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BackgroundAt the 15th Conference of Parties of the UN Framework Convention on Climate Change, Copenhagen, 2009, harvested wood products were identified as an additional carbon pool. This modification eliminates inconsistencies in greenhouse gas reporting by recognizing the role of the forest and timber sector in the global carbon cycle. Any additional CO2-effects related to wood usage are not considered by this modification. This results in a downward bias when the contribution of the forest and timber sector to climate change mitigation is assessed. The following article analyses the overall contribution to climate protection made by the forest management and wood utilization through CO2-emissions reduction using an example from the German state of North Rhine-Westphalia. Based on long term study periods (2011 to 2050 and 2100, respectively). Various alternative scenarios for forest management and wood usage are presented.ResultsIn the mid- to long-term (2050 and 2100, respectively) the net climate protection function of scenarios with varying levels of wood usage is higher than in scenarios without any wood usage. This is not observed for all scenarios on short and mid term evaluations.The advantages of wood usage are evident although the simulations resulted in high values for forest storage in the C pools. Even the carbon sink effect due to temporal accumulation of deadwood during the period from 2011 to 2100 is outbalanced by the potential of wood usage effects.ConclusionsA full assessment of the CO2-effects of the forest management requires an assessment of the forest supplemented with an assessment of the effects of wood usage. CO2-emission reductions through both fuel and material substitution as well as CO2 sink in wood products need to be considered.An integrated assessment of the climate protection function based on the analysis of the study’s scenarios provides decision parameters for a strategic approach to climate protection with regard to forest management and wood use at regional and national levels.The short-term evaluation of subsystems can be misleading, rendering long-term evaluations (until 2100, or even longer) more effective. This is also consistent with the inherently long-term perspective of forest management decisions and measures.

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According to the United Nations International Panel on Climate Change good practice guidance, an annual forest biomass carbon balance (AFCB) can be estimated by either the stock-difference (SD) or the gainloss (GL) method. An AFCB should be accompanied by an analysis and estimation of uncertainty (EU). EUs are to be practicable and supported by sound statistical methods. Sampling and model errors both contribute to an EU. As sample size increases, the sampling error decreases but not the error due to errors in model parameters. Uncertainty in GL AFCB estimates is dominated by model-parameter errors. This study details the delta technique for obtaining an EU with the SD and the GL method applicable to the carbon in aboveground forest biomass. We employ a Brownian bridge process to annualize the uncertainty in SD AFCBs. A blend of actual and simulated data from three successive inventories are used to demonstrate the application of the delta technique to SD-and GL-derived AFCBs during the years covered by the three inventories (SD) and rescaled national wood volume harvest statistics (GL). Examples are limited to carbon in live trees with a stem diameter of 7 cm or greater. We confirm that a large contribution to the uncertainty in an AFCB comes from models used to estimate biomass. Application of the delta technique to summary statistics can significantly underestimate uncertainty as some sources of uncertainty cannot be quantified from the available information. We discuss limitations and problems with the Monte Carlo technique for quantifying uncertainty in an AFCB.