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Maintaining soil organic matter (SOM) is crucial for healthy and productive agricultural soils and requires understanding at the process level, including the role of SOM protection by soil aggregates and the connection between microbial growth and aggregate formation. We developed the Soil Aggregation through Microbial Mediation (SAMM) model, to represent this important connection. The pools of SAMM are fully measurable, and we calibrated and evaluated it against data from a long-term bare fallow experiment in a tropical sandy soil. This experiment received additions of plant litter of different compositions, which resulted in twice the soil carbon stocks in the best treatment compared to the control (about 8 vs. 4 t C ha -1 in 0–15 cm soil depth) after 25 years. As hypothesized, the SAMM model effectively represented the microbial growth response after the addition of litter and the subsequent formation and later destabilization of aggregates. The low correlations between different calibrated model parameters (r<0.5 for all parameters; r>0.4 for only 4 of 22) showed that SAMM is parsimonious. SAMM was able to capture differences between treatments in soil organic carbon (Nash–Sutcliffe modeling efficiency (EF) of 0.68), microbial nitrogen (EF of 0.24), and litter carbon (EF of 0.80). The amount of carbon within the aggregates (EF of 0.60) and in the free silt and clay fraction (EF of 0.24) was also simulated very well to satisfactorily. Our model results suggested that in spite of the sandy soil, up to 50 % of carbon stocks were stabilized through aggregate protection mechanisms; and that microbial and physical aggregate formation coexists. A version of the SAMM model without aggregate protection (SAMMnoAgg) initially failed to stabilize soil organic carbon (EF decreased to -3.68) and the simulation of microbial nitrogen worsened (EF of 0.13). By recalibrating SAMMnoAgg, it was possible to partially correct for the lack of aggregate protection by reducing the rate of mineral-attached carbon decomposition by about 85 % (EF of 0.68, 0.75, and 0.18 for SOC, litter carbon, and microbial nitrogen, respectively). However, the slightly better evaluation statistics of SAMM (e.g., Akaike information criterion of 5351 vs. 5554) suggest that representing aggregate dynamics in SOM models can be beneficial and necessary to understand the mechanism behind SOM dynamics. Our results indicate that current models without aggregate formation partly compensate for the absence of aggregate protection by lowering the turnover rates of other pools. Thus, they remain suitable options where data on aggregate associated carbon are not available. [ABSTRACT FROM AUTHOR]

In light of the large role that soil organic matter (SOM) plays in maintaining healthy and productive agricultural soils, it is crucial to understand the processes of SOM protection including the role of soil aggregate protection. Yet, few numerical process models include aggregate formation and even fewer represent the important connection between microbial growth and aggregate formation. Here, we propose a model of S oil A ggregation through M icrobial M ediation (SAMM), which consist of measurable pools and 5 couples soil aggregate formation to microbial growth. The model was evaluated against data from a long term bare-fallow experiment in a tropical sandy soil, subject to plant litter additions of different compositions. The SAMM model effectively represented the microbial growth response after litter addition and the following formation and later disruption of aggregates. Model parameter correlation was low (all r < 0.5; r > 0.4 for only 4 of 22 parameters) showing that SAMM is well parameterized. Differences between treatments resulting from different litter compositions could be captured by SAMM for soil organic carbon (Nash-Sutcliffe modelling efficiency (EF) of 0.68), microbial nitrogen (EF of 0.24) and litter carbon (EF of 0.80). Aggregate-related fractions, i.e., carbon inside aggregates (EF of 0.60) and also carbon in the free silt and clay fraction (EF of 0.24) were simulated very well to satisfactory. Analysis of model parameters led to further noteworthy insights. For example, model results suggested that up to 50 % of carbon in the soil is stabilized through aggregate protection, even in a sandy soil, and that both microbial activity and physical aggregate formation coexist. When aggregate formation was deactivated, the model failed to stabilize soil organic carbon (EF dropped to -3.68) and microbial nitrogen was represented less well (EF of 0.13). By re-calibrating the model version with deactivated aggregates, it was possible to partly correct for removing the aggregate formation, i.e., by reducing the decomposition rate of mineral attached carbon by about 85 % (EF of 0.68, 0.75 and 0.18 for SOC, litter carbon and microbial nitrogen, respectively). Yet, the overall slightly better evaluation statistics (e.g., Akaike information critereon of 5351 vs 5554) show the potential importance of representing aggregate dynamics within SOM models. Our results indicate that current models without aggregate formation partly compensate the missing protection effect by lowering turnover rates of other pools and thus may still be suitable options where data on aggregate associated carbon is not available. [ABSTRACT FROM AUTHOR]

