The dynamics of soil aggregation, including aggregate formation by biogenic and physicogenic processes, is affected by the soil management system. The present study aimed to divide soil aggregates into biogenic and physicogenic, and to characterise the aggregates in terms of soil exchange complex, distribution of total organic carbon (TOC), nitrogen (N) levels, and natural 13C and 15N abundance, and determine C levels in the soil organic matter (SOM) fractions of the aggregates. The areas studied were under a no-till system (NTS) established 15 years before, conventional tillage system (CTS) managed with ploughing and harrowing for 56 years, and a secondary forest (Forest) and pasture grass (Axonopus compressus) (Pasture) (both ≥30 years old). Undisturbed soil samples were collected at 0–5 and 5–10 cm. CTS was unsuitable for biogenic aggregate formation, and NTS and Forest areas showed similar biogenic and physicogenic aggregate content. The Pasture area promoted the formation of biogenic aggregates. In contrast to CTS, NTS increased TOC, calcium, magnesium, nitrogen and phosphorus levels. Considering the parameters evaluated, the Forest area showed the most variation (differences) between biogenic and physicogenic aggregates. Biogenic aggregates exhibited higher TOC and nutrient levels than their physicogenic counterparts. In the CTS area, the absence of legumes and the long-term and constant use of N-fertilisers resulted in 15N soil enrichment (at 0–5 cm). In the Pasture area, the absence of legumes and the constant deposition of cattle manure also increased 15N content relative to NTS and Forest areas. The Forest area had the lowest 15N values in the two layers and aggregate types studied. The levels of 13C reflect the type of material incorporated in the soil (mostly C3 plants in Forest and NTS areas and C4 plants in Pasture and CTS areas). The Pasture area favoured the formation of stable SOM, with higher levels of C content in humin fraction (C-HUM) and mineral-associated OC (MOC). CTS compromised SOM stabilisation, producing lower levels of C-HUM, MOC, and moderately oxidisable and resistant fractions. The biogenic aggregates enhanced soil fertility and contained higher C content in SOM fractions than the physicogenic aggregates. We conclude that biogenic rather than physicogenic aggregates can be considered reliable indicators of soil quality.

The soil organic matter (SOM) content and dynamic are related to vegetation cover, climate, relief, and geology; these factors have strong variation in space in the southeastern of Brazil. The objective of the study was to compare and evaluate performance of classical multiple linear regressions (MLR) and geographically weighted regression (GWR) models to predict soil organic carbon (SOC) and chemical fractions of organic matter in the Brazilian southeastern mountainous region. The regression models were fitted based on SOC and chemical fractions of SOM. The points ( = 89) were selected by pedologist's experience along transects and toposequences. The covariates were also selected using the empirical knowledge of pedologists when choosing variables that drive soil carbon content and its dynamics. Geology map, legacy soils map, terrain attributes derived from digital elevation model, and remote sensing indices derived from RapidEye sensor bands were used as covariates. In all MLR models (except for fulvic acid fraction [FAF]), the legacy soil map was selected as a covariate by the stepwise approach. The geology map was not selected as important covariate to predict FAF and humin (HUM). At least one variable derived from remote sensing was selected by the adjusted models. For the prediction of the SOC, HUM, and FAF, the GWR models had the highest performance. The MLR models extrapolated the results, especially for SOC. The relationships among SOC, SOM fractions, and environmental covariates were affected by local landscape variability, and the GWR model was better at modeling.

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O uso de ácido indolbutírico (IBA) como estimulador do enraizamento em estacas de Bougainvillea spectabilis Willd. pode propiciar aumento de raízes para a formação de mudas comercializáveis.  Objetivou-se avaliar o enraizamento, a formação de brotos e a sobrevivência de estacas herbáceas, lenhosas e semi-lenhosas de Bougainvillea com o uso de ácido indolbutírico (IBA).  As estacas foram coletadas e tratadas com o IBA (1000 e 2000 mg/lt).  Aos 56 dias avaliaram-se a porcentagem de estacas vivas, enraizadas e com brotos; o número de brotos e de raízes por estaca e o comprimento da maior raiz e maior broto.  As menores porcentagens de enraizamento foram verificadas nas estacas sem o uso de IBA.  Maiores diferenças foram verificadas para as estacas lenhosas.  O uso do IBA favorece o enraizamento de estacas de Bougainvillea, com melhor desempenho para as estacas lenhosas e na concentração de 2000 mg/lt de IBA.<div id="__if72ru4sdfsdfrkjahiuyi_once" style="display: none;"> </div><div id="__zsc_once"> </div><div id="__if72ru4sdfsdfruh7fewui_once" style="display: none;"> </div><div id="__hggasdgjhsagd_once" style="display: none;"> </div>

Digital elevation models (DEM) used in digital soil mapping (DSM) are commonly selected based on measures and indicators (quality criteria) that are thought to reflect how well a given DEM represents the terrain surface. The hypothesis is that the more accurate a DEM, the more accurate will be the DSM predictions. The objective of this study was to assess different criteria to identify the DEM that delivers the most accurate DSM predictions. A set of 10 criteria were used to evaluate the quality of nine DEMs constructed with different data sources, processing routines and three resolutions (5, 20, and 30 m). Multinomial logistic regression models were calibrated using 157 soil observations and terrain attributes derived from each DEM. Soil class predictions were validated using leave-one-out cross-validation. Results showed that, for each resolution, the quality criteria are useful to identify the DEM that more accurately represents the terrain surface. However, for all three resolutions, the most accurate DEM did not produce the most accurate DSM predictions. With the 20-m resolution DEMs, DSM predictions were five percentage points less accurate when using the more accurate DEM. The 5-m resolution was the most accurate DEM overall and resulted in DSM predictions with 44% accuracy; this value was equal to that obtained with two coarser resolution, lower accuracy DEMs. Thus, identifying the truly best DEM for DSM requires assessment of the accuracy of DSM predictions using some form of external validation, because not necessarily the most accurate DEM will produce the best DSM predictions.

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Fertilidad del suelo, fracciones húmicas y abundancia natural de 13 ABSTRACTHumic fractions of soil organic matter (SOM) and measurements of 13 C and 15 N isotope can be used to highlight differences between management systems with different intensities of land use. This study characterized soil fertility, quantified carbon levels in the humic fractions and evaluated the natural abundance of 13 C and 15 N in systems cultivated under no-tillage system (NTS) and conventional tillage system (CTS) or used with secondary forest or perennial pasture in Marmeleiro, Parana State, Southern Brazil. NTS was more efficient than the conventional tillage system (CTS) in increasing pH ( RESUMEN El uso de las fracciones húmicas de la materia orgánica del suelo (MOS) y las mediciones isotópicas de 13 C y 15 N se puede utilizar para resaltar las diferencias entre los sistemas de gestión con diferentes intensidades de uso de la tierra. El estudio caracteriza la fertilidad del suelo, cuantifica los niveles de carbono en las fracciones húmicas y evaluó la abundancia natural de 13 C y 15 N en el sistema de siembra directa (NTS), sistema de labranza convencional (CTS), bosque secundario y pastizales en el Sur de Brasil. NTS es más eficaz en el aumento de pH (