Carbon Storage in Protected Areas — Technical Report

05 November 2008

The United Nations Environment Programme World Conservation Monitoring
Centre (UNEP-WCMC) is the biodiversity assessment and _ policy
implementation arm of the United Nations Environment Programme (UNEP),
the world's foremost intergovernmental environmental organization. The centre
has been in operation since 1989, combining scientific research with practical
policy advice.

UNEP-WCMC provides objective, scientifically rigorous products and services to
help decision makers recognize the value of biodiversity and apply this knowledge to
all that they do. Its core business is managing data about ecosystems and biodiversity,
interpreting and analysing that data to provide assessments and policy analysis, and
making the results available to international decision-makers and businesses.

Prepared by

Alison Campbell, Lera Miles, Igor Lysenko, Holly Gibbs, Adam Hughes

a ¥Y
UNEP WCMC

Disclaimer: The contents of this report do not necessarily reflect the views
or policies of UNEP-WCMC or contributory organisations.
The designations employed and the presentations do not imply
the expressions of any opinion whatsoever on the part of
UNEP-WCMC or contributory organisations concerning the
legal status of any country, territory, city or area or its
authority, or concerning the delimitation of its frontiers or

boundaries.

Citation: Campbell, A., Miles. L., Lysenko, I., Hughes, A., Gibbs, H.
2008. Carbon storage in protected areas: Technical report.

UNEP World Conservation Monitoring Centre

Acknowledgements: This work has been supported by the Federal Ministry for the
Environment, Nature Conservation and Nuclear Safety

(Germany).

With thanks to: the protected areas team at UNEP-WCMC for
encouragement in undertaking this project and support in the
use of the World Database of Protected Areas; Bernardo
Strassburg, Allan Spessa and Guido van der Werff for
discussion of terrestrial carbon data sources; Neil Burgess,
Charles Besancon, and Barney Dickson for comments on the

draft.

Contents
Executive Summary
IntroductiOmeeeecererttctecrccsestecc cnet csenceserscemtesncstescocecestsnsceutcessesisescsrerterse=s
Section 1 - Carbon storage within the protected area network
We thod ology preci ceeee er ven-senceeeseceeerescesscascverscescersoseescaceouscrecneevactesvessnstissscsenteesete
How much carbon is stored within the protected area network? ...........eeeeeeeeeees 10
Global protection
Carbon outside the protected area netWOrk................::escsesseesceeecesseeseenseeeeeseees
REST ONAMPHOLECHOM ee ceresssceeosessctesncosrsscrerscessrsscessersssoscessarasrieatrsussscesesstaecaseees
Section 2 - The value of carbon stored within protected areas
Section 3 - Comparison of regional and global results ............0.eeeeeeeeeeeeeseeeeeeeeees
Above ground biomass — Brazilian AmaZO0 ..............::cescceseeeeesseeeeeeeereeeneeeeenneens
Soilfcarbonl=(Canadaver:.trrc-scseccsseesncencereecescsensssartersssceezescertast==
Section 4 - Carbon and conservation priority areas ..............eeeeeeececeeeceeseeeeeeeeneeeeaees
SUING fs coc ov ie sa cn sodocuced Soesh aeceaeravinisixsncsey sade dsuipcenssuacstavuveceussnectsusaptevasutesssccsevexsiee

Scope for further research
RREGETEM CES errr cree reer ans ea coat raccaceTueen eee ona na set orca cudenece outencsndebec desteesnecceeets cas
Annex | — Carbon storage in ecosystems data revieW.............:::cc:cceccesseesecessereeeneeeees

Carbon in terrestrial ecosystems

(CarbonyinsmarineccOsyStemiSperser esses cecteeece teense ese ee recon ennee eet cratee cea

Annex 2 — Valuing carbon storage within ecosystems

@anbons markets re cee stcesssceenconscevssacnscsysvctesscerevcoresnerseee

BP OLESthy/CATDOM) PLOJCCIS:. tc2 eee ccestccnsecaesesersecesecesesctestosestace res ecncesscceieetesneseaserss
Figure 1: Global carbon stock density in terrestrial ecosystems ............:.:ceseeeseeeeeees 6
Figure 2: Carbon stock density in tropical forest..............::essceeesecesscesseeesseenseeeeseeeneees 7
Figure 3: Terrestrial carbon stock in the protected area network by region............... 13
Figure4: Regional variation in total carbon stores (Gt) across protected area

CALC OTIC oS rre res eee cp Seem re ne reer ee aoe nec ere died sateen ableabneet ons Sed loaceeeerets Weeeeee 14
Figure 5: Carbon density in Amazon Basin.............:c:cc:cesescescescesseseescnscescesenseeseasens 19
Figure 6: Carbon density in Carbon density in Amazon Basin. ...............::ceceeeeeeee 20
Figure 8: Soil carbon density in Camada................eeeceeeeceeeceeeseceeeeceeeeensereeneeeeeeneeeeeee 21
Figure 9: Peat carbon component density in selected Canadian landscapes............... 22
Figure 10: Protected areas and carbon storage, Tanzania. ................::cessceeeeeeereeeeeeee 24
Figure 11: Carbon and biodiversity values, Tanzamia................::cescceeseeesceeeeeeeereeeneee 25
Figure 12: Protected areas and carbon storage, Papua New Guinea...............::ee1 25
Figure 13: Carbon and biodiversity values, Papua New Guinea. .............:.ceseeeeeeeeeeee 26
Table 1: Global terrestrial carbon storage in protected areas ...............::csseseeseeseeeeeee
Table 2: Estimated carbon storage within protected areas (Gt), by region. ..
Table 3: Regional variation in carbon density ..............-e::cesseceeeceesereeeeeeneeees
Table 4: Estimated value of carbon storage within protected areas (Gt), by region... 17
Table 5: Global datasets considered— carbon stored in vegetation ..............:::::e1
Table 6: Selected regional studies considered for USE............:2:cs1cceeceeeeeeeeee
Table 7: Carbon market Transactions and Values, 2006 and 2007 ............::::ceceeee

Table 8. Percentage share of land use project types in the voluntary market
Table 9. market values for carbon in forest sector. Price of land based offsets ......... 53

LESSY

Executive Summary

Carbon emissions from deforestation account for an estimated 20% of global carbon
emissions (IPCC 2007); second only to that produced by fossil fuel combustion. To
successfully reduce greenhouse gas emissions from land cover change, effective
strategies for protecting natural habitats are needed. Designation of new protected
areas and strengthening of the current protected area network could form one
contribution towards achieving this. Protected areas are designated with the objectives
of conserving biodiversity, but also fulfil an important role in maintaining terrestrial
carbon stocks, especially where there is little other remaining natural vegetation
cover. Knowledge of the carbon storage function of protected areas would therefore
be a useful input into the development of strategies for reducing emissions from land
use change; in particular, it is relevant to the current discussions surrounding reducing
emissions from deforestation and forest degradation (REDD) under the UN
Framework Convention on Climate Change (UNFCCC).

Our assessment of carbon storage in protected areas integrates information from the
best available data sources, with the aim of informing decision-making at global,
regional and national levels. Earth’s terrestrial ecosystems are estimated to store
around 2,050 gigatons (Gt) of carbon in their biomass and soil (to 1 m depth).
Protected areas worldwide cover 12.2% of the land surface, and contain over 312
GtC, or 15.2% of the global terrestrial carbon stock.

This estimate is broken down by region and IUCN protected area management
category. South America is notable for both its large volume of carbon and for the
high proportion of this carbon stored within protected areas; 27% of a total store of
340 GtC. By way of contrast, the Pacific has a low total carbon store but a high
carbon density, and only 4% is stored within protected areas. Increasing protected
area coverage in this region would provide a higher carbon benefit per unit area than
for other regions. Amongst the IUCN categories, only 4% of the carbon stock is
contained within protected areas designated under categories I-II, which generally
place stringent restrictions on resource use. More research is required into the carbon
storage implications of the various types of protected area management. A greater
level of carbon loss would be expected from areas allowing sustainable forest
management, for example, than those that restrict use of forest resources. A notional
estimate of the financial value of the carbon storage services provided by the world’s
protected area network is also presented. If all of the carbon stored within ecosystems
were to be valued according to current carbon market prices, it would have an
estimated worth of €5,700 billion

The data presented also allow identification of areas of high carbon value which are
not covered by the current protected areas network on a global and regional level.
This also provides the opportunity to identify areas that are not just high in carbon,
but also have high biodiversity value, increasing the scope for delivering ‘multiple
benefits’ from climate mitigation. By way of demonstration, the global figures
presented here were overlain with areas of high biodiversity, based on the spatial

overlay of the outcomes of muitiple conservation priority setting exercises, for
Tanzania and Papua New Guinea.

Contents

EXE CUULVERSUMIMANY Hees rescore eee scree. ceetec eremeeet ett seer ee eee 1
Introd uc HOn eres ere erresaiesteer or etree ee soe)
Section 1 - Carbon storage within the protected area network bis)
IMethodolo gyi cere rsvee tineles erences cates tere enrstencvaressi one coe tees eon)
How much carbon is stored within the protected area network? .............c00c00c0000- 10
Globallprotectionemeswee. ste erce erecta ee eee 10
Carbon outside the protected area network.. 11
Regional protection 12
Section 2 - The value of carbon stored within protected areas.............0.00ccccccceseeseeeee 16

Section 3 - Comparison of regional and global results
Above ground biomass — Brazilian Amazon....... :

SY FELL 71 8 Vosonoenoce eo rocees5e co CC ac ECO SCOLAIRE LEE EEL EE EEE PEPEOPEPEE ECE EPRCEE ERECT EEE ener
Scope for further research
REFERENCES Reretscer cisco te eee eae ae a ee | SOUS
Annex | — Carbon storage in ecosystems data review
Carbon in terrestrial ecosystems
Carbon in marine ecosystems .............cccccccesceseeeseees
Annex 2 — Valuing carbon storage within ecosystems..
Carbonimarketss. Ss esti Doe ee ee oe AO, PE I ee

Figure 1: Global carbon stock density in terrestrial ecosystems
Figure 2: Carbon stock density in tropical forest.............ccccccccccsssesseeeeeseeeeees
Figure 3: Terrestrial carbon stock in the protected area network by region
Figure4: Regional variation in total carbon stores (Gt) across protected area

(SNE) OC a SA EE ee RR i oir eS Pe Rea Pe RE A 14
Figure 5: Carbon density in Amazon Basin..............cccccccssssssescsesessesesesessescsveveceesenees 19
Figure 6: Carbon density in Carbon density in Amazon Basi. .............:csceccseseeeee+ 20
Figure 8: Soil carbon density in Canada..............ccccscececcscsesessesesescssesesesssecerseevacseeees 21
Figure 9: Peat carbon component density in selected Canadian landscapes............... 22
Figure 10: Protected areas and carbon storage, Tanzamia. ...........cccccssessesseseseseseeeeees 24
Figure 11: Carbon and biodiversity values, Tanzamia..............c.cccccssssssessseseeceseeeeesees 25
Figure 12: Protected areas and carbon storage, Papua New Guinea...............:.eece-0 25
Figure 13: Carbon and biodiversity values, Papua New Guinea. .............e.ccseceseseeeeee 26
Table 1: Global terrestrial carbon storage in protected areas ............sccceseseceeceeeeeeees
Table 2: Estimated carbon storage within protected areas (Gt), by region.

Table 3: Regional variation in carbon Gensity ..............ccccccccessssssesescscscesescsceceeeeceeens
Table 4: Estimated value of carbon storage within protected areas (Gt), by region... 17
Table 5: Global datasets considered— carbon stored in vegetation ................00c0s00+
Table 6: Selected regional studies considered for USe..........0..:cscececeeceseeeesceeesceceeceees
Table 7: Carbon market Transactions and Values, 2006 and 2007 ..............0-++-

Table 8. Percentage share of land use project types in the voluntary market
Table 9. market values for carbon in forest sector. Price of land based offsets ......... 53

Executive Summary

Carbon emissions from deforestation account for an estimated 20% of global carbon
emissions (IPCC 2007); second only to that produced by fossil fuel combustion. To
successfully reduce greenhouse gas emissions from land cover change, effective
strategies for protecting natural habitats are needed. Designation of new protected
areas and strengthening of the current protected area network could form one
contribution towards achieving this. Protected areas are designated with the objectives
of conserving biodiversity, but also fulfil an important role in maintaining terrestrial
carbon stocks, especially where there is little other remaining natural vegetation
cover. Knowledge of the carbon storage function of protected areas would therefore
be a useful input into the development of strategies for reducing emissions from land
use change; in particular, it is relevant to the current discussions surrounding reducing
emissions from deforestation and forest degradation (REDD) under the UN
Framework Convention on Climate Change (UNFCCC).

