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林业科学 ›› 2019, Vol. 55 ›› Issue (3): 72-78.doi: 10.11707/j.1001-7488.20190308

• 论文与研究报告 • 上一篇    下一篇

杉木单木枯损率与初植密度、竞争和气候因子的关系

张雄清1,2, 王翰琛1, 鲁乐乐1, 陈传松3, 段爱国1, 张建国1,2   

  1. 1. 中国林业科学研究院林业研究所 国家林业和草原局林木培育重点实验室 北京 100091;
    2. 南京林业大学南方现代林业协同创新中心 南京 210037;
    3. 中国林业科学研究院亚热带林业实验中心 分宜 336600
  • 收稿日期:2017-02-14 修回日期:2017-05-26 出版日期:2019-03-25 发布日期:2019-04-17
  • 基金资助:
    国家自然科学基金项目(31670634);中国科协青年人才托举项目(2017QNRC001)。

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

Zhang Xiongqing1,2, Wang Hanchen1, Lu Lele1, Chen Chuansong3, Duan Aiguo1, Zhang Jianguo1,2   

  1. 1. Key Laboratory of Tree Breeding and Cultivation of the National Forestry and Grassland Administration Research Institute of Forestry, CAF Beijing 100091;
    2. Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University Nanjing 210037;
    3. Experimental Center of Subtropical Forestry, CAF Fenyi 336600
  • Received:2017-02-14 Revised:2017-05-26 Online:2019-03-25 Published:2019-04-17

摘要: [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/Dg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。

关键词: 单木枯损率, 杉木, 连接模型, 初植密度, 气候变量, 竞争

Abstract: [Objective]It is important to analyze the relationship between tree mortality and planting density, competition, site index, and climate factors for managing Chinese fir(Cunninghamia lanceolata)well.[Method] Based on the Chinese fir data in Jiangxi Province, three widely used model for analyzing binary data which are logit, probit and cloglog link models were used to modelling tree mortality and compared with each other. Then we introduced the plot and tree random effects to the selected model in order.[Result] The result showed that the logit model was the best(AIC=4 700.419), followed by probit model, and cloglog model. Also accounting for the plot and tree random effects at the same time had the best performance, and its AUC was 0.966 8, which was close to 1. In addition, we also found:mortality rate increased with increasing initial planting density and site index; decreased with increasing d/Dg; decreased with increasing mean annual temperature and previous summer mean temperature; increased with increasing previous winter mean minimum temperature and annual heat-moisture index.[Conclusion] Logit model performed well on modeling tree mortality in relation to planting density, competition, site index, and climate factors. The research of relationship between mortality and annual heat-moisture index could be helpful for managing Chinese fir plantations under the climate change.

Key words: tree mortality, Chinese fir, link models, initial planting density, climate, competition

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