redd abacus sp - world agroforestry centre system such as windows, linux or mac. 1.2 the minimum...

1 | REDD Abacus Users Manual

REDD Abacus SP User Manual and Software

Degi Harja

Sonya Dewi

Meine van Noordwijk

Andree Ekadinata

Arief Rahmanulloh


1. General Information

1.1 The REDD Abacus Software

The REDD Abacus software is available on the internet. It can be downloaded freely from

http://www.worldagroforestry.org/sea/projects/allreddi/softwares, and available for any

operating system such as Windows, Linux or Mac.

1.2 The Minimum Requirement

REDD Abacus is a light application, so that can be run in computers that have general

specifications. The minimum specifications are:

1. 1 GB Hard disk space (included JVM)

2. Memory Capacity 256 MB

3. Good condition desktop or portable computer, with any operating system (Windows, Linux ,

Mac)

1.3 Software disclaimer and citation

The REDD Abacus software is in the public domain. The users may neither assert propriety rights

thereto nor represent them to anyone as other than World Agroforestry Center produced

programs and cite REDD Abacus as follows:

Example:

This project was analyzed using the REDD Abacus software (World Agroforestry Center 2011,

Bogor, Indonesia: World Agroforestry Center (ICRAF) Southeast Asia Regional Program

http://www.worldagroforestry.org/sea/projects/allreddi/softwares).

1.4 How to contact

For additional information and help, please see the REDD Abacus project website:

http://www.worldagroforestry.org/sea/projects/allreddi/ or contact these following addresses:

- Degi Harja ([email protected]) for software technical questions

- Sonya Dewi ([email protected]) and Meine van Noordwijk ([email protected]) for

software background and concepts

- Andree Ekadinata ([email protected]) for Geographic Information System (GIS) analysis

- Arief Rahmanulloh ([email protected]) for profitability analysis

2. Getting Started

http://www.worldagroforestry.org/sea/projects/allreddi/softwares


There are several installation packages on the website (or distributed CD package) for any

Operating System (Windows, Linux and Mac). Below is the general instruction for each Operating

System:

Windows

The package available in two types, some include a Java Virtual Machine (JVM) and some

without. For those unfamiliar with the term “Java Virtual Machine” we suggested to download

the one include JVM. Otherwise you can have separate Java installation before installing the

REDD Abacus software. The Java software can be downloaded from:

http://www.java.com/en/download/.

After downloading, extract the zip file then double-click the .exe file, follow the instruction on

the installation procedure.

NOTES:

If you have problems with installer file (sometime it is not working on some Windows 7 OS),

please try use the zip package without the installer.

Extract the zip file, and use “run_abacus.bat” file for running the application (double click).

You can create the shortcut to “run_abacus.bat” file by right clicking the file, select “Send to”->

“Desktop”

Linux

After downloading open a shell and, cd to the directory where you downloaded the installer.

At the prompt type: sh ./abacus.bin

NOTES: you need to install Java Virtual Machine (version 1.6 or later)

Mac

After downloading, double-click abacus

NOTES:

Requires Mac OS X 10.0 or later

The compressed installer should be recognized by Stuffit Expander and should automatically be

expanded after downloading. If it is not expanded, you can expand it manually using StuffIt

Expander 6.0 or later.

If you have any problems launching the installer once it has been expanded, make sure that the

compressed installer was expanded using Stuffit Expander. If you continue to have problems,

please contact technical support.

3. Overview

http://www.java.com/en/download/

http://www.aladdinsys.com/expander/index.html

http://www.aladdinsys.com/expander/index.html


3.1 The Basic Methods For Estimating Opportunity Cost

Opportunity costs refer to the potential economic gains that could be made if certain types of land

use change are not happening, e.g. as part of an emission reduction program. If the opportunity

costs are low relative to the amount of emission reduction that can be achieved by avoiding this

category of land use change, it may be of interest to stakeholders of emission reduction to offset

the opportunity costs and make contracts that secure that the carbon remains stored. The

difference in economic value ($/ha), per unit avoidable emission (tCO2e/ha) takes the dimensions

of a price ($/tCO2e). If the economic value of emission reduction elsewhere (e.g. on a virtual

‘carbon market’) is higher than the opportunity costs of avoiding emissions in a certain landscape,

it may be financially attractive for all parties to develop contracts that ensure local emission

reduction. Several other elements of price (implementation and monitoring plus transaction costs)

also play a role, but if opportunity costs are higher than going market prices, discussions of

economic incentives for voluntary emission reduction will be a non-starter. A further discussion of

backgrounds is provided in White et al., 2010 and van Noordwijk et al., 2011.

Opportunity cost curves indicate how much emission reduction might be feasible at what price.

The basis for their constructing is [1] The differences in economic value ($/ha) and [2] Time-

averaged C stock (t C/ha) of any type of [3] land use change. The land use change may have

occurred (if the opportunity cost is a retrospective analysis of recent history) or is deemed

plausible in a forward looking scenario of land use change.

REDD Abacus was developed to analyze the opportunity cost of land use changes in a landscape

or area within a period of time and generate the abatement cost curve using

a) A legend that represents land use change from the perspective of economic (‘land use) as well

as carbon storage (‘land cover’) perspectives, and that allows land use change data to be

compiled by a combination of land cover change detection and economic constraints (e.g.

labour requirements in relation to human population density) (see point 3.2.1 for further

explanation of land use system characterization)

b) Typical carbon stock data for each legend unit (see point 3.2.3 for further explanation and

appendix 3 for time averaged carbon stock calculation steps

c) Net Present Value for each land use type, typically using a private (= farm gate) accounting

stance (White et al., 2010) and/or a social (= national economy) one

d) A matrix of land use change values, that are internally consistent and represents either

historical change or a forward looking scenario.

With these inputs, the program performs four steps (Figure 3.1):

1. Convert differences in carbon stocks into estimated emissions (see Appendix 7 for further

explanation).

2. Construct a table of opportunity costs for every type of land use change from the differences in

NPV and C stocks

3. Determine the actual emissions for each cell in the matrix from the area involved and the

emissions per unit area

4. Present the cumulative emission total after sorting by opportunity cost


Together these four steps lead to a two-dimensional graph charting the opportunity costs of

avoiding deforesting land-use changes against volume of carbon-dioxide equivalent emissions.

source: van Noordwijk et al. 2010

Figure 3.1. Steps in deriving an opportunity cost (OpCost) curve that relates the changes in economic

profitability (net present value) and typical carbon stocks of land-use (LU) systems, to a land-use change

matrix that describes the changes that have occurred (for a retrospective OpCost curve) or might occur

(for a scenario OpCost curve).

As indication of a feasible level of economic incentives, a price level of USD 5/tCO2e, is used as

default leaving some space for transaction and implementation costs (Stern, 2007; Swallow et al.,

2007). The user can easily adjust this price level and evaluate the consequences

Starting The Application and Create New Project

How to go:

Click on the application shortcut to start the REDD

ABACUS application. (each operating system may

have different method for starting the application,

see the section 2. Getting Started)

The main windows will appear as shown on the

right figure

How to do:


Click “File” -> “New” on the menu bar to create new Abacus Project

You will be asked to define label for the new Project. Click “Ok”.

After defining the Project label, the window will show as on Figure below.

You can define the description of the project and reset the label.

Further Readings

Dewi S, van Noordwijk M and Ekadinata A. 2008. Does carbon emission to the atmosphere pay?

Abatement cost curves for three provinces in Indonesia. Bogor, Indonesia. World Agroforestry

Centre - ICRAF, SEA Regional Office (Available from:

http://www.worldagroforestry.org/sea/Publications/files/poster/PO0141-08.PDF)

van Noordwijk, M., Dewi S., Suyanto, Minang P., White D., Robiglio V., Hoang MH., Ekadinata A,

Mulia R., and Harja D. 2011. Abatement cost curves relating past greenhouse gas emissions to the

economic gains they allowed. Project Report. Bogor, Indonesia. World Agroforestry Centre - ICRAF,

SEA Regional Office. 82 p.

White D and Minang P, eds. 2010. Estimating the opportunity costs of REDD+ A training manual.

Washington, USA: World Bank Institute. (Available from

http://wbi.worldbank.org/wbi/Data/wbi/wbicms/files/drupal-

acquia/wbi/OppCostsREDD+manual.pdf).

4. Spatial and Carbon Stock Input Data

http://www.worldagroforestry.org/sea/Publications/files/poster/PO0141-08.PDF

http://wbi.worldbank.org/wbi/Data/wbi/wbicms/files/drupal-acquia/wbi/OppCostsREDD+manual.pdf



Spatial and Carbon Stock data is used for calculating the estimated emission matrix. Below are the

brief steps for preparing the data and how it used on the application.

4.1 Land use system characterization

Land use system is a mixture of land cover (e.g., Forest land, Grassland, Wetlands) and land use

(e.g., Cropland, Settlements) classes. The characterization of land use system has to be able to

represent variation of carbon stock and economic profitability. The Information about land use

system characterizations are needed to estimate carbon stocks, emissions, and removals of

greenhouse gases associated with Land Use, Land-Use Change and Forestry (LULUCF) activities.

Six broad categories of land are described here may be considered as top-level categories for

representing land areas within a country. The categories are consistent with the

Intergovernmental Panel on Climate Change (IPCC) Guidelines and the requirements of Articles 3.3

and 3.4 of the Kyoto Protocol, and may be further subdivided as described in Appendix 1.

The top-level land categories for GHG inventory reporting are:

a) Cropland

This category includes arable and tillage land and agro-forestry systems where woody

vegetation falls below the thresholds used for the forest land category, consistent with the

selection of national definitions; part of the agroforestry systems falls into this class.

b) Forest land

This category includes all land with woody vegetation, usually sub-divided into managed and

unmanaged, and further by ecosystem type as specified in the IPCC Guidelines 2003 Chapter 3.

