Skip to main content

Advertisement

SpringerLink
Log in

Land use and climate change impacts on distribution of plant species of conservation value in Eastern Ghats, India: a simulation study

  • Published:
Environmental Monitoring and Assessment Aims and scope Submit manuscript

Abstract

Effective monitoring of the current status of species distributions and predicting future distributions are very important for conservation practices at the ecosystem and species levels. The human population, land use, and climate are important factors that influence the distributions of species. Even though future simulations have many uncertainties, such studies can provide a means of obtaining species distributions, range shifts, and food production and help mitigation and adaptation planning. Here, we simulate the population, land use/land cover and species distributions in the Eastern Ghats, India. A MaxEnt species distribution model was used to simulate the potential habitats of a group of endemic (28 species found in this region) and rare, endangered, and threatened (RET) (22 species found in this region) plant species on the basis of IPCC AR5 scenarios developed for 2050 and 2070. Simulations of populations in 2050 indicate that they will increase at a rate of 1.12% relative to the base year, 2011. These increases in population create a demand for more land for settlement and food productions. Land use land cover (LULC) simulations show an increase in built-up land from 3665.00 km2 in 2015 to 3989.56 km2 by 2050. There is a minor increase of 0.04% in the area under agriculture in 2050 compared with 2015. On the other hand, the habitat simulations show that the combined effects of climate and land use change have a greater influence on the decline of potential distributions of species. Climate change and the prevailing rate of LULC change will reduce the extents of the habitats of endemic and RET species (~ 60% and ~ 40%, respectively). The Eastern Ghats have become extensively fragmented due to human activities and have become a hotspot of endemic and RET species loss. Climate and LULC change will enhance the species loss and ecosystem services.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  • Abolmaali, S. M., Tarkesh, M., & Bashari, H. (2018). MaxEnt modeling for predicting suitable habitats and identifying the effects of climate change on a threatened species, Daphne mucronata, in central Iran. Ecological Informatics, 43, 116–123. https://doi.org/10.1016/j.ecoinf.2017.10.002.

    Article  Google Scholar 

  • Alexandratos, N., & Bruinsma, J. (2012). World agriculture towards 2030/2050: The 2012 revision, ESA working paper 12–03. Rome: FAO.

    Google Scholar 

  • Arsanjani, J. J., Helbich, M., Kainz, W., & Boloorani, A. D. (2013). Integration of logistic regression, Markov chain and cellular automata models to simulate urban expansion. International Journal of Applied Earth Observation and Geoinformation, 21, 265–275.

    Article  Google Scholar 

  • Balaguru, B., John britto, S. J. S., Nagamurugan, N., Natarajan, D., & Soosairaj, S. (2006). Identifying conservation priority zones for effective management of tropical forests in Eastern Ghats of India. Biodiversity and Conservation, 15, 1529–1543. https://doi.org/10.1007/s10531-004-6678-1.

    Article  Google Scholar 

  • Bentsen, M., Bethke, I., Debernard, J. B., Iversen, T., Kirkevåg, A., et al. (2013). The Norwegian earth system model, NorESM1-M—Part 1: Description and basic evaluation of the physical climate. Geoscientific Model Development, 6, 687–720. https://doi.org/10.5194/gmd-6-687-2013.

    Article  Google Scholar 

  • Berkes, F. (2007). Community-based conservation in a globalized world. PNAS, 104(39), 15188–15193. https://doi.org/10.1073/pnas.0702098104.

    Article  Google Scholar 

  • Browder, J. O. (2002). The urban-rural interface: Urbanization and tropical forest cover change. Urban Ecosystem, 6(21). https://doi.org/10.1023/A:1025962512653.

  • Cardinale, B. J., Duffy, J. E., Gonzalez, A., Hooper, D. U., Perrings, C., Venail, P., Narwani, A., Mace, G. M., Tilman, D., Wardle, D. A., Kinzig, A. P., Daily, G. C., Loreau, M., Grace, J. B., Larigauderie, A., Srivastava, D. S., & Naeem, S. (2012). Biodiversity loss and its impact on humanity. Nature, 486, 59–67.

    Article  CAS  Google Scholar 

  • CBD. (2009). Secretariat of the Convention on Biological Diversity. Connecting Biodiversity and Climate Change Mitigation and Adaptation: Report of the Second Ad Hoc Technical Expert Group on Biodiversity and Climate Change. Montreal, Technical Series No. 41, pp 126.

