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1 #!/usr/bin/env Rscript
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2
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11
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3 #suppressPackageStartupMessages(library("optparse"))
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4 #suppressPackageStartupMessages(library("rjson"))
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5
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13
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6 options_list <- list(
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7 make_option(c("-s", "--save_log"), action="store_true", default=FALSE, help="Save R logs"),
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8 make_option(c("-m", "--output_r_log"), action="store", help="Output dataset for R logs"),
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9 make_option(c("-o", "--output"), action="store", help="Output dataset")
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10 )
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11
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13
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12 parser <- OptionParser(usage="%prog [options] file", options_list)
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13 args <- parse_args(parser, positional_arguments=TRUE)
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14 opt <- args$options
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15
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16
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17 daylength = function(L){
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18 # from Forsythe 1995
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19 p = 0.8333
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20 dl <- NULL
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21 for (i in 1:365) {
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22 theta <- 0.2163108 + 2 * atan(0.9671396 * tan(0.00860 * (i - 186)))
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23 phi <- asin(0.39795 * cos(theta))
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24 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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25 }
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26 # return a vector of daylength in 365 days
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27 dl
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28 }
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29
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30
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31 # source("daylength.R")
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32 hourtemp = function(L,date){
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33 # L = 37.5 specify this in main program
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34 # base development threshold for BMSB
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35 threshold <- 12.7
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36 # threshold2 <- threshold/24 degree hour accumulation
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37 #expdata <- tempdata[1:365,11:13] # Use daily max, min, mean
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38 # daily minimum
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39 dnp <- expdata[date,2]
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40 # daily maximum
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41 dxp <- expdata[date,3]
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42 dmean <- 0.5 * (dnp + dxp)
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43 #if (dmean>0) {
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44 #dnp <- dnp - k1 * dmean
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45 #dxp <- dxp + k2 * dmean
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46 #} else {
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47 #dnp <- dnp + k1 * dmean
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48 #dxp <- dxp - k2 * dmean
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49 #}
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50 dd <- 0 # initialize degree day accumulation
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51
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52 if (dxp<threshold) {
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53 dd <- 0
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54 } else {
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55 # extract daylength data for entire year
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56 dlprofile <- daylength(L)
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57 # initialize hourly temperature
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58 T <- NULL
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59 #initialize degree hour vector
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60 dh <- NULL
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61 # calculate daylength in given date
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62 # date <- 200
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63 y <- dlprofile[date]
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64 # night length
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65 z <- 24 - y
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66 # lag coefficient
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67 a <- 1.86
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68 # night coefficient
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69 b <- 2.20
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70 #import raw data set
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71 #tempdata <- read.csv("tempdata.csv")
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72 # Should be outside function otherwise its redundant
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73 # sunrise time
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74 risetime <- 12 - y/2
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75 # sunset time
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76 settime <- 12 + y/2
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77 ts <- (dxp - dnp) * sin(pi * (settime-5)/(y + 2 * a)) + dnp
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78 for (i in 1:24) {
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79 if (i > risetime && i < settime) {
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80 # number of hours after Tmin until sunset
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81 m <- i - 5
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82 T[i] = (dxp - dnp) * sin(pi * m/(y + 2 * a)) + dnp
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83 if (T[i]<8.4) {
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84 dh[i] <- 0
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85 } else {
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86 dh[i] <- T[i] - 8.4
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87 }
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88 } else if (i>settime) {
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89 n <- i - settime
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90 T[i] = dnp + (ts - dnp) * exp(-b * n/z)
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91 if (T[i]<8.4) {
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92 dh[i] <- 0
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93 } else {
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94 dh[i] <- T[i] - 8.4
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95 }
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96 } else {
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97 n <- i + 24 - settime
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98 T[i] = dnp + (ts - dnp) * exp(-b * n / z)
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99 if (T[i]<8.4) {
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100 dh[i] <- 0
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101 } else {
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102 dh[i] <- T[i] - 8.4
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103 }
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104 }
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105 }
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106 dd <- sum(dh) / 24
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107 }
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108 return = c(dmean, dd)
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109 return
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110 }
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111
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112
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113 mortality.egg = function(temperature) {
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114 if (temperature < 12.7) {
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115 mort.prob = 1
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116 } else {
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117 # 100% mortality if <12.7
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118 mort.prob = 0.8 - temperature / 40
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119 if (mort.prob<0) {
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120 mort.prob = 0.01
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121 }
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122 }
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123 return = mort.prob
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124 return
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125 }
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126
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127
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128 mortality.nymph = function(temperature) {
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129 if (temperature<12.7) {
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130 mort.prob = 0.03
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131 } else {
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132 # at low temperature
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133 mort.prob = -temperature * 0.0008 + 0.03
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134 }
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135 return = mort.prob
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136 return
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137 }
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138
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139
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140 mortality.adult = function(temperature) {
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141 if (temperature < 12.7) {
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142 mort.prob = 0.002
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143 } else {
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144 mort.prob = -temperature * 0.0005 + 0.02
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145 }
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146 return = mort.prob
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147 return
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148 }
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149
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150
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151 # model initialization
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152 # TODO: add tool params for the following options.
