Abstract
Forests provide a wide range of ecosystem services, and ecosystem models can be applied to assess the contribution of different forest management strategies to climate mitigation and adaptation. Complex model output and trade-offs between environmental, economic, and social sustainability dimensions are difficult to convey. To facilitate stakeholder communication, we developed composite indicators based on ten ecosystem service indicators obtained from ecosystem model simulations representing 19 forestry management strategies across three ecoregions and climate scenario projections in Sweden. Eight alternative composites were generated around a central framework addressing sustainability aspects in terms of wood production, preservation of biodiversity, climate change mitigation and adaptation (risk management). A combination of principal component analysis, exploratory factor analysis, Cronbach’s coefficient alpha, and hierarchical cluster analysis was applied to account for the statistical relationships between indicators. Z-score normalization was superior to min-max normalization in capturing differences among management strategies. Two weighting schemes were applied, based on policy prioritizations between sub-components that reflected 1) current policy with an equal emphasis on production and biodiversity, and 2) a stronger focus on nature protection. Equal emphasis generated a larger range of scores (76.0 ± 21.2) than the focus on nature protection (32.0 ± 5.8), as the latter would provide less production benefits and thereby fewer trade-offs between production and other aspects. The final scores of the 19 management strategies fell within a variance boundary of each other, showing their contribution to different policy targets and the usefulness of combining strategies at the landscape level. The composites displayed agreement across regions and scenarios. They indicated that a shift from even-aged conifer monocultures towards a combination of continuous cover, broadleaf-mixture, and unmanaged would work well for balancing goals under changing climate conditions.
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