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Four microorganisms, Pseudomonas sp. (ER2), Aspergillus niger (ER6), Cladosporium herbarum (ER4) and Penicilluim sp. (ER3), were isolated from cucumber leaves previously treated with metalaxyl using enrichment technique. These isolates were evaluated for detoxification of metalaxyl at the recommended dose level in aquatic system. The effect of pH and temperature on the growth ability of the tested isolates was also investigated by measuring the intracellular protein and mycelia dry weight for bacterial and fungal isolates, respectively. Moreover, the toxicity of metalaxyl after 28 d of treatment with the tested isolates was evaluated to confirm the complete removal of any toxic materials (metalaxyl and its metabolites). The results showed that the optimum degree pH for the growth of metalaxyl degrading isolates (bacterial and fungal isolates) was 7. The temperature 30℃ appeared to be the optimum degree for the growth of either fungal or bacterial isolates. The results showed that Pseudomonas sp. (ER2) was the most effective isolate in metalaxyl degradation followed by Aspergillus niger (ER6), Cladosporium herbarum (ER4) and Penicilluim sp. (ER3), respectively. There is no toxicity of metalaxyl detected in the supematant after 28 d of treatment with Pseudomonas sp. (ER2). The results suggest that bioremediation by Pseudomonas sp. (ER2) isolate was considered to be effective method for detoxification of metalaxyl in aqueous media. 相似文献
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Steven R. Beissinger Jason G. Bragg David J. Coates J. Gerard B. Oostermeijer Paul Sunnucks Nathan H. Schumaker Meredith V. Trotter Andrew G. Young 《Conservation biology》2015,29(3):755-764
We examined how ecological and evolutionary (eco‐evo) processes in population dynamics could be better integrated into population viability analysis (PVA). Complementary advances in computation and population genomics can be combined into an eco‐evo PVA to offer powerful new approaches to understand the influence of evolutionary processes on population persistence. We developed the mechanistic basis of an eco‐evo PVA using individual‐based models with individual‐level genotype tracking and dynamic genotype–phenotype mapping to model emergent population‐level effects, such as local adaptation and genetic rescue. We then outline how genomics can allow or improve parameter estimation for PVA models by providing genotypic information at large numbers of loci for neutral and functional genome regions. As climate change and other threatening processes increase in rate and scale, eco‐evo PVAs will become essential research tools to evaluate the effects of adaptive potential, evolutionary rescue, and locally adapted traits on persistence. 相似文献
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