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Stem rust, or black rust, of wheat, caused by Puccinia graminis f. sp. tritici, has recently re-emerged in several parts of the world, with epidemics occurring in eastern Africa, as well as northern and southern Europe. Damage mechanisms from disease dynamically affect the physiology of the crop as it grows and develops, and as the epidemic progresses, leading to yield losses in the stem rust-diseased wheat stand. Process-based agrophysiological models that include disease-induced damage mechanisms can help to better understand the physiological processes leading to yield losses, and to inform strategic decisions such as breeding strategies. Such models have not been developed for wheat stem rust so far. Two damage mechanisms for stem rust, light stealing and assimilate diversion, were incorporated in the agrophysiological simulation model WHEATPEST. The model, tested from experimental field data retrieved from the literature, provides a satisfactory representation of the system, although consistently underestimates relative yield losses by about 6.9%, resulting in relative yield losses between 17% and 56%. Analyses highlight the importance of the diversion of assimilates toward the pathogen in the magnitude of yield loss. Considering only the reduction of green leaf area would underestimate damage from stem rust by at least threefold. The analysis also shows the importance of the dynamic interplay between disease and crop growth, especially the dynamics of leaf area, on yield loss. Directions to consider additional damage mechanisms are proposed, and perspectives for future research, especially in relation to plant breeding strategies under climate change, are offered.

The cultivation of grape varieties with partial resistance to disease may become an important component for disease management in the future. The impact of partial resistance on downy mildew epidemics according to its components have not been explored so far. This work aims to model, understand, and quantitatively analyse the effect of partial resistance against dual disease epidemics (foliage and clusters) caused by Plasmopara viticola, and rank the efficiency of different resistance components in disease suppression. We use an epidemiological simulation model to integrate the effect of four components of partial resistance, expressed as relative resistance parameters, i.e. infection efficiency (RRIE), latency period (RRLP), sporulation (RRSP), and infectious period (RRIP). Both the individual and combined effect of these components of resistance on downy mildew epidemics are evaluated through a sensitivity analysis. A comparison of simulation runs in different scenarios of disease conduciveness using experimental measurements of components of partial resistance for 16 different grapevine varieties is also performed. Increasing values of RR parameters led to a suppression of disease progress on foliage. The strongest reduction of epidemics on foliage is generated by increases in RRIE, followed by RRSP, RRIP, and last by RRLP. The effect of partial resistance on epidemics is more conspicuous in a scenario of limited disease conduciveness. The strongest suppressive effect of simulated epidemics on clusters is associated with RRIE, and the lowest effect with RRLP, with similar effects of increasing values of RRIP and RRSP. The use of experimentally measured relative resistance parameters to run simulated epidemics shows a reduction of the area under the disease progress curve from 4 × 105 (on a susceptible reference grapevine variety) to 4 × 102 (on cv. Bronner), i.e. a reduction of disease by 1000. The simulation of the varietal effect in intermediate and less favour

A process-based simulation model for the grapevine-downy mildew pathosystem was developed in order to quantitatively synthesize the literature available and to provide a tool to guide strategic decisions for disease management. The model includes: i) the main processes involved in the disease dual epidemics on leaves and clusters, from inoculum mobilisation to disease multiplication on foliage, and to infection of clusters; and ii) host dynamics, i.e. crop development, growth, and physiological and disease-induced senescence. A numerical evaluation was performed to investigate the response of the model to changes of the main epidemiological parameters, i.e. the basic infection rate corrected for the removals (RcOPT), the duration of latency period (LP), the duration of infectious period (IP), and the rate of primary infections (P). Increasing values of RcOPT and IP, and decreasing values of LP resulted in a faster increase of the epidemic on both foliage and clusters, while decreasing values of P delayed epidemics. The simulated dynamics of epidemics on foliage and clusters conformed to patterns of dual epidemics observed for downy mildew. The model can be useful for investigating the effect of strategic disease management tools such as the use of resistant varieties or to investigate the behaviour of the pathosystem under scenarios of climate change.

Scenario analysis constitutes a useful approach to synthesize knowledge and derive hypotheses in the case of complex systems that are documented with mainly qualitative or very diverse information. In this article, a framework for scenario analysis is designed and then, applied to global wheat health within a timeframe from today to 2050. Scenario analysis entails the choice of settings, the definition of scenarios of change, and the analysis of outcomes of these scenarios in the chosen settings. Three idealized agrosystems, representing a large fraction of the global diversity of wheat-based agrosystems, are considered, which represent the settings of the analysis. Several components of global changes are considered in their consequences on global wheat health: climate change and climate variability, nitrogen fertilizer use, tillage, crop rotation, pesticide use, and the deployment of host plant resistances. Each idealized agrosystem is associated with a scenario of change that considers first, a production situation and its dynamics, and second, the impacts of the evolving production situation on the evolution of crop health. Crop health is represented by six functional groups of wheat pathogens: the pathogens associated with Fusarium head blight; biotrophic fungi, Septoria-like fungi, necrotrophic fungi, soilborne pathogens, and insect-transmitted viruses. The analysis of scenario outcomes is conducted along a risk-analytical pattern, which involves risk probabilities represented by categorized probability levels of disease epidemics, and risk magnitudes represented by categorized levels of crop losses resulting from these levels of epidemics within each production situation. The results from this scenario analysis suggest an overall increase of risk probabilities and magnitudes in the three idealized agrosystems. Changes in risk probability or magnitude however vary with the agrosystem and the functional groups of pathogens. We discuss the effects of global chan

