Pleistocene terrestrial warming trend in East Asia linked to Antarctic ice sheets growth

Domain: earth_science
Published: 2025-09-10
Editorial outcome: major_revision

Abstract
How terrestrial mean annual temperature (MAT) evolved throughout the past 2 million years (Myr) remains elusive, limiting our understanding of the patterns, mechanisms, and impacts of past temperature changes. Here we report a ~2-Myr terrestrial MAT record based on fossil microbial lipids preserved in the Heqing paleolake, East Asia. The increased amplitude and periodicity shift of glacial-interglacial changes in our record align with those in sea surface temperature (SST) records. However, its long-term warming trend (1.0 °C/Myr, 95% CI = 0.4–1.7 °C/Myr) during 1.8–0.6 Myr ago diverges from the contemporaneous SST cooling. We propose that the Pleistocene warming in East Asia primarily resulted from regionally enhanced heat input and greenhouse effect of rising water vapor driven by Antarctic ice sheets (AIS) growth, highlighting the important climatic effect of AIS evolution. Such long-term warming across the Mid-Pleistocene Transition might have been beneficial for archaic humans’ flourishing in Eurasia.

Introduction
The Pleistocene, about 2.6 million years (Myr) to 11,700 years ago, is an important geological epoch that witnessed the evolution and expansion of our genus Homo1–4. During this epoch, the cyclicity of Earth’s climate shifted from 41 thousand years (kyr) to 100 kyr with an increasing glacial-interglacial contrast, as inferred from the δ18O record of benthic foraminifera, which reflects the combined signal of deep-sea temperature and land-ice volume or sea level5. In the marine realm, paleotemperature reconstructions based on alkenones, Mg/Ca, and faunal proxies in marine sediments indicate that sea surface temperature (SST) generally decreased with a similar rhythm to the benthic δ18O record6–8. In the terrestrial realm, however, due to the scarcity of suitable proxies and high-quality archives, the long-term Pleistocene temperature history remains insufficiently understood. This limits our understanding of the pattern and mechanism of global climate change during this critical geological epoch, as well as the effects of past temperature changes on the evolutionary trajectory of the human species.

Branched glycerol dialkyl glycerol tetraethers (brGDGTs), a suite of membrane-spanning lipids synthesized by heterotrophic bacteria, are emerging as a popular tool for quantifying past terrestrial temperatures9–12. This paleothermometer, developed and well-calibrated with natural climate gradients13,14, has been validated by microbial cultivation15,16 and molecular dynamics simulations17 to reflect physiological adaptation to temperature variations. Recently, the application of the brGDGT paleothermometer in a 3-Myr loess-paleosol sequence on the Chinese Loess Plateau (CLP) revealed an unexpected Pleistocene land warming18, diverging from most marine temperature records. This implies that global temperatures cannot be represented only by marine archives, and the incorporation of terrestrial temperatures is needed for assessing global temperature changes and trends. However, brGDGTs are argued to be likely affected by vegetation coverage and seasonality in soils at the mid-latitude CLP10, especially during glacial periods. Therefore, how glacial terrestrial temperature evolved during the Pleistocene remains largely unknown18. Hence, new terrestrial temperature records are still required to further decipher the characteristics of mean annual air temperature (MAT) evolution during the Pleistocene.

Here, we provide insights into Pleistocene terrestrial temperature evolution by analyzing brGDGTs from a well-dated lacustrine sediment core retrieved from the Heqing Basin (HB)19 (HQ, 26°34′ N, 100°10′ E, 2190 m a.s.l., 97% recovery) in southwestern China (Fig. 1, see “Methods” section). Our HQ MAT record generally resembles marine SST records at glacial-interglacial timescales; however, its long-term warming trend from 1.8 Ma to 0.6 Ma indicates a decoupling between terrestrial and marine temperatures. This long (~2-Myr), continuous, and highly resolved terrestrial MAT time series might provide a benchmark for Pleistocene terrestrial temperature variations from the Asian monsoon region that accommodates more than a fifth of the world’s population.

Results
Assessing non-thermal influences on the brGDGT paleothermometer

Despite the great potential of brGDGTs for paleotemperature reconstructions, the impacts of non-thermal factors, such as soil input, changes in water-column structure, water chemistry, and bacterial communities, and seasonal bias should be carefully evaluated prior to the quantitative application of this paleothermometer.

For the HQ core sediments, the influence of soil input on brGDGT-based temperature reconstruction appears to be negligible. In surrounding soils (Supplementary Fig. 1), brGDGTs are characterized by a higher degree of methylation (MBT) and a lower degree of cyclization (DC) than those in lake sediments in the Heqing paleolake (Supplementary Fig. 2a, b). Therefore, while potential soil brGDGT input can bias MBT and reconstructed temperature towards higher values, DC should be biased towards lower values. In our core, however, DC is weakly but positively correlated with MBT (r = 0.14, p = 0.01) and not correlated with reconstructed MAT (r = 0.06, p = 0.22) (Supplementary Fig. 3a, b). The ratio of hexamethylated to pentamethylated brGDGT (IIIa/IIa) can also be used to distinguish brGDGT provenance, and a value > 0.92 can generally indicate the aquatic origin of brGDGTs20. IIIa/IIa is > 0.92 for 97% samples in the HQ core (avg. 1.56 ± 0.38, N = 380), much higher than that in surrounding soils (avg. 0.10 ± 0.05, N = 12) (Supplementary Fig. 2c). Therefore, brGDGTs in the Heqing paleolake should be predominantly produced within the lake, and variations in brGDGT distributions are almost unaffected by soil input.

Within the Heqing paleolake, the impact of water-column structure, water chemistry, and bacterial community changes on brGDGT-based temperature reconstruction should also be minor. First, as methanogens produce relatively high amounts of GDGT-0, GDGT-0/crenarchaeol (GDGT-0/cren) ratio can be used to reflect the relative volume of the anoxic and oxic portions of the water column21–24. For 94% of the samples in the HQ core, the GDGT-0/cren ratio is below 1.5 (Supplementary Fig. 2d). This is lower and more stable than that in the Plio-Pleistocene sediments of Lake El’gygytgyn (LE)22 and the 250-kyr sediments of Lake Chala23, indicating a relatively stable lake water-column structure of the paleo Lake Heqing. Second, reconstructed temperature can be biased toward high values in lakes with high salinity (conductivity)14,25. The abundant carbonate preserved in the HQ core26 and relatively high CBT’ values (Supplementary Fig. 2e) indicate an alkaline paleolake. However, the occurrence of freshwater diatoms throughout the HQ core27 and negligible late-eluting isomers after 5-methyl and 6-methyl brGDGTs (which are generally high in brackish and saline lakes25) suggest a freshwater environment. Actually, in the global brGDGT dataset for freshwater lakes, while most lakes are alkaline, brGDGTs can faithfully track temperature, and there is no significant offset in reconstructed temperatures between lakes with pH = 7–8 and >8 (Supplementary Fig. 4). Furthermore, the effect of brGDGT isomerization (IR6ME), reflecting changes in bacterial community related to multiple non-thermal parameters, must be considered when assessing brGDGT methylation as a temperature proxy28. IR6ME ranges from 0.33 to 0.75 (Supplementary Fig. 2f), and it is slightly correlated with MBT’5ME (r = 0.33, p < 0.01) in the HQ core (Supplementary Fig. 3c), implying a likely impact of changes in bacterial community and IR6ME. However, the variations of MBT, MBT’5ME and MBT’6ME are quite consistent with each other in our core, particularly after 1.5 Myr ago (Ma) (Supplementary Fig. 5). This contradicts the opposite impacts of IR6ME on MBT’5ME and MBT (or MBT’6ME)29, suggesting that they reflect a common temperature signal, rather than the isomer effect.

Finally, a substantial influence of seasonality on the brGDGT paleothermometer can be excluded for the Heqing paleolake. Given the low latitude setting, the Heqing region experiences restricted monthly changes in air temperature (Supplementary Fig. 1), and when further considering the buffering effect of lake water, seasonal temperature changes could be even smaller. More importantly, it is generally believed that brGDGT-producing bacteria is active above freezing and therefore brGDGTs can record mean temperature above freezing (MAF) or mean lake water temperature (MLWT)11,14,29–31. At Heqing, the relatively high winter air temperature (7.5 °C) suggests that lakes in this region are likely ice-free year-round, and consequently, MAF or MLWT equals MAT. Two lines of evidence further indicate that the growth and preservation of these bacteria/lipids may not depend on seasonal temperature variations in non-freezing lakes: (i) in equatorial lakes spanning a MAT range of ca. 2–25 °C, no correlation between brGDGT concentration (possibly reflecting its production) and temperature is observed32, and (ii) in the global lake dataset, MBT’5ME correlates more strongly with MAF or MLWT than with mean summer temperature (MST), and additionally, reconstructed growth temperature approximates MAF or MLWT rather than MST (Supplementary Fig. 6).

Overall, brGDGTs in the Heqing paleolake appear to be ideal for tracing MAT variations due to the weak influences of non-thermal factors. The applications of different lacustrine calibrations based on various statistical methods11,14,29–31 show similar trends and amplitudes of MAT reconstructions, although the absolute values might differ (Supplementary Fig. 7). Nevertheless, we note that reconstructed MAT based on 4 calibrations11,14,30,31 is weakly but significantly correlated with IR6ME (p ≤ 0.05) (Supplementary Fig. 3e–h), pointing to a potentially minor impact of brGDGT isomerization on these calibrations. On the other hand, reconstructed temperature based on the recent calibration29, which may mitigate the isomer effect, has no correlation with IR6ME (r = 0.08, p = 0.14) throughout the core (Supplementary Fig. 3d), and therefore, this calibration was applied for quantitative temperature reconstruction. Furthermore, to rigorously constrain the potential effects of soil input and water-column structure changes, we excluded samples with IIIa/IIa < 0.9220 or GDGT-0/cren > 1.522,23 for the HQ core. A total of 23 samples were rejected, accounting for only 6% of the 380 samples (Supplementary Fig. 2i). The excluded samples are mainly from the top section of the core, in agreement with the substantial changes in lake depositional environment since ~0.15 Ma inferred from magnetic susceptibility33 (Supplementary Fig. 2j) and other proxies19,27.

Characteristics of Pleistocene terrestrial temperature variations

Our screened biomarker-based reconstruction, with an average resolution of ~5 kyr, shows that MAT at the HB varied from 5.8 °C to 15.0 °C during the past 2 Myr, mostly (93%) between 7.0 °C and 12.0 °C (Fig. 2a). On orbital timescales, the 100-kyr glacial-interglacial cycles gradually replaced the 41-kyr cycles, with strong periods of both 41 kyr and ~80–120 kyr during the Mid-Pleistocene Transition (MPT, 1.25 Ma to 0.7 Ma) (Supplementary Fig. 8). The average temperature amplitude increased from about 3 °C during the early Pleistocene to 4 °C at 1.0–0.2 Ma (Fig. 2a). Such orbital-scale variations of low-latitude terrestrial temperature, including both cyclicity and amplitude, closely resemble those in the global SST stack8, tropical SST stack6, and benthic δ18O5 (Fig. 2 and Supplementary Fig. 8). This coherent rhythm of terrestrial and marine temperatures indicates that they have followed a common control on orbital timescales during the Pleistocene epoch and confirms the reliability of our brGDGT-based quantitative temperature reconstruction at the HB. The emergence of the 100-kyr periodicity during the MPT, and its full establishment at ~0.6 Ma, possibly reflects an important role of high-latitude ice sheet influence34 on low-latitude terrestrial temperature variability since the MPT.

A notable feature of the long-term Heqing paleotemperature trend is that, both glacial and particularly interglacial temperatures became warmer from ~1.8 Ma to 0.6 Ma (Figs. 2a and 3a). Such a long-term land surface warming is at odds with the pronounced cooling in marine surface temperatures during this period (–2.5 °C/Myr for global SST8 and –0.8 °C/Myr for tropical SST6). A Mann–Kendall trend test (S = 4148, Z = 3.16, p < 0.01) suggests that the warming trend at the HB was statistically significant. This trend still exists when considering the analytical and calibration error of the brGDGT paleothermometer, as 1000 times of Monte Carlo simulations incorporating the 1.8 °C uncertainty all show warming trends, with an average value of 1.0 ± 0.3 °C/Myr (95% confidence interval = 0.4–1.7) (Fig. 3a, Supplementary Fig. 9), and the proportion of significant (p < 0.05) regressions is 78%. Moreover, various lacustrine calibrations11,14,29–31 yield similar warming trends ranging between 0.7 °C/Myr and 1.6 °C/Myr from 1.8 Ma to 0.6 Ma, and the average value (1.1 °C/Myr) is almost identical to that inferred by the calibration used in this study (1.0 °C/Myr). The above lines of evidence indicate that the long-term warming trend at the HB is statistically robust.

Given the close match of our biomarker-inferred MAT to marine SST records on orbital timescales (Fig. 2) and the minor impacts of non-thermal factors on the brGDGT proxy assessed above, the identified early to mid-Pleistocene terrestrial warming is unlikely due to the defect of the brGDGT paleothermometer. The Pleistocene Tsuga pollen record from the same core19 also lends strong support to our reconstructed temperature record based on microbial membrane lipids. Modern investigations show that Tsuga distribution in the Asian monsoon region is constrained by winter temperature at regions with sufficient precipitation19. Furthermore, MAT at the HB strongly depends on winter temperature (Supplementary Fig. 10). Therefore, Tsuga pollen can be used as a sensitive, albeit qualitative, temperature proxy in this region. The long-term trend in Tsuga content and its glacial-interglacial variation both align well with those in our reconstructed MAT (Fig. 2a, d and Supplementary Fig. 11). This further reinforces the robustness of the brGDGT-based quantitative temperature estimates.

The absence of a long-term land surface cooling during the past 2 Myr does not seem to be just a local phenomenon limited to the HB. A 1.74-Myr pollen-based MAT record from the Zoige Basin (ZB), eastern Tibetan Plateau35 (33° N) indicates a 1.4 °C/Myr warming trend (p < 0.01; 95% confidence interval = 0.6–2.1) before 0.6 Ma (Fig. 3b), using all modern pollen data from China and Mongolia as the training dataset. On the CLP, palaeotemperature reconstructions from eolian deposits at Lingtai (35° N) suggest a 0.8 °C/Myr warming (p < 0.05; 95% confidence interval = 0.1–1.8) during this period based on the brGDGT paleothermometer18, corroborated by a low-resolution carbonate clumped isotope record36 (Fig. 3c). Another low-resolution brGDGT-based paleotemperature record from the North China Plain37 indicates no obvious long-term trend during the Pleistocene, despite the complex changes in sedimentary facies. Beyond East Asia, available long Pleistocene terrestrial temperature records also show no obvious cooling trend from 1.8 Ma to 0.6 Ma or during the MPT; however, these records are generally fragmentary or argued to be affected by non-thermal factors (Supplementary Discussion). Moreover, in the marine realm, temperatures during 1.8–0.6 Ma were also relatively stable or slightly increased in the deep sea38–40 (except for the Atlantic record41) and the western Pacific warm pool8,42–45 (Supplementary Fig. 12). Therefore, long-term temperature trends at some terrestrial regions (such as East Asia), warm pool and deep sea, might have diverged from the general SST trend during the past 2 Myr. The divergent Pleistocene temperature trends, which have not attracted sufficient attention from the paleoclimate community previously, indicate that the Earth’s climate system has possibly evolved into a more complex mode since ~2 Ma.

