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Simulating Long‐Term and Residual Effects of Nitrogen Fertilization on Corn Yields, Soil Carbon Sequestration, and Soil Nitrogen Dynamics
Author(s) -
He X.,
Izaurralde R. C.,
Vanotti M. B.,
Williams J. R.,
Thomson A. M.
Publication year - 2006
Publication title -
journal of environmental quality
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.888
H-Index - 171
eISSN - 1537-2537
pISSN - 0047-2425
DOI - 10.2134/jeq2005.0259
Subject(s) - soil carbon , carbon sequestration , environmental science , nitrogen , mineralization (soil science) , agronomy , human fertilization , biomass (ecology) , zoology , soil water , chemistry , soil science , biology , organic chemistry
Soil carbon sequestration (SCS) has the potential to attenuate increasing atmospheric CO 2 and mitigate greenhouse warming. Understanding of this potential can be assisted by the use of simulation models. We evaluated the ability of the EPIC model to simulate corn ( Zea mays L.) yields and soil organic carbon (SOC) at Arlington, WI, during 1958–1991. Corn was grown continuously on a Typic Argiudoll with three N levels: LTN1 (control), LTN2 (medium), and LTN3 (high). The LTN2 N rate started at 56 kg ha −1 (1958), increased to 92 kg ha −1 (1963), and reached 140 kg ha −1 (1973). The LTN3 N rate was maintained at twice the LTN2 level. In 1984, each plot was divided into four subplots receiving N at 0, 84, 168, and 252 kg ha −1 Five treatments were used for model evaluation. Percent errors of mean yield predictions during 1958–1983 decreased as N rate increased (LTN1 = −5.0%, LTN2 = 3.5%, and LTN3 = 1.0%). Percent errors of mean yield predictions during 1985–1991 were larger than during the first period. Simulated and observed mean yields during 1958–1991 were highly correlated ( R 2 = 0.961, p < 0.01). Simulated SOC agreed well with observed values with percent errors from −5.8 to 0.5% in 1984 and from −5.1 to 0.7% in 1990. EPIC captured the dynamics of SOC, SCS, and microbial biomass. Simulated net N mineralization rates were lower than those from laboratory incubations. Improvements in EPIC's ability to predict annual variability of crop yields may lead to improved estimates of SCS.