Skip to main navigation Skip to search Skip to main content

D1.1 Forest management approaches across Europe

  • Diana Da Silva Feliciano
  • , Mart-Jan Schelhaas
  • , Sara Uzquiano
  • , Silvester Boonen
  • , Marcus Lindner
  • , Jaena Tiongco
  • , Marco Lovrić
  • , Valentina Bacciu
  • , Alessio Menini
  • , Mikko Peltoniemi
  • , Tudor Stancioiu
  • , Florencia Franzini
  • , Ajdin Starcevic
  • , Igor Staritsky
  • , Chidiebere Ofoegbu

Research output: Book/ReportOther report

Abstract

The National Forestry Accounting Plans (NFAP) by all EU member states, the FACESMAP
country reports and other relevant published literature were reviewed to identify current forest
management approaches and trends across Europe, as well as silvicultural practices
implemented. Even-aged forestry is the most common forest management regime in Nordic
countries such as Finland, Sweden, Norway. Multifunctional forest management is implemented
in France, Belgium, Spain. Agroforestry is implemented in Spain and Portugal. Coppicing is
implemented in Portugal, United Kingdom, and Greece. Closer-to-nature forest management is
implemented in Slovenia and Germany, for example. Many countries are following the principles
of sustainable management principles, namely Germany, the Netherlands, Austria, France, and
Czechia.
Typology studies of forest managers in Europe were reviewed. Most types of forest owners fall
within 5 main categories, namely economic-oriented, tradition-oriented, environmentalists, nonactive/passive and multi-objective forest owners. Even though most studies on typologies do not
associate actual forest management approaches to forest owner or manager types, scattered
information on forest management intensity, size of forest holding, silvicultural practices
implemented, tree improvement, tree species, implementation of nature protection measures,
ownership type, resistance to change, advisory sources, exist and was collated and associated
to forest owner types. Based on available literature and expert knowledge, the percentage of
forest managed per type of forest owner/manager in each country was derived, however with
low confidence. According to the literature, other potential forest owner types exist (e.g., female
forest owners, new forest owners) and these should be further investigated to understand if they
can be considered as a separate type of owner or if their characteristics would place them within
any of the five forest owner types identified. Distinctive forest management approaches can be
associated to each of these emerging types such as managing forest only for the purpose of
offsetting greenhouse gas emissions.
Harvest patterns in repeated national forest inventory data from 11 countries were analysed
following the fate of individual trees on over 230 thousand plots for 2-4 cycles. The average
annual harvest rate (i.e., the probability that a certain tree is harvested) per 1-degree grid cell,
which we used as a reference showing the real (spatial) differentiation in harvest rate was
calculated and mapped. This map was then visually compared to various alternatives, where
harvest rates were calculated and mapped using groupings from a range of potential
explanatory variables such as biogeographic zone, country, protection, topography, and
population characteristics. A clear effect of constraining external factors on the harvest rate that
works in a similar way all over Europe was found, with elevation as the best predictor. However,
within these constraints, a very clear difference between countries was also found, which makes it difficult to generalize management approaches across borders. These inventory-based
observations can be connected in a straightforward way to the forest resource models (LPJGUESS and EFISCEN-Space) but give only information on the combined effect of the behaviour
of the individual forest owners. Since no information is available on the individual owners of the
plots, it is currently impossible to assign them to one of the classes as defined in the literature
review. A further analysis of observed harvest events at the plot level (intensity, frequency)
combined with observed forest structure and tree species composition may give some more
information on the possible ownership and/or management approach at the plot level. Results
from the interviews and the survey will be needed to bridge the gap between the observationbased approach and the literature review.
Based on a review of Climate-Smart Forestry (CSF) definitions and biodiversity management
literature, a comprehensive definition for Climate and Biodiversity-Smart (CBS) Forestry was
developed. CBS incorporates four main pillars: climate change mitigation, adaptation,
biodiversity, and other ecosystem services provisioning. To implement CBS in practice, criteria
are needed to assess what measures can qualify as CBS. So far, CSF assessment has mostly
relied on criteria and indicators of sustainable forest management. However, the existing
indicator lists refer mostly to forests and lack information on CBS forest management impacts
on forest value chains and wood product use. Assessing biodiversity impacts of forest
management also requires further method development, e.g., by specifying minimum
requirements of key parameters such as amount of deadwood in the forest or maintenance of
retention trees. A review of potential CBS forest management practices was carried out. The
measures were categorized and evaluated on the relevance to CBS. CBS needs to be tailored
according to regional conditions. This was illustrated using the ForestPaths demo cases as
examples. Further research is needed to elaborate a wider framework to assess and weigh CBS
indicators and to guide CBS assessment (e.g., in the context of ForestPaths forest simulation
modelling) and its implementation in practical decision-making across the European countries.
Original languageEnglish
PublisherZenodo
Number of pages152
Publication statusPublished - 4 Nov 2024

Fingerprint

Dive into the research topics of 'D1.1 Forest management approaches across Europe'. Together they form a unique fingerprint.

Cite this