JOURNAL OF YANGTZE RIVER SCIENTIFIC RESEARCH INSTI ›› 2020, Vol. 37 ›› Issue (5): 59-66.DOI: 10.11988/ckyyb.20190138


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 Online:2020-05-01 Published:2020-06-10

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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