The effect of host community functional traits on plant disease risk varies along an elevational gradient

Towards an integrative mechanistic framework for biodiversity-consumer relationships

Terrestrial plant diversity plays a pivotal role in influencing the abundance, diversity, and impacts of herbivores and pathogens (collectively, plant consumers). However, it is unclear whether the relationships between biodiversity and herbivory reflect the same underlying ecological mechanisms as the relationships between biodiversity and disease. This uncertainty results in part from decades of independent, siloed research on each consumer group. We propose that, across herbivores and pathogens, plant diversity-consumer relationships arise from five fundamental factors: (1) density of a focal plant, (2) total plant biomass, (3) plant neighborhood quality, (4) resource diversity, and (5) structural complexity. By matching established hypotheses to these five fundamental factors, we highlight opportunities for growth in the rapidly developing field of plant-consumer interactions.

A trade-off between investment in molecular defense repertoires and growth in plants

Given the negative fitness effects that pathogens impose on their hosts, the benefits of resistance should be universal. However, there is marked variation across plant species in the number of nucleotide-binding leucine-rich repeat receptors, which form a cornerstone of defense. The growth-defense trade-off hypothesis predicts costs associated with defense investment to generate variation in these traits. Our analysis comparing features of the intracellular immune-receptor repertoires with trait data of 187 species shows that in wild plants, the size of the molecular defense repertoire correlates negatively with growth. By contrast, we do not find evidence for a growth-defense trade-off in agricultural plants. Our cross-species approach highlights the central role of defense investment in shaping ecological trait variation and its sensitivity to domestication.

Diversity inhibits foliar fungal diseases in grasslands: Potential mechanisms and temperature dependence

A long-standing debate exists among ecologists as to how diversity regulates infectious diseases (i.e., the nature of diversity-disease relationships); a dilution effect refers to when increasing host diversity inhibits infectious diseases (i.e., negative diversity-disease relationships). However, the generality, strength, and potential mechanisms underlying negative diversity-disease relationships in natural ecosystems remain unclear. To this end, we conducted a large-scale survey of 63 grassland sites across China to explore diversity-disease relationships. We found widespread negative diversity-disease relationships that were temperature-dependent; non-random diversity loss played a fundamental role in driving these patterns. Our study provides field evidence for the generality and temperature dependence of negative diversity-disease relationships in grasslands, becoming stronger in colder regions, while also highlighting the role of non-random diversity loss as a mechanism. These findings have important implications for community ecology, disease ecology, and epidemic control.

A mechanistic framework of enemy release

The enemy release hypothesis (ERH) is the best-known hypothesis explaining high performance (e.g. rapid population growth) of exotic species. However, the current framing of the ERH does not explicitly link evidence of enemy release with exotic performance. This leads to uncertainty regarding the role of enemy release in biological invasions. Here, we demonstrate that the effect of enemy release on exotic performance is the product of three factors: enemy impact, enemy diversity, and host adaptation. These factors are modulated by seven contexts: time since introduction, resource availability, phylogenetic relatedness of exotic and native species, host-enemy asynchronicity, number of introduction events, type of enemy, and strength of growth-defence trade-offs. ERH-focused studies frequently test different factors under different contexts. This can lead to inconsistent findings, which typifies current evidence for the ERH. For example, over 80% of meta-analyses fail to consider ecological contexts which can alter study findings; we demonstrate this by re-analysing a recent ERH synthesis. Structuring the ERH around factors and contexts promotes generalisable predictions about when and where exotic species may benefit from enemy release, empowering effective management. Our mechanistic factor-context framework clearly lays out the evidence required to support the ERH, unifies many enemy-related invasion hypotheses, and enhances predictive capacity.

Host functional traits as the nexus for multilevel infection patterns

Understanding pathogen transmission and infection patterns at multiple biological scales is a central issue in disease ecology and evolution. Here, we suggest that functional traits of host species readily affect infection patterns of species, communities, and landscapes, and thus serve as a linkage for multilevel studies of infectious disease.

Disease decreases variation in host community structure in an old-field grassland

Disease may drive variation in host community structure by modifying the interplay of deterministic and stochastic processes that shape communities. For instance, deterministic processes like ecological selection can benefit species less impacted by disease. When communities have higher levels of disease and disease consistently selects for certain host species, this can reduce variation in host community composition. On the other hand, when host communities are less impacted by disease and selection is weaker, stochastic processes (e.g., drift, dispersal) may play a bigger role in host community structure, which can increase variation among communities. While effects of disease on host community structure have been quantified in field experiments, few have addressed the role of disease in modulating variation in structure among host communities. To address this, we conducted a field experiment spanning three years, using a tractable system: foliar fungal pathogens in an old-field grassland community dominated by the grass Lolium arundinaceum, tall fescue. We reduced foliar fungal disease burden in replicate host communities (experimental plots in intact vegetation) in three fungicide regimens that varied in the seasonal duration of fungicide treatment and included a fungicide-free control. We measured host diversity, biomass, and variation in community structure among replicate communities. Disease reduction generally decreased plant richness and increased aboveground biomass relative to communities experiencing ambient levels of disease. These changes in richness and aboveground biomass were consistent across years despite changes in structure of the plant communities over the experiment's three years. Importantly, disease reduction amplified host community variation, suggesting that disease diminished the degree to which host communities were structured by stochastic processes. These results of experimental disease reduction both highlight the potential importance of stochastic processes in plant communities and reveal the potential for disease to regulate variation in host community structure.

