This file was created by scanning the printed publication.
Errors identified by the software have been corrected;
however, some errors may remain.
Some Methodological Approaches to
Estimate and Monitor Carbon Mitigation
in the Forestry Sector1
Ben H.J. de Jong2
Abstract-Forestry and agroforestry are promlsmg land-use
alternatives for reducing the increasing levels of global atmospheric
carbon. To understand the role of forestry and agroforestry systems
in the carbon cycle it is necessary to quantify both the net annual
carbon fluxes and the total carbon content of the systems. The effect
of a forestry project has to be compared with a "business as usual"
baseline.
There exist various methodological approaches to estimate the
impact on carbon fluxes of forestry and agroforestry. Known problems of baseline assumptions, carbon flux reporting, and monitoring and verification are exemplified with field collected data and
recent experiences of the Scolel Te Pilot Project for Community
Forestry and Carbon Sequestration in Chiapas, Mexico (Scolel Te
1998). The "Greenhouse Gas Bubble (GGB)" concept as an alternative instrument for carbon offset trading and reporting is discussed.
The third Conference of the Parties to the United Nations
Framework Convention on Climate Change (UN-FCCC),
held in December 1997 in Kyoto, Japan describe two marketbased mechanisms that will allow countries to trade in
greenhouse gas emission (GHG) reductions:
1. Between two Annex 1 countries (countries with binding emission limits), known as Joint Implementation (JI),
and
2. Between an Annex 1 country and a non-Annex 1
country (countries with no binq.ing emission limits, mainly
developing countries), known as Clean Development Mechanism (CDM).
The existence of carbon offsets in low-cost countries and
demand in obligated high-cost countries may create a market for the buying and selling of GHG offsets. Under a
possible future carbon offset trading program, countries
would be most likely to pay for such reductions in another
country where the cost for reducing emissions is lower.
Al though forestry measures are not yet specifical:~l incl uded
within the current articles relating to the CDM , it seems
likely that provisions for forestry will be included at some
stage, given the significance of developing country forests
Ipaper presented at the North American Science Symposium: Toward a
Unified Framework for Inventorying and Monitoring Forest Ecosystem
Resources, Guadalajara, Mexico, November 1-6,1998.
2 Ben H.J. de Jong is Research Scientist at El Colegio de la Frontera
Sur (ECOSUR), located in San Cristobal de las Casas; 29290 Chiapas,
Mexico. e-mail:bjong@sclc.ecosur.mx
3 There is some debate on the interpretation of the Kyoto protocol relating
to forestry. One particular discussion is whether forests are specifically
excluded from the CDM.
130
within the global carbon cycle. Several studies have indicated that the global potential for enhancing carbon (C)
storage by forestry and agroforestry may be as much as
60-90 x 109 tons of C (tC, Dixon et al. 1991; Winjum et al.
1992; Dixon et al. 1993; Trexler and Haugen 1994; Brown et
al. 1995). Forestry and land-use mitigation measures can
serve other environmental, economic, and social interest
simultaneously, and may offer some of the most costeffective ways to climate change mitigation. GHG offset
projects in the land use and forestry sector can particularly
be attractive if they can be tied to local social and economic
goals (Trexler 1993).
In Mexico, the forestry sector is a key element in any
national greenhouse emissions mitigation plan. Currently,
land use /land cover (LUILC) change is the second source of
C emissions to the atmosphere, accounting for an estimated
35% of total emissions. However, the forestry sector has the
potential to convert Mexico from a net carbon source to a
carbon sink, if proper actions are taken (Masera et al. 1997).
Using forests as a means of mitigating climate change
could be achieved both by conserving existing stocks of C
in forests that are currently threatened, and by creating
new stocks in growing trees.
In forestry, as with other types of activities, the net effect
of a project is the difference between the project scenario and
a baseline, reference, or "business-as-usual" case (Fig. 1).
