Estimating temporal changes in soil carbon stocks at ecoregional scale in Madagascar using remote-sensing

• Published in: International journal of applied earth observation and geoinformation Vol. 54; pp. 1 - 14
• Main Authors: Grinand, C., Maire, G. Le, Vieilledent, G., Razakamanarivo, H., Razafimbelo, T., Bernoux, M.
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.02.2017; Elsevier
• Subjects: Agricultural sciences; Bioclimatology; Change detection; Deforestation; Ecology, environment; Life Sciences; PLSR; Random forest; Soil organic carbon; Soil study; Soil-landscape factors; Spectroscopy; Deforestation; Spectroscopy; Change detection; Soil-landscape factors; Random forest; Soil organic carbon; PLSR
• ISSN: 1569-8432; 1872-826X
• DOI: 10.1016/j.jag.2016.09.002

•Remote sensing archives were used to detect significant soil organic carbon stocks.•Production of high resolution maps of changes in soil organic stocks for a 20 years period.•Deforestation is responsible for both gains and losses at landscape scale.•Significant net losses in humid region lower than reported in the literature.•New perspectives in monitoring soil carbon at various scales. Soil organic carbon (SOC) plays an important role in climate change regulation notably through release of CO2 following land use change such a deforestation, but data on stock change levels are lacking. This study aims to empirically assess SOC stocks change between 1991 and 2011 at the landscape scale using easy-to-access spatially-explicit environmental factors. The study area was located in southeast Madagascar, in a region that exhibits very high rate of deforestation and which is characterized by both humid and dry climates. We estimated SOC stock on 0.1ha plots for 95 different locations in a 43,000ha reference area covering both dry and humid conditions and representing different land cover including natural forest, cropland, pasture and fallows. We used the Random Forest algorithm to find out the environmental factors explaining the spatial distribution of SOC. We then predicted SOC stocks for two soil layers at 30cm and 100cm over a wider area of 395,000ha. By changing the soil and vegetation indices derived from remote sensing images we were able to produce SOC maps for 1991 and 2011. Those estimates and their related uncertainties where combined in a post-processing step to map estimates of significant SOC variations and we finally compared the SOC change map with published deforestation maps. Results show that the geologic variables, precipitation, temperature, and soil-vegetation status were strong predictors of SOC distribution at regional scale. We estimated an average net loss of 10.7% and 5.2% for the 30cm and the 100cm layers respectively for deforested areas in the humid area. Our results also suggest that these losses occur within the first five years following deforestation. No significant variations were observed for the dry region. This study provides new solutions and knowledge for a better integration of soil threats and opportunities in land management policies.