Sweden has the world’s highest density of moose. Moose is not only an important game species, it also causes damages to forestry and traffic accidents. In addition, foresters respond by planting spruce monocultures to avoid moose browsing, which reduces biodiversity.
To maintain a healthy moose population in balance with the other interests, management is adaptive based on the knowledge and experiences of local hunters and landowners and the policy makers, The National Forest Agency (NFA) and the Swedish Environmental Protection Agency (SEPA). However, the local stakeholders do rarely agree on what is an appropriate moose population, which leads to conflicts that are hard to resolve.
A key problem is that it is very difficult to understand and predict the full consequences of different options and scenarios for moose hunting and forest management. In this project ESM-CLR (PI Oskar Franklin) addresses this problem in collaboration with NFA and SEPA by developing a systems analysis framework and science-based tools for integrated modelling of the moose population, forestry, and their interactions and consequences for biodiversity and traffic accidents. We analyse the short and long term consequences for multiple scenarios of moose hunting and forest management. Based on the results we elucidate and quantify the trade-offs and possible synergies between moose hunting, forest production, biodiversity and the risk of traffic accidents.
In addition, we will provide a “scenario-based” modelling tool for managers both at a national and regional level, which enables mediated type of modelling exercise together with the relevant stakeholders (land- and forest owners, hunter’s organizations, authorities and planning bodies). The aim is to promote a shared ownership of the planning process, a common understanding of how and why decisions in wildlife management are concluded, and therefore more constructive discussions among stakeholders.
We also plan to extend this framework to include additional forms of land use and important wildlife species in Sweden (deer species, wild boar, bear, and wolf), as well as establishing a capacity for systems analysis of land use and wildlife management in other countries and regions.
Last edited: 28 March 2019
23.11.2017 - 31.03.2019
Franklin O , Moltchanova E, Kraxner F, Seidl R, Bottcher H, Rokityiansky D, & Obersteiner M (2012). Large-scale forest modeling: Deducing stand density from inventory data. International Journal of Forestry Research 934974 DOI:10.1155/2012/934974.
Koca D, Smith B, Bergh J, Nilsson U, Franklin O , Obersteiner M , & Sykes MT (2006). Increased accuracy in climate impact studies by incorporating forest management practices within a process-based regional ecosystem modelling framework. Meddelanden från Lunds universitets geografi ska institution. Avhandlingar No.162 162: 77-89.
International Institute for Applied Systems Analysis (IIASA)
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