Spatial partitioning of biomass and diversity in a lowland Bolivian forest: Linking field and remote sensing measurements

Large-scale inventories of forest biomass and structure are necessary for both understanding carbon dynamics and conserving biodiversity. High-resolution satellite imagery is starting to enable structural analysis of tropical forests over large areas, but we lack an understanding of how tropical forest biomass links to remote sensing. We quantified the spatial distribution of biomass and tree species diversity over 4 ha in a Bolivian lowland moist tropical forest, and then linked our field measurements to high-resolution Quickbird satellite imagery. Our field measurements showed that emergent and canopy dominant trees, being those directly visible from nadir remote sensors, comprised the highest diversity of tree species, represented 86% of all tree species found in our study plots, and contained the majority of forest biomass. Emergent trees obscured 1–15 trees with trunk diameters (at 1.3 m, diameter at breast height (DBH)) ≥20 cm, thus hiding 30–50% of forest biomass from nadir viewing. Allometric equations were developed to link remotely visible crown features to stand parameters, showing that the maximum tree crown length explains 50–70% of the individual tree biomass. We then developed correction equations to derive aboveground forest biomass, basal area, and tree density from tree crowns visible to nadir satellites. We applied an automated tree crown delineation procedure to a high-resolution panchromatic Quickbird image of our study area, which showed promise for identification of forest biomass at community scales, but which also highlighted the difficulties of remotely sensing forest structure at the individual tree level.     

Estimation of stand attributes in <Emphasis Type="Italic">Cryptomeria japonica</Emphasis> and <Emphasis Type="Italic">Chamaecyparis obtusa</Emphasis> stands using QuickBird panchromatic data

This study aims to estimate stand density and stand volume in Cryptomeria japonica and Chamaecyparis obtusa stands from high-resolution satellite data and verify the reliability and uncertainty of the data. Sixty circular sample plots of 0.04 ha each were established. Their stand densities were estimated from the number of tree crowns derived from high-resolution satellite data using the watershed method. Stand densities derived from field surveys in the sample plots were compared with those obtained from high-resolution satellite data by stand age class. As a result, there was a positive correlation between them for sample plots of 41 years of age and over (R = 0.82); however, there was no correlation between them for sample plots of 40 years and under. Individual diameters at breast height (DBH) were estimated from crown areas obtained from high-resolution satellite data for the two species. Using the estimated DBH, individual tree heights were predicted from the height–diameter curves. Stand volumes were estimated from the sum of individual volumes, which were derived from volume formulas having two variables, i.e., DBH and height. Stand volumes derived from the field survey were compared with those obtained from high-resolution satellite data. The correlation coefficient between them for stands of 41 years of age and over was 0.78.     

Allometric equations for aboveground biomass estimation by size class for Pinus brutia Ten. trees growing in North and South Aegean Islands, Greece

Empirical allometric equations relating biomass of aboveground components to dendrometric variables for Pinus brutia Ten. trees are derived in this paper. They are based on data collected from Lesvos (North Aegean Sea) and Crete (South Aegean Sea) Islands. Comparisons to published equations for the same species growing in northwestern and southeastern Turkey, for Pinus nigra A. growing in Turkey and Pinus halepensis Mill. found in Western Aegean (island of Evia), are also presented. The biomass of branches from destructively sampled trees (twelve in Crete and six in Lesvos) was divided into four size classes (0?C0.63 cm, 0.64?C2.5 cm, 2.51?C7.61 cm, and 7.62?C22.8 cm). Tree crown biomass was calculated as the sum of the biomass in the four classes plus the fraction of stem above crown base. Over bark stem biomass was estimated through bole volume conversion based on wood density. The results showed clearly that, for a given diameter, the Cretan trees had more crown biomass and a higher share of small branches than trees on Lesvos, probably due to differences in environment and stand structure. Comparisons to published diameter versus crown biomass equations reveal a lower crown biomass for Turkish sites of Calabrian pine and Aleppo pine on Evia Island, while only Turkish Black pine seems to be comparable to the Calabrian pine on Crete. The derived allometries can be used for landscape fire behavior modeling, for ecophysiological studies and for the Kyoto protocol requirements of carbon changes in Pinus brutia Ten. forests located in northern and southern Greek sites.     

