Mapping soil organic carbon on a national scale: Towards an improved and updated map of Madagascar
Ramifehiarivo, Nandrianina | Brossard, Michel | Grinand, Clovis | Andriamananjara, Andry | Razafimbelo, Tantely | Rasolohery, Andriambolantsoa | Razafimahatratra, Hery | Seyler, Frédérique | Ranaivoson, Ntsoa | Rabenarivo, Michel | Albrecht, Alain | Razafindrabe, Franck | Razakamanarivo, Herintsitohaina
Assessment of soil organic carbon stocks (SOCs) is highly relevant considering that SOCs is the central driver in climate change mitigation and soil fertility. In Madagascar, a first attempt at mapping SOCs on a national scale was undertaken in 2009 with previous soil data. Advanced research on soil carbon mapping on a global scale is required to enable better land use decisions. This study aims to (i) evaluate the drivers of soil organic carbon (SOC) storage in the first 30cm soil layer on a national scale from spatially explicit explanatory environmental variables and a recent soil database and (ii) update the spatial distribution of SOCs at this scale through digital mapping. A spatial model was established using randomForest, a decision tree algorithm and based on 10 pedoclimatic, topographic, and vegetation variables. The model was developed with 1993 available soil plot data (collected from 2010 to 2015) and their environmental information (“VALSOL-Madagascar” database). These data were divided into two sets: a first set (n=835) used for model calibration and a second set (n=358) for external validation. Results showed that mean annual temperature (MAT, °C), mean annual precipitation (MAP, mm), elevation (m) and Normalized Difference Vegetation Index (NDVI) were the most important predictors of SOCs. The retained prediction model had a Root Mean Squared Error (RMSE) equal to 25.8MgC·ha⁻¹. The predicted SOCs from fitted models ranged from 28 to 198MgC·ha⁻¹ with total SOCs to 4137 TgC. Depending on soil type, Ferralsols (35 to 165MgC·ha⁻¹) and Andosols (48 to 198MgC·ha⁻¹) had relevant results related to the number of soil profiles (n=856 and 171 respectively). Despite the need for in-depth analysis, the model and map produced in the present study has greatly improved our knowledge of the spatial distribution of SOCs in Madagascar and reduced uncertainty compared to the former map. This map provides new perspectives in sustainable land management in Madagascar.
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