The objective of this study was to investigate distribution of phosphorus (P) in different soil profiles as influenced by land-use changes. The study sites were located in six districts of the Maha Sarakham province, Northeast Thailand. Soil samples were collected from five soil depths: 0-20, 20-40, 40-60, 60-80, and 80-100 cm under four adjacent land uses, including forest, cassava, sugarcane, and rice paddy. The air-dried soil samples were subjected to determine available P using a Bray II extractant. The concentration of P was then measured employing a UV-VIS spectrophotometer. When considering P stock at each soil layer, higher P stock was in topsoil (0-20 cm) than in each of the 5 layers of subsoils. Agricultural practices, such as high rate of chemical fertilizer input, can enhance P stocks in soils of upland crops (i. e., sugarcane and cassava), in comparison to paddy and forest soils. Additionally, deep plowing in the upland soils prior to cultivation can induce P leaching from topsoil to subsoil, as seen in the larger amount of P accumulation in the upland subsoil. This study pointed out that the same land use, with different agricultural practices from farmers, could lead to different patterns of P distribution in topsoil and subsoil. To restore P in agricultural soil, fertilizer management for crop cultivation is needed. [ABSTRACT FROM AUTHOR]

Against the background of current understanding of dissolved organic carbon (DOC) adsorption onto clay surfaces, it remains unclear if bulk DOC or its fractions contribute to microaggregate formation in the top layers of coarse‐textured soils. We therefore investigated the effects of long‐term inputs of biochemically contrasting organic residues on the chemical characteristics and vertical distribution of DOC in a coarse‐textured Ultisol. During 2007–2008, DOC samples were extracted from soil profiles of a long‐term residue quality field experiment initiated in 1995. In this field experiment, groundnut stover, dipterocarp and tamarind leaf litter, as well as rice straw of contrasting biochemical quality, were applied yearly at 10 Mg ha−1. Groundnut, dipterocarp and tamarind produced large amounts (7.1–11.8 g C m−2) of high‐molecular‐weight (HMW; > 10 kDa) DOC, which was found in high concentrations (30–50 mg C kg−1) in the topsoil (0–15 cm). Rice straw, however, produced large amounts (3.5 g C m−2) of low‐molecular‐weight (LMW; < 1 kDa) DOC during the initial stage of decomposition. Although the HMW DOC was retained in the topsoil (0–15 cm), the LMW DOC was rapidly translocated to lower soil depths (60–80 cm). This translocation was facilitated by the low adsorption potential of the rice straw‐derived LMW DOC on colloidal surfaces of the topsoil. There was a significant positive correlation of C in the HMW DOC with that in fine particles, indicating their contribution to microaggregate formation and thus C accumulation. It was concluded that biochemical quality of residues as a determinant of concentration and chemistry of DOC and its vertical dynamics along the soil profile must be considered for SOC accumulation in coarse‐textured soils. Furthermore, we found reasonable indications that HMW DOC contributes to microaggregate formation in topsoils. Highlights: Residue quality determined vertical dynamics of DOC in coarse– textured Ultisols.Lignin‐ and polyphenol‐rich residues produced HMW DOC in topsoil.LMW DOC derived from cellulose‐rich residues was translocated to the subsoil.There were indications that HMW DOC supported microaggregate formation in topsoils. [ABSTRACT FROM AUTHOR]