File:Berelyekh river, indigirka lowland pollen r 1.svg

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Original file(SVG file, nominally 1,440 × 900 pixels, file size: 208 KB)

Captions

Captions

Pollen diagram of Berelyekh river, Indigirka lowland, Northeast Siberia, Russia

Summary[edit]

Description
English: Pollen diagram of Berelyekh river, Indigirka lowland, Northeast Siberia, Russia
Date
Source Own work
Author Merikanto
SVG development
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This diagram was created with an unknown SVG tool.

This image is based on pollen data from Neotoma.

    1. some kind of neotoma pollen diagram by dataset number
    2. equal with columns,columns represent percent from maximum of earch pollen species
    3. 24.20,2021 v 0000.0000
    4. original script is
    5. https://quantpalaeo.wordpress.com/2018/05/18/statigraphic-diagrams-with-ggplot/

library("neotoma") library("tidyverse")

  1. get dataset list
  2. pollen_sites <- get_dataset(datasettype = "pollen", x = 253)
    1. berelekh middle weichselian
    1. neotoma dataset id of Berelekh longest sequence

dataset_number=3063 sitename1<-'Berelyekh River, Indigirka Lowland'

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

pollen_sites <- get_dataset(datasettype = "pollen", x = dataset_number)


  1. download_data

pollen_data <- get_download(pollen_sites) pollen_data <- pollen_data1

  1. ecological.group = factor(ecological.group, levels = c("TRSH", "UPHE", "VACR","AQVP", "AQBR","ALGA")),
  2. ecological.group = factor(ecological.group, levels = c("TRSH","UPHE","AQVP","VACR","AQBR","FUNGI","ALGA","FUNG","AMOE","TARD")),

wanted <- c("TRSH", "UPHE", "VACR", "AQBR", "AQVP", "TARD", "ALGA")

thin_pollen <- bind_cols( counts(pollen_data), ages(pollen_data) %>% select(depth, age, age.type) ) %>% gather(key = taxon, value = count, -depth, -age, -age.type) %>% left_join(pollen_data$taxon.list, c("taxon" = "taxon.name")) %>% filter(ecological.group %in% wanted) %>% group_by(depth) %>% mutate(percent = count / sum(count) * 100)

svg(filename=outfilename1, width=16, height=10, pointsize=16)

thin_pollen %>% mutate(taxon = factor(taxon, levels = unique(taxon[order(ecological.group)]))) %>% group_by(taxon) %>% filter(max(percent) >= 3, sum(percent > 0) >= 3) %>% ggplot(aes(x = age, y = percent, fill = ecological.group)) + ggtitle(sitename1)+ geom_area(aes(y = percent * 10), alpha = 0.3, show.legend = FALSE) + geom_area(show.legend = FALSE) + coord_flip(ylim = c(0, max(thin_pollen$percent))) + scale_x_reverse(expand = c(0.02, 0)) + scale_y_continuous(breaks = scales::pretty_breaks(n = 2)) + facet_wrap(~ taxon, nrow = 1) + labs(x = expression(Age~^{14}*C~BP), y = "Percent", fill = "Group") + theme_grey(base_size = 11)+ theme(strip.text.x = element_text(angle = 90, size = 11, hjust = 0), panel.spacing = unit(x = 1, units = "pt"), axis.text.x = element_text(size = 11), axis.text.y = element_text(size = 11), axis.title.x = element_text(size = 16), axis.title.y = element_text(size = 16), title=element_text(size = 22),

)

dev.off()

print(".")

Licensing[edit]

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Date/TimeThumbnailDimensionsUserComment
current15:18, 24 October 2021Thumbnail for version as of 15:18, 24 October 20211,440 × 900 (208 KB)Merikanto (talk | contribs)Uploaded own work with UploadWizard

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