Europe's Lost Frontiers, volume 1: Context and Methodology

Description

Europe's Lost Frontiers was the largest directed archaeological research project undertaken in Europe to investigate the inundated landscapes of the Early Holocene North Sea - the area frequently referred to as 'Doggerland'. Funded through a European Research Council Advanced Grant (project number 670518), the project ran from 2015 to 2021, and involved more than 30 academics, representing institutions spread geographically from Ireland to China. A vast area of the seabed was mapped, and multiple ship expeditions were launched to retrieve sediment cores from the valleys of the lost prehistoric landscapes of the North Sea. This data has now been analysed to provide evidence of how the land was transformed in the face of climate change and rising sea levels. This volume is the first in a series of monographs dedicated to the analysis and interpretation of data generated by the project. As a precursor to the publication of the detailed results, it provides the context of the study and method statements. Later volumes will present the mapping, palaeoenvironment, geomorphology and modelling programmes of Europe's Lost Frontiers. The results of the project confirm that these landscapes, long held to be inaccessible to archaeology, can be studied directly and provide an archaeological narrative. This data will become increasingly important at a time when contemporary climate change and geo-political crises are pushing development within the North Sea at an unprecedented rate, and when the opportunities to explore this unique, heritage landscape may be significantly limited in the future. Cover Title Page Copyright page Frontispiece Dedication Funding Contents Page List of Figures General Editor’s Preface The Lost Frontiers Team Authors’ details Acknowledgements Chapter 1 Europe’s Lost Frontiers: context and development Vincent Gaffney and Simon Fitch Figure 1.1 Survey areas prior to Europe’s Lost Frontiers discussed in this chapter. (1) North Sea Palaeolandscape Project (2) Humber REC (3-4) West Coast Palaeolandscape Project. ASTER DEM is a product of METI and NASA. ETOPO2v2 is the property of the Nat Figure 1.2 Area of Doggerland mapped by the North Sea Palaeolandscape Project (Gaffney et al. 2009: Figure 3.23). Figure 1.3 Red flag mapping from Gaffney et al. (2007: Figure 9.8). This image combines threat and uncertainty data based on distance to feature and depth of overlying sediment. The lack of sediment cover and direct association with identified features wi Figure 1.4 Distribution of features located within the southern North Sea during the NSPP and BSSS projects. Table 1.1 Numbers and area of features, excluding coastlines, identified through the NSPP and BSSS projects (2008-2012). After Gaffney et al. 2011: Table 5.1 Figure 1.5 Map used in the final ERC application showing course of two submerged river valleys to be targeted for coring by the Lost Frontiers project team, overlaid on NSPP project base map (Gaffney et al. 2007). Figure 1.6 Initial modification of the Europe’s Lost Frontiers coring programme following funding in 2016. Figure 1.7 Additional modifications to Europe’s Lost Frontiers coring programme following BREXIT. Figure 1.8 Final Europe’s Lost Frontiers coring programme. Figure 1.9 Europe’s Lost Frontiers core study area (1), Cardigan and Liverpool Bays (3) and area of study added as part of the Brown Bank survey (2). Figure 1.10 Iterative research methodology within Europe’s Lost Frontiers. Chapter 2 Beyond the site: A re-evaluation of the value of extensive commercial datasets for palaeolandscape research Simon Fitch and Eleanor Ramsey Figure 2.1 Timeslice at 0.076s through the Southern North Sea MegaSurvey 3D seismic dataset. The NSPP study area is outlined in blue and the extended study area discussed within this paper is outlined in red. Figure 2.2 Graph of the frequency from the PGS MegaSurvey 3D seismic data. Figure 2.3 Additional, original 3D datasets utilised for comparison with data generated through MegaSurvey processing. Table 2.1: Additional, original 3D