Diffusivity Models and Greenhouse Gases Fluxes from a Forest, Pasture, Grassland and Corn Field in Northern Hokkaido, Japan

Information on the most influential factors determining gas flux from soils is needed in predictive models for greenhouse gases emissions. We conducted an intensive soil and air sampling along a 2 000 m transect extending from a forest, pasture, grassland and corn field in Shizunai, Hokkaido (Japan), measured CO2, CH4, N2O and NO fluxes and calculated soil bulk density (rho(b)), air-filled porosity (f(a)) and total porosity (0). Using diffusivity models based on either f(a) alone or on a combination of f(a) and Phi, we predicted two pore space indices: the relative gas diffusion coefficient (D-s/D-o) and the pore tortuosity factor (tau). The relationships between pore space indices (D-s/D-o and tau) and CO2, CH4, N2O and NO fluxes were also studied. Results showed that the grassland had the highest rho(b) while f(a) and Phi were the highest in the forest. CO2, CH4, N2O and NO fluxes were the highest in the grassland while N2O dominated in the corn field. Few correlations existed between f(a), Phi, rho(b) and gases fluxes while all models predicted that D-s/D-o and tau significantly correlated with CO2 and CH4 with correlation coefficient (tau) ranging from 0.20 to 0.80. Overall, diffusivity models based on f(a) alone gave higher D-s/D-o, lower tau, and higher R-2 and better explained the relationship between pore space indices (D-s/D-o and tau) and gases fluxes. Inclusion of D-s/D-o and tau in predictive models will improve our understanding of the dynamics of greenhouse gas fluxes from soils. D-s/D-o and tau can be easily obtained by measurements of soil air and water and existing diffusivity models.