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31
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1 #!/usr/bin/env Rscript
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2
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3 suppressPackageStartupMessages(library("optparse"))
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4
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5 options_list <- list(
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6 make_option(c("-adult_mort", "--adult_mort"), action="store", help="Adjustment rate for adult mortality"),
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7 make_option(c("-adult_nymph_accum", "--adult_nymph_accum"), action="store", help="Adjustment of DD accumulation (old nymph->adult)"),
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8 make_option(c("-egg_mort", "--egg_mort"), action="store", help="Adjustment rate for egg mortality"),
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9 make_option(c("-latitude", "--latitude"), action="store", help="Latitude of selected location"),
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10 make_option(c("-location", "--location"), action="store", help="Selected location"),
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11 make_option(c("-min_clutch_size", "--min_clutch_size"), action="store", help="Adjustment of minimum clutch size"),
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12 make_option(c("-max_clutch_size", "--max_clutch_size"), action="store", help="Adjustment of maximum clutch size"),
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13 make_option(c("-nymph_mort", "--nymph_mort"), action="store", help="Adjustment rate for nymph mortality"),
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14 make_option(c("-old_nymph_accum", "--old_nymph_accum"), action="store", help="Adjustment of DD accumulation (young nymph->old nymph)"),
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15 make_option(c("-output", "--output"), action="store", help="Output dataset"),
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16 make_option(c("-oviposition", "--oviposition"), action="store", help="Adjustment for oviposition rate"),
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17 make_option(c("-photoperiod", "--photoperiod"), action="store", help="Critical photoperiod for diapause induction/termination"),
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18 make_option(c("-replications", "--replications"), action="store", help="Number of replications"),
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19 make_option(c("-se_plot", "--se_plot"), action="store", help="Plot SE"),
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20 make_option(c("-start_year", "--start_year"), action="store", help="Starting year"),
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21 make_option(c("-sim_year", "--sim_year"), action="store", help="Simulation year"),
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22 make_option(c("-temperature_datasets", "--temperature_datasets"), action="store", help="Temperature data for selected location"),
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23 make_option(c("-young_nymph_accum", "--young_nymph_accum"), action="store", help="Adjustment of DD accumulation (egg->young nymph)"),
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24 )
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25
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26 parser <- OptionParser(usage="%prog [options] file", options_list)
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27 arguements <- parse_args(parser, positional_arguments=TRUE)
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28 opt <- args$options
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29 args <- arguments$args
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30
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31 temperature_datasets <- strsplit(opt$temperature_datasets, ",")
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32
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33 # read in the input temperature datafile
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34 data.input(opt$location, opt$start_year, temperature_datasets)
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35
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36 input.name<-paste(opt$location, opt$sim_year, ".Rdat" ,sep="")
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37 output.name<-paste(opt$location, opt$sim_year, "sim.Rdat", sep="")
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38 load(input.name)
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39
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40 # initialize matrix for results from all replications
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41 S0.rep<-S1.rep<-S2.rep<-S3.rep<-S4.rep<-S5.rep<-matrix(rep(0,365*n.rep),ncol=n.rep)
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42 newborn.rep<-death.rep<-adult.rep<-pop.rep<-g0.rep<-g1.rep<-g2.rep<-g0a.rep<-g1a.rep<-g2a.rep<-matrix(rep(0,365*n.rep),ncol=n.rep)
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43
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44 # loop through replications
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45 for (N.rep in 1:n.rep)
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46 {
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47 # during each replication
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48 n<-1000 # start with 1000 individuals -- user definable as well?
