When governments or regulators get involved in negotiations about greenhouse gas emissions or carbon trading, they rely on scientifically robust, verifiable measurements of the value and volume of carbon produced or sequestered by human activities.
There are three ways in which carbon levels are accounted for in forestry:
The best method to use depends mainly on the objectives of the assessment, its geographical scale and the resources available to carry out the evaluation. The most robust and cost-effective carbon stock accounts will typically combine all three approaches alongside remote sensing technology (satellite imagery and aerial photography).
The simplest method of assessment looks at how carbon stocks have changed between two points in time. Conventional forest mensuration methods estimate timber volumes, which then convert to dry weight – and hence carbon – using reference tables.
Problems associated with carbon stock accounting:
An inventory-based approach, particularly if used to assess carbon stocks or sequestration in woody biomass only, can be used to cover large land areas and a variety of species and site conditions.
Several carbon accounting models are applicable to the UK. They use theoretical and empirically derived models of carbon flows through the forestry value chain.
Flux-based carbon accounting directly measures the flow of carbon into and out of the forest. State-of-the-art sensors using a technique called eddy correlation to continuously monitor carbon exchange between all the carbon pools in a forest ecosystem and the atmosphere.
Forest Research uses this technique to measure carbon exchange in lowland oak woodland at the Straits Flux Station.
Benefits and drawbacks:
Flux-based calculations are ideal for delivering information on short-term variations in the magnitude of the carbon sink and in quantifying net carbon exchange in forest systems where the individual carbon pools are difficult to measure. Carbon flux studies also provide an essential validation for inventory methods across different forestry systems.
The model is applicable at the stand, forest and national level. It uses as input data, estimates of stand structure and growth obtained from yield tables that are applied at the stand level (Edwards and Christie, 1981). When stand-level carbon estimates are combined with area/age-class information, forest and national carbon stocks can be estimated. CARBINE can be used to estimate historical forest carbon stocks (if information on area is available), as well as current and future carbon stocks under different forest area and management scenarios. Using the same set of yield tables for all estimates assumes the same growth rates/patterns would be observed at any time: historic, current or future. This means that changes that might affect growth rate or form are excluded, such as the improvement of planting material or better site quality. Carbon stock changes are inferred from differences in carbon stock estimates at different times.
The model consists of four sub-models or ‘compartments’ which estimate carbon stocks in the forest, soil, and wood products and, additionally, the impact on the greenhouse gas balance of direct and indirect fossil fuel substitution attributable to the forestry system.
The model is able to represent all of the introduced and native plantation and naturally-occurring species relevant to the UK. The forest carbon sub-model is further compartmentalised to represent fractions due to tree stems, branches, foliage, and roots. The impact of different forest management regimes can only be assessed for the range of tree species, yield classes and management regimes represented in published yield tables (Edwards and Christie, 1981). However, at present not all of these are implemented in CARBINE.
Wood products are represented as long-lived and short-lived sawn timber, particleboard and paper. Carbon in harvested stemwood is allocated to these wood product categories using an assortment forecasting model that accounts for variation in product out-turn due to tree species and tree size class distribution at time of harvest (Rollinson and Gay, 1983). Wood products in primary use are assumed to decay over time with no account taken of carbon stocks in landfill or greenhouse gas emissions (due to wood products) from landfill. ‘Inherited’ emissions from wood products replaced are not considered.
CARBINE incorporates a Soil Carbon Accounting model (SCOTIA), based on a simplified version of the ECOSSE model (Smith et al., 2011), coupled with a litter decomposition model derived from the ForClim-D model (Perruchoud et al., 1999; Liski et al., 2002). Above ground turnover of material such as foliage, branches and dead stemwood enters the litter pool, which is then broken down to F-material (Fermenting) as a function of temperature and rainfall, releasing CO2. The soil is divided into a number of layers to which carbon from decayed litter, dead roots, and root exudates enters each layer and is assigned to four active pools and also inert carbon. Carbon is lost through aerobic and anaerobic decomposition, transfer between layers and washout of material and dissolved organic carbon (DOC).
