Introduction

At times since the last glacial maximum, global and regional temperatures were warmer than today, such as during the Younger Dryas stadial when the Southern Hemisphere experienced warming while the Northern Hemisphere cooled1. High-resolution paleoclimate records from these intervals offer insights into synoptic weather patterns that may become dominant in the coming decades as the climate warms. Located in the southwestern Pacific, from 34 °S to 47 °S (extending to 53 °S when including the southern territorial islands), Aotearoa New Zealand is ideally positioned to investigate long-term changes in both the El Nino-Southern Oscillation (ENSO) and the migration of the southern westerly wind belt through high-resolution lacustrine and fjord sediment archives.

Throughout the last glacial maximum (c. 20 ka), the Southern Alps of New Zealand were extensively glaciated2 with deglaciation characterised by rapid glacial retreat, resulting in the formation of pro-glacial and kettle lakes. The Antarctic Cold Reversal (ACR, c. 14.7–13.0 ka) was dominated by seasonal, wet conditions1,3 and glacial advance4 with a switch to warm and dry conditions during the Younger Dryas (c. 12.9–11.6 ka), while the Northern Hemisphere cooled1,3. While significant advances have been made in reconstructing the Southern Hemisphere millennial climate patterns during the Holocene, the relatively detailed examination of centennial and decadal climate patterns remains challenging5. Here we shed light on the Southern Hemisphere climate evolution since c. 16.5 ka from a unique, high-resolution environmental magnetic record from a sediment core collected from Waiwhakaata, Lake Hayes in Te Waipounamu South Island of New Zealand.

Waiwhakaata, Lake Hayes (44.98 °S, 168.81 °E) is a small (2.76 km2) holomictic lake located in Central Otago, New Zealand. The lake is fed by one small stream at the northern shore (Fig. 1), which drains a 44 km2 catchment with a basement geology of Cretaceous alpine schist. Since the arrival of European settlers (c. 150 years ago), frequent hypolimnetic anoxia occurs in the lake due to a combination of geographical and bathymetric factors, and excessive delivery of macronutrients. Until c. 10,000 years ago, the lake was part of an enlarged Lake Wakatipu6 and, therefore, may have captured a more well-integrated hydrographic record of the wider Wakatipu basin than it does today. See ref. 3 for detailed descriptions of the lake structure, drainage basin, and core lithostratigraphy.

Fig. 1: Location maps and Panorama.
Fig. 1: Location maps and Panorama.
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a Panoramic view of Waiwhakaata, Lake Hayes looking to the northwest. b bathymetric map showing the core location, which was positioned in the depocenter of the lake. c regional overview showing the larger Lake Wakatipu with Lake Hayes (white square). Bathymetric contours in Fig. 1b were redrawn from Lake Hayes [cartographic material]: bathymetry / by J. Irwin; New Zealand Oceanographic Institute. Date 1981. Photo credit Fig. 1a Sylvia Ohneiser.

Results

Magnetic susceptibility varies between 20 × 10−5 and 30 × 10−5 S.I. with peaks of up to 239 × 10−5 (Fig. 2). Saturation remanent magnetisation (Mrs) varies between 0.89 mAm2/kg and 13.7 mAm2/kg with an interval of variable values between 15 ka and c. 13 ka as shown by magnetic susceptibility. Coercivity of remanence (Bcr) is low overall (c. 35 mT) except for the 15–13 ka high variability interval (40–60 mT, Fig. 2). First Order Reversal Curve (FORC) analyses revealed three dominant magnetic signatures. Type A (Fig. 3, samples 3,4,5 and 7) have a narrow central ridge between 10 and 80 mT with limited vertical spread indicating Single Domain (SD) particles with little magnetostatic interactions7. Our choice of field spacing during analyses (2 mT) limits how narrow the ridge will appear on FORC diagrams. Type B (Fig. 3, samples 1–2) have a broader ridge between 0 and c. 40 mT peaking at Bc ≈ 20 mT. Type C samples (Fig. 3, samples 6 and 8 and Fig. 4) have FORC diagrams with an oval central peak centred at Bc ≈ 60–70 mT and Bu ≈ −5 mT, with significant vertical spreading typical of strongly interacting SD particles. Hysteresis analyses of schist, grey glacial clay, silt deposits and regolith/soil from around the lake revealed very low concentrations of magnetic minerals with low coercivity, superparamagnetic grains or multidomain grains (Fig. 5). FORC analysis was conducted on the sample which appeared to have the highest concentration of magnetic minerals, but the data were too noisy to allow characterisation of magnetic minerals (Sample 3, Fig. 5C) except for a faint multidomain signature in Sample 6 (Fig. 5D). X-ray Fluorescence (XRF) ratios Fe/Ti and Mn/Fe (Fig. 2), are divided into an upper section (above c. 300 cm) with limited variability and lower section (below 300 cm) with high amplitude variations and prominent peaks in Mn/Fe.

