R/format_catches.R
In ices-tools-prod/icesFO: Functions to support the creation of ICES Fisheries Overviews
Defines functions
format_catches
Documented in
format_catches
#' Format the data from the time-series of ICES historical, official and preliminary catches.
#'
#' Format the data from the ICES Stock Assessment Database for the downloaded year and the specific Ecoregion
#' for which you are producing the Fisheries Overviews.
#'
#' @param year the year required
#' @param historical a dataframe output from load_historical_catches() required.
#' @param official a dataframe output from load_official_catches() required.
#' @param preliminary a dataframe output from load_preliminary_catches() optional.
#' @param ecoregion an identifier of the Ecoregion of interest
#' @param species_list a list of species common names and scientific names
#' from ASFIS
#' @param sid the main table from ICES Stock Information DB (SD)
#'
#' @return A data frame..
#'
#' @note
#' Can add some helpful information here
#'
#' @seealso
#' \code{\link{format_sid}} for formatting raw data from the ICES Stock Information database.
#'
#' \code{\link{icesFO-package}} gives an overview of the package.
#'
#' @examples
#' \dontrun{
#' sid <- load_sid(2019)
#' species_list <- load_asfis_species()
#' historical <- load_historical_catches()
#' official <- load_official_catches()
#' preliminary <- load_preliminary_catches(2018)
#' catches_format <-
#' format_catches(2019, "Celtic Seas", historical, official, preliminary,
#' species_list, sid)
#' }
#'
#' @references
#'
#' The ICES stock information Database web sevices: \url{http://sid.ices.dk/services/}
#'
#' @export
format_catches <- function(year, ecoregion, historical, official, preliminary = NULL, species_list, sid) {
fish_category <- dplyr::mutate(sid, X3A_CODE = substr(sid$StockKeyLabel, start = 1, stop = 3))
fish_category <- dplyr::select(fish_category, X3A_CODE, FisheriesGuild)
fish_category$X3A_CODE <- toupper(fish_category$X3A_CODE)
fish_category <- unique(fish_category)
# fish_category<- fish_category[complete.cases(fish_category),]
historic_bs <- c("III (not specified)", "III b Baltic 23",
"III b+c (not specified)", "III b-d (not specified)",
"III c Baltic 22", "III d (not specified)",
"III d Baltic 24", "III d Baltic 25",
"III d Baltic 26", "III d Baltic 27",
"III d Baltic 28 (not specified)", "III d Baltic 28-1",
"III d Baltic 28-2", "III d Baltic 29",
"III d Baltic 30", "III d Baltic 31",
"III d Baltic 32")
historic_ns <- c("III a", "IIIa and IV (not specified)",
"IIIa and IVa+b (not specified)", "IV (not specified)",
"IV a", "IV a+b (not specified)",
"IV b", "IV b+c (not specified)",
"IV c", "VII d")
historic_uk <- paste0(c("^UK", "^Channel", "^Isle of Man"),
collapse = "|")
#these historical catches definition need decission on conflicts
historic_bob <- c("VIII a", "VIII b", "VIII c", "VIII d2", "VIII e2",
"IX a", "IX b2", "VIII d (not specified)", "VIII (not specified)","VIII e (not specified)", "IX (not specified)",
