The aim of this post is to introduce the various methods that have evolved to measure forest carbon stocks and focus on one of the most commonly used high level methods. Subsequent posts will focus on other methods.
Importance of measurement
Forests are of global importance because of their biodiversity and the carbon they sequester. A reservoir or system which has the capacity to accumulate or release carbon is known as a “pool” (FAO, 2016). In the context of forests it refers to the amount of carbon stored in the world’s forest ecosystem, mainly in living biomass and soil, but to a lesser extent also in dead wood and litter.
Estimating the aboveground biomass of forests is the most crucial step in quantifying carbon stocks of forests since it is typically the largest pool and contributes to atmospheric carbon fluxes to a much greater extent compared with carbon stored in belowground biomass, litter and dead organic matter (Gibbs et al., 2007) (Kumar and Mutanga, 2017) (Vashum and Jayakumar, 2012).
Methods for measurement
The most accurate method for measuring carbon in aboveground biomass at a tree and plot level involves harvesting and weighing the trees and relating carbon stock values to the weight of biomass, which typically assumed to be 50% of the dry weight of biomass (Pearson et al., 2005). This approach is impractical for larger scale assessments and non-destructive techniques such as development of tree allometric equations (which relate tree measurements to above ground biomass based on regression analyses) allows scaling up over larger regions. Use of remote sensing techniques also allows larger areas of land to be covered by measuring tree volume and converting into biomass using statistical relationships (Brown, 1997; Chave et al., 2005).
Biome approach
Climate, vegetation type and geography are some of the major factors affecting the amount of carbon stored in forest biomass (Anitha et al., 2015; Stas, 2014). The biome-averages approach assumes that approximations of aboveground biomass of a landscape or region can be made based on geographically explicit datasets zones (Brown, 1997; Gibbs et al., 2007; Houghton, 1999). These datasets provide estimations of carbon stored in broad forest types and are useful for rapid large-scale assessments where no field data exists.
Biome averages are based on either compilations of whole-tree harvest measurement data (specific to very local conditions and represent small area of forest only) or on forest inventory data archived by the United Nations Food and Agricultural Organization (FAO) and others. These FAO developed global ecological zones (shown in Figure 1 below) are used as a basis for zoning in the (IPCC, 2006) and (Gibbs and Brown, 2007) methods for forest carbon calculations.
Figure 1: FAO 2010 Global Ecological Zones
Limitations
Biome-average estimates allow a rapid assessment of carbon stocks to be made, which have the option to be subsequently refined as soon as more detailed information becomes available. There are a number of limitations in using a biome-averages approach however. Estimates used by the FAO were generally not collected using sampling schemes appropriate for the biome and national scales (Brown, 1997; FAO, 2012; Gibbs et al., 2007). Another issue is that generic equations for ecological zones or forest types may not accurately reflect tree biomass in a specific area or region (Segura and Kanninen, 2005) and the variation and spatial distribution of aboveground biomass and the factors controlling them at landscape level are still poorly understood (Anitha et al., 2015; Murphy and Bowman, 2012; Stas, 2014). Additionally, biomass estimates for older secondary forests are lacking and require further research (Gibbs et al., 2007; Stas, 2014).
In the next post I will discuss another approach to forest carbon stock measurement: use of allometric models.