  • Ceballos, G., Ehrlich, P. R., Barnosky, A. D., García, A., Pringle, R., & Palmer, T. M. (2015). Accelerated modern human-induced species losses: Entering the sixth mass extinction. Science Advances, 1, e1400253. https://doi.org/10.1126/sciadv.1400253.

    Article  Google Scholar 

  • Census. (2001). http://www.censusindia.gov.in/2011-common/census_data_2001.html. Accessed 16 Aug 2018.

  • Census. (2011). http://censusindia.gov.in/. Accessed 16 Aug 2018.

  • Chitale, V. S., Behera, M. D., & Roy, P. S. (2014). Future of endemic flora of biodiversity hotspots in India. PLoS One, 9, e115264. https://doi.org/10.1371/journal.pone.0115264.

    Article  CAS  Google Scholar 

  • Collins, W. J., Bellouin, N., Doutriaux-Boucher, M., Gedney, N., et al. (2011). Development and evaluation of an earth-system model—HadGEM2. Geoscientific Model Development, 4, 1051–1075. https://doi.org/10.5194/gmd-4-1051-2011.

    Article  Google Scholar 

  • Congalton, R. G. (1991). A review of assessing the accuracy of classifications of remotely sensed data. Remote Sensing of Environment, 37(1), 35–46. https://doi.org/10.1016/0034-4257(91)90048-B.

    Article  Google Scholar 

  • Corlett, R. T. (2016). Plant diversity in a changing world: Status, trends, and conservation needs. Plant Diversity, 38(1), 10–16. https://doi.org/10.1016/j.pld.2016.01.001.

    Article  Google Scholar 

  • d’Amoura, C. B., Reitsma, F., Baiocchi, G., Barthel, S., et al. (2017). Future urban land expansion and implications for global croplands. PNAS, 114(13), 8939–8944. https://doi.org/10.1073/pnas.1606036114.

    Article  CAS  Google Scholar 

  • d’Annunzio, R., Sandker, M., Finegold, Y., & Min, Z. (2015). Projecting global forest area towards 2030. Forest Ecology and Management, 352, 124–133. https://doi.org/10.1016/j.foreco.2015.03.014.

    Article  Google Scholar 

  • Deb, J. C., Phinn, S., Butt, N., & McAlpine, C. A. (2017). The impact of climate change on the distribution of two threatened dipterocarp trees. Ecology and Evolution, 7, 2238–2248. https://doi.org/10.1002/ece3.2846.

    Article  Google Scholar 

  • deFries, R. S., Rudel, T., Uriarte, M., & Hansen, M. (2010). Deforestation driven by urban population growth and agricultural trade in the twenty-first century. Nature Geoscience, 3, 178–181. https://doi.org/10.1038/ngeo756.

    Article  CAS  Google Scholar 

  • Dufresne, J. L., Foujols, M. A., Denvil, S., Caubel, A., Marti, O., et al. (2013). Climate change projections using the IPSL-CM5 earth system model: From CMIP3 to CMIP5. Climate Dynamics, 40, 2123–2165. https://doi.org/10.1007/s00382-012-1636-1.

    Article  Google Scholar 

  • Dyderski, M. K., Paź, S., Frelich, L. E., & Jagodziński, A. M. (2018). How much does climate change threaten European forest tree species distributions? Global Change Biology, 24, 1150–1163. https://doi.org/10.1111/gcb.13925.

    Article  Google Scholar 

  • Eberhardt, L. L. (1987). Population projections from simple models. Journal of Applied Ecology, 24, 103–118.

    Article  Google Scholar 

  • Elith, J., & Leathwick, J. R. (2009). Species distribution models: Ecological explanation and prediction across space and time. Annual Review of Ecology, Evolution, and Systematics, 40, 677–697.

    Article  Google Scholar 

  • Elith, J., Phillips, S. J., Hastie, T., Dudík, M., Chee, Y. E., & Yates, C. J. (2011). A statistical explanation of MaxEnt for ecologists. Diversity and Distributions, 17, 43–57. https://doi.org/10.1111/j.1472-4642.2010.00725.x.

    Article  Google Scholar 

  • Elmhagen, B., Eriksson, O., & Lindborg, R. (2015). Implications of climate and land-use change for landscape processes, biodiversity, ecosystem services, and governance. Ambio, 44, 1–5. https://doi.org/10.1007/s13280-014-0596-6.

