R/manage_expansion_sim.R
In FMestre1/MetaLandSim: Landscape and Range Expansion Simulation
Defines functions
manage_expansion_sim
Documented in
manage_expansion_sim
manage_expansion_sim <- function(mapsize, dist_m, areaM, areaSD, Npatch,percI, param, b=1, tsteps, iter,
variable,var_min,var_max,by)
{
range_expansion1 <-
function(rl, percI, param, b, tsteps, iter)
{
if(!inherits(rl, "landscape"))
#if (class(rl) != "landscape")
{
stop(paste(rl, " should be an object of class class 'landscape'.", sep = ""),
call. = FALSE)
}
mapsize <- rl$mapsize
dist_m <- rl$minimum.distance
areaM <- rl$mean.area
areaSD <- rl$SD.area
Npatch <- rl$number.patches
disp <- rl$dispersal
node.expansion <- function(occ_landscape, param, b, node, tsteps) {
output0 <- as.data.frame(matrix(nrow = tsteps, ncol = 2))
output0[, 1] <- 1:nrow(output0)
npatch <- occ_landscape$number.patches
mapsize <- occ_landscape$mapsize
ID_land <- max(occ_landscape$nodes.characteristics$ID)
mapsize <- occ_landscape$mapsize
nrow_land <- nrow(occ_landscape$nodes.characteristics)
clock <- 1
if (node == "North") {
xx1xx <- "S"
xx2xx <- NA
xx3xx <- mapsize
xx4xx <- "North"
xx7xx <- NA
xx8xx <- 0
xx9xx <- "South"
}
if (node == "South") {
xx1xx <- "N"
xx2xx <- NA
xx3xx <- 0
xx4xx <- "South"
xx7xx <- NA
xx8xx <- mapsize
xx9xx <- "North"
}
if (node == "East") {
xx1xx <- "W"
xx2xx <- mapsize
xx3xx <- NA
xx4xx <- "East"
xx7xx <- 0
xx8xx <- NA
xx9xx <- "West"
}
if (node == "West") {
xx1xx <- "E"
xx2xx <- 0
xx3xx <- NA
xx4xx <- "West"
xx7xx <- mapsize
xx8xx <- NA
xx9xx <- "East"
}
repeat {
if (node == "North") {
xx5xx <- min(abs(mapsize - occ_landscape$nodes.characteristics[,
2])[abs(mapsize - occ_landscape$nodes.characteristics[, 2]) !=
0])
xx6xx <- abs(mapsize - occ_landscape$nodes.characteristics[, 2])
xx10xx <- min(occ_landscape$nodes.characteristics[, 2][occ_landscape$nodes.characteristics[,
2] != 0])
xx11xx <- occ_landscape$nodes.characteristics[, 2]
}
if (node == "South") {
xx5xx <- min(occ_landscape$nodes.characteristics[, 2][occ_landscape$nodes.characteristics[,
2] != 0])
xx6xx <- occ_landscape$nodes.characteristics[, 2]
xx10xx <- min(abs(mapsize - occ_landscape$nodes.characteristics[,
2])[abs(mapsize - occ_landscape$nodes.characteristics[, 2]) !=
0])
xx11xx <- abs(mapsize - occ_landscape$nodes.characteristics[, 2])
}
if (node == "East") {
xx5xx <- min(abs(mapsize - occ_landscape$nodes.characteristics[,
1])[abs(mapsize - occ_landscape$nodes.characteristics[, 1]) !=
0])
xx6xx <- abs(mapsize - occ_landscape$nodes.characteristics[, 1])
xx10xx <- min(occ_landscape$nodes.characteristics[, 1][occ_landscape$nodes.characteristics[,
1] != 0])
xx11xx <- occ_landscape$nodes.characteristics[, 1]
}
if (node == "West") {
xx5xx <- min(occ_landscape$nodes.characteristics[, 1][occ_landscape$nodes.characteristics[,
1] != 0])
xx6xx <- occ_landscape$nodes.characteristics[, 1]
xx10xx <- min(abs(mapsize - occ_landscape$nodes.characteristics[,
1])[abs(mapsize - occ_landscape$nodes.characteristics[, 1]) !=
0])
xx11xx <- abs(mapsize - occ_landscape$nodes.characteristics[, 1])
}
ocupp <- "N"
if (clock == 1 || (clock >= 2 & ocupp == "N")) {
occ_landscape$nodes.characteristics[nrow_land + 1, ] <- NA
occ_landscape$nodes.characteristics$ID[(nrow_land + 1)] <- (ID_land +
1)
area1 <- mean(occ_landscape$nodes.characteristics$areas[1:nrow_land])
occ_landscape$nodes.characteristics$radius[(nrow_land + 1)] <- sqrt((area1 *
10000)/pi)
occ_landscape$nodes.characteristics$areas[(nrow_land + 1)] <- (occ_landscape$nodes.characteristics$radius[(nrow_land +
1)]) * mapsize
occ_landscape$nodes.characteristics$y[nrow_land + 1] <- xx3xx
occ_landscape$nodes.characteristics$x[nrow_land + 1] <- xx2xx
