bcFuns {FSA} | R Documentation |

Creates a function for a specific back-calculation model based on definitions in Vigliola and Meekan (2009).

bcFuns(BCM, verbose = FALSE)

`BCM` |
A single numeric between 1 and 22 or a string that indicates which back-calculation model to use (based on numbers and names in Vigliola and Meekan (2009)). |

`verbose` |
A logical that indicates whether a message about the model and parameter definitions should be output. |

The following back-calculation models, based on definitions with abbreviations and model numbers from Vigliola and Meekan (2009), are supported.

Abbreviation | Number | Model |

DALE | 1 | Dahl-Lea |

FRALE | 2 | Fraser-Lee |

BI, LBI | 3 | (Linear) Biological Intercept |

BPH, LBPH | 4 | (Linear) Body Proportional Hypothesis |

TVG | 5 | Time-Varying Growth |

SPH, LSPH | 6 | (Linear) Scale Proportional Hypothesis |

AE, AESPH | 7 | (Age Effect) Scale Proportional Hypothesis |

AEBPH | 8 | (Age Effect) Body Proportional Hypothesis |

MONA | 9 | Monastyrsky |

MONA-BPH | 10 | Monastyrsky Body Proportional Hypothesis |

MONA-SPH | 11 | Monastyrsky Scale Proportional Hypothesis |

WAKU | 12 | Watanabe and Kuroki |

FRY | 13 | Fry |

MF, ABI | 14 | Modified Fry, Allometric Biological Intercept |

FRY-BPH, ABPH | 15 | Fry, Allometric Body Proportional Hypothesis |

FRY-SPH, ASPH | 16 | Fry, Allometric Scale Proportional Hypothesis |

QBPH | 17 | Quadratic Body Proportional Hypothesis |

QSPH | 18 | Quadratic Scale Proportional Hypothesis |

PBPH | 19 | Polynomial Body Proportional Hypothesis |

PSPH | 20 | Polynomial Scale Proportional Hypothesis |

EBPH | 21 | Exponential Body Proportional Hypothesis |

ESPH | 22 | Exponential Scale Proportional Hypothesis |

A function that can be used to predict length at previous age (Li) given length-at-capture (Lc), hard-part radius-at-age i (Ri), and hard-part radius-at-capture (Rc). In addition, some functions/models may require the previous age (agei) and the age-at-capture (agec), certain parameters related to the biological intercept (R0p & L0p), or certain parameters estimated from various regression models (a,b,c,A,B,C). See source for more information.

http://derekogle.com/IFAR/supplements/backcalculation/

Derek H. Ogle, derek@derekogle.com

Vigliola, L. and M.G. Meekan. 2009. The back-calculation of fish growth from otoliths. pp. 174-211. in B.S. Green et al. (editors). Tropical Fish Otoliths: Information for Assessment, Management and Ecology. Review: Methods and Technologies in Fish Biology and Fisheries 11. Springer. [Was (is?) available from https://www.researchgate.net/publication/226394736_The_Back-Calculation_of_Fish_Growth_From_Otoliths.]

## Simple Examples ( bcm1 <- bcFuns(1) ) bcm1(20,10,40) ## Example with dummy length-at-cap, radii-at-cap, and radii-at-age lencap <- c(100,100,100,150,150) radcap <- c(20,20,20,30,30) rad <- c( 5,10,15,15,25) bcm1(lencap,rad,radcap) ( bcm2 <- bcFuns("FRALE") ) bcm2(lencap,rad,radcap,2) # demonstrated with a=2

[Package *FSA* version 0.8.18 Index]