Repeated-measures ANOVA for the temperature and time effects on R_h under different soil moisture treatments.

a<p>%WHC: percent of water holding capacity.</p

Changes of Q₁₀ and R_h with incubation time at different soil moisture treatments.

<p>The Q₁₀ regression functions are quadratic for 20%, 40% and 60% WHC and cubic for 80% and 100% WHC. Error bars (n = 4) represent standard deviations. R² is the coefficient of determination. P is the significance level.</p

Regression equations of heterotrophic respiration (R_h) with temperature under different moisture treatments.

a<p>%WHC: percent of water holding capacity.</p>b<p>R_h represents soil heterotrophic respiration rate and T represents temperature.</p>c<p>R² is the coefficient of determination; * and ** indicate significance at P≤0.05 and P≤0.01, respectively.</p

Responses of soil heterotrophic respiration (R_h) to changes in soil temperature after 7 (A), 30 (B), and 90 (C) days of incubation.

<p>Each data point is the mean of four replicates under each soil moisture treatment. Error bars represent standard errors (n = 4).</p

Correlations between Q₁₀ and soil microbial and chemical properties.

<p>MBC: microbial biomass carbon, DOC: dissolved organic carbon, TP: total phosphorus, and F:B: ratio of fungi to bacteria. r is the correlation coefficient. P is the significance level.</p

Wettability of Supercritical CO₂–Brine–Mineral: The Effects of Ion Type and Salinity

Deep saline aquifers are considered as perfect storage sites to sequestrate CO₂. Interfacial tensions (IFTs) and contact angles (CAs) are key parameters in the heat and mass transfer processes for CO₂/brine/mineral systems in porous media. In the present study, a molecular dynamics simulation method was used to investigate the effects of brine salinity and ion type on wettability of CO₂/brine/mineral systems at 20 MPa and 318.15 K. Four common brines were selected as NaCl, KCl, CaCl₂, and MgCl₂. Interfacial tensions, water contact angles, and hydrogen bond structure and dynamics have been analyzed. The effects of brine salinity and ion type on water contact angles were found to be very complicated. For MgCl₂ and NaCl solutions, the contact angle increases with salinity. For CaCl₂ and KCl solutions, contact angle first increases and then remains constant with salinity. The product of IFT­(CO₂–brine) and the cosine of CA was found to be constant for all brine solutions studied. In the context of large uncertainty of experimentally measured contact angles, this finding is very useful to predict contact angles using interfacial tension data. Due to the fact that IFT­(CO₂–brine) × cos­(CA) is usually related with capillary pressure and residual trapping capacity, this finding is also very helpful to predict these parameters at different brine conditions. More work is required to study the effects of pressure, temperature, and solid surface structure on this relationship

Relationships between scaling constant/intercept and tree age (a), diameter at breast height (DBH, b), height (c), density (d), latitude (e), longitude (f), and elevation (g).

<p>The model with the best fit among the linear, quadratic and power function models is presented. ** significant at α = 0.01 level. Error bars are standard errors of the scaling exponents.</p

Relationships between belowground biomass and tree age (a), diameter at breast height (DBH, b), height (c), density (d), latitude (e), longitude (f), and elevation (g).

<p>The model with the best fit among the linear, quadratic and power function models is presented. ** significant at α = 0.01 level. Error bars are too small to be shown.</p

Relationships between scaling exponent and tree age (a), diameter at breast height (DBH, b), height (c), density (d), latitude (e), longitude (f), and elevation (g).

<p>The scaling exponent of each age, DBH, height, density, latitude, longitude, and elevated group was estimated using reduce major axis (RMA) regression analysis. The model with the best fit among the linear, quadratic and power function models is presented. ** significant at α = 0.01 level. Error bars are standard errors of the slopes.</p

Relationship between belowground biomass and aboveground biomass of forests in China.

<p>The model is estimated using reduced major axis regression method (n = 6153). ** significant at α = 0.01 level.</p