Knock-on community impacts of a novel vector: spillover of emerging DWV-B from Varroa-infested honeybees to wild bumblebees.

This is the final version. Available from the publisher via the DOI in this record.The Sanger sequences that support the findings of this study have been deposited in GenBank with virus accession codes MG264907‐MG265503 and Nosema accession codes MK942707‐MK942712; SMRT reads have been archived in NCBI's Sequence Read Archive with BioProject accession number PRJNA542789. Prevalence and qPCR data that support the findings will be available from the Dryad Digital Repository: https://doi.org/10.5061/dryad.70jt240.Novel transmission routes can directly impact the evolutionary ecology of infectious diseases, with potentially dramatic effect on host populations and knock-on effects on the wider host community. The invasion of Varroa destructor, an ectoparasitic viral vector in Western honeybees, provides a unique opportunity to examine how a novel vector affects disease epidemiology in a host community. This specialist honeybee mite vectors deformed wing virus (DWV), an important re-emerging honeybee pathogen that also infects wild bumblebees. Comparing island honeybee and wild bumblebee populations with and without V. destructor, we show that V. destructor drives DWV prevalence and titre in honeybees and sympatric bumblebees. Viral genotypes are shared across hosts, with the potentially more virulent DWV-B overtaking DWV-A in prevalence in a current epidemic. This demonstrates disease emergence across a host community driven by the acquisition of a specialist novel transmission route in one host, with dramatic community level knock-on effects

Distribution modelling and statistical phylogeography: an integrative framework for generating and testing alternative biogeographical hypotheses

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/73644/1/j.1365-2699.2007.01814.x.pd

Choosing summary statistics by least angle regression for approximate Bayesian computation

YesBayesian statistical inference relies on the posterior distribution. Depending on the model, the posterior can be more or less difficult to derive. In recent years, there has been a lot of interest in complex settings where the likelihood is analytically intractable. In such situations, approximate Bayesian computation (ABC) provides an attractive way of carrying out Bayesian inference. For obtaining reliable posterior estimates however, it is important to keep the approximation errors small in ABC. The choice of an appropriate set of summary statistics plays a crucial role in this effort. Here, we report the development of a new algorithm that is based on least angle regression for choosing summary statistics. In two population genetic examples, the performance of the new algorithm is better than a previously proposed approach that uses partial least squares.Higher Education Commission (HEC), College Deanship of Scientific Research, King Saud University, Riyadh Saudi Arabia - research group project RGP-VPP-280

Forward-in-Time, Spatially Explicit Modeling Software to Simulate Genetic Lineages Under Selection

SELECTOR is a software package for studying the evolution of multiallelic genes under balancing or positive selection while simulating complex evolutionary scenarios that integrate demographic growth and migration in a spatially explicit population framework. Parameters can be varied both in space and time to account for geographical, environmental, and cultural heterogeneity. SELECTOR can be used within an approximate Bayesian computation estimation framework. We first describe the principles of SELECTOR and validate the algorithms by comparing its outputs for simple models with theoretical expectations. Then, we show how it can be used to investigate genetic differentiation of loci under balancing selection in interconnected demes with spatially heterogeneous gene flow. We identify situations in which balancing selection reduces genetic differentiation between population groups compared with neutrality and explain conflicting outcomes observed for human leukocyte antigen loci. These results and three previously published applications demonstrate that SELECTOR is efficient and robust for building insight into human settlement history and evolution

Equations for the estimation of strong ground motions from shallow crustal earthquakes using data from Europe and the Middle East : vertical peak ground acceleration and spectral acceleration

This article presents equations for the estimation of vertical strong ground motions caused by shallow crustal earthquakes with magnitudes M w 5 and distance to the surface projection of the fault less than 100km. These equations were derived by weighted regression analysis, used to remove observed magnitude-dependent variance, on a set of 595 strong-motion records recorded in Europe and the Middle East. Coefficients are included to model the effect of local site effects and faulting mechanism on the observed ground motions. The equations include coefficients to model the observed magnitude-dependent decay rate. The main findings of this study are that: short-period ground motions from small and moderate magnitude earthquakes decay faster than the commonly assumed 1/r, the average effect of differing faulting mechanisms is similar to that observed for horizontal motions and is not large and corresponds to factors between 0.7 (normal and odd) and 1.4 (thrust) with respect to strike-slip motions and that the average long-period amplification caused by soft soil deposits is about 2.1 over those on rock sites