Slices of stalagmites from Áaktun Kóopo' Cave revealed several changes in colour throughout their growth (Fig. S1), which may indicate changes in mineralogy or crystal fabrics. To investigate these variations and determine the mineralogical composition of the stalagmites (e.g., calcite vs. aragonite), nine samples were analysed from visually distinct sections of stalagmite E0-C for XRD analysis (Fig. S2a). Additionally, a sample was collected from the bottom portion of stalagmite E1, where the fan-like crystal texture and silky gloss suggested aragonite as the dominant polymorph (Figs. S1 and S2). Each sample consisted of approximately 1 g of carbonate powder that was drilled using a Proxxon machine equipped with a diamond-coated stainless-steel drill bit. XRD measurements were performed at the Institute of Earth Sciences, Heidelberg University, using a Bruker D8 ADVANCE Eco diffractometer. The measurements were conducted with the following parameters: Cu Kα radiation source, 30 kV voltage, 33 mA current, Ni filter, SSD160 detector. Samples were analysed in rotating sample holders over an angular range of 2θ from 5 to 70°, with increments of 0.019° and a counting time of 1 s per step. Peak positions and intensities were processed using Diffrac.Suite EVA software (Bruker).

Thin sections have been used to study the crystal fabrics in further detail, i.e. the individual expression of mineral phases, direction, non-carbonate contamination and/or signs of dissolution (e.g., Frisia et al., 2002; Perrin et al., 2014). Thin sections were prepared from stalagmites E0-B, E0-C, E4, E8, and the upper section of E1. These sections were analysed under a polarized transmitted-light microscope (KEYENCE VHX-6000) at the Institute of Earth Sciences, Heidelberg University.

Laser ablation ICP-MS analyses of selected stalagmites and for Sr/Ca ratios followed established protocols (Warken et al., 2021; Jochum et al., 2012; Schorndorf, 2024) and were performed using a 193 nm ArF excimer laser (NWR193UC by New Wave Research) coupled to an inductively coupled plasma quadrupole mass spectrometer (Thermo Fisher iCAP-Q) at the Institute of Environmental Physics, Heidelberg University. Line scans were conducted along the growth axis of the stalagmite slices using a rectangular spot size of 25×100 µm. The repetition rate was set to 20 Hz, with scan speeds of 5 µm s⁻¹ for stalagmites E1 and E8, and 10 µm s⁻¹ for stalagmite E23-3. To eliminate potential surface contamination, a pre-ablation step was performed along each scan path using a circular spot size of 150 µm at a scan speed of 100 µm s⁻¹ and a repetition rate of 10 Hz. Background counts were measured with the laser in the off mode and subtracted from the raw data. Data processing involved an outlier correction using a floating 1.5 interquartile range (IQR). To account for matrix effects, blank-corrected count rates of ⁴³Ca and ⁸⁸Sr were normalized to the ⁴⁴Ca signal, which served as an internal standard for the total ablation efficiency. External calibration was performed using silicate glass NIST SRM 612, with reference values provided by Jochum et al. (2011). Drift corrections were applied through linear interpolation between two standard measurements taken before and after each ablation path. The resulting Sr/Ca elemental ratios are presented as mass concentration ratios.

For stalagmites E0-C, E1, and E23-3, approximately 50–90 µg of powdered samples were drilled using a Micromill (2010 A Sherline) equipped with a micro milling cutter (TiSiN) of 500 µm in diameter. Most samples were analyzed for their stable isotope composition of oxygen (δ18O) and carbon (δ13C) at the Institute of Earth Sciences, Heidelberg University, using a ThermoFinnigan MAT253Plus gas source mass spectrometer equipped with a Thermo Fisher Scientific Kiel IV carbonate device. Quality control is based on the analysis of an in-house standard (Solnhofen limestone, δ13CVPDB=+1.38±0.03 ‰ and δ18OVPDB=-4.59±0.06 ‰) calibrated to the reference material IAEA-603 (calcite; δ13CVPDB=+2.46±0.01 ‰ and δ18OVPDB=-2.37±0.04 ‰). A part of the samples of E0-C was analysed at Elemtex Ltd., Cornwall, UK, using an isotope ratio mass spectrometer (IRMS) (Thermo Scientific Delta V) coupled with a Gasbench II. Here, quality control is performed using a Carrara marble standard (δ13C =2.10 ‰, δ18O =-2.01 ‰) and a second in-house calcite standard (δ13C =2.89 ‰, δ18O =-6.15 ‰), calibrated directly against NBS18 and NBS19.

