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Widespread decline of pollinator populations is of concern for both natural and agricultural ecosystems. Pathogens have been identified as a major contributor to the decline of some bee species, making understanding host–pathogen dynamics a crucial area of research. Sunflower pollen (Helianthus annuus L.; Asterales: Asteraceae) dramatically and consistently reduces infection by a prevalent gut pathogen, Crithidia bombi Lipa &Triggiani 1988 (Kinetoplastida:Trypanosomatidae), in the common eastern bumble bee (Bombus impatiens Cresson 1863; Hymenoptera: Apidae), when consumed by bees post-infection, but we do not know if sunflower can confer protection when consumed before exposure. We asked whether feeding bumble bees sunflower pollen diets prior to pathogen exposure decreases Crithidia infection compared to buckwheat pollen (Fagopyrum esculentum Moench; Polygonales: Polygonaceae). Buckwheat pollen was used as a comparison since it has a similar protein concentration as sunflower pollen, but results in higher Crithidia counts more comparable to typical wildflower pollen when consumed post-infection. Bumble bees were fed sunflower or buckwheat pollen for 7 d, inoculated with Crithidia, and then fed a wildflower pollen control diet for seven more days before assessing infection. We found that consuming a sunflower pollen diet before inoculation did not reduce Crithidia cell counts compared to buckwheat pollen. Furthermore, bumble bee survival and consumption of sucrose solution and pollen did not differ between these diets. The results show no evidence of sunflower pollen providing prophylactic resistance against Crithidia bombi infection, indicating that the timing at which sunflower pollen is consumed relative to exposure has important consequences for infection. Graphical Abstract

1. Animals' social and movement behaviours can impact the transmission dynamics of infectious diseases, especially for pathogens transmitted through close contact between hosts or through contact with infectious stages in the environment. 2. Estimating pathogen transmission rates and R0 from natural systems can be challenging. Because host behavioural traits that underlie the transmission process vary predictably with body size, one of the best-studied traits among animals, body size might therefore also predict variation in parasite transmission dynamics. 3. Here, we examine how two host behaviours, social group living and the intensity of habitat use, scale allometrically using comparative data from wild primate, carnivore and ungulate species. We use these empirical relationships to parameterize classical compartment models for infectious micro- and macroparasitic diseases, and examine how the risk of pathogen invasion changes as a function of host behaviour and body size. We then test model predictions using comparative data on parasite prevalence and richness from wild mammals. 4. We report a general pattern suggesting that smaller-bodied mammal species utilizing home ranges more intensively experience greater risk for invasion by environmentally transmitted macroparasites. Conversely, larger-bodied hosts exhibiting a high degree of social group living could be more readily invaded by directly transmitted microparasites. These trends were supported through comparison of micro- and macroparasite species richness across a large number of carnivore, primate and ungulate species, but empirical data on carnivore macroparasite prevalence showed mixed results. 5. Collectively, our study demonstrates that combining host behavioural traits with dynamical models of infectious disease scaled against host body size can generate testable predictions for variation in parasite risk across species; a similar approach might be useful in future work focused on predicting parasite distributions in local host communities.

Intracellular plant defense against pathogens is mediated by a class of disease resistance genes known as NB‐LRRs or NLRs (R genes). Many of the diseases these genes protect against are more prevalent in regions of higher rainfall, which provide better growth conditions for the pathogens. As such, we expect a higher selective pressure for the maintenance and proliferation of R genes in plants adapted to wetter conditions. In this study, we enriched libraries for R genes using RenSeq from baits primarily developed from the common sunflower (Helianthus annuus) reference genome. We sequenced the R gene libraries of Silphium integrifolium Michx, a perennial relative of sunflower, from 12 prairie remnants across a rainfall gradient in the Central Plains of the United States, with both Illumina short‐read (n = 99) and PacBio long‐read (n = 10) approaches. We found a positive relationship between the mean effective annual precipitation of a plant's source prairie remnant and the number of R genes in its genome, consistent with intensity of plant pathogen coevolution increasing with precipitation. We show that RenSeq can be applied to the study of ecological hypotheses in non‐model relatives of model organisms. We sequenced the disease resistance genes of a broadly distributed flowering plant, Silphium integrifolium, across a rainfall gradient in the Central United States. We found that disease resistance gene count increased with increasing rainfall along the gradient, suggesting an evolutionary pressure for robust immune systems in regions with high biotic stress. Our findings may find applications in breeding programs seeking to develop disease‐resistant crops.

