Provenance of rhizobial symbionts is similar for invasive and noninvasive acacias introduced to California.

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.

Models of Plant Resistance Deployment.

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.

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.

Different landscape effects on the genetic structure of two broadly distributed woody legumes, Acacia salicina and A. stenophylla (Fabaceae).

Restoring degraded landscapes has primarily focused on re-establishing native plant communities. However, little is known with respect to the diversity and distribution of most key revegetation species or the environmental and anthropogenic factors that may affect their demography and genetic structure. In this study, we investigated the genetic structure of two widespread Australian legume species (Acacia salicina and Acacia stenophylla) in the Murray-Darling Basin (MDB), a large agriculturally utilized region in Australia, and assessed the impact of landscape structure on genetic differentiation. We used AFLP genetic data and sampled a total of 28 A. salicina and 30 A. stenophylla sampling locations across southeastern Australia. We specifically evaluated the importance of four landscape features: forest cover, land cover, water stream cover, and elevation. We found that both species had high genetic diversity (mean percentage of polymorphic loci, 55.1% for A. salicina versus. 64.3% for A. stenophylla) and differentiation among local sampling locations (A. salicina: ΦPT = 0.301, 30%; A. stenophylla: ΦPT = 0.235, 23%). Population structure analysis showed that both species had high levels of structure (6 clusters each) and admixture in some sampling locations, particularly A. stenophylla. Although both species have a similar geographic range, the drivers of genetic connectivity for each species were very different. Genetic variation in A. salicina seems to be mainly driven by geographic distance, while for A. stenophylla, land cover appears to be the most important factor. This suggests that for the latter species, gene flow among populations is affected by habitat fragmentation. We conclude that these largely co-occurring species require different management actions to maintain population connectivity. We recommend active management of A. stenophylla in the MDB to improve gene flow in the adversity of increasing disturbances (e.g., droughts) driven by climate change and anthropogenic factors.

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.

Phylogenetic signals and predictability in plant-soil feedbacks.

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.

Novel model-based clustering reveals ecologically differentiated bacterial genomes across a large climate gradient.

A pervasive challenge in microbial ecology is understanding the genetic level where ecological units can be differentiated. Ecological differentiation often occurs at fine genomic levels, yet it is unclear how to utilise ecological information to define ecotypes given the breadth of environmental variation among microbial taxa. Here, we present an analytical framework that infers clusters along genome-based microbial phylogenies according to shared environmental responses. The advantage of our approach is the ability to identify genomic clusters that best fit complex environmental information whilst characterising cluster niches through model predictions. We apply our method to determine climate-associated ecotypes in populations of nitrogen-fixing symbionts using whole genomes, explicitly sampled to detect climate differentiation across a heterogeneous landscape. Although soil and plant host characteristics strongly influence distribution patterns of inferred ecotypes, our flexible statistical method enabled us to identify climate-associated genomic clusters using environmental data, providing solid support for ecological specialisation in soil symbionts.

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.

Linking microbial co-occurrences to soil ecological processes across a woodland-grassland ecotone.

Ecotones between distinct ecosystems have been the focus of many studies as they offer valuable insights into key drivers of community structure and ecological processes that underpin function. While previous studies have examined a wide range of above-ground parameters in ecotones, soil microbial communities have received little attention. Here we investigated spatial patterns, composition, and co-occurrences of archaea, bacteria, and fungi, and their relationships with soil ecological processes across a woodland-grassland ecotone. Geostatistical kriging and network analysis revealed that the community structure and spatial patterns of soil microbiota varied considerably between three habitat components across the ecotone. Woodland samples had significantly higher diversity of archaea while the grassland samples had significantly higher diversity of bacteria. Microbial co-occurrences reflected differences in soil properties and ecological processes. While microbial networks were dominated by bacterial nodes, different ecological processes were linked to specific microbial guilds. For example, soil phosphorus and phosphatase activity formed the largest clusters in their respective networks, and two lignolytic enzymes formed joined clusters. Bacterial ammonia oxidizers were dominant over archaeal oxidizers and showed a significant association (p < 0.001) with potential nitrification (PNR), with the PNR subnetwork being dominated by Betaproteobacteria. The top ten keystone taxa comprised six bacterial and four fungal OTUs, with Random Forest Analysis revealing soil carbon and nitrogen as the determinants of the abundance of keystone taxa. Our results highlight the importance of assessing interkingdom associations in soil microbial networks. Overall, this study shows how ecotones can be used as a model to delineate microbial structural patterns and ecological processes across adjoining land-uses within a landscape.

