Biomass and stem volume equations for tree species in Europe

A review of stem volume and biomass equations for tree species growing in Europe is presented. The mathematical forms of the empirical models, the associated statistical parameters and information about the size of the trees and the country of origin were collated from scientific articles and from technical reports. The total number of the compiled equations for biomass estimation was 607 and for stem volume prediction it was 230. The analysis indicated that most of the biomass equations were developed for aboveground tree components. A relatively small number of equations were developed for southern Europe. Most of the biomass equations were based on a few sampled sites with a very limited number of sampled trees. The volume equations were, in general, based on more representative data covering larger geographical regions. The volume equations were available for major tree species in Europe. The collected information provides a basic tool for estimation of carbon stocks and nutrient balance of forest ecosystems across Europe as well as for validation of theoretical models of biomass allocation.

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A review of biomass equations for China's tree species

Earth System Science Data ◽

10.5194/essd-12-21-2020 ◽

2020 ◽

Vol 12 (1) ◽

pp. 21-40 ◽

Cited By ~ 7

Author(s):

Yunjian Luo ◽

Xiaoke Wang ◽

Zhiyun Ouyang ◽

Fei Lu ◽

Liguo Feng ◽

...

Keyword(s):

Tree Species ◽

Carbon Accounting ◽

Sub Saharan Africa ◽

Background Information ◽

Vegetation Coverage ◽

Biomass Estimation ◽

Tree Biomass ◽

Biomass Equation ◽

Geographical Regions ◽

Biomass Equations

Abstract. Tree biomass equations are the most commonly used method to estimate tree and forest biomasses at various spatial and temporal scales because of their high accuracy, efficiency and conciseness. For decades, many tree biomass equations have been reported in diverse types of literature (e.g., journals, books and reports). These scattered equations are being compiled, and tree biomass equation datasets are currently available for many geographical regions (e.g., Europe, North America and sub-Saharan Africa) and countries (e.g., Australia, Indonesia and Mexico). However, one important country stands out as an area where a large number of biomass equations have not yet been reviewed and inventoried extensively: China. Therefore, in this study, we carried out a broad survey and critical review of the literature (from 1978 to 2013) on biomass equations in China and compiled a normalized tree biomass equation dataset for China. This dataset consists of 5924 biomass equations for nearly 200 tree species and their associated background information (e.g., geographical location, climate and stand description), showing sound geographical, climatic and forest vegetation coverage across China. The dataset is freely available at https://doi.org/10.1594/PANGAEA.895244 (Luo et al., 2018) for noncommercial scientific applications, and this dataset fills an important regional gap in global biomass equations and provides key parameters for biomass estimation in forest inventory and carbon accounting studies in China.

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ChinAllomeTree 1.0: China's normalized tree biomass equation dataset

10.5194/essd-2019-1 ◽

2019 ◽

Author(s):

Yunjian Luo ◽

Xiaoke Wang ◽

Zhiyun Ouyang ◽

Fei Lu ◽

Liguo Feng ◽

...

Keyword(s):

Geographical Location ◽

Allometric Equation ◽

Carbon Accounting ◽

Sub Saharan Africa ◽

Background Information ◽

Biomass Estimation ◽

Tree Biomass ◽

Biomass Equation ◽

Geographical Regions ◽

Biomass Equations

Abstract. The tree biomass equation, which is also called the tree allometric equation, is the most commonly used method to estimate tree and forest biomass at various spatial-temporal scales because of its high accuracy, efficiency and conciseness. For decades, many tree biomass equations have been reported in diverse types of literature (e.g., journals, books and reports). These scattered equations are being compiled, and tree biomass equation datasets are currently available for many geographical regions (e.g., Europe, North America and Sub-Saharan Africa) and countries (e.g., Australia, Indonesia and Mexico) except for in an important region of the world, Eastern Asia, specifically China. Therefore, in this study, we carried out an extensive survey and critical review of the literature (from 1978–2013) on biomass equations conducted in China and developed China’s normalized tree biomass equation dataset (ChinAllomeTree version 1.0). This dataset consists of 5,924 biomass component equations for nearly 200 species and their associated background information (e.g., geographical location, climate and stand description), showing sound geographical, climatic and forest vegetation coverages across China. The dataset is freely available at https://doi.pangaea.de/10.1594/PANGAEA.895244 for noncommercial scientific applications, which fills an important regional gap in global biomass datasets and provides key parameters for biomass estimation in forest inventory and carbon accounting in China.

