In the context of climatic change, more severe and long-lasting droughts will modify the fitness of plants, with potentially worse consequences on the relict trees. We have investigated the leaf phenotypic (anatomical, physiological and biochemical) plasticity in well-watered, drought-stressed and re-watered plants of two populations of Platanus orientalis, an endangered species in the west of the Mediterranean area. The two populations originated in contrasting climate (drier and warmer, Italy (IT) population; more humid and colder, Bulgaria (BG) population). The IT control plants had thicker leaves, enabling them to maintain higher leaf water content in the dry environment, and more spongy parenchyma, which could improve water conductivity of these plants and may result in easier CO₂ diffusion than in BG plants. Control BG plants were also characterized by higher photorespiration and leaf antioxidants compared to IT plants. BG plants responded to drought with greater leaf thickness shrinkage. Drought also caused substantial reduction in photosynthetic parameters of both IT and BG plants. After re-watering, photosynthesis did not fully recover in either of the two populations. However, IT leaves became thicker, while photorespiration in BG plants further increased, perhaps indicating sustained activation of defensive mechanisms. Overall, our hypothesis, that plants with a fragmented habitat (i.e., the IT population) lose phenotypic plasticity but acquire traits allowing better resistance to the climate where they became adapted, remains confirmed.

A modified genetic algorithm is proposed for a parameter identification of an E. coli fed-batch fermentation model. In the simple genetic algorithm the best chromosome does not always keep on improving in each generation. Obtained good solutions could be destroyed by either crossover or mutation or both operations. The aim of the modified genetic algorithm is to prevent this disadvantage. In view of the fact that there is no general theory about tuning the genetic algorithm parameters, some adjustments of genetic parameters, according to the regarded problem, are done to improve the conventional genetic algorithm. The simulation results illustrate that the use of proposed modified genetic algorithm for a parameter identification of fermentation processes is highly efficient and effective. The functions and parameter adjustments, proposed here, enhance the algorithm performance. Still more, the implementation of the modified genetic algorithm leads to noticeable decreasing of the solution time.