Predicting seedling biomass of radiata pine from allometric variables

Allometric equations predict tree seedling biomass from non-destructively measured variables such as stem diameter (D), height (H) and seedling silhouette area (A), measured by digital imaging. This study investigates whether one general allometric equation can predict biomass of radiata pine (Pinus radiata D.Don) seedlings grown under three levels of photosynthetic photon flux density (PPFD). It also identifies which commonly used variables (A, D ² H or D ²) were the best for predicting seedling biomass under these conditions. Radiata pine seedlings were grown with constant daytime (12 h d⁻¹) PPFD = 500, 250 or 125 μmol m⁻² s⁻¹ for 11 weeks. Seedlings were randomly selected every 10 d for measurement. Analysis of covariance tested whether the relationship between seedling biomass and A, D ² H or D ² varied for each PPFD level. PPFD levels influenced the relationship between biomass and A, D ² H or D ². As a result, “full” allometric models which varied with PPFD levels were more accurate and precise at predicting biomass than “reduced” models which did not vary with PPFD level, although a “reduced” model using D ² also performed well.     

Aboveground biomass of three conifers in the Qianyanzhou plantation, Jiangxi Province, China

Regressive models of the aboveground biomass for three conifers in subtropical China—slash pine (Pinus elliottii), Masson pine (P. massoniana) and Chinese fir (Cunninghamia lanceolata)—were established. Regression analysis of leaf biomass and total biomass of each branch against branch diameter (d), branch length (L), d ³ and d ² L was conducted with functions of linear, power and exponent. A power law equation with a single parameter (d) was proved to be better than the rest for Masson pine and Chinese fir, and a linear equation with parameter (d ³) is better for slash pine. The canopy biomass was derived by adopting the regression equations to all branches of each individual tree. These kinds of equations were also used to fit the relationship between total tree biomass, branch biomass, foliage biomass and tree diameter at breast height (D), tree height (H), D ³ and D ² H, respectively. D ² H was found to be the best parameter for estimating total biomass. However, for foliage biomass and branch biomass, both parameters and equation forms showed some differences among species. Correlations were highly significant (P<0.001) for foliage biomass, branch biomass and total biomass, among which the equation of the total biomass was the highest. With these equations, the aboveground biomass of Masson pine forest, slash pine forest and Chinese fir forest were estimated, in addition to the allocation of aboveground biomass. The above-ground biomass of Masson pine forest, slash pine forest and Chinese fir forest was 83.6, 72.1 and 59 t/hm² respectively, and the stem biomass was more than the foliage biomass and the branch biomass. The underground biomass of these three forests which estimated with others’ research were 10.44, 9.42 and 11.48 t/hm², and the amount of carbon-fixed were 47.94, 45.14 and 37.52 t/hm², respectively. __________ Translated from Chinese Journal of Applied Ecology, 2006, 17(8): 1382–1388 [译自: 应用生态学报]     

Tree biomass estimation in regenerating areas of tropical dry vegetation in northeast Brazil

Allometric equations have been developed for various different vegetation types but have rarely been validated in the field and never for dry tropical forest such as caatinga. In three areas of semi-arid Brazil, with regenerating caatinga vegetation, we measured and weighed twelve hundred individuals of four tree species and used the data to validate equations previously determined in mature caatinga. They and several other equations developed for tropical vegetations overestimate the biomass (B) of trees from the regeneration areas by more than 20%, possibly because these trees have reduced crowns, with lower branch masses. We then determined new allometric equations for them, validating equations for one site against data of the others and pooling the data if they were cross-validated. The best equations were power ones, based on diameter at breast height (D), with little improvement by including height, crown area and/or wood density (Caesalpinia pyramidalis, B = 0.3129D^1.8838; Croton sonderianus, B = 0.4171D^1.5601; Mimosa ophthalmocentra, B = 0.4369D^1.8493; and Mimosa tenuiflora, B = 0.3344D^1.9648 and 0.4138D^1.7718).     