Our assessment of carbon storage in protected areas integrates informatior. from the
best available data sources, with the aim of informing decision-making at global,
regional and national levels. Earth’s terrestrial ecosystems are estimated to store
around 2,050 gigatons (Gt) of carbon in their biomass and soil (to 1 m depth).
Protected areas worldwide cover 12.2% of the land surface, and contain over 312
GtC, or 15.2% of the global terrestrial carbon stock.

This estimate is broken down by region and IUCN protected area management
category. South America is notable for both its large volume of carbon and for the
high proportion of this carbon stored within protected areas; 27% of a total store of
340 GtC. By way of contrast, the Pacific has a low total carbon store but a high
carbon density, and only 4% is stored within protected areas. Increasing protected
area coverage in this region would provide a higher carbon benefit per unit area than
for other regions. Amongst the IUCN categories, only 4% of the carbon stock is
contained within protected areas designated under categories I-II, which generally
place stringent restrictions on resource use. More research is required into the carbon
storage implications of the various types of protected area management. A greater
level of carbon loss would be expected from areas allowing sustainable forest
management, for example, than those that restrict use of forest resources. A notional
estimate of the financial value of the carbon storage services provided by the world’s
protected area network is also presented. If all of the carbon stored within ecosystems
were to be valued according to current carbon market prices, it would have an
estimated worth of €5,700 billion

The data presented also allow identification of areas of high carbon value which are
not covered by the current protected areas network on a global and regional level.
This also provides the opportunity to identify areas that are not just high in carbon,
but also have high biodiversity value, increasing the scope for delivering ‘multiple
benefits’ from climate mitigation. By way of demonstration, the global figures
presented here were overlain with areas of high biodiversity, based on the spatial

overlay of the outcomes of multiple conservation priority setting exercises, for
Tanzania and Papua New Guinea.

The estimates reported here should be viewed in the context of our knowledge of the
success of protected areas in reducing or halting land cover change. Evidence suggests
that protected areas are effective at reducing land cover change within their
boundaries (Clark et al. 2008), although one issue rarely taken into account is that of
leakage. While protected areas may effectively reduce deforestation within their
borders, there is a risk that deforestation pressures are merely displaced elsewhere;
either to other areas of forest or to other ecosystems entirely. This highlights the issue
that although the total figures for carbon within protected areas appear high; this is
still a small proportion of the global terrestrial carbon stock. 85% of the global carbon
stock lies outside of the protected area network, and could be considered more
vulnerable to release through land use change. Forests are not the only ecosystem that
store carbon and this should be taken into account in the development of climate
change mitigation policies; in particular there is a large carbon store in northern
latitude soils and peatland. It is vitai from a climate change perspective that this
carbon is managed appropriately.

It is clear that there is no ‘one size fits all’ approach to protecting carbon stocks within
terrestrial habitats. Other land use options for the protection of carbon should be
incorporated, including through community-conserved areas and the development of
best practices for land management and land use planning. The implementation of
REDD on a large scale is unlikely to be feasible without the support of indigenous and
local communities. The official recognition and encouragement of community-based
forest management is becoming more widespread, and could also become a viable
component of, or complement to, protected areas in reducing deforestation.

Although it is recognised that extension or strengthening of the protected area
network is only one possible element in the management of terrestrial carbon, the
large amount of carbon stored within protected areas, particularly in proportion to the
land area covered, suggests that protected areas could play a role in climate change
mitigation. Investment in a protected area network could be a valuable component of
a national strategy for reducing emissions from deforestation and forest degradation,
in support of the objectives of the UN Framework Convention on Climate Change.

Introduction

Recent recognition of the importance of land use change in the carbon cycle, and the
commitment to include reduced emissions from deforestation and degradation
(REDD) in the post-2012 agreements of the UNFCCC, has raised the policy relevance
of carbon storage in terrestrial ecosystems. Research has traditionally focused on the
role of ecosystems as carbon sinks, rather than as potential sources, but the
importance in climate change mitigation of protecting the existing carbon stocks is
becoming increasingly recognised. Depending on the method of forest clearing and
the subsequent use of the felled trees and land, deforestation not only releases carbon
stored in the above ground biomass, but leads to decomposition of roots and
mobilization of soil carbon. Global greenhouse gas emissions from changes in land
use, including tropical deforestation, are estimated to make up around 20% of annual
global emissions from all sources (IPCC 2007), though there is a high level of
uncertainty attached to the precise figure. Forest degradation, the loss of carbon stocks
from land still officially designated as forest, adds another unquantified volume of
CO>-equivalent gases to the atmosphere every year. Forest fragmentation and
degradation also increase the risk of forest fires, which release further carbon
emissions and increase susceptibility to future fires.

Protected areas are primarily designated for the purpose of biodiversity conservation,
but have a substantial additional value in maintaining ecosystem services; including
climate regulation through carbon storage. Despite this, there is little knowledge of
the carbon storage within the world’s protected area network, and no global scale
estimate has previously been produced. Such knowledge would quantify one of the
multiple benefits provided by protected areas, which could be useful in protected area
planning and financing. Discussions at the recent UNFCCC’s 13'" Conference of the
Parties focussed on guidance for demonstration (pilot) REDD projects, potential
policy mechanisms and incentives for developing countries. The precise form of any
future REDD mechanism as part of a post-2012 emissions reduction agreement is yet
to be determined.

In the context of the carbon stocks already under protection, a distinction should be
made between the actual process of reducing emissions from land use change, and the
proposed REDD mechanism under discussion at the UNFCCC. Whilst the current
protected area network undoubtedly plays a role in conserving the carbon stock, it is
not clear whether existing protected stocks will be included in a REDD mechanism.
Currently, there are a number of options on the table, including the measurement of
emissions from deforestation and degradation against past rates of deforestation; with
compensation for existing protected stocks not out of the question but appearing less
likely. This should be taken into account when reading this report, which has a focus

on the potential role of protected areas in the actual achievement of reductions in
emissions from land use.

The global protected area network contains many ecosystem types other than forest,
each with its own carbon storage capacity. This technical report presents an estimate
of the total carbon storage function of protected areas. The report is broken down into
four main sections, with background information reported in the Annexes. Section 1
reports the level of carbon storage within the protected area network, broken down by
region and according to the IUCN protected area management category. A rough

estimate of the financial value of the carbon storage services provided by the global
protected area network is presented in Section 2. Section 3 presents the regional
analyses used to validate the global data, and the outputs of this study are
contextualised in Section 4 through a demonstration of the potential use of the data in
identifying areas of high carbon and high biodiversity areas in Papua New Guinea and
Tanzania. A review of the available carbon storage datasets used to produce the global
carbon map, and a review of carbon market values used in the selection of an
estimated value for terrestrial carbon can be found in Annexes | and 2 respectively

This work illustrates the potential role of protected areas in climate change mitigation
and will be a useful input to current discussions on a mechanism for reducing
emissions from deforestation (REDD) under the UN Framework Convention on
Climate Change (UNFCCC), or any other mechanism for protecting carbon stored
within ecosystems.

Section 1 - Carbon storage within the protected area network
Methodology

Global carbon storage in terrestrial ecosystems

The methods for estimating carbon storage vary widely, and no single method is
considered highly accurate. The use of improved technology for biomass estimation
and databases for soil carbon estimation is likely to improve the accuracy of carbon
estimates in coming years. A global scale dataset on carbon in live biomass (Ruesch
& Gibbs, in review), and a dataset on soil carbon produced by the International
Geosphere-Biosphere Programme (IGBP-DIS 2000) were selected for use in this
analysis following a comprehensive review of the available data (Annex 1).

The biomass carbon stock data were estimated using the Intergovernmental Panel on
Climate Change (IPCC) Tier-1 approach (IPCC 2006, Gibbs et al. 2007). A combined
map of carbon storage in terrestrial ecosystems was produced using globally
consistent estimates for above and below ground biomass. These are the most recent
estimates available for global vegetation carbon, and the only global estimates to
follow IPCC Good Practice Guidance for reporting greenhouse gas emissions (IPCC,
2006).

It is also important to quantify soil carbon storage, as research has suggested that soil
carbon accounted for 28% of net loss from land use change in the period 1850-1990
(Houghton 2005). A soil organic carbon dataset (SOC), published by the IGBP in
1998, was selected for use in this study (IGBP-DIS 2000) on the basis of availability,
scale and provenance. It estimates organic carbon density to 1 m depth, at 5 minute
resolution, which is appropriate for quantifying SOC in most cases, but undoubtedly
underestimates SOC storage in deeper peatland systems. No global spatially explicit
map of peat extent and depth is yet available, and this is an acknowledged limitation
of the current data, particularly given that peatlands have been estimated to contain at
least 550Gt of carbon, containing as much carbon as all terrestrial biomass but
covering only 3% of the land areas (Parish et al. 2008).

A globally consistent map of carbon storage in terrestrial ecosystems (
Figure 1) was produced by combining a number of datasets

1. Global biomass carbon stock map based on IPCC Tier-1 Methodology.
(Ruesch & Gibbs, in review).

2. Global Soil Data Products CD-ROM. (IGBP-DIS 2000).

3. Coastlines and country’s boundaries of the world /World Vector shoreline
plus, 3“ edition. (the National Geospatial-Intelligence Agency, 2004)

4. Area Correction Global Grid, ACGG. (UNEP-WCMC 2007)

ACGG, the global raster dataset (ArcInfo Grid format) identifying the actual area of a
grid cell on the Earth surface in km* (with a precision of 0.001 km’ for cells of 0.0045
degree resolution; about 500 meters on the equator, henceforth referred to as
“standard resolution”), was applied as a template for all intermediate maps and the
final combined map. All original sources and outputs were maintained and analysed in
the common original projection (Geographic, spheroid/datum WGS84). ACGG values
were applied to reflect on-the-surface grid cell size change at various latitudes; in

particular in calculation of areas and other statistics derived from the combination of
area and other parameters (e.g. carbon stock within a particular region derived from
carbon density values).

World Vector Shoreline Plus (vector dataset) was applied as a high resolution
(1:250,000) basemap. It was converted into the standard resolution raster (ArcInfo
Grid format).

Both biomass carbon and soil carbon maps (raster datasets) were converted into the
standard resolution grids. As the original resolution of these data was lower than
required, minor amendments were applied to ensure that the whole terrestrial area was
covered by the combined map. These minor amendments included elimination of the
area falling beyond the extent of the basemap over the coastline, and the assignment
of the nearest cell value to terrestrial areas close to the coastline that had been omitted
in the original sources due to lower raster resolution. The total extent of the area
where this extrapolation applied did not exceed 0.5% of the total land surface.

Figure 1: Global carbon stock density in terrestrial ecosystems (above and below
ground biomass plus soil carbon) (Gibbs et al. 2007; Ruesch & Gibbs in review;
IGBP 2000)

A carbon stock estimate for tropical forest is also presented (Figure 2), as an example
of how the carbon data can be separated according to ecosystem and region of
interest.

On a global scale, the use of biome averages and the increased uncertainty of carbon
storage estimates for higher biomass classes tend to lead to a less accurate picture for
individual regions than equivalent regional maps (Annex 1). Whilst much variability
can be found at a regional scale, these biome-based estimates do provide a consistent
indicative picture of the pattern of carbon storage.

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Selection of regional data

There are a large number of national and regional estimates of carbon storage in
terrestrial ecosystems (Annex 1, Table 6). Such estimates tend to be more accurate
because they are extrapolated over smaller scales, rely on better inventory data, and
can account for spatial variation in more detail. Comparisons of the global datasets
used in this analysis with regional data were carried out for the purposes of data
validation.

Datasets for biomass in the Amazon Basin (Saatchi et al. 2007) and SOC in Canada
(Tarncoi & Lacelle 1996) were selected to assess the accuracy of the global data for
both biomass and soil in two areas of high carbon storage. Following review of
available estimates (Annex 1), both datasets were considered to be the most accurate
available both for the regions and carbon pools that they provide estimates for.
Although other datasets for the Amazon could be considered equally accurate, they do
not provide estimates for all vegetation classes.

Selection of protected area data

Broadly speaking, protected areas can be defined as areas of land or sea “dedicated to
the protection and maintenance of biological diversity and of natural and associated
cultural resources, managed through legal or other effective means” (IUCN 1994).
Protected area data were obtained from the World Database on Protected Areas
(WDPA), which holds spatial and attribute information on over 120,000 nationally
and internationally protected sites.

