With annotations by: AccessIPCC - Version 1.02 - 2010 Dec 14 - Contains annotated versions of all 44 Chapters of Working Groups 1, 2 & 3
With the exception of Chapter and Section headings, all coloured text has been inserted by AccessIPCC. The non-coloured text is the IPCC original.
A number of emails from the Climate Research Unit (CRU) of the University of East Anglia were published on the Internet in November 2009. This has provided a window into the world of climate science.
We have identified a number of key individuals involved in the emails whom we have designated as Persons of Concern [PoC]; a Journal in which a PoC has published has been designated as a Journal of Concern [JoC].
This is not to suggest that we believe such papers are necessarily flawed, but rather that, as Joseph Alcamo noted at Bali in October 2009, "as policymakers and the public begin to grasp the multi-billion dollar price tag for mitigating and adapting to climate change, we should expect a sharper questioning of the science behind climate policy".
References occur in a list at the end of each chapter. Citations are within the normal text of sections and paragraphs.
Person of Concern Key individual involved in CRU emails as defined in this spreadsheet.
|References, Citations, IPCC Roles||1||1|
Journal of Concern A Journal which has published articles by one or more PoCs (Person of Concern)
Model or Simulation Reference appears to be a model or simulation, not observation or experiment
Non Peer Reviewed Reference has no Journal or no Volume or no Pages or it has Editors.
Self Reference Concern Author of a chapter containing references to own work.
|References, Citations, IPCC Roles||46||73|
Paper authored or co-authored by person who is also in list of Authors of another chapter.
Paper dated 2007, when IPCC policy stated cutoff was December 2005
The short inline citation matched with more than one reference; however, AccessIPCC will link to the first reference found.
The short inline citation was not matched with any reference. Believed to be caused by typing errors.
The reference was probably peer reviewed.
|Chapter 9: Forestry||-||-||-||-|
|9.2 Status of the sector and trends||-||-||-||-|
|9.2.1 Forest area||-||8||-||-|
|9.2.2 Forest management||1||2||-||-|
|9.2.3 Wood supply, production and consumption of forest products||-||2||-||-|
|9.3 Regional and global trends in terrestrial greenhouse gas emissions and removals||5||28||-||-|
|9.4 Assessment of mitigation options||-||-||-||-|
|9.4.1 Conceptual introduction||-||2||-||1|
|9.4.2 Description of mitigation measures||-||-||-||-|
|22.214.171.124 Maintaining or increasing forest area: reducing deforestation and degradation||-||2||-||1|
|126.96.36.199 Maintaining or increasing forest area: afforestation/reforestation||1||5||-||-|
|188.8.131.52 Forest management to increase stand- and landscape-level carbon density||1||2||-||-|
|184.108.40.206 Increasing off-site carbon stocks in wood products and enhancing product and fuel substitution||3||-||-||-|
|9.4.3 Global assessments||-||-||-||-|
|220.127.116.11 Regional bottom-up assessments||8||30||2||5|
|18.104.22.168 Global Forest sectoral modelling||5||44||3||6|
|22.214.171.124 Global forest mitigation in climate stabilization analysis||-||5||-||-|
|9.4.4 Global summation and comparison||-||-||-||-|
|9.5 Interactions with adaptation and vulnerability||2||3||-||-|
|9.5.1 Climate impacts on carbon sink and adaptation||1||9||-||-|
|9.5.2 Mitigation and adaptation synergies||4||15||1||-|
|9.6 Effectiveness of and experience with policies||-||-||-||-|
|9.6.1 Policies aimed at reducing deforestation||2||21||-||-|
|9.6.2 Policies aimed to promote afforestation and reforestation||-||2||-||-|
|9.6.3 Policies to improve forest management||2||17||1||-|
|9.6.4 Policies to increase substitution of forest-derived biofuels for fossil fuels and biomass for energy-intensive materials||1||3||-||-|
|9.6.5 Strengthening the role of forest policies in mitigating climate change||-||2||-||-|
|9.6.6 Lessons learned from project-based afforestation and reforestation since 2000||-||3||-||-|
|126.96.36.199 Potential non-permanence of carbon storage||-||5||-||-|
|188.8.131.52 Additionality and baselines||-||-||-||-|
|184.108.40.206 Options for scaling up||-||1||-||-|
|9.7 Forests and Sustainable Development||-||-||-||-|
|9.7.1 Conceptual aspects||-||2||-||-|
|9.7.2 Ancillary effects of GHG mitigation policies||2||4||-||-|
|9.7.3 Implications of mitigation options on water, biodiversity and soil||3||4||-||-|
|9.8 Technology, R & D, deployment, diffusion and transfer||2||13||-||-|
|9.9 Long-term outlook||-||3||-||-|
|Number of citations of various credibilities||43||255||7||14|
|Percentages of citations of various credibilities||13.5%||79.9%||2.2%||4.4%|
Gert Jan Nabuurs (The Netherlands), Omar Masera (Mexico) [SRC:3],
|Potentially Biased Authors||1|
Kenneth Andrasko (USA) [SRC:4], Pablo Benitez-Ponce (Equador) [SRC:3], Rizaldi Boer (Indonesia), Michael Dutschke (Germany) [SRC:2], Elnour Elsiddig (Sudan), Justin Ford-Robertson (New Zealand), Peter Frumhoff (USA) [SRC:2], Timo Karjalainen (Finland) [SRC:3], Olga Krankina (Russia) [SRC:2], Werner A. Kurz (Canada) [SRC:3], Mitsuo Matsumoto (Japan) [SRC:1], Walter Oyhantcabal (Uruguay), Ravindranath N.H. (India) [SRC:6], Maria José Sanz Sanchez (Spain), Xiaquan Zhang (China) [SRC:1],
|SRC >= 5||1|
|Potentially Biased Authors||10|
Frederic Achard (Italy) [SRC:2], Carlos Anaya (Mexico), Sander Brinkman (The Netherlands) [SRC:1], Wenjun Chen (Canada) [SRC:1], Raymond E. (Ted) Gullison (Canada) [SRC:1], Niro Higuchi (Brazil), Monique Hoogwijk (The Netherlands), Esteban Jobbagy (Argentina) [SRC:3], G. Cornelis van Kooten (Canada), Franck Lecocq (France), Steven Rose (USA) [SRC:1], Bernhard Schlamadinger (Austria) [SRC:6], Britaldo Silveira Soares Filho (Brazil), Brent Sohngen (USA) [SRC:4], Bart Strengers (The Netherlands) [SRC:2], Eveline Trines (The Netherlands) [SRC:1],
|SRC >= 5||1|
|Potentially Biased Authors||10|
Mike Apps (Canada) [SRC:4], Eduardo Calvo (Peru),
|Potentially Biased Authors||1|
Nabuurs, G.J., O. Masera, K. Andrasko, P. Benitez-Ponce, R. Boer, M. Dutschke, E. Elsiddig, J. Ford-Robertson, P. Frumhoff, T. Karjalainen, O. Krankina, W.A. Kurz, M. Matsumoto, W. Oyhantcabal, N.H. Ravindranath, M.J. Sanz Sanchez, X. Zhang, 2007: Forestry. In Climate Change 2007: Mitigation. Contribution of Working Group III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change [B. Metz, O.R. Davidson, P.R. Bosch, R. Dave, L.A. Meyer (eds)], Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.
During the last decade of the 20th century, deforestation in the tropics and forest regrowth in the temperate zone and parts of the boreal zone remained the major factors responsible for emissions and removals, respectively. However, the extent to which the carbon loss due to tropical deforestation is offset by expanding forest areas and accumulating woody biomass in the boreal and temperate zones is an area of disagreement between land observations and estimates by top-down models. Emissions from deforestation in the 1990 s are estimated at 5.8 GtCO2/yr (medium agreement, medium evidence).
Bottom-up regional studies show that forestry mitigation options have the economic potential at costs up to 100 US$/tCO2-eq to contribute 1.3-4.2 GtCO2-eq/yr (average 2.7 GtCO2-eq/yr) in 2030 . About 50% can be achieved at a cost under 20 US$/tCO2-eq (around 1.6 GtCO2/yr) with large differences between regions. Global top-down models predict far higher mitigation potentials of 13.8 GtCO2-eq/yr in 2030 at carbon prices less than or equal to 100 US$/tCO2-eq. Regional studies tend to use more detailed data and a wider range of mitigation options are reviewed, Thus, these studies may more accurately reflect regional circumstances and constraints than simpler, more aggregate global models. However, regional studies vary in model structure, coverage, analytical approach, and assumptions (including baseline assumptions). In the sectoral comparison in Section 11.3 , the more conservative estimate from regional studies is used. Further research is required to narrow the gap in the potential estimates from global and regional assessments (medium agreement, medium evidence).
The carbon mitigation potentials from reducing deforestation, forest management, afforestation, and agro-forestry differ greatly by activity, regions, system boundaries and the time horizon over which the options are compared. In the short term, the carbon mitigation benefits of reducing deforestation are greater than the benefits of afforestation. That is because deforestation is the single most important source, with a net loss of forest area between 2000 and 2005 of 7.3 million ha/yr.
Mitigation options by the forestry sector include extending carbon retention in harvested wood products, product substitution, and producing biomass for bioenergy. This carbon is removed from the atmosphere and is available to meet society’s needs for timber, fibre, and energy. Biomass from forestry can contribute 12-74 EJ/yr to energy consumption, with a mitigation potential roughly equal to 0.4-4.4 GtCO2/yr depending on the assumption whether biomass replaces coal or gas in power plants (medium agreement, medium evidence).
In the long term, a sustainable forest management strategy aimed at maintaining or increasing forest carbon stocks, while producing an annual sustained yield of timber, fibre or energy from the forest, will generate the largest sustained mitigation benefit. Most mitigation activities require up-front investment with benefits and co-benefits typically accruing for many years to decades. The combined effects of reduced deforestation and degradation, afforestation, forest management, agro-forestry and bioenergy have the potential to increase from the present to 2030 and beyond (medium agreement, medium evidence).
Global change will impact carbon mitigation in the forest sector but the magnitude and direction of this impact cannot be predicted with confidence as yet. Global change may affect growth and decomposition rates, the area, type, and intensity of natural disturbances, land-use patterns, and other ecological processes (medium agreement, medium evidence).
Forestry can make a very significant contribution to a low-cost global mitigation portfolio that provides synergies with adaptation and sustainable development. However, this opportunity is being lost in the current institutional context and lack of political will to implement and has resulted in only a small portion of this potential being realized at present (high agreement, much evidence).
Globally, hundreds of millions of households depend on goods and services provided by forests. This underlines the importance of assessing forest sector activities aimed at mitigating climate change in the broader context of sustainable development and community impact. Forestry mitigation activities can be designed to be compatible with adapting to climate change, maintaining biodiversity, and promoting sustainable development. Comparing environmental and social co-benefits and costs with the carbon benefit will highlight trade-offs and synergies, and help promote sustainable development (low agreement, medium evidence).
Realization of the mitigation potential requires institutional capacity, investment capital, technology RD and transfer, as well as appropriate policies and incentives, and international cooperation. In many regions, their absence has been a barrier to implementation of forestry mitigation activities. Notable exceptions exist, however, such as regional successes in reducing deforestation rates and implementing large-scale afforestation programmes. Considerable progress has been made in technology development for implementation, monitoring and reporting of carbon benefits but barriers to technology transfer remain (high agreement, much evidence).
Forestry mitigation activities implemented under the Kyoto Protocol, including the Clean Development Mechanism (CDM), have to date been limited. Opportunities to increase activities include simplifying procedures, developing certainty over future commitments, reducing transaction costs, and building confidence and capacity among potential buyers, investors and project participants (high agreement, medium evidence).
While the assessment in this chapter identifies remaining uncertainties about the magnitude of mitigation benefits and costs, the technologies and knowledge required to implement mitigation activities exist today.
In the context of global change and sustainable development, forest management activities play a key role through mitigation of climate change. However, forests are also affected by climate change and their contribution to mitigation strategies may be influenced by stresses possibly resulting from it. Socio-economically, global forests are important because many citizens depend on the goods, services, and financial values provided by forests. Within this context, mitigation options have to be sought.
The world’s forests have a substantial role in the global carbon cycle. IPCC 2007a [NPR, 2007] ) reports the latest estimates for the terrestrial sink for the decade 1993 - 2003 at 3,300 MtCO2/yr, ignoring emissions from land-use change ( Denman et al., 2007 [NPR, SRC, 2007] , Table 7.1 ). The most likely estimate of these emissions for 1990 s is 5,800 MtCO2/yr, which is partly being sequestered on land as well ( IPCC, 2007a [NPR, 2007] ).
The IPCC Third Assessment Report (TAR) ( Kauppi et al., 2001 [NPR, SRC] ) concluded that the forest sector has a biophysical mitigation potential of 5,380 MtCO2/yr on average up until 2050, whereas the SR LULUCF ( IPCC, 2000a [NPR] ) presented a biophysical mitigation potential on all lands of 1167 0 MtCO2/yr in 2010 (copied in IPCC, 2001 [NPR] , p. 110).
Forest mitigation options include reducing emissions from deforestation and forest degradation, enhancing the sequestration rate in existing and new forests, providing wood fuels as a substitute for fossil fuels, and providing wood products for more energy-intensive materials. Properly designed and implemented, forestry mitigation options will have substantial co-benefits in terms of employment and income generation opportunities, biodiversity and watershed conservation, provision of timber and fibre, as well as aesthetic and recreational services.
Many barriers have been identified that preclude the full use of this mitigation potential. This chapter examines the reasons for the discrepancy between a large theoretical potential and substantial co-benefits versus the rather low implementation rate.
Since the IPCC Third Assessment Report (TAR), new mitigation estimates have become available from local to global scale ( Sathaye et al., 2007 [Ambiguous] ) as well as major economic reviews and global assessments ( Stern, 2006 [NPR] ). There is early research into the integration of mitigation and adaptation options and the linkages to sustainable development ( MEA, 2005a [NPR] ). There is increased attention to reducing emissions from deforestation as a low cost mitigation option, and with significant positive side-effects ( Stern, 2006 [NPR] ). There is some evidence that climate change impacts can also constrain the forest potential. There are very few multiple land-use studies that examine a wider set of
forest functions and economic constraints ( Brown et al., 2004 [NPR] ). Furthermore, the literature shows a large variation of mitigation estimates, partly due to the natural variability in the system, but partly also due to differences in baseline assumptions and data quality. In addition, Parties to the Convention are improving their estimates through the design of National Systems for Greenhouse Gas (GHG) Inventories.
Basic problems remain. Few major forest-based mitigation analyses have been conducted using new primary data. There is still limited insight regarding impacts on soils, lack of integrated views on the many site-specific studies, hardly any integration with climate impact studies, and limited views in relation to social issues and sustainable development. Little new effort was reported on the development of global baseline scenarios of land-use change and their associated carbon balance, against which mitigation options could be examined. There is limited quantitative information on the cost-benefit ratios of mitigation interventions. Finally, there are still knowledge gaps in how forest mitigation activities may alter, for example, surface hydrology and albedo ( IPCC, 2007b [NPR, 2007] : Chapter 4 ).
This chapter: a) provides an updated estimate of the economic mitigation potential through forests; b) examines the reasons for difference between a large theoretical potential and a low rate of implementation; and c) and integrates the estimates of the economic potential with considerations to both adaptation and mitigation in the context of sustainable development.
The global forest cover is 3952 million ha ( Table 9.1 ), which is about 30 percent of the world’s land area ( FAO, 2006a [NPR] ). Most relevant for the carbon cycle is that between 2000 and 2005, gross deforestation continued at a rate of 12.9 million ha/yr. This is mainly as a result of converting forests to agricultural land, but also due to expansion of settlements, infrastructure, and unsustainable logging practices ( FAO, 2006a [NPR] ; MEA, 2005b [NPR] ). In the 1990 s, gross deforestation was slightly higher, at 13.1 million ha/yr. Due to afforestation, landscape restoration and natural expansion of forests, the most recent estimate of net loss of forest is 7.3 million ha/yr. The loss is still largest in South America, Africa and Southeast Asia ( Figure 9.1 ). This net loss was less than that of 8.9 million ha/yr in the 1990 s.
|Region||Forest area, (mill. ha)||Annual change (mill. ha/yr)||Carbon stock in living biomass (MtCO2)||Growing stock in 2005|
|North and Central America||705,849||-0.3||-0.3||150,333||153,633||155,467||78,582|
Thus, carbon stocks in forest biomass decreased in Africa, Asia, and South America, but increased in all other regions. According to FAO 2006a [NPR] ), globally net carbon stocks in forest biomass decreased by about 4,000 MtCO2 annually between 1990 and 2005 ( Table 9.1 ).
The area of forest plantation was about 140 million ha in 2005 and increased by 2.8 million ha/yr between 2000 and 2005, mostly in Asia ( FAO, 2006a [NPR] ). According to the Millennium Ecosystem Assessment ( 2005b ) scenarios, forest area in industrialized regions will increase between 2000 and 2050 by about 60 to 230 million ha. At the same time, the forest area in the developing regions will decrease by about 200 to 490 million ha. In addition to the decreasing forest area globally, forests are severely affected by disturbances such as forest fires, pests (insects and diseases) and climatic events including drought, wind, snow, ice, and floods. All of these factors have also carbon balance implications, as discussed in Sections 9.3 and 9.4 . Such disturbances affect roughly 100 million ha of forests annually ( FAO, 2006a [NPR] ). Degradation, defined as decrease of density or increase of disturbance in forest classes, affected tropical regions at a rate of 2.4 million ha/yr in the 1990 s.
Data on progress towards sustainable forest management were collected for the recent global forest resources assessment ( FAO, 2006a [NPR] ). These data indicate globally there are many good signs and positive trends (intensive forest plantation and rising conservation efforts), but also negative trends continue (primary forests continue to become degraded or converted to agriculture in some regions). Several tools have been developed in the context of sustainable forest management, including criteria and indicators, national forest programmes, model forests and certification schemes. These tools can also support and provide sound grounds for mitigation of climate change and thus carbon sequestration.
Nearly 90% of forests in industrialized countries are managed “according to a formal or informal management plan” ( FAO, 2001 [NPR] ). National statistics on forest management plans are not available for many developing countries. However, preliminary estimates show that at least 123 million ha, or about 6% of the total forest area in these countries is covered by a “formal, nationally approved forest management plan covering a period of at least five years.” Proper management plans are seen as prerequisites for the development of management strategies that can also include carbon-related objectives.
Market-based development of environmental services from forests, such as biodiversity conservation, carbon sequestration, watershed protection, and nature-based tourism, is receiving attention as a tool for promoting sustainable forest management. Expansion of these markets may remain slow and depends on government intervention ( (Katila and Puustjärvi, 2004 ) ). Nevertheless, development of these markets and behaviour of forest owners may influence roundwood markets and availability of wood for conventional uses, thus potentially limiting substitution possibilities.
Global wood harvest is about 3 billion m3 and has been rather stable in the last 15 years ( FAO, 2006a [NPR] ). Undoubtedly, the amount of wood removed is higher, as illegally wood removal is not recorded. About 60% of removals are industrial roundwood; the rest is wood fuel (including fuelwood and charcoal). The most wood removal in Africa and substantial proportions in Asia and South America are non-commercial wood fuels. Recently, commercial biomass for bioenergy received a boost because of the high oil prices and the government policies initiated to promote renewable energy sources.
Although accounting for only 5% of global forest cover, forest plantations were estimated in 2000 to supply about 35% of global roundwood harvest and this percentage is expected to increase ( FAO, 2006a [NPR] ). Thus, there is a trend towards concentrating the harvest on a smaller forest area. Meeting society’s needs for timber through intensive management of a smaller forest area creates opportunities for enhanced forest protection and conservation in other areas, thus contributing to climate change mitigation. With rather stable harvested volumes, the manufacture of forest products has increased as a result of improved processing efficiency. Consumption of forest products is increasing globally, particularly in Asia.
Mitigation measures will occur against the background of ongoing change in greenhouse gas emissions and removals. Understanding current trends is critical for evaluation of additional effects from mitigation measures. Moreover, the potential for mitigation depends on the legacy of past and present patterns of change in land-use and associated emissions and removals. The contribution of the forest sector to greenhouse gas emissions and removals from the atmosphere remained the subject of active research, which produced an extensive body of literature ( Table 9.2 and IPCC, 2007a [NPR, 2007] : Chapter 7 and 10).
Globally during the 1990 s, deforestation in the tropics and forest regrowth in the temperate zone and parts of the boreal zone were the major factors responsible for emissions and removals, respectively ( Table 9.2 ; Figure 9.2 ). However, the extent to which carbon loss due to tropical deforestation is offset by expanding forest areas and accumulating woody biomass in the boreal and temperate zones is the area of disagreement between land observations and estimates by top-down models. The top-down methods based on inversion of atmospheric transport models estimate the net terrestrial carbon sink for the 1990 s, which is the balance of sinks in northern latitudes and source in tropics ( Gurney et al., 2002 [JoC, MoS] ). The latest estimates are consistent with the increase found in the terrestrial carbon sink in the 1990 s over the 1980 s.
Denman et al. 2007 [NPR, SRC, 2007] ) reports the latest estimates for gross residual terrestrial sink for the 1990 s at 9,500 MtCO2/yr, while their estimate for emissions from deforestation amounts to 5,800 MtCO2/yr. The residual sink estimate is significantly higher than any land-based global sink estimate and in the upper range of estimates produced by inversion of atmospheric transport models ( Table 9.2 ). It includes the sum of biases in estimates of other global fluxes (fossil fuel burning, cement production, ocean uptake, and land-use change) and the flux in terrestrial ecosystems that are not undergoing change in land use.
Improved spatial resolution allowed separate estimates of the land-atmosphere carbon flux for some continents ( Table 9.2 ). These estimates generally suggest greater sink or smaller source than the bottom-up estimates based on analysis of forest inventories and remote sensing of change in land-cover ( (Houghton, 2005 ) ). While the estimates of forest expansion and regrowth in the temperate and boreal zones appear relatively well constrained by available data and consistent across published results, the rates of tropical deforestation are uncertain and hotly debated ( Table 9.2 ( Fearnside and Laurance, 2004 ) ). Studies based on remote sensing of forest cover report lower rates than UN-ECE/FAO ( 2000 ) and lower carbon emissions carbon ( Achard et al., 2004 [JoC, MoS, SRC] ).
