Introduction
Paleogeography, describing the ancient distribution of highlands, lowlands, shallow seas and deep ocean basins, is widely used in a range of fields including paleoclimatology, plate tectonic reconstructions, paleobiogeography, resource exploration and geodynamics. Global deep-time paleogeographic compilations have been published (e.g., Blakey, 2008; Golonka et al., 2006; Ronov, et al., 1984, 1989; Scotese, 2001, 2004; Smith et al., 1994). However, they are generally presented as static paleogeographic snapshots with varying map projections and different time intervals represented by the maps, and are tied to different plate motion models. This makes it difficult to convert the maps into a digital format, link them to alternative digital plate tectonic reconstructions and update them when plate motion models are improved. It is therefore challenging to use paleogeographic maps to help constrain or interpret numerical models of mantle convection that predict long-wavelength topography (Gurnis et al., 1998; Spasojevic and Gurnis, 2012) based on different tectonic reconstructions, or as an input to models of past ocean and atmosphere circulation/climate (Goddéris et al., 2014; Golonka et al., 1994) and models of past erosion/sedimentation (Salles et al., 2017).
In order to address these issues, we develop a workflow to restore the ancient paleogeographic geometries back to their modern coordinates so that the geometries can be attached to a different plate motion model. This is the first step towards the construction of paleogeographic maps with flexible spatial and temporal resolutions that are more easily testable and expandable with the incorporation of new paleoenvironmental data sets (e.g., Wright et al., 2013). In this study, we use a set of global paleogeographic maps (Golonka et al., 2006) covering the entire Phanerozoic time period as the base paleogeographic model. Coastlines on these paleogeographic maps represent estimated maximum marine transgression surfaces (Kiessling et al., 2003). We first restore the global paleogeographic geometries of Golonka et al. (2006) to their present-day coordinates by reversing the sign of the rotation angle, and then reconstruct them to geological times using a different plate motion model of Matthews et al. (2016). We then use paleoenvironmental information from marine fossil collections from the Paleobiology Database to modify the inferred paleo-coastline locations and paleogeographic geometries. Next, we use the revised paleogeography to estimate the surface areas of global paleogeographic features including deep oceans, shallow marine environments, landmasses, mountains and ice sheets. In addition, we compare the global flooded continental areas since the Devonian calculated from the revised paleogeography with other results derived from other paleoenvironment and paleo-lithofacies maps (Ronov, 1994; Smith et al., 1994; Walker et al., 2002; Blakey, 2003, 2008; Golonka, 2007b, 2009, 2012) or from the strontium isotope record (van der Meer et al., 2017). We estimate the terrestrial areal change over time associated with transferring reconstruction, filling gaps and modifying the paleogeographic geometries based on consistency test. Finally, we test the marine fossil collection data set used in this study for fossil abundances over time using different timescales of the International Commission on Stratigraphy (ICS2016; Cohen et al., 2013, updated) and of Golonka (2000) and discuss the limitations of the workflow we develop in this study.
Data and paleogeographic model
The data used in this study are global paleogeographic maps and
paleoenvironmental data for the last 402 million years (Myr), which
originate from the set of paleogeographic maps produced by Golonka et al. (2006) and the Paleobiology Database (PBDB,
Timescale since the Early Devonian (Golonka, 2000) used in the paleogeographic maps of Golonka et al. (2006), the original timescale of Sloss (1988) and of the International Commission on Stratigraphy (ICS2016). Ages in italics are obtained by linear interpolation between subdivisions.