Calculating emission reductions associated with a project
scenario present certain difficulties in land use because
carbon fluxes from vegetation and soil are complex, bidirectional and continuous. A number of methodological and
policy questions need to be addressed before forestry carbon
offset trading can provide reliable, verifiable emission reductions (Tipper & De Jong 1998). This paper discusses
some of the methodological approaches related to the quantification of carbon sequestration in forestry projects:
• Establishment of baseline assumptions
• Accounting procedures to quantify the effect of forestry
projects on carbon budgets
• Monitoring and verification of project performance
The following sections illustrate the effect of the different approaches applied to address these problems. Where
necessary, particular reference is made to the Scolel Te
Pilot Project for Community Forestry and Carbon Sequestration in Chiapas, Mexico (Scolel Te 1998) and the results
of an assessment ofthe cost of a large-scale forestry program
for CO 2 sequestration (Tipper et al. 1998). The "Greenhouse
Gas Bubble (GGB)" concept as an alternative instrument
for carbon offset trading and reporting in the forestry sector
is discussed.
USDA Forest Service Proceedings RMRS-P-12. 1999
Expected
accumulation of
carbon through
Average accumulation
project
through project
Net average
project effect
Average Baseline
~
Figure 1.-Hypothetical effect of a C mitigation project, compared to a "business-as-usual"
baseline.
Baseline Assumptions
The definition of a suitable baseline or reference case
involves the elaboration of a hypothetical or counterfactual
scenario. Differences in the order of a single percentage
point in the assumed rate ofloss of current carbon storage in
the baseline assumption can halve or double the perceived
net effect of a given intervention over the course of a 60 year
. time frame. As such, the interests at stake are considerable.
Since both the buyer and the seller of a carbon offset have
interest in a high net effect of a project, they may exaggerate
the baseline assumption, unless some form of regulatory
mechanism is used to counterbalance these interests.
The main problem to establish a baseline within the LUI
LC sector relates to the prediction offuture changes. This is
particularly difficult, because the proximal causes and driving forces behind land-use decisions are diverse, interrelated, and often discontinuous. At regional levels, factors
such as demographic changes and government policies often
have significant effects. At specific locations, uncertainties
about land ownership, social conflicts, the impact of development projects, crop failure and fires can cause unpredictable
changes in land-use decisions among farmers (De J ong et al.
1998). Methods used are either extrapolations of past rates
of change of carbon stocks into the future (trend-based
models), or process-based models that attempt to simulate
the demographic and economic processes driving land-use
change (Brown et al. 1989; Faeth et al. 1994; Fearnside and
Malheiros-Guimaraes 1996; De Jong et al. 1998). One problem with trend-based predictions is the influence of the
geographic domain used in the assessment-if the domain is
restricted to areas where deforestation has been rapid in
the past, then the baseline loss of carbon will appear high.
Where records show considerable variations in the rate of
LUILC change over time and/or space, it is not obvious
which scenario will be most likely in the future (Box 1).
Another approach is to apply process-based models. Although these models may be capable of assessing the
USDA Forest Service Proceedings RMRS-P-12. 1999
relative vulnerability of different categories of vegetation,
they generally require large investments in data collection
to make credible representations of land-use change processes. In densely populated areas where various factors
influence local and regional land-use decisions, if will be
difficult to define which factor is the main driving force
behind the L UILC change dynamics. Rudel and Roper (1997)
tested various factors that are thought to contribute to deforestation in the tropics for 68 tropical countries. The factors
they tested are, among others, population pressure, economic
growth, and national land-use policies. Based on their results, they distinguish two types of deforestation processes:
1. a frontier model, characterized by the opening up of new
areas, and
2. animmiserization model, characterized by a continuous
fragmentation and deforestation in densely populated areas, dominated by resource-poor farmers.
Both processes occur simultaneously in Chiapas. In the
densely populated Highlands ofChiapas, the immiserization
process dominates, while the frontier model prevails in the
nearby tropical lowland forests of the Selva Lacandona.
Thus, land-use policies may have a positive effect in one
region, but can create negative impacts in the other region.
In fact, during the 70's the Mexican government promoted
the frontier model in the Selva Lacandona region at least
partly to reduce the immiserization process in densely
populated areas. This makes the development of a general
process-based land-use model complex and very sensitive
to variations between regions. As such, it is most likely
that reliable process-based models that explain land-use
decision-making will first be developed on a regional scale.
