Foliage Biomass of the forests of Eurasia: correction of empirical modeling methods

При разработке аллометрических моделей биомассы деревьев и древостоев имеется ряд неопределенностей, обусловленных несовершенством методических приемов как при получении исходной информации, так и при ее обработке с целью выявления искомых закономерностей. В статье дан анализ двух методических мифов, распространенных при оценке биомассы ассимиляционного аппарата деревьев и древостоев. Использована база экспериментальных данных о биомассе хвои (листвы) деревьев и древостоев соответственно в количестве 10,9 и 2,94 тысяч определений 16 и 10 древесных видов (родов) Евразии. На их основе построены всеобщие модели (generic models) биомассы хвои (листвы) на уровнях дерева и древостоя. Показано завышение оценок биомассы листвы (хвои) в результате механического переноса традиционного метода моделирования объема ствола дерева и древостоя на оценку биомассы их ассимиляционного аппарата. Рекомендовано отказаться от использования предиктора (D2 H) и включать в модель или один диаметр ствола, или диаметр ствола и высоту дерева раздельно. От использования полноты в качестве независимой переменной в модели ассимиляционного аппарата древостоев можно отказаться и во избежание возможных смещений оценок включать вместо полноты совокупность двух независимых переменных – густоту древостоя и средний диаметр стволов. When developing allometric models of the biomass of trees and forests, there are a number of uncertainties due to the imperfection of methodological techniques both for obtaining harvest data and for processing it in order to identify the desired patterns. Two methodological myths are analyzed in the paper that are common in assessing the foliage biomass of trees and stands. We used the database of harvest data on the foliage biomass of trees and stands, in the amount of 10.9 and 2.94 thousand definitions of 16 and 10 tree species (genera) of Eurasia respectively. Generic models of the foliage biomass are designed at tree and stand levels. It is shown that the estimation of foliage biomass is overestimated as a result of mechanical transfer of the traditional methods of modeling the volume of a tree stem and a forest stand to the estimation of the foliage biomass. It is recommended to abandon the use of the predictor (D2 H) and include in the model either single diameter of a stem, or the stem diameter and tree height separately. The use of basal area as an independent variable in the model of the stand foliage can be abandoned and, in order to avoid possible biases of estimates, include instead of it a set of two independent variables – the tree density and the average stem diameter.

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Estimation of DBH at Forest Stand Level Based on Multi-Parameters and Generalized Regression Neural Network

Forests ◽

10.3390/f10090778 ◽

2019 ◽

Vol 10 (9) ◽

pp. 778 ◽

Cited By ~ 5

Author(s):

Zhou ◽

Wu ◽

Zhou ◽

Fang ◽

Zheng ◽

...

Keyword(s):

Neural Network ◽

Remote Sensing ◽

Basal Area ◽

Tree Age ◽

Generalized Regression Neural Network ◽

Independent Variables ◽

Modeling And Prediction ◽

Independent Variable ◽

Generalized Regression ◽

Better Than

The diameter at breast height (DBH) is an important factor used to estimate important forestry indices like forest growing stock, basal area, biomass, and carbon stock. The traditional DBH ground surveys are time-consuming, labor-intensive, and expensive. To reduce the traditional ground surveys, this study focused on the prediction of unknown DBH in forest stands using existing measured data. As a comparison, the tree age was first used as the only independent variable in establishing 13 kinds of empirical models to fit the relationship between the age and DBH of the forest subcompartments and predict DBH growth. Second, the initial independent variables were extended to 19 parameters, including 8 ecological and biological factors and 11 remote sensing factors. By introducing the Spearman correlation analysis, the independent variable parameters were dimension-reduced to satisfy very significant conditions (p ≤ 0.01) and a relatively large correlation coefficient (r ≥ 0.1). Finally, the remaining independent variables were involved in the modeling and prediction of DBH using a multivariate linear regression (MLR) model and generalized regression neural network (GRNN) model. The (root-mean-squared errors) RMSEs of MLR and GRNN were 1.9976 cm and 1.9655 cm, respectively, and the R2 were 0.6459 and 0.6574 respectively, which were much better than the values for the 13 traditional empirical age–DBH models. The use of comprehensive factors is beneficial to improving the prediction accuracy of both the MLR and GRNN models. Regardless of whether remote sensing image factors were included, the experimental results produced by GRNN were better than MLR. By synthetically introducing ecological, biological, and remote sensing factors, GRNN produced the best results with 1.4688 cm in mean absolute error (MAE), 13.78% in MAPE, 1.9655 cm for the RMSE, 0.6574 for the R2, and 0.0810 for the Theil’s inequality coefficient (TIC), respectively. For modeling and prediction based on more complex tree species and a wider range of samples, GRNN is a desirable model with strong generalizability.

