Speaker
Description
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Introduction
Global warming is a pressing issue for all countries and especially their primary producers. The carbon (C) farming industry is an integral part of Europe’s and Australia’s transition to address the threat of global warming.
Prior to designing C farming projects, proponents, policy makers and government agencies need to identify where it is most effective to invest to sequester C. The scientific literature has abundantly demonstrated that the C sequestration potential varies significantly across the landscape, depending on the agricultural management practices, the physico-chemical properties of the soil itself and the characteristics of the local climate (Li et al., 2020). Moreover, it is unclear whether the strategies proposed today to sequester C in specific regions will be effective under future climatic conditions.
This project aims therefore to use state-of-the-art technology to develop, for the first time, a high-resolution, publicly available online decision support system displaying the C sequestration potential across the entire State of Queensland in Australia, under current and future climate change scenarios. -
Materials and methods
Through a collaboration between the Queensland Department of Environment, Science and Innovation, and INRAE (French National Research Institute for Agriculture, Food, and Environment), this ongoing study assesses the potential of sequestering C in the soil and woody vegetation components by simulating three land use change scenarios: converting land from i) cropland to grassland, ii) from cropland to forest, and iii) from grassland to forest. Each land use change scenario is simulated for a duration of either 25 or 100 years (the two possible permanence periods prescribed by the Australian Clean Energy Regulator) under current and future climatic conditions.
The C sequestration potential is assessed using the newly released DayCent-CABBI biogeochemical model, which incorporates microbial-explicit processes and a refined perennial plant submodule. The model is parameterised using publicly available spatial datasets regarding soil, weather and land use information, as well as local expert knowledge to determine region-specific vegetation management data (e.g., common crop rotations, sowing densities, planting and harvesting dates, fertiliser and irrigation rates, etc.). -
Results and Discussion
To date there are no tools that allow C farming project proponents, policymakers and government agencies to visualise where, across different regions and landscapes, there is the highest C sequestration potential under current and future climatic conditions.
To date, the initial model calibration and validation phase has focused on sugarcane cropping systems, showing promising results (Fig. 1). On average, the model provided reliable simulations of soil water and nitrogen dynamics, which resulted in a good agreement between observed and simulated yields, with RRMSE and Modelling Efficiency values of 11.1 % and 0.79, respectively.
This project uses Queensland as a case study to set up a modelling framework, which will provide a regularly updatable and transparent state-of-the-art platform to support science-based decision making in C farming projects. Importantly, the framework is designed to incorporate other features, such as the ability to simulate the impact of different crop management practices and the full suite of greenhouse gas emissions (carbon dioxide, methane and nitrous oxide) across land uses and climatic scenarios. The methodology established will be available to develop soil C sequestration potential maps of other statutory bodies (e.g. Australia and France), refining the approach used by Launay et al. (2021) and Martin et al. (2021) by allowing to test the agronomic and environmental performances of current and innovative cropping systems (including different crop rotations under conservation and organic agriculture) under climate change. -
References
Launay, C., Constantin, J., Chlebowski, F., Houot, S., Graux, A.-I., Klumpp, K., Martin, R., Mary, B., Pellerin, S., Therond, O., 2021. Estimating the carbon storage potential and greenhouse gas emissions of French arable cropland using high-resolution modeling. Glob. Chang. Biol. 27, 1645–1661. https://doi.org/https://doi.org/10.1111/gcb.15512
Li, J., Nie, M., Pendall, E., 2020. Soil physico-chemical properties are more important than microbial diversity and enzyme activity in controlling carbon and nitrogen stocks near Sydney, Australia. Geoderma 366, 114201. https://doi.org/https://doi.org/10.1016/j.geoderma.2020.114201
Martin, M.P., Dimassi, B., Román Dobarco, M., Guenet, B., Arrouays, D., Angers, D.A., Blache, F., Huard, F., Soussana, J.-F., Pellerin, S., 2021. Feasibility of the 4 per 1000 aspirational target for soil carbon: A case study for France. Glob. Chang. Biol. 27, 2458–2477. https://doi.org/https://doi.org/10.1111/gcb.15547
| Keywords | Land use change, decision support system, future climatic conditions |
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