Evolutionary bi-stability in pathogen transmission mode

Many pathogens transmit to new hosts by both infection (horizontal transmission) and transfer to the infected host's offspring (vertical transmission). These two transmission modes require speci®c adap- tations of the pathogen that can be mutually exclusive, resulting in a trade-off between horizontal and vertical transmission. We show that in mathematical models such trade-offs can lead to the simultaneous existence of two evolutionary stable states (evolutionary bi-stability) of allocation of resources to the two modes of transmission. We also show that jumping between evolutionary stable states can be induced by gradual environmental changes. Using quantitative PCR-based estimates of abundance in seed and vege- tative parts, we show that the pathogen of wheat, Phaeosphaeria nodorum, has jumped between two distinct states of transmission mode twice in the past 160 years, which, based on published evidence, we interpret as adaptation to environmental change. The ®nding of evolutionary bi-stability has impli- cations for human, animal and other plant diseases. An ill-judged change in a disease control programme could cause the pathogen to evolve a new, and possibly more damaging, combination of transmission modes. Similarly, environmental changes can shift the balance between transmission modes, with adverse effects on human, animal and plant health.

Modeling of relationships between weather and Septoria tritici epidemics on winter wheat: A critical approach

Two models for predicting Septoria tritici on winter wheat (cv. Ri-band) were developed using a program based on an iterative search of correlations between disease severity and weather. Data from four consecutive cropping seasons (1993/94 until 1996/97) at nine sites throughout England were used. A qualitative model predicted the presence or absence of Septoria tritici (at a 5% severity threshold within the top three leaf layers) using winter temperature (January/February) and wind speed to about the first node detectable growth stage. For sites above the disease threshold, a quantitative model predicted severity of Septoria tritici using rainfall during stern elongation. A test statistic was derived to test the validity of the iterative search used to obtain both models. This statistic was used in combination with bootstrap analyses in which the search program was rerun using weather data from previous years, therefore uncorrelated with the disease data, to investigate how likely correlations such as the ones found in our models would have been in the absence of genuine relationships.

A model for the evolution of pathogen-induced leaf shedding

A size-structured plant population model is developed to study the evolution of pathogen-induced leaf shedding under various environmental conditions. The evolutionary stable strategy (ESS) of the leaf shedding rate is determined for two scenarios: i) a constant leaf shedding strategy and ii) an infection load driven leaf shedding strategy. The model predicts that ESS leaf shedding rates increase with nutrient availability. No effect of plant density on the ESS leaf shedding rate is found even though disease severity increases with plant density. When auto-infection, that is increased infection due to spores produced on the plant itself, plays a key role in further disease increase on the plant, shedding leaves removes disease that would otherwise contribute to disease increase on the plant itself. Consequently leaf shedding responses to infections may evolve. When external infection, that is infection due to immigrant spores, is the key determinant, shedding a leaf does not reduce the force of infection on the leaf shedding plant. In this case leaf shedding will not evolve. Under a low external disease pressure adopting an infection driven leaf shedding strategy is more efficient than adopting a constant leaf shedding strategy, since a plant adopting an infection driven leaf shedding strategy does not shed any leaves in the absence of infection, even when leaf shedding rates are high. A plant adopting a constant leaf shedding rate sheds the same amount of leaves regardless of the presence of infection. Based on the results we develop two hypotheses that can be tested if the appropriate plant material is available.

Evaluation of a predictive model for Mycosphaerella graminicola for economic and environmental benefits

A method was developed to evaluate crop disease predictive models for their economic and environmental benefits. Benefits were quantified as the value of a prediction measured by costs saved and fungicide dose saved. The value of prediction was defined as the net gain made by using predictions, measured as the difference between a scenario where predictions are available and used and a scenario without prediction. Comparable 'with' and 'without' scenarios were created with the use of risk levels. These risk levels were derived from a probability distribution fitted to observed disease severities. These distributions were used to calculate the probability that a certain disease induced economic loss was incurred. The method was exemplified by using it to evaluate a model developed for Mycosphaerella graminicola risk prediction. Based on the value of prediction, the tested model may have economic and environmental benefits to growers if used to guide treatment decisions on resistant cultivars. It is shown that the value of prediction measured by fungicide dose saved and costs saved is constant with the risk level. The model could also be used to evaluate similar crop disease predictive models.

A predictive model for early-warning of Septoria leaf blotch on winter wheat

Disease-weather relationships influencing Septoria leaf blotch (SLB) preceding growth stage (GS) 31 were identified using data from 12 sites in the UK covering 8 years. Based on these relationships, an early-warning predictive model for SLB on winter wheat was formulated to predict the occurrence of a damaging epidemic (defined as disease severity of 5% or > 5% on the top three leaf layers). The final model was based on accumulated rain > 3 mm in the 80-day period preceding GS 31 (roughly from early-February to the end of April) and accumulated minimum temperature with a 0A degrees C base in the 50-day period starting from 120 days preceding GS 31 (approximately January and February). The model was validated on an independent data set on which the prediction accuracy was influenced by cultivar resistance. Over all observations, the model had a true positive proportion of 0.61, a true negative proportion of 0.73, a sensitivity of 0.83, and a specificity of 0.18. True negative proportion increased to 0.85 for resistant cultivars and decreased to 0.50 for susceptible cultivars. Potential fungicide savings are most likely to be made with resistant cultivars, but such benefits would need to be identified with an in-depth evaluation.

