Mid-Pliocene Shorelines of the US Atlantic Coastal Plain — an Improved Elevation Database with Comparison to Earth Model Predictions

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Earth-Science Reviews 145 (2015) 117–131

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Mid-Pliocene shorelines of the US Atlantic Coastal Plain — An improved elevation database with comparison to Earth model predictions

A. Rovere a,b,⁎,P.J.Heartyc, J. Austermann d,J.X.Mitrovicad,J.Galeb,R.Mouchae, A.M. Forte f,M.E.Raymob a MARUM, University of Bremen and ZMT, Leibniz Center for Tropical Marine Ecology, Germany b Lamont-Doherty Earth Observatory, Columbia University, NY, United States c Department of Environmental Studies, UNC Wilmington, NC, United States d Department of Earth and Planetary Sciences, Harvard University, MA, United States e Department of Earth Sciences, Syracuse University, NY, United States f Département des Sciences de la Terre et de l'Atmosphère, UQAM, Canada article info abstract

Article history: For nearly a century, the Atlantic Coastal Plain (ACP) of the United States has been the focus of studies investigat- Received 3 September 2014 ing Pliocene and Pleistocene shorelines, however, the mapping of paleoshorelines was primarily done by using Accepted 20 February 2015 elevation contours on topographic maps. Here we review published geologic maps and compare them to Available online 20 March 2015 paleoshoreline locations obtained through geomorphometric classification and satellite data. We furthermore present the results of an extensive field campaign that measured the mid-Pliocene (~3.3–2.9 Ma) shorelines of Keywords: the Atlantic Coastal Plain using high-accuracy GPS and digital elevation models. We compare our new dataset US Atlantic Coastal Plain fi Mid-Pliocene shoreline to positions and elevations extracted from published maps and nd that the extracted site information from ear- Sea level lier studies is prone to significant error, both in the location and, more severely, in the elevation of the Dynamic topography paleoshoreline. We also investigate, using geophysical modeling, the origin of post-depositional displacement Glacial isostatic adjustment of the shoreline from Georgia to Virginia. In particular, we correct the elevation of our shoreline for glacial isostatic adjustment (GIA) and then compare the corrected elevation to predictions of mantle flow-induced dynamic topography (DT). While a subset of these models does reconcile the general trends in the observed elevation of the mid-Pliocene shoreline, local discrepancies persist. These discrepancies suggests that either (i) the DT and GIA models presented here do not capture the full range of uncertainty in the input parameters; and/or (ii) other influences, such as sediment loading and unloading or local fault-driven tectonics, may have contribut- ed to post-depositional deformation of the mid-Pliocene shoreline that are not captured in the above models. In this context, our field measurements represent an important observational dataset with which to compare future generations of geodynamic models. Improvements in models for DT, GIA and other relevant processes, together with an expanded, geographically distributed set of shoreline records, will ultimately be the key to obtaining more accurate estimates of eustatic sea level not only in the mid-Pliocene but also earlier in the Cenozoic. © 2015 Elsevier B.V. All rights reserved.

Contents

1. Introduction...... 118 2. Literaturemaps,geomorphometricmapsandremotesensingdatasets...... 118 3. FieldmeasurementsanddatafromDEMs...... 120 3.1. Elevationofthemid-Plioceneshoreline...... 120 3.2. Theinnercontinentalshelfinmid-Pliocene...... 121 3.3. Observedshorelinesandpaleorelativesealevels...... 124 4. Comparison between literature maps and ﬁelddata...... 125 5. Warpingofthemid-Plioceneshoreline...... 125 6. Conclusions...... 129

⁎ Corresponding author at: MARUM — Center for Marine Environmental Sciences, University of Bremen, Room MARUM II 3230, Leobener Str., D-28359 Bremen, Germany. Tel.: +49 42121865871. E-mail address: [email protected] (A. Rovere).

Acknowledgments...... 129 AppendixA. Supplementarydata...... 129 References...... 129

1. Introduction present the results of two ﬁeld expeditions in which we measured the mid-Pliocene shoreline at 21 sites from Georgia to Virginia. This infor-

The last time in Earth's history that atmospheric CO2 levels were as mation is supplemented with constraints at an additional 31 sites high as today (~400 ppmv, Pagani et al., 2009) was the mid-Pliocene where the mid-Pliocene shoreline has been identified on DEMs from (~3.3 to 2.9 Ma), a period that preceded the onset of extensive northern the US National Elevation Dataset. We also present an overview of hemisphere glaciation and that was characterized by global mean tem- sitesalongtheACPwheremid-Pliocenemarine(seafloor) sedimentary peratures as much as 3 °C warmer than the present (Raymo et al., 1996; facies have been identified and we attempt to calculate indicative Dowsett et al., 2009). Thus, understanding the mid-Pliocene warm peri- ranges and the reference water level associated with the measurement od (MPWP) allows us to explore climate sensitivity and polar ice sheet of the scarp to obtain the elevation of paleo sea level. All these datasets, stability in a slightly warmer world. Indeed, the MPWP has served as a including original field data and vectors derived from literature maps, target for the testing of climate and ice sheet models designed to predict are included as supplementary material and represent the most com- the future response of Earth's climate to increasing levels of greenhouse prehensive elevation database for the mid-Pliocene shoreline of the gases (e.g. Pollard and Deconto, 2009; Dowsett et al., 2010; Haywood Atlantic seaboard yet produced. et al., 2010; Bragg et al., 2012). However, the evaluation of climate Finally, we compare our derived position and elevation of the model results has been hampered by the limitations of the available Pliocene shoreline with published data and with geophysical predic- paleoclimate data sets and, in particular, by uncertainty in the proxies tions of post-depositional deformation to address two major questions used to investigate the maximum eustatic sea level (or minimum concerning the Pliocene sea-level history of the eastern US seaboard: polar ice volume) attained during the MPWP. (1) What is the accuracy of published mid-Pliocene shoreline estimates Estimates for peak MPWP sea level range from 10 to 35 m above the on the ACP with respect to our newly collected elevation and corre- present (e.g. Dowsett and Cronin, 1990; Miller et al., 2012)andavalue sponding field data?; and (2) how well do the geophysical predictions of 25 m has been typically adopted in numerical climate model simula- of GIA and DT match the observed deformation of the Pliocene tions (e.g., Dowsett et al., 2010; Haywood et al., 2013). Field observa- paleoshoreline along the ACP? The answers to each of these questions tions that can provide constraints on sea level during the MPWP are have implications that extend beyond our study area, as they make few in number and, until recently, were rarely corrected for the effects clear that improvement of Earth models and the correct measurement of glacial isostatic adjustment (GIA, Raymo et al., 2011) or dynamic and interpretation of relative sea level markers in the field is paramount topography (DT, Rowley et al., 2013). It is now recognized that such for any future study of sea level during the mid-Pliocene and, more corrections must be made before estimates of local sea level can be generally, throughout the Cenozoic. mapped into a rigorous estimate of globally averaged, or eustatic sea level (ESL) in the Pliocene. Recently, Rovere et al. (2014) argued that 2. Literature maps, geomorphometric maps and remote regions characterized by broad coastal plain terraces bounded by abrupt sensing datasets scarps with mid-Pliocene shallow marine facies at their base can provide a direct indication of the position of MPWP shorelines. Further- Historically, the mid-Pliocene shoreline on the ACP is referred to as more, the elevation of the scarp base, measured over large distances and the Orangeburg Scarp in Georgia, South Carolina and North Carolina corrected for GIA, can then be used to test existing model predictions of and the Thornburg or Chippenham Scarp in Virginia, following the DT. name of the cities or counties where the scarp was most often identified Along the US Atlantic Coastal Plain (hereafter ACP), the mid-Pliocene (Fig. 1). In this study, we refer to this feature as either a ‘scarp’ or a shoreline has been preserved as an almost-continuous feature over ‘shoreline’. Temporally correlative with the scarp are shelly deposits of ~900 km from Georgia to Virginia (Doering, 1960; Dowsett and mid-Pliocene age represented by the Raysor, Duplin and Yorktown for- Cronin, 1990; Ator et al., 2005; Barnhardt, 2009; Adams et al., 2010), mations (Fig. 1); these units consist of marine facies of the mid-Pliocene and has the highest elevation amongst a sequence of Plio-Pleistocene inner continental shelf (Richards, 1950, 1969; Huddlestun, 1988; shorelines. This feature has been traditionally called a scarp (as in the Dowsett and Cronin, 1990, see Section 3.2 for the description of sites Orangeburg Scarp) despite the fact that this term, in physical geogra- on the ACP with marine mid-Pliocene deposits). The shoreline is well phy, is defined as an almost vertical slope and is often regarded as syn- defined and has been described by several authors in the Carolinas, onymous with ‘cliff’. In fact, the geomorphic expression of this Southern Virginia and Northern Georgia; in Northern Virginia it cannot paleoshoreline is a subtle change in slope, from the almost flat coastal be clearly distinguished from the Fall Line. For this reason we focus in plain to a rise with a slope of 5–15° (Fig. 1). At the scale of the entire this paper on the area between latitude 32° N (Northern Goergia) and ACP, the elevation of the base of the mid-Pliocene scarp has historically 38° N (Southern Virginia), where the scarp is best defined and has been measured using topographic maps (e.g., Winker and Howard, been studied by several authors (Fig. 1). In southern Georgia and Florida, 1977a,b). Only recently has it been possible to use digital elevation the morphology of the paleoshoreline changes from a scarp to a series models (Doar, 2012; Rovere et al., 2014) that allow the determination of barriers, or ridges, which have been recognized as markers of former of the paleoshoreline elevation with greater accuracy. Few authors Pliocene and Pleistocene sea levels (Winker and Howard, 1977a; have identified the mid-Pliocene shoreline in the field, and most of Markewich et al., 2013). In central-southern Florida, the Cypresshead these have focused on sites in Orangeburg County (South Carolina) Formation contains units with upper shoreface sediments that have (e.g., Colquhoun, 1986; Dowsett and Cronin, 1990; Doar, 2012). Most been dated to mid-Pliocene age with biostratigraphy and correlated recently, Rovere et al. (2014) mapped the scarp at several sites in with the Raysor Formation to the north (Fountain, 2009). Georgia, South Carolina and North Carolina using high-accuracy GPS Seaward of the mid-Pliocene scarp there are several other strand- and digital elevation models (DEMs). lines,alsoreferredtoas‘scarps’ in literature, which are mostly correlat- In this paper, we integrate the dataset presented in Rovere et al. ed with Pleistocene sea level variations. Although the study and (2014) into a collection of published data that describe the position description of such scarps is not the main aim of this paper, in Fig. 1 and elevation of the mid-Pliocene shoreline on the ACP. We then we represent the ones that have been mapped on the entire coastal A. Rovere et al. / Earth-Science Reviews 145 (2015) 117–131 119

