Elements of disease in a changing world: modelling feedbacks between infectious disease and ecosystems

Pathways linking nutrient enrichment, habitat structure, and parasitism to host-resource interactions

Human activities simultaneously alter nutrient levels, habitat structure, and levels of parasitism. These activities likely have individual and joint impacts on food webs. Furthermore, there is particular concern that nutrient additions and changes to habitat structure might exacerbate the size of epidemics and impacts on host density. We used a well-studied zooplankton-fungus host-parasite system and experimental whole water column enclosures to factorially manipulate nutrient levels, habitat structure (specifically: mixing), and presence of parasites. Nutrient addition increased infection prevalence, density of infected hosts, and total host density. We hypothesized that nutrients, mixing, and parasitism were linked in multiple ways, including via their combined effects on phytoplankton (resource) abundance, and we used structural equation modeling to disentangle these pathways. In the absence of the parasite, both nutrients and mixing increased abundance of phytoplankton, whereas host density was negatively related to phytoplankton abundance, suggesting a mixture of bottom-up and top-down control of phytoplankton. In the presence of the parasite, nutrients still increased phytoplankton abundance but mixing no longer did, and there was no longer a significant relationship between host density and phytoplankton. This decoupling of host-resource dynamics may have resulted from reduced grazing due to illness-mediated changes in feeding behavior. Overall, our results show that the impact of one human activity (e.g., altered habitat structure) might depend on other human impacts (e.g., parasite introduction). Fortunately, carefully designed experiments and analyses can help tease apart these multifaceted relationships, allowing us to understand how human activities alter food webs, including interactions between hosts and their parasites and resources.

Reconciling contrasting effects of nitrogen on host immunity and pathogen transmission using stoichiometric models

Hosts rely on the availability of nutrients for growth, and for defense against pathogens. At the same time, changes in host nutrition can alter the dynamics of pathogens that rely on their host for reproduction. For primary producer hosts, enhanced nutrient loads may increase host biomass or pathogen reproduction, promoting faster density-dependent pathogen transmission. However, the effect of elevated nutrients may be reduced if hosts allocate a growth-limiting nutrient to pathogen defense. In canonical disease models, transmission is not a function of nutrient availability. Yet, including nutrient availability is necessary to mechanistically understand the response of infection to changes in the environment. Here, we explore the implications of nutrient-mediated pathogen infectivity and host immunity on infection outcomes. We developed a stoichiometric disease model that explicitly integrates the contrasting dependencies of pathogen infectivity and host immunity on nitrogen (N) and parameterized it for an algal-host system. Our findings reveal dynamic shifts in host biomass build-up, pathogen prevalence, and the force of infection along N supply gradients with N-mediated host infectivity and immunity, compared with a model in which the transmission rate was fixed. We show contrasting responses in pathogen performance with increasing N supply between N-mediated infectivity and N-mediated immunity, revealing an optimum for pathogen transmission at intermediate N supply. This was caused by N limitation of the pathogen at a low N supply and by pathogen suppression via enhanced host immunity at a high N supply. By integrating both nutrient-mediated pathogen infectivity and host immunity into a stoichiometric model, we provide a theoretical framework that is a first step in reconciling the contrasting role nutrients can have on host-pathogen dynamics.

Feedback loops between 3D vegetation structure and ecological functions of animals

Ecosystems function in a series of feedback loops that can change or maintain vegetation structure. Vegetation structure influences the ecological niche space available to animals, shaping many aspects of behaviour and reproduction. In turn, animals perform ecological functions that shape vegetation structure. However, most studies concerning three-dimensional vegetation structure and animal ecology consider only a single direction of this relationship. Here, we review these separate lines of research and integrate them into a unified concept that describes a feedback mechanism. We also show how remote sensing and animal tracking technologies are now available at the global scale to describe feedback loops and their consequences for ecosystem functioning. An improved understanding of how animals interact with vegetation structure in feedback loops is needed to conserve ecosystems that face major disruptions in response to climate and land-use change.

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.

Niche theory for within-host parasite dynamics: Analogies to food web modules via feedback loops

Why do parasites exhibit a wide dynamical range within their hosts? For instance, why does infecting dose either lead to infection or immune clearance? Why do some parasites exhibit boom-bust, oscillatory dynamics? What maintains parasite diversity, that is coinfection v single infection due to exclusion or priority effects? For insights on parasite dose, dynamics and diversity governing within-host infection, we turn to niche models. An omnivory food web model (IGP) blueprints one parasite competing with immune cells for host energy (PIE). Similarly, a competition model (keystone predation, KP) mirrors a new coinfection model (2PIE). We then drew analogies between models using feedback loops. The following three points arise: first, like in IGP, parasites oscillate when longer loops through parasites, immune cells and resource regulate parasite growth. Shorter, self-limitation loops (involving resources and enemies) stabilise those oscillations. Second, IGP can produce priority effects that resemble immune clearance. But, despite comparable loop structure, PIE cannot due to constraints imposed by production of immune cells. Third, despite somewhat different loop structure, KP and 2PIE share apparent and resource competition mechanisms that produce coexistence (coinfection) or priority effects of prey or parasites. Together, this mechanistic niche framework for within-host dynamics offers new perspective to improve individual health.

Long-term nitrogen enrichment mediates the effects of nitrogen supply and co-inoculation on a viral pathogen

Host nutrient supply can mediate host-pathogen and pathogen-pathogen interactions. In terrestrial systems, plant nutrient supply is mediated by soil microbes, suggesting a potential role of soil microbes in plant diseases beyond soil-borne pathogens and induced plant defenses. Long-term nitrogen (N) enrichment can shift pathogenic and nonpathogenic soil microbial community composition and function, but it is unclear if these shifts affect plant-pathogen and pathogen-pathogen interactions. In a growth chamber experiment, we tested the effect of long-term N enrichment on infection by Barley Yellow Dwarf Virus (BYDV-PAV) and Cereal Yellow Dwarf Virus (CYDV-RPV), aphid-vectored RNA viruses, in a grass host. We inoculated sterilized growing medium with soil collected from a long-term N enrichment experiment (ambient, low, and high N soil treatments) to isolate effects mediated by the soil microbial community. We crossed soil treatments with a N supply treatment (low, high) and virus inoculation treatment (mock-, singly-, and co-inoculated) to evaluate the effects of long-term N enrichment on plant-pathogen and pathogen-pathogen interactions, as mediated by N availability. We measured the proportion of plants infected (i.e., incidence), plant biomass, and leaf chlorophyll content. BYDV-PAV incidence (0.96) declined with low N soil (to 0.46), high N supply (to 0.61), and co-inoculation (to 0.32). Low N soil mediated the effect of N supply on BYDV-PAV: instead of N supply reducing BYDV-PAV incidence, the incidence increased. Additionally, ambient and low N soil ameliorated the negative effect of co-inoculation on BYDV-PAV incidence. BYDV-PAV infection only reduced chlorophyll when plants were grown with low N supply and ambient N soil. There were no significant effects of long-term N soil on CYDV-RPV incidence. Soil inoculant with different levels of long-term N enrichment had different effects on host-pathogen and pathogen-pathogen interactions, suggesting that shifts in soil microbial communities with long-term N enrichment may mediate disease dynamics.