Bole Biomass Research Articles

Energy potential of Eucalyptus spp. Clone biomass. in the northern region of the legal amazon

The objective of this research was to characterize the energetic properties of the biomass of the bole and twig of clones of Eucalyptus spp. for direct burning and charcoal production. To characterize the wood of the bole and the branch, three trees were selected using the simple random method, from which discs with a thickness of 5 cm (base, middle and top), were obtained from these same trees and samples of the branch were obtained. The biomass of the bole and twig of Eucalyptus urophylla x Eucalyptus gradis presented acceptable characteristics for both direct burning and charcoal production. However, charcoal from bole biomass presented energy properties of total yield in charcoal (33.23%), fixed carbon content (63.50%), higher calorific value (7047.19 kcal/kg) and ash (0.23%) within the recommended range for quality charcoal. A carbonization rate of 500°C is recommended, as it presented a higher percentage of fixed carbon and consequently a higher calorific value and fixed carbon stock.

Estimation of above ground bole biomass and carbon stock of trees in Urhonigbe Forest Reserve, Edo State, Nigeria

Estimation of above ground bole biomass and carbon stock of trees in Urhonigbe Forest Reserve, Edo State, Nigeria

Stand-Level Variation Drives Canopy Water Storage by Non-vascular Epiphytes Across a Temperate-Boreal Ecotone

Epiphytes, including bryophytes and lichens, can significantly change the water interception and storage capacities of forest canopies. However, despite some understanding of this role, empirical evaluations of canopy and bole community water storage capacity by epiphytes are still quite limited. Epiphyte communities are shaped by both microclimate and host plant identity, and so the canopy and bole community storage capacity might also be expected to vary across similar spatial scales. We estimated canopy and bole community cover and biomass of bryophytes and lichens from ground-based surveys across a temperate-boreal ecotone in continental North America (Minnesota). Multiple forest types were studied at each site, to separate stand level and latitudinal effects. Biomass was converted into potential canopy and bole community storage on the basis of water-holding capacity measurements of dominant taxa. Bole biomass and potential water storage was a much larger contributor than outer canopy. Biomass and water storage capacity varied greatly, ranging from 9 to >900kg ha–1 and 0.003 to 0.38 mm, respectively. These values are lower than most reported results for temperate forests, which have emphasized coastal and old-growth forests. Variation was greatest within sites and appeared to reflect the strong effects of host tree identity on epiphyte communities, with conifer-dominated plots hosting more lichen-dominated epiphyte communities with lower potential water storage capacity. These results point to the challenges of estimating and incorporating epiphyte contributions to canopy hydrology from stand metrics. Further work is also needed to improve estimates of canopy epiphytes, including crustose lichens.

A comparison between traditional ordinary least-squares regression and three methods for enforcing additivity in biomass equations using a sample of Pinus radiata trees

Background: Additivity has long been recognised as a desirable property of systems of equations to predict the biomass of components and the whole tree. However, most tree biomass studies report biomass equations fitted using traditional ordinary least-squares regression. Therefore, we aimed to develop models to estimate components, subtotals and above-ground total biomass for a Pinus radiata D.Don biomass dataset using traditional linear and nonlinear ordinary leastsquares regressions, and to contrast these equations with the additive procedures of biomass estimation.Methods: A total of 24 ten-year-old trees were felled to assess above-ground biomass. Two broad procedures were implemented for biomass modelling: (a) independent; and (b) additive. For the independent procedure, traditional linear models (LINOLS) with scaled power transformations and y-intercepts and nonlinear power models (NLINOLS) without y-intercepts were compared. The best linear (transformed) models from the independent procedure were further tested in three different additive structures (LINADD1, LINADD2, and LINADD3). All models were evaluated using goodness-of-fit statistics, standard errors of estimates, and residual plots.Results: The LINOLS with scaled power transformations and y-intercepts performed better for all components, subtotals and total above-ground biomass in contrast to NLINOLS that lacked y-intercepts. The additive model (LINADD3) in a joint generalised linear least-squares regression, also called seemingly unrelated regression (SUR), provided the best goodness-of-fit statistics and residual plots for four out of six components (stem, branch, new foliage and old foliage), two out of three subtotals (foliage and crown), and above-ground total biomass compared to other methods. However, bark, cone and bole biomass were better predicted by the LINOLS method.Conclusions: SUR was the best method to predict biomass for the 24-tree dataset because it provided the best goodness-of-fit statistics with unbiased estimates for 7 out of 10 biomass components. This study may assist silviculturists and forest managers to overcome one of the main problems when using biomass equations fitted independently for each tree component, which is that the sum of the biomasses of the predicted tree components does not necessarily add to the total biomass, as the additive biomass models do.

