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The precise estimation of sugarcane yield at the field scale is urgently required for harvest planning and policy-oriented management. Sugarcane yield estimation from satellite remote sensing is available, but satellite image acquisition is affected by adverse weather conditions, which limits the applicability at the field scale. Secondly, existing approaches from remote sensing data using vegetation parameters such as NDVI (Normalized Difference Vegetation Index) and LAI (Leaf Area Index) have several limitations. In the case of sugarcane, crop yield is actually the weight of crop stalks in a unit of acreage. However, NDVI's over-saturation during the vigorous growth period of crops results in significant limitations for sugarcane yield estimation using NDVI. A new sugarcane yield estimation is explored in this paper, which employs allometric variables indicating stalk magnitude (especially stalk height and density) rather than vegetation parameters indicating the leaf quantity of the crop. In this paper, UAV images with RGB bands were processed to create mosaic images of sugarcane fields and estimate allometric variables. Allometric equations were established using field sampling data to estimate sugarcane stalk height, diameter, and weight. Additionally, a stalk density estimation model at the pixel scale of the plot was created using visible light vegetation indices from the UAV images and ground survey data. The optimal stalk density estimation model was applied to estimate the number of plants at the pixel scale of the plot in this study. Then, the retrieved height, diameter, and density of sugarcane in the fields were combined with stalk weight data to create a model for estimating the sugarcane yield per plot. A separate dataset was used to validate the accuracy of the yield estimation. It was found that the approach presented in this study provided very accurate estimates of sugarcane yield. The average yield in the field was 93.83 Mg ha−1, slightly higher than the sampling yield. The root mean square error of the estimation was 6.63 Mg ha−1, which was 5.18% higher than the actual sampling yield. This study offers an alternative approach for precise sugarcane yield estimation at the field scale. [ABSTRACT FROM AUTHOR]

Background: Carbon (C) sink and stock are among the most important ecosystem services provided by forests in climate change mitigation policies. In this context, old-growth forests constitute an essential reference point for the development of close-to-nature silviculture, including C management techniques. Despite their small extent in Europe, temperate old-growth forests are assumed to be among the most prominent in terms of biomass and C stored. However, monitoring and reporting of C stocks is still poorly understood. To better understand the C stock amount and distribution in temperate old-growth forests, we estimated the C stock of two old-growth stands in the Dinaric Alps applying different assessment methods, including direct and indirect approaches (e.g., field measurements and allometric equations vs. IPCC standard methods). This paper presents the quantification and the distribution of C across the five main forest C pools (i.e., aboveground, belowground, deadwood, litter and soil) in the study areas and the differences between the applied methods. Results: We report a very prominent C stock in both study areas (507 Mg C ha− 1), concentrated in a few large trees (36% of C in 5% of trees). Moreover, we found significant differences in C stock estimation between direct and indirect methods. Indeed, the latter tended to underestimate or overestimate depending on the pool considered. Conclusions: Comparison of our results with previous studies and data collected in European forests highlights the prominence of temperate forests, among which the Dinaric Alps old-growth forests are the largest. These findings provide an important benchmark for the development of future approaches to the management of the European temperate forests. However, further and deeper research on C stock and fluxes in old-growth stands is of prime importance to understand the potential and limits of the climate mitigation role of forests. [ABSTRACT FROM AUTHOR]

Owing to their important roles in biogeochemical cycles, phytoplankton functional types (PFTs) have been the aim of an increasing number of ocean color algorithms. Yet, none of the existing methods are based on phytoplankton carbon (C) biomass, which is a fundamental biogeochemical and ecological variable and the "unit of accounting" in Earth System models. We present a novel bio-optical algorithm to retrieve size-partitioned phytoplankton carbon from ocean color satellite data. The algorithm is based on existing algorithms to estimate particle volume from a power-law particle size distribution (PSD). Volume is converted to carbon concentrations using a compilation of allometric relationships. We quantify absolute and fractional biomass in three PFTs based on size - picophytoplankton (0.5-2 µm in diameter), nanophytoplankton (2-20 µm) and microphytoplankton (20-50 µm). The mean spatial distributions of total phytoplankton C biomass and individual PFTs, derived from global SeaWiFS monthly ocean color data, are consistent with current understanding of oceanic ecosystems, i.e. oligotrophic regions are characterized by low biomass and dominance of picoplankton, whereas eutrophic regions have large biomass to which nanoplankton and microplankton contribute relatively larger fractions. Global spatially integrated phytoplankton carbon biomass standing stock estimates using our PSD-based approach yield on average ~0.2-0.3 Gt of C, consistent with analogous estimates from two other ocean color algorithms, and several state-of-the-art Earth System models. However, the range of phytoplankton C biomass spatial variability globally is larger than estimated by any other models considered here, because the PSD-based algorithm is not a priori empirically constrained and introduces improvement over the assumptions of the other approaches. Satisfactory in situ closure observed between PSD and POC measurements lends support to the theoretical basis of the PSD-based algorithm. Uncertainty budget analyses indicate that absolute carbon concentration uncertainties are driven by the PSD parameter No which determines particle number concentration to first order, while uncertainties in PFTs' fractional contributions to total C biomass are mostly due to the allometric coefficients. [ABSTRACT FROM AUTHOR]

Ecologically and economically sustainable planning of forest resources requires tools capable of providing estimates with adequate accuracy on volume, biomass and woody increments. Interest in these attributes has increased since the United Nations Framework Convention on Climate Change has been given a further boost by the birth of the carbon credit market in the early 2000s. However, the data collection necessary to formulate allometric models for estimating wood volume is challenging, both due to the considerable amount of data required and because the necessary destructive measurements are very laborious. Furthermore, given the great structural, managerial and environmental diversity that characterizes the Italian forests, the sample size for the development of allometric models must necessarily be large. Over the years, all these aspects have led to a progressive abandonment of measurements in the forests for the production of volume tables. Recent applications of the terrestrial laser scanner (TLS) for collecting dimensional information on trees have demonstrated their effectiveness. In this study we present the work carried out in the autumn/winter 2022-2023 for the creation of new volume tables for the black pine forests in Vallombrosa (FI -- Central Italy), based on data collected with a TLS. The study involved the same pine forests studied in 1969 for the production of volume tables in Vallombrosa. After showing the methods and analysis needed to obtain the volume tables, the paper discusses the results in comparison with those produced in 1969. [ABSTRACT FROM AUTHOR]

The increasing level of atmospheric carbon dioxide and its effects on our climate system has become a global environment issue. The forest ecosystem is essential for the stability of carbon in the atmosphere as it operates as a carbon sink and provides a habitat for numerous species. Therefore, our understanding of the structural elements of the forest ecosystem is vital for the estimation of forest biomass or terrestrial carbon stocks. Over the last two decades, light detection and ranging (LIDAR) technology has significantly revolutionized our understanding of forest structures and enhanced our ability to monitor forest biomass. This paper presents a review of metrics for forest biomass estimation, outlines metrics selection methods for biomass modeling, and addresses various assessment criteria for the selection of allometric equations for the aboveground forest biomass estimations, using LIDAR data. After examining one hundred publications written by different authors between 1999 and 2023, it was observed that LIDAR technology has become a dominant data collection tool for aboveground biomass estimation with most studies focusing on the use of airborne LIDAR data for the plot-level analysis on a local scale. Parametric-based models dominated in most studies with coefficient of determination (R2) and root mean square error (RMSE) as assessment criteria. In addition, mean top canopy height (MCH) and quadratic mean height (QMH) were reported as strong predictors for aboveground biomass (AGB) estimation. Pixel-based uncertainty analysis was found to be a reliable method for assessing spatial variations in uncertainties. [ABSTRACT FROM AUTHOR]

