Imported cultural values grids and added new script for cultural valu…

…es Mollusca as sample

Mollusca.Rmd

@@ -51,6 +51,16 @@ figs$reportingStatusMap
 figs$reportingStatusFig
 ```
 
+## Molluscs with Indigenous cultural significance
+
+These include the [Giant pacific octopus](#taxon:Enteroctopus dofleini), known in Hul'qumi'num as [**sqi'mukw**](#taxon:Enteroctopus dofleini).
+
+```{r, echo=FALSE, message=FALSE, warning=FALSE}
+source("scripts/Cultural_map_script.R")
+animal.cultural.map <- mx_cultural_map("mollusca")
+animal.cultural.map
+```
+
 ## Top community contributions to our knowledge of the island mollusc diversity
 
 Here, you can browse photos of mollusc species commonly documented around Galiano Island, as well as recent observations, most favourited observations, and top observers, based on [iNaturalist](http://inaturalist.org/) data. Please help contribute to the growing record of the island mollusc diversity by submitting your observations to the [Biodiversity Galiano iNaturalist project.](http://inaturalist.org/projects/biodiversity-galiano-island) 

scripts/Cultural_map_script.R

@@ -0,0 +1,78 @@
+# Map Galiano Island's marine animal diversity
+
+# Load libraries
+
+library(dplyr)
+library(leaflet)
+library(raster)
+library(reshape2)
+library(rjson)
+library(scales)
+library(sf)
+library(stringr)
+library(viridis)
+
+# Source dependencies
+
+source("scripts/utils.R")
+
+mx_diversityRowToOptions <- function (row) {
+  return (list(mx_regionId = row$cell_id, mx_richness = row$richness))
+}
+
+mx_cultural_map <- function (taxon) {
+    title <- str_to_title(taxon);
+
+    # Read gridded marine animal dataset
+
+    gridded.records <- read.csv(str_glue("tabular_data/{taxon}_all_records_gridded.csv"))
+
+    hulq <- read.csv("tabular_data/reintegrated-hulq.csv")
+    hulqTaxa <- hulq$Taxon.name
+
+    # Filter only those records with cultural values
+    cultural.records <- gridded.records[gridded.records$scientificName %in% hulqTaxa, ]
+
+    # Summarize species by grid cell and export to JSON file for viz
+
+    culturalTaxa <- mx_griddedObsToHash(cultural.records)
+
+    culturalData <- list(taxa = culturalTaxa, mapTitle = str_glue("Diversity for {title} with cultural values"))
+
+    mx_writeJSON(culturalTaxa, str_glue("viz_data/Cultural-{taxon}PlotData.json"))
+
+    # Load choropleth
+
+    choropleth <- mx_read(str_glue("spatial_data/vectors/{taxon}_hulq_grid"))
+
+    # Plot choropleth
+
+    richness <- choropleth$richness
+    t <- max(richness)
+    values <- 0:t
+    pal <- leaflet::colorNumeric(viridis_pal(option = "D")(t), domain = values)
+
+    # Plot map
+
+    culturalMap <- leaflet(options=list(mx_mapId="Cultural")) %>%
+      fitBounds(-123.6, 48.85,  -123.2917, 49.03) %>%
+      addTiles(options = providerTileOptions(opacity = 0.5)) %>%
+      addLegend(position = 'topright',
+                pal = pal,
+                bins = ifelse(t < 5, t, 5),
+                values = values,
+                title = "Richness",
+                labels = values)
+
+    # Draw the gridded data in a funny way so that richness, cell_id etc. can be tunnelled through options one at a time
+    for (i in 1:nrow(choropleth)) {
+      row <- choropleth[i,]
+      culturalMap <- culturalMap %>% addPolygons(data = row, fillColor = pal(row$richness), fillOpacity = 0.4, weight = 0,
+                                                   popup = paste("Richness:", row$richness), 
+                                                   popupOptions = popupOptions(closeButton = FALSE),
+                                                   options = mx_diversityRowToOptions(row))
+    }
+
+    #Note that this statement is only effective in standalone R
+    print(culturalMap)   
+}

scripts/Diversity_map_script.R

@@ -68,5 +68,6 @@ mx_diversity_map <- function (taxon) {
     }
 
     #Note that this statement is only effective in standalone R
-    print(diversityMap)    
+    print(diversityMap)  
+
 }

spatial_data/vectors/crustacea_hulq_grid/crustacea_hulq_grid.prj

@@ -0,0 +1 @@
+PROJCS["WGS_1984_UTM_Zone_10N",GEOGCS["GCS_WGS_1984",DATUM["D_WGS_1984",SPHEROID["WGS_1984",6378137.0,298.257223563]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",500000.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-123.0],PARAMETER["Scale_Factor",0.9996],PARAMETER["Latitude_Of_Origin",0.0],UNIT["Meter",1.0]]

spatial_data/vectors/echinodermata_hulq_grid/echinodermata_hulq_grid.prj

@@ -0,0 +1 @@
+PROJCS["WGS_1984_UTM_Zone_10N",GEOGCS["GCS_WGS_1984",DATUM["D_WGS_1984",SPHEROID["WGS_1984",6378137.0,298.257223563]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",500000.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-123.0],PARAMETER["Scale_Factor",0.9996],PARAMETER["Latitude_Of_Origin",0.0],UNIT["Meter",1.0]]

spatial_data/vectors/fishes_hulq_grid/fishes_hulq_grid.prj

@@ -0,0 +1 @@
+PROJCS["WGS_1984_UTM_Zone_10N",GEOGCS["GCS_WGS_1984",DATUM["D_WGS_1984",SPHEROID["WGS_1984",6378137.0,298.257223563]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",500000.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-123.0],PARAMETER["Scale_Factor",0.9996],PARAMETER["Latitude_Of_Origin",0.0],UNIT["Meter",1.0]]

spatial_data/vectors/mammalia_hulq_grid/mammalia_hulq_grid.prj

@@ -0,0 +1 @@
+PROJCS["WGS_1984_UTM_Zone_10N",GEOGCS["GCS_WGS_1984",DATUM["D_WGS_1984",SPHEROID["WGS_1984",6378137.0,298.257223563]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",500000.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-123.0],PARAMETER["Scale_Factor",0.9996],PARAMETER["Latitude_Of_Origin",0.0],UNIT["Meter",1.0]]

spatial_data/vectors/mollusca_hulq_grid/mollusca_hulq_grid.prj

@@ -0,0 +1 @@
+PROJCS["WGS_1984_UTM_Zone_10N",GEOGCS["GCS_WGS_1984",DATUM["D_WGS_1984",SPHEROID["WGS_1984",6378137.0,298.257223563]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",500000.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-123.0],PARAMETER["Scale_Factor",0.9996],PARAMETER["Latitude_Of_Origin",0.0],UNIT["Meter",1.0]]