ABSTRACT Adopting land-uses that contribute with a considerable litter input can affect the accumulation, protection, and bioavailability of organic carbon in the edaphic environment, compromising the different compartments of soil organic matter (SOM) and the associated benefits. Moreover, changes in seasons can influence the dynamic of SOM. Notably, the mechanisms involved in SOM stabilization and storage, particularly in agroforestry production areas, are still poorly explored. This study aimed to verify if the contents of soil organic carbon (SOC) and the physical fractions of the SOM are modified as a function of agroforestry systems implemented in the short term, and verify if seasonality can affect the compartmentalization of SOM in agrifood systems. Also, we tested if the carbon management index (CMI) is sensitive to detecting management practices quality across the unmanaged pasture, different agroforestry systems, and a reference area (forest). We measured soil physical properties, SOC content in bulk soil, particular organic carbon (POC), and mineral-associated organic carbon (MAOC) fractions at three different depths (0.00-0.05, 0.05-0.10, and 0.10-0.20 m) in response to the adoption of agroforestry systems. Our results show that after a short period of implementation of agroforestry systems, significant changes were observed in SOC contents and the physical fractions of SOM in the most superficial layers (0.00-0.05 and 0.05-0.10 m), with emphasis on the particulate fraction of SOM. We verified that the seasonality affected the SOC, POC, and MAOC contents. We also found that the CMI index was more sensitive and efficient in detecting changes arising from seasonality and the management practices involved. According to this index, it was possible to verify that the agroforestry system with the highest density of species for biomass production (AS3) has been accumulating more carbon in the soil. Therefore, this study provides relevant information regarding soil carbon management in agroforestry systems.

Abstract The aim of this study was to evaluate the distribution of chemical and physical fractions of soil organic matter (SOM) in anthropic horizons of soil profiles in the west of Pará. The highest total organic carbon values were observed in the superficial horizons, especially in the antrópico LAd and antrópico CHd (45.0g kg-1). Were observed predominance of recalcitrant organic material. It appears that most of the C found in the SOM fractions is associated with C stabilization mechanisms such as the recalcitrance provided by the presence of pyrogenic coal, in addition to its ability to present carboxylic groups that increase its interaction with the mineral fraction of the soil, characterizing the mechanism of chemical protection. It is observed that the SOM fractions can function as indicators that contribute to better understanding of the soil carbon dynamics in soils with antrópico horizons.

ABSTRACT Soil aggregates and their stability affect a wide range of soil properties. This study aimed to (a) verify whether biogenic aggregation provides higher macro- and microaggregate stabilization, and (b) evaluate whether biogenic aggregates are associated with higher labile organic carbon and glomalin contents. Three management systems were evaluated (permanent pasture, PP; no-tillage system, NT; and no-tillage + Brachiaria system, NT+B) as well as a reference area (Atlantic Forest biome vegetation, NF). According to their origin or formation pathway, the aggregates were separated, identified, and classified as biogenic (formed by biological processes) and physicogenic (resulting from chemical and physical actions). The PP system provided the greatest stabilization of the macroaggregates, regardless of the formation pathway, as reflected by a greater mean weight diameter (MWD). The PP system also influenced the degree of microaggregate stability by increasing the bond strength and reducing the dispersion of the clay fraction. Finally, the PP system elevated the contents of labile organic carbon (POXC), easily extractable glomalin (GRSP-EE), and total glomalin (GRSP-T) under both formation pathways. The NT+B system favored the stabilization of macroaggregates, especially in the subsurface soil layer, compared with the NT area. In the aggregates of the NT and NT+B areas, the highest values observed were for water-dispersible clay (WDC) and the lowest values observed were for non-dispersible clay (NDC), a pattern opposite to that observed in the aggregates of the PP and NF areas. In the biogenic aggregates of all areas, a high POXC content was quantified, and biogenic aggregation proportionally increased the values of MWD, GRSP-EE, and GRSP-T relative to physicogenic aggregation. The results showed that grain production systems, pasture systems, and non-anthropized environments differentially influenced aggregation and the concentrations of organic fractions associated with aggregate stability. This study highlights the need for future studies using these indicators to monitor the quality of soils, especially those with sandy texture, which are considered more fragile.

