Forestry, Climate Change, and Kyoto

Transcription

1 Citation: Brown, S Forestry, Climate Change, and Kyoto. Seventeenth Annual C. E. Farnsworth Memorial Lecture, Faculty of Forestry, SUNY College of Environmental Science and Forestry, Syracuse, NY. Forestry, Climate Change, and Kyoto Sandra Brown Winrock International The E. Farnsworth Lecture SUNY Syracuse March 28, 2000

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3 TABLE OF CONTENTS ACKNOWLEDGEMENTS...5 EXECUTIVE SUMMARY ROLE OF LAND-USE CHANGE AND FORESTRY (LUCF) IN CLIMATE CHANGE Carbon budget of forests Mitigation potential of forests Co-benefits of mitigation projects Land-use change and forestry and the Kyoto Protocol What are carbon offsets? DESIGN OF LUCF CARBON-OFFSET PROJECTS Key issues related to carbon-offset projects Carbon accounting in LUCF projects How is carbon inventoried and monitored? Guidelines for avoiding negative consequences of leakage COSTS OF MEASURING AND MONITORING CARBON OFFSETS Costs and precision Technological tools for developing cost-efficient monitoring methods PRACTICAL EXPERIENCE FROM PILOT PROJECTS: THE NOEL KEMPFF CLIMATE ACTION PROJECT, BOLIVIA Project site description With-project case Without-project case Carbon monitoring How the technical issues are addressed (from Brown et al. 1999) CONCLUSIONS...34 REFERENCES...34 List of Tables Table 1. Decision matrix of main carbon pools...16 Table 2. Examples of indicators Table 3. Strategies for managing leakage Table 4. Number of plots sampled in the different forest strata of the Noel Kempff project area Table 5. Results of carbon inventory...30 Winrock International 3

4 List of Figures Figure 1. Increase in variable costs as coefficient of variation...23 Figure 2. Relationship between level of desired precision and total variable cost...27 Figure 3. Transect of the forest in the Noel Kempff Climate Action Project...28 Figure 4. 3D image of a forest transect...28 List of Boxes Box 1. LUCF projects and without-project cases Box 2. Software for estimating carbon Winrock International 4

5 ACKNOWLEDGEMENTS The basis of this paper originates from a report prepared for the US Agency for International Development, entitled "Land-Use and Forestry Carbon-Offset Projects", prepared for the USAID Environment Officers Training Workshop (9/1999). Winrock International 5

6 EXECUTIVE SUMMARY On a global scale, land-use change and forestry activities have historically been, and are currently, net sources of carbon dioxide to the atmosphere, a major greenhouse gas. However, through management, humans have the potential to change the direction and magnitude of the flux of carbon dioxide between the land and atmosphere while at the same time providing multiple co-benefits to meet environmental and socioeconomic goals of sustainable development. The recognition that LUCF activities could be both sources and sinks of carbon led to their inclusion in the Kyoto Protocol. Articles 6 and 12 in the Protocol pertain to project-level activities and emissions trading; however, whether LUCF projects will be included in these articles is still being debated and a decision may be made at the Conference of Parties 6 meeting in Emission offsets are basically a quantity of carbon generated from an activity that can be traded with a country or a private entity to assist with their compliance under Article 3 of the Protocol. At present there is no market for carbon trading from LUCF projects, although many pilot projects have been implemented with investments primarily from developed country entities. There are many LUCF projects in various stages of design and implementation around the world, and much experience has been gained to date in dealing with the many issues surrounding these projects. There are several technical and scientific issues related to the use of LUCF activities as flexibility mechanisms, including additionality, development of without-project baseline scenarios, leakage, permanence, accounting, monitoring methods, and accuracy and precision of the carbon benefits. Experience in implementing pilot projects has led to the formulation of guidelines and methods for dealing with these issues. Many of the methods incorporate the skills and expertise from traditional fields such as forestry, ecology, landscape modeling, and remote sensing. A key aspect of implementing LUCF projects for trading carbon credits is to accurately measure and monitor project-level GHG benefits to known levels of precision. Criteria to consider in the selection of carbon pools to inventory and monitor are the type of project, the size of the pool, their rate of change, their direction of change, cost to measure, and attainable accuracy and precision. A partial accounting system may be used that must include all pools anticipated to decrease and a selection of pools anticipated to increase as a result of the project. Only pools that are measured and monitored can be incorporated into the calculation of carbon benefits. Land-use change and forestry projects are generally easier to quantify and monitor than national inventories due to clearly defined boundaries, ease of stratification, and sampling efficiency and selective accounting. Techniques and methods for measuring individual carbon pools in LUCF projects exist, and are based on commonly accepted principles of forest inventory, soil sampling, and ecological surveys. However, they have not been universally applied to all projects and methods for accounting for the carbon benefits have not been standardized. Monitoring relates to the on-going measurement of carbon pools. The frequency and intensity of monitoring depends to a large extent on the nature of the project. For those projects designed to avoid emissions through arresting deforestation or logging there is a need to establish that no trees are removed or clearings made over the course of the project and that the carbon is remaining constant or increasing. Moreover, a random selection of permanent plots need only be Winrock International 6

7 measured as part of the ongoing monitoring program. And, not all of the initial carbon pools need be measured at every interval; the judicious selection of some pools could serve as indicators that the project is following the expected trajectory. Remote sensing technology may be useful for monitoring LUCF projects, though to date it has hardly been used. Promising advances in this area to provide cost-efficient means for monitoring include a system that couples dual-camera videography with a pulse laser profiler, data recorders, and differential GPS mounted to a single engine plane. Tests with this system are encouraging and have shown that the indices collected by this system can be correlated with aboveground biomass. Projecting the without-project baselines for many LUCF projects can be problematic because of the need to estimate the likely changes in land-use and corresponding carbon that would have occurred in the project area if the project had not been implemented. Such changes in land use are hard to predict because of socioeconomic, cultural, and political conditions. Use of proxy areas for monitoring certain indicators and models based on local conditions can facilitate the development of without-project baselines. Spatially explicit models that simulate changes in land use in response to biophysical and socioeconomic factors are also an important tool for developing baselines. Field methods to accurately quantify carbon pools exist, but the level of precision varies by pool and intensity of sampling. However, stratification of the project area into more or less homogeneous units, based on vegetation type, soil type, land-use history, or topography, can increase the precision of the carbon measurements without increasing the cost unduly because it lowers the variance (amount of variation around the mean) of measurements thus requiring fewer plots to be within acceptable levels of precision. Although techniques and tools exist to measure carbon pools in the project area to a high degree of precision, this does not necessarily result in the same level of precision for the carbon offsets. For projects whose baseline depends upon projecting changes in land use where valid proxy sites are unavailable, there is likely high uncertainty about the without-project baseline. The carbon offset per unit area of land is the difference between the carbon pools in the project, which is high if the project is conserving carbon in existing forests or sequestering carbon in plantations on non-forest land, and the carbon pools in agricultural or degraded lands, which is low. Thus the error estimate, expressed as a percent of the mean difference, is likely to be small, similar to that obtained for the carbon pools in the forest. However, as the difference between the project and with-project baseline decreases, the percentage error of the carbon offset per unit area of land increases. Currently there are no guidelines as to which level of precision carbon pools should be measured and monitored in projects. Setting such a level would encourage project developers to measure projects precisely if the price of carbon was high. The potential for leakage from carbon-offset projects is highly dependent on the type of demand for a resource (e.g., agricultural land, fuel, or timber for local or export consumption), market boundaries (local, regional, national, or global), and the extent to which a project satisfies the demand for a resource. Even if a project is designed well and incorporates activities to minimize leakage, leakage may not be eliminated completely; and in such cases, the project needs to estimate the leakage and adjust the offset estimates accordingly. Because LUCF projects tend not to be completely "leakage-proof", certain strategies have been proposed to manage negative Winrock International 7

