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We analyse new genomic data (0.05–2.95x) from 14 ancient individuals from Portugal distributed from the Middle Neolithic (4200–3500 BC) to the Middle Bronze Age (1740–1430 BC) and impute genomewide diploid genotypes in these together with published ancient Eurasians. While discontinuity is evident in the transition to agriculture across the region, sensitive haplotype-based analyses suggest a significant degree of local hunter-gatherer contribution to later Iberian Neolithic populations. A more subtle genetic influx is also apparent in the Bronze Age, detectable from analyses including haplotype sharing with both ancient and modern genomes, D-statistics and Y-chromosome lineages. However, the limited nature of this introgression contrasts with the major Steppe migration turnovers within third Millennium northern Europe and echoes the survival of non-Indo-European language in Iberia. Changes in genomic estimates of individual height across Europe are also associated with these major cultural transitions, and ancestral components continue to correlate with modern differences in stature. Index for VCF fileIndex for VCF filepost_imputation_Martiniano_et_al_2017_public.vcf.gz.tbiVCF file containing imputed genotype data belonging to 67 newly sequenced and publicly available ancient samples.VCF file containing imputed genotype data belonging to 67 newly sequenced and publicly available ancient samples which we analysed in Martiniano et al. (2017).post_imputation_Martiniano_et_al_2017_public.vcf.gzREADME_Martiniano_et_al_2017Description of the methods used for genotype imputation.

These are ice-penetrating radar data connecting the newly chosen Beyond EPICA Little Dome C core site to the EPICA Dome C core site, collected in late 2019. These data are presented in a paper in The Cryosphere (https://doi.org/10.5194/tc-2020-345), where full processing and collection methods are described. Data collection and processing Data were collected using a new very high frequency (VHF) radar, built by the Remote Sensing Center at the University of Alabama (Yan et al., 2020). The system transmitted 8 us chirps, with peak transmit power of 125--250 W per channel, at 200 MHz center frequency and 60 MHz bandwidth. There were 5--8 operational channels at various points. The antennas were pulled behind a tracked vehicle, with controlling electronics in the rear of the vehicle. Data were collected at travel speeds of 2--3.5 m/s. Data processing consisted of coherent integration (i.e. unfocused SAR), pulse compression, motion compensation (by tracking internal horizons), coherent channel combination, and de-speckling using a median filter. Two-way travel time was converted to depth assuming a correction of 10 m of firn-air and a constant radar wave speed of 168.5 m/us (e.g., Winter et al., 2017). After other processing was complete, different radargrams were spliced together to create a continuous profile extending from EPICA Dome C to the Beyond EPICA Little Dome C core site, and then the data were interpolated to have constant, 10-m horizontal spacing. The re-interpolated data were used for horizon tracing, which was done semi-automatically to follow amplitude peaks between user-defined clicks. For the bed reflection, we always picked the first notable return in the region of the bed. File description The file format is hdf5, which can be read with many programming languages. There are three groups in the file: processed_data, picks, and geographic_information. The processed_data gives the return power matrix (dB), and the depth (m) and two-way travel time (us) for the fast-time dimension. The picks give the depths (m) of different reflecting horizons traced in the corresponding paper. Ages and age uncertainties (kyr), interpolated from the AICC2012 timescale, are included as attributes on each pick. Bed and basal unit picks are included (ageless). The geographic_information gives latitude and longitude (decimal degrees), and the distance along-profile (km). References Bazin, L., Landais, A., Lemieux-Dudon, B., Toyé Mahamadou Kele, H., Veres, D., Parrenin, F., Martinerie, P., Ritz, C., Capron, E., Lipenkov, V., Loutre, M. F., Raynaud, D., Vinther, B., Svensson, A., Rasmussen, S. O., Severi, M., Blunier, T., Leuenberger, M., Fischer, H., Masson-Delmotte, V., Chappellaz, J., and Wolff, E.: An optimized multi-proxy, multi-site Antarctic ice and gas orbital chronology (AICC2012): 120-800 ka, 9, 1715–1731, https://doi.org/10.5194/cp-9-1715-2013, 2013. Winter, A., Steinhage, D., Arnold, E. J., Blankenship, D. D., Cavitte, M. G. P., Corr, H. F. J., Paden, J. D., Urbini, S., Young, D. A., and Eisen, O.: Comparison of measurements from different radio-echo sounding systems and synchronization with the ice core at Dome C, Antarctica, 11, 653–668, https://doi.org/10.5194/tc-11-653-2017, 2017. Yan, J.-B., Li, L., Nunn, J. A., Dahl-Jensen, D., O’Neill, C., Taylor, R. A., Simpson, C. D., Wattal, S., Steinhage, D., Gogineni, P., Miller, H., and Eisen, O.: Multiangle, Frequency, and Polarization Radar Measurement of Ice Sheets, 13, 2070–2080, https://doi.org/10.1109/JSTARS.2020.2991682, 2020. These data were generated in the frame of Beyond EPICA. The project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No. 815384 (Oldest Ice Core). It is supported by national partners and funding agencies in Belgium, Denmark, France, Germany, Italy, Norway, Sweden, Switzerland, The Netherlands and the United Kingdom. Logistic support is mainly provided by PNRA and IPEV through the Concordia Station system. The radar shipment and personnel transportation to Antarctica were provided by U.S. NSF under grant 1921418, which also partly supported the development of the VHF radar. Radar development was further supported by internal funding from the University of Alabama. DL and DDJ were partially supported by the Villum Foundation (grant number 16572). Any opinions expressed and arguments employed herein do not necessarily reflect the official views of the European Union funding agency or other national funding bodies.