The International Union for the Conservation of Nature (IUCN) describes six
Management categories for protected areas, according to the objectives for
management. Any protected area must have biodiversity conservation as a major aim,
but the degree of permitted use varies. Amongst the categories, I and II are more
restrictive; III and IV are variable, whereas V and VI explicitly recognise sustainable
use as an appropriate land use. The WDPA also holds information on a large number
of protected areas that have no formal designation or for which the designation is not
known, and for areas that may not meet the protected area definitions such as forest
reserves or community conservation areas. Difficulties with data validation are an
acknowledged limitation of the WDPA, as the data is received from a number of
different sources. Whilst this is true for all of the data contained within the WDPA,
data for which an IUCN category has been provided is considered to be more robust
than that for which designation is unknown. The WDPA is currently undergoing
redevelopment to improve data validation processes.

For the purposes of this analysis, all WDPA sites were incorporated to allow inclusion
of those areas that meet the protected area definition, but may not have an IUCN
management category recorded. In addition, it was considered that any area of land
with some degree of protection conferred upon it should be included in the analysis.
For reporting purposes, all sites stored within the WDPA will be referred to as
‘protected areas’ in full recognition that these areas may not have official protection
status.

The results are presented initially for carbon stored in all WDPA sites (including
those with no IUCN category). In view of the fact that not all protected areas are

managed for the same purpose, as defined above, the results are also broken down
into protected area categories I-II, LIV, LVI. This allows for some degree of
separation of:

a) The areas of land that have been given management categories (and are
therefore more likely to be officially recognised protected areas) from those
that may be forest reserves

b) Protected areas that allow different degrees of resource use and land use
change, as defined by the IUCN protected area management category
(outlined above).

This separation is made for the purposes of comment on the potential level of
protection afforded to the carbon. For example, substantial land cover change would
not be expected in any protected area, but increases in sustainable use of land within
categories V and VI might be expected, with implications for the carbon stored in that
area. It should be noted that this analysis does not incorporate any actual measure of
the likelihood that the carbon will be conserved within protected sites.

Production of the global carbon storage within protected areas map

The globally consistent map of carbon storage in terrestrial ecosystems was overlaid
with data from the WDPA.

To enable overlay of the protected areas with the combined carbon density maps, the
vector data from the WDPA (UNEP-WCMC & IUCN, version 2007) were converted
to the standard resolution raster. This process was straightforward for polygonal data.
Additional data represented only by approximate location of the protected area
(latitude/longitude) and its total area were transformed into proportional circles,
centred at the given location and equal in area to the size recorded in the WDPA.
These new polygons were also converted into the raster and incorporated, as they
provided additional data for the analysis. Although this method assumes considerable
distortion for particular protected areas boundaries, it is widely applied for protected
coverage estimates over large territories, and at the continental or global level
potential distortion in coverage assessment does not exceed 3-4 %, according to our
calculations. Polygonal layers of protected areas, in particular IUCN category I-VI
and protected areas with no IUCN category assigned, were converted to separate
raster datasets.

All of the maps represented in this report were produced using the combined raster
map of a carbon class and relevant protected areas class (one or more categories
brought into a single raster). It should be noted that, due to overlap between various
categories of protected area, statistics on total extent or carbon content within
categories and groups of categories of protected areas cannot be calculated as a simple
sum of relevant totals. All calculations were based on spatial analysis, through
identification of the actual total extent of protected areas, and overlay of this
intermediate dataset with the rasters identifying the carbon content distribution.
Analyses were conducted using ESRI ArcGIS 9.2 with the Spatial Analyst extension.

How much carbon is stored within the protected area network?

Global protection

The combined map of global carbon storage (Figure 1) shows that earth’s terrestrial
ecosystems store an estimated 2,052 gigatons (Gt) of carbon in their biomass and soil.
Two distinct bands of high carbon density can be noted in the northern latitudes and
the tropics.

According to our estimates, 15.2% of the global carbon stock is contained within the
protected area network, highlighting the relevance of protected areas to climate
change mitigation. As protected areas cover 12.2% of the land area (according to the
criteria used in this analysis) (Table 1), they capture a proportionately high amount of
carbon given that they were not designated for this purpose. There are a number of
potential reasons for the high carbon benefit of protected areas; it could be that high
carbon areas such as tropical forest are more likely to be protected, or it could be the
case that much of the carbon in non-protected areas has been lost already. Clearly,
land that has already been cleared for agriculture or urban growth will have lower
carbon content than land that has been protected; this factor was not incorporated into
our analysis. Conversely, some protected areas cover rock and ice deserts that would
not be expected to have high carbon content. Regardless, it appears that protected
areas could have a role to play in future ecosystem based climate change policies.

A total of 312 Gt carbon is currently under some degree of protection (taking into
account all sites within the WDPA) which would be equivalent to 1142 Gt CO} if lost
to the atmosphere; or more than 43 times the total annual global emissions from fossil
fuel (26.4Gt; IPCC, 2007). This comparison is made for perspective only; even if all
protected areas were converted to a different land use not all of this carbon would be
released to the atmosphere. A large amount of carbon will likely be emitted from
conversion of forest to agriculture, for example, but this will also depend on the type
of agriculture and the management of the agricultural land. The loss of 2.5% of
carbon within protected areas would result in higher carbon dioxide emissions than an
entire year of fossil fuel combustion.

Table 1: Global terrestrial carbon storage in protected areas

Protected area category % \and cover | Total carbon | % terrestrial carbon
protected stored (Gt) stock in protected

The extent to which protected areas are effective at conserving their carbon stores is
another question. This depends on a number of factors such as whether areas are
actively managed, the level of enforcement, the level of resource use permitted, land
use change pressures, and governance. Much of the study on this topic has focused
upon forested protected areas, and a review of the evidence suggests that protected
areas are an effective tool for reducing deforestation within their boundaries; that is,
there is usually less deforestation within formally protected areas than in their
immediate surroundings (Clark et al. 2008).

10

Clark et al. (2008) also identified that protected areas designated under categories I-II
seem to be more effective at reducing deforestation than those which include a focus
on sustainable use (V-VI); although there are comparatively few studies on
deforestation rates within category V-VI protected areas. This is an important point to
consider, as protected area categories I-II, which are the most restrictive in terms of
land use, store only 4.2% of the carbon stock (

Table 1), whereas double the percentage of total carbon stock is protected when
considering categories I-VI. It could be expected that some carbon may be lost from
the less restrictive protected areas through, for example, the sustainable use permitted
in category V-VI areas; but conversely this may avoid leakage of deforestation to
other areas. More research would be required into the impact of such management
practices on carbon stocks, and the type of land use permitted in each protected area,
before even qualitative statements as to the carbon storage value of the different
protected area management categories could be made. Analysis of the potential
carbon protection benefit of protected areas in terms of the emissions that would
likely be prevented through protection of carbon ‘on the ground’ is beyond the scope
of this present study

Carbon outside the protected area network

Although protected areas clearly have a large carbon storage benefit, there is still a
total of 1,740 Gt of carbon lying outside of the protected area network. This carbon
could be considered more vulnerable to release into the atmosphere if fewer
restrictions are placed on land use change. There have been very few studies able to
quantify, for example, the extent to which land-use change is displaced from protected
areas to surrounding land, although there is some evidence that this does occur (Ewers
& Rodrigues 2008). Although the reduction of carbon emissions is undoubtedly the
first priority of policies such as REDD, from a conservation perspective the potential
for land use change to be displaced into lower carbon areas with high biodiversity
value needs to be considered. Even purely from a carbon perspective there is a risk of
displacement into high carbon non-forest areas. Efforts to reduce emissions from land
based carbon should not focus on forests alone (Miles & Kapos 2008).

Protected areas are not the only tool that should be utilised in protecting the carbon
stored in terrestrial ecosystems. Community conserved areas (CCAs) and Indigenous
lands have been shown to be effective tools for reducing deforestation, even more so
than many protected areas (Clark et al. 2008). The potential for reducing carbon
emissions through improved forest management is another avenue for exploration,
and is particularly important if we are to reduce emissions from forest degradation. A
recent study has reported that reduced impact logging can reduce carbon emissions by
approximately 30% over conventional logging, and estimated that improving logging
practices in managed forests globally could retain at least 1.6Gt carbon per year (Putz
et al. 2008); more carbon than is currently protected in the Pacific (Figure 3). In
addition, participatory forest management in Tanzania has been shown to lead to
improved forest condition (Blomley et al. 2008). From a climate change mitigation
perspective, the high amount of carbon outside of the protected area network suggests
a need to both ensure the protection of carbon within protected areas, and to improve
land use planning and management in areas identified as high in carbon content, for
which the designation of new protected areas would only be one available option.

Regional protection

There are regional variations in both the total carbon store and the amount that is
protected (Figure 3). Although the data reported here gives an overview, ideally more
accurate regional source data would be used to determine carbon protection priorities.

For the purposes of this study, the global map was divided into major continuous
geographical regions. The largest carbon stores can be found in North Eurasia, North
America, South America and Africa (Figure 3). Protected areas in South America
store the most carbon, both in absolute terms (91Gt) and as a proportion of total stock
(27%; Table 2). Comparatively high levels of protection can also be seen in Central
America & Caribbean and Greenland (although these regions have a low total stock
and the carbon is arguably less vulnerable to disturbance as fewer pressures are acting
upon the land).

Low levels of protection are evident in North Eurasia, with only 8.8% of carbon
protected out of the largest regional carbon stock. This is likely due to the large
amounts of carbon stored in the biomass, and particularly the soils, of the large tracts
of mostly unprotected boreal forest in this region (Schmitt et al. 2008). Again, this is
not to say that the carbon stored in these areas is necessarily more vulnerable to
release, as the land is arguably subject to less land-use pressure than carbon outside
protected areas in tropical regions. Indonesia, for example, has high deforestation
rates (Hansen et al. 2008) due to factors such as oil palm expansion (Nellemann et al.
2007) which can involve emissions from the burning of high carbon peatland as well
as that from deforestation. It could be considered that the estimate of only 15% of
carbon protected in this region is of more concern than the lower levels of protection
in North Eurasia. Indeed, although South America has the highest amount of carbon
protected, a recent study has estimated that over three-fifths of forest clearing occurs
in this region (mostly in Brazil; Hansen et al. 2008), suggesting a need for increased
conservation and protection measures.

As specified previously, the figures reported above in Figure 3 and Table 2 are for all
sites within the WDPA, including those designated under the less restrictive land use
categories V-VI and those that have not been assigned an IUCN management
category. Estimates for the total carbon storage for each region under protected area
categories I-II, I-IV, I-VI, and all protected areas are shown in Figure 4, ranked
according to land area.

Two thirds of the large amounts of carbon protected in South America are in the less
restrictive protected areas, and the majority of the 20Gt total is protected in categories
V-VI in East Asia. Generally, between a third and a half of the protected area carbon
is stored in the more restrictive categories I-IV across the regions, with the exceptions
of Australia/New Zealand, North Eurasia and Greenland

12

Table 2: Estimated carbon storage within protected areas (Gt), by region.
Percentages calculated from carbon figures in tonnes, rather than the
Gigatonnes presented here.

Region
number

Region

North America
Greenland

Central America &
Caribbean

South America

Terrestrial

Total
388

Carbon in
carbon stock, Gt | protected areas,
%
In protected
areas
59 15.1
2 S12

ei Africa

8 Middle East

9 South Asia
Oneal East Asia

ll South East Asia 20 15.0
12 Australia/New Zealand 85 10 12.0
13 Pacific 3 0.1 4.3
14 Antarctic & peripheral <0.1 03

islands

Figure 3: Terrestrial carbon stock in the protected area network by region. Total
(proportional pie-charts), and stored within the protected areas network (green
segments); red numbers are region numbers from Table 2.

Africa N. Eurasia

49
36
31
27
21 25
3 q 4 4
|
it Vv I-VI AIlLWOPA i HV I-VI All WOPA
91
N.America S.America
39 57
49
31 29
3 4 a 4
til lv I-VI All WDPA 1-H lv I-VI All WDPA
East Asia Australia / N. Zealand
20 20
i a
2 2
= — | . rey: | ee |
It IAvV I-VI All WOPA tl lv I-VI All WDPA
Middle East Europe
12 14
3 3 3 4
pe eee Ee | |
it Hiv I-VI AllWOPA cel lV I-VI All| WDPA
SE Asia S. Asia
14 20
11
U Be | be | a 1 3 3 4
——————
i ive I-VI All WOPA -l Hv I-VI All WDOPA
C.America & Caribbean Pacific
1 2 3 2 0.06 0.08 0.09 0.11
—— a
I 14Vv I-VI All WOPA 1 IV I-VI AILWDPA

Figure 4: Regional variation in total carbon stores (Gt) across protected area categories.
Regions are ordered according to land area (Greenland and Antarctic not shown).