Plot-based monitoring has yielded much information on the taxonomic diversity and carbon (C) storage in tropical lowland forests of the Amazon basin. This has resulted in an improved understanding of the relationship between lowland forest biomass dynamics and global change drivers, such as climate change and atmospheric CO2 concentration. Much less attention has been paid to the mountain ecosystems of South America that comprise montane forests and alpine vegetation (páramo, puna, high Andean grasslands, wetlands, and alpine heath). This vegetation complex provides a variety of ecosystem services and forms a natural laboratory along various physiographic, geological and evolutionary history/biogeography, and land use history gradients. Here, we review existing empirical understanding and model-based approaches to quantify the contribution of mountain ecosystems to ecosystem service provision in the rapidly changing socioecological setting of the South American mountains. The objective of this paper is to outline a broad road map for the implementation of mountain vegetation into dynamic global vegetation models (DGVM) for use in Earth System Models (ESM), based on our current understanding of their structure and function and of their responsiveness to global change drivers. We also identify treeline processes, critical in mountain ecosystems, as key missing elements in DGVMs/ESMs, and thus explore in addition a treeline model. Stocktaking of the availability of empirical data was undertaken from eight research sites along the Andes and in south-eastern Brazil. Out of eight sites, two (one each in Venezuela and Brazil) had some climate, ecological and ecophysiological data potentially suitable to parametrise a DGVM. Tree biomass data were available for six sites. A preliminary assessment of the Joint UK Land Environment Simulator (JULES) DGVM was made to identify gaps in available data and their impacts on model parametrisation and calibration. Additionally, the potential climate-determined elevation of the treeline was modelled to check the DGVM for its ability to identify the transition between the montane forest and alpine vegetation. Outcomes of the evaluation of the JULES land surface model identified the following key processes in montane forests: temperature-related decrease in net primary production, respiration, and allocation to above-ground biomass and increase in soil C stocks with elevation. There was a variable agreement between simulated biomass and those derived from field measurements via allometric equations. We identified major gaps between data availability and the needs for process-based modelling of South American mountain vegetation and its dynamics in DGVMs. To bridge this gap, we propose a transdisciplinary network, composed of members of the theoretical/modelling and empirical scientific communities, to study the natural dynamics of mountain ecosystems and their responses to global change drivers locally, regionally and at the continental scale, within a social-ecological system framework. The work presented here forms the basis for the design of data collection from field measurements and instrumental monitoring stations to parametrise and verify DGVMs. The network is designed to collaborate with and complement existing long-term research initiatives in the region and will adopt existing standard field protocols. Complementary protocols will ensure compatibility between field data collection and data needed for process-based and empirical models. [ABSTRACT FROM AUTHOR]

In order to reduce the impact of global warming, forestry carbon sink trading is an effective approach to achieving carbon neutrality, while carbon storage estimation plays an important role as the basis of the whole carbon sink trading. Therefore, an accurate estimation of carbon storage is conducive to the sustainable development of carbon sink trading. In this paper, we use laser SLAM technology to model an artificial forest in three dimensions, extract the tree parameters by the point cloud processing software, and calculate the carbon storage according to the allometric growth equation of the tree species. The experimental results show that the loop path is the best among the three-path planning of ZEB-HORIZON scanner data acquisition. For large-scale plantations, the fusion data acquisition of linear and loop paths by Livox Mid-40 and ZEB-HORIZON LIDAR can be adopted with a highly precise and a complete 3D point cloud obtained. The Lidar360 software is used for single wood segmentation and parameter extraction, and the manual measurement is taken as the quasi-true value. After the measurement accuracy analysis, the carbon storage estimation is met. Using the volume source biomass method in the sample plot inventory method, the carbon storages of camphor and cypress in the experimental area were estimated through the allometric growth equation of camphor and cypress and the international conversion rate. [ABSTRACT FROM AUTHOR]

Bamboo forest is a special forest type, and its aboveground biomass (AGB) is a key indicator of its carbon sequestration capacity and ecosystem productivity. Due to its complex canopy structure and particular growth pattern, the AGBs of individual bamboos that were estimated using traditional remotely sensed data are of relatively low accuracy. In recent years, the point cloud data scanned by terrestrial laser scanners (TLS) offer the possibility for more accurate estimations of bamboo AGB. However, bamboo culms tend to have various bending degrees during the growth process, which causes the AGB estimated on culm height (H) to be generally less than the true value. In this paper, taking one sample plot of the Moso bamboo forest in Hutou Village, Chongqing, China as the study site, we employed a TLS to acquire the point cloud data. The layer-wise distance discrimination method was first developed to accurately segment individual bamboos from the dense stand. Next, the diameter at breast height (DBH) and culm length (L) of an individual bamboo were precisely extracted by fitting the cross-section circle and constructing the longitudinal axis of the bamboo culm, respectively. Lastly, the AGBs of the Moso bamboos in the study site were separately calculated using the allometric equations with the DBH and L as predictor variables. As results, the precision of the complete bamboo segmentation was 90.4%; the absolute error ( A E ) of the extracted DBHs ranged from −1.22 cm to 0.88 cm ( R 2 = 0.93, R M S E = 0.40 cm); the A E of the extracted Hs varied from –0.77 m to 1.02 m ( R 2 = 0.91, R M S E = 0.45 m); and the A E of the extracted Ls varied from −1.08 m to 0.77 m ( R 2 = 0.95, R M S E = 0.23 m). The total estimated AGB of the Moso bamboos in the sample plot increased by 2.85%, from 680.40 kg on H to 696.36 kg on L. These measurements demonstrated the unique benefits of the TLS-acquired point cloud in characterizing the structural parameters of Moso bamboos and estimating their AGBs with high accuracy. [ABSTRACT FROM AUTHOR]

Key message: In this paper it is shown that a simultaneous adjustment provides more efficient estimates of total tree biomass than with independent modelling for biomass estimates by compartments (canopy, bole and roots). Context: When modeling tree biomass, it is important to consider the additivity property, since the total tree biomass must be equal to the sum of the biomass of the components. Objective: The aim of this study was to assess the simultaneous estimation performance, considering the additivity principle with respect to independent estimate when modeling biomass components and total biomass. Methods: Individual modeling of total biomass and biomass components of leaves, branches, bole without bark, bole bark, and roots was performed on Pinus elliottii Engelm trees derived from forest stands in southern Brazil. Five nonlinear models were tested, and the best performance for estimating the total biomass of each component was selected, characterizing the independent estimation. The models selected for each component were fitted using the nonlinear seemingly unrelated regression method, which characterizes simultaneous estimation. Results: Independent fitting of coefficients for biomass components and total biomass was not satisfactory, as the sum of the biomass component estimates diverged from the total biomass. This was not observed when the simultaneous fitting was used, which takes into account the additivity principle, and resulted in more effective estimators. Conclusion: The simultaneous estimation method must be used in modeling tree biomass. [ABSTRACT FROM AUTHOR]

