Large-scale fungicide spray heterogeneity and the regional spread of resistant pathogen strains

Optimal Resistance Management for Mixtures of High-Risk Fungicides: Robustness to the Initial Frequency of Resistance and Pathogen Sexual Reproduction

There is a strong consensus that selection for fungicide resistant pathogen strains can be most effectively limited by using applications of mixtures of fungicides designed to balance disease control against selection. However, how to do this in practice is not entirely characterized. Previous work indicates optimal mixtures of pairs of fungicides which are both at a high risk of resistance can be constructed using pairs of doses that select equally for both single resistant strains in the first year of application. What has not been addressed thus far is the important real-world case in which the initial levels of resistance to each fungicide differ, for example because the chemicals have been available for different lengths of time. We show how recommendations based on equal selection in the first year can be suboptimal in this case. We introduce a simple alternative approach, based on equalizing the frequencies of single resistant strains in the year that achieving acceptable levels of control is predicted to become impossible. We show that this strategy is robust to changes in parameters controlling pathogen epidemiology and fungicide efficacy. We develop our recommendation using a preexisting, parameterized model of Zymoseptoria tritici (the pathogen causing Septoria leaf blotch on wheat), which exemplifies the range of plant pathogens that predominantly spread clonally, but for which sexual reproduction forms an important component of the life cycle. We show that pathogen sexual reproduction can influence the rate at which fungicide resistance develops but does not qualitatively affect our optimal resistance management recommendation. [Formula: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.

Large-scale study validates that regional fungicide applications are major determinants of resistance evolution in the wheat pathogen Zymoseptoria tritici in France

In modern cropping systems, the near-universal use of plant protection products selects for resistance in pest populations. The emergence and evolution of this adaptive trait threaten treatment efficacy. We identified determinants of fungicide resistance evolution and quantified their effects at a large spatiotemporal scale. We focused on Zymoseptoria tritici, which causes leaf blotch in wheat. Phenotypes of qualitative or quantitative resistance to various fungicides were monitored annually, from 2004 to 2017, at about 70 sites throughout 22 regions of France (territorial units of 25 000 km² on average). We modelled changes in resistance frequency with regional anti-Septoria fungicide use, yield losses due to the disease and the regional area under organic wheat. The major driver of resistance dynamics was fungicide use at the regional scale. We estimated its effect on the increase in resistance and relative apparent fitness of each resistance phenotype. The predictions of the model replicated the spatiotemporal patterns of resistance observed in field populations (R² from 0.56 to 0.82). The evolution of fungicide resistance is mainly determined at the regional scale. This study therefore showed that collective management at the regional scale could effectively complete local actions.

Fungicide Resistance Evolution and Detection in Plant Pathogens: Plasmopara viticola as a Case Study

The use of single-site fungicides to control plant pathogens in the agroecosystem can be associated with an increased selection of resistance. The evolution of resistance represents one of the biggest challenges in disease control. In vineyards, frequent applications of fungicides are carried out every season for multiple years. The agronomic risk of developing fungicide resistance is, therefore, high. Plasmopara viticola, the causal agent of grapevine downy mildew, is a high risk pathogen associated with the development of fungicide resistance. P. viticola has developed resistance to most of the fungicide classes used and constitutes one of the most important threats for grapevine production. The goals of this review are to describe fungicide resistance evolution in P. viticola populations and how to conduct proper monitoring activities. Different methods have been developed for phenotyping and genotyping P. viticola for fungicide resistance and the different phases of resistance evolution and life cycles of the pathogen are discussed, to provide a full monitoring toolkit to limit the spread of resistance. A detailed revision of the available tools will help in shaping and harmonizing the monitoring activities between countries and organizations.

The Hsp90 Inhibitor, Monorden, Is a Promising Lead Compound for the Development of Novel Fungicides

