Biomass Conversion And Expansion Factors Research Articles

Effects of Biotic and Abiotic Factors on Biomass Conversion and Expansion Factors of Natural White Birch Forest (Betula platyphylla Suk.) in Northeast China

Biomass conversion and expansion factors (BCEFs) are widely utilized in national and regional biomass estimates and greenhouse gas reporting, as they can be used to directly transform the stocking volume into biomass. In this study, the power function was used as the basic model form with biotic variables, and abiotic variables were considered to improve the fitting results. Then, the random effects parameters were also introduced into the models to describe the variation of BCEFs among different forest management units. Random sampling strategies were applied to calibrate the random effects. The results showed that the stocking volume exhibited a negative proportional relationship in the stem BCEF (BCEFst), the root BCEF (BCEFro) and the total tree BCEF (BCEFto) models, and the quadratic mean diameter exhibited a positive proportional relationship in the branch BCEF (BCEFbr) and the foliage BCEF (BCEFfol) models. In addition, the fitting effect of generalized models with abiotic predictors was superior to that of the basic models. Considering the effects of abiotic variables on the BCEFs of each component, the results showed that BCEFst and BCEFto decreased as the mean annual precipitation increased; BCEFbr increased as the annual temperature increased; BCEFfol gradually decreased as the elevation increased; and BCEFro first increased with increasing mean annual temperature and then declined. In conclusion, abiotic factors explained the variation in BCEFs for the biomass components of the natural white birch forest. Although the fitting effect of generalized models with abiotic predictors was superior to that of the basic models, the mixed-effects model was preferable for modeling the BCEFs of each component. In addition, the prediction precision of the mixed-effects models enhanced gradually with increasing sample size, and the selection of eight plots for calibration and prediction based on the mixed-effects model was the best sampling strategy in this study of a natural white birch forest.

Stand-level biomass estimation for Korean pine plantations based on four additive methods in Heilongjiang province, northeast China

Background: Korean pine ( Pinus koraiensis Siebold & Zucc.) is one of the primary plantation conifer species of economic and ecological importance in northeast China. Forest biomass estimation in the broader landscape has been receiving attention from researchers and forest managers. The development of forest stand biomass models is regarded an effective method to estimate forest biomass at large scales. This study was carried out for developing stand-level biomass models for Korean pine plantations. Four additive methods were compared: Aggregation 1, Aggregation 2, Adjustment, and Disaggregation. All the stand biomass additive modeling systems (i.e., total, root, stem, branch, and leaf) included both stand volume and biomass conversion and expansion factors (BCEFs) as predictors. Results: The predictive performance of the four additive methods and Constant BCEFs were ranked as follows: Aggregation 1 > Disaggregation > Adjustment > Aggregation 2 > Constant BCEFs. The prediction accuracy of the four additive methods was not consistent across the stand volume intervals. Conclusion: The model based on the Aggregation 1 method was recommended for predicting stand biomass. However, different additive method should be selected according to the stand volume intervals of the Korean pine plantations.

Temporal and Spatial Change of Carbon Storage in Alara Forest Planning Unit

Aim of study: Land use and carbon stock changes of Alara Forest Planning Unit (FPU) between the years of 1997 and 2017 were investigated.
 Area of study: Alara Forest Planning Unit (FPU) of Alanya Forest Enterprise (FE) within the boundaries of Antalya province, southwest Turkey.
 Material and methods: Data obtained from the forest management plans for the periods of 1997-2006, 2008-2017 and 2018-2037 were used in the study. Biomass conversion and expansion factors (BCEF), root to shoot ratios (R) and carbon factors (CF) were used for carbon stock estimation.
 Main results: Total forest area of the Alara FPU decreased from 7497 ha to 7344 ha, while total carbon stock of the forest lands increased by 12.7%, from 1997 to 2017.
 Highlights: Despite the reduction of total forest area from 1997 to 2017, carbon stocks of all biomass pools in forest ecosystem raised with the increase of productive forest lands and growing stock.

