Intraspecific functional diversity in hosts and its effect on disease risk across a climatic gradient

The proportion of resistant hosts in mixtures should be biased towards the resistance with the lowest breaking cost

Current agricultural practices facilitate emergence and spread of plant diseases through the wide use of monocultures. Host mixtures are a promising alternative for sustainable plant disease control. Their effectiveness can be partly explained by priming-induced cross-protection among plants. Priming occurs when plants are challenged with non-infective pathogen genotypes, resulting in increased resistance to subsequent infections by infective pathogen genotypes. We developed an epidemiological model to explore how mixing two distinct resistant varieties can reduce disease prevalence. We considered a pathogen population composed of three genotypes infecting either one or both varieties. We found that host mixtures should not contain an equal proportion of resistant plants, but a biased ratio (e.g. 80 : 20) to minimize disease prevalence. Counter-intuitively, the optimal ratio of resistant varieties should contain a lower proportion of the costliest resistance for the pathogen to break. This benefit is amplified by priming. This strategy also prevents the invasion of pathogens breaking all resistances.

Is It in the Stars? Exploring the Relationships between Species' Traits and Sea Star Wasting Disease

AbstractAn explanation for variation in impacts of sea star wasting disease across asteroid species remains elusive. Although various traits have been suggested to play a potential role in sea star wasting susceptibility, currently we lack a thorough comparison that explores how life-history and natural history traits shape responses to mass mortality across diverse asteroid taxa. To explore how asteroid traits may relate to sea star wasting, using available data and recognizing the potential for biological correlations to be driven by phylogeny, we generated a supertree, tested traits for phylogenetic association, and evaluated associations between traits and sea star wasting impact. Our analyses show no evidence for a phylogenetic association with sea star wasting impact, but there does appear to be phylogenetic association for a subset of asteroid life-history traits, including diet, substrate, and reproductive season. We found no relationship between sea star wasting and developmental mode, diet, pelagic larval duration, or substrate but did find a relationship with minimum depth, reproductive season, and rugosity (or surface complexity). Species with the greatest sea star wasting impacts tend to have shallower minimum depth distributions, they tend to have their median reproductive period 1.5 months earlier, and they tend to have higher rugosities relative to species less affected by sea star wasting. Fully understanding sea star wasting remains challenging, in part because dramatic gaps still exist in our understanding of the basic biology and phylogeny of asteroids. Future studies would benefit from a more robust phylogenetic understanding of sea stars, as well as leveraging intra- and interspecific comparative transcriptomics and genomics to elucidate the molecular pathways responding to sea star wasting.

'Resistance Mixtures' Reduce Insect Herbivory in Strawberry (Fragaria vesca) Plantations

The transition toward more sustainable plant protection with reduced pesticide use is difficult, because there is no "silver bullet" available among nonchemical tools. Integrating several plant protection approaches may thus be needed for efficient pest management. Recently, increasing the genetic diversity of plantations via cultivar mixing has been proposed as a possible method to reduce pest damage. However, previous studies have not addressed either the relative efficiency of exploiting cultivar mixing and intrinsic plant herbivore resistance or the potential utility of combining these approaches to increase cropping security. Here, using a full factorial experiment with 60 woodland strawberry plots, we tested for the relative and combined effect of cultivar mixing and intrinsic plant resistance on herbivore damage and yield. The experiment comprised two levels of diversity ("high" with 10 varieties and "low" with two varieties) and three levels of resistance ("resistant" comprising only varieties intrinsically resistant against strawberry leaf beetle Galerucella tenella; "susceptible" with susceptible varieties only; and "resistance mixtures" with 50:50 mixtures of resistant and susceptible varieties). The experiment was carried out over two growing seasons. Use of resistant varieties either alone or intermixed with susceptible varieties in "resistance mixtures" reduced insect herbivory. Interestingly, resistant varieties not only reduced the mean damage in "resistance mixtures" by themselves being less damaged, but also protected intermixed susceptible varieties via associational resistance. The effect of higher genetic diversity was less evident, reducing herbivory only at the highest level of herbivore damage. In general, herbivory was lowest in plots with high diversity that included at least some resistant varieties and highest in low diversity plots consisting only of susceptible varieties. Despite this, no significant difference in yield (fruit biomass) was found, indicating that strawberry may be relatively tolerant. Our results demonstrate that combined use of high genetic diversity and resistant varieties can help reduce pest damage and provide a useful tool for sustainable food production. "Resistance mixtures" may be particularly useful for sensitive food crops where susceptible varieties are high yielding that could not be completely replaced by resistant ones.