This paper investigates the consequences of ignoring the clustered data structure on allometric models. Clustered data, in the form of multiple trees sampled from multiple forest stands is commonly used to develop biomass allometric models. Of 102 reviewed papers published between 2012 and 2016 that reported biomass allometric models, 84 (82%) have used a clustered sampling design. However, in as many as 80% of these, the clustered data structure was ignored, potentially violating the independence assumption in ordinary least squares methods. The consequences of ignoring clustered data structure were empirically validated using two clustered biomass datasets (of 110 and 220 trees, with the cluster size of 5 and 10 trees respectively). We showed that when Intraclass Correlation Coefficient (ICC) was higher than zero, ignoring the clustered data structure returned underestimated standard errors, affecting further the confidence interval and t-test results. The underestimation level depended on ICC (which shows the variance proportion that was caused by the forest stand) and on cluster size (the number of trees sampled from one forest stand). We also showed that using first-order autocorrelation tests, such as the traditional Durbin-Watson statistic, to detect the autocorrelation due to clustered structure could be misleading as the test may show lack of autocorrelation even though ICC is different from zero. In conclusion, when ICC is higher than zero, ignoring the clustered data structure yields over-confident biomass predictions (due to underestimated confidence interval) and/or incorrect research conclusions (due to overestimated evidence against null hypothesis in t-test). Therefore, using a modelling approach that accounts for the hierarchical structure of the data is highly recommended when any form of clustering can be identified, even if the autocorrelation is not significant. [ABSTRACT FROM AUTHOR]

Boreal forests are particularly vulnerable to climate warming, which increases the occurrence of natural disturbances, such as fires and insect outbreaks. It is therefore essential to better understand climate-induced changes in boreal vegetation dynamics. This requires accurate estimates of variations in biomass across regions and time. This remains challenging in the extensive larch forests of northeast Siberia because of the paucity of allometric equations and physical properties of woody debris needed for quantifying aboveground biomass pools from field surveys. Our study is the first to present values of mean squared diameter (MSD) and specific gravity that can be used to calculate fine dead and downed woody debris loads in Cajander larch (Larix cajanderi) forests using the line-intersect sampling approach. These values were derived from field measurements collected in 25 forest stands in the Republic of Sakha, Russia, and compared with values reported for other prevalent boreal tree species. We developed allometric equations relating diameter at breast height (DBH, at 1.3 m) to stem wood, stem bark, branches, foliage, and aboveground biomass based on measurements of 63 trees retrieved from previous studies. Differences between our allometric models and existing equations were assessed in predicting larch aboveground biomass in 53 forest stands sampled in the Republic of Sakha. We found that using fine woody debris (FWD) parameters from other boreal tree species and allometric equations developed in other regions may result in significantly lower biomass estimates in larch-dominated forests of northeast Siberia. The FWD parameters and allometric equations presented in our paper can be used to refine estimates of aboveground biomass in Cajander larch forests in northeast Siberia. [ABSTRACT FROM AUTHOR]

Reliable data on CO2 quantification is increasingly important to quantify the climate benefits of forest landscape restoration and international commitments, such as the Warsaw REDD+ Framework and Nationally Determined Contributions under the Paris Agreement. Calophyllum inophyllum L. (nyamplung as a local name or tamanu tree for the commercial name) is an increasingly popular tree species in forest landscape restoration and bioenergy production for a variety of reasons. In this paper, we present allometric equations for aboveground biomass (AGB), belowground biomass (BGB), and total above- and belowground biomass (TABGB) predictions of C. inophyllum L. Data collection was carried out twice (2017 and 2021) from 40 trees in Java, Indonesia. Allometric equations using the natural logarithm of diameter at breast height (lnDBH) and ln height (lnH) for biomass prediction qualified the model's fit with statistical significance at 95% of the confidence interval for AGB, BGB, and TABGB predictions. The results showed that the linear models using both lnDBH and lnH were well fit and accurate. However, the model with lnDBH is more precise than the model using lnH. Using lnDBH as a predictor, the R2 values were 0.923, 0.945, and 0.932, and MAPE were 24.7, 37.0, and 25.8 for AGB, BGB, and TABGB, respectively. Using lnH as a predictor, the R2 values were 0.887, 0.918, and 0.898 and MAPE were 37.4, 49.0, and 39.8 for AGB, BGB, and TABGB, respectively. Consequently, the driven allometric equations can help accurate biomass quantification for carbon-trading schemes of C. inophyllum L. [ABSTRACT FROM AUTHOR]

Background: Fuelwood is considered to be the primary source of cooking energy in Tanzania and, due to ongoing deforestation, access to fuelwood is becoming more cumbersome. On-farm agroforestry systems can reduce dependency on off-farm fuel; however, the output of on-farm produced fuel is typically uncertain as production potentials are often not known. In this paper, we have developed allometric equations to model the above-ground woody biomass (AGWB) production from intercropped Gliricidia sepium (Jacq.) Kunth ex Walp (Gliricidia) shrubs and Cajanus cajan (L.) Millsp. (pigeon pea) plants. Methods: We used a destructive sampling approach, for measuring the dendrometric characteristics, such as the root collar diameter at a 20 cm stem height (RCD20) and the stem height to estimate the AGWB production. The models are based on 112 Gliricidia and 80 pigeon pea observations from annually pruned plants. Seven allometric equations were fitted to derive the best-fit models for the AGWB production. Results: We found that using a natural log-transformed linear model with RCD20 as a single predictor variable provides the highest explanatory value to estimate the AGWB production (Gliricidia: R2 = 95.7%, pigeon pea: R2 = 91.4%) while meeting Ordinary Least Square (OLS) estimator requirements. Adding stem height as an additional variable to predict the AGWB production does not improve model accuracy enough to justify the extra work for including it. Conclusions: While on-farm pigeon pea plants produced a stable amount of woody biomass per annum, annual fuelwood production from Gliricidia shrubs increased over the years. Compared to the annual fuelwood consumption data from the literature, our results show that on-farm produced fuelwood can substantially offset the demand for off-farm fuel, potentially resulting in household fuelwood autarky. [ABSTRACT FROM AUTHOR]

Hake is an important species of economic interest and thus the subject of a large literature, but its biology parameters which are essential for stock assessment and management remains insufficiently known. The aim of this paper was, therefore, to describe the growth, length-weight relationship and reproduction of Merluccius merluccius in the Algerian western coast. Consequently, we studied growth and estimated age, using the length-weight relationship was determined according to the allometric equation (Sparre et al., 1989) and the growth of M. merluccius was estimated computing the Von Bertalanffy growth equation (VBGF) (Beverton et Holt, 1957).The gonadoso-matic index (GSI) was calculated monthly by the equation: GSI = (gonad weight/fish weight without gonad)*100. Size at maturity (L50) was defined as the size at which 50% of individuals were mature. The female-male ratio was 1.14: 0.88. The total length and weight of females ranged from 24 cm to 33.7 cm and 104.94 g to 270.29 g respectively and for males was 23.7 cm to 34.8 cm and 95.4 g to 292.07 g. The growth parameters for males were calculated as L∞=34.80 cm k= 0.470 year-1, t0= -1.49 year and for females L∞= 35.70 cm, k= 0.360 year-1, t0= -2.76 year. The length-weight relationship was W= 0.024*L2648 for female and W= 0.012*L2 828 for Male. Monthly values of the gonadosomatic index indicated that spawning occurred mainly in December, January and February. The result of the present work will be a step forward to the improvement of the fisheries assessment and management of M. merluccius in this area. [ABSTRACT FROM AUTHOR]

