Revisiting the Use of Managed Land as a Proxy for
Estimating National Anthropogenic Emissions andRemovals

IPCC Expert Meeting Report
5 -7 May, 2009, INPE, São José dos Campos, BRAZIL

Task Force on National Greenhouse Gas Inventories

12Supporting material prepared for consideration by the Intergovernmental Panel on Climate Change (IPCC). This supporting material has
not been subject to formal IPCC review processes. Neither the papers presented at the expert meeting nor this report of its proceedings
has been subjected to IPCC review.

The IPCC would like to thank Brazil and INPE for their generous support in holding this meeting.

Published by the Institute for Global Environmental Strategies (IGES), Hayama, Japan on behalf of the IPCC
© The Intergovernmental Panel on Climate Change (IPCC), 2010.
Please cite as:
IPCC 2010, Revisiting the Use of Managed Land as a Proxy for Estimating National Anthropogenic Emissions andRemovals, eds: Eggleston H.S., Srivastava N., Tanabe K., Baasansuren J. Meeting Report, 5 -7 May, 2009, INPE, São José
dos Campos, Brazil, Pub. IGES, Japan 2010
IPCC Task Force on National Greenhouse Gas Inventories (TFI)
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Printed in Japan

ISBN 978-4-88788-061-0

3

4

Revisiting the Use of Managed Land as a Proxy for Estimating National
Anthropogenic Emissions and Removals

Meeting report
5 -7 May, 2009, INPE, São José dos Campos, BRAZIL

5

Contents
1.

Executive Summary .............................................................................................................................................. 7

2.

Introduction ............................................................................................................................................................ 8
2.1.

3.

4.

5.

6.

7.

Previous Discussions in the IPCC .............................................................................................................. 8

Rationale and assumptions underlying the managed land proxy ...................................................................... 9
3.1.

Direct and Indirect Anthropogenic Effects ................................................................................................ 10

3.2.

IPCC Guidelines Treatment of Time Series and Annual Estimates ....................................................... 11

Assessment of the managed land proxy ........................................................................................................... 12
4.1.

Assumption 1 – Direct Effects ................................................................................................................... 12

4.2.

Assumption 2 – Indirect Effects ................................................................................................................ 12

4.3.

Assumption 3 - Variability .......................................................................................................................... 12

4.4.

Natural Effects and the Managed Land Proxy ......................................................................................... 13

Sectoral considerations ...................................................................................................................................... 13
5.1.

Cropland and Settlements ......................................................................................................................... 13

5.2.

Grassland ................................................................................................................................................... 13

5.3.

Wetlands..................................................................................................................................................... 14

5.4.

Forest Lands .............................................................................................................................................. 14

5.5.

Other Lands................................................................................................................................................ 15

Discussion on the methodological options ........................................................................................................ 15
6.1.

Managed land proxy .................................................................................................................................. 16

6.2.

Component separation .............................................................................................................................. 16

6.3.

Comparison between two time series....................................................................................................... 16

6.4.

Default factors and Optimal Fingerprinting ............................................................................................... 17

6.5.

Activity based approach ............................................................................................................................ 18

Conclusions ......................................................................................................................................................... 19

Annex 1.

References ............................................................................................................................................ 21

Annex 2.

Co-Chairs Summary.............................................................................................................................. 24

Annex 3.

Background Papers............................................................................................................................... 25

Annex 4.

Presentations......................................................................................................................................... 49

Annex 5.

Agenda................................................................................................................................................... 50

Annex 6.

Participants List ..................................................................................................................................... 51

6

1. Executive Summary
The IPCC Guidelines for National Greenhouse Gas Inventories and the Good Practice Guidance are used byParties to the UNFCCC to report their anthropogenic emissions by sources and removals by sinks as required by
the UNFCCC and by Annex I Parties for accounting under the Kyoto Protocol.
In 2003 the IPCC reported that “The scientific community cannot currently provide a practicable methodology thatwould factor out direct human-induced effects from indirect human-induced and natural effects for any broad
range of LULUCF activities and circumstances” (IPCC 2003b). Therefore the IPCC Guidelines have adopted theuse of estimates of greenhouse gas emissions and removals on managed land as a proxy for the estimation ofanthropogenic emissions and removals. Since 2003 the scientific understanding of the drivers of greenhouse gas
fluxes from LULUCF sources has developed and so the IPCC decided to revisit the use of the managed land
proxy.
While several concerns and deficiencies of the managed land proxy were identified, none of the alternatives
considered at the meeting proved to be sufficiently well developed (for all Tier levels required) to justify an IPCC
recommendation for change in the default estimation approach, thus the meeting concluded that the managed
land proxy is currently the only widely applicable method to estimate the separation between anthropogenic andnatural fluxes. Participants also recognised that with increasing impacts of climate change (an indirect humaninduced cause) the managed land proxy could in the future include an increasing proportion of natural andindirect human contributions to the reported emissions and removals. Therefore work needs to continue toidentify and test approaches to separating (factoring-out) anthropogenic impacts from others. The meeting briefly
reviewed a number of proposed alternatives to the managed land proxy and considered they still needed further
development before they can be assessed for use by the IPCC. These methods need to be reviewed with regard
to their methodological implications, data requirements and compatibility with the inventory principles.
While the meeting agreed that annual emission inventories should estimate the actual emissions in the inventory
year, it was also noted that there is a need to be able to identify the impact of mitigation and management efforts
even where these are obscured by inter-annual variations in greenhouse gas fluxes for example by the impactsof natural processes (e.g. wildfire) or indirect human-induced processes (e.g. climate change impacts).
A clearer, common understanding of anthropogenic is needed particularly in relation to the distinction between
direct, indirect and natural effects, and how to classify effects that have a range of natural and direct influences,for example where there is a natural origin (e.g. dry lightening strike) but the associated emission is mainly
determined by direct anthropogenic factors (e.g. management of forest plantation) or vice versa for example,
where there is an anthropogenic origin (e.g. accidental fire ignition) but the magnitude of emissions is determinedby natural causes (e.g. prolonged drought causing severe fire conditions).
Guidance for wetlands will need development in the future but currently the scientific understanding of the factors
determining these fluxes is still developing. One issue that will need to be addressed is how to deal with areas
with significant natural fluxes, so that emissions estimated using the IPCC guidelines reflect the changes seen by
the atmosphere. This situation occurs in other sectors but is particularly acute in the wetland sector. In addition,
emissions and removals from wetlands are impacted by processes and activities on neighbouring lands as they
are connected by significant lateral fluxes of water, carbon and nutrients.

7

2. Introduction

The meeting in Brazil started with invited papers
reviewing some of the background and current
scientific causal understanding of these effects andpractical approaches to estimating them (SeeAnnex 1). The issues were discussed in smallergroups. The outline of the document was agreed bythese groups, the draft report prepared by the corewriting team, reviewed twice by all the participants,
each time revised by the core writing team toaddress reviewer comments.

The IPCC Guidelines on National Greenhouse Gas
Inventories and the Good Practice Guidance areused by Parties to the United Nations Framework
Convention on Climate Change (UNFCCC) toreport emissions and removals as required by theconvention. The Revised 1996 Guidelines (IPCC
1997) and the subsequent Good Practice Guidance(IPCC 2000; IPCC 2003a), are currently adopted by
the UNFCCC for reporting 1. The IPCC has recently
updated this guidance in the 2006 Guidelines (IPCC
2006) and these are currently being considered by
the UNFCCC.

This report first describes the current managed land
proxy and its rationale. It then reviews the use ofthis proxy, both globally and by sector and thenbriefly considers some potential alternatives. The
report concludes that despite the increasing
recognition of shortcomings, the managed land
proxy remains the recommended default method forreporting anthropogenic GHG emissions andremovals and that further research to separate
direct human induced from indirect and naturaleffects is encouraged.

The UNFCCC requires the estimation and reportingof anthropogenic emissions and removals ofgreenhouse gases not covered by the Montreal
Protocol. Generally the definition of anthropogenic
emissions is clear. However, emissions andremovals associated with land use activities(LULUCF 2 and/or AFOLU 3) occur together withthose of natural origin, and it is not always
straightforward how only to estimate theanthropogenic components. In this situation theauthors of the IPCC Guidelines have usedemissions and removals from managed land as aproxy for anthropogenic emissions and removals(implicitly in the Revised 1996 Guidelines andexplicitly in later documents). The São José dos
Campos meeting was to review the use of managed
land as a proxy for anthropogenic emissions in thecontext of improved understanding of the causal
drivers of changes in carbon stocks in the various
land carbon pools.

2.1. Previous Discussions in the
IPCC
The IPCC has previously considered this issue
twice. COP Decision 11/CP7 requested the IPCC,
amongst other things, to consider how to separate(factor out) direct human-induced effects fromindirect and natural effects on emissions andremovals. The possible causes of indirect andnatural effects included: age class structure, CO2
and nitrogen fertilisation, disturbances, etc. The
IPCC’s first meeting on the issue in Geneva in
2002 4, developed a work plan for a possible IPCC
report to provide a framework for factoring out, but
questioned the feasibility of providing ...a definite
methodology complete with facts and figures. The
second meeting in Geneva in 2003 concluded that
The scientific community cannot currently provide apracticable methodology [to] factor out direct
human-induced effects from indirect humaninduced and natural effects for any broad range of
LULUCF activities and circumstances. (IPCC
2003b) .

This report summarizes the discussions andoutcome of the São José dos Campos meeting
which assessed the appropriateness of the use ofmanaged land as a proxy for anthropogenic effects
in different contexts and considered methods being
developed to apportion greenhouse gas emissions
and removals to specific drivers.
1 The use of Revised 1996 Guidelines and thesubsequent Good Practice Guidance is mandatory forAnnex I parties and encouraged for Non-Annex I Parties.
2 LULUCF – Land Use, Land-Use Change and Forestry,a sector in the IPCC Good Practice

3 AFOLU – Agriculture, Forestry and Other Land Use, a

4 The IPCC’s meetings were held as a result of a request

sector in the 2006 Guidelines.

from the UNFCCC (Decision 11/CP7)

8

3. Rationale and assumptions
underlying the managed land
proxy

Thus, inventory compilers should report allemissions and removals that occur on managed
land. Managed land in this context is given a broad
definition:

The distinction between anthropogenic and naturalemissions is clear in most sectors apart from
LULUCF / AFOLU. It is clear, that estimating all
carbon stock changes in LULUCF/AFOLU would
capture management, all disturbances, indirect
anthropogenic effects and natural processes, andthe IPCC guidelines provides appropriate details on
how to estimate these stock changes. However,
although the effects of particular factors may be
estimated, because of interactions it is less clear if it
is possible to apportion the total carbon stockchange uniquely to individual drivers (e.g. possible
biomass increases or decreases driven by differing
management regimes, age distribution of forests,
natural disturbances, CO2 and nitrogen fertilisationetc.).

Managed land is land where human interventions
and practices have been applied to perform
production, ecological or social functions.

Ibid. Page 1.5 (4),The rationale behind the managed land proxy is
explained in volume 4 of the 2006 Guidelines:
The key rationale for this approach is that the
preponderance of anthropogenic effects occurs
on managed lands. By definition, all direct
human-induced effects on greenhouse gas
emissions and removals occur on managed
lands only. While it is recognized that no area of
the Earth’s surface is entirely free of human
influence (e.g., CO2 fertilization), many indirect
human influences on greenhouse gases (e.g.,increased N deposition, accidental fire) will bemanifested predominately on managed lands,
where human activities are concentrated. Finally,
while local and short-term variability in emissions
and removals due to natural causes can besubstantial (e.g., emissions from fire, seefootnote 1), the natural ‘background’ ofgreenhouse gas emissions and removals bysinks tends to average out over time and space.
This leaves the greenhouse gas emissions andremovals from managed lands as the dominantresult of human activity.

Therefore the IPCC guidelines recommend using
emissions and removals from managed land as aproxy for anthropogenic emissions and removals:
Anthropogenic emissions and removals meansthat greenhouse gas emissions and removals
included in national inventories are a result of
human activities. The distinction between naturaland anthropogenic emissions and removals
follows straightforwardly from the data used toquantify human activity. In the Agriculture,
Forestry and Other Land Use (AFOLU) Sector,
emissions and removals on managed land aretaken as a proxy for anthropogenic emissions
and removals, and interannual variations innatural background emissions and removals,
though these can be significant, are assumed toaverage out over time. 5

Ibid. Page 1.5 (4),biomass pool are not equivalent in the inventory
year. For grassland biomass burning and burning ofagriculture residues, the assumption of equivalenceis generally reasonable. However, woody vegetation
may also burn in these land categories, andgreenhouse gas emissions from those sources
should be reported using a higher Tier method.
Further, in many parts of the world, grazing is the
predominant land use in Forest Land that are
regularly burnt (e.g., grazed woodlands andsavannas), and care must be taken before assuming
synchrony in such systems. For Forest Land,
synchrony is unlikely if significant woody biomass iskilled (i.e., losses represent several years of growthand C accumulation), and the net emissions should
be reported. Examples include: clearing of native
forest and conversion to agriculture and/or
plantations and wildfires in Forest Land.

2006 Guidelines Vol. 1 Ch. 1 Page 1.4 (4),5 The 2003 Good Practice guidance allows that

If methods are applied that do not capture removalsby regrowth after natural disturbances, then it is notnecessary to report the CO2 emissions associatedwith natural disturbance events.
(page 3.49)
but the 2006 Guidelines was more specific and does notassume the re-growth will balance the emissions fromthe disturbance:
Equivalence (synchrony) of CO2 emissions andremovals: CO2 net emissions should be reported
where the CO2 emissions and removals for the(page 2.41)

9accounting for emissions and removals aim tofactor-out the impact of these activities prior to a
pre-defined reference year (e.g. the Kyoto
Protocol).

The key assumptions behind the managed land
construct are listed below and a discussion about
the validity of these assumptions follows in section
3 of the report:•

all direct human-induced effects on
greenhouse gas emissions and removals
occur on managed lands only: naturalprocesses (e.g. wildfire, pest outbreaks,
drought impacts, etc.) are assumed tocontribute only a small proportion of theemissions and removals on managed land•

indirect human influences are manifested
predominantly on managed lands•

the substantial natural, short-term andlocal variability averages out over time.

The methods in all the IPCC emission inventory
guidance aim to estimate all the greenhouse gas
emissions to, and removals from, the atmosphereon the lands to which they are applied and so
include both direct and indirect effects. The IPCC
guidelines state that all emissions and removals
from managed lands should be reported asanthropogenic emissions. The UNFCCC asks for “Anational inventory of anthropogenic emissions bysources and removals by sinks of all greenhousegases not controlled by the Montreal Protocol” (Art12, Para. 1) and makes no distinction between
direct and indirect anthropogenic emissions.