Sloss (1988) | Golonka (2000) | ICS2016 | ||||||||
---|---|---|---|---|---|---|---|---|---|---|
Era | Subsequence | Start | End | Time slice | Epoch/age | Start | End | Reconstruction | Start | End |
(Ma) | (Ma) | (Ma) | (Ma) | time (Ma) | (Ma) | (Ma) | ||||
Cenozoic | Tejas III | 29 | 0 | late Tejas III | Tortonian–Gelasian | 11 | 2 | 6 | 11.63 | 1.80 |
late Tejas II | Burdigalian–Serravallian | 20 | 11 | 14 | 20.44 | 11.63 | ||||
late Tejas I | Chattian–Aquitanian | 29 | 20 | 22 | 28.1 | 20.44 | ||||
Tejas II | 39 | 29 | early Tejas III | Priabonian–Rupelian | 37 | 29 | 33 | 37.8 | 28.1 | |
Tejas I | 60 | 39 | early Tejas II | Lutetian–Bartonian | 49 | 37 | 45 | 47.8 | 37.8 | |
early Tejas I | Thanetian–Ypresian | 58 | 49 | 53 | 59.2 | 47.8 | ||||
Mesozoic | Zuni III | 96 | 60 | late Zuni IV | middle Campanian–Selandian (Late Cretaceous–earliest Paleogene) | 81 | 58 | 76 | 79.8 | 59.2 |
late Zuni III | late Cenomanian–early Campanian (Late Cretaceous) | 94 | 81 | 90 | 96.1 | 79.8 | ||||
Zuni II | 134 | 96 | late Zuni II | late Aptian–middle Cenomanian (Early Cretaceous–earliest Late Cretaceous) | 117 | 94 | 105 | 119.0 | 96.1 | |
late Zuni I | late Valanginian–early Aptian (Early Cretaceous) | 135 | 117 | 126 | 136.4 | 119.0 | ||||
Zuni I | 186 | 134 | early Zuni III | late Tithonian–early Valanginian (latest Late Jurassic–earliest Early Cretaceous) | 146 | 135 | 140 | 147.4 | 136.4 | |
early Zuni II | late Bathonian–middle Tithonian (earliest Middle Jurassic–Late Jurassic) | 166 | 146 | 152 | 166.8 | 147.4 | ||||
early Zuni I | middle Aalenian–middle Bathonian (Middle Jurassic) | 179 | 166 | 169 | 172.8 | 166.8 | ||||
Absaroka III | 245 | 186 | late Absaroka III | late Hettangian–early Aalenian (Early Jurassic–earliest Middle Jurassic) | 203 | 179 | 195 | 200.0 | 172.8 | |
late Absaroka II | late Carnian–middle Hettangian (Late Triassic–earliest Jurassic) | 224 | 203 | 218 | 232 | 200.0 | ||||
late Absaroka I | Induan–early Carnian (Early–earliest Late Triassic) | 248 | 224 | 232 | 252.17 | 232 | ||||
Paleozoic | Absaroka II | 268 | 245 | early Absaroka IV | Roadian–Changhsingian (Late Permian) | 269 | 248 | 255 | 272.3 | 252.17 |
early Absaroka III | Sakmarian–Kungurian (Early Permian) | 285 | 269 | 277 | 295.0 | 272.3 | ||||
Absaroka I | 330 | 268 | early Absaroka II | Gzhelian–Asselian (latest Carboniferous–earliest Permian) | 296 | 285 | 287 | 303.7 | 295.0 | |
early Absaroka I | Bashkirian–Kasimovian (Late Carboniferous) | 323 | 296 | 302 | 323.2 | 303.7 | ||||
Kaskaskia II | 362 | 330 | Kaskaskia IV | middle Visean–Serpukhovian (Lower Carboniferous) | 338 | 323 | 328 | 341.4 | 323.2 | |
Kaskaskia III | late Famennian–early Visean (latest Devonian–Early Carboniferous) | 359 | 338 | 348 | 365.6 | 341.4 | ||||
Kaskaskia I | 401 | 362 | Kaskaskia II | Givetian–early Famennian (Middle–Late Devonian) | 380 | 359 | 368 | 387.7 | 365.6 | |
Kaskaskia I | late Pragian–Eifelian (Early–Middle Devonian) | 402 | 380 | 396 | 408.7 | 387.7 |
Global distributions and number of fossil collections since the Devonian. The greyscale background shows global present-day topography ETOPO1 (Amante and Eakins, 2009) with lighter shades corresponding to increasing elevation. Fossil collections from the PBDB are colored following the standard used by the International Commission on Stratigraphy.
[Figure omitted. See PDF]
The paleogeographic maps of Golonka et al. (2006) are constructed using a plate tectonic model available in the supplement of Golonka (2007a), where relative plate motions are described. In this rotation model, paleomagnetic data are used to constrain the paleolatitudinal positions of continents and rotation of plates, and hotspots, where applicable, are used as reference points to calculate paleolongtitudes (Golonka, 2007a). This rotation model is necessary to restore these paleogeographic geometries (Golonka et al., 2006) to their present-day coordinates so that they can be attached to a different plate motion model. The relative plate motions of Golonka (2006, 2007a) are based on the reconstruction of Scotese (1997, 2004).
Here, we use a global plate kinematic model to reconstruct paleogeographies back in time from present-day locations. The global tectonic reconstruction of Matthews et al. (2016), with continuously closing plate boundaries from 410–0 Ma, is primarily constructed from a Mesozoic and Cenozoic plate model (230–0 Ma; Müller et al., 2016) and a Paleozoic model (410–250 Ma; Domeier and Torsvik, 2014). This model is a relative plate motion model that is ultimately tied to Earth's spin axis through a paleomagnetic reference frame for times before 70 Ma, and a moving hotspot reference frame for younger times (Matthews et al., 2016).
