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Protecting an artificial savanna as a nature-based solution to restore carbon and biodiversity in the Democratic Republic of the Congo

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Abstract
A large share of the global forest restoration potential is situated in artificial 'unstable' mesic African savannas, which could be restored to higher carbon and biodiversity states if protected from human-induced burning. However, uncertainty on recovery rates in protected unstable savannas impedes science-informed forest restoration initiatives. Here, we quantify the forest restoration success of anthropogenic fire exclusion within an 88-ha mesic artificial savanna patch in the Kongo Central province of the Democratic Republic of the Congo (DR Congo). We found that aboveground carbon recovery after 17 years was on average 11.40 +/- 0.85 Mg C ha-1. Using a statistical model, we found that aboveground carbon stocks take 112 +/- 3 years to recover to 90% of aboveground carbon stocks in old-growth forests. Assuming that this recovery trajectory would be representative for all unstable savannas, we estimate that they could have a total carbon uptake potential of 12.13 +/- 2.25 Gt C by 2100 across DR Congo, Congo and Angola. Species richness recovered to 33.17% after 17 years, and we predicted a 90% recovery at 54 +/- 2 years. In contrast, we predicted that species composition would recover to 90% of old-growth forest composition only after 124 +/- 3 years. We conclude that the relatively simple and cost-efficient measure of fire exclusion in artificial savannas is an effective nature-based solution to climate change and biodiversity loss. However, more long-term and in situ monitoring efforts are needed to quantify variation in long-term carbon and diversity recovery pathways. Particular uncertainties are spatial variability in socio-economics and growing conditions as well as the effects of projected climate change. Fire exclusion in an artificial savanna in the DR Congo resulted in rapid aboveground carbon recovery, at 11.40 +/- 0.85 Mg C ha-1 after 17 years and reaching 90% of aboveground carbon stocks in old-growth forests after 112 +/- 3 years. Species richness is predicted to recover even faster, reaching 90% of old-growth values after 54 +/- 2 years. We conclude that the relatively simple and cost-efficient measure of fire exclusion in artificial savannas is an effective nature-based solution to climate change and biodiversity loss, but more long-term monitoring efforts are needed to quantify variation in recovery pathways.image
Keywords
FIRE-PROTECTION, FOREST RECOVERY, TREE DENSITY, AFRICAN, VEGETATION, SECONDARY, BIOMASS, STOCKS, DETERMINANTS, EXCLUSION, artificial savanna, biodiversity recovery, carbon recovery, Central Africa, Congo Basin, forest restoration, nature-based solution