Biotic and abiotic drivers of intraspecific trait variation within plant populations of three herbaceous plant species along a latitudinal gradient

Background

The importance of intraspecific trait variation (ITV) is increasingly acknowledged among plant ecologists. However, our understanding of what drives ITV between individual plants (ITV_BI) at the population level is still limited. Contrasting theoretical hypotheses state that ITV_BI can be either suppressed (stress-reduced plasticity hypothesis) or enhanced (stress-induced variability hypothesis) under high abiotic stress. Similarly, other hypotheses predict either suppressed (niche packing hypothesis) or enhanced ITV_BI (individual variation hypothesis) under high niche packing in species rich communities. In this study we assess the relative effects of both abiotic and biotic niche effects on ITV_BI of four functional traits (leaf area, specific leaf area, plant height and seed mass), for three herbaceous plant species across a 2300 km long gradient in Europe. The study species were the slow colonizing Anemone nemorosa, a species with intermediate colonization rates, Milium effusum, and the fast colonizing, non-native Impatiens glandulifera.

Results

Climatic stress consistently increased ITV_BI across species and traits. Soil nutrient stress, on the other hand, reduced ITV_BI for A. nemorosa and I. glandulifera, but had a reversed effect for M. effusum. We furthermore observed a reversed effect of high niche packing on ITV_BI for the fast colonizing non-native I. glandulifera (increased ITV_BI), as compared to the slow colonizing native A. nemorosa and M. effusum (reduced ITV_BI). Additionally, ITV_BI in the fast colonizing species tended to be highest for the vegetative traits plant height and leaf area, but lowest for the measured generative trait seed mass.

Conclusions

This study shows that stress can both reduce and increase ITV_BI, seemingly supporting both the stress-reduced plasticity and stress-induced variability hypotheses. Similarly, niche packing effects on ITV_BI supported both the niche packing hypothesis and the individual variation hypothesis. These results clearly illustrates the importance of simultaneously evaluating both abiotic and biotic factors on ITV_BI. This study adds to the growing realization that within-population trait variation should not be ignored and can provide valuable ecological insights.

Electronic supplementary material

The online version of this article (10.1186/s12898-017-0151-y) contains supplementary material, which is available to authorized users.

Mosaics often outperform pyramids: insights from a model comparing strategies for the deployment of plant resistance genes against viruses in agricultural landscapes

The breakdown of plant virus resistance genes is a major issue in agriculture. We investigated whether a set of resistance genes would last longer when stacked into a single plant cultivar (pyramiding) or when deployed individually in regional mosaics (mosaic strategy). We modeled the genetic and epidemiological processes shaping the demogenetic dynamics of viruses under a multilocus gene-for-gene system, from the plant to landscape scales. The landscape consisted of many fields, was subject to seasonality, and of a reservoir hosting viruses year-round. Strategy performance depended principally on the fitness costs of adaptive mutations, epidemic intensity before resistance deployment and landscape connectivity. Mosaics were at least as good as pyramiding strategies in most production situations tested. Pyramiding strategies performed better only with slowly changing virus reservoir dynamics. Mosaics are more versatile than pyramiding strategies, and we found that deploying a mosaic of three to five resistance genes generally provided effective disease control, unless the epidemics were driven mostly by within-field infections. We considered the epidemiological and evolutionary mechanisms underlying the greater versatility of mosaics in our case study, with a view to providing breeders and growers with guidance as to the most appropriate deployment strategy.