datasets used for cross comparison purposes. Figure 2.4 Data comparison for survey Z3NAM1988A. Figure 2.5 Frequency values within the 3D legacy seismic volumes assessed within this study. Figure 2.6 Frequency values within the Parametric Echo Sounder dataset. Figure 2.7 Cross-checking between horizontal and vertical slices within the 3D dataset. (A) shows correlation across a wide area with multiple responses along highlighted line, whilst (B) shows the correlation across highlighted line for a single feature. Figure 2.8 Features within sample area, digitised within SMT Kingdom. Figure 2.10 Features within the ArcGIS project cleaned and simplified. Figure 2.9 Features identified within sample area, imported into an ArcGIS project. Figure 2.11 A timeslice with opacity filters applied (B), whilst (A) is the resulting interpretation of features derived from image B. It is clear the combination of opacity filters on the timeslice supports fine resolution imaging of small-scale features Figure 2.12 An RMS slice from the Outer Silver Pit area. The slice is generated from the volume between 0s and 0.1s. Figure 2.13 Base horizon layer imported from SMT Kingdom into GIS. Figure 2.14 Areas used to split the horizon point dataset. Figure 2.15 Detail within Area 1, showing band divisions used to de-stripe the data. Figure 2.16 Interpolated raster of Area 1 prior to manual de-striping. Figure 2.17 Interpolated raster of Area 1 after manual de-striping. Figure 2.18 3D vertical exaggeration of features within Area 1 using ArcScene. Figure 2.19 Interpolated raster mosaic after values for Area 1 and Area 2 had been re-evaluated. Figure 2.20 A 3D Geobody Model, constructed from the seismic timeslices, and displayed within the seismic volume. Figure 2.21 A channel visualised by cutting the geobody model to reveal the base of the channel model. By using such methods, it is possible to understand, more fully, the morphology and formation of such structures. Chapter 3 A description of palaeolandscape features in the southern North Sea Simon Fitch, Vincent Gaffney, Rachel Harding, James Walker, Richard Bates, Martin Bates and Andrew Fraser Figure 3.1 GIS Mapping of the features recorded by the Europe’s Lost Frontiers project. Figure 3.2 Seismic line from ‘Gauss 159B’ survey acquired in 1990 by the RGD and BGS over the Dogger Bank. A Holocene channel can clearly be seen to be incised into the underlying late Pleistocene deposits (Dogger Bank Formation). Figure 3.3 Areas divisions of landscape features within the study area. Figure 3.4 Cross section across the southern flank of the Dogger Bank. The Holocene features can be seen to incise into the underlying late Pleistocene deposits. Figure 3.5 Example of the later Holocene reuse of pro-glacial channels. This is evidenced by smaller (black) channels cut within the main valley and the formation of dendritic feeders on the side of the valley. Figure 3.6 The main drainage channels of the Dogger Bank drain south into a major channel located at the foot of the bank and in the area of the Oyster Ground, eventually flowing to the west and into the Outer Silver Pit. Figure 3.7 Mottling of the seismic data within the Oyster ground can clearly be seen in this image. A number of small palaeochannels can also be seen through the mottling. Figure 3.8 Area 1, early Holocene features of the Dogger Bank. The main watersheds are shown as dashed black lines, the features in the southwest of Area 1, including the Shotton River, would have been the longest-lived structures on the Dogger Bank. Figure 3.9 Map of the Eastern Sector/Area 2. Figure 3.10 The extent of wetland response is outlined within the red hashed area. The location of BRITICE core 147VC is marked in orange. Figure 3.11 Interpretation of a seismic line crossing the base of the Dogger Bank area (near the area marked B in Figure 3.8) clearly shows a large channel running at the base of Dogger Bank (shown here as the DB5 unit between 141VC and 140VC) (Roberts et Figure 3.12 Cross section across the east of the Oyster ground. The topographic rise which forms the watershed is apparent. Figure 