Fig. 2: Lake Hayes core summary with core images, age model, magnetic properties and XRF elemental ratios.
Fig. 2: Lake Hayes core summary with core images, age model, magnetic properties and XRF elemental ratios.
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a Condensed core image with radiocarbon ages. Laminated grey silt dominates below 380 cm with a gradational shift to diatomaceous olive-green mud above 380 cm. b “Mag Sus” is the magnetic susceptibility, and (c), Saturation remanent magnetisation (Mrs) and (d), Coercivity of remanence (Bcr) are the saturation remanent magnetisation and the coercivity of remanence derived from Isothermal Remanence Magnetisation (IRM) data, respectively. X-ray Fluorescence (XRF) elemental ratio (e), Fe/Ti indicates whether sediments have been affected by Fe reduction and (f), Mn/Fe indicates the degree of water column oxygenation where high values indicate poor oxygenation.

Fig. 3: Core image with magnetic records.
Fig. 3: Core image with magnetic records.
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a Condensed core image with radiocarbon ages (b), “Mag Sus” is the magnetic susceptibility and (c), Coercivity of remanence (Bcr). d Core divisions discussed in the text, and (e), First Order Reversal Curve (FORC) diagrams with corresponding (f) vertical and horizontal profiles of the three FORC morphologies (categories): Type A — biogenic soft and hard magnetite, Type B — detrital magnetite, and Type C — greigite. High resolution FORCs for samples α and β are in Fig. 4.

Fig. 4: High-resolution FORCs of samples from the Younger Dryas and from the ACR in Fig. 3.
Fig. 4: High-resolution FORCs of samples from the Younger Dryas and from the ACR in Fig. 3.
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α and β show details of the magnetic signature of two greigite-bearing samples: α from the Younger Dryas and β from the ACR. The First Order Reversal Curve (FORC) diagram is dominated by oval central peak at 60 mT indicating the presence of greigite with the addition of a thin central ridge indicative of biogenic particles (magnetofossils).

Fig. 5: Rock magnetic data from lithologies surrounding Lake Hayes.
Fig. 5: Rock magnetic data from lithologies surrounding Lake Hayes.
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a Hysteresis data of laminated silt and mud deposits which crop out above the modern level of Lake Hayes. b Hysteresis data of schist and weathered schist showing very low concentrations of magnetic minerals. c, d are FORC analyses of samples 3 and 6 from (a) with low magnetic mineral concentration resulting in poor quality FORC data.

FORCs allow the identification of mixtures of magnetic particles because they simultaneously provide information on domain state, coercivity, concentration, and magnetostatic interactions8. We identified three distinct magnetic mixtures (Fig. 3):

