摘要
【目的】通过分析生长率模型系统更新数据的差异,为年度监测数据更新提供依据。【方法】采用第六次至第九次全国森林资源连续清查四川省2002、2017、2012和2017年4个年度固定样地调查数据,应用非线性回归估计方法,建立了18个树种(组)单木胸径和蓄积生长率模型,13个主要乔木林类型林分材积生长率模型,胸径一元模型、年龄一元模型和胸径-年龄二元模型,10个主要乔木林类型三储量联立估测模型。【结果】模型拟合的决定系数R^(2)均大于0.9,能够满足林分蓄积生长的模拟更新,解决了蓄积量、生物量和碳储量间计算的兼容性问题,单位面积蓄积量混合效应模型为基于林分因子的储量更新提供了有效的参考。【结论】活立木和林木采用胸径-年龄二元生长率模型更新精度较高,散生木采用单木生长率模型更新精度较高,四旁树采用胸径一元林分生长率模型更新精度较高。
【Objective】The aim is to provide basis for updating annual monitoring data by analyzing the difference of growth rate model types. 【Method】 The models of DBH and stock growth rate for18 tree species(groups),stand volume growth rate model for 13 main arbor types,DBH single model,age single model and DBH-age dual model,and simultaneous estimation models(volume,biomass,and carbon storage)for 10 main tree types were established by applying nonlinear regression estimation method with the data from the sixth to ninth consecutive Forest Inventory of Sichuan province in 2002,2017,2012 and 2017. 【Result】 The R^(2)coefficients of model fitting are all greater than 0.9,which could meet the simulation update of stand volume,biomass,and carbon storage growth,and solve the compatibility problem of volume,biomass and carbon storage. The mixed effect model of unit area volume provided an effective method for the stock update based on stand factors.【Conclusion】The binary DBH-age growth rate model has higher accuracy for prediction of stand and forest,the single DBH growth rate model has higher accuracy for prediction of scatter trees,and the single DBH stand growth rate model has higher updating accuracy for quadrangle trees.
作者
吴恒
胥辉
WU Heng;XU Hui(Forestry College,Southwest Forestry University,Kunming 650224;Southwest Survey and Planning Institute,National Forestry and Grassland Administration,Kunming 650031)
出处
《四川农业大学学报》
CSCD
北大核心
2022年第6期893-900,906,共9页
Journal of Sichuan Agricultural University
基金
国家自然科学基金项目(31770677,31660202)
云南省唐守正院士工作站(2018IC066)资助。