Possible controls on long-term temperature variations in East Asia

The long-term warming trend during 1.8–0.6 Ma observed for the 3 East Asian records at Heqing, Zoige, and Lingtai, in contrast to the contemporaneous global sea surface cooling, cannot be primarily attributed to the relatively high elevation of these terrestrial records. Observational data and numerical models for global temperature variations suggest that, elevated land surfaces warm faster than those near sea-level during the past several decades46. During the last glacial maximum (LGM), GDGT-based temperature reconstructions from East African lakes show amplified cooling with elevation, resulting in a significantly steeper lapse rate than today47. Both modern and LGM data show that at higher elevations, temperature amplification is greater than near sea level, but the warming or cooling trends at different elevations cannot be inverted. Based on ERA5 reanalysis, HadCRUT5 dataset, and CMIP6 historical simulations (1959–2014), land surface warming is on average 16% higher at 2190 m a.s.l. than that at sea level across the tropics and subtropics (40° S to 40° N)46. Assuming a similar elevation-dependent warming at Heqing, the warming trend should be 0.9 °C/Myr at sea level, still opposite to the 2.5 °C/Myr cooling for global SST.

Atmospheric carbon dioxide (CO2) is considered the main greenhouse gas responsible for current global warming and the primary forcing for past temperature changes48. Based on the recent compilation of vetted and modernized data from various proxies48, no long-term trend in CO2 level is observed from 1.8 Ma to 0.6 Ma (Supplementary Fig. 13a). One might argue that this synthesis might mostly rely on records with higher density of datapoints, as its variation resembles that for the record inferred from δ13C of terrestrial C3 plant remains, which accounts for 30% of the total datapoints during 2.6–0.2 Ma (Supplementary Fig. 13a). To reconcile the potential artifact caused by this issue, as well as the systematic bias and large scattering of each work using different methods and archives, we further compiled a CO2 stack by normalizing 11 long Pleistocene CO2 reconstructions vetted by the CenCO2PIP Consortium48 (Supplementary Methods). This stack still indicates no long-term trend in CO2 level during the past 2 Myr (Fig. 4a). Such a relatively stable CO2 level can partially explain the absence of a long-term Pleistocene cooling on land, but is insufficient to drive the long-term terrestrial warming at East Asia (Fig. 3a–c).

We hypothesize that the long-term terrestrial warming trend from 1.8 Ma to 0.6 Ma in East Asia might be dynamically linked to Antarctic ice sheets (AIS) growth and its associated feedbacks. The growth of AIS at 2.0–0.6 Ma (Fig. 4b) could have resulted in substantial cooling and sea ice expansion in southern high latitudes49. The high-latitude SST cooling and its equatorward propagation through the Peru Coastal Current or the atmosphere and its thermal coupling within the ocean50 can then lead to pronounced SST decrease in the equatorial eastern Pacific, thus strengthening the tropical zonal SST gradient and Walker circulation (Fig. 4c). Enhanced Walker circulation (or the La Niña-like condition) can both promote relatively increased heat accumulation in the western Pacific (Supplementary Fig. 12c) under the background of global sea surface cooling (Fig. 3d), and strengthen Asian summer monsoons51,52. Changes in the cross-equatorial pressure gradient due to the asynchronous development of bipolar ice sheets can also strengthen Asian summer monsoon circulations49. The progressive strengthening of monsoons has been widely documented at the HB and CLP19,27,51,53 (Fig. 4e, f). As the Asian summer monsoon can transport warm and humid air masses (including water vapor) from tropical oceans (including the warm pool with increased heat accumulation) to the Asian continent54, an intensified summer monsoon can thus warm the continent through sensible heat flux and latent heat release55. Moreover, the rising water vapor could also amplify regional warming56,57 as it is an important greenhouse gas in the atmosphere. Our numerical simulation (Supplementary Methods) also shows that the expansion of AIS can potentially increase tropical zonal SST gradient and elevate surface temperature over much of the Eurasian continent, with an overall strengthening in the Asian summer monsoon (Supplementary Fig. 14), despite that it might be simplistic and may not exactly capture the real processes of AIS expansion.

In summary, during 1.8–0.6 Ma, both glacial and interglacial temperatures might have increased on land (particularly East Asia). This is likely driven by a series of processes caused by the AIS growth under a relatively long-term stable global CO2 level, highlighting the importance of AIS evolution on global climate change. Our quantitative MAT record challenges the recent climate model simulations3,58 which yield a decreasing trend in global terrestrial temperature during the past 2 Myr, forced with a modeled gradual lowering of atmospheric CO259 that differs from proxy-based paleo-CO2 reconstructions (Supplementary Fig. 13). Based on marine temperature reconstructions5–8 and climate model simulations3, it was believed previously that the global climate cooled during the Pleistocene and therefore the dispersal of hominins into extratropical regions during this period1,3,4,58,60 was thought to be related to improved adaptability of archaic humans to cold environments2,60. Based on our Heqing and some other terrestrial records (Figs. 3 and 4), however, the reconstructed long-term warming and wetting trends on land (at least Asian monsoon regions) imply that extratropical Eurasia might have gradually become more suitable for the survival of hominins from the early to mid-Pleistocene. This should have been directly beneficial for our ancestors to flourish in Eurasia across the MPT1,3,4,58,60, not necessarily requiring that they could adapt to climate stress such as extremely cold and arid environments. Particularly, the slightly increased glacial temperature might have facilitated hominins to survive through the prolonged glacial times, although cultural innovations might have also played an important role60. Moreover, our results highlight the possible divergent evolution of land surface temperatures (at least in some regions) and marine temperatures, and the processes involved could be helpful for projecting future temperature changes with regional patterns identified.

Methods
Study site, sampling, and chronology

The Heqing paleo-lake is located at the center of the HB in Yunnan Province, southwest China. Pilot geophysical surveys indicate that ancient sediments accumulated up to 700 m in the basin since the late Cenozoic, and therefore the basin might serve as a potential terrestrial archive in the Indian monsoon region61. At the HB, the mean annual, January, and July temperatures are approximately 13.8 °C, 6.8 °C, and 19.6 °C, respectively (Supplementary Fig. 1). The mean annual precipitation is 962 mm, with 80% occurring from June to September due to the influence of the Indian summer monsoon (ISM). The vegetation is dominated by northern subtropical evergreen broad-leaved forest19,26.

In 2002, a 665.83-m (calibrated depth) long sedimentary core (26°34′ 43″ N, 100°10′ 14″ E, 2190 m a.s.l.) was retrieved from the center of the lake basin using the internal piston technique to avoid twist and distortion of the sediment core27. The whole core recovery is higher than 97%19, allowing for high-resolution and continuous paleoclimatic reconstructions. Laminated greyish-green calcareous clay and silty clay dominate the core, with thin-bedded silt and fine sand layers, except that two intervals of sand layers with fine gravels occur at 372.5–371.9 m and 195.4–189.5 m. Aqueous herb pollen and freshwater diatoms are found throughout the sequence, suggesting that the sediments were of typical lacustrine origin19,27,62. Moreover, 12 surface soils were collected surrounding the Heqing paleolake in 2025 (Supplementary Fig. 1). For each soil sample, three randomly collected subsamples (upper 5 cm) were pooled and mixed to make one composite sample representing that location.

The chronology of HQ drilling core has been well-established by magnetostratigraphy, radiocarbon dating, and astronomical tuning19. Briefly, paleomagnetic measurements of the thermal demagnetization were used to generate the geomagnetic polarity sequence of the HQ core, and the framework of the core was then established by correlating it with the geomagnetic polarity time scale (GPTS)63. The Matuyama/Gauss (M/G) boundary (~2.6 Ma) is located at 614.47 m, indicating that the age of the 665.83-m core can be extended back to the Pliocene epoch. Combined paleomagnetic and radiocarbon analysis identified that the Laschamp Excursion event (~40 ka64) occurs at ~4.5 m. Finally, a refined astronomical time scale was developed by simultaneously tuning the filtered 41- and 21-kyr components of the Tsuga pollen content to Earth’s orbital obliquity and precession parameters19.

GDGT analysis and proxy calculation

Generally, 1–3 g homogenized sediment and soil samples with a known amount of C46 internal standard65 were extracted with dichloromethane (DCM):methanol (9:1) using a Dionex™ ASE™ 350 at 100 °C and 1500 psi. The total lipid extract was then subject to base hydrolysis, and the extracted neutral fraction was eluted by n-hexane and MeOH:dichloromethane (1:1, v/v) on a silica gel column to separate it into a polar and polar fractions. After filtration, the polar fraction was analyzed on a high-performance liquid chromatograph/atmospheric pressure chemical ionization-mass spectrometer (HPLC/APCI-MS) system (with a Shimadzu LC-MS 8030) at the IEECAS. GDGTs were separated on two coupled silica columns (250 mm × 4.6 mm, 3 μm; GL Sciences Inc.) using isopropanol and n-hexane as elutes18. Selected ion monitoring (SIM) mode was used to target specific [M+H]+ ions for GDGTs and the internal standard (C46), and subsequently GDGTs were quantified by integration of the peak area of [M+H]+ ions, and comparison to that of C46.

The MBT, MBT’5ME, MBT’6ME, DC, CBT’, and IR6ME indices of brGDGTs were calculated as follows13,66–68:

MBT = (Ia + Ib + Ic) / (Ia + Ib + Ic + IIa + IIb + IIc + IIIa + IIIb + IIIc) (1)

MBT’5ME = (Ia + Ib + Ic) / (Ia + Ib + Ic + IIa + IIb + IIc + IIIa + IIIb + IIIc) (2)

MBT’6ME = (Ia + Ib + Ic) / (Ia + Ib + Ic + IIa’ + IIb’ + IIc’ + IIIa’ + IIIb’ + IIIc’) (3)

DC = (Ic + IIc + IIc’ + IIIc + IIIc’) / (Ia + Ib + Ic + IIa + IIb + IIc + IIa’ + IIb’ + IIc’ + IIIa + IIIb + IIIc + IIIa’ + IIIb’ + IIIc’) (4)

CBT’ = log((Ic + IIa’ + IIb’ + IIc’ + IIIa’ + IIIb’ + IIIc’) / (Ia + IIa + IIIa)) (5)

IR6ME = (IIIa’ + IIa’ + IIIb’ + IIIc’ + IIb’ + IIc’) / (IIIa + IIa + IIIa’ + IIa’ + IIIb + IIIc + IIIb’ + IIIc’ + IIb + IIc + IIb’ + IIc’) (6)

