The dilution effect predicts increasing biodiversity to reduce the risk of infection, but the generality of this effect remains unresolved. Because biodiversity loss generates predictable changes in ...host community competence, we hypothesised that biodiversity loss might drive the dilution effect. We tested this hypothesis by reanalysing four previously published meta‐analyses that came to contradictory conclusions regarding generality of the dilution effect. In the context of biodiversity loss, our analyses revealed a unifying pattern: dilution effects were inconsistently observed for natural biodiversity gradients, but were commonly observed for biodiversity gradients generated by disturbances causing losses of biodiversity. Incorporating biodiversity loss into tests of generality of the dilution effect further indicated that scale‐dependency may strengthen the dilution effect only when biodiversity gradients are driven by biodiversity loss. Together, these results help to resolve one of the most contentious issues in disease ecology: the generality of the dilution effect.
The dilution effect predicts increasing biodiversity to reduce the risk of infection, but the generality of this effect remains unresolved. Here, by re‐analyzing the (often conflicting) results of previously published meta‐analyses, we show that ecological processes like habitat fragmentation, urbanisation, and agricultural intensification consistently lead to increases in infectious diseases, likely because these events drive concurrent losses of local biodiversity and predictable changes in host community composition.
Summary
Human alteration of natural habitats may change the processes governing species interactions in wild communities. Wild populations are increasingly impacted by agricultural intensification, ...yet it is unknown whether this alters biodiversity mediation of disease dynamics.
We investigated the association between plant diversity (species richness, diversity) and infection risk (virus richness, prevalence) in populations of Plantago lanceolata in natural landscapes as well as those occurring at the edges of cultivated fields. Altogether, 27 P. lanceolata populations were surveyed for population characteristics and sampled for PCR detection of five recently characterized viruses.
We find that plant species richness and diversity correlated negatively with virus infection prevalence. Virus species richness declined with increasing plant diversity and richness in natural populations while in agricultural edge populations species richness was moderately higher, and not associated with plant richness. This difference was not explained by changes in host richness between these two habitats, suggesting potential pathogen spill‐over and increased transmission of viruses across the agro‐ecological interface. Host population connectivity significantly decreased virus infection prevalence.
We conclude that human use of landscapes may change the ecological laws by which natural communities are formed with far reaching implications for ecosystem functioning and disease.
See also the Commentary on this article by Lacroix, 230: 2094–2096.
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.
Plant biodiversity, spatial structure, and abiotic conditions are rapidly changing under human influenced environmental change. Here, Laine reviews how plant–disease associations are affected both directly and through interactive effects by this change.
Recent methodological advances have uncovered tremendous microbial diversity cohabiting in the same host plant, and many of these microbes cause disease. In this review we highlight how the presence ...of other pathogen species, or other pathogen genotypes, within a plant can affect key components of host–pathogen interactions: (i) within-plant virulence and pathogen accumulation, through direct and host-mediated mechanisms; (ii) evolutionary trajectories of pathogen populations, through virulence evolution, generation of novel genetic combinations, and maintenance of genetic diversity; and (iii) disease dynamics, with multiple infection likely to render epidemics more devastating. The major future challenges are to couple a community ecology approach with a molecular investigation of the mechanisms operating under coinfection and to evaluate the evolution and effectiveness of resistance within a coinfection framework.
Molecular tools are becoming readily available for the study of parasites. These technical advances have shown that multiple infection is common in the wild and in agriculture, with the same host individual simultaneously infected by several pathogen genotypes or species (i.e., coinfection).
Under coinfection, pathogens may interact either directly (mechanical or chemical interactions) or indirectly through host resources or defenses.
These direct or host-mediated interactions under coinfection can change virulence, within-host pathogen accumulation, and transmission.
Such plant-level effects can also be seen at the population level, with coinfection rendering epidemics more devastating.
Coinfection may drive the evolutionary trajectories of pathogen populations through its effects on virulence evolution and on the generation and maintenance of genetic diversity in pathogen populations.
Infection by multiple pathogens of the same host is ubiquitous in both natural and managed habitats. While intraspecific variation in disease resistance is known to affect pathogen occurrence, how ...differences among host genotypes affect the assembly of pathogen communities remains untested. In our experiment using cloned replicates of naive Plantago lanceolata plants as sentinels during a seasonal virus epidemic, we find non-random co-occurrence patterns of five focal viruses. Using joint species distribution modelling, we attribute the non-random virus occurrence patterns primarily to differences among host genotypes and local population context. Our results show that intraspecific variation among host genotypes may play a large, previously unquantified role in pathogen community structure.
