Energy absorption of xenon clusters in helium nanodroplets under strong laser pulses

Energy absorption of xenon clusters embedded in helium nanodroplets from strong femtosecond laser pulses is studied theoretically. Compared to pure clusters we find earlier and more efficient energy absorption in agreement with experiments. This effect is due to resonant absorption of the helium nanoplasma whose formation is catalyzed by the xenon core. For very short double pulses with variable delay both plasma resonances, due to the helium shell and the xenon core, are identified and the experimental conditions are given which should allow for a simultaneous observation of both of them.Comment: 4 pages, 4 figure

Fitness cost of resistance: impact on management

Fungicides are important tools for the management of fungal diseases in many crops. But eventually, most fungicides fail because the treated pathogen population evolves resistance to the fungicide. This chapter focuses on how our knowledge of fitness costs associated with resistance informs strategies of fungicide deployment that help to avoid or delay development of resistance. Many different fungicide deployment strategies should be considered that take into account fungal population genetics as well as the specific agroecosystem. Mono-applications will be replaced by strategies that use several fungicides with different modes of action. Modeling approaches will be needed to inform us regarding the optimum strategies to use under different circumstances. It is clear that fitness costs connected to mutations that encode fungicide resistance will need to be better measured and taken into account in order to design optimum fungicide deployment strategies. We discuss the importance of fitness costs in assessing the usefulness of fungicide mixtures that contain a high-risk fungicide together with a low-risk fungicide and the role of population dynamical mathematical models of plant–pathogen interaction. According to models, the fitness cost of resistance determines the outcome of competition between the sensitive and resistant pathogen strains. If fitness costs are absent, then the use of the high-risk fungicide in a mixture selects for resistance, and the fungicide eventually becomes nonfunctional. If there is a cost of resistance, then an optimal ratio of fungicides in the mixture can be found, at which selection for resistance is expected to vanish and the level of disease control can be optimized

Can high-risk fungicides be used in mixtures without selecting for fungicide resistance?

Fungicide mixtures produced by the agrochemical industry often contain low-risk fungicides, to which fungal pathogens are fully sensitive, together with high-risk fungicides known to be prone to fungicide resistance. Can these mixtures provide adequate disease control while minimizing the risk for the development of resistance? We present a population dynamics model to address this question. We found that the fitness cost of resistance is a crucial parameter to determine the outcome of competition between the sensitive and resistant pathogen strains and to assess the usefulness of a mixture. If fitness costs are absent, then the use of the high-risk fungicide in a mixture selects for resistance and the fungicide eventually becomes nonfunctional. If there is a cost of resistance, then an optimal ratio of fungicides in the mixture can be found, at which selection for resistance is expected to vanish and the level of disease control can be optimized

Laser-driven nanoplasmas in doped helium droplets: Local ignition and anisotropic expansion

Doping a helium nanodroplet with a tiny xenon cluster of a few atoms only, sparks complete ionization of the droplet at laser intensities below the ionization threshold of helium atoms. As a result, the intrinsically inert and transparent droplet turns into a fast and strong absorber of infrared light. Microscopic calculations reveal a two-step mechanism to be responsible for the dramatic change: Avalanche-like ionization of the helium atoms on a femtosecond time scale, driven by field ionization due to the quickly charged xenon core is followed by resonant absorption enabled by an unusual cigar-shaped nanoplasma within the droplet.Comment: 4 pages, 4 figure

Spatially explicit ecological modeling improves empirical characterization of plant pathogen dispersal

