4.5 Article

Impact of Grazing Intensity and Seasons on Greenhouse Gas Emissions in Tropical Grassland

Journal

ECOSYSTEMS
Volume 20, Issue 4, Pages 845-859

Publisher

SPRINGER
DOI: 10.1007/s10021-016-0065-0

Keywords

grassland management; grazing height; CH4 from grassland soil; soil respiration; water-filled pore space; nitrous oxide

Categories

Funding

  1. Sao Paulo Research Foundation (Fapesp) [2011/00060-8, 2012/06718-8, 2012/14956-6, 2012/04605-1]
  2. FAPESP
  3. Conselho Nacional de Desenvolvimento Cientifico Tecnologico (CNPq)
  4. Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior (CAPES)
  5. Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP) [11/00060-8] Funding Source: FAPESP

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Greenhouse gases (GHG) can be affected by grazing intensity, soil, and climate variables. This study aimed at assessing GHG emissions from a tropical pasture of Brazil to evaluate (i) how the grazing intensity affects the magnitude of GHG emissions; (ii) how season influences GHG production and consumption; and (iii) what are the key driving variables associated with GHG emissions. We measured under field conditions, during two years in a palisade-grass pasture managed with 3 grazing intensities: heavy (15 cm height), moderate (25 cm height), and light (35 cm height) N2O, CH4 and CO2 fluxes using static closed chambers and chromatographic quantification. The greater emissions occurred in the summer and the lower in the winter. N2O, CH4, and CO2 fluxes varied according to the season and were correlated with pasture grazing intensity, temperature, precipitation, % WFPS (water-filled pores space), and soil inorganic N. The explanatory variables differ according to the gas and season. Grazing intensity had a negative linear effect on annual cumulative N2O emissions and a positive linear effect on annual cumulative CO2 emissions. Grazing intensity, season, and year affected N2O, CH4, and CO2 emissions. Tropical grassland can be a large sink of N2O and CH4. GHG emissions were explained for different key driving variables according to the season.

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