Forest coverage in the Netherlands has expanded from 2% at the beginning of the nineteenth century to 11% nowadays (370,000 ha). Wood production is only one function among many others including recreation and nature protection. Consequently, the harvest level is low relative to the increment (~55%), and the wood-based industry is not an important economic activity. Forests are inventoried at irregular time intervals, with the last inventory in 2012–2013.
There is no regular program for making projections for the forest-based sector. In 2005, the Dutch Ministry for Agriculture, Nature and Food safety requested a projection for demand and supply of wood for the period 2005–2025, aiming at mapping risks and opportunities for forest owners as well as the woodworking industries. This study includes resource projections using two models, one is the individual tree-based model ForGEM and the other is the large scale scenario model EFISCEN.
Both models used data from the 5th National Forest Inventory (2001–2005) as a starting point and focussed on the 240,000 ha that were classified as production forest (i.e. excluding areas that are likely managed for different purposes). For the ForGEM simulations, plots were classified into 19 representative groups based on species and stand structure, and simulations were done for each group. For the EFISCEN simulations, the data were aggregated into eight groups based on dominant species. Both models simulated low and high harvesting scenarios, roughly aiming at removal of 40% and 80% of the increment, respectively. A simple supply estimation was done for the remaining 120,000 ha of other forest and trees outside forest.
The model outcomes differed substantially due to differences in treatment of increment. Additional uncertainty arises from the rather subjective judgement of the field crew as to whether a plot belongs to the production forest category or other forest category. With the sixth National Forest Inventory (NFI6) recently being completed, a better assessment of actual increment and forest management is possible, and more accurate projections can be made. Preferably, future projections should include additional information such as GIS analysis and estimates of costs and revenues. However, the most uncertain factor will remain the forest owners’ behaviour, especially how they will react to changes in prices and policies.
- Clerkx APPM, Schelhaas MJ, Zwart J (2015) Oogst in het Nederlandse bos: analyse van niet-geoogste plots uit de Zesde Nederlandse Bosinventarisatie. Alterra rapport 2610, WageningenGoogle Scholar
- Jansen JJ, Sevenster J, Faber PJ (1996) Opbrengsttabellen voor belangrijke boomsoorten in Nederland. IBN rapport 221, IBN-DLO, WageningenGoogle Scholar
- KNMI (2007) Koninklijk Nederlands Meteorologisch Instituut. www.knmi.nl. Accessed 23 July 2007
- Kramer K, van der Werf DC (2010) Equilibrium and non-equilibrium concepts in forest genetic modelling: population- and individually-based approaches. For Syst 19:100–112Google Scholar
- Oosterbaan A, van den Berg CA, Schelhaas MJ (2007) Ontwikkelingen in vraag en aanbod van rondhout in Nederland en aangrenzend gebied en mogelijke knelpunten en kansen voor de bos- en houtsector in de periode 2005–2025. Alterra rapport 1510, WageningenGoogle Scholar
- Sallnäs O (1990) A matrix growth model of the Swedish forest. Studia Forestalia Suecica 183Google Scholar
- Schelhaas MJ, Wijdeven SMJ, van der Werf DC (2005) Zelfregulerende bossen. Een modelstudie naar effecten van ‘niets doen’ en actief beheer op ontwikkelingen in bosstructuur. Wageningen, Alterra, Alterra-rapport 1270Google Scholar
- Schelhaas MJ, van Brusselen J, Pussinen A et al (2006) Outlook for the development of European forest Resources. A study prepared for the European Forest Sector Outlook Study (EFSOS). Geneva Timber and Forest Discussion Paper, ECE/TIM/DP/41. UN-ECE, GenevaGoogle Scholar
- Schelhaas MJ, Eggers J, Lindner M et al (2007) Model documentation for the European Forest Information Scenario model (EFISCEN 3.1). Alterra report 1559, Wageningen, EFI Technical Report 26, Joensuu, FinlandGoogle Scholar
- Schelhaas MJ, Clerkx APPM, Daamen WP et al (2014) Zesde Nederlandse Bosinventarisatie; Methoden en basisresultaten. Alterra rapport 2545, WageningenGoogle Scholar