Monograph. Bogor, July 2012

Monograph Models for Estimating Tree Biomass

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Haruni Krisnawati Wahyu Catur Adinugroho Rinaldi Imanuddin

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at Various Forest Ecosystem Types in Indonesia

Bogor, July 2012

MINISTRY OF FORESTRY FORESTRY RESEARCH AND DEVELOPMENT AGENCY

RESEARCH AND DEVELOPMENT CENTER FOR CONSERVATION AND REHABILITATION

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Monograph Models for Estimating Tree Biomass

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Bogor, July 2012



Jakarta, Oktober 2011

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Monograph Allometric Models for Estimating Tree Biomass at Various Forest Ecosystem Types in Indonesia

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© 2012 Research and Development Center for Conservation and Rehabilitation, Forestry Research and Development Agency ISBN: 978-979-3145-93-8 All rights reserved

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It is prohibited to reproduce all or part of this monograph, in the form of photocopy, print, microfilm, electronic media or any other form, except for education or other non-commercial purposes by including the following sources: Krisnawati, H., W.C. Adinugroho and R. Imanuddin. 2012. Monograph: Allometric Models for Estimating Tree Biomass at Various Forest Ecosystem Types in Indonesia. Research and Development Center for Conservation and Rehabilitation, Forestry Research and Development Agency, Bogor, Indonesia. Translated from:

Krisnawati, H., W.C. Adinugroho dan R. Imanuddin. 2012. Monograf: Model-Model Alometrik untuk Pendugaan Biomassa Pohon pada Berbagai Tipe Ekosistem Hutan di Indonesia. Pusat Penelitian dan Pengembangan Konservasi dan Rehabilitasi, Badan Penelitian dan Pengembangan Kehutanan, Bogor, Indonesia. Published by: Research and Development Center for Conservation and Rehabilitation, Forestry Research and Development Agency – Ministry of Forestry Jl. Gunung Batu No. 5, Bogor 16610, Indonesia Tel/Fax: +62 251 8633234 / +62 251 8638111 Email: [email protected]; website: http://www.p3kr.com

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Foreword

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Ecosystem Types in Indonesia” was prepared to solve this problem. This monograph is a product of the study by researchers of the Forestry Research and Development Agency (FORDA) on the research related to the tree biomass and volume allometric models that have already been developed at various tree species and forest ecosystem types in Indonesia. This monograph is expected to serve as an important input to the development of the Indonesian National Carbon Accounting System (INCAS). In order to produce this monograph, an extensive study of the available literature was required. The constructive input of experts on the substance of the monograph during the Focus Group Discussion and the Expert Team meeting have increased the quality of this monograph. This was an essential input to the realization and achievement of this monograph. We would like to express our appreciation and thanks to all the parties that have contributed directly or indirectly to the preparation of this monograph. Thank you to IAFCP (IndonesiaAustralia Forest Carbon Partnership) that provided financial assistance to the discussion of the final draft of this monograph through the Focus Group Discussion and Expert Team meeting and also assisted in the publication. Specifically, to the Director of the Research and Development Center for Conservation and Rehabilitation and to the Writer Team, we express our appreciation for and congratulations on this achievement.

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It is clear that climate change, as an implication of the increased concentration of greenhouse gas (GHG) in the atmosphere, has had an impact on the sustainability of the earth’s living creatures. In order to protect the stability of the concentration of GHG in the atmosphere, several mitigation and adaptation efforts should be made to reduce GHG emissions and minimize the impact of climate change. As a framework for mitigating the impacts of climate change, REDD+ is perceived as one of the policy mechanisms that has huge potential to reduce emissions from deforestation and forest degradation, through its role in conservation, sustainable forest management and enhancement of forest carbon stocks. One of the important components for the implementation of REDD+ is the application of a transparent, comparable, coherent, complete and accurate MRV (measurement, reporting and verification) system. The challenge in implementing such a system is enabling society and concerned parties to understand their role in attaining targets for reducing emissions and increasing carbon stocks. At a most basic level, the tools for the calculation of carbon stocks and the monitoring of changes should be prepared in order to calculate the emissions level in all ecosystem types and land uses. Under a REDD+ mechanism, the method for determining the Reference Emission Level most appropriate to the specific local conditions in Indonesia is imperative. For this, specific allometric models that are appropriate to the location, ecosystem type and tree species are necessary. Currently, the guidelines or references related to the use of allometric models for estimating biomass and carbon stock as well as for determining the local (specific) emission factor are not yet available in Indonesia. The monograph “Allometric Models for Estimating Tree Biomass at Various Forest

Jakarta, July 2012 Director General of the Forestry Research and Development Agency,

Dr. Ir. Iman Santoso, M.Sc

MONOGRAPH Allometric Models for Estimating Tree Biomass at Various Forest Ecosystem Types in Indonesia

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Acknowledgements

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Australia Forest Carbon Partnership (IAFCP), IAFCP Coordinators, and Senior Forestry Expert, Silver Hutabarat from INCAS-IAFCP. High appreciation is also given to the team of experts who reviewed the draft monograph, i.e. Teddy Rusolono (IPB), Ronggo Sadono (UGM), Fajar Pambudi (Unmul), Tatang Tiryana (IPB), Sofwan Bustomi (FORDA), Ari Wibowo (FORDA), and Djoko Wahjono (FORDA), and to all the participants of the Focus Group Discussion on “Assessment of Tree Biomass and Volume Allometric Models for Carbon Accounting in Indonesia” that was held on 7-8 June 2012 in Bogor and the participants of the Expert Team Meeting held on 27-28 June 2012 in Jakarta, who have provided constructive inputs for the completion of the contents and substance of this monograph. We hope that this monograph will be beneficial.

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This monograph was prepared on the initiative of the Writer Team as researchers of the Research and Development Center for Conservation and Rehabilitation – Forestry Research and Development Agency. However, we are very much aware that without the support and assistance of several parties, this monograph could never have been realized. Because of this, we would like to express our thanks to all the parties who have assisted in the preparation of this monograph, especially to Enok Heryati and Popi Berlin (technician of Forest and Environmental Service Valuation Research Group – Research and Development Center for Conservation and Rehabilitation) who have assisted in the compilation of data and information from various sources of literature. The compilation of this monograph would not have been possible without the strong support and encouragement of the Director General of the Forestry Research and Development Agency (FORDA) with in Ministry of Forestry, the Director of the Research and Development Center for Conservation and Rehabilitation in FORDA, the Director of the Forest Resources Inventory and Monitoring (Directorate General of Forestry Planning) as the Executing Agency of Indonesia-

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Bogor, July 2012 Writer Team, Haruni Krisnawati Wahyu Catur Adinugroho Rinaldi Imanuddin

Table of Contents Foreword ......................................................... iii Acknowledgements ......................................... iv Table of Contents .............................................. v List of Tables.................................................... vi List of Figures ................................................. vii

Background ......................................... 3 Objectives and Benefits ......................... 4 Data Collection ..................................... 7 Evaluation of the Allometric Models ... 10

3. Description of the Database ...................... 11

4.2

Tree Volume Allometric Models .......... 28

5.1

Variability of tree biomass and volume estimates within natural forest ecosystem ........................................... 33

5.2

Variability of tree biomass and volume estimates within plantation forest ecosystem ........................................... 36

Source of Information of the Allometric Models ............................................... 13 Geographical Distribution of the Allometric Models .............................. 14

6. The Use of Allometric Models for Estimating Biomass ............................ 41 7. Closing....................................................... 57 References ...................................................... 61 Appendices ..................................................... 65

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3.2

Tree Biomass Allometric Models ......... 27

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3.1

4.1

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2. Methods ...................................................... 5 2.1 2.2

Scope of the Allometric Models by Species................................................ 22

5. Tree Biomass and Volume Estimates......... Estimates......... 31

1. Introduction ................................................. 1 1.1 1.2

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Abstract ........................................................... xi

Distribution of the Allometric Models by Ecosystem Type ............................. 16

4. Allometric Models ..................................... 25

List of Appendices ......................................... viii Glossary ........................................................... ix

3.3


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List of Tables Scope of the allometric models in this monograph connected to land use categories according to the IPCC Guidelines and Directorate General of Forestry Planning .... 17

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Biomass allometric models that can be used to estimate aboveground tree biomass according to the main ecosystem type ......... 46 Volume allometric models that can be used to estimate tree volume according to the main ecosystem type .......................................... 49

The values of BEF (biomass expansion factor) that have been developed for some tree species and ecosystem types in Indonesia .... 51

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Default value of BEF according to IPCC Guidance (2003) ........................................ 54

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Default value of BCEF according to IPCC Guidelines (2006) ...................................... 55

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Possible sequences to determine the approach used in biomass estimation (numbers of sequences refer to Figure 19) ... 55

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3.

4.

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List of Figures

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Parts of the trees measured for the tree biomass allometric model ............................. 9

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Types of volume measured for the tree volume allometric model .............................. 9

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The number of literatures that presented tree biomass and/or volume allometric models used in this monograph until mid-2012....... 13

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Geographical distribution of the availability of tree biomass and volume allometric models that have been developed in Indonesia ........ 15

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Geographical distribution of the available tree biomass allometric models developed in Indonesia ................................................... 18

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Geographical distribution of the available tree volume allometric models developed in Indonesia ................................................... 21

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Distribution of the available tree biomass and volume allometric models by ecosystem type ........................................................... 22

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Distribution of the available tree biomass allometric models by species ...................... 23

13. Aboveground tree biomass estimated from various biomass allometric models for dryland forest, peat swamp forest and mangrove forest ecosystem types (References are based on Appendix 3) ........ 34 14. Tree volume estimated from various volume allometric models for dryland forest, peat swamp forest and mangrove forest ecosystem types (References are based on Appendix 5)............................................... 5)............................................... 35

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Selection of the literatures used for analysis in this monograph ........................................ 8

15. Aboveground tree biomass estimated from various biomass allometric models for fast-growing and slow-growing tree species (References are based on Appendix 3) ......... 37

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16. Tree volumes estimated from various volume allometric models for fast-growing and slowgrowing tree species (References are based on Appendix 5)............................................... 38

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17. Aboveground tree biomass for (a) Acacia mangium and (b) Pinus merkusii estimated from various biomass allometric models developed from several locations (References are based on Appendix 3) ......... 39

10. Distribution of the available tree volume allometric models by species ...................... 24

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11. Distribution of the available tree biomass allometric models according to the part of tree biomass measured ............................... 27

12. Distribution of the available tree volume allometric models according to volume types (tdl on stem volume followed by numbers indicates that the model was developed for estimating stem volume up to the top diameter limit of the stem, i.e. 4 cm, 5 cm, 7 cm, and 10 cm) .......................................... 29

18. Tree volumes for (a) Acacia mangium and (b) Pinus merkusii estimated from various allometric volume models developed from several locations (References are based on Appendix 5)............................................... 40 19. The diagram presenting the procedures of the use of available allometric models for estimating tree biomass .............................. 45


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List of Appendices 3. References-Appendices 1 and 2 .................... 89 4. Tree volume allometric models that have been developed according to tree species and ecosystem type in Indonesia ......................... 95 5. References-Appendix 4.............................. 115

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1. Tree biomass allometric models that have been developed according to tree species and ecosystem type in Indonesia ......................... 67 2. List of tree species included in the development of biomass allometric models for mixed-species ......................................... 85

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Glossary Aboveground tree : Total oven-dry weight of all parts of a tree above the ground including stem, biomass branch, twig, leaves, flower and fruit if any Accuracy

: How close an estimated value is to the actual (measured) value

Allometry

: The relationship between the size or growth of a component with that of the whole organism

BCEF

: Biomass Conversion and Expansion Factor,, a factor used for expansion of merchantable growing stock volume to aboveground biomass, stated in unit per ha

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Belowground tree : Total oven-dry weight of the part of a tree under the ground (roots) biomass : Systematic error, or deviation from the true value of measurement

Biomass

: Total dry weight of living organism, stated in kilograms or tons

Branch biomass

: Total oven-dry weight of the branch part of a tree

Branch volume

: Volume of the part of the tree that grows from the trunk

Carbon

: Chemical element with symbol C and atomic number 6

Carbon stock

: Carbon stored in biomass

Clear bole height

: Height of the tree measured until its first branching

Correction factor

: Constant value used to correct the bias as a consequence of the data transformation to the logarithm value

Merchantable volume

: Stem volume up to the height of crown base

Dbh

: Volume of the crown part of a tree : Diameter at breast height height, a diameter as high as the breast or about 1.3m above the ground : A measure of how well the variation of dependent variable (Y) ( can be explained by the independent variable ((X) in the regression model, often written with the symbol R2 or R-sq

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Determination coefficient

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Crown volume

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Bias

Error

: Residual or deviation

Firewood volume

: Wood volume measured on the basis of the wood that is used for firewood. The firewood volume is not determined one by one, but in stacked volume

Flower biomass

: Total oven-dry weight of the flower part of a tree

Form factor

: The correction factor; calculated from the ratio between the actual volume of the tree and the cylinder volume with the same diameter and height

Fruit biomass

: Total oven-dry wight of the fruit part of a tree

Height of the crown base

: Height of the tree measured until the branches form a crown

Leaf biomass

: Total oven-dry weight of the leaf part of a tree


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Regression analysis : A statistical method for estimating the relationship between a dependent variable or response variable (Y) and one or more independent variables or predictor variables (X) : Total oven-dry weight of the root part of a tree

Sample

: Object selected to represent a population and used for analysis

Sample tree

: A tree selected to represent a population with the criteria normal growth

Stand

: Community of plants (trees) in a certain area

Stand BEF

: Stand Biomass Expansion Factor, a factor used to expand the stem biomass per unit area of the stand [∑( Volume*wood density)] to aboveground stand biomass

Stem biomass

: Total oven-dry weight of the stem part of a tree

Total tree height

: Length of a tree that has fallen plus the height of the remaining base (stump), stated in meters with one digit after the decimal point

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Root biomass

Total stem volume : Volume measured on the basis of total height (until the top) of the tree Total tree biomass : Total oven-dry weight of all the parts of a tree

Factor, a factor used to expand the stem biomass to : Tree Biomass Expansion Factor, aboveground tree biomass

Tree volume

: A product of basal area and tree height/length, and then corrected by a constant factor (known as a tree form factor)

Twig biomass

: Total oven-dry weight of the twig part of a tree

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Tree BEF

Clear bole volume : Stem volume measured until the height of the first branch Variant

: How far the data is distributed at the average

Volume

: The quantity of three-dimensional space of an object, stated in cubic meter, as a product of the basic units of length, width/thickness, and height

: Also known as specific gravity of wood, i.e. oven-dry weight per unit volume of wood (kg/m3 or gr/cm3)

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Wood density

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Stem volume up to : Stem volume measured until the height of a certain point diameter (example: 4 x cm top diameter cm, 5 cm, 7 cm, 10 cm) limit

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Glossary

Abstract

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This monograph reviews tree biomass and volume allometric models that have been developed for various tree species and ecosystem types in Indonesia. The mathematical forms of the allometric models, the associated statistical parameters, as well as information about the size (tree diameter and height) and the number of sample trees used to develop the models were collated from various sources published in scientific journals (both national and international), research and technical reports, proceedings and student theses. The total number of the allometric models presented in this monograph is 807 models consisting of 437 allometric models for estimating tree biomass components and 370 allometric models for estimating several types of tree volume. Results of the spatial distribution analyses of the existing allometric models indicated that 90% of the allometric models were developed for three major islands (Java, Kalimantan and Sumatra). A relatively small number of biomass allometric models were developed for eastern islands of Indonesia (Papua and Sulawesi), except for several volume allometric models. Either biomass or volume allometric models are available for some major ecosystem types in Indonesia even though their distributions are uneven throughout the country. Most (88%) of the biomass allometric models were developed to estimate aboveground tree biomass components. Besides information on the model distribution and data coverage, this monograph also analyzes variability of the predicted biomass and volume resulted from the models, the use of the models for estimating tree biomass, gap analysis and strategy to fill the gaps. The collected information of allometric models provides a basic tool for estimation of forest biomass based on its ecosystem type. The information also provides input to support the national carbon accounting system and estimation of carbon stock changes from greenhouse gas emissions reduction and carbon stock enhancement in the land-based sector.

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Keywords:: allometric model, biomass, volume, tree diameter, tropical forest ecosystem, Indonesia


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Introduction


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Accurate information on the forest carbon stored in biomass is required to describe the conditions of the forest ecosystem to support the management of forests and specifically, the sustainability of forest resources, understanding the dynamics of carbon in the forest ecosystem, and estimating the impact on the ecosystem as a consequence of deforestation, change in land use, and climate change (Eamus et al., 2000; Comley and McGuiness, 2005; Soares and SchaefferNovelli, 2005). This information is also imperative as a basic component in the accounting and monitoring of national carbon (Eamus et al., 2000; Snowdon et al., 2000; Keith et al., 2000) which is the main input in developing a strategy for the reduction of greenhouse gas (GHG) emissions, particularly carbon dioxide (CO2) from the land sector. The carbon stock that is stored in the forest biomass and its changes (the loss of carbon through emissions as a consequence of deforestation and forest degradation, and the increase in carbon through sequestration from growth, forest regeneration, aforestation and reforestation) should be measured and monitored because the changes in carbon stock will influence the concentration of carbon dioxide (CO2) in the atmosphere. The carbon stock and its changes are relatively difficult to measure, and its estimated value probably still depends on the uncertainty level (Clark et al., al., 2001; Jenkins et al., 2003). This uncertainty can be due to sampling error, measurement error or regression model error (MacDicken, 1997). Reliability of the estimated forest carbon stock and understanding of the dynamics of carbon in the forest ecosystem can be increased by applying current knowledge concerning tree allometry, in the form of the biomass allometric model and the volume allometric model (Jenkins et al., 2003;

Zianis and Mencuccini, 2003; Lehtonen et al., 2004). The biomass allometric model can be used to directly estimate the stand tree biomass, from tree measurement data (diameter or combination of diameter and height) in the forest stand inventory, or by adding the specific gravity or wood density and the biomass expansion factor (IPCC, 2003) or the biomass conversion and expansion factor (IPCC, 2006) in using the tree volume allometric model. From the aggregation of the biomass of individual trees, the biomass of the forest stand can be obtained. A remote sensing technique can also be applied to estimate the stand forest volume and biomass (Montes eett al al., 2000; Drake at al., al., 2002). However, the accuracy of the estimated value greatly depends on the data from measuring tree dimensions in the field; in this case, the allometric model is still needed to estimate the biomass at individual tree level before the estimated biomass at stand level or wider forest area can be obtained. The allometric model is commonly used in biology to describe change in a systematic way (Huxley, 1993; Parresol, 1999). The term allometry comes from the Greek word ‘allos’ which means ‘other’ and ‘metron’ which means ‘measurement’ (Niklas, 1994). Allometry is used to indicate a proportion between the relative growth rates of the different components of one individual tree. This relationship is mathematically referred to as an allometric model wherein it is generally stated in the form of a logarithmic or power function. By using the allometric model that is already formulated, the biomass of one tree can be estimated just by entering the parameter of the result of measuring the dimension of the tree, like the diameter at breast height (Dbh) or the combination of Dbh and height. The stand biomass can later be calculated by summing the biomass of individual trees.

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1.1 Background


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specific local allometric models based on the tree species and forest ecosystem types in Indonesia.

1.2 Objectives and Benefits

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This monograph aims to serve as a reference in estimating forest biomass through: (1) compilation and review on tree biomass and volume allometric models that have been developed for several tree species and forest ecosystem types in Indonesia, (2) development of an allometric model database to know the status of information currently available on tree allometry, identification of the gaps of information and modeling method, and (3) optimization of the use of allometric models. This monograph provides basic information for the national carbon accounting system and for estimating the carbon stock change from GHG emissions reduction, for example through the REDD+ mechanism. Furthermore, this monograph can be used as a supporting instrument in the implementation of Presidential Decree No. 71/2011 concerning the Implementation of the National Greenhouse Gas Inventory, particularly in the land-based sector.

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In the mechanism of REDD+ (Reducing Emissions from Deforestation and Forest Degradation, and the role of conservation, sustainable forest management and enhancement of forest carbon stock), allometric models that are appropriate to the specific condition of the location in Indonesia are necessary to estimate the change in the biomass and forest carbon stocks produced from the activity of reducing GHG emissions. Currently, guidelines or references related to the use of allometric models for estimating biomass and carbon stock and determining the local (specific) emission factor in Indonesia are unavailable. On the other hand, the allometric models to estimate tree biomass (including its components, e.g. stem, branches, twigs and leaves) and tree stem volume (including measurements from the tree stem volume to the height of the first branch or crown base, the volume of the tree stem up to a certain point diameter limit and the total stem volume) have already been developed for several tree species and forest ecosystems in Indonesia. In order to use these allometric models as a reference, a comprehensive study on tree biomass and volume allometric models that already exist for Indonesia is necessary. A study on several tree volume allometric models in Indonesia was conducted by Bustomi et al. (2002); however, it is limited to the tree species found in plantation forests. Keith and Krisnawati (2010) conducted a comprehensive study on research related to the estimation of forest biomass in Indonesia, including the tree biomass allometric models that already existed. The compilation of tree biomass and volume allometric models requires a huge amount of time, energy and cost (particularly for large tree samples). Because of this, allometric models for the estimation of tree biomass (both biomass and volume) that have been developed in Indonesia should be compiled in a database and analyzed to obtain a reference on the

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Introduction

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02

Methods


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The compilation of tree biomass and volume allometric models presented in this monograph is based on existing allometric models that have been developed for several tree species and forest ecosystem types in Indonesia. In order to compile these models, a survey and literature study were conducted of more than 250 references that reported or presented the results of studies related to tree biomass and/or volume or model formulation for estimating these dimensions to estimate carbon stock stored in biomass at various types of vegetation and forest ecosystems in Indonesia. Sources of literature studied included national and international publications, in the form of published scientific journals and seminar proceedings, and unpublished research reports, technical reports, student theses and dissertations. The literatures studied in this monograph were limited to literatures issued or published prior to mid-2012. From the above literatures, the study was then limited to only the literature that reported or presented allometric models that were developed from sample trees or field data gathered from the site or location of the research applying the destructive sampling (Figure 1). The destructive method directly measures the biomass by harvesting the sample tree and measuring the actual biomass of every individual component of the sample tree (stem, branch, twig, leaves, roots, flower and fruit if any) by weighing. The literatures that present the result of the estimation of the forest biomass and carbon stock in one location but use the general allometric model such as the one developed by Brown (1997) and Chave et al. (2005), or that which use an allometric model developed in another location (outside the research location) were not included in this monograph. Similarly, mathematical models produced from the relationship of the remote sensing data

(satellite image), like the non-destructive method for the estimation of aboveground biomass, are not included in this monograph. From each literature studied, all information related to the details of the location was recorded: (1) location of the research or location where the sample trees were obtained (province, district, sub-district, village or specific name of the location), (2) geographical position (longitudinal and latitudinal coordinates), (3) condition of the location (forest type, rainfall, temperature, altitude, soil type, land use history), and (4) stand condition (dominant tree species, stand age for plantation forests, year of harvesting for loggedover forests or year when a disturbance occurred (such as burning) for secondary forests, spacing or stand density, stand height, etc.). Aside from these, the time when the research or sample tree collection in the field site was carried out was also recorded. This information (if available from the literature source) was compiled and stored in a database.

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2.1 Data Collection


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Stocktaking information through tracking the literature related to tree biomass and volume estimation

Does the literature have an allometric model?

No

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Yes

Was the model developed sitespecific?

No

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The literature is included in the analysis of this monograph

Selection of the literatures used for analysis in this monograph

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Figure 1.

The literature is included in the database

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For allometric models, the following information was recorded: (1) method of obtaining the sample trees, (2) component or part of the tree biomass measured for the biomass allometric model (Figure 2), (3) type of the tree volume used for the volume allometric model (total height, height of commercial tree or up to diameter of a certain point of the stem) (Figure 3), (4) method for formulation of the allometric model, (5) number of sample trees used to formulate the model, (6) size of the sample trees (diameter and height), (7) variables used to formulate the model, (8) model form (power, logarithm, polynomial, etc.), and (9) statistical parameters of the resulted model. For the biomass, several information was also recorded in the database, including the methods for measuring the green weight of the tree biomass components in the field, taking sub-samples from

8

Methods

every component for drying and weighing in the laboratory, and drying the sub-samples in the laboratory. The value used as input in the biomass allometric model is the biomass defined as the dry weight of the organic material in kilograms. All data compiled in the database were mapped based on the geographic references (longitude, latitude and specific name of the location). If the geographic information was not reported in the literature and only the location name was available, the coordinates of the location were acquired from the administrative map and Google Earth. This information was then spatially overlapped to find the geographic distribution of the available information on the allometric models according to location (island or province) and ecosystem type in Indonesia.

Flower Leaves

Fruit

Stem Twig Branch

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Stem Volu ume up to 4 cm top diametter limit

Stem m Volume up to 7 cm top diameter limit

Stem V Volume up to 10 cm top dia ameter limit

Merchantablle Volume

Clear Bole Volume

Total Stem Volume

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Stem Volume up to 5 cm to S op diameter limit

Parts of the trees measured for the tree biomass allometric model

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Figure 2.

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R t Root

Types of volume measured for the tree volume allometric model


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The existing tree biomass and volume allometric models are very useful for the estimation of forest biomass and carbon stocks in Indonesia. Therefore, model selection in this monograph was not based on location, forest type, tree species, site condition, stand age, sampling method and statistical analysis method used to develop the allometric models. The main considerations in evaluating the tree biomass and volume allometric models are statistical values, including: (1) unit value of the independent variable or predictor variable (X) and dependent variable or response variable (Y), (2) value of parameter coefficient, (3) value of the standard error of the parameter, and (4) value of the determination coefficient (R2) that reflects the proportion of the total variation of Y that can be explained by the variation of X X.. Also, the use of a correction factor in these allometric models was evaluated (Baskerville, 1972; Sprugel, 1983; Snowdon, 1990). The correction factor is

primarily needed to eliminate the bias that is introduced when data transformation is used (e.g. logarithm transformation) in the regression analysis of the allometric model with the least squares method. However, information on the value of the correction factor is not included in the Appendix of this monograph since studies that reported or used the correction factor are minimal. Apart from the criteria above, evaluation was also carried out through testing by accounting the biomass values of individual trees based on the diameter of the sample trees used to formulate the model and comparing them with the estimated biomass curve obtained from the model. An evaluation of the qualitative performance of the model based on biological or logical considerations was also applied in this monograph. Some of the allometric models reported in the literature are not recommended for use. The reasons for this, among others, are that the estimated parameter obtained from the model is not realistic (for example, the parameter value is negative and the form of the tree allometry obtained is not realistic, that is overestimated or underestimated).

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2.2 Evaluation of the Allometric Models

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Methods

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Description of the Database


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The source of information of the allometric model presented in this monograph was obtained from 193 literatures (published and unpublished). From these literatures, most of the information was obtained from scientific journals or research reports (61%). Aside from these, 62 literatures (32%) are student theses and dissertations from Indonesian universities while the remaining literatures (7%) are seminar proceedings. The data and information compiled from these various sources are important for metadata analysis (Scargle, 2000) because if it focused only on published scientific journals, research reports or proceedings, 32% of the information collected would not be included in this monograph. Besides this, the information presented would be less comprehensive and probably biased as it would not reflect diverse data and information from a variety of current literature. From the 193 literatures used in this monograph that reported allometric models, 42% presented allometric models to estimate tree biomass (total tree biomass, aboveground tree biomass, and biomass of tree’s components such as stem, branches, twigs, leaves, flowers, fruit, bark, stump, and roots) (Appendix 1) and 58% presented allometric models to estimate tree volume (total tree volume, volume up to crown base or clear bole volume, and volume of the tree up to certain top diameter limit) (Appendix 4). Most (94%) of the allometric models presented in Appendices 1 and 4 of this monograph were reported in the period of 1980–2012 (Figure 4). It is apparent that research interest in tree biomass or volume allometric model development has increased continuously since 1970–1980 up

to present. The development of tree biomass allometric models began rapidly after the year 2000, compared with previous years where only 1-5 literatures reported biomass allometric models. In the period of 2000-2012, about 77% of published literatures presented allometric models for the tree biomass estimation. This development was in line with the increasing need for information on evaluating or estimating biomass and forest carbon stocks as well as its changes as a follow-up of the UN Convention on Climate Change and the Kyoto Protocol (UN, 1998). Furthermore, the negotiations on reducing emissions from deforestation and forest degradation, and the role of conservation, sustainable forest management, and enhancement of forest carbon stock in developing countries (REDD+) during the commitment period postKyoto Protocol also led to more attention being focused on the methodology of biomass and carbon stock estimation (UNFCCC, 2009).

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3.1 Source of Information of the Allometric Models

Jumlah Number of Pustaka Literatures

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Volume

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Biomassa

70 60 50 40 30 20 10 0 1970-1980

Figure 4.

1980-1990 1990-2000 Periodtahun Periode

2000-2012

The number of literatures that presented tree biomass and/or volume allometric models used in this monograph until mid2012


13

3.2 Geographical Distribution of the Allometric Models

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Each reference of the location of the tree biomass or volume allometric models developed in Indonesia was classified according to island or province to obtain information on the spatial distribution of the availability of tree biomass

and volume allometric models in Indonesia. This spatial distribution reflects the distribution of the location for sampling trees used to develop the allometric models. From the spatial distribution of the availability of the tree biomass and volume allometric models in Indonesia (Figure 5), it can be seen that most (90%) of the allometric models that have been

Figure 5.

14

Geographical distribution of the availability of tree biomass and volume allometric models that have been developed in Indonesia


development of tree biomass allometric models was only reported from one location in Sulawesi and two locations in Papua while the development of tree volume allometric models was reported from several locations in Maluku, Nusa Tenggara, Papua and Sulawesi (Figure 5).

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developed came from three islands, i.e. Java, Kalimantan and Sumatra. This is an indication that so far, the location of the research or sample collection of the tree biomass and volume were mostly conducted in these three islands. For islands in the eastern part of Indonesia, the available information on tree biomass and volume allometric models is still relatively limited. The


15

3.3 Distribution of the Allometric Models by Ecosystem Type

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Each reference of the allometric model location is categorized according to the ecosystem type, i.e. natural forests and plantation forests. The types of natural forests were then differentiated into dryland forests, peat swamp forests and mangrove forest. If the information was available from the literature source, each type of natural forest ecosystem was classified again according to its condition, primary or secondary. In this monograph, primary forests are forests that are not yet intensively disturbed by human land use activities while secondary forests are forests that are already intensively disturbed by human land use activities, such as fire and harvesting. Plantation forests were differentiated into industrial plantation forests managed by state and private-owned companies (hereafter referred to as plantation forests in this monograph) and community plantation forests (hereafter referred to as community forests). The consideration in the classification of these two types of plantation forests is more on the silvicultural treatment and the management applied. The silvicultural treatment and management of industrial plantation forests are in general more intensive compared to community plantation forests, which would probably influence the production of tree biomass. Aside from the ecosystem types outlined above, heath forests are also included in this study because this type of forest has specific vegetation characteristics (generally stunted trees with thin stems, thick leaves and a low biodiversity

compared to other low dryland forest ecosystem) and its soil is nutrient poor (Whitmore, 1975; MacKinnon et al. 1996; Richards, 1996). Information on several biomass allometric models developed for crop plantations (such as rubber and oil palm) and agricultural plants (such as coffee and banana) are also included in the Appendix of this monograph. If the categories for the above ecosystem types are connected to land use classifications according to the IPCC Guideline (2006) and forest and land use classifications conducted by the Directorate General of Forestry Planning (Ministry of Forestry), then the scope of the allometric models in this monograph according to these two types of classification is shown in Table 1. The IPCC Guideline divided the use of lands into 6 categories for the purpose of reporting the GHG inventory, i.e.: (1) Forest Land, (2) Cropland, (3) Grassland, (4) Wetlands, (5) Settlements, and (6) Other Lands. The Directorate General of Forestry Planning divided the forest covers and land uses in Indonesia into 23 classes that include forested areas and other land use areas (Table 1).

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Therefore, survey and literature study from various sources of information (library, research institutions, universities, etc.) throughout Indonesia will be conducted continuously to update the data and information already compiled in the database and analyzed in this monograph.