Allometric models for estimation of aboveground carbon stocks in improved fallows in eastern Zambia

This paper presents allometric functions for estimation of C stocks in aboveground tree biomass in 2-year-old improved fallows in eastern Zambia. A total of 222 individual trees representing 12 tree species were destructively harvested for C analysis by LECO CHN-1000 analyzer. Allometric models relating collar diameter (D₁₀) and total tree height (H) to stem and total aboveground C stocks were developed using data from tree fallows. Logarithmically transformed power functions displayed a good ability to stabilize variance of aboveground C stocks and showed a good fit (84 < R ² < 99) with a bias of 0.7–3.6%. D₁₀ alone and in combination with H explained most of the variability in total aboveground C stocks. Validation of the species-specific and generalized models with field data indicated that they accurately predicted aboveground tree C stocks. Generalized C estimation functions were also validated and described 73–97% of variability in aboveground C stocks with an average unsigned deviation of 1.5–4.9%. The C functions will serve as a vital tool for predicting and monitoring C pool sizes in long-term studies and agroforestry projects, especially where destructive sampling is not possible.     

Carbon accumulation in aboveground and belowground biomass and soil of different age native forest plantations in the humid tropical lowlands of Costa Rica

Generic or default values to account for biomass and carbon accumulation in tropical forest ecosystems are generally recognized as a major source of errors, making site and species specific data the best way to achieve precise and reliable estimates. The objective of our study was to determine carbon in various components (leaves, branches, stems, structural roots and soil) of single-species plantations of Vochysia guatemalensis and Hieronyma alchorneoides from 0 to 16 years of age. Carbon fraction in the biomass, mean (±standard deviation), for the different pools varied between 38.5 and 49.7% (±3 and 3.8). Accumulated carbon in the biomass increased with the plantation age, with mean annual increments of 7.1 and 5.3 Mg ha⁻¹ year⁻¹ for forest plantations of V. guatemalensis and H. alchorneoides, respectively. At all ages, 66.3% (±10.6) of total biomass was found within the aboveground tree components, while 18.6% (±20.9) was found in structural roots. The soil (0–30 cm) contained 62.2 (±13) and 71.5% (±17.1) of the total carbon (biomass plus soil) under V. guatemalensis and H. alchorneoides, respectively. Mean annual increment for carbon in the soil was 1.7 and 1.3 Mg ha⁻¹ year⁻¹ in V. guatemalensis and H. alchorneoides. Allometric equations were constructed to estimate total biomass and carbon in the biomass which had an R ²aj (adjusted R square) greater than 94.5%. Finally, we compare our results to those that could have resulted from the use of default values, showing how site and species specific data contribute to the overall goal of improving carbon estimates and providing a more reliable account of the mitigation potential of forestry activities on climate change.     

The population dynamics and productivity of <Emphasis Type="Italic">Acacia pennatula</Emphasis> in the pasturelands of the Nature Reserve Mesas de Moropotente,Estelí, Nicaragua

Acacia pennatula trees are the most conspicuous woody species in the pasturelands of the Nature Reserve Mesas de Moropotente, Estelí, Nicaragua. Cattle ranchers keep A. pennatula because it produces fence posts, forage (pods) and firewood. A population projection matrix model was developed to: (1) estimate the sustainable harvest (H) of fence posts at different tree population densities, (2) explore the range of recruitment (R), and survival and growth of both saplings and small poles compatible with current population density, and (3) determine how much carbon is stored in the soil-pasture-tree system. Acacia pennatula trees take 40 years to reach H size (D₃₀ ≥ 30 cm). Estimated sustainable H from current tree population density is 1.8l7 trees ha⁻¹ year⁻¹, yielding 2.8 large and 11.2 regular size fence posts ha⁻¹ year⁻¹. This annual output easily satisfies the needs of a typical 100 ha cattle ranch in the study area. Current population density is congruent with very low R (<100 saplings ha⁻¹ year⁻¹), very low survival rates (<0.30%) and/or retarded D₃₀ growth of saplings and small poles. Total carbon in tree biomass was only 37 Mg ha⁻¹. Cattle ranchers have learned to harness the invasive nature of the species to obtain valuable tree products for farm use or sale.     

