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Proceeding Paper

Can Elevation Affect the Distribution of Nymphalidae Butterflies Adjacent to the Protected Regions in the Eastern Himalayan Landscape of West Bengal, India? †

by
Panchali Sengupta
Department of Zoology, West Bengal State University, Berunanpukaria, Malikapur, Barasat 700126, India
†
Presented at the 3rd International Electronic Conference on Diversity: Biodiversity of Animals, Plants and Microorganisms, 15–17 October 2024; Available online: https://sciforum.net/event/IECD2024.
Biol. Life Sci. Forum 2024, 39(1), 6; https://doi.org/10.3390/blsf2024039006
Published: 26 February 2025
(This article belongs to the Proceedings of The 3rd International Electronic Conference on Diversity: Biodiversity of Animals, Plants and Microorganisms)
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Abstract

:
Studies on the influence of latitudinal and elevation gradient on species diversity, richness, and evenness are significant. The present study attempts to document the elevational distribution of nymphalidae butterflies in the surrounding regions outside the jurisdiction of the protected areas of the Eastern Himalayas. Determination of diversity, evenness, richness, dominance, and Gini’s coefficient was undertaken across six elevational belts (≤1500 masl, 1501–2000 masl, 2001–2500 masl, 2501–3000 masl, 3001–3500 masl, ≥3501 masl). The highest values of diversity (H’ = 6.34) and species richness (R1 = 2.497; R2 = 12.01) were represented by a mid-elevation peak at 2501–3000 masl. However, evenness values (E = 1.424; EBG = 0.951; Eq = 0.987) were greatest at ≥3501 masl. Topographical uniqueness coupled with the formation of cloud cover at higher elevation may provide a habitat sustaining montane forest specialist species. Such differences in elevation could probably influence the diversity and distribution of nymphalidae, with immense ecological significance.

1. Introduction

Studies on the distribution patterns of species must include not only an understanding of their specific ecological requirements, but also of their geographical context, which shapes the structure and dynamics of species’ geographical range [1]. The Himalayan region’s varying elevational gradients create alterations in vegetation composition in response to climate change. This, in turn, harbors butterfly communities of varying diversity and species richness. Refs. [2,3,4] have stressed the distribution of butterflies across high-elevation forests of the Himalayas. Ref. [5] opined that butterfly density, diversity, and richness depend largely on the presence of their specific host plants. Interaction with larval host plants appears to be an important aspect of biological diversification, and such interactions are probably determined by nutrient content, plant phenology, and geographical distribution [6,7,8]. Ref. [9] has also found a significant correlation between butterfly species richness and vegetation richness under similar environmental conditions. The usage of several indices could prove beneficial in interpreting the distribution of species, which, in turn, influence biodiversity.
Studies on the occurrence of butterfly species across the Himalayan regions are plentiful [10,11,12,13,14]. Although [15] discussed the elevational distribution of butterfly species, such information with regard to the surroundings of the protected regions of the Eastern Himalayan landscape, West Bengal, is scarce. The present study was designed to investigate the diversity, evenness, dominance, and richness of butterfly species from forest fringes adjacent to the protected regions of West Bengal, India.

2. Materials and Methods

2.1. Study Area

The entire study was undertaken in the surroundings outside the jurisdiction of the protected areas of Singalika National Park (27°07′ N, 88°04′ E), Neora Valley National Park (27°04′ N, 88°42′ E), Gorumara National Park (26.7° N, 88.8° E), and Buxa Tiger Reserve (26°39′0″ N, 89°34′48″ E). The study was conducted between March 2023 and February 2024. The entire study site was divided into six elevational belts (≤1500 masl, 1501–2000 masl, 2001–2500 masl, 2501–3000 masl, 3001–3500 masl, ≥3501 masl) in the forest fringes adjacent to the protected areas across the Eastern Himalayan landscape, West Bengal, India.

2.2. Sampling Protocol

Within each elevational belt, transects (500–800 m) were established at suitable and accessible locations. Within each transect, 12 permanent points were established. At each point, butterfly species within a radius of 5 m were observed for 5 min. This sampling procedure was repeated three times every month during the entire period. Importantly, sampling was undertaken on sunny days between 10:00 h to 14:00 h to ensure the recording of optimal data. The restriction of sampling to sunny days (less than 30% cloud cover) as much as possible was due to the total absence or reduction in butterfly activity on windy or cloudy days [16]. Therefore, it was determined that the sampling of butterfly species only during sunny days would probably not interfere with data compilation and analytics.
Butterflies were identified in the field with the help of illustrated guidebooks [17,18]. However, butterflies that could not be identified in the field were photographed for subsequent identification by a taxonomist.