Spatio-temporal connectivity and host resistance influence evolutionary and epidemiological dynamics of the canola pathogen Leptosphaeria maculans.

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.

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.

Assessing the durability and efficiency of landscape-based strategies to deploy plant resistance to pathogens.

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.

Earthworm-induced shifts in microbial diversity in soils with rare versus established invasive earthworm populations.

European earthworms have colonised many parts of Australia, although their impact on soil microbial communities remains largely uncharacterised. An experiment was conducted to contrast the responses to Aporrectodea trapezoides introduction between soils from sites with established (Talmo, 64 A. trapezoides m-2) and rare (Glenrock, 0.6 A. trapezoides m-2) A. trapezoides populations. Our hypothesis was that earthworm introduction would lead to similar changes in bacterial communities in both soils. The effects of earthworm introduction (earthworm activity and cadaver decomposition) did not lead to a convergence of bacterial community composition between the two soils. However, in both soils, the Firmicutes decreased in abundance and a common set of bacteria responded positively to earthworms. The increase in the abundance of Flavobacterium, Chitinophagaceae, Rhodocyclaceae and Sphingobacteriales were consistent with previous studies. Evidence for possible soil resistance to earthworms was observed, with lower earthworm survival in Glenrock microcosms coinciding with A. trapezoides rarity in this site, lower soil organic matter and clay content and differences in the diversity and abundance of potential earthworm mutualist bacteria. These results suggest that while the impacts of earthworms vary between different soils, the consistent response of some bacteria may aid in predicting the impacts of earthworms on soil ecosystems.

Linking fungal-bacterial co-occurrences to soil ecosystem function.

Fungi and bacteria are major players in soil biogeochemical cycles, however, most studies linking soil processes to microbial function ignore the potential role of interactions between these groups. A small number of studies have used correlation network analyses to investigate fungal-bacterial co-occurrences in soil, and revealed differences, as well as overlaps, in the ecosystem roles of these groups. These results contradict the view that fungi and bacteria are two distinct functional groups which can be studied in isolation. A more comprehensive understanding of the interplay between soil properties, biogeochemical cycles and the interactions between fungi and bacteria will be an important step towards improving the prediction and management of soil ecosystem services.

The emerging science of linked plant-fungal invasions.

Contents 1314 I. 1315 II. 1316 III. 1322 IV. 1323 V. 1325 VI. 1326 VII. 1326 VIII. 1327 1328 References 1328 SUMMARY: Invasions of alien plants are typically studied as invasions of individual species, yet interactions between plants and symbiotic fungi (mutualists and potential pathogens) affect plant survival, physiological traits, and reproduction and hence invasion success. Studies show that plant-fungal associations are frequently key drivers of plant invasion success and impact, but clear conceptual frameworks and integration across studies are needed to move beyond a series of case studies towards a more predictive understanding. Here, we consider linked plant-fungal invasions from the perspective of plant and fungal origin, simplified to the least complex representations or 'motifs'. By characterizing these interaction motifs, parallels in invasion processes between pathogen and mutualist fungi become clear, although the outcomes are often opposite in effect. These interaction motifs provide hypotheses for fungal-driven dynamics behind observed plant invasion trajectories. In some situations, the effects of plant-fungal interactions are inconsistent or negligible. Variability in when and where different interaction motifs matter may be driven by specificity in the plant-fungal interaction, the size of the effect of the symbiosis (negative to positive) on plants and the dependence (obligate to facultative) of the plant-fungal interaction. Linked plant-fungal invasions can transform communities and ecosystem function, with potential for persistent legacies preventing ecosystem restoration.

Symbiosis limits establishment of legumes outside their native range at a global scale.

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.

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.

Differential plant invasiveness is not always driven by host promiscuity with bacterial symbionts.

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.