Predicting climate change impacts on the distribution of the threatened Garcinia indica in the Western Ghats, India

Akhter, 2017, Habitat distribution modelling to identify areas of high conservation value under climate change for Mangifera sylvatica Roxb. of Bangladesh, Land Use Pol., 60, 223, 10.1016/j.landusepol.2016.10.027 Allouche, 2006, Assessing the accuracy of species distribution models: prevalence, kappa and the true skill statistic (TSS), J. Appl. Ecol., 43, 1223, 10.1111/j.1365-2664.2006.01214.x Anderegg, 2015, Tree mortality from drought, insects, and their interactions in a changing climate, New Phytol., 208, 674, 10.1111/nph.13477 Bedia, 2011, Predicting plant species distribution across an Alpine rangeland in northern Spain: a comparison of probabilistic methods, Appl. Veg. Sci., 14, 415, 10.1111/j.1654-109X.2011.01128.x Chandran, 2010, Ecology of the Swampy Relic forests of Kathalekan from Central Western Ghats, India. Bioremediation, biodiversity and bioavailability, Glob. Sci. Book J., 4, 54 Chen, 2011, Rapid range shifts of species associated with high levels of climate warming, Science, 333, 1024, 10.1126/science.1206432 Chethana, 2013, Reconciling natural history and species ecology: Myristica beddomei (Myristicaceae) in the Western Ghats, India. Trop. Conserv. Sci., 6, 663, 10.1177/194008291300600506 Christensen, J.H., Coauthors, 2007. Regional climate projections. Climate Change 2007: The Physical Science Basis. In: S. Solomon et al., (Eds.), Cambridge University Press, pp. 847–940. Cincotta, 2000, Human population in the biodiversity hotspots, Nature, 404, 990, 10.1038/35010105 Coetzee, 2009, Ensemble models predict important bird areas in southern Africa will become less effective for conserving endemic birds under climate change, Glob. Ecol. Biogeogr., 18, 701, 10.1111/j.1466-8238.2009.00485.x Dahanukar, 2004, Distribution, endemism and threat status of freshwater fishes in the Western Ghats of India, J. Biogeogra., 31, 123, 10.1046/j.0305-0270.2003.01016.x Dale, 2001, Climate change and forest disturbances, Bioscience, 51, 723, 10.1641/0006-3568(2001)051[0723:CCAFD]2.0.CO;2 Dawson, 2011, Beyond predictions: biodiversity conservation in a changing climate, Science, 332, 53, 10.1126/science.1200303 Deb, 2017, The impact of climate change on the distribution of two threatened Dipterocarp trees, Ecol. Evol., 7, 2238, 10.1002/ece3.2846 Deb, 2017, Climatic induced shifts in the distribution of teak (Tectona grandis) in tropical Asia: implications for forest management and planning, Environ. Manage., 60, 422, 10.1007/s00267-017-0884-6 Dobrowski, 2013, The climate velocity of the contiguous United States during the 20th century, Glob. Chang. Biol., 19, 241, 10.1111/gcb.12026 Duckett, 2013, Keeping up with the neighbours: using a genetic measurement of dispersal and species distribution modelling to assess the impact of climate change on an Australian arid zone gecko (Gehyra variegata), Divers. Distrib., 19, 964, 10.1111/ddi.12071 Elith, 2009, Species distribution models: ecological explanation and prediction across space and time, Annu. Rev. Ecol. Evol. Syst., 40, 677, 10.1146/annurev.ecolsys.110308.120159 Elith, 2006, Novel methods improve prediction of species’ distribution from occurrence data, Ecography, 19, 129, 10.1111/j.2006.0906-7590.04596.x Elith, 2011, A statistical explanation of Maxent for ecologists, Divers. Distrib., 17, 43, 10.1111/j.1472-4642.2010.00725.x Fielding, 1997, A review of methods for the assessment of prediction errors in conservation presence/absence models, Environ. Conserv., 24, 38, 10.1017/S0376892997000088 Fourcade, 2014, Mapping species distributions with MaxEnt using a geographically biased sample