species_report.Rmd

---
title: "species_report"
output: html_document
params:
  nspeciestable: NA
  speciesdata: NA
  speciesrast: NA
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```

```{r, echo=FALSE}
# Load the required libraries
library(ggplot2)
library(gtable)
library(grid)
library(leaflet)
library(sp)
library(rgdal)
library(raster)
library(RColorBrewer)
library(plotly)
library(dplyr)
```


## What is this document?

This markdown document was produced from the Shark Explorer App (SEA), which is currently hosted at <http://rossdwyer.shinyapps.io/sharkray_mpa/>.

This report presents data for the species...
```{r, echo=FALSE}
# Sort out the species data table
sharkdat2 <- params$speciesdata # The `params` object available in the document.
#names(sharkdat)[1] <- 'binomial' # Ensures continuity between pages
sharkdat2 <- sharkdat2 %>%
  select(FBname,order_name,family_nam,
         binomial,Length,
         DemersPelag,Vulnerability,Resilience,
         code)
levels(sharkdat2$Resilience) <- c("Very low", "Low", "Medium", "High")

sharkdat2$FBname[params$nspeciestable]

####

specName <- as.character(params$speciesdata$binomial[params$nspeciestable])  # Assign the row number to the df to extract the species name

specName
```


Which has the following attributes
```{r, echo=FALSE}
sharkdat2[params$nspeciestable,]
```

An interactive map showing the species distribution
```{r, echo=FALSE, message=FALSE, warning=FALSE}
pal <- c("#de2d26","#f93")

# Assign the species raster
 newdata <- params$speciesrast
 newdata[newdata <= 0] <- NA 

 leaflet() %>% 
   setView(lng = 0, lat = 0,  zoom = 1) %>% 
   addProviderTiles(providers$OpenStreetMap.BlackAndWhite) %>%
   addLegend(colors = pal[1], # Adds new legend with species name (binomial)
             position = "topright",
             labels = specName) %>%
   addRasterImage(layerId ="layer2",
                  newdata,
                  colors=pal[1], 
                  opacity = 0.5) %>%
   mapOptions(zoomToLimits = "first")

```

The Vulnerability plot
```{r, echo=FALSE}
par(mar = c(4, 4, 1, .1), font.axis = 2,font.lab = 2) # stops the arial font issue   
ggplot(data = params$speciesdata,
       aes(x = code, y = Vulnerability, 
           fill = pointborder,colour = pointborder
       )) + 
  geom_dotplot(dotsize = 0.4,binwidth = 2, 
               binaxis = "y", stackdir = "center", binpositions="all") + 
  scale_fill_manual(values=c("#d3d3d3"))+
  scale_color_manual(values=c("#d3d3d3"))+
  scale_x_discrete(limits=c("CR", "EN", "VU", "NT", "LC", "DD"))+
  labs(title="",x="IUCN code", y = "Vulnerability Index")+
  theme_minimal()+
  theme(legend.position="none") # Remove legend
```

The dispersal data plot is shown in the box below.

```{r, echo=FALSE}
#Read in Dispersal distance data
# Df <- read.csv("Data/DispersalKernel_Properties.csv")
# # Add a column detailing if we have Dispersal distance data for a species
# sharkdat$DispersalKernel <- "No"
# for (i in 1:nrow(Df)){
#   inum <- which(as.character(sharkdat$binomial)==as.character(Df$ScientificName[i]))
#   sharkdat$DispersalKernel[inum] <- "Yes"
# }
# 
# Function to make the empty dispersal plot
makeDispersalplot <- function(xmax=1000){
  xx <- seq(0, log(xmax), length=1000)
  yy <- rep(0,length(xx))

  #par(oma = c(0.1,1,2,1.5))
  par(mar = c(4, 4, 2, .5), font.axis = 2,font.lab = 2) # stops the arial font issue
  plot(x=xx,y=yy, xaxt="n", las=1,
       xlab="Maximum dispersal distance (km)",
       ylab="Probability of dispersal", type="n",ylim=c(0,1),
       bty="l")
  axis(1, at= log(c(0.01, seq(0.1,1,l=10),
                    seq(1,10,l=10),seq(10,100,l=10),
                    seq(100,1000,l=10),
                    seq(1000,10000,l=10))+1), labels=F, tcl=-0.3)
  axis(1, at= log(c(0.1,1,10,100,1000,10000)+1),
       labels=c(0.1,1,10,100,1000,10000))

  legend("top",bty="n",
         inset = c(0,-0.13),
         xpd = TRUE, horiz = TRUE,
         lty=1,lwd=2,
         col=c(1:3),
         legend = c("Mark-recapture",
                    "Passive acoustic",
                    "Satellite"))
}

makeDispersalplot(1500) 
```