Simulation study reveals that regional parameterization improves bark beetle outbreak predictions in boreal forests, highlighting the critical role of overwintering dynamics.
European spruce bark beetle ( Ips typographus L., SBB) outbreaks are expected to intensify under climate change and increasingly affect the boreal forests of Northern Europe, where they have historically caused only minor damage. Integrating SBB disturbances into forest dynamics models can support risk assessment and integrative forest management. Reliable simulations of SBB outbreaks require adaptation of model parameters to regional phenological conditions. This study aimed to (i) evaluate the transferability of the bark beetle module implemented in iLand from temperate Central European conditions to boreal Northern European conditions, (ii) develop and test boreal-specific parameters of the module and modify their values where necessary, and (iii) examine the internal processes controlling annual beetle development and generation timing. Key parameters differing between temperate and boreal conditions were identified and evaluated through sensitivity analyses. Model simulations were compared with observations from an SBB outbreak in Finland. Parameters requiring modification under boreal conditions were related to infestation onset, beetle development, and overwintering. Simulations using the temperate parameterisation did not sustain the SBB outbreak following a large-scale wind disturbance in boreal conditions. In contrast, the boreal parameterisation reproduced more closely the observed outbreak. Overwintering parameters had the strongest influence on model transferability. Day length and the proportion of beetles overwintering in the soil were identified as the most sensitive parameters. Under both parameterisations, filial and sister-brood generations developed every year, while the second parental generation was limited. The proposed boreal parameterisation improves the applicability of the iLand bark beetle module under boreal forest conditions and supports more robust simulations across climatic regions.
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Șimon et al. (2026) studied this question.
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