East Siberian ice wedges recording dust transport variability during the Late Pleistocene

Domain: earth_science
Published: 2025-11-10
Editorial outcome: major_revision

Abstract
During the Late Pleistocene, a severely cold and dry climate strengthened dust production across the Northern Hemisphere. Despite many studies examining aridification and dust production, there is a lack of understanding about dust transportation during global climate variability. Long-range transported (LRT) dust can be traced by comparing global geochemical signatures and constraining provenance relationships. Here we report rare earth element abundances and strontium, neodymium, and oxygen isotope compositions of inorganic substances in ice wedges from Batagay and Central Yakutia (Cyuie and Churapcha), which comprise Yedoma deposits that formed in unglaciated Beringia. Distinct geochemical properties reflect differences between local and LRT dust contributions. Particles in the Batagay ice wedges show higher similarities to Chinese aeolian deposits, while those in Central Yakutia indicate stronger local input. These provenance constraints highlight variability in atmospheric circulation transporting dust to the Arctic during the Late Pleistocene, linking climate changes to aerosol distribution.

Introduction
Mineral dust in the atmosphere, one of the key components of the climate system, can be used as an indicator to examine climate change. It is transported by the Earth’s wind regime, affected by both the regional and large-scale climate system1. Dust in proximal regions is mainly carried by near-surface winds via creeping and saltation2,3, while long-range transport (LRT) from distal regions is largely driven by synoptic-scale atmospheric circulation3,4. The frequency and intensity of such LRT events may be modulated by millennial-scale climate oscillations5. Additionally, atmospheric dust directly absorbs and scatters radiation and indirectly modifies the properties of clouds, affecting Earth’s climate systems6,7. Dust radiative forcing also makes an important contribution to polar amplification8. Thus, investigating the provenance, distribution, and transport of dust is crucial to understanding dust-climate linkages and how atmospheric conditions respond to climate change.

During the last glacial period, dust production and deposition were greatly enhanced9,10. Dust is recorded in many deposits, particularly loess, which can incorporate both LRT dust and locally derived material9. Loess is primarily composed of silt-sized particles (2–63μm), but often incorporates a significant fraction finer than 10μm, potentially reflecting background dust transported hundreds to thousands of kilometers by westerlies11,12. Accordingly, loess and loess-like deposits serve as valuable archives of past dust dynamics. Located across central and northern Siberia, Yakutia is one of the major regions where loess is distributed11,13,14, and there is a special type of loess-like deposits called Yedoma (Fig. 1; Supplementary Fig. 1). Yedoma, or ice complex, is a silt-dominated ice-rich syngenetic permafrost with massive ice wedges, which developed across Beringia during the Late Pleistocene11,15,16. Although Yedoma in Alaska (i.e., eastern Beringia) has been considered to be aeolian-processed deposits since ref. 17, the depositional processes of Yedoma in Siberia (i.e., western Beringia) remain debated13,15,16. Because it lies at the interface between major mid-latitude dust sources and the Arctic, understanding the provenance and transport mechanisms of Yedoma source material is crucial for reconstructing past atmospheric dust circulation and its climatic implications.

Syngenetic ice wedges, widely distributed in northeastern Siberia, grew during permafrost formation and accommodated significant amounts of sediment18, recording paleoclimate and paleoenvironment conditions during permafrost development. A substantial portion of the Yedoma deposits has been lost during post-depositional permafrost degradation, changing the permafrost environment since the Pleistocene-Holocene transition19,20. Nevertheless, well-preserved syngenetic ice wedges without thaw evidence are considered to retain original materials and geochemical signatures, which were implemented during Yedoma formation21–23. To elucidate the origin and transport of Yedoma sediments during the Late Pleistocene, we sampled such well-preserved syngenetic ice wedges without any thaw-related disturbance from Batagay (upper ice complex, UIC) and Central Yakutia (Cyuie and Churapcha) (Supplementary Notes; Supplementary Figs. 2, 3; Supplementary Table 1). Formation ages of the ice wedges studied in the middle part of the Batagay UIC (~60–27 ka; ref. 24) fall within the middle to late (mid-late) Marine Isotope Stages (MIS) 3 (~45–30 ka), based on newly available radiocarbon ages (see Methods; Supplementary Notes; Supplementary Table 2), which corresponds to the period before the Last Glacial Maximum (LGM). In contrast, the Central Yakutia ice wedges formed in early to middle MIS 2 (~21–18 ka; refs. 21, 22), representing the LGM period.

In this study, we constrain the provenance and transport pathways of inorganic solid particles preserved in syngenetic ice wedges from Batagay and Central Yakutia by measuring trace element concentrations, particularly rare earth elements (REE), and isotope compositions of Sr, Nd, and O, which have been widely used to trace provenances for various types of materials (e.g., rock, sediment, and dust; refs. 1, 25–27). Formed mainly by snow compaction and hoarfrost accretion22,23, rather than surface water infiltration, our ice wedge samples effectively trap atmospheric input and are expected to preserve atmospheric dust signals. Unlike host sediments, well-preserved ice wedge infill is less affected by redeposition and sediment reworking, and thus can more directly record atmospheric deposition during ice wedge growth. Together, these datasets allow us to evaluate the relative contributions of local versus LRT sources during the mid-late MIS 3 (Batagay) and the LGM (MIS 2; Central Yakutia).

Results
Grain-size distributions and trace element systematics
The possibility of containing the LRT dust in both regions is suggested by the bimodal to polymodal grain-size distributions, indicative of a polygenetic origin (Supplementary Notes; Supplementary Fig. 4; Supplementary Data 1; refs. 12, 28). Alongside a dominant silt-sized peak (10–80μm range), all samples display a secondary mode or shoulder around 1μm, consistent with the fine-grained LRT dust. Because REE, Sr isotope, and quartz oxygen isotope compositions can be grain-size dependent25,26,29, we therefore analyze size-separated fractions (see Methods).

REE concentrations varied across grain-size fractions but did not exhibit any systematic correlation with particle size (Supplementary Fig. 5; Supplementary Data 2). Differences between sample groups are more prominent than those among grain-size fractions, indicating that the REE concentrations are mainly controlled by provenance rather than grain-size effects. To compare the geochemical compositions of all samples and possible source areas (PSAs), Fig. 2 and Supplementary Fig. 6 present selected element ratios, including REE and other trace elements. These data are normalized to post-Archean Australian shale (PAAS; ref. 30). The element ratios used in these binary plots have been suggested as useful particle size-independent provenance tracers25.

The binary plots suggest that our samples represent mixtures of LRT dust from the Chinese sources and locally derived material, with varying proportions (Fig. 2; Supplementary Fig. 6). The Batagay samples overlap closely with the Ordos Plateau (OP) field, suggesting a relatively stronger input from Chinese dust. In contrast, the Central Yakutia samples fall between the fields of the Lena and Yana River suspended particulate matter (SPM) and the northern China aeolian deposits, probably the OP, suggesting a mixture of regional input and distal dust sources. Europium anomalies (Eu/Eu*) also distinguish the two groups (Supplementary Notes; Supplementary Fig. 5): the Batagay samples overlap with the OP to the northern margin of the Tibetan Plateau (NMTP) fields, whereas the Central Yakutia samples align more closely with the Lena and Yana SPM (Fig. 2c, d; Supplementary Fig. 6a–e). In detail, the Lena River SPM systematically shifts toward the Aldan Shield lamproites across all element ratios. The Central Yakutia samples show a similar deviation, trending toward both the Lena River SPM and the Aldan Shield lamproites, likely demonstrating a substantial contribution from this crystalline lithology of the Aldan Shield.

Strontium and neodymium isotopes
The measured 87Sr/86Sr ratios of bulk ice wedge sediments range from 0.715784 to 0.717100 in Batagay and from 0.716610 to 0.717291 in Central Yakutia (Fig. 3; Supplementary Data 3). The fine fractions (<10 and <5μm) show higher ratios, ranging from 0.719567 to 0.722099 in Batagay and from 0.720124 to 0.721181 in Central Yakutia, indicating a grain-size effect with increasing 87Sr/86Sr toward the fine fractions. In contrast, εNd(0) values show little evidence of grain-size effects but display clear regional differences. Bulk εNd(0) values from the Batagay samples (−8.8 to −8.5) are higher than those from the Central Yakutia samples (−18.3 to −16.3), and the fine fractions show the same contrast (−8.2 to −7.9 in Batagay and −14.7 to −14.3 in Central Yakutia), highlighting the distinct provenance signals between the two sites.

The Batagay values appear near the isotope range of the Greenland glacial dust and are plotted between the ranges of Mongolian Gobi Desert (MG), northern boundary of China (NBC), Chinese Loess Plateau (CLP), and the NMTP (Fig. 3). This similarity in radiogenic isotopes suggests that our samples may share a common East Asian provenance with the Greenland glacial dust. Numerous studies have reported that dust in the Greenland ice cores originated from major dust-emitting sources in East Asia (e.g., CLP, MG, and the Taklimakan Desert, TK) during the last glacial period31–33. Although dust of European origin has also been reported in Greenland, and Sr-Nd isotopes alone are insufficient to distinguish between European and Asian sources34, geographical distance makes it more plausible that atmospheric dust deposited in our study area originated from East Asia.

Bulk Central Yakutia samples overlap with the isotopic range of Alaskan loess, and the εNd(0) values overlap with those of Aldan Shield lamproites (Fig. 3). Although direct comparison of Sr isotopes is complicated by grain-size effects and by the use of whole-rock lamproite values26,35, the εNd(0) overlap suggests a contribution from the Aldan Shield-derived material. The more radiogenic 87Sr/86Sr in the Central Yakutia samples relative to the lamproites can be attributed to grain-size partitioning26. However, the fine fractions (<10 and <5μm) shift for both Sr and Nd isotopes toward the fields of the Eastern Qinling Mountains (EQLM) and OP, suggesting additional contributions of Chinese dust, consistent with mixing signatures inferred from REE ratios (Fig. 2).

Although the reported 87Sr/86Sr values for the Lena and Yana River SPM (0.716624 to 0.717728 for the Lena; 0.713647 to 0.716892 for the Yana and its tributary; ref. 36) are similar to those of our samples, Nd isotopes for these rivers are scarce. We alternatively compare our dataset with the Laptev Sea sediments (LSS) and northeastern (NE) Siberian loess as more integrative local references (Fig. 3). The LSS cannot be regarded as a single definitive local endmember, because the LSS represents a mixture of sediments derived from diverse sources, including coastal erosion and river discharge, and because riverine SPM draining limited watersheds can have different chemical compositions37,38. Nonetheless, the isotopic similarity between LSS and all samples suggests that local sources likely contributed to the ice wedge sediments. Similarly, NE Siberian loess exhibits Sr isotopes comparable to our samples at equivalent size fractions (<5μm). However, NE Siberian loess shows Nd isotope compositions distinct from the samples. This εNd(0) discrepancy indicates that the Nd systematics require additional components, consistent with mixing between local lithologies and LRT dust. Indeed, all samples fall within the mixing field defined by several PSAs (Fig. 3b). The Batagay samples cannot be explained solely by local lithologies such as the Kharaulakh-Suordakh volcanic rocks or Aldan Shield lamproites. Because those reference values are based on whole-rock measurements and therefore not directly comparable to the fine sediment fractions, we treat them as bounding constraints on the local compositional range. The Batagay values are consistent with mixing between a set of hypothetical local endmembers (reflecting Kharaulakh-Suordakh and Aldan Shield contributions) and the OP-NMTP mixing endmembers (red dotted lines in Fig. 3b). For Central Yakutia, mixing trajectories between the OP-NMTP mixing endmembers and a local endmember defined by the bulk samples can explain the observed shift toward finer fractions (blue dotted lines in Fig. 3b). The bulk Central Yakutia compositions are taken as an approximation of the local source, showing Aldan Shield-like εNd(0) values and elevated 87Sr/86Sr compared to lamproites. Taken together, these results suggest that both study sites may contain LRT dust from the OP and NMTP in addition to local material. This interpretation is broadly consistent with the REE-based evidence (Fig. 2), which also points to contributions from Chinese PSAs. We note, however, that REE and Sr-Nd isotope signatures can be influenced by distinct grain-size and mineralogical fractions, which may account for the minor discrepancies observed between the two provenance signals. The REE data suggest OP as the dominant source (Fig. 2), whereas the Sr-Nd isotopes imply mixing with additional components (Fig. 3).