16


Scope of the allometric models in this monograph connected to land use categories according to the IPCC Guidelines and Directorate General of Forestry Planning Category by IPCC Guideline

Scope of Category by Directorate allometric models General in this monograph of Forestry Planning

Mangrove Forest Plantation Forest Community Forest Agriculture Estate

Forest Primary Dryland Forest Secondary Dryland Forest Primary Peat Swamp Forest Secondary Peat Swamp Forest Primary Mangrove Forest Secondary Mangrove Forest Plantation Forest Other Land Use Area Shrub-Mixed Dryland Farm Dryland Agriculture Estate Crop Plantation Transmigration Area Rice Field Grassland

Forest Land

Cropland

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Forest Ecosystem Dryland Forest; Heath Forest Peat Swamp Forest

From the distribution of the availability of allometric models (biomass and volume) according to the ecosystem type (Figure 8) it can be seen that almost all types of forest ecosystems in Indonesia have available information on tree biomass or volume allometric models although this is not evenly distributed across all sites or islands (Figures 6 and 7). Plantation forests (including community forests) have relatively more information on tree biomass allometric models at about 52% of the total available information on tree biomass allometric models (Figure 8), with the largest distribution in Java (Figure 6). This indicates that research activities related to the estimation of biomass are mostly conducted in plantation forests in Java. This could be because the research interest is higher in this region, with easy access to research locations, and the availability of laboratory facilities are sufficient for analyzing biomass. The dryland forest ecosystem occupies the next rank with about 17% (Figure 8) of available tree biomass allometric models, particularly in Kalimantan and Sumatra where the sample trees were obtained (Figure 6).

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Table 1.

Grassland

Shrub

Wetlands

Swamp Swamp shrub

Settlements Other Land

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Settlement Area Barren Land Fish Pond Airport Mining Area Water Cloud covered

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-


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Geographical distribution of the available tree biomass allometric models developed in Indonesia

The majority of the volume allometric models are for the plantation and dryland forest ecosystem types, which cover about 44% and 38% respectively of the total number of tree volume allometric models reviewed in this monograph (Figure 8). The large contribution for these types of forest ecosystem occurred primarily during 1990-2000 when the activity of tree sampling was conducted mostly in plantation forest areas managed by Perum Perhutani in Java and in the production natural forest areas (HPH/IUPHHK) in some

18


of the provinces of four large islands (Sumatra, Kalimantan, Sulawesi and Papua). The number of locations with available allometric models according to the ecosystem type is also very diverse. The heath forest ecosystem has the smallest representation in the total number of sampling location (1% of the total number of available allometric models), with sampling locations in the provinces of West Kalimantan and Central Kalimantan (Figure 6). This number, although small, can probably represent

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the condition of the heath forests in Indonesia, wherein 77% (of the 32.000 km2 that remains in Indonesia) is located in Kalimantan or about 20% of low dryland forest that remains in Kalimantan (MacKinnon et al., 1996). The peat swamp forest ecosystem type has a representation of 7% of the number of sampling locations for the tree biomass allometric models and 6% for the tree volume allometric models (Figure 8). This number does not represent the condition of the peat swamp forests in Indonesia

that covers an area of 20.6 million ha (10.8% of the land area of Indonesia), spreading across four large islands, i.e. Sumatra (35%), Kalimantan (32%), Papua (30%), and Sulawesi (3%) (Wahyunto et al., 2005). Most (73%) of the allometric models developed in this peat swamp forest ecosystem type were based on sample trees collected from several locations in Riau and Central Kalimantan provinces (Figure 6 and Figure 7). Most of the dryland forest ecosystem can be found in Kalimantan, Sulawesi and Papua.


19

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Geographical distribution of the available tree volume allometric models developed in Indonesia

Although the total number of available tree biomass and volume allometric models for this type of ecosystem occupy the second rank after the plantation forest ecosystem (Figure 8), the locations with available information on biomass allometric models do not represent the large distribution of dryland forest areas in those three islands, considering that the biodiversity

20


and vegetation structures in this type of forest ecosystem are very diverse, from lowland to highland forests. The database indicates that the availability of allometric models for highland forest ecosystem over 1000 m above sea level is relatively very minimal. A wide area of mangrove forest vegetations can be found in Papua, covering more than half of

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the total extent of mangrove forests in Indonesia (Ruitenbeek, 1992). However, the availability of allometric models for the mangrove forest ecosystem in this area is very low, except for several tree volume allometric models that have been developed in West Papua (Figure 7). Of the total 15 literatures available on the tree biomass and volume allometric models for mangrove forest

ecosystem type, 77% of the models were developed based on sample trees collected from the mangrove forest areas in the provinces of West Kalimantan and Riau (Figures 6 and 7).


21

60 Volume

Number of allometric models (%)

50

Biomass

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Figure 8.

Ecosystem type

(Schima wallichii) (6%), tusam (Pinus merkusii) Schima wallichii (5%) and sengon (Paraserianthes ( falcataria) (5%). Apparently, the development of volume allometric models has been faster than that of biomass allometric models (Figure 10); it includes more than 70 species of 42 genera. From the total number of available tree volume allometric models, 89% were developed for specific species, both tree species growing in natural forests and in plantation forests. The remaining 11% of the models was developed for mixed-species, including species from Dipterocarpaceae family, non-Dipterocarpaceae, commercial woods, Shorea genera, non-Shorea, etc. Most of the tree volume allometric models for natural forests were developed for meranti (Shorea sp.) (19%), followed by keruing (Dipterocarpus sp.) (5%). For plantation forests, the species with the most available tree volume allometric models are Acacia spp. (mainly A. mangium and A. auriculiformis) (12%), Pinus merkusii (6%) and Eucalyptus sp. (E. deglupta and E. grandis) (4%).

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3.4 Scope of the Allometric Models by Species

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Of the total number of available biomass allometric models, 47% were developed for natural forest ecosystem types (dryland forest, peat swamp forest and mangrove forest), and 53% were developed for plantation forest ecosystems (including community forests). The number of species included in the tree biomass allometric models presented in this monograph is about 47 species, including 24% mixed-species of trees (Figure 9). The list of tree species included in the biomass allometric models developed for mixedspecies in several forest ecosystems can be seen in Appendix 2. Of the tree biomass allometric models developed for specific species (Figure 9), it seems that many allometric models were developed for plantation forests, particularly for mangium (Acacia mangium) (14%), followed by puspa

22


Distribution of the available tree biomass and volume allometric models by ecosystem type

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Acacia auriculiformis Acacia crassicarpa Acacia mangium Agathis loranthifolia Avicennia marina Borassodendron borneensis Bruguiera parviflora Bruguiera sexangula Bruguiera spp. Bruguiera gymnorrhiza Cotylelobium burckii Coffea sp. Dalbergia latifolia Dipterocarpaceae Dipterocarpus sp. Dipterocarpus kerrii Elaeis guineensis Elmerrillia celebica Elmerrillia ovalis Eucalyptus grandis Ficus sp. Geunsia pentandra Gigantochloa sp. Gmelina arborea Gonystylus bancanus Hevea brasiliensis Hopea sp. Intsia sp. Macaranga gigantea tteea a Musa paradisiaca diis d isiia acca a Palaquium sp. qu q uiiu um m ssp p.. Paraserianthes eess fa ffalcataria allcca atta arriia a Pi P in nu uss m me errkku ussiiii Pinus merkusii Piper aduncum Pi P ipeerr a ip ad du un nccu um m Po P om meeti tia a ssp p.. Pometia sp. Rh R hiiz iz o op ph ho orra aa ap piiccu ulla atta a Rhizophora apiculata Rh R hiiz iz o op ph ho orra am mu uccrro on na atta a Rhizophora mucronata Rh R hiiz iz o op ph ho orra a ssp p Rhizophora sp. Schima wallichii SSc ch hiim ma aw wa allllii SSh ho o Shorea sp. Shorea SSh ho orreea a leprosula SSh ho o Shorea parvifolia Swietenia macrophylla Swietenia mahagony Tectona grandis Xylocarpus granatum Mixed Species

0

5

10

15

20

25

Number of biomass allometric models (%)

Figure 9.

Distribution of the available tree biomass allometric models by species


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Acacia Agathis Alstonia Altingia Bischofia Bruguiera Calophyllum Dactylocladus Dalbergia Diospyros Dipterocarpus Disoxylum Dryobalanops Duabanga Durio Eucalyptus Eusideroxylon Gmelina Gonystylus Heritiera Hopea Intsia Manilkara Melanorrhoea Palaquium Paraserianthes Parashorea Peronema Pinus Podocarpus uss u Pometia meeti m tia a Pterocarpus occa o arrp rpu uss Pterospermum rro ossp peerrm mu um m Rhizophora Rh R hiiz izo op ph ho orra a Schima SScch hiim ma a SSh ho orreea a Shorea Swietenia SSw wiieetteen niia a Syzygium SSy yzyyg yz giiu um m TTectona Te ecctto on na a TTimonius Ti im mo on niiu uss To To Toona Vatica SSh ho orreea a & Gonystylus G Shorea SSh ho orreea a&D Shorea Dipterocarpus Non Shorea Non Dipterocarpaceae Commercial Timbers Dipterocarpaceae Dipterocarpaceae Non Shorea Mixed Species

0

3

6

9

12

Number of volume allometric models (%)

Figure 10. Distribution of the available tree volume allometric models by species

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04

Allometric Models


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4.1 Tree Biomass Allometric Models where X = independent variable (Dbh, or combination of Dbh and height), and Y = dependent variable (biomass); a = allometric model coefficient; and b = allometric model exponent. About 27% of the models are presented in the form of 'linear logarithmic' mathematical

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relationship:

where log (Y ((Y) Y)) is a natural logarithmic transformation (ln) or a base-10 logarithmic transformation (‘log 10’ or commonly denoted

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The total number of tree biomass allometric models presented in this monograph is 437 (from 81 literatures). These have been compiled from various models developed separately for trees’ biomass components and are classified by ecosystem type, tree species, and location (province) (Appendix 1). Most (88%) of the tree biomass allometric models that have been developed in Indonesia are for estimating aboveground tree biomass, either total aboveground tree biomass or the biomass of an individual tree’s components above the ground (Figure 11). There are still few allometric models (less than 12%) developed for estimating belowground tree biomass (roots). These models are mainly developed from sample roots of small trees. This is because the root biomass sampling is difficult and takes time, effort, and considerable costs.

as ‘log’) from biomass data (total tree biomass including root, total aboveground biomass, or biomass of each component of a tree ), log ((X) is Dbh (either natural logarithmic transformation (ln) or logarithmic transformation with base 10

Total Biomass Aboveground Biomass + Stilt Root Aboveground Biomass Fruit Flower + Fruit Leaves Twig Branch + Twig g Branch ncch n h Bark Ba B arrkk Stem Stump m-S St tu um mp p Stem St S te em m Cl C le ea arr B Bo olle eS St te em m Clear Bole Stem Stem Branch St S te em m+B Br ra an ncch h Stump Sttu S um mp p Stilt Sti S tilltt Root Ro R oo ott Root cm) Ro R oo ott ((D D > 0.5 0..5 0 5 ccm m)) (D < 0.5 0..5 0 5 cm) ccm m)) Roott (D Root Ro R oo ott

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(log)), while a and b are regression coefficients. Most biomass allometric models in this

monograph are presented in the form of non-linear

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mathematical relationship (power function), but in

0

20

40

practice most of the researchers apply logarithmic transformations in the process of fitting the regression model using the least squares method in order to create a linear regression relationship and then back-transformed into the original arithmetic

60

80

100

Number of allometric models (%)

Figure 11. Distribution of the available tree biomass

allometric models according to the part of tree biomass measured

value to estimate tree biomass. Transformation of biomass value into a logarithmic value in the regression with the least squares method leads to bias when logarithmic value is back-transformed to the original unit (Baskerville, 1972; Sprugel,

Based on the models developed in Indonesia, tree biomass allometric models are usually presented in the form of power function:

1983; Snowdon, 1990). Nevertheless, this bias can be avoided by multiplying the result with a correction factor (Sprugel, 1983; Parresol, 1999):


27

Or If using a base-10 logarithmic transformation.

where

is the estimated biomass value,

average value of biomass, and error variance

is the

is the value of

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The other alternative to avoid linear logarithmic transformation is the direct application of a nonlinear regression method, which can be found in several statistical softwares. Almost all of the tree biomass allometric models analyzed in this monograph use a Dbh (diameter at breast height) variable, or a combination of Dbh and tree height. About 82% of the biomass allometric models use only one variable, i.e. Dbh, as a tree biomass estimator, while the remaining (18%) uses a tree height variable in addition to the diameter variable as the tree biomass estimators. The forms of mathematical relationship used in tree biomass allometric models are shown in Appendix 1. The number of sample trees used to develop biomass allometric models varied from 3 to 200 trees, with most of the models using 20-30 trees on average (Appendix 1). However, the allometric models with a small number of sample trees ((N < 10) are not recommended to be used for estimating tree biomass. According to sources of literature, the majority of models used sample trees from a single stand, but some used sample trees from several similar stands, spreading across one or many research locations. The range of diameter of sample trees used to develop the biomass allometric models also varied (Appendix 1). For the dryland forest ecosystem, diameter of sample trees used were 1 - 130 cm, with the small diameter sample trees (Dbh maximum <10 cm) were commonly used to develop biomass allometric models for secondary dryland forest or

post-fire forest. Biomass allometric models for the peat swamp forest ecosystem used sample trees with diameter of 2 - 75.1 cm; with a minimum Dbh of 2 cm is commonly used for secondary peat swamp forest. The sample tree diameters for the mangrove forest ecosystem were 1.1 - 67.1 cm, with a maximum Dbh < 10 cm encountered in the biomass allometric models for the mangrove species in areas planted after harvesting activity or in rehabilitation forests. For plantation forest ecosystems, the range of diameter used was about 1- 95 cm; small trees were commonly used to develop biomass allometric models in young plantation forests. The variety of sample tree diameters shows that the range of diameter needs to be considered when using existing tree biomass allometric models. The extrapolation or use of allometric models to estimate tree biomass outside the diameter range of the sample trees should be conducted with caution since the resulting estimated value could be under- or overestimate. The value of the determination coefficient ((R2) from the regression models varied. It is commonly (98%) in the range of between > 0.5 and close to 1.00. Lower values of R2 were also found in this monograph, particularly for tree biomass allometric models for leaves, flowers and fruits, with a few sample trees and small diameters.

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If using a natural logarithmic transformation

28

Allometric Models

4.2 Tree Volume Allometric Models Tree volume allometric models that have been developed in Indonesia are presented in Appendix 4, classified according to ecosystem type, tree species and location (province). In total, 370 volume allometric models are compiled in this monograph, consisting of total stem volume model (45%), stem volume up to the first branch and stem volume up to the crown base (31%), and stem volume up to a certain top diameter limit (21%). The rest are models for estimating volume

Total Stem Volume Crown Volume Branch Volume Fuelwood Volume Stem Volume tdl4 Stem Volume tdl5 Stem Volume tdl7 Stem Volume tdl10 Merchantable Volume Clear Bole Stem Volume 0

10

20

30

40

50

Number of alllometric models (%)

Figure 12. Distribution of the available tree volume allometric

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models according to volume types (tdl on stem volume followed by numbers indicates that the model was developed for estimating stem volume up to the top diameter limit of the stem, i.e. 4 cm, 5 cm, 7 cm, and 10 cm)

al., 1995; Krisnawati and Bustomi, 2002; 2004). Nevertheless, the additional time, staff and budget required for application in the field need to be considered if the tree height variable has to be included. In fact, not all of the literature sources of tree volume allometric models reported the number of trees sampled in order to develop the model. According to literatures that reported this information, the number of sample trees varied from 36 to 2392, with 50 - 150 trees commonly used (Appendix 4). The range of diameter of sample trees for each volume allometric model also varied from 5.0 to 50.7 cm. The diameter range of sample trees was 10 - 150.7 cm for dryland forest ecosystem; 19 -110 cm for peat swamp forest ecosystem; 10 57.6 cm for mangrove forest ecosystem; and 5 110 cm for plantation forest ecosystem (Appendix 4). The variation of diameter indicates that the range of diameter needs to be considered when using volume allometric model to estimate tree volume and biomass.

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of parts of a tree, such as branches, crown and firewood (Figure 12).

The value of the determination coefficient ((R2) resulted from volume estimation regression models was commonly high, from 0.62 to almost 1.00. This shows that over 60% of the variation of volume data can be explained by the variation of diameter (in the case of only one variable used as an estimator) or variation of diameter and height data (in the case of a combination of two variables used, diameter and height). Of those determination coefficients, over 95% of tree volume allometric models had a determination coefficient of over 0.90.

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Similar with the tree biomass allometric models, most of the volume allometric models analyzed in this monograph were presented in the form of non-linear function (power function), although during the process of model fitting, most of the researchers applied a logarithmic transformation and then back-transformed the value into an arithmetic value to estimate tree volume. The bias introduced when the logarithmic transformation was used can be avoided by multiplying the estimated value with a correction factor as explained previously in the biomass allometric models (Sub-Section 4.1). Approximately 65% of the tree volume allometric models developed used a single variable, i.e. diameter at breast height (Dbh) as a volume estimator, while 35% used a combination of Dbh and tree height variables. The result of the regression relationship analysis of tree volume allometric models shows that using additional height variables aside from diameter can improve the prediction of 1 - 3% compared to using the diameter variable only (Wahjono et


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05

Tree Biomass and Volume Estimates


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There is a high variation of tree biomass estimates between the natural forest ecosystem types, including dryland forest, peat swamp forest and mangrove forest ecosystems (Figure 13). This variation of biomass estimates was also found within a single type of ecosystem. For instance, trees with the same diameter (Dbh = 40 cm), the aboveground tree biomass estimated from the biomass allometric models varied between 431 and 1590 kg/tree for mixed-species that existed in the dryland forest ecosystem (Figure 13a), between 887 and 1743 kg/tree for mixedspecies in the peat swamp forest ecosystem (Figure 13b), and between 645 and 2748 kg/tree for several dominant tree species in the mangrove forest ecosystem (Figure 13c). The larger the tree diameter, the bigger the difference in biomass value estimated by these allometric models for these three types of ecosystem (Figure 13). The variety of tree biomass estimates was significant. Aside from the different types of allometric models used, other factors also inf luenced the results, such as ecological condition, environment, location and the diverse anthropogenic factors in those three types of

ecosystem that might influence the biomass value of a tree. From the three types of natural forest ecosystem compared (Figure 13a-c), it can be seen that variation in the biomass estimates of the trees in peat swamp forest was considerably less compared to the other two types of natural forest. However, this variation was only represented by five available biomass allometric models that had been developed in Riau, South Sumatra and Central Kalimantan. The composition of flora, species, and the growth rate of trees in each ecosystem type also contributed to the development of tree biomass. The varied estimation values were also found in the tree volumes within and across those three ecosystem types (Figure 14). Depending on the volume allometric model used, the value of volume estimates on trees with the same diameter and from the same ecosystem type showed variation. As an example, a tree with a diameter of 50 cm gave a volume of 1.9 - 2.4 m3 for mixed-species in the dryland forest ecosystem (Figure 14a), from 2.4 to 2.7 m3 for mixed -species in the peat swamp forest ecosystem (Figure 14b), and from 1.3 to 2.2 m3 for some dominant species in the mangrove forest ecosystem (Figure 14c). However, several volume allometric models for dryland forest and peat swamp forest ecosystems gave relatively consistent estimates of tree volume (Figure 14a-b).

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5.1 Variability of tree biomass and volume estimates within natural forest ecosystem

Aboveground Biomass (kg/tree)

5000 Adinugroho (2009)

(a) Dryland Forest (DLF)

4000

Ambagau (1999) Basuki et al. (2009)

3000

Ketterings et al. (2001) Samalca (2007)

2000

Thojib et al. (2002) 1000

Yamakura et al. (1986) Hashimoto et al. (2004)

0 0

5

10 15 20 25 30 35 40 45 50 55 60 65 70 Dbh (cm)

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(b) Peat Swamp Forest (PSF)

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5000 4000

Jaya et al. (2007) Novita (2010) Dharmawan et al. (2012) Widyasari (2010)

10 15 20 25 30 35 40 45 50 55 60 65 70 Dbh D bh (cm) (cm)

5000

oorest rest (MF) (MF)


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((c) c) M

4000

Am B Bg R Ra Ra Xg

3000 2000

: Avicenia marina : Bruguiera sp. : Bruguiera gymnorrhiza : Rhizophora sp. : Rhizophora apiculata : Rhizophora mucronata : Xylocarpus granatum

1000

Ra (Amira, 2008) Am (Dharmawan & Siregar, 2008) Ra (Hilmi, 2003) Rm (Hilmi, 2003) B (Hilmi, 2003) Rm (Sukardjo & Yamada, 1992) Bg (Krisnawati et al., 2012) Xg (Talan, 2008)

0 0

5

10 15 20 25 30 35 40 45 50 55 60 65 70

R (Supratman, 1994)

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Figure 13. Aboveground tree biomass estimated from various biomass allometric models for dryland forest, peat swamp Figure 13. forest Aboveground tree biomass estimated from various biomass allometric models for dryland and mangrove forest ecosystem types (References are based on Appendix 3) forest, peat swamp forest and mangrove forest ecosystem types (References are based on Appendix 3) 34


1

6 Broadhead (1995) Direktorat Inventarisasi Hutan (1990b) Pusat Inventarisasi Hutan (1985) Pusat Inventarisasi Hutan (1986a) Pusat Inventarisasi Hutan (1986b) Pusat Inventarisasi Hutan (1986c) Pusat Inventarisasi Hutan (1988) Wiroatmodjo (1995) Direktorat Inventarisasi Hutan (1990d) Direktorat Inventarisasi Hutan (1990h) Direktorat Inventarisasi Hutan (1990i)

Tree Volume (m3)

(a) Dryland Forest (DLF) 4

2

0 0

5

10 15 20 25 30 35 40 45 50 55 60 65 70

6 (b) Peat Swamp Forest (PSF)

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Direktorat Inventarisasi Hutan (1990c)

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Rachman & Abdurrochim (2000) Soemarna & Suprapto (1971)

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Direktorat Inventarisasi Hutan (1991a)

0 0

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Tree Volume (m3)

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Dbh (cm)

10 15 20 25 30 35 40 45 50 55 60 65 70 Dbh D bh ((cm) cm)

6

Tree Volume (m3)

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(c)) M Mangrove angrove Forest Forest ((MF) MF) R : Rhizophora sp. Ra : Rhizophora apiculata Rc : Rhizophora congjungata

4

2

Ra (Marlia, 1999) Rc (Sjafe’i, 1972) R (Rachman & Abdurrochim, 1989)

0 0

5

10 15 20 25 30 35 40 45 50 55 60 65 70 Dbh (cm)

Figure 14.Tree volume estimated from various volume allometric modelsfor dryland forest, peat Tree volume estimated from various volume allometric models for dryland forest, peat swamp forest and Figure 14. mangrove forest ecosystem types (References are based on Appendix 5) swamp forest and mangrove forestecosystem types (References are based on Appendix 5) MONOGRAPH Allometric Models for Estimating Tree Biomass at Various Forest Ecosystem Types in Indonesia

2

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A variety was also found in the tree biomass and volume values estimated from the allometric models developed for tree species in plantation forests, either for fast growing species, such as Acacia mangium, Paraserianthes falcataria and Eucalyptus sp., or slow growing species such as Pinus merkusii, Swietenia macrophylla and Tectona grandis (Figures 15 and 16). From the three species compared, for each category of growth rate in the plantation forest ecosystem (Figures 15 and 16), this shows that the biomass allometric models were relatively consistent in predicting aboveground tree biomass compared to the volume allometric models with the variation of tree biomass for the tree species were relatively smaller. However, the variety was only reflected by the three biomass allometric models, which used sample trees of small diameter (< 50 cm). In general, a larger variation in biomass from allometric models occurs in estimated values as the tree diameter grows. A variety in tree biomass and volume estimates was also found for allometric models developed for trees of the same species. Figures 17 and 18 show examples of the estimated values of tree biomass and volume allometric models for

Acacia mangium and Pinus merkusii developed for several locations in Indonesia. Although the same methods were used to develop the allometric models, the variety of biomass and volume estimates resulted from these models was mainly caused by the variation in environmental condition and anthropogenic factors in Indonesia. The difference in methodology used for sampling and field measurement may also influence the result of biomass and volume estimation. Result of analysis of the tree biomass and volume allometric models conducted for Acacia mangium and Pinus merkusii (Figure 17) indicates that different allometric models used to estimate biomass resulted in a variety of tree biomass estimates for the same diameters, even though for some models (such as Pinus merkusii) merkusii) they were developed using sample trees taken in nearby locations (Figure 17). However, the difference in models used did not indicate a significant difference in the volume estimation between locations (Figure 18).

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5.2 Variability of tree biomass and volume estimates within plantation forest ecosystem

36



3000 (a) Fast growing species

2500 2000

Mangium (Heriansyah et al., 2003)

1500

Sengon (Rusolono, 2006) Ekaliptus (Onrizal et al., 2009)

1000 500 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 Dbh (cm)

(b) Slow growing species

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Jati (Hendri, 2001)

1500

Tusam (Hendra, 2005)

1000

Mahoni (Adinugroho & Sidiyasa, 2006)

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FIN

Dbh (cm)

Figure 15. Aboveground tree biomass estimated from various biomass allometric models for fast-growing and slowFigure 15. growing Aboveground tree(References biomassare estimated from various biomass allometric models for fast tree species based on Appendix 3) growing and slowgrowing tree species (References are based on Appendix 3)


37

6

Tree Volume (m3)

(a) Fast growing species Mangium (Siswanto & Harbagung, 2004)

4

Sengon (Bustomi et al., 2008) Ekaliptus (Direktorat Inventarisasi Hutan, 1990g)

2

0 5 10 15 20 25 30 35 40 45 50 55 60 65 70

PY

0

Dbh (cm) 6

CO

Tree Volume (m3)

(b) Slow growing species 4

Jati (Pramugari, 1982) Mahoni (Wahjono & Sumarna, 1987)

2

0 0

AL

Tusam (Imanuddin, 1999)

5 10 15 20 25 30 35 40 45 50 55 60 65 70 Dbh (cm)

FIN

Figure16. 16. Tree estimated from various volume allometric for fast-growing andfast slow-growing Figure Treevolumes volume estimated from various volume models allometric models for growingtree andspecies (References are based on Appendix 5) slowgrowing tree species (References are based on Appendix 5)

38



3000 (a) Acacia mangium

2500

JABAR (Heriansyah et al., 2003)

2000

JABAR (Purwitasari, 2011)

1500

SUMSEL (Wicaksono, 2004)

1000

KALTIM (Hardjana, 2011a) JABAR (Heriyanto & Siregar, 2007a)

500 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 Dbh (cm)

(b) Pinus merkusii

CO

2500

JABAR (Siregar, 2007b)

2000

JABAR (Heriansyah et al., 2003)

1500

JABAR (Hendra, 2005)

1000 500 0 0

AL


3000

PY

0

JABAR (Heriyanto & Siregar, 2007)

5 10 15 20 25 30 35 40 45 50 55 60 65 70

FIN

Dbh (cm)

Figure 17. Aboveground tree biomass for (a) Acacia mangium and (b) Pinus merkusii estimated from various biomass Figure 17.allometric Aboveground tree biomass for (a) Acacia(References mangium merkusii estimated from models developed from several locations areand(b) based onPinus Appendix 3) various biomass allometric models developed from several locations(References are based on Appendix 3)


39

6 (a) Acacia mangium

Tree Volume (m3)

JABAR (Setiawan, 1995) 4

KALBAR (Siswanto & Harbagung, 2004) KALSEL (Imanudin & Bustomi, 2004)

2

SUMSEL (Sumarna & Bustomi, 1986)

0 5 10 15 20 25 30 35 40 45 50 55 60 65 70

PY

0

Dbh (cm) 6

CO

JABAR (Imanuddin, 1999)

4

JABAR (Pangaribuan, 1990) JATENG (Sukmana et.al., 1976)

2

0

JATIM (Suharlan et al., 1977)

5 10 15 20 25 30 35 40 45 50 55 60 65 70

FIN

0

AL

Tree Volume (m3)

(b) Pinus merkusii

Dbh (cm)

Figure 18. Tree volumes for (a) Acacia mangium and (b) Pinus merkusii estimated from various allometric volume models Figure 18. Tree volumes for (a)locations Acacia(References mangiumare and (b)on Pinus merkusii estimated from various developed from several based Appendix 5) allometric volume models developed from several locations(References are based on Appendix 5)

40


PY CO AL FIN

06

The Use of Allometric Models for Estimating Biomass


41

AL

FIN PY

CO

Approach-1 is used when the tree biomass allometric model is available for a species or ecosystem type to be estimated in a certain site (species species or ecosystem and sitespecific model).. If the biomass allometric

PY

FIN

AL

1.

model for a certain species or ecosystem type in a certain site is available, the next step is to identify whether the range of diameter (Dbh) of trees from forest inventory has similar diameter range of the sample trees used to develop the biomass allometric model. If the trees’ diameter is in the same range as the sample trees, then the biomass allometric model can be applied directly to estimate the tree biomass. The biomass allometric models that can be used to estimate tree biomass based on the species or ecosystem type using Approach-1 are presented in Table 2. The (aboveground) stand biomass can then be estimated by summing the biomass from individual trees that make up the stand. [[Note Note: if the diameter of the trees from forest [Note: inventory is out of the diameter range of the sample trees, then validation is required to test the estimated values of tree biomass. If the estimated value shows a tendency to be an over- or underestimate, then Approach-2 can be applied].

CO

The available tree biomass and volume allometric models are very useful for estimating the forest biomass and carbon stocks in Indonesia, despite the variability of estimates produced by the models. The tree biomass and volume allometric models compiled in this monograph can be applied directly to forest stand inventory to estimate the biomass and carbon stocks in a certain location by using only measurable tree parameters, such as Dbh and height, with some conditions based on the approaches used. Figure 19 presents a sequence diagram of approach or methodology in using allometric models for estimating aboveground tree biomass and then estimating aboveground stand biomass. In general, the diagram in Figure 19 can be explained by several approaches as follows:


43

1

1

FOREST INVENTORY DATA FOREST INVENTORY DATA Species, Diameter Height (H)) (Tree (Tree Species, Diameter (D),(D), andand Height (H))

2

2

11 11

Is the biomass Is the biomass allometricallometric model model available available on the site? on the site?

Yes 3

Yes Yes

3

8

PY No No No

9

AL

Is the D distribution Is the D distribution of inventory of inventory in the in the range of sample range of sample trees’for D used trees’ D used the for the biomass allometric biomass allometric model? model?

9

Is the tth he eD Is d di distribution the is sttrri Dib bu distribution uttiio on n nv n ve en ntto or ry y iin n tth he ein the of inventory of inventory the range sample ofpllsample e range off s o sa am mp e us u se ed d orr for trees’ D trees’ used D ffo for used biomass biomass allometric allometric b llo om me et trriic c mo m od de e model pe p ed d on on model developed developed other site? other site? ot o t

No No

5

No

Yes

5

FIN

USE ET TH THE HE EB BI BIOMASS USE IO OM MA THE AS SS SBIOMASS ALLOMETRIC ALLOMETRIC LL L LO OM ME ET TR RIIC C MODEL MO M OD DE EL L MODEL B = f ((D D)),, BB== ff ((D D,, H H) (D), (D, (D), B) = f (D, H)

6

13 13

Is the D distribution Is the D distribution of inventory in the of inventory in the range of sample range of sample trees’ D used the trees’ D used forfor the volume allometric volume allometric model? model?

No No

No No Yes Yes

Yes Yes

10 1 0

10 USE THE USE BIOMASS THE BIOMASS ALLOMETRIC ALLOMETRIC MODEL MODEL AVAILABLE AVAILABLE ON OTHER ON OTHER SITE SITE

No No

Yes Yes

Yes es e s Yes

4

Yes

Was volume Was Wa W as s tth the he ethe volume allometric model allllo a om me ettrriic c model allometric developed developed thethe de d ev ve ello op pe ed d fforfor same sa s am me es sp p species/ same species/ ecosystem onon thethe e coecosystem syst site? site?

Is a biomass Is a biomass allometric allometric modelmodel available available on other on other site site that has that the has same the same species/ecosystem species/ecosystem of mo off the site? the site?

No

Yes

12 1 2 12

8

CO

No

4

Is the volume Is the volume allometric model allometric model available site? available on on thethe site?

