\\n\\t\\t\\t| \\n\\t\\t\\t Bin_Fluxes<\/p>\\n\\t\\t\\t<\/td>\\n\\t\\t\\t | \\n\\t\\t\\t ind/m2/day<\/p>\\n\\t\\t\\t<\/td>\\n\\t\\t<\/tr>\\n\\t<\/tbody>\\n<\/table>\\n\\n <\/p>\\n\\n For more details about the FORCIS database column description, please check the data descriptor paper Chaabane et al. (2023) (https://doi.org/10.1038/s41597-023-02264-2).<\/strong><\/p>\\n\\nThe database is kept open for any new entries and the updated version will be released in csv format. The labels of updated versions of the released “.csv” files will contain the date of their publication and versioning number.<\/p>\" #> #> $access_right #> [1] \"open\" #> #> $creators #> $creators[[1]] #> name affiliation #> 1 Chaabane, Sonia CEREGE, France and Max Planck, Germany #> 2 de Garidel, Thibault CEREGE, France #> 3 Giraud, Xavier CEREGE, France #> 4 Schiebel, Ralf Max Planck, Germany #> 5 Beaugrand, Gregory LOG, France #> 6 Brummer, Geert-Jan NIOZ, Netherlands #> 7 Casajus, Nicolas FRB CESAB #> 8 Greco, Mattia Polish Academy of Sciences, Poland #> 9 Grigoratou, Maria Mercator Ocean International, France #> 10 Howa, Hélène LPG-BIAF, France #> 11 Jonkers, Lukas MARUM, Germany #> 12 Kucera, Michal MARUM, Germany #> 13 Kuroyanagi, Azumi Tohoku Univ., Japan #> 14 Meilland, Julie MARUM, Germany #> 15 Monteiro, Fanny BRIDGE, UK #> 16 Mortyn, Graham ICTA UAB, Spain #> 17 Almogi-Labin Ahuva #> 18 Asahi Hirofumi #> 19 Avnaim-Katav Simona #> 20 Bassinot Franck #> 21 Davis Catherine V. #> 22 Field David B. #> 23 Hernandez-Almeida Ivan #> 24 Herut Barak #> 25 Hosie Graham #> 26 Howard Will #> 27 Jentzen Anna #> 28 Johns David G. #> 29 Keigwin Lloyd #> 30 Kitchener John #> 31 Kohfeld Karen E. #> 32 Lessa Douglas V.O. #> 33 Manno Clara #> 34 Marchant Margarita #> 35 Ofstad Siri #> 36 Ortiz Joseph D. #> 37 Post Alexandra #> 38 Rigual-Hernandez Andres #> 39 Rillo Marina C. #> 40 Robinson Karen #> 41 Sagawa Takuya #> 42 Sierro Francisco #> 43 Takahashi Kunio T. #> 44 Torfstein Adi #> 45 Venancio Igor #> 46 Yamasaki Makoto #> 47 Ziveri Patrizia #> orcid #> 1 0000-0002-4653-8610 #> 2 0000-0001-8983-9571 #> 3 0000-0002-6252-7647 #> 4 0000-0001-5067-8176 #> 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 #> #> #> $keywords #> $keywords[[1]] #> [1] \"Planktonic Foraminifera\" \"FORCIS database\" #> [3] \"Biodiversity\" #> #> #> $version #> [1] \"10\" #> #> $resource_type #> [1] \"dataset\" #> #> $license #> id #> 7 cc-by-4.0 #> #> $files #> id key size #> 1 1c00f40e-85d4-4e39-99eb-30411aace76e iho_oceans_boundaries.rds 9198965 #> 2 e299ff1a-71f9-426e-9762-059e410b0c60 FORCIS_cpr_north_11072024.csv 67556549 #> 3 26bf5117-9215-42a6-b53f-f4c36d39fa39 FORCIS_data_template.xlsx 357853 #> 4 07439fa9-ec45-44ca-8c1d-b57b1f45f371 FORCIS_taxonomy_levels.xlsx 24998 #> 5 70c5a9c8-4ff4-49bd-b1c7-f72a8e8e6c2d FORCIS_net_11072024.csv 27189945 #> 6 3d3c0c0b-4635-4f51-a3c4-ca7090312277 FORCIS_cpr_south_11072024.csv 64583224 #> 7 bfb3f092-e40c-499f-b14e-8d6f62295f89 FORCIS_pump_11072024.csv 649676 #> 8 08699afd-f95e-411b-b956-af10ef25a5a0 FORCIS_trap_11072024.csv 13270806 #> checksum #> 1 md5:ff8d2f16650ef1f0cdcb4c3986112648 #> 2 md5:a32bbb863fe795cfcb953ca8928fd9c8 #> 3 md5:ef3c3d67f1824c026fe6fb36aef0b56b #> 4 md5:e12a45e2d34def4c1642353597a04bf8 #> 5 md5:18be71f701075318d7b0a0782d1effc7 #> 6 md5:c9e410a749e513c2023780990fc9169e #> 7 md5:9bee5c30a35dacb623dc7ac4ff564117 #> 8 md5:76bac6d2c85f699da059bfd48334baf4 #> self #> 1 https://zenodo.org/api/records/12724286/files/iho_oceans_boundaries.rds/content #> 2 https://zenodo.org/api/records/12724286/files/FORCIS_cpr_north_11072024.csv/content #> 3 https://zenodo.org/api/records/12724286/files/FORCIS_data_template.xlsx/content #> 4 https://zenodo.org/api/records/12724286/files/FORCIS_taxonomy_levels.xlsx/content #> 5 https://zenodo.org/api/records/12724286/files/FORCIS_net_11072024.csv/content #> 6 https://zenodo.org/api/records/12724286/files/FORCIS_cpr_south_11072024.csv/content #> 7 https://zenodo.org/api/records/12724286/files/FORCIS_pump_11072024.csv/content #> 8 https://zenodo.org/api/records/12724286/files/FORCIS_trap_11072024.csv/content #>"},{"path":"https://frbcesab.github.io/forcis/reference/ggmap_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Map the spatial distribution of FORCIS data — ggmap_data","title":"Map the spatial distribution of FORCIS data — ggmap_data","text":"Maps spatial distribution FORCIS data.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/ggmap_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Map the spatial distribution of FORCIS data — ggmap_data","text":"","code":"ggmap_data(data, col = \"red\", ...)"},{"path":"https://frbcesab.github.io/forcis/reference/ggmap_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Map the spatial distribution of FORCIS data — ggmap_data","text":"data data.frame. One obtained read_*_data() functions. col character length 1. color data map. ... graphical parameters passed geom_sf().","code":""},{"path":"https://frbcesab.github.io/forcis/reference/ggmap_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Map the spatial distribution of FORCIS data — ggmap_data","text":"ggplot object.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/ggmap_data.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Map the spatial distribution of FORCIS data — ggmap_data","text":"","code":"# Attach the package ---- library(\"forcis\") # Import example dataset ---- file_name <- system.file(file.path(\"extdata\", \"FORCIS_net_sample.csv\"), package = \"forcis\") net_data <- read.table(file_name, dec = \".\", sep = \";\") # Add 'data_type' column ---- net_data$\"data_type\" <- \"Net\" # Map data (default) ---- ggmap_data(net_data) # Map data ---- ggmap_data(net_data, col = \"black\", fill = \"red\", shape = 21, size = 2)"},{"path":"https://frbcesab.github.io/forcis/reference/plot_record_by_depth.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot sample records by depth of collection — plot_record_by_depth","title":"Plot sample records by depth of collection — plot_record_by_depth","text":"function produces barplot FORCIS sample records depth.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/plot_record_by_depth.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot sample records by depth of collection — plot_record_by_depth","text":"","code":"plot_record_by_depth(data)"},{"path":"https://frbcesab.github.io/forcis/reference/plot_record_by_depth.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot sample records by depth of collection — plot_record_by_depth","text":"data data.frame, .e. FORCIS dataset.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/plot_record_by_depth.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot sample records by depth of collection — plot_record_by_depth","text":"ggplot object.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/plot_record_by_depth.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot sample records by depth of collection — plot_record_by_depth","text":"","code":"# Attach the package ---- library(\"forcis\") # Import example dataset ---- file_name <- system.file(file.path(\"extdata\", \"FORCIS_net_sample.csv\"), package = \"forcis\") net_data <- read.table(file_name, dec = \".\", sep = \";\") # Add 'data_type' column ---- net_data$\"data_type\" <- \"Net\" # Plot data by year (example dataset) ---- plot_record_by_depth(net_data) #> Warning: There was 1 warning in `mutate()`. #> ℹ In argument: `upper_lim = as.numeric(gsub(\"-.*\", \"\", #> .data$sampling_interval))`. #> Caused by warning: #> ! NAs introduced by coercion"},{"path":"https://frbcesab.github.io/forcis/reference/plot_record_by_month.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot sample records by month — plot_record_by_month","title":"Plot sample records by month — plot_record_by_month","text":"function produces barplot FORCIS sample records month.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/plot_record_by_month.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot sample records by month — plot_record_by_month","text":"","code":"plot_record_by_month(data)"},{"path":"https://frbcesab.github.io/forcis/reference/plot_record_by_month.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot sample records by month — plot_record_by_month","text":"data data.frame, .e. FORCIS dataset.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/plot_record_by_month.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot sample records by month — plot_record_by_month","text":"ggplot object.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/plot_record_by_month.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot sample records by month — plot_record_by_month","text":"","code":"# Attach the package ---- library(\"forcis\") # Import example dataset ---- file_name <- system.file(file.path(\"extdata\", \"FORCIS_net_sample.csv\"), package = \"forcis\") net_data <- read.table(file_name, dec = \".\", sep = \";\") # Add 'data_type' column ---- net_data$\"data_type\" <- \"Net\" # Plot data by year (example dataset) ---- plot_record_by_month(net_data)"},{"path":"https://frbcesab.github.io/forcis/reference/plot_record_by_season.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot sample records by season — plot_record_by_season","title":"Plot sample records by season — plot_record_by_season","text":"function produces barplot FORCIS sample records season.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/plot_record_by_season.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot sample records by season — plot_record_by_season","text":"","code":"plot_record_by_season(data)"},{"path":"https://frbcesab.github.io/forcis/reference/plot_record_by_season.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot sample records by season — plot_record_by_season","text":"data data.frame, .e. FORCIS dataset.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/plot_record_by_season.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot sample records by season — plot_record_by_season","text":"ggplot object.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/plot_record_by_season.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot sample records by season — plot_record_by_season","text":"","code":"# Attach the package ---- library(\"forcis\") # Import example dataset ---- file_name <- system.file(file.path(\"extdata\", \"FORCIS_net_sample.csv\"), package = \"forcis\") net_data <- read.table(file_name, dec = \".\", sep = \";\") # Add 'data_type' column ---- net_data$\"data_type\" <- \"Net\" # Plot data by year (example dataset) ---- plot_record_by_season(net_data)"},{"path":"https://frbcesab.github.io/forcis/reference/plot_record_by_year.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot sample records by year — plot_record_by_year","title":"Plot sample records by year — plot_record_by_year","text":"function produces barplot FORCIS sample records year.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/plot_record_by_year.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot sample records by year — plot_record_by_year","text":"","code":"plot_record_by_year(data)"},{"path":"https://frbcesab.github.io/forcis/reference/plot_record_by_year.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot sample records by year — plot_record_by_year","text":"data data.frame, .e. FORCIS dataset.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/plot_record_by_year.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot sample records by year — plot_record_by_year","text":"ggplot object.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/plot_record_by_year.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot sample records by year — plot_record_by_year","text":"","code":"# Attach the package ---- library(\"forcis\") # Import example dataset ---- file_name <- system.file(file.path(\"extdata\", \"FORCIS_net_sample.csv\"), package = \"forcis\") net_data <- read.table(file_name, dec = \".\", sep = \";\") # Add 'data_type' column ---- net_data$\"data_type\" <- \"Net\" # Plot data by year (example dataset) ---- plot_record_by_year(net_data)"},{"path":"https://frbcesab.github.io/forcis/reference/read_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Read FORCIS data — read_cpr_north_data","title":"Read FORCIS data — read_cpr_north_data","text":"functions read one specific csv file FORCIS database (see ) stored folder path. function download_forcis_db() must used first store locally database.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/read_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read FORCIS data — read_cpr_north_data","text":"","code":"read_cpr_north_data( path = \".\", version = options()$forcis_version, check_for_update = options()$check_for_update ) read_cpr_south_data( path = \".\", version = options()$forcis_version, check_for_update = options()$check_for_update ) read_plankton_nets_data( path = \".\", version = options()$forcis_version, check_for_update = options()$check_for_update ) read_pump_data( path = \".\", version = options()$forcis_version, check_for_update = options()$check_for_update ) read_sediment_trap_data( path = \".\", version = options()$forcis_version, check_for_update = options()$check_for_update )"},{"path":"https://frbcesab.github.io/forcis/reference/read_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read FORCIS data — read_cpr_north_data","text":"path character length 1. folder FORCIS database saved. version character length 1. version number (two numbers, e.g. 08 instead 8) FORCIS database use. Default latest version. Note argument can handle global option forcis_version. example, user calls options(forcis_version = \"07\"), version 07 used default current R session. Note recommended use latest version database. check_for_update logical. TRUE (default) function check newer version FORCIS database available Zenodo print informative message. Note argument can handle global option check_for_update. example, user calls options(check_for_update = FALSE), message download latest version disabled current R session.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/read_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read FORCIS data — read_cpr_north_data","text":"data.frame. See https://zenodo.org/doi/10.5281/zenodo.7390791 preview datasets.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/read_data.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Read FORCIS data — read_cpr_north_data","text":"read_plankton_nets_data() reads FORCIS plankton nets data read_pump_data() reads FORCIS pump data read_cpr_north_data() reads FORCIS CPR North data read_cpr_south_data() reads FORCIS CPR South data read_sediment_trap_data() reads FORCIS sediment traps data","code":""},{"path":[]},{"path":"https://frbcesab.github.io/forcis/reference/read_data.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read FORCIS data — read_cpr_north_data","text":"","code":"if (FALSE) { # \\dontrun{ # Attach the package ---- library(\"forcis\") # Folder in which the database will be saved ---- path_to_save_db <- \"data\" # Download the database ---- download_forcis_db(path = path_to_save_db) # Import plankton nets data ---- plankton_nets_data <- read_plankton_nets_data(path = path_to_save_db) } # }"},{"path":"https://frbcesab.github.io/forcis/reference/reshape_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Reshape and simplify FORCIS data — reshape_data","title":"Reshape and simplify FORCIS data — reshape_data","text":"Reshapes FORCIS data pivoting species columns two columns: taxa (taxon names) counts (taxon abundances). converts wider data.frame long format.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/reshape_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Reshape and simplify FORCIS data — reshape_data","text":"","code":"reshape_data(data)"},{"path":"https://frbcesab.github.io/forcis/reference/reshape_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Reshape and simplify FORCIS data — reshape_data","text":"data data.frame, .e. FORCIS dataset, except CPR North data.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/reshape_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Reshape and simplify FORCIS data — reshape_data","text":"data.frame reshaped long format.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/reshape_data.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Reshape and simplify FORCIS data — reshape_data","text":"","code":"# Attach the package ---- library(\"forcis\") # Import example dataset ---- file_name <- system.file(file.path(\"extdata\", \"FORCIS_net_sample.csv\"), package = \"forcis\") net_data <- read.table(file_name, dec = \".