File:Mamontovy khayata pollen 1.svg

author={Andrei A {Andreev} and Lutz {Schirrmeister} and Christine {Siegert} and Anatoly A {Bobrov} and Dieter {Demske} and Maria {Seiffert} and Hans-Wolfgang {Hubberten}},
title=Template:Fig. 3: Pollen and spore counts of the Mamontovy Khayata sequences,
year={2002},
doi={10.1594/PANGAEA.728482},
url={https://doi.org/10.1594/PANGAEA.728482},
note={In supplement to: Andreev, AA et al. (2002): Paleoenvironmental changes in northeastern Siberia during the Late Quaternary - evidence from pollen records of the Bykovsky Peninsula. Polarforschung, 70, 13-25, https://doi.org/10.2312/polarforschung.70.13},
type={data set},
publisher={PANGAEA}

1. 3. pollen diagram of Mamontovy Khayata
   5. 28.10.21 0000.0005

library("tidyverse") library("dplyr") library("stringi") library("stringr") library("pracma")

library("ggplot2") library("cowplot")

library("neotoma") library("rioja") library("ggpalaeo") #Need new version

1. 1. https://doi.pangaea.de/10.1594/PANGAEA.728482

plot_taxons=1 plot_groups=0

plot_to_svg=1

1. 1. minimum pollen count %

minpercent1=40

sitename1="Mamontovy Khayata"

1. from Pangaea
2. https://doi.pangaea.de/10.1594/PANGAEA.728482

finame1<-"Mamontovy_Khayata_pollen_spores.tab"

sitename_x0=tolower(sitename1) sitename_x1<-str_replace(sitename_x0,' ', '_') outfilename1<-paste0("./",sitename_x1,"_pollen_n.svg") outfilename2<-paste0("./",sitename_x1,"_pollen_groups_1.svg")

#dev.off()

in1<- readLines(finame1)

length1<-length(in1)

1. print (length1)

n=1 loc1=n

in_komments=0 in_species=0

long_specie_table_00<-vector()

for(n in 1:length1) { rowi=in1[n] sica=substr(rowi,1,2) sica2=substr(rowi,1,13) sica3=substr(rowi,1,8) #print(sica) #print(n)

if(in_species==1) { if (identical(sica3,"License:")) { sica3="" in_species=0 } }

if(in_species==1) { #print(rowi) specie01<-word(rowi,1,sep = "\\ \\[") specie02<-word(specie01,1,sep = "\\ \\*") #print(specie1) specie2<-sub("\t", "", specie02) long_specie_table_00<-c(long_specie_table_00, specie2) #print(specie2) }

if(in_komments==1) { if (identical(sica2,"Parameter(s):")) { sica2="" in_species=1

#print(rowi)

#stop(-3) } }

if (identical(sica,"/*")) { in_komments=1 #"comment in" #break } if (identical(sica,"*/")) { in_komments=0 in_species=0 #"comment out" loc1=n break }

}

1. stop(-4)

namef1<-read.csv(finame1, skip = loc1,nrows=1, sep=" ",header = F)

dataf1 = read.csv(finame1, skip = loc1+1, sep=" ",header = F)

1. namef1

1. dataf1

rowlen1<-nrow(dataf1) collen1<-ncol(dataf1)

1. print (collen1)

ages1<-dataf1["V1"] ages1<-ages1*1000

poldatas1<-dataf1[5:57] polnames1<-namef1[5:57] groupdatas1<-dataf1[58:62] groupnames1<-namef1[58:62]

long_specie_table_01<-long_specie_table_00[4:56]

1. long_specie_table_01

long_polnames01<-as.data.frame(long_specie_table_01)

names(long_polnames01)<-"taxon"

long_polnames1=data.frame(t(long_polnames01))

1. stop(-1)

names(ages1)<-"age" names(polnames1)<-c("taxon")

polnames1 <- data.frame(lapply(polnames1, function(x) {

                 gsub("\\[#\\]", "", x)
             }))

groupnames1 <- data.frame(lapply(groupnames1, function(x) {

                 gsub("\\ \\[#\\]", "", x)
             }))

1. print("Data ...")

