Estimate release rate (RPUE: Released fish Per Unit Effort) from a creel survey design

Computes release rate estimates with standard errors and confidence intervals from a creel survey design with attached interview and catch data. Uses ratio-of-means estimation via survey::svyratio(). RPUE measures the rate of released fish per unit effort, analogous to HPUE for harvested fish.

Usage

estimate_release_rate(
  design,
  by = NULL,
  variance = "taylor",
  conf_level = 0.95,
  missing_sections = "warn"
)

Arguments

design

A creel_design object with interviews (via add_interviews) and catch data (via add_catch) attached. The catch data must include records with catch_type = "released".

by

Optional tidy selector for grouping variables. Accepts bare column names (e.g., by = day_type, by = species), multiple columns, or tidyselect helpers. When species grouping is used, per-species release rates are estimated.

variance

Character string specifying variance estimation method. Options: "taylor" (default), "bootstrap", or "jackknife".

conf_level

Numeric confidence level (default: 0.95).

missing_sections

Character string controlling behavior when a registered section has no interview observations. "warn" (default) emits a cli_warn() and inserts an NA row with data_available = FALSE. "error" aborts with cli_abort(). Ignored for non-sectioned designs.

Value

A creel_estimates S3 object with method = "ratio-of-means-rpue". Estimates tibble has columns: estimate, se, ci_lower, ci_upper, n (plus any grouping columns).

Details

RPUE is estimated as the ratio of total released fish to total effort (ratio-of-means). Release data comes from add_catch() records with catch_type = "released". Interviews with no releases contribute 0 to the numerator (zero-fill), ensuring the effort denominator is correct.

Note

When called on a sectioned design, no .lake_total row is produced. Release rates (fish per angler-hour) are not additive across sections. Lake-wide release rate requires a separate unsectioned call.

See also

estimate_harvest_rate for harvest rate, add_catch

Other "Estimation": est_length_distribution(), estimate_catch_rate(), estimate_effort(), estimate_effort_aerial_glmm(), estimate_harvest_rate(), estimate_total_catch(), estimate_total_harvest(), estimate_total_release()

Examples

library(tidycreel)
data(example_calendar)
data(example_counts)
data(example_interviews)
data(example_catch)

design <- creel_design(example_calendar, date = date, strata = day_type)
design <- add_counts(design, example_counts)
#> Warning: No weights or probabilities supplied, assuming equal probability
design <- add_interviews(design, example_interviews,
  catch = catch_total, effort = hours_fished,
  trip_status = trip_status, trip_duration = trip_duration
)
#> ℹ No `n_anglers` provided — assuming 1 angler per interview.
#> ℹ Pass `n_anglers = <column>` to use actual party sizes for angler-hour
#>   normalization.
#> ℹ Added 22 interviews: 17 complete (77%), 5 incomplete (23%)
design <- add_catch(design, example_catch,
  catch_uid = interview_id,
  interview_uid = interview_id,
  species = species,
  count = count,
  catch_type = catch_type
)

# Overall release rate (all species combined)
rpue <- estimate_release_rate(design)
#> Warning: Small sample size for CPUE estimation.
#> ! Sample size is 22. Ratio estimates are more stable with n >= 30.
#> ℹ Variance estimates may be unstable with n < 30.
print(rpue)
#> 
#> ── Creel Survey Estimates ──────────────────────────────────────────────────────
#> Method: ratio-of-means-rpue
#> Variance: Taylor linearization
#> Confidence level: 95%
#> 
#> # A tibble: 1 × 5
#>   estimate     se ci_lower ci_upper     n
#>      <dbl>  <dbl>    <dbl>    <dbl> <int>
#> 1    0.602 0.0956    0.414    0.789    22

# Per-species release rates
rpue_by_species <- estimate_release_rate(design, by = species)
#> Warning: Small sample size for CPUE estimation.
#> ! Sample size is 22. Ratio estimates are more stable with n >= 30.
#> ℹ Variance estimates may be unstable with n < 30.
#> Warning: Small sample size for CPUE estimation.
#> ! Sample size is 22. Ratio estimates are more stable with n >= 30.
#> ℹ Variance estimates may be unstable with n < 30.
#> Warning: Small sample size for CPUE estimation.
#> ! Sample size is 22. Ratio estimates are more stable with n >= 30.
#> ℹ Variance estimates may be unstable with n < 30.
print(rpue_by_species)
#> 
#> ── Creel Survey Estimates ──────────────────────────────────────────────────────
#> Method: ratio-of-means-rpue
#> Variance: Taylor linearization
#> Confidence level: 95%
#> Grouped by: species
#> 
#> # A tibble: 3 × 6
#>   species estimate     se ci_lower ci_upper     n
#>   <chr>      <dbl>  <dbl>    <dbl>    <dbl> <int>
#> 1 bass      0.212  0.0762   0.0631    0.362    22
#> 2 panfish   0.0885 0.0564  -0.0221    0.199    22
#> 3 walleye   0.301  0.0745   0.155     0.447    22