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Forest landscape restoration is a widely accepted approach to sustainable forest management. In addition to revitalizing degraded sites, forest landscape restoration can increase the supply of sustainable timber and thereby reduce logging in natural forests. The current study presents a spatial land use optimization model and utilizes a linear programming algorithm that integrates timber production and timber processing chains to meet timber demand trade-offs and timber supply. The objective is to maximize yield and profit from forest plantations under volatile timber demands. The model was parameterized for a case study in Thai Nguyen Province, Vietnam, where most forest plantations grow Acacia mangium (A. mangium). Data were obtained from field surveys on tree growth, as well as from questionnaires to collect social-economic information and determine the timber demand of local wood processing mills. The integration of land use and wood utilization approaches reduces the amount of land needed to maintain a sustainable timber supply and simultaneously leads to higher yields and profits from forest plantations. This forest management solution combines economic and timber yield aspects and promotes measures focused on economic sustainability and land resource efficiency.

info:eu-repo/semantics/published

Forest Focus (Regulation (EC) No 2152/2003) is a Community scheme for harmonized, broadbased, comprehensive and long-term monitoring of European forest ecosystems. Under this scheme the monitoring of air pollution effects on forests is carried out by participating countries on the basis of the systematic network of observation points (Level I) and of the network of observation plots for intensive and continuous monitoring (Level II). According to Article 15(1) of the Forest Focus Regulation Member States shall annually, through the designated authorities and agencies, forward to the Commission geo-referenced data gathered under the scheme, together with a report on them by means of computer telecommunications and/or electronic technology. For managing the data JRC has implemented a Forest Focus Monitoring Database System. This report presents the methodology used to validate Level II data. The procedures applied at the various stages of checking data Compliance, Conformity and Uniformity are described. The report also provides detailed information on the interpretation of data formats and the threshold values used in the Conformity range tests., JRC.H.7-Land management and natural hazards

The aim of the presented Internal Report 2001 is to analyse the temporal development of defoliation of Picea abies in Europe by means of the transnational Level I data set. Additional external deposition and meteorological data are used to describe the influence of single stress factors. Evaluations are conducted using multivariate linear models in a two step analysis. Step 1 evaluates variables that were available in annual or higher time resolution in relation to annual mean plot defoliation for the years 1994 to 2000. The regression coefficient for the interaction term 'year*plotid' is interpreted as plot-wise time trend. It is presented in maps and after a geostatistical analysis detecting spatial autocorrelation interpolated by the geostatistical method 'kriging'. Rooted mean squared errors (RMSE) are calculated for all plots. They give a sensitive measure for the discontinuity of defoliation development and serve as a conservative estimate for the accuracy of the linear models offering a tool for quality control when interpreting the time trends. Results of step 1 show significant influences of insects, age and country as well as their interaction terms on annual mean defoliation. Time trends were only significant for plots and countries, which shows that for Picea abies there is no significant mean European wide trend. Fungi gave implausible results, whereas summer precipitation showed insignificant but mostly plausible effects. Larger regions with deteriorating defoliation are observed in southern Sweden and Finland, in Estonia as well as in alpine regions of Switzerland, Austria, and Slovenia. Improving crown condition is observed in northern Scandinavia, Lithuania, southern Poland, and in Slovakia. The analysis of the RMSE reveals single plots with extreme defoliation values, these could however only be partly explained by information available from the Level I data base. The interpretation of time trends at these plots has to be conducted with care. Step 2 of the analysis is the explanation of plot-wise time trends and RMSE values by predictors of low temporal resolution. Preliminary results show that trends of defoliation are correlated with the difference in SOx deposition between 1998 and 1997, with water availability and base saturation. The promising results for sulphur deposition underline the necessity to include annual deposition values into step 1 of the analysis in the future. Site characteristics may show closer correlation when combined with meteorological data of higher time resolution. After discussion of the results in an editorial group the evaluations are foreseen to be extended and applied to other main tree species for a presentation in the Forest Condition Report of UN/ECE and EU in 2002.

The aim of this Internal Report is to analyse the spatial and temporal development of defoliation for Norway spruce (Picea abies) as well as for European and Sessile oak (Quercus robur and Q. petraea) in Europe by means of the transnational Level I data set of ICP Forests and the European Union's 'Scheme on the Protection of Forests against Atmospheric Pollution'. Additional external deposition and meteorological data are used to describe the influence of single stress factors. According to the methodology published in LORENZ et al. (2002) the medium term mean defoliation is used to describe the spatial variability whereas the plot and year specific differences to the medium term mean are used to describe the temporal variability. Possible refinements of the methodology are outlined as well. In line with expectations the analyses of the spatial variability of Norway spruce and oak species show significant correlations of insects, age and country with annual mean defoliation. In general, the deposition of sulphur was positively correlated with medium term mean defoliation. The models revealed no consistent results for the nitrogen components but nitrate deposition was significant in the model for Norway spruce with negative regression coefficients. The index for fungi infestation was negatively correlated with medium term mean defoliation of oak species. This was not expected from the understanding of fungi as damaging effect but was also found for beech (Fagus sylvatica) in earlier evaluations (LORENZ et al. 2002). The index for insect pests was significant in the models for Norway spruce as well as for oak. Additionally, plausible but not significant correlations were found with precipitation. Time trends were mapped for Norway spruce and oak species as a description of the mean development in the evaluation period. The analyses of the temporal variation of defoliation for Norway spruce and oak will be carried out for the Technical Report Level I 2003. Additionally, alternative methods and amendments to the method published by LORENZ et al. (2002) will be tested.

FORMIT-M is a widely applicable, open-access, simple and flexible, climate-sensitive forest management simulator requiring only standard forest inventory data as input. It combines a process-based carbon balance approach with a strong inventory-based empirical component. The model has been linked to the global forest sector model EFI-GTM to secure consistency between timber cutting and demand, although prescribed harvest scenarios can also be used. Here we introduce the structure of the model and demonstrate its use with example simulations until the end of the 21st century in Europe, comparing different management scenarios in different regions under climate change. The model was consistent with country-level statistics of growing stock volumes (R2 = 0.938) and its projections of climate impact on growth agreed with other studies. The management changes had a greater impact on growing stocks, harvest potential and carbon balance than projected climate change, at least in the absence of increased disturbance rates., Environmental Modelling & Software, 115, ISSN:1364-8152, ISSN:1873-6726