Carbon dynamics in the Brazilian Cerrado: stocks and fluxes estimated by a model data fusion framework (CARDAMOM)

Savannas are a major component of the world’s vegetation and cover a land surface of about 15 Mkm², accounting for about 30% of the terrestrial primary production. In the South America, the Brazilian Savanna (Cerrado) is the second largest biome (2 Mkm²), after the Amazon biome, and a hotspot of biodiversity. The Cerrado region is heterogeneous, with savanna vegetation ranging from open grassland, through a gradient of increasing tree density to nearly closed-canopy woodland. The cerrado vegetation is markedly seasonal in phenology and is often burned, either naturally or as part of a management cycle. Due its large occupation, Cerrado have the potential to influence the regional and possibly the global energy, water and carbon (C) balances. The allocation of the net primary productivity (NPP) of an ecosystem between canopy, woody tissue and fine roots is an important descriptor of the functioning of an ecosystem, and an important feature to correctly represent in terrestrial ecosystem models for carbon rates estimation, as well as their residence time, variation with climate and disturbance, and in order to make better forecasts. Such estimation in Cerrado regions remains still difficult given the lack of important soil and vegetation data. Previous studies have showed that the fluxes of water and C are closely related to each other, and to the diurnal cycle of solar radiation. However, there is no study clearly assessing the allocation of C through the different types of vegetation, either in the different types of physiognomies. To help estimating the C flows across the different C pools and types of vegetation, we are using Carbon Data Model Framework (CARDAMOM) which is a computer programme that retrieves terrestrial carbon (C) cycle variables by combining C cycle observations with a mass balance model. CARDAMOM produces global dynamic estimates of plant and soil C pools, their exchanges with each other and with the atmosphere, and C cycling variables for processes driving change. It also produces a C cycle analysis consistent with C measurements and climate, and it is suited for using with global-scale satellite observations such as aboveground biomass (ABG) or leaf area index (LAI). For that, we count on field data available (AGB, BGB) and satellite data (LAI, AGB, soil C), which will help to present robust analyses of C cycling across gradients of biomass in the Brazilian Cerrado.