On a project scale, baseline assumptions can also cause
major problems in relation to credibility and probability.
For example, forests not facing any threat cannot claim C
offset (Trexler 1993). However, if forests do present threats,
how to guarantee that the exploitative action that threatens
the forest is not simply displaced to another area?
131
100
% of
1996
C stock
80
15
9
Comllas
i
i
60
1984 1990 1996
J--1996
A
2016
2006
2026
B
Figure A is based on the interpretation of satellite images of 1974, 1984, 1990 (MSS), and
1996 (TM) of an area of approximately 300,000 ha in the highlands of Chiapas. For each
major LU/LC class C-densities were measured in 39 field plots. To project possible C loss in
the future, the C-density of the completely deforested LU/LC classes (agriculture, pasture and
settlements) were assumed to have lost all the vulnerable C stock, thus their C density was
set to O. From the C densities of all other classes the average C density of the completely
deforested LU/LC classes was subtracted to estimate the C pools that were prone to be lost
through LU/LC change (So called vulnerable C). The C density of each LU/LC class was
incorporated in the LU/LC statistics to calculate the decrease in C stock during the periods
1974-1984,1984-1990,1990-1996, and 1974-1996. The highest, lowest and average
decrease in C-stock, expressed in % per year was used to predict future trends in vulnerable
carbon storage. Depending on the rate of C storage depletion, in 2050 the expected C stock
fluctuates between.3 and 15 x 106 tC.
Figure B is based on the comparison of LU/LC between an historical vegetation map (which
was elaborated through interpretation of aerial photographs of the 1970s) and the
interpretation of a 1996 TM satellite image. C densities of the major LU/LC classes were
collected in 29 field plots. C densities and LU/LC statistics were then used to derive estimates
of change in carbon stocks, as expressed in % per year, for the whole region and separately
for the three SUb-regions, using natural or political boundaries as the separation criteria. The
Northern region and Marques de Comillas present the highest depletion in carbon stock,
whereas the carbon stock in the Lacandon Community remains almost unchanged. The first
two regions are subject to government induced settlement programs, whereas the Lacandon
Community, which contains the Montes Azules Biosphere Reserve, is subject to government
conservation efforts. Total C stock in The Nothern Region and Marques de Comillas would
decrease with about 35 % in the next 30 years, while the stock in the Lacandon Community
would reduce with about 5 % in the same period. C stock for the whole region would
decrease with about 20%.
132
USDA Forest Service Proceedings RMRS-P-12. 1999
Carbon Fluxes in Managed
Systems _ _ _ _ _ _ _ _ __
Various carbon accounting procedures exist to explain
the system C dynamics, relative to a baseline (Tipper and
De Jong 1998). All accounting procedures are somehow
based on flux models that try to estimate temporal changes
in carbon pools and fluxes between pools (Box 2).
The results of the flux estimation can be reported as:
• Yearly fluxes between the vegetation and the atmosphere (expressed in tC/year) or the sum of the yearly
fluxes at a given cut-off date (expressed in tC, Nabuurs
and Mohren 1993, 1995; De Jong et al. 1995,1998).
• Long-term average increase in the carbon stock of a
managed stand relative to a hypothetical baseline (expressed in tC, N abuurs and Mohren 1995; De J ong et al.
1998).
• Cumulative carbon storage (expressed in tC.years,
Tipper and De Jong 1998).
Yearly Fluxes
This method is conceptually the simplest way to provide carbon offsets to reduce emissions. In this procedure
changes in pools and fluxes between pools are calculated and
presented on a yearly basis. One ofthe main shortcomings of
this approach is related to the fact that carbon fluxes in
The C flux models C02FIX, developed by Nabuurs and Mohren (1993) and GORCAM, developed by
Schlamadinger and Marland (1996) derive carbon accumulation and storage by a tree plantation over the
course of a number of rotations, based on an "expected growth" curve. Adjustments can be made for product
lifetime. Soil C fluxes generally are simulated by a litter, humus and deadwood decomposition fraction and a
litter humification factor. Tree mortality, leaf, branch and root turnover rates, and harvesting can change the
living biomass, while decomposition, humification and burning are factors that can affect dead biomass and
product pools. In GORCAM, part of the medium and long lived products can be assigned to energy, when a
fuel substitution factor is used (Schlamadinger and Marland, 1996).
