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Geospatial modeling of Brown oak (Quercus semecarpifolia) habitats in the Kumaun Himalaya under climate change scenario

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Abstract

The study explores the use of multiple criteria decision techniques in predicting spatial niche of Brown oak (also known as Kharsu oak, Quercus semecarpifolia Sm.) formation in midaltitude (2,400–3,500 meter amsl) Kumaun Himalaya. Predictive models using various climatic and topographical factors influencing Brown oak’s growth and survival were developed to define its current ecological niche. Analytical Hierarchical Process (AHP) method involving Saaty’s pair-wise comparison was performed to rank the explanatory powers of each compared variable. Variables were suitably weighted using fuzzy factor standardization scheme to reflect their relative importance in defining species niche. An optimum indicator was then chosen for deriving a site suitability map of brown oak. This study establishes the role of aspect in the current distribution of the species along with known influence of altitude. Future niches of oak has been tracked in the projected climate change scenario of +1°C and +2°C rise in temperature and 20 mm in precipitation. The results show that on predicted +1°C and +2°C increase in temperature, present habitat of brown oak distribution may be reduced by 40 per cent and 76 per cent respectively.

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References

  • Allen CD and Breshears DD (1998) Drought-induced shift of a forest-woodland ecotone: Rapid landscape response to climate variation. Proceedings of the National Academy of Sciences USA. 95: 14839–14842

    Article  Google Scholar 

  • Aspinall R (1992) An Inductive Modelling Procedure Based on Bayes’ Theorem for Analysis of Pattern in Spatial Data, International Journal of Geographical Information Systems 6(2):105–121

    Article  Google Scholar 

  • Baker MB Jr (1975) Modeling Management of Ponderosa Pine Forest Resources. In Proceedings of Watershed Management Symposium, ASCE Irrigation and Drainage Division, Logan, UT, August 11–13. pp. 478–493

  • Baker MB Jr (1982) Influence of Clearing Ponderosa Pine on Timing of Snowmelt Runoff. In Proceedings of the Western Snow Conference, Reno NV, April 19–23. pp. 20–26

  • Baker MB Jr (1986) Effects of Ponderosa Pine Treatments on Water Yield in Arizona. Water Resources Research 21(1):67–73

    Article  Google Scholar 

  • Bakkenes M, Alkemade JRM, Ihle F, Leemans R and Latour JB (2002) Assessing effects of forecasted climate change on the diversity and distribution of European higher plants for 2050. Global Change Biology 8: 390–407

    Article  Google Scholar 

  • Bartlein PJ, Prentice IC and Webb T (1986) Climatic response surfaces from pollen data for some eastern North American taxa. Journal of Biogeography 13:35–57

    Article  Google Scholar 

  • Beinat E (2001) Multi-Criteria Analysis for Environmental Management”. Journal of Multi-Criteria Decision Analysis 10:51

    Article  Google Scholar 

  • Charnes A and Cooper W (1961) Management Models and Industrial Applications of Linear Programming. John Wiley and Sons

  • Charnes A and Cooper WW (1961) Management Models and Industrial Applications of Linear Programming. Wiley & Sons, New York

    Google Scholar 

  • Chen K, Blong R and Jacobson C (2001) MCE-RISK: Integrating Multicriteria Evaluation and GIS for Risk Decision-making in Natural Hazards, Environmental Modelling Software 16:387–397

    Article  Google Scholar 

  • Deshingkar P, Bardley PN, Chadwick MJ and Leach G (1997) Adapting to climate change in a Forest-Based Land Use System: A Case Study of Himachal Pradesh, India. Report submitted to the SEI

  • Deng H (1999) Multi-criteria analysis with fuzzy pair wise comparison. International Journal of Approximate Reasoning 21: 215–231

    Article  Google Scholar 

  • Dirnböck T, Hobbs RJ, Lambeck RJ and Caccetta PA (2002) Vegetation distribution in relation to topographically driven processes in southwestern Australia. Appl Veg Sci 5:147–158

    Article  Google Scholar 

  • Ellenberg H (1988) Floristic changes due nitrogen deposition in central Europe. In: Nilsson J., Grennfelt P. (eds.). Critical loads for sulphur and nitrogen, Report from a workshop held at Skokloster, Sweden 19–24 March, 1988. Miljörapport/Nord 15 Nordic Council of Ministers, Kopenhagen.

