Frank van den Bosch

The dynamics of an eco-epidemic model with biological control

In the study of biological control very few researchers take into account that the pest to be controlled often also infests wild plant species. In this paper a model concerning the effect of a wild host plant species on biologically-based technologies for pest control (BBTs) is formulated and analyzed. The pest species considered here does not only feed on the crop but also has a wild host species. Mathematical analyses of the model equations with regard to invariance of non-negativity, boundedness of solutions, nature of equilibria, permanence and global stability are analyzed. As the transmission rate parameter value is changed, the disease-induced coexistence state and the disease-induced persistent cycles for the populations are admissible. In particular, we show that the internal steady state, if it exists, switches from stable to unstable and back to stable again as the transmission rate increases. This implies that biological control has both stabilizing and destabilizing effects. Further, the presence of a wild host plant has a highly destabilizing effect on the pest community. In addition, when the transmission rate varies periodically, the system exhibits complex dynamics including quasiperiodic solution, chaotic attractors and so on. We answer several important questions about the long-term behavior of the interacting species. Various consequences for biological control programs are discussed.

Governing Principles Can Guide Fungicide-Resistance Management Tactics

Fungicide-resistance management would be more effective if principles governing the selection of resistant strains could be determined and validated. Such principles could then be used to predict whether a proposed change to a fungicide application program would decrease selection for resistant strains. In this review, we assess a governing principle that appears to have good predictive power. The principle states that reducing the product of the selection coefficient (defined as the difference between the per capita rate of increase of the sensitive and resistant strains) and the exposure time of the pathogen to the fungicide reduces the selection for resistance. We show that observations as well as modeling studies agree with the predicted effect (i.e., that a specific change to a fungicide program increased or decreased selection or was broadly neutral in its effect on selection) in 84% of the cases and that only 5% of the experimental results contradict predictions. We argue that the selection coefficient and exposure time principle can guide the development of resistance management tactics.

A Population-Dynamics Approach to Assess the Threat of Plant Pathogens as Biological Weapons against Annual Crops

I recent years there has been considerable concern expressed in the scientific and popular literature about the threat of biological terrorism (Simon 1997, Henderson 1998, Abelson 1999,Atlas 1999, Osterholm 1999, Stone 2000, Hardy 2001, Stimson Center 2001). This general interest had been propelled by US executive orders on weapons of mass destruction, White House initiatives on biological and chemical weapons preparedness (White House 1994, 1998a, 1998b, 1998c, 1999a), and the release of information from the former Soviet Union on the extent of biological weapons research conducted during the cold war (Alibek and Handelman 1999, Tucker 1999). Obviously, this concern has intensified since the tragedies of September 11, 2001 (Lawler 2001). Much attention has been directed toward the use of pathogenic microorganisms as biological weapons against humans, but there has been growing awareness of the potential use of microbes as weapons against crops as well (MacKenzie 1999, Rogers et al. 1999, Schaad et al. 1999,Yang and Sanogo 2000), especially in view of information that has come to light concerning Iraq’s past efforts to develop biological weapons against crop plants (Whitby and Rogers 1997). The impact of plant diseases on agriculture is immense. In the United States, for example, annual total losses due to crop diseases are estimated at over

The emergence of resistance to fungicides.

30 billion, with 65% of that amount attributed to introduced (invasive) microbes (Pimentel et al. 2000). Economically important pathogens continue to be accidentally introduced, some with very large economic consequences (Bandyopadhyay et al. 1998, Gottwald et al. 2001).Although, to our knowledge, plant pathogens have never been deliberately introduced into US crops as an act of warfare or terrorism, there is concern that this and many other countries are vulnerable to such acts of aggression (Kadlec 1995, Horn and Breeze 1999, Pearson 1999). The chances of a given plant pathogen being used successfully as a biological weapon involve, among other things, ease of production, storage, and delivery, and then the fate of the introduced pathogen once it is introduced into a susceptible crop (Schaad et al. 1999). This article is concerned with assessing the risk of the latter, including accidentally introduced plant pathogens (Yang et al. 1991, Ruesink et al. 1995, Schmitz and Simberloff 1997, Enserink 1999), a key component of the Executive Order on Invasive Species (White House 1999b). The Animal and Plant Health Inspection Service (APHIS) of the US Department of Agriculture uses several

Adaptation to the cost of resistance: a model of compensation, recombination, and selection in a haploid organism

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.

Shared influence of pathogen and host genetics on a trade‐off between latent period and spore production capacity in the wheat pathogen, Puccinia triticina

Populations of pathogenic organisms often evolve resistance in response to the use of pesticides or antibiotics. This rise of resistance may be followed by a fall when chemical control is suspended and resistance alleles carry a fitness cost. Another possibility is that mutations at secondary loci compensate for the cost, usually without loss of resistance. This enables resistant types to withstand invasion by the susceptible wild-type; resistance then persists in the population, which reduces the efficacy of future pesticide or antibiotic use. We examined a two-locus model of a haploid organism that adapts to the cost of resistance by a single compensatory mutation. We addressed the question how different combinations of cost and compensation and different levels of recombination affect the consequences of a single pesticide application. Resistance will become fixed in the population when the fraction of the population exposed to pesticide exceeds the cost of resistance. Compensatory mutations reduce the cost of resistance and therefore this threshold level of pesticide use. In the absence of pesticide, recombination promotes stability of equilibria. In the presence of pesticide, recombination accelerates the fixation of resistance and compensating alleles; recombination may also enable the persistence of compensated resistant types after pesticide use.