Economics of integrated harvests with biomass for energy in non-industrial forests in the northeastern US forest

Economic drivers explaining the harvest of biomass for energy use in northeastern forests in the United States are not well understood. However, knowledge of these drivers is essential for bioenergy policy development, biomass supply estimates, and assessments of harvesting impacts on forest ecosystems and carbon stocks. Using empirical data from 35 integrated harvest sites in northeastern US non-industrial forests, we analyzed the economics of mixed wood product logging operations that included biomass for energetic use from both landowner and logging contractor perspectives. Results were highly variable but indicate that biomass harvest removal intensities were not explained by primary forest management objectives, harvest area, or harvested wood product quantity. Rather than harvest area or choice of machinery, we identified biomass harvest intensity as a main driver of profits for a harvest operation, as measured in hourly and total net income to the logging contractor. While biomass stumpage payments to the landowner were marginal, tree bole biomass constituted more than half (54%) of the extracted volume by weight, far outweighing biomass derived from tops and limbs only. Biomass harvests, therefore, might encourage logging contractors to intensify harvest removals rather than increase harvest area or choose a specific harvest type or method. Such intensification could have beneficial or detrimental impacts on a stand and needs to be addressed through further studies of potential consequences for biodiversity and various ecosystem services.

Accounting tropical forest carbon stock with synergistic use of space-borne ALOS PALSAR and COSMO-Skymed SAR sensors

The objective of this study is to precisely quantify the forest aboveground biomass (AGB) and carbon stock in a tropical deciduous forest with synergistic use of space-borne L-band ALOS PALSAR and X-band COSMO-Skymed SAR data, along with field inventory data. AGB serves as a decisive parameter for preparing global decision making policy targeting the impact of reducing emissions from deforestation and forest degradation and climate change. The study proposed optimal regression models for assessing above-ground bole biomass over tropical deciduous mixed forests of Munger (Bihar, India) with synergistic use of ALOS PALSAR and COSMO-Skymed sigma nought images. Coefficient of determination (r2) of 0.89 and RMSE of 15.12 Mg ha−1 were calculated for the best fit integrated model. On validation, the integrated model produced a model accuracy of 78%, r2 = 0.89, RMSE = 16.64 Mg ha−1 and Willmott’s index of agreement of 0.934. Resulting modeled AGB were converted to carbon and carbon dioxide equivalents using conversion factors. L-band showed higher accuracy in the estimation in comparison to X-band; but the estimation accuracy improved with the synergistic use of both X- and L-band SAR data. Hence, the study recommends the combined use of X- and L-band SAR with exceptional capabilities for improved assessment of tropical forest stand AGB and carbon with significant contribution towards operational forestry and policy making.

Investment Uncertainty Analysis in Eucalyptus Bole Biomass Production in Brazil

Forestry investment projects for the biomass production of the eucalyptus bole can be characterized by uncertain environments, which result in economic risk to the forest producer, however that can be measured by applying probabilistic techniques. This was our motivation and justification for analyzing the economic-financial viability of different silvicultural practices for eucalyptus bole biomass production under conditions of uncertainties, running Monte Carlo method for risk management. The experiment was carried out in the state of São Paulo, Brazil, using 5 treatments with spacings of 3 × 2 m; 3 × 1 m; 1.5 × 2 m; 3 m × 0.5 m; and 1.5 m × 1.0 m, i.e., different spacings between planting lines and plants. These treatments were characterized as investment projects. To develop stochastic models, we relied on technical-economic deterministic variables. We evaluated the investment projects based on the cash flows under conditions of uncertainty, discounted at the attractiveness rate calculated by capital asset pricing model. With the results of these economic flows, the net present value, the modified internal rate of return and the profitability index values were estimated, commonly used in the analysis of investments in projects. The results showed that based on economic metrics, the three-year rotation cycle for forest stands for biomass production of the main bole of eucalyptus, with a spacing of three meters between rows and two meters between plants, had an 83% probability of economic success. The sensitivity analysis showed that the bole biomass of eucalyptus is the most important variable for determining the economic-financial feasibility of the investment project.