USDA Forest Service Proceedings RMRS-P-12. 1999
133
forestry ecosystems are irregular and bi-directional. In the
simplest case, a plantation system generally shows a slow
uptake of carbon during the growing cycle and high emissions shortly after harvesting (Fig. 2). If the offset trading
assign credits on the yearly flux basis, what to do with the
negative flux (emission) after harvesting?
An economic assessment of the effect of a forestry project
based on yearly fluxes requires the summation of the flows
over a specific period of time, to derive a total expressed in
tC. In the case of conservation of forest reserves, this is
rather straightforward, as this alternative prevents a oneoff release of carbon. However, when the management
scheme includes periodic harvesting of (part of) the stand,
the total C accumulated will depend largely on the relationship between rotation length and the time horizon set as the
project limit. The buyer of the offset credits will prefer to set
the time horizon just before harvesting, whereas the carbon
offset will be at least partly lost when harvesting takes place.
:r " '.
Long-Term Average Increase
Many projects in the pilot phase of the UN-FCCC program
of Activities Implemented Jointly are assessed on the basis
of the long-term average increase in the carbon stocks
relative to the baseline, expressed in tC (Fig. 2, Tipper and
De Jong 1998). This approach assumes a long-term maintenance of the alternative system, calculates the yearly fluxes
related to C dynamics and estimates the average effect ofthe
system on a long time horizon (typically 100-150 years).
250
Stock
150
250
nnrmm6
1111111111111
m1TI'
Baseline
100
200
. 150
100
Tei
50
----------:-Acc ----- ------- ----
_. --- _. ----- --- -- ---------- ----- ----- -- --- -- ---------- -~A-v
o
------
--~,.,.,.",...----
a
20
60
40
10
-20
The cumulative carbon storage approach is based on the
expected lifetime of carbon emissions and radiative forcing
of the CO 2 in the atmosphere (See Tipper and De Jong 1998
for the theoretical explanation of this approach). It assumes
that most of the CO 2 emitted at the present will be absorbed
within a time scale of about 100 years, and that the cumulative radiative forcing produced by the emission will be
proportional to the area under the depletion curve, expressed in tC.years. Calculation of this area provides an
estimate of the cumulative carbon storage that would be
required to offset an emission of 1 tC at the present time
(About 50 tC.years per tC emission). To apply the tC.years
to tC conversion factor to forestry projects, a cut-off date
needs to be defined that will limit the amount of credit that
can be obtained from a given project activity. A cut-off date
~
~lllIlllilill
200
-10
Cumulative Carbon Storage
Plantation
TC/ha
0
Some of the major shortcomings of this accounting system is that it is not compatible with national level emission
reporting so that additional inventory work would be required to reconcile the reporting systems and that the
performance ofthe system over such long time horizons will
be difficult to estimate and that various insurance mechanisms have to be developed in case the system fails within
the time horizon. This approach is attractive since up-front
investment may be credited in expectation of future increases in terrestrial carbon stocks. In fact, this approach
currently applies to the Scolel Te Pilot Project (Scolel Te
1998).
80
Yearly flux
I
r:=:==::
~
v-
,.....-==-::
v
Yr
50
a
100
-----
Figure 2.-Graphical representation of the various accounting procedures to explain the system C dynamics, relative to a
baseline. Stock = accumulated carbon in the system; TC I = emission offset in tC, using the cumulative carbon storage
approach; Av. Acc =long-term average accumulation increase of C in the system, relative to the baseline; Yearly flux =net
yearly C flux of the system.
