Published February 9, 2021 | Version v1

Data from: Palaeontology meets metacommunity ecology: The Maastricthian dinosaur fossil record of North America as a case study

  • 1. University of Leon
  • 2. Finnish Environment Institute
  • 3. University of Oulu
  • 4. University College London
  • 5. University of Edinburgh

Description

Documenting the patterns and potential associated processes of ancient biotas has always been a central challenge in palaeontology. Over the last decades, intense debate has focused on the organisation of dinosaur–dominated communities, yet no general consensus has been reached on how these communities were organised in a spatial context and if primarily affected by abiotic or biotic agents. Here, we used analytical routines typically applied in metacommunity ecology to provide novel insights into dinosaurian distributions across the latest Cretaceous of North America. To do this, we combined fossil occurrences with functional, phylogenetic and palaeoenvironmental modelling, and adopted the perspective that more reasonable conclusions on palaeoecological reconstructions can be gained from studies that consider the organisation of biotas along ecological gradients at multiple spatial scales. Our results showed that dinosaurs were restricted in range to different parts of the Hell Creek Formation, prompting the recognition of discrete and compartmentalised faunal areas during the Maastrichtian at fine-grained scales, whereas taxa ranges formed quasi–nested groups when combining data from various geological formations across the Western Interior of North America. Although groups of dinosaurs had coincident range boundaries, their communities responded to multiple ecologically–important gradients when compensating for differences in sampling effort. Metacommunity structures of both ornithischians and theropods were correlated with climatic barriers and potential trophic relationships between herbivores and carnivores, thereby suggesting that dinosaurian faunas were shaped by physiological constraints and a combination of bottom-up and top-down forces across multiple spatial grains and extents.

Notes

Additional Supporting files include the following Appendices:

Appendix S1. Body mass distributions based on product partition models with Markov sampling computations.

            Appendix S2. Functional and phylogenetic features for each spatial scale and study clade.

            Appendix S3. R packages and statistical routines.

            Appendix S4. Elements of metacommunity structure for the conservative fixed–fixed null model.

            Appendix S5. Results for the forward selection of explanatory variables.

            Appendix S6. Results for ordinary least squares (OLS) regression models.

            Appendix S7. Results for commonality analysis (CA) for each spatial scale and study clade.

            Appendix S8. Measuring the spatial autocorrelation of OLS model residuals.

The Excel file includes occurrence data, palaeoenvironmental reconstructions, and functional features:

Sheets 1 and 2 contain raw information on each study site for the Hell Creek and other North American geological formations, respectively.

Sheet 1 includes palaeoenvironmental information for the Hell Creek Formation (i.e. lithofacies -C, channel; FP, floodplain- and palaeotopography -m.a.s.l. after log-transformation). Raw PalaeoDEM data (Scotese and Wright, 2018) are also available here: https://www.earthbyte.org/paleodem-resource-scotese-and-wright-2018/

Sheet 2 contains raw information on the log-transformed palaeoenvironmental reconstructions for the Maastrichtian of North America (Palaeotopography -m.a.s.l., TempMean and TempSDann in K; Prec and PrecSDann in kgm-2). Raw palaeoclimate GCMs (Valdés et al., 2017) can also be obtained here: https://www.paleo.bristol.ac.uk/ummodel/scripts/papers/

Sheet 3 includes a taxon-specific classification into several functional guilds (see the main text for details):

These files may be opened and edited in Excel. 
For details or further queries, please contact Jorge García-Girón (jogarg@unileon.es).

Funding provided by: University of León*
Crossref Funder Registry ID:
Award Number: 2017

Funding provided by: Spanish Ministry of Economy and Industry*
Crossref Funder Registry ID:
Award Number: CGL2017–84176R

Funding provided by: Junta de Castilla y León
Crossref Funder Registry ID: http://dx.doi.org/10.13039/501100014180
Award Number: LE004G18

Funding provided by: Academy of Finland
Crossref Funder Registry ID: http://dx.doi.org/10.13039/501100002341
Award Number: 331957

Funding provided by: Academy of Finland
Crossref Funder Registry ID: http://dx.doi.org/10.13039/501100002341
Award Number: 322652

Funding provided by: European Research Council Starting Grant*
Crossref Funder Registry ID:
Award Number: ERC StG 2017, 756226, PalM

Funding provided by: University of León
Crossref Funder Registry ID:
Award Number: 2017

Funding provided by: Spanish Ministry of Economy and Industry
Crossref Funder Registry ID:
Award Number: CGL2017–84176R

Funding provided by: European Research Council Starting Grant
Crossref Funder Registry ID:
Award Number: ERC StG 2017, 756226, PalM

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