Prediction of potential distribution of Didymodon (Bryophyta, Pottiaceae) in Xinjiang based on the MaxEnt model
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摘要: 该文基于MaxEnt模型，利用获得的132个对齿藓属（Didymodon）植物在新疆分布的信息，结合RCP45 CO2排放情景下2050年和2070年的19个生物气候数据预测该属在当代、2050年和2070年的潜在分布区域。结果显示，最湿季平均温度、年平均气温、最干季降水量和年降水量是影响该属分布最主要的气候因子，其贡献率分别为33.6%、22.2%、16.4%和14.6%；模型模拟准确度高（AUC值达0.84）；在当代气候条件下，对齿藓属植物的适宜生境面积占新疆总面积的38.51%；最适分布区域是中部的天山山脉、南部昆仑山脉的东部和西部的帕米尔高原；与当代的分布预测结果相比，未来（2050年和2070年）该属适宜栖息地分布范围总体上呈现退缩趋势；退缩后的适宜生境面积分别占新疆总面积的36.56%和37.87%。温度和降水量可能是引起对齿藓属地理分布退缩的重要气候因子。研究结果可为探讨气候变化对干旱、半干旱区苔藓植物物种分布的影响提供参考资料。Abstract: Based on data from 19 bioclimatic variables under the current (1950-2000) and future (2050s, 2070s) climatic conditions with RCP45 CO2 emission scenarios and on 132 distributional records of Didymodon in Xinjiang, we predicted the potential distribution of this genus in Xinjiang in the different periods by using the MaxEnt model and ArcGIS 10.2 software. Results showed that the major factors were mean temperature of wettest quarter, annual mean temperature, precipitation of driest quarter and annual precipitation, with relative contribution percentages of 33.6%, 22.2%, 16.4%, and 14.6%, respectively. For the simulation model with high accuracy, the AUC reached 0.84. For the contemporary climate conditions, suitable habitat of Didymodon accounted for 38.51% of the total area, with the most suitable distribution areas found to be the Tianshan Mountains, east of the Kunlun Mountains, and the Pamir Plateau. Compared to the present distribution, the suitable habitat distribution range of the genus will shrink in the future (2050s and 2070s); after shrinking, the suitable habitat area will account for 36.56% and 37.87% of Xinjiang's total area, respectively. Temperature and precipitation will likely be the important climatic factors causing the geographical distribution retreat of Didymodon. This research provides a reference for studying the effects of climate change on the species distribution of bryophytes in arid and semi-arid areas.
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Keywords:
- Didymodon /
- MaxEnt model /
- Potential distribution region /
- Prediction
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