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Published on: January 19, 2020
Ecological niche modelling of bank voles in Western Europe
Sara Amirpour Haredasht1, Miguel Barrios, Jamshid Farifteh
1Measure, Model & Manage Bioresponses, Biosystems Department, KU Leuven, Kasteelpark Arenberg 30, Leuven B-3001, Belgium. Jean-Marie.Aerts@biw.kuleuven.be
Abstract:
The bank vole (Myodes glareolus) is the natural host of Puumala virus (PUUV) in vast areas of Europe. PUUV is one of the hantaviruses which are transmitted to humans by infected rodents. PUUV causes a general mild form of hemorrhagic fever with renal syndrome (HFRS) called nephropathia epidemica (NE). Vector-borne and zoonotic diseases generally display clear spatial patterns due to different space-dependent factors. Land cover influences disease transmission by controlling both the spatial distribution of vectors or hosts, as well as by facilitating the human contact with them. In this study the use of ecological niche modelling (ENM) for predicting the geographical distribution of bank vole population on the basis of spatial climate information is tested. The Genetic Algorithm for Rule-set Prediction (GARP) is used to model the ecological niche of bank voles in Western Europe. The meteorological data, land cover types and geo-referenced points representing the locations of the bank voles (latitude/longitude) in the study area are used as the primary model input value. The predictive accuracy of the bank vole ecologic niche model was significant (training accuracy of 86%). The output of the GARP models based on the 50% subsets of points used for testing the model showed an accuracy of 75%. Compared with random models, the probability of such high predictivity was low (χ(2) tests, p < 10(-6)). As such, the GARP models were predictive and the used ecologic niche model indeed indicates the ecologic requirements of bank voles. This approach successfully identified the areas of infection risk across the study area. The result suggests that the niche modelling approach can be implemented in a next step towards the development of new tools for monitoring the bank vole's population.
Insights
Ecological niche modeling accurately predicted bank vole populations, identifying infection risk areas for Puumala virus (PUUV) in Europe. This method aids in monitoring bank vole distribution and disease spread.
Area of Science:
- Ecology
- Epidemiology
- Biogeography
Background:
- The bank vole (Myodes glareolus) hosts Puumala virus (PUUV), a hantavirus causing nephropathia epidemica (NE) in humans.
- Zoonotic diseases exhibit spatial patterns influenced by host distribution and land cover, affecting transmission dynamics.
Purpose of the Study:
- To evaluate ecological niche modeling (ENM) for predicting bank vole geographical distribution using spatial climate data.
- To assess the predictive accuracy of the Genetic Algorithm for Rule-set Prediction (GARP) for bank vole populations.
Main Methods:
- Utilized GARP to model the ecological niche of bank voles in Western Europe.
- Input data included meteorological data, land cover types, and geo-referenced bank vole locations.
- Model accuracy was validated using training and testing subsets.
Main Results:
- The bank vole ecological niche model demonstrated significant predictive accuracy (86% training, 75% testing).
- GARP models showed high predictivity compared to random models (p < 10(-6)).
- The approach successfully identified areas with infection risk.
Conclusions:
- Ecological niche modeling effectively predicts bank vole distribution and identifies areas of PUUV infection risk.
- This ENM approach provides a foundation for developing tools to monitor bank vole populations and manage zoonotic disease risk.
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