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Management of plant disease in agro-ecosystems ideally relies on a combination of host genetic resistance, chemical control, and cultural practices. Growers increasingly rely on chemical and genetic options, but their relative benefits in disease control, yield, and economic outcomes are rarely quantified. We explore this relationship for blackleg crown canker disease (caused by Leptosphaeria maculans ), a major biotic constraint limiting canola production globally. Data from 20 field trials conducted from 2013 to 2015 in canola-growing regions of Australia were used to assess the effects of host resistance and fungicide treatment on blackleg severity, grain yield, and gross margin. In the absence of fungicide, blackleg disease was 88% lower in the most resistant compared with the most susceptible blackleg resistance category. In the most susceptible resistance category, the most effective fungicide treatment significantly reduced blackleg severity (from 50 to 6%) and increased grain yield (478 kg/ha, 41%) and gross margin (AU$120/ha, 17%). However, the mean benefits of fungicide tended to decrease with increasing levels of genetic resistance, to the point that yield, disease, and gross margin benefits were close to zero in the most resistant cultivars. Overall, these findings suggest that fungicides can reduce blackleg severity, but the benefits of application strongly depend on associated levels of genetic resistance. Canola cultivars with higher genetic resistance reliably reduced blackleg disease and maintained grain yield without the associated cost of fungicide application. The intensification of canola production to meet increasing global demand will require strategies to sustainably manage and protect finite genetic resistance resources to control blackleg disease., Competing Interests: The author(s) declare no conflict of interest.

Many publications lack sufficient background information (e.g. location) to be interpreted, replicated, or reused for synthesis. This impedes scientific progress and the application of science to practice. Reporting guidelines (e.g. checklists) improve reporting standards. They have been widely taken up in the medical sciences, but not in ecological and agricultural research. Here, we use a community-centred approach to develop a reporting checklist (AgroEcoList 1.0) through surveys and workshops with 23 experts and the wider agroecological community. To put AgroEcoList in context, we also assessed the agroecological community's perception of reporting standards in agroecology. A total of 345 researchers, reviewers, and editors, responded to our survey. Although only 32% of respondents had prior knowledge of reporting guidelines, 76% of those that had said guidelines improved reporting standards. Overall, respondents agreed on the need of AgroEcolist 1.0; only 24% of respondents had used reporting guidelines before, but 78% indicated they would use AgroEcoList 1.0. We updated AgroecoList 1.0 based on respondents' feedback and user-testing. AgroecoList 1.0 consists of 42 variables in seven groups: experimental/sampling set-up, study site, soil, livestock management, crop and grassland management, outputs, and finances. It is presented here, and is also available on github (https://github.com/AgroecoList/Agroecolist). AgroEcoList 1.0 can serve as a guide for authors, reviewers, and editors to improve reporting standards in agricultural ecology. Our community-centred approach is a replicable method that could be adapted to develop reporting checklists in other fields. Reporting guidelines such as AgroEcoList can improve reporting standards and therefore the application of research to practice, and we recommend that they are adopted more widely in agriculture and ecology., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Daykin et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Genetic resistance forms the foundation of infectious disease management in crops. However, rapid pathogen evolution is causing the breakdown of resistance and threatening disease control. Recent research efforts have identified strategies for resistance gene deployment that aim to disrupt pathogen adaptation and prevent breakdown. To date, there has been limited practical uptake of such strategies. In this paper, we focus on the socio-economic challenges associated with translating applied evolutionary research into scientifically informed management strategies to control pathogen adaptation. We develop a conceptual framework for the economic valuation of resistance and demonstrate that in addition to various direct benefits, resistance delivers considerable indirect and non-market value to farmers and society. Incentives for stakeholders to engage in stewardship strategies are complicated by the uncertain timeframes associated with evolutionary processes, difficulties in assigning ownership rights to genetic resources and lack of governance. These interacting biological, socio-economic and institutional complexities suggest that resistance breakdown should be viewed as a wicked problem, with often conflicting imperatives among stakeholders and no simple cause or solution. Promoting the uptake of scientific research outcomes that address complex issues in sustainable crop disease management will require a mix of education, incentives, legislation and social change. This article is part of the theme issue 'Infectious disease ecology and evolution in a changing world'.