Recent analyses highlight the important role of other carbon flows. These flows were largely overlooked by earlier research and include carbon export through river systems ( Raymond and Cole, 2003 [JoC] ), volcanic activity and other geological processes ( Richey et al., 2002 [JoC] ), transfers of material in and out of products pool ( Pacala et al., 2001 [JoC, MoS] ), and uptake in freshwater ecosystems ( Janssens et al., 2003 [JoC, SRC] ).
Attribution of estimated carbon sink in forests to the short- and long-term effects of the historic land-use change and shifting natural disturbance patterns on one hand, and to the effects of N and CO2 fertilization and climate change on the other, remains problematic ( Houghton, 2003b [MoS] ). For the USA, for example, the fraction of carbon sink attributable to changes in land-use and land management might be as high as 98% ( Caspersen et al., 2000 [JoC] ), or as low as 40% ( Schimel et al., 2001 [JoC, SRC] ). Forest expansion and regrowth and associated carbon sinks were reported in many regions ( Table 9.2 ; Figure 9.2 ). The expanding tree cover in South Western USA is attributed to the long-term effects of fire control but the gain in carbon storage was smaller than previously thought. The lack of consensus on factors that control the carbon balance is an obstacle to development of effective mitigations strategies.
Large year-to-year and decade scale variation of regional carbon sinks ( (Rodenbeck et al., 2003 ) ) make it difficult to define distinct trends. The variation reflects the effects of climatic variability, both as a direct impact on vegetation and through the effects of wild fires and other natural disturbances. There are indications that higher temperatures in boreal regions will increase fire frequency; possible drying of the Amazon basin would increase fire frequency there as well ( Cox et al., 2004 [MoS] ). Global emissions from fires in the 1997 /98 El Nino year are estimated at 7,700 MtCO2/yr, 90% from tropics ( Werf et al., 2004 [JoC] ).
The picture emerging from Table 9.2 is complex because available estimates differ in the land-use types included and in the use of gross fluxes versus net carbon balance, among other variables. This makes it impossible to set a widely accepted baseline for the forestry sector globally. Thus, we had to rely on the baselines used in each regional study separately ( Section 220.127.116.11 ), or used in each global study ( Section 18.104.22.168 ). However, this approach creates large uncertainty in assessing the overall mitigation potential in the forest sector. Baseline CO2 emissions from land-use change and forestry in 2030 are the same as or slightly lower than in 2000 (see Chapter 3 , Figure 3.10 ).
|Regions||Annual carbon flux based on international statistics||Annual carbon flux during 1990s|
|UN-ECE, 2000||Based on inversion of atmospheric transport models||Based on land observations|
|OECD North America||1,833 ± 2,2009||0 ÷ 1,1005|
|Europe||316||495 ± 7526||0 ± 7331|
|Countries in Transition||1,726||3,777 ± 3,4472||1,100 ± 2,9339|
|1,181 ÷ -1,5887|
|Separately: Russia||1,572||4,767 ± 2,9339||1,907± 4698|
|Northern Africa||623 ± 3,5932|
|Sub-Saharan Africa||-576 ±2353|
|-440 ± 1104|
|-1,283 ± 7331|
|Caribbean, Central and South America||-2,310||-1,617 ± 9723|
|-1,577 ± 7334|
|-2,750 ± 1,1001|
|Separately: Brazil||± 73312|
|Developing countries of South and East Asia and Middle East||-2,493 ± 2,7132||-3,997 ± 1,8331|
|-1,734 ± 5503|
|-1,283 ± 5504|
|Separately: China||2,273 ± 2,4202||- 110 ± 7331|
|128 ± 9513|
|Global total||4,767 ± 5,5009||-7,993 ± 2,9331|
|2,567 ± 2,93310||-3,300 ÷ 7,7005|
|Annex I (excluding Russia)||130019|
In this section, a conceptual framework for the assessment of mitigation options is introduced and specific options are briefly described. Literature results are summarized and compared for regional bottom-up approaches, global forest sector models, and global top-down integrated model approaches. The assessment is limited to CO2 balances and economic costs of the various mitigation options. Broader issues including biodiversity, sustainable development, and interactions with adaptation strategies are discussed in subsequent sections.
Terrestrial carbon dynamics are characterized by long periods of small rates of carbon uptake, interrupted by short periods of rapid and large carbon releases during disturbances or harvest. Depending on the stage of stand  development, individual stands are either carbon sources or carbon sinks (1m3 of wood stores ~ 0.92 tCO2)  . For most immature and mature stages of stand development, stands are carbon sinks. At very old ages, ecosystem carbon will either decrease or continue to increase slowly with accumulations mostly in dead organic matter and soil carbon pools. In the years following major disturbances, the losses from decay of residual dead organic matter exceed the carbon uptake by regrowth. While individual stands in a forest may be either sources or sinks, the forest carbon balance is determined by the sum of the net balance of all stands. The theoretical maximum carbon storage (saturation) in a forested landscape is attained when all stands are in old-growth state, but this rarely occurs as natural or human disturbances maintain stands of various ages within the forest.
The design of a forest sector mitigation portfolio should consider the trade-offs between increasing forest ecosystem carbon stocks and increasing the sustainable rate of harvest and transfer of carbon to meet human needs ( Figure 9.3 ). The selection of forest sector mitigation strategies should minimize net GHG emissions throughout the forest sector and other sectors affected by these mitigation activities. For example, stopping all forest harvest would increase forest carbon stocks, but would reduce the amount of timber and fibre available to meet societal needs. Other energy-intensive materials, such as concrete, aluminium, steel, and plastics, would be required to replace wood products, resulting in higher GHG emissions ( Gustavsson et al., 2006 [Ambiguous] ). Afforestation may affect the net GHG balance in other sectors, if for example, forest expansion reduces agricultural land area and leads to farming practices with higher emissions (e.g., more fertilizer use), conversion of land for cropland expansion elsewhere, or increased imports of agricultural products ( McCarl and Schneider, 2001 [JoC, ARC] ). The choice of system boundaries and time horizons affects the ranking of mitigation activities ( Figure 9.3 ).
Forest mitigation strategies should be assessed within the framework of sustainable forest management, and with consideration of the climate impacts of changes to other processes such as albedo and the hydrological cycle ( Marland et al., 2003 [JoC, SRC] ). At present, however, few studies provide such comprehensive assessment.
For the purpose of this discussion, the options available to reduce emissions by sources and/or to increase removals by sinks in the forest sector are grouped into four general categories:
Each mitigation activity has a characteristic time sequence of actions, carbon benefits and costs ( Figure 9.4 ). Relative to a baseline, the largest short-term gains are always achieved through mitigation activities aimed at emission avoidance (e.g., reduced deforestation or degradation, fire protection, and slash burning). But once an emission has been avoided, carbon stocks on that forest will merely be maintained or increased slightly. In contrast, the benefits from afforestation accumulate over years to decades but require up-front action and expenses. Most forest management activities aimed at enhancing sinks require up-front investments. The duration and magnitude of their carbon benefits differ by region, type of action and initial condition of the forest. In the long term, sustainable forest management strategy aimed at maintaining or increasing forest carbon stocks, while producing an annual yield of timber, fibre, or energy from the forest, will generate the largest sustained mitigation benefit.
Reduction in fossil fuel use in forest management activities, forest nursery operations, transportation and industrial production provides additional opportunities similar to those in other sectors, but are not discussed here (e.g., see Chapter 5 , Transportation). The options available in agro-forestry systems are conceptually similar to those in other parts of the forest sector and in the agricultural sector (e.g., non-CO2 GHG emission management). Mitigation using urban forestry includes increasing the carbon density in settlements, but indirect effects must also be evaluated, such as reducing heating and cooling energy use in houses and office buildings, and changing the albedo of paved parking lots and roads.
Each of the mitigation activities is briefly described. The development of a portfolio of forest mitigation activities requires
an understanding of the magnitude and temporal dynamics of the carbon benefits and the associated costs.
Deforestation - human-induced conversion of forest to non-forest land uses - is typically associated with large immediate reductions in forest carbon stock, through land clearing. Forest degradation - reduction in forest biomass through non-sustainable harvest or land-use practices - can also result in substantial reductions of forest carbon stocks from selective logging, fire and other anthropogenic disturbances, and fuelwood collection ( Asner et al., 2005 [JoC] ).
In some circumstances, deforestation and degradation can be delayed or reduced through complete protection of forests ( Soares-Filho et al., 2006 [JoC, MoS] ), sustainable forest management policies and practices, or by providing economic returns from non-timber forest products and forest uses not involving tree removal (e.g., tourism). Protecting forest from all harvest typically results in maintained or increased forest carbon stocks, but also reduces the wood and land supply to meet other societal needs.
Reduced deforestation and degradation is the forest mitigation option with the largest and most immediate carbon stock impact in the short term per ha and per year globally (see Section 9.2 and global mitigation assessments below), because large carbon stocks (about 350-900 tCO2/ha) are not emitted when deforestation is prevented. The mitigation costs of reduced deforestation depend on the cause of deforestation (timber or fuelwood extraction, conversion to agriculture, settlement, or infrastructure), the associated returns from the non-forest land use, the returns from potential alternative forest uses, and on any compensation paid to the individual or institutional landowner to change land-use practices. These costs vary by country and region ( Sathaye et al., 2007 [Ambiguous] ), as discussed below.
Afforestation and reforestation are the direct human-induced conversion of non-forest to forest land through planting, seeding, and/or the human-induced promotion of natural seed sources. The two terms are distinguished by how long the non-forest condition has prevailed. For the remainder of this chapter, afforestation is used to imply either afforestation or reforestation. To date, carbon sequestration has rarely been the primary driver of afforestation, but future changes in carbon valuation could result in large increases in the rates of afforestation ( US EPA, 2005 [NPR] ).
Afforestation typically leads to increases in biomass and dead organic matter carbon pools, and to a lesser extent, in soil carbon pools, whose small, slow increases are often hard to detect within the uncertainty ranges ( Paul et al., 2003 [MoS] ). Biomass clearing and site preparation prior to afforestation may lead to short-term carbon losses on that site. On sites with low initial soil carbon stocks (e.g., after prolonged cultivation), afforestation can yield considerable soil carbon accumulation rates (e.g., ( Post and Kwon 2000 ) ) report rates of 1 to 1.5 t CO2/yr). Conversely, on sites with high initial soil carbon stocks, (e.g., some grassland ecosystems) soil carbon stocks can decline following afforestation (e.g., Tate et al. 2005 [MoS] ) report that in the whole of New Zealand soil carbon losses amount up to 2.2 MtCO2/yr after afforestation). Once harvesting of afforested land commences, forest biomass carbon is transferred into wood products that store carbon for years to many decades. Accumulation of carbon in biomass after afforestation varies greatly by tree species and site, and ranges globally between 1 and 35 t CO2/ha.yr ( Richards and Stokes, 2004 [JoC] ).
Afforestation costs vary by land type and region and are affected by the costs of available land, site preparation, and labour. The cost of forest mitigation projects rises significantly when opportunity costs of land are taken into account (VanKooten et al., 2004 ). A major economic constraint to afforestation is the high initial investment to establish new stands coupled with the several-decade delay until afforested areas generate revenue. The non-carbon benefits of afforestation, such as reduction in erosion or non-consumptive use of forests, however, can more than off-set afforestation cost ( Richards and Stokes, 2004 [JoC] ).
Forest management activities to increase stand-level forest carbon stocks include harvest systems that maintain partial forest cover, minimize losses of dead organic matter (including slash) or soil carbon by reducing soil erosion, and by avoiding slash burning and other high-emission activities. Planting after harvest or natural disturbances accelerates tree growth and reduces carbon losses relative to natural regeneration. Economic considerations are typically the main constraint, because retaining additional carbon on site delays revenues from harvest. The potential benefits of carbon sequestration can be diminished where increased use of fertilizer causes greater N2O emissions. Drainage of forest soils, and specifically of peatlands, may lead to substantial carbon loss due to enhanced respiration ( (Ikkonen et al., 2001 ) ). Moderate drainage, however, can lead to increased peat carbon accumulation ( Minkkinen et al., 2002 [MoS] ).
Landscape-level carbon stock changes are the sum of stand-level changes, and the impacts of forest management on carbon stocks ultimately need to be evaluated at landscape level. Increasing harvest rotation lengths will increase some carbon pools (e.g., tree boles) and decrease others (e.g., harvested wood products ( Kurz et al., 1998 [SRC] ).
Wood products derived from sustainably managed forests address the issue of saturation of forest carbon stocks. The annual harvest can be set equal to or below the annual forest increment, thus allowing forest carbon stocks to be maintained or to increase while providing an annual carbon flow to meet society’s needs of fibre, timber and energy. The duration of carbon storage in wood products ranges from days (biofuels) to centuries (e.g., houses and furniture). Large accumulations of wood products have occurred in landfills ( (Micales and Skog, 1997 ) ). When used to displace fossil fuels, woodfuels can provide sustained carbon benefits, and constitute a large mitigation option (see Box 9.2).
Wood products can displace more fossil-fuel intensive construction materials such as concrete, steel, aluminium, and plastics, which can result in significant emission reductions ( (Petersen and Solberg, 2002 ) ). Research from Sweden and Finland suggests that constructing apartment buildings with wooden frames instead of concrete frames reduces lifecycle net carbon emissions by 110 to 470 kg CO2 per square metre of floor area ( (Gustavsson and Sathre, 2006 ) ). The mitigation benefit is greater if wood is first used to replace concrete building material and then after disposal, as biofuel.
For quantification of the economic potential of future mitigation by forests, three approaches are presented in current literature. These are: a) regional bottom-up assessments per country or continent; b) global forest sector models; and c) global multi-sectoral models. An overview of studies for these approaches is presented in Section 9.4.3 . The final integrated global conclusion and regional comparison is given in Section 9.4.4 . Supply of forest biomass for bioenergy is given in Box 9.2 and incorporated in Section 22.214.171.124 , within the energy sector’s mitigation potential. For comments on the baselines, see Section 9.3 .
Regional assessments comprise a variety of model results. On the one hand, these assessments are able to take into account the detailed regional specific constraints (in terms of ecological constraints, but also in terms of land owner behaviour and institutional frame).On the other hand, they also vary in assumptions, type of potential addressed, options taken into account, econometrics applied (if any), and the adoption of baselines. Thus, these assessments may have strengths, but when comparing and summing up, they have weaknesses as well. Some of these assessments, by taking into account institutional barriers, are close to a market potential.
The available studies about mitigation options differ widely in basic assumptions regarding carbon accounting, costs, land areas, baselines, and other major parameters. The type of mitigation options considered and the time frame of the study affect the total mitigation potential estimated for the tropics. A thorough comparative analysis is, therefore, very difficult. More detailed estimates of economic or market potential for mitigation options by region or country are needed to enable policy makers to make realistic estimates of mitigation potential under various policy, carbon price, and mitigation program eligibility rule scenarios. Examples to build on include Benitez-Ponce et al. 2007 [SRC, 2007] and Waterloo et al. 2003 [NPR] ), highlighting the large potential by avoiding deforestation and enhancing afforestation and reforestation, including bioenergy.
Assumptions of future deforestation rates are key factors in estimates of GHG emissions from forest lands and of mitigation benefits, and vary significantly across studies. In all the studies, however, future deforestation is estimated to remain high in the tropics in the short and medium term. Sathaye et al. 2007 [Ambiguous] ) estimate that deforestation rates continue in all regions, particularly at high rates in Africa and South America, for a total of just under 600 million ha lost cumulatively by 2050 . Using a spatial-explicit model coupled with demographic and economic databases, Soares-Filo et al. ( 2006 ) predict that, under a business-as-usual scenario, by 2050, projected deforestation trends will eliminate 40% of the current 540 million ha of Amazon forests, releasing approximately 117,000 ± 30,000 MtCO2 of carbon to the atmosphere ( Box 9.1 ).
Reducing deforestation is, thus, a high-priority mitigation option within tropical regions. In addition to the significant carbon gains, substantive environmental and other benefits could be obtained from this option. Successfully implementing mitigation activities to counteract the accelerated loss of tropical forests requires understanding the causes for deforestation, which are multiple and locally based; few generalizations are possible ( Chomitz et al., 2006 [NPR] ).
Recent studies have been conducted at the national, regional, and global scale to estimate the mitigation potential (areas, carbon benefits and costs) of reducing tropical deforestation. In a short-term context ( 2008 - 2012 Jung 2005 [NPR] ) estimates that 93% of the total mitigation potential in the tropics corresponds to avoided deforestation. For the Amazon basin, Soares- Filo et al. ( 2006 ) estimate that by 2050 the cumulative avoided deforestation potential for this region reaches 62,000 MtCO2 under a “governance” scenario (see Box 9.1 ).
An empirically based, policy-sensitive simulation model of deforestation for the Pan-Amazon basin has been developed ( Soares-Filho et al., 2006 [JoC, MoS] ) ( Figure 9.7 ). Model output for the worst-case scenario (business-as-usual) shows that, by 2050, projected deforestation trends will eliminate 40% of the current 5.4 million km2 of Amazon forests, releasing approximately 117,000 MtCO2 cumulatively by 2050 . Conversely, under the best-case governance scenario, 4.5 million km2 of forest would remain in 2050, which is 83% of the current extent or only 17% deforested, reducing cumulative carbon emissions by 2050 to only 55,000 MtCO2. Current experiments in forest conservation on private properties, markets for ecosystem services, and agro-ecological zoning must be refined and implemented to achieve comprehensive conservation. Part of the financial resources needed for these conservation initiatives could come in the form of carbon credits resulting from the avoidance of 62,000 MtCO2 emissions over 50 years.
Looking at the long-term, ( Sohngen and Sedjo, 2006 [NPR, SRC] ) estimate that for 27.2 US$/tCO2, deforestation could potentially be virtually eliminated. Over 50 years, this could mean a net cumulative gain of 278,000 MtCO2 relative to the baseline and 422 million additional hectares in forests. For lower prices of 1.36 US$/tCO2, only about 18,000 MtCO2 additional could be sequestered over 50 years. The largest gains in carbon would occur in Southeast Asia, which gains nearly 109,000 MtCO2 for 27.2 US$/tCO2, followed by South America, Africa, and Central America, which would gain 80,000, 70,000, and 22,000 MtCO2 for 27.2 US$/tCO2, respectively ( Figure 9.5 ).
In a study of eight tropical countries covering half of the total forested area, Grieg-Gran 2004 [NPR] ) present a best estimate of total costs of avoided deforestation in the form of the net present value of returns from land uses that are prevented, at 5 billion US$ per year. These figures represent costs of 483 US$ to 1050 US$/ha.
Afforestation and reforestation
The assumed land availability for afforestation options depends on the price of carbon and how that competes with existing or other land-use financial returns, barriers to changing land uses, land tenure patterns and legal status, commodity price support, and other social and policy factors.
Cost estimates for carbon sequestration projects for different regions compiled by ( Cacho et al., 2003 ) ) and by Richards and Stokes 2004 [JoC] ) show a wide range. The cost is in the range of 0.5 US$ to 7 US$/tCO2 for forestry projects in developing countries, compared to 1.4 US$ to 22 US$/tCO2 for forestry projects in industrialized countries. In the short-term ( 2008 - 2012 ), an estimate of economic potential area available for afforestation/ reforestation under the Clean Development Mechanism (CDM) is estimated to be 5.3 million ha in Africa, Asia and Latin America together, with Asia accounting for 4.4 million ha ( Waterloo et al., 2003 [NPR] ).
Summing the measures, the cumulative carbon mitigation benefits ( Figure 9.6 ) by 2050 for a scenario of 2.7 US$/tCO2 + 5% annual carbon price increment for one model are estimated to be 91,400 MtCO2; 59% of it coming from avoided deforestation. These estimates increase for a higher price scenario of 5.4 US$/tCO2 + 3%/yr annual carbon price into 104,800 MtCO2), where 69% of total mitigation comes from avoiding deforestation ( Sathaye et al., 2007 [Ambiguous] ). During the period 2000 - 2050, avoided deforestation in South America and Asia dominate by accounting for 49% and 21%, respectively, of the total mitigation potential. When afforestation is considered, Asia dominates. The mitigation potential of the continents Asia, Africa and Latin America dominates the global total mitigation potential for the period up to 2050 and 2100, respectively ( Figure 9.6 ).
In conclusion, the studies report a large variety for mitigation potential in the tropics. All studies indicate that this part of the world has the largest mitigation potential in the forestry sector. For the tropics, the mitigation estimates for lower price ranges (<20 US$/tCO2) are around 1100 MtCO2/yr in 2040, about half of this potential is located in Central and South America ( Sathaye et al., 2007 [Ambiguous] ; Soares Filho et al., 2006 [NotFound] ; Sohngen and Sedjo, 2006 [NPR, SRC] ). For each of the regions Africa and Southeast Asia, this mitigation potential is estimated at 300 MtCO2/yr in 2040 . In the high range of price scenarios (< 100 US$/tCO2), the mitigation estimates are in the range of 3000 to 4000MtCO2/yr in 2040 . In the summary overviews in Section 9.4.4 , an average estimate of 3500 is used, with the same division over regions: 875, 1750 and 875 for Africa, Latin and South America, and Southeast Asia, respectively. The global economic potential for the tropics ranges from 1100 to 3500 MtCO2/yr in 2040 ( Table 9.6 ).