No

Yes

Was the biomass Was the biomass allometricallometric model model developed developed for the for the same species/ same species/ ecosystem ecosystem on the on the site? site?

Yes

No

14 14 THE VOLUME USEUSE THE VOLUME ALLOMETRIC MODEL ALLOMETRIC MODEL = f (D), f (D, V =V f (D), V =Vf =(D, H) H)

B = f (D), B =Bf =(D), f (D, B =H)f (D, H)

6

ABOVEGROUND TREE BIOMASS (kg) ABOVEGROUND TREE BIOMASS (kg)

7

7

Figure 19. The diagram presenting the procedures of the use of available allometric models for estimating tree biomass

44


23 23

No No

25

AreAre both both treetree D and D and H H data data available? available?

25

DevelopDevelop a new allometric a new allometric model based modelon based on

No No

SNI 7725:2011 SNI 7725:2011

YesYes 24 24

Is a volume volume allometric allometric model model available available on on other othersite site that that has has the the same same species/ecosystem species/ecosystem ofof the site? site?

USE USE THETHE GEOMETRIC GEOMETRIC FORMULA FORMULA

PY

20 20

V =V¼π = ¼π x D2xxDH2 xx FH x F

No No Yes Yes Is Is the the D distribution distribution of of inventory inventory in inthe the range range of of sample sample trees’ trees’ D used used for forthe the volume volume allometric allometric model model developed developedon on other other site? site?

No No Yes Yes

16 16

No No

Is s ttr tree Is re ee etree BEF BE B EF FBEF va v value allu ue value e av a va aiavailable? illa ab blle e? ? available?

YesYes Ye Yes

18

USE US U SE E USE TH T THE HE ETHE FORMULA FO F O FORMULA

FIN

USE USE THE THE VOLUME VOLUME ALLOMETRIC ALLOMETRIC MODEL MODEL AVAILABLE AVAILABLE ON ONOTHER OTHER R SITE SITE

No

YesYes

17 1 7 17

22 22

No N o

AreAre wood wood density density datadata available? available?

AL

21 21

CO

15 15

B =BV= WD x WD x BEF x tree BEFtree tree ttr re ee eVx tree

18

19

USE THE USEFORMULA THE FORMULA B = Σ(V Btree =x Σ(V WD) x WD) x tree x BEFstand BEFstand

19 USE THEUSE FORMULA THE FORMULA B = VstandBx=BCEF Vstand x BCEF

((D D, ,H H) ) VV = = f (D), (D), V V ==ff(D, (D, H)

ABOVEGROUND ABOVEGROUND STAND STANDBIOMASS BIOMASS (ton/ha) (ton/ha)


45

Table 2.

Biomass allometric models that can be used to estimate aboveground tree biomass according to the main ecosystem type

Ecosystem Type

Tree Species

Location

Allometric models

No. of sample trees

DBH (cm)

R2

Sources

KALTENG

lnAGB = -3.408 + 2.708 lnDb

40

1.1-115

0.98

Anggraeni (2011)

NATURAL FOREST DLF

Mixed Mixed

KALTIM

lnAGB = -1.201 + 2.196 lnD

122

6-200

0.96

Basuki et al. (2009)

Intsia sp.

Papua

lnAGB = - 0.762 + 2.51 logD

13

5.5-40

0.99

Maulana and Asmoro (2011b)

DLF

Pometia sp.

Papua

logAGB = -0.841 + 2.572 logD

15

5-40

0.99

Maulana and Asmoro (2011a)

DLFs

Mixed

Jambi

lnAGB = -2.75 + 2.591 lnD

29

7.6-48.1

0.95

Ketterings et al. (2001)

DLFs

Mixed

Jambi

AGB = 0.11ρD2+0.62

DLFs

Mixed

KALTIM

AGB = 0.19999 D2.14

DLFs

Mixed

Jambi

AGB = 0.0639 D2.3903

DLFs

Schima wallichii

SUMSEL

AGB = 0.459 D1.364

29

7.6-48.1

63

2-24.2

0.93

Adinugroho Adinugroho (2009)

21

10.3-48

0.97

Thojib et al (2002)

15

3-24.6

0.92

Salim (2006)

CO

PY

DLF DLF

nda

Ketterings et al al. (2001)

Mixed

KALBAR

lnAGB = -1.861 + 2.528 lnD

12

2.55-30.3

0.99

Onrizal (2004)

Avicennia marina

JABAR

AGB = 0.1848 D2.3524

47

6.4-35.2

0.98

Darmawan & Siregar (2008)

MF

Bruguiera gymnorrhiza

KALBAR

logAGB = -0.552 + 2.244 logD

33

5-60.9

0.99

Krisnawati et al. (2012)

MF

Rhizophora apiculata

KALBAR

logAGB = -1.315 + 2.614 logD

37

2.5-67.1

0.96

Re-analyzed from Amira (2008)

MF

Xylocarpus granatum

KALBAR

logAGB = -0.763 + 2.23 logD

30

5.9-49.4

0.95

Talan (2008)

PSF

Mixed

KALTENG

AGB = 0.107 D2.486

nda

2-35

0.90

Jaya et al. (2007)

PSFs (post-fire)

Mixed

SUMSEL

AGB = 0.153 D2.40

20

2-30.2

0.98

Widyasari (2010)

PSFs (post-logging)

Mixed

SUMSEL

AGB = 0.206 D2.451

30

5.3-64

0.96

Novita (2010)

FIN

AL

HF MF

PLANTATION FOREST PF

Acacia auriculiformis

DIY

AGB = 0.078 (D2H)0.902

10

nda

0.96

BPKH Wil. XI & MFP II (2009)

PF

Acacia crassicarpa

SUMSEL

AGB = 0.027 D2.891

10

6-28

0.96

Rahmat (2007)

PF

Acacia mangium

JABAR

AGB = 0.199 D2.148

22

1.4-18.9

0.99

Heriyanto & Siregar (2007a)

PF

Acacia mangium

SUMSEL

AGB = 0.070 D2.58

30

8.69-28.3

0.97

Wicaksono (2004)

PF

Dalbergia latifolia

DIY

AGB = 0.7458 (D2H)0.6394

10

nda

0.89


PF

Eucalyptus grandis

SUMUT

AGB = 0.0678 D2.5794

18

2.4-27.2

0.99

Onrizal et al (2008; 2009)

PF

Gmelina arborea

KALTIM

AGB = 0.06 (D2H)0.88

24

nda

0.98

Agus (2002)

PF

Paraserianthes falcataria

JABAR

AGB = 0.1126 D2.3445

34

2-30

0.94

Siringoringo & Siregar (2006)

46


Location

Allometric models

No. of sample trees

DBH (cm)

R2

Sources

PF


JATENG

logAGB = -1.239 + 2.561 logD

30

< 43.8

0.97

Rusolono (2006)

PF


JATIM

AGB = 0.3196 D1.9834

35

16.6-31.2

0.87

Siregar (2007a)

PF

Pinus merkusii

JABAR

AGB = 0.0936 D2.4323

80

0.4-44

0.95

Siregar (2007b)

PF

Pinus merkusii

JABAR

logAGB = -0.686 + 2.26 logD

30

17.8-57

0.94

Hendra (2002)

PF

Shorea leprosula

JABAR

AGB = 0.032 D2.7808

18

9.9-20

0.98

Heriansyah et al. (2009)

PF

Swietenia macrophylla

JABAR

logAGB = -1.32 + 2.65 logD

30

14.3-36.9

0.96

Adinugroho & Sidiyasa (2006)

PF

Swietenia mahagony

JATENG

AGB = 0.903 (D2H)0.684

10

nda

0.99


PF

Tectona grandis

JABAR

AGB = 0.054 D 2.579

PF

Tectona grandis

JATENG

AGB = 0.015 (D2H)1.084

PF

Tectona grandis

DIY

AGB = 0.370 D2.125

PY

Tree Species

Ecosystem Type

32

4.8-26.2

0.98

Siregar (2011)

10

nda

0.98

BPKH Wil.XI & MFP II BPKH (2009) (2009)

15

5.1-27.1

0.92

Aminuddin (2008)

Approach-2 is used when the tree biomass allometric model for a species or ecosystem type to be estimated is not available at the site, but the biomass allometric model for the species or ecosystem type has been developed for another site. If the biomass allometric model for a tree species or ecosystem type has been developed for another site, it is necessary to check whether the range of tree diameters from the forest inventory is in the diameter range of the sample trees used to develop the tree biomass allometric model. If the tree diameters from the forest inventory are within the range of the diameter of the sample trees, the biomass allometric model developed in another site can be applied directly to estimate the tree biomass. As in Approach-1, the biomass allometric models that can be used to estimate tree biomass gained using Approach-2 are presented in Table 2. The (aboveground) stand biomass

FIN

AL

2.

CO

Note: Biomass allometric models were taken from above ground tree biomass (AGB) allometric models as presented in Appendix 1 with the criteria: if several aboveground tree biomass allometric models are available for the same species or ecosystem type at the same site, the allometric model is chosen from those which has a wider range of diameter in their sample trees, a higher determination coefficient (R2), and sufficient sample size (n ≥ 10).

3.

can later be measured by summing the biomass of individual trees that comprise the stand. [Note: If the diameter of the trees from forest inventory is out of the diameter range of the sample trees, then validation is required to test the estimated values of tree biomass. If the estimation value shows a tendency to be an over- or underestimate, the Approach-3 can be applied]. Approach-3 is used when the tree biomass allometric model has not been developed for a species or ecosystem type (either in the site or in another site), but a tree volume allometric model specific to species or ecosystem type has been developed for the site to be estimated. As for the use of biomass allometric model, the first step before using the volume allometric model is to identify the diameter range of the trees that have been used to develop the model.


47

where:

Biomasstree

aboveground tree biomass (kg) Volumetree = merchantable volume (m3) WD = wood density (kg/m3) BEFtree = biomass expansion factor for trees The volume allometric models that can be used to estimate tree volume (Vtrees ((Vtrees) Vtrees using Approach-3 is shown in Table 3. The information of the species wood density in Indonesia can be gained from varous resources, such as from Oey (1964), al. (2004), and Martawidjaya Abdurrochim et al. et al. (2005). If the wood density for the species to be estimated is not available, then the average value of the wood density of the genus can be used. The value of tree BEF can be obtained by a comparison or ratio between the aboveground tree biomass and the stem biomass.

FIN

AL

=

CO

𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡 = 𝑉𝑉𝑉𝑉𝐵𝐵𝐵𝐵𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝐵𝐵𝐵𝐵𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡 ∗ 𝑊𝑊𝑊𝑊𝑊𝑊𝑊𝑊 ∗ 𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡

48

Several values of the tree BEF have already been developed for some tree species and ecosystem types in Indonesia (Table 4). The (aboveground) stand biomass can be calculated by summing the individual biomass from the trees in the stand.

PY

If the tree diameters from forest inventory are within the range of the sample trees, then volume allometric model can be implemented directly to estimate the volume of the trees. [Note: if the tree diameters from the forest inventory are outside the range of diameter from the sample trees, validation is required, and it is necessary to evaluate the estimated tree volume resulting from the model. If the estimated value shows a tendency to over-or under-estimate, Approach-4 can be used]. In order to convert the value of the tree volume into aboveground biomass, the tree volume estimated from the allometric volume model can be multiplied by the value of wood density and the biomass expansion factor:


Table 3.

Volume allometric models that can be used to estimate tree volume according to the main ecosystem type

Ecosystem Tree Species Type

Location

Allometric models

No. of sample trees

DBH (cm)

R2

Sources

NATURAL FOREST Dipterocarpaceae (Non Shorea)

Maluku

V = 0.0002134 D2.4613

50

nda

0.99

Direktorat Inventarisasi Hutan (1990e)

DLF

Dipterocarpus cornutus

KALBAR

V = 0.000417 D2.21

268

23-139

0.98

Priyanto (1997)

DLF


KALSEL

V = 0.000141 D2.5141

129

20-> 100

nda

Soemarna and Siswanto (1986a)

DLF


KALTIM

V = 0.0001075 D2.145 H0.557

130

12-140

nda

Yudjar and Budi (1991)

DLF

Dryobalanops lanceolata

KALBAR

V = 0.0000893 D2.619

105

20-94

0.97

Siswanto et al., al (1996)

DLF

Dryobalanops spp.

KALBAR

V = 0.000661 D2.1

268

22.5-118

0.97

Priyanto Priyanto (1997)

DLF

Duabanga sp.

NTB

V = 0.000107 D2.5541

68

nda

0.99

Direktorat Direktorat InventaInventa risasi Hutan (1990f)

DLF

Eusideroxylon zwageri

SUMSEL

V = 0.0001049 D2.5728

262

8-33

nda

Harbagung and Suharlan (1984)

DLF

Non-Dipterocarpaceae

Maluku

DLF

Non-Duabanga and Toona

NTB

DLF

Shorea leprosula

KALSEL

DLF

Shorea spp.

Jambi

DLF

Shorea spp.

KALBAR

DLF

Shorea spp.

DLF

CO

PY

DLF

55

nda

0.99


V = 0.000051464 D2.5874

204

nda

0.95

Direktorat Inventarisasi Hutan (1990f)

nda

nda

nda

Wardaya (1990)

V = 0.0003053 D2.3035

134

20-100

nda

Soemarna and Suyana (1980)

V = 0.000372 D2.25

268

23-140

0.97

Priyanto (1997)

KALSEL

V = 0.0001865 D2.4257

204

20-154

nda

Suyana and Soemarna (1984)

Shorea spp.

KALTENG

V = 0.0002427 D2.3894

172

20->105

0.97

Wahjono and Soemarna (1985)

DLF

spp.. Shorea spp

KALTIM

V = 0.000331 D2.332

188

20-124

0.97

Soemarna and Suyana (1981)

DLF

Shorea spp spp..

Lampung

V = 0.000942 D2.0647

nda

nda

0.92

Soemarna (1977)

DLF

spp.. Shorea spp

Maluku

V = 0.000239 D

50

nda

0.99


DLF

Shorea spp spp..

Riau

V = 0.000507 D2.1894

100

20-84

0.95

Siswanto (1988)

DLF

Shorea spp spp.. & Dipterocarpus

KALTENG

V = 0.000261 D

61

10->60

0.99

Wahjono and Imanuddin (2007)

DLF

Shorea sumatrana

SUMBAR

V = 0.0001546 D2.4664

nda

nda

nda

Soemarna and Siswanto (1986b)

DLF

Toona suren

NTB

V = 0.00013 D2.5017

68

nda

0.97

Direktorat Inventarisasi Hutan (1990f)

DLF

Vatica celebencis

SULSEL

V = 0.000313 D2.2656

200

20-79

nda

Suyana and Soemarna (1981)

MF

Bruguiera spp.

KALBAR

V = 0.00008196 D2.568

80

7-48

nda

Soemarna (1980b)

MF

Rhizophora conjungata

KALTIM

V = 0.0000675 D1.947 H0.714

nda

nda

nda

Sjafe’i (1972)

FIN

V = 0.73 + 0.000045 (D2H)

AL

V = 0.000168 D2.507

2.4329

2.37847


49

No. of sample trees

DBH (cm)

R2

Sources

V = 0.0000534 D2.097 H0.739

180

nda

nda

Soemarna (1980a)

PABAR

V = 0.00029 D

nda

nda

nda

Rachman and Abdurrochim (1989)

Dactylocladus stenostachys

KALTENG

V = 0.000156 D2.107 H0.445

233

29-79.5

nda

Soemarna (1978)

PSF

Dipterocarpacea (Non Shorea)

KALTENG

V = 0.000136 D2.5035

nda

nda

0.97

Direktorat Inventarisasi Hutan (1991b)

PSF

Gonystilus sp.

KALTENG

V = 0.000124 D2.538

nda

nda

0.97

Direktorat Inventa Inventarisasi Hutan (1991b)

PSF

Other species non Dipterocarpaceae and Gonystillus

KALTENG

V = 0.000166 D2.438

nda

nda

0.97


PSF

Intsia sp.

PABAR

V = 0.000141 D2.477

PSF

Shorea spp.

KALTENG

V = 0.000101 D2.5844

PSF

Vatica spp.

PABAR

V = 0.0002953 D2.2705

HRW

Callopyllum sp.

KALBAR


Location

Allometric models

MF

Rhizophora spp.

KALBAR

MF

Rhizophora spp.

PSF

H

0.462

PY

1.890

nda

0.97

Direktorat InventaInventa risasi risasi Hutan (1990c)

nda

nda

0.98


246

nda

0.78

Direktorat Inventarisasi Hutan (1990c)

logV = -1.005 + 2.556 logD

107

20-75

0.98

Krisnawati and Bustomi (2002)

logV = -4.155 + 2.605 logD

PF


JATENG

nda

nda

0.95

Siswanto (2008)

PF

Acacia mangium

JABAR

CO

246

logV = -3.321 + 1.99 logD

46

5-35

0.98

Krisnawati et al., (1997)

PF

Acacia mangium

KALBAR

V = 0.000253 D2.292

51

10-35

0.94

Siswanto and Harbagung (2004)

PF

Acacia mangium

KALSEL

V = 0.000328 D2.2764

nda

nda

0.98

Imanuddin and Bustomi (2004)

PF

Acacia mangium

SUMSEL

V = 0.000122 D2.4697

103

nda

nda

Soemarna and Bustomi (1986)

PF

Agathis loranthifolia

JATENG

logV = -3.824 + 2.447 logD

nda

nda

0.96

Siswanto and Imanuddin (2008)

PF

Alstonia sp. sp.

SUMSEL

V = 0.000081 D2.06 H0.662

61

nda

0.92

Ermawati (1995)

PF

Altingia exelsa

JABAR

V = 0.000257 D

nda

nda

nda

Siswanto and Wahjono (1996)

PF

Dalbergia latifolia

Bali

V = 0.0004757 D2.0449

59

nda

0.91


PF

Dalbergia latifolia

JATIM

Log V = -3.56789 + 2.114559 log D

nda

nda

0.83

Siswanto and Imanuddin (2008)

PF

Dalbergia sisoides

NTT

V = 0.0000723 D2.4646

125

nda

0.98

Direktorat Inventarisasi Hutan (1990g)

PF

Eucalyptus spp.

NTT

V = 0.00006598 D2.5056

130

nda

0.98

Direktorat Inventarisasi Hutan (1990g)

PF

Gmelina arborea

SUMSEL

V = 0.0000669 D1.952 H0.794

103

5->30

0.99

Wahjono et al., (1995)

FIN

AL

PLANTATION FOREST

50


2.2563

Location

Allometric models

No. of sample trees

DBH (cm)

R2

Sources

PF

Manilkara kauki

Bali

V = 0.00122 D1.7445

90

nda

0.84


PF


Banten

V = 0.00011 D2.5414

nda

nda

0.94

Bustomi and Imanuddin (2004)

PF


JABAR

logV = -3.859 + 2.48 logD

nda

nda

nda

Bustomi et al., (1995)

PF


JATIM

logV = -3.702 + 2.423 logD

nda

nda

0.98

Siswanto (2008)

PF

Pinus merkusii

JABAR & JATIM

V = 0.0000305 D1.642 H1.356

nda

nda

nda

Soemarna and Sudiono (1972)

PF

Pinus merkusii

JATENG

V = 0.00000831 D3.254

100

nda

0.97

Suparno (1994)

PF

Pometia acuminata

PABAR

V = 0.000002 D2.394 H1.511

PF


JATIM

V = 0.000305 D2.162

PY


nda

nda

nda

Rachman and Abdurrochim (1989)

nda

nda

nda

Wahjono W ahjono and Soemarna (1987)

Table 4.

CO

Note: Volume allometric models were taken from commercial tree volume models (merchantable volume or clear bole volume) as presented in Appendix 4 with the criteria: if several commercial tree volume models are available for the same species or ecosystem type at the same site, then the allometric model is chosen from those which has a wider range of diameter in their sample trees, a higher determination coefficient (R2), and sufficient sample size (n ((n> n> > 30).

The values of BEF (biomass expansion factor) that have been developed for some tree species and ecosystem types in Indonesia

Tree species/ecosystem type

BEF value

Source

Wicaksono (2004)


1.61

Krisnawati et al. (2012)

Bruguiera sp.

1.57

Hilmi (2003), reanalyzed

1.58

Langi (2007), reanalyzed

1.61

Langi (2007), reanalyzed

Endospermum diadenum

1.66

Thoyib et al. (2002), reanalyzed

Eucalyptus grandis

1.33

Onrizal et al. (2009), reanalyzed

Evodia sp.

1.42

Hashimoto et al. (2004), reanalyzed

Ficus sp.

1.11


Fordia sp.

1.32


Gardenia anysophylla

1.82


Geunsia pentandra

1.11

Hashimoto et al (2004), reanalyzed

Gonystylus bancanus

1.67

Siregar (1995), reanalyzed

Hevea brasiliensis

1.73

Cesylia (2009), reanalyzed

Macaranga gigantea

1.43


Macaranga spp.

1.16


Melastoma malabathricum

1.06


Elmerrillia celebica

FIN

Elmerrillia ovalis

AL

1.33

Acacia mangium


51

Tree species/ecosystem type

BEF value

Source

1.16



1.34

Rusolono (2006), reanalyzed

Pinus merkusii

1.31

Hendra (2002)

Piper aduncum

1.07



1.55

Amira (2008)

Rhizophora macronata

1.61

Hilmi (2003), reanalyzed

Rhizophora spp.

1.68

Supratman (1994), reanalyzed

Schima wallichii

1.37

Salim (2006), reanalyzed


1.36

Adinugroho and Sidiyasa (2006)

Tectona grandis

1.46

Hendri (2001), reanalyzed

Trema sp.

1.14

al.. (2004), reanalyzed Hashimoto et al

Xylocarpus granatum

1.81

Talan (2008)

Mixed Species (Heath forest)

1.23

al. (2000) reanalyzed Miyamoto et al.

Mixed species (Secondary dryland forest)

1.49

Adinugroho (2009)

Mixed species (Logged-over peat swamp forest)

1.33

Novita (2010), reanalyzed

CO

Approach-4 is used when the volume allometric model for a specific species or ecosystem type in a specific site ((species species or ecosystem and site-specific model) model) is not available, but the volume allometric model is available or has been developed in another site. If the volume allometric model for a tree species or ecosystem type is available in another site, then the next step is to ensure that the range of tree diameters from the inventory is within the diameter range of sample trees used to develop the model. If the tree diameters from the inventory are within the range of the sample tree diameters, then the volume allometric model, which has been developed in another site, can be directly applied. [Note: if the tree diameters from the inventory are outside the sample trees’ diameter range, then validation is necessary to check the tree volume estimates resulted by the model. If the estimate value shows

a tendency to over- or under-estimate, then Approach-5 can be applied].

FIN

AL

4.

PY

Nauclea sp.

52


In order to convert the tree volume into the aboveground biomass, the tree volume should be multiplied by the value of wood density and the tree biomass expansion factor, as it is described in Approach-3. The (aboveground) stand biomass can later be obtained by summing the biomass of individual trees in the stand.

5.

Approach-5 is used when the biomass and volume allometric models are not available for a specific species or ecosystem type, but the height data (besides diameter) is available from field measurement or inventory of trees in the stand. If the tree height data is available, the tree volume can then be obtained using the geometric formula approach (tree volume is

calculated as cylinder volume multiplied with the stem form factor) as follows:

tree volume (m3) 3.14 diameter at breast height (cm) tree height (m) form factor

Approach-6 is used in the condition where: (a) a biomass allometric model is not available for a tree species or ecosystem type to be estimated; however, (b) a volume allometric model or height data (besides diameter) is available, which can be used to estimate volume for the specific species or ecosystem type; and (c) the wood density data is available, but (d) tree BEF data is not available. If the tree BEF value developed specifically for the species or ecosystem type to be estimated is not available, then this approach for the stand BEF value can be applied. For the stand BEF, Brown and Lugo (1992) developed an equation to calculate BEF for broad-leaved forests, as follows:

AL

CO

The form factor (F) is the correction factor; calculated from the ratio between the actual volume of the tree and the cylinder volume with the same diameter and height. If the form factor for the specific species to be estimated is not available, then a general stem form factor of 0.6 can be applied (Krisnawati and Harbagung, 1996). The estimated tree volume resulted from the above geometric approach is then converted into aboveground tree biomass following Approach-3 and Approach-4, i.e. tree volume gained from

6.

PY

where: V = π = Dbh = H = F =

the geometric calculation is multiplied by the species wood density and the tree’s biomass expansion factor. The (aboveground) stand biomass can later be measured by summing the biomass of the individual trees in the stand.

BEF = Exp {3.213 – 0.506*Ln(BV)} for BV < 190 t/ha

FIN

1.74 for BV ≥ 190t/ha (n = 56; R2adj = 0.76) where:

BV = the biomass of inventoried volume (t/ha); calculated as the product of VOB/ha (m3/ha) and wood density (t/m3)


53

Table 5.

Default value of BEF according to IPCC Guidance (2003)

Climatic zone Tropical

Forest type

Minimum Dbh (cm)

BEF (including bark)

Conifer

10

1.3 (1.2 – 4.0)

Broadleaf

10

3.4 (2.0 – 9.0)

If the average wood density for the family is also unavailable, then the aboveground stand biomass can be calculated using the BCEF value value as follows:

For conifer forests, BEF value is determined in the range of 1.05 - 1.58, with an average value of 1.3 (Se= 0.06). Besides the above equation, the default BEF value according to IPCC Guidance (2003) can also be applied (Table 5). For Approach-6, the value of biomass estimates is the value of aboveground stand biomass:

PY

𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠 = 𝑉𝑉𝑉𝑉𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠 ∗ 𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵

where: Biomassstand = aboveground stand biomass (ton/ha) Vstand = stand volume (m3/ha) BCEF = biomass conversion and expansion factor In this approach, the default value of BCEF as specified in the IPCC Guidelines (2006) can be used (Table 6).

CO

𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠 = �� 𝑉𝑉𝑉𝑉𝐵𝐵𝐵𝐵𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝑡𝑡𝑡𝑡𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵 ∗ 𝑊𝑊𝑊𝑊𝑊𝑊𝑊𝑊� ∗ 𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠

Approach-7 is used when the following conditions are present: (a) no tree biomass allometric model is available for a certain species or ecosystem type to be estimated, but (b) a volume allometric model or height data (besides diameter) is available, which can be used to estimate volume for the specific species or ecosystem type; and (c) wood density value is unavailable for specific species or species group (genus, family). In this Approach-7, if the value of specific wood density for the tree species to be estimated is unavailable, it is possible to use the average value of wood density for the genus. If the average wood density for the genus is also not available, it is acceptable to use the average wood density for the family.

FIN

7.

54

8.

AL

where: Biomassstand = aboveground stand biomass (ton/ha) Volumetree = tree volume (m3) WD = wood density (kg/m3) BEFstand = stand biomass expansion factor


Approach-8 is used when the following conditions are present: (a) no specific tree biomass allometric models nor volume allometric models are available for the species or ecosystem type to be estimated, (b) no height data (besides diameter) is available for estimation of tree volume using a geometric formula approach, and (c) no data on wood density is available, either for species or species group (genus, family).

Table 6.

Default value of BCEF according to IPCC Guidelines (2006)

Humid Tropical

Forest type Conifer

Natural forests

Volume (m3) <10

11-20

21-40

41-60

61-80

80-120

120-200

>200

4

1.75

1.25

1

0.8

0.76

0.7

0.7

(3-6)

(1.4-2.4)

(1-1.5)

(0.8-1.2)

(0.7-1.2)

(0.6-1)

(0.6-0.9)

(0.6-0.9)

9

4

2.8

2.05

1.7

1.5(1-1.8)

1.3

0.95

(4-12)

(2.5-4.5)

(1.4-3.4)

(1.2-2.5)

(1.2-2.2)

(0.9-1.6)

(0.7-1.1)

No

Sequence

8

1-2-3-4-8-9-11-12-13-14-15-25-6-7

9

1-2-3-4-8-9-11-12-13-14-15-16-17-6-7 1-2-3-4-8-9-11-12-13 1-2-3-4-8-9-11-1213-14-15-16-17-6-7 -14-15-16-17-6-7

10

1-2-3-4-8-9-11-12-13-14-15-18-7 1-2-3-4-8-9-11-12-13 1-2-3-4-8-9-11-1213-14-15-18-7 -14-15-18-7

11

1-2-3-4-8-9-11-12-13-14-15-19-7 1-2-3-4-8-9-11-12-13 1-2-3-4-8-9-11-1213-14-15-19-7 -14-15-19-7

12

1-2-3-4-8-9-11-12-13-14-15-25-6-7 1-2-3-4-8-9-11-12-13 1-2-3-4-8-9-11-1213-14-15-25-6-7 -14-15-25-6-7

13

1-2-3-4-8-9-11-12-20-21-22-15-16-17-6-7

14

1-2-3-4-8-9-11-12-20-21-22-15-16-18-7

15

1-2-3-4-8-9-11-12-20-21-22-15-19-7

16

1-2-3-4-8-9-11-12-20-21-22-15-25-6-7

17

1-2-3-4-8-9-11-12-20-21-22-15-16-17-6-7 1-2-3-4-8-9-11-12-20-

18

1-2-3-4-8-9-11-12-20-21-22-15-16-18-7 1-2-3-4-8-9-11-12-20-

19

1-2-3-4-8-9-11-12-20-21-22-15-19-7

CO

If this condition occurs, it is suggested that a new biomass allometric model should be developed for the specific species and ecosystem type in the site in question. The procedure for developing the new tree biomass allometric model refers to the Indonesian National Standard (SNI) 7725:2011 regarding the Development of allometric equations for estimating forest carbon stocks based on the field measurements (groundbased forest carbon accounting). Through the above approaches, a sequence flow of applications can be developed to obtain an estimated value of aboveground tree biomass and/or an estimated value of aboveground stand biomass (Table 7). The choice of approach used will determine the accuracy level and the complexity of the methodology. The smaller the number of approach used, the higher the accuracy of the estimated value for biomass of specific species or ecosystem type at the site.

PY

Climatic zone

1-2-3-4-8-9-11-12-20-21-22-15-25-6-7

21

1-2-3-4-8-11-12-20-23-24-15-16-17-6-7

22

1-2-3-4-8-11-12-20-23-24-15-16-18-7

23

1-2-3-4-8-11-12-20-23-24-15-19-7

24

1-2-3-4-8-11-12-20-23-24-15-25-6-7

25

1-2-3-4-8-11-12-20-23-25-6-7

26

1-2-3-4-8-11-12-20-21-22-15-16-17-6-7

Possible sequences to determine the approach used in biomass estimation (numbers of sequences refer to Figure 19)

27

1-2-3-4-8-11-12-20-21-22-15-16-18-7

28

1-2-3-4-8-11-12-20-21-22-15-19-7

29

1-2-3-4-8-11-12-20-21-22-15-25-6-7

Sequence

30

1-2-3-4-8-11-12-20-21-22-15-16-17-6-7

31

1-2-3-4-8-11-12-20-21-22-15-16-18-7

32

1-2-3-4-8-11-12-20-21-22-15-19-7

FIN

AL

20

Table 7.