"IX b (not specified)")
historic_cs <- c("VI a", "VI b2", "VII a", "VII b", "VII c2", "VII f", "VII g", "VII h",
"VII j2", "VII k2", "VII (not specified)", "VII b+c (not specified)",
"VII c (not specified)", "VII d-k (not specified)", "VII f-k (not specified)",
"VII g-k (not specified)", "VII j (not specified)")
historic_is <- c("V a (North-East)", "V a (South-West)", "V a1", "V a (not specified)", "V a2")
historic_az <- c("X (not specified)", "X a (not specified)")
historic_gs <- c("XII a3", "II (not specified)", "II b (not specified)", "II b2", "V (not specified)", "V a (North-East)", "V a (not specified)",
"V a (South-West)", "V a+b1 (not specified)", "V a2", "XII (not specified)", "XII a (not specified)", "XIV (not specified)",
"XIV a", "XIV b (not specified)", "XIV b2" )
if(ecoregion == "Norwegian Sea"){
historic_nw <- c( "II a1", "II b1", "I and IIa (not specified)","II a (not specified)",
"II (not specified)", "II a2", "II b (not specified)",
"II b2", "XIV", "XIVa" )
}
if(ecoregion == "Barents Sea"){
historic_br <- c( "I (not specified)", "I a","I b", "I and IIa (not specified)","II a (not specified)",
"II (not specified)", "II a2", "II b (not specified)",
"II b2" )
}
historical[is.na(historical)] <- 0
catch_dat_1950 <- tidyr::gather(historical, YEAR, VALUE, -Country, -Species, -Division)
catch_dat_1950 <-
dplyr::mutate(catch_dat_1950, YEAR = as.numeric(gsub("X", "", YEAR)),
VALUE = ifelse(VALUE == "<0.5",
as.numeric(0),
VALUE),
VALUE = ifelse(!is.na(VALUE),
as.numeric(VALUE),
NA),
Country = dplyr::case_when(
grepl(historic_uk, Country) ~ "United Kingdom",
grepl("^Germany", Country) ~ "Germany",
Country %in% c("Un. Sov. Soc. Rep.") ~ "Russian Federation",
grepl("Faeroe Islands", Country) ~ "Faroe Islands",
grepl("Other nei", Country) ~ "OTHER",
TRUE ~ Country
),
ISO3 = countrycode::countrycode(Country, "country.name", "iso3c", warn = FALSE),
ECOREGION = dplyr::case_when(
Division %in% historic_bs ~ "Baltic Sea",
Division %in% historic_ns ~ "Greater North Sea",
Division %in% historic_bob ~ "Bay of Biscay and the Iberian Coast",
Division %in% historic_cs ~ "Celtic Seas",
Division %in% historic_is ~ "Icelandic Waters",
Division %in% historic_az ~ "Azores",
Division %in% historic_gs ~ "Greenland Sea",
if(ecoregion == "Norwegian Sea"){
Division %in% historic_nw ~ "Norwegian Sea"
},
if(ecoregion == "Barents Sea"){
Division %in% historic_br ~ "Barents Sea"
},
TRUE ~ "OTHER"))
catch_dat_1950 <- dplyr::filter(catch_dat_1950, YEAR <= 2005)
catch_dat_1950 <- dplyr::left_join(catch_dat_1950, y = species_list, c("Species" = "English_name"))# Merge to add FAO species information
catch_dat_1950 <- dplyr::left_join(catch_dat_1950, y = species_list,c("Species" = "Scientific_name", # Merge to add FAO species information
"X3A_CODE"))
catch_dat_1950 <- dplyr::left_join(catch_dat_1950, y = fish_category, by = "X3A_CODE")
catch_dat_1950 <- dplyr::select(catch_dat_1950,YEAR,
COUNTRY = Country,
ISO3,