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HOW TO ESTIMATE BLACK WATTLE ABOVEGROUND BIOMASS FROM HETEROSCEDASTIC DATA?

FLORESTA ◽

10.5380/rf.v51i1.65236 ◽

2020 ◽

Vol 51 (1) ◽

pp. 028

Author(s):

Thiago Wendling Gonçalves de Oliveira ◽

Vinícius Morais Coutinho ◽

Luan Demarco Fiorentin ◽

Mateus Niroh Inoue Sanquetta ◽

Carlos Roberto Sanquetta ◽

...

Keyword(s):

Aboveground Biomass ◽

Nonlinear Models ◽

Basic Density ◽

Tree Height ◽

Error Variance ◽

Total Biomass ◽

Independent Variables ◽

Independent Variable ◽

Black Wattle ◽

Total Tree

This study developed a system of equations for predicting total aboveground and component biomass in black wattle trees. A total of 140 black wattle trees at age 10 years were measured regarding their diameter at 1.30 m height above the ground (d), total tree height (h), basic wood density (branches and stem), and biomass (stem, crown, and aboveground). We evaluated the performance of linear and nonlinear allometric models by comparing the statistics of R2adj., RRMSE%, and BIC. Nonlinear models performed better when predicting crown biomass (using only d as an independent variable), and stem and aboveground biomass (using d and h as independent variables). Adding basic density did not significantly improve biomass modeling. The residuals had non-homogeneous variance; thus, the fitted equations were weighted, with weights derived from a function containing the same independent variables of the fitted biomass function. Subsequently, we used a simultaneous set of equations to ensure that the sum of each component's estimated biomass values was equal to the total biomass values. Simultaneous fitting improved the performance of the equations by guaranteeing the components' additivity, and weighted regression allowed to stabilize error variance, ensuring the homoscedasticity of the residuals.

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Restore and sequester: estimating biomass in native Australian woodland ecosystems for their carbon-funded restoration

Australian Journal of Botany ◽

10.1071/bt11018 ◽

2011 ◽

Vol 59 (7) ◽

pp. 640 ◽

Cited By ~ 18

Author(s):

J. H. Jonson ◽

D. Freudenberger

Keyword(s):

Native Species ◽

Basal Area ◽

Tree Height ◽

Ground Level ◽

Stem Diameter ◽

Allometric Equations ◽

Total Biomass ◽

Tree Biomass ◽

Below Ground ◽

Total Tree

In the south-western region of Australia, allometric relationships between tree dimensional measurements and total tree biomass were developed for estimating carbon sequestered in native eucalypt woodlands. A total of 71 trees representing eight local native species from three genera were destructively sampled. Within this sample set, below ground measurements were included for 51 trees, enabling the development of allometric equations for total biomass applicable to small, medium, and large native trees. A diversity of tree dimensions were recorded and regressed against biomass, including stem diameter at 130 cm (DBH), stem diameter at ground level, stem diameter at 10 cm, stem diameter at 30 cm, total tree height, height of canopy break and mean canopy diameter. DBH was consistently highly correlated with above ground, below ground and total biomass. However, measurements of stem diameters at 0, 10 and 30 cm, and mean canopy diameter often displayed equivalent and at times greater correlation with tree biomass. Multi-species allometric equations were also developed, including ‘Mallee growth form’ and ‘all-eucalypt’ regressions. These equations were then applied to field inventory data collected from three locally dominant woodland types and eucalypt dominated environmental plantings to create robust relationships between biomass and stand basal area. This study contributes the predictive equations required to accurately quantify the carbon sequestered in native woodland ecosystems in the low rainfall region of south-western Australia.