Endophytic fungi are great resources for the identification of useful natural products such as antimicrobial agents. In this study, we performed the antifungal screening of various plant endophytic fungi against the dollar spot pathogen Sclerotinia homoeocarpa and finally selected Humicola sp. JS-0112 as a potential biocontrol agent. The bioactive compound produced by the strain JS-0112 was identified as monorden known as an inhibitor of heat shock protein 90 (Hsp90). Monorden exhibited strong antagonistic activity against most tested plant pathogenic fungi particularly against tree pathogens and oomycetes with the minimum inhibitory concentration values less than 2.5 μg mL-1. Extensive in planta assays revealed that monorden effectively suppressed the development of several important plant diseases such as rice blast, rice sheath blight, wheat leaf rust, creeping bentgrass dollar spot, and cucumber damping-off. Especially, it showed much stronger disease control efficacy against cucumber damping-off than a synthetic fungicide chlorothalonil. Subsequent molecular genetic analysis of fission yeast and Fusarium graminearum suggested that Hsp90 is a major inhibitory target of monorden, and sequence variation among fungal Hsp90 is a determinant for the dissimilar monorden sensitivity of fungi. This is the first report dealing with the disease control efficacy and antifungal mechanism of monorden against fungal plant diseases and we believe that monorden can be used as a lead molecule for developing novel fungicides with new action mechanism for the control of plant diseases caused by fungi and oomycetes.

Spatiotemporal dynamics of fungicide resistance in the wheat pathogen Zymoseptoria tritici in France

BACKGROUND

Management of pesticide resistance is a major issue in modern agricultural systems, particularly in the context of the broader challenge of reducing pesticide use. However, such management must be adapted to resistance dynamics, which remains challenging to predict due to its dependence on many biological traits of pests, interactions with the environment and pesticide use. We retrospectively studied the evolution of reported resistances to four modes of action (benzimidazoles, quinone outside inhibitors, sterol demethylation inhibitors and succinate dehydrogenase inhibitors), in French populations of the wheat pathogen Zymoseptoria tritici.

RESULTS

We used statistical models to analyse the Performance trial network data set (2004-2017; ∼ 70 locations in France yearly). They highlighted contrasting behaviours between phenotypes, for example: (i) stable spatial distributions and colonization front structures over time, and (ii) different frequency growth rates at the national scale and between regions.

CONCLUSION

We provide a quantitative description of the spatiotemporal patterns of resistance evolution for fungicides with several modes of action. Moreover, we highlight some unexpected resistance dynamics in France, with major differences between the north and south. This complex pattern of resistance evolution in French populations is consistent with previous descriptions of dynamics at the European scale. These results should make it easier to anticipate evolution locally and to improve the management of resistance. © 2019 Society of Chemical Industry.

Using Epidemiological Principles to Explain Fungicide Resistance Management Tactics: Why do Mixtures Outperform Alternations?

Whether fungicide resistance management is optimized by spraying chemicals with different modes of action as a mixture (i.e., simultaneously) or in alternation (i.e., sequentially) has been studied by experimenters and modelers for decades. However, results have been inconclusive. We use previously parameterized and validated mathematical models of wheat Septoria leaf blotch and grapevine powdery mildew to test which tactic provides better resistance management, using the total yield before resistance causes disease control to become economically ineffective ("lifetime yield") to measure effectiveness. We focus on tactics involving the combination of a low-risk and a high-risk fungicide, and the case in which resistance to the high-risk chemical is complete (i.e., in which there is no partial resistance). Lifetime yield is then optimized by spraying as much low-risk fungicide as is permitted, combined with slightly more high-risk fungicide than needed for acceptable initial disease control, applying these fungicides as a mixture. That mixture rather than alternation gives better performance is invariant to model parameterization and structure, as well as the pathosystem in question. However, if comparison focuses on other metrics, e.g., lifetime yield at full label dose, either mixture or alternation can be optimal. Our work shows how epidemiological principles can explain the evolution of fungicide resistance, and also highlights a theoretical framework to address the question of whether mixture or alternation provides better resistance management. It also demonstrates that precisely how spray tactics are compared must be given careful consideration. [Formula: see text] Copyright © 2018 The Author(s). This is an open access article distributed under the CC BY 4.0 International license .

Is the emergence of fungal resistance to medical triazoles related to their use in the agroecosystems? A mini review

Triazole fungicides are used broadly for the control of infectious diseases of both humans and plants. The surge in resistance to triazoles among pathogenic populations is an emergent issue both in agriculture and medicine. The non-rational use of fungicides with site-specific modes of action, such as the triazoles, may increase the risk of antifungal resistance development. In the medical field, the surge of resistant fungal isolates has been related to the intensive and recurrent therapeutic use of a limited number of triazoles for the treatment and prophylaxis of many mycoses. Similarities in the mode of action of triazole fungicides used in these two fields may lead to cross-resistance, thus expanding the spectrum of resistance to multiple fungicides and contributing to the perpetuation of resistant strains in the environment. The emergence of fungicide-resistant isolates of human pathogens has been related to the exposure to fungicides used in agroecosystems. Examples include species of cosmopolitan occurrence, such as Fusarium and Aspergillus, which cause diseases in both plants and humans. This review summarizes the information about the most important triazole fungicides that are largely used in human clinical therapy and agriculture. We aim to discuss the issues related to fungicide resistance and the recommended strategies for preventing the emergence of triazole-resistant fungal populations capable of spreading across environments.