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MLA
DJIOFACK, Brice Y., et al. “Protecting an Artificial Savanna as a Nature-Based Solution to Restore Carbon and Biodiversity in the Democratic Republic of the Congo.” GLOBAL CHANGE BIOLOGY, vol. 30, no. 1, 2024, doi:10.1111/gcb.17154.
APA
DJIOFACK, B. Y., Beeckman, H., Bourland, N., Belanganayi, B. L., Laurent, F., Ilondea, B. A., … Hubau, W. (2024). Protecting an artificial savanna as a nature-based solution to restore carbon and biodiversity in the Democratic Republic of the Congo. GLOBAL CHANGE BIOLOGY, 30(1). https://doi.org/10.1111/gcb.17154
Chicago author-date
DJIOFACK, Brice Y., Hans Beeckman, Nils Bourland, Basile Luse Belanganayi, Félix Laurent, Bhely Angoboy Ilondea, Laurent Nsenga, et al. 2024. “Protecting an Artificial Savanna as a Nature-Based Solution to Restore Carbon and Biodiversity in the Democratic Republic of the Congo.” GLOBAL CHANGE BIOLOGY 30 (1). https://doi.org/10.1111/gcb.17154.
Chicago author-date (all authors)
DJIOFACK, Brice Y., Hans Beeckman, Nils Bourland, Basile Luse Belanganayi, Félix Laurent, Bhely Angoboy Ilondea, Laurent Nsenga, Alain Huart, Menard Mbende Longwwango, Victor Deklerck, Geert Lejeune, William Verbiest, Jan Van den Bulcke, Joris Van Acker, Tom De Mil, and Wannes Hubau. 2024. “Protecting an Artificial Savanna as a Nature-Based Solution to Restore Carbon and Biodiversity in the Democratic Republic of the Congo.” GLOBAL CHANGE BIOLOGY 30 (1). doi:10.1111/gcb.17154.
Vancouver
1.
DJIOFACK BY, Beeckman H, Bourland N, Belanganayi BL, Laurent F, Ilondea BA, et al. Protecting an artificial savanna as a nature-based solution to restore carbon and biodiversity in the Democratic Republic of the Congo. GLOBAL CHANGE BIOLOGY. 2024;30(1).
IEEE
[1]
B. Y. DJIOFACK et al., “Protecting an artificial savanna as a nature-based solution to restore carbon and biodiversity in the Democratic Republic of the Congo,” GLOBAL CHANGE BIOLOGY, vol. 30, no. 1, 2024.
@article{01HP1GNBQA0Q58J3MNFFNJFPW2,
  abstract     = {{A large share of the global forest restoration potential is situated in artificial 'unstable' mesic African savannas, which could be restored to higher carbon and biodiversity states if protected from human-induced burning. However, uncertainty on recovery rates in protected unstable savannas impedes science-informed forest restoration initiatives. Here, we quantify the forest restoration success of anthropogenic fire exclusion within an 88-ha mesic artificial savanna patch in the Kongo Central province of the Democratic Republic of the Congo (DR Congo). We found that aboveground carbon recovery after 17 years was on average 11.40 +/- 0.85 Mg C ha-1. Using a statistical model, we found that aboveground carbon stocks take 112 +/- 3 years to recover to 90% of aboveground carbon stocks in old-growth forests. Assuming that this recovery trajectory would be representative for all unstable savannas, we estimate that they could have a total carbon uptake potential of 12.13 +/- 2.25 Gt C by 2100 across DR Congo, Congo and Angola. Species richness recovered to 33.17% after 17 years, and we predicted a 90% recovery at 54 +/- 2 years. In contrast, we predicted that species composition would recover to 90% of old-growth forest composition only after 124 +/- 3 years. We conclude that the relatively simple and cost-efficient measure of fire exclusion in artificial savannas is an effective nature-based solution to climate change and biodiversity loss. However, more long-term and in situ monitoring efforts are needed to quantify variation in long-term carbon and diversity recovery pathways. Particular uncertainties are spatial variability in socio-economics and growing conditions as well as the effects of projected climate change.

 Fire exclusion in an artificial savanna in the DR Congo resulted in rapid aboveground carbon recovery, at 11.40 +/- 0.85 Mg C ha-1 after 17 years and reaching 90% of aboveground carbon stocks in old-growth forests after 112 +/- 3 years. Species richness is predicted to recover even faster, reaching 90% of old-growth values after 54 +/- 2 years. We conclude that the relatively simple and cost-efficient measure of fire exclusion in artificial savannas is an effective nature-based solution to climate change and biodiversity loss, but more long-term monitoring efforts are needed to quantify variation in recovery pathways.image}},
  articleno    = {{e17154}},
  author       = {{DJIOFACK, Brice Y. and  Beeckman, Hans and  Bourland, Nils and  Belanganayi, Basile Luse and Laurent, Félix and  Ilondea, Bhely Angoboy and  Nsenga, Laurent and  Huart, Alain and  Longwwango, Menard Mbende and  Deklerck, Victor and  Lejeune, Geert and Verbiest, William and Van den Bulcke, Jan and Van Acker, Joris and  De Mil, Tom and Hubau, Wannes}},
  issn         = {{1354-1013}},
  journal      = {{GLOBAL CHANGE BIOLOGY}},
  keywords     = {{FIRE-PROTECTION,FOREST RECOVERY,TREE DENSITY,AFRICAN,VEGETATION,SECONDARY,BIOMASS,STOCKS,DETERMINANTS,EXCLUSION,artificial savanna,biodiversity recovery,carbon recovery,Central Africa,Congo Basin,forest restoration,nature-based solution}},
  language     = {{eng}},
  number       = {{1}},
  pages        = {{18}},
  title        = {{Protecting an artificial savanna as a nature-based solution to restore carbon and biodiversity in the Democratic Republic of the Congo}},
  url          = {{http://doi.org/10.1111/gcb.17154}},
  volume       = {{30}},
  year         = {{2024}},
}

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