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Rscript_age_depth_models.R
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Rscript_age_depth_models.R
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# UTF-8
# Project : PhD in environmental sciences 2017-2020
# Author: Dorian Gaboriau - [email protected] - [email protected]
# Thesis: Natural factors of large wildfires in the boreal forest and prediction of future fire activity in the Northwest Territories, Canada
# Chapter 2 : Reconstitution and caracterization of the past fire regimes, vegetation and comparison with past climatic conditions (Holocene period) in the central NWT, Canada
# Author : Gaboriau Dorian
# Last update : October 2020
# R code for construction of Winbacon age depth models
rm(list = ls()) # Deleting variables from the environment R
##############################################################################################################################
# WinBacon installation
#Load the package WinBacon
wd = "C://Users//client//Documents//R//win-library//3.5//WinBacon_2.2"
setwd(wd)
source("bacon.R")
#Bacon (Blaauw and Christen, 2011) is an approach to age-depth modelling that uses Bayesian statistics to reconstruct
#Bayesian accumulation histories for deposits, through combining radiocarbon and other dates with prior information.
#In many cases Bacon isn't bothered by outlying dates, since the dates are modelled using a student-t distribution with wide tails (Christen and Pérez, 2009).
#Any age-depth model produces estimates of accumulation rates, either implicitly or explicitly. For example, the most
#popular method of connecting the mid-points of dated levels using linear sections (Blaauw, 2010), assumes that a
#deposit accumulated linearly between each dated level, and that changes in accumulation rate took place abruptly and
#exactly at the dated depths.
#Bacon divides a core into many thin vertical sections (by default of res=5 cm thickness), and through millions of
#Markov Chain Monte Carlo (MCMC) iterations estimates the accumulation rate (in years/cm; so more correctly,
#sedimentation times) for each of these sections. Combined with an estimated starting date for the first section, these
#accumulation rates then form the age-depth model. The accumulation rates are constrained by prior information as
#described below.
#The section thickness (default res=5) will dictate to some degree the flexibility of the age-depth model.
#At certain core depths, hiatuses can be inferred.
#Bacon is often used to age-model 14C-dated sequences
#Radiocarbon dates should be calibrated using either IntCal13 (for terrestrial northern hemisphere material; Reimer et al., 2013)
#(cc = 1)
#Bacon's calendar scale is cal BP (calendar years before AD 1950)
#Four columns (labID, age, error, depth), separated by commas, .csv file
##############################################################################################################################
# LAKE EMILE
dir("C:/Users/client/Documents/R/win-library/3.5/winBacon_2.2/Cores")
read.csv("./Cores/Emile/Emile.csv")
b1 = Bacon("Emile", d.min = 0, runname = "", d.max = 456, d.by = 0.5, cc = 1, prob = 0.95, rev.yr = T, postbomb = 1, rev.d=F, unit = "cm", rotate.axes = T, normal = T)
#Read the table with ages
Emile_bacon_ages = read.table("...Emile_92_ages.txt", header = T, sep = "")
Emile_bacon_ages
##############################################################################################################################
# LAKE IZAAC
read.csv("./Lake_Izaac")
#Read the table with ages
b1 = Bacon("Izaac", d.min = 0, runname = "", d.max = 359, d.by = 0.5, cc = 1, prob = 0.95, rev.yr = T, postbomb = 1, rev.d=F, unit = "cm", rotate.axes = T, normal = T)
Izaac_bacon_ages = read.table("...Izaac_72_ages.txt", header = T, sep = "")
Izaac_bacon_ages
##############################################################################################################################
# LAKE PARADIS
read.csv("./Lake_Paradis")
#Read the table with ages
b1 = Bacon("Paradis", d.min = 0, runname = "", d.max = 450, d.by = 0.5, cc = 1, prob = 0.95, rev.yr = T, postbomb = 1, rev.d=F, unit = "cm", rotate.axes = T, normal = T)
Paradis_bacon_ages = read.table("..Paradis_91_ages.txt", header = T, sep = "")
Paradis_bacon_ages
##############################################################################################################################
# LAKE SAXON
read.csv("./Lake_Saxon")
#Read the table with ages
b1 = Bacon("Saxon", d.min = 0, runname = "", d.max = 350, d.by = 0.5, cc = 1, prob = 0.95, rev.yr = T, postbomb = 1, rev.d=F, unit = "cm", rotate.axes = T, normal = T)
Saxon_bacon_ages = read.table("...Saxon_71_ages.txt", header = T, sep = "")
Saxon_bacon_ages