Plant-soil interactions can be important drivers of biological invasions. In particular, the symbiotic relationship between legumes and nitrogen-fixing soil bacteria (i.e. rhizobia) may be influential in invasion success. Legumes, including Australian acacias, have been introduced into novel ranges around the world. Our goal was to examine the acacia-rhizobia symbiosis to determine whether cointroduction of non-native mutualists plays a role in invasiveness of introduced legumes. To determine whether acacias were introduced abroad concurrently with native symbionts, we selected four species introduced to California (two invasive and two noninvasive in the region) and identified rhizobial strains associating with each species in their native and novel ranges. We amplified three genes to examine phylogenetic placement (16S rRNA) and provenance (nifD and nodC) of rhizobia associating with acacias in California and Australia. We found that all Acacia species, regardless of invasive status, are associating with rhizobia of Australian origin in their introduced ranges, indicating that concurrent acacia-rhizobia introductions have occurred for all species tested. Our results suggest that cointroduction of rhizobial symbionts may be involved in the establishment of non-native acacias in their introduced ranges, but do not contribute to the differential invasiveness of Acacia species introduced abroad., (© The Author(s) 2022. Published by Oxford University Press on behalf of FEMS.)

Owing to their evolutionary potential, plant pathogens are able to rapidly adapt to genetically controlled plant resistance, often resulting in resistance breakdown and major epidemics in agricultural crops. Various deployment strategies have been proposed to improve resistance management. Globally, these rely on careful selection of resistance sources and their combination at various spatiotemporal scales (e.g., via gene pyramiding, crop rotations and mixtures, landscape mosaics). However, testing and optimizing these strategies using controlled experiments at large spatiotemporal scales are logistically challenging. Mathematical models provide an alternative investigative tool, and many have been developed to explore resistance deployment strategies under various contexts. This review analyzes 69 modeling studies in light of specific model structures (e.g., demographic or demogenetic, spatial or not), underlying assumptions (e.g., whether preadapted pathogens are present before resistance deployment), and evaluation criteria (e.g., resistance durability, disease control, cost-effectiveness). It highlights major research findings and discusses challenges for future modeling efforts.

Recent advances in gene-editing technologies have opened new avenues for genetic pest control strategies, in particular around the use of gene drives to suppress or modify pest populations. Significant uncertainty, however, surrounds the applicability of these strategies to novel target species, their efficacy in natural populations and their eventual safety and acceptability as control methods. In this article, we identify issues associated with the potential use of gene drives in agricultural systems, to control pests and diseases that impose a significant cost to agriculture around the world. We first review the need for innovative approaches and provide an overview of the most relevant biological and ecological traits of agricultural pests that could impact the outcome of gene drive approaches. We then describe the specific challenges associated with using gene drives in agricultural systems, as well as the opportunities that these environments may offer, focusing in particular on the advantages of high-threshold gene drives. Overall, we aim to provide a comprehensive view of the potential opportunities and the remaining uncertainties around the use of gene drives in agricultural systems., Competing Interests: The authors declare that there is no conflict of interest., (© 2021 The Authors. Evolutionary Applications published by John Wiley & Sons Ltd.)

