report5_VMS.R

library(icesTAF)
library(icesFO)
library(sf)
library(ggplot2)
library(dplyr)

## Run utilies
source("bootstrap/utilities.r")

# set values for automatic naming of files:
cap_year <- 2022
cap_month <- "October"
ecoreg_code <- "NrS"
ecoreg <- "NrS"
###########
##Load data
###########

# read vms fishing effort
effort <-
  sf::st_read("vms_effort.csv",
               options = "GEOM_POSSIBLE_NAMES=wkt", crs = 4326)
effort <- dplyr::select(effort, -WKT)

# read vms swept area ratio
sar <-
  sf::st_read("vms_sar.csv",
               options = "GEOM_POSSIBLE_NAMES=wkt", crs = 4326)
sar <- dplyr::select(sar, -WKT)


#set range of years in plots

year_range = "2018-2021"


###########
## 3: VMS #
###########

#~~~~~~~~~~~~~~~#
# A. Effort map
#~~~~~~~~~~~~~~~#

gears <- c("Static", "Midwater", "Otter", "Demersal seine","Dredge", "Beam")

effort <-
    effort %>%
      dplyr::filter(fishing_category_FO %in% gears) %>%
      dplyr::mutate(
        fishing_category_FO =
          dplyr::recode(fishing_category_FO,
            Static = "Static gears",
            Midwater = "Pelagic trawls and seines",
            Otter = "Bottom otter trawls",
            `Demersal seine` = "Bottom seines",
            Dredge = "Dredges",
            Beam = "Beam trawls"),
          mw_fishinghours = as.numeric(mw_fishinghours)
        ) %>%
      filter(!is.na(mw_fishinghours)) %>% 
      filter(mw_fishinghours != 0)

# write layer
write_layer <- function(dat, fname) {
  sf::write_sf(dat, paste0("report/", fname, ".shp"))
  files <- dir("report", pattern = fname, full = TRUE)
  files <- files[tools::file_ext(files) != "png"]
  zip(paste0("report/", fname, ".zip"), files, extras = "-j")
  file.remove(files)
}
write_layer(effort, paste0(cap_year, "_", ecoreg,"_FO_VMS_effort"))

# save plot
plot_effort_map(effort, ecoregion) +
  ggtitle(paste0("Average MW Fishing hours ", year_range))

ggplot2::ggsave(file_name(cap_year,ecoreg_code,"VMS_effort_update", ext = "png", dir = "report"), width = 170, height = 200, units = "mm", dpi = 300)

# #### investigation
# library(ggplot2)
# ggplot(effort, aes(x=mw_fishinghours)) + geom_histogram()
# length(which(effort$mw_fishinghours == 0))
# breaks <- get_map_breaks(effort$mw_fishinghours)
# unique(breaks)
# x <- which(breaks == ">0 - 0 (n = 53)")
# effort[x,]
#~~~~~~~~~~~~~~~#
# A. Swept area map
#~~~~~~~~~~~~~~~#

# write layer
write_layer(sar, paste0(cap_year, "_", ecoreg,"_FO_VMS_sar"))

plot_sar_map(sar, ecoregion, what = "surface") +
  ggtitle(paste0("Average surface swept area ratio ",year_range))

ggplot2::ggsave(file_name(cap_year,ecoreg_code,"VMS_sarA", ext = "png", dir = "report"), width = 170, height = 200, units = "mm", dpi = 300)

plot_sar_map(sar, ecoregion, what = "subsurface")+
  ggtitle(paste0("Average subsurface swept area ratio ",year_range))

ggplot2::ggsave(file_name(cap_year,ecoreg_code,"VMS_sarB", ext = "png", dir = "report"), width = 170, height = 200, units = "mm", dpi = 300)