Understanding plant diseases across scales – the role of epidemiology

Food security and safety depends to a large extent on the crops we grow, and plant health is a key factor in securing our livelihood. FAO estimates that up to 40% of food crops annually are lost to plant pest including diseases. For disease to occur, a pathogen must be able to infect a susceptible host plant under suitable environmental conditions. In plant disease epidemiology we study the development of diseases in plant populations: how the pathogens spread, pathogen evolution and the impact of disease management. The ultimate goal is to limit disease occurrence and spread in order to secure high yields of good quality in our managed cropping systems. To reach this goal, we need to understand the patterns and mechanisms of pathogen population dynamics across scales, ranging from pathogen’s interaction with particular plant hosts, to pathogen movement across the globe. All scales are interlinked and changes at one level will impact the other scales. In my presentation, I will use a few examples from my own research to illustrate different scales within plant disease epidemiology: from the genetic regulation in the interaction between a pathogen and its host during the infection process, how this changes the pathogen populations at larger scales and how this impacts the disease spread and development in the field, in a region or even across continents.

Our challenge is to create sustainable cropping systems. I will elaborate on how I aim to develop my methodology and theoretical framework in plant disease epidemiology in order to improve our understanding of plant diseases and to identify new ways to limit their impact. Future sustainable disease management will depend on our ability to understand the complexity of pathogen impact and plant diseases in relation to crop diversity, agricultural practices and landscape ecology. One way of achieving this goal is to combine knowledge from different disciplines using network analysis. In plant disease epidemiology, network analysis can be used to integrate biological information with other types of information. In my research, one of my aims is to uncover information about population structure of pathogens using molecular methods, and combine this information with other relevant disciplines such as social sciences or economics that studies choice of management decision at farm level or trade patterns. This integration of information can reveal patterns of disease development and spread to optimize plant disease management. This creates opportunity to reveal new solutions where plant pathology knowledge is incorporated in the design of resilient and sustainable cropping systems.