Agroforests are usually included in this category.

c) Grassland

This category includes rangelands and pasture land that is not considered as cropland. The

category also includes all grassland from wild lands to recreational areas as well as agricultural

and silvi-pastoral systems that do not meet the forest land criterion, subdivided into managed

and unmanaged consistent with national definitions.

d) Other land

This category includes bare soil, rock, ice, and all unmanaged land areas that do not fall into

any of the other five categories. It allows the total of identified land areas to match the national

area, where data are available.

e) Settlements

This category includes all developed land, including transportation infrastructure and human

settlements of any size, unless they are already included under other categories.

f) Wetlands

This category includes land that is covered or saturated by water for all or part of the year (e.g.,

peat land) and that does not fall into the forest land, cropland, grassland or settlements


categories. The category can be subdivided into managed and unmanaged according to

national definitions.

When applying these categories, inventory agencies should classify land under only one category

to prevent double counting. If a country's land classification system does not match categories (i)

to (vi) as described above, it is good practice to combine or disaggregate the existing land classes of

this system of land-use classification in order to use the categories presented here, and to report

on the procedure adopted. It is also good practice to specify national definitions for all categories

used in the inventory and report any threshold or parameter values used in the definitions. Where

national land classification systems are being changed or developed for the first time, it is good

practice to ensure their compatibility with land-use classes (i) to (vi) (IPCC, 2003).

Countries will use their own definitions, which may, of course, refer to internationally accepted

definitions, such as those by IPCC, FAO, Ramsar, etc. For that reason no definitions are given here

beyond broad descriptions. In addition, the detailed definitions and the national approach to

distinguishing between land uses should be described in a transparent manner. Land-cover types

to be classified are determined and defined prior to the classification processes. This stage is

important to guide the sampling and the classification and is a basic for the land cover list data in

Project main screen of REDD Abacus software (Figure 6.1).

Transition Eligibility

Land Use System Input

How to go:

Click “Input”->”Spatial & Carbon Stock Data”->”Land Use System” button menu on the main

frame

Or

Expands the tree menu on the tree menu frame (on the left side by default) on “Input”-

>”Spatial & Carbon Stock Data”->”Land Use System” (highlight the last child menu)

How to do:

By default there only one Land Use System defined. You can add more by clicking the “+”

(plus) button on the table menu bar. And click “-“ (minus) button for removing.

Rename the label according to your Land Use System data, and add description if

necessary.

You can do copy and paste method for renaming the label (ex. copy from MS Excel table)


Click “Transition Eligibility” tab to define the eligibility for each land use transition (Figure

below).

Further Readings

Intergovernmental Panel on Climate Change [IPCC], 2003. Good Practice Guidance for Land Use,

Land-Use Change and Forestry. Chapter 3 & 4 (Available from: http://www.ipcc-

nggip.iges.or.jp/public/gpglulucf/gpglulucf_contents.html)

Widayati A, Ekadinata A, Johana F, and Said Z 2010. Component C: Consequences of land-use

change for carbon emissions. In: van Noordwijk M. and Tata HL, eds. Human Livelihoods,

ecosystem services and the habitat of the Sumatra orang utan: Rapid assessment in Batang Toru

and Tripa. Bogor, Indonesia: World Agroforestry Center (ICRAF) Southeast Asia Regional Program

(Available from:

http://www.worldagroforestry.org/Sea/Publications?do=view_pub_detail&pub_no=RP0270-11).

http://www.ipcc-nggip.iges.or.jp/public/gpglulucf/gpglulucf_contents.html

http://www.ipcc-nggip.iges.or.jp/public/gpglulucf/gpglulucf_contents.html

http://www.worldagroforestry.org/Sea/Publications?do=view_pub_detail&pub_no=RP0270-11


4.2 Area Size and Spatial Zonation

[Andree to fill]

Area Size and Zonation Input

How to go:

Click “Input”->”Spatial & Carbon Stock Data”->”Zonation Setting” button menu on the main

frame

Or


>”Spatial & Carbon Stock Data”->” Zonation Setting” (highlight the last child menu)

How to do:

By default one Zone was defined. You can add more by clicking the “+” (plus) button on the

table menu bar. And click “-“ (minus) button for removing.

You may rename the zone label according to your preference.

You can do copy and paste method for modifying the data on the table (ex. copy from MS

Excel table)

4.3 Transition Matrix

Time series of land use/cover mapping as the basis for the classification scheme is produced from

satellite image interpretation. At least two time steps that cover the specified time period are

needed. Analysis of land-cover changes and the trajectories can be presented as a standardised

framework called ‘Analysis of Land-Use/-Cover Trajectories’ (ALUCT) and is based on interpreted

and classified satellite images. This procedures applied in ALUCT will result in several data needed

for the abatement cost curve analysis input in this REDD Abacus software such as land cover

classification, land cover change and the transition matrix.


The transition matrix resulted shows the quantity of land use transition that will affect the

estimate of national emission levels. That is why estimating land use system transition is essential

for REDD+ opportunity cost analysis. Past changes are calculated by comparing land use systems

from different years. Probable future land use trajectories can be determined by extrapolating past

changes and/or by developing land use models (see the simulation chapter).

The entire procedure of ALUCT is presented in figure xx.

Figure xx Overall workflow in ALUCT

Source: Widayati et al. 2010

Overall workflow will enable us to do some cross-tabulation of the two land cover map that result

in a land use change matrix (Table 1).

Table 1 Example of land-use change matrix

2001–2009 Forest (ha) Agroforest/mosaics (ha) Oil palm (ha) Total 2001

Forest 1000 2000 1000 4000

Agroforest/mosaics 500 500 2000 3000

Oil palm 500 500 2000 3000

Total 2009 2000 3000 5000 10000*

For the analysis using REDD Abacus the data inside land use change matrix then normalized to the

total area* of study in order to get the proportion of each land use changes (Table 2).

Table 2 Example of land use changes transition matrix

2001–2009 Forest (ha) Agroforestry/mosaics (ha) Oil palm (ha) Total 2001

Forest 0.1 0.2 0.1 0.4

Agroforest/mosaics 0.05 0.05 0.2 0.3

Oil palm 0.05 0.05 0.2 0.3

Total 2009 0.2 0.3 0.5 1


Every value inside the matrix represents the fraction (%) of land cover change per sub-national

zone (The sum of all cells within this equal to 1) in hectare (ha) unit.

Transition Matrix Data Input

How to go:

Click “Input”->”Spatial & Carbon Stock Data”->”Transition Matrix” button menu on the

main frame

Or


>”Spatial & Carbon Stock Data”->” Transition Matrix” (highlight the last child menu)

How to do:

Fill in the transition time scale on the top of the table

You can change the unit by selecting the dropdown menu on the top-left table. By default

the unit is in “Fraction Hectare”, the other option is in total “Hectare” unit.


Excel table)

The “Fraction Hectare” unit is good for controlling the total fraction (should be 1 in total)

For editing on actual hectare unit, select the unit dropdown menu on the top-left to

“Hectare” then you can start editing.

Note: you can leave the total area field on Zonation Setting empty and it can be filled up

automatically by the total area from this table.


Further Readings

Widayati A, Ekadinata A, Johana F and Said Z. 2010. Component C: Consequences of land-use change

for carbon emissions. Human Livelihoods, ecosystem services and the habitat of the Sumatra orang

utan: Rapid assessment in Batang Toru and Tripa. Bogor, Indonesia: World Agroforestry Center (ICRAF)

Southeast Asia Regional Program. (Available from:

http://www.worldagroforestry.org/Sea/Publications?do=view_pub_detail&pub_no=RP0270-11).

World Agroforestry Center 2009.Analysis of Land Use and Cover Trajectory (ALUCT). (Available from

http://www.worldagroforestrycentre.org/sea/projects/tulsea/inrmtools/ALUCT).

4.4 Carbon stock data

The stock-difference method builds on carbon stock inventories from land use changes to estimate

sequestration or emissions. Carbon stocks in each carbon pool are estimated by measuring the

standing stock of biomass at the beginning and at the end of the accounting period.

Within each land-use category, C stock changes and emission/removal estimations can involve the

five carbon pools that are defined in Table 6 (see appendix 4). For some land-use categories and

estimation methods, C stock changes maybe based on the three aggregate carbon pools (i.e.,

biomass, dead organic matter and soils). National circumstances may require modifications of the

pool definitions introduced in Table 6 (IPCC 2006).

Four main steps of C-stock changes estimation (Figure xx) are:

1. Estimation of time-averaged C-stock of each land use systems to determine the emission

factors, i.e., differences between time-averaged C-stock of original land use systems with

subsequences land use systems;

2. Quantification of activity data, i.e., areas of each transitions of land use/cover types;

3. Calculation of emission estimation based on the activity data from step B and emission factors

form step A;


http://www.worldagroforestrycentre.org/sea/projects/tulsea/inrmtools/ALUCT


4. Uncertainty analysis of the estimates.

Source: Ekadinata et al. 2010

Figure xx Four main steps of the C-stock-difference estimation from land use/cover changes

Further Readings

Ekadinata A, Rahmanulloh A, Pambudhi F, Ibrahim I, van Noordwijk M, Sofiyuddin M, Sardjono MA,

Rahayu S, Dewi S, Budidarsono S and Said Z. 2010. Carbon Emissions from Land Use, Land Use

Change and Forestry (LULUCF) in Berau District East Kalimantan, Indonesia. Bogor, Indonesia:

World Agroforestry Center (ICRAF) Southeast Asia Regional Program. (Available from:

http://worldagroforestry.org/sea/Publication?do=view_pub_detail&pub_no=RP0269-11).

Hairiah K, Sitompul SM, van Noordwijk M and Palm CA. 2001. Methods for sampling carbon stocks

above and below ground. ASB Lecture Note 4B. Bogor, Indonesia. International Centre for Research

in Agroforestry, SEA Regional Research Programme. 23p (Available from:

http://www.worldagroforestrycentre.org/sea/Publications/searchpub.asp?publishid=1003).

