Soil respiration simulation based on soil temperature and water content in artificial smooth brome grassland
Juying Wu A , Zhuo Pang A B , Tiejun Sun A , Haiming Kan A , Wei Hu A and Xiaona Li A
+ Author Affiliations
- Author Affiliations
A Research and Development Centre for Grass and Environment, Beijing Academy of Agriculture and Forestry Sciences, 100097, Beijing, China; Postal address: No. 9, Middle of Shuguang Garden Road, Haidian District, 100097, Beijing, China.
B Corresponding author. Email: pangzhuo@grass-env.com
The Rangeland Journal 38(6) 579-589 https://doi.org/10.1071/RJ16023
Submitted: 16 March 2016 Accepted: 25 October 2016 Published: 14 December 2016
Abstract
Correctly quantifying the relationships between soil respiration and environmental factors and their sources of variability is essential to predict future carbon fluxes and climate feedback. Soil water conditions and soil temperature strongly affect soil respiration and the dynamics of soil organic matter. Despite this, simulation of soil respiration (Rs) based on soil temperature (Ts) and soil volumetric water content (θ) must still be improved, as demonstrated by its discrepant model performance among different seasons. With the objective of gaining a further understanding of the relationships of Rs with Ts and θ and providing an improved model to simulate Rs variations, we measured hourly Rs, Ts and θ using the chamber technique in artificial smooth brome grassland for analysis. We began by dividing the four seasons of a year according to the daily mean air temperature, followed by representing the seasonal variation of Rs, Ts and θ. We found that Rs correlated significantly with Ts in an exponential relationship and with θ in a parabolic relationship seasonally, where the determination coefficient of the Rs-θ relationship was significantly larger than that of the Rs-Ts relationship. We also discovered that the shape of the Rs-θ relationship was seasonally dependent because the optimal θ and the width of the peak Rs around the optimal θ were seasonally specific. Finally, by considering seasonality, the combinational simulation model explained more variation of soil respiration. Thus, seasonality should be considered for more reliable model simulations of soil respiration. These findings are relevant for more accurate predictions and modelling of soil respiration, particularly in temperate artificial grasslands with a continental monsoon climate, where the ‘Birch effect’ strengthens seasonality, and these findings further our understanding of changes in the rates of soil carbon losses as artificial grassland is established.
Additional keywords: climate change, conservation biology, grasslands, soil carbon, restoration ecology.
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