Quartz oxygen isotopes
Oxygen isotope compositions of quartz grains are effective in differentiating distinct provenances in well-mixed aeolian dust1. Since δ18O values of aeolian quartz are influenced by grain-size effects with low-temperature microcrystalline quartz29, we report grain-by-grain isotopic compositions subdivided by grain-size to avoid such effects (see Methods; Fig. 4; Supplementary Data 4). The δ18O (vs V-SMOW) distributions of all grain-size fractions are generally characterized by two dominant isotope ranges, around +10‰ and +15‰ (Fig. 4). The overall distributions differ between Batagay and Central Yakutia, and these differences are confirmed by statistical analyses (see Fig. 4 caption). For three coarser fractions (>32μm), the Batagay samples show relatively wide peak areas from +10 to +20‰, while the Central Yakutia samples have primary peaks at +10‰ and secondary peaks around +15‰. The finest fractions (<32µm) exhibit broad distributions at all sites, suggesting the mixing of various grain provenances. In particular, the dominant peak areas for the finest fraction of the Batagay samples shift toward values around +15‰, indicating distinct source contributions compared with the Central Yakutia samples.

The main +10‰ peaks of the measured δ18O values in Fig. 4 are attributed to the local influx of granitic or metamorphic components. The Batagay sampling site is located in the Yana River basin along the Verkhoyansk Range, where granitoid intrusions are common in the central part of the Verkhoyansk-Kolyma orogen (Supplementary Fig. 1; ref. 39). Through glacial erosion or river discharge, sediments from the Verkhoyansk Mountains could contain significant amounts of quartz grains with δ18O values of approximately +10‰, which may have been generated by weathering of granitoid intrusions. Similarly, in the Lena and Aldan River basins, where the Cyuie and Churapcha sampling sites are located, glaciogenic sediments and morainic materials from the Verkhoyansk Mountains during the Pleistocene are common40. Besides, the Lena River flows from the southern part of the Siberian Platform consisting of Proterozoic metamorphic rocks and granitoids41, and the Aldan River originates in the Aldan Shield which comprises Archaean metamorphic series40. Therefore, the primary sources of Lena and Aldan Rivers are crystalline rocks of metamorphic origins, may comprising the δ18O values of +10‰, which is also consistent with the radiogenic 87Sr/86Sr and εNd(0) signatures observed in the Central Yakutia samples.

The different peaks of δ18O values in the sedimentary component range of approximately +15‰ seen in Fig. 4 could be contributed by both local sources and LRT dust. The basement of central and northern Yakutia is mostly Mesozoic sedimentary rocks and Late Paleozoic and Mesozoic folded sediments, respectively (Supplementary Fig. 1; ref. 40). Either glacial erosion of local bedrock or aeolian transport like saltation from local sediments can provide a basis for δ18O values near +15‰. The sedimentary components also likely contain LRT quartz from the Chinese arid regions, as previously suggested by REE and Sr-Nd isotope systematics. In this regard, the ranges of δ18O values taking into account particle sizes from the MG (+15.1 to 17.3‰ for <16µm; +12.6 to 15.1‰ for 16−63µm) and the OP and NMTP (+16.1 to 18.5‰ for <16µm; +14.0 to 17.0‰ for 16−63µm) as reported in ref. 27 overlap with the range in which peaks for sedimentary components appear in the samples. Notably, the δ18O distribution of the Batagay samples has a prominent peak in this range (Fig. 4), suggesting that LRT dust may have contributed particularly significantly from the Chinese arid regions to Batagay during the mid-late MIS 3. In addition, for the Batagay samples, the dominant δ18O peak near +15‰ is more pronounced in the finer fractions of quartz particles than in the coarser fractions (Fig. 4d). This may reflect a larger proportion of LRT dust in the finer fractions. The contrasting proportions of +15‰ peaks between the Batagay and Central Yakutia samples likely reflect different contributions of LRT versus local material, with the Batagay distribution showing a stronger LRT component and the Central Yakutia distributions retaining more local input, consistent with the stronger local signatures in the Central Yakutia samples inferred from REE ratios (Fig. 2) and Sr-Nd isotopes (Fig. 3).

Methods
Pretreatment
Bulk ice wedge samples were melted and oven-dried at about 40°C to extract only sediment fractions. The extracted sediment samples were sequentially pretreated with 1M HCl and 17.5% H2O2 to remove acid-soluble minerals (e.g., carbonates) and organic matter, respectively. After the sample settled from the suspension, the supernatant was removed by pipette and 17.5% H2O2 solution was added again until all organic material was removed. The resulting inorganic residue was rinsed three times with Milli-Q water and oven-dried at approximately 60°C. Each sample was divided into four portions for analyses of particle size distribution, trace elements, and radiogenic and oxygen isotopes.

Grain-size distribution
After removing acid-soluble minerals and organic materials, samples were dispersed in distilled water for particle size analysis. Measurements were performed using Mastersizer 3000 Particle Size Analyzer (Malvern Panalytical) at the Cooperative Laboratory Center, Pukyong National University, Republic of Korea. Based on laser diffraction technique, this instrument has a measurement range of 0.01 to 3500µm with 100 size classes. The grain-size distributions were calculated by the Mie scattering theory.

Trace element analyses
Trace element concentrations were analyzed for several grain-size fractions (bulk, <125μm, 63−125μm, <63μm, 32−63μm, and <32μm) obtained by dry sieving, when sufficient sample material was available. Approximately 0.1 g of each sample was weighed and dissolved in a mixture of 5 ml HF, 4 ml HNO3, and 1 ml HClO4 in Teflon digestion vessels at 185°C for 24 h. After complete dissolution, the decomposed samples were evaporated to dryness on a hot plate, re-dissolved in 3% HNO3, and diluted appropriately depending on the target elements. REE and trace element concentrations were determined using an iCAP Q (Thermo Fisher Scientific) inductively coupled plasma mass spectrometer (ICP-MS) at the Korea Institute of Ocean Science and Technology (KIOST), Republic of Korea. Two certified reference materials (CRMs) MESS-4 (marine sediment) and BCR-667 (estuarine sediment) were analyzed alongside the samples to validate the accuracy. The results for the CRMs are summarized in Supplementary Table 3. For MESS-4, recoveries of certified elements are within 11% of the certified values, with relative standard deviations (RSDs) below 8.2%. For BCR-667, recoveries of certified elements are within 8.9% of the certified values, with RSDs below 1.9%.

Sr and Nd isotope analyses
Sr and Nd isotope analyses were conducted on nine bulk samples, three <10µm fractions, and three <5µm fractions using a TRITON plus (Thermo Fisher Scientific) thermal ionization mass spectrometer (TIMS) at Korea Polar Research Institute (KOPRI), Republic of Korea. The <10µm and <5µm fractions were separated by gravity sedimentation based on Stokes’ Law and subsequently recovered by centrifugation. Approximately 30 mg of each sample was dissolved in a mixture of 2 ml HF, 1 ml HNO3 and 0.1 ml HClO4 in closed Teflon vials at 120°C for 3 to 4 days. Sr was separated using quartz columns (AG 50W-X8, #100-200) with 2.5 N HCl and 6 N HCl and then loaded onto Re filaments with 1M H3PO4. Nd was extracted by quartz columns (AG 50W-X8, #200-400) using DIW and 0.2 M HIBA (α-Hydroxyisobutyric acid) solution, and loaded onto Re filaments with 0.1M H3PO4. For the bulk samples, procedural blanks were <110 pg for Sr and <60 pg for Nd. Reproducibility and accuracy were assessed by analyzing the international reference materials NBS-987 for Sr and JNdi-1 for Nd, which were treated as unknowns. Long-term measurements yielded mean values of 87Sr/86Sr = 0.710256 ± 0.000006 (2σ, n=15) for NBS-987 and 143Nd/144Nd = 0.512122 ± 0.000005 (2σ, n=15) for JNdi-1. Mass fractionation during measurement was corrected by internal normalization to 86Sr/88Sr = 0.1194 and 146Nd/144Nd = 0.7219, respectively. During the analyses of fine fractions (<10 and <5μm), procedural blanks were <41 pg for Sr and <43 pg for Nd. Repeated measurements yielded mean values of 87Sr/86Sr = 0.710252 ± 0.000006 (2σ, n=8) for NBS-987 and 143Nd/144Nd = 0.512119 ± 0.000004 (2σ, n=8) for JNdi-1. Each Sr analysis consisted of 100 measurement cycles per run, and each Nd analysis consisted of 140 cycles per run.

Oxygen isotope analysis for quartz
To measure oxygen isotopic composition of quartz grains, the samples reacted with a mixture of concentrated H2SiF6 and 10% HCl until all clay mineral was removed and only quartz grains remained. Each sample was divided into four size fractions (>125, 63−125, 32−63 and <32µm) by dry sieving. Quartz grains of >125, 63−125 and 32−63µm fractions were individually hand-picked, mounted in 1-inch epoxy and polished. Due to difficulties in sample preparation, one representative sample from each site was selected to measure the finest fractions. The finest fractions (<32μm) were mounted in 6-mm diameter acrylic resin to achieve greater flatness during polishing. NBS-28 standards were also prepared with 6-mm diameter resin mount in the same way. The polished acrylic resin mounts were embedded in an indium-filled 1-inch Al disc for higher electrical conductivity. The sample and standard mounts were embedded in the same disc, allowing measurement in the same session. All sample mounts were finally coated with gold prior to measurements.

Oxygen isotope compositions of individual quartz grains were determined by a CAMECA IMS 1300-HR3 multicollector-equipped ion microprobe at Korea Basic Science Institute (KBSI), Republic of Korea. For the analysis of the coarser grains (>32µm), a 20 μm Cs+ primary beam of 2.5 to 3.0 nA accelerated at 10 kV. A 10 keV electron gun of 150 μm in diameter was applied for electrostatic charge compensation. Negative secondary ions were extracted with a potential of −10 kV. The field aperture size was 3000×3000μm. A mass resolving power (MRP) was ~5000 at 10% peak height. Both 16O and 18O were simultaneously collected in two Faraday cup detectors fitted with 1010 Ω (L’2) and 1011 Ω (H’2) resistors, respectively. Each analysis consisted of pre-sputtering (80 to 100 s), automatic beam centering to the field and contrast apertures, mass calibration for 16O, and measurements (20 cycles of 4 s). The instrumental mass fractionation (IMF) was corrected using NBS-28 quartz (δ18O V-SMOW = 9.6‰). Under these conditions, the 16O- count rate was typically ~1×109 cps/nA. An internal precision (standard error of the mean of the cycles in a single measurement; 2σ) of ±0.1 to 0.2‰ is achieved by NBS-28 quartz standards. The external reproducibility (standard deviation between several spots) was about ±0.3‰.

The finest fractions (<32µm) were also measured by in-situ spot analysis, with a 5 μm Cs+ beam of ~100 pA. 16O and 18O were detected with a Faraday cup and electron multiplier, respectively. Each analysis consisted of pre-sputtering (80 to 100 s), automatic beam centering, mass calibration, and measurements (20 cycles of 4 s). Other instrumental operation parameters were the same as the analyses of the three coarser fractions (>32µm). Under these conditions, the 16O- count rate was typically ~1×108 cps/nA. The internal precision (2σ) was ±0.3 to 0.4‰ by NBS-28 quartz standards. The external reproducibility was about ±0.4‰.

