Estimating Aboveground Biomass for Broadleaf Woody Plants and Young Conifers in Sierra Nevada, California, Forests

Abstract Quantification of biomass is fundamental to a wide range of research and natural resource management goals. An accurate estimation of plant biomass is essential to predict potential fire behavior, calculate carbon sequestration for global climate change research, assess critical wildlife habitat, and so forth. Reliable allometric equations from simple field measurements are necessary for efficient evaluation of plant biomass. However, allometric equations are not available for many common woody plant taxa in the Sierra Nevada. In this report, we present more than 200 regression equations for the Sierra Nevada western slope that relate crown diameter, plant height, crown volume, stem diameter, and both crown diameter and height to the dry weight of foliage, branches, and entire aboveground biomass. Destructive sampling methods resulted in regression equations that accurately predict biomass from one or two simple, nondestructive field measurements. The tables presented here will allow researchers and natural resource managers to easily choose the best equations to fit their biomass assessment needs.

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

Canadian Journal of Forest Research ◽

10.1139/cjfr-2020-0485 ◽

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.

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Allometric equation for aboveground biomass estimation in moist Afromontane forest in Gesha and Sayilem district in Kaffa zone, southwestern Ethiopia

10.21203/rs.3.rs-54064/v1 ◽

2020 ◽

Author(s):

Admassu Merti ◽

Teshome Soromessa ◽

Tura Bareke

Keyword(s):

Wood Density ◽

Aboveground Biomass ◽

Allometric Equation ◽

Allometric Equations ◽

Individual Species ◽

Biomass Estimation ◽

Regression Equations ◽

Strongly Correlated ◽

Afromontane Forest ◽

Species Specific

Abstract Background: Allometric equations which are regressions linking the biomass to some independent variables are used to estimate tree components from the forest. The generic equation developed by many authors may not adequately reveal the tree biomass in a specific region in tropics including in Ethiopia. Therefore, the use of species specific allometric equations is important to achieve higher levels of accuracy because trees of different species may differ. The objective of the study was to develop species-specific allometric equations for Apodytes dimidiata, Ilex mitis, Sapium ellipticum and shrubs (Galiniera saxifraga and Vernonia auriculifera) using semi-destructive method for estimating the aboveground biomass (AGB). For purpose of sampling trees, individual species were categorized into trees whose Diameter at breast height (DBH) is ≥ 5 cm.Results: All the necessary biomass calculations were done, and biomass equations were developed for each species. The regression equations relate AGB with DBH, height (H), and density (ρ) were computed and the models were tested for accuracy based on observed data. The best model was selected based higher adj R2 and lower residual standard error and Akaike information criterion than rejected models. The relations for all selected models are significant (p<0.000), which showed strong correlation AGB with selected dendrometric variables. Accordingly, the AGB was strongly correlated with DBH and was not signiﬁcantly correlated with wood density and height individually in Ilex mitis. In combination, AGB was strongly correlated with DBH, height; DBH and wood density; are better for carbon assessment than general equations.Conclusions: The specific allometeric equation developed for the Gesha-Sayilem Afromontane Forest which can be used in similar moist forests in Ethiopia for the implementation of Reduced Emission from Deforestation and Degradation (REDD+) activities to benefit the local communities from carbon trade.

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Parameterisation of allometric equations for quantifying aboveground biomass of Norway spruce (Picea abies (L.) H. Karst.) in the Czech Republic

Journal of Forest Science ◽

10.17221/61/2017-jfs ◽

2018 ◽

Vol 64 (No. 3) ◽

pp. 108-117

Author(s):

Čihák Tomáš ◽

Vejpustková Monika

Keyword(s):

Czech Republic ◽

Picea Abies ◽

Norway Spruce ◽

Aboveground Biomass ◽

Slenderness Ratio ◽

Allometric Equations ◽

Tree Age ◽

Regression Equations ◽

Data Set ◽

The Czech Republic

The aim of the present study was to develop allometric equations for predicting aboveground biomass of Norway spruce (Picea abies (Linnaeus) H. Karsten) applicable to the typically managed spruce forest on acidic and nutrient-medium sites in the Czech Republic. The models were based on an extensive data set of 139 spruce trees collected in 25 stands on 15 sites. The biomass in dry mass was modelled using linear regression equations with one (diameter at breast height – D), two (D, slenderness ratio – H/D) or three (D, H/D, site index – SI, or tree age – A) predictors. The models were validated using the leave-one-out method. The value of the root mean square error of cross-validation was chosen as the main criterion for the best-model selection. Both the total aboveground biomass and stem biomass were best predicted by three-variable models (D, H/D, SI). For crown and foliage biomass the simple one-variable model (D) is recommended.

