CARBON & BIODIVERSITY CALCULATOR

Data sources

Carbon

The carbon values generated by the Carbon and Biodiversity Calculator are calculated from a data layer that is a combination of several different datasets. The basemap is a global, IPCC Tier 1 carbon dataset (Ruesch, A., Gibbs, H.K. 2008), and for some countries, this data has been replaced with higher resolution data.

BENIN, BURUNDI, CAMEROON, CÔTE D’LVOIRE, GHANA, GUINEA, KENYA, RWANDA, SIERRA LEONE, TOGO, UGANDA, ZAMBIA

Several data sources were brought together to generate a carbon map comprising above- and below-ground biomass, with soil carbon to 1 metre depth. The above-ground biomass was derived from a model for tropical Africa at 500m resolution, which uses remotely-sensed MODIS NBAR data from 2000-2003 (Baccini et al. 2008). Ecosystem-specific conversion factors (IPCC 2006) were used to add below-ground biomass to this map, with the factors allocated to FAO ecological zones (FAO 2001). The carbon mass of the resulting total was estimated as half the biomass (Gibbs & Brown 2007). There were no model data for zones with < 9 tons of biomass per hectare. Values from a global biomass carbon map (Ruesch & Gibbs 2008) were substituted in these zones, giving a final map of biomass carbon. Soil organic carbon to a depth of 1 metre was added from a new dataset (Scharlemann et al. in prep) based on the Harmonised World Soil Database (FAO et al. 2008).

CAMBODIA

Carbon stock data for Cambodia was derived from several sources. A map of forest cover in 2005/2006 was provided by the Forestry Administration (FA) of Cambodia (Kingdom of Cambodia 2007). This map is considered the most recent and accurate for forest extent in the country. For areas classified in the FA dataset as non-forest or as ‘other forest’, an earlier land cover map (JICA 2002) was used to provide more detailed information on vegetation type. Carbon stock values were assigned to the different land cover classes based on published estimates of biomass or carbon stocks in different vegetation types in Cambodia. Where no estimates from Cambodia existed, estimates from similar vegetation types of neighbouring countries were used. Where there were several published biomass or carbon values for a given vegetation type, the available estimates were averaged the result applied. Most published biomass or carbon values provided information on above-ground biomass only; to determine below-ground biomass for a given land cover class, we used ecosystem-specific conversion factors (IPCC 2006), which provided ratios of below–ground biomass to above-ground biomass for different FAO ecological zones (FAO 2001). Bare soils and rocks, urban and built-up areas, as well as water features, were deemed to hold no above- or below-ground biomass carbon, and so were assigned zero biomass carbon values. These classes cover about 3% of the country’s total area. The resulting biomass carbon map was then combined with data on the spatial distribution of soil carbon to 1 metre depth, which were extracted from the Global Map of Terrestrial Soil Carbon Stocks (Scharlemann et al. in prep.) because no suitable national data were available. The final combined dataset here is provided at 500m resolution.

Values for carbon content in different vegetation classes were from a number of different literature sources. These are:

TANZANIA
ECUADOR

National biomass carbon was based on an updated vegetation stratification (MAE 2009, updated) and on above-ground biomass estimates compiled from national sources. Where no national estimates were available, relevant regional or global average estimates were used. This dataset includes below-ground as well as above-ground carbon. In the Amazon region, the detail within the forest types was further increased by using spatially explicit biomass estimates from Saatchi et al. (2007) at 1km resolution. Below ground biomass was calculated by applying IPCC root-to- shoot ratios (IPCC 2006) by ecoregion (FAO 2001; Cárdenas et al. 2009; Josse et al. 2009). A factor of 0.5 was used to convert from biomass into carbon stocks in tonnes per hectare (Brown 2002). Soil organic carbon to a depth of 1 metre was added from a new dataset (Scharlemann et al. In prep) based on the Harmonised World Soil Database (FAO et al. 2008).