Radiocarbon age dating
After melting of ice wedge samples, we freeze-dried the samples and screened the sediments originally included in the wedge ice using a stereomicroscope. Organic macro remains were picked. Radiocarbon dating was performed at the MICADAS facility at Alfred Wegener Institute (AWI) Bremerhaven, Germany53. Plant remains were cleaned with acid-base-acid treatment as described in ref. 53. The samples were subsequently combusted in an elemental analyzer (Elementar vario Isotope). Produced CO2 was further graphitized utilizing the automated graphitization system (AGE-3; Ionplus AG; ref. 54) and radiocarbon measurements were conducted. Radiocarbon data were normalized and blank corrected against size-matched standard (NIST Oxalic Acid II, NIST SRM 4990C) and 14C-free blank material (Phthalic Acid; Sigma Aldrich 320064), and data integrity was checked against the processing wood standard IAEA-C5 and lab-internal sediment standards.

All radiocarbon results were reported as F14C and conventional radiocarbon ages (Supplementary Table 2). We used the IntCal20 dataset (ref. 55) to calibrate the ages with CALIB Radiocarbon Calibration version 8.2 (ref. 56), which are given as calibrated years before present (cal yr BP). We also calibrated non-finite ages for comparative reasons. To provide a minimum age estimate, a theoretical standard deviation of 1000 radiocarbon years was computed in CALIB following ref. 57. We have rounded all results with standard deviations in the radiocarbon ages greater than 50 yr to the nearest 10 yr.

Calculation for Sr-Nd mixing curves
Binary mixing trajectories in Fig. 3 between PSA endmembers were calculated using average Sr and Nd isotope ratios and elemental concentrations of the respective endmembers. The mixed isotopic ratio Rmix was obtained as:

Rmix = (fA CA RA + fB CB RB) / (fA CA + fB CB) (1)

where R is the isotope ratio, C is the element concentration (Sr or Nd), and f is the mixing fraction of endmembers A and B.

Oxygen isotope distributions
The δ18O distributions of quartz grains were evaluated using Gaussian kernel density estimation (KDE) with bandwidth h determined by the normal reference rule (h=σ·(4/(3n))1/5), where σ is the standard deviation and n is the number of measurements; ref. 58). KDEs were calculated using Microsoft Excel (Microsoft Ltd., USA) with the Real Statistics Resource Pack (Release 8.9.1; ref. 59). Group differences were assessed for each size fraction (>125, 63−125, 32−63, and <32µm) using three statistical approaches: Welch t-test, Mann–Whitney U test, and permutation test.

Ice-sheet reconstructions
To illustrate the ice-sheet extent in Fig. 1, we used published reconstructions of the Eurasian Ice Sheet Complex (EISC), Greenland Ice Sheet (GIS), Laurentide Ice Sheet (LIS), and Cordilleran Ice Sheet (CIS) from refs. 60, 61. Within the MIS 3 reconstructions, only the 40 ka time slice shows a more extensive ice cover in eastern Siberia because it incorporates a maximum Quaternary ice-extent template to match empirical evidence from the Kamchatka Peninsula60. This likely overestimates the ice extent in the Verkhoyansk region, where field evidence indicates limited local glaciation62–64. To avoid misinterpretation, the 40 ka reconstruction was excluded, and the MIS 3 ice extent is illustrated using the 30, 35, and 45 ka time slices.