Fig. 1. Map of the ACP with mid-Pliocene shorelines digitized from maps published in scientific journals or technical reports (colored lines, “literature maps” in the text) and earlier shorelines (dashed lines, extracted from Doering, 1960; Ator et al., 2005; Dicken et al., 2007a,b; Barnhardt, 2009; Doar, 2012). The numbers 1–8 indicate outcrops of marine mid-Pliocene sites identified from the literature (Huddlestun, 1988; Dowsett and Cronin, 1990)orsurveyedinthisstudy(seealsoFig. 4 for details), and blue dots represent points identified in the paleo- biology database (http://paleodb.org). Letters a–e refer to Pliocene formations reported in Dicken et al. (2007a,b) (http://pubs.usgs.gov/of/2005/1323/ and http://pubs.usgs.gov/of/2005/ 1325/). Gray areas mark the units older than mid-Pliocene identified by Dicken et al. (2007a,b) immediately west of the scarp. The vector data used to create this figure are available as supplementary material. plain (Doering, 1960; Ator et al., 2005; Dicken et al., 2007a,b; Barnhardt, 1977a; McCartan et al., 1984; Mixon et al., 2000; Willoughby, 2003; 2009; Doar, 2012). Other studies on Pleistocene shorelines in the ACP Ator et al., 2005; Dicken et al., 2007a; Barnhardt, 2009; Meitzen et al., date back to al least 1930 (Cooke, 1930; Cooke et al., 1943; Colquhoun 2009; Doar, 2010a,b; Nystrom, 2010; Doar, 2012). In this paper, we et al., 1968; Cooke, 1971; Ward et al., 1971a,b 1973; Cronin, 1980; refer to the above studies as ‘literature maps’. The literature maps Cronin et al., 1981; Colman and Mixon, 1988; Hollin and Hearty, 1990; range in scale from 1:24,000 to 1:800,000. We began by georeferencing Krantz, 1991; Toscano and York, 1992; Pazzaglia, 1993; Kaufman et al., each literature map (i.e. digitizing it in latitude/longitude space), and 1996; Muhs et al., 2003; Willis, 2006; Wehmiller, 2013). For an exten- then vectorized the mapped line representing the scarp using GIS. Dur- sive and comprehensive review of the Pleistocene shorelines in the ing the vectorization process, one can specify whether a mapped feature ACP, the reader is directed to the recent work of Doar and Kendall has an associated elevation as well as the source of that value. We chose (2014). the 1/3 arcsecond DEMs from the US National Elevation Dataset as the Several maps of the mid-Pliocene shoreline on the ACP have been source for elevation data (Gesch et al., 2002; Gesch, 2007). The NED published in the last four decades, both in scientific journals and in dataset in the East Coast is derived mostly from light detection and reports from USGS or State Geological Surveys (Winker and Howard, ranging (LIDAR) data in North and South Carolina and from complex 120 A. Rovere et al. / Earth-Science Reviews 145 (2015) 117–131 linear interpolation of contours (including hydrography) using complex discuss our results in terms of mid-Pliocene sea levels and post- linear interpolation in the remaining areas (Evans, 2014). We generated depositional movements that warped the shoreline across its length. a series of lines (colored lines in Fig. 1, see supplementary materials for the vector dataset) representing the mid-Pliocene shoreline in the ACP 3. Field measurements and data from DEMs according to different sources. Each line is associated with an elevation value extracted from the DEMs (with a nominal error of ±1.55 m, see 3.1. Elevation of the mid-Pliocene shoreline Table 1 and Section 3.1 for details on DEM accuracy). The data from literature maps match, at the scale of the entire ACP, In 2013 we carried out two field campaigns to map the scarp and the results of morphometric analyses based on DEMs (Fig. 2a–d). measure its position and elevation with the highest possible accuracy. Geomorphometry is the quantitative study of topography (Pike, 2000) For this purpose, we used two different GPS systems: the first system and uses mathematical, statistical and image processing techniques to consisted of a Trimble ProXRT receiver, a Zephyr antenna, Terrasync bin different aspects of a land surface into geomorphic categories. In software centimeter edition, and a GeoXh data collector; the second sys- Fig. 2a, b we compare the mid-Pliocene shoreline derived from litera- tem consisted of a Trimble R7 receiver with integrated antenna, Survey ture maps to the map of USGS land surface forms (http://rmgsc.cr. controller software, and a TSC data collector. The GPS antenna was usgs.gov/ecosystems/docs/us_landsurfaceforms_30m_dd83.htm) that mounted on a car and the software was set to collect one data point was obtained with traditional geomorphometric methods (i.e., the per second while driving. We concentrated on routes as orthogonal as Cress et al., 2009 modification of the landform classification of possible to the modern shoreline as well as less developed roadways Hammond, 1954). In Fig. 2c, d we compare the scarp with a map that more typically conform to the natural landscape. Moreover, obtained using a more recent geomorphometric method, called we cruised at a low speed, as constant as possible, in order to collect ‘geomorphons’ (Jasiewicz and Stepinski, 2013), that classifies landforms the maximum number of data points per kilometer driven and using the principle of pattern recognition. In both cases, the mid- to avoid post-processing problems in the GPS data due to sudden accel- Plioceneshorelinedepictedinliteraturemapsmarkstheedge(orborder) erations of the antenna. Where the mid-Pliocene shoreline was identi- of a large area characterized by geomorphometric maps as ‘flat’.Inthe fied in the field, geographic coordinates and point IDs were noted. In area of Orangeburg, the type location for the mid-Pliocene scarp, both North Carolina, a connection to a Real Time Kinematics service was geomorphometric maps identify the scarp near the location where available and, thus, highly accurate data were available in real time. In WinkerandHoward(1977a)located it. Virginia, Georgia and South Carolina, positioning data and associated Some aspects of the scarp can also be identified using satellite data. errors were determined through post-processing of the GPS data For example, using synthetic aperture radar (SAR) data from the ALOS using either Trimble Pathfinder Office (pro XRT receiver data) or PALSAR's L-band sensor, one can distinguish a lithological and pedogen- Trimble Business Center (R7 receiver data) software combined with ic contrast near the mid-Pliocene shoreline (Fig. 2e, f). Under HV polar- the closest Continuously Operating Reference Stations (CORS, http:// ization (which better captures lithological contrasts; Won and Ryu, geodesy.noaa.gov/CORS/). We discarded data points with a post- 2002; Williams and Greeley, 2004), the sandier substrate typical of the processed accuracy N±1 m (this constituted 39% of the total data set, Pliocene marine terrace has lower signal amplitude and is represented primarily collected from areas of bad satellite reception, for example by darker pixels than most lithologic substrates. By contrast, the more when the GPS signal was compromised by buildings or trees); we ob- highly weathered and clayey forested areas appear bright in the SAR tained sub-meter accuracy (b±1 m) for ~61% of our original dataset of image. East of the scarp, the mid-Pliocene sediments are sandy, which 86,063 points (Table 1). All our elevation data have been referred to leads to sandy, well-drained soils (Markewich et al., 1990) that show the North American Vertical Datum of 1988, the same reference system more consistently black in the SAR dataset. West of the scarp, the sub- used in DEMs of the US National Elevation dataset. strate and soils are probably more variable, more clay-rich and have As shown by radar datasets (Fig. 2c, d), the mid-Pliocene shoreline therefore lighter colors in the SAR. The Cretaceous-age material and/or can be identified as a subtle topographic change (Fig. 3a–f, i, j) and as saprolites that lie west of the scarp developed in the crystalline rocks a transition between different sedimentologic and pedogenic features of the Piedmont. In general, the SAR images reveal that the mid- (Fig. 3g, h, j). In most cases, the mid-Pliocene shoreline abuts directly Pliocene shoreline marks a lithological contrast between sandier sub- against Miocene or older features, marking a 2–15 Mya hiatus in depo- strates east of the scarp and clayey, forested sediments west of it. sition (the location of Miocene and older units is identified from state In summary, literature maps, geomorphometric classifications and geological maps in Fig. 1). Assuming that the Pliocene shoreline effec- satellite data all show that the mid-Pliocene shoreline on the ACP is a tively erased the earlier terrestrial drainage patterns and topography, prominent, almost continuous from Georgia to Virginia. Doar (2012) stream drainage development would have initiated at the onset of re- highlighted that the Orangeburg Scarp is a feature whose existence is gression from the Pliocene highstand and continued for the past 3 Ma. certain, since it can be recognized from morphometric analyses and sat- Thus, flat areas are far more extensive seaward of the Orangeburg ellite data, but whose precise ground location is uncertain. In the follow- Scarp than landward of the scarp. Landward (west) of the scarp, more ing section, we present the results of our field expeditions aimed at hills and stream valleys characterize the landscape. In contrast, surface evaluating the uncertainty in the scarp location and elevation, and we sediments seaward of the mid-Pliocene shoreline are sandier and contrast with the deep-red clay-rich sediments to the west and landward side of the scarp (e.g., Fig. 3g, h). The field evidence provides observational calibration of the results obtained by ALOS-SAR datasets de- Table 1 scribed in the previous section and represented in Fig. 2c. Accuracy of the GPS data acquired on the ACP and the fi fi Root Mean Square Error (RMSE) between GPS and In the eld, we identi ed and measured the mid-Pliocene shoreline DEM data. RMSE between GPS and 1/3 arcseconds DEM at 21 locations labeled with letters in Table 2 (additional information calculated on data with an accuracy b0.5 m: 1.55 m. and field pictures are available as supplementary material). To supple- Accuracy (m) % of points ment this dataset and expand the areal coverage of our mapping of the mid-Pliocene paleoshoreline, we also extracted topographic tran- 0.5 23.1 1 38.0 sects from 1/3 arcsecond DEMs (USGS, National Elevation Dataset). 1.5 17.9 The vertical accuracy of DEM data is taken to be ±1.55 m, a number es- 2 9.9 timated by comparing our most accurate GPS data (precision b0.5 m) 2.5 5.6 with DEM values at the same point (Table 1). Our accuracy estimate is 3 5.6 the same estimate as for the US-wide National Elevation Dataset A. Rovere et al. / Earth-Science Reviews 145 (2015) 117–131 121

