1. Austin, M.P. and van Niel, K.P., 2011. Improving species distribution models for climate change studies: variable selection and scale. Journal of Biogeography 38, pp.1–8.  https://doi.org/10.1111/j.1365-2699.2010.02416.x

Google Scholar

2. Barnosky, A.D., Matzke, N., Tomiya, S., Wogan, G.O., Swartz, B., Quental, T.B., Marshall, C., McGuire, J.L., Lindsey, E.L., Maguire, K.C., Mersey, B. and Ferrer, E.A., 2011. Has the Earth’s sixth mass extinction already arrived? Nature 471, pp.51–57.

Google Scholar

3. BSI, 2023. Plant Discoveries 2022 (including algae, fungi & microbes). A.A. Mao, D.K. Agrawala & Sinjini Mukherjee (eds). The Director, Botanical Survey of India. (https://bsi.gov.in/uploads/documents/Plant%20Discoveries/Plant%20Discoveries%202022%20for%20upload%20final.pdf)

Google Scholar

4. Chandramohan, K., Mahesh, Y., Rambabu, K. and Kiran, E., 2020. A taxonomic revision of the genus Eriolaena (Malvaceae) in India. Annals of Plant Sciences 9(1), pp.3681–3692

Google Scholar

5. Dai, X., Wu, W., Ji, L., Tian, S., Yang, B., Guan, B. and Wu, D., 2022. MaxEnt model-based prediction of potential distributions of Parnassia wightiana (Celastraceae) in China. Biodiversity Data Journal 10: e81073.  https://doi.org/10.3897/BDJ.10.e81073

Google Scholar

6. Debata, S., Panda, R.M. and Palita, S.K., 2019. Chiropteran diversity and the key determinants of their distribution in Eastern Ghats, India. Biodivers Conserv. 2, pp.82385–82404.

Google Scholar

7. Elith, J., Phillips, S.J., Hastie, T., Dudik, M., Chee, Y.E. and Yates, C.J., 2011. A statistical explanation of MaxEnt for ecologists. Divers Distrib 17, pp.43–57.  https://doi.org/10.1111/j.1472-4642.2010.00725.x

Google Scholar

8. Elser, J.J., Fagan, W.F., Kerkhoff, A.J., Swenson, N.G. and Enquist, B.J., 2010. Biological stoichiometry of plant production: metabolism, scaling and ecological response to global change. New Phytologist, 186, pp.593–608. https://doi.org/10.1111/j.1469-8137.2010.03214.x

Google Scholar

9. Florey, A.B., Smith, C.D. and Jones, E.F., 2012. Modeling species distributions using maximum entropy: Evaluating iteration thresholds and replication types. Journal of Ecological Modelling, 245(3), pp.112–125.

10. Franklin, J., 2010. Mapping species distributions: spatial inference and prediction. Cambridge University Press, Cambridge, United Kingdom.  https://doi.org/10.1017/CBO9780511810602

Google Scholar

11. Hernandez, P.A., Graham, C.H., Master, M.M. and Albert, D., 2006. The effect of sample size on the performance of species distribution models. Ecography, 29, pp.773–785.

12. Malik, K., Saranya, K.R.L., Reddy, C.S. and Varghese, A.O., 2022 Predicting the habitat suitability of Dipterocarpus indicus – An endemic and endangered species in the Western Ghats, India.   Spatial Information Research. 30(5), pp.617–632.  https://doi.org/10.1007/s41324-022-00466-1

Google Scholar

13. Mathur, M., Mathur, P. and Purohit, H., 2023. Ecological niche modelling of a critically endangered species Commiphora wightii (Arn.) Bhandari using bioclimatic and non-bioclimatic variables. Ecological Processes 12, 8.  https://doi.org/10.1186/s13717-023-00423-2

Google Scholar

14. Maury-Lechon, G. and Curtet, L., 1998. Biogeography and evolutionary systematics of Dipterocarpaceae, pp. 5–44. In Appannah, S. & J.M. Turnbull (eds), A Review of Dipterocarps: Taxonomy, Ecology and Silviculture. Center for International Forestry Research, Indonesia.