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 reproductivenumber, 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 amaximum 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.

Guiding deployment of resistance in cereals using evolutionary principles

Genetically controlled resistance provides plant breeders with an efficient means of controlling plant disease, but this approach has been constrained by practical difficulties associated with combining many resistance genes together and strong evolutionary responses from pathogen populations leading to subsequent resistance breakdown. However, continuing advances in molecular marker technologies are revolutionizing the ability to rapidly and reliably manipulate resistances of all types - major gene, adult plant and quantitative resistance loci singly or multiply into individual host lines. Here, we argue that these advances provide major opportunities to deliberately design deployment strategies in cereals that can take advantage of the evolutionary pressures faced by target pathogens. Different combinations of genes deployed either within single host individuals or between different individuals within or among crops, can be used to reduce the size of pathogen populations and generate patterns of disruptive selection. This will simultaneously limit immediate epidemic development and reduce the probability of subsequent evolutionary change in the pathogen for broader infectivity or increased aggressiveness. The same general principles are relevant to the control of noncereal diseases, but the most efficacious controls will vary reflecting the range of genetic options available and their fit with specific ecology and life-history combinations.

Spatial distribution of single-nucleotide polymorphisms related to fungicide resistance and implications for sampling

Spatial distribution of single-nucleotide polymorphisms (SNPs) related to fungicide resistance was studied for Botrytis cinerea populations in vineyards and for B. squamosa populations in onion fields. Heterogeneity in this distribution was characterized by performing geostatistical analyses based on semivariograms and through the fitting of discrete probability distributions. Two SNPs known to be responsible for boscalid resistance (H272R and H272Y), both located on the B subunit of the succinate dehydrogenase gene, and one SNP known to be responsible for dicarboximide resistance (I365S) were chosen for B. cinerea in grape. For B. squamosa in onion, one SNP responsible for dicarboximide resistance (I365S homologous) was chosen. One onion field was sampled in 2009 and another one was sampled in 2010 for B. squamosa, and two vineyards were sampled in 2011 for B. cinerea, for a total of four sampled sites. Cluster sampling was carried on a 10-by-10 grid, each of the 100 nodes being the center of a 10-by-10-m quadrat. In each quadrat, 10 samples were collected and analyzed by restriction fragment length polymorphism polymerase chain reaction (PCR) or allele specific PCR. Mean SNP incidence varied from 16 to 68%, with an overall mean incidence of 43%. In the geostatistical analyses, omnidirectional variograms showed spatial autocorrelation characterized by ranges of 21 to 1 m. Various levels of anisotropy were detected, however, with variograms computed in four directions (at 0°, 45°, 90°, and 135° from the within-row direction used as reference), indicating that spatial autocorrelation was prevalent or characterized by a longer range in one direction. For all eight data sets, the β-binomial distribution was found to fit the data better than the binomial distribution. This indicates local aggregation of fungicide resistance among sampling units, as supported by estimates of the parameter θ of the β-binomial distribution of 0.09 to 0.23 (overall median value = 0.20). On the basis of the observed spatial distribution patterns of SNP incidence, sampling curves were computed for different levels of reliability, emphasizing the importance of sample size for the detection of mutation incidence below the risk threshold for control failure.

