Changes In Forest Carbon Stocks Research Articles

Imputing forest carbon stock estimates from inventory plots to a nationally continuous coverage.

The U.S. has been providing national-scale estimates of forest carbon (C) stocks and stock change to meet United Nations Framework Convention on Climate Change (UNFCCC) reporting requirements for years. Although these currently are provided as national estimates by pool and year to meet greenhouse gas monitoring requirements, there is growing need to disaggregate these estimates to finer scales to enable strategic forest management and monitoring activities focused on various ecosystem services such as C storage enhancement. Through application of a nearest-neighbor imputation approach, spatially extant estimates of forest C density were developed for the conterminous U.S. using the U.S.’s annual forest inventory. Results suggest that an existing forest inventory plot imputation approach can be readily modified to provide raster maps of C density across a range of pools (e.g., live tree to soil organic carbon) and spatial scales (e.g., sub-county to biome). Comparisons among imputed maps indicate strong regional differences across C pools. The C density of pools closely related to detrital input (e.g., dead wood) is often highest in forests suffering from recent mortality events such as those in the northern Rocky Mountains (e.g., beetle infestations). In contrast, live tree carbon density is often highest on the highest quality forest sites such as those found in the Pacific Northwest. Validation results suggest strong agreement between the estimates produced from the forest inventory plots and those from the imputed maps, particularly when the C pool is closely associated with the imputation model (e.g., aboveground live biomass and live tree basal area), with weaker agreement for detrital pools (e.g., standing dead trees). Forest inventory imputed plot maps provide an efficient and flexible approach to monitoring diverse C pools at national (e.g., UNFCCC) and regional scales (e.g., Reducing Emissions from Deforestation and Forest Degradation projects) while allowing timely incorporation of empirical data (e.g., annual forest inventory).

High-resolution mapping of forest carbon stocks in the Colombian Amazon

Abstract. High-resolution mapping of tropical forest carbon stocks can assist forest management and improve implementation of large-scale carbon retention and enhancement programs. Previous high-resolution approaches have relied on field plot and/or light detection and ranging (LiDAR) samples of aboveground carbon density, which are typically upscaled to larger geographic areas using stratification maps. Such efforts often rely on detailed vegetation maps to stratify the region for sampling, but existing tropical forest maps are often too coarse and field plots too sparse for high-resolution carbon assessments. We developed a top-down approach for high-resolution carbon mapping in a 16.5 million ha region (> 40%) of the Colombian Amazon – a remote landscape seldom documented. We report on three advances for large-scale carbon mapping: (i) employing a universal approach to airborne LiDAR-calibration with limited field data; (ii) quantifying environmental controls over carbon densities; and (iii) developing stratification- and regression-based approaches for scaling up to regions outside of LiDAR coverage. We found that carbon stocks are predicted by a combination of satellite-derived elevation, fractional canopy cover and terrain ruggedness, allowing upscaling of the LiDAR samples to the full 16.5 million ha region. LiDAR-derived carbon maps have 14% uncertainty at 1 ha resolution, and the regional map based on stratification has 28% uncertainty in any given hectare. High-resolution approaches with quantifiable pixel-scale uncertainties will provide the most confidence for monitoring changes in tropical forest carbon stocks. Improved confidence will allow resource managers and decision makers to more rapidly and effectively implement actions that better conserve and utilize forests in tropical regions.

Quantifying the effects of climate change and harvesting on carbon dynamics of boreal aspen and jack pine forests using the TRIPLEX-Management model