Fig. 2. (a) USGS surface forms obtained from 1-arcsecond digital elevation models; (b) geomorphometric map representing geomorphons in the ACP (Jasiewicz and Stepinski, 2013); (c) ALOS PALSAR data. Sandy substrates appear darker than muddy, forested substrates. Note the strong amplitude difference in the SAR data across the central portion of the scarp corresponding to the well-preserved siliclastic contrasts. Black lines in a, b and c represent the position of the scarp as inferred by Winker and Howard (1977a). Red dots represent the points reported in Table 2. The maps on the right portion of each ﬁgure are a zoomed-in version in the direct vicinity of the mid-Pliocene scarp, Orangeburg, SC, indicated as black boxes in the maps to the left.

accuracy (Gesch et al., 2014) and is consistent with the vertical accuracy 3.2. The inner continental shelf in mid-Pliocene estimate of ±1.53 m cited by Rovere et al., 2014. Using these topographic transects on DEMs, we identiﬁed the mid-Pliocene shoreline The sea occupied the ACP during the mid-Pliocene period over the at an additional 31 sites, labeled with numbers in Table 2. course of numerous orbitally-paced sea-level cycles. Many low and 122 A. Rovere et al. / Earth-Science Reviews 145 (2015) 117–131

ab c

d ef

Fig. 3. The mid-Pliocene scarp at different locations along the ACP: (a) Thornburg, VA; (b) Richmond, VA; (c) Smithfield, NC; (d) Raeford North, NC; (e) Allendale North, SC; (f) Brooklet North, GA; g and h highlight the transition in soil color and composition at the location of the scarp near Orangeburg, SC. g is taken looking ‘offshore’ (east), while h is taken in the ‘onshore’ direction from the scarp, which is represented by the dashed black line; (i) Orangeburg South, SC; (j) schematic cross section of the scarp measured on GPS (gray band, transect OB_S) and DEM (black band, transect 20) transects. The underlying formations have been extracted from Dicken et al. (2007a,b) and adapted to the position of the scarp. Formation descriptions from USGS (http://mrdata.usgs.gov) are as follows. Duplin Formation: ‘Secondary unit description from USGS Lexicon (ref. SC003): sands, sandy and silty clays, and very shelly sands, which frequently overlie a phosphatic basal conglomerate.’ Huber/Lisbon/Barnwell Formations, undivided: ‘Poorly to well sorted sand, clay and carbonates deposited in delta-dominated fluvial- and open-marine environments. Unit is characterized by commercial kaolin bodies in older strata from westernmost South Carolina to central Georgia. Younger strata are cyclic marine deposits with deeper water facies exposed in western Georgia. Carbonate facies are locally mined in western Georgia for agricultural lime. Neogene strata (undifferentiated): Poorly sorted clayey sand and gravel deposited in a fluvial environment in South Carolina but becoming more fluvio-marine in Georgia. Unit is characterized by in situ weathered feldspar and an abundance of quartzite gravel and cobbles.’ All images except c and h are taken looking eastward (i.e. offshore). Additional field photos are available in the supplementary material. mid-stand facies and sediments have been preserved on the ACP, and Yorktown and equivalent formations (Fig. 1, letters a–e), and can all today these units outcrop in river bluffs or in artificial cuts in the terrain be dated to the mid-Pliocene. These formations represent the most created by mining and road-building activities (see blue dots and num- landward of the Plio-Pleistocene marine sequences that mantle the bered sites in Fig. 1). These outcrops belong to the Raysor, Duplin, ACP. No mid-Pliocene marine facies have been found west of the scarp A. Rovere et al. / Earth-Science Reviews 145 (2015) 117–131 123

Table 2 Locations where the mid-Pliocene shoreline has been identified (see supplementary material for further details). Numbers in the first column indicate DEM profiles. Additional information are available in the supplementary material.

