Skip to main content

Predicting habitat suitability of Litsea glutinosa: a declining tree species, under the current and future climate change scenarios in India


Litsea glutinosa (Lour.) C.B.Rob., an evergreen tree with significant ecological and medicinal value, has seen its distribution gradually decline due to unsustainable harvesting, overexploitation, and climate change. Habitat suitability modelling can be an effective tool for the conservation and management of L. glutinosa. This study aims to predict L. glutinosa habitat suitability in India under current and future climate change scenarios. Our study identified the important predictors that affect L. glutinosa distribution. In addition, the L. glutinosa habitat suitability area and its percent difference in the current and future were assessed, and potential conservation sites were identified. This study is based on the widely used maximum entropy (MaxEnt) species distribution model (SDM). We used current and future modelled data of the sixth version of the Model for Interdisciplinary Research on Climate (MIROC6) from Coupled Model Intercomparison Projects (CMIP6) Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5 and SSP5-8.5) emission scenarios for the period (2030s, 2050s and 2070s). Results demonstrated that the MaxEnt performance is good with an area under the receiver operator characteristic (AUC/ROC) curve of 0.852. L. glutinosa distribution is most influenced by the mean diurnal range (Bio2), contributing 55.1%. Notably, under high emissions and warmer climates of the SSP5-8.5 scenario, the suitable habitat of L. glutinosa would tend to increase. Under the SSP5-8.5 scenario, the maximum area of excellent habitat is 0.298 M km2. The study identified the sub-Himalayan region, the central-eastern region, the northeastern ranges, and the western ghats as candidate areas for species conservation.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Data Availability

All data generated or analysed during this study are included in this published article (and its supplementary information files).


Download references


We are highly thankful to The Director, Tropical Forest Research Institute, Jabalpur, Madhya Pradesh for providing necessary facilities for the field investigations and the Central University of Rajasthan for research facilities through the DST-FIST funded Remote sensing and GIS Lab in the Department of Environmental science. Finally, we thank the Editor-in-Chief and two anonymous reviewers for their valuable comments.


Part of this research was financially supported by the Indian Council of Forestry Research and Education, Dehradun under the project ID: 205/TFRI/2013/Gen-2(29) and National Bamboo Mission, New Delhi, under the project ID: 278/NBM/TFRI/2020-21/GTI-3(45).

Author information

Authors and Affiliations


Corresponding author

Correspondence to Naseer Mohammad.

Ethics declarations

Conflict of interest

The authors declare no conflict of interest.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 1432 KB)

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Gupta, R., Sharma, L.K., Rajkumar, M. et al. Predicting habitat suitability of Litsea glutinosa: a declining tree species, under the current and future climate change scenarios in India. Landscape Ecol Eng 19, 211–225 (2023).

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI:


  • Litsea glutinosa
  • Species decline
  • Anthropogenic pressure
  • MaxEnt
  • CMIP6
  • Species distribution model