Seasonal and inter-annual variability of soil CO2 efflux in a Norway spruce forest over an eight-year study

0489008 - ÚVGZ 2019 RIV NL eng J - Journal Article
Acosta, Manuel - Dařenová, Eva - Krupková, Lenka - Pavelka, Marian
Seasonal and inter-annual variability of soil CO2 efflux in a Norway spruce forest over an eight-year study.
Agricultural and Forest Meteorology. Roč. 256, jun (2018), s. 93-103. ISSN 0168-1923. E-ISSN 1873-2240
R&D Projects: GA MŠMT(CZ) LO1415; GA MŠMT(CZ) EF16_013/0001609
Research Infrastructure: CzeCOS II - 90061
Institutional support: RVO:86652079
Keywords : Automated chamber system * Day of the year * Picea abies * Soil carbon flux * Temperature Soil water content
OECD category: Ecology
Impact factor: 4.189, year: 2018
Method of publishing: Limited access
https://www.sciencedirect.com/science/article/pii/S0168192318300856?via%3Dihub

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.
Permanent Link: http://hdl.handle.net/11104/0283504