Infections by more than one strain of a pathogen predominate under natural conditions. Mixed infections can have significant, though often unpredictable, consequences for overall virulence, pathogen transmission and evolution. However, effects of mixed infection on disease development in plants often remain unclear and the critical factors that determine the outcome of mixed infections remain unknown. The fungus Zymoseptoria tritici forms genetically diverse infections in wheat fields. Here, for a range of pathogen traits, we experimentally decompose the infection process to determine how the outcomes and consequences of mixed infections are mechanistically realized. Different strains of Z. tritici grow in close proximity and compete in the wheat apoplast, resulting in reductions in growth of individual strains and in pathogen reproduction. We observed different outcomes of competition at different stages of the infection. Overall, more virulent strains had higher competitive ability during host colonization, and less virulent strains had higher transmission potential. We showed that within-host competition can have a major effect on infection dynamics and pathogen population structure in a pathogen and host genotype-specific manner. Consequently, mixed infections likely have a major effect on the development of septoria tritici blotch epidemics and the evolution of virulence in Z. tritici., (© 2021 The Authors. Environmental Microbiology published by Society for Applied Microbiology and John Wiley & Sons Ltd.)

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.

There is strong evidence for a phylogenetic signal in the degree to which species share co-evolved biotic partners and in the outcomes of biotic interactions. This implies there should be a phylogenetic signal in the outcome of feedbacks between plants and the soil microbiota they cultivate. However, attempts to identify a phylogenetic signal in plant-soil feedbacks have produced mixed results. Here we clarify how phylogenetic signals could arise in plant-soil feedbacks and use a recent compilation of data from feedback experiments to identify: whether there is a phylogenetic signal in the outcome of plant-soil feedbacks; and whether any signal arises through directional or divergent changes in feedback outcomes with evolutionary time. We find strong evidence for a divergent phylogenetic signal in feedback outcomes. Distantly related plant species show more divergent responses to each other's soil microbiota compared with closely related plant species. The pattern of divergence implies occasional co-evolutionary shifts in how plants interact with soil microbiota, with strongly contrasting feedback responses among some plant lineages. Our results highlight that it is difficult to predict feedback outcomes from phylogeny alone, other than to say that more closely related species tend to have more similar responses., (©2020 The Authors. New Phytologist ©2020 New Phytologist Foundation.)

Scientists are rapidly developing synthetic gene drive elements intended for release into natural populations. These are intended to control or eradicate disease vectors and pests, or to spread useful traits through wild populations for disease control or conservation purposes. However, a crucial problem for gene drives is the evolution of resistance against them, preventing their spread. Understanding the mechanisms by which populations might evolve resistance is essential for engineering effective gene drive systems. This review summarizes our current knowledge of drive resistance in both natural and synthetic gene drives. We explore how insights from naturally occurring and synthetic drive systems can be integrated to improve the design of gene drives, better predict the outcome of releases and understand genomic conflict in general., (© 2020 The Authors. Journal of Evolutionary Biology published by John Wiley & Sons Ltd on behalf of European Society for Evolutionary Biology.)

Genetic diversity within pathogen populations is critically important for predicting pathogen evolution, disease outcomes and prevalence. However, we lack a good understanding of the processes maintaining genetic variation and constraints on pathogen life-history evolution. Here, we analysed interactions between 12 wheat host genotypes and 145 strains of Zymoseptoria tritici from five global populations to investigate the evolution and maintenance of variation in pathogen virulence and reproduction. We found a strong positive correlation between virulence (amount of leaf necrosis) and reproduction (pycnidia density within lesions), with substantial variation in both traits maintained within populations. On average, highly virulent isolates exhibited higher reproduction, which might increase transmission potential in agricultural fields planted to homogeneous hosts at a high density. We further showed that pathogen strains with a narrow host range (i.e. specialists) for reproduction were on average less virulent, and those with a broader host range (i.e. generalists) were on average less fecund on a given specific host. These costs associated with adaptation to different host genotypes might constrain the emergence of generalists by disrupting the directional evolution of virulence and fecundity. We conclude that selection favouring pathogen strains that are virulent across diverse hosts, coupled with selection that maximizes fecundity on specific hosts, may explain the maintenance of these pathogenicity traits within and among populations., Competing Interests: None declared., (© 2020 The Authors. Evolutionary Applications published by John Wiley & Sons Ltd.)

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., Competing Interests: The authors have declared that no competing interests exist.

