Soil Respiration in European Grasslands in Relation to Climate and Assimilate Supply

Abstract

Soil respiration constitutes the second largest flux of carbon (C) between terrestrial ecosystems and the atmosphere. This study provides a synthesis of soil respiration (R s ) in 20 European grasslands across a climatic transect, including ten meadows, eight pastures and two unmanaged grasslands. Maximum rates of R s (R s max ), R s at a reference soil temperature (10°C; R s 10 ) and annual R s (estimated for 13 sites) ranged from 1.9 to 15.9 μmol CO 2 m −2 s −1 , 0.3 to 5.5 μmol CO 2 m −2 s −1 and 58 to 1988 g C m −2 y −1 , respectively. Values obtained for Central European mountain meadows are amongst the highest so far reported for any type of ecosystem. Across all sites R s max was closely related to R s 10 .Assimilate supply affected R s at timescales from daily (but not necessarily diurnal) to annual.Reductions of assimilate supply by removal of aboveground biomass through grazing and cutting resulted in a rapid and a significant decrease of R s . Temperature-independent seasonal fluctuations of R s of an intensively managed pasture were closely related to changes in leaf area index (LAI). Across sites R s 10 increased with mean annual soil temperature (MAT), LAI and gross primary productivity (GPP), indicating that assimilate supply overrides potential acclimation to prevailing temperatures. Also annual R s was closely related to LAI and GPP. Because the latter two parameters were coupled to MAT, temperature was a suitable surrogate for deriving estimates of annual R s across the grasslands studied. These findings contribute to our understanding of regional patterns of soil C fluxes and highlight the importance of assimilate supply for soil CO 2 emissions at various timescales.

Ecosystem photosynthesis regulates soil respiration on a diurnal scale with a short-term time lag in a coastal wetland

“…In general, diurnal soil respiration lagged photosynthetic activity on hourly scales (e.g. Baldocchi et al, 2006;Liu et al, 2006;Bahn et al, 2008;Yan et al, 2011). The time lags of 0e4 h in our results are consistent with previous findings.…”

“…It is well documented that soil respiration may lag canopy photosynthesis by times that vary from hours to weeks in different ecosystems including forests Tang et al, 2005;Baldocchi et al, 2006;Moyano et al, 2008;Wingate et al, 2010), grasslands (Bahn et al, 2008(Bahn et al, , 2009Yan et al, 2011;Vargas et al, 2011a) and croplands Cheng, 2001, 2004;Han et al, 2007). The highly variable time lags between photosynthesis and soil respiration might be controlled by the species, transport distance (plant height and phloem path-length), root depth, plant physiology and growth stage, and environmental conditions (Davidson and Holbrook, 2009;Kuzyakov and Gavrichkova, 2010;Mencuccini and Hölttä, 2010;Wingate et al, 2010).…”

Biotic and climatic controls on interannual variability in carbon fluxes across terrestrial ecosystems

“…To take an extreme instance, drought can even cause the mortality of plants due to hydraulic failure and carbon starvation, and thus reduced the ecosystem productivity (McDowell et al, 2008;Niu et al, 2014). The direct effect of water stress is usually accompanied by reduction of leaf area index, maximum photosynthetic rate, and respiratory substrate, and the changes in plant morphology and microbe community, which might further reduce the ecosystem physiological rates (Bahn et al, 2008;van der Molen et al, 2011).…”

A remote sensing model to estimate ecosystem respiration in Northern China and the Tibetan Plateau

“…difficult for satellite technology to monitor various respiratory processes, especially those in the soil (Valentini et al, 2000;Running et al, 2004;Olofsson et al, 2008;Xiao et al, 2008;Tang et al, 2012), which limit the application of remote sensing data in R e estimation. However, R e showed close relationships with easily satellite-retrieved GPP (e.g., Knohl et al, 2005;Tang et al, 2005;Moyano et al, 2007Moyano et al, , 2008Larsen et al, 2007;Bahn et al, 2008;Gomez-Casanovas et al, 2012;Huang and Niu, 2013) and temperature (e.g., Lloyd and Taylor, 1994;Frank et al, 2002;Reichstein et al, 2003;Bond-Lamberty and Thomson, 2010) in most of ecosystems, and upon these relationships some empirical or semi-empirical satellite-driven R e models were developed and validated at the plot or regional scale (Vourlitis et al, 2003;Gilmanov et al, 2005;Rahman et al, 2005;Schubert et al, 2010;Jägermeyr et al, 2014). However, extensive studies reported that the responses to GPP and temperature varied among the R e components (e.g., Gaumont-Guay et al, 2008;Kuzyakov and Gavrichkova, 2010), and the current satellite-driven R e models almost all neglected these differences.…”