14

A large proportion of carbon protected in Africa and South America is in areas which
do not have an IUCN management category. Again, it is not clear what implication
this has for the vulnerability of the carbon store within protected areas, although as
discussed earlier categories I-II are more successful in reducing deforestation (Clark
et al. 2008) and by definition are more restrictive of land use change.

Total figures of carbon storage in each region are clearly important for carbon
accounting, and quantifying the current carbon storage benefits of the protected area
network. However, as suggested in Figure 4, regional totals are in general indicative
of the land area of the region, rather than ‘carbon richness’ per se. It is perhaps more
appropriate to consider the carbon density of an area when, for example, identifying
priority areas for REDD. Such patterns can be more readily seen when regions are
ranked by land area, and the amount of carbon per hectare of land is displayed (Table
3).

Table 3: Regional variation in carbon density

Region Land area | Total carbon stock | Carbon density |
(million km2) (Gt) t/ha
Africa 30 388 119
North 5
Eurasia “al 22 185
North America 21 16 182
South America 18 341 192
Antarctic “14 | 100 | 0.4
East Asia 12 108
Australia/New Zealand 8 107
Middle East 7
[Europe 5 54 rae 195
South East Asia 5
South Asia 4
Greenland 2
Mesoamerica & Caribbean 0.8
0.1

Although comparatively low in total carbon stocks, it is clear that the South East Asia,
Central America & Caribbean, and Pacific regions could be considered ‘high carbon
density’ areas. In addition to this, the Pacific has the lowest proportion of total carbon
stock within protected areas at 4% (not inclusive of Antarctica), despite the fact that
more carbon would be protected per hectare of land protected than in any of the other
region outside of South East Asia. Purely from a carbon storage perspective,
increasing protection in these regions would provide more ‘value for money’ than
anywhere else on the globe. In addition, a low total land area but high carbon density
would suggest that carbon could be vulnerable to land use pressures in these areas. It
appears appropriate therefore, that Papua New Guinea is a potential pilot country to
receive assistance in developing and implementing REDD strategies. Further

information of high carbon density and high biodiversity area mapping in Papua New
Guinea can be found in Section 4.

15

It is clear that protected areas have the potential to make a useful contribution to
protecting carbon stored in ecosystems. However, evidence shows that they need
proper investment if they are to be effective at avoiding land use change (or carbon
loss through land degradation), and therefore act as effective tools for the protection
of carbon stores. A lack of sustainable financing for the protected area network has
clearly been a barrier to effective protected area management in the past. The
following section of this report considers the notional value of the protected area
network, if the carbon stored within protected areas was to be valued according to
current market prices.

Section 2 - The value of carbon stored within protected areas

Carbon emissions from deforestation account for an estimated 20% of global carbon
emissions (IPCC 2007); second only to that produced by fossil fuel combustion.
Despite this, projects relating to Land Use, Land Use Change, and Forestry
(LULUCF) in 2006 accounted for only 1% of an international carbon market that has
risen to US$64 billion (€47 billion) in 2007 (Capoor & Ambrosi 2008). Given the
contribution of deforestation and land degradation to carbon emissions, it is likely that
the value of carbon storage in ecosystems will increase, particularly as the overall
carbon market is projected to increase in value (Annex 2).

For the first time, one of the non-provisioning ecosystem services provided by
protected areas has a financial market associated with it in which the international
community is engaged. In addition, the data presented here has gone some way
towards quantifying the carbon storage service provided by protected areas; providing
an opportunity to illustrate the value of carbon stored within protected areas if it was
to be traded on the current carbon market.

A notional value of the carbon stored within the protected area network is presented
here, based on a review of carbon markets, and the current levels of finance attached
to land-use based carbon (Annex 2). From the values reviewed, it would appear that a
reasonable range for the valuation of carbon stored in terrestrial ecosystems is €1-10
for the retail price. Within this, a conservative estimate of €3 — €7 at the higher end
would appear acceptable for carbon stored in ecosystems across the board, based upon
the range of current market prices and considering that forestry based projects
command higher prices within the voluntary market, whereas carbon stored within
other ecosystems will undoubtedly command a lower price (Annex 2).

The price of stored carbon will be variable, and any single value placed on carbon
stored in ecosystems should therefore be considered very speculative, particularly
given that the scale of the market is yet to be determined through, for example, REDD
implementation. In addition, the access that carbon already stored within the protected
area network would have to carbon finance is not clear. The values reported below
should be viewed only as an indication of the worth of carbon stored in protected
areas according to current market prices, rather than an estimation of their value. The
notional estimates are reported with full recognition that not all carbon stored in
ecosystems will have a financial value, and that the value will differ for carbon from
different sources and regions.

16

Estimates of the financial value of carbon stored within protected areas by region
(Table 4) are based on the application of values of €3, €5, and 7€ /tCOz¢ to all carbon
stored in the protected area network. The mid-range value of €5 /tCO2e gives an
estimate of €5,700 billion for the carbon within protected areas, if it were valued at
current market prices. Even taking the lower range estimates of €3 and €1, the value is
more than €1,100 billion. Again, this should not be taken as an estimate of protected
area value; such comparisons are problematic as it is not possible to equate stored
carbon to carbon ‘not emitted’.

Table 4: Estimated value of carbon storage within protected areas by region

Co2e (Gt) | Notional value Notional Notional
(€billion) value value
eaen (€billion) (€billion)
Region stock :
(Gt) (~notional :
value at Priced at €3 Priced at €5 Priced at €7
€1)
North America 59 215 644 1,074 1,504
Greenland 60
| Central America
& Caribbean 105

South America 91 334 1,003 1,671 2,339
Europe (Ane eS 148 247 346

North Eurasia

Africa 1,253
Middle East

South Asia 4 14 43 ar ee
East Asia
South East Asia 218 363

Australia/New

Zealand 261
Pacific 3
Antarctic &

peripheral

islands 0.05
roma | 31

To put these figures in context, it has been estimated that $6 billion per year is spent
on protected area management, less than 12% of which is spent in developing
countries (Balmford et al. 2003). Balmford et al. (2003) also estimated the costs of
effective protected areas in densely settled regions of Latin and Central America,
Africa, and Asia; and found that costs ranged from $130/km2/year, to $5,000/km2/yr,
with typical costs falling in the region of $1,000/km2/yr. Moore et al. (2004)
estimated that the entire budget for ecoregion conservation in Africa would be $630
million. However, the calculation above based on total stock is different from the
value calculated on the basis of emissions avoided, and such carbon finance will
mostly be made available through REDD. As noted previously, the position of
protected areas within a REDD mechanism is unclear, and it is most likely that the

17

current protected area network would only receive a portion of REDD finance if they
were demonstrably at risk of deforestation. The identification of such areas would be
a useful topic for further analysis.

Consideration of the value of carbon storage within protected areas also provides no
indication of the mechanisms through which this money could be made available, nor
the stakeholders to whom the finance would be available to. Whilst such a discussion
is beyond the scope of this report, it is worth noting that this is a major issue for
REDD. There are no guarantees that even for new protected areas included in a
REDD mechanism carbon finance from national level systems will come back to the
site level, let alone the local people and forest users. In addition, the financial value of
carbon is likely to be lower for non-forest ecosystems; with the potential to result in
the conservation of forest at the expense of other ecosystems. Inequitable distribution
of benefits and unresolved issues of land tenure would appear to be the major
stumbling blocks to ensuring that finance from the conservation of carbon reaches the
appropriate stakeholders (Coad et al. 2008), and need consideration in the
development of REDD policies.

The potential role of protected areas in REDD policy

As has been indicated throughout this report, the relationship between REDD policy
and protected areas is complex. This has been highlighted through the difficulty in
attaching carbon finance to protected areas. As in theory carbon stored within
protected areas is not at risk of release to the atmosphere, it would not be explicitly
included in a REDD mechanism that was focused on reducing national emissions,
rather than rewarding countries for protecting their carbon stocks. Whilst there is still
the potential for countries to be compensated on the basis of existing carbon stocks
through mechanisms such as that suggested by the Terrestrial Carbon Group (TCG
2008), it appears more likely that REDD will take the format of measuring reduced
emissions from deforestation and degradation against past baselines

Clearly, where protected areas are at risk from deforestation, there could be a role of
strengthening the protected area network, and further study would be required into
emissions from protected areas through deforesiation. In addition, expansion of the
protected network would be one option for reducing emissions.

Regardless of the role of protected areas within REDD, it is clear that they have a
large role to play in the actual process of reducing emissions from land use change, as
they store a large amount of carbon; the protection of which could play a large role in
the mitigation of climate change. This clearly makes protected areas relevant to all
decisions related to carbon in ecosystems, including those relating directly to REDD;
especially if we are concerned with delivering biodiversity and livelihood co-benefits
from climate mitigation measures.

Section 3 - Comparison of regional and global results

An initial analysis of the uncertainty in global estimation of carbon stocks is reported
here, based on a comparison of selected regional datasets with the global data. As
there was no suitable regional dataset available to simultaneously analyse carbon
storage in biomass and in soil, regional datasets were cross-checked against relevant
layers of the global map. For this purpose, the original Global Biomass Carbon Stock
Map (Ruesch & Gibbs, in review) was compared with data for the Amazon (Saatchi et
al. 2007); and Global Soil Data (IGBP-DIS 2000) was compared with soil and
peatland data for Canada (Tarnocai & Lacelle 1996; Tarnocai 2005).

Above ground biomass — Brazilian Amazon

Saatchi et al. (2007) estimated carbon stocks in Amazon Basin vegetation by
combining data from biomass plots and remote sensing data (incorporating forest
characteristics and environmental variables). This approach combines biomass
estimates (limited in spatial coverage) with remote sensing for the entire region
(limited in capacity for biomass estimation), improving the capacity of the predictive
model (Houghton et al. 2007). A decision tree approach was used to develop the
spatial distribution of Above Ground Biomass (AGB) in 7 distinct biomass classes in
lowland old-growth forests with more than 80% accuracy. AGB for other vegetation
types such as the woody and herbaceous savannah and secondary forests were directly
estimated from the regression analysis of satellite data.

The legend in Figure 5 shows the class ranges applied by regional study authors.
Some areas outside of the Amazon basin, that were present in the original dataset are
not shown on this map and were not encountered in cross-checking with global data.

Carbon, tons/hectare
Tey 0

Lt

(33 Other basins

Figure 5: Carbon density in Amazon Basin (based on Saatchi et al. 2007; extent
and colour scheme are amended).

The equivalent estimate from the global vegetation carbon map is presented in Figure
6.

Carbon, tons/hectare

0
laa 1 - 25
| 26 - 50

Other basins

Figure 6: Carbon density in Carbon density in Amazon Basin (based on Ruesch &
Gibbs, in review).

It is apparent that the global data did not identify areas with carbon density above 200
tonnes per hectare; in fact approximately 80% of this territory was assigned with a
single value (193 t/ha). This corresponds with the conclusion of Saatchi et al. (2007)
that biome averages are likely to underestimate carbon density due to the lack of
dependency between vegetation type and biomes, and could account for a large
proportion of the disagreement between the two datasets

Due to the relatively broad range of values (50 t/ha steps) included in separate classes
for the regional data sources, there was no straightforward way to calculate the
potential carbon stock in the region with any precision. As a simplified assumption,
the mid-point value was taken as a basis for calculation of the carbon stock. An
estimate of the carbon stock based on regional data for above ground biomass is 125.2
Gigatons against 101.9 Gt from the global dataset. Although the result of this
simplified comparison (23% difference) cannot be applied as a precise measurement,
it is likely that the global map underestimates the carbon content across the Amazon
region.

Considering that the global data is obviously more coarse scale, this is an expected
level of variation between the two datasets. The Saatchi et al. (2007) data was
obtained from both sampling of biomass plots and remote sensing data, and included
old growth forest, floodplains, and small coastal patches, using a more recent land
cover map at lkm resolution. The Amazon regional estimate also included
differentiation of disturbed and non-disturbed forest, whereas the global data
necessarily utilised biome averages. Further efforts are required for bringing together
outputs of extensive regional studies and for making their results more easily
comparable and compatible in respect of methodology and data formats, as it appears
that the global data underestimates carbon stocks in high biomass areas.

Soil carbon — Canada f
The Soil Organic Carbon Digital Database of Canada (Tarnocai & Lacelle 1996) is
based on the Soil Landscapes of Canada (SLC version 2), part of the National Soils
Database, and maintained by the Eastern Cereal and Oilseed Research Centre of
Agriculture and Agri-Food Canada. The Canadian SOC Database provides estimates
for carbon density and total stock for over 10,000 landscape units representing the
whole territory of Canada (Figure 7). The equivalent estimate from the global SOC
map is presented in Figure 8.