\", sep = \";\") # Add 'data_type' column ---- net_data$\"data_type\" <- \"Net\" # Dimensions of the data.frame ---- dim(net_data) #> [1] 2451 77 # Reshape data ---- net_data <- reshape_data(net_data) # Dimensions of the data.frame ---- dim(net_data) #> [1] 137256 23 # Column names ---- colnames(net_data) #> [1] \"data_type\" #> [2] \"cruise_id\" #> [3] \"profile_id\" #> [4] \"sample_id\" #> [5] \"sample_min_depth\" #> [6] \"sample_max_depth\" #> [7] \"profile_depth_min\" #> [8] \"profile_depth_max\" #> [9] \"profile_date_time\" #> [10] \"cast_net_op_m2\" #> [11] \"subsample_id\" #> [12] \"sample_segment_length\" #> [13] \"subsample_count_type\" #> [14] \"subsample_size_fraction_min\" #> [15] \"subsample_size_fraction_max\" #> [16] \"site_lat_start_decimal\" #> [17] \"site_lon_start_decimal\" #> [18] \"sample_volume_filtered\" #> [19] \"subsample_all_shells_present_were_counted\" #> [20] \"total_of_forams_counted_ind\" #> [21] \"sampling_device_type\" #> [22] \"taxa\" #> [23] \"counts\""},{"path":"https://frbcesab.github.io/forcis/reference/select_columns.html","id":null,"dir":"Reference","previous_headings":"","what":"Select columns in FORCIS data — select_columns","title":"Select columns in FORCIS data — select_columns","text":"Selects columns FORCIS data. FORCIS data contains 100 columns, function can used lighten data.frame easily handle speed computations.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/select_columns.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Select columns in FORCIS data — select_columns","text":"","code":"select_columns(data, cols = NULL)"},{"path":"https://frbcesab.github.io/forcis/reference/select_columns.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Select columns in FORCIS data — select_columns","text":"data data.frame. One obtained read_*_data() functions. cols character vector column names keep addition required ones (see get_required_columns()) taxa columns. Can NULL (default).","code":""},{"path":"https://frbcesab.github.io/forcis/reference/select_columns.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Select columns in FORCIS data — select_columns","text":"data.frame.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/select_columns.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Select columns in FORCIS data — select_columns","text":"","code":"# Attach the package ---- library(\"forcis\") # Import example dataset ---- file_name <- system.file(file.path(\"extdata\", \"FORCIS_net_sample.csv\"), package = \"forcis\") net_data <- read.table(file_name, dec = \".\", sep = \";\") # Add 'data_type' column ---- net_data$\"data_type\" <- \"Net\" # Dimensions of the data.frame ---- dim(net_data) #> [1] 2451 77 # Select a taxonomy ---- net_data <- select_taxonomy(net_data, taxonomy = \"VT\") # Dimensions of the data.frame ---- dim(net_data) #> [1] 2451 77 # Select only required columns (and taxa) ---- net_data <- select_columns(net_data) # Dimensions of the data.frame ---- dim(net_data) #> [1] 2451 77"},{"path":"https://frbcesab.github.io/forcis/reference/select_taxonomy.html","id":null,"dir":"Reference","previous_headings":"","what":"Select a taxonomy in FORCIS data — select_taxonomy","title":"Select a taxonomy in FORCIS data — select_taxonomy","text":"Selects taxonomy FORCIS data. FORCIS database provides three different taxonomies: \"LT\" (lumped taxonomy), \"VT\" (validated taxonomy) \"OT\" (original taxonomy). See https://doi.org/10.1038/s41597-023-02264-2 information.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/select_taxonomy.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Select a taxonomy in FORCIS data — select_taxonomy","text":"","code":"select_taxonomy(data, taxonomy)"},{"path":"https://frbcesab.github.io/forcis/reference/select_taxonomy.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Select a taxonomy in FORCIS data — select_taxonomy","text":"data data.frame. One obtained read_*_data() functions. taxonomy character length 1. One among \"LT\", \"VT\", \"OT\".","code":""},{"path":"https://frbcesab.github.io/forcis/reference/select_taxonomy.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Select a taxonomy in FORCIS data — select_taxonomy","text":"data.frame.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/select_taxonomy.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Select a taxonomy in FORCIS data — select_taxonomy","text":"","code":"# Attach the package ---- library(\"forcis\") # Import example dataset ---- file_name <- system.file(file.path(\"extdata\", \"FORCIS_net_sample.csv\"), package = \"forcis\") net_data <- read.table(file_name, dec = \".\", sep = \";\") # Add 'data_type' column ---- net_data$\"data_type\" <- \"Net\" # Dimensions of the data.frame ---- dim(net_data) #> [1] 2451 77 # Select a taxonomy ---- net_data <- select_taxonomy(net_data, taxonomy = \"VT\") # Dimensions of the data.frame ---- dim(net_data) #> [1] 2451 77"},{"path":[]}]
+[{"path":[]},{"path":"https://frbcesab.github.io/forcis/CODE_OF_CONDUCT.html","id":"our-pledge","dir":"","previous_headings":"","what":"Our Pledge","title":"Contributor Covenant Code of Conduct","text":"members, contributors, leaders pledge make participation community harassment-free experience everyone, regardless age, body size, visible invisible disability, ethnicity, sex characteristics, gender identity expression, level experience, education, socio-economic status, nationality, personal appearance, race, caste, color, religion, sexual identity orientation. pledge act interact ways contribute open, welcoming, diverse, inclusive, healthy community.","code":""},{"path":"https://frbcesab.github.io/forcis/CODE_OF_CONDUCT.html","id":"our-standards","dir":"","previous_headings":"","what":"Our Standards","title":"Contributor Covenant Code of Conduct","text":"Examples behavior contributes positive environment community include: Demonstrating empathy kindness toward people respectful differing opinions, viewpoints, experiences Giving gracefully accepting constructive feedback Accepting responsibility apologizing affected mistakes, learning experience Focusing best just us individuals, overall community Examples unacceptable behavior include: use sexualized language imagery, sexual attention advances kind Trolling, insulting derogatory comments, personal political attacks Public private harassment Publishing others’ private information, physical email address, without explicit permission conduct reasonably considered inappropriate professional setting","code":""},{"path":"https://frbcesab.github.io/forcis/CODE_OF_CONDUCT.html","id":"enforcement-responsibilities","dir":"","previous_headings":"","what":"Enforcement Responsibilities","title":"Contributor Covenant Code of Conduct","text":"Community leaders responsible clarifying enforcing standards acceptable behavior take appropriate fair corrective action response behavior deem inappropriate, threatening, offensive, harmful. Community leaders right responsibility remove, edit, reject comments, commits, code, wiki edits, issues, contributions aligned Code Conduct, communicate reasons moderation decisions appropriate.","code":""},{"path":"https://frbcesab.github.io/forcis/CODE_OF_CONDUCT.html","id":"scope","dir":"","previous_headings":"","what":"Scope","title":"Contributor Covenant Code of Conduct","text":"Code Conduct applies within community spaces, also applies individual officially representing community public spaces. Examples representing community include using official e-mail address, posting via official social media account, acting appointed representative online offline event.","code":""},{"path":"https://frbcesab.github.io/forcis/CODE_OF_CONDUCT.html","id":"enforcement","dir":"","previous_headings":"","what":"Enforcement","title":"Contributor Covenant Code of Conduct","text":"Instances abusive, harassing, otherwise unacceptable behavior may reported community leaders responsible enforcement nicolas.casajus@fondationbiodiversite.fr. complaints reviewed investigated promptly fairly. community leaders obligated respect privacy security reporter incident.","code":""},{"path":"https://frbcesab.github.io/forcis/CODE_OF_CONDUCT.html","id":"enforcement-guidelines","dir":"","previous_headings":"","what":"Enforcement Guidelines","title":"Contributor Covenant Code of Conduct","text":"Community leaders follow Community Impact Guidelines determining consequences action deem violation Code Conduct:","code":""},{"path":"https://frbcesab.github.io/forcis/CODE_OF_CONDUCT.html","id":"id_1-correction","dir":"","previous_headings":"Enforcement Guidelines","what":"1. Correction","title":"Contributor Covenant Code of Conduct","text":"Community Impact: Use inappropriate language behavior deemed unprofessional unwelcome community. Consequence: private, written warning community leaders, providing clarity around nature violation explanation behavior inappropriate. public apology may requested.","code":""},{"path":"https://frbcesab.github.io/forcis/CODE_OF_CONDUCT.html","id":"id_2-warning","dir":"","previous_headings":"Enforcement Guidelines","what":"2. Warning","title":"Contributor Covenant Code of Conduct","text":"Community Impact: violation single incident series actions. Consequence: warning consequences continued behavior. interaction people involved, including unsolicited interaction enforcing Code Conduct, specified period time. includes avoiding interactions community spaces well external channels like social media. Violating terms may lead temporary permanent ban.","code":""},{"path":"https://frbcesab.github.io/forcis/CODE_OF_CONDUCT.html","id":"id_3-temporary-ban","dir":"","previous_headings":"Enforcement Guidelines","what":"3. Temporary Ban","title":"Contributor Covenant Code of Conduct","text":"Community Impact: serious violation community standards, including sustained inappropriate behavior. Consequence: temporary ban sort interaction public communication community specified period time. public private interaction people involved, including unsolicited interaction enforcing Code Conduct, allowed period. Violating terms may lead permanent ban.","code":""},{"path":"https://frbcesab.github.io/forcis/CODE_OF_CONDUCT.html","id":"id_4-permanent-ban","dir":"","previous_headings":"Enforcement Guidelines","what":"4. Permanent Ban","title":"Contributor Covenant Code of Conduct","text":"Community Impact: Demonstrating pattern violation community standards, including sustained inappropriate behavior, harassment individual, aggression toward disparagement classes individuals. Consequence: permanent ban sort public interaction within community.","code":""},{"path":"https://frbcesab.github.io/forcis/CODE_OF_CONDUCT.html","id":"attribution","dir":"","previous_headings":"","what":"Attribution","title":"Contributor Covenant Code of Conduct","text":"Code Conduct adapted Contributor Covenant, version 2.1, available https://www.contributor-covenant.org/version/2/1/code_of_conduct.html. Community Impact Guidelines inspired Mozilla’s code conduct enforcement ladder. answers common questions code conduct, see FAQ https://www.contributor-covenant.org/faq. Translations available https://www.contributor-covenant.org/translations.","code":""},{"path":"https://frbcesab.github.io/forcis/CONTRIBUTING.html","id":null,"dir":"","previous_headings":"","what":"Contributing to forcis","title":"Contributing to forcis","text":"First , thanks taking time contribute forcis! types contributions encouraged valued. See Table contents different ways help details project handles . Please make sure read relevant section making contribution. make lot easier us maintainers smooth experience involved.","code":""},{"path":"https://frbcesab.github.io/forcis/CONTRIBUTING.html","id":"table-of-contents","dir":"","previous_headings":"","what":"Table of contents","title":"Contributing to forcis","text":"Code conduct Style guide Commit messages Asking questions Reporting bugs Requesting features Contributing code","code":""},{"path":"https://frbcesab.github.io/forcis/CONTRIBUTING.html","id":"code-of-conduct","dir":"","previous_headings":"","what":"Code of conduct","title":"Contributing to forcis","text":"project released Contributor Code Conduct. participating, expected uphold code. Please report unacceptable behavior nicolas.casajus@fondationbiodiversite.fr.","code":""},{"path":"https://frbcesab.github.io/forcis/CONTRIBUTING.html","id":"style-guide","dir":"","previous_headings":"","what":"Style guide","title":"Contributing to forcis","text":"use Tidyverse style guide writing R code. Functions documented roxygen2 syntax. forcis uses lower_snake_case.","code":""},{"path":"https://frbcesab.github.io/forcis/CONTRIBUTING.html","id":"commit-messages","dir":"","previous_headings":"","what":"Commit messages","title":"Contributing to forcis","text":"want contribute commiting changes, please try use Conventional commits specification.","code":""},{"path":"https://frbcesab.github.io/forcis/CONTRIBUTING.html","id":"asking-questions","dir":"","previous_headings":"","what":"Asking questions","title":"Contributing to forcis","text":"ask question, best search existing Issues might help . case found suitable issue still need clarification, can write question issue. still feel need ask question need clarification, recommend following: Open new Issue. Use template other_issue.md. Provide much context can ’re running . Provide project platform versions (paste output sessionInfo()). take care issue soon possible.","code":""},{"path":[]},{"path":"https://frbcesab.github.io/forcis/CONTRIBUTING.html","id":"before-submitting-a-bug-report","dir":"","previous_headings":"Reporting bugs","what":"Before submitting a bug report","title":"Contributing to forcis","text":"good bug report shouldn’t leave others needing chase information. Therefore, ask investigate carefully, collect information describe issue detail report. Please complete following steps advance help us fix potential bug fast possible. Make sure using latest version forcis. Determine bug really bug error side. see users experienced (potentially already solved) issue , check already bug report existing bug error bug tracker.","code":""},{"path":"https://frbcesab.github.io/forcis/CONTRIBUTING.html","id":"how-do-i-submit-a-bug-report","dir":"","previous_headings":"Reporting bugs","what":"How do I submit a bug report?","title":"Contributing to forcis","text":"use GitHub Issues track bugs errors. run issue project: Open new Issue. Use template bug_report.md. Explain behavior expect actual behavior. Please provide much context possible describe reproduction steps someone else can follow recreate issue . usually includes code reproducible example. take care issue soon possible.","code":""},{"path":[]},{"path":"https://frbcesab.github.io/forcis/CONTRIBUTING.html","id":"before-requesting-a-feature","dir":"","previous_headings":"Requesting features","what":"Before requesting a feature","title":"Contributing to forcis","text":"Make sure using latest version forcis. Read documentation carefully find functionality already covered. Perform search see enhancement already suggested. , add comment existing issue instead opening new one.","code":""},{"path":"https://frbcesab.github.io/forcis/CONTRIBUTING.html","id":"how-do-i-submit-a-feature-request","dir":"","previous_headings":"Requesting features","what":"How do I submit a feature request?","title":"Contributing to forcis","text":"Feature requests tracked GitHub Issues. Open new Issue. Use template feature_request.md. Provide clear descriptive title issue identify suggestion. Provide step--step description suggested enhancement many details possible. Explain enhancement useful forcis users. take care issue soon possible.","code":""},{"path":[]},{"path":"https://frbcesab.github.io/forcis/CONTRIBUTING.html","id":"general-workflow","dir":"","previous_headings":"Contributing code","what":"General workflow","title":"Contributing to forcis","text":"use GitHub flow collaborate project: Fork repository using GitHub interface. Clone fork using git clone fork-url (replace fork-url URL fork). Alternatively, open RStudio IDE create New Project Version Control. Create new branch w/ git checkout -b branch-name (replace branch-name name new branch). Make contribution (see examples). Stage (git add) commit (git commit) changes often necessary Push changes GitHub w/ git push origin branch-name. Submit Pull Request original repo. review PR soon possible.","code":""},{"path":[]},{"path":"https://frbcesab.github.io/forcis/CONTRIBUTING.html","id":"editing-the-readme","dir":"","previous_headings":"Contributing code > Improve documentation","what":"Editing the README","title":"Contributing to forcis","text":"want contribute improving README, please edit README.Rmd (README.md). forget update README.md running:","code":"rmarkdown::render(\"README.Rmd\")"},{"path":"https://frbcesab.github.io/forcis/CONTRIBUTING.html","id":"editing-vignettes","dir":"","previous_headings":"Contributing code > Improve documentation","what":"Editing vignettes","title":"Contributing to forcis","text":"want contribute editing existing vignette, just edit corresponding Rmd file stored vignettes/ folder. want contribute adding new vignette, create new Rmd file vignettes/ folder add following header: use new external dependency, forget add DESCRIPTION file section Suggests (package already listed section Imports). Check integrity package :","code":"--- title: \"Vignette Title\" output: rmarkdown::html_vignette vignette: > %\\VignetteIndexEntry{Vignette Title} %\\VignetteEngine{knitr::rmarkdown} %\\VignetteEncoding{UTF-8} --- devtools::check()"},{"path":"https://frbcesab.github.io/forcis/CONTRIBUTING.html","id":"editing-function-documentation","dir":"","previous_headings":"Contributing code > Improve documentation","what":"Editing function documentation","title":"Contributing to forcis","text":"want contribute improving documentation function, open corresponding file R/ folder edit lines starting #' (roxygen2 syntax). Update documentation (Rd files man/ folder) running: use new external