Biomass and Volume Modeling along with Carbon Concentration Variations of Short-Rotation Poplar Plantations

Short-rotation forestry is of interest to provide biomass for bioenergy and act as a carbon sink to mitigate global warming. The Poplar tree (Populus × xiaohei) is a fast-growing and high-yielding tree species in Northeast China. In this study, a total of 128 Populus × xiaohei trees from the Songnen Plain, Heilongjiang Province, Northeastern China, were harvested. Several available independent variables, such as tree diameter at breast height (D), tree’s total height (H), crown width (CW), and crown length (CL), were differently combined to develop three additive biomass model systems and eight stem volume models for Populus × xiaohei tree. Variance explained within the three additive biomass model systems ranged from 83% to 98%, which was lowest for the foliage models, and highest for the stem biomass models. Similar findings were found in the stem volume models, in which the models explained more than 94% of the variance. The additional predictors, such as H, CL, or CW, evidently enhanced the model fitting and performance for the total and components biomass along with the stem volume models. Furthermore, the biomass conversion and expansion factors (BCEFs) of the root (118.2 kg/m3), stem (380.2 kg/m3), branch (90.7 kg/m3), and foliage (31.2 kg/m3) were also calculated. The carbon concentrations of Populus × xiaohei in root, stem, branch, and foliage components were 45.98%, 47.74%, 48.32%, and 48.46%, respectively. Overall, the newly established models in this study provided complete and comprehensive tools for quantifying the biomass and stem volume of Populus × xiaohei, which might be essential to be specifically utilized in the Chinese National Forest Inventory.

Species-specific biomass allometric models and expansion factors for indigenous and planted forests of the Mozambique highlands

Secondary Miombo woodlands and forest plantations occupy increasing areas in Mozambique, the former due to anthropogenic activities. Plantations, mainly species of Eucalyptus and Pinus, are being established on sites previously covered by secondary Miombo woodlands. This affects the evolution, cycle and spatiotemporal patterns of carbon (C) storage and stocks in forest ecosystems. The estimation of C storage, which is indispensable for formulating climate change policies on sequestrating CO2, requires tools such as biomass models and biomass conversion and expansion factors (BCEF). In Mozambique, these tools are needed for both indigenous forests and plantations. The objective of this study is to fit species-specific allometric biomass models and BCEF for exotic and indigenous tree species. To incorporate efficient inter-species variability, biomass equations were fitted using nonlinear mixed-effects models. All tree component biomass models had good predictability; however, better predictive accuracy and ability was observed for the 2-predictors biomass model with tree height as a second predictor. The majority of the variability in BCEF was explained by the variation in tree species. Miombo species had larger crown biomass per unit of stem diameter and stored larger amounts of biomass per stem volume. However, due to relatively rapid growth, larger stem diameters, heights, and stand density, the plantations stored more biomass per tree and per unit area.

Tree and stand level estimations of Abies alba Mill. aboveground biomass

Key messageWe provided a complete set of tree- and stand-level models for biomass and carbon content of silver firAbies alba. This allows for better characterization of forest carbon pools in Central Europe than previously published models. The best predictor of biomass at the stand level is stand volume, and the worst are stand basal area and density.ContextAmong European forest-forming tree species with high economic and ecological significance, Abies alba Mill. is the least characterized in terms of biomass production.AimsTo provide a comprehensive set of tree- and stand-level models for A. alba biomass and carbon stock. We hypothesized that (among tree stand characteristics) volume will be the best predictor of tree stand biomass.MethodsWe studied a chronosequence of 12 A. alba tree stands in southern Poland (8–115 years old). We measured tree stand structures, and we destructively sampled aboveground biomass of 96 sample trees (0.0–63.9 cm diameter at breast height). We provided tree-level models, biomass conversion and expansion factors (BCEFs) and biomass models based on forest stand characteristics.ResultsWe developed general and site-specific tree-level biomass models. For stand-level models, we found that the best predictor of biomass was stand volume, while the worst were stand basal area and density.ConclusionOur models performed better than other published models, allowing for more reliable biomass predictions. Models based on volume are useful in biomass predictions and may be used in large-scale inventories.

