The dataset comprises of X ray fluorescence log ratio time series data for two sediment cores from Lago Pato, a small lake basin at 51.3003 S, 72.6786 W and approx 33 m a.s.l., which is topographically separated from Lago del Toro in Torres del Paine (TdP). The data are used to constrain glacier dynamics and lake level change in the TdP and Ultima Esperanza region over the last approx 30,000 cal a BP (30 ka). LP08 was extracted from the current depocentre in November 2007 to March 2008. LP16 was extracted the terrestrial shoreline in November 2015.
This project was funded by the Natural Environment Research Council (NERC) through the British Antarctic Survey (BAS) and an UGent BOF bilateral collaboration project. RMcC was supported by Programa Regional R17A10002 and R20F0002 (PATSER) ANID. We gratefully acknowledge the University of Magallanes (UMAG) and the University of Santiago (Carolina Diaz) for assistance with fieldwork; the NERC/SUERC AMS Radiocarbon Facility for providing initial range-finder radiocarbon dates; the NERC Isotope Geosciences Laboratory (NIGL, now National Environmental Isotope Facility, NEIF, at the British Geological Survey) and Melanie Lang for stable carbon isotope analysis; Aberystwyth University (David Kelly), Durham University (Neil Tunstall and Christopher Longley) and Edinburgh University (Chris Hayward) for use of their core scanning and microprobe facilities and technical support.
Last Glacial Maximum, Patagonia, Southern Hemisphere Westerly Winds, glaciation, lake level changes, palaeoclimate, palaeolimnology
Roberts, S., McCulloch, R., Emmings, J., & Davies, S. (2022). Geochemical X ray fluorescence log ratio time series data for two sediment cores, LP08 and LP16, extracted from Lago Pato, Torres del Paine, Southern Chile (Version 1.0) [Data set]. NERC EDS UK Polar Data Centre. https://doi.org/10.5285/6bd95602-f2e3-4968-8622-c4aeb71c214c
|Access Constraints:||No restrictions apply.|
|Use Constraints:||This data is governed by the NERC data policy http://www.nerc.ac.uk/research/sites/data/policy/ and supplied under Open Government Licence v.3 http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/.|
|ISO Topic Categories:||
|Name||UK Polar Data Centre|
|Organisation||British Antarctic Survey|
|Name||Dr Stephen J Roberts|
|Role(s)||Technical Contact, Investigator|
|Organisation||British Antarctic Survey|
|Name||Robert D McCulloch|
|Organisation||Centro de Investigacion en Ecosistemas de la Patagonia (CIEP)|
|Name||Joseph F Emmings|
|Organisation||British Geological Survey|
|Name||Sarah J Davies|
|Reference:||Roberts, S.J., McCulloch, R.D.M., Emmings, J., et al. (2022) Late glacial and Holocene palaeolake history of the Última Esperanza region of Southern Patagonia. Frontiers in Earth Science, 10. https://doi.org/10.3389/feart.2022.813396
Grinsted, A., Moore, J.C., and Jevrejeva, S. (2004). Application of the cross wavelet transform and wavelet coherence to geophysical time series. Nonlinear Processes in Geophysics 11, 561-566.
Trauth, M.H. (2015). "Time-Series Analysis," in MATLAB® Recipes for Earth Sciences, ed. M. H. Trauth. (Berlin, Heidelberg: Springer Berlin Heidelberg), 151-213.
|Quality:||XRF-CS data from finely laminated glaciolacustrine sediments in Units 1-2 were smoothed to 200 micrometers, other data to 2mm, and equal spaced time-intervals (10-years and 100-years) for use in time series analysis were generated. Time series datasets were centred, standardised (Z-scores), detrended and interpolated using a 10-year or 100-year Piecewise Cubic Hermite Interpolating Polynomial (PCHIP) function, which avoids spline artefacts and preserve the shape of the original XRF-CS data series.|
A chronology for each record was established using Accelerator Mass Spectrometry (AMS) radiocarbon dating of 21 samples from the LP08 record and 15 samples from the LP16 record. Calibration of radiocarbon ages was undertaken in OXCAL v.4.4 using the SHCal20.14C Southern Hemisphere atmosphere calibration curve (SH20). Radiocarbon ages are reported as conventional radiocarbon years BP (14C years BP) ±1sigma; and calibrated ages as 2sigma; (95.4%) ranges, median and mean calendar years BP (cal a BP and cal ka BP, relative to 1950 CE), rounded to the nearest ten years. Age-depth models were developed using Bayesian age-depth modelling software (rBACON v.2.5). Modelled age data mean ages produced by the SH20M1H (Southern Hemisphere, SHcal20, radiocarbon calibration curve) in rBACON, where M1 indicates Model 1 and H indicates the inclusion of a hiatus in the model.
Sediment cores were collected using a UWITEC-gravity corer, Livingston piston corer and a Russian corer from the deepest point (approx 3.5 m of water depth) in Lago Pato:
- LP08 record from 51.3003 S, 72.6786 W, 32 m a.s.l. is 600 cm long
- LP16 record from 51.3031 S, 72.6816 W, 33?34 m a.s.l. is 295 cm long
Contiguous downcore wet-sediment Energy Dispersive Spectrometry (EDS) X-ray fluorescence core scanning (XRF-CS) data was collected using an ITRAX XRF core scanner at Aberystwyth University fitted with a Molybdenum (Mo) anode X-ray tube (settings: 30 kV, 50 mA, count time 10 seconds, at 2 mm contiguous intervals and for LP08 Unit 6 (equivalent to mean ± 2-sigma: 4.5±7.0 years), at 200 μm intervals for LP08 Unit 1 (1.3±4.2 years), with LP08 basal Unit 1 scanned at 100 micrometers, and at 500 micrometers for LP16 Units 2-6 (9.6±17.4 years) and at 200 micrometers for LP16 Unit 1 200 micrometers (1.1±1.6 years). Data from finely laminated glaciolacustrine sediments in Units 1-2 were measured at or smoothed to 200 micrometers (from 100 micrometers interval data) before analysis.