Intergovermental Panel on Climate Change. 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.). Published by IGES Japan (Available from:

http://www.ipcc-nggip.iges.or.jp/public/2006gl/vol4.html).

Sitompul SM, Hairiah K, van Noordwijk M and Palm CA. 2001. Carbon stocks of tropical land use

systems as part of the global C balance: effects of forest conversion and options for clean

development activities. ASB Lecture Note 4A. Bogor, Indonesia. International Centre for Research

in Agroforestry, SEA Regional Research Programme. 49p. (Available from:

http://www.worldagroforestrycentre.org/sea/Publications/searchpub.asp?publishid=1002).

Time-averaged carbon stock (c-stock)

The concept of time-averaged C-stock along with land use-systems are particularly developed to

suit the common patterns of land use trajectories in the tropical landscapes with a definite and

relatively short rotation. As an example, the traditional shifting cultivation cut across several

http://worldagroforestry.org/sea/Publication?do=view_pub_detail&pub_no=RP0269-11

http://www.worldagroforestrycentre.org/sea/Publications/searchpub.asp?publishid=1003

http://www.ipcc-nggip.iges.or.jp/public/2006gl/vol4.html

http://www.worldagroforestrycentre.org/sea/Publications/searchpub.asp?publishid=1002


different sequences of land cover types (e.g., secondary forest- cleared land- annual crop-shrub -

agroforest) and different land use and activities (e.g., non-timber forest product gathering, slashing

and burning-planting and harvesting of paddy-rubber tapping, rattan harvesting) within a

particular rotation period (e.g., 40 years, 60 years). Land use systems should be able to capture the

temporal dynamics of C-stock such that the typical or average C-stock across a system can be

calculated, which is known as time-averaged C-stock.

For the purpose of a REDD+ opportunity cost analysis, a value of time-averaged carbon stock is

needed for each land use. This single value is used for carbon accounting purposes and compared

with a single-value economic indicator of net present value (NPV) is necessary for each land use. A

time-averaged carbon stock value integrates the gains and losses over a life-cycle of a land use

(ton/ha or Mg/ha).

Time-averaged carbon stock data is normally obtained from measurements. The basic assumption

for area-based carbon-stock accounting is the carbon stock changes occurred within and between

land-use systems, each characterised as a fraction (ai) of total area (A) (the stratum weighting) and

with time-dependent carbon stock density Cit (the stratum mean). See the manual of RACSA

(Hairiah et. al. 2010) for further information about the method for calculating time-average carbon

stock.

Carbon Stock Data Input

How to go:

Click “Input”->”Spatial & Carbon Stock Data”->”Carbon Stock” button menu on the main

frame

Or


>”Spatial & Carbon Stock Data”->” Carbon Stock” (highlight the last child menu)

How to do:

Fill in the associated carbon stock data to the table. The unit is on Mg/ha or Ton/ha


Excel table)


Further Readings

Hairiah K, Dewi S, Agus F, van Noordwijk M, Rahayu S, Velarde SJ. 2010. Measuring Carbon Stocks

Across Land Use Systems: A Manual. Bogor, Indonesia. World Agroforestry Centre (ICRAF), SEA

Regional Office, Brawijaya University and ICALRRD (Indonesian Center for Agricultural Land

Resources Research and Development.

Hairiah K, Subekti R. 2007. Petunjuk praktis Pengukuran karbon tersimpan di berbagai macam

penggunaan lahan. World Agroforestry Centre, ICRAF Southeast Asia. ISBN 979- 3198-35-4. 77p.

(Available from:

http://www.worldagroforestrycentre.org/sea/Publications/files/manual/MN0035-07/MN0035-

07-1.PDF).

5. Economic Input Data

5.1 Net Present Value

Net present value (NPV) or sometimes called present value, is a calculation commonly used to

estimate the profitability of a land use over many years. NPV takes into account the time-value of

money. Since waiting for profits is less desirable than obtaining profits now, the “value” of future

profits is discounted by a specific percentage rate (White et al. 2010).

There are many land use systems involving perennials crops and thus constitute long term

investment. NPV measures profitability by addressing differently future costs and benefit streams.

NPV accumulates discounted revenues less costs of tradable inputs and domestics factors over the

period of calculation.

Tradable inputs consist of fertilizer, fuel and farming tools; while domestic factors are combination

of land, labor and management. Costs are defined by multiplying price with the quantity of each

items applied during the activities in the period of calculation.

The benefits consist of monetary outputs yielded by the land-uses activity along the period of cash

flow or analytic horizon. Each land-use activity has different outputs, single or varies –all outputs

should be monetary valued using appropriate prices.

The calculation of NPV is based on formula follows:

Source: Monke and Pearson, 1995

For brief explanation of NPV calculation see Table 3.

http://www.worldagroforestrycentre.org/sea/Publications/files/manual/MN0035-07/MN0035-07-1.PDF

http://www.worldagroforestrycentre.org/sea/Publications/files/manual/MN0035-07/MN0035-07-1.PDF


Table 3 Profitability of a land use within a period of time (Yn)

The NPV is the accumulation of discounted profit within a period of time (Y1……Yn= -100 + -50 +

20…+60). This calculation can also be done by Microsoft excel using following syntax:

“= NPV(discount rate; profit value)”

NPV of a land use activity over the period of calculation is appraised as profitable if NPV greater

than 0. In contrary, if the NPV less than zero is called unprofitable by definition. This does not

necessary mean that there are not positive cash flow. This situation means that it would be more

profitable to do other things with the land, labor and capital than to devote them to this activity.

Profitability can be assessed using both private and social values. If the calculation employs

financial prices so it called private profitability, while social profitability uses economics prices. So

what the different between financial and economics price?

Table 4 The different between financial (private) and economic (social) price

Private Profitability Social Profitability

Reflecting actual markets Reflecting economic efficiency

at national scale

Net return received by the land-use

operator, farmers

Potential net return

Show the competitiveness of

agricultural systems at given current

technology, output values, import

cost, policy transfer

Measure comparative advantage in

agricultural commodity system

Price used: actual market price Price used: world price

(Source: Monke and Pearson, 1995)

The differences private NPV and social NPV occurred because of either policy distortions, eg. taxes,

subsidy, import restrictions etc.

Y1 Y2 Y3 Yn

Total Cost 100 50 50 40

Total Benefit 0 0 70 100

Profit (Benefit-Cost) -100 -50 20 60


Cost Benefit Unit Input

How to go:

Click “Input”->”Economic Data”->”Cost Benefit Unit” button menu on the main frame

Or


>”Economic Data”->”Cost Benefit Unit” (highlight the last child menu)

How to do:

By default the Cost Benefit Unit is only for Private “price”

To add the Social price, click on “+” (plus) sign, and select the label “Social” on the add

dialog

You can define other or more “price” unit for the cost-benefit analysis


Net Present Value (NPV) Input

How to go:

Click “Input”->”Economic Data”->”NPV” button menu on the main frame

Or


>”Economic Data”->”NPV” (highlight the last child menu)

How to do:

Fill in the NPV on the available table for corresponding land use and zone


Excel table)

Further Readings

Monke EA and SR Pearson. 1995. The Policy Analysis Matrix for Agricultural Development. Cornell

University Press. Ithaca and London.

Pagiola S, B Bosquet. 2009. Estimating the Costs of REDD+ at the Country Level. Version 2.2, Forest

Carbon Partnership Facility World Bank. Washington D.C. 22p.

White D, Borner J, Gockowski J. 2010. Profits from land uses. In: White D and Minang P, eds.

Estimating the Opportunity costs of REDD+ A training manual. Washington, USA: World Bank

Institute. (Available from http://wbi.worldbank.org/wbi/Data/wbi/wbicms/files/drupal-


3.2.4 Conversion Cost-Benefit

Conversion Cost-Benefit calculates the surplus (benefit) or losses (cost) occurred due to land use change activity. Land use change may contribute to either negative or positive opportunity cost as a result of NPV differences. The land conversion itself may generate additional profits or losses, the profits are depend on whether the initial land cover yield additional benefit when it is converted to the other land cover, or it is even extra cost.




This Conversion cost-benefit is one of analysis performed in REDD Abacus in order to get the final value of land use change NPV. It represents in per hectare opportunity cost of each land use change. The surplus or benefit generated from land conversion should be added in the next land use activity. So that the final NPV is calculated based on the following formula: NPV final= NPVt2 - NPVt1 + NPVconversion benefit

A common case reflecting the benefit of land use change is in case of forest. Let us see the example

of land the conversion from undisturbed forest into log off forest. The estimated profits (expressed

in NPV) from undisturbed forest is $0/ha (NPVt1, see figure Ap 3 of Appendix 5) and profits from

log of mixed garden is $302/ha (NPVt2, see figure Ap 3 of Appendix 5). In this case there is

$1765/ha (see figure Ap.4 of Appendix 5) of additional benefit from the conversion of undisturbed

forest into commercial type (mixed garden). This additional benefit of conversion can be

approached using the profit from timber concession activity (HPH). Based on prior formula the

NPV final will be $2067/ha ($302/ha - $0/ha + $1765/ha= $2067/ha). In REDD Abacus this NPV

final must be multiplied by area fraction (ha, see figure Ap.5 of Appendix 5) and area transition

(fraction ha or % ha from total area, see figure Ap.6 of Appendix 5) in order to get the total NPV

changes ratio within the period of analysis (see figure Ap7. of Appendix 5).

Conversion Cost-Benefit Data Input

How to go:

Click “Input”->”Economic Data”->”Conversion Cost-Benefit” button menu on the main

frame

Or


>”Economic Data”->” Conversion Cost-Benefit” (highlight the last child menu)

How to do:

Fill in the associated conversion cost-benefit data to the table.

The default unit is on $/ha (average dollar per-ha area), however you change it to net value

($) by changing the unit option on top-left of the table to “$”.