The PBDB is a compilation of global fossil data covering deep geological time. All fossil collections in the database contain detailed metadata, including on the time range (typically biostratigraphic age), present-day geographic coordinates, host lithology and paleoenvironment. Figure 1 represents distributions of the global fossil collections at present-day coordinates and shows their numbers since the Devonian. The recorded fossil collections are unevenly distributed both spatially and temporally, largely due to the differences in fossil preservation, the spatial sampling biases of fossil localities and the uneven entry of fossil data to the PBDB (Alroy, 2010). For this study, a total of 57 854 fossil collections with temporal and paleoenvironmental assignments from 402 to 2 Ma were downloaded from the database on 7 September 2016.
Methods
The methodology can be divided into three main steps: (1) the original
paleogeographic geometries are restored to present-day coordinates by
applying the inverse of the rotations used to make the reconstruction, (2) these restored geometries are then rotated to new locations using the plate
tectonic model of Matthews et al. (2016) and (3) the paleo-coastline locations
and paleogeographic geometries are adjusted using paleoenvironmental data
from the PBDB. Figure 2 illustrates the generalized workflow that can be
applied to a different paleogeography model. In order to represent the
paleogeographic maps as digital geographic geometries, they are first
georeferenced using the original projection and coordinate system (global
Mollweide in Golonka et al., 2006), and then re-projected into the WGS84
geographic coordinate system. The resulting maps are then attached to the
original rotation model using the open-source and cross-platform plate
reconstruction software GPlates (
Workflow used to transfer a set of paleogeographic geometries from one reconstruction to another, followed by revision using paleoenvironmental information indicated by marine fossil collections from the Paleobiology Database (PBDB).
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(a) Original global paleogeographic map from Golonka et al. (2006) at 126 Ma. (b) Global paleogeographic geometries at 126 Ma in present-day coordinates. (c) Global paleogeography at 126 Ma reconstructed using the plate motion model of Matthews et al. (2016). Gaps are highlighted in pink. (d) Global paleogeography at 126 Ma reconstructed using the reconstruction of Matthews et al. (2016) with gaps fixed by filling with adjacent paleoenvironment attributes. Grey lines indicate reconstructed present-day coastlines and terrane boundaries. Mollweide projection with 0 E central meridian.
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Lookup table to classify fossil data indicating different paleoenvironments into marine or terrestrial settings and their corresponding paleogeographic types presented in Golonka et al. (2006). Terrestrial fossil paleoenvironments correspond to paleogeographic features of landmasses, mountains or ice sheets and marine fossil paleoenvironments to shallow marine environments or deep oceans.
Marine | Terrestrial/transitional zone | ||||
---|---|---|---|---|---|
Paleogeography | Fossil paleoenvironments | Paleogeography | Fossil paleoenvironments | ||
shallow marine environments/deep oceans | marine indet. | slope | Landmasses/mountains | terrestrial indet. | pond |
carbonate indet. | basinal (carbonate) | fluvial indet. | crater lake | ||
peritidal | basinal (siliceous) | alluvial fan | lacustrine delta plain | ||
shallow subtidal indet. | marginal marine indet. | channel lag | lacustrine interdistributary bay | ||
open shallow subtidal | coastal indet. | coarse channel fill | lacustrine delta front | ||
lagoonal/restricted shallow subtidal | estuary/bay | fine channel fill | lacustrine prodelta | ||
sand shoal | lagoonal | channel | lacustrine deltaic indet. | ||
reef, buildup or bioherm | paralic indet. | wet floodplain | lacustrine indet. | ||
peri-reef or sub-reef | interdistributary bay | dry floodplain | dune | ||
intra-shelf/intraplatform reef | delta front | floodplain | inter-dune | ||
platform/shelf-margin reef | prodelta | crevasse splay | loess | ||
slope/ramp reef | deltaic indet. | levee | eolian indet. | ||
basin reef | foreshore | mire/swamp | cave | ||
deep subtidal ramp | shore face | fluvial–lacustrine indet. | fissure fill | ||
deep subtidal shelf | transition zone/lower shore face | delta plain | sinkhole | ||
deep subtidal indet. | offshore | fluvial–deltaic indet. | karst indet. | ||
offshore ramp | submarine fan | lacustrine – large | tar | ||
offshore shelf | basinal (siliciclastic) | lacustrine – small | spring | ||
offshore indet. | deep-water indet. | ice sheets | glacial |
When the paleogeographic geometries in present-day coordinates are attached to a new reconstruction model, as Matthews et al. (2016) used in this study, the resulting paleogeographies result in gaps (Fig. 3c, pink) and overlaps between neighboring polygons, when compared to the original reconstruction (Fig. 3a). These gaps and overlaps essentially arise from the differences in the reconstructions described in Matthews et al. (2016) and Golonka et al. (2006). The reconstruction of Golonka et al. (2006) has a tighter fit of the major continents within Pangea prior to the supercontinent breakup. In addition, this reconstruction contains a different plate motion history and block boundary definitions in regions of complex continental deformation, for example along active continental margins (e.g., Himalayas, western North America; Fig. 3c).