OECD North America
Figure 9.8 shows the technical potential of management actions aimed at modifying the net carbon balance in Canadian forests ( Chen et al., 2000 [MoS, SRC] ). Of the four scenarios examined, the potential was largest in the scenario aimed at reducing regeneration delays by reforesting after natural disturbances. The second largest estimate was obtained with annual, large-scale (125 million ha) low-intensity (5 kg N/ha/yr) nitrogen fertilization programmes. Neither of these scenarios is realistic,
however, but can be seen as indications of the type of measures and impact on carbon balance (as described by Chen et al., 2000 [MoS, SRC] ). Chen’s measures sum up to a technical potential of 570 MtCO2/yr. Based on the assumption that the economic potential is about 10% of technical potential (see Section 126.96.36.199 . for carbon prices 20 US$/tCO2), the economic potential can be “guesstimated” at around 50-70 MtCO2/yr ( Table 9.6 ).
Other studies have explored the potential of large-scale afforestation in Canada. Mc Kenney et al. ( 2004 ) project that at a carbon price of 25 US$/tCO2, 7.5 million ha of agricultural land would become economically attractive for poplar plantations. Economic constraints are contributing to the declining trend in afforestation rates in Canada from about 10,000 ha/yr in 1990 to 4,000 ha/yr in 2002 ( White and Kurz, 2005 [MoS, SRC] ).
For the USA, Richards and Stokes 2004 [JoC] ) reviewed eight national estimates of forest mitigation and found that carbon prices ranging from 1 to 41 US$/tCO2 generated an economic mitigation potential of 47-2,340 MtCO2/yr from afforestation, 404 MtCO2 from forest management, and 551-2,753 MtCO2/yr from total forest carbon. Sohngen and Mendelsohn 2003 [MoS, SRC] ) found that a carbon programme with prices rising from 2 US$/tCO2 to 51 US$/tCO2 during this century could induce sequestration of 122 to 306 MtCO2/yr total carbon sequestration, annualized over a 100-year time frame.
US EPA 2005 [NPR] ) present that, at 15 US$/tCO2, the mitigation potential of afforestation and forest management (annualized) would amount to 356 MtCO2/yr over a 100-year time frame. At 30 US$/tCO2, this analysis would generate 749 MtCO2 annualized over 100 years. At higher prices and in the long term, the potential was mainly determined by biofuels. With the mitigation potential given above for Canada, the OECD North America sums to a range of 400 to 820 MtCO2/yr in 2040 ( Table 9.6 ).
Most assessments shown ( Figure 9.9 ) are of the carbon balance of the forest sector of Europe’s managed forest as a whole  . Additional effects of measures were studied by ( Cannell 2003 ) Benitez-Ponce et al. 2007 [SRC, 2007] EEA 2005 [NPR] and Eggers et al. 2007 [NPR, ARC, 2007] Karjalainen et al, 2003 [SRC] ) present a projection of the full sector carbon balance ( Figure 9.9 Eggers et al. 2007 [NPR, ARC, 2007] ) presents the European forest sector carbon sink under two global SRES scenarios, and a maximum difference between scenarios of 197 MtCO2/yr in 2040 . Therefore, an additionally achievable sink of 90 to 180 MtCO2/yr was estimated ( Table 9.6 ). Economic analyses were not only done; country studies were done, for example, ( Hoen and Solberg 1994 ) ) for Norway. New European scale economic analyses may be available from the INSEA  project, MEACAP project  , and Carbo Europe  .
Issues in European forestry where mitigation options can be found include: afforestation of abandoned agricultural lands; bioenergy from complementary fellings; and forest management practices to address carbon saturation in older forests. Furthermore, management of small now under-managed woodlands represent a potential ( Viner et al., 2006 [NPR] ) and also in combination with adaptation measures in connecting the fragmented nature reserves ( Schröter et al., 2005 [JoC, ARC] ).
The forests of the Russian Federation include large areas of primary (mostly boreal) forests. Most estimates indicate that the Russian forests are neither a large sink nor a large source. Natural disturbances (fire) play a major role in the carbon balance with emissions up to 1,600 MtCO2/yr ( Zhang et al., 2003 [Ambiguous] ). Large uncertainty surrounds the estimates for the current carbon balance ( ((Shvidenko and Nilsson et al., 2003 ) ). For the decade 1990 - 2000, the range of carbon sink values for Russia is 350-750 MtCO2/yr ( (Nilsson et al., 2003; ) ( Izrael et al., 2002 ) ). A recent analysis estimated the net sink in Russia at 146-439 MtCO2/yr at present ( Sohngen et al., 2005 [NPR, SRC] ). They projected this baseline to be about 257 MtCO2 per year in 2010, declining to a net source by 2030 as younger forests mature and are harvested. They estimated the economic potential in Russia of afforestation and reforestation at 73-124 MtCO2/yr on average over an 80-year period, for a carbon price of 1.9-3.55 US$/tCO2, and 308-476 MtCO2/yr at prices of more than 27 US$/tCO2 ( Figure 9.10 ). Based on these estimates, the estimated economic mitigation potential would be between 150 and 300 MtCO2/yr in the year 2040 ( Table 9.6 ).
Richards and Brack 2004 [NotFound] ) used estimates of establishment rates for hardwood (short and long rotation) and softwood plantations to model a carbon account for Australia’s post- 1990 plantation estate. The annual sequestration rate in forests and wood products together is estimated to reach 20 MtCO2/yr in 2020 .
New Zealand reached a peak in new planting of around 98,000 ha in 1994 and estimates of stock changes largely depend on afforestation rates (MfE, 2002 ). If a new planting was maintained at 40,000 ha/yr, the stock increase in forests established since 1990 (117 MtCO2 cumulative since 1990 ) is estimated to offset all increases in emissions in New Zealand since 1990 . The total stock increase in all forests would offset all emissions increases until 2020 .
However, the current new planting rate has declined to 6,000 ha and conversion of 7,000 ha of plantations to pasture has led to net deforestation in the year to March 2005 ( MAF, 2006 [NPR] ). As a result, the total removal units anticipated to be available during the first commitment period dropped to 56 MtCO2 in 2005 (MfE, 2005 ( Trotter et al. 2005 ) ) estimate New Zealand has approximately 1.45 million ha of marginal pastoral land suitable for afforestation. If all of this area was established, total sequestration could range from 10 to 42 MtCO2/yr. This would lead to a removal of approximately 44 to 170 MtCO2 cumulative by 2010 at 13 US$/tCO2.
In Japan, 67% of the land is covered with forests including semi-natural broad-leaved forests and planted coniferous forests mostly. The sequestration potential is estimated in the range of 35 to 70 MtCO2/yr ( Matsumoto et al., 2002 [SRC] ; Fang et al., 2005 [JoC] ), and planted forests account for more than 60% of the carbon sequestration. These assessments show that there is little potential for afforestation and reforestation, while forest management and practices for planted forests including thinning and regeneration are necessary to maintain carbon sequestration and to curb saturation. In addition, there seems to be large potential for bioenergy as a mitigation option.
These three countries for the region lead to an estimate of potential in the range of 85 to 255 MtCO2/yr in 2040 ( Table 9.6 ).
Non-annex I East Asia
East Asia to a large extent formed by China, Korea, and Mongolia has a range of forest covers from a relatively small area of moist tropical forest to large extents of temperate forest and steppe-like shrubland. Country assessments for the forest sector all project a sink ranging from 75 to 400 MtCO2/yr ( (Zhang and Xu, 2003 ) ). Given the large areas and the fast economic development (and thus demand for wood products resulting in increased planting), the additional potential in the region would be in the high range of the country assessments at 150 to 400 MtCO2/yr ( Table 9.6 ). Issues in forestry with which the carbon sequestration goal can be combined sustainably are: reducing degradation of tropical and dry woodlands; halting desertification of the steppes (see Chapter 8 ); afforestation; and bioenergy from complementary fellings.
Currently, no integrated assessment ( Section 188.8.131.52 ) and climate stabilization economic models ( Section 3.3.5 ) have fully integrated a land use sector with other sectors in the models. Researchers have taken several approaches, however, to account for carbon sequestration in integrated assessment models, either by iterating with the land sector models (e.g., Sohngen and Mendelsohn, 2003 [MoS, SRC] ), or implementing mitigation response curves generated by the sectoral model ( Jakeman and Fisher, 2006 [NPR, ARC] ). The sectoral model results described here use exogenous carbon price paths to simulate effects of different climate policies and assumptions. The starting point and rate of increase are determined by factors such as the aggressiveness of the abatement policy, abatement option and cost assumptions, and the social discount rate ( Sohngen and Sedjo, 2006 [NPR, SRC] ).
Since TAR, several new global assessments of forest mitigation potential have been produced. These include Benitez-Ponce et al, 2004 [NPR, SRC] ; 2007 Waterloo et al. 2003 [NPR] ) with a constraints study, Sathaye et al. 2007 [Ambiguous] Strengers et al. 2007 [NPR, SRC, 2007] Vuuren et al. 2007 [JoC, SRC, 2007] and Riahi et al. 2006 [NPR, MoS, ARC] ). Global estimates are provided that are consistent in methodology across countries and regions, and in terms of measures included. Furthermore, they provide a picture in which the forestry sector is one option that is part of a multi sectoral climate policy and its measures. Thus, these assessments provide insight into whether land-based mitigation is a cost-efficient measure in comparison to other mitigation efforts. Some of these models use a grid-based global land-use model and provide insight into where these models allocate the required afforestation ( Figure 9.11 ).
The IMAGE model ( Strengers et al., 2007 [NPR, SRC, 2007] ) allocates bio-energy plantations and carbon plantations mostly in the fringes of the large forest biomes, and in Eastern Europe. The Waterloo study only looked at tropical countries, but found by far the largest potential in China and Brazil. Several models report at the regional level, and project strong avoided deforestation in Africa, the Amazon, and to a lesser extent in Southeast Asia (where land opportunity costs in the timber market are relatively high). Benitez-Ponce 2004 [NPR, SRC] ) maps geographic distribution of afforestation, adjusted by country risk estimates, under a 50 US$/t carbon price. Afforestation activity is clustered in bands in South-Eastern USA, Southeast Brazil and Northern South America, West Africa, north of Botswana and East Africa, the steppe zone grasslands from Ukraine through European Russia, North- Eastern China, and parts of India, Southeast Asia, and Northern Australia. Hence, forest mitigation is likely to be patchy, but predictable using an overlay of land characteristics, land rental rates, and opportunity costs, risks, and infrastructure capacity.
Several models produced roughly comparable assessments for a set of constant and rising carbon price scenarios in the EMF 21 modelling exercise, from 1.4 US$/tCO2 in 2010 and, rising by 5% per year to 2100, to a 27 US$ constant CO2 price, to 20 US$/tCO2 rising by 1.4 US$/yr though 2050 then capped. This exercise allowed more direct comparison of modelling assumptions than usual. Caveats include: (1) models have varying assumptions about deforestation rates over time, land area in forest in 2000 and beyond, and land available for mitigation; and (2) models have different drivers of land use change (e.g., population and GDP growth for IMAGE, versus land rental rates and timber market demand for GTM).
Global models provide broad trends, but less detail than national or project analyses. Generally global models do not address implementation issues such as transaction costs (likely to vary across activities, regions), barriers, and mitigation programme rules, which tend to drive mitigation potential downward toward true market potential. Political and financial risks in implementing afforestation and reforestation by country were considered by Benitez-Ponce et al. 2007 [SRC, 2007] ), for example, who found that the sequestration reduced by 59% once the risks were incorporated.
In the last few years, more insight has been gained into carbon supply curves. At a price of 5 US$/tCO2 Sathaye et al. 2007 [Ambiguous] ) project a cumulative carbon gain of 10,400 MtCO2 by 2050 ( Figure 9.12 b). The mitigation results from a combination of avoided deforestation (68%) and afforestation (32%). These results are typical in their very high fraction of mitigation from reduced deforestation. Sohngen and Sedjo 2006 [NPR, SRC] ) estimate some 80% of carbon benefits in some scenarios from land-use change (e.g., reduced deforestation and afforestation/reforestation) versus some 20% from forest management.
Benitez-Ponce et al. 2007 [SRC, 2007] ) project that at a price of 13.6 US$/tCO2, the annual sequestration from afforestation and reforestation for the first 20 years amounts to on average 510 MtCO2/yr ( Figure 9.12 a). For the first 40 years, the average annual sequestration is 805 MtCO2/yr. The single price of 13.6 US$/tCO2 used by Benitez-Ponce et al. 2005 [NPR, SRC] ) should make afforestation an attractive land-use option in many countries. It covers the range of median values for sequestration costs that Richards and Stokes 2004 [JoC] ) give of 1 US$ to 12 US$/tCO2, although VanKooten et al. ( 2004 ) present marginal cost results rising far higher. Sathaye et al. 2007 [Ambiguous] ) project the economic potential cumulative carbon gains from afforestation and avoided deforestation together (see also tropics, Section 184.108.40.206 .). In the moderate carbon price scenarios, the cumulative carbon gains by 2050 add up to 91,400 to 104,800 MtCO2.
The anticipated carbon price path over time has important implications for forest abatement potential and timing. Rising carbon prices provide an incentive for delaying forest abatement actions to later decades, when it is more profitable ( Sohngen and Sedjo, 2006 [NPR, SRC] ). Carbon price expectations influence forest investment decisions and are, therefore, an important consideration for estimating mitigation potential. Contrary, high constant carbon prices generate significant early mitigation, but the quantity may vary over time. Mitigation strategies need to take into account this temporal dimension if they seek to meet specific mitigation goals at given dates in the future ( US EPA, 2005 [NPR] ).
Some patterns emerge from the range of estimates reviewed in order to assess the ratio between economic potential and technical potential ( Sathaye et al., 2007 [Ambiguous] ;( Lewandrowski et al., 2004; ) US EPA, 2005 [NPR] ; Richards and Stokes, 2004 [JoC] ). The technical potential estimates are generally significantly larger than the economic potential. These studies are difficult to compare, since each estimate uses different assumptions by different analysts. Economic models used for these analyses can generate mitigation potential estimates in competition to other forestry or agricultural sector mitigation options. Generally, they do not specify or account for specific policies and measures and market penetration rates, so few market potential estimates are generated. Many studies do not clearly state which potentials are estimated.
The range of economic potential as a percentage of technical potential is 2% to 100% (the latter against all costs). At carbon prices less than 7 US$/tCO2, the highest estimate of economic potential is 16% of the technical potential. At carbon prices from 27 US$/tCO2 to 50 US$/tCO2, the range of economic potential is estimated to be 58% or higher of the technical potential, a much higher fraction as carbon prices rise. Table 9.3 summarizes mitigation results for four major global forest analyses for a single near-term date of 2030 : two forest sector models - GTM ( Sohngen and Sedjo, 2006 [NPR, SRC] ; and GCOMAP ( Sathaye et al., 2007 [Ambiguous] ), one recent detailed spatially resolved analysis of afforestation ( Benitez-Ponce et al., 2007 [SRC, 2007] ), and one integrated assessment model with detail for the forest sector (IMAGE 2.2, Vuuren et al., 2007 [JoC, SRC, 2007] ). These studies offer roughly comparable results, including global coverage of the forest sector, and land-use competition across at least two forest mitigation options (except Benitez-Ponce et al., 2007 [SRC, 2007] ). All but the Benitez-Ponce et al. study have been compared by the modelling teams in the EMF 21 modelling exercise (see Sections 220.127.116.11 and 3.3.5 ) as well.
These global models ( Table 9.3 ) present a large potential for climate mitigation through forestry activities. The global annual potential in 2030 is estimated at 13,775 MtCO2/yr (at carbon prices less than or equal to 100 US$/tCO2), 36% (~5000 MtCO2/yr) of which can be achieved under a price of 20 US$/tCO2. Reduced deforestation in Central and South America is the most important measure in a single region with 1,845 MtCO2/yr. The total for the region is the largest for Central and South America with an estimated total potential of 3,100 MtCO2/yr. Regions with a second largest potential, each around 2000 MtCO2, are Africa, Centrally Planned Asia, other Asia, and USA. These results project significantly higher mitigation than the regional largely bottom-up results. This is somewhat surprising, and likely, the result of the modelling structure, assumptions, and which activities are included. Additional research is required to resolve the various estimates to date using different modelling approaches of the potential magnitude of forestry mitigation of climate change.
|Region||Activity||Potential at costs equal||Fraction in cost class:||Fraction in cost class:|
|or less than|
|100 US$/tCO2 , in||1-20 US$/tCO2||20-50 US$/tCO2|
|MtCO2/yr in 2030 1)|
|Non-annex I East Asia||Afforestation||605||0.26||0.26|
|Countries in transition||Afforestation||545||0.35||0.3|
|Central and South America||Afforestation||750||0.39||0.33|
Current use of biomass from fuelwood and forest residues reaches 33 EJ (see Section 4.3.3 ). Three main categories of forest residues may be used for energy purposes: primary residues (available from additional stemwood fellings or as residues (branches) from thinning salvage after natural disturbances or final fellings); secondary residues (available from processing forest products) and tertiary residues (available after end use). Various studies have assessed the future potential supply of forest biomass ( Yamamoto et al., 2001 [MoS, ARC] ; Smeets and Faaij, 2007 [NPR, ARC, 2007] ;( Fischer and Schrattenholzer, 2001 ) ). Furthermore, some global biomass potential studies include forest residues aggregated with crop residue and waste ( Sørensen, 1999 [NPR] ). At a regional or national scale, studies are more detailed and often include economic considerations ( (Koopman, 2005; ) Bhattacharya et al., 2005 [SRC] ; Lindner et al., 2005 [NPR] ; Cuiping et al., 2004 [NotFound] ). Typical values of residue recoverability are between 25 and 50 % of the logging residues and between 33 and 80% of processing residues. Lower values are often assumed for developing regions ( Yamamoto et al., 2001 [MoS, ARC] ; Smeets and Faaij, 2007 [NPR, ARC, 2007] ). At a global level, scenario studies on the future energy mixture ( IPCC, 2000c [NPR] ; Sørensen, 1999 [NPR] ; OECD, 2006 [NPR] ) have included residues from the forestry sector in their energy supply (market potential).
The technical potential of primary biomass sources given by the different global studies is aggregated by region in Table Box 9.2. From this table, it can conclude that biomass from forestry can contribute from about a few percent to about 15% (12 to 74 EJ/yr) of current primary energy consumption. It is outside the scope of this chapter to examine all pros and cons of increased production required for biomass for bioenergy (see Section 11.9 ).
|OECD North America||3||11|
|Japan + Australia + New Zealand||1||3|
|Economies in Transition|
|Central and Eastern Europe, the Caucasus and Central Asia||2||10|
|Non-Annex I East Asia||1||5|
|Non-Annex I Other Asia||1||8|
|World low and high estimates||12||74|
|World (based on global studies) assumed economic potential||14||65|
In general, the delivery or production costs of forestry residues are expected to be at a level of 1.0 to 7.7 US$/GJ. Smeets and Faaij 2007 [NPR, ARC, 2007] ) concluded that at a global level, the economic potential of all types of biomass residues is 14 EJ/yr: at the very lower level of estimates in the table. This and the notion that the summation of the column of lower ranges of dry matter supply equals 700 million tonnes (which is assumed stemwood) is half of current global stemwood harvesting) was the reason to estimate the economic potential at 10-20% of above given numbers.
The CO2 mitigation potential can only be calculated if the actual use and the amount of use of forestry biomass supply are known. This depends on the balance of supply and demand (see bioenergy in Section 18.104.22.168 .). However, to give an indication of the order of magnitude of the figures the CO2-eq emissions avoided have been calculated from the numbers in Table 9.5 using the assumption that biomass replaces either coal (high range) or gas (low range). Based on these calculations8, the CO2-eq emissions avoided range from 420 to 4,400 MtCO2/yr for 2030 . This is about 5 to 25% of the total CO2-eq emissions that originate from electricity production in 2030, as reported in the World Energy Outlook ( OECD, 2006 [NPR] ).
Evaluating the cost-competitiveness of forestry mitigation versus other sector options in achieving climate mitigation goals requires different modelling capabilities. Global integrated assessment and climate economic models are top-down models, generally capable of dynamically representing feedbacks in the economy across sectors and regions and reallocations of inputs, as well as interactions between economic and atmospheric-ocean-terrestrial systems. These models can be used to evaluate long-term climate stabilization scenarios, like achieving a stabilization target of 450 or 650 CO2-eq by 2100 (see Section 3.3.5 ). In this framework, the competitive mitigation role of forest abatement options, such as afforestation, can be estimated as part of a dynamic portfolio of the least-cost combination of mitigation options from across all sectors of the economy, including energy, transportation, and agriculture.
To date, researchers have used various approaches to represent terrestrial carbon sequestration in integrated assessment models. These approaches include iterating with the land-sector models (e.g., Sohngen and Mendelsohn, 2003 [MoS, SRC] ), and implementing mitigation response curves generated by a sectoral model ( Jakeman and Fisher, 2006 [NPR, ARC] ). At present, all integrated assessment models include afforestation strategies, but only some consider avoided deforestation, and none explicitly model forest management mitigation options (e.g., harvest timing: Rose et al., 2007 [NPR, MoS, SRC, 2007] ). However, the top-down mitigation estimates account for economic feedbacks, as well as for some biophysical feedbacks such as climate and CO2 fertilization effects on forest growth.
The few estimates of global competitive mitigation potential of forestry in climate stabilization in 2030 are given in Table 9.4 . Some estimates represent carbon plantation gains only, while others represent net forest carbon stock changes that include plantations as well as deforestation carbon loses induced by bioenergy crops. On-going top-down land-use modelling developments should produce more refined characterization of forestry abatement alternatives and cost-effective mitigation potential in the near future. The results in Table 9.4 suggest a reasonable central estimate of about 700 million tonne CO2 in 2030 from forestry in competition with other sectors for achieving stabilization, significantly less than the regional bottom-up or global sector top-down estimates in this chapter summarized in Table 9.7 .
|Carbon price in scenario (US$/tCO2-eq)||Mitigation potential in 2030|
|MtCO2-eq/yr||Number of scenario results|
|0 - 20||40 - 970||4|
|20 - 50||604 - 790||3|
|50 - 100||nd||0|
An overview of estimates derived in the regional bottom-up estimates as given in Section 22.214.171.124 are presented in Table 9.6 . Based on indications in literature and carbon supply curves, the fraction of the mitigation potential in the cost class < 20 US$/tCO2 was estimated.
|Economic potential in 2040 (MtCO2/yr) low||Economic potential in 2040 (MtCO2/yr) high||Fraction of total (technical) potential in cost class <20 US$/tCO2|
|Caribbean, Central and South America||500||1750||0.6|
|Non Annex I East Asia||150||400||0.3|
|Non Annex I South Asia||300||875||0.6|
Assuming a linear implementation rate of the measures, the values in Table 9.4 were adjusted to 2030 values (the values required in the cross sector summation in Chapter 11 , Table 11.3 ). The 2030 values are presented in Table 9.7 against the values derived from global forest sector models, and from global integrated models for three world regions. The mitigation effect of biomass for bioenergy (see text, Box 9.2) was excluded.
