Studying Wild Plant Pathosystems to Understand Crop Plant Pathosystems: Status, Gaps, Challenges, and Perspectives.

Phytopathology is a highly complex scientific discipline. Initially, its focus was on the study of plant-pathogen interactions in agricultural and forestry production systems. Host-pathogen interactions in natural plant communities were generally overlooked until the 1970s when plant pathologists and evolutionary biologists started to take an interest in these interactions, and their dynamics in natural plant populations, communities, and ecosystems. This article introduces the general principles of plant pathosystems, provides a basic critical overview of current knowledge of host-pathogen interactions in natural plant pathosystems, and shows how this knowledge is important for future developments in plant pathology especially as it applies in cropping systems, ecology, and evolutionary biology. Plant pathosystems can be further divided according to the structure and origin of control, as autonomous (wild plant pathosystems, WPPs) or deterministic (crop plant pathosystems, CPPs). WPPs are characterized by the disease triangle and closed-loop (feedback) controls, and CPPs are characterized by the disease tetrahedron and open-loop (non-feedback) controls. Basic general, ecological, genetic, and population structural and functional differences between WPPs and CPPs are described. It is evident that we lack a focus on long-term observations and research of diseases and their dynamics in natural plant populations, metapopulations, communities, ecosystems, and biomes, as well as their direct or indirect relationships to CPPs. Differences and connections between WPPs and CPPs, and why, and how, these are important for agriculture varies. WPP and CPP may be linked by strong biological interactions, especially where the pathogen is in common. This is demonstrated through a case study of lettuce (Lactuca spp., L. serriola and L. sativa) and lettuce downy mildew (Bremia lactucae). In other cases where there is no such direct biological linkage, the study of WPPs can provide a deeper understanding of how ecology and genetics interacts to drive disease through time. These studies provide insights into ways in which farming practices may be changed to limit disease development. Research on interactions between pathosystems, the "cross-talk" of WPPs and CPPs, is still very limited and, as shown in interactions between wild and cultivated Lactuca spp.-B. lactucae associations, can be highly complex. The implications and applications of this knowledge in plant breeding, crop management, and disease control measures are considered. This review concludes with a discussion of theoretical, general and specific aspects, challenges and limits of future WPP research, and application of their results in agriculture.

Metapopulation Structure Predicts Population Dynamics in the Cakile maritima-Alternaria brassicicola Host-Pathogen Interaction.

AbstractIn symbiotic interactions, spatiotemporal variation in the distribution or population dynamics of one species represents spatial and temporal heterogeneity of the landscape for the other. Such interdependent demographic dynamics result in situations where the relative importance of biotic and abiotic factors in determining ecological processes is complicated to decipher. Using a detailed survey of three metapopulations of the succulent plant Cakile maritima and the necrotrophic fungus Alternaria brassicicola located along the southeastern Australian coast, we developed a series of statistical analyses-namely, synchrony analysis, patch occupancy dynamics, and a spatially explicit metapopulation model-to understand how habitat quality, weather conditions, dispersal, and spatial structure determine metapopulation dynamics. Climatic conditions are important drivers, likely explaining the high synchrony among populations. Host availability, landscape features facilitating dispersal, and habitat conditions also impact the occurrence and spread of disease. Overall, we show that the collection of extensive data on host and pathogen population dynamics, in combination with spatially explicit epidemiological modeling, makes it possible to accurately predict disease dynamics-even when there is extreme variability in host population dynamics. Finally, we discuss the importance of genetic information for predicting demographic dynamics in this pathosystem.

Optimizing Plant Disease Management in Agricultural Ecosystems Through Rational In-Crop Diversification.