Fractional abundances of individual brGDGTs, GDGT proxies, and brGDGT concentration were provided in Figshare (DATA AVAILABILITY). The IR6ME values vary from 0.33 to 0.75 for our brGDGT data, and therefore, we applied the recent calibration29, which can effectively correct the isomer effect on the brGDGT paleothermometer. Replicated pretreatment and analysis of 10 samples suggests an average analytical error of 0.3 °C, while the RMSE for the calibration is 1.8 °C. Therefore, we conservatively compounded the calibration error with analytical error such that the total error for our temperature reconstruction = sqrt(calibration error^2 + analytical error^2)69 = 1.8 °C. We should point out that the calibration error is possibly caused by the uncertainties in obtaining growth temperature for each sample in the calibration dataset, as well as the global spread of samples and the accompanying large variations in other non-thermal environmental parameters. At a single site and for a specific core, GDGTs can more accurately record the relative temperature changes (such as the temperature offsets or trends) than the absolute values, as it can reduce systematic calibration error and site-specific effects47,69,70. Monte Carlo simulations were further performed on Python to calculate the uncertainty for the linear trend of temperature variation during 1.8–0.6 Ma (CODE AVAILABILITY), under the 1.8 °C error of absolute temperature values.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "The manuscript by Wang et al. presents new estimates of terrestrial mean annual temperatures (MAT) from a low-latitude site of China covering the last 2 Ma. The results add to the growing list of arguments for a long-term decoupling of regional terrestrial temperatures from benthic temperature trends and changes in ice volume during the Middle Pleistocene. The novel aspects of this study include namely the geographic location of the dataset, which represents the first MAT estimate for the low latitudes of Eurasia. The low latitude setting makes this dataset valuable due to a relatively weak seasonal bias (aliasing), but this part of the manuscript needs a more careful argumentation, in my opinion (please see “specific comments” below).\n\nThe manuscript is well written; a few typos and stylistic issues are listed below. I would also suggest improvements to the structure of argumentation (please see below).\n\nMethods are described adequately, in my opinion, and conclusions appear supported by the data, although I am not able to fully evaluate veracity of the GDGT proxy due to my limited expertise. The hypothesized mechanism of the long-term temperature decoupling builds upon previous literature (which is referenced), and is partly supported by paleoclimate model in the supplement.\n\nThe results represent an important contribution to our understanding of the climate evolution and high–low latitude interactions during the Pleistocene. I enjoyed reading about the proposed implications for the migration of hominins to Eurasia.\n\nSPECIFIC COMMENTS:\n1) brGDGT proxy at Heqing\nThe authors propose that the low-latitude lacustrine record of brGDGT is not strongly affected by seasonality (line 72), which seems reasonable given the low latitude setting. However, considering the sensitivity of MAT to winter temperatures at the Heqing site (line 105), I would expect some discussion on the origin of brGDGT in the context of seasonal variations in temperature and precipitation. The discussion on lines 146-163 appears incomplete. Please explain: are the GDGT-bearing bacteria autochthonous to the lake or were the lipids transported to lake from soil profiles? What is the role of monsoonal seasonality in the growth and preservation of these bacteria/lipids? I understand the argument with Tsuga content on lines 154-157, but considering that this winter proxy varies on glacial/interglacial time scales, is it reasonable to neglect seasonality as one of the controls on the GDGT dataset? Please try to address these questions in the discussion.\n2) Structure of argumentation\nThe section “Possible controls….” (lines 146-..) includes the main discussion of the mechanism of temperature decoupling. The first paragraph, addressing the possible seasonal bias in the GDGT proxy, does not fit here. I would suggest moving this paragraph higher, as a separate section (perhaps “The role of seasonality….” or “Seasonal bias….”?).\n3) Language\nL20-24: this is a terrible sentence; please rephrase, split in two\nL36: “flourish” is a verb; please rephrase “facilitated the flourish”\nL46: perhaps not necessary to explain that we inhabit the terrestrial realm.\nL90: “full” instead of “fully”\nL132-136: sentence too long, hard to understand; please rephrase\nL192: “Progressive” instead of “progressively”\nL199: “albeit quite qualitatively”: what do you mean? please explain", "reviewer_2": "Wang et al. show a new Pleistocene (2 - 0.2 Ma) terrestrial temperature reconstruction from a paleolake in southwestern China using fossilized microbial lipids (brGDGTs). The study presents a valuable high-resolution temperature record from a region and an archive (land temperatures) where there is little long-term continuous Pleistocene temperature reconstruction. They hypothesized that Antarctic Ice Sheet expansion is the cause/mechanism of a warming during the MPT in terrestrial archives, which they differ from Global SST. However, I don’t think that the hypothesized mechanisms presented here, the references of additional studies to support their hypothesis and the extended data support their study/hypothesis. I have a lot of main concerns and I think a re-evaluation of what I think is an over-interpretation of the data needs to be done.\n\nMain comments:\nMy main concern is the over-interpretation of the temperature change seen in the record. When taking into account the RMSE of the calibration and standard deviation of the data, its hard to see how this warming can be separated from the natural variability of the reconstructed temperature. A 1°C temperature change from a proxy that has 1.8°C (keep in mind this is +/- 1.8°C) it's a big stretch in interpreting significant temperature changes to claim such mechanisms/conclusions.\nSecond, I am concerned about the references. First, they are not only wrong (the number doesn't correspond to the reference), but also I could not find the same data or information reported by the references in some cases.\n1. Lake Baikal reference number is wrong, and the closest reference of it doesn’t show the BioSi reconstructions that are shown here in Figure 3. The paper uses Biogenic Si to identify glacial and interglacial sections but it has not been used as a long-term temperature reconstruction. This is mostly because BioSi is subjected to dissolution, so you can't use the abundance of it to say that there is a temperature trend over time, you use it to identity warmer intervals than others to then do cyclo-stratigrpahy or studies like that, not to infer quantitative temperature changes over time.\n2. Lake Malawi, the proxy used here is TEX86 which has its own issues in freshwater lakes, but more importantly, the original paper doesn’t claim to have an increase in temperature because the variability in the data is within the uncertainty (2sigma = 0.8°C). Additionally, this study clearly showed CO2 as the main driver of significant temperature changes along the record and the overall conclusion of it had to do more with a wetter/drier climate than temperature changes.\n3. Lake El'gygytgyn: this warming rate you mention here 1. Is not significant (see p-value) and the record doesn’t show cooling around the MPT (in agreement with your hypothesis) but also it does not show warming. The main change that happens at this high-latitude site is a change in hydrological conditions.\n4. In line 435, reference 24, this paper doesn’t show anything about the formation and demise of the Heqing paleolake. I could not find such a reference. Also, I don't know why you dismissed those intervals? Even though they don't represent a full lake according to what you said they could give you more information about changes during key periods of time (last interglacial to LGM and Plio-Pleistocene) that have been shown to have a more extreme or a more drastic change that could help differentiate noise vs. signal.\n5. Reference 81 and 82. These are not peer-review articles. 81 is a public-facing article from a science journalist and 82 is a conference abstract. I don’t think you should cite non-peer review references in a manuscript submitted to Nature Communications.\nThird, one of your data that supports your hypothesis is your extended data figure 6 which is the results of the model output of PI-AIS(PI). First, I think the figure should benefit from having labels (“a”, “b”, etc…) and a more descriptive figure caption. Second, the results in this figure do not clearly support your hypothesis or the figures should be presented differently. I think you could benefit from having a box or an arrow that can show what you mean in the text. For example, you have “shows that the expansion of AISs can potentially increase tropical zonal SST gradient”, where in the figure you can see that? I don’t see these maps and it is obvious to me to see such an increase in tropical zonal SST. Also, you have “elevate surface temperature over Eurasia” which regions are you talking about because there is a combination of warm and cold regions over Eurasia. You have “with an overall increase in water vapor in the Asian monsoon region”, again, highlight the regions you are talking about in these maps because I see some strong red colors over India/Tibet but a blue color around South China where I think your core comes from. Anaways, I don't see how these results clearly support your statements. By the way, next to the water vapor panel there is an “x” above 30N, what's that?\n\nMinor comments:\nAdd elevation in abstract? I think that when talking about temperature reconstruction its good to know if the terrestrial temperatures are near sea level or high elevation sites.\nAdd modern MAT in the figures to see how it compares with your reconstructed temperatures? The general thought is that the last million years were colder than today…. So I want to see how modern MAT looks with your reconstructed temperature and if your estimate is colder or warmer than that as your present absolute values.\nYou used the Global SST from Clark, but they also present SST compilations by basin. I think that rather than using individual cores near your location you can add how the SST evolution in the Warm Pool looks in comparison with your record. Then, you can evaluate other mechanisms of why you don't see a clear temperature change over the MPT like other global records.\nLine 186-187: you are claiming that there is a decrease in SST in the equatorial eastern Pacific that is strengthening the tropical zonal SST gradient and walker circulation, but when looking at Figure 4c.. 1. I think the records should go all the way back to the beginning of the Pleistocene, and 2. you can have that data with the new Global SST compilation by basin from Clark et al. 2024.. And probably highlight where the “pronounced decrease” happens because with my eyes, in that figure, I don’t see any “pronounced” change.\nYou report a 1°C/myr… but what's the error or standard deviation of this?\nLine-by-line\nLine 60-61: “This implies that Pleistocene global temperature, or at least terrestrial temperature, cannot be simply represented by marine temperature.” I think you should re-arrange this sentence by saying something like global temperatures cannot be represented only by marine archives and the incorporation of terrestrial temperatures is needed for assessing global temperature changes and trends. Or something along the lines that global temperature are both terrestrial and marine, not that terrestrial temperatures are not represented by marine (that is obvious)\nLine 62: Do you mean glacial-interglacial? Or just glacial? Is just strange to only mention glacial if you are referring to the entire pleistocene. Also that sentence could be two sentences rather than one.\nLine 69: what's the elevation?\nLine 80: looking at the SD Fig.1. Seems to me that the gradual transition really starts at ~1.2Ma in your record… not before… no?\nLine 89-92: is there a reference to cite here? As it is written it seems like there is a need for a larger evidence of that high-latitude ice-volumen forcing .\nLine 197: reference?\nLine 704: what is ESL, I don’t see it defined anywhere.", "reviewer_3": "Review of Wang et al. for Nature Communications\nJoseph B. Novak\nRecommendation\nReject and encourage resubmission.\nSummary\nWang et al.’s manuscript entitled “Pleistocene terrestrial warming trend linked to Antarctic Ice Sheets Growth” presents a 2-million-year terrestrial paleotemperature record from Heqing paleolake in southwestern China. The reconstructed paleotemperatures show a warming trend, rather than cooling, over the 1.8–0.6 Ma interval, in contrast to marine sea surface temperature records, which the authors attribute to dynamical changes in the Earth’s atmospheric circulation in response to Antarctic Ice Sheet growth.\n\nThe lack of a rigorous assessment of the branched GDGT biomarker distributions used to generate the paleotemperature record is seriously concerning. While the authors argue that the similarity between the reconstructed paleotemperatures to a pollen record in the same sediment core indicates that the brGDGTs are primarily recording temperature, I remain unconvinced, especially since this core comes from what appears to have been an alkaline lake based on the occurrence of carbonate sediments (Shen et al., 2007; ref. 52 in this manuscript). The presentation of the pollen data on a log-scale is somewhat odd and, possibly, misleading since pollen data are usually presented on a linear y-axis scale.\n\nA thorough assessment of any possible non-thermal influence on the brGDGT distributions in this lake is fundamental to this study. The lack of this needed supplementary discussion ultimately motivates my recommendation to reject the manuscript. However, the data presented here hold the potential to be a landmark dataset in the field if the authors can show that these non-thermal factors are not influencing the brGDGT biomarkers here. Therefore, I encourage the resubmission of this manuscript after my comments are addressed.\n\nMajor Comments\nExtended Data Figure 3: Why is the Tsuga data plotted on a log scale? This is odd to me since pollen data are typically plotted on a linear scale. Is there a justification for this or is it simply to present that data in such a way that they appear to closely resemble the brGDGT MAT reconstruction? Similarly, is the strength of the correlation shown in the scatterplot dependent on the log transformation of the Tsuga pollen data? Is there perhaps some sort of bulk geophysical proxy data (magnetic susceptibility, bulk density) that could be used to make this comparison more effectively?\nL146 and Figure 3: The authors make a statement here regarding “the absence of a long-term terrestrial cooling during the past 2 Myr.” However, the data presented in the manuscript only represent a relatively small number of locations and narrow band of latitudes. In Figure 3, the authors show data from five sites. One dataset (Lake Baikal) is not a paleotemperature dataset (see my comment below). The remaining four datasets are from the tropics or near tropics, three of which are from China spanning a very narrow range of latitude (27–35°N). So, essentially, are the authors claiming that Southern China and Eastern Africa are representative of terrestrial temperature change throughout the entire Earth? This is unlikely, considering that modern climate change is resulting in remarkably different rates of temperature change in the high latitudes vs. the tropics. See also the pollen paleotemperature record from Lake El’gygytgyn, which shows a long-term cooling since the Pliocene (see Fig. 3d of Daniels et al., 2021 shows this nicely [https://doi.org/10.1002/jqs.3347]). Although these data do not sample every glacial-interglacial cycle, they appear to directly contradict the claim made here and are not discussed in the manuscript.\nL457–463: Why is there no supplementary text or figures showing the long-term trends in IR6Me, CBT’, brGDGT concentration and GDGT-0/Cren ratio in these samples? It is very important to understand the potential for non-thermal factors to influence brGDGT paleotemperature reconstructions, especially in what the authors consider a “terrestrial MAT time series benchmark for Pleistocene terrestrial temperature variations.”\nThere are several important factors that must be discussed for the community to understand whether the brGDGT distributions are accurately capturing temperature. These include: (1) brGDGT provenance; (2) the potential for changes in lake water chemistry to affect the brGDGT distributions; (3) whether there were changes in other aspects of the brGDGT distributions that are correlated with the warming inferred between ~1.2–0.2 Ma in Heqing Basin.\nFor example, the brGDGT paleotemperature reconstruction method used here (developed by the same lead author) is supposed to disentangle the relative contributions of 5-methyl and 6-methyl brGDGT producers when estimating paleotemperatures (i.e., remove the potential temperature bias from multiple brGDGT-producing bacterial communities contributing lipids to sediment). Are the resulting paleotemperature estimates from this method correlated with IR6Me, CBT', BIT, etc. in these samples? If so, does this imply that there is a substantial non-thermal influence on the temperatures reported here that is not accounted for by this method? If not, does that mean the method is working? We do not know because this is not explored.