Name Marker elevation Marker elevation Paleo RSL estimate LON LAT Source and elevation and uncertainty and error derived from accuracy including colluvium Eqs. (1) and (2)

TH — Thornburg, VA 76.54 ± 0.8 74.54 ± 1.8 79.54 ± 2.7 −77.5263 38.1341 This paper 1 76.48 ± 1.55 74.48 ± 2.55 79.48 ± 3.25 −77.5330 38.0724 This paper RG — Ruther Glen, VA 77.90 ± 1 75.9 ± 2 80.9 ± 2.83 −77.5462 38.0157 This paper AS — Ashland, VA 68.4 ± 1.3 66.4 ± 2.3 71.4 ± 3.05 −77.5034 37.7110 This paper 2 67.11 ± 1.55 65.11 ± 2.55 70.11 ± 3.25 −77.5121 37.6189 This paper RM — Richmond, VA 64.81 ± 0.5 62.81 ± 1.5 67.81 ± 2.5 −77.5109 37.5039 This paper 3 66.33 ± 1.55 64.33 ± 2.55 69.33 ± 3.25 −77.5290 37.4748 This paper CH — Chesterﬁeld, VA 66.77 ± 0.3 64.47 ± 1.3 69.47 ± 2.39 −77.5497 37.4073 This paper 4 61.46 ± 1.55 59.46 ± 2.55 64.46 ± 3.25 −77.5689 37.0054 This paper PG — Piney Grove, NC 59.28 ± 0.6 57.28 ± 1.61 62.28 ± 2.57 −77.7235 36.3839 This paper LT — Littleton, NC 61.12 ± 0.63 59.12 ± 1.63 64.12 ± 2.58 −77.7372 36.3609 This paper 5 55.29 ± 1.55 53.29 ± 2.55 58.29 ± 3.25 −78.0376 35.8503 This paper SM — Smithﬁeld, NC 59.02 ± 0.5 57.02 ± 1.5 62.02 ± 2.5 −78.3640 35.5781 This paper 6 73.37 ± 1.55 71.37 ± 2.55 76.37 ± 3.25 −78.5485 35.3780 This paper 7 73.46 ± 1.55 71.46 ± 2.55 76.46 ± 3.25 −78.9461 35.1311 This paper 8 82.06 ± 1.55 80.06 ± 2.55 85.06 ± 3.25 −79.0278 35.0799 This paper 9 78.96 ± 1.55 76.96 ± 2.55 81.96 ± 3.25 −79.2336 34.9795 Rovere et al. (2014), EPSL (17) RF_S — Raeford South NC 79.85 ± 1.18 77.85 ± 2.18 82.85 ± 2.96 −79.3423 34.9500 This paper RF_N — Raeford North, NC 79.80 ± 1.18 77.8 ± 2.18 82.8 ± 2.96 −79.3202 34.9481 Rovere et al. (2014), EPSL (RF) 10 79.27 ± 1.55 77.27 ± 2.55 82.27 ± 3.25 −79.4048 34.9062 This paper 11 79.2 ± 1.55 77.2 ± 2.55 82.2 ± 3.25 −79.4878 34.8460 Rovere et al. (2014), EPSL (16) 12 75.9 ± 1.55 73.9 ± 2.55 78.9 ± 3.25 −79.6193 34.7647 Rovere et al. (2014), EPSL (15) 13 75.6 ± 1.55 73.6 ± 2.55 78.6 ± 3.25 −80.0095 34.4715 Rovere et al. (2014), EPSL (14) 14 70.16 ± 1.55 68.16 ± 2.55 73.16 ± 3.25 −80.1622 34.3350 Rovere et al. (2014), EPSL (13) 15 70.16 ± 1.55 68.16 ± 2.55 73.16 ± 3.25 −80.3751 34.0912 This paper 16 73.06 ± 1.55 71.06 ± 2.55 76.06 ± 3.25 −80.4103 34.0578 Rovere et al. (2014), EPSL (12) 17 69.89 ± 1.55 67.89 ± 2.55 72.89 ± 3.25 −80.4970 33.9291 Rovere et al. (2014), EPSL (11) SA — Saint Matthews, SC 71.74 ± 0.1 69.73 ± 1.1 74.73 ± 2.29 −80.6553 33.6988 This paper CA — Cameron, SC 63.29 ± 0.64 61.3 ± 1.64 66.3 ± 2.59 −80.6780 33.6222 This paper 18 64.14 ± 1.55 62.14 ± 2.55 67.14 ± 3.25 −80.7321 33.6017 This paper 19 67.4 ± 1.55 65.4 ± 2.55 70.4 ± 3.25 −80.7900 33.5404 Rovere et al. (2014), EPSL (10) OB_N — Orangeburg North, SC 66.12 ± 1.52 64.17 ± 2.52 69.17 ± 3.22 −80.8042 33.5344 This paper 20 66.52 ± 1.55 64.52 ± 2.55 69.52 ± 3.25 −80.8164 33.5162 This paper OB_S — Orangeburg South, SC 68.23 ± 0.38 66.23 ± 1.38 71.23 ± 2.43 −80.8450 33.5025 Rovere et al. (2014), EPSL (OB) 21 63.73 ± 1.55 61.73 ± 2.55 66.73 ± 3.25 −80.9336 33.4122 Rovere et al. (2014), EPSL (9) 22 57.6 ± 1.55 55.6 ± 2.55 60.6 ± 3.25 −80.9826 33.3859 This paper BG — Bamberg, SC 51.75 ± 1.9 49.75 ± 2.91 54.75 ± 3.53 −81.0547 33.3022 This paper 23 53.69 ± 1.55 51.69 ± 2.55 56.69 ± 3.25 −81.1413 33.1907 This paper AL_N — Allendale North, SC 61.12 ± 0.38 59.11 ± 1.38 64.11 ± 2.43 −81.2951 33.0407 Rovere et al. (2014), EPSL (AL) AL_S — Allendale South, SC 61.9 ± 0.18 59.9 ± 1.18 64.9 ± 2.33 −81.3190 33.0181 This paper 24 43 ± 1.55 41 ± 2.55 46 ± 3.25 −81.5055 32.6275 Rovere et al. (2014), EPSL (8) SV — Sylvania, GA 42.02 ± 0.1 39.45 ± 2.22 44.45 ± 2.99 −81.5217 32.6116 This paper 25 45.78 ± 1.55 43.78 ± 2.55 48.78 ± 3.25 −81.5623 32.5637 Rovere et al. (2014), EPSL (7) 26 43.41 ± 1.55 41.41 ± 2.55 46.41 ± 3.25 −81.6242 32.4479 Rovere et al. (2014), EPSL (6) 27 42.18 ± 1.55 40.18 ± 2.55 45.18 ± 3.25 −81.6504 32.3808 Rovere et al. (2014), EPSL (5) BR_N — Brooklet North, GA 42.82 ± 0.44 40.82 ± 1.44 45.82 ± 2.47 −81.6684 32.3615 Rovere et al. (2014), EPSL (BR) BR_S — Brooklet South, GA 43.88 ± 2.54 41.88 ± 3.54 46.88 ± 4.07 −81.6892 32.3326 This paper 28 34.8 ± 1.55 32.8 ± 2.55 37.8 ± 3.25 −81.7919 32.0945 Rovere et al. (2014), EPSL (4) 29 34.8 ± 1.55 32.8 ± 2.55 37.8 ± 3.25 −81.7997 32.0700 Rovere et al. (2014), EPSL (3) 30 33.74 ± 1.55 31.74 ± 2.55 36.74 ± 3.25 −81.8180 32.0086 Rovere et al. (2014), EPSL (2) 31 36.36 ± 1.55 34.36 ± 2.55 39.36 ± 3.25 −81.8380 31.9415 Rovere et al. (2014), EPSL (1) GV — Glenville, GA 36 ± 1.32 34 ± 2.32 39 ± 3.07 −81.8367 31.9331 This paper

