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Simulate observations

Source: R/simulateObservations.R
simulateObservations.Rd

Parameters specify a monitoring program that is applied to simulate observations from the example trajectories. Parameters for the caribou monitoring program, disturbance scenario and the true population trajectory can be specified with getScenarioDefaults().

Usage

simulateObservations(
  paramTable,
  trajectories = NULL,
  cowCounts = NULL,
  freqStartsByYear = NULL,
  collarNumYears = 4,
  collarOffTime = 4,
  collarOnTime = 4,
  caribouYearStart = 4,
  recSurveyMonth = 3,
  recSurveyDay = 15,
  distScen = NULL,
  writeFilesDir = NULL,
  surv_data = NULL,
  recruit_data = NULL
)

Arguments

paramTable

data.frame. Parameters for the simulations. See getScenarioDefaults() for details.

trajectories

data.frame. Optional example demographic trajectory. If NULL the trajectory will be simulated from the national model.

cowCounts

data.frame. Optional. Number of cows counted in aerial surveys each year. If NULL, and paramTable contains cowMult the number of cows that survive calving based on the collar data is multiplied by cowMult to determine the number of cows counted in aerial surveys. If paramTable does not contain cowMult paramTable$cowCount is used to set the number of cows counted in aerial surveys each year. If a data.frame is provided it must have columns "Year" and "Cows".

freqStartsByYear

data.frame. Optional. Number of collars deployed in each year. If NULL paramTable$collarCount is used as the target number of collars and each year that collars are deployed they will be topped up to this number. If a data.frame is provided it must have 2 columns "Year" and "numStarts" and the "numStarts" is the absolute number of collars deployed in that year.

collarNumYears

integer. Number of years until collar falls off

collarOffTime

integer. Month that collars fall off. A number from 1 (January) to 12 (December)

collarOnTime

integer. Month that collars are deployed. A number from 1 (January) to 12 (December)

caribouYearStart

integer. The first month of the year for caribou.

recSurveyMonth

integer. The month of simulated recruitment surveys.

recSurveyDay

integer. The day for simulated recruitment surveys.

distScen

data.frame. Disturbance scenario. Must have columns "Year", "Anthro", and "fire_excl_anthro" containing the year, percentage of the landscape covered by anthropogenic disturbance buffered by 500 m, and the percentage covered by fire that does not overlap anthropogenic disturbance. See disturbanceMetrics(). If NULL the disturbance scenario is simulated based on paramTable

writeFilesDir

character. If not NULL simSurvObs and simRecruitObs results will be saved to csv files in the directory provided

surv_data

data.frame. Optional existing survival data in bboudata format. Will be combined with simulated data if ... Otherwise ignored.

recruit_data

data.frame. Optional existing recruitment data in bboudata format. Will be combined with simulated data if ... Otherwise ignored.

Value

a list with elements:

  • minYr: first year in the simulations,

  • maxYr: last year in the simulations,

  • simDisturbance: a data frame with columns Anthro, fire_excl_anthro, Total_dist, and Year,

  • simSurvObs: a data frame of survival data in bboutools format,

  • simRecruitObs: a data frame of recruitment data in bboutools format,

  • exData: a tibble of expected population metrics based on the initial model,

  • paramTable: a data frame recording the input parameters for the simulation.

Details

For a detailed description of the process for simulating data see the vignette (vignette("bayesian-model-outputs", package = "caribouMetrics")) and Hughes et al. 2025.

References

Hughes, J., Endicott, S., Calvert, A.M. and Johnson, C.A., 2025. Integration of national demographic-disturbance relationships and local data can improve caribou population viability projections and inform monitoring decisions. Ecological Informatics, 87, p.103095. https://doi.org/10.1016/j.ecoinf.2025.103095

See also

Caribou demography functions: bbouMakeSummaryTable(), caribouBayesianPM(), caribouPopGrowth(), caribouPopSimMCMC(), compositionBiasCorrection(), demographicCoefficients(), demographicProjectionApp(), demographicRates(), doSim(), getBBNationalInformativePriors(), getOutputTables(), getPriors(), getScenarioDefaults(), getSimsInitial(), getSimsNational(), plotRes(), popGrowthTableJohnsonECCC, runScnSet()

Examples

scns <- getScenarioDefaults(projYears = 10, obsYears = 10,
                            collarCount = 20, cowMult = 5)

simO <- simulateObservations(scns)