The range of estimates in the literature and presented in Table 9.7 help in understanding the uncertainty surrounding forestry mitigation potential. Bottom-up estimates of mitigation generally include numerous activities in one or more regions represented in detail. Top-down global modelling of sectors and of long-term climate stabilization scenario pathways generally includes fewer, simplified forest options, but allows competition across all sectors of the economy to generate a portfolio of least-cost mitigation strategies. Comparison of top-down and bottom-up modelling estimates ( Figure 9.13 ) is difficult at present. This stems from differences in how the two approaches represent mitigation options and costs, market dynamics, and the effects of market prices on model and sectoral inputs and outputs such as labour, capital, and land. One important reason that bottom-up results yield a lower potential consistently for every region ( Figure 9.13 ) is that this type of study takes into account (to some degree) barriers to implementation. The bottom-up estimate has, therefore, characteristics of a market potential study, but the degree is unknown.
|Regional bottom-up estimate||Global forest sector models||Global integrated assessment models|
|Economies in transition||150||90||210||3,600|
The uncertainty and differences behind the studies referred to, and the lack of baselines are reasons to be rather conservative with the final estimate for the forestry mitigation potential. Therefore, mostly the bottom-up estimates are used in the final estimate. This stands apart from any preference for a certain type of study. Thus synthesizing the literature, we estimate that forestry mitigation options have the economic potential (at carbon prices up to 100 US$/tCO2) to contribute between 1270 and 4230 MtCO2/yr in 2030 (medium confidence, medium agreement). About 50% of the medium estimate can be achieved at a cost under 20 US$/tCO22 MtCO2/yr: see Figure 9.14 ). The combined effects of reduced deforestation and degradation, afforestation, forest management, agro-forestry and bioenergy have the potential to increase gradually from the present to 2030 and beyond. For comparison with other sectors in Chapter 11 , Table 11.2 , data on cost categories <0 US$/tCO2 and 20-50 US$100/tCO2 have been derived from Tables 9.3 and 9.6 , using cost information derived from regional bottom-up studies and global top- down modelling. The cost classes assessed should be seen as rough cost-class indications, as the information in the literature varies a lot. These analyses assume gradual implementation of mitigation activities starting at present.
This sink enhancement/emission avoidance will be located for 65% in the tropics (high confidence, high agreement; Figure 9.14 ); be found mainly in above-ground biomass; and for 10% achieved through bioenergy (medium confidence, medium agreement). In the short term, this potential is much smaller, with 1180 MtCO2/yr in 2010 (high confidence, medium agreement). Uncertainty from this estimate arises from the variety of studies used, the different assumptions, the different measures taken into account, and not taking into account possible leakage between continents.
These final results allow comparison with earlier IPCC estimates for forestry mitigation potential ( Figure 9.15 ). The estimates for Second Assessment Report (SAR), Third Assessment Report (TAR) and Special Report have to be seen as estimates for a technical potential, and are comparable to our Fourth Assessment Report (AR4) estimates for a carbon dioxide price < 100 US$/tCO2 (as displayed). As the bars in this figure are lined by the year to which they apply, one would expect an increasing trend towards the right-hand columns. This is not the case. Instead a large variety is displayed. There is a trend visible through the consecutive IPCC reports, and not so much through the years to which the estimate applies. When ignoring the TAR synthesis, we start with the highest estimate in SAR (just over 8000 MtCO2/yr), then follows SR LULUCF with 5500 MtCO2, and TAR with 5300. Finally, the present report follows with a conservative estimate of 3140 (including bioenergy).
Some of the mitigation potential as given in this chapter might be counteracted by adverse effects of climate change on forest ecosystems ( Fischlin et al., 2007 [NPR, 2007] ). Further, mitigation-driven actions in forestry could have positive adaptive consequences (e.g., erosion protection) or negative adaptation consequences (e.g., increase in pest and fires). Similarly, adaptation actions could have positive or negative consequences on mitigation. To avoid trade-offs, it is important to explore options to adapt to new climate circumstances at an early stage through anticipatory adaptation ( Robledo et al., 2005 [NPR] ). The limits to adaptation stem in part from the way that societies exacerbate rather than ameliorate vulnerability to climate fluctuations ( (Orlove, 2005 ) ) that can also affect mitigation potentials. There are significant opportunities for mitigation and for adapting to climate change, while enhancing the conservation of biodiversity, and achieving other environmental as well as socio-economic benefits. However, mitigation and adaptation have been considered separately in the global negotiations as well as in the literature until very recently. Now, the two concepts are seen to be linked, however to achieve synergies may be a challenge ( (Tol, 2006 ) ). In the IPCC Third Assessment Report, potential synergy and trade-off issues were not addressed. This section explores the synergy between mitigation and adaptation in the forest sector ( Ravindranath and Sathaye, 2002 [NPR, SRC] ). The potential and need for incorporating adaptation strategies and practices in mitigation projects is illustrated with a few examples.
In addition to natural factors, forest ecosystems have long been subjected to many human-induced pressures such as land-use change, over-harvesting, overgrazing by livestock, fire, and introduction of new species. Climate change constitutes an additional pressure that could change or endanger these ecosystems. The IPCC Fourth Assessment report ( Fischlin et al., 2007 [NPR, 2007] and Easterling et al., 2007 [NPR, ARC, 2007] ) has highlighted the potential impacts of climate change on forest ecosystems. New findings indicate that negative climate change impacts may be stronger than previously projected and positive impacts are being over-estimated as well as the uncertainty on predictions.
Recent literature indicates that the projected potential positive effect of climate change as well as the estimated carbon sink in mature forests may be substantially threatened by enhancing or changing the regime of disturbances in forests such as fire, pests, drought, and heat waves, affecting forestry production including timber ( Fuhrer et al., 2007 [NPR, 2007] ; Sohngen et al., 2005 [NPR, SRC] ; Ciais et al., 2005 [JoC] ).
Most model limitations persist; models do not include key ecological processes, and feedbacks. There are still inconsistencies between the models used by ecologists to estimate the effects of climate change on forest production and composition, and the models used by foresters to predict forest yield ( Easterling et al., 2007 [NPR, ARC, 2007] ). Despite the achievements and individual strengths of the selected modelling approaches, core problems of global land-use modelling have not yet been resolved. For a new generation of integrated large-scale land-use models, a transparent structure would be desirable ( Heistermann et al., 2006 [MoS] ).
Global change, including the impacts of climate change, can affect the mitigation potential of the forestry sector by either increasing (nitrogen deposition and CO2 fertilization), or decreasing (negative impacts of air pollution,) the carbon sequestration. But, recent studies suggest that the beneficial impacts of climate change are being overestimated by ignoring some of the feedbacks ( (Körner, 2004 ) ) and assumption of linear responses. Also, the negative impacts may be larger than expected ( Schroter et al., 2005 [JoC, ARC] ), with either some effects remaining incompletely understood ( Betts et al., 2004 [MoS] ) or impossible to separate one from the other.
The mitigation and adaptation trade-offs and synergies in the forestry sector are dealt with in Klein et al. 2007 [NPR, ARC, 2007] ). Many of the response strategies to address climate change, such as Global Environmental Facility (GEF) and Clean Development Mechanism (CDM), Activities under Article 3.3 and Article 3.4 and the Adaptation Fund aim at implementation of either mitigation or adaptation technologies or policies. It is necessary to promote synergy in planning and implementation of forestry mitigation and adaptation projects to derive maximum benefit to the global environment as well as local communities or economies, for example promoting adaptive forest management (McGinley & Finegan, 2003 [NotFound] ). However, recent analyses not specifically focused on the Forestry sector point out that it may be difficult to enhance synergies. This is due to the different actors involved in mitigation and adaptation, competitive use of funds, and the fact that in many cases both activities take place at different implementation levels ( (Tol, 2006 ) ). It should also be taken into account that activities to address mitigation and adaptation in the forestry sector are planned and implemented locally.
It is likely that adaptation practices will be easier to implement in forest plantations than in natural forests. Several adaptation strategies or practices can be used in the forest sector, including changes in land use choice ( Kabat et al., 2005 [JoC] ), management intensity, hardwood/softwood species mix, timber growth and harvesting patterns within and between regions, changes in rotation periods, salvaging dead timber, shifting to species more productive under the new climatic conditions, landscape planning to minimize fire and insect damage, and to provide connectivity, and adjusting to altered wood size and quality ( (Spittlehouse and Stewart, 2003 ) ). A primary aim of adaptive management is to reduce as many ancillary stresses on the forest resource as possible. Maintaining widely dispersed and viable populations of individual species minimizes the probability that localized catastrophic events will cause extinction ( Fischlin et al., 2007 [NPR, 2007] ). While regrowth of trees due to effective protection will lead to carbon sequestration, adaptive management of protected areas also leads to conservation of biodiversity and reduced vulnerability to climate change. For example, ecological corridors create opportunities for migration of flora and fauna, which facilitates adaptation to changing climate.
Adaptation practices could be incorporated synergistically in most mitigation projects in the forest sector. However, in some cases, mitigation strategies could also have adverse implications for watersheds in arid and semi-arid regions (UK FRP,Adaptation practices could be incorporated synergistically in most mitigation projects in the forest sector. However, in some cases, mitigation strategies could also have adverse implications for watersheds in arid and semi-arid regions (UK FRP,) and biodiversity ( (Caparros and Jacquemont, 2003 ) ). To achieve an optimum link between adaptation and mitigation activities, it is necessary to clearly define who does the activity, where and what are the activities for each case. Several principles can be defined ( Murdiyarso et al., 2005 [NPR] ): prioritizing mitigation activities that help to reduce pressure on natural resources, including vulnerability to climate change as a risk to be analysed in mitigation activities; and prioritizing mitigation activities that enhance local adaptive capacity, and promoting sustainable livelihoods of local populations.
Considering adaptation to climate change during the planning and implementation of CDM projects in forestry may also reduce risks, although the cost of monitoring performance may become very complex ( Murdiyarso et al., 2005 [NPR] ). Adaptation and mitigation linkages and vulnerability of mitigation options to climate change are summarized in Table 9.8 , which presents four types of mitigation actions.
|Mitigation option||Vulnerability of the mitigation option to climate change||Adaptation options||Implications for GHG emissions due to adaptation|
|A. Increasing or maintaining the forest area|
|Reducing deforestation and forest degradation||
Vulnerable to changes in rainfall, higher temperatures (native forest dieback, pest attack, fire and, droughts)
Fire and pest management.
Protected area management
Linking corridors of protected areas
No or marginal implications for GHG emissions, positive if the effect of perturbations induced by climate change can be reduced
|Afforestation / Reforestation||
Vulnerable to changes in rainfall, and higher temperatures (increase of forest fires, pests, dieback due to drought)
Species mix at different scales.
Fire and pest management.
Increase biodiversity in plantations by multi-species plantations.
Introduction of irrigation and fertilisation.
No or marginal implications for GHG emissions, positive if the effect of perturbations induced by climate change can be reduced.
May lead to increase in emissions from soils or use of machinery and fertilizer.
|B. Changing forest management: increasing carbon density at plot and landscape level|
|Forest management in plantations||Vulnerable to changes in rainfall, and higher temperatures (i.e. managed forest dieback due to pest or droughts)||
Pest and forest fire management.
Adjust rotation periods.
Species mix at different scales
Marginal implications on GHGs.
May lead to increase in emissions from soils or use of machinery or fertilizer use
|Forest management in native forest||Vulnerable to changes in rainfall, and higher temperatures (i.e. managed forest dieback due to pest, or droughts)||
Pest and fire management
Species mix at different scales
No or marginal
|C. Substitution of energy intensive materials|
Increasing substitution of fossil energy intensive products by wood products
Stocks in products not vulnerable to climate change
No implications in GHGs emissions
Bioenergy production from forestry
An intensively managed plantation from where biomass feedstock comes is vulnerable to pests, drought and fire occurrence, but the activity of substitution is not.
Suitable selection of species to cope with changing climate. Pest and fire management
No implications for GHG emissions except from fertilizer or machinery use
Reducing deforestation is the dominant mitigation option for tropical regions ( Section 9.4 ). Adaptive practices may be complex. Forest conservation is a critical strategy to promote sustainable development due to its importance for biodiversity conservation, watershed protection and promotion of livelihoods of forest-dependent communities in existing natural forest ( IPCC, 2002 [NPR] ).
Afforestation and reforestation are the dominant mitigation options in specific regions (e.g., Europe). Currently, afforestation and reforestation are included under Article 3.3 and in Articles 6 and 12 (CDM) of the Kyoto Protocol. Plantations consisting of multiple species may be an attractive adaptation option as they are more resilient, or less vulnerable, to climate change. The latter as a result of different tolerance to climate change characteristic of each plantation species, different migration abilities, and differential effectiveness of invading species ( IPCC, 2002 [NPR] ).
Agro-forestry provides an example of a set of innovative practices designed to enhance overall productivity, to increase carbon sequestration, and that can also strengthen the system’s ability to cope with adverse impacts of changing climate conditions. Agro-forestry management systems offer important opportunities creating synergies between actions undertaken for mitigation and for adaptation ( Verchot et al., 2006 [NPR] ). The area suitable for agro-forestry is estimated to be 585- 1215 Mha with a technical mitigation potential of 1.1 to 2.2 PgC in terrestrial ecosystems over the next 50 years ( (Albrecht and Kandji, 2003 ) ). Agro-forestry can also help to decrease pressure on natural forests and promote soil conservation, and provide ecological services to livestock.
Bioenergy. Bioenergy plantations are likely to be intensively managed to produce the maximum biomass per unit area. To ensure sustainable supply of biomass feedstock and to reduce vulnerability to climate change, the practices mentioned above for afforestation and reforestation projects need to be explored such as changes in rotation periods, salvage of dead timber, shift to species more productive under the new climatic conditions, mixed species forestry, mosaics of different species and ages, and fire protection measures.
Adaptation and mitigation synergy and sustainable development
The need for integration of mitigation and adaptation strategies to promote sustainable development is presented in Klein et al. 2007 [NPR, ARC, 2007] ). The analysis has shown the complementarity or synergy between many of the adaptation options and mitigation ( Dang et al., 2003 [JoC, ARC] ). Promotion of synergy between mitigation and adaptation will also advance sustainable development, since mitigation activities could contribute to reducing the vulnerability of natural ecosystems and socio-economic systems ( Ravindranath, 2007 [SRC, 2007] ). Currently, there are very few ongoing studies on the interaction between mitigation, adaptation and sustainable development ( Wilbanks, 2003 [JoC] ; Dang et al., 2003 [JoC, ARC] ). Quantification of synergy is necessary to convince the investors or policy makers ( Dang et al., 2003 [JoC, ARC] ).
The possibility of incorporating adaptation practices into mitigation projects to reduce vulnerability needs to be explored. Particularly, Kyoto Protocol activities under Article 3.3, 3.4 and 12 provide an opportunity to incorporate adaptation practices. Thus, guidelines may be necessary for promoting synergy in mitigation as well as adaptation programmes and projects of the existing UNFCCC and Kyoto Protocol mechanisms as well as emerging mechanisms. Integrating adaptation practices in such mitigation projects would maximize the utility of the investment flow and contribute to enhancing the institutional capacity to cope with risks associated with climate change ( Dang et. al., 2003 [JoC, ARC] ).
This section examines the barriers, opportunities, and implementation issues associated with policies affecting mitigation in the forestry sector. Non-climate policies, that is forest sector policies that affect net greenhouse gas emissions from forests, but that are not designed primarily to achieve climate objectives, as well as policies primarily designed to reduce net forest emissions are considered. Many factors influence the efficacy of forest policies in achieving intended impacts on forest land-use, including land tenure, institutional and regulatory capacity of governments, the financial competitiveness of forestry as a land use, and a society’s cultural relationship to forests. Some of these factors typically differ between industrialized and developing countries. For example, in comparison to developing countries, industrialized countries tend to have relatively small amounts of unallocated public lands, and relatively strong institutional and regulatory capacities. Where appropriate, policy options and their effectiveness are examined separately for industrialized and developing countries. Because integrated and non-climate policies are designed primarily to achieve objectives other than net emissions reductions, evaluations of their effectiveness focus primarily on indicators, such as maintenance of forest cover. This provides only partial insight into their potential to mitigate climate change. Under conditions with high potential for leakage, for example, such indicators may overestimate the potential for carbon benefits ( Section 9.6.3 ).
Deforestation in developing countries, the largest source of emissions from the forestry sector, has remained at high levels since 1990 ( FAO, 2005 [NPR] ). The causes of tropical deforestation are complex, varying across countries and over time in response to different social, cultural, and macroeconomic conditions ( (Geist and Lambin, 2002 ) ). Broadly, three major barriers to enacting effective policies to reduce forest loss are: (i) profitability incentives often run counter to forest conservation and sustainable forest management ( Tacconi et al., 2003 [NPR] ); (ii) many direct and indirect drivers of deforestation lie outside of the forest sector, especially in agricultural policies and markets ( Wunder, 2004 [NPR] ); and (iii) limited regulatory and institutional capacity and insufficient resources constrain the ability of many governments to implement forest and related sectoral policies on the ground ( Tacconi et al., 2003 [NPR] ).
In the face of these challenges, national forest policies designed to slow deforestation on public lands in developing countries have had mixed success:
China ( Cohen et al., 2002 [NPR] ), the Philippines and Thailand ( Granger, 1997 [NPR] ) have significantly reduced deforestation rates in response to experiencing severe environmental and public health consequences of forest loss and degradation. In India, the Joint Forest Management programme has been effective in partnering with communities to reduce forest degradation ( Bhat et al., 2001 [SRC] ). These examples indicate that strong and motivated government institutions and public support are key factors in implementing effective forest policies.
Options for maintaining forests on private lands in developing countries are generally more limited than on public lands, as governments typically have less regulatory control. An important exception is private landholdings in the Brazilian Amazon, where the government requires that landowners maintain 80% of the property under forest cover. Although this regulation has had limited effectiveness in the past ( (Alves et al., 1999 ) ), recent experience with a licensing and monitoring system in the state of Mato Grosso has shown that commitment to enforcement can significantly reduce deforestation rates.
A recently developed approach is for governments to provide environmental service payments to private forest owners in developing countries, thereby providing a direct financial incentive for the retention of forest cover. Relatively high transaction costs and insecure land and resource tenure have thus far limited applications of this approach in many countries ( Grieg-Gran, 2004 [NPR] ). However, significant potential may exist for developing payment schemes for restoration and retention of forest cover to provide climate mitigation (see below) and watershed protection services.
In addition to national-level policies, numerous international policy initiatives to support countries in their efforts to reduce deforestation have also been attempted:
Taken together, non-climate policies have had minimal impact on slowing tropical deforestation, the single largest contribution of land-use change to global carbon emissions. Nevertheless, there are promising examples where countries with adequate resources and political will have been able to slow deforestation. This raises the possibility that, with sufficient institutional capacity, financial incentives, political will and sustained financial resources, it may possible to scale up these efforts. One potential source of additional financing for reducing deforestation in developing countries is through well-constructed carbon markets or other environmental service payment schemes (Winrock International, 2004; Stern, 2006 [NPR] ).
Under the UNFCCC and Kyoto Protocol, no climate policies currently exist to reduce emissions from deforestation or forest degradation in developing countries. The decision to exclude avoided deforestation projects from the CDM in the Kyoto Protocol’s first commitment period was in part based on methodological concerns. These concerns are particularly associated with additionality and baseline setting and whether leakage could be sufficiently controlled or quantified to allow for robust carbon crediting ( Trines et al., 2006 [NPR, MoS, SRC] ). In December 2005, COP-11 established a two-year process to review relevant scientific, technical, and methodological issues and to consider possible policy approaches and positive incentives for reducing emissions from deforestation in developing countries ( UNFCCC, 2006 [NPR] ).
Recent studies suggests a broad range of possible architectures by which future climate policies might be designed to effectively reduce emissions from tropical deforestation and forest degradation ( Schlamadinger et al., 2005 [NPR, SRC] ; Trines et al., 2006 [NPR, MoS, SRC] ). For example, Santilli et al. 2005 [JoC] ), propose that non-Annex I countries might, on a voluntary basis, elect to reduce their national emissions from deforestation. The emission reductions could then be credited and sold to governments or international carbon investors at the end of a commitment period, contingent upon agreement to stabilize, or further reduce deforestation rates in the subsequent commitment periods.
One advantage of a national-sectoral approach over a project-based approach to reduce emissions from deforestation relates to leakage, in that any losses in one area could be balanced against gains in other areas. This does not entirely address the leakage problem since the risk of international leakage remains, as occurs in other sectors.
Other proposals emphasize accommodation to diverse national circumstances, including differing levels of development, and include a suggestion of separate targets for separate sectors ( Grassl et al., 2003 [NPR] ). This includes a “no-lose” target, whereby emission allowances can be sold if the target is reached. No additional emission allowances would have to be bought if the target was not met. A multi-stage approach such that the level of commitment of an individual country increases gradually over time; capacity building and technology research and development; or quantified sectoral emission limitation and reduction commitments similar to Annex 1 commitments under the Kyoto Protocol ( Trines et al., 2006 [NPR, MoS, SRC] ).
Proposed financing mechanisms include both carbon market-based instruments ( Stern, 2006 [NPR] ) and non-market based channels, for example, through a dedicated fund to voluntarily reduce emissions from deforestation ( UNFCCC, 2006 [NPR] ). Box 9.3 discusses recent technical advances relevant to the effective design and implementation of climate policies aimed at reducing emissions from deforestation and forest degradation.
