Nonstationarity in wildlife disease dynamics: Insights from the prairie dog–plague system

Authors: BARILLE, GABRIEL - University Of Wyoming; LAYFIELD, JOSHUA - University Of Wyoming; Augustine, David; Porensky, Lauren; DUCHARDT, COURTNEY - University Of Arizona; RANGWALA, IMTIAZ - University Of Colorado; DAVIDSON, ANA - Colorado State University

Submitted to: Oikos
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/22/2026
Publication Date: 7/17/2026
Citation: Barille, G., Layfield, J., Augustine, D.J., Porensky, L.M., Duchardt, C., Rangwala, I., Davidson, A. 2026. Nonstationarity in wildlife disease dynamics: Insights from the prairie dog–plague system. Oikos. 2026(10). Article e12216. https://doi.org/10.1002/oik.12216.
DOI: https://doi.org/10.1002/oik.12216

Interpretive Summary: Understanding the factors that allow diseases to spread through wildlife populations is important for developing strategies to prevent or manage disease outbreaks. Epizootic outbreaks of plague occur periodically in rodent populations in rangelands of the western US, and are especially notable as the cause of dramatic fluctuations in black-tailed prairie dog populations. We used datasets collected from a 29-year period (~1992 - 2020) from 9 different locations across the Great Plains to evaluate the importance of weather conditions as well as the size and distribution of prairie dog colonies in driving epizootic outbreaks of plague. We found that the probability of a plague outbreak consistently increased as colony size and proximity to other colonies increased across all of the study sites. In contrast, although our analysis indicated specific precipitation and temperature conditions were often associated with plague outbreaks, the direction and magnitude of these effects often varied across different study sites. These results help identify how local versus range-wide factors influence the timing of plague epizootics in prairie dogs, which in turn has consequences for vegetation conditions in rangeland ecosystems.

Technical Abstract: Ecological relationships often vary in strength and direction across ecosystems, a pattern that has become increasingly evident as ecology expands to broader spatial and temporal scales. Although such nonstationarity—the changing effect of predictor variables across spatiotemporal contexts—is widely acknowledged in ecological research, it has received limited attention in the study of wildlife diseases. Here, we evaluated nonstationarity in sylvatic plague epizootics among black-tailed prairie dog (Cynomys ludovicianus) colonies across nine federally managed grasslands in the Great Plains, USA. Using a 29-year dataset (~1992–2020) and a mixed-effects machine learning approach, we assessed how the effects of climate and colony characteristics on plague varied in strength and direction at each grassland. Across sites, colony size, clustering, and structural connectedness showed generally stationary, positive associations with outbreak probability. By contrast, weather effects were strongly nonstationary: temperature and precipitation alternately increased, decreased, or showed little association with outbreaks depending on the grassland. Predictor importance also shifted across space and within epizootics; at some sites precipitation signaled outbreak onset, whereas host spatial structure governed subsequent spread and persistence. These results indicate that host aggregation provides a consistent scaffold for transmission, while environmental drivers act locally and vary through time. Recognizing this contrast can improve forecasting and mitigation, as interventions such as vaccination or vector control are likely to perform differently across environmental contexts. Methodologically, explicitly modeling slope heterogeneity identified where and when covariate effects differ, offering a transferable approach for disentangling local from broad-scale drivers of wildlife disease across heterogeneous landscapes.