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Toward a biome-scale monitoring of the Congo basin forest functional composition

Expected strong climate, demographic and economic changes in Central Africa threaten the sustainability of ecological, social and economic services Congo Basin Forests (CBF) provide to humanity. In addition to deforestation, anthropogenic environmental impacts will lead to dramatic changes in forest tree functional composition with potential deleterious feedbacks on carbon and water cycles among other services.

Our project aims at developing an integrated approach for the monitoring of tree functional diversity of the CBF to support biome-scale assessment of their vulnerability to global changes. Achieving such aim faces several challenges that define the specific objectives of the project: (1) Gather, harmonize and share existing data to provide ground-truth estimates of multiple dimensions of tree diversity in the CBF. (2) Connect existing forest plots to develop a regional network of observatories for a consistent monitoring of functional dynamics. (3) Characterize variation in functioning of canopy species along environmental gradients, combining proximal sensing of tree phenology and ground ecophysiological and functional trait measurements. (4) Develop an up-scaling chain from field data, to proximal and intermediate high-resolution (Sentinel-1 and Sentinel-2) and coarse-resolution remote sensing data captured by time-series of satellite data of various types and resolutions provided by recent and upcoming Earth Observation Systems to quantify biomescale Essential Biodiversity Variables (EBVs). (5) Combine biome-scale EBVs and environmental drivers to assess CBF vulnerability to expected changes (based on trend analyses and space-for-time substitution approaches). (6) Disseminate the project outcome to forest stakeholders, and by technology transfer and capacity development of students and staff in the academic and operational African partner institutions of the project.

International Collaboration Projects PCI2023-2, call 2023.

Project PCI2023-146002-2 funded by MCIN/AEI/10.13039/501100011033 and co-funded by the European Union.

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