dplRCon (version 1.0)

Example 1: Example 1: Producing correlation figure

Description

This describes the workflow required to generate the correlation figure published in "On the influence of tree size on the climate - growth relationship of New Zealand kauri (Agathis australis): insights from annual, monthly and daily growth patterns. J Wunder, AM Fowler, ER Cook, M Pirie, SPJ McCloskey. Trees 27 (4), 937-948".

Examples

## Not run: 
# #library('dplRCon')
# #loading data
# data(ring.raw)
# data(ring.stand)
# data(dbh.po.nc)
# data(SOI)
# data(temperature)
# data(precipitation)
# #Subset "near-pith" is the material within 0 -20cm from the estimated pith
# spline200.sub0.20.n   <- TruncSeriesPithoffset( ring.raw, ring.stand, dbh.po.nc, c(1,200))
# # Subset "far-pith" is the material further than 20cm from the estimated pith
# spline200.sub20.2000.n  <- TruncSeriesPithoffset( ring.raw, ring.stand, dbh.po.nc, c(200,200000))
# # Whole dataset, through truncated functions to get in the same format as the above two datasets
# spline200.sub0.2000.n  <- TruncSeriesPithoffset( ring.raw, ring.stand, dbh.po.nc, c(00,200000))
# 
# #series.bootstapped
# boot.0.20   <-  series.bootstrap( spline200.sub0.20.n$sub.series.stand, stat, 999, 
# names.stat, aver.by.tree = FALSE)
# boot.20.2000   <- series.bootstrap(spline200.sub20.2000.n$sub.series.stand, stat, 999, 
# names.stat, aver.by.tree = FALSE)
# boot.full   <- series.bootstrap(spline200.sub0.2000.n$sub.series.stand, stat, 999, 
# names.stat, aver.by.tree = FALSE)
# 
# #calculate seasonal climate
# SOI.anom.season.data  <- climate.anom.dendro.season( SOI, 1933, 1992, 1876, is.anomaly="TRUE")
# temp.anom.season.data	<- climate.anom.dendro.season( temperature, 1933, 1992, 1876, 
#                 is.anomaly="TRUE")
# prec.anom.season.data	<- climate.anom.dendro.season( precipitation, 1933, 1992, 1876, 
#                 is.anomaly="TRUE")
# 
# # Calculate the correlations for each of the climate variables
# period.RF<-c(1900,1990)
# col.names.season <- list("SON_2", "DJF_2", "MAM_2", "JJA_2", "SON_1", "DJF_1", "MAM_1","JJA_1", 
# "SON", "DJF", "MAM", "JJA")
# 
# ##	Full dataset
# site.full <- site.chron(spline200.sub0.2000.n$sub.series.stand, aver.by.tree=FALSE)
# site.chron.data <- cbind(site.full$aver.site, site.full$aver.site)
# site.boot.full <- ts(boot.full$boot.series.mean, start=tsp(site.full$aver.site)[1] )
# site.boot.data<-list(site.boot.full, site.boot.full) 	
# corr.SOI.full<-correlation.function(SOI.anom.season.data, site.chron.data, site.boot.data, 
#       period.RF,col.names.season, Climate.name="SOI", 
#       Subset.name=c("0-20cm","20-200cm" ) )
# corr.prec.full<-correlation.function(prec.anom.season.data, site.chron.data, site.boot.data, 
#       period.RF, col.names.season, Climate.name="SOI",
#       Subset.name=c("0-20cm","20-200cm" ) )
# corr.temp.full<-correlation.function(temp.anom.season.data, site.chron.data, site.boot.data, 
#       period.RF, col.names.season, Climate.name="SOI", 
#       Subset.name=c("0-20cm","20-200cm" ) )
# 
# 
# ##	Near vs Far
# site.0.20  <- site.chron(spline200.sub0.20.n$sub.series.stand, aver.by.tree=FALSE)
# site.20.200 <- site.chron(spline200.sub20.2000.n$sub.series.stand, aver.by.tree=FALSE)
# site.chron.data <- cbind(site.0.20$aver.site, site.20.200$aver.site)
# 
# site.boot.0.20 <- ts(boot.0.20$boot.series.mean, start=tsp(site.0.20$aver.site)[1] )
# site.boot.20.200 <- ts(boot.20.2000$boot.series.mean, start=tsp(site.20.200$aver.site)[1] )
# site.boot.data<-list(site.boot.0.20, site.boot.20.200) 
# 
# 
# corr.SOI<-correlation.function(SOI.anom.season.data, site.chron.data,site.boot.data, period.RF, 
# col.names.season, Climate.name="SOI", Subset.name=c("0-20cm","20-200cm" ) )
# corr.prec<-correlation.function(prec.anom.season.data, site.chron.data, site.boot.data, period.RF, 
# col.names.season, Climate.name="SOI",  Subset.name=c("0-20cm","20-200cm" ) )
# corr.temp<-correlation.function(temp.anom.season.data, site.chron.data, site.boot.data, period.RF, 
# col.names.season, Climate.name="SOI",Subset.name=c("0-20cm","20-200cm" ) )
# 
# #Plotting
# Figure.correlation.barplot(corr.temp, corr.prec, corr.SOI, 
#         corr.temp.full, corr.prec.full, corr.SOI.full, 
#         col.names.season)
# ## End(Not run)