max_cluster <- max(occ_landscape$nodes.characteristics$cluster, na.rm = T)
occ_landscape$nodes.characteristics$cluster[(nrow_land + 1)] <- c(max_cluster +
1)
occ_landscape$nodes.characteristics$colour <- as.character(occ_landscape$nodes.characteristics$colour)
occ_landscape$nodes.characteristics$colour[(nrow_land + 1)] <- xx4xx
occ_landscape$nodes.characteristics$species[(nrow_land + 1)] <- 0
occ_landscape$nodes.characteristics$nneighbour[(nrow_land + 1)] <- xx5xx
occ_landscape$number.patches <- occ_landscape$number.patches + 1
dist_nodos <- occ_landscape$distance.to.neighbours
dist_nodos[, (nrow_land + 1)] <- c(xx6xx)
colnames(dist_nodos)[(nrow_land + 1)] <- xx4xx
dist_nodos[(nrow_land + 1), ] <- c(xx6xx, 0)
rownames(dist_nodos)[(nrow_land + 1)] <- xx4xx
occ_landscape$distance.to.neighbours <- dist_nodos
}
if (clock >= 2 & ocupp == "Y") {
rl1 <- rland.graph(mapsize = occ_landscape$mapsize, dist_m = occ_landscape$minimum.distance,
areaM = occ_landscape$mean.area, areaSD = occ_landscape$SD.area,
Npatch = npatch, disp = occ_landscape$dispersal, plotG = FALSE)
occ_landscape <- suppressWarnings(species.graph(rl = rl1, method = "percentage",
parm = 0, plotG = FALSE))
occ_landscape$nodes.characteristics[nrow_land + 2, ] <- NA
occ_landscape$nodes.characteristics$ID[(nrow_land + 1):(nrow_land +
2)] <- (ID_land + 1):(ID_land + 2)
area1 <- mean(occ_landscape$nodes.characteristics$areas[1:nrow_land])
occ_landscape$nodes.characteristics$radius[(nrow_land + 1):(nrow_land +
2)] <- sqrt((area1 * 10000)/pi)
occ_landscape$nodes.characteristics$areas[(nrow_land + 1):(nrow_land +
2)] <- (occ_landscape$nodes.characteristics$radius[(nrow_land +
1)]) * mapsize
occ_landscape$nodes.characteristics$y[nrow_land + 1] <- xx3xx
occ_landscape$nodes.characteristics$x[nrow_land + 1] <- xx2xx
occ_landscape$nodes.characteristics$y[nrow_land + 2] <- xx8xx
occ_landscape$nodes.characteristics$x[nrow_land + 2] <- xx7xx
max_cluster <- max(occ_landscape$nodes.characteristics$cluster, na.rm = T)
occ_landscape$nodes.characteristics$cluster[(nrow_land + 1):(nrow_land +
2)] <- c(max_cluster + 1)
occ_landscape$nodes.characteristics$colour <- as.character(occ_landscape$nodes.characteristics$colour)
occ_landscape$nodes.characteristics$colour[(nrow_land + 1)] <- xx4xx
occ_landscape$nodes.characteristics$colour[(nrow_land + 2)] <- xx9xx
occ_landscape$nodes.characteristics$species[(nrow_land + 1)] <- 0
occ_landscape$nodes.characteristics$species[(nrow_land + 2)] <- 1
occ_landscape$nodes.characteristics$nneighbour[(nrow_land + 1)] <- xx5xx
occ_landscape$nodes.characteristics$nneighbour[(nrow_land + 2)] <- xx10xx
occ_landscape$number.patches <- occ_landscape$number.patches + 2
dist_nodos <- occ_landscape$distance.to.neighbours
dist_nodos[, (nrow_land + 1)] <- NA
dist_nodos[, (nrow_land + 2)] <- NA
dist_nodos[(nrow_land + 1), ] <- NA
dist_nodos[(nrow_land + 2), ] <- NA
dist_nodos[, (nrow_land + 1)] <- c(xx6xx, 0, mapsize)
dist_nodos[, (nrow_land + 2)] <- c(xx11xx, mapsize, 0)
dist_nodos[(nrow_land + 1), ] <- c(xx6xx, 0, mapsize)
dist_nodos[(nrow_land + 2), ] <- c(xx11xx, mapsize, 0)
colnames(dist_nodos)[(nrow_land + 1)] <- xx4xx
colnames(dist_nodos)[(nrow_land + 2)] <- xx9xx
rownames(dist_nodos)[(nrow_land + 1)] <- xx4xx
rownames(dist_nodos)[(nrow_land + 2)] <- xx9xx
occ_landscape$distance.to.neighbours <- dist_nodos
}
class(occ_landscape) <- "metapopulation"
occ_landscape_new <- spom(sp = occ_landscape, kern = "op1",
conn = "op1", colnz = "op1", ext = "op1", param_df = param, b = b,
c1 = NULL, c2 = NULL, z = NULL, R = NULL)
if (occ_landscape_new$nodes.characteristics$species2[nrow_land + 1] ==
0)
ocupp <- "N"
if (occ_landscape_new$nodes.characteristics$species2[nrow_land + 1] ==
1)
ocupp <- "Y"