The emergence of resistance to fungicides

Many studies exist about the selection phase of fungicide resistance evolution, where a resistant strain is present in a pathogen population and is differentially selected for by the application of fungicides. The emergence phase of the evolution of fungicide resistance--where the resistant strain is not present in the population and has to arise through mutation and subsequently invade the population--has not been studied to date. Here, we derive a model which describes the emergence of resistance in pathogen populations of crops. There are several important examples where a single mutation, affecting binding of a fungicide with the target protein, shifts the sensitivity phenotype of the resistant strain to such an extent that it cannot be controlled effectively ('qualitative' or 'single-step' resistance). The model was parameterized for this scenario for Mycosphaerella graminicola on winter wheat and used to evaluate the effect of fungicide dose rate on the time to emergence of resistance for a range of mutation probabilities, fitness costs of resistance and sensitivity levels of the resistant strain. We also evaluated the usefulness of mixing two fungicides of differing modes of action for delaying the emergence of resistance. The results suggest that it is unlikely that a resistant strain will already have emerged when a fungicide with a new mode of action is introduced. Hence, 'anti-emergence' strategies should be identified and implemented. For all simulated scenarios, the median emergence time of a resistant strain was affected little by changing the dose rate applied, within the range of doses typically used on commercial crops. Mixing a single-site acting fungicide with a multi-site acting fungicide delayed the emergence of resistance to the single-site component. Combining the findings with previous work on the selection phase will enable us to develop more efficient anti-resistance strategies.

An epidemiological framework for modelling fungicide dynamics and control

Defining appropriate policies for controlling the spread of fungal disease in agricultural landscapes requires appropriate theoretical models. Most existing models for the fungicidal control of plant diseases do not explicitly include the dynamics of the fungicide itself, nor do they consider the impact of infection occurring during the host growth phase. We introduce a modelling framework for fungicide application that allows us to consider how “explicit” modelling of fungicide dynamics affects the invasion and persistence of plant pathogens. Specifically, we show that “explicit” models exhibit bistability zones for values of the basic reproductive number () less than one within which the invasion and persistence threshold depends on the initial infection levels. This is in contrast to classical models where invasion and persistence thresholds are solely dependent on . In addition if initial infection occurs during the growth phase then an additional “invasion zone” can exist for even smaller values of . Within this region the system will experience an epidemic that is not able to persist. We further show that ideal fungicides with high levels of effectiveness, low rates of application and low rates of decay lead to the existence of these bistability zones. The results are robust to the inclusion of demographic stochasticity.

Time-dependent infectivity and flexible latent and infectious periods in compartmental models of plant disease

Compartmental models have become the dominant theoretical paradigm in mechanistic modeling of plant disease and offer well-known advantages in terms of analytic tractability, ease of simulation, and extensibility. However, underlying assumptions of constant rates of infection and of exponentially distributed latent and infectious periods are difficult to justify. Although alternative approaches, including van der Plank's seminal discrete time model and models based on the integro-differential formulation of Kermack and McKendrick's model, have been suggested for plant disease and relax these unrealistic assumptions, they are challenging to implement and to analyze. Here, we propose an extension to the susceptible, exposed, infected, and removed (SEIR) compartmental model, splitting the latent and infection compartments and thereby allowing time-varying infection rates and more realistic distributions of latent and infectious periods to be represented. Although the model is, in fact, more general, we specifically target plant disease by demonstrating how it can represent both the van der Plank model and the most commonly used variant of the Kermack and McKendrick (K & M) model (in which the infectivity response is delay Gamma distributed). We show how our reformulation retains the numeric and analytic tractability of SEIR models, and how it can be used to replicate earlier analyses of the van der Plank and K & M models. Our reformulation has the advantage of using elementary mathematical techniques, making implementation easier for the nonspecialist. We show a practical implication of these results for disease control. By taking advantage of the easy extensibility characteristic of compartmental models, we also investigate the effects of including additional biological realism. As an example, we show how the more realistic infection responses we consider interact with host demography and lead to divergent invasion thresholds when compared with the "standard" SEIR model. An ever-increasing number of analyses purportedly extract more biologically realistic invasion thresholds by adding additional biological detail to the SEIR model framework; we contend that our results demonstrate that extending a model that has such a simplistic representation of the infection dynamics may not, in fact, lead to more accurate results. Therefore, we suggest that modelers should carefully consider the underlying assumptions of the simplest compartmental models in their future work.

