---
title: "Biodiversidad Marina Bahía Pardelas"
output: 
  flexdashboard::flex_dashboard:
    theme: lumen
    social: menu
    source: embed
    logo: https://www.proyectosub.org.ar/wp-content/uploads/2020/04/logoinatproyectosub.png
---

```{r setup, include=FALSE}
library(flexdashboard)
library(leaflet)
library(ggplot2)
library(plotly)
library(spocc)
library(rinat)
library(mapr)


library(RColorBrewer)
palette(brewer.pal(8, "Set2"))


```

```{r dataread, message=FALSE, warning=FALSE, include=FALSE}


#Extract data from the project "biodiversidad-marina-bahia-pardelas"
#projecy_info <- pardelas_obs <- get_inat_obs_project("biodiversidad-marina-bahia-pardelas", type = "info", raw = FALSE)

#extract observations
#pardelas_obs <- get_inat_obs_project(projecy_info$id, type = "observations")

#create data frame with reduced info
#pardelas_obs_dataframe <- data.frame(name = pardelas_obs$taxon.name,longitude = as.numeric(pardelas_obs$longitude),latitude = as.numeric(pardelas_obs$latitude),user=pardelas_obs$user_login,date= as.Date(pardelas_obs$observed_on), taxonrank=pardelas_obs$taxon.rank,taxonid=pardelas_obs$taxon.id,taxon= pardelas_obs$iconic_taxon.name, stringsAsFactors = FALSE)

#As some of the taxon information  (eg Phylum) is not included in the rinat package we proceed to import data from csv. the package "spocc" shoul be explored for download data.

#Read data downloaded from inat site 
pardelas_obs_web <- read.csv("observations-2022.csv")

#we create a dataframe with the variable of interest.
pardelas_obs_dataframe <- data.frame(
name = pardelas_obs_web$scientific_name,
longitude = pardelas_obs_web$longitude,
latitude = pardelas_obs_web$latitude,
user=pardelas_obs_web$user_login,
date= as.Date(pardelas_obs_web$observed_on),
taxonid=pardelas_obs_web$id,
taxon= pardelas_obs_web$iconic_taxon_name,
kindom= pardelas_obs_web$taxon_kingdom_name,
phylum=pardelas_obs_web$taxon_phylum_name,
class=pardelas_obs_web$taxon_class_name,
order=pardelas_obs_web$taxon_order_name,
genus=pardelas_obs_web$taxon_genus_name,
stringsAsFactors = FALSE)

#add year from date info
pardelas_obs_dataframe$year <- as.numeric(format(pardelas_obs_dataframe$date,"%Y"))

obs_byyear = as.data.frame(table(pardelas_obs_dataframe$year))
colnames(obs_byyear)=c("Año","Observaciones") 

```


Column1{data-width=250}
-------

### Tabla Observaciones {data-width=245}
```{r taxalist}
knitr::kable(as.data.frame(table(reorder(pardelas_obs_dataframe$name,rep(-1,length(pardelas_obs_dataframe$name)),sum))),col.names = c("Especies","Observaciones"))

