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Sustainable soil carbon sequestration practices need to be rapidly scaled up and implemented to contribute to climate change mitigation. We highlight that the major potential for carbon sequestration is in cropland soils, especially those with large yield gaps and/or large historic soil organic carbon losses. The implementation of soil carbon sequestration measures requires a diverse set of options, each adapted to local soil conditions and management opportunities, and accounting for site-specific trade-offs. We propose the establishment of a soil information system containing localised information on soil group, degradation status, crop yield gap, and the associated carbon-sequestration potentials, as well as the provision of incentives and policies to translate management options into region- and soil-specific practices.

The remarkable complexity of soil and its importance to a wide range of ecosystem services presents major challenges to the modeling of soil processes. Although major progress in soil models has occurred in the last decades, models of soil processes remain disjointed between disciplines or ecosystem services, with considerable uncertainty remaining in the quality of predictions and several challenges that remain yet to be addressed. First, there is a need to improve exchange of knowledge and experience among the different disciplines in soil science and to reach out to other Earth science communities. Second, the community needs to develop a new generation of soil models based on a systemic approach comprising relevant physical, chemical, and biological processes to address critical knowledge gaps in our understanding of soil processes and their interactions. Overcoming these challenges will facilitate exchanges between soil modeling and climate, plant, and social science modeling communities. It will allow us to contribute to preserve and improve our assessment of ecosystem services and advance our understanding of climate-change feedback mechanisms, among others, thereby facilitating and strengthening communication among scientific disciplines and society. We review the role of modeling soil processes in quantifying key soil processes that shape ecosystem services, with a focus on provisioning and regulating services. We then identify key challenges in modeling soil processes, including the systematic incorporation of heterogeneity and uncertainty, the integration of data and models, and strategies for effective integration of knowledge on physical, chemical, and biological soil processes. We discuss how the soil modeling community could best interface with modern modeling activities in other disciplines, such as climate, ecology, and plant research, and how to weave novel observation and measurement techniques into soil models. We propose the establishment of an international soil modeling consortium to coherently advance soil modeling activities and foster communication with other Earth science disciplines. Such a consortium should promote soil modeling platforms and data repository for model development, calibration and intercomparison essential for addressing contemporary challenges.

Modeling global C cycles requires in-depth 'knowledge about small-scale C stocks and turnover processes, yet different soil organic C (SOC) pools reveal considerable spatiotemporal heterogeneity, at the field scale, which is scarcely 'known due to the considerable workload associated with traditional fractionation procedures. We investigated the potential of mid-infrared spectroscopy combined with partial least squares regression (MIRS-PLSR) for rapid assessment of different particulate organic matter (POM) pools and their spatial heterogeneity at the field scale. Locally calibrated prediction models estimated the contents of SOC, POM of three size classes (POMI: 2000-250 [micro]m; POM2: 250-53 [micro]m; and POM3:53-20 [micro]m), and lignin contents for 129 locations in a 1.3-ha test field. Relations between the parameters were described using correlation analysis and fuzzy- [kappa] statistics. All parameters were predicted successfully by applying local calibrations for MIRS-PLSR ([R.sup.2] = 0.77-0.96). The prediction model for POM1 chiefly relied on specific signals of lignin and cellulose; contents of POM2 were estimated by spectral bands assigned to degradation products as aliphatic C-H groups and aromatic moieties; carboxylic groups essentially contributed to the prediction of POM3. There was a close spatial relation between the coarse POM1 and POM2 fractions and lignin ([kappa] = 0.77), which largely also explained variations in bulk SOC. In contrast, POM3 exhibited a less deterministic pattern in the field, thus contributing little to the spatial variation in SOC content. doi: 10.2136/sssaj2009.0195