2.3. Data Analysis

Determination of species diversity (Shannon index “H’”), species evenness (Pielou index “E”, Buzas and Gibson index “EB”, equitability index “Eq”), species richness (Menhinick index “R1”, Margalef index “R2”), species dominance (Berger–Parker dominance “D”), and Gini’s coefficient was performed using the Biodiversity package in R version 2.5-6 software.
The Shannon diversity index (H’) of butterfly species across different elevational belts in the study site is calculated using the formula H’ =Σ pi(ln pi), where pi = ni/N. Here, “ni” is the number of individuals of the ith species, and N = Σ ni [19]. Pielou’s species evenness index (E) is determined using the formula H’/ln(S), where “H’” is the Shannon diversity index and “S” is the total number of species in a study area [19]. The Buzas and Gibson index (EB) is obtained using the formula: e − Σi(ni/Nln(ni/N))/S, where “ni” is the number of species of individuals of the ith species, “N” is the total number of individuals, and “S” is the total number of species in the study area [20]. The equitability index (Eq) is derived using formula −Σi(ni/N − ln(ni/N))/lnN, where “ni” is the number of species of individuals of the ith species and “N” is the total number of individuals in the study area [19]. The Menhinick index of species richness (R1) is ascertained using the formula S/√Σini, where “ni” is the number of species of individuals of the ith species and “S” is the total number of species in the study area. Margalef’s index of species richness (R2) is determined using the formula S − 1/lnN, where “S” is the total number of species and “N” is the total number of individuals across the study area [19]. Berger–Parker dominance index (D) is obtained using the formula Nmax/N, where “Nmax” is the number of individuals in the most abundant species and “N” is the total number of individuals in the study area [21]. The Gini coefficient (G) measures the extent of inequality in the distribution of species across the study site. It measures the level of inequality on a scale from 0 to 1, with higher values close to 1 indicating greater inequality in species distribution [22].

3. Results

A total of 88 species of nymphalidae butterflies were recorded across six elevational belts in the study area. Importantly, 2001–2500 masl harbored a maximum number of individuals (1462) and maximum number of species (87). In contrast, the minimum number of individuals (401) and minimum number of species (45) were encountered ≥3501 masl (Table 1).
The highest species diversity (H’ = 6.34) and species richness values (R1 = 2.497; R2 = 12.01) were observed at 2501–2500 masl. However, the lowest species diversity (H’ = 5.42) and species richness values (R1 = 2.247; R2 = 7.341) were noted at ≥3501 masl. The formation of a mid-elevation peak in species diversity and species richness was the characteristic feature of this study (Figure 1 and Figure 2).
Evenness in species distribution was observed to be highest at ≥3501 masl (E = 1.424; EB = 0.952; Eq = 0.987). On the contrary, species evenness was reported to be lowest at ≤1500 masl (E = 1.402; EB = 0.892; Eq = 0.972) (Table 2).
Significantly, butterfly species were most dominant at ≤1500 masl (D = 0.047) (Table 2). Additionally, ≤1500 masl also represented the greatest inequality in species distribution (G = 0.264). However, ≥3501 masl had a highly homogenous species distribution, with the lowest “G” values (0.153) (Table 2).

