ALBERT

Description: Biodiversity is expected to change in response to future global warming. However, it is difficult to predict how species will track the ongoing climate change. Here we use the fossil record of planktonic foraminifera to assess how biodiversity responded to climate change with a magnitude comparable to future anthropogenic warming. We compiled time series of planktonic foraminifera assemblages, covering the time from the last ice age across the deglaciation to the current warm period. Planktonic foraminifera assemblages shifted immediately when temperature began to rise at the end of the last ice age and continued to change until approximately 5,000 years ago, even though global temperature remained relatively stable during the last 11,000 years. The biotic response was largest in the mid latitudes and dominated by range expansion, which resulted in the emergence of new assemblages without analogues in the glacial ocean. Our results indicate that the plankton response to global warming was spatially heterogeneous and did not track temperature change uniformly over the past 24,000 years. Climate change led to the establishment of new assemblages and possibly new ecological interactions, which suggests that current anthropogenic warming may lead to new, different plankton community composition.

Description: The Last Interglacial (~129,000–116,000 years ago) is the most recent geologic period with a warmer-than-present climate. Proxy-based temperature reconstructions from this interval can help contextualize natural climate variability in our currently warming world, especially if they can define changes on decadal timescales. Here, we established a ~4.800-year-long record of sea surface temperature (SST) variability from the eastern Mediterranean Sea at 1–4-year resolution by applying mass spectrometry imaging of long-chain alkenones to a finely laminated organic-matter-rich sapropel deposited during the Last Interglacial. We observe the highest amplitude of decadal variability in the early stage of sapropel deposition, plausibly due to reduced vertical mixing of the highly stratified water column. With the subsequent reorganization of oceanographic conditions in the later stage of sapropel deposition, when SST forcing resembled the modern situation, we observe that the maximum amplitude of reconstructed decadal variability did not exceed the range of the recent period of warming climate. The more gradual, centennial SST trends reveal that the maximal centennial scale SST increase in our Last Interglacial record is below the projected temperature warming in the twenty-first century.

Description: 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.

Description: Palaeoclimate data hold the unique promise of providing a long-term perspective on climate change and as such can serve as an important benchmark for climate models. However, palaeoclimate data have generally been archived with insufficient standardisation and metadata to allow for transparent and consistent uncertainty assessment in an automated way. Thanks to improved computation capacity, transient palaeoclimate simulations are now possible, calling for data products containing multi-parameter time series rather than information on a single parameter for a single time slice. Efforts are underway to simulate a complete glacial–interglacial cycle using general circulation models (https://www.palmod.de/, last access: 6 May 2020), and to confront these simulations with palaeoclimate data, we have compiled a multi-parameter marine palaeoclimate data synthesis that contains time series spanning 0 to 130 000 years ago. We present the first version of the data product that focuses exclusively on time series for which a robust chronology based on benthic foraminifera δ18O and radiocarbon dating is available. The product contains 896 time series of eight palaeoclimate parameters from 143 individual sites, each associated with rich metadata, age–depth model ensembles, and information to refine and update the chronologies. This version contains 205 time series of benthic foraminifera δ18O; 169 of benthic foraminifera δ13C; 131 of seawater temperature; 174 and 119 of planktonic foraminifera δ18O and δ13C; and 44, 38 and 16 of carbonate, organic carbon and biogenic silica content, respectively. The data product is available in three formats (R, LiPD and netCDF) facilitating use across different software and operating systems and can be downloaded at https://doi.org/10.1594/PANGAEA.908831 (Jonkers et al., 2019). This data descriptor presents our data synthesis strategy and describes the contents and format of the data product in detail. It ends with a set of recommendations for data archiving.