Soil moisture influence on the interannual variation in temperature sensitivity of soil organic carbon mineralization in the Loess Plateau

Abstract

Abstract. Temperature sensitivity of soil organic carbon (SOC) mineralization (i.e., Q 10 ) determines how strong the feedback from global warming may be on the atmospheric CO 2 concentration; thus, understanding the factors influencing the interannual variation in Q 10 is important for accurately estimating local soil carbon cycle. In situ SOC mineralization rate was measured using an automated CO 2 flux system (Li-8100) in long-term bare fallow soil in the Loess Plateau (35 • 12 N, 107 • 40 E) in Changwu, Shaanxi, China from 2008 to 2013. The results showed that the annual cumulative SOC mineralization ranged from 226 to 298 g C m −2 yr −1 , with a mean of 253 g C m −2 yr −1 and a coefficient of variation (CV) of 13 %, annual Q 10 ranged from 1.48 to 1.94, with a mean of 1.70 and a CV of 10 %, and annual soil moisture content ranged from 38.6 to 50.7 % soil water-filled pore space (WFPS), with a mean of 43.8 % WFPS and a CV of 11 %, which were mainly affected by the frequency and distribution of precipitation. Annual Q 10 showed a quadratic correlation with annual mean soil moisture content. In conclusion, understanding of the relationships between interannual variation in Q 10 , soil moisture, and precipitation are important to accurately estimate the local carbon cycle, especially under the changing climate.

Effect of Precipitation Variation on Soil Respiration in Rain-Fed Winter Wheat Systems on the Loess Plateau, China

“…Changes in both the distribution and amount of precipitation have significant effects on soil CO 2 emissions by regulating VWC; this is especially true in rain-fed agricultural areas, where precipitation is the primary driver of biological activity [ 26 ]. Generally, an increase in VWC will increase the aboveground and underground biomass, as well as substrate concentrations of plants [ 5 , 13 ], thereby enhancing R s [ 14 ]. However, a previous study also found that a decrease in VWC increased T s and then increased R s [ 33 ].…”

“…The R s was fitted to T s and VWC with empirical exponential and quadratic functions [ 10 , 13 ], respectively: where R s , VWC, and T s represent the soil respiration, soil volume water content, and soil temperature, respectively, and a, b, and c are fitting coefficients. Then, the following nonlinear models were used to express the relationships between VWC and T s and R s [ 31 , 32 ]: …”

“…Precipitation is the primary driver of biological activity in arid and semiarid areas, and it further regulates the dynamics of R s by affecting the synergistic and decoupling effect of T s and VWC [ 5 , 11 ]. It has been reported that when the VWC is sufficient, increasing T s will improve R s by increasing the net photosynthesis rate [ 12 ], substrate concentration [ 13 ], and microbial biomass [ 14 ]. However, when water stress occurs, the VWC may be decoupled from the T s and become the primary factor affecting R s [ 11 ].…”

“…Temperature sensitivity (Q 10 ) is a critical metric for characterizing the relationship between T s and R s [ 17 , 18 , 19 ], and may be influenced by other biotic and abiotic factors, such as precipitation [ 18 , 20 ], VWC [ 13 ], root biomass [ 17 ], and microorganisms [ 19 ]; Q 10 can also lead to hysteresis (between T s and R s ) at multiple scales [ 21 ]. Previous studies have shown that the VWC may indirectly affect Q 10 because the diffusion of extracellular enzymes produced and the available substrates must occur in the liquid phase [ 13 , 22 ]. Moreover, because the thermal conductivity in the liquid phase is higher than that in the solid phase, the elevated VWC caused by precipitation promotes the C transport rate of plants, which further affects the hysteresis relationship [ 23 , 24 ].…”

Improving the sustainability of tobacco cultivation by optimizing nitrogen fertilization

“…Soil-based techniques, however, are not suited for Mediterranean areas. In these environments, seasonal variability of both soil moisture and temperature is a serious constraint for accurate forecast of the actual amounts of mineral N available to plants since mineralization rates are greatly affected by these two parameters (Pessarakli, 1994;Zhang et al, 2015). Among plant-based approaches, the critical N concentration (N ct expressed as % of Dry Matter, DM) has been proven to be a reliable parameter for monitoring N fertilization rates in the soil-plant system (Lemaire et al, 2007).…”