Fletcher W. Halliday

Diverse ecological communities can reduce pathogen transmission; a phenomenon known as the dilution effect of biodiversity. This effect, in turn, depends on variation in host species’ ability to spread disease (i.e., host competence) and which host species persist under biodiversity loss. Mutualistic symbionts can influence host competence and are sensitive to variation in host biodiversity; yet whether mutualists can modify dilution effects is unknown, partially because quantifying host competence during epidemics remains challenging. We experimentally tested whether mutualists could modify dilution effects by establishing gradients of host species richness, community competence, and access to the below-ground arbuscular mycorrhizal fungus (AMF), Rhizoglomus irregulare . Plant hosts were then exposed to the fungal root pathogen, Rhizoctonia solani , and disease spread was monitored over the course of an epidemic. Overall, host richness did not affect epidemic outcomes. Instead, AMF inoculation increased disease risk via species-specific increases in host competence. Moreover, communities containing highly competent host species experienced more disease, but only in the presence of mutualistic AMF. These results underscore the importance of plant community composition in mycorrhiza-mediated disease dynamics and suggest that predicting disease in our changing word might require a deeper understanding of host-symbiont and pathogen-symbiont interactions under global change.

Herbivory is a key ecological process shaping biodiversity and ecosystem functioning. Predicting herbivory under global change is challenging due to interacting drivers and ecosystem complexity, but mechanistic insights can improve forecasts. Here, we specifically examined how two important global change factors—drought and infectious disease—influence herbivory in plants of different climatic origins, and how we can use intraspecific trait variation to make general predictions. We further examined whether trait–herbivory relationships change in these different environmental contexts. In a manipulative field study, we grew 1161 plant individuals from seeds of 65 populations from 18 distantly related grassland species. Using a common garden experiment, we factorially crossed a drought treatment (by reducing irrigation) and a pathogen removal treatment (by applying fungicide) on plants originating along an elevation gradient. We measured invertebrate herbivory and five key plant traits that potentially mediate herbivory. We used generalized linear mixed effects models and structural equation modelling to test how global change shapes plant traits, herbivory and trait–herbivory links. All plant traits were affected by at least one treatment, and four of the five measured plant traits were associated with herbivory (leaf dry matter content, specific leaf area, biomass, leaf area). Contrary to our expectations, trait–herbivory links were robust across experimental treatments. While global change treatments had limited net effects on herbivory, leaf dry matter content and biomass appeared to mediate environmentally induced changes in herbivory in a counterbalancing manner. Furthermore, populations that originated on higher elevations tended to be most susceptible to herbivory. Synthesis : In classic trait‐based approaches, traits reflect different plant strategies that evolved over long‐term evolutionary timescales. Our study indicates that these trade‐offs also emerge consistently across populations within single species, yielding similar ecological consequences. This is exemplified by increased herbivore susceptibility of plants from high elevation origins, mediated by their decreased leaf dry matter contents, a trait that reflects plant defence levels. Ultimately, the stability of trait–herbivory relationships across environmental gradients suggests that growth–defence trade‐offs are conserved across biological scales, suggesting that accounting for within‐species trait variation could improve predictions of future ecosystem processes.

Plant diseases occurring across wild and crop plants present modelling and management challenges. Wild plant and crop pathosystems differ in ecological structure, evolutionary dynamics and responsiveness to human intervention. At the interface, pathogens may spill over, spill back, persist or evolve, shaped by host diversity, dispersal processes and landscape connectivity. The potential importance of factors including pathogen dispersal, host life history and spatial configuration are examined through a qualitative comparison of case studies: Puccinia graminis, Phakopsora pachyrhizi, Xylella fastidiosa, Pyricularia oryzae Triticum lineage and Austropuccinia psidii. These examples illustrate how wild hosts may function as reservoirs, recombination partners or spillover targets, and how their role influences management efficacy and evolutionary risk. We explore the consequences of this wild–crop interface through two central questions: (i) how should plant diseases involving wild and cultivated pathosystems be managed, and (ii) what proportion of management effort should be allocated to each system? We show the principles underpinning answers to these questions via a conceptual framework based on a generic compartmental model incorporating asymmetric transmission and system-specific interventions, thereby accounting for key aspects of pathogen spread within and between wild host and crop populations. Finally, we identify critical data needs and modelling directions to better inform disease management on the wild plant–crop interface and argue for a more integrative approach bridging ecological and anthropogenic drivers of epidemics. This article is part of the theme issue ‘Wild plant pathosystems’.

The seasonal timing of pathogen development, i.e. its phenology, may be determined by host or environmental cues and shape pathogen communities. Yet, it is less clear to what degree seasonal patterns of pathogen community assembly vary over longer timescales and how strongly variation is determined by local environmental factors. This raises two general questions: how repeatable is seasonal pathogen community assembly across years? If community assembly is not repeatable, what role does environmental variation play in driving differing patterns of pathogen phenology? To address these questions, we tracked fungal pathogen prevalences in a field population of grass, tall fescue (Lolium arundinaceum) , over 3 years and used multivariate analyses to test for concordance between pathogen community assembly and seasonal environmental conditions. Ordination analyses showed that pathogen communities began at a similar community state each spring but diverged among years as the growing season progressed. To examine this, we tested for concordance between variation in the whole pathogen community structure and environmental conditions. Dissimilarity in pathogen community assembly was largely explained by interannual variation in environmental conditions, with precipitation and relative humidity being most important. Taken together, our results suggest linkages between interannual variation in environmental conditions and pathogen community assembly. This article is part of the theme issue ‘Wild plant pathosystems’.