Google Scholar

15. Meinshausen, M., Nicholls, Z.R.J., Lewis, J., Gidden, M.J., Vogel, E., Freund, M., Beyerle, U., Gessner, C., Nauels, A., Bauer, N., Canadell, J.G., Daniel, J.S., John, A., Krummel, P.B., Luderer, G., Meinshausen, N., Montzka, S.A., Rayner, P.J., Reimann, S., Smith, S.J., van den Berg, M., Velders, G.J.M., Vollmer, M.K., and Wang, R.H.J., 2020: The shared socio-economic pathway (SSP) greenhouse gas concentrations and their extensions to 2500, Geosci. Model Dev., 13, pp.3571–3605,  https://doi.org/10.5194/gmd-13-3571-2020

16. Naidu, M.T, Kumar, O.A. and Venkaiah, M., 2014b. Taxonomic diversity of lianas in tropical forests of northern Eastern Ghats of Andhra Pradesh, India. Notulae Scientia Biologicae, 6, pp.59–65.  https://doi.org/10.15835/nsb619193

Google Scholar

17. Naidu, M.T., Kumar, O.A., Rao, M.S., and Venkaiah, M., 2014a. Impact of Indira Sagar Dam in the Eastern Ghats of Andhra Pradesh on the floristic wealth. International Journal of Advanced Research in Science and Technology, 3, pp.8–16

Google Scholar

18. Naimi, B., 2013. Usdm: Uncertainty analysis for species distribution models. R Packag. version 1, pp.1–12.

19. Namitha, L.H., Achu, A.L., Reddy, C.S. and Beevy, S., 2022. Ecological modelling for the conservation of Gluta travancorica Bedd. - An endemic tree species of southern Western Ghats, India. Ecological Informatics. 71, 101823.  https://doi.org/10.1016/j.ecoinf.2022.101823

Google Scholar

20. Nazeri, A., Gholami, R. and Rashidi, S., 2012. Outsourcing and its impact on operational performance. Proceedings of the 2012 Internation0al Conference on Industrial Engineering and Operations Management, Istanbul, Turkey, July 3 – 6. 

Google Scholar

21. Padal, S.B., Rao, J.P., Naidu, M.T., Rao, D.S., Rao, M.S., Prameela, R. and Aruna, K., 2009. Some important Pteridophytes from Eastern Ghats of northern Andhra Pradesh, India.  Journal of Nature Conservation, 21, pp.287–294.

22. Pearson, R.G., Raxworthy, C.J., Nakamura, M. and Peterson, A.T., 2007. Predicting species distributions from small numbers of occurrence records: a test case using cryptic geckos in Magadascar. Journal of Biogeography., 34, pp.102–117.  https://doi.org/10.1111/j.1365-2699.2006.01594.x

Google Scholar

23. Phillips, S.J. and Dudík, M., 2008. Modeling of species distributions with Maxent:  new extensions and a comprehensive evaluation. Ecography 31(2), pp.161–175.  https://doi.org/10.1111/j.0906-7590.2008.5203.x

Google Scholar

24. Phillips, S.J., Anderson, R.P. and Schapire, R.E., 2006. Maximum entropy modeling of species geographic distributions. Ecological Modelling, 190, pp.231–259.  https://doi.org/10.1016/j.ecolmodel.2005.03.026

Google Scholar

25. Polak, T. and Saltz, D., 2011. Reintroduction as an ecosystem restoration technique. Conservation Biology, 25(3), pp.424-424.  https://doi.org/10.1111/j.1523-1739.2011.01669.x

Google Scholar

26. POWO, 2023. Plants of the World Online. https://powo.science.kew.org/

27. Pradhan, P., 2016. Strengthening Maxent modelling through screening of redundant explanatory bioclimatic variables with variance inflation factor analysis. Researcher, 8(5), pp.29–34.

Google Scholar

28. Prentice, I.C., 1992. Climate change and long-term vegetation dynamics. In Glenn, D.C., Peet, R.K., Veblen, T.T. (eds), Plant Succession: Theory and Prediction. Chapman and Hall, London, pp. 293–339.

Google Scholar

29. Priti, H., Aravind, N.A., Shaanker, R.U. and Ravikanth, G., 2016. Modelling impacts of future climate on the  distribution  of Myristicaceae species in the Western Ghats, India. Ecological Engineering, 89, pp.14–23.  https://doi.org/10.1016/j.ecoleng.2016.01.006

Google Scholar

30. Pulparambil, H. and Pradeep, N.S., 2023. Ecological niche modelling in identifying habitats for effective species conservation: A study on Endemic aquatic plant Crinum malabaricum. Journal for Nature Conservation 76(6), 126517.  https://doi.org/10.1016/j.jnc.2023.126517

Google Scholar

31. Raju, A.J.S., Ramana, K.V. and Chandra, P.H., 2013. Floral ecology and pollination in Eriolaena lushingtonii (Sterculiaceae), an endemic and threatened deciduous tree species of southern peninsular India. Journal of Threatened Taxa 5(9), pp.4359–4367.  https://doi.org/10.11609/JoTT.o3168.4359-67

Google Scholar

32. Rawat, N., Purohit, S., Painuly, V., Negi, G.S. and Bisht, M.P.S., 2021. Habitat distribution modeling of endangered medicinal plant Picrorhiza kurroa (Royle ex Benth) under climate change scenarios in Uttarakhand Himalaya, India. Ecological Informatics, 68, 101550.  https://doi.org/10.1016/j.ecoinf.2021.101550