if (ocupp == "N") {
occ_landscape <- occ_landscape_new
occ_landscape$nodes.characteristics <- occ_landscape$nodes.characteristics[,
-c(9, 11)]
names(occ_landscape$nodes.characteristics)[names(occ_landscape$nodes.characteristics) ==
"species2"] <- "species"
occ_landscape <- occ_landscape[-9]
}
if (ocupp == "Y")
value <- clock
if (ocupp == "N")
value <- 0
output0[clock, 2] <- value
if (clock == tsteps)
break
if (nrow(occ_landscape$nodes.characteristics) == (npatch + 1)) {
occ_landscape$nodes.characteristics <- occ_landscape$nodes.characteristics[-(nrow_land +
1), ]
occ_landscape$distance.to.neighbours <- occ_landscape$distance.to.neighbours[-(nrow_land +
1), ]
occ_landscape$distance.to.neighbours <- occ_landscape$distance.to.neighbours[,
-(nrow_land + 1)]
occ_landscape$number.patches <- occ_landscape$number.patches - 1
}
if (nrow(occ_landscape$nodes.characteristics) == (npatch + 2)) {
occ_landscape$nodes.characteristics <- occ_landscape$nodes.characteristics[-c((nrow_land +
1):(nrow_land + 2)), ]
occ_landscape$distance.to.neighbours <- occ_landscape$distance.to.neighbours[-c((nrow_land +
1):(nrow_land + 2)), ]
occ_landscape$distance.to.neighbours <- occ_landscape$distance.to.neighbours[,
-c((nrow_land + 1):(nrow_land + 2))]
occ_landscape$number.patches <- occ_landscape$number.patches - 2
}
clock <- clock + 1
}
if (sum(output0[, 2]) == 0) {
out_vec <- 0
output1 <- cbind(0, out_vec)
colnames(output1) <- c("DISTANCE", "TIME STEP")
output1 <- as.data.frame(output1)
return(output1)
}
if (sum(output0[, 2]) != 0) {
output1 <- output0[output0[, 2] != 0, ]
output1[, 1] <- output1[, 1] * mapsize
colnames(output1) <- c("DISTANCE", "TIME STEP")
output1 <- as.data.frame(output1)
return(output1)
}
}
distance <- mapsize * 1:tsteps
outputN <- distance
outputS <- distance
outputE <- distance
outputW <- distance
for (i in 1:iter) {
sp1 <- species.graph(rl = rl, method = "percentage", parm = percI, nsew = "none",
plotG = FALSE)
nodeN <- node.expansion(occ_landscape = sp1, param, b, node = "North",
tsteps)
outputN <- suppressWarnings(cbind(outputN, c(nodeN[, 2], rep(NA, length(outputN) -
length(nodeN[, 2])))))
nodeS <- node.expansion(occ_landscape = sp1, param, b, node = "South",
tsteps)
outputS <- suppressWarnings(cbind(outputS, c(nodeS[, 2], rep(NA, length(outputS) -
length(nodeS[, 2])))))
nodeE <- node.expansion(occ_landscape = sp1, param, b, node = "East",
tsteps)
outputE <- suppressWarnings(cbind(outputE, c(nodeE[, 2], rep(NA, length(outputE) -
length(nodeE[, 2])))))
nodeW <- node.expansion(occ_landscape = sp1, param, b, node = "West",
tsteps)
outputW <- suppressWarnings(cbind(outputW, c(nodeW[, 2], rep(NA, length(outputW) -
length(nodeW[, 2])))))
}
outputN[is.na(outputN)] <- 0
outputS[is.na(outputS)] <- 0
outputE[is.na(outputE)] <- 0
outputW[is.na(outputW)] <- 0
tstepsN <- outputN[,2]
tstepsS <- outputS[,2]
tstepsE <- outputE[,2]
tstepsW <- outputW[,2]
for (x in 2:(iter + 1)) {
i_N <- which(outputN[, x] != 0)
outputN[i_N, x] <- 1
i_S <- which(outputS[, x] != 0)
outputS[i_S, x] <- 1
i_E <- which(outputE[, x] != 0)
outputE[i_E, x] <- 1
i_W <- which(outputW[, x] != 0)
outputW[i_W, x] <- 1
}
outputN <- cbind(outputN[, 1], rowSums(outputN[, 2:(ncol(outputN))]))
outputS <- cbind(outputS[, 1], rowSums(outputS[, 2:(ncol(outputS))]))
outputE <- cbind(outputE[, 1], rowSums(outputE[, 2:(ncol(outputE))]))
outputW <- cbind(outputW[, 1], rowSums(outputW[, 2:(ncol(outputW))]))
outputN <- cbind(outputN[, 1:2], outputN[, 2]/iter, tstepsN)
outputS <- cbind(outputS[, 1:2], outputS[, 2]/iter, tstepsS)
outputE <- cbind(outputE[, 1:2], outputE[, 2]/iter, tstepsE)
outputW <- cbind(outputW[, 1:2], outputW[, 2]/iter, tstepsW)
outputN <- as.data.frame(outputN)
