放牧对高寒草地植被生长的影响及其生物量预测模型构建
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  • 英文篇名:Effect of grazing on vegetation characters in alpine meadow and its prediction model construction
  • 作者:苏淑兰 ; 肖建设 ; 裴青生 ; 李晓东 ; 苏文将
  • 英文作者:SU Shulan;XIAO Jianshe;PEI Qingsheng;LI Xiaodong;SU Wenjiang;Qinghai Institute of Meteorological Science,Key Laboratory for Disaster Prevention and Mitigation in Qinghai Province;Qinghai Academy of Animal Science and Veterinary Medicine;
  • 关键词:放牧 ; 生物量 ; 高度 ; 盖度 ; 气象条件
  • 英文关键词:grazing;;biomass;;canopy height;;coverage;;climate conditions
  • 中文刊名:CYKX
  • 英文刊名:Pratacultural Science
  • 机构:青海省气象科学研究所青海省防灾减灾重点实验室;青海大学畜牧兽医科学院;
  • 出版日期:2019-01-15
  • 出版单位:草业科学
  • 年:2019
  • 期:v.36;No.306
  • 基金:青海省科技厅科技支撑计划“高寒地区家庭牧场精细化轮牧及羔羊生产研究与师范”;; 青海省气象局项目“草地植被系统碳储量模型构建及其变化分析”;; 青海省科技计划项目(2017-HZ-801)
  • 语种:中文;
  • 页:CYKX201901005
  • 页数:7
  • CN:01
  • ISSN:62-1069/S
  • 分类号:27-33
摘要
以青海省海晏县高寒草地为研究对象,分析了2003–2015年围封与自由放牧地植被变化及其与气象因子的关系。结果表明,1)2003–2015年生长季(5–9月)自由放牧草地植被高度、产量均显著低于围封草地,盖度仅6–7月显著高于围封样地(P<0.05);2)以围封草地7月末观测数据作为年牧草高度和盖度最大值,发现2003–2015年高度呈抛物线型变化趋势,盖度呈倒抛物线型变化趋势;3)年牧草产量最大值与6–7月平均气温趋势一致,且呈显著幂函数相关关系(P<0.01),降水对牧草的影响有一定的滞后性,即年牧草产量与上一年降水呈显著幂函数相关关系;4)利用SPSS线性回归分析做年牧草产量预测模型结果为y=124.44T6-7月+2.59R上一年–2 180.23(P<0.01)。
        Based on alpine meadow in Haiyan,Qinghai Province,we analyzed the effect of fencing and climatic conditions on vegetation characters from 2003 to 2015.The results indicate that:1) The free grazing grassland aboveground biomass,canopy height were significantly lower than that of fencing land(from May to September) in recent 13 years,and the coverage on June and July significantly lower than that in fencing land.2) Based on the data which were observed at the end of July in fencing grassland,we found that canopy height a trend of parabola,and the coverage showed a power function trend;3) The maximum value of annual aboveground biomass is consistent with the trend of average temperature from June to July,and has a significant power function relationship(P<0.01),the impact of the precipitation for the remain delay,aboveground biomass and the year precipitation has a significant power function relationship;4) We used SPSS l Linear regression analysis to build a prediction model for the aboveground biomass,which showed as follow:y=124.44TJune-July+2.59 Rprevious year–2 180.23(P<0.01).
引文
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