摘要
【目的】树干径向变化测量仪(Dendrometer)可以连续记录树干各阶段变化信息,包括树干收缩、恢复和生长等,提取和分析这些信息对于深入理解树木径向生长及其对环境的响应具有重要价值,而快速高效地提取和整合海量数据需进行繁复的数据处理与分析。为提高树干径向变化数据的分析效率和管理能力,林业工作者亟需易操作且实用的树干径向变化数据分析程序。【方法】针对常用周期循环法提取各阶段树干径向变化的原则和树干径向昼夜变化存在规律及树干径向变化测量仪运行中可能出现异常情况,基于Python语言开发了一个用户友好型的树干径向变化提取程序DAIP(Dendrometer Analyzer In Python),并以2019年生长季累月(6—9月)六盘山香水河与叠叠沟小流域的华北落叶松(Larix gmelinii var.principis-rupprechtii)人工林树干径向变化数据为例,提取和分析了树干径向变化的主要参数,并与半自动化提取程序“dendrometeR”进行了比较。【结果】在提取结果方面,DAIP提取树干半径变化的主要参数值与“dendrometeR”程序的提取结果基本一致,保证提取数据的可靠性。相比传统的数据处理方式,DAIP在异常数据判定和高效提取径向数据方面具有较大优势,可以较好识别分布在不同气候区内树体特征各异的华北落叶松树干径向变化数据集的“数据缺失”、“数据异常增加和减小”以及“数据无变化”等可疑数据类型;DAIP可快速自动提取生长季内树干半径的变化周期数、收缩阶段历时及收缩量、恢复阶段历时及恢复量、增加阶段历时及增量等主要参数。诚然,DAIP当前版本存在一定不足,如在异常数据判定方面,对“长时段数据无变化”这种异常数据的界定还存在不确定性;在树干径向变化参数提取方面,若各变化阶段分界点处的数据波动较大,对分界点的判定可能存在误差。【结论】DA
【Objective】The Dendrometer can record raw data and provide valuable information of stem radial variation in time series,including stem shrinkage,recovery and increment.It is of great importance to extract and analyze the variation,which contributes to comprehend tree growth and the responses to the environment.However,it is impossible to extract and integrate the massive data efficiently without complicated data processing and analysis.It is urgent to develop a practical stem variation data analysis program for improving the data analysis efficiency and management ability.【Method】In terms of three premises the principle of extracting stem radial variation of each stage by periodic cycle method,the pattern of the diurnal variation and the abnormality occurred during the operation of dendrometer,we developed a user-friendly stem radial variation extraction program based on Python(Dendrometer Analyzer In Python,DAIP).With the data of radial variation of Larix gmelinii var.principis-rupprechtii plantations during the 2019 growing season(From June to September)in the Xiangshuihe and Diediegou watersheds of Liupan Mountain,China,we extracted and analyzed the key parameters of stem radial variation by DAIP,and compared the calculation results with those by the semi-automatic"dendrometeR"extraction program.【Result】The principal parameter values of the stem radial vari-ation generated and calculated by the DAIP were basically consistent with those by the"dendromete R"program.Compared with tra-ditional methodologies,DAIP had greater advantages in the determination of abnormal data and efficient data extraction,and could recognize the suspicious data types more precisely such as"time warp","sudden growth or shrinkage"and"constant values"in the data set of trees with different characteristics collected from separate climate regions.It also could automatically and quickly export the main stem variation parameters such as the amount of stem radius variation cycles,the daily amplitude and duration of shrinkage,recov
作者
刘泽彬
刘安迪
于澎涛
涂立辉
LIU Zebin;LIU Andi;YU Pengtao;TU Lihui(Key Laboratory of Forest Ecology and Environment of National Forestry and Grassland Administration,Institute of Forest Ecology,Environment and Nature Conservation,Chinese Academy of Forestry,Beijing 100091,China;The Experimental High School Attached to Beijing Normal University,Beijing 100032,China)
出处
《陆地生态系统与保护学报》
2021年第1期90-99,共10页
Terrestrial Ecosystem and Conservation
基金
宁夏多功能林业分区域研究与示范(YES-16-12)
中央级公益性科研院所基本科研业务费专项资金项目(CAFYBB2020QB004)。