Data availability
All data generated in this study are provided in the Supplementary Information and the Source Data files.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "The paper by Kim et al. deals with the dust production and the routes of long-range transported (LRT) dust be jet streams during the Late Pleistocene in the Northern Hemisphere. The study reconstructed and compared the chemical properties of dust particles worldwide and from two Yedoma sites with ice wedges in eastern Siberia (Batagay and Central Yakutia) by measuring rare earth element (REE) abundances, strontium, neodymium, and oxygen isotope compositions of inorganic substances.\nThe authors concluded that the Batagay and Central Yakutia samples have different geochemical properties due to differences in local and LRT mechanisms. The Batagay ice wedges show higher similarities to Chinese aeolian deposits and Greenland glacial dust while the Central Yakutia ice wedges are more representative of local materials.\nThis is a valuable contribution to the international community. It can be published after major revisions.\n1) First, it should be clarified what is loess (or loess-like sediments) in the Yedoma formations and what is long-range transport (LRT) of dust. Both should have different grain sizes. The loess-like deposits of the so-called Yedoma consist of s silt-sized particles, but the LRT dust contains mostly smaller particles. Quartz and also coarse grained sized particles may also be local material or even recycled from older material in the area. The trapping of dust (and silt), for example by vegetation or biocrusts is also an important factor in the development of loess landscapes. Some of the material may have been temporarily deposited and then transported again. There may also be some fluvial or colluvial input to the sections. However, some signals in REE or Sr isotopes are obvious for LRT.\n2) The chronological framework is very important for this study and its conclusions, and in my opinion, this needs to be improved. The authors have separated pre- and late Glacial Maximum for the Batagay and Yakutia ice wedges - but the chronological framework is quite uncertain, and not described in detail. For example, Murton et al. (2022) show quite a lot of uncertainty in the dating.\n3) There is a local ice cap on the Verkhoyansk Mountains between Batagay and Central Yakutia that is out of phase with the global Last Glacial Maximum. This is also true for Pleistocene ice extent in Alaska, see e.g. Stauch and Gualtier (1–3). They have a maximum extent in MIS 4 or even just before. This shows that humidity is the main driver of ice and that local ice caps can also influence at least the local wind fields.\nIn addition, there were so many climatic fluctuations during the last glacial cycle that this should be clarified before drawing a big picture from the Chinese desert to Greenland based on such a rough chronological framework. For example, the aforementioned LRT of dust from China to Siberia needs to be proven and the period in which this direction occurred needs to be established. Without a time frame, the conclusion remains highly speculative. Provide some age constraints for your samples and also from the surround areas.\nIn my opinion, this should be also confirmed by paleoclimatic models. The North Atlantic and the distribution of the Pleistocene ice influenced the jet stream. There are local wind fields over the ice sheets, and there were easterly winds in front of the ice caps. There are quite a lot of climatic fluctuations during the last glacial cycle and therefore quite a lot of fluctuations in the direction of the jet stream. The Feno-Scandinavian ice sheet is important for the climate in Asia. In particular, during the global Last Glacial Maximum, this ice sheet, at its largest extent, blocked moist air masses to the east during its largest extent. There are eastly winds in front of the ice sheet which are also responsible for the dust and loess distribution, please see the model of Schaffernicht et al. (4), who also discussed the dust distribution in front of the European ice sheet during the LGM. Local ice can also have an influence on wind direction and especially on the transport of silt-size particles, as shown in many papers.\n4) Statistics:\nThe biplots in Figures 2 and 3 show only the overlap between the REE or isotope ratios of the samples with those of the other proxies. In order to provide a more reliable distinction, a statistical analysis with respect to the differences between samples and proxies can improve the interpretation to which group the samples are assigned. Another aspect which to consider is whether the samples and the data from the proxies are of the same age.\nFigure 4 is not convincing and also on line 169 they mentioned an overlap. I think they should test the differences.\nSome other questions remain open:\nIs there any evidence to rule out repeated deposition and transport and a mixing of the sampled material?\n5) Figures:\nI did not understand figure 1: is the legend for LGM, MIS 3 and MIS 4 for the extent of the ice? If so, the figure is wrong. See my comments above, the ice in Siberia is related to the incoming moisture from the west, which is blocked during MIS 4 and especially doing MIS 2. The maximum extent in the interstadial of the last glacial cycle (MIS 3) in older literature is based on radiocarbon ages and these are all minimum ages. The ice in eastern Siberia has its maximum extent in MIS 4 or even earlier, because there is less moisture in that area afterwards due to the blocking moist air masses by the Feno- Scandinavian ice sheet.\nFrank Lehmkuhl, 6.3.2025\nReferences\n1. Diekmann, B. et al. Late Quaternary lake dynamics in the Verkhoyansk Mountains of Eastern Siberia: implications for climate and glaciation history. Polarforschung 86, 97–110 (2017).\n2. Stauch, G. & Gualtieri, L. Late Quaternary glaciations in northeastern Russia. Journal of Quaternary Science: Published for the Quaternary Research Association 23, 545–558 (2008).\n3. Stauch, G. & Lehmkuhl, F. Quaternary glaciations in the Verkhoyansk Mountains, northeast Siberia. Quaternary Research 74, 145–155 (2010).\n4. Schaffernicht, E. J., Ludwig, P. & Shao, Y. Linkage between Dust Cycle and Loess of the Last Glacial Maximum in Europe. https://www.atmos-chem-phys-discuss.net/acp-2019-693/ (2019) doi:10.5194/acp-2019-693.", "reviewer_2": "The manuscript \"East Siberian ice wedges recording the polar jet stream during the Late Pleistocene\" by Kim et al. studies the provenance of mineral dust in the Late Pleistocene ice wedges collected from Siberia.\nMy report is very short, as I find the manuscript well structured, easy to follow, and the results and conclusions well justified. I think the manuscript is suitable for publication and would be of interest to many. I only have a few notes and corrections for the authors below.\nKey results: The results indicate a significant contribution from distant Asian sources for the pre-LGM dust in the Siberian ice wedges, while the late LGM dust is more locally sourced. The authors attribute these differences to changes in the polar jet stream pathway patterns that themselves are linked to changes in the extent of ice sheets.\nValidity:\nThe manuscript uses multiple methods to infer the provenance of the dust, making the provenance analysis more robust.\nThe data obtained by different methods are mostly consistent with each other and point to the conclusions presented in the manuscript. The data are also consistent with previous studies, and the compilation of data from previous studies is extensive.\nSignificance:\nI think the results of this study are significant, not only because of the samples, which may be unavailable in the future if they melt, but also because the results offer important new insights to the links between dust and climate and will be of interest to many in the fields of dust and paleoclimate research and beyond.\nData and methodology:\nOnly the ICP-MS/AES methods need more details on the analytical parameters and information on the standards used.\nThe Sm values of the Lena and Yana SPM samples seem to be incorrectly reported in Supplementary Table 2. Please correct.\nAnalytical approach:\nWhile a PCA may have been useful in presenting the REE/trace element data in a more robust way, I do not think it is absolutely necessary, since the main features are already evident from the existing figures.\nI would, however, have liked to see more plots on different trace elements (possibly in the supplementary information), for example Eu/Eu*, Y/∑REE, Y/Tb, Y/La, as these are also used by the cited paper of Ferrat et al. (2011).\nSuggested improvements:\nFig. 3. The grain size fraction that each dataset represents would be good to include in the figure, as the Sr isotopes can be influenced by the grain size. I would also like to hear what are the authors’ thoughts on why the Batagay values are not close to OP or EQLM if they are the main sources based on REE (Fig.2)?\nWhile I do not disagree with the conclusions, the similarity of Greenlandic and Alaskan dust to the samples of this study are only based on the Sr-Nd isotopes. For this reason, I would add a bit of uncertainty to the conclusions about these regions. Especially since in Greenland, the Sr-Nd isotopes have not been enough to discriminate the European and Asian dust (Ujvari et al. 2015 – cited in the manuscript).\nLines 225-227: It would be nice to explain in a bit more detail why the jet stream responses to the ice sheet changes in the way that is suggested (for those who are not familiar with the atmospheric aspects of the study). So what are the mechanisms behind the changes in the jet stream pathways?\nClarity and context: The manuscript is well structured and clearly presented.\nReferences: References to previous research are appropriate and encompassing.\nMy expertise: I am not very familiar with Yedoma or permafrost deposits in general (have not worked with those).", "reviewer_3": "Review of Kim et al Nature Communications\nApril 2025\nKim and coauthors present geochemical provenance data on Yedoma sediments from two sites in Siberia. The data include Sr-Nd isotopes and REE, presumably on the bulk fraction, and O isotopes on individual quartz grains split into several size fractions. The data are used to reconstruct the position of the northern branch of the polar jet during the LGM.\nThe writing is clear and the paper is well-organized with nice-looking figures. Overall, the ice wedges represent an interesting paleoclimate archive that deserves exploration. However, we have some serious concerns with the data and their interpretation, and do not consider the conclusions to be supported by the data.\nRegarding the provenance data, the paper lacks sufficient characterization of the local source area geochemistry, particularly for Nd. The Laptev Sea sediments (LSS) that the authors use in place of local sediment compositions actually plot between the Batagay and Central Yakutia sites, suggesting that the LSS may reflect mixing of local materials that are simply not represented in Fig. 3. Without true characterization of the Beringia potential dust source composition, it is not possible to estimate the inputs of local vs LRT dust from Chinese deserts.\nFurther, we are not convinced that the sites, particularly Central Yakutia, are receiving dust from Chinese deserts. If they were, we would expect to see compositions that reflect mixing of local and long-range-transported (LRT) end-members. Instead, the Sr-Nd isotope compositions of the sites are both tightly clustered, which is more indicative of input from a single source. It’s possible that the Batagay samples follow a mixing trend between two end-members, with one of them being Chinese desert material. However, the blue points in Fig. 3 really do not appear to be following a mixing trend. Certainly if transport were occurring from Chinese deserts over both sites and onward to Greenland, the data points should follow the same mixing curve – which they clearly do not.\nIn addition, there are several important analytical details that are missing. One is the size distribution of the Yedoma silts used for Sr-Nd analysis. Sr isotopes are known to have a grain size effect (e.g. Biscaye and Dasch, 1971; Grousset and Biscaye, 2005; Gaiero, 2007); thus, it is important to compare apples-to-apples size fractions among different studies. In the case of LRT dust, scientists typically analyze the fine fraction (<5 um). At the very least, even if the <5 um fraction was not isolated in this study, the measured grain size fraction used for the isotope analyses needs to be stated. Based on Extended Data Fig. 5, it appears that the silts are quite coarse (10s to 100s of µm diameter) – so isotopic analysis of the bulk size fraction is not directly comparable to other fine-fraction data such as the dust from Greenland ice cores.\nThe Sr and Nd isotopes were run with isotopic reference materials but it is unclear whether they were used both as bracketing standards to correct the isotope ratios and as ‘unknowns’ to assess accuracy of the analyses. Given the numbers analyzed for NBS-987 (n = 100) and JNdi-1 (n = 140), it seems as though these are bracketing standards – in which case, additional reference materials should be reported to provide an independent check on the accuracy of the isotope ratios.\nIn addition to source area geochemistry, the inference that Beringia was a source of high-latitude dust in the past would be supported better through some mapped deposits of potential source sediments. What is the geomorphic evidence for dust generation in this region? Are there maps of glacial extent? Outwash plains?\nThe quartz O isotope data are interesting, in that several of the curves are bimodal, suggesting inputs from multiple sources. The interpretation related to these data would be strengthened by inclusion of comparable data on the potential source regions (e.g. Beringia and Asian deserts) included in the figure, rather than just in the text. Ideally these would be plotted against another provenance tracer (e.g. bivariate plot) and be supported by mixing calculations. The interpretation provided on Line 175 – that both >32 and <32 sediments are contributed by LRT of Chinese dust – is implausible. Considering that local sources can account for the oxygen isotope values in the coarser fraction (Line 160), it does not make sense that all this relatively coarse silt would have come thousands of km from China rather than from local sediments. We think in this case, the most parsimonious interpretation needs to be made rather than basing the interpretation on rare exceptions in the literature of long-distance coarse particle transport.\nLikewise, the REE data in Extended Data Figure 4 are a helpful addition, but could be leveraged toward the interpretation more effectively by including a panel that directly compares the patterns of the different regions. We would advocate for further normalizing samples to a single element, e.g. Yb or Lu, to more effectively compare the patterns. By eyeball, the data in panels a and b actually look more similar to panel d than to panel c, supporting a local source for the Yedoma silts. Figure 2 in the main text helps with these comparisons, but we are not convinced that the Lena and Yana sediments fully characterize the local dust source region, given the older bedrock to the south, shown in Extended Data Figure 1, which would provide sediment with more negative εNd values, as shown by the Central Yakutia sites in Fig. 3.