Last updated | August 21, 2025

Indicator information

Name

Belowground Biomass Carbon Indicator (BBCI)

Unit

The belowground biomass carbon (BBC) is expressed in Mg (megagrams or tonnes) of carbon per ha. It represents an estimation of the carbon stored in the roots of all living trees. This carbon pool is calculated as a fraction of the aboveground biomass carbon stock using root-to-shoot ratios (R). It is derived from two main data sources: the global aboveground biomass map produced by the CCI BIOMASS project (Santoro et al., 2023a and Santoro et al., 2023b) and the 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories (IPCC, 2019). 

Area of interest

The BBCI has been calculated and distributed through REST services at country, terrestrial ecoregion and protected area level and is available in KCBD - Global Biodiversity Data Viewer (GBDV) at country level.

Related targets

	Sustainable Development Goal 13 on climate action
	Global Biodiversity Framework Target 8
	Global Biodiversity Framework Target 10

Policy question

There are two main policy questions to which BBCI is relevant:

• How do protected areas contribute, through the conservation of vegetation resources, to the health and productivity of the ecosystems and to the sustainability of the local communities that depend on these ecosystem services derived from them? Tree-root systems provide various ecosystem services that improve soil conditions and prevent soil degradation.

• How do protected areas contribute to carbon storage and hence to offset the impacts of fossil fuel emissions and to climate change mitigation? Forests represent one of the largest terrestrial organic carbon reservoirs, and significantly contribute to the regulation of the global carbon cycle. Root biomass represents a stable and relatively inaccessible carbon stock, mainly affected by the removal of the canopy. Protected areas may contribute to biomass and carbon retention and hence to the reduction of net emissions of greenhouse gasses responsible for climate change.

Use and interpretation

The BBCI provides an estimation of the amount of carbon stocks in tree roots. Together with the AGCI and SOCI, it provides a complete overview of the total carbon stored in forest areas (trees and soil). Roots are a long term and stable carbon sink, accounting for about 0.2 - 0.4 of the above ground biomass across biogeographical regions (Reich et al., 2014) of the total tree biomass. Moreover, well stablished and developed root systems provide various ecosystem services related to improved soil quality (higher cation exchange capacity and nutrient turnaround) and soil characteristics (improved aeration, soil porosity) as well as several soil-water-atmosphere interactions.

As a derived dataset, the BBCI inherits some of the characteristics from the original data, such as the spatial (100 m) and temporal (year 2022) resolution. In addition, water bodies, urban areas, permanent snow/ice and bare area land cover classes (ESA (2024)) are masked.

Key caveats

The BBCI is a derived product from two main sources of information:

• Above-ground biomass (AGB) data provided by the global terrestrial biomass map derived from Earth Observation data in the framework of the CCI BIOMASS project) funded by the European Space Agency (ESA).

• Chapter 4 of the 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories (IPCC, 2019), which indicates the most updated root-to-shoot ratios (R).

The IPCC Root-to-shoot ratios depend on the biogeographic conditions (ecozone), forest type, forest origin (natural or planted) and aboveground biomass density (Table 4.4 of IPCC, 2019). However, while the biomass map provides wall-to-wall global coverage, the IPCC ratios are not available for all existing combinations of the parameters indicated above. In order to estimate the root-to-shoot ratios in the classes not represented in the IPCC table , the following assumptions were made:

1. Missing ecozones in the IPCC table: use the ratio for the most similar ecozone included in the IPCC table. The similarity considers the way trees allocate biomass in the belowground component (i.e., higher ratios for dry ecozones)

2. Missing Continent for a certain ecozone in the IPCC table: use the average ratio available for other continents located in the same ecozone and same biomass class (if appropriate)

3. Missing Origin in the IPCC table: use the ratio for the same Forest type but different forest origin (if available)

4. Missing Forest type: use the ratio for the same (or most similar) Forest type but different Origin (if available)

5. Missing AGB class: use the ratio for the available AGB class (if available).

Similarly, some of the auxiliary dataset necessary to map the root-to-shoot ratios do not have global coverage. For instance, the Spatial Database of Planted Trees (Harris et al., 2019) used to identify the forest origin currently does not provide information for China and India. A similar situation occurs with the dataset providing the extent of Quercus forests, which covers only Europe and part of Asia. However, these and new datasets are under development and new releases may allow to fill these gaps.

Currently, the BGB map that we used to produce the BGCI is recently developed, and has not yet been validated nor reviewed by any scientific organism. Therefore, it should be used with caution and as a mere indication of the amount of carbon stock in tree roots.

In essence, the errors in the BGCI are mainly due to the uncertainty in the source datasets (the AGB map, the root-to-shoot ratios and the auxiliary dataset used to map the variables determining these ratios) that propagates into the BGB map, and the assumptions used for the missing ratios (for which there is no uncertainty estimate).