Local and General Above-Ground Biomass Functions for Pinus palustris Trees

There is an increasing interest in estimating biomass for longleaf pine (Pinus palustris Mill.), an important tree species in the southeastern U.S. Most of the individual-tree allometric models available for the species are local, relying on stem diameter outside bark at breast height (DBH) and total tree height (HT), but seldom include stand-level variables such as stand age, basal area or stand density. Using the biomass dataset of 296 longleaf pine trees sampled in the southeastern U.S. by different forestry research institutions, we developed a set of local and general systems of tree biomass equations to predict total tree total above-stump biomass, bole biomass outside bark, live branch biomass and live foliage biomass. The local systems were based on DBH or DBH and HT, and the general systems included in addition to DBH and HT, stand-level variables such as age, basal area and stand density. This paper reports the first set of general allometric equations reported for longleaf pine trees. These systems of biomass equations provide tools to support managers in making management decisions for the species in a variety of ecological, silvicultural and economics applications. The systems can be applied to trees growing over a large geographical area and having a wide range of ages and stand characteristics.

Carbon Dynamics in Quercus semecarpifolia (Kharsu Oak) and Quercus floribunda (Moru Oak) Forests of Garhwal Himalaya, India

Oaks are the canopy forming, climax keystone species of moist temperate forest of Garhwal Himalaya whose biomass and carbon cycling data is obscure. Patterns of biomass and carbon pool of Quercus semecarpifolia (Kharsu Oak) and Quercus floribunda (Moru Oak) were quantified in Garhwal Himalaya. The dead organic matter (DOM) contributed 9.13 and 8.66% to the carbon pool in Kharsu Oak and Moru Oak forests respectively. The bole biomass contributed 71% (282.01 Mg/ha) and 59% (280.51 Mg/ha) and stump-root biomass contributed 62% (70.34 Mg/ha) and 60% (68.60 Mg/ha) significantly to the live carbon respectively in above two forests. Oak forests have great potential for enhanced future carbon stocks suggesting the relevance of DOM as a significant contributor to carbon pool in Oaks of Garhwal Himalaya.

LIDAR-based estimation of bole biomass for precision management of an Amazonian forest: Comparisons of ground-based and remotely sensed estimates

Abstract Based on airborne LIDAR data on canopy morphology and height of Amazon forest trees, we developed allometric models to estimate dry biomass stored in the boles of dominant and co-dominant individuals and compared these results with those from equations based on traditional variables such as diameter at breast height (DBH). The database consisted of 142 trees of interest for logging in a forest under management for timber in Brazil's state of Acre. The trees chosen for study were selected through proportional sampling by diameter class (ranging from 45 to 165 cm DBH) in order to properly represent the dominant and co-dominant tree populations with diameters appropriate for harvest. Subsequent to LIDAR profiling of these trees, they were felled, subjected to a battery of dimensional measurements and sampled for wood-density determination. A set of models was generated, followed by model selection and identity testing in order to compare groups of basic wood density (low, medium and high). The morphometric variables of the crown had high explanatory power for bole biomass independent of whether the allometric equations included DBH. When calculating bole biomass with equations that include basic wood density, the best estimate is obtained using variables for both DBH and crown morphology. To obtain an allometric equation that encompasses species in all three classes of basic density, one should either use only independent variables representing crown dimensions or complement these with variables for basic density (BD) and total height (Ht). The study demonstrates the feasibility of using ground-based measurements to calibrate biomass models that include only LIDAR-based variables, allowing much larger areas to be surveyed with reasonable accuracy. The present study is designed to produce data needed for forest management, but the methods developed here can be adapted to studies aimed at reducing the uncertainty in biomass estimates of whole forests (not just harvestable trees) for use in quantifying carbon emissions from forest loss and degradation.