Effects of stand features on aboveground biomass and biomass conversion and expansion factors based on a Pinus sylvestris L. chronosequence in Western Poland

Although Scots pine (Pinus sylvestris L.) is one of the most economically important European timber trees, there is still insufficient data about biomass variability and its relationships with stand features. Therefore, we aimed: (1) to develop biomass models for different aboveground biomass components at tree and stand levels, as well as biomass conversion and expansion factors (BCEFs), (2) to assess the relationships between stand parameters and aboveground biomass and BCEFs and (3) to compare stand biomass obtained using BCEFs with models developed based on stand parameters (age, basal area, stand volume and mean height). Using a chronosequence (3–117 years old) of 120 plots within even-aged pure Scots pine stands and 791 sample trees, we prepared tree- and stand-level allometric equations and BCEFs for aboveground biomass determination. Using stand age, density, stand volume and mean height, we prepared a set of models for biomass and BCEFs. Our study indicated that stand biomass increased with increasing height, volume and age and with decreasing stand density during stand development. Stand-level models provided better accuracy than BCEF-based models. The best predictors of biomass were stand volume and mean height. We also confirmed highly dynamic increases in stand biomass and decreases in BCEFs in the youngest phase of stand growth and relative stabilization in later stages of Scots pine stand development. The models obtained may be used in large-scale forest biomass inventories and increase our knowledge of carbon sequestration in forest biomass.

Effects of Stand Age on Biomass Allocation and Allometry of Quercus Acutissima in the Central Loess Plateau of China

We studied the effects of stand age on allocation and equation fitting of aboveground and below-ground biomass in four Quercus acutissima stands (14, 31, 46, and 63 years old) in the Central Loess Plateau of China. The stem wood, stem bark, branch, foliage, and belowground biomass of each of the 20 destructive harvesting trees were quantified. The mean total biomass of each tree was 28.8, 106.8, 380.6, and 603.4 kg/tree in the 14-, 31-, 46-, and 63-year-old stands, respectively. Aboveground biomass accounted for 72.25%, 73.05%, 76.14%, and 80.37% of the total tree biomass in the 14-, 31-, 46-, and 63-year-old stands, respectively, and stem wood was the major component of tree biomass. The proportion of stem (with bark) biomass to total tree biomass increased with stand age while the proportions of branch, foliage, and belowground biomass to total tree biomass decreased with stand age. The ratio of belowground biomass to aboveground biomass decreased from 0.39 in the 14-year-old stand to 0.37, 0.31, and 0.24 in the 31-, 46-, and 63-year-old stands, respectively. Age-specific biomass equations in each stand were developed for stem wood, stem bark, aboveground, and total tree. The inclusion of tree height as a second variable improved the total tree biomass equation fitting for middle-aged (31-year-old and 46-year-old) stands but not young (14 years old) and mature (63 years old) stands. Moreover, biomass conversion and expansion factors (BCEFs) varied with stand age, showing a decreasing trend with increasing stand age. These results indicate that stand age alters the biomass allocation of Q. acutissima and results in age-specific allometric biomass equations and BCEFs. Therefore, to obtain accurate estimates of Q. acutissima forest biomass and carbon stocks, age-specific changes need to be considered.