dependency example section, forget add DESCRIPTION file section Imports (package already listed). Check integrity package :","code":"devtools::document() devtools::check()"},{"path":"https://frbcesab.github.io/forcis/CONTRIBUTING.html","id":"fix-bug","dir":"","previous_headings":"Contributing code","what":"Fix bug","title":"Contributing to forcis","text":"want contribute improving code function, open edit corresponding file R/ folder. Check integrity package : forget adapt unit tests function editing corresponding file stored tests/testthat/ folder. use package testthat implement unit tests. Check tests running:","code":"devtools::check() devtools::test()"},{"path":"https://frbcesab.github.io/forcis/CONTRIBUTING.html","id":"new-feature","dir":"","previous_headings":"Contributing code","what":"New feature","title":"Contributing to forcis","text":"want contribute submitting new feature, please follow workflow: Create new R file folder R/. Implement code function. Document function w/ roxygen2 syntax. necessary, add additional dependencies DESCRIPTION file. Update package documentation w/ devtools::document(). Create new R file folder tests/testthat/. Implement unit tests new function. Check integrity package w/ devtools::check(). Thanks contribution!","code":""},{"path":"https://frbcesab.github.io/forcis/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"GNU General Public License","title":"GNU General Public License","text":"Version 2, June 1991Copyright © 1989, 1991 Free Software Foundation, Inc.,51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA Everyone permitted copy distribute verbatim copies license document, changing allowed.","code":""},{"path":"https://frbcesab.github.io/forcis/LICENSE.html","id":"preamble","dir":"","previous_headings":"","what":"Preamble","title":"GNU General Public License","text":"licenses software designed take away freedom share change . contrast, GNU General Public License intended guarantee freedom share change free software–make sure software free users. General Public License applies Free Software Foundation’s software program whose authors commit using . (Free Software Foundation software covered GNU Lesser General Public License instead.) can apply programs, . speak free software, referring freedom, price. General Public Licenses designed make sure freedom distribute copies free software (charge service wish), receive source code can get want , can change software use pieces new free programs; know can things. protect rights, need make restrictions forbid anyone deny rights ask surrender rights. restrictions translate certain responsibilities distribute copies software, modify . example, distribute copies program, whether gratis fee, must give recipients rights . must make sure , , receive can get source code. must show terms know rights. protect rights two steps: (1) copyright software, (2) offer license gives legal permission copy, distribute /modify software. Also, author’s protection , want make certain everyone understands warranty free software. software modified someone else passed , want recipients know original, problems introduced others reflect original authors’ reputations. Finally, free program threatened constantly software patents. wish avoid danger redistributors free program individually obtain patent licenses, effect making program proprietary. prevent , made clear patent must licensed everyone’s free use licensed . precise terms conditions copying, distribution modification follow.","code":""},{"path":"https://frbcesab.github.io/forcis/LICENSE.html","id":"terms-and-conditions-for-copying-distribution-and-modification","dir":"","previous_headings":"","what":"TERMS AND CONDITIONS FOR COPYING, DISTRIBUTION AND MODIFICATION","title":"GNU General Public License","text":"0. License applies program work contains notice placed copyright holder saying may distributed terms General Public License. “Program”, , refers program work, “work based Program” means either Program derivative work copyright law: say, work containing Program portion , either verbatim modifications /translated another language. (Hereinafter, translation included without limitation term “modification”.) licensee addressed “”. Activities copying, distribution modification covered License; outside scope. act running Program restricted, output Program covered contents constitute work based Program (independent made running Program). Whether true depends Program . 1. may copy distribute verbatim copies Program’s source code receive , medium, provided conspicuously appropriately publish copy appropriate copyright notice disclaimer warranty; keep intact notices refer License absence warranty; give recipients Program copy License along Program. may charge fee physical act transferring copy, may option offer warranty protection exchange fee. 2. may modify copy copies Program portion , thus forming work based Program, copy distribute modifications work terms Section 1 , provided also meet conditions: ) must cause modified files carry prominent notices stating changed files date change. b) must cause work distribute publish, whole part contains derived Program part thereof, licensed whole charge third parties terms License. c) modified program normally reads commands interactively run, must cause , started running interactive use ordinary way, print display announcement including appropriate copyright notice notice warranty (else, saying provide warranty) users may redistribute program conditions, telling user view copy License. (Exception: Program interactive normally print announcement, work based Program required print announcement.) requirements apply modified work whole. identifiable sections work derived Program, can reasonably considered independent separate works , License, terms, apply sections distribute separate works. distribute sections part whole work based Program, distribution whole must terms License, whose permissions licensees extend entire whole, thus every part regardless wrote . Thus, intent section claim rights contest rights work written entirely ; rather, intent exercise right control distribution derivative collective works based Program. addition, mere aggregation another work based Program Program (work based Program) volume storage distribution medium bring work scope License. 3. may copy distribute Program (work based , Section 2) object code executable form terms Sections 1 2 provided also one following: ) Accompany complete corresponding machine-readable source code, must distributed terms Sections 1 2 medium customarily used software interchange; , b) Accompany written offer, valid least three years, give third party, charge cost physically performing source distribution, complete machine-readable copy corresponding source code, distributed terms Sections 1 2 medium customarily used software interchange; , c) Accompany information received offer distribute corresponding source code. (alternative allowed noncommercial distribution received program object code executable form offer, accord Subsection b .) source code work means preferred form work making modifications . executable work, complete source code means source code modules contains, plus associated interface definition files, plus scripts used control compilation installation executable. However, special exception, source code distributed need include anything normally distributed (either source binary form) major components (compiler, kernel, ) operating system executable runs, unless component accompanies executable. distribution executable object code made offering access copy designated place, offering equivalent access copy source code place counts distribution source code, even though third parties compelled copy source along object code. 4. may copy, modify, sublicense, distribute Program except expressly provided License. attempt otherwise copy, modify, sublicense distribute Program void, automatically terminate rights License. However, parties received copies, rights, License licenses terminated long parties remain full compliance. 5. required accept License, since signed . However, nothing else grants permission modify distribute Program derivative works. actions prohibited law accept License. Therefore, modifying distributing Program (work based Program), indicate acceptance License , terms conditions copying, distributing modifying Program works based . 6. time redistribute Program (work based Program), recipient automatically receives license original licensor copy, distribute modify Program subject terms conditions. may impose restrictions recipients’ exercise rights granted herein. responsible enforcing compliance third parties License. 7. , consequence court judgment allegation patent infringement reason (limited patent issues), conditions imposed (whether court order, agreement otherwise) contradict conditions License, excuse conditions License. distribute satisfy simultaneously obligations License pertinent obligations, consequence may distribute Program . example, patent license permit royalty-free redistribution Program receive copies directly indirectly , way satisfy License refrain entirely distribution Program. portion section held invalid unenforceable particular circumstance, balance section intended apply section whole intended apply circumstances. purpose section induce infringe patents property right claims contest validity claims; section sole purpose protecting integrity free software distribution system, implemented public license practices. Many people made generous contributions wide range software distributed system reliance consistent application system; author/donor decide willing distribute software system licensee impose choice. section intended make thoroughly clear believed consequence rest License. 8. distribution /use Program restricted certain countries either patents copyrighted interfaces, original copyright holder places Program License may add explicit geographical distribution limitation excluding countries, distribution permitted among countries thus excluded. case, License incorporates limitation written body License. 9. Free Software Foundation may publish revised /new versions General Public License time time. new versions similar spirit present version, may differ detail address new problems concerns. version given distinguishing version number. Program specifies version number License applies “later version”, option following terms conditions either version later version published Free Software Foundation. Program specify version number License, may choose version ever published Free Software Foundation. 10. wish incorporate parts Program free programs whose distribution conditions different, write author ask permission. software copyrighted Free Software Foundation, write Free Software Foundation; sometimes make exceptions . decision guided two goals preserving free status derivatives free software promoting sharing reuse software generally.","code":""},{"path":"https://frbcesab.github.io/forcis/LICENSE.html","id":"no-warranty","dir":"","previous_headings":"","what":"NO WARRANTY","title":"GNU General Public License","text":"11. PROGRAM LICENSED FREE CHARGE, WARRANTY PROGRAM, EXTENT PERMITTED APPLICABLE LAW. EXCEPT OTHERWISE STATED WRITING COPYRIGHT HOLDERS /PARTIES PROVIDE PROGRAM “” WITHOUT WARRANTY KIND, EITHER EXPRESSED IMPLIED, INCLUDING, LIMITED , IMPLIED WARRANTIES MERCHANTABILITY FITNESS PARTICULAR PURPOSE. ENTIRE RISK QUALITY PERFORMANCE PROGRAM . PROGRAM PROVE DEFECTIVE, ASSUME COST NECESSARY SERVICING, REPAIR CORRECTION. 12. EVENT UNLESS REQUIRED APPLICABLE LAW AGREED WRITING COPYRIGHT HOLDER, PARTY MAY MODIFY /REDISTRIBUTE PROGRAM PERMITTED , LIABLE DAMAGES, INCLUDING GENERAL, SPECIAL, INCIDENTAL CONSEQUENTIAL DAMAGES ARISING USE INABILITY USE PROGRAM (INCLUDING LIMITED LOSS DATA DATA RENDERED INACCURATE LOSSES SUSTAINED THIRD PARTIES FAILURE PROGRAM OPERATE PROGRAMS), EVEN HOLDER PARTY ADVISED POSSIBILITY DAMAGES. END TERMS CONDITIONS","code":""},{"path":"https://frbcesab.github.io/forcis/LICENSE.html","id":"how-to-apply-these-terms-to-your-new-programs","dir":"","previous_headings":"","what":"How to Apply These Terms to Your New Programs","title":"GNU General Public License","text":"develop new program, want greatest possible use public, best way achieve make free software everyone can redistribute change terms. , attach following notices program. safest attach start source file effectively convey exclusion warranty; file least “copyright” line pointer full notice found. Also add information contact electronic paper mail. program interactive, make output short notice like starts interactive mode: hypothetical commands show w show c show appropriate parts General Public License. course, commands use may called something show w show c; even mouse-clicks menu items–whatever suits program. also get employer (work programmer) school, , sign “copyright disclaimer” program, necessary. sample; alter names: General Public License permit incorporating program proprietary programs. program subroutine library, may consider useful permit linking proprietary applications library. want , use GNU Lesser General Public License instead License.","code":" Copyright (C) This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA. Gnomovision version 69, Copyright (C) year name of author Gnomovision comes with ABSOLUTELY NO WARRANTY; for details type `show w'. This is free software, and you are welcome to redistribute it under certain conditions; type `show c' for details. Yoyodyne, Inc., hereby disclaims all copyright interest in the program `Gnomovision' (which makes passes at compilers) written by James Hacker. , 1 April 1989 Ty Coon, President of Vice"},{"path":"https://frbcesab.github.io/forcis/articles/data-conversion.html","id":"count-formats","dir":"Articles","previous_headings":"","what":"Count formats","title":"Data conversion","text":"FORCIS database includes counts foraminifera species collected multiple devices. counts reported different formats: Raw abundance: number specimens counted within sampling unit. Number concentration: number specimens per cubic meter. Relative abundance: percentage specimens relative total counted. Fluxes: number specimens per square meter per day. Binned counts: number specimens categorized specific range (minimum maximum) within sampling unit.","code":""},{"path":"https://frbcesab.github.io/forcis/articles/data-conversion.html","id":"conversion-functions","dir":"Articles","previous_headings":"","what":"Conversion functions","title":"Data conversion","text":"functions detailed vignette allow convert counts following formats Raw abundance, Relative abundance Number concentration. NOTE: FORCIS data Sediment traps CPR North supported functions. First, let’s import required package. going , download latest version FORCIS database. vignette use plankton nets data FORCIS database. Let’s import latest release data. NB: vignette, use subset plankton nets data, whole dataset. importing data, initial step involves choosing taxonomic level analyses, (different taxonomic levels described data paper). Let’s use function select_taxonomy() select VT taxonomy (validated taxonomy): data contains counts taxonomic level, can proceed conversion functions: compute_*(). functions accept two arguments: input data aggregate arguments. aggregate = TRUE, function return transformed counts species using sample unit. aggregate = FALSE, re-calculate species’ abundance subsample.","code":"library(forcis) # Create a data/ folder ---- dir.create(\"data\") # Download latest version of the database ---- download_forcis_db(path = \"data\", version = NULL) # Import net data ---- net_data <- read_plankton_nets_data(path = \"data\") # Select taxonomy ---- net_data <- select_taxonomy(net_data, taxonomy = \"VT\")"},{"path":"https://frbcesab.github.io/forcis/articles/data-conversion.html","id":"compute_abundances","dir":"Articles","previous_headings":"Conversion functions","what":"compute_abundances()","title":"Data conversion","text":"function converts counts raw abundances, using sampling metadata sample volume total assemblage counts. calculates raw abundance taxon whose counts reported either relative abundance number concentrations. functions compute_*() output table long-format well message reporting amount data converted missing metadata.","code":"# Convert species counts in raw abundance ---- net_data_raw_ab <- compute_abundances(net_data, aggregate = TRUE) #> Counts from 26 samples could not be converted because of missing volume data #> Relative counts from 24 samples could not be converted because of missing data on total assemblage # Format ---- dim(net_data) #> [1] 2451 77 dim(net_data_raw_ab) #> [1] 39032 16 # Header ---- net_data_raw_ab <- as.data.frame(net_data_raw_ab) head(net_data_raw_ab) #> data_type cruise_id profile_id sample_id sample_min_depth #> 1 Net RinaldoDohrn L20_RinaldoDohrn_10_1 L20_10_1 0 #> 2 Net RinaldoDohrn L20_RinaldoDohrn_10_1 L20_10_1 0 #> 3 Net RinaldoDohrn L20_RinaldoDohrn_10_1 L20_10_1 0 #> 4 Net RinaldoDohrn L20_RinaldoDohrn_10_1 L20_10_1 0 #> 5 Net RinaldoDohrn L20_RinaldoDohrn_10_1 L20_10_1 0 #> 6 Net RinaldoDohrn L20_RinaldoDohrn_10_1 L20_10_1 0 #> sample_max_depth profile_depth_min profile_depth_max profile_date_time #> 1 20 0 300 09/04/1979 #> 2 20 0 300 09/04/1979 #> 3 20 0 300 09/04/1979 #> 4 20 0 300 09/04/1979 #> 5 20 0 300 09/04/1979 #> 6 20 0 300 09/04/1979 #> cast_net_op_m2 sample_segment_length site_lat_start_decimal #> 1 NA NA 40.7 #> 2 NA NA 40.7 #> 3 NA NA 40.7 #> 4 NA NA 40.7 #> 5 NA NA 40.7 #> 6 NA NA 40.7 #> site_lon_start_decimal sample_volume_filtered taxa counts_raw_ab #> 1 15.08 1000 b_digitata_VT 0 #> 2 15.08 1000 b_pumilio_VT 0 #> 3 15.08 1000 b_variabilis_VT 0 #> 4 15.08 1000 c_nitida_VT 0 #> 5 15.08 1000 d_anfracta_VT 0 #> 6 15.08 1000 g_adamsi_VT 0"},{"path":"https://frbcesab.github.io/forcis/articles/data-conversion.html","id":"compute_concentrations","dir":"Articles","previous_headings":"Conversion functions","what":"compute_concentrations()","title":"Data conversion","text":"function transforms counts number concentration abundances. also leverages sampling metadata sample volume total assemblage counts compute number concentration species.","code":"# Convert species counts in number concentration ---- net_data_n_conc <- compute_concentrations(net_data, aggregate = TRUE) #> Counts from 14 samples could not be converted because of missing volume data #> Relative counts from 24 samples could not be converted because of missing data on total assemblage"},{"path":"https://frbcesab.github.io/forcis/articles/data-conversion.html","id":"compute_frequencies","dir":"Articles","previous_headings":"Conversion functions","what":"compute_frequencies()","title":"Data conversion","text":"function computes relative abundance species using total assemblage counts available.","code":"# Convert species counts in relative abundance ---- net_data_rel_ab <- compute_frequencies(net_data, aggregate = TRUE) #> Counts from 12 samples could not be converted because of missing volume data #> Counts from 0 samples could not be converted because of missing data on total assemblage"},{"path":"https://frbcesab.github.io/forcis/articles/data-visualization.html","id":"setup","dir":"Articles","previous_headings":"","what":"Setup","title":"Data visualization","text":"First, let’s import required packages. going , download latest version FORCIS database. vignette use plankton nets data FORCIS database. Let’s import latest release data. NB: vignette, use subset plankton nets data, whole dataset.","code":"library(forcis) library(ggplot2) # Create a data/ folder ---- dir.create(\"data\") # Download latest version of the database ---- download_forcis_db(path = \"data\", version = NULL) # Import net data ---- net_data <- read_plankton_nets_data(path = \"data\")"},{"path":"https://frbcesab.github.io/forcis/articles/data-visualization.html","id":"geom_basemap","dir":"Articles","previous_headings":"","what":"geom_basemap()","title":"Data visualization","text":"function geom_basemap() can used easily add World countries, oceans bounding box ggplot2 object. layers come Natural Earth website defined Robinson projection.","code":"# World basemap ---- ggplot() + geom_basemap()"},{"path":"https://frbcesab.github.io/forcis/articles/data-visualization.html","id":"ggmap_data","dir":"Articles","previous_headings":"","what":"ggmap_data()","title":"Data visualization","text":"function ggmap_data() can used plot FORCIS data World map. Let’s map plankton nets data. User can customize aesthetic data: function works output various functions available forcis package. example: Note forcis package pipe-friendly. can export map function ggsave() package ggplot2.","code":"# Map raw net data ---- ggmap_data(net_data) # Customize map ---- ggmap_data(net_data, col = \"#ff0000\", fill = NA, shape = 21, size = 3) # Filter net data ---- indian_net_data <- filter_by_ocean(net_data, ocean = \"Indian Ocean\") # Map filtered data ---- ggmap_data(indian_net_data) # Same as before, but w/ the pipe ---- net_data %>% filter_by_ocean(ocean = \"Indian Ocean\") %>% ggmap_data() # Map filtered data ---- indian_net_data_map <- net_data %>% filter_by_ocean(ocean = \"Indian Ocean\") %>% ggmap_data() + ggtitle(\"FORCIS net data - Indian Ocean\") # Save as PNG ---- ggsave(indian_net_data_map, filename = \"indian_net_data_map.png\", width = 20, height = 11, units = \"cm\", dpi = 300, scale = 1.5, bg = \"white\")"},{"path":"https://frbcesab.github.io/forcis/articles/data-visualization.html","id":"plot_record_by_year","dir":"Articles","previous_headings":"","what":"plot_record_by_year()","title":"Data visualization","text":"function plot_record_by_year() plots number records (y-axis) year (x-axis).","code":"# Plot number of records by year ---- plot_record_by_year(net_data)"},{"path":"https://frbcesab.github.io/forcis/articles/data-visualization.html","id":"plot_record_by_month","dir":"Articles","previous_headings":"","what":"plot_record_by_month()","title":"Data visualization","text":"function plot_record_by_month() plots number records (y-axis) month (x-axis).","code":"# Plot number of records by month ---- plot_record_by_month(net_data)"},{"path":"https://frbcesab.github.io/forcis/articles/data-visualization.html","id":"plot_record_by_season","dir":"Articles","previous_headings":"","what":"plot_record_by_season()","title":"Data visualization","text":"function plot_record_by_season() plots number records (y-axis) season (x-axis).","code":"# Plot number of records by season ---- plot_record_by_season(net_data)"},{"path":"https://frbcesab.github.io/forcis/articles/data-visualization.html","id":"plot_record_by_depth","dir":"Articles","previous_headings":"","what":"plot_record_by_depth()","title":"Data visualization","text":"function plot_record_by_depth() plots number records (x-axis) depth intervals (y-axis).","code":"# Plot number of records by depth ---- plot_record_by_depth(net_data)"},{"path":"https://frbcesab.github.io/forcis/articles/database-versions.html","id":"using-the-latest-version","dir":"Articles","previous_headings":"","what":"Using the latest version","title":"Database versions","text":"package forcis designed handle versioning database Zenodo inform user new version available time /uses one read_*_data() functions. following message displayed: mentioned message, decision download use latest version database left user. good practice ensure user works latest version database might add line beginning script: Note FORCIS database saved forcis-db/version-99/, 99 label version. regularly download new versions, content folder forcis-db/ can increase time can interesting manually delete folder previous versions.","code":"A newer version of the FORCIS database is available. Use 'download_forcis_db(version = NULL)' to download it. download_forcis_db(version = NULL, ...)"},{"path":"https://frbcesab.github.io/forcis/articles/database-versions.html","id":"using-a-specific-version","dir":"Articles","previous_headings":"","what":"Using a specific version","title":"Database versions","text":"reasons user wants freeze version /uses, possible disable message setting argument check_for_update FALSE read_*_data() functions. also possible disable message globally current session: package forcis “knows” version database used last time. hidden file .forcis created/updated time function download_forcis_db() read_*_data() called. hidden file contains one line: Note hidden file used functions forcis package. User doesn’t edit hand. want sure use specific version database, can use argument version read_*_data() functions, use following line: time, user can run function get_current_version() check version database currently use. , recommended use latest version database.","code":"options(check_for_update = FALSE) FORCIS_VERSION=99 options(forcis_version = \"99\")"},{"path":"https://frbcesab.github.io/forcis/articles/forcis.html","id":"installation","dir":"Articles","previous_headings":"","what":"Installation","title":"Get started","text":"install forcis package, run: forcis package depends sf package requires spatial system libraries (GDAL PROJ). Please read page trouble install forcis.","code":"## Install < remotes > package (if not already installed) ---- if (!requireNamespace(\"remotes\", quietly = TRUE)) { install.packages(\"remotes\") } ## Install dev version of < forcis > from GitHub ---- remotes::install_github(\"FRBCesab/forcis\")"},{"path":"https://frbcesab.github.io/forcis/articles/forcis.html","id":"setup","dir":"Articles","previous_headings":"","what":"Setup","title":"Get started","text":"First, let’s attach required packages.","code":"library(forcis)"},{"path":"https://frbcesab.github.io/forcis/articles/forcis.html","id":"download-forcis-database","dir":"Articles","previous_headings":"","what":"Download FORCIS database","title":"Get started","text":"FORCIS database consists collection five csv files hosted Zenodo. csv regularly updated recommend use latest version Let’s download latest version FORCIS database download_forcis_db(): default (version = NULL), function downloads latest version database. database saved data/forcis-db/version-99/, 99 version number. N.B. package forcis designed handle versioning database Zenodo. Read Database versions information.","code":"# Create a data/ folder ---- dir.create(\"data\") # Download latest version of the database ---- download_forcis_db(path = \"data\", version = NULL)"},{"path":"https://frbcesab.github.io/forcis/articles/forcis.html","id":"import-forcis-data","dir":"Articles","previous_headings":"","what":"Import FORCIS data","title":"Get started","text":"vignette, use plankton nets data FORCIS database. Let’s import latest release data. N.B. use subset plankton nets data, whole dataset.","code":"# Import plankton nets data ---- net_data <- read_plankton_nets_data(path = \"data\")"},{"path":"https://frbcesab.github.io/forcis/articles/forcis.html","id":"select-a-taxonomy","dir":"Articles","previous_headings":"","what":"Select a taxonomy","title":"Get started","text":"FORCIS database provides three different taxonomies: LT: lumped taxonomy VT: validated taxonomy OT: original taxonomy See associated data paper information. importing data going , next step involves choosing taxonomic level analyses. Let’s use function select_taxonomy() select VT taxonomy (validated taxonomy):","code":"# Select taxonomy ---- net_data_vt <- select_taxonomy(net_data, taxonomy = \"VT\")"},{"path":"https://frbcesab.github.io/forcis/articles/forcis.html","id":"to-go-further","dir":"Articles","previous_headings":"","what":"To go further","title":"Get started","text":"Additional vignettes available depending user wishes: Database versions vignette provides information deal versioning database Select, reshape, filter data vignette shows examples select, filter reshape FORCIS data Data conversion vignette describes conversion functions available forcis compute abundances, concentrations, frequencies Data visualization vignette describes plotting functions available forcis","code":""},{"path":"https://frbcesab.github.io/forcis/articles/forcis.html","id":"references","dir":"Articles","previous_headings":"","what":"References","title":"Get started","text":"Chaabane S, De Garidel-Thoron T, Giraud X, Schiebel R, Beaugrand G, Brummer G-J, Casajus N, Greco M, Grigoratou M, Howa H, Jonkers L, Kucera M, Kuroyanagi , Meilland J, Monteiro F, Mortyn G, Almogi-Labin , Asahi H, Avnaim-Katav S, Bassinot F, Davis CV, Field DB, Hernández-Almeida , Herut B, Hosie G, Howard W, Jentzen , Johns DG, Keigwin L, Kitchener J, Kohfeld KE, Lessa DVO, Manno C, Marchant M, Ofstad S, Ortiz JD, Post , Rigual-Hernandez , Rillo MC, Robinson K, Sagawa T, Sierro F, Takahashi KT, Torfstein , Venancio , Yamasaki M & Ziveri P (2023) FORCIS database: global census planktonic Foraminifera ocean waters. Scientific Data, 10, 354. DOI: 10.1038/s41597-023-02264-2.","code":""},{"path":"https://frbcesab.github.io/forcis/articles/sampling-devices.html","id":"site-identifier","dir":"Articles","previous_headings":"","what":"Site identifier","title":"Sampling devices","text":"site characterized location (longitude latitude coordinates). Associated information water depth ocean basin. unique identifier site_id either sourced original publication/study (e.g. PECH_B), generated database managers (e.g. MedSeaCruise_St1).","code":""},{"path":"https://frbcesab.github.io/forcis/articles/sampling-devices.html","id":"profile-identifier","dir":"Articles","previous_headings":"","what":"Profile identifier","title":"Sampling devices","text":"net data, profiles distinguished time collection location well. profile table, profile_id attributed based profile date (time collection) coordinates. Overall, profile identifier coordinates, different times sampling incremented. cases, coordinates, profile date site water depth profile change slightly due multiple sampling events ship movements (e.g. multiple sampling events carried site). sediment trap data, profile identifier incremented deployment changed. date, depth range profile, availability environmental data including ambient seawater chemistry, profile season also included table profiles.","code":""},{"path":"https://frbcesab.github.io/forcis/articles/sampling-devices.html","id":"cast-identifier","dir":"Articles","previous_headings":"","what":"Cast identifier","title":"Sampling devices","text":"cast_id provides information regarding casts, sampling device name, depth range cast, mesh size, net opening plankton tow.","code":""},{"path":"https://frbcesab.github.io/forcis/articles/sampling-devices.html","id":"sample-identifier","dir":"Articles","previous_headings":"","what":"Sample identifier","title":"Sampling devices","text":"sample characterized depth range, volume water filtered (net data), coordinates, segment length (CPR data), date sampling, situ temperature salinity.","code":""},{"path":"https://frbcesab.github.io/forcis/articles/sampling-devices.html","id":"subsample-identifier","dir":"Articles","previous_headings":"","what":"Subsample identifier","title":"Sampling devices","text":"One sample divided different subsamples (subsample_id) based subsample_size_fraction_min, subsample_size_fraction_max /subsample_living_or_dead. information also reported : subsample_count_type, subsample_sieved_or_measured, subsample_storage_type, subsample_splitting_type.","code":""},{"path":"https://frbcesab.github.io/forcis/articles/select-and-filter-data.html","id":"setup","dir":"Articles","previous_headings":"","what":"Setup","title":"Select, reshape, and filter data","text":"First, let’s import required packages. going , download latest version FORCIS database. vignette use plankton nets data FORCIS database. Let’s import latest release data. NB: vignette, use subset plankton nets data, whole dataset.","code":"library(forcis) # Create a data/ folder ---- dir.create(\"data\") # Download latest version of the database ---- download_forcis_db(path = \"data\", version = NULL) # Import net data ---- net_data <- read_plankton_nets_data(path = \"data\")"},{"path":"https://frbcesab.github.io/forcis/articles/select-and-filter-data.html","id":"select_taxonomy","dir":"Articles","previous_headings":"","what":"select_taxonomy()","title":"Select, reshape, and filter data","text":"FORCIS database provides three different taxonomies: LT (lumped taxonomy), VT (validated taxonomy) OT (original taxonomy). See associated data paper information. importing data going , next step involves choosing taxonomic level analyses. Let’s use function select_taxonomy() select VT taxonomy (validated taxonomy):","code":"# Select taxonomy ---- net_data <- select_taxonomy(net_data, taxonomy = \"VT\")"},{"path":"https://frbcesab.github.io/forcis/articles/select-and-filter-data.html","id":"select_columns","dir":"Articles","previous_headings":"","what":"select_columns()","title":"Select, reshape, and filter data","text":"FORCIS data contains 100 columns, function select_columns() can used lighten data.frame easily handle speed computations. default, required columns listed get_required_columns() species columns kept. can also use argument cols keep additional columns.","code":"# Select taxonomy ---- net_data <- select_columns(net_data)"},{"path":"https://frbcesab.github.io/forcis/articles/select-and-filter-data.html","id":"filter_by_month","dir":"Articles","previous_headings":"","what":"filter_by_month()","title":"Select, reshape, and filter data","text":"filter_by_month() function filters observations based month sampling. requires two arguments: data numeric vector values 1 12.","code":"# Filter data by sampling month ---- net_july_aug <- filter_by_month(net_data, months = 7:8) # Number of original records ---- nrow(net_data) #> [1] 2451 # Number of filtered records ---- nrow(net_july_aug) #> [1] 516"},{"path":"https://frbcesab.github.io/forcis/articles/select-and-filter-data.html","id":"filter_by_year","dir":"Articles","previous_headings":"","what":"filter_by_year()","title":"Select, reshape, and filter data","text":"filter_by_year() function filters observations based year sampling. requires two arguments: data numeric vector years interest.","code":"# Filter data by sampling year ---- net_90_20 <- filter_by_year(net_data, years = 1990:2020) # Number of original records ---- nrow(net_data) #> [1] 2451 # Number of filtered records ---- nrow(net_90_20) #> [1] 2283"},{"path":"https://frbcesab.github.io/forcis/articles/select-and-filter-data.html","id":"filter_by_bbox","dir":"Articles","previous_headings":"","what":"filter_by_bbox()","title":"Select, reshape, and filter data","text":"function filter_by_bbox() can used filter FORCIS