Publication Details

AFRICAN RESEARCH NEXUS

SHINING A SPOTLIGHT ON AFRICAN RESEARCH

earth and planetary sciences

Vegetation dynamics in response to evolution of the Asian Monsoon in a warm world: Pollen evidence from the Weihe Basin, central China

Global and Planetary Change, Volume 193, Article 103269, Year 2020

Late Miocene and Pliocene climate changes provide an analogue for understanding linkages between variations in precipitation, the intensity of the Asian Monsoon (AM) and vegetation in a warm world with high atmospheric CO2. This study presents a reconstruction of vegetation and paleoclimate based on a pollen sequence between ~10.8 and 7.2 Ma, in addition to an analysis of pollen assemblages of Pliocene and Pleistocene, from the Weihe Basin, central China. Based on the Coexistence Approach (CA), the reconstruction indicates that the late Miocene and Pliocene climate was warmer and wetter than today, and that the vegetation responded to a strengthened AM prior to the onset of the Northern Hemisphere glaciations (NHG) during the early Pliocene. A significant vegetation shift from forest to grassland occurred at ~9.0 Ma, suggesting a climate shift from warm-wet to cool-dry in central East Asia earlier than previously thought. The quantitative reconstruction suggests that mean annual precipitation exceeded ~800 mm/year and the warm season (June to September) precipitation exceeded ~560 mm during ~10.8–7.2 Ma. Based on pollen analysis, the late Pliocene, however, appears to have been relatively cool and dry, followed by a colder and drier Pleistocene, associated with an overall weakening of the AM. The paleoclimate reconstruction reveals that the AM exhibited phased weakening since ~10.8 Ma, which is consistent with stepwise global temperature variations. It is clear that vegetation variations were mainly driven by the AM precipitation and global cooling in the semi-humid region of the Weihe Basin since the late Cenozoic. This study provides insights into vegetation dynamics under global warming conditions.
Statistics
Citations: 16
Authors: 8
Affiliations: 5
Study Approach
Quantitative