Abstract
Abstract. CO2 production and transport from forest floors is an important component of the carbon cycle and is closely related to the global atmosphere CO2 concentration. If we are to understand the feedback between soil processes and atmospheric CO2, we need to know more about the spatio-temporal variability of this soil respiration under different environmental conditions. In this study, long-term measurements were conducted in a spruce-dominated forest ecosystem in western Germany. Multivariate analysis-based similarities between different measurement sites led to the detection of site clusters along two CO2 emission axes: (1) mainly controlled by soil temperature and moisture condition, and (2) mainly controlled by root biomass and the forest floor litter. The combined effects of soil temperature and soil moisture were used as a time-dependent rating factor affecting the optimal CO2 production and transport at cluster level. High/moderate/weak time-dependent rating factors were associated with the different clusters. The process-based, most distant clusters were identified using specified pattern characteristics: the reaction rates in the soil layers, the activation energy for bio-chemical reactions, the soil moisture dependency parameter, the root biomass factor, the litter layer factor and the organic matter factor. A HYDRUS-1D model system was inversely used to compute soil hydraulic parameters from soil moisture measurements. Heat transport parameters were calibrated based on observed soil temperatures. The results were used to adjust CO2 productions by soil microorganisms and plant roots under optimal conditions for each cluster. Although the uncertainty associated with the HYDRUS-1D simulations is higher, the results were consistent with both the multivariate clustering and the time-dependent rating of site production. Finally, four clusters with significantly different environmental conditions (i.e. permanent high soil moisture condition, accumulated litter amount, high variability in soil moisture content, and dominant temperature dependence) were found to be relevant in explaining the spatio-temporal variability of CO2 efflux and providing reference-specific characteristic values for the investigated area.
Highlights
Understanding the feedback between terrestrial ecosystems and the atmosphere is one of the key issues for predicting the evolution of atmospheric CO2 concentration and global climatic change (Longdoz et al, 2000)
If we are to understand the feedback between soil processes and atmospheric CO2, we need to know more about the spatiotemporal variability of this soil respiration under different environmental conditions
All investigated soil parameters are randomly distributed except the litter depth, which may be highly influenced by local-scale factors, such as wind or transport through preferential surface flow
Summary
Understanding the feedback between terrestrial ecosystems and the atmosphere is one of the key issues for predicting the evolution of atmospheric CO2 concentration and global climatic change (Longdoz et al, 2000). More studies are required on the role of soil processes if we are to improve our understanding of the flux rate functions and the stability and resilience of soil processes that contribute to large-scale surface fluxes of water, heat and greenhouse gases (Fang and Moncrieff, 1999). The release of CO2 from the soil surface is the result of a number of complex processes, including CO2 production, gas transport and interactions between physical and biological factors within the soil (Moncrieff and Fang, 1999). Soil respiration is often measured as a flux of carbon dioxide from the soil surface, i.e. as soil CO2 efflux which approximately equals soil respiration at annual scale, but is influenced by transport conditions over shorter time steps (Raich and Schlesinger, 1992; Niinistö et al, 2011)
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