摘要
根据黄家河流域天然林25个定位监测样地的3次监测数据,采用马尔柯夫链模型预测了其天然林生长发育不同状态级的分布变化规律,研究表明:马尔柯夫链模型可适用于天然林保护的监测预警研究;黄家河流域天然林保护监测调查时间间隔短,仅为1a,适宜采用增长分级法确定其生长和发育状态级进行预警;黄家河流域天然林的生长增长度、发育持续度和发展耦合度均呈逐年下降的趋势。在近5a内,其天然林保护为轻警,应及时加强保护力度。
Using the Markov chain model, the varying law of growth and upgrowth class distribution of natural forests in the Huangjiahe river basin of Yunnan with the monitoring data collected 3 times from the 25 permanent plots was predicted. The result reveals as follows： 1） the Markov chain model is applicable to the monitoring and early - warning research of natural forest protection; 2） the increment grading rules should be adopted to classify the forest status in the Huangjiahe river basin for early - warning, for its monitoring survey interval is very short and only one year; 3） the growth increment degree, upgrowth sustainability degree and development coupling degree of the forests in the Huangjiahe river basin have got a reducing tendency year after year. During 5 years around this year, the warning degrees of natural forest protection will be light warning. More and stronger protection activities should be launched there in time.
出处
《林业调查规划》
2006年第2期67-72,共6页
Forest Inventory and Planning
基金
国家科技攻关计划项目(2000-K01-04-05-02)
关键词
黄家河流域
天然林保护
监测预警
生长发育
马尔柯夫链模型
Huangjia river basin
natural forest protection
monitoring
early- warning
growth
upgrowth
Markov chain model
