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Vector-transmitted diseases of plants have had devastating effects on agricultural production worldwide, resulting in drastic reductions in yield for crops such as cotton, soybean, tomato, and cassava. Plant-vector-virus models with continuous replanting are investigated in terms of the effects of selection of cuttings, roguing, and insecticide use on disease prevalence in plants. Previous models are extended to include two replanting strategies: frequencyreplanting and abundance-replanting. In frequency-replanting, replanting of infected cuttings depends on the selection frequency parameter ε , whereas in abundance-replanting, replanting depends on plant abundance via a selection rate parameter also denoted as ε.  The two models are analysed and new thresholds for disease elimination are defined for each model. Parameter values for cassava, whiteflies, and African cassava mosaic virus serve as a case study. A numerical sensitivity analysis illustrates how the equilibrium densities of healthy and infected plants vary with parameter values. Optimal control theory is used to investigate the effects of roguing and insecticide use with a goal of maximizing the healthy plants that are harvested. Differences in the control strategies in the two models are seen for large values of ε.  Also, the combined strategy of roguing and insecticide use performs better than a single control.

Effective use of biocontrol agents (BCAs) is a potentially important component of sustainable agriculture; recently, there has been a trend for combined use of several BCAs, with an expectation of synergistic interactions among them. A previous numerical study suggested that, under homogenous conditions in which two BCAs occupied the same host tissue as the pathogen, combined use of two BCAs with different biocontrol mechanisms resulted, in most cases, in efficacies similar to using the more efficacious one alone; this result is consistent with published experimental results. The present study investigates whether combined use of a mycoparasitic and a competitive BCA leads to greater efficacy than that expected when the model is modified to allow for fluctuating temperature regimes and the effects of temperature on the pathogen and BCAs. Within the range of parameter values considered, combined use of two BCAs is shown to be less effective than that expected under the assumption of Bliss independence, and to result in a level of efficacy similar to that achieved by the more efficacious component used alone, indicating antagonistic interactions between the two BCAs. Nevertheless, combined use of two BCAs resulted in a slightly longer delay in epidemic development than did individual use of BCAs. Stochastic variability in simulated hourly temperatures did not result in a high level of variability in efficacy among replicates; nevertheless, the among-replicate variability appeared to be greater for the combined use of BCAs than for individual BCAs used alone. In contrast, there were greater effects of varying BCA-temperature relationships and application time (reflected in the temperature profile) on efficacy, suggesting the importance of characterizing the relationship between BCA activity and environmental conditions in future research.

A previously published generic mathematic model has been used in a numerical study to understand the dynamics of foliar pathogens in relation to mechanisms, and timing and coverage of biocontrol agent (BCA) applications. With the model parameter values used, it was demonstrated that a BCA possessing either competition or induced resistance as the main mechanism of biological control was more effective in reducing disease development than a BCA with either mycoparasitism or antibiosis as its mechanism. Application coverage, ranging from 50 to 90%, had little effect on biocontrol efficacy, particularly for a BCA with competition and induced resistance as the main mechanism of biocontrol. Conversely, delayed application of BCA had more profound effects on biocontrol efficacy for those with competition or induced resistance as their main mechanism than those with mycoparasitism and antibiosis. Biocontrol efficacy was greatest for a single BCA combining competition with mycoparasitism or antibiosis. The efficacy for a single BCA combining induced resistance with competition critically depended on application time; the efficacy was greatly reduced for delayed applications. The present study suggests that development of an effective strategy for BCA application is critically dependent upon our quantitative understanding of several key biocontrol processes and their interactions. Without reliable quantitative estimation of these processes, it is impossible to make quantitative predictions about biological control and hence to optimize BCA application strategies.

We have developed a generic modelling framework to understand the dynamics of foliar pathogen and biocontrol agent (BCA) populations in order to predict the likelihood of successful biocontrol in relation to the mechanisms involved. The model considers biocontrol systems for foliar pathogens only and, although it is most applicable to fungal BCA systems, does not address a specific biocontrol system. Four biocontrol mechanisms (competition, antibiosis, mycoparasitism and induced resistance) were included within the model rubric. Because of the wide range of mechanisms involved we use Trichoderma/Botrytis as an exemplar system. Qualitative analysis of the model showed that the rates of a BCA colonising diseased and/or healthy plant tissues and the time that the BCA remains active are two of the more important factors in determining the final outcome of a biocontrol system. Further evaluation of the model indicated that the dynamic path to the steady-state population levels also depends critically on other parameters such as the host-pathogen infection rate. In principle, the model can be extended to include other potential mechanisms, including spatio-temporal heterogeneity, fungicide effects, non-fungal BCA and strategies for BCA application, although with a cost in model tractability and ease of interpretation.

Here, a quasi-steady-state approximation was used to simplify a mathematical model for fungal growth in carbon-limiting systems, and this was fitted to growth dynamics of the soil-borne plant pathogen and saprotroph Rhizoctonia solani. The model identified a criterion for invasion into carbon-limited environments with two characteristics driving fungal growth, namely the carbon decomposition rate and a measure of carbon use efficiency. The dynamics of fungal spread through a population of sites with either low (0.0074 mg) or high (0.016 mg) carbon content were well described by the simplified model with faster colonization for the carbon-rich environment. Rhizoctonia solani responded to a lower carbon availability by increasing the carbon use efficiency and the carbon decomposition rate following colonization. The results are discussed in relation to fungal invasion thresholds in terms of carbon nutrition.