No 1

1-2-3-4-5-6-7

2

1-2-3-4-5-6-7

3

1-2-3-4-8-9-10-6-7

4

1-2-3-4-8-9-10-6-7

5

1-2-3-4-8-9-11-12-13-14-15-16-17-6-7

6

1-2-3-4-8-9-11-12-13-14-15-16-18-7

7

1-2-3-4-8-9-11-12-13-14-15-19-7

33

1-2-3-4-8-11-12-20-21-22-15-25-6-7

34

1-2-3-4-8-11-23-24-15-16-17-6-7

35

1-2-3-4-8-11-23-24-15-16-18-7

36

1-2-3-4-8-11-23-24-15-19-7

37

1-2-3-4-8-11-23-24-15-25-6-7

38

1-2-3-4-8-11-23-25-6-7


55

Sequence

No

Sequence

39

1-2-3-8-9-10-6-7

79

1-2-11-12-13-14-15-16-17-6-7

40

1-2-3-8-9-10-6-7

80

1-2-11-12-13-14-15-18-7

41

1-2-3-8-9-11-12-13-14-15-16-17-6-7

81

1-2-11-12-13-14-15-19-7

42

1-2-3-8-9-11-12-13-14-15-16-18-7

82

1-2-11-12-13-14-15-25-6-7

43

1-2-3-8-9-11-12-13-14-15-19-7

83

1-2-11-12-20-21-22-15-16-17-6-7

44

1-2-3-8-9-11-12-13-14-15-25-6-7

84

1-2-11-12-20-21-22-15-16-18-7

45

1-2-3-8-9-11-12-13-14-15-16-17-6-7

85

1-2-11-12-20-21-22-15-19-7

46

1-2-3-8-9-11-12-13-14-15-18-7

86

1-2-11-12-20-21-22-15-25-6-7

47

1-2-3-8-9-11-12-13-14-15-19-7

87

1-2-11-12-20-21-22-15-16-17-6-7 -22-15-16-17-6-7

48

1-2-3-8-9-11-12-13-14-15-25-6-7

88

1-2-11-12-20-21-22-15-16-18-7 21-22-15-16-18-7 21 -22-15-16-18-7

49

1-2-3-8-9-11-12-20-21-22-15-16-17-6-7

89

1-2-11-12-20-21-22-15-19-7 1-2-11-12-20-21 1-2-11-12-2021-22-15-19-7 -22-15-19-7

50

1-2-3-8-9-11-12-20-21-22-15-16-18-7

90

1-2-11-12-20-21-22-15-25-6-7 1-2-11-12-20-21 1-2-11-12-2021-22-15-25-6-7 -22-15-25-6-7

51

1-2-3-8-9-11-12-20-21-22-15-19-7

91

1-2-11-12-20-23-24-15-16-17-6-7

52

1-2-3-8-9-11-12-20-21-22-15-25-6-7

92

1-2-11-12-20-23-24-15-16-18-7

53

1-2-3-8-9-11-12-20-21-22-15-16-17-6-7

93

1-2-11-12-20-23-24-15-19-7

54

1-2-3-8-9-11-12-20-21-22-15-16-18-7

94

1-2-11-12-20-23-24-15-25-6-7

55

1-2-3-8-9-11-12-20-21-22-15-19-7

95

1-2-11-12-20-23-25-6-7

56

1-2-3-8-9-11-12-20-21-22-15-25-6-7

96

1-2-11-12-20-21-22-15-16-17-6-7

57

1-2-3-8-11-12-20-23-24-15-16-17-6-7

97

1-2-11-12-20-21-22-15-16-18-7

58

1-2-3-8-11-12-20-23-24-15-16-18-7

98

1-2-11-12-20-21-22-15-19-7

59

1-2-3-8-11-12-20-23-24-15-19-7

99

1-2-11-12-20-21-22-15-25-6-7

60

1-2-3-8-11-12-20-23-24-15-25-6-7

100

1-2-11-12-20-21-22-15-16-17-6-7

61

1-2-3-8-11-12-20-23-25-6-7

101

1-2-11-12-20-21-22-15-16-18-7

62

1-2-3-8-11-12-20-21-22-15-16-17-6-7

102

1-2-11-12-20-21-22-15-19-7

63

1-2-3-8-11-12-20-21-22-15-16-18-7

103

1-2-11-12-20-21-22-15-25-6-7

64

1-2-3-8-11-12-20-21-22-15-19-7

104

1-2-11-23-24-15-16-17-6-7

65

1-2-3-8-11-12-20-21-22-15-25-6-7

AL

CO

PY

No

1-2-11-23-24-15-16-18-7

1-2-3-8-11-12-20-21-22-15-16-17-6-7 1-2-3-8-11-12-20-21 1-2-3-8-11-12-2021-22-15-16-17-6-7 -22-15-16-17-6-7

106

1-2-11-23-24-15-19-7

67

1-2-3-8-11-12-20-21-22-15-16-18-7 1-2-3-8-11-12-20-21 1-2-3-8-11-12-2021-22-15-16-18-7 -22-15-16-18-7

107

1-2-11-23-24-15-25-6-7

68

1-2-3-8-11-12-20-21-22-15-19-7 1-2-3-8-11-12-20-21 1-2-3-8-11-12-2021-22-15-19-7 -22-15-19-7

108

1-2-11-23-25-6-7

69

1-2-3-8-11-12-20-21-22-15-25-6-7 1-2-3-8-11-12-20-21 1-2-3-8-11-12-2021-22-15-25-6-7 -22-15-25-6-7

70

1-2-3-8-11-23-24-15-16-17-6-7

71

1-2-3-8-11-23-24-15-16-18-7

72

1-2-3-8-11-23-24-15-19-7

73

1-2-3-8-11-23-24-15-25-6-7

74

1-2-3-8-11-23-25-6-7

75

1-2-11-12-13-14-15-16-17-6-7

76

1-2-11-12-13-14-15-16-18-7

77

1-2-11-12-13-14-15-19-7

78

1-2-11-12-13-14-15-25-6-7

FIN

105

66

56


Note: The underlined red numbers indicate directional arrows in dashed-lines (Figure 19) which means that the sequence continued, despite the required information being unavailable.

PY CO AL FIN

07

Closing


57

AL

FIN PY

CO

during climactic conditions (undisturbed by human land use activities). Allometric models for secondary natural forest ecosystems (especially old secondary forest) are required to calculate the growth process and the accumulation of forest biomass more completely after human land use activities.

4.

The tree sample data used to develop biomass allometric models is still relatively limited to sample trees of less than 100 cm. Biomass data of sample trees above 100 cm is necessary considering that large trees contribute significantly to the total biomass in forest ecosystems.

PY

3.

Most of the allometric models are developed based on relationship of log-log regression (biomass log is a function of diameter log). The usee of this logarithmic transformation is to us make the relationship model linear and the range of error ((error variance) homogeneous. Logarithm transformation back to the original unit will introduce bias that needs to be corrected. But, bias correction for the transformed data cannot be performed while calculating individual tree biomass as the standard error values are not reported in the literature (bias values that have been generated are not known).

The availability of allometric models for ecosystem types in eastern Indonesia (including Sulawesi, Maluku, Nusa Tenggara and Papua) is still lacking. These models are urgently needed considering that the vegetation structure and taxonomy of tree species in eastern Indonesia are very different from those in western Indonesia, which is separated by the Wallace line.

FIN

1.

AL

CO

Data and information on carbon stocks stored in forest biomass including spatial changes are necessary to develop GHG emissions reduction strategies as the result of deforestation and forest degradation as well as to increase forest carbon stocks. A comprehensive, credible and verified National Carbon Accounting System is required. It is therefore necessary to prepare the tools for biomass and carbon stock estimation and to monitor the changes, in order to determine the emission reduction that takes place. One of the initial steps in developing the system is to make an inventory and review of tree biomass and volume allometric models that have been developed in accordance with the local conditions in Indonesia. The results of the studies presented in this monograph show that tree biomass and volume allometric models have been developed for various tree species and forest ecosystems in Indonesia. Current models in general represent major forest ecosystem types, although the distribution of the models may not represent all variations of tree species and ecosystems that exist in Indonesia. From the database and the results of the study of allometric models that have been developed in Indonesia, several gaps have been identified, such as:

2.

The availability of allometric models for primary and secondary natural forest ecosystem types is relatively limited, but these models are necessary to determine the maximum biomass of natural forests

To fill these information gaps, possible strategies can be carried out: 1.

Identification of locations that are not currently represented by the data and identification of new sources of information about the development of allometric models for estimating forest biomass at various locations in Indonesia. Information on spatial distribution of the sampling location of allometric models, overlapped with the spatial distribution of forest ecosystem type in Indonesia, can be used to identify these gaps.


59

Therefore, to determine the location of sample trees for measuring biomass in the field it is necessary to consider the distribution and representation of the locations.

4.

Sample tree data used to develop allometric models should cover the range of tree diameters in the population (representing the existing distribution of diameter class), and the sample should be representative

Investigation of uncertainty associated with the models caused by the use of logarithmic transformation through analysis of the data of individual tree biomass measurements available from the model, so that bias correction can be applied in the calculation of individual tree biomass.

FIN

AL

CO

3.

The development of general allometric models specific to ecosystem type to cope with the diversity of ecological zone that exists in Indonesia.

PY

2.

of the number of trees in order to produce statistically reliable models. Additional samples of large trees are required to expand the scope of available models, especially for the tree species and forest ecosystem types for which large trees can still be found in the field.

60

Closing

References

PY

Comley, B.W.T. and McGuinness, K.A. 2005. Above- and below-ground biomass, and allometry of four common northern Australian mangroves. Australian Journal of Botany 53 (5): 431-436. Drake, J.B., Dubayah, R.O., Knox, R.G., Clark, D.B. and Blair, J.B. 2002. Sensitivity of large-footprint lidar to canopy structure and biomass in a neotropical rainforest. Remote Sensing of Environment 81: 378–392. Eamus, D., McGuinness, K. and Burrows, W. 2000. Review of allometric relationships for estimating woody biomass for Queensland, the Northern Territory and Western Australia. National Carbon Accounting System Technical Report 5A. Australian Greenhouse Office, Canberra. 56p. Huxley, J.S. 1993. Problems of relative growth. John Hopkins University Press, London. Intergovernmental Panel on Climate Change [IPCC]. 2003. Good Practice Guidance for Land Use, Land-Use Change and Forestry, Prepared by the National Greenhouse Gas Inventories Programme. Penman, J., Gystarsky, M., Hiraishi, T., Krug, T., Kruger, D., Pipatti, R., Buendia, L., Miwa, K., Ngara, T., Tanabe, K. and Wagner, F. (eds.). IGES, Japan. Intergovernmental Panel on Climate Change [IPCC]. 2006. 2006 IPCC Guidelines for National Greenhouse Gas Inventories, Prepared by the National Greenhouse Gas Inventories Programme. Eggleston, H.S., Buendia, L., Miwa, K., Ngara, T. and Tanabe, K. (eds.). IGES, Japan. Jenkins, J.C., Chojnacky, D.C., Heath, L.S. and Birdsey, R.A. 2003. National-scale biomass

FIN

AL

CO

Abdurrochim, S., Mandang, Y.I. dan Uhaedi, S. 2004. Atlas Kayu Indonesia Jilid III. Pusat Penelitian dan Pengembangan Teknologi Hasil Hutan, Bogor. Badan Standardisasi Nasional [BSN]. 2011. SNI 7225:2011, Penyusunan persamaan alometrik untuk penaksiran cadangan karbon hutan berdasar pengukuran lapangan (ground based forest carbon accounting). Badan Standardisasi Nasional, Jakarta. Baskerville, G.L. 1972. Use of logarithmic regression in the estimation of plant biomass. Canadian Journal of Forestry 2: 49–53. Brown, S. 1997. Estimating biomass and biomass change of tropical forests, a premier. FAO Forestry Paper 134. Brown, S. and Lugo, A.E. 1982. The storage and production of organic matter in tropical forests and their role in the global carbon cycle. Biotropica 14: 161-187. Bustomi, S., D. Wahjono, Harbagung dan Sumarna, K. 2002. Tariff dan Tabel Volume Beberapa Jenis Pohon di Hutan Tanaman. Pusat Litbang Hutan dan Konservasi Alam, Bogor. 79p. Chave, J., Andalo, C., Brown, S., Cairns, M.A., Chambers, J.Q., Eamus, D., Fölster, H., Fromard, F., Higuchi, N., Kira, T., Lescure, J.-P. Nelson, B.W., Ogawa, H., Puig, H., Riéra, B., and Yamakura, T. 2005. Tree allometry and improved estimation of carbon stocks and balance in tropical forests. Oecologia 145: 87–99. Clark, D.A., Brown, S., Kicklighter, D.W., Chambers, J.Q., Thomlimson, J.R. and Ni, J. 2001. Measuring net primary production in forests: concepts and field methods. Ecological Applications 11(2): 356–370.


61

PY

age for boreal forests. Forest Ecology and Management 188: 211–224. MacDicken, K.G. 1997. A guide to monitoring carbon storage in forestry and agroforestry projects. Winrock International Institute for Agricultural Development. 87p. Mackinnon, K., Hatta, G., Halim, H. and Mangalik, A. 1996. The Ecology of Kalimantan. Periplus Editions, Singapore. Martawijaya, A., Kartasujana, I., Kadir, K. dan Prawira, S.A. 2005. Atlas Kayu Indonesia Jilid I (Edisi revisi). Pusat Penelitian dan Pengembangan Hasil Hutan, Bogor. Martawijaya, A., Kartasujana, I., Mandang, Y.I., Prawira, S.A. dan Kadir, K. 2005. Atlas Kayu Indonesia Jilid II (Edisi revisi). Pusat Penelitian dan Pengembangan Hasil Hutan, Bogor. Montes, N., Gauquelin, T., Badri, W., Bertaudiere, V. and Zaoui, E.H. 2000. A non-destructive method for estimating above-ground forest biomass in threatened woodlands. Forest Ecology and Management 130: 37–46. Niklas, K.J. 1994. Plant allometry: the scaling of form and process. University of Chicago Press, Chicago. Parresol, B.R. 1999. Assessing tree and stand biomass: a review with examples and critical comparisons. Forest Science 45:573-593. Reyes, G., Brown, S., Chapman, J. and Lugo, A.E. 1992. Wood densities of tropical tree species. General Technical Report SO-88. USDA Forest Service,Southern Forest Experiment Station, New Orleans, Louisiana, USA. Richards, P.W. 1996. The Tropical Rain Forest: An Ecological Study. 2nd edition. Cambridge University Press, Cambridge, UK. Ruitenbeek, H.J. 1992. Mangrove Management: An Economic Analysis of Management Options with a Focus on Bintuni Bay, Irian Jaya. Environmental Management and Development in Indonesia Project

FIN

AL

CO

estimators for United States tree species. Forest Science 49: 12–35. Keith, H., Barrett, D. and Keenan, R. 2000. Review of allometric relationships for estimating woody biomass for New South Wales, the Australian Capital Territory, Victoria, Tasmania, and South Australia. National Carbon Accounting System Technical Report 5B. Australian Greenhouse Office, Canberra. 114 p. Keith, H. and Krisnawati, H. 2010. Biomass estimates for Carbon accounting in Indonesia. Preliminary report. IndonesiaAustralia Forest Carbon Partnership. 60p. Ketterings, Q.M., Coe, R., Noordwijk, v.M., Ambagau, Y., and Palm, C.A. 2001. Reducing uncertainty in the use of allometric biomass equations for predicting aboveground tree biomass in mixed secondary forests. Forest Ecology and Management 146: 199–209. Krisnawati, H. dan Bustomi, S. 2002. Tabel isi pohon jenis bintangur (Callophyllum Callophyllum sp.) di KPH Sanggau, Kalimantan Barat. Buletin Penelitian Hutan 630: 1-15. Krisnawati, H. dan Bustomi, S. 2004. Model penduga isi pohon bebas cabang jenis sungkai (Peronema ( Peronema canescens) canescens ) di KPH Banten. Buletin Penelitian Hutan 644: 3950. Krisnawati, H. dan Harbagung. 1996. Kajian angka bentuk batang untuk pendugaan volume jenis-jenis hutan alam. Prosiding Diskusi Hasil-Hasil Penelitian dalam Menunjang Pemanfaatan Hutan yang Lestari, Cisarua, Bogor, 11-12 Maret 1996. Hal 177-191. Lehtonen, A., Mäkipää, R., Heikkinen, J., Sievänen, R. and Liski, J. 2004. Biomass expansion factors (BEFs) for Scots pine, Norway spruce and birch according to stand

62

References

Snowdon, P. 1990. A ratio estimator for bias correction in logarithmic regressions. Canadian Journal of Forestry Research 21: 720-724.

Wahyunto, S. Ritung, Suparto, H. dan Subagjo. 2005. Sebaran Gambut dan Kandungan Karbon di Sumatera dan Kalimantan. Proyek Climate Change, Forests and Peatlands in Indonesia. Wetlands InternationalIndonesia Programme dan Wildlife Habitat Canada. Bogor. Whitmore, T.C. 1975. Tropical Rain Forests of the Far East. Clarendon Press, Oxford, UK. Zianis, D. and Mencuccini, M. 2003. Aboveground biomass relationship for beech ((Fagus moesiaca Cz.) trees in Vermio Mountain, Northern Greece, and generalised equations for Fagus spp. Annals of Forest Science 60: 439–448.

CO

Snowdon, P., Eamus, D., Gibbons, P., Khanna, P.K., Keith, H., Raison, R.J. and Kirschbaum, M.U.F. 2000. Synthesis of allometrics, review of root biomass and design of future woody biomass sampling strategies. National Carbon Accounting System Technical Report 17. Australian Greenhouse Office, Canberra. 114 p.

Sumatera Selatan. Buletin Penelitian Hutan 587: 31-44.

PY

(EMDI), Environmental Reports 8, Jakarta and Halifax. Scargle, J. 2000. Publication bias: the “FileDrawer” Problem in scientific inference. Journal of Scientific Exploration 14: 91-106.

Soares, M.L.G. and Schaeffer-Novelli, Y.S. 2005. Aboveground biomass of mangrove species. I. Analysis of models. Estuarine, Coastal and Shelf Science 65: 1-18.

AL

Sprugel, D.G. 1983. Correcting for bias in logtransformed allometric equations. Ecology 64: 209–210. United Nations [UN]. 1998. Kyoto Protocol to the United Nations Framework Convention on Climate Change.

FIN

United Nations Framework Convention on Climate Change [UNFCCC]. 2009. Draft decision [-/CP.15] Methodological guidance for activities relating to reducing emissions from deforestation and forest degradation and the role of conservation, sustainable management of forest and enhancement of forest carbon stocks in developing countries. Subsidiary body for scientific and technological advice, Copenhagen. Wahjono, D., Krisnawati, H. dan Harbagung. 1995. Tabel isi pohon sementara jenis Gmelina arborea di Daerah Subanjeriji,


63

AL

FIN PY

CO

PY CO AL FIN

Appendices


65

AL

FIN PY

CO


67

FIN

Mixed

Borassodendron borneensis

HF

HF

HF

HF

HF

HF

DLF

DLF

DLF

3

4

5

6

7

8

9

10

11

Mixed

Mixed

DLF

DLF

DLF

DLF

DLF

DLF

DLF

DLF

DLF

DLF

DLF

DLF

14

15

16

17

18

19

20

21

22

23

24

25

Mixed

13

Dipterocarpaceae

Dipterocarpaceae

Commercial

Mixed

Mixed

Mixed

Mixed

Mixed

Mixed

Mixed

Mixed

DLF

DLF

12

Mixed

Borassodendron borneensis

Mixed

Mixed

Mixed

Mixed

Mixed

Mixed

HF

2

Mixed

HF

1

Species

Ecosystem Type

KALTIM

KALTIM

KALTIM

KALTIM

KALTIM

KALTIM

KALTIM

KALTIM

KALTIM

KALTENG

KALTENG

KALTENG

KALTENG

KALTENG

KALTENG

KALTIM

KALTIM

KALTENG

KALTENG

KALTENG

KALBAR

KALBAR

KALBAR

KALBAR

KALBAR

Site

Le

Br+Tw

AGB

AGB

St

AGB

Le

4.8 4.8

184

2

115.0

115.0

115.0

nda

nda

69.7

69.7

69.7

30.3

30.3

30.3

30.3

30.3

Max

1.1

115.0

WL = 0.0915 (WS+WB)0.727

WB = 0.119 Ws

1.059

lnW = -1.498 + 2.234 lnD

5.0

5.0

191 191

5.0

6.0

83

122

76

Ws = 0.02903 (D2H)0.981 lnW = -1.201 + 2.196 lnD

40

lnW = -1.2495 + 2.311 lnD

W = 0.0455 D

55.0 .0

30.1

68.9

5.7

6.0 6.0

14

1.69

130.0

130.0

70.0

200.0

130.0

30.1

30.1

5.7

0.975

5.7

2

14

115.0 14

1.1

115.0

W = 0.0286 D2.41

W = 0.024 (D H)

40

40

lnW = -2.246 + 2.482 lnD

1.1

PY 40

ρ + 2.288 lnW = -3.049 + 0.54 lnWD + 2.288 lnD lnW = -3.408 + 2.708 lnDpkl

1.1 1.1

40

1.1

40

lnW = -0.881 + 0.976 lnWs

40

nda

nda

nda

nda

4.8

184

lnW = -3.217 + 2.057 lnD - 0.018 lnD3

lnW = -3.285 + 2.612 lnD

WL = 0.00944 D2

2

WS = 0.0123 D

lnW = -3.86 + 1.01 lnD2

CO

lnW = -4.28 + 1.36 lnD

2.6

12

2.6

2.6

2.6

2.6

Min

DBH (cm)

184

12

12

12

12

∑ Sample Trees

lnW = -2.26 + 1.27 lnD2

lnW = -3.101 + 2.066 lnD

lnW = -5.298 + 2.926 lnD

lnW = -6.908 + 3.541 lnD

lnW = -2.688 + 2.829 lnD

lnW = -1.861 + 2.528 lnD

Model Form

AL

Br+Tw

St

TTB

AGB

Rt

Le

Br

St

Le

St

Le

Br+Tw

St

Le

Tw

Br

St

AGB

Component

nda

nda

nda

nda

nda

11.1

5.5

5.5

5.5

2.4

2.4

2.4

2.4

2.4

2.4

nda

nda

nda

nda

nda

5.4

5.4

5.4

5.4

5.4

Min

nda

nda

nda

nda

nda

43.5

23.0

23.0

23.0

49.0

49.0

49.0

49.0

49.0

49.0

nda

nda

35.9

35.9

35.9

25.2

25.2

25.2

25.2

25.2

Max

H (m)

0.92

0.90

0.98

0.96

0.99

0.98

0.80

0.90

0.97

0.98

0.98

0.97

0.93

0.97

0.98

nda

nda

0.81

0.91

0.99

0.98

0.97

0.96

0.99

0.99

R2

nda

nda

nda

nda

nda

0.15

nda

nda

nda

0.38

0.39

0.52

0.53

0.52

0.41

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

Se

Tree biomass allometric models that have been developed according to tree species and ecosystem type in Indonesia

No

Appendix 1.

78

78

11

11

78

61

38

38

38

8

8

8

8

8

8

78

78

45

45

45

49

49

49

49

49

Ref

Note

68


DLFs

DLFs

DLFs

DLFs

DLFs

DLFs

DLFs

DLFs

DLFs

DLFs

DLFs

44

45

46

47

48

49

50

51

52

53

DLFs

37

43

DLFs

36

DLFs

DLFs

35

DLFs

DLFs

34

42

DLFs

33

41

DLFs

32

DLFs

DLF

31

40

DLF

30

DLFs

DLF

29

DLFs

DLF

28

39

DLF

27

38

DLF

Ecosystem Type

26

No

Ficus sp.

Mixed (70 yrs)

Mixed (7 yrs)

Mixed (20 yrs)

Mixed

Mixed

Mixed

Mixed

Mixed

Mixed

Mixed

Mixed

Mixed

Mixed

Mixed

Mixed

Mixed

Mixed

Mixed

Macaranga gigantea

Macaranga gigantea

KALTIM

Jambi

Jambi

Jambi

KALTIM

KALTIM

KALTIM

KALTIM

KALTIM

KALTIM

KALTIM

KALTIM

Jambi

Jambi

Jambi

Jambi

Jambi

Jambi

Jambi

KALTIM

KALTIM

KALTIM

KALTIM

Papua

AGB

AGB

AGB

AGB

AGB

Rt

Le

Br+Tw

St

AGB

TTB

TTB

AGB

Le

Tw

Br

St

AGB

CO 29

30

W = 0.1135 D1.22 H1.12

3.5

2.0

22.0 .0

63

63

6.1

30

17

W = 0.0639 D2.513 2.349

lnW = -2.59 + 2.6 lnD

W = 0.0639 D

3.5

6.0

21

108

3.2 3.2

10.3

273

W = 0.0639 D2.390

lnW = -2.51 + 2.44 lnD

W = 0.0457 D1.98

W = 0.0263 D 1.79

2.0

63

2.0

2.0

63

63

5.0

61

5.2

3.5

3.5

3.5

W = 0.0166 D2.44

W = 0.0978 D 2.20

W = 0.19999 D2.14

7.6 3.5

9.1

42.0

20.5

48.0

20.3

24.2

24.2

24.2

24.2

24.2

9.0

9.5

48.1

48.1

48.1

48.1

48.1

48.1

48.1

37.4

37.4

37.4

70.0

40.0

70.0

40.0

70.0

70.0

Max

PY 200

lnW = -2.39 + 2.60 lnD W = 0.0978 D2.58

30

lnW = -2.96 + 1.56 lnD

30

30

lnW = -1.32 + 1.17 lnD

lnW = -1.63 + 1.58 lnD

30

W = 0.11 ρ D2+0.62

lnW = -3.64 + 2.77 lnD

29

lnW = -2.75 + 2.591 lnD

7.6

nda

6

WL = 0.144 (WS+W

Le

AGB

0.778 B)

nda

6

nda

6

St WB = 0.0494 Ws1.351

5.0

5.0

5.0

5.5

5.0

5.0

Min

DBH (cm)

Br+Tw

24

15

19

13

20

20

∑ Sample Trees

lnW = -2.193 + 2.371 lnD

logW = -0.8406 + 2.572 logD

lnW = -1.098 + 2.142 lnD

AL

logW = - 0.762 + 2.51 logD

lnW = -1.813 + 2.339 lnD

lnW = -1.232 + 2.178 lnD

Model Form

Ws = 0.0132 (D2H)0.976

AGB

AGB

AGB

AGB

KALTIM

AGB

Papua

AGB

Component

KALTIM

KALTIM

Site

FIN

Macaranga gigantea

Shorea sp.

Pometia sp.

Palaquium sp.

Intsia sp.

Hopea sp.

Dipterocarpus sp.

Species

nda

6.1

6.1

6.1

nda

nda

nda

nda

nda

nda

4.0

5.0

4.8

4.8

4.8

4.8

4.8

nda

nda

nda

nda

nda

nda

6.0

nda

8.0

nda

nda

Min

nda

28.3

28.3

28.3

nda

nda

nda

nda

nda

nda

15.0

10.0

32.4

32.4

32.4

32.4

32.4

nda

nda

nda

nda

nda

nda

22.4

nda

25.9

nda

nda

Max

H (m)

0.95

0.94

0.95

0.97

0.85

0.87

0.66

0.83

0.95

0.93

0.66

0.59

0.93

0.63

0.56

0.65

0.93

Nda

0.95

nda

0.95

0.98

0.98

0.99

0.98

0.98

0.99

0.99

R2

nda

nda

nda

nda

nda

0.24

0.40

0.34

0.16

0.17

nda

nda

0.50

0.77

0.66

0.75

0.77

nda

nda

nda

nda

nda

nda

0.08

nda

0.02

nda

nda

Se

22

73

73

73

22

2

2

2

2

2

33

57

5

5

5

5

5

37

37

74

74

74

11

43

11

44

11

11

Ref

Note


69

Ecosystem Type

DLFs

DLFs

DLFs

DLFs

DLFs

DLFs

DLFs

DLFs

DLFs

DLFs

DLFs

DLFs

DLFs

DLFs

DLFs

DLFs

DLFs

DLFs

DLFs

No

54

55

56

57

58

59

60

61

62

63

64

65

66

67

68

69

70

71

72

Schima wallichii (3 yrs post-fire)






Schima wallichii (1 yr post-fire)





Schima wallichii

Schima wallichii

Schima wallichii

Schima wallichii

Schima wallichii

Piper aduncum

Other types

Geunsia pentandra

Species

JABAR

JABAR

JABAR

JABAR

JABAR

JABAR

JABAR

JABAR

JABAR

JABAR

JABAR

SUMSEL

SUMSEL

AGB

Le

Tw

Br

St

AGB

Le

Tw

Br

St

AGB

Le

Tw

Br

St

SUMSEL

SUMSEL

AGB

AGB

SUMSEL

KALTIM

AGB

AGB

3.0

15

lnW = -0.902 + 2.33 lnD

lnW = -1.33 + 2.04 lnD

lnW = -3.06 + 3.47 lnD

lnW = -1.84 + 1.99 lnD

lnW = -1.24 + 1.91 lnD

lnW = -0.926 + 2.03 lnD

lnW = -1.68 + 2.87 lnD

lnW = -3.28 + 3.28 lnD

1.6

15

13

13

13

13

13

56

56

1.0

1.0

1.0 1.0

1.0

1.0

1.0

1.1

1.1

4.8

3.0

3.0

3.0

3.0

3.0

3.0

3.0

2.1

1.6

1.6

1.6

1.6

1.6

1.6

PY

1.1

3.0

1.6

56

lnW = -2.44 + 3.57 lnD

1.1

1.6

5.3

5.3

5.3

5.3

5.3

nda

nda

nda

Min

1.6

56

lnW = -1.46 + 2.35 lnD

3.0

24.6

24.6

24.6

24.6

24.6

8.3

20.3

16.2

Max

3.0

56

lnW = -1.22 + 2.67 lnD

W = 0.141 D1.998

CO

3.0

15

1.366

1.1

3.0

15

W = 0.208 D

3.0

15

2.104

W = 0.038 D2.088

3.0

W = 0.262 D

3.2

15

3.2

3.4

Min

DBH (cm)

37

108

20

∑ Sample Trees

W = 0.459 D1.366

lnW = -2.42 + 2.39 lnD

lnW = -2.49 + 2.4 lnD

lnW = -2.89 + 2.62 lnD

Model Form

AL

Component

FIN KALTIM

KALTIM

Site

7.5

3.5

3.5

3.5

3.5

3.5

3.4

3.4

3.4

3.4

3.4

17.0

17.0

17.0

17.0

17.0

nda

nda

nda

Max

H (m)

0.88

0.92

0.85

0.85

0.74

0.88

0.86

0.53

0.91

0.92

0.94

0.92

0.90

0.99

0.99

0.92

0.92

0.81

0.91

R2

0.19

0.09

0.21

0.01

0.17

0.11

0.16

0.01

0.16

0.10

0.09

nda

nda

nda

nda

nda

nda

nda

nda

Se

47

47

47

47

47

47

47

47

47

47

47

60

60

60

60

60

22

22

22

Ref

a

a

a

a

a

a

a

a

a

a

a

Note

70


DLFs

DLFs

DLFs

DLFs

DLFs

DLFs

DLFs

DLFs

DLFs

MF

MF

MF

MF

MF

MF

MF

MF

MF

MF

MF

MF

MF

74

75

76

77

78

79

80

81

82

83

84

85

86

87

88

89

90

91

92

93

94

Ecosystem Type

73

No

Bruguiera parviflora









Riau

Riau

Riau

KALBAR

KALBAR

KALBAR

KALBAR

KALBAR

KALBAR

KALBAR

JABAR

JABAR

JABAR

JABAR

JABAR

JABAR

JABAR

Fl+Fr

Br+Tw

St

Rt

AGB

lnW - -2.01 + 2.51 lnD

lnW = -1.25 + 2.60 lnD

Model Form

14

14

15

15

15

15

∑ Sample Trees

14

lnW = -1.66 + 2.41 lnD

1.3

1.3

1.3

1.3

1.3

1.0

1.0

1.0

1.0

Min

7 7

W = 0.962 (D2H)0.0109 W = 0.0902 (D2H)0.0004

6 7

W = 0.987 (D2H)0.0372

33

33

logW = -1.516 + 2.283 D

logW = -0.552 + 2.244 D

logW = -3.422 + 2.358 D

10.0

10.0

10.0

5.7

24.8

24.8

24.8

33.5

60.9

60.9

60.9

5.0

33

logW = -1.380 + 2.056 D logW = -0.987 + 1.592 D

60.9

55.0 .0

5.0

33

logW = -2.408 + 3.106 D

60.9

35.2

55.0 .0

5.0

33

logW = -0.499 + 2.037 D

W = 0.168 D

60.9

6.4

47

1.794

35.2

35.2

5.0

6.4

47

33

6.4

47

W = 0.185 D2.352

W = 0.291 D2.260

5.1

5.1

5.1

5.1

5.1

4.8

4.8

4.8

4.8

Max

DBH (cm)

PY

14

14

lnW = -3.17 + 3.66 lnD

lnW = -1.90 + 2.45 lnD

CO

lnW = -1.22 + 2.69 lnD

lnW = -1.02 + 2.64 lnD

lnW = -1.25 + 1.35 lnD

lnW = -2.90 + 3.60 lnD

AL

Fl+Fr

Le

Tw

Br

St

Rt

AGB

TTB

Le

Tw

Br

St

AGB

Le

JABAR

JABAR

Tw

Br

JABAR

JABAR

St

Component

JABAR

Site

FIN


Avicennia marina

Avicennia marina

Avicennia marina










Species

nda

nda

nda

7.4

6.6

6.6

6.6

6.6

6.6

6.6

3.5

3.5

3.5

2.5

2.5

2.5

2.5

2.5

2.1

2.1

2.1

2.1

Min

nda

nda

nda

20.9

20.9

20.9

20.9

20.9

20.9

20.9

11.3

11.3

11.3

7.0

7.0

7.0

7.0

7.0

7.5

7.5

7.5

7.5

Max

H (m)

0.94

0.98

0.99

0.98

0.99

0.45

0.82

0.85

0.94

0.97

0.86

0.98

0.98

0.82

0.65

0.85

0.96

0.96

0.54

0.71

0.69

0.84

R2

nda

nda

nda

0.01

0.00

0.44

0.04

0.05

0.04

0.01

nda

nda

nda

0.20

0.04

0.19

0.10

0.10

0.27

0.51

0.37

0.25

Se

40

40

40

39

39

39

39

39

39

39

16

16

16

47

47

47

47

47

47

47

47

47

Ref

a

a

a

a

a

a

a

a

a

Note


71

MF

MF

MF

MF

MF

MF

MF

MF

MF

MF

MF

MF

MF

MF

MF

MF

MF

MF

MF

MF

104

105

106

107

108

109

110

111

112

113

114

115

116

117

118

119

120

121

122

MF

102

103

MF

101

Bruguiera sexangula

MF

MF

99

100














Bruguiera spp.