A model that accurately evaluates changes in forest productivity and carbon (C) stocks in response to climate change and forest management will permit us to assess the impact of global changes. The goal of this study is to forecast potential effects of climate change and clearcuts on C dynamics of boreal trembling aspen (Populus tremuloides Michx.) and jack pine (Pinus banksiana Lamb.) forests near the southern edge of the boreal forest in Saskatchewan, Canada. We validated the TRIPLEX-Management model against eddy covariance measurements, C stocks, and growth data. Constant climate (repeated measurements) and four climate change scenarios (IPCC SRES A2 and B1) generated from Coupled Global Climate Model (CGCM3.1) and the Model for Interdisciplinary Research on Climate (MIROC3.2), respectively, were used in scenario simulations. Clearcuts were assumed to occur in 2010 and 2055 for each forest type. Normalized root mean square error (NRMSE) between simulated and observed variables including C fluxes, C stocks (e.g., aboveground biomass C and soil organic C), and stand characteristics such as mean DBH (diameter at breast height) and stand density ranged from 11% to 22%. The Willmott index of agreement (d) between simulated and observed variables ranged from 0.95 to 1.00 with the exception of net ecosystem productivity (NEP, d=0.88). The model tended to project higher NEP and C stocks under warm but wet climate (CGCM3.1 A2 and B1) vs. warm and dry climate (MIROC3.2 A2 and B1), and slightly higher NEP under IPCC SERS B1 vs. A2, for both forest types. When clearcuts occurred, the model projected negative NEP (C losses) during the seven to 11years following clearcuts for both forest types under the five climate scenarios. Regrowth of the forest generally led to greater C accumulation when clearcuts occurred in 2010 than in 2055. Overall, the TRIPLEX-Management model is capable of simulating C dynamics for aspen and jack pine forests as well as their responses to drought and harvesting disturbances. Climate change at the southern edge of the boreal forest in North America may enhance the C sequestration rate if there are no severe drought events. A longer rotation age (>90years), may therefore, not be necessary in southern boreal forests in order to increase C sequestration.

Dawn of Drone Ecology: Low-Cost Autonomous Aerial Vehicles for Conservation

Tropical deforestation continues to be a major driver of biodiversity loss and greenhouse gas emissions. Remote sensing technology is increasingly used to assess changes in forest cover, species distributions and carbon stocks. However, satellite and airborne sensors can be prohibitively costly and inaccessible for researchers in developing countries. Here, we describe the development and use of an inexpensive (<$2,000) unmanned aerial vehicle for surveying and mapping forests and biodiversity (referred to as ‘Conservation Drone’ hereafter). Our prototype drone is able to fly pre-programmed missions autonomously for a total flight time of ~25 minutes and over a distance of ~15 km. Non-technical operators can program each mission by defining waypoints along a flight path using an open-source software. This drone can record videos at up to 1080 pixel resolution (high definition), and acquire aerial photographs of <10 cm pixel resolution. Aerial photographs can be stitched together to produce real-time geo-referenced land use/cover maps of surveyed areas. We evaluate the performance of this prototype Conservation Drone based on a series of test flights in Aras Napal, Sumatra, Indonesia. We discuss the further development of Conservation Drone 2.0, which will have a bigger payload and longer range. Initial tests suggest a flight time of ~50 minutes and a range of ~25 km. Finally, we highlight the potential of this system for environmental and conservation applications, which include near real-time mapping of local land cover, monitoring of illegal forest activities, and surveying of large animal species.

Carbon Credit Eligibility under Area Regulation of Harvest Levels in Northern Minnesota

Abstract We evaluated the implications of area regulation of harvest on eligible carbon under both the Voluntary Carbon Standard (VCS) and the Chicago Climate Exchange (CCX) for public forest lands in north central Minnesota (89,840 ha total). We used data from the carbon submodel of the US Forest Service Forest Vegetation Simulator (Lake States variant) to evaluate changes in forest carbon stocks under different management scenarios. Baseline harvest intensity was defined by considering the manager's short-range tactical plans and the distribution of harvests by cover type and intensity class then became the “business as usual” (BAU) for use in the calculation of eligible carbon under the VCS and CCX. Under VCS, the most effective way to increase carbon stocks while meeting other management objectives was to shift harvest practices to lower intensity entries and retain higher residual basal areas. The carbon stock change rates for each manager varied significantly under the BAU scenario and resulted in a mean annual net decrease. Because CCX carbon credit eligibility requires a net increase of carbon stocking from the base year, area regulation may create periods of time where there is no eligible carbon volume. An alternate management strategy that uses the area regulation method, reduces harvest intensity, and decreases overall acreage harvested was able to provide higher postharvest carbon stocks versus the BAU scenario under VCS.

