Field-scale spatial correlation between contents of iron oxides and CO2 emission in an Oxisol cultivated with sugarcane

• Autor(a) principal: Rabelo de Souza Bahia, Angelica Santos [UNESP]
• Data de Publicação: 2015
• Outros Autores: Marques Junior, Jose [UNESP], Panosso, Alan Rodrigo [UNESP], Camargo, Livia Arantes [UNESP], Siqueira, Diego Silva [UNESP], Teixeira, Daniel De Bortoli [UNESP], La Scala Junior, Newton [UNESP]
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162015000200157&lng=en&nrm=iso&tlng=en; http://hdl.handle.net/11449/129819
• topic: Hematite; Goethite; Soil respiration; Geostatistics; Cross-semivariograms

Soil CO2 emission (FCO2) is one of the main sources of carbon release into the atmosphere. Moreover, FCO2 is related to soil attributes governing the transfer of gases from soil to the atmosphere. This study aimed firstly to describe the spatial variability of hematite (Hm), goethite (Gt), iron extracted with sodium dithionite-citrate-bicarbonate (Fe-d) contents, soil CO2 emission (FCO2) and free-water porosity (FWP) and secondly, to develop statistical models to predict the above mentioned factors in an Oxisol cultivated under manual harvesting of sugarcane (Saccharum spp.) in southeastern Brazil. The study was conducted on an irregular 50 m x 50 m grid containing 89 points, each 0.5-10 m apart. The 0-0.1 m soil layer at each sampling point was used to assess soil FCO2, moisture and total pore volume. The results were subjected to descriptive statistical and geostatistical analyses using auto-and cross-semivariograms. All soil attributes exhibited a spatial dependence structure and the experimental semivariograms fitted spherical and exponential models. The Gt content was the individual attribute that exhibited the highest linear and spatial correlation, especially with FCO2. We were able to use diffuse reflectance spectroscopy to map large areas, which allows for easy identification and estimation of soil attributes such as FCO2 and FWP. Geostatistical techniques faciltate the interpretation of spatial relationships between soil respiration and the examined properties.