    Article  Google Scholar 

  • FAO. (2017). The future of food and agriculture: Trends and challenges. Rome.

  • Feng, Y., Ma, K. M., Zhang, Y. X., & Guo, Q. R. (2011). Effects of slope position on species abundance distribution of Quercus wutaishanica community in Dongling Mountain of Beijing. Chinese Journal of Applied Ecology, 30, 2137–2144.

    Google Scholar 

  • Foley, J. A., DeFries, R., Asner, G. P., Barford, C., et al. (2005). Global consequences of land use. Science, 570–574.

  • Forsyth, T. (2017). Population and natural resources. In D. Richardson, N. Castree, M. F. Goodchild, A. Kobayashi, W. Liu, & R. A. Marston (Eds.), International Encyclopedia of Geography: People, the Earth, Environment and Technology. https://doi.org/10.1002/9781118786352.wbieg0041.

    Chapter  Google Scholar 

  • Gent, P. R., Danabasoglu, G., Donner, L. J., Holland, M. M., Hunke, E. C., et al. (2011). The community climate system model version 4. Journal of Climate, 24, 4973–4991. https://doi.org/10.1175/2011JCLI4083.1.

    Article  Google Scholar 

  • Gerstner, K., Dormann, C. F., Stein, A., Manceur, A. M., & Seppelt, R. (2014). Effects of land use on plant diversity: A global meta-analysis. Journal of Applied Ecology, 51, 1690–1700. https://doi.org/10.1111/1365-2664.12329.

    Article  Google Scholar 

  • Giam, X., Bradshaw, C. J. A., Tan, H. T. W., & Sodhi, N. S. (2010). Future habitat loss and the conservation of plant biodiversity. Biological Conservation, 143, 1594–1602. https://doi.org/10.1016/j.biocon.2010.04.019.

    Article  Google Scholar 

  • Hanski, I. (2011). Habitat loss, the dynamics of biodiversity, and a perspective on conservation. Ambio, 40(3), 248–255.

    Article  Google Scholar 

  • Hengl, T., de Jesus, J. M., Heuvelink, G. B. M., Gonzalez, M. R., Kilibarda, M., et al. (2017). SoilGrids250m: Global gridded soil information based on machine learning. PLoS One, 12, e0169748. https://doi.org/10.1371/journal.pone.0169748.

    Article  CAS  Google Scholar 

  • Hughes, J. B., Daily, G. C., & Ehrlich, P. R. (1998). The loss of population diversity and why it matters. In P. H. Raven (Ed.), Nature and Human Society (pp. 71–83). Washington, D.C.: National Academy Press.

    Google Scholar 

  • IPCC. (2014). Climate change 2014: Synthesis report. In Core Writing Team, R. K. Pachauri, & L. A. Meyer (Eds.), 151 pp. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Geneva: IPCC.

    Google Scholar 

  • IUCN. (2012). IUCN red list categories and criteria: Version 3.1 (2nd ed. , iv + 32 pp.). Gland: IUCN.

    Google Scholar 

  • Jain, S. K., & Rao, R. R. (Eds.). (1983). An assessment of threatened plants of India (pp. 1–334). Howrah: Botanical Survey of India.

    Google Scholar 

  • Jayakumar, S., Arockiasamy, D. I., & John Britto, S. (2002). Conserving forests in the eastern Ghats of Tamil Nadu through remote sensing and GIS: A case study in Kolli Hills. Current Science, 82(10), 1259–1267.

    Google Scholar 

  • Kale, M. P., Chavan, M., Pardeshi, S., Joshi, C., Verma, P. A., Roy, P. S., Srivastav, S. K., Srivastava, V. K., Jha, A. K., Chaudhari, S., Giri, Y., & Krishna Murthy, Y. V. N. (2016). Land-use and land-cover change in Western Ghats of India. Environmental Monitoring and Assessment, 188, 188–387. https://doi.org/10.1007/s10661-016-5369-1.

    Article  Google Scholar 

  • Kannaiyan, S. (2015). Biodiversity wealth of Eastern Ghats. ENVIS Newsletter. http://eptrienvis.nic.in/All%20PDF%20Files/Biodiversity%20wealth%20of%20Eastern%20ghats.pdf. Accessed 14 January 2019.