3.13 Location of mapped features within Area 3. Figure 3.14 Topographic depressions southeast of the Outer Silver Pit (Area 3) Figure 3.15 early Holocene landscape features in Area 4. Figure 3.16 Mapped palaeochannels in Area 2 flow towards the -40m bathymetric contour, below this line virtually no features are mapped. This supports the hypothesis that the axial area was a marine inlet during the Holocene/Mesolithic. Figure 3.17: Major features, Late Palaeolithic c. 11,500 BP. Figure 3.18 Coastlines of early Mesolithic Doggerland c. 10,000 BP. Figure 3.19 Coastlines of Mesolithic Doggerland c. 8500 BP. Figure 3.20 Coastlines of the earliest Neolithic c. 7000 BP. Chapter 4 From extensive to intensive: moving into the mesolithic landscape of Doggerland Simon Fitch Chapter 5 Figure 4.1 Location of the Arch-Area_1 study area is shown by a red box. Bathymetric data courtesy of EMODNET Bathymetry Portal, ETOPO1 topographic data courtesy of the NCEI and NOAA. Figure 4.2 The NSPP 2007 interpretation of the channel system overlain on EMODNET bathymetry. Figure 4.3 Multibeam Bathymetric image of the survey area generated through the Humber REC. Figure: 4.4 Humber REC 2D seismic line over main channel and tributary channel Figure: 4.5 Humber REC 2D seismic line showing several strong reflectors in the main channel. Figure 4.6 A timeslice from the 3D seismic data at 0.076s derived from the PGS Megamerge dataset. The red box is the position of the Humber REC 2D survey, and the position of vibracores VC39/39A and VC40 are shown as yellow circles. Chapter 5 The archaeological context of Doggerland during the final Palaeolithic and Mesolithic James Walker, Vincent Gaffney, Simon Fitch, Rachel Harding, Andrew Fraser, Merle Muru and Martin Tingle Figure 5.1 A) The Colinda ‘harpoon’, found within a chunk of ‘moorlog’ peat dredged from the Leman / Ower banks off the Norfolk coast in 1931 (after Flemming 2002); B) A bone point recovered from beach walking at Massvlakte 2 in the Netherlands (courtesy Figure 5.2 Temperature curve for the Final Pleistocene and Early Holocene (Late Glacial and Postglacial between 17 and 7 thousand years ago) as derived from Greenland Ice Core data, and redrawn from Price (2015). Note the climatic variability of the Final Figure 5.3 Map showing the projected coastlines of Doggerland and the southern North Sea since the final millennia of the Last Glacial Maximum, with key dates for the transgression highlighted. Table 5.1 Mesolithic sites and findspots from territorial waters, the nearshore zone (12 nautical miles of the shoreline) of the North Sea basin. For category Type: CF = Collection of Finds; SF = Single Find; (U) = Unstratified; (S Figure 5.4 The sites and findspots located on the map are a combination of the SplashCOS viewer database, and data points presented in Tables (5.1 and 5.2), with the exception of findspots from Norwegian waters beyond the extent of the map. See this volum Figure 5.5 Four snapshots of landscape evolution across the period of 10,000–7000 cal BP. The period in question spans both the 8.2 ka cold event, and the Storegga tsunami, and shows different stages of Doggerland as it transitioned into an archipelago an Figure 5.6 Anders Fischer’s model for the predictive location of submerged Mesolithic sites has been used to great effect in the nearshore waters in and around Denmark. Image from Fischer (2007). The model shows potentially favourable site locations in di Figure 5.7 Figure 5.7 River Valleys active in the Mesolithic, identified through seismic survey and palaeobathymetry, and marked by blue arrows. Figure 5.8 The location of Core ELF001A where evidence of Storegga tsunami run-up deposits in highly localised areas prompted reconsideration of the event’s impact. Chapter 6 The Southern River: methods for the investigation of submerged palaeochannel systems Simon Fitch, Richard Bates and Rachel Harding Chapter 7 Table 6.1 Geological deposits within the study area Figure 6.1 The location of the Southern River is within the box on the main map. Figure 6.2 The location of the 2D seismic data shown in Figures 6.3 