External reproducibility at both labs is better than 0.04 ‰ for δ13C_VPDB and 0.07 ‰ for δ18O_VPDB at the 1σ confidence level, and all δ13C and δ18O values are reported relative to Vienna Pee Dee Belemnite (VPDB) standard.

A total of 157 samples from Áaktun Kóopo' speleothems as well as the three drip water samples were analysed using high-precision ²³⁰Th/U dating at the Institute of Environmental Physics, Heidelberg University. For the analysis, small sample plates weighing approximately 100 mg were cut perpendicular to their growth direction using a diamond wire saw and subsequently leached in weak acid, weighed, dissolved in ultra-clean nitric acid and spiked with our in-house triple-spike solution (“TriSpike”, ²³³U, ²³⁶U and ²²⁹Th) (Kerber et al., 2023). For drip water analysis, about 15 to 30 mL of sample was weighed and spiked with “TriSpike”, acidified with ultra-clean nitric acid, subsequently dried down and re-dissolved. Overall, the preparation involving sample leaching, dissolution, spiking, and wet column extraction chromatography using Eichrom UTEVA resin followed established protocols (Wefing et al., 2017; Matos et al., 2015; Douville et al., 2010). Chemical blanks are regularly monitored and commonly below 0.4 fg for ²³⁴U and 0.04 fg for ²³⁰Th (Kerber et al., 2023, 2025).

Isotope measurements were performed with a multi-collector inductively coupled plasma source mass spectrometer (MC-ICP-MS, Thermo Fisher Neptune plus) using a semi-static multi-cup setting as described by Kerber et al. (2023). Mass spectrometry techniques and data treatment procedures are detailed in Kerber et al. (2023, 2025). Data analysis was performed using a Python-based GUI application (Kerber et al., 2025). Ages were calculated using the half-lives provided by Cheng et al. (2013) for ²³⁰Th and ²³⁴U as well as by Jaffey et al. (1971) for ²³⁸U. All uncertainties are reported at the 2σ level, excluding errors associated with half-life values.

To constrain recent carbonate deposition, the tops of presumably modern speleothems were analysed using radiocarbon dating. Small calcite samples (10–20 mg) were cut from the tops of stalagmites E0-C, E1, and E8 using a diamond wire saw at the Institute of Environmental Physics, Heidelberg University. To avoid contamination by ambient air, the samples were leached in 4 % hydrochloric acid prior to hydrolysis and graphitization. A detailed description of the sample preparation routine is provided in Therre et al. (2021). The resulting graphite–iron compounds were measured using a 200 kV tandem mini carbon dating system (MICADAS) accelerator mass spectrometer (AMS) at the Curt-Engelhorn Center for Archaeometry in Mannheim, Germany (Kromer et al., 2013; Synal et al., 2007). Details regarding long-term blank values and external standard reproducibility can be found in Beisel et al. (2025) and Therre et al. (2021).

The age-depth models for selected stalagmites were constructed using a suite of established approaches: linear interpolation, linear regression, Bchron (Haslett and Parnell, 2008), Bacon (Blaauw and Christen, 2011; Blaauw et al., 2021), COPRA (Breitenbach et al., 2012), and StalAge (Scholz and Hoffmann, 2011). Model construction followed and extended the protocols of the Speleothem Isotopes Synthesis and Analysis (SISAL) working group (Roesch and Rehfeld, 2020), which is provided as a supplement to Comas-Bru et al. (2020); SISAL.AM. In case of identified hiatuses, the age-depth models were split at the depth of the growth interruption into separate sections. This approach improves model convergence and allows more methods to return successful chronologies, rather than including the hiatuses in the models. For each model, the median and the 2.5 %–97.5 % quantiles across the ensemble were extracted to define the central age estimate and its 95 % uncertainty range at each depth. To derive the final chronology, all models that returned successful chronologies were included. At each depth, the composite chronology was calculated as the arithmetic mean of the selected models (equal weights): μfinald=1N∑i=1NMi(d) where Mi(d) is the age of model i at depth d, and N is the number of selected models. The corresponding 95 % uncertainty was derived by combining (i) the between-model spread (standard error of model ages) and (ii) the mean within-model uncertainty (average 95 % half-widths) in quadrature: σfinal,95=σbetween2+σwithin‾2 Where geochemically defined annual cycles from Sr/Ca variations were identified, the resulting layer-count chronologies were treated as an independent constraint rather than being incorporated into the composite chronology. These were converted to absolute ages by anchoring the layer-count chronology either (i) to the year of stalagmite extraction, if continuous growth until collection can be assumed, or (ii) to the U-Th age with the smallest analytical uncertainty within the counted interval. For intervals in which seasonal variations were less pronounced or individual cycles were indistinct, a conservative uncertainty of ±0.5 layers per 10 counted layers was assigned, reflecting the potential for missed or ambiguous cycles.