Cropping system diversification for food production in Mindanao rubber plantations: a rice cultivar mixture and rice intercropped with mungbean

Including food production in non-food systems, such as rubber plantations and biofuel or bioenergy crops, may contribute to household food security. We evaluated the potential for planting rice, mungbean, rice cultivar mixtures, and rice intercropped with mungbean in young rubber plantations in experiments in the Arakan Valley of Mindanao in the Philippines. Rice mixtures consisted of two- or three-row strips of cultivar Dinorado, a cultivar with higher value but lower yield, and high-yielding cultivar UPL Ri-5. Rice and mungbean intercropping treatments consisted of different combinations of two- or three-row strips of rice and mungbean. We used generalized linear mixed models to evaluate the yield of each crop alone and in the mixture or intercropping treatments. We also evaluated a land equivalent ratio for yield, along with weed biomass (where Ageratum conyzoides was particularly abundant), the severity of disease caused by Magnaporthe oryzae and Cochliobolus miyabeanus, and rice bug (Leptocorisa acuta) abundance. We analyzed the yield ranking of each cropping system across site-year combinations to determine mean relative performance and yield stability. When weighted by their relative economic value, UPL Ri-5 had the highest mean performance, but with decreasing performance in low-yielding environments. A rice and mungbean intercropping system had the second highest performance, tied with high-value Dinorado but without decreasing relative performance in low-yielding environments. Rice and mungbean intercropped with rubber have been adopted by farmers in the Arakan Valley.

The evolution of plant virus transmission pathways

The evolution of plant virus transmission pathways is studied through transmission via seed, pollen, or a vector. We address the questions: under what circumstances does vector transmission make pollen transmission redundant? Can evolution lead to the coexistence of multiple virus transmission pathways? We restrict the analysis to an annual plant population in which reproduction through seed is obligatory. A semi-discrete model with pollen, seed, and vector transmission is formulated to investigate these questions. We assume vector and pollen transmission rates are frequency-dependent and density-dependent, respectively. An ecological stability analysis is performed for the semi-discrete model and used to inform an evolutionary study of trade-offs between pollen and seed versus vector transmission. Evolutionary dynamics critically depend on the shape of the trade-off functions. Assuming a trade-off between pollen and vector transmission, evolution either leads to an evolutionarily stable mix of pollen and vector transmission (concave trade-off) or there is evolutionary bi-stability (convex trade-off); the presence of pollen transmission may prevent evolution of vector transmission. Considering a trade-off between seed and vector transmission, evolutionary branching and the subsequent coexistence of pollen-borne and vector-borne strains is possible. This study contributes to the theory behind the diversity of plant-virus transmission patterns observed in nature.

Epidemiological and evolutionary management of plant resistance: optimizing the deployment of cultivar mixtures in time and space in agricultural landscapes

The management of genes conferring resistance to plant–pathogens should make it possible to control epidemics (epidemiological perspective) and preserve resistance durability (evolutionary perspective). Resistant and susceptible cultivars must be strategically associated according to the principles of cultivar mixture (within a season) and rotation (between seasons). We explored these questions by modeling the evolutionary and epidemiological processes shaping the dynamics of a pathogen population in a landscape composed of a seasonal cultivated compartment and a reservoir compartment hosting pathogen year-round. Optimal deployment strategies depended mostly on the molecular basis of plant–pathogen interactions and on the agro-ecological context before resistance deployment, particularly epidemic intensity and landscape connectivity. Mixtures were much more efficient in landscapes in which between-field infections and infections originating from the reservoir were more prevalent than within-field infections. Resistance genes requiring two mutations of the pathogen avirulence gene to be broken down, rather than one, were particularly useful when infections from the reservoir predominated. Combining mixture and rotation principles were better than the use of the same mixture each season as (i) they controlled epidemics more effectively in situations in which within-field infections or infections from the reservoir were frequent and (ii) they fulfilled the epidemiological and evolutionary perspectives.

A Combination of Species Evenness and Functional Diversity Is the Best Predictor of Disease Risk in Multihost Communities

Although accumulated evidence has shown that biodiversity can play an important role in disease transmission and prevalence, it remains unclear how different measures of diversity based on taxonomy or function perform in predicting disease risk. In this article, we assess the relative ability of species richness, Shannon's evenness index, single functional traits, and several functional diversity metrics and their interactions to predict disease risk in both nonequilibrium and equilibrium communities simulated by a multihost epidemiological model. On the basis of generalized linear models and Akaike's information criterion, we found that Shannon's evenness index outperforms species richness as a single variable in explaining variation in disease risk, while the best combination consists of Shannon's evenness index and functional diversity. This study is, to our knowledge, the first to demonstrate the important role played by species evenness and functional diversity in accounting for variation in disease risk in multihost communities.

