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Owner mapping for forest scenario modelling — A Lithuanian case study

Mozgeris, Gintautas, Brukas, Vilis, Stanislovaitis, Andrius, Kavaliauskas, Marius, Palicinas, Michailas
Forest policy and economics 2017 v.85 pp. 235-244
attitudes and opinions, biomass, carbon, case studies, ecosystem services, experts, feeds, forest management, foresters, forests, interviews, issues and policy, managers, models, motivation, private forestry, private research, profits and margins, qualitative analysis, species diversity, trees, Lithuania
Ample research on private forest owners (PFOs) has established high heterogeneity in owners' objectives, motivations and management decisions. Such heterogeneity is, however, rarely taken into account in forest scenario modelling. This study, in contrast, conducts a detailed forest owner mapping that feeds into simulations of ecosystem services (ES) under alternative future scenarios. First, we identify four private forest owner types (FOT) – Forest Businessmen, Household Foresters, Passive Forest Lovers, and Ad Hoc Owners through in-depth interviews and qualitative analyses on a case study area in western Lithuania. Next, each forest estate and forest compartment is assigned a FOT by combining the property registry and forest characteristics with opinions of two types of local experts: state forest managers and inspectors from the State Forest Service. Third, a set of forest management (FM) programmes is specified using field interviews and desktop research, FM records, and expert judgement for each forest compartment. Finally, ES provision is projected using a behavioural matrix combining management styles of FOTs with details of FM programmes. We simulate the dynamics of profits from forestry activities, accumulated carbon in live biomass and tree species diversity under a reference scenario without substantial changes; and a policy intervention scenario. The study demonstrates that treating forest owners as a homogenous group overestimates profits from timber and underestimates the provision of the other analysed ES, potentially misinforming policy decisions.