3.1. Direct and Indirect
Anthropogenic Effects

The Kyoto Protocol does state that “The netchanges in greenhouse gas emissions by sources
and removals by sinks resulting from direct humaninduced land-use change and forestry activities,
limited to afforestation, reforestation anddeforestation since 1990, measured as verifiablechanges in carbon stocks in each commitment
period, shall be used to meet the commitments
under this Article of each Party included in Annex I.”(Article 3 Para 3) 6.

Indirect anthropogenic effects are second order
impacts of human activities on emissions bysources or removals by sinks. They include effects
such as:•

Impacts of climate change inducedchanges in temperature, precipitation, andlength of growing season.

•

Climate change induced inter-annual andinter-decadal variability in suchenvironmental factors.

•

Changes in ambient CO2 concentrations(i.e. CO2 fertilisation).

•

Human-induced increases in nitrogen
availability (e.g. increased N deposition).

•

Impact of local and regional air pollution(e.g. ozone, particulates).

•

Changes in disturbances regimes,
including extreme events (e.g. climatechange can alter scale, intensity andfrequency of fire, pest attack, windthrow,flooding etc.).

Subsequently, in the Marrakesh Accords decisionon Land Use, Land-Use Change and Forestry(LULUCF) the Conference of Parties to the
UNFCCC invited the IPCC
To develop practicable methodologies to factor
out direct human-induced changes in carbon
stocks and greenhouse gas emissions bysources and removals by sinks from changes incarbon stocks and greenhouse gas emissions bysources and removals by sinks due to indirect
human-induced and natural effects (such as
those from carbon dioxide fertilization andnitrogen deposition), and effects due to pastpractices in forests (pre-reference year), to be

6 UNFCCC decision for the Kiyoto Protocol 16/CMP 1,

article 1, Affirms that the following principles govern thetreatment of land use, land-use change and forestry
activities: … (h) That accounting excludes removals
resulting from: (i) elevated carbon dioxide concentrations
above their pre-industrial level; (ii) indirect nitrogen
deposition; and (iii) the dynamic effects of age structure
resulting from activities and practices before thereference year

While management activities used in forestry andagriculture and their effect over long time scales(e.g., age structure and past practices; woody
encroachment) are a direct effect some possible
10

Multi-year averaging: Countries should reportannual inventory estimates that are based onbest estimates for actual emissions and removals
in that year. Generally, single year estimatesprovide the best approximation of realemissions/removals and a time series of single
year estimates prepared according to goodpractice can be considered consistent. Countries
should, where possible, avoid using multi-year
averaging of data that would result in over- or
under-estimates of emissions over time,increased uncertainty, or reduced transparency,
comparability or time-series consistency of theestimates. However, in some specific cases thatare described for specific sectors in Volume 2-5,
multi-year averaging may be the best or even the
only way to estimate data for a single year. In thecase of high or uncertain annual variability – asin the growth of various tree species in a year –and where there is higher confidence in the
average annual growth rate over a period ofyears then multi-year averaging can improve thequality of the overall estimate.

submitted to the Conference of the Parties at its
tenth session;(UNFCCC 11/CP.7, para 3)
However, as noted above, in 2003 the IPCC said
that:
The scientific community cannot currently
provide a practicable methodology that would
factor out direct human-induced effects fromindirect human-induced and natural effects forany broad range of LULUCF activities andcircumstances. Research efforts are addressing
some particular effects, such as CO2 fertilization,over a range of spatial scales and are providing
information relevant to the separability andattribution of different effects at specific sites
where good historical information is available andintensive measurements are being carried out.
Such efforts are expected to provide anincreasing understanding of the feasibility andpracticability of a broadly based approach to theissues of separability and attribution.

2006 GL, Vol. 1 Ch. 2 Page 2.11 (4),(IPCC 2003b)

Here the guidelines do allow some averaging ofmulti-year data. However this is in the context of
empirical input data where a measurement in one
year, if used for other years, may be subject tolarge errors due to this inter-annual variability and avalue averaged over many years may be morereliable and subject to smaller errors. It is important
to note that the guidelines do NOT allow for
averaging of emission estimates in order to disguiselarge real inter-annual variability. This also has theeffect that Tier 1 methods may not be able toestimate the total inter-annual variability whichshould be evident in higher tier methods.

3.2. IPCC Guidelines Treatment ofTime Series and Annual Estimates
Some participants noted that for a few Parties to the
UNFCCC following the IPCC Guidelines leads toestimates of fluxes of greenhouse gases dominatedby inter-annual changes, driven largely by naturalcause (Kurz W. A. 2009; Richards G. 2009). The
2006 IPCC guidelines give clear guidance on thetreatment of annual emissions:
Inventory year and time series

While inter-annual variability may largely be driven
by climate variability and natural disturbances,estimation of the impacts of these factors iscomplicated by:

National inventories contain estimates for thecalendar year during which the emissions to (orremovals from) the atmosphere occur. Where
suitable data to follow this principle are missing,emissions/removals may be estimated using datafrom other years applying appropriate methods
such as averaging, interpolation andextrapolation. A sequence of annual greenhousegas inventory estimates (e.g., each year from1990 to 2000) is called a time series. Because of
the importance of tracking emissions trends overtime, countries should ensure that a time seriesof estimates is as consistent as possible.

2006 GL, Vol. 1 Ch. 1 Page 1.4 (4),
And
11

•

Need for historical activity and climate
data, which can be difficult to obtain.

•

Impacts of past land management
practices, which occur when priorconditions affect the impact of current
management practices, such as the longterm effect of past practices on soil organic
matter and nitrogen contents, forest ageclass structure and soil organic matterdecay.

The meeting noted that the aim of emission
inventories is to provide a best estimate of theemissions and removals in a given year and thus do
not try to remove or reduce the impact of interannual variations on anthropogenic emissions (e.g.
those caused by climate effects on forestry,
agriculture or energy production). The meeting
further noted that subsequent accounting (such asthat of a future climate agreement) could agree toaverage out this variability in a transparent manner
if desired.

may be more related to fuel load than to the causeof ignition.

4. Assessment of the managed land
proxy

By virtue of their location managed lands are often
more exposed to indirect effects such as pollutants
and nutrient deposition. However other indirect andnatural effects, such as CO2 fertilization, theinfluence of a changing climate, and disturbances ofnatural origin largely occur indifferently on managed
and unmanaged lands. However, unmanaged lands
are likely to respond more strongly to N deposition
per unit N deposited than fertilized managed lands
where nitrogen is the limiting factor for vegetation
growth. Often emissions with a natural origin arelargely determined by direct and indirect
anthropogenic effects. For example, an ongoinginsect outbreak in forests in western North America
has a natural origin but the geographic extent islargely determined by warmer winters (an indirect
effect of anthropogenic climate change) and themagnitude of the emissions is affected by past
management (fire suppression and not harvesting
pine forests) and current harvesting decisions(salvage logging of dead trees) (Kurz W. A. 2008a;
Richards G. 2009)

4.2.

many indirect human influences on greenhousegases (e.g., increased N deposition, accidentalfire) will be manifested predominately on
managed lands, where human activities areconcentrated..

Ibid

In São José dos Campos, meeting participants
examined the use of the managed land proxy andits underlying assumptions.

4.1.

Assumption 2 – Indirect Effects

Assumption 1 – Direct Effects

all direct human-induced effects on greenhousegas emissions and removals occur on managed
lands only. 7

2006 GL, Vol. 4 Ch. 1 Page 1.5,
Implicitly, natural processes are assumed tocontribute only a small proportion of the emissions
and removals on managed land. However, somedirect human-induced effects can spread into
unmanaged lands and some natural effects occur
within managed lands. The relative importance of
these exceptions differs between countries andover time. For example prescribed fires may spreadfrom managed lands onto unmanaged lands andnatural wildfires occur within managed lands.
Nutrients (e.g. fertiliser) and dissolved GHG (e.g.
N2O, (Clough T.J. 2007)) may flow from managed
lands to unmanaged lands which can affect growthand emissions and removals on those unmanaged
lands or wetlands, lakes and rivers. While themagnitude of these effects is not clear andmethodologies to quantify the effects of nutrient
flows are not yet available, it is likely that the
impacts of these factors are generally much smaller
than the direct effect on managed land or the
impacts of natural disturbances on managed land,
and the consequence of fire on unmanaged land

4.3.

Assumption 3 - Variability

while local and short-term variability in emissions
and removals due to natural causes can besubstantial … the natural ‘background’ ofgreenhouse gas emissions and removals bysinks tends to average out over time and space.

Ibid
Two presentations highlighted the importance ofinter-annual variability generated by indirect andnatural effects, such as climatic variations (Richards
G. 2009), and large scale disturbances (Kurz W. A.
2008b) and a further presentation demonstrated theinter-annual variability due to disturbances(mortality), age class distribution and site
distribution, using a model that was designed tosimulate carbon stock changes and fluxes(Somogyi Z. 2009). The effect of climate variability

7 Note that, according the the Guidelines, if there is adirect human induced activity in a land that previously
was unmanaged, that land immediately becomesmanaged land.

12the managed land proxy may generally be
predominantly of anthropogenic origin (both direct
and indirect) and that the contribution from naturalcauses is negligible over time. In some countries
natural disturbances occurring within the managed
forest (wildfires, pest outbreaks, windthrow due tostorms) can contribute large and highly variable
emissions to the GHG balance reported using themanaged land proxy (Kurz W. A. 2008b), and thebackground uptake may be significant, althoughaccounting methods which take account of this in all
years may be relatively insensitive to it, and where
new forests are established any increase in uptake
due to background effects may perhaps be thoughtof as direct anthropogenic. It is important toacknowledge that this proportion of natural andindirect contribution to the managed land proxy
fluxes can be large and highly variable in somecountries.

is also occasionally observed in other inventory
sectors, e.g. the energy sector where hydro-electric
power generation and energy use for heating andair conditioning can vary annually with climatic
variations.
Such effects may be more clearly identifiable where
higher-tier methodologies have been applied toestimate development The inter-annual variability
driven by climate variability and extreme events is
not reflected in the inventories when the inventory
compilers, usually using lower tier methods,
averaged input data over multiple years. The
climatic component of the inter-annual variability will
only show up when estimates based on processmodels or additional high frequency observations
are used.
The signal of the impact of direct human-induced
emissions and removals, or the impact of mitigation
measures, may not be discernible when
confounded by large inter-annual variations. The
ability to discern the signal of the mitigation from thenoise of the inter-annual variability is importantwhen inventory estimates are used for monitoring
the impacts of mitigation measures.

5. Sectoral considerations
The meeting considered the use of the managed
land proxy for each of the six broad land use
categories defined in the IPCC Guidelines. The
main issues identified were associated withwetlands and forests.

The assumption of a neutral balance of greenhousegas emissions and removals of pristine lands was
first stated in the 1996 Guidelines. However the
residual uptake of carbon (the “missing sink”)
estimated in the IPCC Fourth Assessment Report(IPCC 2007) (6) to amount to a sink of 2.6 Gt/yr inthe 1990s (with a range of 0.9 to 4.3 Gt/yr) indicatesthat natural effects will not average to zero during adecade. In addition, the total area disturbed (e.g.
burnt) may vary considerably over time (Mouillot F.
2005). Natural and indirect effects may not average
to zero in forests on managed land, either (Somogyi
Z. 2009).

5.1.

All cropland and settlements are managed. The
meeting concluded that the managed land proxy isa good approach for estimating anthropogenic
emissions and removals from these lands.
Measurement-based estimates of C stock changes
on cropland soils will always capture a combinationof natural, direct and indirect anthropogenic effects.
Potential, future, improvements to inventory
methodologies are needed before it is possible toassess the impact of cropland or settlement
management practices on adjacent un-managed aswell as other managed lands (for example throughrun-off or erosion) which are not subject to rigorous
inventory estimation, especially on wetlands andwater bodies.

Thus, although these background emissions andremovals may average out over the long run for
carbon, it may be on a time scale much greaterthan one year. Emissions of CH4 and N2O are neverbalanced by removals of these gases. The use ofannual greenhouse gas inventories should take this
into account, noting that year-to-year changes may
be due to these causes and not part of a trend.

5.2.

Grassland

Not all grassland is managed. For example,
extensive areas of tundra can be considered unmanaged grassland. The meeting concluded thatthe managed land proxy is a good approach for4.4. Natural Effects and theManaged Land Proxy
Consideration of the three assumptions (above)
imply that emissions and removals reported using

Cropland and Settlements13

(eg depth of the water table and growing season
precipitation) over the emissions and removals ofdifferent greenhouse gases from wetlands (Lafleur
2007; Strack M. 2007). Small scale studies haveshown that these different processes and effects
can be quantified but the scientific tools that havebeen developed are not operational at the national
scale or applicable for lower tier methods. Similarly,
small-scale studies have demonstrated therelatively important inter-annual variability in the
GHG budget of peatlands (Bubier J.L. 2003; BubierJ. 2005); again the measurements that have beencollected and tools that were developed cannot at
this point be generalised for large-scale
applications.

estimating direct and indirect anthropogenic
emissions and removals from managed grasslands.
Managed grassland experience disturbances,namely fires, but these tend to be associated withmanagement practices rather than natural eventsand are therefore mainly anthropogenic emissions
or removals and reported as such using themanaged land proxy.

5.3.

