Get a set of simulation results from the national demographic model

Source: R/getSimsNational.R

Get a set of simulation results from the national demographic model

getSimsNational(
  replicates = 1000,
  N0 = 1000,
  Anthro = seq(0, 100, by = 1),
  fire_excl_anthro = 0,
  useQuantiles = NULL,
  populationGrowthTable = NULL,
  cPars = getScenarioDefaults(),
  forceUpdate = F,
  interannualVar = eval(formals(caribouPopGrowth)$interannualVar)
)

Arguments

replicates

integer. Number of replicate populations.

N0

initial population size

Anthro, fire_excl_anthro

numeric. A vector of numbers between 0 and 100 representing the percentage of the landscape covered by anthropogenic disturbance buffered by 500 m, and the percentage covered by fire that does not overlap anthropogenic disturbance. The two vectors will be combined with expand.grid() to give the set of scenarios simulated.

useQuantiles

logical or numeric. If it is a numeric vector it must be length 2 and give the low and high limits of the quantiles to use. If useQuantiles != FALSE, each replicate population is assigned to a quantile of the distribution of variation around the expected values, and remains in that quantile as covariates change. If useQuantiles = TRUE, replicate populations will be assigned to quantiles in the default range of 0.025 and 0.975.

populationGrowthTable

data.frame.popGrowthTableJohnsonECCC is included in the package and should be used in most cases. A custom table of model coefficients and standard errors or confidence intervals can be provided but it must match the column names of popGrowthTableJohnsonECCC. If the table does not contain the standard error it is calculated from the confidence interval.

cPars

optional. Parameters for calculating composition survey bias term.

forceUpdate

logical. If the default inputs are used the result is cached. Set forceUpdate to TRUE to ensure the simulations are re-run.

interannualVar

list or logical. List containing interannual variability parameters. These can be either coefficients of variation (R_CV, S_CV), beta precision parameters (R_phi, S_phi), or random effects parameters from a logistic glmm (R_annual, S_annual). Set to FALSE to ignore interannual variability.

Value

a list with two elements:

  • summary: a tibble with a summary of parameter values for each scenario. Column names are Anthro, Mean, lower, upper, Parameter.

  • samples: a tibble with parameter values for each scenario and replicate 4 rows per replicate \* scenario. Column names are Anthro, Parameter and Value

Examples

getSimsNational()
#> Using saved object
#> $summary
#> # A tibble: 505 × 5
#>    Anthro  Mean lower upper Parameter            
#>     <dbl> <dbl> <dbl> <dbl> <chr>                
#>  1      0 0.875 0.686 0.999 Adult female survival
#>  2      1 0.878 0.676 0.998 Adult female survival
#>  3      2 0.873 0.693 0.997 Adult female survival
#>  4      3 0.871 0.675 0.997 Adult female survival
#>  5      4 0.871 0.691 0.997 Adult female survival
#>  6      5 0.876 0.689 0.997 Adult female survival
#>  7      6 0.875 0.701 0.995 Adult female survival
#>  8      7 0.874 0.703 0.998 Adult female survival
#>  9      8 0.869 0.682 0.997 Adult female survival
#> 10      9 0.871 0.679 0.996 Adult female survival
#> # ℹ 495 more rows
#> 
#> $samples
#> # A tibble: 505,000 × 3
#>    Anthro Parameter                 Value
#>     <dbl> <chr>                     <dbl>
#>  1      0 Adult female survival     0.875
#>  2      0 Recruitment               0.398
#>  3      0 Adjusted recruitment      0.211
#>  4      0 Population growth rate    1.04 
#>  5      0 Female population size  946    
#>  6      1 Adult female survival     0.944
#>  7      1 Recruitment               0.269
#>  8      1 Adjusted recruitment      0.143
#>  9      1 Population growth rate    1.10 
#> 10      1 Female population size 1244    
#> # ℹ 504,990 more rows
#>