create_data_input {SharkDemography} | R Documentation |
The demography functions in this package require a large amount of detailed life history information. This is provided to these functions as a multi-level list of various life history parameters with the class 'Demography.inputs'. This function creates the template for this input data which can be filled in after it is created.
create_data_input(maturity.type, t0 = FALSE)
maturity.type |
The type of maturity estimates from the source life history study. must be one of 'logistic - int/slope', 'logistic - a50/a95', 'normal' or 'uniform'. |
t0 |
Logical argument regarding whether the growth models included "t0" or "L0" as as a parameter. Default is 'FALSE' |
A multi-level list of the class 'Demography.inputs'
######-----------
# Example code for Silky sharks
######-----------
silky_data <- create_data_input("logistic - int/slope", t0 = FALSE)
# Add growth data
silky_data$`growth`$model.type <- "logistic"
silky_data$growth$pars$Linf <- 268
silky_data$growth$pars$k <- 0.14
silky_data$growth$pars$L0 <- 82.7
silky_data$growth$se$Linf.se <- 5.8
silky_data$growth$se$k.se <- 0.006
silky_data$growth$se$L0.se <- 1.6
silky_data$growth$corr.matrix <- matrix(ncol = 3, nrow = 3,
dimnames = list(c("Linf", "k", "L0"),c("Linf", "k", "L0")),
data = c(1.0000000, -0.907188, 0.6233407,
-0.9071881, 1.0000000, -0.8572509,
0.6233407,-0.857250, 1.0000000))
# Add maturity data
silky_data$maturity$pars$intercept <- -15.90
silky_data$maturity$pars$slope <- 1.14
silky_data$maturity$se$intercept.se <- 2.78258
silky_data$maturity$se$slope.se <- 0.1971363
silky_data$maturity$corr.matrix <- matrix(ncol = 2, nrow = 2,
dimnames = list(c("Intercept", "slope")
,c("Intercept", "slope")),
data = c(1.0000000, -0.9922574,
-0.9922574, 1.0000000))
# max age lower bound
silky_data$max.age$min <- 28
# Add fecundity info
silky_data$litter.size$mean <- 10
silky_data$litter.size$se <- 3
silky_data$gest.period <- 1
silky_data$repro.cycle <- 2
# Add TL conversions (if available and required)
silky_data$Lt.type <- "TL"
silky_data$Lt.to.Wt$model.type <- "PCL"
silky_data$Lt.to.Wt$pars$a <- 2.73e-5
silky_data$Lt.to.Wt$pars$b <- 2.86
silky_data$convert.TL$model.type <- "PCL"
silky_data$convert.TL$pars$a <- 2.08
silky_data$convert.TL$pars$b <- 1.32