Plot catch curve — plot_catchcurve • ggFishPlots

Plot a catch curve to estimate instantaneous total mortality (Z) using age data

Usage

plot_catchcurve(
  dt,
  age = "age",
  sex = "sex",
  time = NULL,
  age.range = NULL,
  female.sex = "F",
  male.sex = "M",
  split.by.sex = FALSE,
  base_size = 8,
  legend.position = "bottom"
)

Arguments

dt: A data.frame, tibble or data.table
age: Character argument giving the name of the age column in dt
sex: Character argument giving the name of the sex column in dt. Ignored if split.by.sex == FALSE.
time: Split analysis by time? If NULL, all data are assumed to stem from one time point. Using a character argument giving the name of a time column splits the analysis by unique values in that column and produces a faceted plot.
age.range: Defines the age range to be used for Z estimation. If NULL, all ages are used. If a numeric vector of length 2, the first number defines the minimum age to include and the last number the maximum age. It is also possible to use differing ranges by sex when split.by.sex = TRUE: use a named list of length two with names referring to female.sex and male.sex. Provide a numeric vector of length 2 to each element (first number defining the minimum age to include and the last number the maximum age). See Examples.
female.sex: A character denoting female sex in the sex column of dt
male.sex: A character denoting male sex in the sex column of dt
split.by.sex: Logical indicating whether the result should be split by sex.
base_size: Base size parameter for ggplot. See ggtheme.
legend.position: Position of the ggplot legend as a character. See ggtheme.

Details

Calculates and plots the basic log-linearized catch curve to estimate instantaneous mortality. See e.g. Ogle (2013).

Author

Mikko Vihtakari // Institute of Marine Research.

Examples

# Catch curve including all ages
data(survey_ghl)
plot_catchcurve(survey_ghl)
#> $plot

#> 
#> $text
#> [1] "Instantenous total mortality (Z) estimated using a catch curve and\nage range .\n\nZ = 0.19 (0.123-0.257 95% CIs)\nN at age 0 = 1448 (449-4674 95% CIs)\nLongevity = 38.3 years (23.8 - 68.8 95% CIs)\n\n"
#> 
#> $params
#> # A tibble: 2 × 8
#>   sex   term        estimate std.error statistic  p.value conf.low conf.high
#>   <chr> <chr>          <dbl>     <dbl>     <dbl>    <dbl>    <dbl>     <dbl>
#> 1 both  (Intercept)    7.28     0.573      12.7  2.25e-13    6.11      8.45 
#> 2 both  age           -0.190    0.0328     -5.79 2.85e- 6   -0.257    -0.123
#> 
# \donttest{
# Specific ages
plot_catchcurve(survey_ghl, age.range = c(10,26))
#> $plot

#> 
#> $text
#> [1] "Instantenous total mortality (Z) estimated using a catch curve and\nage range 10-26.\n\nZ = 0.356 (0.312-0.401 95% CIs)\nN at age 0 = 68394 (29985-156005 95% CIs)\nLongevity = 31.2 years (25.7 - 38.3 95% CIs)\n\n"
#> 
#> $params
#> # A tibble: 2 × 8
#>   sex   term        estimate std.error statistic  p.value conf.low conf.high
#>   <chr> <chr>          <dbl>     <dbl>     <dbl>    <dbl>    <dbl>     <dbl>
#> 1 both  (Intercept)   11.1      0.387       28.8 1.54e-14   10.3      12.0  
#> 2 both  age           -0.356    0.0207     -17.2 2.81e-11   -0.401    -0.312
#> 
# Split by sex
plot_catchcurve(survey_ghl, age.range = c(10,26), split.by.sex = TRUE)
#> $plot

#> 
#> $text
#> [1] "Instantenous total mortality (Z) estimated using a catch curve and\nage range 10-26 for both sexes.\n\nFemales:\nZ = 0.31 (0.256-0.365 95% CIs)\nN at age 0 = 23925 (8625-66368 95% CIs)\nLongevity = 32.5 years (24.8 - 43.4 95% CIs)\n\nMales:\nZ = 0.511 (0.492-0.53 95% CIs)\nN at age 0 = 145002 (105241-199785 95% CIs)\nLongevity = 23.3 years (21.8 - 24.8 95% CIs)"
#> 
#> $params
#> # A tibble: 4 × 8
#>   sex   term        estimate std.error statistic  p.value conf.low conf.high
#>   <chr> <chr>          <dbl>     <dbl>     <dbl>    <dbl>    <dbl>     <dbl>
#> 1 F     (Intercept)   10.1     0.479        21.1 1.49e-12    9.06     11.1  
#> 2 F     age           -0.310   0.0257      -12.1 3.87e- 9   -0.365    -0.256
#> 3 M     (Intercept)   11.9     0.147        80.8 8.62e-18   11.6      12.2  
#> 4 M     age           -0.511   0.00866     -59.0 3.72e-16   -0.530    -0.492
#> 
# Split by sex, separate age.range
plot_catchcurve(survey_ghl,
age.range = list("F" = c(13,26), "M" = c(10,26)),
split.by.sex = TRUE)
#> $plot

#> 
#> $text
#> [1] "Instantenous total mortality (Z) estimated using a catch curve and\nage range  for females and  for males.\n\nFemales:\nZ = 0.37 (0.31-0.431 95% CIs)\nN at age 0 = 86119 (25990-285354 95% CIs)\nLongevity = 30.7 years (23.6 - 40.5 95% CIs)\n\nMales:\nZ = 0.511 (0.492-0.53 95% CIs)\nN at age 0 = 145002 (105241-199785 95% CIs)\nLongevity = 23.3 years (21.8 - 24.8 95% CIs)"
#> 
#> $params
#> # A tibble: 4 × 8
#>   sex   term        estimate std.error statistic  p.value conf.low conf.high
#>   <chr> <chr>          <dbl>     <dbl>     <dbl>    <dbl>    <dbl>     <dbl>
#> 1 F     (Intercept)   11.4     0.550        20.7 9.51e-11   10.2      12.6  
#> 2 F     age           -0.370   0.0276      -13.4 1.38e- 8   -0.431    -0.310
#> 3 M     (Intercept)   11.9     0.147        80.8 8.62e-18   11.6      12.2  
#> 4 M     age           -0.511   0.00866     -59.0 3.72e-16   -0.530    -0.492
#> 
# }