REST OF THE WORLD

For the rest of the world. a global map of biomass carbon stored in above and below ground living vegetation was used. It was created using the International Panel on Climate Change (IPCC) recommendations on methods and default values for assessing carbon stocks and emissions. This dataset has synthesized and mapped the IPCC Tier-1 (most basic level) default values using a global land cover map stratified by continent, ecoregion and forest disturbance-level. This global gridded dataset depicts vegetation biomass carbon stocks at the processing resolution of 1 x 1 km. Soil organic carbon to a depth of 1 metre was added from a new dataset (Scharlemann et al. In prep) based on the Harmonised World Soil Database (FAO et al. 2008).

It is important to be aware of the limitations of these data. They are not directly linked to ground-based measures of carbon stocks and have not been validated with field data. The approach used masks variations within classes and may lead to unnatural, abrupt gradients between vegetation classes as defined by the GLC 2000 and FAO ecoregions (Gibbs et al. 2007). This means that the actual carbon storage in a given location could be more or less than indicated. This map is used in the Carbon and Biodiversity Calculator because it is the most appropriate global biomass carbon map available to date. Other pantropical above ground biomass carbon datasets have been developed in recent years. These datasets differ quite substantially between countries, and evaluation of their accuracy for different countries is still ongoing. Learn more

protected areas

Protected areas data are provided from the World Database on Protected Areas (WDPA); the most comprehensive global spatial dataset on terrestrial and marine protected areas. The WDPA is a joint project of UNEP and IUCN, produced by UNEP-WCMC and the IUCN World Commission on Protected Areas (WCPA), and contains information from national governments, non-governmental organizations, academic institutions, international biodiversity convention secretariats and many others. As of October 2010, the WDPA is openly available on its interactive host website, protected planet

key biodiversity areas

Key Biodiversity Areas represent sites identified as the most important areas for biodiversity conservation worldwide. They are identified using a simple globally standardised criteria based on importance in maintaining species populations.

forest status

The different classes of forest degradation were derived by comparing spatial data on the potential extent of forest with spatial data on the current extent of forest. Potential extent was generated from existing ecoregion/ecozone classifications (FAO, 1999, Olson et al., 2001) and climate data (Hijmans et al., 2005). A global forest map (SDSU 2011) was used to map the current extent of forests and a tree canopy density map (Hansen et al 2003) was used to separate them into open and closed forests within their common extent and to add woodlands areas.

It is important to note, that the map of potential forest extent is valid at the macro-regional level only and might be inaccurate at the local level (for further information see (WRI 2011)).

Data on intact forest areas was used from:

Restoration potential

Opportunities for restoration of degraded lands were assessed by creating a map of land use intensity (human pressure) which in turn was used to classify degraded lands by suitability for different types of restoration. The dataset was generated at 1km cell resolution. For further information see (WRI 2011).

The following data was used:

carbon sequestration potential

Potential maximum carbon stock was mapped using the data from Ruesch and Gibbs (2008), including any relevant adjustments or additions that have been incorporated in the UNEP-WCMC Carbon and Biodiversity Calculator. The difference between the potential maximum carbon stock and the current carbon stock was calculated through geospatial analysis. This dataset builds on the assumption that restoration will not change the carbon content of the soil, which in the long term is unlikely.

The assessment gives a coarse and highly uncertain, but spatially explicit, estimate of the amount of carbon that could potentially be gained through restoration of opportunity areas up to the level of carbon stocking that is represented by comparable non-degraded areas. The dataset was generated at 1km cell resolution. For further information see WRI (2011).

ecological gap analyses

Some parties to the Convention on Biological Diversity (CBD) have carried out national gap analyses to identify high priority sites (HiPs) to expand or improve their protected area systems and networks, as part of their commitments under the CBD Programme of Work on Protected Areas. Relevant stakeholders were involved in the national gap analysis.

Brazil

Brazil has developed a map of priority areas for conservation, sustainable use and benefit sharing of biodiversity. An update occurred in 2006/Publicação on January 23, 2007 - Ordinance No 9 – MMA

Ecuador

Ecuador has identified terrestrial and marine Conservation Priority Areas and ‘ecological gaps’ in the national protected areas system. These are areas of importance for conservation of key species and/or ecosystems, and mostly are not yet designated as Protected Areas. The criteria used to identify the sites include occurrence of particular species and habitat types, as well as irreplaceability of sites and their vulnerability to pressures that affect biodiversity (Cuesta et al. 2006; Campos et al. 2007). Areas were classified into six categories of conservation priority.