The gaps and overlaps cause changes in the total terrestrial or oceanic paleogeographic areas at different time intervals, becoming larger or smaller, when compared with the original paleogeographic maps (Golonka et al., 2006). The gaps can be fixed by interactively extending the outlines of the polygons in a GIS platform to make the plates connect as in the original paleogeographic maps (Fig. 3a, c, d). Changes in the extent of total terrestrial or oceanic area of the paleogeographies with filled gaps are compared with the original paleogeographies in Fig. 3d (Golonka et al., 2006).
Once the gaps are filled, the reconstructed paleogeographic features are compared with the paleoenvironments indicated by the marine fossil collections from the PBDB. These comparisons aim to identify the differences between the mapped paleogeography and the marine fossil collection environments in order to revise the paleo-coastline locations and paleogeographic geometries. Fossil collections belonging to each time interval (Table 1; Golonka, 2000) are first extracted from the data set downloaded from the PBDB. Only the fossil collections with temporal ranges lying entirely within the corresponding time intervals are selected, as opposed to including the fossil collections that have larger temporal ranges. Fossil collections with temporal ranges crossing any time-interval boundary are not taken into consideration. As a result, a minimum number of fossil collections are selected for each time interval. The selected fossil collections are classified into either the terrestrial or marine setting category, according to a lookup table (Table 2).
Marine fossil collections are then attached to the plate motion model of Matthews et al. (2016) so they can be reconstructed at each time interval. Subsequently, a point-in-polygon test is used to determine whether or not the indicated marine fossil collection is within the appropriate marine paleogeographic polygon. The results of these tests are discussed in the following section.
(a) Test between the global paleogeography at 76 Ma reconstructed using the plate motion model of Matthews et al. (2016) with gaps fixed and the paleoenvironments indicated by the marine fossil collections from the PBDB. (b) Area modified (blue) to resolve the test inconsistencies. (c) Test between the revised paleogeography at 76 Ma and the same marine fossil collections. Mollweide projection with 0 E central meridian.
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Test between unrevised and revised paleogeography at 76 Ma, respectively, and paleoenvironments indicated by the marine fossil collections from the PBDB, and revision of the paleo-coastlines and paleogeographic geometries based on the test results, for southern North America (a, b, c), southern South America (d, e, f), northern Africa (g, h, i) and India (j, k, l). Regional Mollweide projection.
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In the next step, we modify the paleo-coastline locations and paleogeographic geometries based on the test (Figs. 4, 5 and Supplement). Modifications are made according to the following rules. (1) Marine fossil collections from the PBDB are presumed to be well dated, constrained geographically, not reworked and representative of their broader paleoenvironments. Their indicative environments are assumed to be correct. (2) Only marine fossil collections within 500 km of the nearest paleo-coastlines are taken into account as most marine fossil collections used in this study are located within 500 km from the paleo-coastlines (see Fig. S1 in the Supplement). (3) The paleo-coastlines and paleogeographic geometries are modified until they are consistent with the marine fossil collection environments and at the same time remain about 30 km distance from the fossil points used (Fig. 5c, f, l). (4) The adjacent paleo-coastlines are accordingly adjusted and smoothed (Figs. 4, 5). (5) The modified area (Fig. 5b, e, k, blue) resulting from shifting the coastline is filled using the shallow marine environment. These rules are designed to maximize the use of the paleoenvironmental information obtained from the marine fossil collections to improve the coastline locations and paleogeography while attempting to minimize spurious modifications.
However, in some rare cases, outlier marine fossil data may be a deceptive recorder of paleogeography. For instance, Wichura et al. (2015) discussed the discovery of a 17 Myr old beaked whale fossil 740 km inland from the present-day coastline of the Indian Ocean in east Africa. The authors found evidence to suggest that this whale could have traveled inland from the Indian Ocean along an eastward-directed fluvial (terrestrial) drainage system and was stranded there, rather than representing a marine setting that would be implied under our assumptions. Therefore, theoretically, when using the fossil collections to improve paleogeography, additional concerns about living habits of fossils and associated geological settings should be taken into account. In this study, we have removed this misleading fossil whale from the data set. Such instances of deceptive fossil data are a potential limitation within our workflow, which we seek to minimize by excluding inconsistent fossils more than 500 km away from previously interpreted paleo-coastlines described above.
