scholarly journals Challenges in estimating forest biomass: use of allometric equations for three boreal tree species

2019 ◽  
Vol 49 (12) ◽  
pp. 1613-1622
Author(s):  
Dingliang Xing ◽  
J.A. Colin Bergeron ◽  
Kevin A. Solarik ◽  
Bradley Tomm ◽  
S. Ellen Macdonald ◽  
...  
Keyword(s):  
Populus Tremuloides ◽  
Aboveground Biomass ◽  
Tree Species ◽  
Picea Glauca ◽  
Forest Cover ◽  
Forest Biomass ◽  
Belowground Biomass ◽  
Allometric Equations ◽  
Shoot Ratio ◽  
Root To Shoot Ratio

Regionally fitted allometric equations for individual trees and root-to-shoot ratio values are normally used to estimate local aboveground and belowground forest biomass, respectively. However, uncertainties arising from such applications are poorly understood. We developed equations for both aboveground and belowground biomass using destructive sampling for three dominant upland boreal tree species in northwestern Alberta, Canada. Compared with our equations, the diameter-based national equations derived for use across Canada underestimated aboveground biomass for Picea glauca (Moench) Voss but gave reasonable estimates for Populus balsamifera L. and Populus tremuloides Michx. The national equations based on both tree diameter and height overestimated aboveground biomass for the Populus species but underestimated it for Picea glauca in our study area. The approach of root-to-shoot ratio proposed by the Intergovernmental Panel on Climate Change (IPCC) overestimated belowground biomass by 16%–41%, depending on forest cover type, in comparison with our values estimated directly on site, with the greatest bias in deciduous-dominated stands. When the general allometric equations for aboveground biomass and the root-to-shoot ratio for belowground biomass were combined to estimate stand biomass, overestimation could be as high as 18% in our study area. The results of our study support the development of improved regional allometric equations for more accurate local-scale estimations. Incorporating intraspecific variation of important traits such as tree taper may be especially helpful.

Assessment of Biomass Expansion Factor (BEF) and Root-to-shoot Ratio (R) for some Tree Species of Uttarakhand, India

2014 ◽  
Vol 37 (4) ◽  
pp. 371-377
Author(s):  
Laxmi Rawat ◽  
Pramod Kumar ◽  
Nishita Giri
Keyword(s):  
Tree Species ◽  
Tectona Grandis ◽  
Expansion Factor ◽  
Pinus Roxburghii ◽  
Biomass Expansion Factor ◽  
Shorea Robusta ◽  
Shoot Ratio ◽  
Harvesting Method ◽  
Root To Shoot Ratio ◽  
Age Series

The present study was conducted in Shorea robusta (sal), Pinus roxburghii (Chir pine), Tectona grandis (Teak) and Ailanthus excelsa (Ardu) plantations of different ages at different sites in Uttarakhand. Biomass was calculated on the basis of complete tree harvesting method (stratified mean tree technique method). Biomass Expansion Factor (BEF) and root-to-shoot ratio (R) of all these 4 tree species have been calculated and presented in this paper. Sample trees of S. robusta were of 45, 53 and 60 years of age. BEF for all these 3 age series were assessed as 1.3 at 45 years, 1.4 at 53 years and 1.2 at 60 years of age. Similarly, R values were assessed as 0.27, 0.28 and 0.26, respectively, in these 3 age series. BEF and R values assessed for T. grandis (28 years age) as 1.46 and 0.21; and for A. excelsa (39 years age) as 1.23 and 0.23, respectively. BEF for P. roxburghii trees calculated as 2.3 for 13 years age, 1.75 for 20 years, 1.71 for 22 years, 1.5 for 33 years and 1.46 for trees of 45 years of age. Similarly, R values were 0.2 for 13 years, 0.21 for 20 years, 0.12 for 22 years, 0.13 for 33 years and 0.15 for 45 years of age. P. roxburghii sample trees have shown decreasing order of BEF with increasing age, whereas S. robusta has not shown such trend along the chronosequence.

Development of an improved model estimating the nutrient content of the bole for four boreal tree species

1998 ◽  
Vol 28 (1) ◽  
pp. 37-43 ◽  
Author(s):  
P Rochon ◽  
D Paré ◽  
C Messier
Keyword(s):  
Populus Tremuloides ◽  
Tree Species ◽  
Picea Glauca ◽  
Nonlinear Models ◽  
Abies Balsamea ◽  
Nutrient Content ◽  
Forest Harvesting ◽  
Nutrient Concentrations ◽  
Nutrient Contents ◽  
Improved Model