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

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.

Airborne scanning LiDAR in a double sampling forest carbon inventory

To meet Kyoto Protocol obligations, New Zealand is required to estimate forest carbon stock change over the first commitment period (2008–2012). New Zealand has three subcategories of forest, namely: Natural forest; Pre-1990 forest; and Post-1989 forest. The Post-1989 forest carbon inventory undertaken in 2008 used discrete return airborne LiDAR and ground-based measurements of 0.06 ha circular plots located on a 4-km × 4-km grid. The national carbon stock estimate was based on a double sampling scheme consisting of 246 plots from which both ground and LiDAR data were obtained, supplemented with 46 additional plots assessed using only LiDAR. This paper describes the relationships established between carbon stocks estimated using ground-based measurements and LiDAR metrics. A regression model explaining 74% of the variation in total carbon was developed using LiDAR 30th percentile height (P30ht) and canopy cover (%Cover). The regression estimator improved the precision of the national carbon stock estimate in 2008 by 6% compared to the ground-based estimate. This inventory indicates that it is possible to reduce the cost of obtaining carbon stock estimates to a specified level of precision using a combination of ground-based and LiDAR measurements in a double sampling approach. The theoretical maximum improvement in precision expected in 2012, when additional LiDAR data are expected to be available, is 50–55%.

Implications of sampling design and sample size for national carbon accounting systems

BackgroundCountries willing to adopt a REDD regime need to establish a national Measurement, Reporting and Verification (MRV) system that provides information on forest carbon stocks and carbon stock changes. Due to the extensive areas covered by forests the information is generally obtained by sample based surveys. Most operational sampling approaches utilize a combination of earth-observation data and in-situ field assessments as data sources.ResultsWe compared the cost-efficiency of four different sampling design alternatives (simple random sampling, regression estimators, stratified sampling, 2-phase sampling with regression estimators) that have been proposed in the scope of REDD. Three of the design alternatives provide for a combination of in-situ and earth-observation data. Under different settings of remote sensing coverage, cost per field plot, cost of remote sensing imagery, correlation between attributes quantified in remote sensing and field data, as well as population variability and the percent standard error over total survey cost was calculated. The cost-efficiency of forest carbon stock assessments is driven by the sampling design chosen. Our results indicate that the cost of remote sensing imagery is decisive for the cost-efficiency of a sampling design. The variability of the sample population impairs cost-efficiency, but does not reverse the pattern of cost-efficiency of the individual design alternatives.Conclusions, brief summary and potential implicationsOur results clearly indicate that it is important to consider cost-efficiency in the development of forest carbon stock assessments and the selection of remote sensing techniques. The development of MRV-systems for REDD need to be based on a sound optimization process that compares different data sources and sampling designs with respect to their cost-efficiency. This helps to reduce the uncertainties related with the quantification of carbon stocks and to increase the financial benefits from adopting a REDD regime.

Complete forest carbon cycle and budget in China, 1999–2008

Forest carbon cycle consists of biological and industrial cycles, whose carbon budget and carbon stock change should be estimated. The complete forest carbon budget was seldom reported in China, and carbon budget was mainly used to calculate forest biological carbon stock change. Therefore, we analyzed and presented the complete forest carbon cycle by dividing it into three carbon pools: pre-harvest forest, harvested wood product (HWP) manufacturing, and HWP use and disposal. Then, the carbon budget and net carbon flux of each pool during 1999–2008 were calculated using forest inventory data, HWP production and consumption, and economic data. The results showed that about 1334.46 and 1423.84TgC carbon were sequestered from atmosphere in 1999–2003 and 2004–2008, respectively. The two periods had forest ecosystem net carbon flux of 1356.29 and 1442.90TgC, adding up to 2799.19TgC. For the industrial part, 112.14Tg carbon was stored in new HWP, but 40.86Tg more carbon was released from HWP production, use and disposal. We went onto compare the carbon budgets of 1999–2003 and 2004–2008, and found out that net sequestered carbon was 89.38TgC higher in the latter period, 86.61TgC more stored in forest ecosystem and 2.77TgC less released from the industrial carbon cycle. Subsequently, we studied the relationship between carbon emission reduction and forest industrial carbon cycle, and verified that optimizing HWP production process and extending HWP lifespan can effectively reduce carbon emission. At the end, we proposed gaps and future studies.