GUILD = FisheriesGuild,
ECOREGION,
SPECIES_NAME = Scientific_name,
SPECIES_CODE = X3A_CODE,
COMMON_NAME = Species,
VALUE)
# add in official
catch_dat_2010 <- tidyr::gather(official, YEAR, VALUE, -Country, -Species, -Area, -Units)
catch_dat_2010 <- dplyr::filter(catch_dat_2010, Country != "")
catch_dat_2010 <- dplyr::mutate(catch_dat_2010,YEAR = as.numeric(gsub("X", "", YEAR)),
VALUE = as.numeric(VALUE),
Country = countrycode::countrycode(Country,"iso2c", "country.name"),
Country = ifelse(grepl("Guernsey|Isle of Man|Jersey", Country),
"United Kingdom",
Country),
ISO3 = countrycode::countrycode(Country, "country.name", "iso3c", warn = FALSE),
Country = gsub("(United Kingdom) .*", "\\1", Country),
Area = tolower(Area),
ECOREGION = dplyr::case_when(
Area %in% c("27.3.bc", "27.3.d", "27.3_nk") ~ "Baltic Sea",
Area %in% c("27.3.a", "27.4", "27.7.d") ~ "Greater North Sea",
Area %in% c("27.8.a", "27.8.b","27.8.c",
"27.8.d.2", "27.8.e.2", "27.9.a",
"27.9.b.2") ~ "Bay of Biscay and the Iberian Coast",
Area %in% c("27.6.a", "27.6.b.2","27.7.a", "27.7.b", "27.7.c.2",
"27.7.f", "27.7.g", "27.7.h","27.7.j.2", "27.7.k.2") ~ "Celtic Seas",
Area %in% c("27.5.a.1", "27.5.a.2","27.5.a_NK","27.5.a_nk","27.12.a.4") ~ "Icelandic Waters",
Area %in% c("27.10.a.2") ~ "Azores",
Area %in% c("27.12.a.3", "27.2.b.2", "27.5.a.2", "27.14.a", "27.14.b.2") ~ "Greenland Sea",
if(ecoregion == "Norwegian Sea"){
Area %in% c("27.2.a.1", "27.2.a.2","27.2.a_NK","27.2.a_nk", "27.2.b.1", "27.2.b.2", "27.2.b_NK","27.2.b_nk","27.14.a", "27.14_NK", "27.14_nk") ~ "Norwegian Sea"
},
if(ecoregion =="Barents Sea"){
Area %in% c("27.1.a", "27.1.b","27.2.a.2","27.2.a_NK","27.2.a_nk", "27.2.b.2","27.2.b_NK","27.2.b_nk", "27.1_NK", "27.1_nk") ~ "Barents Sea"
}))
catch_dat_2010 <- dplyr::left_join(catch_dat_2010,species_list, c("Species" = "X3A_CODE"))
catch_dat_2010 <- dplyr::left_join(catch_dat_2010,fish_category, by = c("Species" = "X3A_CODE"))
catch_dat_2010<- catch_dat_2010[!is.na(catch_dat_2010$ECOREGION),]
catch_dat_2010 <- dplyr::select(catch_dat_2010,YEAR,
COUNTRY = Country,
ISO3,
GUILD = FisheriesGuild,
ECOREGION,
SPECIES_NAME = Scientific_name,
SPECIES_CODE = Species,
COMMON_NAME = English_name,
VALUE)
catch_dat_2010 <- dplyr::group_by(catch_dat_2010,YEAR, COUNTRY, GUILD, ECOREGION,COMMON_NAME)
catch_dat_2010 <- dplyr::summarise(catch_dat_2010, VALUE = sum(VALUE))
# now do preliminary catches
catch_dat_prelim <- dplyr::filter(preliminary, Country != "")
# tidyr::gather(ï..Year, -Country, -AphiaID, -Area, -Catch) %>%
catch_dat_prelim <- dplyr::mutate(catch_dat_prelim, YEAR = Year,
VALUE = AMS.Catch.TLW.,
Country = countrycode::countrycode(Country,"iso2c", "country.name"),
Country = ifelse(grepl("Guernsey|Isle of Man|Jersey", Country),
"United Kingdom",
Country),
ISO3 = countrycode::countrycode(Country, "country.name", "iso3c", warn = FALSE),
Country = gsub("(United Kingdom) .*", "\\1", Country),
Area = tolower(Area))
#check why areas names are different!!