Time series analysis
Log-n element/Ti ratio XRF-CS Z-scores were used for time series analysis (Fast Fourier Transform FFT, periodograms, Lomb-Scargle Power Spectrum, Wavelet Power Spectrum, Peak Identification) in MATLAB. Equally spaced (10-year and 100-year) time-intervals were generated using a Piecewise Cubic Hermite Interpolated Polynomial (PCHIP) function, which avoids spline artefacts and preserve the shape of the original XRF-CS data series (Grinsted et al., 2004; Trauth, 2015). Time series data were detrended (polynomial linear best fit) to remove the long-term linear trend. Second order polynomial Locally Weighted Scatterplot Smoothing (LOESS) 100-year smoothing (0.1 sampling interval with outliers removed) was also used to compare datasets to published data.
Data were analysed in MATLAB v. R2021a, R v. 4.1.0/Rstudio v. 1.4.171, using the R packages Vegan, Rioja, Tidyverse, ggplot2, Ggally v. 2.1.2. Code is available from: https://github.com/stever60/Lago_Pato
|Data Storage:||The LP08 and LP16 datasets are arranged as follows:
The input output csv files are arranged into subfolders as follows. These subfolders represent different time periods in the LP08 and LP16 records. Changing the time period investigated alters the Z-scores produced.
LPLP08_8ka - covering the last 8000 years
LP08_10ka - covering the last 10,000 years
LP08_Unit1 - covering 21,180-29,780 cal a BP
LP08_Unit1_basal - covering 26,490-29,780 cal a BP
LP16_11ka - covering the last 11,000 years
LP16_14ka - covering the last 14,000 years
LP16_Unit1 - covering 20,400-27,550 cal a BP
LP08_LP16_10ka - comparison of dataset pairs for LP08 and LP16 records covering the last 10,000 years
LP08_LP16_21_27ka - comparison of dataset pairs for LP08 and LP16 records covering the 21-27 ka cal BP
LP08_LP16_Fig9_LnFe_Mn - Fe/Mn natural log ratio time series data used in the Frontiers paper for LP008 and LP16 records
The following log ratio dataset pairs were run:
The filename within each folder matches the folder name and indicates the time period covered by the time series. For example:
Output datafiles (e.g., LP08_Unit1_basal_ouput.csv)
The filename within each folder matches the folder name and indicates the time period covered by the time series.
The key for the columns in each dataset pair (e.g., 1_Fe_Mn_&_Mn_Ti) are as follows (in order from left to right.
% As measured data
s1x, s1xn series 1x time scale (cal a BP)
s2x, s2xn series 2x time scale (cal a BP)
series1_input series 1y input data (log ratios)
series2_input series 2y input data (log ratios)
s1n series 1y normalised (Z-scores)
s2n series 2y normalised (Z-scores)
series1ydl series 1y detrended - linear best fit
series1ydlnorm series 1y standardised (Z-scores) detrended (linear best fit)
series2ydl series 2y detrended - linear best fit
series2ydlnorm series 2y standardised (Z-scores) detrended (linear best fit)
% Interpolated data
sx1inter series 1x time scale interpolated (10 or 100 year intervals)
sy1inter series 1y interpolated (10 or 100 year intervals)
sy1norminter series 1y standardised (Z-scores) & interpolated (10 or 100 year intervals)
sx2inter series 2x time scale interpolated (10 or 100 year intervals)
sy2inter series 2y interpolated (10 or 100 year intervals)
sy2norminter series 2y standardised (Z-scores) & interpolated (10 or 100 year intervals)
% Detrended & interpolated data (s = reshaped array into wide format)
x2 or x2s series 1x time scale interpolated (10 or 100 year intervals)
x4 or x4s series 2x time scale interpolated (10 or 100 year intervals)
y2 or y2s series 1y detrended and factor interpolated data - subtracted from mean
y2l or y2sl series 1y detrended and factor interpolated data - subtracted from linear
y4 or y4s detrended and factor interpolated data series 2 - subtracted from mean
y4l or y4sl detrended and factor interpolated data series 2 - subtracted from linear
% Standardized, Detrended & interpolated data
y2ln or y2sln series 1y standardised and detrended data - subtracted from linear best fit
y4ln or y4sln series 2y standardised (Z-scores) and detrended and factor interpolated data - subtracted from linear
% Standardized, Detrended & interpolated periodicity data
s1period periodicity of series 1y standardized (Z-scores) and detrended (subtracted from linear best fit) interpolated data (i.e., y2ln or y2sln)
s2period periodicity of series 2y standardized (Z-scores) and detrended (subtracted from linear best fit) interpolated data (i.e., y4ln or y4sln)
msc Magnitude squared coherence (MSC) of s1period and s2period for the time series
frcspect Frequency cross spectrum (FCS) of s1period and s2period for the time series
08_5ka - covering the last 5000 years