This compilation contains data reported in the manuscript Cardenas, Lamb, Jobe, Mohrig, and Swartz, Morphodynamic preservation of fluvial channel belts. As of Nov 2022, this manuscript is submitted to SEPM (Society for Sedimentary Geology) journal The Sedimentary Record. Compilation contains: (1) Table showing the edge coordinates of each channel belt in the associated manuscript. (2) Table showing centerline point coordinates. (3) Table showing all width measurements for each channel belt. (4) A compilation table showing representative geometric measurements for each belt. (5) A python script to generate paleoflow directions from centerline coordinates. (6) A script to generate various geometric measurements from belt edge coordinates. (7) A script to plot histograms of geometric measurements.

3D geological models of dolomitized clinoforms (10 different realisations) and flow simulation results according to Scenario 1 in Teoh, C.P. et al (2021) doi:10.1016/j.marpetgeo.2021.105344. Models are built using surface-based modelling approach (doi:10.1007/s11004-018-9764-8). Flow simulations are run with IC-FERST, using unstructured tetrahedral meshes that adapt to geological heterogeneity and flow behaviour throughout the simulation to improve simulation quality and performance. For each of the 10 stochastic realisations, 5 geological models are available with corresponding flow simulation results: - Only clinoforms and facies boundaries - 1 dolomite body per clinothem (~20% dolomite) - 2 dolomite bodies per clinothem (~40% dolomite) - 3 dolomite bodies per clinothem (~60% dolomite) - 4 dolomite bodies per clinothem (~80% dolomite) Input model files for simulation are provided in Exodus (.e) and GMSH (.msh) formats. Flow simulation settings are provided for IC-FERST in .mpml files (multifluids.github.io) Flow simulation results are provided as: 3D unstructured adaptive mesh in .vtu format, which can be opened with Paraview (www.paraview.org). Time interval between successive mesh outputs is 1 month. In- and outflow rates and volumetric proportions per phase in .csv Naming of files and folders: Sxxxxxx_yyyyz where: 'xxxxxx' is the stochastic seed number used to sample the input statistics and create the geological model 'yyyy' is either 'clino' or 'dolo' to indicate if the model represents respectively only clinoforms, or contains dolomite bodies 'z' corresponds to the number of dolomite bodies per clinothem {"references": ["https://doi.org/10.1016/j.marpetgeo.2021.105344", "https://doi.org/10.1007/s11004-018-9764-8"]}

