Making a geologic outcrop map with rmacrostrat
In rmacrostrat: Fetch Geologic Data from the 'Macrostrat' Platform

Authors: The Palaeoverse Development Team

Last updated: 2024-10-17

# Introduction `rmacrostrat` is an R package that allows users to easily retrieve geologic data from the [Macrostrat](https://macrostrat.org) database and facilitates analyses of these data within the R environment. This vignette (or tutorial, if you prefer) is provided to guide you through the installation process and some of the functionality available within `rmacrostrat`. Specifically, we will focus on making a geographic map of a specific geologic formation, a commonly required (and very important) figure for a variety of purposes across the geosciences. # Installation The `rmacrostrat` package can be installed via CRAN, or its dedicated [GitHub repository](https://github.com/palaeoverse/rmacrostrat) if the development version is preferred. To install via CRAN, simply use: wzxhzdk:0 To install the development version, first install the `devtools` package, and then use `install_github` to install `rmacrostrat` directly from GitHub. wzxhzdk:1 You can now load `rmacrostrat` using the standard `library` function: wzxhzdk:2 **Before we get into the good stuff, the development team has a small request**. If you use `rmacrostrat` in your research, please cite the associated publication. This will help us to continue our work in supporting you to do yours. You can access the appropriate citation via: wzxhzdk:3 wzxhzdk:4 # Context The Hell Creek is a geologic formation from the late Cretaceous and early Paleogene of North America, which is found cropping out across Montana and North and South Dakota, in the United States. It consists of both freshwater and brackish clays, mudstones, and sandstones, deposited by a fluvial system on the shoreline of the Western Interior Seaway. The Hell Creek is famous for its preservation of an extensive array of both terrestrial and marginal marine fossils from just prior to the K/Pg mass extinction (66 million years ago), including widely recognizable dinosaurs such as *Edmontosaurus*, *Triceratops* and *Tyrannosaurus rex*. In this vignette, we will show you how to use `rmacrostrat` to find the outcrop of the Hell Creek Formation, and use this to create a map which could be used in a potential publication. Whilst we have chosen a specific formation, this approach could be applied to any number of geologic units of interest. So, let's dive in! # Fetching First, we want to find the `strat_name_id`s that are associated with the Hell Creek. These IDs are linked to unique stratigraphic names given to one or more geologic units, such as Macrostrat units or map units, in the Macrostrat database. We can search for the relevant IDs by using some of the `def_*` functions. These functions provide information about the data stored in the database. Let's have a look at the information associated with the name Hell Creek, using `def_strat_names()`: wzxhzdk:5 wzxhzdk:6 We can see that there are three different `strat_name`s associated with the name Hell Creek. You'll also see that all three have the same `concept_id`, showing that these stratigraphic names are united under a single geologic entity. We can therefore use this `concept_id` to search for all references to the Hell Creek: wzxhzdk:7 wzxhzdk:8 Yup, these three are the only entries for Hell Creek. But hang on! Before going ahead and using these to pull our spatial data, you'll also notice that one of the `strat_name`s here is actually the Hell Creek "Member", which is described as belonging to the Lance Formation. On a hunt in the literature, it turns out that this is a term used for the Hell Creek before it was designated to the rank of formation (Archibald, 1982), so it's okay to include here. But it's always worth remembering to check your data for errors prior to using it! Let's go ahead and use the `strat_name_id`s associated with the Hell Creek `concept_id` to get some spatial data. To do this, we'll need to use the `get_map_outcrop()` function, which allows us to grab outcrop polygons from geologic maps. Let's do that now, specifying that we want the output to be returned as an sf, or 'simple features', object. An sf object is a collection of simple features (representations of real world objects) that includes attributes and geometries in the form of a `data.frame`. wzxhzdk:9 Nice. Let's have a look at the first entry to see what the data looks like. wzxhzdk:10 wzxhzdk:11 That looks like what we need! We have a simple features collection consisting of multi-polygons, with attributes that indicate it contains data for the Hell Creek Formation. Now let's move on to visualizing the data. # Visualization To plot our outcrop map, we'll have to install and load some packages that let us handle and plot spatial data. Let's do that now. wzxhzdk:12 wzxhzdk:13 First, we can use the packages `rnaturalearth` and `rnaturalearthhires` to get the maps and state/province outlines of the USA, Mexico and Canada to use as a background. wzxhzdk:14 Now we're ready to plot our outcrop! We can use the `ggplot2` package to help us do this, in particular the `geom_sf()` function. Let's plot our background maps and outcrop now: wzxhzdk:15