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Stem volume equations for native tree species in southern New South Wales and Victoria

Australian Forestry ◽

10.1080/00049158.1998.10674752 ◽

1998 ◽

Vol 61 (4) ◽

pp. 275-286 ◽

Cited By ~ 20

Author(s):

Huiquan Bi ◽

Fiona Hamilton

Keyword(s):

Tree Species ◽

New South ◽

New South Wales ◽

Stem Volume ◽

South Wales ◽

Native Tree ◽

Native Tree Species ◽

Volume Equations

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Guidelines for choosing volume equations in the presence of measurement error in height

Canadian Journal of Forest Research ◽

10.1139/x99-215 ◽

2000 ◽

Vol 30 (2) ◽

pp. 306-310 ◽

Cited By ~ 22

Author(s):

M S Williams ◽

H T Schreuder

Keyword(s):

Measurement Error ◽

Tree Species ◽

Measurement Errors ◽

Tree Diameter ◽

Total Height ◽

Volume Equations

Assuming volume equations with multiplicative errors, we derive simple conditions for determining when measurement error in total height is large enough that only using tree diameter, rather than both diameter and height, is more reliable for predicting tree volumes. Based on data for different tree species of excurrent form, we conclude that measurement errors up to ±40% of the true height can be tolerated before inclusion of estimated height in volume prediction is no longer warranted.

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Semi-automatic classification of tree species in different forest ecosystems by spectral and geometric variables derived from Airborne Digital Sensor (ADS40) and RC30 data

Remote Sensing of Environment ◽

10.1016/j.rse.2010.08.006 ◽

2011 ◽

Vol 115 (1) ◽

pp. 76-85 ◽

Cited By ~ 65

Author(s):

L.T. Waser ◽

C. Ginzler ◽

M. Kuechler ◽

E. Baltsavias ◽

L. Hurni

Keyword(s):

Tree Species ◽

Forest Ecosystems ◽

Automatic Classification ◽

Geometric Variables

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Producing Framework Tree Species for Restoring Forest Ecosystems in Northern Thailand

Small-scale Forestry ◽

10.1007/s11842-008-9070-2 ◽

2008 ◽

Vol 7 (3-4) ◽

pp. 403-415 ◽

Cited By ~ 11

Author(s):

Stephen Elliott ◽

Cherdsak Kuaraksa

Keyword(s):

Tree Species ◽

Forest Ecosystems ◽

Northern Thailand

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Forest Biomass Estimation Based on Forest Inventory Data in Middle and Last Scales

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.183-185.220 ◽

2011 ◽

Vol 183-185 ◽

pp. 220-224

Author(s):

Ming Ze Li ◽

Wen Yi Fan ◽

Ying Yu

Keyword(s):

Tree Species ◽

Forest Inventory ◽

Forest Biomass ◽

Biomass Estimation ◽

Total Biomass ◽

Inventory Data ◽

Biomass Equation ◽

Tree Species Composition ◽

Forest Inventory Data ◽

Ecosystem Carbon

The forest biomass (which is referred to the arbor aboveground biomass in this research) is one of the most primary factors to determine the forest ecosystem carbon storages. There are many kinds of estimating methods adapted to various scales. It is a suitable method to estimate forest biomass of the farm or the forestry bureau in middle and last scales. First each subcompartment forest biomass should be estimated, and then the farm or the forestry bureau forest biomass was estimated. In this research, based on maoershan farm region, first the single tree biomass equation of main tree species was established or collected. The biomass of each specie was calculated according to the materials of tally, such as height, diameter and so on in the forest inventory data. Secondly, each specie’s biomass and total biomass in subcompartment were calculated according to the tree species composition in forest management investigation data. Thus the forest biomass spatial distribution was obtained by taking subcompartment as a unit. And last the forest total biomass was estimated.

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Constructing single-entry stem volume models for four economically important tree species of Greece

Folia Oecologica ◽

10.2478/foecol-2021-0014 ◽

2021 ◽

Vol 48 (2) ◽

pp. 136-146

Author(s):

Panagiotis P. Koulelis ◽

Kostas Ioannidis

Keyword(s):

Tree Species ◽

National Level ◽

Sustainable Use ◽

Information Criterion ◽

Cost Effective ◽

Volume Estimation ◽

Stem Volume ◽

Nonlinear Regression Models ◽

Cubic Polynomial ◽

Two Parameter

Abstract Three different nonlinear regression models were tested for their ability to predict stem volume for economically important native tree species in Greece. Τhe models were evaluated using adjusted R square (Adj Rsqr) root mean square error (RMSE) and Akaike information criterion (AICc), where necessary. In general, the quadratic polynomial and cubic polynomial models and the two-parameter power models fit the data well. Although the two-parameter power function fit best for fir, oak, and beech trees, the cubic polynomial model produced the best fit statistics for black pine. Making forest inventory estimates often involves predicting tree volumes from only the diameter at breast height (DBH) and merchantable height. This study covers important gaps in fast and cost-effective methods for calculating the volume of tree species at national level. However, the increasing need for reliable estimates of inventory components and volume changes requires more accurate volume estimation techniques. Especially when those estimates concern the national inventory, those models must be validated using an entire range of age/diameter and site classes of each species before their extended use across the country to promote the sustainable use of forest resources.

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