8 leakage. The strategies need to be developed and implemented in the early stages of a project to ensure success in minimizing leakage. The costs of measuring and monitoring carbon offsets are a function mainly of the desired level of precision, the type of project activities, the size and distribution of the project, and the natural variation of the various carbon pools by vegetation strata. The natural variation determines the number of plots that must be sampled to be within a given precision level. The size and distribution of the project affects the time to sample the plots; the more spread out the higher cost involved in, for example, travel between sampling areas. The type of project activities determines which carbon pools should be measured and monitored and thus the time to sample. An example of the cost of inventorying the initial carbon pools in one pilot project in Bolivia shows that variable costs could drop rapidly from about $108,000 (for 452 plots) for a precision level of ±5% to $1,000 (for four plots) for a level of ±30%. Estimating future monitoring costs based on the first inventory is difficult, because different sampling intensities will most likely be used but future costs are likely to be less expensive than the initial inventory. Variable costs per plot are not expected to decrease significantly, but the number of plots to be monitored in future years is likely to be fewer, thus the total variable cost will be less. Fixed costs are also expected to be lower in future monitoring events because of previous experience. Changes in the management of lands and forests for developing carbon offsets have a significant potential to help developed countries reach emission reduction targets. Overcoming issues related to additionality, baselines, leakage, and duration are challenging, but experience with pilot projects to date provide strategies to address these issues. Accurately measuring and monitoring carbon in biomass in land-use change and forestry projects relatively precisely can be accomplished, but measurements of soil are more difficult and potentially more costly. However, measurements of soil carbon pools may not be needed in many project types. There are little data available to address the costs of inventorying and monitoring carbon pools in projects. Experience suggests that initial costs to establish carbon offsets based on field measurements are modest (about <$0.25/t C), and are likely to decrease in future monitoring events. New technological advances in monitoring are likely to reduce costs too. To realize the potential of LUCF projects for mitigating carbon emissions requires further development of techniques, tools and scientific understanding of carbon measurements as well as guidance from policy makers on many issues such as types of eligible projects, duration of projects, accounting methods, certification process, and reporting. Winrock International 8

9 1. Role of Land-Use Change and Forestry (LUCF) in Climate Change On a global scale, land-use change and forestry have historically been, and are currently, net sources of carbon dioxide, the main greenhouse gas (GHG), to the atmosphere (Brown et al. 1996, Schimel et al. 1996). Forests are influenced by natural and human causes, including harvesting, over-harvesting and degradation, large-scale occurrence of wildfire, fire control, pest and disease outbreaks, and conversion to non-forest use, particularly agriculture and pastures. These disturbances generally cause forests to become sources of CO 2 because the rate of net primary productivity is exceeded by total respiration or oxidation of plants, soil, and dead organic matter (net ecosystem production [NEP] < 0). At the same time, however, some areas of harvested and degraded forests or agricultural and pasture lands are abandoned and revert naturally to forests or are converted to plantations, thus becoming C sinks, i.e., the rate of respiration from plants, soil and dead organic matter is exceeded by net primary productivity (NEP > 0). The present role of land-use change and forestry (LUCF) in the global C cycle is not only a function of present land use, but also of past use and disturbance. Prior to this century, CO 2 emissions from changes in forest lands, mainly caused by agricultural expansion in mid- and high-latitude countries, were higher than emissions from the combustion of fossil fuels (Houghton and Skole 1990). From the turn of the century until about the 1930s, global CO 2 emissions from changes in land use were similar in magnitude to those from fossil fuel combustion. After about the 1940s, CO 2 emissions from the changes in forest use in the tropics dominated the flux from the biota to the atmosphere. Since then, worldwide fossil fuel use has soared, biotic emissions from the mid- and high-latitude regions has declined greatly as forests expanded onto abandoned agricultural lands and as logged stands regrew, and deforestation in the tropics has accelerated (Brown et al. 1996). The past and present patterns of land use are responsible for the current situation in regard to the C pools and flux of the world s forests Carbon budget of forests The total C pool in the world's forests (live and dead organic matter) is about 830 Pg (1 Pg = g or billion metric tons), with about 42% in the vegetation (S. Brown 1998). About 52% of the total pool is in tropical forests, 35% in boreal forests, and 13% in temperate forests. The estimated net C flux from the world s forests is a source of 0.95 ± 0.5 Pg yr -1, or about 16% of the amount produced by burning fossil fuels and cement manufacture (S. Brown 1998). Nontropical forests are estimated to be a C sink of 0.7 ± 0.2 Pg yr -1. Tropical forests are estimated to be a relatively large net C source of 1.65 ± 0.4 Pg yr -1 between (S. Brown 1998) caused by deforestation, harvesting, and gradual degradation of the growing stock. The total tropical source is equivalent to almost 28% of the 1990 fossil fuel emissions. Temperate and boreal forests are for the most part C sinks because: (1) they are, on average, composed of relatively young classes with higher rates of net primary production as they recover from past human and natural disturbances; (2) a larger proportion of these forests are actively managed, i.e., established, tended, and protected; and (3) some areas may be responding to increased levels of atmospheric CO 2 and nitrogen (fertilization effect) (Brown et. al. 1996). However, there is a finite time period over which this C sink can occur. For example, the current Winrock International 9

