Impacts of bioeconomy on climate have been much discussed, but less attention has been given to biodiversity deterioration. One approach to assess biodiversity impacts is Life Cycle Assessment (LCA). Finland is a forested country with intensive forest industries, but only coarse biodiversity LCA methods are available. The aim of this study was to further develop and apply approaches to assess the biodiversity impacts of wood use in Finland. With the species richness approach (all taxons included), biodiversity impacts were higher in Southern than in Northern Finland but impacts in Southern and Northern Finland were lower when mammals, birds and molluscs were included. With the ecosystem indicators approach, if the reference situation were forest in its natural state, biodiversity impacts were higher than in the case where the initial state of forest before final felling was used to derive biodiversity loss. In both cases, the biodiversity impacts were higher in Northern Finland. These results were not coherent as the model applying species richness data assesses biodiversity loss based on all species, whereas the ecosystem indicators approach considers vulnerable species. One limitation of the species richness approach was that there were no reliable datasets available. In the ecosystem indicators approach, it was noticed that the biodiversity of managed Finnish forests is substantially lower than in natural forests. Biodiversity LCA approaches are highly sensitive to reference states, applied model and data. It is essential to develop approaches capable of comparing biodiversity impacts of forest management practices, or when looking at multiple environmental impacts simultaneously with the LCA framework.
Myllyviita, T., Sironen, S., Saikku, L., Holma, A., Leskinen, P. and Palme, U. Assessing biodiversity impacts in life cycle assessment framework - Comparing approaches based on species richness and ecosystem indicators in the case of Finnish boreal forests. Journal of Cleaner Production 236, 1 November 2019, 117641. https://doi.org/10.1016/j.jclepro.2019.117641