Phytogeographic retrospective in ecotonal areas guided by soil attributes

Re-establishing deforested ecosystems to pre-settlement vegetation is difficult, especially in ecotonal areas, due to lack of knowledge about the original physiognomy. Our objective was to use a soils database that included chemical and physical parameters to distinguish soil samples of forest from those of savannah sites in a municipality located in the southeastern Brazil region. Discriminant analysis (DA) was used to determine the original biome vegetation (forest or savannah) in ecotone regions that have been converted to pasture and are degraded. First, soils of pristine forest and savannah sites were tested, resulting in a reference database to compare to the degraded soils. Although the data presented, in general had a high level of similarity among the two biomes, some differences occurred that were sufficient for DA to distinguish the sites and classify the soil samples taken from grassy areas into forest or savannah. The soils from pastured areas presented quality worse than the soils of the pristine areas. Through DA analysis we observed that, from seven soil samples collected from grassy areas, five were most likely originally forest biome and two were savannah, ratified by a complementary cluster analysis carried out with the database of these samples. The model here proposed is pioneer. However, the users should keep in mind that using this technology, i.e., establishing a regional-level database of soil features, using soil samples collected both from pristine and degraded areas is critical for success of the project, especially because of the ecological and regional particularities of each biome.

Molecular identification of fungal communities in a soil cultivated with vegetables and soil suppressiveness to Rhizoctonia solani

Fungi constitute an important part of the soil ecosystem, playing key roles in decomposition, cycling processes, and biotic interactions. Molecular methods have been used to assess fungal communities giving a more realistic view of their diversity. For this purpose, total DNA was extracted from bulk soils cultivated with tomato (STC), vegetables (SHC), and native forest (SMS) from three sites of the Taquara Branca river basin in Sumaré County, São Paulo State, Brazil. This metagenomic DNA was used as a template to amplify fungal 18S rDNA sequences, and libraries were constructed in Escherichia coli by cloning PCR products. The plasmid inserts were sequenced and compared to known rDNA sequences in the GenBank database. Of the sequenced clones, 22 were obtained from the SMS sample, 18 from the SHC sample, and 6 from the STC sample. Although most of the clone sequences did not match the sequences present in the database, individual amplified sequences matched with Glomeromycota (SMS), Fungi incertae sedis (SMS), and Neocallimastigomycota (SHC). Most of the sequences from the amplified taxa represent uncultured fungi. The molecular analysis of variance (AMOVA) indicated that fluctuations observed of haplotypes in the composition may be related to herbicide application. © 2013 Silvana Pompéia Val-Moraes et al.

Modelagem do transporte de sedimentos na alta Bacia do Córrego Cachoeirinha (Rio Claro, SP) através do software Soil and Water Assessment Tool (SWAT)

This study aimed to simulate and evaluate the sediment transport in Upper Basin Stream Cachoeirinha in Rio Claro, SP, and compare the results with previous studies performed in the same basin. The modeling software used in this study was Soil and Water Assessment Tool (SWAT), which is a very comprehensive tool that discusses many physical processes. In this work, the hydrosedimentological processes were treated, aiming to understand the sediment production and transport. The Basin Stream Cachoeirinha has an area with predominantly agricultural use, especially sugar cane. The database for inclusion in software was constructed from the following elements: climatic, topographical, soil type and use and land cover of the area, also including the parameters of Modified Universal Soil Loss Equation (MUSLE). The analysis was conducted for a period of 16 years (1994-2010), which is the range of data available from CEAPLA. The results were analyzed in terms of annual runoff and sediment yield. The average sediment delivery in the simulation was 0.94 t/ha/year, while the maximum annual contribution was 7.28 t/ha/year

Organic farm does not improve neither soil, or water quality in rural watersheds from southeastern Brazil

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Correlating soil porosity and respective geological unit in Paraíba do sul Valley, Brazil: a geostatistical methodology proposal

This manuscript aims proposing a methodology for correlating soil porosity to the respective geological units using geostatistical analysis techniques, including interpolation data by kriging. The site studied was in Lorena municipality, Paraíba do Sul Valley, southeastern Brazil. Specifically all studies were carried out within an area of 12 km2 located at Santa Edwirges farm. The database comprehended 41 soil samples taken at different geological and geomorphologic units at three different depths: surface, 50 cm and 100 cm depth. The geostatistical analyses results were correlated to a geological mapping specifically elaborated for the site. This mapping accounts for two different geological formations and a geological contact characterized by a shearing zone. The results indicate the existence of a significant relationship between the soil porosity and the respective geological units. The studies revealed that the residual soils from weathered granitic rocks tend to have higher porosities than the residual soils from weathered biotite gneiss rocks, while the soil porosity within the shearing zone is relatively un-sensitive to the respective geological formation. The spatial patterns observed were efficient to evaluate the relationship between the soil porosity, geology unit and the and geomorphology showing a good potential for correlating with others soil properties such as hydraulic conductivity, soil water retention curves and erosion potentials.