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Effects of climate change on the distribution of wild population of Metasequoia glyptostroboides, an endangered and endemic species in China.

ZHU Ying-ying, XU Xiao-ting*   

  1. (Key Laboratory of Bio-resource and Eco-environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu 610065, China).
  • Online:2019-06-10 Published:2019-06-10

Abstract: The relict gymnosperm species, Metasequoia glyptostroboides Hu & Cheng (dawn redwoods), is a wellknown example of living fossil. It is an endangered, endemic and a national key protected species of China. Its wild populations survive only in the border region of Hunan, Hubei provinces and the Chongqing municipality in southcentral China. Although it has been widely cultivated worldwide, the cultivated populations are incapable of regenerating naturally. The wild populations are facing rapid population decline due to reduced natural regeneration. Therefore, the humaninduced climate change is likely to increase the extinction risk of M. glyptostroboides. To explore the effects of climate change on M.glyptostroboides, we established the species distribution models using its wild distribution records and current climatic data. Using these models, we predicted its future distributions based on the climate data simulated by three global circulation models (CCSM4, CNRM-CM5 and HadGEM2-ES). Our results show that the current potential suitable habitats for M. glyptostroboides are mainly the adjacent areas of Hubei, Chongqing, Hunan and Guizhou, which is consistent with its actual distribution area. The wild population of M. glyptostroboides will shift northwest to the present distribution area in the future (2070s) under both RCP2.6 and RCP8.5 scenarios, but with lower habitat suitability (<0.5). Our findings suggest a dramatic decline in the suitable habitats of M. glyptostroboides and this may likely wipe out its wild populations entirely in the near future. Our results suggest that climate change may threaten the wild populations ofM. glyptostroboides.

Key words: the Great Xing’an Mountains, moisture content of fuel, prediction model, one-hour time step, extrapolation.