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.

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.

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.

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.

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.

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.

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.

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.

Evolution of pathogen specialisation in a host metapopulation: joint effects of host and pathogen dispersal.

Metapopulation processes are important determinants of epidemiological and evolutionary dynamics in host-pathogen systems, and are therefore central to explaining observed patterns of disease or genetic diversity. In particular, the spatial scale of interactions between pathogens and their hosts is of primary importance because migration rates of one species can affect both spatial and temporal heterogeneity of selection on the other. In this study we developed a stochastic and discrete time simulation model to specifically examine the joint effects of host and pathogen dispersal on the evolution of pathogen specialisation in a spatially explicit metapopulation. We consider a plant-pathogen system in which the host metapopulation is composed of two plant genotypes. The pathogen is dispersed by air-borne spores on the host metapopulation. The pathogen population is characterised by a single life-history trait under selection, the infection efficacy. We found that restricted host dispersal can lead to high amount of pathogen diversity and that the extent of pathogen specialisation varied according to the spatial scale of host-pathogen dispersal. We also discuss the role of population asynchrony in determining pathogen evolutionary outcomes.

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.

Rapid genetic change underpins antagonistic coevolution in a natural host-pathogen metapopulation.

Antagonistic coevolution is a critical force driving the evolution of diversity, yet the selective processes underpinning reciprocal adaptive changes in nature are not well understood. Local adaptation studies demonstrate partner impacts on fitness and adaptive change, but do not directly expose genetic processes predicted by theory. Specifically, we have little knowledge of the relative importance of fluctuating selection vs. arms-race dynamics in maintaining polymorphism in natural systems where metapopulation processes predominate. We conducted cross-year epidemiological, infection and genetic studies of multiple wild host and pathogen populations in the Linum-Melampsora association. We observed asynchronous phenotypic fluctuations in resistance and infectivity among demes. Importantly, changes in allelic frequencies at pathogen infectivity loci, and in host recognition of these genetic variants, correlated with disease prevalence during natural epidemics. These data strongly support reciprocal coevolution maintaining balanced resistance and infectivity polymorphisms, and highlight the importance of characterising spatial and temporal dynamics in antagonistic interactions.

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.

Diversity and evolution of effector loci in natural populations of the plant pathogen Melampsora lini.

Genetic variation for pathogen infectivity is an important driver of disease incidence and prevalence in both natural and managed systems. Here, we use the interaction between the rust pathogen, Melampsora lini, and two host plants, Linum marginale and Linum usitatissimum, to examine how host-pathogen interactions influence the maintenance of polymorphism in genes underlying pathogen virulence. Extensive sequence variation at two effector loci (AvrP123, AvrP4) was found in M. lini isolates collected from across the native range of L. marginale in Australia, as well as in isolates collected from a second host, the cultivated species L. usitatissimum. A highly significant excess of nonsynonymous compared with synonymous polymorphism was found at both loci, suggesting that diversifying selection is important for the maintenance of the observed sequence diversity. Agrobacterium-mediated transient transformation assays were used to demonstrate that variants of both the AvrP123 and AvrP4 genes are differentially recognized by resistance genes in L. marginale. We further characterized patterns of nucleotide variation at AvrP123 and AvrP4 in 10 local populations of M. lini infecting the wild host L. marginale. Populations were significantly differentiated with respect to allelic representation at the Avr loci, suggesting the possibility of local selection maintaining distinct genetic structures between pathogen populations, whereas limited diversity may be explained via selective sweeps and demographic bottlenecks. Together, these results imply that interacting selective and nonselective factors, acting across a broad range of scales, are important for the generation and maintenance of adaptively significant variation in populations of M. lini.

Positive selection in AvrP4 avirulence gene homologues across the genus Melampsora.

