Doutoranda em Oceanografia IO-USP. Trabalho com pesca de peixes recifais no Banco dos Abrolhos, BA.

tarefa_1.r mariliatarefa_1.r exercicio_4.r exercicio_5.r exercicio_7_2.r exerc_8_2.r

trabalho_final_-_proposta.txt

Optei por unir as duas propostas e elaborar as funções VLOT e FRO. A função VLOT é utilizada dentro da função FRO, de modo que ambas são complementares. Foram elaboradas duas funções, com uma página de ajuda para cada.

Função 01

VLOT                    package:unknown                 R Documentation


Value of the optimum length 


Description:

     Calculates the optimal length of a fish specie. It is used in the "FRO" function 
to provide the optimum size of a fish in the fishing catches and to provide the megaspawners 
size of a particular specie. 


Usage:

      VLOT (x) 


Arguments:

    x    Data frame with five columns (age, mean weight, mean length, number of
         individuals, number of individuals* mean weight). The values are numeric and the
         colnames should be: "age", "meanwei","meanlen", "numbind", "mul". 


Details:

        Identifies the length at which the number of fish in a given age class multiplied by 
        the average individual weight is maximum 

Value:

        Return the optimum length 


Author(s):

        Marília Previero 


References:

        FROESE, R. Keep it simple: three indicators to deal with overfishing. 
        Fish and Fisheries, Oxford, v. 5, n.1, p. 86–91, 2004. 


See Also:

        [[FRO|link text]]


Examples:

age=seq(from=1, to=20)
meanwei=c(0.05, 0.1,  0.3,0.7,	0.1,2.26,2.38,3.2,3.6,4.2,4.9,5.4,5.5,6.2,6.5,6.9,7.3,7.9,8.3,8.9)
meanlen=seq(from=10, to=86, by=4)
numbind=c(2, 4, 14, 22, 24, 66, 88, 122, 133, 131, 144, 99, 98, 76, 55, 33, 18,11, 7, 3)
mul=c(0.10, 0.40 ,4.20,15.40,2.40, 149.16, 209.44 ,390.40, 478.80, 550.20, 705.60, 534.60,539.00 ,471.20 ,357.50 ,227.70, 131.40 , 86.90 , 58.10 , 26.7)

data=data.frame(cbind(age, meanwei, meanlen, numbind, mul))
data
VLOT(data)
     

VLOT<- function(x)# x é um data frame com cinco colunas: age, meanwei,meanlen, numbind, mul  
{
  ma=max(x$mul)# encontra o valor máximo da coluna "mul"
  Len=x[x$mul==ma,1]# encontra o valor de "meanlen" correspondente ao valor de "ma"
  return (Len)# retorna o valor de Len, que é o VLOT
}

Script: script_vlot.txt

Função 02

FRO                        package:unknown                     R Documentation


Fishery indicators of Froese (2004) 


Description:

       To a certain fish specie, calculates the percentage of mature individuals, 
       the percentage of optimum size individuals and the percentage of mega spawners in 
       fisheries catches.
 
Usage:

       FRO(x,i,L50) 


Arguments:

  x    Data frame with one column containing the lengths of the individuals. 
       The colname should be "len"
  i    Data frame with five columns (age, weight, average length, the number 
       of individuals, number of subjects * Average weight). The colnames should
       be: "age", "meanwei","meanlen", "numbind", "mul". 
  L50  Numeric. Average size of first maturation, available in the literature 
       for the studied specie. 


Details:

       Records the percentage of individuals in the sample that are larger than the 
       L50, the percentage of individuals whose lengths are in the range of 10% below
       to 10% above that the value of the optimal size. Records the percentage of 
       individuals in the sample that have size 10% or more than the value of the optimal
       size.

Value:

   
  mat : Percentage of individuals in the sample that are larger than its L50

  lot : Percentage of individuals in the sample with optimum size
  
  mgr : Percentage of megaspawners  individuals in the sample

    
Author(s):

    Marília Previero
 

References:

     FROESE, R. Keep it simple: three indicators to deal with overfishing. 
Fish and Fisheries, Oxford, v. 5, n.1, p. 86–91, 2004. 


See Also:

      [[VLOT]] 


Examples:

age=seq(from=1, to=20)
meanwei=c(0.05 , 0.1,  0.3,0.7,	0.1,2.26,2.38,3.2,3.6,4.2,4.9,5.4,5.5,6.2,6.5,6.9,7.3,7.9,8.3,8.9)
meanlen=seq(from=10, to=86, by=4)
numbind=c(2, 4, 14, 22, 24, 66, 88, 122, 133, 131, 144, 99, 98, 76, 55, 33, 18,11, 7, 3)
mul=c(0.10, 0.40 , 4.20,  15.40, 2.40, 149.16, 209.44 ,390.40, 478.80, 550.20, 705.60, 534.60,539.00 ,471.20 ,357.50 ,227.70, 131.40 , 86.90 , 58.10 , 26.7)

opt=data.frame(cbind(age, meanwei, meanlen, numbind, mul))
VLOT(opt)

len=rnorm(100,mean=18, sd=15)
le=data.frame(len)
FRO(le,opt,9) 
     

FRO<-function(x,t,L50)
{
  mat=100*(sum(x>L50))/length(x$len) #contabiliza a porcentagem de indivíduos na amostra que são maiores que o L50
  lot=100*(sum(sum(x<VLOT(t)*1.1) - sum(x<VLOT(t)*0.9)))/length(x$len) #o lot vai ser a porcentagem de indivíduos 
  que estão no intervalo de comprimentos 10% menor a 10% maior que o VLOT.
  mgr=100 *(sum(x>VLOT(t)*1.1))/length(x$len) # o mgr é a porcentagem de indivíduos na amostra que tem tamanho maior
  que 10% a mais do VLOT.
  res=list(mat=mat, lot=lot, mgr=mgr) # resulta os valores de mat, lot e mgr
  return(res)
}

Script : script_fro.txt