#Author: Hannah Edwards
#Population density estimates of spotted hyaena (Crocuta crocuta) in two KwaZulu-Natal protected areas
#SECR model for the uMkhuze 2019 density estimate with a 20km buffer

#There are three input files for each SECR model:
#"..._td_ml.txt" Trap deployment file - contains the ID number of each detector (camera trap station), the X and Y coordinates of the spatial location of the camera trap stations, and whether the camera station was active (1; at least one camera active) or non-active (0; both cameras inactive) on each sampling occasion.
#"..._ac_ml.txt" Capture history file - contains the animal identity, camera trap station, and sampling occasion of captures of identified spotted hyaenas.
#"...SS.csv" state-space file - contains a binary matrix of suitable (1) and unsuitable (0) habitat for spotted hyaenas within the study site. I removed all "unsuitable" habitat before importing the state-space file into R.

#Clear R workspace
rm(list=ls())

#Load the secr library
library(secr)
library(sp)
library(rgdal)

#Set the working directory - 20,000 buffer
setwd("C:/Users/hedwa/Desktop/Hyaena Project/SECR Models/S3_uMkhuze_2019_SECR/SECR_Inputs_S3_uMkhuze_2019_20000 buffer")

#Load the secr input data
trap.obj<-read.traps('S3_20190811_20191004_Hyaena_Spotted_td_ml.txt',detector="proximity",
                     binary.usage=T)

#Remember to remove all non-habitat rows from SS csv and then delete 'Habitat' column
#change X-Coord and Y_Coord to X and Y

msk<-read.mask(file= 'S3_20190811_20191004_Hyaena_Spotted_SS.csv',spacing=500,header=T)

ch<-read.capthist("S3_20190811_20191004_Hyaena_Spotted_ac_ml.txt","S3_20190811_20191004_Hyaena_Spotted_td_ml.txt",
                  detector="proximity",fmt="trapID",noccasions=55)

#Run the model - Keep sigma and g0 constant
model_null <- secr.fit(ch, model = list(D ~ 1, g0 ~ 1, sigma ~ 1),
                        mask = msk, detectfn = 0, hcov = NULL, trace = F,
                        method = "Nelder-Mead",control = list(maxit = 9999))

model_null