Workflow: Example 1: Producing correlation figure
In dplRCon: Concordance for Dendroclimatology
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
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
## 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)
dplRCon documentation built on May 2, 2019, 2:02 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 | ## 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)
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.