and 6.4 is indicated by the black line (top). The lower image is an example of the original 2D Boomer dataset used for targeting the cores within the Southern River. Figure 6.3 2D Boomer data after bandpass filtering applied. Figure 6.4 2D Boomer data after amplitude and gain correction applied. Figure 6.5 A combined Bathymetric and seismic data surface of the Southern River. The dendritic network is visible at the head of the river, whilst sinuousity increases as the river proceeds south towards the location of the Holocene coastline. Figure 6.6 A seismic cross section showing the position of the Humber REC core Arch VC51 and Europe’s Lost Frontier’s cores ELF006 and ELF001A. Figure 6.7 The distinctive laminated sediments (SRF6) that produce a clear signal in the seismic data are visible in these images of cores ELF033 and ELF054. Table 6.2 Seismic facies within the Southern River system Chapter 7 Establishing a lithostratigraphic and palaeoenvironmental framework for the investigation of vibracores from the southern North Sea Martin Bates, Ben Gearey, Tom Hill, David Smith, John Whittaker and Erin Kavanagh Figure 7.1 Distribution of cores taken during Europe’s Lost Frontiers Figure 7.2 Flow diagram illustrating pathways of samples in the laboratory. Figure 7.3 Cold storage facility for the Lost Frontiers Project at Lampeter (Left). Core recording (Right). Table 7.1. ELF 045, lithology table. Figure 7.4 Cores ELF 47 and ELF 51. Figure 7.5 Basic lithological profiles drawn up in the Southern Valley. Table 7.2. Cores sampled in project. Abbreviations as follows: P1, profile 1, uncalibrated OSL; P2, profile 2, calibrated OSL; D, OSL sediment ages. Table 7.3. Example of data from rapid assessment of cores samples. Table 7.4 Detailed assessment of microfossils from ELF 047. Table 7.5. Cores selected for pollen and diatom investigation. Table 7.6. Cores samples for macrofossil analysis. Chapter 8 Sedimentary Ancient DNA Palaeoenvironmental Reconstruction in the North Sea Landscape Robin Allaby, Rebecca Cribdon, Rosie Everett and Roselyn Ware Chapter 9 Figure 8.1 Differential sedaDNA fragmentation (top) and deamination (bottom) damage patterns in Doggerland palaeoenvironments. Fragmentation expressed as the lambda parameter of the exponential distribution of sedaDNA fragment sizes. Deamination expressed Figure 8.2 Coring sites used for sedaDNA analysis. A) Cores 1-20. B) Cores in range 21-60 over the Southern River area. C) Cores 20-60. D) Core sites selected for deep sequencing. Estimated 8200 BP coastline shown in black and estimated Storegga tsunami r Chapter 9 Palaeomagnetic analysis of cores from Europe’s Lost Frontiers Samuel E. Harris, Catherine M. Batt and Elizabeth Topping Figure 9.1 Locations of cores used in this study. Figure 9.2 Schematic representation of the detrital remanent magnetisation mechanism from left to right - how the acquisition of the geomagnetic field occurs in sediments. Figure 9.3 Location of the UK archaeomagnetic PSVC (Meriden: 52.43°N, -1.62°E), UK Lake Windemere sequence WINPSV_12k (Avery et al. 2017), and FENNOSTACK comprised of seven lake sediment sequences from four lakes (Snowball et al. 2007). Figure 9.4 Sampling of core ELF019 during the first sampling trip (© Erin Kavanagh). Table 9.1. Summary of palaeomagnetic sampling details with core locations. Table 9.1. Summary of palaeomagnetic sampling details with core locations. Figure 9.5 Palaeomagnetic analysis procedure followed when full analysis takes place. Table 9.2 The stage of palaeomagnetic analysis carried out on each core to date: X denotes completion, P denotes partial analysis. Magnetic susceptibility carried out on obtained samples at the University of Bradford (1) and carried out using the handheld Table 9.2 The stage of palaeomagnetic analysis carried out on each core to date: X denotes completion, P denotes partial analysis. Magnetic susceptibility carried out on obtained samples at the University of Bradford (1) and carried out using the handheld Figure 9.6 Comparison of the Inclination data isolated through PCA with associated errors against the WINPSV-12k (Avery et al. 2017) calibration curve. Figure 9.7 Left: Magnetic susceptibility values for core ELF001A averaged from three separate runs and corrected for drift of sensor. Features on the plot are noted in the text. Right: Image of the core for comparisons. Table 9.3 Definitions of magnetic proxies referred to in text and used to characterise the magnetic minerals present. Table 9.3 Definitions of magnetic proxies referred to in text and used to characterise the magnetic minerals present. Figure 9.8 Stratigraphic trends of the rock magnetic parameters for ELF001A. The plots show the variations in a) magnetic susceptibility, b) susceptibility of ARM, c) S-ratio, d) Saturation Isothermal Remanent Magnetisation (SIRM), e) ARMχ/SIRM ratio, f) Figure 9.9 Left: Magnetic susceptibility values for core ELF002 averaged from three separate runs and corrected for drift sensor. Features on the plot are noted in the text. Right: Image of the core for comparisons. Figure 9.10 Left: Magnetic susceptibility values for core ELF003 averaged from three separate runs and corrected for drift sensor. Features on the plot are noted in the text. Right: Image of the core for comparisons. Figure 9.11 Left: Magnetic susceptibility values for core ELF019 averaged from three separate runs and corrected for drift sensor. Features on the plot are noted in the text. Right: Image of the core for comparisons. Figure 9.12 The declination and inclination values plotted down core for ELF019 from the analysis of 21 samples. Figure 9.13 Down core plot of magnetic proxies calculated for core ELF019. Chapter 10 Applying chemostratigraphic techniques to shallow bore holes: Lessons and case studies from Europe’s lost Frontiers Alexander Finlay, Richard Bates, Mohammed Ben Sharada and Sarah Davies Chapter 11 Figure 10.1 A summary of the benefits of typical analytical tools utilised in chemostratigraphic studies and their acronyms. Table 10.1 Elements commonly utilised for archaeological and paleoenvironmental research (summarised from Davies et al. 2015 and Chemostrat multiclient report NE118). Table 10.1 Elements commonly utilised for archaeological and paleoenvironmental research (summarised from Davies et al. 2015 and Chemostrat multiclient report NE118). Figure 10.2 Location map of cores referred to in this paper. Bathymetric data is derived from the EMODnet Bathymetry portal - http://www.emodnet-bathymetry.eu. Topographic data derived from the NOAA ETOPO1 dataset, courtesy of the NCEI - https://www.ngdc. Figure 10.3 PCA of elemental data for core ELF19 showing the likely mineralogical and material drivers for variation in elemental compositions. a - component 1 and 2, b - component 2 and 3. Figure 10.4 Chemostratigraphic zonation of core ELF19. Si/Rb likely reflects variations in grain size with higher values being more Sand (Quartz) rich and higher Rb being more Clay rich. Ca/Rb likely reflects variations in carbonate (Ca) compared to clay Table 10.2 Likely elemental affinities for core ELF19. Table 10.2: Likely elemental affinities for core ELF19. Table 10.3 Chemical definition of Chemo Zones and boundaries for core ELF19. Table 10.3 Chemical definition of Chemo Zones and boundaries for core ELF19. Figure 10.5 Boxplots showing the correlation of observed mineralogy and chemistry within core ELF19. Table 10.4 Integrated chemical and ecological results for core ELF19. Figure 10.6 This figure demonstrates an excellent match in the chemostratigraphic zonation of core ELF19 and ecological biostratigraphic data. Figure 10.7 Orkney core locations Figure 10.8 The elemental variations utilised to define the chemostratigraphic zonation in the study area. Sr/Br likely reflects variations in shell material (Sr - aragonite) and organic material (Br). Sr/Rb likely reflects variations in shell material (Sr - aragonite) and Clay (Rb). Si/Br likely reflects variations in sand (Si - Quartz) and organic material (Br). Table 10.5 Chemical, sedimentological and environmental interpretation of chemo zones and integrated facies identification. Figure 10.9 Chemostratigraphic correlation of chemo zones in wells A, B