Durable strategies to deploy plant resistance in agricultural landscapes

The deployment of resistant crops often leads to the emergence of resistance-breaking pathogens that suppress the yield benefit provided by the resistance. Here, we theoretically explored how farmers' main leverages (resistant cultivar choice, resistance deployment strategy, landscape planning and cultural practices) can be best combined to achieve resistance durability while minimizing yield losses as a result of plant viruses. Assuming a gene-for-gene type of interaction, virus epidemics are modelled in a landscape composed of a mosaic of resistant and susceptible fields, subjected to seasonality, and a reservoir hosting viruses year-round. The model links the genetic and the epidemiological processes, shaping at nested scales the demogenetic dynamics of viruses. The choice of the resistance gene (characterized by the equilibrium frequency of the resistance-breaking virus at mutation-selection balance in a susceptible plant) is the most influential leverage of action. Our results showed that optimal strategies of resistance deployment range from 'mixture' (where susceptible and resistant cultivars coexist) to 'pure' strategies (with only resistant cultivar) depending on the resistance characteristics and the epidemiological context (epidemic incidence and landscape connectivity). We demonstrate and discuss gaps concerning virus epidemiology across the agro-ecological interface that must be filled to achieve sustainable disease management.

Influence of cultivated landscape composition on variety resistance: an assessment based on wheat leaf rust epidemics

In plant pathology, the idea of designing variety management strategies at the scale of cultivated landscapes is gaining more and more attention. This requires the identification of effects that take place at large scales on host and pathogen populations. Here, we show how the landscape varietal composition influences the resistance level (as measured in the field) of the most grown wheat varieties by altering the structure of the pathogen populations. For this purpose, we jointly analysed three large datasets describing the wheat leaf rust pathosystem (Puccinia triticina/Triticum aestivum) at the country scale of France with a Bayesian hierarchical model. We showed that among all compatible pathotypes, some were preferentially associated with a variety, that the pathotype frequencies on a variety were affected by the landscape varietal composition, and that the observed resistance level of a variety was linked to the frequency of the most aggressive pathotypes among all compatible pathotypes. This data exploration establishes a link between the observed resistance level of a variety and landscape composition at the national scale. It illustrates that the quantitative aspects of the host-pathogen relationship have to be considered in addition to the major resistance/virulence factors in landscape epidemiology approaches.

Changes in Fungicide Resistance Frequency and Population Structure of Pyricularia oryzae after Discontinuance of MBI-D Fungicides

The changes in fungicide resistance frequency and population structure of the rice blast fungus Pyricularia oryzae were monitored after the discontinuance of melanin biosynthesis inhibitor targeting scytalone dehydratase (MBI-D) fungicides use in Saga Prefecture, Japan. After discontinuance in 2003, the frequency of resistant isolates decreased from 71.8% in 2002 to 25% in 2003, and became undetectable in 2007. The initial marked decrease was due to a decline of isolates possessing the predominant haplotype, although the haplotypic diversity among resistant isolates remained high from 2003 to 2005. These results revealed that resistant isolates were less fit in comparison with sensitive isolates in the absence of MBI-D fungicide pressure under field conditions. Pairwise F_ST values indicated that the change in population structure after MBI-D discontinuance was explainable by a rapid change in the proportions of resistant and sensitive subpopulations. Depending upon the existence of fitness cost and rapid changes in population structure, it may be possible to reintroduce MBI-D fungicides in areas where resistance has already developed, although we speculate that fitness cost related to MBI-D resistance may be small based on our present results and previous findings.

Optimal strategies for the eradication of asiatic citrus canker in heterogeneous host landscapes

ABSTRACT The eradication of nonnative plant pathogens is a key challenge in plant disease epidemiology. Asiatic citrus canker is an economically significant disease of citrus caused by the bacterial plant pathogen Xanthomonas citri subsp. citri. The pathogen is a major exotic disease problem in many citrus producing areas of the world including the United States, Brazil, and Australia. Various eradication attempts have been made on the disease but have been associated with significant social and economic costs due to the necessary removal of large numbers of host trees. In this paper, a spatially explicit stochastic simulation model of Asiatic citrus canker is introduced that describes an epidemic of the disease in a heterogeneous host landscape. We show that an optimum eradication strategy can be determined that minimizes the adverse costs associated with eradication. In particular, we show how the optimum strategy and its total cost depend on the topological arrangement of the host landscape. We discuss the implications of the results for invading plant disease epidemics in general and for historical and future eradication attempts on Asiatic citrus canker.

