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Options for monitoring and estimating historical carbon emissions from forest degradation in the context of REDD+

Options for monitoring and estimating historical carbon emissions from forest degradation in the... Measuring forest degradation and related forest carbon stock changes is more challenging than measuring deforestation since degradation implies changes in the structure of the forest and does not entail a change in land use, making it less easily detectable through remote sensing. Although we anticipate the use of the IPCC guidance under the United Framework Convention on Climate Change (UNFCCC), there is no one single method for monitoring forest degradation for the case of REDD+ policy. In this review paper we highlight that the choice depends upon a number of factors including the type of degradation, available historical data, capacities and resources, and the potentials and limitations of various measurement and monitoring approaches. Current degradation rates can be measured through field data (i.e. multi-date national forest inventories and permanent sample plot data, commercial forestry data sets, proxy data from domestic markets) and/or remote sensing data (i. e. direct mapping of canopy and forest structural changes or indirect mapping through modelling approaches), with the combination of techniques providing the best options. Developing countries frequently lack consistent historical field data for assessing past forest degradation, and so must rely more on remote sensing approaches mixed with current field assessments of carbon stock changes. Historical degradation estimates will have larger uncertainties as it will be difficult to determine their accuracy. However improving monitoring capacities for systematic forest degradation estimates today will help reduce uncertainties even for historical estimates. Keywords: REDD+, forest, global change, monitoring, deforestation, degradation, tropical countries, remote sensing Introduction stocks have neither been well characterized in space, From the perspective of the UNFCCC for REDD+, forest nor in time. degradation refers to a loss of carbon stock within forest To address climate change mitigation actions in the land. Forest disturbances that lead to degradation such forest sector, five different components have been as over-harvesting, forest fires, pests and climatic events agreed upon by Parties to the United Framework Con- including drought, wind, snow, ice, and floods have vention on Climate Change (UNFCCC) under negotia- been estimated to affect roughly 100 million of hectares tions for Reduced Emissions from Deforestation and globally per year [1,2]. This value represents almost 10 Degradation (REDD+). These include reducing defores- times the area that is affected by deforestation globally tation, reducing degradation, forest enhancement, sus- -1 (i.e. 13 million hayr tainable management of forests, and forest conservation. for 2000-2005) [3,4]. In particular, tropical regions are well known for large scale distur- The negotiations identify the need to establish national bances that lead to forest degradation [5-8], but over forest monitoring systems that use an appropriate com- large areas, the processes that reduce forest carbon bination of remote sensing and ground-based forest car- bon inventory approaches for estimating anthropogenic forest-related greenhouse gas emissions by sources, * Correspondence: martin.herold@wur.nl removals by sinks, and the need to establish reference Wageningen University. Center for Geoinformation, Droevendaalsesteeg 3, 6708 PB Wageningen. The Netherlands Full list of author information is available at the end of the article © 2011 Herold et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Herold et al. Carbon Balance and Management 2011, 6:13 Page 2 of 7 http://www.cbmjournal.com/content/6/1/13 emission levels using historical data and adjusted for methods to assess carbon stock changes in forest land national circumstances [9]. remaining forest land, using a combination of activity Issues related to assessing and monitoring forest data and emission factors. While deforestation usually degradation and associated carbon stock changes have removes almost all of the forest carbon stock perma- been subject to international debate on the political and nently, the losses in term of carbon stock due to forest technical level [10,11]. Recent history is of particular degradation depend on the type and the frequency of interest in the early stages of REDD+ implementation, the human-induced disturbances. The equation demon- in order to understand which drivers and activities have strates that the definition and distinction of deforesta- led to forest degradation and to quantify the carbon tion and degradation need to be clear, and that different emissions caused by this process to provide a reference types of degradation processes exist. emission level. Because of the risk that action on defor- estation may increase degradation, this is necessary to prove that REDD+ implementation has a positive impact [12]. Here we provide an overview of methods and (1) approaches for monitoring carbon emissions from forest degradation, with a focus on historical periods. We structure the review around a set of critical issues and assumptions, as follows: Forest degradation can be defined in many ways � REDD+ has specific monitoring requirements [15-17] but no single definition has been agreed upon at including a focus on the national level, the use of the international level. Forest degradation, from the point of IPCC guidance, the need to establish a reference emis- view of the UNFCCC for REDD+ purposes, refers to a sion level, and to assess how REDD+ policies and mea- loss of carbon stock within forest land that remain for- sures address the drivers and activities causing forest est land [11]. The UNFCCC also refers to anthropogenic carbon loss, emissions and removals. Thus, we assume that degrada- � TheIPCCguidancesuggeststheuseofactivitydata tion represents a human-induced negative impact on (changes in extent of areas affected) and emission fac- carbon stocks, with measured forest variables (i.e. tors (changes in carbon stock within areas) to estimate canopy cover) remaining above the threshold for the emissions on the national level, with most effort to be definition of a forest. This threshold and other para- put on the most important emission sources (i.e. key meters vary from country to country but need to be category analysis), and with different ways to handle applied consistently over time. uncertainties (i.e. different Tiers for carbon stock