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Abstract: Solubility of proline–leucine dipeptide, in water and in aqueous sodium chloride solutions, was measured at T =(288.15, 298.15, 308.15 and 313.15)K as a function of electrolyte concentration m =(0.1, 0.25, 0.5, 0.75 and 1)mol·kg−1 of water. Solubility data has been evaluated from density measurements using a vibrating tube densimeter. It has been observed that sodium chloride renders the dipeptide proline–leucine more soluble in water. Salting-in coefficients and standard free energies of transfer of proline–leucine, from water to aqueous sodium chloride solutions, have been calculated from the solubility data. Standard enthalpies and entropies of transfer have also been estimated and interpreted in terms of electrostatic and hydrophobic perturbed domains in the hydration shells of the dipeptide and of the cation and anion of the salt, as a function of temperature and salt concentration. [Copyright &y& Elsevier]

One of the current challenges in evolutionary ecology is understanding the long-term persistence of contemporary-evolving predator-prey interactions across space and time. To address this, we developed an extension of a multi-locus, multi-trait eco-evolutionary individual-based model that incorporates several interacting species in explicit landscapes. We simulated eco-evolutionary dynamics of multiple species food webs with different degrees of connectance across soil-moisture islands. A broad set of parameter combinations led to the local extinction of species, but some species persisted, and this was associated with (1) high connectance and omnivory and (2) ongoing evolution, due to multi-trait genetic variability of the embedded species. Furthermore, persistence was highest at intermediate island distances, likely because of a balance between predation-induced extinction (strongest at short island distances) and the coupling of island diversity by top predators, which by travelling among islands exert global top-down control of biodiversity. In the simulations with high genetic variation, we also found widespread trait evolutionary changes indicative of eco-evolutionary dynamics. We discuss how the ever-increasing computing power and high-resolution data availability will soon allow researchers to start bridging the in vivo-in silico gap. [ABSTRACT FROM AUTHOR]