Kaikki aineistot
Lisää
Coinfections by multiple parasites predominate in the wild. Interactionsbetween parasites can be antagonistic, neutral, or facilitative, and they canhave significant implications for epidemiology, disease dynamics, and evolu-tion of virulence. Coinfections commonly result from sequential exposure ofhosts to different parasites. We argue that the sequential nature of coinfectionsis important for the consequences of infection in both natural and man-madeenvironments. Coinfections accumulate during host lifespan, determining thestructure of the parasite infracommunity. Interactions within the parasite com-munity and their joint effect on the host individual potentially shape evolution ofparasite life-history traits and transmission biology. Overall, sequential coin-fections have the potential to change evolutionary and epidemiological out-comes of host–parasite interactions widely across plant and animal systems.
While pathogenic and mutualistic microbes are ubiquitous across ecosystems and often co-occur within hosts, how they interact to determine patterns of disease in genetically diverse wild populations is unknown. To test whether microbial mutualists provide protection against pathogens, and whether this varies among host genotypes, we conducted a field experiment in three naturally-occurring epidemics of a fungal pathogen, Podosphaera plantaginis, infecting a host plant, Plantago lanceolata, in the Åland Islands, Finland. In each population, we collected epidemiological data on experimental plants from six allopatric populations that had been inoculated with a mixture of mutualistic arbuscular mycorrhizal fungi or a non-mycorrhizal control. Inoculation with arbuscular mycorrhizal fungi increased growth in plants from every population, but also increased host infection rate. Mycorrhizal effects on disease severity varied among host genotypes and strengthened over time during the epidemic. Host genotypes that were more susceptible to the pathogen received stronger protective effects from inoculation. Our results show that arbuscular mycorrhizal fungi introduce both benefits and risks to host plants, and shift patterns of infection in host populations under pathogen attack. Understanding how mutualists alter host susceptibility to disease will be important for predicting infection outcomes in ecological communities and in agriculture.
Both theory and experimental evolution studies predict migration to influence the outcome of antagonistic coevolution between hosts and their parasites, with higher migration rates leading to increased diversity and evolutionary potential. Migration rates are expected to vary in spatially structured natural pathosystems, yet how spatial structure generates variation in coevolutionary trajectories across populations occupying the same landscape has not been tested. Here, we studied the effect of spatial connectivity on host evolutionary potential in a natural pathosystem characterized by a stable Plantago lanceolata host network and a highly dynamic Podosphaera plantaginis parasite metapopulation. We designed a large inoculation experiment to test resistance of five isolated and five well-connected host populations against sympatric and allopatric pathogen strains, over 4 years. Contrary to our expectations, we did not find consistently higher resistance against sympatric pathogen strains in the well-connected populations. Instead, host local adaptation varied considerably among populations and through time with greater fluctuations observed in the well-connected populations. Jointly, our results suggest that in populations where pathogens have successfully established, they have the upper hand in the coevolutionary arms race, but hosts may be better able to respond to pathogen-imposed selection in the well-connected than in the isolated populations. Hence, the ongoing and extensive fragmentation of natural habitats may increase vulnerability to diseases.
Many pathogens possess the capacity for sex through outcrossing, despite being able to reproduce also asexually and/or via selfing. Given that sex is assumed to come at a cost, these mixed reproductive strategies typical of pathogens have remained puzzling. While the ecological and evolutionary benefits of outcrossing are theoretically well-supported, support for such benefits in pathogen populations are still scarce. Here, we analyze the epidemiology and genetic structure of natural populations of an obligate fungal pathogen, Podosphaera plantaginis. We find that the opportunities for outcrossing vary spatially. Populations supporting high levels of coinfection -a prerequisite of sex - result in hotspots of novel genetic diversity. Pathogen populations supporting coinfection also have a higher probability of surviving winter. Jointly our results show that outcrossing has direct epidemiological consequences as well as a major impact on pathogen population genetic diversity, thereby providing evidence of ecological and evolutionary benefits of outcrossing in pathogens.
Many pathogens possess the capacity for sex through outcrossing, despite being able to reproduce also asexually and/or via selfing. Given that sex is assumed to come at a cost, these mixed reproductive strategies typical of pathogens have remained puzzling. While the ecological and evolutionary benefits of outcrossing are theoretically well-supported, support for such benefits in pathogen populations are still scarce. Here, we analyze the epidemiology and genetic structure of natural populations of an obligate fungal pathogen, Podosphaera plantaginis. We find that the opportunities for outcrossing vary spatially. Populations supporting high levels of coinfection –a prerequisite of sex – result in hotspots of novel genetic diversity. Pathogen populations supporting coinfection also have a higher probability of surviving winter. Jointly our results show that outcrossing has direct epidemiological consequences as well as a major impact on pathogen population genetic diversity, thereby providing evidence of ecological and evolutionary benefits of outcrossing in pathogens.
The diversity and composition of natural communities are rapidly changing due to anthropogenic disturbances. Magnitude of this compositional reorganization varies across the globe, but reasons behind the variation remain largely unknown. Disturbances induce temporal turnover by stimulating species colonizations, causing local extinctions, altering dominance structure, or all of these. We test which of these processes drive temporal community changes, and whether they are constrained by natural environmental gradients. Moreover, we assess to what degree identity shifts translate to changes in dominance structure.