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49 # Generation, Stage, DD, T, Diapause
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50 vec.ini<-c(0,3,0,0,0)
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51 # overwintering, previttelogenic,DD=0, T=0, no-diapause
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52 vec.mat<-rep(vec.ini,n)
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53 vec.mat<-t(matrix(vec.mat,nrow=5)) # complete matrix for the population
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54 ph.p<-daylength(L) # complete photoperiod profile in a year, requires daylength function
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55
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56 tot.pop<-NULL # time series of population size
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57 gen0.pop<-rep(0,365) # gen.0 pop size
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58 gen1.pop<-rep(0,365)
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59 gen2.pop<-rep(0,365)
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60 S0<-S1<-S2<-S3<-S4<-S5<-rep(0,365)
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61 g0.adult<-g1.adult<-g2.adult<-rep(0,365)
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62 N.newborn<-N.death<-N.adult<-rep(0,365)
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63 dd.day<-rep(0,365)
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64
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65 ptm <- proc.time() # start tick
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66
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67 # all the days
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68 for (day in 1:365)
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69 {
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70 photoperiod<-ph.p[day] # photoperiod in the day
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71 temp.profile<-hourtemp(L,day)
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72 mean.temp<-temp.profile[1]
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73 dd.temp<-temp.profile[2]
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74 dd.day[day]<-dd.temp
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75 death.vec<-NULL # trash bin for death
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76 birth.vec<-NULL # new born
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77 #n<-length(vec.mat[,1]) # population size at previous day
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78
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79 # all individuals
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80 for (i in 1:n)
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81 {
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82 vec.ind<-vec.mat[i,] # find individual record
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83 # first of all, still alive?
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84 # adjustment for late season mortality rate
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85 if (L<40)
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86 {
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87 post.mort<-1
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88 day.kill<-300
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89 }
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90 else
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91 {
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92 post.mort<-2
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93 day.kill<-250
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94 }
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95 # egg
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96 if(vec.ind[2]==0)
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97 {
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98 death.prob=ar.em*mortality.egg(mean.temp)
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99 }
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100 else if (vec.ind[2]==1 | vec.ind[2]==2)
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101 {
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102 death.prob=ar.nm*mortality.nymph(mean.temp)
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103 }
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104 # for adult
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105 else if (vec.ind[2]==3 | vec.ind[2]==4 | vec.ind[2]==5)
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106 {
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107 if (day<day.kill)
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108 {
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109 death.prob=ar.am*mortality.adult(mean.temp)
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110 }
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111 else
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112 {
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113 death.prob=ar.am*post.mort*mortality.adult(mean.temp)} # increase adult mortality after fall equinox
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114 }
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115 #(or dependent on temperature and life stage?)
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116 u.d<-runif(1)
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117 if (u.d<death.prob)
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118 {
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119 death.vec<-c(death.vec,i)
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120 }
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121 else
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122 {
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123 # aggregrate index of dead bug
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124 # event 1 end of diapause
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125 if (vec.ind[1]==0 && vec.ind[2]==3)
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126 {
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127 # overwintering adult (previttelogenic)
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128 if (photoperiod>ph.cr && vec.ind[3]>68 && day<180)
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129 {
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130 # add 68C to become fully reproductively matured
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131 vec.ind<-c(0,4,0,0,0) # transfer to vittelogenic
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132 vec.mat[i,]<-vec.ind
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133 }
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134 else
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135 {
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136 vec.ind[3]<-vec.ind[3]+dd.temp # add to DD
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137 vec.ind[4]<-vec.ind[4]+1 # add 1 day in current stage
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138 vec.mat[i,]<-vec.ind
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139 }
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140 }
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141 if (vec.ind[1]!=0 && vec.ind[2]==3)
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142 {
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143 # NOT overwintering adult (previttelogenic)
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144 current.gen<-vec.ind[1]
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145 if (vec.ind[3]>68)
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146 {
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147 # add 68C to become fully reproductively matured
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148 vec.ind<-c(current.gen,4,0,0,0) # transfer to vittelogenic
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149 vec.mat[i,]<-vec.ind
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150 }
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151 else
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152 {
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153 vec.ind[3]<-vec.ind[3]+dd.temp # add to DD
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154 vec.ind[4]<-vec.ind[4]+1 # add 1 day in current stage
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155 vec.mat[i,]<-vec.ind
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156 }
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157 }
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158
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159 # event 2 oviposition -- where population dynamics comes from
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160 if (vec.ind[2]==4 && vec.ind[1]==0 && mean.temp>10)
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161 {
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162 # vittelogenic stage, overwintering generation
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163 if (vec.ind[4]==0)
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164 {
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165 # just turned in vittelogenic stage
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166 n.birth=round(runif(1,2+min.ovi.adj,8+max.ovi.adj))
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167 }
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168 else
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169 {
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170 p.birth=ar.ovi*0.01 # daily probability of birth
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171 u1<-runif(1)
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172 if (u1<p.birth)
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173 {
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174 n.birth=round(runif(1,2,8))
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175 }
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176 }
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177 vec.ind[3]<-vec.ind[3]+dd.temp # add to DD
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178 vec.ind[4]<-vec.ind[4]+1 # add 1 day in current stage
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179 vec.mat[i,]<-vec.ind
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180 if (n.birth>0)
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181 {
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182 # add new birth -- might be in different generations
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183 new.gen<-vec.ind[1]+1 # generation +1
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184 new.ind<-c(new.gen,0,0,0,0) # egg profile
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185 new.vec<-rep(new.ind,n.birth)
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186 new.vec<-t(matrix(new.vec,nrow=5)) # update batch of egg profile
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187 birth.vec<-rbind(birth.vec,new.vec) # group with total eggs laid in that day
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188 }
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189 }
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190
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191 # event 2 oviposition -- for gen 1.
