Simulation of aboveground biomass production under different rainfall scenarios and soil types in the Caatinga Biome, Brazil

• Autor(a) principal: Althoff, Tiago Diniz
• Data de Publicação: 2018
• Outros Autores: Silva, Rafael R., Martins, Júlio C. R., Wanderley, Lucas S. A., Sales, Aldo T., Menezes, Romulo S. C.
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Revista Geama
• Texto Completo: https://www.journals.ufrpe.br/index.php/geama/article/view/1887
• topic: Century model; forage; semi-arid region

Drought years have a negative impact on the livestock production systems of the Brazilian semiarid region because of the strong reduction of forage production on the rangelands. Although drought is recurrent in the Brazilian semiarid, up to the present moment, there are notools that could help farmers to mitigate the effects of these extreme climate conditions. In this sense, simulation of biochemical cycles using mathematical models could be a helpful tool to understand these processes. The Century model has been largely used to estimate the impact of different environmental variables, management practices, and climate scenarios in the vegetation. The study aims to evaluate the Century model to simulate the dynamics of aboveground biomass production and soil carbon in the Caatinga ecosystem under three different rainfall scenarios: 1) Precipitation 50% below the long-term average; 2) Long-term average rainfall; 3) 50% above the long-term average rainfall. Moreover, two types of soil (sandy and clay) were evaluated in the simulations. Dry years led to 42 and 20% reductions in aboveground biomass production in the shrubby and herbaceous layers, respectively, but there were no significant differences between soil types. Further adjustments in the model are required to simulate herbaceous biomass in the Caatinga ecosystem. At the end of the adaptation phase, we expect that the Century model will generate useful information to fill the lack of knowledge about variability of forage production in the Caatinga, helping in the adaptation to possible climate changes.