Researchers have developed a new modeling approach to better estimate pathogen dynamics in bats, significantly enhancing our understanding of white-nose syndrome, a devastating disease impacting hibernating bat populations in North America.
The multi-scale dynamic occupancy hurdle model (MS-DOHM) was created to effectively monitor the spread of Pseudogymnoascus destructans (Pd), the fungus responsible for the disease, which has led to drastic population declines in several bat species. By integrating pathogen load and prevalence into its calculations, the MS-DOHM offers more accurate insight into how the pathogen affects bat colonies over time.
Traditional methods, often reliant on simplistic presence/absence data, have been insufficient in capturing the complexities of pathogen dynamics. The MS-DOHM, however, utilizes quantitative real-time PCR (qPCR) cycle thresholds to estimate pathogen load, providing a more nuanced picture of Pd's impact.
Data for the model was acquired from sampling conducted from 2011 to 2017 across 42 sites, including caves and mines, with a specific focus on hibernating little brown bats (Myotis lucifugus). On average, a minimum of eleven swabs were taken from bats during each sampling visit. Using qPCR methods, researchers determined the presence of Pd based on cycle threshold (Ct) values, with results indicating that a Ct score of 40 or lower was considered positive.
The MS-DOHM model produced significantly higher pathogen estimates compared to both traditional dynamic occupancy models and naïve occupancy methods. Specifically, site-level pathogen presence estimates were determined to be as much as 11.9% higher than dynamic occupancy models and 35.7% greater than naïve occupancy estimates. This disparity underscores the importance of incorporating pathogen load and prevalence into the framework to enable early detection and potentially prevent further spread by facilitating timely conservation efforts.
"By integrating multiple levels of data, including all qPCR runs, pathogen load, and sampled bat populations, the MS-DOHM model not only improves the reliability of pathogen detection but also yields earlier estimates of pathogen arrival," stated the authors of the article.
One of the remarkable revelations from this model was that it estimated pathogen arrival at affected sites one to two years earlier than traditional methods. For instance, discrepancies in the initial year of pathogen detection were identified at 16.7% of the sites compared to the dynamic occupancy model and 52.4% compared to naïve occupancy assessments. This earlier detection can have significant implications for conservation management and intervention strategies.
Given that prevalence and pathogen load increase over time, understanding these dynamics becomes crucial for bat species under threat. The model showed that pathogen prevalence correlated positively with how long Pd had been detected at a site. Interestingly, while the MS-DOHM projected stable prevalence rates at certain sites, it also indicated possible decreases in pathogen load over time within colonies that had been previously positive.
"In scenarios where pathogen loads decreased, it suggests there could be instances of resistance developing among particular bat populations," explained the authors, revealing an important avenue for further investigation into potential recovery mechanisms.
The implications of this research extend beyond just understanding white-nose syndrome. As the model establishes a comprehensive framework for pathogen dynamics, it can potentially be applied to other species and diseases. The need for precise surveillance methods that rapidly respond to emerging wildlife diseases is critical, and the MS-DOHM provides a promising tool to meet this challenge.
Conservationists argue that early detection of pathogens is essential for mitigating the impacts of disease outbreaks and improving management responses. The framework proposed by the MS-DOHM offers a pathway forward, allowing for informed decisions that can effectively combat ongoing threats to wildlife health.
As bat populations continue to be affected by white-nose syndrome, the significance of adopting advanced modeling techniques cannot be overstated. The new model not only aids in understanding how pathogens spread through ecosystems but also emphasizes the importance of adapting our monitoring efforts to better protect vulnerable species.