Biodiversity plays multifaceted roles in societal development and ecological sustainability. In agricultural ecosystems, using biodiversity to mitigate plant diseases has received renewed attention in recent years but our knowledge of the best ways of using biodiversity to control plant diseases is still incomplete. In term of in-crop diversification, it is not clear how genetic diversity per se in host populations interacts with identifiable resistance and other functional traits of component genotypes to mitigate disease epidemics and what is the best way of structuring mixture populations. In this study, we created a series of host populations by mixing different numbers of potato varieties showing different late blight resistance levels in different proportions. The amount of naturally occurring late blight disease in the mixture populations was recorded weekly during the potato growing seasons. The percentage of disease reduction (PDR) in the mixture populations was calculated by comparing their observed late blight levels relative to that expected when they were planted in pure stands. We found that PDR in the mixtures increased as the number of varieties and the difference in host resistance (DHR) between the component varieties increased. However, the level of host resistance in the potato varieties had little impact on PDR. In mixtures involving two varieties, the optimum proportion of component varieties for the best PDR depended on their DHR, with an increasing skewness to one of the component varieties as the DHR between the component varieties increased. These results indicate that mixing crop varieties can significantly reduce disease epidemics in the field. To achieve the best disease mitigation, growers should include as many varieties as possible in mixtures or, if only two component mixtures are possible, increase DHR among the component varieties.

Climate change and disease in plant communities.

Climate change is triggering similar effects on the incidence and severity of disease for crops in agriculture and wild plants in natural communities. The complexity of natural ecosystems, however, generates a complex array of interactions between wild plants and pathogens in marked contrast to those generated in the structural and species simplicity of most agricultural crops. Understanding the different impacts of climate change on agricultural and natural ecosystems requires accounting for the specific interactions between an individual pathogen and its host(s) and their subsequent effects on the interplay between the host and other species in the community. Ultimately, progress will require looking past short-term fluctuations to multiyear trends to understand the nature and extent of plant and pathogen evolutionary adaptation and determine the fate of plants under future climate change.

Genetic analysis reveals long-standing population differentiation and high diversity in the rust pathogen Melampsora lini.

A priority for research on infectious disease is to understand how epidemiological and evolutionary processes interact to influence pathogen population dynamics and disease outcomes. However, little is understood about how population adaptation changes across time, how sexual vs. asexual reproduction contribute to the spread of pathogens in wild populations and how diversity measured with neutral and selectively important markers correlates across years. Here, we report results from a long-term study of epidemiological and genetic dynamics within several natural populations of the Linum marginale-Melampsora lini plant-pathogen interaction. Using pathogen isolates collected from three populations of wild flax (L. marginale) spanning 16 annual epidemics, we probe links between pathogen population dynamics, phenotypic variation for infectivity and genomic polymorphism. Pathogen genotyping was performed using 1567 genome-wide SNP loci and sequence data from two infectivity loci (AvrP123, AvrP4). Pathogen isolates were phenotyped for infectivity using a differential set. Patterns of epidemic development were assessed by conducting surveys of infection prevalence in one population (Kiandra) annually. Bayesian clustering analyses revealed host population and ecotype as key predictors of pathogen genetic structure. Despite strong fluctuations in pathogen population size and severe annual bottlenecks, analysis of molecular variance revealed that pathogen population differentiation was relatively stable over time. Annually, varying levels of clonal spread (0-44.8%) contributed to epidemics. However, within populations, temporal genetic composition was dynamic with rapid turnover of pathogen genotypes, despite the dominance of only four infectivity phenotypes across the entire study period. Furthermore, in the presence of strong fluctuations in population size and migration, spatial selection may maintain pathogen populations that, despite being phenotypically stable, are genetically highly dynamic.

Lessons from a Life in Time and Space.

A research career investigating epidemiological and evolutionary patterns in both natural and crop host-pathogen systems emphasizes the need for flexibility in thinking and a willingness to adopt ideas from a wide diversity of subdisciplines. Here, I reflect on the pivotal issues, research areas, and interactions, including the role of science management, that shaped my career in the hope of demonstrating that career paths and collaborations in science can be as diverse and unpredictable as the natural world in which we study our organisms of choice.

Mosaics, mixtures, rotations or pyramiding: What is the optimal strategy to deploy major gene resistance?

