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Xiaogang Yin

Multidisciplinary Research Unit for Grasslands and Forage Crops, Lusignan

Modelling root turnover and SOC storage with STICS

Annual meeting: 2018

Fields-Topics: P3 Population and Ecosystems,P6 Applied Maths

Type of talk: Fellows Speed Presentation

Modelling root turnover and SOC storage with STICS


I had received my PhD degree on 28th June 2015 from China Agricultural University (CAU). Then I had been a postdoctoral researcher in Aarhus University during July 2015 to April 2016. Then I was included in the Auto’N project in INRA AgroImpact as a postdoctoral researcher since 1st November 2016. I started the AgreenSkills+ project since 1st May 2017. I am also currently an associate professor in the college of agronomy and biotechnology, China Agricultural University since January 2018. I am interested in nitrogen and carbon cycling in agroecosystems, climate change and adaptation, and crop modelling. I have been included in several national and international projects in crop production, crop modelling, climate change and N cycling since 2010.


Modelling root turnover and SOC storage with STICS

How to optimize carbon balance and increase soil organic carbon (SOC) storage in cultivated soils has received great attention with the aim of mitigating greenhouse gas emissions from agriculture. Modelling SOC storage is a cost-effective way to explore measures that both improve SOC stocks and enhances crop production. However, it is still a challenge to predict SOC storage in a wide range of conditions and to simulate management options such as crop diversity in the rotation. Moreover, the contribution of belowground materials, especially the impact of crop root traits (such as root density, root lifespans and activity in the rhizosphere), still remains uncertain. It is hypothesized that the contribution of belowground materials to SOC storage is strongly related to root activity and root turnover which vary widely between crop species. A new research version of the STICS soil-crop model (v8.42), improving the root growth module for perennial crops, was developed to simulate strategies of crop carbohydrates allocation, root turnover and belowground carbon inputs to soil. It has been successfully parameterized for Miscanthus, Switchgrass and alfalfa. Thus, the objectives of the research project are: i) to parameterize the new STICS root module for typical cereal/grass crops (namely maize, winter wheat and tall fescue), ii) to assess the impacts of root traits on SOC storage in crop rotations (mainly including maize, winter wheat, tall fescue, Miscanthus, Switchgrass and alfalfa) for typical long term experiments in France. The International Database for Evaluation of STICS (IDE-STICS) and the long-term field experiments from the Observatories network ACBB will be used to parameterize and validate the model. The project is expected to validate the genericity of the new STICS root module and improve our understanding of the driving factors of SOC storage with robust simulations for cereal/perennial crop rotations.

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