esti- Besides the definition, in the REDD+ context it is mation), encouraging continuous improvements over necessary to understand the drivers and activities caus- time, ing degradation. Such information is needed not only � Current and historical assessments of forest degrada- for formulating appropriate REDD+ strategies and poli- tion need to be consistent, in order through serial corre- cies, but also for the definition of suitable methods for lation to reduce the impact of absolute uncertainty, measuring and monitoring. Various types of degradation � Different methods including field measurement and will have different effects on the forest (carbon) and will remote sensing are needed to derive activity data and result in different types of indicators (i.e. trees being emission factors for different degradation processes. The removed, canopy damaged), which can be used for mon- data availability varies for differing historical periods and itoring degradation using in situ and remote methods. regions. Usually, different degradation processes are present within one country, with interactions among processes Discussion and recurrent events that leads to even more carbon Requirements for monitoring - definitions, drivers and the emissions. Forest degradation processes may or may not IPCC guidance affect large areas, but usually they are not equally dis- Equation 1 provides a conceptual overview of how to tributed over the country’s territory. They are often estimate gross carbon emission (Cgr_em) from forest focused on specific areas, and this should be considered land due to deforestation and loss of carbon stock in in national measurement and monitoring efforts [18,19]. forest land remaining forest land, at the national level. The main drivers for direct forest degradation include: Following the Good Practice Guidance for Land Use, a. Extraction of forest products for subsistence and Land-Use Change and Forestry (GPG-LULUCF) [13] local markets: privately or communally managed forests and the Guidelines for Agriculture, Forestry and Other are often subject to extraction of forest products for Land Use (AFOLU) [14], forest degradation uses Herold et al. Carbon Balance and Management 2011, 6:13 Page 3 of 7 http://www.cbmjournal.com/content/6/1/13 immediate use or sale by local households, such as col- actual inventories with repeated measurements to lection of fuelwood for cooking, collection of fruits, directly measure changes in forest biomass and/or well roots and other edible or medicinal tree parts, collection parameterized models in combination with plot data of fodder for livestock, and harvesting of timber and [10]. thatch for construction. In addition, most developing The IPCC guidelines [13] also provide the concept of countries have seen rapid urbanization in recent dec- key source categories that should be assessed and ades, which has created a market for forest-based pro- selected. A key source category is “an emission or sink ducts (i.e. charcoal) that, in some cases, has resulted in category that is prioritized within the national inventory system because its estimate has a significant influence forest degradation. b. Industrial/commercial extraction of forest pro- on a country’s total inventory of direct greenhouse gases ducts: Large scale selective logging and other harvesting in terms of the absolute level of emissions, the trend in practices often occur in unregulated forest areas, exacer- emissions, or both” [13]. Key source categories should bated by poor logging practices such as multiple entries be estimated using higher tiers where possible and thus into forests [20]. help to focus the available monitoring resources on the c. Uncontrolled anthropogenic wildfire: This is a most important components. major source of degradation in many types of forests, and may be deliberate or accidental. Field observations and expert surveys to assess UNFCCC Decision 4/CP.15 [9] requests: “To use the degradation most recent Intergovernmental Panel on Climate A critical step in estimating forest degradation is a well Change guidance and guidelines, as adopted or encour- designed and implemented field sampling scheme to aged by the Conference of the Parties, as appropriate, as collect carbon stock data on the ground, in order to a basis for estimating anthropogenic forest-related assess carbon stock changes over time. Field methods to greenhouse gas emissions by sources and removals by evaluate carbon stock changes include [10]: sinks, forest carbon stocks and forest area changes”.In this context, countries should consider two measure- ➣ Inventory-based approaches (national, sub- ment components to estimate the emissions associated national), with forest degradation: ➣ Data from targeted field surveys (including inter- 1) Areas of forest that remain forest and are affected views) and from research and permanent sample by degradation (considered at the national level), ideally plots, often implemented as local studies, stratified into different disturbances or degradation ➣ Commercial forestry data (i.e. logging concessions types. How much forest area, and where, is undergoing and harvest estimates), degradation? Such statistics, calculated through forest ➣ Proxy data from domestic markets (charcoal, sub- inventories or through remote sensing, are also referred sistence) such as timber production rates estimated to as Activity Data (AD). The GPG-LULUCF identifies from sawmill, sales, and export statistics [21]. three approaches to represent land areas, in increasing order of complexity [13]. For the assessment of forest If available, the collection of national forest data degradation, only the mostcomplex thirdapproach through periodic forest inventories since the 1980s seems most appropriate, where changes in land use allows the estimation of emissions associated with his- categories can be tracked on a spatial basis [10]. torical and current forest degradation processes [22]. 