Pathogen genes involved in interactions with their plant hosts are expected to evolve under positive Darwinian selection or balancing selection. In this study a single copy avirulence gene, AvrP4, in the plant pathogen Melampsora lini, was used to investigate the evolution of such a gene across species. Partial translation elongation factor 1-alpha sequences were obtained to establish phylogenetic relationships among the Melampsora species. We amplified AvrP4 homologues from species pathogenic on hosts from different plant families and orders, across the inferred phylogeny. Translations of the AvrP4 sequences revealed a predicted signal peptide and towards the C-terminus of the protein, six identically spaced cysteines were identified in all sequences. Maximum likelihood analysis of synonymous versus non-synonymous substitution rates indicated that positive selection played a role in the evolution of the gene during the diversification of the genus. Fourteen codons under significant positive selection reside in the C-terminal 28 amino acid region, suggesting that this region interacts with host molecules in most sequenced accessions. Selection pressures on the gene may be either due to the pathogenicity or avirulence function of the gene or both.

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.

Population structure and diversity in sexual and asexual populations of the pathogenic fungus Melampsora lini.

Many pathogens undergo both sexual and asexual reproduction to varying degrees, yet the ecological, genetic and evolutionary consequences of different reproductive strategies remain poorly understood. Here we investigate the population genetic structure of wild populations of the plant pathogen Melampsora lini on its host Linum marginale, using amplified fragment length polymorphism (AFLP) markers, two genes underlying pathogen virulence, and phenotypic variation in virulence. In Australia, M. lini occurs as two genetically and geographically divergent lineages (AA and AB), one of which is completely asexual (AB), and the other able to reproduce both clonally and sexually (AA). To quantify the genetic and evolutionary consequences of these different life histories, we sampled five populations in each of two biogeographical regions. Analysis of AFLP data obtained for 275 isolates revealed largely disjunct geographical distributions for the two different lineages, low genetic diversity within lineages, and strong genetic structure among populations within each region. We also detected significant divergence among populations for both Avr genes and virulence phenotypes, although generally these values were lower than those obtained with AFLP markers. Furthermore, isolates belonging to lineage AA collectively harboured significantly higher genotypic and phenotypic diversity than lineage AB isolates. Together these results illustrate the important roles of reproductive modes and geographical structure in the generation and maintenance of virulence diversity in populations of M. lini.

The current and future dynamics of disease in plant communities.

Pathogens are powerful evolutionary forces shaping the structure and dynamics of both individual species and of the communities of which they are part, at a broad range of genetic, ecological, spatial, and temporal scales. At all these levels their impact varies from the subtle and little recognized through to the most obvious destruction. Today the direct role of pathogens in natural plant communities is better recognized than at previous times, although the nuances of their interactions and the cascade of ramifications that can flow through changing biotic and abiotic effects are only now gaining recognition. However, as human influence on pathogens increases--either directly through enhanced if accidental dispersal, or through anthropogenic impacts on climate--we may expect to see increasing evidence of pathogens affecting plant species, community structure, and ecosystem function.

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.

Evolutionary diversification through hybridization in a wild host-pathogen interaction.

Coevolutionary outcomes between interacting species are predicted to vary across landscapes, as environmental conditions, gene flow, and the strength of selection vary among populations. Using a combination of molecular, experimental, and field approaches, we describe how broad-scale patterns of environmental heterogeneity, genetic divergence, and regional adaptation have the potential to influence coevolutionary processes in the Linum marginale-Melampsora lini plant-pathogen interaction. We show that two genetically and geographically divergent pathogen lineages dominate interactions with the host across Australia, and demonstrate a hybrid origin for one of the lineages. We further demonstrate that the geographic divergence of the two lineages of M. lini in Australia is related to variation among lineages in virulence, life-history characteristics, and response to environmental conditions. When correlated with data describing regional patterns of variation in host resistance diversity and mating system these observations highlight the potential for gene flow and geographic selection mosaics to generate and maintain coevolutionary diversification in long-standing host-pathogen interactions.