Contribution of the Global Regulator Gene gacA to Persistence and Dissemination of Pseudomonas fluorescens Biocontrol Strain CHA0 Introduced into Soil Microcosms.

Structural and regulatory genes involved in the synthesis of antimicrobial metabolites are essential for the biocontrol activity of fluorescent pseudomonads and, in principle, amenable to genetic engineering for strain improvement. An eventual large-scale release of such bacteria raises the question of whether such genes also contribute to the persistence and dissemination of the bacteria in soil ecosystems. Pseudomonas fluorescens wild-type strain CHA0 protects plants against a variety of fungal diseases and produces several antimicrobial metabolites. The regulatory gene gacA globally controls antibiotic production and is crucial for disease suppression in CHA0. This gene also regulates the production of extracellular protease and phospholipase. The contribution of gacA to survival and vertical translocation of CHA0 in soil microcosms of increasing complexity was studied in coinoculation experiments with the wild type and a gacA mutant which lacks antibiotics and some exoenzymes. Both strains were marked with spontaneous resistance to rifampin. In a closed system with sterile soil, strain CHA0 and the gacA mutant multiplied for several weeks, whereas these strains declined exponentially in nonsterile soil of different Swiss origins. The gacA mutant was less persistent in nonrhizosphere raw soil than was the wild type, but no competitive disadvantage when colonizing the rhizosphere and roots of wheat was found in the particular soil type and during the period studied. Vertical translocation was assessed after strains had been applied to undisturbed, long (60-cm) or short (20-cm) soil columns, both planted with wheat. A smaller number of cells of the gacA mutant than of the wild type were detected in the percolated water and in different depths of the soil column. Single-strain inoculation gave similar results in all microcosms tested. We conclude that mutation in a single regulatory gene involved in antibiotic and exoenzyme synthesis can affect the survival of P. fluorescens more profoundly in unplanted soil than in the rhizosphere.

Quinoa (Chenopodium quinoa) reaction to herbicide residue in a Brazilian Savannah soil

The quinoa (Chenopodium quinoa Willd.) cultivation, one of the most promising in double cropping with soybeans or maize, depends on weed control. The objective of this work was to evaluate quinoa reaction to herbicide residue in a savannah soil. Six herbicide treatments, trifluralin, pendimethalin, clomazone, imazaquin, trifluralin + imazaquin and control, were applied, prior to summer cultivation of soybean, in a Dark-Red Latosol (typic Haplustox). Soybean cultivar BR 9 Savana was grown and soil samples were collected at 15, 38, 100, 145 and 206 days after treatment and stored at -5ºC. Bioassays were conducted in greenhouse, using quinoa, cultivar Q18. Imazaquin was the most harmful to quinoa seedlings, up to 206 days after application, followed by clomazone 15-38 days after application; trifluralin and pendimethalin had no residual effect. These results suggest that a broad-base screening should be conducted.

Effects of fire on soil nitrogen dynamics and microbial biomass in savannas of Central Brazil

The objective of this work was to study the effects of fire on net N mineralization and soil microbial biomass in burned and unburned cerrado stricto sensu sites. The study was carried out from April 1998 to April 2000. The pH values were significantly higher in the burned site while soil moisture content was significantly higher in the unburned site (P<0.05). The soil C/N ratio was 22/1 and the available NO3-N ranged between 1.5 and 2.8 mg kg-¹ dry weight. However, the NH4-N concentration ranged between 3 and 34 mg kg-1 dry weight in the burned site and between 3 and 22 mg kg-1 dry weight in the unburned site. The NH4-N increased after fire, but no significant changes were observed for NO3-N (P<0.05). The NO3-N accumulation occurred in short periods during the rainy season. The rates of net N mineralization increased during the rainy season while reductions in soil microbial biomass were observed at both sites. This suggested that the peak in microbial activities occurred with the first rain events, with an initial net immobilization followed by net mineralization. Both sites presented the same pattern for mineralization/immobilization, however, the amount of inorganic-N cycled annually in unburned site was 14.7 kg ha-1 per year while the burned site presented only 3.8 kg ha-¹ of inorganic-N, one year after the burning.

Decomposition of Arachis pintoi and Hyparrhenia rufa litters in monoculture and intercropped systems under lowland soil

Tropical grasslands under lowland soils are generally underutilized and the litter of forage legumes may be used to recover these degraded pastures. The objective of this work was to study the dynamics of litter decomposition of Arachis pintoi (pinto peanut), Hyparrhenia rufa (thatching grass) and a mixture of both species in a lowland soil. These treatments were analyzed in three areas: grass monoculture, legume monoculture and legume intercropped with the grass during the dry and wet seasons. Litter bags containing the legume, grass or a mixture of both species were incubated to estimate the decomposition rate and microorganism colonization. Decomposition constants (K) and litter half-lives (T1/2) were estimated by an exponential model whereas number of microorganisms in specific media were determined by plate dilution. The decomposition rate, release of nutrients and microorganisms number, especially bacteria, increased when pinto peanut was added to thatching grass, influenced by favorable lignin/N and C/N ratios in legume litter. When pinto peanut litter was incubated in the grass plots, 50% N and P was released within about 135 days in the dry season and in the wet season, the equivalent release occurred within 20 days. These results indicate that A. pintoi has a great potential for nutrient recycling via litter and can be used to recover degraded areas.

Influence of repeated applications of glyphosate on its persistence and soil bioactivity

Pesticide degradation studies are essential to evaluate its impact in the environment and on non-target organisms. The effect of repeated soil applications of the herbicide glyphosate on its dissipation and on soil microorganisms was studied by radiometric and microbial techniques. Results indicated fast dissipation of the [14C]-glyphosate or [14C]metabolites extractable residues (half-life of 0.92±0.29 month), but increasing half-lives of total mineralization ranging from 2.2 to 3.4 months as the number of applications increased from 1 to 4. No significant correlation was found between 14CO2 production and dehydrogenase activity.

Data-driven topo-climatic mapping with machine learning methods

Automatic environmental monitoring networks enforced by wireless communication technologies provide large and ever increasing volumes of data nowadays. The use of this information in natural hazard research is an important issue. Particularly useful for risk assessment and decision making are the spatial maps of hazard-related parameters produced from point observations and available auxiliary information. The purpose of this article is to present and explore the appropriate tools to process large amounts of available data and produce predictions at fine spatial scales. These are the algorithms of machine learning, which are aimed at non-parametric robust modelling of non-linear dependencies from empirical data. The computational efficiency of the data-driven methods allows producing the prediction maps in real time which makes them superior to physical models for the operational use in risk assessment and mitigation. Particularly, this situation encounters in spatial prediction of climatic variables (topo-climatic mapping). In complex topographies of the mountainous regions, the meteorological processes are highly influenced by the relief. The article shows how these relations, possibly regionalized and non-linear, can be modelled from data using the information from digital elevation models. The particular illustration of the developed methodology concerns the mapping of temperatures (including the situations of Föhn and temperature inversion) given the measurements taken from the Swiss meteorological monitoring network. The range of the methods used in the study includes data-driven feature selection, support vector algorithms and artificial neural networks.