Merge pull request #131 from NOAA-EDAB/dev

Update master with all data and plot corrections in dev as of Feb 8
NOAA-EDAB · Feb 8, 2024 · c04d7ab · c04d7ab
2 parents 5cb4845 + 6f9dd73
commit c04d7ab
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diff --git a/DESCRIPTION b/DESCRIPTION
@@ -46,6 +46,6 @@ Suggests:
 	zoo,
 	rlang
 VignetteBuilder: knitr
-RoxygenNote: 7.3.0
+RoxygenNote: 7.3.1
 Depends: 
     R (>= 2.10)
diff --git a/R/ecodata.R b/R/ecodata.R
@@ -11,6 +11,5 @@
 #'To learn more about using \code{ecodata}, start with the vignette: \code{browseVignettes(package="ecodata")} or click the index link below
 #'
 #'
-#' @docType package
-#' @name ecodata
-NULL
+"_PACKAGE"
+
diff --git a/R/plot_bottom_temp_seasonal_gridded.r b/R/plot_bottom_temp_seasonal_gridded.r
@@ -23,7 +23,7 @@ plot_bottom_temp_seasonal_gridded <- function(shadedRegion = NULL,
     xmin = -77
     xmax = -66
     ymin = 35.5
-    ymax = 43
+    ymax = 45
     xlims <- c(xmin, xmax)
     ylims <- c(ymin, ymax)
 
@@ -58,7 +58,13 @@ plot_bottom_temp_seasonal_gridded <- function(shadedRegion = NULL,
     ggplot2::coord_sf(xlim = xlims, ylim = ylims) +
     ggplot2::facet_wrap(Var~.)+
     ecodata::theme_map() +
-    #ggplot2::scale_fill_viridis_c(option = 'A',name = 'Bottom \n Temp')+
+    #ggplot2::scale_fill_gradient2(name = 'Bottom \n Temp',
+                                  #low = scales::muted("blue"),
+                                  #mid = "white",
+                                  #high = scales::muted("red"),
+                                  #limits = c(5,25),
+                                  #labels = c("5", "10", "15", "20", "25")) +
+    ggplot2::scale_fill_viridis_c(option = 'B',name = 'Bottom \n Temp')+
     ggplot2::ggtitle('Seasonal Mean Bottom Temperature')+
     ggplot2::xlab("Longitude") +
     ggplot2::ylab("Latitude") +

diff --git a/R/plot_habitat_diversity.R b/R/plot_habitat_diversity.R
@@ -59,8 +59,8 @@ plot_habitat_diversity <- function(shadedRegion = NULL,
     #ggplot2::geom_ribbon(ggplot2::aes(ymin = Lower, ymax = Upper), alpha = 0.5)+
     ggplot2::geom_point()+
     ggplot2::geom_line()+
-    ggplot2::geom_point(data = fix, aes(x = Time, y = mean), size = setup$line.size)+
-    ggplot2::geom_line(data = fix, aes(x = Time, y = mean), linewidth = setup$line.size)+
+    ggplot2::geom_point(data = fix, ggplot2::aes(x = Time, y = mean), size = setup$line.size)+
+    ggplot2::geom_line(data = fix, ggplot2::aes(x = Time, y = mean), linewidth = setup$line.size)+
     ggplot2::ggtitle(paste(report,"Species Shannon Diversity from Habitat Assessment"))+
     ggplot2::ylab("Shannon Diversity")+
     ggplot2::xlab(ggplot2::element_blank())+

diff --git a/R/plot_hms_stock_status.R b/R/plot_hms_stock_status.R
@@ -51,11 +51,11 @@ plot_hms_stock_status <- function(shadedRegion = NULL,
       #(B.Bmsy == 0.5) ~"a",
       #(B.Bmsy <1) ~"a",
       #(B.Bmsy == 1) ~"a",
-      (F.Fmsy == 1) ~ "a",
-      (F.Fmsy >1) ~ "a",
+      #(F.Fmsy == 1) ~ "a",
+      #(F.Fmsy >1) ~ "a",
       #(F.Fmsy < 1 & B.Bmsy > 0.5 & B.Bmsy < 1) ~ "b",
-      (F.Fmsy < 1 & B.Bmsy < 1) ~ "b",
-      (F.Fmsy < 1 & B.Bmsy > 1) ~ "c"))
+      (F.Fmsy > 1 | B.Bmsy < 1) ~ "b",
+      (F.Fmsy < 1 & B.Bmsy > 1) ~ "a"))
 