Excel table)


Further Readings

Monke, E. A. and S. R. Pearson. 1995. The Policy Analysis Matrix for Agricultural Development.

Cornell University Press. Ithaca and London.

White D, Borner J, Gockowski J. 2010. Profits from Land Uses. In: White D and Minang P, eds.

Estimating the opportunity costs of REDD+ A training manual. Washington, USA: World Bank



6. Additional Emission

The emission from other sources which can’t be simply calculated from stock differences is

incorporated here. Emission from the peat, for example, may also come from root respiration and

peat decomposition. Additional emission from this kind of source is incorporated on “Belowground

Emission” matrix. While other additional emission from aboveground dynamic which may can’t be

simply calculated from stock differences is added to “Modified Emission” matrix.

6.1 Belowground Emission

Belowground Emissions, provides a way to examine the effects of including different carbon pools

within an opportunity cost analysis. Belowground emission is calculated based on the root

emission and soil carbon.

As measurement of root biomass is not simple (although there is a method that uses the root

diameter at stem base and allometric equations), normally there are several default assumptions

for the shoot:root ratio based on available literature (Cairns et al. 1997; Mokany et al. 2006).

Soil carbon consists of organic carbon, inorganic carbon, and charcoal. Inorganic in the forms of

carbonate usually exists in calcareous soils, but insignificant in neutral and acid soils. The main

form of the soil carbon is the soil organic carbon. Soil organic matter does not include forest litter.

Soil organic carbon differs greatly between peat soil and mineral soil. The main change in soil

carbon contents due to land use change is rarely larger than 20 Mg carbon ha-1 (IPCC, 1997;




Murty, et al. 2002), unless in wetland conditions. In case of that belowground emissions, which

typically occur at a slower rate, can be substantial, especially in peatlands.

Belowground Emission Data Input

How to go:

Click “Input”->”Additional Emission”->”Belowground Emission” button menu on the main

frame

Or


>”Additional Emission”->”Belowground Emission” (highlight the last child menu). See

Figure

How to do:

Fill in the associated belowground emission data to the table.

The default unit is on Mg CO2-eq/ha.year (average emission), however you change it to net

emission per year by changing the unit option on top-left of the table to “Mg CO2-eq/year”.


Excel table)

Further Readings

Cairns M A, Brown S, Helmer E H and Bumgardner G A,1997. Root biomass allocation in the world’s

upland forests. Oecologia, 111: 1-11. available at:

http://www.winrock.org/ecosystems/files/rootbiomassallocationintheworldsuplandforests1997.

pdf

http://www.winrock.org/ecosystems/files/rootbiomassallocationintheworldsuplandforests1997.pdf

http://www.winrock.org/ecosystems/files/rootbiomassallocationintheworldsuplandforests1997.pdf


Mokany K, Raison J R, and Prokushkin AS, 2006. Critical analysis of root-shoot ratios in terrestrial

biomes. Glob. Change Biol. 12: 84-96.

Page, S.E., F. Siegert, J.O. Rieley, H.V. Boehm, A. Jayak, and S. Limin, 2002. The amount of carbon

released from peat and forest fires in Indonesia during 1997. NATURE, VOL 420, 2002.

Parish, F., A. Sirin, D. Charman, H. Joosten, T. Minayeva, M. Silvius, and L. Stringer (Eds.). 2007.

Assessment on Peatlands, Biodiversity and Climate Change: Main Report. Global Environment

Centre, Kuala Lumpur and Wetlands International, Wageningen.

Wahyunto, Ritung S, Subagjo H. 2003. Peta Luas Sebaran Lahan Gambut dan Kandungan Karbon di

Pulau Sumatera 1990–2002. Bogor, Indonesia: Wetlands International, Indonesia Program and

Rapid assessment in Tripa and Batang Toru - 117 - Wildlife Habitat Canada (Available from:

http://www.wetlands.or.id/PDF/buku/Atlas%20Sebaran%20Gambut%20Sumatera.pdf).

6.2 Modified Emission

The emission may not come from stock differences only. The transition processes itself may

contribute a significant amount of emission that could be considered on REDD mechanism (?)

Other emission sources such establishment of transportation facility, energy consumption by the

factory or else, may should be accommodated here (?).

7. Output

7.1 Output Summary

7.1.1 Summary

The output summary is including average and total emission per-year (in Mg CO2-eq/Ha.Year and

Mg CO2-eq/Year), average and total sequestration per-year (in Mg CO2-eq/Ha.Year and Mg CO2-

eq/Year), average and total NPV (in $/Ha.Year and $/Ha), both with and without ineligible

conversion.

Output Summary

How to go:

Click “Output”->”Summary” button menu on the main frame

Or

Expands the tree menu on the tree menu frame (on the left side by default) on “Output”-

>”Summary” (highlight the last child menu). See Figure

And click “Summary” tab

How to do:

You can do copy method for copying the data to other application (ex. copy to MS Excel

http://www.wetlands.or.id/PDF/buku/Atlas%20Sebaran%20Gambut%20Sumatera.pdf


table)

7.1.2 Avoidable Emission

Avoidable emission shows how much emission reduction can be achieved at a specific carbon price

(cost threshold, in $/Mg CO2-eq) that is considered from the opportunity cost analysis.

Avoidable Emission

How to go:

Click “Output”->”Summary” button menu on the main frame

Or


>”Summary” (highlight the last child menu).

And click “Avoidable Emission” tab

How to do:

By default the Cost Threshold is 5 $/ Mg CO2-eq, you can changes this by clicking the

“Update” button, and changes the value on the input dialog.

The total avoidable emission is on the top of the table (may changes when the Cost

Threshold were modified)

You can changes the emission unit in either average (Mg CO2-eq/Ha.Year) or total per-year

(Mg CO2-eq/Year) by changing the unit option on the right side of avoidable emission

value.


The table is the list of the all conversion that is avoidable (it’s opportunity cost was under

the cost threshold defined)

To see the eligible conversion only, check the “Eligible Only” checkbox

You can do copy method for copying the data into other application, such as MS Excel table.

7.2 Abatement Cost Curve

An abatement cost curve compares the quantity of potential emission reductions with their costs.

The vertical axis represents the opportunity cost of the emissions (in monetary units per tCO2e),

and the horizontal axis depicts the corresponding quantity of reduction (often measured in million

tCO2e per year).

Figure 3.6 illustrates the above cases. The abatement level A* (on the horizontal axis) is the

quantity at which the carbon price P* (on the vertical axis) is equal to REDD+ costs. At this level of

abatement, the country receives a REDD+ payment the area of the rectangle 0P*mn. To reach this

level of abatement, it faces costs equal to the area under the abatement curve up to A*. The

difference between these costs and the REDD+ payment are a net benefit to the country (known as

a ‘rent’ or a ‘producer surplus’). Should a country reduce fewer emissions by less than this level

(for example, abatement level A1), it would give up some of this potential rent (the area of the

triangle tsm). Conversely, if the country chooses an abatement level higher than A* (for example,

A2), it will face additional costs that are not compensated by the additional REDD+ income (area

nmwv) (white et. al. 2010).


Figure 3.6 REDD+ rents and costs Source: White et al. 2010 .

This provides the answer of how much emission reduction can be achieved at a specific carbon

price that is considered from the opportunity analysis above. The answer to this question enables a

country to establish a reference emission level (REL) – a basis from which a country commits to

reduce emissions. The REL is an important component of REDD+ preparation because:

If a country reduces deforestation too little, it will miss opportunities to increase its net REDD+ revenues. or

It is possible for a country to reduce deforestation ‘too much’ – that is, to reduce deforestation at a cost that is higher than the compensation it receives through REDD+.

It is important to note, however, that agreements on payment mechanisms and associated rules have not yet been reached (Angelsen 2009). Thus, such REDD+ rents may not be structured exactly as explained above.

Abatement Cost Curve

How to go:

Click “Output”->”Abatement Cost Curve” button menu on the main frame

Or


>”Abatement Cost Curve” (highlight the last child menu).

How to do:

The chart shows an avoidable emission (vertical red-dashed line by default) at a specific

carbon price (cost threshold in horizontal red-dashed line by default)

Each bar represent one land use transition with their Emission (or Sequestration) in

horizontal dimension, and the Opportunity Cost in vertical dimension


The bars were sorted by Opportunity Cost value in ascending order

The positive horizontal length of the sorted bars is the total emission from all emitted

transition (and sequestration on negative horizontal axis)

The chart is fully customize, see Appendix xxx on how to customize the chart

Figure

Further Readings

Angelsen, A. 2008. How Do We Set the Reference Levels for REDD Payments? In A. Angelsen, ed.,

Moving Ahead with REDD: Issues, Options and Implications. Bogor, Indonesia: Center for International

Forestry Research (CIFOR).

Angelsen, A. 2009. What will REDD cost? Presentation Rainforest Foundation Norway (RFN). 18 June.

www.slideshare.net/amiladesaram/angelsen-rfn-redd-costs

White D, Minang P, van Noordwijk M, Hyman G. 2010. RED(D++) policy context. In: White D and Minang

P, eds. Estimating the Opportunity costs of REDD+ A training manual. Washington, USA: World Bank






7.3 Emission Matrix

Emission Matrix show the emission (or sequestration if the value is negative) of each land use

transition. The value is calculated from carbon stock changes of the transition, plus belowground

emission (if enabled) and plus modified emission (if enabled).

Emission Matrix

How to go:

Click “Output”->”Emission Matrix” button menu on the main frame

Or

Expands the tree menu on the tree menu frame (on the left side by default) on “Output”->”

Emission Matrix” (highlight the last child menu). See Figure

How to do:

The frame consist of four tabs:

1. Zone Partition: emission for each transition on every zones

2. Net Emission: net emission (total emission + total sequestration) for each land use

transition, combined for all zones

3. Total Emission: emission (positive value) for each land use transition, combined for all

zones

4. Total Sequestration: sequestration (negative value) for each land use transition,

combined for all zones

The default emission unit is Mg CO2-eq/Ha.Year, you can change it to total emission unit

per-year by changing the unit option on the top-left table to Mg CO2-eq/Year



7.4 Cost-Benefit Total

The Cost-Benefit Total Matrix show the total cost-benefit of each land use transition. The value is

calculated from NPV changes of the transition, plus conversion cost-benefit.