Knowledge about the biomass productivity of trees planted in a rainwater harvesting structure, i.e., a trench (T), relative to a normal pit (P) on degraded land is scarce. The objective of this research paper is to compare the effect of T with P on the growth and biomass production of the Acacia saligna and Casuarina equisetifolia which were planted on degraded land. All the individual stems of both species in the T and P, their diameters at breast height (DBH) and heights in 2016 and 2020 were measured. Species-specific allometric equations were used to quantify the biomass production of the studied species. The t-tests were used for data analysis; both A. saligna and C. equisetifolia individuals planted in the T had higher DBH and height increment as compared with A. saligna and C. equisetifolia that were planted and grown in a P. The results also revealed significant differences on the mean DBH and height of A. saligna and C. equisetifolia planted in a T and P (p < 0.05). Between 2016 and 2020, the total biomass (TB) of A. saligna planted in a T and in a P increased significantly (p < 0.05) on average by 25.5 kg/tree and 7.7 kg/tree, respectively (p < 0.05). Similarly, the mean TB values of the C. equisetifolia planted in a T and a P between 2016 and 2020 increased significantly (p < 0.05) by 28.9 kg/tree and 13.1 kg/tree, respectively. Finally, establishing trenches to restore degraded lands was shown to facilitate growth and biomass production of planted species on degraded land. [ABSTRACT FROM AUTHOR]

To validate and to improve ecological products obtained from satellites, such as a leaf area index (LAI), above‐ground biomass (AGB), and a fraction of photosynthetically active radiation (fAPAR), in‐situ accurate data are indispensable. They must be not a single point‐data but an areal data representing the satellite footprint. Their accuracy needs to be much higher than the required accuracy for the satellite products. The quantitative assessment of their error is necessary for evaluating the satellite products' error from the discrepancy between the satellite products and the in‐situ data. However, such data had not been available. In particular, there had been few data of LAI in a sparse evergreen needle‐leaved forest, because of difficulty of accuracy control of in‐situ observation in such a forest. To overcome the difficulty and to obtain the representative LAI, we made an allometric equation to estimate the leaf mass of Picea glehnii in northern Hokkaido. We report the allometric equations of leaf mass and AGB of P. glehnii, its leaf mass per area (LMA), its leaf life span, its leaf distribution, its crown shapes, its wood specific gravity, and tree locations. We also report LAI, AGB, and fAPAR within the 500 m × 500 m area, which is the footprint scale of the Global Change Observation Mission‐Climate satellite, in a pure and sparse forest of P. glehnii in northern Hokkaido. These precise data are useful for validation of other satellite data, especially with higher spatial resolution, and forest structure modeling. The complete data set for this abstract published in the Data Paper section of the journal is available in electronic format in MetaCat in JaLTER at http://db.cger.nies.go.jp/JaLTER/metacat/metacat/ERDP-2020-06.1/jalter-en. [Correction added on 7 September 2020, after first online publication: JaLTER URL has been updated.] [ABSTRACT FROM AUTHOR]

One of the important aspects to support the success of REDD+ programme is the availability of a standard methodology and method to estimate carbon stock in forest or agroforestry land, which is recognized by the United Nations Framework Convention on Climate Change (UNFCCC). This paper aims to describe and discuss a method to estimate the carbon stocks in agroforestry land in Hutumury Village, Ambon. The formulation of allometric equation for nutmeg (Myristica fragrans Houtt) is used to predict the aboveground biomass of nutmeg-based agroforestry land. The carbon mass equation model was constructed based on a significant relationship between carbon mass of nutmeg tree and its diameters at breast height and tree height. In order to analyse the biomass content, a destructive sampling technique was used. After felling, dimensional measurement was performed for each tree. The results of the study showed that the equation model for estimating aboveground biomass of nutmeg tree was allometric equation of Power, i.e., Y = 134.353 * (D**2.424) or ln (Y) = ln (134.353) + (2.424 * ln (D)) with R2 (adj) = 0.977 and standard error (SE) = 0.183. This allometric equation is a local allometric model and much needed to support REDD+ especially in Maluku Province. In addition, aboveground biomass predictors are easy to determine as only stem diameters are required to be measured mainly in dense forests. [ABSTRACT FROM AUTHOR]

A set of $$n$$ -principal points of a $$p$$ -dimensional distribution is an optimal $$n$$ -point-approximation of the distribution in terms of a squared error loss. It is in general difficult to derive an explicit expression of principal points. Hence, we may have to search the whole space $$R^p$$ for $$n$$ -principal points. Many efforts have been devoted to establish results that specify a linear subspace in which principal points lie. However, the previous studies focused on elliptically symmetric distributions and location mixtures of spherically symmetric distributions, which may not be suitable to many practical situations. In this paper, we deal with a mixture of elliptically symmetric distributions that form an allometric extension model, which has been widely used in the context of principal component analysis. We give conditions under which principal points lie in the linear subspace spanned by the first several principal components. [ABSTRACT FROM AUTHOR]

The determination the forced vital capacity (FVC) and the forced expiratory volume in 1 second (FEV1) during spirometry studies, is at the core of the evaluation of the pulmonary function of patients with respiratory diseases. The Global Lung Function Initiative (GLI) offers the most extensive data set of normal lung functions available, which is currently used to determine the average expected/predicted FEV1 and FVC (pred V), and their lower limit of normal (LLN, 5th percentile) at any given height and age for women and men. These prediction equations are currently expressed in a rather complex form: pred V = exp [p+ (a x Ln (height) + (n x Ln (age)) + spline] and LLN = exp(Ln (pred V) + Ln (1 – 1.645 x S x CV)/S) ; and are currently used to generate interpretations in commercialized spinographic system. However, as shown in this paper, these equations contain physiological and fundamental allometric information on lung volumes that become obvious when rewriting mean predicted values as a "simple" power function of height and LLN as a percentage of the mean predicted values. We therefore propose to present the equations of prediction obtained from the GLI data using simplified expressions in adults (18–95 years old) to reveal some of their physiological and allometric meaning. Indeed, when predicted FEV1 and FVC (pred V) were expressed under the form pred V= αx height a x b(age), the resulting exponent (a) ranges between 2 and 3, transforming the one dimension of a length (size) into a volume , akin to the third-order power (cubic) function of height historically used to predict lung volumes. Only one function, b (age), is necessary to replace all the factors related to age, including the tables of discrete data of spline functions original equations. Similarly, LLN can be expressed as LLN = c (age) x pred V to become a simple percentage of the predicted values, as a function of age. The equations with their respective new polynomial functions were validated in 52,764 consecutive spirometry tests performed in 2022 in 22,612 men and 30,152 women at the Cleveland Clinic. Using these equations, it become obvious that for both women and men, FEV1/FVC ratio decreases with the size as the exponent of the power function of height is lower for FEV1 than FVC. We conclude that rewriting the GLI predicted equations with simpler formulations restitutes to the GLI data some of their original allometric meaning, without altering the accuracy of their prediction. • The Global Lung Function Initiative (GLI) offers the most extensive data set of normal lung functions available, which is currently used to determine the average expected/predicted FEV1 and FVC (pred V), and their lower limit of normal (LLN, 5th percentile). • Rewriting the GLI predicted equations as a power function of height gives to the GLI data a unique physiological and allometric meaning. [ABSTRACT FROM AUTHOR]

In this paper it is presented a gentle review of empirical and theoretical advances in understanding the role of size in biological organisms. More specifically, it deals with how the energy demand, expressed by the metabolic rate, changes according to the mass of an organism. Empirical evidence suggests a power-law relation between mass and metabolic rate, namely the allometric equation. For vascular organisms, the exponent 3 of this powerlaw is smaller than one, which implies scaling economy; that is, the greater the organism is, the lesser energy per cell it demands. However, the numerical value of this exponent is a theme of extensive debate and a central issue in comparative physiology. A historical perspective is shown, beginning with the first empirical insights in the sec. 19 about scaling properties in biology, passing through the two more important theories that explain the scaling properties quantitatively. Firstly, the Rubner model considers organism surface area and heat dissipation to derive 3 = 2/3. Secondly, the West-Brown-Enquist theory explains such scaling properties due to the hierarchical and fractal nutrient distribution network, deriving 3 = 3/4. [ABSTRACT FROM AUTHOR]