Aboveground biomass and carbon stock in the largest sacred grove of Manipur,Northeast India

Aboveground biomass and carbon stock in the largest sacred grove of Manipur was estimated for trees with diameter [10 cm at 1.37 m height.The aboveground biomass,carbon stock,tree density and basal area of the sacred grove ranged from 962.94 to 1130.79 Mg ha~(-1),481.47 to 565.40 Mg ha~(-1) C,1240 to 1320 stem ha~(-1) and79.43 to 90.64 m~2 ha~(-1),respectively.Trees in diameter class of 30–40 cm contributed the highest proportion of aboveground biomass(22.50–33.73%).The aboveground biomass and carbon stock in research area were higher than reported for many tropical and temperate forests,suggesting a role of spiritual forest conservation for carbon sink management.     

Developing individual tree-based models for estimating aboveground biomass of five key coniferous species in China

Estimating individual tree biomass is critical to forest carbon accounting and ecosystem service modeling. In this study, we developed one- (tree diameter only) and two-variable (tree diameter and height) biomass equations, biomass conversion factor (BCF) models, and an integrated simultaneous equation system (ISES) to estimate the aboveground biomass for five conifer species in China, i.e., Cunninghamia lanceolata (Lamb.) Hook., Pinus massoniana Lamb., P. yunnanensis Faranch, P. tabulaeformis Carr. and P. elliottii Engelm., based on the field measurement data of aboveground biomass and stem volumes from 1055 destructive sample trees across the country. We found that all three methods, including the one- and two-variable equations, could adequately estimate aboveground biomass with a mean prediction error less than 5%, except for Pinus yunnanensis which yielded an error of about 6%. The BCF method was slightly poorer than the biomass equation and the ISES methods. The average coefficients of determination (R ²) were 0.944, 0.938 and 0.943 and the mean prediction errors were 4.26, 4.49 and 4.29% for the biomass equation method, the BCF method and the ISES method, respectively. The ISES method was the best approach for estimating aboveground biomass, which not only had high accuracy but also could estimate stocking volumes simultaneously that was compatible with aboveground biomass. In addition, we found that it is possible to develop a species-invariant one-variable allometric model for estimating aboveground biomass of all the five coniferous species. The model had an exponent parameter of 7/3 and the intercept parameter a ₀ could be estimated indirectly from stem basic density (a ₀ = 0.294 ρ).     

Crown area allometries for estimation of aboveground tree biomass in agricultural landscapes of western Kenya

Classical allometries determine biomass from measurements of diameter at breast height or volume. Neither of these measurements is currently possible to be derived directly from remote sensing. As biomass estimates at larger scales require remotely sensed data, new allometric relations are required using crown area and/or tree height as predictor of biomass, which can both be derived from remote sensing. Allometric equations were developed from 72 trees semi-randomly selected for destructive sampling in three 100?km² sentry sites in western Kenya. The equations developed fit the data well with about 85?% of the observed variation in aboveground biomass explained by crown area. Addition of height and wood density as second predictor variables improved model fit by 6 and 2?% and lowered the relative error by 7 and 2?%, respectively. The equation with crown area in combination with height and wood density estimated representative aboveground biomass carbon to be about 20.8?±?0.02?t?C?ha^?1; which is about 19?% more than the amount estimated using an allometry with diameter at breast height as predictor. These results form the basis for a new generation of allometries using crown area as a predictor of aboveground biomass in agricultural landscapes. Biomass predictions using crown area should be supported by height and wood density and the application of crown area equations for remote sensing based up-scaling should consider crown interactions with competing or coexisting neighboring trees.     

Variation in wood density and carbon content of tropical plantation tree species from Ghana

Most research on carbon content of trees has focused on temperate species, with less information existing for tropical trees and very little for tropical plantations. This study investigated factors affecting the carbon content of nineteen tropical plantation tree species of ages seven to twelve and compared carbon content of Khaya species from two ecozones in Ghana. For all sample trees, volume of the main stem, wood density, wood carbon (C) concentration and C content were determined. Estimated stem volume for the 12-year-old trees varied widely among species, from 0.01 to 1.04 m³, with main stem C content ranging from 3 to 205 kg. Wood density among species varied from 0.27 to 0.76 g cm^?3, with faster growing species exhibiting lower density. Significant differences in wood density also occurred with position along the main stem. Carbon concentration also differed among tree species, ranging from 458 to 498 g kg^?1. Differences among species in main stem C content largely reflected differences among species in estimated main stem volume, with values modified somewhat by wood density and C concentration. The use of species-specific wood density values was more important for ensuring accurate conversion of estimated stem volumes to C content than was the use of species-specific C concentrations. Significant differences in wood density did exist between Khaya species from the wet and moist semi-deciduous ecozones, suggesting climatic and site factors may also need to be considered. Wood densities for these plantation grown trees were lower than literature values reported for the same species in natural forests, suggesting that the application of data derived from natural forests could result in overestimation of the biomass and C content of trees of the same species grown in plantations.     