Quantifying small‐scale deforestation and forest degradation in African woodlands using radar imagery

AbstractCarbon emissions from tropical land‐use change are a major uncertainty in the global carbon cycle. In African woodlands, small‐scale farming and the need for fuel are thought to be reducing vegetation carbon stocks, but quantification of these processes is hindered by the limitations of optical remote sensing and a lack of ground data. Here, we present a method for mapping vegetation carbon stocks and their changes over a 3‐year period in a > 1000 km2 region in central Mozambique at 0.06 ha resolution. L‐band synthetic aperture radar imagery and an inventory of 96 plots are combined using regression and bootstrapping to generate biomass maps with known uncertainties. The resultant maps have sufficient accuracy to be capable of detecting changes in forest carbon stocks of as little as 12 MgC ha−1 over 3 years with 95% confidence. This allows characterization of biomass loss from deforestation and forest degradation at a new level of detail. Total aboveground biomass in the study area was reduced by 6.9 ± 4.6% over 3 years: from 2.13 ± 0.12 TgC in 2007 to 1.98 ± 0.11 TgC in 2010, a loss of 0.15 ± 0.10 TgC. Degradation probably contributed 67% (96.9 ± 91.0 GgC) of the net loss of biomass, but is associated with high uncertainty. The detailed mapping of carbon stock changes quantifies the nature of small‐scale farming. New clearances were on average small (median 0.2 ha) and were often additions to already cleared land. Deforestation events reduced biomass from 33.5 to 11.9 MgC ha−1 on average. Contrary to expectations, we did not find evidence that clearances were targeted towards areas of high biomass. Our method is scalable and suitable for monitoring land cover change and vegetation carbon stocks in woodland ecosystems, and can support policy approaches towards reducing emissions from deforestation and degradation (REDD).

Comparison of depth- and mass-based approaches for estimating changes in forest soil carbon stocks: A case study in young plantations and secondary forests in West Java, Indonesia

Soil carbon (C) stocks in forest ecosystems have been widely estimated to a fixed soil depth (i.e., 0–30 cm) to clarify temporal changes in the C pool. However, surface elevations change as a result of compaction or expansion of the soil under forest management and land use. On the other hand, the calculation of soil C stocks based on “equivalent soil mass” is not affected by compaction or expansion of forest soil. To contribute to the development of a forest C accounting methodology, we compared changes in soil C stocks over 4 years between depth- and mass-based approaches using original soil data collected at 0–30 cm depths in young plantations and secondary forests in West Java, Indonesia. Our methodology expanded on the mass-based approach; rather than using one representative value for the mass-based calculation of soil C stocks, we adjusted individual values, maintaining the coefficient of variance in soil mass. We also considered the effect of an increase or decrease in soil organic matter on equivalent soil mass. Both increasing and decreasing trends in soil C stocks became clearer when the mass-based approach was used rather than the depth-based approach. The trends in soil C stocks based on equivalent soil mass were particularly evident in the surface soil layers (0–5 cm) and in plantation sites, compared with those for soil profiles including subsurface soil layers (0–30 cm) and in secondary forests. These trends in soil C stocks corresponded with temporal trends in litter stocks. We suggest that equivalent mass-basis soil C stock for the upper 30 cm of soil be calculated based on multiple soil layers to reduce estimation errors. Changes in soil organic matter mass had little effect on the estimation of soil C stock on an equivalent mass basis. For the development of a forest C accounting system, the mass-based approach should be used to characterize temporal trends in soil C stocks and to improve C cycle models, rather than simpler methods of calculating soil C stocks. These improvements will help to increase the tier level of country-specific forest C accounting systems.