\nRegarding the potential source regions shown on Fig. 3, the African sources are not relevant based on geography and atmospheric transport patterns. We would recommend removing them from the figure and discussion. In addition, the “Alaska” field reflects only the Fairbanks loess data of Biscaye et al. 1997 and not more recent data from southcentral Alaska that characterize the active Copper River dust source and related glaciofluvial sources (Koffman et al., 2022). It may be worth including these data for a more complete representation of Alaska sources.\nFinally, while a Chinese desert source *could* be a plausible end-member for Batagay dust, it does not follow that the jet itself had to have gone directly over the site. There is plenty of dust transport that occurs not in the jet, for example through synoptic-scale systems. For instance, extratropical cyclones transport dust from Patagonia to Antarctica, including onto the East Antarctic plateau – yet the Southern Hemisphere polar jet maintains an annular structure and does not shift directly over the ice sheet to deposit this dust.\nFurthermore, regarding the position of the jet: the authors should reconsider the conceptual models of the jet stream presented in Fig. 1 and Extended Data Fig. 6. Although some synoptic weather patterns can produce large meridional waves propagating toward (or even across) the North Pole, it seems implausible that a distinct polar jet stream from the Laptev Sea to Greenland would represent mean climatology. To inform these schematic depictions, we recommend examining mean wind climatologies from existing LGM climate model simulations (e.g., Brady et al., 2013), and perhaps also modern reanalysis products such as ERA5. Furthermore, the configuration of the polar and subtropical jet streams has large seasonality, and it could be beneficial to present both summer and winter circulation climatologies instead of annual.\nReferences Cited:\nBiscaye, P. E., & Dasch, E. J. (1971). The rubidium, strontium, strontium-isotope system in deep-sea sediments: Argentine Basin. Journal of Geophysical Research, 76(21), 5087-5096.\nBiscaye, P. E., Grousset, F. E., Revel, M., Van der Gaast, S., Zielinski, G. A., Vaars, A., & Kukla, G. (1997). Asian provenance of glacial dust (stage 2) in the Greenland Ice Sheet Project 2 ice core, Summit, Greenland. Journal of Geophysical Research, 102(C12), 26,765-726,781.\nBrady, E.C., Otto-Bliesner, B.L., Kay J.E., and Rosenbloom, N. (2013). Sensitivity to\nGlacial Forcing in the CCSM4. Journal of Climate 26, 1901–1925.\nhttps://doi.org/10.1175/JCLI-D-11-00416.1\nGaiero, D. M. (2007). Dust provenance in Antarctic ice during glacial periods: From where in southern South America? Geophysical Research Letters, 34(17).\nGrousset, F. E., & Biscaye, P. E. (2005). Tracing dust sources and transport patterns using Sr, Nd and Pb isotopes. Chemical Geology, 222, 149-167.\nKoffman, B. G., Saylor, P., Zhong, R., Sethares, L., Yoder, M. F., Hanschka, L., . . . Osterberg, E. C. (2022). Provenance of Anthropogenic Pb and Atmospheric Dust to Northwestern North America. Environmental Science & Technology, 56(18), 13107-13118. doi:10.1021/acs.est.2c03767", "reviewer_4": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts."}, "author_response": "We sincerely appreciate all reviewers for their thoughtful and constructive comments, which\ngreatly helped us to improve our manuscript. We provide a point-by-point response to each\ncomment below (responses are in orange).\nREVIEWER COMMENTS\nReviewer #1 (Remarks to the Author):\nThe paper by Kim et al. deals with the dust production and the routes of long-range transported\n(LRT) dust be jet streams during the Late Pleistocene in the Northern Hemisphere. The study\nreconstructed and compared the chemical properties of dust particles worldwide and from two\nYedoma sites with ice wedges in eastern Siberia (Batagay and Central Yakutia) by measuring\nrare earth element (REE) abundances, strontium, neodymium, and oxygen isotope\ncompositions of inorganic substances.\nThe authors concluded that the Batagay and Central Yakutia samples have different\ngeochemical properties due to differences in local and LRT mechanisms. The Batagay ice\nwedges show higher similarities to Chinese aeolian deposits and Greenland glacial dust while\nthe Central Yakutia ice wedges are more representative of local materials.\nThis is a valuable contribution to the international community. It can be published after major\nrevisions.\nThank you for the thorough summary, helpful comments and positive feedback to signify this\nstudy.\n1) First, it should be clarified what is loess (or loess-like sediments) in the Yedoma formations\nand what is long-range transport (LRT) of dust. Both should have different grain sizes. The\nloess-like deposits of the so-called Yedoma consist of silt-sized particles, but the LRT dust\ncontains mostly smaller particles. Quartz and also coarse grained sized particles may also be\nlocal material or even recycled from older material in the area. The trapping of dust (and silt),\nfor example by vegetation or biocrusts is also an important factor in the development of loess\nlandscapes. Some of the material may have been temporarily deposited and then transported\nagain. There may also be some fluvial or colluvial input to the sections. However, some signals\nin REE or Sr isotopes are obvious for LRT.\n1-1. We agree that clearly distinguishing between loess (or loess-like sediments) and LRT dust\nis essential. Yedoma consists predominantly of silt-sized particles deposited by mixed\nsedimentary processes (e.g., aeolian, fluvial, and slope-derived input) during syngenetic ice\nwedge growth. In contrast, LRT dust consists of finer particles (typically <10 or <5 μm)\ntransported long distances in the mid- to upper troposphere. Although Yedoma is generally silt-\ndominated, our grain-size data show a secondary mode around 1 μm (Supplementary Fig. 4),\nwhich we interpret as a fine-grained LRT component. These distinctions have been clarified in\nthe revised Introduction (Lines 48-50) and Results (Lines 93-95).\nCoarser particles, including quartz, are plausibly derived from local recycling or short-range\ntransport, as you note. This interpretation is consistent with the isotope data, which vary\nsystematically with grain size. Sr-Nd isotope compositions suggest mixing between local and\nLRT sources, while fine fractions (<10 and <5 μm) shift systematically toward OP-NMTP\nvalues (Fig. 3). Oxygen isotope distributions of the <32 μm fraction broaden and show greater\noverlap with the Chinese desert range, consistent with higher fine-grained LRT dust\ncontributions (Fig. 4).\nFinally, we note that the relative prominence of LRT signals differs among proxies. REE\ncompositions tend to highlight LRT contributions more clearly, whereas Sr-Nd and O isotopes\nreflect both local and LRT inputs but with stronger sensitivity to grain size and mineralogical\nfractions. These differences likely account for the proxy-specific discrepancies observed, as\nnoted in Lines 175-179.\n2) The chronological framework is very important for this study and its conclusions, and in my\nopinion, this needs to be improved. The authors have separated pre- and late Glacial Maximum\nfor the Batagay and Yakutia ice wedges - but the chronological framework is quite uncertain,\nand not described in detail. For example, Murton et al. (2022) show quite a lot of uncertainty\nin the dating.\n1-2. We appreciate your emphasis on the importance of the chronological framework. To\nimprove the age constraints of the Batagay ice wedges, we have considered additional\nradiocarbon age data (Opel et al., under review; unpublished plant macro ages). These data\nbroadly suggest a formation interval between ~45,000 and 30,000 cal yr BP, corresponding to\nmiddle to late MIS 3, but we have not formally incorporated them into the current manuscript\nbecause they are not yet published. Instead, we rely on the established age range of ~60-27 ka\n(late MIS 4 to MIS3; Murton et al., 2022), which substantially overlaps with MIS 3 (~57-29\nka). Accordingly, as clarified in the revised Introduction (Lines 71-76) and consistently adopted\nthroughout the revised text (e.g., Fig. 1; Discussion), we conservatively frame the Batagay ice\nwedges within MIS 3. For clarity, we now assign the Batagay UIC to MIS 3 and the Central\nYakutia ice wedges to MIS 2.\n3) There is a local ice cap on the Verkhoyansk Mountains between Batagay and Central Yakutia\nthat is out of phase with the global Last Glacial Maximum. This is also true for Pleistocene ice\nextent in Alaska, see e.g. Stauch and Gualtier (1–3). They have a maximum extent in MIS 4 or\neven just before. This shows that humidity is the main driver of ice and that local ice caps can\nalso influence at least the local wind fields.\nIn addition, there were so many climatic fluctuations during the last glacial cycle that this\nshould be clarified before drawing a big picture from the Chinese desert to Greenland based on\nsuch a rough chronological framework. For example, the aforementioned LRT of dust from\nChina to Siberia needs to be proven and the period in which this direction occurred needs to be\nestablished. Without a time frame, the conclusion remains highly speculative. Provide some\nage constraints for your samples and also from the surround areas.\nIn my opinion, this should be also confirmed by paleoclimatic models. The North Atlantic and\nthe distribution of the Pleistocene ice influenced the jet stream. There are local wind fields over\nthe ice sheets, and there were easterly winds in front of the ice caps. There are quite a lot of\nclimatic fluctuations during the last glacial cycle and therefore quite a lot of fluctuations in the\ndirection of the jet stream. The Feno-Scandinavian ice sheet is important for the climate in Asia.\nIn particular, during the global Last Glacial Maximum, this ice sheet, at its largest extent,\nblocked moist air masses to the east during its largest extent. There are eastly winds in front of\nthe ice sheet which are also responsible for the dust and loess distribution, please see the model\nof Schaffernicht et al. (4), who also discussed the dust distribution in front of the European ice\nsheet during the LGM. Local ice can also have an influence on wind direction and especially\non the transport of silt-size particles, as shown in many papers.\n1-3. Thank you for these insightful suggestions. Your comments prompted us to focus more\nclosely on the climatic fluctuations during the last glacial cycle. We now conservatively\ninterpret the Batagay ice wedges as forming during MIS 3 (see response 1-2), a period\ncharacterized by relatively warm and unstable climate conditions. We also fully agree that local\nice caps in the Verkhoyansk Mountains likely reached their maximum extent during MIS 4 or\nearlier, driven by moisture availability, and did not expand significantly during the LGM.\nThe Verkhoyansk local ice cap appears to have remained limited even during MIS 3. Therefore,\nthere was probably little difference in its extent between MIS 3 (when the Batagay ice wedges\nformed) and the LGM (when the Central Yakutia ice wedges formed). Based on this, we have\nsubstantially revised our interpretation: rather than attributing changes in dust transport to ice-\nsheet extent around Beringia, we now focus on the role of climate-driven variability in\nsynoptic-scale atmospheric circulation. As the Verkhoyansk ice cap was likely not\nextensively developed during either MIS 3 or the LGM, a detailed discussion of its potential\ninfluence on local wind fields would be overly speculative. We have therefore chosen not to\nelaborate further on this point in the revised manuscript.\nOur revised Discussion section highlights the possibility of ‘episodic meridional transport\nof Asian dust to the Arctic across Siberia’, even under past climate conditions. This pathway\nis supported by modern observations and modeling studies (Huang et al. 2015; Zhao et al.\n2022), where cyclonic systems over northeast Asia facilitate rapid meridional transport.\nWe propose that such events were relatively frequent during MIS 3 (warmer and more variable\nclimate) compared to the LGM, thereby explaining the stronger Chinese dust signals in the\nBatagay samples. In contrast, during the LGM, the development of the Siberian High and the\nsouthward displacement of the westerlies (Brady et al., 2013; Yanase & Abe-Ouchi, 2007)\nlikely suppressed meridional transport, resulting in weaker Chinese dust signatures in Central\nYakutia. Although paleoclimatic modeling could further test this mechanism, such analysis lies\nbeyond the scope of this study. Instead, we believe that our findings will provide a valuable\ngeochemical basis for future model-based investigations of dust transport under paleoclimate\nconditions.\n4) Statistics:\nThe biplots in Figures 2 and 3 show only the overlap between the REE or isotope ratios of the\nsamples with those of the other proxies. In order to provide a more reliable distinction, a\nstatistical analysis with respect to the differences between samples and proxies can improve\nthe interpretation to which group the samples are assigned. Another aspect which to consider\nis whether the samples and the data from the proxies are of the same age.\n1-4 (1). Thank you for this constructive suggestion. We agree that statistical approaches can be\nuseful to summarize complex geochemical datasets. However, in our case we consider such\napproaches less suitable for several reasons. First, our samples represent mixtures of both local\nand distal sources rather than a single provenance. A simple statistical clustering against\nreference datasets would therefore risk oversimplifying these multi-source signals and may not\nappropriately capture the true provenance characteristics. Second, multivariate methods like\nPCA emphasize the largest axes of variance and may obscure the more subtle but critical\nfeatures (e.g., Eu anomalies, grain-size independent tracers suggested by Ferrat et al., 2011)\nthat we highlight in our interpretation. To address your concern regarding the limited\nconfirmation in the original biplots, we have instead expanded our direct geochemical\ncomparisons by adding further element ratios (e.g., Eu/Eu*, Y/∑REE, Y/Tb) in Fig. 2 and a\nseries of new plots in Supplementary Fig. 6. In addition, Fig. 3 now includes further analyses\nof the fine fractions and illustrates mixing relationships among multiple reference datasets as\nan alternative to statistical analysis. We believe these additional visualizations more\nappropriately capture the complex mixture of sources while avoiding the risk of\noversimplification inherent in broad statistical classifications.\nWith respect to the temporal comparability of samples and reference datasets, we note that\nall ages are provided in Supplementary Data 2 and 3. Some reference materials are broadly\ncoeval with our samples (LGM or late Pleistocene), whereas others have either unknown ages\nor substantially older formation ages. However, the proxies used in this study (REE, Sr-Nd,\nand O isotopes) are not modified by surface processes and preserve the source composition, so\ntheir use as provenance constraints does not require exact age equivalence. In the case of Sr-\nNd isotopes, while radiogenic decay can alter isotope ratios over geological time, we use the\npresent-day measured values of the reference samples rather than attempting to reconstruct\ninitial values. Nd isotopes, for instance, are reported as ε (0) indicating the present-day\nNd\nmeasured values. This ensures that the direct comparisons remain valid for constraining\npotential source contributions.