Improving global paleogeography since the late Paleozoic using paleobiology

Cao, Wenchao; Zahirovic, Sabin; Flament, Nicolas; Williams, Simon; Golonka, Jan; Müller, R. Dietmar

doi:https://doi.org/10.5194/bg-14-5425-2017

Articles | Volume 14, issue 23

https://doi.org/10.5194/bg-14-5425-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

https://doi.org/10.5194/bg-14-5425-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 14, issue 23

Research article

|

04 Dec 2017

Research article |

| 04 Dec 2017

Improving global paleogeography since the late Paleozoic using paleobiology

Wenchao Cao, Sabin Zahirovic, Nicolas Flament, Simon Williams, Jan Golonka, and R. Dietmar Müller

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Final revised paper (published on 04 Dec 2017)
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Preprint (discussion started on 18 Apr 2017)
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Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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RC1: 'Referee Report', Anonymous Referee #1, 03 May 2017
- AC1: 'Response to reviewer 1', Wenchao Cao, 03 Jul 2017
RC2: 'review of bg-2017-94: Improving global paleogeography since the late Paleozoic using paleobiology', Anonymous Referee #2, 03 May 2017
- AC2: 'Response to reviewer 2', Wenchao Cao, 03 Jul 2017

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

ED: Reconsider after major revisions (12 Jul 2017) by Tina Treude

AR by Wenchao Cao on behalf of the Authors (22 Aug 2017)

ED: Referee Nomination & Report Request started (26 Aug 2017) by Tina Treude

RR by Shanan Peters (24 Sep 2017)

Suggestions for revision or reasons for rejection

Accurate paleogeographic reconstructions are required to test a wide range of hypotheses in the geosciences and they are a critical foundation upon which to build next-generation 4D Earth systems models. In order to produce the best possible reconstructions, no data can be left behind. This paper represents an important step towards a general method by which paleogeographically sensitive proxy data (e.g., fossils, sediments) can be used to test and improve existing paleogeographic reconstructions. This type of reconstruction model-data comparison is critical and the scale of the problem is such that algorithmic solutions and automation are of great added value. The paper is well written, the examples given are clear and powerful, and the potential of the approach and scientific outcomes are substantial. I have only a few suggestions, detailed below.

1) Discrete timescales of reconstructions and the mapping of proxy data therein.

Table 1 outlines the timescale used for the Golonka reconstructions and this represents the first major cull of Paleobiology Database data. Only those collections that are temporally resolved in the PBDB to fall entirely within the bins specified by the reconstruction timescale are included. An example bin used is the “late Cenomanian-early Campanian.” According to the methods description, this means that any PBDB fossil collection assigned to a time interval of “Cenomanian” or “Campanian” would be omitted from the analysis and only fossil collections resolved to a finer biostratigraphic zone within these two international ages would be included. This is an understandable convention given the discrete bins of the original Golonka reconstructions, but this protocol results in a large cull of PBDB data. International ages (e.g., Cenomanian) are generally defined by our ability to consistently correlate globally. It is certainly the case that biostratigraphic zonation can be more precise, particularly in the marine record, but a stage-level age assignment for a given collection is something that PBDB data enterers would be very satisfied with in the majority of cases. Indeed, in the example of the Cenomanian and Campanian above, there are more than 2,200 collections resolved to these two intervals and these would not be included. Similar numbers of collections are probably omitted from all such divided international ages (this is somewhat conveyed in the differences between curves in FIg. 11). Does this cull matter? Given that the Cenomanian-Turonian sea level high stand is likely captured by at least some collections that are resolved only to “Cenomanian,” its possible that it does. There are a few statistical approaches one could take to overcoming this problem (in addition to improving the PBDB ages constraints, see below).

Finally, it is noted that PBDB data were “downloaded” from the database on a given date. This is a useful description, but the PBDB API allows for very specific definition of download protocols in the form of a URL. I strongly recommend that these details either be specified or, better still, that the URL for the API request be provided (it might also be good to include citations that describe these PBDB resources). Requesting an official PBDB publication number, should the manuscript be accepted, and including that in the Acknowledgements would be appropriate as well. John Alroy and company’s original vision and the many PBDB data contributors should be recognized in this capacity.

2) The “500 km test”

Fossil collections deviating by more than 500 km from previously interpreted paleoshorelines are excluded herein. Why 500km? Why not 397 km? Or 193 km? With few exceptions, whenever there is some value arbitrarily defined as a threshold there is a more interesting and principled approach. I would find the distribution of deviations between “previously interpreted” shorelines and PBDB collections fascinating, both in aggregate and on an interval-by-interval and/or a plate-by-plate basis. These distributions would have statistical utility of several different types, including defining a principled threshold criterion for data rejection. To me, this would be single most interesting analytical addition to the paper.

One potential utility of adopting an approach that leveraged the statistical nature of the distribution of deviations is that this could be used to add quantitative estimates of error (mostly of a random nature) that is introduced at every step, from the original coordinates of PBDB collections (some of which are most certainly not accurately located) to the assignment of an age.

3) Minor points/questions: Use of fossils in pre-Triassic reconstructions, plates that appear during Phanerozoic, and next steps.

For geologically obvious reasons, not all plates can be tracked backwards in time to the Paleozoic. Are such plates excluded here? Does this matter to any of the results presented herein?