Dense sampling in some stalagmites allows for first-order linear two-endmember mixing regressions (Osmond type 1 – like “isochrons”). In this study, such “isochrons” are applied only to closely spaced, co-genetic subsamples and are interpreted as local, first-order estimates of R02i, similar to the approaches of Warken et al. (2020) or Stinnesbeck et al. (2020). The “isochron” approach using ISOPLOT (Ludwig and Titterington, 1994; Ludwig, 2008; Vermeesch, 2018), produced five successful “isochrons” from three stalagmites (E0-C, E4, E8), which yielded R02i ranging from 6.4±2.4 to as large as 19±10 (Fig. S5, Sect. S1.1). To apply stratigraphic constraints (e.g., Roy-Barman and Pons-Branchu, 2016; Hellstrom, 2006), we used samples with no detectable ²³²Th as stratigraphic anchors, as their ages are unaffected by initial Th contamination and because those provide a steady growth pattern. In addition, we adopt the assumption that stalagmite tops with elevated ²³²Th are younger than uncorrected ages below them, but older than the year of collection. From Stalagmite E0-C, 34 of 51 samples could be placed in stratigraphic order using individual R02i ranging from 11.5 to 49 (Fig. 4b). In contrast, for other stalagmites, such as E0-B or E1, only single ages can be corrected using a stratigraphically derived ratio. Lastly, we exploit distinct cyclic variations in Sr/Ca ratios from LA-ICP-MS measurements (Fig. S4) to estimate relative age differences between ²³⁰Th/U measurements, thus allowing to correct the ages and estimate R02i (James et al., 2025). For example, in stalagmite E23-3, in total 331±17 Sr/Ca minima are counted from 0 to 84 mm dft. Assuming the topmost layer to correspond to 2022 AD (the year of collection), the R02i is estimated to 26 ± 7 to align the ²³⁰Th/U ages with the layer-counted age model presuming Sr/Ca seasonal cycles within uncertainties of both methods. In contrast, in the upper section of stalagmite E8 (8.5–26 mm dft), ages could only be corrected with individual R02i ranging from 7 to 35.5 to match the Sr/Ca-based age-depth model. Overall, to correct stalagmite ages with the different approaches, R02i ranging from 4 to 68 are found (Table S3). Notably, only one sample from stalagmite E1 requires a ratio as high as 68, while most other samples need ratios between 30 and 50 or lower. R02i < 20 are only found for three ages via stratigraphic constraint and for nine ages by isochrons. Therefore, samples without specific estimates are corrected by using the mean ratio of 35.5 ± 32.5 to account for the full range of possible initial Th corrections (Table S3). Taken together, these independent approaches indicate that strongly elevated initial Th activity ratios are plausible and necessary at least in parts of the record to obtain stratigraphically consistent age models, even though the exact numerical values of R02i for individual, highly contaminated samples remain poorly constrained.

Overall, our analysis shows that significantly elevated and strongly variable R02i (up to 68) are required to correct stalagmite ages from Áaktun Kóopo' Cave for initial Th contamination (Table S3). These values greatly exceed the commonly assumed upper continental crust ratio of (230Th/232Th) ∼0.8 (Taylor and McLennan, 1985). However, they align with findings from other tropical sites (e.g., the Caribbean and Southeast Asia) where similarly high ratios have been reported (e.g., Beck et al., 2001; Richards and Dorale, 2003; Partin et al., 2007; Carolin et al., 2013; Arienzo et al., 2015; Hoffmann et al., 2010; Moseley et al., 2015; Ridley et al., 2015; Stinnesbeck et al., 2020; Vieten et al., 2024a, 2024b; Steidle et al., 2021; Warken et al., 2021; James et al., 2025). Furthermore, our measurements demonstrate that this pronounced variability is largely unsystematic, occurring not only spatially across different stalagmites within the same cave, similar to findings in Larga Cave, Puerto Rico (Vieten et al., 2024b; Warken et al., 2020; Kerber et al., 2025), but also temporally within individual stalagmites.