Forest Type,Diversity and Biomass Estimation in Tropical Forests of Western Ghat of Maharashtra Using Geospatial Techniques

Tropical forests are the world’s largest terrestrial storehouses of carbon and are recognized as rich, diverse and highly productive ecosystems. The present study was conducted to characterize the land use, diversity and biomass of tropical forest in Western Ghat of Maharashtra State in India through satellite remote sensing and GIS. The study has been designed and implemented to promote analysis on Western Ghat biodiversity resources including trees, shrubs and herbs based on inventorying, monitoring and mapping. Field measured biomass is integrated with spectral responses of various bands and indices of the Landsat TM satellite image for estimation of above-ground biomass in a 36,046 km² area of relic forest in the Central Western Ghat. The above-ground biomass from field-based inventory varied from 30.2 to 151.1 ton/ha in moist deciduous forest, 9.2–99.1 ton/ha in dry deciduous forest, 42.1–158.6 ton/ha in semi-evergreen forest, and 160.9–271 ton/ha in evergreen forest. The total above-ground biomass of the study area was estimated to be 95.2 M tons. A regression equation between field above-ground biomass and a Normalized Difference Vegetation Index was used for spectral modeling to estimate and prepare the above-ground biomass map in the region. A total 120 plant species in 81 genera and 31 families were identified in the study area. This study emphasizes the importance of relic forests for their biodiversity, carbon sequestration and total biomass.     

Estimating coarse root biomass with ground penetrating radar in a tree-based intercropping system

Conventional measurements of tree root biomass in tree-based intercropping (TBI) systems can be inadequate in capturing the heterogeneity of rooting patterns or can be highly destructive and non-repeatable. In this study, we estimated coarse root biomass using ground penetrating radar (GPR) of 25-year-old trees inclusive of five species (Populus deltoides × nigra clone DN-177, Juglans nigra L., Quercus rubra L., Picea abies L. Karst, and Thuja occidentalis L.) at a TBI site in Southern Ontario, Canada. Subsurface images generated by GPR were collected in grids (4.5 × 4.5 m) centred on tree stems. The predictive relationship developed between GPR signal response and root biomass was corrected for species effects prior to tree-scale estimates of belowground biomass. Accuracy of the tree-scale estimates was assessed by comparing coarse root biomass measured from complete excavations of the corresponding tree. The mean coarse root biomass estimated from GPR analysis was 54.1 ± 8.7 kg tree^?1 (mean ± S.E.; n = 12), within 1 % of the mean coarse root biomass measured from excavation. Overall there was a root mean square error of 14.4 kg between measured and estimated biomass with no detectable bias despite variable conditions within the in-field and multi-species study. Root system C storage by species, calculated with species-specific root carbon concentrations, is estimated at 5.4 ± 0.7–34.8 ± 6.9 kg C tree^?1 at this site. GPR is an effective tool for non-destructively predicting coarse root biomass in multi-species environments such as temperate TBI systems.     

Allometric models for estimating aboveground biomass of shade trees and coffee bushes grown together

Allometric models for dominant shade tree species and coffee plants (Coffea arabica) were developed for coffee agroforestry systems in Matagalpa, Nicaragua. The studied shade tree species were Cordia alliodora, Juglans olanchana, Inga tonduzzi and I. punctata. The models predict aboveground biomass based on diameter at breast height (for trees), and the stem diameter at a height of 15 cm and plant height (for coffee plants). In addition, the specific gravity of the studied species was determined.The total aboveground biomass of the shade trees varied between 3.5 and 386 kg per tree, and between 0.005 and 2.8 kg per plant for coffee. The aboveground biomass components (foliage, branch, and stem) are closely related with diameter at breast height (r > 0.75). The best-fit models for aboveground biomass of the shade trees were logarithmic, with adjusted R ² between 0.71 and 0.97. In coffee plants, a high correlation was found (r = 0.84) with the stem diameter at 15 cm height, and the best-fit model was logarithmic, as well. The mean specific gravity was 0.52 (± 0.11) for trees and 0.82 (± 0.06) for coffee plants.     

