Modeling nitrogen mineralization at surface and deep layers of sandy soils
| Autor: | Roberto Alvarez, Alfredo Bono, Nicolás F. Romano |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
0106 biological sciences
Nitrogen mineralization Agricultura Soil Science Soil science 04 agricultural and veterinary sciences 01 natural sciences Aerobic incubation CIENCIAS AGRÍCOLAS Modeling in depth Environmental chemistry Soil water 040103 agronomy & agriculture 0401 agriculture forestry and fisheries Environmental science Agricultura Silvicultura y Pesca Agronomy and Crop Science Nitrogen cycle 010606 plant biology & botany |
| Zdroj: | Archives of Agronomy and Soil Science. 63:870-882 |
| ISSN: | 1476-3567 0365-0340 |
| DOI: | 10.1080/03650340.2016.1241391 |
| Popis: | We evaluated potential soil nitrogen mineralization of 46 sandy fields of the Pampas for determining the contribution of deep layers to mineralization and modeling its trend in depth as a possible tool for improving current existing mineralization models based on surface data. Mineralization, total and mineral nitrogen decreased with depth. A potential model fitted well to these variables (R2 = 0.95–0.99), but mineralization showed a more stratified profile. Consequently, the fraction of total nitrogen mineralized decreased with depth despite soils had constant texture across the profile. Potential mineralization to 1 m depth could be estimated using data from the 0–0.2-m soil layer and the average curvature of the potential model (R2 = 0.60) or linear regression methods (R2 = 0.71). Another estimation of potential mineralization could be performed by developing a pedotransfer function which used as predictors total nitrogen and depth (R2 = 0.62), without the need of laboratory incubations. Our results showed that for sandy soils, deep nitrogen mineralization account for 40% of soil mineralization and can be assessed using surface data or the total nitrogen content of the soils. Because surface soil mineralization and whole profile mineralization were highly correlated, it is improbable that field mineralization modeling may be improved using deep data in these soils. Fil: Romano, Nicolas Fermin. Instituto Nacional de Tecnología Agropecuaria. Centro Regional La Pampa-San Luis. Estación Experimental Agropecuaria Anguil; Argentina Fil: Alvarez, Roberto. Universidad de Buenos Aires. Facultad de Agronomía; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario; Argentina Fil: Bono, Alfredo. Instituto Nacional de Tecnología Agropecuaria. Centro Regional La Pampa-San Luis. Estación Experimental Agropecuaria Anguil; Argentina |
| Databáze: | OpenAIRE |
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