Humic tropical lakes and wetlands are globally important sources of atmospheric greenhouse gases (GHGs). However, mechanistic insight into GHG cycling in such systems remains limited—especially in understudied central Africa. To address this, here we measured high‐, falling‐, and low‐water seasonal concentrations and isotopic compositions of the major dissolved GHGs , , and in Africa's largest humic lake: Mai Ndombe, Democratic Republic of Congo. We find that the water column is weakly to non‐stratified and is highly supersaturated with respect to atmospheric equilibrium for all GHGs across all seasons, sampling stations, and water depths. Additionally, all GHG concentrations increase steadily with increasing water depth, reflecting atmospheric gas exchange due to physical mixing in the upper water column as well as biological processes. Extrapolating these results—combined with field measurements such as temperature and wind speed—we estimate that Lake Mai Ndombe emits 375 ± 32 Gg C yr ⁻¹ as , 623 ± 136 Mg C yr ⁻¹ as , and 223 20 Mg N yr ⁻¹ as ( propagated Monte Carlo uncertainty). Furthermore, carbon‐isotope signals suggest that is largely sourced from respiration of bioavailable organic carbon, whereas reflects sedimentary methanogenesis followed by aerobic methanotrophy in the water column. Finally, bulk and position‐specific isotopic compositions reveal a nitrogen cycle dominated by sedimentary denitrification, with near‐quantitative reduction to prior to upward diffusion into the water column and eventual outgassing. Combined, these observations reveal that carbon inputs, total water depth, and/or dissolved oxygen saturation are the major drivers of the flux and composition of GHGs emitted from Lake Mai Ndombe and potentially other tropical humic lakes.

Within tropical forest ecosystems, wetlands such as swamp forests are an important interface between the terrestrial and aquatic landscape. Despite this assumed importance, there is a paucity of carbon flux data from wetlands in tropical Africa. Therefore, the magnitude and source of carbon dioxide (CO₂) fluxes, carbon isotopic ratios, and environmental conditions were measured for 3 years between 2019 and 2022 in a seasonally flooded forest and a perennially flooded forest in the Cuvette Centrale of the Congo Basin. The mean surface fluxes for the seasonally flooded site and the perennially flooded site were 2.36±0.51 and 4.38±0.64 $\mathrm{\mu }\mathrm{mol}{\mathrm{m}}^{-\mathrm{2}}{\mathrm{s}}^{-\mathrm{1}}$ , respectively. The time series data revealed no marked seasonal pattern in CO₂ fluxes. As for the environmental drivers, the fluxes at the seasonally flooded site exhibited a positive correlation with soil temperature and soil moisture. Additionally, the water level appeared to be a significant factor, demonstrating a quadratic relationship with the soil fluxes at the seasonally flooded site. δ¹³C values showed a progressive increase across the carbon pools, from aboveground biomass to leaf litter and then to soil organic carbon (SOC). However, there was no significant difference in δ¹³C enrichment between SOC and soil-respired CO₂. This lack of enrichment can be attributed to either a significant contribution from the autotrophic component of soil respiration or closed system dynamics. An in-situ-derived gas transfer velocity (k₆₀₀=2.95 cm h⁻¹) was used to calculate the aquatic CO₂ fluxes at the perennially flooded site. Despite the low k₆₀₀, relatively high CO₂ surface fluxes were found due to very high partial pressure of CO₂ (pCO₂) values measured in the flooding waters. Overall, these results offer a quantification of the CO₂ fluxes from forested wetlands and provide insights into the temporal variability of these fluxes and their sensitivity to environmental drivers.

Congo Basin lakes Mai Ndombe and Tumba are major CO ₂ sources. Here we show that their dissolved inorganic carbon is some 2,170–3,515 ¹⁴ C years old and partially (39–40%) originates from the surrounding peatlands. This implies a loss pathway for peat carbon, in which microbes respire old carbon within the peat and the resulting CO ₂ is transported to the lakes and outgassed, linking these immense ancient stores to the modern carbon cycle.

The Kasaï River Basin (KRB), the largest tributary system of the Congo basin, is undergoing rapid land-use transformation driven by population growth and expanding economic activities. However, existing global and regional land-cover products do not fully capture this highly heterogeneous, smallholder-dominated landscape or its temporal dynamics. Here, we develop a regionally calibrated 30 m resolution land-cover dataset for the KRB for 2017–2024 by combining 3,734 reference observations across five classes (urban, water, forest, savanna/grassland, cropland) with a random forest classifier trained on multi-source Earth observation datasets encoded as embeddings by Google’s AlphaEarth Foundations. The resulting classification achieves 96%–100% accuracy for urban and water classes and 74%–87% for forest, savanna/grassland, and cropland classes, substantially outperforming current global products (30%–65%). This improvement results from using a large region-specific training dataset and a modeling strategy designed to capture land surface phenology; this enhances the detection of inter-annual dynamics in rotational and intermittent smallholder agriculture, characteristic for many tropical regions such as the KRB. We estimate that in 2024 cropland covered 16.2% of the KRB, while forest and savanna/grassland occupied 41.1% and 41.5%, respectively—values that contrast sharply with those from existing products, which report cropland extents of only 0.1%–4.7%. Transition analysis further reveals that over 53 128 km ² of forest and grassland in the KRB have been converted to cropland between 2017 and 2024. These results highlight the need for regionally calibrated land-cover products in heterogeneous tropical landscapes. By resolving the systematic biases present in existing global products, the dataset produced here provides an accurate, high-resolution benchmark that underpins environmental modeling, food security analysis, and land-use decision-making in the KRB and other tropical regions.

Within tropical forest ecosystems, wetlands such as swamp forests are an important interface between the terrestrial and aquatic landscape. Despite this assumed importance, there is a paucity of carbon flux data from wetlands in tropical Africa. Therefore, the magnitude and source of CO₂ fluxes, carbon isotopic ratios, and environmental conditions were measured for three years between 2019 to 2022 in a seasonally flooded forest and a perennially flooded forest in the Cuvette Centrale of the Congo Basin. The mean surface fluxes for the seasonally flooded site and the perennially flooded site were 2.36 ± 0.51 µmol m^-2 s^-1 and 4.38 ± 0.64 µmol m^-2 s^-1 respectively. The time series data revealed no discernible seasonal pattern in CO₂ fluxes. As for the environmental drivers, the fluxes at the seasonally flooded site exhibited a positive correlation with soil temperature and soil moisture. Additionally, the water table depth appeared to be a significant factor, demonstrating a quadratic relationship with the soil fluxes at the seasonally flooded site. δ¹³C values showed a progressive increase across the carbon pools, from above-ground biomass, then leaf litter, to soil organic carbon (SOC). However, there was no significant difference in δ¹³C enrichment between SOC and soil respired CO₂. An in-situ derived gas transfer velocity (k₆₀₀ = 2.95 cm h^-1) was used to calculate the aquatic CO₂ fluxes at the perennially flooded site. Despite the low k_600, relatively high CO₂ surface fluxes were found due to very high dissolved pCO₂ values measured in the flooding waters. Overall, these results offer a quantification of the CO₂ fluxes from forested wetlands and provide an insight of the temporal variability of these fluxes as well as their sensitivity to environmental drivers.