ABSTRACT An important strategy for the sustainable management of Cerrado soils is no-till (NT) systems, which may improve soil properties, particularly aggregation. Soil aggregates can be categorized according to their formation pathways into physicogenic (Phy) and biogenic (Bio). This study aimed (i) to quantify the relative proportion of physicogenic and biogenic aggregates and (ii) evaluate the levels of total organic carbon and their respective humic and physical fractions in the aggregates’ formation pathways. The following managed and unmanaged sites were evaluated: a 6-year no-till site (6NT), an 18-year no-till site (18NT), a conventional tillage site (CT), and a reference Cerrado site (RS). Retained aggregates were analyzed morphologically, separated into Phy and Bio, and quantified. Subsequently, aggregates were subjected to total organic carbon (TOC) determination, fulvic acid carbon, humic acid carbon, humin carbon, particulate organic carbon (POC), mineral-associated organic carbon, and free light fraction carbon (FLFC). The proportion of Bio aggregates increased with decreasing management intensity. When TOC and humic acid carbon levels were compared between sites, it was found that Bio aggregates from 18NT and 6NT contained higher carbon content than Bio aggregates from CT. Particulate organic carbon and FLFC differed between aggregate types, with higher POC values observed in Bio aggregates from CT and 18NT and higher FLFC values in Bio aggregates from CT, 6NT, and 18NT. The practices adopted in the conservation management system favored biogenic aggregation in the Cerrado region, which can be proven through the study of the fractions of soil organic matter contained in these aggregates. The biogenic aggregation changed the SOM dynamics. Principal component analysis showed a clear distinction between conventional and conservationist management systems.

ABSTRACT: The soil particles can be gathered through physical and/or chemical processes in association with the biological activity, leading to the formation of aggregates. Soil aggregates has several functions in the soil, increasing macroporosity and water circulation - consequently reducing soil erosion and mechanical resistance to root growth, contributing to greater fixation of plants to the soil and absorption of water and nutrients, and protection of intra-aggregate organic matter. The aggregates were initially classified morphologically and in terms of their stability. In recent years, another way of evaluating aggregates, regarding their formation or origin pathway, has gained prominence in the studies conducted in Brazil. As for their origin, the aggregates can be classified morphologically as physicogenic, biogenic, or intermediate. This manuscript presents the techniques used to sample aggregates, the morphological patterns for their distinction observed in different soil classes and management types, and the chemical and physical properties. Additionally, we present analyses that are not commonly used to evaluate aggregates but which have the potential to be used as tools for a better understanding of their origin and to evaluate their modifications when subject to different types of management. In practical terms, identifying the aggregate origin and determining the related attributes allows recognizing the effect of vegetation/soil/management on soil aggregate forming agents, mainly roots and soil fauna, which reflects soil quality. For future studies, and especially to determine the importance of biogenic aggregation in improving edaphic properties, we suggest the use of micromorphology, near-infrared spectroscopy, X-ray computed tomography, clay dispersion analyses in addition with chemical, physical, and biological analysis. This approach can contribute to the identification of other patterns related to pedogenesis and the pathways of aggregate formation.

ABSTRACT Quantification of soil properties is essential for better understanding of the environment and better soil management. The conventional techniques of laboratory analysis are sometimes costly and detrimental to the environment. Thus, development of new techniques for soil analysis that do not generate residues, such as spectroscopy, is increasingly necessary as a viable way to estimate a wide range of soil properties. The objective of this study was to predict the levels of organic carbon (OC), clay, and extractable phosphorus (P), from the spectral responses of soil samples in the visible and near infrared (Vis-NIR), medium infrared (MIR), and Vis-NIR-MIR using different preprocessing methods combined with five prediction models. Soil samples were collected in Iconha, Espírito Santo State, Brazil, in the Ribeirão Inhaúma basin. A total of 184 samples were collected from 92 sites at two depths (0.00-0.10 and 0.10-0.30 m). Physical, chemical, and spectral analyses were performed according to routine soil laboratory methods. Random selection was made of 70 % of total samples for training and 30 % for validation of the models. The coefficient of determination (R2) and root mean square error (RMSE) were calculated in order to assess model performance. The standardized indexes of prediction error RPD and RPIQ were also calculated. For clay and OC, the best R2 was found in the MIR spectrum, at 0.69 and 0.65, respectively, and for P, it was 0.57 in Vis-NIR. The MSC (Multiplicative Scatter Correction), CR (Continuum removal), and SNV (Standard Normal Variate) preprocesses were most efficient for predicting clay, OC, and P, respectively, while the PLSR - Partial Least Squares Regression (OC and P) and SVM - Support Vector Machine (clay) gave the best predictions and are therefore recommended for modeling these properties in the study area. The models identified in this study can be used to discriminate soils according to a critical test value for clay, OC, and P.