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Abstract Individual heterogeneity, in number of parasites, size, etc., interacts critically with population dynamics. We tease this out in a model case study of microparasite load with empirically supported assumptions to investigate how variance in load interacts with population dynamics, We show how the mean and variance of load vary throughout an epidemic. Further, we show how mean and variance have mutual negative feedbacks on each other mediated by high death rates at high loads. Helpfully, we find that mean and variance provide information into underlying processes as well. Population trends in the mean and variance reveal underlying trends in within-host processes, e.g. differentiating host evolution of defence that manifests as tolerance, constitutive resistance, inducible resistance or acquired resistance. Our findings apply to many microparasites, including fungal pathogens which show large variance in infection load. As a case study, we consider endangered frog populations recovering from fungal epidemics and find that the mean and variance guide management actions. Lastly, we demonstrate the impact of load variance on host fitness, pathogen fitness and host population suppression. Our results demonstrate the importance of trait heterogeneity and the insights available from relatively simple models, both for microparasite load and possibly other traits. 

Abstract BackgroundEctothermic arthropods, like ticks, are sensitive indicators of environmental changes, and their seasonality plays a critical role in the dynamics of tick-borne disease in a warming world. Juvenile tick phenology, which influences pathogen transmission, may vary across climates, with longer tick seasons in cooler climates potentially amplifying transmission. However, assessing juvenile tick phenology is challenging in arid climates because ticks spend less time seeking for blood meals (i.e. questing) due to desiccation pressures. As a result, traditional collection methods like dragging or flagging are less effective. To improve our understanding of juvenile tick seasonality across a latitudinal gradient, we examinedIxodes pacificusphenology on lizards, the primary juvenile tick host in California, and explored how climate factors influence phenological patterns. MethodsBetween 2013 and 2022, ticks were removed from 1527 lizards at 45 locations during peak tick season (March–June). Tick counts were categorized by life stage (larvae and nymphs) and linked with remotely sensed climate data, including monthly maximum temperature, specific humidity and Palmer Drought Severity Index (PDSI). Juvenile phenology metrics, including tick abundances on lizards, Julian date of peak mean abundance and temporal overlap between larval and nymphal populations, were analyzed along a latitudinal gradient. Generalized additive models (GAMs) were applied to assess climate-associated variation in juvenile abundance on lizards. ResultsMean tick abundance per lizard ranged from 0.17 to 47.21 across locations, with the highest abundance in the San Francisco Bay Area and lowest in Los Angeles, where more lizards had zero ticks attached. In the San Francisco Bay Area, peak nymphal abundance occurred 25 days earlier than peak larval abundance. Temporal overlap between larval and nymphal stages at a given location varied regionally, with northern areas showing higher overlap, possibly due to the bimodal seasonality of nymphs. We found that locations with higher temperatures and increased drought stress were linked to lower tick abundances, although the magnitude of these effects depended on regional location. ConclusionsOur study, which compiled 10 years of data, reveals significant regional variation in juvenileI. pacificusphenology across California, including differences in abundance, peak timing, and temporal overlap. These findings highlight the influence of local climate on tick seasonality, with implications for tick-borne disease dynamics in a changing climate. Graphical Abstract 

Abstract Disease outcomes depend heavily on infection intensity which is often heterogeneous across and within host populations. Most individuals carry low pathogen loads and a few carry high loads, a pattern known as aggregation. Although well characterized in macroparasite systems, aggregation and infection intensity are rarely incorporated into microparasite models.This raises key questions: Do similar mechanisms underlie aggregation in macro‐ and microparasite systems? Moreover, how do aggregation and load‐dependent effects shape outcomes such as host suppression and virulence–transmission trade‐offs?To address these questions, we developed a series of differential equation models that allow the pathogen load distribution across hosts to evolve dynamically, shaped by both within‐ and between‐host processes. We applied this framework to the amphibian chytrid fungus system caused byBatrachochytrium dendrobatidis(Bd), a fungal pathogen threatening amphibian populations worldwide.Our results show that both stronger load‐dependent mortality and faster within‐host replication reduce aggregation. Aggregation, in turn, weakens host suppression and flattens virulence–transmission trade‐off, shifting peak transmission to higher replication rates.Overall, our models show that similar mechanisms of infection intensity and aggregation influence host–pathogen dynamics in microparasites as in macroparasites. This work offers a framework for advancing theoretical and data‐driven understanding of how within‐host processes scale to population‐level disease dynamics, advocating for a unified approach to disease modelling that bridges the macro‐ and microparasites. 

