Climate-Driven Habitat Suitability Mapping of Terminalia Arjuna (Roxb.) Wight & Arn. in Tropical Tasar-growing States of India using Maxent Modelling
DOI:
https://doi.org/10.36808/if/2026/v152i7/171273Keywords:
Terminalia arjuna, MaxEnt modelling, habitat suitability, tropical tasar sericulture, bioclimatic variablesAbstract
Terminalia arjuna (Roxb.) Wight & Arn. is an ecologically and economically important tree species serving as a primary host for the tropical tasar silkworm. The present study aimed to assess its current habitat suitability and distribution across India using the Maximum Entropy (MaxEnt) modelling approach. A total of 2,448 occurrence records were obtained from the Global Biodiversity Information Facility (GBIF) and field surveys, of which 145 spatially filtered points were used for modelling. Nineteen bioclimatic variables (BIO1-BIO19) from the WorldClim database were utilized as environmental predictors. The model demonstrated high predictive accuracy with an AUC value of 0.891. Among the variables, annual mean temperature (BIO1) contributed the most, followed by precipitation of the wettest quarter (BIO16) and mean temperature of the wettest quarter (BIO8). The habitat suitability map indicated that highly suitable regions are concentrated in central and eastern India, including Madhya Pradesh, Chhattisgarh, Jharkhand, and Odisha. The study highlights the critical role of climatic factors in shaping the distribution of T. arjuna and provides valuable insights for conservation planning and sustainable expansion of tropical tasar sericulture.
References
Ab Lah, N.Z., Yusop, Z., Hashim, M., Mohd Salim, J. and Numata, S. (2021). Predicting the habitat suitability of Melaleuca cajuputi based on the MaxEnt species distribution model, Forests, 12 (11): 1449. DOI: https://doi.org/10.3390/f12111449
Crispim-Mendes, T., Valerio, F., Marques, A.T., Pita, R., Godinho, S. and Silva, J.P. (2024). High-resolution species distribution modelling reveals spatio-temporal variability of habitat suitability in a declining grassland bird, Landscape Ecology, 39 (3): 49. DOI: https://doi.org/10.1007/s10980-024-01848-6
Das, S., Singh, P., Kumar, D., Singh, J., Giri, S. and Sathyanarayana, K. (2022). Impact of foliar supplementation of nitrogen on protein content of Terminalia arjuna leaf and tasar silkworm Antheraea mylitta, Plant Archives, 22: 140-143. DOI: https://doi.org/10.51470/PLANTARCHIVES.2022.v22.specialissue.027
Devi, V., Fulekar, M.H., Charles, B., Reddy, C.S. and Pathak, B. (2024). Predicting habitat suitability and species richness under climate change scenarios, Environmental Monitoring and Assessment, 196 (11): 1136. DOI: https://doi.org/10.1007/s10661-024-13290-x
Fick, S.E. and Hijmans, R.J. (2017). WorldClim 2: New 1 km spatial resolution climate surfaces for global land areas, International Journal of Climatology, 37 (12): 4302–4315. DOI: https://doi.org/10.1002/joc.5086
Giri, S., Das, S. and Sathyanarayana, K. (2023). Nutrient dynamics and sustainability of wild tasar silkworm on Sal flora, Plant Archives, 23 (1). DOI: https://doi.org/10.51470/PLANTARCHIVES.2023.v23.no1.065
Hosseini, N., Ghorbanpour, M. and Mostafavi, H. (2024). Habitat potential modelling and the effect of climate change on the current and future distribution of three Thymus species in Iran using MaxEnt, Scientific Reports, 14 (1): 3641. DOI: https://doi.org/10.1038/s41598-024-53405-5
Jena, K., Kumari, R., Pandey, J.P., Kar, P.K., Akhtar, J., Singh, A.K. and Sinha, A.K. (2021). Biochemical characterization of sericin isolated from cocoons of tropical tasar silkworm Antheraea mylitta raised on three different host plants for its prospective utilization, Journal of Asia-Pacific Entomology, 24 (3): 903-911. DOI: https://doi.org/10.1016/j.aspen.2021.07.018
