Emerging Themes and Approaches in Plant Virus Epidemiology.

Plant diseases caused by viruses share many common features with those caused by other pathogen taxa in terms of the host-pathogen interaction, but there are also distinctive features in epidemiology, most apparent where transmission is by vectors. Consequently, the host-virus-vector-environment interaction presents a continuing challenge in attempts to understand and predict the course of plant virus epidemics. Theoretical concepts, based on the underlying biology, can be expressed in mathematical models and tested through quantitative assessments of epidemics in the field; this remains a goal in understanding why plant virus epidemics occur and how they can be controlled. To this end, this review identifies recent emerging themes and approaches to fill in knowledge gaps in plant virus epidemiology. We review quantitative work on the impact of climatic fluctuations and change on plants, viruses, and vectors under different scenarios where impacts on the individual components of the plant-virus-vector interaction may vary disproportionately; there is a continuing, sometimes discordant, debate on host resistance and tolerance as plant defense mechanisms, including aspects of farmer behavior and attitudes toward disease management that may affect deployment in crops; disentangling host-virus-vector-environment interactions, as these contribute to temporal and spatial disease progress in field populations; computational techniques for estimating epidemiological parameters from field observations; and the use of optimal control analysis to assess disease control options. We end by proposing new challenges and questions in plant virus epidemiology.

Pest categorisation of Gymnosporangium spp. (non-EU).

Following a request from the European Commission, the EFSA Panel on Plant Health performed a pest categorisation of Gymnosporangium spp. (non-EU), a well-defined and distinguishable group of fungal plant pathogens of the family Pucciniaceae affecting woody species. Many different Gymnosporangium species are recognised, of which at least 14 species are considered not to be native in the European Union. All the non-EU Gymnosporangium species are not known to be present in the EU and are regulated in Council Directive 2000/29/EC (Annex IAI) as harmful organisms whose introduction into the EU is banned. Gymnosporangium spp. are biotrophic obligate plant pathogens. These rust fungi are heteroecious as they require Juniperus, Libocedrus, Callitropsis, Chamaecyparis or Cupressus (telial hosts) and rosaceous plants of subfamily Pomoideae (aecial hosts) to complete their life cycle. The pathogens could enter the EU via host plants for planting (including artificially dwarfed woody plants) and cut branches. They could establish in the EU, as climatic conditions are favourable and hosts are common. They would be able to spread following establishment by movement of host plants for planting and cut branches, as well as by natural dispersal. Should Gymnosporangium spp. (non-EU) be introduced in the EU, impacts can be expected in orchards, ornamental trees and nurseries. On telial hosts, these pathogens cause galls on stems, twigs and branches, and fusiform swellings on stems. Foliar infections on aecial hosts may lead to severe defoliations. The main knowledge gap concerns the limited available information on the biology, distribution range and impact of several non-EU Gymnosporangium spp. The criteria assessed by the Panel for consideration of Gymnosporangium spp. (non-EU) as potential quarantine pests are met, while, for regulated non-quarantine pests, the criterion on the pest presence in the EU is not met.

Pest categorisation of Entoleuca mammata.

Following a request from the European Commission, the EFSA Plant Health (PLH) Panel performed a pest categorisation of Entoleuca mammata, a well-defined and distinguishable fungus of the family Xylariaceae native to North America. The species was moved from the genus Hypoxylon to the genus Entoleuca following a revision of the genus. The former species name H. mammatum is used in the Council Directive 2000/29/EC. E. mammata is the causal agent of Hypoxylon canker of quaking aspen (Populus tremuloides) and other poplars (Populus spp.). The pathogen has been reported in 16 EU Member States (MS), without apparent limiting ecoclimatic factors, but mostly (with the exception of Sweden) with a restricted distribution. E. mammata is a protected zone (PZ) quarantine pest (Annex IIB) for Ireland and the UK (Northern Ireland). The main hosts present in the EU (P. tremula, P. nigra and hybrid poplars) are widespread throughout most of the risk assessment area, including the PZ. The main means of spread are wind-blown ascospores, plants for planting and wood with bark. E. mammata is not currently reported to be of significant economic importance in the EU MS where the pathogen is reported, but has been shown to cause significant damage in the USA. Risk reduction options include appropriate site selection for poplar plantations, avoiding wounds, and debarking wood. The main uncertainties concern the distribution of the pathogen in the EU, the susceptibility of cultivated hybrid poplars to the pathogen and thus the potential damage to poplar plantations in the RA area. The criteria assessed by the Panel for consideration as potential PZ quarantine pest are met. The criterion of plants for planting being the main pathway for spread for regulated non-quarantine pests is not met: plants for planting are only one of the means of spread of the pathogen.

Network epidemiology and plant trade networks.

Models of epidemics in complex networks are improving our predictive understanding of infectious disease outbreaks. Nonetheless, applying network theory to plant pathology is still a challenge. This overview summarizes some key developments in network epidemiology that are likely to facilitate its application in the study and management of plant diseases. Recent surveys have provided much-needed datasets on contact patterns and human mobility in social networks, but plant trade networks are still understudied. Human (and plant) mobility levels across the planet are unprecedented-there is thus much potential in the use of network theory by plant health authorities and researchers. Given the directed and hierarchical nature of plant trade networks, there is a need for plant epidemiologists to further develop models based on undirected and homogeneous networks. More realistic plant health scenarios would also be obtained by developing epidemic models in dynamic, rather than static, networks. For plant diseases spread by the horticultural and ornamental trade, there is the challenge of developing spatio-temporal epidemic simulations integrating network data. The use of network theory in plant epidemiology is a promising avenue and could contribute to anticipating and preventing plant health emergencies such as European ash dieback.