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192 if (vec.ind[2]==4 && vec.ind[1]==1 && mean.temp>12.5 && day<222)
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193 {
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194 # vittelogenic stage, 1st generation
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195 if (vec.ind[4]==0)
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196 {
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197 # just turned in vittelogenic stage
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198 n.birth=round(runif(1,2+min.ovi.adj,8+max.ovi.adj))
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199 }
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200 else
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201 {
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202 p.birth=ar.ovi*0.01 # daily probability of birth
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203 u1<-runif(1)
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204 if (u1<p.birth)
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205 {
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206 n.birth=round(runif(1,2,8))
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207 }
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208 }
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209 vec.ind[3]<-vec.ind[3]+dd.temp # add to DD
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210 vec.ind[4]<-vec.ind[4]+1 # add 1 day in current stage
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211 vec.mat[i,]<-vec.ind
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212 if (n.birth>0)
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213 {
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214 # add new birth -- might be in different generations
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215 new.gen<-vec.ind[1]+1 # generation +1
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216 new.ind<-c(new.gen,0,0,0,0) # egg profile
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217 new.vec<-rep(new.ind,n.birth)
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218 new.vec<-t(matrix(new.vec,nrow=5)) # update batch of egg profile
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219 birth.vec<-rbind(birth.vec,new.vec) # group with total eggs laid in that day
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220 }
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221 }
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222
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223 # event 3 development (with diapause determination)
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224 # event 3.1 egg development to young nymph (vec.ind[2]=0 -> egg)
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225 if (vec.ind[2]==0)
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226 {
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227 # egg stage
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228 vec.ind[3]<-vec.ind[3]+dd.temp # add to DD
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229 if (vec.ind[3]>=(68+dd.adj1))
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230 {
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231 # from egg to young nymph, DD requirement met
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232 current.gen<-vec.ind[1]
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233 vec.ind<-c(current.gen,1,0,0,0) # transfer to young nym stage
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234 }
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235 else
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236 {
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237 vec.ind[4]<-vec.ind[4]+1 # add 1 day in current stage
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238 }
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239 vec.mat[i,]<-vec.ind
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240 }
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241
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242 # event 3.2 young nymph to old nymph (vec.ind[2]=1 -> young nymph: determines diapause)
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243 if (vec.ind[2]==1)
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244 {
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245 # young nymph stage
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246 vec.ind[3]<-vec.ind[3]+dd.temp # add to DD
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247 if (vec.ind[3]>=(250+dd.adj2))
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248 {
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249 # from young to old nymph, DD requirement met
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250 current.gen<-vec.ind[1]
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251 vec.ind<-c(current.gen,2,0,0,0) # transfer to old nym stage
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252 if (photoperiod<ph.cr && day > 180)
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253 {
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254 vec.ind[5]<-1
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255 } # prepare for diapausing
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256 }
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257 else
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258 {
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259 vec.ind[4]<-vec.ind[4]+1 # add 1 day in current stage
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260 }
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261 vec.mat[i,]<-vec.ind
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262 }
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263
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264 # event 3.3 old nymph to adult: previttelogenic or diapausing?