2) Changes in forest carbon stocks due to the degra- When designing the sampling scheme of a National For- dation processes per unit area. How much carbon is lost est Inventory, both the forest ecology and forest type are from the forests and released to the atmosphere due to important in determining the expected biomass content the degradation process? Such amounts, commonly and general properties of growth dynamics, and human measured through forest field sampling and repeated practices that alter forest carbon, including degradation -1 -1 forest inventories (and reported as MgCha yr ) are also activities that reduce the carbon stock, need to be con- referred to as Emission Factors (EF). These changes sidered [23] and data collected stratified accordingly. should be calculated for each of the five forest carbon Interactions between drivers, where significant, also pools: aboveground biomass, belowground biomass, need to be taken into account. deadwood, litter, and soil organic matter [13]. The IPCC The estimation of forest carbon stock change with [13] provides three tiers for estimating emissions, with relatively low uncertainty (i.e. at Tier 3 level) assumes increasing levels of data requirements, analytical com- that consistent measurements are made at different plexity and increasing accuracy. Tier 1 uses IPCC points in time, i.e. before the degradation and at several default values; Tier 2 uses country-specific data (i.e. col- points in time afterwards, to establish reliable emission factors. In most developing countries, however, the lected within the national boundary) and Tier 3 uses Herold et al. Carbon Balance and Management 2011, 6:13 Page 4 of 7 http://www.cbmjournal.com/content/6/1/13 necessary long-term forest datasets are almost non-exis- to be derived. Not all degradation processes can be moni- tent, or are focused on specific field assessments for tored with high certainty using remote sensing data (Table commercial timber which cover only limited parts of the 1). The more severe the degradation and the canopy country. In these cases, the time variable has to be sub- damage, the easier it is to accurately map it from satellite stituted by space (e.g. evaluating the net carbon stock observations [25]. Mapping from aircraft provides much decreases over a large area where all the successional more detail and resolves most of the limitations inherent stages of managed and unmanaged forests are present). to space-based measurements [26-28]. This latter approach would consider the carbon stocks Mapping forest degradation with remote sensing data is more challenging than mapping deforestation [29] of intact and unmanaged forests as the reference value and by comparison would estimate the emissions of the because the degraded forest is a complex mix of differ- degraded forests per unit of area. ent land cover types (vegetation, dead trees, soil, shade) Permanent sample plots are typically used to monitor and the signature of the degradation often changes changes in studies on forest resources and temporal within 1-2 years [30-32]. So far, to address forest degra- dynamics. When historical records exist, it is worthwhile dation, medium spatial resolution sensors, such as Land- repeating measurements using the same sampling sat, ASTER and SPOT, have mostly been used for scheme. Forest inventory data are routinely collected by degradation mapping. High and very high resolution forestry organizations in many countries and are usually satellite imagery, such as Ikonos or Quickbird, and aerial not focused on assessing the impact of forest degrada- digital imagery acquired with videographyhavealso tion on carbon stocks. However, earlier inventories, for been used. Methods for mapping forest degradation example those that focus on merchantable volumes of range from simple image interpretation to highly sophis- commercially interesting species, can be correlated with ticated automated algorithms [10]. similar inventories in the present era, supplemented by With these issues in mind, there are three main information on forest properties that allows for the approaches to evaluating forest degradation with remote assessment of biomass, enabling an estimate of historical sensing: biomass content of the forest [24]. ➣ Direct detection of degradation processes (obser- Remote sensing methods to measure degradation ving forest canopy damage) and area changes, in Measurement and monitoring of the area affected by for- which the features of interest to be enhanced and est degradation through remote sensing offers a series of extracted from the satellite imagery consist of forest advantages: i) it represents a consistent, coherent, trans- canopy gaps, small clearings and the structural forest changes resulting from disturbance [31,33,34]. This parent and fairly accurate way of reporting on area, and it allows for near-real time reporting on land use changes, ii) approach requires frequent mapping because the it offers spatially detailed national data even on remote spatial signatures of the degraded forests change and logistically complicated regions, and iii) it is the only once canopy gaps close (i.e. gaps are covered by approach that offers, potentially at least, objective informa- low-biomass secondary species). tion on historical trends in areas where data do not exist ➣ Indirect approaches (observing human infrastruc- today. However, it also has several disadvantages: i) it can ture) are useful when degradation intensity is low (lit- be hampered by clouds in some regions (for optical data), tle canopy damage) or when the direct approach ii) it is limited by the technical capacity to sense and cannot be applied due to infrequent coverage and lit- record the change in canopy cover (for fine-scale changes) tle spectral evidence remains from the canopy gaps. and iii) image interpretations may be difficult equivocal The remote sensing analysis focuses on the spatial and/or labor intensive, especially if national estimates are distribution and evolution of human infrastructure (i. Table 1 Forest degradation activities and their degree of detection using Landsat-type data, adapted from [44]. Highly Detectable Detection limited & increasing data/ Detection very limited effort � Deforestation � Selective logging � Harvesting of most non-timber plants � Forest fragmentation � Forest surface fires products � Recent slash-and-burn agriculture � A range of edge-effects � Low-mechanized selective logging � Major canopy fires � Oldslash-and-burn agriculture � Narrow roads (< 6 m wide) � Major roads � Small scale mining � Understory thinning and clear cutting � Conversion to tree monoculture � Unpaved secondary roads (6-20 m wide) � Invasion of exotic species � Hydroelectric dams and other forms of flood � Selective thinning of canopy trees disturbances � Large-scale mining Herold et al. Carbon Balance and Management 2011, 6:13 Page 5 of 7 http://www.cbmjournal.com/content/6/1/13 e. roads, population centers), which is used as a proxy degradation associated with local markets and subsis- for newly degraded areas [35,36]. This method works tence, where the historical field data sources are gener- best to map newly degraded forest areas but is less ally rare and where remote sensing approaches have effective for repeated degradation. limited ability to provide information based on archived ➣ Monitoring carbon emissions from biomass burn- data. In