Developing synergy regression models with space-borne ALOS PALSAR and Landsat TM sensors for retrieving tropical forest biomass

Forest stand biomass serves as an effective indicator for monitoring REDD (reducing emissions from deforestation and forest degradation). Optical remote sensing data have been widely used to derive forest biophysical parameters inspite of their poor sensitivity towards the forest properties. Microwave remote sensing provides a better alternative owing to its inherent ability to penetrate the forest vegetation. This study aims at developing optimal regression models for retrieving forest above-ground bole biomass (AGBB) utilising optical data from Landsat TM and microwave data from L-band of ALOS PALSAR data over Indian subcontinental tropical deciduous mixed forests located in Munger (Bihar, India). Spatial biomass models were developed. The results using Landsat TM showed poor correlation (R 2 = 0.295 and RMSE = 35 t/ha) when compared to HH polarized L-band SAR (R 2 = 0.868 and RMSE = 16.06 t/ha). However, the prediction model performed even better when both the optical and SAR were used simultaneously (R 2 = 0.892 and RMSE = 14.08 t/ha). The addition of TM metrics has positively contributed in improving PALSAR estimates of forest biomass. Hence, the study recommends the combined use of both optical and SAR sensors for better assessment of stand biomass with significant contribution towards operational forestry.

Developing Biomass Equations for Western Hemlock and Red Alder Trees in Western Oregon Forests

Biomass estimates are required for reporting carbon, assessing feedstock availability, and assessing forest fire threat. We developed diameter- and height-based biomass equations for Western hemlock (Tsuga heterophylla (Raf.) Sarg.) and red alder (Alnus rubra Bong.) trees in Western Oregon. A system of component biomass equations was fitted simultaneously with a constrained seemingly unrelated regression. Additionally, a linear model that predicts total aboveground biomass as a function of DBH and height was also fitted. The predicted total biomass was then apportioned to different components according to the predicted proportions from beta, Dirichlet, and multinomial log-linear regressions. Accuracy of these methods differed between species with higher root mean squared error (RMSE) being produced in red alder trees. Within species, the accuracy of the equation for bole biomass was better than the equations for other components. None of these methods stood out as a clear winner, but the multinomial log-linear regression produced marginally better results compared to other methods in terms of RMSE, except for Western hemlock bark biomass and red alder bole and branch biomass. The equations based on a seemingly unrelated regression provided lower RMSEs for those species-component combinations.

ALLOMETRIC MODELS FOR ESTIMATING ABOVEGROUND BIOMASS AND BIOMASS ALLOCATION OF CAPIXINGUI TREES (Croton floribundus Spreng.) IN AN AGRISILVICULTURAL SYSTEM

ABSTRACT The objective of this study was to select allometric models to estimate total and pooled aboveground biomass of 4.5-year-old capixingui trees established in an agrisilvicultural system. Aboveground biomass distribution of capixingui was also evaluated. Single- (diameter at breast height [DBH] or crown diameter or stem diameter as the independent variable) and double-entry (DBH or crown diameter or stem diameter and total height as independent variables) models were studied. The estimated total biomass was 17.3 t.ha-1, corresponding to 86.6 kg per tree. All models showed a good fit to the data (R2ad > 0.85) for bole, branches, and total biomass. DBH-based models presented the best residual distribution. Model lnW = b0 + b1* lnDBH can be recommended for aboveground biomass estimation. Lower coefficients were obtained for leaves (R2ad > 82%). Biomass distribution followed the order: bole>branches>leaves. Bole biomass percentage decreased with increasing DBH of the trees, whereas branch biomass increased.

Cumulative continuous predictions for bole and aboveground woody biomass in Eucalyptus globulus plantations in northwestern Spain

At present there is increasing interest in modelling biomass to estimate carbon sequestration or the availability of forest products for use as bioenergy. The biomass of different tree components can be estimated to provide more detailed information. However, the different components have not been clearly defined. Moreover, the greater the number of components considered, the more difficult it is to fit the system of equations with any guarantee of statistical robustness. To overcome these limitations, we developed a continuous function that predicts cumulative biomass from the stump until any top diameter (including the biomass of branches). We also used two different methods to predict bole biomass: a cumulative continuous biomass function and conversion from volume to biomass by use of a taper equation and average wood density. We used a mixed-effects modelling framework to account for correlated errors in developing the taper equation. We developed a separate equation to estimate the foliar biomass for use in estimating total aboveground tree biomass. The cumulative aboveground woody biomass equation is implicitly additive, and no heteroscedasticity was observed, thereby resolving two of the main modelling goals in the development of biomass equations. For predicting cumulative bole biomass, estimation from volume generated less error, after bias correction, than direct estimation. Moreover, the indirect method also yields useful variables such as volume and height limits. Other variables such as carbon and nutrient contents, calorific power, ash content, etc. can be estimated by multiplying the mean contents by the predicted biomass or, for more accurate predictions, by using equations based on the relative diameter.