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Allometric Equations for Estimating Aboveground Biomass of Eucalyptus urophylla S.T. Blake in East Nusa Tenggara

Jurnal Manajemen Hutan Tropika (Journal of Tropical Forest Management) ◽

10.7226/jtfm.27.1.24 ◽

2021 ◽

Vol 27 (1) ◽

pp. 24-31

Author(s):

R Sadono ◽

◽

W Wahyu ◽

F Idris

Keyword(s):

Aboveground Biomass ◽

Tree Height ◽

Allometric Equation ◽

Allometric Equations ◽

Accurate Estimation ◽

Eucalyptus Urophylla ◽

Individual Tree ◽

Eucalyptus Plantation ◽

Diameter At Breast Height ◽

Breast Height

Understanding the essential contribution of eucalyptus plantation for industry development and climate change mitigation requires the accurate quantification of aboveground biomass at the individual tree species level. However, the direct measurement of aboveground biomass by destructive method is high cost and time consuming. Therefore, developing allometric equations is necessary to facilitate this effort. This study was designed to construct the specific allometric models for estimating aboveground biomass of Eucalyptus urophylla in East Nusa Tenggara. Forty two sample trees were utilized to develop allometric equations using regression analysis. Several parameters were selected as predictor variables, i.e. diameter at breast height (D), quadrat diameter at breast height combined with tree height (D2H), as well as D and H separately. Results showed that the mean aboveground biomass of E. urophylla was 143.9 ± 19.44 kg tree-1. The highest biomass were noted in stem (80.06%), followed by bark (11.89%), branch (4.69%), and foliage (3.36%). The relative contribution of stem to total aboveground biomass improved with the increasing of diameter class while the opposite trend was recorded in bark, branch, and foliage. The equation lnŶ = lna + b lnD was best and reliable for estimating the aboveground biomass of E. urophylla since it provided the highest accurate estimation (91.3%) and more practical than other models. Referring to these findings, this study concluded the use of allometric equation was reliable to support more efficient forest mensuration in E. urophylla plantation.

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Cover–biomass relationships of an invasive annual grass, Bromus rubens, in the Mojave Desert

Invasive Plant Science and Management ◽

10.1017/inp.2020.33 ◽

2020 ◽

pp. 1-5

Author(s):

Scott R. Abella

Keyword(s):

Aboveground Biomass ◽

Mojave Desert ◽

Invasive Plant ◽

Plant Biomass ◽

Percent Cover ◽

Regression Equations ◽

Annual Grass ◽

Bromus Rubens ◽

Regression Slopes ◽

Study Sites

Abstract Estimates of plant biomass are helpful for many applications in invasive plant science and management, but measuring biomass can be time-consuming, costly, or impractical if destructive sampling is inappropriate. The objective of this study was to assess feasibility of developing regression equations using a fast, nondestructive measure (cover) to estimate aboveground biomass for red brome (Bromus rubens L.), a widespread nonnative annual grass in the Mojave Desert, USA. At three study sites, including one measured for three consecutive years, B. rubens cover spanned 0.1% to 85% and aboveground biomass 1 to 321 g m−2. In log10-transformed linear regressions, B. rubens cover accounted for 68% to 96% of the variance in B. rubens biomass among sites, with all coefficients of determination significant at P < 0.05. For every doubling of percent cover, biomass was predicted to increase by 78%, 83%, and 144% among the three sites. At the site measured for three consecutive years, which ranged in rainfall from 65% to 159% of the long-term average, regression slopes each year differed from other years. Regression results among sites were insensitive to using cover classes (10 classes encompassing 0% to 100% cover) compared with simulated random distribution of integer cover within classes. Biomass of B. rubens was amenable to estimation in the field using cover, and such estimates may have applications for modeling invasive annual plant fuel loads and ecosystem carbon storage.

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ESTIMATION OF ABOVE GROUND BIOMASS OF THE THREE SITES (GRAZED SITE, PROTECTED SITE AND SEED SOWN SITE) FOR COMPARING THEIR PRODUCTIVITY IN KASHMIR VALLEY

FLORA AND FAUNA ◽

10.33451/florafauna.v23i2pp259-262 ◽

2017 ◽

Vol 23 (2) ◽

Author(s):

AFSHAN ANJUM BABA ◽

SYED NASEEM UL-ZAFAR GEELANI ◽

ISHRAT SALEEM ◽

MOHIT HUSAIN ◽

PERVEZ AHMAD KHAN ◽

...

Keyword(s):

Protected Areas ◽

Aboveground Biomass ◽

Plant Biomass ◽

Summer Season ◽

Above Ground Biomass ◽

Spring Season ◽

Kashmir Valley ◽

Ground Biomass ◽

Maximum Value ◽

Protected Site

The plant biomass for protected areas was maximum in summer (1221.56 g/m2) and minimum in winter (290.62 g/m2) as against grazed areas having maximum value 590.81 g/m2 in autumn and minimum 183.75 g/m2 in winter. Study revealed that at Protected site (Kanidajan) the above ground biomass ranged was from a minimum (1.11 t ha-1) in the spring season to a maximum (4.58 t ha-1) in the summer season while at Grazed site (Yousmarag), the aboveground biomass varied from a minimum (0.54 t ha-1) in the spring season to a maximum of 1.48 t ha-1 in summer seasonandat Seed sown site (Badipora), the lowest value of aboveground biomass obtained was 4.46 t ha-1 in spring while as the highest (7.98 t ha-1) was obtained in summer.