    Google Scholar 

  • Frescino TS, Edwards Jr TC and Moisen GG (2001) Modeling spatially explicit forest structural attributes using Generalised Additive Models. Journal of Vegetation Science 12:15–26

    Google Scholar 

  • Gottfried MD, Rogers RR and Curry RK (2004) First record of Late Cretaceous coelacanths from Madagascar. In: Arratia G, Wilson M.V.H, Cloutier R, editors. Recent advances in the origin and early radiation of vertebrates. Dr Pfeil Verlag; Munich: 2004. 687-691 p

    Google Scholar 

  • Gonzalez P (2001) Desertification and a shift of forest species in the West African Sahel. Climate Res 17: 217–228

    Article  Google Scholar 

  • Heikkinon RK and Birks HJB (1996) Spatial and environmental components of variation in the distribution patterns of sub-arctic plant species at Kovo, N. Finland — a case study at the mesoscale level. Ecography 19:341–351

    Google Scholar 

  • Huntley B, Berry PM, Cramer W and McDonald AP (1995) Modelling present and potential future ranges of some European higher plants using climate response surfaces. Journal of Biogeography 967–1001

  • Huston MA (1994) Biological Diversity: The Coexistence of Species on Changing Landscape. Cambridge University Press, Cambridge 708 p

    Google Scholar 

  • IPCC (2006) Climate Change, http://www1.ipcc.ch/ipccreports/methodology-reports.htm Accessed on 5 November 2009

  • Jensen ME and Everett R (1993) An overview of ecosystem management principles. pp. 9–18 in Jensen M.E. and P.S. Bourgeron (eds.) Eastside Forest Ecosystem Health Assesment: vol. II Ecosystem Management: Principles and Applications. USDA Forest Service

  • Kapetsky JM and Aguilar-Manjarrez J (2007) Geographic Information Systems, Remote Sensing and Mapping for the Development and Management of Marine Aquaculture, FAO, Rome, 97–102

    Google Scholar 

  • Kirschbaum, MUF, Cannell MGR, Cruz RVO, Galinski W and Cramer WP (1996) Climate change impacts on forests. In: Climate Change 1995, Impacts, Adaptation and Mitigation of Climate Change: Scientific-Technical Analyses, Cambridge University Press, Cambridge

    Google Scholar 

  • Louis R, Iverson I, Schwartz MW, Anantha M Prasad (2004) Potential colonization of newly available tree-species habitat under climate change: an analysis for five eastern US species, Landscape Ecology 19: 787–799

    Article  Google Scholar 

  • Malczewski J (1999) GIS and Multi-Criteria Decision Analysis, John Wiley and Sons, New York

    Google Scholar 

  • Midgley GF, Hannah L, Millar D, Ruther-ford MC and Powrie LW (2002) Assessing the vulnerability of species richness to anthropogenic climate change in a biodiversity hotspot. Global Ecology and Biogeography 11: 445–451

    Article  Google Scholar 

  • McDaniels TL, Gregory RS and Fields D (1999) Democratizing Risk Management: Successful public involvement in local water management decisions. Risk Analysis 19(3):497–510

    Google Scholar 

  • Moisen GG Edwards TCJ (1999) Use of generalized linear models and digital data in a forest inventory of Utah. Journal of Agricultural, Biological and Environmental Statistics 4(4): 372–390

    Article  Google Scholar 

  • Nute D, Rosenberg, G, Nath S, Verma B, Rauscher HM, Twery MJ and Grove M (2000) Goals and goal orientation in decision support systems for ecosystem management. Computers and Electronics in Agriculture 27:355–375

