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Olivier Blarquez, Université de Montréal
28 September 2015
paleofire R package
Motivations
• Regroup all analytical methods within a single
environment
• Ease analysis steps
• Share analytical methods within the paleofire
community
• Promote GCD usage and associated analyses for
ecologists, modellers, etc.
• R is free, the paleofire package is under GNU GPL3
Some stats and dates
• Proof of concept elaborated during the GCD meeting in Salt
Lake city in May 2013
• 7 versions: currently 1.1.6 (since 8 Jan. 2014)
• 21 functions
• 736 charcoal series in the GCD package (v3)
• 48 pages of help
• 1 tutorial and manuscript in Computers and Geosciences
(Nov. 2014)
Number of downloads from
10/2014 to 09/2015
Number of downloads per day from the Rstudio mirror
Total: 5138
paleofire main
functionalities
• Charcoal series
selection
• pfInteractive
• pfSiteSel
• pfAddData (custom
data)
paleofire main
functionalities
• Charcoal series (or sites) selection
• Transformation of charcoal data
• pfTransform (e.g. Power et al. 2008)
• Compositing i.e. construction of temporal trends
• pfCompositeLF (e.g. Daniau et al. 2012)
• Mapping: gridding and spatio temporal interpolation
• pfDotMap, pfGridding, pfSimpleGrid
paleofire main
functionalities
• Tests
• pfKruskall
• Miscellaneous
• pfToKml (export sites to Google
Earth)
• pfPublication (extract
publication data)
• potveg (extract biome information)
• etc..
Better than words: some
examples
# Install and load paleofire
install.packages("paleofire")
library(paleofire) # Load the package
# Select all sites and plot them:
all_sites <- pfSiteSel()
plot(all_sites)
Ex: Plot all sites on a map
Ex: Select sites in eastern
North America
# Sites in Eastern North America
NA <- pfSiteSel(lat>30,long<(-50),long>-170)
# Retrieve the potential vegetations of those sites using
the classification of Levavasseur et al. (2012)
NA_veg <- potveg(NA,classif="l12")
plot(NA_veg)
Ex: Select sites in eastern North
America
+ and in the boreal forest
Ex: Select sites in eastern North
America
+ and in the boreal forest
+ and add one unpublished site
# Create a vector with location of files
loc=c(“path/site1.csv”,”path/site2.csv”)
# Create an object
mysites=pfAddData(files=loc, type=“CharAnalysis”)
Transform charcoal series
and produce a composite curve
# Because of taphonomy, units, methods, etc.
# series needs to be homogenized:
BNA_trans <- pfTransform(BNA, add=mysites,
method=c("MinMax", “Box-Cox" ,"Z-Score"))
# Look at Power et al. (2008) for details
# Compositing:
BNA_comp <- pfCompositeLF(BNA_trans,
tarAge=seq(-50,11700,20),
hw=250,nboot=1000)
plot(BNA_comp)
Transform charcoal series
and produce a composite curve
# Compositing:
BNA_comp <- pfCompositeLF(BNA_trans,
tarAge=seq(-50,11700,20),
hw=250,nboot=1000)
Transform charcoal series
and produce a composite curve
Ex: Map charcoal anomalies
at 6 ka BP in Europe
ID <- pfSiteSel(id_region==‘EURO’)
TR <- pfTransform(ID,method=c("MinMax", “Box-Cox" ,"Z-
Score"))
# Spatio temporal interpolation using a tricube weight
function
Grd1<-pfGridding(TR, age=6000,
cell_size=200000,time_buffer=500, distance_buffer=300000)
plot(grd1)
Ex: Map charcoal anomalies
at 6 ka BP in Europe
Ex: Map charcoal anomalies
at 6 ka BP in Europe
# Same procedure but using lat-long WGS84 coordinates (5° grid
here); to do this first update paleofire using the GitHub
repos:
install.packages(‘devtools’)
library(devtools)
install_github(‘paleofire/paleofire’)
p=pfGridding(TR,cell_size=5,time_buffer =50,distance_buffer =
300000, age=6000,proj4='+proj=longlat +ellps=WGS84
+datum=WGS84 +no_defs’)
plot(p)
# Save the result as a netcdf file
writeRaster(p$raster,file="path/filename.nc",format='CDF')
Go further…
• Next version will link to the http://paleofire.org
website and online GCD
• Github: http://github.com/paleofire
• CRAN http://cran.r-
project.org/web/packages/paleofire/

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paleofire R

