fb4package (version 2.0.0)

analyze_energy_budget: Analyze energy budget from FB4 results

Description

Analyzes energy budget components from FB4 simulation results. Calculates proportional allocation to different processes with uncertainty propagation when available.

Usage

analyze_energy_budget(result, individual_id = NULL, confidence_level = 0.95)

Value

A named list with four elements:

energy_components

The list returned by get_energy_budget_uncertainty, containing six component sub-lists each with estimate, se, ci_lower, and ci_upper.

proportions

Named list of proportional allocations (prop_respiration, prop_egestion, prop_excretion, prop_sda, prop_net), each a sub-list with estimate, se, ci_lower, and ci_upper. NULL when consumption energy is zero or unavailable.

summary_metrics

Named list with gross_growth_efficiency, metabolic_scope, and assimilation_efficiency sub-lists (each estimate + se). NULL when proportions are unavailable.

balance_check

Named list with consumption_energy, total_allocated, balance_error, and relative_error (all numeric) to verify mass-balance closure.

Plus the context scalars method, has_uncertainty, and

individual_id.

Arguments

result

FB4 result object

individual_id

Individual ID for hierarchical models (NULL for population/single individual)

confidence_level

Confidence level for intervals (default 0.95)

Examples

# \donttest{
data(fish4_parameters)
sp   <- fish4_parameters[["Oncorhynchus tshawytscha"]]$life_stages$adult
info <- fish4_parameters[["Oncorhynchus tshawytscha"]]$species_info
bio  <- Bioenergetic(
  species_params     = sp,
  species_info       = info,
  environmental_data = list(
    temperature = data.frame(Day = 1:30, Temperature = rep(12, 30))
  ),
  diet_data = list(
    proportions = data.frame(Day = 1:30, Prey1 = 1.0),
    energies    = data.frame(Day = 1:30, Prey1 = 5000),
    prey_names  = "Prey1"
  ),
  simulation_settings = list(initial_weight = 100, duration = 30)
)
bio$species_params$predator$ED_ini <- 5000
bio$species_params$predator$ED_end <- 5500
result <- run_fb4(bio, strategy = "direct", p_value = 0.5, verbose = FALSE)
budget <- analyze_energy_budget(result)
# }