this case, historical reference emission levels ing. This approach includes three primary categories: can hardly be established, particularly at the national detection of active fires, mapping of post-fire burned level. areas (fire scars) and fire characterization (e.g. fire Historical monitoring of industrial/commercial extrac- tion of forest products can benefit from the use of severity, energy released). For the purposes of emis- sion estimation, the latter two categories, described archived satellite data, which could be analyzed with the in GOFC-GOLD (2010), are more relevant. The ‘bot- support of other data sources such as forestry conces- tom up’ method [37] uses the area affected by fire, sion data. Specific emission factors can be estimated the fuel loading per unit area, the proportion of bio- from present-day data on carbon stock losses due to mass consumed as a result of fire (combustion fac- similar degradation processes (i.e. as occurring at pre- tor) and the emission factor. A recently proposed sent) and by studying their chronosequences, applied alternative is directly to measure the power emitted consistently for historically periods with suitable activity by actively burning fires and to derive from this data. In this case the estimation of historical reference value the total biomass consumed [38,39]. However, emissions is driven by the activity data. A similar this approach is less suitable for historical periods. approach could be applied for the case of fires. Table 2 is focused on the changes in the aboveground carbon pool, which is perhaps the most recognized and Conclusions obvious carbon pool to estimate [41]. It is to be recog- Many developing countries will not have the data and nized that measuring the carbon stock changes caused capacities to provide suitable carbon emissions estimates by forest degradation in each pool within a country at on all types of forest degradation for historical periods consistent levels of detail and accuracy is unlikely to be [40]. Table 2 provides an overview of data source possible. It may be advisable to focus monitoring on the options for different degradation processes and drivers. most important categories (i.e. through an IPCC key Estimation of forest carbon changes in from historical source category analysis) and on specific areas within degradation processes are unlikely to be able to rely on the country. This would help to make the monitoring existing past data in many countries as there are little or more targeted and efficient, capturing the most impor- tant components [18,23]. In this context, there is a need no historical field data available. Remote sensing to establish extend and recent carbon density determina- to explore advanced approaches for spatial-temporal tion remains the only source to provide data for asses- field sampling schemes, incorporating types of forest sing past trends. This is particularly evident for degradation by intensity and age, and integrating them Table 2 Options for estimating activity data and emission factors for historical degradation on the national level beyond the use of default data (Tier 1) Activity and driver of forest Suitable and available data sources for activity Suitable and available data sources for emission degradation data (on national level) factors (on national level) Extraction of forest products for � Limited historical data � Limited historical data subsistence and local markets, such � Information from local scale studies or national � Information from local scale studies, community- as fuelwood and charcoal proxies (i.e. population growth and wood demand), if based monitoring or permanent sample plots, if available available � Only long-term cumulative changes may be observed � Emission factors can be measured at present time from historical satellite data and applied consistently for historical periods with suitable activity data Industrial/commercial extraction of � Historical satellite data (Landsat time series) analysed � National forest inventories and harvest estimates forest products such as selective with concession areas from commercial forestry (i.e. company records of logging � Direct approach should be explored for recent years wood volume extracted in selective logging activities (i.e. since year circa-2000, depending on national in the past), if available coverage) and indirect approach for longer periods � Emission factors can be measured today and can be (back to 1990) applied consistently for historical periods with suitable activity data Other disturbances such as � Historical satellite-based fire data records (since 2000) � Emission factors can be measured today and can be (uncontrolled) wildfires to be analysed with Landsat-type data applied consistently for historical periods with suitable activity data Herold et al. Carbon Balance and Management 2011, 6:13 Page 6 of 7 http://www.cbmjournal.com/content/6/1/13 conservation, sustainable management of forests and enhancement of with historical remote sensing data. In addition, we forest carbon stocks in developing countries, Decision COP 15/4. 2009. would also like to point out some examples on how 10. GOFC-GOLD: A sourcebook of methods and procedures for monitoring uncertainties can be handled in a REDD+ implementa- and reporting anthropogenic greenhouse gas emissions and removals caused by deforestation, gains and losses of carbon stocks in forest tion context [42,43]. remaining forests, and forestation. GOFC-GOLD Report version COP15-1 edition 2010 [http://www.gofc-gold.uni-jena.de/redd/]. 11. UNFCCC: Informal meeting of experts on methodological issues related Acknowledgements to forest degradation. Chair’s summary of key messages. 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Trends in Ecology & Evolution 2006, 21:227-229. and take full advantage of: doi:10.1186/1750-0680-6-13 • Convenient online submission Cite this article as: Herold et al.: Options for monitoring and estimating historical carbon emissions from forest degradation in the context of • Thorough peer review REDD+. Carbon Balance and Management 2011 6:13. • No space constraints or color figure charges • Immediate publication on acceptance • Inclusion in PubMed, CAS, Scopus and Google Scholar • Research which is freely available for redistribution Submit your manuscript at www.biomedcentral.com/submit http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Carbon Balance and Management Springer Journals

Options for monitoring and estimating historical carbon emissions from forest degradation in the context of REDD+

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Copyright © 2011 by Herold et al; licensee BioMed Central Ltd.
