sean-rohan-NOAA
commented
6 months ago Filled using the code below. Maps at the bottom.
# Install GAP packages ----
# remotes::install_github(repo = "afsc-gap-products/gapindex")
# remotes::install_github(repo = "afsc-gap-products/akgfmaps")
# remotes::install_github(repo = "afsc-gap-products/coldpool")
# Load GAP packages
library(gapindex)
library(akgfmaps)
library(coldpool)
# Prepare CPUE in kg/ha ----
channel <- gapindex::get_connected()
ebs_dat <- gapindex::get_data(year_set = c(2010, 2017:2019, 2021:2023),
survey_set = "EBS",
spp_codes = 21740,
haul_type = 3,
abundance_haul = "Y",
sql_channel = channel
)
ebs_2018 <- gapindex::get_data(year_set = 2018,
survey_set = "EBS",
spp_codes = 21740,
haul_type = 13,
abundance_haul = "N",
sql_channel = channel
)
nbs_dat <- gapindex::get_data(year_set = c(2010, 2017:2019, 2021:2023),
survey_set = "NBS",
spp_codes = 21740,
haul_type = 3,
abundance_haul = "Y",
sql_channel = channel
)
ebs_cpue <- gapindex::calc_cpue(racebase_tables = ebs_dat)
ebs_cpue_2018 <- gapindex::calc_cpue(racebase_tables = ebs_2018)
nbs_cpue <- gapindex::calc_cpue(racebase_tables = nbs_dat)
all_cpue <- rbind(ebs_cpue, nbs_cpue, ebs_cpue_2018)
all_cpue$CPUE_KGHA <- all_cpue$CPUE_KGKM2/100
all_cpue$LONGITUDE <- (all_cpue$LONGITUDE_DD_START + all_cpue$LONGITUDE_DD_END)/2
all_cpue$LATITUDE <- (all_cpue$LATITUDE_DD_START + all_cpue$LATITUDE_DD_END)/2
all_cpue$COMMON_NAME <- "walleye pollock"
# Make CPUE sf layers ----
cpue_stack <- akgfmaps::make_idw_stack(x = all_cpue,
region = "ebs",
set.breaks = c(0, 50, 100, 200, 300, Inf),
grouping.vars = "YEAR",
extrapolation.grid.type = "sf"
)
# Setup temperature layers ----
year_vec <- names(terra::rast(coldpool:::nbs_ebs_bottom_temperature))
for(ii in year_vec) {
if(ii == 2020) {next}
sel_layer_df <- as.data.frame(terra::rast(coldpool::nbs_ebs_bottom_temperature)[[as.character(ii)]],
na.rm = FALSE,
xy = TRUE) |>
tidyr::pivot_longer(cols = 3) |>
sf::st_as_sf(coords = c("x", "y"),
crs = coldpool:::ebs_proj_crs) |>
dplyr::rename(YEAR = name,
temperature = value) |>
stars::st_rasterize()
sel_layer_df$temperature <- cut(sel_layer_df$temperature,
breaks = c(-2, 0, 2))
sel_layer_df <- sel_layer_df |>
sf::st_as_sf() |>
dplyr::group_by(temperature) |>
dplyr::summarise(n = n()) |>
dplyr::select(-n) |>
dplyr::ungroup() |>
sf::st_intersection(cpue_stack$map_layers$survey.area)
sel_layer_df$YEAR <- as.numeric(ii)
if(ii == year_vec[1]) {
bt_year_df <- sel_layer_df
} else{
bt_year_df <- dplyr::bind_rows(bt_year_df, sel_layer_df)
}
}
lt_2 <- bt_year_df |>
dplyr::group_by(YEAR) |>
summarise(do_union = TRUE)
lt_0 <- bt_year_df |>
dplyr::filter(temperature == "(-2,0]") |>
dplyr::group_by(YEAR) |>
summarise(do_union = TRUE)
# Mask for 2018
mask_2018 <- akgfmaps::get_base_layers(select.region = "nbs", set.crs = "EPSG:3338")$survey.grid |>
dplyr::filter(
STATIONID %in% c("V-01", "U-01", "T-01", "S-01", "R-01",
"V-02", "U-02", "T-02", "S-02", "R-02",
"DD-03", "ZZ-03", "Y-03", "X-03", "W-03", "V-03", "U-03", "T-03", "S-03", "R-03",
"DD-04", "CC-04", "BB-04", "AA-04", "ZZ-04", "Y-04", "X-04", "W-04", "V-04", "U-04", "T-04", "S-04", "R-04",
"DD-05", "CC-05", "BB-05", "AA-05", "ZZ-05", "Y-05", "X-05", "W-05", "V-05", "U-05", "T-05", "S-05", "R-05",
"DD-06", "CC-06", "BB-06", "AA-06", "ZZ-06", "Y-06", "X-06", "W-06", "V-06", "U-06", "T-06", "S-06", "R-06",
"DD-07", "CC-07", "BB-07", "AA-07", "ZZ-07", "Y-07", "X-07", "W-07", "V-07", "U-07", "T-07", "S-07", "R-07",
