François Mougeot, Xavier Lambin, Beatriz Arroyo, Juan-José Luque-Larena
The detected warning signal is early enough for timely farming decisions ahead of the autumn sowing season, allowing increased monitoring and preventive management actions prior to a vole outbreak. It can be used in future work to develop predictive models, whose accuracy can be improved as new data become available. © 2026 The Author(s). Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.
BACKGROUND: Rodent outbreaks have significant socio-economic impacts worldwide, affecting food production and public health. Management actions to limit these impacts are more effective when implemented preventively rather than reactively. Because anticipation is crucial, managers need reliable and timely warning signals of rodent population growth (PGR) for efficient pest management, farming decisions or disease prevention. Using common vole Microtus arvalis outbreaks in NW Spain as a case study, we searched for early climatic signals associated with increased vole PGR using 16 years of abundance data from trapping surveys in six sites (2009-2025).
RESULTS: Study populations fluctuated with a 3-year period and PGR was suppressed 1 year after a peak (low phase). We found that both rainfall between Marcht-1 and Marcht, and minimum temperature between February t and June t predicted vole PGR between July t and Julyt+1. Using time windows constrained to reflect when management actions can be preventively implemented in the agricultural calendar, we further show that rainfall between Marcht-1 and Julyt-1 predicted vole PGR, providing a warning signal 1 year before a peak. Combining this early predictor with field-evidence about the low phase provided easy to use information about vole outbreak risk in the region.
CONCLUSION: The detected warning signal is early enough for timely farming decisions ahead of the autumn sowing season, allowing increased monitoring and preventive management actions prior to a vole outbreak. It can be used in future work to develop predictive models, whose accuracy can be improved as new data become available. © 2026 The Author(s). Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.