Bruguiera spp.

Bruguiera spp.

Bruguiera spp.

Bruguiera spp.

Bruguiera spp.

Bruguiera spp.

Bruguiera spp.

Bruguiera spp.

Bruguiera spp.

Riau

Riau

Riau

Riau

Riau

Riau

Riau

Riau

KALBAR

KALBAR

KALBAR

KALBAR

KALBAR

Riau

Riau

Riau

Riau

Riau

Riau

Riau

KALTIM

KALTIM

Br+Tw

Br+Tw

St

Rt

Le

Tw

Br

St

TTB

Le

Tw

Br

St

AGB

Rt

Fr

Le

Tw

Br

St

TTB

Rt

7 9 9

W = 0.8902 (D H) W = 1.0293 (D2H)0.0126

2

0.0796

∑ Sample Trees

W = 0.0685 (D2H)0.0252

Model Form

9

10.8 10.8 10.8

12

12

2.5

2.5

2.5

1.1

1.1

11.1 .1

11.1 .1

34

21

21

21

21

W = 5.59 D0.69 1.34

2.5

2.5

34

34

34

5 5

0.081

W = 0.902 (D H)

W = 0.904 (D2H)0.029

10.0

10.0

1.1

21 2

1.1

21

W = 0.64 D

W = 0.0078 D3.09

W = 2.13 D0.69

W = 0.21 D2.45

W = 0.75 D2.23

logW = -1.68 + 1.92 logD

49.5

49.5

38.2

38.2

38.2

38.2

38.2

38.2

40.0

40.0

40.0

40.0

40.0

22.3

22.3

22.3

22.3

22.3

22.3

22.3

37.0

37.0

37.0

40.5

40.5

40.5

40.5

24.8

Max

PY

10.8

12

10.8

10.8

12

12

10.8

12

34

logW = -1.29 + 1.63 logD

logW = -2.02 + 2.37 logD

10.5

10.5

10.5

10.0

10.0

10.0

10.0

10.0

Min

DBH (cm)

12

11

11

CO

logW = -1.78 + 2.84 logD

logW = -1.34 + 2.60 logD

W = 6.5 D1.00

W = 10.45 D

0.54

W = 5.52 D0.56

W = 6.63 D0.58

W = 4.82 D

0.71

W = 0.95 D1.87

W = 10.11 D

1.3

lnW = -3.89 + 3.04 lnD

lnW = -5.59 + 3.35 lnD

11

W = 0.0602 (D H) 0.00525

lnW = -2.24 + 2.57 lnD

2

9

W = 0.073 (D2H)0.0021

AL

Fl+Fr

St

Riau

KALTIM

Le

Br+Tw

St

Le

Component

Riau

Riau

Riau

Riau

Site

FIN

Bruguiera sexangula

MF

98

Bruguiera sexangula

Bruguiera sexangula

MF

MF


96

MF

95

Species

97

Ecosystem Type

No

nda

nda

11.0

11.0

11.0

11.0

11.0

11.0

2.9

2.9

2.9

2.9

2.9

12.0

12.0

12.0

12.0

12.0

12.0

12.0

12.3

12.3

12.3

nda

nda

nda

nda

nda

Min

nda

nda

32.0

32.0

32.0

32.0

32.0

32.0

27.3

27.3

27.3

27.3

27.3

19.5

19.5

19.5

19.5

19.5

19.5

19.5

18.0

18.0

18.0

nda

nda

nda

nda

nda

Max

H (m)

0.97

0.99

0.94

0.66

0.68

0.85

0.98

0.98

0.87

0.68

0.88

0.95

0.97

0.98

0.45

0.61

0.91

0.89

0.99

0.99

0.95

0.88

0.91

0.97

0.88

0.95

0.98

0.96

R2

nda

nda

nda

nda

nda

nda

nda

nda

0.22

0.23

0.26

0.20

0.14

nda

nda

nda

nda

nda

nda

nda

0.28

0.54

0.34

nda

nda

nda

nda

nda

Se

40

40

30

30

30

30

30

30

7

7

7

7

7

30

30

30

30

30

30

30

70

70

70

40

40

40

40

40

Ref

Note

72


MF

MF

MF

MF

MF

MF

MF

MF

MF

MF

MF

MF

MF

MF

133

134

135

136

137

138

139

140

141

142

143

144

145

146

CF

MF

132

149

MF

131

CF

MF

130

CF

MF

129

147

MF

128

148

MF

MF

126

127

MF

MF

124

125

MF

Ecosystem Type

123

No

Rhizophora mucronata

Dalbergia latifolia

Mixed


Xylocarpus granatum

Xylocarpus granatum

Xylocarpus granatum

Xylocarpus granatum

Xylocarpus granatum

Rhizophora spp.

Rhizophora spp.

Rhizophora spp.

Rhizophora spp.












DIY

JATENG & DIY

DIY

KALBAR

KALBAR

KALBAR

KALBAR

KALBAR

KALTIM

KALTIM

KALTIM

KALTIM

Riau

Riau

Riau

Riau

Riau

Riau

Rt-slt

AGB

AGB

AGB

Le

Tw

Br

St

AGB

Rt

5 5 5

W = 0.0404 (D H) W = 0.8164 (D2H)0.0359

2

0.0034

∑ Sample Trees

W = 0.0748 (D2H)0.0021

Model Form

11.1

7

49.4

49.4

5.9

5.9 5.9

5.9 5.9

30

10

58

10

0.902

W = 0.078 (D H)

W = 0.022 (D2H)1.010 W = 0.746 (D2H)0.639

nda

nda

nnda da

49.4

5.9

30

30

5.9

30

nda

nda

nda

49.4

49.4

46.5

46.5

11.0

46.5

46.5

11.0

11.0

11.0

11

30 2

24.5

24.5

24.5

24.5

24.5

PY

11.1

11.1

11.1

11.1

24.5

24.5

7.8

7.8

7.8

7.8

7.8

49.5

49.5

49.5

Max

11

logW = -0.968 + 1.51 logD

logW = - 1.00 + 1.79 logD

logW = - 2.20 + 2.78 logD

logW = - 1.09 + 2.28 logD

logW = - 0.763 + 2.23 logD

lnW = -1.79 + 2.21 lnD

lnW = -4.74 + 1.56 lnD + 1.47 lnH

11

11

7

7

7

7

7

11.1

11.1

7

CO

lnW = -5.11 + 1.48 lnD + 2.60 lnH

lnW = -3.04 + 1.75 lnD + 1.15 lnH

W = 0.0008 D3.64

0.87

W = 0.52 D

W = 2.19 D0.86

W = 0.0007 D3.73

W = 0.031 D

2.64

W = 0.47 D2.15

W = 0.5 D

2.32

2.0 2.0

10

Ws = -1.919 + 2.597 logD

2.0

2.0

2.0

10.0

10.0

10.0

Min

DBH (cm)

10

10

Ws = -1.996 + 3.273 logD

WR = -2.4696 + 3.880 logD

10 10

W = -0.904 + 2.950 logD

Ws = -0.933 + 2.753 logD

AL

Br+Tw

St

Rt

Fr

Le

Tw

Br

St

TTB

Rt-slt

Riau

Le

JATENG

Br+Tw

St

AGB

Rt

Fl+Fr

Le

Component

JATENG

JATENG

JATENG

JATENG

Riau

Riau

Riau

Site

FIN




Species

nda

nda

nda

4.9

4.9

4.9

4.9

4.9

10.5

10.5

10.5

10.5

12.0

12.0

12.0

12.0

12.0

12.0

12.0

4.0

4.0

4.0

4.0

4.0

nda

nda

nda

Min

nda

nda

nda

22.1

22.1

22.1

22.1

22.1

25.0

25.0

25.0

25.0

17.1

17.1

17.1

17.1

17.1

17.1

17.1

7.0

7.0

7.0

7.0

7.0

nda

nda

nda

Max

H (m)

0.89

0.84

0.96

0.75

0.75

0.90

0.95

0.95

0.97

0.94

0.95

0.97

0.91

0.99

0.99

0.91

0.90

0.91

0.90

0.89

0.87

0.90

0.88

0.89

0.95

0.95

0.96

R2

nda

nda

nda

0.20

0.24

0.21

0.12

0.11

0.17

0.32

0.35

0.22

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

Se

12

12

12

71

71

71

71

71

70

70

70

70

30

30

30

30

30

30

30

69

69

69

69

69

40

40

40

Ref

a

a

a

a

a

Note


73

CF

CF

174

175

CF

165

CF

CF

164

173

CF

163

CF

CF

162

172

CF

161

CF

CF

160

171

CF

159

CF

CF

158

CF

CF

157

170

CF

156

169

CF

155

CF

CF

154

168

CF

153

CF

CF

152

CF

CF

151

166

CF

150

167

Ecosystem Type

No










Le

SULUT

JATENG

JABAR

JABAR

JABAR

JABAR

JABAR

JABAR

JABAR

JABAR

JABAR

SULUT

SULUT

SULUT

SULUT

SULUT

SULUT

SULUT

SULUT

SULUT

AGB

St-fb

A-(D>0.5 cm)

A-(D<0.5 cm)

Stp

Le

Tw

Br

logW = -1.061 + 2.49 logD

logW = -0.701 + 2.4 logD

Model Form

15

15

15

15

logW = -2.678 + 2.88 logD

logW = -2.041 + 2.49 logD

logW = -2.638 + 2.89 logD

logW = -1.2 + 1.83 logD 15 8

logW = -2.0 + 2.67 logD W = -67.6 + 1.442D - 3.16H

H

8 18

W = - 10.3 + 382D -2.08H W = 0.0199 (D2H)0.930

8

W = 144543.9 D2.86 H1.38

8 8

W = - 0.088 + 0.948 D + 0.154H

W = 28.8 D1.04 H0.187

8

8

8

0.939

W = -2.74 + 16.4D + 0.741H

W = 3388.4 D 2.17

W = - 13.7 + 763D -7.69H

8

15

logW = -0.148 + 0.624 logD

W = -32.3 + 550 D - 1.84H

7.5

7.5

7.5

7.5

7.5

7.5

6.9

6.9

6.9

6.9

6.9

6.9

6.9

6.9

50.0

50.0

50.0

50.0

50.0

50.0

37.2

37.2

37.2

37.2

37.2

37.2

37.2

37.2

Max

DBH (cm) Min

nda

5.0

5.0

5.0 5.0

55.0 .0

5.0

5.0

5.0

5.0

5.0

7.5

7.5

nda

>50

>50

>50

>50

>50

>50

>50

>50

>50

50.0

50.0

PY

15

logW = -1.58 + 2.79 logD

CO

15

15

15

15

15

15

15

15

15

∑ Sample Trees

logW = -1.190 + 2.71 logD

logW = -1.520 + 2.29 logD

logW = -4.0 + 2.49 logD

logW = -0.863 + 1.63 logD

logW = -2.046 + 2.47 logD

logW = -1.620 + 2.39 logD

logW = -2.092 +2.51 logD

AL

St-stp

AGB

Rt

Fr

Le

Tw

Br

Brk

St

TTB

Rt

Fr

Tw

SULUT

Br

Brk

SULUT

SULUT

St

SULUT

SULUT

TTB

Component

SULUT

Site

FIN


Elmerrillia ovalis

Elmerrillia ovalis

Elmerrillia ovalis

Elmerrillia ovalis

Elmerrillia ovalis

Elmerrillia ovalis

Elmerrillia ovalis

Elmerrillia ovalis









Species

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

6.5

6.5

6.5

6.5

6.5

6.5

6.5

6.5

6.5

6.5

6.5

6.5

6.5

6.5

6.5

6.5

Min

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

28.6

28.6

28.6

28.6

28.6

28.6

28.6

28.6

29.3

29.3

29.3

29.3

29.3

29.3

29.3

29.3

Max

H (m)

0.99

0.81

0.85

0.81

0.88

0.97

0.87

0.94

0.97

0.98

0.97

0.77

0.94

0.98

0.98

0.98

0.99

0.99

0.95

0.74

0.89

0.96

0.98

0.96

0.98

0.99

R2

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

0.03

0.11

0.08

0.03

0.11

0.09

0.08

0.03

0.05

0.11

0.01

0.05

0.12

0.11

0.09

0.07

Se

12

56

56

56

56

56

56

56

56

56

41

41

41

41

41

41

41

41

41

41

41

41

41

41

41

41

Ref

b

b

b

b

b

b

b

b

b

Note

74


CF

CF

CF

CF

CF

CF

CF

CF

CF

CF

CF

CF

CF

CF

CF

CF

CF

PSF

PSF

PSF

PSF

PSF

PSF

PSF

PSF

PSF

PSF

PSF

177

178

179

180

181

182

183

184

185

186

187

188

189

190

191

192

193

194

195

196

197

198

199

200

201

202

203

Ecosystem Type

176

No

Mixed

Mixed

Mixed

Mixed

Mixed

Mixed

Mixed

Mixed

Mixed

Mixed

Mixed

Tectona grandis

Tectona grandis

Tectona grandis

Tectona grandis

Tectona grandis

Tectona grandis

Tectona grandis

Tectona grandis

Swietenia mahagony

Pinus merkusii

Pinus merkusii

Pinus merkusii



KALTENG

KALTENG

KALTENG

KALTENG

KALTENG

KALTENG

KALTENG

KALTENG

KALTENG

KALTENG

KALTENG

DIY

DIY

DIY

DIY

DIY

DIY

DIY

JATENG

JATENG

JABAR

JABAR

JABAR

JATENG

Tw

Tw

Br

Br

Br

Br

St

St

St

St

AGB

Rt

Fl+Fr

Le

logW = -2.786 + 3.031 logD

logW = -1.061 + 2.343 logD

logW = -1.239 + 2.561 logD

Model Form

5.1 5.1

15

2.176

CO 5.1

15

W = 0.0076 (DH)1.1937

W = 0.016 D2.037

1.486 W = 0.008 (D*ρ*H) (DρH)1.486

W = 0.043 (Dρ)2.450

W = 0.0036 (DH)

1.513

W = 0.037 (DρH) W = 0.009 D2.605

1.523

W = 0.251 (Dρ)2.404

W = 0.014 (DH)1.569

W = 0.048 D2.604

nda nda

30

nda

30

30

nda

nnda da

30

30

nnda da

nda

30

30

nda

nda

30

30

2.0

nda

30

2, 486

nda

5.1

15

W = 0.107 D

27.1

27.1

27.1

27.1

27.1

nda

nda

44.0

44.0

44.0

43.8

43.8

43.8

43.8

43.8

Max

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

35.0

27.1

27.1

PY 5.1

15

W = 0.037 D2.167

W = 0.187 D

5.1

15

W = 0.0498 D2.196 0.751

5.1

15

W = 0.0789 D2.178

W = 0.166 D

2.13

W = 0.412 D

15

nda

10

W = 0.370 D2.125

W = 0.015 (D2H)1.084

nda

10

W = 0.903 (D H) 0.684

0.4

2

0.4

80

W = 0.094 D

80

2.432

W = 0.010 D2.604

0.4

80

W = 0.103 D2.459

nda

nda

nda

nda

Min

DBH (cm)

nda

30

30

30

30

∑ Sample Trees

30

logW = -1.84 + 2.01 logD

logW = -2.39 + 2.496 logD

AL

Br+Tw

St

AGB

TTB

AGB

AGB

Rt

AGB

TTB

Le

Tw

Br

JATENG

St

JATENG

AGB

Component

JATENG

JATENG

Site

FIN




Species

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

Min

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

Max

H (m)

nda nda

0.97 0.973 0.89 0.890

0.79

0.81

0.85

0.88

nda

nda

nda

nda

nda

nda

0.841 0.84

nda

0.98

nda

nda

0.14

0.08

0.19

0.44

0.22

0.12

0.10

nda

nda

nda

nda

nda

0.10

0.12

0.14

0.09

0.07

Se

0.92 0.921

0.97

0.90

0.91

0.03

0.72

0.85

0.86

0.92

0.93

0.98

0.99

0.94

0.95

0.95

0.93

0.94

0.94

0.96

0.97

R2

17

17

17

17

17

17

17

17

17

17

36

6

6

6

6

6

6

6

12

12

66

66

66

59

59

59

59

59

Ref

Note


75

PSF

PSF

PSF

229

PSF

219

227

PSF

218

228

PSF

217

PSF

PSF

216

PSF

PSF

215

226

PSF

214

225

PSF

213

PSF

PSF

212

224

PSF

211

PSF

PSF

210

223

PSF

209

PSF

PSF

208

222

PSF

207

PSF

PSF

206

PSF

PSF

205

220

PSF

204

221

Ecosystem Type

No

Dipterocarpus kerrii


Cotylelobium burckii



KALTENG

KALTENG

KALTENG

KALTENG

KALTENG

KALTENG

Riau

Riau

Riau

Riau

Riau

Riau

KALTENG

KALTENG

KALTENG

KALTENG

KALTENG

KALTENG

2

nda

30

30

nda

nda

2.2897

(DρH) W = 0.085 (Dρ (D ρH) H)1.4345

W = 0.0145D - 0.47D + 30.64D263.32 W = 0.7034D2 - 16.518D + 147.2

AGB

W = 0.217 D

2.38

lnW = -1.53 + 2.38 lnD

lnW = 1.40 + 2.00 lnD -1.82 lnρ

AGB

W = 0.30 D

2.29

lnW = -1.21 + 2.29 lnD lnW = -2.10 + 2.09 lnD + 0.55 lnH

AGB

PY 5.0 5.0

20

5.0

20

20

40.0

40.0

40.0

40.0

40.0

55.0 .0

5.0

20

20

40.0

nda

5.0 5.0

nda

20

W = -0.0012D3 + 0.12D2 2.33D+17.03

nda

nda

nda

nda

nda

nda

nda

W = 0.003D3 - 0.139D2 + 21.189D

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

Max

nda

nda

nda

2

W = -0.0142D + 1.553D - 31.817D 3

W = 0.002D3 - 0.15D2 + 3.53D 21.202

3

nda

nda

30

W = 0.4864 (Dρ (Dρ) (D ρ))

nda

30

nda

30

W = 0.0355 (DH) 1.474

2.4695

W = 0.1032 D

W = 0.047 (Dρ (DρH) (D ρH) H)1.2184

CO

30

W = 0.1994 (Dρ (Dρ) (D ρ)) nda

nda

30

1.968

nda

30

nda

nda

30 30

nda

30

W = 0.0225 (DH)1.2501

W = 0.0628 D

2.0565

(DρH)0.8503 W = 0.0466 (D

(Dρ)1.3779 W = 0.125 (D

W = 0.028 (DH)

0.8803

AL

W = 0.0467 D1.5055 nda

nda

30

1.174

30

nda

30

W = 0.0542 (Dρ)1.9173 W = 0.0146 (DρH)

Min

DBH (cm)

∑ Sample Trees

Model Form

AGB

AGB

AGB

Le

Brk

Tw

Br

St

AGB

TTB

TTB

TTB

TTB

Rt

Rt

Rt

Rt

KALTENG

KALTENG

Le

Le

Le

Le

Tw

Tw

Component

KALTENG

KALTENG

KALTENG

KALTENG

KALTENG

KALTENG

Site

FIN


Mixed

Mixed

Mixed

Mixed

Mixed

Mixed

Mixed

Mixed

Mixed

Mixed

Mixed

Mixed

Mixed

Mixed

Mixed

Mixed

Mixed

Mixed

Mixed

Mixed

Species

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

Min

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

Max

H (m)

0.96

0.96

0.95

0.98

0.97

0.97

0.79

0.91

0.93

0.87

0.95

0.95

0.96

0.93

0.96

0.96

0.92

0.92

0.90

0.89

0.78

0.77

0.79

0.83

0.77

0.76

R2

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

Se

4

4

4

4

4

4

35

35

35

35

35

35

17

17

17

17

17

17

17

17

17

17

17

17

17

17

Ref

b

b

b

b

b

b

Note

76


PSF

PSF

PSF

PSF

PSF

PSF

PSF

PSF

PSF

PSF

PSF

PSFs

PSFs

PSFs

PSFs

PSFs

PSFs

PSFs

PSFs

PSFs

PSFs

PF

PF

PF

PF

PF

PF

PF

231

232

233

234

235

236

237

238

239

240

241

242

243

244

245

246

247

248

249

250

251

252

253

254

255

256

257

Ecosystem Type

230

No

Acacia crassicarpa

Acacia crassicarpa

Acacia crassicarpa

Acacia crassicarpa

Acacia crassicarpa

Acacia crassicarpa

Acacia crassicarpa

Mixed

Mixed

Mixed

Mixed

Mixed

Mixed

Mixed

Mixed

Mixed

Mixed

Shorea parvifolia

Shorea parvifolia

Shorea parvifolia

Shorea parvifolia

Gonystylus bancanus

Gonystylus bancanus

Gonystylus bancanus

SUMSEL

Riau

Riau

Riau

Riau

Riau

Riau

SUMSEL

SUMSEL

SUMSEL

SUMSEL

SUMSEL

SUMSEL

SUMSEL

SUMSEL

SUMSEL

SUMSEL

KALTENG

KALTENG

KALTENG

KALTENG

Riau

Riau

Riau

AGB

TTB

Rt

Le

Tw

Br

St

Le

Tw

Br

St

AGB

AGB

Le

Tw

Br

St

AGB

AGB

AGB

AGB

Le

Tw

Br

Brk

St

Riau

AGB

Riau

AGB lnW = -2.47 + 2.44 lnD

lnW = -2.61 + 2.78 lnD +0.80 lnρ

lnW = -2.24 + 2.12 lnD +0.52 lnH

Model Form

2.0

20

5.3

5.3

5.3

30

30

30

W = 0.206284 D2.4511 2.44672

40

H

4.6 6.0

40 10

0.165

Hbc W = 0.0267 D2.8912

W = 0.398918 D

2.041

4.6

40

W = 0.433874 D0.158 H1.040

4.6

44.6 .6

40

40

W = 0.122947 D

44.6 .6

40

W = 0.211401 D1.965 H-0.454

1.793

W = 0.0018 D5.37H-2.299

W = 0.168976 D 0.133

4.6

5.3

30

2.322

5.3

30

W = 0.066973 D 1.9158

W = 0.066742 D1.7589

W = 0.00862 D2.6927

W = 0.158976 D

2.0

20

W = 0.153108 D2.40

30.2

30.2

30.2

30.2

40.0

40.0

40.0

40.0

75.1

75.1

75.1

75.1

75.1

40.0

40.0

Max

28.0

23.5

23.5

23.5

23.5

23.5

23.5

64.0

64.0

64.0

64.0

64.0

30.2

PY

2.0

20

1.65

W = 0.072444 D

2.0

20

W = 0.022387 D2.13

W = 0.007763 D2.51

2.0

20

5.0

20

lnW = -1.03 + 2.08 lnD - 0.51 lnρ ln

CO

5.0 5.0

20 20

5.0

10.0

10.0

10.0

10.0

10.0

5.0

5.0

Min

DBH (cm)

20

10

10

10

10

10

20

20

∑ Sample Trees

W = 0.060256 D2.62

lnW = -2.99 + 2.35 lnD + 0.44 lnH

W = 0.09 D

2.58

lnW = -2.36 + 2.58 lnD

lnW = -3.05 + 1.62 lnD

lnW = -3.01 + 2.04 lnD

lnW = -4.3 + 2.65 lnD

lnW = -5.33 + 2.27 lnD

AL

Component

KALTENG

KALTENG

Site

FIN

Gonystylus bancanus

Gonystylus bancanus



Species

nda

nda

nda

nda

nda

nda

nda

6.6

6.6

6.6

6.6

6.6

2.8

2.8

2.8

2.8

2.8

nda

nda

nda

nda

14.2

14.2

14.2

14.2

14.2

nda

nda

Min

nda

nda

nda

nda

nda

nda

nda

31.2

31.2

31.2

31.2

31.2

19.1

19.1

19.1

19.1

19.1

nda

nda

nda

nda

44.3

44.3

44.3

44.3

44.3

nda

nda

Max

H (m)

0.96

0.99

0.99

0.99

0.98

0.95

0.99

0.61

0.77

0.84

0.96

0.96

0.98

0.67

0.85

0.85

0.98

0.99

0.99

0.99

0.99

0.96

0.97

0.94

0.99

0.99

0.98

0.97

R2

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

0.33

0.35

0.42

0.31

0.19

nda

nda

Se

58

81

81

81

81

81

81

46

46

46

46

46

77

77

77

77

77

4

4

4

4

64

64

64

64

64

4

4

Ref

Note


77

PF

PF

PF

PF

PF

280

281

282

283

PF

275

PF

PF

274

279

PF

273

278

PF

272

PF

PF

271

PF

PF

270

276

PF

269

277

PF

PF

264

PF

PF

263

268

PF

262

267

PF

261

PF

PF

260

PF

PF

259

265

PF

258

266

Ecosystem Type

No

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Species

KALTIM

KALBAR

KALBAR

KALBAR

KALBAR

KALBAR

JABAR

JABAR

JABAR

JABAR

JABAR

JABAR

JABAR

JABAR

JABAR

JABAR

JABAR

JABAR

JABAR

JABAR

AGB

Rt

Le

Br

St

TTB

AGB

AGB

Rt

St

AGB

TTB

Rt

Le

Br

St

Rt

AGB

TTB

TTB

Rt

Le

JABAR

JABAR

Tw

Br

JABAR

JABAR

St

Rt

<5

8

nda

15

2.8202

nda

1.4

15

22

W = 1.6106 (D2H)0.6173

W = 2.5121 (D H)

1.4

1.4

22

22

W = 0.071D2.715

W = -3.43 + 0.09 D2

9.9 9.0

27 6

nnda da

nda

27

W = 5.59 + 0.13 D2 - 1.11 H

nnda da

27

W = -6.21 + 0.44 D2 - 0.92 H W = -0.06 + 0.66 D + 0.01 D2 - 0.38 H

27

27

W = 0.12 + 0.70D - 2.56 H

nda

nda

2

nda

26

nda

logW = -0.727 + 1.131 logD W = 0.0824 D1.4448

W = 0.0066 D2.96

W = 0.1524 D

1.4

22

2.1227

21.0

20.0

nda

nda

nda

nda

nda

nda

18.9

18.9

18.9

18.9

nda

nda

nda

nda

nda

nda

nda

40.0

40.0

40.0

40.0

40.0

40.0

40.0

PY

nda

W = 0.1995 D2.1479

W = 0.1997 D2.2351

2

1.0193

15

W = 2.4877 (D H)

nda

15

1.0087

2

15

W = 1.7143 (D2H)0.9934

W = 0.0059 D

CO nda

15 nda

nda

15

W = 0.0528 D

2.7224

W = 0.0471 D2.706

W = 0.140928 D2.31

W = 0.012882 D2.49 <5

<5

8

1.89

8

<5

W = 0.060256 D

<5

8

<5

8 8

5.0

8

Max

DBH (cm) Min

∑ Sample Trees

W = 0.013182 D2.32

W = 0.0910201 D 1.36

W = 0.070794 D2.36

W = 0.00134896 D2.46

Model Form

AL

Component

FIN JABAR

JABAR

Site

nda

7.9

nda

nda

nda

nda

nda

nda

3.5

3.5

3.5

3.5

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

Min

nda

13.7

nda

nda

nda

nda

nda

nda

13.9

13.9

13.9

13.9

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

Max

H (m)

0.99

0.78

0.49

0.69

0.84

0.85

nda

0.95

0.96

0.99

0.99

0.99

0.97

0.65

0.86

0.97

0.99

0.99

0.99

0.99

0.98

0.97

0.99

0.38

0.96

0.98

R2

0.01

0.05

0.02

0.05

0.16

0.23

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

Se

20

76

76

76

76

76

18

31

28

28

28

28

27

27

27

27

25

25

25

55

55

55

55

55

55

15

Ref

d

d

c

c

c

c

Note

78


PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

285

286

287

288

289

290

291

292

293

294

295

296

297

298

299

300

301

302

303

304

305

306

307

308

309

Ecosystem Type

284

No

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Species

FIN SUMSEL

SUMSEL

SUMSEL

SUMSEL

SUMSEL

SUMSEL

SUMSEL

SUMSEL

SUMSEL

SUMSEL

SUMSEL

SUMSEL

SUMSEL

SUMSEL

SUMSEL

SUMSEL

SUMSEL

SUMSEL

SUMSEL

Rt

Le

Br+Tw

St

TTB

Rt

Le

Br+Tw

St

TTB

Rt

Le

Br+Tw

St

TTB

Rt

Le

2.2 8.7 8.7 8.7

26 12 12 12

W = 124.51- 33.45D + 2.77D2 0.05D3

2.2

Min

9.5

12

9.5 9.5

12

12

W = 0.1022 D1.0499

7.0

2.1835

7.0

13.1

13.1

13.1

12

12

12

12

2.5425

W = 0.0014 D2.9264 1.4529

15 15

0.9542

W = 3.1325 (D H)

W = 3.1632 (D2H)1.2020

2

15

W = 3.2245 (D2H)1.1887

nda

nda

nda

nnda da

15

W = 1.415 (D H)

0.9512

13.1

12 2

13.1

12

W = 0.1255 D2.2981

W = 0.1923 D

W = 0.0617 D2.0527

W = 0.0343 D

7.0

12

W = 0.1033 D2.4718

W = 0.0177 D

9.9

9.9

15.2

15.2

15.2

15.2

15.2

11.2

11.2

11.2

11.2

11.2

nda

nda

nda

nda

20.1

20.1

20.1

20.1

20.1

9.9

9.9

9.9

PY

7.0

12

W = 0.0699 D

12

1.8436

W = 0.0126 D2.9027

7.0

12

W = 0.0455 D2.4533

W = 0.1628 D

9.5

12

1.7

9.5

12

W = 0.0005 D2.7389

W = 0.0635 D1.3842

W = 0.9305 D1.1238

CO

8.7

12

2.7470

W = 0.0226 D

8.7

12

W = 0.0005 D3.6486

W = 0.0044 D

2.5079

W = 0.0000025 D5.8210

W = 0.1121 D1.8049

38.5

38.5

Max

DBH (cm)

26

∑ Sample Trees

W = 179.81- 41.54D + 3.14D2 0.05D3

Model Form

AL

Br+Tw

St

TTB

Rt

SUMSEL

Le

SUMSEL

Br+Tw

SUMSEL

SUMSEL

St

St

Riau

SUMSEL

AGB

Component

Riau

Site

nda

nda

nda

nda

11.2

11.2

11.2

11.2

11.2

5.6

5.6

5.6

5.6

5.6

10.6

10.6

10.6

10.6

10.6

4.2

4.2

4.2

4.2

4.2

nda

nda

Min

nda

nda

nda

nda

12.8

12.8

12.8

12.8

12.8

7.0

7.0

7.0

7.0

7.0

13.6

13.6

13.6

13.6

13.6

5.5

5.5

5.5

5.5

5.5

nda

nda

Max

H (m)