conﬁrming that the scarp marks the maximum sea-level ingression in mollusks, including both bivalves (such as oysters and pectens) and gas- the last 3.5 Ma. Based on foraminifera, calcareous nanofossils and tropods, but also corals such as Septastrea marylandica (Fig. 4b, c). In marine ostracod species composition at sites 1–4(Fig. 1), Dowsett and Virginia, we sampled the Yorktown Formation at Skippers Quarry Cronin (1990) inferred that the Duplin and equivalent formations (Fig. 4d), where mining activities have exposed a marine section lying such as the Raysor (sites 5–7ofFig. 1) were deposited in an ocean directly on granitic bedrock at the SW margin of the quarry. The ~7–9 °C warmer in this region than today. Yorktown Formation extends in elevation from 28.9 m to 35.3 m, and One of the type localities of the mid-Pliocene Duplin Formation on is covered by ﬂuvial deposits to an elevation of 38.3 m. At this site, the the ACP is at the Lumber River, south of Lumberton, NC (site 4 in faunal assemblage is dominated by in situ (articulated, Fig. 4e) Fig. 1), a site that correlates in faunal content with a nearby outcrop at Mercenaria sp. in the lower section and by Pecten sp. and Ostrea sp. Robeson Farm (site 3 in Fig. 1). Strontium isotopic ratios yield ages of assemblages in the upper section (Fig. 4f). 2.88–3.57 Ma for site 3 (McGregor et al., 2011), and 2.3–2.8 Ma for Despite their biostratigraphic correlation, only one (Robeson Farm) site 4 (Graybill et al., 2009). At Lumber River, the Duplin Formation is of the two absolute ages of the Duplin-Yorktown Formation can be exposed along a cut bank in the river. The entire exposure extends directly correlated to the mid-Pliocene (3.3 to 2.9 Ma), as the other approximately 1.7 m above the water level (water level was measured dates to a younger age. Strontium isotopic dating is based on the fact at an elevation of 28 ± 1.14 m, Fig. 4a) and the outcrop contains mostly that 87Sr/86Sr in ocean water has varied continually through time 124 A. Rovere et al. / Earth-Science Reviews 145 (2015) 117–131

a b c

1m 10 cm

d e f

Fig. 4. Mid-Pliocene marine sites near the US East Coast. (a) A cut bank in the Lumber River, where the Duplin Formation is exposed up to ~1.7 m above the river water level (for geographic location see site number 4 in Fig. 1); (b) coral Septastrea marylandica at the same site (identified by comparison with a specimen held at the Florida Museum of Natural History, Florida); (c) in situ articulated Ostrea collected at the Lumber River site; (d) the Yorktown formation at Skippers Quarry, VA (for geographic location see site number 8 in Fig. 1). The dashed line indicates the top part of the Yorktown (mid-Pliocene) formation, overlain by fluvial deposits. The formation here lies on granitic bedrock, which is at the base of the section, near the road; (e) in situ articulated Mercenaria sp. in the lower part of the mid-Pliocene section at Skippers Quarry; (f) pectinid in the higher part of the mid-Pliocene section at Skippers Quarry. reflecting changes in the balance between the processes that supply and individual organisms. This would help to evaluate the effect of second- remove strontium to and from the oceans. Biogenic carbonate secreted ary diagenesis and recrystallization on trace element abundances and by marine organisms incorporates strontium dissolved in seawater Sr isotope ratios. Sandstrom et al. (2014) demonstrated that reliable without measurable isotopic fractionation and thereby preserves a re- ages can be achieved when using these methods with the Sr isotope cord of marine strontium isotope evolution. Calibration of this record seawater curve. using independent stratigraphic data has provided a powerful chrono- logical framework against which the marine record can be compared 3.3. Observed shorelines and paleo relative sea levels (Farrell et al., 1995; McArthur et al., 2001). The accuracy of this method varies depending on different factors, amongst which are as follows: (1) In Rovere et al. (2014) we interpreted the base of mid-Pliocene scarp preservation of the original 87Sr/86Sr in the marine carbonate signal; (2) in the US Atlantic Coastal Plain, South Africa and South Australia as Analytic precision of 87Sr/86Sr measurements; (3) accuracy of the model being representative of intertidal to shallow subtidal environments. In used to assign a numeric age calibration to the isotope curve (e.g. the this study, we review our interpretation for the US Atlantic Coastal LOWESS regression method of McArthur et al. (2001)); (4) uncertainty Plain. We place paleo-sea level in proximity of the toe of the scarp, as envelope (95% confidence interval); and 5) slope of the age calibration identified on either GPS or DEM profiles (images for all the topographic curve against numeric age (Howarth and McArthur, 1997). Even with profiles and their location are attached in the supplementary KMZ file). a pristine carbonate sample and measurement precision better than In sea-level studies, the aim of field investigations is to obtain the rela- ±10 ppm (2σ) for Sr, the relatively shallow slope of the Pliocene inter- tive sea level (RSL) at a specific location, which is the elevation of the val of the reference Sr curve between 4.0 and 2.5 Ma reflects a large ancient sea level relative to present sea level. To obtain this, we have error that subdivision of the MPWP into individual interglacial events to correct the ancient sea-level marker for its position relative to the (e.g., MIS G17, K1 and KM3) is not possible. reference water level: Better absolute dating methods for marine mid-Pliocene units are important to support better understanding of the mid-Pliocene warm ½¼RSL ½Marker elevation −½ðReference water level 1Þ period. One improvement would be, as suggested by Sandstrom et al. (2014), to examine different species from different environments by both expressed relative to the same datum (e.g. mean tidal level) combining optical images, scanning electron microscope (SEM), qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi cathodoluminescence and X-ray diffraction (XRD) with elemental and ÂÃ RSL Error ¼ ðÞElevation accuracy 2 þ ðÞIndicative range 2 ð2Þ Sr isotope analyses of micro-drilled calcite and aragonite layers within A. Rovere et al. / Earth-Science Reviews 145 (2015) 117–131 125

