Ab initio DFT study of structural and mechanical properties of methane and carbon dioxide hydrates

The structural and mechanical properties of methane and carbon dioxide hydrates were investigated using density functional theory simulations. Well-established equations of state of solids and exchange-correlation functionals were used for fitting the unit lattice total energy as a function of volume, and the full second-order elastic constants of these two gas hydrates were determined by energy–strain analyses. The polycrystalline elastic properties were also calculated from the unit lattice results. The final results for methane hydrate agree well with available experimental data and with other theoretical results. The two gas hydrates were found to be highly elastically isotropic, but they differed significantly in shear properties. The presented results for carbon dioxide hydrates are the first complete set reported so far. The results are a significant contribution to the ab initio material characterisation of gas hydrates required for ongoing fundamental studies and technological applications.     

Atomistic simulations of liquid–liquid coexistence in confinement: comparison of thermodynamics and kinetics with bulk

We review a few simulation methods and results related to the structure and non-equilibrium dynamics in the coexistence region of immiscible symmetric binary fluids, in bulk as well as under confinement, with special emphasis on the latter. Monte Carlo methods to estimate interfacial tensions for flat and curved interfaces have been discussed. The latter, combined with a thermodynamic integration technique, provides contact angles for coexisting fluids attached to the wall. For such three-phase coexistence, results for the line tension are also presented. For the kinetics of phase separation, various mechanisms and corresponding theoretical expectations have been discussed. A comparative picture between the domain growth in bulk and confinement (including thin-film and semi-infinite geometry) has been presented from molecular dynamics simulations. Applications of finite-size scaling technique have been discussed in both equilibrium and non-equilibrium contexts.     

The trophic responses of two different rodent–vector–plague systems to climate change

Plague, the causative agent of three devastating pandemics in history, is currently a re-emerging disease, probably due to climate change and other anthropogenic changes. Without understanding the response of plague systems to anthropogenic or climate changes in their trophic web, it is unfeasible to effectively predict years with high risks of plague outbreak, hampering our ability for effective prevention and control of the disease. Here, by using surveillance data, we apply structural equation modelling to reveal the drivers of plague prevalence in two very different rodent systems: those of the solitary Daurian ground squirrel and the social Mongolian gerbil. We show that plague prevalence in the Daurian ground squirrel is not detectably related to its trophic web, and that therefore surveillance efforts should focus on detecting plague directly in this ecosystem. On the other hand, plague in the Mongolian gerbil is strongly embedded in a complex, yet understandable trophic web of climate, vegetation, and rodent and flea densities, making the ecosystem suitable for more sophisticated low-cost surveillance practices, such as remote sensing. As for the trophic webs of the two rodent species, we find that increased vegetation is positively associated with higher temperatures and precipitation for both ecosystems. We furthermore find a positive association between vegetation and ground squirrel density, yet a negative association between vegetation and gerbil density. Our study thus shows how past surveillance records can be used to design and improve existing plague prevention and control measures, by tailoring them to individual plague foci. Such measures are indeed highly needed under present conditions with prevailing climate change.     

Effects of density dependence,zooplankton and temperature on blue whiting Micromesistius poutassou growth

Blue whiting Micromesistius poutassou mean total length at age in the north‐east Atlantic Ocean was found to vary by around ±6% during the period 2004–2011 and mean mass at age by ±22% during the years 1981–2013. Linear modelling provided strong evidence that these phenotypic growth variations can be explained by trophic conditions, mainly negative density dependence and also food availability, and a negative long‐term temperature effect on asymptotic size.     

Eco‐evolutionary experience in novel species interactions

A better understanding of how ecological novelty influences interactions in new combinations of species is key for predicting interaction outcomes, and can help focus conservation and management efforts on preventing the introduction of novel organisms or species (including invasive species, GMOs, synthetic organisms, resurrected species and emerging pathogens) that seem particularly ‘risky’ for resident species. Here, we consider the implications of different degrees of eco‐evolutionary experience of interacting resident and non‐resident species, define four qualitative risk categories for estimating the probability of successful establishment and impact of novel species and discuss how the effects of novelty change over time. Focusing then on novel predator–prey interactions, we argue that novelty entails density‐dependent advantages for non‐resident species, with their largest effects often being at low prey densities. This is illustrated by a comparison of predator functional responses and prey predation risk curves between novel species and ecologically similar resident species, and raises important issues for the conservation of endangered resident prey species.     

Filter materials for phosphorus removal from wastewater in treatment wetlands—A review

This paper aims to collect and analyse existing information on different filter media used for phosphorus (P) removal from wastewater in constructed wetlands. The most commonly used materials are categorized as natural materials (considered in 39 papers), industrial byproducts (25 papers) and man-made products (10 papers). A majority of studies on sorbents have been carried out in lab-scale systems as batch experiments, and only very few studies have highlighted results on full-scale systems. Among the great variety of filter media studied, most of materials had a pH level >7 and high Ca (CaO) content. The highest P-removal capacities were reported for various industrial byproducts (up to 420 g P kg⁻¹ for some furnace slags), followed by natural materials (maximum 40 g P kg⁻¹ for heated opoka) and man-made filter media (maximum 12 g P kg⁻¹ for Filtralite). We found a significant positive Spearman Rank Order Correlation between the P retention and CaO and Ca content of filter materials (R² = 0.51 and 0.43, respectively), whereas the relation of P retention to pH level was weak (R² = 0.22) but significant. There is probably an optimal level of hydraulic loading rate at which the P removal is the highest. Additional important factors determining the applicability of filter materials in treatment wetlands such as saturation time, availability at a local level, content of heavy metals, and the recyclability of saturated filter media as fertilizer should be taken into consideration.     

Prediction model of DnBP degradation based on BP neural network in AAO system

A laboratory-scale anaerobic-anoxic-oxic (AAO) system was established to investigate the fate of DnBP. A removal kinetic model including sorption and biodegradation was formulated, and kinetic parameters were evaluated with batch experiments under anaerobic, anoxic, oxic conditions. However, it is highly complex and is difficult to confirm the kinetic parameters using conventional mathematical modeling. To correlate the experimental data with available models or some modified empirical equations, an artificial neural network model based on multilayered partial recurrent back propagation (BP) algorithm was applied for the biodegradation of DnBP from the water quality characteristic parameters. Compared to the kinetic model, the performance of the network for modeling DnBP is found to be more impressive. The results showed that the biggest relative error of BP network prediction model was 9.95%, while the kinetic model was 14.52%, which illustrates BP model predicting effluent DnBP more accurately than kinetic model forecasting.     

Competition limits adaptation and productivity in a photosynthetic alga at elevated CO2

When competitive exclusion between lineages and genetic adaptation within lineages occur on the same timescale, the two processes have the potential to interact. I use experimental microbial evolution where strains of a photosynthetic microbe that differ in their physiological response to CO₂ enrichment are grown either alone or in communities for hundreds of generations under CO₂ enrichment. After about 300 generations of growth, strains that experienced competition while adapting to environmental change are both less productive and less fit than corresponding strains that adapted to that same environmental change in the absence of competitors. In addition, I find that excluding competitors not only limits that strain''s adaptive response to abiotic change, but also decreases community productivity; I quantify this effect using the Price equation. Finally, these data allow me to empirically test the common hypothesis that phytoplankton that are most able to take advantage of carbon enrichment in single-strain populations over the short term will increase in frequency within multi-strain communities over longer timescales.