Productivity of Northern Eurasian forests: Analysis of uncertainties

Indicators of biological productivity of forests (live and dead biomass, net primary production, net and grossgrowth) are crucial for both assessment of the impacts of terrestrial ecosystems on major biogeochemical cyclesand practice of sustainable forest management. However, different information and the diversity of methods usedin the assessments of forests productivity cause substantial variation in reported estimates. The paper containsa systems analysis of the existing methods, their uncertainties, and a description of available information. Withrespect to Northern Eurasian forests, the major reasons for uncertainties could be categorized as following: (1)significant biases that are inherent in a number of important sources of available information (e.g., forest inventorydata, results of measurements of some indicators in situ); (2) inadequacy and oversimplification of models ofdifferent types (empirical aggregations, process-based models); (3) lack of data for some regions; and (4) upscalingprocedure of “point” observations.Based on as comprehensive as possible adherence to the principles of systems analysis, we made an attemptto provide a reanalysis of indicators of forests productivity of Russia aiming at obtaining the results for whichuncertainties could be estimated in a reliable and transparent way. Within a landscape-ecosystem approach it hasrequired (1) development of an expert system for refinement of initial data including elimination of recognizedbiases; (2) delineation of ecological regions based on gradients of major indicators of productivity; (3) transitionto multidimensional models (e.g., for calculation of spatially distributed biomass expansion factors); (4) use ofprocess-based elements in empirical models; and (5) development of some approaches which presumably do nothave recognized biases. However, taking into account the fuzzy character of the problem, the above approach (aswell as any other individually used method) is not able to recognize structural uncertainties. In order to assess those,a special statistical procedure for harmonizing the multiple constraints of the estimates obtained by independentmethods (landscape-ecosystem approach; flux measurements; process-based vegetation models; inverse modeling)was used to estimate uncertainty of the final results. Application of the above methodology resulted in a reliableassessment of major indicators of productivity. For instance, live biomass at the country’s level is estimated withuncertainty of 4-6%, net primary production – 7-10% (confidential interval 0.9). It was recognized the tendencyof increasing productivity of Russian forests during the last four decades at level of 0.5 0.2% year