The terms used in these two equations are defined as follows: of this calculation includes both the error in the location of the scarp as given by the original authors as well as an error related to the Marker elevation and elevation accuracy. The marker elevation is the georeferencing process. elevation of a sea level marker measured in the field today, in our In Fig. 5b we show the frequency distribution of the values case the base of the mid-Pliocene ‘scarp’ measured with either GPS representing the horizontal distance between our points in Table 2 or on DEMs. A critical point is the recognition that the base of the and the nearest scarp in literature maps. Overall, the average distance scarp is rarely exposed and it may be mantled by colluvial deposits. between points in literature maps and the real position of the scarp is The absence of both intertidal facies immediately near the scarp 1.9 km. The analysis of the angle created by the line connecting our (which are present in the other two scarps described in Rovere point and the nearest point in a literature map (rose diagram, inset in Fig. 5b) shows that most maps tend to place the scarp landward with et al. (2014)) and subsurface data (such as, for example, ground pen- respect to its real position. This might be due to the better accuracy in etrating radar data, see O'Neal and Dunn (2003) for an application to the identification of the scarp in the field rather than on maps, where fi Pleistocene shorelines) make it dif cult to understand how thick the seaward flat areas are usually easier to identify. – colluvial deposits are. An acceptable estimate is that they are 1 3m Analyzing the difference in elevation between our shoreline points thick; therefore all measured elevations are systematically high by, and the elevations extracted from literature maps shows that, on aver- on average, 2 m. For this reason, in order to take into account age, the less accurate literature maps overestimate the real elevation colluviation, we subtracted 2 m from all our elevation measure- of the scarp by 5.4 m (Fig. 5c). This is in agreement with the fact that ments. Elevation accuracy is defined as the accuracy of the measure- the scarp has generally been placed landward in literature maps relative ment, in our case the vertical error of our GPS or DEM data. In order to our measurements and therefore at higher elevations. This pattern to take the uncertainty of coverage by colluvium deposits into changes slightly when only the most detailed maps are analyzed (Fig. 5d). In this case, the maps tend to place the scarp only slightly account, we added an additional error of 1 m to our GPS or DEM lower than its real elevation. accuracy. In addition, we find that discrepancies between literature maps and Reference water level and Indicative range. These terms are the actual location of the scarp are not equally distributed along the ACP. borrowed from Holocene studies (see Engelhart and Horton, 2012, In Fig. 6 we show the elevation of mid-Pliocene shorelines on the ACP as and references therein) and in our case, we define reference water a function of latitude; it is evident that the shoreline mapped by Winker level as the relationship between the marker and the former sea and Howard (1977a) deviates from our field data and from other shore- level: i.e., where was sea level in relation to the scarp feature at the lines around 33.5°N. We note, in this regard, that Winker and Howard time it formed? The indicative range is the uncertainty associated (1977a) characterized their elevation profile north of this latitude as ‘ ’ fi to the reference water level, or, in other words, the elevation range highly uncertain (Fig. 6). The literature maps also deviate signi cantly from our data between 36.5°N and 37.5°N. occupied by a sea-level indicator (e.g. van de Plassche, 1986; It is evident from Fig. 6 that our field data give a much more detailed Shennan and Horton, 2002; Engelhart and Horton, 2012). picture of elevation variations over the entire length of the Pliocene ACP Obtaining reference water level and indicative range often requires scarp. For instance, the scarp varies between 33.74 ± 1.55 m in northern that a modern analog of the paleo landform is identified and measured. Georgia (site 30, ~32°N) and 82.06 ± 1.55 m in northern North Carolina This involves the assumption that wave characteristics, tidal ranges and (site 8, ~35 N). Moving northward, the elevation of the mid-Pliocene living distributions of marine organisms were not significantly different shoreline decreases by about 30 m from 35° to 36.5°N and then from modern conditions. Studies of modern beach profile variations at increases beyond this location, reaching an elevation of ~78 m in different places along the ACP show that the major break in slope Thornburg, Virginia (Fig. 6 and Table 2). At the time of its formation, along beaches in the ACP occurs at 3–7 m depth (Hallermeier, 1981; the scarp profile from Georgia to Virginia was horizontal (i.e., at sea Larson and Kraus, 1994; Lee et al., 1998), and corresponds to the maxi- level) and coincident with the paleo shoreline. As plotted in Fig. 6,our mum water depth for near shore erosion by extreme wave conditions data show that since its formation the mid-Pliocene shoreline has (Hallermeier, 1981). We therefore choose a reference water level of been warped by tens of meters of differential (post-depositional) verti- −5 m and an indicative range of 4 m. We emphasize that this value cal movement across the ACP over the last 3 Ma. In the next section, we may be improved by surveying modern analogs along the ACP. discuss two physical processes that contribute to this deformation — In Table 2, we present both the measured elevation of the marker GIA and DT — and review the results of geophysical modeling of these (i.e. the scarp) for each point in our database and its associated RSL processes. elevation as well as the estimated accuracy calculated using, respectively, Eqs. (1) and (2). We also provide a marker elevation and uncertainty 5. Warping of the mid-Pliocene shoreline that takes into account the possibility that colluvium mantles the scarp. We note that when comparing our dataset with literature maps one The ACP is located on the peripheral bulge of the former Laurentide should use the sea-level marker elevation as observed in the field; ice sheet complex and is therefore experiencing ongoing crustal subsi- when comparing the data with GIA or Earth models, the value used dence or, equivalently, relative sea level rise due to glacial isostatic ad- should be the RSL elevation as calculated in Eq. (1). justment. Raymo et al. (2011) demonstrated that the contribution to the present-day elevation of mid-Pliocene sea-level markers from GIA 4. Comparison between literature maps and field data may be divided into two parts: (1) a signal associated with the residual response to ice loading during the most recent Pleistocene glacial cy- What is the accuracy of published mid-Pliocene shoreline estimates cles; and (2) a quasi-uniform drop in sea level associated with an in- on the ACP with respect to our newly measured elevation and corre- crease in global ice volume at the end of the MPWP. The latter is very sponding field data? To answer this question, we compare the lines ex- close to the signal at distance from the ice sheet growth (i.e., in the tracted from literature maps with the location and elevation of the scarp far-field) and only departs from eustasy due to lithospheric flexure in measured at the 52 locations reported in Table 2. To do this, we use the response to ocean unloading at the shelf (Raymo et al., 2011). We will ArcGis® ‘Near 3d’ tool that calculates the linear distance and elevation focus here on the GIA signal due to the first effect, deformation of the difference between a set of points (in our case, our locations) and the paleoshoreline elevation due to loading associated with the Pleistocene nearest node of the nearest line (the shorelines extracted from litera- ice age cycles. A global calculation of this signal, based on the ice model ture maps). The way this tool works is represented in Fig. 5a. The result history over the last 3 Myr constructed and adopted in Raymo et al. 126 A. Rovere et al. / Earth-Science Reviews 145 (2015) 117–131

Landward N NORTH 0.4 NW NE cy

n 0.3

+65m e u Nearest point W E

(elevation extracted from DEM) eq r f 0.2

Nearest ive Nearest distance SW SE angle 0.1 Relat b S Elevation of Mid-Pliocene 0 shoreline measured a +57m with GPS or DEM Seaward 012345678910 Linear distance between shoreline measured in the ﬁeld and nearest point in literature maps (km) at all scales

0.4 Maps at scales Maps at scales < 1:100,000 > 1:100,000 (less detailed) -5.4 (more detailed) 1.2 y -18 7.2 -6.7 9.1 0.3 quenc

re 0.2 ive f

lat 0.1 Re c d 0 -60 -50 -40 -30 -20 -10 0 10 20 30 40 50 60 -60 -50 -40 -30 -20 -10 0 10 20 30 40 50 60 Difference in elevation between shoreline measured in the ﬁeld and nearest point in literature maps (m)

Fig. 5. (a) Schematic representation of how the ‘Near’ GIS tool was used to compare the horizontal and vertical distances between our field data and the shoreline identified in literature maps. This frame shows a planar view of the shoreline. Orange represents the scarp identified in literature maps. The blue dot represents the shoreline measured in the field. (b) Histo- grams representing the linear nearest distance (see panel a) between the shoreline identified in literature maps and the nearest scarp measured in the field. The rose diagram inserted in this figure shows the direction of the nearest angle as exemplified in a. Directions in the upper semi-circle mean that the literature map placed the scarp landward of the real point (as in panel a), while directions in the lower part of the circle mean that the literature map placed the scarp seaward of the real point. (c) Elevation difference between the shoreline identified in the field and the nearest point in literature maps at scales lower than 1:100,000 (less detailed) with average and 2σ values indicated. (d) Same as c but for maps at scales larger than 1:100,000 (more detailed).

(2011), is shown in Fig. 7a. This calculation is based on a spherical sym- for contamination due to GIA. As the subsidence of the peripheral bulge metric, viscoelastic Earth model with lithospheric thickness of 96 km, continues, and sea level rises in this region, the GIA correction shown in and uniform upper and lower mantle viscosities of 5 × 1020 Pa s and Fig. 7a will trend toward zero (over thousands of years). If the Earth 5×1021 Pa s, respectively. model and ice history adopted in computing Fig. 7a are accurate, then Fig. 7a represents the predicted residual crustal elevation (or topog- the results indicate that the correction for GIA is relatively constant at raphy) due to the Pleistocene glacial cycles, and any mid-Pliocene ~15 m along the mid-Pliocene shoreline in the ACP, with the exception shoreline elevation has to be corrected for this signal in order to account of sites north of 36°N. The prediction is, however, sensitive to the

120

100

40 Elevation (meters)

0 31.5 32.0 32.5 33.0 33.5 34.0 34.5 35.0 35.5 36.0 36.5 37.0 37.5 38.0 Latitude (degrees)

