Genotypic and phenotypic diversity in populations of plant-probiotic <Emphasis Type="Italic">Pseudomonas</Emphasis> spp. colonizing roots

Several soil microorganisms colonizing roots are known to naturally promote the health of plants by controlling a range of plant pathogens, including bacteria, fungi, and nematodes. The use of theses antagonistic microorganisms, recently named plant-probiotics, to control plant-pathogenic fungi is receiving increasing attention, as they may represent a sustainable alternative to chemical pesticides. Many years of research on plant-probiotic microorganisms (PPM) have indicated that fluorescent pseudomonads producing antimicrobial compounds are largely involved in the suppression of the most widespread soilborne pathogens. Phenotype and genotype analysis of plant-probiotic fluorescent pseudomonads (PFP) have shown considerable genetic variation among these types of strains. Such variability plays an important role in the rhizosphere competence and the biocontrol ability of PFP strains. Understanding the mechanisms by which genotypic and phenotypic diversity occurs in natural populations of PFP could be exploited to choose those agricultural practices which best exploit the indigenous PFP populations, or to isolate new plant-probiotic strains for using them as inoculants. A number of different methods have been used to study diversity within PFP populations. Because different resolutions of the existing microbial diversity can be revealed depending on the approach used, this review first describes the most important methods used for the assessment of fluorescent Pseudomonas diversity. Then, we focus on recent data relating how differences in genotypic and phenotypic diversity within PFP communities can be attributed to geographic location, climate, soil type, soil management regime, and interactions with other soil microorganisms and host plants. It becomes evident that plant-related parameters exert the strongest influence on the genotypic and phenotypic variations in PFP populations.     

Relationship between protean career orientation and work–life balance: A resource perspective

Despite the commonly held belief that a protean career orientation (PCO) enables employees to achieve more balance in their lives, little is known about the relationship between PCO and work–life balance. Using two waves of data collection separated by 2.5 years, this study examined the relationship between PCO and work–life balance among a sample of 367 college‐educated employees in the United States. Analysis was conducted to empirically distinguish PCO from conceptually related constructs, and structural equation modeling was used to examine the process that explains the linkage between PCO and balance. We found that PCO was positively related to work–life balance. We also found support for the role of several resources (social capital, psychological capital, and perceived employability) that explain the relationship between PCO and balance. In particular, PCO was associated with extensive career planning activities that were related to the accumulation of three forms of career capital—human capital, social capital, and psychological capital. In turn, social capital and psychological capital were associated with high employability, which was related to greater work–life balance for individuals who take a whole‐life perspective on their careers. We discuss the theoretical and practical implications of the findings and provide suggestions for future research. Copyright © 2015 John Wiley & Sons, Ltd.     

Stability,resonance and role of turbulent stresses in 1D alluvial flows

Environmental Fluid Mechanics - Linear stability analysis is used to investigate the behavior of small perturbations of a uniform flow in a straight channel with an erodible bed composed by a...     

Study of a surface coating present on a Renaissance Piety from the Museum of Ancient Art (Castello Sforzesco,Milan)

Environmental Science and Pollution Research - The surface coating present on a marble Piety dating to the Renaissance period and stored at the Castello Sforzesco-Museum of Ancient Art (Milan,...     

Sustainable mechanochemical synthesis of β-cyclodextrin polymers by twin screw extrusion

Environmental Science and Pollution Research - Cyclodextrin nanosponges (CD-NS) are cross-linked cyclodextrin polymers characterized by a nanostructured three-dimensional network. CD-NSs in the...     

Investigation of biomass waste biochar production to act as matrix for urea

Journal of Material Cycles and Waste Management - In this work, the synthesis of biochar from several biomass wastes to act as matrix for urea was investigated. The objective was to select the most...     

Design-based estimation in environmental surveys with positional errors

The recent increased availability of information about the micro-geographic positions of population units in environmental surveys has led to important developments in spatial sampling methodologies and, as a result, has improved the estimation accuracy. In real data, however, information about the location of units is often affected by inaccuracy about their exact spatial positions, and these non-sampling errors can affect the estimation procedure. This paper aims to investigate the effects of positional errors on total estimation through a Monte-Carlo simulation study based on real populations of trees. Starting from perfect positioning, we examine two typical types of coarsening that frequently impact two different species of trees. The simulation results show that the exploitation of spatial information to estimate population totals continues to be relevant in the context of environmental surveys, even in the presence of inaccuracies.     

Cholesterol,beta-sitosterol,ergosterol, and coprostanol in agricultural soils

In this work we analyzed the sterol content of agricultural soils. Three eukaryotic sterols, cholesterol, beta-sitosterol, and ergosterol were chosen as representative of the animal, plant, and fungal kingdoms, while coprostanol was validated as a marker of human fecal matter contamination. Three soils subjected to different treatments (sewage sludge application, irrigation by saline waters, and contamination by industrial and municipal wastes) were sampled and their sterol content was measured and compared with adjacent untreated soils. The effects of time, location, and treatment were evaluated by means of a number of statistical techniques. Beta-sitosterol concentration varied from 0.9 to 30 mg kg(-1). Lesser values were measured in Cremona (2.1 mg kg(-1)) than in Bari (4.0 mg kg(-1)) and Naples (10.9 mg kg(-1)) soils. No significant effects were detected for cholesterol and ergosterol. Coprostanol was present after sewage sludge disposal and contamination by industrial and municipal wastes, while it was absent in the soil treated with saline water and in the adjacent untreated soil. Coprostanol concentration did not vary much within site and time of sampling, with a mean value of 0.2 mg kg(-1). We confirmed coprostanol as a useful persistent marker of human fecal matter contamination. Multivariate analysis highlighted a clear distinction between the eukaryotic sterols and coprostanol. In addition, a different behavior between ergosterol and cholesterol on one side and beta-sitosterol on the other was detected. This preliminary work suggests that sterols deserve a deeper study of their use as indicators in agricultural soils.     

Inventory routing for dynamic waste collection

We consider the problem of collecting waste from sensor equipped underground containers. These sensors enable the use of a dynamic collection policy. The problem, which is known as a reverse inventory routing problem, involves decisions regarding routing and container selection. In more dense networks, the latter becomes more important. To cope with uncertainty in deposit volumes and with fluctuations due to daily and seasonal effects, we need an anticipatory policy that balances the workload over time. We propose a relatively simple heuristic consisting of several tunable parameters depending on the day of the week. We tune the parameters of this policy using optimal learning techniques combined with simulation. We illustrate our approach using a real life problem instance of a waste collection company, located in The Netherlands, and perform experiments on several other instances. For our case study, we show that costs savings up to 40% are possible by optimizing the parameters.     

The Environmental “Risky” Region: Identifying Land Degradation Processes Through Integration of Socio-Economic and Ecological Indicators in a Multivariate Regionalization Model

The economic policy needs to pay increasingly more attention to the environmental issues, which requires the development of methodologies able to incorporate environmental, as well as macroeconomic, goals in the design of public policies. Starting from this observation, this article proposes a methodology based upon a Simonian satisficing logic made operational with the help of goal programming (GP) models, to address the joint design of macroeconomic and environmental policies. The methodology is applied to the Spanish economy, where a joint policy is elicited, taking into consideration macroeconomic goals (economic growth, inflation, unemployment, public deficit) and environmental goals (CO₂, NO _x and SO _x emissions) within the context of a computable general equilibrium model. The results show how the government can “fine-tune” its policy according to different criteria using GP models. The resulting policies aggregate the environmental and the economic goals in different ways: maximum aggregate performance, maximum balance and a lexicographic hierarchy of the goals.