Linking litter decomposition to soil physicochemical properties, gas transport, and land use

Litter decomposition is a critical process in carbon cycling, which can be affected by land use. The relationship between litter decomposition and soil properties under different land uses remains unclear. Litter decomposition can be quantified by the Tea Bag Index (TBI), which includes a decomposition rate k and a stabilization factor S. Our objective was to investigate linkages between TBI and soil physicochemical and gas transport properties and land use. We buried three pairs of tea bags in 20 sites (covering cropland, grassland, heathland, and forest land uses) in a transect from the western to the eastern coast of the Jutland peninsula, Denmark. The tea bags were retrieved after 90 d and TBI was determined. Disturbed and undisturbed (100 cm(3) soil cores) samples were collected from each site. Thereafter, clay content, organic carbon (OC), bulk density (rho(b)), pH, electrical conductivity (EC), oxalate-extractable phosphorus (P-ox), aluminum (Al-ox), and iron (Fe-ox) content, soil water content, gas diffusivity (D-p/D-0), and air permeability (k(a)) at -10 kPa were measured. Results showed that grasslands had the highest k and S among four land uses, and agricultural soils (croplands and grasslands) exhibited higher TBI values than seminatural soils (forest and heathland). The prediction of S was better than that of k based on multiple linear regression analysis involving soil physicochemical properties. Clay content and OC were not strong predictors. Including D-p/D-0 and k(a) improved the prediction of S, and finally, the inclusion of land use enhanced the prediction of both k and S. The different trends between two distinct land-use groups can be attributed to pH, P-ox, and rho(b).

Automated summary

The study revealed that grasslands exhibit the highest decomposition rate and stability among different land use types, with agricultural soils showing higher TBI values compared to seminatural soils. The inclusion of soil physicochemical properties in multiple linear regression analysis improved the prediction of stability in litter decomposition.