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Main ZooMSS model function for complete simulations

Source: R/zoomss_model.R
zoomss_model.Rd

This is the main wrapper function that orchestrates a complete ZooMSS model simulation from parameter setup through model execution to output processing.

Usage

zoomss_model(input_params, Groups = NULL, isave = 1)

Arguments

input_params

Data frame containing model parameters and environmental time series. Must include columns: time (time vector in years), sst (sea surface temperature), and chl (chlorophyll). Can optionally include cellID for spatial data. The time step (dt) and maximum time (tmax) are automatically calculated from the time vector. Can be created using createInputParams().

Groups

Data frame defining functional groups with their biological parameters. Must include columns defining species characteristics, size ranges, and feeding parameters. If NULL, uses default ZooMSS functional groups. Can be obtained/customized using getGroups().

isave

Save frequency in time steps (default: 10)

Value

Complete ZooMSS model results object containing:

  • param: Model parameters and environmental forcing data

  • time: Time values corresponding to saved results (accounting for isave)

  • abundance: Abundance time series (time x groups x size classes)

  • growth: Growth rate time series

  • mortality: Mortality rate time series

  • diet: Diet composition time series

  • Additional model structure and kernel data

Details

Run Complete ZooMSS Model Simulation

This function coordinates the entire ZooMSS modeling workflow:

  1. Validates that environmental time series data is provided

  2. Sets up model parameters using the Groups data and input parameters

  3. Initializes the model structure and feeding kernels

  4. Runs the model forward in time with dynamic environmental forcing

  5. Processes outputs by averaging the final 50% of the simulation

  6. Returns organized results including abundances, diets, growth, and mortality

This is the primary entry point for running ZooMSS simulations with environmental forcing.

Examples

if (FALSE) { # \dontrun{
# Basic usage with default groups
env_data <- createEnviroData(10, 0.01)
input_params <- createInputParams(env_data$time, env_data$sst, env_data$chl)
results <- zoomss_model(input_params, isave = 50)

# Using custom groups
Groups <- getGroups()  # Get default groups
Groups$W0[1] <- -12.5          # Modify a parameter
results <- zoomss_model(input_params, Groups, isave = 100)

# Loading groups from file
custom_groups <- getGroups(source = "file", file = "my_groups.csv")
results <- zoomss_model(input_params, custom_groups)
} # }