   unknown <- stock_status |>
     dplyr::filter(is.na(F.Fmsy) | is.na(B.Bmsy)) |>
@@ -85,7 +85,7 @@ plot_hms_stock_status <- function(shadedRegion = NULL,
     ggplot2::geom_text(data = unknownp, ggplot2::aes(x = x, y = y, label = text), #Custom legend for unknown stock status
                        size = c(4.75,rep(4,3))) +
     ggplot2::annotate(geom="text", x=0.43, y=5, label="ATL SBN (F/Fmsy = 22.5)",
-                      color="#1B9E77")+
+                      color="#D95F02")+
     ggplot2::scale_color_brewer(palette = "Dark2", #Change legend labels for clarity
                                 breaks = stock_status$score) +
     ggplot2::xlab(expression(~B/B[msy])) +

diff --git a/R/plot_species_dist.R b/R/plot_species_dist.R
@@ -24,7 +24,7 @@ plot_species_dist <- function(shadedRegion = NULL,
   if (report == "MidAtlantic") {
     filterEPUs <- c("MAB")
   } else {
-    stop("This is a shelfwide indicator only used in the MidAtlantic report")
+    returnMessage <- "This is a shelfwide indicator only used in the MidAtlantic report"
     filterEPUs <- c("GB", "GOM")
   }
 
@@ -85,6 +85,9 @@ plot_species_dist <- function(shadedRegion = NULL,
     #
     # }
 
+    if (report == "NewEngland"){
+      p <- returnMessage
+    }
     return(p)
 
 }

diff --git a/R/plot_species_groupings.R b/R/plot_species_groupings.R
@@ -39,21 +39,28 @@ plot_species_groupings <- function(shadedRegion = NULL,
     dplyr::distinct() |>
     dplyr::group_by(dplyr::across(varName), Fed.Managed) |>
     dplyr::summarize_all(dplyr::funs(paste(na.omit(.), collapse = ", "))) |>
+    dplyr::ungroup() |>
     tidyr::spread(Fed.Managed, COMNAME) |>
-    dplyr::arrange(factor(get(varName), levels = c("Apex Predator", "Piscivore", "Planktivore", "Benthivore", "Benthos")))
-  fix<-fix[c(1,3,2,4,5)] |>
-    dplyr::mutate_all(tolower)
+    dplyr::arrange(factor(get(varName), levels = c("Apex Predator", "Piscivore", "Planktivore", "Benthivore", "Benthos"))) |>
+    dplyr::mutate(dplyr::across(dplyr::everything(), tolower)) |>
+    dplyr::rename(Guild = !!varName,
+                  Joint = JOINT) |>
+    dplyr::relocate(Guild,MAFMC,Joint)
+
+  # fix<-fix[c(1,3,2,4,5)] |>
+  #   dplyr::mutate_all(tolower)
 
   # code for generating plot object p
   # ensure that setup list objects are called as setup$...
   # e.g. fill = setup$shade.fill, alpha = setup$shade.alpha,
   # xmin = setup$x.shade.min , xmax = setup$x.shade.max
   #
 
+
   p <- flextable::flextable(fix) |>
     flextable::set_caption('Feeding guilds and management bodies.') |>
     flextable::fontsize(size=8, part = "all") |>
-    flextable::set_header_labels(SOE.20 = "Guild",
+    flextable::set_header_labels(SOE.24 = "Guild",
                                  MAFMC = "MAFMC",
                                  JOINT = "Joint",
                                  NEFMC = "NEFMC",

diff --git a/R/plot_wind_revenue.R b/R/plot_wind_revenue.R
@@ -33,20 +33,26 @@ plot_wind_revenue <- function(shadedRegion = NULL,
   # e.g., calculate mean, max or other needed values to join below
    fix <- tidyr::separate(ecodata::wind_revenue,col=Var, into = c("Species", "Var"),sep = "-sum_") |>
      dplyr::filter(Var == varName) |>
-     dplyr::mutate(Value = Value/1000000,
-                   Time = as.integer(Time)) |>
+     dplyr::mutate(Value = Value/1000000) |>
      dplyr::mutate(Species = dplyr::recode(Species,"MONK"="MONKFISH"))
 