  • Kavzoglu, T., & Mather, P. M. (2010). The use of back propagating artificial neural networks in land cover classification. Indian Journal of Remote Sensing, 24(23), 4907–4938. https://doi.org/10.1080/0143116031000114851.

    Article  Google Scholar 

  • Mani, M. S. (1974). The vegetation and phytogeography of the Eastern Ghats. In M. S. Mani (Ed.), Ecology and biogeography in India. The Hague: Junk W b.v., Publishers.

    Chapter  Google Scholar 

  • Manish, K., Telwala, Y., Nautiyal, D. C., & Pandit, M. K. (2016). Modelling the impacts of future climate change on plant communities in the Himalaya: A case study from eastern Himalaya, India. Modeling Earth Systems and Environment, 2, 92–12. https://doi.org/10.1007/s40808-016-0163-1.

    Article  Google Scholar 

  • Martin, G. M., Bellouin, N., Collins, W. J., Culverwell, I. D., Halloran, P. R., et al. (2011). The HadGEM2 family of Met Office Unified Model climate configurations. Geoscientific Model Development, 4, 723–757. https://doi.org/10.5194/gmd-4-723-2011.

    Article  Google Scholar 

  • Masui, T., Matsumoto, K., Hijioka, Y., Kinoshita, T., Nozawa, T., et al. (2011). An emission pathway for stabilization at 6 W m−2 radiative forcing. Climatic Change, 109, 59. https://doi.org/10.1007/s10584-011-0150-5.

    Article  CAS  Google Scholar 

  • Ministry of Environment and Forests (MoEF). (2008). National biodiversity action plan, 78 pp. New Delhi: Government of India. MoEF, Paryavaran Bhavan.

    Google Scholar 

  • Murphy, D. M., & Ravishankara, A. R. (2018). Trends and patterns in the contributions to cumulative radiative forcing from different regions of the world. PNAS, 115(52), 13192–13197. https://doi.org/10.1073/pnas.1813951115.

    Article  CAS  Google Scholar 

  • Naidu, M. T., & Kumar, O. A. (2016). Tree diversity, stand structure, and community composition of tropical forests in Eastern Ghats of Andhra Pradesh, India. Journal of Asia-Pacific Biodiversity, 9(3), 328–334. https://doi.org/10.1016/j.japb.2016.03.019.

    Article  Google Scholar 

  • NBSS&LUP. (2002). https://www.nbsslup.in/. Accessed 24 November 2018.

  • Oliver, T. H., & Morecroft, M. D. (2014). Interactions between climate change and land use change on biodiversity: Attribution problems, risks, and opportunities. WIREs Climate Change, 5, 317–335. https://doi.org/10.1002/wcc.271.

    Article  Google Scholar 

  • Phillips, S. J., Anderson, R. P., & Schapired, R. E. (2006). Maximum entropy modeling of species geographic distributions. Ecological Modelling, 190, 231–259. https://doi.org/10.1016/j.ecolmodel.2005.03.026.

    Article  Google Scholar 

  • Pijanowski, B. C., Brown, D. G., Shellito, B. A., & Manik, G. A. (2002). Using neural networks and GIS to forecast land use changes: A land transformation model. Computers, Environment and Urban Systems, 26(6), 553–575. https://doi.org/10.1016/S0198-9715(01)00015-1.

    Article  Google Scholar 

  • Pijanowski, B. C., Tayyebi, A., Doucette, J., Pekin, B. K., Braun, D., & Plourde, J. (2014). A big data urban growth simulation at a national scale: Configuring the GIS and neural network based land transformation model to run in a high performance computing (HPC) environment. Environmental Modelling & Software, 51, 250–268. https://doi.org/10.1016/j.envsoft.2013.09.015.

    Article  Google Scholar 

  • Pontius, R. G. (2000). Quantification error versus location error in comparison of categorical maps. Photogrammetric Engineering and Remote Sensing, 66(8), 1011–1016.

    Google Scholar 

  • Prasad, V. K., Kant, Y., & Badarinath, K. V. S. (2001). CENTURY ecosystem model application for quantifying vegetation dynamics in shifting cultivation areas: A case study from Rampa Forests, Eastern Ghats (India). Ecological Research, 16, 497–507. https://doi.org/10.1046/j.1440-1703.2001.00412.x.

