Paleoclimate and paleoecology of the continental Eastern Mediterranean region - High-resolution pollen analysis from Lake Van during the Middle Pleistocene (MIS 8 to 10)

东地中海大陆地区的古气候和古生态 - 中更新世凡湖的高分辨率花粉分析（MIS 8 至 10）

• 批准号: 438764207
• 负责人: Professor Dr. Thomas Litt, since 10/2022
• 金额: --
• 依托单位: Geologischer Dienst Nordrhein-Westfalen Landesbetrieb
• 依托单位国家: 德国
• 项目类别: Infrastructure Priority Programmes
• 财政年份: 2020
• 资助国家: 德国
• 起止时间: 2019-12-31 至 2022-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/438764207?language=en
• 关键词: Paleoclimate; paleoecology; continental; Eastern; Mediterranean

Our current knowledge about paleoclimate development in the Near East beyond 250,000 years is rather poor. Lake Van (Eastern Anatolia, Turkey) represents an excellent key site for the investigation of the climatic evolution in the continental Eastern Mediterranean region. It fills the gap in data coverage between northern Levant and Mediterranean region. The project offers the unique opportunity to evaluate the variability of local / regional vegetation, fire frequency and climate variability during the third-last glacial-interglacial cycle (Marine Isotope Stage (MIS) 8 to 10; ca. 240 to 350 ka BP) by combing interdisciplinary data from palynology, microscopic charcoal and stable isotopes. The high-resolution palynological datasets resulting from this project are the basis for biome modelling and reconstruction of the climate development in the Eastern Mediterranean region tested with multivariate statistical methods (e.g., probability density function for reconstruction of temperature and precipitation). The aim of this study is the investigation of global climate signals below the frequency of Milankovitch cycles to determine whether they demonstrate a direct impact on vegetation composition and/or on the environmental conditions in this climatic sensitive region.

我们目前对近东 25 万年以来古气候发展的了解相当匮乏。凡湖（土耳其安纳托利亚东部）是研究东地中海大陆地区气候演变的绝佳关键地点。它填补了黎凡特北部和地中海地区数据覆盖范围的空白。该项目提供了独特的机会，通过结合孢粉学、显微木炭和稳定同位素的跨学科数据。该项目产生的高分辨率孢粉学数据集是利用多元统计方法（例如用于重建温度和降水的概率密度函数）测试的东地中海地区气候发展生物群落建模和重建的基础。本研究的目的是调查米兰科维奇周期频率以下的全球气候信号，以确定它们是否对该气候敏感地区的植被组成和/或环境条件产生直接影响。