西非Sudanian热带林地11个树种地上生物量异速生长预测

Allometric models are necessary for estimating biomass in terrestrial ecosystems. Generalized allometric relationship exists for many tropical trees, but species- and region-specific models are often lacking. We developed species-specific allometric models to predict aboveground biomass for 11 native tree species of the Sudanian savanna-woodlands. Diameters at the base and at breast height, with species means ranging respectively from 11 to 28 cm and 9 to 19 cm, and the height of the trees were used as predictor variables. Sampled trees spanned a wide range of sizes including the largest sizes these species can reach. As a response variable, the biomass of the trees was obtained through destructive sampling of 4 754 trees during wood harvesting. We used a stepwise multiple regression analysis with backward elimination procedure to develop models separately predicting, total biomass of the trees, stem biomass, and biomass of branches and twigs. All species-specific regression models relating biomass with measured tree dimensions were highly significant (p < 0.001). The biomass of branches and twigs was less predictable compared to stem biomass and total biomass, although their models required fewer predictors and predictor interactions. The best-fit equations for total above-ground biomass and stem biomass had R ² > 0.70, except for the Acacia species; for branches including twig biomass, R²-values varied from 0.749 for Anogeissus leiocarpa to 0.183 for Acacia macrostachya. The use of these equations in estimating available biomass will avoid destructive sampling, and aid in planning for sustainable use of these species.     

Allometry and partitioning of individual tree biomass and carbon of Abies nephrolepis Maxim in northeast China

Abies nephrolepis Maxim is an important commercial conifer species in northeastern China. In this study, we compared the partitioning and variations of biomass and carbon concentration for four tree components (i.e. stem, root, branch, and foliage). The results indicated that foliage had the largest carbon concentration, which was significantly different from other tree components. Above-ground biomass or carbon accounted for about 78% of the total tree biomass or carbon, whereas below-ground biomass or carbon corresponded to about 22%. The root-to-shoot ratio averaged .28 for biomass and .27 for carbon. We applied likelihood analysis to investigate the error structure of allometric relationship W?=?a·D^b and found that the multiplicative error structure was favored. Thus, the additive systems of biomass and carbon equations in a log-transformed scale were constructed using nonlinear seemly unrelated regression. The model fitting results showed that all biomass and carbon equations fitted the data well. Further, five approaches for calculating carbon stock of individual trees were evaluated and compared. The carbon allometric equations and the estimated biomass multiplied by weighted mean carbon concentration were more advantageous, whereas using the generic carbon concentration constants produced significant biases in estimating the carbon stock of individual trees.     

Biomass equations for sixty-five North American tree species

The paper presents a comprehensive review of the biomass equations for 65 North American tree species. All equations are of the form M = aD^b, where M is the oven-dry weight of the biomass component of a tree (kg), D is diameter at breast height (DBH) (cm), and a and b are parameters. Equations for the following tree components were included in the review: total aboveground biomass, stem wood, stem bark, total stem (wood and bark), foliage, and branches (wood and bark). A total of 803 equations are presented with the range of DBH values of the sample, sample size, coefficient of determination R², standard error of the estimate, fitting method used to estimate the parameters a and b, correction factor for a bias introduced by logarithmic transformation of the data, site index and geographic location of the sampled stand(s), and a reference to the paper in which the equation (or the data) was published. The review is a unique source of equations that can be used to estimate tree biomass and/or to study the variation of biomass components for a tree species.     

Effects of forest canopy gap on biomass of Abies faxoniana seedlings and its allocation in subalpine coniferous forests of western Sichuan

Using a strip transect sampling method, the density, height (≤ 100 cm), basal diameter and components of biomass of Abies faxoniana seedlings, living in a forest gap (FG) and under the forest canopy (FC) of subalpine natural coniferous forests in western Sichuan, were investigated and the relationships among different components of biomass analyzed. The results indicated that the density and average height (H) of A. faxoniana seedlings were significantly different in the FG and under the FC, with the values being 12903 and 2017 per hm², and 26.6 and 24.3 cm. No significant differences were found in the average basal diameter (D) and biomass. The biomass allocation in seedling components was significantly affected by forest gap. In the FG, the biomass ratio of branch to stem reached a maximum of 1.54 at age 12 and then declined and fluctuated around 0.69. Under the FC, the biomass ratio of branch to stem increased with seedling growth and exceeded 1.0 at about age 15. The total biomass and the biomass of leaves, stems, shoots and roots grown in the FG and under the FC were significantly correlated with D ² H. There were significant and positive correlations among the biomass of different components. __________ Translated from Chinese Journal of Applied Ecology, 2007, 18(4): 721–727 [译自: 应用生态学报]     