With the advent of new genetic technologies such as gene silencing and gene drive, efforts to develop additional management tools for weed management is gaining significant momentum. These technologies promise novel ways to develop sustainable weed control options because gene silencing can switch-off genes mediating adaptation (e.g. growth, herbicide resistance), and gene drive can be used to spread modified traits and to engineer wild populations with reduced fitness. However, applying gene silencing and/or gene drive is expected to be inherently complex as their application is constrained by several methodological and technological difficulties. In this review we explore the challenges of these technologies, and discuss strategies and resources accessible to accelerate the development of gene-tech based tools for weed management. We also highlight how gene technologies can be integrated into existing management tactics such as classical biological control, and their possible interactions., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Plant species, populations and communities are under threat from climate change, invasive pathogens, weeds and habitat fragmentation. Despite considerable research effort invested in genome engineering for crop improvement, the development of genetic tools for the management of wild plant populations has rarely been given detailed consideration. Gene drive systems that allow direct genetic management of plant populations via the spread of fitness-altering genetic modifications could be of great utility. However, despite the rapid development of synthetic tools and their enormous promise, little explicit consideration has been given to their application in plants and, to date, they remain untested. This article considers the potential utility of gene drives for the management of wild plant populations, and examines the factors that might influence the design, spread and efficacy of synthetic drives. To gain insight into optimal ways to design and deploy synthetic drive systems, we investigate the diversity of mechanisms underlying natural gene drives and their dynamics within plant populations and species. We also review potential approaches for engineering gene drives and discuss their potential application to plant genomes. We highlight the importance of considering the impact of plant life-history and genetic architecture on the dynamics of drive, investigate the potential for different types of resistance evolution, and touch on the ethical, regulatory and social challenges ahead.

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.

Genetic, physiological and physical homogenization of agricultural landscapes creates ideal environments for plant pathogens to proliferate and rapidly evolve. Thus, a critical challenge in plant pathology and epidemiology is to design durable and effective strategies to protect cropping systems from damage caused by pathogens. Theoretical studies suggest that spatio-temporal variation in the diversity and distribution of resistant hosts across agricultural landscapes may have strong effects on the epidemiology and evolutionary potential of crop pathogens. However, we lack empirical tests of spatio-temporal deployment of host resistance to pathogens can be best used to manage disease epidemics and disrupt pathogen evolutionary dynamics in real-world systems. In a field experiment, we simulated how differences in Brassica napus resistance deployment strategies and landscape connectivity influence epidemic severity and Leptosphaeria maculans pathogen population composition. Host plant resistance, spatio-temporal connectivity [stubble loads], and genetic connectivity of the inoculum source [composition of canola stubble mixtures] jointly impacted epidemiology (disease severity) and pathogen evolution (population composition). Changes in population composition were consistent with directional selection for the ability to infect the host (infectivity), leading to changes in pathotype (multilocus phenotypes) and infectivity frequencies. We repeatedly observed decreases in the frequency of unnecessary infectivity, suggesting that carrying multiple infectivity genes is costly for the pathogen. From an applied perspective, our results indicate that varying resistance genes in space and time can be used to help control disease, even when resistance has already been overcome. Furthermore, our approach extends our ability to test not only for the efficacy of host varieties in a given year, but also for durability over multiple cropping seasons, given variation in the combination of resistance genes deployed.