SIS along a continuum (SIS(c)) epidemiological modelling and control of diseases on directed trade networks.

Network theory has been applied to many aspects of biosciences, including epidemiology. Most epidemiological models in networks, however, have used the standard assumption of either susceptible or infected individuals. In some cases (e.g. the spread of Phytophthora ramorum in plant trade networks), a continuum in the infection status of nodes can better capture the reality of epidemics in networks. In this paper, a Susceptible-Infected-Susceptible model along a continuum in the infection status (SIS(c)) is presented, using as a case study directed networks and two parameters governing the epidemic process (probability of infection persistence (p(p)) and of infection transmission (p(t)). The previously empirically reported linear epidemic threshold in a plot of p(p) as a function of p(t) (Pautasso and Jeger, 2008) is derived analytically. Also the previously observed negative correlation between the epidemic threshold and the correlation between links in and out of nodes (Moslonka-Lefebvre et al., 2009) is justified analytically. A simple algorithm to calculate the threshold conditions is introduced. Additionally, a control strategy based on targeting market hierarchical categories such as producers, wholesalers and retailers is presented and applied to a realistic reconstruction of the UK horticultural trade network. Finally, various applications (e.g., seed exchange networks, food trade, spread of ideas) and potential refinements of the SIS(c) model are discussed.

Integrating natural and social science perspectives on plant disease risk, management and policy formulation.

Plant diseases threaten both food security and the botanical diversity of natural ecosystems. Substantial research effort is focused on pathogen detection and control, with detailed risk management available for many plant diseases. Risk can be assessed using analytical techniques that account for disease pressure both spatially and temporally. We suggest that such technical assessments of disease risk may not provide an adequate guide to the strategies undertaken by growers and government to manage plant disease. Instead, risk-management strategies need to account more fully for intuitive and normative responses that act to balance conflicting interests between stakeholder organizations concerned with plant diseases within the managed and natural environments. Modes of effective engagement between policy makers and stakeholders are explored in the paper, together with an assessment of such engagement in two case studies of contemporary non-indigenous diseases in one food and in one non-food sector. Finally, a model is proposed for greater integration of stakeholders in policy decisions.

Plant health and global change--some implications for landscape management.

Global change (climate change together with other worldwide anthropogenic processes such as increasing trade, air pollution and urbanization) will affect plant health at the genetic, individual, population and landscape level. Direct effects include ecosystem stress due to natural resources shortage or imbalance. Indirect effects include (i) an increased frequency of natural detrimental phenomena, (ii) an increased pressure due to already present pests and diseases, (iii) the introduction of new invasive species either as a result of an improved suitability of the climatic conditions or as a result of increased trade, and (iv) the human response to global change. In this review, we provide an overview of recent studies on terrestrial plant health in the presence of global change factors. We summarize the links between climate change and some key issues in plant health, including tree mortality, changes in wildfire regimes, biological invasions and the role of genetic diversity for ecosystem resilience. Prediction and management of global change effects are complicated by interactions between globalization, climate and invasive plants and/or pathogens. We summarize practical guidelines for landscape management and draw general conclusions from an expanding body of literature.

Disease spread in small-size directed networks: epidemic threshold, correlation between links to and from nodes, and clustering.

Network epidemiology has mainly focused on large-scale complex networks. It is unclear whether findings of these investigations also apply to networks of small size. This knowledge gap is of relevance for many biological applications, including meta-communities, plant-pollinator interactions and the spread of the oomycete pathogen Phytophthora ramorum in networks of plant nurseries. Moreover, many small-size biological networks are inherently asymmetrical and thus cannot be realistically modelled with undirected networks. We modelled disease spread and establishment in directed networks of 100 and 500 nodes at four levels of connectance in six network structures (local, small-world, random, one-way, uncorrelated, and two-way scale-free networks). The model was based on the probability of infection persistence in a node and of infection transmission between connected nodes. Regardless of the size of the network, the epidemic threshold did not depend on the starting node of infection but was negatively related to the correlation coefficient between in- and out-degree for all structures, unless networks were sparsely connected. In this case clustering played a significant role. For small-size scale-free directed networks to have a lower epidemic threshold than other network structures, there needs to be a positive correlation between number of links to and from nodes. When this correlation is negative (one-way scale-free networks), the epidemic threshold for small-size networks can be higher than in non-scale-free networks. Clustering does not necessarily have an influence on the epidemic threshold if connectance is kept constant. Analyses of the influence of the clustering on the epidemic threshold in directed networks can also be spurious if they do not consider simultaneously the effect of the correlation coefficient between in- and out-degree.

Modelling disease spread and control in networks: implications for plant sciences.

Networks are ubiquitous in natural, technological and social systems. They are of increasing relevance for improved understanding and control of infectious diseases of plants, animals and humans, given the interconnectedness of today's world. Recent modelling work on disease development in complex networks shows: the relative rapidity of pathogen spread in scale-free compared with random networks, unless there is high local clustering; the theoretical absence of an epidemic threshold in scale-free networks of infinite size, which implies that diseases with low infection rates can spread in them, but the emergence of a threshold when realistic features are added to networks (e.g. finite size, household structure or deactivation of links); and the influence on epidemic dynamics of asymmetrical interactions. Models suggest that control of pathogens spreading in scale-free networks should focus on highly connected individuals rather than on mass random immunization. A growing number of empirical applications of network theory in human medicine and animal disease ecology confirm the potential of the approach, and suggest that network thinking could also benefit plant epidemiology and forest pathology, particularly in human-modified pathosystems linked by commercial transport of plant and disease propagules. Potential consequences for the study and management of plant and tree diseases are discussed.