Carbon, tons/hectare
i 0

[1-5
(|6-10

{4 11-20

[4 21-50

[4 51 - 100

(4 101 - 200

iy 201 - 400

Gi 401 - 800

(i > 800

9] Other countries

101 - 200
201 - 400
fim 401 - 800

fi > 800
(3 Other countries

Figure 7: Soil carbon density in Canada (based on IGBP-DIS, 2000).

Comparison of the maps derived from these two datasets reveals substantial
differences both in relative abundance of carbon across geographical regions and in
absolute values of carbon stock in high density areas. In particular, the national
dataset depicts vast territories in the Canadian north and across sub-arctic islands as
areas in which soil carbon density exceeds 300 tons/ha, whereas no density above 200
t/ha is identified for these territories from a global dataset. The high carbon “belt”
expanding from north-west Canada through its central part towards south-east part
seems to be depicted similarly by both datasets, but soil carbon density differs
considerably. The maximum density identified by a global dataset is 822 t/ha and only
53,000 km? is identified with density above 800 t/ha. In contrast, the regional dataset
shows the extent of the territory with carbon density above 800 t/ha to exceed 839,000
km° and within this, 115,000 km” has an estimated density in excess of 1,600 t/ha.

The estimate of total carbon stock in Canada derived by authors of the regional study
(Tarnocai & Lacelle, 1996) is 262.3 Gigatons. This number is 40.6% higher than the
relevant number derived from a global dataset (186.6 Gt). This higher level of
uncertainty is expected for soil data, which has not been accurately estimated at a
global scale (Annex 1), and it is clear that the underestimation of carbon in soil in
high density areas is a limitation of this study.

Peat land carbon — Canada

The Peatlands of Canada Digital Database (Tarnocai er al. 2005) provides an estimate
of the peatland extent of Canada. The map presented in Figure 9 is derived from this
regional source and estimates the average density of peat carbon within all landscape
units containing peatlands. It should be noted that, due to variations in the ratio of
peatland area within landscape units, the densities depicted on the map may represent
the total density of soil carbon within a particular unit only when peatland completely
covers that particular landscape unit. For units with a lower ratio of peatland area, an
additional amount of carbon is expected to be found in non-peatland habitats. An
example of continuous territory in which peatlands cover reaches 100% is highlighted
on the map (Figure 9).

Peat carbon, tons/hectare
0

Figure 8: Peat carbon component density in selected Canadian landscapes (based on
Tarnocai ¢7 z/ 2005). Red outline indicates the territory with 100% peatland coverage.

Figure 9: Soil carbon density in Canada (based on IGBP-DIS, 2000).

Comparison of these two datasets reveals substantial differences in SOC estimates for
peatland. For the regional dataset, the maximum density of peatland carbon in
separate landscape units reaches 3,500 tons/ha, while there are no values higher than

22

822 tons/ha identified by the global dataset. Within the area represented by
continuous peatlands (highlighted on figure 9), estimates available from the regional
dataset exceeded ones derived from the global data by 500-1000 tons/ha for almost
the entire sample area. An estimate of total soil carbon within all landscape units
represented on the map is 110.5 Gt (based on global data) whilst the carbon stock of
the peatlands alone is estimated as 144.5 Gt (based on Tarnocai et al. 2005) or 30.7%
higher. Considering that additional carbon is stored by non-peat soils, and their extent
within the study area, its total stock here may be higher by 31 Gt (a modest estimate
based on the assumption that 100 tons/ha is the average carbon content for all
remaining territory) or up to 56 Gt (based on an extract from a global dataset, where
the lowest carbon content area equivalent in size to the “non-peatland” extent of the
study area was accounted for).

These preliminary comparisons indicate that there is a high probability that the global
map of carbon content under-estimates soil carbon stocks, and further efforts are
required to increase reliability of global data. This is particularly true for peatland, as
a global estimate for carbon storage in peatland was not available at the time of study.
The estimates presented in this report should therefore be considered conservative,
and this emphasises need for the development of a more accurate global carbon map,
particularly for high carbon soils such as peatland. The spatial distribution of carbon
does appear to be estimated with more accuracy on a global scale than total values.

Section 4 - Carbon and conservation priority areas

The concept of identifying ‘win-win’ areas where ecosystem services and biodiversity
overlap is growing in prominence, but is difficult to put into practice due to a lack of
quantitative data (Naidoo et al. 2008). The data presented here allow identification of
areas of high carbon value which are not covered by the current protected areas
network on a global level. This provides the opportunity to identify areas for
protection or management in selected regions that are not just high in carbon, but also
have high biodiversity value; i.e. managing for ‘multiple benefits’. This data in
particular should provide useful input into the development of climate mitigation
policies, such as REDD, although localised pressures such as deforestation pressure
and the costs of protection should also be taken into account (Miles & Kapos 2008).

For these analyses, areas of high biodiversity value were identified based on the
spatial overlay of the outcomes of multiple conservation priority setting exercises.
These layers were: WWF Global 200 terrestrial priority ecoregions (Olson ef al.
2001), WWE Global 200 freshwater priority ecoregions (Olson et al. 2001),
amphibian diversity areas (Duellman 1999), Endemic Bird Areas datasets
(Stattersfield et al. 1998) and Conservation International hotspots (Myers et al. 2000).
Areas were assigned a value according to the number of ‘priority’ layers they

represented (e.g. areas that were included under all of the conservation priority areas
were assigned a 5).

The utility of such mapping is demonstrated here through case studies in Tanzania
and Papua New Guinea, which have been chosen as they are the first two countries
selected for assistance in developing and implementing REDD strategies by the
Norwegian Fund for Prevention of Deforestation in Developing Countries, launched

23

at the UN Framework Convention on Climate Change Conference of Parties in Bali,
December 2007. They also host very different ecosystems, cultures and political
contexts.

The maps for protected area coverage and carbon storage (Figure 10) combined with
conservation priorities in Tanzania (Figure 11) suggest that there is a large area of
unprotected land that is both high in carbon value and a priority for conservation. This
is also the case in Papua New Guinea (Figure 12, Figure 13). It should be noted that
priority setting schemes often use the lack of protected areas as an indicator of threat,
so high priority areas may appear to be situated outside of the protected area network
as an artefact of this. Regardless, such mapping allows for identification of areas that
should be focused on in future conservation strategies if the aim is to prevent carbon
emissions whilst conserving biodiversity.

These maps serve to demonstrate the relatively simple nature of combining carbon
and biodiversity data to set conservation priorities, and should be viewed more as a
tool for demonstration in priority setting workshops rather than as a tool for priority-
setting at a national level per se. Ideally, more accurate and context specific national
data should be used for the setting of national priorities, as these might differ from
those that would be determined on a global scale, and could correspond to the land
use pressures acting in that area.

om

Tanzania

[Je rtectes area
Carbon Stock
Tonshectare
{jgjo-10
Gij10-20
Gjx-0
Hy 50-100
(i 100-150
Way 150-200
(BB 200 - 2x0
Ba x0-«0
IRB «00-00
HE > 1000

Figure 10: Protected areas and carbon storage, Tanzania. Protected area data
includes all sites stored within the WDPA, including forest reserves.

24

Biodiversity Priorities,

overtap of
Uli 2-5
(23 Protectedarea
Carbon Stock
Tons/hectare

Figure 11: Carbon and biodiversity values, Tanzania.

“Papua New Guin ea

(Ce petected Area
Carbon Stock
Tonsihectare

[o-10

Figure 12: Protected areas and carbon storage, Papua New Guinea

Biodiversity Priorities,
overlap of

Wh r-5

(5) Protected Area

Carbon Stock

Tons/hectare

Figure 13: Carbon and biodiversity values, Papua New Guinea. Note that the
scale differs from that presented for Tanzania; highlighted areas have a higher
carbon content and conservation priority.

Summary

This analysis has brought together global data on carbon storage in vegetation and soil
to estimate the amount of carbon stored within the protected area network. The carbon
data used was considered to be the best available at the time of study, but is less
accurate than regional data and likely underestimates carbon storage in high biomass
areas; particularly in soil.

From the information presented in this report, it is clear that protected areas store a
large amount of carbon; 312 Gt or 15.2% of the total terrestrial carbon stock.
Strengthening of existing protected area networks and the creation of new protected
areas could therefore form part of a climate change mitigation strategy. Based on
current market prices, the carbon stored in ecosystems would be worth between
€1,142 and €7,992 billion, if each tonne was valued in the market. This is the first
attempt to quantify one of the benefits of the protected area network that had until
recently been largely overlooked. Less than half of the carbon within the protected
area network is stored in the more restrictive IUCN protected area management
categories I-IV, but more research is required as to the impacts of different
management categories on stored carbon

Regions differ in carbon storage iotals, densities, and levels of protection. South

America has the largest total carbon stores and the highest levels of protection at 25%
(not including Greenland). The Pacific has the lowest level of protection with 96% of

26

the carbon unprotected, and is also one of the regions with the highest carbon density,
second only to South East Asia. A significant carbon store in the boreal soils and
northern latitude forests of Eurasia also has low levels of protection, but is likely
subject to less land use pressure than that of the tropics.

The data presented here have also demonstrated the capacity to identify areas that
have both high carbon content and high biodiversity value, which could assist in
conservation priority setting and the identification of ‘multiple benefit’ areas for
protection or management of carbon for climate mitigation strategies, such as through
REDD implementation.

Climate change mitigation policy related to terrestrial carbon storage (namely
REDD), has thus far concentrated mostly on forest ecosystems. It should be
emphasised that forests are not the only ecosystems that can make a valuable
contribution to climate change mitigation; a considerable amount of carbon is also
protected in the soil and in the biomass and of other ecosystems. The carbon storage
of peatland is a major area that has not been addressed in this report.

In addition, the large majority of global terrestrial carbon stocks are stored outside of
the protected area network. Whilst protected areas clearly have a carbon storage
benefit and can clearly play a role in reducing emissions from land use change,
protected areas are only one option for conserving terrestrial ecosystems. Most carbon
is stored outside of the protected area network, and protecting the carbon in one area
will be of little consequence if carbon is lost from other land areas. In order to
successfully included carbon storage in terrestrial ecosystems as a climate mitigation
strategy, other land use options for the protection of carbon should be incorporated,
including through CCAs and the development of best practices for land management
and land use planning. The implementation of climate policy such as REDD on a
large scale is unlikely to be feasible without the support of indigenous and local
communities. The official recognition and encouragement of community-based forest
management is becoming more widespread, and could become a viable component of,
or complement to, protected areas in reducing deforestation

Scope for further research
Data improvements

There are a large number of challenges to estimating carbon storage, and it is likely
that improved data for carbon storage in vegetation and soils will become available at
global, regional, and national scales. The European Space Agency has recently made
available a new global land cover dataset (GlobCover) from 2005 that is considered to
be more accurate than the GLC2000. In addition, the FAO has released the
Harmonised World Soil Database which provides estimates for soil carbon
(FAO/IIASA/ISRIC/ISS-CAS/JRC 2008). Utilising this data, new estimates of
calculated carbon stocks using the Intergovernmental Panel on Climate Change
(IPCC) Tier-1 approach (IPCC 2006, Gibbs et al. 2007) could be generated.

In addition, it is clear that the carbon storage estimates in soils likely underestimate
carbon stocks in high density areas. This is particularly the case for peatland, as there

27

is currently no dataset available for peat distribution and depth globally, but it is a
significant carbon store. Quantifying this peatland carbon store, and the level of
emissions from peatland loss and degradation, would be a valuable contribution to
climate policy development

We have also identified that maps of carbon storage within marine and coastal
ecosystems are not readily available. This is a potential important area for further
research and collaboration building, including with respect to valuation of marine
protected areas, but also for the wider issues of carbon storage within marine
ecosystems, and the potential impact of human activities with the aim of climate
mitigation.

Next steps

Following estimates of the amount of carbon stored in protected areas, the next logical
step is to provide some estimate of the efficacy of protected areas in reducing carbon
emissions. UNEP-WCMC, in collaboration with The Nature Conservancy and
University of South Dakota has provided an estimate of emissions from deforestation
within protected areas. The data presented here also provide the basis for mapping
high carbon and high biodiversity areas at the scale of the entire tropical biome. This
could also include identification of areas under deforestation and degradation
pressures, and provide guidance on new methods for doing gap analysis for protected
areas with carbon as an input.

Although this report is mainly focused on protected areas, this is only a small area for
research in the broader view of carbon storage and biodiversity. A holistic view of the
carbon storage implications of improved forest management, and sustainable use of
forest resources is an important area for future research; taking into account issues
such as certification schemes, leakage and local livelihoods. Information on how
IUCN management categories relate to levels of degradation, and the implications for
carbon storage, is also required. The impacts of governance on carbon storage in
particular would be a useful input to this discussion.