An improved model for estimating nutrient contents of the commercial portion of tree boles was developed for four boreal tree species (Populus tremuloides Michx., Betula papyrifera Marsh., Picea glauca (Moench) Voss, and Abies balsamea (L.) Mill.). This model considers the spatial pattern of variation of nutrient concentrations inside the bole and its relationships with tree size. For all species-nutrient combinations, no significant pattern was found for vertical variations in nutrient concentrations, while two types of nonlinear models, using distance from the tree periphery as the independent variable, fit the pattern of horizontal (or radial) variations. These patterns of variability were used to estimate the global nutrient concentration of the bole by using mathematical integration. The values obtained with this method were generally lower, especially for large stems, than values obtained with traditional methods that do not consider the variability of nutrient concentrations inside the bole. This improved model would permit better estimates of the amounts of nutrients lost in biomass upon forest harvesting, as well as internal cycling of nutrients within the bole.

scholarly journals Quantifying the Spatial Heterogeneity and Driving Factors of Aboveground Forest Biomass in the Urban Area of Xi’an, China

2020 ◽  
Vol 9 (12) ◽  
pp. 744
Author(s):  
Xuan Zhao ◽  
Jianjun Liu ◽  
Hongke Hao ◽  
Yanzheng Yang
Keyword(s):  
Spatial Distribution ◽  
Urban Area ◽  
Aboveground Biomass ◽  
Tree Species ◽  
City Planning ◽  
Urban Forest ◽  
Forest Biomass ◽  
Q Value ◽  
Biomass Distribution ◽  
Land Type

Investigating the spatial distribution of urban forest biomass and its potential influencing factors would provide useful insights for configuring urban greenspace. Although China is experiencing an unprecedented scale of urbanization, the spatial pattern of the urban forest biomass distribution as a critical component in the urban landscape has not been fully examined. Using the geographic detector method, this research examines the impacts of four geographical factors (GFs)—dominant tree species, forest categories, land types, and age groups—on the aboveground biomass distribution of urban forests in 1480 plots in Xi’an, China. The results indicate that (1) the aboveground biomass and four GFs show obvious heterogeneity regarding their spatial distribution in Xi’an; (2) the dominant tree species and age group which impacts the patterns of aboveground biomass are the primary GFs, with the independent q value (a statistic metric used to quantify the impacts of GFs in this study) reaching 0.595 and 0.202, respectively, while the forest category and land type were weakly linked to the spatial variation of aboveground biomass, with a q value of 0.087 and 0.076, respectively; and (3) the interactions among these four GFs also tend to contribute to the distribution pattern of aboveground biomass. The interactions between GFs achieved a larger impact than the sum of impacts that were independently obtained from the factors. Our results showed that the method of using a geographical detector is a useful tool in the urban area, and can reveal the driver pattern of aboveground biomass and provide a reference for city planning and management.

Climate-based Allometric Biomass Equations for Five Major Canadian Timber Species

2021 ◽  
Author(s):  
Kun Xu ◽  
Jinghe Jiang ◽  
Fangliang He
Keyword(s):  
Aboveground Biomass ◽  
Forest Biomass ◽  
Allometric Equations ◽  
Accurate Estimation ◽  
Biomass Estimation ◽  
Change Scenario ◽  
Mean Annual Temperature ◽  
Timber Species ◽  
Trembling Aspen ◽  
Allometric Models

Accurate estimation of forest biomass is essential to quantify the role forests play at balancing terrestrial carbon. Allometric equations based on tree size have been used for this purpose worldwide. There is little quantitative understanding on how environmental variation may affect tree allometries. Even less known is how to incorporate environmental factors into such equations to improve estimation. Here we tested the effects of climate on tree allometric equations and proposed to model forest biomass by explicitly incorporating climatic factors. Among the five major Canadian timber species tested, the incorporation of climate was not found to improve the allometric models. For trembling aspen and tamarack, the residuals of their conventional allometric models were found strongly related to frost-free period and mean annual temperature, respectively. The predictions of the two best climate-based models were significantly improved, which indicate that trembling aspen and tamarack store more aboveground biomass when growing in warmer than in colder regions. We showed that, under the RCP4.5 modest climate change scenario, there would be a 10% underestimation of aboveground biomass for these two species if the conventional non-climate models would still be in use in 2030. This study suggests the necessity to proactively develop climate-based allometric equations for more accurate and reliable forest biomass estimation.

