MIR                package:unknown                R Documentation



Description:

  Marginal increment analysis (MIA) provides a useful, semi-direct method 
  of validating the periodicity of band formation. The marginal increment 
  ratio (MIR) has been the most widely technique used for this analysis 
  and provides a mean of the increment between months of capture to determine 
  the season of band formation. 

Usage:

     MIR(x)

Arguments:

 x: A data frame containing for each individual the following columns.
    
    ID: numeric variable. Is the key identification of individual.
   
    Sex: factor variable. Is the sex of individual (M or F).

    Month: factor variable. Is the month of capture of individual. 

    Age: numeric variable. Is the age of each individual.
 
    R: numeric variable. Is the radius of the structure. 

    Rn: numeric variable. Is the radius of the ultimate band or band pair.
    
    Rn1: numeric variable. Is the radius of the next to last complete band pair.


Details:

     Measurements of the numeric variables (R, Rn and Rn1) must be in mm.

Value:

     Returns a data.frame with the mean MIR calculated for each individual.

     Returns the mean MIR per month, season, and Month vs Sex for all ages combined.

     Returns a plot of means MIR by month.

     
Warning:

  If the sample presents NA's the argument error.bars of the function
  plotMeans, will display the following message if requested ("sd" or "conf.int")
  Warning in arrows(1:n.levs, means - sds, 1:n.levs, means + sds, angle = 90,:
  zero-length arrow is of indeterminate angle and so skipped


Note:

     require(Rcmdr)
  
     http://finzi.psych.upenn.edu/R/library/Rcmdr/html/plotMeans.html

Author(s):

Fabio Prior Caltabellotta, M.Sc.
Doutorando em Zoologia - Campus Botucatu
Universidade Estadual Paulista "Júlio de Mesquita Filho" - UNESP
Laboratório de Pesquisa em Elasmobrânquios
fabioblueshark@gmail.com
fabiopc@ibb.unesp.br 


References:

Cailliet G.M, Smith W.D, Mollet H.F, Goldman K.J (2006) Age and growth studies of chondrichthyan fishes: the need 
   for consistency in terminology, verification, validation,and growth function fitting. Environ Biol Fish 77:211-228.

Lessa R, Santana FM, Hazin FH (2004) Age and growth of the blue shark Prionace glauca (Linnaeus, 1758) off
   northeastern Brazil. Fish Res 66:19–30.

Natanson LJ, Casey JG, Kohler NE (1995) Age and growth estimates for the dusky shark, Carcharhinus
   obscurus, in the western North Atlantic Ocean. Fish Bull 93:116–126.

See Also:

     help(plotMeans)

Examples:

ID <- c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25)
Age <- c(2, 3, 2, 3, 2, 3, 3, 3, 2, 2, 2, 2, 2, 3, 2, 2, 3, 3, 2, 2, 2, 3, 2, 4, 3)
Sex <- c("F", "F", "M", "M", "F", "F", "M", "F", "F", "F", "M", "M", "M", "F", "F", "F", "F", "F", "M", "F", "F", "F", "M", "F", "F")
Month <- c("January","January","February","February","March","March","March","April","April","May","May","June","June","July","July","August","August","August","September","October","November","November","December","December","December")
Season <- c("Summer","Summer","Summer","Summer","Autumn","Autumn","Autumn","Autumn","Autumn","Autumn","Autumn","Winter","Winter","Winter","Winter","Spring","Spring","Spring","Spring","Spring","Spring","Spring","Summer","Summer","Summer") 
R <- c(2.95, 3.26, 2.30, 3.09, 3.06, 2.22, 2.95, 3.19, 2.03, 2.31, 2.89, 3.64, 2.15, 2.54, 2.75, 2.14, 2.51, 2.48, 2.73, 2.18, 3.06, 2.87, 2.29, 3.74, 3.01)
Rn <- c(2.59, 2.99, 2.16, 3.02, 2.84, 2.15, 2.76, 3.10, 1.76, 2.12, 2.78, 3.49, 1.84, 2.26, 2.43, 1.94, 2.25, 2.44, 2.49, 2.08, 2.94, 2.47, 2.18, 3.56, 2.91)
Rn1 <- c(2.10, 2.84, 1.79, 2.66, 2.68, 2.03, 2.63, 2.91, 1.40, 1.80, 2.32, 3.28, 1.41, 2.07, 2.16, 1.68, 1.90, 2.33, 2.22, 1.98, 2.67, 2.27, 1.93, 3.40, 2.82)
dados <- data.frame(cbind(ID,Age,R,Rn,Rn1,Sex,Month,Season))

MIR(dados)