Paleo RSL range derived from Eq.1 and 2 Dickens et al., 2007 Orangeburg Willoughby 2003 Orangeburg Ator et al., 2005 Chippenham Doar 2010a,b,2012 Orangeburg Ator et al., 2005 Thornburg Ator et al., 2005 Coats McCartan et al., 1984 Orangeburg Mixon et al., 2000 Thornburg Ator et al., 2005 Orangeburg Meitzen et al., 2009 Orangeburg Winker and Howard, 1977 Orangeburg Barnhardt, 2009 Orangeburg Nystrom 2010 Orangeburg Orangeburg scarp Dowsett & Cronin, 1990

Fig. 6. Latitude versus elevation plot of all the shorelines represented in Fig. 1. Colors are consistent with those of Fig. 1, each representing a different literature map. Each line has been identiﬁed using LOESS interpolation of the original topographic data, excluding extreme depressions representing river valleys (see supplementary materials for a similar graph showing the results of the interpolation compared to the real topography for each shoreline). Squares represent the elevation of the scarp measured in the ﬁeld, while black circles represent scarp elevation obtained from DEM transects. The blue band represents the Paleo RSL and associated error calculated from Eqs. (1) and (2), as shown in Table 2. A. Rovere et al. / Earth-Science Reviews 145 (2015) 117–131 127

a b 40

24 84 81 78 75 72 84 81 78 75 72

−20 −10 0 10 20 6 8 10 12 14 16

c d 40

24 84 81 78 75 72 84 81 78 75 72

−40 −20 0 20 40 0 10 20 30 40

Fig. 7. (a) GIA signal in the present-day elevation of a MPWP sea-level marker associated with incomplete adjustment in response to the late Pleistocene ice and ocean loading cycles. This prediction is based on the ICE-5G ice history (Peltier, 2004) and an Earth structure model characterized by a lithospheric thickness of 96 km, an upper mantle viscosity of 5 × 1020 Pa s and a lower mantle viscosity of 5 × 1021 Pa s. (b) Standard deviation of model predictions obtained using 36 different Earth structure models distinguished by varying the lithospheric thickness (71 km and 96 km), upper mantle viscosity (1 × 1020 Pa s, 3 × 1020 Pa s and 5 × 1020 Pa s) and lower mantle viscosity (6 different values ranging from 3 × 1021 Pasto30×1021 Pa s). (c) Change in DT since 3 Ma based on the mantle convection model TX2007V2 (Rowley et al., 2013). A slight difference in this map compared to Rowley et al. (2013) arises from using an Indo-Atlantic hotspot reference frame rather than a no-net rotation reference frame for the plate reconstruction. (d) Spread of four different DT predictions (TX2007V1, TX2007V2, TX2008V1, TX2008V2) around their mean (calculated as the standard deviation at each point). These simulations differ in the density and viscosity structure of the adopted Earth model. Note the difference in the range of the color scale (left frames) and gray scale (right frames). In all frames, all the predictions are in meters, and the thick black line indicates the location of the mid-Pliocene shoreline and has been obtained connecting the points shown in Table 2. adopted mantle viscosity field, which is uncertain. In this regard, we uncertainty that is also relatively constant along the profile. Therefore, calculated predictions based on 36 different mantle viscosity profiles we may conservatively conclude the GIA correction along the part of to explore the magnitude of this uncertainty and for each of those the ACP has an absolute uncertainty of ± 11 m. models we have computed the GIA correction at all sites along the It is clear from Fig. 7a and b that GIA alone cannot explain the shoreline (see the spreadsheet in supplementary material accompany- warping of the mid-Pliocene shoreline across the ACP, and consequently ing this manuscript). Fig. 7b shows the geographic variation in the there must be a post-depositional signal that is not accounted for. spread of these 36 model runs around their mean, as measured by the Therefore, additional processes capable of deforming the entire ACP standard deviation of the simulations. The spread, which has a value from Georgia to Virginia must be contributing to the present day of ~11 m, indicates significant uncertainty in the GIA correction, an elevation of the shoreline. Marple and Talwani (1993, 2000),and 128 A. Rovere et al. / Earth-Science Reviews 145 (2015) 117–131

Bartholomew and Rich (2012) used geomorphic evidence, mostly relat- mantle viscosity and buoyancy structure. We note, in addition, that ed to the morphology and orientation of river channels, to argue for the the modeling of Rowley et al. (2013) did not incorporate lateral varia- presence of a buried East Coast fault system in the Carolinas and Virginia. tions in mantle viscosity. Including such structure would particularly Others have argued that changes in mantle flow-induced dynamic to- impact relatively short spatial scales in the DT predictions. At longer pography (Mitrovica et al., 1989; Gurnis, 1990, 1993; Forte et al., wavelengths, the impact of such heterogeneity in mantle viscosity is 1993a,b) have affected the elevation of the ACP (e.g. Moucha et al., likely to be small compared to the current uncertainty in seismic 2008; Müller et al., 2008; Spasojević et al., 2008). Most recently, tomography/buoyancy structure (Moucha et al., 2007). Rowley et al. (2013) showed that models of DT change can reproduce Finally, we compare the field observations described in previous the broad North–South tilting trend of the Pliocene shoreline in the sections to the numerical predictions of post-depositional deformation ACP, obtaining best fits for the northern part (i.e. Virginia). Fig. 7c due to GIA and DT. Fig. 8 shows the observed field data corrected for shows Rowley et al.'s (2013) preferred model of dynamic topography GIA (including uncertainty in both) in the blue band. This blue band change since 3 Ma; the DT signal increases moving northward along also assumes a distinct value for the eustatic sea-level difference be- the ACP to ~37°N and then decreases somewhat at higher latitudes. tween the mid-Pliocene and present-day, ranging from 0 m in Fig. 8a As noted by Rowley et al. (2013), the predicted DT change along the to 30 m in Fig. 8d. The four predictions of DT change from Rowley scarp correlates well with the extent of flooding of the ACP. Their pre- et al. (2013) are reproduced on each frame. In addition, we also show diction is, however, sensitive to the viscosity and buoyancy structure the recent prediction by Steinberger et al. (2015), which is based on a of the mantle. As one measure of the sensitivity to this uncertainty, viscosity and density model that is derived from the tomography Fig. 7d shows the spread of four different DT model runs described by model of Grand (2002; 2010 model update) through fitting surface ob- Rowley et al. (2013), where the measure of spread at each geographic servables (for model details see supplementary material in Steinberger location is once again given by the standard deviation of the numerical et al., 2015). This prediction is amongst a group of models that predict results about their mean. The four DT models represent two viscosity long-term subsidence of the whole US East coast (Müller et al., 2008; profiles, each paired with two density structures (Rowley et al., 2013). Spasojević et al., 2008); such models are difficult to reconcile with the In contrast to the GIA results in Fig. 7b, Fig. 7d indicates that the robust- observed extent of Pliocene flooding of the ACP since they would require ness of the predictions varies strongly along the strike of the shoreline. a significantly higher degree of melting during the Pliocene than Published predictions of dynamic topography and its rate of change previously thought (i.e., essentially the disappearance of all ice sheets vary significantly, which is largely a consequence of differing input den- and glaciers). The total amplitude of the GIA-corrected shoreline eleva- sity (i.e., buoyancy) and viscosity fields as well as distinct treatments of tions is ~50 m and, of the four DT predictions by Rowley et al. (2013), surface plate velocity boundary conditions (e.g. Flament et al., 2013). All the one shown in Fig. 7c (TX2007V2; represented by the solid black line four mantle flow simulations used to construct Fig. 7dwereconstrained in each of the four panels in Fig. 8) shows a comparable change in eleva- to fit present-day observables such as surface topography, free air grav- tion. The remaining three DT predictions (dashed lines) over-predict the ity anomalies, plate velocities and the excess ellipticity of the core- elevation change in the southern section of the scarp, below 35°N. mantle boundary (Simmons et al., 2007, 2009). Any prediction of DT While model TX2007V2 captures the general trend in the GIA- should certainly be based on models that satisfy present-day con- corrected observations, namely an increase in elevation of the shoreline straints, however it is unlikely that the four DT predictions discussed as one moves from 32°N to ~38°N, it does not predict the localized drop above cover the full range of possible outcomes given uncertainties in in the elevation of ~50 m between 35°N–36°N in Virginia (nor do the