4. Discussion

Heterogeneous environmental conditions with fluctuating floristic composition and structure influence the distribution of butterflies in a non-random manner. Significantly, in a world witnessing constant change, climatic variations can be studied rather effectively across elevational gradients as compared to latitude, thereby influencing the sustenance of montane communities [23]. Any elevational changes are known to positively or negatively alter the functioning of an insect system [24]. Significantly, investigation of the changing trends of species diversity, richness, evenness, and dominance across elevational gradients could prove beneficial for biodiversity studies.
Measurements of diversity, richness, evenness, and dominance are traditionally recognized as the four pillars determining community structure. The selection of a specific index is essential in assessing the habitat heterogeneity in a forest ecosystem. Further, in order to achieve sustainability in forest management during ongoing climate change, standardization of such indices would be helpful [22]. The most popular tool for quantifying species diversity, the Shannon index combines two aspects of diversity: the number of species and the abundance of species [25]. Although it is better suited for devising classical forest inventory [26], the Gini coefficient measures the degree of inequality in the distribution of species [22]. Species evenness reflects the distribution of species, with lesser values of species evenness denoting greater rarity in species distribution. Buzas and Gibson’s measure of evenness is used to demonstrate the concept of species dispersion in the log series [20]. Thus, with an increase in the number of individuals and the number of species, for a log series distribution, Pielou’s evenness (E) and Buzas–Gibson (EBG) values decrease [20]. Importantly, communities dominated by a single species possessing lower evenness yields reduced productivity, with less stability [27]. Thus, dominance can be considered to be property of individual species, with dominant species in a community possessing a greater dominance index against subordinate species assigned with lower (negative) values [28]. Dominance thereby highlights the effect of diversity on community stability and ecosystem function [29]. The Berger–Parker dominance index is probably the most effective tool recognized for monitoring biodiversity. In case of any linearly distributed population, the fraction of total sampled individuals denoted by the most abundant species is known as Berger–Parker index [21]. Widely studied indices of species richness (Menhinick index and Margalef index) show greater ability to differentiate between ecosystems [19].
The highest species dominance observed in this study at the lowest elevation belt (≤1500 masl) could probably be associated with the abundance of resources (both biotic and abiotic) for tropical species. Thermal energy is crucial for basic physiology, affecting feeding requirements by influencing water availability in dietary resources (i.e., nectar, mud puddles, and fruit juices) [18,30]. Greater availability of resources could be linked to larger inequality in the distribution of butterflies, leading to higher values of Gini’s coefficient at ≤1500 masl in this study. On the contrary, the lowest value of Gini’s coefficient at higher elevation (≥3501 masl) could probably be indicative of the least inequality or greater homogeneity in species distribution. This could probably be linked to the highest evenness indices (E, EBG, and Eq) at ≥3501 masl observed during the present investigation.
The Himalayan region creates an ecologically unique spectrum of environmental conditions, in turn supporting varied climatic gradients across elevational belts [31,32]. A unimodal pattern of species distribution (mid-elevation peak) along elevational gradients has been observed among differing insect groups [33,34,35,36]. A hump-shaped pattern of species representation across varying elevation bands has been discussed for lepidopterans [37,38,39].
The first ever attempt to examine the elevational-range-based distribution of butterflies in the Eastern Himalayas using Rapoport’s rule has been presented by [40]. The present study also shows a hump-shaped pattern in species diversity and richness, with a peak at 2501–3000 masl. Larger-range species were considered to overlap in the middle of the geographical domain, perhaps leading to the creation of the distinct mid-elevation peak in diversity and richness also observed by [41]. Refs. [42,43] have witnessed a similar pattern in the distribution of species on the basis of geographical constraints. Climate change is associated with an upward shift in the community elevation score in butterfly communities [44,45]. Loss of higher-elevation species in the lowland coupled with the range expansion of lowland species into mid-elevation bands perhaps contributed to the increase in species richness at intermediate elevation [46].
Climate has a significant impact on butterfly distribution. Temperature decreases with increasing elevation, whereas moisture availability shows a positive trend. These are the two important factors determining butterfly biology, as well as host plant growth and survival. However, these two factors could be considered to be highest at intermediate elevation, in turn leading to peak in-species diversity and richness at intermediate elevation, which has been shown in this study as well as previous studies [47]. Additionally, actual evapotranspiration (AET) strongly dictates butterfly distribution [48]. AET is reported to decline strongly at higher elevation [49], probably leading to the decrease in species richness at higher elevation seen in this study. Species belonging to such a stressful habitat are recognized for devising different life history strategies for survival. Ref. [50] reported a decline in diet breadth among temperate butterflies colonizing higher elevations. With the highest-elevation species sharing close affinity with temperate zone inhabitants in the study, the reduction in distribution, diversity, and richness in this zone (≥3501 masl) could be due to a lower diet breadth among nymphalidae. Decreased butterfly diversity at higher elevation might be associated with environmental factors such as reduced temperature and precipitation [32,48,51] and lower vegetation richness [9,52]. Harsh weather conditions, especially snow cover in the montane environment, also restrict the distribution of species [53,54]. Significantly, the occurrence of Ypthima nareda, Y. sakra, Aulocera swaha, and Callerebia scanda at the highest elevations (3001–3500 masl and ≥3501 masl), probably with their associates (i.e., Ergrostis pilosa, Imperata cylindrica, Poa annua, and Digitaria ciliata, respectively), illustrates strict monophagy. Extreme climatic conditions could perhaps affect the occurrence of plant species, in turn restricting their distribution or leading to their extinction. Arundinaria maling and A. aristata, with localized distribution at this elevation, could also interfere with the occurrence of Lethe verma, L. latiaris, L. scanda, L. serbonis, and L. insana. The highly specific relationship of Araschnia with Urtica probably justifies the restricted distribution of such species in montane environments.
Such interplay between rainfall patterns, temperature variation, and climatic conditions profoundly impact the vegetation types across the study area. Forest types ranging from lower-elevation tropical (moist to dry deciduous, semi-evergreen) to sub-tropical (broad-leaved hill-pine forest), leading to wet temperate forests along with the virgin forest tracts of Rhododendron, Magnolia, and Machilus at the highest elevation [55], help in shaping the community structure, contributing to the productivity and resilience of this vital ecosystem. Functionally, the Himalayan forest ecosystem shares more affinities with tropical than temperate forests. The Himalayas are characterized by trees reaching their peak physiological activities during autumn, when soil moisture is quite high owing to monsoonal precipitation, which is characterized by sunny days with milder temperature [56].