134
USDA Forest Service Proceedings RMRS-P-12. 1999
in the order of 100 years has already been applied to various
projects assessed on the average stock increase approach
and seems also rational for the cumulative carbon storage
approach. Even if the system is broken off before the cut-off
date, it still contributes to the overall radiative forcing
reduction, and the amount oftC emission offset obtained up
till then can be calculated with the following formula:
tC emission offset in year i = Li (Cacc,i - Cbase) / Conversion Factor
Where Cacc,i is the C accumulated in the alternative system
and Cbase,i the C accumulated in the baseline, both in year i
(Fig. 2). This approach is attractive as it resolves the accounting problems between emissions and uptake and there
is no need to assume the conditions for indefinite sustainability of an equilibrium state of forest management (For a
discussion on the advantages and disadvantages of this
approach see Tipper and De J ong 1998). The a pproach is also
in line with the global climate change concern: the greenhouse effect of certain gases in the atmosphere. This approach would require international agreement on the conversion factor. Once agreed upon, it needs to be reviewed
periodically to take into account changes to the nature of
the sinks due to climate change and land cover change, such
as change in ecosystem productivity through climate change
and CO 2 fertilization.
Monitoring and Verification
Notwithstanding the overwhelming literature available
about potential biotic mitigation measures, there is still a
large gap between accepting that C fluxes can in fact be
modified to help mitigate climate change and accepting
that this modification can take the form of individual
projects that can be monitored and verified as part of a C
emissions control system (Trexler 1993). By definition, monitoring activities of C mitigation projects typically measure
all significant flows, whereas verification aims at evaluating the accuracy and reliability of the monitoring scheme.
Monitoring programs are important for land-use projects to
increase the reliability of data and to improve project performance. To ensure that forestry projects used for GHG mitigation are reliable and verifiable, guidelines are needed to
provide structure and direction for project managers (Sathaye
and Ravindranath 1997). These authors also point out that
carbon pools in forest systems as well as forest products and
energy should be evaluated for their significance (pool size)
and vulnerability (rate and direction of change). Decisions
about appropriate methodology and intensity depend on the
relative importance of the individual pools (significance,
speed and direction of change). Possible leakage issues must
be addressed within a regional or national context (Leakage
is the term used to describe the shifting of activities with
GHG implications outside the boundaries of a project in
space and/or time, Andrasko 1997). The Scolel Te project in
Chiapas, Mexico gives an example of how monitoring and
leakage can be addressed in a project in which many individual farmers participate (Andrasko 1997; De Jong et al.
1997). The project is designed to increase farmer income by
implementing a set of alternative practices chosen by the
farmers that also increase carbon stocks. Each farmer presents a "plan Vivo" current land-use plan of his land, which
is a starting point to monitor possible land-use changes in
USDA Forest Service Proceedings RMRS-P-12. 1999
the future. Furthermore, the project is designed to also
reduce potential leakage off-site, especially to the Selva
Lacandona rainforest (De Jong et al. 1995, 1997).
Definition of the project boundary is important to facilitate decisions about questions such as if observed carbon
fluxes relate to a certain project or not. The project boundary has to be set into a regional or national context to avoid
what Andrasko (1997) calls ''Edge Effect", that is the set of
policy and technical issues emerging at the boundaries of
monitoring domains. To avoid leakage or double accounting
of carbon offsets it is essential to establish a linkage between
individual carbon sequestration projects and regional or
national flux reporting. Selecting the monitoring domain
boundaries between project and regional and national accounting involves decision-making about the accuracy desired at both levels and financial resources available.
Assessment of offset reliability will ultimately require
international agreements on a risk assessment methodology that can commonly be applied across projects and
project types. Crucial to offset reliability is the timeline
over which projects should be assessed and whether all
projects should be subject to a common timeline analysis
(Trexler 1993).
Greenhouse Gas Bubble (GGB) __
Many scientists believe that the uncertainties in estimating the size of fluxes related to LUILC changes can be
reduced to acceptable levels if that is the desire of the
international community (Noble 1998). Monitoring programs
can be designed to provide credibility to forestry carbon
offset projects. The effectiveness, cost and reliability of
methods vary by type of project, scale, and the fluxes
being monitored (Sathaye and Ravindranath 1997). One
solution to cope with the monitoring domain problem is the
development of what Andrasko (1997) calls "nested" monitoring systems. While developing countries, including
Mexico, are not obliged to accept national binding emission
limits, they could establish voluntarily GGBs covering specific regions and/or sectors (Tipper and De Jong 1998). To
establish a GGB, the government sets an emission ceiling
over a specific region and/or sector, such as a major forest
area. Once the limit of a GGB is established, any extra
emission reduction could then be credited. Such a system
would allow to set up a reporting scheme that is mutually
compatible and information flows between the monitoring
entities could improve the accuracy of both systems. For
example, up till now an average carbon density for each
land cover class is used as the basis to estimate fluxes by
comparing land-cover statistics. Project-level monitoring
schemes could develop carbon density equations wi thin each
land cover class, based on satellite image interpretation.