0.91

0.77

0.63

0.91

0.97

0.85

0.98

0.92

0.96

0.76

0.78

0.69

0.83

0.72

0.90

0.94

0.66

0.94

0.87

0.93

0.79

0.80

0.91

0.86

0.97

0.99

R2

nda

nda

nda

nda

0.04

0.09

0.30

0.01

0.03

0.03

0.21

0.01

0.28

0.01

0.07

0.43

0.03

0.69

0.05

0.81

0.38

0.15

0.25

0.45

nda

nda

Se

27

27

27

27

34

34

34

34

34

34

34

34

34

34

34

34

34

34

34

34

34

34

34

34

48

48

Ref

Note


79

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

324

325

326

327

328

329

330

331

332

333

334

335

336

337

PF

321

322

PF

320

323

PF

PF

318

319

PF

PF

314

317

PF

313

PF

PF

312

PF

PF

311

315

PF

310

316

Ecosystem Type

No

Gmelina arborea

Gmelina arborea

Eucalyptus grandis

Eucalyptus grandis

Eucalyptus grandis

Eucalyptus grandis

Eucalyptus grandis

Eucalyptus grandis

Eucalyptus grandis

Eucalyptus grandis

Eucalyptus grandis

Eucalyptus grandis

Mixed

Mixed

Mixed

Mixed




KALTIM

KALTIM

SUMUT

SUMUT

SUMUT

SUMUT

SUMUT

SUMUT

SUMUT

SUMUT

SUMUT

SUMUT

JABAR

JABAR

JABAR

JABAR

JATENG

JATENG

JATENG

St

AGB

AGB

Le

Br+Tw

St

AGB

Rt

Le

Br+Tw

St

AGB

TTB

Rt

AGB

TTB

Rt

Le

8.7 8.7

30 30

2.835

2

8.7

30

W = 0.070 D2.58

nda

2.2 2.2

2.2

2.4

2.4

12

12

12

12 18

18

2.0075

W = 0.0625 D1.9472 0.1297

CO 2.2

3

W = 0.2644 D

24 24

0.88

W = 0.06 (D H)

W = 0.03 (D2H)0.94

2

nda

nda

2.0

11.5

30

11.5

11.5

30

30

11.5

30

30

W = 0.0004 D

2.77

4.5

4.5

4.5

10.0

10.0

10.0

10.0

25.1

25.1

25.1

28.3

28.3

28.3

28.3

28.3

Max

nda

nda

21.0

23.9

23.9

23.9

23.9

16.8

27.2

27.2

27.2

27.2

4.5

PY

W = 0.288 D1.94

W = 0.002 D2.71

W = 0.38 D2.03

W = 0.36 D 2.06

3.7

2.4

W = -0.77 + 1.13D

18

18

0.6549

W = 0.5775 D

2.4

18

W = 0.0228 D2.0779

W = 0.0436 D2.6883

W = 0.0678 D2.5794

W = 0.7601 D

W = 0.1892 D2.0436

1.0

1.0

3

W = 0.0159 D

W = 0.0008 D3.865

1.0

2.684

1.0

3 3

W = 0.001 D

0.4

0.4

W = 0.2825 D3.684

4.195

nda

nda

lnW = -0.989 + 0.278 ln(D H)

lnW = -3.212 + 0.905 ln(D2H)

lnW = -5.464 + 0.942 ln(D2H)

8.7

30 0.4

8.7

30

W = 0.4601 D0.883

W = 0.01 D

1.999

W = 0.034 D1.982

W = 0.026 D

Min

DBH (cm)

∑ Sample Trees

Model Form

AL

Br+Tw

St

Br+Tw

SUMSEL

JATENG

St

SUMSEL

AGB

Le

SUMSEL

Tw

SUMSEL

Br

St

AGB

Component

SUMSEL

SUMSEL

SUMSEL

SUMSEL

Site

FIN


Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Species

nda

nda

3.2

17.5

17.5

17.5

17.5

6.7

2.6

2.6

2.6

2.6

2.5

2.5

2.5

2.5

nda

nda

nda

nda

0.7

0.7

0.7

8.4

8.4

8.4

8.4

8.4

Min

nda

nda

22.2

26.5

26.5

26.5

26.5

21.0

27.0

27.0

27.0

27.0

7.3

7.3

7.3

7.3

nda

nda

nda

nda

33.1

33.1

33.1

25.6

25.6

25.6

25.6

25.6

Max

H (m)

0.98

0.98

0.94

0.60

0.60

0.80

0.81

0.78

0.32

0.82

0.98

0.99

0.71

0.72

0.77

0.81

0.95

0.92

0.92

0.98

Nda

Nda

Nda

0.28

0.69

0.44

0.96

0.97

R2

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

Se

3

3

62

52

52

52

52

63

50

50

50

50

68

68

68

68

10

10

10

10

32

32

32

75

75

75

75

75

Ref

a

a

a

a

e

e

e

e

Note

80


PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

339

340

341

342

343

344

345

346

347

348

349

350

351

352

353

354

355

356

357

358

359

360

361

362

363

364

365

Ecosystem Type

338

No

Pinus merkusii

Pinus merkusii

Pinus merkusii

Pinus merkusii

Pinus merkusii

Pinus merkusii

Pinus merkusii

Pinus merkusii

Pinus merkusii

Pinus merkusii

Pinus merkusii

Pinus merkusii

Pinus merkusii

Pinus merkusii

Pinus merkusii







JATENG

JABAR

JABAR

JABAR

JABAR

JABAR

JABAR

JABAR

JABAR

JABAR

JABAR

JABAR

JABAR

JABAR

JABAR

JATIM

JATIM

JATIM

JABAR

JABAR

JABAR

5.3

10

16.6 16.6 16.6

35

35

35

2.565

nda

15

2.815

1.9

23

1.924

logW = -1.18 + 1.72 logD W = 0.2825 D2.0542

Stp

logW= -1.47 + 1.66 logD

logW = -1.74 + 2.01 logD

logW = -2.07 + 2.47 logD

logW = -0.88 + 2.31 logD

logW = -0.686 + 2.26 logD

W = 0.02035 D2.129

W = 0.115 D

17.8 1.0

3

17.8

17.8

17.8

17.8

17.8

30

30

30

30

30

30

1.9

1.9

23

1.9

23

W = 0.197 D 2.061

23

nda

15

W = 0.177 D2.050

W = 0.0031 D3.023

nda

7.6

31.2

31.2

31.2

30.0

30.0

30.0

30.0

20.7

20.7

20.7

20.7

nda

nda

Max

10.0

57.0

57.0

57.0

57.0

57.0

57.0

11.0

11.0

11.0

11.0

nda

nda

PY

nda

15

W = 0.0315 D2.847 W = 0.0288 D

0.6

12

W = 0.0229 D2.84

W = 0.0069 D

.063

W = 0.2831 D2

W = 0.3196 D1.983

W = 0.129 D0.687

W = 0.028 D

CO

2.0

34

2.697

2.0

2.0

34 34

2.0

34

W = 0.148 D2.299

W = 0.113 D2.345

W = (0.1038 - 0.0071D)/(1-0.0688D)

St

Le

Tw

Br

5.3

10

W = 0.0264 + 0.0005 D3.2766

W = -0.367 + 0.0334 D1.916 5.3

5.3

10

10

nda

24

0.427

W = 0.0124 D2.444

2

W = 0.12 (D H)

nda

Min

DBH (cm)

24

∑ Sample Trees

W = 0.017 (D2H)0.765

Model Form

AL

St-stp

AGB

Rt

St

AGB

TTB

Rt

AGB

TTB

TTB

Rt

AGB

TTB

TTB

Rt

AGB

TTB

Le

Bengkulu

JABAR

Br+Tw

St

AGB

Le

Br+Tw

Component

Bengkulu

Bengkulu

Bengkulu

KALTIM

KALTIM

Site

FIN


Hevea brasiliensis

Hevea brasiliensis

Hevea brasiliensis

Hevea brasiliensis

Gmelina arborea

Gmelina arborea

Species

nda

14.0

14.0

14.0

14.0

14.0

14.0

2.4

2.4

2.4

2.4

nda

nda

nda

nda

nda

nda

nda

2.5

2.5

2.5

2.5

8.2

8.2

8.2

8.2

nda

nda

Min

nda

30.0

30.0

30.0

30.0

30.0

30.0

7.3

7.3

7.3

7.3

nda

nda

nda

nda

nda

nda

nda

7.3

7.3

7.3

7.3

18.3

18.3

18.3

18.3

nda

nda

Max

H (m)

0.88

0.44

0.68

0.81

0.71

0.90

0.94

0.92

0.96

0.95

0.95

0.98

0.99

0.99

0.97

0.94

0.87

0.91

0.62

0.93

0.94

0.95

0.18

0.98

0.99

0.99

0.65

0.85

R2

nda

0.01

0.08

0.03

0.02

0.05

0.01

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

Se

10

23

23

23

23

23

23

29

29

29

29

25

25

25

14

65

65

65

68

68

68

68

80

80

80

80

3

3

Ref

e

Note


81

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

378

379

380

381

382

383

384

385

386

387

388

389

390

391

PF

373

PF

PF

372

377

PF

371

PF

PF

370

376

PF

369

PF

PF

368

PF

PF

367

375

PF

366

374

Ecosystem Type

No

Shorea leprosula (2x2m)+ pinus


Shorea leprosula (2x2m)






Shorea leprosula

Shorea leprosula

Shorea leprosula

Shorea leprosula

Shorea leprosula

Shorea leprosula

Shorea leprosula

Shorea leprosula






JABAR

JABAR

JABAR

JABAR

JABAR

JABAR

JABAR

JABAR

KALTIM

JABAR

JABAR

JABAR

JABAR

JABAR

JABAR

JABAR

KALBAR

KALBAR

KALBAR

KALBAR

KALBAR

AL 2.8

45

1.95

AGB

TTB

Rt

Le

Br+Tw

St

AGB

TTB

AGB

Br

St-fb

St

St+Br

Rt

AGB

2.8

45

nda nda 5.0

15

98

2.333

3.23

5.0

3.0

98 3

99.9 .9

3 3.1971

99.9 .9

9.9

9.9

3 3 3

3.4811

W = 0.06235 D2.5196

W = 0.08483 D2.4680

W = 0.00091 D

99.9 .9

3

W = 0.00644 D2.3782

W = 0.00229 D

9.9

9.9 3

3

9.9

5.0

98

3

5.0

98

W = 0.01497 D2.9353

W = 0.02005 D2.9542

W = 0.0195 D3.0285

W = 0.067 D2.859

W = 0.000039 D

W = 0.058 D2.58

W = 0.06 D2.61

W = 0.058 D2.62

W = 0.013 D

95.0

nda

nda

nda

8.9

8.9

8.9

8.9

8.9

8.9

70.5

10.0

10.0

10.0

Max

20.0

20.0

20.0

20.0

20.0

20.0

20.0

20.0

8.3

95.0

95.0

95.0

PY

nda

15

W = 0.0726 D2.378

15

CO

2.8

45

W = 0.059 D2.390

W = 0.02754 D3.22

TTB

W = 0.00794 D

AGB+Rtslt

3.25

W = 0.00741 D2.23

W = 0.02042 D 2.8

2.8

45

2.8

45

W = 0.00275 D4.01

45

5.2

35

W = 0.02138 D2.1

lnW = -3.566 + 2.122 lnD + 0.77 lnH

W = 1.6224 D1.1012

1.0

1.0

3

1.551

3

1.0

3

W = 0.0263 D2.2834 W = 0.1146 D

Min

DBH (cm)

∑ Sample Trees

Model Form

Rt-slt

Tw

Le

Br

St

St

SUMUT

KALBAR

Rt

Le

Br+Tw

Component

JATENG

JATENG

JATENG

Site

FIN


Pinus merkusii

Pinus merkusii

Pinus merkusii

Pinus merkusii

Species

7.9

7.9

7.9

7.9

7.9

7.9

7.9

7.9

nda

5.0

5.0

5.0

5.0

nda

nda

nda

1.6

1.6

1.6

1.6

1.6

1.6

4

nda

nda

nda

Min

13.7

13.7

13.7

13.7

13.7

13.7

13.7

13.7

nda

40.0

40.0

40.0

40.0

nda

nda

nda

10.5

10.5

10.5

10.5

10.5

10.5

44.8

nda

nda

nda

Max

H (m)

0.99

0.99

0.98

0.99

0.99

0.99

0.99

0.99

0.99

0.61

0.96

0.98

0.98

0.96

0.97

0.98

0.99

0.99

0.94

0.97

0.99

0.98

0.92

0.95

0.96

0.98

R2

nda

nda

nda

nda

nda

nda

nda

nda

0.11

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

Se

26

26

26

26

26

26

26

26

21

19

19

19

19

25

25

25

51

51

51

51

51

51

72

10

10

10

Ref

e

e

e

e

e

e

e

e

e

b

b

b

b

b

e

e

e

Note

82


PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

393

394

395

396

397

398

399

400

401

402

403

404

405

406

407

408

409

410

Ecosystem Type

392

No

Shorea leprosula (all spacing)


Shorea leprosula (semua jarak tanam)

Shorea leprosula (3x3m)+pinus












Shorea leprosula (2x2m)+ pinus TTB

JABAR

JABAR

JABAR

JABAR

JABAR

JABAR

JABAR

JABAR

JABAR

JABAR

JABAR

JABAR

JABAR

JABAR

St

AGB

TTB

Rt

Le

Br+Tw

St

AGB

TTB

Rt

Le

W = 0.00995 D2.6703

W = 0.04432 D2.4987

Model Form

9.9 9.9

3 3

W = 0.02637 D2.7020

W = 0.03185 D2.7808

W = 0.03766 D2.7875

W = 0.00374 D3.0287

W = 0.00073 D3.3432

W = 0.00016 D4.3287

W = 0.00462 D3.3528

W = 0.00379 D3.6137

9.9

9.9

3

9.9

9.9

18

18

99.9 .9

20.0

20.0

20.0

20.0

20.0

20.0

20.0

20.0

20.0

20.0

20.0

20.0

20.0

20.0

20.0

20.0

20.0

20.0

20.0

Max

PY 9.9

9.9

9.9

9.9

9.9

18

3

3

3

3

3

W = 0.00612 D3.5056

9.9

9.9

CO 3

2.8375

W = 0.00549 D

3

W = 0.00141 D2.9344

W = 0.00129 D

3

9.9

3

3.3695

9.9

3

9.9

9.9

3

3

9.9

Min

DBH (cm)

3

∑ Sample Trees

W = 0.01066 D2.2063

W = 0.05933 D2.5433

W = 0.06261 D2.5930

W = 0.02603 D2.2143

W = 0.01007 D2.2883

AL

Br+Tw

St

AGB

Rt

JABAR

JABAR

Le

Br+Tw

JABAR

JABAR

St

Component

JABAR

Site

FIN




Species

7.9

7.9

7.9

7.9

7.9

7.9

7.9

7.9

7.9

7.9

7.9

7.9

7.9

7.9

7.9

7.9

7.9

7.9

7.9

Min

13.7

13.7

13.7

13.7

13.7

13.7

13.7

13.7

13.7

13.7

13.7

13.7

13.7

13.7

13.7

13.7

13.7

13.7

13.7

Max

H (m)

0.98

0.98

0.98

0.99

0.89

0.94

0.99

0.98

0.99

0.96

0.99

0.99

0.98

0.99

0.99

0.99

0.94

0.99

0.99

R2

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

Se

26

26

26

26

26

26

26

26

26

26

26

26

26

26

26

26

26

26

26

Ref

e

e

e

e

e

e

e

e

e

e

e

e

e

e

e

e

Note


83

Ecosystem Type

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

E/A

E/A

E/A

E/A

E/A

E/A

No

411

412

413

414

415

416

417

418

419

420

421

422

423

424

425

426

427

428

429

430

431

432

433

434

435

436

437

Musa sp.

Hevea brasiliensis

Gigantochloa sp.

Elaeis guineensis

Elaeis guineensis

Coffea sp.

Tectona grandis

Tectona grandis

Tectona grandis

Tectona grandis

Tectona grandis

Tectona grandis

Tectona grandis

Tectona grandis

Tectona grandis

Tectona grandis

Tectona grandis

Tectona grandis






JATIM

Banten

JATIM

SUMUT

SUMUT

JATIM

JATIM

JATIM

JATIM

JATENG

JATENG

JATENG

JATENG

JATENG

JATENG

JABAR

JABAR

JABAR

JABAR

JABAR

AGB

TTB

AGB

AGB

AGB

AGB

St

Br+Tw

Le

Rt

Stp

Le

Tw

Br

W = 0.0058 D2.4762

W = 0.00338 D3.0852

Model Form

CO 4.8

W = 0.030 D2.13

W = 419 - 16.9D + 0.322D2

W = 0.131 D

2.278

W = 0.00238 D2.3385 H0.9411

W = 0.0002 D3.49

W = 0.2822 D

2.0636

W = 0.0287 (D2H)0.959

W = 0.0058 (D2H)1.038

W = 0.0660 DB 1, 752

W = 108 D1.7939

11.0 .0

30

7.0

3.0 26.1

nda nda

nda

11

nnda da

nda

34

nda

31

27.0

36.8

7.0

nda

nda

10.0

nda

nda

nda

74.8

74.8

74.8

74.8

74.8

nda

13.5

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

PY nda

9

nda

6.7

24

17

6.7

6.7

W = 503.38 D1.8476

24

24

1.0364

W = 19.775 D

6.7

24

6.7

W = 285.421 D2.261

24

nda

4.6

4.6

4.6

8.5

8.5

8.5

8.5

8.5

8.5

7.9

7.9

7.9

nda

26.2

26.2

26.2

36.9

36.9

36.9

36.9

36.9

36.9

20.0

20.0

20.0

Min

74.8

6.7

24

W = 1485.4 D2.8238

W = 5788 D

4.8

32

2.3375

4.8

9

32

14.3

14.3

14.3

14.3

14.3

14.3

9.9

9.9

9.9

Max

DBH (cm) Min

30

30

30

30

30

30

18

18

18

∑ Sample Trees

W = 0.093 D2.462

W = 0.054 D2.579

W = 0.006 D

2.702

logW = -1.65 + 1.96 logD

logW = -1.86 + 1.93 logD

logW = -2.57 + 2.42 logD

logW = -3.23 + 3.46 logD

logW = -1.36 + 2.61 logD

logW = -1.32 + 2.65 logD

W = 0.0053 D 2.8516

AL

St-stp

TTB

AGB

Rt

Stp

Le

Tw

Br

JABAR

JABAR

St-stp

AGB

Rt

Le

Br+Tw

Component

JABAR

JABAR

JABAR

JABAR

JABAR

Site

FIN





Species

nda

17.6

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

19.6

19.6

19.6

25.8

25.8

25.8

25.8

25.8

25.8

13.7

13.7

13.7

Max

H (m)

0.99

0.75

0.95

0.99

Nda

0.95

0.99

0.98

0.99

0.79

0.85

0.63

0.86

0.93

0.95

0.97

0.98

0.89

0.64

0.69

0.64

0.83

0.95

0.96

0.95

0.91

0.93

R2

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

0.15

0.13

0.18

0.16

0.06

0.06

nda

nda

nda

Se

9

13

53

42

79

9

54

54

54

24

24

24

24

24

24

67

67

67

1

1

1

1

1

1

26

26

26

Ref

Note

Notes for Appendix 1 Ecosystem Type:

Component:

Model Form:

HF

: Heath forest

Rt

: Root

D

: Diameter at breast height (cm)

DLF

: Dry land forest

Rt-slt

: Stilt Root

Db

: Diameter at the stem base (cm)

DLFs : Secondary dry land forest

Rt-(D < 0.5 cm) : Root with diameter < 0.5 cm H

: Tree height (m)

MF

: Mangrove forest

Rt-(D > 0.5 cm) : Root with diameter > 0.5 cm Ws

CF CF PSF PSF PSFs

: Community forest :: Community forest Peat land forest :: Peat land forest Secondary peat land forest

AGB AGB Fl Fl Fr

: Aboveground Biomass :: Aboveground Biomass Flower :: Flower Fruit

: Oven-dry weight of stem biomass (kg) (kg) biomass

PSFs PF PF E/A

:: Secondary peat land forest Plantation forest :: Plantation forest Estate/Agriculture

Fr TTB TTB St

:: Fruit Total tree biomass :: Total Stemtree biomass

E/A

: Estate/Agriculture

St St-fb St-fb St-stp

:: Stem Stem up to the first branch :: Stem to the first branch Stem up excluiding stump

St-smp Br Br Le

:: Stem Branchexcluiding stump :: Branch Leaf :: Leaf Bark

Tw Stp Stp

PY

:: Oven-dry Oven-dry weight weight of of biomass biomass (kg) (kg) 3 :: Wood density (kg/m Wood density (kg/m3))

CO

Le Brk Brk Tw

W W ρ ρ

:: Bark Twig :: Twig Stump : Stump

AL

Note: Note: a : Reccommended for estimating biomass of the trees with small diameters (< 10 cm) ab :: Reccommended for estimating biomassforofsmall the trees with class) small diameters (< 10 cm) Unrealistic estimates (negative values diameter bc :: Unrealistic estimates (negative values for small diameter class) Overestimate :: Overestimate Underestimate :: Underestimate The model is not advisable to use (the number of sample trees used is insufficient)

enda nda

:: The model is not advisable to use (the number of sample trees used is insufficient) no data available : no data available

FIN

cd de

84


Appendix 2.

No.

List of tree species included in the development of biomass allometric models for mixed-species

Ecosystem Type

Site

Species

Ref

HF

KALBAR

Combretocarpus rotundifolius., Dactylocadus stenostachys, Diospyros sp., Dryobalanops sp., Fragraea fragrans, Knema sp., Mesua hexapetalum, Shorea sp., Syzygium durifolium, Vatica cinerea, Xanthophyllum sp.

49

2

HF

KALTENG

Agathis bornensis, Calophyllum pulcherrimum, Calophyllum sp., sp., Canarium sp.,., Cotylelobium lanceolatum, Engeihardia serliata, Eugenia cf. klosii, Garcinia rostrata, Hopea griffithii, Palaquium leiocarpum, Sageraea elliptica, Shorea platycarpa, Shorea rugosa, Shorea teysmanniana, Sindora leiocarpa, Syzygium cf. klossii, Ternstroemia aneura, Tristania obovata, Vatica umbonata

45

3

DLF

JABAR

Alstonia scolaris, Antidesma montanum, Bridelia monoeca, Gliricidia sepium, Glochidion seiceum, Glumea balsamifera, Melastoma malabathricum, Oraxylum indicum, Piper aduneum, Vitex piñata, Wrightia calycina

68

4

DLF

KALTENG

Anthocephalus sinensis, Elaterospermum tapos, Macaranga hypoleuca, Quercus lineata, Shorea fallax, Shorea desiphylla, Shorea johorensis, Shorea laevifolia, Shorea leprosula, Shorea lineata, Shorea macrophylla, Shorea parvifolia, Shorea platyclados, Shorea sp.

8

5

DLF

KALTIM

Peronema canescens, Schima wallichii, Shorea sp., Vernonia arborea, Vitex pinnata

38

6

DLF

KALTIM

Allantospermum sp., Alseodaphne sp., Archidendron sp., Baccaurea sp., sp., Calophyllum sp., Canarium sp., Dacryodes sp., Dialium sp., Bouea sp., Diospyrus sp., Drypetes sp., Dyophyllum sp., Garcinia sp., Heretera sp., Knema sp., Koompassia sp., Lithocarpus sp., Lophopetalum sp., Madhuca sp., Mangifera sp., Mezzetia sp., Parishia sp., Scaphium sp., Shorea sp., sp., Stemonurus sp., Syzygium sp., Syzygium sp., Vatica sp., Xanthophyllum sp.

61

Aporosa elmeri, Aporosa sphaedophora, Arthocarpus anisophyllus, Bacacaurea sp., Baccaurea deflexa, Baccaurea kunstleri, Baccaurea pendula, Baccaurea sp., Barringtonia macrostachy, Beilschmiedia sp., Dacryodes rugosa, Dialium indum, Dialium platycephalum, Dialium sp., Dillenia excelsa, Dillenia excemia, Dipterocarpus crinitus, Dryobalanops sp., Drypetes sp., Elaeocarpus sp., Eugenia cuprea, Eugenia sp., Girroniera nervosa, Hopea mangerawan, Horsfieldia grandis, Litsea noronhae, Litsea sp., Mallotus echinatus, Milletia sericea, Myristica sp., Neoscortechinia kingii, Ochanostachys amentacea, Ochanostachys sp., Ostodes macrophylla, Oxymitra grandiflora, Polaquem dasyphyllum, Polyalthia glauca, Polyalthia rumphii, Pometia tomentosa, Santiria operculata, Santiria tomentosa, Shorea laevis, Shorea leprosula, Shorea ovalis, Sindora sp., Sterculia rubiginosa, Strombosia rotundifolia, Strombosia sp., Xanthophyllum heteropleurum

11

FIN

AL

CO

PY

1

7

DLF

KALTIM


85

No.

Ecosystem Type

Site

Species

Ref

DLF

KALTIM

Dipterocarpus convertus, Dipterocarpus crinitus, Dipterocarpus grandiflorus, Dipterocarpus humeratus, Dipterocarpus pacyphyllus, Dipterocarpus palmbanicus, Hopea cernua, Hopea dryobalanoides, Hopea mengarawan, Palaquium gutta, Palaquium rostratum, Palaquium sp., Shorea agamii, Shorea atrinervosa, Shorea macroptera, Shorea parvifolia, Shorea parvistipulata, Shorea retusa, Shorea smithiana, Shorea superba, Shorea sp.

78

9

DLFs

Jambi

Dactylocladus stenostachys, Eugenia sp,, Ginetroshesia soliaris, Macaranga maingayi, Mallotus paniculatus, Mastixia pentandra, Pentaspadon motleyi, Shorea sp.,., Strombosia javanica, Styrac benzoin, Jirak, Maribungan, Nilao, Patang buah

37

10

DLFs

Jambi

Dactylocladus stenostachys, Eugenia sp.,, Ginetroshesia soliaris, Macaranga maingayi, Mallotus paniculatus, Mastixia pentandra, Pentaspadon motleyi, Shorea sp.,., Strombosia javanica, Styrac benzoin, Jirak, Maribungan, Nilao, Patang buah

5

11

DLFs

KALTIM

Anthocepalus chinensis, Arthocarpus elasticus, Arthocarpus sp., Canarium commune, Cratoxylon sumatranume, Dimocarpus longan, Dyera costulata, ., Ficus variegata, Gmelina arborea, Koompassia excelsa, Eugenia sp., Macaranga gigantea, Macaranga triloba, Macaranga sp., Nauclea subdita, Nephelium lappaceum, Octomeles sumatrana, Paraserianthes falcataria, Piper aduncum, Pterospermum celebicum, Solenospermum sp., Garun, Huboq, Kanhop, Kayu lari-lari, Kayu tatak, Kelihidaq, Kelima, Lingau, Tudaq

57

12

DLFs

KALTIM

Aglaia sp sp., ., Anglauria malfinas, Anthocepalus chinensis, Artocarpus anisophyllus, Baccaurea sp sp., Calophyllum inophyllum, Campnosperma macrophylla, Canarium commune, Cratoxylon sumtaranume, Diallium sp., sp ., Dimocarpus longan, Diospyros celebica, Dipterocarpus gracilis, Dracontomelon mangiferum, Dryobalanops lanceolata, Durio oxleyanus, Ellmeleria dandells, Endospermum moluccanum, Eugenia sp., Eusyderoxylon zwageri, Ficus variegeta, Hopea ferrugenia, Knema latifolia, Koompassia excelsa, Litsea firma, Macaranga triloba, Myristica sp.,., Nephelium lappaceum, Octomeles sumatrana, Palaquium sp., Pentae sp sp., Piper anducum, Pterospermum celebicum, Quercus sp., Shorea acuminatissima, Shorea assamica, Shorea bracteolata, Shorea parvifolia, Shorea pinanga, Shorea seminis, Sindora wallichii, Vatica rassak, Beluhboq, Buan, Hubon, Jemelek, Jeruk Hutan, Kanhon, Kayu lapar, Kayu lari-lari, Kayu sabun, Kayu Tatak, Kopi-kopian, Langalung, Pangan, Porang, Sembukau, Tamha, Tanam Haloq, Taringdung

33

Actinodaphne glabra, Aglaia sp., Alseodaphne elmeri, Artocarpus lanceifolius, Artocarpus rigidus, Clerodendrum adenophysum, Cratoxylum sumatranum, Dillenia reticulata, Dimocarpus longan, Ficus grassularoides, Ficus obscura, Ficus sp., Fordia splendidissima, Glochidion sp., Litsea cf. angulata, Litsea cf. angulata, Litsea sp., Macaranga gigantea, Macaranga pearsonii, Mallotus paniculatus, Melastoma malabathricum, Melicope glabra, Piper aduncum, Semecarpus glaucus, Symplocos fasciculata, Syzygium sp., Trema tomentosa, Vernonia arborea

2

FIN

AL

CO

PY

8

13

86

DLFs

KALTIM

List of tree species included in the development of biomass allometric models for mixed-species

Species

Ref

DLFs

KALTIM

Artocarpus sp., Blumea sp., Bridelia sp., Cratoxylon arborescens, Dysoxlon sp., Eodia sp., Ficus spp, Fordia sp., Geunsia pentandra, Helisia sp., Leucosyke capitelata, Macaranga spp., Mallotus sp., Melastoma malabathricum, Nauclea sp., Piper aduncum, Poikilospermum sp., Pterospermum javanicum, Trema orientalis, Trema tomentosa, Vernonia arborea

22

15

DLFs (20 yrs)

Jambi

Endospermum diadenum, Gardenia anysophylla, Macaranga gigantea

73

16

DLFs (7 yrs)

Jambi

Endospermum diadenum, Hevea brasiliensis, Macaranga gigantea

73

17

DLFs (70 yrs)

Jambi

Arthocarpus nitidus, Gironniera hirta, Kompassia malaccensis, Litsea sp., Macaranga sp., Shorea leprosula, Shorea sp.

73

18

CF

JATENG & DIY

Acacia auriculiformis, Dalbergia latifolia, Paraserianthes falcataria, Swietenia mahagony, Tectona grandis

12

19

PSF

KALTENG

sp., Callophylum Aglaia rubiginosa, Blumeodendron tokbrai, Caladiifolia sp., hosei, Campnosperma corieaceum, Cantleya corniculata, Dactylocladus stenostachys, Diospyros cf. evena, Garcinia celebica, Garcinia sp., Litsea sp.,, Memecylon septicatum, Myristica iners, Nephelium maingayi, sp., Shorea uliginosa, Syzygium sp., sp Tectratomia tretrandra, Palaquium sp., sp., Syzygium sp. Tetrameristra glabra, Tristaniophsis sp.,

17

20

PSFs

SUMSEL

Antidesma montanum, Blumeodendron tokbrai, Cantleya corrniculata, Crytocarya crassinervia, Dacryodes bankense, Elaeocarpus palembanicus, Endospermum malaccensis, Eugenia sp., Horsfieldia crassifolia, Macaranga mainganyi, Palaquium burkii, Parastemon urophyllus, Paratocarpus venenosus, Pithecellobium lobatum, Shorea dasyphylla, bebangun

77

21

PSFs

Alseodaphne insignis, Crytocarya crassinervia, Dacryodes cf. rostrata, Dyera lowii, Elaeocarpus griffthii, Gonystylus bancanus, Horsfieldia sp., Lithocarpus sundaicus, Litsea noronhae, Palaquium ridleyi, Polyalthia sumatrana, Macaranga maingayi, Mezzetia parviflora, Shorea dasyphylla, Shorea uliginosa, Syzygium bankense, Syzygium sp.1, Syzygium sp.2, Tetramerista glabra

46

PY

14

Site

CO

Ecosystem Type

AL

No.

FIN

SUMSEL


87

AL

FIN PY

CO

Appendix 3.

References-Appendices 1 and 2

1.

Adinugroho, W.C. dan Sidiyasa, K. 2006. Model pendugaan biomasa pohon mahoni (Swietenia macrophylla King) di atas permukaan tanah. Jurnal Penelitian Hutan dan Konservasi Alam 3(1): 103– 117.

10. Basuki, T.M., Adi, R.N., dan Sukresno. 2004. Informasi teknis stok karbon organik dalam tegakan Pinus merkusii, Agathis loranthifolia dan tanah. Prosiding Ekspose BP2TPDAS-IBB Surakarta, Kebumen, 3 Agustus 2004. Pp. 84–94.

2.

Adinugroho, W.C. 2009. Persamaan alometrik biomassa dan faktor ekspansi biomassa vegetasi hutan sekunder bekas kebakaran di PT. Inhutani I Batu Ampar, Kalimantan Timur. Info Hutan 6 (2): 125–132.

