Biogenic and Physicogenic Aggregates Under Different Crops With Black Oat in Nova Friburgo, Brazil

Abstract

<jats:p>ABSTRACT The objective of this study was to evaluate the efficiency of black oat (Avena strigosa Schreb) crops in recovering soil aggregation, and quantify the nutrient contents in aggregates considering their formation pathways (biogenic and physicogenic) in crop areas in a mountains environment in the municipality of Nova Friburgo, RJ, Brazil. The landscape was stratified into two sections for the study: upper, two areas with black oat crops, one fertilized and one not fertilized one not fertilized, and one adjacent forest area representing the original soil conditions; and lower: one fertilized area with black oat, and one fertilized area with black oat intercrops with oilseed radish (Raphanus sativus L.) and vetch (Vicia sativa L.), and one adjacent forest area representing the original soil conditions. The aggregates were separated according to their formation pathways, quantifying the weight percentage of each formation pathway. The aggregate stability and nutrient and organic carbon contents were evaluated. The fertilized area in the upper section had the highest biogenic aggregate percentage, which was associated with the highest total organic carbon contents, and soil fertility. This area also had the highest weighted mean diameter (WMD) and geometric mean diameter (GMD) of aggregates. The intercrop area in the lower section had the highest biogenic aggregate percentage and the lowest P, Ca+2, Mg+2, and K+ contents in the aggregates. The management systems affected the aggregate formation pathways. Morphological classification is an important tool for the monitoring of soil management. The black oat crops increased the biogenic aggregate formation, which become reservoir of nutrients.</jats:p>

Edaphic fauna and soil properties under different managements in areas impacted by natural disaster in a mountainous region

“…The soil fauna community is known to influence the formation and stability of biogenic aggregates (Ferreira et al, 2020;Lima et al, 2020). In this study, Coleoptera larvae were positively associated with MWDbio, whereas Coleoptera was associated with MWDphy (Figure 4).…”

“…Cover crops have been proposed as an alternative to increase soil cover and C inputs (Poeplau and Don, 2015;Duval et al, 2016;Lima et al, 2020) and to improve soil physical quality (Recio-Vázquez et al, 2014). For example, black oats (Avena strigosa Schreb.)…”

Physicogenic and biogenic aggregates under different management systems in the Cerrado region, Brazil

“…In soils under native vegetation, a greater action of biological agents (macrofauna and flora) occurs because of the stability of the environment. In a secondary forest area in southeastern Brazil, Lima et al (2020) observed termite nest in the soil, which probably contributed to the formation of the aggregates from the biogenic pathway. In a study involving individuals from the edaphic fauna and aggregates genesis, Batista et al (2013a) observed that the Cerrado vegetation area was important in distinguishing the characteristics of the different types of aggregates because it is a native environment.…”

“…The results showed that soil management has a determining effect on the formation process of aggregates. Under adequate soil use and management practices, maintenance or increase in the SOM content (plants aerial part and root systems) may occur and favor the population of edaphic micro and macroorganisms development in the rhizosphere, and contribute to the formation of the biogenic aggregates (Bronick and Lal, 2005;Lima et al, 2020).…”

Biogenic and physicogenic aggregates: formation pathways, assessment techniques, and influence on soil properties

“…In this study, Pulleman et al (2005), based on descriptions by Bullock et al (1985), described, methodologically, what biogenic and physicogenic aggregates are and highlighted for the first time the class of intermediate aggregates. In Brazil, some studies used aggregates ranging from 19 to 8 mm (Melo et al, 2019a); 9.7 to 4.0 mm (Batista, 2015;Ferreira et al, 2020); 9.5 to 4.0 mm (Velasquez et al, 2007;Loss et al, 2017;Ventura et al, 2018;Mergen Junior et al, 2019a,b); 9.7 to 8.0 mm (Batista et al, 2013;Loss et al, 2014;Rossi et al, 2016;Fernandes et al, 2017;Lima et al, 2020;Pinto et al, 2021). Pulleman et al (2005) point out that small aggregates (1 to 2 mm) are very fragile, which makes separation hard; however, larger aggregates (19 to 8 mm) makes separation easier, which decreases the error associated with aggregation pathway classification (Jouquet et al, 2009;Melo et al, 2019a).…”