These equation can be adopted and incorporated in the
periodic regional land cover change detection system, that
has to be set up to comply with the GGB agreement. The U.S.
Acid Rain Program uses the GGB concept to control S02 and
NO x emissions (Solomon 1994).
As with other management systems, the procedures of
monitoring and verification of GGB and project performance should be constantly subject to improvement and
refinement. The key to improvement is to reflect upon the
main sources of error within the system. In the Scolel Te
135
Pilot Project, for example, the carbon densities and fluxes of
the land management systems are currently based partly on
direct biomass measurements, supplemented by the best
available data in the literature. New data will be used to
improve C-flux modelling, as these come available from
project and GGB monitoring and verification. Figure 3
illustrates the potential information flows that can occur
during the planning and implementation stages between
GGB and project assessments. Project monitoring, as handled
by the Scolel Te Pilot Project is also set up to improve
farmers' compliance with monitoring schedules. This will be
subject to gradual improvement through modification of the
Plan Vivo methodology, training of farmers, and linkage of
incen tive payments to fulfillment of reporting requirements.
GGBs could be established in regions where:
• Already exist interest in carbon sequestration
• Poverty alleviation is critical and al tern a tive options are
lacking (e.g. immizeration areas)
• Biodiversity conservation is of national and/or international importance
• Data on LUILC changes and related carbon fluxes are
available
• Inward and outward fluxes or leakage are limited and
measurable
Mexico, as a non-Annex 1 country, is very keen to explore
the CDM potential, especially of the forestry sector. The
Level
government is currently setting up a Mexican Office for
Greenhouse Gas Mitigation (MGGM). The National Institute of Ecology (INE), which is in charge of the Global
Climate Convention, has already initiated studies that are
required under the commitments of the Kyoto protocol and
was the first country in Latin America to provide initial
communication under the protocol. To comply with the
increasing requirements of the UNFCCC and subsequent
protocols, INE is currently improving its capacity to:
• Identify, adapt, and implement methodologies for GHG
emissions assessment of the various sectors
• Calculate emission baselines to assess GHG mitigation
initiatives
• identify promising forestry mitigation options, presenting their main technical and economic features
Table 1 presents a summary of activities and their requirements, necessary to set up and manage GHG offset
programs. Some of these activities are already in progress,
whereas others fit well within a GGB framework, such as
nested GHG accounting frameworks, policy instruments
to standardize accounting and presentation procedures,
and data integration procedures. Data collected within a
GGB framework can be used to improve the accuracy of
national GHG emission reporting, and GGB can eventually
be the starting point to establish future binding national
emission limits.
Monitoring
Verification
National
reporting
PLANNING
Region
Baseline Assessment
Baseline studies of C-flux estimation of LU/LC change
dynamics
I
Project
Results:
Refining Baseline assumptions
• Refining C-sequestration models of new systems
Estimation of C-sequestration potential of
project, based on regional baseline and ~----------,
accepted sequestration models
IMPLEMENTATION
Region
Periodic LU/LC Change detection
Results:
Baseline reports to comply with
voluntary limits of emissions
Project
Monitoring of project performance
-oE<~---
Results:
GHG-flux reporting
System performance reporting
Refining system revision criteria
Evaluation of C accumulation in new systems and control
plots
Results:
Refining C-sequestration models
• Guidelines for system establishment and maintenance
• Providing new data for project performance reporting
Figure 3.-lnformation flows between the reporting entities, within a Greenhouse Gas Bubble (GGB) framework.
136
USDA Forest Service Proceedings RMRS-P-12. 1999
Table 1.-Activities and their requirements, necessary to set up and implement a Greenhouse Gas Bubble. bold: activities and requirements in
process; normal: proposed activities and instrument development; italic: aditional activities and requirements that have to be
developed.