    Article  Google Scholar 

  • Penuelas J and Boada M (2003) A global changeinduced biome shift in the Montseny Mountains (NE Spain). Global Change Biology 9: 131–140

    Article  Google Scholar 

  • Pomerol JC and Sergio BR (2000) Multicriterion Decision in Management, Principles and Practice. Kluwer Academic Publishers, London

    Google Scholar 

  • Rauscher HM (1999) Ecosystem management decision support for federal forests in the United States: A review. Forest Ecology and Management 114:173–197

    Article  Google Scholar 

  • Ravindranath NH, Joshil, NV, Sukumar R and Saxena A (2006) Impact of climate change on forest in India. Current Science 90(3):354–361

    Google Scholar 

  • Saran S, Ghosh S, Shrivastava G, Roy PS, Talukdar G and Prasad N (2003) Spatial Decision Support System for Biodiversity Conservation Prioritization: A Case Study for Web Based Approach. Asian Journal of Geoinformatics 4(1):21–30

    Google Scholar 

  • Schlesinger WH (1991) Biogeochemistry: An analysis of global change. Academic Press, San Diego. pp. 443

    Google Scholar 

  • Saaty TL (1980) The Analytic Hierarchy Process: Planning, Priority Setting, Resource Allocation, McGraw-Hill Comp., New York 54–55

    Google Scholar 

  • Singh JS, Rawat YS and Chaturvedi OP (1983) Replacement of oak forest with pine in the Himalaya affects the nitrogen cycle. Nature 311:54–56

    Article  Google Scholar 

  • Singh JS and Singh SP (1986) Structure and function of central Himalayan Oak forests. Proceedings of Indian Academic of Science 96: 156–189

    Google Scholar 

  • Singh JS and Singh SP (1992) Forest of Himalaya; Structure, functioning and impact of man, Gyanodaya Prakashan, Nainital, India

    Google Scholar 

  • Sukumar R, Ramesh R, Pant RK and Rajagopalan G (1993) A d13C record of late Quaternary climate change from tropical peats in southern India. Nature 364:703–706

    Article  Google Scholar 

  • Sukumar R, Suresh HS and Ramesh R (1995) Climate change and its impacts on tropical montane ecosystems in southern India. Journal of Biogeography 22:533–536

    Article  Google Scholar 

  • Stockwell DRB and Peters D (1999) The GARP Modeling System: problems and solutions to automated spatial prediction. International Journal of Geographical Information Science 13(2)143–158

    Article  Google Scholar 

  • Tecle A and Lucien (1993) Concepts of Multi-Criterion Decision Making.” Chapter 3 in H.P. Nachtnebel (ed.) Decision Support System in Water Resource Management. Paris, France: UNESCO Press

    Google Scholar 

  • Thuiller W, Lavorel S, Araújo MB (2005) Niche properties and geographic extent as predictors of species sensitivity to climate change. Global Ecology and Biogeography 14:347–357

    Article  Google Scholar 

  • Troup RS (1921) The silviculture of Indian trees Clarendon Press, Oxford, UK pp. 1195

    Google Scholar 

  • Upreti N, Tewari JC and Singh SP (1985) The oak forests of Kumaun Himalaya (India): Composition, Diversity, and regeneration. Mountain Research and Development 5:163–174

    Article  Google Scholar 

  • Woodward FI (1987) Climate and Plant Distribution. New York: Cambridge University Press. 174 p

    Google Scholar 

  • Zeleny M (1982) Multiple Criteria Decision Making. McGraw-Hill Book Company, New York

    Google Scholar 

Download references

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Saran, S., Joshi, R., Sharma, S. et al. Geospatial modeling of Brown oak (Quercus semecarpifolia) habitats in the Kumaun Himalaya under climate change scenario. J Indian Soc Remote Sens 38, 535–547 (2010). https://doi.org/10.1007/s12524-010-0038-2

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  • DOI: https://doi.org/10.1007/s12524-010-0038-2

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