Biogenic volatile organic compounds (BVOCs) are emitted by vegetation and react with other compounds to form ozone and secondary organic matter (OM). In regional air quality models, biogenic emissions are often calculated using a plant functional type approach, which depends on the land use category. However, over cities, the land use is urban, so trees and their emissions are not represented. Here, we develop a bottom-up inventory of urban tree biogenic emissions in which the location of trees and their characteristics are derived from the tree database of the Paris city combined with allometric equations. Biogenic emissions are then computed for each tree based on their leaf dry biomass, tree-species-dependent emission factors, and activity factors representing the effects of light and temperature. Emissions are integrated in WRF-CHIMERE air quality simulations performed over June–July 2022. Over Paris city, the urban tree emissions have a significant impact on OM, inducing an average increase in the OM of about 5 %, reaching 14 % locally during the heatwaves. Ozone concentrations increase by 1.0 % on average and by 2.4 % during heatwaves, with a local increase of up to 6 %. The concentration increase remains spatially localized over Paris, extending to the Paris suburbs in the case of ozone during heatwaves. The inclusion of urban tree emissions improves the estimation of OM concentrations compared to in situ measurements, but they are still underestimated as trees are still missing from the inventory. OM concentrations are sensitive to terpene emissions, highlighting the importance of favoring urban tree species with low-terpene emissions. [ABSTRACT FROM AUTHOR]

Understory small trees and shrubs play a crucial role in the biogeochemical cycles in forest ecosystems. However, their biomass in northeastern China is still uncertain and has been heavily disregarded due to the limited number of available allometric equations. For this study, 782 plants from 33 species obtained by the destructive method were used to develop species-specific and generalized aboveground allometric biomass equations based on collar diameter (D) and height (H) using weighted nonlinear seemingly unrelated regression. Each biomass component was shown to be well predicted by D alone, with R2 adj. values mostly greater than 0.80. The majority of species performed better in the models for wood and aboveground biomass when H was included as D2H. Furthermore, generalized equations for the two components showed a comparatively large coefficient of variation but comparable Bias to species-specific equations, especially for small trees. It is recommended to estimate biomass using generalized equations for mixed species only when species-specific equations are unavailable at a given site. However, in the event when precision is not the primary concern, generalized equations are also suggested. The developed equations will help to improve the accuracy of biomass assessment of understory woody plants in northeastern China forest ecosystems. [ABSTRACT FROM AUTHOR]

Shrub volume is used to calculate numerous, essential ecological indicators in rangeland ecosystems such as biomass, fuel loading, wildlife habitat, site productivity, and ecosystem structure. Field techniques for biomass estimation, including destructive sampling, ocular estimates, and allometric techniques, use shrub height and canopy widths to estimate volume and translate it to biomass with species‐specific allometric equations. These techniques are time‐consuming and pose challenges, including removal of plant material and training of observers. We compared canopy volume estimates from field‐based measurements with drone‐collected canopy volume estimates for seven dominant shrub species within mountain big sagebrush (Artemisia tridentata subsp. vaseyana) plant communities in southern Idaho, USA. Canopy height and two perpendicular width measurements were taken from 103 shrubs of varying sizes, and volume was estimated using a traditional allometric equation. Overlapping aerial images captured with a DJI Mavic 2 Professional drone were used to create a 3D representation of the study area using structure‐from‐motion photogrammetry. Each shrub was extracted from the point cloud, and volume was estimated using allometric and volumetric methods. The volumetric method, which involved converting point clouds to raster canopy height models with 2.5‐ and 5‐cm grid cells, outperformed the allometric method (R2 > 0.7) and was more reproducible and robust to user‐related variability. Drone‐estimated volume best‐matched field‐estimated volume (R2 > 0.9) for three larger species: A. tridentata subsp. tridentata, A. tridentata subsp. vaseyana, and Purshia tridentata. The volume of smaller shrubs (canopy widths <1 m) was slightly overestimated from drone‐based models. We argue that drone‐based models provide a suitable alternative to field methods, while having the added benefit of being less time‐consuming, with fewer limitations, and more easily scaled to larger study areas than traditional field techniques. Finally, we demonstrate a proof of concept for automating canopy volume estimates using point‐cloud‐based automatic shrub detection algorithms. These findings demonstrate that drone‐collected images can be used to assess shrub canopy volume for at least five upland sagebrush steppe shrub species and support the integration of drone data collection into rangeland vegetation monitoring. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Anatolian Environmental & Animal Science is the property of Bulent Verep and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Ever since the Kyoto Protocol, agroforestry has gained increased attention as a strategy to sequester carbon (C) and mitigate global climate change. Agroforestry has been recognized as having the greatest potential for C sequestration of all the land uses analyzed in the Land-Use, Land-Use Change and Forestry report of the IPCC; however, our understanding of C sequestration in specific agroforestry practices from around the world is rudimentary at best. Similarly, while agroforestry is well recognized as a land use practice capable of producing biomass for biopower and biofuels, very little information is available on this topic. This thematic issue is an attempt to bring together a collection of articles on C sequestration and biomass for energy, two topics that are inextricably interlinked and of great importance to the agroforestry community the world over. These papers not only address the aboveground C sequestration, but also the belowground C and the role of decomposition and nutrient cycling in determining the size of soil C pool using specific case studies. In addition to providing allometric methods for quantifying biomass production, the biological and economic realities of producing biomass in agroforestry practices are also discussed. [ABSTRACT FROM AUTHOR]

The research described in this paper was performed in the Niepolomice Forest (Southern Poland) in 2001 as part of the Forest Environmental Monitoring and Management System (FOREMMS; 5FP IST) project. The material for the present study consisted of the measurement results of the biomass of Scots pine shoots with needles and needles alone carried out on 113 felled sample trees. The purpose of this study was to construct empirical equations for estimating the foliage biomass of Scots pine from easy to measure parameters. To achieve this aim, the dependence of the foliage biomass of Scots pine on stem diameter, height, age, crown length, basal area increment of the trees was analyzed. Using the biometric characteristics such as: tree diameter at breast height (dbh), basal area increment, age, height, and crown length empirical equations for estimating the foliage biomass of Scots pine reasonably precisely have been established. The created empirical equation gives accurate foliage biomass estimates. The explained variability varies between 65 and 85%, it depends on the number of variables applied in the equation. The equations presented in this paper were created with a view to their possible use in ecological studies where biomass quantity may be used, for example, in modeling carbon circulation in the forest ecosystem. From the point of view of forestry practice, these equations may help to assess biomass production in Scots pine stands. [ABSTRACT FROM AUTHOR]