Viral diseases are a key constraint in the production of staple food crops in lesser developed countries. New and improved disease control methods are developed and implemented without consideration of the selective pressure they impose on the virus. In this paper, we analyse the evolution of within-plant virus titre as a response to the implementation of a range of disease control methods. We show that the development of new and improved disease control methods for viral diseases of vegetatively propagated staple food crops ought to take the evolutionary responses of the virus into consideration. Not doing so leads to a risk of failure, which can result in considerable economic losses and increased poverty. Specifically in vitro propagation, diagnostics and breeding methods carry a risk of failure due to the selection for virus strains that build up a high within-plant virus titre. For vegetatively propagated crops, sanitation by roguing has a low risk of failure owing to its combination of selecting for low virus titre strains as well as increasing healthy crop density.

In a previous paper, we proposed a fungal growth model (Lamour et al., 2001 IMA J. Math. Appl. Med. Biol., 17, 329-346), describing the colonization and decomposition of substrate, subsequent uptake of nutrients, and incorporation into fungal biomass, and performed an overall-steady-state analysis. In this paper we assume that where nutrient dynamics are much faster than the dynamics of fungal biomass and substrate, the system will reach a quasi-steady-state relatively quickly. We show how the quasi-steady-state approximation is a simplification of the full fungal growth model. We then derive an explicit fungal invasion criterion, which was not possible for the full model, and characterize parameter domains for invasion and extinction. Importantly, the fungal invasion criterion takes two forms: one for systems where carbon is limiting, another for systems where nitrogen is limiting. We focus attention on what happens in the short term immediately following the introduction of a fungus to a fungal-free system by analysing the stability of the trivial steady state, and then check numerically whether the fungus is able to persist. The derived invasion criterion was found to be valid also for the full model. Knowledge of the factors that determine invasion is essential to an understanding of fungal dynamics. The simplified model allows the invasion criterion to be tested with experimental data.

The material used for propagation and planting of many perennial crop plants is derived from vegetative cuttings which are first multiplied in a nursery. This situation was modelled to analyse the dynamics of a plant virus epidemic in a combined nursery-plantation system and the comparative effects of disease management activities in the plantation and in the nursery. The plant populations were partitioned into healthy and diseased categories and were linked according to basic SI models of disease transmission. Removal of diseased plants and replanting operations in both the plantation and nursery were included in the model and two variants were analysed in which mother plants (from which cuttings were taken) remained in the plantation or were harvested. The former is shown to be the limiting case for a large number of cuttings per plant. A criterion was derived for the invasion of disease into a healthy combined system. This consisted of four additive terms: the basic reproductive numbers of disease in the plantation alone and in the nursery alone, and two terms describing the cycling of diseased material between the plantation and nursery. Disease can still invade the system with basic reproductive numbers in the plantation or in the nursery less than 1 depending on the magnitude of cycling. Under some conditions only diseased plants remain in the plantation and nursery. For such a case a criterion was derived for the invasion of healthy plants into a fully diseased system. This depended on replanting rates in the plantation and nursery, and infection, mortality and removal rates of healthy plants.

Growth of soil-borne fungi is poorly described and understood, largely because non-destructive observations on hyphae in soil are difficult to make. Mathematical modelling can help in the understanding of fungal growth. Except for a model by Paustian & Schnürer (1987a), fungal growth models do not consider carbon and nitrogen contents of the supplied substrate, although these nutrients have considerable effects on hyphal extension in soil. We introduce a fungal growth model in relation to soil organic matter decomposition dealing with the detailed dynamics of carbon and nitrogen. Substrate with a certain carbon : nitrogen ratio is supplied at a constant rate, broken down and then taken up by fungal mycelium. The nutrients are first stored internally in metabolic pools and then incorporated into structural fungal biomass. Standard mathematical procedures were used to obtain overall-steady states of the variables (implicitly from a cubic equation) and the conditions for existence. Numerical computations for a wide range of parameter combinations show that at most one solution for the steady state is biologically meaningful, specified by the conditions for existence. These conditions specify a constraint, namely that the 'energy' (in terms of carbon) invested in breakdown of substrate should be less than the 'energy' resulting from breakdown of substrate, leading to a positive carbon balance. The biological interpretation of the conditions for existence is that for growth the 'energy' necessary for production of structural fungal biomass and for maintenance should be less than the mentioned positive carbon balance in the situation where all substrate is colonized. In summary, the analysis of this complicated fungal growth model gave results with a clear biological interpretation.

Growth of soil-borne fungi is poorly described and understood, largely because non-destructive observations on hyphae in soil are difficult to make. Mathematical modelling can help in the understanding of fungal growth. Except for a model by Paustian & Sch urer (1987a), fungal growth models do not consider carbon and nitrogen contents of the supplied substrate, although these nutrients have considerable effects on hyphal extension in soil. We introduce a fungal growth model in relation to soil organic matter decomposition dealing with the detailed dynamics of carbon and nitrogen. Substrate with a certain carbon : nitrogen ratio is supplied at a constant rate, broken down and then taken up by fungal mycelium. The nutrients are first stored internally in metabolic pools and then incorporated into structural fungal biomass. Standard mathematical procedures were used to obtain overall-steady states of the variables (implicitly from a cubic equation) and the conditions for existence. Numerical computations for a wide range of parameter combinations show that at most one solution for the steady state is biologically meaningful, specified by the conditions for existence. These conditions specify a constraint, namely that the 'energy' (in terms of carbon) invested in breakdown of substrate should be less than the 'energy' resulting from breakdown of substrate, leading to a positive carbon balance. The biological interpretation of the conditions for existence is that for growth the 'energy' necessary for production of structural fungal biomass and for maintenance should be less than the mentioned positive carbon balance in the situation where all substrate is colonized. In summary, the analysis of this complicated fungal growth model gave results with a clear biological interpretation.