摘要
以八宝河流域为研究区域,研究了3种不同植被类型下土壤全碳(tOTAL cARBON,TC)、全氮(tOTAL nITROGEN,TN)含量变化特征及其与环境因子的关系,结果表明:(1) 0~50 CM土层,TC含量大小为林地>灌丛>草地,林地土壤TC含量(87.29 G·KG^(-1))显著大于灌丛(53.56 G·KG^(-1))和草地(52.32 G·KG^(-1))。TN含量依然表现为林地最大(5.89 G·KG^(-1)),其次为草地(4.51 G·KG^(-1)),灌丛的TN含量最低(4.28G·KG^(-1))。3种植被类型土壤TC、TN含量随土层深度的增加均呈减少趋势。(2)环境因子间相互作用,共同影响土壤碳氮含量。直接作用效应:土壤TC和TN相互直接作用最大。间接作用效应:土壤含水量(sOIL wATER cONTENT,SWC)主要通过TN对土壤TC含量产生间接正效应,容重(bULK dENSITY,BD)主要通过TC对土壤TN含量产生间接负效应。研究该区域不同植被类型下土壤TC、TN变化特征及其主要影响因子,可为该区域土地资源的合理利用提供科学资料。
Taking Babao River Basin as the research area,the characteristics of Soil Total Carbon(STC)and Soil Total Nitrogen(STN) content and their relationships with environmental factors were studied under three different vegetation types.The results showed that:(1) In the 0-50 cm soil layer,the magnitude of STC content was woodland > scrub > grassland,and the STC content of woodland(87.29 g·kg^(-1)) was significantly greater than that of scrub(53.56 g·kg^(-1)) and grassland(52.32 g·kg^(-1)).The STN content still showed maximum in the woodland(5.89 g·kg^(-1)),followed by grassland(4.51 g·kg^(-1)) and the lowest in the scrub(4.28 g·kg^(-1)).STC and STN content decreased with increasing soil depth in three vegetation types.(2) Environmental factors interacted with each other and jointly affected STC and STN.Direct effect:STC and STN content had the greatest direct effect on each other.Indirect effects:soil water content had an indirect positive effect on STC content mainly through STN,and bulk density had an indirect negative effect on STN content mainly through STC.The study of the characteristics of STC and STN changes and their main influencing factors under different vegetation types in the region can provide scientific information for the rational utilization of land resources in the region.
作者
刘英
Liu Ying(Qinghai Agriculture and Animal Husbandry Engineering Consulting Corporation,Xining 810008,China)
出处
《青海科技》
2023年第5期43-48,共6页
Qinghai Science and Technology
关键词
八宝河流域
土壤碳氮
环境因子
通径分析
Babao River Basin
Soil carbon and nitrogen
Environmental factor
Path analysis