data spatial bounding box (argument bbox). Let’s filter plankton net data spatial rectangle located Indian ocean. Note argument bbox can object class bbox (package sf) vector four numeric values defining square bounding box. vector numeric values provided, coordinates must defined system WGS 84 (epsg=4326).","code":"# Filter by spatial bounding box ---- net_data_bbox <- filter_by_bbox(net_data, bbox = c(45, -61, 82, -24)) # Number of original records ---- nrow(net_data) #> [1] 2451 # Number of filtered records ---- nrow(net_data_bbox) #> [1] 320"},{"path":"https://frbcesab.github.io/forcis/articles/select-and-filter-data.html","id":"filter_by_ocean","dir":"Articles","previous_headings":"","what":"filter_by_ocean()","title":"Select, reshape, and filter data","text":"function filter_by_ocean() can used filter FORCIS data one several oceans (argument ocean). Let’s filter plankton net data located Indian ocean. Use function get_ocean_names() retrieve name World oceans according IHO Sea Areas dataset version 3 (used package).","code":"# Filter by ocean name ---- net_data_indian <- filter_by_ocean(net_data, ocean = \"Indian Ocean\") # Number of original records ---- nrow(net_data) #> [1] 2451 # Number of filtered records ---- nrow(net_data_indian) #> [1] 1640 # Get ocean names ---- get_ocean_names() #> [1] \"Arctic Ocean\" \"Indian Ocean\" \"Mediterranean Sea\" #> [4] \"North Atlantic Ocean\" \"North Pacific Ocean\" \"South Atlantic Ocean\" #> [7] \"South Pacific Ocean\" \"Southern Ocean\""},{"path":"https://frbcesab.github.io/forcis/articles/select-and-filter-data.html","id":"filter_by_polygon","dir":"Articles","previous_headings":"","what":"filter_by_polygon()","title":"Select, reshape, and filter data","text":"function filter_by_polygon() can used filter FORCIS data spatial polygon (argument polygon). Let’s filter plankton net data spatial polygon defining boundaries Indian ocean.","code":"# Import spatial polygon ---- file_name <- system.file(file.path(\"extdata\", \"IHO_Indian_ocean_polygon.gpkg\"), package = \"forcis\") indian_ocean <- sf::st_read(file_name, quiet = TRUE) # Filter by polygon ---- net_data_poly <- filter_by_polygon(net_data, polygon = indian_ocean) # Number of original records ---- nrow(net_data) #> [1] 2451 # Number of filtered records ---- nrow(net_data_poly) #> [1] 1640"},{"path":"https://frbcesab.github.io/forcis/articles/select-and-filter-data.html","id":"filter_by_species","dir":"Articles","previous_headings":"","what":"filter_by_species()","title":"Select, reshape, and filter data","text":"function filter_by_species() allows filter FORCIS data one species. takes data.frame vector species names (argument species). Let’s subset plankton net data keep observations G. glutinata C. nitida.","code":"# Filter by species ---- glutinata_nitida <- filter_by_species(net_data, species = c(\"g_glutinata_VT\", \"c_nitida_VT\")) # Dimensions of original data ---- dim(net_data) #> [1] 2451 77 # Dimensions of filtered data ---- dim(glutinata_nitida) #> [1] 2451 23"},{"path":"https://frbcesab.github.io/forcis/articles/select-and-filter-data.html","id":"reshape_data","dir":"Articles","previous_headings":"","what":"reshape_data()","title":"Select, reshape, and filter data","text":"function reshape_data() converts FORCIS data long format. Two columns created: taxa (taxon names) counts (taxon counts).","code":"# Convert to long format ---- net_data_long <- reshape_data(net_data) # Dimensions of original data ---- dim(net_data) #> [1] 2451 77 # Dimensions of reshaped data ---- dim(net_data_long) #> [1] 137256 23 # Column names ---- colnames(net_data_long) #> [1] \"data_type\" #> [2] \"cruise_id\" #> [3] \"profile_id\" #> [4] \"sample_id\" #> [5] \"sample_min_depth\" #> [6] \"sample_max_depth\" #> [7] \"profile_depth_min\" #> [8] \"profile_depth_max\" #> [9] \"profile_date_time\" #> [10] \"cast_net_op_m2\" #> [11] \"subsample_id\" #> [12] \"sample_segment_length\" #> [13] \"subsample_count_type\" #> [14] \"subsample_size_fraction_min\" #> [15] \"subsample_size_fraction_max\" #> [16] \"site_lat_start_decimal\" #> [17] \"site_lon_start_decimal\" #> [18] \"sample_volume_filtered\" #> [19] \"subsample_all_shells_present_were_counted\" #> [20] \"total_of_forams_counted_ind\" #> [21] \"sampling_device_type\" #> [22] \"taxa\" #> [23] \"counts\""},{"path":"https://frbcesab.github.io/forcis/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Nicolas Casajus. Author, maintainer, copyright holder. Mattia Greco. Author. Xavier Giraud. Author. Sonia Chaabane. Author.","code":""},{"path":"https://frbcesab.github.io/forcis/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Casajus Nicolas, Greco Mattia, Giraud Xavier, Chaabane Sonia (2024). forcis: R client access FORCIS database. R package version 0.0.0.9000, https://frbcesab.github.io/forcis. Chaabane Sonia, De Garidel-Thoron Thibault, Giraud Xavier, Schiebel Ralf, Beaugrand Gregory, Brummer Geert-Jan, Casajus Nicolas, Greco Mattia, Grigoratou Maria, Howa Hélène, Jonkers Lukas, Kucera Michal, Kuroyanagi Azumi, Meilland Julie, Monteiro Fanny, Mortyn Graham, Almogi-Labin Ahuva, Asahi Hirofumi, Avnaim-Katav Simona, Bassinot Franck, Davis Catherine V., Field David B., Hernández-Almeida Iván, Herut Barak, Hosie Graham, Howard , Jentzen Anna, Johns David G., Keigwin Lloyd, Kitchener John, Kohfeld Karen E., Lessa Douglas V. O., Manno Clara, Marchant Margarita, Ofstad Siri, Ortiz Joseph D., Post Alexandra, Rigual-Hernandez Andres, Rillo Marina C., Robinson Karen, Sagawa Takuya, Sierro Francisco, Takahashi Kunio T., Torfstein Adi, Venancio Igor, Yamasaki Makoto, Ziveri Patrizia (2023). “FORCIS database: global census planktonic Foraminifera ocean waters.” Scientific Data, 10, 354. doi:10.1038/s41597-023-02264-2.","code":"@Manual{, title = {forcis: {An} {R} client to access the {FORCIS} database}, author = {{Casajus Nicolas} and {Greco Mattia} and {Giraud Xavier} and {Chaabane Sonia}}, year = {2024}, note = {R package version 0.0.0.9000}, url = {https://frbcesab.github.io/forcis}, } @Article{, title = {The {FORCIS} database: {A} global census of planktonic {F}oraminifera from ocean waters}, author = {{Chaabane Sonia} and {De Garidel-Thoron Thibault} and {Giraud Xavier} and {Schiebel Ralf} and {Beaugrand Gregory} and {Brummer Geert-Jan} and {Casajus Nicolas} and {Greco Mattia} and {Grigoratou Maria} and {Howa Hélène} and {Jonkers Lukas} and {Kucera Michal} and {Kuroyanagi Azumi} and {Meilland Julie} and {Monteiro Fanny} and {Mortyn Graham} and {Almogi-Labin Ahuva} and {Asahi Hirofumi} and {Avnaim-Katav Simona} and {Bassinot Franck} and {Davis Catherine V.} and {Field David B.} and {Hernández-Almeida Iván} and {Herut Barak} and {Hosie Graham} and {Howard Will} and {Jentzen Anna} and {Johns David G.} and {Keigwin Lloyd} and {Kitchener John} and {Kohfeld Karen E.} and {Lessa Douglas V. O.} and {Manno Clara} and {Marchant Margarita} and {Ofstad Siri} and {Ortiz Joseph D.} and {Post Alexandra} and {Rigual-Hernandez Andres} and {Rillo Marina C.} and {Robinson Karen} and {Sagawa Takuya} and {Sierro Francisco} and {Takahashi Kunio T.} and {Torfstein Adi} and {Venancio Igor} and {Yamasaki Makoto} and {Ziveri Patrizia}}, journal = {Scientific Data}, volume = {10}, pages = {354}, doi = {10.1038/s41597-023-02264-2}, year = {2023}, }"},{"path":[]},{"path":"https://frbcesab.github.io/forcis/index.html","id":"table-of-contents","dir":"","previous_headings":"","what":"Table of contents","title":"An R Client to Access the FORCIS Database","text":"• Overview • Features • Installation • Get started • Long-form documentations • Citation • Contributing • Acknowledgments • References","code":""},{"path":"https://frbcesab.github.io/forcis/index.html","id":"overview","dir":"","previous_headings":"","what":"Overview","title":"An R Client to Access the FORCIS Database","text":"goal R package forcis provide interface FORCIS database global foraminifera distribution (Chaabane et al. 2023). database includes data living planktonic foraminifera diversity distribution global oceans 1910 2018 collected using plankton tows, continuous plankton recorder, sediment traps plankton pump global ocean.","code":""},{"path":"https://frbcesab.github.io/forcis/index.html","id":"features","dir":"","previous_headings":"","what":"Features","title":"An R Client to Access the FORCIS Database","text":"main purpose forcis package download, select, filter, homogenize, visualize FORCIS data. Functions page provides full description features available package.","code":""},{"path":"https://frbcesab.github.io/forcis/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"An R Client to Access the FORCIS Database","text":"can install development version GitHub : N.B. forcis package depends sf package requires spatial system libraries (GDAL PROJ). Please read page trouble install forcis. Finally can attach package forcis :","code":"## Install < remotes > package (if not already installed) ---- if (!requireNamespace(\"remotes\", quietly = TRUE)) { install.packages(\"remotes\") } ## Install dev version of < forcis > from GitHub ---- remotes::install_github(\"FRBCesab/forcis\") library(\"forcis\")"},{"path":"https://frbcesab.github.io/forcis/index.html","id":"get-started","dir":"","previous_headings":"","what":"Get started","title":"An R Client to Access the FORCIS Database","text":"overview main features forcis, please read Get started vignette.","code":""},{"path":"https://frbcesab.github.io/forcis/index.html","id":"long-form-documentations","dir":"","previous_headings":"","what":"Long-form documentations","title":"An R Client to Access the FORCIS Database","text":"forcis provides five vignettes learn package: Get started vignette describes core features package Database versions vignette provides information deal versioning database Select filter data vignette shows examples handle FORCIS data Data conversion vignette describes conversion functions available forcis compute abundances, concentrations, frequencies Data visualization vignette describes plotting functions available forcis","code":""},{"path":"https://frbcesab.github.io/forcis/index.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"An R Client to Access the FORCIS Database","text":"Please cite package : Casajus N, Greco M, Giraud X & Chaabane S (2024) forcis: R client access FORCIS database. R package version 0.0.0.9000. URL: https://frbcesab.github.io/forcis/. can also run:","code":"citation(\"forcis\")"},{"path":"https://frbcesab.github.io/forcis/index.html","id":"contributing","dir":"","previous_headings":"","what":"Contributing","title":"An R Client to Access the FORCIS Database","text":"types contributions encouraged valued. information, check Contributor Guidelines. Please note forcis project released Contributor Code Conduct. contributing project, agree abide terms.","code":""},{"path":"https://frbcesab.github.io/forcis/index.html","id":"acknowledgments","dir":"","previous_headings":"","what":"Acknowledgments","title":"An R Client to Access the FORCIS Database","text":"package developed FRB-CESAB working group FORCIS aims understand importance main stressors temperature ocean acidification govern foraminifera species distribution calcification processes, focus present near-future ocean impacts. want thanks Khalil Hammami (@khammami) valuable contribution package.","code":""},{"path":"https://frbcesab.github.io/forcis/index.html","id":"references","dir":"","previous_headings":"","what":"References","title":"An R Client to Access the FORCIS Database","text":"Chaabane S, De Garidel-Thoron T, Giraud X, Schiebel R, Beaugrand G, Brummer G-J, Casajus N, Greco M, Grigoratou M, Howa H, Jonkers L, Kucera M, Kuroyanagi , Meilland J, Monteiro F, Mortyn G, Almogi-Labin , Asahi H, Avnaim-Katav S, Bassinot F, Davis CV, Field DB, Hernández-Almeida , Herut B, Hosie G, Howard W, Jentzen , Johns DG, Keigwin L, Kitchener J, Kohfeld KE, Lessa DVO, Manno C, Marchant M, Ofstad S, Ortiz JD, Post , Rigual-Hernandez , Rillo MC, Robinson K, Sagawa T, Sierro F, Takahashi KT, Torfstein , Venancio , Yamasaki M & Ziveri P (2023) FORCIS database: global census planktonic Foraminifera ocean waters. Scientific Data, 10, 354. DOI: 10.1038/s41597-023-02264-2.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/computations.html","id":null,"dir":"Reference","previous_headings":"","what":"Compute count conversions — compute_abundances","title":"Compute count conversions — compute_abundances","text":"Functions convert species counts different formats: raw abundance, relative abundance, number concentration, using counts metadata.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/computations.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Compute count conversions — compute_abundances","text":"","code":"compute_abundances(data, aggregate = TRUE) compute_concentrations(data, aggregate = TRUE) compute_frequencies(data, aggregate = TRUE)"},{"path":"https://frbcesab.github.io/forcis/reference/computations.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Compute count conversions — compute_abundances","text":"data data.frame. One obtained read_*_data() functions. aggregate logical length 1. FALSE counts derived subsample. TRUE (default) subsample counts aggregated sample_id.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/computations.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Compute count conversions — compute_abundances","text":"data.frame.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/computations.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Compute count conversions — compute_abundances","text":"compute_concentrations() converts counts number concentrations (n specimens/m³). compute_frequencies() converts counts relative abundances (% specimens per sampling unit). compute_abundances() converts counts raw abundances (n specimens/sampling unit).","code":""},{"path":"https://frbcesab.github.io/forcis/reference/data_to_sf.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert a data frame into an sf object — data_to_sf","title":"Convert a data frame into an sf object — data_to_sf","text":"function can used convert data.frame sf object. Note coordinates (columns site_lon_start_decimal site_lat_start_decimal) projected Robinson coordinate system.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/data_to_sf.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert a data frame into an sf object — data_to_sf","text":"","code":"data_to_sf(data)"},{"path":"https://frbcesab.github.io/forcis/reference/data_to_sf.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert a data frame into an sf object — data_to_sf","text":"data data.frame, .e. FORCIS dataset output filter_*() function.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/data_to_sf.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert a data frame into an sf object — data_to_sf","text":"sf POINTS object.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/data_to_sf.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert a data frame into an sf object — data_to_sf","text":"","code":"# Attach packages ---- library(\"forcis\") library(\"ggplot2\") # Import example dataset ---- file_name <- system.file(file.path(\"extdata\", \"FORCIS_net_sample.csv\"), package = \"forcis\") net_data <- read.table(file_name, dec = \".\", sep = \";\") # Add 'data_type' column ---- net_data$\"data_type\" <- \"Net\" # Dimensions of the data.frame ---- dim(net_data) #> [1] 2451 77 # Filter by years ---- net_data_sub <- filter_by_year(net_data, years = 1992) # Convert to an sf object ---- net_data_sub_sf <- data_to_sf(net_data_sub) # World basemap ---- ggplot() + geom_basemap() + geom_sf(data = net_data_sub_sf)"},{"path":"https://frbcesab.github.io/forcis/reference/download_forcis_db.html","id":null,"dir":"Reference","previous_headings":"","what":"Download the FORCIS database — download_forcis_db","title":"Download the FORCIS database — download_forcis_db","text":"Downloads entire FORCIS database collection five csv files Zenodo (https://zenodo.org/doi/10.5281/zenodo.7390791). Additional files also downloaded.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/download_forcis_db.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download the FORCIS database — download_forcis_db","text":"","code":"download_forcis_db( path = \".\", version = options()$forcis_version, check_for_update = options()$check_for_update, overwrite = FALSE, timeout = 60 )"},{"path":"https://frbcesab.github.io/forcis/reference/download_forcis_db.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download the FORCIS database — download_forcis_db","text":"path character length 1. folder FORCIS database saved. Note subdirectory created, e.g. forcis-db/version-99/ (99 version number). version character length 1. version number (two numbers, e.g. 08 instead 8) FORCIS database use. Default latest version. Note argument can handle global option forcis_version. example, user calls options(forcis_version = \"07\"), version 07 used default current R session. Note recommended use latest version database. check_for_update logical. TRUE (default) function check newer version FORCIS database available Zenodo print informative message. Note argument can handle global option check_for_update. example, user calls options(check_for_update = FALSE), message download latest version disabled current R session. overwrite logical. TRUE override downloaded files FORCIS database. Default FALSE. timeout integer. timeout downloading files Zenodo. Default 60. number can increased low Internet connection.