10 C sink in European forests may disappear within 50 to 100 years (Kauppi et al. 1992), although others suggest that it may take forests up to several centuries to millennia to reach a C steady state in all components, including coarse woody debris and soil (Lugo and Brown 1986). The estimated large C source from the tropics is due mostly to the high rates of deforestation in this region, currently estimated to be about 15.4 Mha yr -1 during , but with large uncertainties (FAO 1993). However, during the period , rates of tropical deforestation are reported to have decreased to 12.7 Mha yr -1 (FAO 1997). This 18% decrease since the 1980s has reduced the net tropical flux by about 0.1 Pg C/yr (Houghton 2000). Much of the deforested area is converted to agricultural land, pastures, or shifting cultivation which have considerably lower biomass C than forests. In addition to deforestation, large areas of forests are harvested. For example, about 5.9 Mha yr -1 of tropical forests were logged during , mostly from mature forests (83%) rather than secondary forests (FAO 1993). These harvested forests can regenerate and accumulate C if they are not severely damaged during harvesting operations, are protected, or are relatively inaccessible to human populations, but many of them become degraded (e.g., Brown et al. 1993a,b, Putz and Pinard 1993). Forest degradation, resulting in a loss of C in the vegetation and/or soil, occurs through activities such as damage to residual trees and soil from poor logging practices, log poaching, fuelwood collection, overgrazing, and anthropogenic fire (Goldammer 1990; Brown et al. 1993b; FAO 1993; Flint and Richards 1994) Mitigation potential of forests Although LUCF activities have been a source of GHGs, they have the potential to mitigate GHG emissions through changes in the management and use of the land. The goal of mitigation of carbon emissions through LUCF activities is to reduce the emissions from the land, and transfer carbon from the atmosphere to the land through enhancement of the existing carbon stocks or increase forest area. Most land-use and forestry practices that mitigate GHG emissions through maintaining or enhancing carbon on the land make good social, economic, and ecological sense even in the absence of climate change considerations (Brown et al. 1996). Land-use and forestry activities for mitigation are often criticized because GHG mitigation is often viewed as the main goal of the project. Instead LUCF activities can meet the more conventional objectives for managing forests such as sustainable forest development, industrial wood and fuel production, traditional forest uses, protection of soil; water and biodiversity; recreation; rehabilitation of damaged lands; and the like. The carbon conserved and sequestered from managing for these objectives will be an added benefit. Land-use and forest management practices that meet the objectives given above can be grouped into three categories based on how they are viewed to curb the rate of increase in atmospheric CO 2. These categories are: (1) management for carbon emission avoidance, (2) management for carbon sequestration, and (3) management for carbon substitution. The main goal of management for C emission avoidance is to conserve existing C pools in forest vegetation and soil through options such as averting deforestation or logging and protecting forest in reserves, changing harvesting regimes (e.g., reduced impact logging or lengthening rotation times), and controlling other anthropogenic disturbances such as fire and pest outbreaks. Significant carbon conservation clearly would occur in the tropics where high rates of deforestation and forest degradation occur due to expansion of arable and grazing lands and subsistence and commodity demand for wood products. Global action to mitigate C emissions by conserving C pools may lead to more interest and success in controlling deforestation and Winrock International 10

11 making agriculture more sustainable (Brown et al. 1996). Expansion of "protected areas" into areas of both mature and secondary forests for conservation of biodiversity, for example, are another means for conserving carbon. It is also likely that the trend towards management of forests for sustainable timber production in the world's forests will increase in the future. Using forests this way, including extending rotation cycles, reducing damage to remaining trees, reducing logging waste, implementing soil conservation practices, and using wood in a more efficient way, ensures that a large fraction of their carbon is conserved on the land (Moura-Costa 1996). Management for C sequestration means increasing the amount of C stored in vegetation (living above and below ground biomass), dead organic matter and soil (litter, dead wood, and mineral soil), and durable wood products. Increasing the C pool in existing forests can be accomplished by silvicultural treatments, protecting secondary forests and other degraded forests whose biomass and soil C densities are less than their maximum value and allowing them to sequester C by natural or artificial regeneration, and to establish plantations on non-forested lands or increase the tree cover on agricultural or pasture lands (agroforestry) for environmental protection and local needs. The C pool in durable wood products can be increased by expanding demand for wood products at a rate faster than the decay rate of the existing wood product pool, and by extending the lifetime of wood products. Management for C substitution aims at increasing the transfer of sustainably grown forest biomass C into products (e.g., construction materials and biofuels) rather than using fossil-fuelbased energy and products and cement-based products. Substitution management has the greatest mitigation potential in the long term (Marland and Marland 1992). It views forests as renewable resources and focuses on the transfer of biomass C into products that substitute for, or lessen the use of, fossil fuels rather than on increasing the C pool itself. This approach involves extending the use of forests for wood products and fuels obtained either from establishing new forests or plantations, or increasing the growth of existing forests through silvicultural treatments. The potential amount of C that could be conserved and sequestered through the implementation of an aggressive program of changing LUCF practices over the next 50 years or so is about Pg or equivalent to about 12 to 15% of the business-as usual fossil-fuel emissions over the same time period (Brown et al. 1996). The tropics have the potential to conserve and sequester by far the largest quantity of carbon (80% of the total), followed by the temperate zone (17% of the total) and the boreal zone (3% of the total) Co-benefits of mitigation projects Land use and forestry projects for mitigating GHG emissions can provide the financing to meet multiple environmental and socioeconomic co-benefits and development goals of local, regional, and national priority for the host country (P. Brown 1998, Brown et al. 1996, Frumhoff et al. 1998, Pinard and Putz 1997, Trexler and Associates 1998). For example, environmental cobenefits from carbon-offset projects aimed at avoiding emissions through averting deforestation and/or forest harvesting conserve existing or restore biodiversity, protect habitat for species with wide ranges, and protect soil and water resources. Protection of soil and water resources can have further benefits by reducing siltation or risk of flooding downstream, which in turn can protect fisheries and hydroelectric dams. In addition to the aforementioned co-benefits, reduced- Winrock International 11

12 impact logging projects generally improve the sustainability of forest management, ensuring a more continuous supply of wood of desired species. From a socioeconomic perspective, projects can provide funds for local sustainable development enterprises, technology transfer, renewable energy, and expansion of national parks. For example, the Noel Kempff Climate Action Project (see below) provided funds to: purchase and permanently retire logging concessions and expand a national park, develop community enterprises such as ecotourism and commercialization of non-timber forest products, provide agricultural extension, support sustainable agricultural practices, improve health care and educational opportunities, and introduce renewable energy technology. Projects designed to sequester carbon, such as afforestation and agroforestry, may provide many of the same environmental co-benefits as for emission avoidance projects. However, the potential co-benefits will depend on the location, scale, use of native versus non-native species, and management intensity. For example, longer rotation plantations are expected to have a more positive impact on soils and water resources and biodiversity than shorter, more intensively managed plantations. Also, plantations of native species are likely to be more environmentally acceptable than on non-natives on sites where natural or assisted regeneration is feasible. However, on badly degraded lands, non-natives are often the only species that will grow, and in these situations it has been shown that such plantations can serve as a foster ecosystems enabling native species to become established (Lugo et al. 1993). On degraded sites, it is important that the selection of species consider water and nutrient requirements, as many non-natives demand high levels of these resources; local community needs must also be considered in species selection. Socioeconomic co-benefits of afforestation and agroforestry projects include provision of financial returns on the investment from products such as timber, woodfuel, agroforest crops etc., local employment opportunities, renewable energy, and technology transfer. There is a potential for carbon-offset projects to have negative socioeconomic impacts if local communities do not participate in all phases of the project, particularly when there may be competing priorities for land use Land-use change and forestry and the Kyoto Protocol The recognition that LUCF activities could be both sources and sinks of carbon led to their inclusion in the Kyoto Protocol. There are several articles in the Protocol that refer to LUCF activities, two of which pertain to project-level activities and emissions trading (Articles 6 and 12). Article 6 is related to emission-allowance trading between Annex 1 or developed countries. Article 6 states that for the purpose of meeting its commitments, any Annex 1 country may transfer to, or acquire from, any other Annex 1 country emission reduction units resulting from projects aimed at reducing anthropogenic emissions by sources or enhancing anthropogenic sinks of greenhouse gases in any sector of the economy. Two key additional provisions in this article are that any emission reduction units from a project must be additional to any that would otherwise occur and that the acquisition of emission reduction units must be supplemental to domestic actions. Article 12 defines the Clean Development Mechanism (CDM), whose purpose is to assist non- Annex 1 countries achieve sustainable development, while at the same time assist Annex 1 countries in achieving compliance with their quantified emission limitation and reduction Winrock International 12