\nFigure 4 is not convincing and also on line 169 they mentioned an overlap. I think they should\ntest the differences.\n1-4 (2). Fig. 4 presents grain-by-grain oxygen isotope data obtained by SIMS, displayed as\nGaussian kernel density curves to illustrate the internal variability of individual samples. By\ncontrast, the Chinese reference datasets are derived from bulk analyses. These reference\ndatasets cannot be represented as continuous distributions, as shown in Fig. 4, and direct\nstatistical comparison with our data is not feasible. Instead, we performed statistical tests\n(Welch t-test, Mann-Whitney U, and permutation test) within our dataset to evaluate whether\noxygen isotope distributions differ statistically significantly among sites. The results, now\nreported in the revised Fig. 4 caption and Methods, show that the Batagay sample is statistically\ndistinct from the Central Yakutia samples (p < 0.001), while no significant differences were\ndetected between the Cyuie and Churapcha samples (p ~ 0.8). In addition, to improve the\nvisibility of potential overlaps with the reference data, we have revised Fig. 4 by highlighting\nthe peak ranges where the reference values occur. This revision improves clarity in assessing\nsite-specific differences in the degree of overlap with reference values.\nSome other questions remain open:\nIs there any evidence to rule out repeated deposition and transport and a mixing of the sampled\nmaterial?\n1-4 (3). We agree that repeated deposition, reworking, or mixing cannot be completely ruled\nout. However, multiple observations suggest such processes are unlikely to dominate our\nsamples. First, we specifically targeted well-preserved syngenetic ice wedges without thaw-\nrelated disturbance as noted in the Introduction (Lines 65-71; Lines 83-85; Kim et al., 2019;\nYang et al., 2023; Park et al., 2024). Unlike host sediments, the syngenetic ice wedge infill we\nanalyzed is less affected by redeposition or reworking. Second, our ice wedge samples formed\nprimarily by snow compaction and hoar frost accretion (Yang et al., 2023; Park et al., 2024),\nrather than snowmelt or surface water infiltration, which minimizes the chance of secondary\ninput, providing a more direct record of atmospheric deposition during ice wedge growth\n(Lines 81-83). Together, these features indicate that the geochemical signals we observe most\nlikely represent primary atmospheric deposition during ice wedge growth, rather than being\noverprinted by repeated transport or mixing.\n5) Figures:\nI did not understand figure 1: is the legend for LGM, MIS 3 and MIS 4 for the extent of the\nice? If so, the figure is wrong. See my comments above, the ice in Siberia is related to the\nincoming moisture from the west, which is blocked during MIS 4 and especially doing MIS 2.\nThe maximum extent in the interstadial of the last glacial cycle (MIS 3) in older literature is\nbased on radiocarbon ages and these are all minimum ages. The ice in eastern Siberia has its\nmaximum extent in MIS 4 or even earlier, because there is less moisture in that area afterwards\ndue to the blocking moist air masses by the Feno-Scandinavian ice sheet.\n1-5. We agree that the Feno-Scandinavian Ice Sheet was extensive during MIS 4 and MIS 2,\nand that its presence likely blocked incoming moisture, thereby limiting glaciation in eastern\nSiberia during these periods. In our original Fig. 1, we referred to the ice sheet reconstructions\nof Batchelor et al. (2019), which modelled ice extent at several time slices across MIS 3 (30,\n35, 40, and 45 ka). Among these, only the 40 ka reconstruction shows more extensive ice cover\nin eastern Siberia, due to the incorporation of the maximum Quaternary ice-extent template to\nmatch the empirical evidence from the Kamchatka Peninsula. As you note, this 40 ka\nconfiguration likely overestimates the ice extent for interior northeastern Siberia, including the\nVerkhoyansk Mountains. To avoid potential misinterpretation, we have revised Fig. 1 by\nexcluding the 40 ka reconstruction and clarified this in the Methods section (Lines 408-414).\nInstead, the ice extent for MIS 3 is now illustrated based on the other three time slices (30,\n35, and 45 ka), which better reflect the likely limited glaciation in northeastern Siberia during this\nperiod.\nFrank Lehmkuhl, 6.3.2025\nReferences\n1. Diekmann, B. et al. Late Quaternary lake dynamics in the Verkhoyansk Mountains of Eastern\nSiberia: implications for climate and glaciation history. Polarforschung 86, 97–110 (2017).\n2. Stauch, G. & Gualtieri, L. Late Quaternary glaciations in northeastern Russia. Journal of\nQuaternary Science: Published for the Quaternary Research Association 23, 545–558 (2008).\n3. Stauch, G. & Lehmkuhl, F. Quaternary glaciations in the Verkhoyansk Mountains, northeast\nSiberia. Quaternary Research 74, 145–155 (2010).\n4. Schaffernicht, E. J., Ludwig, P. & Shao, Y. Linkage between Dust Cycle and Loess of the\nLast Glacial Maximum in Europe. https://www.atmos-chem-phys-discuss.net/acp-2019-\n693/ (2019) doi:10.5194/acp-2019-693.\nReviewer #2 (Remarks to the Author):\nThe manuscript \"East Siberian ice wedges recording the polar jet stream during the Late\nPleistocene\" by Kim et al. studies the provenance of mineral dust in the Late Pleistocene ice\nwedges collected from Siberia.\nMy report is very short, as I find the manuscript well structured, easy to follow, and the results\nand conclusions well justified. I think the manuscript is suitable for publication and would be\nof interest to many. I only have a few notes and corrections for the authors below.\nThank you for the encouraging assessment and thoughtful comments on our manuscript.\nKey results: The results indicate a significant contribution from distant Asian sources for the\npre-LGM dust in the Siberian ice wedges, while the late LGM dust is more locally sourced.\nThe authors attribute these differences to changes in the polar jet stream pathway patterns that\nthemselves are linked to changes in the extent of ice sheets.\nThank you for the clear summary of our key findings.\nValidity:\nThe manuscript uses multiple methods to infer the provenance of the dust, making the\nprovenance analysis more robust. The data obtained by different methods are mostly consistent\nwith each other and point to the conclusions presented in the manuscript. The data are also\nconsistent with previous studies, and the compilation of data from previous studies is\nextensive.\nThank you for acknowledging the robustness of our multi-method provenance analysis and for\nyour positive assessment of our data compilation and interpretation.\nSignificance:\nI think the results of this study are significant, not only because of the samples, which may be\nunavailable in the future if they melt, but also because the results offer important new insights\nto the links between dust and climate and will be of interest to many in the fields of dust and\npaleoclimate research and beyond.\nWe sincerely appreciate your recognition of the significance of our findings. Your comment on\nthe unique value of the samples and their broader implications for dust and climate interactions\nis truly encouraging.\nData and methodology:\nOnly the ICP-MS/AES methods need more details on the analytical parameters and information\non the standards used.\nThe Sm values of the Lena and Yana SPM samples seem to be incorrectly reported in\nSupplementary Table 2. Please correct.\n2-1. We are truly grateful for this valuable comment. We carefully re-evaluated our ICP-\nMS/AES analytical procedures together with the analytical institution. In the original analyses,\ncertified reference materials (CRMs) were not sufficiently documented to validate the accuracy.\nTo address this, we reanalyzed all samples with appropriate CRMs and standardized protocols.\nThe revised Methods section and Supplementary Table 2 now provide detailed information on\nanalytical parameters and reference materials. The reanalyzed dataset is broadly consistent with\nthe original results and does not alter the overall interpretations of the study. We believe these\nrevisions ensure that our dataset meets the analytical standards expected for publication in\nNature Communications.\nThe Sm values for the Lena and Yana SPM in the REE dataset (Supplementary Data 2) have\nalso been corrected. We sincerely appreciate your careful reading of these details.\nAnalytical approach:\nWhile a PCA may have been useful in presenting the REE/trace element data in a more robust\nway, I do not think it is absolutely necessary, since the main features are already evident from\nthe existing figures.\nI would, however, have liked to see more plots on different trace elements (possibly in the\nsupplementary information), for example Eu/Eu*, Y/∑REE, Y/Tb, Y/La, as these are also used\nby the cited paper of Ferrat et al. (2011).\n2-2. Thank you for this helpful suggestion. We have expanded our presentation of element\nratios by replacing several plots in Fig. 2 with ratios highlighted in Ferrat et al. (2011) (e.g.,\nEu/Eu*, Y/∑REE, Y/Tb). In addition, we have added a suite of new ratio plots in\nSupplementary Fig. 6 to provide a more comprehensive comparison. We believe these revisions\nsubstantially improve the clarity and robustness of our geochemical interpretation, in direct\nresponse to this comment.\nSuggested improvements:\nFig. 3. The grain size fraction that each dataset represents would be good to include in the\nfigure, as the Sr isotopes can be influenced by the grain size. I would also like to hear what are\nthe authors’ thoughts on why the Batagay values are not close to OP or EQLM if they are the\nmain sources based on REE (Fig.2)?\n2-3. Thank you for the valuable comments. Regarding grain-size effects on Sr isotopes, we\nconducted additional analyses of fine fractions (<10 and <5 μm). The grain-size fractions of all\nsamples and the compared datasets are now indicated in Fig. 3 and its caption, allowing\nassessment of potential size-related effects. Regarding the Batagay values, we interpret their\noffset from OP or EQLM as reflecting the multi-source nature of the Batagay samples. These\nsamples likely represent mixtures of local sediments and distal sources, including OP, NMTP\nand possibly MG. Although OP or EQLM appear as dominant sources based on REE\ncompositions (Fig. 2), they do not plot close to Batagay in the Sr-Nd isotopes (Fig. 3), as you\nnote. In the revised Fig. 3, however, mixing trajectories that combine OP and NMTP encompass\nthe Baagay data. We further note that REE and Sr-Nd isotopes are not necessarily controlled\nby the same grain-size or mineralogical fractions, which likely accounts for the observed\ndiscrepancy between the REE- and isotope-based provenance signals. This explanation has\nbeen incorporated into the revised manuscript (Lines 175-179).\nWhile I do not disagree with the conclusions, the similarity of Greenlandic and Alaskan dust\nto the samples of this study are only based on the Sr-Nd isotopes. For this reason, I would add\na bit of uncertainty to the conclusions about these regions. Especially since in Greenland, the\nSr-Nd isotopes have not been enough to discriminate the European and Asian dust (Ujvari et\nal. 2015 – cited in the manuscript).\n2-4. As you point out, the apparent similarity of our samples to Greenlandic and Alaskan dust\nrelies solely on Sr-Nd isotope data, given the scarcity of comparative datasets. We agree that\nthis alone does not provide a sufficiently robust basis to extend our interpretation toward long-\nrange dust transport between Siberia and Greenland or Alaska, particularly since Sr-Nd\nisotopes have proven insufficient to distinguish European and Asian dust in Greenland (Újvári\net al., 2015). Throughout the revised manuscript, we have therefore removed the speculative\ndiscussion of Greenland and Alaska to avoid potential overinterpretation. Instead, we have\nexpanded the discussion of the dust transport variability from China to Siberia, which is\nconsistently supported by multiple geochemical proxies in our dataset. We believe this revision\nimproves the clarity and balance of our provenance interpretation.\nLines 225-227: It would be nice to explain in a bit more detail why the jet stream responses to\nthe ice sheet changes in the way that is suggested (for those who are not familiar with the\natmospheric aspects of the study). So what are the mechanisms behind the changes in the jet\nstream pathways?\n2-5. In the original version, we attributed the variability in dust transport pathways to jet stream\nshifts in response to ice sheet extent. However, following the comments of reviewer #3 (see\nresponse 3-9), we have adopted more conservative terminology (‘synoptic-scale systems’,\n‘atmospheric circulation’ or ‘dust transport’ rather than ‘jet stream’) and revised the\ninterpretation throughout the manuscript. In particular, the spatial distribution of ice sheets near\nour study area shows little difference between the two studied intervals (MIS 3 versus the LGM;\nsee responses 1-3 and 1-5 to reviewer #1). Instead, we attribute the variability to broader\nclimatic changes and associated synoptic-scale circulation patterns. Observations under\nmodern conditions show that Asian dust is generally transported eastward by the westerlies but\ncan also reach the Arctic rapidly along meridional pathways, especially when low-pressure\nsystems over northeast Asia generate intensified cyclonic flow (Huang et al., 2015; Zhao et al.,\n2022). Such meridional transport may have been more frequent during MIS 3, when the climate\nwas relatively warm and variable, consistent with the strong Chinese dust signal in the Batagay\nsamples. In contrast, during the LGM, strengthened Siberian High pressure and a southward\ndisplacement of the westerlies likely suppressed meridional transport, which is consistent with\nthe dominance of local dust signatures in the Central Yakutia samples. These mechanisms and\nthe associated variability in transport patterns are now incorporated into the revised Discussion,\nFig. 1, and Supplementary Fig. 7.\nClarity and context: The manuscript is well structured and clearly presented.\nReferences: References to previous research are appropriate and encompassing.\nMy expertise: I am not very familiar with Yedoma or permafrost deposits in general (have not\nworked with those).\nReviewer #3 (Remarks to the Author):\nReview of Kim et al Nature Communications\nApril 2025\nKim and coauthors present geochemical provenance data on Yedoma sediments from two sites\nin Siberia. The data include Sr-Nd isotopes and REE, presumably on the bulk fraction, and O\nisotopes on individual quartz grains split into several size fractions. The data are used to\nreconstruct the position of the northern branch of the polar jet during the LGM.\nThe writing is clear and the paper is well-organized with nice-looking figures. Overall, the ice\nwedges represent an interesting paleoclimate archive that deserves exploration. However, we\nhave some serious concerns with the data and their interpretation, and do not consider the\nconclusions to be supported by the data.\nThank you for the clear summary and comments on our manuscript. We also appreciate the\ncritical feedback, which helped us to carefully reconsider and clarify the interpretation of our\ndata.