Once deployed uniformly in the field, genetically controlled plant resistance is often quickly overcome by pathogens, resulting in dramatic losses. Several strategies have been proposed to constrain the evolutionary potential of pathogens and thus increase resistance durability. These strategies can be classified into four categories, depending on whether resistance sources are varied across time (rotations) or combined in space in the same cultivar (pyramiding), in different cultivars within a field (cultivar mixtures) or among fields (mosaics). Despite their potential to differentially affect both pathogen epidemiology and evolution, to date the four categories of deployment strategies have never been directly compared together within a single theoretical or experimental framework, with regard to efficiency (ability to reduce disease impact) and durability (ability to limit pathogen evolution and delay resistance breakdown). Here, we used a spatially explicit stochastic demogenetic model, implemented in the R package landsepi, to assess the epidemiological and evolutionary outcomes of these deployment strategies when two major resistance genes are present. We varied parameters related to pathogen evolutionary potential (mutation probability and associated fitness costs) and landscape organization (mostly the relative proportion of each cultivar in the landscape and levels of spatial or temporal aggregation). Our results, broadly focused on qualitative resistance to rust fungi of cereal crops, show that evolutionary and epidemiological control are not necessarily correlated and that no deployment strategy is universally optimal. Pyramiding two major genes offered the highest durability, but at high mutation probabilities, mosaics, mixtures and rotations can perform better in delaying the establishment of a universally infective superpathogen. All strategies offered the same short-term epidemiological control, whereas rotations provided the best long-term option, after all sources of resistance had broken down. This study also highlights the significant impact of landscape organization and pathogen evolutionary ability in considering the optimal design of a deployment strategy.

Differential impact of landscape-scale strategies for crop cultivar deployment on disease dynamics, resistance durability and long-term evolutionary control.

A multitude of resistance deployment strategies have been proposed to tackle the evolutionary potential of pathogens to overcome plant resistance. In particular, many landscape-based strategies rely on the deployment of resistant and susceptible cultivars in an agricultural landscape as a mosaic. However, the design of such strategies is not easy as strategies targeting epidemiological or evolutionary outcomes may not be the same. Using a stochastic spatially explicit model, we studied the impact of landscape organization (as defined by the proportion of fields cultivated with a resistant cultivar and their spatial aggregation) and key pathogen life-history traits on three measures of disease control. Our results show that short-term epidemiological dynamics are optimized when landscapes are planted with a high proportion of the resistant cultivar in low aggregation. Importantly, the exact opposite situation is optimal for resistance durability. Finally, well-mixed landscapes (balanced proportions with low aggregation) are optimal for long-term evolutionary equilibrium (defined here as the level of long-term pathogen adaptation). This work offers a perspective on the potential for contrasting effects of landscape organization on different goals of disease management and highlights the role of pathogen life history.

Climate change accelerates local disease extinction rates in a long-term wild host-pathogen association.

Pathogens are a significant component of all plant communities. In recent years, the potential for existing and emerging pathogens of agricultural crops to cause increased yield losses as a consequence of changing climatic patterns has raised considerable concern. In contrast, the response of naturally occurring, endemic pathogens to a warming climate has received little attention. Here, we report on the impact of a signature variable of global climate change - increasing temperature - on the long-term epidemiology of a natural host-pathogen association involving the rust pathogen Triphragmium ulmariae and its host plant Filipendula ulmaria. In a host-pathogen metapopulation involving approximately 230 host populations growing on an archipelago of islands in the Gulf of Bothnia we assessed changes in host population size and pathogen epidemiological measures over a 25-year period. We show how the incidence of disease and its severity declines over that period and most importantly demonstrate a positive association between a long-term trend of increasing extinction rates in individual pathogen populations of the metapopulation and increasing temperature. Our results are highly suggestive that changing climatic patterns, particularly mean monthly growing season (April-November) temperature, are markedly influencing the epidemiology of plant disease in this host-pathogen association. Given the important role plant pathogens have in shaping the structure of communities, changes in the epidemiology of pathogens have potentially far-reaching impacts on ecological and evolutionary processes. For these reasons, it is essential to increase understanding of pathogen epidemiology, its response to warming, and to invoke these responses in forecasts for the future.

In situ conservation-harnessing natural and human-derived evolutionary forces to ensure future crop adaptation.