outputS <- as.data.frame(outputS)
outputE <- as.data.frame(outputE)
outputW <- as.data.frame(outputW)
names(outputN) <- c("DISTANCE", "OCCUPATION", "PROPORTION", "TIME STEPS")
names(outputS) <- c("DISTANCE", "OCCUPATION", "PROPORTION", "TIME STEPS")
names(outputE) <- c("DISTANCE", "OCCUPATION", "PROPORTION", "TIME STEPS")
names(outputW) <- c("DISTANCE", "OCCUPATION", "PROPORTION", "TIME STEPS")
output <- list(NORTH = outputN, SOUTH = outputS, EAST = outputE, WEST = outputW)
class(output) <- "expansion"
return(output)
}
var1 <- rep(seq(from=var_min,to=var_max,by=by))
outputN <- data.frame(matrix(nrow = tsteps, ncol = length(var1)))
outputS <- data.frame(matrix(nrow = tsteps, ncol = length(var1)))
outputE <- data.frame(matrix(nrow = tsteps, ncol = length(var1)))
outputW <- data.frame(matrix(nrow = tsteps, ncol = length(var1)))
clock <- 1
namesN <- as.character()
namesS <- as.character()
namesE <- as.character()
namesW <- as.character()
for (i in 1:length(var1)){
if (variable=="dist") dist_m <- var1[i]
if (variable=="area") areaM <- var1[i]
if (variable=="npatch") Npatch <- var1[i]
if (variable=="sizevar") areaSD <- var1[i]
rl <- rland.graph(mapsize, dist_m, areaM, areaSD, Npatch, disp=0, plotG=FALSE)
rg <- range_expansion1(rl, percI, param, b, tsteps, iter)
if(clock==1){
outputN[,clock] <- rg$NORTH$DISTANCE/1000
outputS[,clock] <- rg$SOUTH$DISTANCE/1000
outputE[,clock] <- rg$EAST$DISTANCE/1000
outputW[,clock] <- rg$WEST$DISTANCE/1000
}
outputN[,clock+1] <- rg$NORTH[,4]
outputS[,clock+1] <- rg$SOUTH[,4]
outputE[,clock+1] <- rg$EAST[,4]
outputW[,clock+1] <- rg$WEST[,4]
clock <- clock+1
}
if (variable=="area") varname <- "MEAN PATCH AREA"
if (variable=="dist") varname <- "MINIMUM DISTANCE BETWEEN PATCHES"
if (variable=="npatch") varname <- "NUMBER OF PATCHES"
if (variable=="sizevar") varname <- "STAND. DEV. OF PATCH SIZE"
names(outputN) <- c("DISTANCE(km)",as.character(var1))
names(outputS) <- c("DISTANCE(km)",as.character(var1))
names(outputE) <- c("DISTANCE(km)",as.character(var1))
names(outputW) <- c("DISTANCE(km)",as.character(var1))
outN <- as.data.frame(matrix(ncol=3,nrow=length(var1)))
names(outN) <- c(varname,"MEAN EXPANSION SPEED","MAXIMUM EXPANSION DISTANCE")
outN[,1] <- var1
for(i in 1:nrow(outN)){
val1 <- outputN[,i+1]
val2 <- length(val1[val1!=0])
if (val2==0) {
outN[i,2] <- NA
outN[i,3] <- NA
}
if (val2!=0) {
val3 <- outputN[,1][val2]
outN[i,2] <- val3/tsteps
outN[i,3] <- val3
}
}
outS <- as.data.frame(matrix(ncol=3,nrow=length(var1)))
names(outS) <- c(varname,"MEAN EXPANSION SPEED","MAXIMUM EXPANSION DISTANCE")
outS[,1] <- var1
for(i in 1:nrow(outS)){
val1 <- outputN[,i+1]
val2 <- length(val1[val1!=0])
if (val2==0) {
outS[i,2] <- NA
outS[i,3] <- NA
}
if (val2!=0) {
val3 <- outputN[,1][val2]
outS[i,2] <- val3/tsteps
outS[i,3] <- val3
}
}
outE <- as.data.frame(matrix(ncol=3,nrow=length(var1)))
names(outE) <- c(varname,"MEAN EXPANSION SPEED","MAXIMUM EXPANSION DISTANCE")
outE[,1] <- var1
for(i in 1:nrow(outE)){
val1 <- outputN[,i+1]
val2 <- length(val1[val1!=0])
if (val2==0) {
outE[i,2] <- NA
outE[i,3] <- NA
}
if (val2!=0) {
val3 <- outputN[,1][val2]
outE[i,2] <- val3/tsteps
outE[i,3] <- val3
}
}
outW <- as.data.frame(matrix(ncol=3,nrow=length(var1)))
names(outW) <- c(varname,"MEAN EXPANSION SPEED","MAXIMUM EXPANSION DISTANCE")
outW[,1] <- var1
for(i in 1:nrow(outW)){
val1 <- outputN[,i+1]
val2 <- length(val1[val1!=0])
if (val2==0) {
outW[i,2] <- NA
outW[i,3] <- NA
}
if (val2!=0) {
val3 <- outputN[,1][val2]
outW[i,2] <- val3/tsteps
outW[i,3] <- val3
}
}
pN2 <- gvisLineChart(outN, xvar = varname, yvar = "MAXIMUM EXPANSION DISTANCE", options = list(title = "North-Distance",