Disease-weather relationships for powdery mildew and yellow rust on winter wheat

Key weather factors determining the occurrence and severity of powdery mildew and yellow rust epidemics on winter wheat were identified. Empirical models were formulated to qualitatively predict a damaging epidemic (>5% severity) and quantitatively predict the disease severity given a damaging epidemic occurred. The disease data used was from field experiments at 12 locations in the UK covering the period from 1994 to 2002 with matching data from weather stations within a 5 km range. Wind in December to February was the most influential factor for a damaging epidemic of powdery mildew. Disease severity was best identified by a model with temperature, humidity, and rain in April to June. For yellow rust, the temperature in February to June was the most influential factor for a damaging epidemic as well as for disease severity. The qualitative models identified favorable circumstances for damaging epidemics, but damaging epidemics did not always occur in such circumstances, probably due to other factors such as the availability of initial inoculum and cultivar resistance.

Apical leaf necrosis as a defence mechanism against pathogen attack: effects of high nutrient availability on onset and rate of necrosis

An outdoor experiment was conducted to increase understanding of apical leaf necrosis in the presence of pathogen infection. Holcus lanatus seeds and Puccinia coronata spores were collected from two adjacent and otherwise similar habitats with differing long-term N fertilization levels. After inoculation, disease and necrosis dynamics were observed during the plant growing seasons of 2003 and 2006. In both years high nutrient availability resulted in earlier disease onset, a higher pathogen population growth rate, earlier physiological apical leaf necrosis onset and a reduced time between disease onset and apical leaf necrosis onset. Necrosis rate was shown to be independent of nutrient availability. The results showed that in these nutrient-rich habitats H. lanatus plants adopted necrosis mechanisms which wasted more nutrients. There was some indication that these necrosis mechanisms were subject to local selection pressures, but these results were not conclusive. The findings of this study are consistent with apical leaf necrosis being an evolved defence mechanism.

Apical leaf necrosis and leaf nitrogen dynamics in diseased leaves: a model study

Apical leaf necrosis is a physiological process related to nitrogen (N) dynamics in the leaf. Pathogens use leaf nutrients and can thus accelerate this physiological apical necrosis. This process differs from necrosis occurring around pathogen lesions (lesion-induced necrosis), which is a direct result of the interaction between pathogen hyphae and leaf cells. This paper primarily concentrates on apical necrosis, only incorporating lesion-induced necrosis by necessity. The relationship between pathogen dynamics and physiological apical leaf necrosis is modelled through leaf nitrogen dynamics. The specific case of Puccinia triticina infections on Triticum aestivum flag leaves is studied. In the model, conversion of indirectly available N in the form of, for example, leaf cell proteins (N-2(t)) into directly available N (N-1(t), i.e. the form of N that can directly be used by either pathogen or plant sinks) results in apical necrosis. The model reproduces observed trends of disease severity, apical necrosis and green leaf area (GLA) and leaf N dynamics of uninfected and infected leaves. Decreasing the initial amount of directly available N results in earlier necrosis onset and longer necrosis duration. Decreasing the initial amount of indirectly available N, has no effect on necrosis onset and shortens necrosis duration. The model could be used to develop hypotheses on how the disease-GLA relation affects yield loss, which can be tested experimentally. Upon incorporation into crop simulation models, the model might provide a tool to more accurately estimate crop yield and effects of disease management strategies in crops sensitive to fungal pathogens.

A model for the evolution of pathogen-induced leaf shedding

A size-structured plant population model is developed to study the evolution of pathogen-induced leaf shedding under various environmental conditions. The evolutionary stable strategy (ESS) of the leaf shedding rate is determined for two scenarios: i) a constant leaf shedding strategy and ii) an infection load driven leaf shedding strategy. The model predicts that ESS leaf shedding rates increase with nutrient availability. No effect of plant density on the ESS leaf shedding rate is found even though disease severity increases with plant density. When auto-infection, that is increased infection due to spores produced on the plant itself, plays a key role in further disease increase on the plant, shedding leaves removes disease that would otherwise contribute to disease increase on the plant itself. Consequently leaf shedding responses to infections may evolve. When external infection, that is infection due to immigrant spores, is the key determinant, shedding a leaf does not reduce the force of infection on the leaf shedding plant. In this case leaf shedding will not evolve. Under a low external disease pressure adopting an infection driven leaf shedding strategy is more efficient than adopting a constant leaf shedding strategy, since a plant adopting an infection driven leaf shedding strategy does not shed any leaves in the absence of infection, even when leaf shedding rates are high. A plant adopting a constant leaf shedding rate sheds the same amount of leaves regardless of the presence of infection. Based on the results we develop two hypotheses that can be tested if the appropriate plant material is available.

