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

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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