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265 if (vec.ind[2]==2)
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266 {
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267 # old nymph stage
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268 vec.ind[3]<-vec.ind[3]+dd.temp # add to DD
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269 if (vec.ind[3]>=(200+dd.adj3))
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270 {
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271 # from old to adult, DD requirement met
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272 current.gen<-vec.ind[1]
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273 if (vec.ind[5]==0)
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274 {
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275 # non-diapausing adult -- previttelogenic
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276 vec.ind<-c(current.gen,3,0,0,0)
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277 }
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278 else
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279 {
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280 # diapausing
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281 vec.ind<-c(current.gen,5,0,0,1)
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282 }
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283 }
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284 else
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285 {
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286 vec.ind[4]<-vec.ind[4]+1 # add 1 day in current stage
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287 }
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288 vec.mat[i,]<-vec.ind
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289 }
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290
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291 # event 4 growing of diapausing adult (unimportant, but still necessary)##
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292 if (vec.ind[2]==5)
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293 {
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294 vec.ind[3]<-vec.ind[3]+dd.temp
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295 vec.ind[4]<-vec.ind[4]+1
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296 vec.mat[i,]<-vec.ind
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297 }
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298 } # else if it is still alive
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299 } # end of the individual bug loop
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300
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301 # find how many died
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302 n.death<-length(death.vec)
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303 if (n.death>0)
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304 {
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305 vec.mat<-vec.mat[-death.vec, ]}
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306 # remove record of dead
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307 # find how many new born
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308 n.newborn<-length(birth.vec[,1])
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309 vec.mat<-rbind(vec.mat,birth.vec)
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310 # update population size for the next day
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311 n<-n-n.death+n.newborn
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312
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313 # aggregate results by day
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314 tot.pop<-c(tot.pop,n)
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315 s0<-sum(vec.mat[,2]==0) #egg
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316 s1<-sum(vec.mat[,2]==1) # young nymph
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317 s2<-sum(vec.mat[,2]==2) # old nymph
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318 s3<-sum(vec.mat[,2]==3) # previtellogenic
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319 s4<-sum(vec.mat[,2]==4) # vitellogenic
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320 s5<-sum(vec.mat[,2]==5) # diapausing
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321 gen0<-sum(vec.mat[,1]==0) # overwintering adult
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322 gen1<-sum(vec.mat[,1]==1) # first generation
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323 gen2<-sum(vec.mat[,1]==2) # second generation
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324 n.adult<-sum(vec.mat[,2]==3)+sum(vec.mat[,2]==4)+sum(vec.mat[,2]==5) # sum of all adults
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325 gen0.pop[day]<-gen0 # gen.0 pop size
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326 gen1.pop[day]<-gen1
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327 gen2.pop[day]<-gen2
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328 S0[day]<-s0
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329 S1[day]<-s1
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330 S2[day]<-s2
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331 S3[day]<-s3
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332 S4[day]<-s4
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333 S5[day]<-s5
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334 g0.adult[day]<-sum(vec.mat[,1]==0)
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335 g1.adult[day]<-sum((vec.mat[,1]==1 & vec.mat[,2]==3) | (vec.mat[,1]==1 & vec.mat[,2]==4) | (vec.mat[,1]==1 & vec.mat[,2]==5))
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336 g2.adult[day]<-sum((vec.mat[,1]==2 & vec.mat[,2]==3) | (vec.mat[,1]==2 & vec.mat[,2]==4) | (vec.mat[,1]==2 & vec.mat[,2]==5))
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337
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338 N.newborn[day]<-n.newborn
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339 N.death[day]<-n.death
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340 N.adult[day]<-n.adult
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341 print(c(N.rep,day,n,n.adult))
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342 } # end of 365 days
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343
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344 #proc.time() - ptm
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345 dd.cum<-cumsum(dd.day)
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346 # save(dd.day,dd.cum,S0,S1,S2,S3,S4,S5,N.newborn,N.death,N.adult,tot.pop,gen0.pop,gen1.pop,gen2.pop,g0.adult,g1.adult,g2.adult,file="wenatchee2013sim.Rdat")
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347 #newborn.rep<-death.rep<-adult.rep<-pop.rep<-g0.rep<-g1.rep<-g2.rep<-g0a.rep<-g1a.rep<-g2a.rep<-matrix(rep(0,365*n.rep),ncol=n.rep)
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348 # collect all the outputs
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349 S0.rep[,N.rep]<-S0
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350 S1.rep[,N.rep]<-S1
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351 S2.rep[,N.rep]<-S2
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352 S3.rep[,N.rep]<-S3
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353 S4.rep[,N.rep]<-S4
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354 S5.rep[,N.rep]<-S5
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355 newborn.rep[,N.rep]<-N.newborn
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356 death.rep[,N.rep]<-N.death
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357 adult.rep[,N.rep]<-N.adult
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358 pop.rep[,N.rep]<-tot.pop
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359 g0.rep[,N.rep]<-gen0.pop
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360 g1.rep[,N.rep]<-gen1.pop
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361 g2.rep[,N.rep]<-gen2.pop
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362 g0a.rep[,N.rep]<-g0.adult
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363 g1a.rep[,N.rep]<-g1.adult
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364 g2a.rep[,N.rep]<-g2.adult
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365 }
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366
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367 save(dd.day,dd.cum,S0.rep,S1.rep,S2.rep,S3.rep,S4.rep,S5.rep,newborn.rep,death.rep,adult.rep,pop.rep,g0.rep,g1.rep,g2.rep,g0a.rep,g1a.rep,g2a.rep,file=opt$output)
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368 # maybe do not need to export this bit, but for now just leave it as-is
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369 # do we need to export this Rdat file?