Further research is also required into the carbon storage of non-forest ecosystems and
soils. The introduction of REDD could have significant implications for the
conservation of these areas, which can have high carbon and biodiversity benefit. This
could be explored through the removal of the forest carbon layer from the carbon
map, identifying high carbon areas with low forest cover and high biodiversity
benefit; analyses which would also be useful for the biofuel debate. The issue of the
potential for REDD to conserve forest at the expense of other ecosystems, and how
non-forest ecosystems can be incorporated into REDD mechanisms is one requiring
further attention.

Indeed, REDD will have implications for biodiversity conservation on all scale, and
an analysis of the potential biodiversity impacts of the various proposals for REDD
would be useful input to current discussions, which could include discussion of the
potential place for protected areas within REDD.

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30

Annex 1 — Carbon storage in ecosystems data review

A comprehensive literature review of the available data sources for terrestrial carbon
storage was undertaken in order to source the most accurate data for global and
regional carbon stocks. This section identifies the available carbon storage maps, and
provides a summary of the data chosen to produce the global carbon map.

Carbon in terrestrial ecosystems

The IPCC guidelines for national level estimation of carbon stocks identify three
broad carbon pools: biomass (above and below ground living vegetation), dead
organic matter (DOM), and soil organic carbon (SOC) (IPCC 2006). Carbon stocks
are generally measured using inventories over small spatial scales, with allometric or
statistical relationships used to determine biomass and carbon stocks over a given
area. These can be extrapolated to larger scales with average carbon densities applied
according to ecosystem type. Other approaches involve ecosystem modelling, and
either of these mapping approaches can be used in combination with remote sensing
techniques. Soil stock estimates require knowledge of the organic carbon content of
soil profiles and the spatial distribution of the various soil or vegetation types; and can
be estimated to varying depths.

Carbon stock estimates differ according to the methodology selected, the
comprehensiveness of the inventories, ecosystem model parameters selected,
allometric and statistical equations used, and the land cover maps used for spatial
representation. One of the major issues with global carbon stock estimation is the
existence of a wide range of national and regional estimates that vary in these
methodological factors. On the other hand, global datasets may lack accuracy because
they do not capture variations in vegetation cover over relatively small scales (Potter
1999).

Global estimates

There are currently a small number of readily available global carbon storage datasets,
each providing different estimates and accounting for different carbon pools. Due to
differences in national accounting, coarse scale but globally consistent carbon maps
necessarily use the ‘Tier 1’ (broad-brush) IPCC approach, extrapolating carbon
densities for vegetation types to global averages on a biome scale. Most estimates are
based upon biome carbon averages that are modified in ways not often transparent
(Gibbs et al. 2007); again indicative of the methodological problems of standardising
carbon accounting over a large scale. Until recently, the most widely used reference
data for carbon storage in vegetation was from Olson et al. (1983), which was based
on over 20 years of field investigations and an analysis of published literature (Olson
et al. 1985). Similarly, soil carbon profiles have often involved the use of carbon
density averages from original studies (Zinke et al. 1984; Batjes 1996; Post et al.
1982) to allocate values to soil types in the FAO soil map of the world.

31

Data for carbon storage in vegetation
The estimates available to date (Table 5) are derived from either biome averages

based on site measurement data, or the use of satellite observations in combination
with ecosystem models. A more in-depth look at the three datasets is reported below.

Table 5: Global datasets considered— carbon stored in vegetation

| Carbon pools | Methods Source
Above and | NASA-CASA ecosystem model driven by AVHRR. | Potter (1999)
below ground | Average carbon (g/m2) multiplied by area for each
biomass, vegetation type to estimate total carbon
Above and | Update of Olson et al. (1983) vegetation data onto | PAGE (WRI
below ground | the Global Land Cover Characteristics Database of | 2000)
biomass, 1998
Above and | IPCC Tier 1 approach. Above ground biomass | SAGE
below ground | carbon stock estimates obtained through the |(Ruesch &
biomass application of biome averages to a recent land cover | Gibbs, in
map (GLC2000). review)

Potter (1999) dataset

A global dataset for above-ground biomass has been compiled by Potter (1999), using
an ecosystem modei driven by satellite observations, which estimates parameters such
as carbon fixation, plant biomass, litter fall, and nutrient exchange on a daily or
seasonal basis. Satellite ‘greenness’ data from the Advanced Very High Resolution
Radiometer (AVHRR) fed into the NASA-CASA ecosystem model.

One advantage of the ecosystem modelling technique is that it can simulate regional
variability in carbon stores (Potter 1999, Cao & Woodward 1998, Ni 2001), long
recognised as an issue in biomass estimation across large forested areas (IGBP 1998).
Similarly, it can separately model the biomass in wood, leaves, and roots. However,
the complexities of ecosystem models mean that they are often more accurate over
regional than global scales (Le Toan et al. 2004). Indeed, whilst modelling does avoid
limitations in forest biomass inventories; incomplete understanding of ecosystem
processes, combined with uncertainties in key parameter estimates, severely limit the
accuracy of the approach (Tian et al. 2000; Malhi et al. 2006). Additionally, it has
been suggested that current optical satellite sensors, such as AVHRR, cannot be used
to estimate carbon stocks with any degree of certainty (Thenkabail et al. 2004 in
Gibbs et al. 2007; GCP; Houghton, 2005) and cannot accurately estimate biomass in
closed canopy forests (Houghton et al. 2001) or other high biomass areas (Lefsky
2002; Le Toan et al. 2004). The output in this case was also based on a now-outdated
1990 land use map.

PAGE (2000) estimate

The Olson et al. (1983) map of carbon storage in vegetation, widely considered to be
the most consistent on a global scale, was the basis for the global carbon estimate
incorporated into the Pilot Analysis of Global Ecosystems (PAGE; WRI 2000). The
data were reapplied to the Global Land Cover Characteristics Database of 1998, and
the iow and high estimates used in modelling (WRI 2000). The spatial data for

vegetation from the high range Olson ef al. (1983) estimates gave a 10 km resolution
map of carbon storage in terrestrial ecosystems.

There are a number of issues with this study. The spatial estimation of carbon stocks
used a very broad classification of ecosystem types (forest, grassland, etc) by mid,
high and low latitudinal bands, instead of more specific vegetation types. The Olson
et al. (1983) data also relies on direct measurement of biomass, and it had been
suggested that this methodology can be biased towards high biomass areas unless
statistically consistent inventory methods are used (Fang & Wang 2001, Fang et al.
2006).

SAGE (2008) estimate

This estimate calculated carbon stocks using the Intergovernmental Panel on Climate
Change (IPCC) Tier-1 approach (IPCC 2006, Gibbs et al. 2007). Above-ground
biomass carbon stock estimates for each country were obtained through the
application of biome averages to a recent land cover map (Bartholome & Belward
2005). Below-ground biomass was similarly estimated using the IPCC root-to-shoot
ratios by vegetation type (IPCC 2006). Biomass values reported by IPCC (2006) were
converted to carbon stocks through application of the IPCC standard 0.47 carbon
fraction. Time-averaged carbon stocks for cropping systems were estimated by
assuming linear growth rates, and using half the peak carbon stock (van Noordwijk et
al. 1997). This data splits carbon estimates into more vegetation classes than the
Olson data, allowing for more realistic variation than in the PAGE estimate. For
example, Olson et al. (1983) used a single value for all tropical forest (Gibbs er al.
2007). The data used in this estimate varies by continent, ecoregion, and vegetation
type, for both above and below-ground biomass (H. Gibbs pers comm.).

There are some drawbacks to his approach. As with all studies using biome averages,
there is no variation within vegetation classes, and therefore the abrupt changes
between e.g. grassland and shrubland at the boundaries are not realistic. More detailed
regional studies have demonstrated significant variation in biomass on much smaller
spatial scales (Saatchi et al. 2007, Malhi et al. 2006). Regardless, these data are the
most recent available for global vegetation carbon, and as the only global estimates to
follow IPCC guidelines they appear to be the most accurate and the most relevant to
REDD negotiations. The data was also readily available for use following
communication with the author, and was therefore selected for use in this study

Other global data sources (Luyssaert et al. 2007, Bolin & Sukumar 2000, Kauppi
2003, Dixon et al. 1994, Cao & Woodward 1998) exist, but are either outdated or
focused only on forest ecosystems. The Global Carbon Project aims to provide
detailed data sources for accurate accounting of carbon storage, but these data are not
yet available. Long wavelength SAR and Vegetation Canopy Lidar (VCL) have been
identified as potential tools for the production of a global estimate (Drake et al. 2002)
VCL shows potential for obtaining biomass estimates from space and has the ability
to measure forest height, and SAR should have the capacity to produce global
biomass maps up to values of 100 t/ha. Global biomass estimations may also be
improved using imagery from the Advanced Land Observing Satellite (ALOS), a
Japanese satellite featuring PALSAR (an L- band frequency high performance SAR
satellite) and ideal for biomass estimation (JAXA EORC 2008). The satellite covers
each of the earth’s land masses three times a year, and has the capacity to produce the

33

first systematic global observations for biomass map generation (Kellendorfer et al.
2008)

Data for carbon storage in soil

The importance of carbon storage in soil is becoming increasingly recognised
following observations that the soil carbon store contains three times as much as that
of vegetation (Smith 2007, IPCC 2000); with storage in peat soil contributing a
significant amount towards this total (Mitra et al. 2005, Hoojier et al. 2006, Botch et
al. 1995).

Current global estimates are based upon the small number of available estimates of
carbon in various soil profiles (Eswarran et al. 1993, Batjes 1996, Zinke et al. 1984)
or vegetation units/climatic zones (Post et al. 1982). Large scale estimates of soil
carbon are still limited by a lack of knowledge of different soils in terms of spatial
distribution and land use (Batjes 1996). There is also some debate over the depth to
which carbon storage in soils should be measured for carbon accounting. The default
value specified in the IPCC guidelines is 0-30cm (IPCC 2006), but the vertical
distribution of SOC is poorly understood (Jobbagy & Jackson 2000), as is its
vulnerability to disturbance at different depths and by different processes. It could be
considered that the IPCC guidelines are conservative, and consequently most global
estimates of SOC are to a depth of 1m (Mikhailova & Post 2006).

Potter & Klooster (1997) and WRI (2000) have produced global carbon maps based
on data from Post et al. (1982) and Batjes (1996) respectively. Jobbagy & Jackson
(2000), Puzachenko et al. (2006), and The United States Department of Agriculture -
Natural Resources Conservation Service (USDA-NRCS) have similarly produced
global SOC maps (1m depth). Various other studies have modelled the potential
impact of climate change on soil carbon pools (Jones et al. 2005), but do not include
data on soil profiles and are aimed at more theoretical projections of future carbon
stores than quantification of current carbon stock. Work is currently in progress to
create improved an improved soil map through the SOTER project. Whilst SOTER
maps are already available for Eurasia, parts of Africa, and South America, a global
dataset has not yet been developed (Dobos et al. 2005). The Global Environment
Facility Soil Organic Carbon Modelling System (GEFSOC) project (Easter et al.
2007) has produced some regional SOC estimates but is not currently available for
global estimates.

A SOC dataset published by the International Geosphere-Biosphere Programme in
1998 (IGBP-DIS 2000) estimates organic carbon density to | m depth, at 5 minute
resolution. This dataset is based on the FAO Soil Map of the World and ISRIC pedon
data and was selected for use in this study as a readily available data source that is
considered reliable on a global scale (downloaded from http://daac.ornl.gov/). The 1m
depth is appropriate for this analysis, but likely underestimates carbon emissions from
deeper peatland systems. No global dataset of peat depth is yet available.

Regional estimates

There are a large number of national and regional estimates of carbon storage in
terrestrial ecosystems (Table 6). Such estimates tend to be more accurate because they

34

are extrapolated over smaller scales, rely on better inventory data, and can account for
spatial variation in more detail.

Table 6: Selected regional studies considered for use due to quality or

availability of data.