The vast spread of R02i may be attributed to the varying contributions of multiple Th reservoirs within the karst and epikarst environments (Li et al., 2022; Wortham et al., 2022; Huang et al., 2024). Rather than a single source, Th can be transported as a complex mixture of detrital particles (e.g., clay minerals, aluminosilicates, iron oxyhydroxides), colloidal phases, and organic complexes (Morton et al., 2001; Nascimento et al., 2019; Reiller et al., 2002; Richards and Dorale, 2003). In tropical environments with relatively young reef limestones as host rock, such as the YP, the rapid dissolution and varying mobilization of these different organic and inorganic fractions lead to highly variable initial Th isotopic signatures. This dynamic reflects the observations from various aquatic systems, where the (230Th/232Th) activity ratio has been shown to vary by orders of magnitude (Scott, 1968; Hubert et al., 2006; Hirose et al., 2012; Töchterle et al., 2022; Moore and Sackett, 1964; Moore, 1981). Consequently, highly elevated and time-variable R02i should be regarded as the rule rather than the exception in such settings, fundamentally questioning the applicability of a static “bulk earth” value for age corrections. In such settings, initial Th corrections are best treated as approximations with explicit uncertainty, constrained where possible by multiple, independent estimates of R02i.

Because we do not find any systematic behaviour that would allow to predict R02i a priori, developing accurate age models remains challenging. Initial Th corrections are particularly critical for younger speleothems (less than a few thousand years old), as even small uncertainties in the R02i can significantly influence age models. While monitoring ZAC and drip water provides a baseline for estimating R02i (Wortham et al., 2022; Li et al., 2022), this approach often fails to capture long-term temporal variability. In Áaktun Kóopo' Cave, for example, the (230Th/232Th) activity ratio from supposedly modern carbonate and drip-water samples remains far below the highest estimated ratios (up to 68) required to align stalagmite ages with the sedimentary sequence. Therefore, to reduce the uncertainty of corrected ages in similar karst settings, it is strongly recommended to employ a combination of independent validation methods. Integrating ²³⁰Th/U dating with radiocarbon or other radiometric dating methods (Akers et al., 2019; Huang et al., 2024; Sengupta et al., 2025) or annual layer counting (e.g., Warken et al., 2025; Domínguez-Villar et al., 2012; James et al., 2025; Faraji et al., 2021; Nagra et al., 2017) provides a more robust framework to constrain these erratic detrital inputs and secure reliable chronologies.

Figure 4 shows the individual age-depth models constructed for stalagmites E0-B, E0-C, E1, E4, E8, and E23-3, as described in detail in Sects. 2 and S1.1. Although some of the analysed stalagmites exhibit decade-long growth interruptions, their chronologies overlap and suggest continuous carbonate deposition in Áaktun Kóopo' Cave over the last 2.7 kyr with mean growth rates of 200–300 µm a⁻¹ (Fig. 5).

While E0-B covers the oldest growth period (633 ± 161 BC to 403 ± 54 AD, Fig. 4a), the growth of its “sibling” E0-C can be divided into three periods separated by hiatuses: (1) 538 ± 56 to 811 ± 52 AD; (2) 994 ± 29 to 1311 ± 15 AD; and (3) 1451 ± 22 to 1835 ± 53 AD (Fig. 4b). The last millennium is also covered by several speleothems (Fig. 5), with E1 growing from 1440 ± 39 to 1577 ± 42 AD and between 1635 ± 24 to 1926 ± 20 AD (Fig. 4c). Stalagmite E4 grew from approximately 228 ± 88 to 1611 ± 118 AD, even though high initial Th contamination led to the rejection of 24 of 28 samples (Fig. 4d). Similar challenges arose for the chronology of E8, where growth could be tightly constrained for the latest part (1605 ± 24 to 1733 ± 33 AD, Fig. 4e). Lastly, the growth history of stalagmite E23-3 can be divided into two periods, with the older part covering 1070 ± 7 to 1347 ± 9 AD, and the upper part spanning 1441 ± 5 AD to the year of collection in 2022 AD (Fig. 4f).