The biomass to carbon ratio used for this indicator is the same as for the aboveground biomass carbon indicator (AGBI): 0.5. This value is considered a good approximation of the typical carbon content in the biomass of terrestrial vegetation, and is consistent with the IPCC Good Practice Guidance for LULUCF (IPCC, 2003) and in other studies (Baccini et al., 2017; Zarin et al., 2016; Achard et al., 2014; Baccini et al., 2012; Saatchi et al., 2011; Gallaun et al., 2010). There is however some variation of this biomass to carbon conversion factor for different tree species, different components of a tree or a stand and age of the stand, which may be accounted for in more detailed assessments (Ruesch and Gibbs, 2008; Thurner et al., 2014).

Because the BBCI is computed within the boundaries of each protected area, results will be affected by the accuracy of the available protected area boundaries.

Indicator status

The belowground biomass dataset is derived from the aboveground biomass dataset developed by ESA's CCI BIOMASS project using root-to-shoot ratios. It was derived within the JRC and it will be made available on the KCBD Global Biodiversity Data Viewer. The computation of the Below Ground Biomass and its assessment in protected areas are not yet published.

Available data and resources

Data

BBCI values are provided at country level on the KCBD Global Biodiversity Data Viewer .

Update frequency

Planned annually.

Code

The procedure for the computation of the indicator, which currently involves the use of a wide range of software to handle the different steps, is documented in Juffe Bignoli et al. (2024).

Methodology

The BBCI is calculated from the belowground carbon dataset, which in turn is derived from the global terrestrial Above Ground Biomass map developed by the CCI BIOMASS project using the IPCC root-to-shoot ratios (IPCC, 2019). The belowground carbon map estimates, with a spatial resolution of 100 m and for the reference year 2022, the amount of tree root biomass in Mg/ha. The belowground biomass was converted to carbon content using the conversion factor of 0.5 (Mg C / Mg dry matter), which is consistent with the approach in the Good Practice Guidance in LULUCF by the IPCC (2003) and within the range of values (0.47 - 0.51) used in the related literature (Ruesch and Gibbs, 2008; Thurner et al., 2014).

The root biomass carbon is the result of two main inputs:

• Above-ground biomass (AGB) data provided by the global terrestrial biomass map derived from Earth Observation data in the framework of the CCI BIOMASS project funded by the European Space Agency (ESA).

• Chapter 4 of the 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories (IPCC, 2019) which indicates the most updated root-to-shoot ratios (R).

Additionally, auxiliary datasets were necessary to map the Root-to-Shoot ratios. The IPCC Root-to-shoot ratios depend on the biogeographic conditions (ecozone), forest type, forest origin (natural or planted) and the aboveground biomass density (Table 4.4 of IPCC, 2019). These were combined to create a map, which includes the different categories represented in the 2019 IPCC report. To retain the maximum amount of information from the aboveground biomass data set, and harmonize the two layers, a set of pre-processing procedures were applied for the construction of the categorical/combination layer representing the biogeographical-specific characteristics of the R.

Each value from the AGB map was multiplied by an R coefficient to calculate the belowground biomass fraction and obtain a belowground biomass map, which inherit the spatial (100 m) and temporal (year 2022) resolution of the input AGB map. The belowground biomass map was then converted to carbon units and then submitted to the standard procedure for continuous raster datasets described in details Juffe Bignoli et al. (2024) in order to derive the minimum, maximum and mean of BBCI (as density, in Mg C/ha) as well as the total BGC stored (Mg) within each country, terrestrial ecoregion and protected area. UNESCO Biosphere Reserves were discarded as well as protected areas with known areas but undefined boundaries.

Input datasets

References

Achard, F., Beuchle, R., Mayaux, P., Stibig, H. J., Bodart, C., Brink, A., ... & Lupi, A. (2014). Determination of tropical deforestation rates and related carbon losses from 1990 to 2010. Global change biology, 20(8): 2540-2554. https://doi.org/10.1111/gcb.12605

Baccini, A. G. S. J., Goetz, S. J., Walker, W. S., Laporte, N. T., Sun, M., Sulla-Menashe, D., ... & Samanta, S. (2012). Estimated carbon dioxide emissions from tropical deforestation improved by carbon-density maps. Nature climate change, 2(3): 182. https://doi.org/10.1038/nclimate1354

Baccini, A., Walker, W., Carvalho, L., Farina, M., Sulla-Menashe, D., & Houghton, R. A. (2017). Tropical forests are a net carbon source based on aboveground measurements of gain and loss. Science, 358(6360): 230-234. https://doi.org/10.1126/science.aam5962

Brus, D.J., G.M. Hengeveld, D.J.J. Walvoort, P.W. Goedhart, A.H. Heidema, G.J. Nabuurs, K. Gunia, 2011. Statistical mapping of tree species over Europe. Special Issue European Journal of Forest Research. https://doi.org/10.1007/s10342-011-0513-5