The literature on the importance of plant pathogens sometimes emphasizes their possible role in historical food shortages and even in famines. Aside from such major crises, plant pathogens should also be seen as important reducers of crop performances, with impacts on system sustainability, from the ecological, agronomical, social, and economic standpoints – all contributing ultimately to affecting food security. These views need reconciliation in order to produce a clearer picture of the multidimensional effects of plant disease epidemics. Such a picture is needed for disease management today, but would also be useful for future policies. This article attempts to develop a framework that would enable assessment of the impacts of plant diseases, referred collectively to as crop health, on food security via its components. We have combined three different existing definitions of food security in order to develop a framework consisting of the following six components: (1) Availability. Primary production; (2) Availability. Import - Stockpiles; (3) Access. Physical and supply chain; (4) Access. Economic; (5) Stability of food availability; (6) Utility-Safety-Quality-Nutritive value. In this framework, components of food security are combined with three attributes of production situations: the nature of the considered crop (i.e. food- or non-food), the structure of farms (i.e. subsistence or commercial), and the structure of markets (i.e. weakly organized and local, to strongly organized and globalized). The resulting matrix: [Food security components] × [Attributes of production situations] provides a framework where the impacts of chronic, acute, and emerging plant disease epidemics on food security can be examined. We propose that, given the number of components and interactions at play, a systems modelling approach is required to address the functioning of food systems exposed to plant disease risks. This approach would have application in both the management of the

Modelling the effects of plant diseases and pests on crop performance, starting with crop yield, is an important new challenge MACSUR wants to address. We have established a small "Pest and Disease" group within MACSUR, where we address this question, with particular emphasis on wheat and grapevine. In the case of wheat, a reference data set from Denmark is being used as a key reference set for wheat - septoria tritici blotch - leaf rust interaction. In a first step an ensemble of seven wheat growth models of different complexity implement defined mechanisms for damages through pest and diseases using field data of a "pest-free" treatment for crop model calibration and idealised (temporal) patterns of injuries represented by simplified disease progress curves. In a second step field data of non-protected field plots are provided together with disease severity data to test simulations of real disease effects on crop yield loss against observed data. In parallel, we collected information on available data for pest and disease impacts by a questionnaire to evaluate their suitability for crop growth as well as for pest and disease modelling. We shall report our results in this exercise, and outline the approach we envision to (i) continue this work on wheat, and (ii) expand it to other crops such as grapevine.

PR, IFPRI3; ISI; CRP2; A Ensuring Sustainable food production; HarvestChoice, EPTD; PIM, CGIAR Research Program on Policies, Institutions, and Markets (PIM)

Policy makers and researchers need to develop long-term priorities using reliable, quantitative tools to assess the risks associated with plant diseases over a range of plant pathogens and over space. EPIWHEAT is a generic simulation model designed to analyse potential disease epidemics in wheat, i.e., epidemics that depend only on the physical environment, and that are not constrained by any disease control. The model is developed on a core structure involving healthy, latent, infectious, and removed sites, and accounts for lesion expansion. It simulates in a simple way host dynamics (growth and senescence). The model involves as few parameters as possible, and a few driving functions. Here, EPIWHEAT is populated with parameters for brown rust (leaf rust; Puccinia triticina) and Septoria tritici blotch (Zymoseptoria tritici). Simulated epidemics are compared to observations at the field, national (France), and European scales. The model appears to represent a sound basis for predicting potential epidemics of wheat foliar diseases at large scales. Areas for model development are documented and discussed. EPIWHEAT appears to provide a simple, generic, transparent, flexible, and reliable platform to modelling potential epidemics caused by leaf pathogens of wheat.

This review addresses four principles on which sustainable pest management in rice is to be grounded. The goal of modern pest management is to contribute to agricultural sustainability, with its different facets (food security, balanced relations between man-made and natural ecosystems, conservation of ecosystem services). The four principles are considered in turn within the classic Human - Pest - Environment - Crop framework. Biodiversity, as a first principle, is fundamental to the functioning of food webs. The second principle, host plant resistance (HPR), is a pro-poor, and an often highly efficient element that critically contributes to sustainable crop protection. HPR needs to account for the other principles in its implementation in order to sustain durable resistances over time and space. The third principle, landscape ecology, encompasses inter-linked levels of spatial hierarchies governing the performance of systems (pests, host plants, plant genotypic make-ups, plant and crop physiology, trophic chains, and the physical environment). The fourth principle, hierarchies, concerns the different levels of hierarchy in a landscape, from biological to social. This principle concerns the very fabric of human societies, which involve perceptions, knowledge, and attitudes, which translate into decision-making at several scales, from the individual farmer to policy-makers. This principle thus addresses psychological, policy, and decision-making dimensions. In this review, all organisms that may be harmful to rice are referred to as 'pests', including pathogens and animal pests. We do not address all rice pests, but proceed through a few key examples, nor do we enter into the specifics of pest management strategies covering the range of rice production situations. This is because of the very large range of rice pests, of the corresponding diversity of rice production situations worldwide, of the unprecedented rate of diversification of rice production in response to