## import data file: daily maximum water levels/windspeed, called h
h<- as.numeric(sample (1:500,size=10000,replace=TRUE)) # example numeric array for h, replace with real data
######## min WoO requirement ################
failure <- 3
# failure= period free from inundation which needs to be exceeded for seedlings to anchor after
stranding
# this is the loop to calculate inundation free days
diff <- 0
maxdur <- array(data = NA, dim = (length(h)), dimnames = NULL)
## array for output: inundation free period
maxel <- array(data = NA, dim = (length(h)), dimnames = NULL)
## array for output: water level which inundation free period is
## calculated for
for (i in 1:paste(length(h) - 1)) {
maxdur[i] <- 0
maxel[i] <- h[i]
diff <- h[i] > h[i+1]
if (diff == TRUE) {
q=i+1
while (((h[i] > h[q])) && (q < length(h))) {
maxdur[i] <- maxdur[i] + 1
q=q+1
}
}
}
# ------------------------------------WoONa <- cbind(maxel, maxdur, deparse.level = 1)
WoO <- na.omit(WoONa) ## deletes last day for which maxdur is NA
disperse <- WoO[WoO[, 2] >= 1, ] ## selects all days where diaspore strand all WoO >= 1 day no inundation,
## all potential WoO
plot(density(disperse[, 1])) ##density of all WoO <=1 day
plot(disperse[, 1], disperse[, 2], xlab = "elevation", ylab = "WoO duration [days]")
## plots elevation against duration of WoO i.e. inundation free period all
## WoO which are defined as successful (longer than failure input)
## select all where windows occurred
defWoO <- disperse[disperse[, 2] > failure, ]
density(defWoO[, 1])
plot(density(defWoO[, 1]))
## density of all WoO which are defined successful
############# calculate P success ##########
establish <- array(data = NA, dim = length(disperse[, 1]), dimnames = NULL)
### marks for all dispersal events, if minimum duration of WoO is >
### failure threshold
for (i in 1:length(disperse[, 1])) {
dispersal <- (disperse[i, 2]) > failure
seedling <- dispersal == TRUE
if (seedling == TRUE) {
establish[i] <- 1
} else {
establish[i] <- 0
}
}
WoOfin <- cbind(establish, disperse)
### probability of survival for different elevations, P success ####
d1 <- WoOfin[WoOfin[, 1] == 1, ]
step <- 0:ceiling(sqrt(length(d1[, 1])))
## sqrt of N,round up, define number of steps for probability analysis
## along height gradient
Pvalue <- array(data = NA, dim = max(step), dimnames = NULL)
fromheight <- array(data = NA, dim = max(step), dimnames = NULL)
toheight <- array(data = NA, dim = max(step), dimnames = NULL)
PvalueNo <- array(data = NA, dim = max(step), dimnames = NULL)
stepvector <- array(data = NA, dim = max(step), dimnames = NULL)
startel <- min(WoOfin[, 2])
stepsize <- as.numeric((max(WoOfin[, 2]) - min(WoOfin[, 2]))/max(step))
## calculate size of steps probability calculation
for (i in 0:(max(step) - 1)) {
Pselect2 <- 0
Pselect1 <- 0
Pselect2 <- subset(WoOfin, (WoOfin[, 2] >= (startel + (stepsize * i))),)
Pselect1 <- subset(Pselect2, (Pselect2[, 2] <= (startel + (stepsize * (1 +i)))), )
Pvalue[i] <- (sum(Pselect1[, 1])/c(length(Pselect1[, 1])))
PvalueNo[i] <- (sum(Pselect1[, 1])/c(length(Pselect1[, 1]))) * sum(Pselect1[,1])
fromheight[i] <- as.numeric(startel + (stepsize * (i - 1)))
toheight[i] <- as.numeric(startel + (stepsize * (i)))
}
Pvaluedeath <- c(1 - Pvalue) ## P value for failure
## plot results: density for all successful WoO and Psuccess
b3 <- density(defWoO[, 1])
## all established seedlings density
plot(fromheight, Pvalue, type = "l", col = "red", axes = "false", lwd = 4, xlab = "elevation",ylab = "P success")
par(mar = c(5, 4, 4, 4))
box(which = "plot", lty = "solid", lwd = 3)
mtext(4, text = "density", line = 2)
axis(2, col = "red", lwd = 3, ylim = c(0, 1), cex.axis = 1.5)
par(usr = c(par("usr")[1:2], 0, c((max(b3$y)) + 1e-05)))
lines(b3, lwd = 3)
axis(4, lwd = 3, cex.axis = 1.5)
axis(1, lwd = 3, cex.axis = 1.5)
## show histogramm of duration of all WoO >=1 day for max 100 days
hist(disperse[, 2], breaks = c(max(disperse[, 2])), xlim = c(0, 100), cex.axis = 1.5,xlab = "WoO length",ylab
= "frequency")