Yield Per Recruit

An implementation of equilibrium-based yield per recruit methods. Yield per recruit methods can used to estimate the optimal yield for a fish population as described by Walters and Martell (2004) . The yield can be based on the number of fish caught (or harvested) or biomass caught for all fish or just large (trophy) individuals.

Introduction

ypr is an R package that implements equilibrium-based yield per recruit methods. Yield per recruit methods can used to estimate the optimal yield for a fish population (Walters and Martell 2004). The yield can be based on the number of fish caught (or harvested) or biomass for all fish or just large (trophy) individuals.

The key life history parameters are

• The growth coefficient (k) and mean maximum length (Linf) from the Von Bertalanffy growth curve
• The length at which 50% mature (Ls)
• The length at which 50% vulnerable to harvest (Lv)
• The instantaneous annual natural mortality rate (M)
• The number of spawners per spawner at low density (Rk)

The calculations do not account for stochasticity, predator-prey dynamics, angler responses or density-dependent growth.

Information

For definitions of all 28 population parameters see ?ypr_population.

For an explanation of the calculations see the ypr vignette.

Demonstration

Schedule

library(ypr)
population <- ypr_population(Rk = 5, Ls = 50, Rmax = 100, rho = 0.6)
ypr_plot_schedule(population, x = "Length", y = "Spawning")

head(ypr_schedule(population))
#> # A tibble: 6 x 11
#>     Age Length Weight Fecundity  Spawning NaturalMortality Vulnerability
#>   <int>  <dbl>  <dbl>     <dbl>     <dbl>            <dbl>         <dbl>
#> 1     1   13.9   27.0      27.0  3.13e-56            0.181      3.13e-56
#> 2     2   25.9  174.      174.   2.91e-29            0.181      2.91e-29
#> 3     3   36.2  476.      476.   1.04e-14            0.181      1.04e-14
#> 4     4   45.1  918.      918.   3.46e- 5            0.181      3.46e- 5
#> 5     5   52.8 1469.     1469.   9.95e- 1            0.181      9.95e- 1
#> 6     6   59.3 2090.     2090.  10.00e- 1            0.181     10.00e- 1
#> # ... with 4 more variables: Retention <dbl>, FishingMortality <dbl>,
#> #   Survivorship <dbl>, FishedSurvivorship <dbl>

Fish

library(ypr)
ypr_plot_fish(population, color = "white")

head(ypr_tabulate_fish(population))
#> # A tibble: 6 x 7
#>     Age Surviving Spawning   Caught Harvested Released HandlingMortality
#>   <dbl>     <dbl>    <dbl>    <dbl>     <dbl>    <dbl>             <dbl>
#> 1     1      69.3 2.17e-54 4.34e-55  1.73e-55 2.60e-55                 0
#> 2     2      56.7 1.65e-27 3.30e-28  1.32e-28 1.98e-28                 0
#> 3     3      46.4 4.84e-13 9.69e-14  3.87e-14 5.81e-14                 0
#> 4     4      38.0 1.31e- 3 2.63e- 4  1.05e- 4 1.58e- 4                 0
#> 5     5      31.1 3.10e+ 1 6.19e+ 0  2.48e+ 0 3.72e+ 0                 0
#> 6     6      23.4 2.34e+ 1 4.69e+ 0  1.88e+ 0 2.81e+ 0                 0

Stock-Recruitment

ypr_plot_sr(population)

ypr_tabulate_sr(population)
#> # A tibble: 3 x 7
#>   Type        pi     u    Eggs Recruits Spawners Fecundity
#>   <chr>    <dbl> <dbl>   <dbl>    <dbl>    <dbl>     <dbl>
#> 1 unfished 0     0     357733.     80.0    190.      3764.
#> 2 actual   0.2   0.08  201443.     69.3    125.      3232.
#> 3 optimal  0.418 0.167 106584.     54.4     76.5     2785.

Yield

ypr_tabulate_yield(population)
#> # A tibble: 2 x 8
#>   Type       pi     u Yield   Age Length Weight Effort
#>   <chr>   <dbl> <dbl> <dbl> <dbl>  <dbl>  <dbl>  <dbl>
#> 1 actual  0.2   0.08   9.97  7.88   66.5  3232.   2.12
#> 2 optimal 0.418 0.167 12.8   7.11   63.6  2785.   5.14
ypr_plot_yield(population)

Uncertainty

library(ggplot2)
populations <- ypr_populations(Rk = c(3,7), Ls = c(40, 60), Rmax = 100)
ypr_plot_yield(populations, plot_values = FALSE) +
  facet_grid(Rk~Ls)

Installation

To install the latest development version from GitHub

# install.packages("devtools")
devtools::install_github("poissonconsulting/ypr")

To install the latest development version from the Poisson drat repository

# install.packages("drat")
drat::addRepo("poissonconsulting")
install.packages("ypr")

Interaction

To interactively explore the effects of altering individual parameters on the schedule, stock-recruitment and yield see the ypr shiny app.

Creditation

Development of ypr was supported by the Habitat Conservation Trust Foundation and the Ministy of Forests, Lands and Natural Resource Operations.

The hex was designed by The Forest.

Contribution

Please report any issues.

Pull requests are always welcome.

Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.

References