NOBEL – Novel business models and mechanisms for the sustainable supply of and payment for forest ecosystem services

Project summary

Payments for Ecosystem Services (PES) are an important mechanism to link the demands of the society with the service providers. The objectives of the project NOBEL are:

  • to develop business models and mechanisms to internalise the socio-economic value of forest ecosystems,
  • combine public policy tools with business models for implementing payments for forest ecosystem services (FES) at multiple levels, and
  • demonstrate and compare alternative approaches for payments in case studies in Europe. NOBEL will explore the requirements for disseminating spatial information for the development of business models and innovative policies for the provision of FES.

In NOBEL three types of business models will be considered

  1. direct interaction between FES providers and FES beneficiaries
  2. interaction between business companies and FES providers where companies pay directly to providers and pass the costs (totally or partially) to their clients, and
  3. interaction between government and FES providers, where the government pays providers for their services and passes the costs to consumers via taxes or fees.

In implementing these business models, alternative mechanisms for the payments (e.g. voluntary payments, natural capital markets) will be explored. A web-based auctioning platform and a spatial information platform will be developed to support the design of business models for multifunctional forest management. For the prediction and optimization of multiple FES a framework of indicators will be designed and available forest ecosystem models will be applied. Management practices, stakeholder attitudes and consumer behaviour will be discussed at supra-national and regional level with policy makers, providers and beneficiaries.

Summary of NMBU’s main responsibilities in the project

FES information is rarely available from national databases. The spatial distribution of FES on large areas is frequently limited by the lack of information because field data collection with traditional methods requires much effort in terms of time and cost. However, spatial data that can be used to derive FES indicators are quite often available and the spatial data and information to map FES might come from several sources (e.g. national acquisition programs for aerial photographs or laser scanning). We will provide an overview of the most relevant and available spatial data and information to map FES in all participating countries. Existing satellite data from pan-European programs such as COPERNICUS will be assessed as well. Furthermore, data for ground-truthing the remotely sensed data will be screened (e.g. national forest inventory data) and the accessibility to these data will be verified.

Spatial information on remaining source areas of natural and near-natural forests will be essential in order to safeguard biodiversity and FES (Sverdrup-Thygeson et al. 2016). Based on experiences and results obtained by Sverdrup-Thygeson et al. (2016) new FES indicators will be explored and demonstrated with available spatial data in the participating countries. This will allow efficient mapping of FES from pan-European data infrastructure and national data acquisition campaigns. The following FES will be explored: timber and non-timber forest products, carbon, biodiversity, recreation, wildlife and protection against gravitational hazards.

Involved countries and partners
Austria – University of Natural Resources and Life Sciences (BOKU)
France – French National Institute for Agricultural Research (INRA)
Germany – Technische Universität München (TUM)
Norway –  Norwegian University of Life Sciences (NMBU)
Spain – Forest Sciences and Technology Centre of Catalonia (CTFC)
Sweden – Swedish University of Agricultural Sciences (SLU)
Portugal – School of Agriculture / Instituto Superior de Agronomia (ISA)

Project Duration
36

Funding
ERA-NET Cofund Action “ForestValue – Innovating the forest-based bioeconomy”
Norwegian Research Council

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