20.500.12556/RUL-133426 Modelling future growth of mountain forests under changing environments Models to predict the effects of different silvicultural treatments on future forest development are the best available tools to demonstrate and test possible climate-smart pathways of mountain forestry. This chapter reviews the state of the art in modelling approaches to predict the future growth of European mountain forests under changing environmental and management conditions. Growth models, both mechanistic and empirical, which are currently available to predict forest growth are reviewed. The chapter also discusses the potential of integrating the effects of genetic origin, species mixture and new silvicultural prescriptions on biomass production into the growth models. The potential of growth simulations to quantify indicators of climate-smart forestry (CSF) is evaluated as well. We conclude that available forest growth models largely differ from each other in many ways, and so they provide a large range of future growth estimates. However, the fast development of computing capacity allows and will allow a wide range of growth simulations and multi-model averaging to produce robust estimates. Still, great attention is required to evaluate the performance of the models. Remote sensing measurements will allow the use of growth models across ecological gradients. SDG 15 climate-smart forestry CLIMO forestry management modelling gorski gozdovi sonaravno gozdarstvo podnebno pametno gozdarstvo modeliranje true false true Angleški jezik Slovenski jezik Neznano 2021-11-26 12:38:56 2021-11-26 12:45:35 2023-01-18 09:28:43 0000-00-00 00:00:00 2022 0 0 Str. 223-262 0000-00-00 Zaloznikova Objavljeno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 630*61+630*22:630*111 10.1007/978-3-030-80767-2_7 86700547 86678787 https://link.springer.com/chapter/10.1007/978-3-030-80767-2_7 0 5c47d249-4ead-11ec-abdb-00155dcfd717 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=151485 RAZ_Bosela_Michal_2022.pdf RAZ_Bosela_Michal_2022.pdf 1 32608B2DB69D20DDB30DD66679D91332 3d331cf479c83825e6d49ada6d307e562ef68953986c3e718c721672a46e06c6 51c0ce0e-4eae-11ec-abdb-00155dcfd717 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=151494 Biotehniška fakulteta 0 0 0