Equations for estimating the above-ground biomass of Larix sibirica in the forest-steppe of Mongolia

Biomass functions were established to estimate above-ground biomass of Siberian larch (Larix sibirica) in the Altai Mountains of Mongolia. The functions are based on biomass sampling of trees from 18 different sites, which represent the driest locations within the natural range of L. sibirica. The best performing regression model was found for the equations y = (D ² H)/(a+bD) for stem biomass, y = aD ^b for branch biomass, and y=aD ^b H ^c for needle biomass, where D is the stem diameter at breast height and H is the tree height. The robustness of the biomass functions is assessed by comparison with equations which had been previously published from a plantation in Iceland. There, y=aD ^b H ^c was found to be the most significant model for stem and total above-ground biomasses. Applying the equations from Iceland for estimating the above-ground biomass of trees from Mongolia resulted in the underestimation of the biomass in large-diameter trees and the overestimation of the biomass in thin trees. The underestimation of thick-stemmed trees is probably attributable to the higher wood density, which has to be expected under the ultracontinental climate of Mongolia compared to the euoceanic climate of Iceland. The overestimation of the biomass in trees with low stem diameter is probably due to the high density of young growth in the not systematically managed forests of the Mongolian Altai Mountains, which inhibits branching, whereas the plantations in Iceland are likely to have been planted in lower densities.     

Effects of pruning on radial growth and biomass increment of trees growing in homegardens of Kerala, India

To evaluate the effects of pruning on stem radial growth increment and leaf and twig biomass production, an experiment with four pruning intensities (0, 50, 75 and 90%) on ten locally important tree species (Ailanthus triphysa, Albizia odoratissima, Artocarpus hirsutus, Bombax malabarica, Bridelia crenulata, Erythrina indica, Grewia tiliifolia, Macaranga peltata, Terminalia paniculata and Xylia xylocarpa ), was carried out. The results did not support the contention that a certain level of pruning promotes stem growth in trees. Instead, all species have a level of pruning that reduces annual increment in stem diameter. In Ailanthus triphysa and Artocarpus hirsutus trees subjected to different pruning intensities showed a decline in the annual increment in stem diameter while in other species diameter increment reduced when the pruning intensity was 75% and 90%. Response to pruning in terms of biomass production also varied from species to species. In Erythrina indica, Macaranga peltata and Terminalia paniculata annual foliage and branch production in pruned trees was significantly more than that of the un-pruned trees. However, in Ailanthus triphysa, Albizia odoratissima, Artocarpus hirsutus, Bridelia crenulata, Grewia tiliifolia and Xylia xylocarpa pruned trees produced comparatively more amount of foliage and branches produced annually than that by the un-pruned trees when the pruning was carried out once in 2 years. Based on these observations it is recommended that trees of Erythrina indica, Macaranga peltata and Terminalia paniculata may be pruned at 50% level annually while the trees of Ailanthus triphysa, Albizia odoratissima, Artocarpus hirsutus, Bridelia crenulata, Grewia tiliifolia and Xylia xylocarpa may be pruned at the same pruning intensity once in 2 years.     

Aboveground biomass equations for individual trees of <Emphasis Type="Italic">Cryptomeria japonica</Emphasis>, <Emphasis Type="Italic">Chamaecyparis obtusa</Emphasis> and <Emphasis Type="Italic">Larix kaempferi</Emphasis> in Japan

Generic equations are proposed for stem, branch and foliage biomass of individual trees in even-aged pure stands of Cryptomeria japonica, Chamaecyparis obtusa and Larix kaempferi. Biomass data was collected from a total of 1,016 individual trees from 247 stands throughout Japan, and five regression models were assessed by root mean square error, mean bias, fit index (FI), and AIC. The results show that a power equation using diameter at breast height (dbh) and height is the most suitable for all species and components. This equation is more accurate than the familiar power equation that uses ‘dbh² height’, and it expresses the greater volume of branch and foliage mass of trees with a lower height/diameter ratio. A power equation using dbh is more reasonable for models with dbh as the only independent variable and more accurate than a power equation using ‘dbh² height’ for estimating branch and foliage mass. Estimating error for branch and foliage mass is larger than that for stem mass, but the entire aboveground biomass can be estimated with an error of less than 19%, except in the case of small trees with dbh less than 10 cm.     