Cost-Benefit Total Matrix

How to go:

Click “Output”->” Cost-Benefit Total” button menu on the main frame

Or


Cost-Benefit Total” (highlight the last child menu). See Figure

How to do:


1. Zone Partition: cost-benefit value for each transition on every zones

2. Net Cost-Benefit: net cost-benefit (sum of cost-benefit value from all zones) for each

land use transition

3. Benefit: total positive cost-benefit value from all zones for each land use transition

4. Cost: total negative cost-benefit value from all zones for each land use transition

The default cost-benefit unit is $/Ha, you can change it to total cost benefit unit ($) by

changing the unit option on the top-left table to “$”.



7.5 Opportunity Cost

Opportunity Cost Matrix is the opportunity cost for a unit of emission for each land use

transition. The unit is $/Mg CO2-eq.

Opportunity Cost Matrix

How to go:

Click “Output”->”Opportunity Cost” button menu on the main frame

Or


Opportunity Cost” (highlight the last child menu).

How to do:


1. Zone Partition: cost-benefit value for each transition on every zones

2. Net OpCost: net opportunity cost (sum of opportunity cost value from all zones) for

each land use transition

3. Positive OpCost: total positive opportunity cost value from all zones for each land use

transition

4. Negative OpCost: total negative opportunity cost value from all zones for each land use

transition



8. Simulation

8.1 Simulation Scenario with ABACUS

Originally ABACUS aims to analyze the opportunity costs of changing land use systems per unit emitted

carbon from the conversions in the past. It is a retrospective analysis that reflects the actual changes

and what would have been the forgone opportunities, in term of financial benefit, if those conversions

were avoided. The analysis provides a simple, first approximation of quantitative indication of feasible

avoidable emissions were there incentive mechanisms in the past and that given that drivers of land

use changes do not change in the future, such that the land use changes in the future are stationary in

rates and trends, the level of avoidable emissions in the future resemble those in the past. While this

retrospective analysis is useful in itself in providing the entry point to the discussion on the feasibility of

compensation-based mechanism of climate change mitigation actions, the prospective analysis will be

providing us with valuable ex-ante analysis for planning purposes. In particular the analysis can serve as

the main tool to assess the trade-offs between AFOLU emissions and land-based development agenda

to be as basis of negotiation platform among multiple stakeholders to achieve inclusive, integrative and

informed low emission development strategy. ABACUS facilitates the prospective analysis in two ways:

- Assuming the process of land use changes are stationary in rates and trends, due to the fixed

amount of land and decreasing extent of forests, in absolute terms the conversion and

therefore the emissions will slow down. The prospective analysis should therefore take this into

account in projecting the emissions in the future based on the changes on the previous time

steps and also the avoidable emissions given a particular threshold level of compensation per

unit CO2-e emission

- Diverging factors that affect land use changes, e.g., some policy interventions, new economic

drivers, changes in demographic structures, environmental hazards, may lead to non-stationary

process of land use changes. In this case the rate and trends of land use transitions may be

altered either uniformly across the landscapes or variably among zones within the landscapes.

Some of these factors can be anticipated and combined with plausible policy interventions,

some scenarios can be developed and formulated into a land use plan policy which further

translated into anticipated extent and location of some particular land use transitions.

Simulating these scenario based on the existing landscape enables us to run the prospective

analysis on future emissions and avoidable emissions

Some examples of scenarios: halting deforestation within Conservation Area, establishing oil palm only

from shrubs under Non-Forest Land, avoiding conversion of rubber agroforest to oil palm, stopping

conversions on peatland.

Once the scenario of Reference Emission Level (REL) is set and simulated, ABACUS can help comparing

the projected emissions from different scenarios with REL scenario. Therefore how much emission

reduction can be expected in association to particular loss or gain in profits at the landscape level under

each scenario can be quantified. The analysis will help the government in facilitating the multi

stakeholder process of developing the land use planning for low emission development strategy

(LUWES) (reference).


Simulation

How to go:

Click “Simulation”->”Scenario”->”Generate Model” button menu on the main frame

Or

Expands the tree menu on the tree menu frame (on the left side by default) on

“Simulation”->”Scenario”->”Generate Model” (highlight the last child menu). See Figure

How to do:

Figure xx shows the frame for starting the simulation

Click on “Generate Simulation Button” for generating the scenario matrix

Define the number of iteration periods for the simulation

The frame will shows the options for modifying the scenario

See the next box for how to modifying the scenario


TIPS: you can right click on the one of the rows (period), and select “Check Out Project” to

get new independent Abacus Project based on the selected period. After, you can do

modification on the project and also start new simulation based on that project

independently

8.2 Technical notes for Simulating Scenario under ABACUS

The process of land use changes to be simulated follows Markov Chain, in which transition to land use

in the next time step only depends on the current land use and the probability of change. The

probability of each pair of land use class is compiled as Transition Probability Matrix (TPM), which in the

case of stationary land use change process derived solely from the past Land Use Transition Matrix

(LUTM).

1999 2009

Land use maps of two time steps

Land Use Transition Matrix

(in hectares)


Land Use Transition Matrix

(fraction)

Transition Probability

Matrix


The Transition Probability Matrix is calculated by normalize each row of Land Use Transition Matrix to

sum up to 1. The existing Land Use (L) in 1999 changed to Land Use in 2009 through the Transition

Probability Matrix (P), or mathematically it can be written as follows:

L(t+1) = L(t) x P(t)

where:

- L(t) is a row vector or fraction land uses at time t

- P(t) is the Transition Probability Matrix at time t

If the process of land use changes in the following time steps is stationary, the Transition Probability

Matrix is constant over time, i.e., P(t+i) = P(t) = P. Otherwise, we can apply some particular scenarios in

two ways:

- By altering the probability or rate of conversion from one particular land use type to another

through the modification of the Transition Probability Matrix at a particular time step

- By determining the converted areas (either in hectares or in fraction) in the future through the

modification of the Land Use Transition Matrix at a particular time step

As a default ABACUS always offer the constant TPM and L(t+1) based on the constant TPM; if we would

like to simulate stationary process scenario, then no modification is necessary. However, if we want to

simulate particular scenarios we need to modify either the TPM or the LUTM in hectares of LUTM in

fraction. As an illustration, a future scenario of enforcement of law through policy and action to halt

deforestation of Undisturbed forest for this particular landscape can be done by one of the following:

- Changing the first row of the TPM for t+1 or P(t+1) to


- Changing the first row of the LUTM for t+1 or L(t+1) to have all the total area of Undisturbed

forest in the first cell and all the rest in the first row zero

- Changing the first row of the normalized LUTM for t+1 or L(t+1) to 1 in the first cell and 0 for

the rest of the cells in the first row

Scenario of policy that allows establishment of oil palm only from shrubs can be captured by setting all

the cells in 5th column to 0 except for that in the 6th row, however those other rows which are affected

by the changes such that the sum is not equal to 1 anymore has to be adjusted. For the purpose of

REDD+, then for all forest classes and other land use types that has higher C-stock than Oil palm should

perhaps stay as they are, and therefore shift and add the number in each cell in the 5th column (except

for the 6th row) to the number in each associated the diagonal cell, e.g., for Logged-over forest (2nd

row), change the 5th column cell to 0 and add 0.1111 to the 2nd column, which becomes 0.4167+0.1111

= 0.5278.

Please note that most likely the scenarios are varied across zones. In the case of legal zoning of forest

as is in the Indonesian case, the conservation areas should have different scenarios from production

forest and from other, for instance. Zonation based on soil types, i.e., mineral soil and peatland could

be very instrumental in some areas in Indonesia where peatland is extensive and under threat while we

know that emissions caused by land use changes on peatland could be much higher than those in

mineral soils.

Transition Probability Matrix

How to go:

Click “Simulation”->”Scenario”->”Transition Probability Matrix” button menu on the main

frame

Or


“Simulation”->”Scenario”-> ”Transition Probability Matrix” (highlight the last child menu).

See Figure

If the frame is empty, see how to generate the model section (above)

How to do:

You can start to modify the scenario by editing the matrix table

The sum of each row values should be equal to 1 (slide the table to the right to see the total

of each row values)


Select the iteration period to be modified

After the editing the “Update Model” button (above the table) will become enabled

You should click the “Update Model” button after finishing the modification on that

iteration period

NOTE: if you plan to modify the scenario on more than one period, the modification should

be start from the earlier iteration period (otherwise, the modified scenario on the later

period will overwrote by the previous one)

TIPS: you can highlight the row header of a land use system and right click, then click “Set

no conversion” to set the No Conversion scenario from the highlighted land use system


Land Use Transition Scenario

How to go:

Click “Simulation”->”Scenario”->”Land Use Transition Scenario” button menu on the main

frame

Or


“Simulation”->”Scenario”-> ” Land Use Transition Scenario” (highlight the last child menu).

See Figure


How to do:

This scenario matrix is has the same role as the Transition Probability Matrix above,

except this using the actual land area size

The default unit is “Fraction Hectare”, thus the sum of all values in one zone matrix should

be equal to 1.