The Changes in China's Forests: An Analysis Using the Forest Identity

Changes in forest carbon stocks are a determinant of the regional carbon budget. In the past several decades, China has experienced a pronounced increase in forest area and density. However, few comprehensive analyses have been conducted. In this study, we employed the Forest Identity concept to evaluate the changing status of China's forests over the past three decades, using national forest inventory data of five periods (1977–1981, 1984–1988, 1989–1993, 1994–1998, and 1999–2003). The results showed that forest area and growing stock density increased by 0.51% and 0.44% annually over the past three decades, while the conversion ratio of forest biomass to growing stock declined by 0.10% annually. These developments resulted in a net annual increase of 0.85% in forest carbon sequestration, which is equivalent to a net biomass carbon uptake of 43.8 Tg per year (1 Tg = 1012 g). This increase can be attributed to the national reforestation/afforestation programs, environmentally enhanced forest growth and economic development as indicated by the average gross domestic product.

Evaluating the Potential of Commercial Forest Inventory Data to Report on Forest Carbon Stock and Forest Carbon Stock Changes for REDD+ under the UNFCCC

In the context of the adoption at the 16th Conference of the Parties in 2010 on the REDD+ mitigation mechanism, it is important to obtain reliable data on the spatiotemporal variation of forest carbon stocks and changes (called Emission Factor, EF). A re-occurring debate in estimating EF for REDD+ is the use of existing field measurement data. We provide an assessment of the use of commercial logging inventory data and ecological data to estimate a conservative EF (REDD+ phase 2) or to report on EF following IPCC Guidance and Guidelines (REDD+ phase 3). The data presented originate from five logging companies dispersed over Gabon, totalling 2,240 plots of 0.3 hectares.We distinguish three Forest Types (FTs) in the dataset based on floristic conditions. Estimated mean aboveground biomass (AGB) in the FTs ranges from 312 to 333 Mg ha−1. A 5% accuracy is reached with the number of plots put in place for the FTs and a low sampling uncertainty obtained (± 10 to 13 Mg ha−1). The data could be used to estimate a conservative EF in REDD+ phase 2 and only partially to report on EF following tier 2 requirements for a phase 3.

Options for sampling and stratification for national forest inventories to implement REDD+ under the UNFCCC

BackgroundDeveloping countries that are willing to participate in the recently adopted (16th Session of the Conference of Parties (COP) in Cancun) mitigation mechanism of Reducing emissions from Deforestation and Forest Degradation - and the role of conservation, sustainable management of forests and enhancement of forest carbon stocks (REDD+) - will have to establish a national forest monitoring system in order to assess anthropogenic forest-related greenhouse gas emissions by sources and removals by sinks. Such a system should support the Measurement, Reporting and Verification (MRV) requirement of the United Nations Framework Convention on Climate Change (UNFCCC) as the REDD+ mechanism is results-based. A national forest inventory (NFI) is one potential key component of such an MRV system. Following the Decision adopted during the 15th Session of the COP in Copenhagen, the most recent Intergovernmental Panel on Climate Change (IPCC) Guidance and Guidelines should be used as a basis for estimating anthropogenic forest-related greenhouse gas emissions by sources and removals by sinks and changes in forest carbon stocks and area.ResultsFirst, we present the key indispensable elements of the IPCC Guidance and Guidelines that have been developed to fulfil the UNFCCC reporting requirements. This is done in order to set the framework to develop the MRV requirement in which a NFI for REDD+ implementation could be developed. Second, within this framework, we develop and propose a novel scheme for the stratification of forest land for REDD+. Finally, we present some non-exhaustive optional elements within this framework that a country could consider to successfully operationalise and implement its REDD+ NFI.ConclusionEvidently, both the methodological guidance and political decisions on REDD+ under the UNFCCC will continue to evolve. Even so, and considering that there exists decades of experience in setting up traditional NFIs, developing a NFI that a country may use to directly support REDD+ activities under the UNFCCC represents the development of a new challenge in this field. It is therefore important that both the scientific community and national implementing agencies acquaint themselves with both the context and content of this challenge so that REDD+ mitigation actions may be implemented successfully and with environmental integrity. This paper provides important contributions to the subject through our proposal of the stratification of forest land for REDD+.