Genetically-controlled plant resistance can reduce the damage caused by pathogens. However, pathogens have the ability to evolve and overcome such resistance. This often occurs quickly after resistance is deployed, resulting in significant crop losses and a continuing need to develop new resistant cultivars. To tackle this issue, several strategies have been proposed to constrain the evolution of pathogen populations and thus increase genetic resistance durability. These strategies mainly rely on varying different combinations of resistance sources across time (crop rotations) and space. The spatial scale of deployment can vary from multiple resistance sources occurring in a single cultivar (pyramiding), in different cultivars within the same field (cultivar mixtures) or in different fields (mosaics). However, experimental comparison of the efficiency (i.e. ability to reduce disease impact) and durability (i.e. ability to limit pathogen evolution and delay resistance breakdown) of landscape-scale deployment strategies presents major logistical challenges. Therefore, we developed a spatially explicit stochastic model able to assess the epidemiological and evolutionary outcomes of the four major deployment options described above, including both qualitative resistance (i.e. major genes) and quantitative resistance traits against several components of pathogen aggressiveness: infection rate, latent period duration, propagule production rate, and infectious period duration. This model, implemented in the R package landsepi, provides a new and useful tool to assess the performance of a wide range of deployment options, and helps investigate the effect of landscape, epidemiological and evolutionary parameters. This article describes the model and its parameterisation for rust diseases of cereal crops, caused by fungi of the genus Puccinia. To illustrate the model, we use it to assess the epidemiological and evolutionary potential of the combination of a major gene and different traits of quantitative resistance. The comparison of the four major deployment strategies described above will be the objective of future studies.

Microbial symbiosis is integral to plant growth and reproduction, but its contribution to global patterns of plant distribution is unknown. Legumes (Fabaceae) are a diverse and widely distributed plant family largely dependent on symbiosis with nitrogen-fixing rhizobia, which are acquired from soil after germination. This dependency is predicted to limit establishment in new geographic areas, owing to a disruption of compatible host-symbiont associations. Here we compare non-native establishment patterns of symbiotic and non-symbiotic legumes across over 3,500 species, covering multiple independent gains and losses of rhizobial symbiosis. We find that symbiotic legume species have spread to fewer non-native regions compared to non-symbiotic legumes, providing strong support for the hypothesis that lack of suitable symbionts or environmental conditions required for effective nitrogen-fixation are driving these global introduction patterns. These results highlight the importance of mutualisms in predicting non-native species establishment and the potential impacts of microbial biogeography on global plant distributions.

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.

Identification of mechanisms that allow some species to outcompete others is a fundamental goal in ecology and invasive species management. One useful approach is to examine congeners varying in invasiveness in a comparative framework across native and invaded ranges. Acacia species have been widely introduced outside their native range of Australia, and a subset of these species have become invasive in multiple parts of the world. Within specific regions, the invasive status of these species varies. Our study examined whether a key mechanism in the life history of Acacia species, the legume-rhizobia symbiosis, influences acacia invasiveness on a regional scale. To assess the extent to which species varying in invasiveness correspondingly differ with regard to the diversity of rhizobia they associate with, we grew seven Acacia species ranging in invasiveness in California in multiple soils from both their native (Australia) and introduced (California) ranges. In particular, the aim was to determine whether more invasive species formed symbioses with a wider diversity of rhizobial strains (i.e. are more promiscuous hosts). We measured and compared plant performance, including aboveground biomass, survival, and nodulation response, as well as rhizobial community composition and richness. Host promiscuity did not differ among invasiveness categories. Acacia species that varied in invasiveness differed in aboveground biomass for only one soil and did not differ in survival or nodulation within individual soils. In addition, acacias did not differ in rhizobial richness among invasiveness categories. However, nodulation differed between regions and was generally higher in the native than introduced range. Our results suggest that all Acacia species introduced to California are promiscuous hosts and that host promiscuity per se does not explain the observed differences in invasiveness within this region. Our study also highlights the utility of assessing potential mechanisms of invasion in species' native and introduced ranges., (© The Authors 2016. Published by Oxford University Press on behalf of the Annals of Botany Company.)

