Schibalski A., Lehtonen A., Hickler T., Schröder B. (2017). Identifying important topics for model refinement in a widely used process-based model informed by correlative model analyses in a boreal forest. Silva Fennica vol. 51 no. 4 article id 6977. 24 p. https://doi.org/10.14214/sf.6977
Highlights• Continental-scale model parameterization of widely used LPJ-GUESS experiences problems when applied on the regional level.• Competition, disturbances and soil conditions are crucial for explaining treeline position in Finland, besides climatic limitation.• Picea abies is overly dominant in LPJ-GUESS model, as key competitive mechanisms are not implemented in sufficient detail.
AbstractModels attempting to predict treeline shifts in changing climates must include the relevant ecological processes in sufficient detail. A previous correlative model study has pointed to nutrients, competition, and temperature as the most important factors shaping the treelines of Pinus sylvestris L., Picea abies (L.) H. Karst. and Betula pubescens Ehrh. in Finnish Lapland. Here, we applied a widely used process-based dynamic vegetation model (LPJ-GUESS) to (i) test its capability to simulate observed spatial and temporal patterns of the main tree species in Finnish Lapland, and (ii) to explore the model representation of important processes in order to guide further model development. A European parameterization of LPJ-GUESS overestimated especially P. abies biomass and the species' northern range limit. We identified implemented processes to adjust (competition, disturbance) and crucial processes in boreal forests to include (nutrient limitation, forest management) which account for the model's failure to (edaphically) restrict P. abies in Finnish Lapland and the resulting species imbalance. Key competitive mechanisms are shade and drought tolerance, nutrient limitation, fire resistance, and susceptibility to disturbances (storm, herbivory) which we discussed with respect to boreal ecology and promising model developments to provide a starting point for future model development.