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153 # start with 1000 individuals
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154 n <- 1000
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155 # Generation, Stage, DD, T, Diapause
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156 vec.ini <- c(0,3,0,0,0)
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157 # overwintering, previttelogenic, DD = 0, T = 0, no-diapause
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158 vec.mat <- rep(vec.ini,n)
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159 # complete matrix for the population
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160 vec.mat <- t(matrix(vec.mat, nrow = 5))
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161 # latitude for Asheville NC
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162 L <- 35.58
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163 # complete photoperiod profile in a year, requires daylength function
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164 ph.p <- daylength(L)
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165
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166 # load temperature data@location/year
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167 load("asheville2014.Rdat")
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168
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169 # time series of population size
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170 tot.pop <- NULL
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171
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172 # gen.0 pop size
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173 gen0.pop <- rep(0, 365)
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174 gen1.pop <- rep(0, 365)
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175 gen2.pop <- rep(0, 365)
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176
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177 # aggregate
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178 S0 <- S1 <- S2 <- S3 <- S4 <- S5 <- rep(0, 365)
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179 g0.adult <- g1.adult <- g2.adult <- rep(0, 365)
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180
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181 # birth death adults
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182 N.newborn <- N.death <- N.adult <- rep(0, 365)
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183
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184 # degree-day accumulation
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185 dd.day <- rep(0, 365)
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186
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187 # start tick
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188 ptm <- proc.time()
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189
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190 for (n.sim in 1:1000) {
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191 # loop through 1000 simulations
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192 for (day in 1:365) {
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193 # loop through 365 day/yr
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194 photoperiod <- ph.p[day]
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195 # photoperiod in the day
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196 temp.profile <- hourtemp(L,day)
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197 # temperature profile
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198 mean.temp <- temp.profile[1]
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199 # mean temp
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200 dd.temp <- temp.profile[2]
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201 # degree-day
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202 dd.day[day] <- dd.temp
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203 death.vec <- NULL
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204 # trash bin for death
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205 birth.vec <- NULL
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206 # record new born
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207 for (i in 1:n) {
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208 # loop through all individual
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209 vec.ind <- vec.mat[i,]
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210 # find individual record
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211 # first of all, still alive?