width = 500, height = 300, curveType = "function", legend = "none", titleTextStyle = "{colour:'black', fontName:'Courier', fontSize:16}",
vAxis = "{title: 'Maximum Expansion Distance(km)'}", hAxis = "{title: 'Variable'}", series = "[{color: '#006400'}]",
backgroundColor = "#D1EEEE"))
pS2 <- gvisLineChart(outS, xvar = varname, yvar = "MAXIMUM EXPANSION DISTANCE", options = list(title = "South-Distance",
width = 500, height = 300, curveType = "function", legend = "none", titleTextStyle = "{colour:'black', fontName:'Courier', fontSize:16}",
vAxis = "{title: 'Maximum Expansion Distance(km)'}", hAxis = "{title: 'Variable'}", series = "[{color: '#0000FF'}]",
backgroundColor = "#D1EEEE"))
pE2 <- gvisLineChart(outE, xvar = varname, yvar = "MAXIMUM EXPANSION DISTANCE", options = list(title = "East-Distance",
width = 500, height = 300, curveType = "function", legend = "none", titleTextStyle = "{colour:'black', fontName:'Courier', fontSize:16}",
vAxis = "{title: 'Maximum Expansion Distance(km)'}", hAxis = "{title: 'Variable'}", series = "[{color: '#8B0000'}]",
backgroundColor = "#D1EEEE"))
pW2 <- gvisLineChart(outW, xvar = varname, yvar = "MAXIMUM EXPANSION DISTANCE", options = list(title = "West-Distance",
width = 500, height = 300, curveType = "function", legend = "none", titleTextStyle = "{colour:'black', fontName:'Courier', fontSize:16}",
vAxis = "{title: 'Maximum Expansion Distance(km)'}", hAxis = "{title: 'Variable'}", series = "[{color: '#FF4500'}]",
backgroundColor = "#D1EEEE"))
ln1 <- gvisMerge(pN2, pS2, horizontal = TRUE)
ln2 <- gvisMerge(pE2, pW2, horizontal = TRUE)
ln.final <- gvisMerge(ln1, ln2, horizontal = FALSE)
ln.final$html$caption <- paste("<div><span> MetaLandSim range expansion simulation - Expansion scenarios produced
considering variation in ",varname,". </span><br />", sep = "")
ln.final$html$footer <- paste("\n<!-- htmlFooter -->\n<span> \n ",R.Version()$version.string,"• <a href=\"http://code.google.com/p/google-motion-charts-with-r/\">googleVis-", packageVersion("googleVis"),"</a>\n • MetaLandSim-",packageVersion("MetaLandSim"),"\n • <a href=\"https://developers.google.com/terms/\">Google Terms of Use</a> • <a href=\"https://google-developers.appspot.com/chart/interactive/docs/gallery/linechart.html#Data_Policy\">Data Policy</a>\n</span></div>\n</body>\n</html>\n", sep="")
output <- list(NORTH = outN, SOUTH = outS, EAST = outE, WEST = outW, SimN = outputN, SimS = outputS, SimE = outputE, SimW = outputW)
plot(ln.final)
return(output)
}
FMestre1/MetaLandSim documentation built on Feb. 4, 2023, 5:46 p.m.
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Defines functions manage_expansion_sim
Documented in manage_expansion_sim
manage_expansion_sim <- function(mapsize, dist_m, areaM, areaSD, Npatch,percI, param, b=1, tsteps, iter,
variable,var_min,var_max,by)
{
range_expansion1 <-
function(rl, percI, param, b, tsteps, iter)
{
if(!inherits(rl, "landscape"))
#if (class(rl) != "landscape")
{
stop(paste(rl, " should be an object of class class 'landscape'.", sep = ""),
call. = FALSE)
}
mapsize <- rl$mapsize
dist_m <- rl$minimum.distance
areaM <- rl$mean.area
areaSD <- rl$SD.area
Npatch <- rl$number.patches
disp <- rl$dispersal
node.expansion <- function(occ_landscape, param, b, node, tsteps) {
output0 <- as.data.frame(matrix(nrow = tsteps, ncol = 2))
output0[, 1] <- 1:nrow(output0)
npatch <- occ_landscape$number.patches
mapsize <- occ_landscape$mapsize
ID_land <- max(occ_landscape$nodes.characteristics$ID)
mapsize <- occ_landscape$mapsize
nrow_land <- nrow(occ_landscape$nodes.characteristics)
clock <- 1
if (node == "North") {
xx1xx <- "S"
xx2xx <- NA
xx3xx <- mapsize
xx4xx <- "North"
xx7xx <- NA
xx8xx <- 0
xx9xx <- "South"
}
if (node == "South") {
xx1xx <- "N"