13 commitments under Article 3. Under the CDM, non-annex 1 countries will benefit from project activities resulting in certified emission reductions (CERs) and Annex 1 countries may use the CERs accruing from such project activities to contribute to their commitments. Any CERs obtained between 2000 and 2008 can be banked and used towards compliance in the first commitment period. In essence, Article 12 allows for emission-offset trading between developed and developing countries. Further, emission reductions resulting from such project activities shall be real, measurable, long-term benefits related to mitigation of climate change, and additional to any that would occur without the project. Although LUCF projects are not explicitly mentioned in these Articles 6 and 12, they are not explicitly rejected either. Moreover, Article 6 refers to projects that enhance anthropogenic sinks in any sector of the economy, thus implying that LUCF projects would be included. However, LUCF projects are not explicitly mentioned in Article 12. Whether LUCF projects will be included in the CDM is still being debated, and a decision may be made at the Conference of Parties 6 meeting in 2000 by which time the special report of the IPCC on Land Use, Land-Use Change, and Forestry will be completed What are carbon offsets? Emission offsets are basically a quantity of carbon (avoided emissions or sequestered carbon) generated from an activity that can be traded with a country or a private entity to assist with their compliance under Article 3 of the Protocol. For example, to comply with the Kyoto Protocol, the USA will need to reduce its carbon emissions to a level equivalent to 93% of its 1990 emissions during the commitment period A utility company in the U.S. that emits 100 units of carbon may be required to reduce its carbon emissions by seven units to achieve a total emission of 93 units. It can accomplish this internally through changes in efficiency of power generation and/or acquire carbon offsets. The utility company might, for instance, invest in a project in a developing country designed to avert deforestation. This project could prevent five units of carbon emissions to the atmosphere, thus these five units would offset some of the seven units the utility needs to reduce; the utility then would need to reduce its domestic emissions by two units only. Another strategy is that private entities in a developing country could develop a project (e.g., averted deforestation or plantation establishment) and sell the carbon offsets to a developed country utility at the going price, assuming that the project met criteria and standards that are likely to develop if LUCF projects are included in the CDM. At present there is no market for carbon trading from LUCF projects, although many pilot projects have been implemented with investments primarily from developed country entities with the anticipation that this will occur in the not-to-distant future. 2. Design of LUCF Carbon-Offset Projects There are many LUCF projects in various stages of design and implementation around the world, ranging from forest protection, changes in forest management, forestation (afforestation, reforestation, and restoration), and community forestry and agroforestry). Most of the forestation projects are in non-tropical countries and most of the other project types are in tropical countries. Much experience has been gained to date by these projects in advancing the field in carbon monitoring, without-project baseline development, and leakage prevention. Certain steps are undertaken in the formulation and implementation of LUCF projects for determining the GHG benefits. Typically, the first step in formulating a project is to perform a Winrock International 13

14 feasibility study. The feasibility study, which is usually based on existing data sources, establishes with and without-project scenarios to show additionality and to estimate GHG benefits, and addresses project leakage and permanence issues. The feasibility study usually serves as the basis for raising funding and investments. Once the project is implemented, all estimates and scenarios initially used are then quantified under actual project conditions; these are used to refine the initial GHG benefits. A plan for monitoring with and without-project conditions and leakage is then implemented to track the GHG benefits over time. In this section key issues related to carbon-offset projects, methods for inventorying and monitoring carbon, projecting without-project baselines, accuracy and precision of carbon accounting, and practical guidelines for avoiding negative consequences of leakage are discussed Key issues related to carbon-offset projects There are several technical and scientific issues related to the use of LUCF activities as flexibility mechanisms (Brown et al. 1997; P. Brown 1998). Many of these issues are considered to be threats to the implementation of LUCF projects for carbon trading; however most of these concerns apply equally to energy-sector projects. Experience in implementing pilot projects has led to the formulation of preliminary guidelines for dealing with these issues or avoiding their negative consequences of them (P. Brown 1998). Additionality: An essential criterion under both Articles 6 and 12 is that the project s activities must lead to carbon benefits that are additional to a business-as-usual scenario. In other words, an additional project is one that would have had no chance of being implemented but for the mechanisms in Articles 6 and 12 and the GHG emissions would be higher but for the carbon-offsets from the project (Swisher 1998). Baselines or without-project case: To quantify the additional carbon benefits from LUCF projects requires the development of a baseline scenario against which changes in carbon pools in the with-project case can be compared; in other words, what would have happened on the land without the project. For example, in a project aimed at avoiding emissions by preventing deforestation, the baseline would be based on predicting how deforestation in the project area would have occurred without the project over the life of the project. Further elaboration of this topic will be given below. Leakage is the unexpected loss of anticipated carbon benefits resulting from additional effects of the project's activities outside the project boundaries. For example, preventing deforestation may cause the displaced persons to move elsewhere and deforest, thus there is little to no additional carbon savings referred to as activity shifting. Or, stopping or reducing forest harvesting may cause harvesting to increase in another region or another country to satisfy the demand referred to as market effects. Leakage is commonly thought of as a loss in carbon, but in some cases leakage can be positive where project activities inadvertently lead to more carbon benefits than originally estimated. Leakage can often be anticipated and prevented as part of the project design by addressing the demands for products or resources (e.g., agricultural land, timber, fuelwood) contributing to the land-use change. Duration: A unique feature of LUCF projects is the possibility of a reversal of carbon benefits from either natural disturbances such as fires, disease, pests, and unusual weather events; or from the lack of reliable guarantees that the original LUCF activities Winrock International 14

15 will not return. However, strategies have been identified that could guard against such reversals such as establishment of contingency carbon credits, insurance, and mixed portfolios of projects. Projected changes in climate are predicted to change the carbon dynamics of forests (Kirschbaum et al. 1996; Tian et al. 1998) that could also affect the permanence of carbon offsets. However, LUCF carbon-offset projects should be viewed not as a permanent solution, but rather to postpone emissions to buy time to develop and implement policies and measures requiring longer lead times Carbon accounting in LUCF projects A key aspect of implementing LUCF projects for trading carbon credits is to accurately quantify the project-level GHG benefits to known levels of precision. In LUCF projects, the main focus is on carbon (as carbon dioxide), but other gases such as methane and nitrous oxides may be included as appropriate. Box 1. Examples of LUCF projects and the corresponding without-project case that could be implemented. With-project case Without-project case Prevent deforestation and improve agriculture Forest clearing or slash-and-burn for cultivation or pasture Prevent forest degradation High rates of timber and/or fuelwood extraction Prevent logging Forest with continued logging Reduced impact logging Traditional logging with high damage Improved forest management Traditional forest management Plantation establishment Agroforesty: trees and crops shade coffee Degraded or marginal non-forested lands Annual crops Sun coffee In this section I discuss which pools need to be quantified, how they can be measured accurately in the with- and without-project situation to a known level of precision, and the techniques that can be used to monitor the carbon benefits over the length of the project. I distinguish between the initial carbon inventory and subsequent monitoring: in the initial inventory the relevant major pools or fluxes need to be quantified in the with- and without-project situation, but in subsequent monitoring only selected pools or fluxes may be measured and even indicators could be used. I then discuss the technical challenges in projecting what the likely business-as-usual changes in major pools would have been in the project area without the project, and how these challenges have been addressed from experience with pilot projects to date Which carbon pools need to be inventoried and monitored? Focussing on carbon simplifies the task because the problem is reduced to calculating the net differences between carbon stocks for the with- and the projected without-project conditions on the same piece of land over a specified time period. The challenge is to identify which pools need to be quantified in the project, to measure them accurately to a known, and often predetermined, level of precision, and to monitor them over the length of the project. Criteria to consider in the selection of carbon pools to inventory and monitor are the type of project, the size Winrock International 15

