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Modeled and Measured Ecosystem Respiration in Maize–Soybean Systems Over 10 Years
Author(s) -
Zhan Ming,
Liska Adam J.,
NguyRobertson Anthony L.,
Suyker Andrew E.,
Pelton Matthew P.,
Yang Haishun
Publication year - 2019
Publication title -
agronomy journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.752
H-Index - 131
eISSN - 1435-0645
pISSN - 0002-1962
DOI - 10.2134/agronj2018.02.0086
Subject(s) - eddy covariance , crop residue , environmental science , soil carbon , agronomy , ecosystem respiration , soil respiration , crop , ecosystem , soil water , soil science , agriculture , ecology , biology
Core Ideas The combination of crop and soil models can predict daily measured CO 2 emissions. Crop residue is the main source of carbon inputs to soil and largely determines soil organic carbon. Where residue is removed for biofuels, increased carbon emissions will occur.Crop residue is an abundant resource for the potential production of biofuels, but a better understanding of its use on net carbon emissions must be developed to mitigate climate change. This analysis combines two established crop growth models (Hybrid‐Maize and Soysim) with a simple soil and crop residue respiration model to estimate daily ecosystem respiration (ERe) from maize and soybean; ERe was estimated to be the sum of CO 2 emissions from the oxidation of the growing crop, crop residue, and soil organic carbon (SOC). Model‐estimated CO 2 fluxes from irrigated continuous maize and irrigated maize–soybean cropping systems in eastern Nebraska were compared with tower eddy covariance measurements of CO 2 fluxes from 2001 to 2010 from those fields. Modeled C emissions closely estimated measured seasonal patterns of CO 2 dynamics and measured daily ERe ( R 2 : 0.87, 0.84). Measured and modeled annual ERe values were also compared and better agreement was found in maize compared to soybean. As there are limited comparisons of modeled soil emissions with eddy covariance measured CO 2 fluxes, this study is important for the validation of these types of models and to support their potential use in quantifying emissions from crop residue for biofuels.

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