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/download_forcis_db.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download the FORCIS database — download_forcis_db","text":"return value. FORCIS files saved path folder.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/download_forcis_db.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Download the FORCIS database — download_forcis_db","text":"FORCIS database regularly updated. global structure tables doesn’t change versions bugs can fixed new records can added. recommended use latest version database. package designed handle versioning database Zenodo inform user new version available time /uses one read_*_data() functions. information, please read vignette available https://frbcesab.github.io/forcis/articles/database-versions.html.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/download_forcis_db.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Download the FORCIS database — download_forcis_db","text":"Chaabane S, De Garidel-Thoron T, Giraud X, et al. (2023) FORCIS database: global census planktonic Foraminifera ocean waters. Scientific Data, 10, 354. DOI: https://doi.org/10.1038/s41597-023-02264-2.","code":""},{"path":[]},{"path":"https://frbcesab.github.io/forcis/reference/download_forcis_db.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Download the FORCIS database — download_forcis_db","text":"","code":"if (FALSE) { # \\dontrun{ # Attach the package ---- library(\"forcis\") # Folder in which the database will be saved ---- path_to_save_db <- \"data\" # Download the database ---- download_forcis_db(path = path_to_save_db) # Check the content of the folder ---- list.files(path_to_save_db, recursive = TRUE) } # }"},{"path":"https://frbcesab.github.io/forcis/reference/filter_by_bbox.html","id":null,"dir":"Reference","previous_headings":"","what":"Filter FORCIS data by a spatial bounding box — filter_by_bbox","title":"Filter FORCIS data by a spatial bounding box — filter_by_bbox","text":"Filters FORCIS data spatial bounding box.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/filter_by_bbox.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Filter FORCIS data by a spatial bounding box — filter_by_bbox","text":"","code":"filter_by_bbox(data, bbox)"},{"path":"https://frbcesab.github.io/forcis/reference/filter_by_bbox.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Filter FORCIS data by a spatial bounding box — filter_by_bbox","text":"data data.frame. One obtained read_*_data() functions. bbox object class bbox (package sf) vector four numeric values defining square bounding box. Values must follow order: minimum longitude (xmin), minimum latitude (ymin), maximum longitude (xmax), maximum latitude (ymax). Important: vector numeric values provided, coordinates must defined system WGS 84 (epsg=4326).","code":""},{"path":"https://frbcesab.github.io/forcis/reference/filter_by_bbox.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Filter FORCIS data by a spatial bounding box — filter_by_bbox","text":"data.frame containing subset data desired bounding box.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/filter_by_bbox.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Filter FORCIS data by a spatial bounding box — filter_by_bbox","text":"","code":"# Attach the package ---- library(\"forcis\") # Import example dataset ---- file_name <- system.file(file.path(\"extdata\", \"FORCIS_net_sample.csv\"), package = \"forcis\") net_data <- read.table(file_name, dec = \".\", sep = \";\") # Add 'data_type' column ---- net_data$\"data_type\" <- \"Net\" # Dimensions of the data.frame ---- dim(net_data) #> [1] 2451 77 # Filter by oceans ---- net_data_sub <- filter_by_bbox(net_data, bbox = c(45, -61, 82, -24)) # Dimensions of the data.frame ---- dim(net_data_sub) #> [1] 320 77"},{"path":"https://frbcesab.github.io/forcis/reference/filter_by_month.html","id":null,"dir":"Reference","previous_headings":"","what":"Filter FORCIS data by month of sampling — filter_by_month","title":"Filter FORCIS data by month of sampling — filter_by_month","text":"Filters FORCIS data month sampling.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/filter_by_month.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Filter FORCIS data by month of sampling — filter_by_month","text":"","code":"filter_by_month(data, months)"},{"path":"https://frbcesab.github.io/forcis/reference/filter_by_month.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Filter FORCIS data by month of sampling — filter_by_month","text":"data data.frame. One obtained read_*_data() functions. months numeric containing one several months.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/filter_by_month.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Filter FORCIS data by month of sampling — filter_by_month","text":"data.frame containing subset data desired months.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/filter_by_month.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Filter FORCIS data by month of sampling — filter_by_month","text":"","code":"# Attach the package ---- library(\"forcis\") # Import example dataset ---- file_name <- system.file(file.path(\"extdata\", \"FORCIS_net_sample.csv\"), package = \"forcis\") net_data <- read.table(file_name, dec = \".\", sep = \";\") # Add 'data_type' column ---- net_data$\"data_type\" <- \"Net\" # Dimensions of the data.frame ---- dim(net_data) #> [1] 2451 77 # Filter by months ---- net_data_sub <- filter_by_month(net_data, months = 1:2) # Dimensions of the data.frame ---- dim(net_data_sub) #> [1] 305 77"},{"path":"https://frbcesab.github.io/forcis/reference/filter_by_ocean.html","id":null,"dir":"Reference","previous_headings":"","what":"Filter FORCIS data by ocean — filter_by_ocean","title":"Filter FORCIS data by ocean — filter_by_ocean","text":"Filters FORCIS data one several oceans.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/filter_by_ocean.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Filter FORCIS data by ocean — filter_by_ocean","text":"","code":"filter_by_ocean(data, ocean)"},{"path":"https://frbcesab.github.io/forcis/reference/filter_by_ocean.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Filter FORCIS data by ocean — filter_by_ocean","text":"data data.frame. One obtained read_*_data() functions. ocean character vector one several ocean names. Use function get_ocean_names() find correct spelling.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/filter_by_ocean.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Filter FORCIS data by ocean — filter_by_ocean","text":"data.frame containing subset data desired oceans.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/filter_by_ocean.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Filter FORCIS data by ocean — filter_by_ocean","text":"","code":"# Attach the package ---- library(\"forcis\") # Import example dataset ---- file_name <- system.file(file.path(\"extdata\", \"FORCIS_net_sample.csv\"), package = \"forcis\") net_data <- read.table(file_name, dec = \".\", sep = \";\") # Add 'data_type' column ---- net_data$\"data_type\" <- \"Net\" # Dimensions of the data.frame ---- dim(net_data) #> [1] 2451 77 # Get ocean names ---- get_ocean_names() #> [1] \"Arctic Ocean\" \"Indian Ocean\" \"Mediterranean Sea\" #> [4] \"North Atlantic Ocean\" \"North Pacific Ocean\" \"South Atlantic Ocean\" #> [7] \"South Pacific Ocean\" \"Southern Ocean\" # Filter by oceans ---- net_data_sub <- filter_by_ocean(net_data, ocean = \"Indian Ocean\") # Dimensions of the data.frame ---- dim(net_data_sub) #> [1] 1640 77"},{"path":"https://frbcesab.github.io/forcis/reference/filter_by_polygon.html","id":null,"dir":"Reference","previous_headings":"","what":"Filter FORCIS data by a spatial polygon — filter_by_polygon","title":"Filter FORCIS data by a spatial polygon — filter_by_polygon","text":"Filters FORCIS data spatial polygon.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/filter_by_polygon.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Filter FORCIS data by a spatial polygon — filter_by_polygon","text":"","code":"filter_by_polygon(data, polygon)"},{"path":"https://frbcesab.github.io/forcis/reference/filter_by_polygon.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Filter FORCIS data by a spatial polygon — filter_by_polygon","text":"data data.frame. One obtained read_*_data() functions. polygon sf POLYGON object.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/filter_by_polygon.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Filter FORCIS data by a spatial polygon — filter_by_polygon","text":"data.frame containing subset data desired spatial polygon.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/filter_by_polygon.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Filter FORCIS data by a spatial polygon — filter_by_polygon","text":"","code":"# Attach the package ---- library(\"forcis\") # Import example dataset ---- file_name <- system.file(file.path(\"extdata\", \"FORCIS_net_sample.csv\"), package = \"forcis\") net_data <- read.table(file_name, dec = \".\", sep = \";\") # Add 'data_type' column ---- net_data$\"data_type\" <- \"Net\" # Dimensions of the data.frame ---- dim(net_data) #> [1] 2451 77 # Import Indian Ocean spatial polygons ---- file_name <- system.file(file.path(\"extdata\", \"IHO_Indian_ocean_polygon.gpkg\"), package = \"forcis\") indian_ocean <- sf::st_read(file_name) #> Reading layer `IHO_Indian_ocean_polygon' from data source #> `/home/runner/work/_temp/Library/forcis/extdata/IHO_Indian_ocean_polygon.gpkg' #> using driver `GPKG' #> Simple feature collection with 1 feature and 1 field #> Geometry type: MULTIPOLYGON #> Dimension: XY #> Bounding box: xmin: 1508984 ymin: -6336039 xmax: 12568840 ymax: 3246966 #> Projected CRS: +proj=robin +lon_0=0 +x_0=0 +y_0=0 +datum=WGS84 +units=m +no_defs # Filter by polygon ---- net_data_sub <- filter_by_polygon(net_data, polygon = indian_ocean) # Dimensions of the data.frame ---- dim(net_data_sub) #> [1] 1640 77"},{"path":"https://frbcesab.github.io/forcis/reference/filter_by_species.html","id":null,"dir":"Reference","previous_headings":"","what":"Filter FORCIS data by species — filter_by_species","title":"Filter FORCIS data by species — filter_by_species","text":"Filters FORCIS data species list.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/filter_by_species.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Filter FORCIS data by species — filter_by_species","text":"","code":"filter_by_species(data, species)"},{"path":"https://frbcesab.github.io/forcis/reference/filter_by_species.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Filter FORCIS data by species — filter_by_species","text":"data data.frame. One obtained read_*_data() functions. species character vector listing species interest.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/filter_by_species.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Filter FORCIS data by species — filter_by_species","text":"data.frame containing subset data.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/filter_by_species.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Filter FORCIS data by species — filter_by_species","text":"","code":"# Import example dataset ---- file_name <- system.file(file.path(\"extdata\", \"FORCIS_net_sample.csv\"), package = \"forcis\") net_data <- read.table(file_name, dec = \".\", sep = \";\") # Add 'data_type' column ---- net_data$\"data_type\" <- \"Net\" # Select a taxonomy ---- net_data <- select_taxonomy(net_data, taxonomy = \"VT\") # Select only required columns (and taxa) ---- net_data <- select_columns(net_data) # Dimensions of the data.frame ---- dim(net_data) #> [1] 2451 77 # Get species names ---- get_species_names(net_data) #> [1] \"b_digitata_VT\" \"b_pumilio_VT\" #> [3] \"b_variabilis_VT\" \"c_nitida_VT\" #> [5] \"d_anfracta_VT\" \"g_adamsi_VT\" #> [7] \"g_bulloides_VT\" \"g_calida_VT\" #> [9] \"g_cavernula_VT\" \"g_conglobatus_VT\" #> [11] \"g_conglomerata_VT\" \"g_crassaformis_VT\" #> [13] \"g_elongatus_VT\" \"g_falconensis_VT\" #> [15] \"g_glutinata_VT\" \"g_hexagona_VT\" #> [17] \"g_hirsuta_VT\" \"g_inflata_VT\" #> [19] \"g_cultrata_VT\" \"g_minuta_VT\" #> [21] \"g_ruber_albus_VT\" \"g_ruber_albus_or_elongatus_VT\" #> [23] \"g_ruber_any_VT\" \"g_ruber_ruber_VT\" #> [25] \"g_rubescens_VT\" \"g_scitula_VT\" #> [27] \"g_siphonifera_VT\" \"g_tenellus_VT\" #> [29] \"g_theyeri_VT\" \"g_truncatulinoides_VT\" #> [31] \"g_truncatulinoides_left_VT\" \"g_truncatulinoides_right_VT\" #> [33] \"g_tumida_VT\" \"g_ungulata_VT\" #> [35] \"g_uvula_VT\" \"n_vivans_VT\" #> [37] \"h_digitata_VT\" \"h_pelagica_VT\" #> [39] \"n_dutertrei_VT\" \"n_incompta_VT\" #> [41] \"n_pachyderma_VT\" \"n_pachyderma_incompta_VT\" #> [43] \"o_riedeli_VT\" \"o_universa_VT\" #> [45] \"p_obliquiloculata_VT\" \"s_dehiscens_VT\" #> [47] \"t_clarkei_VT\" \"t_fleisheri_VT\" #> [49] \"t_humilis_VT\" \"t_iota_VT\" #> [51] \"t_parkerae_VT\" \"t_quinqueloba_VT\" #> [53] \"t_sacculifer_VT\" \"t_sacculifer_no_sac_VT\" #> [55] \"t_sacculifer_sac_VT\" \"UnID_VT\" # Select records for three species ---- net_data_sub <- filter_by_species(data = net_data, species = c(\"g_inflata_VT\", \"g_elongatus_VT\", \"g_glutinata_VT\")) # Dimensions of the data.frame ---- dim(net_data_sub) #> [1] 2451 24 # Get species names ---- get_species_names(net_data_sub) #> [1] \"g_elongatus_VT\" \"g_glutinata_VT\" \"g_inflata_VT\""},{"path":"https://frbcesab.github.io/forcis/reference/filter_by_year.html","id":null,"dir":"Reference","previous_headings":"","what":"Filter FORCIS data by year of sampling — filter_by_year","title":"Filter FORCIS data by year of sampling — filter_by_year","text":"Filters FORCIS data year sampling.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/filter_by_year.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Filter FORCIS data by year of sampling — filter_by_year","text":"","code":"filter_by_year(data, years)"},{"path":"https://frbcesab.github.io/forcis/reference/filter_by_year.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Filter FORCIS data by year of sampling — filter_by_year","text":"data data.frame. One obtained read_*_data() functions. years numeric containing one several years.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/filter_by_year.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Filter FORCIS data by year of sampling — filter_by_year","text":"data.frame containing subset data desired years.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/filter_by_year.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Filter FORCIS data by year of sampling — filter_by_year","text":"","code":"# Attach the package ---- library(\"forcis\") # Import example dataset ---- file_name <- system.file(file.path(\"extdata\", \"FORCIS_net_sample.csv\"), package = \"forcis\") net_data <- read.table(file_name, dec = \".\", sep = \";\") # Add 'data_type' column ---- net_data$\"data_type\" <- \"Net\" # Dimensions of the data.frame ---- dim(net_data) #> [1] 2451 77 # Filter by years ---- net_data_sub <- filter_by_year(net_data, years = 1992) # Dimensions of the data.frame ---- dim(net_data_sub) #> [1] 610 77"},{"path":"https://frbcesab.github.io/forcis/reference/forcis-package.html","id":null,"dir":"Reference","previous_headings":"","what":"forcis: An R Client to Access the FORCIS Database — forcis-package","title":"forcis: An R Client to Access the FORCIS Database — forcis-package","text":"Provides interface FORCIS database (https://zenodo.org/doi/10.5281/zenodo.7390791) global foraminifera distribution. package allows download handle FORCIS data. part FRB-CESAB working group FORCIS. https://www.fondationbiodiversite.fr/en/-frb--action/programs--projects/le-cesab/forcis/.","code":""},{"path":[]},{"path":"https://frbcesab.github.io/forcis/reference/forcis-package.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"forcis: An R Client to Access the FORCIS Database — forcis-package","text":"Maintainer: Nicolas Casajus nicolas.casajus@fondationbiodiversite.fr (ORCID) [copyright holder] Authors: Mattia Greco mgreco@iopan.pl (ORCID) Xavier Giraud giraud@cerege.fr (ORCID) Sonia Chaabane sonia.chaabane@fondationbiodiversite.fr (ORCID)","code":""},{"path":"https://frbcesab.github.io/forcis/reference/geom_basemap.html","id":null,"dir":"Reference","previous_headings":"","what":"Add a World basemap to a ggplot object — geom_basemap","title":"Add a World basemap to a ggplot object — geom_basemap","text":"Creates World base map can added ggplot object. Spatial layers come Natural Earth project (https://www.naturalearthdata.com/) defined Robinson coordinate system.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/geom_basemap.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Add a World basemap to a ggplot object — geom_basemap","text":"","code":"geom_basemap()"},{"path":"https://frbcesab.github.io/forcis/reference/geom_basemap.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Add a World basemap to a ggplot object — geom_basemap","text":"ggplot object.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/geom_basemap.