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370
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371
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372 #########################################
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373 # input starting year and how many years
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374 # n.yr and start.yr needs to be integer
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375 # loc.name needs to be CHARACTER and matches exactly the name in the csv file!!!
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376 data.input=function(loc, start.yr, temperature.datasets)
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377 {
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378 n.yr <- length(temperature_datasets)
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379 for (i in 1:n.yr)
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380 {
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381 expdata<-matrix(rep(0,365*3),nrow=365)
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382 yr<-start.yr+i # replace 2004 with start. yr
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383 name.input<-paste(temperature.datasets[i], ".csv", sep="")
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384 namedat<-paste(loc, yr,".Rdat",sep="")
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385 temp.data<-read.csv(file=name.input, header=T)
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386
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387 expdata[,1]<-c(1:365)
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388 expdata[,2]<-temp.data[c(1:365),3] #minimum
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389 expdata[,3]<-temp.data[c(1:365),2] #maximum
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390 save(expdata,file=namedat)
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391 }
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392 }
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393 #########################################
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394
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395 #########################################
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396 daylength=function(L)
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397 {
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398 # from Forsythe 1995
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399 p=0.8333
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400 dl<-NULL
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401 for (i in 1:365)
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402 {
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403 theta<-0.2163108+2*atan(0.9671396*tan(0.00860*(i-186)))
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404 phi<-asin(0.39795*cos(theta))
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405 dl[i]<-24-24/pi*acos((sin(p*pi/180)+sin(L*pi/180)*sin(phi))/(cos(L*pi/180)*cos(phi)))
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406 }
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407 dl # return a vector of daylength in 365 days
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408 }
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409 #########################################
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410
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411 #########################################
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412 hourtemp=function(L,date)
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413 {
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414 threshold<-14.17 # base development threshold for BMSB
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415 dnp<-expdata[date,2] # daily minimum
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416 dxp<-expdata[date,3] # daily maximum
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417 dmean<-0.5*(dnp+dxp)
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418 dd<-0 # initialize degree day accumulation
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419
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420 if (dxp<threshold)
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421 {
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422 dd<-0
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423 }
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424 else
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425 {
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426 dlprofile<-daylength(L) # extract daylength data for entire year
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427 T<-NULL # initialize hourly temperature
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428 dh<-NULL #initialize degree hour vector
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429 # date<-200
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430 y<-dlprofile[date] # calculate daylength in given date