    Article  CAS  Google Scholar 

  • Pullaiah, T., & Rao, M. (2002). Flora of Eastern Ghats, Hill Ranges of South East India (Vol. I). New Delhi: Regency Publications.

    Google Scholar 

  • Puyravaud, J., Davidar, P., & Laurance, W. F. (2010). Cryptic loss of India’s native forests. Science, 329(5987), 32. https://doi.org/10.1126/science.329.5987.32-b.

    Article  CAS  Google Scholar 

  • Ramachandran, A., Radhapriya, P., Jayakumar, S., Dhanya, P., & Geetha, R. (2016). Critical analysis of forest degradation in the southern Eastern Ghats of India: Comparison of satellite imagery and soil quality index. PLoS One, 11(1), e0147541 https://doi.org/10.1371/journal.pone.0147541.

    Article  Google Scholar 

  • Ramesh, S., & Kaplana, K. (2015). Ecological integrity and environmental protection for Vijayawada region—Scattered Eastern Ghats. International Journal of Sustainable Built Environment, 4(1), 109–116. https://doi.org/10.1016/j.ijsbe.2015.03.003.

    Article  Google Scholar 

  • Rao, M. J., Prasad, C. H., Mohammad, M., & Kakkassery, A. I. (2013). Bauxite mining in Eastern Ghats of Andhra Pradesh: Possible environmental implications and measures for environmentally friendly mining. International Journal of Science and Research, 5(4), 1434–1437.

    Google Scholar 

  • Rawat, G. S. (1997). Conservation status of forests and wildlife in the Eastern Ghats, India. Environmental Conservation, 24(4), 307–315.

    Article  CAS  Google Scholar 

  • Remya, K., Ramachandran, A., & Jayakumar, S. (2015). Predicting the current and future suitable habitat distribution of Myristica dactyloides Gaertn. using MaxEnt model in the Eastern Ghats, India. Ecological Engineering, 82, 184–188.

    Article  Google Scholar 

  • Reshma, M. R., Roy, P. S., Chakravarthi, V., Sanjay, J., & Joshi, P. K. (2018). Long-term land use and land cover changes (1920–2015) in Eastern Ghats, India: Pattern of dynamics and challenges in plant species conservation. Ecological Indicators, 85, 21–36. https://doi.org/10.1016/j.ecolind.2017.10.012.

    Article  Google Scholar 

  • Riahi, K., Rao, S., Krey, V., Cho, C., et al. (2011). RCP 8.5: A scenario of comparatively high greenhouse gas emissions. Climatic Change, 109, 33. https://doi.org/10.1007/s10584-011-0149-y.

    Article  CAS  Google Scholar 

  • Ripple, W. J., Wolf, C., Newsome, T. M., Galetti, M., & 15,368 scientist signatories from 184 countries. (2017). World scientists’ warning to humanity: A second notice. BioScience, 67(12), 1026–1028. https://doi.org/10.1093/biosci/bix125.

    Article  Google Scholar 

  • Rounsevell, M. D. A., Reginster, I., Araújo, M. B., Carter, T. R., et al. (2006). A coherent set of future land use change scenarios for Europe. Agriculture, Ecosystems & Environment, 114(1), 57–68. https://doi.org/10.1016/j.agee.2005.11.027.

    Article  Google Scholar 

  • Roy, P. S., Kushwaha, S. P. S., Murthy, M. S. R., Roy, A., Kushwaha, D., et al. (2012). Biodiversity characterisation at landscape level: National Assessment, 140 pp. Dehradun: Indian Institute of Remote Sensing.

    Google Scholar 

  • Salghuna, N. N., Prasad, P. R. C., & Kumari, J. A. (2018). Assessing the impact of land use and land cover changes on the remnant patches of Kondapalli Reserve Forest of the Eastern Ghats, Andhra Pradesh, India. The Egyptian Journal of Remote Sensing and Space Science. https://doi.org/10.1016/j.ejrs.2018.01.005.

  • Schleuning, M., Fründ, J., Schweiger, O., Welk, E., Albrecht, J., Albrecht, M., Beil, M., Benadi, G., Blüthgen, N., Bruelheide, H., Böhning-Gaese, K., Dehling, D. M., Dormann, C. F., Exeler, N., Farwig, N., Harpke, A., Hickler, T., Kratochwil, A., Kuhlmann, M., Kühn, I., Michez, D., Mudri-Stojnić, S., Plein, M., Rasmont, P., Schwabe, A., Settele, J., Vujić, A., Weiner, C. N., Wiemers, M., & Hof, C. (2016). Ecological networks are more sensitive to plant than to animal extinction under climate change. Nature Communications, 7, 13965. https://doi.org/10.1038/ncomms13965.