16 of the pool, their rate of change, their direction of change, cost to measure, and attainable accuracy and precision (MacDicken 1997a,b). The carbon credits from a project for all pools measured (pools 1 to n) are: = 1 n (carbon in pool 1 for with-project case carbon in pool 1 for without-project case) It is clear that for some pools the difference will be positive (e.g. stopping deforestation or lengthening forest rotation will have more carbon in trees on average [with-project] than conversion of forests to agriculture or shorter rotation [without-project]), but for others it will be negative (e.g. dead wood pool in an averted logging project will be less than the dead wood pool in a conventional logging practice). Basically, a selective accounting system may be used that includes all pools anticipated to exhibit a negative change (i.e. those pools that are smaller in the with-project case than in the without-project case) and selection of pools anticipated to give a positive change (i.e. those pools that are larger in the with-project case than in the withoutproject case) as a result of the project. Only pools that are measured and monitored can be incorporated into the calculation of carbon benefits. The major carbon pools in LUCF projects are: live biomass, dead biomass, soil, and wood products. Each of these can be subdivided further: for example, live biomass may include leaves, twigs, branches, tree bole, and coarse and fine roots, palms, herbaceous plants (forest understory, grasses, and agricultural plants) shrubs, and vines; dead biomass fine litter and coarse woody debris; soil the mineral and organic horizons and peat; and wood products the long-lived products in use or in landfills. Table 1 is a guide for selecting which pools to quantify and monitor for different types of LUCF projects. Land-use change and forestry projects have often been targeted for criticism as mitigation projects because it is suggested that changes in soil carbon pools are difficult to measure. However, of the projects illustrated in Table 1, in only one case is it noted that the soil carbon pool should be measured (Y), because the project may actually cause this pool to decline. For several cases it is recommended that soil carbon be measured because the project is likely to increase the size of this pool, but the cost to attain a given precision level may be high. Winrock International 16

17 Table 1. A decision matrix of main carbon pools for examples of forestry projects to illustrate the selection of pools to quantify and monitor. A Y for yes in the matrix for a given project type indicates that the change in this pool is likely to be large and should be measured. An R for recommended indicates that the change in the pool could be significant but measuring costs to achieve desired levels of precision may be high. An N for no indicates that the change is likely small to none and thus it is not necessary to measure this pool. An M for maybe indicates that the change in this pool may need to be measured depending upon the forest type and/or management intensity of the project. Project type Avoid Emissions Carbon pools Live biomass Dead biomass Wood Products Trees Herbaceous Roots Fine Coarse Soil Stop deforestation Y M R M Y R M Stop logging Y M R M Y N Y Reduced impact logging Y M R R Y N Y Improved forest management Y M R M Y M Y Sequester Carbon Protect secondary forest Y M R R Y M N Plantations Y M R M M R Y Agroforestry Y Y M N N R M Short-rotation energy plantations *Stores carbon in unburned fossil fuels 2.3. How is carbon inventoried and monitored? Y N M N N Y * Before implementing a new offset project, experience with pilot projects has shown that an assessment of the area, including collecting as much relevant data as possible, is a time- and cost-efficient activity. Relevant data and information include: a ground-truthed land-cover/landuse map of the project area; identification of pressures on the land and its resources; history of land use in project area; the identification of without-project proxy areas for future monitoring; the climate regime (particularly temperature and rainfall); soil types, topography, and socioeconomic activities (e.g., forestry and agricultural practices). Such information is useful to delineate relatively homogeneous land-cover strata (e.g., by forest and soil type) for designing the inventorying and monitoring sampling scheme, improving baseline projections, and developing guidelines for leakage avoidance. Land-use change and forestry projects are generally easier to quantify and monitor than national inventories due to clearly defined boundaries, ease of stratification, and sampling efficiency and selective accounting. Techniques and methods for measuring individual carbon pools in LUCF projects are well established, and are based on commonly accepted principles of forest inventory, soil sampling, and ecological surveys (MacDicken 1997; Pinard and Putz 1996,1997; Post et al. 1999). However, they have not been universally applied to all projects. Methods for measuring fluxes of non-carbon GHGs are less well developed and their magnitudes are often based on Winrock International 17

18 changes in carbon pools due to biomass burning and corresponding emission factors (Houghton et al. 1997). The uncertainties in the emission factors are high; and it might be prudent in most carbon-offset projects to ignore these fluxes unless they change in a negative direction as a result of the project Inventory of carbon pools There are specialized fields of forestry called mensuration and biometrics that develops methods for sampling and measuring forest trees, the component that provides the most carbon benefits in most LUCF projects. Foresters have been sampling and measuring forests for merchantable volume and tree growth for decades and their techniques are well developed and accepted. Winrock's methodology (MacDicken 1997a) incorporates these mensuration techniques for inventorying and monitoring LUCF projects for carbon. For inventorying forest carbon, the use of fixed-area permanent plots (often a series of nested plots where forests are composed of smallto large-diameter classes) is recommended; this approach is generally considered as the statistically superior means for evaluating changes in forest characteristics, including carbon pools. Within these plots, all the carbon pools can be measured or estimated, with the exception of wood products. Methods are well established and tested for determining the number, size, and distribution of permanent plots (i.e., sampling design) for maximizing the precision for a given monitoring cost (MacDicken 1997a) (see Box 2, next page). To estimate live tree biomass, diameters of all trees are measured and converted to biomass and carbon estimates (carbon = 50% of biomass), generally using allometric biomass regression equations. Such equations exist for practically all forests of the world; some are species specific and others, particularly in the tropics, are more generic in nature (e.g., Alves et al. 1997; S. Brown 1997; Schroeder et al. 1997). Sampling a sufficient number of trees to represent the size and species distribution in a forest to generate local allometric regression equations with high precision, particularly in complex tropical forests, is extremely time-consuming and costly, and generally beyond the means of most projects. Experience to date with the development of generic equations, for both tropical and temperate forests, has shown that measurements of diameter at breast height, as is typical for trees, explains more than 95% of the variation in tree biomass. The advantage of using generic equations, stratified by, e.g., ecological zones or species group (broadleaf or conifer), is that they tend to be based on a large number of trees (S. Brown 1997) and span a wider range of diameters; this increases the accuracy and precision of the equations. It is very important that the database for regressions equations contain large diameter trees, as these tend to account for more than 30% of the aboveground biomass in mature tropical forests (Brown and Lugo 1992; Pinard and Putz 1996). A disadvantage is that the generic equations may not accurately reflect the true biomass of the trees in the project. However, relatively inexpensive field measurements (e.g., diameter and height relationships of the larger trees) performed at the beginning of a project can be used to check the validity of the generic equations. For plantation or agroforestry projects, developing or acquiring local biomass Winrock International 18

