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防风固沙优良树种欧李的潜在适生区及生态特征

张琴 宋经元 邵飞 傅生辰 孙成忠 袁丽钗 谢彩香

张琴, 宋经元, 邵飞, 傅生辰, 孙成忠, 袁丽钗, 谢彩香. 防风固沙优良树种欧李的潜在适生区及生态特征[J]. 北京林业大学学报, 2018, 40(3): 66-74. doi: 10.13332/j.1000-1522.20170180
引用本文: 张琴, 宋经元, 邵飞, 傅生辰, 孙成忠, 袁丽钗, 谢彩香. 防风固沙优良树种欧李的潜在适生区及生态特征[J]. 北京林业大学学报, 2018, 40(3): 66-74. doi: 10.13332/j.1000-1522.20170180
Zhang Qin, Song Jingyuan, Shao Fei, Fu Shengchen, Sun Chengzhong, Yuan Lichai, Xie Caixiang. Potential suitable distribution area and ecological characteristics of Cerasus humilis, an excellent tree species for windproof and sand fixation[J]. Journal of Beijing Forestry University, 2018, 40(3): 66-74. doi: 10.13332/j.1000-1522.20170180
Citation: Zhang Qin, Song Jingyuan, Shao Fei, Fu Shengchen, Sun Chengzhong, Yuan Lichai, Xie Caixiang. Potential suitable distribution area and ecological characteristics of Cerasus humilis, an excellent tree species for windproof and sand fixation[J]. Journal of Beijing Forestry University, 2018, 40(3): 66-74. doi: 10.13332/j.1000-1522.20170180

防风固沙优良树种欧李的潜在适生区及生态特征

doi: 10.13332/j.1000-1522.20170180
基金项目: 

“十二五”国家科技支撑计划课题 2015BAI05B01

国家自然科学基金项目 81473304

详细信息
    作者简介:

    张琴。主要研究方向:药用植物地理分布及产地适宜性。Email: zhangqin1992yx@163.com 地址:100193北京市海淀区马连洼北路151号

    责任作者:

    谢彩香, 副研究员。主要研究方向:药用植物地理分布及产地适宜性。Email: caixiangxie@163.com 地址:同上

  • 中图分类号: S793.9;R931.2

Potential suitable distribution area and ecological characteristics of Cerasus humilis, an excellent tree species for windproof and sand fixation

  • 摘要: 目的欧李作为我国特有的生态型树种,在防风固沙、蓄水保土等方面具有重要的生态和经济价值,因此研究欧李的全球潜在适生区及其生态特征,对欧李树种的推广种植和防沙治理具有重要意义。方法本文根据379个欧李分布点和19个生态因子数据,采用BIOCLIM、DOMAIN、MAXENT和GARP 4个生态位模型预测欧李的全球潜在适生区,并分析欧李分布区的生态特征,以受试者工作特征曲线ROC和Kappa两个统计量进行模型评价。结果欧李的全球潜在适生区主要分布在30°~52° N、102°~137° E范围内的亚洲,包括中国、韩国、朝鲜以及与中国东北接壤的俄罗斯远东地区,另外,阿富汗和塔吉克斯坦也有少量分布,其中最适宜区主要分布在中国。模型评估表明,4个模型的AUC值均达到0.85以上,Kappa值均达到0.7以上,4个模型预测精度良好,一致性显著,均可用来预测欧李潜在适生区。欧李分布区的生态特征为:年平均温度范围为3.2~13.9℃,昼夜温差月均值范围为10.1~13.0℃,昼夜温差与年温差比值范围为24~30,温度变化方差范围为9234~13581,最湿月份降水量范围为115~226mm,最干月份降水量范围为2~10mm,雨量变化方差范围为77~115。结论欧李潜在适生区主要位于温带季风气候带,最适宜区主要分布在中国东北和华北地区,该地区可大规模种植欧李以实现荒漠化治理,而韩国、朝鲜、俄罗斯远东区和阿富汗等地适宜性相对较低,可先进行小规模试种,再扩大生产。

     

  • 图  1  欧李样本点分布图

    Figure  1.  Distributing points of Cerasus humilis

    图  2  生态适宜性分析技术路线

    Figure  2.  Technical route of ecological suitability analysis

    图  3  欧李全球潜在适生区

    A.BIOCLIM模型;B.DOMAIN模型;C.MAXENT模型;D.GARP模型。

    Figure  3.  Global potential suitable distributing area of C. humilis

    A, BIOCLIM model; B, DOMAIN model; C, MAXENT model; D, GARP model.

    图  4  7个主要因子生态特征

    bio1.年平均温度; bio2.昼夜温差月均值; bio3.昼夜温差与年温差比值; bio4.温度变化方差; bio13.最湿月份降水量; bio14.最干月份降水量; bio15.雨量变化方差。

    Figure  4.  Ecological characteristics of seven main factors

    bio1, mean annual temperature; bio2, monthly mean value of diurnal temperature difference; bio3, isothermality; bio4, SD of temperature seasonality; bio13, precipitation of the wettest month; bio14, precipitation of the driest month; bio15, variation of precipitation seasonlity.

    表  1  环境变量

    Table  1.   Environmental variables

    环境变量Environmental variable 单位Unit
    年平均温度Mean annual temperature(bio1)
    昼夜温差月均值Monthly mean value of diurnal temperature difference (max. temperature-min. temperature) (bio2)
    昼夜温差与年温差比值Isothermality (bio2/bio7×100)(bio3) 1
    温度变化方差SD of temperature seasonality(bio4) 1
    最热月份最高温Max. temperature of the warmest month(bio5)
    最冷月份最低温Min. temperature of the coldest month(bio6)
    年温度变化范围Annual temperature range(bio5- bio6)(bio7)
    最湿季度平均温度Mean temperature of the wettest quarter(bio8)
    最干季度平均温度Mean temperature of the driest quarter(bio9)
    最暖季度平均温度Mean temperature of rhe warmest quarter(bio10)
    最冷季度平均温度Mean temperature of the coldest quarter(bio11)
    年平均降水量Annual mean precipitation(bio12) mm
    最湿月份降水量Precipitation of the wettest month(bio13) mm
    最干月份降水量Precipitation of the driest month(bio14) mm
    雨量变化方差Variation of precipitation seasonality(bio15) 1
    最湿季度降水量Precipitation of the wettest quarter(bio16) mm
    最干季度降水量Precipitation of the driest quarter(bio17) mm
    最暖季度平均降水量Mean precipitation of the warmest quarter(bio18) mm
    最冷季度平均降水量Mean precipitation of the coldest quarter(bio19) mm
    下载: 导出CSV

    表  2  4个模型AUC和Kappa统计量

    Table  2.   Statistic values of AUC and Kappa of the four models

    模型Model AUC均值
    Average of AUC
    AUC标准差
    Standard deviation of AUC
    Kappa均值
    Average of Kappa
    Kappa标准差
    Standard deviation of Kappa
    BIOCLIM 0.973 0.01 0.979 0.02
    DOAMIN 0.993 0.001 0.983 0.003
    GARP 0.897 0.02 0.790 0.04
    MAXENT 0.858 0.02 0.716 0.05
    下载: 导出CSV
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  • 收稿日期:  2017-05-16
  • 修回日期:  2017-11-15
  • 刊出日期:  2018-03-01

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