Wetlands

Pristine wetlands naturally emit and remove GHG,
providing a background of natural fluxes against
which the direct human impact can be difficult toassess. Wetlands (notably peat lands) containsignificant stocks of carbon (Tarnocai C. 2009)
which could be released through the impact ofindirect human-induced impacts (climate change)
with fluxes potentially greater than those resulting
from direct human activities. Wetlands differ fromother lands in that the greenhouse gas fluxes
appear to be significantly affected by lateral fluxesof water, carbon and nutrients from adjacent lands.
For this reason, wetlands affect, and are affectedby, processes and activities that are taking place on
adjacent lands which can alter greenhouse gas
emissions and removals. One example is thecorrelation between greenhouse gas emissions
from water bodies (lakes, reservoirs) and land use
or land management activities on the watershed(Worrall F. 2003; Bastviken D. 2004; Kortelainen P.
2006; Juutinen S. 2009). Another is theeutrophication of water bodies that disrupt thegreenhouse gas dynamics in un-managed water
bodies that are not included in managed land proxy(enhancing emissions or removals; (Huttunen J.T.
2003a; Huttunen J.T. 2003b; Huttunen J.T. 2003c).
Care needs to be taken to ensure that estimation ofthese processes does not lead to double-counting.
Experience shows the challenges in monitoring
different types of wetlands, notably managed
wetlands that have been abandoned, because
although area information may be available, thestatus of the wetlands in a transition phase is sodiverse that emissions and removals cannot berobustly quantified by a land category approach(Myllys M. 1996). The IPCC AR4 emphasized theuncertainty in the global carbon cycle due to lack ofproper knowledge on soil carbon (of which
peatlands would constitute a significant proportion)(IPCC 2007). Further, there are significant
challenges in monitoring at the appropriate spatial
and temporal scales, some of the important controls

Estimating all emissions and removals on peatlandson the time scale relevant to reporting may notalways reflect their true contribution to radiative
forcing. For example, northern peatlands havecontributed to long-term cooling the climate bysequestering CO2; nevertheless, their current
annual GHG budget could be calculated as asource (of CH4) in total CO2eq. (Frolking S. 2006;
Frolking S. 2007). This could be true for other types
of wetlands with significant long-term carbon
sequestration potential.
Due to the complex climate and landscape factors
affecting the GHG budget of wetlands, and the lackof broadly applicable methodologies to quantify
anthropogenic emissions and removals, the current
guidance continues to be, while incomplete, themost practicable, with its focus on human activities(e.g. drainage of peatland and flooding) whose
impacts are clear. Rapid improvements in thescientific understanding may warrant re-visiting thecurrent guidance in the mid-term.
Due to incomplete scientific understanding and thelack of comprehensive and widely applicableapproaches, the IPCC guidance focuses on humanactivities that directly and significantly impact
wetlands, namely drainage of peatland andflooding. Meeting participants concluded that thisapproach is helpful in quantifying anthropogenic
emissions and removals from wetlands.

5.4.

Forest Lands

Forests can be either managed or unmanaged andthere are extensive boreal and tropical unmanaged
forests. Both managed temperate and tropicalmanaged and unmanaged forests currently appear
14

the spread and development of the
disturbance (such as past management
and climate changes)

to be a significant carbon sink (Stephens B. B.
2007; Le Quere C. 2009).
While the use of the managed land proxy captures
most direct and indirect anthropogenic effects onforest lands some issues were raised:
•

•

•

•

Thus the ability to attribute changes in fluxes ofgreenhouse gases to natural or anthropogenic
factors would increase the understanding ofanthropogenic emissions.

Some management activities (e.g.
prescribed fires) have the potential tospread to unmanaged lands.

5.5.

Natural wildfires that are ignited and burnon managed land can lead to a large
proportion of the emissions from managed
forests (Kurz W. A. 2008b). In Russian
forests, the frequency of fires outside
intact forests is higher than in intact forestssuggesting a direct human impact on thenumber of wildfires (Mollicone D. 2006).
The extent and intensity (not theoccurrence) of disturbances (windthrow,pest outbreaks, fires) in managed forests
is necessarily related to past and present
management because past and present
management determine the amount ofavailable carbon, vulnerability andresilience of forests. Natural wildfires canstart in the managed forest or spread into
it from adjacent unmanaged areas. The
emissions are directly related to fire
intensity (which is a result of weather
conditions prior to and during the fire) and
fuel consumption (which is a result of fuelloads and stand history).

Other Lands

This category includes bare soil, rock, ice, and all
unmanaged land areas that do not fall into any of
the other five categories. The other lands category
is assumed not to be a significant carbon pool.
Hence significant greenhouse gas emissions do notoccur in this category except if land changes to orfrom this category from or to another category.
Therefore the issue of separating anthropogenic
from natural emissions is not relevant here.

6. Discussion on the methodologicaloptions
It is clear that carbon stock change estimates
capture management, disturbances, indirect
anthropogenic effects and natural processes – bothcurrent and past factors. However, the challenges
remain in apportioning the total carbon stockchange and non-CO2 GHG emissions andremovals to individual drivers (e.g. anthropogenic
changes to wetlands, differing management
regimes, age class distribution of forest stands,
disturbances, possible biomass increases ordecreases driven by climate change, CO2
fertilisation etc.).

There was concern that by designatingareas, currently unmanaged, for activities
that do not impact the carbon stock (suchas conservation) it would be possible toinclude significant carbon sinks that are
occurring without direct humanintervention thus obscuring the impact of
direct human activities. This is the case in
Brazil where large protected areas in
Amazonia (e.g. national forests,
conservation units, indigenous peoples
land) have the potential to offset the real
deforestation emissions (Krug T. 2009).

Meeting participants recognised methodologicaldevelopments in recent years and the further needto improve the separation of anthropogenic from
non-anthropogenic fluxes and their expression in
the inventory time series and in some cases directfrom indirect effects. A number of methodologicaloptions were considered in a preliminary fashion
and are further elaborated below. Note that these
options are not necessarily mutually exclusive.
1. Maintenance of the managed land proxySome natural disturbances can causesignificant changes in carbon fluxes (e.g.
pest outbreaks) that cannot be controlled.
The actual size of the flux is determined by
a combination of the original natural cause
and direct and indirect effects that control

2. Component separation (quantify the
influence of different drivers and thenidentify which drivers contribute toanthropogenic emissions)
15

6.2.

3. Comparison of two time series (thatrepresent two different levels of humanactivities, e.g. current management and no
management, or improved management
vs. business as usual management)

Component separation

This is an approach which seeks to quantify thecontribution of the following:

4. Default factors and optimal fingerprinting(without quantifying the relative
contributions, apply a default factor whichindicates the impact of the human activity)
5. Activity based approach (estimate
emissions by different activities and sum
up anthropogenic contributions))
The meeting considered that these options areworth further investigation. However before they
can be widely used they will need to be assessedwith regard to the science, methodologicalimplications, data requirements (e.g. Tier 1, 2 and 3variations), and consistency with the generalprinciples of inventory guidelines. Thus the
managed land proxy remains for the time being theapproach for distinguishing between anthropogenic
and non-anthropogenic emissions and removals
adopted by the IPCC emission inventory guidelines.

•

Past management and legacies (e.g. age
class legacy) e.g. species distribution,
distribution of forest area by site, andsuppression of natural disturbances•

CO2 fertilisation, N fertilisation, climate(both inter-annual and long term trends),
etc•

The effects of recent anthropogenic
activities on managed land and on areas
outside the managed land (e.g. planting,regeneration, harvesting.)•

The effects of natural and anthropogenic
disturbances (e.g. wildfires, accidental
fires, pest outbreaks, floods, windthrow) on
managed land (and on unmanaged lands)•

Other environmental factors (e.g.
precipitation, temperature trends)

All the proposed refinements to the managed land
proxy are based on modelling frameworks that canspatially integrate the interactions between humanactivities and natural drivers, and their combined
long and short-term effects; this knowledge ismostly site-specific and not currently available at
the global scale. If these models are used they will
have considerable data and information needs andthere will need to be careful consideration of how topresent the methods, assumptions and resultstransparently.

For each factor it is necessary to estimate its impact
on the fluxes of greenhouse gases and so apportion
the total flux between the different factors. This
assumes that the impacts of each factor can be
added linearly – if there are cross-factor effects thisleads to added complications in the approach (e.g.
the impact of CO2 fertilisation may depend on past
management legacies). There are scientificmethods that can be used to identify thesecomponents (8) but their usefulness and global
applicability still need to be assessed.

6.1.

6.3. Comparison between two timeseriesManaged land proxy

The managed land proxy (described above) is a
first approach for distinguishing between
anthropogenic and non-anthropogenic emissions
and removals and is the approach in existing IPCC
guidance, including the 2006 Guidelines.

A comparison of two time series of net GHG
balance estimates could be used to determine theimpacts of two levels of human activities. For
example, a Tier 3 model could be used to represent
current management (i.e. the estimated actual
emissions and removals) and compare these to amodel run with no direct human activities.
Alternatively current levels of management activities
could be compared to business-as-usual
management activities to account for impacts ofchanges in human activities (similar to theapproaches used for project-level accounting).

While the methods described in the other options(below) may help us assess the extent to which thisapproach separates non-anthropogenic andanthropogenic emissions and removals, themanaged land proxy remains the only applicableapproach approved by the IPCC.

16

attribute future changes in soil carbon to changes
resulting from direct impacts of climate on soils,
indirect effects via changes in productivity, changes
in land use, and improved management /technology (Smith J.U. 2005; Smith P. 2006; Smith
P. 2007). Tett and Gedney et al both usedecosystem models and optimal fingerprinting
statistical techniques to attribute observed changes
to different potential causes (Tett S.F.B. 2002;
Gedney N. 2006).

A comparison between the actual time series (amodel of fluxes that actually occurred including
natural, indirect and direct effects) and a second
time series in which the fluxes from the known
anthropogenic factors that drive the emissions are
removed (the factors removed include all harvestingand human-caused fires). The difference inbetween these two resulting estimates can be
attributed to human activities as the impacts ofnatural and indirect effects occur in both time series
and therefore cancel each other out. The direct
anthropogenic impacts on removals must also beassessed and taken out of the baseline.
Identification of direct human impacts on removals
can be difficult in cases such as large-scale fire
suppression where it is difficult to know how muchfire would have occurred in the absence of fire
suppression efforts.

The approach has been used widely to separate out
direct anthropogenic effects. This approach isessentially involved in existing Tier 1 factors forcropland management since those factors were
derived from multiple comparisons of C difference
between different management systems at thesame physical locations. Therefore, indirect andnatural effects are similar for both systems so thefactor is primarily capturing direct anthropogenic
effects. However, by cancelling out much theindirect and natural effects, the existing Tier 1
factors do not report those emissions and removals
that the atmosphere sees. Canada has used thisapproach with Century model for Tier 2 factors (e.g.
(Smith W.N. 2001; Kurz W. A. 2008b)) that areused to estimate C change on cropland forreporting under the UNFCCC. While these methods
are already used to develop default factors that varyover space, time and changes in management
practices, their use to develop default emission
factors would require further elaboration andapplication to a wider range of national
circumstances, followed by formal adoption by the
IPCC.

This approach requires identification of all theanthropogenic factors involved, to model accurately
the anthropogenic drivers of emissions andremovals and to accurately represent the actual
outcomes. This can be achieved with Tier 3 models
that simulate forest dynamics with and without
management such as harvesting or planting.
However, this approach may be able to separateout anthropogenic emissions and removals in amore accurate way than the managed land proxy
without completely representing all the factors
involved. The comparison approach also requiresthat the interaction between anthropogenic factors
and disturbance can be quantified. (Böttcher H.
2008)

6.4. Default factors and Optimal
Fingerprinting

Optimal fingerprinting is a formal detection andattribution technique developed to isolate thecauses of observed change. In short, the models
are run with all factors included, and allowed to vary
within set ranges. The models are then run again,
fixing one potential driver at a time. By comparing
the model outputs to the observations, the distinct
spatio-temporal patterns of the response serve as‘fingerprints’ that allow the observed change to be
separated into contributions from each factor(Gedney N. 2006). These formal detection andattribution techniques can be further developed andused to attribute annual to decadal variability ofcarbon and GHG budgets in managed ecosystems
to human and natural driving processes.

Another approach is to develop and apply default
factors to attribute impacts of anthropogenic andnatural effects on fluxes of greenhouse gases. .
Detailed understanding of the processes involved
could lead to quantification of Tier 1 factors that
could be used by countries to remove nonanthropogenic effects. More confident attribution todifferent anthropogenic and natural factors ofchanges in ecosystems has been developed in thelast few years. (Tett S.F.B. 2002; Tett S.F.B. et al.
2002; Smith J.U. 2005; Gedney N. 2006; Nabuurs
G.J. 2006; Smith P. 2006; Betts R.A. 2007; Eggers
J. 2008; Gillett N.P. 2008; Schelhaas M.J.
Submitted). Smith J.U and Smith P. et al for
example, both used an ecosystem model to

These methods can potentially be used to develop
default factors that would vary over space and/ortime and management practices. This would require17these activities. Currently there is no scientificconsensus about how to construct such a scenario.
Generic studies have developed a basis fordeveloping the activity based approach (Böttcher H.
2008) but decisions on what constitutes the“background” or “baseline” scenario and the"anthropogenic" contributions should result from ascience-policy dialogue.

further elaboration and assessment by the IPCC.
While the development and use of these factors
would greatly simplify the attribution of fluxes to thevarious factors, the approach will need carefulvalidation and documentation to provide credible
results.

6.5.

Activity based approach

In order for this approach to be effective it would benecessary to correctly identify all the humanactivities driving the greenhouse gas fluxes and to
be able to accurately model each of the factors andhow they interact. Currently this may be applicablein specific situations but there is insufficientscientific knowledge at present to apply thisapproach everywhere. Applying this approach at anational scale will need considerable data andinformation and probably will be difficult to apply
transparently.

In this approach, as a first step, specific humanactivities and their impact on emissions andremovals are identified and estimated. The
approach then sums up the impacts of theindividual activities, and accounts only for theircontribution to emissions and removals but
excludes indirect and natural effects that are
currently included in the managed land proxy.
Estimating the impact of specific human activities
on emissions and removals requires assumptions
about a "background" or "baseline" scenario without

18

7. Conclusions

4. The meeting noted progress with thedevelopment of methods for separating
anthropogenic from non-anthropogenic
emissions and removals, and the possibility
for comparison between these methods.
The methods considered by the meetingwere:

1. Despite valid concerns, the managed land
proxy remains a globally applicable,
assessed and approved method forseparating anthropogenic emissions andremovals.
The meeting noted that the managed land
proxy is a first approach for distinguishing
between anthropogenic and nonanthropogenic emissions and removals,
and is the current approach in the 2003
Good Practice Guidance for Land Use,
Land-use Change and Forestry and the2006 Guidelines for National Greenhouse
Gas Inventories. Refinements are being
developed that so far can only be
implemented with higher tier methodologies
2. The meeting recognised that the managed
land proxy has several shortcomings andthat for some national circumstances (forexample Canada and Australia) natural
disturbances can play a significant role influxes from managed land. The managed
land proxy makes a number ofassumptions, none of which is universallytrue: direct effects spill over onto
unmanaged land; natural effects occur inmanaged lands; indirect effects may notoccur mainly on managed land; and naturaleffects on managed land may not averageout to zero over reasonable time scales.
For some countries and circumstances, useof the managed land proxy may lead toemission and removal estimates dominatedby natural effects occurring on managed
land and this would need to be recognised
where inventory estimates were used inestimates of anthropogenic or management
effects. In addition, inter-annual variationsin fluxes (driven by natural effects) may
swamp the changes in fluxes due tomitigation efforts and there may besignificant background uptakes.
3. Tier 1 and Tier 2 approaches may not resultin emission and removal estimates withsignificant inter-annual variability as input
data may be averaged. However moving toTier 3 can result in significant inter-annual
variability where annual climatic effects andannual area disturbed are more correctly
represented or measured.

