Age-dependent patterns of spatial autocorrelation in fish populations.

The degree of spatial autocorrelation in population fluctuations increases with dispersal and geographical covariation in the environment, and decreases with strength of density dependence. Because the effects of these processes can vary throughout an individual's lifespan, we studied how spatial autocorrelation in abundance changed with age in three marine fish species in the Barents Sea. We found large interspecific differences in age-dependent patterns of spatial autocorrelation in density. Spatial autocorrelation increased with age in cod, the reverse trend was found in beaked redfish, while it remained constant among age classes in haddock. We also accounted for the average effect of local cohort dynamics, i.e. the expected local density of an age class given last year's local density of the cohort, with the goal of disentangling spatial autocorrelation patterns acting on an age class from those formed during younger age classes and being carried over. We found that the spatial autocorrelation pattern of older age classes became increasingly determined by the distribution of the cohort during the previous year. Lastly, we found high degrees of autocorrelation over long distances for the three species, suggesting the presence of far-reaching autocorrelating processes on these populations. We discuss how differences in the species' life history strategies could cause the observed differences in age-specific variation in spatial autocorrelation. As spatial autocorrelation can differ among age classes, our study indicates that fluctuations in age structure can influence the spatio-temporal variation in abundance of marine fish populations.

The effectiveness of mass vaccination on Marek's disease virus (MDV) outbreaks and detection within a broiler barn: a modeling study.

Marek's disease virus (MDV), a poultry pathogen, has been increasing in virulence since the mid twentieth century. Since multiple vaccines have been developed and widely implemented, losses due to MDV have decreased. However, vaccine failure has occurred in the past and vaccine breakthroughs remain a problem. Failure of disease control with current vaccines would have significant economic and welfare consequences. Nevertheless, the epidemiology of the disease during a farm outbreak is not well understood. Here we present a mathematical model to predict the effectiveness of vaccines to reduce the outbreak probability and disease burden within a barn. We find that the chance of an outbreak within a barn increases with the virulence of an MDV strain, and is significantly reduced when the flock is vaccinated, especially when there the contaminant strain is of low virulence. With low quantities of contaminated dust, there is nearly a 100% effectiveness of vaccines to reduce MDV outbreaks. However, the vaccine effectiveness drops to zero with an increased amount of contamination with a middle virulence MDV strain. We predict that the larger the barn, and the more virulent the MDV strain is, the more virus is produced by the time the flock is slaughtered. With the low-to-moderate virulence of the strains studied here, the number of deaths due to MDV is very low compared to all-cause mortality regardless of the vaccination status of the birds. However, the cumulative MD incidence can reach 100% for unvaccinated cohorts, and 35% for vaccinated cohorts. These results suggest that death due to MDV is an insufficient metric to assess the prevalence of MDV broiler barns regardless of vaccine status, such that active surveillance is required to successfully assess the probability of MDV outbreaks, and to limit transmission of MDV between successive cohorts of broiler chickens.