100

-50

-100 a) ESL=0m b) ESL=22m

100

0 Elevation change since 3 Ma (meters) -50

-100 c) ESL=14m d) ESL=30m

32 33 34 35 36 37 38 32 33 34 35 36 37 38 Latitude (degrees)

TX2007V2 TX2007V1 TX2008V2 TX2008V1 Steinberger et al., 2015

Fig. 8. Misfit between observations and models for the elevation of the mid-Pliocene shoreline: The blue band represents the elevation change obtained by subtracting the effect of GIA from the elevation of our field data (where we took into account both effect (1) and (2) described in the text). The four panels represent four different ESL scenarios for the mid-Pliocene (for a description of each scenario, see Table 2 of Rovere et al. (2014)). The uncertainty given by the width of the blue band takes into account the uncertainties in both the paleo RSL estimate and the GIA models. The black and gray lines are predictions from five different DT models and are identical on each frame. A. Rovere et al. / Earth-Science Reviews 145 (2015) 117–131 129 other DT predictions in Fig. 8). This localized reversal of the elevation elevation gradients along the entire extent of the scarp, in particular gradient cannot be due to GIA, which produces a relatively smooth sig- the topographic step at 35°N–36°N. It is possible that this step in eleva- nal across the peripheral bulge. It is possible that the feature reflects tion is due to local tectonics (Marple and Talwani, 1993, 2000; local tectonic effects in Virginia (Marple and Talwani, 1993, 2000; Bartholomew and Rich, 2012; Berti et al., 2015), and this possibility Bartholomew and Rich, 2012; Berti et al., 2015), such as a buried dip- warrants further study. In any event, further work is also necessary to slip fault (McTigue and Segall, 1988), or, less likely, an un-modeled compute DT changes for a wider class of mantle convection simulations component of DT. We emphasize that the DT models described here that satisfy present-day global geophysical observables. In addition, bet- do not account for local tectonic effects. ter modeling of other post-depositional effects such as the loading and Another possible origin of the misfit is post-depositional deforma- unloading associated with sediment redistribution will be important. tion associated with sediment redistribution. Loading associated with The latter will require knowledge of both the spatial distribution of sed- Neogene sediments on the continental shelf is likely to have driven up- iment deposition on the continental shelf (derived, for example, from lift inland (Rowley et al., 2013), and this trend may have been accentu- isopach maps and offshore seismic profiles) as well as erosion rates on ated by erosional unloading within the continent (Cronin, 1981; land over the past 3 Ma. Such calculations could be incorporated into Pazzaglia and Gardner, 1994). Rowley et al. (2013) estimated that the an extended ice age sea-level theory that has been designed to incorpo- net amplitude of deformation-driven sediment loading and erosional rate sediment transport (Dalca et al., 2013). unloading along the Orangeburg scarp is between +20 and −8m. The dataset presented in this paper can serve as a crucial constraint However, it is not clear that the movement of sediment loads from inland on geodynamic models and also as a target for testing of disparate pub- to the continental shelf could explain the north–southtrendsinthedefor- lished predictions of dynamic topography change (e.g. Moucha et al., mation of the Orangeburg Scarp, although this remains a possibility. The 2008; Müller et al., 2008; Spasojević et al., 2008; Flament et al., 2013; Gulf of Mexico experiences significant sediment influx, but this process Rowley et al., 2013; Steinberger et al., 2015). In contrast to site- would seem to be too distant from the Orangeburg scarp to cause signif- specific paleo sea-level records, the mid-Pliocene shoreline along the icant differential uplift at 35°N–36°N (Dalca et al., 2013; Ferrier et al., ACP is a powerful constrain on geophysical models because it displays 2015). An additional possibility for the misfit between observations differential uplift that is independent of the eustatic sea-level change and models of DT and GIA is the effect of passive margin uplift in re- from the mid-Pliocene to present-day. Increasing the database of sponse to increased continental compression (Pedoja et al., 2011, 2014; Pliocene shorelines globally will also be a key to reducing current uncer- Blanco-Chao et al., 2014; Yamato et al., 2014). tainties in models of GIA and DT and, ultimately, constraining ice volumes during the mid-Pliocene. Moreover, reconstructions of Cenozoic 6. Conclusions sea-level change derived from seismic stratigraphy may also be improved as the DT histories of passive margins around the world are bet- In this paper, we have presented the results of a systematic mapping ter constrained. Essential to these investigations will be the type of field of the mid-Pliocene shoreline, typically called the Orangeburg or studies of paleoshorelines of Pliocene and Pleistocene age that we have Thornburg Scarp, along the Atlantic Coastal Plain from Virginia to presented here. Such shorelines are young enough to be well preserved Georgia. This paleoshoreline represents a major geomorphic feature and dated, and old enough to record vertical deformation over time that has been a focus of research for at least half a century (Richards, scales characteristic of mantle convection. 1950) and mapped by numerous authors (e.g. Winker and Howard, 1977a; Doar, 2012). Acknowledgments A comparison of new field elevation data with literature maps indicates that the extraction of site information from previously published The authors acknowledge NSF grant OCE-1202632 ‘PLIOMAX’ for maps results in potentially large errors in both the location and eleva- support. AR's research is also supported by the Institutional Strategy of tion of the shoreline. The subtle geomorphic expression of the mid- the University of Bremen, funded by the German Excellence Initiative Pliocene shoreline on the ACP is such that existing topographic maps (ABPZuK-03/2014) and by ZMT, the Center for Tropical Marine Ecology, only provide an approximate location of the feature, and this also University of Bremen. JXM and JA were additionally funded by Harvard leads to significant errors in establishing the elevation of the shoreline. University, and JXM, RM and AMF acknowledge support from the We note that the average difference in elevation between our ground Canadian Institute for Advanced Research. AMF was also supported by control points and the most detailed literature maps ranges between the Natural Sciences and Engineering Research Council of Canada. This 1.2 ± 7.9 m (2σ, Fig. 5c). Errors of this magnitude have potentially study was motivated by discussions at the workshops of MEDFLOOD significant implications for estimates of ancient ice volumes. (INQUA project 1203) and PALSEA, a PAGES/INQUA/WUN working The results in this paper update the dataset associated with the ACP group. The authors wish to thank R. Portell (UFMNH), W. Doar and described in Rovere et al. (2014). The uncertainty in paleo sea level re- R. Willoughby (SCGS), R. Berquist (VA), J. Tillery (NC), K. Hearty (NC), construction at the 52 sites we have included in the present analysis and R. Lockwood (C William and Mary) for their expertise and collabo- is, on average, ±3 m. Better information on the modern shorelines ration during field expeditions, James Bear, Tom Brazell (deceased), and and their morphology and on the depth of colluvium deposits at differ- Josh Heckler for granting access to the Skipper's Quarry, and K. Ferrier ent places along the ACP are required in order to improve the accuracy (Georgia Tech) for comments on the role of sediment loading and of our paleo RSL estimates. However, our elevation profile along the ACP unloading on post-depositional displacement of the mid-Pliocene demonstrates that the mid-Pliocene shoreline has been significantly de- shoreline. We also thank B. Steinberger for providing his dynamic formed. Specifically, the elevation of the scarp rises from Georgia to topography predictions and M. Vacchi (CEREGE, France) for discussions North Carolina, decreases sharply in southern Virginia, and then rises on indicative range and reference water level. We acknowledge again near Richmond, Virginia. These results reinforce the argument K. Pedoja (Caen, France) and F.J. Pazzaglia for their constructive com- by Moucha et al. (2008) that “passive margins”,eventhosewithno ments in the review process obvious signs of active tectonics, cannot be considered stable over time scales of millions of years. Appendix A. Supplementary data The long wavelength warping (100s of kms) of the mid-Pliocene shoreline suggests that dynamic topography driven by mantle flow Supplementary data associated with this article can be found in the has played a major role in this deformation (Rowley et al., 2013; online version, at http://dx.doi.org/10.1016/j.earscirev.2015.02.007. Rovere et al., 2014). However, the combined model predictions of DT These data include Google maps of the most important areas described and GIA considered in this study do not yet reproduce observed in this article. 130 A. Rovere et al. / Earth-Science Reviews 145 (2015) 117–131

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