You can use the actual area in “Hectare” unit (change the unit option in top-left of the table)

for the scenario. But you might want to change it back to “Fraction Hectare” to check the

consistency

Select the iteration period to be modified

After the editing the “Update Model” button (above the table) will become enabled

You should click the “Update Model” button after finishing the modification on that


iteration period

NOTE: if you plan to modify the scenario on more than one period, the modification should

be start from the earlier iteration period (otherwise, the modified scenario on the later

period will overwrote by the previous one)

TIPS: you can highlight the row header of a land use system and right click, then click “Set

no conversion” to set the No Conversion scenario from the highlighted land use system

8.3 Simulation Output

The output of the simulation is provided for each of the time step and can be exported easily to

produce a family of curves of cumulative emissions during the period of simulation. These curves will

enable us to readily compare the expected emission reductions among different scenarios applied. On

the other hand the output also offers the total profit generated from changing land uses in the overall

landscape. Therefore if the Reference Emission Level scenario or Business As Usual Scenario or

Historical Projection has been set, then comparisons over emissions, emission reductions and

opportunity costs across multiple scenarios can be made.

Within our applications so far, only financial cost-benefit from land use systems is considered, while it

should be noted that total REDD+ costs are much larger than that, some is easier to quantify than

others. The limitation to financial cost benefit only within the existing applications is not inherent to the

software but more to the availability of data and analysis. Any economic opportunity cost and

implementation costs or any other quantifiable costs could be accommodated by ABACUS.

Simulation Output Summary

How to go:

Click “Simulation”->”Simulation Output”->”Summary” button menu on the main frame

Or


“Simulation”-> ”Simulation Output”->”Summary” (highlight the last child menu). See Figure


How to do:

The output summary has three tabs:

1. Total: shows the emission summary (as in the project output summary) per-period of

simulation (figure xx)

2. Cumulative: shows the emission summary in cumulative over the periods of simulation

3. Avoidable Emission: shows the avoidable emission over the period with single cost

threshold (carbon price)


On “Avoidable Emission” tab, you can changes the threshold by changing the value on the

available field (top of the table) and click “Update” button after to refreshing the avoidable

emission table

Other Simulation Output Matrix

How to go:

Click “Simulation”->”Simulation Output” button menu on the main frame

Or


“Simulation”-> ”Simulation Output”

How to do:

The output matrix has the same format as on the project output, except there were


separated into simulation periods

The output matrix including:

o Land Use Transition: shows the changes on land use transition over the simulation

periods (figure xx)

o Emission: shows the changes on emitted emission per-land use transition, over the

simulation periods

o Cost-Benefit Total: shows the changes on total cost-benefit per-land use transition,

over the simulation periods

o Opportunity Cost: shows the changes on opportunity cost per-land use transition, over

the simulation periods

APPENDICES

1. Example of Land Cover Categories

Table 1 below, present the example of land-cover catagories and respective definition used in one

of World Agroforestry Study in Tripa and Batang Toru study sites in Sumatra, Indonesia.

Table xx. Land-cover types and definitions

No. Land-use/-cover types

Description


1 Undisturbed forest Undisturbed forest is natural forest cover with dense

canopy, highly diverse species and basal areas. It has no

logging roads, indicating that it has never been logged, at

least not on a large scale, and is usually located in areas

with rough topography. Canopy cover of undisturbed forest

is usually >80%. In satellite images it is indicated by high

value of vegetation index and infrared spectrum channels

and lower value in visible spectrum channels.

2 Undisturbed swamp

forest

Similar to #1, but located in swamp environment and

normally with lower vegetation and canopy density

compared to lowland and mountainous forest.

3 Disturbed/degraded

forest

Natural forest area having been disturbed by logging or

other timber extraction or fire but still has relatively dense

tree cover and dense canopy. Canopy cover is around 20–

60%. Large trees with diameter >30 cm can be found.

4 Disturbed swamp

forest

Similar to #3, located in swamp environment.

5 Rubber agroforest Rubber agroforest is characterised by the presence of

rubber trees mixed with other tree species, which form a

stand structure similar to secondary forest. Rubber trees

typically account for less than 70% of the population of

trees above 10 cm dbh (diameter at breast height). When

the presence of non-rubber trees is dominant and the plot

is old enough, the area will be very hard to differentiate

from natural forest.

6 Mixed garden Mixed garden is a tree-based system with more than 30%

of the area consisting of various species of trees. Mixed

gardens are usually located relatively close to settlements

or roads.

7 Agroforest Agroforest is defined as a tree-based system mixed with

crops and other vegetation with a range of density and

diversity lower than but similar to mixed gardens; usually

also includes natural understorey vegetation. The location

is not limited by distance to any other land use.

8 Estate/plantation Monoculture plantation of tree crops and/or timber. Tree

canopy cover is around 30–50%.

9 Oil palm Monoculture plantation of oil palm planted by private

companies and local people.

10 Coffee agroforest Mixed cultivation system of coffee and shade trees, mostly

managed by local people; normally located close to

settlements.

11 Cleared land Area where trees have been cleared, which includes ex-


logging areas or slashed-and-burned areas prepared for

agriculture; vegetation cover is usually herbaceous

vegetation and/or grass.

12 Cropland Cropland is intensively cultivated land and is mostly

planted with annual crops such as staple food, vegetables,

fruit.

13 Shrubs, grass Area dominated by non-woody vegetation, which is usually

an ex-forest clearing area that undergoes natural secondary

regrowth. For old shrubs, there is a low cover of trees,

around 5% cover; but no trees with diameter >20 cm.

14 Settlement Settlement refers to built area (city or village), which

includes road, main road and/or logging road; for rural

settlement this includes home gardens immediately located

near the houses.

15 Water body Water body refers to an area covered with water, for

example, stream, lake, pond.

16 No data No data refers to unclassified area, clouds, and shadow

area.

The peat-land map was utilised to distinguish between swamp forest and lowland forest, as the

aboveground carbon-stock differs between these vegetation types.

2. What is carbon dioxide equivalent (CO2-eq)?

The major greenhouse gas associated with land use change is carbon dioxide (CO2). Carbon is approximately 46% of the biomass (per kilogram of dry weight) stored in trees and 57% of soil organic matter. When one unit of tree carbon is burned or otherwise decomposes, the carbon combines with two units of oxygen to produce one unit of CO2. Given the atomic weights of carbon (12) and oxygen (16), one unit of C is equal to 3.67 units of CO2 ((12+(2*16))/12)=44/12=3.67). Deforestation and degradation affect the production other greenhouse gases (GHGs) including nitrous oxide (N2O) and methane (CH4). They are more dangerous greenhouse gases. N20 and CH4 have 231 and 23 times higher global warming potential than CO2. To standardize the effect of different emissions, international convention measures greenhouse gas loading in terms of CO2 equivalents, represented by CO2-eq.

Source: IPCC, 2006.

3. Customizing the Abacus Chart

The chart shows the opportunity analysis in graphical curve. See section 7.2 for the chart interpretations. By default the chart shown as on figure below.


3.1 Setting the displayed component

You can customize the displayed value element by selecting the toolbar shown below.

The value elements that can be selected are:

Emission (positive X axis) Sequestration (negative X axis) Positive NPV (positive Y axis) Negative NPV (negative Y axis)

An example of value element selection shown below:

The legend box display can be toggle by selecting this toolbar icon:

The threshold line display can be toggle by selecting this toolbar icon:

Threshold value (and its line) can be modified by right clicking

the horizontal line and click “Set Threshold” on popup menu. Or


you can directly dragging the horizontal line (OpCost threshold) up and down.

Another display setting can be accessed through this toolbar icon: (Display Setting). The display

setting dialog shows the options for:

Whether you only want to display the eligible elements only

(eligible transition and zones)

Cost Benefit Unit options to display on the chart

The X axis unit can be selected either average emission unit (Mg

CO2-eq/Ha.Year) or total emission unit per-year (Mg CO2-

eq/Year). You can also customize the unit range.

The Y axis unit can be selected either on logarithmic scale (by

default) or normal scale. You can also customize the unit range.

3.2 Adding the bar label The curve bar of the chart represents one land use transition. The dimension is Emission (width) and

Opportunity Cost (height). The interesting transition can be recognized easily on the chart, either the

highest emitter or the biggest dimension in conjunction with the Opportunity Cost. To emphasize the

interesting bar, a label can be added to the chart for each of the bar.

To add label for the bar, highlight the selected bar and right click. Click the popup menu “Add Label” as

shown on the figure below.

The added label can be dragged, so you can compose the position of the label according to your

preference. The label can be removed again by right clicking the label and click “Remove Label” popup

menu. An example of chart with labels is shown below.


3.3 Customizing the chart format

The chart color, line style and font size can be customized by clicking the toolbar icon:

The format setting dialog shows the option for customized the format of:

X Axis: font and line format for the axis title and

numbering unit

Y Axis: font and line format for the axis title and

numbering unit

Bar Color: the legend color for the curve bars

Label: font and label shape color format

Legend: font style format

Threshold: font and line format for horizontal

and vertical line

Background: the background color only

All of the setting panels were similar for most of the same type setting. Here is described the common

setting that was available:

Font

You can define the font type, size and color. If necessary the font effect can also be applied. On each

there were font preview showing the changes you made automatically.

Line

Line format that can be modified are:

Line Size: the size of line in pixel


Line Format: the format definition using a pattern of array value, separated by semicolon (if it’s

empty than standard line format is used). The rule is as follows:

- one value i.e. “10”, means a dashed line with 10 pixel length for both line and space

segment

- two value i.e. “10;5”, means a dashed line with 10 pixel length of line segment and 5

pixel length of space segment

- more than two value i.e. “10;5;2;5”, means a dashed line with two order of line-space

segment with length each 10 and 5 pixel, followed by 2 and 5 pixel dash segment

Line Color: the color of the line that can be selected

using the color selector dialog

Shape

The shape format is combination of the line format setting

(as described above) as the format for border line and

additional of two field setting:

Fill Color: the color of the shape fill that can be

selected using the color selector dialog

Corner: the shape corner definition in pixel radius of rounded corner (set 0 for sharp corner).

The examples of corner setting shown below:

Bar Color

For the Bar Color setting it’s defined as a legend pattern

of shape color setting. The color will represent a

zonation legend color on the chart. You can define as

much as possible the color legend, click “+” (plus) sign

to add and “-“ (minus) sign to remove the color. The

default color pattern is available as selectable dropdown

menu under the legend color.