Region Ecosystem Carbon | pool Availability Reference
Basin biomass (2007)
Amazon | Old Vegetation Unknown Malhi et al.
Basin growth biomass DOM (2006)
forest
Brazilian | All SO Readily downloadable Cermi et al.
Amazon (2007)
Tropical | Forest Woody Biomass | Available Gibbs et al.
Africa (2007)
Africa (2002)
Tropical | Forest Vegetation Available Brown et al.
South biomass (2001)

SE Asia
Northern | Forest
Latitude
Northern | Forest
Latitude

East Gibbs et al.
Asia (2007a)
Tropical | Forest Vegetation Unknown Brown et al.

biomass & SOC (1993)
Goodale et al.
(2002)

Myeni et al.
(2001)

}All==————_—«s|: Unknown Potter (2006)

(2006) _
= a
Lacelle (1996)

Available Tarmocai &

Do not appear to be

patially explicit

Unknown

Above ground
ee

Lacelle

USA [All
USA All
Canada _ | All
Canada _ | Peatland
Russia All
Russia All

Russia Forest

All Nilsson et al.
appear spatially explicit (2000)
(1996)

Forest stand (http://daac.ornl.gov/RLC/ | Stone et al
guides/RLC_forest_carbon | (2003)
_73.html)

Europe | Forest

Vegetation Map produced would Nabuurs &
biomass require author contact Schelhaas
(2003)

Europe All

SOC Available Jones et al. 2005

35

Tropical estimates

Given the importance of tropical forest deforestation in carbon fluxes, much of the
national and regional analysis has focused upon the tropical forest ecosystems
(Achard 2004, DeFries et al. 2002, Houghton 2003). Many studies have focused
specifically on tropical forest within Latin America (Brown & Lugo 1992, Chave et
al. 2003, Baker et al. 2004, Malhi et al. 2006, Saatchi et al. 2007) with wide ranging
results in carbon storage and distribution estimates (Houghton et al. 2003).
Interestingly, the Olson et al. (1983) data and Potter (1999) were shown to
underestimate biomass in the Amazon, and lack accurate spatial representation of
biomass densities respectively. Other studies have focused upon tropical Asia (Brown
et al. 1993; Chabra et al. 2002) including one comprehensive study by Gibbs &
Brown (2007a), updating estimates based on GIS processing of FAO georeferenced
data onto the GLC 2000 land cover map. Relatively few carbon stock estimates have
been carried out in Africa, the most comprehensive of which was provided by Gaston
et al. (1998) and updated by Gibbs & Brown (2007b).

Saatchi et al. (2007) estimated carbon stocks in Amazon Basin vegetation by
combining data from biomass plots and remote sensing data (incorporating forest
characteristics and environmental variables). This approach combines biomass
estimates (limited in spatial coverage) with remote sensing for the entire region
(limited in capacity for biomass estimation), improving the capacity of the predictive
model (Houghton et al. 2007). In contrast with other studies of the Amazon, biomass
values were calculated according to all vegetation types present, such as old growth
forest, floodplains, and small coastal patches. The Saatchi et al. (2007) estimate
improved the model by combining optical data with radar data (Houghton et al.
2007). This dataset was considered to be one of the most reliable for the tropical
region, accounting for all vegetation types in a region for which the need to protect
forest from deforestation has been highlighted. The dataset was also readily available,
and was therefore appropriate for use in this study.

Despite the fact that there is a substantial carbon store in the soils of tropical forest
(41% of the total tropical carbon store according to Brown & Lugo (1982)), very few
studies have estimated SOC for tropical regions. A number of estimates do exist for
parts of Africa (Zinke et al. 2002, Batjes 2004, Milne et al. 2006) and Brazil (Batjes
& Dijkshoorn 1999, Batjes 2005, Bernoux 2002, Moraes et al. 1995, Cerri et al. 2007)
but do not correspond to the geographical area covered by Saatchi et al. (2007) and
were therefore not selected for use in this study.

Northern Latitude estimates

Although a large amount of detailed inventory data is available for northern latitude
forests (Dong et al. 2003), there are many areas in which inventory data is patchy and
not adequately georeferenced (Houghton er al. 2001). Biomass of ecosystems other
than forest is also less well known, and accurate soil carbon data for boreal
ecosystems is lacking.

There are a number of estimates of the total carbon storage in northern latitude forest
(Goodale et al. 2002, Myeni et al. 2001, Liski et al. 2003), with other studies focusing
on Russia (Shivdenko & Nilsson 2003, Alexeyev et al. 1995, Houghton et al. 2007,
Stone et al. 2003), China (Wang ef al. 2007, Piao et al. 2005), North America
(Birdsey 1992, Zhang & Kondragunta 2006) and Europe (Kauppi et al. 1992,

36

Nabuurs, &. Schelhaas 2003). There are in addition some estimates of the entire
carbon store for USA (Potter 2006) and Russia (Nilsson et al. 2000). A recent study
into the North American carbon budget (CCSP 2007) has estimated the terrestrial
carbon stocks (biomass, litter and soil) across ecosystems, biomes, and countries
(USA, Canada and Mexico) in North America but does not provide spatially explicit
data. Many of these studies are based on old inventory data, and do not appear to have
produced readily available spatially explicit estimates. In addition, the carbon storage
in northern latitude soils is receiving increased attention due to estimates that they
account for approximately 45% of the entire terrestrial carbon store (Post et al. 1982,
Gower et al. 2001). The decision was therefore taken to identify a SOC dataset for
northern latitudes, as there were few accurate biomass datasets obviously available.

Datasets for SOC were identified in China (Xie et al. 2007, Yu et al. 2007), Russia
(Orlov et al. 1996, Rozhkov et al. 1996, Stolbovi & Vladimir 2004) and Europe
(Jones et al. 2005, Dobos et al. 2005). In selecting a SOC dataset, however, it seemed
appropriate to choose an area of high carbon storage, incorporating peatlands, such as
the boreal area of Russia and North America. The Soil Organic Database of Canada is
considered to be one of the most accurate data sets available for soil carbon content
(Kuhry et al. 2002) and a map of soil organic carbon in Canada (Tarnocai & Lacelle,
1996), was therefore selected for use in this study. Peatland soils store a large amount
of carbon (Mistra et al. 2005, Hoojier et al. 2006), and Canada has the largest area of
peatland soil in the world. In addition, a recent map of carbon in peat soils in Canada
has been produced (Tarnocai 2005), providing a comprehensive spatially explicit and
detailed carbon storage estimate. This appears to be the most comprehensive SOC
data available across a large and high carbon content region to date. The CARBO-
North Project, due for completion in 2010, is likely to be a useful information source
in the future.

Summary of global and regional estimates

It is clear that there are a large number of datasets available, providing carbon
estimates for a variety of ecosystems, regions, and carbon pools. The majority of
studies focus upon forest biomass and soil carbon, and carbon storage in other
ecosystem types is less well known. The methods for estimating carbon storage vary
widely, and no single method is considered highly accurate. The use of improved
technology for biomass estimation and databases for soil carbon estimation is likely to
improve the accuracy of carbon estimates in coming years.

On a global scale, the use of biome averages and the increased uncertainty of carbon
storage estimates for higher biomass classes tend to lead to a less accurate picture for
individual regions than equivalent regional maps. Whilst much variability can be
found at a regional scale, these biome-based estimates do provide a consistent
indicative picture of the pattern of carbon storage. From the global datasets assessed
here, the SAGE estimates using IPCC methodologies (Reusch & Gibbs, in review,
Gibbs et al. 2007) have been selected for use. The data are globally consistent and

split carbon density averages more finely into more vegetation classes than the data
provided by Olson et al. (1983).

It is also important to quantify soil carbon storage, as research has suggested that soil
carbon accounted for 28% of net loss from land use change in the period 1850-1990

37

(Houghton 2005), and failure to include soil carbon would underestimate carbon
storage at northern latitudes, which is estimated to contribute 53% of the total carbon
store (WRI 2000). The IGBP-DIS (2000) soil data was selected for use as a readily
available source to 1m depth. The only global litter carbon estimate was produced
through ecosystem modelling as part of the Potter (1999) study, and was not
considered appropriate for this study.

At a regional scale, there is a much wider range of data available for carbon storage.
Datasets for biomass in the Amazon Basin (Saatchi et al. 2007) and SOC in Canada
(Tarncoi & Lacelle 1996) were selected to provide context of the accuracy of the
global data for both biomass and soil in two areas of high carbon storage. Both
datasets are considered to be the most accurate available both for the regions and
carbon pools that they provide estimates for, as although other datasets for the
Amazon could be considered equally accurate, they do not provide estimates for all
vegetation classes.

Carbon in marine ecosystems

From the review above it is clear that many studies have focused on the estimation of
carbon storage within terrestrial ecosystems. Comparatively, knowledge of carbon
storage within marine environments is limited, and no equivalent literature exists. For
this reason, we were not able to include marine ecosystems in this analysis. This
would appear to be a significant knowledge gap, considering that the total amount of
carbon stored in the ocean is 50 times that of the atmosphere (IPCC 2001). Despite
this, there is some information available relating to carbon storage in specific marine
ecosystems, such as mangroves and coral reefs; and marine organisms.

Mangroves

Mangrove forests are highly productive (Bouillon et al. 2008), and their ability to
store organic carbon is extremely significant, despite accounting for less than 1% of
total forest cover on earth (Ayukai 1998). The total global storage of carbon in
mangroves has been estimated at 4 PgC (Twilley et al. 1992). Various techniques can
be used to estimate the standing biomass of mangrove forests, most commonly
satellite imagery combined with field data (Mann 2000); a methodology used for
biomass estimation in Florida (Simard et al. 2006) and South Africa (Steinke et al.
1995). Other studies have estimated carbon storage in mangrove forests of Australia
(Ayukai 1998, Matsui 1998), Brazil (Soares and Schaeffer-Novelli 2005), and the
Dominican Republic (Sherman et al. 2003) through inventories, aerial photography
and statistical relationships; producing varying results. Of these, only the estimate by
Steinke et al (1995) considered below ground biomass. Also important is the carbon
stored in the soils of mangrove swamps and sand marshes, which has been estimated
on a global scale (Chmuera et al. 2003). As with terrestrial forest biomass, remote
sensing appears to lack accuracy in estimation of carbon stored in high biomass areas
(Lucas et al. 2007, Mougin et al. 1999, Simard et al. 2006; cited in Proisy et al.
2007).

Coral Reefs
Corals store carbon in their calcium carbonate skeletons. However, due to the

production of COz in the calcification process, it has been suggested that coral reefs
generally act as alkalinity sinks and CO) releasing sites (Suzuki 2003). Unfortunately

38

there is little data involving carbon biomass storage in coral reefs and this is a
significant gap in our knowledge. Of the few studies that do exist, they are focused on
the calcification and productivity of the coral (Andréfouét & Payri 2001, Field et al.
1998)

Plankton

Estimation of carbon storage in the oceans is constrained by the difficulties of
measuring biomass of marine organisms such as phytoplankton and zooplankton,
which varies on termporal, horizontal, and vertical scales. A number of studies
(Kopezynska & Fiala 2003, Batten et al. 1999, Behrenfeld & Boss 2006) have
attempted to measure biomass across small scales using plankton recorders,
biochemical analyses, and optical indices. In addition, several studies (Goes et al.
2004, Smith et al. 1998, Fiala et al. 1998; Brock & McClain 1992) have used satellite
ocean colour remote sensing analysis in order to determine the level of interannual
variability of plankton biomass, which is strongly influenced by meteorological and
oceanographic conditions (Goes et al. 2004). However, there is little data relating to
the amount of carbon biomass of marine plankton for a specific area, largely due to
the aforementioned spatial and temporal variability. Strong blooms may develop
during certain periods during the year, determined by both global and local factors
(Twilley et al. 1992).

Macrophytes / Microphytes

Seagrasses and seaweeds have high rates of primary production (Alongi, 1997).
Remote sensing has been used to estimate seagrass biomass in a number of areas
(Armstrong 1993, Mumby et al. 1997), and similar remote sensing technology has
been used for estimating biomass in submerged Kelp (large seaweeds; Simms 2003).
Seagrass meadows have been estimated to account for 15% of the total carbon storage
in marine ecosystems (Duarte et al. 2004). In addition, the potential contribution of
microscopic algae to marine carbon storage should not be overlooked, and their
biomass has been measured thorough spectrophotometry in the South West Pacific
(Garrigue 1998). The organic metabolism in coastal regions is greatly impacted
(particularly in estuaries) by climate variability and anthropogenic activity (Smith &
Hollibaugh, 1993).

Duarte et al (2004) have constructed a carbon budget model for the coastal ocean in
order to examine the organic export from vegetated habitats to the open ocean
together with the possible impact of their destruction. Their results estimated an
organic carbon burial in the coastal ocean at 210-244 Tg Cy", which was found to be
almost double the value of the previous assessment of global carbon budget (IPCC
2001; cited in Duarte et al. 2004). For example, the Hinchinbrook Channel is known
to be net autotrophic, meaning that the respired and buried organic carbon is less than
the fixed organic carbon present (Ayukai 1998). In general, marine vegetation is
shown to export a significant amount of organic carbon to adjacent ecosystems and
also store a vast amount in the sediments (Jennerjahn & Ittekkot 2002, Chmura et al.
2003, Brevik & Homburg, 2004; cited in Duarte et al. 2004).

