【目的】森林资源监测的周期缩短、监测区域越来越小,精准监测成为森林资源监测的必然,对省域森林资源监测数据的误差进行控制是一项重点工作。【方法】以浙江省2004—2015年森林资源连续清查年度监测的5 375个固定样地数据为基础数据源,区分松类、杉类、硬阔、软阔4个树种组和小径级(6～12 cm)、中径级(14～26 cm)、大径级(≥28 cm)3个胸径级,组成12个研究类组,将全年划分为4、5、6、7、8、9、10、11月至次年3月等8个生长月,对各类组的蓄积月生长率进行了抽样估算,获得了蓄积月生长率和年生长率值。在此基础上,分析了各类组的月生长率动态曲线。【结果】不同的树种组,其林木蓄积月生长率变动曲线有所不同,在4—10月的主生长期内,月生长率最高月与最低月比在2.0～2.2之间; 1年中,松、杉、软阔有2个生长高峰但出现时间与高度不尽一致,硬阔只有1个生长高峰; 随着径级的增大,蓄积生长率呈明显下降趋势,中径级蓄积生长率为小径级的77%～88%,大径级蓄积生长率为中径级的64%～90%、小径级的56%～77%。【结论】浙江全省林木的蓄积月际生长率存在较大差异,开展短周期森林资源调查时(如年度监测),需要进行时间误差校正和起源误差校正(起源调整系数)。研究认为时间误差的校正基准月定在6—8月期间为宜,在此基础上分别按天然、人工起源计算起源校正系数,浙江天然林的调整系数为0.908 6,人工林的为1.091 4。
Abstract
【Objective】In the wake of the shorting cycle and the reducing area of the forest resources monitoring, the precision monitoring became inevitable and the error control became the focus of the forest resources monitoring. 【Method】In this study, we used continuous monitoring results of fixed sample plots from 2004 to 2015 in Zhejiang Province as key data sources. These data were classified into 12 study groups based on four types of tree species(pine, Taxodium, hard and soft broad-leaved tree species)and three diameter at breast height(DBH)classes(small, medium and large). Furthermore, an entire year was classified into eight growth months(April, May, June, July, August, September, October and November to March of the following year). The monthly and annual volume growth rates of each group in each growth month were obtained by sampling estimation of the monthly growth rates of the 12 study groups. Based on these data, the monthly growth rate fluctuation curve of each group was analyzed. 【Result】The analysis indicated that the monthly volume growth rate fluctuation curve was different for the various tree species. In the main growth season, the ratio of the highest to lowest monthly growth rate was between 2.0 and 2.2. Two growth peaks with different appearance time and height were identified for the pine, Taxodium and soft broad-leaved tree species, whereas the hard broad-leaved tree species showed only one peak. However, when the DBH increased, the volume growth rate decreased significantly. The growth rate of trees with medium DBH was 77%-88% that of trees with small DBH. The growth rate of trees with large DBH was 64%-90% that of trees with medium DBH, and 56%-77% that of trees with small DBH.【Conclusion】There were large differences existing in the monthly volume growth rates of Zhejiang Province. Therefore the time error correction and the origin error correction were necessary in short cycle investigation of forest resources. It was appropriate to choose June, July or August as the correction month of time error. Based on this, the regulative coefficient of natural forest is 0.908 6, and the regulative coefficient of man-made forest is 1.091 4 in Zhejiang Province.
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基金
收稿日期:2016-09-13 修回日期:2016-12-15
基金项目:国家林业局“全国森林资源年度监测试点”项目(资调函[2014]53号)
第一作者:陶吉兴(taojixing@126.com),教授级高级工程师。
引文格式:陶吉兴,王文武,徐达,等. 基于固定样地连续监测数据的林木蓄积生长率月际分布[J]. 南京林业大学学报(自然科学版),2017,41(2):111-116.
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