\nThe overarching point of this comment is that there is not sufficient information provided here for me (or anyone else) to judge whether the brGDGT distributions are authentically capturing temperature in the Heqing paleolake record. This is particularly important to consider since the sediments in this lake core are calcareous clays, suggesting that the lake was alkaline. These alkaline lakes appear to be especially challenging environments for brGDGT paleotemperature reconstruction, for example Lin et al. (2024) [https://doi.org/10.1016/j.earscirev.2024.104694]. Indeed, Shen et al. (ref. 52 here) report large changes in sedimentary carbonate content in this lake core. Shen et al. described substantial changes in the amplitude of these sedimentary carbonate cycles through time and the deposition of gravels associated with regional mountain uplift throughout the core. Are these sedimentary features, indicative of changes in lake water chemistry and, perhaps, changes in brGDGT provenance, respectively, related to any aspects of the paleotemperature record presented here?\nIn my view, this manuscript cannot pass review until the potential non-thermal influence on the brGDGT distributions is addressed. I appreciate the huge amount of effort that went into analyzing this dataset and I strongly encourage the authors to address these comments and resubmit their work. Long terrestrial paleoclimate records are a rare and special thing with the potential to capture the thought and attention of the scientific community. This is why we must treat them carefully, and critically, to be sure about their underlying quality.\nSupplementary data: Why is there no supplementary data table with the reconstructed temperatures and underlying brGDGT distributions? It is standard practice to share this information.\nMinor Comments\nL19: “Our knowledge of Earth’s temperature history” rather than “knowledge on.”\nL36: “flourishing” rather than “flourish.”\nL42 and elsewhere: The SI convention now is to italicize the δ in δ18O.\nL73: timeseries should be written as one word, not two.\nL90: “full establishment” rather than “fully establishment.”\nL93: Consider rephrasing to: “A notable feature of the long-term Heqing paleotemperature trend is that…”\nL96: “trend” in “pronounced cooling trend” can be removed as it is unnecessary.\nL104–106: I do not really follow what you mean here. Mean annual temperature by definition incorporates the temperature of all months equally. Is this statement trying to parse the slight difference in the correlation strength between MAT and summer vs. winter temperature? This seems like a bit of a stretch to me since the difference in Pearson’s r here is rather minor.\nL116–117: does this imply that a different result is obtained if a more restricted pollen training dataset is used?\nL124–126: The Lake Baikal biogenic silica record does not track paleotemperature directly and certainly not in a linear fashion. I therefore urge extreme caution in interpreting this record as a paleotemperature proxy dataset as is done here. A major drawback of this data type is that it cannot distinguish relative differences in how cold individual glacial periods were. This is because it is impossible to have less than 0% biogenic silica content, meaning that any potential differences in temperature between glacial periods is missed by the proxy signal. You will notice that this is essentially the value of every glacial period (at least the stadials, interstadials have slightly higher content) over the entire 1.8-million-year period covered by the Prokopenko et al. 2006 record you reference here.\nSee Prokopenko et al. 2001 [doi:10.1006/qres.2000.2212] for a thorough discussion. See also Battarbee et al. 2005 [https://doi.org/10.1016/j.gloplacha.2004.11.007] for an explanation of the nonlinear nature of the diatom signal in Lake Baikal sediments due to the dissolution of ~99% of diatoms prior to their burial in Lake Baikal sediments.\nL126–129: After looking at this paleotemperature record again, the claim made here about Lake El'gygytgyn is a stretch. This is reflected by the weak p-value, which does not compel me to think the “trend” discussed here is statistically significant. This statement also appears to ignore the pollen paleotemperature record from Lake El’gygytgyn, which shows a long-term cooling (see Fig. 3d of Daniels et al., 2021 https://doi.org/10.1002/jqs.3347).\nL135: I do not understand what “or (and)” means.\nL157–159: I question whether this reference is appropriate. The study here is a discussion of spatial patterns of seasonal temperature change in Eurasia, which is not really relevant to the discussion of whether warm and cold season temperatures can evolve in the same direction that it is invoked to support in this manuscript.\nL146–163: This discussion seems to largely miss an important point: we fundamentally do not understand the seasonality of the brGDGT temperature proxy. See discussion in Zhao et al., 2023 [https://doi.org/10.1016/j.quascirev.2023.108124]. In the tropics this is not a problem since seasonality is small, but in the middle and high latitudes this leads to a weak relationship between MAF temperature and MBT’5Me (Zhao et al., 2023).\nL168–173: This is hard to follow, please clarify.\nL174–177: Again, I urge caution in interpreting the Lake Baikal biogenic silica record as a paleotemperature proxy. See my comment above.\nL222–224: Tropical temperatures in China and Africa, not terrestrial temperatures in toto.\nFigure 1: Please make the arrows a color other than bright green on the red background. The arrows are not visible to colorblind people.\nFigure 2: It is not necessary to overlay your temperature record onto the other records. They can be compared simply by looking at the differences in their trends.\nExtended Data Figure 4: Please choose a colorblind figure color palette for panel B.\nExtended Data Figure 7: Wouldn’t the topical calibration of Zhao et al. (2023) be more appropriate here? The global calibration is intended for deep time applications."}, "author_response": "Point-by-point response to the reviewers’ comments\nWe greatly appreciate the 3 reviewers for constructive comments concerning our\nmanuscript entitled “Pleistocene terrestrial warming trend linked to Antarctic Ice Sheets\ngrowth” (NCOMMS-24-85101-T). We have addressed those comments carefully and\nmade corrections or explanations accordingly. The following details our point-by-point\nresponses (in blue) to those comments, while in the main text, our changes are noted by\n“track changes” (line numbers mentioned here refer to the marked manuscript). We are\ngrateful for those comments and suggestions that further improved the quality of our\nwork.\nReviewer #1 (Remarks to the Author):\nThe manuscript by Wang et al. presents new estimates of terrestrial mean annual\ntemperatures (MAT) from a low-latitude site of China covering the last 2 Ma. The\nresults add to the growing list of arguments for a long-term decoupling of regional\nterrestrial temperatures from benthic temperature trends and changes in ice volume\nduring the Middle Pleistocene. The novel aspects of this study include namely the\ngeographic location of the dataset, which represents the first MAT estimate for the low\nlatitudes of Eurasia. The low latitude setting makes this dataset valuable due to a\nrelatively weak seasonal bias (aliasing), but this part of the manuscript needs a more\ncareful argumentation, in my opinion (please see “specific comments” below).\nThe manuscript is well written; a few typos and stylistic issues are listed below. I would\nalso suggest improvements to the structure of argumentation (please see below).\nMethods are described adequately, in my opinion, and conclusions appear supported by\nthe data, although I am not able to fully evaluate veracity of the GDGT proxy due to\nmy limited expertise. The hypothesized mechanism of the long-term temperature\ndecoupling builds upon previous literature (which is referenced), and is partly\nsupported by paleoclimate model in the supplement.\nThe results represent an important contribution to our understanding of the climate\nevolution and high–low latitude interactions during the Pleistocene. I enjoyed reading\nabout the proposed implications for the migration of hominins to Eurasia.\nRe: Thanks for your positive assessment of our work, and please see below our response\nto your comments.\nSPECIFIC COMMENTS:\n1) brGDGT proxy at Heqing\nThe authors propose that the low-latitude lacustrine record of brGDGT is not strongly\naffected by seasonality (line 72), which seems reasonable given the low latitude setting.\nHowever, considering the sensitivity of MAT to winter temperatures at the Heqing site\n(line 105), I would expect some discussion on the origin of brGDGT in the context of\nseasonal variations in temperature and precipitation. The discussion on lines 146-163\nappears incomplete.\nPlease explain:\nare the GDGT-bearing bacteria autochthonous to the lake or were the lipids transported\nto lake from soil profiles?\nRe: We further collected and analyzed soils surrounding the Heqing Basin. The results\nindicate that brGDGTs were predominantly produced within the Heqing paleolake, and\nthe influence of soil input is minor.\nFirst, in surrounding soils (Supplementary Fig. 1) brGDGTs are characterized by higher\ndegree of methylation (MBT) and lower degree of cyclization (DC) than those in lake\nsediments in the Heqing Basin (Supplementary Fig. 2). Therefore, while potential soil\nbrGDGT input can bias MBT and reconstructed temperature towards higher values, DC\nshould be biased towards lower values. However, DC is weakly but positively\ncorrelated with MBT (r = 0.14, p = 0.01) and not correlated with reconstructed MAT (r\n= 0.06, p = 0.22) in our record (Supplementary Fig. 3).\nSecond, the ratio of hexamethylated to pentamethylated brGDGT (IIIa/IIa) can also be\nused to distinguish brGDGT provenance, and a value > 0.92 can generally indicate\naquatic origin of brGDGTs (Xiao et al., 2016, BG), although a value < 0.92 not\nnecessarily means significant soil contribution in lakes. IIIa/IIa is > 0.92 for 97%\nsamples in the HQ core (avg. 1.56 ± 0.38, N = 380), much higher than that in\nsurrounding soils (0.10 ± 0.05, N = 12).\nNevertheless, to rigorously constrain the potential effect of soil input and water-column\nstructure, we further exclude samples with IIIa/IIa < 0.92 or GDGT-0/cren > 1.5. Only\n23 samples (accounting for 6% of the 380 samples) were removed, and therefore our\nprevious record and interpretation was not affected.\nPlease see Lines 95–110 and Lines 163–170 for related discussion.\nWhat is the role of monsoonal seasonality in the growth and preservation of these\nbacteria/lipids? I understand the argument with Tsuga content on lines 154-157, but\nconsidering that this winter proxy varies on glacial/interglacial time scales, is it\nreasonable to neglect seasonality as one of the controls on the GDGT dataset? Please\ntry to address these questions in the discussion.\nRe: In soils, due to the effect of soil humidity on brGDGT production, seasonal changes\nin monsoon precipitation might affect the brGDGT palaeothermometry. In the Heqing\npaleolake, however, as brGDGTs were autochthonous, brGDGTs should not be affected\nby seasonal changes in water availability. We can further neglect temperature\nseasonality as a dominant control on the GDGT dataset. Given the low latitude setting,\nthe Heqing region experiences restricted monthly changes in air temperature\n(Supplementary Fig. 1), and when further considering the buffering effect of lake water,\nseasonal temperature changes might be even smaller. More importantly, it is generally\nbelieved that brGDGT-producing bacteria is active above freezing and therefore\nbrGDGTs can record mean temperature above freezing (MAF) or mean lake water\ntemperature (MLWT) (Zhao et al., 2021, SB; Martínez-Sosa et al., 2021, GCA; Zhao et\nal., 2023, QSR; Wang et al., 2024, EPSL). At Heqing, the relatively high winter air\ntemperature (7.5 oC) suggests that lakes in this region should be ice-free year-round,\nand consequently MAF or MLWT equals MAT. Two lines of evidence further indicate\nthat the growth and preservation of these bacteria/lipids might not depend on seasonal\ntemperature variations in non-freezing lakes: (i) in equatorial lakes spanning a MAT\nrange of ca. 2–25 oC, no correlation between brGDGT concentration and temperature\nis observed (Tierney et al., 2010, GCA), and (ii) in the global lake dataset, MBT’\n5ME\nexhibits better correlations with MAF or MLWT than with mean summer temperature\n(MST), and additionally, reconstructed growth temperature approximates MAF or\nMLWT rather than MST (Supplementary Fig. 6). This has been discussed in Lines 145–\n161 in the revised manuscript.\n2) Structure of argumentation\nThe section “Possible controls….” (lines 146-..) includes the main discussion of the\nmechanism of temperature decoupling. The first paragraph, addressing the possible\nseasonal bias in the GDGT proxy, does not fit here. I would suggest moving this\nparagraph higher, as a separate section (perhaps “The role of seasonality….” or\n“Seasonal bias….”?).\nRe: Thanks for this suggestion. This paragraph is removed and the discussion of\nseasonality is added in Lines 145–161 in the “Assessing non-thermal influence on the\nbrGDGT paleothermometer” section.\n3) Language\nL20-24: this is a terrible sentence; please rephrase, split in two\nRe: This sentence was deleted due to the word limit in Abstract.\nL36: “flourish” is a verb; please rephrase “facilitated the flourish”\nRe: Thanks, and “facilitated the flourish of archaic humans” is changed to “been\nbeneficial for archaic humans’ flourishing” (Lines 39–40).\nL46: perhaps not necessary to explain that we inhabit the terrestrial realm.\nRe: We have deleted “where we inhabit” according to your suggestions.\nL90: “full” instead of “fully”\nRe: Revised (Line 191).\nL132-136: sentence too long, hard to understand; please rephrase\nRe: This sentence was split in two (Lines 250–255).\nL192: “Progressive” instead of “progressively”\nRe: Revised (Line 308).\nL199: “albeit quite qualitatively”: what do you mean? please explain\nRe: We meant that the model results might be simplistic and cannot exactly capture the\nreal processes in AIS expansion. This is explained in Lines 320–322.\nReviewer #2 (Remarks to the Author):\nWang et al. show a new Pleistocene (2 - 0.2 Ma) terrestrial temperature reconstruction\nfrom a paleolake in southwestern China using fossilized microbial lipids (brGDGTs).\nThe study presents a valuable high-resolution temperature record from a region and an\narchive (land temperatures) where there is little long-term continuous Pleistocene\ntemperature reconstruction. They hypothesized that Antarctic Ice Sheet expansion is the\ncause/mechanism of a warming during the MPT in terrestrial archives, which they differ\nfrom Global SST. However, I don’t think that the hypothesized mechanisms presented\nhere, the references of additional studies to support their hypothesis and the extended\ndata support their study/hypothesis. I have a lot of main concerns and I think a re-\nevaluation of what I think is an over-interpretation of the data needs to be done.\nRe: Thanks for your comments which help us further improve our manuscript. Please\nsee below our responses to your comments.\nMain comments:\nMy main concern is the over-interpretation of the temperature change seen in the record.\nWhen taking into account the RMSE of the calibration and standard deviation of the\ndata, it’s hard to see how this warming can be separated from the natural variability of\nthe reconstructed temperature. A 1°C temperature change from a proxy that has 1.8°C\n(keep in mind this is +/- 1.8°C) it's a big stretch in interpreting significant temperature\nchanges to claim such mechanisms/conclusions.\nRe: A Mann-Kendall trend test (S = 4148, Z = 3.16, p < 0.01) suggests that the warming\ntrend (1.0 ± 0.3 oC/Myr) is statistically significant. That is, the warming trend is not a\nrandom noise, and along with the clear glacial/interglacial cycles, could not be induced\nby the calibration uncertainty. The 1.8 oC calibration error is caused by the uncertainties\nin obtaining growth temperature for each sample in the calibration set, as well as the\nglobal spread of samples and the accompanying variation in other non-thermal\nenvironmental parameters. At a single sit and for a specific core, this systematic error\nshould be much smaller, particularly for the HQ core where non-thermal influence on\nthe brGDGT paleothermometer can be well-constrained. Similar discussion has also\nbeen presented by many GDGT studies such as Peterse et al. (2011, EPSL), Tierney et\nal. (2010, NG), and Johnson et al. (2016, Nature). Therefore, for our temperature record,\nwhile absolute temperature estimates should be interpreted with caution, we believe\nthat relative temperature changes are generally reliable. Actually, other calibrations\nbased on various statistic methods yield similar warming trend from 1.8 to 0.6 Ma,\nranging from 0.7 to 1.6 oC/Myr (avg. 1.1 oC/Myr), further suggesting that the warming\nobserved here is robust. The related discussion has been added in Lines 197–199 and\nLines 445–461. Moreover, we performed Monte Carlo simulations to assess uncertainty\non the temperature record for 1.8–0.6 Ma. We added an error of 1.8 oC to see whether\nthis uncertainty would affect our conclusion. The results for 1,000 times of simulation\nshowed that 99.9% of the slopes were negative (as the slopes were calculated from\nyounger to older ages, Fig. R1), confirming that the observed warming trend during\n1.8–0.6 Ma is reliable.