Level
Activities
Requirements
Planning stage
Greenhouse Gas Bubble (GGB)
• Identification of critical areas (INE 1998)
• Identification of project opportunities
(INE 1998)
• LUILC change modelling with associated
GHG flows (Tipper et a11998)
• Identification of government policies and
short and medium term development programs
• Identification and quantification of sources of
leakage
Policy instruments to define baseline determination
Agreement on default values of major parameters
Guidelines on format data reporting
LUILC change detection protocols
Leakage tracking procedures
Quantification procedures to measure GHG impact
of policies
• Identification and acceptance of a minimum set
of credible, well designed, verifiable forest
mitigation activities (De Jong et al 1997)
• Data on carbon densities and variation in LUILC
classes (De Jong et al 1999)
Project
• Elaboration of proposals of farmer and
community management plans
• Ex ante estimation of GHG fluxes in
management systems
• Identification of possible project level
sources of leakage
• Policy instruments to standardize accounting,
modelling and data presentation procedures
Interactions between levels
• Exchange of information to improve
accuracy of data at both levels
(De Jong et a11997, Figure 3)
• Standardization of data presentation
• Data Integration procedures
•
•
•
•
•
•
Implementation stage
GGB
• Periodic LU/LC change assessments
Project
• Plot and system wise monitoring and
verification of GHG fluxes in managed
and control plots
References ____________________
Andrasko, K 1997. Forest Management for Greenhouse Gas Benefits: Resolving Monitoring Issues Across Project and National
Boundaries. Mitigation and Adaptation Strategies for Global
Change 2(2-3): 117-132.
Brown, S. Cannell M.G.R, Kauppi, P., Heuveldop, J., Sathaye J.,
Singh, N. and Weyers, S., 1995 Establishment and management
of forests for mitigation of greenhouse gas emissions. IPCC 1995
Assessment. Cambridge University Press.
Brown, S., Gillespie, AJ.R, and Lugo, AE. 1989. Biomass estimation for Tropical Forests with Applications to Forest Inventory
Data, Forest Science 35(4): 881-902.
De Jong, B.H.J., Montoya-Gomez, G., Nelson, K, Soto-Pinto, 1.,
Taylor, J., and Tipper, R 1995. Community forest management
and carbon sequestration: A feasibility study from Chiapas,
Mexico. Interciencia 20(6): 409-416.
DeJong, Ben H.J., Ochoa-Gaona, S., Soto-Pinto, L., Castillo-Santiago,
M.A,Montoya-G6mez, G., Tipper,R, and March-Mifsut, 1.,1998.
Modelling Forestry and Agroforestry Opportunities for Carbon
Mitigation at a Landscape Level. pp. 221-237. In: G.J. Nabuurs,
T. Nuutinen, H. Bartelink and M. Korhonen (Eds.). Forest Scenario modelling for ecosystem management at landscape level,
EFI Proceedings No 19.
DeJong, BenH.J., Tipper,R, and Taylor, J.1997.AFrameworkfor
Monitoring and Evaluation of Carbon Mitigation by Farm Forestry Projects: Example of a Demonstration Project in Chiapas,
Mexico. Mitigation and Adaptation Strategies for Global Change
2(2-3): 231-246.
Dixon, RK 1997. The U.S. Initiative on Joint Implementation. Int.
J. Environment and Pollution 8(112): 1-17.
USDA Forest Service Proceedings RMRS-P-12. 1999
Dixon, RK, Andrasko, K.J., SUi:isman, F. G., Lavinson, M.A, Trexler,
M.C., and Vinson, T.S. 1993 Forest Sector Carbon Offset Projects:
Near-term Opportunities to Mitigate Greenhouse Gas Emissions. Water, Air and Soil Pollution 70: 561-577.
Dixon, RK, Sathaye, J.A, Mayeres, S.P., Masera, O.R, Makarov,
AA, Toure, S., Makundi, W., and Wiel, S., 1996. Greenhouse Gas
Mitigation Strategies: Preliminary Results from the U.S. Country Study Program. Ambio 25(1): 26-32.