Volume equations and biomass estimates for three species in tropicalmoist forest in the Orientale province,Democratic Republic of Congo

Volume equations predict the volume of the stem of a tree from dendrometrical characteristics that are easy to measure, such as diameter and/or height. These equations can serve as a surrogate for biomass equations, by converting the stem volume to stem biomass, and then expanding it to the total aboveground biomass. This is especially important for Central Africa where biomass equations are scarce, whereas volume equations are common. We measured the stem volume of 459 trees in the Yoko forest, Orientale province, Democratic Republic of Congo. These trees belonged to three species: Gilbertiodendron dewevrei (limbali), Guarea thompsonii (bossé foncé) and Scorodophloeus zenkeri (divida). Species-specific volume equations were fitted using these data, and biomass estimates were derived from these volume equations. The fitted volume equations were consistent with other location-specific volume equations for the same species. The biomass estimates derived from the fitted volume equations were also found to be consistent with multispecies pantropical biomass equations.     

Classifying tree species in a northern mixed forest using high-resolution IKONOS data

The high-spatial-resolution IKONOS satellite is now operating as a resource and disaster monitor, after a successful launch in September 1999. The ground resolution of the IKONOS panchromatic band is about 1m, the greatest of any satellite. The objectives of this study were to verify the extent to which high-resolution IKONOS data can be used to classify tree species. A field survey and image analysis study used IKONOS imagery to classify 21 species in mixed stands of deciduous and conifer species with the following results: (1) The panchromatic and multi-spectral bands 4, 3, and 2 were useful for classifying tree species owing to the great difference in the reflectance values between tree species. (2) Some groups, for which there were significant differences among species, were identified using Tukeys multiple comparison test; conifers and some broadleaved trees were identified correctly more often than other species. (3) A random selection of validation pixels showed that the overall classification accuracy was 62%. The classification accuracy of broadleaved trees was a little low, ranging from 40% to 63%, while that of conifers exceeded 70%. (4) The overall accuracy of the classification at the genus level improved by 4% more than the species level. The misclassification of broadleaved trees was due to the similar spectral characteristics of species in the same genus.     

Applicability of Fitted and Published Biomass Equations for Larix Species in Northeastern China

ABSTRACT

This study reviewed published biomass equations for Larix species in the literature and developed additive biomass equations (by nonlinear seemingly unrelated regression known as NSUR) and independent equations, respectively, based on DBH-only and DBH-H variables with the biomass data of 150 trees sampled in northeastern China. The applicability of fitted and published equations was comprehensively assessed with respect to Larix species, their provinces and origins when applied in northeastern China. The results showed that equations derived from the local study area did not always perform better than the published biomass equations in the literature. Tree-level equations performed slightly broader than stand-level equations. Nonlinear regression could provide higher applicability due to correction factors in the linear regression. Adding tree height as the second variable improved the applicability of stem and aboveground published equations. The applicability of original published equations was better for northeastern China for sites of similar latitude. When using published biomass equations, care should be taken to assess the uncertainty and applicability of biomass equations, which is important for the sustainable management of forested resources. Published information on biomass equations is especially necessary for forestry organizations that do not have the opportunity to develop their own equations.     

Comparison of satellite images with different spatial resolutions to estimate stand structural diversity in urban forests

The structural diversity in urban forests is highly important to protect biodiversity. In particular, fruit trees and bush species, cavity-bearing trees and coarse, woody debris provide habitats for animals to feed, nest and hide.Improper silvicultural practices, intensive recreational use and illegal harvesting lead to a decline in the structural diversity in forests within larger metropolitan cities. It is important to monitor the structural diversity at definite time intervals using effective technologies with a view to instituting the necessary conservation measures. The use of satellite images seems to be appropriate to this end. Here we aimed to identify the associations between the textural features derived from the satellite images with different spatial resolutions and the structural diversity indices in urban forest stands(Shannon–Wiener index, complexity index, dominance index and density of wildlife trees).Rapid Eye images with a spatial resolution of 5 m 9 5 m,ASTER images with a spatial resolution of 15 m 9 15 m and Landsat-8 ETM satellite images with a spatial resolution of 30 m 9 30 m were used in this study. The firstorder(standard deviation of gray levels) and second order(GLCM entropy, GLCM contrast and GLCM correlation)textural features were calculated from the satellite images.When associations between textural features in the images and the structural diversity indices were assessed using the Pearson correlation coefficient, very high associations were found between the image textural features and the diversity indices. The highest association was found between the standard deviation of gray levels(SDGLRAP) derived from RVIRAPof Rapid Eye image and the Shannon–Wiener index(Hh) calculated on the basis of tree height(R2= 0.64). The findings revealed that Rapid Eye satellite images with a spatial resolution of 5 m 9 5 m are most suitable for estimating the structural diversity in urban forests.     

