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 CO 2 ,CH 4 ,N 2 O and NO fluxes and calculated soil bulk density (ρ b ),air-filled porosity (f a ) and total porosity (Φ).Using diffusivity models based on either f a alone or on a combination of f a and Φ,we predicted two pore space indices: the relative gas diffusion coefficient (D s /D o ) and the pore tortuosity factor (τ).The relationships between pore space indices (D s /D o and τ) and CO 2 ,CH 4 ,N 2 O and NO fluxes were also studied.Results showed that the grassland had the highest ρ b while f a and Φ were the highest in the forest.CO 2 ,CH 4 ,N 2 O and NO fluxes were the highest in the grassland while N 2 O dominated in the corn field.Few correlations existed between f a ,Φ,ρ b and gases fluxes while all models predicted that D s /D o and τ significantly correlated with CO 2 and CH 4 with correlation coefficient (r) ranging from 0.20 to 0.80.Overall,diffusivity models based on f a alone gave higher D s /D o ,lower τ,and higher R 2 and better explained the relationship between pore space indices (D s /D o and τ) and gases fluxes.Inclusion of D s /D o and τ in predictive models will improve our understanding of the dynamics of greenhouse gas fluxes from soils.D s /D o and τ can be easily obtained by measurements of soil air and water and existing diffusivity models.

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, N20 and NO fluxes and calculated soil bulk density （Pb）, air-filled porosity （fa） and total porosity （Ф）. Using diffusivity models based on either fa alone or on a combination of fa and 4, we predicted two pore space indices： the relative gas diffusion coefficient （Ds/Do） and the pore tortuosity factor （T）. The relationships between pore space indices （Ds/Do and T） and C02, CH4, N2O and NO fluxes were also studied. Results showed that the grassland had the highest Pb while fa and Ф were the highest in the forest. CO2, CH4, N20 and NO fluxes were the highest in the grassland while N20 dominated in the corn field. Few correlations existed between fa, Ф, Pb and gases fluxes while all models predicted that Ds/Do and T significantly correlated with CO2 and CH4 with correlation coefficient （r） ranging from 0.20 to 0.80. Overall, diffusivity models based on fa alone gave higher Ds/Do, lower τ, and higher R2 and better explained the relationship between pore space indices （Ds/Do and τ） and gases fluxes. Inclusion of Ds/Do and τ in predictive models will improve our understanding of the dynamics of greenhouse gas fluxes from soils. Ds/Do and τ can be easily obtained by measurements of soil air and water and existing diffusivity models.