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Biomass functions applicable to European beech

Journal of Forest Science ◽

10.17221/4553-jfs ◽

2012 ◽

Vol 51 (No. 4) ◽

pp. 147-154 ◽

Cited By ~ 23

Author(s):

E. Cienciala ◽

M. Černý ◽

J. Apltauer ◽

Z. Exnerová

Keyword(s):

Tree Height ◽

European Beech ◽

Biomass Estimation ◽

Managed Forests ◽

Independent Variables ◽

Breast Height ◽

Allometric Functions ◽

Branch Biomass ◽

Independent Variable ◽

Total Tree

This material describes parameterization of allometric functions applicable to biomass estimation of European beech trees. It is based on field data from destructive measurements of 20 full-grown trees with diameter at breast height (dbh) from 5.7 to 62.1 cm. The parameterization was performed for total tree aboveground biomass (AB; besides stump), stem and branch biomass, respectively. The allometric functions contained two or three parameters and used dbh either as a single independent variable or in combination with tree height (H). These functions explained 97 to 99% of the variability in the measured AB. The most successful equation was that using both dbh and H as independent variables in combination with three fitted parameters. H, as the second independent variable, had rather a small effect on improving the estimation: in the case of AB, H as independent variable improved prediction accuracy by 1–2% whereas in the case of branch biomass by about 5%. The parameterized biomass equations are applicable to tree specimens of European beech grown in typically managed forests.

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Above-ground phytomass of a tropical deciduous forest on the coast of Jalisco, México

Journal of Tropical Ecology ◽

10.1017/s0266467400006131 ◽

1992 ◽

Vol 8 (01) ◽

pp. 87-96 ◽

Cited By ~ 67

Author(s):

Angelina Martinez-Yrizar ◽

Jose Sarukhan ◽

Alfredo Perez-Jimenez ◽

Emmanuel Rincon ◽

Jose Manuel Maass ◽

...

Keyword(s):

Regression Analysis ◽

Deciduous Forest ◽

Basal Area ◽

Tree Height ◽

Tropical Dry Forests ◽

Stepwise Multiple Regression ◽

Tropical Deciduous Forest ◽

Stepwise Multiple Regression Analysis ◽

Independent Variable ◽

The Mean

ABSTRACTPhytomass was determined for a tropical deciduous forest in Chamela, Jalisco, México. The mean canopy height was 6.9 m, and the total basal area was 25.6 m2ha−1(dbh > 3.0 cm). The estimated phytomass for this forest (85 Mg ha−1) is among the highest values for tropical dry forests with similar seasonal climates. A stepwise multiple regression analysis showed that phytomass can be predicted firstly by basal area (R2= 0.88), then by wood specific gravity (R2= 0.91), and finally by the inclusion of tree height in the regression (R2= 0.92). Each new independent variable explained significant variance in the phytomass estimation.

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Comparison of interferometric and stereo-radargrammetric 3D metrics in mapping of forest resources

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprsarchives-xl-7-w3-425-2015 ◽

2015 ◽

Vol XL-7/W3 ◽

pp. 425-431

Author(s):

K. Karila ◽

M. Karjalainen ◽

X. Yu ◽

M. Vastaranta ◽

M. Holopainen ◽

...

Keyword(s):