Figure 5 compares the late Holocene Áaktun Kóopo' Cave growth history with periods covered by other published stalagmite records from the northern YP. Notably, while most records are from the northwestern or central YP (Kennett et al., 2022; Medina-Elizalde et al., 2010; James et al., 2025, 2026; Frappier et al., 2014; Medina-Elizalde et al., 2016a), there is a marked absence of stalagmite proxy records from the northeastern YP for the last 1600 years, with only one record covering an earlier period between 1037 BC and 397 AD (Medina-Elizalde et al., 2016b). Given the known regional heterogeneity in past hydroclimate reconstructions and projected trends, the Áaktun Kóopo' Cave record thus fills an important gap in the region (Douglas et al., 2016; Obrist‐Farner et al., 2023; Steinman et al., 2022).

While precise ²³⁰Th/U dating establishes the absolute chronological framework for these stalagmites, the numerous growth interruptions (hiatuses) observed throughout their growth histories provide an additional, independent means to cross-validate these highly corrected age models. Detectable either as macroscopic millimeter- to centimeter-thick mud layers or via microscopic thin-section analysis, these hiatuses indicate discrete environmental events that simultaneously affected multiple stalagmites within the cave (Fig. 4).

One prominent flooding layer (∼1 cm thick) appears in stalagmites E0-C, E1, and E23-3, which were all collected from the same cave area at a similar elevation. This layer likely represents a single event around 1400 AD. By comparing the ²³⁰Th/U dates across the stalagmites, the timing can be constrained between ∼1350 and ∼1430 AD. The latest confirmed carbonate precipitation prior to the event is recorded by stalagmite E23-3, which yielded a ²³⁰Th/U age of 1347 ± 9 AD. Following the flood, stalagmite E1's growth resumed directly upon the detrital substrate at 1428 ± 40 AD. The sediment sequence of Sullivan et al. (2025) from Cenote Muyil ca. 80 km south of Áaktun Kóopo' Cave recorded a period of intense hurricane activity between 1285 and 1420 AD in the area, which suggests that a major storm event may have caused the flooding of the cave during that time. Indeed, historical records report a major hurricane (“hurricane of the four winds”) that impacted the area in 1464 AD (Sullivan et al., 2025; Masson and Lope, 2014), which is however not fully consistent with our date, suggesting another extreme event caused the mud layer in Áaktun Kóopo' Cave. Thinner layers (0.5–1 mm) in stalagmites E1 and E8, which also stem from the same area in the cave, correspond to a shorter interruption that may have lasted only months to years. The timing can be precisely dated to 1624 ± 24 AD within the continuous age models of stalagmite E8, perfectly aligning with a brief hiatus observed in E1 between ∼ 1590 and ∼ 1630 AD. In addition to detecting and dating single extreme events that may have impacted the environment and the people living in the area, such markers could serve as key stratigraphic tie-points, analogous to ash layers in marine sediments or ice cores, for anchoring proxy records and refining chronologies (Warken et al., 2025). Fine laminations (alternating carbonate and mud/clay) of stalagmite E4 even suggest recurrent flooding in the part of the cave near the entrance. While the current efforts limit a more precise dating of the individual layers, future studies could deliver a more detailed history of local flooding (Frappier et al., 2014; Denniston and Luetscher, 2017; Gonzalez-Lemos et al., 2015).

Although many hiatuses coincide with clear flooding layers, other interruptions could reflect periods of reduced effective moisture due to reduced precipitation and/or enhanced evapotranspiration, or other processes. For example, the special morphology of Áaktun Kóopo' Cave (Fig. 1b) makes it conceivable that a sufficiently high-water table sealed cave ventilation in some sections of the cave, leading to elevated cave CO₂. Because Áaktun Kóopo' Cave was visited and modified by the Maya, at least during the Late Preclassic (-250 to 300 AD) and Early Classic (300–600 AD) periods (Gómez, 2020), human influence on speleothem development can also not be ruled out. Deforestation and agricultural practices above the cave, for example, may have altered soil cover and infiltration pathways, thereby influencing recharge and ultimately affected speleothem formation. Likewise, cave use and ritual activities might have modified the cave's microclimate (e.g., CO₂ concentration, humidity, temperature) or sedimentological conditions in ways that impacted speleothem formation, although such influences remain speculative. Disentangling natural hydrological variability from potential anthropogenic influences on speleothem formation remains a challenging task and requires a comprehensive multi-proxy approach that explores all aspects of speleothem formation, aimed at separating climatic from human-induced signals.