Invertebrate herbivores are important and diverse, and their abundance and impacts will likely shift under climate change. Yet, past studies of invertebrate herbivory have documented highly variable ...responses to changing temperature, making it challenging to predict the direction and magnitude of these shifts. One explanation for these responses is that changing environmental conditions drive concurrent changes in plant communities and herbivore traits. The impacts of changing temperature on herbivory might therefore depend on how temperature combines and interacts with characteristics of plant and herbivore communities. To test this, we surveyed damage to leaves by invertebrate herbivores on 4400 plant individuals in 220 sampling plots along a 1101 m elevational gradient. Increasing temperature drove community‐level herbivory via at least three overlapping mechanisms: increasing temperature directly reduced herbivory, indirectly affected herbivory by reducing plant‐community phylogenetic diversity, and indirectly affected herbivory by altering the effects of plant‐community functional and phylogenetic diversity on herbivory. Consequently, increasing plant functional diversity reduced herbivory in colder environments while increasing plant phylogenetic diversity increased herbivory in warmer environments. Moreover, different herbivore feeding guilds varied in their response to temperature and plant community composition. These results indicate that, even along a single elevation gradient in a single year, a variety of mechanisms can concurrently drive herbivory, thereby supporting the hypothesis that a universal response of herbivory to changing environmental conditions is unlikely to exist. Instead, our results highlight the importance of considering both plant and herbivore community context to predict how climate change will alter invertebrate herbivory.
Aim
Joint species distribution models (JSDMs) are an important tool for predicting ecosystem 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 performance of JSDMs for community‐level prediction are based on individual species predictions 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 alternative JSDMs across broad environmental gradients emulating transferable applications.
Innovation
We connect the evaluation of JSDM predictions to Bayesian model selection theory under which the log score is the preferred performance measure for probabilistic 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 forest 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 variables and compositional dependence modelled using a multinomial likelihood. The addition of flexible residual species correlations improved model predictions only within JSDMs applying a reduced set of environmental variables highlighting potential confounding between unobserved environmental conditions and residual species dependence. 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 predictive performance of JSDMs and highlights the importance of accounting for species dependence when interest is in community composition under novel conditions.
The legacy of the use and misuse of antibiotics in recent decades has left us with a global public health crisis: antibiotic-resistant bacteria are on the rise, making it harder to treat infections. ...At the same time, evolution of antibiotic resistance is probably the best-documented case of contemporary evolution. To date, research on antibiotic resistance has largely ignored the complexity of interactions that bacteria engage in. However, in natural populations, bacteria interact with other species; for example, competition and grazing are import interactions influencing bacterial population dynamics. Furthermore, antibiotic leakage to natural environments can radically alter bacterial communities. Overall, we argue that eco-evolutionary feedback loops in microbial communities can be modified by residual antibiotics and evolution of antibiotic resistance. The aim of this review is to connect some of the well-established key concepts in evolutionary biology and recent advances in the study of eco-evolutionary dynamics to research on antibiotic resistance. We also identify some key knowledge gaps related to eco-evolutionary dynamics of antibiotic resistance, and review some of the recent technical advantages in molecular microbiology that offer new opportunities for tackling these questions. Finally, we argue that using the full potential of evolutionary theory and active communication across the different fields is needed for solving this global crisis more efficiently.
This article is part of the themed issue ‘Human influences on evolution, and the ecological and societal consequences'.
Coinfections by multiple parasites predominate in the wild. Interactions between parasites can be antagonistic, neutral, or facilitative, and they can have significant implications for epidemiology, ...disease dynamics, and evolution of virulence. Coinfections commonly result from sequential exposure of hosts to different parasites. We argue that the sequential nature of coinfections is important for the consequences of infection in both natural and man-made environments. Coinfections accumulate during host lifespan, determining the structure of the parasite infracommunity. Interactions within the parasite community and their joint effect on the host individual potentially shape evolution of parasite life‐history traits and transmission biology. Overall, sequential coinfections have the potential to change evolutionary and epidemiological outcomes of host–parasite interactions widely across plant and animal systems.
Parasite coinfections are common throughout plant and animal kingdoms. The resulting parasite–parasite interactions can potentially influence parasite traits such as infection success and virulence.
Coinfections of multiple parasites can occur simultaneously, but more often sequentially, with a gap of time between the infections. This can dramatically change the outcome of coinfection.
Sequential and repeated infection events are very common in nature. Regardless, research on coinfections has largely focused on simultaneous attack by multiple parasites.
Sequential coinfections have also implications for parasite epidemiology and prevention. Designing disease-prevention strategies that account for coinfections and their timing could significantly improve success of intervention efforts.
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