Carbon Capture and Storage

Carbon sequestration in marine environments has been suggested as a climate change
mitigation option (Preuss 2001). However, there remains a serious question towards
the health of marine ecosystems if the sea is continually used to sequester carbon. The

39

Department of Energy (DOE 1999) claim that there is too little information to
estimate the amount of carbon that can be sequestered without harming marine
ecosystems, both on a short-term and long-term basis. It is vital therefore to gain
further information on the amount of carbon biomass present in marine ecosystems, in
order to demonstrate their vulnerability and their essential role in carbon storage.

Summary

There is a current lack of data for carbon storage within marine and coastal ecosystems
beyond the site level, and it is therefore difficult to gain a general picture of the carbon
storage capacity. For example, comparisons between biomass data from different
mangrove areas are difficult as the biomass is a function of the history and structural
variability (Soares & Schaeffer-Novelli, 2005). As with the terrestrial carbon data,
there are questions over the accuracy of comparing biomass measurements estimated
through different methods, yet there is no data for and regional estimates, even on a
coarse scale. The difficulty of quantitative biomass measurements in the coastal ocean
(Smith & Hollibaugh 1993) has resulted in the marine environment being a significant
gap in the carbon budget (Bouillon et al. 2008), in particular for seagrasses and coral
reefs. This is of particular importance when considering the high carbon storage
estimated in the coastal ocean (Duarte et al. 2004), which is highly vulnerable to
climate change through increasing temperatures and sea level rise.

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48

Annex 2 — Valuing carbon storage within ecosystems

The value of carbon stored in terrestrial ecosystems

Carbon emissions from deforestation account for an estimated 20% of emissions
(IPCC 2007); second only to that produced by fossil fuel combustion. Despite this,
projects relating to land use and forestry (LULUCF) accounted for only 1% of an
international carbon market worth $30 billion (€23 billion) in 2006 (Capoor &
Ambrosi 2007). The value of the market has risen to US$64 billion (€47 billion) in
2007 (Capoor & Ambrosi 2008). Given the contribution of deforestation and land
degradation to carbon emissions, it is likely that the value of carbon storage in
ecosystems will increase, particularly as the overall carbon market is projected to
increase in value (Hasselknippe & Roine 2007, Ebeling & Yasue 2008). Indeed, there
have been estimates from some reviewers that over $43 billion could be made
available to developing countries if REDD projects are formalized (Roe et al. 2007),
and that forested areas could be worth $200-10,000 per hectare depending upon a
number of factors such as carbon content and project type (Peskett 2007).

The range of forest carbon values reported above (Peskett 2007) highlights the
uncertainty in predicting a market value for stored carbon in a relatively volatile
market. The top end value corresponds to carbon trading for EUAs (European
emission allowances) on the biggest market, the EU Emissions Trading Scheme (EU
ETS), and would undoubtedly be an overestimate (Smith et al. 2000). There are also a
number of issues surrounding the permanence of carbon stored in ecosystems, which
lead to further uncertainties in the market value and place its value at a lower level to
the broader market e.g. for renewable energy schemes. In addition, carbon related to
land use is mostly traded though Verified Emission Reductions (VERs) on the lower
value Voluntary Market rather than through Certified Emission Reductions (CERs)
under the higher value Clean Development Mechanism (CDM); and the lack of Land
use, land use change and forestry (LULUCF) projects under the CDM makes the
value of a formalized market for carbon stored in ecosystems difficult to predict.
However, a large portion of the offsets in the growing voluntary sector retail market
are currently sourced through LULUCF mechanisms (Hamilton et al. 2008), and
whilst carbon offsetting through afforestation is often criticised, it is likely that an
avoided emissions project such as avoided deforestation would be competitive in the
market due to the perceived added benefits for biodiversity conservation (Chomitz et
al. 2006, Stern 2007).

The price of stored carbon will clearly be variable, and determined by a number of
factors. Any single value placed on carbon stored in ecosystems should therefore be
considered very speculative, particularly given that the scale of the market is yet to be
determined through, for example, REDD implementation. Despite this, it is possible
to gain some perspective of the potential value of carbon stored in ecosystems through
by assigning an indicative value based of the range of values observed in current
carbon markets and forestry projects.

49

Carbon markets

Markets in which carbon is traded can be broadly split into regulated markets and
voluntary markets. They are reported here to provide context for this assessment of
where carbon stored in ecosystems would likely sit in the overall carbon market. The
volume and value of carbon trading is clearly highest in regulatory markets (Table 7),
although the voluntary market is increasing rapidly and is indicative of demand for
projects not included in the UNFCCC. The regulatory market consists of the EU ETS,
the CDM and Joint Implementation (JI) markets, and the New South Wales market.
The voluntary market can be split into the Chicago Climate Exchange (CCX) and
‘over the counter trading’ (OTC). The CCX differs from the OTC market in that it is a
formal exchange, a legally binding ‘cap and trade’ system that members sign up to
voluntarily; whereas OTC is not driven by an emissions cap and mostly involves
project-based transactions generating VERs.

Table 7. Carbon market Transactions and Values, 2006 and 2007. Source:
Ecosystem Marketplace, New Carbon Finance, World Bank. Reported in
Hamilton et al. 2008

Markets Volume (MtCO2e) Value (US$million)
2006 2007 2006 2007

Voluntary OTC Market 14.3 42.1 58.5 258.4

CCX 10.3 22.9 38.3 72.4

Total Voluntary 24.6 65.0 96.7 330.8

Markets

EU ETS 1,1044

Primary CDM 537 551 6,887

Secondary CDM 25 240 8,384

Joint Implementation 16 41 141

New South Wales 225 224

20 25
Total Regulated 1,702 ieee 40,072 66,087
Markets

Total Global Market 1,727 | 2,983 | 40,169 66,417

EU ETS

The largest carbon market is the EU ETS, both in terms of volume traded and value of
transactions. Forestry credits are not currently eligible for trading on the EU ETS, and
its value is therefore not representative of carbon stored in ecosystems (Tollefson
2008). However, it should still be considered because it sends price signals to the rest
of the market. The average price for carbon traded on the EU ETS in 2006 was $20
per tCO2e (Capoor & Ambrosi 2007), a price that has risen to €20-25 for EUAs in
2007 (Capoor & Ambrosi 2008). Values for EUAs on the ECX were reported at
carbonfinanceonline.com to be €24.66 (from 10" April — Se May 2008 for Dec08
delivery), with €24.91 reported at carbonpositive.net in the first week of May. The
value has been increasing throughout May, closing at €26.11 on Reuters (23" May
2008), and €26.10 on Point Carbon (closing on 26" May 2008).

Table 9. Market values for carbon in forest sector. Price of land based offsets.
Adapted from Kollmuss ¢ 24 (2008), Taiyab (2006), Hamilton ¢7 a4 (2008)

Offset Price (t/CO2e)

Voluntary carbon standard | All minus new HFC _ | €5-15

(carbon market actors)

VER+ CDM minus large
hydro

CCX* All (mostly soil | €1-2
carbon)

Climate, Community and | LULUCF €5-10

Biodiversity standards (NGOs and
g porations)

Plan Vivo (NGOs)

Climate Care (UK) Community based | £6.50

energy, some forestry

Conservation International Forestry $5 Avoided
deforestation

$8-12 restoration

Face Foundation Forestry €10-13
Future Forests Forestry (and some | £13-16

energy)
Green Fleet Australia AUS$ 9.30

Primaklima Forestry €1.50

*Values on CCX have risen in early 2008 so this range is likely an underestimate
for May 2008

From the values presented above, it would appear that a reasonable range for the
valuation of carbon stored in terrestrial ecosystems falls at €1-10 for retail price,
considering that some would be attached to ‘standards’ and higher value, and
assuming that avoided deforestation is tested on the voluntary market for
formalization in the UNFCCC. Within this, a conservative estimate of €3 — €7 at the
higher end would appear acceptable for carbon stored in ecosystems across the board,
considering that forestry based projects command higher prices within the current
averages traded in the voluntary market and the values for forest carbon projects, and
that carbon stored within other ecosystems will undoubtedly command a lower price.
It is recognized that the value is highly speculative, and is being used only as an
indication of the potential worth of carbon stored in protected areas, rather than as a
prediction or thorough estimation of their value.

References

Brown, K; Adger, N; Boyd, E; Corbera-Elizalde, E & Shackley, S. 2004. How do
CDM projects contribute to sustainable development? Tyndall Centre for
Climate Change Research Technical Report 16.

Capoor, K., and Ambrosi, P. 2007. State and Trends of the Carbon Market. 2007. The
World Bank, Washington D.C., USA

Capoor, K., and Ambrosi, P. 2008. State and Trends of the Carbon Market. 2008. The
World Bank, Washington D.C., USA

53

Table 8. Percentage share of land use project types in the voluntary market

(OTC & CCX). Hamilton et al. 2008

Project type Percentage of land use market
Afforestation/Reforestation 13%

Plantation/Monoculture

Afforestation/Reforestation Native Restoration | 42%

Avoided deforestation 28%

Agricultural soil 16%

Other biological sequestration (such as | 0.1%

wetlands preservation)

It is difficult to forecast what the discussions at the UNFCCC conference in Bali will
do to the market, with Merril Lynch recently announcing a $9 million investment in a
REDD project in Aceh and the likelihood of further REDD testing in the voluntary
market. Recent commentary on carbonpositive.net suggested that the inclusion of
REDD in the UNFCCC will likely change the market for forest carbon. New Forests,
one example of a carbon company interested in investing in REDD in Papua New
Guinea, propose to protect various tracts of land to create VERs that they estimate
will be in the $3-$11 price range

Forestry carbon projects

A recent evaluation of the potential carbon finance that could be generated through
REDD (Ebeling & Yasue, 2008) based calculations on a range of €5-30/tCO2;
obtained through analysis of international markets. The lower range estimates appear
more accurate in the current market, especially when considering the value of carbon
traded through various carbon sequestration and storage projects. The Scolel de Te
project in Mexico generated carbon emission reduction units (ERUs) worth $10-12/tc
(de Jong et al. 2000, Brown et al. 2004) under the Joint Implementation (JI)
mechanism. The lower price applied to existing carbon stock conservation because of
their lack of inclusion in the CDM (Brown et al. 2004). Future Forests also purchases
carbon from reforestation projects at $12/tc (Smith & Scherr 2002).

Analysing predicted ‘forest carbon’ prices from a number of sources (Grubb et al.
2001, Point Carbon 2001, den Elzen & De Moor 2002), Smith & Scherr (2002)
concluded that market price estimates fall within an $8-40t/c range, most likely to
command a price of $15-20 if the US ratifies Kyoto and credits are banked for the
second commitment period. However, Neef et al. (2007) maintain that with few
market signals available for forest carbon under the CDM, the most reliable price
remains that established by the BioCarbon Fund of US$4 per carbon credit. Others
report that a price for stored carbon of $10 per ton is more realistic, and could likely
increase over the coming decades (Laurance 2007).

Table 9. Market values for carbon in forest sector. Price of land based offsets.
Adapted from Kollmuss ¢/ 2/ (2008), Taiyab (2006), Hamilton ¢ a (2008)

Offset Project type Price (t/CO2e)
Voluntary carbon standard | All minus new HFC _ | €5-15
(carbon market actors)

VER+ CDM minus large | €5-15
hydro
CCX* All (mostly _ soil

carbon)

Climate, Community and | LULUCF €5-10

Biodiversity standards (NGOs and

large corporations)

Plan Vivo (NGOs) LULUCF €2.5-9.5
| Climate Care (UK) Community based | £6.50

energy, some forestry
Forestry

$5
deforestation

$8-12 restoration
€10-13
£13-16

Conservation International Avoided

Face Foundation

Forestry
Future Forests

Forestry (and some

energy)
Green Fleet Australia AUS$ 9.30
Primaklima Forestry €1.50

*Values on CCX have risen in early 2008 so this range is likely an underestimate
for May 2008

From the values presented above, it would appear that a reasonable range for the
valuation of carbon stored in terrestrial ecosystems falls at €1-10 for retail price,
considering that some would be attached to ‘standards’ and higher value, and
assuming that avoided deforestation is tested on the voluntary market for
formalization in the UNFCCC. Within this, a conservative estimate of €3 — €7 at the
higher end would appear acceptable for carbon stored in ecosystems across the board,
considering that forestry based projects command higher prices within the current
averages traded in the voluntary market and the values for forest carbon projects, and
that carbon stored within other ecosystems will undoubtedly command a lower price.
It is recognized that the value is highly speculative, and is being used only as an
indication of the potential worth of carbon stored in protected areas, rather than as a
prediction or thorough estimation of their value.

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