Experimental evidence for an intraspecific Janzen-Connell effect mediated by soil biota

The negative effect of soil pathogens on seedling survival varies considerably among conspecific individuals, but the underlying mechanisms are largely unknown. For variation between heterospecifics, a common explanation is the Janzen-Connell effect: negative density dependence in survival due to specialized pathogens aggregating on common hosts. We test whether an intraspecific Janzen-Connell effect exists, i.e., whether the survival chances of one population's seedlings surrounded by a different conspecific population increase with genetic difference, spatial distance, and trait dissimilarity between them. In a shade-house experiment, we grew seedlings of five populations of each of two subtropical tree species (Castanopsis fissa and Canarium album) for which we measured genetic distance using intersimple sequence repeat (ISSR) analysis and eight common traits/characters, and we treated them with soil material or soil biota filtrate collected from different populations. We found that the relative survival rate increased with increasing dissimilarity measured by spatial distance, genetic distance, and trait differences between the seedling and the population around which the soil was collected. This effect disappeared after soil sterilization. Our results provide evidence that genetic variation, trait similarity, and spatial distance can explain intraspecific variation in plant-soil biotic interactions and suggest that limiting similarity also occurs at the intraspecific level.

History, Epidemic Evolution, and Model Burn-In for a Network of Annual Invasion: Soybean Rust

Ecological history may be an important driver of epidemics and disease emergence. We evaluated the role of history and two related concepts, the evolution of epidemics and the burn-in period required for fitting a model to epidemic observations, for the U.S. soybean rust epidemic (caused by Phakopsora pachyrhizi). This disease allows evaluation of replicate epidemics because the pathogen reinvades the United States each year. We used a new maximum likelihood estimation approach for fitting the network model based on observed U.S. epidemics. We evaluated the model burn-in period by comparing model fit based on each combination of other years of observation. When the miss error rates were weighted by 0.9 and false alarm error rates by 0.1, the mean error rate did decline, for most years, as more years were used to construct models. Models based on observations in years closer in time to the season being estimated gave lower miss error rates for later epidemic years. The weighted mean error rate was lower in backcasting than in forecasting, reflecting how the epidemic had evolved. Ongoing epidemic evolution, and potential model failure, can occur because of changes in climate, host resistance and spatial patterns, or pathogen evolution.

Host Genotype and Coinfection Modify the Relationship of within and between Host Transmission

Variation in individual-level disease transmission is well documented, but the underlying causes of this variation are challenging to disentangle in natural epidemics. In general, within-host replication is critical in determining the extent to which infected hosts shed transmission propagules, but which factors cause variation in this relationship are poorly understood. Here, using a plant host, Plantago lanceolata, and the powdery mildew fungus Podosphaera plantaginis, we quantify how the distinct stages of within-host spread (autoinfection), spore release, and successful transmission to new hosts (alloinfection) are influenced by host genotype, pathogen genotype, and the coinfection status of the host. We find that within-host spread alone fails to predict transmission rates, as this relationship is modified by genetic variation in hosts and pathogens. Their contributions change throughout the course of the epidemic. Host genotype and coinfection had particularly pronounced effects on the dynamics of spore release from infected hosts. Confidently predicting disease spread from local levels of individual transmission, therefore, requires a more nuanced understanding of genotype-specific infection outcomes. This knowledge is key to better understanding the drivers of epidemiological dynamics and the resulting evolutionary trajectories of infectious disease.