Inter-annual variability and spatial coherence of net primary productivity across a western Oregon Cascades landscape

Inter-annual variability (IAV) of forest Net Primary Productivity (NPP) is a function of both extrinsic (e.g., climate) and intrinsic (e.g., stand dynamics) drivers. As estimates of NPP in forests are scaled from trees to stands to the landscape, an understanding of the relative effects of these factors on spatial and temporal behavior of NPP is important. Although a high degree of spatial coherence (i.e., the degree of spatial synchrony over time) is often assumed, this inherent behavior is rarely examined. Quantifying this term may improve future predictions as site-level estimates are scaled up spatially. We quantified the spatial coherence of bole biomass production (BBP) within and between trees, and bole-related NPP (NPPB) between sites of varying age, elevation, moisture, and species composition across a forested landscape in the western Cascade Range of Oregon. Within sites, individual trees with lower than average BBP were the most coherent. IAV of BBP increased as average tree BBP increased and spatial coherence was reduced. Among sites, NPPB was the most spatially coherent (r=0.92) between young sites, while older sites and comparisons between age classes revealed a much larger range in spatial coherence (r=−0.18 to 0.85). Our findings indicate climate variability may be of greater importance for spatial coherence between young sites, and that intrinsic factors could be decreasing spatial coherence between older sites or sites not in close proximity. The wide range in spatial coherence between sites found in this study, coupled with the complex land use history patterns across forested landscapes, has significant implications for modeling and scaling of NPP.

Allometric equations for predicting aboveground biomass of beech-hornbeam standsin the Hyrcanian forests of Iran

A better understanding of the carbon biomass from forests is needed to improve both models and mitigation efforts related to the global C cycle and greenhouse gas mitigation. Despite the importance of Hyrcanian forests for biodiversity conservation, no study with biomass destruction has been done to predict biomass and carbon pools from this forest. Mixed-specific regression equations with 45 sample trees using different input variables such as diameter, height and wood density were developed to estimate the aboveground biomass of beech-hornbeam stands. All the sample trees were harvested and the diameter at breast height (DBH) spanned from 31 to 104 cm so as to represent the diameter distribution reported in the beech-hornbeam stand management. Using only diameter as an input variable, the stands regression model estimates the aboveground biomass of the stand with an average deviation of 19% (R<sup>2</sup><sub>adj</sub> = 0.92; SEE = 0.22). Adding height as the second explanatory variable slightly improved the estimation with an average deviation of 18% (R<sup>2</sup><sub>adj</sub> = 0.95; SEE = 0.17). Adding only height or wood density did not improve significantly the estimations. Using the three variables together improved the precision of bole biomass prediction of stands with an average deviation of 10.3% (R<sup>2</sup><sub>adj</sub> = 0.965; SEE = 0.167). 68% of the observed variation in the aboveground biomass of beech-hornbeam stands was explained only by diameter.  

Estimating attributes of deciduous forest cover of a sanctuary in India utilizing Hyperion data and PLS analysis

Continuous and comprehensive evaluation of biochemical and biophysical attributes of forest ecosystems is a key aspect for monitoring their health status in the current global change scenario. Traditional methods of monitoring forest cover such as inventorying are time consuming, cost intensive, and untimely in delivering the output. The present study was carried out to monitor three important deciduous forest covers of India (teak, bamboo, and mixed), utilizing Hyperion (EO1) data of two seasons and partial least squares regression analysis. Attributes measured were canopy chlorophyll, nitrogen, cellulose, lignin, and biomass of tree trunks. Measured attributes showed a wider range, indicating variation in the growth phase of the covers. PLS models developed in this study showed higher R2 values (0.63–0.90 for chlorophyll and nitrogen, 0.52–0.80 for cellulose and lignin, 0.80–0.86 for bole biomass). From the spectral data analysis we conclude that PLS regression with selected bands is better for the computation of specific biochemical parameters. For parameters such as bole biomass, reflectance spectra of 165 bands worked better. Developed models are advantageous for monitoring two important tropical covers (teak and bamboo) by utilizing space-borne data. A PLS model developed for teak-cover biomass worked well with mixed species cover (tested as an independent data set), indicating the applicability of the model across similar tropical covers.

