Last updated | August 21, 2025

Indicator information

Name

Dead Wood Carbon Indicator (DWCI) and Litter Carbon Indicator (LCI)

Unit

The dead wood carbon and litter carbon are expressed in Mg (megagrams or tonnes) of carbon per ha. They represent an estimation of the carbon stored in the dead wood and in undecomposed leaves on the ground surface of forest areas. This carbon pool is calculated as a fraction of the above ground biomass carbon stock, based on the methodology and using the conversion ratios provided by Harris et al., 2021.

Area of interest

The DWCI and the LCI have been calculated and distributed through REST services at country, terrestrial ecoregion and protected area level and are 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 DWCI and LCI are 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? Dead wood and litter provide various ecosystem services that contribute to the maintenance of adequate levels of organic matter in the soil, thus improving soil conditions, reduce water erosion 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. Dead wood and litter represents a quite dynamic and accessible carbon stock, heavily 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 DWCI and LCI provides an estimation of the amount of carbon stocks in dead wood and undecomposed leaves on soil surface. Together with the AGCI. BGCI and SOCI, these two carbon pools contribute to the total carbon stored in forest areas (trees and soil). Dead wood and litter are a highly dynamic carbon sink, both for anthropogenic activities and natural degradation processes. They account for about 8% and 5% respectively (Pan et al., 2011) of the above ground biomass and their importance is related to the variety of ecosystem services such as the contribution, as a source of organic matter, to the improvement of chemical and physical soil properties (higher cation exchange capacity and nutrient turnaround) and soil characteristics (improved aeration, soil porosity) and to the protection from water erosion.

As derived datasets, the DWCI and LCI inherit some of the characteristics from the original above ground biomass 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 DWCI and LCI are products derived from the following datasets:

• 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).

• Conversion ratios provided by Harris et al., 2021, which in turn depend on the biogeographic conditions (ecological zone), rainfall regime and altitude.

Currently, the Dead Wood and Litter maps that we used to produce the DWCI and LCI are recently developed, and have not yet been validated nor reviewed by any scientific organism. Therefore, they should be used with caution and as a mere indication of the amount of carbon stock in dead wood and litter.

In essence, the errors in the DWCI and LCI are mainly due to the uncertainty in the source datasets (the AGB map, the conversion ratios and the auxiliary datasets used to map these ratios) that propagates into the DWCI and LCI maps.

The biomass to carbon ratio used for these indicators are the same as for the above ground biomass carbon indicator (AGBI): 0.5. There is however some variation of this biomass to carbon conversion factors for different biomes, taxonomic divisions and even tissue types, which may be accounted for in more detailed assessments (Martin et al., 2021; Ruesch and Gibbs, 2008; Thurner et al., 2014).

Because the DWCI and LCI are computed within the boundaries of each protected area, results will be affected by the accuracy of the available protected area boundaries.

Indicator status

The Dead Wood and Litter maps are derived from the Above Ground Biomass map developed by ESA CCI BIOMASS project. They have been computed within the JRC and it will be made available on the Digital Observatory for Protected Areas main page. The computation of the Dead Wood and Litter carbon stocks and their assessment in protected areas are not yet published.

Available data and resources

Data

DWCI and LCI 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

DWCI and LCI values are  calculated from the two corresponding maps od Dead Wood and Litter biomass, which in turn are derived from the global Above Groud Biomass map developed by the CCI BIOMASS project.

The Dead Wood and Litter carbon maps estimate, with a spatial resolution of 100 m and for the reference year 2021, the amount of dead wood and of undecomposed leaves biomass in Mg/ha. Biomass Is converted into 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 procedure for the computation of Dead Wood and Litter datasets is based on the methodology provided by Harris et al., 2021 and it consists in the application of conversion coefficients to the Above Ground Biomass values. Conversion coefficients are function of three different spatial parameters: ecological zones, annual rainfall and elevation.

The following inputs are used for the built-up of a look-up table for data conversion:

• FAO Global Ecological Zones, defined as zones or areas with broad yet relatively homogeneous natural vegetation formations, with similar physiognomy. Boundaries of the Ecological Zones approximately coincide with the map of Köppen-Trewartha climatic types.

• Monthly mean rainfall: global 30 arc-seconds (Worldclim 2) monthly data are used to derive the average annual rainfall.

• Gridded bathymetric data set (GEBCO), providing elevation data, in meters, on a 15 arc-second interval grid.

Once each input parameter is reclassed, the coefficients below (as from table S4 of Harris et al., 2021) are applied to convert Above Ground Biomass to Dead Wood and Litter values, respectively:

Each value from the AGB map was multiplied by the corresponding coefficient to calculate the dead wood and litter biomass fraction, respectively, and obtain the two Dead Wood and Litter biomass Maps, which inherit the spatial (100 m) and temporal (year 2022) resolution of the input AGB map.

The two maps were 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 DWCI and LCI (as density, in Mg C/ha) as well as the total DWCI and LCI 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

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

FAO (2012) Global ecological zones for FAO forest reporting: 2010 Update. Forest Resources Assessment Working Paper 179, Rome, 2012. https://www.fao.org/3/ap861e/ap861e00.pdf

Fick, S. E. & Hijmans, R. J. (2017). WorldClim 2: New 1-km spatial resolution climate surfaces for global land areas. International Journal of Climatology, 37: 4302-4315. https://doi.org/10.1002/joc.5086

Harris, N.L., Gibbs, D.A., Baccini, A. et al. Global maps of twenty-first century forest carbon fluxes. Nat. Clim. Chang. 11, 234–240 (2021). https://doi.org/10.1038/s41558-020-00976-6

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

Martin, A.R., Domke, G.M., Doraisami, M. et al. Carbon fractions in the world’s dead wood. Nat Commun 12, 889 (2021). https://doi.org/10.1038/s41467-021-21149-9

Pan, Y., Birdsey, R., Fang, J., Houghton, R., Kauppi, P.E., Kurz, W.A., Phillips, O.L., Shvidenko,A., Lewis, SL.L., Canadell, J.G., Ciais, P., Jackson, R.B., Pacala, S.W., McGuire, A.D., Piao, S., Rautiainen, A., Sitch, S., Hayes, D. (2011). A Large and Persistent Carbon Sink in the World’s Forests. Science Volume 333, Issue 6045: Investing Early in Education. Aug 2011. DOI: 10.1126/science.1201609

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.

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

Weatherall, P., et al. (2014). A new digital bathymetric model of the world's oceans. Earth and Space Science, 2, https://doi.org/10.1002/2015EA000107