Different environmental gradients associated to the spatiotemporal and genetic pattern of the H5N8 highly pathogenic avian influenza outbreaks in poultry in Italy

Comprehensive understanding of the patterns and drivers of avian influenza outbreaks is pivotal to inform surveillance systems and heighten nations’ ability to quickly detect and respond to the emergence of novel viruses. Starting in early 2017, the Italian poultry sector has been involved in the massive H5N8 highly pathogenic avian influenza epidemic that spread in the majority of the European countries in 2016/2017. Eighty‐three outbreaks were recorded in north‐eastern Italy, where a densely populated poultry area stretches along the Lombardy, Emilia‐Romagna and Veneto regions. The confirmed cases, affecting both the rural and industrial sectors, depicted two distinct epidemic waves. We adopted a combination of multivariate statistics techniques and multi‐model regression selection and inference, to investigate how environmental factors relate to the pattern of outbreaks diversity with respect to their spatiotemporal and genetic diversity. Results showed that a combination of eco‐climatic and host density predictors were associated with the outbreaks pattern, and variation along gradients was noticeable among genetically and geographically distinct groups of avian influenza cases. These regional contrasts may be indicative of a different mechanism driving the introduction and spreading routes of the influenza virus in the domestic poultry population. This methodological approach may be extended to different spatiotemporal scale to foster site‐specific, ecologically informed risk mitigating strategies

Genetic Structure of Bluefin Tuna in the Mediterranean Sea Correlates with Environmental Variables

Abstract Background Atlantic Bluefin Tuna (ABFT) shows complex demography and ecological variation in the Mediterranean Sea. Genetic surveys have detected significant, although weak, signals of population structuring; catch series analyses and tagging programs identified complex ABFT spatial dynamics and migration patterns. Here, we tested the hypothesis that the genetic structure of the ABFT in the Mediterranean is correlated with mean surface temperature and salinity. Methodology We used six samples collected from Western and Central Mediterranean integrated with a new sample collected from the recently identified easternmost reproductive area of Levantine Sea. To assess population structure in the Mediterranean we used a multidisciplinary framework combining classical population genetics, spatial and Bayesian clustering methods and a multivariate approach based on factor analysis. Conclusions FST analysis and Bayesian clustering methods detected several subpopulations in the Mediterranean, a result also supported by multivariate analyses. In addition, we identified significant correlations of genetic diversity with mean salinity and surface temperature values revealing that ABFT is genetically structured along two environmental gradients. These results suggest that a preference for some spawning habitat conditions could contribute to shape ABFT genetic structuring in the Mediterranean. However, further studies should be performed to assess to what extent ABFT spawning behaviour in the Mediterranean Sea can be affected by environmental variation.(undefined

Results of the Mantel and partial-Mantel tests.

<p>Results of the Mantel and partial-Mantel tests.</p

Canonical/constrained Correspondence Analysis ordination plot of ABFT samples.

<p>The environmental variables are represented by arrows: Mean-S = salinity; Mean-t = temperature.</p

GENELAND results for K = 3 using the spatial model with correlated allele frequencies.

<p>A) Map of estimated posterior probability of population membership (by posterior mode); B-D) plots representing the assignment of pixels to the southern (B), northern (C) and central cluster (D). The highest membership values are in light yellow and the contour lines indicate the spatial position of genetic discontinuities between populations.</p

Correspondence Analysis plot of ABFT samples performed on population allele counts.

<p>The eigenvalues barplots are drawn in the bottom right corner and black bars correspond to the two axes used in the biplot (on the left CA axis 1 vs 2, on the right CA axis 1 vs 3). Grey bars represent the axes considered in the analysis but not used to draw the graph.</p

Map of surface salinity and temperature and sampling locations of <i>T. thynnus</i> in the Mediterranean.

<p>Temperature is described in colour gradient (from 14.5°C to 23.5°C) while salinity through contour map (each isoline shows a change of 1 psu). Sampling data are described in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0080105#pone.0080105.s006" target="_blank">Text S1</a> and Tab S1(1 =  SAR, 2 =  ADR, 3 =  LIG, 4 =  ALG, 5 =  ALB, 6 =  STY, 7 =  CYP).</p

STRUCTURE analysis.

<p>A) Plot of the Log posterior probability vs K (blue line) and Evanno’s method (black line). B) Bar plot of the posterior probability of the coefficient of membership. Each vertical line represents an individual and colours represent the inferred ancestry from K ancestral populations. Results for K = 2–4 are shown.</p