The Heureka Research Programme - Mistra

identified relationships were used to adjust the statistical growth and yieldmodel. The modelling covered a range of stand types and growing conditionsfor the main tree species spruce and pine.A method of linking the results from the process-based model and thestatistical growth and yield model was developed. The method is based onthe concept of adjusting an intrinsic tree age in the empirical growth modelto target the relative changes in the growth potential found by the processbasedsimulations, e.g. when trees are growing better they are regarded asyounger and more vital. The adjustment of the growth potential occurs inevery 5-year period to take into account the stage of the stand developmentand thus the effects of management.Climate scenariosThe simulations of the climate change responses of tree growth were basedon four climate scenarios generated by the regional climate model RCA3developed by the Rossby Centre of the Swedish Meterological and HydrologicalInstitute (SMHI) (Kjellström et al. 2005, 2009). RCA3 was used todown-scale the results of two global circulation models, forced by IPPCemission scenarios: ECHAM5 (emission scenarios A2, A1B, B1) and Had-CM3 (emission scenario A1B), according to SMHI’s recommendations tocapture a range of variation in the predictions of climate change.User valueToday, most researchers agree that the global climate is changing. If so, theempirically-based statistical growth and yield models will not give validestimates without adjustments. Including the effects of a changing climatein long-term planning is vital to make the right decisions for the future (cf.Freeman et al. 2005). Choices of species, thinning regime and age for finalfelling are examples of decisions that have to be reconsidered in a changingclimate. Valid forecasting of the development of the tree layer is crucial forreliable predictions of the outcome of all the goods and services associatedwith the tree layer that is provided by the Heureka system.Scientific resultsProcess-based model simulations were used to estimate the effect of elevatedCO 2, temperature and changed patterns of humidity and precipitation on netprimary production for Norway spruce and Scots pine covering all of Swedenin an approx. 50x50 km grid. Based on these simulations climate changeresponse factors were generated specifically for Swedish conditions (Figure13) (Freeman & Sahlée 2009) as an improvement of the Scandinavian simulations(Bergh et al. 2009). Response functions were developed to transfer theclimate change signal from the process-based model to the statistical growthand yield model based on these factors. The functions of the climate changeresponse were finally used to adjust the growth forecasted by the statisticalmodel (Freeman, Wikström & Elfving 2009).41