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    张财, 查天山, 贾昕, 刘鹏, 李成. 毛乌素沙地油蒿群落叶面积指数动态及模拟[J]. 北京林业大学学报, 2018, 40(3): 75-83. DOI: 10.13332/j.1000-1522.20170298
    引用本文: 张财, 查天山, 贾昕, 刘鹏, 李成. 毛乌素沙地油蒿群落叶面积指数动态及模拟[J]. 北京林业大学学报, 2018, 40(3): 75-83. DOI: 10.13332/j.1000-1522.20170298
    Zhang Cai, Zha Tianshan, Jia Xin, Liu Peng, Li Cheng. Dynamics and simulation of leaf area index for Artemisia ordosica community in the Mu Us Desert of northwestern China[J]. Journal of Beijing Forestry University, 2018, 40(3): 75-83. DOI: 10.13332/j.1000-1522.20170298
    Citation: Zhang Cai, Zha Tianshan, Jia Xin, Liu Peng, Li Cheng. Dynamics and simulation of leaf area index for Artemisia ordosica community in the Mu Us Desert of northwestern China[J]. Journal of Beijing Forestry University, 2018, 40(3): 75-83. DOI: 10.13332/j.1000-1522.20170298

    毛乌素沙地油蒿群落叶面积指数动态及模拟

    Dynamics and simulation of leaf area index for Artemisia ordosica community in the Mu Us Desert of northwestern China

    • 摘要:
      目的本研究以毛乌素沙地灌木油蒿群落为研究对象,研究如何快速、准确、连续地获取油蒿群落LAI,获取长期连续的LAI数据对研究生态系统过程与环境变化间的相互关系具有重要意义。
      方法本文采用原位连续监测和野外试验的方法,于2013和2014年每年4—10月使用LAI-2000冠层分析仪定期测定油蒿群落LAI,同时利用太阳辐射传感器和光量子传感器测得的辐射数据计算地面观测NDVI(NDVIground)并获取同期遥感MODIS NDVI(NDVIMODIS)。用LAI数据分析油蒿叶面积群落指数的季节动态,并与归一化积温、NDVIground和NDVIMODIS分别建立经验模型,得到最优油蒿群落LAI模拟模型。
      结果油蒿群落LAI在整个生长季内的变化与物候具有一致性,整体上随时间呈现单峰型变化趋势,4—8月末油蒿持续生长,LAI稳定增大,8月份达到峰值,2013年为1.09m2/m2,2014年为1.33m2/m2。9月初至9月中旬油蒿冠层结构趋于稳定,LAI变化较小;9月下旬油蒿叶片开始枯黄掉落,LAI迅速下降。经验证,利用NDVIground模拟荒漠地区油蒿群落LAI效果最优(R2=0.76, P < 0.01)。
      结论在荒漠地区简单测量NDVI并使用本文研究模型,可以快速、无破坏地获取长期连续可靠的LAI数据,研究结果对理解和预测荒漠生态系统对全球气候变化的响应具有重要意义。

       

      Abstract:
      ObjectiveOur objective here was to rapidly and accurately obtain long-term continuous LAI for Artemisia ordosica communities in the Mu Us Desert of northwestern China, which is of great importance for understanding the relationship between ecosystem processes and environmental changes.
      MethodWe measured LAI in a typical A. ordosica community using the LAI-2000 canopy analyzer (LI-COR, USA) from April to October in the growing season of 2013 and 2014, and obtained MODIS NDVI (NDVIMODIS) data for the same periods. Ground-based NDVI (NDVIground) was calculated from incident and reflected solar radiation and photosynthetically active radiation, which were measured by radiation sensors mounted on a tower in the center of the community. LAI measurements were used to examine seasonal changes and construct LAI models. Normalized effective accumulated temperature, NDVIground and NDVIMODIS were used to construct optimal LAI model for the community.
      ResultThe seasonal dynamics was consistent with the phenophases of A. ordosica and showed a hump-shaped pattern. LAI increased from April to late August, reached a peak in August (1.09 and 1.33m2/m2 in 2013 and 2014, respectively), remained relatively stable from early September to mid-September, and rapidly declined from late September due to the defoliation of A. ordosica. The optimal LAI model was NDVIground (R2=0.76, P < 0.01).
      ConclusionOur results indicate that long-term continuous LAI estimates for A. ordosica communities in the Mu Us Desert can be easily obtained using NDVI measurements and the model. The model can be used to understand and predict ecological impacts of climate change.

       

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