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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 cm3 soil cores) samples were collected from each site. Thereafter, clay content, organic carbon (OC), bulk density (ρb), pH, electrical conductivity (EC), oxalate‐extractable phosphorus (Pox), aluminum (Alox), and iron (Feox) content, soil water content, gas diffusivity (Dp/D0), and air permeability (ka) 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 Dp/D0 and ka 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, Pox, and ρb. Core Ideas: Litter decomposition, quantified by the Tea Bag Index (TBI), was determined across land uses.Grasslands had the highest decomposition rate and stabilization factor of plant litter.Soil gas transport was more important to stabilization factor not decomposition rate.Variability in the TBI parameters was affected by soil pH, Pox, and ρb.The inclusion of land use improved the predictions of both TBI parameters. [ABSTRACT FROM AUTHOR]

The average particle density (rd) is a fundamental soil property, used for calculating the total porosity. Traditional rd measurement by pycnometer method is tedious and time-consuming. In this study, visible-near-infrared (vis-NIR) spectroscopy and a simple two-compartment linear and curvilinear pedotransfer function only requiring knowledge of soil organic matter content (OM) were tested and compared as alternative, indirect, rapid, and cost-effective methods. Soil rd was measured by water pycnometer on 179 soils representing a wide range of OM (0.002-0.767 kg kg-1), whereas soil spectra were measured on air-dry samples by vis-NIR spectroscopy. The rd models were developed using partial least squares regression with leave-one-out-cross-validation using vis-NIR spectral data, and a simple twocompartment pedotransfer function, rd = A(OM) + B(1 - OM) using the OM content. Predictive abilities of these two methods were tested using three different datasets: (i) minerals soils (OM < 0.1 kg kg-1), (ii) organic soils (OM > 0.1 kg kg-1), and (iii) all soils. Calibrating the two-compartment pedotransfer function for the entire dataset gave expected values for the individual particle densities of OM (A = 1.244 g cm-3) and mineral particles (B = 2.615 g cm-3). The vis-NIR spectroscopy model successfully predicted soil rd for the entire dataset (R2 = 0.87, RMSECV = 0.10 g cm-3), with a poorer performance than the two-compartment linear model (R2 = 0.96, RMSE = 0.06 g cm-3). Using only the mineral soils data did not suffice to obtain realistic and accurate vis-NIR spectroscopy (R2 = 0.62, RMSECV = 0.02 g cm-3) or OM based (R2 = 0.80, RMSE = 0.02 g cm-3) models for rd, illustrating the importance of the wide range of OM content considered in the present study. [ABSTRACT FROM AUTHOR]