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Land uses and cultivation are important factors controlling SOC storage on the Loess Plateau. These factors may also affect the relative importance of different mechanisms for the stabilization of organic matter in the soil. Easily oxidizable organic carbon (EOC), aggregation and aggregate C fractions in the soil were measured under different land uses. Aggregates were fractionated using a wet-sieving procedure to obtain the distribution of water-stable aggregates. The fractions of aggregates, aggregate SOC and aggregate EOC in grassland and forestland were generally higher than those in farmland. Furthermore, because conventional cultivation destroyed aggregates, the dominant aggregate size fractions were b 0.5 mm for farmland and N0.5 mm for other land uses. Compared to the corresponding values in farmland, the mean weight diameter (MWD) in forestland and grassland increased by 808%-417%, and the stability ratio of water-stable aggregate (WSAR) increased by 920%-553%. Aggregate formation and its dominant size fraction were associated closely with its carbon fractions. SOC and EOC in farmland tended to be concentrated in smaller-sized aggregates, whereas SOC and EOC under other land uses tended to concentrate in larger-sized aggregates. EOC tended to concentrate in larger aggregates than SOC. The small fractions of the aggregates formed large fractions by combining with fresh organic matter. So converting slope farmland to forestland and grassland could improve the storage and quality of SOC, and the tendency of SOC transfer.

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Soil is the largest carbon reservoir on the terrestrial surface. Soil organic carbon (SOC) not only regulates global climate change, but also indicates soil fertility level in croplands. SOC prediction based on remote sensing images has generated great interest in the research field of digital soil mapping. The short revisiting time and wide spectral bands available from Sentinel-2A (S2A) remote sensing data can provide a useful data resource for soil property prediction. However, dense soil surface coverage reduces the direct relationship between soil properties and S2A spectral reflectance such that it is difficult to achieve a successful SOC prediction model. Observations of bare cropland in autumn provide the possibility to establish accurate SOC retrieval models using the S2A super-spectral reflectance. Therefore, in this study, we collected 225 topsoil samples from bare cropland in autumn and measured the SOC content. We also obtained S2A spectral images of the western Guanzhong Plain, China. We established four SOC prediction models, including random forest (RF), support vector machine (SVM), partial least-squares regression (PLSR), and artificial neural network (ANN) based on 15 variables retrieved from the S2A images, and compared the prediction accuracy using RMSE (root mean square error), R2 (coefficient of determination), and RPD (ratio of performance to deviation). Based on the optimal model, the spatial distribution of SOC was mapped and analyzed. The results indicated that the inversion model with the RF algorithm achieved the highest accuracy, with an R2 of 0.8581, RPD of 2.1313, and RMSE of 1.07. The variables retrieved from the shortwave infrared (SWIR) bands (B11 and B12) usually had higher variable importance, except for the ANN model. SOC content mapped with the RF model gradually decreased with increasing distance from the Wei river, and values were higher in the west than in the east. These results matched the SOC distribution based on measurements at the sample sites. This research provides evidence that soil properties such as SOC can be retrieved and spatially mapped based on S2A images that are obtained from bare cropland in autumn.

Laccase catalyzes the oxidation of natural phenols and thereby is believed to initialize reactions in lignification and delignification. Numerous phenolic mediators have also been applied in laccase-mediator systems. However, reaction details after the primary O-H rupture of phenols remain obscure. In this work two types of isomeric phenols, EUG (eugenol) and ISO (trans-/cis-isoeugenol), were used as chemical probes to explore the enzymatic reaction pathways, with the combined methods of time-resolved UV-Vis absorption spectra, MCR-ALS, HPLC-MS, and quantum mechanical (QM) calculations. It has been found that the EUG-consuming rate is linear to its concentration, while the ISO not. Besides, an o-methoxy quinone methide intermediate, (E/Z)-4-allylidene-2-methoxycyclohexa-2,5-dienone, was evidenced in the case of EUG with the UV-Vis measurement, mass spectra and TD-DFT calculations; in contrast, an ISO-generating phenoxyl radical, a (E/Z)-2-methoxy-4-(prop-1-en-1-yl) phenoxyl radical, was identified in the case of ISO. Furthermore, QM calculations indicated that the EUG-generating phenoxyl radical (an O-centered radical) can easily transform into an allylic radical (a C-centered radical) by hydrogen atom transfer (HAT) with a calculated activation enthalpy of 5.3 kcal mol(-1) and then be fast oxidized to the observed eugenol quinone methide, rather than an O-radical alkene addition with barriers above 12.8 kcal mol(-1). In contrast, the ISO-generating phenoxyl radical directly undergoes a radical coupling (RC) process, with a barrier of 4.8 kcal mol(-1), while the HAT isomerization between O- and C-centered radicals has a higher reaction barrier of 8.0 kcal mol(-1). The electronic conjugation of the benzyl-type radical and the aromatic allylic radical leads to differentiation of the two pathways. These results imply that competitive reaction pathways exist for the nascent reactive intermediates generated in the laccase-catalyzed oxidation of natural phenols, which is important for understanding the lignin polymerization and may shed some light on the development of efficient laccase-mediator systems.