Overview of carbon stock change estimation

The emissions and removals of CO2 for the AFOLU Sector, based on changes in ecosystem C stocks, are estimated for each land-use category (including both land remaining in a land-use category as well as land converted to another land use). Carbon stock changes are summarized by Equation 2.1.

Equation 2.1

Annual carbon stock changes for the entire AFOLU Sector estimated as the sum

OF CHANGES IN ALL LAND-USE CATEGORIES

ACAFOLU = &CFL + ACcl + ACgl + ACwl + ACSL + ACOL

Where:

AC = carbon stock change Indices denote the following land-use categories: AFOLU = Agriculture, Forestry and Other Land Use FL = Forest Land

CL

= Cropland

GL

= Grassland

WL

= Wetlands

SL

= Settlements

OL

= Other Land

For each land-use category, carbon stock changes are estimated for all strata or subdivisions of land area (e.g., climate zone, ecotype, soil type, management regime etc., see Chapter 3) chosen for a land-use category (Equation 2.2). Carbon stock changes within a stratum are estimated by considering carbon cycle processes between the five carbon pools, as defined in Table 1.1 in Chapter 1. The generalized flowchart of the carbon cycle (Figure 2.1) shows all five pools and associated fluxes including inputs to and outputs from the system, as well as all possible transfers between the pools. Overall, carbon stock changes within a stratum are estimated by adding up changes in all pools as in Equation 2.3. Further, carbon stock changes in soil may be disaggregated as to changes in C stocks in mineral soils and emissions from organic soils. Harvested wood products (HWP) are also included as an additional pool.

Where:

AClu = carbon stock changes for a land-use (LU) category as defined in Equation 2.1.

i = denotes a specific stratum or subdivision within the land-use category (by any combination of species, climatic zone, ecotype, management regime etc., see Chapter 3), i = 1 to n.

Where:

AClui = carbon stock changes for a stratum of a land-use category Subscripts denote the following carbon pools: AB = above-ground biomass BB = below-ground biomass DW = deadwood LI = litter SO = soils

HWP = harvested wood products

Estimating changes in carbon pools and fluxes depends on data and model availability, as well as resources and capacity to collect and analyze additional information (See Chapter 1, Section 1.3.3 on key category analysis). Table 1.1 in Chapter 1 outlines which pools are relevant for each land-use category for Tier 1 methods, including cross references to reporting tables. Depending on country circumstances and which tiers are chosen, stock changes may not be estimated for all pools shown in Equation 2.3. Because of limitations to deriving default data sets to support estimation of some stock changes, Tier 1 methods include several simplifying assumptions:

Figure 2.1 Generalized carbon cycle of terrestrial AFOLU ecosystems showing the flows of carbon into and out of the system as well as between the five C pools within the system.

Figure 2.1 Generalized carbon cycle of terrestrial AFOLU ecosystems showing the flows of carbon into and out of the system as well as between the five C pools within the system.

Increase of carbon stocks due to growth

Carbon fluxes due to discrete events, i.e., from harvest residues and natural disturbance

Carbon fluxes due to continuous processes, i.e. decomposition

Soil organic matter

Increase of carbon stocks due to growth

Carbon fluxes due to discrete events, i.e., from harvest residues and natural disturbance

Carbon fluxes due to continuous processes, i.e. decomposition

Soil organic matter

• change in below-ground biomass C stocks are assumed to be zero under Tier 1 (under Tier 2, country-specific data on ratios of below-ground to above-ground biomass can be used to estimate below-ground stock changes);

• under Tier 1, dead wood and litter pools are often lumped together as 'dead organic matter' (see discussion below); and

• dead organic matter stocks are assumed to be zero for non-forest land-use categories under Tier 1. For Forest Land converted to another land use, default values for estimating dead organic matter carbon stocks are provided in Tier 1.

The carbon cycle includes changes in carbon stocks due to both continuous processes (i.e., growth, decay) and discrete events (i.e., disturbances like harvest, fire, insect outbreaks, land-use change and other events). Continuous processes can affect carbon stocks in all areas in each year, while discrete events (i.e., disturbances) cause emissions and redistribute ecosystem carbon in specific areas (i.e., where the disturbance occurs) and in the year of the event.

Disturbances may also have long-lasting effects, such as decay of wind-blown or burnt trees. For practicality, Tier 1 methods assume that all post-disturbance emissions (less removal of harvested wood products) are estimated as part of the disturbance event, i.e., in the year of the disturbance. For example, rather than estimating the decay of dead organic matter left after a disturbance over a period of several years, all post-disturbance emissions are estimated in the year of the event.