Tree- and Stand-Level Biomass Estimation in a Larix decidua Mill. Chronosequence

Carbon pool assessments in forests is one of the most important tasks of forest ecology. Despite the wide cultivation range, and economical and traditional importance, the aboveground biomass of European larch (Larix decidua Mill.) stands is poorly characterized. To increase knowledge about forest biomass accumulation and to provide a set of tools for aboveground biomass estimation, we studied a chronosequence of 12 larch forest stands (7–120 years old). From these stands, we measured the biomass of 96 sample trees ranging from 1.9 to 57.9 cm in diameter at breast height. We provided age-specific and generalized allometric equations, biomass conversion and expansion factors (BCEFs) and biomass models based on forest stand characteristics. Aboveground biomass of stands ranged from 4.46 (7-year-old forest stand) to 445.76 Mg ha−1 (106-year-old). Stand biomass increased with increasing stand age, basal area, mean diameter, height and total stem volume and decreased with increasing density. BCEFs of the aboveground biomass and stem were almost constant (mean BCEFs of 0.4688 and 0.3833 Mg m−3, respectively). Our generalized models at the tree and stand level had lower bias in predicting the biomass of the forest stands studied, than other published models. The set of tools provided fills the gap in biomass estimation caused by the low number of studies on larch biomass, which allows for better estimation of forest carbon pools.

Difference analysis in estimating biomass conversion and expansion factors of masson pine in Fujian Province, China based on national forest inventory data: A comparison of three decision tree models of ensemble learning.

Biomass conversion and expansion factors (BCEFs) are important parameters for estimating carbon storage in forest biomass. Clarifying the source of differences in estimating BCEFs could reduce uncertainties in forest biomass carbon estimation. The decision tree models of ensemble learning can be used to properly figure out the source of differences in estimating BCEFs. However, the comparison of different decision tree models for analyzing differences in estimating BCEFs has never been reported. In this study, three models [the boosted regression trees (BRT), random forest(RF), and Cubist] and data of 331 masson pine plots from the 8th Chinese National Forest Inventory for Fujian Province were used to analyze the differences in estimating BCEFs (including above- and below-ground). The results showed that BCEFs were following right-skewed distribution, with the mean, minimum and maximum value being 0.69 t·m-3, 0.67 t·m-3 and 0.71 t·m-3, respectively. All three models performed well in BCEFs prediction and fitting, and could explain more than 92.8% variations of BCEFs. All three models showed that average DBH and volume were the top two highest relative importance predictors. BCEFs decreased with the increases of average DBH and volume. Stand characteristics factors, such as average DBH, volume, average age and average height, had great influence on BCEFs. Both soil factors and topographic factors had little influence on BCEFs. Using a few variables (such as average DBH, volume, average age and avera-ge height) which contained more BCEFs prediction information could have preferable forecasting precision when building BCEFs models. Moreover, widely representative samples with different average tree ages, average DBH and volume should be chosen to calculate BCEFs when applying constant BCEFs.

Least squares-based biomass conversion and expansion factors best estimate biomass than ratio-based ones: Statistical evidences based on tropical timber species

Due to its readiness to convert stem volumes (V) into biomass, national and regional aboveground biomass estimates and greenhouse gas reporting are generally based on biomass conversion and expansion factors (BCEFs). BCEF-based biomass (W) is computed by the following regression through the origin (RTO): W?=?BCEF?×?V. However, the regression slope (BCEF) is not obtained using least squares (LS); it is obtained as the ratio of observed biomass and stem volume. Therefore, the sum of squares of the residuals is not minimum. This may lead to strongly biased biomass estimates. Furthermore, in this case, the biomass is not modelled. In the present study, it was suggested that BCEFs should be obtained using LS through RTO. The objective of this study was to compare LS-based and ratio-based BCEFs with regard to predictive accuracy and ability. A dataset of 75 trees from 4 species was used for the comparisons.•LS-based BCEFs were associated with higher predictive accuracy and ability than ratio-based ones.•It was proved that RTO is appropriated for estimating BCEFs, as the intercept a was consistently not significant.•Ratio-based BCEFs may lead to seriously biased biomass and carbon stocks estimates.•BCEFs should be estimated using least squares.

