Rita Lopes

Abstract
"Masseiras" is an ancient Portuguese agriculture system, where soil was developed from sand dunes enriched with seaweeds over more than a century. Due to the importance for the local economy, this system evolved for greenhouse structures. In this study we compared the bacterial community composition and structure of "Masseiras" soil, aiming at assessing the potential impact of different agricultural practices. The bulk soil of two greenhouses (following or not the recommended agriculture good practices, FGP and NFGP, respectively) was compared based on their physicochemical properties and bacterial community. In both FGP and NFGP, Proteobacteria, Acidobacteria, Actinobacteria, Bacteroidetes, Firmicutes, and Gemmatimonadetes were in a proportion of 5:1:1:1:1:1. However, the bacterial community of soil FGP was richer and more diverse than that of soil NFGP. Members of the classes Bacilli and Gemm-1, with higher relative abundance in NFGP and FGP, respectively, were those contributing most for distinguishing the bacterial communities of both soils. The differences in the structure of the bacterial communities correlated (Mantel test) with some soil physicochemical properties, such as electrical conductivity and nitrate and Zn contents, which were significantly higher in soil NFGP than in soil FGP.

Abstract
The main purpose of this work was to assess the (i) short-term effect of the main nitrification and denitrification variables on the nitrogen's biological removal via nitrite from highstrength leachates, and (ii) the effect of the presence/absence of nitrites/nitrates in a downstream photo-oxidation process. The biological reaction rates were evaluated as a function of several parameters: (i) temperature, dissolved oxygen (DO) concentration and pH, on the nitrification; and (ii) pH, temperature and the addition of phosphate ions, on the denitrification. At the beginning of most nitrification assays, it was verified that the ammonia stripping occurred simultaneously to the nitrification, reaching up to 31% removal of total dissolved nitrogen. The maximum nitrification rate obtained was 37 +/- 2 mg NH4+-N/(h.g VSS) (25 degrees C, 1.02.0 mg O-2/L, pH not controlled), consuming 5.3 +/- 0.4 mg CaCO3/mg NH4+-N. The highest denitrification rate achieved was 27 +/- 1 mg NO2--N/(h.g VSS) (pH between 7.5 and 8.0, 30 degrees C, adding 30 mg PO43-/L), with a C/N consumption ratio of 1.6 +/- 0.1 mg CH3OH/mg. NO2--N and an overall alkalinity production of 3.2 +/- 0.1 mg CaCO3/mg NO2--N. The denitrification process showed to be sensitive to all studied parameters, while the nitrification reaction did not suffered significant change when DO content was changed. The two most abundant bacterial groups in the nitrification and denitrification processes, as indicated by the 454-pyrosequencing analysis of the 16S rRNA gene, were affiliated to Saprospiraceae/Nitrosomonadaceae and Hyphomicrobiaceae/Saprospiraceae, respectively. The abundance of Nitrosomonadaceae and Hyphomicrobiaceae (in particular, Hyphomicrobium) in the nitrification and denitrification process, respectively, is in agreement with the nitrifying and denitrifying activity of these bacterial members. The photo-Fenton reaction rate was assessed considering the presence of nitrites and nitrates and the absence of both in a leachate after biological oxidation and coagulation/sedimentation steps. The results showed that for a pre-treated leachate without nitrogen, the DOC degradation rate decreased 28%, while for a bio-treated leachate containing nitrites, the H2O2 consumption was 2.4 times higher.

Abstract
Previous studies demonstrated the capability of mixed culture DC1 to mineralize the thiocarbamate herbicide molinate through the activity of molinate hydrolase (MolA). Because liquid suspensions are not compatible with long-term storage and are not easy to handle when bioremediation strategies are envisaged, in this study spray drying was evaluated as a cost-effective method to store and transport these molinate biocatalysts. Microparticles of mixed culture DC1 (DC1) and of cell free crude extracts containing MolA (MA) were obtained without any carrier polymer, and with calcium alginate (CA) or modified chitosan (MCt) as immobilizing agents. All the DC1 microparticles showed high molinate degrading activity upon storage for 6 months, or after 9 additions of similar to 0.4 mM molinate over 1 month. The DC1-MCt microparticles were those with the highest survival rate and lowest heterogeneity. For MA microparticles, only MA-MCt degraded molinate. However, its V-max was only 1.4% of that of the fresh cell free extract (non spray dried). The feasibility of using the DC1-MCt and MA-MCt microparticles in bioaugmentation processes was assessed in river water microcosms, using mass (g):volume (L) ratios of 1:13 and 1:0.25, respectively. Both type of microparticles removed 65-75% of the initial 1.5 mg L-1 molinate, after 7 days of incubation. However, only DC1-MCt microparticles were able to degrade this environmental concentration of molinate without disturbing the native bacterial community. These results suggest that spray drying can be successfully used to produce DC1-MCt microparticles to remediate molinate polluted sites through a bioaugmentation strategy.

Abstract
Previously, two municipal solid waste commercial composts (MSW1 and MSW2) were characterized. Although sharing the same type of raw material, most of their physicochemical, stability and maturity properties differed. The present study aimed to characterize them at a microbiological level, and to infer on possible relationships between the composts properties and the structure of their bacterial communities. Both the 16S rRNA gene-based PCR-DGGE profiling and 454-pyrosequencing technology showed that the structure of the bacterial communities of these composts was distinct. The bacterial community of MSW1 was more diverse than that of MSW2. Multivariate analyses revealed that the high electrical conductivity, Cu content as well as the low phytotoxity of compost MSW1, when compared to MSW2, contributed most to shape its bacterial community structure. Indeed, high abundance of halophilic (Halomonadaceae and Brevibacteriaceae) and metal resistant organisms (Brevibacteriaceae and Bacillaceae) were found in MSW1. In addition, Pseudonocardiaceae, Streptomycetaceae, Bacillaceae, and Brevibacteriaceae may have contributed to the high humic-like acids content and low phytotoxicity of MSW1. In contrast, the high organic matter content and the high density of the cultivable fungi population were the parameters most correlated with the structure of the bacterial community of compost MSW2, dominated by Corynebacteriaceae and mainly Aerococcaceae, taxonomic groups not commonly found in composts.

Abstract
Microorganisms are vital in mediating the earth's biogeochemical cycles; yet, despite our rapidly increasing ability to explore complex environmental microbial communities, the relationship between microbial community structure and ecosystem processes remains poorly understood. Here, we address a fundamental and unanswered question in microbial ecology: 'When do we need to understand microbial community structure to accurately predict function?' We present a statistical analysis investigating the value of environmental data and microbial community structure independently and in combination for explaining rates of carbon and nitrogen cycling processes within 82 global datasets. Environmental variables were the strongest predictors of process rates but left 44% of variation unexplained on average, suggesting the potential for microbial data to increase model accuracy. Although only 29% of our datasets were significantly improved by adding information on microbial community structure, we observed improvement in models of processes mediated by narrow phylogenetic guilds via functional gene data, and conversely, improvement in models of facultative microbial processes via community diversity metrics. Our results also suggest that microbial diversity can strengthen predictions of respiration rates beyond microbial biomass parameters, as 53% of models were improved by incorporating both sets of predictors compared to 35% by microbial biomass alone. Our analysis represents the first comprehensive analysis of research examining links between microbial community structure and ecosystem function. Taken together, our results indicate that a greater understanding of microbial communities informed by ecological principles may enhance our ability to predict ecosystem process rates relative to assessments based on environmental variables and microbial physiology.