Ensuring the availability of the broadest possible germplasm base for agriculture in the face of increasingly uncertain and variable patterns of biotic and abiotic change is fundamental for the world's future food supply. While ex situ conservation plays a major role in the conservation and availability of crop germplasm, it may be insufficient to ensure this. In situ conservation aims to maintain target species and the collective genotypes they represent under evolution. A major rationale for this view is based on the likelihood that continued exposure to changing selective forces will generate and favor new genetic variation and an increased likelihood that rare alleles that may be of value to future agriculture are maintained. However, the evidence that underpins this key rationale remains fragmented and has not been examined systematically, thereby decreasing the perceived value and support for in situ conservation for agriculture and food systems and limiting the conservation options available. This study reviews evidence regarding the likelihood and rate of evolutionary change in both biotic and abiotic traits for crops and their wild relatives, placing these processes in a realistic context in which smallholder farming operates and crop wild relatives continue to exist. It identifies areas of research that would contribute to a deeper understanding of these processes as the basis for making them more useful for future crop adaptation.

Addressing the Challenges of Pathogen Evolution on the World's Arable Crops.

Advances in genomic and molecular technologies coupled with an increasing understanding of the fine structure of many resistance and infectivity genes, have opened up a new era of hope in controlling the many plant pathogens that continue to be a major source of loss in arable crops. Some new approaches are under consideration including the use of nonhost resistance and the targeting of critical developmental constraints. However, the major thrust of these genomic and molecular approaches is to enhance the identification of resistance genes, to increase their ease of manipulation through marker and gene editing technologies and to lock a range of resistance genes together in simply manipulable resistance gene cassettes. All these approaches essentially continue a strategy that assumes the ability to construct genetic-based resistance barriers that are insurmountable to target pathogens. Here we show how the recent advances in knowledge and marker technologies can be used to generate more durable disease resistance strategies that are based on broad evolutionary principles aimed at presenting pathogens with a shifting, landscape of fluctuating directional selection.

Trade-offs and evolution of thermal adaptation in the Irish potato famine pathogen Phytophthora infestans.

Temperature is one of the most important environmental parameters with crucial impacts on nearly all biological processes. Due to anthropogenic activity, average air temperatures are expected to increase by a few degrees in coming decades, accompanied by an increased occurrence of extreme temperature events. Such global trends are likely to have various major impacts on human society through their influence on natural ecosystems, food production and biotic interactions, including diseases. In this study, we used a combination of statistical genetics, experimental evolution and common garden experiments to investigate the evolutionary potential for thermal adaptation in the potato late blight pathogen, Phytophthora infestans, and infer its likely response to changing temperatures. We found a trade-off associated with thermal adaptation to heterogeneous environments in P. infestans, with the degree of the trade-off peaking approximately at the pathogen's optimum growth temperature. A genetic trade-off in thermal adaptation was also evidenced by the negative association between a strain's growth rate and its thermal range for growth, and warm climates selecting for a low pathogen growth rate. We also found a mirror effect of phenotypic plasticity and genetic adaptation on growth rate. At below the optimum, phenotypic plasticity enhances pathogen's growth rate but nature selects for slower growing genotypes when temperature increases. At above the optimum, phenotypic plasticity reduces pathogen's growth rate but natural selection favours for faster growing genotypes when temperature increases further. We conclude from these findings that the growth rate of P. infestans will only be marginally affected by global warming.

Specialization for resistance in wild host-pathogen interaction networks.

Properties encompassed by host-pathogen interaction networks have potential to give valuable insight into the evolution of specialization and coevolutionary dynamics in host-pathogen interactions. However, network approaches have been rarely utilized in previous studies of host and pathogen phenotypic variation. Here we applied quantitative analyses to eight networks derived from spatially and temporally segregated host (Linum marginale) and pathogen (Melampsora lini) populations. First, we found that resistance strategies are highly variable within and among networks, corresponding to a spectrum of specialist and generalist resistance types being maintained within all networks. At the individual level, specialization was strongly linked to partial resistance, such that partial resistance was effective against a greater number of pathogens compared to full resistance. Second, we found that all networks were significantly nested. There was little support for the hypothesis that temporal evolutionary dynamics may lead to the development of nestedness in host-pathogen infection networks. Rather, the common patterns observed in terms of nestedness suggests a universal driver (or multiple drivers) that may be independent of spatial and temporal structure. Third, we found that resistance networks were significantly modular in two spatial networks, clearly reflecting spatial and ecological structure within one of the networks. We conclude that (1) overall patterns of specialization in the networks we studied mirror evolutionary trade-offs with the strength of resistance; (2) that specific network architecture can emerge under different evolutionary scenarios; and (3) network approaches offer great utility as a tool for probing the evolutionary and ecological genetics of host-pathogen interactions.

