长江科学院院报 ›› 2020, Vol. 37 ›› Issue (5): 59-66.DOI: 10.11988/ckyyb.20190138

• 水土保持与生态建设 • 上一篇    下一篇

2010—2015年三江源地区植被净初级生产力变化特征及影响因素分析

贺倩1, 杨雪琴1, 戴晓爱1,2   

  1. 1.成都理工大学 地球科学学院,成都 610059;
    2.成都理工大学 地学空间信息技术国土资源部重点实验室,成都 610059
  • 收稿日期:2019-01-03 出版日期:2020-05-01 发布日期:2020-05-01
  • 作者简介:贺 倩(1996-),女,山西吕梁人,本科在读,主要从事地理信息科学研究。E-mail:18215671290@163.com
  • 基金资助:
    2018年国家级大学生创新创业训练计划项目(201810616018)

Variation Characteristics and Influence Factors of Net PrimaryProductivity of Vegetation in the Three-River Headwaters Regionfrom 2010 to 2015

HE Qian1, YANG Xue-qin1, DAI Xiao-ai1,2   

  1. 1. College of Earth Sciences, Chengdu University of Technology, Chengdu 610059, China;
    2. Key Laboratoryof Geoscience Spatial Information Technology of Ministry of Land and Resources of China, Chengdu Universityof Technology, Chengdu 610059, China
  • Received:2019-01-03 Published:2020-05-01 Online:2020-05-01

摘要: 三江源地区生态环境先天脆弱,掌握其植被净初级生产力(Net Primary Productivity,NPP)的时空变化特征及其影响因素对于环境保护具有重要意义。基于改进的CASA(Carnegie-Ames-Stanford Approach)模型估算三江源地区2010—2015年的NPP空间分布及变化特征,引入地理探测器探讨植被、气候和地形因素及其交互作用对NPP的影响。结果表明:①整体上三江源地区NPP表现为自东向西逐渐减小的空间分布特征;2015年较2010年中部地区NPP减少最为严重,其次为西部地区,而东部NPP增加,且NPP的减少量大于NPP的增加量。②各因素对NPP的影响程度不同,从NPP空间分布现状角度分析,对NPP的影响由大到小依次为NDVI、太阳辐射、降雨量、温度、高程、坡度、坡向;从NPP动态变化角度分析,影响由大到小依次为NDVI、降雨量、太阳辐射、温度。③各因素的交互作用对NPP的空间分布现状及动态变化都表现出双因子或非线性增强作用,且NDVI与降雨量的交互作用最强。④地理探测器能够较好地指示各因素及其交互作用对NPP的影响,具有较好的效果。研究结果将为三江源地区的生态环境保护工作提供依据。

关键词: NPP, 时空变化, CASA模型, 地理探测器, 影响因素, 三江源地区

Abstract: The ecological environment in the Three-River Headwaters Region is inherently fragile. Understanding the temporal and spatial variation characteristics of the net primary productivity (NPP) of vegetation and its influence factors is of great significance for environmental protection. In this paper we estimated the spatial distribution and variation characteristics of NPP in the region from 2010 to 2015 using the improved CASA (Carnegie-Ames-Stanford Approach) model, and examined the influences of vegetation, climate and topography and their interactions on NPP via Geodetector. Results show that: (1) NPP in the Three-River Headwaters Region decreased gradually from east to west in general; NPP in 2015 decreased most seriously in the central region, followed by that in the western region, while increased in the eastern region compared to 2010, and the decrement of NPP was greater than the increment. (2) The influence degree of various factors on NPP was different. From the perspective of the current spatial distribution of NPP, the influence of NDVI was the largest, followed by solar radiation, precipitation, temperature, elevation, slope and aspect in sequence; from the perspective of dynamic variation of NPP, NDVI, precipitation, solar radiation and temperature were major influence factors in sequence. (3) The interactions of various factors on the spatial distribution status and dynamic variation of NPP showed a double-factor or nonlinear enhancement, and the interaction between NDVI and precipitation was the strongest. (4) Geodetector is well effective in depicting the influence of various factors and their interactions on NPP.

Key words: NPP, temporal and spatial variations, CASA model, Geodetector, influence factor, Three-River Headwaters Region

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