•

Maintenance of the managed land
proxy

•

Component separation (quantify the
influence of different drivers and thenidentify which drivers contribute toanthropogenic emissions)•Comparison of two time series (thatrepresent two different levels of humanactivities, e.g. current management
and no management, or improved
management vs. business as usual
management)•

Default factors and optimal
fingerprinting (without quantifying therelative contributions, apply a default
factor which indicates the impact of thehuman activity)•

Activity based approach (estimate
emissions by different activities andsum up anthropogenic contributions))

The participants recognized that thesemethods, which largely involve Tier 3
representation of ecosystem dynamics,
could potentially refine the estimation ofanthropogenic emissions and removals but
considered that they needed further work;in particular: with regard to the science;
methodological implications; datarequirements, Tier 1 – 3 variations, andconsistency with the general principles ofinventory guidelines. The meeting hopedthat further work by the scientific community
will result in more mature approaches which
can be assessed at a later date.
5. The meeting noted that the aim of emission
inventories is to provide a best, while
pragmatic, estimate of the emissions andremovals in a given year and thus do not try
to remove or reduce the impact of interannual variations (e.g. those caused byclimate effects). The meeting further noted19

loading due to tree mortality from pest
outbreaks or windthrow). One issue that willneed to be addressed is how to deal withareas with significant natural fluxes, so thatemissions estimated using the current IPCC
guidelines do not reflect the changes seenby the atmosphere. This situation occurs inother sectors but is particularly acute in thewetland sector.

that subsequent accounting can averageout this variability in a transparent manner if
so desired.
While the meeting agreed that annual
emission inventories should estimate theactual emissions in the inventory year, it
was also noted that there is also arequirement to be able to identify the
impact of mitigation and management
efforts even where these are overwhelmedby the impacts of natural processes (e.g.
natural disturbances) or where these are
obscured by inter-annual variations ingreenhouse gas fluxes.

7. Guidance for wetlands will needdevelopment in the future. Currently,
scientific understanding, and the ability totranslate it into practical methods, isimmature. With increasing impacts ofclimate change the relative contribution ofnatural and indirect human-induced fluxes
to the total is expected to increase (thusmaking the managed land proxyincreasingly inappropriate as a proxy offluxes due to direct human activities).
Therefore research needs to continue toquantify the contribution of indirect humanand natural causes of emissions andremovals to develop methods for factoringout direct human impacts from all others.

6. A clearer common understanding ofanthropogenic is needed particularly in
relation to the distinction between direct,
indirect and natural effects, and how toclassify effects that have a range of naturaland direct influences, for example where
there is a natural origin but the emission ismainly determined by direct anthropogenic
factors or where there is an anthropogenic
origin (e.g. fire ignition) but the magnitudeof the emissions is affected by naturalcauses (e.g. extreme drought or high fuel20

Annex 1.

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Tett S.F.B., Jones G.S., Stott P.A., Hill D.C., Mitchell J.F.B., Allen M.R., Ingram W.J., Johns T.C.,
Johnson C.E., Jones A., Roberts D.L., Sexton D.M.H., Woodage M.J. (2002). "Estimation ofnatural and anthropogenic contributions to 20th century temperature change. ." J. Geophys.
Res 107(D16): 4306.
Tett S.F.B. et al. (2002). "Estimation of natural and anthropogenic contributions to 20th century
temperature change. ." J. Geophys. Res 107: 4306.
Worrall F., Reed M., Warburton J., Burt T. (2003). "Carbon budget for a British upland peat catchment."
Science of the Total Environment 312: 133-146.

23

Annex 2.

Co-Chairs Summary

Revisiting the Use of Managed Land as a Proxy for Estimating National Anthropogenic
Emissions and Removals
5 -7 May, INPE, São José dos Campos, Sao Paulo, BRAZIL
Co-Chairs Summary•

Anthropogenic emissions and removals affect the level of greenhouse gases in theatmosphere. The IPCC has grouped these emissions and removals under theheadings: energy; industrial processes and product use; agriculture, forestry and otherland use; and waste.

•

IPCC inventory methods for forestry and land use estimate greenhouse gas emissions
and removals from the atmosphere.

•

IPCC’s advice in the 2006 Guidelines is that the anthropogenic component ofemissions and removals from forestry and land use is the component which occurs on
managed land. This is the managed land proxy.

•

The experts noted the managed land proxy is a first approach for distinguishing
between anthropogenic and non-anthropogenic emissions and removals, and is thecurrent approach in the 2003 Good Practice Guidance for Land Use, Land-use Change
and Forestry and the 2006 Guidelines for National Greenhouse Gas Inventories.

•

The experts noted progress with the development of methods for separating
anthropogenic from non-anthropogenic emissions and removals, and the possibility forcomparison between these methods.

•

The experts noted that these methods include component separation, detailed
modelling grounded in empirical observation, comparison of time series, andfingerprinting. They noted that some of these methods had been outlined inpresentations made during plenary sessions of the meeting, and considered that thesemethods could be helpful in improving estimates. Some of these methods could be thebasis for Tier 1 approaches.

•

The experts noted that where these methods are used to help estimate anthropogenic
emissions and removals, it is important that the methods and estimates are fully
described and transparently documented; are applied in accordance with time seriesconsistency; and follow good practice.

•

The experts noted that the outcome of the meeting will be summarised in a report to
the IPCC Plenary.

TFI Co-Chairs, Saõ José dos Campos, 7th May 200924

Annex 3.

Background Papers

Richard Birdsey, Yude Pan, Jingyun Fang “Carbon Fluxes of Boreal and Temperate
Forests”

24

Gary Richards “Background Paper to the IPCC Expert Meeting Revisiting the use of 30
Managed Land as a Proxy for Estimating Anthropogenic Emissions and Removals”
Pete Smith “Fingerprinting as a technique for attributing direct and indirect humaninduced effects (including changes in C stocks in crop & grasslands caused byclimate change)”37

Werner A. Kurz “Large inter-annual variations in carbon emissions and removals”

39

25

Invited Background paper

Carbon Fluxes of Boreal and Temperate Forests

Richard Birdsey and Yude Pan, (U.S. Forest Service), Jingyun Fang, (Peking University)
Introduction
Here we report recently published estimates of average annual change in carbon stocks forboreal and temperate forests of the northern hemisphere. Estimates are shown for regions orlarge countries, which are generally categorized as boreal or temperate depending on thedominant proportion of forest area falling into the category boreal or temperate. The
approximate time period is the decade 1995-2005, though there is significant variation in thereported estimates depending on the source of information. The most likely causes ofobserved sources and sinks are identified to the extent possible. Significant trends are noted
and as well as the magnitude of interannual variability, if this information is evident in theliterature. Estimates are based on peer-reviewed literature. Some of the estimates include
carbon changes in harvested wood products. There are differences in the treatment of somecarbon pools such as soils, and in the definition of what constitutes a forest.
For the most part, estimates are based on the inventory approach, meaning that the estimates
are calculated from forest inventory data which is converted to carbon using one of several
approaches. This is the generally accepted method for international greenhouse gas inventory
reporting, but there can some variability in estimating biomass carbon according to method if
the approach involves converting volume to carbon (Linder and Karjalainen 2007). This
problem is avoided in the U.S. because the inventory approach involves direct calculation of
biomass from individual tree measurements without requiring the intermediate step of making a
volume estimate (Jenkins et al. 2003). Some of the estimates presented are based on
ecosystem models or other approaches that combine inventory data, models and atmospheric
inversions.

26

Summary Table: Average annual change in carbon stocks by selected regions andcountries, approximate years 1995-2005. Estimates are from country- or region-specificstudies so the separation of boreal from temperate is approximate. Causes of sink orsource and trends are identified where known.
Region and country

Borealforests(TgCyr-1)

Temperate
forests(TgCyr-1)

North America

38

138

Canada

28

USA

190

Trend and interannual Significant causal
variability (if known)
factors1-Probably decreasing-Interannual variability
moderate but increasing-Probably decreasing-High interannual
variability-No significant trend.
-Low interannual
variability.

China

92

-Trend unknown-High interannual
variability-Trend unknown-Low interannual variability-possibly increasing-variability depends on
country-Trend unknown-High interannual
variability-Increasing-Decadal variability

Europe363-No significant trend-Low interannual variability

USA (Alaska)

10

MexicoNorthern Eurasia
Russia

-52
240

455

240

-Varies by country (seebelow)-Age class-Harvesting-Natural disturbance-Age class-Harvesting-Natural disturbance-CO2 and N dep.
-Natural disturbance-Climate variability-CO2-Land cover change-Natural disturbance-Varies by country (seebelow)-Age class-Harvesting-Natural disturbance-Land cover change-Age-class effects-CO2-Land cover change-Age-class effects-CO2-see above-see above
Total of North
America and
278
593
Northern Eurasia
1Land cover change, age-class effects, harvesting or management, natural disturbance, climate
variability, CO2 and N deposition, other factors.

27

Brief Description for Each Region or Country
North America
Between 1990 and 2004, Canada’s forests were a net sink of 17 TgCyr-1 but annual estimates
ranged from a sink of more than 40 TgCyr-1 to a source of 40 TgCyr-1 (Environment Canada
2006). In a given year, boreal forests of Canada may be sources or sinks for carbon
depending largely on wildfire and insect activity (Kurz et al. 2008). The most recent estimates
point toward a more persistent source of CO2 from forests, as mountain pine beetle and otherinsect outbreaks increase. Projections suggest that Canada’s forests will remain a source ofCO2 for several decades (Kurz et al. 2008). This projected source does not include the effects
of increasing CO2 or climate variability, factors that may offset some of the CO2 release fromnatural disturbances (Balshi et al. 2007; Chen et al. 2006).
Temperate forests and wood products of the USA have been a stable sink of about 190 TgCyr-1
for several decades according to estimates based on forest inventories (Birdsey et al. 2006;
Smith and Heath 2008). Interannual variability is low, in the range of + or – 25% of the longterm average primarily because of wildfire and insects. The main causes of the stable carbon
sink are historic harvesting and land-cover changes which have produced an age-class
distribution favorable for high ecosystem productivity, and a steady rate of harvesting for wood
products followed by regeneration. Other approaches to estimating the size of the USA
temperate carbon sink, such as inverse modeling and satellite-driven ecosystem produce
similar but more variable results (Pacala et al. 2001). There is some concern that increasing
tree mortality caused by drought, wildfire and insect outbreaks, may reduce the magnitude of
the carbon sink in future decades (van Mantgem et al. 2008).
Boreal forests of Alaska have sequestered approximately 10 TgCyr-1 (Yarie and Billings 2002;
McGuire et al. 2004). Because of highly variable fire frequency, it is likely that Alaska boreal
forests occasionally release sufficient C during the highest fire years to be a net source of C to
the atmosphere (Tan et al. 2004). Because of the lack of active management of much of
Alaska’s boreal forest, climate change, natural disturbance rates and CO2 fertilization are likely
to be dominant factors now and in the future. Among these factors, CO2 fertilization may havethe dominant effect on ecosystem carbon flux (Balshi et al. 2007).
Temperate forests of Mexico were a net source of about 52 TgCyr-1 to the atmosphere during
the 1990’s, primarily as a result of deforestation and forest degradation, but also reflecting
insect outbreaks, wildfire, and other damages (De Jong et al. 2000; Masera et al. 1997).
Reductions in carbon stocks are partially offset by recovery of degraded forests andestablishment of industrial wood plantations. The trend is not known, but implementation ofafforestation programs and potential adoption of a strategy to reduce deforestation anddegradation could reduce or reverse the historical and persistent source of atmospheric CO2(Masera et al. 2001).
Northern Eurasia
Estimates of carbon flux for Russian forests are highly variable. One recent estimate suggests
a forest carbon sink of 240 TgCyr-1 (Kudeyarov et al. 2007) and another older estimate is 406
TgC yr-1 (Nilsson et al. 2003). Yet another recent study concluded that land-cover and landuse change in northern Eurasian boreal ecosystems resulted in a net source of CO2 to the28atmosphere of 45 TgC yr-1 primarily from fire and climate (Hayes et al. 2009). Factors
influencing the current carbon sink in Russia’s forests include harvesting, age-class distribution,and natural disturbances, which also contribute to a high interannual variability especially fromfire (Balshi et al. 2007). In the future, climate variability and CO2 fertilization will likely become
increasingly important leading to some significant uncertainty about whether the current rate ofsequestration can be maintained, or will increase or decrease.
Between recent forest inventory periods, China’s forests sequestered about 92 TgCyr-1 (Piao et
al. 2009). Age-class structure is driving large periodic changes in the size of the carbon sink, areflection of rates of forest recovery primarily from tree planting (Fang et al. 2007; Pan et al.
2004). Since China continues to implement an aggressive tree planting effort, it is expectedthat the current rate of C sequestration will continue to be high or even increase for many
decades because the increasing area of young forests will maintain the relatively young ageclass distribution (Ju et al. 2007). Another important factor besides age class is likely to be
CO2 fertilization, at least for several decades according to process model simulations (Ju et al.
2007).
In Europe, biomass stocks have been increasing for decades, with the current forest sink
estimated to be approximately 363 TgCyr-1 (Janssens et al. 2003). The main causes of thispersistent C sink appear to be an excess of growth over harvest, a favorable age-class
distribution resulting from increasing forest area, low levels of natural disturbance, reductions indamage from air pollution, and CO2 fertilization (Ciais et al. 2008). Another important factor
may be nitrogen deposition, though it has been difficult to separate this from other factors(Churkina et al. 2007; Magnani et al. 2007). It is likely that forest biomass in Europe willcontinue to increase at least for several decades since current biomass is still significantly lessthan the potential maximum, assuming that the current levels of harvest and disturbanceremain constant (Ciais et al. 2008).
Summary and Conclusions
This brief review estimated that northern temperate and boreal forests sequestered nearly 0.9
PcCyr-1 over the approximate period of 1995-2005. Temperate forests were responsible for
two-thirds of this total. In general, the trend in boreal forest estimates seems to suggest asmaller and highly variable sink in the near future because of natural disturbances, though theprospective impact of climate variability and increasing CO2 may alter this conclusion. The
trend in temperate forests is difficult to assess because the circumstances of individual
countries are highly variable, depending on land use, management, and air pollution much
more than boreal regions.
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Sundquist, E.T.; Stallard, R.F. et al. 2001. Consistent land and atmosphere-based U.S. carbon
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31