catch_dat_prelim <- dplyr::mutate(catch_dat_prelim, ECOREGION = dplyr::case_when(
Area %in% c("27_3_bc", "27_3_c_22","27_3_d","27_3_d_24","27_3_d_25","27_3_d_26","27_3_d_30",
"27_3_d_27","27_3_d_31","27_3_nk", "27_3_b_23", "27_3_d_28_2","27_3_d_32","27_3_d_29") ~ "Baltic Sea",
Area %in% c("27_3_a", "27_4_a","27_4_b", "27_4_c", "27_7_d") ~ "Greater North Sea",
Area %in% c("27_8_a", "27_8_b","27_8_c",
"27_8_d_2", "27_8_e_2", "27_9_a",
"27_9_b_2")~ "Bay of Biscay and the Iberian Coast",
Area %in% c("27_6_a", "27_6_b_2","27_7_a", "27_7_b", "27_7_c_2","27_7.e",
"27_7_f", "27_7_g", "27_7_h","27_7_j_2", "27_7_k_2")~"Celtic Seas",
Area %in% c("5_a_1", "5_a_2","12_a_4")~"Icelandic Waters",
Area %in% c("2_a_1", "2_a_2", "2_b_1", "2_b_2", "14.a")~"Norwegian Sea",
TRUE ~ "OTHER"))
catch_dat_prelim <- dplyr::filter(catch_dat_prelim,ECOREGION != "OTHER")
catch_dat_prelim <- dplyr::left_join(catch_dat_prelim, species_list, c("Species.Latin.Name" = "Scientific_name"))
catch_dat_prelim <- dplyr::left_join(catch_dat_prelim, fish_category, by = "X3A_CODE")
catch_dat_prelim <- dplyr::select(catch_dat_prelim,YEAR,
COUNTRY = Country,
ISO3,
GUILD = FisheriesGuild,
ECOREGION,
SPECIES_NAME = Species.Latin.Name,
SPECIES_CODE = X3A_CODE,
COMMON_NAME = English_name,
VALUE)
catch_dat_prelim$COMMON_NAME[which(catch_dat_prelim$SPECIES_NAME == "Ammodytes")] <- "Sandeels(=Sandlances) nei"
catch_dat_prelim$SPECIES_CODE[which(catch_dat_prelim$SPECIES_NAME == "Ammodytes")] <- "SAN"
if (is.null(preliminary)) {
df <- dplyr::bind_rows(catch_dat_2010,catch_dat_1950)
} else {
df <- dplyr::bind_rows(catch_dat_2010,catch_dat_1950, catch_dat_prelim)
}
df <- dplyr::ungroup(df)
df <- dplyr::mutate(df, GUILD = ifelse(is.na(GUILD),
"undefined",
GUILD))
df$COUNTRY<-gsub("Russian Federation", "\\Russia\\",df$COUNTRY)
df$COUNTRY<-gsub("Russia", "Russian Federation", df$COUNTRY)
df <- dplyr::select(df,YEAR,
COUNTRY,
ISO3,
GUILD ,
ECOREGION,
SPECIES_NAME,
SPECIES_CODE,
COMMON_NAME,
VALUE)
# df$GUILD[which(ices_catch_dat$SPECIES_CODE == "WHB")] <- "pelagic"
df <- dplyr::filter(df, ECOREGION %in% ecoregion)
return(df)
}
ices-tools-prod/icesFO documentation built on Aug. 28, 2020, 2:33 p.m.
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Defines functions format_catches
Documented in format_catches
#' Format the data from the time-series of ICES historical, official and preliminary catches.
#'
#' Format the data from the ICES Stock Assessment Database for the downloaded year and the specific Ecoregion
#' for which you are producing the Fisheries Overviews.
#'
#' @param year the year required
#' @param historical a dataframe output from load_historical_catches() required.
#' @param official a dataframe output from load_official_catches() required.
#' @param preliminary a dataframe output from load_preliminary_catches() optional.
#' @param ecoregion an identifier of the Ecoregion of interest
#' @param species_list a list of species common names and scientific names
#' from ASFIS
#' @param sid the main table from ICES Stock Information DB (SD)
#'
#' @return A data frame..
#'
#' @note
#' Can add some helpful information here
#'
#' @seealso
#' \code{\link{format_sid}} for formatting raw data from the ICES Stock Information database.
#'
#' \code{\link{icesFO-package}} gives an overview of the package.