    Article  CAS  Google Scholar 

  • Schmidt, G. A., Kelley, M., Nazarenko, L., Ruedy, R., Russell, G. L., et al. (2014). Configuration and assessment of the GISS model E2 contributions to the CMIP5 archive. Journal of Advances in Modeling Earth Systems, 6, 141–184. https://doi.org/10.1002/2013MS000265.

    Article  Google Scholar 

  • Segan, D. B., Murray, K. A., & Watson, J. E. M. (2016). A global assessment of current and future biodiversity vulnerability to habitat loss–climate change interactions. Global Ecology and Conservation, 5, 12–21. https://doi.org/10.1016/j.gecco.2015.11.002.

    Article  Google Scholar 

  • Seto, K. C., Güneralp, B., & Hutyra, L. R. (2012). Global forecasts of urban expansion to 2030 and direct impacts on biodiversity and carbon pools. PNAS, 109(40), 16083–16088. https://doi.org/10.1073/pnas.1211658109.

    Article  Google Scholar 

  • Shimono, A., Zhou, H., Shen, H., Hirota, M., Ohtsuka, T., & Tang, Y. (2010). Patterns of plant diversity at high altitudes on the Qinghai-Tibetan Plateau. Journal of Plant Ecology, 3, 1–7. https://doi.org/10.1093/jpe/rtq002.

    Article  Google Scholar 

  • Sirami, C., Caplat, P., Popy, S., Clamens, A., et al. (2017). Impacts of global change on species distributions: Obstacles and solutions to integrate climate and land use. Global Ecology and Biogeography, 26, 385–394. https://doi.org/10.1111/geb.12555.

    Article  Google Scholar 

  • Souza, D. M., Teixeira, R. F., & Ostermann, O. P. (2015). Assessing biodiversity loss due to land use with life cycle assessment: Are we there yet? Global Change Biology, 21, 32–47. https://doi.org/10.1111/gcb.12709.

    Article  Google Scholar 

  • Thomson, A. M., Calvin, K. V., Smith, S. J., Kyle, G. P., Volke, A., et al. (2011). RCP4.5: A pathway for stabilization of radiative forcing by 2100. Climatic Change, 109, 77. https://doi.org/10.1007/s10584-011-0151-4.

    Article  CAS  Google Scholar 

  • Tilman, D., & Lehman, C. (2001). Human-caused environmental change: Impacts on plant diversity and evolution. PNAS, 98, 5433–5440. https://doi.org/10.1073/pnas.091093198.

    Article  CAS  Google Scholar 

  • Tsarouchi, G. M., Mijic, A., Moulds, S., & Buytaert, W. (2014). Historical and future land-cover changes in the upper Ganges basin of India. International Journal of Remote Sensing, 35, 3150–3176. https://doi.org/10.1080/01431161.2014.903352.

    Article  Google Scholar 

  • Tyler, T., Herbertsson, L., Olsson, P. A., Fröberg, L., et al. (2017). Climate warming and land-use changes drive broad-scale floristic changes in southern Sweden. Global Change Biology, 24, 2607–2621. https://doi.org/10.1111/gcb.14031.

    Article  Google Scholar 

  • United Nations, Department of Economic and Social Affairs, Population Division (UN DESA). (2017). World population prospects: The 2017 revision. New York: United Nations.

    Google Scholar 

  • Vaidyanathan, G. (2018). Science and culture: Imagining a climate-change future, without the dystopia. PNAS, 115(51), 12832–12835. https://doi.org/10.1073/pnas.1819792116.

    Article  CAS  Google Scholar 

  • van Vuuren, D. P., Stehfest, E., den Elzen, M. G. J., Kram, T., van Vliet, J., et al. (2011). RCP2.6: Exploring the possibility to keep global mean temperature increase below 2°C. Climatic Change, 109, 95. https://doi.org/10.1007/s10584-011-0152-3.