```


Column2 {.tabset .tabset-fade}
-------

### Mapa
```{r map, message=FALSE, warning=FALSE}

library(XML)
library(OpenStreetMap)
library(lubridate)
library(ggmap)
library(ggplot2)
library(raster)
library(sp)

options(digits=10)
# Reaf the GPX file of each reef track- read one by one and then stored in a dataframe (reef1, reef2..)
pfile <- htmlTreeParse(file = "DII_22-MAR-19_12hs.gpx", error = function(...) {
}, useInternalNodes = T)
elevations <- as.numeric(xpathSApply(pfile, path = "//trkpt/ele", xmlValue))
times <- xpathSApply(pfile, path = "//trkpt/time", xmlValue)
coords <- xpathSApply(pfile, path = "//trkpt", xmlAttrs)
lats <- as.numeric(coords["lat",])
lons <- as.numeric(coords["lon",])
#save track reef in data frame
track_reef1 = data.frame(lon = lons,
                         lat = lats)

pfile <- htmlTreeParse(file = "DI_11-MAR-19_14hs.gpx", error = function(...) {
}, useInternalNodes = T)
elevations <- as.numeric(xpathSApply(pfile, path = "//trkpt/ele", xmlValue))
times <- xpathSApply(pfile, path = "//trkpt/time", xmlValue)
coords <- xpathSApply(pfile, path = "//trkpt", xmlAttrs)
lats <- as.numeric(coords["lat",])
lons <- as.numeric(coords["lon",])
#save track reef in data frame
track_reef2 = data.frame(lon = lons,
                         lat = lats)

pfile <- htmlTreeParse(file = "MIII_26-MAR-19_13hs.gpx", error = function(...) {
}, useInternalNodes = T)
elevations <- as.numeric(xpathSApply(pfile, path = "//trkpt/ele", xmlValue))
times <- xpathSApply(pfile, path = "//trkpt/time", xmlValue)
coords <- xpathSApply(pfile, path = "//trkpt", xmlAttrs)
lats <- as.numeric(coords["lat",])
lons <- as.numeric(coords["lon",])
#save track reef in data frame
track_reef3 = data.frame(lon = lons,
                         lat = lats)

pfile <- htmlTreeParse(file = "MII_11-MAR-19_13hs.gpx", error = function(...) {
}, useInternalNodes = T)
elevations <- as.numeric(xpathSApply(pfile, path = "//trkpt/ele", xmlValue))
times <- xpathSApply(pfile, path = "//trkpt/time", xmlValue)
coords <- xpathSApply(pfile, path = "//trkpt", xmlAttrs)
lats <- as.numeric(coords["lat",])
lons <- as.numeric(coords["lon",])
#save track reef in data frame
track_reef4 = data.frame(lon = lons,
                         lat = lats)

pfile <- htmlTreeParse(file = "MI_22-MAR-19_14hs.gpx", error = function(...) {
}, useInternalNodes = T)
elevations <- as.numeric(xpathSApply(pfile, path = "//trkpt/ele", xmlValue))
times <- xpathSApply(pfile, path = "//trkpt/time", xmlValue)
coords <- xpathSApply(pfile, path = "//trkpt", xmlAttrs)
lats <- as.numeric(coords["lat",])
lons <- as.numeric(coords["lon",])
#save track reef in data frame
track_reef5 = data.frame(lon = lons,
                         lat = lats)

pfile <- htmlTreeParse(file = "SII_26-MAR-19_14hs.gpx", error = function(...) {
}, useInternalNodes = T)
elevations <- as.numeric(xpathSApply(pfile, path = "//trkpt/ele", xmlValue))
times <- xpathSApply(pfile, path = "//trkpt/time", xmlValue)
coords <- xpathSApply(pfile, path = "//trkpt", xmlAttrs)
lats <- as.numeric(coords["lat",])
lons <- as.numeric(coords["lon",])
#save track reef in data frame
track_reef6 = data.frame(lon = lons,
                         lat = lats)

pfile <- htmlTreeParse(file = "SI_11-MAR-19_14hs.gpx", error = function(...) {
}, useInternalNodes = T)
elevations <- as.numeric(xpathSApply(pfile, path = "//trkpt/ele", xmlValue))
times <- xpathSApply(pfile, path = "//trkpt/time", xmlValue)
coords <- xpathSApply(pfile, path = "//trkpt", xmlAttrs)
lats <- as.numeric(coords["lat",])
lons <- as.numeric(coords["lon",])
#save track reef in data frame
track_reef7 = data.frame(lon = lons,
                         lat = lats)


photoicon <- makeIcon(
  iconUrl = "https://www.proyectosub.org.ar/wp-content/uploads/2021/03/cameraicon.png",
  iconWidth = 15, iconHeight = 13,
  iconAnchorX = 15, iconAnchorY = 13)

seapen <- paste("",sep = "
",paste0(""),paste0("Place: ", "Sea Pen"),paste0("Species: ", "Stylatula"))

reef <- paste("",sep = "
",paste0(""),paste0("Place: ", "Rocky Reef"))

overhang <- paste("",sep = "
",paste0(""),paste0("Place: ", "Rocky Reef Overhang"))

sandripplesunderwater <- paste("",sep = "
",paste0(""),paste0("Place: ", "sand ripples underwater"))


leaflet() %>% 
  addMiniMap(toggleDisplay = T) %>% 
  addProviderTiles(providers$Esri.WorldImagery) %>%
addCircleMarkers(data = pardelas_obs_dataframe, ~longitude, ~latitude,weight = 0.5,col = 'green', fillColor = 'green',radius = 4, fillOpacity = 0.5, stroke = T, label =pardelas_obs_dataframe$name,group = 'Observaciones')%>% 
addMarkers(-64.256072,-42.625413, popup=seapen, icon = photoicon,group = 'Habitat')%>% 
addMarkers(-64.265982,-42.623450, popup=reef,icon = photoicon,group = 'Habitat')%>%
addMarkers(-64.260400,-42.623689, popup=overhang,icon =photoicon, group = 'Habitat')%>% 
addMarkers(-64.278155,-42.617193, popup=sandripplesunderwater,icon =photoicon, group = 'Habitat')%>%
addPolylines(data = track_reef1, ~lon, ~lat,
               weight = 3,
               color = 'red',
               popup = 'This is a line!', 
               smoothFactor = 3,
               group = 'Arrecifes')%>%
addPolylines(data = track_reef2, ~lon, ~lat,
               weight = 3,
               color = 'red',
               popup = 'This is a line!', 
               smoothFactor = 3,
               group = 'Arrecifes')%>%
  addPolylines(data = track_reef3, ~lon, ~lat,
               weight = 3,
               color = 'red',
               popup = 'This is a line!', 
               smoothFactor = 3,
               group = 'Arrecifes')%>%
  addPolylines(data = track_reef4, ~lon, ~lat,
               weight = 3,
               color = 'red',
               popup = 'This is a line!', 
               smoothFactor = 3,
               group = 'Arrecifes')%>%
  addPolylines(data = track_reef5, ~lon, ~lat,
               weight = 3,
               color = 'red',
               popup = 'This is a line!', 
               smoothFactor = 3,
               group = 'Arrecifes')%>%  
  addPolylines(data = track_reef6, ~lon, ~lat,
               weight = 3,
               color = 'red',
               popup = 'This is a line!', 
               smoothFactor = 3,
               group = 'Arrecifes')%>%  
  addPolylines(data = track_reef7, ~lon, ~lat,
               weight = 3,
               color = 'red',
               popup = 'This is a line!', 
               smoothFactor = 3,
               group = 'Arrecifes')%>%
addLayersControl(overlayGroups = c('Habitat',
                                   'Observaciones','Arrecifes'),options = layersControlOptions(collapsed = FALSE),position = 'topright')