#'
#' @examples
#' \dontrun{
#' sid <- load_sid(2019)
#' species_list <- load_asfis_species()
#' historical <- load_historical_catches()
#' official <- load_official_catches()
#' preliminary <- load_preliminary_catches(2018)
#' catches_format <-
#' format_catches(2019, "Celtic Seas", historical, official, preliminary,
#' species_list, sid)
#' }
#'
#' @references
#'
#' The ICES stock information Database web sevices: \url{http://sid.ices.dk/services/}
#'
#' @export
format_catches <- function(year, ecoregion, historical, official, preliminary = NULL, species_list, sid) {
fish_category <- dplyr::mutate(sid, X3A_CODE = substr(sid$StockKeyLabel, start = 1, stop = 3))
fish_category <- dplyr::select(fish_category, X3A_CODE, FisheriesGuild)
fish_category$X3A_CODE <- toupper(fish_category$X3A_CODE)
fish_category <- unique(fish_category)
# fish_category<- fish_category[complete.cases(fish_category),]
historic_bs <- c("III (not specified)", "III b Baltic 23",
"III b+c (not specified)", "III b-d (not specified)",
"III c Baltic 22", "III d (not specified)",
"III d Baltic 24", "III d Baltic 25",
"III d Baltic 26", "III d Baltic 27",
"III d Baltic 28 (not specified)", "III d Baltic 28-1",
"III d Baltic 28-2", "III d Baltic 29",
"III d Baltic 30", "III d Baltic 31",
"III d Baltic 32")
historic_ns <- c("III a", "IIIa and IV (not specified)",
"IIIa and IVa+b (not specified)", "IV (not specified)",
"IV a", "IV a+b (not specified)",
"IV b", "IV b+c (not specified)",
"IV c", "VII d")
historic_uk <- paste0(c("^UK", "^Channel", "^Isle of Man"),
collapse = "|")
#these historical catches definition need decission on conflicts
historic_bob <- c("VIII a", "VIII b", "VIII c", "VIII d2", "VIII e2",
"IX a", "IX b2", "VIII d (not specified)", "VIII (not specified)","VIII e (not specified)", "IX (not specified)",
"IX b (not specified)")
historic_cs <- c("VI a", "VI b2", "VII a", "VII b", "VII c2", "VII f", "VII g", "VII h",
"VII j2", "VII k2", "VII (not specified)", "VII b+c (not specified)",
"VII c (not specified)", "VII d-k (not specified)", "VII f-k (not specified)",
"VII g-k (not specified)", "VII j (not specified)")
historic_is <- c("V a (North-East)", "V a (South-West)", "V a1", "V a (not specified)", "V a2")
historic_az <- c("X (not specified)", "X a (not specified)")
historic_gs <- c("XII a3", "II (not specified)", "II b (not specified)", "II b2", "V (not specified)", "V a (North-East)", "V a (not specified)",
"V a (South-West)", "V a+b1 (not specified)", "V a2", "XII (not specified)", "XII a (not specified)", "XIV (not specified)",
"XIV a", "XIV b (not specified)", "XIV b2" )
if(ecoregion == "Norwegian Sea"){
historic_nw <- c( "II a1", "II b1", "I and IIa (not specified)","II a (not specified)",
"II (not specified)", "II a2", "II b (not specified)",
"II b2", "XIV", "XIVa" )
}
if(ecoregion == "Barents Sea"){
historic_br <- c( "I (not specified)", "I a","I b", "I and IIa (not specified)","II a (not specified)",
"II (not specified)", "II a2", "II b (not specified)",
"II b2" )
}
historical[is.na(historical)] <- 0
catch_dat_1950 <- tidyr::gather(historical, YEAR, VALUE, -Country, -Species, -Division)
catch_dat_1950 <-
dplyr::mutate(catch_dat_1950, YEAR = as.numeric(gsub("X", "", YEAR)),
VALUE = ifelse(VALUE == "<0.5",
as.numeric(0),
VALUE),
VALUE = ifelse(!is.na(VALUE),
as.numeric(VALUE),
NA),
Country = dplyr::case_when(
grepl(historic_uk, Country) ~ "United Kingdom",
grepl("^Germany", Country) ~ "Germany",
Country %in% c("Un. Sov. Soc. Rep.") ~ "Russian Federation",
grepl("Faeroe Islands", Country) ~ "Faroe Islands",
grepl("Other nei", Country) ~ "OTHER",
TRUE ~ Country
),
ISO3 = countrycode::countrycode(Country, "country.name", "iso3c", warn = FALSE),
ECOREGION = dplyr::case_when(
Division %in% historic_bs ~ "Baltic Sea",
Division %in% historic_ns ~ "Greater North Sea",
Division %in% historic_bob ~ "Bay of Biscay and the Iberian Coast",