The ecological and evolutionary factors that drive the emergence and maintenance of variation in mutualistic benefit (i.e., the benefits provided by one partner to another) in mutualistic symbioses are not well understood. In this study, we evaluated the role that host and symbiont phylogeny might play in determining patterns of mutualistic benefit for interactions among nine species of Acacia and 31 strains of nitrogen-fixing rhizobial bacteria. Using phylogenetic comparative methods we compared patterns of variation in mutualistic benefit (host response to inoculation) to rhizobial phylogenies constructed from housekeeping and symbiosis genes; and a multigene host phylogeny. We found widespread genotype-by-genotype variation in patterns of plant growth. A relatively large component of this variation (21-28%) was strongly influenced by the interacting evolutionary histories of both partners, such that phylogenetically similar host species had similar growth responses when inoculated with phylogenetically similar rhizobia. We also found a relatively large nonphylogenetic effect for the average mutualistic benefit provided by rhizobia to plants, such that phylogenetic relatedness did not predict the overall benefit provided by rhizobia across all hosts. We conclude that phylogenetic relatedness should frequently predict patterns of mutualistic benefit in acacia-rhizobial mutualistic interactions; but that some mutualistic traits also evolve independently of the phylogenies., (© 2016 The Author(s).)

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.

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.

Plant resistance (R) genes are a crucial component in plant defence against pathogens. Although R genes often fail to provide durable resistance in an agricultural context, they frequently persist as long-lived balanced polymorphisms in nature. Standard theory explains the maintenance of such polymorphisms through a balance of the costs and benefits of resistance and virulence in a tightly coevolving host-pathogen pair. However, many plant-pathogen interactions lack such specificity. Whether, and how, balanced polymorphisms are maintained in diffusely interacting species is unknown. Here we identify a naturally interacting R gene and effector pair in Arabidopsis thaliana and its facultative plant pathogen, Pseudomonas syringae. The protein encoded by the R gene RPS5 recognizes an AvrPphB homologue (AvrPphB2) and exhibits a balanced polymorphism that has been maintained for over 2 million years (ref. 3). Consistent with the presence of an ancient balanced polymorphism, the R gene confers a benefit when plants are infected with P. syringae carrying avrPphB2 but also incurs a large cost in the absence of infection. RPS5 alleles are maintained at intermediate frequencies in populations globally, suggesting ubiquitous selection for resistance. However, the presence of P. syringae carrying avrPphB is probably insufficient to explain the RPS5 polymorphism. First, avrPphB homologues occur at very low frequencies in P. syringae populations on A. thaliana. Second, AvrPphB only rarely confers a virulence benefit to P. syringae on A. thaliana. Instead, we find evidence that selection for RPS5 involves multiple non-homologous effectors and multiple pathogen species. These results and an associated model suggest that the R gene polymorphism in A. thaliana may not be maintained through a tightly coupled interaction involving a single coevolved R gene and effector pair. More likely, the stable polymorphism is maintained through complex and diffuse community-wide interactions.

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.

Variation in host resistance and in the ability of pathogens to infect and grow (i.e. pathogenicity) is important as it provides the raw material for antagonistic (co)evolution and therefore underlies risks of disease spread, disease evolution and host shifts. Moreover, the distribution of this variation in space and time may inform us about the mode of coevolutionary selection (arms race vs. fluctuating selection dynamics) and the relative roles of G × G interactions, gene flow, selection and genetic drift in shaping coevolutionary processes. Although variation in host resistance has recently been reviewed, little is known about overall patterns in the frequency and scale of variation in pathogenicity, particularly in natural systems. Using 48 studies from 30 distinct host-pathogen systems, this review demonstrates that variation in pathogenicity is ubiquitous across multiple spatial and temporal scales. Quantitative analysis of a subset of extensively studied plant-pathogen systems shows that the magnitude of within-population variation in pathogenicity is large relative to among-population variation and that the distribution of pathogenicity partly mirrors the distribution of host resistance. At least part of the variation in pathogenicity found at a given spatial scale is adaptive, as evidenced by studies that have examined local adaptation at scales ranging from single hosts through metapopulations to entire continents and - to a lesser extent - by comparisons of pathogenicity with neutral genetic variation. Together, these results support coevolutionary selection through fluctuating selection dynamics. We end by outlining several promising directions for future research., (© 2012 The Authors. Journal of Evolutionary Biology © 2012 European Society For Evolutionary Biology.)

