Closing the DAta gap to develop Land Surface MOdels for COngo Basin forests - DAMOCO

01 September 2022 → 01 December 2026
Federal funding: various
Research disciplines
  • Natural sciences
    • Modelling and simulation
    • Climatology
    • Global ecology
    • Palaeo-ecology
    • Terrestrial ecology
    • Plant ecology
  • Agricultural and food sciences
    • Forest protection
    • Forestry management and modelling
climate change forest ecosystems Congo Basin ecosystem services landsurface models
Project description

The importance of accounting for ecosystem services was massively acknowledged on COP26. More than 100 World leaders promised to stop deforestation by 2030, and the EU specifically pledged to focus on protecting Congo Basin forests. This revealed an increasing global awareness that protecting climate-resistant, diverse, carbon-rich and CO2-absorbing areas such as the Congo Basin, is one of the most important nature-based solutions to halt temperature rise. However, there is a striking discrepancy between the Congo Basin’s paramount importance on the one hand and its poor scientific coverage on the other hand. As a result of this data gap, the two latest generations of Earth System Models are not capturing present-day tropical forest carbon dynamics. Therefore, the general ambition of this project is to contribute to closing the Congo Basin forest data gap and improve Land Surface Models to capture its biodiversity and carbon dynamics.
To reach this ambition, we will first collect new data on permanent forest inventory plots scattered across the Congo basin. The data will span multiple time scales by combining four different methodological approaches: (i) eddy-covariance data from CongoFlux (an ICOS ESFRI station) will provide (sub-)daily measurements of carbon and water fluxes; (ii) repeated tree measurements will reveal decadal-scale changes in the carbon balance, (iii) measuring a wide array of tree traits on the plots will allow in-depth analysis of decadal-scale changes in taxonomic and functional composition, and (iv) identification of radiocarbon dated fossil charcoal will reveal century-scale and millennial-scale changes in biodiversity. By themselves, those data will shed light on the short- and long-term resilience of critical Congo Basin forest ecosystem functions. Secondly, we will combine all collected data to parameterize and validate the Ecosystem Demography model (ED2) for the Congo Basin forest. Finally, we will use the newly parameterized and validated model to simulate future dynamics of Congo Basin biodiversity and carbon balance under different emission scenarios.
The project will have major scientific impact because the data will be made available through well-known and widely used scientific repositories, which all struggle with a common data gap in the Congo Basin. The project will contribute to capacity building by coaching Congolese students to become future science leaders. Finally, at the end of this project the Democratic Republic of Congo will have refined information on its past, present and future forest ecosystem and climate services, which will foster major policy impact at the national and international level.