of presence data: a performance assessment of methods for correcting sampling bias, PLoS One, 9, e97122, 10.1371/journal.pone.0097122 Franklin, 2009 Franklin, 2013, Species distribution models in conservation biogeography: developments and challenges, Divers. Distrib., 19, 1217, 10.1111/ddi.12125 Gallagher, 2013, Species loss and gain in communities under future climate change: consequences for functional diversity, Ecography, 36, 531, 10.1111/j.1600-0587.2012.07514.x Gormley, 2011, Using presence-only and presence-absence data to estimate the current and potential distributions of established invasive species, J. Appl. Ecol., 48, 25, 10.1111/j.1365-2664.2010.01911.x Graham, 2006, A comparison of methods for mapping species ranges and species richness, Glob. Ecol. Biogeogr., 15, 578, 10.1111/j.1466-8238.2006.00257.x GuilleraArroita, 2015, Is my species distribution model fit for purpose? Matching data and models to applications, Glob. Ecol. Biogeogr., 24, 276, 10.1111/geb.12268 Hamann, 2006, Potential effects of climate change on ecosystem and tree species distribution in British Columbia, Ecology, 87, 2773, 10.1890/0012-9658(2006)87[2773:PEOCCO]2.0.CO;2 Hansen, 2010, Global surface temperature change, Rev. Geophys., 48, 10.1029/2010RG000345 Hernandez, 2008, Predicting species distributions in poorly-studied landscapes, Biodivers. Conserv., 17, 1353, 10.1007/s10531-007-9314-z IMD, 2016 IPCC., 2007. IPCC Fourth Assessment Report (AR4) – Climate Change 2007: Synthesis Report. Geneva, Switzerland. IUCN., 2015. The IUCN Red List of Threatened Species. Version 2015.2. Jaynes, 1957, Information theory and statistical mechanics, Phys. Rev., 106, 620, 10.1103/PhysRev.106.620 Jena, 2016, CMIP5 projected changes in the annual cycle of indian monsoon rainfall, Climate., 4, 1 Krishna Kumar, 2006, Unraveling the mystery of Indian monsoon failure during El Nino, Science, 314, 115, 10.1126/science.1131152 Kshirsagar, 2008 Kumar, 2009, Potential habitat distribution for the freshwater diatom Didymosphenia geminata in the continental US, Front. Ecol. Environ., 7, 415, 10.1890/080054 Kumar, 2014, Using district-level occurrences in MaxEnt for predicting the invasion potential of an exotic insect pest in India, Comput. Electron. Agr., 103, 55, 10.1016/j.compag.2014.02.007 Lindner, 2010, Climate change impacts, adaptive capacity, and vulnerability of European forest ecosystems, For. Ecol. Manage., 259, 698, 10.1016/j.foreco.2009.09.023 Malcolm, 2006, Global warming and extinctions of endemic species from biodiversity hotspots, Conserv. Biol., 20, 538, 10.1111/j.1523-1739.2006.00364.x Mathew, 2001, Multiple shoot regeneration in kokum and camboge, J. Spices Aromatic Crops, 10, 151 Millennium Ecosystem Assessment, 2005 Mohan, 2012, In vitro and in vivo adventitious bud differentiation from mature seeds of these Garcinia spp, Indian J. Natl. Prod. Resour., 3, 65 Molur, S., Smith, K.G., Daniel, B.A., Darwall, W.R.T., 2011. The Status and Distribution of Freshwater Biodiversity in the Western Ghats. International Union for Conservation of Nature (IUCN), Gland, Switzerland and Zoo Outreach Organization (ZOO), Coimbatore, India. Moss, R., Babiker, M., Brinkman, S., Calvo, E., Carter, T., Edmonds, J., Elgizouli, I., Emori, S., Erda, L., Hibbard, K.A., et al., 2008. Towards new scenarios for analysis of emissions, climate change, impacts, and response strategies. IPCC Expert Meeting Report on New Scenarios. Intergovernmental Panel on Climate Change, Noordwijkerhout. Myers, 2000, Biodiversity hotspots for conservation priorities, Nature, 403, 853, 10.1038/35002501 Nayar, 2014, vol. 1 Patel, 2013, Anxiolytic activity of aqueous extract of Garcinia indica in mice, Int. J. Green Pharm., 