杉木单木枯损率与初植密度、竞争和气候因子的关系

Tree Mortality in Relation to Planting Density, Competition and Climate Factors for Chinese Fir Plantation in Southern China

【目的】分析杉木单木枯损率与初植密度、竞争和气候因子的关系,为杉木科学经营管理提供决策依据。【方法】以江西杉木密度试验林为研究对象,选取常用的logit、probit和cloglog 3种二分类变量数据结构模型构建杉木单木枯损率基础模型,并进行选择。以选择出的最优模型为基础,引入样地和样木的随机效应构建杉木单木枯损率混合效应模型。【结果】logit模型的AIC值最小(4 700.419),probit模型次之,cloglog模型最差。考虑样地和样木两水平随机效应的混合效应模型模拟精度最高,其AUC值为0.966 8。初植密度、林分优势高越大,杉木单木枯损率越高;相对直径d/D_g越大,杉木单木枯损率越低;气候越干旱,杉木单木枯损率越高;温度升高,杉木单木枯损率减小。【结论】考虑样地和样木两水平的logit模型能够较好分析杉木单木枯损率与初植密度、竞争、立地和气候因子的关系,并且随着气候干旱发生,杉木单木枯损率提高。

[Objective ] It io important to analyze the relationship between tree mortality and planting density, ccmpetition , site index , and climato facWre foe managing Chineso fir % Cuooioghamij ) well.' Method ] Based on the Chinese ft data in Jiangxi Previncc , three widely used model foe analyzing binary data which are looit, probit and clooloo link modeO were used It modelling tree mortality and ccmpared with each other. Then we introduccd the plot and tree random efects to the selected modd in ordee.[Result ] The resuh showed that the looit modd was the best % AIL = 4 700. 419), followed by probit modd, and clooloo modd. Also acccunting for the plot and tree random Cects at the same time had the best performance, and its AUC was 0. 966 8 , which was close It 1. In addition , we also found : mortality rate increased with increesing initid planting density and site index;decreesed with increesing d/Eg;decreesed with increasing mean annud temperature and previous summer mean temperature;increesed with increesing previous wtnte mean mtntmum tempeatu5eand annuaoheat-motetu5etndei.[ Conc ou eton] Logttmodeopeoomed weoon modeotng tree mortal! te in oelation te planting density, ccmpetition, site index, and climate factors. The oesearch of oelationship belteen mortalita and annual heat-moisture index cculd be helpful foe managing Chinese fir plantations undeo the climate change.