plot of chunk plot-outcrop

Looking good! But we can take this map a bit further. A common dinosaur found in the Hell Creek is *Edmontosaurus*, a large duck-billed dinosaur. Let's combine what we've got so far with data from [The Paleobiology Database](https://paleobiodb.org) (PBDB) to make a map of *Edmontosaurus* occurrences in the Hell Creek. wzxhzdk:16

plot of chunk plot-Edmontosaurus

Those *Edmontosaurus* occurrences are now plotted on the map. You may notice that there are some occurrences that don't overlay the plotted outcrop, despite apparently being from the Hell Creek. This could be due to an error in the PBDB data, potentially relating to the accuracy of the latitude and longitude co-ordinates, or it could be that we're missing some outcrop data of the Hell Creek. Either way, this shows that plotting occurrences over their respective outcrop can a good way to explore potential data issues. Aside from those errant occurrences, it's starting to look pretty good! But we can add a few more finishing touches to really make it pop. First, let's the use package [`rphylopic`](https://rphylopic.palaeoverse.org/index.html) to add a silhouette of *Edmontosaurus* to the map. wzxhzdk:17 wzxhzdk:18 wzxhzdk:19 wzxhzdk:20

plot of chunk add-rphylopic

Nice! Finally, we can add a few other touches to make it a publication-worthy figure, including an inlay map, a scale bar, and a North arrow: wzxhzdk:21

plot of chunk add-inlay-scale

And that's it! One completed map. ...But that's not all we can do with outcrop data! As a quick extra, let's calculate the total outcrop area of the Hell Creek Formation: wzxhzdk:22 wzxhzdk:23 So from these few lines of code, we can work out that the total outcrop area for the Hell Creek Formation is a touch larger than the total land area of Polynesia (which is approximately 37,141 km^2^)! Pretty neat. Hopefully this vignette has shown you some potential uses for `rmacrostrat` functions and helped provide a workflow for your own analyses. If you have any questions about the package or its functionality, please feel free to join our [Palaeoverse Google group](https://groups.google.com/g/palaeoverse) and leave a comment; we'll aim to answer it as soon as possible! If you're interested in learning more about `rmacrostrat`, don't forget to check out our other vignettes! You can see which ones are available by calling `vignette(package = "rmacrostrat")`. # References Archibald, J.D. (1982). A study of Mammalia and geology across the Cretaceous-Tertiary boundary in Garfield County, Montana (Vol. 122). Univ of California Press. Dunnington, D. (2023). *ggspatial: Spatial Data Framework for ggplot2*. R package version 1.1.9, . Gearty, W., and Jones, L.A., 2023, rphylopic: An R package for fetching, transforming, and visualising PhyloPic silhouettes: Methods in Ecology and Evolution, v. 14, p. 2700–2708, doi: [10.1111/2041-210X.14221](https://doi.org/10.1111/2041-210X.14221). Massicotte, P., South, A. (2023). *rnaturalearth: World Map Data from Natural Earth*. R package version 1.0.1, . Pebesma, E., & Bivand, R. (2023). Spatial Data Science: With Applications in R. Chapman and Hall/CRC, doi: 10.1201/9780429459016. Pebesma, E., 2018. Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10 (1), 439-446, doi: [10.32614/RJ-2018-009](https://doi.org/10.32614/RJ-2018-009). Peters, S.E., Husson, J.M., and Czaplewski, J., 2018, Macrostrat: A Platform for Geological Data Integration and Deep‐Time Earth Crust Research: Geochemistry, Geophysics, Geosystems, v. 19, p. 1393–1409, doi: [10.1029/2018GC007467](https://doi.org/10.1029/2018GC007467). Uhen, M.D., Allen, B., Behboudi, N., Clapham, M.E., Dunne, E., Hendy, A., Holroyd, P.A., Hopkins, M., Mannion, P., Novack-Gottshall, P. and Pimiento, C., 2023. Paleobiology Database User Guide Version 1.0. *PaleoBios*, 40(11). doi: [10.5070/P9401160531](https://doi.org/10.5070/P9401160531). Wickham H. 2016 ggplot2: Elegant Graphics for Data Analysis. *Springer-Verlag New York*. Wickham H., Hester J., Chang W., Bryan J. (2022). *devtools: Tools to Make Developing R Packages Easier*. R package version 2.4.5, . Wilke C (2024). *cowplot: Streamlined Plot Theme and Plot Annotations for 'ggplot2'*. R package version 1.1.3, .