"DD-08", "CC-08", "BB-08", "AA-08", "ZZ-08", "Y-08", "X-08", "W-08", "V-08", "U-08", "T-08", "S-08", "R-08",
"DD-09", "CC-09", "BB-09", "AA-09", "ZZ-09", "Y-09", "X-09", "W-09", "V-09", "U-09", "T-09", "S-09", "R-09",
"DD-10", "CC-10", "BB-10", "AA-10", "ZZ-10", "Y-10", "X-10", "W-10", "V-10", "U-10", "T-10", "S-10", "R-10")
) |>
dplyr::group_by() |>
summarise(do_union = TRUE) |>
sf::st_make_valid() |>
dplyr::mutate(YEAR = 2018)
# Make maps
plot_cpue <- ggplot() +
geom_sf(data = cpue_stack$extrapolation.stack,
mapping = aes(fill = var1.pred), color = NA) +
geom_sf(data = mask_2018, fill = "white", color = NA) +
geom_sf(data = cpue_stack$map_layers$survey.strata, fill = NA, color = "black") +
geom_sf(data = cpue_stack$map_layers$akland, color = NA, fill = "grey50") +
scale_fill_manual(name = expression(CPUE~(kg/ha)),
values = c("gray90",
viridis::viridis(
option = "mako",
direction = -1,
n = 5,
begin = 0.20,
end = 0.80)),
labels = c("No catch", ">0–50", ">50–100", ">100–200", ">200–300", ">300")) +
coord_sf(xlim = cpue_stack$map_layers$plot.boundary$x,
ylim = cpue_stack$map_layers$plot.boundary$y) +
facet_wrap(~YEAR, ncol = 4) +
theme_bw() +
theme(axis.title = element_text(color = "black", face = "bold"),
axis.text = element_text(color = "black", size = 5),
axis.ticks = element_line(color = "black"),
legend.position = "right",
strip.text = element_text(size = 9,
color = "white",
face = "bold",
margin = margin(0.5, 0, 0.5, 0, "mm")),
strip.background = element_rect(fill = "#0055a4",
color = NA))
plot_cpue_lt0 <- plot_cpue +
geom_sf(data = lt_0, fill = "pink3", color = NA, alpha = 0.6) +
geom_sf(data = lt_0, fill = NA, color = "pink3") +
coord_sf(xlim = cpue_stack$map_layers$plot.boundary$x,
ylim = cpue_stack$map_layers$plot.boundary$y) +
scale_x_continuous(breaks = cpue_stack$map_layers$lon.breaks) +
scale_y_continuous(breaks = cpue_stack$map_layers$lat.breaks)
plot_cpue_lt2 <- plot_cpue +
geom_sf(data = lt_2, fill = "pink3", color = NA, alpha = 0.6) +
geom_sf(data = lt_2, fill = NA, color = "pink3") +
coord_sf(xlim = cpue_stack$map_layers$plot.boundary$x,
ylim = cpue_stack$map_layers$plot.boundary$y) +
scale_x_continuous(breaks = cpue_stack$map_layers$lon.breaks) +
scale_y_continuous(breaks = cpue_stack$map_layers$lat.breaks)
png(filename = "pollock_cpue_lt0_wide.png", width = 8, height = 4, units = "in", res = 300)
print(plot_cpue_lt0)
dev.off()
png(filename = "pollock_cpue_lt2_wide.png", width = 8, height = 4, units = "in", res = 300)
print(plot_cpue_lt2)
dev.off()
png(filename = "pollock_cpue_lt0_tall.png", width = 7, height = 7.5, units = "in", res = 300)
print(plot_cpue_lt0 +
facet_wrap(~YEAR, ncol = 3) +
theme(legend.position = c(0.66, 0.15),
legend.direction = "horizontal",
axis.text = element_text(color = "black", size = 7)) +
guides(fill = guide_legend(title.position = "top", title.hjust = 0.5))
)
dev.off()
png(filename = "pollock_cpue_lt2_tall.png", width = 7, height = 7.5, units = "in", res = 300)
print(plot_cpue_lt2 +
facet_wrap(~YEAR, ncol = 3) +
theme(legend.position = c(0.66, 0.15),
legend.direction = "horizontal",
axis.text = element_text(color = "black", size = 7)) +
guides(fill = guide_legend(title.position = "top", title.hjust = 0.5))
)
dev.off()
Data product requested: CPUE and isotherm (0 and 2 degrees) map for pollock in the EBS and NBS during all years the EBS survey was conducted. Example from 2019 shown below.
Output type: Plots
Species: walleye pollock
Region : EBS/NBS
Research team making the request: Ebett Siddon