19 Box 2. Software for estimating carbon stocks, sample size, and cost in forestry and agroforestry projects Winrock has developed a software package to accompany its methods manual to facilitate analysis of field data for estimating carbon stocks and to estimate the number of plots needed by stratum based on the variance of a number of preliminary plots. During data collection from the permanent plots, times to reach the plots and to measure all the pools and the number of people in the field crew is also recorded; this information is used to determine variable costs of measuring. Estimating Carbon Pools And Carbon Offsets Spreadsheets (Excel) for estimating carbon in four main pools 1. above-ground vegetation (trees with diameters at breast height (dbh) greater than 5 cm) 2. herbaceous vegetation (less than 5 cm dbh) 3. fine litter 4. soil to 30 cm depth 5. dead wood Single entry regression equations are used to estimate biomass of aboveground vegetation; a summary of the available regression equations is included in the package. Sample plots are either single or nested. Sampling error (expressed as a percent of the mean) is calculated for each pool and the total inventory. The inventory spreadsheet is being modified to include measurement error and regression error in the statistical analysis. A simple spreadsheet accounting model for calculating offsets for forest management or averted deforestation activities based on with -project field measurements and without-project baseline scenarios. Estimating Sample Size A sample size calculator uses data from preliminary sample plots to calculate the number of permanent plots required to achieve a given level of precision, expressed as a percent of the mean (±% 5, 10, 20) The number of sample plots are allocated to each vegetation type based on the variation in the population Estimating Variable Cost The sample size calculator is linked to a spreadsheet with detailed information on inventory costs collected as part of a project Measurement costs per plot are estimated for each vegetation type and for the total inventory based on fixed and variable costs. Total inventory costs are estimated for different levels of precision. Total inventory costs are estimated for different levels of precision. Winrock International 19

20 regression equations is less problematic, as much work has been done on plantation and agroforest species (Lugo 1997). Dead wood, both lying and standing, is an important carbon pool in forests and one that should be measured in many LUCF projects (Table 1). Methods have been developed for this component and have been tested in many forest types and generally require no more effort than measuring live trees (Harmon and Sexton 1996). Total root biomass is another important carbon pool and can represent up to 40% of total biomass (Cairns et al. 1997). However, quantifying this pool can be expensive and no practical standard field techniques yet exist. Instead, recent reviews of the literature based on research studies of all examples of the world forests are available for estimating root biomass carbon based on aboveground biomass carbon (e.g., Cairns et al. 1997). The ability to measure soil carbon pools is a source of contention in LUCF projects as mentioned above; however, like for vegetation, there is a well established set of methods and documentation for measuring soil carbon pools (Post et al. 1999). Measuring change in soil carbon over relatively short time periods is more problematic, but as shown in Table 1, this pool need not be measured in most projects. In cases where changes in soil carbon are included, rates of soil oxidation under different land uses are available in the literature (e.g., summarized in the LUCF sector of the IPCC Guidelines for National Greenhouse Gas Inventories; Houghton et al. 1997). Promising technologies for measuring carbon both directly and indirectly, involving in some cases the use of modeling and remote sensing, are on the horizon (Post et al. 1999). The long-term effectiveness of carbon storage in wood products depends on the uses of wood produced through project activities. In projects that reduce output of harvested wood by preventing logging or improved forest management (and deforestation if some of the wood cut during deforestation entered the wood products market), the change in the wood products pool would be negative because the input to the product pool would be reduced (assuming no leakage to meet the demand). This negative change in the wood product pool would reduce some of the carbon benefits from the project and this would have to be accounted for. In plantation projects, wood that goes into long- to medium-term products (e.g., sawtimber for housing, particle board, paper) represents an additional carbon storage. Several methods exist for accounting for the storage of long-lived wood products and they have been used to calculate the net changes in wood product stocks in several countries (Heath et al. 1996; Pingoud et al. 1996, Nabuurs and Sikkema 1998; Winjum et al. 1998). These methods account for inputs of new products to the pool as well as the decay, oxidation, and retirement of products from past use, accumulated as far back as individual country s records allow. Recently, an IPCC Expert group for the Land Use and Forestry Sector of the Guidelines for GHG Inventories completed a report that describes and evaluates the approaches available for estimating carbon emissions or removals for forest harvesting and wood products (Brown et al. 1999; Lim et al. 1999). A decision on which methodology to be used in the Guidelines is pending from the Subsidiary Body for Scientific and Technical Advice (SBSTA) Monitoring of carbon pools Monitoring relates to the on-going measurement of carbon pools. Permanent sample plots allow for efficient assessments of changes in carbon pools over time and for cost and time-efficient verification of the project s reported carbon benefits (MacDicken 1997a). The frequency and intensity of monitoring depends to a large extent on the nature of the project. Those projects designed to avoid emissions through arresting deforestation or logging need primarily to Winrock International 20

21 establish that no trees are removed or clearings made over the course of the project and that the carbon is remaining constant or increasing. Moreover, a random selection of permanent plots need only be measured as part of the ongoing monitoring program. And, not all of the initial carbon pools need be measured at every interval; the judicious selection of some pools could serve as indicators that the project is following the expected trajectory. In projects designed to sequester carbon, either in protecting secondary forests or through establishment of new forests (cf. Table 1), changes in all carbon pools being claimed need to be re-measured periodically (but see below). Remote sensing technology may be useful for monitoring LUCF projects, though to date it has hardly been used (K. Brown 1996). Interpretation of satellite imagery has been used mostly for producing land-use maps of project areas and for estimating rates of land-use change or deforestation in the project formulation phase. However, remote sensing technology clearly has potential for monitoring forest protection projects and trends in plantation or agroforestry establishment at the sub-national to national scales. Monitoring of improved forest management or secondary forests, particularly in the tropics, is difficult with the current suite of satellites (Helmer et al. 1999), but future development and launching of new satellites may overcome this problem. Not all remotely-sensed monitoring activities need to use data from satellites. Because LUCF projects have well defined boundaries and are relatively small in area (several thousand to hundreds of thousand ha), remotely-sensed data from low flying airplanes can be used for monitoring (see section 3.2 below). In some circumstances, models can be useful tools to complement monitoring activities for LUCF projects by estimating changes in carbon pools over short time periods for which direct measurements fall below detectable levels, followed by direct measurements over longer time intervals to verify model projections (MacDicken 1997a; Post et al. 1999; Vine et al. 1999). Process-based models are particularly useful for projecting slowly occurring changes in soil carbon pools (Paustian et al Post et al. 1999). Models of soil carbon dynamics are generally available for most situations. Likewise, process-based models exist for the vegetation component of secondary forests, plantations, and agroforests (e.g., Maclaren 1996, Schlamadinger and Marland 1996; International Centre for Research in Agroforestry (ICRAF) n.d.) that could be used in conjunction with direct field measurements Projecting without-project baselines During the formulation stage of a carbon-offset project, without-project baselines are estimated. Once the project is implemented, the assumptions and data used to develop this baseline need to be verified and the baseline revised if needed. However, there is discussion as to whether the baseline should be fixed or constantly updated and revised over the length of the project. The key argument for revising the baseline over the length of the project is that this ensures more realistic offsets. For example, it is clear that if a forest protection project assumed a deforestation rate of 1%/yr over the length of the project in calculating its carbon credits, whereas the results of ongoing monitoring in adjacent proxy areas found it to be 0.5%/yr several years after the project started, the carbon offsets could be reduced; however attributing cause and effect after a project has started can be problematic. A key counter argument is that if baselines are revised continuously this could have a significant impact on the economic value of the project; it will introduce another source of risk to the project. But as with the duration issue (see Winrock International 21

