Effects of climatic factors on the net primary productivity in the source region of Yangtze River, China

Zhe Yuan,Jijun Xu,Yongqiang Wang,Zhiguang Wu

doi:10.1038/s41598-020-80494-9

Abstract

The ecosystem of the Source Region of Yangtze River (SRYR) is highly susceptible to climate change. In this study, the spatial–temporal variation of NPP from 2000 to 2014 was analyzed, using outputs of Carnegie–Ames–Stanford Approach model. Then the correlation characteristics of NPP and climatic factors were evaluated. The results indicate that: (1) The average NPP in the SRYR is 100.0 gC/m2 from 2000 to 2014, and it shows an increasing trend from northwest to southeast. The responses of NPP to altitude varied among the regions with the altitude below 3500 m, between 3500 to 4500 m and above 4500 m, which could be attributed to the altitude associated variations of climatic factors and vegetation types; (2) The total NPP of SRYR increased by 0.18 TgC per year in the context of the warmer and wetter climate during 2000–2014. The NPP was significantly and positively correlated with annual temperature and precipitation at interannual time scales. Temperature in February, March, May and September make greater contribution to NPP than that in other months. And precipitation in July played a more crucial role in influencing NPP than that in other months; (3) Climatic factors caused the NPP to increase in most of the SRYR. Impacts of human activities were concentrated mainly in downstream region and is the primary reason for declines in NPP.

Highlights

As an important component of global terrestrial ecosystem, vegetation plays a crucial role in in energy transfer, carbon cycle, water balance and climate r egulation[1]
The changes in vegetation in alpine regions have been investigated with NDVI, EVI or Net primary productivity (NPP)
The simulated average NPP in our study was 100.0 gC/km[2] in Source Region of Yangtze River (SRYR), which was similar to the value of 82.04 gC/km[2] in SRYY20 and 143.17 gC/km[2] in TRH21

Summary

Introduction

As an important component of global terrestrial ecosystem, vegetation plays a crucial role in in energy transfer, carbon cycle, water balance and climate r egulation[1]. Net primary productivity (NPP) is defined as the net amount of carbon taken in by plants via photosynthesis, and is equal to the difference between the carbon assimilated during photosynthesis and that released during plant r espiration[2,3] It is an important indicator of ecosystem function and widely used for vegetation dynamics measure and ecological security assessment[4,5]. Numerous ecosystem productivity models based on RS and light use efficiency (LUE) can be applied for estimating NPP, such as Carnegie–Ames–Stanford-Approach (CASA) m odel[7] and Biome Biogeochemical Cycles (Biome-BGC) model[8]. The outputs of these models, namely geospatial NPP simulated results, can reveal continuous spatio-temporal patterns of vegetation. The hydrothermal climatic factors refer to precipitation and temperature, which can be obtained from meteorological data and the NPP data was simulated by CASA model

Methods

Results

Conclusion