Fractal analysis of canopy architectures of Acacia angustissima, Gliricidia sepium, and Leucaena collinsii for estimation of aboveground biomass in a short rotation forest in eastern Zambia

A study was conducted at Msekera Regional Agricultural Research Station in eastern Zambia to (1) describe canopy branching properties of Acacia angustissima, Gliricidia sepium and Leucaena collinsii in short rotation forests, (2) test the existence of self similarity from repeated iteration of a structural unit in tree canopies, (3) examined intra-specific relationships between functional branching characteristics, and (4) determine whether allometric equations for relating aboveground tree biomass to fractal properties could accurately predict aboveground biomass. Measurements of basal diameter (D10) at 10cm aboveground and total height (H), and aboveground biomass of 27 trees were taken, but only nine trees representative of variability of the stand and the three species were processed for functional branching analyses (FBA) of the shoot systems. For each species, fractal properties of three trees, including fractal dimension (Dfract), bifurcation ratios (p) and proportionality ratios (q) of branching points were assessed. The slope of the linear regression of p on proximal diameter was not significantly different (P < 0.01) from zero and hence the assumption that p is independent of scale, a pre-requisite for use of fractal branching rules to describe a fractal tree canopy, was fulfilled at branching orders with link diameters >1.5 cm. The proportionality ration q for branching patterns of all tree species was constant at all scales. The proportion of q values >0.9 (fq) was 0.8 for all species. Mean fractal dimension (Dfract) values (1.5?1.7) for all species showed that branching patterns had an increasing magnitude of intricacy. Since Dfract values were ≥1.5, branching patterns within species were self similar. Basal diameter (D10), proximal diameter and Dfract described most of variations in aboveground biomass, suggesting that allometric equations for relating aboveground tree biomass to fractal properties could accurately predict aboveground biomass. Thus, assessed Acacia, Gliricidia and Leucaena trees were fractals and their branching properties could be used to describe variability in size and aboveground biomass.     

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]     

Allometric equations based on a fractal branching model for estimating aboveground biomass of four native tree species in the Philippines

Fractal branching models can provide a non-destructive and generic tool for estimating tree shoot and root length and biomass, but field validation is rarely described in the literature. We compared estimates of above ground tree biomass for four indigenous tree used on farm in the Philippines based on the WanFBA model tree architecture with data from destructive sampling. Allometric equations for the four species varied in the constant (biomass at virtual stem diameter 1) and power of the scaling rule (b in Y = aD ^b ), deviating from the value of 8/3 that is claimed to be universal. Allometric equations for aboveground biomass were 0.035 D ^2.87 for Shorea contorta, 0.133 D ^2.36 for Vitex parviflora, 0.063 D ^2.54 for Pterocarpus indicus and 0.065 D ^2.28 for Artocarpus heterophyllus, respectively. Allometric equations for branch biomass had a higher b factor than those for total biomass (except in Artocarpus); allometric equations for the leave + twig fraction a lower b. The performance of the WanFBA model was significantly improved by introduction of a tapering factor “τ“ for decrease of branch diameter within a single link. All statistical tests performed on measured biomass versus biomass predicted from the WanFBA results confirm the viability of the WanFBA model as a non-destructive tool for predicting above-ground biomass equations for total biomass, branch biomass and the leaf + twig fraction.     

Models for estimation of carbon sequestered by Cupressus lusitanica plantation stands at Wondo Genet,Ethiopia

This study compared models for estimating carbon sequestered aboveground in Cupressus lusitanica plantation stands at Wondo Genet College of Forestry and Natural Resources, Ethiopia. Relationships of carbon storage with tree component and stand age were also investigated. Thirty trees of three different ages (5, 12 and 24 years), comprising 10 trees from each stand, were sampled in order to generate dry biomass and carbon data from tree components. Five linear and non-linear biomass and carbon models were compared and evaluated for estimation of overall aboveground carbon, carbon by age groups, and carbon by diameter at breast height (DBH) classes using performance indicator statistics. Among the models compared, a carbon model described by Y = b ₀ D ² H + ? (p-value < 0.001), where D = DBH (in cm), H = total height of the tree (in m), ? = error, and b ₀ is a parameter, was found to be the best model for estimation of carbon sequestered aboveground in C. lusitanica plantation stands of the study area. The study also indicated the overall superiority of carbon models over biomass models in estimation of aboveground carbon of C. lusitanica. It was concluded that, for the range of DBH utilised in the current study, the carbon model described can be a useful tool in estimation of carbon storage of C. lusitanica plantations in the study area and other related sites.     

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.     

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.     

Above- and belowground biomass in a Brazilian Cerrado

Cerrado is a biome that occupies about 25% of the Brazilian territory and is characterized by a gradient of grassland to savanna and forest formations and by high species richness. It has been severely affected by degradation and deforestation and has been heavily fragmented over the past 4-5 decades. Despite the recognized overall ecological importance of the Cerrado, there are only few studies focusing on the quantification of biomass in this biome. We conducted such a case study in the South-East of Brazil in a cerrado sensu stricto (cerrado s.s.) with the goal to produce estimates of above- and belowground biomass and to develop allometric equations. A number of 120 trees from 18 species were destructively sampled and partitioned into the components: leaves, branches and bole. Five models with DBH (D), height (H), D²H and wood density (WD) as independent variables were tested for the development of allometric models for individual tree aboveground biomass (leaves + branches + bole). One model based on basal area (BA) as a stand parameter was also tested as an alternative approach for predicting aboveground biomass in the stand level. Belowground biomass was estimated by subsampling on 10 sample plots. Mean aboveground tree biomass (bole, branches and leaves) was estimated to be 62,965.5 kg ha⁻¹(SE = 14.6%) and belowground biomass accounted for 37,501.8 kg ha⁻¹ (SE = 23%). The best-fit equation for the estimation of individual tree aboveground biomass include DBH and wood density as explanatory variables (R² = 0.898; SEE = 0.371) and is applicable for the diameter range of this study (5.0-27.6 cm) and in environments with similar conditions of the cerrado s.s. sampled. In the stand level, the model tested presented a higher goodness of fit than the single tree models (R² = 0.934; SEE = 0.224). Our estimates of aboveground biomass are higher than reported by other studies developed in the same physiognomy, but the estimates of belowground biomass are within the range of values reported in other studies from sites in cerrado s.s. Both biomass estimates, however, exhibit relatively large standard errors. The root-to-shoot ratio of the sample trees is in the magnitude of reported values for savanna ecosystems, but smaller than estimated from other studies in the cerrado s.s.     

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.     

Biomass estimations in forests of different disturbance history in the Atlantic Forest of Rio de Janeiro,Brazil

Tropical forests are large reservoirs of biomass and there is a need for information on existing carbon stocks in these ecosystems and especially the effects of logging on these stocks. Reliable estimates of aboveground biomass stocks within the Atlantic Forest are rarely available. Past human disturbance is an important factor affecting forest structure variation and biomass accumulation among tropical forest ecosystems. To support the efforts of improving the quality of estimations of the current and future biomass carbon storage capacity of this disturbed forest region we tested a non-experimental small scale approach to compare the aboveground tree biomass (AGB) of forest sites. Three sites with known disturbance histories have been investigated: complete cut down, selective logging and conservation since 70 years. The woody plant community (dbh ≥ 10 cm) was censused and canopy openness in conjunction with leaf area index has been obtained by hemispherical photographs at each site. Estimates of aboveground tree biomass have been carried out using an allometric equation for moist tropical forests already applied for the study area. Additionally, a FAO standard equation has been employed for crosschecking our results. We identified significant differences in recent AGB of the three compared forest sites. With 313 (±48 Mg ha⁻¹) the highest AGB-values have been found in the preserved forest area within a National Park, followed by 297 (±83) Mg ha⁻¹ at the former clear cut site. Lowest AGB has been calculated for the area with past selective logging: 204 (±38) Mg ha⁻¹. Values calculated with the FAO standard equation showed the same trend but at a lower AGB level. Our results based an a small scale approach suggest that biomass productivity can recover in a forest which was completely cleared 60 years ago to reach AGB values up to a level that almost represents the situation in a preserved forest. Selective logging may slow down AGB accumulation and the effect is measurable after several decades.     

Seasonal variation in biomass and primary productivity of para grass (Brachiaria mutica) under a mixed tree stand and in an adjacent open area in northern India

Seasonal changes in biomass, net primary productivity and turnover of dry matter of para grass (Brachiaria mutica) under a mixed tree stand and in an adjacent open stand in northern India are presented. Both stands attained peak values of live shoot biomass in September with a higher value under mixed tree stand (665 g m^–2) than in the open stand (522 g m^–2). The net aboveground production was 590 and 527 g m^–2 yr^–1 under mixed tree stand and in the open, respectively. The belowground net primary production was also greater under mixed tree stand (100 g m^–2 yr^–1) than in the open (76 g m^–2 yr^–1). Maximum aboveground and belowground net primary productions in both stands were obtained during the rainy season. The total net primary production for para grass was about 15% higher under mixed tree stand than in the open. The turnover rates of total plant biomass were greatest in the rainy season and the least during the summer season. The system transfer functions showed that the production of para grass on both stands was aboveground-oriented, accounting for 85–87% of annual total net primary production.     

Allometric relations for biomass partitioning of Nothofagus antarctica trees of different crown classes over a site quality gradient

Data on tree biomass are essential for understanding the forest carbon cycle and plant adaptations to the environment. We determined biomass accumulation and allometric relationships in the partitioning of biomass between aboveground woody biomass, leaves and roots in Nothofagus antarctica. We measured above- and belowground biomass of N. antarctica trees across different ages (5–220 years) and crown classes (dominant, codominant, intermediate and suppressed) in three site qualities. The biomass allocation patterns were studied by fitting allometric functions in biomass partitioning between leaves (M_L), stem and branches (M_S) and roots (M_R). These patterns were tested for all pooled data and according to site quality and crown classes. Biomass accumulation varied with crown class and site quality. The root component represented 26–72% of the total biomass depending on age and site. N. antarctica scaling exponents for the relationships M_Lvs. M_S, M_Avs. M_R, and M_Svs. M_R were close to those predicted by the allometric biomass partitioning model. However, when biomass allocation was analyzed by site quality the scaling exponents varied following the optimal partitioning theory which states that plants should allocate more biomass to the part of the plant that acquires the most limiting resource. In contrast, the crown class effect on biomass partitioning was almost negligible. In conclusion, to obtain accurate estimations of biomass in N. antarctica trees the allometric approach appears as an useful tool but the site quality should be taken into consideration.     

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.     

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.     

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.     

Additive prediction of aboveground biomass for Pinus radiata (D. Don) plantations

A general and two country-specific systems of additive equations were developed to predict aboveground biomass of Pinus radiata plantations from stand variables that are routinely measured in inventory plots and predicted by conventional growth and yield models. The data for this work consisted of 319 plot-based biomass estimates that were derived from individual tree biomass equations developed in situ. These plot-based biomass estimates were compiled from studies reported in the forestry and ecological literature since 1960 and also from personal communications. They represent more than 60 sites worldwide with a majority in Australia and New Zealand. The systems of additive biomass equations developed from these data provide an alternative and addition to the current methods of estimating the aboveground biomass of P. radiata plantations. They also provide a direct linkage between forest inventory measures, outputs from conventional growth and yield models and biomass and carbon stock estimates at the same spatial scale. This direct linkage provides a new basis for scaling to a remote sensing image from which biomass and carbon stocks across the landscape can be mapped. Comparisons of prediction accuracies between this approach and other methods such as scaling up from individual tree biomass estimates and biomass expansion factors highlighted considerable methodological differences in the estimates of aboveground biomass and associated uncertainties over a range of stand age and conditions. These differences should be carefully evaluated before adopting a particular method to estimate aboveground biomass and carbon stocks of P. radiata plantations at a local, regional or national scale.     