22 above), strategies can be developed to guard against such risks such as establishment of a "carbon credit bank", insurance, and mixed portfolios of projects. Projecting the without-project baselines for many LUCF projects can be problematic because of the need to estimate the likely changes in land-use and corresponding carbon that would have occurred in the project area if the project had not been implemented i.e. the business-as-usual. Such changes in land use are hard to predict because of socio-economic, cultural, and political conditions. In projects, models of land-use change can be formulated based on such variables as human population dynamics, geomorphology of the land, land cover, climatic zone, transportation infrastructure, accessibility to forests, access to markets, timber supply and demand, and the like (e.g., GEOMOD by Hall et al. 1995a; 1995b, Hall et al. 2000). However, use of models always requires actual data for verification of model outputs. One approach to verify without-project baselines is to identify an area similar enough to the project area that it can serve as a valid proxy under the assumption that the project was not implemented (Vine et al. 1999). The establishment of valid proxy areas for some projects may not be easy, and to overcome such difficulties, proxy areas must be identified in the project design phase. Once a valid proxy area had been identified, certain indicators could be monitored to track the proxy without-project baseline (Table 2); these indicators could then be used to verify the actual projected without-project baseline. Key indicators for baseline monitoring in proxy areas vary by project type, but data from remote sensing will play an important role. For many LUCF projects, monitoring reference plots could be established in the proxy comparison area. The establishment of monitoring plots in the proxy areas is particularly important in any project related to changes in forest logging practices. These plots are needed to measure damage and to determine regrowth rates. Routine collection (every 5 years or so) of data on the indicators described here (Table 2) over the life of the project will be crucial for determining the actual without-project situation against which the with-project activities can be compared. Winrock International 22

23 Table 2. Examples of indicators that could be used for monitoring without-project baselines in proxy areas for a selection of land-use change and forestry carbon-offset projects. With-project case Without-project case Indicators for baseline monitoring in proxy area Prevent deforestation Forest clearing for agriculture or pasture Rates of land-use change by remote sensing; accessibility to forests; population growth Prevent logging Forest with continued logging Rates of timber extraction, remote sensing & field plots for damage assessment, permanent plots for regrowth rates Reduced impact logging Traditional logging Rates of timber extraction, remote sensing & field plots for damage assessment, permanent plots for regrowth rates Plantations Degraded non-forested lands Rates of land-use change by remote sensing, carbon contents of non-forest lands Agroforestry Annual crops/sun coffee Agricultural land-use practices by remote sensing/census, production of agricultural products by type Accuracy and precision Field methods to accurately quantify carbon pools exist, but the level of precision varies by pool and by sampling effort. The total error in measuring a given carbon pool is based on sampling error (number of plots used to represent the population of interest), measurement error (error in measuring parameter of interest such as stem diameter and soil carbon), and regression error when appropriate (e.g., conversion of tree diameter to biomass based on a regression equation). Sampling error is usually the largest source of error and can account for more than 90% of the total error (Phillips et al., 2000), and increased precision generally comes at increasing cost of inventorying because of the time involved in establishing the appropriate number and distribution of permanent plots. However, stratification of the project area into more or less homogeneous units, based on vegetation type, soil type, land-use history, or topography, can increase the precision of the carbon measurements without increasing the cost unduly because it lowers the variance (amount of variation around the mean) of measurements, thus requiring fewer plots to be within acceptable levels of precision. For example, stratification of the Noel Kempff Climate Action Project area into more or less homogeneous units can decrease the variation within a vegetation type, requiring fewer plots and reducing the variable cost for a given precision level (Figure 1). Winrock International 23

24 40 Based on number of plots needed for precision level of +/-10% - assumes one forest strata Variable costs ($K) Coefficient of variation (%) Figure 1. Increases in variable costs as coefficient of variation (CV=standard deviation/mean, in %) for a vegetation type increases to maintain a fixed precision level. A doubling of the CV causes cost to almost quadruple. Data are from the Noel Kempff Climate Action Project and assumes area is covered by one of the six forest strata (see Table 4). Cost data are from Powell (1999). Carbon inventorying and monitoring of forests can be more complicated than traditional forest inventories as each carbon pool will have a different variance. The sample size for each pool can be calculated individually and, based on resources available for inventorying the project and the information in Table 1, more informed decisions can be made about which pools to measure and count in an offset project. Such information can be used at the design stage of the project to select which pools to be included, which can have significant implications for the total cost of the project and cost per ton of carbon. Although techniques and tools exist to measure carbon pools in the project area to a high degree of precision, this does not necessarily result in the same level of precision for the carbon offsets. First, there is likely high uncertainty about the without-project baseline as discussed above. Second, the carbon offset per unit area of land is the difference between the carbon stocks in the project, which is high if the project is conserving carbon in existing forests or sequestering carbon in plantations on non-forest land, and the carbon stock in agricultural or degraded lands, which is low. Thus the error estimate, expressed as a percent of the mean difference, is likely to be small, and similar to that obtained for the carbon pools in the forest. However, as the difference between the project and with-project baseline decreases (for example in reduced impact logging or changes in agricultural practices or soil management), the percentage error of the carbon offset per unit area of land increases. To reduce this error in projects related to Winrock International 24

25 changes in logging practices, monitoring can be designed to measure the carbon offset directly as in the Noel Kempff Climate Action Project in Bolivia (see below for further details of this project). Currently there are no guidelines as to which level of precision carbon pools should be measured and monitored in projects. Setting such a level would encourage project developers to measure projects precisely if the price of carbon was high. For example, regulations could be set that projects could only claim the mean minus a lower confidence level. To illustrate the effect of this, consider the following example: if the total average carbon offset was 5 million t C, a ±30% confidence interval would be equivalent to a lower bound of 3.5 million t C. If the carbon was worth $10/t C, this would represent a loss of carbon benefits of 1.5 million t, equivalent to $15 million, a value likely to greatly exceed the cost of monitoring to a ±5% precision level (see below). Thus it is likely that project developers would chose high precision levels for their monitoring Guidelines for avoiding negative consequences of leakage The potential for leakage from carbon-offset projects is highly dependent on the type of demand for a resource (e.g., agricultural land, fuel, or timber for local or export consumption), market boundaries (local, regional, national, or global), and the extent to which a project satisfies the demand for a resource (P. Brown et al. 1997). Even if a project is designed well and incorporates activities to minimize leakage, leakage may not be eliminated completely. In such cases, the project needs to estimate the leakage and adjust the offset estimates accordingly. Because LUCF projects tend not to be completely "leakage-proof", certain strategies have been proposed to manage negative leakage (Table 3). The strategies need to be developed and implemented in the early stages of a project to ensure success in minimizing leakage. For those projects that reduce timber output for the export market, maintaining output is important (P. Brown et al. 1997). The concern of reducing timber harvesting is that the shortfall in timber production will be made up by increased harvesting in other areas outside the project area. However, in many tropical forests only a few tree species, among hundreds sometimes, are considered commercial with developed markets. One might argue that within these forests there is a finite number of these few commercial species (at least until smaller individuals of these species grow to the large sizes typically harvested). Thus when harvesting for these few species is reduced or halted as in a carbon-offset project, it may be difficult to make up the shortfall by harvesting elsewhere because the number of individuals of these commercial species is limited. By protecting the small number of commercial tree species in a project, it is as though they are locked up permanently and loggers are unable to go far enough to get other individuals of the same species. Thus the potential for leakage in the situation would be minimal. Winrock International 25

