Predicting Rodent Population Dynamics as Early Warning for Zoonotic Disease Transmission

Abstract

Purpose: Rodent borne diseases, including those indirectly transmitted by vectors, represent an increasing threat for public health. The provisioning of early warning indicators of the changing hazard is of great utility for the improvement of prevention and control strategies.Climate can affect tree seed production, which represents the major food resources for several rodent species including Apodemus flavicollis, a very common forest rodent species and an important reservoir for different zoonotic pathogens (as Hantavirus, TBEV and Borrelia burgdorferi s.l). We thus investigate how climatic data alone might be useful to predict rodent population dynamics which in turn affect rodent borne disease risk as seen in previous studies. Methods & Materials: Rodents were monitored for 20 years (2000-2020) using Capture-Mark-Recapture method. Four grids with 8 × 8 multiple live traps and intertrap distance of 15 m were located in the Province of Trento, northern Italy. At each session a set of standard parameters were recorded (for example: species, sex, body mass, etc..) and animals were individually tagged with a subcutaneous transponder. Animal abundance was obtained using the Jolly-Seber method and then averaged over study sites and year of sampling. Temperature and precipitation data were obtained from a weather station close to the study area. Linear models were implemented to assess how yearly average mice abundance was associated with previous years weather conditions. Results: We found that warmer summers two years before sampling are positively related to A. flavicollis average population densities in forests dominated by beech belonging to European alpine biomes. On the other hand, precipitation occurring during the autumn before sampling negatively influenced mice abundance. We thus hypothesized that wetter conditions during this season could reduce mice survival. Conclusion: To the best of our knowledge, this is one of the first attempts at investigating how rodent abundance might be predicted using climatic data obtained from local weather stations in the alpine region. Our results highlight important correlations, which eventually might be used for estimating risk of transmission of rodent borne zoonotic pathogens.