Recent analyses (DeFries et al., 2006; UNFCCC, 2006 [NPR] ) indicate considerable progress since the Third Assessment Report and the IPCC Good Practice Guidance for Land Use, Land-Use Change and Forestry ( IPCC, 2003 [NPR] ) in data acquisition and development of methods and tools for estimating and monitoring carbon emissions from deforestation and forest degradation in developing countries. Remote sensing approaches to monitoring changes in land cover/land use at multiple scales and coverage are now close to operational on a routine basis. Measuring forest degradation through remote sensing is technically more challenging, but methods are being developed (DeFries et al., 2006 ).
Various methods can be applied, depending on national capabilities, deforestation patterns, and forest characteristics. Standard protocols need to be developed for using remote sensing data, tools and methods that suit both the variety of national circumstances and meet acceptable levels of accuracy. However, quantifying accuracy and ensuring consistent methods over time are more important than establishing consistent methods across countries.
Several developing countries, including India and Brazil, have systems in place for national-scale monitoring of deforestation (DeFries et al., 2006 ). While well-established methods and tools are available for estimating forest carbon stocks, dedicated investment would be required to expand carbon stock inventories so that reliable carbon estimates can be applied to areas identified as deforested or degraded through remote sensing. With sound data on both change in forest cover and on change in carbon stocks resulting from deforestation and degradation, emissions can be estimated using methods described by the new IPCC Inventory Guidelines ( IPCC, 2006 [NPR] ).
Non-climate forest policies have a long history in successful creation of plantation forests on both public and private lands in developing and developed countries. If governments have strong regulatory and institutional capacities, they may successfully control land use on public lands, and state agencies can reforest these lands directly. In cases where such capacities are more limited, governments may enter into joint management agreements with communities, so that both parties share the costs and benefits of plantation establishment ( Williams, 2002 [NPR] ). Incentives for plantation establishment may take the form of afforestation grants, investment in transportation and roads, energy subsidies, tax exemptions for forestry investments, and tariffs against competing imports ( Cossalter and Pye-Smith, 2003 [NPR] ). In contrast to conservation of existing forests, the underlying financial incentives to establish plantations may be positive. However, the creation of virtually all significant plantation estates has relied upon government support, at least in the initial stages. This is due, in part, to the illiquidity of the investment, the high cost of capital establishment and long waiting period for financial return.
Industrialized countries generally have sufficient resources to implement policy changes in public forests. However, the fact that these forests are already managed to relatively high standards may limit possibilities for increasing sequestration through changed management practices (e.g., by changing species mix, lengthening rotations, reducing harvest damage and or accelerating replanting rates). There may be possibilities to reduce harvest rates to increase carbon storage however, for example, by reducing harvest rates and/or harvest damage.
Governments typically have less authority to regulate land use on private lands, and so have relied upon providing incentives to maintain forest cover, or to improve management. These incentives can take the form of tax credits, subsidies, cost sharing, contracts, technical assistance, and environmental service payments. In the United States, for example, several government programmes promote the establishment, retention, and improved management of forest cover on private lands, often of marginal agricultural quality (Box 9.4; Gaddis et al., 1995 [NPR] ).
The lack of robust institutional and regulatory frameworks, trained personnel, and secure land tenure has constrained the effectiveness of forest management in many developing countries ( Tacconi et al., 2003 [NPR] ; Box 9.5). Africa, for example, had about 649 million forested hectares as of 2000 ( FAO, 2001 [NPR] ). Of this, only 5.5 million ha (0.8%) had long-term management plans, and only 0.9 million ha (0.1%) were certified to sound forestry standards. Thus far, efforts to improve logging practices in developing countries have met with limited success. For example, reduced-impact logging (RIL) techniques would increase carbon storage over traditional logging, but have not been widely adopted by logging companies, even when they lead to cost savings ( (Holmes et al., 2002 ) ). Nevertheless, there are several examples where large investments in building technical and institutional capacity have dramatically improved forestry practices ( Dourojeanni, 1999 [NPR, MoS] ).
Many programmes in the United States support the establishment, retention, and improved management of forest cover on private lands. These entail contracts and subsidies to private landowners to improve or change land-use management practices. USDA also provides technical information, research services, cost sharing and other financial incentives to improve land management practices, including foresting marginal agricultural lands, and improving the management of existing of forests. Examples include the Conservation Reserve Program; Forestry Incentives Program, and Partners for Wildlife; ( Richards et al., 2006 [NPR] ). For example, in the 20-year period between 1974 and 1994, the Forestry Incentives Program spent 200 US$ million to fund 1.34 million hectares of tree planting; 0.58 million hectares of stand improvement; and 11 million hectares of site preparation for natural regeneration ( Gaddis et al., 1995 [NPR] ).
Richards et al. 2006 [NPR] ) suggest that substantial gains in carbon sequestration and storage could be achieved by increasing the resources and scope of these programmes and through new results-based programmes, which would reward landowners based on the actual carbon they sequester or store.
Forest and land use policies across African countries have historically passed through two types of governance: Under traditional systems controlled by families, traditional leaders and communities, decisions regarding land allocation, redistribution and protection were the responsibility of local leaders. Most land and resources were under relatively sustainable management by nomadic or agro-pastoralist communities who developed systems to cope with vulnerable conditions. Agriculture was typically limited to shifting cultivation, with forest and range resources managed for multiple benefits.
Under central government systems, land-use policies are sectoral-focused, with strong governance in the agricultural sector. Agriculture expansion policies typically dominate land use at the expense of forestry and rangeland management. This has greatly influenced present day forest and range policies and practices and resulted in vast land degradation ( IUCN, 2002 [NPR] ; 2004 ).The adoption of centralized land management policies and legislation system has often brought previously community-oriented land management systems into national frameworks, largely without the consent and involvement of local communities. Central control is reflected in large protected areas, with entry of local communities prevented.
Presently, contradiction and conflicts in land-use practices between sectors and communities is common. Negotiations demanding decentralization and equity in resource distribution may lead to changes in land tenure systems in which communities and official organizations will increasingly agree to collaboration and joint management in which civil societies participate. Parastatal institutions, established in some countries, formulate and implement policies and legislation that coordinate between sectors and to encourage community participation in land and resource management.
Land tenure categories characteristically include private holdings (5–25% of national area), communal land (usually small percentage) and state lands (the majority of the land under government control). Each faces many problems generated by conflicting rights of use and legislation that gives greater government control on types of resource use even under conditions of private ownership. Land control system and land allocation policy adopted by central governments often have negative impacts on land and tree tenure. Local communities are not encouraged to plant, conserve and manage trees on government owned land that farmers use on lease systems. Even large-scale farmers who are allocated large areas for cultivation, abandon the land and leave it as bare when it becomes non-productive. Forest lands reserved and registered under community ownership are communally managed on the basis of stakeholder system and shared benefits.
Evidence from many case studies in Sudan suggests that integrated forest management where communities have access rights to forest lands and are involved in management, is a key factor favouring the restoration of forest carbon stocks ( IUCN, 2004 [NPR] ). These projects provide examples of a collaborative system for the rehabilitation and use of the forest land property based on defined and acceptable criteria for land cultivation by the local people and for renewal of the forest crop.
Policies aimed at liberalizing trade in forest products have mixed impacts on forest management practices. Trade liberalization in forest products can enhance competition and can make improved forest management practices more economically attractive in mature markets ( Clarke, 2000 [NPR] ). But, in the relatively immature markets of many developing countries, liberalization may act to magnify the effects of policy and market failures ( Sizer et al., 1999 [NPR] ).
The recent FAO forest assessment conservatively estimates that insects, disease and fire annually impact 3.2% of the forests in reporting countries ( FAO, 2005 [NPR] ). Policies that successfully increase the forest protection against natural disturbance agents may reduce net emissions from forest lands ( Richards et al., 2006 [NPR] ). In industrialized countries, a history of fire suppression and a lack of thinning treatments have created high fuel loads in many public forests, such that when fires do occur, they release large quantities of carbon ( Schelhaas et al., 2003 [ARC] ).
A major technical obstacle is designing careful management interventions to reduce fuel loading and to restore landscape heterogeneity to forest structure (USDA Forest Service, 2000 [NPR] ). Scaling up their application to large forested areas, such as in Western USA, Northern Canada or Russia, could lead to large gains in the conservation of existing carbon stocks (Sizer et al., 2005 [NotFound] ). Forest fire prevention and suppression capacities are rudimentary in many developing countries, but trial projects show that with sufficient resources and training, significant reductions in forest fires can be achieved ( ITTO, 1999 [NPR] ).
Voluntary certification to sustainable forest management standards aims to improve forest management by providing incentives such as increased market access or price premiums to certified producers who meet these standards. Various certification schemes have collectively certified hundreds of millions of hectares in the last decade and certification can result in measurable improvements in management practices ( Gullison, 2003 [SRC] ). However, voluntary certification efforts to date continue to be challenged in improving the management of forest managers operating at low standards, where the potential for improvement and net emissions reductions are greatest. One possible approach to overcome current barriers in areas with weak forest management practices is to include stepwise or phased approaches to certification ( (Atyi and Simula, 2002 ) ).
Countries may promote the use of bioenergy for many non-climate reasons, including increasing energy security and promoting rural development ( Parris, 2004 [NPR] ). Brazil, for example, has a long history of encouraging plantation establishment for the production of industrial charcoal by offering a combination of tax exemption for plantation lands, tax exemption for income originating from plantation companies, and deductibility of funds used to establish plantations ( Couto and Betters, 1995 [NPR] ). The United States provides a range of incentives for ethanol production including exclusion from excise taxes, mandating clean air performance requirements that created markets for ethanol, and tax incentives and accelerated depreciation schedules for electricity generating equipment that burn biomass ( USDOE, 2005 [NPR] ). The Australian Government’s Mandatory Renewable Energy Target, which seeks to create a market for renewable energy, provides incentives for the development of renewable energy from plantations and wood waste (Government of Australia, 2006 ).
Building codes and other government policies that, where appropriate, can promote substitution of use of sustainably harvested forest products wood for more energy-intensive construction materials may have substantial potential to reduce net emissions ( (Murphy, 2004 ) ). Private companies and individuals may also modify procurement to prefer or require certified wood from well-managed forests on environmental grounds. Such efforts might be expanded once the climate mitigation benefits of sustainably harvested wood products are more fully recognized.
Policies have generally been most successful in changing forestry activities where they are consistent with underlying profitability incentives, or where there is sufficient political will, financial resources and regulatory capacity for effective implementation. Available evidence suggests that policies that seek to alter forestry activities where these conditions do not apply have had limited effectiveness. Additional factors that influence the potential for non-climate policies to reduce net emissions from the forest sector include their ability to (1) provide relatively large net reductions per unit area; (2) be potentially applicable at a large geographic scale; and, (3) have relatively low leakage ( Niesten et al., 2002 [NPR, SRC] ).
By these criteria, promising approaches across both industrialized and developing countries include policies that combat the loss of public forests to natural disturbance agents, and “Payment for Environmental Services” (PES) systems that provide an incentive for the retention of forest cover. In both cases, there are good examples where they have been successfully implemented at small scales, and the impediments to increasing scale are relatively well understood. There is also a successful history of policies to create new forests, and these have led to large on-site reductions in net emissions. Care must be taken, however, to make sure that at plantation creation, there is no displacement of economic or subsistence activities that will lead to forest clearing elsewhere. Policies to increase the substitution of fossil fuels with bioenergy have also had a large positive impact on net emissions. If feedstock is forestry waste, then there is little potential leakage. If new plantations are created for biofuel, then care must be taken to reduce leakage.
Because forestry policies tend not to have climate mitigation as core objective, leakage and other factors that may limit net reductions are generally not considered. This may change as countries begin to integrate climate change mitigation objectives more fully into national forestry policies. Countries where such integration is taking place include Costa Rica, the Dominican Republic, and Peru ( Rosenbaum et al., 2004 [NPR] ).
Experience is limited by the fact that Joint Implementation is not operational yet, and the first call for afforestation and reforestation (A/R) methodologies under CDM was only issued in September 2004 . In addition, the modalities and procedures for CDM A/R as decided in December 2003 are complex. Nevertheless, the capacities built up through the development of projects and related methodologies should not be underestimated. As of November 2006, 27 methodologies were submitted, 17 from Latin America, four from Asia and Africa respectively, and two from Eastern Europe. The four which were approved by the CDM Executive Board relate to projects located in China, Moldova, Albania and Honduras and all consist of planting forests on degraded agricultural land. In anticipation of Joint Implementation, several projects are under development in several Annex I countries in Eastern Europe, notably in Romania, Ukraine and the Czech Republic.
There are voluntary project-based activities in the USA, with a programme for trading certificates established by the Chicago Climate Exchange ( Robins, 2005 [NPR] ). The Voluntary Reporting ( 1605 (b)) Program of the US Department of Energy ( USDOE, 2005 [NPR] ) provides reporting guidelines for forestry activities. Since the Special Report on LULUCF ( IPCC, 2000a [NPR] ), there has been methodological progress in several areas discussed below.
There is no indication that leakage effects are necessarily higher in forestry than in project activities in other sectors but they can be significant ( Chomitz, 2002 [JoC] ). Some studies distinguish between primary and secondary effects. A primary effect is defined as resulting from agents that perform land use activities reflected in the baseline. Populations previously active on the project area may shift their activities to other areas. In land protection projects, logging companies may shift operations or buy timber from outside the project area to compensate for reduced supply of the commodity (activity outsourcing). Secondary leakage is not linked to project participants or previous actors on the area. It is often a market effect, where a project increases (by forest plantation) or decreases (deforestation avoidance) wood supply. Quantitative estimates of leakage ( Table 9.9 ) suggest that leakage varies by mitigation activity and region.
The order of magnitude and even the direction of leakage (negative versus positive), however, depend on the project design ( Schwarze et al., 2003 [NPR] ). Leakage risk is likely to be low if a whole country or sector is involved in the mitigation activity, or if project activities are for subsistence and do not affect timber or other product markets. There are also well-documented methods to minimize leakage of project-based activities. For example, afforestation projects can be combined with biomass energy plants, or they may promote the use of timber as construction material. Fostering agricultural intensification in parallel can minimize negative leakage from increased local land demand. Where a project reduces deforestation, it can also reduce pressure on forest lands, for example, by intensifying the availability of fuel wood from other sources for local communities. Projects can be designed to engage local people formerly responsible for deforestation in alternative income-generating activities ( Sohngen and Brown, 2004 [SRC] ).
Leakage appears to have a time dimension as well, due to the dynamics of the forest carbon cycle and management (for example, timing of harvest, planting and regrowth, or protection). Analysis in the USA indicates that national afforestation in response to a carbon price of 15 US$/tCO2 would have 39% leakage in the first two decades, but decline to 24% leakage over five to ten decades, due to forest management dynamics ( US EPA, 2005 [NPR] ).
|Activity||Region||Leakage estimation method||Estimated leakage rate (% of carbon mitigation)||Source|
|Afforestation: tropical region estimates|
|Afforestation of degraded lands||Kolar district, Karnataka, India hypothetical project||Household wood demand survey||0.02||Ravindranath, et al., 2007|
|Plantations, forest conservation, agro-forestry of degraded lands||Magat watershed, Philippines hypothetical project||Historical rates of technology adoption||19 – 41||Authors estimates based on Lasco et al., 2007|
|Afforestation on small landowner parcels||Scolel Té project, Chiapas, Mexico||Household wood demand survey||0||De Jong et al., 2007|
|(some positive leakage)|
|Afforestation degraded uplands||Betalghat hypothetical project, Uttaranchal, India||Household wood demand survey||10||Hooda et al., 2007|
|from fuelwood, fodder|
|Afforestation, farm forestry||Bazpur hypothetical project, Uttaranchal, India||Household wood demand survey||20||Hooda et al., 2007|
|from fuelwood, poles|
|Afforestation: global and temperate region estimates|
|Afforestation (plantation establishment)||Global||PEM||0.4-15.6||Sedjo and Sohngen, 2000|
|Afforestation||USA-wide||PEM||18-42||Murray et al., 2004|
|Afforestation only||USA-wide||PEM||24||US EPA, 2005|
|Afforestation and forest management jointly||USA-wide||PEM||-2.8 a)||US EPA, 2005|
|Avoided deforestation: tropical region estimates|
|Avoided deforestation||Bolivia, Noel Kempff project and national||PEM||2-38 discounted||Sohngen and Brown, 2004|
|Avoided deforestation and biofuels: temperate region estimates|
|Avoided deforestation||Northeast USA||PEM||41-43||US EPA, 2005|
|Avoided deforestation||Rest of USA||PEM||0-92||US EPA, 2005|
|Avoided deforestation||Pacific Northwest USA||PEM||8-16||US EPA, 2005|
|Avoided deforestation (reduced timber sales)||Pacific Northwest USA||Econometric model||43 West region||Wear and Murray, 2004|
|58 Continental US|
|84 US and Canada|
|Biofuel production (short rotation woody crops)||USA||PEM||0.2||US EPA, 2005|
The reversibility of carbon removal from the atmosphere creates liability issues whenever integrating land use in any kind of accounting system. There needs to be a liability for the case that carbon is released back into the atmosphere because Parties to the UNFCCC agreed, “…that reversal of any removal due to land use, land-use change and forestry activities be accounted for at the appropriate point in time” ( UNFCCC, 2001 [NPR] ). In 2000, the Colombian delegation first presented a proposal to create expiring Certified Emission Reductions under CDM ( UNFCCC, 2001 [NPR] ). Its basic idea is that the validity of Certified Emission Reductions (CERs) from afforestation and reforestation project activities under CDM is linked to the time of existence of the relating stocks. The principle of temporary crediting gained support over the subsequent years. Consequently, the Milan Decision 19/CP.9 ( UNFCCC, 2003 [NPR] ) created two types of expiring CERs: temporary CERs - tCERs and long-term CERs - lCERs. The validity of both credit types is limited and reflected on the actual certificate. The credit owner is liable to replace them when they expire or when the relating stocks are found to be lost at the end of the commitment period. Afforestation and reforestation projects need to be verified first at a time at the discretion of the project participants, and in intervals of exactly five years thereafter. The value of temporary CERs critically depends on the market participants’ mitigation cost expectations for future commitment periods. Assuming constant carbon prices, the price for a temporary CER during the first commitment period is estimated to range between 14 and 35 % of that of a permanent CER from any other mitigation activity ( Dutschke, et al., 2005 [JoC, SRC] ). This solution is safe from the environmental integrity point of view, yet it has created much uncertainty among project developers ( Pedroni, 2005 [JoC] ).
A project that claims carbon credits for mitigation needs to demonstrate its additionality by proving that the same mitigation effect would not have taken place without the project. For CDM, the Executive Board’s Consolidated Additionality Tool offers a standardized procedure to project developers. Specific for CDM afforestation and reforestation (A/R), there is an area eligibility test along the forest definitions provided under the relevant Decision 11/CP.7 in order to avoid implementation on areas that prior to the project start were forests in 1990 or after. In the modalities and procedures for CDM, there are three different baseline approaches available for A/R. So far, only one has been successfully applied in the four approved methodologies.
For project monitoring, there is now an extended guidance available ( IPCC, 2006 [NPR] ; USDOE, 2005 [NPR] ). Monitoring costs depend on many variables, including the project complexity (including the number of stakeholders involved), heterogeneity of the forest type, the number and type of carbon pools, and GHG to be monitored and the appropriate measurement frequencies. There is a trade-off between the completeness of monitoring data and the carbon price that can be achieved: monitoring costs can sum up an important share of a project’s transaction costs. Proper design of the monitoring plan is, therefore, essential for the economic viability of forestry projects. If project developers can demonstrate that omitting particular carbon pools from the project’s quantification exercise does not constitute an overestimate of the project’s GHG benefits, such pools may be left outside the monitoring plan.
For forestry mitigation projects to become viable on a larger scale, certainty over future commitments is needed because forestry needs a long planning horizon. Rules need to be streamlined, based on the experience gathered so far. Standardization of project assessment can play important roles to overcome uncertainty among potential buyers and investors, and to prevent negative social and environmental impacts.
Despite relative low costs and many possible positive side-effects, the pace with which forest carbon projects are being implemented is slow. This is due to a variety of barriers. Barriers can be categorized as economic, risk-related, political/bureaucratic, logistic, and capacity or political will (the latter barrier also occurring in industrialized countries; Trines et al., 2006 [NPR, MoS, SRC] ). One of the most important climate-related barriers is the complexity of the rules for afforestation and reforestation project activities. This leads to uncertainty among project developers and investors. Temporary accounting of credits is a major obstacle for two reasons: (1) The future value of temporary CERs depends on the buyer’s confidence in the underlying project. This may limit investor interest in getting involved in project development. (2) The value of temporary CERs hinges on future allowance price expectations because they will have to be replaced in future commitment periods. Furthermore, EU has deferred its decision to accept forestry credits under its emissions trading scheme. Even if EU decided to integrate these credits, this would come too late to take effect in the first commitment period because trees need time to grow. Given the low value of temporary CERs, transaction costs have a higher share in afforestation and reforestation than in energy mitigation projects. Simplified small-scale rules were introduced in order to reduce transaction costs, but the maximum size of 8 kilotonnes of average annual CO2 net removal limits their viability.
Sustainable forest management of both natural and planted forests is essential to achieving sustainable development. It is a means to reduce poverty, reduce deforestation, halt the loss of forest biodiversity, and reduce land and resource degradation, and contribute to climate change mitigation. Forests play an important role in stabilization of greenhouse gas concentrations in the atmosphere while promoting sustainable development (Article 2; Kyoto Protocol). Thus, forests have to be seen in the framework of the multiple dimensions of sustainable development, if the positive co-benefits from forestry mitigation activities have to be maximized. Important environmental, social, and economic ancillary benefits can be gained by considering forestry mitigation options as an element of the broader land management plans.