Combating plant diseases--the Darwin connection

Although Darwin knew of plant diseases, he did not study them as part of his analysis of natural selection. Effective plant disease control has only been developed after his death. This article explores the relevance of Darwin's ideas to three problem areas with respect to diseases caused by fungi: emergence of new diseases, loss of disease resistance bred into plants and development of fungicide resistance. Darwin's concept of change through natural or artificial selection relied on selection of many small changes, but subsequent genetic research has shown that change can also occur through large steps. Appearance of new diseases can involve gene duplication, transfer or recombination, but all evidence points to both host plant resistance and fungicide susceptibility being overcome through point mutations. Because the population size of diseases such as rusts and powdery and downy mildews is so large, all possible point mutations are likely to occur daily, even during moderate epidemics. Overcoming control measures therefore reflects the overall fitness of these mutants, and much resource effort is being directed towards assessment of their fitness, both in the presence and in the absence of selection. While recent developments in comparative genomics have caused some revision of Darwin's ideas, experience in managing plant disease control measures clearly demonstrates the relevance of concepts he introduced 150 years ago. It also reveals the remarkable speed and the practical impact of adaptation in wild microorganism populations to changes in their environment, and the difficulty of stopping or delaying such adaptation.

Evolutionary epidemiology of drug-resistance in space

How can we optimize the use of drugs against parasites to limit the evolution of drug resistance? This question has been addressed by many theoretical studies focusing either on the mixing of various treatments, or their temporal alternation. Here we consider a different treatment strategy where the use of the drug may vary in space to prevent the rise of drug-resistance. We analyze epidemiological models where drug-resistant and drug-sensitive parasites compete in a one-dimensional spatially heterogeneous environment. Two different parasite life-cycles are considered: (i) direct transmission between hosts, and (ii) vector-borne transmission. In both cases we find a critical size of the treated area, under which the drug-resistant strain cannot persist. This critical size depends on the basic reproductive ratios of each strain in each environment, on the ranges of dispersal, and on the duration of an infection with drug-resistant parasites. We discuss optimal treatment strategies that limit disease prevalence and the evolution of drug-resistance.

The spread of drug-resistant parasites erodes the efficacy of therapeutic treatments against many infectious diseases and is a major threat of the 21st century. The evolution of drug-resistance depends, among other things, on how the treatments are administered at the population level. “Resistance management” consists of finding optimal treatment strategies that both reduce the consequence of an infection at the individual host level, and limit the spread of drug-resistance in the pathogen population. Several studies have focused on the effect of mixing different treatments, or of alternating them in time. Here, we analyze another strategy, where the use of the drug varies spatially: there are places where no one receives any treatment. We find that such a spatial heterogeneity can totally prevent the rise of drug-resistance, provided that the size of treated patches is below a critical threshold. The range of parasite dispersal, the relative costs and benefits of being drug-resistant compared to being drug-sensitive, and the duration of an infection with drug-resistant parasites are the main factors determining the value of this threshold. Our analysis thus provides some general guidance regarding the optimal spatial use of drugs to prevent or limit the evolution of drug-resistance.

Sustainable agriculture and plant diseases: an epidemiological perspective

The potential for modern biology to identify new sources for genetical, chemical and biological control of plant disease is remarkably high. Successful implementation of these methods within globally and locally changing agricultural environments demands new approaches to durable control. This, in turn, requires fusion of population genetics and epidemiology at a range of scales from the field to the landscape and even to continental deployment of control measures. It also requires an understanding of economic and social constraints that influence the deployment of control. Here I propose an epidemiological framework to model invasion, persistence and variability of epidemics that encompasses a wide range of scales and topologies through which disease spreads. By considering how to map control methods onto epidemiological parameters and variables, some new approaches towards optimizing the efficiency of control at the landscape scale are introduced. Epidemiological strategies to minimize the risks of failure of chemical and genetical control are presented and some consequences of heterogeneous selection pressures in time and space on the persistence and evolutionary changes of the pathogen population are discussed. Finally, some approaches towards embedding epidemiological models for the deployment of control in an economically plausible framework are presented.

Adaptation to the cost of resistance in a haploid clonally reproducing organism: the role of mutation, migration and selection