Invited Background Paper

Background Paper to the IPCC Expert Meeting Revisiting the use of Managed
Land as a Proxy for Estimating Anthropogenic Emissions and Removals
Dr Gary Richards
Introduction
Article 4(1a) of the United Nations Framework Convention on Climate Change calls for the Parties to:(a) Develop, periodically update, publish and make available to the Conference of the Parties, inaccordance with Article 12, national inventories of anthropogenic emissions by sources andremovals by sinks of all greenhouse gases not controlled by the Montreal Protocol, using
comparable methodologies to be agreed upon by the Conference of the Parties;
In most non-land based reporting sectors (those other than Agriculture and Land Use, Land Use
Change and Forestry) anthropogenic emissions are readily separated from other indirect or naturally
caused emissions. Typically, the emissions in these sectors are point-source, a direct result of humanactivity and instantaneous in response to human action.
In the land sectors this separation of anthropogenic and natural emissions is not so readily achieved.
As pointed out in the IPCC 2006 Guidelines, “The factors governing emissions and removals can beboth natural and anthropogenic (direct or indirect) and it can be difficult to clearly distinguish between
causal factors”.
Beyond the difficulty in directly attributing the ‘cause’ to either anthropogenic or natural source, there is
the added complexity that variability in climate will have a large effect on the scale of emissions fromthe same action over time.
To deal with these difficult separation issues it is necessary to look beyond simple attribution of cause
to find an approach that comprehensively deals with the interrelated impacts of:factoring out natural, indirect and legacy effects;
stabilising interannual variability, andthe overarching need to retain symmetry in accounting while dealing with these impacts.
The Managed Lands Proxy
Moving from the activity based approaches that focussed on attribution of cause as characterised by
the early IPCC deliberations on this issue (see the Rockhampton meeting, September 1997, Expert
group Meeting on biomass burning and land-use change and forestry in dealing with fires) approaches
have followed the general trend LULUCF inventory method to focus on a land use rather a than causal
activity.
Under this land use approach, first seen in the 2003 Good Practice Guidance and furthered in the 2006
IPCC AFOLU Guidelines, lands are separated into managed and unmanaged. Pragmatically, emissions
from unmanaged lands are considered to be natural in origin, and emissions from managed land,32anthropogenic. The effect of this on the reporting of anthropogenic emissions is that naturally caused
emissions (e.g., from natural disturbances) on managed lands are reported as anthropogenic.
The test of this pragmatic approach is how much the reporting of natural emissions on managed landas being anthropogenic would, in both absolute quantum and trend, add to truly anthropogenic(caused) emissions.
If the impact of including them is significant, there is then the question of how emissions from natural
disturbances may be factored out of the emissions estimation on managed lands.
A second issue that arises with the inclusion of emissions from natural disturbances on managed lands
is that they are often episodic in nature. Emissions tend to be instantaneous, while recovery may occur
over decades. This gives rise to concerns that the managed land proxy may, by accepting naturalemissions on managed land, introduce a scale of interannual variability that corrupts any understandingof trends in truly anthropogenic emissions.
A further challenge in implementing the managed land construct is the clarity of the definitional
approach to the separation of managed and unmanaged land, and its ability to be consistently applied
across national inventories.
The 2003 Good Practice Guidance did not provide an explicit definition for managed lands, noting“Managed land may be distinguished from that unmanaged by fulfilling not only the production, but also
ecological and social functions”. That managed lands were a proxy for anthropogenic emissions was
not explicitly stated, but given effect through guidance and methods.
The 2006 IPCC Guidelines were more explicit on the use of managed lands as a proxy foranthropogenic emissions. The 2006 IPCC Guidelines state “For the AFOLU Sector anthropogenic
greenhouse gas emissions and removals by sinks are defined as all those occurring on ‘managed land’.
Managed land is land where human interventions and practices have been applied to perform
production, ecological or social functions”.
The scale at which emissions from natural disturbances and legacy effects add to anthropogenic
emissions, and the extent to which interannual variability is exacerbated, will in part depend on how
narrowly or broadly the definition of managed land is applied. The broader the interpretation, the larger,
in both absolute scale and proportion of reported emissions, amount of non-anthropogenic emissions
that will be included in inventory estimates. One test of the consistency in these interpretations is tolook at the definitions and their impacts in recent inventories compiled under the 2003 Good PracticeGuidance as discussed later in this paper.
Testing the Effectiveness of the Proxy
From the previous discussion, the appropriateness of using managed land as a proxy for anthropogenic
emissions can be tested by:• evaluating how clear and how consistently applied the definition of managed land is;• assessing whether the introduction of non-anthropogenic emissions is of an acceptable scale(while accepting that to do a strict identification of anthropogeicity by cause is not possible andthat this will lead to use of a proxy, and the pragmatism inevitably induced). These nonanthropogenic emissions come from:• natural disturbances;33• indirect effects; and,• legacy (e.g., forest age class structure).
• assessing whether the additional interannual variability caused by the inclusion as anthropogenic
the emissions of natural disturbances, indirect effects and legacy effects beyond those fromnatural fluctuations (e.g., from climate) acceptable?
Given that attempts to attribute emissions to either natural or anthropogenic causes have not worked in
the past and that accounting has moved to a land use basis, there is an inherent logic in dismissing
unmanaged land from accounts. There is the potential that even if one or more of the tests outlined
above raises question over the use of managed land as the singular proxy for anthropogenic emissions,
there may also be the potential to provide some secondary treatments on managed land that limit these
problems.
A second phase of tests can then be applied to determine whether it is possible to treat these
problems, to an acceptable level, within managed land. Provisions contained within the 1996 IPCC
Guidelines and 2003 Good Practice Guidance that attempted to do this include:• the symmetrical removal of both sources and removals by subsequent sinks on lands affected bynatural disturbances; and,• multi-year rolling averages to smooth trends given interannual variability.
• Treatments in the rules and modalities for the Kyoto Protocol to factor out legacy and indirect
effects include:• use of activity cut-off dates to identify lands brought into the accounting (e.g., afforestation,
reforestation and deforestation only after 1990); and,• net-net accounting and caps on gross emissions.
Beyond these approaches that have already been applied to inventories, there is the potential to factor
out age-based legacy effects and to use process-driven (i.e., including climate legacy effects) models tofactor out the effects of climate variability.
Should the use of managed land prove unacceptable as the singular means of separating natural andanthropogenic emissions, then the options outlined above, and others, may be applied on managed
lands to derive an acceptable outcome.
How clear is the definition?
Although the 2003 Good Practice Guidance and 2006 IPCC Guidelines definitions of managed landdiffer, they contain similar elements that could be presumed to lead to the same outcome when applied
nationally. Both definitions seek some form of human benefit around social, ecological and production
functions from managed land.
The key difference between the two that could lead to a divergence in application is that the 2006 IPCC
Guidelines talk about “...human interventions and practices...” which infers that a direct, physical humanactivity is required to bring land into a managed condition. The 2003 Good Practice Guidance is more
ambiguous, not specifying human actions or interventions, but of fulfilling “...not only the production, butalso ecological and social functions”. It is possible that a national definition under the 2003 Good
Practice Guidance could include broad land areas, such as wilderness that are protected from human34intervention, in order to serve an ecological function, but that would not meet the test of “... humaninterventions or practices...” under the 2006 IPCC Guidelines.
As the 2003 Good Practice Guidance provides support for the currently applied guidelines, it is possible
to look at the range of national definitional treatments in the production of current inventories. Two
examples of contrasting approaches are for Australia and Canada. As the 2003 Good PracticeGuidance requires coverage of land for purposes of social and ecological function and given the rangeof legislative provisions that cover the entirety of the national land area, Australia took the decision that
there was no immediate basis for excising land. For forests, this has been the practice of mostcountries. In applying the 2003 IPCC Good Practice Guidance, Canada identified areas of forest thatfell outside of the managed land definitions.
Due to the divergence in application and uncertainty in the eventual definition, the 2003 Good Practiceor 2006 IPCC Guidelines, variants point to a need to further consider the construct and intent of the
managed land definitions. This does not directly question the use of managed land as a proxy foranthropogenic emissions, but points to a need for more clarity and certainty in the definitions if it is toconsistently serve this purpose. Key in this will be determining the inclusiveness of the definition andthis will directly impact on the appropriateness of the proxy. Decisions cannot be taken in isolation ofother potential treatments of natural emissions, legacy effects and interannual variability on managed
land.
Scale of non-anthropogenic emissions entering the accounting
Natural Disturbances
The scale of non-anthropogenic emissions from natural disturbances will be affected by both national
circumstance and the inclusiveness of land into the national managed land definition. For a country like
Australia, with episodic extreme fire events, this is very large - conceivably representing in the order ofover a quarter of the national inventory for all sectors in any one year.
Here again, changes between the 2003 Good Practice Guidance and the 2006 IPCC Guidelines are
germane. The 2003 Good Practice Guidance contained provisions that state“If methods are appliedthat do not capture removals by regrowth after natural disturbances, then it is not necessary to report
the CO2 emissions associated with natural disturbance events”. The effect of the symmetrical inclusion
or exclusion of natural emissions from disturbances is to either respectively include or exclude theaffected land area from accounting. If the occurrence of natural disturbances was stable over time andif the span of accounting covered a full disturbance and recovery cycle, then the net result of either
approach would be the same. Presumably, there would be few instances where the reporting period
was this long, and where there was no interannual variability in scale of natural disturbances.
Under the 2006 IPCC Guidelines, the provisions for exclusion of natural disturbances were removed,
enforcing the potential for the entry of a significant scale of natural emissions to the accounting. This
also meant the interannual variability in emissions was also large.
The impact of the change from the application in the 2003 Good Practice Guidance to the removal ofthese provisions in the 2006 IPCC Guidelines clearly has an impact on the appropriateness of the useof the managed land proxy. In national circumstances, where natural emissions caused by natural
disturbance on managed land are large and variable, the inability to excise those emissions andsubsequent removals (effectively by excising those lands where the natural emissions dominate),
reduces the appropriateness of the use of managed land as a proxy for anthropogenic emissions.
35

Indirect effects
Indirect effects include emissions and removals induced by climate change, CO2 fertilisation andenhanced atmospheric nitrogen deposition.
The question on indirect effects starts with whether they should be considered as anthropogenic (andfactored into anthropogenic accounting), anthropogenic but not directly human induced (and therefore
although anthropogenic are not deliberate or additional and should be factored out of accounting), or
considered a source of natural emissions. Subsequent scientific questions, that may or may not need tobe addressed depending on accounting treatment, are the net direction of overall effects (sinks orsource) and the persistence of any effect.
Independent of both of these considerations is the nature of the lands to which they are applied. If theireffect is limited to managed lands (land where there is human intervention and implementation ofmanagement practice is applied), then presumably any effect will be overwhelmed by the emissions
and removals affected by the management. Therefore, scale is unlikely to be a problem.
For inventories prepared using methods that are sensitive to climate variability, there is the potential for
exacerbated variability (particularly extremes) arising from climate change to disrupt inventory trends.
Presuming that the emissions are to be included in accounting, the issues of trend disruption is then amatter of scale. If small in scale, then inventory trends will not be affected, and this will be the case formany countries. However, for many countries the scale and therefore the trend disruption will besignificant.
The 1996 IPCC (Revised) Guidelines applied ‘smoothing by rolling to means moderate this effect andthe 2003 Good Practice Guidance did not explicitly remove those provisions. However, these provisions
were removed in the 2006 IPCC Guidelines. The effect of the removal of these smoothing provisions
meant that there will be a significant effect of interannual variability from indirect effects that is notmoderated by the use of the managed land proxy for countries that:• have a large area;• adopt an inclusive approach to defining managed lands;• use estimation methods sensitive to climate variability; and,• have variable climates.
• However, large or small, this moderation by the managed land proxy may not fully compensate
for the removal of the smoothing provisions.

36

Legacy effects
Legacy effects are an accounting issue that has multiple dimensions, but is assisted by the managed
land proxy. Legacy effects can be human or natural in source. Presumably legacy effects on
unmanaged land are natural emissions and removals and are therefore rightly excised from accounting.
Legacy effects from both natural and anthropogenic causes can occur on managed land. Depending on
the treatment of natural disturbances (excision or inclusion on managed land), natural emissions (ifexcluded) should not be significant, where the principles applied to current reporting are reapplied topast events that have a legacy (lagged effect) into the inventory reporting period. If not, then the legacy
effect will be a windfall gain from ongoing removals from historic natural disturbances.
For legacy effects from human activity, the question is one of accounting policy and is independent of
the effects of the managed land proxy. It could be taken that where there was a legacy effect from ahuman activity, the land would be defined as managed (the managed land definition making noreference to the human activity or practice being within the accounting and reporting period). In thiscase, decisions on inclusion or exclusion of these emissions is unaffected by the proxy.
Interannual Variability
The acceptability of the scale of interannual variability entering national accounts depends on manyfactors:• the national circumstance (land area, climate variability etc);• the estimation method (targets whether recognising climate variability or not, or on annual or
mulit-year periods);• the inclusiveness of the managed land definition; and,• the inclusion or exclusion of natural disturbances.
The main concerns with interannual variability are not of anthropogenicity, although the more naturalemissions included the larger and more likely variability, but are in the accounting construct. Short baseand reporting periods (e.g., 1990 against commitment period years) have the capacity to be unduly
influenced by variability that diverges from trend. This is particularly for the one year 1990 where thevariability is magnified by five to account for comparison to the five commitment period years under the
Kyoto Protocol.
The provisions for smoothing annual estimates of emissions, as previously applied in the 1996 IPCC
Guidelines provided one approach. Current recommendations are to apply multi-year measurement of
average input data to the estimation process. The different effects of smoothing outputs and inputs
should be carefully tested. Nevertheless, this will only apply to measurement based inventories where
repeat measurement intervals are over many years. For model-based inventories where time-series areusually monthly, , annual estimates are reported.

