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草业学报 ›› 2014, Vol. 23 ›› Issue (6): 11-19.DOI: 10.11686/cyxb20140602

• 论文 • 上一篇    下一篇

基于CSCS的黑河上游潜在植被NPP及其水热关系研究

王大为1,2,赵军1,*,韩涛2,李丽丽3   

  1. 1.西北师范大学地理与环境科学学院, 甘肃 兰州 730070;
    2.西北区域气候中心, 甘肃 兰州 730020;
    3.兰州大学资源环境学院,甘肃 兰州 730000
  • 收稿日期:2013-11-04 出版日期:2014-12-20 发布日期:2014-12-20
  • 通讯作者: E-mail:zhaojun@nwnu.edu.cn
  • 作者简介:王大为(1983-),男,甘肃兰州人,助理工程师,硕士
  • 基金资助:
    国家自然科学基金(40961026和30972135)资助

Analysis of net primary production of potential natural vegetation in the upper reaches of the Heihe River basin

WANG Da-wei1,2,ZHAO Jun1,HAN Tao2,LI Li-li3   

  1. 1.College of Geography and Environment Science, Northwest Normal University, Lanzhou 730070,China;
    2.Northwest Regional Climate Center, Lanzhou 730020, China;
    3.College of Earth and Environmental Sciences, Lanzhou 73000, China
  • Received:2013-11-04 Online:2014-12-20 Published:2014-12-20

摘要: 潜在植被NPP空间分布格局是植被长期适应自然的结果,是NPP与外界环境关系的反映,通过这种关系有助于理解地表碳循环发生的环境背景。本研究利用综合顺序分类法(CSCS)对黑河上游潜在植被进行模拟,通过植被反演计算潜在植被NPP总量以及累积量,探讨了潜在植被NPP与水热因子之间的相关性。结果表明,黑河上游潜在植被类型共有8个类,且具有明显的垂直地带性分布特征。潜在植被NPP积累量分布特征为河流流经的地区高于其他地区,在山区中,随着海拔的上升,NPP积累量呈先上升后下降的趋势,潜在植被的NPP积累量由黑河上游水热分布条件决定的。NPP积累量与≥0℃年积温在寒冷和寒温级内呈正相关,在微温级内呈负相关;与湿润度在干旱、微干、微润和湿润4个等级内呈正相关,在潮湿级内呈负相关。这种分布格局反映了潜在植被对生境和气候变化的多元适应性结构。

Abstract: Understanding the spatial pattern of the potential natural vegetation (PNV) is import for identifying the response of spatial pattern to the climate change and carbon cycling and for predicting net primary production (NPP) distribution of PNV in ecological restoration projects. The dynamic characteristics of spatial distribution, the potential vegetation of NPP, the gross and cumulative NPP and the relationship between NPP and hydro-thermal factors on the upper research of Heihe River were investigated by using meteorological data including rainfall, temperature and accumulative temperature ≥0℃ (1960-2009) in conjunction with the location and altitude record from 12 climate stations in western China covering the period from 1960 to 2009. Based on these data, we used a comprehensive sequential classification system (CSCS) method, validated at regional and global scales, to estimate the NPP variation of grassland ecosystems and the responses to climate change. PNV’s fell into 8 classes based on vertical zones. Increasing altitude in the mountainous region resulted in NPP initially tending to rise but subsequently decline. The predictive distribution of NPP was dependent on hydro-thermal factors. The relationship between NPP and annual accumulated temperature ≥0℃ was negative in cold areas, but was positive in cool temperate areas. There were positive correlations between NPP and humidity in arid, semiarid, sub-humid and humid areas. The spatial pattern of PNV reflected the ability of vegetation to adapt to different habitats and climate change.

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