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Chinese Agricultural Science Bulletin ›› 2015, Vol. 31 ›› Issue (22): 21-25.doi: 10.11924/j.issn.1000-6850.casb14120176

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Study on Relationship Model of Leaf Area Index and Site Index, Stand Age, Stand Density of Larix principis-rupprechtii Plantations

Wang Xiongbin1, Xu Chengli2, Yu Xinxiao2, Li Jie1   

  1. (1Water Resources Institute of Hebei/ Engineering Research Center for Water Saving in Agriculture of Hebei,Shijiazhuang 050051;2Mulan-weichang National Forestry Administration of Hebei Province, Weichang Hebei 068400;3College of Soil and Water Conservation, Beijing Forestry University, Beijing 100083)
  • Received:2014-12-25 Revised:2015-05-20 Accepted:2015-05-25 Online:2015-08-20 Published:2015-08-20

Abstract: In order to research the ecological function of Larix principis-rupprechtii forest and improve forest management, the relationship model of leaf area index and stand age, stand density, site index of Larix principis-rupprechtii forest was fitted with statistical software. The model was based on the investigation data of 209 pieces of Larix principis-rupprechtii forest standard, taking stand density, forest age, site index as the independent variables, and the canopy leaf area index as the dependent variable. The results showed that the relationship model of leaf area index and stand age, stand density and site index had the following characteristics: the canopy leaf area index of Larix principis-rupprechtii forest increased with the increase of stand age, stand density and site index. In the condition of low stand age and stand density, the crown closure was also low, the leaf area index increased linearly with the increase of stand density and age, while the leaf area index increased slowly with the increase of stand density and age when crown closure was high. The steady value of leaf area index was higher in the higher site index forest. The emulation values of the fitting model coincided with the actual condition. The theoretical value of the canopy leaf area index of Larix principis-rupprechtii forest can be obtained quickly by the fitting model.