  • 1. Olivier Blarquez, Université de Montréal 28 September 2015 paleofire R package
  • 2. Motivations • Regroup all analytical methods within a single environment • Ease analysis steps • Share analytical methods within the paleofire community • Promote GCD usage and associated analyses for ecologists, modellers, etc. • R is free, the paleofire package is under GNU GPL3
  • 3. Some stats and dates • Proof of concept elaborated during the GCD meeting in Salt Lake city in May 2013 • 7 versions: currently 1.1.6 (since 8 Jan. 2014) • 21 functions • 736 charcoal series in the GCD package (v3) • 48 pages of help • 1 tutorial and manuscript in Computers and Geosciences (Nov. 2014)
  • 4. Number of downloads from 10/2014 to 09/2015 Number of downloads per day from the Rstudio mirror Total: 5138
  • 5. paleofire main functionalities • Charcoal series selection • pfInteractive • pfSiteSel • pfAddData (custom data)
  • 6. paleofire main functionalities • Charcoal series (or sites) selection • Transformation of charcoal data • pfTransform (e.g. Power et al. 2008) • Compositing i.e. construction of temporal trends • pfCompositeLF (e.g. Daniau et al. 2012) • Mapping: gridding and spatio temporal interpolation • pfDotMap, pfGridding, pfSimpleGrid
  • 7. paleofire main functionalities • Tests • pfKruskall • Miscellaneous • pfToKml (export sites to Google Earth) • pfPublication (extract publication data) • potveg (extract biome information) • etc..
  • 8. Better than words: some examples # Install and load paleofire install.packages("paleofire") library(paleofire) # Load the package # Select all sites and plot them: all_sites <- pfSiteSel() plot(all_sites)
  • 9. Ex: Plot all sites on a map
  • 10. Ex: Select sites in eastern North America # Sites in Eastern North America NA <- pfSiteSel(lat>30,long<(-50),long>-170) # Retrieve the potential vegetations of those sites using the classification of Levavasseur et al. (2012) NA_veg <- potveg(NA,classif="l12") plot(NA_veg)
  • 11. Ex: Select sites in eastern North America + and in the boreal forest
  • 12. Ex: Select sites in eastern North America + and in the boreal forest + and add one unpublished site # Create a vector with location of files loc=c(“path/site1.csv”,”path/site2.csv”) # Create an object mysites=pfAddData(files=loc, type=“CharAnalysis”)
  • 13. Transform charcoal series and produce a composite curve # Because of taphonomy, units, methods, etc. # series needs to be homogenized: BNA_trans <- pfTransform(BNA, add=mysites, method=c("MinMax", “Box-Cox" ,"Z-Score")) # Look at Power et al. (2008) for details # Compositing: BNA_comp <- pfCompositeLF(BNA_trans, tarAge=seq(-50,11700,20), hw=250,nboot=1000) plot(BNA_comp)
  • 14. Transform charcoal series and produce a composite curve # Compositing: BNA_comp <- pfCompositeLF(BNA_trans, tarAge=seq(-50,11700,20), hw=250,nboot=1000)
  • 15. Transform charcoal series and produce a composite curve
  • 16. Ex: Map charcoal anomalies at 6 ka BP in Europe ID <- pfSiteSel(id_region==‘EURO’) TR <- pfTransform(ID,method=c("MinMax", “Box-Cox" ,"Z- Score")) # Spatio temporal interpolation using a tricube weight function Grd1<-pfGridding(TR, age=6000, cell_size=200000,time_buffer=500, distance_buffer=300000) plot(grd1)
  • 17. Ex: Map charcoal anomalies at 6 ka BP in Europe
  • 18. Ex: Map charcoal anomalies at 6 ka BP in Europe # Same procedure but using lat-long WGS84 coordinates (5° grid here); to do this first update paleofire using the GitHub repos: install.packages(‘devtools’) library(devtools) install_github(‘paleofire/paleofire’) p=pfGridding(TR,cell_size=5,time_buffer =50,distance_buffer = 300000, age=6000,proj4='+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs’) plot(p) # Save the result as a netcdf file writeRaster(p$raster,file="path/filename.nc",format='CDF')
  • 19. Go further… • Next version will link to the http://paleofire.org website and online GCD • Github: http://github.com/paleofire • CRAN http://cran.r- project.org/web/packages/paleofire/