Dinerstein et al. (2017), An Ecoregion-Based Approach to Protecting Half the Terrestrial Realm, BioScience, Volume 67, Issue 6, June 2017, Pages 534–545, https://doi.org/10.1093/biosci/bix014

ESA (2024). ESA Land Cover CCI – Product User Guide and Specification. CDR and ICDR Sentinel-3 Land Cover (v2.1.1) – v2.1.1. Available online at https://cds.climate.copernicus.eu/datasets/satellite-land-cover?tab=documentation

Gallaun, H., Zanchi, G., Nabuurs, G. J., Hengeveld, G., Schardt, M., & Verkerk, P. J. (2010). EU-wide maps of growing stock and above-ground biomass in forests based on remote sensing and field measurements. Forest Ecology and Management, 260(3): 252-261. https://doi.org/10.1016/j.foreco.2009.10.011

Harris, N.L., E.D. Goldman, and S. Gibbes. 2019. “Spatial Database of Planted Trees Version 1.0.” Technical Note. Washington, DC: World Resources Institute. Available online at:  https://www.wri.org/publication/spatialdatabase-planted-trees

IPCC. (2013). Good Practice Guidance for Land Use, Land-Use Change and Forestry. Intergovernmental Panel on Climate Change. IPCC National Greenhouse Gas Inventories Programme. Available online at: https://www.ipcc-nggip.iges.or.jp/public/gpglulucf/gpglulucf_files/GPG_LULUCF_FULL.pdf

Juffe-Bignoli et al. (2024) Delivering Systematic and Repeatable Area-Based Conservation Assessments: From Global to Local Scales. Land 2024, 13, 1506. https://doi.org/10.3390/land13091506

Lázaro, C., Mandrici, A., Delli, G., Caudullo, G., Bourgoin, C. et al., Challenges in integrating global environmental data with GISCO administrative layers – A GIS perspective, Publications Office of the European Union, 2025. https://dx.doi.org/10.2760/8183010

Reich, P. B., Luo, Y., Bradford, J. B., Poorter, H., Perry, C. H., & Oleksyn, J. (2014). Temperature drives global patterns in forest biomass distribution in leaves, stems, and roots. Proceedings of the National Academy of Sciences, 111(38), 13721-13726. https://doi.org/10.1073/pnas.1216053111

Ruesch, A., and Holly K. Gibbs. 2008. New IPCC Tier-1 Global Biomass Carbon Map For the Year 2000. Available online from the Carbon Dioxide Information Analysis Center [http://cdiac.ess-dive.lbl.gov], Oak Ridge National Laboratory, Oak Ridge, Tennessee.

Saatchi, S. S., Harris, N. L., Brown, S., Lefsky, M., Mitchard, E. T., Salas, W., ... & Petrova, S. (2011). Benchmark map of forest carbon stocks in tropical regions across three continents. Proceedings of the National Academy of Sciences, 108(24): 9899-9904. https://doi.org/10.1073/pnas.1019576108

Santoro, M.; Cartus, O., Lucas, R., Kay, H. (2023a): CCI Biomass Algorithm Theoretical Basis Document v5. Aberystwyth University and GAMMA Remote Sensing, 2023.

https://climate.esa.int/documents/2788/D2_2_Algorithm_Theoretical_Basis_Document_ATBD_V5.0_20231219.pdf

Santoro, M.; Cartus, O. (2023b): CCI BIOMASS Product User Guide v4. Aberystwyth University and GAMMA Remote Sensing, 2023.  https://climate.esa.int/media/documents/D4.3_CCI_PUG_V4.0_20230605.pdf

Santoro, M.; Cartus, O. (2025): ESA Biomass Climate Change Initiative (Biomass_cci): Global datasets of forest above-ground biomass for the years 2007, 2010, 2015, 2016, 2017, 2018, 2019, 2020, 2021 and 2022, v6.0. NERC EDS Centre for Environmental Data Analysis, 17 April 2025. doi:10.5285/95913ffb6467447ca72c4e9d8cf30501. https://dx.doi.org/10.5285/95913ffb6467447ca72c4e9d8cf30501

Thurner, M., Beer, C., Santoro, M., Carvalhais, N., Wutzler, T., Schepaschenko, D., ... & Schmullius, C. (2014). Carbon stock and density of northern boreal and temperate forests. Global Ecology and Biogeography, 23(3): 297-310. https://doi.org/10.1111/geb.12125

UNEP-WCMC & IUCN (2025). Protected Planet: The World Database on Protected Areas (WDPA) [On-line], [January/2025], Cambridge, UK: UNEP-WCMC and IUCN. www.protectedplanet.net

Zarin, D. J., Harris, N. L., Baccini, A., Aksenov, D., Hansen, M. C., Azevedo‐Ramos, C., ... & Allegretti, A. (2016). Can carbon emissions from tropical deforestation drop by 50% in 5 years? Global change biology, 22(4): 1336-1347. https://doi.org/10.1111/gcb.13153