Division %in% historic_cs ~ "Celtic Seas",
Division %in% historic_is ~ "Icelandic Waters",
Division %in% historic_az ~ "Azores",
Division %in% historic_gs ~ "Greenland Sea",
if(ecoregion == "Norwegian Sea"){
Division %in% historic_nw ~ "Norwegian Sea"
},
if(ecoregion == "Barents Sea"){
Division %in% historic_br ~ "Barents Sea"
},
TRUE ~ "OTHER"))
catch_dat_1950 <- dplyr::filter(catch_dat_1950, YEAR <= 2005)
catch_dat_1950 <- dplyr::left_join(catch_dat_1950, y = species_list, c("Species" = "English_name"))# Merge to add FAO species information
catch_dat_1950 <- dplyr::left_join(catch_dat_1950, y = species_list,c("Species" = "Scientific_name", # Merge to add FAO species information
"X3A_CODE"))
catch_dat_1950 <- dplyr::left_join(catch_dat_1950, y = fish_category, by = "X3A_CODE")
catch_dat_1950 <- dplyr::select(catch_dat_1950,YEAR,
COUNTRY = Country,
ISO3,
GUILD = FisheriesGuild,
ECOREGION,
SPECIES_NAME = Scientific_name,
SPECIES_CODE = X3A_CODE,
COMMON_NAME = Species,
VALUE)
# add in official
catch_dat_2010 <- tidyr::gather(official, YEAR, VALUE, -Country, -Species, -Area, -Units)
catch_dat_2010 <- dplyr::filter(catch_dat_2010, Country != "")
catch_dat_2010 <- dplyr::mutate(catch_dat_2010,YEAR = as.numeric(gsub("X", "", YEAR)),
VALUE = as.numeric(VALUE),
Country = countrycode::countrycode(Country,"iso2c", "country.name"),
Country = ifelse(grepl("Guernsey|Isle of Man|Jersey", Country),
"United Kingdom",
Country),
ISO3 = countrycode::countrycode(Country, "country.name", "iso3c", warn = FALSE),
Country = gsub("(United Kingdom) .*", "\\1", Country),
Area = tolower(Area),
ECOREGION = dplyr::case_when(
Area %in% c("27.3.bc", "27.3.d", "27.3_nk") ~ "Baltic Sea",
Area %in% c("27.3.a", "27.4", "27.7.d") ~ "Greater North Sea",
Area %in% c("27.8.a", "27.8.b","27.8.c",
"27.8.d.2", "27.8.e.2", "27.9.a",
"27.9.b.2") ~ "Bay of Biscay and the Iberian Coast",
Area %in% c("27.6.a", "27.6.b.2","27.7.a", "27.7.b", "27.7.c.2",
"27.7.f", "27.7.g", "27.7.h","27.7.j.2", "27.7.k.2") ~ "Celtic Seas",
Area %in% c("27.5.a.1", "27.5.a.2","27.5.a_NK","27.5.a_nk","27.12.a.4") ~ "Icelandic Waters",
Area %in% c("27.10.a.2") ~ "Azores",
Area %in% c("27.12.a.3", "27.2.b.2", "27.5.a.2", "27.14.a", "27.14.b.2") ~ "Greenland Sea",
if(ecoregion == "Norwegian Sea"){
Area %in% c("27.2.a.1", "27.2.a.2","27.2.a_NK","27.2.a_nk", "27.2.b.1", "27.2.b.2", "27.2.b_NK","27.2.b_nk","27.14.a", "27.14_NK", "27.14_nk") ~ "Norwegian Sea"
},
if(ecoregion =="Barents Sea"){
Area %in% c("27.1.a", "27.1.b","27.2.a.2","27.2.a_NK","27.2.a_nk", "27.2.b.2","27.2.b_NK","27.2.b_nk", "27.1_NK", "27.1_nk") ~ "Barents Sea"
}))
catch_dat_2010 <- dplyr::left_join(catch_dat_2010,species_list, c("Species" = "X3A_CODE"))
catch_dat_2010 <- dplyr::left_join(catch_dat_2010,fish_category, by = c("Species" = "X3A_CODE"))
catch_dat_2010<- catch_dat_2010[!is.na(catch_dat_2010$ECOREGION),]
catch_dat_2010 <- dplyr::select(catch_dat_2010,YEAR,
COUNTRY = Country,
ISO3,
GUILD = FisheriesGuild,
ECOREGION,
SPECIES_NAME = Scientific_name,
SPECIES_CODE = Species,
COMMON_NAME = English_name,
VALUE)
catch_dat_2010 <- dplyr::group_by(catch_dat_2010,YEAR, COUNTRY, GUILD, ECOREGION,COMMON_NAME)
catch_dat_2010 <- dplyr::summarise(catch_dat_2010, VALUE = sum(VALUE))
# now do preliminary catches
catch_dat_prelim <- dplyr::filter(preliminary, Country != "")
# tidyr::gather(ï..Year, -Country, -AphiaID, -Area, -Catch) %>%
catch_dat_prelim <- dplyr::mutate(catch_dat_prelim, YEAR = Year,
VALUE = AMS.Catch.TLW.,
Country = countrycode::countrycode(Country,"iso2c", "country.name"),
Country = ifelse(grepl("Guernsey|Isle of Man|Jersey", Country),
"United Kingdom",
Country),
ISO3 = countrycode::countrycode(Country, "country.name", "iso3c", warn = FALSE),
Country = gsub("(United Kingdom) .*", "\\1", Country),
Area = tolower(Area))
#check why areas names are different!!