Emerging infectious diseases (EIDs) are a salient threat to many animal taxa, causing local and global extinctions, altering communities and ecosystem function. The EID chytridiomycosis is a prominent driver of amphibian declines, which is caused by the fungal pathogen Batrachochytrium dendrobatidis (Bd). To guide conservation policy, we developed a predictive decision‐analytic model that combines empirical knowledge of host‐pathogen metapopulation dynamics with expert judgment regarding effects of management actions, to select from potential conservation strategies. We apply our approach to a boreal toad (Anaxyrus boreas boreas) and Bd system, identifying optimal strategies that balance tradeoffs in maximizing toad population persistence and landscape‐level distribution, while considering costs. The most robust strategy is expected to reduce the decline of toad breeding sites from 53% to 21% over 50 years. Our findings are incorporated into management policy to guide conservation planning. Our online modeling application provides a template for managers of other systems challenged by EIDs.

1. The need to increase our understanding of factors that regulate animal population dynamics has been catalysed by recent, observed declines in wildlife populations worldwide. Reliable estimates of demographic parameters are critical for addressing basic and applied ecological questions and understanding the response of parameters to perturbations (e.g. disease, habitat loss, climate change). However, to fully assess the impact of perturbation on population dynamics, all parameters contributing to the response of the target population must be estimated. 2. We applied the reverse-time model of Pradel in Program MARK to 6 years of capture—recapture data from two populations of Anaxyrus boreas (boreal toad) populations, one with disease and one without. We then assessed a priori hypotheses about differences in survival and recruitment relative to local environmental conditions and the presence of disease. 3. We further explored the relative contribution of survival probability and recruitment rate to population growth and investigated how shifts in these parameters can alter population dynamics when a population is perturbed. 4. High recruitment rates (0·41) are probably compensating for low survival probability (range 0·51—0·54) in the population challenged by an emerging pathogen, resulting in a relatively slow rate of decline. In contrast, the population with no evidence of disease had high survival probability (range 0·75—0·78) but lower recruitment rates (0·25). 5. Synthesis and applications. We suggest that the relationship between survival and recruitment may be compensatory, providing evidence that populations challenged with disease are not necessarily doomed to extinction. A better understanding of these interactions may help to explain, and be used to predict, population regulation and persistence for wildlife threatened with disease. Further, reliable estimates of population parameters such as recruitment and survival can guide the formulation and implementation of conservation actions such as repatriations or habitat management aimed to improve recruitment.

Population cycles in forest Lepidoptera often result from recurring density-dependent epizootics of entomopathogens. While these systems are typically dominated by a single pathogen species, insects are often infected by multiple pathogens, yet little is known how pathogens interact to affect host dynamics. The apparent invasion of northeastern North America by the fungal entomopathogen Entomophaga maimaiga some time prior to 1989 provides a unique opportunity to evaluate such interactions. Prior to the arrival of E. maimaga , the oscillatory dynamics of host gypsy moth, Lymantria dispar , populations were apparently driven by epizootics of a nucleopolyhedrovirus. Subsequent to its emergence, E. maimaiga has caused extensive mortality in host populations, but little is known about how it has altered multigenerational dynamics of the gypsy moth and its virus. Here we compared demographic data collected in gypsy moth populations prior to vs. after E. maimaiga 's invasion. We found that the recently invading fungal pathogen virtually always causes greater levels of mortality in hosts than does the virus, but fungal mortality is largely density independent. Moreover, the presence of the fungus has apparently not altered the gypsy moth-virus density-dependent interactions that were shown to drive periodic oscillations in hosts before the arrival of the fungus.