The quantitative structure model (QSM) contains the branch geometry and attributes of the tree. AdQSM is a new, accurate, and detailed tree QSM. In this paper, an automatic modeling method based on AdQSM is developed, and a low-cost technical scheme of tree structure modeling is provided, so that AdQSM can be freely used by more people. First, we used two digital cameras to collect two-dimensional (2D) photos of trees and generated three-dimensional (3D) point clouds of plot and segmented individual tree from the plot point clouds. Then a new QSM-AdQSM was used to construct tree model from point clouds of 44 trees. Finally, to verify the effectiveness of our method, the diameter at breast height (DBH), tree height, and trunk volume were derived from the reconstructed tree model. These parameters extracted from AdQSM were compared with the reference values from forest inventory. For the DBH, the relative bias (rBias), root mean square error (RMSE), and coefficient of variation of root mean square error (rRMSE) were 4.26%, 1.93 cm, and 6.60%. For the tree height, the rBias, RMSE, and rRMSE were—10.86%, 1.67 m, and 12.34%. The determination coefficient (R2) of DBH and tree height estimated by AdQSM and the reference value were 0.94 and 0.86. We used the trunk volume calculated by the allometric equation as a reference value to test the accuracy of AdQSM. The trunk volume was estimated based on AdQSM, and its bias was 0.07066 m3, rBias was 18.73%, RMSE was 0.12369 m3, rRMSE was 32.78%. To better evaluate the accuracy of QSM's reconstruction of the trunk volume, we compared AdQSM and TreeQSM in the same dataset. The bias of the trunk volume estimated based on TreeQSM was −0.05071 m3, and the rBias was −13.44%, RMSE was 0.13267 m3, rRMSE was 35.16%. At 95% confidence interval level, the concordance correlation coefficient (CCC = 0.77) of the agreement between the estimated tree trunk volume of AdQSM and the reference value was greater than that of TreeQSM (CCC = 0.60). The significance of this research is as follows: (1) The automatic modeling method based on AdQSM is developed, which expands the application scope of AdQSM; (2) provide low-cost photogrammetric point cloud as the input data of AdQSM; (3) explore the potential of AdQSM to reconstruct forest terrestrial photogrammetric point clouds. [ABSTRACT FROM AUTHOR]

Black locust is a drought-resistant tree species with high biomass productivity during juvenility; it is able to thrive on wastelands, such as former brown coal fields and dry agricultural areas. However, research conducted on this species in such areas is limited. This paper aims to provide a basis for predicting tree woody biomass for black locust based on tree, competition, and site variables at 14 sites in northeast Germany that were previously utilized for mining or agriculture. The study areas, which are located in an area covering 320 km x 280 km, are characterized by a variety of climatic and soil conditions. Influential variables, including tree parameters, competition, and climatic parameters were considered. Allometric biomass models were employed. The findings show that the most important parameters are tree and competition variables. Different former land utilizations, such as mining or agriculture, as well as growth by cores or stumps, significantly influenced aboveground woody biomass production. The new biomass models developed as part of this study can be applied to calculate woody biomass production and carbon sequestration of Robinia pseudoacacia L. in short rotation coppices in previous mining and agricultural areas. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Journal of Forest Research is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Turkish Journal of Maritime & Marine Sciences is the property of Ordu University, Fatsa Faculty of Marine Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The assessment of forest biomass has been a focus of research, aiming to understand matter–energy relationships in forest ecosystems and address forestry practice issues. In recent decades there has been increased societal interest in rational forest resource exploitation, necessitating accurate biomass estimation. In Greece there has been limited efforts in estimating forest biomass, and the current study focuses on habitat type 9340, "Quercus ilex and Quercus rotundifolia forests," located in the protected areas "GR1420004–Karla–Mavrovouni–Kefalovryso Velestinou–Neochori" and "GR1430001–Oros Pilio and Paraktia Thalassia Zoni (Mount Pilion and Coastal Sea Zone)" in the Natura 2000 network. The habitat falls within the thermo-Mediterranean zone and the study aims to estimate the biomass and carbon storage to contribute to sustainable EU forest strategies. Due to resource limitations, a generalized allometric equation was proposed as an alternative to traditional biomass estimation methods. The above-ground biomass per hectare was estimated, ranging from 16.10 to 205.27 Mg ha−1 (mean 61.91 Mg ha−1). Furthermore, two approaches were used to estimate the total biomass in the habitat: regional averages based on spatial distribution and spatial interpolation using a geographic information system. The total estimated biomass for habitat 9340 is 183,505 Mg, with the carbon storage in standing dry biomass amounting to 83,725.25 Mg. Despite the absence of sampled biomass specimens, this study combines robust statistical techniques with published empirical values to provide a solid framework for estimating assimilated CO2. Sequestered CO2 in the study area is estimated at 306,992.58 Mg. Therefore, the significant role of Quercus ilex L. in carbon storage in Mediterranean forest ecosystems is highlighted by sequestering a substantial amount of CO2. [ABSTRACT FROM AUTHOR]

Shrubbery and young plantations, with a large number of tree species, take up a broad area in subtropical Chinese forests and contribute a significant part to forest biomass and carbon (C) stocks. However, the biomass and C stocks of shrubbery and young plantations were generally underestimated or excluded in forest biomass calculations due to the scarce of standard equations for estimating biomass. The aim of this study was to develop appropriate regression equations for biomass estimation of shrubbery and young plantations. A total of 108 individuals of 15 most widespread shrub and young tree species were sampled by destructive harvesting, and the dry weight of each component of trees, i.e., foliage, branch, stem and root were obtained. The dry biomass of each component was correlated with plant height (H), basal diameter of stem (D), crown area (CA) and their composite variables D2H and CV (CA × H) by using seemingly uncorrelated regression, and the best fitted model was chosen according to the determination coefficient (R2), root mean squared error (RMSE), Akaike's information criterion (AIC) and percent relative standard errors (PRSE) less than 25%. In the species-specific equations, H, D or D2H were used as the appropriate independent variables in most of the equations, and only a few of them were CA or CV. In the multiple species equations, H was an important variable to predict the biomass, but the predictors of biomass equation for different functional groups or life forms were different due to diversity of external morphology. The species-specific equations had low biases, while the general equations for functional groups and life forms showed comparable biases, and the general equations for all species had the highest prediction biases. Therefore, general equations for functional groups or life forms are recommended to estimate biomass for species without species-specific allometric equations. [ABSTRACT FROM AUTHOR]

Biomass equations are a helpful tool to estimate the tree and stand biomass production and standing stock. Such estimations are of great interest for science but also of great importance for global reports on the carbon cycle and the global climate system. Even though there are various collections and generic meta-analyses available with biomass equations for mature trees, reports on biomass equations for juvenile trees (seedlings and saplings) are mainly missing. Against the background of an increasing amount of reforestation and afforestation projects and forests in young successional stages, such equations are required. In this study we have collected data from various studies on the aboveground woody biomass of 19 common tree species growing in Europe. The aim of this paper was to calculate species-specific biomass equations for the aboveground woody biomass of single trees in dependence of root-collar-diameter (RCD), height (H) and the combination of the two (RCD H). Next to calculating species-specific biomass equations for the species available in the dataset, we also calculated generic biomass equations for all broadleaved species and all conifer species. The biomass equations should be a contribution to the pool of published biomass equations, whereas the novelty is here that the equations were exclusively derived for young trees. [ABSTRACT FROM AUTHOR]

