Exploratory Fishing Step (No Population Effect)

Applies a given matrix of effort by patch and fleet to determine the potential returns from fishing without modifying the underlying population. This is an exploratory step used internally by simmar to build the "buffet" that allocate_effort uses for spatial effort reallocation.

Usage

go_fish(
  e_p_fl,
  fauna,
  n_p_a,
  fleets,
  groupers = c("fleet", "patch"),
  output_format = c("tidy", "matrix")
)

Arguments

e_p_fl

Numeric matrix of effort by patch (rows) and fleet (columns), with column names matching fleet names. Typically the current step's effort matrix from simmar.

fauna

Named list of fauna objects from create_critter.

n_p_a

Named list (one element per species in fauna) of numbers-at-age matrices [patch, age], representing the current population state to fish against. Typically extracted from sim[[step]][[critter]]$n_p_a.

fleets

Named list of fleet objects from create_fleet.

groupers

Character vector. Grouping columns for tidy output format (default: c("fleet", "patch")). Ignored when output_format = "matrix".

output_format

Character. Output format:

"tidy": (default) Returns a list of tidy data frames with species summed across and effort joined.
"matrix": Returns a list of patches x fleets matrices (species summed). Designed for direct use with allocate_effort. Substantially faster.

Value

A named list with six elements, each summed across species:

c_p_fl: Catch by patch and fleet
r_p_fl: Revenue by patch and fleet
prof_p_fl: Profit by patch and fleet
cpue_p_fl: Catch per unit effort (NA where effort = 0)
rpue_p_fl: Revenue per unit effort (NA where effort = 0)
ppue_p_fl: Profit per unit effort (NA where effort = 0)

Format of each element depends on output_format.

Details

go_fish runs a single, movement-free time step (move_fish = 0) for each critter in fauna using the supplied population state n_p_a, then aggregates catch, revenue, and profit across species via aggregate_yields.

The function is also useful for "what-if" analyses: you can probe the revenue surface under different effort distributions before committing to a simulation run.

Examples

if (FALSE) { # \dontrun{
# Probe the revenue surface under current effort
n_p_a_now <- lapply(fauna, function(cr) cr$n_p_a_0)
buffet <- go_fish(e_p_fl, fauna, n_p_a_now, fleets, output_format = "matrix")

# Use with allocate_effort to redistribute effort spatially
result <- allocate_effort(
  effort_by_patch = e_p_fl,
  buffet          = buffet,
  fleets          = fleets,
  open_patch      = open_patches
)
} # }