\nFigure R1. Distributions of slopes under 1,000 times of Monte Carlo simulation (with\nan uncertainty of 1.8 oC) for the Heqing temperature record during 1.8–0.6 Ma.\nSecond, I am concerned about the references. First, they are not only wrong (the number\ndoesn't correspond to the reference), but also I could not find the same data or\ninformation reported by the references in some cases.\nRe: Many thanks for pointing out this and we have carefully checked the references.\nWe are sorry for the incorrect reference numbers in the figure captions and have\ncorrected them in the revised version. The reference numbers in the main text and the\ndata used in the previous version are correct.\n1. Lake Baikal reference number is wrong, and the closest reference of it doesn’t show\nthe BioSi reconstructions that are shown here in Figure 3. The paper uses Biogenic Si\nto identify glacial and interglacial sections but it has not been used as a long-term\ntemperature reconstruction. This is mostly because BioSi is subjected to dissolution, so\nyou can't use the abundance of it to say that there is a temperature trend over time, you\nuse it to identity warmer intervals than others to then do cyclo-stratigrpahy or studies\nlike that, not to infer quantitative temperature changes over time.\nRe: Here we refer to Prokopenko et al. (2006, QSR), and the data were downloaded\nfrom https://www.ncei.noaa.gov/access/paleo-search/study/6068. The dissolution of\nBioSi mainly occurs above the upper 30cm of sediments, in the water column or at the\nsurface sediment-water interface. In deeper sediments, Si saturation is reached, thereby\nbuffering against further dissolution (Mackay, 2007, ESR). This implies that dissolution\nshould not significantly affect long-term trends of BioSi. Actually, for the 5-Ma diatom\nrecord of Lake Baikal (Prokopenko et al., 2001, QI), it generally resembles the benthic\nδ18O record before 1.8 Ma rather than exhibiting an increasing trend (Fig. R2). This\nfurther indicates that the long-term trend of diatom and BioSi should not be\nsignificantly biased and the relatively stable trend during the past 1.8 Myr might record\na climatic signal. Moreover, we acknowledge that the dissolution effect is likely to have\nhad a relatively large impact on the preservation of diatom valves during glacial periods\nbecause of overall low diatom productivity (Mackay, 2007, ESR). However, the\ninterglacial trend might be generally reliable. Nevertheless, considering your concerns,\nwe have revised this section as “The biogenic silica (BioSi) record from Lake Baikal\n(54 oN), which probably tracks temperature fluctuations in high-latitude continental\nEurasia, shows no obvious trend from 1.8 Ma to 0.6 Ma (Fig. 3d). However, it is\ngenerally believed that the response of BioSi to temperature is non-linear and\nqualitative, especially due to the significant dissolution effect during glacial period.\nTherefore, only the interglacial trend might be reliable” in Lines 231–236.\nFigure R2. [REDACTED]. Prokopenko et al. (2001, QI).\n2. Lake Malawi, the proxy used here is TEX which has its own issues in freshwater\n86\nlakes, but more importantly, the original paper doesn’t claim to have an increase in\ntemperature because the variability in the data is within the uncertainty (2sigma =\n0.8°C). Additionally, this study clearly showed CO as the main driver of significant\n2\ntemperature changes along the record and the overall conclusion of it had to do more\nwith a wetter/drier climate than temperature changes.\nRe: The TEX paleothermometer is generally problematic in lakes, but it might be\n86\nreliable in large lakes such as Lake Tanganyika (Tierney et al., 2010, NG) and Lake\nMalawi (Johnson et al., 2016, Nature), especially with rigorous quality control. For this\nrecord, samples that may potentially be affected by non-Thaumarchaeota contribution\nand soil input have been rejected for analysis. The remaining accepted temperatures\nindicate a 2 oC warming from 1.3 to 0.6 Ma, larger than the 2 sigma error (0.8 oC). We\nagree with the reviewer that this study mainly focus on long-term hydrological rather\nthan temperature changes, and for temperature only glacial-interglacial changes for the\npast 0.6 Ma were discussed. However, given that no other long Pleistocene terrestrial\ntemperature record is available from Africa, we feel that it is not proper to ignore this\nwork. Nevertheless, to address your concern, we have revised the discussion on the\nLake Malawi record as “Beyond Eurasia, a 1.3-Myr-long temperature record inferred\nfrom TEX at Lake Malawi, East Africa (11 oS) shows an approximate 2.9 oC/Myr\n86\nwarming trend (p < 0.01) during 1.3–0.6 Ma (Fig. 3e). However, for this record, the\nTEX paleothermometer might be complicated by the ill-defined ecology of freshwater\nThaumarchaeota contribution and soil input have been rejected for analysis” in Lines\n243–249.\n3. Lake El'gygytgyn: this warming rate you mention here 1. Is not significant (see p-\nvalue) and the record doesn’t show cooling around the MPT (in agreement with your\nhypothesis) but also it does not show warming. The main change that happens at this\nhigh-latitude site is a change in hydrological conditions.\nRe: We fully agree with you, and this sentence is revised as “Further north at Lake\nEl’gygytgyn, Far East Russia (67.5 oN), while regional aridification increased during\nthe MPT, no significant warming or cooling trend is observed based on brGDGTs” in\nLines 236–239.\n4. In line 435, reference 24, this paper doesn’t show anything about the formation and\ndemise of the Heqing paleolake. I could not find such a reference. Also, I don't know\nwhy you dismissed those intervals? Even though they don't represent a full lake\naccording to what you said they could give you more information about changes during\nkey periods of time (last interglacial to LGM and Plio-Pleistocene) that have been\nshown to have a more extreme or a more drastic change that could help differentiate\nnoise vs. signal.\nRe: Sorry for the incorrect reference number cited here. We intended to cite An et al.\n(2011, Science) which stated that “an abrupt drop in δ18O (a measure of the ratio of\nstable isotopes 18O:16O) and a shift in the relationship between δ18O and δ13C (a measure\nof the ratio of stable isotopes 13C:12C) of adult ostracod Ilyocypris microspinata shells\naround 11.1 m probably indicate the beginning of a change from a closed paleolake to\nan open system. At 7.4 m depth, the simultaneous disappearance of two benthic\nostracod species (Ilyocypris microspinata and Lineocypris jiangsuensis) indicates that\nthe basin became a fully open system as it is today. Accordingly, we focus on the\ninterval when the system was closed”.\nIn the revised manuscript, we have added GDGT data from the upper section, and it\nnow covers the 0–2 Ma. However, 23 samples were rejected after carefully assessing\nthe potential effects of non-thermal factors such as soil input and changes in water-\ncolumn structure on brGDGTs. The excluded samples are mainly from the top section\nof the core, in agreement with our previous statement. This was discussed in Lines 164–\n171.\nDespite that brGDGTs cannot be used to reconstruct temperature during the past 0.15\nMa at the Heqing paleolake, a previous study from another site in southwestern China\nhas demonstrated that brGDGTs can quantitatively track past temperature variations\nfrom last interglacial to LGM in this region (Zhao et al., 2021, SB). Moreover, we wish\nto focus on the interval after Northern Hemisphere Glaciation (2–3 Ma), especially the\nlong-term trend from 1.8 to 0.6 Ma, and therefore samples older than 2 Ma were not\nanalyzed. Nevertheless, the close match of our biomarker-inferred MAT with marine\nSST records on orbital timescales, and with Tsuga content in both glacial-interglacial\nvariation and long-term trend, reinforce the robustness of our quantitative temperature\nestimates.\n5. Reference 81 and 82. These are not peer-review articles. 81 is a public-facing article\nfrom a science journalist and 82 is a conference abstract. I don’t think you should cite\nnon-peer review references in a manuscript submitted to Nature Communications.\nRe: Thanks for this reminder. We have deleted the two references in the revised\nmanuscript. They were used to argue for our CO stack and therefore this does not affect\n2\nour temperature record and related discussion.\nOverall, we acknowledge that the records from Lake Baikal, Lake Malawi and Lake\nEl'gygytgyn might have their own weakness and limitation. However, it appears to be\nimproper to ignore all these records due to the lack of Pleistocene terrestrial temperature\nrecords with higher quality in other regions. In the revised manuscript, we have just\ndescribed these records and pointed out potential complicating factors. We also avoid\nconcluding a long-term pattern for other regions beyond East Asia due to limited\nevidence. Actually, the large uncertainty in other terrestrial records highlights the\nimportance of our Heqing MAT record.\nThird, one of your data that supports your hypothesis is your extended data figure 6\nwhich is the results of the model output of PI-AIS(PI). First, I think the figure should\nbenefit from having labels (“a”, “b”, etc…) and a more descriptive figure caption.\nSecond, the results in this figure do not clearly support your hypothesis or the figures\nshould be presented differently. I think you could benefit from having a box or an arrow\nthat can show what you mean in the text. For example, you have “shows that the\nexpansion of AISs can potentially increase tropical zonal SST gradient”, where in the\nfigure you can see that? I don’t see these maps and it is obvious to me to see such an\nincrease in tropical zonal SST. Also, you have “elevate surface temperature over\nEurasia” which regions are you talking about because there is a combination of warm\nand cold regions over Eurasia. You have “with an overall increase in water vapor in the\nAsian monsoon region”, again, highlight the regions you are talking about in these maps\nbecause I see some strong red colors over India/Tibet but a blue color around South\nChina where I think your core comes from. Anaways, I don't see how these results\nclearly support your statements. By the way, next to the water vapor panel there is an\n“x” above 30N, what's that?\nRe: Thanks for these comments. According to your comments, we have further revised\nthe figure for modelling results (Supplementary Figure 12) and enrich its caption to\nsupport our statements.\n(i) The labels for each panel and a more descriptive figure caption were added in this\nfigure.\n(ii) We used a blue box and a green arrow to highlight a decrease in SST in the eastern\ntropical Pacific relative to the western tropical Pacific, and thus the strengthening of the\nzonal SST gradient in the tropical Pacific in panel b.\n(iii) In panel a, the terrestrial temperature difference between PI and AIS experiments\nshows an overall warming in the majority of the Eurasian continent (except Eastern\nRussia and India) driven by AIS expansion. The warming at Heqing (red circle) is\nconsistent with proxy-based reconstruction.\n(iv) The northward penetration of summer precipitation and water vapor in central and\nnortheastern China (panel c and d) suggests intensified Asian summer monsoon driven\nby AIS expansion, despite that summer precipitation and water vapor might be reduced\nin southeast Asia. This might be more obvious if only the Asian land monsoon region\nwas analyzed (Fig. R3).\n(v) The “x” next to panel d was deleted.\nOverall, despite that our model might be simplistic and may not exactly capture changes\nin climatic parameters, it demonstrates that the expansion of AISs can potentially\nincrease tropical zonal SST gradient and elevate surface temperature over the majority\nof the Eurasian continent, with an overall strengthening in Asian summer monsoon.\nFigure R3. Differences in summer precipitation rate and summer water vapor between\nPI and AIS experiments over the Asian land monsoon region. The range of the monsoon\nregion is defined by Wang et al. (2011, CD).\nMinor comments:\nAdd elevation in abstract? I think that when talking about temperature reconstruction\nit’s good to know if the terrestrial temperatures are near sea level or high elevation sites.\nRe: Its altitude is 2190 m a.s.l., and we have added it in the Abstract (Line 27).\nAdd modern MAT in the figures to see how it compares with your reconstructed\ntemperatures? The general thought is that the last million years were colder than\ntoday…. So I want to see how modern MAT looks with your reconstructed temperature\nand if your estimate is colder or warmer than that as your present absolute values.\nRe: The modern MAT is 13.8 oC at the Heqing Basin (Line 378). As is expected, it is\ngenerally higher than reconstructed temperatures for the last million years. However,\nas explained previously, absolute temperature estimates should be interpreted with\ncaution, and relative temperature changes are more meaningful. Therefore, we have not\ndiscussed this in the manuscript.\nYou used the Global SST from Clark, but they also present SST compilations by basin.\nI think that rather than using individual cores near your location you can add how the\nSST evolution in the Warm Pool looks in comparison with your record. Then, you can\nevaluate other mechanisms of why you don't see a clear temperature change over the\nMPT like other global records.\nRe: Thanks for this suggestion. We have added the SST stack for Indo-Pacific warm\npool (IPWP) in Supplementary Fig. 10 according to your suggestion. The IPWP stack\nalso shows a relatively stable temperature during 1.8–0.6 Ma, in contrast to the\nsignificant cooling in other basins such as eastern tropical Pacific. This is in agreement\nwith our hypothesis (discussed in Lines 302–305) that the expansion of AISs can\npotentially increase tropical zonal SST gradient and promote relatively increased heat\naccumulation in the western Pacific, then strength Asian monsoons, and finally elevate\nsurface temperature over Eurasia.\nLine 186-187: you are claiming that there is a decrease in SST in the equatorial eastern\nPacific that is strengthening the tropical zonal SST gradient and walker circulation, but\nwhen looking at Figure 4c.. 1. I think the records should go all the way back to the\nbeginning of the Pleistocene, and 2. you can have that data with the new Global SST\ncompilation by basin from Clark et al. 2024.. And probably highlight where the\n“pronounced decrease” happens because with my eyes, in that figure, I don’t see any\n“pronounced” change.\nRe: Many thanks for this recommendation. We have recalculated the zonal SST gradient\nusing SST stacks for Indo-Pacific Warm Pool (IPWP) and Eastern tropical Pacific (ETP)\nreported by Clark et al. (2024, Science). This extends the zonal SST gradient record\nback to 2 Ma. We have also added the ETP SST stack of Clark. Please see Fig. 4c for\nthe two records. Data older than 2 Ma are not presented as they are beyond the scope\nof this work.\nYou report a 1°C/myr… but what's the error or standard deviation of this?\nRe: It is 0.3 oC/Myr and we have added it in Line 198.\nLine-by-line\nLine 60-61: “This implies that Pleistocene global temperature, or at least terrestrial\ntemperature, cannot be simply represented by marine temperature.” I think you should\nre-arrange this sentence by saying something like global temperatures cannot be\nrepresented only by marine archives and the incorporation of terrestrial temperatures is\nneeded for assessing global temperature changes and trends. Or something along the\nlines that global temperature are both terrestrial and marine, not that terrestrial\ntemperatures are not represented by marine (that is obvious)\nRe: Thanks, and this sentence is changed to “This implies that global temperatures\ncannot be represented only by marine archives and the incorporation of terrestrial\ntemperatures is needed for assessing global temperature changes and trends” in Lines\n65–67.\nLine 62: Do you mean glacial-interglacial? Or just glacial? Is just strange to only\nmention glacial if you are referring to the entire pleistocene. Also that sentence could\nbe two sentences rather than one.\nRe: We intended to highlight glacial periods here, as brGDGTs might be strongly\naffected by vegetation coverage and seasonality in soils at the mid-latitude CLP. This\nsentence is revised as “However, brGDGTs are argued to be likely affected by\nvegetation coverage and seasonality in soils at the mid-latitude CLP, especially during\nglacial periods” (Lines 69–71).\nLine 69: what's the elevation?\nRe: The elevation (2190 m a.s.l.) is added in Line 78.\nLine 80: looking at the SD Fig.1. Seems to me that the gradual transition really starts at\n~1.2Ma in your record… not before… no?\nRe: According to your suggestion, this sentence was changed to “On orbital timescales,\nthe 100-kyr glacial-interglacial cycles gradually replaced the 41-kyr cycles, with strong\nperiods of both 41 kyr and ~80–120 kyr during the Middle Pleistocene Transition (MPT,\n1.25 to 0.7 Ma) (Supplementary Fig. 7)” (Lines 179–182).