Type A: Biogenic magnetite

Type A FORCs are characterised by a narrow central ridge, which is typical of noninteracting, single-domain biogenic magnetite. These particles are produced by magnetotactic bacteria, a broad group of motile prokaryotes that synthesise iron-based minerals known as magnetosomes9 which they use to navigate (known as magnetotaxis)10. These bacteria have been observed to ‘swim’ in the direction of the local geomagnetic field11, and their magnetosomes (magnetofossils) have been identified in sediments ranging from abyssal marine12 to fresh water13. In microoxic environments, they produce magnetite (Fe3O4), which is the most commonly identified biogenic magnetic mineral12,13. Biogenic magnetite has been further subdivided into biogenic hard and soft from coercivity spectra14, where coercivity differences have been linked to magnetosome morphology15,16. In Lake Hayes samples, horizontal profiles through the central ridge (Bu = 0) indicate that both biogenic hard and soft components are present with a peak response between 20 mT and 60 mT, followed by a gradual decay to 80 mT. Biogenic Soft magnetite appears to be confined to the upper part of the core (Fig. 3 samples 3 and 4), and Biogenic Hard magnetite (Fig. 3 samples 5 and 7) is in the lower part of the core.

Type B: Detrital Magnetite

Is identified by the overlap of a low-coercivity central ridge peaking at or near Bc = 0 on the horizontal profile and a broad base with increasing vertical spread towards Bc = 0 on the vertical profile. The overall coercivity is lower than Type A samples (the peak in the horizontal profile occurs at 20–30 mT, Fig. 3, samples 1 and 2). Type B FORCs indicate magnetite grains with a broad grain size distribution ranging from superparamagnetic to pseudo-single domain17, which we suggest are either sourced directly from surrounding schist or from erosion of soils.

Type C: Greigite

Care must be taken when interpreting FORCs from samples with mixed populations of SP and SD grains because peak coercivities can range widely from c. 70 mT for SD grains to zero for SP grains18. Type C FORC diagrams display an oval central peak at c. 60 mT, which indicates the presence of natural single domain (SD) greigite with substantial magnetostatic interactions19 (Fig. 3, samples 6, 8, and Fig. 4 α and β). Greigite (Fe3S4) is a thiospinel which, in sedimentary environments, can form rapidly during reduction diagenesis20,21. If sufficient reagents are present, the diagenetic reaction will lead to paramagnetic pyrite (FeS2). However, when reagents are limited, intermediate phases such as ferrimagnetic greigite, can form22. An alternative interpretation is that Type C FORCs contain monoclinic pyrrhotite (Fe7S8), however, the coercivity range of this mineral extends beyond the range of the horizontal profiles, and pyrrhotite FORCs have a less oval profile19. Furthermore, pyrrhotite is unlikely to form in low-temperature aqueous reducing conditions23 and is more likely to be of detrital origin (i.e., eroded from basement rocks). The basement rocks of the Lake Hayes drainage basin are Caples and Rakaia terrane schists, which have been reported to contain metamorphic magnetite and minor pyrite and pyrrhotite24. In the Wakatipu basin, coarse (> 3 mm) detrital magnetite is abundant in the Arrow River sediments immediately north of Lake Hayes and in metavolcanic horizons in greenschist facies rocks24. Magnetic analyses of basement schist, glacial deposits, soils and regolith from the lake catchment identified only magnetite (Fig. 5). Therefore, we suggest that magnetic mineralogy of Type C samples is dominated by greigite formed in situ under reducing conditions.

High-resolution FORC analyses of two samples, one from within the Younger Dryas (Fig. 4, sample α at 373 cm) and one from the ACR (Fig. 4, sample β at 400 cm), were carried out to understand better the magnetic mineral compositions. Both analyses revealed an oval central peak centred at c. 60 mT, which is typical of sedimentary greigite, but they also contain the thin, narrow central ridge which is typical of biogenic magnetic particles (magnetofossils). The biogenic contribution, identified with the central ridge, remains relatively stable (from 0.109 mAm2/kg in α to 0.129 mAm2/kg in β, see supplementary table) with identical coercivity distribution in both samples, while the authigenic (abiotic) greigite concentration, identified with the remaining FORC contributions, increases (from 2.03 mAm2/kg in α at 373 cm to 5.40 mAm2/kg in β at 400 cm).

In sulphide-reducing environments9, biogenic greigite can also be produced by bacteria which have so far been divided into many-celled prokaryotes9,25 and large rod-shaped bacteria26. The magnetic properties of biogenic greigite are poorly understood but appear to be similar to those of biogenic magnetite27. However, because the co-existence of biogenic magnetite and greigite is in essence, impossible24, it is reasonable to interpret the narrow central FORC ridge observed in Type C samples as being the signature of biogenic greigite.