Forecasting disease epidemics may require considering both abiotic and biotic conditions. Abiotic conditions can influence pathogen dispersal, survival, and infection, while prior infection by one pathogen species can alter host susceptibility to subsequent pathogens, creating historical contingencies. Yet, the relative importance of environmental conditions, within-host pathogen interactions, and their potential interplay in predicting seasonal disease dynamics remain underexplored. To better understand these interactions and improve ecological forecasts of disease risk, we analyzed more than 41,000 plant-level observations of three foliar fungal diseases on the grass species tall fescue in North Carolina, collected from 2017–2024. We built temporally explicit random forest models which for two of the three focal diseases accurately (>80%) predicted future disease dynamics from a complex abiotic and biotic predictor space. From these models, we identified key environmental thresholds that intensified annual epidemics. We then supplemented those machine-learning models with Bayesian hierarchical models and survival analyses, finding that pathogen-pathogen interactions can be as important as environmental conditions in predicting disease risk. Furthermore, for two of the three focal diseases, prior infection by a different pathogen facilitated the subsequent infection and the strength of this facilitation was modulated by environmental context. From this study we draw two major conclusions, one ecological and one methodological. First, knowledge of a host’s current disease state may be as important as local environmental conditions for predicting disease dynamics. Second, by integrating complementary modeling approaches, we can develop both predictive forecasts and mechanistic insight into the biotic and abiotic drivers of infectious disease. Open Research Statement: All data and code used to generate the results contained in this paper are available on GitHub ( https://github.com/cb-scott/WidenerLongTermAnalysis ). Upon publication the final version of all scripts and datafiles will be archived on Zenodo with a permanent DOI.

Many disease epidemics recur seasonally, and such seasonal epidemics can be shaped by species interactions among parasites, pathogens, or other microbes. Field experiments are a classic approach for understanding species interactions but are rarely used to study seasonal epidemics. Our research objective was to help fill this gap by manipulating the seasonal timing of the establishment of infectious diseases while tracking epidemics and other ecological responses. To do this, we conducted a multiyear field experiment in an old field in the Piedmont of North Carolina, USA, dominated by the grass species tall fescue ( Lolium arundinaceum (Schreb). Darbysh). In the field, tall fescue experienced seasonal epidemics of multiple foliar fungal diseases: anthracnose in spring, brown patch in mid‐summer, and crown rust in late summer to fall. In a fully randomized design, we applied four fungicide treatments to replicate plots of intact vegetation in specific seasons to manipulate the timing of disease epidemics. One treatment was designed to delay the establishment of anthracnose until mid‐summer, and another to delay the establishment of both anthracnose and brown patch until fall. In a third treatment, fungicide was applied year‐round, and, in a fourth treatment, fungicide was never applied. The experiment comprised 64 plots, each 2 m × 2 m, surveyed from May 2017 to February 2020. Here, we report a dataset documenting responses in the community structure of both plants and foliar fungi. To track disease prevalence in the host population across seasons and years, this dataset includes monthly leaf‐level observations of the disease status of over 100,000 leaves. To quantify transmission and investigate within‐host pathogen interactions, we longitudinally surveyed disease status in host individuals of known age at least weekly over two growing seasons. Finally, the dataset includes annual data on infection prevalence of the systemic fungal endophyte Epichloë coenophiala , community‐level aboveground plant biomass, and plant community cover. These data can be used for meta‐analyses, comparisons, and syntheses across systems as ecologists seek to predict and mechanistically understand seasonal disease epidemics. There are no copyrights on the dataset, and we request that users of this dataset cite this paper in all publications resulting from its use.

Emerging infectious diseases, biodiversity loss, and anthropogenic environmental change are interconnected crises with massive social and ecological costs. In this Review, we discuss how pathogens and parasites are responding to global change, and the implications for pandemic prevention and biodiversity conservation. Ecological and evolutionary principles help to explain why both pandemics and wildlife die-offs are becoming more common; why land-use change and biodiversity loss are often followed by an increase in zoonotic and vector-borne diseases; and why some species, such as bats, host so many emerging pathogens. To prevent the next pandemic, scientists should focus on monitoring and limiting the spread of a handful of high-risk viruses, especially at key interfaces such as farms and live-animal markets. But to address the much broader set of infectious disease risks associated with the Anthropocene, decision-makers will need to develop comprehensive strategies that include pathogen surveillance across species and ecosystems; conservation-based interventions to reduce human–animal contact and protect wildlife health; health system strengthening; and global improvements in epidemic preparedness and response. Scientists can contribute to these efforts by filling global gaps in disease data, and by expanding the evidence base for disease–driver relationships and ecological interventions.

Plant pathogens are important for community assembly and ecosystem functioning and respond to a variety of abiotic and biotic factors, which may change along elevational gradients. Thus, elevational gradients are a valuable model system for exploring how environmental, plant community and soil factors influence pathogen communities. Yet, how these factors influence pathogens in natural ecosystems remains poorly understood. We examined the dynamics of plant fungal pathogens along elevational gradients, as well as the mechanisms shaping these dynamics, by combining a field survey on the Tibetan Plateau with a global meta‐analysis. In the field survey, increasing elevation was associated with a decrease in soil fungal pathogen richness but not in foliar fungal disease symptoms. Elevation was primarily related to soil fungal pathogen richness through abiotic factors, whereas no association was found between elevation and foliar fungal diseases. The meta‐analysis confirmed the generality of our field survey results: elevation was associated with a decrease in soil fungal pathogen richness, but it had no consistent relationship with foliar fungal diseases or pathogens. Thus, above‐ and belowground plant pathogen communities showed distinct elevational patterns, providing new insights into underlying mechanisms.