\nRegarding the provenance data, the paper lacks sufficient characterization of the local source\narea geochemistry, particularly for Nd. The Laptev Sea sediments (LSS) that the authors use in\nplace of local sediment compositions actually plot between the Batagay and Central Yakutia\nsites, suggesting that the LSS may reflect mixing of local materials that are simply not\nrepresented in Fig. 3. Without true characterization of the Beringia potential dust source\ncomposition, it is not possible to estimate the inputs of local vs LRT dust from Chinese deserts.\n3-1. Thank you for this important comment. We fully acknowledge that the local source\ngeochemistry in Beringia is not yet comprehensively characterized, particularly for Nd isotopes.\nAs you note, the Laptev Sea sediments (LSS) likely integrate signals from multiple local\nmaterials and may therefore reflect mixing rather than a discrete local endmember. To address\nthis limitation, we have expanded the range of local reference datasets considered in Fig. 2 and\nFig. 3, including Kharaulakh-Suordakh mafic rocks (chosen because of proximity to the study\narea), Aldan Shield lamproites (included because the Lena River flowing through the Central\nYakutia site drains the Aldan Shield), and northeastern Siberian loess (which may reflect a\nmixed origin like the LSS, but its Sr-Nd isotopes represent the only reported loess compositions\nin close proximity to the study area). We explicitly note that whole-rock values of Aldan\nlamproite and Kharaulakh-Suordakh volcanic rocks are not treated as direct equivalents of fine\nsediments, but rather treated as bounding constraints to define the plausible local compositional\nrange (Lines 164-166). These datasets allow us to approximate local endmember compositions\nfor comparison with our samples. Nevertheless, we agree that without more extensive\ncharacterization of potential Beringian dust sources, it is not possible to fully distinguish local\nversus LRT contributions in a quantitative sense. We have therefore interpreted our provenance\nsignals in qualitative rather than quantitative terms, emphasizing the consistent signatures\nsuggesting contributions from Chinese sources. We also highlight the need for future studies to\nbetter characterize the geochemistry of potential local dust sources across Beringia, which will\nbe essential for refining source contributions in this region.\nFurther, we are not convinced that the sites, particularly Central Yakutia, are receiving dust\nfrom Chinese deserts. If they were, we would expect to see compositions that reflect mixing of\nlocal and long-range-transported (LRT) end-members. Instead, the Sr-Nd isotope compositions\nof the sites are both tightly clustered, which is more indicative of input from a single source.\nIt’s possible that the Batagay samples follow a mixing trend between two end-members, with\none of them being Chinese desert material. However, the blue points in Fig. 3 really do not\nappear to be following a mixing trend. Certainly if transport were occurring from Chinese\ndeserts over both sites and onward to Greenland, the data points should follow the same mixing\ncurve – which they clearly do not.\n3-2. Thank you for this careful assessment. We agree that, in the simplest case of two-\ncomponent mixing with identical local endmembers and the Chinese LRT dust source, the data\nwould be expected to align along a single mixing trajectory. However, several factors make\nsuch a pattern unlikely across both sites.\nFirst, the two sites do not share a single local composition. In revised Fig. 3, the Central\nYakutia samples appear to be influenced predominantly by Aldan Shield-derived materials,\nwhereas Batagay may also integrate mafic inputs. Consequently, if Chinese possible source\nareas (PSAs) contribute to both regions, each site would mix with a different local endmember,\nresulting in distinct mixing trajectories rather than a single curve (Fig. 3b). In addition, because\nthe Chinese PSAs span a range of Sr-Nd values rather than a single point, it is more appropriate\nto compare the samples against a mixing field rather than expect alignment along one idealized\nline.\nSecond, the relative contributions of local versus LRT sources differ between the sites. The\ntight clustering of bulk Central Yakutia samples reflects the dominance of locally derived\nmaterials as you note, whereas Batagay compositions fall within the Chinese PSA-defined\nmixing field (Fig. 3). Mixing trajectories between OP-NMTP and local endmembers\nencompass the Batagay data, suggesting a local + LRT mixture. For Central Yakutia, bulk\nsamples remain close to the local field (Aldan Shield-like ɛ with radiogenic 87Sr/86Sr),\nNd\nadditional analyses of <10 μm and <5 μm fractions show a shift toward OP-NMTP\ncompositions. This shift, slightly higher ɛ values in addition to Sr isotope grain-size effects,\nNd\nsuggests the possibility of minor Chinese dust contributions to the fine fractions, even though\nlocal sources remain dominant overall. Oxygen isotope data provide additional support (Fig.\n4), where both samples show broadening of the <32 μm distributions and partial overlap with\nChinese desert values, yet the Central Yakutia samples retain a stronger local peak compared\nto the Batagay samples.\nFinally, we have removed speculative statements about a continuous Chinese-to-Greenland\npathway (see response 2-4 to reviewers #2). We now focus our interpretation on episodic\nsynoptic-scale meridional transport from China to East Siberia during MIS 3, and emphasize\nthat the Central Yakutia samples from the LGM contain a greater proportion of locally sourced\nmaterials.\nIn addition, there are several important analytical details that are missing. One is the size\ndistribution of the Yedoma silts used for Sr-Nd analysis. Sr isotopes are known to have a grain\nsize effect (e.g. Biscaye and Dasch, 1971; Grousset and Biscaye, 2005; Gaiero, 2007); thus,\nit is important to compare apples-to-apples size fractions among different studies. In the case of\nLRT dust, scientists typically analyze the fine fraction (<5 um). At the very least, even if the\n<5 um fraction was not isolated in this study, the measured grain size fraction used for the\nisotope analyses needs to be stated. Based on Extended Data Fig. 5, it appears that the silts are\nquite coarse (10s to 100s of µm diameter) – so isotopic analysis of the bulk size fraction is not\ndirectly comparable to other fine-fraction data such as the dust from Greenland ice cores.\n3-3. We fully acknowledge that Sr isotopes are sensitive to grain size, and that direct\ncomparison with other datasets requires clear specification of the analyzed size fractions.\nBecause of the limited availability of sample materials, our initial analyses were performed on\nbulk aluminosilicates. To address this limitation and ensure comparability with fine-fraction\n(<5 μm) datasets commonly used in LRT dust studies, we subsequently obtained additional\nsamples and conducted Sr-Nd isotope analyses on <10 μm and <5 μm fractions. The procedures\nof size separation and analyses are now described in the revised Methods, and the grain-size\nfractions of all datasets are clearly indicated in Fig. 3 and its caption.\nThe fine-fraction analyses show a marked shift in Sr isotopes consistent with the known\ngrain-size effect and a smaller shift in Nd isotopes relative to the bulk samples, both trending\ntoward the OP-NMTP endmembers. This pattern suggests not only the expected grain-size\neffect of Sr isotope but also a relatively greater proportion of LRT dust in the finer fractions.\nThese additional measurements strengthen the robustness of our provenance interpretation and\nensure that our dataset is directly comparable with other fine-fraction studies.\nThe Sr and Nd isotopes were run with isotopic reference materials but it is unclear whether\nthey were used both as bracketing standards to correct the isotope ratios and as ‘unknowns’ to\nassess accuracy of the analyses. Given the numbers analyzed for NBS-987 (n = 100) and JNdi-\n1 (n = 140), it seems as though these are bracketing standards – in which case, additional\nreference materials should be reported to provide an independent check on the accuracy of the\nisotope ratios.\n3-4. Bracketing standards were not used in our Sr and Nd isotope analyses. Instead, the\ninternational reference materials NBS-987 (Sr) and JNdi-1 (Nd) were treated as unknowns to\nassess external reproducibility and analytical accuracy. Instrumental mass bias was corrected\nby internal normalization (86Sr/88Sr = 0.1194; 146Nd/144Nd = 0.7219). We clarify that the\nnumbers previously reported (n = 100 for NBS-987; n = 140 for JNdi-1) referred to the number\nof measurement cycles within a single run, rather than replicate analyses, which may have\ncaused confusion. The originally reported values were based on one Sr standard run and two\nNd standard runs.\nTo better document reproducibility, we have revised the text to report long-term results based\non 15 replicate measurements of each standard during the measurement period, yielding\n87Sr/86Sr = 0.710256 ± 6 (2σ, n = 15) and 143Nd/144Nd = 0.512122 ± 5 (2σ, n = 15). For\nadditional analyses of the fine fractions (<10 and <5 μm), 8 replicate measurements of each\nstandard yielded 87Sr/86Sr = 0.710252 ± 6 (2σ, n = 8) for NBS-987 and 143Nd/144Nd = 0.512119\n± 4 (2σ, n = 8) for JNdi-1. These values are in good agreement with accepted values, confirming\nthe accuracy and reliability of our dataset. This information has been incorporated into the\nrevised Methods section.\nIn addition to source area geochemistry, the inference that Beringia was a source of high-\nlatitude dust in the past would be supported better through some mapped deposits of potential\nsource sediments. What is the geomorphic evidence for dust generation in this region? Are\nthere maps of glacial extent? Outwash plains?\n3-5. We appreciate this thoughtful comment. In the original version, we speculated that\nBeringia might have acted as a dust source during the Late Pleistocene, as numerical modeling\nstudies have suggested the plausibility of Siberia and Alaska as potential dust contributors\n(Lambert et al., 2015; Mahowald et al., 2006). However, following the reviewers’ feedback,\nwe have removed this interpretation from the revised manuscript. We now focus on\ndistinguishing local versus LRT contributions recorded in the Batagay and Central Yakutia ice\nwedges, without invoking Beringia as a separate dust source or transport pathway. Accordingly,\nwe no longer discuss geomorphic evidence for dust generation in Beringia.\nThe quartz O isotope data are interesting, in that several of the curves are bimodal, suggesting\ninputs from multiple sources. The interpretation related to these data would be strengthened by\ninclusion of comparable data on the potential source regions (e.g. Beringia and Asian deserts)\nincluded in the figure, rather than just in the text. Ideally these would be plotted against another\nprovenance tracer (e.g. bivariate plot) and be supported by mixing calculations. The\ninterpretation provided on Line 175 – that both >32 and <32 sediments are contributed by LRT\nof Chinese dust – is implausible. Considering that local sources can account for the oxygen\nisotope values in the coarser fraction (Line 160), it does not make sense that all this relatively\ncoarse silt would have come thousands of km from China rather than from local sediments.\nWe think in this case, the most parsimonious interpretation needs to be made rather than basing\nthe interpretation on rare exceptions in the literature of long-distance coarse particle transport.\n3-6. We have revised Fig. 4 and its caption to include oxygen isotope ranges of PSAs as colored\nbands, allowing direct visual comparison. We also attempted bivariate plots and mixing\ncalculations, but their interpretive utility was limited because the available reference datasets\ndiffer in sample type, number of samples, and grain-size fractions. These inconsistencies\npreclude direct one-to-one comparisons across proxies. Nevertheless, the most pronounced\noxygen isotope compositions observed in the finest fractions of the Batagay samples fall within\nthe OP-NMTP range, consistent with other provenance tracers. This has been incorporated into\nthe revised Fig. 4.\nAs you note, attributing the coarse fractions to LRT from China was an over-interpretation.\nWe have therefore removed this statement from the manuscript. The ~15‰ peak in the coarse\nfractions is interpreted as being most plausibly derived from local sediments, while\nacknowledging that this peak range may still reflect a mixture of both local and LRT sources.\nLikewise, the REE data in Extended Data Figure 4 are a helpful addition, but could be leveraged\ntoward the interpretation more effectively by including a panel that directly compares the\npatterns of the different regions. We would advocate for further normalizing samples to a single\nelement, e.g. Yb or Lu, to more effectively compare the patterns. By eyeball, the data in panels\na and b actually look more similar to panel d than to panel c, supporting a local source for the\nYedoma silts. Figure 2 in the main text helps with these comparisons, but we are not convinced\nthat the Lena and Yana sediments fully characterize the local dust source region, given the\nolder bedrock to the south, shown in Extended Data Figure 1, which would provide sediment with\nmore negative εNd values, as shown by the Central Yakutia sites in Fig. 3.\n3-7. We have revised Supplementary Fig. 5 by normalizing the datasets to Yb, which facilitates\nclearer inter-comparisons of REE patterns as suggested. We also expanded local reference\ndatasets in revised Figs. 2-3 and Supplementary Figs. 5-6 to include Aldan Shield lamproites\nand Kharaulakh-Suordakh volcanic rocks. Overall, the REE patterns in Supplementary Fig. 5\nfor both sites are loess-like, showing overall flat PAAS-normalized trends that differ from the\nlocal bedrock compositions (Aldan Shield lamproites and Kharaulakh-Suordakh volcanic\nrocks). However, the Central Yakutia samples exhibit pronounced Eu anomalies, a feature also\nobserved in the Lena and Yana SPM as well as in the local bedrocks. In the revised Fig. 2 and\nSupplementary Fig. 6, the Lena SPM consistently resembles the Central Yakutia samples, but\nalso shows a shift toward Aldan Shield-like values. This combination suggests that the Central\nYakutia dust likely incorporates a contribution from Aldan Shield-derived material, which is\nnow noted in the revised text (Lines 115-119). As you note, the more negative ɛ values of the\nNd\nAldan Shield bedrock are consistent with the Central Yakutia compositions in revised Fig. 3.\nRegarding the potential source regions shown on Fig. 3, the African sources are not relevant\nbased on geography and atmospheric transport patterns. We would recommend removing them\nfrom the figure and discussion. In addition, the “Alaska” field reflects only the Fairbanks loess\ndata of Biscaye et al. 1997 and not more recent data from southcentral Alaska that characterize\nthe active Copper River dust source and related glaciofluvial sources (Koffman et al., 2022).\nIt may be worth including these data for a more complete representation of Alaska sources.\n3-8. We have revised Fig. 3 and the associated discussion accordingly. As you note, African\nsource regions are geographically and climatologically implausible contributors to the studied\nsediments. We have therefore removed the African sources from both the figure and the text to\navoid any misinterpretation. Regarding the Alaska field, we appreciate the suggestion to\nincorporate additional datasets beyond the Fairbanks loess. We have updated Fig. 3 to include\nmore recent data from southcentral Alaska (Koffman et al., 2022). This revision provides a\nmore comprehensive representation of Alaskan sources.