5. Conclusions

Designing similar studies for other areas adjoining the protected areas of the Himalayan landscape could probably be insightful. Importantly, the surrounding regions of protected areas represent disturbed or moderately disturbed habitats with higher levels of biodiversity [57]. In accordance with the intermediate disturbance hypothesis (IDH), which posits a unimodal relationship between distribution and diversity [58], future investigations need to be conducted regarding butterfly assemblages in such regions of ecological significance.

Funding

This research received no external funding.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data are unavailable.

Acknowledgments

The author is highly grateful to Narayan Ghorai for his valuable suggestions and cooperation during the study. The constant support and encouragement of the faculty members of the Department of Zoology, West Bengal State University, is also acknowledged.

Conflicts of Interest

The author declares no conflicts of interest.

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Figure 1. Species diversity values of nymphalidae across elevational gradients.
Figure 1. Species diversity values of nymphalidae across elevational gradients.
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Figure 2. Species richness values of nymphalidae across elevational gradients.
Figure 2. Species richness values of nymphalidae across elevational gradients.
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Table 1. Distribution of nymphalidae butterflies across elevational gradients.
Table 1. Distribution of nymphalidae butterflies across elevational gradients.
Butterfly Species Elevational Distribution (masl)
≤15001501–20002001–25002501–30003001–3500≥3501
Subfamily: Danainae
Tirumala limniace (Cramer)		++++++++---
Tirumala septentrionis (Butler)++++++++---
Danaus genutia (Cramer)-++++--
Danaus chrysippus (Linnaeus)+++++++++++++++++
Parantica melaneus (Cramer)++++++-
Parantica aglea (Stoll)+++++-
Euploea sylvester (Fabricius)-++++-
Euploea core (Cramer)+++++++++++++++
Subfamily: Charaxinae
Polyura athamas (Drury)		+++++--
Polyura eudamippus (Doubleday)++++--
Charaxes bernardus (Fabricius)++++--
Charaxes marmax Westwood++++--
Charaxes solon (Fabricius)++++--
Melanitis leda (Linnaeus)++++++--
Melanitis phedima (Cramer)-++++-
Melanitis zitenius (Herbst)++++--
Mycalesis perseus (Fabricius)++++--
Mycalesis mineus (Linnaeus)++++--
Orsotrioena medus (Fabricius)+++++-
Ypthima baldus
(Fabricius)		+++++-
Ypthima nareda (Kollar)+++++++
Ypthima sakra Moore-+++++++
Aulocera swaha (Kollar)-++++++
Callerebia ananda (Moore)--+++-
Callerebia scanda (Kollar)--++++
Neope pulaha (Moore)--++++
Neope yama (Moore)-++++-
Zophoessa jalaurida
(De Niceville)		--++++
Lethe goalpara (Moore)-++++++
Lethe nicetas (Hewitson)--+++-
Lethe verma (Kollar)-+++++
Lethe latiaris Hewitson++++++
Lethe scanda (Moore) ++++++
Lethe serbonis (Hewitson)+++++++
Lethe insana (Kollar)+++++++
Lethe rohria (Fabricius)+++++++
Subfamily: Heliconiinae
Acraea issoria (Hübner)		+++++-
Childrena childreni (Gray)-+++++
Argyreus hyperbius (Linnaeus)++++++++
Issoria lathonia (Linnaeus)--++++
Cethosia cyane (Drury)++++++
Phalanta phalantha (Drury)++++++
Vagrans egista (Cramer)+++++-
Subfamily: Limenitinae
Sumalia daraxa (Doubleday)		+++++--
Parasarpa dudu (Doubleday)+++++-
Parasarpa zayla (Doubleday)-++++++
Athyma perius
(Linnaeus)		++++++-
Athyma selenophora (Kollar)++++++-
