Vegetation productivity determines the response of butterflies along elevation gradients in the trans‐Himalayas, Nepal

Abstract Environmental parameters along elevational gradients affect the number of butterflies and the variety of species. However, which variables play significant roles and how they operate can be difficult to untangle. Here, we examine the relationships between observed butterfly richness (overall and subgroups) at different elevation gradients and remotely sensed environmental variables (vegetation productivity, surface temperature, landscape heterogeneity, and moisture stress) using generalized linear models. We surveyed butterflies with a fixed‐point count method in 19 elevation bands within 1600–5200 m above sea level in Manang district, trans‐Himalayan region, north‐central Nepal. The number of butterflies in each elevation band was studied and estimated, then interpolated across the lowest and highest elevation to estimate butterfly species richness. Then, the selection of models was performed on butterfly richness and elevations to test the best model support based on the lowest value of the Akaike information criterion and a multimodel averaging for other environmental variables. Altogether, 94 butterfly species, representing 20 subfamilies and six families, were recorded throughout the study periods. We obtained cubic model support for overall species richness, Papilionidae, and Hesperiidae, quadratic to Nymphalidae and Pieridae, and the linear model to Lycaenidae. In our study, vegetation productivity was found to have a significant positive impact on butterfly communities. Our study further suggests species richness of Papilionidae and Hesperiidae has a strong positive correlation with surface temperature and landscape heterogeneity and negative associations with moisture stress but other subgroups of butterfly communities including overall species richness showed insignificant relationships with these variables. This study provides significant information related to the responses of montane butterflies to environmental variables along elevational gradients from the Himalayas Nepal. However, further detailed studies on the functional behaviors of butterflies potentially offer more insights into their distribution patterns and ecological relationship in the montane environment.

Authors

Institutions

Publication Details

Journal
Ecosphere
Published
2024-10-01
DOI
https://doi.org/10.1002/ecs2.70019
Citations
4
Primary Topic
Ecology and Vegetation Dynamics Studies
Type
article
Field-Weighted Citation Impact
2.76

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Vegetation productivity determines the response of butterflies along elevation gradients in the trans‐Himalayas, Nepal

Ashant Dewan, Kiran Thapa Magar, Bimal Raj Shrestha, Suraj Baral et al.
4 citations
Ecosphere
Ecology and Vegetation Dynamics Studies
2.76
article

Vegetation productivity determines the response of butterflies along elevation gradients in the trans‐Himalayas, Nepal

Ashant Dewan, Kiran Thapa Magar, Bimal Raj Shrestha, Suraj Baral, Sanej Prasad Suwal, Shanta Budha‐Magar, Pratichhya Shrestha, Prakash Gaudel, Sanjaya Raj Tamang, Min Bahadur Gurung
article en
4 citations

Abstract

Abstract Environmental parameters along elevational gradients affect the number of butterflies and the variety of species. However, which variables play significant roles and how they operate can be difficult to untangle. Here, we examine the relationships between observed butterfly richness (overall and subgroups) at different elevation gradients and remotely sensed environmental variables (vegetation productivity, surface temperature, landscape heterogeneity, and moisture stress) using generalized linear models. We surveyed butterflies with a fixed‐point count method in 19 elevation bands within 1600–5200 m above sea level in Manang district, trans‐Himalayan region, north‐central Nepal. The number of butterflies in each elevation band was studied and estimated, then interpolated across the lowest and highest elevation to estimate butterfly species richness. Then, the selection of models was performed on butterfly richness and elevations to test the best model support based on the lowest value of the Akaike information criterion and a multimodel averaging for other environmental variables. Altogether, 94 butterfly species, representing 20 subfamilies and six families, were recorded throughout the study periods. We obtained cubic model support for overall species richness, Papilionidae, and Hesperiidae, quadratic to Nymphalidae and Pieridae, and the linear model to Lycaenidae. In our study, vegetation productivity was found to have a significant positive impact on butterfly communities. Our study further suggests species richness of Papilionidae and Hesperiidae has a strong positive correlation with surface temperature and landscape heterogeneity and negative associations with moisture stress but other subgroups of butterfly communities including overall species richness showed insignificant relationships with these variables. This study provides significant information related to the responses of montane butterflies to environmental variables along elevational gradients from the Himalayas Nepal. However, further detailed studies on the functional behaviors of butterflies potentially offer more insights into their distribution patterns and ecological relationship in the montane environment.

EcosphereVol. 15(10)
Tribhuvan University (NP), Northland District Health Board (NZ), Zoological Research Museum Alexander Koenig (DE), Leibniz Institute for the Analysis of Biodiversity Change (DE), Nepal Academy of Science and Technology (NP), Tokyo Metropolitan University (JP), Kathmandu Medical College Teaching Hospital (NP), National Trust for Nature Conservation (NP)
Rufford Foundation, Mohamed bin Zayed Species Conservation Fund
Life below water
Openalex Percentile: Top 10%
Ecology and Vegetation Dynamics Studies
2.76
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.