Death Assemblage - Arkle 2017Raw abundances of death assemblage data from seven localities around St. Croix, USVI. Singletons have been removed and bivalve abundances have been halved to provide a minimum number of individuals (MNI). First two letters in row names (sites) indicate locality (SC=Smuggler's Cove, CH=Christiansted Harbor, PP=Power Plant, SR=Salt River Bay, MP=Molasses Pier, HP=Ha'Penny Bay, DS=Dump Site). First set of numbers in sample labels indicate position on the transect (in meters). Letters B,C, and D indicate depth (see text), and numbers 11 and 12 indicate sampling years (2011 and 2012, respectively). Columns are species names.Arkle_Dead_FINAL.xlsxLife Assemblage - Arkle 2017Raw abundances of life assemblage data from seven localities around St. Croix, USVI. Singletons have been removed. First two letters in row names (sites) indicate locality (SC=Smuggler's Cove, CH=Christiansted Harbor, PP=Power Plant, SR=Salt River Bay, MP=Molasses Pier, HP=Ha'Penny Bay, DS=Dump Site). First set of numbers in sample labels indicate position on the transect (in meters). Letter A indicates that all are living individuals, and numbers 11 and 12 indicate sampling years (2011 and 2012, respectively). Columns are species names.Arkle_Live_Final.xlsxSeagrass Census - Arkle 2017Average seagrass and macroalgal abundances from seven localities around St. Croix, USVI. First two letters in row names (sites) indicate locality (SC=Smuggler's Cove, CH=Christiansted Harbor, PP=Power Plant, SR=Salt River Bay, MP=Molasses Pier, HP=Ha'Penny Bay, DS=Dump Site). First set of numbers in sample labels indicate position on the transect (in meters), and numbers 11 and 12 indicate sampling years (2011 and 2012, respectively). Columns are species names.Arkle_Seagrass_FINAL.xlsx Death assemblages that occupy the upper tens of centimeters of sediment in shallow-marine settings are often subject to extensive mixing, thereby limiting their usefulness in assessing environmentally mediated compositional changes through time in the local biota. Here, we provide evidence that dense, Thalassia-rich seagrass beds preserve a stratigraphic record of biotic variation because their dense root–rhizome mats inhibit mixing. We sampled benthic mollusk assemblages at seven localities in Thalassia-rich beds around St. Croix, USVI, collecting three separate sediment intervals of ~13 cm each to a total depth of ~40 cm below the sediment–water interface, and found evidence that sedimentary intervals preserved compositional stratigraphy. Further, some localities displayed systematic, directional changes down-core. An examination of interval-to-interval changes in composition revealed that compositional variation was unique from locality to locality rather than reflecting coordinated, island-wide transitions. In general, however, relative abundances of epifaunal gastropods and small lucinid bivalves tended to decrease with depth below the sediment–water interface. Quantitative comparisons of life-to-death assemblages from each successive sedimentary interval demonstrated that the shallowest death assemblages were typically more similar to the life assemblages than were deeper assemblages, suggesting that deeper intervals provide records of earlier community states.

The Late Ordovician Mass Extinction (LOME) coincided with dramatic climate changes, but there are numerous ways in which these changes could have driven marine extinctions. We use a palaeobiogeographic database of rhynchonelliform brachiopods to examine the selectivity of Late Ordovician – Early Silurian genus extinctions and evaluate which extinction drivers are best supported by the data. The first (latest Katian) pulse of the LOME preferentially affected genera restricted to deeper waters or to relatively narrow (< 35°) palaeolatitudinal ranges. This pattern is only observed in the latest Katian, suggesting that it reflects drivers unique to this interval. Extinction of exclusively deeper-water genera implies that changes in water mass properties such as dissolved oxygen content played an important role. Extinction of genera with narrow latitudinal ranges suggests that interactions between shifting climate zones and palaeobiogeography may also have been important. We test the latter hypothesis by estimating whether each genus would have been able to track habitats within its thermal tolerance range during the greenhouse-icehouse climate transition. Models including these estimates are favoured over alternative models. We argue that the LOME, long regarded as nonselective, is highly selective along biogeographic and bathymetric axes that are not closely correlated with taxonomic identity. Brachiopod genus local rangescsv file with the local stratigraphic ranges of brachiopod taxa (species where resolved, otherwise genera). Please contact authors with specific questions about the structure of the database and the meaning of column headings. R code for analysis of this dataset is included as Supplemental Material in the publication.Local.Ranges.csv

