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    应用最大熵模型预测中国淡水蛏在中国的潜在地理分布

    Using maximum entropy model to predict the potential geographical distribution of Novaculina chinensis in China

      摘要
    • 摘要:
      背景 中国淡水蛏（Novaculina chinensis）是中国特有物种和国家Ⅱ级保护水生野生动物，具有重要的生态价值和较高的经济价值，但其在我国的潜在地理分布尚不清楚。
      目的 了解中国淡水蛏在我国的潜在地理分布和影响因子。
      方法 本研究收集中国淡水蛏的地理分布数据，应用最大熵模型预测中国淡水蛏在我国的潜在地理分布，并分析影响其地理分布的关键环境因子。
      结果 MaxEnt模型预测准确度极高，平均面积值（AUC值）为0.991。中国淡水蛏在我国的潜在适生区域主要分布在长江中下游地区、淮河流域、珠江三角洲和东部沿海区域；适生区面积为39.99×104 km2，其中低、中和高适生区面积分别为22.79×104 km4、7.39×104 km4和9.81×104 km2。综合分析结果表明，海拔、最干月降水量、等温性和最湿季度平均温度是影响中国淡水蛏潜在我国地理分布的主导环境因子，累计因子贡献率为95.5%；主导环境因子的最适范围：海拔小于100 m、最干月降水量为19.8~41.2 mm、等温性为14.5~25.4和最湿季度平均温度为25.3~35.0 ℃。
      结论 本研究首次采用MaxEnt模型获得了中国淡水蛏的潜在地理分布，找出了影响中国淡水蛏地理分布范围的主导环境因子。中国淡水蛏在我国有广阔的的适生区域，但仍需对其加强资源管理保护。

       

      Abstract:
      Background Novaculina chinensis is an endemic species and a second-class protected aquatic wildlife in China, it plays an important ecological role and has high economic value. However, its potential geographical distribution in China is still unclear.
      Objective The study aims to understand the potential geographical distribution of N. chinensis in China and its related environmental factors.
      Methods The distribution records of N. chinensis and its grid layer data were used to predict its potential suitable area in China based on the maximum entropy (MaxEnt) model, meanwhile, the dominant environmental factors affecting its geographical distribution were analyzed.
      Results The results showed that the MaxEnt model had extremely high prediction accuracy, with an average AUC value of 0.991. The potential suitable area of N. chinensis in China was mainly located in the middle and lower reaches of the Yangtze River, the Huaihe River Basin, the Pearl River Delta and the eastern coastal areas. The suitable habitat areas was 39.99×104 km2, of which the low, medium, and high suitable habitat area was 22.79×104, 7.39×104, and 9.81×104 km2, respectively. The comprehensive analysis results indicated that elevation, precipitation of driest month, isothermality and mean temperature of wettest quarter were the dominant environmental factors affecting the potential geographical distribution of N. chinensis in China, with a cumulative factor contribution rate of 95.5%. The optimal range of dominant environmental factors were: elevation (lower than 100 m), precipitation of driest month (19.8−41.2 mm), isothermality (14.5−25.4) and mean temperature of wettest quarter (25.3−35.0 ℃).
      Conclusion In the study, it is the first time of using the MaxEnt model to obtain the potential geographical distribution of N. chinensis in China, and find the dominant environmental factors that affect its geographical distribution. N. chinensis have vast suitable areas in China, but there is still need to strengthen its resource management and protection.

       

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