    Article  CAS  Google Scholar 

  • Venter, O., Sanderson, E. W., Magrach, A., Allan, J. R., Beher, J., Jones, K. R., Possingham, H. P., Laurance, W. F., Wood, P., Fekete, B. M., Levy, M. A., & Watson, J. E. (2016). Sixteen years of change in the global terrestrial human footprint and implications for biodiversity conservation. Nature Communications, 7, 12558. https://doi.org/10.1038/ncomms12558.

    Article  CAS  Google Scholar 

  • Watanabe, M., Suzuki, T., O’Ishi, R., Komuro, Y., Watanabe, S., Emori, S., et al. (2010). Improved climate simulation by MIROC5: Mean states, variability, and climate sensitivity. Journal of Climate, 23, 6312–6335. https://doi.org/10.1175/2010JCLI3679.1.

    Article  Google Scholar 

  • Watanabe, S., Hajima, T., Sudo, K., Nagashima, T., Takemura, T., et al. (2011). MIROC-ESM 2010: Model description and basic results of CMIP5-20c3m experiments. Geoscientific Model Development, 4, 845–872. https://doi.org/10.5194/gmdd-4-1063-2011.

    Article  Google Scholar 

  • Wieczynski, D. J., Boyle, B., Buzzard, V., Duran, S. M., Henderson, A. N., Hulshof, C. M., Kerkhoff, A. J., McCarthy, M., Michaletz, S. T., Swenson, N. G., Asner, G. P., Bentley, L. P., Enquist, B. J., & Savage, V. M. (2018). Climate shapes and shifts functional biodiversity in forests worldwide. PNAS, 116(2), 587–592. https://doi.org/10.1073/pnas.1813723116.

    Article  CAS  Google Scholar 

  • Wu, T., Song, L., Li, W., Wang, Z., et al. (2014). An overview of BCC climate system model development and application for climate change studies. Journal of Meteorological Research, 28, 34–56. https://doi.org/10.1007/s13351-014-3041-7.

    Article  Google Scholar 

  • Yukimoto, S., Adachi, Y., Hosaka, M., Sakami, T., Yoshimura, H., et al. (2011). A new global climate model of the Meteorological Research Institute: MRI-CGCM3—Model description and basic performance. Journal of the Meteorological Society of Japan, 90A, 23–64. https://doi.org/10.2151/jmsj.2012-A02.

    Article  Google Scholar 

  • Zeng, X. H., Zhang, W. J., Song, Y. G., & Shen, H. T. (2014). Slope aspect and slope position have effects on plant diversity and spatial distribution in the hilly region of Mount Taihang, North China. Journal of Food, Agriculture and Environment, 12, 391–397.

    Google Scholar 

Download references

Acknowledgments

The authors are thankful to the Ministry of Earth Sciences, Government of India, for a research grant. Authors are thankful to all the data providers such as openstreetmap, USGS earth explorer, Registrar General & Census Commissioner, India, and IPCC. PSR is also thankful to the National Academy of Science (NASI) for a Platinum Jubilee Fellowship. PKJ is also thankful to the Department of Science & Technology—Promotion of University Research and Scientific Excellence (DST-PURSE) of Jawaharlal Nehru University for research support.

Author information

Authors and Affiliations

  1. Centre for Earth, Ocean and Atmospheric Sciences, University of Hyderabad, Hyderabad, 500046, India

    Reshma M. Ramachandran & Vishnubhotla Chakravarthi

  2. Innovation Systems for the Dry lands, ICRISAT, Pathancheru, Hyderabad, 502 324, India

    Parth Sarathi Roy

  3. School of Environmental Sciences, Jawaharlal Nehru University, New Delhi, 110067, India

    Pawan Kumar Joshi

  4. Indian Institute of Tropical Meteorology, Centre for Climate Change Research, Pashan, Pune, 411008, India

    J. Sanjay

Authors
  1. Reshma M. Ramachandran
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Parth Sarathi Roy
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Vishnubhotla Chakravarthi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Pawan Kumar Joshi
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. J. Sanjay
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Reshma M. Ramachandran.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

ESM 1

(DOCX 2220 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ramachandran, R.M., Roy, P.S., Chakravarthi, V. et al. Land use and climate change impacts on distribution of plant species of conservation value in Eastern Ghats, India: a simulation study. Environ Monit Assess 192, 86 (2020). https://doi.org/10.1007/s10661-019-8044-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10661-019-8044-5

Keywords

Search

Navigation