Functional traits explain waterbirds' host status, subtype richness, and community-level infection risk for avian influenza

Species functional traits can influence pathogen transmission processes, and consequently affect species' host status, pathogen diversity, and community-level infection risk. We here investigated, for 143 European waterbird species, effects of functional traits on host status and pathogen diversity (subtype richness) for avian influenza virus at species level. We then explored the association between functional diversity and HPAI H5Nx occurrence at the community level for 2016/17 and 2021/22 epidemics in Europe. We found that both host status and subtype richness were shaped by several traits, such as diet guild and dispersal ability, and that the community-weighted means of these traits were also correlated with community-level risk of H5Nx occurrence. Moreover, functional divergence was negatively associated with H5Nx occurrence, indicating that functional diversity can reduce infection risk. Our findings highlight the value of integrating trait-based ecology into the framework of diversity-disease relationship, and provide new insights for HPAI prediction and prevention.

Plant disease risk is modified by multiple global change drivers

Plant diseases are strongly influenced by host biodiversity, spatial structure, and abiotic conditions. All of these are undergoing rapid change, as the climate is warming, habitats are being lost, and nitrogen deposition is changing nutrient dynamics of ecosystems with ensuing consequences for biodiversity. Here, I review examples of plant-pathogen associations to demonstrate how our ability to understand, model and predict disease dynamics is becoming increasingly difficult, as both plant and pathogen populations and communities are undergoing extensive change. The extent of this change is influenced via both direct and combined effects of global change drivers, and especially the latter are still poorly understood. Change at one trophic level is expected to drive change also at the other, and hence feedback loops between plants and their pathogens are expected to drive changes in disease risk both through ecological as well as evolutionary mechanisms. Many of the examples discussed here demonstrate an increase in disease risk as a result of ongoing change, suggesting that unless we successfully mitigate global environmental change, plant disease is going to become an increasingly heavy burden on our societies with far-reaching consequences for food security and functioning of ecosystems.

Intraspecific trait variation and changing life-history strategies explain host community disease risk along a temperature gradient

Predicting how climate change will affect disease risk is complicated by the fact that changing environmental conditions can affect disease through direct and indirect effects. Species with fast-paced life-history strategies often amplify disease, and changing climate can modify life-history composition of communities thereby altering disease risk. However, individuals within a species can also respond to changing conditions with intraspecific trait variation. To test the effect of temperature, as well as inter- and intraspecifc trait variation on community disease risk, we measured foliar disease and specific leaf area (SLA; a proxy for life-history strategy) on more than 2500 host (plant) individuals in 199 communities across a 1101 m elevational gradient in southeastern Switzerland. There was no direct effect of increasing temperature on disease. Instead, increasing temperature favoured species with higher SLA, fast-paced life-history strategies. This effect was balanced by intraspecific variation in SLA: on average, host individuals expressed lower SLA with increasing temperature, and this effect was stronger among species adapted to warmer temperatures and lower latitudes. These results demonstrate how impacts of changing temperature on disease may depend on how temperature combines and interacts with host community structure while indicating that evolutionary constraints can determine how these effects are manifested under global change. This article is part of the theme issue 'Infectious disease ecology and evolution in a changing world'.

Mechanistic models to meet the challenge of climate change in plant-pathogen systems

Evidence that climate change will impact the ecology and evolution of individual plant species is growing. However, little, as yet, is known about how climate change will affect interactions between plants and their pathogens. Climate drivers could affect the physiology, and thus demography, and ultimately evolutionary processes affecting both plant hosts and their pathogens. Because the impacts of climate drivers may operate in different directions at different scales of infection, and, furthermore, may be nonlinear, abstracting across these processes may mis-specify outcomes. Here, we use mechanistic models of plant-pathogen interactions to illustrate how counterintuitive outcomes are possible, and we introduce how such framing may contribute to understanding climate effects on plant-pathogen systems. We discuss the evidence-base derived from wild and agricultural plant-pathogen systems that could inform such models, specifically in the direction of estimates of physiological, demographic and evolutionary responses to climate change. We conclude by providing an overview of knowledge gaps and directions for future research in this important area. This article is part of the theme issue 'Infectious disease ecology and evolution in a changing world'.