A model of compensatory evolution with respect to fungicide resistance in a haploid clonally reproducing fungus is developed in which compensatory mutations mitigate fitness costs associated with resistance. The role of mutation, migration and selection in invasion of rare genotypes when the environment changes from unsprayed to sprayed and from sprayed to unsprayed is analysed in detail. In some circumstances (ignoring back mutations) stable internal steady-state values for multiple genotypes can be obtained. In these cases a threshold value (f*) for the fraction of the population exposed to the fungicide can be derived for the transition between different steady-state conditions. Conditions are derived for invasion-when-rare of resistant genotypes at boundary equilibria established sometime after the onset of spraying and conversely of sensitive genotypes sometime after the cessation of spraying are derived. In these cases conditions are presented for (a) the invasion of a resistant genotype with a compensatory mutation (resistant-compensated) into a sensitive-uncompensated population that has re-equilibrated following the onset of spraying and (b) the invasion of a susceptible-uncompensated genotype into a resistant-compensated population that has re-equilibrated following the cessation of spraying, provided certain conditions are met. A resistant-compensated genotype may be fixed (or at near-fixation) in the population following a period of spraying, provided the mean intrinsic growth rate of the resistant-compensated genotype in a sprayed environment (over exposed and non-exposed parts of the population) is greater than that of the susceptible-uncompensated genotype. The fraction of the population exposed (the efficiency of spraying) is critical in this respect. However, it is possible for a sensitive-uncompensated genotype to invade provided there is no fitness gain associated with the resistant-compensated genotype, introduction by migration occurs following equilibration of the population to the new environment, and competitive effects are re-imposed when spraying ceases. We further derive a threshold level for the resident resistant-compensated population to reduce to following the cessation of spraying, such that the introduced susceptible-uncompensated genotype will invade. These results will be of use in determining the long-term persistence of resistance in a pathogen population once a fungicide is no longer effective and removed from use.

Within-host disease ecology in the sea fan Gorgonia ventalina: modeling the spatial immunodynamics of a coral-pathogen interaction

We develop a spatially explicit model for the within-host interactions between a fungal pathogen and the immune response by its coral host. The model is parameterized for the recent epizootic of Aspergillus sydowii in the sea fan Gorgonia ventalina, but its structure is adaptable to many other diseases attacking corals worldwide, fungal infections in other invertebrates and plants, and opportunistic fungal infections in vertebrates. Model processes include pathogen growth and spread through consumption of host tissue, chemotactic attraction of undifferentiated host amoebocytes to infections, and amoebocyte differentiation into various cell types that attack the pathogen. Sensitivity analysis shows that the spread rate of a single localized infection is determined primarily by the pathogen's potential rate of host tissue consumption and by the host's ability to replenish the pool of undifferentiated amoebocytes and sustain a long-term response. The spatial localization of immune responses creates potentially strong indirect interactions between distant lesions, allowing new infections to grow rapidly while host resources are concentrated at older, larger infections. These findings provide possible mechanistic explanations for effects of environmental stressors (e.g., ocean warming, nutrient enrichment) on aspergillosis prevalence and severity and for the observed high spatial and between-host variability in disease impacts.

Models of fungicide resistance dynamics

We describe two classes of models used for fungicide and antibiotic resistance dynamics. One class assumes that the density of the pathogen (or severity of the disease caused by the pathogen) has no feedback effects on the rate at which new infections arise. The second class does not make this assumption. A quantitative relationship between these two classes is derived. We then discuss the two sets of assumptions made in the literature about initial conditions: either both the fungicide-sensitive strain and the -resistant strain are initially at low density, or the sensitive strain is resident at nonlow density and the resistant strain is initially at low density. We show that models of fungicide resistance dynamics with and without density-dependent feedback give contrasting predictions on the effects of pathogen life-cycle parameters and the effects of the fungicide (dose, frequency, use of mixtures, spatial usage restrictions) on the evolution, invasion, and spread of fungicide resistance. We further show that the evaluation of a resistance management strategy requires a very precise definition of what constitutes a good strategy.

Epidemiological models for invasion and persistence of pathogens

Motivated by questions such as "Why do some diseases take off, while others die out?" and "How can we optimize the deployment of control methods," we introduce simple epidemiological concepts for the invasion and persistence of plant pathogens. An overarching modeling framework is then presented that can be used to analyze disease invasion and persistence at a range of scales from the microscopic to the regional. Criteria for invasion and persistence are introduced, initially for simple models of epidemics, and then for models with greater biological realism. Some ways in which epidemiological models are used to identify optimal strategies for the control of disease are discussed. Particular attention is given to the spatial structure of host populations and to the role of chance events in determining invasion and persistence of plant pathogens. Finally, three brief case studies are used to illustrate the practical applications of epidemiological theory to understand invasion and persistence of plant pathogens. These comprise long-term predictions for the persistence and control of Dutch elm disease; identification of methods to manage the spread of rhizomania on sugar beet in the U.K. by matching the scale of control with the spatial and temporal scales of the disease; and analysis of evolutionary change in virus control to identify risks of inadvertent selection for damaging virus strains.