and C Figure 10.10 Chemostratigraphic correlation of chemo sub zones in wells A, B and C. Figure 10.11 Chemostratigraphic zonation of core ELF1A (from Gaffney et al. 2020). Sr likely reflects the amount of shell material (aragonite) Rb likely reflects the amount of clay, Si likely reflects the amount of sand (Quartz) and Zr the amount of detrital zircon in the core. Figure 10.12 Chemostratigraphic zonation of the Stroregga tsunami deposit preserved in core ELF1A (from Gaffney et al. 2020). Table 10.6 Chemo facies identified in core ELF1A (see Gaffney et al. 2020 supplementary information for full discussion). Figure 10.13 Comparison of the relative density of core ELF1A calculated from XRF data to the interpreted seismic data (from Gaffney et al. 2020). Table 10.7 A summary interpretation of geochemical and seismic datasets. Chapter 11 Introduction to geochemical studies within Europe’s Lost Frontiers Mohammed Ben Sharada, Ben Stern and Richard Telford Chapter 12 Figure 11.1 Locations of the three cores mentioned in the text. Table 11.1 Core identifiers, location and depth. Table 11.1 Core identifiers, location and depth. Table 11.2 The percentage of organics and carbonates. Table 11.2 the percentage of organics and carbonates. Figure 11.2 Extracted ion chromatogram (EIC), for 71m/z showing n-alkanes in the sample ELF002. Figure 11.3 Extracted ion chromatogram (EIC)’ for 71m/z, showing n-alkanes in the sample ELF007 Figure 11.4 Extracted ion chromatogram (EIC)’ for 71m/z, showing n-alkanes in the sample ELF009. Figure 11.5 Fatty acids found in sample ELF002. Figure 11.6 Fatty acids found in sample ELF007. Figure 11.7 Fatty acids found in sample ELF009. Figure 11.8 XRD pattern of sample ELF002. Figure 11.9 XRD pattern of sample ELF007. Figure 11.10 XRD pattern of sample ELF009. Table 11.3 Characteristic (2θ) values, and the d-spaces of standards and the obtained samples pattern. Figure 11.11 Comparison between the ELF002 pattern and the standard of quartz, berlinite and calcite. Figure 11.12 PXRD of ELF007 overlain with reference patters of quartz, berlinite and halite. Figure 11.13 PXRD of ELF009 overlain with reference patters of quartz and halite. Chapter 12 Constructing sediment chronologies for Doggerland Tim Kinnaird, Martin Bates, Rebecca Bateman and Aayush Srivastava Chapter 13 Figure 12.1 Locations of cores mentioned in text. Figure 12.2 For successful OSL dating, both environmental and mineral characteristics are important: zeroing during transport and deposition is a function of environmental conditions and luminescence behaviour. Figure 12.3 Illustrative luminescence-depth plots for the Doggerland cores: illustrating, (A., ELF05B) stratigraphic breaks and temporal discontinuities, (B., ELF012) rapid sedimentation and short chronology, (C., ELF022) slow sedimentation and long chron Figure 12.4 Sampling strategy for ELF cores – illustrated with core ELF001A: (a) core, with sub-units identified; (b) core, with sampling positions indicated; (c) removal of sediment for OSL profiling, OSL dating and dosimetry. Figure 12.5 Illustrative luminescence-depth plots for ELF001A: on the left, IRSL and OSL net signal intensities and depletion indices; on the right, apparent dose and sensitivity distributions. Figure 12.6 De distributions for ELF001A, 90-150µm, shown relative to the stratigraphy of the core. Units for ELF001A as discussed in the text. Figure 12.7 Stored dose estimates for the 90-150µm and 150-250µm quartz fractions.  Table 12.1 Stored dose estimates for the 90-150µm quartz fractions from ELF001A (lab code, CERSA114). Figure 12.8 Dosimetry of core ELF001A: semi-quantitative and absolute down-core variations in radionuclide concentrations. Table 12.2 Weighted combinations of OSL depositional ages for ELF001A. Figure 12.9 (left) Apparent vs stored dose estimates for discrete depths in core across a subset of sampled cores, encompassing terrestrial, littoral and marine deposits; (right) Quartz SAR OSL depositional ages shown relative to depth in core for the sam Chapter 13 Building chronologies for Europe’s Lost Frontiers: radiocarbon dating and