基于SOFM网络对黄土高原森林生态系统的养分循环分类研究  

SOFM-based nutrient cycling classification of forest ecosystems in the Loess Plateau

作　　者：陈凯[1] 刘增文[2,3] 李俊[2] 田楠[1] 时腾飞[2] 

机构地区：[1]西北农林科技大学林学院,杨凌712100 [2]西北农林科技大学资源环境学院,杨凌712100 [3]农业部黄土高原农业资源与环境修复重点开放实验室,杨凌712100

出　　处：《生态学报》2011年第23期7022-7030,共9页Acta Ecologica Sinica

基　　金：国家自然科学基金项目(31070630)

摘　　要：对森林生态系统进行分类是认识森林生态过程的根本途径,传统的从结构角度对森林生态系统分类只能反映森林的外在特征,而无法从功能角度区别森林的本质差异。通过对黄土高原3个生物气候区18个不同森林生态系统的养分循环特征测算和分析,选取了能全面反映养分的积累和分布(生物量、枯落物积累量、养分积累量)、循环通量(年吸收量、年存留量、年归还量)以及养分循环效率(循环系数、利用系数、养分生产力)等多方面指标作为分类指标体系,利用自组织映射特征网络(Self-Organizing Feature Maps,SOFM)聚类方法,从养分循环的角度将黄土高原森林生态系统划分为2个一级类型,6个二级类型。该分类结果与实际较符,从而探索了森林生态系统的功能分类方法,也验证了SOFM网络模型应用于森林养分循环分类的可行性。The classification of forest ecosystems is fundamental for identifying forest ecological processes. Traditional methods of structural classification, such as climatic, geo-hydrologic, vegetative, and eco-systematic methods, reflect only external forest features without distinguishing essential functional differences. The functional classification of forest ecosystems would help remedy the deficiencies of traditional structural classification methods and provide a theoretical basis for forest management. Nutrient cycling, which is one of the main functions of forests, plays an important role in protecting the stability and sustainable development of forest ecosystems. An attempt to classify a forest ecosystem according to nutrient cycling processes is certainly a significant work. In this paper, nutrient cycling characteristics of 18 different forest ecosystems in 3 regions of the Loess Plateau were analyzed. The regions included the sand-blown region in the north part of the Loess Plateau, the hilly region in the middle part of the Loess Plateau, and the gullied region in the south part of the Loess Plateau. Indices of nutrient accumulation and distribution （ including biomass, litter accumulation, and nutrient accumulation）, nutrient cycling flux （ annual absorption, retention, and return）, and nutrient cycling efficiency （ recycling coefficient, utilization ratio, and nutrient productivity） were calculated. Self-organizing Feature Maps （SOFM） was used for nutrient cycling classification. Through the analysis, two first-order classes （ including I-Moderate-quick nutrient cycling and II-Slow nutrient cycling） and six second-order types were identified. The classification results were consistent with the actual forest characteristics. Furthermore, the results accurately reflected differences in nutrient cycling characteristics among the different ecosystems. A variety of indices reflecting different nutrient cycling processes were used in this classification. This approach avoided errors and ma

关 键 词：森林生态系统分类 养分循环 自组织映射特征网络 

分 类 号：S718.5[农业科学—林学]