Abstract
Organic farming is often considered a strategy that increases croplands’ soil organic carbon (SOC) stock. However, organic farms currently occupy only a small fraction of cropland, and it is unclear how the full-scale expansion of organic farming will impact soil carbon inputs and SOC stocks. Here we use a spatially explicit biogeochemical model to show that the complete conversion of global cropland to organic farming without the use of cover crops and plant residue (normative scenario) will result in a 40% reduction of global soil carbon input and 9% decline in SOC stock. An optimal organic scenario that supports widespread cover cropping and enhanced residue recycling will reduce global soil carbon input by 31%, and SOC can be preserved after 20 yr following conversion to organic farming. These results suggest that expanding organic farming might reduce the potential for soil carbon sequestration unless appropriate farming practices are implemented.
Original language | English |
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Pages (from-to) | 719-725 |
Number of pages | 7 |
Journal | Nature Climate Change |
Volume | 13 |
Early online date | 29 Jun 2023 |
DOIs | |
Publication status | Published - Jul 2023 |
Bibliographical note
Funding Information:We thank R. Girault and Y. Behara for help regarding carbon losses in manure management process; D. Angers, E. Ceschia and C. Poeplau for inputs on how to consider cover crops. This work was funded by ADEME, Bordeaux Sciences Agro (Univ. Bordeaux), INRAE’s committee on organic farming (MP Métabio) and Aberdeen University. M.K. and P.S. acknowledge support from the CIRCASA project, which received funding from the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement no 774378.
Data Availability Statement
All data on crop areas, soil carbon inputs and soil organic carbon stocks for any of the scenarios and organic shares considered in this paper are available on a public repository57.Code availability
The model code for GOANIM is available in its most recent version at https://github.com/Pie90/GOANIM_public/, together with a full model documentation. All analyses were done using R x64 3.5.3. For RothC we used the ‘cin_month’ and ‘runExplicitSol’ functions from the RothC package to respectively estimate SCI0 and SOC stock evolution across time.
Keywords
- agriculture
- biogeochemistry
- Environmental impact