Skip to contents

Compute trophic levels for functional groups using diet composition

Source: R/utils.R
extractTrophicLevels.Rd

Calculates trophic levels for each functional group based on their diet composition using an iterative Gauss-Seidel algorithm.

Usage

extractTrophicLevels(mdl)

Arguments

mdl

ZooMSS model results object containing 3D diet data (mdl$diet). Dimensions are time, groups, prey_items where columns 1:3 are always phytoplankton size classes and remaining columns are zooplankton/fish groups.

Value

Matrix where rows are time steps and columns are functional groups

Details

Calculate Trophic Levels from Diet Matrix

This function computes trophic levels by:

  • Starting with phytoplankton at trophic level 1.0

  • Initializing all other groups at trophic level 2.0

  • Iteratively updating trophic levels based on weighted diet composition

  • Continuing until convergence (difference < 0.01) or maximum iterations (100)

  • Processing 3D diet arrays with time series data

Trophic level calculation follows: TL = 1 + sum(diet_fraction_i * TL_prey_i)

The function calculates trophic levels for each time step separately and dynamically determines the number of groups from the diet matrix dimensions.

This provides a quantitative measure of each group's position in the food web and is useful for analyzing ecosystem structure and energy transfer efficiency.

Examples

if (FALSE) { # \dontrun{
# After running ZooMSS model with 3D time series
results <- zoomss_model(input_params, Groups)
trophic_levels <- extractTrophicLevels(results)  # Returns matrix (time x groups)

# View trophic levels by group for final time step
final_tl <- trophic_levels[nrow(trophic_levels), ]
names(final_tl) <- results$param$Groups$Species
print(final_tl)
} # }