The last deglaciation (from ~21,000 to 9,000 years ago), during which the huge ice sheets over the North America and Scandinavia melted, is a period of tremendous climate and environmental changes. These changes are documented by physically based paleoenvironmental indicators (such as oxygen or carbon isotopes in ice cores and marine cores), but less by biologically based data (such as paleo-vegetation). Paleo-vegetation data is, however, crucial to document continental-scale climate and environmental changes over the deglaciation. This project aimed, for this period of the last deglaciation, at 1) building a comprehensive documentation of vegetation and climate changes over terrestrial areas from widely available pollen data, 2) assessing the impact of both climate and atmospheric CO2 changes on the vegetation and 3) investigating the changes in large-scale atmosphere circulation and hydrological cycle responsible for these surface climate and vegetation changes. These results should contribute to quantifying the range of possible changes in these circulations in the future. Finally, this project provides new benchmarking data for understanding environmental changes and evaluating climate models which are used for climate projections.
Pollen-based climate reconstructions have generally been implemented with conventional statistical approaches (e.g. modern analog, regression and response-surface techniques), which assume that vegetation responses to climate remain the same through time and that modern data contain all the information necessary to interpret fossil pollen data. However, plant-climate interactions are sensitive to atmospheric CO2 concentration, and present-day relationships between climate and present plant distributions may not be representative of those under much lower atmospheric CO2 concentration. That is the reason why pollen-based climate reconstructions over the last deglaciation had hardly been performed. Therefore, for pollen-based climate reconstruction in this project, we used an “inverse modeling through iterative forward modeling” (IMIFM) approach (Izumi and Bartlein, 2016). The IMIFM approach, which originated as an inverse vegetation-modeling approach, have developed to overcome some debatable issues of conventional statistical approaches for climate reconstruction, as was mentioned earlier. The IMIFM approach is based on a forward modeling approach with equilibrium vegetation models (BIOME4 and BIOME5-beta) that uses input of climate, soil properties, surface air pressure and atmospheric CO2 concentrations to mechanically simulate vegetation under a specific environment. As a result, we consider several factors including atmospheric CO2 concentration for pollen-based climate reconstruction over the world.
Our biomization procedure and IMIFM approach were applied to several regions and validated by our former papers, Izumi and Lézine (2016) for Africa and Izumi and Bartlein (2016) for North America. Moreover, we enlarged the application beyond the last deglaciation period (i.e. vegetation and climate changes over the last 90,000 years at the Lake Bambili, Cameroon).
