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The ShellChron package contains all formulae and documentation requiredto run the ShellChron model. The ShellChron model uses stable oxygenisotope records (d18O) from seasonal paleo-archives to create an agemodel for the archive.

In short, ShellChron feeds a temperature sinusoid (Figure 1; see detailsin “temperature_curve()” function) and a skewed growth rate sinusoid(Figure 2; see details in “growth_rate_curve()” function) to a d18Omodel (see details in “d18O_model()” function). The resulting modeledd18O is then compared with the user-provided d18O data and theparameters of the temperature and growth rate functions are optimizedusing the SCEUA algorithm (seeDuan et al.,1992) to match the d18O data. As aresult, the timing of each data point with reference to the seasonalcycle is exported, from which an age model for the entire record can beconstructed.

The model builds on previous work byJudd etal. 2018 and expands onthis previous model in several key ways:

1. ShellChron allows SCEUA optimization to be carried out in a slidingwindow through the data and recognizes year transitions (see“cumulative_day()” formula) to produce seamless age models throughmultiple years. Overlapping windows are used to estimate thereproducibility of model results.
2. ShellChron provides the option to take uncertainties on the inputdata (“D_err” and “d18Oc_err”) into account in error estimation(see “mc_err_orth()” and "export_results() functions), providingrealistic errors on the age estimation which were previouslyunsupported.
3. ShellChron supports different empirical formulae for convertingtemperature and d18O of the precipitation fluid into d18O records,providing compatibility with records consisting of variousmineralogies (e.g. calcite and aragonite).
4. ShellChron offers more dynamic input options for data on thevariable that is not modeled (usually d18O of precipitation fluid),circumventing the (often false) assumption that this variableremains constant throughout the year and preventing fixed values forthis variable hardcoded in the model.
5. ShellChron achieves more efficient SCEUA modeling by pre-guessingthe parameters of temperature and growth rate sinusoids using asinusoidal regression (see “sinreg()” formula). This is an essentialfeature that allows ShellChron to process more optimization windowswhile retaining competitive processing time (see Figure 3).

NOTE: To run optimally, ShellChron requires sampling distance datato be provided in micrometers (see “data_import()” function). Theoptimal structure of the input CSV should be as follows (see descriptionin “Virtual_shell” example):

column 1: D Sampling distance, in micrometers along the virtualrecord.

column 2: d18Oc stable oxygen isotope value, in permille VPDB.

column 3: YEARMARKER Vector of zeroes with “1” marking yeartransitions.

column 4: D_err Sampling distance uncertainty, in micrometers.

column 5: d18Oc_err stable oxygen isotope value uncertainty, inpermille.

When you use ShellChron, please citede Winter,2022:

de Winter, N.J. (2022) “ShellChron 0.4.0: a new tool for constructingchronologies in accretionary carbonate archives from stable oxygenisotope profiles” Geoscientific Model Development 15, 1247-1267, DOI:10.5194/gmd-15-1247-2022

You can install the released version of ShellChron fromCRAN with:

install.packages("ShellChron")

And the development version fromGitHub with:

# install.packages("devtools")devtools::install_github("nielsjdewinter/ShellChron")

This is a basic example which shows you how to solve a common problem:

library(ShellChron)## Full model run# WARNING: Running the full ShellChron model (even on small example data) always takes some time (usually in the order of 30-60 minutes)# example <- wrap_function(path = getwd(),#  file_name = system.file("extdata", "Virtual_shell.csv",#  package = "ShellChron"),#  "calcite",#  1,#  365,#  d18Ow = 0,#  t_maxtemp = 182.5,#  MC = 1000,#  plot = FALSE,#  plot_export = FALSE,#  export_raw = FALSE)"# Quick demo on how to create an SST curve# Set parametersT_amp<-20T_per<-365T_pha<-150T_av<-15T_par<- c(T_amp,T_per,T_pha,T_av)SST<- temperature_curve(T_par,1,1)# Run the function