37

Conclusion
On the basis of the previous discussions, it is worth reframing the question about whether managed
land is proxy for anthropogenic emissions. If proxy is to be taken as the sole and singular treatment toseparate anthropogenic and natural emissions, then managed land is a very questionable proxy.
If the question is reframed, to ask whether the managed land construct assists in separating
anthropogenic emissions then the answer is certainly yes. However, subsequent treatments of atechnical nature (removal of emissions from natural disturbance), and of a policy nature (removal of any
legacy effect and smoothing of interannual variability) should be applied in support.
What would a decision to go down this path mean for the 2006 IPCC AFOLU Guidelines? In regard to
the AFOLU chapter, and in fact the Guidelines more fully, the additional provisions to support the
managed land approach have existed in previous (currently applied) Guidelines, and Good Practice
Guidence. A decision to move to the use of the 2006 IPCC Guidelines by Parties could simply containtext that enabled the carry forward of averaging provisions and the potential to excise emissions andremovals from natural disturbances as contained in the currently adopted Guidelines. The qualifications
on the definition of managed land in the 2006 IPCC Guidelines to require “...human intervention or
managed practices...” would seem to address ambiguity in the 2003 Good Practice Guidance definition.
Recalling that the UNFCCC calls for inventories of anthropogenic emissions only, the ramifications forthe 2006 AFOLU Guidelines would be almost negligible if provisions were added to make the use ofmanaged land an acceptable proxy for separating anthropogenic emissions from natural emissions.

38

Invited Background Paper

Fingerprinting as a technique for attributing direct and indirect humaninduced effects (including changes in C stocks in crop & grasslands
caused by climate change)
Pete Smith
Institute of Biological & Environmental Sciences, School of Biological Sciences, University of Aberdeen,
Cruickshank Building, St Machar Drive, Aberdeen, AB24 3UU, Scotland, UK
The attribution of changes in carbon stocks and in greenhouse gas (GHG) emissions came toprominence when the Kyoto Protocol was signed in 1997(http://unfccc.int/kyoto_protocol/items/2830.php). Article 3.3 of the Kyoto Protocol states that “netchanges in greenhouse gas emissions by sources and removals by sinks resulting from direct humaninduced land-use change and forestry activities” need to be accounted for, and Article 3.4 states that“additional human-induced activities” could also be considered. This wording thrust the science of
attribution of observed ecosystem changes to a) direct human induced factors (e.g. land use and land
management change), b) indirect human induced factors (e.g. climate change and N deposition) or to c)natural factors (e.g. natural climate variability). Working group I of the Intergovernmental Panel on
Climate Change (IPCC) were charged with examining the potential to factor out natural from direct andindirect human induced ecosystem carbon and GHG changes (IPCC, 2003). In considering the use of
split plot multi-factorial experiments and ecosystem models to attribute changes in C stocks and GHG
emissions to natural and direct, and indirect human-induced factors, the IPCC concluded at the timethat “these methods provide only limited potential to separate direct and indirect effects, sincedifferences in carbon stocks and greenhouse gas emissions and removals between plots result not only
from direct human-induced effects but also from the interactions with indirect human-induced effects,
natural effects and past” (IPCC, 2003).
Very recently, advances in modelling and in attribution methodology have allowed the more confident
attribution of changes in ecosystems to different anthropogenic and natural factors (Tett et al., 2002;
Smith et al., 2005; Smith et al., 2006; Gedney et al., 2006; Betts et al., 2007; Gillet et al., 2008, Eggers
et al 2008, Nabuurs et al. 2006, 2008, Schelhaas et al. subm). Smith et al. (2005), Smith et al. (2006)
and Smith et al. (2007), for example, used an ecosystem model to attribute future changes in soil
carbon to changes resulting from direct impacts of climate on soils, indirect effects via changes in
productivity, changes in land use, and improved management / technology. Tett et al. (2002) and
Gedney et al. (2006) used ecosystem models and optimal fingerprinting statistical techniques toattribute observed changes to different potential causes. This is a formal detection and attribution
technique developed to isolate the causes of observed change. In short, the models are run with all
factors included, and allowed to vary within set ranges. The models are then run again, fixing one
potential driver at a time. By comparing the model outputs to the observations, the distinct spatiotemporal patterns of the response serve as ‘fingerprints’ that allow the observed change to be
separated into contributions from each factor (Gedney et al., 2006). These formal detection andattribution techniques can be further developed and used to attribute annual to decadal variability ofcarbon and GHG budgets in managed European ecosystems to human and natural driving processes.
In this presentation I will show how these techniques are already used in climate science, and I willshow examples of how models and data have been used to examine how much observed or modelledchange in soil carbon can be attributed to climate change, and how much can only be explained byother factors. I will finish by presenting an economic analysis of the agricultural mitigation options to39

show how vitally important it is, both environmentally and economically, to develop robust methods thatallow human induced indirect and direct climate effects to be disentangled to allow robust accounting in
the land based sector. I will end with examples of Tier III national accounting systems already in use forcarbon / GHG accounting that have the potential to factor out various causes of observed change on
managed land, and consider if tier I equivalents are possible.
References
Betts, R.A., Boucher, O., Collins, M., Cox. P.M., Falloon, P.D., Gedney, N., Hemming, D.L.,
Huntingford, C., Jones, C.D., Sexton, D.M. & Webb, M.J. (2007) Projected increase in continental
runoff due to plant responses to increasing carbon dioxide. Nature 448, 1037-1040.
Eggers, J., M Lindner, S Zudin, S Zaehle & J Liski. 2008. Impact of changing wood demand, climate
and land use on European forest resources and carbon stocks during the 21st century. Global
Change Biology 14, 1-16.
Gedney, N. Cox, P.M., Betts, R.A., Boucher, O., Huntingford, C. & Stott, P.A. (2006) Detection of adirect carbon dioxide effect in continental river runoff records. Nature 439, 835-838.
Gillett, N.P., Stone, D.A., Stott, P.A., Nozawa, T., Karpechko, A.Y., Hegerl, G.C., Wehner, M.F., Jones,
P.D. (2008) Attribution of polar warming to human influence. Nature Geoscience 1, 750-754.
IPCC (2003) IPCC meeting on current scientific understanding of the processes affecting terrestrial
carbon stocks and human influences upon them. Expert Meeting Report, Geneva, Switzerland, 21–
23 July 2003. IPCC – XXI/INF.1 (22.IX.2003), IPCC Twenty-First Session, 3 and 6–7 November
2003, Vienna.
Nabuurs, G.J., J. van Brusselen, A Pussinen. M.J. Schelhaas. 2006. Future harvesting pressure on
European forests. European Journal of Forest Research 126, 391–400
Nabuurs, G.J., Thurig, N. Heidema, K. Armolaitis, P. Biber, E. Cienciala, E. Kaufmann, R. Makipaa, P.
Nilsen, R. Petritsch, T. Pristova, J. Rock, M.J. Schelhaas, R. Sievanen, Z. Somogyi, P. Vallet 2008.
Hotspots of the carbon cycle in European forests. Forest Ecology and Management 256, 194-200.
Schelhaas, M.J., E Cienciala, J Eggers, T Groen, G Hengeveld, M Lindner, G-J Nabuurs, G Zanchi.
Submitted. Quantification of mitigation measures in European forestry. Submitted to Forest Ecology
and Management.
Smith, J.U., Smith, P., Wattenbach, M., Zaehle, S., Hiederer, R., Jones, R.J.A., Montanarella, L.,
Rounsevell, M.D.A., Reginster, I., Ewert, F. (2005) Projected changes in mineral soil carbon ofEuropean croplands and grasslands, 1990-2080. Global Change Biology 11, 2141–2152. (doi:
10.1111/j.1365-2486.2005.01075.x).
Smith, P., Smith, J.U., Wattenbach, M., Meyer, J., Lindner, M., Zaehle, S., Hiederer, R., Jones, R.,
Montanarella, L., Rounsevell, M., Reginster, I., Kankaanpää, S. (2006) Projected changes inmineral soil carbon of European forests, 1990-2100. Canadian Journal of Soil Science 86, 159-169.
Smith, P., Chapman, S.J., Scott, W.A., Black, H.I.J., Wattenbach, M., Milne, R., Campbell, C.D., Lilly, A,
Ostle, N., Levy, P., Lumsdon, D.G., Millard, P., Towers, W., Zaehle, S. & Smith, J.U. 2007. Climatechange cannot be entirely responsible for soil carbon loss observed in England and Wales, 19782003. Global Change Biology 13, 2605-2609. doi: 10.1111/j.1365-2486.2007.01458.x.
Tett, S.F.B. et al. (2002) Estimation of natural and anthropogenic contributions to 20th century
temperature change. J. Geophys. Res. 107, 4306. (doi:10.1029/ 2000JD000028).

40

Invited Background Paper

Large inter-annual variations in carbon emissions and removals
Werner A. Kurz
Canadian Forest Service
Natural Resources Canada
506 West Burnside Road,
Victoria BC, V8Z 1M5, Canadae-mail: wkurz@nrcan.gc.ca
BackgroundThe underlying assumption of the “managed land proxy” is that for the land use, land-use change andforestry (LULUCF) sector, the emissions and removals from managed lands are primarily due toanthropogenic activities. This proxy is currently used for the reporting of national greenhouse gas(GHG) budgets because there is no agreed-upon methodology to separate direct-human induced
emissions and removals from those emissions and removals that are attributable to natural or indirect
human-induced causes.
Forests are under varying degrees of direct human influences. In some large countries not all regions
are accessible, populated or otherwise affected by direct human influences. The managed land proxy
therefore provides a crude first approximation to distinguish between direct-human and other causes bystratifying the land area into managed and unmanaged components. While the managed land proxyhas been useful in enabling the initial development of national greenhouse gas inventories for the
LUCUCF sector, data now available raise several concerns. Here we focus on concerns for the
managed forest.
First, in large countries with low population density (such as Canada, Russia, Australia and others) thecontribution of natural and indirect-human induced processes to the net greenhouse gas balance of the
managed forest can be very large and confound the contribution of anthropogenic activities.
Second, the interannual variability of the net GHG balance can be very large as a result of interannual
variability in climatic conditions, and (in part as a consequence of this variability) in natural
disturbances, including fires, insects, windthrow and drought.
Third, the predicted impacts of climate change include increases in natural disturbance rates and otherextreme events, as well as increasing mal-adaptation of existing forest to the new climatic conditions.
These climate change impacts are projected to increase the influence of indirect-human and naturalprocesses on the net GHG balance in the managed forest. This will render the managed land proxyincreasingly inaccurate and inappropriate as a means for reporting emissions and removals fromanthropogenic activities.
Here we will briefly describe the factors contributing to large interannual variations in reported GHG net
balances for the managed forest, and discuss ways in which these might be addressed such thatanthropogenic emissions and removals are separated from those caused by natural and indirect-humanprocesses.

41

Summary of Disturbance Impacts on Emissions and Removals
Natural disturbances (such as wildfires, insect outbreaks, and windthrow) differ in several ways withregard to their impacts on greenhouse gas emissions and removals: these include the magnitude andtiming of emissions in the year of the disturbance and thereafter, as well as the temporal variability inthe occurrence of the disturbances.
Impacts on GHG emissions and removals
Fires cause large emissions in the year of disturbance from the consumption and oxidation of biomass
and dead organic matter in the litter, fine and coarse woody debris pools. Fires also contribute large
quantities of non-CO2 greenhouse gas emissions in the form of CH4 and N2O. Crown fires are typicallystand replacing and kill a large proportion of the live tree biomass, while ground fires result in no orpartial tree mortality. In Canada, the average amount of carbon transferred annually from live biomass
to dead organic matter pools through wildfire exceeds the amount of carbon emitted directly to theatmosphere during the fire. Fire-killed biomass added to dead organic matter decomposes in the years
after the burn. Fires therefore affect post-disturbance carbon dynamics with burned stands acting as net
carbon sources for several yeas post fire until, following regeneration and stand establishment, theregrowing forest contributes a larger sink than areas that were not affected by fire.
Insects cause negligible direct emissions in the year of the outbreak. The primary impact of defoliatinginsects is initially a reduction in tree growth (and therefore net carbon uptake). Repeated defoliation
events can lead to increasing tree mortality. Bark beetles can cause significant mortality rates in the firstyear of stand attack. Depending on the proportion of host tree species in the stand, the amount ofmortality caused by the insect, and the response of the surviving trees, forests can be turned into net
carbon sources for one or more years after the insect outbreak.
Windthrow reduces C uptake immediately after the event, and like insects, does not cause (material)
increased emissions in the year of the event. In the years after the event stands affected by windthrow
will be net sources of greenhouse gases but will eventually turn back into sinks.
The carbon dynamics after all types of natural disturbances is further affected by salvage logging whichremoves carbon that would otherwise be released through decomposition and transfers some of it toharvested wood products or bioenergy uses. Rates of carbon uptake can further be affected by humanactivities aimed at accelerating forest regrowth including planting, vegetation management or otheractivities aimed at accelerating the establishment of a forest.
The implication of the temporal responses of emissions and removals following different typesof disturbance is that the direct emissions from wildfire are strongly correlated with area
disturbed. But for all other disturbances and for post-fire emissions, the impacts on the emissions andremoval balance occurs in the years after the disturbance, contributing to greater emissions during theinitial years after the disturbance and to greater removals in later years. Quantification of the temporal
dynamics of post-disturbance carbon dynamics is necessary if impacts from natural disturbances were
to be separated from anthropogenic contributions.
Temporal variability
Fires are characterized by large regional variations in the proportion of the forest area annually burned.
Area burned also displays high inter-annual variability, with minimum and maximum area burned
differing by as much as an order of magnitude. Area annually burned can also exhibit high inter42

