Detailed global modelling of soil organic carbon in cropland, grassland and forest soils

Abstract

Assessments of the global carbon (C) cycle typically rely on simplified models which consider large areas as homogeneous in terms of the response of soils to land use or consider very broad land classes. For example, “cropland” is typically modelled as an aggregation of distinct practices and individual crops over large regions. Here, we use the process-based Rothamsted soil Carbon Model (RothC model), which has a history of being successfully applied at a global scale, to calculate attainable SOC stocks and C mineralization rates for each of c. 17,000 regions (combination of soil type and texture, climate type, initial land use and country) in the World, under near-past climate conditions. We considered 28 individual crops and, for each, multiple production practices, plus 16 forest types and 1 grassland class (total of 80 classes). We find that conversion to cropland can result in SOC increases, particularly when the soil remains covered with crop residues (an average gain of 12 t C/ha) or using irrigation (4 t C/ha), which are mutually reinforcing effects. Attainable SOC stocks vary significantly depending on the land use class, particularly for cropland. Common aggregations in global modelling of a single agricultural class would be inaccurate representations of these results. Attainable SOC stocks obtained here were compared to long-term experiment data and are well aligned with the literature. Our results provide a regional and detailed understanding of C sequestration that will also enable better greenhouse gas reporting at national level as alternatives to IPCC tier 2 defaults.

Spatial Pattern of Soil Carbon Density in Cultivated Land of Different Domains of Madhya Pradesh

“…The SOCD, TOCD, SICD and TCD ranged from 4.73 to 25.12, 9.22 to 48.98, 1.00 to 21. 29 (2018) also expressed that the effect of land use on SOC was the most significant on topsoil. The variation in SOC is due to the variation in texture [54,55] and mineralogy [56,57] of soils.…”

“…These include measurement methods, data sources (SOC data and SOC environmental covariates) and their resolution and extent, the different periods of data collection, or using multiple modeling and evaluation strategies (Grunwald, 2009;Ogle et al2010;Stockmann et al2013). Thus, there is a need for study describing SOC spatial variability across local to global scales [25,26,27,28,29].…”

The Effect of Crop Rotation and Cultivation History on Predicted Carbon Sequestration in Soils of Two Experimental Fields in the Moscow Region, Russia

“…These results are consistent with our data about the long-term effects of the previous land use (under natural forest vegetation) visible in different SOC dynamics in long-term field experiments. Morais et al [32] simulated with the RothC model changes in the annual SOC stock in 2014-2100 (without a climate change effect) globally for all land use classes. They demonstrated that the conversion of forest to cropland generally results in SOC loss, and SOC loss is typically faster than SOC recovery.…”

The Effect of Crop Rotation and Cultivation History on Predicted Carbon Sequestration in Soils of Two Experimental Fields in the Moscow Region, Russia

“…These results are consistent with our data about the long-term effect of deforestation visible in different SOC dynamics in the long-term field experiments. Morais et al [26] simulated with RothC model changes in the annual SOC stock in 2014-2100 (without climate change effect) globally for all land use classes. They demonstrated that the conversion of forest to cropland in general result in SOC loss, and, SOC loss is typically faster than SOC recovery.…”