Comparison of Aspergillus species-complexes detected in different environmental settings

Purpose: Samples from different environmental sources were screened for the presence of Aspergillus, and the distribution of the different species-complexes was determined in order to understand differences among that distribution in the several environmental sources and which of these species complexes are present in specific environmental settings. Methods: Four distinct environments (beaches, poultries, swineries and hospital) were studied and analyzed for which Aspergillus complexes were present in each setting. After plate incubation and colony isolation, morphological identification was done using macro- and microscopic characteristics. The universal fungal primers ITS1 and ITS4 were used to amplify DNA from all Aspergillus isolates, which was sequenced for identification to species complex level. SPSS v15.0 for Windows was used to perform the statistical analysis. Results: Thirty-nine isolates of Aspergillus were recovered from both the sand beach and poultries, 31 isolates from swineries, and 80 isolates from hospital environments, for a total 189 isolates. Eleven species complexes were found total. Isolates belonging to the Aspergillus Versicolores species-complex were the most frequently found (23.8%), followed by Flavi (18.0%), Fumigati (15.3%) and Nigri (13.2%) complexes. A significant association was found between the different environmental sources and the distribution of the several species-complexes (p<0.001); the hospital environment had a greater variability of species-complexes than other environmental locations (10 in hospital environment, against nine in swine, eight in poultries and seven in sand beach). Isolates belonging to Nidulantes complex were detected only in the hospital environment, whereas the other complexes were identified in more than one setting. Conclusion: Because different Aspergillus complexes have different susceptibilities to antifungal drugs, and different abilities in producing mycotoxins, knowledge of the species-complex epidemiology for each setting may allow preventive or corrective measures to be taken toward decreasing professional workers or patient exposure to those agents.

Controling delayed transitions with applications to prevent single species extinctions

A new method is proposed to control delayed transitions towards extinction in single population theoretical models with discrete time undergoing saddle-node bifurcations. The control method takes advantage of the delaying properties of the saddle remnant arising after the bifurcation, and allows to sustain populations indefinitely. Our method, which is shown to work for deterministic and stochastic systems, could generally be applied to avoid transitions tied to one-dimensional maps after saddle-node bifurcations.

Supply chain optimization of residual forestry biomass for bioenergy production: the case study of Portugal

Within a large set of renewable energies being explored to tackle energy sourcing problems, bioenergy can represent an attractive solution if effectively managed. The supply chain design supported by mathematical programming can be used as a decision support tool to the successful bioenergy production systems establishment. This strategic decision problem is addressed in this paper where we intent to study the design of the residual forestry biomass to bioelectricity production in the Portuguese context. In order to contribute to attain better solutions a mixed integer linear programming (MILP) model is developed and applied in order to optimize the design and planning of the bioenergy supply chain. While minimizing the total supply chain cost the production energy facilities capacity and location are defined. The model also includes the optimal selection of biomass amounts and sources, the transportation modes selection, and links that must be established for biomass transportation and products delivers to markets. Results illustrate the positive contribution of the mathematical programming approach to achieve viable economic solutions. Sensitivity analysis on the most uncertain parameters was performed: biomass availability, transportation costs, fixed operating costs and investment costs. (C) 2015 Elsevier Ltd. All rights reserved.