U-Pb detrital zircon data to Eastern Betic basement and basin samples_Supplementary to Booth-Rea et al. (under review)

U-Pb detrital zircon LA-IC-MS data from the SE Betic basins and their metasedimentary basement, supplementary to Basin Response to Slab Tearing under the Eastern Betics by Booth-Rea et al. (submitted to Tectonics). Supplementary data and code to Booth-Rea et al., *Basin response to slab tearing underthe Eastern Betics*, submitted to *Tectonics*. Author: Carlos J. Garrido (Instituto Andaluz de Ciencias de la Tierra, CSIC-UGR, Granada, Spain).License: CC BY 4.0. This archive contains the LA-ICP-MS U-Pb detrital zircon dataset and the analysis andplotting code that underlie the detrital-zircon provenance study, so that the age spectra,the inter-sample comparison and the maximum depositional ages can be reproduced. ## Contents ### data/| File | Description ||---|---|| `UPb_zircon_data.xlsx` | LA-ICP-MS U-Pb analyses for all detrital and reference samples (isotopic ratios, ages, concordance). Primary dataset. || `KS_Dmax_matrix.csv` | Pairwise two-sample Kolmogorov-Smirnov D-max distance matrix between the concordant best-age distributions. || `MDS_coordinates.csv` | Non-metric MDS raw and rotated coordinates for each sample. || `MDS_metadata.json` | MDS run metadata (algorithm, number of initialisations, random seed, Kruskal stress-1). || `detritalPy_input_all.xlsx` | detritalPy-format input built from `UPb_zircon_data.xlsx` (all analyses). || `detritalPy_input_concordant.xlsx` | detritalPy-format input restricted to concordant analyses (feeds the figures). || `reference_AG_Jabaloy2021.xlsx` | Aguilas Arc reference samples AG-03 and AG-20 (data from Jabaloy-Sanchez et al., 2021). || `reference_PT_SanchezMartinez2012.xlsx` | Iberian Massif Permo-Triassic reference samples PT-4 and PT-6 (data from Sanchez-Martinez et al., 2012). || `literature_pools.xlsx` | Compiled reference distributions for the Alpujarride and Nevado-Filabride complexes (from the cited literature). | ### Data sources of the reference inputsThe reference/comparison distributions are third-party published data included here only to make thefigures reproducible: Aguilas Arc samples AG-03 and AG-20 from Jabaloy-Sanchez et al. (2021); IberianMassif Permo-Triassic samples PT-4 and PT-6 from Sanchez-Martinez et al. (2012); and the Alpujarride /Nevado-Filabride literature compilation. Cite those publications for the underlying data. ### scripts/| File | Description ||---|---|| `convert_supp_to_detritalpy.py` | Builds the detritalPy-format input files from the U-Pb data table. || `plot_fig_KDE_CDF.py` | Kernel density estimate, cumulative distribution and pie panels (manuscript Figure 10). || `plot_fig_MDS.py` | Kolmogorov-Smirnov distance computation and non-metric MDS plot (manuscript Figure 12). | ## Software and parameters The analysis uses [detritalPy](https://github.com/grsharman/detritalPy) (Sharman et al., 2018,*The Depositional Record* 4, 202-215) and the SMACOF non-metric MDS implementation ofscikit-learn. Python 3. Calculation parameters:- 238U/235U = 137.818; decay constants 1.55125e-10 and 9.8485e-10 yr-1.- Concordance filter: 90 <= 100*t206/238 / t207/235 <= 110.- Best age: 206Pb/238U below 950 Ma, 207Pb/206Pb above.- KDE bandwidth 15 Ma; histogram bin 40 Ma.- MDS: metric = false, n_init = 50, max_iter = 300, random seed = 42; Kruskal stress-1 = 0.0625. ## Reproduction 1. `python scripts/convert_supp_to_detritalpy.py` regenerates the detritalPy input from the U-Pb data table.2. `python scripts/plot_fig_KDE_CDF.py` and `python scripts/plot_fig_MDS.py` regenerate the figures and the K-S / MDS output files (`KS_Dmax_matrix.csv`, `MDS_coordinates.csv`, `MDS_metadata.json`). Scripts read their inputs from `data/` and are configured with relative paths; run them fromthe archive root.