Host ranges are commonly quantified to classify herbivores and plant pathogens as either generalists or specialists. Here, we summarize patterns and mechanisms in the interactions of plants with these enemies along different axes of specificity. We highlight the many dimensions within which plant enemies can specify and consider the underlying ecological, evolutionary and molecular mechanisms. Host resistance traits and enemy effectors emerge as central players determining host utilization and thus host range. Finally, we review approaches to studying the causes and consequences of variation in the specificity of plant-enemy interactions. Knowledge of the molecular mechanisms that determine host range is required to understand host shifts, and evolutionary transitions among specialist and generalist strategies, and to predict potential host ranges of pathogens and herbivores., (Copyright © 2012 Elsevier Ltd. All rights reserved.)

Host-pathogen coevolution is a major driver of species diversity, with an essential role in the generation and maintenance of genetic variation in host resistance and pathogen infectivity. Little is known about how resistance and infectivity are structured across multiple geographic scales and what eco-evolutionary processes drive these patterns. Across southern Australia, the wild flax Linum marginale is frequently attacked by its rust fungus Melampsora lini. Here, we compare the genetic and phenotypic structure of resistance and infectivity among population pairs from two regions where environmental differences associate with specific life histories and mating systems. We find that both host and pathogen populations are genetically distinct between these regions. The region with outcrossing hosts and pathogens that go through asexual cycles followed by sexual reproduction showed greater diversity of resistance and infectivity phenotypes, higher levels of resistance and less clumped within-population spatial distribution of resistance. However, in the region where asexual pathogens infect selfing hosts, pathogens were more infective and better adapted to sympatric hosts. Our findings largely agree with expectations based on the distinctly different host mating systems in the two regions, with a likely advantage for hosts undergoing recombination. For the pathogen in this system, sexual reproduction may primarily be a survival mechanism in the region where it is observed. While it appears to potentially have adverse effects on local adaptation in the short term, it may be necessary for longer-term coevolution with outcrossing hosts.

Multihost pathogens occur widely on both natural and agriculturally managed hosts. Despite the importance of such generalists, evolutionary studies of host-pathogen interactions have largely focused on tightly coupled interactions between species pairs. We characterized resistance in a collection of Arabidopsis thaliana hosts, including 24 accessions collected from the Midwest USA and 24 from around the world, and patterns of virulence in a collection of Pseudomonas syringae strains, including 24 strains collected from wild Midwest populations of A. thaliana (residents) and 18 from an array of cultivated species (nonresidents). All of the nonresident strains and half of the resident strains elicited a resistance response on one or more A. thaliana accessions. The resident strains that failed to elicit any resistance response possessed an alternative type III secretion system (T3SS) that is unable to deliver effectors into plant host cells; as a result, these seemingly nonpathogenic strains are incapable of engaging in gene for gene interactions with A. thaliana. The remaining resident strains triggered greater resistance compared to nonresident strains, consistent with maladaptation of the resident bacterial population. We weigh the plausibility of two explanations: general maladaptation of pathogen strains and a more novel hypothesis whereby community level epidemiological dynamics result in adaptive dynamics favoring ephemeral hosts like A. thaliana., (© 2010 The Author(s). Evolution© 2010 The Society for the Study of Evolution.)

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.

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.

Ecological, evolutionary and molecular models of interactions between plant hosts and microbial pathogens are largely based around a concept of tightly coupled interactions between species pairs. However, highly pathogenic and obligate associations between host and pathogen species represent only a fraction of the diversity encountered in natural and managed systems. Instead, many pathogens can infect a wide range of hosts, and most hosts are exposed to more than one pathogen species, often simultaneously. Furthermore, outcomes of pathogen infection vary widely because host plants vary in resistance and tolerance to infection, while pathogens are also variable in their ability to grow on or within hosts. Environmental heterogeneity further increases the potential for variation in plant host-pathogen interactions by influencing the degree and fitness consequences of infection. Here, we describe these continua of specificity and virulence inherent within plant host-pathogen interactions. Using this framework, we describe and contrast the genetic and environmental mechanisms that underlie this variation, outline consequences for epidemiology and community structure, explore likely ecological and evolutionary drivers, and highlight several key areas for future research.