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Biomass of understory species of Pinus halepensis Mill. forests in the Kassandra Peninsula - Chalkidiki

Silva Gandavensis ◽

10.21825/sg.v63i0.841 ◽

1998 ◽

Vol 63 ◽

Author(s):

P. Smiris ◽

F. Maris ◽

K. Vitoris ◽

N. Stamou ◽

P. Ganatsas

Keyword(s):

Moisture Content ◽

Aboveground Biomass ◽

Quercus Ilex ◽

Pinus Halepensis ◽

Biomass Estimation ◽

Regression Equations ◽

Pistacia Lentiscus ◽

Quercus Coccifera ◽

Understory Species ◽

Cistus Incanus

This study deals with the biomass estimation of the understory species of Pinus halepensis forests in the Kassandra peninsula, Chalkidiki (North Greece). These species are: Quercus coccifera, Quercus ilex, Phillyrea media, Pistacia lentiscus, Arbutus unedo, Erica arborea, Erica manipuliflora, Smilax aspera, Cistus incanus, Cistus monspeliensis, Fraxinus ornus. A sample of 30 shrubs per species was taken and the dry and fresh weights and the moisture content of every component of each species were measured, all of which were processed for aboveground biomass data. Then several regression equations were examined to determine the key words.

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New Forest Aboveground Biomass Maps of China Integrating Multiple Datasets

Remote Sensing ◽

10.3390/rs13152892 ◽

2021 ◽

Vol 13 (15) ◽

pp. 2892

Author(s):

Zhongbing Chang ◽

Sanaa Hobeichi ◽

Ying-Ping Wang ◽

Xuli Tang ◽

Gab Abramowitz ◽

...

Keyword(s):

Carbon Emissions ◽

Aboveground Biomass ◽

Regional Scale ◽

Remote Sensing Data ◽

Field Measurements ◽

Random Forest Regression ◽

Multiple Datasets ◽

Optimal Weighting ◽

Two Hybrid ◽

Forest Aboveground Biomass

Mapping the spatial variation of forest aboveground biomass (AGB) at the national or regional scale is important for estimating carbon emissions and removals and contributing to global stocktake and balancing the carbon budget. Recently, several gridded forest AGB products have been produced for China by integrating remote sensing data and field measurements, yet significant discrepancies remain among these products in their estimated AGB carbon, varying from 5.04 to 9.81 Pg C. To reduce this uncertainty, here, we first compiled independent, high-quality field measurements of AGB using a systematic and consistent protocol across China from 2011 to 2015. We applied two different approaches, an optimal weighting technique (WT) and a random forest regression method (RF), to develop two observationally constrained hybrid forest AGB products in China by integrating five existing AGB products. The WT method uses a linear combination of the five existing AGB products with weightings that minimize biases with respect to the field measurements, and the RF method uses decision trees to predict a hybrid AGB map by minimizing the bias and variance with respect to the field measurements. The forest AGB stock in China was 7.73 Pg C for the WT estimates and 8.13 Pg C for the RF estimates. Evaluation with the field measurements showed that the two hybrid AGB products had a lower RMSE (29.6 and 24.3 Mg/ha) and bias (−4.6 and −3.8 Mg/ha) than all five participating AGB datasets. Our study demonstrated both the WT and RF methods can be used to harmonize existing AGB maps with field measurements to improve the spatial variability and reduce the uncertainty of carbon stocks. The new spatial AGB maps of China can be used to improve estimates of carbon emissions and removals at the national and subnational scales.

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Allometric equations for accurate estimation of above-ground biomass in logged-over tropical rainforests in Sarawak, Malaysia

Journal of Forest Research ◽

10.1007/s10310-009-0149-1 ◽

2009 ◽

Vol 14 (6) ◽

pp. 365-372 ◽

Cited By ~ 46

Author(s):

Tanaka Kenzo ◽

Ryo Furutani ◽

Daisuke Hattori ◽

Joseph Jawa Kendawang ◽

Sota Tanaka ◽

...

Keyword(s):

Allometric Equations ◽

Tropical Rainforests ◽

Accurate Estimation ◽

Above Ground Biomass ◽

Ground Biomass

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Ultrasonic Imaging of a Crack Using Modified Time Reversal

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.846.553 ◽

2016 ◽

Vol 846 ◽

pp. 553-558

Author(s):

Jed Guinto ◽

Philippe Blanloeuil ◽

Chun H. Wang ◽

Francis Rose ◽

Martin Veidt

Keyword(s):

Time Reversal ◽

Computational Simulation ◽

Field Measurements ◽

Tone Burst ◽

Data Matrix ◽

Accurate Estimation ◽

Diffraction Tomography ◽

Static Data ◽

Reconstruction Quality ◽

Scatter Field

A majority of the research in Structural Health Monitoring focuses on detection of damage. This paper presents a method of imaging crack damage in an isotropic material using the Time Reversal imaging algorithm. Inputs for the algorithm are obtained via computational simulation of the propagation field of a crack in a medium under tone-burst excitation. The approach is similar to existing techniques such as Diffraction Tomography which makes use of the multi-static data matrix constructed using scatter field measurements from the computational simulation. Results indicate excellent reconstruction quality and accurate estimation of damage size.

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