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Meshalkina, Joulia; Lomonosov Moscow State University, Faculty of Soil Science, Moscow; Yaroslavtsev, Alexis; Russian Timiryazev State Agrarian University, Laboratory of Agroecological Monitoring, Ecosystem Modeling and Prediction, Moscow; Mazirov, Ilya; Russian Timiryazev State Agrarian University, Laboratory of Agroecological Monitoring, Ecosystem Modeling and Prediction, Moscow; Samardzic, Miljan; Russian Timiryazev State Agrarian University, Laboratory of Agroecological Monitoring, Ecosystem Modeling and Prediction, Moscow; Valentini, Riccardo; Russian Timiryazev State Agrarian University, Laboratory of Agroecological Monitoring, Ecosystem Modeling and Prediction, Moscow; Vasenev, Ivan; Russian Timiryazev State Agrarian University, Laboratory of Agroecological Monitoring, Ecosystem Modeling and Prediction, Moscow
Eurasian journal of soil science, 07/2015, Letnik: 4, Številka: 3Journal Article
The eddy covariance (EC) technique as a powerful statistics-based method of measurement and calculation the vertical turbulent fluxes of greenhouses gases within atmospheric boundary layers provides the continuous, long-term flux information integrated at the ecosystem scale. An attractive way to compare the agricultural practices influences on GHG fluxes is to divide a crop area into subplots managed in different ways. The research has been carried out in the Precision Farming Experimental Field of the Russian Timiryazev State Agricultural University (RTSAU, Moscow) in 2013 under the support of RF Government grant # 11.G34.31.0079, EU grant # 603542 LUС4С (7FP) and RF Ministry of education and science grant # 14-120-14-4266-ScSh. Arable Umbric Albeluvisols have around 1% of SOC, 5.4 pH (KCl) and NPK medium-enhanced contents in sandy loam topsoil. The CO2 flux seasonal monitoring has been done by two eddy covariance stations located at the distance of 108 m. The LI-COR instrumental equipment was the same for the both stations. The stations differ only by current crop version: barley or vetch and oats. At both sites, diurnal patterns of NEE among different months were very similar in shape but varied slightly in amplitude. NEE values were about zero during spring time. CO2 fluxes have been intensified after crop emerging from values of 3 to 7 µmol/s∙m2 for emission, and from 5 to 20 µmol/s∙m2 for sink. Stabilization of the fluxes has come at achieving plants height of 10-12 cm. Average NEE was negative only in June and July. Maximum uptake was observed in June with average values about 8 µmol CO2 m−2 s−1. Although different kind of crops were planted on the fields A and B, GPP dynamics was quite similar for both sites: after reaching the peak values at the mid of June, GPP decreased from 4 to 0.5 g C CO2 m-2 d-1 at the end of July. The difference in crops harvesting time that was equal two weeks did not significantly influence the daily GPP patterns. Cumulative assimilation of CO2 at the end of the growing season was about 150 g C m−2 for both sites. So the difference in NEE was the consequence of essentially higher respiration rates in case of vetch and oats (about 350 g C m−2) comparing to barley (250 g C m−2) that needs additional research. The results have shown high daily and seasonal dynamic of CO2 emission too as a result of different and contrasted conditions: crop type, crop development stage, soil moisture and air temperature. Obtained unique for Russian agriculture data are useful for land-use practices environmental assessment, for soil organic carbon dynamics analysis and agroecological evaluation.
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