Future of Endemic Flora of Biodiversity Hotspots in India

被引:69
作者
Chitale, Vishwas Sudhir [1 ,2 ]
Behera, Mukund Dev [1 ]
Roy, Partha Sarthi [3 ]
机构
[1] Indian Inst Technol Kharagpur, Ctr Oceans Rivers Atmosphere & Land Sci, Kharagpur, W Bengal, India
[2] Int Ctr Integrated Mt Dev ICIMOD, Kathmandu, Nepal
[3] Univ Hyderabad, Univ Ctr Earth & Space Sci, Hyderabad 500134, Andhra Pradesh, India
关键词
SPECIES DISTRIBUTION MODELS; CLIMATE-CHANGE; RANGE SHIFTS; CONSERVATION; RICHNESS; AREAS;
D O I
10.1371/journal.pone.0115264
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
India is one of the 12 mega biodiversity countries of the world, which represents 11% of world's flora in about 2.4% of global land mass. Approximately 28% of the total Indian flora and 33% of angiosperms occurring in India are endemic. Higher human population density in biodiversity hotspots in India puts undue pressure on these sensitive eco-regions. In the present study, we predict the future distribution of 637 endemic plant species from three biodiversity hotspots in India; Himalaya, Western Ghats, Indo-Burma, based on A1B scenario for year 2050 and 2080. We develop individual variable based models as well as mixed models in MaxEnt by combining ten least co-related bioclimatic variables, two disturbance variables and one physiography variable as predictor variables. The projected changes suggest that the endemic flora will be adversely impacted, even under such a moderate climate scenario. The future distribution is predicted to shift in northern and northeastern direction in Himalaya and Indo-Burma, while in southern and south-western direction in Western Ghats, due to cooler climatic conditions in these regions. In the future distribution of endemic plants, we observe a significant shift and reduction in the distribution range compared to the present distribution. The model predicts a 23.99% range reduction and a 7.70% range expansion in future distribution by 2050, while a 41.34% range reduction and a 24.10% range expansion by 2080. Integration of disturbance and physiography variables along with bioclimatic variables in the models improved the prediction accuracy. Mixed models provide most accurate results for most of the combinations of climatic and non-climatic variables as compared to individual variable based models. We conclude that a) regions with cooler climates and higher moisture availability could serve as refugia for endemic plants in future climatic conditions; b) mixed models provide more accurate results, compared to single variable based models.
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页数:15
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