Bioenergy consumption and biogas potential in Cambodian households

&nbsp; Residential bioenergy consumption and bioenergy resources based on by-products of residential agricultural production and animal husbandry have been analyzed statistically, based on a nationwide residential livelihood and energy survey conducted in Cambodia in 2009. Furthermore, the potential for biomethanation, residential biogas consumption and small-scale power generation for non-electrified rural areas has been assessed. Household potential of biogas substrates in Cambodia, based on nationally representative data has not been presented earlier. This paper proposes mixtures of substrates for biogas production for various livelihood zones of Cambodia. The occurrence of biomass suitable for biomethanation is most favorable in unelectrified rural areas, except for fishing villages. The theoretical daily biogas potential from animal dung and rice husk appears to be promising for households in unelectrified rural villages, both for household digesters and units designed for small-scale electricity generation. Theoretical CH4 content of biogas was 63.9% and specific biogas yield 0.41 Nm3/kg for households in unelectrified villages. Based on the survey, the energy content of biogas potential is 25.5 PJ per year. This study shows that biogas has nationally significant technical potential in Cambodia. </p

Evaluating genetic drift in time-series evolutionary analysis

The Wright-Fisher model is the most popular population model for describing the behaviour of evolutionary systems with a finite population size. Approximations have commonly been used but the model itself has rarely been tested against time-resolved genomic data. Here, we evaluate the extent to which it can be inferred as the correct model under a likelihood framework. Given genome-wide data from an evolutionary experiment, we validate the Wright-Fisher drift model as the better option for describing evolutionary trajectories in a finite population. This was found by evaluating its performance against a Gaussian model of allele frequency propagation. However, we note a range of circumstances under which standard Wright-Fisher drift cannot be correctly identified. (C) 2017 The Author(s). Published by Elsevier Ltd.Peer reviewe