Phytoplankton dynamics
Jens Daniel Müller
18 February, 2021
Last updated: 2021-02-18
Checks: 7 0
Knit directory: BloomSail/
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library(tidyverse)1 Scope of this script
- Read and plot phytoplankton data
2 Phytoplankton cell counts
2.1 Data preparation
# read file
tp <- read_csv(
here::here("data/intermediate/_summarized_data_files",
"tp.csv"),
col_types = cols(ID = col_character())
)
# read cruise dates
cruise_dates <-
read_csv(
here::here(
"data/intermediate/_summarized_data_files",
"cruise_date.csv"
),
col_types = cols(ID = col_character())
)
# filter relevant data
tp <- tp %>%
filter(
station %in% parameters$stations_in_phytoplankton,
class == parameters$class_in_phytoplankton,
Species != "Nodulariadead"
) %>%
mutate(ID = if_else(ID == "180722", "180723", ID))
# calculate mean total phytoplankton biomass in different water depth intervals
tp <- tp %>%
mutate(dep_grid = cut(
dep,
breaks = c(-1, parameters$surface_dep, parameters$max_dep),
labels = c("0-6", "6-25")
)) %>%
drop_na()
# calculate mean biomass in depth interval
tp_ID_grid <- tp %>%
group_by(ID, dep_grid, Species) %>%
summarise(value = mean(value, na.rm = TRUE)) %>%
ungroup()
# join with cruise dates
tp_ID_grid <- full_join(cruise_dates, tp_ID_grid)2.2 Time series plot
tp_ID_grid %>%
filter(Species != "total") %>%
ggplot(aes(date_time_ID, value, col = dep_grid)) +
geom_point() +
geom_line() +
facet_wrap(~ Species, ncol = 1) +
scale_color_brewer(palette = "Set1", name = "Depth (m)") +
scale_x_datetime(breaks = "week", date_labels = "%d %b") +
labs(y = expression(Biomass ~ (mg~m^-3))) +
theme(axis.title.x = element_blank())
ggsave(
here::here(
"output/Plots/Figures_publication/appendix",
"Fig_B2.pdf"
),
width = 140,
height = 90,
dpi = 300,
units = "mm"
)
ggsave(
here::here(
"output/Plots/Figures_publication/appendix",
"Fig_B2.png"
),
width = 140,
height = 90,
dpi = 300,
units = "mm"
)
sessionInfo()R version 4.0.3 (2020-10-10)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 18363)
Matrix products: default
locale:
[1] LC_COLLATE=English_Germany.1252 LC_CTYPE=English_Germany.1252
[3] LC_MONETARY=English_Germany.1252 LC_NUMERIC=C
[5] LC_TIME=English_Germany.1252
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] forcats_0.5.0 stringr_1.4.0 dplyr_1.0.2 purrr_0.3.4
[5] readr_1.4.0 tidyr_1.1.2 tibble_3.0.4 ggplot2_3.3.3
[9] tidyverse_1.3.0 workflowr_1.6.2
loaded via a namespace (and not attached):
[1] tidyselect_1.1.0 xfun_0.19 haven_2.3.1 colorspace_2.0-0
[5] vctrs_0.3.6 generics_0.1.0 htmltools_0.5.0 yaml_2.2.1
[9] rlang_0.4.10 later_1.1.0.1 pillar_1.4.7 withr_2.3.0
[13] glue_1.4.2 DBI_1.1.0 RColorBrewer_1.1-2 dbplyr_2.0.0
[17] modelr_0.1.8 readxl_1.3.1 lifecycle_0.2.0 munsell_0.5.0
[21] gtable_0.3.0 cellranger_1.1.0 rvest_0.3.6 evaluate_0.14
[25] labeling_0.4.2 knitr_1.30 ps_1.5.0 httpuv_1.5.4
[29] fansi_0.4.1 broom_0.7.3 Rcpp_1.0.5 promises_1.1.1
[33] backports_1.2.1 scales_1.1.1 jsonlite_1.7.2 farver_2.0.3
[37] fs_1.5.0 hms_0.5.3 digest_0.6.27 stringi_1.5.3
[41] rprojroot_2.0.2 grid_4.0.3 here_1.0.1 cli_2.2.0
[45] tools_4.0.3 magrittr_2.0.1 crayon_1.3.4 whisker_0.4
[49] pkgconfig_2.0.3 ellipsis_0.3.1 xml2_1.3.2 reprex_0.3.0
[53] lubridate_1.7.9.2 assertthat_0.2.1 rmarkdown_2.6 httr_1.4.2
[57] rstudioapi_0.13 R6_2.5.0 git2r_0.27.1 compiler_4.0.3