Forestry policies and measures undertaken to reduce GHG emissions may have significant positive or negative impacts on environmental and sustainable development objectives that are a central focus of other multilateral environmental agreements (MEAs), including UN Convention on Biological Diversity (CBD), UN Convention to Combat Desertification (CCD), and Ramsar Convention on Wetlands. In Article 2.1(a, b), Kyoto Protocol, Parties agreed various ways to consider potential impacts of mitigation options and whether and how to establish some common approaches to promoting the sustainable development contributions of forestry measures. In addition, a broad range of issues relating to forest conservation and sustainable forest management have been the focus of recent dialogues under the Intergovernmental Forum on Forests.
Recent studies highlighted that strategic thinking about the transition to a sustainable future is particularly important for land ( Swanson et al., 2004 [NPR, ARC] ). In many countries, a variety of separate sets of social, economic and environmental indicators are used, making it difficult to allow for adequate monitoring and analysis of trade-offs between these interlinked dimensions. Still, sustainable development strategies often remain in the periphery of government decision-making processes; and lack coordination between sub-national and local institutions; and economic instruments are often underutilized.
To manage forest ecosystems in a sustainable way implies knowledge of their main functions, and the effects of human practices. In recent years, scientific literature has shown an increasing attempt to understand integrated and long-term effects of current practices of forest management on sustainable development. But often, environmental or socio-economic effects are considered in isolation, or there is no sufficient understanding of the potential long-term impacts of current practices on sustainable development. Payment for Environmental Services (PES) schemes for forest services (recognizing carbon value) may be foreseen as part of forest management implementation, providing new incentives to change to more sustainable decision patterns. Experience, however, is still fairly limited and is concentrated in a few countries, notably in Latin America, and has had mixed results to date ( Wunder, 2004 [NPR] ).
Important environmental, social, and economic ancillary benefits can be gained by considering forestry mitigation options as an element of the broad land management plans, pursuing sustainable development paths, involving local people and stakeholders and developing adequate policy frameworks.
Climate mitigation policies may have benefits that go beyond global climate protection and actually accrue at the local level ( Dudek et al., 2002 [NPR] ). Since ancillary benefits tend to be local, rather than global, identifying and accounting for them can reduce or partially compensate the costs of the mitigation measures. However, forests fulfil many important environmental functions and services that can be enhanced or negatively disturbed by human activities and management decisions. Negative effects can be triggered by some mitigation options under certain circumstances. Positive and negative impacts of mitigation options on sustainable development are presented in Table 9.10 .
|Activity category||Sustainable development implications|
|A. Increasing or maintaining the forest area|
|Reducing deforestation and forest degradation||Positive||Positive or negative||Positive|
|Promotes livelihood.||Provides sustained income for poor communities. Forest protection may reduce local incomes.||Biodiversity conservation. Watershed protection. Soil protection. Amenity values (Nature reserves, etc.)|
|Afforestation/reforestation||Positive or negative||Positive or negative||Positive or negative|
|Promotes livelihood. Slows population migration to other areas (when a less intense land use is replaced). Displacement of people may occur if the former activity is stopped, and alternate activities are not provided. Influx of outside population has impacts on local population.||Creation of employment (when less intense land use is replaced). Increase/decrease of the income of local communities. Provision of forest products (fuelwood, fibre, food construction materials) and other services.||Impacts on biodiversity at the tree, stand, or landscape level depend on the ecological context in which they are found. Potential negative impacts in case on biodiversity conservation (mono-specific plantations replacing biodiverse grasslands or shrub lands). Watershed protection (except if water-hungry species are used) . Losses in stream flow. Soil protection. Soil properties might be negatively affected.|
|B. Changing to sustainable forest management|
|Forest management in plantations||Positive||Positive||Positive|
Creation of employment
Increase of the income of local communities.
Provision of forest products (fuelwood, fibre, food, construction materials) and other services.
Enhance positive impacts and minimize negative implications on biodiversity, water and soils.
|Sustainable forest management in native forest||Positive||Positive||Positive|
Creation of employment.
Increase of the income of local communities.
Provision of forest products (fuelwood, fibre, food, construction materials) and other services.
Sustainable management prevents forest degradation, conserves biodiversity and protects watersheds and soils.
|C. Substitution of energy intensive materials|
|Substitution of fossil intensive products by wood products||[Positive or negative]||[Positive]||[Negative]|
Forest owners may benefit.
Potential for competition with the agricultural sector (food production, etc.).
Increased local income and employment in rural and urban areas.
Potential diversification of local economies.
Non-sustainable harvest may lead to loss of forests, biodiversity and soil.
|Bioenergy production from forestry||Positive or negative||Positive or negative||Positive or negative|
Forest owners may benefit.
Potential for competition with the agricultural sector (food production, etc.)
Increased local income and employment.
Potential diversification of local economies.
Provision of renewable and independent energy source.
Potential competition with the agricultural sector (food production, etc.)
Benefits if production of fuelwood is done in a sustainable way.
Mono specific short rotation plantations for energy may negatively affect biodiversity, water and soils, depending on site conditions.
Stopping or slowing deforestation and forest degradation (loss of carbon density) and sustainable forest management may significantly contribute to avoided emissions, conserve water resources and prevent flooding, reduce run-off, control erosion, reduce river siltation, and protect fisheries and investments in hydroelectric power facilities; and at the same time, preserve biodiversity ( Parrotta, 2002 [NPR] ). Thus, avoided deforestation has large positive implications for sustainable development. Further, natural forests are a significant source of livelihoods to hundreds and millions of forest-dependent communities.
Plantations provide an option to enhance terrestrial sinks and mitigate climate change. Effects of plantations on sustainable development of rural societies have been diverse, depending on socio-economic and environmental conditions and management regime. Plantations may have either significant positive and /or negative effects (environmental and social effects). They can positively contribute, for example, to employment, economic growth, exports, renewable energy supply and poverty alleviation. In some instances, plantation may also lead to negative social impacts such as loss of grazing land and source of traditional livelihoods.
Large investments have been made in commercial plantations on degraded lands in Asia. However, lack of consultation with stakeholders (state of land tenure and use rights) may result in failure to achieve the pursued results. Better integration between social goals and afforestation is necessary ( Farley et al., 2004 [NPR, SRC] ). As demand increases for lands to afforest, more comprehensive, multidimensional environmental assessment and planning will be required to manage land sustainably.
Agro-forestry can produce a wide range of economic, social and environmental benefits, and probably wider than in case of large-scale afforestation. Agro-forestry systems could be an interesting opportunity for conventional livestock production with low financial returns and negative environmental effects (overgrazing and soil degradation). For many livestock farmers, who may face financial barriers to develop this type of combined systems (e.g., silvo-pastoral systems), payment for environmental services could contribute to the feasibility of these initiatives ( (Gobbi, 2003 ) ). Shadow trees and shelter may have also beneficial effects on livestock production and income, as reported by ( Bentancourt et al., 2003 ) ). Little evidence of local extinctions and invasions of species risking biodiversity has been found when practising agro-forestry ( Clavijo et al., 2005 [SRC] ).
The Millennium Development Goals (MDGs) aim at poverty reduction, and to improve health, education, gender equality, sanitation and environmental sustainability to promote Sustainable Development. Forest sector can significantly contribute to reducing poverty and improving livelihoods (providing access to forest products such as fuelwood, timber, and non timber products). Land degradation, access to water and food and human health remained at the centre of global attention under the debate on the World Summit on Sustainable Development (WSSD). A focus on five key thematic areas was proposed (Water, Energy, Health, Agriculture, and Biodiversity -WEHAB), driving attention to the fact that managing the natural resources like forest in a sustainable and integrated manner is essential for sustainable development. In this regard, to reverse the current trend in forest degradation as soon as possible, strategies need to be implemented that include targets adopted at national and, where appropriate, regional levels to protect ecosystems and to achieve integrated management of land, water and living resources associated to forest areas, while strengthening regional, national and local capacities.
Literature describing in detail the environmental impacts of different forest activities is still scarce and focuses mostly on planted forests. For these reasons, the discussion focuses more on plantations. It is important to underline that while benefits of climate change mitigation are global, co-benefits and costs tend to be local ( OECD, 2002 [NPR] ) and, in accordance, trade-offs have to be considered at local level.
Water cycle: Afforestation may result in better balance in the regional water cycle balance by reducing run-off, flooding, and control of groundwater recharge and watersheds protection. However, massive afforestation grasslands may reduce water flow into other ecosystems and rivers, and affect aquifers layer and recharge, and lead to substantial losses in stream flow ( Jackson et al, 2005 [JoC, SRC] ). In addition, some possible changes in soil properties are largely driven by changes in hydrology.
Soils: Intensively managed plantations have nutrient demands that may affect soil fertility and soil properties, for example leading to higher erosion of the uncovered mineral soil surface (Perez-Bidegain et al., 2001; ( Carrasco-Letellier et al., 2004 ) ); and biological properties changes ( (Sicardi et al., 2004 ) ) if the choice of species is not properly matched with site conditions. Regarding chemical properties, increased Na concentrations, exchangeable sodium percentage and soil acidity, and decreased base saturation have been detected in many situations. ( Jackson, et al., 2005 [JoC, SRC] ).In general, afforestation of low soil carbon croplands may present considerable opportunities for carbon sequestration in soil, while afforestation of grazing land can result in relatively smaller increases or decreases in soil carbon ( Section 126.96.36.199 ). Most mitigation options other than monoculture plantations conserve and protect soils and watersheds.
Biodiversity: Plantations can negatively affect biodiversity if they replace biologically rich native grassland or wetland habitats ( (Wagner, et al., 2006 ) ). Also, plantations can have either positive or negative impacts on biodiversity depending on management practices ( Quine and Humphrey, 2005 [NPR] ). Plantations may act as corridors, source, or barriers for different species, and a tool for landscape restoration (Parrota, 2002 ). Other forestry mitigation options such as reducing deforestation, agro-forestry, multi-species plantations, and sustainable native forest management lead to biodiversity conservation.
Managing plantations to produce goods (such as timber) while also enhancing ecological services (such as biodiversity) involves several trade-offs. Overcoming them involves a clear understanding of the broader ecological context in which plantations are established as well as participation of the different stakeholders. The primary management objective of most industrial plantations traditionally has been to optimize timber production. This is not usually the case in small-scale plantations owned by farmers, where more weight is given to non-timber products and ecological services. A shift from a stand level to a broader forest and non-forest landscape level approach will be required to achieve a balance between biodiversity and productivity/profitability.
The literature seems to suggest that plantations, mainly industrial plantations, require careful assessment of the potential impacts on soils, hydrological cycle and biodiversity, and that negative impacts could be controlled or minimized if adequate landscape planning and basin management and good practices are introduced. Carbon sequestration strategies with afforestation of non-forest lands should consider their full environmental consequences. The ultimate balance of co-benefits and impacts depends on the specific site conditions and previous and future land and forest management.
R&D and technology transfer have a potential to promote forest sector mitigation options by increasing sustainable productivity, conserving biodiversity and enhancing profitability. Technologies are available for promoting mitigation options from national level to forest stand level, and from single forest practices to broader socio-economic approaches ( IPCC, 2000b [NPR] ).
Traditional and/or existing techniques in forestry including planting, regeneration, thinning and harvesting are fundamental for implementation of mitigation options such as afforestation, reforestation, and forest management. Further, improvement of such sustainable techniques is required and transfer could build capacity in developing countries. Biotechnology may have an important role especially for afforestation and reforestation. As the area of planted forests including plantations of fast-growing species for carbon sequestration increases, sustainable forestry practices will become more important for both productivity and environment conservation.
The development of suitable low-cost technologies will be necessary for promoting thinning and mitigation options. Moreover, technology will have to be developed for making effective use of small wood, including thinned timber, in forest products and markets. Thinning and tree pruning for fuelwood and fodder are regularly conducted in many developing countries as part of local integrated forest management strategies. Although natural dynamics are part of the forest ecosystem, suppression of forest fires and prevention of insect and pest disease are important for mitigation.
Regarding technology for harvesting and procurement, mechanized forest machines such as harvesters, processors and forwarders developed in Northern Europe and North America have been used around the world for the past few decades. Mechanization under sustainable forest management seems to be effective for promoting mitigation options including product and energy substitution ( Karjalainen and Asikainen, 1996 [SRC] ). However, harvesting and procurement systems vary due to terrain, type of forest, infrastructure and transport regulations, and appropriate systems also vary by regions and countries. Reduced impact logging is considered in some cases such as in tropical forests ( Enters et al., 2002 [NPR] ).
There is a wide array of technologies for using biomass from plantations for direct combustion, gasification, pyrolysis, and fermentation (see Section 188.8.131.52 ). To conserve forest resources, recycling of wood waste material needs to be expanded. Technology for manufacturing waste-derived board has almost been established, but further R&D will be necessary to re-use waste sawn timber, or to recycle it as lumber. While these technologies often need large infrastructure and incentives in industrialized countries, practical devices such as new generations of efficient wood-burning cooking stoves ( Masera et al., 2005 [SRC] ) have proved effective in developing countries. They are effective as a means to reduce the use of wood fuels derived from forests, at the same time providing tangible sustainable development benefits for local people, such as reduction in indoor air pollution levels.
Technological R&D for estimation of carbon stocks and fluxes is fundamental not only for monitoring but also for evaluating policies. Practical methods for estimating carbon stocks and fluxes based on forest inventories and remote sensing have been recommended in the Good Practice Guidance for LULUCF ( IPCC, 2003 [NPR] ). Over the last three decades, earth observation satellites have increased in number and sophistication (DeFries et al., 2006 ). High-resolution satellite images have become available, so new research on remote sensing has begun on using satellite radar and LIDAR (light detection and ranging) for estimating forest biomass ( Hirata et al., 2003 [NPR, MoS] ). Remote sensing methods are expected to play an increasing role in future assessments, especially as a tool for mapping land cover and its change over time. However, converting these maps into estimates of carbon sources and sinks remains a challenge and will continue to depend on in-situ measurements and modelling.
Large-scale estimations of the forest sector and its carbon balance have been carried out with models such as the CBM-CFS2 ( Kurz and Apps, 2006 [SRC] ), CO2FIX V.2 model ( Masera et al., 2003 [NPR, MoS, SRC] ), EFISCEN ( Nabuurs et al., 2005 [NPR, ARC] , 2006 ), Full CAM ( Richards and Evans, 2004 [MoS] ), and GORCAM ( Schlamadinger and Marland, 1996 [SRC] ).
Micrometeorological observation of carbon dioxide exchange between the terrestrial ecosystem and the atmosphere has been carried out in various countries ( (Ohtani, 2005 ) ). Based on the observation, a global network FLUXNET ( (Baldocchi et al., 2001 ) ) and regional networks including AmeriFlux, EUROFLUX, AsiaFlux and OzNet are being enlarged for stronger relationships.
New technologies for monitoring and verification including remote sensing, carbon flux modelling, micrometeorological observation and socio-economic approaches described above will facilitate the implementation of mitigation options. Furthermore, the integration of scientific knowledge, practical techniques, socio-economic and political approaches will become increasingly significant for mitigation technologies in the forest sector.
Few forest-based mitigation analyses have been conducted using primary data. There is still limited insight regarding impacts on soils, lack of integrated views on the many site-specific studies, hardly any integration with climate impact studies, and limited views in relation to social issues and sustainable development. Little new effort was reported on the development of global baseline scenarios of land-use change and their associated carbon balance, against which mitigation options could be examined. There is limited quantitative information on the cost-benefit ratios of mitigation interventions.
Technology deployment, diffusion and transfer in the forestry sector provide a significant opportunity to help mitigate climate change and adapt to potential changes in the climate. Apart from reducing GHG emissions or enhancing the carbon sinks, technology transfer strategies in the forest sector have the potential to provide tangible socio-economic and local and global environmental benefits, contributing to sustainable development ( IPCC, 2000b [NPR] ). Especially, technologies for improving productivity, sustainable forest management, monitoring, and verification are required in developing countries. However, existing financial and institutional mechanism, information and technical capacity are inadequate. Thus, new policies, measures and institutions are required to promote technology transfer in the forest sector.
For technology deployment, diffusion and transfer, governments could play a critical role in: a) providing targeted financial and technical support through multilateral agencies (World Bank, FAO, UNDP, UNEP), in developing and enforcing the regulations to implement mitigation options; b) promoting the participation of communities, institutions and NGOs in forestry projects; and c) creating conditions to enable the participation of industry and farmers with adequate guidelines to ensure forest management and practices as mitigation options. In addition, the role of private sector funding of projects needs to be promoted under the new initiatives, including the proposed flexible mechanisms under the Kyoto Protocol. The Global Environmental Facility (GEF) could fund projects that actively promote technology transfer and capacity building in addition to the mitigation aspects ( IPCC, 2000b [NPR] ).
Mitigation measures up to 2030 can prevent the biosphere going into a net source globally. The longer-term mitigation prospects (beyond 2030 ) within the forestry sector will be influenced by the interrelationship of a complex set of environmental, socio-economic and political factors. The history of land-use and forest management processes in the last century, particularly within the temperate and boreal regions, as well as on the recent patterns of land-use will have a critical effect on the mitigation potential.
Several studies have shown that uncertainties in the contemporary carbon cycle, the uncertain future impacts of climatic change and its many dynamic feedbacks can cause large variation in future carbon balance projections ( Lewis et al., 2005 [NPR, MoS] ). Other scenarios suggest that net deforestation pressure will slow over time as population growth slows and crop and livestock productivity increase. Despite continued projected loss of forest area, carbon uptake from afforestation and reforestation could result in net sequestration ( Section 3.2.2 ).
Also, the impacts of climate change on forests will be a major source of uncertainty regarding future projections ( Viner et al., 2006 [NPR] ). Other issues that will have an effect on the long-term mitigation potential include future sectoral changes within forestry, changes in other economic sectors, as well as political and social change, and the particular development paths within industrialized and developing countries beyond the first half of the 21st century. The actual mitigation potential will depend ultimately on solving structural problems linked to the sustainable management of forests. Such structural problems include securing land tenure and land rights of indigenous people, reducing poverty levels in rural areas and the rural-urban divide, and providing disincentives to short-term behaviour of economic actors and others. Considering that forests store more carbon dioxide than the entire atmosphere ( Stern, 2006 [NPR] ), the role of forests is critical.
Forestry mitigation projections are expected to be regionally unique, while still linked across time and space by changes in global physical and economic forces. Overall, it is expected that boreal primary forests will either be sources or sinks depending on the net effect of some enhancement of growth due to climate change versus a loss of soil organic matter and emissions from increased fires. The temperate forests in USA, Europe, China and Oceania, will probably continue to be net carbon sinks, favoured also by enhanced forest growth due to climate change. In the tropical regions, the human induced land-use changes are expected to continue to drive the dynamics for decades. In the meantime, the enhanced growth of large areas of primary forests, secondary regrowth, and increasing plantation areas will also increase the sink. Beyond 2040, depending on the extent and effectiveness of forest mitigation activities within tropical areas, and very particularly on the effectiveness of policies aimed at reducing forest degradation and deforestation, tropical forest may become net sinks. In the medium to long term as well, commercial bio-energy is expected to become increasingly important.
In the long-term, carbon will only be one of the goals that drive land-use decisions. Within each region, local solutions have to be found that optimize all goals and aim at integrated and sustainable land use. Developing the optimum regional strategies for climate change mitigation involving forests will require complex analyses of the trade-offs (synergies and competition) in land-use between forestry and other land uses, the trade-offs between forest conservation for carbon storage and other environmental services such as biodiversity and watershed conservation and sustainable forest harvesting to provide society with carbon-containing fibre, timber and bio-energy resources, and the trade-offs among utilization strategies of harvested wood products aimed at maximizing storage in long-lived products, recycling, and use for bioenergy.