Forest Inventory ◽

Forest Canopy ◽

Basal Area ◽

Tree Height ◽

Forest Resources ◽

Canopy Height ◽

Stem Diameter ◽

Stem Volume ◽

Test Plot ◽

3D Data

Accurate forest resources maps are needed in diverse applications ranging from the local forest management to the global climate change research. In particular, it is important to have tools to map changes in forest resources, which helps us to understand the significance of the forest biomass changes in the global carbon cycle. In the task of mapping changes in forest resources for wide areas, Earth Observing satellites could play the key role. In 2013, an EU/FP7-Space funded project “Advanced_SAR” was started with the main objective to develop novel forest resources mapping methods based on the fusion of satellite based 3D measurements and in-situ field measurements of forests. During the summer 2014, an extensive field surveying campaign was carried out in the Evo test site, Southern Finland. Forest inventory attributes of mean tree height, basal area, mean stem diameter, stem volume, and biomass, were determined for 91 test plots having the size of 32 by 32 meters (1024 m<sup>2</sup>). Simultaneously, a comprehensive set of satellite and airborne data was collected. Satellite data also included a set of TanDEM-X (TDX) and TerraSAR-X (TSX) X-band synthetic aperture radar (SAR) images, suitable for interferometric and stereo-radargrammetric processing to extract 3D elevation data representing the forest canopy. In the present study, we compared the accuracy of TDX InSAR and TSX stereo-radargrammetric derived 3D metrics in forest inventory attribute prediction. First, 3D data were extracted from TDX and TSX images. Then, 3D data were processed as elevations above the ground surface (forest canopy height values) using an accurate Digital Terrain Model (DTM) based on airborne laser scanning survey. Finally, 3D metrics were calculated from the canopy height values for each test plot and the 3D metrics were compared with the field reference data. The Random Forest method was used in the forest inventory attributes prediction. Based on the results InSAR showed slightly better performance in forest attribute (i.e. mean tree height, basal area, mean stem diameter, stem volume, and biomass) prediction than stereo-radargrammetry. The results were 20.1% and 28.6% in relative root mean square error (RMSE) for biomass prediction, for TDX and TSX respectively.

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Penafsiran Luas Bidang Dasar Tegakan Pinus Merkusii menggunakan Foto Udara di Kesatuan Pemangkuan Hutan (KPH) Kedu Perum Perhutani Unit 1 Jawa Tengah

Forum Geografi ◽

10.23917/forgeo.v23i2.5005 ◽

2009 ◽

Vol 23 (2) ◽

pp. 112

Author(s):

S Sahid

Keyword(s):

Regression Analysis ◽

Aerial Photograph ◽

Basal Area ◽

Tree Height ◽

Tree Density ◽

Stem Diameter ◽

Permanent Plots ◽

Crown Diameter ◽

Pinus Merkusii ◽

Stand Basal Area

The research aim to estimate the basal area of Pinus merkusii combired comprises measurement by aerial photograph with scale of 1:20.000 field and to measurement field. The stand parameters measured are the number of the trees per hectare (N), the tree height (H) and crown diameter (D). Whereas, estimation of the stand basal area was based on the measurement of the stem diameter in the permanent plots. The result of the regression analysis showed that the based area of the Pinus merkusii stand (lbds) had correlation with the number of the trees per hectare (N), the tree height (H) and crown diameter (D), the regression is as follows: Basal areas or tree densities of compartement 100 and 102 have been optimum. Therefore, resin production compartement 100 and 102 is higher than compartement 101 having lower basal are or tree density. It is for those reasons, the compartement 101 needs action to cut the suppressed trees to make optimum basal area.

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Growth assessment of upper hill dipterocarp (Shorea platyclados) at the various slope in a rehabilitated landscape

IOP Conference Series Earth and Environmental Science ◽

10.1088/1755-1315/914/1/012027 ◽

2021 ◽

Vol 914 (1) ◽

pp. 012027

Author(s):

F Reksawinata ◽

P Pamoengkas ◽

H H Rachmat

Keyword(s):

Growth Performance ◽

Basal Area ◽

Tree Height ◽

Average Diameter ◽

Stem Diameter ◽

Average Height ◽

Annual Increment ◽

Area Index ◽

Shorea Platyclados ◽

Mean Annual Increment

Abstract Rehabilitation aims to improve landscape function while increasing its resilience to climate change. Gunung Dahu research forest is a rehabilitated hilly landscape that is planted with more than 25 dipterocarp species, including an upper hill dipterocarp tree of Shorea platyclados at various site conditions. This study aimed to assess the growth performance of S. platyclados at five sloping levels class of 0-8%, 8-15%, 15-25%, 25-45%, and >45%. Observed growth attributes were stem diameter, total height, basal area, Mean Annual Increment (MAI), and Leaf Area Index (LAI), and diameter. The results showed that sloping levels significantly affect the growth performance of the planted trees. The highest slope level (>45%) supported the highest average stem diameter and tree height (41.48 cm and 20.86 m). The sloping level of >45%, 25-45%, 15-25%, 8-15%, and 0-8% yield different value of average diameter which were 41.48 cm, 35.86 cm, 36.54 cm, 34.61 cm, and 31.23, while the average height were 20, 86m, 19.78 m, 16.72 m, 18.84 m, 18.61 m respectively. Thus, the upper hill dipterocarp of S. platyclados is a prospective native tree species for rehabilitating hilly upland landscapes.