Climate change may have limited effect on global risk of potato late blight

Weather affects the severity of many plant diseases, and climate change is likely to alter the patterns of crop disease severity. Evaluating possible future patterns can help focus crop breeding and disease management research. We examined the global effect of climate change on potato late blight, the disease that caused the Irish potato famine and still is a common potato disease around the world. We used a metamodel and considered three global climate models for the A2 greenhouse gas emission scenario for three 20-year time-slices: 2000-2019, 2040-2059 and 2080-2099. In addition to global analyses, five regions were evaluated where potato is an important crop: the Andean Highlands, Indo-Gangetic Plain and Himalayan Highlands, Southeast Asian Highlands, Ethiopian Highlands, and Lake Kivu Highlands in Sub-Saharan Africa. We found that the average global risk of potato late blight increases initially, when compared with historic climate data, and then declines as planting dates shift to cooler seasons. Risk in the agro-ecosystems analyzed, varied from a large increase in risk in the Lake Kivu Highlands in Rwanda to decreases in the Southeast Asian Highlands of Indonesia.

The contribution of intra- and interspecific tolerance variability to biodiversity changes along toxicity gradients

The worldwide distribution of toxicants is an important yet understudied driver of biodiversity, and the mechanisms relating toxicity to diversity have not been adequately explored. Here, we present a community model integrating demography, dispersal and toxicant-induced effects on reproduction driven by intraspecific and interspecific variability in toxicity tolerance. We compare model predictions to 458 species abundance distributions (SADs) observed along concentration gradients of toxicants to show that the best predictions occur when intraspecific variability is five and ten times higher than interspecific variability. At high concentrations, lower settings of intraspecific variability resulted in predictions of community extinction that were not supported by the observed SADs. Subtle but significant species losses at low concentrations were predicted only when intraspecific variability dominated over interspecific variability. Our results propose intraspecific variability as a key driver for biodiversity sustenance in ecosystems challenged by environmental change.

Quantitative plant resistance in cultivar mixtures: wheat yellow rust as a modeling case study

Unlike qualitative plant resistance, which confers immunity to disease, quantitative resistance confers only a reduction in disease severity and this can be nonspecific. Consequently, the outcome of its deployment in cultivar mixtures is not easy to predict, as on the one hand it may reduce the heterogeneity of the mixture, but on the other it may induce competition between nonspecialized strains of the pathogen. To clarify the principles for the successful use of quantitative plant resistance in disease management, we built a parsimonious model describing the dynamics of competing pathogen strains spreading through a mixture of cultivars carrying nonspecific quantitative resistance. Using the parameterized model for a wheat-yellow rust system, we demonstrate that a more effective use of quantitative resistance in mixtures involves reinforcing the effect of the highly resistant cultivars rather than replacing them. We highlight the fact that the judicious deployment of the quantitative resistance in two- or three-component mixtures makes it possible to reduce disease severity using only small proportions of the highly resistant cultivar. Our results provide insights into the effects on pathogen dynamics of deploying quantitative plant resistance, and can provide guidance for choosing appropriate associations of cultivars and optimizing diversification strategies.

Identifying highly connected counties compensates for resource limitations when evaluating national spread of an invasive pathogen

Surveying invasive species can be highly resource intensive, yet near-real-time evaluations of invasion progress are important resources for management planning. In the case of the soybean rust invasion of the United States, a linked monitoring, prediction, and communication network saved U.S. soybean growers approximately $200 M/yr. Modeling of future movement of the pathogen (Phakopsora pachyrhizi) was based on data about current disease locations from an extensive network of sentinel plots. We developed a dynamic network model for U.S. soybean rust epidemics, with counties as nodes and link weights a function of host hectarage and wind speed and direction. We used the network model to compare four strategies for selecting an optimal subset of sentinel plots, listed here in order of increasing performance: random selection, zonal selection (based on more heavily weighting regions nearer the south, where the pathogen overwinters), frequency-based selection (based on how frequently the county had been infected in the past), and frequency-based selection weighted by the node strength of the sentinel plot in the network model. When dynamic network properties such as node strength are characterized for invasive species, this information can be used to reduce the resources necessary to survey and predict invasion progress.

