Large uncertainties in future biome changes in Africa call for flexible climate adaptation strategies

Abstract

Anthropogenic climate change is expected to impact ecosystem structure, biodiversity and ecosystem services in Africa profoundly. We used the adaptive Dynamic Global Vegetation Model (aDGVM), which was originally developed and tested for Africa, to quantify sources of uncertainties in simulated African potential natural vegetation towards the end of the 21st century. We forced the aDGVM with regionally downscaled high‐resolution climate scenarios based on an ensemble of six general circulation models (GCMs) under two representative concentration pathways (RCPs 4.5 and 8.5). Our study assessed the direct effects of climate change and elevated CO2 on vegetation change and its plant‐physiological drivers. Total increase in carbon in aboveground biomass in Africa until the end of the century was between 18% to 43% (RCP4.5) and 37% to 61% (RCP8.5) and was associated with woody encroachment into grasslands and increased woody cover in savannas. When direct effects of CO2 on plants were omitted, woody encroachment was muted and carbon in aboveground vegetation changed between –8 to 11% (RCP 4.5) and –22 to –6% (RCP8.5). Simulated biome changes lacked consistent large‐scale geographical patterns of change across scenarios. In Ethiopia and the Sahara/Sahel transition zone, the biome changes forecast by the aDGVM were consistent across GCMs and RCPs. Direct effects from elevated CO2 were associated with substantial increases in water use efficiency, primarily driven by photosynthesis enhancement, which may relieve soil moisture limitations to plant productivity. At the ecosystem level, interactions between fire and woody plant demography further promoted woody encroachment. We conclude that substantial future biome changes due to climate and CO2 changes are likely across Africa. Because of the large uncertainties in future projections, adaptation strategies must be highly flexible. Focused research on CO2 effects, and improved model representations of these effects will be necessary to reduce these uncertainties.

Woody-biomass projections and drivers of change in sub-Saharan Africa

“…While our models do not incorporate mechanistic relationships or biogeochemical feedbacks that could alter the climate-driven trends, our results are generally consistent with those reported by Martens and colleagues 42 , who used an adaptive Dynamic Global Vegetation Model (aDGVM) to quantify ecosystem response to climate forcings under RCP 4.5 and RCP 8.5. The authors reported that woody vegetation changed between −8 to 11% under RCP 4.5, and by −22 to −6% under RCP 8.5 when CO 2 enrichment was omitted.…”

Forest regeneration within Earth system models: current process representations and ways forward

“…aDGVM2 builds upon aDGVM, but instead of having PFTs with a fixed set of traits defined at model initialization it allows individuals to assume unique trait combinations during the simulation in response to environmental conditions (Scheiter et al ., 2013). aDGVM2 has been run at regional to continental scales on multiple continents (Langan et al ., 2017; Martens et al ., 2021) and shows promise for global‐scale simulations.…”

Examining the sensitivity of the terrestrial carbon cycle to the expression of El Niño

“…LPJ-GUESS requires soil texture (Zobler, 1986;Sitch et al, 2003), daily temperature, precipitation, incoming shortwave radiation and the annual mean atmospheric carbon dioxide (CO 2 ) concentration. The atmospheric CO 2 concentration, varying annually, was compiled from atmospheric measurements (McGuire et al, 2001;Smith et al, 2014). We used the CRUNCEP V7 dataset (Viovy, 2018) as the meteorological forcing input for LPJ-GUESS.…”