Search

Purpose: The purposes of this study are to characterize the relationship between basal soil respiration at 0 °C (R0) and the temperature sensitivity (Q10) of soil respiration and climate, soil, and vegetation factors and to establish R0 and Q10 models. Materials and methods: We compiled R0 and Q10 and variables (i.e., climate factors, soil properties, and vegetation characteristics) that were measured in various terrestrial ecosystems. Results and discussion: The results showed that both R0 and Q10 could generally be fitted by a normal distribution curve across various ecosystems, but they varied greatly among the different ecosystems. The lowest median R0 and Q10 appeared in the desert, while the highest median R0 and Q10 appeared in the deciduous broad-leaf forest and deciduous needle-leaf forest ecosystems, respectively. The relationship between R0 and Q10 across different soil depths varied among the different ecosystems, with the highest and lowest R2 occurring in the cropland (R2 = 0.701) and evergreen needle-leaf forest (R2 = 0.095), respectively. A model that included Q10, fine root production and the ratio of soil organic carbon to total nitrogen (TN) explained 75.0% (R2 = 0.750) of the variation in R0, with a P value less than 0.001. Q10 was further expressed as a model (R2 = 0.663, P < 0.001) including annual precipitation, mean air temperature, TN, bulk density, and leaf area index. Conclusions: Our R0 models can potentially be used to improve terrestrial carbon cycle models by considering the comprehensive effects of Q10 and soil and vegetation factors. [ABSTRACT FROM AUTHOR]

The terrestrial carbon (C) cycle plays an important role in global climate change, but the vegetation and environmental drivers of C fluxes are poorly understood. We established a global dataset with 1194 available data across site-years including gross primary productivity (GPP), ecosystem respiration (ER), net ecosystem productivity (NEP), and relevant environmental factors to investigate the variability in GPP, ER and NEP, as well as their covariability with climate and vegetation drivers. The results indicated that both GPP and ER increased exponentially with the increase in mean annual temperature (MAT) for all biomes. Besides MAT, annual precipitation (AP) had a strong correlation with GPP (or ER) for non-wetland biomes. Maximum leaf area index (LAI) was an important factor determining C fluxes for all biomes. The variations in both GPP and ER were also associated with variations in vegetation characteristics. The model including MAT, AP and LAI explained 53% of the annual GPP variations and 48% of the annual ER variations across all biomes. The model based on MAT and LAI explained 91% of the annual GPP variations and 92.9% of the annual ER variations for the wetland sites. The effects of LAI on GPP, ER or NEP highlighted that canopy-level measurement is critical for accurately estimating ecosystem-atmosphere exchange of carbon dioxide. The present study suggests a significance of the combined effects of climate and vegetation (e.g., LAI) drivers on C fluxes and shows that climate and LAI might influence C flux components differently in different climate regions. [ABSTRACT FROM AUTHOR]