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Doutoranda em Oceanografia IO-USP. Trabalho com pesca de peixes recifais no Banco dos Abrolhos, BA.
Ambas as propostas são objetivas, factíveis e de interesse para teu campo de estudo. Porém, eu não entendi como seria dado o VLOT no plano A. Já existe essa informação na literatura? Me parece que o plano B deveria ser um passo dentro do plano A, não? Outra coisa, no plano A o vetor LEN é dado pelo usuário, certo? Em caso positivo o vetor LEN também seria um argumento da função.
—- Carlos
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