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Environment; Environmental Management; Ecosystems; Forestry
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Abstract

Measuring forest degradation and related forest carbon stock changes is more challenging than measuring deforestation since degradation implies changes in the structure of the forest and does not entail a change in land use, making it less easily detectable through remote sensing. Although we anticipate the use of the IPCC guidance under the United Framework Convention on Climate Change (UNFCCC), there is no one single method for monitoring forest degradation for the case of REDD+ policy. In this review paper we highlight that the choice depends upon a number of factors including the type of degradation, available historical data, capacities and resources, and the potentials and limitations of various measurement and monitoring approaches. Current degradation rates can be measured through field data (i.e. multi-date national forest inventories and permanent sample plot data, commercial forestry data sets, proxy data from domestic markets) and/or remote sensing data (i. e. direct mapping of canopy and forest structural changes or indirect mapping through modelling approaches), with the combination of techniques providing the best options. Developing countries frequently lack consistent historical field data for assessing past forest degradation, and so must rely more on remote sensing approaches mixed with current field assessments of carbon stock changes. Historical degradation estimates will have larger uncertainties as it will be difficult to determine their accuracy. However improving monitoring capacities for systematic forest degradation estimates today will help reduce uncertainties even for historical estimates. Keywords: REDD+, forest, global change, monitoring, deforestation, degradation, tropical countries, remote sensing Introduction stocks have neither been well characterized in space, From the perspective of the UNFCCC for REDD+, forest nor in time. degradation refers to a loss of carbon stock within forest To address climate change mitigation actions in the land. Forest disturbances that lead to degradation such forest sector, five different components have been as over-harvesting, forest fires, pests and climatic events agreed upon by Parties to the United Framework Con- including drought, wind, snow, ice, and floods have vention on Climate Change (UNFCCC) under negotia- been estimated to affect roughly 100 million of hectares tions for Reduced Emissions from Deforestation and globally per year [1,2]. This value represents almost 10 Degradation (REDD+). These include reducing defores- times the area that is affected by deforestation globally tation, reducing degradation, forest enhancement, sus- -1 (i.e. 13 million hayr tainable management of forests, and forest conservation. for 2000-2005) [3,4]. In particular, tropical regions are well known for large scale distur- The negotiations identify the need to establish national bances that lead to forest degradation [5-8], but over forest monitoring systems that use an appropriate com- large areas, the processes that reduce forest carbon bination of remote sensing and ground-based forest car- bon inventory approaches for estimating anthropogenic forest-related greenhouse gas emissions by sources, * Correspondence: martin.herold@wur.nl removals by sinks, and the need to establish reference Wageningen University. Center for Geoinformation, Droevendaalsesteeg 3, 6708 PB Wageningen. The Netherlands Full list of author information is available at the end of the article © 2011 Herold et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Herold et al. Carbon Balance and Management 2011, 6:13 Page 2 of 7 http://www.cbmjournal.com/content/6/1/13 emission levels using historical data and adjusted for methods to assess carbon stock changes in forest land national circumstances [9]. remaining forest land, using a combination of activity Issues related to assessing and monitoring forest data and emission factors. While deforestation usually degradation and associated carbon stock changes have removes almost all of the forest carbon stock perma- been subject to international debate on the political and nently, the losses in term of carbon stock due to forest technical level [10,11]. Recent history is of particular degradation depend on the type and the frequency of interest in the early stages of REDD+ implementation, the human-induced disturbances. The equation demon- in order to understand which drivers and activities have strates that the definition and distinction of deforesta- led to forest degradation and to quantify the carbon tion and degradation need to be clear, and that different emissions caused by this process to provide a reference types of degradation processes exist. emission level. Because of the risk that action on defor- estation may increase degradation, this is necessary to prove that REDD+ implementation has a positive impact [12]. Here we provide an overview of methods and (1) approaches for monitoring carbon emissions from forest degradation, with a focus on historical periods. We structure the review around a set of critical issues and assumptions, as follows: Forest degradation can be defined in many ways � REDD+ has specific monitoring requirements [15-17] but no single definition has been agreed upon at including a focus on the national level, the use of the international level. Forest degradation, from the point of IPCC guidance, the need to establish a reference emis- view of the UNFCCC for REDD+ purposes, refers to a sion level, and to assess how REDD+ policies and mea- loss of carbon stock within forest land that remain for- sures address the drivers and activities causing forest est land [11]. The UNFCCC also refers to anthropogenic carbon loss, emissions and removals. Thus, we assume that degrada- � TheIPCCguidancesuggeststheuseofactivitydata tion represents a human-induced negative impact on (changes in extent of areas affected) and emission fac- carbon stocks, with measured forest variables (i.e. tors (changes in carbon stock within areas) to estimate canopy cover) remaining above the threshold for the emissions on the national level, with most effort to be definition of a forest. This threshold and other para- put on the most important emission sources (i.e. key meters vary from country to country but need to be