CARBINE relies on UK Forestry Commission yield tables to provide basic input data on stand growth and structure. Currently these models are limited to the representation of pure-species, even-aged stands. As a result, neither model can be used to evaluate mixed-species stands, and no account is taken of understorey species. Both models can be ‘forced’ to approximate uneven-aged or mixed tree stands by assuming a large number of even-aged patches of different species and varying age class.
The forest carbon pools included in the sub-model are stem, branches, foliage, and roots. The model utilises pre-existing yield models developed for each species, yield class and management regime to estimate the development of merchantable stem volume at an annual time-step. Potentially, there are over 1000 different yield models available for different combinations of species, yield class and management regime. However, in general only one or two examples for each tree species are represented in CARBINE, although a comprehensive range of species relevant to the UK is covered.
The choice of yield class represented for a given species takes into account typical site productivity and any genetic improvements due to breeding (notably for poplar). The yield models are based on an extensive permanent sample plot network maintained across the UK and are considered to be robust. However, a recent study has highlighted possible deficiencies in the predictions of volume development made by the models, particularly for the latter stages of a rotation typical in the UK at present (Matthews, 2003). The yield tables take stem mortality throughout the rotation into account, and predictions are given for live stem volumes, i.e. net of mortality. The fate of dead standing trees or litter from any mortality (trees, branches or foliage) is allocated to the ‘waste’ compartment in the wood products sub-model.
Volume estimates obtained from yield tables are multiplied by relevant forest areas to give merchantable stem volume for the entire area. It is assumed that the area provided is the net planted area. Volume is converted to total tree volume (including stem, branches, foliage and roots) using total/merchantable (T/M) ratios (commonly referred to as expansion factors) for each of the major species groups. These expansion factors are assumed to vary with stand top height. The variation of T/M ratio with top height is assumed to handle site- and age-dependent effects. The T/M ratios are derived from published biomass studies, but the studies were not designed explicitly to address carbon sequestration issues. Consequently there is some uncertainty as to the robustness of the conversion from stem to total tree volume.
Total tree volume is converted to carbon using published values of specific wood density (Lavers and Moore, 1983) and an assumed carbon content of 50% (Matthews, 1993). The same density is assumed for all woody tree components. The same carbon content is assumed for all woody components, based on the review of Matthews (1993). Default carbon content values generally can be used, but they should be supported by a validated sample (IPCC 2000).
Forest areas and age-class distributions can be used by CARBINE to estimate total (estate-level) forest carbon. Results are presented as total forest carbon stocks and are not broken down into the individual pools of stem, branches, foliage and roots.
CARBINE may be biased in terms of the forest management regimes represented. The standard thinning regime assumed for most species is based on recommended practice (Edwards and Christie, 1981). However, in reality actual forest management departs significantly from these recommendations due to economic constraints and/or requirements to meet varying objectives in different localities within the UK. Variations in thinning regime will result in variations in forest carbon stocks for which predictions based on the assumption of standard management will be biased. This may not be a large source of bias in national carbon estimates, if the alternative management regimes vary both positively and negatively around the ‘average’. On the other hand, CARBINE may not predict carbon stocks well for individual stands or even districts when forest management is different from the management options available in the model. More information may be required on current and potential future management practices to justify the use of the ‘average’ regime in all circumstances, or to inform modification of assumptions. Unmanaged or ‘semi-natural’ forest is poorly modelled as it is assumed to follow the same growth patterns as unthinned productive forest up to the maximum potential carbon stock.