xx2xx <- NA
xx3xx <- 0
xx4xx <- "South"
xx7xx <- NA
xx8xx <- mapsize
xx9xx <- "North"
}
if (node == "East") {
xx1xx <- "W"
xx2xx <- mapsize
xx3xx <- NA
xx4xx <- "East"
xx7xx <- 0
xx8xx <- NA
xx9xx <- "West"
}
if (node == "West") {
xx1xx <- "E"
xx2xx <- 0
xx3xx <- NA
xx4xx <- "West"
xx7xx <- mapsize
xx8xx <- NA
xx9xx <- "East"
}
repeat {
if (node == "North") {
xx5xx <- min(abs(mapsize - occ_landscape$nodes.characteristics[,
2])[abs(mapsize - occ_landscape$nodes.characteristics[, 2]) !=
0])
xx6xx <- abs(mapsize - occ_landscape$nodes.characteristics[, 2])
xx10xx <- min(occ_landscape$nodes.characteristics[, 2][occ_landscape$nodes.characteristics[,
2] != 0])
xx11xx <- occ_landscape$nodes.characteristics[, 2]
}
if (node == "South") {
xx5xx <- min(occ_landscape$nodes.characteristics[, 2][occ_landscape$nodes.characteristics[,
2] != 0])
xx6xx <- occ_landscape$nodes.characteristics[, 2]
xx10xx <- min(abs(mapsize - occ_landscape$nodes.characteristics[,
2])[abs(mapsize - occ_landscape$nodes.characteristics[, 2]) !=
0])
xx11xx <- abs(mapsize - occ_landscape$nodes.characteristics[, 2])
}
if (node == "East") {
xx5xx <- min(abs(mapsize - occ_landscape$nodes.characteristics[,
1])[abs(mapsize - occ_landscape$nodes.characteristics[, 1]) !=
0])
xx6xx <- abs(mapsize - occ_landscape$nodes.characteristics[, 1])
xx10xx <- min(occ_landscape$nodes.characteristics[, 1][occ_landscape$nodes.characteristics[,
1] != 0])
xx11xx <- occ_landscape$nodes.characteristics[, 1]
}
if (node == "West") {
xx5xx <- min(occ_landscape$nodes.characteristics[, 1][occ_landscape$nodes.characteristics[,
1] != 0])
xx6xx <- occ_landscape$nodes.characteristics[, 1]
xx10xx <- min(abs(mapsize - occ_landscape$nodes.characteristics[,
1])[abs(mapsize - occ_landscape$nodes.characteristics[, 1]) !=
0])
xx11xx <- abs(mapsize - occ_landscape$nodes.characteristics[, 1])
}
ocupp <- "N"
if (clock == 1 || (clock >= 2 & ocupp == "N")) {
occ_landscape$nodes.characteristics[nrow_land + 1, ] <- NA
occ_landscape$nodes.characteristics$ID[(nrow_land + 1)] <- (ID_land +
1)
area1 <- mean(occ_landscape$nodes.characteristics$areas[1:nrow_land])
occ_landscape$nodes.characteristics$radius[(nrow_land + 1)] <- sqrt((area1 *
10000)/pi)
occ_landscape$nodes.characteristics$areas[(nrow_land + 1)] <- (occ_landscape$nodes.characteristics$radius[(nrow_land +
1)]) * mapsize
occ_landscape$nodes.characteristics$y[nrow_land + 1] <- xx3xx
occ_landscape$nodes.characteristics$x[nrow_land + 1] <- xx2xx
max_cluster <- max(occ_landscape$nodes.characteristics$cluster, na.rm = T)
occ_landscape$nodes.characteristics$cluster[(nrow_land + 1)] <- c(max_cluster +
1)
occ_landscape$nodes.characteristics$colour <- as.character(occ_landscape$nodes.characteristics$colour)
occ_landscape$nodes.characteristics$colour[(nrow_land + 1)] <- xx4xx
occ_landscape$nodes.characteristics$species[(nrow_land + 1)] <- 0
occ_landscape$nodes.characteristics$nneighbour[(nrow_land + 1)] <- xx5xx
occ_landscape$number.patches <- occ_landscape$number.patches + 1
dist_nodos <- occ_landscape$distance.to.neighbours
dist_nodos[, (nrow_land + 1)] <- c(xx6xx)
colnames(dist_nodos)[(nrow_land + 1)] <- xx4xx
dist_nodos[(nrow_land + 1), ] <- c(xx6xx, 0)
rownames(dist_nodos)[(nrow_land + 1)] <- xx4xx
occ_landscape$distance.to.neighbours <- dist_nodos
}
if (clock >= 2 & ocupp == "Y") {
rl1 <- rland.graph(mapsize = occ_landscape$mapsize, dist_m = occ_landscape$minimum.distance,
areaM = occ_landscape$mean.area, areaSD = occ_landscape$SD.area,
Npatch = npatch, disp = occ_landscape$dispersal, plotG = FALSE)
occ_landscape <- suppressWarnings(species.graph(rl = rl1, method = "percentage",
parm = 0, plotG = FALSE))
occ_landscape$nodes.characteristics[nrow_land + 2, ] <- NA