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212 if (vec.ind[2] == 0) {
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213 # egg
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214 death.prob = mortality.egg(mean.temp)
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215 } else if (vec.ind[2] == 1 | vec.ind[2] == 2) {
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216 # nymph
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217 death.prob = mortality.nymph(mean.temp)
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218 } else if (vec.ind[2] == 3 | vec.ind[2] == 4 | vec.ind[2] == 5) {
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219 # for adult
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220 death.prob = mortality.adult(mean.temp)
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221 }
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222 u.d <- runif(1)
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223 if (u.d<death.prob) {
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224 death.vec <- c(death.vec,i)
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225 } else {
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226 # aggregrate index of dead bug
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227 # event 1 end of diapause
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228 if (vec.ind[1] == 0 && vec.ind[2] == 3) {
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229 # overwintering adult (previttelogenic)
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230 if (photoperiod>13.5 && vec.ind[3] > 68 && day < 180) {
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231 # add 68C to become fully reproductively matured
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232 # transfer to vittelogenic
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233 vec.ind <- c(0,4,0,0,0)
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234 vec.mat[i,] <- vec.ind
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235 } else {
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236 # add to DD
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237 vec.ind[3] <- vec.ind[3] + dd.temp
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238 vec.ind[4] <- vec.ind[4] + 1 # add 1 day in current stage
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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 if (vec.ind[1]!=0 && vec.ind[2] == 3) {
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243 # NOT overwintering adult (previttelogenic)
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244 current.gen <- vec.ind[1]
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245 if (vec.ind[3]>68) {
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246 # add 68C to become fully reproductively matured
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247 # transfer to vittelogenic
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248 vec.ind <- c(current.gen,4,0,0,0)
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249 vec.mat[i,] <- vec.ind
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250 } else {
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251 # add to DD
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252 vec.ind[3] <- vec.ind[3] + dd.temp
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253 # add 1 day in current stage
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254 vec.ind[4] <- vec.ind[4] + 1
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255 vec.mat[i,] <- vec.ind
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256 }
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257 }
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258 # event 2 oviposition -- where population dynamics comes from
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259 # vittelogenic stage, overwintering generation
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260 if (vec.ind[2] == 4 && vec.ind[1] == 0 && mean.temp>10) {
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261 if (vec.ind[4] == 0) {
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262 # just turned in vittelogenic stage
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263 n.birth = round(runif(1,10,20))
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264 } else {
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265 p.birth = 1/4/75
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266 # prob of birth
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267 u1 <- runif(1)
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268 if (u1<p.birth) {
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269 n.birth = n.birth
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270 }
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271 }
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272 # add to DD
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273 vec.ind[3] <- vec.ind[3] + dd.temp
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274 # add 1 day in current stage
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275 vec.ind[4] <- vec.ind[4] + 1
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276 vec.mat[i,] <- vec.ind
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277 if (n.birth>0) {
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278 # add new birth -- might be in different generations
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279 # generation + 1
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280 new.gen <- vec.ind[1] + 1
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281 # egg profile
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282 new.ind <- c(new.gen,0,0,0,0)
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283 new.vec <- rep(new.ind,n.birth)
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284 # update batch of egg profile
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285 new.vec <- t(matrix(new.vec,nrow = 5))
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286 # group with total eggs laid in that day
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287 birth.vec <- rbind(birth.vec,new.vec)
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288 }
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289 }
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290 # event 2 oviposition -- for gen 1.
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291 if (vec.ind[2] == 4 && vec.ind[1] == 1 && mean.temp>12.5 && day<222) {
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292 # vittelogenic stage, 1st generation
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293 if (vec.ind[4] == 0) {
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294 # just turned in vittelogenic stage
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295 n.birth = round(runif(1,10,20))
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296 } else {
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297 p.birth = 1/4/75
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298 u1 <- runif(1)
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299 if (u1<p.birth) {
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300 n.birth = n.birth
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301 }
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302 }
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303 # add to DD
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304 vec.ind[3] <- vec.ind[3] + dd.temp
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305 # add 1 day in current stage
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306 vec.ind[4] <- vec.ind[4] + 1
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307 vec.mat[i,] <- vec.ind
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308 if (n.birth>0) {
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309 # add new birth -- might be in different generations
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310 # generation + 1
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311 new.gen <- vec.ind[1] + 1
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312 # egg profile
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313 new.ind <- c(new.gen,0,0,0,0)
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314 new.vec <- rep(new.ind,n.birth)
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315 # update batch of egg profile
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316 new.vec <- t(matrix(new.vec,nrow = 5))
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317 # group with total eggs laid in that day
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318 birth.vec <- rbind(birth.vec,new.vec)
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319 }
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320 }
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321 # event 3 development (with diapause determination)
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322 # event 3.1 egg development to young nymph (vec.ind[2] = 0 -> egg)
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323 # egg stage
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324 if (vec.ind[2] == 0) {
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325 # add to DD
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326 vec.ind[3] <- vec.ind[3] + dd.temp
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327 # from egg to young nymph
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328 if (vec.ind[3] >= 53.30 && -0.9843 * dd.temp + 33.438>0) {
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329 current.gen <- vec.ind[1]
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330 # transfer to young nym stage
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331 vec.ind <- c(current.gen,1,0,0,0)
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332 } else {
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333 # add 1 day in current stage
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334 vec.ind[4] <- vec.ind[4] + 1
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335 }
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336 vec.mat[i,] <- vec.ind
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337 }
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338 # event 3.2 young nymph to old nymph (vec.ind[2] = 1 -> young nymph: determines diapause)
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339 # young nymph stage
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340 if (vec.ind[2] == 1) {
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341 # add to DD
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342 vec.ind[3] <- vec.ind[3] + dd.temp
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343 # from young to old nymph
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344 if (vec.ind[3] >= 537/2 && -0.45 * dd.temp + 18>0) {
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345 current.gen <- vec.ind[1]
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346 # transfer to old nym stage
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347 vec.ind <- c(current.gen,2,0,0,0)
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348 # prepare for diapausing
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349 if (photoperiod<13.5 && day > 180) {
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350 vec.ind[5] <- 1
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351 }
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352 } else {
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353 # add 1 day in current stage
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354 vec.ind[4] <- vec.ind[4] + 1
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355 }
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356 vec.mat[i,] <- vec.ind
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357 }
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358 # event 3.3 old nymph to adult: previttelogenic or diapausing?