26 Table 3. Strategies for managing leakage for examples of land-use change and forestry carbon-offset projects (modified from P. Brown et al. 1997, P. Brown, Pers. Comm. 1999). Project activities Forest protection Improved forest management, reduced impact logging Displaced product or resource Demand for land for subsistence crops Demand for land for commercial crops Local demand for timber/fuelwood Export demand for timber Local demand for timber Export demand for timber Conditions signaling leakage Decrease in agricultural output Decrease in agricultural output Decrease or halt timber/fuelwood output Decrease or halt timber output Decrease timber output in the near term Decrease timber output in the near term Plantations Degraded lands Increase wood output, decrease in prices Increase agricultural productivity Demand for land for commercial crops Expansion onto adjacent forest lands 3. Costs of Measuring and Monitoring Carbon Offsets Strategies for managing leakage Create alternative income sources; add component on improved agricultural productivity on existing lands Create alternative income sources; add component on improved agricultural productivity on existing lands; sustainable forestry in buffer area Promote alternative wood sources e.g., plantations, sustainable harvesting in buffer zone Promote alternative wood sources e.g., plantations, sustainable harvesting in buffer zone Gradual phase in of project, develop alternative sources of timber/fuelwood e.g. agroforests, plantations Gradual phase in of project, produce certified wood to command higher prices and maintain income Use as feedstock for renewable energy plants, plant specialty species suited for growing conditions Protect adjacent forests, implement sustainable forestry The costs of measuring and monitoring carbon offsets are a function mainly of the desired level of precision, the type of project activities, the size and distribution of the project (e.g., areal extent, contiguous or fragmented), and the natural variation of the various carbon pools by vegetation strata. The natural variation determines the number of plots that must be sampled to be within a given precision level. The size and distribution of the project affects the time to sample the plots; the more spread out the higher cost involved in, for example, travel between sampling areas. The type of project activities determines which carbon pools should be measured and monitored and thus the time to sample Costs and precision The total cost is the sum of fixed costs and variable costs. Typically, fixed costs for measuring and monitoring carbon include recruitment and hiring of personnel, training, development of sampling strategy and site selection, collection of data about project area, production of maps from satellite imagery and other sources, project management activities, travel, and data analysis and reporting. Variable costs generally include those related to the field sampling such as labor (supervisor and crew), equipment, transportation, camp maintenance, food, and housing. These Winrock International 26

27 variable costs can be partitioned to establish the cost of sampling a plot in a given strata or vegetation type (see Box 2). Factors that affect the cost of sampling a plot include travel time to plots, travel time to base camp (in large projects the base camp can change location), and time to measure the particular set of carbon pools within a plot. Plots in dense forests are likely to take more time to establish and measure than those in more open forests. Few carbon-offset projects have detailed cost data. One exception is the data for the Noel Kempff Climate Action Project collected during the initial carbon inventory phase. For the first inventory, total fixed costs were estimated to be about $196,000, variable costs per plot ranged between $230 (least dense strata) to $281 (very dense liana forests) for a total of about $154,000 (625 plots), and the grand total cost was about $350,000 (Powell 1999). The precision of the inventory, based on sampling error only, was ±4%. These costs do not cover the cost of measuring the amount of dead biomass produced per unit of wood harvested, a major component of the offset, in the logging impact plots. Measurements of this component were completed in the field season of 1999 and the cost analysis will be forthcoming. Using data from the Noel Kempff Climate Action Project, the effect of desired precision levels of the total carbon in vegetation and soil on total variable cost was investigated (Figure 2). The variable costs dropped rapidly from about $108,000 (452 plots) for a precision level of ±5% to $1,000 (four plots) for a level of ±30%; fixed costs would be the same for all levels of precision. Estimating future monitoring costs based on the first inventory is difficult because different sampling intensities will most likely be used (see section and above); but future monitoring costs are likely to be less expensive than the initial inventory. Variable costs per plot are not expected to decrease significantly, but the number of plots to be monitored in future years is likely to be fewer, thus the total variable cost will be less. Fixed costs are also expected to be lower in future monitoring events because of previous experience; however, several of the costs, such as production of updated maps, project management activities, travel, and data analysis and reporting, will still be incurred. Advances in technology are likely to reduce monitoring costs in the future, as discussed in the next section. Winrock International 27

28 120 [452 plots] 100 Variable costs ($K) [81 plots] 20 [14 plots] [4 plots] Precision level (%) (Fixed costs were about $196K) Figure 2. Relationship between level of desired precision (± % of total carbon storage; see Table 4) and total variable cost for the Noel Kempff Climate Action Project (data from Powell 1999) Technological tools for developing cost-efficient monitoring methods Remotely sensing can provide a useful means for monitoring LUCF projects, and a range of remote data collection technologies are now available ranging from satellite imagery to aerial photo-imagery from low flying airplanes. A promising advance in this area couples dual-camera digital videos (wide-angle and zoom) with a pulse laser profiler, data recorders, and differential GPS (geographical positioning system) mounted on a single engine plane (D. Slaymaker, pers. comm. 1999, approach in testing stage; Department of Forestry and Conservation Management, University of Massachusetts 1999). This system is able to produce indices of crown density, number of stems per unit area, and canopy height (from the pulse laser; Figure. 3), a combination of which is expected to correlate highly with aboveground forest biomass. The plane flies aerial transects across the project area at a fixed altitude of 1,000 feet above ground, capturing 200 m wide georeferenced strips and a resolution of 50 cm with the wide-angle camera, and a 20 m wide georeferenced strips and a 3 cm resolution with the zoom camera. The plane also flies at 4,000 feet above ground using 70 mm film to collect stereo images; these images are used to create 3-D models of the terrain (Figure 4). From analysis of these two sets of data, individual crowns, species types, and the presence of large emergent trees can readily be interpreted. This type of system will be especially useful for monitoring projects related to arresting or modifying logging and monitoring for small-scale human disturbance in protected forests as the presence and extent of forest gaps can readily be observed. Routine collection (every 3-5 years) of dualcamera videography data such as described here coupled with field measured or modeled data on Winrock International 28

29 carbon pools over the life of the project will be crucial for monitoring both the with-project activities and proxy without-project cases. Figure 3. Transect of the forest in the Noel Kempff Climate Action Project captured by a laser pulse profiler showing the variation in canopy height (from Dana Slaymaker 1999). The base level is 160 M. Figure 4. 3D image (color image converted to black and white) of a forest transect in the Noel Kempff Climate Action Project captured by the dual-camera videography system (from Dana Slaymaker 1999). Winrock International 29