README.md

In jonathansmart/AquaticLifeHistory: Life History Analysis Tools

AquaticLifeHistory

AquaticLifeHistory allows users to undertake fisheries life history analyses using contemporary approaches as simple R functions. These analyses currently include length-at-age modelling using a multi-model approach, estimating age-at-maturity and length-at-maturity. The main package functions are:

• Estimate_Growth() performs length-at-age analyses using a von Bertalanffy growth model, Gompertz model and/or Logistic model.
• Estimate_Age_Maturity() Estimates age-at-maturity using either binomial maturity or proportion mature data and age.
• Estimate_Len_Maturity() Estimates age-at-maturity using either binomial maturity or proportion mature data and length.

Installation

You can install the latest released version from CRAN with:

install.packages("AquaticLifeHistory")

You can install the development version of AquaticLifeHistory from Github with:

# install.packages("devtools")
devtools::install_github("jonathansmart/AquaticLifeHistory")

Usage

Perform growth analysis

library(AquaticLifeHistory)

# load example data set
data("growth_data")

# Run function with three default model candidates.
# Model parameters, AIC values are returned and a plot with bootstrapped CI's is printed to examine fits.
Estimate_Growth(growth_data)

#> $VonB
#>         Parameter           SE
#> Linf 2439.5652138 50.416331766
#> k       0.1253499  0.006938586
#> L0    659.2971929 14.318722887
#> RSE    97.9461196           NA
#> 
#> $Logistic
#>         Parameter          SE
#> Linf 2163.8640309 26.46867817
#> g       0.2894532  0.01039625
#> L0    727.0885234 13.58771346
#> RSE   110.3850532          NA
#> 
#> $Gompertz
#>        Parameter           SE
#> Linf 2250.136998 32.621706305
#> g       0.207524  0.008455423
#> L0    695.603478 13.779414070
#> RSE   103.855273           NA
#> 
#> $AIC
#>   Model    AICc AIC diff Weight
#> 1    VB 3535.10     0.00      1
#> 2   Log 3605.40    70.30      0
#> 3   Gom 3569.54    34.45      0

Perform age-at-maturity analysis

# load example data set
data("maturity_data")

# Run function to estimate age-at-maturity parameters
Estimate_Age_Maturity(maturity_data)
#>     Estimate        SE
#> A50 13.95113 0.3033328
#> A95 16.53427 0.5321205

# A plot can also be returned with bootstrapped CI's.
Estimate_Age_Maturity(maturity_data, return = "plot")

For further examples of these and other functions use the provided vignettes

browseVignettes("AquaticLifeHistory")

jonathansmart/AquaticLifeHistory documentation built on Feb. 12, 2024, 10:47 a.m.