\nFinally, while a Chinese desert source *could* be a plausible end-member for Batagay dust,\nit does not follow that the jet itself had to have gone directly over the site. There is plenty of dust\ntransport that occurs not in the jet, for example through synoptic-scale systems. For instance,\nextratropical cyclones transport dust from Patagonia to Antarctica, including onto the East\nAntarctic plateau – yet the Southern Hemisphere polar jet maintains an annular structure and\ndoes not shift directly over the ice sheet to deposit this dust.\n3-9. Thank you for these helpful comments. We fully agree that the similarity between the\nChinese source data and our sample data does not necessarily imply that the polar jet stream\nmust have passed directly over our study sites. In light of this important point, we have revised\nthe Discussion to frame our interpretation in terms of broader atmospheric circulation related\nto synoptic-scale systems, rather than the jet stream. In particular, modern observations show\nthat Asian dust can be transported meridionally to the Arctic via cyclonic systems over\nnortheast Asia (Huang et al., 2015; Zhao et al., 2022), a mechanism conceptually similar to the\nPatagonian dust transport to Antarctica, as noted in your comment. We now emphasize such\nsynoptic-scale variability as the more plausible driver of episodic long-range dust transport\nduring MIS 3, consistent with the strong Chinese dust signals observed in the Batagay samples.\nThis revision is reflected throughout the manuscript.\nFurthermore, regarding the position of the jet: the authors should reconsider the conceptual\nmodels of the jet stream presented in Fig. 1 and Extended Data Fig. 6. Although some synoptic\nweather patterns can produce large meridional waves propagating toward (or even across) the\nNorth Pole, it seems implausible that a distinct polar jet stream from the Laptev Sea to\nGreenland would represent mean climatology. To inform these schematic depictions, we\nrecommend examining mean wind climatologies from existing LGM climate model\nsimulations (e.g., Brady et al., 2013), and perhaps also modern reanalysis products such as\nERA5. Furthermore, the configuration of the polar and subtropical jet streams has large\nseasonality, and it could be beneficial to present both summer and winter circulation\nclimatologies instead of annual.\n3-10. We agree that our original schematic depictions of the jet stream may have given the\nimpression of representing mean climatology, which was not our intent. In the revised\nmanuscript, we have substantially simplified these figures and reframed them to illustrate\ngeneralized dust transport pathways rather than specific jet stream tracks. In particular, the\nmeridional transport is not intended to represent mean circulation, but instead schematically\nillustrates episodic events that were likely more ‘frequent’ during MIS 3 than during the LGM.\nThis is clarified in the revised Fig. 1 caption (Lines 583-585) and avoids potential\noverinterpretation of the schematics as mean flow patterns.\nWhile we recognize the significance of mean wind climatology from LGM simulations and\nmodern reanalysis products such as ERA5, a full model-data comparison lies beyond the scope\nof this study. Instead, we draw on modern observational and modeling evidence (e.g., Huang\net al., 2015; Zhao et al., 2022) to highlight how synoptic-scale variability can facilitate\nmeridional dust transport to the Arctic. We also acknowledge the importance of seasonality in\natmospheric circulation. However, given the temporal resolution of our samples, we cannot\nresolve seasonal differences. We therefore retain a simplified depiction of dust transport events,\nwhile clarifying this limitation in the revised Discussion (Lines 260-261).\nReferences Cited:\nBiscaye, P. E., & Dasch, E. J. (1971). The rubidium, strontium, strontium-isotope system in\ndeep-sea sediments: Argentine Basin. Journal of Geophysical Research, 76(21), 5087-5096.\nBiscaye, P. E., Grousset, F. E., Revel, M., Van der Gaast, S., Zielinski, G. A., Vaars, A., & Kukla,\nG. (1997). Asian provenance of glacial dust (stage 2) in the Greenland Ice Sheet Project 2 ice\ncore, Summit, Greenland. Journal of Geophysical Research, 102(C12), 26,765-726,781.\nBrady, E.C., Otto-Bliesner, B.L., Kay J.E., and Rosenbloom, N. (2013). Sensitivity to\nGlacial Forcing in the CCSM4. Journal of Climate 26, 1901–1925.\nhttps://doi.org/10.1175/JCLI-D-11-00416.1\nGaiero, D. M. (2007). Dust provenance in Antarctic ice during glacial periods: From where in\nsouthern South America? Geophysical Research Letters, 34(17).\nGrousset, F. E., & Biscaye, P. E. (2005). Tracing dust sources and transport patterns using Sr,\nNd and Pb isotopes. Chemical Geology, 222, 149-167.\nKoffman, B. G., Saylor, P., Zhong, R., Sethares, L., Yoder, M. F., Hanschka, L., . . . Osterberg,\nE. C. (2022). Provenance of Anthropogenic Pb and Atmospheric Dust to Northwestern North\nAmerica. Environmental Science & Technology, 56(18), 13107-13118.\ndoi:10.1021/acs.est.2c03767\nReviewer #4 (Remarks to the Author):\nI co-reviewed this manuscript with one of the reviewers who provided the listed reports. This\nis part of the Nature Communications initiative to facilitate training in peer review and to\nprovide appropriate recognition for Early Career Researchers who co-review manuscripts.\nWe appreciate your contribution to this co-review.\nReferences\nBatchelor, C. L. et al. The configuration of Northern Hemisphere ice sheets through the\nQuaternary. Nat. Commun. 10, 3713 (2019).\nBrady, E. C., Otto-Bliesner, B. L., Kay, J. E. & Rosenbloom, N. Sensitivity to glacial forcing\nin the CCSM4. J. Climate 26, 1901-1925 (2013).\nFerrat, M. et al. Improved provenance tracing of Asian dust sources using rare earth elements\nand selected trace elements for palaeomonsoon studies on the eastern Tibetan Plateau. Geochim.\nCosmochim. Acta 75, 6374-6399 (2011).\nHuang, Z. et al. Short-cut transport path for Asian dust directly to the Arctic: a case study.\nEnviron. Res. Lett. 10, 114018 (2015).\nKim, K. et al. Greenhouse gas formation in ice wedges at Cyuie, central Yakutia. Permafr.\nPeriglac. Process. 30, 48-57 (2019).\nKoffman, B. G. et al. Provenance of anthropogenic Pb and atmospheric dust to northwestern\nNorth America. Environ. Sci. Technol. 56, 13107-13118 (2022).\nLambert, F. et al. Dust fluxes and iron fertilization in Holocene and Last Glacial Maximum\nclimates. Geophys. Res. Lett. 42, 6014-6023 (2015).\nMahowald, N. M. et al. Change in atmospheric mineral aerosols in response to climate: Last\nglacial period, preindustrial, modern, and doubled carbon dioxide climates. J. Geophys. Res.\n111, D10202 (2006).\nMurton, J. B. et al. A multimethod dating study of ancient permafrost, Batagay Megaslump,\neast Siberia. Quat. Res. 105, 1-22 (2022).\nPark, H. et al. A biogeochemical study of greenhouse gas formation from two ice complexes\nof Batagay Megaslump, East Siberia. Permafr. Periglac. Process. 35, 437-449 (2024).\nÚjvári, G. et al. Two possible source regions for central Greenland last glacial dust. Geophys.\nRes. Lett. 42, 10399-10408 (2015).\nYanase, W. & Abe-Ouchi, A. The LGM surface climate and atmospheric circulation over East\nAsia and the North Pacific in the PMIP2 coupled model simulations. Clim. Past 3, 439-451\n(2007).\nYang, J. W. et al. Origin of CO2, CH4, and N2O trapped in ice wedges in central Yakutia and\ntheir relationship. Permafr. Periglac. Process. 34, 122-141 (2023).\nZhao, X., Huang, K., Fu, J. S. & Abdullaev, S. F. Long-range transport of Asian dust to the\nArctic: identification of transport pathways, evolution of aerosol optical properties, and impact\nassessment on surface albedo changes. Atmos. Chem. Phys. 22, 10389-10407 (2022)."}, {"round": 2, "reviewer_comments": {"reviewer_1": "I am happy with the rebuttal. However, I am not fully convinced by (1) the age model of the sediment samples and (2) with the first paragraph of the discussion (lines 236-244). Please note, that not all researchers agree that the Yedoma deposits are of loess origin. Perhaps the unpublished age could support (1) and some more references could support the idea in (2).", "reviewer_2": "The authors have addressed my previous comments. I am happy to see that they have reanalyzed their samples for trace elements and provided more data on the fine grain size fractions. The revised discussion based on the new data and comments from Reviewers #1 and #3 is more clear and robust than in the previous version. I would accept this manuscript after addressing my following comments (one comment on the structure of the manuscript and a few minor note):\n- The Results section includes some discussion in lines 136, 139-140, 147, 164-171, and 195-209, i.e., the sections on trace elements and isotope ratios. The quartz O-isotope results section does not have this problem (the source identification is separated from the results). It would be good to have the same structure for all methods and move the trace element and isotope provenance interpretations to the “Dust source identification” section. (Or to use another solution to unify the structure for all methods.)\n- Line 165: “share a common provenance” with what? Greenland? Please clarify.\n- Lines 274-275 and Fig. S1: It is not evident what are the loess-like sediments in Fig. S1 – are they the Cenozoic sediments?\n- Lines 525-526: the errors of the isotope ratios are very large (6 for Sr ratio and 4 for Nd)", "reviewer_3": "Second review of Kim et al, Nature Communications\nSeptember 2025\nKim and coauthors have overhauled the manuscript in response to reviewer feedback, and the resulting paper presents clear interpretations based on robust data. I appreciate the authors’ openness to feedback and substantial effort in revising the paper. I believe this work represents an important contribution to the paleoclimate literature, and is ready for publication at this time.\nOne minor comment:\nIn figure 3, the <5 um data from Batagay are not visible. Perhaps double-check that they are included here?", "reviewer_4": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts."}, "author_response": "Point-by-point response (responses highlighted in orange)\nREVIEWER COMMENTS\nReviewer #1 (Remarks to the Author):\nI am happy with the rebuttal. However, I am not fully convinced by (1) the age model of the\nsediment samples and (2) with the first paragraph of the discussion (lines 236-244). Please note,\nthat not all researchers agree that the Yedoma deposits are of loess origin. Perhaps the\nunpublished age could support (1) and some more references could support the idea in (2).\n(1) Thank you for this important comment. In the revised version, we have incorporated new\nradiocarbon ages obtained from plant macro remains in the Batagay ice wedges (Lines 71-76;\nMethods; Supplementary Notes; Supplementary Table 2). These ages consistently point to\nmiddle to late MIS 3 (~45-30 ka), significantly refining our previous age estimates (~60-27 ka\nfor the entire Upper Ice Complex; Murton et al., 2022) and providing stronger chronological\nconstraints for the Batagay ice wedges studied. We believe this addition significantly\nstrengthens our age model.\n(2) Thank you for pointing out the ongoing debate regarding the origin of Yedoma deposits. In\nthe revised Discussion, we have clarified that Yedoma is considered not exclusively of loess\norigin. We also added additional references to support this broader interpretation.\nReviewer #2 (Remarks to the Author):\nThe authors have addressed my previous comments. I am happy to see that they have\nreanalyzed their samples for trace elements and provided more data on the fine grain size\nfractions. The revised discussion based on the new data and comments from Reviewers #1 and\n#3 is more clear and robust than in the previous version. I would accept this manuscript after\naddressing my following comments (one comment on the structure of the manuscript and a few\nminor note):\n- The Results section includes some discussion in lines 136, 139-140, 147, 164-171, and 195-\n209, i.e., the sections on trace elements and isotope ratios. The quartz O-isotope results section\ndoes not have this problem (the source identification is separated from the results). It would be\ngood to have the same structure for all methods and move the trace element and isotope\nprovenance interpretations to the “Dust source identification” section. (Or to use another\nsolution to unify the structure for all methods.)\nWe appreciate your favorable and detailed review and thoughtful suggestion regarding the\nstructure of the Results section. In the revision, we unified the structure by organizing the\nResults into three method-based subsections, each presenting both data and interpretation. The\nDiscussion then focuses on broader climatic implications beyond the proxy-level\ninterpretations. We believe this approach improves readability and aligns well with the\njournal’s style.\n- Line 165: “share a common provenance” with what? Greenland? Please clarify.\nRevised to clarify that the common provenance is East Asian, shared with the Greenland dust.\n- Lines 274-275 and Fig. S1: It is not evident what are the loess-like sediments in Fig. S1 – are\nthey the Cenozoic sediments?\nThe term ‘loess-like sediments’ was intended to indicate Yedoma, but it has been deleted to\navoid confusion, as it was not essential to our interpretation.\n- Lines 525-526: the errors of the isotope ratios are very large (6 for Sr ratio and 4 for Nd)\nThe error ranges were originally expressed using the convention of reporting uncertainties on\nthe last digits. Thus, ± 6 corresponds to ± 0.000006 for Sr, and ± 4 corresponds to ± 0.000004\nfor Nd. To avoid ambiguity, we have revised the notation to report the full uncertainties\nexplicitly.\nReviewer #3 (Remarks to the Author):\nSecond review of Kim et al, Nature Communications\nSeptember 2025\nKim and coauthors have overhauled the manuscript in response to reviewer feedback, and the\nresulting paper presents clear interpretations based on robust data. I appreciate the authors’\nopenness to feedback and substantial effort in revising the paper. I believe this work represents\nan important contribution to the paleoclimate literature, and is ready for publication at this time.\nOne minor comment:\nIn figure 3, the <5 um data from Batagay are not visible. Perhaps double-check that they are\nincluded here?\nWe sincerely thank you for the positive evaluation of our revised manuscript and for the careful\nobservation. The <5 μm data from Batagay were included in the original figure, but their values\nare nearly identical to those of the <10 μm fraction and were obscured by overlapping symbols.\nWe have revised Fig. 3 to ensure that the <5 μm data are now clearly visible.\nReviewer #4 (Remarks to the Author):\nI co-reviewed this manuscript with one of the reviewers who provided the listed reports. This\nis part of the Nature Communications initiative to facilitate training in peer review and to\nprovide appropriate recognition for Early Career Researchers who co-review manuscripts.\nWe appreciate your contribution to this co-review.\nReferences\nMurton, J. B. et al. A multimethod dating study of ancient permafrost, Batagay Megaslump,\neast Siberia. Quat. Res. 105, 1-22 (2022)."}, {"round": 3, "reviewer_comments": {"reviewer_1": "I saw that you are not really want to add more details concerning the chronologgical frame. However, as the other reviewers do not address this point I agree with this version."}, "author_response": ""}]

Decision letter