occ_landscape$nodes.characteristics$ID[(nrow_land + 1):(nrow_land +
2)] <- (ID_land + 1):(ID_land + 2)
area1 <- mean(occ_landscape$nodes.characteristics$areas[1:nrow_land])
occ_landscape$nodes.characteristics$radius[(nrow_land + 1):(nrow_land +
2)] <- sqrt((area1 * 10000)/pi)
occ_landscape$nodes.characteristics$areas[(nrow_land + 1):(nrow_land +
2)] <- (occ_landscape$nodes.characteristics$radius[(nrow_land +
1)]) * mapsize
occ_landscape$nodes.characteristics$y[nrow_land + 1] <- xx3xx
occ_landscape$nodes.characteristics$x[nrow_land + 1] <- xx2xx
occ_landscape$nodes.characteristics$y[nrow_land + 2] <- xx8xx
occ_landscape$nodes.characteristics$x[nrow_land + 2] <- xx7xx
max_cluster <- max(occ_landscape$nodes.characteristics$cluster, na.rm = T)
occ_landscape$nodes.characteristics$cluster[(nrow_land + 1):(nrow_land +
2)] <- c(max_cluster + 1)
occ_landscape$nodes.characteristics$colour <- as.character(occ_landscape$nodes.characteristics$colour)
occ_landscape$nodes.characteristics$colour[(nrow_land + 1)] <- xx4xx
occ_landscape$nodes.characteristics$colour[(nrow_land + 2)] <- xx9xx
occ_landscape$nodes.characteristics$species[(nrow_land + 1)] <- 0
occ_landscape$nodes.characteristics$species[(nrow_land + 2)] <- 1
occ_landscape$nodes.characteristics$nneighbour[(nrow_land + 1)] <- xx5xx
occ_landscape$nodes.characteristics$nneighbour[(nrow_land + 2)] <- xx10xx
occ_landscape$number.patches <- occ_landscape$number.patches + 2
dist_nodos <- occ_landscape$distance.to.neighbours
dist_nodos[, (nrow_land + 1)] <- NA
dist_nodos[, (nrow_land + 2)] <- NA
dist_nodos[(nrow_land + 1), ] <- NA
dist_nodos[(nrow_land + 2), ] <- NA
dist_nodos[, (nrow_land + 1)] <- c(xx6xx, 0, mapsize)
dist_nodos[, (nrow_land + 2)] <- c(xx11xx, mapsize, 0)
dist_nodos[(nrow_land + 1), ] <- c(xx6xx, 0, mapsize)
dist_nodos[(nrow_land + 2), ] <- c(xx11xx, mapsize, 0)
colnames(dist_nodos)[(nrow_land + 1)] <- xx4xx
colnames(dist_nodos)[(nrow_land + 2)] <- xx9xx
rownames(dist_nodos)[(nrow_land + 1)] <- xx4xx
rownames(dist_nodos)[(nrow_land + 2)] <- xx9xx
occ_landscape$distance.to.neighbours <- dist_nodos
}
class(occ_landscape) <- "metapopulation"
occ_landscape_new <- spom(sp = occ_landscape, kern = "op1",
conn = "op1", colnz = "op1", ext = "op1", param_df = param, b = b,
c1 = NULL, c2 = NULL, z = NULL, R = NULL)
if (occ_landscape_new$nodes.characteristics$species2[nrow_land + 1] ==
0)
ocupp <- "N"
if (occ_landscape_new$nodes.characteristics$species2[nrow_land + 1] ==
1)
ocupp <- "Y"
if (ocupp == "N") {
occ_landscape <- occ_landscape_new
occ_landscape$nodes.characteristics <- occ_landscape$nodes.characteristics[,
-c(9, 11)]
names(occ_landscape$nodes.characteristics)[names(occ_landscape$nodes.characteristics) ==
"species2"] <- "species"
occ_landscape <- occ_landscape[-9]
}
if (ocupp == "Y")
value <- clock
if (ocupp == "N")
value <- 0
output0[clock, 2] <- value
if (clock == tsteps)
break
if (nrow(occ_landscape$nodes.characteristics) == (npatch + 1)) {
occ_landscape$nodes.characteristics <- occ_landscape$nodes.characteristics[-(nrow_land +
1), ]
occ_landscape$distance.to.neighbours <- occ_landscape$distance.to.neighbours[-(nrow_land +
1), ]
occ_landscape$distance.to.neighbours <- occ_landscape$distance.to.neighbours[,
-(nrow_land + 1)]
occ_landscape$number.patches <- occ_landscape$number.patches - 1
}
if (nrow(occ_landscape$nodes.characteristics) == (npatch + 2)) {
occ_landscape$nodes.characteristics <- occ_landscape$nodes.characteristics[-c((nrow_land +
1):(nrow_land + 2)), ]
occ_landscape$distance.to.neighbours <- occ_landscape$distance.to.neighbours[-c((nrow_land +
1):(nrow_land + 2)), ]
occ_landscape$distance.to.neighbours <- occ_landscape$distance.to.neighbours[,