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359 # old nymph stage
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360 if (vec.ind[2] == 2) {
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361 # add to DD
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362 vec.ind[3] <- vec.ind[3] + dd.temp
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363 # from old to adult
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364 if (vec.ind[3] >= 537/2 && -0.50 * dd.temp + 22>0) {
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365 current.gen <- vec.ind[1]
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366 # non-diapausing adult -- previttelogenic
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367 if (vec.ind[5] == 0) {
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368 vec.ind <- c(current.gen,3,0,0,0)
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369 # diapausing
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370 } else {
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371 vec.ind <- c(current.gen,5,0,0,1)
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372 }
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373 } else {
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374 # add 1 day in current stage
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375 vec.ind[4] <- vec.ind[4] + 1
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376 }
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377 vec.mat[i,] <- vec.ind
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378 }
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379 # event 4 growing of diapausing adult (unimportant, but still necessary)##
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380 if (vec.ind[2] == 5) {
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381 vec.ind[3] <- vec.ind[3] + dd.temp
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382 vec.ind[4] <- vec.ind[4] + 1
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383 vec.mat[i,] <- vec.ind
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384 }
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385 } # else if it is still alive
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386 } # end of the individual bug loop
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387 # find how many died
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388 n.death <- length(death.vec)
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389 if (n.death>0) {
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390 vec.mat <- vec.mat[-death.vec, ]
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391 }
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392 # remove record of dead
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393 # find how many new born
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394 n.newborn <- length(birth.vec[,1])
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395 vec.mat <- rbind(vec.mat,birth.vec)
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396 # update population size for the next day
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397 n <- n-n.death + n.newborn
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398
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399 # aggregate results by day
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400 tot.pop <- c(tot.pop,n)
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401 # egg
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402 s0 <- sum(vec.mat[,2] == 0)
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403 # young nymph
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404 s1 <- sum(vec.mat[,2] == 1)
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405 # old nymph
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406 s2 <- sum(vec.mat[,2] == 2)
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407 # previtellogenic
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408 s3 <- sum(vec.mat[,2] == 3)
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409 # vitellogenic
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410 s4 <- sum(vec.mat[,2] == 4)
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411 # diapausing
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412 s5 <- sum(vec.mat[,2] == 5)
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413 # overwintering adult
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414 gen0 <- sum(vec.mat[,1] == 0)
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415 # first generation
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416 gen1 <- sum(vec.mat[,1] == 1)
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417 # second generation
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418 gen2 <- sum(vec.mat[,1] == 2)
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419 # sum of all adults
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420 n.adult <- sum(vec.mat[,2] == 3) + sum(vec.mat[,2] == 4) + sum(vec.mat[,2] == 5)
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421 # gen.0 pop size
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422 gen0.pop[day] <- gen0
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423 gen1.pop[day] <- gen1
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424 gen2.pop[day] <- gen2
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425 S0[day] <- s0
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426 S1[day] <- s1
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427 S2[day] <- s2
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428 S3[day] <- s3
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429 S4[day] <- s4
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430 S5[day] <- s5
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431 g0.adult[day] <- sum(vec.mat[,1] == 0)
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432 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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433 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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434 N.newborn[day] <- n.newborn
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435 N.death[day] <- n.death
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436 N.adult[day] <- n.adult
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437 }
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11
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438 #print(n.sim)
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0
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439 }
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440
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441 proc.time() - ptm
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442 dd.cum <- cumsum(dd.day)
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11
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443 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=opt$output)
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