category analysis), and with different ways to handle applied consistently over time. uncertainties (i.e. different Tiers for carbon stock esti- Besides the definition, in the REDD+ context it is mation), encouraging continuous improvements over necessary to understand the drivers and activities caus- time, ing degradation. Such information is needed not only � Current and historical assessments of forest degrada- for formulating appropriate REDD+ strategies and poli- tion need to be consistent, in order through serial corre- cies, but also for the definition of suitable methods for lation to reduce the impact of absolute uncertainty, measuring and monitoring. Various types of degradation � Different methods including field measurement and will have different effects on the forest (carbon) and will remote sensing are needed to derive activity data and result in different types of indicators (i.e. trees being emission factors for different degradation processes. The removed, canopy damaged), which can be used for mon- data availability varies for differing historical periods and itoring degradation using in situ and remote methods. regions. Usually, different degradation processes are present within one country, with interactions among processes Discussion and recurrent events that leads to even more carbon Requirements for monitoring - definitions, drivers and the emissions. Forest degradation processes may or may not IPCC guidance affect large areas, but usually they are not equally dis- Equation 1 provides a conceptual overview of how to tributed over the country’s territory. They are often estimate gross carbon emission (Cgr_em) from forest focused on specific areas, and this should be considered land due to deforestation and loss of carbon stock in in national measurement and monitoring efforts [18,19]. forest land remaining forest land, at the national level. The main drivers for direct forest degradation include: Following the Good Practice Guidance for Land Use, a. Extraction of forest products for subsistence and Land-Use Change and Forestry (GPG-LULUCF) [13] local markets: privately or communally managed forests and the Guidelines for Agriculture, Forestry and Other are often subject to extraction of forest products for Land Use (AFOLU) [14], forest degradation uses Herold et al. Carbon Balance and Management 2011, 6:13 Page 3 of 7 http://www.cbmjournal.com/content/6/1/13 immediate use or sale by local households, such as col- actual inventories with repeated measurements to lection of fuelwood for cooking, collection of fruits, directly measure changes in forest biomass and/or well roots and other edible or medicinal tree parts, collection parameterized models in combination with plot data of fodder for livestock, and harvesting of timber and [10]. thatch for construction. In addition, most developing The IPCC guidelines [13] also provide the concept of countries have seen rapid urbanization in recent dec- key source categories that should be assessed and ades, which has created a market for forest-based pro- selected. A key source category is “an emission or sink ducts (i.e. charcoal) that, in some cases, has resulted in category that is prioritized within the national inventory system because its estimate has a significant influence forest degradation. b. Industrial/commercial extraction of forest pro- on a country’s total inventory of direct greenhouse gases ducts: Large scale selective logging and other harvesting in terms of the absolute level of emissions, the trend in practices often occur in unregulated forest areas, exacer- emissions, or both” [13]. Key source categories should bated by poor logging practices such as multiple entries be estimated using higher tiers where possible and thus into forests [20]. help to focus the available monitoring resources on the c. Uncontrolled anthropogenic wildfire: This is a most important components. major source of degradation in many types of forests, and may be deliberate or accidental. Field observations and expert surveys to assess UNFCCC Decision 4/CP.15 [9] requests: “To use the degradation most recent Intergovernmental Panel on Climate A critical step in estimating forest degradation is a well Change guidance and guidelines, as adopted or encour- designed and implemented field sampling scheme to aged by the Conference of the Parties, as appropriate, as collect carbon stock data on the ground, in order to a basis for estimating anthropogenic forest-related assess carbon stock changes over time. Field methods to greenhouse gas emissions by sources and removals by evaluate carbon stock changes include [10]: sinks, forest carbon stocks and forest area changes”.In this context, countries should consider two measure- ➣ Inventory-based approaches (national, sub- ment components to estimate the emissions associated national), with forest degradation: ➣ Data from targeted field surveys (including inter- 1) Areas of forest that remain forest and are affected views) and from research and permanent sample by degradation (considered at the national level), ideally plots, often implemented as local studies, stratified into different disturbances or degradation ➣ Commercial forestry data (i.e. logging concessions types. How much forest area, and where, is undergoing and harvest estimates), degradation? Such statistics, calculated through forest ➣ Proxy data from domestic markets (charcoal, sub- inventories or through remote sensing, are also referred sistence) such as timber production rates estimated to as Activity Data (AD). The GPG-LULUCF identifies from sawmill, sales, and export statistics [21]. three approaches to represent land areas, in increasing order of complexity [13]. For the assessment of forest If available, the collection of national forest data degradation, only the mostcomplex thirdapproach through periodic forest inventories since the 1980s seems most appropriate, where changes in land use allows the estimation of emissions associated with his- categories can be tracked on a spatial basis [10]. torical and current forest degradation processes [22]. 