Influence of cultivated landscape composition on variety resistance: an assessment based on wheat leaf rust epidemics

In plant pathology, the idea of designing variety management strategies at the scale of cultivated landscapes is gaining more and more attention. This requires the identification of effects that take place at large scales on host and pathogen populations. Here, we show how the landscape varietal composition influences the resistance level (as measured in the field) of the most grown wheat varieties by altering the structure of the pathogen populations. For this purpose, we jointly analysed three large datasets describing the wheat leaf rust pathosystem (Puccinia triticina/Triticum aestivum) at the country scale of France with a Bayesian hierarchical model. We showed that among all compatible pathotypes, some were preferentially associated with a variety, that the pathotype frequencies on a variety were affected by the landscape varietal composition, and that the observed resistance level of a variety was linked to the frequency of the most aggressive pathotypes among all compatible pathotypes. This data exploration establishes a link between the observed resistance level of a variety and landscape composition at the national scale. It illustrates that the quantitative aspects of the host-pathogen relationship have to be considered in addition to the major resistance/virulence factors in landscape epidemiology approaches.

Genomic and resistance gene homolog diversity of the dominant tallgrass prairie species across the U.S. Great Plains precipitation gradient

BACKGROUND

Environmental variables such as moisture availability are often important in determining species prevalence and intraspecific diversity. The population genetic structure of dominant plant species in response to a cline of these variables has rarely been addressed. We evaluated the spatial genetic structure and diversity of Andropogon gerardii populations across the U.S. Great Plains precipitation gradient, ranging from approximately 48 cm/year to 105 cm/year.

METHODOLOGY/PRINCIPAL FINDINGS

Genomic diversity was evaluated with AFLP markers and diversity of a disease resistance gene homolog was evaluated by PCR-amplification and digestion with restriction enzymes. We determined the degree of spatial genetic structure using Mantel tests. Genomic and resistance gene homolog diversity were evaluated across prairies using Shannon's index and by averaging haplotype dissimilarity. Trends in diversity across prairies were determined using linear regression of diversity on average precipitation for each prairie. We identified significant spatial genetic structure, with genomic similarity decreasing as a function of distance between samples. However, our data indicated that genome-wide diversity did not vary consistently across the precipitation gradient. In contrast, we found that disease resistance gene homolog diversity was positively correlated with precipitation.

SIGNIFICANCE

Prairie remnants differ in the genetic resources they maintain. Selection and evolution in this disease resistance homolog is environmentally dependent. Overall, we found that, though this environmental gradient may not predict genomic diversity, individual traits such as disease resistance genes may vary significantly.

Networks in plant epidemiology: from genes to landscapes, countries, and continents

There is increasing use of networks in ecology and epidemiology, but still relatively little application in phytopathology. Networks are sets of elements (nodes) connected in various ways by links (edges). Network analysis aims to understand system dynamics and outcomes in relation to network characteristics. Many existing natural, social, and technological networks have been shown to have small-world (local connectivity with short-cuts) and scale-free (presence of super-connected nodes) properties. In this review, we discuss how network concepts can be applied in plant pathology from the molecular to the landscape and global level. Wherever disease spread occurs not just because of passive/natural dispersion but also due to artificial movements, it makes sense to superimpose realistic models of the trade in plants on spatially explicit models of epidemic development. We provide an example of an emerging pathosystem (Phytophthora ramorum) where a theoretical network approach has proven particularly fruitful in analyzing the spread of disease in the UK plant trade. These studies can help in assessing the future threat posed by similar emerging pathogens. Networks have much potential in plant epidemiology and should become part of the standard curriculum.

Beyond yield: plant disease in the context of ecosystem services

The ecosystem services concept provides a means to define successful disease management more broadly, beyond short-term crop yield evaluations. Plant disease can affect ecosystem services directly, such as through removal of plants providing services, or indirectly through the effects of disease management activities, including pesticide applications, tillage, and other methods of plant removal. Increased plant biodiversity may reduce disease risk if susceptible host tissue becomes less common, or may increase risk if additional plant species are important in completing pathogen life cycles. Arthropod and microbial biodiversity may play similar roles. Distant ecosystems may provide a disservice as the setting for the evolution of pathogens that later invade a focal ecosystem, where plants have not evolved defenses. Conversely, distant ecosystems may provide a service as sources of genetic resources of great value to agriculture, including disease resistance genes. Good policies are needed to support conservation and optimal use of genetic resources, protect ecosystems from exotic pathogens, and limit the homogeneity of agricultural systems. Research is needed to provide policy makers, farmers, and consumers with the information required for evaluating trade-offs in the pursuit of the full range of ecosystem services desired from managed and native ecosystems.