Detalhes bibliográficos
Ano de defesa: |
2016 |
Autor(a) principal: |
Silva, Elienai Ferreira da [UNESP] |
Orientador(a): |
Não Informado pela instituição |
Banca de defesa: |
Não Informado pela instituição |
Tipo de documento: |
Dissertação
|
Tipo de acesso: |
Acesso aberto |
Idioma: |
por |
Instituição de defesa: |
Universidade Estadual Paulista (Unesp)
|
Programa de Pós-Graduação: |
Não Informado pela instituição
|
Departamento: |
Não Informado pela instituição
|
País: |
Não Informado pela instituição
|
Palavras-chave em Português: |
|
Link de acesso: |
http://hdl.handle.net/11449/138071
|
Resumo: |
Soil CO2 emission (FCO2) in agricultural areas is a process that results of the interaction of different factors such as climate and soil conditions. In this sense, the aim of this study was to investigate the spatial and temporal variability of FCO2, soil temperature (Tsoil), soil moisture (Msoil) and air-filled pore space (AFPS) and their interactions in a sugarcane field reform. This study was conducted in a 90 × 90- m sampling grid with 100 points spaced at distances of 10 m; at these points, 10 measurements were performed over a period of 28 days. In order to measure the FCO2, it was used a LI-8100A. Along with the measurements of FCO2, Tsoil and Msoil were also measured. It was observed an increase of 78% in FCO2 due to the rainfall in the study area. The linear regression models using only Msoil and AFPS explained 85% and 80%, respectively, of the variability of FCO2, indicating that over the time, the emission of CO2 was controlled by varying the content of water and soil aeration. The adjusted models to describe the spatial variability of FCO2, Tsoil, Msoil and AFPS were spherical and exponential. However, the spherical model was more predominant. We did not identify spatial variability using the maps for some days. Probably this happened because we used the small scale. It can have collaborated for random behavior. The spatiotemporal variability of CO2 emission, temperature, moisture and air-filled pore space was affected by rainfall in the study area. We can divide this variability in three periods: before, during and after rainfall. The higher values of CO2 emissions was observed during rainfall and lower values before and after rainfall. |