4.3 Review

Use of models to evaluate carbon sequestration in agricultural soils

Journal

SOIL SCIENCE AND PLANT NUTRITION
Volume 66, Issue 1, Pages 21-27

Publisher

TAYLOR & FRANCIS LTD
DOI: 10.1080/00380768.2019.1702477

Keywords

Climate change mitigation; DNDC; long term experiment; RothC; soil organic matter

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The Rothamsted Carbon (RothC) model, which is one of widely used soil carbon (C) models, was validated against long-term experimental datasets in Japan and modified to suit Andosols and paddy soils reflecting unique soil C turnover mechanisms in these soils. Nationwide soil C calculation system was developed by combining these modified models and spatial model input data such as weather, soil type, land use, and agricultural activities. The model was validated in China and Thailand by using long-term field experimental datasets, too. Further studies especially in tropical Asia will be needed. Matching conceptual model C pools with measurable fractions have been big challenges. Using various plant materials, two conceptual pools of plant litter, decomposable plant material (DPM) and resistant plant material (RPM), in the RothC were successfully identified. It was achieved by comparing the default proportions of DPM and RPM pools in the RothC and proportions in plant material fractions determined by two-step acid hydrolysis with H2SO4. The trial to match all of five C pools in the model, however, remains unachieved though a study was conducted comparing not only the size of C pools but mean residence time of the pools. A web-based decision support tool called 'Visualization of CO2 absorption by soils' was developed. This allows users to easily calculate changes in soil C, CH4 and N2O emissions, and fossil fuel consumption. With this tool, farmers can see how to improve the environmental sustainability of their products and this tool may help spread mitigation options widely. Soil C sequestration can help achieve climate change mitigation and sustainable agricultural production. Importance of long-term field observations should be more highlighted because long-term experiments have supported the development of modeling approaches. I hope models will be more widely used by decision makers. Collaboration between modeling and monitoring studies is important.

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