Recently, it has been suggested that soil organic C (SOC) does not always respond linearly to increasing C input, thereby limiting the rate and efficiency of C stabilization in soils. Therefore, we postulated that when a soil is exposed to a broad range of C inputs through a range of manure treatments, it will show C saturation behavior and different SOC pools will saturate at different rates. To test this, different SOC pools were isolated by physical fractionation techniques from a long-term agricultural experiment in Lethbridge, Canada. In this experiment, manure has been applied since 1973 at rates of 0, 60, 120, and 180 Mg [ha.sup.-1] [yr.sup.-l] (wet weight). In the total mineral soil as well as the small macroaggregates (250-2000 [micro]m), microaggregates (53-250 [micro]m), and the silt plus clay fraction (2000 [micro]m) were the only water-stable aggregate fraction that increased in C content across all manure input levels. Further physical separation of macroaggregates into subpools by microaggregate isolation showed that coarse (>250 [micro]m) particulate organic matter (POM) was the fraction that accounted most for the increase in C content of the large macroaggregates. Furthermore, the turnover of large macroaggregates increased with increasing manure applications, as indicated by decreased formation and stabilization of intramicroaggregate POM within the large macroaggregates. We conclude that as C input increases, the mineral fraction of a soil saturates and consequently additional C input will only accumulate in labile soil C pools that have a relatively faster turnover. Abbreviations: cPOM, coarse particulate organic matter; fine iPOM, fine intramicroaggregate particulate organic matter; LF, light fraction; POM, particulate organic matter; SOC, soil organic carbon; SOM, soil organic matter.

D-Amino acids indicate aging, bacterial origin, and pathogenic properties of peptides in the environment, but the reliable assessment of D-enantiomers must account for a yet unknown formation during hydrolyses. Here, we introduce a method for the in vitro determination of the hydrolysis-induced racemization (HIR) of amino acids in environmental samples. It involves hydrolyses with hydroand deuteriochloric acid (6 M, 12 h, 105[degrees]C), desalting, and selective detection of chiral mass fragments of amino acid-N-pentafluoropropionyl derivatives, D-Amino acids formed in [sup.2]HCl incorporated deuterium into their [C.sub.[alpha]] position. This resulted in a relative signal loss of the nondeuterated fragment compared with the [sup.1]HCl hydrolysate. Mathematically evaluating the relative target signal intensities of both hydrolysates allowed the quantification of the proportion of D-amino acids formed during sample processing. Side-chain incorporations of deuterium were no limitations for this method as they could be estimated from that of the respective L-enantiomers. In soil and litter samples, between 0 (D-glutamic acid) and 85% (D-alloisoleucine) of the detected D-amino acids were formed upon hydrolysis (standard error, 5-11%). For a given amino acid, the HIR varied by a factor of 2-10 between samples, thereby confirming that HIR must be individually assessed for samples from different environments.

To elucidate the role of microorganisms for C and N sequestration in arable soils converted to grassland (sites of the Conservation Reserve Program; CRP), we determined amino sugars as indicators for microbial residues in surface samples (0-5 cm) obtained from each of 10 adjacent native grassland, CRP, and cropland sites across the U.S. Great Plains. The CRP sites were 6 to 10 yr and the cropland sites were >80 yr old. Compared with native grasslands, the CRP sites had lost between 17 and 50% and the cropland sites between 32 and 94% of their surface soil organic matter (SOM). The C/N ratio was not significantly different among the three land-use systems, indicating that C and N losses occurred at similar intensity. The mean amino sugar concentrations decreased in the order native grassland (70 g [kg.sup.-1] C; 750 g [kg.sup.-1] N) > CRP (53 g [kg.sup.-1] C; 570 g [kg.sup.-1] N) > cropland (47 g [kg.sup.-1] C; 450 g [kg.sup.-1] N). This decrease in the element-normalized concentrations of amino sugars indicated that they responded faster to management than other C or N containing compounds. The response of individual amino sugars related to soil compaction and the temperature regime. We suggest that the resequestration of C and N into the residues of bacteria and fungi requires several years, but as it depends on land use it could be manipulated using, for example, soil decompacting techniques to improve CRP efficiency.

Changes in the composition and amount of saccharides have been shown to reflect soil organic matter (SOM) dynamics. The effect of climate on soil monosaccharide pools was investigated in this study. Particle-size fractions were obtained from composite samples taken from the top 10 cm of soil at 18 native grassland sites along mean annual temperature (MAT) and precipitation (MAP) transects from Saskatoon, Canada to southern Texas, USA. Neutral and acidic sugars were determined in the bulk soil,