In plants, pollen- and seed-dispersal distributions are characteristically leptokurtic, with significant consequences for spatial genetic structure and nearest-neighbour mating. However, most studies to date have been on wind- or insect-pollinated species. Here, we assigned paternity to quantify effective pollen dispersal over 9 years of mating, contrasted this to seed dispersal and examined their effects on fine-scale spatial genetic structure, within the bird-pollinated shrub Banksia hookeriana (Proteaceae). We used 163 polymorphic amplified fragment length polymorphism markers to assess genetic structure and pollen dispersal in a spatially discrete population of 112 plants covering 0.56 ha. Spatial autocorrelation analysis detected spatial genetic structure in the smallest distance class of 0-5 m (r=0.025), with no significant structure beyond 8 m. Experimentally quantified seed-dispersal distances for 337 seedlings showed a leptokurtic distribution around a median of 5 m, reaching a distance of 36 m. In marked contrast, patterns of pollen dispersal for 274 seeds departed strikingly from typical near-neighbour pollination, with a distribution largely corresponding to the spatial distribution of plants. We found very high multiple paternity, very low correlated paternity and an equal probability of siring for the 50 closest potential mates. Extensive pollen carryover was demonstrated by multiple siring in 83 of 86 (96.5%) two-seeded fruits. Highly mobile nectar-feeding birds facilitate this promiscuity through observed movements that were effectively random. As the incidence of bird-pollination is markedly greater in the Southwest Australian Floristic Region than elsewhere, our results have broad and novel significance for the evolution and conservation for many species in Gondwanan lineages.

Measures of population genetic structure and diversity of disease-causing organisms are commonly used to draw inferences regarding their evolutionary history and potential to generate new variation in traits that determine interactions with their hosts. Parasite species exhibit a range of population structures and life-history strategies, including different transmission modes, life-cycle complexity, off-host survival mechanisms and dispersal ability. These are important determinants of the frequency and predictability of interactions with host species. Yet the complex causal relationships between spatial structure, life history and the evolutionary dynamics of parasite populations are not well understood. We demonstrate that a clear picture of the evolutionary potential of parasitic organisms and their demographic and evolutionary histories can only come from understanding the role of life history and spatial structure in influencing population dynamics and epidemiological patterns.

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.

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.

The pattern of accumulation of genetic variation over time in seed banks is poorly understood. We examined the genetic structure of the aerial seed bank of Banksia hookeriana within a single 15-year-old population in fire-prone southwestern Australia, and compared genetic variation between adults and each year of a 9-year-old seed bank using amplified fragment length polymorphism (AFLP). B. hookeriana is well suited to the study of seed bank dynamics due to the canopy storage of its seeds, and because each annual crop can be identified. A total of 304 seeds from nine crop years and five maternal plants were genotyped, along with 113 plants from the adult population. Genetic variation, as assessed by the proportion of polymorphic markers (P(p)) and Shannon's index (I), increased slightly within the seed bank over time, while gene diversity (H(j)), did not change. P(p), I, and H(j) all indicated that genetic variation within the seed bank quickly approached the maximal level detected. Analysis of molecular variance revealed that less than 4% of variation could be accounted for by variation among seeds produced in different years, whereas there was greater differentiation among maternal plants (12.7%), and among individual seeds produced by different maternal plants (83.4%). With increasing population age, offspring generated each year were slightly more outbred, as indicated by an increase in the mean number of nonmaternal markers per offspring. There were no significant differences for H(j) or I between adults and the seed bank. Viability of seeds decreased with age, such that the viability of 9-year-old seeds was half that of 2-year-old seeds. These results suggest that variable fire frequencies have only limited potential to influence the amount of genetic variation stored within the seed bank of B. hookeriana.