Comparison of allometric equations and biomass expansion factors for six evergreen broad-leaved trees in subtropical forests in southern Korea

This study was conducted to compare the allometric equations and biomass expansion factors (BEFs) of six dominant evergreen broad-leaved trees (Camellia japonica L, Castanopsis sieboldii Hatus, Quercus acuta Thunb, Q. glauca Thunb, Machilus thunbergii S. et Z., and Neolitsea sericea Koidz) in subtropical forests. A total of 86 trees were destructively sampled to quantify the aboveground biomass of each tree component (i.e., leaves, branches, and stem). Species-specific or generalized allometric equations and species-dependent BEFs were developed for each tree component of the six broad-leaved forest trees. Species-specific allometric equations were significant (P < 0.05), with the diameter at breast height (DBH) accounting for 68–99% of the variation, whereas generalized allometric equations explained 64–96% of the variation. The values of stem density ranged broadly from 0.49 g cm^?3 for C. sieboldii to 0.79 g cm^?3 for Q. glauca, with a mean value of 0.68 g cm^?3. The BEFs were significantly (P < 0.05) lower for C. sieboldii (1.25) than for M. thunbergii (2.02). Stem density and aboveground BEFs had a significant negative relationship with tree ages. The results indicate that species-specific allometric equations and species-dependent BEFs are applicable for obtaining accurate biomass estimates of subtropical evergreen broad-leaved forests.     

Integrated individual tree biomass simultaneous equations for two larch species in northeastern and northern China

Forest biomass estimation at large scale has become an important topic in the background of facing global climate change, and it is fundamental to develop individual tree biomass equations suitable for large-scale estimation. Based on the measured data of biomass components and stem volume from 100 sample trees of two larch species (Larix gmelinii and L. principis-rupprechtii) in northeastern and northern China, an integrated equation system including individual tree biomass equations, stem volume equation and height–diameter regression model were constructed using the dummy variable model and error-in-variable simultaneous equations. In the system, all the parameters of equations were estimated simultaneously, so that the aboveground biomass equation was compatible to stem volume equation and biomass conversion factor (B_CF) function; the belowground biomass equation was compatible to root-to-shoot ratio (R_SR) function; and stem wood, stem bark, branch and foliage biomass equations were additive to aboveground biomass equation. In addition, the system also ensured the compatibility between one- and two-variable models. The results showed that: (1) whether aboveground biomass equations or belowground biomass equations and stem volume equations, the estimates for larch in northeastern China were greater than those in northern China; (2) B_CF of a larch tree decreased with the growing diameter while R_SR increased with the growing diameter; (3) the proportion of stem wood biomass to aboveground biomass increased with the growing diameter while those of stem bark, branch, and foliage biomass decreased.     

Biomass and nutrient allocation to aboveground components in fertilized <Emphasis Type="Italic">Eucalyptus saligna</Emphasis> and <Emphasis Type="Italic">E. urograndis</Emphasis> plantations

The objective of this study was to evaluate biomass allocation and nutrient pools in aboveground biomass components in 18-month-old plantations of Eucalyptus saligna and E. urophylla × E. grandis (i.e. E. urograndis) in Brazil. The plantations were established by pulp companies in a large area comprising three soil types (Acrisols, Vertisols and Leptosols) in the grassland biome in southern Brazil, and an operational regime of planting and maintenance fertilization was used to ensure full availability of nutrients. Vertisols showed the highest availability of soil nutrients, and the P and Ca concentrations in aboveground biomass were also highest in this type of soil. The nutritional status of both species indicates great consumption of nutrients, particularly of P, K and Ca. At this early age, canopy biomass components still made the largest relative contribution, although debarked stem biomass already accounted for 41.5% and 37.4 of total aboveground biomass in E. saligna, and E. urograndis, respectively. Nutrient concentrations in biomass components were similar across species. For all macronutrients, except Ca and Mg, the concentration gradient followed the order wood < bark < branches < leaves. For all micronutrients, except Cu, the concentration gradient followed the order wood < branches ≈ bark < leaves. At the plantation stage studied, i.e. before canopy closure, the importance of the components as nutrient pools followed the order leaves > branches > wood > bark. The branches hold the majority of Ca reserves in biomass and are a very important pool of Mg, K, P and B. The bark makes a small contribution to total biomass, but stores a similar amount of Ca as leaves, being the second major pool after the branches. Comparison of the nutrients supplied by fertilization and the amounts stored in soil and aboveground indicates that the operational dose should be adjusted to each type of soil after further experimental fertilizer trials, as the supply of N and P appears to be too high, particularly for Vertisols. This is leading to the immobilization of P in biomass components that are not of importance in the biological or biochemical nutrient cycles, thus increasing the risk of larger exports of P during biomass removal.     

