Recombination in West Nile Virus: minimal contribution to genomic diversity

Recombination is known to play a role in the ability of various viruses to acquire sequence diversity. We consequently examined all available West Nile virus (WNV) whole genome sequences both phylogenetically and with a variety of computational recombination detection algorithms. We found that the number of distinct lineages present on a phylogenetic tree reconstruction to be identical to the 6 previously reported. Statistically-significant evidence for recombination was only observed in one whole genome sequence. This recombination event was within the NS5 polymerase coding region. All three viruses contributing to the recombination event were originally isolated in Africa at various times, with the major parent (SPU116_89_B), minor parent (KN3829), and recombinant sequence (AnMg798) belonging to WNV taxonomic lineages 2, 1a, and 2 respectively. This one isolated recombinant genome was out of a total of 154 sequences analyzed. It therefore does not seem likely that recombination contributes in any significant manner to the overall sequence variation within the WNV genome

Framework for strategic wind farm site prioritisation based on modelled wolf reproduction habitat in Croatia

In order to meet carbon reduction targets, many nations are greatly expanding their wind power capacity. However, wind farm infrastructure potentially harms wildlife, and we must therefore find ways to balance clean energy demands with the need to protect wildlife. Wide-ranging carnivores live at low density and are particularly susceptible to disturbance from infrastructure development, so are a particular concern in this respect. We focused on Croatia, which holds an important population of wolves and is currently planning to construct many new wind farms. Specifically, we sought to identify an optimal subset of planned wind farms that would meet energy targets while minimising potential impact on wolves. A suitability model for wolf breeding habitat was carried out using Maxent, based on six environmental variables and 31 reproduction site locations collected between 1997 and 2015. Wind farms were prioritised using Marxan to find the optimal trade-off between energy capacity and overlap with critical wolf reproduction habitat. The habitat suitability model predictions were consistent with the current knowledge: probability of wolf breeding site presence increased with distance to settlements, distance to farmland and distance to roads and decreased with distance to forest. Spatial optimisation showed that it would be possible to meet current energy targets with only 31% of currently proposed wind farms, selected in a way that reduces the potential ecological cost (overall predicted wolf breeding site presence within wind farm sites) by 91%. This is a highly efficient outcome, demonstrating the value of this approach for prioritising infrastructure development based on its potential impact on wide-ranging wildlife species