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红椿天然林优树选择
引用本文:汪洋,闵水发,江雄波,郑德国,宋丛文,章定青,付秋生,陈文学.红椿天然林优树选择[J].浙江农林大学学报,2016,33(5):841-848.
作者姓名:汪洋  闵水发  江雄波  郑德国  宋丛文  章定青  付秋生  陈文学
作者单位:1.湖北生态工程职业技术学院, 湖北 武汉 4302002.堵河源自然保护区 管理局, 湖北 竹山 4422003.湖北省建始县林业局, 湖北 建始 4453004.湖北省竹山县林业局, 湖北 竹山 442200
基金项目:湖北省科学技术公益性研究项目402012DBA40001
摘    要:自2013年以来,在湖北省全省范围内调查红椿Toona ciliata种质资源的基础上,对12个县市的红椿天然林进行优树选择。确定选优林分,将16~40年生红椿以5 a为龄级分组,利用优势木对比法,通过异龄林树龄校正,在各龄级组共选出候选优树52株。对候选优树材积进行多元线性回归,建立材积(y),胸径(x1),树高(x2)回归方程y=-3.066+0.065x2+0.094x2, R2=0.961。通过材积实测值与理论值残差分析,将候选优树按生长量分为3级。通过主成分分析法,剔除特征根和贡献率小的形质因子,从6个形质因子中筛选获得冠高树高比、平均冠幅、干形和分枝角等4个因子建立形质分级标准,将候选优树按形质分为3级。对优选优树生长量和形质综合评分,筛选出1级优树7株,2级优树22株,3级优树11株,共40株,占候选优树的76.92%。可基本保证湖北地区红椿种质资源圃的建立和种源试验需求。图 1 表 9 参19

关 键 词:林木育种学    红椿    天然林    优树选择    材积    形质
收稿时间:2015-10-20

Selection criteria for superior Toona ciliata trees in natural forests of Hubei
WANG Yang,MIN Shuifa,JIANG Xiongbo,ZHENG Deguo,SONG Congwen,ZHANG Dingqing,FU Qiusheng,CHEN Wenxue.Selection criteria for superior Toona ciliata trees in natural forests of Hubei[J].Journal of Zhejiang A&F University,2016,33(5):841-848.
Authors:WANG Yang  MIN Shuifa  JIANG Xiongbo  ZHENG Deguo  SONG Congwen  ZHANG Dingqing  FU Qiusheng  CHEN Wenxue
Institution:1.Hubei Vocational College of Ecological Engineering, Wuhan 430200, Hubei, China2.Management Office, Duheyuan Nature Reserve, Zhushan 442200, Hubei, China3.Forest Enterprise of Jianshi County, Jianshi 445300, Hubei, China4.Forest Enterprise of Zhushan County, Zhushan 442200, Hubei, China
Abstract:In order to obtain and preserve fine germplasm resources of Toona ciliata in natural communities of Hubei Province, in 3 consecutive years from 2013, genetic resources of T. ciliata were determined in Hubei Province, on the basis of which, superior tree selections were made in 12 different administrative regions. Natural forest stands for superior tree selection were determined by establishing five age groups covering 16-40 a, each in 5 a. The 5-superior-tree-comparison method was employed to select superior trees on 5 age groups and the uneven tree ages of the selected target trees were adjusted. Two independent evaluation standards for timber volumn and shape quality value indexes were proposed to establish the selective criterion. Results of the initial selection were 52 preliminary superior T. ciliata trees. The multiple linear regression for timber volume (y), DBH(x1) and tree height (x2) wasy=-3.066+0.065x2+0.094x2, R2=0.961, indicating a highly significant linear relation between y and x(x2, x2). Results showed that 52 preliminary superior trees could be classified into 3 grades of growth volume with residual analysis of measured values and theoretical values: 10 Class A superior trees, 38 Class B and 4 Class C, covering 19.23%, 73.08% and 7.69% of the total. Furthermore, the four screened out shape factors named ratio of crown height to tree height, average crown breadth, stem straightness and branching angle, with accumulative contribution rates 91.718%, approximately represented the general information of all 6 factors. Hence, all 52 priliminary superior trees were classified to three tree grading standards of shape quality values, with 30 Class A, 12 Class B and 10 Class C, occupying 57.69 %, 23.08% and 19.23% respectively of the total. In the end, the comprehensive evaluation standard of superior trees of T. ciliata for both growth volumn and shape quality value was utilized, with individuals of Class C eliminated from 2 grading groups, obtaining 40 superior trees in total, i.e. 7 of grade 1, 22 of grade 2, and 11 of grade 3 respectively, accounting for 76.92% of the 52 preliminaries. With these grading systems considered, fast growth and fine shape quality value of the selected superior trees can be guaranteed, and these selected superior trees approximate the demands for the establishment of genetic resource nurseries and provenance tests of T. ciliata in the Hubei region. The comprehensive selection standard of superior tree of T. ciliata can be practiced as a reference in the Hubei region.Ch, 1 fig. 9 tab. 19 ref.]
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