4.02.07 - Large-scale forest inventory and scenario modelling



Publication Alert: Global biodiversity and productivity

Positive biodiversity-productivity relationship predominant in global forests

This article, in which IUFRO officeholder Gert Jan Nabuurs is a co-author, has just been published in Science.

The relationship between biodiversity and ecosystem productivity has been explored in detail in herbaceous vegetation, but patterns in forests are far less well understood. Liang et al. have amassed a global forest data set from >770,000 sample plots in 44 countries. A positive and consistent relationship can be discerned between tree diversity and ecosystem productivity at landscape, country, and ecoregion scales. On average, a 10% loss in biodiversity leads to a 3% loss in productivity. This means that the economic value of maintaining biodiversity for the sake of global forest productivity is more than fivefold greater than global conservation costs.

Details at: http://science.sciencemag.org/content/354/6309/aaf8957

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Susana Barreiro, Portugal


Clara Anton Fernandez, Norway

Carlos Sanquetta, Brazil

About Unit


Analyses of the potential of the forest ecosystem to provide a diverse set of goods and services are becoming more and more important when forming strategies for resource utilisation and forest policies. It includes analyses of the effects of policies and strategic plans on site-specific, on-the-ground forest and ecosystem management. Common issues in forest policy making and ecosystem management are such as: what are the effects of changes in management practices or external conditions (e.g. human population, forest ownership, timber utilization techniques, climate) on timber production or what is the effective land-use allocation between timber production, agriculture and nature conservation, for example, when taking into account the multiple needs of current and future generations. Examples are the EU goal to reach 20% renewable energy sources in 2020, to a large extent by forest bio-fuel. Simultaneously, there are conflicting demands of using wood as a raw material for a numerous of products and to sequester carbon in forest biomass and soil.

Forestry models based on large-scale forest inventory are tools for such analysis at national and regional level. To share methods and techniques developed by teams and individual researchers in different countries and regions it is necessary to understand the similarities and differences between different approaches and settings. To analyse global problems such as the effects of climate change we need common standards for terms related with modelling and analysis (glossary) and harmonized outputs (statistics) from our modelling efforts.

General objectives

  • to promote the use of forest scenario modelling in forest policy making, regional land-use planning, and forest management;
  • to define the requirements for large-scale forest inventory from the scenario modelling point of view;
  • to improve the linkages with forest sector modelling concerning, e.g., timber supply and wood quality; and
  • to develop modelling and valuation of non-timber benefits.

Specific objectives

  • to bring together forestry modellers and analysts from different disciplines with forest management planning and forest policy experts from different conditions;
  • to construct facilities for distributing and sharing information related to requirements and experiences; and
  • to promote international co-operation via common projects.

State of Knowledge

Typically tools for large scale modelling have been operating plot level forest data (e.g., National Forest Inventory data). Moreover, data and analyses have concerned forest land only. Of several reasons, such as fragmentation of forests and its effects on biodiversity, it is desirable to base analyses on wall-to-wall data and also to incorporate dynamic relations to other land uses. Such approaches imply, among others, high demands on data acquisition, on data base management (huge data sets), on computational capacities of computers, and on methodological approaches.