Mercurial > repos > greg > insect_phenology_model
changeset 5:1878a03f9c9f draft
Uploaded
| author | greg |
|---|---|
| date | Wed, 22 Nov 2017 13:22:49 -0500 |
| parents | e7b1fc0133bb |
| children | fe3f86012394 |
| files | insect_phenology_model.R insect_phenology_model.xml |
| diffstat | 2 files changed, 652 insertions(+), 657 deletions(-) [+] |
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--- a/insect_phenology_model.R Mon Nov 13 12:57:46 2017 -0500 +++ b/insect_phenology_model.R Wed Nov 22 13:22:49 2017 -0500 @@ -1,656 +1,647 @@ -#!/usr/bin/env Rscript - -suppressPackageStartupMessages(library("optparse")) - -option_list <- list( - make_option(c("-a", "--adult_mort"), action="store", dest="adult_mort", type="integer", help="Adjustment rate for adult mortality"), - make_option(c("-b", "--adult_accum"), action="store", dest="adult_accum", type="integer", help="Adjustment of DD accumulation (old nymph->adult)"), - make_option(c("-c", "--egg_mort"), action="store", dest="egg_mort", type="integer", help="Adjustment rate for egg mortality"), - make_option(c("-e", "--location"), action="store", dest="location", help="Selected location"), - make_option(c("-f", "--min_clutch_size"), action="store", dest="min_clutch_size", type="integer", help="Adjustment of minimum clutch size"), - make_option(c("-i", "--max_clutch_size"), action="store", dest="max_clutch_size", type="integer", help="Adjustment of maximum clutch size"), - make_option(c("-j", "--nymph_mort"), action="store", dest="nymph_mort", type="integer", help="Adjustment rate for nymph mortality"), - make_option(c("-k", "--old_nymph_accum"), action="store", dest="old_nymph_accum", type="integer", help="Adjustment of DD accumulation (young nymph->old nymph)"), - make_option(c("-n", "--num_days"), action="store", dest="num_days", type="integer", help="Total number of days in the temperature dataset"), - make_option(c("-o", "--output"), action="store", dest="output", help="Output dataset"), - make_option(c("-p", "--oviposition"), action="store", dest="oviposition", type="integer", help="Adjustment for oviposition rate"), - make_option(c("-q", "--photoperiod"), action="store", dest="photoperiod", type="double", help="Critical photoperiod for diapause induction/termination"), - make_option(c("-s", "--replications"), action="store", dest="replications", type="integer", help="Number of replications"), - make_option(c("-t", "--se_plot"), action="store", dest="se_plot", help="Plot SE"), - make_option(c("-v", "--input"), action="store", dest="input", help="Temperature data for selected location"), - make_option(c("-y", "--young_nymph_accum"), action="store", dest="young_nymph_accum", type="integer", help="Adjustment of DD accumulation (egg->young nymph)") -) - -parser <- OptionParser(usage="%prog [options] file", option_list=option_list) -args <- parse_args(parser, positional_arguments=TRUE) -opt <- args$options - -get_daylight_length = function(latitude, temperature_data, num_days) -{ - # Return a vector of daylight length (photoperido profile) for - # the number of days specified in the input temperature data - # (from Forsythe 1995). - p = 0.8333 - daylight_length_vector <- NULL - for (i in 1:num_days) { - # Get the day of the year from the current row - # of the temperature data for computation. - doy <- temperature_data[i, 4] - theta <- 0.2163108 + 2 * atan(0.9671396 * tan(0.00860 * (doy - 186))) - phi <- asin(0.39795 * cos(theta)) - # Compute the length of daylight for the day of the year. - daylight_length_vector[i] <- 24 - (24 / pi * acos((sin(p * pi / 180) + sin(latitude * pi / 180) * sin(phi)) / (cos(latitude * pi / 180) * cos(phi)))) - } - daylight_length_vector -} - -get_temperature_at_hour = function(latitude, temperature_data, daylight_length_vector, row, num_days) -{ - # Base development threshold for Brown Marmolated Stink Bug - # insect phenology model. - # TODO: Pass insect on the command line to accomodate more - # the just the Brown Marmolated Stink Bub. - threshold <- 14.17 - - # Input temperature currently has the following columns. - # # LATITUDE, LONGITUDE, DATE, DOY, TMIN, TMAX - # Minimum temperature for current row. - dnp <- temperature_data[row, 5] - # Maximum temperature for current row. - dxp <- temperature_data[row, 6] - # Mean temperature for current row. - dmean <- 0.5 * (dnp + dxp) - # Initialize degree day accumulation - dd <- 0 - if (dxp < threshold) { - dd <- 0 - } - else { - # Initialize hourly temperature. - T <- NULL - # Initialize degree hour vector. - dh <- NULL - # Daylight length for current row. - y <- daylight_length_vector[row] - # Darkness length. - z <- 24 - y - # Lag coefficient. - a <- 1.86 - # Darkness coefficient. - b <- 2.20 - # Sunrise time. - risetime <- 12 - y / 2 - # Sunset time. - settime <- 12 + y / 2 - ts <- (dxp - dnp) * sin(pi * (settime - 5) / (y + 2 * a)) + dnp - for (i in 1:24) { - if (i > risetime && i < settime) { - # Number of hours after Tmin until sunset. - m <- i - 5 - T[i] = (dxp - dnp) * sin(pi * m / (y + 2 * a)) + dnp - if (T[i] < 8.4) { - dh[i] <- 0 - } - else { - dh[i] <- T[i] - 8.4 - } - } - else if (i > settime) { - n <- i - settime - T[i] = dnp + (ts - dnp) * exp( - b * n / z) - if (T[i] < 8.4) { - dh[i] <- 0 - } - else { - dh[i] <- T[i] - 8.4 - } - } - else { - n <- i + 24 - settime - T[i]=dnp + (ts - dnp) * exp( - b * n / z) - if (T[i] < 8.4) { - dh[i] <- 0 - } - else { - dh[i] <- T[i] - 8.4 - } - } - } - dd <- sum(dh) / 24 - } - return=c(dmean, dd) - return -} - -dev.egg = function(temperature) -{ - dev.rate= -0.9843 * temperature + 33.438 - return = dev.rate - return -} - -dev.young = function(temperature) -{ - n12 <- -0.3728 * temperature + 14.68 - n23 <- -0.6119 * temperature + 25.249 - dev.rate = mean(n12 + n23) - return = dev.rate - return -} - -dev.old = function(temperature) -{ - n34 <- -0.6119 * temperature + 17.602 - n45 <- -0.4408 * temperature + 19.036 - dev.rate = mean(n34 + n45) - return = dev.rate - return -} - -dev.emerg = function(temperature) -{ - emerg.rate <- -0.5332 * temperature + 24.147 - return = emerg.rate - return -} - -mortality.egg = function(temperature) -{ - if (temperature < 12.7) { - mort.prob = 0.8 - } - else { - mort.prob = 0.8 - temperature / 40.0 - if (mort.prob < 0) { - mort.prob = 0.01 - } - } - return = mort.prob - return -} - -mortality.nymph = function(temperature) -{ - if (temperature < 12.7) { - mort.prob = 0.03 - } - else { - mort.prob = temperature * 0.0008 + 0.03 - } - return = mort.prob - return -} - -mortality.adult = function(temperature) -{ - if (temperature < 12.7) { - mort.prob = 0.002 - } - else { - mort.prob = temperature * 0.0005 + 0.02 - } - return = mort.prob - return -} - -# Read in the input temperature datafile into a Data Frame object. -# The input data currently must have 6 columns: -# LATITUDE, LONGITUDE, DATE, DOY, TMIN, TMAX -temperature_data <- read.csv(file=opt$input, header=T, strip.white=TRUE, sep=",") -start_date <- temperature_data[1, 3] -end_date <- temperature_data[opt$num_days, 3] -latitude <- temperature_data[1, 1] -daylight_length_vector <- get_daylight_length(latitude, temperature_data, opt$num_days) - -cat("Number of days: ", opt$num_days, "\n") - -# Initialize matrix for results from all replications. -S0.rep <- S1.rep <- S2.rep <- S3.rep <- S4.rep <- S5.rep <- matrix(rep(0, opt$num_days * opt$replications), ncol = opt$replications) -newborn.rep <- death.rep <- adult.rep <- pop.rep <- g0.rep <- g1.rep <- g2.rep <- g0a.rep <- g1a.rep <- g2a.rep <- matrix(rep(0, opt$num_days * opt$replications), ncol=opt$replications) - -# loop through replications -for (N.rep in 1:opt$replications) { - # During each replication start with 1000 individuals. - # TODO: user definable as well? - n <- 1000 - # Generation, Stage, DD, T, Diapause. - vec.ini <- c(0, 3, 0, 0, 0) - # Overwintering, previttelogenic, DD=0, T=0, no-diapause. - vec.mat <- rep(vec.ini, n) - # Complete matrix for the population. - vec.mat <- base::t(matrix(vec.mat, nrow=5)) - # Time series of population size. - tot.pop <- NULL - gen0.pop <- rep(0, opt$num_days) - gen1.pop <- rep(0, opt$num_days) - gen2.pop <- rep(0, opt$num_days) - S0 <- S1 <- S2 <- S3 <- S4 <- S5 <- rep(0, opt$num_days) - g0.adult <- g1.adult <- g2.adult <- rep(0, opt$num_days) - N.newborn <- N.death <- N.adult <- rep(0, opt$num_days) - dd.day <- rep(0, opt$num_days) - - # All the days included in the input temperature dataset. - for (row in 1:opt$num_days) { - # Get the integer day of the year for the current row. - doy <- temperature_data[row, 4] - # Photoperiod in the day. - photoperiod <- daylight_length_vector[row] - temp.profile <- get_temperature_at_hour(latitude, temperature_data, daylight_length_vector, row, opt$num_days) - mean.temp <- temp.profile[1] - dd.temp <- temp.profile[2] - dd.day[row] <- dd.temp - # Trash bin for death. - death.vec <- NULL - # Newborn. - birth.vec <- NULL - - # All individuals. - for (i in 1:n) { - # Find individual record. - vec.ind <- vec.mat[i,] - # First of all, still alive? - # Adjustment for late season mortality rate. - if (latitude < 40.0) { - post.mort <- 1 - day.kill <- 300 - } - else { - post.mort <- 2 - day.kill <- 250 - } - if (vec.ind[2] == 0) { - # Egg. - death.prob = opt$egg_mort * mortality.egg(mean.temp) - } - else if (vec.ind[2] == 1 | vec.ind[2] == 2) { - death.prob = opt$nymph_mort * mortality.nymph(mean.temp) - } - else if (vec.ind[2] == 3 | vec.ind[2] == 4 | vec.ind[2] == 5) { - # For adult. - if (doy < day.kill) { - death.prob = opt$adult_mort * mortality.adult(mean.temp) - } - else { - # Increase adult mortality after fall equinox. - death.prob = opt$adult_mort * post.mort * mortality.adult(mean.temp) - } - } - # (or dependent on temperature and life stage?) - u.d <- runif(1) - if (u.d < death.prob) { - death.vec <- c(death.vec, i) - } - else { - # Aggregrate index of dead bug. - # Event 1 end of diapause. - if (vec.ind[1] == 0 && vec.ind[2] == 3) { - # Overwintering adult (previttelogenic). - if (photoperiod > opt$photoperiod && vec.ind[3] > 68 && doy < 180) { - # Add 68C to become fully reproductively matured. - # Transfer to vittelogenic. - vec.ind <- c(0, 4, 0, 0, 0) - vec.mat[i,] <- vec.ind - } - else { - # Add to dd. - vec.ind[3] <- vec.ind[3] + dd.temp - # Add 1 day in current stage. - vec.ind[4] <- vec.ind[4] + 1 - vec.mat[i,] <- vec.ind - } - } - if (vec.ind[1] != 0 && vec.ind[2] == 3) { - # Not overwintering adult (previttelogenic). - current.gen <- vec.ind[1] - if (vec.ind[3] > 68) { - # Add 68C to become fully reproductively matured. - # Transfer to vittelogenic. - vec.ind <- c(current.gen, 4, 0, 0, 0) - vec.mat[i,] <- vec.ind - } - else { - # Add to dd. - vec.ind[3] <- vec.ind[3] + dd.temp - # Add 1 day in current stage. - vec.ind[4] <- vec.ind[4] + 1 - vec.mat[i,] <- vec.ind - } - } - - # Event 2 oviposition -- where population dynamics comes from. - if (vec.ind[2] == 4 && vec.ind[1] == 0 && mean.temp > 10) { - # Vittelogenic stage, overwintering generation. - if (vec.ind[4] == 0) { - # Just turned in vittelogenic