The bank vole Clethrionomys glareolus is a widespread rodent in European woodlands, but detailed demographic information from southern Europe is limited. We investigated its demography in a lowland woodland in the Po Plain (NW Italy) using CMR surveys conducted in 1994 and 2002. We estimated population abundance using closed-population models and analysed survival (Φ) and recapture probability (p) using Cormack–Jolly–Seber models at monthly and seasonal temporal scales. Both study periods showed pronounced seasonal fluctuations in abundance, with peaks occurring during the reproductive season. Despite the 8 year between surveys, mean abundance remained similar (40.8±6.8 and 42.8±5.3), indicating medium-term demographic stability. Nevertheless, the two study periods differed markedly in demographic structure. A male biased sex ratio was observed in 1994 (0.47; χ² = 25.85, p < 0.001) and 2002 (0.73; χ² = 4.17, p = 0.041), whereas monthly variation was marginal or not significant in both periods. Monthly survival analyses strongly supported temporal variation in apparent survival, with time-dependent models receiving strong support in both periods. However, seasonal aggregation of capture histories reduced support for temporal heterogeneity Seasonal survival was Φ = 0.318 (95% CI = 0.244–0.403) in 1994–1995, whereas in 2002–2003 it was Φ = 0.457 (95% CI = 0.352–0.566) for females and Φ = 0.327 (95% CI = 0.235–0.433) for males. Abundance and survival were not significantly related, suggesting that recruitment and/or dispersal probably contributed more than survival to population fluctuations. The population trend we observed closely resemble those reported for non-cyclic bank vole populations in temperate European forests, indicating that our populations do not exhibit distinctive demographic patterns and retain the seasonal dynamics observed in Central Europe. The study highlights how the temporal resolution adopted in CMR analyses can substantially influence demographic inference, emphasizing the importance of evaluating survival processes at multiple temporal scales.