Interpretation of magnetic mineralogy

Based on FORC results and magnetic characteristics, we divided the core into three intervals: a lower interval between 480 to 390 cm (Fig. 3, Interval I), a central interval between 390 cm and 360 cm (Fig. 3, Interval II) and an upper interval between 360 cm and the core top (Fig. 3, Interval III).

Interval I – The Antarctic Cold Reversal (480 cm to 390 cm)

The radiocarbon age model indicates that sediments between 480 cm and 390 cm (Interval I) were deposited during the ACR. Because the working half of the core was destructively sampled after magnetic susceptibility measurements were made and several years elapsed until magnetic mineralogy samples were collected from the archive half, the alignment and correlation of magnetic susceptibility with Mrs/Bcr data was made difficult.

Magnetite and greigite have very similar magnetic susceptibility values of 5.8 × 10−4 m3 kg−1 28 and 3.2 × 10−4 m3 kg−1 29 respectively therefore we suggest magnetic susceptibility is not mineralogy sensitive in this interval.

However, because Mrs data are primarily concentration-dependent (like magnetic susceptibility), we suggest that during the ACR, high Mrs and magnetic susceptibility is associated with greigite, while low Mrs and magnetic susceptibility are associated with magnetite intervals.

The fluctuations in magnetic susceptibility, coercivity and magnetic mineral concentrations recorded during the ACR can be interpreted as follow: High coercivity (Bcr) samples have high Mrs, and Type C FORCs indicative of greigite. The alternate low coercivity samples have low Mrs, and Type A FORCs indicative of biogenic magnetite.

Magnetotactic bacteria reside in the water column at the oxic-anoxic transition zone9 or, in the case of well-oxygenated bottom waters, beneath the sediment-water interface. We suggest the presence of biogenic magnetite recovered in the sediments indicates that the lake was aerobic. Greigite samples on the other hand indicate reducing or anoxic conditions either during sediment deposition (i.e., greigite was produced at the sediment-water interface), or after deposition.

The FORC signature of the Type C samples suggested the presence of both biogenic and authigenic greigite. We, therefore, suggest that greigite formation begins with magnetotactic bacteria before the onset of the abiogenic greigite formation, owing to their biomineralizing capabilities at very low iron concentrations. We suggest that greigite in Lake Hayes was produced syndepositionally or near-syndepositionally under the anoxic conditions of the lakebed, regardless of whether greigite was precipitated biologically or chemically. If greigite had formed long after deposition deep in the sediment column, we would not expect it to be confined to thin intervals (< 5 cm) interleaved with thin intervals of biogenic magnetite, the feedstock for iron sulphide minerals such as greigite.

We interpret the oscillations between greigite (Type C samples) and biogenic magnetite (Type A samples) below 390 cm as reflecting alternations between oxic and anoxic conditions. The Fe/Ti ratio in XRF data supports this interpretation because it indicates selective depletion of iron-bearing minerals relative to titanium-bearing minerals (Fe is prone to dissolution during reduction while Ti is not). Prior work in lacustrine systems30 showed that the Mn/Fe ratio is also a useful redox indicator because Mn is relatively more mobile under anoxic conditions and is more sensitive to redox changes than Fe. Accordingly, the varying Mn/Fe ratio in the Lake Hayes record provides additional evidence for episodic changes in the redox state of lake water. However, partitioning of Fe and Mn in aquatic systems is complex and can be influenced by a number of factors31 therefore a combination of complementary paleo-redox indicators should be used. In the case of the Lake Hayes succession, strong evidence of reducing conditions is inferred from the magnetic mineral assemblages combined with the selective depletion of iron-bearing minerals in the Fe/Ti XRF ratio, while peaks in Mn/Fe data may indicate oxygenation events. Previous research on magnetic variations in lacustrine sediments13 led to the suggestion that lakes can experience oscillations between oxic and anoxic states, where oxygen levels become depleted through excess nutrient load and productivity until a mixing event oxygenates the lake.