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Aboveground biomass (AGB) of short-stature shrubs and trees contain a substantial part of the total carbon pool within boreal ecosystems. These ecosystems, however, are changing rapidly due to climate-mediated atmospheric changes, with overall observed decline in woody plant AGB in boreal northwestern Canada. Allometric equations provide a means to quantify woody plant AGB and are useful to understand aboveground carbon stocks as well as changes through time in unmanaged boreal ecosystems. In this paper, we provide allometric equations, regression coefficients, and error statistics to quantify total AGB of shrubs and short-stature trees. We provide species- and genus-specific as well as multispecies allometric models for shrub and tree species commonly found in northwestern boreal forest and peatland ecosystems. We found that the three-dimensional field variable (volume) provided the most accurate prediction of shrub multispecies AGB (R2 = 0.79, p < 0.001), as opposed to the commonly used one-dimensional variable (basal diameter) measured on the longest and thickest stem (R2 = 0.23, p < 0.001). Short-stature tree AGB was most accurately predicted by stem diameter measured at 0.3 m along the stem length (R2 = 0.99, p < 0.001) rather than stem length (R2 = 0.29, p < 0.001). Via the two-dimensional variable cross-sectional area, small-stature shrub AGB was combined with small-stature tree AGB within one single allometric model (R2 = 0.78, p < 0.001). The AGB models provided in this paper will improve our understanding of shrub and tree AGB within rapidly changing boreal environments. [ABSTRACT FROM AUTHOR]

Homegarden agroforestry systems are suggested to hold a large potential for climate change mitigation and adaptation. This is due to their multifunctional role in providing income, food and ecosystem services while decreasing pressure on natural forests and hence saving and storing carbon. In this paper, above-ground biomass carbon and tree species diversity of trees was quantified in homegardens around two villages in the dry south-eastern part of Moneragala district of Sri Lanka. A total of 45 dry zone homegardens were sampled on size, diameter at breast height, tree height and species diversity. Using allometric equations, we find a mean above-ground biomass stock of 13 mega grams of carbon per hectare (Mg C ha) with a large range among homegardens (1-56 Mg C ha, n = 45) due to a variation of tree diversity and composition between individual homegardens. Mean above-ground carbon stock per unit area was higher in small homegardens (0.2 ha, 26 Mg C ha, n = 11) and statistically different compared to medium (0.4-0.8 ha, 9 Mg C ha, n = 27) and large (1.0-1.2 ha, 8 Mg C ha, n = 7) homegardens. In total, 4,278 trees were sampled and 70 tree species identified and recorded. The Shannon Wiener index were used to evaluate diversity per homegarden and ranged from 0.76 to 3.01 with a mean value of 2.05 ± 0.07 indicating a medium evenly distributed diversity of sampled tree species. The results show a vast heterogeneity in terms of carbon stock and tree diversity within the less studied dry zone homegardens; results that contribute to more knowledge of their expansion potential as well as climate mitigation and adaptation potential. The results are also useful for whether homegardens should be considered to be included as an activity to enhance natural forest cover within Sri Lanka's newly commenced UN-REDD National Programme. [ABSTRACT FROM AUTHOR]

Biomass allocation in seedlings and saplings at different stages of growth is important information for studying the response of species to site conditions. The objectives of the paper are: (a) to analyse the relationship between height and biomass in young Norway spruce and European beech trees, (b) to study the influence of the leaf area on ontogenetic growth stages and biomass sequestration capacity on the regeneration of these two species. 96 seedlings (H < 30 cm) and saplings (31 < H < 130 cm) were collected in different light conditions in a case study in the Alps (Trentino province, Italy). Leaf Area Index and shoot/root ratio were used as indicators of the ecological conditions (e.g. light, soil moisture, nutrient status) able to influence the seedlings and saplings growth. Two non-linear regressions were fitted to analyse the relationship between height and biomass and to develop the aboveground and below-ground allometric equations. Non-linear regressions show that sapling or seedling height is a good predictor of above-ground and below-ground biomass with a R²aj above 0.8 for all equations and a R²aj above 0.9 for above-ground biomass of Norway spruce. The results show that silvicultural practices may influence the regeneration patterns and increase the biomass allocation rate influencing stand density and canopy cover. [ABSTRACT FROM AUTHOR]

Forest above-ground biomass (AGB) can be estimated based on light detection and ranging (LiDAR) point clouds. This paper introduces an accurate and detailed quantitative structure model (AdQSM), which can estimate the AGB of large tropical trees. AdQSM is based on the reconstruction of 3D tree models from terrestrial laser scanning (TLS) point clouds. It represents a tree as a set of closed and complete convex polyhedra. We use AdQSM to model 29 trees of various species (total 18 species) scanned by TLS from three study sites (the dense tropical forests of Peru, Indonesia, and Guyana). The destructively sampled tree geometry measurement data is used as reference values to evaluate the accuracy of diameter at breast height (DBH), tree height, tree volume, branch volume, and AGB estimated from AdQSM. After AdQSM reconstructs the structure and volume of each tree, AGB is derived by combining the wood density of the specific tree species from destructive sampling. The AGB estimation from AdQSM and the post-harvest reference measurement data show a satisfying agreement. The coefficient of variation of root mean square error (CV-RMSE) and the concordance correlation coefficient (CCC) are 20.37% and 0.97, respectively. AdQSM provides accurate tree volume estimation, regardless of the characteristics of the tree structure, without major systematic deviations. We compared the accuracy of AdQSM and TreeQSM in modeling the volume of 29 trees. The tree volume from AdQSM is compared with the reference value, and the determination coefficient (R2), relative bias (rBias), and CV-RMSE of tree volume are 0.96, 6.98%, and 22.62%, respectively. The tree volume from TreeQSM is compared with the reference value, and the R2, relative Bias (rBias), and CV-RMSE of tree volume are 0.94, −9.69%, and 23.20%, respectively. The CCCs between the volume estimates based on AdQSM, TreeQSM, and the reference values are 0.97 and 0.96. AdQSM also models the branches in detail. The volume of branches from AdQSM is compared with the destructive measurement reference data. The R2, rBias, and CV-RMSE of the branches volume are 0.97, 12.38%, and 36.86%, respectively. The DBH and height of the harvested trees were used as reference values to test the accuracy of AdQSM's estimation of DBH and tree height. The R2, rBias, and CV-RMSE of DBH are 0.94, −5.01%, and 9.06%, respectively. The R2, rBias, and CV-RMSE of the tree height were 0.95, 1.88%, and 5.79%, respectively. This paper provides not only a new QSM method for estimating AGB based on TLS point clouds but also the potential for further development and testing of allometric equations. [ABSTRACT FROM AUTHOR]

This study was conducted at Rilagala conservation forest, Nawalapitiya to assess and compare the plant diversity, above ground biomass and carbon stock in the periphery and interior of an isolated sub montane forest in Sri Lanka. All trees above 5 cm Diameter at Breast Height (DBH) in eleven randomly demarcated 25 m × 25 m plots were recorded. Distance up to 100 m from the forest boundary considered as the periphery (8 plots) and over 200 m as the core (3 plots). A total of 1,583 trees belonging to 29 species were recorded and aboveground biomass (AGB) and carbon stocks were calculated using allometric equations. The tree diversity of each plot was calculated using the Shannon diversity index (H'). Results were statistically analysed using single factor ANOVA. The species richness and H' were the highest at the periphery (n=23, H'= 2.55) while the lowest at forest interior (n=11, H'= 1.97). The highest tree density was recorded at periphery (2,992 trees ha-1) and it decreased to 1,408 trees ha-1 towards the core. The average DBH was 8.5 ± 3.33 cm and it increased towards the forest interior (9.7 ± 4.51 cm) from the periphery (7.2 ± 3.74 cm). Estimated aboveground biomass ranged from 63.99 - 108.13 Mg ha-1 with a mean of 82.53 ± 14.39 Mg ha-1. The above ground C stock was estimated from 31.99 - 54.07 Mg ha-1 with a mean of 41.26 ± 7.2 Mg ha-1. However, there was no significant difference between forest periphery and core in variables, except species richness (p<0.05). The study revealed that the diversity and density of trees decreased towards the forest interior and vice versa was recorded for DBH, AGB and carbon stock. The study highlights the importance of conserving isolated tropical sub montane forest patches for carbon sequestration. [ABSTRACT FROM AUTHOR]