Results
Paleoenvironmental tests
Global reconstructed paleogeographic maps from 402 to 2 Ma are tested against paleoenvironments indicated by the marine fossil collections that are reconstructed in the same rotation model (Matthews et al., 2016). The consistency ratio is defined by the marine fossil collections within shallow marine or deep ocean paleogeographic polygons as a percentage of all marine fossil collections at the time interval, and in contrast, the inconsistency ratio is defined by the marine fossil collections not within shallow marine or deep ocean paleogeography as a percentage of all marine fossil collections. Heine et al. (2015) used a similar metric to evaluate global paleo-coastline models since the Cretaceous.
(a) Consistency ratios between global paleogeography with gap filled, but before PBDB test for the period 402–2 Ma, reconstructed using the plate motion model of Matthews et al. (2016) and the paleoenvironments indicated by the marine fossil collections from the PBDB. (b) Numbers of consistent (light grey) and inconsistent (dark grey) marine fossil collections used in the tests for each time interval from 402 to 2 Ma.
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The inconsistent marine fossil collections are used to modify coastlines and paleogeographic geometries according to the rules outlined in the Methods section. The consistency ratios of marine fossil collections during 402–2 Ma are all over 55 %, with an average of 75 % (Fig. 6a, shaded area) although with large fluctuations over time (Fig. 6). This indicates that the paleogeography of Golonka et al. (2006) has relatively high consistency with the fossil records. However, 52 fossil collections over all time intervals cannot be resolved as they are over 500 km distant from the nearest coastline (for example, red points in Fig. 5c, l). Therefore, in some cases, the paleogeography cannot be fully reconciled with the paleobiology (see Supplement). The results since the Cretaceous are similar to that of Heine et al. (2015).
The sums of marine fossil collections change significantly over time (Fig. 6b); for example, there are more than 4000 in total within 269–248 Ma but only 20 during 37–29 Ma. These variations are due to the spatiotemporal sampling bias and incompleteness of the fossil record (Benton et al., 2000; Benson and Upchurch, 2013; Smith et al., 2012; Valentine et al., 2006; Wright et al., 2013), biota extinction and recovery (Hallam and Wignall, 1997; Hart, 1996), the uneven entry of fossil data to the PBDB (Alroy, 2010) and our temporal selection criterion. In addition, the differences in the duration of geological time subdivisions lead to some time intervals having shorter time spans that contain fewer fossil records, which we discuss in a later section. As for the time intervals during which fossil data are scarce, the fossil collections are of limited use in improving paleogeography. However, additional records in the future will increase the usefulness of the PBDB in such instances.
Global paleogeography from 402 to 2 Ma reconstructed using the plate motion model of Matthews et al. (2016) and revised using paleoenvironmental data from the PBDB. Black dotted lines indicate subduction zones, and other black lines denote mid-ocean ridges and transforms. Grey outlines delineate reconstructed present-day coastlines and terranes. Mollweide projection with 0 E central meridian.
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(continued)
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Revised global reconstructed paleogeography
Based on the PBDB test results at all the time intervals, we can revise the inferred paleo-coastlines and paleogeographic geometries using the approach described in the Methods section. As a result, the revised paleo-coastlines and paleogeographies are significantly improved, mainly in the regions of North America, South America, Europe and Africa during the Late Carboniferous, Middle Permian, Triassic, Jurassic, Late Cretaceous and most of Cenozoic (Figs. 4, 5, 6 and Supplement). The resulting improved global paleogeographic maps since the Devonian are presented in Fig. 7. They provide improved paleo-coastlines that are important to constrain past changes in sea level and long-wavelength dynamic topography.
Global paleogeographic feature areas as percentages of Earth's total surface area estimated from the revised paleogeographic maps from 402 Ma to 2 Ma.
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Global flooded continental area since the Early Devonian from the original paleogeographic maps of Golonka et al. (2006; grey solid line) and from the revised paleogeography in this study (pink line). Results for Blakey (2003, 2008), Golonka (2007b, 2009, 2012), Ronov (1994), Smith et al. (2004) and Walker et al. (2002) are as in van der Meer et al. (2017). The van der Meer et al. (2017) curve (green line) is derived from the strontium isotope record of marine carbonates.
