Journal
AGRICULTURAL AND FOREST METEOROLOGY
Volume 256, Issue -, Pages 93-103Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.agrformet.2018.03.005
Keywords
Automated chamber system; Day of the year; Picea abies; Soil carbon flux; Temperature; Soil water content
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Funding
- Ministry of Education, Youth and Sports of the Czech Republic within the National Sustainability Programme I (NPU I) [LO1415]
- grant: Completion of the research infrastructure CzeCOS to increase international quality of research of the global climate change impacts on ecosystem processes [CZ.02.1.01/0.0/0.0/16_013/0001609]
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Automated soil CO2 efflux chamber measurements were carried out over a period of eight years in a young Norway spruce forest in the northeast region of the Czech Republic to determine seasonal and inter-annual variables affecting this flux. The data obtained was summarized and analysed with the aims of estimating long-term carbon losses from the soil and comparing selected models to determine the model best describing soil CO2 efflux. Our results show that seasonal variation in soil CO2 efflux was driven mainly by soil temperature, while inter-annual variation showed the closest relationship with precipitation. The total amount of carbon released from the soil into the atmosphere per season varied from 6.4 to 11.2 tC ha(-1) over the eight-year record. One of the variables used in the CO2 efflux models, beside environmental variables, was day of year (DOY). Incorporating this variable into models improved the estimation of soil CO2 efflux dynamics. Therefore, we assume that models incorporating DOY could be used effectively to gap-fill measured soil chamber data. These models could also be appropriate for filling longer gaps on a scale from days to weeks, because DOY, as a single parameter, covers up to 80% of variability in the data. This study also demonstrated the different levels of correlation between investigated climate variables and soil CO2 efflux at seasonal and inter-annual time scales. This highlights the importance of different environmental variables in interpreting long-term soil CO2 efflux data and also modelling the complexity of the processes connected with soil CO2 efflux in Norway spruce forest.
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