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Add a World basemap to a ggplot object — geom_basemap","text":"","code":"# Attach packages ---- library(\"forcis\") library(\"ggplot2\") # World basemap ---- ggplot() + geom_basemap()"},{"path":"https://frbcesab.github.io/forcis/reference/get_available_versions.html","id":null,"dir":"Reference","previous_headings":"","what":"Get available versions of the FORCIS database — get_available_versions","title":"Get available versions of the FORCIS database — get_available_versions","text":"Gets available versions FORCIS database querying Zenodo API (https://developers.zenodo.org).","code":""},{"path":"https://frbcesab.github.io/forcis/reference/get_available_versions.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get available versions of the FORCIS database — get_available_versions","text":"","code":"get_available_versions()"},{"path":"https://frbcesab.github.io/forcis/reference/get_available_versions.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get available versions of the FORCIS database — get_available_versions","text":"data.frame three columns: publication_date: date release version version: label version access_right: version open restricted?","code":""},{"path":"https://frbcesab.github.io/forcis/reference/get_available_versions.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get available versions of the FORCIS database — get_available_versions","text":"","code":"# Attach the package ---- library(\"forcis\") # Versions of the FORCIS database ---- get_available_versions() #> publication_date version access_right #> 1 2024-07-11 10 open #> 2 2024-07-08 09 open #> 3 2024-02-09 08 open #> 4 2023-12-14 07 open #> 5 2023-12-12 06 open #> 6 2023-09-14 05 open #> 7 2023-07-26 04 open #> 8 2023-06-14 03 open #> 9 2023-05-24 02 open #> 10 2022-12-02 01 restricted"},{"path":"https://frbcesab.github.io/forcis/reference/get_current_version.html","id":null,"dir":"Reference","previous_headings":"","what":"Get the version of the FORCIS database currently used — get_current_version","title":"Get the version of the FORCIS database currently used — get_current_version","text":"Returns version FORCIS database currently used project. function read content hidden file .forcis created function download_forcis_db(). file keeps track latest version database used dedicated project. information, please read vignette available https://frbcesab.github.io/forcis/articles/database-versions.html.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/get_current_version.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get the version of the FORCIS database currently used — get_current_version","text":"","code":"get_current_version()"},{"path":"https://frbcesab.github.io/forcis/reference/get_current_version.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get the version of the FORCIS database currently used — get_current_version","text":"character length 1, .e. label version use.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/get_current_version.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get the version of the FORCIS database currently used — get_current_version","text":"","code":"if (FALSE) { # \\dontrun{ # Attach the package ---- library(\"forcis\") # Folder in which the database will be saved ---- path_to_save_db <- \"data\" # Download the database ---- download_forcis_db(path = path_to_save_db, version = NULL) # Get the version of the database ---- get_current_version() } # }"},{"path":"https://frbcesab.github.io/forcis/reference/get_ocean_names.html","id":null,"dir":"Reference","previous_headings":"","what":"Get World ocean names — get_ocean_names","title":"Get World ocean names — get_ocean_names","text":"function returns name World oceans according IHO Sea Areas dataset version 3 (Flanders Marine Institute, 2018).","code":""},{"path":"https://frbcesab.github.io/forcis/reference/get_ocean_names.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get World ocean names — get_ocean_names","text":"","code":"get_ocean_names()"},{"path":"https://frbcesab.github.io/forcis/reference/get_ocean_names.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get World ocean names — get_ocean_names","text":"character vector World ocean names.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/get_ocean_names.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Get World ocean names — get_ocean_names","text":"Flanders Marine Institute (2018). IHO Sea Areas, version 3. Available online : https://www.marineregions.org/. DOI: https://doi.org/10.14284/323.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/get_ocean_names.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get World ocean names — get_ocean_names","text":"","code":"if (FALSE) { # \\dontrun{ get_ocean_names() } # }"},{"path":"https://frbcesab.github.io/forcis/reference/get_required_columns.html","id":null,"dir":"Reference","previous_headings":"","what":"Get required column names — get_required_columns","title":"Get required column names — get_required_columns","text":"Gets required column names (except taxa names) package. function designed help users add additional columns select_columns() (argument cols) missing list.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/get_required_columns.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get required column names — get_required_columns","text":"","code":"get_required_columns()"},{"path":"https://frbcesab.github.io/forcis/reference/get_required_columns.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get required column names — get_required_columns","text":"character.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/get_required_columns.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get required column names — get_required_columns","text":"","code":"# Get required column names (expect taxa names) ---- get_required_columns() #> [1] \"data_type\" #> [2] \"cruise_id\" #> [3] \"profile_id\" #> [4] \"sample_id\" #> [5] \"sample_min_depth\" #> [6] \"sample_max_depth\" #> [7] \"profile_depth_min\" #> [8] \"profile_depth_max\" #> [9] \"profile_date_time\" #> [10] \"cast_net_op_m2\" #> [11] \"subsample_id\" #> [12] \"sample_segment_length\" #> [13] \"subsample_count_type\" #> [14] \"subsample_size_fraction_min\" #> [15] \"subsample_size_fraction_max\" #> [16] \"site_lat_start_decimal\" #> [17] \"site_lon_start_decimal\" #> [18] \"sample_volume_filtered\" #> [19] \"subsample_all_shells_present_were_counted\" #> [20] \"total_of_forams_counted_ind\" #> [21] \"sampling_device_type\""},{"path":"https://frbcesab.github.io/forcis/reference/get_species_names.html","id":null,"dir":"Reference","previous_headings":"","what":"Get species names from column names — get_species_names","title":"Get species names from column names — get_species_names","text":"Gets species names column names. function just utility easily retrieve taxon names.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/get_species_names.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get species names from column names — get_species_names","text":"","code":"get_species_names(data)"},{"path":"https://frbcesab.github.io/forcis/reference/get_species_names.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get species names from column names — get_species_names","text":"data data.frame. One obtained read_*_data() functions.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/get_species_names.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get species names from column names — get_species_names","text":"data.frame.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/get_species_names.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get species names from column names — get_species_names","text":"","code":"if (FALSE) { # \\dontrun{ # Folder in which the database is stored ---- path_to_db <- \"data\" # Download and read the plankton nets data ---- plankton_nets_data <- read_plankton_nets_data(path_to_db) # Select a taxonomy ---- plankton_nets_data <- select_taxonomy(plankton_nets_data, taxonomy = \"OT\") # Retrieve taxon names ---- get_species_names(nets) } # }"},{"path":"https://frbcesab.github.io/forcis/reference/get_version_info.html","id":null,"dir":"Reference","previous_headings":"","what":"Print information of a specific version of the FORCIS database — get_version_info","title":"Print information of a specific version of the FORCIS database — get_version_info","text":"Prints information specific version FORCIS database querying Zenodo API (https://developers.zenodo.org).","code":""},{"path":"https://frbcesab.github.io/forcis/reference/get_version_info.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Print information of a specific version of the FORCIS database — get_version_info","text":"","code":"get_version_info(version = NULL)"},{"path":"https://frbcesab.github.io/forcis/reference/get_version_info.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Print information of a specific version of the FORCIS database — get_version_info","text":"version character length 1. label version. Use get_available_versions() list available versions. NULL (default) latest version used.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/get_version_info.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Print information of a specific version of the FORCIS database — get_version_info","text":"list information version, including: title, doi, publication_date, description, access_right, creators, keywords, version, resource_type, license, files.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/get_version_info.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Print information of a specific version of the FORCIS database — get_version_info","text":"","code":"# Attach the package ---- library(\"forcis\") # Get information for the latest version of the FORCIS database ---- get_version_info() #> $title #> [1] \"The FORCIS database: A global census of planktonic Foraminifera from ocean waters\" #> #> $doi #> [1] \"10.5281/zenodo.12724286\" #> #> $publication_date #> [1] \"2024-07-11\" #> #> $description #> [1] \"The FORCIS (Foraminifera Response to Climatic Stress) database is a synthesis grouping datasets on living planktonic foraminifera. We assembled foraminiferal diversity and distribution data in the global oceans from 1910 until 2018, curating published and unpublished datasets. This database includes data collected using plankton tows, continuous plankton recorder, sediment traps and plankton pump from the global ocean.<\/p>\\n\\n The FORCIS database version 01 is composed of 5 files (“.csv” format). All data coming from different sampling devices were put into separate “.csv” files. Only the data of the CPR from the Southern Hemisphere have been separated from the Northern Hemisphere CPR data as the data structure is not the same (species counts resolved vs. binned total counts, respectively). <\/p>\\n\\n Apart from the file of CPR data from the Northern Hemisphere that contains only metadata and binned total counts, all the remaining four files contain 4 blocks:<\/p>\\n\\n \\n\\t- \\n\\t
Block 1: metadata (from column 1 to 71)<\/p>\\n\\t<\/li>\\n\\t - \\n\\t
Block 2: original counts (from column 72 to 274)<\/p>\\n\\t<\/li>\\n\\t - \\n\\t
Block 3: generated counts based on the validated taxonomy (from column 275 to 331). We added “_VT” to each species name to distinguish it from other taxonomy levels. E.g. “g_bulloides” became “g_bulloides_VT”. The number of species counted per subsample is also reported in the column “number_of_species_counted_VT”<\/p>\\n\\t<\/li>\\n\\t - \\n\\t
Block 4: generated counts based on the lumped taxonomy (from column 332 to 379). In this case, we added “_LT” to each species name. E.g. “n_dutertrei” became “n_dutertrei_VT”. We also calculated the number of species counted per subsample and reported it in the column “number_of_species_counted_LT”<\/p>\\n\\t<\/li>\\n<\/ul>\\n\\n Foraminifera abundance data counts are reported in different categories in the blocks 1,2 and 3 and described in the table below:<\/p>\\n\\n \\n\\t\\n\\t\\t\\n\\t\\t\\t| \\n\\t\\t\\t count_type<\/strong><\/p>\\n\\t\\t\\t<\/td>\\n\\t\\t\\t| \\n\\t\\t\\t unit<\/strong><\/p>\\n\\t\\t\\t<\/td>\\n\\t\\t<\/tr>\\n\\t\\t\\n\\t\\t\\t| \\n\\t\\t\\t Absolute<\/p>\\n\\t\\t\\t<\/td>\\n\\t\\t\\t | \\n\\t\\t\\t ind/m3<\/p>\\n\\t\\t\\t<\/td>\\n\\t\\t<\/tr>\\n\\t\\t | \\n\\t\\t\\t| \\n\\t\\t\\t Relative<\/p>\\n\\t\\t\\t<\/td>\\n\\t\\t\\t | \\n\\t\\t\\t %<\/p>\\n\\t\\t\\t<\/td>\\n\\t\\t<\/tr>\\n\\t\\t | \\n\\t\\t\\t| \\n\\t\\t\\t Raw<\/p>\\n\\t\\t\\t<\/td>\\n\\t\\t\\t | \\n\\t\\t\\t number of individuals<\/p>\\n\\t\\t\\t<\/td>\\n\\t\\t<\/tr>\\n\\t\\t | \\n\\t\\t\\t| \\n\\t\\t\\t Fluxes<\/p>\\n\\t\\t\\t<\/td>\\n\\t\\t\\t | \\n\\t\\t\\t ind/m2/day<\/p>\\n\\t\\t\\t<\/td>\\n\\t\\t<\/tr>\\n\\t\\t | \\n\\t\\t\\t| \\n\\t\\t\\t Bin_Absolute<\/p>\\n\\t\\t\\t<\/td>\\n\\t\\t\\t | \\n\\t\\t\\t ind/m3<\/p>\\n\\t\\t\\t<\/td>\\n\\t\\t<\/tr>\\n\\t\\t | \\n\\t\\t\\t| \\n\\t\\t\\t Bin_Relative<\/p>\\n\\t\\t\\t<\/td>\\n\\t\\t\\t | \\n\\t\\t\\t %<\/p>\\n\\t\\t\\t<\/td>\\n\\t\\t<\/tr>\\n\\t\\t | \\n\\t\\t\\t| \\n\\t\\t\\t Bin_Raw<\/p>\\n\\t\\t\\t<\/td>\\n\\t\\t\\t | \\n\\t\\t\\t number of individuals<\/p>\\n\\t\\t\\t<\/td>\\n\\t\\t<\/tr>\\n\\t\\t | \\n\\t\\t\\t| \\n\\t\\t\\t Bin_Fluxes<\/p>\\n\\t\\t\\t<\/td>\\n\\t\\t\\t | \\n\\t\\t\\t ind/m2/day<\/p>\\n\\t\\t\\t<\/td>\\n\\t\\t<\/tr>\\n\\t<\/tbody>\\n<\/table>\\n\\n <\/p>\\n\\n For more details about the FORCIS database column description, please check the data descriptor paper Chaabane et al. (2023) (https://doi.org/10.1038/s41597-023-02264-2).<\/strong><\/p>\\n\\nThe database is kept open for any new entries and the updated version will be released in csv format. The labels of updated versions of the released “.csv” files will contain the date of their publication and versioning number.<\/p>\" #> #> $access_right #> [1] \"open\" #> #> $creators #> $creators[[1]] #> name affiliation #> 1 Chaabane, Sonia CEREGE, France and Max Planck, Germany #> 2 de Garidel, Thibault CEREGE, France #> 3 Giraud, Xavier CEREGE, France #> 4 Schiebel, Ralf Max Planck, Germany #> 5 Beaugrand, Gregory LOG, France #> 6 Brummer, Geert-Jan NIOZ, Netherlands #> 7 Casajus, Nicolas FRB CESAB #> 8 Greco, Mattia Polish Academy of Sciences, Poland #> 9 Grigoratou, Maria Mercator Ocean International, France #> 10 Howa, Hélène LPG-BIAF, France #> 11 Jonkers, Lukas MARUM, Germany #> 12 Kucera, Michal MARUM, Germany #> 13 Kuroyanagi, Azumi Tohoku Univ., Japan #> 14 Meilland, Julie MARUM, Germany #> 15 Monteiro, Fanny BRIDGE, UK #> 16 Mortyn, Graham ICTA UAB, Spain #> 17 Almogi-Labin Ahuva #> 18 Asahi Hirofumi #> 19 Avnaim-Katav Simona #> 20 Bassinot Franck #> 21 Davis Catherine V. #> 22 Field David B. #> 23 Hernandez-Almeida Ivan #> 24 Herut Barak #> 25 Hosie Graham #> 26 Howard Will #> 27 Jentzen Anna #> 28 Johns David G. #> 29 Keigwin Lloyd #> 30 Kitchener John #> 31 Kohfeld Karen E. #> 32 Lessa Douglas V.O. #> 33 Manno Clara #> 34 Marchant Margarita #> 35 Ofstad Siri #> 36 Ortiz Joseph D. #> 37 Post Alexandra #> 38 Rigual-Hernandez Andres #> 39 Rillo Marina C. #> 40 Robinson Karen #> 41 Sagawa Takuya #> 42 Sierro Francisco #> 43 Takahashi Kunio T. #> 44 Torfstein Adi #> 45 Venancio Igor #> 46 Yamasaki Makoto #> 47 Ziveri Patrizia #> orcid #> 1 0000-0002-4653-8610 #> 2 0000-0001-8983-9571 #> 3 0000-0002-6252-7647 #> 4 0000-0001-5067-8176 #> 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 #> #> #> $keywords #> $keywords[[1]] #> [1] \"Planktonic Foraminifera\" \"FORCIS database\" #> [3] \"Biodiversity\" #> #> #> $version #> [1] \"10\" #> #> $resource_type #> [1] \"dataset\" #> #> $license #> id #> 10 cc-by-4.0 #> #> $files #> id key size #> 1 1c00f40e-85d4-4e39-99eb-30411aace76e iho_oceans_boundaries.rds 9198965 #> 2 e299ff1a-71f9-426e-9762-059e410b0c60 FORCIS_cpr_north_11072024.csv 67556549 #> 3 26bf5117-9215-42a6-b53f-f4c36d39fa39 FORCIS_data_template.xlsx 357853 #> 4 07439fa9-ec45-44ca-8c1d-b57b1f45f371 FORCIS_taxonomy_levels.xlsx 24998 #> 5 70c5a9c8-4ff4-49bd-b1c7-f72a8e8e6c2d FORCIS_net_11072024.csv 27189945 #> 6 3d3c0c0b-4635-4f51-a3c4-ca7090312277 FORCIS_cpr_south_11072024.csv 64583224 #> 7 bfb3f092-e40c-499f-b14e-8d6f62295f89 FORCIS_pump_11072024.csv 649676 #> 8 08699afd-f95e-411b-b956-af10ef25a5a0 FORCIS_trap_11072024.csv 13270806 #> checksum #> 1 md5:ff8d2f16650ef1f0cdcb4c3986112648 #> 2 md5:a32bbb863fe795cfcb953ca8928fd9c8 #> 3 md5:ef3c3d67f1824c026fe6fb36aef0b56b #> 4 md5:e12a45e2d34def4c1642353597a04bf8 #> 5 md5:18be71f701075318d7b0a0782d1effc7 #> 6 md5:c9e410a749e513c2023780990fc9169e #> 7 md5:9bee5c30a35dacb623dc7ac4ff564117 #> 8 md5:76bac6d2c85f699da059bfd48334baf4 #> self #> 1 https://zenodo.org/api/records/12724286/files/iho_oceans_boundaries.rds/content #> 2 https://zenodo.org/api/records/12724286/files/FORCIS_cpr_north_11072024.csv/content #> 3 https://zenodo.org/api/records/12724286/files/FORCIS_data_template.xlsx/content #> 4 https://zenodo.org/api/records/12724286/files/FORCIS_taxonomy_levels.xlsx/content #> 5 https://zenodo.org/api/records/12724286/files/FORCIS_net_11072024.csv/content #> 6 https://zenodo.org/api/records/12724286/files/FORCIS_cpr_south_11072024.csv/content #> 7 https://zenodo.org/api/records/12724286/files/FORCIS_pump_11072024.csv/content #> 8 https://zenodo.org/api/records/12724286/files/FORCIS_trap_11072024.csv/content #>"},{"path":"https://frbcesab.github.io/forcis/reference/ggmap_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Map the spatial distribution of FORCIS data — ggmap_data","title":"Map the spatial distribution of FORCIS data — ggmap_data","text":"Maps spatial distribution FORCIS data.