AbstractAim: Joint species distribution models (JSDMs) are an important tool for predicting ecosys-tem diversity and function under global change. The growing complexity of modern JSDMs necessitates careful model selection tailored to the challenges of community prediction under novel conditions (i.e., transferable models). Common approaches to evaluate the per-formance of JSDMs for community- level prediction are based on individual species predic-tions that do not account for the species correlation structures inherent in JSDMs. Here, we formalize a Bayesian model selection approach that accounts for species correlation structures and apply it to compare the community- level predictive performance of alterna-tive JSDMs across broad environmental gradients emulating transferable applications.Innovation: We connect the evaluation of JSDM predictions to Bayesian model selec-tion theory under which the log score is the preferred performance measure for proba-bilistic prediction. We define the joint log score for community- level prediction and distinguish it from more commonly applied JSDM evaluation metrics. We then apply the joint community log score to evaluate predictions of 1918 out- of- sample boreal for-est understory communities spanning 39 species generated using a novel multinomial JSDM framework that supports alternative species correlation structures: independent, compositional dependence and residual dependence.Main conclusions: The best performing JSDM included all observed environmental vari-ables and compositional dependence modelled using a multinomial likelihood. The ad-dition of flexible residual species correlations improved model predictions only within JSDMs applying a reduced set of environmental variables highlighting potential con-founding between unobserved environmental conditions and residual species depend-ence. The best performing JSDM was consistent across successional and bioclimatic gradients regardless of whether interest was in species- or community- level prediction. Our study demonstrates the utility of the joint community log score to compare the pre-dictive performance of JSDMs and highlights the importance of accounting for species dependence when interest is in community composition under novel conditions.
The inherently variable nature of epidemics renders predictions of when and where infection is expected to occur challenging. Differences in pathogen strain composition, diversity, fitness, and spatial distribution are generally ignored in epidemiological modeling and are rarely studied in natural populations, yet they may be important drivers of epidemic trajectories. To examine how these factors are linked to epidemics in natural host populations, we collected epidemiological and genetic data from 15 populations of the powdery mildew fungus, Podosphaera plantaginis, on Plantago lanceolata in the Åland Islands, Finland. In each population, we tracked spatiotemporal disease progression throughout one epidemic season and coupled our survey of infection with intensive field sampling of the pathogen. We found that strain composition varied greatly among populations in the landscape. Within populations, strain composition was driven by the sequence of strain activity: early-active strains reached higher abundances, leading to consistent strain compositions over time. Co-occurring strains also varied in their contribution to the growth of the local epidemic, and these fitness inequalities were linked to epidemic dynamics: a higher proportion of hosts became infected in populations containing strains that were more similar in fitness. Epidemic trajectories in the populations were also linked to strain diversity and spatial dynamics: higher infec- tion rates occurred in populations containing higher strain diversity, while spatially clustered epidemics experienced lower infection rates. Together, our results suggest that spatial and/or temporal variation in the strain composition, diversity, and fitness of pathogen populations are important factors generating variation in epidemiological trajectories among infected host populations.
Abstract Sphagnum is the major genus in northern peatlands that contributes to peat formation and carbon sequestration. Sphagnum growth in summer has been fairly well studied but the information about growth in autumn and winter is limited. Therefore, we studied how the growth of Sphagnum is seasonally distributed with a particular interest on possible winter growth. The linear increment and biomass production of three Sphagum species was measured in three Northern European bogs over a year. In all sites, our results indicate the highest annual linear increment in S. angustifolium (28 mm), followed by S. magellanicum (20 mm) and S. fuscum (13 mm), but the biomass production was fairly even among the species (189, 192 and 215 g m−2, respectively). Both linear increment and biomass production depended mostly on meteorological parameters rather than ecophysiological or microsite properties. The seasonal measurements revealed a significant linear increment and biomass production during the winter that accounted for ca. 10% and ca. 5% from the annual values, respectively. Moreover, the mean daily rates of linear increment in autumn often exceeded the increment in summer. Our results thus indicate the ability for year-around growth of Sphagna if the conditions are favorable, including during boreal winter.
After drainage for forestry and agriculture, peat extraction is one of the most important causes of peatland degradation. When peat extraction is ceased, multiple after-use options exist, including abandonment, restoration, and replacement (e.g., forestry and agricultural use). However, there is a lack of a global synthesis of after-use research. Through a systematic review of 356 peer-reviewed scientific articles, we address this research gap and examine (1) what after-use options have been studied, (2) what the studied and recognized impacts of the after-use options are, and (3) what one can learn in terms of best practices and research gaps. The research has concentrated on the impacts of restoration (N = 162), abandonment (N = 72), and replacement (N = 94), the latter of which consists of afforestation (N = 46), cultivation (N = 34) and creation of water bodies (N = 14). The studies on abandonment, restoration, and creation of water bodies have focused mostly on analyzing vegetation and greenhouse gas (GHG) fluxes, while the studies assessing afforestation and cultivation sites mostly evaluate the provisioning ecosystem services. The studies show that active restoration measures speed-up vegetation recolonization on bare peat areas, reduce GHG emissions and decrease negative impacts on water systems. The most notable research gap is the lack of studies comparing the environmental and social impacts of the after-use options. Additionally, there is a lack of studies focusing on social impacts and downstream hydrology, as well as long-term monitoring of GHG fluxes. Based on the reviewed studies, a comparison of the impacts of the after-use options is not straightforward. We emphasize a need for comparative empirical research in the extracted sites with a broad socio-ecological and geographical context.