Abstract Changing climate has driven shifts in species phenology, influencing a range of ecological interactions from plant–pollinator to consumer–resource. Phenological changes in host–parasite systems have implications for pathogen transmission dynamics. The seasonal timing, or phenology, of peak larval and nymphal tick abundance is an important driver of tick‐borne pathogen prevalence through its effect on cohort‐to‐cohort transmission. Tick phenology is tightly linked to climatic factors such as temperature and humidity. Thus, variation in climate within and across regions could lead to differences in phenological patterns. These differences may explain regional variation in tick‐borne pathogen prevalence of the Lyme disease‐causingBorreliabacteria in vector populations in the United States. For example, one factor thought to contribute to high Lyme disease prevalence in ticks in the eastern United States is the asynchronous phenology of ticks there, where potentially infected nymphal ticks emerge earlier in the season than uninfected larval ticks. This allows the infected nymphal ticks to transmit the pathogen to hosts that are subsequently fed upon by the next generation of larval ticks. In contrast, in the western United States where Lyme disease prevalence is generally much lower, tick phenology is thought to be more synchronous with uninfected larvae emerging slightly before, or at the same time as, potentially infected nymphs, reducing horizontal transmission potential. Sampling larval and nymphal ticks, and their host‐feeding phenology, both across large spatial gradients and through time, is challenging, which hampers attempts to conduct detailed studies of phenology to link it with pathogen prevalence. In this study, we demonstrate through intensive within‐season sampling that the relative abundance and seasonality of larval and nymphal ticks are highly variable along a latitudinal gradient and likely reflect the variable climate in the far western United States with potential consequences for pathogen transmission. We find that feeding patterns were variable and synchronous feeding of juvenile ticks on key blood meal hosts was associated with mean temperature. By characterizing within‐season phenological patterns of the Lyme disease vector throughout a climatically heterogeneous region, we can begin to identify areas with high potential for tick‐borne disease risk and underlying mechanisms at a finer scale. 

ABSTRACT Spatial processes, particularly scale‐dependent feedbacks, may play important and underappreciated roles in the dynamics of bistable ecosystems. For example, self‐organised spatial patterns can allow for stable coexistence of alternative states outside regions of bistability, a phenomenon known as a Busse balloon. We used partial differential equations to explore the potential for such dynamics in coral reefs, focusing on how herbivore behaviour and mobility affect the stability of coral‐ and macroalgal‐dominated states. Herbivore attraction to coral resulted in a Busse balloon that enhanced macroalgal resilience, with patterns persisting in regions of parameter space where nonspatial models predict uniform coral dominance. Thus, our work suggests herbivore association with coral (e.g., for shelter) can prevent reefs from reaching a fully coral‐dominated state. More broadly, this study illustrates how consumer space use can prevent ecosystems from undergoing wholesale state transitions, highlighting the importance of explicitly accounting for space when studying bistable systems. 

Abstract Wildfires are a significant ecological force in the western United States, reshaping landscapes and ecological communities. However, assessing wildfires' full impact is challenging due to the complexity of fire severity and its varied effects on ecological dynamics. Understanding species‐specific responses to disturbances within their environmental context is essential for predicting cascading ecological impacts. Arthropods, including ticks, are particularly sensitive to both abiotic and biotic changes, making them especially vulnerable to the impacts of wildfire.In this study, we tease apart the complex direct and indirect effects of wildfire on tick populations through a combination of field‐level measurements and remote sensing. We assessed tick densities across 88 plots within large, protected reserves in California following three wildfires in August 2020, using data on soil conditions, vegetation cover, tick densities and landscape‐level remotely sensed variables related to vegetation regeneration and vertebrate recolonization. To support a multi‐scalar approach, we applied piecewise structural equation models to incorporate factors across distinct spatial scales and assess how fire severity affects tick populations, with vegetation and habitat structure as mediating variables, thereby evaluating the relative importance of local drivers within a broader landscape context.Our results indicate that tick densities were consistently lower in burned plots across all vegetation types, with higher fire severity associated with the greatest reductions. This direct effect of fire severity outweighed indirect influences such as the presence of remaining woody debris, which can support tick populations by offering microhabitat for vertebrate hosts following a fire event.Landscape‐level characteristics—such as proximity to the fire perimeter and the percentage of the reserve burned—exerted stronger influences on tick densities than plot‐level fire severity. These broader spatial characteristics likely facilitate the movement of vertebrate hosts into unburned areas, promoting tick recolonization and recovery following wildfire disturbance. Our results suggest that simplified field assessments focusing on key habitat indicators may be effective for monitoring tick responses to wildfire.Synthesis and applications. This study highlights the importance of integrating multiple data sources and ecological scales to predict wildfire impacts on ecosystems and public health. By advancing our understanding of wildfire effects on ticks, the research offers valuable insights for ecosystem management and disease vector control. The use of advanced statistical tools, like piecewise structural equation models, combined with remotely sensed data, can facilitate rapid assessments and targeted monitoring efforts. 

Most hosts contain few parasites, whereas few hosts contain many. This pattern, known as aggregation, is well-documented in macroparasites where parasite intensity distribution among hosts affects host–parasite dynamics. Infection intensity also drives fungal disease dynamics, but we lack a basic understanding of host–fungal aggregation patterns, how they compare with macroparasites and if they reflect biological processes. To begin addressing these gaps, we characterized aggregation of the fungal pathogenBatrachochytrium dendrobatidis(Bd) in amphibian hosts. Utilizing the slope of Taylor’s Power law, we found Bd intensity distributions were more aggregated than many macroparasites, conforming closely to lognormal distributions. We observed that Bd aggregation patterns are strongly correlated with known biological processes operating in amphibian populations, such as epizoological phase (i.e. invasion, post-invasion and enzootic), and intensity-dependent disease mortality. Using intensity-dependent mathematical models, we found evidence of evolution of host resistance based on aggregation shifts in systems persisting with Bd following disease-induced declines. Our results show that Bd aggregation is highly conserved across disparate systems and contains signatures of potential biological processes of amphibian–Bd systems. Our work can inform future modelling approaches and be extended to other fungal pathogens to elucidate host–fungal interactions and unite host–fungal dynamics under a common theoretical framework.