3.

Agus, C. 2002. Production and consumption of carbon by fast growing species of Gmelina arborea Roxb. in tropical plantation forest. In: Sabarnurdin, M.S., Hardiwinoto, S., Rimbawanto, A. and Okimori, Y. (Eds.). Proceedings of the Seminar on Dipterocarp Reforestation to Restore Environment through Carbon Sequestration. Yogyakarta, 26-27 September 2001. Pp. 187–196.

11. Basuki, T.M., van Laake, P.E., Skidmore, A.K., and Hussin, Y.A. 2009. Allometric equations for estimating the above-ground biomass in tropical lowland Dipterocarp forests. Forest Ecology and Management 257: 1684–1694.

PY

CO

Akbar, A. dan Priyanto, E. 2011. Perhitungan karbon untuk perbaikan faktor emisi dan serapan GRK kehutanan pada hutan alam gambut. Laporan Hasil Penelitian Pusat Penelitian Sosial Ekonomi dan Kebijakan Kehutanan, Bogor.

5.

Ambagau, Y. 1999. Pendugaan jumlah total biomassa tegakan hutan sekunder pada areal bekas lahan bakar (slash–and–burn)) dan pengaruhnya terhadap pH dan kerapatan isi tanah di Sepunggur, Jambi. Skripsi Departemen Manajemen Hutan, Fakultas Kehutanan, Institut Pertanian Bogor, Bogor. Aminudin, S. 2008. Kajian potensi cadangan karbon pada pengusahaan hutan rakyat: (studi kasus Hutan Rakyat Desa Dengok, Kecamatan Playen, Kabupaten Gunung Kidul). Thesis Sekolah Pascasarjana, Institut Pertanian Bogor, Bogor.

FIN 7.

13. Cesylia, L. 2009. Cadangan karbon pada (Hevea brasiliensis) brasiliensis pertanaman karet (Hevea di Perkebunan Karet Bojong Datar PTP Nusantara VIII Kabupaten Pandeglang Banten. Thesis Sekolah Pascasarjana, Institut Pertanian Bogor, Bogor. 14. Darussalam, D. 2011. Pendugaan potensi serapan karbon pada tegakan Pinus di KPH Cianjur Perum Perhutani Unit III Jawa Barat dan Banten. Skripsi Departemen Manajemen Hutan, Fakultas Kehutanan, Institut Pertanian Bogor, Bogor.

AL

4.

6.

12. BPKH Wilayah XI Jawa-Madura & MFP II. 2009. Alometrik berbagai jenis pohon untuk menaksir kandungan biomassa dan karbon di Hutan Rakyat. Laporan BPKH Wilayah XI Jawa-Madura & MFP II, Yogyakarta.

Amira, S. 2008. Pendugaan biomassa jenis Rhizophora apiculata Bl. di hutan mangrove, Batu Ampar, Kabupaten Kubu Raya, Kalimantan Barat. Skripsi Departemen Konservasi dan Sumberdaya Hutan, Fakultas Kehutanan, Institut Pertanian Bogor, Bogor.

8.

Anggraeni, B.W. 2011. Model pendugaan cadangan biomassa dan karbon hutan tropis basah di PT. Sari Bumi Kusuma, Kalimantan Tengah. Thesis Program Pascasarjana Faskultas Kehutanan, Universitas Gadjah Mada, Yogyakarta.

9.

Arifin, J. 2001. Estimasi cadangan C pada berbagai sistem penggunaan lahan di Kecamatan Ngantang, Malang. Skripsi-S1. Universitas Brawijaya, Malang.

15. Dewi, M. 2011. Model persamaan alometrik massa karbon akar dan root to shoot ratio biomassa dan massa karbon pohon mangium (Acacia mangium Wild). Skripsi Departemen Manajemen Hutan, Fakultas Kehutanan, Institut Pertanian Bogor, Bogor.

16. Dharmawan, I.W.S. dan Siregar, C.A. 2008. Karbon tanah dan pendugaan karbon tegakan Avicenia marina (Forsk.) Vierh. di Ciasem, Purwakarta. Jurnal Penelitian Hutan dan Konservasi Alam 5 (4): 317–328. 17. Dharmawan, I.W.S., Darusman, T., Naito, R., Arifanti, V.B., Lugina, M. and Hartoyo, M.E. 2012. ITTO Project Technical Report PD 73/89 (F, M, I) Phase II: Development and testing of a carbon MRV methodology and monitoring plan: allometric equation development, forest biomass mapping (aboveground carbon stock), water level and peat anaysis (belowground carbon stock). Center for Research and Development of Climate Change and Policy-FORDA & Starling Resources. Bogor.


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18. Djumakking, W. 2003. Potensi Acacia mangium dalam mengikat karbon (Studi Kasus di RPH Maribaya, BKPH Parung Panjang Jawa Barat). Skripsi Departemen Manajemen Hutan, Fakultas Kehutanan, Institut Pertanian Bogor, Bogor.

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80. Yulyana, R. 2005. Potensi kandungan karbon pada Hevea brasiliensis) brasiliensis) yang disadap pertamanan karet (Hevea (studi kasus di perkebunan inti rakyat kecamatan Pondok Kelapa Kabupaten Bengkulu Utara). Thesis Sekolah Pascasarjana, Institut Pertanian Bogor, Bogor.

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93

AL

FIN PY

CO


95

DLF

DLF

DLF

DLF

DLF

DLF

DLF

DLF

DLF

DLF

DLF

7

8

9

10

11

12

13

14

15

16

17

DLF

4

DLF

DLF

3

6

DLF

2

DLF

DLF

1

5

Ecosystem Type

No

FIN

Tree Species

SUMSEL SUMUT

Dipterocarpaceae (Non Shorea)








Dipterocarpaceae

KALSEL

KALSEL

KALSEL

KALSEL

KALSEL

KALBAR

SULUT

Jambi

SUMBAR


Dipterocarpaceae

Maluku


Jambi

Dipterocarpaceae (Non Shorea) Lampung

Bengkulu



SULSEL

Mixed

PABAR

Location

AL 129

V10 = 0.0000476 D2.409 H0.507

Vbr = 0.000073 D (2.652/D)

2.647

nda

nda

20->100

129

V10 = 0.000106 D

20->100

129 2.619

20->100

Vtb = 0.000141 D2.514

+

129

Vcb = 0.000417 D Vtb = 0.0000503 D2.24 H0.65

20->100

nda

23-139

nda

2.21

268

V = 0.000209 D

nda

nda

nda

2.40

169

nda

nda

nda

nda

nda

nda

14-39

14-39 14-39

14-39 14-39

14-39

13.25-25.4

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

Hm (m)

PY

CO

nda

nda

50

424

nda

nda

nda

nda 59

nda

DBH (cm)

nda

Sample ∑ Trees

V = 0.000174 D2.429

V = 0.000148 D2.510

V = 0.0000948 D2.577

V = 0.000668 D2.086

Vtb = 0.000213 D2.461

V = 0.000150 D2.458

V = 0.000174 D2.430

V = 0.000271 D2.299

V = 0.000128 D2.452

V = 0.0021 D1.644

Model Form

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

H (m)

nda

0.17

nda 0.98

0.16

nda

0.15

0.12

nda nda

nda

nda

nda

0.17

0.12

nda

0.10

0.21

nda

0.27

0.17

nda

Se

0.98

nda

nda

0.96

nda

nda

0.99

0.94

nda

0.93

0.97

0.85

R2

Tree volume allometric models that have been developed according to tree species and ecosystem type in Indonesia

Callopyllum sp.

Appendix 4.

99

83

83

83

83

48

52

3

21

50

49

16

15

53

13

19

2

Ref

Note

96


DLF

DLF

DLF

DLF

DLF

DLF

DLF

31

32

33

34

35

36

37

DLF

26

DLF

DLF

25

30

DLF

24

DLF

DLF

23

29

DLF

22

DLF

DLF

21

DLF

DLF

20

27

DLF

19

28

DLF

Ecosystem Type

18

No

Duabanga moluccana

Duabanga moluccana

Dryobalanops spp.

Dryobalanops spp.

Dryobalanops spp.

Dryobalanops spp.





Dipterocarpus spp.

Dipterocarpus spp.

Dipterocarpus spp.





NTB

NTB

KALTIM

KALTIM

KALTENG

KALBAR

KALBAR

KALBAR

KALBAR

KALBAR

nda

KALTENG

SUMUT

KALTIM

KALTIM

KALTIM

KALTIM

KALSEL

AL

V = 0.000163 D

12-140

nda

105

V10 = 0.000104 (D+1)2.21 H0.504

24-152

50 2.3

V = 0.000355 D

21-141

50

V = 0.000269 D2.35

V = 0.0103 D1.190 H0.883

80.2-150.6

80.2-150.6

60

V = 0.000252 D

60

Nda

nda

2.319

V = 0.000269 D

22.5-118

268

20-94

2.36

Vcb = 0.000661 D2.1

105

Vtb = 0.0000544 D2.274 H0.574 20-94

20-94

nda

125

105

nda

nda

V10 = 0.000174 D2.492

nda

nda

20-94

12-140

130

15-39

nda

nda

nda

15-37

15-37

nda

nda

nda

nda

nda

Hm (m)

nda

nda

19-30 19-30

19-30 19-30

nda

13.34-25.3

15-39

15-39

15-39

PY

CO

130

nda

nda

nda

nda nda

nda

nda

DBH (cm)

nda

nda

Sample ∑ Trees

105

Vtb = 0.0000893 D2.619

2.419

V = 0.000148 D 2.51

0.558

H

V = (0.828 D )/10000 2.51

Vtb = 0.000108 D 2.145

V = 0.000155 D2.495

V = (-0.0101 + (-0.0365 (D*H)) + (0.531 (D2H)))/10000

V = (0.117 + (-1.905 D) + (13.914 D2))/1000000

Vm = 0.000261 D

V = 0.000103 D2.626

KALSEL 2.254

V = 0.0000478 D2.78 + (3.191/D)

Model Form

KALSEL

Location

FIN




Tree Species

23-37

18-26

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

H (m)

0.99

0.99

nda

nda

nda

0.97

0.97

0.98

0.98

0.97

0.98

nda

0.96

nda

nda

nda

nda

0.98

0.98

0.98

R2

nda

nda

nda

nda

nda

nda

0.17

0.15

0.16

0.17

nda

nda

nda

0.14

0.17

nda

nda

nda

nda

nda

Se

63

63

111

111

107

48

73

73

73

73

109

107

21

112

112

25

25

99

99

99

Ref

D> 80cm

Note


97

DLF

DLF

DLF

DLF

DLF

DLF

DLF

DLF

DLF

DLF

DLF

DLF

47

48

49

50

51

52

53

54

55

56

57

58

DLF

43

DLF

DLF

42

46

DLF

41

DLF

DLF

40

45

DLF

39

DLF

DLF

38

44

Ecosystem Type

No

PABAR PABAR nda

Commercial timbers

Commercial timbers

Commercial timbers

NTB

Other species (Non Duabanga dan Toona) PABAR

Lampung

Commercial timbers

SUMUT

Other species

SULUT

SULTRA

SULTENG

Maluku

Bengkulu

KALTIM

KALTIM

SULSEL

AL

Vtb = 0.0000766 D2.247 H0.569

SUMSEL

8-33 8-33

262 262

nda

8-33

nda

nda

nda

nda

nda nda nda 124

2.2690

2.373

nda nda nda nda

nda nda nda 2932

2.139 1.996 2.564

V = 0.000101 D

V = 0.000584 D

V = 0.000309 D

V = 0.0000129 D3.229

nda

204

Vtb = 0.0000515 D2.587

V = 0.0000998 D2.506

V = 0.000225 D

V = 0.000297 D

2.523

V = 0.00010249 D

V = 0.000124 D

nda

nda

55

2.491

Vtb = 0.000168 D

nda

nda

2.507

V = 0.000168 D2.420

102

nda

nda

nda

nda

nda

nda

nnda da

nda nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

4-17

4-17

4-17

4-17

nda

nda

Hm (m)

PY

CO

nda

262

8-33

nda

nda

262

nda

DBH (cm)

68

Sample ∑ Trees

nda

V = (-0.0075 + 0.528(D2H))/10000

V = (0.183 + (-2.536 D) + (14.738 D2))/10000

V = 0.000143 D2.481

2.121

Vtb = 0.0000750 D H0.691

V7 = 0.000101 D 2.619

2.573

Vtb = 0.000105 D

V = 0.000295 D 2.2

Vtb = 0.000107 D2.554

Model Form

SUMSEL

SUMSEL

Other species (Non Dipterocarpaceae)

Other species

Other species

Other species

Other species

Other species

Hopea bracteata

Hopea bracteata

Heritiera spp.




SUMSEL

Jambi

NTB

Location

FIN


Durio zibethinus

Duabanga sp.

Tree Species

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

H (m)

0.97

0.82

0.93

0.62

0.95

0.94

0.93

nda

0.97

nda

0.99

0.95

nda

nda

0.95

nda

nda

nda

nda

0.99

0.99

R2

nda

nda

nda

nda

0.22

0.16

0.19

nda

0.17

nda

0.09

0.17

nda

nda

0.19

0.11

0.08

0.16

0.16

nda

0.18

Se

109

2

2

2

17

15

21

52

20

51

16

13

25

25

19

32

32

32

32

35

17

Ref

Note

98


Ecosystem Type

DLF

DLF

DLF

DLF

DLF

DLF

DLF

DLF

DLF

DLF

DLF

DLF

DLF

DLF

DLF

DLF

DLF

DLF

No

59

60

61

62

63

64

65

66

67

68

69

70

71

72

73

74

75

76

Shorea leprosula

Shorea leprosula

Shorea leprosula

Shorea leprosula

Shorea hopeifolia

Shorea hopeifolia

Shorea bracteolata

Shorea bracteolata

KALSEL

KALSEL

KALSEL

KALSEL

KALTIM

KALTIM

nda

KALTIM

KALTIM

nda

Quercus, Castanopsis, Engelbardtia

Shorea bracteolata

KALTIM

SUMSEL )/1000 nda

nda nda nda nda nda nda

V = 0.000679 -5.53 D + 18.48 D2 V = (0.083 + (-0.165 DH) + (0.572 D2H))/10000 Vcb = 0.73 + 0.000045 D2H V = 0.992 + 0.000034 D2H V = 0.22 + 0.0000185 D2H Vcb = -0.223 + 0.0000611 D2H

nda

nda

nda

nda

nda

nda

nda

59

V = 0.00017 D2.4

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

Hm (m)

nda

nnda da

nnda da

nda

nda

nda

nda

PY

CO

nda

nda

nda

nda

nda nda

nda

nda

nda

nda

nda

730 nda

nda

DBH (cm)

1175

Sample ∑ Trees

nda

V = 0.00068 - 0.86 DH + 0.74 D2H

V = 0.00101 + -6.356 D + 18.97 D2

V = 0.0000297 D2 H0.975

V = -0.379 + 0.0056 D + 0.0012 D2

V = (0.648 D

V = 0.000000777 D3.627

Jambi 2.373

V = 0.000164 D2.433

V = 0.000289 D2.291

AL

V = 0.0000777 D2.627

V = 0.0000963 D2.541

V = 0.0000995 D2.359

Model Form

SUMSEL

SUMBAR

Parashorea spp.

Non Dipterocarpaceae




Jambi

nda

nda

Location

FIN


Other Meranti group

Other commercial species

Tree Species

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

H (m)

nda

nda

nda

nda

nda

nda

0.98

nda

nda

0.98

0.97

0.93

nda

nda

nda

nda

0.97

0.97

R2

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

0.49

nda

nda

0.17

nda

0.16

nda

nda

Se

106

106

106

106

25

25

109

25

25

110

1

50

3

50

49

53

109

109

Ref

Note


99

DLF

DLF

DLF

DLF

DLF

DLF

DLF

DLF

DLF

DLF

DLF

DLF

DLF

83

84

85

86

87

88

89

90

91

92

93

94

95

DLF

80

DLF

DLF

79

82

DLF

78

DLF

DLF

77

81

Ecosystem Type

No

Jambi Jambi Jambi

Shorea parvifolia Shorea leprosula



Bengkulu Jambi Jambi Jambi Jambi Jambi KALBAR KALTENG KALTENG

Shorea spp.

Shorea spp.

Shorea spp.

Shorea spp.

Shorea spp.

Shorea spp.

Shorea spp.

Shorea spp.

SUMBAR

Shorea spp.

Shorea pauciflora

SUMBAR

Jambi

Shorea parvifolia; Shorea leprosula

Shorea pauciflora

KALTIM

KALTIM

KALSEL

AL 20-<100

nda

23-140 20->105 20->105

268 172 172

2.389 2.45

V10 = 0.000219 D

Vtb = 0.0002427 D

Vcb = 0.000372 D

20-100

134 2.25

0.376

V10 = 0.000133 D H 2.6

20-100

20-100

20-100

nda

nda

134

134

134

nda

60

nda

nda

nda nda

20-<100

20-<100

20-<100

133

133

133

13-38

13-38

13-38

13-38

nda

nda

nda

nda

Hm (m)

13-41

13-41

13.35-26

12-30 12-30

12-30 12-30

12-30

12-30

nda

nda

nda

nda

PY

CO

133

nda

nda

nda

nda

DBH (cm)

Vtb = 0.000091 D2.018 H0.751

V10 = 0.000254 D2.392

Vtb = 0.000305 D2.304

V = 0.00025 D2.35

V = 0.0000918 D2.575

2.368

V10 = 0.0000678 D H0.444

V10 = 0.000134 D2.549

V10 = 0.000119 D2.32 H0.356

Vtb = 0.000093 D2.136 H0.61

V10 = 0.00023 D2.244

Vtb = 0.00029 D2.345

V = (-0.0018 - 0.0494 DH + 0.541 D2H)/10000

V = (0.128 -2.359 D + 15.551 D2)/10000 nda

nda

V = 0.181 + 0.0000249 D2H

Sample ∑ Trees nda

Model Form

V = -0.53 + 0.0000469 D2H

FIN KALSEL

Location

Shorea leprosula

Shorea leprosula

Shorea leprosula

Shorea leprosula

Tree Species

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

H (m)

0.98

0.97

0.97

nda

nda

nda

nda

nda

0.99

0.99

nda

0.99

0.99

0.99

0.98

nda

nda

nda

nda

R2

0.17

0.17

nda

0.16

0.11

0.19

0.18

nda

0.14

0.11

nda

0.14

0.12

0.15

0.16

nda

nda

nda

nda

Se

102

102

48

88

88

88

88

53

13

84

84

101

101

101

101

25

25

106

106

Ref

Note

100


DLF

DLF

DLF

DLF

DLF

DLF

DLF

DLF

DLF

DLF

DLF

DLF

DLF

DLF

DLF

DLF

DLF

DLF

DLF

DLF

DLF

97

98

99

100

101

102

103

104

105

106

107

108

109

110

111

112

113

114

115

116

Ecosystem Type

96

No

Lampung

Maluku

Riau

Riau Riau

Shorea spp.

Shorea spp.

Shorea spp.

Shorea spp.

Shorea spp.

Riau

Shorea spp.

SULTENG SULTRA SUMBAR SUMSEL SUMSEL SUMUT Tad

Shorea spp.

Shorea spp.

Shorea spp.

Shorea spp.

Shorea spp.

Shorea spp.

Shorea spp.

Riau

Riau

Shorea spp.

Shorea spp.

Riau

Shorea spp.

Riau

Lampung

Shorea spp.

Shorea spp.

Lampung

Model Form

AL 0.6

H

29-99 nda 20-104 20-104

20-104

275 50 140 140 140

20-84

100

nda nda nda nda nda

nda nda 72 1027

)/10000

2.619

2.525

nda

nda

nda

20-84

20-84

100

100

20-84

20-104

100

140

nda

V = 0.000109 D

V = 0.000106 D

2.912

V = 0.0000951 D 2.563

2.238

V = 0.000386 D

V = (0.976 D

29-99

275

nda

nda nda

nnda da

nnda da

nda

nda

nda

18-34

18-34

18-34

18-34

14-34

14-34

14-34

14-34

nda

15.5-35

15.5-35

nda

13-41

13-41

Hm (m)

PY

CO

nda

20->105

20->105

DBH (cm)

nda

172

172

Sample ∑ Trees

nda

V = 0.00003 D2.823

V = 0.000114D2.522

0.792

H

2.159

V10 = 0.000135 D H0.496

Vtb = 0.000106 D 1.943

2.313

Vtb = 0.000507 D2.189 V10 = 0.00036 D

0.48

2.202

V10 = 0.0000672 D H0.67

2.176

V = 0.000119 D

H

2.427

V10 = 0.000229 D

V = 0.000286 D 2.336

Vtb = 0.000239 D 2.433

Vtb = 0.000942 D 2.065

Vtb = 0.000194 D 1.971

V = 0.000364 D2.546

V10 = 0.0000841 D2.229 H0.565

Vtb = 0.0000617 D2.074 H0.808

FIN KALTENG

KALTENG

Location

Shorea spp.

Shorea spp.

Shorea spp.

Tree Species

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

H (m)

0.97

0.99

0.99

nda

nda

0.97

nda

0.95

0.97

0.94

0.95

nda

nda

nda

nda

0.99

0.92

nda

0.98

0.98

0.98

R2

nda

0.16

nda

0.16

nda

0.19

nda

0.15

0.11

0.16

0.15

0.12

0.12

0.14

0.14

0.09

0.19

0.15

0.16

0.15

0.13

Se

109

21

50

50

49

20

51

67

67

67

67

7

7

7

7

16

77

77

15

102

102

Ref

Note


101

DLF

DLF

DLF

DLF

DLF

DLF

DLF

DLF

125

126

127

128

129

130

131

132

DLF

DLF

124

133

DLF

123

DLF

120

DLF

DLF

119

122

DLF

118

DLF

DLF

117

121

Ecosystem Type

No

KALSEL

KALSEL

KALSEL

Shorea parvifolia, S. pauciflora, S. johoriensis, etc



KALTIM KALTIM

Shorea parvifolia, etc


Shorea & Dipterocarpus

Shorea sumatrana Aceh

SUMBAR

SUMBAR

KALTIM


Shorea sumatrana

KALTIM

KALTENG


Shorea.& Dipterocarpus

KALTENG

Vtb = 0.0000676 D2.05 H0.793

KALSEL


Shorea.& Dipterocarpus

V10 = 0.000172 D2.478

KALBAR

Shorea parvifolia, S. uliginosa, etc

V = 0.00017 D

2.446

2.24

Vtb = 0.0000664 D

Vtb = 0.000155 D

2.466

V10 = 0.000248 D

2.235

H

0.55

H

0.23

Vtb = 0.000207 D2.256 H0.23

V10 = 0.000343 D2.347

Vtb = 0.000331 D2.332

Vcb (ub) = 0.000212 D2.407

Vcb (ob) = 0.000261 D2.378

V10 = 0.0000849 D2.224 H0.551

V10 = 0.000163 D2.508

Vtb = 0.000162 D2.486

AL

Vtb = 0.000186 D2.426

KALBAR


20-124

188

20->100 20->100

120 120

nda

20-124

188

nda

20-124

188

20-124

10->60

61

188

10->60

61

20-154

20-154

20-154

20-154

20-120

20-120

20-120

20-120

DBH (cm)

11-49

11-49

11-49

13-44

13-44

13-44

13-44

Hm (m)

nda

13-34

13-34

16-46 16-46

16-46 16-46

16-46

16-46

11->25

11->25

11-49

PY

CO

204

204

204

204

143

143

143

KALBAR

V10 = 0.0000624 D2.1980 H0.6687

FIN


143

Sample ∑ Trees

Vtb = 0.0000488 D2.098 H0.834

Model Form

KALBAR

Location


Tree Species

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

H (m)

0.95

0.99

nda

nda

nda

nda

0.97

0.99

0.99

nda

nda

nda

nda

nda

nda

nda

nda

R2

0.05

0.09

nda

0.22

0.19

0.22

0.20

nda

nda

0.19

0.14

0.23

0.22

0.22

0.22

0.16

0.15

Se

33

84

84

89

89

89

89

100

100

98

98

98

98

82

82

82

82

Ref

Note

102


Ecosystem Type

DLF

DLF

DLF

DLF

DLF

DLF

DLF

MF

MF

MF

MF

MF

MF

MF

MF

MF

MF

MF

No

134

135

136

137

138

139

140

141

142

143

144

145

146

147

148

149

150

151

KALBAR

Bruguiera spp.


KALTIM

KALTIM

Riau

Rhizophora apiculata & R. mucronata


Riau

KALBAR

KALBAR


Bruguiera spp.

Bruguiera spp.

KALBAR

KALBAR

Bruguiera spp.

Bruguiera spp.

KALBAR

Bruguiera spp.

Riau

KALTIM

2.568

1.947

Vtb = 0.0000675 D H0.714

V = 0.000124 D2.417

V5 = 0.000647 D1.727 H0.988

V = 0.000107 D2.4

V7 = 0.0000198 D2.741 H0.378

V10 = 0.0000209 D2.612 H0.473

Vtb = 0.0000709 D2.051 H0.698

V7 = 0.0000285 D2.927

V10 = 0.0000226 D2.969

Vtb = 0.000082 D

V = 0.0135 D1.61

V = 0.0367 -0.0716 DH + 0.533 D2H)/10000

V = (0.0149 -0.0737 D + 12.335 D2)/10000

V10 = 0.000116 D2.196 H0.456

SULSEL

KALTIM

Vtb = 0.0000827 D2.036 H0.725

AL

V10 = 0.000267 D2.343

Vtb = 0.000313 D2.266

Vtb = 0.00013 D2.502

Model Form

SULSEL

SULSEL

SULSEL

NTB

Location

FIN


Vatica spp.

Vatica spp.

Vatica celebencis

Vatica celebencis

Vatica celebencis

Vatica celebencis

Toona sureni

Tree Species

nda

nda

nda nda

5-39

10-57.6

7-48

7-48

7-48

455

50

80

80

80

7-48

5-24

5-24

5-24

4-3

nda

nda

11-29

11-29

11-29

11-29

nda

Hm (m)

nda

nnda da

7-30 7-30

8.5-36

5-24

5-24

5-24

PY

CO

80

7-48

7-48

80

80

10-54.1

nda

nda

20-79

50

nda

nda

200

20-79

20-79

200 200

20-79

nda

DBH (cm)

200

68

Sample ∑ Trees

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

H (m)

nda

nda

0.99

0.96

nda

nda

nda

nda

nda

nda

0.97

nda

nda

nda

nda

nda

nda

0.97

R2

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

0.15

0.14

0.17

0.18

0.22

Se

75

75

76

44

80

80

80

80

80

80

44

25

25

97

97

97

97

17

Ref

Note


103



Gonystilus sp.

Gonystilus sp.

Gonystylus bancanus

Gonystylus bancanus

Gonystylus bancanus

Gonystylus bancanus

Gonystylus bancanus

Gonystylus bancanus

PSF

PSF

PSF

PSF

PSF

PSF

PSF

PSF

PSF

PSF

163

164

165

166

167

168

169

170

171

172

Gonystylus bancanus


PSF

162

PSF

KALTENG


PSF

161

173

KALTENG

Other mixed species

PSF

160

KALTENG

KALTENG

KALTENG

KALTENG

KALTENG

KALTENG

KALTENG

Riau

KALTENG

KALTENG

KALBAR

Papua

PABAR

Riau

Mixed (Campnosperma)

Riau

PABAR

PSF

Rhizophora spp.

Rhizophora spp.

PABAR

AL

H 0.445

V (ub) = 0.00465 D

1.781

nda

74

nda

nda

74 2.417

74

nda

74 2.512

nda

nda

nda

nda

nda

63

63

nda

nda

nda

29-79.5

233 nda

29-79.5

nda

nda

nda

nda

233

nda

nda

246

292

63

Vcb (ub) = 0.000128 D V (ub) = 0.000271 D

nda

nda

nda

12-28

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

Hm (m)

nda

nda

nda

nda nda

nda nda

nda

nda

nda

nda

nda

12-28

PY

CO

nda

nda

nda

nda

nda

nda

DBH (cm)

2.385

Vcb (ob) = 0.000255 D

V (ob) = 0.0258 D1.366

V (ub) = 0.00236 D1.861

Vcb (ub) = 0.000287 D2.291

V = 0.000364 D2.256

Vtb = 0.000124 D2.538

Vtb = 0.000136 D2.504

Vtb = 0.000154 D 2.107

V = 0.000289 D2.291

V = 0.000205 D2.384

V = 0.000418 D2.208

V = 0.000148 D2.479

V = 0.00029 D2.311

V7 = 0.000184 D2.46

Vtb = 0.00029 D1.89 H0.462

V = 0.00013 D2.494

nda

V7 = 0.0000228 D2.324 H0.804

KALBAR

159

MF

156

Rhizophora spp.

Rhizophora spp.

nda

V10 = 0.0000135 D2.224 H1.086

KALBAR

Callopyllum sp.

MF

155

FIN

PSF

MF

154

Rhizophora spp.

Sample ∑ Trees 180

Model Form

Vtb = 0.0000534 D2.097 H0.74

KALBAR

158

MF

153

Rhizophora spp.

Location

MF

MF

152

Tree Species

157

Ecosystem Type

No

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

H (m)

0.94

0.97

0.98

0.98

0.96

0.94

0.95

0.99

0.97

0.97

nda

nda

nda

nda

0.98

0.96

nda

nda

nda

nda

nda

nda

R2

0.02

0.02

0.01

0.01

0.02

0.01

0.02

0.17

0.13

0.14

0.13

nda

nda

nda

0.18

0.15

nda

nda

nda

nda

nda

nda

Se

28

28

28

28

28

28

28

22

23

23

78

78

108

59

14

22

11

60

60

79

79

79

Ref

Note

104

Tree volume allometric models that have been developed according to tree species and ecosystem type in Indonesia Riau

KALTENG

Hopea bracteata

Hopea spp.

Intsia sp.

Intsia sp.

Other species

Other species

Other species (Non Dipterocarpaceae &Gonystylus)

Melanorrhoea wallichii

Palaquium spp.

Palaquium spp.

Palaquium spp.

Podocarpus neriifolius


Shorea spp.

Shorea spp.

Shorea spp.

Shorea spp.

Shorea spp.

Shorea spp.

Shorea spp.

Shorea spp.

PSF

PSF

PSF

PSF

PSF

PSF

PSF

PSF

PSF

PSF

PSF

PSF

PSF

PSF

PSF

PSF

PSF

PSF

PSF

PSF

PSF

176

177

178

179

180

181

182

183

184

185

186

187

188

189

190

191

192

193

194

195

196

Riau

Riau

KALTENG

KALTENG

KALTENG

KALTENG

KALTENG

Jambi

Papua

Papua

nda

Riau

Maluku

Jambi

KALTENG

PABAR

Papua

KALTENG

KALTENG

Riau

Model Form

nda

nda

V = 0.000178 D2.24

V = 0.000154 D

27 - 78

nda

nda 2.464

V = 0.000331 D

80

nda nda

20-110 253

2.31

V = 0.0000446 D 1.913

H

nda nda

20-110 253

1.123

nda

20-110

253

)/1000

16.4 - 27.55

nda

nda

nda

2.312

V = 0.000321 D

V = (0.494 D

PY nda

nda

2.322

Vtb = 0.000101 D

nda

nda

nda

nda

nda

nda

nda

13.5-24.5

nda

nda

nda

nda

nda

nda

nda

nda

nda

18.3-33.85

nda

Hm (m)

2.584

V = 0.000316 D2.3

nda

nda

53

nda

19-78

80

nda

nda

nda

Vtb = (0.00018 + 2.102 D2 + 0.3734 D2H)/10000

nda

nda

CO

nda

nda nda

20-110

253

nda

nda

nda

nda

nda

24-74

nda

DBH (cm)

246

nda

nda

nda

80

63

Sample ∑ Trees

lnV = -8.037 + 2.23 lnD

2.718

V = 0.0000495 D

V = 0.000282 D 2.32

V = 0.000513 D 2.23

V = 0.000295 D2.3

Vtb = 0.000166 D2.438

V = 0.000061 D 2.712

V = 0.000267 D 2.359

Vtb = 0.000141 D2.477

V = 0.0000762 D2.579

V = 0.000145 D2.52

AL

V = 0.000245 D2.38

V = 0.000191 D2.48

Vcb (ob) = 0.000712 D2.115

FIN

Gonystylus bancanus

PSF

175

KALTENG

Gonystylus bancanus

PSF

Location

174

Tree Species

Ecosystem Type

No

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

H (m)

0.91

0.96

nda

nda

nda

nda

0.98

0.99

nda

nda

0.95

0.98

0.98

0.99

0.97

0.96

nda

0.97

nda

nda

nda

0.96

0.95

R2

nda

0.16

nda

nda

nda

nda

0.13

nda

nda

nda

nda

nda

nda

nda

0.14

0.17

nda

0.16

nda

nda

nda

nda

0.01

Se

62

22

107

87

87

87

23

35

54

54

109

62

36

35

23

22

87

14

59

107

107

62

28

Ref

Note


105

PSF

PF

PF

PF

PF

PF

208

209

210

211

212

213

PF

Callopyllum sp.