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431 z<-24-y # night length
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432 a<-1.86 # lag coefficient
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433 b<-2.20 # night coefficient
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434 #tempdata<-read.csv("tempdata.csv") #import raw data set
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435 # Should be outside function otherwise its redundant
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436 risetime<-12-y/2 # sunrise time
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437 settime<-12+y/2 # sunset time
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438 ts<-(dxp-dnp)*sin(pi*(settime-5)/(y+2*a))+dnp
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439 for (i in 1:24)
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440 {
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441 if (i>risetime && i<settime)
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442 {
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443 m<-i-5 # number of hours after Tmin until sunset
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444 T[i]=(dxp-dnp)*sin(pi*m/(y+2*a))+dnp
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445 if (T[i]<8.4)
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446 {
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447 dh[i]<-0
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448 }
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449 else
|
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450 {
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451 dh[i]<-T[i]-8.4
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452 }
|
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453 }
|
|
|
454 else if (i>settime)
|
|
|
455 {
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456 n<-i-settime
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457 T[i]=dnp+(ts-dnp)*exp(-b*n/z)
|
|
|
458 if (T[i]<8.4)
|
|
|
459 {
|
|
|
460 dh[i]<-0
|
|
|
461 }
|
|
|
462 else
|
|
|
463 {
|
|
|
464 dh[i]<-T[i]-8.4
|
|
|
465 }
|
|
|
466 }
|
|
|
467 else
|
|
|
468 {
|
|
|
469 n<-i+24-settime
|
|
|
470 T[i]=dnp+(ts-dnp)*exp(-b*n/z)
|
|
|
471 if (T[i]<8.4)
|
|
|
472 {
|
|
|
473 dh[i]<-0
|
|
|
474 }
|
|
|
475 else
|
|
|
476 {
|
|
|
477 dh[i]<-T[i]-8.4
|
|
|
478 }
|
|
|
479 }
|
|
|
480 }
|
|
|
481 dd<-sum(dh)/24
|
|
|
482 }
|
|
|
483 return=c(dmean,dd)
|
|
|
484 return
|
|
|
485 }
|
|
|
486 #########################################
|
|
|
487
|
|
|
488 #########################################
|
|
|
489 dev.egg=function(temperature)
|
|
|
490 {
|
|
|
491 dev.rate=-0.9843*temperature+33.438
|
|
|
492 return=dev.rate
|
|
|
493 return
|
|
|
494 }
|
|
|
495 #########################################
|
|
|
496
|
|
|
497 #########################################
|
|
|
498 dev.young=function(temperature)
|
|
|
499 {
|
|
|
500 n12<--0.3728*temperature+14.68
|
|
|
501 n23<--0.6119*temperature+25.249
|
|
|
502 dev.rate=mean(n12+n23)
|
|
|
503 return=dev.rate
|
|
|
504 return
|
|
|
505 }
|
|
|
506 #########################################
|
|
|
507
|
|
|
508 #########################################
|
|
|
509 dev.old=function(temperature)
|
|
|
510 {
|
|
|
511 n34<--0.6119*temperature+17.602
|
|
|
512 n45<--0.4408*temperature+19.036
|
|
|
513 dev.rate=mean(n34+n45)
|
|
|
514 return=dev.rate
|
|
|
515 return
|
|
|
516 }
|
|
|
517 #########################################
|
|
|
518
|
|
|
519 #########################################
|
|
|
520 dev.emerg=function(temperature)
|
|
|
521 {
|
|
|
522 emerg.rate<--0.5332*temperature+24.147
|
|
|
523 return=emerg.rate
|
|
|
524 return
|
|
|
525 }
|
|
|
526 #########################################
|
|
|
527
|
|
|
528 #########################################
|
|
|
529 mortality.egg=function(temperature)
|
|
|
530 {
|
|
|
531 if (temperature<12.7)
|
|
|
532 {
|
|
|
533 mort.prob=0.8
|
|
|
534 }
|
|
|
535 else
|
|
|
536 {
|
|
|
537 mort.prob=0.8-temperature/40
|
|
|
538 if (mort.prob<0)
|
|
|
539 {
|
|
|
540 mort.prob=0.01
|
|
|
541 }
|
|
|
542 }
|
|
|
543 return=mort.prob
|
|
|
544 return
|
|
|
545 }
|
|
|
546 #########################################
|
|
|
547
|
|
|
548 #########################################
|
|
|
549 mortality.nymph=function(temperature)
|
|
|
550 {
|
|
|
551 if (temperature<12.7)
|
|
|
552 {
|
|
|
553 mort.prob=0.03
|
|
|
554 }
|
|
|
555 else
|
|
|
556 {
|
|
|
557 mort.prob=temperature*0.0008+0.03
|
|
|
558 }
|
|
|
559 return=mort.prob
|
|
|
560 return
|
|
|
561 }
|
|
|
562 #########################################
|
|
|
563
|
|
|
564 #########################################
|
|
|
565 mortality.adult=function(temperature)
|
|
|
566 {
|
|
|
567 if (temperature<12.7)
|
|
|
568 {
|
|
|
569 mort.prob=0.002
|
|
|
570 }
|
|
|
571 else
|
|
|
572 {
|
|
|
573 mort.prob=temperature*0.0005+0.02
|
|
|
574 }
|
|
|
575 return=mort.prob
|
|
|
576 return
|
|
|
577 }
|
|
|
578 ######################################### |