The dose rate debate: does the risk of fungicide resistance increase or decrease with dose?

This paper reviews the evidence relating to the question: does the risk of fungicide resistance increase or decrease with dose? The development of fungicide resistance progresses through three key phases. During the ‘emergence phase’ the resistant strain has to arise through mutation and invasion. During the subsequent ‘selection phase’, the resistant strain is present in the pathogen population and the fraction of the pathogen population carrying the resistance increases due to the selection pressure caused by the fungicide. During the final phase of ‘adjustment’, the dose or choice of fungicide may need to be changed to maintain effective control over a pathogen population where resistance has developed to intermediate levels. Emergence phase: no experimental publications and only one model study report on the emergence phase, and we conclude that work in this area is needed. Selection phase: all the published experimental work, and virtually all model studies, relate to the selection phase. Seven peer reviewed and four non-peer reviewed publications report experimental evidence. All show increased selection for fungicide resistance with increased fungicide dose, except for one peer reviewed publication that does not detect any selection irrespective of dose and one conference proceedings publication which claims evidence for increased selection at a lower dose. In the mathematical models published, no evidence has been found that a lower dose could lead to a higher risk of fungicide resistance selection. We discuss areas of the dose rate debate that need further study. These include further work on pathogen-fungicide combinations where the pathogen develops partial resistance to the fungicide and work on the emergence phase.

Accounting for the economic risk, caused by variation in disease severity, in fungicide dose decisions: exemplified for Mycosphaerella graminicola on winter wheat

A method is presented to calculate economic optimum fungicide doses accounting for the risk-aversion of growers responding to variability in disease severity between crops. Simple dose-response and disease-yield loss functions are used to estimate net disease-related costs (fungicide cost, plus disease-induced yield loss) as a function of dose and untreated severity. With fairly general assumptions about the shapes of the probability distribution of disease severity and the other functions involved, we show that a choice of fungicide dose which minimises net costs on average across seasons results in occasional large net costs caused by inadequate control in high disease seasons. This may be unacceptable to a grower with limited capital. A risk-averse grower can choose to reduce the size and frequency of such losses by applying a higher dose as insurance. For example, a grower may decide to accept ‘high loss’ years one year in ten or one year in twenty (i.e. specifying a proportion of years in which disease severity and net costs will be above a specified level). Our analysis shows that taking into account disease severity variation and risk-aversion will usually increase the dose applied by an economically rational grower. The analysis is illustrated with data on septoria tritici leaf blotch of wheat caused by Mycosphaerella graminicola. Observations from untreated field plots at sites across England over three years were used to estimate the probability distribution of disease severities at mid-grain filling. In the absence of a fully reliable disease forecasting scheme, reducing the frequency of ‘high loss’ years requires substantially higher doses to be applied to all crops. Disease resistant cultivars reduce both the optimal dose at all levels of risk and the disease-related costs at all doses.

Effects of plant pathogens on population dynamics and community composition in grassland ecosystems: two case studies

Grassland ecosystems comprise a major portion of the earth’s terrestrial surface, ranging from high-input cultivated monocultures or simple species mixtures to relatively unmanaged but dynamic systems. Plant pathogens are a component of these systems with their impact dependent on many interacting factors, including grassland species population dynamics and community composition, the topics covered in this paper. Plant pathogens are affected by these interactions and also act reciprocally by modifying their nature. We review these features of disease in grasslands and then introduce the 150-year long-term Park Grass Experiment (PGE) at Rothamsted Research in the UK. We then consider in detail two plant-pathogen systems present in the PGE, Tragopogon pratensis-Puccinia hysterium and Holcus lanata-Puccinia coronata. These two systems have very different life history characteristics: the first, a biennial member of the Asteraceae infected by its host-specific, systemic rust; the second, a perennial grass infected by a host-non-specific rust. We illustrate how observational, experimental and modelling studies can contribute to a better understanding of population dynamics, competitive interactions and evolutionary outcomes. With Tragopogon pratensis-Puccinia hysterium, characterised as an “outbreak” species in the PGE, we show that pathogen-induced mortality is unlikely to be involved in host population regulation; and that the presence of even a short-lived seed-bank can affect the qualitative outcomes of the host-pathogen dynamics. With Holcus lanata-Puccinia coronata, we show how nutrient conditions can affect adaptation in terms of host defence mechanisms, and that co-existence of competing species affected by a common generalist pathogen is unlikely.

Chess endgames: data and strategy

While Nalimov’s endgame tables for Western Chess are the most used today, their Depth-to-Mate metric is not the only one and not the most effective in use. The authors have developed and used new programs to create tables to alternative metrics and recommend better strategies for endgame play.