The paper presents new estimates of live biomass (phytomass) and net primary production (NPP) of Russian forests for 1993 and 2003. These indicators are estimated based on forest inventory data and a specially developed semi-empirical modeling system. The latter contains regional models of growth by major forest forming species, multi-dimensional models of phytomass and models of biological production. It is shown that the fractional structure of forest phytomass substantially differs from previous estimates that indicated significant temporal trends of the share of aboveground wood (AGW), green part (GP) and belowground (BG) phytomass. The total forest NPP (of 307 g C m^-2yr^-1 for 2003) is substantially higher than previously reported. These changes may be attributed to climatic change which was dramatic over the last four decades, particularly in Asian Russia.

The Carbon Cycle Data Assimilation System (CCDAS) infers values of the parameters controlling the function of a process model of the terrestrial biosphere using various observations. An obvious restriction of this approach is the limitation by the dynamics of the underlying process model. Careful study of the model-data mismatch and analysis of residuals can alert us to the presence of systematic errors which then candidate processes to extend the terrestrial biosphere model and the assimilation system. In a previous study, Rayner et al. [2005] noticed systematic underestimate of carbon release events in the tropics. The most likely explanation for this was the absence of any model of biomass burning in the biosphere model used in that study. Here, we extend CCDAS to infer the spatial and temporal patterns of biomass burning in the period 1979-1999. In a first attempt we include some flux components to account for missing processes. This so-called weak constraint form avoids biasing the inferences since the underlying model is no longer forced to match data without necessary processes. Also the magnitudes of the extra inferred fluxes quantify the missing processes.

Terrestrial carbon fluxes are an important factor for the studies of global warming. This study focuses on estimating a fluctuation of the terrestrial carbon fluxes in the Tokai region, Japan. The local biosphere model used calculates carbon, water, and heat fluxes, and required some climate and vegetation parameters as inputs. The model was operated in 2000-2004 using meteorological data and MODIS data products. We estimated spatial distributions in heat and carbon fluxes at spatial resolution of 1*1 km, and validated an adaptability of the model using measured data at the Takayama flux-site. As a result, estimated GPP and heat fluxes had a good relationship to measured data. We can precisely check on the accuracy of the model to estimate the spatial and temporal patterns of the terrestrial carbon fluxes.

Three techniques for separation of total CO₂ efflux from soil into root and microbial respiration were compared: component integration, root exclusion and pulse labelling of shoots in ¹⁴CO₂ atmosphere. The contribution of rhizosphere to total CO₂ efflux from soil varied from 19 to 49% (including root respiration amounted to 9-32%). The share of non-rhizosphere respiration was 51-80%. The results obtained by component integration and root exclusion techniques were similar. Rhizosphere respiration estimated by pulse labelling were less as estimated by two non-isotopic methods.

Amazonian forests play an important and complex role in the global carbon cycle, contributing substantially to increases (via land use change emissions) and possibly to net sequestration (in intact forests) of atmospheric CO₂. Predicting these processes of net carbon uptake and release depends crucially on understanding ecosystem response to both seasonal and interannual variations. However, prominent ecosystem modeling studies of the Amazonian carbon cycle [Tian et al., 1998; Botta 2002] appear to make seasonal predictions (wet-season carbon uptake and dry-season loss) at odds with both some site-specific observations (which show the opposite pattern, Saleska et al., [2003]) and basin-wide satellite observations (which imply large-scale increases in the activity of photosynthetic vegetation during the dry season, Huete et al., [2005]).

Better quantification of atmosphere-ecosystem exchange of the isotopologues of CO₂ could substantially improve our ability to probe under­lying physiological and ecological mechanisms controlling ecosystem carbon exchange, but the ability to make long-term continuous measurements of the isotopic composition of exchange fluxes has been limited by measure­ment difficulties. Quantum cascade (QC) lasers are a new generation of infrared light sources that offer increased stability and power for absorption spectroscopy applications (including the measurement of isotope ratios in atmospheric CO₂) and promise substantial improvements over existing instruments: smaller size, increased robustness, and most significantly for remote or long-term field deployments, no need for cryogenic cooling of laser or detectors. 

Forestry and Forest Products Research Institute erected a CO₂ flux observation tower at a Japanese beech forest, and have measured CO₂ flux with closed-pass eddy covariance method for 5 years. During the observation period, 2003 was the most CO₂ absorbed year, and the amount was 1.9 times larger than 2004, which was the least CO₂ absorbed year. To investigate the cause of the smaller CO₂ absorption in 2004, we referred some meteorological factors in 2003 and 2004.  Solar radiation (during green-leaved season) was larger in 2004 than 2003, in contradiction to CO₂ absorption.  On the other, air temperature was higher in 2004 than 2003 (both in green-leaved and defoliated season). We assumed that larger respiration in 2004 effected the depression of annual CO₂ absorption.  At our research site, annual mean air temperature in 2004 was 0.95 degree centigrade warmer than 2003.  The result of this study suggests the tendency that warmer climate may cause less CO₂ absorption in this Japanese beech forest.

Year-to-year variations in summer drawdown of northern hemisphere atmospheric carbon dioxide (CO₂) are compared with corresponding year-to-year variations in sea- level pressure (SLP), surface air temperature and the productivity of land vegetation as inferred from the satellite-derived normalized difference vegetation index (NDVI). Annual values of CO₂ drawdown for the years 1980-2000 are estimated from smoothed time series derived directly from individual flask samples at the 9 northern hemisphere monitoring stations with the most continuous records. The leading principal component of the 9 standardized drawdown time series, in which all stations exhibit positive loadings, is used to represent the hemispheric signal in the CO₂ drawdown. Linear regression analysis is used to infer the spatial patterns of anomalies in sea level pressure, surface air temperature and the NDVI observed during various seasons of years in which the drawdown is anomalously strong.

Annual changes in soil carbon stock are considered of the abandoned managed agricultural lands that were under natural regrowth over the territory of Russia within the period 1990-2002. Total area of abandoned agricultural land is 21,6 millions ha. The projections of changes in the carbon stock have been made for the period from present to 2010. The ROTHC model was employed in the investigation of carbon dynamics in soils. The territory of Russia was subdivided into 40 regions. The average basic soil and climatic parameters, as well as the annual input of organic matter into soils due to natural succession were estimated for each region. Average annual net-emission over the territory of abandoned lands was 2,1 ± 1,8 Tg C/yr in 1990-1999. CO₂ removal from the atmosphere by soils was 5,2 ± 2,8 Tg C/yr on average in 2000-2002. A total increase in carbon stock of the abandoned lands over the country can be as high as 153 Tg C (that corresponds to the removal of 561 Tg of CO₂ from the atmosphere) in 2010. Central regions of the European part of Russia, south of East Siberia and the Far East will have the highest intensity of carbon sequestration.