Athyma opalina (Kollar)--+++++
Athyma asura (Moore)--++++
Neptis jumbah (Moore)+++++--
Neptis hylas (Linnaeus)+++++--
Neptis ananta (Moore)++++++
Neptis yerburyi (Butler)-+++--
Euthalia aconthea (Cramer)++++++++++
Euthalia nais (Forster)+++++++-
Tanaecia lepidea (Butler)+++++++++
Tanaecia julii (Lesson)++++++--
Euthalia lubentina (Cramer)++++++
Euthalia sahadeva (Moore)-+++--
Euthalia franciae (Gray)-+++--
Subfamily: Cyrestinae
Cyrestis thyodamas Boisduval		+++++++
Chersonesia risa (Doubleday)+++++--
Stibochiona nicea (Gray)++++--
Subfamily: Biblidinae
Ariadne ariadne (Linnaeus)		+++++++
Ariadne merione (Cramer)++++++++
Subfamily: Apaturinae
Apatura ambica (Kollar)		+++++++
Apatura sordida (Moore)-+++--
Dilipa morgiana (Westwood)-+++++
Hestina nama (Doubleday)+++++-
Herona marathus (Doubleday)+++++--
Subfamily: Nymphalinae
Araschnia prorsoides
(Blanchard)		--++++
Symbrenthia niphanda (Moore)-+++++
Symbrenthia hypselis (Godart)-+++++
Symbrenthia hippoclus (Cramer)-++++++
Vanessa indica (Herbst)++++++
Vanessa cardui (Linnaeus)+++++++
Aglais cashmiriensis (Kollar)+++++++++
Kaniska canace (Linnaeus)++++++++++
Junonia orithiya (Linnaeus)++++++
Junonia hierta (Fabricius)++++++++++-
Junonia lemonias (Linnaeus)+++++++-
Junonia almana (Linnaeus)++++--
Hypolimnas misippus (Linnaeus)+++++++
Kallima alompra (Moore)---+++
Subfamily: Libytheinae
Libythea lepita (Moore)		-+++++
Libythea myrrha (Godart)-++++++
Libythea narina rohini (Marshall)-++++-
Note: ”+” indicates 0–19 individuals; “++” indicates 20–29 individuals; “+++” indicates 30–39 individuals; “++++” indicates 40–49 individuals; “+++++” indicates 50–59 individuals; “++++++” indicates 60–69 individuals; and “-” indicates the absence of individuals.
Table 2. Values of species evenness, species dominance, and Gini coefficient across elevational gradients.
Table 2. Values of species evenness, species dominance, and Gini coefficient across elevational gradients.
IndicesElevational Gradients (masl)
≤1500 1501–20002001–25002501–30003001–3500≥3501
Pielou’s index1.4021.4201.4181.4231.4191.424
Buzas and Gibson index0.8920.9330.9270.9420.9340.952
Equitability index0.9720.9840.9830.9860.9840.987
Berger–Parker
dominance		0.0470.0310.0460.0250.0300.032
Gini’s coefficient0.2640.2050.1840.1850.2020.153
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Sengupta, P. Can Elevation Affect the Distribution of Nymphalidae Butterflies Adjacent to the Protected Regions in the Eastern Himalayan Landscape of West Bengal, India? Biol. Life Sci. Forum 2024, 39, 6. https://doi.org/10.3390/blsf2024039006

AMA Style

Sengupta P. Can Elevation Affect the Distribution of Nymphalidae Butterflies Adjacent to the Protected Regions in the Eastern Himalayan Landscape of West Bengal, India? Biology and Life Sciences Forum. 2024; 39(1):6. https://doi.org/10.3390/blsf2024039006

Chicago/Turabian Style

Sengupta, Panchali. 2024. "Can Elevation Affect the Distribution of Nymphalidae Butterflies Adjacent to the Protected Regions in the Eastern Himalayan Landscape of West Bengal, India?" Biology and Life Sciences Forum 39, no. 1: 6. https://doi.org/10.3390/blsf2024039006

APA Style

Sengupta, P. (2024). Can Elevation Affect the Distribution of Nymphalidae Butterflies Adjacent to the Protected Regions in the Eastern Himalayan Landscape of West Bengal, India? Biology and Life Sciences Forum, 39(1), 6. https://doi.org/10.3390/blsf2024039006

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