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We subsequently calculate the area covered by each paleogeographic feature as a percentage of Earth's total surface area at each time interval from 402 to 2 Ma (Fig. 8), using the HEALPix pixelization method that results in equal sampling of data on a sphere (Górski et al., 2005) and therefore equal sampling of surface areas. This method effectively excludes the effect of overlaps between paleogeographic geometries.
As a result, the areas of landmass, mountain and ice sheet generally indicate increasing trends, while shallow marine and deep ocean areas show decreasing trends through geological time (Fig. 8). Overall, the computed areas increase in the following order: ice sheet (average 1.0 % of Earth surface), mountain belts (3.4 %), shallow marine (14.3 %), landmass (21.3 %) and deep ocean (60.1 %). Only during the time interval of 323–296 Ma are landmass and shallow marine areas nearly equal at about 14.0 %, and only during 359–285 Ma do ice sheet areas exceed mountain areas, but ice sheets only exist during 380–285, 81–58 and 37–2 Ma. With Pangea formation during the latest Carboniferous or the Early Permian and breakup initiation in the Early Jurassic (Blakey, 2003; Domeier et al., 2012; Lenardic, 2016; Stampfli et al., 2013; Vai, 2003; Veevers, 2004; Yeh and Shellnutt, 2016), these paleogeographic feature areas significantly change over time (Fig. 8). During 323–296 Ma (Late Carboniferous–earliest Permian), the landmass extent reaches its smallest area (13.6 %) and subsequently undergoes a rapid increase until peaking at 26.6 % between 224 and 203 Ma (Late Triassic). In contrast, ice sheets reach their largest area (7.2 %) between 323 and 296 Ma. In the Early Jurassic of Pangea breakup, landmass area rapidly decreases from 26.6 % between 224 and 203 Ma to 23.5 % between 203 and 179 Ma, but shallow marine area increases by 3.7 %.
Discussions
Global flooded continental areas
We estimate the global flooded continental areas since the Early Devonian from the revised paleogeography in this study (Fig. 9, pink solid line) and from the original paleogeographic maps of Golonka et al. (2006; Fig. 9, grey solid line). Both sets of results are similar, with a decrease during Pangea amalgamation from the Late Devonian until the Late Carboniferous, increase from the Early Jurassic with the breakup of Pangea until the Late Cretaceous and then a decrease again until the Pleistocene. We compare the two curves (pink solid line, grey solid line; Fig. 9) to the results of other studies (Fig. 9; Ronov, 1994; Smith et al., 1994; Walker et al., 2002; Blakey, 2003, 2008; Golonka, 2007b, 2009, 2012) derived from independent paleoenvironment and paleo-lithofacies data. The results are generally consistent, except for the periods 338–269 Ma and 248–203 Ma, during which the flooded continental areas for this study and Golonka et al. (2006) are smaller, reflecting smaller extent of transgression in these times. Van der Meer et al. (2017, green line in Fig. 9) derived sea level and continental flooding from the strontium isotope record of marine carbonates. These results are generally consistent with the estimates from paleoenvironment and paleo-lithofacies data, except during the Permian and the Late Jurassic–early Cretaceous, during which van der Meer et al. (2017) predict larger extent of flooding than others (Fig. 9). This could indicate that the evolution of Sr Sr reflects variations in the composition of emergent continental crust (Bataille et al., 2017; Flament et al., 2013) as well as global weathering rates (e.g., Flament et al., 2013; Vérard et al., 2015; van der Meer et al., 2017).
Terrestrial areal change due to filling gaps and modifying the paleo-coastlines and paleogeographic geometries over time. Green: based on the original paleogeographic maps of Golonka et al. (2006); red: based on paleogeography reconstructed using a different plate motion model of Matthews et al. (2016) and gaps filled; blue: based on paleogeography with gaps fixed and revised using the paleoenvironments indicated by marine fossil collections from the PBDB.
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Terrestrial areal change associated with transferring reconstruction, filling gaps and revising paleogeography
We estimate the terrestrial areas, including ice sheets, mountains and landmasses, as percentages of Earth's surface area, from the original paleogeography of Golonka et al. (2006; Fig. 10, green), from the paleogeography reconstructed using a different plate motion model of Matthews et al. (2016) and gaps filled (Fig. 10, red) and from the paleogeography with gaps fixed and revised using the paleoenvironmental information indicated by marine fossil collections from the PBDB (Fig. 10, blue). These three curves are similar and generally indicate a reverse changing trend to the flooded continental areal curves over time (Fig. 9), as expected. We also calculate the areas of the terrestrial paleogeographic geometries after transferring the reconstruction but before filling gaps and the results are nearly identical to the original terrestrial paleogeographic areas of Golonka et al. (2006). This is because the reconstruction of Golonka et al. (2006) has a tighter fit of the major continents within Pangea prior to the supercontinent breakup than the reconstruction of Matthews et al. (2016), so that transferring the paleogeographic geometries mainly produces gaps rather than overlaps. Comparing between the three curves (Fig. 10), filling gaps results in a larger terrestrial areal change than revising paleogeographic geometries based on PBDB test. Therefore, variation of the underlying plate reconstruction is the main factor that contributes to the terrestrial areal change (Fig. 10, red and green), and the effect of revising paleogeographic geometries based on paleobiology is secondary (Fig. 10, blue).