3.4 Setting the chart size and transferring the snapshot The chart can be transferred to other application by either using the saved image or clipboard copy

method. Click the toolbar icon (Save Image) for saving the image into commons image file format

such JPG, PNG, GIF or BMP. To get the best image quality, it’s suggested to save it in BMP file format

(bigger file size).

The chart can be copied into clipboard by clicking the toolbar icon (Copy Image), and you can paste

it into other application such MS Words, MS PowerPoint or an image editor (i.e. Photoshop, Gimp etc)

Notes: the chart snapshot that was saved or copied is the same size (in pixel) as showed on the

monitor.

To get bigger resolution of the snapshot, you can do the zooming method

by clicking toolbar icon (Zoom). The zoom dialog will shows the option

for zooming the chart size. The chart can be resized by percentage ratio or

using the pixel size definition. Click ok after the modification.

The chart can be zoomed in and out directly clicking the toolbar icon (Zoom In) and (Zoom Out).

The toolbar icon for the chart modification and snapshot transferring is shown below

GLOSSARY

Above ground biomass.

Biomass above the soil surface: trees and other vegetation.

Accounting stance.

The viewpoint from which costs and benefits are calculated. Typical accounting stances for

analyzing REDD+ initiatives are that of: an entire country, individual groups within a country, the

government, and global community.

AFOLU

Acronym for Agriculture, Forestry and Other Land Uses. Recommended by IPCC Guidelines (2006)

as a new term covering LULUCF (Land Use, Land Use Change and Forestry) and agriculture.

Area Fraction

Total of land use change area (ha) divided by a total size of a landscape

Below ground biomass.

Biomass below the soil surface: plant roots and other soil biota.

Allometric equation.

Scaling rule or equation that relates tree biomass (or similar properties) to stem diameter and/or

tree height.

Biomass.

The total mass of living organisms including plants and animals for a given area usually expressed

as dry weight in g m-2 or kg ha-1. Organic matter consisting of or recently derived from living


organisms (especially regarded as fuel) excluding peat. Includes products, by-products and waste

derived from such material. For most ecological research and for the purposes of this manual,

"biomass" is a vegetation attribute that refers to the weight of plant material within a given area.

Another commonly used term for biomass is "production" which refers to how much vegetation is

produced in an area.

Carbon dioxide equivalent.

A measure used to compare different greenhouse gases based on their contribution to radiative

forcing. The UNFCCC (2005) uses global warming potentials (GWPs) as factors to calculate carbon

dioxide equivalent.

Carbon pool.

A reservoir or subsystem which has the capacity to accumulate or release carbon. Examples of

carbon pools are forest biomass, wood products, soils and the atmosphere. The units are mass (kg

ha-1 or Mg ha-1).

Carbon stocks.

Total carbon stored (absolute quantity) in terrestrial ecosystems at a specific time, as living or

dead plant biomass (above and below-ground) and in the soil, along with usually negligible

quantities as animal biomass. The units are Mg ha-1.

Carbon stock change

The carbon stock in a pool can change due to the difference between additions of carbon and losses

of carbon. When the losses are larger than the additions, the carbon stock becomes smaller, and

thus the pool acts as a source to the atmosphere; when the losses are smaller than the additions,

the pools acts as a sink to the atmosphere.

Carbon sequestration.

The removal of carbon from the atmosphere and long-term storage in sinks, such as ocean or terrestrial ecosystems, through physical or biological processes, such as photosynthesis. Costs

Cost refer to the value in alternative uses of the factors of production used by a firm (labour

costs, material costs, capital costs). Costs may be fixed or variable.

Country-specific data.

Data for either activities or emissions that are based on research carried out on sites either in that

country or otherwise representative of that country.

Cropland

This category includes arable and tillage land, and agro-forestry systems where vegetation falls

below the threshold used for the forest land category, consistent with the selection of national

definitions

Deforestation

Most definitions describe deforestation as the long-term or permanent conversion of land from

forest to non-forest. In an annex to a decision made by the UNFCCC Conference of Parties (COP),

which serves as a meeting of the Parties to the Kyoto Protocol, deforestation is defined as ‘the

direct human-induced conversion of forested land to non-forested land’. The FAO defines

deforestation as ‘the conversion of forest to another land use or the long-term reduction of the tree

canopy cover below the minimum 10% threshold’. Definitions also stipulate minimum tree heights

(FAO: 5 m in situ) and minimum areas (FAO: 0.5 ha), and that agriculture must not be the dominant

use. But the definitions of minimum canopy cover, height and area vary from country to country.

Degradation


Changes within the forest which negatively affect the structure or function of the forest stand or

site, and thereby lower the capacity of the forest to supply products and/or services. In the context

of a REDD mechanism, forest degradation results in the net loss of carbon from the ecosystem. One

way to measure degradation is to measure the decrease

in the carbon stock per area unit (e.g. hectare).

Discount rate.

A rate reflecting a time-preference at which the value future profits are reduced in a multi-period

model.

Emissions.

The release of greenhouse gases and/or their precursors into the atmosphere over a specified area

and period of time (UNFCCC Article 1.4).

Forest5

Forest is a minimum area of land of 0.05 – 1.0 hectares with tree crown cover (or equivalent

stocking level) of more than 10 – 30 per cent with trees with the potential to reach a minimum

height of 2 – 5 metres at maturity in situ. A forest may consist either of closed forest formations

where trees of various storeys and undergrowth cover a high portion of the ground or open forest.

Young natural stands and all plantations which have yet to reach a crown density of 10 – 30 per

cent or tree height of 2 – 5 metres are included under forest, as are areas normally forming part of

the forest area which are temporarily unstocked as a result of human intervention such as

harvesting or natural causes but which are expected to revert to forest.

5 In the context of the Kyoto Protocol, as stipulated by the Marrakesh Accords, cf. paragraph 1 of the Annex to draft decision -/CMP.1 (Land use, land-use change and forestry) contained in document FCCC/CP/2001/13/Add.1, p.58.

Forest land

This category includes all land with woody vegetation consistent with thresholds used to define

forest land in the national GHG inventory, sub-divided at the national level into managed and

unmanaged and also by ecosystem type as specified in the IPCC Guidelines.6 It also includes

systems with vegetation that currently falls below, but is expected to exceed, the threshold of the

forest land category.

Good Practice.

A set of procedures intended to ensure that greenhouse gas (GHG) inventories are accurate in the

sense that they are systematically neither over- nor underestimates so far as can be judged, and

that uncertainties are quantified and reduced so far as possible. Good Practice covers choice of

estimation methods appropriate to national circumstances, quality assurance and quality control

at the national level, quantification of uncertainties and data archiving and reporting to promote

transparency.

Grassland

This category includes rangelands and pasture land that is not considered as cropland. It also

includes systems with vegetation that fall below the threshold used in the forest land category and

is not expected to exceed, without human intervention, the thresholds used in the forest land

category. This category also includes all grassland from wild lands to recreational areas as well as

agricultural and silvo-pastural systems, subdivided into managed and unmanaged, consistent with

national definitions.

Greenhouse Gases.


Are radiatively active trace gases in the atmosphere that trap infrared radiation. The earth absorbs

the sun’s short wave, ultraviolet radiation and emits long-wave, infrared radiation to outer space.

The absorption of radiation causes warming. How much infrared energy escapes to outer space is

strongly affected by the composition of the earth’s athmosphere, such as carbon dioxide (CO2),

methane (CH4), nitrous oxides (N2O), and chloroflourocarbons (CFCs) absorb some of this outgoing

infrared radiation.

Ground truth.

A remote sensing term referring to the actual condition of the Earth surface as determined by field

visits.

Intergovernmental Panel on Climate Change (IPCC)

Established in 1988 as a special body by the UN Environmental programme and the World

Meteorological Organization to provide assessments to policymakers of the results of ongoing

climate change research. The IPCC is responsible for providing the scientific and technological

foundation for the United Nations Framework Convention on Climate change (UNFCCC), primarily

through the publication of periodic assessment reports.

Kyoto Protocol

An agreement made in 1997 under the United Nations Framework Convention on Climate Change

(UNFCCC). Annex I countries that ratify this Protocol (categorized as Annex I countries) commit to

reducing their emissions of carbon dioxide and five other GHGs. The Kyoto Protocol now covers

more than 170 countries globally, but only 60% in terms of global GHG emissions. As of December

2007, the US and Kazakhstan are the only signatory nations not to have ratified the Protocol. The

first commitment period of the Kyoto Protocol

ends in 2012, and international talks began in May 2007 on the next commitment period.

Land cover.

The classification of the biophysical surface of the Earth, comprising vegetation, soils, rocks, water

bodies and areas built by humans.

Land use (LU).

The classification of human activities, occupation and settlement of the land surface; e.g., annual

crops, tree crops, plantations, urban, conservation area, etc.

Land use classification system.

A framework for organizing land uses according to characteristics that differentiate them and

make them unique (forests, agriculture, pastures, urban, etc)

Land use system (LUS).

Dynamic characteristics and interactions in activities across space and time on the Earth surface.

The word system refers to sequential cyclical changes that are part of a land use, such as the

crop/fallow rotation in shifting cultivation systems. For the sake of brevity, the term land use is

employed throughout the manual

Landscape.

A non-exact area of land. A portion of land or territory which the eye can comprehend in a single

view, including all the objects it contains.

Leakage.