Dixon, RK, Schroeder, P.E. and Winjum, J.K (Eds.). 1991 Assessment of Promising Forest Management Practices and Technologies for Enhancing the Conservation and Sequestration of
Atmospheric Carbon and Their Costs at the Site Level. EP N6001
3-91/067, US-EPA, Washington DC.
Faeth, P., Cort, C. and Livernash, R, 1994. Evaluating the Carbon
Sequestration Benefits of Forestry projects in Developing Countries. World Resources Institute.
Fearnside, F.M. and Malheiros-Guimaraes, W. 1996. Carbon uptake by secondary forests in Brazilian Amazonia. Forest Ecology
and Management 80: 35-46.
INE, 1998. http://www.ine.gob.mx
Masera, O.R, Bellon, M.R, and Segura, G. 1995. Forest Management Options for Sequestering Carbon in Mexico. Biomass and
Bioenergy 8(5): 357-367.
. .
Masera, O.R, Ordonez, M.J., and Dirzo, R 1997. Carbon enusslOns
from Mexican forests: Current situation and long-term scenarios.
Climatic Change 35: 265-295.
Nabuurs, G.J. and Mohren, G.M.J. 1993. Carbon fixation through
forestation activities: A study of the carbon sequestering potential of selected forest types, commissioned by the Foundation
Face. Inst. for Forestry and Nature Research (IBN-DLO),
Wageningen, The Netherlands, IBN Research Report 93/4.204 pp.
137
Nabuurs, G.J. and Mohren, G.M.J. 1995. Modelling analysis of
potential carbon sequestration in selected forest types. Canadian
Journal of Forest Research 25: 1157-1172.
Noble, I., 1998. The Gross-net Issue. http://www.igbp.kva.se/
grossnet.html. 6 pp.
Rudel, T. and Roper, J. 1997. The Paths to Rain Forest Destruction:
Crossnational Patterns ofTropical deforestation, 1975-90. World
development 25(1): 53-65.
Sathaye, J. and Ravindranath, N.H. 1997. Policies, Measures and
the Monitoring Needs of Forest Sector Carbon Mitigation.
Mitigation and Adaptation Strategies for Global Change 2(23): 101-115.
Schlamadinger, B. and Marland, G. 1996. The role of forest and
bioenergy strategies in the global carbon cycle. Biomass and
Bioenergy 10: 275-300.
Scolel Te, 1998. http://www.ed.ac.ukI-ebfrll:http:llwww.ecosur.mx
Solomon, B.D. 1994. U.S. S02 emission trading: lessons for a global
carbon budget. pp. 1083-1086. In: Global Climate Change: science, policy and mitigation strategies. Proceedings of the Air and
Waste Management Association International Specialty Conference, April 5-8, 1994. Phoenix Arizona.
138
Tipper, R and De Jong, B.H.J. 1998. Quantification and regulation
of carbon offsets from forestry: comparison of alternative methodologies, with special reference to Chiapas, Mexico. The Commonwealth Forestry Review (In Press).
Tipper, R, De Jong, B.H.J., Ochoa-Gaona, S., Soto-Pinto, M.L.,
Castillo-Santiago, M.A., Montoya-GOmez, G., and March-Mifsut.
I. 1998. Assessment of the Cost of Large Scale Forestry for C02
Sequestration: Evidence from Chiapas, Mexico. lEA Greenhouse
Gas R&D Programme. 84 pp.
Trexler, M C and Haugen, C. 1994 Keeping it green: evaluating
tropical forestry strategies to mitigate global warming. World
Resources Institute, Washington DC, U.S.A.
Trexler, M.C. 1993. Manipulating biotic carbon sources and sinks
for climate change mitigation: Can science keep up with practice?
Water, Air, and Soil Pollution 70: 579-593.
Winjum, J. K., Dixon, RK., and Schroeder, P. E. 1992 Estimating
the global potential of forest and agroforest management practices to sequester carbon. Water, Air and Soil Pollution 64:
213-22.
Worldbank,1997.
USDA Forest Service Proceedings RMRS-P-12. 1999