Marine fossil collection abundances in two different timescales
We test the marine fossil collection data set used in this study for fossil abundances over time with two different timescales: ICS2016 and Golonka (2000; Table 1). The results indicate the abundances of the data set in the two timescales are significantly different in most time intervals (Fig. 11). Generally, shorter time spans contain fewer data; for instance, there are about 400 marine fossil collections between 224 and 203 Ma using the Golonka (2000) timescale (Fig. 11, red), while there are over 1300 collections during 232–200 Ma using the ICS2016 timescale (Fig. 11, blue). In addition, the difference of the start age and end age of the time interval could remarkably affect the fossil abundance, so that there are over 2000 marine fossil collections between 387.7 and 365.6 Ma in ICS2016 but fewer than 300 collections between 380 and 359 Ma using the Golonka (2000) timescale. As a result, the timescale applied to the paleobiology could significantly affect the fossil collection abundance being assigned to paleogeographic time intervals.
Fossil abundance test on the marine fossil collection data set used in this study with two different timescales: Golonka (2000) and ICS2016 (Table 1).
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Limitations of the workflow
The workflow we develop in this study illustrates transferring paleogeographic geometries from one plate motion model to another and then using paleoenvironmental information indicated by marine fossil collections from the PBDB to improve the paleo-coastline locations and paleogeographic geometries. However, the methodology still has some limitations. Transferring paleogeographic geometries to a different reconstruction inevitably results in gaps and/or overlaps, which can only be addressed using presently laborious methods. In addition, revising the coastlines and paleogeographic geometries based on the PBDB test is also currently achieved manually, and could be automated in the future.
Paleogeographic maps such as those considered here typically represent discrete time periods of many millions of years, whereas global plate motion models, even though also based on tectonic stages, provide a somewhat more continuous description of evolving plate configurations. A remaining question is how to provide a continuous representation of paleogeographic change that combines continuous plate motion models with paleogeographic maps that do not explicitly capture changes at the same temporal resolution. In addition, it is currently difficult to apply a timescale to the raw paleobiology data from the PBDB that are currently not tied to any timescale. The paleoenvironmental data used here have variable temporal resolutions, but the paleo-coastlines representing maximum transgressions are presented in a location at specific times. However, due to the inaccessibility of the original data that were used to build the paleogeographic maps, we are not in a position to estimate the temporal resolution of the original coastlines and paleogeographic maps.
The PBDB is a widely used resource (e.g., Wright et al., 2013; Finnegan et
al., 2015; Heim et al., 2015; Mannion et al., 2015; Nicolson et al., 2015;
Fischer et al., 2016; Tennant et al., 2016; Close et al., 2017; Zaffos et
al., 2017), yet, the spatial coverage of data is still highly heterogeneous,
with relatively few data points across large areas of the globe for some
time periods. Hence, it is important to combine it with other geological data,
such as stratigraphic data from StratDB Database (
Conclusions
Our study highlights the flexibility of digital paleogeographic models linked to plate tectonic reconstructions in order to better understand the interplay of continental growth and eustasy, with wider implications for understanding Earth's paleotopography, ocean circulation and the role of mantle convection in shaping long-wavelength topography. We present a workflow that enables the construction of paleogeographic maps with variable spatial and temporal resolutions, while also becoming more testable and expandable with the incorporation of new paleoenvironmental data sets.
We develop an approach to revise the paleo-coastline locations and paleogeographic geometries using paleoenvironmental information indicated by the marine fossil collections from the PBDB. Using this approach, the consistency ratio between the paleogeography and the paleobiology records since the Devonian is increased from an average 75 % to nearly full consistency. The paleogeography in the main regions of North America, South America, Europe and Africa is significantly improved, especially in the Late Carboniferous, Middle Permian, Triassic, Jurassic, Late Cretaceous and most portions of the Cenozoic. The flooded continental areas since the Late Devonian inferred from the revised global paleogeography in this study are generally consistent with the results derived from other paleoenvironment and paleo-lithofacies data or from the strontium isotope record in marine carbonates.