\nLine 89-92: is there a reference to cite here? As it is written it seems like there is a need\nfor a larger evidence of that high-latitude ice-volume forcing.\nRe: Here we have added “Clark et al., 1999, Science”, and changed “high-latitude ice-\nvolume forcing” to “ice sheet influence” (Lines 192–193).\nLine 197: reference?\nRe: A reference (Allen and Ingram, 2002, Nature) is added (Line 314).\nLine 704: what is ESL, I don’t see it defined anywhere.\nRe: Its definition “ice-volume equivalent sea-level” is added in Line 1077.\nReviewer #3 (Remarks to the Author):\nReview of Wang et al. for Nature Communications\nJoseph B. Novak\nRecommendation\nReject and encourage resubmission.\nSummary\nWang et al.’s manuscript entitled “Pleistocene terrestrial warming trend linked to\nAntarctic Ice Sheets Growth” presents a 2-million-year terrestrial paleotemperature\nrecord from Heqing paleolake in southwestern China. The reconstructed\npaleotemperatures show a warming trend, rather than cooling, over the 1.8–0.6 Ma\ninterval, in contrast to marine sea surface temperature records, which the authors\nattribute to dynamical changes in the Earth’s atmospheric circulation in response to\nAntarctic Ice Sheet growth.\nThe lack of a rigorous assessment of the branched GDGT biomarker distributions used\nto generate the paleotemperature record is seriously concerning. While the authors\nargue that the similarity between the reconstructed paleotemperatures to a pollen record\nin the same sediment core indicates that the brGDGTs are primarily recording\ntemperature, I remain unconvinced, especially since this core comes from what appears\nto have been an alkaline lake based on the occurrence of carbonate sediments (Shen et\nal., 2007; ref. 52 in this manuscript). The presentation of the pollen data on a log-scale\nis somewhat odd and, possibly, misleading since pollen data are usually presented on a\nlinear y-axis scale.\nA thorough assessment of any possible non-thermal influence on the brGDGT\ndistributions in this lake is fundamental to this study. The lack of this needed\nsupplementary discussion ultimately motivates my recommendation to reject the\nmanuscript. However, the data presented here hold the potential to be a landmark\ndataset in the field if the authors can show that these non-thermal factors are not\ninfluencing the brGDGT biomarkers here. Therefore, I encourage the resubmission of\nthis manuscript after my comments are addressed.\nRe: Thanks for your positive assessment of our record. We agree with you that a\nthorough assessment of any possible non-thermal influence on the brGDGT\npaleothermometer in this lake is fundamental to this study. Accordingly, we have added\na new section to discuss the potential influences of soil input, changes in water-column\nstructure, water chemistry, and bacterial communities, and seasonal bias in details\n(Lines 91–171). We can demonstrate that these factors are unlikely to significantly bias\nour temperature record, especially when excluding 6% samples (mainly from the top\nsection of the core) that may potentially be affected by soil input and water-column\nstructure changes. We hope that the supplementary discussion can address your concern\nabout the robustness of our temperature record.\nWe should point out that the high carbonate content in the core is because that the\nHeqing basin is a mountainous basin with regional bedrock being dominated by\ncarbonates (An et al., 2011, Science; Yang et al., 2024, QSR), rather than indicating a\nbrackish to saline paleolake. Actually, the occurrence of freshwater diatoms (Yang et\nal., 2024, QSR), and negligible late-eluting isomers after 5-methyl and 6-methyl\nbrGDGTs which are generally high in brackish and saline lakes (Wang et al., 2021,\nGCA) throughout the core suggest a freshwater environment. In the global lacustrine\nbrGDGTs dataset for freshwater lakes, while most lakes are alkaline, brGDGTs can\nfaithfully track temperature and there is no significant offset in reconstructed\ntemperature between lakes with pH = 7–8 and > 8 (Supplementary Fig. 5). Therefore,\nwe believe that the high carbonate content (and possibly high alkalinity) do not affect\nthe quantitative application of the brGDGT paleothermometer in Lake Heqing\nsediments. This supplementary discussion is added in Lines 122–130. Moreover,\naccording to your suggestion, the pollen data are presented with a linear y-axis scale\n(Supplementary Fig. 9b). Nevertheless, the overall pattern remains unchanged, and its\nlong-term trend and glacial-interglacial variation both align with those in our\nreconstructed MAT.\nMajor Comments\nExtended Data Figure 3: Why is the Tsuga data plotted on a log scale? This is odd to\nme since pollen data are typically plotted on a linear scale. Is there a justification for\nthis or is it simply to present that data in such a way that they appear to closely resemble\nthe brGDGT MAT reconstruction? Similarly, is the strength of the correlation shown in\nthe scatterplot dependent on the log transformation of the Tsuga pollen data? Is there\nperhaps some sort of bulk geophysical proxy data (magnetic susceptibility, bulk density)\nthat could be used to make this comparison more effectively?\nRe: A log scale used previously was to reveal the subtle changes in Tsuga during glacial\nperiods (quite low), following An et al. (2011). Using a log scale will not alter the\noverall structure of the data. In the revised version, Tsuga pollen is plotted on a linear\nscale in Supplementary Fig. 9 according to your suggestion. The glacial-interglacial\nvariations and long-term trends of Tsuga pollen agree even better with the brGDGT-\nbased MAT reconstruction, and the correlation coefficient (r) in the scatterplot slightly\nincreases from 0.45 to 0.47 (Supplementary Fig. 9c). The magnetic susceptibility record\nis added in Supplementary Fig. 2j. It provides further support for the substantial changes\nin lake depositional environment at ~0.15 Ma inferred from other proxies.\nL146 and Figure 3: The authors make a statement here regarding “the absence of a long-\nterm terrestrial cooling during the past 2 Myr.” However, the data presented in the\nmanuscript only represent a relatively small number of locations and narrow band of\nlatitudes. In Figure 3, the authors show data from five sites. One dataset (Lake Baikal)\nis not a paleotemperature dataset (see my comment below). The remaining four datasets\nare from the tropics or near tropics, three of which are from China spanning a very\nnarrow range of latitude (27–35°N). So, essentially, are the authors claiming that\nSouthern China and Eastern Africa are representative of terrestrial temperature change\nthroughout the entire Earth? This is unlikely, considering that modern climate change\nis resulting in remarkably different rates of temperature change in the high latitudes vs.\nthe tropics. See also the pollen paleotemperature record from Lake El’gygytgyn, which\nshows a long-term cooling since the Pliocene (see Fig. 3d of Daniels et al., 2021 shows\nthis nicely [https://doi.org/10.1002/jqs.3347]). Although these data do not sample every\nglacial-interglacial cycle, they appear to directly contradict the claim made here and are\nnot discussed in the manuscript.\nRe: Thanks for pointing out this issue. We acknowledge that the data from 5–6 sites are\nnot sufficient to conclude a global pattern. In the revised manuscript, we avoid the\nstatement that the absence of a long-term cooling during the past 2 Myr is a global\nphenomenon, and limit our statement to East Asia.\nFor the Lake Baikal record, it might be improper to ignore this work due to the lack of\nlong Pleistocene terrestrial temperature record in high-latitude regions. In the revised\nmanuscript (Lines 231–236), we have just described the that biogenic silica (BioSi)\nrecord shows no obvious trend from 1.8 Ma to 0.6 Ma, and clarified that the response\nof BioSi to temperature is non-linear and qualitative, especially due to the significant\ndissolution effect during glacial period, according to your comments. Nevertheless, the\noverall trend for interglacial might be reliable.\nFor Lake El’gygytgyn, we find that the pollen paleotemperature record (Melles et al.,\n2012, Science; Brigham-Grette et al., 2013, Science) not necessarily contradict our\nclaim of the absence of a long-term cooling during the past 2 Myr. Please see Fig. R4\nfor Lake El’gygytgyn’s pollen record compiled by Daniels et al. (2022, JQS). While\nthey reported a continuous record from 3.6 to 2.1 Ma, only data for 4 glacial-interglacial\ncycles was reported, and the data is especially lacking for the critical period discussed\nin our study for unknown reason. Therefore, we stated that “High-resolution, but\ndiscontinuous, pollen-based Pliocene-Pleistocene temperature record has also been\nreported for this lake, and data from the critical 1.8–0.6 Ma period is scarce” in Lines\n241–243.\nFigure R4. [REDACTED]. Figure source: Daniels et al. (2022, JQS).\nL457–463: Why is there no supplementary text or figures showing the long-term trends\nin IR6Me, CBT’, brGDGT concentration and GDGT-0/Cren ratio in these samples? It\nis very important to understand the potential for non-thermal factors to influence\nbrGDGT paleotemperature reconstructions, especially in what the authors consider a\n“terrestrial MAT time series benchmark for Pleistocene terrestrial temperature\nvariations.”\nRe: Thanks for this suggestion. GDGT indices such as IR , CBT’, and GDGT-0/cren\n6ME\nratio, and brGDGT concentration have been added in Supplementary Data. We have\nalso plotted these GDGT indices in Supplementary Fig. 2 and used them to constrain\nnon-thermal influences (Lines 91–171).\nThere are several important factors that must be discussed for the community to\nunderstand whether the brGDGT distributions are accurately capturing temperature.\nThese include: (1) brGDGT provenance; (2) the potential for changes in lake water\nchemistry to affect the brGDGT distributions; (3) whether there were changes in other\naspects of the brGDGT distributions that are correlated with the warming inferred\nbetween ~1.2–0.2 Ma in Heqing Basin.\nFor example, the brGDGT paleotemperature reconstruction method used here\n(developed by the same lead author) is supposed to disentangle the relative\ncontributions of 5-methyl and 6-methyl brGDGT producers when estimating\npaleotemperatures (i.e., remove the potential temperature bias from multiple brGDGT-\nproducing bacterial communities contributing lipids to sediment). Are the resulting\npaleotemperature estimates from this method correlated with IR6Me, CBT', BIT, etc.\nin these samples? If so, does this imply that there is a substantial non-thermal influence\non the temperatures reported here that is not accounted for by this method? If not, does\nthat mean the method is working? We do not know because this is not explored.\nRe: As mentioned above, according to your suggestions, we have added a new section\nto discuss the potential influences of soil input, changes in water-column structure,\nwater chemistry, and bacterial communities, and seasonal bias in details (Lines 91–171).\nWe can demonstrate that these factors are unlikely to significantly bias our temperature\nrecord, especially when excluding 6% samples (mainly from the top section of the core)\nthat may potentially be affected by soil input and water-column structure changes. We\nhope that the supplementary discussion can address your concern about the robustness\nof our temperature record.\nMoreover, the positive relationship (r = 0.33, p < 0.01) between the ratio of 6- over 5-\nmethyl brGDGTs (IR ) and MBT’ in the HQ core possibly points to a slight\n6ME 5ME\nimpact of bacterial community change related to complex changes in multiple non-\nthermal parameters (Novak et al., 2025, G3). On the other hand, the reconstructed MAT\nbased on our new calibration has no correlation with IR (r = 0.08, p = 0.14)\n6ME\n(Supplementary Fig. 3). Therefore, we have applied the recent calibration of Wang et\nal. (2024, EPSL) which may mitigate the isomer effect driven by community shift. This\nhas been discussed in Lines 130–145.\nThe overarching point of this comment is that there is not sufficient information\nprovided here for me (or anyone else) to judge whether the brGDGT distributions are\nauthentically capturing temperature in the Heqing paleolake record. This is\nparticularly important to consider since the sediments in this lake core are calcareous\nclays, suggesting that the lake was alkaline. These alkaline lakes appear to be especially\nchallenging environments for brGDGT paleotemperature reconstruction, for example\nLin et al. (2024) [https://doi.org/10.1016/j.earscirev.2024.104694]. Indeed, Shen et al.\n(ref. 52 here) report large changes in sedimentary carbonate content in this lake core.\nShen et al. described substantial changes in the amplitude of these sedimentary\ncarbonate cycles through time and the deposition of gravels associated with regional\nmountain uplift throughout the core. Are these sedimentary features, indicative of\nchanges in lake water chemistry and, perhaps, changes in brGDGT provenance,\nrespectively, related to any aspects of the paleotemperature record presented here?\nRe: As explained above, in the revised manuscript we have added a new section to\ndiscuss the potential influences of non-thermal factors on quantitative temperature\nreconstruction in the core (Lines 91–171). By carefully screening GDGT distributions,\nwe can demonstrate that these factors are unlikely to significantly bias our temperature\nrecord, especially when excluding 6% samples (mainly from the top section of the core)\nthat may potentially be affected by soil input and water-column structure changes.\nMoreover, the high carbonate content in the core is because that the Heqing basin is a\nmountainous basin with regional bedrock being dominated by carbonates (An et al.,\n2011, Science; Yang et al., 2024, QSR), rather than indicating a brackish to saline\npaleolake. This is supported by the occurrence of freshwater diatoms (Yang et al., 2024,\nQSR), and negligible late-eluting isomers of 5-methyl and 6-methyl brGDGTs which\nare generally high in brackish and saline lakes (Wang et al., 2021, GCA) throughout the\ncore. On the other hand, in the global lacustrine brGDGTs dataset for freshwater lakes,\nwhile most lakes are alkaline, brGDGTs can faithfully track temperature and there is no\nsignificant offset in reconstructed temperature between lakes with pH = 7–8 and > 8\n(Supplementary Fig. 5). As for Lin et al. (2024, ESR), they provide no evidence that\nalkalinity can affect brGDGT-based temperature reconstructions in lacustrine\nconditions. Additionally, the calibration method used in our work can effectively\nmitigate the potential effect of changing isomer ratio related to changes in lake water\nchemistry and bacteria community structure. Therefore, we believe that the high\ncarbonate content (and possibly high alkalinity) do not affect the quantitative\napplication of the brGDGT paleothermometer in Lake Heqing sediments. This has been\ndiscussed in Lines 121–145. Furthermore, the two short intervals of sand layers with\nfine gravels occurred at 372.5–371.9 m and 195.4–189.5 m (An et al., 2011, Science).\nFor our dataset, only 1 sample was within them, and it exhibits much higher GDGT/cren\nratio (2.4) and therefore is rejected for quantitative temperature reconstruction\n(Supplementary Data).\nIn my view, this manuscript cannot pass review until the potential non-thermal\ninfluence on the brGDGT distributions is addressed. I appreciate the huge amount of\neffort that went into analyzing this dataset and I strongly encourage the authors to\naddress these comments and resubmit their work. Long terrestrial paleoclimate records\nare a rare and special thing with the potential to capture the thought and attention of the\nscientific community. This is why we must treat them carefully, and critically, to be sure\nabout their underlying quality.\nRe: We appreciate your positive assessment on the merit of our record. We hope that\nthe supplementary data and discussion can address your concern about its robustness.\nSupplementary data: Why is there no supplementary data table with the reconstructed\ntemperatures and underlying brGDGT distributions? It is standard practice to share this\ninformation.\nRe: Thanks for this reminder and we have added the data in Supplementary Data file.\nMinor Comments\nL19: “Our knowledge of Earth’s temperature history” rather than “knowledge on.”\nRe: This sentence was deleted due to the word limit for Abstract.\nL36: “flourishing” rather than “flourish.”\nRe: Thanks, and “facilitated the flourish of archaic humans” is changed to “been\nbeneficial for archaic humans’ flourishing” (Lines 39–40).\nL42 and elsewhere: The SI convention now is to italicize the δ in δ18O.\nRe: The δ in δ18O is italicized in Lines 46, 50, 185, 563, 1051.\nL73: timeseries should be written as one word, not two.\nRe: “time series” is changed to “timeseries” (Line 86).\nL90: “full establishment” rather than “fully establishment.”\nRe: “fully” is changed to “full” (line 191).\nL93: Consider rephrasing to: “A notable feature of the long-term Heqing\npaleotemperature trend is that…”\nRe: This sentence is rephrased according to your suggestion (Line 194–197).\nL96: “trend” in “pronounced cooling trend” can be removed as it is unnecessary.