A comparison of carbon assessment methods for optimizing timber production and carbon sequestration in Scots pine stands

Projected changes in forest carbon stocks and carbon balance differ according to the choice of estimation methods and the carbon pools considered. Here, we compared three carbon assessment methods for optimizing timber production and carbon sequestration in six example Scots pine (Pinus sylvestris L.) stands in Finland. The forest carbon stock was assessed, with three methods: stem carbon, biomass expansion factors (BEFs), and a process-based model. Given a carbon price of 40€t−1 (equivalent to 10.9€t−1 CO2) and a 3% discount rate, the highest average carbon stock and mean annual increment (MAI) were obtained with the BEF method. Increasing the carbon price from 0 to 200€t−1 resulted in longer optimal rotations and higher MAI, and increased the average carbon stock, especially when carbon was assessed by the BEF method. Comparison of these carbon assessment methods, using economic sensitivity analyses, indicated that optimal thinning regimes and average carbon stocks are strongly dependent on the assessment method. The process-based method led to less frequent thinnings and shorter rotations than the BEF method, due to different predictions of biomass production. As a cost-effective option, optimal thinning regimes play a very important role in timber production and carbon sequestration.

Benefits of Self-Reporting

W. F. Laurance and O. Venter (“Measuring forest changes,” Letters, 30 April, p. 569) question whether, under the proposed REDD mechanism (reducing emissions from deforestation and forest degradation), developing countries should be responsible for producing their own estimates of changes in forest carbon stocks. Instead, they propose that an independent organization should be given this task, and mention the UNEP World Conservation Monitoring Centre as a possible candidate for this role.

An assessment of monitoring requirements and costs of 'Reduced Emissions from Deforestation and Degradation'

BackgroundNegotiations on a future climate policy framework addressing Reduced Emissions from Deforestation and Degradation (REDD) are ongoing. Regardless of how such a framework will be designed, many technical solutions of estimating forest cover and forest carbon stock change exist to support policy in monitoring and accounting. These technologies typically combine remotely sensed data with ground-based inventories. In this article we assess the costs of monitoring REDD based on available technologies and requirements associated with key elements of REDD policy.ResultsWe find that the design of a REDD policy framework (and specifically its rules) can have a significant impact on monitoring costs. Costs may vary from 0.5 to 550 US$ per square kilometre depending on the required precision of carbon stock and area change detection. Moreover, they follow economies of scale, i.e. single country or project solutions will face relatively higher monitoring costs.ConclusionAlthough monitoring costs are relatively small compared to other cost items within a REDD system, they should be shared not only among countries but also among sectors, because an integrated monitoring system would have multiple benefits for non-REDD management. Overcoming initialization costs and unequal access to monitoring technologies is crucial for implementation of an integrated monitoring system, and demands for international cooperation.

Biomass carbon sinks in Japanese forests: 1966-2012

The role of forests in absorbing atmospheric carbon has been recognized under the Kyoto Protocol, which allows signatory countries to use forests as a mitigation option. Although several studies have estimated carbon stock changes in Japanese forests, most only estimate changes up to 1995 or ignore carbon stock changes in natural forests. This study is the first attempt to estimate carbon stock changes in Japanese forests from 1966 to 2012, to coincide with the final year of the Kyoto Protocol's first commitment period. Forest area and growing stock data were analysed. Then, two models for predicting the change in forest area and growing stock were developed. Results showed that most natural forest loss resulted from conversion to plantation forest. The total above-ground and below-ground carbon stock in Japanese forests has been estimated to have increased from 1114.8 TgC in 1966 to 2076.0 TgC in 2012, representing an increase of 20.9 TgC year -1 over the same period. During the first commitment period of the Kyoto Protocol (2008-2012), annual carbon sinks were estimated at 20.1 TgC, of which ∼76.9 per cent were sequestered in plantation forests. Of the 20.1 TgC year -1 , eligible carbon sinks are estimated at 10.2 TgC or ∼78.7 per cent of the maximum or capped amount as allowed under the Marrakesh Accord. Although further effort is needed so that the capped amount of 13 TgC year -1 could be achieved, this study suggests that carbon sinks through forest management could be used to offset industrial carbon emissions.

