Biodiversity and Conservation

, Volume 21, Issue 5, pp 1251–1266 | Cite as

Assessment of impact of climate change on Rhododendrons in Sikkim Himalayas using Maxent modelling: limitations and challenges

  • Pradeep KumarEmail author
Original Paper


Integration of climate change aspects in biodiversity management is one the fundamental requirements for long term biodiversity conservation. The explicit modelling of the biodiversity in response to climate change is the primary requirement for making any adaptation strategy. With Himalayan ecosystem in mind and Rhododendron as the species of concern, the current paper models the biogeography of the genera Rhododendron which are found intermixed in their spatial distribution in Sikkim Himalayas, mainly tree varieties, in response to climate change. The modelling algorithm used in the paper is Maxent (maximum entropy) which has estimated the target probability distribution by finding the probability distribution of Maxent. After projection of modelled bioclimatic layers to future climate scenario of SRES-A1B in Maxent, it was found that the suitable bioclimatic envelope for Rhododendron has shrunk considerably under the envisaged climate change scenario. The results on extent and locations of Rhododendron distributions in both the current and future climate scenarios provide a deep insight to the conservation planners about the kind of strategy that needs to be adopted for conserving Rhododendrons in the face of climate change. The challenges observed while doing this analysis highlight the gaps and set the agenda for further research to make the predictions of climate change driven impact on biodiversity scientifically more robust.


Biodiversity Species distribution Maximum entropy Bioclimatic envelope 



This work was made possible due to ongoing inventorisation of species by Department of Forests, Environment and Wildlife Management, Government of Sikkim under the guidance of Mr S.T. Lachungpa. I owe my thanks to the IT assistant in the Remote Sensing and GIS Cell for data formatting. This work would not have reached its logical conclusion without the constant support and encouragement from Mrs Bharati.


  1. Austin M (2002) Spatial prediction of species distribution: an interface between ecological theory and statistical modelling. Ecol Model 157:101–118CrossRefGoogle Scholar
  2. Dudik M, Phillips SJ, Schapire RE (2004) Performance guarantees for regularized maximum entropy density estimation. ACM Press, New York, pp 655–662Google Scholar
  3. Forman R (1964) Growth under controlled conditions to explain the hierarchial distribution of a moss, Tetraphis pellucida. Ecol Monogr 34:1–25CrossRefGoogle Scholar
  4. Hijmans JR et al (2005) Very high resolution interpolated climate surfaces for global land areas. Int J Climatol 25:1965–1978CrossRefGoogle Scholar
  5. IPCC (2007) Summary for policy makers. IPCC 21, GenevaGoogle Scholar
  6. Kittel TF, Stefen WL, Chapin FS (2000) Global and regional modelling of Arctic ± boreal vegetation distribution and its sensitivity to altered forcing. Glob Change Biol 6:1–18CrossRefGoogle Scholar
  7. Korner C (2002) Mountain biodiversity, its causes and functions. In: Mountain biodiversity: a global assessment. Parthenon Publishing, London, pp 3–20Google Scholar
  8. Krishna AP, Chettri S, Singh KK (2002) Human dimensions of conservation in the Khangchendzonga biosphere reserve. Mt Res Dev 24:328–331CrossRefGoogle Scholar
  9. Liu X, Chen B (2000) Climatic warming in the Tibetan. Int J Climatol 20:1729–1742CrossRefGoogle Scholar
  10. McKenny WD et al (2007) Potential impacts of climate change on the distribution of north American trees. Bioscience 57(11):939–948CrossRefGoogle Scholar
  11. Parmesan C (1996) Climate change and species’ ranges. Nature 382:765–766CrossRefGoogle Scholar
  12. Paul A, Khan ML, Arunachalam A, Arunachalam K (2005) Biodiversity and conservation of Rhododendrons in Arunachal Pradesh in Indo-Burma biodiversity hot spot. Curr Sci 89(4):623Google Scholar
  13. Pearce J, Ferrier S (2000) Evaluating the predictive performance of habitat models developed using logistic regression. Ecol Model 133:225–245CrossRefGoogle Scholar
  14. Pearson RG (2007) Species’ distribution modeling for conservation educators and practitioners. Synthesis. Available at:
  15. Phillips SJ, Miroslav D (2008) Modelling species distribution with maxent: new extensions and a comprehensive evaluation. Ecography 190:161–175CrossRefGoogle Scholar
  16. Phillips SJ, Anderson RP, Schapire RE (2006) Maximum entropy modeling of species geographic distributions. Ecol Model 190:231–259CrossRefGoogle Scholar
  17. Pradhan KC (2010) The Rhododendrons of Sikkim. Sikkim Adventures, Botanical Tours and Travels, TadongGoogle Scholar
  18. Pradhan KC, Lachungpa ST (1990) Sikkim Himalayan Rhododendrons. Primulaceae Books, KalimpongGoogle Scholar
  19. Rawat GS (2008) Predicting impact of climate change on Himalayan flora. National Botanical Research Institute, Lucknow, pp 59–60Google Scholar
  20. Root TL et al (2003) Fingerprints of global warming on wild animals and plants. Nature 421:57–60PubMedCrossRefGoogle Scholar
  21. Shrestha A, Wake C, Mayewski P, Dibb J (1999) Maximum temperature trends in the Himalaya and its vicinity: an analysis based on temperature records from Nepal for the period 1971–94. J Clim 12:2775–2787CrossRefGoogle Scholar
  22. Singh KK, Kumar S, Rai LK, Krishna AP (2003) Rhododendron conservation in Sikkim Himalayas. Curr Sci 85(5):602–606Google Scholar
  23. Steffen WL, Walker BH, Ingram J, Koch GW (1992) Global change and terrestrial ecosystems: the operational plan. S.N, StockholmGoogle Scholar
  24. Thompson C (2008) The Rhododendron phenology project. Royal Botanical Garden, EdinburghGoogle Scholar
  25. Thuiller W (2007) Climate change and the ecologist. Nature 448(2):550–552Google Scholar
  26. Woodward FI (1987) Climate and plant distribution. Cambridge University Press, CambridgeGoogle Scholar
  27. Xu J et al (2007) The melting Himalayas: regional challenges and local impacts of climate change on mountain ecosystems and livelihoods. ICIMOD, KathmanduGoogle Scholar
  28. Yao TD et al (2006) Record and temperature change over the past 100 years in Ice Cores on the Tibetan plateau. Sci China Series D Earth Sci 49(1):1–9CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2012

Authors and Affiliations

  1. 1.Department of ForestsEnvironment and Wildlife Management, Government of SikkimDeorali, GangtokIndia

Personalised recommendations