+   # Code to determine units displayed on y axis
+   if (varName == "landing") {
+     wind_label <- "Landings (million lbs)"
+   } else {
+     wind_label <- "Revenue (millions $2022)"
+   }
+
    if (report == "MidAtlantic") {
      fix <- fix |>
        dplyr::filter(EPU %in% filterEPUs,
                      Species %in% c("LONGFIN SQUID","MONKFISH","SUMMER FLOUNDER",
-                                    "OCEAN QUAHOG",  "SURF CLAM" )) |>
+                                    "OCEAN QUAHOG",  "SURFCLAM" )) |>
        dplyr::mutate(Species = stringr::str_to_sentence(Species))
      } else if (report == "NewEngland") {
        fix <- fix |>
          dplyr::filter(EPU %in% filterEPUs,
-                       Species %in% c("ATLANTIC HERRING","MONKFISH","SEA SCALLOP",
+                       Species %in% c("ATLANTIC HERRING","MONKFISH","ATLANTIC SEA SCALLOP",
                                       "SILVER HAKE",  "SKATES" )) |>
          dplyr::mutate(Species = stringr::str_to_sentence(Species))
      }
@@ -67,7 +73,7 @@ plot_wind_revenue <- function(shadedRegion = NULL,
         ggplot2::geom_point()+
         ggplot2::geom_line()+
         ggplot2::ggtitle(paste0(report,": Fishery Revenue in Wind Lease Areas"))+
-        ggplot2::ylab(expression("Dollars (millions)"))+
+        ggplot2::ylab(wind_label)+
         ggplot2::xlab(ggplot2::element_blank())+
         ggplot2::facet_wrap(.~Species,scales = "free_y") +
         #ecodata::geom_gls()+
@@ -83,7 +89,7 @@ plot_wind_revenue <- function(shadedRegion = NULL,
        ggplot2::geom_point()+
        ggplot2::geom_line()+
        ggplot2::ggtitle(paste0(report,": Fishery Revenue in Wind Lease Areas"))+
-       ggplot2::ylab(expression("Dollars (millions)"))+
+       ggplot2::ylab(wind_label)+
        ggplot2::xlab(ggplot2::element_blank())+
 
        #ecodata::geom_gls()+

diff --git a/R/plot_zoo_abundance_anom.R b/R/plot_zoo_abundance_anom.R
@@ -4,7 +4,7 @@
 #'
 #' @param shadedRegion Numeric vector. Years denoting the shaded region of the plot (most recent 10)
 #' @param report Character string. Which SOE report ("MidAtlantic", "NewEngland")
-#' @param varName Character string. Which variable to plot ("copepod","euphasid")
+#' @param varName Character string. Which variable to plot ("copepod","euphausid")
 #' @return ggplot object
 #'
 #'
@@ -29,12 +29,12 @@ plot_zoo_abundance_anom <- function(shadedRegion = NULL,
   if (varName == "copepod") {
     varName <-  "large-bodied|small-bodied"
     vtitle <- "Small and large-bodied copepod abundance anomaly"
-  } else if (varName == "euphasid") {
+  } else if (varName == "euphausid") {
     varName <-  "Euphausiacea|Cnidaria"
     vtitle <- "Zooplankton abundance anomaly"
 
   } else {
-    stop("Please select either 'copepod' or 'euphasid'")
+    stop("Please select either 'copepod' or 'euphausid'")
   }
 
   # optional code to wrangle ecodata object prior to plotting
@@ -67,10 +67,12 @@ plot_zoo_abundance_anom <- function(shadedRegion = NULL,
                linewidth = setup$hline.size,
                alpha = setup$hline.alpha,
                linetype = setup$hline.lty)+
-    ggplot2::facet_wrap(~EPU,ncol = 1)+
+    ggplot2::facet_wrap(~EPU~Var)+
+    ecodata::geom_gls() +
     ecodata::theme_ts()+
     ecodata::theme_facet()+
-    ggplot2::theme(legend.title = ggplot2::element_blank()) +
+    ggplot2::theme(legend.title = ggplot2::element_blank(),
+                   legend.position = "none") +
     ecodata::theme_title()
 
