This dataset provides delta-Deuterium data for the Lateglacial sediment sequence retrieved from Lake Hämelsee (Germany) in 2013. Compound-specific hydrogen isotope ratios (expressed as δD) normalized to the Vienna Standard Mean Ocean Water (VSMOW) as well as measurement uncertainties (expressed as SD) are presented against both depth (m) and age (cal yr. BP). The data provides information on the Lateglacial development of local climate dynamics: the plant-wax derived δD signal is typically considered to reflect the hydrogen-isotopic composition of plant leaf water and, by extension, precipitation. We therefore interpret the trends in δD record here as an indicator of past hydrological change (cf Sachse et al., 2012). A total of 167 samples from the Lateglacial section of the core were processed using a Dionex 350 accelerated solvent extraction (ASE) system. Solid phase extraction (SPE) was used to separate the extracts into an aliphatic, aromatic and alcohol/fatty acid fraction. Prior to isotope ratio measurement, the aliphatic fraction was further fractionated on a Pasteur pipette column containing activated AgNO3 (10%) coated silica gel. Compound-specific hydrogen isotope ratios (expressed as δD) were subsequently measured on an isotope ratio mass spectrometer. All δD values are normalized to the Vienna Standard Mean Ocean Water (VSMOW) scale using a linear regression function between measured and certified δD values of a standard mix. We refer to Rach et al. (2020) for further details on the exact analytical setup. All measurements were performed in the laboratories of GeoForschungsZentrum Potsdam.

This dataset provides concentrations of n-alkanes for the Lateglacial sediment sequence retrieved from Lake Hämelsee (Germany) in 2013. Concentrations of n-alkanes (ug/g), the Carbon Preference Index (CPI) and the Average Chain Length C21-C33 (ACL) are all presented against both depth (m) and age (cal yr. BP). The n-alkane concentration data provides information on the Lateglacial dynamics of local plant productivity, whereas the ACL and CPI of the sediment samples were determined to estimate origin and preservation condition. A total of 167 samples from the Lateglacial section of the core were processed using a Dionex 350 accelerated solvent extraction (ASE) system. Solid phase extraction (SPE) was used to separate the extracts into an aliphatic, aromatic and alcohol/fatty acid fraction. Separation was achieved by loading the extracts on activated silica columns and eluting each fraction with hexane, hexane/DCM (1:1 v/v) and DCM/MeOH (9:1 v/v) successively. The aliphatic fraction, containing the n-alkanes, was analyzed by gas chromatography-mass spectrometry (GC/MS). The peak areas for each n-alkane homologue were compared to the peak areas from an internal standard (5α-androstane) and an external n-alkane standard mixture for absolute quantification. We refer to Rach et al. (2020) for further details on the exact analytical setup. All measurements were performed in the laboratories of GeoForschungsZentrum Potsdam.

This dataset provides counts of chironomid head capsules for the Lateglacial sediment sequence retrieved from Lake Hämelsee (Germany) in 2013. Counts per taxon are presented against both depth (m) and age (cal yr. BP), and the total amount of material used for analysis (in g) is provided as well. The chironomid data provides information on Lateglacial ecosystem dynamics and were used to interpret changes in aquatic diversity as well as in local climate conditions. A total of 123 samples from the Lateglacial section of the core were treated with warm KOH (10%) to de-flocculate the material and subsequently rinsed through a sieve with a 100-µm mesh. Chironomid head capsules (HCs) were hand-picked from the residue using a Bogorov sorting tray and mounted on permanent microscope slides using Euparal mounting medium. HCs were identified using Brooks et al. (2007) and the dataset presented here has been matched to the taxonomy of the merged Norwegian/Swiss chironomid-climate calibration dataset. Several samples had low chironomid concentrations and for these we amalgamated adjacent samples (within lithological boundaries) to reach a minimum count sum of 50 head capsules per sample. This process resulted in the final chironomid dataset that is presented here, containing 97 samples. All analyses were performed in the laboratories of the University of Amsterdam, the Netherlands.

This dataset provides counts of diatom valves for the Lateglacial sediment sequence retrieved from Lake Hämelsee (Germany) in 2013. Counts per taxon are presented against both depth (m) and age (cal yr. BP). The diatom data provides information on Lateglacial ecosystem dynamics and the dataset was used to interpret changes in aquatic diversity as well as in palaeolimnological conditions. A total of 78 samples were selected for diatom analysis using 2-5 cm sample intervals throughout the Lateglacial section of the core sequence, with a higher sampling resolution (1 cm intervals) around key transitions. Organic matter was removed from the samples (ca. 0.01 grams dried sediment) by oxidation using 5 ml of H2O2 (30%) and heating in a water bath at 70 °C for 24-28 hrs. Subsequently, a few drops of HCl (50%) were added to remove residual H2O2 and carbonates. Samples were washed by adding distilled water, shaking vigorously, centrifuging at 1200 rpm for 4 minutes, and removing the liquid using a pipette. This process was repeated 5 times, and a few drops of ammonia (NH3) were added to the solution prior to the final wash to prevent clumping of diatoms. Diatom slides were mounted using Naphrax and diatoms were identified using Krammer and Lange-Bertalot (1986–1991) and Camburn and Charles (2000). For several samples the target count sum of 300 diatom valves could not be reached due to low concentrations or poor diatom preservation. Prior to analysis and interpretation, and where possible, neighbouring samples with a low count sum were amalgamated until a count of at least 100 valves was reached; if this was not possible the samples were deleted from our dataset prior to subsequent analysis (note that these samples are still included in the dataset provided here). All analyses were performed in the laboratories of University College London, UK.