Achard, F., H.D. Eva, P. Mayaux, H.-J. Stibig, and A. Belward, 2004: Improved estimates of net carbon emissions from land cover change in the Tropics for the 1990’s. Global Biogeochemical Cycles, 18, GB2008, doi:10.1029/2003GB002142. [JoC, MoS, SRC]
Albrecht, A. and S.T. Kandji, 2003: Carbon sequestration in tropical agroforestry systems. Agriculture, Ecosystems & Environment, 99(1-3), pp. 15-27. Clean
Alves, D.S., J.L.G. Pereira, C.L. de Sousa, J.V. Soares, and F. Yamaguchi, 1999: Characterizing landscape changes in central Rondonia using Landsat TM imagery. International Journal of Remote Sensing, 20, pp. 2877-2882. Clean
Atyi, R.E. and M. Simula, 2002: Forest certification: pending challenges for tropical timber. Tropical Forest Update, 12(3), pp. 3-5. Clean
Baldocchi, D., E. Falge, L. Gu, R. Olson, D. Hollinger, S. Running, P. Anthoni, Ch. Bernhofer, K. Davis, R. Evans, J. Fuentes, A. Goldstein, G. Katul, B. Law, X. Lee, Y. Malhi, T. Meyers, W. Munger, W. Oechel, K.T. Paw U, K. Pilegaard, H.P. Schmid, R. Valentini, S. Verma, T. Vesala, K. Wilson, and S. Wofsy, 2001: FLUXNET: A new tool to study the temporal and spatial variability of ecosystem-scale carbon dioxide, water vapor and energy flux densities. Bulletin of the American Meteorological Society, 82(11), pp. 2415-2434. Clean
Benítez-Ponce, P.C., I. Mc Callum, M. Obersteiner, and Y. Yamagata. 2004: Global supply for carbon sequestration: identifying least-cost afforestation sites under country risk considerations. IIASA Interim Report IR-04-022, Laxenburg, Austria. [NPR, SRC]
Benítez-Ponce, P.C., I. McCallum, M. Obersteiner, and Y. Yamagata. 2007: Global potential for carbon sequestration: geographical distribution, country risk and policy implications. Ecological Economics, 60, pp. 572-583. [SRC, 2007]
Bentancourt, K., M. Ibrahim, C. Harvey, and B. Vargas, 2003: Effect of tree cover on animal behavior in dual purpose cattle farms in Matiguas, Matagalpa, Nicaragua. Agroforestería en las Américas, 10, pp. 47-51. Clean
Betts, R.A., P.M. Cox, M. Collins, P.P. Harris, C. Huntingford, and C.D. Jones, 2004: The role of ecosystem-atmosphere interactions in simulated Amazonian precipitation decrease and forest dieback under global climate warming. Theoretical and Applied Climatology, 78(1-3), pp. 157-175. [MoS]
Bhat, D.M, K.S. Murali, and N.H. Ravindranath, 2001: Formation and recovery of secondary forests in india: A particular reference to western ghats in South India. Journal of Tropical Forest Science, 13(4), pp. 601-620. [SRC]
Brown, S., A. Dushku, T. Pearson, D. Shoch, J. Winsten, S. Sweet, and J. Kadyszewski, 2004: Carbon supply from changes in management of forest, range, and agricultural lands of California. Winrock International for California Energy Commission, 144 pp. + app. [NPR]
Cacho, O.J., R L. Hean, and R M. Wise, 2003: Carbon-accounting methods and reforestation incentives. The Australian Journal of Agricultural and Resource Economics, 47, pp. 153-179. Clean
Cannell, M.G.R., 2003: Carbon sequestration and biomass energy offset: theoretical, potential and achievable capacities globally, in Europe and the UK. Biomass and Bioenergy, 24, pp. 97-116. Clean
Caparros, A. and F. Jacquemont, 2003: Conflicts between biodiversity and carbon sequestration programs: economic and legal implications. Ecological Economics, 46, pp. 143-157. Clean
Carrasco-Letellier, L., G. Eguren, C. Castiñeira, O. Parra, and D. Panario, 2004: Preliminary study of prairies forested with Eucalyptus sp. at the Nortwestern Uruguayan soils. Environmental Pollution, 127, pp. 49-55. Clean
Caspersen, J.P., S.W. Pacala, J.C. Jenkins, G.C. Hurtt, P.R. Moorcroft, and R.A. Birdsey, 2000: Contributions of land-use history to carbon accumulation in U.S. forests. Science 290, pp. 1148-1151. [JoC]
Chen, W., J.M. Chen, D.T. Price, J. Cihlar, and J. Liu, 2000: Carbon offset potentials of four alternative forest management strategies in Canada: A simulation study. Mitigation and Adaptation Strategies for Global Change, 5, pp. 143-169. [MoS, SRC]
Chomitz, K.M., P. Buys, G. DeLuca, T.S. Thomas, and S. Wertz-Kanounnikoff, 2006: At Loggerheads? Agricultural expansion, poverty reduction, and the environment in the tropics. The World Bank, Washington, D.C., 284 pp. [NPR]
Ciais, P, P. Peylin P, and P. Bousquet, 2000: Regional biospheric carbon fluxes as inferred from atmospheric CO2 measurements. Ecological Applications, 10(6), pp. 1574-1589. Clean
Ciais, P., M. Reichstein, N. Viovy, A. Granier, J. Ogée, V. Allard, M. Aubinet, N. Buchmann, Chr. Bernhofer, A. Carrara, F. Chevallier, N. De Noblet, A.D. Friend, P. Friedlingstein, T. Grünwald, B. Heinesch, P. Keronen, A. Knohl, G. Krinner, D. Loustau, G. Manca, G. Matteucci, F. Miglietta, J.M. Ourcival, D. Papale, K. Pilegaard, S. Rambal, G. Seufert, J.F. Soussana, M.J. Sanz, E.D. Schulze, T. Vesala, and R. Valentini, 2005: Europe-wide reduction in primary productivity caused by the heat and drought in 2003. Nature (London), 437(7058), pp. 529-533. [JoC]
Clavijo, M., M. Nordenstahl, P. Gundel, and E. Jobbágy, 2005: Poplar afforestation effects on grasslands structure and composition in the flooding pampas. Rangeland Ecology & Management, 58, pp. 474-479. [SRC]
Cohen, D.H., L. Lee, and I. Vertinsky, 2002: China’s natural forest protection program (NFPP): impact on trade policies regarding wood. Prepared for CIDA with the Research Center for Ecological and Environmental Economics, Chinese Academy of Social Sciences, 63 pp. [NPR]
Couto, L. and R. Betters, 1995: Short-rotation eucalypt plantations in Brazil: social and environmental issues. ORNL/TM-12846. Oak Ridge National Laboratory, Oak Ridge, Tennessee. <http://bioenergy.ornl.gov/reports/euc-braz/index.html>. accessed 20 September 2005. [NPR]
Cox, P.M., R.A. Betts, M. Collins, P.P. Harris, C. Huntingford, and C.D. Jones, 2004: Amazonian forest dieback under climate-carbon cycle projections for the 21st century. Theoretical and Applied Climatology, 78, pp. 137-156. [MoS]
Cuiping, L., Yanyongjie, W. Chuangzhi, and H. Haitao: Study on the distribution and quantity of biomass residues resource in China. Biomass and Bioenergy 2004, 27, pp. 111-117. Clean
Dang, H.H., A. Michaelowa, and D.D. Tuan, 2003: Synergy of adaptation and mitigation strategies in the context of sustainable development: in the case of Vietnam. Climate Policy, 3S1, pp. S81- S96. [JoC, ARC]
De Jong, B.H.J., E.E. Bazán, and S.Q. Montalvo, 2007 (in print): Application of the Climafor baseline to determine leakage: The case of Scolel Té. Mitigation and Adaptation Strategies for Global Change. [NPR, 2007]
DeFries, R., F. Achard, S. Brown, M. Herold, D. Murdiyarso, B. Schlamadinger, and C. DeSouza, 2006: Reducing greenhouse gas emissions from deforestation in developing countries: Considerations for monitoring and measuring. Report of the Global Terrestrial Observing System (GTOS) number 46, GOFC-GOLD report 26, 23 pp.<www.fao.org/gtos/pubs.html> accessed 11 June 2007. [NPR, SRC]
Denman, K.L., G. Brasseur, A. Chidthaisong, Ph. Ciais, P. Cox, R.E. Dickinson, D. Hauglustaine, C. Heinze, E. Holland, D. Jacob, U. Lohmann, S. Ramachandran, P.L. da Silva Dias, S.C. Wofsy, X. Zhang, 2007: Couplings Between Changes in the Climate System and Biogeochemistry, Chapter 7 in: Climate Change 2007: The Physical Science Basis, The IPCC Fourth Assessment Report, Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge. [NPR, SRC, 2007]
Dutschke, M., B. Schlamadinger, J.L.P. Wong, and M. Rumberg, 2005: Value and risks of expiring carbon credits from affor-estation and reforestation projects under the CDM. Climate Policy, 5(1). [JoC, SRC]
Easterling, W., P. Aggarwal, P. Batima, K. Brander, L. Erda, M. Howden, A. Kirilenko, J. Morton, J.F. Soussana, J. Schmidhuber, F. Tubiello, Food, Fibre, and Forest Products, Chapter 5 in: Climate Change 2007: Climate Change Impacts, Adaptation and Vulnerability, The IPCC Fourth Assessment Report, Cambridge University Press, Cambridge. [NPR, ARC, 2007]
Eggers, J., M. Lindner, S. Zudin, S. Zaehle, J. Liski, and G.J. Nabuurs, 2007. Forestry in Europe under changing climate and land use. Proceedings of the OECD Conference ‘Forestry: A Sectoral Response to Climate Change’, 21-23 November 2006. In: P. Freer-Smith (ed.), Forestry Commission, UK. [NPR, ARC, 2007]
Enters, T., P.B. Durst, G.B. Applegate, P.C.S. Kho, G. Man, T. Enters, P.B. Durst, G.B. Applegate, P.C.S. Kho, and G. Man, 2002: Trading forest carbon to promote the adoption of reduced impact logging, Applying reduced impact logging to advance sustainable forest management. International conference proceedings, Kuching, Malaysia, RAP-Publication, pp. 261-274. [NPR]
Ericcson, K. and L.J. Nilsson, 2006: Assessment of the potential biomass supply in Europe using a resource-focused approach. Biomass and Bioenergy, 30(1), pp. 1-15. Clean
FAO, 2006b: Summaries of FAO’s work in forestry. Rome, Italy. <http://www.fao.org/forestry/foris/webview/forestry2/index.jsp?siteId=3741&sitetreeId=11467&langId=1&geoId=0> accessed 27 October 2006. [NPR]
Farley, K., E.G. Jobbágy and R.B. Jackson, 2004: Effects of afforestation on water yield: a global synthesis with implications for policy. Center on Global Change, Duke University, Durham. Department of Biology and Nicholas School of the Environment and Earth Sciences, Duke University, Durham. Grupo de Estudios Ambientales - IMASL, Universidad Nacional de San Luis & CONICET, Argentina. [NPR, SRC]
Fearnside, P.M. and W.F. Laurance, 2004: Tropical deforestation and greenhouse-gas emissions. Ecological Applications, 14(4), pp. 982-986. Clean
Fischer, G. and L. Schrattenholzer, 2001: Global bioenergy potentials through 2050. Biomass and Bioenergy, 20, pp. 151-159. Clean
Fischlin, A., G.F. Midgley, J. Price, R. Leemans, B. Gopal, C. Turley, M. Rounsevell, P. Dube, J. Tarazona, A. Velichko, 2007: Ecosystems, their Properties, Goods, and Services, Chapter 4 in: Climate Change 2007: Climate Change Impacts, Adaptation and Vulnerability, The IPCC Fourth Assessment Report, Cambridge University Press, Cambridge. [NPR, 2007]
Fuhrer, J., M. Benitson, A. Fischlin, C. Frei, S. Goyettte, K. Jasper, and C. Pfister, 2007: Climate risks and their impact on agriculture and forests in Switzerland. Climatic change, 72 (accepted in print). [NPR, 2007]
Gaddis, D.A., B.D. New, F.W. Cubbage, R.C. Abt, and R.J. Moulton, 1995: Accomplishments and economic evaluations of the Forestry Incentive Program: a review. SCFER Working Paper (78), pp. 1-52. Southeastern Center for Forest Economics Research, Research Triangle Park, NC. [NPR]
Geist, H.J. and E.F. Lambin, 2002: Proximate causes and underlying driving forces of tropical deforestation. BioScience, 52, pp. 143-150. Clean
Gobbi, J., 2003: Financial behavior of investment in sylvopastoral systems in cattle farms of Esparza, Costa Rica. Agroforestería en las Américas, 10, pp. 52-60. Clean
Government of Australia, 2006: Biofuels Capital Grants (BCG) - Fact Sheet. <http://www.ausindustry.gov.au/content/content.cfm?ObjectID=8B98D9B4-D244-43EF-A4AA7D42B39DFE1B> accessed 27 October 2006. [NPR]
Granger, A., 1997: Bringing tropical deforestation under control change programme. Global environmental change programme briefings, Number 16. Economic and Social Research Council, Global Environmental Change Programme, Sussex, U.K., 4 pp. <http://www.sussex.ac.uk/Units/gec/pubs/briefing/brief-16.pdf> accessed 1 September 2005. [NPR]
Grassl, H., J. Kokott, M. Kulessa, J. Luther, F. Nuscheler, R. Sauerborn, H.-J. Schellnhuber, R. Schubert, and E.-D. Schulze: 2003. Climate protection strategies for the 21st century: Kyoto and beyond. Berlin: German Advisory Council on Global Change (WBGU). [NPR]
Grieg-Gran, M., 2004: Making environmental service payments work for the poor: some experiences from Latin America. International Fund for Agricultural Development Governing Council Side Event. <www.ifad.org/events/gc/27/side/presentation/ieed.ppt> accessed 1 September 2005. [NPR]
Gurney, K.R., R.M. Law, A.S. Denning, P.J. Rayner, D. Baker, P. Bousquet, L. Bruhwiler, Y-H. Chen, P. Ciais, S. Fan, I.Y. Fung, M. Gloor, M. Heimann, K. Higuchi, J. John, T. Maki, S. Maksyutov, K. Masarie, P. Peylin, M. Prather, B.C. Pak, J. Randerson, J. Sarmiento, S. Taguchi, T. Takahashi, and C-W. Yuen, 2002: Towards robust regional estimates of CO2 sources and sinks using atmospheric transport models. Nature, 415, pp. 626-629. [JoC, MoS]
Gustavsson, L. and R. Sathre, 2006: Variability in energy and carbon dioxide balances of wood and concrete building materials. Building and Environment, 41, pp. 940-951. Clean
Gustavsson, L., K. Pingoud, and R. Sathre, 2006: Carbon dioxide balance of wood substitution: comparing concrete and wood-framed buildings. Mitigation and Adaptation Strategies for Global Change, 11, pp. 667-691. Clean
Heistermann, M., C. Müller, and K. Ronneberger, 2006: Review land in sight? Achievements, deficits and potentials of continental to global scale land-use modelling. Agriculture, Ecosystems and Environment, 114(2006), pp. 141-158. [MoS]
Hirata, Y., Y. Akiyama, H. Saito, A. Miyamoto, M. Fukuda, and T. Nisizono, 2003: Estimating forest canopy structure using helicopter-borne LIDAR measurement. P. Corona et al. (eds), Advances in forest inventory for sustainable forest management and biodiversity monitoring, Kluwer Academic Publishers, pp. 125-134. [NPR, MoS]
Hoen, H.F. and B. Solberg, 1994: Potential and efficiency of carbon sequestration in forest biomass through silvicultural management. Forest Science, 40, pp. 429-451. Clean
Holmes, T.P., G.M. Blate, J.C. Zweede, R. Pereira Jr., P. Barreto, F. Boltz, and R. Bauch, 2002: Financial and ecological indicators of reduced impact logging performance in the eastern Amazon. Forest Ecology and Management, 163, pp. 93-110. Clean
Hooda, N., M. Gera, K. Andrasko, J.A. Sathaye, M.K. Gupta, H.B. Vasistha, M. Chandran, and S.S. Rassaily, 2007: Community and farm forestry climate mitigation projects: case studies from Uttaranchal, India. Mitigation and Adaptation Strategies for Global Change. 12(6) pp. 1099-1130. [SRC, 2007]
Houghton, R.A., 2005: Aboveground forest biomass and the global carbon balance. Global Change Biology, 11(6), pp. 945-958. Clean
Houghton, R.A., 2003b: Revised estimates of the annual net flux of carbon to the atmosphere from changes in land use and land management 1850-2000. Tellus Series B Chemical and Physical Meteorology, 55(2), pp. 378-390. [MoS]
Houghton, R.A., D.L. Skole, C.A. Nobre, J.L. Hackler, K.T. Lawrence, and W.H. Chomentowski, 2000: Annual fluxes or carbon from deforestation and regrowth in the Brazilian Amazon. Nature, 403, pp. 301-304. [JoC]
Ikkonen, E.N., V.K. Kurets, S.I. Grabovik, and S.N. Drozdov, 2001: The rate of carbon dioxide emission into the atmosphere from a southern Karelian mesooligotrophic bog. Russian Journal of Ecology, 32(6), pp. 382-385. Clean
IPCC, 2001: Climate Change 2001: Synthesis Report. A Contribution of Working Groups I, II, and III to the Third Assessment Report of the Intergovernmental Panel on Climate Change [Watson, R.T. and the Core Writing Team (eds.)]. Cambridge University Press, Cambridge, United Kingdom, and New York, NY, USA, 398 pp. [NPR]
IPCC, 2006: 2006 IPCC guidelines for national greenhouse gas inventories. Prepared by the National Greenhouse Gas Inventories Programme [Eggleston H.S., L. Buenia, K. Miwa, T. Ngara, and K. Tanabe (eds)]. IPCC-IGES, Japan. [NPR]
IPCC, 2007a: Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change [Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K.B.M.Tignor and H.L. Miller (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 996 pp. [NPR, 2007]
IPCC, 2007b: Climate Change 2007: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change [Parry, M.L., O.F. Canziani, J.P. Palutikof, P.J. van der Linden, C.E. Hanson (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA. [NPR, 2007]
ITTO, 1999: International cross sectoral forum on forest fire management in South East Asia. International Tropical Timber Organization, Jakarta, Indonesia, 7 And 8 December 1998. Report of the Meeting. <http://www.fire.uni-freiburg.de/programmes/itto/cross.pdf> accessed 12 April 2006. [NPR]
Izrael, Y.A., M.L. Gytarsky, R.T. Karaban, A.L. Lelyakin, and I.M. Nazarov: 2002: Consequences of climate change for forestry and carbon dioxide sink in Russian forests. Izvestiya, Atmospheric and Oceanic Physics, 38(Suppl. 1), pp. S84-S98. Clean
Jackson, R.B., E.G. Jobbágy, R Avissar, S. Baidya Roy, D.J. Barrett, Ch.W. Cook, K.A. Farley, D.C. le Maitre, B.A. McCarl, and B.C. Murray, 2005: Trading water for carbon with biological carbon sequestration. Science, 310, pp. 1944-1947. [JoC, SRC]
Janssens, I.A., A. Freibauer, P. Ciais, P. Smith, G.-J. Nabuurs, G. Folberth, B. Schlamadinger, R.W.A. Hutjes, R. Ceulemans, E.-D. Schulze, R. Valentini, and A.J. Dolman, 2003: Europe’s terrestial biosphere absorbs 7 to 12% of European anthropogenic CO2 emissions. Science, 300, pp. 1538-1542. [JoC, SRC]
Jung, M., 2005: The role of forestry sinks in the CDM-analysing the effects of policy decisions on the carbon market. HWWA discussion paper 241, Hamburg Institute of International Economics, 32 pp. [NPR]
Karjalainen, T. and A. Asikainen, 1996: Greenhouse gas emissions from the use of primary energy in forest operations and long-distance transportation of timber in Finland, Forestry, 69, pp. 215-228. [SRC]
Karjalainen, T., A. Pussinen, J. Liski, G.-J. Nabuurs, T. Eggers, T. Lapvetelainen, and T. Kaipainen, 2003: Scenario analysis of the impacts of forest management and climate change on the European forest sector carbon budget. Forest Policy and Economics, 5, pp. 141-155. [SRC]
Katila, M. and E. Puustjärvi, 2004: Markets for forests environmental services: reality and potential. Unasylva, 219(55, 2004/4), pp.53-58. Clean
Kauppi, P., R.J. Sedjo, M. Apps, C. Cerri, T. Fujimori, H. Janzen, O. Krankina, W. Makundi, G. Marland, O. Masera, G.J. Nabuurs, W. Razali, and N.H. Ravindranath, 2001: Technical and economic potential of options to enhance, maintain and manage biological carbon reservoirs and geo-engineering. In Mitigation 2001. The IPCC Third Assessment Report, [Metz, B., et al., (eds.)], Cambridge, Cambridge University Press. [NPR, SRC]
Klein, R.J.T., S. Huq, F. Denton, T. Downing, R.G. Richels, J.B. Robinson, F.L. Toth, 2007: Inter-relationships between Adaptation and Mitigation, Chapter 18 in: Climate Change 2007: Climate Change Impacts, Adaptation and Vulnerability, The IPCC Fourth Assessment Report, Cambridge University Press, Cambridge. [NPR, ARC, 2007]
Koopman, A., 2005: Biomass energy demand and supply for South and South-East Asia - assessing the resource base. Biomass and Bioenergy, 28, pp 133-150. Clean
Körner, C., 2004: Through enhanced tree dynamics carbon dioxide enrichment may cause tropical forests to lose carbon. Philosophical transactions of the Royal Society of London - Series A, 359(1443), pp. 493-498. Clean
Kurz, W.A. and M.J. Apps, 2006: Developing Canada’s national forest carbon monitoring, Accounting and reporting system to meet the reporting requirements of the Kyoto Protocol. Mitigation and Adaptation Strategies for Global Change, 11, pp. 33-43. [SRC]
Kurz, W.A., S.J. Beukema, and M.J. Apps, 1998: Carbon budget implications of the transition from natural to managed disturbance regimes in forest landscapes. Mitigation and Adaptation Strategies for Global Change, 2, pp. 405-421. [SRC]
Lasco, R.D., F.B. Pulhin, and R.F. Sales, 2007 (accepted, in print): An analysis of a forestry carbon sequestration project in the Philippines: the case of upper Magat watershed. Mitigation and Adaptation Strategies for Global Change. [NPR, 2007]
Lewandrowski, J., M. Peters, C. Jones, R. House, M. Sperow, M. Eve, and K. Paustian, 2004: Economics of Sequestering Carbon in the U.S. Agricultural Sector. Technical Bulletin, TB1909, 69 pp. Clean
Lewis, S., O. Phillips, T. Baker, Y. Malhi, and J. Lloyd, 2005: Tropical forests and atmospheric carbon dioxide: Current knowledge and potential future scenarios. Oxford University Press, 260 pp. [NPR, MoS]
Lindner, M., J. Meyer, Th. Eggers, and A. Moiseyev, 2005: Environmentally enhanced bio-energy potential from European forests. A report commissioned by the European Environment Agency through the European Topic Centre on Biodiversity, Paris. European Forest Institute, Joensuu, Finland. [NPR]
