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FOREST RESOURCES WANAGEMENT ›› 2018›› Issue (1): 141-147.doi: 10.13466/j.cnki.lyzygl.2018.01.020

• Technical Application • Previous Articles     Next Articles

Research on the Update of Sub-compartment Resources Archives Based on the Dynamic Growth Model of Forest Stands

HUO Zhenjiang()   

  1. Daxinganling Forest Investigation Planning Institute in Inner Mongolia,Yakeshi 022150,Inner Mongolia,China
  • Received:2017-12-27 Revised:2018-01-18 Online:2018-02-28 Published:2020-09-27

Abstract:

The establishment of the archives of forest resources is an important part of forest resource management.The archives of forest resources must be updated and perfected in time to reflect the dynamic changes of forest resources,to analyze the change in increase or decrease of forest resources and to carry out the forest management more scientifically.The update of the sub-compartment archives is the basis of the renewal of the forest resource archives.Its accuracy determines the reliability of the updating of the forest resource archives.But the number of sub-compartments in a forestry bureau is large,the composition of tree species is complex.If it is calculated on the basis of the growth rate,the workload of the archives updating and calculation is big,the difference in the canopy density and age of each sub-compartment could not be considered and the accuracy of calculation is not guaranteed.To this end,this paper takes the Daxinganling forest in Inner Mongolia as an example,The application of three variable density dynamic growth model controlled by density,age and status index in the update of small class resource archives is discussed.The result shows that the established forest dynamic growth model system can meet the needs of the dynamic update interval of different stand volume,basal area,number of trees per hectare,the average DBH and average tree height survey factors.The results can provide a reliable basis for the update of sub-compartment data.

Key words: sub-compartment, archive update, variable density, stand, growth model

CLC Number: