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China contains 119 million hectares of natural forest, much of which is secondary forest. An accurate estimation of the biomass of these forests is imperative because many studies conducted in northeast China have only used primary forest and this may have resulted in biased estimates. This study analyzed secondary forest in the area using information from a forest inventory to develop allometric models of the aboveground biomass (AGB). The parameter values of the diameter at breast height (DBH), tree height (H), and crown length (CL) were derived from a forest inventory of 2,733 trees in a 3.5 ha plot. The wood-specific gravity (WSG) was determined for 109 trees belonging to ten species. A partial sampling method was also used to determine the biomass of branches (including stem, bark and foliage) in 120 trees, which substantially easy the field works. The mean AGB was 110,729 kg ha–1. We developed four allometric models from the investigation and evaluated the utility of other 19 published ones for AGB in the ten tree species. Incorporation of full range of variables with WSG-DBH-H-CL, significantly improved the precision of the models. Some of models were chosen that best fitted each tree species with high precision (R2 = 0.939, SEE 0.167). At the latitude level, the estimated AGBof secondary forest was lower than that in mature primary forests, but higher than that in primary broadleaf forest and the average level in other types of forest likewise. 

Species distributions and assemblage composition may be the result of trait selection through environmental filters. Here, we ask whether filtering of species at the local scale could be attributed to their hydraulic architectural traits, revealing the basis of hydrological microhabitat partitioning in a Central Amazonian forest. We analyzed the hydraulic characteristics at tissue (anatomical traits, wood specific gravity (WSG)), organ (leaf area, specific leaf area (SLA), leaf area: sapwood area ratio) and whole-plant (height) levels for 28 pairs of congeneric species from 14 genera restricted to either valleys or plateaus of a terra-firme forest in Central Amazonia. On plateaus, species had higher WSG, but lower mean vessel area, mean vessel hydraulic diameter, sapwood area and SLA than in valleys; traits commonly associated with hydraulic safety. Mean vessel hydraulic diameter and mean vessel area increased with height for both habitats, but leaf area and leaf area: sapwood area ratio investments with tree height declined in valley vs plateau species. [Correction added after online publication 29 March 2017: the preceding sentence has been reworded.] Two strategies for either efficiency or safety were detected, based on vessel size or allocation to sapwood. In conclusion, contrasting hydrological conditions act as environmental filters, generating differences in species composition at the local scale. This has important implications for the prediction of species distributions under future climate change scenarios.

The specific gravity (SG) of wood is a measure of the amount of structural material a tree species allocates to support and strength. In recent years, wood specific gravity, traditionally a forester's variable, has become the domain of ecologists exploring the universality of plant functional traits and conservationists estimating global carbon stocks. While these developments have expanded our knowledge and sample of woods, the methodologies employed to measure wood SG have not received as much scrutiny as SG's ecological importance. Here, we reiterate some of the basic principles and methods for measuring the SG of wood to clarify past practices of foresters and ecologists and to identify some of the prominent errors in recent studies and their consequences. In particular, we identify errors in (1) extracting wood samples that are not representative of tree wood, (2) differentiating wood specific gravity from wood density, (3) drying wood samples at temperatures below 100°C and the resulting moisture content complications, and (4) improperly measuring wood volumes. In addition, we introduce a new experimental technique, using applied calculus, for estimating SG when the form of radial variation is known, a method that significantly reduces the effort required to sample a tree's wood.

The specific gravity (SG) of wood is a measure of the amount of structural material a tree species allocates to support and strength. In recent years, wood specific gravity, traditionally a forester's variable, has become the domain of ecologists exploring the universality of plant functional traits and conservationists estimating global carbon stocks. While these developments have expanded our knowledge and sample of woods, the methodologies employed to measure wood SG have not received as much scrutiny as SG's ecological importance. Here, we reiterate some of the basic principles and methods for measuring the SG of wood to clarify past practices of foresters and ecologists and to identify some of the prominent errors in recent studies and their consequences. In particular, we identify errors in (1) extracting wood samples that are not representative of tree wood, (2) differentiating wood specific gravity from wood density, (3) drying wood samples at temperatures below 100°C and the resulting moisture content complications, and (4) improperly measuring wood volumes. In addition, we introduce a new experimental technique, using applied calculus, for estimating SG when the form of radial variation is known, a method that significantly reduces the effort required to sample a tree's wood.

Premise of the Study Basic wood density is an important ecological trait for woody plants. It is used to characterize species performance and fitness in community ecology and to compute tree and forest biomass in carbon cycle studies. While wood density has been historically measured at 12% moisture, it is convenient for ecological purposes to convert this measure to basic wood density, i.e., the ratio of dry mass over green volume. Basic wood density can then be used to compute tree dry biomass from living tree volume. Methods Here, we derive a new exact formula to compute the basic wood density Db from the density at moisture content w denoted Dw, the fiber saturation point S, and the volumetric shrinkage coefficient R. We estimated a new conversion factor using a global wood technology database where values to use this formula are available for 4022 trees collected in 64 countries (mostly tropical) and representing 872 species. Key Results We show that previous conversion factors used to convert densities at 12% moisture into basic wood densities are inconsistent. Based on theory and data, we found that basic wood density could be inferred from the density at 12% moisture using the following formula: Db = 0.828D12. This value of 0.828 provides basic wood density estimates 4–5% smaller than values inferred from previous conversion factors. Conclusions This new conversion factor should be used to derive basic wood densities in global wood density databases. Its use would prevent overestimating global forest carbon stocks and allow predicting better tree species community dynamics from wood density.

Rapid development of remote sensing and Light Detection and Ranging (LiDAR) technology has refined estimates of tree architecture and extrapolation of biomass across large spatial scales. Yet, current biomass maps show significant discrepancies and mismatch to independent ground data. A potential obstacle to accurate biomass estimation is the loss of information on wood density, which can vary at local and regional scales, in the extrapolation process. Here we investigate if variation in wood specific gravity (WSG) substantially impacts the distribution of above-ground biomass (AGB) across a range of scales from local plots to large regions. We collected wood cores and measured tree volume in 341 forest sites across large altitudinal and climatic gradients in Colombia. At all spatial scales, variation in WSG was substantial compared to variation in volume. Imputing study-wide average values of WSG induced regional biases in AGB estimates of almost 30%, consequently undervaluing the difference between forest areas of low and high average wood density. Further, neither stem size nor climate usefully predicted WSG when accounting for spatial dependencies among our sampling plots. These results suggest that remote sensing- and LiDAR-based projections to biomass estimates can be considerably improved by explicitly accounting for spatial variation in WSG, necessitating further research on the spatial distribution of WSG and potential environmental predictors to advance efficient and accurate large-scale mapping of biomass.

The space-time structure of a teak wood specific gravity (SG) dataset was analyzed using a mixed-effects model. Spatial correlation increased in space, a phenomenon attributable to the maturation of apical meristems, while the temporal correlation of vascular meristems decreased over time. The decay of temporal correlation over time was attributed to the diminishing crown effect on the later formed wood further away from the pith, morphogen gradient, and probably changing microenvironmental conditions. The Kronecker product was used to collect spatiotemporal data on the intricate dynamic process of the evolution of the apical and lateral meristems. The results showed that height and relative radial distance (RRD) (i.e., the flow of time with wood formation) were statistically significant factors, with their interaction showing no significance. The results confirm the usefulness of using the space-time approach to elucidate the interaction between the apical and lateral meristems, two major inherent biological systems that control tree growth and wood formation dynamics. To understand the origins of patterns that vary both temporally and spatially in the tree, future work should describe the variation of SG within the tree due to increasing height (space) and diameter (age) as a matrix; then the correlation function can be modelled.

To test whether radial variation of wood specific gravity (WSG) is controlled by tree age or tree size in teak ( Tectona grandis L.f) plantation trees, opposing different-length pith-to-bark strips which represents the differential lateral growth rate was compared using mixed-effects model which considers the heterogeneity of variances and dependency in the data to gain insight into the stochastic processes that govern the wood formation process. Various models were tested in devising an appropriate radial WSG model. Models that accounted for serial correlation in WSG data performed better than the simple structure that assumes zero correlation between measurements. The autoregressive plus random tree effect structure performed better in describing the radial variation pattern. The variability of the data related to random fluctuations during tree development and the wood formation process is modeled by the autoregressive parameter revealing the intrinsic complexity of wood formation. Since they cannot be attributed to observed factors, models should consider temporal or serial correlations when assessing wood quality. The results revealed that tree age is a decisive factor in controlling the WSG of wood, while tree size is statistically less important. Furthermore, the core wood production period varies with the growth rate. It is shown that the core wood area decreased with slow growth. Findings presented here appear to provide the first demonstration of radial variation in WSG with respect to growth rate and age for planted teak growing in Ghana.

Species-specific basic density (BD) data are necessary to improve the indirect methods of biomass determination. The density of tree components (e.g., bark, branches, roots) is studied much less than that of stem wood. Nevertheless, ignoring the specific BD values of these components in biomass calculations can lead to errors. The study aims to investigate BD variation of aboveground and belowground tree components by studying a total of 162 gray alder (Alnus incana (L.) Moench) and common alder (Alnus glutinosa (L.) Gaertn.) trees. From them, 55 stumps were excavated to determine the BD of the belowground components. Our findings reveal that the volume-weighted BD of the stem (wood and bark) and the branch density of common alder are higher compared to gray alder. Both species have similar bark density, while the BD of belowground components is higher for gray alder. The stem wood density of both species increases upward from the stump to the top. Compared to gray alders, the stems of common alders have more distinct radial within-stem density variation. According to our results, the application of default Alnus spp. wood density values recommended in the IPCC guidelines for the calculation of total biomass and carbon stock is likely causing overestimation. The BD values obtained in our study on alders’ biomass components will allow for more accurate appraisals of total biomass and carbon stock for gray and common alder forests.

The Philippines has very few studies in terms of biomass production and carbon stocks in reforestation sites and the level of emission that has been avoided due to forest protection activities. Most of carbon stock estimates being used in the country are based on secondary data or studies in other countries using the same species. The study aimed to provide a reliable assessment on the contribution of reforestation sites in biomass production and carbon stocks and the potential of these plantation to contribute to the climate change mitigation efforts in the Philippines. The guideline prepared by the Philippines' Department of Environment and Natural Resources - Forest Management Bureau (DENR-FMB) in 2021 on Forest Resources Assessment (FRA) which follows the manual of Food and Agriculture Organization of the United Nations (FAO) Forestry Department in conducting FRA was used during data collection. A tract was established in the southern portion of the reforestation site wherein the species planted in 2012 are already very prominent and their diameter at breast height (DBH) and total height were measured and their corresponding wood specific gravity were taken into account. Carbon stocks were estimated using Chave et al.'s and Brown's allometric equations. The estimated carbon stocks using Chave et al.'s formula is 542.3 tC/ha while the estimated carbon stock using Brown's formula is 2001.6 tC/ha. The results of computation using Brown's equation are considerably higher than the results using Chave et al.'s equation considering that Brown's equation only took into consideration the DBH of trees while Chave et al.'s equation included the height and wood specific gravity of each species. The study demonstrated how important our forests in terms of their roles as carbon sinks and therefore contribute to our country's efforts in climate change mitigation.