Under Tier 1, it is assumed that the average transfer rate into dead organic matter (dead wood and litter) is equal to the average transfer rate out of dead organic matter, so that the net stock change is zero. This assumption means that dead organic matter (dead wood and litter) carbon stocks need not be quantified under Tier 1 for land areas that remain in a land-use category1. The rationale for this approach is that dead organic matter stocks, particularly dead wood, are highly variable and site-specific, depending on forest type and age, disturbance history and management. In addition, data on coarse woody debris decomposition rates are scarce and thus it was deemed that globally applicable default factors and uncertainty estimates can not be developed. Countries experiencing significant changes in forest types or disturbance or management regimes in their forests are encouraged to develop domestic data to estimate the impact from these changes using Tier 2 or 3 methodologies and to report the resulting carbon stock changes and non-CO2 emissions and removals.

All estimates of changes in carbon stocks, i.e., growth, internal transfers and emissions, are in units of carbon to make all calculations consistent. Data on biomass stocks, increments, harvests, etc. can initially be in units of dry matter that need to be converted to tonnes of carbon for all subsequent calculations. There are two fundamentally different and equally valid approaches to estimating stock changes: 1) the process-based approach, which estimates the net balance of additions to and removals from a carbon stock; and 2) the stock-based approach, which estimates the difference in carbon stocks at two points in time.

Annual carbon stock changes in any pool can be estimated using the process-based approach in Equation 2.4 which sets out the Gain-Loss Method that can be applied to all carbon gains or losses. Gains can be attributed to growth (increase of biomass) and to transfer of carbon from another pool (e.g., transfer of carbon from the live biomass carbon pool to the dead organic matter pool due to harvest or natural disturbances). Gains are always marked with a positive (+) sign. Losses can be attributed to transfers of carbon from one pool to another (e.g., the carbon in the slash during a harvesting operation is a loss from the above-ground biomass pool), or emissions due to decay, harvest, burning, etc. Losses are always marked with a negative (-) sign.

Equation 2.4

Annual carbon stock change in a given pool as a function of gains and losses

(Gain-Loss Method)

Where:

AC = annual carbon stock change in the pool, tonnes C yr-1 ACG = annual gain of carbon, tonnes C yr-1

Emissions from litter C stocks are accounted for under Tier 1 for forest conversion to other land-use.

ACl = annual loss of carbon, tonnes C yr-1

Note that CO2 removals are transfers from the atmosphere to a pool, whereas CO2 emissions are transfers from a pool to the atmosphere. Not all transfers involve emissions or removals, since any transfer from one pool to another is a loss from the donor pool, but is a gain of equal amount to the receiving pool. For example, a transfer from the above-ground biomass pool to the dead wood pool is a loss from the above-ground biomass pool and a gain of equal size for the dead wood pool, which does not necessarily result in immediate CO2 emission to the atmosphere (depending on the Tier used).

The method used in Equation 2.4 is called the Gain-Loss Method, because it includes all processes that bring about changes in a pool. An alternative stock-based approach is termed the Stock-Difference Method, which can be used where carbon stocks in relevant pools are measured at two points in time to assess carbon stock changes, as represented in Equation 2.5.

Equation 2.5

Carbon stock change in a given pool as an annual average difference between

ESTIMATES AT TWO POINTS IN TIME (STOCK-DIFFERENCE METHOD)

Where:

AC = annual carbon stock change in the pool, tonnes C yr-1 Ctj = carbon stock in the pool at time ti, tonnes C

Ct2 = carbon stock in the pool at time t2, tonnes C

If the C stock changes are estimated on a per hectare basis, then the value is multiplied by the total area within each stratum to obtain the total stock change estimate for the pool. In some cases, the activity data may be in the form of country totals (e.g., harvested wood) in which case the stock change estimates for that pool are estimated directly from the activity data after applying appropriate factors to convert to units of C mass. When using the Stock-Difference Method for a specific land-use category, it is important to ensure that the area of land in that category at times t1 and t2 is identical, to avoid confounding stock change estimates with area changes.

The process method lends itself to modelling approaches using coefficients derived from empirical research data. These will smooth out inter-annual variability to a greater extent than the stock change method which relies on the difference of stock estimates at two points in time. Both methods are valid so long as they are capable of representing actual disturbances as well as continuously varying trends, and can be verified by comparison with actual measurements.

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