiffermuller, 1775
127	Eupithecia sp. 1
128	Eupithecia sp. 2
129	Euphyia coangulata Prout, 1914
130	Euphyia setellata Warren, 1893
131	Euphyia subangulata Kollar, 1844
132	Euphyia sp. 1
133	Euphyia sp. 2
134	Euphyia sp. 3
135	Eustroma chalcoptera Hampson, 1895
136	Eustroma melencolicum venipicta Butler, 1878
137	Eustroma sp. 1
138	Eustroma sp. 2
139	Heterothera sororcula Bastelberger, 1909
140	Hydrelia bicolorata Moore, 1868
141	Hysterura multifaria Swinhoe, 1890
142	Laciniodes plurilinearia Moore, 1867
143	Laciniodes unistirpis Butler, 1878
144	Lampropteryx otregiata Metcalf, 1917
145	Larentia sp.
146	Lobogonodes multistriata Butler, 1889
147	Melanthia alaudaria Freyer, 1846
148	Perizoma bicolor Warren, 1893
149	Pseudopolynesia sp.
150	Photoscotosia chlorochrota Hampson, 1902
151	Photoscotosia dejeani Oberthur, 1893
152	Photoscotosia indecora Prout, 1940
153	Photoscotosia insularis Bastelberger, 1909
154	Photoscotosia metachryseis Hampson, 1896
155	Physetobasis dentifascia Hampson, 1895
156	Stamnodes danilovi Erschoff, 1877
157	Stamnodes pauperaria Eversmann, 1877
Subfamily Sterrhinae (04)
158	Organopoda carnearia Walker, 1861
159	Scopula calcarata D.S. Fletcher, 1958
160	Scopula sp.
161	Timandra correspondens Hampson, 1895

*1—1200–1400 m | 2—1400–1600 m | 3—1600–1800 m | 4—1800–2000 m | 5—2000–2200 m | 6—2200–2400 m | 7—2400–2600 m | 8—2600–2800 m | 9—2800–3000 m | 10—3000–3200 m | 11—3200–3400 m | 12—3400–3600 m | 13—3600–3800 m | 14—3800–4000 m.

Table 3. Correlation between species richness and altitudinal gradient.

	Subfamilies	Altitudinal transects														Correlation coefficient
		1	2	3	4	5	6	7	8	9	10	11	12	13	14	r-value	p-value
1	Desmobathrinae	0	0	0	0	1	1	1	0	0	0	0	0	0	0	+0.290	0.320
2	Ennominae	15	25	36	42	44	44	29	19	7	6	11	13	15	10	-0.597	0.024
3	Geometrinae	0	2	9	5	7	4	6	4	0	0	0	0	0	0	-0.545	0.044
4	Larentiinae	8	9	7	11	10	8	7	7	11	15	27	29	21	17	+0.730	0.003
5	Sterrhinae	1	1	1	3	2	1	1	0	0	0	0	0	0	0	-0.684	0.007

*1—1200–1400 m | 2—1400–1600 m | 3—1600–1800 m | 4—1800–2000 m | 5—2000–2200 m | 6—2200–2400 m | 7—2400–2600 m | 8—2600–2800 m | 9—2800–3000 m | 10—3000–3200 m | 11—3200–3400 m | 12—3400–3600 m | 13—3600–3800 m | 14—3800–4000 m.

Table 4. Indicator species of the Geometridae family with their indicator value and significant p-value.

	Subfamily	Species	Indicator value (%)	p-value	Transect
1	Ennominae	Biston sionitibetica Warren, 1941	100	0.0096	2600–2800 m
2	Ennominae	Corymica spatiosa Prout, 1925	100	0.0099	1200–1400 m
3	Ennominae	Euclidiodes meridionalis Wallengren, 1860	100	0.0096	2600–2800 m
4	Ennominae	Odontopera kanchia Moore, 1883	100	0.0098	2400–2600 m
5	Ennominae	Psyra falcipennis Yazaki, 1994	100	0.0096	2200–2400 m
6	Geometrinae	Chlororithra fea Butler, 1889	100	0.0096	2200–2400 m
7	Larentiinae	Stamnodes danilovi Erschoff, 1877	100	0.0096	2400–2600 m
8	Ennominae	Gelasma inaptaria Walker, 1863	83.33	0.0098	1800–2000 m
9	Ennominae	Plagodis inustaria Moore, 1868	82.35	0.0097	2400–2600 m
10	Ennominae	Ophthalmitis cordularia Swinhoe, 1893	73.21	0.0098	1800–2000 m
11	Larentiinae	Perizoma bicolor Warren, 1893	73.21	0.0099	1200–1400 m
12	Larentiinae	Baynia odontata Prout, 1910	71.66	0.0099	3600–3800 m
13	Larentiinae	Eustroma chalcoptera Hampson, 1895	70.23	0.0098	3600–3800 m
14	Ennominae	Tanaoctenia haliaria Walker, 1861	69.34	0.0098	1200–1400 m
15	Ennominae	Cabera quadrifasciaria Packard, 1873	68.18	0.0099	1600–1800 m
16	Larentiinae	Melanthia alaudaria Freyer, 1846	66.67	0.0099	1600–1800 m
17	Ennominae	Hirasa scripturaria Walker, 1866	64.71	0.0098	2200–2400 m
18	Sterrhinae	Scopula sp.	63.36	0.01	2200–2400 m
19	Ennominae	Eutoea heteroneurata Guenee, 1858	61.52	0.0098	2200–2400 m
20	Ennominae	Lomographa vestaliata Guenee, 1857	59.23	0.0096	1800–2000 m
21	Larentiinae	Stamnodes pauperaria Eversmann, 1877	58.06	0.0099	2800–3000 m
22	Larentiinae	Hysterura multifaria Swinhoe, 1889	53.85	0.0096	3600–3800 m
23	Ennominae	Oxymacaria penumbrata Warren, 1896	53.33	0.0096	1800–2000 m

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