pcod: A Package to Run the Interim PCOD Code

# config.R - to allow users to set all relevant parameters
# in one location. This will be sourced first during the run
# and parameters will be updated from these inputs
rm(list = ls())

# Set a unique ID for this run that can be used to name the output files:
runID <- 1
# Set the number of times you want to run the simulation 
nboot <- 5#00

# set species code. Here are the valid values: 
# BND = bottlenose dolphin
# GS = grey seal
# HPL = harbour porpoise - low Adult survival
# HPH = harbour porpoise - high Adult survival
# HS = harbour seal
# MW = minke whale

spec <- 'HS'
# Based on spec, set up which make init file to run
if(spec == 'BND'){minit.file <- 'MakeInitScenariosBND.R'}
if(spec == 'GS'){minit.file <- 'MakeInitScenariosGS.R'}
if(spec == 'HPL'){minit.file <- 'MakeInitScenarioHP_low_ad_surv.R'}
if(spec == 'HPH'){minit.file <- 'MakeInitScenarioHP_high_ad_surv.R'}
if(spec == 'HS'){minit.file <- 'MakeInitScenariosHS.R'}
if(spec == 'MW'){minit.file <- 'MakeInitScenariosMW.R'}

# Proportions of females in the population 
propfemale <- 0.5

# set threshold size for demographic stochasticity
threshold <- 500
# set population size
pmean <- 4658
Surv <- rep(0,18)
# set calf/pup survival
Surv[1] <- 0.6
# set juvenile survival
Surv[7] <- 0.82
# set adult survival
Surv[13] <- 0.85
# set fecundity value
Fertility <- 0.95
# set age at which a calf or pup becomes independent of its mother
age1 <- 1
#set age at which an average female gives birth to her first calf
age2 <- 4

# set number of years on which piling will occur. Set this to zero if there is no piling
pile_years <- 1
# specify name of csv file that contains information on days on which piling will occur between the quotation marks
# read csv file with schedule of piling activities. 
piling.file <- "MultPilingOpsMultYears.csv"
pile <- read.csv(file = piling.file, header = TRUE)

# input number of piling operations to be modelled
pilesx1 <- 3

# input proportion of animals in each of the vulnerable sub-population(s), default is that the entire population is vulnerable
vulnmean <- c(1)
nvulnmean <- length(vulnmean)

# vulnpile is a matrix indicating which columns of pile are to be combined to provide piling information for each vulnerable sub-population
vulnpile <- matrix(0, nrow = nvulnmean, ncol = pilesx1)

# indicate which operations will affect each vulnerable sub-population
vulnpile[1, ] <- c(1)

# "seasons" determines whether or not the number of animals that are likely to be disturbed each day (NDt) 
# and the number that may experience PTS (NPt) vary by season. seasons = 1, no seasonal variation is the default value; 
# if seasons > 1, remember that the simulated year starts in June, for all species except GS, when it starts in October!
# if seasons = 4, 4 there are seasons in a year. summer = June, July, August; autumn = Sept, Oct, Nov; winter = Dec, Jan, Feb; spring = March, April, May                          
# if seasons = 2 (ie just summer and winter), we will actually require 3 breaks, assuming "summer" = May - October (ie months when water is warmest)

seasons <- 1
# I THINK WE MAY HAVE TO GIVE UP ON EXPLICITLY MODELLING THESE VARIATIONS WITHIN A PILING OPERATION. IT’S SIMPLER TO DIVIDE EACH PILING OPERATION INTO SEPARATE SUB-OPERATIONS FOR EACH SEASON.

# input number of animals predicted to experience significant disturbance on one day of piling for each operation
# in this example, there are three operations each of which disturbs 60 animals
numDT <- c(60, 60, 60)

# now do the same for the number of animals predicted to experience PTS on one day of piling
numPT <- c(2, 2, 2)

# input number of days of "residual" disturbance. DEFAULT IS 1
days <- 1

# decide if PTS can occur on any day (default) or only on the first occasion that an individual is disturbed by 
# change Day1 to TRUE if you want animals to be only vulnerable to PTS on the first day they are disturbed
Day1 <- FALSE

#number of years for simulation
years <- 25

# input number of animals predicted to be killed each year as a result of collisions with tidal energy arrays
NCollisions <- 0

# prop_dist is the proportion of disturbed animals that experience residual days of disturbance if days < 1
prop_dist <- 1