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/ggmap_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Map the spatial distribution of FORCIS data — ggmap_data","text":"","code":"ggmap_data(data, col = \"red\", ...)"},{"path":"https://frbcesab.github.io/forcis/reference/ggmap_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Map the spatial distribution of FORCIS data — ggmap_data","text":"data data.frame. One obtained read_*_data() functions. col character length 1. color data map. ... graphical parameters passed geom_sf().","code":""},{"path":"https://frbcesab.github.io/forcis/reference/ggmap_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Map the spatial distribution of FORCIS data — ggmap_data","text":"ggplot object.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/ggmap_data.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Map the spatial distribution of FORCIS data — ggmap_data","text":"","code":"# Attach the package ---- library(\"forcis\") # Import example dataset ---- file_name <- system.file(file.path(\"extdata\", \"FORCIS_net_sample.csv\"), package = \"forcis\") net_data <- read.table(file_name, dec = \".\", sep = \";\") # Add 'data_type' column ---- net_data$\"data_type\" <- \"Net\" # Map data (default) ---- ggmap_data(net_data) # Map data ---- ggmap_data(net_data, col = \"black\", fill = \"red\", shape = 21, size = 2)"},{"path":"https://frbcesab.github.io/forcis/reference/plot_record_by_depth.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot sample records by depth of collection — plot_record_by_depth","title":"Plot sample records by depth of collection — plot_record_by_depth","text":"function produces barplot FORCIS sample records depth.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/plot_record_by_depth.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot sample records by depth of collection — plot_record_by_depth","text":"","code":"plot_record_by_depth(data)"},{"path":"https://frbcesab.github.io/forcis/reference/plot_record_by_depth.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot sample records by depth of collection — plot_record_by_depth","text":"data data.frame, .e. FORCIS dataset.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/plot_record_by_depth.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot sample records by depth of collection — plot_record_by_depth","text":"ggplot object.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/plot_record_by_depth.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot sample records by depth of collection — plot_record_by_depth","text":"","code":"# Attach the package ---- library(\"forcis\") # Import example dataset ---- file_name <- system.file(file.path(\"extdata\", \"FORCIS_net_sample.csv\"), package = \"forcis\") net_data <- read.table(file_name, dec = \".\", sep = \";\") # Add 'data_type' column ---- net_data$\"data_type\" <- \"Net\" # Plot data by year (example dataset) ---- plot_record_by_depth(net_data)"},{"path":"https://frbcesab.github.io/forcis/reference/plot_record_by_month.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot sample records by month — plot_record_by_month","title":"Plot sample records by month — plot_record_by_month","text":"function produces barplot FORCIS sample records month.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/plot_record_by_month.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot sample records by month — plot_record_by_month","text":"","code":"plot_record_by_month(data)"},{"path":"https://frbcesab.github.io/forcis/reference/plot_record_by_month.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot sample records by month — plot_record_by_month","text":"data data.frame, .e. FORCIS dataset.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/plot_record_by_month.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot sample records by month — plot_record_by_month","text":"ggplot object.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/plot_record_by_month.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot sample records by month — plot_record_by_month","text":"","code":"# Attach the package ---- library(\"forcis\") # Import example dataset ---- file_name <- system.file(file.path(\"extdata\", \"FORCIS_net_sample.csv\"), package = \"forcis\") net_data <- read.table(file_name, dec = \".\", sep = \";\") # Add 'data_type' column ---- net_data$\"data_type\" <- \"Net\" # Plot data by year (example dataset) ---- plot_record_by_month(net_data)"},{"path":"https://frbcesab.github.io/forcis/reference/plot_record_by_season.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot sample records by season — plot_record_by_season","title":"Plot sample records by season — plot_record_by_season","text":"function produces barplot FORCIS sample records season.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/plot_record_by_season.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot sample records by season — plot_record_by_season","text":"","code":"plot_record_by_season(data)"},{"path":"https://frbcesab.github.io/forcis/reference/plot_record_by_season.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot sample records by season — plot_record_by_season","text":"data data.frame, .e. FORCIS dataset.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/plot_record_by_season.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot sample records by season — plot_record_by_season","text":"ggplot object.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/plot_record_by_season.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot sample records by season — plot_record_by_season","text":"","code":"# Attach the package ---- library(\"forcis\") # Import example dataset ---- file_name <- system.file(file.path(\"extdata\", \"FORCIS_net_sample.csv\"), package = \"forcis\") net_data <- read.table(file_name, dec = \".\", sep = \";\") # Add 'data_type' column ---- net_data$\"data_type\" <- \"Net\" # Plot data by year (example dataset) ---- plot_record_by_season(net_data)"},{"path":"https://frbcesab.github.io/forcis/reference/plot_record_by_year.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot sample records by year — plot_record_by_year","title":"Plot sample records by year — plot_record_by_year","text":"function produces barplot FORCIS sample records year.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/plot_record_by_year.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot sample records by year — plot_record_by_year","text":"","code":"plot_record_by_year(data)"},{"path":"https://frbcesab.github.io/forcis/reference/plot_record_by_year.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot sample records by year — plot_record_by_year","text":"data data.frame, .e. FORCIS dataset.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/plot_record_by_year.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot sample records by year — plot_record_by_year","text":"ggplot object.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/plot_record_by_year.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot sample records by year — plot_record_by_year","text":"","code":"# Attach the package ---- library(\"forcis\") # Import example dataset ---- file_name <- system.file(file.path(\"extdata\", \"FORCIS_net_sample.csv\"), package = \"forcis\") net_data <- read.table(file_name, dec = \".\", sep = \";\") # Add 'data_type' column ---- net_data$\"data_type\" <- \"Net\" # Plot data by year (example dataset) ---- plot_record_by_year(net_data)"},{"path":"https://frbcesab.github.io/forcis/reference/read_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Read FORCIS data — read_cpr_north_data","title":"Read FORCIS data — read_cpr_north_data","text":"functions read one specific csv file FORCIS database (see ) stored folder path. function download_forcis_db() must used first store locally database.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/read_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read FORCIS data — read_cpr_north_data","text":"","code":"read_cpr_north_data( path = \".\", version = options()$forcis_version, check_for_update = options()$check_for_update ) read_cpr_south_data( path = \".\", version = options()$forcis_version, check_for_update = options()$check_for_update ) read_plankton_nets_data( path = \".\", version = options()$forcis_version, check_for_update = options()$check_for_update ) read_pump_data( path = \".\", version = options()$forcis_version, check_for_update = options()$check_for_update ) read_sediment_trap_data( path = \".\", version = options()$forcis_version, check_for_update = options()$check_for_update )"},{"path":"https://frbcesab.github.io/forcis/reference/read_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read FORCIS data — read_cpr_north_data","text":"path character length 1. folder FORCIS database saved. version character length 1. version number (two numbers, e.g. 08 instead 8) FORCIS database use. Default latest version. Note argument can handle global option forcis_version. example, user calls options(forcis_version = \"07\"), version 07 used default current R session. Note recommended use latest version database. check_for_update logical. TRUE (default) function check newer version FORCIS database available Zenodo print informative message. Note argument can handle global option check_for_update. example, user calls options(check_for_update = FALSE), message download latest version disabled current R session.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/read_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read FORCIS data — read_cpr_north_data","text":"data.frame. See https://zenodo.org/doi/10.5281/zenodo.7390791 preview datasets.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/read_data.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Read FORCIS data — read_cpr_north_data","text":"read_plankton_nets_data() reads FORCIS plankton nets data read_pump_data() reads FORCIS pump data read_cpr_north_data() reads FORCIS CPR North data read_cpr_south_data() reads FORCIS CPR South data read_sediment_trap_data() reads FORCIS sediment traps data","code":""},{"path":[]},{"path":"https://frbcesab.github.io/forcis/reference/read_data.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read FORCIS data — read_cpr_north_data","text":"","code":"if (FALSE) { # \\dontrun{ # Attach the package ---- library(\"forcis\") # Folder in which the database will be saved ---- path_to_save_db <- \"data\" # Download the database ---- download_forcis_db(path = path_to_save_db) # Import plankton nets data ---- plankton_nets_data <- read_plankton_nets_data(path = path_to_save_db) } # }"},{"path":"https://frbcesab.github.io/forcis/reference/reshape_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Reshape and simplify FORCIS data — reshape_data","title":"Reshape and simplify FORCIS data — reshape_data","text":"Reshapes FORCIS data pivoting species columns two columns: taxa (taxon names) counts (taxon abundances). converts wider data.frame long format.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/reshape_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Reshape and simplify FORCIS data — reshape_data","text":"","code":"reshape_data(data)"},{"path":"https://frbcesab.github.io/forcis/reference/reshape_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Reshape and simplify FORCIS data — reshape_data","text":"data data.frame, .e. FORCIS dataset, except CPR North data.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/reshape_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Reshape and simplify FORCIS data — reshape_data","text":"data.frame reshaped long format.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/reshape_data.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Reshape and simplify FORCIS data — reshape_data","text":"","code":"# Attach the package ---- library(\"forcis\") # Import example dataset ---- file_name <- system.file(file.path(\"extdata\", \"FORCIS_net_sample.csv\"), package = \"forcis\") net_data <- read.table(file_name, dec = \".\", sep = \";\") # Add 'data_type' column ---- net_data$\"data_type\" <- \"Net\" # Dimensions of the data.frame ---- dim(net_data) #> [1] 2451 77 # Reshape data ---- net_data <- reshape_data(net_data) # Dimensions of the data.frame ---- dim(net_data) #> [1] 137256 23 # Column names ---- colnames(net_data) #> [1] \"data_type\" #> [2] \"cruise_id\" #> [3] \"profile_id\" #> [4] \"sample_id\" #> [5] \"sample_min_depth\" #> [6] \"sample_max_depth\" #> [7] \"profile_depth_min\" #> [8] \"profile_depth_max\" #> [9] \"profile_date_time\" #> [10] \"cast_net_op_m2\" #> [11] \"subsample_id\" #> [12] \"sample_segment_length\" #> [13] \"subsample_count_type\" #> [14] \"subsample_size_fraction_min\" #> [15] \"subsample_size_fraction_max\" #> [16] \"site_lat_start_decimal\" #> [17] \"site_lon_start_decimal\" #> [18] \"sample_volume_filtered\" #> [19] \"subsample_all_shells_present_were_counted\" #> [20] \"total_of_forams_counted_ind\" #> [21] \"sampling_device_type\" #> [22] \"taxa\" #> [23] \"counts\""},{"path":"https://frbcesab.github.io/forcis/reference/select_columns.html","id":null,"dir":"Reference","previous_headings":"","what":"Select columns in FORCIS data — select_columns","title":"Select columns in FORCIS data — select_columns","text":"Selects columns FORCIS data. FORCIS data contains 100 columns, function can used lighten data.frame easily handle speed computations.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/select_columns.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Select columns in FORCIS data — select_columns","text":"","code":"select_columns(data, cols = NULL)"},{"path":"https://frbcesab.github.io/forcis/reference/select_columns.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Select columns in FORCIS data — select_columns","text":"data data.frame. One obtained read_*_data() functions. cols character vector column names keep addition required ones (see get_required_columns()) taxa columns. Can NULL (default).","code":""},{"path":"https://frbcesab.github.io/forcis/reference/select_columns.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Select columns in FORCIS data — select_columns","text":"data.frame.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/select_columns.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Select columns in FORCIS data — select_columns","text":"","code":"# Attach the package ---- library(\"forcis\") # Import example dataset ---- file_name <- system.file(file.path(\"extdata\", \"FORCIS_net_sample.csv\"), package = \"forcis\") net_data <- read.table(file_name, dec = \".\", sep = \";\") # Add 'data_type' column ---- net_data$\"data_type\" <- \"Net\" # Dimensions of the data.frame ---- dim(net_data) #> [1] 2451 77 # Select a taxonomy ---- net_data <- select_taxonomy(net_data, taxonomy = \"VT\") # Dimensions of the data.frame ---- dim(net_data) #> [1] 2451 77 # Select only required columns (and taxa) ---- net_data <- select_columns(net_data) # Dimensions of the data.frame ---- dim(net_data) #> [1] 2451 77"},{"path":"https://frbcesab.github.io/forcis/reference/select_taxonomy.html","id":null,"dir":"Reference","previous_headings":"","what":"Select a taxonomy in FORCIS data — select_taxonomy","title":"Select a taxonomy in FORCIS data — select_taxonomy","text":"Selects taxonomy FORCIS data. FORCIS database provides three different taxonomies: \"LT\" (lumped taxonomy), \"VT\" (validated taxonomy) \"OT\" (original taxonomy). See https://doi.org/10.1038/s41597-023-02264-2 information.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/select_taxonomy.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Select a taxonomy in FORCIS data — select_taxonomy","text":"","code":"select_taxonomy(data, taxonomy)"},{"path":"https://frbcesab.github.io/forcis/reference/select_taxonomy.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Select a taxonomy in FORCIS data — select_taxonomy","text":"data data.frame. One obtained read_*_data() functions. taxonomy character length 1. One among \"LT\", \"VT\", \"OT\".","code":""},{"path":"https://frbcesab.github.io/forcis/reference/select_taxonomy.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Select a taxonomy in FORCIS data — select_taxonomy","text":"data.frame.","code":""},{"path":"https://frbcesab.github.io/forcis/reference/select_taxonomy.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Select a taxonomy in FORCIS data — select_taxonomy","text":"","code":"# Attach the package ---- library(\"forcis\") # Import example dataset ---- file_name <- system.file(file.path(\"extdata\", \"FORCIS_net_sample.csv\"), package = \"forcis\") net_data <- read.table(file_name, dec = \".\", sep = \";\") # Add 'data_type' column ---- net_data$\"data_type\" <- \"Net\" # Dimensions of the data.frame ---- dim(net_data) #> [1] 2451 77 # Select a taxonomy ---- net_data <- select_taxonomy(net_data, taxonomy = \"VT\") # Dimensions of the data.frame ---- dim(net_data) #> [1] 2451 77"},{"path":[]}]
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