1. print (polnames1)
2. str(polnames1)

1. str(long_polnames1)

1. polak1<-rbind(polnames1,poldatas1)

polak1<-poldatas1

1. names(polak1)<-polnames1

names(polak1)<-long_polnames1

1. stop(-6)

width1<-ncol(polak1)

polak2<-polak1 / rowSums(polak1) * 100

polak2<-polak2[, colSums(polak2 != 0) > minpercent1]

1. polak2

1. polak3<-c(ages1,polak2)

polak3<-polak2 polak3<-cbind(ages1,polak3)

1. polak3

1. stop(-1)

polak3_spp <- polak3 %>% select(-age,)

# %>% #as.data.frame()

1. polak3_spp <- polak3 %>%
2. select(-age,) %>%
3. as.data.frame(polak3_spp)

1. stop(-1)

polak3_dist <- dist(sqrt(polak3_spp/100))#chord distance

1. stop(-1)

clust <- chclust(polak3_dist, method = "coniss")

1. str(clust)

1. stop(-1)

1. p.col <- c(rep("forestgreen", times=width1))
   1. colors by eco groups, must tune by hand

p.col <- c( rep("forestgreen", times=2), rep("orange", times=7), rep("red", times=2) )

1. ages1

1. y.scale=seq(0,60000,1000)

1. y.scale=1:60

ages2<-ages1$age

y.scale=as.vector(ages2)

y.labels=y.scale

1. str(y.scale)

if(plot_taxons==1) { print("Taxons ...") ## set up mgp for layout

if(plot_to_svg==1) { svg(filename=outfilename1, width=8, height=10, pointsize=16) }

mgp <- c(3, 0.25, 0) par(tcl = -0.15, mgp = mgp)#shorter axis ticks - see ?par

pol.plot <- strat.plot( title=sitename1, ylabel = "Age BP", polak2, yvar=y.scale, #y.tks=y.scale, cex.xlabel = 1.2, cex.ylabel = 1.5, mgp = mgp, y.rev=TRUE, plot.line=FALSE, plot.poly=TRUE, plot.bar=FALSE, col.poly=p.col, scale.percent=TRUE, xSpace=0.01, x.pc.lab=TRUE, x.pc.omit0=TRUE, las=2, xRight = 0.98, #right margin xLeft = 0.13, #left margin with space for 2nd axis yTop = 0.8, #top margin yBottom = 0.1, #bottom margin clust = clust )

addClustZone(pol.plot, clust = clust, nZone = 5)

if(plot_to_svg==1) { dev.off() }

print(".")

}

if(plot_groups==1) { print("Groups ...")

if(plot_to_svg==1) { svg(filename=outfilename2, width=8, height=10, pointsize=16) }

names(groupdatas1)<-"group" names(groupnames1)<-"groupnames"

#stop(-1)

agelen1<-nrow(ages1) groupslen1<-length(groupnames1)

print(agelen1) print(groupslen1)

ages20<-as.vector(ages1$age) ages21<-rep(ages20,groupslen1) ages22<- (matrix(ages21, nrow = groupslen1, byrow = TRUE)) ages2<-as.vector(ages22)

groups20<-as.matrix(groupdatas1) groups21<-t(groups20) #groups22<-pracma::fliplr(groups21) #groups22<-pracma::flipud(groups21)

groups22<-groups21 groups2<-as.vector(groups22)

groupnames20<-as.vector(t(groupnames1)) groupnames21<-rep(groupnames20,agelen1)

groupnames2<-as.vector(as.matrix(groupnames21))

test <- data.frame(age=ages2,pollen=groups2, type=groupnames2)

str(test)

colors1<- rev(c("green","orange","red", "yellow", "violet"))

#ggplot(test, aes(fill=type, y=pollen, x=age) )+ #geom_area()

# stacked area chart gee1<-ggplot(test, aes(fill=type, y=pollen, x=age) ) + ggtitle(sitename1)+ #theme_nothing()+ #geom_area(position="fill", stat="identity")+ geom_area()+

theme(legend.position=c(.9,.75))+ # geom_area()+ #geom_text(aes(y = type, label = pollen, group =type), color = "white") + scale_color_manual(values = colors1 )+ scale_fill_manual(values = colors1 )+ scale_x_reverse()+ coord_flip()

plot(gee1)

if(plot_to_svg==1) { dev.off() }

print(".")

}

1. print (poldatas1)

1. print(in1[loc1])

1. in1