age-depth modelling Derek Hamilton and Tim Kinnaird Chapter 14 Figure 13.1 Locations of cores mentioned in this chapter. Figure 13.2 Age-depth model for ELF001A. Each distribution represents the relative probability that an event occurred at some particular time. For each OSL measurement two distributions have been plotted, one in outline, which is the original result, and Figure 13.3 Age-depth model for ELF007. The model is described in Figure 13.2, with the exception that the outline of the radiocarbon dates is based on the simple calibration of those measurements, whereas the solid ones are the result of the modelling. Figure 13.4 Age-depth model for ELF034. The model is as described in Figures 13.2 and 13.3. Figure 13.5 Calibrated humin fraction and humic acid pairs for depths 180, 185, 193, 202, and 209cm in core ELF034. Figure 13.6 Detail of the bottom of the age-depth model for ELF034. In this detail the humin fraction and humic acid dates at each level have been plotted side-by-side, rather than combined as in Fig 13.4, to show the relationship of each result to the co Chapter 14 A four-dimensional approach to solving problems of behaviour and scale Phil Murgatroyd, Eugene Ch’ng, Tabitha Kabora and Micheál Butler Chapter 15 Simulating a Drowned Landscape: Figure 14.1 The simulation conceptual framework. Figure 14.2 3D visualisation package, showing part of the Southern River valley terrain with simulated sea level. Figure 14.3 A 3D render of the output of the forest dynamic modelling package. Figure 14.4 Graphical output from the landscape modelling package showing areas with differing amounts of inundation over time. Figure 14.5 A screenshot of the quadtree-based large-scale modelling infrastructure, showing herbivore agents responding to resources in a landscape. The red squares show the dynamic partitioning of the environment resulting from the quadtree structure. Figure 14.6 The ELF Augmented Reality sandbox. Figure 14.7 The ELF Augmented Reality sandbox in use. Figure 14.8 The Model 1.1 simulation study area. Figure 14.9 Relative sea-level change over the last 21,000 years in the North Sea region from Glacial Isostatic Adjustment (GIA) model reconstructions (Bradley et al. 2011; Shennan, Bradley and Edwards 2018). Figure 14.10 Table of data showing headings. Figure 14.11 Graph showing one calendar year’s data of water height and atmospheric pressure effect. Figure 14.12 Graph showing 14 year’s water height data. Figure 14.13 Flowchart of the Europe’s Lost Frontier models. Chapter 15 Greetings from Doggerland? Future challenges for the targeted prospection of the southern North Sea palaeolandscape Simon Fitch, Vince Gaffney, James Walker, Rachel Harding and Martin Tingle Chapter 16 (S-2) Figure 15.1 Areas designated for windfarm development within UK and Belgian waters and survey lines associated with the Brown Bank and Southern River study areas (The Crown Estate ©, bathymetry derived from EMODNET. Topography derived from ETOPO) Figure 15.2 Survey on the Southern River estuary Figure 15.3 A flint hammerstone fragment, approximately 50mm wide, was retrieved during a 2019 survey of the Southern River valley (offshore north of the Norfolk coast) from (or near) a surface dated to 8827±30 cal BP SUERC-85715 (Missiaen et al. 2021). S Chapter 16 Supplementary Data Chapter 17 Supplementary data to ‘The archaeological context of Doggerland during the Final Palaeolithic and Mesolithic’ by Walker, Gaffney, Fitch, Harding, Fraser, Muru and Tingle James Walker, Vincent Gaffney, Simon Fitch, Rachel Harding, Andrew Fraser, Merle Muru and Martin Tingle  Supplementary data to ‘Constructing sediment chronologies for Doggerbank, North Sea’ by Kinnaird, Bates, Bateman and Srivastava Tim Kinnaird, Martin Bates, Rebecca Bateman and Aayush Srivastava Tim Kinnaird, Martin Bates, Rebecca Bateman and Aayush Srivastava Table 17-1. Observations / inferences from preliminary OSL screening and subsequent calibrated OSL characterisation, example ELF001A Figure 17.1 Equivalent dose distributions for units 4, 5, 6 and 7 from ELF001A as histogram plots Bibliography Back cover