7, 332, 10.4103/0973-8258.122089 Pearson, 2007, Predicting species’ distributions from small numbers of occurrence records: a test case using cryptic geckos in Madagascar, J. Biogeogr., 34, 102, 10.1111/j.1365-2699.2006.01594.x Peterson, 2007, Ecological niche modelling and understanding the geography of disease transmission, Veter. Ital., 43, 393 Peterson, 2002, Future projections for Mexican faunas under global climate change scenarios, Nature, 416, 626, 10.1038/416626a Peterson, 2011 Phillips, 2009, Sample selection bias and presence-only distribution models: implications for background and pseudo-absence data, Ecol. Appl., 19, 181, 10.1890/07-2153.1 Phillip, S.J., Dudik, M., Schapire, R.E., 2004. A maximum entropy approach to species distribution modelling. In: Proceedings of the 21st International Conference on Machine Learning. Phillips, 2008, Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation, Ecography, 31, 161, 10.1111/j.0906-7590.2008.5203.x Phillips, 2006, Maximum entropy modelling of species geographic distributions, Ecol. Model., 190, 231, 10.1016/j.ecolmodel.2005.03.026 Priti, 2016, Modeling impacts of future climate on the distribution of Myristicaceae species in the Western Ghats, India, Ecol. Eng., 89, 14, 10.1016/j.ecoleng.2016.01.006 Priya Devi, S., Thangam, M., Ramchandrudu, K., Ashok Kumar, J., and Singh, N.P., 2013. Genetic diversity of Kokum (Garcinia indica) in Goa-Tree and fruit characters. Technical Bulletin 33. Raha, 2016, Factors affecting habitat selection by three sympatric otter species in the southern Western Ghats, India, Acta Ecol. Sin., 36, 45, 10.1016/j.chnaes.2015.12.002 Raju, 2016, Selection of global climate models for India using cluster analysis, J. Water Clim. Change, 8, 764, 10.2166/wcc.2016.112 Ramachandran, 2017 Remya, 2015, Predicting the current and future suitable habitat distribution of Myristica dactyloides Gaertn. using MaxEnt model in the Eastern Ghats, India. Ecol. Eng., 82, 184, 10.1016/j.ecoleng.2015.04.053 Rupa Kumar, 2006, High-resolution climate change scenarios for India for the 21st century, Curr. Sci., 90, 334 Rupa Kumar, 2003, Future climate scenarios, 69 Shukla, 2003 Singh, 2014, Observed changes in extreme wet and dry spells during the South Asian summer monsoon season, Nat. Clim. Change, 4, 456, 10.1038/nclimate2208 Swami, 2014, Kokum (Garcinia indica) and its many functional components as related to the human health: a review, J. Food Res. Technol., 2, 130 Swets, 1988, Measuring the accuracy of diagnostic systems, Science, 240, 1285, 10.1126/science.3287615 Thompson, I., Mackey, B., McNulty, S., Mosseler, A., 2009. A Synthesis of the biodiversity/resilience/stability relationship in forest ecosystems. Forest Resilience, Biodiversity, and Climate Change. Secretariat of the Convention on Biological Diversity, Montreal, pp. 67 technical series 43. Thuiller, 2005, Niche properties and geographical extent as predictors of species sensitivity to climate change, Glob. Ecol. Biogeogr., 14, 347, 10.1111/j.1466-822X.2005.00162.x UNESCO, 2007 Ved, D., Saha, D., Ravikumar, K., Haridasan, K., 2015. Garcinia indica. The IUCN Red List of Threatened Species 2015, e. T50126592A50131340. Ved, 2016 Vidhate, 2013, Extraction of cocoa butter alternative from kokum (Garcinia indica) kernel by three-phase partitioning, J. Food Eng., 117, 464, 10.1016/j.jfoodeng.2012.10.051 Wisz, 2008, Effects of sample size on the performance of species distribution models, Divers. Distrib., 14, 763, 10.1111/j.1472-4642.2008.00482.x Yang, 2013, MaxEnt modelling for predicting the potential distribution of medicinal plant Justicia adhatoda L. in Lesser Himalayan foothills, Ecol. Eng., 51, 83, 10.1016/j.ecoleng.2012.12.004