\nRe: Thanks, and revised (Line 199).\nL104–106: I do not really follow what you mean here. Mean annual temperature by\ndefinition incorporates the temperature of all months equally. Is this statement trying to\nparse the slight difference in the correlation strength between MAT and summer vs.\nwinter temperature? This seems like a bit of a stretch to me since the difference in\nPearson’s r here is rather minor.\nRe: Here we meant that changes in Tsuga pollen can generally trace MAT variations at\nHeqing, since (i) Tsuga pollen is largely controlled by winter temperature in this region,\nand (ii) regional MAT strongly depends on winter temperature. We have revised the two\nsentences as “Modern investigations show that Tsuga distribution in the Asian monsoon\nregion is controlled by winter temperature at regions with sufficient precipitation.\nFurthermore, MAT at the Heqing Basin strongly depends on winter temperature\n(Supplementary Fig. 8). Therefore, Tsuga pollen can be used as a sensitive, albeit\nqualitative, temperature proxy in this region” in Lines 207–213.\nL116–117: does this imply that a different result is obtained if a more restricted pollen\ntraining dataset is used?\nRe: The overall trend for the pollen-based reconstruction at Zoige Basin might differ\nwhen using various modern training-sets with different distances (radius = 500 km,\n1000 km, 1500 km, and all samples). However, all reconstructions based on the\nweighted-average partial least squares (WAPLS) method show a warming trend from\n1.5 to 0.6 Ma (Zhao et al., 2021, GPC), when global SST significantly dropped. We\nbelieve that the transfer functions using modern training dataset from a broader region\nmight be less affected by non-thermal factors, and therefore cite the record using all\nmodern pollen data from China and Mongolia as the training dataset.\nL124–126: The Lake Baikal biogenic silica record does not track paleotemperature\ndirectly and certainly not in a linear fashion. I therefore urge extreme caution in\ninterpreting this record as a paleotemperature proxy dataset as is done here. A major\ndrawback of this data type is that it cannot distinguish relative differences in how cold\nindividual glacial periods were. This is because it is impossible to have less than 0%\nbiogenic silica content, meaning that any potential differences in temperature between\nglacial periods is missed by the proxy signal. You will notice that this is essentially the\nvalue of every glacial period (at least the stadials, interstadials have slightly higher\ncontent) over the entire 1.8-million-year period covered by the Prokopenko et al. 2006\nrecord you reference here.\nSee Prokopenko et al. 2001 [doi:10.1006/qres.2000.2212] for a thorough discussion.\nSee also Battarbee et al. 2005 [https://doi.org/10.1016/j.gloplacha.2004.11.007] for an\nexplanation of the nonlinear nature of the diatom signal in Lake Baikal sediments due\nto the dissolution of ~99% of diatoms prior to their burial in Lake Baikal sediments.\nRe: Thanks for this information. For the Lake Baikal record, we fully agree with you\nthat the biogenic silica (BioSi) record does not track paleotemperature in a linear\nfashion. However, it might be improper to ignore this work due to the lack of long\nPleistocene terrestrial temperature record in high-latitude regions. Therefore, in the\nrevised manuscript (Lines 231–236), we have just mentioned that the BioSi record\nshows no obvious trend from 1.8 Ma to 0.6 Ma, and clarified that the response of BioSi\nto temperature is non-linear and qualitative, especially due to the significant dissolution\neffect during glacial period. Nevertheless, the overall trend for interglacial might be\nreliable. Further, in the revised manuscript, we avoid concluding a long-term pattern\nfor other regions beyond East Asia due to limited evidence.\nL126–129: After looking at this paleotemperature record again, the claim made here\nabout Lake El'gygytgyn is a stretch. This is reflected by the weak p-value, which does\nnot compel me to think the “trend” discussed here is statistically significant. This\nstatement also appears to ignore the pollen paleotemperature record from Lake\nEl’gygytgyn, which shows a long-term cooling (see Fig. 3d of Daniels et al., 2021\nhttps://doi.org/10.1002/jqs.3347).\nRe: According to your comments and Reviewer 2’s, we have revised this sentence as\n“Further north at Lake El’gygytgyn, Far East Russia (67.5 oN), while regional\naridification increased during the MPT, no significant warming or cooling trend is\nobserved based on brGDGTs” (Lines 236–239). For the pollen record, while a\ncontinuous record from 3.6 to 2.1 Ma was reported, the data is lacking for the critical\nperiod discussed in our study for unknown reason. Therefore, we cannot say that the\npollen record exhibits a cooling trend during 1.8–0.6 Ma. We state that “High-resolution,\nbut discontinuous, pollen-based Pliocene-Pleistocene temperature record has also been\nreported for this lake, and data from the critical 1.8–0.6 Ma period is scarce” in Lines\n240–242.\nL135: I do not understand what “or (and)” means.\nRe: “or (and)” is changed to “or” (Line 253).\nL157–159: I question whether this reference is appropriate. The study here is a\ndiscussion of spatial patterns of seasonal temperature change in Eurasia, which is not\nreally relevant to the discussion of whether warm and cold season temperatures can\nevolve in the same direction that it is invoked to support in this manuscript.\nRe: The discussion on seasonal bias is moved to an earlier place and the related\ndiscussion is deleted.\nL146–163: This discussion seems to largely miss an important point: we fundamentally\ndo not understand the seasonality of the brGDGT temperature proxy. See discussion in\nZhao et al., 2023 [https://doi.org/10.1016/j.quascirev.2023.108124]. In the tropics this\nis not a problem since seasonality is small, but in the middle and high latitudes this\nleads to a weak relationship between MAF temperature and MBT’5Me (Zhao et al.,\n2023).\nRe: This section is deleted and we have added a new paragraph to discuss the\nseasonality of the brGDGT temperature proxy, just limited to the low-latitude Heqing\nregion (Lines 146–162).\nL168–173: This is hard to follow, please clarify.\nRe: This sentence is revised as “One might argue that this synthesis might mostly rely\non records with higher density of datapoints, as its variation resembles that for the\nrecord inferred from δ13C of terrestrial C3 plant remains, which accounts for 30% of\nthe total datapoints during 2.6–0.2 Ma (Supplementary Fig. 11a). To reconcile the\npotential artifact caused by this issue as well as the systematic bias and large scattering\nof each work using different methods and archives, we further compiled a new CO\n2\nstack by normalizing 11 long Pleistocene CO reconstructions vetted by the\nlong-term trend in CO level during the past 2 Myr (Fig. 4a)” in Lines 275–287. As our\n2\ntwo new stacks show rather similar results, we only use the stack based on vetted\nrecords in the revised manuscript.\nL174–177: Again, I urge caution in interpreting the Lake Baikal biogenic silica record\nas a paleotemperature proxy. See my comment above.\nRe: We have deleted the discussion of Lake Baikal biogenic silica record here.\nL222–224: Tropical temperatures in China and Africa, not terrestrial temperatures in\ntoto.\nRe: This sentence is revised as “Moreover, our results highlight a possible divergent\nevolution of land surface temperatures (at least at some regions) and marine\ntemperatures, and the processes involved could be helpful for projecting future\ntemperature changes with regional patterns identified” (Lines 347–350).\nFigure 1: Please make the arrows a color other than bright green on the red background.\nThe arrows are not visible to colorblind people.\nRe: Thanks for this reminder, and the color of bright green arrows is changed to bright\nblue (Fig. 1).\nFigure 2: It is not necessary to overlay your temperature record onto the other records.\nThey can be compared simply by looking at the differences in their trends.\nRe: This figure is revised according to your suggestion (Fig. 2).\nExtended Data Figure 4: Please choose a colorblind figure color palette for panel B.\nRe: The color palette for panel B is revised (Supplementary Fig. 10).\nExtended Data Figure 7: Wouldn’t the topical calibration of Zhao et al. (2023) be more\nappropriate here? The global calibration is intended for deep time applications.\nRe: The tropical multivariate linear regression calibration of Zhao et al. (2023) is used\n(Supplementary Fig. 13).\n_____________________________________________________________________\nReferences\nAllen, M. R. & Ingram, W. J. Constraints on future changes in climate and the\nhydrologic cycle. Nature 419, 224–232 (2002).\nAn, Z. et al. Glacial-interglacial Indian summer monsoon dynamics. Science 333, 719–\n723 (2011).\nBaxter, A. J., Hopmans, E. C., Russell, J. M. & Sinninghe Damsté, J. S. Bacterial\nGMGTs in East African lake sediments: Their potential as palaeotemperature\nindicators. Geochim. Cosmochim. Acta 259, 155–169 (2019).\nBaxter, A. J. et al. Disentangling influences of climate variability and lake-system\nevolution on climate proxies derived from isoprenoid and branched glycerol\ndialkyl glycerol tetraethers (GDGTs): the 250 kyr Lake Chala record.\nBiogeosciences 21, 2877–2908 (2024).\nBlaga, C. I., Reichart, G. -J., Heiri, O. & Sinninghe Damsté, J. S. Tetraether membrane\nlipid distributions in water-column particulate matter and sediments: a study of 47\nEuropean lakes along a north-south transect. J. Paleolimnol. 41, 523–540 (2009).\nBrigham-Grette, J. et al. Pliocene Warmth, Polar Amplification, and Stepped\nPleistocene Cooling Recorded in NE Arctic Russia. Science 340, 1421–1427\n(2013).\nClark, P. U., Alley, R. B. & Pollard, D. Northern Hemisphere Ice-Sheet Influences on\nGlobal Climate Change. Science 286, 1104–1111 (1999).\nClark, P. U., Shakun, J. D., Rosenthal, Y., Köhler, P. & Bartlein, P. J. Global and regional\ntemperature change over the past 4.5 million years. Science 383, 884–890 (2024).\nDaniels, W. C. et al. Archaeal lipids reveal climate-driven changes in microbial ecology\nat Lake El'gygytgyn (Far East Russia) during the Plio-Pleistocene. J. Quat. Sci. 37,\n900–914 (2022).\nJohnson, T. C. et al. A progressively wetter climate in southern East Africa over the past\n1.3 million years. Nature 537, 220–224 (2016).\nMackay, A. W. The paleoclimatology of Lake Baikal: A diatom synthesis and\nprospectus. Earth Sci. Rev. 82, 181–215 (2007).\nMartínez-Sosa, P. et al. A global Bayesian temperature calibration for lacustrine\nbrGDGTs. Geochim. Cosmochim. Acta 305, 87–105 (2021).\nMelles, M. et al. 2.8 Million Years of Arctic Climate Change from Lake El’gygytgyn,\nNE Russia. Science 337, 315–320 (2012).\nNovak, J. B. et al. The Branched GDGT Isomer Ratio Refines Lacustrine\nPaleotemperature Estimates. Geochem. Geophy. Geosy. 26, e2024GC012069\n(2025).\nPeterse, F. et al. Decoupled warming and monsoon precipitation in East Asia over the\nlast deglaciation. Earth Planet. Sci. Lett. 301, 256–264 (2011).\nProkopenko, A. A. et al. The link between tectonic and paleoclimatic events at 2.8–\n2.5Ma BP in the Lake Baikal region. Quat. Int. 80–81, 37–46 (2001).\nProkopenko, A. A., Hinnov, L. A., Williams, D. F. & Kuzmin, M. I. Orbital forcing of\ncontinental climate during the Pleistocene: a complete astronomically tuned\nclimatic record from Lake Baikal, SE Siberia. Quat. Sci. Rev 25, 3431–3457\n(2006).\nQiang, X., Xu, X., Zhao, H. & Fu, C. Greigite formed in early Pleistocene lacustrine\nsediments from the Heqing Basin, southwest China, and its paleoenvironmental\nimplications. J. Asian Earth Sci. 156, 256–264 (2018).\nTierney, J. E. et al. Environmental controls on branched tetraether lipid distributions in\ntropical East African lake sediments. Geochim. Cosmochim. Acta 74, 4902–4918\n(2010).\nTierney, J. E. et al. Late-twentieth-century warming in Lake Tanganyika unprecedented\nsince AD 500. Nat. Geosci. 3, 422–425 (2010).\nWang, B., Liu, J., Kim, H. -J., Webster, P. J., & Yim, S.-Y. Recent change of the global\nmonsoon precipitation (1979–2008). Clim. Dyn. 39(5), 1123–1135 (2011).\nWang, H., et al. Salinity-controlled isomerization of lacustrine brGDGTs impacts the\nassociated MBT’ terrestrial temperature index. Geochim. Cosmochim. Acta\n5ME\n305, 33–48 (2021).\nWang, H. et al. New calibration of terrestrial brGDGT paleothermometer deconvolves\ndistinct temperature responses of two isomer sets. Earth Planet. Sci. Lett. 626,\n118497 (2024).\nXiao, W. et al. Ubiquitous production of branched glycerol dialkyl glycerol tetraethers\n(brGDGTs) in global marine environments: a new source indicator for brGDGTs.\nBiogeosciences 13, 5883–5894 (2016).\nYang, X., Jin, Z., Zhang, F. & Ma, X. Glacial-interglacial lake hydrochemistry in step\nwith the Pleistocene Indian summer monsoon at the southeastern Tibetan Plateau.\nQuat. Sci. Rev. 329, 108556 (2024).\nZhao, B. et al. Evaluating global temperature calibrations for lacustrine branched\nGDGTs: Seasonal variability, paleoclimate implications, and future directions.\nQuat. Sci. Rev. 310, 108124 (2023).\nZhao, C. et al. Possible obliquity-forced warmth in southern Asia during the last glacial\nstage. Sci. Bull. 66, 1136–1145 (2021).\nZhao, Y., et al. Temperature reconstructions for the last 1.74-Ma on the eastern Tibetan\nPlateau based on a novel pollen-based quantitative method. Global Planet. Change\n199, 103433 (2021)."}, {"round": 2, "reviewer_comments": {"reviewer_1": "Dear authors,\nafter reading the revised version of your manuscript, I can conclude that you have addressed all of my comments and revised the manuscript accordingly. I have no further concerns or questions.\nYours sincerely,\nJiri Laurin", "reviewer_2": "I appreciate the authors answering my concerns. However, I don't think the main concerns of how the data is presented was solved and I think the message of the manuscript needs a revision after the reviews that have already been done.\nAdditionally, there is no discussion of how the high elevation (>1000m) of the archive can affect the temperature seen in the record, which is fundamental for interpretations of land temperature reconstructions.\nEven though you think the non-thermal error is small because of the lithology of the core you don't have a way to quantitatively address it. I think what you need is an appropriate propagation of error in your study to report your warming temperatures, and then evaluate if it is statistically significant. You NEED to incorporate the RMSE of the calibration you are using.\nYou mentioned a “long term” warming in your abstract, however, there is no quantitative result of the warming or any temperature reconstruction. I encourage you to add a quantitative result with the appropriate propagation error to make your abstract clearer and easier for readers to assess the impact of the study.\nAnd in response to your reply of my first comment, I am glad that you show the monte carlo simulation of the slope, but it still doesn’t show the appropriate error propagation of the brGDGT-based temperature reconstruction. I want to see the appropriate lower and upper boundary of your results.\nLake Baikal: seems to me that after answering my concern this is not a useful record to show in your study. Don’t show data that doesn’t support your hypothesis or the main point of the paper. It's a distraction. It is not improper to not include data in your figures that doesn’t help with the story you are telling. You are more than welcome to mention them and include them in suppl. Material but it distracts in short format papers.\nLake Malawi: 2.9°C/Myr, please add the uncertainties and appropriate error propagation for this. And same comment as Lake Baikal.\nNow that you clarify the elevation and included such data… What about changes in lapse rate? How this high-elevation (above 1000m) record is going to amplify the regional temperature trend? Is the warming that you are seeing an amplification of temperature due to elevation and not a response of the mechanism? I think you need to expand more on this and explore the elevation-dependent warming or amplification/changes in temperature. I suggest you do it in a way that you can differentiate if you 1°C is a regional warming or a temperature amplification due to elevation.\nLines 164-171: please show such ratios in a supplementary figure for all samples to assess how different they are. Please add the references for which those ratios are used to exclude GDGTs that are influenced by “non-thermal” factors.\nA suggestion for your Fig. S12. use a red star without filling, not a solid point, so readers can look at the color at your site. Interesting that you rogue that that map is consistent with your data but seems inconsistent with other terrestrial data that you showed.\nALso, your Figure R3. works as a better data visualization for what you want to say… maybe consider including it in the suppl.\nI suggest revisiting the figures you are showing in the main text and focus on the data that helps you support your argument (or main message of the paper). Right now for me looks confusing.\nUnder data availability: what is figshare? Where is the data going to be stored for open access? Make sure you include each individual GDGT (fractional abundance, branched and iso) on it.", "reviewer_4": "Wang et al. presents a 2-million-year temperature records from Heqing Paleolake in southwestern China. The main findings include a warming trend, instead of cooling, during the time interval of 1.8 – 0.6 Ma. The authors link this to the growth of the Antarctic Ice Sheet. The revision is well-written, and I enjoy reading this story.