2) Changes in forest carbon stocks due to the degra- When designing the sampling scheme of a National For- dation processes per unit area. How much carbon is lost est Inventory, both the forest ecology and forest type are from the forests and released to the atmosphere due to important in determining the expected biomass content the degradation process? Such amounts, commonly and general properties of growth dynamics, and human measured through forest field sampling and repeated practices that alter forest carbon, including degradation -1 -1 forest inventories (and reported as MgCha yr ) are also activities that reduce the carbon stock, need to be con- referred to as Emission Factors (EF). These changes sidered [23] and data collected stratified accordingly. should be calculated for each of the five forest carbon Interactions between drivers, where significant, also pools: aboveground biomass, belowground biomass, need to be taken into account. deadwood, litter, and soil organic matter [13]. The IPCC The estimation of forest carbon stock change with [13] provides three tiers for estimating emissions, with relatively low uncertainty (i.e. at Tier 3 level) assumes increasing levels of data requirements, analytical com- that consistent measurements are made at different plexity and increasing accuracy. Tier 1 uses IPCC points in time, i.e. before the degradation and at several default values; Tier 2 uses country-specific data (i.e. col- points in time afterwards, to establish reliable emission factors. In most developing countries, however, the lected within the national boundary) and Tier 3 uses Herold et al. Carbon Balance and Management 2011, 6:13 Page 4 of 7 http://www.cbmjournal.com/content/6/1/13 necessary long-term forest datasets are almost non-exis- to be derived. Not all degradation processes can be moni- tent, or are focused on specific field assessments for tored with high certainty using remote sensing data (Table commercial timber which cover only limited parts of the 1). The more severe the degradation and the canopy country. In these cases, the time variable has to be sub- damage, the easier it is to accurately map it from satellite stituted by space (e.g. evaluating the net carbon stock observations [25]. Mapping from aircraft provides much decreases over a large area where all the successional more detail and resolves most of the limitations inherent stages of managed and unmanaged forests are present). to space-based measurements [26-28]. This latter approach would consider the carbon stocks Mapping forest degradation with remote sensing data is more challenging than mapping deforestation [29] of intact and unmanaged forests as the reference value and by comparison would estimate the emissions of the because the degraded forest is a complex mix of differ- degraded forests per unit of area. ent land cover types (vegetation, dead trees, soil, shade) Permanent sample plots are typically used to monitor and the signature of the degradation often changes changes in studies on forest resources and temporal within 1-2 years [30-32]. So far, to address forest degra- dynamics. When historical records exist, it is worthwhile dation, medium spatial resolution sensors, such as Land- repeating measurements using the same sampling sat, ASTER and SPOT, have mostly been used for scheme. Forest inventory data are routinely collected by degradation mapping. High and very high resolution forestry organizations in many countries and are usually satellite imagery, such as Ikonos or Quickbird, and aerial not focused on assessing the impact of forest degrada- digital imagery acquired with videographyhavealso tion on carbon stocks. However, earlier inventories, for been used. Methods for mapping forest degradation example those that focus on merchantable volumes of range from simple image interpretation to highly sophis- commercially interesting species, can be correlated with ticated automated algorithms [10]. similar inventories in the present era, supplemented by With these issues in mind, there are three main information on forest properties that allows for the approaches to evaluating forest degradation with remote assessment of biomass, enabling an estimate of historical sensing: biomass content of the forest [24]. ➣ Direct detection of degradation processes (obser- Remote sensing methods to measure degradation ving forest canopy damage) and area changes, in Measurement and monitoring of the area affected by for- which the features of interest to be enhanced and est degradation through remote sensing offers a series of extracted from the satellite imagery consist of forest advantages: i) it represents a consistent, coherent, trans- canopy gaps, small clearings and the structural forest changes resulting from disturbance [31,33,34]. This parent and fairly accurate way of reporting on area, and it allows for near-real time reporting on land use changes, ii) approach requires frequent mapping because the it offers spatially detailed national data even on remote spatial signatures of the degraded forests change and logistically complicated regions, and iii) it is the only once canopy gaps close (i.e. gaps are covered by approach that offers, potentially at least, objective informa- low-biomass secondary species). tion on historical trends in areas where data do not exist ➣ Indirect approaches (observing human infrastruc- today. However, it also has several disadvantages: i) it can ture) are useful when degradation intensity is low (lit- be hampered by clouds in some regions (for optical data), tle canopy damage) or when the direct approach ii) it is limited by the technical capacity to sense and cannot be applied due to infrequent coverage and lit- record the change in canopy cover (for fine-scale changes) tle spectral evidence remains from the canopy gaps. and iii) image interpretations may be difficult equivocal The remote sensing analysis focuses on the spatial and/or labor intensive, especially if national estimates are distribution and evolution of human infrastructure (i. Table 1 Forest degradation activities and their degree of detection using Landsat-type data, adapted from [44]. Highly Detectable Detection limited & increasing data/ Detection very limited effort � Deforestation � Selective logging � Harvesting of most non-timber plants � Forest fragmentation � Forest surface fires products � Recent slash-and-burn agriculture � A range of edge-effects � Low-mechanized selective logging � Major canopy fires � Oldslash-and-burn agriculture � Narrow roads (< 6 m wide) � Major roads � Small scale mining � Understory thinning and clear cutting � Conversion to tree monoculture � Unpaved secondary roads (6-20 m wide) � Invasion of exotic species � Hydroelectric dams and other forms of flood � Selective thinning of canopy