Prior to the constraints on rotations provided by sea floor data, there is considerable uncertainty in the paleopositions of the continents, particularly with respect to longitude. At such times, the fossil record becomes increasingly important, not just for shoreline reconstructions but also for continent positions. I have previously detected a quantitative signature of PBDB biogeographic patterns in Paleozoic reconstructions and have concluded that at least some of the signal reflects the fact the the fossil record was relied on more heavily in the Paleozoic than in the post Paleozoic. Does this matter? Is a potentially changing role for fossils in deriving paleopositions detectable in any way here?

I’m excited by the possibility of completely closing the loop, from aggregation of paleogeographically-useful data in PBDB and Macrostrat-type resources to testing and improving paleogeographic reconstructions, in a largely automated, algorithmic fashion. Certainly there are things we are working on now to improve the temporal resolution of PBDB fossil collections, notably by integrating them with stratigraphic models such as those in Macrostrat. I’d be very interested in discussing how to improve this process and to fully capitalize on paleogeographic reconstructions in a way that avoids circularity problems and that makes the data as useful as possible to the GPlates team, and vice versa. This paper is an important and welcome first step.

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RR by Anonymous Referee #4 (26 Sep 2017)

Suggestions for revision or reasons for rejection

There is a growing appreciation of the wide and constructive uses of paleogeographic maps for many areas of the geosciences. The community is transitioning from “static” (as the authors call them) or non digital to digital format paleogeographic maps. As with many aspects of our science, the effort is somewhat scattered and in this case the University of Sydney group is a pioneer in this area.

The authors stated main contribution is to “develop a workflow to restore the ancient paleogeographic geometries back to their modern coordinates”. There longer term goal is to provide 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 paleo-environmental datasets…”. These are worthy goals and I think this manuscript can make a contribution. But I found myself asking almost philosophical questions on the approach here rather than specific comments on the results. I think this manuscript is concise in its explanation of the methods and main results, but it needs expansion of the Discussion. My points below can mainly be addressed in an expansion of the 5.4 Limitations of the Workflow section into a more general Discussion section.

One major point I have is this. As the earlier reviewer #1 implies and I ask – should we use older paleogeographic reconstructions as is being done here, or essentially start over with more quantitative local to regional data and build up to global scale maps? Related to this - are the revised coastlines presented here an improvement over the Golonka 2006 coastlines, and how do we really know? A more general question is how to transition from the largely pre-digital era and publications with little (or at least much less) meta data and documentation of sources of data to the fully digital era? The lesser documentation of earlier paleogeographic research is mainly inevitable in that most (all?) older primary publications with proposed paleoenvironmental features (for example, coastlines) did not give quantitative spatial data in the modern sense. Note for example that the authors in their response to review #1 admit that: “Since the original data that were used to estimate the coastlines are not available for us, it is difficult to give the weight to the paleobiology data. The coastlines drawn on the original maps represent maximum transgression surfaces and we do not know much about their errors.” This latter point is made by the authors despite the well-respected Professor Golonka as the lead author of the synthesis of the coastlines (his 2006 paper) used in the methods in the present paper. In summary, the current community that produces quantitative tectonic reconstructions and paleogeographic maps may have to admit that it might have to essentially "start over" with regional-scale studies in which paleobiological and paleoenvironmental data are entered on GIS-based or other spatially quantitative base maps rather than try to “improve” older maps.

Another point of discussion – there are serious problems with the variability of the temporal resolution of the various paleoenvironmental data used here and this is only partly addressed. For example, maps attempting to show maximum transgressions imply that we know the coastline location at very specific times in the past (especially during Icehouse periods) with perhaps thousands to a few tens thousands years resolution. I agree with reviewer #1 that it might be best, and more appropriate to the data available, to locate only marginal marine zones or belts that suggest much wider temporal and spatial spans involved (10s to a few 100 thousands years). For example, individual fossil locations in PBDB have a temporal resolution dependent on the type of index fossil and where it lies in the paleontological record. Many index fossils have a resolution of many 100 thousands to 1-2 million years. My point is not that this variability of data resolution invalidates using these different data sets, but that there needs to be more discussion here of what exactly is being depicted on the paleogeographic maps and what a particular paleogeographic feature means in terms of temporal and spatial resolution.

Finally, I think these points should be addressed with more discussion in the 5.4 Limitations of the Workflow section. How can the community best move to developing quantitative paleogeography maps? And what have the authors learned by trying to update older paleogeographic maps? The current discussion in section 5.4 of the PBDB is good and provides valid suggestions. Here is an example of the need for more discussion: you state in section 5.4 that “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.” I think the authors who just completed this workflow project should make suggestions on how to answer this question. I would also like the authors to directly address the earlier point I made on the value of revising older paleogeographic maps (Golonka or Blakey as examples) versus building new maps from more fragmentary, but spatially and temporally more quantitative, data from the PBDB, StratDB and Macrostrat.

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ED: Publish subject to minor revisions (Editor review) (27 Sep 2017) by Tina Treude

AR by Wenchao Cao on behalf of the Authors (10 Oct 2017) Author's response Manuscript

ED: Publish subject to technical corrections (21 Oct 2017) by Tina Treude

AR by Wenchao Cao on behalf of the Authors (24 Oct 2017) Author's response Manuscript

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Short summary

We present a workflow to link paleogeographic maps to alternative plate tectonic models, alleviating the problem that published global paleogeographic maps are generally presented as static maps and tied to a particular plate model. We further develop an approach to improve paleogeography using paleobiology. The resulting paleogeographies are consistent with proxies of eustatic sea level change since ~400 Myr ago. We make the digital global paleogeographic maps available as an open resource.