内蒙古草原生物量和地下生产力空间格局及其关键影响因子  

Geographic patterns and controlling factors of biomass and belowground net primary productivity of Inner Mongolia grassland

作　　者：赵鸣飞[1,2] 王宇航[1,2] 左婉怡 康慕谊[1,2] 纪文瑶[1,2] 戴诚[1,2] 

机构地区：[1]北京师范大学地表过程与资源生态国家重点实验室,北京100875 [2]北京师范大学资源学院,北京100875

出　　处：《生态学杂志》2016年第1期95-103,共9页Chinese Journal of Ecology

基　　金：科技部科技基础性工作专项(2011FY110300);国家自然科学基金项目(41271059)资助

摘　　要：基于33个样地获取的地上、地下生物量和地下生产力实测数据,结合气候、土壤、空间因子和多样性等多个指标,利用置换检验、回归分析和分类回归树等统计方法,探究了内蒙古草原的地下生产力、生物量和地下/地上生物量比沿环境梯度变化的空间格局及导致形成该格局的关键影响因子。结果表明:由西南向东北方向,地下生产力、地上生物量和地下生物量均呈显著上升趋势,地下/地上生物量比则无任何显著趋势;地下生产力、地上生物量、地下生物量和地下/地上生物量比的分类回归树模型解释率分别为58.3%、53.3%、78.8%和53.8%。模型显示:地下生产力与土壤容重和Pielou均匀度指数关系最为密切,地上生物量则主要受最暖月最高温控制,而地下生物量变异则分别与年均降水量、p H值和土壤含水量等因子有关,地下/地上生物量比与海拔有一定关系;分别以地下生产力、地上生物量、地下生物量和地下/地上生物量比对应分类回归树模型所甄别出的关键因子建立广义可加模型,所有模型的偏差解释率均在50%以上,表明广义可加模型代表了因变量的大部分变异。地下生产力与土壤容重呈分段函数关系,地上生物量与最暖季最高温显示出非线性关系,地下生物量则与年均降水量整体呈正相关关系,地下/地上生物量比与海拔表现出密切但复杂的关系,且受左右两端极值点影响较大。本研究不仅能为较大尺度上生物量、生产力空间格局研究提供了案例支持,同时对于草地生态系统生产力的深入研究、碳循环的长期监测和天然草场的合理利用与管理等均有重要意义。In order to know the spatial patterns of belowground net primary productivity （BNPP）, aboveground biomass （ AGB ）, belowground biomass （ BGB ） and belowground/ aboveground biomass ratio （B/A） , and the key environmental factors affecting those variables, BNPP, ABG, BGB and soil samples were obtained from 33 sites within a transet （〉1500 km） in the Inner Mongolia grasslands, especially BNPP were collected by ingrowth-bag method and BGB by soil core method. For vegetation survey in each site, we selected 4 subplots （a size of 1 mx 1 m） within one 10 mX 10 m plot to record the properties of each plant species involving height, coverage and abundance. In laboratory, we analyzed 5 soil chemical and physical characteristics. We also got 19 climate indicators and calculated 4 species diversity indices including richness in- dex, Shannon index, Simpson index and Pielou index. We used linear regression analysis to in- vestigate the spatial patterns of the dependent variables, and classification and regression trees （CART） to screen the key envirnmental factors. Linear regression models show that from thesouthwest to the northeast, there are obvious increasing trends in the response variables apart from B/A. Especially, the AGB and BGB data from the southwest exhibit signifant linear relation- ships. CART models of BNPP, AGB, BGB and B/A explain most of variations of the predictors, which represent 58.3%, 53.3%, 78.8% and 53.8% total sum of squares, respectively. We de- tected the possible key factors affecting those dependent variables by CARTs （namely, soil bulk density and Pielou index to BNPP, maximum temperature of warmest month to AGB, annual pre- cipitation to BGB, and eleviation to B/A）. We used BNPP, AGB, BGB and B/A respectively with the key factors identified by CART to establish GAM. Explained deviation rates of all models are over 50%, which indicates that the GAM represents most of the variation of the dependent variable and to a certain extent, verifing the accuracy of CART.

关 键 词：生物量 地下生产力 地下/地上生物量比 空间格局 环境因子 内蒙古草原 

分 类 号：S812[农业科学—草业科学]