Holocene evolution of Saharan vegetation revealed by paleoclimate simulations and machine learning
The Greening of the Sahara (GS) during the African Humid Period (AHP) is a striking example of past climate–vegetation interactions, yet its detailed spatiotemporal patterns across the Holocene remain insufficiently understood. This study develops a data-driven framework that combines paleoclimate simulations with machine learning to reconstruct vegetation dynamics in North Africa. Two machine learning models, an artificial neural network (ANN) and a random forest (RF), were trained on observed nonlinear relationships between vegetation and climate variables. These models were applied to paleoclimate proxy data and the transient climate simulation TraCE-21ka to estimate Holocene normalized difference vegetation index (NDVI). The ANN model outperformed RF in representing complex vegetation–climate linkages and showed closer agreement with proxy evidence. ANN-based reconstructions indicate a rapid expansion of vegetation in North Africa and the Arabian Peninsula following the Younger Dryas (∼12,000 years BP), sustained high vegetation cover during the AHP (10,000–6,200 years BP), and a gradual decline thereafter. However, the ANN underestimated both the overall vegetation cover and the abrupt decline around 6,000 years BP suggested by proxy data. Sensitivity analyses highlight monsoon-driven precipitation as the primary control on vegetation change, with temperature exerting a secondary but reinforcing influence. This machine learning–based framework provides a new perspective for investigating vegetation responses to past and future climate change. • Developed a data-driven framework integrating paleoclimate simulations and machine learning, enabling high-resolution reconstruction of Holocene Saharan vegetation dynamics in a computationally efficient manner. • Revealed a three-phase evolution of Saharan vegetation: rapid expansion (∼12–10 ka BP), sustained high cover (10–6.2 ka BP), and gradual decline—driven primarily by precipitation, with temperature as a secondary factor and minimal influence from CO 2 . • Provided evidence that the Green Sahara played a supporting role in agricultural development and cultural expansion across Eurasia.
Authors
- Cheng Shen (ORCID: https://orcid.org/0000-0003-1727-2638)
- Jian Liu (ORCID: https://orcid.org/0000-0001-7484-401X)
- Xi Zhang (ORCID: https://orcid.org/0000-0002-4638-3997)
- Weiyi Sun
- Bo Lu
- Guangyao Hao
- Deliang Chen
- Guonian Lü
- Liang Ning
Institutions
- China Meteorological Administration (CN)
- Nanjing Normal University (CN)
- Nanjing University of Information Science and Technology (CN)
- Shaanxi Provincial Meteorological Bureau (CN)
- Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application (CN)
- Ministry of Education (BD)
- University of Gothenburg (SE)
- Tsinghua University (CN)
Publication Details
- Journal
- Information Geography
- Published
- 2026-02-10
- DOI
- https://doi.org/10.1016/j.infgeo.2026.100042
- Primary Topic
- Geology and Paleoclimatology Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00