Evaluating LPJ-GUESS for Simulating Drought Responses in Swedish Forest

Forests provide critical ecosystem services, including timber production and climate and water regulation, but these are increasingly threatened by climate-driven disturbances such as drought. The 2018 Swedish drought exemplified this risk, causing extensive wildfires, a severe spruce bark beetle outbreak, and reduced forest productivity. Projections for Nordic countries indicate warmer conditions and more frequent and intense droughts, highlighting the need for tools that can accurately predict such impacts to support adaptive forest management. We evaluated recent LPJ-GUESS developments for simulating drought impacts in Scots pine (Pinus sylvestris) and Norway spruce (Picea abies) in Sweden. We evaluated two LPJ-GUESS versions: a European-optimized version with updated trait and structural parameters for major European tree species, and a second version that adds a mechanistic plant hydraulic scheme to this same parameterization, enabling representation of contrasting isohydric and anisohydric stomatal strategies. Model outputs were evaluated against high-resolution carbon and water flux data from three Swedish ICOS sites and against National Forest Inventory growth records. Preliminary results show that the combined version better captures the 2018 drought signal observed in carbon flux data but does not necessary yield improvements in annual fluxes of gross primary production and evapotranspiration. We conclude with an outlook for steps to improve simulations of drought stress in Nordic forests.