stage. - n.birth=round(runif(1, 2 + opt$min_clutch_size, 8 + opt$max_clutch_size)) - } - else { - # Daily probability of birth. - p.birth = opt$oviposition * 0.01 - u1 <- runif(1) - if (u1 < p.birth) { - n.birth=round(runif(1, 2, 8)) - } - } - # Add to dd. - vec.ind[3] <- vec.ind[3] + dd.temp - # Add 1 day in current stage. - vec.ind[4] <- vec.ind[4] + 1 - vec.mat[i,] <- vec.ind - if (n.birth > 0) { - # Add new birth -- might be in different generations. - new.gen <- vec.ind[1] + 1 - # Egg profile. - new.ind <- c(new.gen, 0, 0, 0, 0) - new.vec <- rep(new.ind, n.birth) - # Update batch of egg profile. - new.vec <- t(matrix(new.vec, nrow=5)) - # Group with total eggs laid in that day. - birth.vec <- rbind(birth.vec, new.vec) - } - } - - # Event 2 oviposition -- for gen 1. - if (vec.ind[2] == 4 && vec.ind[1] == 1 && mean.temp > 12.5 && doy < 222) { - # Vittelogenic stage, 1st generation - if (vec.ind[4] == 0) { - # Just turned in vittelogenic stage. - n.birth=round(runif(1, 2 + opt$min_clutch_size, 8 + opt$max_clutch_size)) - } - else { - # Daily probability of birth. - p.birth = opt$oviposition * 0.01 - u1 <- runif(1) - if (u1 < p.birth) { - n.birth = round(runif(1, 2, 8)) - } - } - # Add to dd. - vec.ind[3] <- vec.ind[3] + dd.temp - # Add 1 day in current stage. - vec.ind[4] <- vec.ind[4] + 1 - vec.mat[i,] <- vec.ind - if (n.birth > 0) { - # Add new birth -- might be in different generations. - new.gen <- vec.ind[1] + 1 - # Egg profile. - new.ind <- c(new.gen, 0, 0, 0, 0) - new.vec <- rep(new.ind, n.birth) - # Update batch of egg profile. - new.vec <- t(matrix(new.vec, nrow=5)) - # Group with total eggs laid in that day. - birth.vec <- rbind(birth.vec, new.vec) - } - } - - # Event 3 development (with diapause determination). - # Event 3.1 egg development to young nymph (vec.ind[2]=0 -> egg). - if (vec.ind[2] == 0) { - # Egg stage. - # Add to dd. - vec.ind[3] <- vec.ind[3] + dd.temp - if (vec.ind[3] >= (68 + opt$young_nymph_accum)) { - # From egg to young nymph, DD requirement met. - current.gen <- vec.ind[1] - # Transfer to young nymph stage. - vec.ind <- c(current.gen, 1, 0, 0, 0) - } - else { - # Add 1 day in current stage. - vec.ind[4] <- vec.ind[4] + 1 - } - vec.mat[i,] <- vec.ind - } - - # Event 3.2 young nymph to old nymph (vec.ind[2]=1 -> young nymph: determines diapause). - if (vec.ind[2] == 1) { - # young nymph stage. - # add to dd. - vec.ind[3] <- vec.ind[3] + dd.temp - if (vec.ind[3] >= (250 + opt$old_nymph_accum)) { - # From young to old nymph, dd requirement met. - current.gen <- vec.ind[1] - # Transfer to old nym stage. - vec.ind <- c(current.gen, 2, 0, 0, 0) - if (photoperiod < opt$photoperiod && doy > 180) { - vec.ind[5] <- 1 - } # Prepare for diapausing. - } - else { - # Add 1 day in current stage. - vec.ind[4] <- vec.ind[4] + 1 - } - vec.mat[i,] <- vec.ind - } - - # Event 3.3 old nymph to adult: previttelogenic or diapausing? - if (vec.ind[2] == 2) { - # Old nymph stage. - # add to dd. - vec.ind[3] <- vec.ind[3] + dd.temp - if (vec.ind[3] >= (200 + opt$adult_accum)) { - # From old to adult, dd requirement met. - current.gen <- vec.ind[1] - if (vec.ind[5] == 0) { - # Non-diapausing adult -- previttelogenic. - vec.ind <- c(current.gen, 3, 0, 0, 0) - } - else { - # Diapausing. - vec.ind <- c(current.gen, 5, 0, 0, 1) - } - } - else { - # Add 1 day in current stage. - vec.ind[4] <- vec.ind[4] + 1 - } - vec.mat[i,] <- vec.ind - } - - # Event 4 growing of diapausing adult (unimportant, but still necessary). - if (vec.ind[2] == 5) { - vec.ind[3] <- vec.ind[3] + dd.temp - vec.ind[4] <- vec.ind[4] + 1 - vec.mat[i,] <- vec.ind - } - } # Else if it is still alive. - } # End of the individual bug loop. - - # Find how many died. - n.death <- length(death.vec) - if (n.death > 0) { - vec.mat <- vec.mat[-death.vec, ] - } - # Remove record of dead. - # Find how many new born. - n.newborn <- length(birth.vec[,1]) - vec.mat <- rbind(vec.mat, birth.vec) - # Update population size for the next day. - n <- n - n.death + n.newborn - - # Aggregate results by day. - tot.pop <- c(tot.pop, n) - # Egg. - s0 <- sum(vec.mat[,2] == 0) - # Young nymph. - s1 <- sum(vec.mat[,2] == 1) - # Old nymph. - s2 <- sum(vec.mat[,2] == 2) - # Previtellogenic. - s3 <- sum(vec.mat[,2] == 3) - # Vitellogenic. - s4 <- sum(vec.mat[,2] == 4) - # Diapausing. - s5 <- sum(vec.mat[,2] == 5) - # Overwintering adult. - gen0 <- sum(vec.mat[,1] == 0) - # First generation. - gen1 <- sum(vec.mat[,1] == 1) - # Second generation. - gen2 <- sum(vec.mat[,1] == 2) - # Sum of all adults. - n.adult <- sum(vec.mat[,2] == 3) + sum(vec.mat[,2] == 4) + sum(vec.mat[,2] == 5) - - # Generation 0 pop size. - gen0.pop[row] <- gen0 - gen1.pop[row] <- gen1 - gen2.pop[row] <- gen2 - - S0[row] <- s0 - S1[row] <- s1 - S2[row] <- s2 - S3[row] <- s3 - S4[row] <- s4 - S5[row] <- s5 - - g0.adult[row] <- sum(vec.mat[,1] == 0) - g1.adult[row] <- 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)) - g2.adult[row] <- 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)) - - N.newborn[row] <- n.newborn - N.death[row] <- n.death - N.adult[row] <- n.adult - } # end of days specified in the input temperature data - - dd.cum <- cumsum(dd.day) - - # Collect all the outputs. - S0.rep[,N.rep] <- S0 - S1.rep[,N.rep] <- S1 - S2.rep[,N.rep] <- S2 - S3.rep[,N.rep] <- S3 - S4.rep[,N.rep] <- S4 - S5.rep[,N.rep] <- S5 - newborn.rep[,N.rep] <- N.newborn - death.rep[,N.rep] <- N.death - adult.rep[,N.rep] <- N.adult - pop.rep[,N.rep] <- tot.pop - g0.rep[,N.rep] <- gen0.pop - g1.rep[,N.rep] <- gen1.pop - g2.rep[,N.rep] <- gen2.pop - g0a.rep[,N.rep] <- g0.adult - g1a.rep[,N.rep] <- g1.adult - g2a.rep[,N.rep] <- g2.adult -} - -# Data analysis and visualization can currently -# plot only within a single calendar year. -# TODO: enhance this to accomodate multiple calendar years. -n.yr <- 1 -day.all <- c(1:opt$num_days * n.yr) - -# mean value for adults -sa <- apply((S3.rep + S4.rep + S5.rep), 1, mean) -# mean value for nymphs -sn <- apply((S1.rep + S2.rep), 1,mean) -# mean value for eggs -se <- apply(S0.rep, 1, mean) -# mean value for P -g0 <- apply(g0.rep, 1, mean) -# mean value for F1 -g1 <- apply(g1.rep, 1, mean) -# mean value for F2 -g2 <- apply(g2.rep, 1, mean) -# mean value for P adult -g0a <- apply(g0a.rep, 1, mean) -# mean value for F1 adult -g1a <- apply(g1a.rep, 1, mean) -# mean value for F2 adult -g2a <- apply(g2a.rep, 1, mean) - -# SE for adults -sa.se <- apply((S3.rep + S4.rep + S5.rep), 1, sd) / sqrt(opt$replications) -# SE for nymphs -sn.se <- apply((S1.rep + S2.rep) / sqrt(opt$replications), 1, sd) -# SE for eggs -se.se <- apply(S0.rep, 1, sd) / sqrt(opt$replications) -# SE value for P -g0.se <- apply(g0.rep, 1, sd) / sqrt(opt$replications) -# SE for F1 -g1.se <- apply(g1.rep, 1, sd) / sqrt(opt$replications) -# SE for F2 -g2.se <- apply(g2.rep, 1, sd) / sqrt(opt$replications) -# SE for P adult -g0a.se <- apply(g0a.rep, 1, sd) / sqrt(opt$replications) -# SE for F1 adult -g1a.se <- apply(g1a.rep, 1, sd) / sqrt(opt$replications) -# SE for F2 adult -g2a.se <- apply(g2a.rep, 1, sd) / sqrt(opt$replications) - -dev.new(width=20, height=30) - -# Start PDF device driver to save charts to output. -pdf(file=opt$output, width=20, height=30, bg="white") - -par(mar = c(5, 6, 4, 4), mfrow=c(3, 1)) - -# Subfigure 1: population size by life stage -title <- paste("BSMB total population by life stage :", opt$location, ": Lat:", latitude, ":", start_date, "to", end_date, sep=" ") -plot(day.all, sa, main=title, type="l", ylim=c(0, max(se + se.se, sn + sn.se, sa + sa.se)), axes=F, lwd=2, xlab="", ylab="", cex=3, cex.lab=3, cex.axis=3, cex.main=3) -# Young and old nymphs. -lines(day.all, sn, lwd=2, lty=1, col=2) -# Eggs -lines(day.all, se, lwd=2, lty=1, col=4) -axis(1, at=c(1:12) * 30 - 15, cex.axis=3, labels=c("Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", "Oct", "Nov", "Dec")) -axis(2, cex.axis=3) -leg.text <- c("Egg", "Nymph", "Adult") -legend("topleft", leg.text, lty=c(1, 1, 1), col=c(4, 2, 1), cex=3) -if (opt$se_plot == 1) { - # Add SE lines to plot - # SE for adults - lines (day.all, sa + sa.se, lty=2) - lines (day.all, sa - sa.se, lty=2) - # SE for nymphs - lines (day.all, sn + sn.se, col=2, lty=2) - lines (day.all, sn - sn.se, col=2, lty=2) - # SE for eggs - lines (day.all, se + se.se, col=4, lty=2) - lines (day.all, se - se.se, col=4, lty=2) -} - -# Subfigure 2: population size by generation -title <- paste("BSMB total population by generation :", opt$location, ": Lat:", latitude, ":", start_date, "to", end_date, sep=" ") -plot(day.all, g0, main=title, type="l", ylim=c(0, max(g2)), axes=F, lwd=2, xlab="", ylab="", cex=3, cex.lab=3, cex.axis=3, cex.main=3) -lines(day.all, g1, lwd = 2, lty = 1, col=2) -lines(day.all, g2, lwd = 2, lty = 1, col=4) -axis(1, at=c(1:12) * 30 - 15, cex.axis=3, labels = c("Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", "Oct", "Nov", "Dec")) -axis(2, cex.axis=3) -leg.text <- c("P", "F1", "F2") -legend("topleft", leg.text, lty=c(1, 1, 1), col=c(1, 2, 4), cex=3) -if (opt$se_plot == 1) { - # Add SE lines to plot - # SE for adults - lines (day.all, g0+g0.se, lty=2) - lines (day.all, g0-g0.se, lty=2) - # SE for nymphs - lines (day.all, g1+g1.se, col=2, lty=2) - lines (day.all, g1-g1.se, col=2, lty=2) - # SE for eggs - lines (day.all, g2+g2.se, col=4, lty=2) - lines (day.all, g2-g2.se, col=4, lty=2) -} - -# Subfigure 3: adult population size by generation -title <- paste("BSMB adult population by generation :", opt$location, ": Lat:", latitude, ":", start_date, "to", end_date, sep=" ") -plot(day.all, g0a, ylim=c(0, max(g2a) + 100), main=title, type="l", axes=F, lwd=2, xlab="", ylab="", cex=3, cex.lab=3, cex.axis=3, cex.main=3) -lines(day.all, g1a, lwd = 2, lty = 1, col=2) -lines(day.all, g2a, lwd = 2, lty = 1, col=4) -axis(1, at=c(1:12) * 30 - 15, cex.axis=3, labels = c("Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", "Oct", "Nov", "Dec")) -axis(2, cex.axis=3) -leg.text <- c("P", "F1", "F2") -legend("topleft", leg.text, lty=c(1, 1, 1), col=c(1, 2, 4), cex=3) -if (opt$se_plot == 1) { - # Add SE lines to plot - # SE for adults - lines (day.all, g0a+g0a.se, lty=2) - lines (day.all, g0a-g0a.se, lty=2) - # SE for nymphs - lines (day.all, g1a+g1a.se, col=2, lty=2) - lines (day.all, g1a-g1a.se, col=2, lty=2) - # SE for eggs - lines (day.all, g2a+g2a.se, col=4, lty=2) - lines (day.all, g2a-g2a.se, col=4, lty=2) -} - -# Turn off device driver to flush output. -dev.off() +#!