trees disturbances � Large-scale mining Herold et al. Carbon Balance and Management 2011, 6:13 Page 5 of 7 http://www.cbmjournal.com/content/6/1/13 e. roads, population centers), which is used as a proxy degradation associated with local markets and subsis- for newly degraded areas [35,36]. This method works tence, where the historical field data sources are gener- best to map newly degraded forest areas but is less ally rare and where remote sensing approaches have effective for repeated degradation. limited ability to provide information based on archived ➣ Monitoring carbon emissions from biomass burn- data. In this case, historical reference emission levels ing. This approach includes three primary categories: can hardly be established, particularly at the national detection of active fires, mapping of post-fire burned level. areas (fire scars) and fire characterization (e.g. fire Historical monitoring of industrial/commercial extrac- tion of forest products can benefit from the use of severity, energy released). For the purposes of emis- sion estimation, the latter two categories, described archived satellite data, which could be analyzed with the in GOFC-GOLD (2010), are more relevant. The ‘bot- support of other data sources such as forestry conces- tom up’ method [37] uses the area affected by fire, sion data. Specific emission factors can be estimated the fuel loading per unit area, the proportion of bio- from present-day data on carbon stock losses due to mass consumed as a result of fire (combustion fac- similar degradation processes (i.e. as occurring at pre- tor) and the emission factor. A recently proposed sent) and by studying their chronosequences, applied alternative is directly to measure the power emitted consistently for historically periods with suitable activity by actively burning fires and to derive from this data. In this case the estimation of historical reference value the total biomass consumed [38,39]. However, emissions is driven by the activity data. A similar this approach is less suitable for historical periods. approach could be applied for the case of fires. Table 2 is focused on the changes in the aboveground carbon pool, which is perhaps the most recognized and Conclusions obvious carbon pool to estimate [41]. It is to be recog- Many developing countries will not have the data and nized that measuring the carbon stock changes caused capacities to provide suitable carbon emissions estimates by forest degradation in each pool within a country at on all types of forest degradation for historical periods consistent levels of detail and accuracy is unlikely to be [40]. Table 2 provides an overview of data source possible. It may be advisable to focus monitoring on the options for different degradation processes and drivers. most important categories (i.e. through an IPCC key Estimation of forest carbon changes in from historical source category analysis) and on specific areas within degradation processes are unlikely to be able to rely on the country. This would help to make the monitoring existing past data in many countries as there are little or more targeted and efficient, capturing the most impor- tant components [18,23]. In this context, there is a need no historical field data available. Remote sensing to establish extend and recent carbon density determina- to explore advanced approaches for spatial-temporal tion remains the only source to provide data for asses- field sampling schemes, incorporating types of forest sing past trends. This is particularly evident for degradation by intensity and age, and integrating them Table 2 Options for estimating activity data and emission factors for historical degradation on the national level beyond the use of default data (Tier 1) Activity and driver of forest Suitable and available data sources for activity Suitable and available data sources for emission degradation data (on national level) factors (on national level) Extraction of forest products for � Limited historical data � Limited historical data subsistence and local markets, such � Information from local scale studies or national � Information from local scale studies, community- as fuelwood and charcoal proxies (i.e. population growth and wood demand), if based monitoring or permanent sample plots, if available available � Only long-term cumulative changes may be observed � Emission factors can be measured at present time from historical satellite data and applied consistently for historical periods with suitable activity data Industrial/commercial extraction of � Historical satellite data (Landsat time series) analysed � National forest inventories and harvest estimates forest products such as selective with concession areas from commercial forestry (i.e. company records of logging � Direct approach should be explored for recent years wood volume extracted in selective logging activities (i.e. since year circa-2000, depending on national in the past), if available coverage) and indirect approach for longer periods � Emission factors can be measured today and can be (back to 1990) applied consistently for historical periods with suitable activity data Other disturbances such as � Historical satellite-based fire data records (since 2000) � Emission factors can be measured today and can be (uncontrolled) wildfires to be analysed with Landsat-type data applied consistently for historical periods with suitable activity data Herold et al. Carbon Balance and Management 2011, 6:13 Page 6 of 7 http://www.cbmjournal.com/content/6/1/13 conservation, sustainable management of forests and enhancement of with historical remote sensing data. In addition, we forest carbon stocks in developing countries, Decision COP 15/4. 2009. would also like to point out some examples on how 10. GOFC-GOLD: A sourcebook of methods and procedures for monitoring uncertainties can be handled in a REDD+ implementa- and reporting anthropogenic greenhouse gas emissions and removals caused by deforestation, gains and losses of carbon stocks in forest tion context [42,43]. remaining forests, and forestation. GOFC-GOLD Report version COP15-1 edition 2010 [http://www.gofc-gold.uni-jena.de/redd/]. 11. UNFCCC: Informal meeting of experts on methodological issues related Acknowledgements to forest degradation. Chair’s summary of key messages. 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Published: Nov 24, 2011

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