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Height-Diameter Allometry for Tree Species in Tanzania Mainland

International Journal of Forestry Research ◽

10.1155/2019/4832849 ◽

2019 ◽

Vol 2019 ◽

pp. 1-17 ◽

Cited By ~ 5

Author(s):

W. A. Mugasha ◽

E. W. Mauya ◽

A. M. Njana ◽

K. Karlsson ◽

R. E. Malimbwi ◽

...

Keyword(s):

Forest Structure ◽

Forest Type ◽

Model Development ◽

Basal Area ◽

Tree Height ◽

Forest Stand ◽

Miombo Woodlands ◽

Mixed Effect ◽

Nonlinear Mixed Effect ◽

Stand Attributes

Total tree height (H) and diameter at beast height (D) are important independent variables in predicting volume, biomass, and other forest stand attributes. However, unlikeDmeasurement, which is easy to measure with high accuracy,Hmeasurement is laborious. This study, therefore, developedH-Drelationships for ten different forest types in Tanzania Mainland. Extents in which climate and forest stand variables explain the variation inH-Dallometry were also assessed. A total of 31782 sample trees covering miombo woodlands, humid montane, lowland forests, bushlands, grasslands, mangroves, cultivated land, wetlands forests, and pines andEucalyptusspecies plantations were used for model development. TheHestimating model without climate and forest stand variables referred herein as “base model” was first developed followed by “generalized model” which included climate and stand variables. All the data were fitted using nonlinear mixed effect modelling approach. Results indicated that generalizedHestimating models had better fit than the base models. We therefore confirm a significant contribution of climate and forest structure variables in improvingH-Dallometry. Among the forest structure variables, basal area (BA) was far more important explanatory variable than other variables. In addition, it was found that the mean treeHtends to increase with the increase of mean precipitation (PRA). We therefore conclude that forest specific generalizedHmodel is to be applied when predictingH. When forest type information is not available, generalized regional model may be applied. Base model may be applied when forest stand or climate information are missing.

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Time trends in inheritance and projected efficiencies of early selection in a large 17-year-old progeny test of Pinusradiata

Canadian Journal of Forest Research ◽

10.1139/x91-168 ◽

1991 ◽

Vol 21 (8) ◽

pp. 1200-1207 ◽

Cited By ~ 24

Author(s):

J. N. King ◽

R. D. Burdon

Keyword(s):

Selection Criterion ◽

Basal Area ◽

Tree Height ◽

Stem Diameter ◽

Stem Volume ◽

Narrow Sense ◽

Narrow Sense Heritability ◽

Needle Penetration ◽

Expected Gain ◽

Partial Correlations

In an open-pollinated progeny trial of Pinusradiata D. Don, stem diameter assessments were cross-referenced for 410 families for ages 5, 10, and 17 years from planting. Also cross-referenced were Cyclaneusma needle cast (CYCLA) and wood density (PILO) measured by Pilodyn needle penetration. Estimated narrow-sense heritability for stem diameter declined mildly from 0.34 at age 5 to 0.25 at age 17. Estimated heritability of family means, however, only declined from 0.59 to 0.55. CYCLA and PILO gave, respectively, narrow-sense heritability estimates of 0.32 and 0.40, with repeatabilities of family means of 0.57 and 0.67. The genetic age-age correlations for stem diameter were all positive and somewhat higher than phenotypic (family-mean) age–age correlations. Such correlations indicated comparable or slightly slower rank changes among progeny families than had been reported previously for diameter, basal area, or stem volume in P. radiata and Pinustaeda L., but faster rank changes than the literature reports for tree height. A considerable contribution of CYCLA to rank changes in stem diameter was evident from path coefficients and partial correlations. PILO made no evident contribution to rank changes. Predicted gains for stem diameter at age 17 were almost maximal using year-10 data, while using CYCLA as an auxiliary selection criterion enhanced expected gain, particularly with selection at year 5. Predicted gains for stem diameter, with age–age correlations extrapolated according to the Lambeth relationship, indicated maximal gains per annum with selection at 7–8 years for rotations of 25–30 years.

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