How do tree stand parameters affect young Scots pine biomass? – Allometric equations and biomass conversion and expansion factors

Abstract Due to the impact of climate change and rising atmospheric carbon dioxide concentrations, assessment of forest carbon pools becomes a crucial task for forest ecology. One of the scientific gaps in this task is the assessment of young tree stands, not included in forest inventories, due to lack of merchantable volume. We aimed to provide a comprehensive set of allometric equations (AEs) and biomass conversion and expansion factors (BCEFs) for young Scots pine tree stands and to develop models of tree stand biomass based on stand features easy-measurable by remote sensing: height and density. We used data collected in 77 tree stands of Scots pine ranging in age from 3 to 20 years in Western and Central Poland, covering forest, post-agricultural and post-industrial sites. Our dataset included 423 sample trees. Our study resulted in collection of 256 site-specific AEs, 12 generalized AEs and equations allowing for dynamic BCEF calculation. Due to lack of BCEF applicability for young trees, we also provided age- and height-dependent functions allowing for precise biomass estimation at the tree-stand level. It was found that tree-stand biomass increased with tree-stand age, height and volume, and decreased with increasing density in the chronosequence. BCEFs decreased with tree-stand age, height and volume and increased with increasing density. Using these relationships we provided stand-level equations based on BCEFs and on tree height – the stand characteristic which is easily obtained from airborne data. These two models did not show a big difference in accuracy. Thus, height-based models are expected to be useful for extensive assessments of young tree stand biomass and carbon sequestration, allowing for better estimation of forest carbon pools. Moreover, our models, in comparison with IPCC guidelines, give more precise values of carbon pools and biomass of young Scots pine tree stands.

Biomass conversion and expansion factors for a chronosequence of young naturally regenerated silver birch (Betula pendula Roth) stands growing on post-agricultural sites

Forest stand biomass or carbon storage in the biomass may be estimated by conversion of the trees volume since roughly 50% of tree biomass is carbon. There is a need to find biomass conversion and expansion factors (BCEFs) for young stands, because those established for older ones may not be relevant due to changes in biomass allocation patterns over stand age and development phases. We developed BCEFs for above- and belowground biomass components of young silver birch stands as separate functions of stand age or variables that reflect growth conditions and the biological status of trees, i.e. top height (H100), mean height (Hg), base diameter (D0), quadratic mean diameter at breast height (Dg) or stand volume (V). Data were collected on 120 pure birch stands that regenerated naturally on post-agricultural lands in Poland. We determined BCEFs based on the stem volume and dry biomass of above- and belowground components. We applied segmented linear regression (SLR) to develop equations for BCEF determination for each of the pre-determined age classes using (a) fixed break points (FBP) found with the Ward method and (b) estimated break points (EBP) derived based on the best fit of regression models during piecewise regression estimation. We found that the use of SLR and non-linear regression (NR) approaches produced similar results in terms of quality of fit. However, non-linear parameter estimates are more efficient than linear ones, as NR seems to be more frequently used and easier to process using existing statistical tools, but at the same time the SLR provides biological interpretation of results (i.e. the point where BCEF value stabilizes and beyond which stand features do not influence BCEF). The largest difference between EBP and FBP occurs for stems, and the smallest for roots. For total biomass and all biomass components except stem, BCEFs are very high for the youngest, shortest and thinnest trees and hence stands with low volume. Their values decrease along with age, height, diameter and volume towards the EBPs. For individuals older, taller, thicker and with higher volume than EBP, there is no influence of age, H100, Hg, D0, Dg and V on BCEF values. We confirmed that H100 might be a good biomass predictor for young birch stands, which is important because measuring tree height is not as time consuming as tree diameter measurements, particularly for young and very dense stands, and this parameter can be obtained from remote sensing technology.