PSF

207

214

Callopyllum sp.

PSF

206

Acacia mangium

Acacia mangium





Callopyllum sp.

Callopyllum sp.

JABAR

JABAR

JATENG

JATENG

JATENG

JATENG

KALBAR

KALBAR

KALBAR

KALBAR

KALTENG

Vatica spp., Dipterocarpus spp., Hopea spp.

PSF

PABAR

Papua

Papua

nda nda

logV7 = -3.836 + 2.208 logD + 0.297 logHbc

Vfw = 0.00191 D

1.91

nda

nda

nda

logV7 = -3.882 + 2.461 logD

Vtb = 0.0000478 D2.76

nda

nda

logVm = -4.044 + 2.003 logD + 0.709 logHcb

nda

nda

nda

nda

nda

logVm = -4.155 + 2.605 logD

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

Hm (m)

PY

CO nda

20 - 110

nda

nda

nda

nda

nda

nda

nda

DBH (cm)

nda

253

246

nda

nda

nda

nda

nda

nda

Sample ∑ Trees

V7 = 0.000133 D2.218 H0.389

Vtb = 0.0000577 D2.176 H0.669

V7 = 0.000191 D 2.426

Vtb = 0.0000989 D2.556

V = 0.000226 D2.423

Vtb = 0.000295 D2.27

lnV = 8.32 + 1.88 lnD + 1.38 lnD2H

lnV = 8.252 + 1.889 lnD + 0.48 lnH

V = 0.0311 (D+1) + 0.00083 D2 + 0.0000115 D2H + 0.0014 H2

Papua

H

0.000033

V = 0.0275D 0.00018

AL

lnV = -7.776 + 2.155 lnD

Papua

Papua

Model Form

V = 0.000224 D2.417

FIN KALBAR

Location

Vatica spp.

205

Timonius nitens

Timonius nitens

PSF

PSF

201

Timonius nitens

204

PSF

200

Syzygium spp.

PSF

PSF

199

Syzygium spp.

203

PSF

198

Shorea sp. & Gonystylus bancanus

PSF

PSF

197

Tree Species

202

Ecosystem Type

No

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

H (m)

0.65

0.95

0.96

0.95

0.98

0.95

nda

nda

nda

nda

nda

0.78

0.99

0.99

nda

nda

nda

nda

R2

nda

nda

0.10

0.11

0.10

0.12

nda

nda

nda

nda

nda

0.18

nda

nda

nda

nda

nda

nda

Se

64

64

68

68

68

68

39

39

39

39

87

14

74

74

54

54

54

108

Ref

*

*

Note

106


Ecosystem Type

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

No

215

216

217

218

219

220

221

222

223

224

225

226

227

228

229

230

231

232

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

KALSEL

KALSEL

KALSEL

KALSEL

KALSEL

KALSEL

KALSEL

KALSEL

KALSEL

KALSEL

KALBAR

KALBAR

JABAR

JABAR

JABAR

AL 5->30

5->30

nda

V (ob) = 0.000135 D H0.613552

V (ub) = 0.000272 D2.317

V (ob) = 0.000243 D2.089 Hbc0.334

1.955862

nda nda

nda

nda nda

nda

nda

nda

Vcb (ub) = 0.000149 D2.145 Hbc0.389 V (ob) = 0.000367 D2.2559

nda

nda

nda

nda

nda

nda

nda

nda

10-35

10-35

Vcb (ub) = 0.000116 D2.118 H0.452

nda

nda

nda

51

51

nda

nda

12-24

12-23

7-17

7-17

7-17

7-17

nda

nda

Hm (m)

nda

nda

nnda da

nnda da

nda

nda

nda

nda

PY

CO

46

46

5->30

5->30

Vcb (ub) = 0.000242 D2.339

Vcb (ob) = 0.000191 D2.059 H0.435

1.992

Vcb (ob) = 0.000126 D H0.583

V cb (ob) = 0.000328 D2.276

1.773

Vtb = 0.0000788 D H0.879

Vtb = 0.000253 D2.292

logV7 = 3.72 + 1.98 logD + 0.44 logH

logV7 = -3.396 + 2.077 logD

logVm = -3.78 + 1.851 logD + 0.62 logH 46

46

logVm = -3.321 + 1.99 logD

JABAR

nda

nda

nda

DBH (cm)

nda

Sample ∑ Trees

Vfw = 0.0000039 D2.48 H1.42

Vtb = 0.000014 D2.3 H0.99

Model Form

JABAR

JABAR

Location

FIN

Tree Species

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

12-20

12-20

12-20

12-20

nda

nda

H (m)

0.98

0.98

0.98

0.98

0.98

0.98

0.98

0.98

0.98

0.98

0.96

0.94

0.99

0.97

0.99

0.98

0.91

0.94

R2

0.14

0.13

0.13

0.13

0.13

0.13

0.13

0.12

0.12

0.13

0.10

0.13

0.05

0.06

0.03

0.05

nda

nda

Se

38

38

38

38

38

38

38

38

38

38

66

66

42

42

42

42

64

64

Ref

Note


107

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

241

242

243

244

245

246

247

248

249

250

PF

237

240

PF

236

PF

PF

235

239

PF

234

PF

PF

233

238

Ecosystem Type

No

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

Acacia mangium

SUMUT

SUMSEL

SUMSEL

SUMSEL

SUMSEL

SUMSEL

KALTIM

KALTIM

KALSEL

KALSEL

KALSEL

KALSEL

nda

V = -0.128 + 0.006H + 0.012 D + 0.006

H

logV4 = -2.933 + 1.792 logD

V4 = 0.000122 D

2.035

10.6-26.1

nda

103 105

nda

nda

nda

103

103

Vtb = 0.0000918 D1.993 H0.71 V4 = 0.000154 D2.425

103

Vtb = 0.000122 D2.47

0.582

10-30

131

V7 = 0.00396 D1.654 H1.243

nda

10-30

131

V7 = 0.000793 D1.887

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

Hm (m)

nda

nda

nda nda

nda nda

nda

131

nda

nda

nda

PY

CO

nda

nda

nda

nda

nda

nda

nda

nda

nda

DBH (cm)

nda

Vm = -0.074 + 0.0000314 D2H

Vcb = 0.0162 + 0.0000312 D2H

V5 (ub) = 0.00019 D2.22 Hbc0.239

1.132

V5 (ub) = 0.0128 D H0.425

V5 (ub) = 0.000256 D2.34

V5 (ob) = 0.000243 D2.139 Hbc0.281

KALSEL

KALSEL

V5 (ob) = 0.000141 D2.012 H0.547

V5 (ob) = 0.000348 D2.279

AL

nda

V (ub) = 0.00019 D2.172 Hbc0.29 nda

nda

Sample ∑ Trees

V (ub) = 0.000122 D2.077 H0.49

Model Form

KALSEL

KALSEL

KALSEL

KALSEL

Location

FIN

Tree Species

16-25

nda

nda

nda

nda

10-30

16-22

16-22

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

H (m)

0.96

0.98

nda

nda

nda

nda

0.87

0.82

nda

nda

0.98

0.98

0.98

0.98

0.98

0.98

0.98

0.98

R2

0.047

0.10

nda

nda

nda

16-22

0.14

0.17

0.07

0.08

0.13

0.13

0.13

0.13

0.12

0.13

0.14

0.13

Se

104

81

81

81

81

61

4

4

55

55

38

38

38

38

38

38

38

38

Ref

*

Note

108


PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

252

253

254

255

256

257

258

259

260

261

262

263

264

265

266

267

268

269

Ecosystem Type

251

No

Alstonia scholaris

Alstonia scholaris

Alstonia scholaris

Alstonia scholaris

Alstonia scholaris

Agathis sp.

Agathis sp.

Agathis sp.

Agathis sp.






Agathis labillardieri

SUMSEL

SUMSEL

SUMSEL

SUMSEL

SUMSEL

Tad

SULUT

SULTRA

SULTENG

JATENG

JATENG

JATENG

JABAR

JABAR

Papua

Papua

SUMUT

SUMUT

SUMUT

Location

AL 20-70 20-70 nda nda

110 110 nda nda

nda

nda

nda

nda 55

nda

2.643

2.471

nda nda

V = 0.011 + 0.0000302 D2H

nda

V = 0.0329 - 0.00686 D + 0.000592 D2 V = 0.000077 D2.304 H0.241

nda

V = -0.0332 + 0.000431D2

V = 0.0000801 D

V = 0.0000659 D

V = 0.00025 D

nda

nda

nda

nda

nda

95

2.353

V = 0.00018 D

nda

nda

nda

nda

55

nda

nda

nda

nda

nnda da

nnda da

nda

nda

nda

nda

nda

nda

nda

nda

nda

PY nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

14-33

14-33

16-25

16-25

16-25

H (m)

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

Hm (m)

nda

CO

10.6-26.1

2.347

V = 0.000157 D2.444

logVm = -4.095 + 2.212 logD + 0.5207 logH

logVm = -3.824 + 2.447 logD

V = 0.000142 D2.455

V = 0.000092 D2.541

V = 0.000086 D2.556

V = 0.0014 D1.762 H 0.111

V = 0.00072 D2.078

logV7 = -3.764 + 1.531 logD + 0.862 logH

10.6-26.1

10.6-26.1

DBH (cm)

105

105

logV4 = -3.638 + 1.492 logD+ 0.814 logH

Sample ∑ Trees 105

Model Form

logV7 = -3.017 + 1.848 logD

FIN

Agathis labillardieri

Acacia mangium

Acacia mangium

Acacia mangium

Tree Species

0.94

0.97

0.96

0.96

0.96

0.99

nda

0.98

nda

0.98

0.96

nda

0.99

0.99

0.86

0.91

0.97

0.95

0.97

R2

0.04

0.04

0.05

0.05

0.05

nda

nda

0.20

nda

0.06

0.08

nda

nda

nda

0.13

0.20

0.043

0.05

0.041

Se

93

93

93

93

93

109

52

20

51

70

70

41

29

29

58

58

104

104

104

Ref

Note


109

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

279

280

281

282

283

284

285

286

287

288

PF

PF

278

289

PF

PF

274

277

PF

273

PF

PF

272

276

PF

271

PF

PF

270

275

Ecosystem Type

No

Dalbergia sisoides

Dalbergia latifolia

Dalbergia latifolia

Dalbergia latifolia

Dalbergia latifolia

Dalbergia latifolia

Bischoffia javanica

Altingia exelsa

Altingia exelsa

Altingia exelsa

Altingia exelsa

Altingia exelsa

Altingia exelsa

Altingia exelsa

Altingia exelsa

Alstonia sp.

Alstonia sp.

Alstonia sp.

Alstonia sp.

Alstonia scholaris

Vcb = 0.000081 D2.06 H0.662

SUMSEL

SUMSEL

NTT

JATIM

JATIM

JATIM

JATIM

Bali

Bali

JABAR

JABAR

JABAR

JABAR

JABAR

JABAR

JABAR

JABAR

nda

logV7 = -3.5 + 2.11 logD + 0.042 logH7

125

nda

logV7 = -3.48 + 2.12 logD

nda

logVm= -3.79 + 1.98 logD + 0.45 logHm

nda

59

nda

nda

nda

nda

nda

nda

nda

nda 36

nda

nda

nda nda

nda

nda

10-33

10-33

116 116

10-33

116

nda

Vtb = 0.0000723 D2.465

10-33

nda

4-16

4-16

4-16

4-16

nda

nda

nda

nda

nda

Hm (m)

nda

nda

nda nda

nnda da

nda

nda

nda

nda

nda

nda

PY

CO

116

nda

nda

61 61

nda

nda

61 61

nda

DBH (cm)

nda

Sample ∑ Trees

logVm= -3.568 + 2.115 logD

Vtb = 0.000476 D 2.045

Vtb = 0.00326 D2.195

V7 = 0.000224 D2.232 H0.118

Vtb = 0.000191 D2.193 H0.19

V7 = 0.000270 D2712

Vtb = 0.000257 D2.256

0.741

H

2.088

Vtb = 0.0000402 D H0.982

Vtb = 0.000124 D 1.874

Vtb = 0.000108 D2.174 H0.527

Vtb = 0.000202 D2.402

Vbr = 0.000032 D2.15 H0.65

AL

V = 0.000089 D2 H0.917

SUMSEL

SUMSEL

Vbr = 0.00000426 (D3)

SUMSEL

Model Form

V = 0.111 - 0.0136 H 0.0146 D + 0.000650 D2 - 0.000024 D2H + 0.00144 DH

Location

FIN

Tree Species

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

H (m)

0.98

0.83

0.83

0.89

0.83

0.91

0.74

nda

nda

nda

nda

nda

nda

nda

nda

0.83

0.92

0.94

0.74

0.92

R2

0.16

0.12

0.12

0.09

0.12

0.17

0.22

nda

nda

nda

nda

0.15

0.11

0.08

0.11

nda

nda

nda

nda

0.05

Se

18

71

71

71

71

12

12

72

72

72

72

9

9

9

9

26

26

26

26

93

Ref

*

Note

110


Ecosystem Type

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

No

290

291

292

293

294

295

296

297

298

299

300

301

302

303

304

305

306

307

308

309

Gmelina arborea

Gmelina arborea

Gmelina arborea

Gmelina arborea

Eucalyptus urophylla

Eucalyptus urophylla

Eucalyptus spp.

Eucalyptus grandis

Eucalyptus grandis

Eucalyptus grandis

Eucalyptus grandis

Eucalyptus grandis

Eucalyptus grandis

Eucalyptus deglupta

Eucalyptus deglupta

Eucalyptus deglupta

Eucalyptus deglupta

KALSEL

KALSEL

KALSEL

KALSEL

SUMSEL

SUMSEL

NTT

SUMUT

SUMUT

SUMUT

SUMUT

SUMUT

SUMUT

SULSEL

SULSEL

KALTIM

AL nda

nda

H

Vub =0.000241 D

1.666

1.85

Vub = 0.000746 D

Vob= 0.000391 D 1.553

Vob = 0.00114 D1.711

0.597

H

H

0.522

V = -0.128 + 0.006 H + 0.012 D

V = 0.000026 D 0.833

nda nda nda nda

nda nda nda nda

nda

nda

130

2.229

nda

10-24

110

2.506

VKP = 0.000066 D

V5 = 0.000446 D H

10-24

110

1.915

V5 = 0.000399 D 0.67

10-24

nda

nda

nnda da

nnda da

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

PY nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

H (m)

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

Hm (m)

nda

CO

110

2.228

1.916

V7 = 0.00144 D

10-24

10-24

nda

nda

10-24

110

110

nda

nda

nda

110

V7 = 0.000396 D2.219

2.181

V10 = 0.000697 D H0.591

V10 = 0.000175 D2.457

logV7 = -1.37 + 2.62 logD + 0.289 logH

logV7 = -1.23 + 2.788 logD

V = 0.102 D - 0.126 (ln(D)2.436) + 0.000014 D2H

V = 0.00004 D3.139 (0.975D) nda

nda

nda

KALTIM

nda

nda

V = 0.0000451 D 2.027 H 0.874

KALTIM

nda

nda

DBH (cm)

nda

100

Sample ∑ Trees

V = 0.000103 D2.317 H0.239

V = 0.000245 D2.543

Model Form

Bengkulu

SULTENG

Location

FIN

Eucalyptus deglupta

Disoxylum Molliscimim

Diospyros celebica

Tree Species

0.98

0.94

0.97

0.93

nda

nda

0.98

0.96

0.94

0.96

0.94

0.95

0.93

0.98

0.98

0.99

0.99

nda

0.96

0.98

R2

0.02

0.02

0.02

0.03

nda

nda

0.18

0.12

0.14

0.12

0.15

0.15

0.17

0.11

0.12

nda

nda

0.16

0.04

nda

Se

56

56

56

56

30

30

18

10

10

10

10

10

10

65

65

37

37

30

92

34

Ref

*

*

*

Note


111

PF

PF

PF

PF

PF

PF

PF

PF

PF

319

320

321

322

323

324

325

326

327

PF

315

PF

PF

314

318

PF

313

PF

PF

312

317

PF

311

PF

PF

310

316

Ecosystem Type

No

Model Form

1.1617

Pinus merkusii

Pinus merkusii

Pinus merkusii

Peronema canesnes

Peronema canesnes









Aceh

Aceh

Aceh

Banten

Banten

SUMSEL

JATIM

JATIM

JATIM

JATIM

JABAR

JABAR

JABAR

logVtb = -3.859 + 2.48 logD

JABAR

Paraserianthes falcataria nda

nda

nda nda

nda nda

V = 0.0001 D H

207 207 207

logV5 (ub) = - 0.677 + 2.42 logD logV10 (ub) = - 0.714 + 2.439 logD logVm (ub) = - 0.801 + 2.471 logD

1.01

V = 0.00024 D2.08 1.7

nda

nda

V = -0.128 + 0.006 H + 0.012 D + 0.022

18.3-83

18.3-83

18.3-83

nda

nda

logV7 = -3.617 + 2.169 logD + 0.266 logH

nda

nda

nda

nda

nda

nda

nda nda

nda

nda

Nda

nda

nda

nda

nda

nda

nda

nda

nda

5-13

Hm (m)

19.3-52.8

19.3-52.8

19.3-52.8

nda

nda

nda

Nda

Nda

PY

CO

nda

nda

nda

nda

nda nda

nda

5->30

DBH (cm)

90

103

Sample ∑ Trees

logV7 = -3.497 + 2.315 logD

logVm = -3.991 + 2.071 logD + 0.636 logH

logVm = -3.702 + 2.423 logD

V5 = 0.00016 D2.078 H0.503

Vtb = 0.0000768 D H0.627 2.137

logV5= -3.59 + 2.353 logD

H

Vm = 0.00087 D

Banten

Paraserianthes falcataria 1.66

Vtb = 0.00011 D

Banten 2.541

AL

Vtb = 0.00122 D1.744

Vtb = 0.0000669 D1.952 H0.794

FIN Bali

SUMSEL

Location


Manilkara kauki

Gmelina arborea

Tree Species

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

H (m)

nda

nda

nda

0.96

0.95

nda

0.99

0.99

0.98

0.98

nda

nda

nda

nda

0.97

0.94

0.84

0.99

R2

0.20

0.21

0.20

0.07

0.08

nda

0.09

0.09

0.13

0.15

0.54

0.41

0.58

0.49

0.20

0.28

0.25

0.08

Se

5

5

5

40

40

31

69

69

69

69

8

8

8

8

6

6

12

103

Ref

*

*

*

*

*

Note

112


PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

329

330

331

332

333

334

335

336

337

338

339

340

341

342

343

344

345

346

347

348

349

350

Ecosystem Type

328

No

Pometia acuminate


Vtb = 0.0000305 D1.642 H1.356

JABAR JATIM

PABAR

Papua

Papua

JATIM

JATIM

JATIM

JATIM

JATENG

JATENG

JATENG

JATENG

JATENG

JATENG nda

nda

nda

nda

nda

100 100 100 100 100

nda

58

2.702

nda

nda nda

V = 0.000179 ((D + 1)2.1023) (H0.373) Vtb = 0.000002 D2.394 H1.511

nda

nda

V = -8.037 + 2.23 lnD

V = 0.0000383 D

nda

16-52

559

V = 0.0000847 D

12-50

240

nda

nda

100

81

12-32

136

nda

nda

nda nda

nda nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

98-33.6

nda

19.3-52.8

19.3-52.8

19.3-52.8

Hm (m)

PY

CO 18-52

750

18-52

nda

298 750

nda

16.4-48.6

50 298

nda

92

18.3-83

18.3-83

18.3-83

DBH (cm)

2.577

V = 0.0000875 D 2.564

V = 0.00141 D2.186

Vfw = 0.000362 D2.434

Vtb = 0.00000831 D3.254

Vfw = 0.0000504 D2.089

Vtb = 0.0000202 D3.016

Vfw = 0.0000505 D 2.065

Vtb = 0.00000424 D 3.409

V = 0.0000997 D2.512

V7 = 0.0000758 D2.606

JATENG

V = 0.0000556 D

JABAR JATIM

2.691

V = 0.0000231 D2.971

V = 0.0000933 D 2.64

V = 0.000169 D2.317

logVm (ob) = - 0.65 + 2.428 logD

AL

207

logV10 (ob) = - 0.574 + 2.399 logD 207

207

Sample ∑ Trees

logV5 (ob) = - 0.559 + 2.392 logD

Model Form

JABAR

JABAR

JABAR

JABAR

Aceh

Aceh

Aceh

Location

FIN


Pinus merkusii

Pinus merkusii

Pinus merkusii

Pinus merkusii

Pinus merkusii

Pinus merkusii

Pinus merkusii

Pinus merkusii

Pinus merkusii

Pinus merkusii

Pinus merkusii

Pinus merkusii

Pinus merkusii

Pinus merkusii

Pinus merkusii

Pinus merkusii

Pinus merkusii

Pinus merkusii

Pinus merkusii

Pinus merkusii

Tree Species

nda

nda

nda

nda

12-32

10-30

nda

nda

nda

nda

nda

nda

nda

10-24

12-32

12-32

nda

nda

nda

nda

nda

nda

nda

H (m)

nda

0.99

0.98

0.95

0.97

0.97

0.81

0.72

0.97

0.66

0.92

0.81

0.94

0.86

Nda

nda

0.94

0.96

0.95

0.92

nda

nda

nda

R2

nda

nda

nda

0.12

0.16

0.12

nda

nda

nda

nda

nda

nda

nda

nda

0.13

0.21

nda

nda

nda

nda

0.17

0.17

0.17

Se

57

46

46

90

90

90

27

94

94

94

94

94

94

91

85

85

45

45

36

27

5

5

5

Ref

*

*

*

*

*

*

Note


113

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

PF

352

353

354

355

356

357

358

359

360

361

362

363

364

365

366

367

368

369

PF

PF

351

370

Ecosystem Type

No

Tectona grandis

Tectona grandis

Tectona grandis

Tectona grandis

Tectona grandis









Schima wallichii

Schima wallichii

Pterospermum javanicum



Pterocarpus indicus

JATIM

JATENG

JATENG

JATENG

JATENG

SUMSEL

JATIM

JATIM

JATIM

JATIM

JATENG

JATENG

JATENG

JABAR

JABAR

JATIM

JATIM

JATIM

NTT

PABAR

Location

Vtb = 0.986 D

H

16-65 nda

nda

44 nda nda

nda nda

nda 147

V = -0.1276 + 0.006 H + 0.012 D + 0.0015

147 nda

V = 0.000838 D1.9386 V = 0.0000000000577 D6.33

nda

32-110

25-62.5

147 2.2568

V = 0.000195 D

30-103.7

147

V = 0.000673 D1.934

V = 0.000224 D2.397

nda

nda

V7 = 0.000127 D2.328 H0.17

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda nda

nda nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

Hm (m)

PY

CO

16-65

16-65

44

44

nda

nda

nda nda

DBH (cm)

Sample ∑ Trees

nda

Vtb = 0.0000984 D2.009 H0.616

V7 = 0.000173 D 2.37

Vtb = 0.000305 D2.162

V = -4.54 + 2.211 D + 0.865 H

V = -3.452 + 1.983 D + 0.175 H

V = -4.439 + 2.213 D + 0.777 H

2.672

V = 0.0000577 D

V = 0.000093 D 2.505

V7 = 0.0000167 D2.18 H1.354

V7 = (-0.323 D + 4.32 D2)/10000

logV7 = -0.000952 + 2.497 logD

0.309

AL

0.845

Model Form

V = 0.00002 D2.989

FIN

Pometia acuminate

Tree Species

nda

12.1-20.5

7.8-16.6

9.7-14.6

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

16-32

16-32

16-32

nda

nda

H (m)

0.62

0.95

0.94

0.92

0.93

nda

nda

nda

nda

nda

0.98

0.89

0.96

nda

nda

nda

nda

nda

nda

nda

R2

nda

0.07

0.25

0.20

0.12

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

nda

Se

96

47

47

47

47

61

105

105

105

105

43

43

43

24

24

86

86

86

95

57

Ref

*

*

*

*

*

Note

NOTES: : Dryland Forest : Peat Swamp Forest : Mangrove Forest : Plantation Forest : Diameter at breast height (cm) : Tree height (m) : Total tree volume (m3) : Merchantable volume (m3) : Clear bole volume (kg) : Stem volume up to 4 cm top diameter limit (m3)

V5 V7 V10 Vtb Vfw Vbr Vcr ob ub *

: Stem volume up to 5 cm top diameter limit (m3) : Stem volume up to 7 cm top diameter limit (m3) : Stem volume up to 10 cm top diameter limit (m3) : Timber volume (m3) : Fuelwood volume (m3) : Branch volume (m3) : Crown volume (m3) : over bark : under bark : It is advisable not to use this model

FIN

AL

CO

PY

DLF PSF MF PF D H V Vm Vcb V4

114


1.

2.

3.

References-Appendix 4

Abdurachman dan Purwaningsih, S. 2007. Tabel volume batang di bawah pangkal tajuk jenis Parashorea spp. di Labanan, Berau Kalimantan Timur. Prosiding Balai Besar Penelitian Dipterokarpa Samarinda. 61p. Asmoro, P.J.P. dan Kuswanda, R. 2007. Penyusunan model pendugaan volume pohon jenis-jenis komersial di hutan alam pada dua areal IUPHHK di Papua Barat. Info Hutan 4(5): 429435. Broadhead, J.S. 1995. Analysis of data from Biotrop logged and unlogged forest permanent sample plot in Jambi province, Sumatra. Report Number: RES/PSP/95/4. Research Project, IndonesiaUK Tropical Forest Management Programme, Palangkaraya. Bustomi, S. 1988. Tabel isi pohon Acacia mangium Willd. untuk daerah Balikpapan, Kalimantan Timur. Buletin Penelitian Hutan 495: 31-38.

5.

Bustomi, S. 2002. Pendugaan isi pohon jenis Pinus merkusii untuk daerah Takengon, Aceh. Buletin Penelitian Hutan 632: 59-71.

6.

Bustomi, S. dan Imanuddin, R. 2004. Pendugaan isi pohon sengon (Paraserianthes Paraserianthes falcataria Backer) di KPH Banten. Buletin Penelitian Hutan 645: 101109.

14. Direktorat Inventarisasi Hutan. 1990. Tabel volume pohon beberapa jenis kayu untuk Propinsi Irian Jaya. Laporan No. 15/Inhut-III/90. 15. Direktorat Inventarisasi Hutan. 1990. Tabel volume pohon beberapa jenis kayu untuk Propinsi Lampung. Laporan No. 07/Inhut-III/90. 16. Direktorat Inventarisasi Hutan. 1990. Tabel volume pohon beberapa jenis kayu untuk Propinsi Maluku. Laporan No. 14/Inhut-III/90. 17. Direktorat Inventarisasi Hutan. 1990. Tabel volume pohon beberapa jenis kayu untuk Propinsi Nusa Tenggara Barat. Laporan No. 10/Inhut-III/90. 18. Direktorat Inventarisasi Hutan. 1990. Tabel volume pohon beberapa jenis kayu untuk Propinsi Nusa Tenggara Timur. Laporan No. 11/Inhut-III/90. 19. Direktorat Inventarisasi Hutan. 1990. Tabel volume pohon beberapa jenis kayu untuk Propinsi Sulawesi Selatan. Laporan No. 12/Inhut-III/90. 20. Direktorat Inventarisasi Hutan. 1990. Tabel volume pohon beberapa jenis kayu untuk Propinsi Sulawesi Tenggara. Laporan No. 13/Inhut-III/90.

AL

7.

13. Direktorat Inventarisasi Hutan. 1990. Tabel volume pohon beberapa jenis kayu untuk Propinsi Bengkulu. Laporan No. 08/Inhut-III/90.

CO

4.

12. Direktorat Inventarisasi Hutan. 1990. Tabel volume pohon beberapa jenis kayu untuk Propinsi Bali. Laporan No. 09/Inhut-III/90.

PY

Appendix 5.

Bustomi, S. dan Soemarna, K. 1986. Tabel isi pohon sementara jenis meranti (Shorea (Shorea spp.) untuk KPH Bangkinang Riau. Buletin Penelitian Hutan 480: 1-126.

Bustomi, S., Harbagung, dan Krisnawati, H. 1995. Tabel isi pohon lokal jenis sengon (Paraserianthes (Paraserianthes falcataria)) di KPH Bogor, Jawa Barat. Buletin falcataria Penelitian Hutan 588: 37-57.

9.

Bustomi, S., Riyadi, D. dan Suharlan, A. 1978. Tabel volume pohon bebas cabang jenis rasamala (Altingia Altingia exelsa Noronhoe) untuk Daerah Garut, Sumedang dan Sukabumi. Laporan Lembaga Penelitian Hutan No. 283.

FIN

8.

10. Darwo. 1996. Tabel volume Eucalyptus grandis di HPHTI PT. Inti Indorayon Utama di Kesatuan Pemangkuan Hutan Samosir, Sumatera Utara. Prosiding diskusi hasil-hasil penelitian Puslitbang Hutan dan Konservasi Alam: 268 – 283. 11. Darwo. 1996. Tabel volume pohon untuk hutan payau di areal HPH PT Bina Lestari I, KPH Indragiri Hilir, Riau. Buletin Balai Penelitian Kehutanan Pematang Siantar 12 (2): 97-111.

21. Direktorat Inventarisasi Hutan. 1990. Tabel volume pohon beberapa jenis kayu untuk Propinsi Sumatra Utara. Laporan No. 06/Inhut-III/90. 22. Direktorat Inventarisasi Hutan. 1991. Tabel volume lokal (tarif) beberapa jenis kayu untuk hutan rawa Propinsi Riau. Laporan No. 01/Inhut-I/91. 23. Direktorat Inventarisasi Hutan. 1991. Tabel volume lokal (tarif) beberapa jenis kayu untuk hutan rawa Propinsi Kalimantan Tengah. Laporan No 02/ Inhut-III/91. 24. Disastra, S.M. 1982. Studi penyusunan tabel volume lokal tegakan puspa (Schima wallichii) di Hutan Pendidikan Gunung Walat. Skripsi Jurusan Manajemen Hutan, Fakultas Kehutanan, Institut Pertanian Bogor, Bogor. 25. Enggelina, A. 1996. Dalam: Bertault, J-G dan K. Kadir (Eds). Silvicultural Research in a Lowland Mixed Dipterocarp Forest of East Kalimantan, the Contribution of STREK Project, CIRAD-Forêt, FORDA, and PT. INHUTANI I. CIRAD-Forêt Publication: 127-137.


115

27. Fakultas Kehutanan IPB. 1996. Penyusunan tabel volume lokal jenis Pinus merkusii di Jawa Barat. 28. Fanani, Z. 1995. Penyusunan tabel volume total dan bebas cabang ramin di Areal HPH PT. Inhutani III, Sampit, Kalimantan Tengah. Skripsi Jurusan Manajemen Hutan, Fakultas Kehutanan, Insitut Pertanian Bogor, Bogor. 29. Farid, A. 1985. Studi penyusunan tabel volume lokal tegakan damar (Agathis loranthifolia Salisb.) di RPH Kabandungan Sukabumi. Skripsi Jurusan Manajemen Hutan, Fakultas Kehutanan, Insitut Pertanian Bogor, Bogor.

CO

30. Harbagung. 1991. Penyusunan model penduga volume pohon jenis Eucalyptus deglupta. Laporan hasil penelitian DPL tahun 1990/1991. Pusat Litbang Hutan dan Konservasi Alam, Bogor.

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PY

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Monograph

Models for Estimating Tree Biomass




ISBN 978-979-3145-93-8

9 789 793 14 593 8

Monograph. Bogor, July 2012

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