德国不莱梅大学 Jonkers, Lukas 团队近日报道了通过浮游生物地理学揭示冰期北大西洋强温度梯度。这一研究成果发表在2023年12月5日出版的国际学术期刊《自然—地球科学》上。

该研究组利用群落相似性随热距离的增加而减小的基本宏观生态学原理，来评估末次冰期气候的模拟。研究人员对来自 647 个地点的浮游有孔虫物种组合的分析表明，当模拟冰期海水温度面对当时的物种组合时获得的相似性衰减模式与现代不同。浮游生物物种更替的现代温度依赖性与模拟之间的不一致的出现，是因为模拟显示末次盛冰期全球变冷相当均匀，而物种组合表明北大西洋亚极地有更强的变冷。

北大西洋隐含的更陡的热梯度与大西洋经向翻转环流减少的气候模式模拟更为一致。研究方法证明了宏观生态学可以用于对过去气候的模拟进行稳健的诊断，并强调了正确解决气候模型中全球变化的空间印记的挑战。

据悉，大约 2 万年前寒冷的末次盛冰期为评估气候模式是否能够模拟不同于现在的气候状态，提供了一个有意义的试验案例。然而，由于对过去环境变量(如海面温度)的重建具有间接和不确定的性质，这种评估仍然含糊不清。

附：英文原文

Title: Strong temperature gradients in the ice age North Atlantic Ocean revealed by plankton biogeography

Author: Jonkers, Lukas, Laepple, Thomas, Rillo, Marina C., Shi, Xiaoxu, Dolman, Andrew M., Lohmann, Gerrit, Paul, Andr, Mix, Alan, Kucera, Michal

Issue&Volume: 2023-12-05

Abstract: The cold Last Glacial Maximum, around 20,000 years ago, provides a useful test case for evaluating whether climate models can simulate climate states distinct from the present. However, because of the indirect and uncertain nature of reconstructions of past environmental variables such as sea surface temperature, such evaluation remains ambiguous. Instead, here we evaluate simulations of Last Glacial Maximum climate by relying on the fundamental macroecological principle of decreasing community similarity with increasing thermal distance. Our analysis of planktonic foraminifera species assemblages from 647 sites reveals that the similarity-decay pattern that we obtain when the simulated ice age seawater temperatures are confronted with species assemblages from that time differs from the modern. This inconsistency between the modern temperature dependence of plankton species turnover and the simulations arises because the simulations show globally rather uniform cooling for the Last Glacial Maximum, whereas the species assemblages indicate stronger cooling in the subpolar North Atlantic. The implied steeper thermal gradient in the North Atlantic is more consistent with climate model simulations with a reduced Atlantic meridional overturning circulation. Our approach demonstrates that macroecology can be used to robustly diagnose simulations of past climate and highlights the challenge of correctly resolving the spatial imprint of global change in climate models.

DOI: 10.1038/s41561-023-01328-7

Source: https://www.nature.com/articles/s41561-023-01328-7