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serac: an R package for ShortlivEd RAdionuclide Chronology of recent sediment cores

Rosalie Bruel
October 25th, 2020

Content - serac: an R package for ShortlivEd RAdionuclide Chronology of recent sediment cores - 1. Get your data ready - 2. Download serac - 3. Test your hypotheses - 4. Citation and references

Dating sediments is the first and critical step of any palaeo-study. Specifically, accurately dating the past century is crucial in palaeoclimate and palaeoecological studies because of the many socio-ecological changes that took place during that period. When annual varves are absent, short-lived radionuclides, based on the measurements of the activity of 137Cs, 241Am, 210Pb, and 226Ra, provide the most accurate and widely used age-depth model technique for the past century.

The isotopes 137Cs, 241Am, 210Pb, and 226Ra are most commonly measured together using a non-destructive gamma-spectrometric analysis, allowing a direct determination of 210Pb unsupported (210Pbex) through the 226Ra activity. Measurements are often stored in a spreadsheet, allowing computation of the age-depth model. Then, figures can be created and edited in a costly photo editor.

Using spreadsheets for storing and computing age-depth models raises the issue of versionning, and increases the risk for errors. Furthermore, most of the common programs (for spreadsheet or photo editing) need a license, that not everyone can afford (think about someone in-between two jobs, with no affiliations).

Our package allows a systematic approach to producing chronologies for sediment cores using short-lived radionuclides (210Pbex, 137Cs, and 241Am). The package is implemented in R (free and open source). Our code itself is open source. We included a number of arguments allowing beginners to tweak the code to edit the output (change in colors, font sizes, etc.), but more advanced users can fork our code from Github and edit it.

Several 210Pbex models are implemented in our package:
  • constant initial concentration (CIC),
  • constant rate of supply (CRS),
  • constant flux constant sedimentation rate (CFCS),
  • piecewise versions of CRS and CFCS.

The steps are documented in our manuscript and in a vignettes you can access from R. In this blogpost I’m including a way for you to test the potential of the function (go directly to the bottom of this page).

1. Get your data ready

The input format has to follow some codes, otherwise R will display an error message.

We are sharing within the package some example data from Lake Allos (France). You can use those to follow along, or based the input format on them. The publication by Wilhelm et al (2012) is accessible here.

left: Lake Allos (Source: Flickr); right: Location, hydrological, geological and geomorphological characteristics of Lake Allos and its catchment (Fig. 1 in Wilhelm et al 2012)
left: Lake Allos (Source: Flickr); right: Location, hydrological, geological and geomorphological characteristics of Lake Allos and its catchment (Fig. 1 in Wilhelm et al 2012)

Your dataset should follow a similar format than the one below. Only 4 columns are in fact mandatory: * top and bottom section of the sample OR average depth and thickness * 210Pbex and error on 210Pbex

With these information, you can compute a simple CRS model. Other models require to add the density.

2. Download serac

You can download serac from my GitHub repository using the packages devtools.

install.packages(devtools)
devtools::install_github(‘rosalieb/serac’, build_vignettes = TRUE)
library(serac)

3. Test your hypotheses

At the minimum, your function will be:

serac(name=‘serac_example_ALO09P12’,coring_yr=2009)

Several sedimentation hypotheses were tested, and this is what the author chose as the best model:

serac(name=‘ALO09P12’, coring_yr=2009, model=c(‘CFCS’), plotphoto=FALSE, minphoto=c(0), maxphoto=c(210), plot_Pb=T, plot_Am=T, plot_Cs=T, Cher=c(30,40), Hemisphere=c(‘NH’), NWT=c(51,61), sedchange=c(75.5), plot_Pb_inst_deposit=T, inst_deposit=c(20,28,100,107,135,142,158,186), suppdescriptor=TRUE, descriptor_lab=c(‘Ca/Fe’), historic_d=c(20,28,100,107,135,142,158,186), historic_a=c(1994,1920,1886,1868), historic_n=c(‘sept 1994 flood’,‘1920 flood’,‘1886 flood’,‘1868 flood ?’), min_yr=c(1750),dmax=c(180), plotpdf=TRUE,preview=F)

Here the output plot:

Serac allows to test several type of sedimentation hypotheses:
  • constant initial concentration (CIC),
  • constant rate of supply (CRS),
  • constant flux constant sedimentation rate (CFCS),

as well as piecewise versions of CRS and CFCS.

Refer to the example in our paper to see the extent of model hypotheses you can test. And please, let us know if you see any issues with the package by sending us an email!

4. Citation and references

To cite our method, please use: Bruel, R., Sabatier, P., 2020. serac: An R package for ShortlivEd RAdionuclide chronology of recent sediment cores. Journal of Environmental Radioactivity 225, 106449. https://doi.org/10.1016/j.jenvrad.2020.106449

Refer to the package’s vignette for more details (if the link doesn’t work, copy and paste in your browser the following: https://rosalieb.github.io/rosaliebruelweb/files/Introduction-to-serac.html).

Table of content created using this method.

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