catch_dat_prelim <- dplyr::mutate(catch_dat_prelim, ECOREGION = dplyr::case_when(
Area %in% c("27_3_bc", "27_3_c_22","27_3_d","27_3_d_24","27_3_d_25","27_3_d_26","27_3_d_30",
"27_3_d_27","27_3_d_31","27_3_nk", "27_3_b_23", "27_3_d_28_2","27_3_d_32","27_3_d_29") ~ "Baltic Sea",
Area %in% c("27_3_a", "27_4_a","27_4_b", "27_4_c", "27_7_d") ~ "Greater North Sea",
Area %in% c("27_8_a", "27_8_b","27_8_c",
"27_8_d_2", "27_8_e_2", "27_9_a",
"27_9_b_2")~ "Bay of Biscay and the Iberian Coast",
Area %in% c("27_6_a", "27_6_b_2","27_7_a", "27_7_b", "27_7_c_2","27_7.e",
"27_7_f", "27_7_g", "27_7_h","27_7_j_2", "27_7_k_2")~"Celtic Seas",
Area %in% c("5_a_1", "5_a_2","12_a_4")~"Icelandic Waters",
Area %in% c("2_a_1", "2_a_2", "2_b_1", "2_b_2", "14.a")~"Norwegian Sea",
TRUE ~ "OTHER"))
catch_dat_prelim <- dplyr::filter(catch_dat_prelim,ECOREGION != "OTHER")
catch_dat_prelim <- dplyr::left_join(catch_dat_prelim, species_list, c("Species.Latin.Name" = "Scientific_name"))
catch_dat_prelim <- dplyr::left_join(catch_dat_prelim, fish_category, by = "X3A_CODE")
catch_dat_prelim <- dplyr::select(catch_dat_prelim,YEAR,
COUNTRY = Country,
ISO3,
GUILD = FisheriesGuild,
ECOREGION,
SPECIES_NAME = Species.Latin.Name,
SPECIES_CODE = X3A_CODE,
COMMON_NAME = English_name,
VALUE)
catch_dat_prelim$COMMON_NAME[which(catch_dat_prelim$SPECIES_NAME == "Ammodytes")] <- "Sandeels(=Sandlances) nei"
catch_dat_prelim$SPECIES_CODE[which(catch_dat_prelim$SPECIES_NAME == "Ammodytes")] <- "SAN"
if (is.null(preliminary)) {
df <- dplyr::bind_rows(catch_dat_2010,catch_dat_1950)
} else {
df <- dplyr::bind_rows(catch_dat_2010,catch_dat_1950, catch_dat_prelim)
}
df <- dplyr::ungroup(df)
df <- dplyr::mutate(df, GUILD = ifelse(is.na(GUILD),
"undefined",
GUILD))
df$COUNTRY<-gsub("Russian Federation", "\\Russia\\",df$COUNTRY)
df$COUNTRY<-gsub("Russia", "Russian Federation", df$COUNTRY)
df <- dplyr::select(df,YEAR,
COUNTRY,
ISO3,
GUILD ,
ECOREGION,
SPECIES_NAME,
SPECIES_CODE,
COMMON_NAME,
VALUE)
# df$GUILD[which(ices_catch_dat$SPECIES_CODE == "WHB")] <- "pelagic"
df <- dplyr::filter(df, ECOREGION %in% ecoregion)
return(df)
}
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