Technological watch

Carbon and Methane as Indicators of Environmental Efficiency of a Silvopastoral System in Eastern Amazon, Brazil

Livestock systems have been identified as major emitters of greenhouse gases due to the use of extensive areas with degraded pastures. The objective of this study was to analyze carbon (CO2) and methane (CH4) fluxes in the atmosphere as indicators of environmental sustainability in silvopastoral systems. CO2 and CH4 fluxes from soil to the atmosphere were monitored in a degraded pasture (predominant species: Panicum maximum cv. Mombaça) grown in full sun and compared with areas with tree species (Bertholletia excelsa, Dipteryx odorata, and Khaya grandifoliola) and productive pasture (Panicum maximum cv. Mombaça) grown in full sun. The study area was in Mojuí dos Campos, western Pará state, Eastern Amazon, Brazil. The evaluations were conducted in a Technological Reference Unit with a silvopastoral system, where animals used the shade of trees during high-temperature periods. The fluxes were measured using an ultraportable greenhouse gas analyzer coupled with static polyvinyl chloride ring chambers installed at the soil–air interface. In conclusion, areas with integrated systems (B. excelsa + pasture and K. grandifoliola + pasture) were better mitigators of CO2 emissions; the highest emissions occurred in the degraded pasture area during the rainiest months. The CH4 fluxes were more intense in the areas with degraded pasture and K. grandifoliola + pasture. Converting degraded pasture areas into integrated crop–livestock–forest systems reduced greenhouse gas emissions in the Amazon over 10 years of implementation. The implementation of integrated crop–livestock–forest systems in long-deforested areas with degraded pastures and a low production capacity showed high potential for changes focused on developing sustainable agriculture in the Amazon.

Publication date: 20/03/2024

Author: Aureane Cristina Teixeira Ferreira Cândido

Reference: doi: 10.3390/su16062547

MDPI (sustainability)


This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 870292.