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Abstract The use of quantitative real-time PCR (qPCR) to monitor pathogens is common; however, quantitative frameworks that consider the observation process, dynamics in pathogen presence, and pathogen load are lacking. This can be problematic in the early stages of disease progression, where low level detections may be treated as ‘inconclusive’ and excluded from analyses. Alternatively, a framework that accounts for imperfect detection would provide more robust inferences. To better estimate pathogen dynamics, we developed a hierarchical multi-scale dynamic occupancy hurdle model (MS-DOHM). The model used data gathered during sampling forPseudogymnoascus destructans (Pd), the causative agent of white-nose syndrome, a fungal disease that has cause severe declines in several species of hibernating bats in North America. The model allowed us to estimate initial occupancy, colonization, persistence and prevalence ofPdat bat hibernacula. Additionally, utilizing the relationship between cycle threshold and pathogen load, we estimated pathogen detectability and modeled expected colony and bat pathogen loads. To assess the ability of MS-DOHM to estimate pathogen dynamics, we compared MS-DOHM’s results to those of a dynamic occupancy model and naïve detection/non-detection. MS-DOHM’s estimates of site-level pathogen presence were up to 11.9% higher than estimates from the dynamic occupancy model and 35.7% higher than naïve occupancy. Including prevalence and load in our modeling framework resulted in estimates of pathogen arrival that were two to three years earlier compared to the dynamic occupancy and naïve detection/non-detection, respectively. Compared to naïve values, MS-DOHM predicted greater pathogen loads on colonies; however, we found no difference between model estimates and naïve values of prevalence. While the model predicted no declines in site-level prevalence, there were instances where pathogen load decreased in colonies that had beenPdpositive for longer periods of time. Our findings demonstrate that accounting for pathogen load and prevalence at multiple scales changes our understanding ofPddynamics, potentially allowing earlier conservation intervention. Additionally, we found that accounting for pathogen load and prevalence within hibernacula and among individuals resulted in a better fitting model with greater predictive ability. 

ABSTRACT The skin microbiome is an essential line of host defense against pathogens, yet our understanding of microbial communities and how they change when hosts become infected is limited. We investigated skin microbial composition in three North American bat species (Myotis lucifugus,Eptesicus fuscus, andPerimyotis subflavus) that have been impacted by the infectious disease, white-nose syndrome, caused by an invasive fungal pathogen,Pseudogymnoascus destructans. We compared bacterial and fungal composition from 154 skin swab samples and 70 environmental samples using a targeted 16S rRNA and internal transcribed spacer amplicon approach. We found that forM. lucifugus, a species that experiences high mortality from white-nose syndrome, bacterial microbiome diversity was dramatically lower whenP. destructanswas present. Key bacterial families—including those potentially involved in pathogen defense—significantly differed in abundance in bats infected withP. destructanscompared to uninfected bats. However, skin bacterial diversity was not lower inE. fuscusorP. subflavuswhenP. destructanswas present despite populations of the latter species declining sharply from white-nose syndrome. The fungal species present on bats substantially overlapped with the fungal taxa present in the environment at the site where the bat was sampled, but fungal community composition was unaffected by the presence ofP. destructansfor any of the three bat species. This species-specific alteration in bat skin bacterial microbiomes after pathogen invasion may suggest a mechanism for the severity of white-nose syndrome inM. lucifugusbut not for other bat species impacted by the disease. IMPORTANCEInherent complexities in the composition of microbiomes can often preclude investigations of microbe-associated diseases. Instead of single organisms being associated with disease, community characteristics may be more relevant. Longitudinal microbiome studies of the same individual bats as pathogens arrive and infect a population are the ideal experiment but remain logistically challenging; therefore, investigations like our approach that are able to correlate invasive pathogens to alterations within a microbiome may be the next best alternative. The results of this study potentially suggest that microbiome-host interactions may determine the likelihood of infection. However, the contrasting relationship between Pd and the bacterial microbiomes ofMyotis lucifugusandPerimyotis subflavusindicate that we are just beginning to understand how the bat microbiome interacts with a fungal invader such as Pd. 

Abstract Disease results from interactions among the host, pathogen, and environment. Inoculation trials can quantify interactions among these players and explain aspects of disease ecology to inform management in variable and dynamic natural environments. White-nose Syndrome, a disease caused by the fungal pathogen, Pseudogymnoascus destructans ( Pd ), has caused severe population declines of several bat species in North America. We conducted the first experimental infection trial on the tri-colored bat, Perimyotis subflavus , to test the effect of temperature and humidity on disease severity. We also tested the effects of temperature and humidity on fungal growth and persistence on substrates. Unexpectedly, only 37% (35/95) of bats experimentally inoculated with Pd at the start of the experiment showed any infection response or disease symptoms after 83 days of captive hibernation. There was no evidence that temperature or humidity influenced infection response. Temperature had a strong effect on fungal growth on media plates, but the influence of humidity was more variable and uncertain. Designing laboratory studies to maximize research outcomes would be beneficial given the high costs of such efforts and potential for unexpected outcomes. Understanding the influence of microclimates on host–pathogen interactions remains an important consideration for managing wildlife diseases, particularly in variable environments.