Comparing the terrestrial areal change over time associated with transferring the reconstruction and filling gaps, and revising paleogeographic geometries using the paleoenvironmental data from the PBDB, indicates that reconstruction difference is a main factor in paleogeographic areal change when comparing with the original maps, and revising paleogeographic geometries based on PBDB test is secondary.
Information about the supplement
We provide two sets of digital global paleogeographic maps during 402–2 Ma: (1) the paleogeography reconstructed using the plate motion model of Matthews et al. (2016) and revised using paleoenvironmental information indicated by the marine fossil collections from the PBDB and (2) the original paleogeography of Golonka et al. (2006). We also provide the original rotation file of Golonka et al. (2006), a set of paleogeographic maps illustrating the PBDB test and revision of paleo-coastlines and paleogeographic geometries, a set of GeoTiff files of all revised paleogeographic maps, paleobiology data in shapefile used in this study separated into two sets of consistent marine fossil collections and inconsistent marine fossil collections, an animation for the revised global paleogeographic maps, and a README file outlined the workflow of this study.
The Supplement related to this article is available online at
No data sets were used in this article.
The authors declare that they have no conflict of interest.
Acknowledgements
This work was supported by Australian Research Council grants IH130200012 (RDM, SZ), DE160101020 (NF) and SIEF RP 04-174 (SW). W. Cao was also supported by a University of Sydney International Scholarship (USydIS). We thank Julia Sheehan and Logan Yeo for digitizing these paleogeographic maps, and John Cannon and Michael Chin for help with GPlates and pyGPlates. We sincerely thank Shanan Peters and three anonymous reviewers for their constructive reviews and suggestions. We thank Natascha Töpfer for editorial support and Tina Treude for editing the manuscript. We are also thankful for the entire PBDB team and all PBDB data contributors. This is Paleobiology Database Publication 296.Edited by: Tina Treude Reviewed by: Shanan Peters and three anonymous referees
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Abstract
Paleogeographic reconstructions are important to understand Earth's tectonic evolution, past eustatic and regional sea level change, paleoclimate and ocean circulation, deep Earth resources and to constrain and interpret the dynamic topography predicted by mantle convection models. Global paleogeographic maps have been compiled and published, but they are generally presented as static maps with varying map projections, different time intervals represented by the maps and different plate motion models that underlie the paleogeographic reconstructions. This makes it difficult to convert the maps into a digital form and link them to alternative digital plate tectonic reconstructions. To address this limitation, we develop a workflow to restore global paleogeographic maps to their present-day coordinates and enable them to be linked to a different tectonic reconstruction. We use marine fossil collections from the Paleobiology Database to identify inconsistencies between their indicative paleoenvironments and published paleogeographic maps, and revise the locations of inferred paleo-coastlines that represent the estimated maximum transgression surfaces by resolving these inconsistencies. As a result, the consistency ratio between the paleogeography and the paleoenvironments indicated by the marine fossil collections is increased from an average of 75 % to nearly full consistency (100 %). The paleogeography in the main regions of North America, South America, Europe and Africa is significantly revised, especially in the Late Carboniferous, Middle Permian, Triassic, Jurassic, Late Cretaceous and most of the Cenozoic. The global flooded continental areas since the Early Devonian calculated from the revised paleogeography in this study are generally consistent with results derived from other paleoenvironment and paleo-lithofacies data and with the strontium isotope record in marine carbonates. We also estimate the terrestrial areal change over time associated with transferring reconstruction, filling gaps and modifying the paleogeographic geometries based on the paleobiology test. This indicates that the variation of the underlying plate reconstruction is the main factor that contributes to the terrestrial areal change, and the effect of revising paleogeographic geometries based on paleobiology is secondary.
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1 EarthByte Group and Basin GENESIS Hub, School of Geosciences, The University of Sydney, Sydney, NSW 2006, Australia
2 EarthByte Group and Basin GENESIS Hub, School of Geosciences, The University of Sydney, Sydney, NSW 2006, Australia; current address: School of Earth and Environmental Sciences, University of Wollongong, Northfields Avenue, Wollongong, NSW 2522, Australia
3 Faculty of Geology, Geophysics and Environmental Protection, AGH University of Science and Technology, Mickiewicza 30, 30-059 Kraków, Poland
4 EarthByte Group and Basin GENESIS Hub, School of Geosciences, The University of Sydney, Sydney, NSW 2006, Australia; Sydney Informatics Hub, The University of Sydney, Sydney, NSW 2006, Australia