Simultaneously analysing morphological, molecular and stratigraphic data suggests a potential resolution to a major remaining inconsistency in crocodylian evolution. The ancient, long-snouted thoracosaurs have always been placed near the Indian gharial Gavialis, but their antiquity (ca 72 Ma) is highly incongruous with genomic evidence for the young age of the Gavialis lineage (ca 40 Ma). We reconcile this contradiction with an updated morphological dataset and novel analysis, and demonstrate that thoracosaurs are an ancient iteration of long-snouted stem crocodylians unrelated to modern gharials. The extensive similarities between thoracosaurs and Gavialis are shown to be an almost ‘perfect storm’ of homoplasy, combining convergent adaptions to fish-eating, as well resemblances between genuinely primitive traits (thoracosaurs) and atavisms (Gavialis). Phylogenetic methods that ignore stratigraphy (parsimony and undated Bayesian methods) are unable to tease apart these similarities and invariably unite thoracosaurs and Gavialis. However, tip-dated Bayesian approaches additionally consider the large temporal gap separating ancient (thoracosaurs) and modern (Gavialis) iterations of similar long-snouted crocodyliforms. These analyses robustly favour a phylogeny which places thoracosaurs basal to crocodylians, far removed from modern gharials, which accordingly are a very young radiation. This phylogenetic uncoupling of ancient and modern gharial-like crocs is more consistent with molecular clock divergence estimates, and also the bulk of the crocodylian fossil record (e.g. all unequivocal gharial fossils are very young). Provided that the priors and models attribute appropriate relative weights to the morphological and stratigraphic signals—an issue that requires investigation—tip-dating approaches are potentially better able to detect homoplasy and improve inferences about phylogenetic relationships, character evolution and divergence dates. DataAndResultFilesThis is a zipped file containing (1) The stratigraphic dates and sources in folder TableS1-StratAges (2) the executable PAUP, MrBayes and BEAST files for the following analyses: Morphology Only Morphology and DNA Morphology and DNA (additional sensitivity analyses) Parsimony bootstrap partition frequencies (for all partitions, not just those found in the bootstrap consensus). The BEAST files were written for BEAST 1.8.2 and will need slight edits to run on BEAST 1.8.3 onwards. We have left the files “as is” as these represent the exact files and BEAST version used.Appendix1_includingTableS2Appendix 1 CONSTRUCTION OF THE MORPHOLOGICAL MATRIXAppendix2APPENDIX 2: PHYLOGENETIC ANALYSES AND RESULTSFigsS1-9_andCaptionsFigures S1 to S9 with captions

Data supplement 2 for article: Jackisch, R., Heincke, B. H., Zimmermann, R., Sørensen, E. V., Pirttijärvi, M., Kirsch, M., Salmirinne, H., Lode, S., Kuronen, U., and Gloaguen, R.: Drone-based magnetic and multispectral surveys to develop a 3D model for mineral exploration at Qullissat, Disko Island, Greenland, Solid Earth, 13, 793–825, https://doi.org/10.5194/se-13-793-2022, 2022. https://se.copernicus.org/articles/13/793/2022/se-13-793-2022.html UAV-based orthomosaic in DN (raw) values (091112_Qullissat_eBee_MSI_orthomosaic_DN_20cm.tif) UAV-based digital elevation model (091112_Qullissat_eBee_DEM__36cm.tif) Qullissat study area, Disko Island, Greenland; center Point: 70.05521N, 53.01338W Reference: WGS84 UTM 22N, EPSG 32622 Sensor: Parrot Sequoia multispectral camera UAV: Sensefly eBee plus This research has been supported by the project MULSEDRO, funded by EITRawMaterials (project ID 16193) and the European Union organization EIT, the Helmholtz-Zentrum Dresden-Rossendorf with the Helmholtz Institute Freiberg for Resource Technology and the Geological Survey of Denmark and Greenland. Reflectance products RAW images can be made available upon reasonable request.