Evaluating the diverse performance of the applied age-depth modelling algorithms reinforces the necessity of our ensemble approach. Consistent with Comas-Bru et al. (2020), no single algorithm universally outperformed the others across all speleothems, as the underlying statistical assumptions of each model respond differently to variations in growth rates and dating resolution. This methodological variability becomes especially evident when comparing the models against independent layer-counting chronologies: while the Bacon model closely matched the visual layer counts for stalagmite E23-3, Bchron and linear interpolation provided the tightest fits for different sections of E8. Furthermore, the individual algorithms diverged significantly in their chronological treatment of extreme events, such as the major flooding layers and resulting hiatuses. The chosen algorithm significantly affects not only the estimated duration of an event, but also its absolute timing. For instance, the first hiatus in stalagmite E0-C (at 40 mm depth) has an estimated duration ranging from 96 (+58/-55) years (linear regression) to 174 (+85/-88) years (Bacon). Consequently, the absolute timing of the growth interruption shifts across models: Bchron dates the onset of the hiatus to 1302 (+25/-4) AD, whereas linear regression places it almost four decades later at 1341 (+26/-25) AD. Constructing a composite “mean” age model is therefore justified, as relying on any single algorithm risks either artificially over-smoothing or over-estimating the timing and duration of discrete environmental events.

To further assess the robustness of our age models, we compared the independent stable oxygen (δ18O) and carbon (δ13C) isotope records of stalagmites E0-C, E1, and E23-3 for their overlapping growth periods. The chronology of stalagmite E23-3 is considered the most reliable anchor for the last 400 years. It is constrained by continuous counting of seasonal Sr/Ca cycles and anchored to the year of extraction (2022 AD), resulting in a cumulative counting error of ±17 years at 1691 AD. When plotting the stable isotope time series using the individually established ²³⁰Th/U age-depth models, the records already show an apparent coherence in both δ18O and δ13C values over the past 600 years (Fig. 6a). Despite being fed by different drip sites within the same cave chamber, the stalagmites capture nearly identical multi-decadal to centennial-scale geochemical patterns. This coherence suggests that the individual proxy records are driven by a common external forcing, such as regional hydroclimate variability affecting cave recharge and prior calcite precipitation (PCP), rather than localized kinetic or drip-specific effects (Skiba and Fohlmeister, 2023; Baker et al., 2019; Treble et al., 2022). However, the individual chronologies appear to be shifted relative to each other, reflected in the weak or insignificant correlations between the stable isotope records. For example, the largest significant coefficient of 0.2 (p<0.01) occurs for the δ18O records of E23-3 and E1. To precisely align the time series, a wiggle-matching procedure was performed using QAnalySeries software (Kotov and Pälike, 2018; Pälike, 2024), similar to the approach of Huang et al. (2024). The upper section of the E1 δ18O record (3–61 mm dft) was tuned to the E23-3 reference record using 10 tie points, while the upper section of E0-C (5–38.6 mm dft) was subsequently matched to E1 using 11 tie points. As a result, the maximum shift of E1 with respect to E23-3 is ca. 20 years directly after the thin flooding layer around 1620 AD, while the other sections are only corrected by <7 years. The chronology of E0-C requires larger shifts by around 25–70 years with respect to E23-3. Overall, the resulting adjustments required to align these independent records fall entirely within the calculated 95 % uncertainty ranges of their respective ²³⁰Th/U age-depth models (Fig. 6b). After the synchronization, the δ18O (δ13C) record of E1 exhibits a correlation of 0.62 (0.61) with E23-3 and 0.42 (0.51) with E0-C (p<0.01, respectively), demonstrating a striking coherence between the stalagmite records. The successful replication of stable isotope patterns across three distinct stalagmites and the tuning required to synchronize them strongly validate our geochronological approach. It demonstrates that the strategies used to correct for elevated and highly variable initial ²³⁰Th contamination, specifically the integration of ²³⁰Th/U dating with seasonal trace-element layer counting and stratigraphic constraints, yield robust and accurate chronologies suitable for high-resolution paleoclimate reconstruction on the YP.