decadal variability, with decadal averages in area burned differing by factors of two or more (Mouillot
and Field 2005). Long-term trends in annual area burned, both increasing and decreasing have been
observed in different regions of the world over the last century (Mouillot and Field 2005).
Insect outbreaks are characterized by multi-year cycles of high insect impacts followed by multi-year
periods of low impact levels. In some regions such cycles have been observed over centuries (e.g.
Esper et al. 2007, Swetnam and Lynch 1993). Climate change impacts (and other factors) havecontributed to an unprecedented outbreak of the mountain pine beetle (Dendroctonus ponderosae
Hopkins) on the greenhouse gas balance of the managed forest in British Columbia, Canada (Kurz etal. 2008a), and other regions of western North America. Other insect species are also expected toincrease in range and impact, while others are expected to continue their outbreak cycles.
Windthrow, like fires, is characterized by large interannual variability, with many years of no or little
windthrow punctuated by occasional extreme events. Several storms in Europe caused tree mortality inexcess of annual harvest.
The implications of the temporal variability in disturbance regimes for the managed land proxy
are twofold. First, the contribution of emissions from wildfires as proportion of total emissions in the
managed forest varies greatly between years, and while it can be estimated (once the area burned in
known) it is not predictable. Second, even decadal (or longer) averages of disturbance impacts varyconsiderably, as a result of processes affecting regional area burned such as the Pacific Decadal
Oscillation (Balshi et al. 2008, Calkin et al. 2005) or regional-scale outbreaks of insects. Thus,
lengthening the accounting period for emissions and removals is by itself not sufficient to address
temporal variability in natural disturbance regimes.
Long-term trends
It is well established that changes in forest disturbance regimes are associated with changes inemissions and removals (Kurz and Apps 1999, Hurtt et al. 2002, Birdsey et al. 2006). The predicted
impacts of global change on forests include, among others, forecasts of changes in natural disturbance
regimes, in particular increases in the area annually burned (Balshi et al. 2008, Amiro et al. 2009).
Increases in the areas affected by natural disturbances, will however, also increase the contribution of
non-anthropogenic process to the emissions and removals reported for the managed forest. This willfurther diminish the suitability of the managed land proxy as an estimate of human-induced emissions
and removals in the future.
Relationship between interannual variability and choice of reporting method
The IPCC Guidelines for LULUCF (and AFOLU) reporting provide parties with choices regarding themethods used to prepare estimates of GHG emissions and removals from managed forests. National
circumstances, such as the availability of forest inventories, remote sensing programs and modelingtools have contributed to parties’ methodological choices. The magnitude of interannual variability ofemissions and removals reported for the managed forest is, however, strongly affected by the choice of
methods.
IPCC guidelines describe two approaches: (1) The default method which calculates stock changes as
the difference between gains and losses and (2) the stock change method which estimates thedifference between stocks at two points in time (IPCC 2003, IPCC 2006).
43Stock change approach
Estimating carbon emissions and removals from the difference in carbon stocks over a period, e.g. twoforest inventories compiled 10 years apart, yields the average stock change from all causes over the
10-year period. Unless auxiliary information is used to annualize the periodic change, there is nointerannual variability in the estimate.
In practice, parties rarely conduct complete inventories in a single year but measure a proportion of all
inventory plots every year. More complex statistical methods are required to annualize such acontinuous inventory and the results will show greater interannual variability. However, because natural
disturbance impacts from the past year are only observed in the subset of plots remeasured this year,
interannual variability tends to be “dampened”. Moreover, in times of increasing natural disturbance
rates, the impacts of disturbances can be underestimated in the most recent year(s), while in times ofdecreasing disturbances disturbance impacts in the most recent year(s) can be overestimated.

One inventory plus change
The second approach to estimating emissions and removals in the managed forest is typically
implemented using detailed data plus models. Parties that implement this approach usually track
annual area disturbed by wildfire and other disturbances and their impacts result in much larger
interannual variability in reported emissions and removals. The choice of model further affects themagnitude of interannual variability.
No climate variability
Parties that use empirically driven models, i.e. those in which forest growth rates are specified by yield
tables or other forms of yield models that are not sensitive to variations in annual climate, will not reportthat component of removals that is associated with annual variability in tree growth rates due to climate
variability. Unless there are long-term trends in climate (or other factors not captured in the empiricalyield tables) the yield tables are expected to average growth rates over a period. It is good practice toconfirm from time to time that the yield tables adequately represent growth rates.
Estimates of emissions associated with heterotrophic respiration (decomposition) are typically derived
from process models (e.g. Kurz et al. 2009). Parties have the choice, however, to estimate
decomposition rates using either average climate conditions or to account for interannual variability inclimate. To be consistent with the representation of tree growth, the Canadian estimation methods
currently use average climate to estimate decomposition rates. Using annual climate parameters would
increase interannual variability in emissions from decomposition.
But even with the impacts of natural disturbances alone, interannual variability in the time series ofemissions and removals in Canada’s managed forest between 1990 and 2007 spans 300 Mt CO2e,equivalent to about 40 % of the emissions in all of Canada (excluding the LULUCF sector). The
predicted variability in the 5-year average of the net GHG balance of Canada’s managed forest for the
first commitment period covered a range of about 200 Mt CO2e due to the large variability in natural
disturbances (Kurz et al. 2008b).
With climate variability
Parties that use climate-sensitive process models to estimate emissions and removals in the managed
forest will report high interannual variation in emissions and removals because their estimates areaffected by both, variations in climate and variations in natural disturbances. In this case, the annual44estimates of anthropogenic emissions and removals in the managed forest are substantiallyconfounded with the impacts of natural disturbances, weather variability and long-term climate trends.
The implications of the choice of estimation method for the interannual variation in reported
emissions and removals in the managed forest proxy can be substantial. It is important to notethat the choice of estimation method affects both the proportion and the timing of the emissions andremovals that are included in the reporting.
Factoring out Processes that Contribute to Interannual Variability
Four methodological options to factor out processes that contribute interannual variability in theemissions and removals are discussed briefly. All involve model simulations and comparisons between
two sets of estimates and all require that the “actual” emission and removals be calculated using theactual human activities, natural disturbances and climate (in the case of models in which climate
variability contributes to emissions and removals). The options differ with regard to the reference
against which these actual values are compared and consequently, how the results of the comparison
need to be interpreted.
Option 1: compare to a scenario with average climate and no disturbances
The first option involves comparing the estimates of actual emissions and removals against the resultsof a second simulation with long-term average climate and no natural disturbances. The difference inthe resulting estimates of emissions and removals can be attributed to natural disturbances andvariations in climate from the average.
Option 2: compare to a scenario with average climate and average disturbances
A variation of the first option would be to use average climate and average disturbance rates for thecomparison against the actual. The difference in the resulting estimates is then attributed to deviationsin climate and disturbances from long-term averages. It would be difficult, however, to determine thelong-term average disturbance rates in periods of change.
Option 3: compare to a scenario with BAU human activity
The third option involves comparing actual estimates against a simulation with the same data on natural
disturbances and climate, except this second simulation uses a “business-as-usual” level of humanactivities. The difference in the resulting estimates can be attributed to changes in human activities
between the baseline and the actual. The impacts of natural disturbances and indirect human effects
are the same in both simulations and therefore cancel each other out.
Option 4: compare to a scenario with no human activity
A fourth option is to compare actual estimates against a simulation in which all anthropogenic impacts
that cause emissions, including all harvesting and human-caused fires are removed. The difference inthe resulting estimates can be attributed to all human activities between the baseline and the actual.
This approach would be more difficult to implement because in this approach the direct anthropogenic
impacts on removals must also be assessed and taken out of the baseline.
For example, if fire suppression efforts are practiced, then how large would the area annually burned bein the absence of such efforts? Note that in many countries less than 5% of the number of fires causewell over 90% of the area burned (Stocks et al. 2002, Calkin et al. 2005). So even a small increase in
the number of fires that are not contained could trigger large increases in area burned. Similarly, where
efforts to suppress insect outbreaks are practiced, these will contribute towards maintaining or45

increasing forest carbon stocks. It is difficult to predict what the insect impacts would have been, had
humans not implemented control activities.
The carbon dynamics of a forest region can be simulated with and without a natural disturbance event.
For example, the difference in emissions and removals between simulations with and without thecurrent Mountain Pine Beetle outbreak in British Columbia, Canada, was 990 Mt CO2e over the 20-year
outbreak period (Kurz et al. 2008a). Thus quantification of the natural disturbance impact is possible.
More difficult, however, is the question whether an insect outbreak is entirely a “natural” disturbance orwhether anthropogenic actions have contributed to it. An unknown fraction of the fires 80 to 120 years
ago could have been caused by human activities. While the pine stands regenerated naturally after
these fires, management decisions, some made decades ago, to suppress fires or to protect stands
from harvesting contributed to today’s host conditions. While the insect outbreak has reached its current
scale because of warmer climatic conditions that contributed to higher winter survival rates and range
expansions northward and to higher elevations, a small but unquantifiable contribution of past
anthropogenic activities cannot be ruled out.
Similarly, catastrophic, large-scale windthrow events that recently affected European countries areclearly caused by the extreme natural events. But did silvicultural decisions over past decades that
affected species choices and stand structure, contribute to the magnitude of the impact of the natural
events? Lastly, fire protection efforts and fuel management can both affect the future area burned by
wildfire.
While the question of complete attribution of natural disturbance events to natural and anthropogenic
causes may be of scientific interest, it greatly complicates any attempts to factor out the direct-humanimpacts on interannual variability from other factors.
If the intent of national GHG inventories is to report the impacts of current anthropogenic
activities then the complications arising from the interactions of past human activities andnatural disturbances can perhaps be ignored?
Conclusions
The two primary sources of interannual variability in GHG emissions and removals in the LULUCF
sector are natural disturbances (such as fire, insects, windthrow, and ice storms) and climate variability(e.g., weather, drought, and cold or hot extremes). Natural disturbances have large impacts per hectare
in the areas where they occur, while climate variability typically causes small changes per hectare but
over large areas.
The impact of disturbances on emissions and removals is not limited to the year of the disturbance. The
ratio of direct emissions and post-disturbance emission differs between disturbance types: fires cause
large direct emissions in the year of the fire, and also considerable post-fire emissions from trees killedin the fire. Insects and windthrow cause very small or no immediate emissions but contribute to large
post-disturbance emissions (and reduced removals).
Fires and windthrow are highly episodic with very large interannual variability. Large interdecadal
variability has also been documented for fires. Insects typically occur in outbreak cycles that can lastfrom several years to a decade or more – these outbreak cycles contribute to interdecadal variability.
46

Using the “managed land” proxy to account for direct human effects yields estimates of emissions andremovals that are to varying degrees confounded with the impacts of natural disturbances and climate
variability.
Factoring out direct human impacts from the impacts of natural disturbances and direct human-induced
effects is at least partly possible and four examples have been provided here. All involve thecomparison between two runs of the same simulation model, but they differ in their approach to which
factors are included or excluded in the pair of simulations used in the comparisons.
Complex issues arise when trying to assess the effects of human activities on the suppression ofnatural disturbances because it is difficult to determine what natural disturbances would have occurredin the absence of suppression and control efforts.
With climate change impacts predicted to cause significant increases in the area annually burned andthe associated emissions in many regions of the world (e.g. Balshi et al. 2008, Amiro et al. 2009),
finding ways to separate direct-human impacts on emissions and removals from natural and indirect
impacts will be increasingly important. This is recognized by the international community and is the
subject of ongoing climate negotiations and scientific research.
References
Amiro, B.D., A. Cantin, M.D. Flanningan, W.J. de Groot, 2009. Future emissions from Canadian boreal
forest fires, Canadian Journal of Forest Research 39: 383-395.
Balshi, .M.S., A.D. McGuire, P. Duffy, M. Flanningan, J. Walsh, J. Mellilo, 2008 Assessing the responseof area burned to changing climate in western boreal North America using a Multivariate
Adaptive Regression Splines (MARS) approach, Global Change Biology 14, 1–23, doi:
10.1111/j.1365-2486.2008.01679.x
Birdsey, R. K. Pregitzer, and A. Lucier 2006. Forest Carbon Management in the United States: 1600–
2100, Journal of Environmental Qualilty 35:1461–1469.
Calkin, D.E., K.M. Gerbert, J.G. Jones, R.P. Neilson 2005. Forest Service Large fire area burned andsuppression expenditure trends, 1970 – 2002, Journal of Forestry, 179-183.
Esper J., U. Büntgen, D.C. Frank, D. Nievergelt and A. Liebhold, 2007. 1200 years of regular outbreaks
in alpine insects, Proc. R. Soc. B (2007) 274, 671–679, doi:10.1098/rspb.2006.0191
Intergovernmental Panel on Climate Change (IPCC), 2003. Penman, J., et al. (Eds.), Good PracticeGuidance for Land Use, Land-Use Change and Forestry. Institute for Global Environmental
Strategies, Hayama.
Intergovernmental Panel on Climate Change (IPCC), 2006. Eggleston, S., et al. (Eds.), Guidelines for
National Greenhouse Gas Inventories. Institute for Global Environmental Strategies, Hayama.
Kurz, W.A., Apps, M.J., 1999. A 70-year retrospective analysis of carbon fluxes in the Canadian forest
sector. Ecol. Appl. 9, 526–547.
Kurz, W.A., C.C. Dymond, T.M. White, G. Stinson, C.H. Shaw, G.J. Rampley, C. Smyth, B.N. Simpson,
E.T. Neilson, J.A. Trofymow, J. Metsaranta, M.J. Apps, 2009, CBM-CFS3: a model of carbondynamics in forestry and land-use change implementing IPCC standards, Ecological Modelling
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Kurz, W.A, C.C. Dymond, G. Stinson, G. J. Rampley, E.T. Neilson, A. L. Carroll, T. Ebata, and L.
Safranyik, 2008a, Mountain pine beetle and forest carbon feedback to climate change, Nature
452:987-990,
Kurz, W.A., G. Stinson, G.J. Rampley, C.C. Dymond and E.T. Neilson, 2008b, Risk of natural
disturbances makes future contribution of Canada’s forests to the global carbon cycle highly
uncertain. Proceedings of the National Academy of Sciences, 105: 1551-1555.
Mouillot F., and C.B. Field 2005. Fire history and the global carbon budget: a 1ox 1o fire history
reconstruction for the 20th century, Global Change Biology 11, 398–420 doi: 10.1111/j.13652486.2005.00920.x
Stocks B.J., J.A. Mason, J.B. Todd, E.M Bosch, B.M. Wotton, B.D. Amiro, M.D. Flannigan, K.G. Hirsch,
K.A. Logan, D.L. Martell, and W.R. Skinner.2002. Large forest fires in Canada, 1959–1997.
Journal of Geophysical Research, 108: 8149, doi: 10.1029/2001JD000484.
Swetnam, T.W. and A.M. Lynch, 1993. Multi-century, regionalscale patterns of western sprucebudworm history. Ecol. Monogr. 63, 399–424. doi:10.2307/2937153

48

Annex 4.

