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Estimating the impact of climate change on the carbon exchange of a temperate meadow steppe in China

Authors :
Zhao Zhang
Jiqiong Zhou
Yuchun Yan
Xu Wang
Baorui Chen
Hongbin Zhang
Xiaoping Xin
Source :
Ecological Indicators, Vol 140, Iss , Pp 109055- (2022)
Publication Year :
2022
Publisher :
Elsevier, 2022.

Abstract

Temperate meadow steppe is a representative ecosystem in northeast China. A process-oriented biogeochemistry model, denitrification–decomposition (DNDC) biogeochemistry model was employed and adapted to interpret and integrate field observations to determine whether temperate meadow steppe ecosystem was a carbon dioxide (CO2) sink during the growing seasons from 2010 to 2011. Then, we applied the model to predict the long-term impacts of climate change on the carbon dynamics in the ecosystem. Daily weather data for 2010–2011 in conjunction with the soil properties data and management practices data for this site were utilized as inputs to simulate the grass growth and soil carbon dynamics. The modeled carbon fluxes were compared with eddy tower data. The observed and modeled CO2 fluxes data were consistent, with both showing that the temperate meadow steppe is a stable carbon sink. Prediction tests were conducted with a baseline and eight alternative climate scenarios for the period 2017–2050. Simulations for the years 2017–2050 found that (1) the temperate meadow steppe will be a carbon sink under the baseline climate conditions; (2) the decelerated warming and drier climate scenario produced the lowest grass production and lowest carbon sequestration; and (3) the accelerated warming and wetter climate scenario produced the highest biomass and highest carbon sequestration. By using DNDC model we can understand carbon dynamics in temperate meadow steppe. The ecosystem production is limited by precipitation, a wetter future climate would substantially elevate the carbon sequestration capacity of the ecosystem. However, the carbon sequestration potential could significantly decrease if the climate is more arid from 2017 to 2050.

Details

Language :
English
ISSN :
1470160X
Volume :
140
Issue :
109055-
Database :
Directory of Open Access Journals
Journal :
Ecological Indicators
Publication Type :
Academic Journal
Accession number :
edsdoj.29252d829ce743669e167ee390bef4c2
Document Type :
article
Full Text :
https://doi.org/10.1016/j.ecolind.2022.109055