Modeling compatible single-tree aboveground biomass equations for masson pine (Pinus massoniana) in southern China

Because of global climate change,it is necessary to add forest biomass estimation to national forest resource monitoring.The biomass equations developed for forest biomass estimation should be compatible with volume equations.Based on the tree volume and aboveground biomass data of Masson pine(Pinus massoniana Lamb.) in southern China,we constructed one-,two-and three-variable aboveground biomass equations and biomass conversion functions compatible with tree volume equations by using error-in-variable simultaneous equations.The prediction precision of aboveground biomass estimates from one variable equation exceeded 95%.The regressions of aboveground biomass equations were improved slightly when tree height and crown width were used together with diameter on breast height,although the contributions to regressions were statistically insignificant.For the biomass conversion function on one variable,the conversion factor decreased with increasing diameter,but for the conversion function on two variables,the conversion factor increased with increasing diameter but decreased with increasing tree height.     

Aboveground biomass quantification and tree-level prediction models for the Brazilian subtropical Atlantic Forest

Forests are the largest biological reservoir of biomass and carbon on the planet. This fact turns them into the main tool to neutralise the CO₂ emitted by human activities. Despite such importance, the uncertainties associated with biomass estimates in forests, especially in (sub)tropical forests, are enormous. Facing this scenario, the objectives of this study were (1) to quantify through destructive sampling the aboveground biomass (AGB) of 105 trees of 47 species occurring in a secondary subtropical evergreen rainforest in Brazil; (2) to investigate the AGB distribution in different tree compartments; and (3) to fit tree-level models to improve biomass estimates for the referred forest type. The results revealed that most of the AGB was stored in the compartments stem and large branches (diameter ≥ 5 cm). There was an increase in the proportion of biomass – in relation to the total tree AGB (kg) – allocated in the large branches as tree diameter at breast height (DBH) increased; this pattern was not observed for the compartments stem, thin branches (diameter < 5 cm), and leaves. The compartments thin branches and leaves represented between 5.4% and 17.0%, and 1.3% and 2.9% of the total tree AGB, respectively. From the 10 fitted biomass models, the linearised power models yielded the smallest errors. The best performance model, which returned a mean bias of 1.7%, may be written as AGB = exp(?8.9807 + 2.1642·ln[DBH] + 0.5072·ln[h] + 0.9999·ln[ρ_bas]); Baskerville’s factor = 1.0175. If there are no (reliable) data on tree total height (h; m), the following model, which embedded the DBH and wood basic specific gravity (ρ_bas; kg m^?3), may be employed: AGB = exp(?9.0086 + 2.4606·ln[DBH] + 1.0895·ln[ρ_bas]); Baskerville’s factor = 1.0206.     

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.     

Soil and microbial respiration in a loblolly pine plantation in response to seven years of irrigation and fertilization

Because soil CO₂ efflux or soil respiration (R_S) is the major component of forest carbon fluxes, the effects of forest management on R_S and microbial biomass carbon (C), microbial respiration (R_H), microbial activity and fine root biomass were studied over two years in a loblolly pine (Pinus taeda L.) plantation located near Aiken, SC. Stands were six-years-old at the beginning of the study and were subjected to irrigation (no irrigation versus irrigation) and fertilization (no fertilization versus fertilization) treatments since planting. Soil respiration ranged from 2 to 6 μmol m⁻² s⁻¹ and was strongly and linearly related to soil temperature. Soil moisture and C inputs to the soil (coarse woody debris and litter mass) which may influence R_H were significantly but only weakly related to R_S. No interaction effects between irrigation and fertilization were observed for R_S and microbial variables. Irrigation increased R_S, fine root mass and microbial biomass C. In contrast, fertilization increased R_H, microbial biomass C and microbial activity but reduced fine root biomass and had no influence on R_S. Predicted annual soil C efflux ranged from 8.8 to 10.7 Mg C ha⁻¹ year⁻¹ and was lower than net primary productivity (NPP) in all stands except the non-fertilized treatment. The influence of forest management on R_S was small or insignificant relative to biomass accumulation suggesting that NPP controls the transition between a carbon source and sink in rapidly growing pine systems.     

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.