/usr/bin/env Rscript + +suppressPackageStartupMessages(library("optparse")) + +option_list <- list( + make_option(c("-a", "--adult_mort"), action="store", dest="adult_mort", type="integer", help="Adjustment rate for adult mortality"), + make_option(c("-b", "--adult_accum"), action="store", dest="adult_accum", type="integer", help="Adjustment of DD accumulation (old nymph->adult)"), + make_option(c("-c", "--egg_mort"), action="store", dest="egg_mort", type="integer", help="Adjustment rate for egg mortality"), + make_option(c("-e", "--location"), action="store", dest="location", help="Selected location"), + make_option(c("-f", "--min_clutch_size"), action="store", dest="min_clutch_size", type="integer", help="Adjustment of minimum clutch size"), + make_option(c("-i", "--max_clutch_size"), action="store", dest="max_clutch_size", type="integer", help="Adjustment of maximum clutch size"), + make_option(c("-j", "--nymph_mort"), action="store", dest="nymph_mort", type="integer", help="Adjustment rate for nymph mortality"), + make_option(c("-k", "--old_nymph_accum"), action="store", dest="old_nymph_accum", type="integer", help="Adjustment of DD accumulation (young nymph->old nymph)"), + make_option(c("-n", "--num_days"), action="store", dest="num_days", type="integer", help="Total number of days in the temperature dataset"), + make_option(c("-o", "--output"), action="store", dest="output", help="Output dataset"), + make_option(c("-p", "--oviposition"), action="store", dest="oviposition", type="integer", help="Adjustment for oviposition rate"), + make_option(c("-q", "--photoperiod"), action="store", dest="photoperiod", type="double", help="Critical photoperiod for diapause induction/termination"), + make_option(c("-s", "--replications"), action="store", dest="replications", type="integer", help="Number of replications"), + make_option(c("-t", "--se_plot"), action="store", dest="se_plot", help="Plot SE"), + make_option(c("-v", "--input"), action="store", dest="input", help="Temperature data for selected location"), + make_option(c("-y", "--young_nymph_accum"), action="store", dest="young_nymph_accum", type="integer", help="Adjustment of DD accumulation (egg->young nymph)"), + make_option(c("-x", "--insect"), action="store", dest="insect", help="Insect name") +) + +parser <- OptionParser(usage="%prog [options] file", option_list=option_list) +args <- parse_args(parser, positional_arguments=TRUE) +opt <- args$options + +parse_input_data = function(input_file, num_rows) { + # Read in the input temperature datafile into a data frame. + temperature_data_frame <- read.csv(file=input_file, header=T, strip.white=TRUE, sep=",") + num_columns <- dim(temperature_data_frame)[2] + if (num_columns == 6) { + # The input data has the following 6 columns: + # LATITUDE, LONGITUDE, DATE, DOY, TMIN, TMAX + # Set the column names for access when adding daylight length.. + colnames(temperature_data_frame) <- c("LATITUDE","LONGITUDE", "DATE", "DOY", "TMIN", "TMAX") + # Add a column containing the daylight length for each day. + temperature_data_frame <- add_daylight_length(temperature_data_frame, num_columns, num_rows) + # Reset the column names with the additional column for later access. + colnames(temperature_data_frame) <- c("LATITUDE","LONGITUDE", "DATE", "DOY", "TMIN", "TMAX", "DAYLEN") + } + return(temperature_data_frame) +} + +add_daylight_length = function(temperature_data_frame, num_columns, num_rows) { + # Return a vector of daylight length (photoperido profile) for + # the number of days specified in the input temperature data + # (from Forsythe 1995). + p = 0.8333 + latitude <- temperature_data_frame$LATITUDE[1] + daylight_length_vector <- NULL + for (i in 1:num_rows) { + # Get the day of the year from the current row + # of the temperature data for computation. + doy <- temperature_data_frame$DOY[i] + theta <- 0.2163108 + 2 * atan(0.9671396 * tan(0.00860 * (doy - 186))) + phi <- asin(0.39795 * cos(theta)) + # Compute the length of daylight for the day of the year. + daylight_length_vector[i] <- 24 - (24 / pi * acos((sin(p * pi / 180) + sin(latitude * pi / 180) * sin(phi)) / (cos(latitude * pi / 180) * cos(phi)))) + } + # Append daylight_length_vector as a new column to temperature_data_frame. + temperature_data_frame[, num_columns+1] <- daylight_length_vector + return(temperature_data_frame) +} + +get_temperature_at_hour = function(latitude, temperature_data_frame, row, num_days) { + # Base development threshold for Brown Marmolated Stink Bug + # insect phenology model. + # TODO: Pass insect on the command line to accomodate more + # the just the Brown Marmolated Stink Bub. + threshold <- 14.17 + # Minimum temperature for current row. + dnp <- temperature_data_frame$TMIN[row] + # Maximum temperature for current row. + dxp <- temperature_data_frame$TMAX[row] + # Mean temperature for current row. + dmean <- 0.5 * (dnp + dxp) + # Initialize degree day accumulation + dd <- 0 + if (dxp < threshold) { + dd <- 0 + } + else { + # Initialize hourly temperature. + T <- NULL + # Initialize degree hour vector. + dh <- NULL + # Daylight length for current row. + y <- temperature_data_frame$DAYLEN[row] + # Darkness length. + z <- 24 - y + # Lag coefficient. + a <- 1.86 + # Darkness coefficient. + b <- 2.20 + # Sunrise time. + risetime <- 12 - y / 2 + # Sunset time. + settime <- 12 + y / 2 + ts <- (dxp - dnp) * sin(pi * (settime - 5) / (y + 2 * a)) + dnp + for (i in 1:24) { + if (i > risetime && i < settime) { + # Number of hours after Tmin until sunset. + m <- i - 5 + T[i] = (dxp - dnp) * sin(pi * m / (y + 2 * a)) + dnp + if (T[i] < 8.4) { + dh[i] <- 0 + } + else { + dh[i] <- T[i] - 8.4 + } + } + else if (i > settime) { + n <- i - settime + T[i] = dnp + (ts - dnp) * exp( - b * n / z) + if (T[i] < 8.4) { + dh[i] <- 0 + } + else { + dh[i] <- T[i] - 8.4 + } + } + else { + n <- i + 24 - settime + T[i]=dnp + (ts - dnp) * exp( - b * n / z) + if (T[i] < 8.4) { + dh[i] <- 0 + } + else { + dh[i] <- T[i] - 8.4 + } + } + } + dd <- sum(dh) / 24 + } + return(c(dmean, dd)) +} + +dev.egg = function(temperature) { + dev.rate= -0.9843 * temperature + 33.438 + return(dev.rate) +} + +dev.young = function(temperature) { + n12 <- -0.3728 * temperature + 14.68 + n23 <- -0.6119 * temperature + 25.249 + dev.rate = mean(n12 + n23) + return(dev.rate) +} + +dev.old = function(temperature) { + n34 <- -0.6119 * temperature + 17.602 + n45 <- -0.4408 * temperature + 19.036 + dev.rate = mean(n34 + n45) + return(dev.rate) +} + +dev.emerg = function(temperature) { + emerg.rate <- -0.5332 * temperature + 24.147 + return(emerg.rate) +} + +mortality.egg = function(temperature) { + if (temperature < 12.7) { + mort.prob = 0.8 + } + else { + mort.prob = 0.8 - temperature / 40.0 + if (mort.prob < 0) { + mort.prob = 0.01 + } + } + return(mort.prob) +} + +mortality.nymph = function(temperature) { + if (temperature < 12.7) { + mort.prob = 0.03 + } + else { + mort.prob = temperature * 0.0008 + 0.03 + } + return(mort.prob) +} + +mortality.adult = function(temperature) { + if (temperature < 12.7) { + mort.prob = 0.002 + } + else { + mort.prob = temperature * 0.0005 + 0.02 + } + return(mort.prob) +} + +temperature_data_frame <- parse_input_data(opt$input, opt$num_days) +# All latitude values are the same, +# so get the value from the first row. +latitude <- temperature_data_frame$LATITUDE[1] + +cat("Number of days: ", opt$num_days, "\n") + +# Initialize matrix for results from all replications. +S0.rep <- S1.rep <- S2.rep <- S3.rep <- S4.rep <- S5.rep <- matrix(rep(0, opt$num_days * opt$replications), ncol = opt$replications) +newborn.rep <- death.rep <- adult.rep <- pop.rep <- g0.rep <- g1.rep <- g2.rep <- g0a.rep <- g1a.rep <- g2a.rep <- matrix(rep(0, opt$num_days * opt$replications), ncol=opt$replications) + +# Loop through replications. +for (N.rep in 1:opt$replications) { + # During each replication start with 1000 individuals. + # TODO: user definable as well? + n <- 1000 + # Generation, Stage, DD, T, Diapause. + vec.ini <- c(0, 3, 0, 0, 0) + # Overwintering, previttelogenic, DD=0, T=0, no-diapause. + vec.mat <- rep(vec.ini, n) + # Complete matrix for the population. + vec.mat <- base::t(matrix(vec.mat, nrow=5)) + # Time series of population size. + tot.pop <- NULL + gen0.pop <- rep(0, opt$num_days) + gen1.pop <- rep(0, opt$num_days) + gen2.pop <- rep(0, opt$num_days) + S0 <- S1 <- S2 <- S3 <- S4 <- S5 <- rep(0, opt$num_days) + g0.adult <- g1.adult <- g2.adult <- rep(0, opt$num_days) + N.newborn <- N.death <- N.adult <- rep(0, opt$num_days) + dd.day <- rep(0, opt$num_days) + # All the days included in the input temperature dataset. + for (row in 1:opt$num_days) { + # Get the integer day of the year for the current row. + doy <- temperature_data_frame$DOY[row] + # Photoperiod in the day. + photoperiod <- temperature_data_frame$DAYLEN[row] + temp.profile <- get_temperature_at_hour(latitude, temperature_data_frame, row, opt$num_days) + mean.temp <- temp.profile[1] + dd.temp <- temp.profile[2] + dd.day[row] <- dd.temp + # Trash bin for death. + death.vec <- NULL + # Newborn. + birth.vec <- NULL + # All individuals. + for (i in 1:n) { + # Find individual record. + vec.ind <- vec.mat[i,] + # First of all, still alive? + # Adjustment for late season mortality rate. + if (latitude < 40.0) { + post.mort <- 1 + day.kill <- 300 + } + else { + post.mort <- 2 + day.kill <- 250 + } + if (vec.ind[2] == 0) { + # Egg. + death.prob = opt$egg_mort * mortality.egg(mean.temp) + } + else if (vec.ind[2] == 1 | vec.ind[2] == 2) { + death.prob = opt$nymph_mort * mortality.nymph(mean.temp) + } + else if (vec.ind[2] == 3 | vec.ind[2] == 4 | vec.ind[2] == 5) { + # For adult. + if (doy < day.kill) { + death.prob = opt$adult_mort * mortality.adult(mean.temp) + } + else { + # Increase adult mortality after fall equinox. + death.prob = opt$adult_mort * post.mort * mortality.adult(mean.temp) + } + } + # (or dependent on temperature and life stage?) + u.d <- runif(1) + if (u.d < death.prob) { + death.vec <- c(death.vec, i) + } + else { + # Aggregrate index of dead bug. + # Event 1 end of diapause. + if (vec.ind[1] == 0 && vec.ind[2] == 3) { + # Overwintering adult (previttelogenic). + if (photoperiod > opt$photoperiod && vec.ind[3] > 68 && doy < 180) { + # Add 68C to become fully reproductively matured. + # Transfer to vittelogenic. + vec.ind <- c(0, 4, 0, 0, 0) + vec.mat[i,] <- vec.ind + } + else { + # Add to dd. + vec.ind[3] <- vec.ind[3] + dd.temp + # Add 1 day in current stage. + vec.ind[4] <- vec.ind[4] + 1 + vec.mat[i,] <- vec.ind + } + } + if (vec.ind[1] != 0 && vec.ind[2] == 3) { + # Not overwintering adult (previttelogenic). + current.gen <- vec.ind[1] + if (vec.ind[3] > 68) { + # Add 68C to become fully reproductively matured. + # Transfer to vittelogenic. + vec.ind <- c(current.gen, 4, 0, 0, 0) + vec.mat[i,] <- vec.ind + } + else { + # Add to dd. + vec.ind[3] <- vec.ind[3] + dd.temp + # Add 1 day in current stage. + vec.ind[4] <- vec.ind[4] + 1 + vec.mat[i,] <- vec.ind + } + } + # Event 2 oviposition -- where population dynamics comes from. + if (vec.ind[2] == 4 && vec.ind[1] == 0 && mean.temp > 10) { + # Vittelogenic stage, overwintering generation. + if (vec.ind[4] == 0) { + # Just turned in vittelogenic stage. + n.birth=round(runif(1, 2 + opt$min_clutch_size, 8 + opt$max_clutch_size)) + } + else { + # Daily probability of birth. + p.birth = opt$oviposition * 0.01 + u1 <- runif(1) + if (u1 < p.birth) { + n.birth=round(runif(1, 2, 8)) + } + } + # Add to dd. + vec.ind[3] <- vec.ind[3] + dd.temp + # Add 1 day in current stage. + vec.ind[4] <- vec.ind[4] + 1 + vec.mat[i,] <- vec.ind + if (n.birth > 0) { + # Add new birth -- might be in different generations. + new.gen <- vec.ind[1] + 1 + # Egg profile. + new.ind <- c(new.gen, 0, 0, 0, 0) + new.vec <- rep(new.ind, n.birth) + # Update batch of egg profile. + new.vec <- t(matrix(new.vec, nrow=5)) + # Group with total eggs laid in that day. + birth.vec <- rbind(birth.vec, new.vec) + } + } + # Event 2 oviposition -- for generation 1. + if (vec.ind[2] == 4 && vec.ind[1] == 1 && mean.temp > 12.5 && doy < 222) { + # Vittelogenic stage, 1st generation + if (vec.ind[4] == 0) { + # Just turned in vittelogenic stage. + n.birth=round(runif(1, 2 + opt$min_clutch_size, 8 + opt$max_clutch_size)) + } + else { + # Daily probability of birth. + p.birth = opt$oviposition * 0.01 + u1 <- runif(1) + if (u1 < p.birth) { + n.birth = round(runif(1, 2, 8)) + } + } + # Add to dd. + vec.ind[3] <- vec.ind[3] + dd.temp + # Add 1 day in current stage. + vec.ind[4] <- vec.ind[4] + 1 + vec.mat[i,] <- vec.ind + if (n.birth > 0) { + # Add new birth -- might be in different generations. + new.gen <- vec.ind[1] + 1 + # Egg profile. + new.ind <- c(new.gen, 0, 0, 0, 0) + new.vec <- rep(new.ind, n.birth) + # Update batch of egg profile. + new.vec <- t(matrix(new.vec, nrow=5)) + # Group with total eggs laid in that day. + birth.vec <- rbind(birth.vec, new.vec) + } + } + # Event 3 development (with diapause determination). + # Event 3.1 egg development to young nymph (vec.ind[2]=0 -> egg). + if (vec.ind[2] == 0) { + # Egg stage. + # Add to dd. + vec.ind[3] <- vec.ind[3] + dd.temp + if (vec.ind[3] >= (68 + opt$young_nymph_accum)) { + # From egg to young nymph, DD requirement met. + current.gen <- vec.ind[1] + # Transfer to young nymph stage. + vec.ind <- c(current.gen, 1, 0, 0, 0) + } + else { + # Add 1 day in current stage. + vec.ind[4] <- vec.ind[4] + 1 + } + vec.mat[i,] <- vec.ind + } + # Event 3.2 young nymph to old nymph (vec.ind[2]=1 -> young nymph: determines diapause). + if (vec.ind[2] == 1) { + # young nymph stage. + # add to dd. + vec.ind[3] <- vec.ind[3] + dd.temp + if (vec.ind[3] >= (250 + opt$old_nymph_accum)) { + # From young to old nymph, dd requirement met. + current.gen <- vec.ind[1] + # Transfer to old nym stage. + vec.ind <- c(current.gen, 2, 0, 0, 0) + if (photoperiod < opt$photoperiod && doy > 180) { + vec.ind[5] <- 1 + } # Prepare for diapausing. + } + else { + # Add 1 day in current stage. + vec.ind[4] <- vec.ind[4] + 1 + } + vec.mat[i,] <- vec.ind + } + # Event 3.3 old nymph to adult: previttelogenic or diapausing? + if (vec.ind[2] == 2) { + # Old nymph stage. + # add to dd. + vec.ind[3] <- vec.ind[3] + dd.temp + if (vec.ind[3] >= (200 + opt$adult_accum)) { + # From old to adult, dd requirement met. + current.gen <- vec.ind[1] + if (vec.ind[5] == 0) { + # Non-diapausing adult -- previttelogenic. + vec.ind <- c(current.gen, 3, 0, 0, 0) + } + else { + # Diapausing. + vec.ind <- c(current.gen, 5, 0, 0, 1) + } + } + else { + # Add 1 day in current stage. + vec.ind[4] <- vec.ind[4] + 1 + } + vec.mat[i,] <- vec.ind + } + # Event 4 growing of diapausing adult (unimportant, but still necessary). + if (vec.ind[2] == 5) { + vec.ind[3] <- vec.ind[3] + dd.temp + vec.ind[4] <- vec.ind[4] + 1 + vec.mat[i,] <- vec.ind + } + } # Else if it is still alive. + } # End of the individual bug loop. + # Find how many died. + n.death <- length(death.vec) + if (n.death > 0) { + vec.mat <- vec.mat[-death.vec, ] + } + # Remove record of dead. + # Find how many new born. + n.newborn <- length(birth.vec[,1]) + vec.mat <- rbind(vec.mat, birth.vec) + # Update population size for the next day. + n <- n - n.death + n.newborn + + # Aggregate results by day. + tot.pop <- c(tot.pop, n) + # Egg. + s0 <- sum(vec.mat[,2] == 0) + # Young nymph. + s1 <- sum(vec.mat[,2] == 1) + # Old nymph. + s2 <- sum(vec.mat[,2] == 2) + # Previtellogenic. + s3 <- sum(vec.mat[,2] == 3) + # Vitellogenic. + s4 <- sum(vec.mat[,2] == 4) + # Diapausing. + s5 <- sum(vec.mat[,2] == 5) + # Overwintering adult. + gen0 <- sum(vec.mat[,1] == 0) + # First generation. + gen1 <- sum(vec.mat[,1] == 1) + # Second generation. + gen2 <- sum(vec.mat[,1] == 2) + # Sum of all adults. + n.adult <- sum(vec.mat[,2] == 3) + sum(vec.mat[,2] == 4) + sum(vec.mat[,2] == 5) + + # Generation 0 pop size. + gen0.pop[row] <- gen0 + gen1.pop[row] <- gen1 + gen2.pop[row] <- gen2 + + S0[row] <- s0 + S1[row] <- s1 + S2[row] <- s2 + S3[row] <- s3 + S4[row] <- s4 + S5[row] <- s5 + + g0.adult[row] <- sum(vec.mat[,1] == 0) + g1.adult[row] <- 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)) + g2.adult[row] <- 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)) + + N.newborn[row] <- n.newborn + N.death[row] <- n.death + N.adult[row] <- n.adult + } # end of days specified in the input temperature data + + dd.cum <- cumsum(dd.day) + + # Collect all the outputs. + S0.rep[,N.rep] <- S0 + S1.rep[,N.rep] <- S1 + S2.rep[,N.rep] <- S2 + S3.rep[,N.rep] <- S3 + S4.rep[,N.rep] <- S4 + S5.rep[,N.rep] <- S5 + newborn.rep[,N.rep] <- N.newborn + death.rep[,N.rep] <- N.death + adult.rep[,N.rep] <- N.adult + pop.rep[,N.rep] <- tot.pop + g0.rep[,N.rep] <- gen0.pop + g1.rep[,N.rep] <- gen1.pop + g2.rep[,N.rep] <- gen2.pop + g0a.rep[,N.rep] <- g0.adult + g1a.rep[,N.rep] <- g1.adult + g2a.rep[,N.rep] <- g2.adult +} + +# Data analysis and visualization can currently +# plot only within a single calendar year. +# TODO: enhance this to accomodate multiple calendar years. +start_date <- temperature_data_frame$DATE[1] +end_date <- temperature_data_frame$DATE[opt$num_days] + +n.yr <- 1 +day.all <- c(1:opt$num_days * n.yr) + +# mean value for adults +sa <- apply((S3.rep + S4.rep + S5.rep), 1, mean) +# mean value for nymphs +sn <- apply((S1.rep + S2.rep), 1,mean) +# mean value for eggs +se <- apply(S0.rep, 1, mean) +# mean value for P +g0 <- apply(g0.rep, 1, mean) +# mean value for F1 +g1 <- apply(g1.rep, 1, mean) +# mean value for F2 +g2 <- apply(g2.rep, 1, mean) +# mean value for P adult +g0a <- apply(g0a.rep, 1, mean) +# mean value for F1 adult +g1a <- apply(g1a.rep, 1, mean) +# mean value for F2 adult +g2a <- apply(g2a.rep, 1, mean) + +# SE for adults +sa.se <- apply((S3.rep + S4.rep + S5.rep), 1, sd) / sqrt(opt$replications) +# SE for nymphs +sn.se <- apply((S1.rep + S2.rep) / sqrt(opt$replications), 1, sd) +# SE for eggs +se.se <- apply(S0.rep, 1, sd) / sqrt(opt$replications) +# SE value for P +g0.se <- apply(g0.rep, 1, sd) / sqrt(opt$replications) +# SE for F1 +g1.se <- apply(g1.rep, 1, sd) / sqrt(opt$replications) +# SE for F2 +g2.se <- apply(g2.rep, 1, sd) / sqrt(opt$replications) +# SE for P adult +g0a.se <- apply(g0a.rep, 1, sd) / sqrt(opt$replications) +# SE for F1 adult +g1a.se <- apply(g1a.rep, 1, sd) / sqrt(opt$replications) +# SE for F2 adult +g2a.se <- apply(g2a.rep, 1, sd) / sqrt(opt$replications) + +dev.new(width=20, height=30) + +# Start PDF device driver to save charts to output. +pdf(file=opt$output, width=20, height=30, bg="white") + +par(mar = c(5, 6, 4, 4), mfrow=c(3, 1)) + +# Subfigure 1: population size by life stage +title <- paste(opt$insect, ": Total pop. by life stage :", opt$location, ": Lat:", latitude, ":", start_date, "-", end_date, sep=" ") +plot(day.all, sa, main=title, type="l", ylim=c(0, max(se + se.se, sn + sn.se, sa + sa.se)), axes=F, lwd=2, xlab="", ylab="", cex=3, cex.lab=3, cex.axis=3, cex.main=3) +# Young and old nymphs. +lines(day.all, sn, lwd=2, lty=1, col=2) +# Eggs +lines(day.all, se, lwd=2, lty=1, col=4) +axis(1, at=c(1:12) * 30 - 15, cex.axis=3, labels=c("Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", "Oct", "Nov", "Dec")) +axis(2, cex.axis=3) +leg.text <- c("Egg", "Nymph", "Adult") +legend("topleft", leg.text, lty=c(1, 1, 1), col=c(4, 2, 1), cex=3) +if (opt$se_plot == 1) { + # Add SE lines to plot + # SE for adults + lines (day.all, sa + sa.se, lty=2) + lines (day.all, sa - sa.se, lty=2) + # SE for nymphs + lines (day.all, sn + sn.se, col=2, lty=2) + lines (day.all, sn - sn.se, col=2, lty=2) + # SE for eggs + lines (day.all, se + se.se, col=4, lty=2) + lines (day.all, se - se.se, col=4, lty=2) +} + +# Subfigure 2: population size by generation +title <- paste(opt$insect, ": Total pop. by generation :", opt$location, ": Lat:", latitude, ":", start_date, "-", end_date, sep=" ") +plot(day.all, g0, main=title, type="l", ylim=c(0, max(g2)), axes=F, lwd=2, xlab="", ylab="", cex=3, cex.lab=3, cex.axis=3, cex.main=3) +lines(day.all, g1, lwd = 2, lty = 1, col=2) +lines(day.all, g2, lwd = 2, lty = 1, col=4) +axis(1, at=c(1:12) * 30 - 15, cex.axis=3, labels = c("Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", "Oct", "Nov", "Dec")) +axis(2, cex.axis=3) +leg.text <- c("P", "F1", "F2") +legend("topleft", leg.text, lty=c(1, 1, 1), col=c(1, 2, 4), cex=3) +if (opt$se_plot == 1) { + # Add SE lines to plot + # SE for adults + lines (day.all, g0+g0.se, lty=2) + lines (day.all, g0-g0.se, lty=2) + # SE for nymphs + lines (day.all, g1+g1.se, col=2, lty=2) + lines (day.all, g1-g1.se, col=2, lty=2) + # SE for eggs + lines (day.all, g2+g2.se, col=4, lty=2) + lines (day.all, g2-g2.se, col=4, lty=2) +} + +# Subfigure 3: adult population size by generation +title <- paste(opt$insect, ": Adult pop. by generation :", opt$location, ": Lat:", latitude, ":", start_date, "-", end_date, sep=" ") +plot(day.all, g0a, ylim=c(0, max(g2a) + 100), main=title, type="l", axes=F, lwd=2, xlab="", ylab="", cex=3, cex.lab=3, cex.axis=3, cex.main=3) +lines(day.all, g1a, lwd = 2, lty = 1, col=2) +lines(day.all, g2a, lwd = 2, lty = 1, col=4) +axis(1, at=c(1:12) * 30 - 15, cex.axis=3, labels = c("Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", "Oct", "Nov", "Dec")) +axis(2, cex.axis=3) +leg.text <- c("P", "F1", "F2") +legend("topleft", leg.text, lty=c(1, 1, 1), col=c(1, 2, 4), cex=3) +if (opt$se_plot == 1) { + # Add SE lines to plot + # SE for adults + lines (day.all, g0a+g0a.se, lty=2) + lines (day.all, g0a-g0a.se, lty=2) + # SE for nymphs + lines (day.all, g1a+g1a.se, col=2, lty=2) + lines (day.all, g1a-g1a.se, col=2, lty=2) + # SE for eggs + lines (day.all, g2a+g2a.se, col=4, lty=2) + lines (day.all, g2a-g2a.se, col=4, lty=2) +} + +# Turn off device driver to flush output. +dev.off()
--- a/insect_phenology_model.xml Mon Nov 13 12:57:46 2017 -0500 +++ b/insect_phenology_model.xml Wed Nov 22 13:22:49 2017 -0500 @@ -20,10 +20,14 @@ -s $replications -t $se_plot -v '$input' --y $young_nymph_accum]]></command> +-y $young_nymph_accum +-x '$insect']]></command> <inputs> <param name="input" type="data" format="csv" label="Temperature data" /> <param name="location" type="text" value="" optional="false" label="Location" /> + <param name="insect" type="select" label="Select insect"> + <option value="Brown Marmolated Stink Bug" selected="True">Brown Marmolated Stink Bug</option> + </param> <param name="replications" type="integer" value="10" min="1" label="Number of replications" /> <param name="photoperiod" type="float" value="13.5" min="0" label="Critical photoperiod for diapause induction/termination" /> <param name="egg_mort" type="integer" value="1" min="0" label="Adjustment rate for egg mortality" />