Variable strength of forest stand attributes and weather conditions on the questing activity of Ixodes ricinus ticks over years in managed forests

Given the ever-increasing human impact through land use and climate change on the environment, we crucially need to achieve a better understanding of those factors that influence the questing activity of ixodid ticks, a major disease-transmitting vector in temperate forests. We investigated variation in the relative questing nymph densities of Ixodes ricinus in differently managed forest types for three years (2008–2010) in SW Germany by drag sampling. We used a hierarchical Bayesian modeling approach to examine the relative effects of habitat and weather and to consider possible nested structures of habitat and climate forces. The questing activity of nymphs was considerably larger in young forest successional stages of thicket compared with pole wood and timber stages. Questing nymph density increased markedly with milder winter temperatures. Generally, the relative strength of the various environmental forces on questing nymph density differed across years. In particular, winter temperature had a negative effect on tick activity across sites in 2008 in contrast to the overall effect of temperature across years. Our results suggest that forest management practices have important impacts on questing nymph density. Variable weather conditions, however, might override the effects of forest management practices on the fluctuations and dynamics of tick populations and activity over years, in particular, the preceding winter temperatures. Therefore, robust predictions and the detection of possible interactions and nested structures of habitat and climate forces can only be quantified through the collection of long-term data. Such data are particularly important with regard to future scenarios of forest management and climate warming

The spatial scale of competition from recruits on an older cohort in Atlantic salmon

Competitive effects of younger cohorts on older ones are frequently assumed to be negligible in species where older, larger individuals dominate in pairwise behavioural interactions. Here, we provide field estimates of such competition by recruits on an older age class in Atlantic salmon (Salmo salar), a species where observational studies have documented strong body size advantages which should favour older individuals in direct interactions. By creating realistic levels of spatial variation in the density of underyearling (YOY) recruits over a 1-km stretch of a stream, and obtaining accurate measurements of individual growth rates of overyearlings (parr) from capture–mark–recapture data on a fine spatial scale, we demonstrate that high YOY density can substantially decrease parr growth. Models integrating multiple spatial scales indicated that parr were influenced by YOY density within 16 m. The preferred model suggested parr daily mass increase to be reduced by 39% when increasing YOY density from 0.0 to 1.0 m−2, which is well within the range of naturally occurring densities. Reduced juvenile growth rates will in general be expected to reduce juvenile survival (via increased length of exposure to freshwater mortality) and increase generation times (via increased age at seaward migrations). Thus, increased recruitment can significantly affect the performance of older cohorts, with important implications for population dynamics. Our results highlight that, even for the wide range of organisms that rely on defendable resources, the direction of competition among age classes cannot be assumed a priori or be inferred from behavioural observations alone

Forcing Versus Feedback: Epidemic Malaria and Monsoon Rains in Northwest India

Malaria epidemics in regions with seasonal windows of transmission can vary greatly in size from year to year. A central question has been whether these interannual cycles are driven by climate, are instead generated by the intrinsic dynamics of the disease, or result from the resonance of these two mechanisms. This corresponds to the more general inverse problem of identifying the respective roles of external forcings vs. internal feedbacks from time series for nonlinear and noisy systems. We propose here a quantitative approach to formally compare rival hypotheses on climate vs. disease dynamics, or external forcings vs. internal feedbacks, that combines dynamical models with recently developed, computational inference methods. The interannual patterns of epidemic malaria are investigated here for desert regions of northwest India, with extensive epidemiological records for Plasmodium falciparum malaria for the past two decades. We formulate a dynamical model of malaria transmission that explicitly incorporates rainfall, and we rely on recent advances on parameter estimation for nonlinear and stochastic dynamical systems based on sequential Monte Carlo methods. Results show a significant effect of rainfall in the inter-annual variability of epidemic malaria that involves a threshold in the disease response. The model exhibits high prediction skill for yearly cases in the malaria transmission season following the monsoonal rains. Consideration of a more complex model with clinical immunity demonstrates the robustness of the findings and suggests a role of infected individuals that lack clinical symptoms as a reservoir for transmission. Our results indicate that the nonlinear dynamics of the disease itself play a role at the seasonal, but not the interannual, time scales. They illustrate the feasibility of forecasting malaria epidemics in desert and semi-arid regions of India based on climate variability. This approach should be applicable to malaria in other locations, to other infectious diseases, and to other nonlinear systems under forcing

First Measurement of the Charge Asymmetry in Beauty-Quark Pair Production

The difference in the angular distributions between beauty quarks and antiquarks, referred to as the charge asymmetry, is measured for the first time in b (b) over bar pair production at a hadron collider. The data used correspond to an integrated luminosity of 1.0 fb(-1) collected at 7 TeV center-of-mass energy in proton-proton collisions with the LHCb detector. The measurement is performed in three regions of the invariant mass of the b (b) over bar system. The results obtained are A(C)(b (b) over bar) (40 10(5) GeV/c(2)) = 1.6 +/- 1.7 +/- 0.6%,where A(C)(b (b) over bar) is defined as the asymmetry in the difference in rapidity between jets formed from the beauty quark and antiquark, where in each case the first uncertainty is statistical and the second systematic. The beauty jets are required to satisfy 2 20 GeV, and have an opening angle in the transverse plane Delta phi > 2.6 rad. These measurements are consistent with the predictions of the standard model

Predictive Distribution of the Dirichlet Mixture Model by Local Variational Inference

In Bayesian analysis of a statistical model, the predictive distribution is obtained by marginalizing over the parameters with their posterior distributions. Compared to the frequently used point estimate plug-in method, the predictive distribution leads to a more reliable result in calculating the predictive likelihood of the new upcoming data, especially when the amount of training data is small. The Bayesian estimation of a Dirichlet mixture model (DMM) is, in general, not analytically tractable. In our previous work, we have proposed a global variational inference-based method for approximately calculating the posterior distributions of the parameters in the DMM analytically. In this paper, we extend our previous study for the DMM and propose an algorithm to calculate the predictive distribution of the DMM with the local variational inference (LVI) method. The true predictive distribution of the DMM is analytically intractable. By considering the concave property of the multivariate inverse beta function, we introduce an upper-bound to the true predictive distribution. As the global minimum of this upper-bound exists, the problem is reduced to seek an approximation to the true predictive distribution. The approximated predictive distribution obtained by minimizing the upper-bound is analytically tractable, facilitating the computation of the predictive likelihood. With synthesized data and real data evaluations, the good performance of the proposed LVI based method is demonstrated by comparing with some conventionally used methods