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Forests provide numerous ecosystem services, such as timber yields, biodiversity protection and climate change mitigation. The type of management has an effect on the provision of these services. Often the demands for these services can lead to conflict – wood harvest can negatively impact biodiversity and climate change mitigation capacity. Although forest management differences are important, spatially explicit data is lacking, in particular on a global scale. We present here a first systematic approach which integrates existing data to map forest management globally through downscaling national and subnational forest data. In our forest management classification, we distinguished between two levels of forest management, with three categories each. Level 1 comprised primary, naturally regrown and planted forests. Level 2 distinguished between different forest uses. We gathered documented locations, where these forest categories were observed, from the literature and a database on ecological diversity. We then performed multinomial logit regression and estimated the effect of 21 socio-economic and bio-physical predictor variables on the occurrence of a forest category. Model results on significance and effect direction of predictor variables were in line with findings of previous studies. Soil and environmental properties, forest conditions and accessibility are important determinants of the occurrence of forest management types. Based on the model results, likelihood maps were calculated and used to spatially allocate national extents of level 1 and level 2 forest categories. When compared to previous studies, our maps showed higher agreement than random samples. Deviations between observed and predicted plantation locations were mostly below 10 km. Our map provides an estimation of global forest management patterns, enhancing previous methodologies and making the best use of data available. Next to having multiple applications, for example within global conservation planning or climate change mitigation analyses, it visualizes the currently available data on forest management on a global level.

Ecosystem management of protection forests aims at maintaining forests near a state during which effective protection is secured. As the evolution of a dynamic forest ecosystem cannot be stopped, silvicultural measures are required which aim at maintaining both the ecosystem integrity and the protective function of mountain forests. Ecosystem integrity is defined as the system’s capacity to maintain structure and ecosystem functions using processes and elements characteristic for its ecoregion. Here, ecosystem functions also reflect the capability of the ecosystem to provide functions of value to humans. Ecosystem integrity of a protection forest implies that the stability (mainly the property resilience is addressed) of the forest is high, because that is required to provide a high level of protection in the long term. The main conditions promoting natural evolutionary processes and ecological stability in protection forests are: (1) a diverse composition of species; (2) sufficient natural regeneration; (3) an optimal forest structure. The first example in this chapter explains how these conditions might be achieved by silvicultural interventions in a forest that mainly protects against rockfall in the Austrian Alps. The second example deals with socio-economic aspects of ecosystem integrity of a forest that also protects against rockfall, but then in the French Alps. Both examples show that forest authorities are aware of techniques to improve the stand stability of protection forests, but the problem is that current forest management is often a kind of trial and error, because the exact consequences of interventions for forest ecosystem dynamics are not known. Therefore, it is proposed that forest ecosystem research should shift focus from protection forest dynamics to the geo-ecosystem functioning of protection forests, including the effects of natural and human disturbances. For this, the concept of panarchy may be a promising way forward. # 2004 Elsevier B.V. All rights reserved.