\nI joined the peer review process after the first round and mainly evaluated the revision/supplements and the rebuttal letter, especially the communications between the authors and reviewer #3. The main concern centers on the insufficient assessment of the non-thermal effects on the brGDGTs, thus will undermine the use of brGDGT as a temperature indicator in this study. After carefully reading the revision, I feel the authors have largely incorporated the Reviewer’s comments and have added a thorough analysis to properly discuss the potential non-thermal influence. I do believe a rigorous assessment of the brGDGT is a must for such an important and long terrestrial temperature record, and I appreciate the authors’ efforts to address those questions.\nI want to echo one important concern that was raised by Reviewer 3 regarding the calibration used in this study. The authors have done a good job of arguing that the brGDGTs are mainly influenced by temperatures, and thus can be a good temperature indicator. What is missing (in the paragraphs around line 125) here is to justify that the best calibration is the one from Wang et al. (2024) EPSL. I encourage the authors to add some discussions here, and I believe it’s not hard, given that the Supplementary Figure 13 shows very similar patterns using different calibrations. The authors briefly touch on this in the method section, but I feel some discussion in the main text is essential. So far, the authors have spent quite a lot of time ruling out the non-thermal effects in the first subsection, and this is the time to directly add information that brGDGTs can be used to reconstruct temperature successfully with this calibration. A few sentences stating the advantages of this calibration and why it fits the best will be very helpful.\nThe figures showing soil GDGTs are missing in the supplements. The authors call out Supplementary Fig. 2 in Lines 84, 88, and 92, but that is not the correct one.\nLine 101, regarding the GDGT-0/cren, please consider citing Schneider et al. (2024) QSR. DOI:\nhttps://doi.org/10.1016/j.quascirev.2024.108851"}, "author_response": "Re: Dear Jiri Laurin, thanks again for reviewing our revised manuscript and we are glad\nto know that you are satisfied with our revision.\nReviewer #2 (Remarks to the Author):\nI appreciate the authors answering my concerns. However, I don't think the main\nconcerns of how the data is presented was solved and I think the message of the\nmanuscript needs a revision after the reviews that have already been done. Additionally,\nthere is no discussion of how the high elevation (>1000m) of the archive can affect the\ntemperature seen in the record, which is fundamental for interpretations of land\ntemperature reconstructions.\nRe: We greatly appreciate your comments on our revised manuscript. We have studied\nyour comments carefully and made corrections or explanations accordingly. Briefly, we\nhave provided new statistical results for data uncertainties, deleted unnecessary\ndiscussion on other terrestrial records, and added the discussion of the effect of\nelevation on long-term temperature trends. We are grateful for those comments and\nsuggestions that further improved the quality of our work. Please see below for our\npoint-by-point responses.\nEven though you think the non-thermal error is small because of the lithology of the\ncore you don't have a way to quantitatively address it. I think what you need is an\nappropriate propagation of error in your study to report your warming temperatures,\nand then evaluate if it is statistically significant. You NEED to incorporate the RMSE\nof the calibration you are using.\nRe: Thanks for this comment. We acknowledge that the non-thermal influences cannot\nbe exactly quantified although they are small (or negligible) in our record. To address\nyour concern, we conservatively compounded the calibration error with analytical error\nto calculate the total error for our temperature reconstruction, according to Tierney et\nal. (2010, Nat. Geosci.) (Lines 379-383). The ±1.8 °C uncertainty for absolute\ntemperature values was visualized in Fig. 2a.\nWe should point out that while absolute temperature estimates should be interpreted\nwith caution, relative temperature changes are believed to be reliable for GDGT-based\nreconstructions, as it can reduce systematic calibration error and site-specific effects\n(Tierney et al., 2010, Nat. Geosci.; Peterse et al., 2011, Earth Planet. Sci. Lett.; Johnson\net al., 2016, Nature; Loomis et al., 2017, Sci. Adv.). Monte Carlo uncertainty\npropagation has the advantage of both being easy to interpret and allowing for a wide\nvariety of uncertainty distributions. Therefore, for our HQ temperature record (1.8–0.6\nMa), we further performed Monte Carlo simulations to calculate the uncertainty for the\nlinear trend of temperature variation during 1.8–0.6 Ma, under the 1.8 °C error of\nabsolute temperature values (Lines 383-392). We found that 1000 times of Monte Carlo\nsimulations incorporating the 1.8 oC uncertainty all show warming trends, with an\naverage value of 1.0 ± 0.3 oC/Myr (95% confidence interval = 0.4–1.7) (Fig. 3a,\nSupplementary Fig. 9), and the proportion of significant (p < 0.05) regressions is 78%\n(Lines 181-185). This indicates that the long-term warming trend at the Heqing Basin\nis statistically robust.\nYou mentioned a “long term” warming in your abstract, however, there is no\nquantitative result of the warming or any temperature reconstruction. I encourage you\nto add a quantitative result with the appropriate propagation error to make your abstract\nclearer and easier for readers to assess the impact of the study.\nRe: Thanks for this suggestion and accordingly, we have added the quantitative result\n(1.0 ± 0.3 oC/million years) in the abstract (Line 25). The propagation error is 0.3 oC\nbased on 1000 times of Monte Carlo simulations incorporating the 1.8 oC uncertainty\nof quantitative temperature reconstruction.\nAnd in response to your reply of my first comment, I am glad that you show the monte\ncarlo simulation of the slope, but it still doesn’t show the appropriate error propagation\nof the brGDGT-based temperature reconstruction. I want to see the appropriate lower\nand upper boundary of your results.\nRe: Based on Monte Carlo Uncertainty Analysis, the propagation error is 0.3 oC, and\nthe lower and upper boundary is 0.4 and 1.7 oC/Myr, respectively at 95% confidence\nlevel. The 95% confidence interval for the warming trend from 1.8 to 0.6 Ma was\nvisualized in Fig. 3a and Supplementary Fig. 9. This was added in Lines 181-184.\nLake Baikal: seems to me that after answering my concern this is not a useful record to\nshow in your study. Don’t show data that doesn’t support your hypothesis or the main\npoint of the paper. It's a distraction. It is not improper to not include data in your figures\nthat doesn’t help with the story you are telling. You are more than welcome to mention\nthem and include them in suppl. Material but it distracts in short format papers.\nLake Malawi: 2.9°C/Myr, please add the uncertainties and appropriate error\npropagation for this. And same comment as Lake Baikal.\nRe: Thanks for these suggestions. The Lake Baikal and Lake Malawi records were\nremoved from Fig. 3, and the discussion on the two records were moved to\nSupplementary Information (Supplementary Discussion). The uncertainty (1.5 oC/Myr)\nand 95% confidence interval (0.2–5.9 oC/Myr) for the warming trend at Lake Malawi\nwas also added in Supplementary Discussion.\nNow that you clarify the elevation and included such data… What about changes in\nlapse rate? How this high-elevation (above 1000m) record is going to amplify the\nregional temperature trend? Is the warming that you are seeing an amplification of\ntemperature due to elevation and not a response of the mechanism? I think you need to\nexpand more on this and explore the elevation-dependent warming or\namplification/changes in temperature. I suggest you do it in a way that you can\ndifferentiate if you 1°C is a regional warming or a temperature amplification due to\nelevation.\nRe: Thanks for this suggestion. We fully agree with you that warming at the Heqing\nBasin might be amplified due to elevation-dependent warming, but this effect cannot\ninverse the temperature trends and thus can hardly explain the warming instead of\ncooling trend of Pleistocene terrestrial temperature. Following your suggestion, we\nadded a paragraph specifically discussing the potential effect of elevation on the\nwarming trend in East Asia in Lines 229-243 as “The long-term warming trend during\n1.8–0.6 Ma observed for the 3 East Asian records at Heqing, Zoige and Lingtai, in\ncontrast to the contemporaneous global sea surface cooling, cannot be primarily\nattributed to the relatively high elevation of these terrestrial records. Observational data\nand numerical models for global temperature variations suggest that, elevated land\nsurfaces warm faster than non-elevated ones during the past several decades46. On the\nother hand, GDGT-based temperature reconstructions from East African lakes\ndemonstrate that cooling during the Last Glacial Maximum was amplified with\nelevation, resulting in a significantly steeper lapse rate than today47. However, while\nelevation might amplify the amplitude of temperature variations, the warming or\ncooling trends at different elevations cannot be inversed. Based on ERA5 reanalysis,\nHadCRUT5 dataset, and CMIP6 historical simulations (1959–2014), land surface\nwarming is on average 16% higher at 2190 m a.s.l than that at sea level across the\ntropics and subtropics (40° S to 40° N)46. Assuming a similar elevation-dependent\nwarming at Heqing, the warming trend should be 0.9 oC/Myr at sea level, still opposite\nto the 2.5 oC/Myr cooling for global SST.”\nLines 164-171: please show such ratios in a supplementary figure for all samples to\nassess how different they are. Please add the references for which those ratios are used\nto exclude GDGTs that are influenced by “non-thermal” factors.\nRe: Thanks for this suggestion. GDGT-based indices, including IIIa/IIa (Supplementary\nFig. 2c) and GDGT-0/cren (Supplementary Fig. 2d), were provided in Supplementary\nFig. 2. The references for which those ratios are used to constrain non-thermal\ninfluences on the brGDGT paleothermometer were added in Line 152.\nA suggestion for your Fig. S12. use a red star without filling, not a solid point, so readers\ncan look at the color at your site. Interesting that you rogue that that map is consistent\nwith your data but seems inconsistent with other terrestrial data that you showed.\nALso, your Figure R3. works as a better data visualization for what you want to say…\nmaybe consider including it in the suppl.\nRe: Thanks. Following your suggestion, the solid point was replaced by a red star with\nfilling in a (now for Supplementary Fig. 14), and Supplementary Fig. 14c&d were\nreplaced by Fig. R3. Moreover, we have deleted the discussion and curves of the Lake\nBaikal, Lake El'gygytgyn, and Lake Malawi records in the main text, and the remaining\n3 records from East Asia are consistent with modeling output.\nI suggest revisiting the figures you are showing in the main text and focus on the data\nthat helps you support your argument (or main message of the paper). Right now for\nme looks confusing.\nRe: Thanks. The Lake Baikal and Lake Malawi records were removed from Fig. 3, and\nlinear regressions with 95% confidence intervals were added. Moreover, the uncertainty\nof the temperature calibration (±1.8 °C) was presented more clearly in Fig. 2a.\nUnder data availability: what is figshare? Where is the data going to be stored for open\naccess? Make sure you include each individual GDGT (fractional abundance, branched\nand iso) on it.\nRe: Figshare is a web-based interface designed for academic research data management\nand research data dissemination. Springer Nature is partnering with figshare at a\nnumber of Nature Portfolio and Academic Journals, offering a straightforward\nrepository option for a wide range of data types. The URL for our data was added in\nLine 396 and will become public after the paper is published (the Figshare private link\nis https://figshare.com/s/7867781e5620cf96c5e0). It consists of all related GDGT\ninformation for this work, including the fractional abundances of individual brGDGTs,\nGDGT proxies including GDGT-0/cren ratio for isoGDGTs, and brGDGT\nconcentration.\nReviewer #4 (Remarks to the Author):\nMy concerns have been resolved after reading the revision and the response letter.\nRe: We are pleased to know that you are satisfied with our revision."}, {"round": 3, "reviewer_comments": {"reviewer_2": "I thank the authors for answering all my concerns. I think the paper is now ready for publication with only some minor comments that they will need to add before acceptance.\n\nPlease add the 95% confidence interval result in your abstract (see Tierney et al., 2025 AGUAdvances as an example of how to report it).\n\nThe first sentence of your abstract should be something that highlights the importance of the period you are reconstructing… not just saying that we don't know terrestrial MAT. Why is it important to reconstruct terrestrial temperature in the Pleistocene? (again, you can look at the previous paper as an example)\n\nLine 35, replace with “Earth’s climate shifted from 41…”\n\nLine 233: non-elevated = than those near sea-level\n\nLine 234: it makes no sense to start that sentence with :”on the other hand” when you are talking about another period of time, maybe you can say: “During the Last glacial maximum, GDGT-based temperature reconstructions from East African lakes show amplified cooling with elevation…” both modern and LGM show that at higher elevation temperature amplification is bigger than near sea level.\n\nabout the data availability: the link that was provided to me does not show the fractional abundances of branched and iso GDGT or neither the ratios calculated in this study. It only shows the Age (Ma), MAT, and MAT-error. PLEASE make sure to upload all of the data so your study is reproducible.\n\n(Remarks on code availability)\nyes it has a readme and isntruction of how to install and run the code.", "reviewer_4": "My concerns have been resolved after reading the revision and the response letter.\n\n(Remarks on code availability)"}, "author_response": "Re: Thanks again for reviewing our revised manuscript and we are pleased to know that\nyou are satisfied with our revision. We are grateful for those comments and suggestions\nthat further improved the quality of our work. Please see below for our point-by-point\nresponses to your minor comments.\n\nPlease add the 95% confidence interval result in your abstract (see Tierney et al., 2025\nAGUAdvances as an example of how to report it).\nRe: Thanks for this suggestion and the 95% CI is added in Line 36.\n\nThe first sentence of your abstract should be something that highlights the importance\nof the period you are reconstructing… not just saying that we don't know terrestrial\nMAT. Why is it important to reconstruct terrestrial temperature in the Pleistocene?\n(again, you can look at the previous paper as an example)\nRe: Thanks. We have added “limiting our understanding of the patterns, mechanisms\nand impacts of past temperature changes” after “How terrestrial mean annual\ntemperature (MAT) evolved throughout the past 2 million years (Myr) remains elusive”\naccording to your suggestion (Lines 31-32).\n\nLine 35, replace with “Earth’s climate shifted from 41…”\nRe: Accepted and revised (Line 46).\n\nLine 233: non-elevated = than those near sea-level\nRe: Thanks, and “non-elevated” was replaced by “those near sea-level” in Line 244.\n\nLine 234: it makes no sense to start that sentence with: “on the other hand” when you\nare talking about another period of time, maybe you can say: “During the Last glacial\nmaximum, GDGT-based temperature reconstructions from East African lakes show\namplified cooling with elevation…” both modern and LGM show that at higher\nelevation temperature amplification is bigger than near sea level.\nRe: Thanks for this suggestion. Accordingly, we have revised this part as “During the\nLast glacial maximum (LGM), GDGT-based temperature reconstructions from East\nAfrican lakes show amplified cooling with elevation, resulting in a significantly steeper\nlapse rate than today. Both modern and LGM data show that at higher elevation\ntemperature amplification is greater than near sea level ...” in Lines 245-249.\n\nabout the data availability: the link that was provided to me does not show the fractional\nabundances of branched and iso GDGT or neither the ratios calculated in this study.\nIt only shows the Age (Ma), MAT, and MAT-error. PLEASE make sure to upload all of\nthe data so your study is reproducible.\nRe: Thanks for emphasizing this point. The URL for our data is provided in DATA\nAVAILABILITY. It consists of all related GDGT information for this work, including\nthe fractional abundances of individual brGDGTs, GDGT proxies including GDGT-\n0/cren ratio for isoGDGTs, and brGDGT concentration.\n\nReviewer #4 (Remarks to the Author):\nMy concerns have been resolved after reading the revision and the response letter.\nRe: We are pleased to know that you are satisfied with our revision."}]

Decision letter