Biomass conversion and expansion factors are afected by thinning

Aim of the study: The objective of this paper is to investigate the use of Biomass Conversion and Expansion Factors (BCEFs) in maritime pine (Pinus pinaster Ait.) stands subjected to thinning.Area of the study: The study area refers to different ecosystems of maritime pine stands inNorthern Portugal.Material and methods: The study is supported by time data series and cross sectional data collected in permanent plots established in the North of Portugal. An assessment of BCEF values for the aboveground compartments and for total was completed for each studied stand. Identification of key variables affecting the value of the BCEFs in time and with thinning was conducted using correlation analysis. Predictive models for estimation of the BCEFs values in time and after thinning were developed using nonlinear regression analysis.Research highlights: For periods of undisturbed growth, the results show an allometric relationship between the BCEFs, the dominant height and the mean diameter. Management practices such as thinning also influence the factors. Estimates of the ratio change before and after thinning depend on thinning severity and thinning type. The developed models allow estimating the biomass of the stands, for the aboveground compartments and for total, based on information of stand characteristics and of thinning descriptors. These estimates can be used to assess the forest dry wood stocks to be used for pulp, bioenergy or other purposes, as well as the biomass quantification to support the evaluation of the net primary productivity.Keywords: carbon; softwood; thinning; volume; wood energy; maritime pine.

Estimating aboveground woody biomass of forests in Poland for FAO/ECE and UNFCCC reporting

Abstract The United Nations Framework Convention on Climate Change and the Kyoto Protocol have committed member states to reduce greenhouse gas emissions by, among others, promoting the increase of carbon sequestration by carbon sinks (including woody biomass in forests). In order to achieve these objectives, an international reporting system was designed. The stock of woody biomass depends on several environmental and managerial factors, which determine species composition and age structure of a forest as well as characteristics of individual trees. Estimating aboveground woody biomass, especially on a nation-wide level, is generally based on the application of conversion factors to known characteristics such as the volume of the growing stock. The application of default conversion factors, as proposed by international guidelines, however, is questionable, since inventory systems for and definitions of growing stock differ from country to country. In this paper, the methods used in Poland to estimate woody biomass for the FAO and the UNFCC reporting, were presented and analysed. We also analysed the influence of some stand and tree characteristics, such as tree species composition and content of bark and its density, on the stock of woody biomass. We conclude that issues not addressed in the IPCC guidelines, such as big differences in wood and bark density, especially for pine, need to be taken into consideration when making estimations. Moreover, the results of this paper show that biomass conversion and expansion factors (BCEF) proposed by IPCC are not adequate for Polish conditions.

Notes on the biomass expansion factors of Quercus mongolica and Quercus variabilis forests in Korea

Biomass expansion factors, which convert timber volume (or dry weight) to biomass, are used for estimating the forest biomass and accounting for the carbon budget at a regional or national scale. We estimated the biomass conversion and expansion factors (BCEF), biomass expansion factors (BEF), root to shoot ratio (R), and ecosystem biomass expansion factor (EBEF) for Quercus mongolica Fisch. and Quercus variabilis Bl. forests based on publications in Korea. The mean BCEF, BEF, and R for Q. mongolica was 1.0383 Mg/m 3 (N = 27; standard deviation [SD], 0.5515), 1.3572 (N = 27; SD, 0.1355), and 0.2017 (N = 32; SD, 0.0447), respectively. The mean BCEF, BEF, and R for Q. variabilis was 0.7164 Mg/m 3 (N = 17; SD, 0.3232), 1.2464 (N = 17; SD, 0.0823), and 0.1660 (N = 8; SD, 0.0632), respectively. The mean EBEF, as a simple method for estimating the ground vegetation biomass, was 1.0216 (N = 7; SD, 0.0232) for Q. mongolica forest ecosystems, and 1.0496 (N = 8; SD, 0.0725) for Q. variabilis forest ecosystems. The biomass expansion factor values in this study may be better estimates of forest biomass in Q. mongolica or Q. variabilis forests of Korea compared with the default values given by the Intergovernmental Panel on Climate Change (IPCC).