Playing on a pathogen's weakness: using evolution to guide sustainable plant disease control strategies.

Wild plants and their associated pathogens are involved in ongoing interactions over millennia that have been modified by coevolutionary processes to limit the spatial extent and temporal duration of disease epidemics. These interactions are disrupted by modern agricultural practices and social activities, such as intensified monoculture using superior varieties and international trading of agricultural commodities. These activities, when supplemented with high resource inputs and the broad application of agrochemicals, create conditions uniquely conducive to widespread plant disease epidemics and rapid pathogen evolution. To be effective and durable, sustainable disease management requires a significant shift in emphasis to overtly include ecoevolutionary principles in the design of adaptive management programs aimed at minimizing the evolutionary potential of plant pathogens by reducing their genetic variation, stabilizing their evolutionary dynamics, and preventing dissemination of pathogen variants carrying new infectivity or resistance to agrochemicals.

Crop pathogen emergence and evolution in agro-ecological landscapes.

Remnant areas hosting natural vegetation in agricultural landscapes can impact the disease epidemiology and evolutionary dynamics of crop pathogens. However, the potential consequences for crop diseases of the composition, the spatial configuration and the persistence time of the agro-ecological interface - the area where crops and remnant vegetation are in contact - have been poorly studied. Here, we develop a demographic-genetic simulation model to study how the spatial and temporal distribution of remnant wild vegetation patches embedded in an agricultural landscape can drive the emergence of a crop pathogen and its subsequent specialization on the crop host. We found that landscape structures that promoted larger pathogen populations on the wild host facilitated the emergence of a crop pathogen, but such landscape structures also reduced the potential for the pathogen population to adapt to the crop. In addition, the evolutionary trajectory of the pathogen population was determined by interactions between the factors describing the landscape structure and those describing the pathogen life histories. Our study contributes to a better understanding of how the shift of land-use patterns in agricultural landscapes might influence crop diseases to provide predictive tools to evaluate management practices.

Below-ground abiotic and biotic heterogeneity shapes above-ground infection outcomes and spatial divergence in a host-parasite interaction.

We investigated the impact of below-ground and above-ground environmental heterogeneity on the ecology and evolution of a natural plant-pathogen interaction. We combined field measurements and a reciprocal inoculation experiment to investigate the potential for natural variation in abiotic and biotic factors to mediate infection outcomes in the association between the fungal pathogen Melampsora lini and its wild flax host, Linum marginale, where pathogen strains and plant lines originated from two ecologically distinct habitat types that occur in close proximity ('bog' and 'hill'). The two habitat types differed strikingly in soil moisture and soil microbiota. Infection outcomes for different host-pathogen combinations were strongly affected by the habitat of origin of the plant lines and pathogen strains, the soil environment and their interactions. Our results suggested that tradeoffs play a key role in explaining the evolutionary divergence in interaction traits among the two habitat types. Overall, we demonstrate that soil heterogeneity, by mediating infection outcomes and evolutionary divergence, can contribute to the maintenance of variation in resistance and pathogenicity within a natural host-pathogen metapopulation.

Epidemiological and Evolutionary Outcomes in Gene-for-Gene and Matching Allele Models.