In temperate climates (between the polar or equatorial regions), lakes can experience annual temperature cycles that can result in thermal stratification. In winter months, for example, lakes can stratify if they become ice-covered and therefore isolated from the atmosphere or in summer months, reduced wind stress and solar surface warming, may also result in stratification32. In this setting, summer thermal stratification ends in the autumn period as the lake loses heat and wind stress increases. Other possible causes for lake stratification may be seasonal ice cover and variations in river input.

Unfortunately, due to very low sedimentation rates in the lake, the seasonal ice cover hypothesis can´t be tested as no observable fine-scale laminae that are typically deposited during prolonged winter ice cover33 could form. However, we consider that because of New Zealand’s maritime influence where warm air masses can penetrate the interior of the land mass at any time of the year, it is unlikely that significant winter ice cover occurred.

Multidecadal changes in river input as a driver for change in stratification or redox state in Lake Hayes are not supported by geochemical records during the ACR 3. However, because annual rainfall is intrinsically linked to the strength of the westerly winds in this sector of the Pacific 3 variations in river input would have a similar effect and be driven by the same process (i.e., more wind results in greater rainfall, higher inflow and more overturning).

We hypothesise that during the ACR interval, alternations in redox conditions recorded in the Lake Hayes sediment core were likely climatically controlled in a similar way as today, where seasonal bottom anoxia happens because of strong summer stratification (and excess nutrient supply) and is followed by winter mixing. We consider that biogenic magnetite intervals indicate enhanced mixing/overturning (more mixing from higher wind stress) periods, and greigite intervals indicate anoxia and stratification (less wind) periods. We suggest that winter wind stress and summer thermal stratification were the main controllers of the redox state of the deep lake waters.

Interval II – The Younger Dryas (390 cm to 360 cm)

The c. 30 cm interval between 360 cm and c. 390 cm (Interval II), corresponds to the Younger Dryas and is dominated by low Mrs, high coercivity, and Type C FORCs indicating the presence of greigite with the Fe/Ti data indicating pervasive Fe dissolution. We suggest this interval indicates persistent reducing conditions and that the lake was stratified and anoxic during the Younger Dryas. Supporting evidence comes from Ca/Ti data 3, which indicates increased carbonate production, which is typically linked to episodes of enhanced evaporation and possible lake closure (i.e., reduced inflow and no outflow)34.

Interval III – The Holocene (360 cm to core top)

Finally, in the upper c. 360 cm (Interval III), magnetic susceptibility has limited variability, while Mrs (Fig. 2) indicates a gradual upcore increase in magnetic grain concentration from c. 360 to c. 250 cm, after which Mrs decreases gradually up the core. Coercivity does not vary greatly, with an average Bcr of 36 mT. A gradual decrease in Bcr after 360 cm may indicate that the transition out of the Younger Dryas was gradual (occurring over several centuries) rather than abrupt. FORC analyses appear to shows an upcore shift from biogenic magnetite to detrital Type B magnetite-dominated mineralogy with supporting evidence for this gradual transition provided by the gradual decrease in Bcr values up core. We do not propose a mechanism for this gradual transition, except that it appears that environmental conditions became unfavourable for magnetotactic bacteria and the production of magnetosomes.

We conducted a spectral analysis of magnetic susceptibility and Fe-Ti XRF data from Interval I. Different age models were tested to include the errors associated with the top and bottom depths of Interval I. With a measurement interval of 5 mm in magnetic susceptibility data the shortest cycle (highest frequency) which can be resolved is 20 mm. When using the average age model, two cycles which exceed the 99% confidence limits are identified in the magnetic susceptibility, which have frequencies of 70 and 52 years (Fig. 6). If using the youngest age model, the cycles are 79 and 55 years and when the oldest age model is used the cycles have a period of 67 and 53 years. Regardless of which age model is used, the spectral peaks are well above the background noise level with a corresponding average Nyquist frequency of 12.8 years as reported by REDFIT. The average sedimentation rate for the entire core is c. 0.3 mm/yr and c. 0.45 mm/yr in Interval I. We did not identify statistically significant cycles in the Fe-Ti XRF data, which we attribute to significantly higher white instrument noise35.