Google Scholar

33. Reddy, C.S., Jha, C.S. and Dadhwal, V.K., 2014. Spatial dynamics of deforestation and forest fragmentation (1930-2013) in Eastern Ghats, India. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-8, pp.637–644.  https://doi.org/10.5194/isprsarchives-XL-8-637-2014

Google Scholar

34. Reddy, C.S., Jha, C.S., Diwakar, P.G. and Dadhwal, V.K., 2015.Nationwide classification of forest types of India using remote sensing and GIS. Environmental Monitoring and Assessment 187(12), 777.  https://doi.org/10.1007/s10661-015-4990-8

Google Scholar

35. Rong, Z., Ouyang, Z.-T., Xie, X., Guo, H.-Q., Tan, D.-Y., Xiao, X.-M., Qi, J.-G., and Zhao, B., 2016. Impact of Climate Change on Vegetation Growth in Arid Northwest of China from 1982 to 2011. Remote Sensing, 8(5), 364. https://doi.org/10.3390/rs8050364

Google Scholar

36. Sharma, S., Arunachalam, K., Bhavsar, D. and Kala, R., 2018. Modeling habitat suitability of Perilla frutescens with MaxEnt in Uttarakhand—A conservation approach. Journal of Applied Research on Medicinal and Aromatic Plants. 10, pp.99–105.  https://doi.org/10.1016/j.jarmap.2018.02.003

Google Scholar

37. Shilpa, B., Giriraj, A., Reddy, C.S., Jentsch, A. and Sudhakar, S., 2012. Species distribution models: Ecological explanation and prediction of an endemic and endangered plant species (Pterocarpus santalinus L.f.). Current Science 102(8), pp.1157–1165.

Google Scholar

38. Shimwell, D., Box, E. and Lieth, H., 1982. Macroclimate and plant forms: an introdution to predictive modeling in phytogeography. The Journal of Applied Ecology 19 (3), 993.

39. Siqueira, M.F.D., Durigan, G., De Marco Junior, P. and Peterson, A.T., 2009. Something from nothing: using landscape similarity and ecological niche modeling to find rare plant species. Journal for Nature Conservation 17 (1), pp.25–32.  https://doi.org/10.1016/j.jnc.2008.11.001

Google Scholar

40. Sousa-Guedes, D., Arenas-Castro, S. and Sillero, N., 2020. Ecological niche models reveal climate change effect on biogeographical regions: the Iberian Pen-insula as a case study. – Climate 8, 42.  https://doi.org/10.3390/cli8030042

Google Scholar

41. Taylor, D. and Hamilton, A., 1994. Impact of Climate Change on Tropical Forests in Africa: Implications for Protected Area Planning Management. Impacts of Climate Change on Ecosystems and Species: Implications for Protected Areas. In Pernetta, J.G., Leemans, R., Endler, Humphrey, D. (eds), IUCN, Gland, pp. 77–94.

42. Thakur, R.C, Dada, L., Beck, L.J., Quelever, L.L.J., Chan, T., Marbouti, M., He X-C, Xavier, C., Sulo, J., Lampilahti, J., Lampimaki, M., Tham, Y.J., Sarnela, N., Lehtipalo, K., Norkko, A., Kulmala, M., Sipila, M. and Jokinen, T., 2022. An evaluation of new particle formation events in Helsinki during a Baltic Sea cyanobacterial summer bloom, Atmos. Chem. Phys., 22, pp.6365–6391 https://doi.org/10.5194/acp-22-6365-2022

Google Scholar

43. Veloz, S.D., 2009. Spatially autocorrelated sampling falsely inflates measures of accuracy for presence-only niche models. Journal of Biogeography. 36, pp.2290–2299.  https://doi.org/10.1111/j.1365-2699.2009.02174.x

Google Scholar

44. Woodward, F.I., 1987. Climate and Plant Distribution. Cambridge University Press, Cambridge, pp. 174.

Google Scholar

45. Ye, X.Z, Zhao, G.H, Zhang, M.Z, Vui, X.Y, Fan, H.H and Liu, B., 2020. Distribution pattern of endangered plants Semiliquidambar catayensis (Hamamelidaceae) in response to climate change after the last interglacial period. Forest, 11(4), 434. https://doi.org/10.3390/f11040434

Google Scholar

46. Zhang, M.G., Slik, J.W.F. and Ma, K.P., 2016. Using species distribution modeling to delineate the botanical richness patterns and phytogeographical regions of China. Scientific Reports 6, pp.1–9.  https://doi.org/10.1038/srep22400

Google Scholar