Gene-for-gene (GFG) and matching-allele (MA) models are qualitatively different paradigms for describing the outcome of genetic interactions between hosts and pathogens. The GFG paradigm was largely built on the foundations of Flor's early work on the flax-flax rust interaction and is based on the concept of genetic recognition leading to incompatible disease outcomes, typical of host immune recognition. In contrast, the MA model is based on the assumption that genetic recognition leads to compatible interactions, which can result when pathogens require specific host factors to cause infection. Results from classical MA and GFG models have led to important predictions regarding various coevolutionary phenomena, including the role of fitness costs associated with resistance and infectivity, the distribution of resistance genes in wild populations, patterns of local adaptation and the evolution and maintenance of sexual reproduction. Empirical evidence (which we review briefly here), particularly from recent molecular advances in understanding of the mechanisms that determine the outcome of host-pathogen encounters, suggests considerable variation in specific details of the functioning of interactions between hosts and pathogens, which may contain elements of both models. In this regard, GFG and MA scenarios likely represent endpoints of a continuum of potentially more complex interactions that occur in nature. Increasingly, this has been recognized in theoretical studies of coevolutionary processes in plant host-pathogen and animal host-parasite associations (e.g., departures from strict GFG/MA assumptions, diploid genetics, multi-step infection processes). However, few studies have explored how different genetic assumptions about host resistance and pathogen infectivity might impact on disease epidemiology or pathogen persistence within and among populations. Here, we use spatially explicit simulations of the basic MA and GFG scenarios to highlight qualitative differences between these scenarios with regard to patterns of disease and impacts on host demography. Given that such impacts drive evolutionary trajectories, future theoretical advances that aim to capture more complex genetic scenarios should explicitly address the interaction between epidemiology and different models of host-pathogen interaction genetics.

Guiding deployment of resistance in cereals using evolutionary principles.

Genetically controlled resistance provides plant breeders with an efficient means of controlling plant disease, but this approach has been constrained by practical difficulties associated with combining many resistance genes together and strong evolutionary responses from pathogen populations leading to subsequent resistance breakdown. However, continuing advances in molecular marker technologies are revolutionizing the ability to rapidly and reliably manipulate resistances of all types - major gene, adult plant and quantitative resistance loci singly or multiply into individual host lines. Here, we argue that these advances provide major opportunities to deliberately design deployment strategies in cereals that can take advantage of the evolutionary pressures faced by target pathogens. Different combinations of genes deployed either within single host individuals or between different individuals within or among crops, can be used to reduce the size of pathogen populations and generate patterns of disruptive selection. This will simultaneously limit immediate epidemic development and reduce the probability of subsequent evolutionary change in the pathogen for broader infectivity or increased aggressiveness. The same general principles are relevant to the control of noncereal diseases, but the most efficacious controls will vary reflecting the range of genetic options available and their fit with specific ecology and life-history combinations.

Host ecotype generates evolutionary and epidemiological divergence across a pathogen metapopulation.

The extent and speed at which pathogens adapt to host resistance varies considerably. This presents a challenge for predicting when--and where--pathogen evolution may occur. While gene flow and spatially heterogeneous environments are recognized to be critical for the evolutionary potential of pathogen populations, we lack an understanding of how the two jointly shape coevolutionary trajectories between hosts and pathogens. The rust pathogen Melampsora lini infects two ecotypes of its host plant Linum marginale that occur in close proximity yet in distinct populations and habitats. In this study, we found that within-population epidemics were different between the two habitats. We then tested for pathogen local adaptation at host population and ecotype level in a reciprocal inoculation study. Even after controlling for the effect of spatial structure on infection outcome, we found strong evidence of pathogen adaptation at the host ecotype level. Moreover, sequence analysis of two pathogen infectivity loci revealed strong genetic differentiation by host ecotype but not by distance. Hence, environmental variation can be a key determinant of pathogen population genetic structure and coevolutionary dynamics and can generate strong asymmetry in infection risks through space.

Achieving sustainable plant disease management through evolutionary principles.

Plants and their pathogens are engaged in continuous evolutionary battles and sustainable disease management requires novel systems to create environments conducive for short-term and long-term disease control. In this opinion article, we argue that knowledge of the fundamental factors that drive host-pathogen coevolution in wild systems can provide new insights into disease development in agriculture. Such evolutionary principles can be used to guide the formulation of sustainable disease management strategies which can minimize disease epidemics while simultaneously reducing pressure on pathogens to evolve increased infectivity and aggressiveness. To ensure agricultural sustainability, disease management programs that reflect the dynamism of pathogen population structure are essential and evolutionary biologists should play an increasing role in their design.