The effect of transmission route on plant virus epidemic development and disease control

Crop pathogens are notorious for their rapid adaptation to their host. We still know little about the evolution of their life cycles and whether there might be trade‐offs between fitness components, limiting the evolutionary potential of these pathogens. In this study, we explored a trade‐off between spore production capacity and latent period in Puccinia triticina, a fungal pathogen causing leaf rust on wheat. Using a simple multivariate (manova) technique, we showed that the covariance between the two traits is under shared control of host and pathogen, with contributions from host genotype (57%), pathogen genotype (18.4%) and genotype × genotype interactions (12.5%). We also found variation in sign and strength of genetic correlations for the pathogen, when measured on different host varieties. Our results suggest that these important pathogen life‐history traits do not freely respond to directional selection and that precise evolutionary trajectories are contingent on the genetic identity of the interacting host and pathogen.

Durable Resistance to Crop Pathogens: An Epidemiological Framework to Predict Risk under Uncertainty

A model for indirect vector transmission and epidemic development of plant viruses is extended to consider direct transmission through vector mating. A basic reproduction number is derived which is the sum of the R(0) values specific for three transmission routes. We analyse the model to determine the effect of direct transmission on plant disease control directed against indirect transmission. Increasing the rate of horizontal sexual transmission means that vector control rate or indirect transmission rate must be increased/decreased substantially to maintain R(0) at a value less than 1. By contrast, proportionately increasing the probability of transovarial transmission has little effect. Expressions are derived for the steady-state values of the viruliferous vector population. There is clear advantage for an insect virus in indirect transmission to plants, especially where the sexual and transovarial transmission rates are low; however information on virulence-transmissibility relationships is required to explain the evolution of a plant virus from an insect virus.

The Effect of Horsfall-Barratt Category Size on the Accuracy and Reliability of Estimates of Pecan Scab Severity

Increasing the durability of crop resistance to plant pathogens is one of the key goals of virulence management. Despite the recognition of the importance of demographic and environmental stochasticity on the dynamics of an epidemic, their effects on the evolution of the pathogen and durability of resistance has not received attention. We formulated a stochastic epidemiological model, based on the Kramer-Moyal expansion of the Master Equation, to investigate how random fluctuations affect the dynamics of an epidemic and how these effects feed through to the evolution of the pathogen and durability of resistance. We focused on two hypotheses: firstly, a previous deterministic model has suggested that the effect of cropping ratio (the proportion of land area occupied by the resistant crop) on the durability of crop resistance is negligible. Increasing the cropping ratio increases the area of uninfected host, but the resistance is more rapidly broken; these two effects counteract each other. We tested the hypothesis that similar counteracting effects would occur when we take account of demographic stochasticity, but found that the durability does depend on the cropping ratio. Secondly, we tested whether a superimposed external source of stochasticity (for example due to environmental variation or to intermittent fungicide application) interacts with the intrinsic demographic fluctuations and how such interaction affects the durability of resistance. We show that in the pathosystem considered here, in general large stochastic fluctuations in epidemics enhance extinction of the pathogen. This is more likely to occur at large cropping ratios and for particular frequencies of the periodic external perturbation (stochastic resonance). The results suggest possible disease control practises by exploiting the natural sources of stochasticity.

Controlling annual weeds in cereals by deploying crop rotation at the landscape scale: Avena sterilis as an example

Pecan scab (Fusicladium effusum) is a destructive pecan disease. Disease assessments may be made using interval-scale-based methods or estimates of severity to the nearest percent area diseased. To explore the effects of rating method-Horsfall-Barratt (H-B) scale estimates versus nearest percent estimates (NPEs)-on the accuracy and reliability of severity estimates over different actual pecan scab severity ranges on fruit valves, raters assessed two cohorts of images with actual area (0 to 6, 6+ to 25%, and 25+ to 75%) diseased. Mean estimated disease within each actual disease severity range varied substantially. Means estimated by NPE within each actual disease severity range were not necessarily good predictors of the H-B scale estimate at <25% severity. H-B estimates by raters most often placed severity in the wrong category compared with actual disease. Measures of bias, accuracy, precision, and agreement using Lins concordance correlation depended on the range of actual severity, with improvements increasing with actual disease severity category (from 0 to 6 through 25+ to 75%); however, the improvement was unaffected by the H-B assessments. Bootstrap analysis indicated that NPEs provided either equally good or more accurate and precise estimate of disease compared with the H-B scale at severities of 25+ to 75%. Inter-rater reliability using NPEs was greater at 25+ to 75% actual disease severity compared with using the H-B scale. Using NPEs compared with the H-B scale will more often result in more precise and accurate estimates of pecan scab severity, particularly when estimating actual disease severities of 25+ to 75%.