Greater risk of physical damage caused by debris fall to understory plants and tree seedlings in old-growth forests than in young forests

Falling canopy debris causes injury and mortality of tree seedlings and understory plants in a wide variety of forests. Canopy structure and dynamics differ between young and old-growth forests: old forests are taller and have more aboveground biomass and greater annual mortality of bole biomass. I predicted that risk of damage caused by debris fall in the understory is greater in old-growth forests than in young forests. I tested this prediction by tracking for 1 year the fates of artificial seedlings placed in young (stand age 31 to 61 years) and old-growth (stand age circa 500 years) Pseudotsuga–Tsuga forests. The risk of physical damage caused by debris fall in old-growth forests was significantly greater than in young forests (P = 0.001). Seedling models were damaged by falling debris at a rate of 4.4%·year−1 and 0.8%·year−1 in old-growth and young forests, respectively. More seedling models were damaged by fallen coarse woody debris in old-growth forests than in young forests, although this trend was not significant (P = 0.134). Approximately 25% of seedling models in both young and old-growth forests were damaged by something other than fallen canopy debris, most likely snow accumulation.

Estimation of Merchantable Bole Volume and Biomass above Sawlog Top in the National Forest Inventory of the United States

Emerging markets for small-diameter roundwood along with a renewed interest in forest biomass for energy have created a need for estimates of merchantable biomass above the minimum sawlog top diameter for timber species in the national forest inventory of the United States. The Forest Inventory and Analysis (FIA) program of the USDA Forest Service recently adopted the component ratio method for estimation of aboveground live tree component biomass, which incorporates regionally specific volume models by species and species group. The merchantable bole component is the biomass of sound wood from a 1.0-ft stump height to a minimum 4.0-in. top diameter. Minimum sawlog top diameters for softwoods and hardwoods in the FIA program are substantially larger than the merchantable bole top diameter, leaving additional bole biomass potentially available for utilization. This article describes a method for estimating merchantable bole biomass for the sawlog component and the component above the minimum sawlog top diameter for timber species in the FIA program.

Canopy closure exerts weak controls on understory dynamics: a 30‐year study of overstory–understory interactions

Stem exclusion and understory reinitiation are commonly described, but poorly understood, stages of forest development. It is assumed that overstory trees exert strong controls on understory herbs and shrubs during the transition from open‐ to closed‐canopy forests, but long‐term observations of this process are rare. We use long‐term data from 188 plots to explore patterns and correlates of variation in understory richness and abundance 15–45 years after clear‐cut logging and burning of two experimental watersheds in western Oregon, USA. We test whether variation in the temporal dynamics of plots can be explained by topoedaphic factors that influence resource availability (insolation and soil moisture), variation in the pace and intensity of overstory development, or characteristics of the vegetation prior to canopy closure. Changes in forest structure were substantial over the study period; canopy cover increased fourfold, stem density by 75%, and bole biomass by two orders of magnitude, although trends were highly variable among individual plots. In contrast, understory richness, foliar cover, and biomass declined only 30–40%, driven by loss of early‐seral colonists, not residual forest species. Canopy closure occurred earlier on north aspects but declines in understory biomass, reflecting loss of colonizing shrubs (without concomitant increases in forest shrubs), were limited to south aspects. In contrast, variation in effective soil moisture had little influence on the pace of decline. Temporal trends were highly asynchronous among plots: nearly 50% of plots experienced some form of decline, but >35% showed no discernible trend. Declines were more likely in plots with greater tree influence before or at peak overstory development, but also in plots with greater understory development prior to canopy closure. Quantile regression models indicated weak relationships between understory biomass and overstory structure at most points in time. Our long‐term data support a model of understory dynamics in which characteristics of the pre‐closure vegetation are as important as overstory structure in determining the timing and nature of decline. Long‐term studies are critical for elucidating patterns and processes that cannot be inferred from short‐term experiments or space‐for‐time substitutions.