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Abstract Many wildlife pathogens can persist in the environment independently of their hosts, with the habitat itself serving as a reservoir and potential source of transmission. However, reliably detecting and quantifying free‐living pathogen stages across heterogeneous landscapes using environmental DNA methods remains challenging. Understanding how landcover and habitat structure drive pathogen distribution at the environmental and host levels is critical for advancing disease surveillance and ecology.Amphibian chytridiomycosis, caused by the fungal pathogenBatrachochytrium dendrobatidis(Bd), provides a useful model system to address these broader challenges, yet most studies have focused on host–pathogen interactions, with less emphasis onBdwithin environmental reservoirs. UsingBdas a model system, we investigated whether pathogen distribution in natural aquatic environments is associated with host infection patterns across gradients of habitat loss. We sampled four tropical amphibian species across eight rainforest landscapes and quantifiedBdin paired water and host samples using a high‐capacity water filtration method coupled with digital and real‐time quantitative polymerase chain reaction detection assays.Our results revealed a strong positive correlation betweenBdDNA concentrations in water and infection loads on amphibian skin, indicating that environmentalBdDNA is associated with host infection patterns.Forest cover and habitat split (i.e. spatial separation between forests and aquatic breeding sites) were the primary predictors ofBdoccurrence, concentration and infection load across environmental and host‐associated forms, and bothBd‐GPL andBd‐Asia‐2/Brazil lineages were detected across our study landscapes.Our study introduces and validates a robust protocol for detecting environmentalBd, providing a scalable approach to quantify pathogen–environment associations across multiple landscapes and environmental gradients.Synthesis and applications: Linking environmental pathogen detection with host infection patterns can improve surveillance of diseases involving environmental transmission, particularly where direct host sampling is logistically challenging. This approach enables the identification of areas of elevated transmission risk and supports targeted monitoring and management under habitat loss and degradation. It also provides a practical tool to guide conservation actions in landscapes undergoing rapid land‐use change.
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This content will become publicly available on May 22, 2027
Integrating infection intensity and aggregation into the dynamics of pathogens with within‐host replication
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.
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- Award ID(s):
- 2120084
- PAR ID:
- 10709644
- Publisher / Repository:
- Wiley
- Date Published:
- Journal Name:
- Journal of Animal Ecology
- ISSN:
- 0021-8790
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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