Extract P Data from ISRIC and Oak Ridge Maps

1 Loading Libraries

library(soilP)    # Phosphorus maps
library(raster)
library(sf)       # Loading shapefiles for background
library(ggplot2)

2 Loading stored data from previous workflow steps

data("ISRIC2011") # raster
data("soilclass") # raster attribute table
data_dir <- system.file("data", package = "soilP", mustWork = TRUE)
extdata_dir <- system.file("extdata", package = "soilP", mustWork = TRUE)

ascending order was manually assigned, maybe there could be a better order.

3 Loading Background Shapefile and Saving it to .Rdata format

GMBA_file <- file.path(extdata_dir, "GMBA mountain inventory_V1.1",
                 "GMBA mountain inventory_V1.1-World.shp")
mountain <- st_read(GMBA_file)

Reading layer `GMBA mountain inventory_V1.1-World' from data source `/Users/fvrodriguez/Library/R/3.4/library/soilP/extdata/GMBA mountain inventory_V1.1/GMBA mountain inventory_V1.1-World.shp' using driver `ESRI Shapefile'
Simple feature collection with 1003 features and 4 fields
geometry type:  MULTIPOLYGON
dimension:      XY
bbox:           xmin: -180 ymin: -55.72135 xmax: 180 ymax: 79.91116
epsg (SRID):    4326
proj4string:    +proj=longlat +datum=WGS84 +no_defs

save(mountain, file =  file.path(data_dir,"mountain.RData"))

4 Importing maize accession collection coordinates

accn_file <- system.file("extdata",
                         "F1PARENTS120.csv",
                         package = "soilP",
                         mustWork = TRUE)
accn_info <- read.csv(accn_file)
accn_info$Elevation_class <- classify_elevation(accn_info$Elevation)

5 Using ISRIC data

ISRIC_P <- extract_P_ISRIC(ISRIC2011, accn_info, soilclass,
                           lon = "Long", lat = "Lat")

Joining, by = "ascending"

5.1 Plotting phosphorus retention map

bg_map("Long", "Lat", data = ISRIC_P$georef, bg = mountain) +
  ggtitle(paste0("Accession selection for F1s")) +
  geom_point(aes(x = Long, y = Lat,
                 shape = Elevation_class,
                 colour = main), 
                 data = ISRIC_P$georef) +
  scale_color_manual(values = ISRIC_P$pal,
                     name = "Phosphorus\nRetention\nPotential",
                     breaks = ISRIC_P$breaks ) +
  scale_shape_manual(values = c(16, 17)) +
  theme(legend.key.size = unit(0.5, 'lines'))

6 Using Oak Ridge National Laboratory Phosphorus Model

nc_in <- file.path(extdata_dir,
              "GLOBAL_PHOSPHORUS_DIST_MAP_1223",
              "data", "pforms_den.nc")
ORNL2013 <- read_P_ORNL(nc_in)
save(ORNL2013,file = file.path(data_dir,"ORNL2013.RData"))

ORNL_P <- extract_P_ORNL(ORNL2013, ISRIC_P$georef,
                         lon = "Long", lat = "Lat" )

6.1 Plotting phosphorus availability map

bg_map("Long", "Lat", data = ORNL_P$georef, bg = mountain) +
  ggtitle(paste0("Accession selection for F1s")) +
  geom_point(aes(x = Long, y = Lat,
                 shape = Elevation_class,
                 colour = lab), 
             data = ORNL_P$georef) +
  scale_colour_gradientn(name = "Labile Inorganic\nPhosphorus",
                         colours = ORNL_P$pal(180),
                         limits = c(1, 180)) +
  scale_shape_manual(values = c(16, 17))

7 Compare ISRIC vs ORNL

boxplot(lab ~ main, las = 2, data = ORNL_P$georef,
        main = paste0("Corresponcence between Phosphorus Maps\n",
                      "ORNL 2013 Vs ISRIC 2011"),
        xlab = "Phosphorus Retention Potential Main Class",
        ylab = "Labile Inorganic Phosphorus")

pairs(ORNL_P$georef[,c("ascending", names(ORNL2013))])