```


### Phylum 
```{r donut}
##numbers of observations by phylum 
taxranks = as.data.frame(table(pardelas_obs_dataframe$phylum))
##Donut plot
p = taxranks %>% plot_ly(labels = ~Var1, values=~Freq) %>% 
  add_pie(hole=0.6) %>% 
  layout(title = ~paste0("Numero total de Taxa: ", length(unique(pardelas_obs_dataframe$taxonid)))) 

plotly::config(p,displayModeBar = F) 
```

### Observaciones por año
```{r obsbyyear}
#plot number of observation by date 
ggplot(obs_byyear, aes(x=Año,y=Observaciones,group=1)) + geom_line() + geom_point()+ xlab("Año") + ylab("Observaciones") + theme_minimal()

```


Column3{data-width=150}
-------

### Números
```{r}
#spp 
nspp = length(unique(pardelas_obs_dataframe$genus))
gauge(nspp, min=0, max=100,label="Genus")

#invertebrates
ninvertebrates = length(unique(pardelas_obs_dataframe$name[pardelas_obs_dataframe$phylum=="Porifera"|pardelas_obs_dataframe$phylum=="Mollusca"|pardelas_obs_dataframe$phylum=="Cnidaria"|pardelas_obs_dataframe$phylum=="	Echinodermata"|pardelas_obs_dataframe$phylum=="Bryozoa"|pardelas_obs_dataframe$phylum=="Platyhelminthes"|pardelas_obs_dataframe$phylum=="Arthropoda"|pardelas_obs_dataframe$phylum=="Brachiopoda"]))
gauge(ninvertebrates, min=0, max=100,label="Invertebrados")

#Ascidiacea
nAscidiacea = length(unique(pardelas_obs_dataframe$name[pardelas_obs_dataframe$class=="Ascidiacea"]))
gauge(nAscidiacea, min=0, max=100,label="Ascidiacea")

#fish
nfish = length(unique(pardelas_obs_dataframe$name[pardelas_obs_dataframe$taxon=="Actinopterygii"]))
gauge(nfish, min=0, max=100,label="Peces")

#algae
nPlants = length(unique(pardelas_obs_dataframe$name[pardelas_obs_dataframe$kindom=="Plantae"| pardelas_obs_dataframe$taxon=="Chromista"]))
gauge(nPlants, min=0, max=100,label="Algas",sectors = gaugeSectors(success = c(0, 40),
                             warning = c(40, 60),
                             danger = c(60, 100),
                             colors = c("green", rgb(0, 1, 0), "#CC664D")))
```