Pilot study on the effects of elevated air temperature and CO<Subscript>2</Subscript> on artificially defoliated silver birch saplings

The impacts of elevated temperature and CO₂ on young silver birch (Betula pendula Roth) saplings after 0, 25, 50 or 75% artificial defoliation were assessed by measuring plant height and dry mass of aboveground compartments and roots and various morphological and physiological variables. Defoliation either increased or decreased plant growth depending on the severity of damage and the climatic treatment. At 21 °C and 400 mg L^?1 CO₂, defoliated plants were not able to compensate for the lost foliage, but growth compensation and adaptation to the changed conditions were greater; growth of young defoliated silver birch saplings increased, which led to increased height and a tendency to enhance final aboveground and root biomass and leaf nitrogen and carbon content compared to the nondefoliated controls. Nevertheless, the short-term effect of the different climatic conditions did not result in a significant overgrowth of defoliated plants. A slight increase in temperature and CO₂ were the most acceptable conditions for defoliated plants; however, a 4 °C increase with correspondingly higher CO₂ was more stressful as shown by less growth in height and biomass allocation to leaves, stems and roots. The findings from the pilot experiment are more applicable to young birch trees, but stress on young trees may be reflected in future tree growth.     

Airborne laser scanning in forest management: Individual tree identification and laser pulse penetration in a stand with different levels of thinning

This study examined the ability of an airborne laser scanner to identify individual trees in the canopy of a Chamaecyparis obtusa stand and investigated the relationship between the penetration rate of the laser pulses and stand attributes under different canopy conditions caused by different levels of thinning. Individual tree crowns were identified from a digital canopy model (DCM) derived from airborne laser scanner data by the watershed segmentation method. The identification rate of individual trees in blocks with heavy thinning (ratio of the basal area of the felled trees to the total basal area, hereinafter thinning ratio of the basal area, 38.0%), moderate thinning (30.4%), and no thinning was 95.3%, 89.2%, and 60.0%, respectively. Individual tree heights were estimated from the DCM values by local maximum filtering within identified individual crowns. Tree height in the three blocks was estimated with a root-mean-square error of 0.95, 0.65, and 0.68 m, respectively. Tree heights determined in a field survey were regressed against those estimated from the DCM, yielding coefficients of determination (r²) of 0.71, 0.87, and 0.85, respectively, for the blocks with heavy thinning, moderate thinning, and no thinning, respectively, and 0.86 overall. The respective penetration rates of the laser pulses through the canopy to the ground were 50.6%, 43.1%, and 9.2%. Regression of the laser pulse penetration rate against the thinning ratio of the basal area and against the total basal area of the remaining trees in 25 quadrats established in the blocks, yielded r² values of 0.89 and 0.74, respectively.     

How much carbon can the Siberian boreal taiga store: a case study of partitioning among the above-ground and soil pools

In the context of global carbon cycle management, accurate knowledge of carbon content in forests is a relevant issue in contemporary forest ecology. We measured the above-ground and soil carbon pools in the darkconiferous boreal taiga. We compared measured carbon pools to those calculated from the forest inventory records containing volume stock and species composition data. The inventory data heavily underestimated the pools in the study area(Stolby State Nature Reserve, central Krasnoyarsk Territory, Russian Federation). The carbon pool estimated from the forest inventory data varied from 25(t ha-1)(low-density stands) to 73(t ha-1)(highly stocked stands). Our estimates ranged from 59(t ha-1)(lowdensity stands) to 147(t ha-1)(highly stocked stands). Our values included living trees, standing deadwood, living cover, brushwood and litter. We found that the proportion of biomass carbon(living trees): soil carbon varied from99:1 to 8:2 for fully stocked and low-density forest stands,respectively. This contradicts the common understanding that the biomass in the boreal forests represents only16–20 % of the total carbon pool, with the balance being the soil carbon pool.