This dataset provides Pediastrum data for the Lateglacial sediment sequence retrieved from Lake Hämelsee (Germany) in 2013. Percent-abundances per taxon (%), total count sum per sample (#/ml) and Pediastrum flux (#/cm²/a) are presented against both depth (m) and age (cal yr. BP). The Pediastrum data provides information on Lateglacial ecosystem dynamics and the dataset was used to interpret changes in aquatic diversity as well as in palaeolimnological conditions. A dataset of lateglacial pollen samples from lake Haemelsee (see https://doi.pangaea.de/10.1594/PANGAEA.939693) was additionally analysed for subfossil remains of Pediastrum, where identification of the Pediastrum taxa mainly followed Komárek and Jankovská (2001) with further taxonomic revisions as summarized in Turner et al. (2014). Our final Pediastrum dataset includes 100 samples, as samples with fewer than 25 identified Pediastrum coenobia were excluded from further analyses. Pediastrum concentrations were calculated by comparing the number of Lycopodium spores encountered during pollen analyses to the number of spores added to the sample. All analyses were performed in the laboratories of the Technische Universität Braunschweig, Germany.

This dataset provides geochemical composition data for the Lateglacial sediment sequence retrieved from Lake Hämelsee (Germany) in 2013, determined using an Itrax X-ray fluorescence (XRF) core scanner. Selected geochemical major and minor elements (Ti, Si, Ca, Fe) expressed as counts per second, as elemental ratios, as centered log-ratios (CLR) and as log-ratios are presented against both depth (m) and age (cal yr. BP). The XRF data was used to provide information on LGIT landscape dynamics at lake Hämelsee. The geochemical composition of the sediments was determined on fresh core splits using an Itrax X-ray fluorescence (XRF) core scanner equipped with a Cr tube. Measurements were performed at 200 µm resolution during 20s exposure time per step at 30 kV tube voltage and 40 mA tube current. The analyses were performed in the laboratories of GFZ, Potsdam.

This dataset provides glycerol dialkyl glycerol tetraethers (GDGTs) concentrations for the Lateglacial sediment sequence retrieved from Lake Hämelsee (Germany) in 2013. GDGTs concentrations (ng/g) are presented against both depth (m) and age (cal yr. BP). The GDGTs dataset was used to calculate the GDGT-0/crenarchaeol ratio, which was interpreted to represent lake water oxygenation, which, given the local settings, was likely driven by changes in windiness. Additionally, the GDGT dataset was used to calculate the degree of methylation of 5-methyl brGDGTs (MBT'5me), which can be used to reconstruct past temperature change through translation MBT'5me into mean temperature of the months above freezing. As such, the GDGT data provides information on LGIT climate dynamics at lake Hämelsee. Of the 167 samples used for lipid extraction (see https://doi.pangaea.de/10.1594/PANGAEA.964524), the alcohol/fatty acid fraction of 94 samples was further processed to analyse glycerol dialkyl glycerol tetraethers (GDGTs), which are membrane lipids of certain archaea and bacteria (Schouten et al., 2013). In short, a known amount of internal standard was added to each fraction, which was then redissolved in hexane:isopropanol 99:1 and passed over a 0.45 µm PTFE filter prior to injection on a Agilent 1260 Infinity ultra-high performance liquid chromatograph coupled to an Agilent 6130 single quadrupole mass spectrometer following the settings and elution protocol of Hopmans et al. (2016). A minimum peak area of 3000 and a signal-to-noise ratio of >3 was maintained as detection limit. Quantification of the GDGTs is based on the assumption that the mass spectrometer equally responds to the GDGTs and the internal standard. All analyses were performed in the laboratories of Utrecht University, the Netherlands.

This dataset provides Loss-on-ignition (LOI) data for the Lateglacial sediment sequence retrieved from Lake Hämelsee (Germany) in 2013. LOI values (%) are presented against both depth (m) and age (cal yr. BP). The LOI data was used to provide information on LGIT landscape dynamics at lake Hämelsee. A total of 369 samples were analyzed for LOI, providing a continuous 1-cm-resolution record across the LGIT and early Holocene sections of the HAEM-B record. Subsamples of 1 cm3 were dried in a 105°C oven for 24 hrs before being placed in a furnace at 550 °C for 4 hrs. Loss-on-ignition was calculated by comparing the dry weight of the samples before and after combustion at 550 °C following Heiri et al. (2001) and results are expressed as a percentage. The analyses were performed in the laboratories of Utrecht University, the Netherlands.

This dataset provides the raw pollen counts for the late-glacial sediment sequence retrieved from Lake Haemelsee (Germany) in 2013. The counts are presented against both depth (cm core depth) and time (cal. yr BP) and cover the time interval from ca 15.200 to 10.400 cal yr BP. A total of 106 samples were counted, with higher sampling resolution around the onset and end of the Younger Dryas, and lower sampling resolution elsewhere in the core. The pollen record provides information about both regional vegetation change as well as changes in the within-lake flora. It was produced to inform on the exact age and duration of major palynological transitions during the late-glacial Cores were retrieved from the lake using a 3-m long UWITEC piston corer deployed from a floating coring platform during field work in July 2013. Volumetric samples were obtained from splits of the core and processed in the laboratory (University of Amsterdam, the Netherlands) using standard protocols.

Raw data for the Luttersee pollen dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.