Carbon Stock Assessment at a Regional Level, on Pure and Mixed Stands, Based on Inventory Data: A Case Study

Following Kyoto protocol considerable research efforts have been made on carbon sequestration assessment of forest stands. The aim of the present study was to test the adequacy of two documented methodologies to obtain stand level dry biomass and carbon estimates, considering its application at regional scale, for pure and mixed stands. The procedures refer to: 1) the estimation of dry biomass through the use of tree biomass models and 2) the use of biomass conversion and expansion factors (BCEF) to convert stem volume raw data into aboveground dry biomass. Using the dry biomass values, carbon stock is easily estimated using conversion factors, being 0.50 a generally accepted value. Case study reports to a pilot zone with pure and mixed stands of Eucalyptus globulus Labill and Pinus pinaster Ait. in Portugal. Procedure 1) gives the most reliable results when the database includes detailed information at tree level, both for pure or mixed stands. When individual tree data is not accessible, option 2) is an interesting option to consider for pure stands. The use of BCEF-based procedure in mixed stands is not advocated at least when considering the direct use of a single conversion factor, as the value of the factor strongly depends on the forest composition.

Biomass Expansion Factors of Natural Japanese Red Pine (Pinus densiflora) Forests in Korea

Biomass expansion factors, which convert the timber volume (or dry weight) to biomass, are used to estimate the forest biomass and account for the carbon budget at the national or regional level. This study estimated the biomass conversion and expansion factors (BCEF), root to shoot ratio (R), biomass expansion factors (BEF) of natural Japanese Red Pine (Pinus densiflora Sieb. et Zucc.) forests based on direct field measurements and publications in Korea. This study attempted to fit the non-linear relationships between the biomass expansion factors (BCEF and BEF) and main stand factors [stand age, tree height, and diameter at breast height (DBH)]. The relationship between BEF and each main stand factor was expressed as a simple logarithmical equation. The BCEF was also expressed as a logarithmical equation of the tree height, DBH, and stand volume, whereas there was no significant relationship between BCEF and stand age. The mean value for BCEF, BEF, and R was 0.5821 Mg m−3 (n = 22, SD = 0.1196), 1.4465 (n = 22, SD = 0.2905), and 0.2220 (n = 17, SD = 0.0687), respectively. The values of the biomass expansion factors in this study may indicate much representativeness to estimate forest biomass in natural Japanese Red Pine forests of Korea than the default values given by the IPCC (2003, 2006).

Individual biomass factors for beech, oak and pine in Slovakia: a comparative study in young naturally regenerated stands

Biomass conversion and expansion factors (BCEF) which convert tree stem volume to whole tree biomass and biomass allocation patterns in young trees were studied in order to estimate tree and stand biomass in naturally regenerated forests. European beech (Fagus sylvatica L.), Sessile oak (Quercus petraea (Mattuschka) Liebl.) and Scots pine (Pinus sylvestris L.) stands were compared. Seven forest stands of each species were chosen to cover their natural distribution in Slovakia. Species-specific BCEF are presented, generally showing a steep decrease in all species in the smallest trees, with the only exception in the case of branch BCEF in beech which grows with increasing tree size. The values of BCEF for all tree compartments stabilise in all species once trees reach about 60–70-mm diameter at base. As they grow larger, all species increase their allocation to stem and branches, while decreasing the relative growth of roots and foliage. There are, however, clear differences between species and also between broadleaves and conifers in biomass allocation. This research shows that species-specific coefficients must be used if we are to reduce uncertainties in estimates of carbon stock changes by afforestation and reforestation activities.

Generalized functions of biomass expansion factors for conifers and broadleaved by stand age, growing stock and site index

Parties to the Kyoto Protocol and/or the United Nations Framework Convention on Climate Change (UNFCCC) are required to account for their direct human-induced carbon emissions and removals including those from forestry and other land use related activities. In most European countries, the forestry related greenhouse gas inventories are largely or exclusively based on converting tree volume data from national forest inventories to biomass using biomass conversion and expansion factors (BCEFs). However, country specific data for many species are often lacking, which considerably increases the uncertainties of the greenhouse gas inventories. The focus of this research was to develop, using internationally published datasets that cover a large geographical area, an extended set of generalized curves of such biomass expansion factors for several species or species groups by age, growing stock and site index.