    # optional code for New England specific (2 panel) formatting
@@ -85,5 +87,5 @@ plot_zoo_abundance_anom <- function(shadedRegion = NULL,
 
 }
 
-attr(plot_zoo_abundance_anom,"varName") <- c("copepod","euphasid")
+attr(plot_zoo_abundance_anom,"varName") <- c("copepod","euphausid")
 attr(plot_zoo_abundance_anom,"report") <- c("MidAtlantic","NewEngland")
diff --git a/data-raw/Fishery Impacts from OSW Development_2023 SOE Report_Christel_UPDATED.xlsx b/data-raw/Fishery Impacts from OSW Development_2023 SOE Report_Christel_UPDATED.xlsx
diff --git a/...-raw/UPDATED_wea_landings_2023 SOE Reports_Christel - Douglas Christel - NOAA Federal.csv b/...-raw/UPDATED_wea_landings_2023 SOE Reports_Christel - Douglas Christel - NOAA Federal.csv
@@ -0,0 +1,55 @@
+GARFO and ASMFC Managed Species,Maximum Percent Total Annual Regional Species Landings,Maximum Percent Total Annual Regional Species Revenue
+Redfish,0.537737474,0.531995934
+Pollock,0.403607303,0.427294448
+White hake,0.33995244,0.3354793
+American plaice,0.280356165,0.262408696
+Witch flounder,0.225986683,0.25206003
+Haddock,0.227643039,0.239032168
+Atlantic halibut,0.235914109,0.228287263
+Monkfish ,0.199184927,0.196783891
+Skate species,0.29,0.3
+Atlantic surfclam,0.168852126,0.175173059
+Yellowtail flounder,0.152951316,0.149214693
+Offshore hake,0.046486926,0.14593979
+Atlantic cod,0.149582482,0.145768893
+Atlantic menhaden**,0.134323765,0.141880564
+American shad*,0.027404255,0.135030286
+Red hake,0.078440074,0.112420702
+Atlantic sea scallop,0.090517481,0.100980112
+Black sea bass,0.097270244,0.099990201
+American eel**,0.097294616,0.093826996
+Silver hake,0.068394326,0.086802419
+Longfin squid,0.080603421,0.082009373
+Scup,0.085717641,0.080968966
+Atlantic mackerel,0.084275349,0.077206562
+Butterfish,0.049862166,0.060246321
+Golden Tilefish,0.060738847,0.057944899
+Chub mackerel,0.061197443,0.055954247
+Winter flounder,0.053520349,0.054544782
+Summer flounder,0.04919601,0.054018854
+American lobster**,0.060314547,0.054010744
+Jonah crab**,0.053231914,0.053091491
+Tautog**,0.04324992,0.050759331
+Atlantic herring,0.04220826,0.049413471
+Bluefish,0.042752088,0.043543898
+Windowpane flounder,0.025095714,0.039795363
+Spiny dogfish,0.038110711,0.035157093
+Ocean quahog,0.031717511,0.032185999
+Horseshoe crab**,0.034464121,0.031248412
+Cobia*,0.032581567,0.029428304
+Atlantic croaker**,0.017050712,0.017970042
+Illex squid,0.018699965,0.016932307
+Striped bass,0.022556611,0.015895645
+Black drum*,0.008870124,0.009620579
+Weakfish*,0.008332349,0.007344359
+Spot**,0.003224814,0.003402403
+Hickory shad*,0.005227273,0.001179856
+,,
+,,
+,,
+,,
+,,
+,,
+,,
+,,
+,,
diff --git a/data-raw/get_wea_landings_rev.R b/data-raw/get_wea_landings_rev.R
@@ -9,28 +9,45 @@ raw.dir <- here::here("data-raw")
 