Presentations

All presentations are available on the IPCC TFI website http://www.ipcc-nggip.iges.or.jp/
Simon Eggleston – Introduction
María Sanz- Sánchez- Treatment of LULUCF Inventories under UNFCCC
Nalin Srivastava - Treatment of Anthropogenic Emissions/Removals in IPCC GHG Inventory Guidelines
Jim Penman - Scoping of meeting including summary of previous IPCC meetings and overall issues
Jennifer Jenkins - Overview of earlier IPCC and other Activities
Gary Richards – The Use of Tier 3 Systems to Factor Out Non-Anthropogenic Emissions and Removals on Managed Land(presented by Annemarie Watt)
Luiz Gylvan Meira Filho – Climate Change and Carbon in the Biosphere
Werner Kurz – Large inter-annual variations in carbon emissions and removals
Zucong Cai – Methane and Nitrous Oxide emissions from rice fields
Pete Smith – Fingerprinting as a technique for attributing direct and indirect human induced effects
Richard Birdsey & Yude Pan – Carbon Fluxes of Boreal and Temperate Forests
Dominique Blain – Managed Land and GHG Emissions/Removals in Wetlands
Joel Goldenfum – Emissions from Freshwater Reservoirs
Zoltan Somogyi – Using the carbon accounting model CASMOFOR to separate the effect of disturbances (“mortality”), ageclass distributionand site distribution: need and feasibility
Devendra Pandey – National Forest Inventory and Assessment of Forest Biomass Carbon Stock of India’s Forests

49Annex 5.
09:30 –
10:00

Tuesday 5th May

10:00 –
12:30

12:3014:00

AgendaWelcome,Introductory Remarks
Plenary 1 – Invited Background Papers
Background: Aims and Objectives
Treatment of LULUCF Inventories and anthropogenic
emissions/removals required by UNFCCC
Treatment of “Anthropogenic Emissions/Removals” in IPCC
GHG Inventory Guidelines
Scoping of meeting including summary of previous IPCC
meetings and overall issues
Overview of earlier IPCC and other Activites
Discussion

Thursday 7th May

Wednesday 6th May

17:00 17:30
09:30 –
12:30
12:3014:00
14:00 –
14:30
14:30 –
17:30
09:30 –
11:00
11:00 –
12:30
12:3014:00
14:00 –
15:30

Simon Eggleston
UNFCCC
Nalin Srivastava
Jim Penman (UK)
Jennifer Jenkins (USA)

LUNCH
Existing modelling approaches to LULUCF/AFOLU
emissions/removals – how do they treat direct and indirectcontributions to carbon fluxes?
Forest Carbon Sink

14:00 –
16:00

Hosts and Co-Chairs
Taka Hiraishi

Large Inter-annual variations in emissions/removals
Methane and Nitrous Oxide Emissions from Soils
Fingerprinting as a technique for attributing direct and indirect
effects (including changes in C stocks in crop & grasslands
caused by climate change)
Wetlands – including peatlands
Discussion
Introduction to Break Out Groups

Gary Richards (Australia)
Luiz-Gylvan Meira-Filho(Brazil)
Werner Kurz (Canada)
Zucong Cai (China)
Pete Smith (UK)
Dominique Blain (Canada)
TSU

2 Breakout Groups (Forest and All Other Lands)
LUNCH
Plenary 2
Reports from BOGS and Discussion
Decide BOG focus for afternoon
BOG discussions continue

Plenary 3 – Reports from BOGS and Discussion.
BOGs draft outline of meeting report
LUNCH
Plenary 4 Agree Draft Outline and Co-Chairs Statement50Annex 6.

Participants List
Carlos Eduardo M TUCCIRhama Consultoria Ambiental Ltda
Rua Lavradio 150/01
90690-330 - Porto Alegre – RS
BrazilTel: +55 51 3398 3755
Fax: +55 51 3308 7292
tucci@rhama.net

Australia
Annemarie WATT
Development of Climate Change
GPO Box 854 Canberra AG 2601
Tel: +61 2 6159 7320
Annemarie.watt@climatechange.gov.au
Bolivia
Emilio GARCIA-APAZANational Programme on Climate Change
1328 Mercado Street
Sala 101 - Ilha do Fundão
Tel: 00591-2-2200206
Fax: 00591-2-2204037
garciaa_emilio@yahoo.com

CanadaBrazilBrian Glenn MCCONKEY
Government of Canada, Agriculture and Agri-Food
CanadaSemiarid Prairie Agricultural Research Centre
Tel: 1 306 778-7281
Fax: 1 306 778-3188
mcconkeyb@agr.gc.ca

Dominique BLAIN
Environment Canada
200 boul Sacré Coeur
Tel: 1 306 778-7281
Fax: 1 306 778-3188
dominique.blain@ec.gc.ca

Luiz PINGUELLI ROSACOPPE/UFRJ
Centro de Tecnologia
bloco G - sala 101 - Ilha do Fundão
Rio de Janairo –lpr@adc.coppe.ufrj.br

Werner Alexander KURZ
Natural Resources Canada, Canadian Forest
Service
506 West Burnside Road, Victoria,
BC V8Z 1M5
Tel: 1 250 363 6031
Fax: 1 250 363 0775
Werner.Kurz@nrcan.gc.ca

Newton PACIORNIKMinistry of Science and Technology –General Coordination on Climate Change
Praia do Flamengo 200 - 7º andar - Rio de Janeiro
BrazilTel: 55-21-25550308
Fax: 55-21-25550306
npaciornik@mct.gov.br
Luiz-Gylvan MEIRA-FILHO
University of São Paulo / Institute for Advanced
StudiesAl. Dos Arapanés, 982
Ap. 111 – Moema
Cep 04524-001
São Paulo
Fax: (55)(11)82022407
lgylvan@uol.com.br

China
Chengyi ZHANG
National Climate Center, China Meteorological
Administration
46 Zhongguancun Nandajie
Haidian District, Beijing 100081
Tel: +86-10-6840-7420
Fax: +86-10-6217-6804
zhangchy@cma.gov.cn

51

Guatemala

Zucong CAI
Institute of Soil Science, Chinese Academy of
Sciences
East Beijing Road 71# Nanjing
Tel: 86-25-8688-1021
Fax: 86-25-8688-1000
zccai@issas.ac.cn

Edwin CASTELLANOS
Universidad del Valle de Guatemala
Tel: (502) 2368 8353
Fax: (502) 2369 7358
ecastell@uvg.edu.gt
Guinea-Bissau

DenmarkJOÃO LONA TCHEDNA
Meteorological Service
Direction Generale de la Meteorologie Nationale:
Cx.P. No 75 1038
CEDEX-BISSAU
Tel: 00245 652 87 16
Fax: 00245 320 17 53
J_Lona@yahoo.fr
dgmeteobissau@yahoo.fr

Peter Aarup IVERSEN
Ministry for Climate and Energy
Stormgade 2-6 1470 Copenhagen, Denmark
Tel: +45 33922942
Fax: + 45 33922801
piv@kemin.dk
FinlandTuija LAPVETELÄINEN
Statistics Finland
PB 6A 00022 Statistics Finland
Tel: +358-9-1734 3429
Fax: +358-9-1734 3429
tuija.lapvetelainen@stat.fi

Hungary
Zoltan SOMOGYI
Hungarian Forest Research InstituteFrankel L. u. 42-44. Budapest
Hungary
Tel: +36-30-465-2684
Fax: +36-1-326-1639
somogyiz@erti.hu

Jukka ALM
Finnish Forest Research Institute (FFRI)
P.O. Box 68 FI-80101 Joensuu Finland
Tel: (+358)50391 3107
Fax: (+358)10211 3001
jukka.alm@metla.fi

India
Devendra PANDEY
Forest Survey of India (Ministry of Environment &Forests)
Kaulagarh Road, PO: IPE Dehradun-248195, India
Tel: +91-135-2756139
Fax: +91-135-2759104
dpandeyifs@rediffmail.com

FranceMartial BERNOUXInstitut de Recherche pour le Développement - IRD
UMR Eco&Sols - Campus SupAgro - Bat 12
Tel: (33)499612108
Fax: (33)499612119
martial.bernoux@ird.fr

Indonesia
Ruandha Agung, Ir. SUGARDIMAN
Ministry of Forestry of The Republic of Indonesia
Manggala Wanabakti Building
Block I 7th Floor
Jl. Gatot Subroto,
Jakarta-10270
Indonesia
Tel: 62215730293
Fax: 62215734632
ra.sugardiman@gmail.com

Germany
Annette FREIBAUER
Johann Heinrich von Thuenen Institute,
Institute for Agricultural Climate Research
Bundesallee 50 38116 Braunschweig
Tel: +49-531-5962634
Fax:+49-531-5962599
annette.freibauer@vti.bund.de52

JapanSouth Africa

Masahiro AMANO
Waseda University
Mikajima 2-579-15 Tokorozawa
Saitama 359-1192
Tel: +81-42-947-6740
Fax: +81-42-947-6740
masahiro_amano@waseda.jp

Khanyisa BRIAN MANTLANA
South African National Biodiversity Institute
P/Bag x 7; Claremont; 7735
Tel: 27217998818
Fax: 27217976903
mantlana@sanbi.org

Satoshi AKAHORIForestry Agency, Japan
36893 Kasumigaseki
Chiyoda-ku, Tokyo
Tel: +81-3-3502-8240
Fax: +81-3-3502-2104
satoshi_akahori@nm.maff.go.jp

SwedenLesotho

Switzerland

Klas, H. ÖSTERBERG
Swedish Environmental Protection Agency
Valhallavägen 195 10648 STOCKHOLM
Tel: 46709326451
Fax: 466981433
klas.osterberg@naturvardsverket.se

Mphethe TONGWANE
Lesotho Meteorological Service
P.O.BOX 14515 MASERU 100
Tel: 00266 22324374
Fax: 00266 22325057
tongwane@lesmet.org.ls

Andreas FISCHLIN
Terrestrial Systems Ecology
ETH Zurich
Universitatstrasse 16, CHN E 21.1
8092 Zurich, Switzerland
Tel: 41446336090
Fax: 41446331123
andreas.fischlin@env.ethz.ch

Papua New Guinea
Sandro FEDERICI
c/o Coalition for Rainforest Nations
Columbia University
New YorkUSA
Sandro.federici@gmail.com

TuvaluIan FRY
Government of Tuvalu
PO Box 7008, Karabar NSW 2620
Tel: 61 2 6299 7558
Fax: 61 2 6284 3136
ianfry@envtuvalu.net

RussiaVladimir Nikolaevich KOROTKOVInstitute of Global Climate and Ecology under
Russian Hydrometeoservice and Academy of
Sciences
20-B Glebovskaya str. Moscow, 107258
Tel: +7 (499) 169-21-98
Fax: +7 (499) 160-08-31
korotkovv@list.ru

UK
Pete SMITH
University of Aberdeen
Institute of Biological and Environmental Sciences
School of Biological Sciences
University of Aberdeen, Cruickshank Building, St
Machar Drive, Aberdeen, AB24 3UU, Scotland, UK
Tel: +44 1224 272702
Fax: +44 1224 272703
pete.smith@abdn.ac.uk

53

FAO

Mark Stephen John BROADMEADOW
Forestry Commission of Great Britain
231 Corstorphine Road, Edinburgh, Midlothian,
EH12 7AT
Tel: +44 1483 326204
Fax: +44 1420 22988
mark.broadmeadow@forestry.gsi.gov.uk

Parviz KOOHAFKAN
FAO
Via del Terme di Caracalla,
00100 Rome, Italy
Tel: 00390657053843
Fax: 00390657056275
Parviz.Koohafkan@FAO.org

USA

Danilo MOLLICONE
Food and Agriculture Organization
via delle Terme di Caracalla, 00100 Roma, Italy
Tel: 0039 06 57055978
Fax:
Danilo.mollicone@fao.org

Richard A. BIRDSEY
U.S. Forest Service
11 Campus Blvd Suite 200,
Newtown Square, PA, 19073
Tel: 01-610-557-4091
Fax: 01-610-557-4095
rbirdsey@fs.fed.us

International Hydropower Association

Jennifer JENKINS
University of Vermont
617 Main St. Burlington, VT, USA 05405
Tel: 802-656-2953
Fax: 802-656-2995
Jennifer.c.jenkins@uvm.edu

Joel Avruch GOLDENFUM
International Hydropower Association
IHA Central Office (Fifth Floor, West)
Nine Sutton Court Road
London Borough of Sutton
SM1 4SZ
Tel: +44 208 652 5295
Mobile: +44 7525 804 935
Fax: +44 208 643 5600
jag@hydropower.org

Kimberly Klunich TODD
United States Environmental Protection Agency
1200 Pennsylvania Avenue (6207-J)
Washington DC 20460
Tel: 12023439833
Fax: 12023432359
klunich.kimberly@epa.gov

UNFCCC
María SANZ- SÁNCHEZ
UNFCCC Secretariat BonnGERMANY
Tel: +49 228815 1488
MSanz-Sanchez@unfccc.int

Uzbekistan
Raisa TARYANNIKOVA
Hydrometeorological Reserch Institute, Centre of
Hydrometeorological Service
72 K.Makhsumov str. Tashkent, 100052
Tel: (99871) 2331150/2358461
Fax: (99871) 2331150
nigmi@albatros.uz

Task Force Bureau
Taka HIRAISHI (Co-Chair)c/o Institute for Global Environmental Strategies
2108-11, Kamiyamaguchi, Hayama, Kanagawa,
240-0115
Japan
Tel: (81 46) 855 3750
Fax: (81 46) 855 3808
hiraishi@iges.or.jp

European Community
Giacomo GRASSI
European Commission - DG Joint Research Centre
Institute for Environment and Sustainability
Climate Change Unit - 20127 TP.050 Ispra (VA) Italy
Tel: +39 0332 785147
Fax: +39 0332 785022
giacomo.grassi@jrc.it
54

Thelma KRUG(Co-Chair)
Instituto Nacional de Pesquisas Espaciais-INPE
Av. Dos Astronautas, 1578 – Jardim da Granja
12227-010 Sao Jose dos Campos Sao Paulo
BrazilTel: +55(12)39456000
Fax: +55 (12)39457130
thelma@dir.iai.int

IPCC NGGIP TSU
c/o IGES,2108-11, Kamiyamaguchi,
Hayama Kanagawa, 240-0115
Japan
Tel: (81 46) 855 3750
Fax: (81 46) 855 3808
Simon EGGLESTON
eggleston@iges.or.jp
Nalin SRIVASTAVA
srivastava@iges.or.jp
Kiyoto TANABE
tanabe@iges.or.jp
Jamsranjav BAASANSUREN
baasansuren@iges.or.jp

Rizaldi BOER
Bogor Agricultural University
Centre for Climate Risk and Opportunity
Management in Southern Asia & Pacific (CCROM
SEAP)
Institut Pertanian Bogor
Kampus IPB Baranangsiang Jalan Raya Pajajaran
Bogor 16151, Indonesia
Tel: (62)251 8623850
Fax: (62)251 8361087
rizaldiboer@gmail.com
James Michael PENMAN
Department of Energy and Climate Change
3 Whitehall Place London SWIAZMM UK
Tel: +44-0207-258-3368 or +44-7717-541-289
Fax: 61 2 6284 3151
jim.penman@decc.gsi.gov.uk

55

56