Allometric equations to predict the total aboveground biomass of tree species in a planted forest in Egypt

2012 ◽  
Vol 123 (1) ◽  
pp. 27-36 ◽  
Author(s):  
Emad Farahat ◽  
Kamal Shaltout ◽  
Hassan El-Kady ◽  
Ahmed Shalapy
Keyword(s):  
Aboveground Biomass ◽  
Tree Species ◽  
Allometric Equations ◽  
Planted Forest

Aboveground and belowground biomass and sapwood area allometric equations for six boreal tree species of northern Manitoba

2002 ◽  
Vol 32 (8) ◽  
pp. 1441-1450 ◽  
Author(s):  
B Bond-Lamberty ◽  
C Wang ◽  
S T Gower
Keyword(s):  
Populus Tremuloides ◽  
Aboveground Biomass ◽  
Root Biomass ◽  
Pinus Banksiana ◽  
Stem Diameter ◽  
Allometric Equations ◽  
Stand Age ◽  
Sapwood Area ◽  
Coarse Root ◽  
Biomass Equations

Allometric equations were developed relating aboveground biomass, coarse root biomass, and sapwood area to stem diameter at 17 study sites located in the boreal forests near Thompson, Man. The six species studied were trembling aspen (Populus tremuloides Michx.), paper birch (Betula papyrifera Marsh.), black spruce (Picea mariana (Mill.) BSP), jack pine (Pinus banksiana Lamb.), tamarack (Larix laricina (Du Roi) Koch.), and willow (Salix spp.). Stands ranged in age from 4 to 130 years and were categorized as well or poorly drained. Stem diameter ranged from 0.1 to 23.7 cm. Stem diameter was measured at both the soil surface (D0) and breast height (DBH). The relationship between biomass and diameter, fitted on a log–log scale, changed significantly at ~3 cm DBH, suggesting that allometry differed between saplings and older trees. To eliminate this nonlinearity, a model of form log10 Y = a + b(log10 D) + c(AGE) + d(log10 D × AGE) was used, where D is stem diameter, AGE is stand age, and the cross product is the interaction between diameter and age. Most aboveground biomass equations (N = 326) exhibited excellent fits (R2 > 0.95). Coarse root biomass equations (N = 205) exhibited good fits (R2 > 0.90). Both D0 and DBH were excellent (R2 > 0.95) sapwood area predictors (N = 413). Faster growing species had significantly higher ratios of sapwood area to stem area than did slower growing species. Nonlinear aspects of some of the pooled biomass equations serve as a caution against extrapolating allometric equations beyond the original sample diameter range.

scholarly journals Allometric equations for pioneer tree species and estimation of the aboveground biomass of a tropical secondary forest in East Kalimantan

Tropics ◽  
2004 ◽  
Vol 14 (1) ◽  
pp. 123-130 ◽  
Author(s):  
Toru HASHIMOTO ◽  
Takeshi TANGE ◽  
Masaya MASUMORI ◽  
Hisayoshi YAGI ◽  
Satohiko SASAKI ◽  
...  
Keyword(s):  
Aboveground Biomass ◽  
Tree Species ◽  
Secondary Forest ◽  
Allometric Equations ◽  
Pioneer Tree Species ◽  
East Kalimantan ◽  
Pioneer Tree ◽  
Tropical Secondary Forest

scholarly journals Two Decades Progress on The Application of Remote Sensing for Monitoring Tropical and Sub-Tropical Natural Forests: A Review

Forests ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 739
Author(s):  
Enoch Gyamfi-Ampadu ◽  
Michael Gebreslasie
Keyword(s):  
Remote Sensing ◽  
Spatial Resolution ◽  
Aboveground Biomass ◽  
Tree Species ◽  
Forest Cover ◽  
High Spatial Resolution ◽  
Remote Sensing Data ◽  
Natural Forests ◽  
Sensing Applications ◽  
Remote Sensing Applications

Forest covers about a third of terrestrial land surface, with tropical and subtropical zones being a major part. Remote sensing applications constitute a significant approach to monitoring forests. Thus, this paper reviews the progress made by remote sensing data applications to tropical and sub-tropical natural forest monitoring over the last two decades (2000–2020). The review focuses on the thematic areas of aboveground biomass and carbon estimations, tree species identification, tree species diversity, and forest cover and change mapping. A systematic search of articles was performed on Web of Science, Science Direct, and Google Scholar by applying a Boolean operator and using keywords related to the thematic areas. We identified 50 peer-reviewed articles that studied tropical and subtropical natural forests using remote sensing data. Asian and South American natural forests are the most highly researched natural forests, while African natural forests are the least studied. Medium spatial resolution imagery was extensively utilized for forest cover and change mapping as well as aboveground biomass and carbon estimation. In the latest studies, high spatial resolution imagery and machine learning algorithms, such as Random Forest and Support Vector Machine, were jointly utilized for tree species identification. In this review, we noted the promising potential of the emerging high spatial resolution satellite imagery for the monitoring of natural forests. We recommend more research to identify approaches to overcome the challenges of remote sensing applications to these thematic areas so that further and sustainable progress can be made to effectively monitor and manage sustainable forest benefits.

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