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
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
|
library(popbio)
library(dplyr)
rm(list=ls())
data<-read.table("DESL.txt",header=T)
germin <- read.table("germination.txt",h=T)
germ <- germin[,"desl"]
create.matrix <- function(data,germ) {
matrices <- list()
for (year in c(2001:2017)) {
i.year <- year - 2000
data1 = data[, c(i.year,i.year+1)]
#Survie germination
sgt <- data1[which(data1[,1] == 2),] # fait la meme chose que sgt=filter(data1, X2003 == 2) mais sans besoin de spécifier le nom de la colonne
sgt1 <- sgt[which(sgt[,2] == 3),]
# sgt0=filter(data1, X2003 == 2)
# sgt10=filter(sgt,X2004 == 3)
# all(sgt==sgt0)
# all(sgt1==sgt10)
#Survie juvénile
sjt <- data1[which(data1[,1] == 3),]
sjt1 <- sjt[which(sjt[,2] == 3),]
sjt11 <- sjt[which(sjt[,2] == 5),]
sjtDeath <- sjt[which(sjt[,2] == 6),]
# sjt0=filter(data1, X2003 == 3)
# sjt10=filter(sjt,X2004 == 3)
# sjt110=filter(sjt,X2004 == 5)
# sjtDeath0=filter(sjt,X2004 == 6)
#Survie adule non fleuri
sant <- data1[which(data1[,1] == 4),]
sant1 <- sant[which(sant[,2] == 4),]
sant11 <- sant[which(sant[,2] == 5),]
santDeath <- sant[which(sant[,2] == 6),]
# sant0=filter(data1, X2003 == 4)
# sant10=filter(sant0,X2004 == 4)
# sant110=filter(sant0,X2004 == 5)
# santDeath0=filter(sant0,X2004 == 6)
# all(sant == sant0)
# all(sant1 == sant10)
# all(sant11 == sant110)
# all(santDeath == santDeath0)
#Survie adulte fleuri
sat <- data1[which(data1[,1] == 5),]
sat1 <- sat[which(sat[,2] == 4),]
sat11 <- sat[which(sat[,2] == 5),]
satDeath <- sat[which(sat[,2] == 6),]
# sat0=filter(data1, X2003 == 5)
# sat10=filter(sat0,X2004 == 4)
# sat110=filter(sat0,X2004 == 5)
# satDeath0=filter(sat0,X2004 == 6)
#Floraison juvénile
fjt <- data1[which(data1[,1] == 3),]
fjt1 <- fjt[which(fjt[,2] == 5),]
# fjt0=filter(data1, X2003 == 3)
# fjt10=filter(fjt,X2004 == 5)
# all(fjt == fjt0)
# all(fjt1 == fjt10)
#Floraison adulte non fleuri
fant <- data1[which(data1[,1] == 4),]
fant1 <- fant[which(fant[,2] == 5),]
# fant0=filter(data1, X2003 == 4)
# fant10=filter(fant,X2004 == 5)
# all(fant == fant0)
# all(fant1 == fant10)
#Floraison adulte fleuri
fat <- data1[which(data1[,1] == 5),]
fat1 <- fat[which(fat[,2] == 5),]
# fat0=filter(data1, X2003 == 5)
# fat10=filter(fat,X2004 == 5)
# all(fat == fat0)
# all(fat1 == fat10)
# #Fécondité
# ft=filter(data1, X2003 == 5)
# Calcul des taux de survie et des taux de fécondité
survG <- dim(sgt1)[1] / germ[i.year]
#germt1=dim(sgt1)[1]
survJ=(dim(sjt1)+dim(sjt11))/(dim(sjt1)+dim(sjt11)+dim(sjtDeath))
survJ <- survJ[1]
survV=(dim(sant1)+dim(sant11))/(dim(sant1)+dim(sant11)+dim(santDeath))
survV <- survV[1]
survR=(dim(sat1)+dim(sat11))/(dim(sat1)+dim(sat11)+dim(satDeath))
survR <- survR[1]
florJ=dim(fjt1)/(dim(sjt1)+dim(sjt11))
florJ <- florJ[1]
florV=dim(fant1)/(dim(sant1)+dim(sant11))
florV <- florV[1]
florR=dim(fat1)/(dim(sat1)+dim(sat11))
florR <- florR[1]
feco <- germ[(i.year+1)] / dim(fat)[1]
# Calcul des élements de la matrice
agr=feco
ajg=survG
ajj=survJ*(1-florJ)
arj=survJ*florJ
arr=survR*florR
arv=survV*florV
avr=survR*(1-florR)
avv=survV*(1-florV)
# Construction de la matrice
# Les deux format donnent effectivement la meme chose, garde celle qu te plait le plus
# A <- matrix(c(0,ajg,0,0,
# 0,ajj,0,arj,
# 0,0,avv,arv,
# agr,0,avr,arr),nrow=4,ncol=4)
A <- matrix(c(0,0,0,agr,
ajg,ajj,0,0,
0,0,avv,avr,
0,arj,arv,arr),4,4,byrow=T)
dimnames(A)<-list(fate=c("G","J","V","R"),state=c("G","J","V","R"))
matrices[[i.year]] <- A
names(matrices)[i.year] <- paste(year,(year+1),sep="-")
}
#remplacer les survie germinations (2001, 2002) et fécondité (2001)
matrices[[1]][1,4]<-22.5958
matrices[[1]][2,1]<-0.31105985
matrices[[2]][2,1]<-0.31105985
return(lambda(matrices[[1]]))
}
create.matrix(data,germ)
library(boot)
la=boot(data, create.matrix, 10)
la
boot.ci(la) |