CARBINE incorporates a new Soil Carbon Accounting model (SCOTIA), based on a simplified version of the ECOSSE model (Smith et al., 2011), coupled with a litter decomposition model derived from the ForClim-D model (Perruchoud et al., 1999; Liski et al., 2002). Above ground turnover of material such as foliage, branches and dead stemwood enters the litter pool, which is then broken down to F-material (Fermenting) as a function of temperature and rainfall, releasing CO2. Within the soil, a number of layers exist, each with its own set of texture (sand, silt, clay) characteristics. Carbon from decayed litter, dead roots, and root exudates enters each layer and is assigned to four active pools; resistant plant material (RPM), readily decomposable plant material (DPM), biological material (BIO) and humic material (HUM). A proportion of organic carbon is also assumed to be inert, and unavailable for further activity. The active pools undergo decomposition and transference, releasing CO2. Decomposition (aerobic and anaerobic) within each pool and layer is influenced by response functions to water saturation in the soil, temperature, pH, and the presence (or not) of plant cover on the soil surface. The availability of water within each layer, and the level of saturation are largely defined from soil texture following Saxton and Rawls (2006) coupled with inputs from rainfall, (or drainage) and removal of water through evapotranspiration. In any soil layer, water above field capacity can drain to lower soil layers, complete with any dissolved organic carbon (DOC). The rates of potential decomposition of each carbon pool and the response functions follow ECOSSE (Smith et al., 2011).
New carbon input to the soil arises from four sources:
Turnover rates for mortality of tree components (roots, foliage etc.) are species dependent and obtained from scientific literature.
The model assumes that any harvested wood products make a contribution that is additional to current consumption. In reality, it is likely that some products manufactured will merely replace other wood products, hence there may be less change in carbon stocks than is predicted by the models. How long the model continues to overestimate stocks will be affected by product service lives and the period over which the model is run.
At thinning and harvest, the CARBINE model allocates merchantable stem volume to various wood products, while the remainder is transferred to the waste pool. The ‘end-use’ wood products represented are:
During wood processing, conversion losses are assumed and enter the waste stream and decay within a year. The amount of carbon allocated to the raw stemwood product, categories of each of the wood products is estimated by first inputting the merchantable stem carbon derived from the forest yield model to a stand volume assortment forecasting model which estimates the volume allocated to sawn timber, roundwood and waste. This is implemented in CARBINE as a set of functions derived from the output of a more general and flexible assortment forecasting program known as ASORT (Rollinson and Gay, 1983). There is no reason why the full ASORT program could not be integrated into CARBINE as a subroutine, providing much greater flexibility. Having allocated some of the stem carbon to sawn timber, roundwood and waste, fractions of the first two categories are further allocated, in different proportions, to the four ‘end-use’ wood product categories specified above. The proportions differ depending on the species harvested. This information is based on expert opinion rather than data or scientific research. A carbon retention curve is used to estimate product decay and return of carbon to the atmosphere. Each wood product category has its own carbon retention curve based on estimated service lives, taking into account not just the decay rate of wood products but the service life as influenced by socio-economic factors. The functions are used to calculate the amount of carbon retained in wood products in successive years after harvest.CARBINE does not include a compartment which represents the carbon dynamics of wood products disposed of to landfill.
Wood products can contribute to greenhouse-gas emissions reductions in two ways, through:
Both types of substitution can be taken into account using CARBINE. Each wood product is assumed to have a characteristic potential (emissions savings factor) to displace alternative materials or fossil fuels, thus determining the magnitude of avoided emissions. This is calculated by assuming an end use for wood products. These assumptions are based on expert opinion rather than data or scientific research. Greenhouse gas emissions over the life cycle of the wood product are compared to the greenhouse gas emissions for the most likely alternative product (for example steel or concrete), allowing for the possibility that the service lives of wood and non-wood products may be different .
Currently the emissions savings factor for wood waste to bioenergy is assumed to be zero. This sub-model of CARBINE was developed in the early 1990s. At this time there was very limited research globally on greenhouse gas emissions over the life cycle of a bioenergy system. The substitution sub-model of CARBINE has not been updated since it was first developed.