A continental-scale chironomid training set for reconstructing Arctic temperatures
A continental-scale chironomid training set for reconstructing Arctic temperatures
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DOI：
10.1016/j.quascirev.2022.107728
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发表时间：
2022-10
影响因子：
4
通讯作者：
A. Medeiros;M. Chipman;D. Francis;L. Hamerlík;P. Langdon;P. Puleo;G. Schellinger;Regan Steigleder;I. Walker;S. Woodroffe;Y. Axford
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作者：
A. Medeiros;M. Chipman;D. Francis;L. Hamerlík;P. Langdon;P. Puleo;G. Schellinger;Regan Steigleder;I. Walker;S. Woodroffe;Y. Axford
我们提供了北美北部、格陵兰、冰岛和斯瓦尔巴群岛402个湖泊的摇摆虫物种组合数据，以解释用于古湖泊重建的全新世亚化石摇摆虫组合。该校准集是通过重新识别和分类协调先前描述的表层沉积物样品中的摇蚊而开发的，与原始出版物相比，在分类分辨率上进行了更精细的识别。该数据集的大范围地理覆盖旨在为北大西洋西北部地区和包括格陵兰在内的北美北极地区的广泛全新世气候提供气候类比。对于这些地区中的许多地区，现代校准数据很稀少，尽管人们对高纬度地区的古气候重建非常感兴趣。基于该训练集的一套基于摇摆学的温度模型在这里进行了评估，并使用最好的统计模型重建了代表格陵兰大范围气候带的五个非冰期湖泊的晚冰期(阿勒德和年轻仙女木)和全新世古温度。与现有的较小的训练集相比，新的大陆范围的训练集为格陵兰的大多数亚化石组合提供了更多的相似之处，其中许多在冰岛和加拿大北部。我们发现，从新模型得到的基于摇摆线的重建与基于冰川的独立证据之间存在很强的一致性，这些证据表明了几千年的全新世温度趋势。一些新的全新世重建与已发表的数据非常相似，但在一些地点和时间段，我们发现改进的古温度重建既归因于新模型更好的分类分辨率，也归因于其扩大的地理/气候覆盖范围，这导致了对物种最优的更好的表征。在冰川晚期，新模型更精细的分类分辨率产生了一种独特的能力，可以从年轻仙女木较冷的温度中分辨出阿勒德的温度，尽管这种温差的幅度可能被低估了。这项研究证明了地理和气候上广泛的古生态训练集的价值。这里给出的大的、分类上统一的数据集应该对未来的广泛调查有用，包括但不限于北极地区的古温度重建。
We present chironomid species assemblage data from 402 lakes across northern North America, Greenland, Iceland, and Svalbard to inform interpretations of Holocene subfossil chironomid assemblages used in paleolimnological reconstruction. This calibration-set was developed by re-identifying and taxonomically harmonizing chironomids in previously described surface sediment samples, with identifications made at finer taxonomic resolution than in original publications. The large geographic coverage of this dataset is intended to provide climatic analogues for a wide range of Holocene climates in the northwest North Atlantic region and North American Arctic, including Greenland. For many of these regions, modern calibration data are sparse despite keen interest in paleoclimate reconstructions from high latitudes. A suite of chironomid-based temperature models based upon this training set are evaluated here and the best statistical model is used to reconstruct late glacial (Allerød and Younger Dryas) and Holocene paleotemperatures at five non-glacial lakes representing a wide range of climate zones across Greenland. The new continent-scale training set offers more analogues for the majority of Greenland subfossil assemblages than existing smaller training sets, with many in Iceland and northern Canada. We find strong agreement between chironomid-based reconstructions derived from the new model and independent glacier-based evidence for multi-millennial Holocene temperature trends. Some of the new Holocene reconstructions are very similar to published data, but at a subset of sites and time periods we find improved paleotemperature reconstructions attributable both to the new model's finer taxonomic resolution and to its expanded geographic/climatic coverage, which resulted in improved characterization of species optima. In the late glacial, the new model's finer taxonomic resolution yields a unique ability to resolve temperatures of the Allerød from colder temperatures of the Younger Dryas, although the magnitude of that temperature difference may be underestimated. This study demonstrates the value of geographically and climatically broad paleoecological training sets. The large, taxonomically harmonized dataset presented here should be useful for a wide range of future investigations, including but not limited to paleotemperature reconstructions across the Arctic.