CBM-CFS3: A model of carbon-dynamics in forestry and land-use change implementing IPCC standards

The scientific community, forest managers, environmental organizations, carbon-offset trading systems and policy-makers require tools to account for forest carbon stocks and carbon stock changes. In this paper we describe updates to the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3) implemented over the past years. This model of carbon-dynamics implements a Tier 3 approach of the Intergovernmental Panel on Climate Change (IPCC) Good Practice Guidance for reporting on carbon stocks and carbon stock changes resulting from Land Use, Land-use Change and Forestry (LULUCF). The CBM-CFS3 is a generic modelling framework that can be applied at the stand, landscape and national levels. The model provides a spatially referenced, hierarchical system for integrating datasets originating from different forest inventory and monitoring programs and includes a structure that allows for tracking of land areas by different land-use and land-use change classes. Ecosystem pools in CBM-CFS3 can be easily mapped to IPCC-defined pools and validated against field measurements. The model uses sophisticated algorithms for converting volume to biomass and explicitly simulates individual annual disturbance events (natural and anthropogenic). Several important scientific updates have been made to improve the representation of ecosystem structure and processes from previous versions of CBM-CFS. These include: (1) an expanded representation of dead organic matter and soil carbon, particularly standing dead trees, and a new algorithm for initializing these pools prior to simulation, (2) a change in the input data requirement for simulating growth from biomass to readily available merchantable volume curves, and new algorithms for converting volume to biomass, (3) improved prediction of belowground biomass, and (4) improved parameters for soil organic matter decay, fire, insect disturbances, and forest management. In addition, an operational-scale version of CBM-CFS3 is freely available and includes tools to import data in standard formats, including the output of several timber supply models that are commonly used in Canada. Although developed for Canadian forests, the flexible nature of the model has enabled it to be adapted for use in several other countries.

Effects of harvest management practices on forest biomass and soil carbon in eucalypt forests in New South Wales, Australia: Simulations with the forest succession model LINKAGES

Understanding long-term changes in forest ecosystem carbon stocks under forest management practices such as timber harvesting is important for assessing the contribution of forests to the global carbon cycle. Harvesting effects are complicated by the amount, type, and condition of residue left on-site, the decomposition rate of this residue, the incorporation of residue into soil organic matter and the rate of new detritus input to the forest floor from regrowing vegetation. In an attempt to address these complexities, the forest succession model LINKAGES was used to assess the production of aboveground biomass, detritus, and soil carbon stocks in native Eucalyptus forests as influenced by five harvest management practices in New South Wales, Australia. The original decomposition sub-routines of LINKAGES were modified by adding components of the Rothamsted (RothC) soil organic matter turnover model. Simulation results using the new model were compared to data from long-term forest inventory plots. Good agreement was observed between simulated and measured above-ground biomass, but mixed results were obtained for basal area. Harvesting operations examined included removing trees for quota sawlogs (QSL, DBH >80 cm), integrated sawlogs (ISL, DBH >20 cm) and whole-tree harvesting in integrated sawlogs (WTH). We also examined the impact of different cutting cycles (20, 50 or 80 years) and intensities (removing 20, 50 or 80 m 3). Generally medium and high intensities of shorter cutting cycles in sawlog harvesting systems produced considerably higher soil carbon values compared to no harvesting. On average, soil carbon was 2–9% lower in whole-tree harvest simulations whereas in sawlog harvest simulations soil carbon was 5–17% higher than in no harvesting.