ypr

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 interval annual natural mortality rate (n)
• The lifetime 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.

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_tabulate_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            0.200      3.13e-56
#> 2     2   25.9  174.      174.  2.91e-29            0.200      2.91e-29
#> 3     3   36.2  476.      476.  1.04e-14            0.200      1.04e-14
#> 4     4   45.1  918.      918.  3.46e- 5            0.200      3.46e- 5
#> 5     5   52.8 1469.     1469.  9.95e- 1            0.200      9.95e- 1
#> 6     6   59.3 2090.     2090.  1.00e+ 0            0.200      1.00e+ 0
#> # … with 4 more variables: Retention <dbl>, FishingMortality <dbl>,
#> #   Survivorship <dbl>, FishedSurvivorship <dbl>

Fish

ypr_plot_fish(population, color = "white")

head(ypr_tabulate_fish(population))
#> # A tibble: 6 x 7
#>     Age Survivors Spawners   Caught Harvested Released HandlingMortalities
#>   <dbl>     <dbl>    <dbl>    <dbl>     <dbl>    <dbl>               <dbl>
#> 1     1      70.1 2.19e-54 4.39e-55  1.76e-55 2.63e-55                   0
#> 2     2      56.1 1.63e-27 3.26e-28  1.30e-28 1.96e-28                   0
#> 3     3      44.9 4.68e-13 9.36e-14  3.74e-14 5.62e-14                   0
#> 4     4      35.9 1.24e- 3 2.48e- 4  9.93e- 5 1.49e- 4                   0
#> 5     5      28.7 2.86e+ 1 5.72e+ 0  2.29e+ 0 3.43e+ 0                   0
#> 6     6      21.1 2.11e+ 1 4.23e+ 0  1.69e+ 0 2.54e+ 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     286350.     80      159.      3600.
#> 2 actual   0.2   0.08  167831.     70.1    108.      3112.
#> 3 optimal  0.458 0.183  84129.     54.0     63.7     2641.

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   8.63  7.67   65.8  3112.   2.12
#> 2 optimal 0.458 0.183 11.7   6.87   62.6  2641.   5.82
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 release from CRAN

install.packages("ypr")

To install the developmental version from GitHub

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

To install the latest developmental release from the Poisson drat repository

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

Information

For more information see the Get Started vignette.

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 partially supported by the Habitat Conservation Trust Foundation and the Ministry 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 contributing, you agree to abide by its terms.

References

Walters, Carl J., and Steven J. D. Martell. 2004. Fisheries Ecology and Management. Princeton, N.J: Princeton University Press.