The role of habitat complexity in transmission of a rodent-borne zoonotic pathogen

Pathogen transmission is shaped not only by host species traits but also by environmental and habitat characteristics, yet the ecological mechanisms linking habitat structure to disease dynamics remain poorly understood. Understanding these mechanisms is essential for predicting how biodiversity and landscape change influence disease emergence. Here, we experimentally tested how habitat complexity shapes disease-related processes, focusing on the Puumula virus (PUUV, Orthohantavirus puumalaense) in its reservoir host, the bank vole (Clethrionomys glareolus) in Lammi, Finland. We conducted a large-scale enclosure experiment using 16 outdoor enclosures (40 m X 30 m each), where we manipulated two key ecological factors: vegetation complexity (mowed vs. unmowed enclosures) and vole density (high density with 10 individuals vs. low density with four individuals). These manipulations allowed us to examine how habitat structure and host density affect contact rates among individuals and their home range, two essentials parameters that play a central role in pathogen transmission dynamics. Each enclosure has been equipped with nine live traps, camera traps, and small mammal tracking boxes, enabling continuous and detailed monitoring of individually marked bank voles with PIT (Passive Integrated Transponder) tags. We applied Generalized Linear Mixed Models to assess how habitat complexity and vole density influence contact rates and home-range size. To assess infection outcomes, saliva and feces samples were collected, along with physiological data such as bone density and fat reserves obtained through X-ray imaging. PCR (polymerase chain reaction) screening for PUUV is used to determine transmission patterns across treatments, allowing us to link ecological conditions directly to pathogen spread. We additionally evaluated the effects of climate on the observed behavioral and transmission patterns. By linking habitat structure and complexity, host behavior, climatic variation and infection data, this study discusses conditions that affect zoonotic hazard, offering guidance for broader understanding of biodiversity–disease relationships and for ecosystem-based habitat management towards disease risk mitigation.