Fig. 6: Spectral analysis of magnetic susceptibility data from Interval I.
Fig. 6: Spectral analysis of magnetic susceptibility data from Interval I.
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Results of magnetic susceptibility data from Interval I using REDFIT-X. Data were converted to the time domain using radiocarbon dates, and Monte Carlo simulations were carried out to determine the confidence Intervals. Two cycles which exceed the 99% confidence limits are identified, which have frequencies of 70 and 52 years.

Discussion

In this sector of the Pacific, several climate oscillations influence interannual climate variability ranging from the annual ENSO36 to the decadal Interdecadal Pacific Oscillation (IPO37). The IPO has been shown to modulate the strength of ENSO38 and, like other climate oscillators in the South Pacific, modulates the frequency of synoptic weather systems, not their intensity39. Sedimentation rates are too low here to resolve the interannual climate oscillations, therefore, the IPO, which has a frequency of roughly 55 years, is the most likely driver of oscillations identified here regardless of which age model is used.

Our understanding of the periodicity of the low-frequency IPO is still relatively poor. Four phases (two cycles) of IPO have been recognised from historical meteorological data through changes in precipitation, surface temperature and mean sea-level pressure; two positive phases spanning 1922–1944 and 1978–1998, respectively, and two negative phases spanning the period 1946–1977 and 1998–202038,39. Paleoclimate reconstructions of the IPO paint a more complex picture. An IPO reconstruction from Antarctic ice cores revealed short-duration (7 ± 5 years) negative phases and long-duration positive phases (61 ± 56 years)40 while reconstructions of the IPO index from a Pacific Basin-wide collection of ice cores showed that a c. 30–70 year multidecadal range was most common for the last c 1500 years but also that the decadal IPO was absent during the Little Ice Age41. While finding an agreed-upon fundamental frequency of the IPO is difficult, cycles detected in the Lake Hayes record with periodicities of between 50 and 80 years are consistent with our current understanding of the IPO.

Our record indicates a strong IPO influence during the ACR, significantly enhancing the impact of ENSO. A high moisture balance has been suggested during this period 3 but no increase in southerly sourced precipitation, which may indicate more westerly and northerly sourced precipitation. We suggest that the strong IPO signal resulted from periods of increased wind (and enhanced rainfall) as modulated by the IPO. Contemporaneous South Island records indicate the snow lines in the Ben Ohau Range began rising at c. 15 ka 4, alpine-glaciers were dynamic42, and chironomid-inferred summer temperature records indicate high amplitude (2–3 °C) temperature fluctuations in the alpine Lake Pukaki1. Glacier mass balance in the Southern Alps of New Zealand is controlled by regional weather patterns rather than average annual temperature43, and therefore, the dynamic glacier margins42 may have been controlled by multidecadal oscillations of synoptic weather patterns we infer from our Lake Hayes magnetic mineral record.

After the ACR, Lake Hayes entered a period of persistent stratification and anoxia for the duration of the Younger Dryas, as interpreted from the magnetic mineral record. Persistent stratification likely indicates little wind and, therefore, reduced precipitation in the basin and possible persistent drought conditions (mega-drought). Magnetic mineral evidence of persistent anoxia and stratification agrees with Ca/Ti data 3, which indicates that enhanced evaporation characterised this period.

After the Younger Dryas, the magnetic minerals indicate a gradual upcore shift from biogenic to detrital magnetite, indicating that environmental conditions became unfavourable for magnetotactic bacteria. Lake Hayes may have been isolated from Lake Wakatipu shortly after c. 10,000 years ago6 which predates the shift to a mixed detrital and biogenic magnetite mineralogy in our record by c. 1500 years. However, because the date is the best estimate, we cannot exclude that the change in lake level may have contributed to the shift in magnetic mineralogy.