This paper presents a method for fitting cylinders into a point cloud, derived from a terrestrial laser-scanned tree. Utilizing high scan quality data as the input, the resulting models describe the branching structure of the tree, capable of detecting branches with a diameter smaller than a centimeter. The cylinders are stored as a hierarchical tree-like data structure encapsulating parent-child neighbor relations and incorporating the tree's direction of growth. This structure enables the efficient extraction of tree components, such as the stem or a single branch. The method was validated both by applying a comparison of the resulting cylinder models with ground truth data and by an analysis between the input point clouds and the models. Tree models were accomplished representing more than 99% of the input point cloud, with an average distance from the cylinder model to the point cloud within sub-millimeter accuracy. After validation, the method was applied to build two allometric models based on 24 tree point clouds as an example of the application. Computation terminated successfully within less than 30 min. For the model predicting the total above ground volume, the coefficient of determination was 0.965, showing the high potential of terrestrial laser-scanning for forest inventories. [ABSTRACT FROM AUTHOR]

This paper presents new allometric models for woody savanna of the dry Sudanian zone of the southern part of Senegal and contributes to the needs for accurate and precise carbon estimates through improved statistical models and methods. The results are based on statistical relationships between the total dry biomass and either tree diameter at breast height (DBH) or tree height for a set of 101 individuals of different sizes from 13 dominant species in 6 protected forests. The statistical regression (cubic order 3) generated for DBH (5-41.5 cm) and tree height (2.5-15.6 m) showed significant R of 0.934 and 0.813, respectively. Using the same database, species-based models for the most represented genera ( Acacia sp., Combretum sp. and Terminalia sp.) show more precision than the generic model. The model residual standard error and relative errors showed a good fit between observed and predicted data. Species-based models showed smaller errors compare to generic models outputs. [ABSTRACT FROM AUTHOR]

Biomass partitioning is important for illustrating terrestrial ecosystem carbon flux. West, Brown and Enquist (WBE) model predicts that an optimal 3/4 allometric scaling of leaf mass and total biomass of individual plants will be applied in diverse communities. However, amount of scientific evidence suggests an involvement of some biological and environmental factors in interpreting the variation of scaling exponent observed in empirical studies. In this paper, biomass information of 1175 forested communities in China was collected and categorized into groups in terms of leaf form and function, as well as their locations to test whether the allocation pattern was conserved or variable with internal and/or environmental variations. Model Type II regression protocol was adopted to perform all the regressions. The results empirically showed that the slopes varied significantly across diverse forested biomes, between conifer and broadleaved forests, and between evergreen and deciduous forests. Based on the results, leaf form and function and their relations to environments play a significant role in the modification of the WBE model to explore more accurate laws in nature. [ABSTRACT FROM AUTHOR]

Afforestation is a mitigation option to reduce the increased atmospheric carbon dioxide levels as well as the predicted high possibility of climate change. In this paper, vegetation survey data, statistical database, National Forest Resource Inventory database, and allometric equations were used to estimate carbon density (carbon mass per hectare) and carbon storage, and identify the size and spatial distribution of forest carbon sinks in plantation ecosystems in sand source areas of north Beijing, China. From 2001 to the end of 2010, the forest areas increased more than 2.3 million ha, and total carbon storage in forest ecosystems was 173.02 Tg C, of which 82.80 percent was contained in soil in the top 0–100 cm layer. Younger forests have a large potential for enhancing carbon sequestration in terrestrial ecosystems than older ones. Regarding future afforestation efforts, it will be more effective to increase forest area and vegetation carbon density through selection of appropriate tree species and stand structure according to local climate and soil conditions, and application of proper forest management including land-shaping, artificial tending and fencing plantations. It would be also important to protect the organic carbon in surface soils during forest management. [ABSTRACT FROM AUTHOR]

• Context: Prescribed burning is increasingly recommended to control encroaching shrublands in the Mediterranean area. • Aims: The aims of this paper are to analyze the fuel structural characteristics of Spartium junceum and how they influence fire behaviour during prescribed burning. • Methods: Two winter-spring prescribed burns were conducted in 2009 and 2011. Fuel load and structure of S. junceum shrubs were assessed using the Cube Method, and shrub 3-D models were built using the FIRE PARADOX FUEL MANAGER software. Allometric equations to estimate S. junceum fuel load were developed. During burning, thermocouples measured temperature variations, which were then analyzed relative to fuel characteristics. • Results: Fuel load components and distribution were strictly related to shrub height; in tall shrubs, most of the fine fuel was more than 1.5 m aboveground. Due to fuel vertical discontinuity, not all shrubs were burned in the fires, but wind increased fire sustainment and fuel consumption. Maximum temperatures (over 800 °C) and residence times were positively related to fuel load. • Conclusion: S. junceum tall shrublands represent high hazard formations due to their elevated fuel load, mostly in fine fuel fractions. Vertical discontinuity among fuel strata limits fire propagation in mild weather conditions. Winter-spring prescribed burning cannot eliminate S. junceum shrublands, but do create shrub cover discontinuity. As S. junceum has fire-adapted morphological traits, a single burn is insufficient to control it. [ABSTRACT FROM AUTHOR]

Ecologically and economically sustainable planning of forest resources requires tools capable of providing estimates with adequate accuracy on volume, biomass and woody increments. Interest in these attributes has increased since the United Nations Framework Convention on Climate Change has been given a further boost by the birth of the carbon credit market in the early 2000s. However, the data collection necessary to formulate allometric models for estimating wood volume is challenging, both due to the considerable amount of data required and because the necessary destructive measurements are very laborious. Furthermore, given the great structural, managerial and environmental diversity that characterizes the Italian forests, the sample size for the development of allometric models must necessarily be large. Over the years, all these aspects have led to a progressive abandonment of measurements in the forests for the production of volume tables. Recent applications of the terrestrial laser scanner (TLS) for collecting dimensional information on trees have demonstrated their effectiveness. In this study we present the work carried out in the autumn/winter 2022-2023 for the creation of new volume tables for the black pine forests in Vallombrosa (FI - Central Italy), based on data collected with a TLS. The study involved the same pine forests studied in 1969 for the production of volume tables in Vallombrosa. After showing the methods and analysis needed to obtain the volume tables, the paper discusses the results in comparison with those produced in 1969.

The aim of this paper is to develop biomass models for commonly multi-stemmed Prosopis juliflora/pallida trees. The data were collected on three of the Cape Verde islands (Maio, Santiago and Santo Antao). The dataset covers 240 trees containing 1,882 stems with stem diameter at breast height over 2 cm; of that 255 individual tree stems were sampled destructively. These calibration data were used to construct stem and tree-level models for estimation of total aboveground biomass and its fine and course fractions with diameter threshold of 5 cm. A set of parameterized biomass models for multi-stemmed Prosopis spp. trees suited for biomass estimation at tree and stem levels using appropriate set of independent variables, commonly available in forest inventory programs, was created. The effect of site (island) on tree allometry was not detected. The two-phase construction of tree biomass models based on destructive sampling limited to individual stems combined with a routine field measurement of entire multi-stemmed tree specimen represents a practicable approach leading to biomass and carbon assessment that may be generally suited for tree species with complex multi-stemmed growth form similar to that of Prosopis spp. [ABSTRACT FROM AUTHOR]