Growth characteristics and allometry of <Emphasis Type="Italic">Robinia pseudoacacia</Emphasis> as a silvopastoral system component

Demand for goat (Capra hircus) meat in the southeastern USA is steadily increasing as a result of preferences exhibited by ethnic communities. Feeding systems that include fodder trees can be developed to take advantage of the natural preference of goats for browse. Data were collected for 2 years on a 5-year old stand of Robinia pseudoacacia L. to evaluate growth characteristics for goat browse and to develop allometric relationships in a randomized complete block design (intra-row spacing 0.5 or 1 m and coppice height 0.25 or 0.50 m) replicated six times. Allometric equations were derived from destructive harvests of 68 trees. Main branch size was not affected by intra-row spacing when trees were coppiced at 0.25 m; however, when coppiced at 0.5 m, trees spaced at 1 m had more and larger branches (P < 0.05) than trees spaced at 0.5 m. Intra-row spacing did not influence tree herbage biomass when trees were spaced at 0.5 m whereas trees coppiced at 0.25 m and spaced at 1 m produced less woody and herbaceous biomass than trees spaced at 0.5 m (P < 0.05). A strong relationship (P < 0.0001) was found between tree herbage biomass and the number of main branches greater than 0.01 m (r ² = 0.80). The results, based on growth characteristics and tree herbage biomass production, suggest that Robinia pseudoacacia L. would be an excellent candidate as a silvopastoral component in the southeastern USA.     

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.     

Soil biological properties under different tree based traditional agroforestry systems in a semi-arid region of Rajasthan,India

An investigation was carried out in an Entisol at farmers’ field in Jaipur district, Rajasthan, India during 2002–2004 to evaluate the effect of traditionally grown trees on soil biological characteristics. Traditionally grown trees in farm lands for study consisted of Prosopis cineraria (L.), Dalbergia sissoo (Roxb.) ex DC, Acacia leucophloea (Roxb.) and Acacia nilotica (L.) Del. having a canopy diameter of 8 m. Results revealed significant and substantial improvement in soil biological activity in terms of microbial biomass C, N and P, dehydrogenase and alkaline phosphatase activity under different tree based agroforestry systems as compared to a no tree control (cropping alone). Soil microbial biomass C, N and P under agroforestry varied between 262–320, 32.1–42.4 and 11.6–15.6 μg g⁻¹ soil, respectively, with corresponding microbial biomass C, N and P of 186, 23.2 and 8.4 μg g⁻¹ soil under a no tree control. Fluxes of C, N and P through microbial biomass were also significantly higher in P. cineraria based land use system followed by D. sissoo, A. leucophloea and Acacia nilotica in comparison to a no tree control. Thus, it is concluded that agroforestry system at farmers’ field enhance soil biological activity and amongst trees, P. cineraria based system brought maximum and significant improvement in soil biological activity.     

Allometric models for predicting above- and belowground biomass of <Emphasis Type="Italic">Leucaena</Emphasis>-KX2 in a shaded coffee agroecosystem in Hawaii

We developed site-specific allometric models for Leucaena leucocephala × pallida var. KX2 trees in a shaded coffee agroecosystem in Hawaii to predict above- and belowground biomass and the regrowth potential of pollarded trees. Models were used to compare tree growth rates in an experimental agroforestry system with different pollarding frequencies and additions of tree pruning residues as mulch. For all allometric equations, a simple power model (Y = aX^b) provided the optimal prediction of biomass or regrowth after pollarding. For aboveground biomass components (stem, branches, leaves, and seed and pods), stem diameter alone was the best predictor variable. Stump diameter provided the best prediction of coarse root biomass and aboveground regrowth after pollarding. Predictions of biomass from generalized allometric models often fell outside the 95% confidence intervals of our site-specific models, especially as biomass increased. The combination of pollarding trees once per year plus the addition of tree mulch resulted in the greatest aboveground regrowth rates as well as accumulation of biomass and C in the stump plus coarse roots. Although optimal prediction required the development of site-specific allometric relationships, a simple power model using stem or stump diameter alone can provide an accurate assessment of above- and belowground tree biomass, as well as regrowth potential under specific management scenarios.     