1. Infectious diseases have the potential to spread rapidly and cause high mortality within populations of immunologically naïve hosts. The recent appearance of avian cholera, a highly virulent disease of birds caused by the bacterium Pasteurella multocida, at remote Arctic seabird colonies is an emerging conservation concern. 2. Determining disease risk to population viability requires a quantitative understanding of transmission potential and the factors that regulate epidemic persistence. Estimates of the basic (R₀) and real-time (Rt) reproductive number are critical in this regard – enumerating the number of secondary infections caused by each primary infection in a newly invaded host population and the decline in transmission rate as susceptible individuals are removed via mortality or immunized recovery. 3. Here, we use data collected at a closely monitored common eider (Somateria moltissima) breeding colony located in the Canadian Arctic to examine transmission and host population dynamics. Specifically, we infer epidemic curves from daily mortality observations and use a likelihood-based procedure to estimate changes in the reproductive number over a series of annual outbreaks. These data are interpreted in relation to concurrent changes in host numbers to assess local extinction risk. 4. Consistent with expectations for a novel pathogen invasion, case incidence increased exponentially during the initial wave of exposure (R₀ = 2·5; generation time = 6·5 days ± 1·1 SD). Disease conditions gradually abated, but only after several years of smouldering infection (Rt ≈ 1). In total, 6194 eider deaths were recorded during outbreaks spanning eight consecutive breeding seasons. Breeding pair abundance declined by 56% from the pre-outbreak peak; however, a robust population of >4000 pairs remained intact upon epidemic fade-out. Overall, outbreak patterns were consistent with herd immunity acting as a mitigating factor governing in the extent and duration of mortality. 5. Disease mortality is frequently modelled as a form of stochastic catastrophe in wildlife population assessments, whereas our approach gives shape to the functional response between transmission and host population dynamics. We conclude that increased emphasis on integrating epidemiological and population processes is essential to predicting the conservation impact of emerging infectious diseases in wildlife.

1. Disease prevalence in wildlife is governed by epidemiological parameters (infection and recovery rates) and response to infection, both of which vary within and among individual hosts. Studies quantifying these individual-scale parameters and documenting their source of variation in wild hosts are fundamental for predicting disease dynamics. Such studies do not exist for the influenza A virus (IAV), despite its strong impact on the global economy and public health. 2. Using capture-recaptures of 3500 individual mallards Anas platyrhynchos during seven migration seasons at a stopover site in southern Sweden, we provide the first empirical description of the individual-based mechanisms of IAV dynamics in a wild reservoir host. 3. For most years, prevalence and risk of IAV infection peaked at a single time during the autumn migration season, but the timing, shape and intensity of the infection curve showed strong annual heterogeneity. In contrast, the seasonal pattern of recovery rate only varied in intensity across years. 4. Adults and juveniles displayed similar seasonal patterns of infection and recovery each year. However, compared to adults, juveniles experienced twice the risk of becoming infected, whereas recovery rates were similar across age categories. Finally, we did not find evidence that infection influenced the timing of emigration. 5. Synthesis and applications. Our study provides robust empirical estimates of epidemiological parameters for predicting influenza A virus (IAV) dynamics. However, the strong annual variation in infection curves makes forecasting difficult. Prevalence data can provide reliable surveillance indicators as long as they catch the variation in infection risk. However, individual-based monitoring of infection is required to verify this assumption in areas where surveillance occurs. In this context, monitoring of captive sentinel birds kept in close contact with wild birds is useful. The fact that infection does not impact the timing of migration underpins the potential for mallards to spread viruses rapidly over large geographical scales. Hence, we strongly encourage IAV surveillance with a multistate capture-recapture approach along the entire migratory flyway of mallards.

An introduction to the theme issue that includes papers that identify how, where and why infectious diseases in wildlife emerge, while also addressing their possible conservation impacts.An introduction to the theme issue that includes papers that identify how, where and why infectious diseases in wildlife emerge, while also addressing their possible conservation impacts.

The evolution of many microbes and pathogens, including circulating viruses such as seasonal influenza, is driven by immune pressure from the host population. In turn, the immune systems of infected populations get updated, chasing viruses even farther away. Quantitatively understanding how these dynamics result in observed patterns of rapid pathogen and immune adaptation is instrumental to epidemiological and evolutionary forecasting. Here we present a mathematical theory of coevolution between immune systems and viruses in a finite-dimensional antigenic space, which describes the cross-reactivity of viral strains and immune systems primed by previous infections. We show the emergence of an antigenic wave that is pushed forward and canalized by cross-reactivity. We obtain analytical results for shape, speed, and angular diffusion of the wave. In particular, we show that viral–immune coevolution generates an emergent timescale, the persistence time of the wave’s direction in antigenic space, which can be much longer than the coalescence time of the viral population. We compare these dynamics to the observed antigenic turnover of influenza strains, and we discuss how the dimensionality of antigenic space impacts the predictability of the evolutionary dynamics. Our results provide a concrete and tractable framework to describe pathogen–host coevolution.