MAF, 2006: The permanent forest sink initative. Bulletin Issue 3, December 2006. Ministry of Agriculture and Forestry, Wellington, New Zealand. <http://www.maf.govt.nz/forestry/pfsi/bulletin/issue-3/index.htm> accessed 11 June 2007. [NPR]
Marland, G., R.A. Pielke Sr, M. Apps, R. Avissar, R.A. Betts, K.J. Davis, P.C. Frumhoff, S.T. Jackson, L.A. Joyce, P. Kauppi, J. Katzenberger, K.G. MacDicken, R.P. Neilson, J.O. Niles, D.D.S. Niyogi, R.J. Norby, N. Pena, N. Sampson, and Y. Xue, 2003: The climatic impacts of land surface change and carbon management, and the implications for climate-change mitigation policy. Climate Policy, 3, pp. 149-157. [JoC, SRC]
Masera, O.R., J.F. Garza Caligaris, M. Kanninen, T. Karjalainen, J. Liski, G.J. Nabuurs, A. Pussinen, B.H.J.d. Jong, G.M.J. Mohren, and B.H.J. de Jong, 2003, Modelling carbon sequestration in afforestation, agroforestry and forest management projects: the CO2FIX V.2 approach. Ecological modeling, 164, pp. 177-199. [NPR, MoS, SRC]
Masera, O.R., R. Díaz, and V. Berrueta, 2005: From cookstoves to cooking systems: The integrated program on sustainable household energy use in Mexico. Energy for Sustainable Development, 9(5), pp. 25-36. [SRC]
McGinley, K. and B. Finegan, 2003: The ecological sustainability of tropical forest management: evaluation of the national forest management standards of Costa Rica and Nicaragua, with emphasis on the need for adaptive management. Forest Policy and Economics, 5(2003), pp. 421-431. Clean
Mertens, B., D. Kaimowitz, A. Puntodewo, J. Vanclay, and P. Mendez, 2004: Modeling deforestation at distinct geographic scales and time periods in Santa Cruz, Bolivia. International Regional Science Review, 27(3), pp. 271-296. [MoS]
MfE, 2002: National Communication 2001: New Zealand’s Third National Communication under the Framework Convention on Climate Change. Ministry for the Environment, Wellington, NZ. <http://www.climatechange.govt.nz/resources/reports/index.html> accessed 11 June 2007. [NPR]
MfE, 2005: Projected balance of units during the first commitment period of the Kyoto Protocol. Ministry for the Environment, Wellington, NZ. <http://www.climatechange.govt.nz/resources/reports/index.html> accessed 11 June 2007. [NPR]
Micales, J.A. and K.E. Skog, 1997: The decomposition of forest products in landfills. International Biodeterioration & Biodegradation, 39(2-3), pp. 145-158. Clean
Minkkinen, K., R. Korhonen, I. Savolainen, and J. Laine, 2002: Carbon balance and radiative forcing of Finnish peatland 1900-2100, the impacts of drainage. Global Change Biology, 8, pp. 785-799. [MoS]
Murdiyarso, D., 2005: Linkages between mitigation and adaptation in land-use change and forestry activities. In Tropical forests and adaptation to climate change: In search of synergies. C. Robledo, C. Kanninen, and L. Pedroni (eds.). Bogor, Indonesia: Center for International Forestry Research (CIFOR), 186 pp. [NPR]
Murphy, R., 2004: Timber and the circle of life. ITTO. Tropical Forest Update, 14(3), pp. 12-14. Clean
Nabuurs, G.J., I.J.J. van den Wyngaert, W.D. Daamen, A.T.F. Helmink, W.J.M. de Groot, W.C. Knol, H. Kramer, and P.J. Kuikman, 2005: National system of greenhouse gas reporting for forest and nature areas under UNFCCC in the Netherlands Wageningen: Alterra, 2005 (Alterra-rapport 1035.1), 57 pp. [NPR, ARC]
Nabuurs, G.J., J. van Brusselen, A. Pussinen, and M.J. Schelhaas, 2006: Future harvesting pressure on European forests. European Journal of Forest Research, 126 (3) pp. 401-412. doi: 10.1007/s10342-006-0158-y. [MoS, ARC]
Niesten, E., P.C. Frumhoff, M. Manion, and J.J. Hardner, 2002: Designing a carbon market that protects forests in developing countries. Philosophical Transactions of the Royal Society, London A, pp. 1875-1888. [NPR, SRC]
Nilsson, S., E.A. Vaganov, A.Z. Shvidenko, V. Stolbovoi, V.A. Rozhkov, I. MacCallum, and M. Ionas, 2003: Carbon budget of vegetation ecosystems of Russia. Doklady Earth Sciences, 393A(9), pp. 1281-1283. Clean
Ohtani, Y., N. Saigusa, S. Yamamoto, Y. Mizoguchi, T. Watanabe, Y. Yasuda, and S. Murayama, 2005: Characteristics of CO2 fluxes in cool-temperate coniferous and deciduous broadleaf forests in Japan. Phyton, 45, pp. 73-80. Clean
Olivier, J.G.J., J.A. Van Aardenne, F. Dentener, V. Pagliari, L.N. Ganzeveld, and J.A.H.W. Peters, 2005: Recent trends in global greenhouse gas emissions: regional trends 1970-2000 and spatial distribution of key sources in 2000. Environmental Science, 2(2-3), pp. 81-99. [ARC]
Orlove, B., 2005: Human adaptation to climate change: a review of three historical cases and some general perspectives. Environmental Science & Policy, 8(6), pp. 589-600. Clean
Pacala, S.W., G.C. Hurtt, D. Baker, P. Peylin, R.A. Houghton, R.A. Birdsey, L. Heath, E.T. Sundquist, R.F. Stallard, P. Ciais, P. Moorcroft, J.P. Caspersen, E. Shevliakova, B. Moore, G. Kohlmaier, E. Holland, M. Gloor, M.E. Harmon, S.-M. Fan, J.L. Sarmiento, C.L. Goodale, and D. Schimel, 2001: Consistent land- and atmosphere-based U.S. carbon sink estimates. Science: 292, pp. 2316-2320. [JoC, MoS]
Pan, Y., T. Luo, R. Birdsey, J. Hom, and J. Melillo, 2004: New estimates of carbon storage and sequestration in China’s forests: effects of age-class and method on inventory-based carbon estimation. Climatic Change, 67(2), pp. 211-236. [JoC, MoS]
Parris, K., 2004: Agriculture, biomass, sustainability and policy: an overview. In Biomass and agriculture: sustainability, markets and policies. K. Parris and T. Poincet (eds.), OECD Publication Service, Paris, pp. 27-36. [NPR]
Parrotta, J.A., 2002: Restoration and management of degraded tropical forest landscapes. In Modern Trends in Applied Terrestrial Ecology. R.S. Ambasht and N.K. Ambasht (eds.), Kluwer Academic/Plenum Press, New York, pp. 135-148 (Chapter 7). [NPR]
Paul, K.I., P.J. Polglase, and G.P. Richards, 2003: Predicted change in soil carbon following afforestation or reforestation, and analysis of controlling factors by linking a C accounting model (CAMFor) to models of forest growth (3PG), litter decomposition (GENDEC) and soil C turnover (RothC). Forest Ecology and Management, 177, 485 pp. [MoS]
Pérez Bidegain, M., P.F. García, and R. Methol, 2001: Long-term effect of tillage intensity for Eucalyptus grandis planting on some soil physical properties in an Uruguayan Alfisol. 3rd International Conference on Land Degradation and Meeting of IUSS Subcommission C-Soil and Water Conservation. September 17-21 2001- Rio de Janeiro - Brazil. [NPR]
Petersen, A.K. and B. Solberg, 2002: Greenhouse gas emissions, life-cycle inventory and cost-efficiency of using laminated wood instead of steel construction. - Case: beams at Gardermoen airport. Environmental Science and Policy, 5, pp. 169-182. Clean
Plattner, G.-K., F. Joos, and T.F. Stocker, 2002: Revision of the global carbon budget due to changing air-sea oxygen fluxes. Global Biogeochemical Cycles, 16(4), 1096 pp., doi:10.1029/2001GB001746. [PoC, JoC]
Post, W.M. and K.C. Kwon, 2000: Soil carbon sequestration and land-use change: processes and potential. Global Change Biology, 6, pp. 317-328. Clean
Potter, C., S. Klooster, R. Myneni, V. Genovese, P.N. Tan, and V. Kumar, 2003: Continental-scale comparisons of terrestrial carbon sinks estimated from satellite data and ecosystem modeling 1982-1998. Global and Planetary Change, 39(3-4), pp. 201-213. [MoS]
Ravindranath, N.H., I. K. Murthy, P. Sudha, V. Ramprasad, M.D.V. Nagendra, C.A. Sahana, K.G. Srivathsa, and H. Khan, 2007: Methodological issues in forestry mitigation projects: A case study of Kolar district. Mitigation and Adaptation Strategies for Global Change, 12 (6) pp. 1077-1098. [SRC, 2007]
Riahi, K., A. Gruebler, and N. Nakicenovic, 2006: Scenarios of long-term socio-economic and environmental development under climate stabilization. Technological Forecasting and Social Change, Special Issue. [NPR, MoS, ARC]
Richards, G.P. and C. Brack: A modelled carbon account for Australia’s post-1990 plantation estate. Australian Forestry, 67(4), pp. 289-300. Clean
Richey, J.E., J.M. Melack, A.K. Aufdenkampe, V.M. Ballester, and L.L. Hess, 2002: Outgassing from Amazonian rivers and wetlands as a large tropical source of atmospheric CO2. Nature, 416(6881), pp. 617-620. [JoC]
Robledo, C., C. Kanninen, and L. Pedroni (eds.), 2005: Tropical forests and adaptation to climate change. In search of synergies. Bogor, Indonesia: Center for International Forestry Research (CIFOR), 186 pp. [NPR]
Rodenbeck, C., S. Houweling, M. Gloor, and M. Heimann, 2003: CO2 flux history 1982-2001 inferred from atmospheric data using a global inversion of atmospheric transport. Atmospheric Chemistry and Physics, 3, pp. 1919-1964. Clean
Rose, S., H. Ahammad, B. Eickhout, B. Fisher, A. Kurosawa, S. Rao, K. Riahi, and D. van Vuuren, 2007: Land in climate stabilization modeling: Initial observations. Energy Modeling Forum Report, Stanford University, <http://www.stanford.edu/group/EMF/projects/group21/EMF21sinkspagenew.htm> accessed January 2007. [NPR, MoS, SRC, 2007]
Rosenbaum, K.L., D. Schoene, and A. Mekouar, 2004: Climate change and the forest sector: possible national and subnational legislation. Food and Agriculture Organization of the United Nations, Rome, 60 pp. [NPR]
Sathaye, J.A., W. Makundi, L. Dale, P. Chan and K. Andrasko, 2007: GHG mitigation potential, costs and benefits in global forests: A dynamic partial equilibrium approach. Energy Journal, Special Issue 3, pp. 127-172. [SRC, 2007]
Sathaye, J.A. and K. Andrasko, 2007: Special issue on estimation of baselines and leakage in carbon mitigation forestry projects: Editorial. Mitigation and Adaptation Strategies for Global Change, 12(6) pp. 963-970. [MoS, SRC, 2007]
Schimel, D.S., J.I. House, K.A. Hibbard, P. Bousquet, P. Ciais, P. Peylin, B.H. Braswell, M.J. Apps, D. Baker, A. Bondeau, J. Canadell, G. Churkina, W. Cramer, A.S. Denning, C.B. Field, P. Friedlingstein, C. Goodale, M. Heimann, R.A. Houghton, J.M. Melillo, B. III, Moore., D. Murdiyarso, I. Noble, S.W. Pacala, I.C. Prentice, M.R. Raupach, P.J. Rayner, R.J. Scholes, W.L. Steffen, and C. Wirth, 2001: Recent patterns and mechanisms of carbon exchange by terrestrial ecosystems. Nature, 414(6860), pp. 169-172. [JoC, SRC]
Schlamadinger, B., L. Ciccarese, M. Dutschke, P.M. Fearnside, S. Brown, and D. Murdiyarso, 2005: Should we include avoidance of deforestation in the international response to climate change? In Carbon forestry: who will benefit? D. Murdiyarso, and H. Herawati (eds.). Proceedings of Workshop on Carbon Sequestration and Sustainable Livelihoods, held in Bogor on 16-17 February 2005. Bogor, Indonesia, CIFOR, pp. 26-41. [NPR, SRC]
Schröter, D., W. Cramer, R. Leemans, I.C. Prentice, M.B. Araujo, N.W. Arnell, A. Bondeau, H. Bugmann, T.R. Carter, C.A. Gracia, A.C. Dela Vega-Leinert, M.J. Metxger, J. Meyer, T.D. Mitchell, I. Reginster, M. Rounsevell, S. Sabate, S. Sitch, B. Smith, J. Smith, P. Smith, M.T. Sykes, K. Thonicke, W. Thuiller, G. Tuck, S. Zaehle, and B. Zierl, 2005: Ecosystem service supply and vulnerability to global change in Europe. Science, 310(5752), pp. 1333-1337. [JoC, ARC]
Schwarze, R., J.O. Niles, and J. Olander, 2003: Understanding and managing leakage in forest-based green-house-gas-mitigation projects. Capturing carbon and conserving biodiversity: The market approach. I.R. Swingland, London, The Royal Society. [NPR]
Shvidenko, A. and S. Nilsson, 2003: A synthesis of the impact of Russian forests on the global carbon budget for 1961-1998. Tellus Series B, 55(2), pp. 391-415. Clean
Shvidenko A., Nilsson S., Rozhkov V.A. 1997. Possibilities for increased carbon sequestration through the implementation of rational forest management in Russia. Water, Air & Soil Pollution, 94:137-162 [NPR]
Sicardi, M., F. García-Prechac, and L. Fromi, 2004: Soil microbial indicators sensitive to land use conversion from pastures to commercial Eucalyptus grandis (Hill ex Maiden) plantations in Uruguay. Applied Soil Ecology, 27, pp. 125-133. Clean
Sizer, N., D. Downes, and D. Kaimowitz, 1999: Tree trade - liberalization of international commerce in forest products: risks and opportunities. World Resources Institute Forest Notes, Washington, D.C., 24 pp. [NPR]
Sizer, N., S. Bass, and J. Mayers (Coordinating Lead Authors), 2005: Wood, fuelwood and non-wood forest products. In Millennium Ecosystem Assessment, 2005: Policy Responses: Findings of the Responses Working Group. Ecosystems and Human Well-being, 3, pp. 257-293. Island Press, Washington, D.C. Clean
Smeets, E.M.W. and A.P.C. Faaij, 2007: Bioenergy potentials from forestry in 2050, an assessment of drivers that determine the potential. <http://www.bioenergytrade.org/downloads/smeetsandfaaijbioenergyfromforestryclimaticcha.pdf> accessed 11 June 2007. [NPR, ARC, 2007]
Soares-Filho, B.S., D. Nepstad, L. Curran, E. Voll, G. Cerqueira, R.A. Garcia, C.A. Ramos, A. Mcdonald, P. Lefebvre, and P. Schlesinger, 2006: Modelling conservation in the Amazon basin. Nature, 440, pp. 520-523. [JoC, MoS]
Sohngen, S., K. Andrasko, M. Gytarsky, G. Korovin, L. Laestadius, B. Murray, A. Utkin, and D. Zamolodchikov, 2005: Stocks and flows: carbon inventory and mitigation potential of the Russian forest and land base. Report of the World Resources Institute, Washington D.C. [NPR, SRC]
Spittlehouse, D.L. and R.B. Stewart, 2003: Adaptation to climate change in forest management. Journal of Ecosystems and Management, 4, pp. 1-11. Clean
Tate, K.R., R.H. Wilde, D.J. Giltrap, W.T. Baisden, S. Saggar, N.A. Trustrum, N.A. Scott, and J.R. Barton, 2005: Soil organic carbon stocks and flows in New Zealand: System development, measurement and modelling. Canadian Journal of Soil Science, 85(4), pp. 481-489. [MoS]
Tol, R.S.J., 2006: Adaptation and mitigation: trade-offs in substance and methods. Environmental Science & Policy, 8, pp. 572-578. Clean
Trines, E., N. Höhne, M. Jung, M. Skutsch, A. Petsonk, G. Silva-Chavez, P. Smith, G.-J. Nabuurs, P. Verweij, B. and Schlamadinger, 2006: Integrating agriculture, forestry and other land use in future climate regimes: Methodological issues and policy options. WAB Report 500101002. Netherlands Environmental Assessment Agency, Bilthoven, the Netherlands. [NPR, MoS, SRC]
Trotter, C., K. Tate, N. Scott, J. Townsend, H. Wilde, S. Lambie, M. Marden, and T. Pinkney, 2005: Afforestation/reforestation of New Zealand marginal pasture lands by indigenous shrublands: the potential for Kyoto forest sinks. Annals of Forest Science, 62, pp. 865-871. Clean
UN-ECE/FAO, 2000: Forest Resources of Europe, CIS, North America, Australia, Japan and New Zealand (industrialized temperate/boreal countries), UN-ECE/FAO Contribution to the Global Forest Resources Assessment 2000. United Nations, New York, NY, USA and Geneva, Switzerland. Geneva Timber and Forest Study Papers, 17, 445 pp. Clean
UNFCCC, 2006: Background paper for the Workshop on Reducing Emissions from Deforestation in Developing Countries, Part I: Scientific, socio-economic, technical and methodological issues related to deforestation in developing countries. Working paper No. 1 (a), 30 August-1 September, Rome, Italy. [NPR]
USDA Forest Service, 2000: Protecting people and sustaining resources in rire-adapted ecosystems: A cohesive strategy, the Forest Service Management response to the General Accounting Office report GAO/RCED-99-65. 13 October, US Department of Agriculture (USDA) Forestry Service, Washington, D.C., pp. 85. [NPR]
Verchot, L.V., J. Mackensen, S. Kandji, M. van Noordwijk, T. Tomich, C. Ong, A. Albrecht, C. Bantilan, K.V. Anupama, and C. Palm, 2006: Opportunities for linking adaptation and mitigation in agroforestry systems. In Tropical forests and adaptation to climate change: In search of synergies, C. Robledo, M. Kanninen, L. Pedroni (eds.), Bogor, Indonesia: Center for International Forestry Research (CIFOR). [NPR]
Viner, D., M. Sayer, M. Uyarra, and N. Hodgson, 2006: Climate change and the European countryside: Impacts on land management and response strategies. Report prepared for the Country Land and Business Association., UK Publishing CLA, UK, 180 pp. [NPR]
Vuuren, D. Van, M. den Elzen, P. Lucas, B. Eickhout, B. Strengers, B van Ruijven, S. Wonink, and R. van Houdt, 2007: Stabilizing greenhouse gas concentrations at low levels: an assessment of reduction strategies and costs. Climatic Change, 81 (2) pp. 119-159. [JoC, SRC, 2007]
Wagner, R.G., K.M. Little, B. Richardson, and K. Mcnabb, 2006: The role of vegetation management for enhancing productivity of the world’s forests. Forestry, 79(1), pp. 57-79. Clean
Walsh, M.E., L.R. Perlack, A. Turhollow, D. de la Torre Ugarte, D.A. Becker, R.L. Graham, S.E. Slinsky, and D.E. Ray, 2000: Oak Ridge National Laboratory, Biomass Feedstock Availability in the United States: 1999 State Level Analysis, April 30, 1999, updated January, 2000: Oak Ridge, TN 37831-6205. [NPR]
Waterloo, M.J., P.H. Spiertz, H. Diemont, I. Emmer, E. Aalders, R. Wichink-Kruit, and P. Kabat, 2003: Criteria potentials and costs of forestry activities to sequester carbon within the framework of the Clean Development Mechanism. Alterra Rapport 777, Wageningen, 136 pp. [NPR]
WBOED, 2000: Striking the right balance: World Bank forest strategy. World Bank Operations Evaluation Department, Precis, 203, 6 pp. Clean
Wear, D. and B.C. Murray, 2004: Federal timber restrictions, interregional spillovers, and the impact on U.S. softwood markets. Journal of Environmental Economics and Management, 47(2), pp. 307-330. Clean
Werf, G.R van der, J.T. Randerson, G.J. Collatz, L. Giglio, P.S. Kasibhatla, A.F. Arellano Jr., S.C. Olsen, E.S. Kasischke, 2004: Continental-scale partitioning of fire emissions during the 1997 to 2001 El Niño/ La Niña period. Science, 303, pp. 73-76. [JoC]
Williams, R.H., 1995: Variants of a low CO2-emitting energy supply system (LESS) for the world - prepared for the IPCC Second Assessment Report Working Group IIa, Energy Supply Mitigation Options, Richland: Pacific Northwest Laboratories, 39 pp. [NPR]
Williams, J., 2002: Financial and other incentives for plantation establishment. Proceedings of the International Conference on Timber Plantation Development. <http://www.fao.org/documents/show_cdr.asp?url_file=//docrep/005/ac781e/AC781E00.htm>. accesssed 1 September 2005. [NPR]
Wunder, S., 2004: Policy options for stabilising the forest frontier: A global perspective. In Land Use, Nature Conservation and the Stability of Rainforest Margins in Southeast Asia, M. Gerold, M. Fremerey, and E. Guhardja (eds). Springer-Verlag Berlin, pp. 3-25. [NPR]
Yoshioka, T., K. Aruga, T. Nitami, H. Sakai, and H. Kobayashi, 2006: A case study on the costs and the fuel consumption of harvesting, transporting, and chipping chains for logging residues in Japan. Biomass and Bioenergy, 30(4), pp. 342-348. Clean
Zhang, X.Q. and D. Xu, 2003: Potential carbon sequestration in China’s forests. Environmental Science & Policy, 6, pp. 421-432. Clean
Zhang, Y.H., M.J. Wooster, O. Tutubalina, and G.LW. Perry, 2003: Monthly burned area and forest fire carbon emission estimates for the Russian Federation from SPOT VGT. Remote Sensing of Environment, 87, pp. 1-15. [MoS]
Person of Concern Key individual involved in CRU emails as defined in this spreadsheet.
Journal of Concern A Journal which has published articles by one or more PoCs (Person of Concern)
Model or Simulation Reference appears to be a model or simulation, not observation or experiment.
Non Peer Reviewed Reference has no Journal or no Volume or no Pages or it has Editors.
Self Reference Concern Author of a chapter containing references to own work.
Paper authored or co-authored by person who is also in list of Authors of another chapter.
Paper dated 2007, when IPCC policy stated cutoff was December 2005
The reference was probably peer reviewed.
NOTE: In the Summary of Reviewer Comments,
Accepted includes only those responses that were unambiguously Accepted.
There are other categories of responses that we have not yet quantified
due to inconsistencies of usage.
|Reviewer||Total Comments||Accepted||IPCC Roles||Papers|
|Government of Japan||3||1||0||2|
|Government of Australia||1||1||0||1|
|Government of U.S. Department of State||1||0||0||0|
|Reviewer Type||Total Comments||Accepted||% Accepted|