 ## Doug Christel
 #wind_xlsx<-"CHRISTEL_2022 State of the Ecosystem Report_Max WEA Species Landings and Revenue.xlsx"
-wind_xlsx<-"SOE 2023 update_Offshore Wind Fishery Data_Christel (3).xlsx"
+wind_rev_xlsx<-"Fishery Impacts from OSW Development_2023 SOE Report_Christel_UPDATED.xlsx"
 get_wea_landings_rev <- function(save_clean = F){
   # import data
-   wea_landings_rev<-readxl::read_excel(file.path(raw.dir,wind_xlsx), sheet = "Highest % Rev Table") %>%
+   wea_landings_rev<-readxl::read_excel(file.path(raw.dir,wind_rev_xlsx),
+                                        sheet = "Cumulative Max Rev and Land") %>%
     # janitor::row_to_names(.,1) %>%
     #  select("Max % Regional Revenue and Landings of fisheries managed by the Atlantic States Marine Fisheries Commission and the New England and Mid-Atlantic Fishery Management Council within Existing Lease Areas and the Draft Primary and Secondary Central Atlantic Call Areas")
 
-     janitor::row_to_names(.,3) %>%
-    dplyr::select( "NEFMC, MAFMC, and ASMFC Managed Species",
-                   "Maximum Percent Total Annual Regional Species Landings",
-                   "Maximum Percent Total Annual Regional Species Revenue") %>%
-    dplyr::rename("perc_landings_max" = "Maximum Percent Total Annual Regional Species Landings",
-                  "perc_revenue_max" = "Maximum Percent Total Annual Regional Species Revenue" ) %>%
+    dplyr::select( "NEFMC and MAFMC Managed Species",
+                   "Maximum Percent Total Annual Regional Species Landings...9",
+                   "Maximum Percent Total Annual Regional Species Revenue...8") %>%
+    dplyr::rename("NEFMC, MAFMC, and ASMFC Managed Species" = "NEFMC and MAFMC Managed Species",
+                  "perc_landings_max" = "Maximum Percent Total Annual Regional Species Landings...9",
+                  "perc_revenue_max" = "Maximum Percent Total Annual Regional Species Revenue...8") %>%
     tidyr::drop_na() %>%
     dplyr::mutate(perc_landings_max = as.numeric(perc_landings_max)*100,
                   perc_revenue_max = as.numeric(perc_revenue_max)*100,
-                  Units = c("Percent"))
+                  Units = c("Percent")) %>%
+    dplyr::mutate(across(where(is.numeric), ~round(., 0))) %>%
+    dplyr::mutate(Council = "NEFSC")
+
+   # Add council data to dataset
+    mafmc <- list("Atlantic mackerel", "Black sea bass", "Bluefish", "Blueline tilefish", "Butterfish",
+                  "Atlantic chub mackerel", "Golden tilefish", "Illex squid", "Longfin squid",
+                  "Ocean quahog", "Scup", "Summer flounder", "Atlantic surfclam")
+
+    for (i in 1:length(mafmc)){
+      wea_landings_rev <- wea_landings_rev %>%
+        dplyr::mutate(Council = replace(Council, wea_landings_rev$`NEFMC, MAFMC, and ASMFC Managed Species` == mafmc[i], "MAFMC"))
+    }
+
+    wea_landings_rev <- wea_landings_rev %>%
+      dplyr::mutate(Council = replace(Council, wea_landings_rev$`NEFMC, MAFMC, and ASMFC Managed Species` == "Monkfish", "MAFMC/NEFMC")) %>%
+      dplyr::mutate(Council = replace(Council, wea_landings_rev$`NEFMC, MAFMC, and ASMFC Managed Species` == "Spiny dogfish", "MAFMC/NEFMC"))
 
   # metadata ----
   attr(wea_landings_rev, "tech-doc_url") <- "https://noaa-edab.github.io/tech-doc/fisheries-revenue-in-wind-development-areas.html"
   attr(wea_landings_rev, "data_files")   <- list(
-    wind_xlsx = wind_xlsx)
+    wind_rev_xlsx = wind_rev_xlsx)
   attr(wea_landings_rev, "data_steward") <- c(
     "Doug Christel <[email protected]>")
   attr(wea_landings_rev, "plot_script") <- list(
@@ -45,8 +62,3 @@ get_wea_landings_rev <- function(save_clean = F){
   }
 }
 get_wea_landings_rev(save_clean = T)
-
-
-
-
-