Increased accuracy in climate impact studies by incorporating forest management practices within a process-based regional ecosystem modelling framework

Process-based simulation models of terrestrial ecosystem dynamics are increasingly being applied as practical tools in forest management. Regional applications of such models are, however, very limited to date. This study presents and tests the performance of a process-based regional ecosystem modelling framework, LPJ-GUESS, which incorporates forest management practices. The model is driven by historical climate data and applied on a grid across Sweden to simulate the infl uence of recent historical management practices on the forest structure and its productivity. The study focuses on species-level interactions and investigates how stem wood volume increment has changed during the historical time period. The performance of the model is evaluated by comparing the simulated forest composition and growth with the observed forest inventory data from Swedish forest regions. The model estimates tend to be somewhat low in the southern and high in the northern part of the country, but generally comparable with observations in all regions of Sweden. Our results emphasize the potential that models like LPJ-GUESS offers to support forestry practice, especially with regard to the choice of species and management regime in a changing environment.