Impact of scale on the effectiveness of disease control strategies for epidemics with cryptic infection in a dynamical landscape: an example for a crop disease

We use a spatially explicit, stochastic model to analyse the effectiveness of different scales of local control strategies in containing the long-term, multi-seasonal spread of a crop disease through a dynamically changing population of susceptible crops in which there is cryptic infection. The model distinguishes between susceptible, infested and symptomatic fields. It is motivated by rhizomania disease on sugar beet in the UK as an exemplar of a spatially structured and partially asymptomatic epidemic. Our results show the importance of matching the scales of local control strategies to prevent intensification and regional spread of disease with the inherent temporal and spatial scales of an epidemic. A simple field-scale containment strategy, whereby the susceptible crop is no longer grown on fields showing symptoms, fails for this system with cryptic infection because the locally applied control lags behind the epidemic. A farm-scale strategy, whereby growers respond to the disease status of neighbouring farms by transferring their quota for sugar beet to farmers in regions of reduced risk, succeeds. We conclude that a soil-borne pathogen such as rhizomania could be managed by movement of susceptible crops in the landscape using a strategy that matches the temporal and spatial scales of the epidemic and which take account of risk aversion among growers. We show some parallels and differences in effectiveness between a ‘culling’ strategy involving crop removal around emerging foci and the local deployment of partially resistant varieties that reduce amplification and transmission of inoculum. Some relationships between the control of plant and livestock diseases are briefly discussed.

Rates of evolution of avirulence phenotypes and DNA markers in a northwest European population of Puccinia striiformis f. sp. tritici

The effects of evolutionary processes in fungal pathogen populations may occur more rapidly and display larger effects in agricultural systems than in wild ecosystems because of human involvement by plant breeding and crop management. In this study, we analysed the rate of evolution in three lineages of a northwest European population of a biotrophic and asexual reproduced fungal pathogen, Puccinia striiformis f. sp. tritici, causing yellow rust on wheat. Pathogen samples were collected between 1975 and 2002 in the UK and Denmark, and assayed for 14 individual avirulence/virulence alleles and up to 234 amplified fragment length polymorphism (AFLP) primer pairs producing approximately 17,000 AFLP fragments. The large number of fragments and a targeted sampling of isolates allowed a reconstruction of phylogenies in great detail, i.e. no homoplasy and a representation of sequential, evolutionary steps by pathogen samples. A recent, phenotypic loss of avirulence was observed at least once for loci corresponding to P. striiformis f. sp. tritici resistance Yr2, Yr3, Yr4, Yr7, Yr9, and Yr15, whereas Avr6 and Avr17 were lost independently in all three lineages, corresponding to 16 events of loss of avirulence (emergence of virulence). The opposite process, restoration of avirulence, was observed for Yr9 and Yr32. An interpretation of phenotypic changes within lineages as independent mutation events resulted in mutation frequencies from 1.4x10(-6) to 4.1x10(-6) per AFLP fragment (locus) per generation, whereas the effective rate by which a mutation from avirulence to virulence was established in the pathogen population, when subject to selection by host resistance genes, was approximately three orders of magnitude faster.

Modelling disease spread and control in networks: implications for plant sciences

Networks are ubiquitous in natural, technological and social systems. They are of increasing relevance for improved understanding and control of infectious diseases of plants, animals and humans, given the interconnectedness of today's world. Recent modelling work on disease development in complex networks shows: the relative rapidity of pathogen spread in scale-free compared with random networks, unless there is high local clustering; the theoretical absence of an epidemic threshold in scale-free networks of infinite size, which implies that diseases with low infection rates can spread in them, but the emergence of a threshold when realistic features are added to networks (e.g. finite size, household structure or deactivation of links); and the influence on epidemic dynamics of asymmetrical interactions. Models suggest that control of pathogens spreading in scale-free networks should focus on highly connected individuals rather than on mass random immunization. A growing number of empirical applications of network theory in human medicine and animal disease ecology confirm the potential of the approach, and suggest that network thinking could also benefit plant epidemiology and forest pathology, particularly in human-modified pathosystems linked by commercial transport of plant and disease propagules. Potential consequences for the study and management of plant and tree diseases are discussed.