Changes in emissions and removals of greenhouse gases outside the accounting system that result

from activities that cause changes within the boundary of the accounting system. There are four

types of leakage: activity displacement, demand displacement, supply displacement, and

investment crowding. If leakage occurs, then the accounting system will fail to give a complete


assessment of the true aggregate changes induced by the activity. (IPCC Special Report on Land

Use, Land Use Change and Forestry.

http://www.ipcc.ch/pdf/special-reports/spm/srl-en.pdf )

Necromass or Dead Organic Matter

The weight of dead organisms, usually expressed as g m-2 or kg ha-1. Necromass consists mainly of

plant litter. It is usually on the soil surface or in the soil, but some may take the form of standing or

attached dead material. Much of the transient or lag in response to rapid climate change by forest

ecosystems can be estimated by the difference between tree regeneration (tree natality) and tree

mortality. Annual necromass increments result from individual tree mortality within stands and

from largerscale disturbance and dieback events (fires, insect infestations, disease infestations,

wind throw). In addition, a significant portion of the carbon stocks which comprise stored

terrestrial carbon of forest and non-forest communities is in the form of necromass.

Net emissions

In REDD+, net emissions are estimates of emissions from deforestation that consider both the

carbon stocks of the forest being cleared and the carbon stock of the replacement land use.

NPV (Net Present Value) The present value of an investment's future net cash flows minus the

initial investment.

Net returns. See profit.

Opportunity costs (REDD+) Refers to the difference in net earnings from conserving or enhancing forests versus converting them to other, typically more valuable, land uses. Opportunity cost analysis provides money-based estimates of how different stakeholders and sectors of the national economy would be affected by REDD policies and payments. They are an important part of a national planning process. Organic matter (or organic material).

Matter that has come from a once-living organism; is capable of decay, or the product of decay; or

is composed of organic compounds.

Other land (as a land-use category)

This category includes bare soil, rock, ice, and all unmanaged land areas that do not fall into any of

the other five categories. It allows the total of identified land areas to match the national area,

where data are available.

Peatland.

Peatland is the land rich in partly decomposed plant remains, with organic C of >18% and

thickness of >50 cm. Peatland is intrinsic to many wetlands around the world. The tropical peat is

about 1 to 7 m thick and at places it can be 20 m thick. Moss, grass, herbs, shrubs and trees may

contribute to the buildup of organic remains, including stems, leaves, flowers, seeds, nuts, cones,

roots, bark and wood. Peat forms in wetlands or peatlands, variously called bogs, moors, muskegs,

pocosins, mires, and peat swamp. Through time, the accumulation of peat creates the substrate,

influences ground-water conditions, and modifies surface morphology of the wetland.

Profit. Net returns, or revenues minus costs.

Reducing emissions from deforestation and forest degradation (REDD and REDD+)

REDD refers to mechanisms currently being negotiated under the UN Framework Convention on

Climate Change process to reduce emissions from deforestation and forest degradation in

developing countries. REDD+ includes enhancement of forest carbon stocks, that is, ‘negative

degradation’ or ‘removals’ on land classified as forests. As used in this book, REDD+ does not

include afforestation and reforestation (A/R).


Reforestation

Reforestation is ‘the direct human-induced conversion of non-forested land to forested land

through planting, seeding and/or the humaninduced promotion of natural seed sources, on land

that was forested, but that has been converted to non-forested land’. In the first commitment

period of the Kyoto Protocol, reforestation activities have been defined as reforestation of lands

that were not forested on 31 December 1989, but have had forest cover at some point during the

past 50 years.

Remote sensing

Practice of acquiring and using data from satellites and aerial photography to infer or measure

land cover/use. May be used in combination with ground surveys to check the accuracy of

interpretation

Removals. Removal of greenhouse gases and/or their precursors from the atmosphere by a sink. Rent.

Also known as economic rent or producer surplus. The value that producers obtain when actual

price exceeds the minimum price sellers will accept. In a REDD+ context, rent is the different

between the international price of carbon and REDD+ costs.

Sequestration

The process of increasing the carbon content of a carbon pool other than the atmosphere. It is

preferred to use the term “sink”.

Sink

Any process, activity or mechanism which removes a greenhouse gas, an aerosol, or a precursor of a greenhouse gas from the atmosphere. (UNFCCC Article 1.8). Notation in the final stages of reporting is the negative (-) sign. Settlements

This category includes all developed land, including transportation infrastructure and human

settlements of any size, unless they are already included under other categories. This should be

consistent with the selection of national definitions.

Stratum.

One of the two or more mutually exclusive subgroups of a frame. The singular of strata.

Wetland.

Land where an excess of water is the dominant factor determining the nature of soil develop.

Zone

Biophysical and/or non biophysical factors that affect the variation of carbon stock and economic

profitability in a landscape.

REFERENCES

Agus F, Hairiah K, Sandra V, van Noordwijk M. 2010. Chapter 5 Carbon Measurement of Land Uses:

Estimating the Opportunity costs of REDD+ A training manual. Washington, USA: World Bank

Institute (Available from http://wbi.worldbank.org/wbi/Data/wbi/wbicms/files/drupal-


Angelsen, A. 2009. What will REDD cost? Presentation Rainforest Foundation Norway (RFN). 18

June. www.slideshare.net/amiladesaram/angelsen-rfn-redd-costs




Ekadinata A, Rahmanulloh A, Pambudhi F, Ibrahim I, van Noordwijk M, Sofiyuddin M, Sardjono MA,

Rahayu S, Dewi S, Budidarsono S and Said Z. 2010. Carbon Emissions from Land Use, Land Use

Change and Forestry (LULUCF) in Berau District East Kalimantan, Indonesia. Bogor, Indonesia:

World Agroforestry Center (ICRAF) Southeast Asia Regional Program (Available from:

http://worldagroforestry.org/sea/Publication?do=view_pub_detail&pub_no=RP0269-11).

Intergovermental Panel on Climate Change [IPCC]. 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.). Published by IGES Japan (Available

from: http://www.ipcc-nggip.iges.or.jp/public/2006gl/vol4.html).

International Panel on Climate Change [IPCC]. 2003. Good Practice Guidance for Land Use, Land-Use

Change and Forestry. Chapter 3 & 4 (Available from: http://www.ipcc-

nggip.iges.or.jp/public/gpglulucf/gpglulucf_contents.html).

Intergovernmental Panel on Climate Change [IPCC]. 1997. Revised 1996 IPCC Guidelines for

National Greenhouse Gas Inventories –Workbook (Volume 2) (Available from: http://www.ipcc-

nggip.iges.or.jp/public/gl/invs1.html).

Monke, E. A. and S. R. Pearson. 1995. The Policy Analysis Matrix for Agricultural Development.

Cornell University Press. Ithaca and London.

Murty D, Kirschbaum MUF, McMurtrie RE, McGilvray H. 2002. Does conversion of forest to

agriculture land change soil carbon and nitrogen? A review of the literature. Global Change

Biology 8, 105-123.

Stern N. 2007. The economics of climate change: The Stern review. Cambridge, UK: Cambridge

University Press (Available from

http://webarchive.nationalarchives.gov.uk/+/http://www.hm-

treasury.gov.uk/stern_review_report.htm).

Swallow BM, van Noordwijk M, Dewi S, Murdiyarso D, White D, Gockowski J, Hyman G,

Budidarsono S, Robiglio V, Meadu V, Eka Dinata A, Agus F, Hairiah K, Mbile P, Sonwa DJ, Weise S.

2007. Opportunities for Avoided Deforestation with Sustainable Benefits: An interim report of the

ASB partnership for the Tropical Forest Margins. Nairobi: ASB Partnership for the Tropical

Forest Margins. Working Paper 42 (Available from

http://www.worldagroforestry.org/sea/Publications/searchpub.asp?publishid=1784).

van Noordwijk M, Tata HL, Ekadinata A, and Mulyoutami E 2010. Component D: Oppurtunity costs

of emission reduction. In: Tata HL, van Noordwijk M, eds. Human livelihoods, ecosystem services

and the habitat of the Sumatra orang utan: rapid assessment in Batang Toru and Tripa. Bogor,

Indonesia: World Agroforestry Center (ICRAF) Southeast Asia Regional Office.

White D, Borner J, Gockowski J. 2010. Profits from Land Uses. In: White D and Minang P, eds.

Estimating the opportunity costs of REDD+ A training manual. Washington, USA: World Bank



White D, Minang P, van Noordwijk M, Hyman G. 2010. RED(D++) policy context. In: White D and

Minang P, eds. Estimating the opportunity costs of REDD+ A training manual. Washington, USA:

World Bank Institute. (Available from

http://worldagroforestry.org/sea/Publication?do=view_pub_detail&pub_no=RP0269-11

http://www.ipcc-nggip.iges.or.jp/public/2006gl/vol4.html

http://www.ipcc-nggip.iges.or.jp/public/gl/invs1.html

http://www.ipcc-nggip.iges.or.jp/public/gl/invs1.html

http://webarchive.nationalarchives.gov.uk/+/http:/www.hm-treasury.gov.uk/stern_review_report.htm

http://webarchive.nationalarchives.gov.uk/+/http:/www.hm-treasury.gov.uk/stern_review_report.htm

http://www.worldagroforestry.org/sea/Publications/searchpub.asp?publishid=1784




http://wbi.worldbank.org/wbi/Data/wbi/wbicms/files/drupal-


White D, Minang P, Swallow B 2010. Introduction. In: White D and Minang P, eds. Estimating the

opportunity costs of REDD+ A training manual. Washington, USA: World Bank Institute.

(Available from http://wbi.worldbank.org/wbi/Data/wbi/wbicms/files/drupal-


Widayati A, Ekadinata A, Johana F, and Said Z 2010. Component C: Consequences of land-use

change for carbon emissions. In: van Noordwijk M. and Tata HL, eds. Human Livelihoods,

ecosystem services and the habitat of the Sumatra orang utan: rapid assessment in Batang Toru

and Tripa. Bogor. Indonesia: World Agroforestry Center (ICRAF) Southeast Asia Regional Office

(Available from:

http://www.worldagroforestry.org/Sea/Publications?do=view_pub_detail&pub_no=RP0270-

11).







redd abacus sp - world agroforestry centre system such as windows, linux or mac. 1.2 the minimum...

Documents