Dispersal is a key ecological process, but it remains difficult to measure. By recording numbers of dispersed individuals at different distances from the source, one acquires a dispersal gradient. Dispersal gradients contain information on dispersal, but they are influenced by the spatial extent of the source. How can we separate the two contributions to extract knowledge about dispersal? One could use a small, point-like source for which a dispersal gradient represents a dispersal kernel, which quantifies the probability of an individual dispersal event from a source to a destination. However, the validity of this approximation cannot be established before conducting measurements. This represents a key challenge hindering progress in characterization of dispersal. To overcome it, we formulated a theory that incorporates the spatial extent of sources to estimate dispersal kernels from dispersal gradients. Using this theory, we re-analyzed published dispersal gradients for three major plant pathogens. We demonstrated that the three pathogens disperse over substantially shorter distances compared to conventional estimates. This method will allow the researchers to re-analyze a vast number of existing dispersal gradients to improve our knowledge about dispersal. The improved knowledge has potential to advance our understanding of species' range expansions and shifts, and inform management of weeds and diseases in crops

Measuring splash-dispersal of a major wheat pathogen in the field

Capacity for dispersal is a fundamental fitness component of plant pathogens. Characterization of plant pathogen dispersal is important for understanding how pathogen populations change in time and space. We devised a systematic approach to measure and analyze rain splash-driven dispersal of plant pathogens in field conditions, using the major fungal wheat pathogen Zymoseptoria tritici as a case study. We inoculated field plots of wheat (Triticum aestivum) with two distinct Z. tritici strains. Next, we measured disease intensity as counts of fruiting bodies (pycnidia) using automated image analysis. These measurements characterized primary disease gradients, which we used to estimate effective dispersal of the pathogen population. Genotyping of re-isolated pathogen strains with strain-specific PCR-reaction confirmed the conclusions drawn from phenotypic data. Consistently with controlled environment studies, we found that the characteristic scale of dispersal is tens of centimeters. We analyzed the data using a spatially-explicit mathematical model that incorporates the spatial extent of the source, rather than assuming a point source, which allows for a more accurate estimation of dispersal kernels. We employed bootstrapping methods for statistical testing and adopted a two-dimensional hypotheses test based on kernel density estimation, enabling more robust inference compared to standard methods. We report the first estimates of dispersal kernels of the pathogen in field conditions. However, repeating the experiment in other environments would lead to more robust conclusions. We put forward advanced methodology that paves the way to further measurements of plant pathogen dispersal in field conditions, which can inform spatially targeted plant disease management

Invasiveness of plant pathogens depends on the spatial scale of host distribution

Plant diseases often cause serious yield losses in agriculture. A pathogen’s invasiveness can be quantified by the basic reproductive number, R₀. Since pathogen transmission between host plants depends on the spatial separation between them, R₀ is strongly influenced by the spatial scale of the host distribution.We present a proof of principle of a novel approach to estimate the basic reproductive number, R₀, of plant pathogens as a function of the size of a field planted with crops and its aspect ratio. This general approach is based on a spatially explicit population dynamical model. The basic reproductive number was found to increase with the field size at small field sizes and to saturate to a constant value at large field sizes. It reaches a maximum in square fields and decreases as the field becomes elongated. This pattern appears to be quite general: it holds for dispersal kernels that decrease exponentially or faster, as well as for fat-tailed dispersal kernels that decrease slower than exponential (i.e., power-law kernels).We used this approach to estimate R₀ in wheat stripe rust (an important disease caused by Puccinia striiformis), where we inferred both the transmission rates and the dispersal kernels from the measurements of disease gradients. For the two largest datasets, we estimated R₀ of P. striiformis in the limit of large fields to be of the order of 30. We found that the spatial extent over which R₀ changes strongly is quite fine-scaled (about 30 m of the linear extension of the field). Our results indicate that in order to optimize the spatial scale of deployment of fungicides or host resistances, the adjustments should be made at a fine spatial scale. We also demonstrated how the knowledge of the spatial dependence of R₀ can improve recommendations with regard to fungicide treatment.This is the publisher’s final pdf. The article is published by John Wiley & Sons, Inc. and copyrighted by the Ecological Society of America. It can be found at: http://esajournals.onlinelibrary.wiley.com/hub/journal/10.1002/%28ISSN%291939-5582/Keywords: dispersal, population dynamics, epidemiology, disease control, spatial scales, host-pathogen interaction, disease gradient, plant disease, mathematical model, basic reproductive numbe