Potential geographical distribution of Rana hanluica in China under climate change

doi:10.13287/j.1001-9332.202112.003

Abstract

Abstract: Global warming in the last few decades had strong impacts on biodiversity and geographi-cal distribution of different animal species worldwide, especially amphibians. Rana hanluica, a frog species endemic in China, is still classified as Least Concerned in the Red List of Threatened Species because few studies have been conducted on this species. To understand the survival of Rana hanluica population, we used maximum entropy models (MaxEnt) to analyze its distribution across regions under current climatic conditions based on 47 distribution records and 20 environmental factors. We investigated the changes in distribution of this species under different climate scenarios in China (2050s and 2070s). Finally, current and future suitable habitats for R. hanluica were mode-led, and the impacts of environmental factors in shaping its distribution were evaluated. The results showed that the prediction accuracy of the MaxEnt model was high, and AUC value of the receiver operating curve was 0.993. The total suitable habitat area for R. hanluica was 36.36×10⁴ km², mainly located in Hunan and Guizhou provinces in China. The major environmental factors influencing the geographic distribution of R. hanluica were precipitation of dryest month and altitude. Under the future climate scenario (2050 and 2070) with two representative concentration pathways (RCPs, SSP1-2.5, SSP5-8.5), the suitable habitat of R. hanluica was reduced in different degrees, resulting in a decreasing trend of the total suitable habitat area. The center of gravity in highly suitable habitat of R. hanluica shifted to high-latitude regions, with the core distribution area in Hunan Province.

Key words: Rana hanluica, climate change scenario, MaxEnt model, environmental variable, potential geographical distribution

XIA Xin, LI Yuan, YANG Dao-de, PI Yang-yan. Potential geographical distribution of Rana hanluica in China under climate change[J]. Chinese Journal of Applied Ecology, 2021, 32(12): 4307-4314.

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