Liu, L., Guan, L., Zhao, H., Huang, Y., Mou, Q., Liu, K. and Hu, J. (2021). Modeling habitat suitability of Houttuynia cordata using MaxEnt under climate change in China, Ecological Informatics, 63: 101324. DOI: https://doi.org/10.1016/j.ecoinf.2021.101324
Manohara, T.N., Pasha, S.V., Swarada, B. and Balakrishna, S.M. (2025). Predicting habitat suitability of Dalbergia latifolia using MaxEnt: Implications for conservation and sustainable forest management, BMC Ecology and Evolution, 25 (1): 1–13. DOI: https://doi.org/10.1186/s12862-025-02446-z
Nguyen, T.T., Gliottone, I. and Pham, M.P. (2021). Current and future predicting habitat suitability of Cunninghamia konishii using MaxEnt model, European Journal of Ecology, 7 (2). DOI: https://doi.org/10.17161/eurojecol.v7i2.15079
Parveen, S., Kaur, S., Baishya, R. and Goel, S. (2022). Predicting the potential suitable habitats of genus Nymphaea in India using MaxEnt modeling, Environmental Monitoring and Assessment, 194 (12): 853. DOI: https://doi.org/10.1007/s10661-022-10524-8
Phillips, S.J., Anderson, R.P. and Schapire, R.E. (2006). Maximum entropy modeling of species geographic distributions, Ecological Modelling, 190 (3–4): 231–259. DOI: https://doi.org/10.1016/j.ecolmodel.2005.03.026
Phillips, S.J., Dudík, M. and Schapire, R.E. (2017). Maxent software for modeling species niches and distributions (Version 3.4.1), Biodiversity Informatics, 1: 1–28.
Rajaram, V., Namasivayam, A., Shanmugam, R., Mahendra, J., Sudhakar, U., Munusamy, T. and Subbiah, U. (2024). Terminalia arjuna: An overview of its magical properties, Bioinformation, 20 (12): 2080. DOI: https://doi.org/10.6026/9732063002002080
Rajlaxmi, A., Chawla, A. and Kumar, M. (2025). Predicting the current and future potential habitat of Taxus species in Indian Himalayan Region using MaxEnt model, Tropical Ecology, 66 (1): 14–34. DOI: https://doi.org/10.1007/s42965-024-00365-6
Rojas-Soto, O., Forero-Rodríguez, J.S., Galindo-Cruz, A., Mota-Vargas, C., Parra-Henao, K.D., Peña-Peniche, A. and Trinidad-Domínguez, C.D. (2024). Calibration areas in ecological niche and species distribution modelling: Unravelling approaches and concepts, Journal of Biogeography, 51 (8): 1416–1428. DOI: https://doi.org/10.1111/jbi.14834
Roy, S., Suman, A., Ray, S. and Saikia, S.K. (2022). Use of species distribution models to study habitat suitability for sustainable management and conservation in the Indian subcontinent, Frontiers in Sustainable Resource Management, 1: 1031646. DOI: https://doi.org/10.3389/fsrma.2022.1031646
WorldClim (2020). WorldClimGlobal Climate Data, Version 2.1. Available from: https://www.worldclim.org/data/worldclim21.html
Zhang, H., Song, J., Zhao, H., Li, M. and Han, W. (2021). Predicting the distribution of the invasive species Leptocybe invasa: Combining MaxEnt and Geodetector models, Insects, 12: 92. DOI: https://doi.org/10.3390/insects12020092
Zhao, Y., Zhang, L. and Wang, C. (2024). Predicting possible distribution of rice leaf roller (Cnaphalocrocis medinalis) under climate change scenarios using MaxEnt model in China, Scientific Reports, 14 (1): 21245. DOI: https://doi.org/10.1038/s41598-024-71228-2
Zhu, Y., Wei, W., Li, H., Wang, B., Yang, X. and Liu, Y. (2018). Modelling the potential distribution and shifts of three varieties of Stipa tianschanica in the Eastern Eurasian Steppe under multiple climate change scenarios, Global Ecology and Conservation, 16: e00501. DOI: https://doi.org/10.1016/j.gecco.2018.e00501
Downloads
Downloads
Published
How to Cite
Issue
Section
License
Unless otherwise stated, copyright or similar rights in all materials presented on the site, including graphical images, are owned by Indian Forester.
