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    邱靖, 朱弘, 陈昕, 汤庚国. 基于DIVA-GIS的水榆花楸适生区模拟及生态特征[J]. 北京林业大学学报, 2018, 40(9): 25-32. DOI: 10.13332/j.1000-1522.20180162
    引用本文: 邱靖, 朱弘, 陈昕, 汤庚国. 基于DIVA-GIS的水榆花楸适生区模拟及生态特征[J]. 北京林业大学学报, 2018, 40(9): 25-32. DOI: 10.13332/j.1000-1522.20180162
    Qiu Jing, Zhu Hong, Chen Xin, Tang Gengguo. Modeling the suitable areas and ecological characteristics of Sorbus alnifolia using DIVA-GIS software[J]. Journal of Beijing Forestry University, 2018, 40(9): 25-32. DOI: 10.13332/j.1000-1522.20180162
    Citation: Qiu Jing, Zhu Hong, Chen Xin, Tang Gengguo. Modeling the suitable areas and ecological characteristics of Sorbus alnifolia using DIVA-GIS software[J]. Journal of Beijing Forestry University, 2018, 40(9): 25-32. DOI: 10.13332/j.1000-1522.20180162

    基于DIVA-GIS的水榆花楸适生区模拟及生态特征

    Modeling the suitable areas and ecological characteristics of Sorbus alnifolia using DIVA-GIS software

    • 摘要:
      目的水榆花楸是一种优良的林木种质资源, 具有重要的生态和观赏价值, 全面了解其在我国的自然分布现状与生态特征, 将有助于制定水榆花楸的资源保护与科学引种规划。
      方法基于183个野外采集与历史标本凭证, 利用地理信息技术的DIVA-GIS软件及其耦合的BIOCLIM模型, 对其适生区分布格局以及主导气候因子进行了首次定性定量分析。
      结果水榆花楸的当代潜在适生区覆盖我国东部季风区各省, 基于BIOCLIM的模型预测结合辛普森多样性指数评估表明:中国中部山区、华北沿海丘陵与东北地区, 是水榆花楸现代3个集中分布的区域, 其中陕、豫、鄂与渝多省交界的山区(秦岭-大巴-巫山山脉)可视为核心分布区域; 气候因子主成分分析(PCA)与主导气候因子贡献率排序依次为:年降水量(bio12)>最湿季降水量(bio16)>温度季节变化方差(bio4)>最暖季降水量(bio18)>最冷季降水量(bio19);累计频率曲线进一步明确水榆花楸地理分布的生态特征分别为:423.00~1508.00 mm, 245.00~675.00 mm, 590.63~1280.93(SD×100), 229.00~655.00 mm和8.00~185.00 mm; 用于模型评估的受试者工作特征曲线(ROC)和Kappa统计值分别达到0.782和0.515, 满足预测精度的一般要求。
      结论水榆花楸当下分布格局在区域尺度上主要受到东亚季风驱动的降水因子影响, 并偏好高海拔适度低温的环境, 此外水榆花楸分布格局的差异在区域尺度上还受海拔、经纬度地理因素不同程度影响。

       

      Abstract:
      ObjectiveSorbus alnifolia, an excellent forest germplasm resources, has significant ecological and ornamental values. An overall understanding of its natural distribution status and ecological characteristics in China will contribute to develop the resource conservation and scientific introduction planning for this species.
      MethodBased on the data from 183 field collection and historical sample documents, we applied DIVA-DIS software of geographic information technology and combined with BIOCLIM model to analyse the distribution pattern of S. alnifolia and its dominant climate factors qualitatively and quantitatively for the first time.
      ResultThe current potential distribution areas of S. alnifolia cover the provinces of Chinese eastern monsoon region, and the evaluation based on results of BIOCLIM Modeling combined with Simpson's diversity index showed that the mountainous regions of central China, coastal hilly area of northern China and northeastern China were its three most concentrated areas. Among them, border of mountainous regions projected from provinces of Shaanxi, Henan, Hubei and Chongqing and their junctions (Qinling-Daba-Wushan mountain ranges) can be regarded as its core distributing areas. Principal component analysis (PCA) of climatic variables and the dominant climate factor contributing rates were in sequence of annual mean precipitation (bio12) > precipitation in the wettest season (bio16) > seasonally varied SD of temperature (bio4) > precipitation in the warmest season (bio18) > precipitation in the coldest season (bio19). The cumulative frequency curves further confirmed that the ecological characteristics of geographical distributing area for S. alnifolia were 423.00-1 508.00 mm, 245.00-675.00 mm, 590.63-1 280.93 (SD×100), 229.00-655.00 mm and 8.00-185.00 mm, respectively. The receiver operating characteristic curve (ROC) and Kappa statistics for model assessment reached 0.782 and 0.515, respectively, meeting the general demands for prediction accuracy.
      ConclusionThe above research indicated that the current distributing pattern of S. alnifolia was mainly affected by precipitation factors driven by the eastern Asian monsoon at regional scale, also with preference of moderately low temperature and high altitude environment. What's more, differences in distributing patterns of S. alnifolia were also affected by geographical factors, including altitude, latitude and longitude to some extent.

       

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