Especies exóticas marino-costeras de Argentina

---
title: "Inicio"
output: 
  flexdashboard::flex_dashboard:
    theme: flatly
    social: menu
    source: embed
    orientation: columns
    logo: http://obsermar.com.ar/wp-content/uploads/2020/11/logoFDSHB-W.png
---

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

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

```

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

#Extract data from the project "biodiversidad-marina-bahia-pardelas"
project_info <- exoticas_obs <- get_inat_obs_project("especies-exoticas-marino-costeras-de-argentina", type = "info", raw = FALSE)

#extract observations
exoticas_obs <- get_inat_obs_project(project_info$id, type = "observations")

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

#preparar dataframe para el mapa
link <- paste("<a href='https://www.inaturalist.org/observations/", exoticas_obs$id, "' target='_blank'>Ver observación<a>", sep = "")
exoticas_obs_dataframe_map <- cbind(exoticas_obs_dataframe[,c(1,5,4,2,3)], link)
#colores

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

obs_byyear = as.data.frame(table(exoticas_obs_dataframe$year), stringsAsFactors = F)
obs_byyear$Var1 <- as.numeric(obs_byyear$Var1)

colnames(obs_byyear)=c("Año","Observaciones") 

# Especies más observadas
spp_bycount = as.data.frame(sort(table(exoticas_obs_dataframe$name), decreasing = T))[1:10,]
colnames(spp_bycount)=c("Especie","Observaciones") 

```

# Especies exóticas marino-costeras de Argentina

## Column1{data-width=250}
  
### Número de especies registradas   {data-width=200}
```{r species}
especies <- length(unique(exoticas_obs_dataframe$name))
valueBox(24, caption = "Especies exóticas", icon = "fas fa-fish")
``` 

### Numero de observaciones
```{r observat}
observaciones <- length(exoticas_obs_dataframe$name)
valueBox(value = observaciones, caption = "Observaciones", icon = "fas fa-eye")
``` 

### Numero de observadores
```{r observer}
observadores <- length(unique(exoticas_obs_dataframe$user))
valueBox(value = observadores, caption = "Observadores", icon = "fas fa-user-friends")
``` 

### Observaciones por año
```{r obs_byyear}
#plot number of observation by date 
p1 <- ggplot(obs_byyear, aes(x=Año,y=Observaciones))+ 
  geom_point(col = "#359e8b", size = 2)+ 
  geom_line(col = "#359e8b") + 
  xlab("Año") + 
  ylab("Número de observaciones") + 
  theme_light()
ggplotly(p1)

```

## Column2 {.tabset .tabset-fade}
  
### Observaciones

```{r map}
  # plot ocurrences
map_leaflet(exoticas_obs_dataframe_map) %>% 
  addMiniMap(toggleDisplay = T)
```

## Column3 {data-width=300 .tabset .tabset-fade}

### Observaciones por especie
```{r taxalist}
knitr::kable(as.data.frame(table(reorder(exoticas_obs_dataframe$name,rep(-1,length(exoticas_obs_dataframe$name)),sum))),col.names = c("Especies","Número de observaciones"))

```