Implications for numerical climate models

Our study recognised the IPO in paleoclimate records and demonstrates its influence on regional climate over multi-decadal and centurial timescales. This study confirms a prolonged period of drought dominated in the Wakatipu basin, indicating a regional shift in the hydrologic system occurred during what is considered to be the warmest period of the last 15,000 years in the Southern Hemisphere (the Younger Dryas stadial as defined by Northern Hemisphere records). A persistent feature in regional climate models44,45 suggests this region is likely to experience increased rainfall as temperatures rise. The reconstructions from Lake Hayes suggest that the opposite may have occurred during this analogous future period, with the region entering a ‘mega drought’ of an extended period of reduced rainfall and an inferred reduction in wind stress. Recent research on the reliability of climate models indicates that multidecadal oscillations are currently not well understood46, or apparently absent from many climate models47. More work is needed to understand the impact of the IPO on New Zealand’s climate (and probably elsewhere) over the coming decades, and whether climate models can resolve and predict the varying influence of multidecadal climate oscillations.

Methods

Two sediment cores were collected in 2015 using a UWITEC coring system in c. 33 m water depth 3 and in 2020, hand samples of sediment, regolith and basement rock cropping out around the lake and the Wakatipu basin were collected for magnetic mineral characterisation. Sediments in the UWITEC core samples comprise an upper unit (0–310 cm) of diatomaceous olive-green mud with thin light brown bands, an intermediate unit (310–380 cm) of medium brown to olive green diatomaceous mud with a thin (c. 15 cm) interval of light grey mud (Fig. 2). Below 380 cm sediments grade from brown diatomaceous mud to laminated grey silt (Fig. 2). We limit our interpretations to the upper c 4.8 m for which there is a published radiocarbon age model 3 and use the composite record 3 which was constructed by the alignment of distinctive marker beds and physical properties data (i.e., density, magnetic susceptibility). Magnetic susceptibility was measured on the split core face at 5 mm intervals using a Bartington MS2E point sensor, which has a stratigraphic 3.5 mm resolution and a penetration depth of up to 3.5 mm, where 90% of the signal is derived from within 3.5 mm of the sensor. Magnetic mineral hysteresis, Isothermal Remanent Magnetisation (IRM), and FORC48 were measured on 0.10–0.15 g crushed samples on a Princeton Measurements Corporation Vibrating Sample Magnetometer (VSM, MicroMag 3900) to saturating fields of between 500 mT and 1 T. FORCs were measured with a field spacing of 2 mT, Bc between 0 and 100 mT, and Bu between − 40 and + 40 mT. FORC data were processed using FORCinel49 with smoothing factors (SF) of 4 to 10. Two additional high-resolution FORCs were measured on a Lake Shore Cryotronics 8600 Series VSM at GeoSphere Austria. These analyses were conducted with a Bc between 0 and 140 mT, Bu between − 49.8 mT and + 80.2 mT, a field step size of 0.4 mT where 676 curves were generated with an averaging time 0.16 s and a pause at reversal of 3 sec with a two-step approach to avoid reversal field overshooting50. Stacks of 16 FORC series for each sample were processed using the VARIFORC (VARIable FORC smoothing) processing protocol with a basic SF of 4 and an SF increase of 0.15 per point along Bc and Bu51. In total, IRM and hysteresis was measured on 97 subsamples, with FORCs generated for 10 selected samples. Major element data were collected using an ITRAX core scanner (Cox Analytical Systems) on u‐channels. Data were converted to the time domain using a previously published 14C age model 3, which was developed from analysis of terrestrial macrofossil and charcoal fragments. The radiocarbon age model used and correlation with climate events are the same as originally reported 3 and have uncalibrated errors ranging from ± 24 years at 198 cm (4529 CAL yrs. BP) to from ± 160 years at 393 cm (12955 CAL yrs. BP). Spectral analysis was conducted using REDFIT-X52. Data were converted to the time domain using the previously published radiocarbon age model 3, where the OFAC was 4, HIFAC was 1, data were divided into 5 equal parts and 1000 simulations were carried out to determine the Monte Carlo Confidence Intervals.