Multimodel ensemble projections of Shorea robusta habitat suitability in Nepal under current and future climates

Shorea robusta Gaertn. (sal) is an ecologically and economically important tree species that forms the dominant forest type in the lowland and mid-hill regions of Nepal. Understanding the habitat suitability of sal under current and future climatic conditions is important for supporting conservation and forest management planning. This study assessed habitat suitability for sal in Nepal using ensemble species distribution modelling based on presence-only data and 31 environmental variables. Four algorithms-Generalized Linear Model (GLM), Random Forest (RF), Boosted Regression Trees (BRT), and Maximum Entropy (MaxEnt)-were implemented using a 70/30 training–testing split and 10 bootstrap replicates. Model performance was generally high, with RF, BRT, and MaxEnt contributing most strongly to the final ensemble projection. The results indicate that suitable habitat for sal is currently concentrated in the Terai and lower Siwalik regions, closely matching its known present distribution. Under the 2070 RCP8.5 scenario, the projection indicates lower suitability in parts of western Nepal and higher suitability in parts of northern and eastern Nepal compared with the baseline current-ensemble projection. Minimum temperature of the coldest month (Bio6) emerged as the most important predictor, followed by temperature seasonality (Bio4), precipitation of the coldest quarter (Bio19), and terrain roughness. These findings provide scenario-based information on sal habitat suitability under current and projected future climatic conditions and can support climate-informed conservation, restoration, and forest management planning in Nepal.

Authors

Institutions

Publication Details

Journal
Discover Forests
Published
2026-08-26
DOI
https://doi.org/10.1007/s44415-026-00125-5
Primary Topic
Species Distribution and Climate Change
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Multimodel ensemble projections of Shorea robusta habitat suitability in Nepal under current and future climates

Dinesh Neupane, Kishor Aryal, Ganesh Puri, Manisha Parajuli et al.
Discover Forests
Species Distribution and Climate Change
article

Multimodel ensemble projections of Shorea robusta habitat suitability in Nepal under current and future climates

Dinesh Neupane, Kishor Aryal, Ganesh Puri, Manisha Parajuli, Arjun Rijal
article en

Abstract

Shorea robusta Gaertn. (sal) is an ecologically and economically important tree species that forms the dominant forest type in the lowland and mid-hill regions of Nepal. Understanding the habitat suitability of sal under current and future climatic conditions is important for supporting conservation and forest management planning. This study assessed habitat suitability for sal in Nepal using ensemble species distribution modelling based on presence-only data and 31 environmental variables. Four algorithms-Generalized Linear Model (GLM), Random Forest (RF), Boosted Regression Trees (BRT), and Maximum Entropy (MaxEnt)-were implemented using a 70/30 training–testing split and 10 bootstrap replicates. Model performance was generally high, with RF, BRT, and MaxEnt contributing most strongly to the final ensemble projection. The results indicate that suitable habitat for sal is currently concentrated in the Terai and lower Siwalik regions, closely matching its known present distribution. Under the 2070 RCP8.5 scenario, the projection indicates lower suitability in parts of western Nepal and higher suitability in parts of northern and eastern Nepal compared with the baseline current-ensemble projection. Minimum temperature of the coldest month (Bio6) emerged as the most important predictor, followed by temperature seasonality (Bio4), precipitation of the coldest quarter (Bio19), and terrain roughness. These findings provide scenario-based information on sal habitat suitability under current and projected future climatic conditions and can support climate-informed conservation, restoration, and forest management planning in Nepal.

Discover ForestsVol. 2(1)
Ministry of Environment, Forests and Climate Change (IN), George Mason University (US), Morphix Technologies (United States) (US), Kentucky State University (US)
Life in Land
Openalex Percentile: Top 11%
Species Distribution and Climate Change
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.