Aboveground productivity of an unsuccessful 140-year-old <Emphasis Type="Italic">Cryptomeria japonica</Emphasis> plantation in northern Kyushu,Japan

We measured the aboveground biomass, biomass increment and litterfall production of a 140-year-old, abandoned Cryptomeria japonica plantation in order to infer the effects of topography on biomass production. The plantation was unsuccessful and the naturally regenerated broad-leaved trees contributed 93.4% (374.2 Mg ha⁻¹) of the total aboveground biomass (400.2 Mg ha⁻¹). Comparing between different slope positions, aboveground biomass decreased downslope corresponding to the decrease in broad-leaved tree biomass. The biomass of C. japonica did not vary with slope position. Biomass increment and litterfall production of the broad-leaved trees also decreased downslope. However, litterfall production per unit biomass and aboveground net primary production per unit biomass increased downslope. Results of a path analysis showed that biomass increment of C. japonica decreased with increasing topographical convexity, whereas biomass and litterfall production of broad-leaved tree increased. Litterfall production of broad-leaved tree decreased with increasing biomass of C. japonica, suggesting that, despite their small biomass, the presence of residual C. japonica may have negative effects on the distribution and productivity of the broad-leaved trees. Our results indicated that total aboveground biomass of the study site was comparable to that of old-growth C. japonica plantations. We inferred that the variation in aboveground biomass of the broad-leaved trees was largely determined by the topography, while their productivity was affected by interactions with planted C. japonica.     

Biomass equations for four shrub species in subtropical China

Estimation of shrub biomass can provide more accurate estimates of forest biomass and carbon sequestration. We developed species-specific biomass regression models for four common shrub species, Chinese loropetal (Loropetalum chinense), white oak (Quercus fabri), chastetree (Vitex negundo var. cannabifolia), and Gardenia (Gardenia jasminoides), in southeast China. The objective of this study was to derive appropriate regression equations for estimation of shrub biomass. The results showed that the power model and the quadratic model are the most appropriate forms of equation. CA (canopy area, m²) as the sole independent variable was a good predictor of leaf biomass. D ² H, where D is the basal diameter (cm) and H is the shrub height (cm), is a good predictor of branch and root biomass, except for V. negundo var. cannabifolia and the root biomass of L. chinense. For total biomass, D ² is the best variable for estimation of L. chinense and G. jasminoides, and D ² H is the best variable for estimation of Q. fabri and V. negundo var. cannabifolia. Although variables D ², D ² H, and H are the preferred predictors for biomass estimation, CV (canopy projected volume, m³) could be used alone to predict branch, root, and total biomass in shrub species with acceptable accuracy and precision.     

Above- and belowground biomass measurements in an unthinned stand of Sitka spruce (<Emphasis Type="Italic">Picea sitchensis</Emphasis> (Bong) Carr.)

Reporting carbon (C) stocks in tree biomass (above- and belowground) to the United Nations Framework Convention on Climate Change (UNFCCC) should be transparent and verifiable. The development of nationally specific data is considered ‘good practice’ to assist in meeting these reporting requirements. From this study, biomass functions were developed for estimating above- and belowground C stock in a 19-year-old stand of Sitka spruce (Picea sitchensis (Bong) Carr.). Our estimates were then tested against current default values used for reporting in Ireland and literature equations. Ten trees were destructively sampled to develop aboveground and tree component biomass equations. The roots were excavated and a root:shoot (R) ratio developed to estimate belowground biomass. Application of the total aboveground biomass function yielded a C stock estimate for the stand of 74 tonnes C ha⁻¹, with an uncertainty of 7%. The R ratio was determined to be 0.23, with an uncertainty of 10%. The C stock estimate of the belowground biomass component was then calculated to be 17 tonnes C ha⁻¹, with an uncertainty of 12%. The equivalent C stock estimate from the biomass expansion factor (BEF) method, applying Ireland’s currently reported default values for BEF (inclusive of belowground biomass), wood density and C concentration and methods for estimating volume, was found to be 60 tonnes C ha⁻¹, with an uncertainty of 26%. We found that volume tables, currently used for determining merchantable timber volume in Irish forestry conditions, underestimated volume since they did not extend to the yield of the forest under investigation. Mean stock values for belowground biomass compared well with that generated using published models.