福建沿海地区第四系较为发育,是研究晚更新世以来相对海平面变化的理想区域。本文以福建宁德NDQK5岩芯中产出的高分辨率介形类化石为研究对象,结合加速器质谱法(accelerator mass spectrometry,AMS)14C和光释光测年技术建立岩芯年代框架,重建了中全新世期间福建沿海地区的相对海平面变化。结果显示,NDQK5岩芯中的介形类化石记录主要分布于4~17.1 m段,对应年代约为8.2~6.9 ka BP。岩芯内共计识别出海相介形类23属26种,根据优势种以及特征种的相对丰度变化特征可将岩芯内的介形类动物群划分为3个组合:①介形类组合A以Bicornucythere bisanensis和Sinocytheridea impressa为主,代表潮下带环境;②介形类组合B以Sinocytheridea impressa和Neomonoceratina delicata为优势种,指示近岸内陆架的沉积环境;③介形类组合C以Sinocytheridea impressa和Loxoconcha ocellifera为主,代表潮间带的沉积环境。基于介形类组合的分布特征,本文推断福建沿海地区海平面约在8.2~7.4 ka BP期间持续上升,并在约7.9~7.4 ka BP区间达到最高;7.4~7.0 ka BP期间海平面下降,随后再次上升。因此,介形类化石记录指示福建沿海地区在全新世高海平面背景下依然存在相对海平面的次一级波动。同时,结合已有福建沿海地区海平面变化驱动机制的研究结果,本研究推断8.2~7 ka BP期间福建沿海地区的海平面变化可能主要受控于冰盖融水;7 ka BP后该地区的海平面波动可能受控于“冰川-水均衡调整”作用。
The term“Holocene temperature conundrum”refers to the inconsistencies between proxy-based reconstructions and transient model simulations,and it challenges our understanding of global temperature evolution during the Holocene.Climate reconstructions indicate a cooling trend following the Holocene Thermal Maximum,while model simulations indicate a consistent warming trend due to icesheet retreat and rising greenhouse gas concentrations.Various factors,such as seasonal biases and overlooked feedback processes,have been proposed as potential causes for this discrepancy.In this study,we examined the impact of vegetation-climate feedback on the temperature anomaly patterns in East Asia during the mid-Holocene(~6 ka).By utilizing the fully coupled Earth system model EC-Earth and performing simulations with and without coupled dynamic vegetation,our objective was to isolate the influence of vegetation changes on regional temperature patterns.Our findings reveal that vegetation-climate feedback contributed to warming across most of East Asia,resulting in spatially diverse temperature changes during the mid-Holocene and significantly improved model-data agreement.These results high-light the crucial role of vegetation-climate feedback in addressing the Holocene temperature conundrum and emphasize its importance for simulating accurate climate scenarios.
Jie ChenQiong ZhangZhengyao LuYanwu DuanXianyong CaoJianping HuangFahu Chen