-c((nrow_land + 1):(nrow_land + 2))]
occ_landscape$number.patches <- occ_landscape$number.patches - 2
}
clock <- clock + 1
}
if (sum(output0[, 2]) == 0) {
out_vec <- 0
output1 <- cbind(0, out_vec)
colnames(output1) <- c("DISTANCE", "TIME STEP")
output1 <- as.data.frame(output1)
return(output1)
}
if (sum(output0[, 2]) != 0) {
output1 <- output0[output0[, 2] != 0, ]
output1[, 1] <- output1[, 1] * mapsize
colnames(output1) <- c("DISTANCE", "TIME STEP")
output1 <- as.data.frame(output1)
return(output1)
}
}
distance <- mapsize * 1:tsteps
outputN <- distance
outputS <- distance
outputE <- distance
outputW <- distance
for (i in 1:iter) {
sp1 <- species.graph(rl = rl, method = "percentage", parm = percI, nsew = "none",
plotG = FALSE)
nodeN <- node.expansion(occ_landscape = sp1, param, b, node = "North",
tsteps)
outputN <- suppressWarnings(cbind(outputN, c(nodeN[, 2], rep(NA, length(outputN) -
length(nodeN[, 2])))))
nodeS <- node.expansion(occ_landscape = sp1, param, b, node = "South",
tsteps)
outputS <- suppressWarnings(cbind(outputS, c(nodeS[, 2], rep(NA, length(outputS) -
length(nodeS[, 2])))))
nodeE <- node.expansion(occ_landscape = sp1, param, b, node = "East",
tsteps)
outputE <- suppressWarnings(cbind(outputE, c(nodeE[, 2], rep(NA, length(outputE) -
length(nodeE[, 2])))))
nodeW <- node.expansion(occ_landscape = sp1, param, b, node = "West",
tsteps)
outputW <- suppressWarnings(cbind(outputW, c(nodeW[, 2], rep(NA, length(outputW) -
length(nodeW[, 2])))))
}
outputN[is.na(outputN)] <- 0
outputS[is.na(outputS)] <- 0
outputE[is.na(outputE)] <- 0
outputW[is.na(outputW)] <- 0
tstepsN <- outputN[,2]
tstepsS <- outputS[,2]
tstepsE <- outputE[,2]
tstepsW <- outputW[,2]
for (x in 2:(iter + 1)) {
i_N <- which(outputN[, x] != 0)
outputN[i_N, x] <- 1
i_S <- which(outputS[, x] != 0)
outputS[i_S, x] <- 1
i_E <- which(outputE[, x] != 0)
outputE[i_E, x] <- 1
i_W <- which(outputW[, x] != 0)
outputW[i_W, x] <- 1
}
outputN <- cbind(outputN[, 1], rowSums(outputN[, 2:(ncol(outputN))]))
outputS <- cbind(outputS[, 1], rowSums(outputS[, 2:(ncol(outputS))]))
outputE <- cbind(outputE[, 1], rowSums(outputE[, 2:(ncol(outputE))]))
outputW <- cbind(outputW[, 1], rowSums(outputW[, 2:(ncol(outputW))]))
outputN <- cbind(outputN[, 1:2], outputN[, 2]/iter, tstepsN)
outputS <- cbind(outputS[, 1:2], outputS[, 2]/iter, tstepsS)
outputE <- cbind(outputE[, 1:2], outputE[, 2]/iter, tstepsE)
outputW <- cbind(outputW[, 1:2], outputW[, 2]/iter, tstepsW)
outputN <- as.data.frame(outputN)
outputS <- as.data.frame(outputS)
outputE <- as.data.frame(outputE)
outputW <- as.data.frame(outputW)
names(outputN) <- c("DISTANCE", "OCCUPATION", "PROPORTION", "TIME STEPS")
names(outputS) <- c("DISTANCE", "OCCUPATION", "PROPORTION", "TIME STEPS")
names(outputE) <- c("DISTANCE", "OCCUPATION", "PROPORTION", "TIME STEPS")
names(outputW) <- c("DISTANCE", "OCCUPATION", "PROPORTION", "TIME STEPS")
output <- list(NORTH = outputN, SOUTH = outputS, EAST = outputE, WEST = outputW)
class(output) <- "expansion"
return(output)
}
var1 <- rep(seq(from=var_min,to=var_max,by=by))
outputN <- data.frame(matrix(nrow = tsteps, ncol = length(var1)))
outputS <- data.frame(matrix(nrow = tsteps, ncol = length(var1)))
outputE <- data.frame(matrix(nrow = tsteps, ncol = length(var1)))
outputW <- data.frame(matrix(nrow = tsteps, ncol = length(var1)))
clock <- 1
namesN <- as.character()
namesS <- as.character()
namesE <- as.character()
namesW <- as.character()
for (i in 1:length(var1)){
if (variable=="dist") dist_m <- var1[i]
if (variable=="area") areaM <- var1[i]
if (variable=="npatch") Npatch <- var1[i]
if (variable=="sizevar") areaSD <- var1[i]
rl <- rland.graph(mapsize, dist_m, areaM, areaSD, Npatch, disp=0, plotG=FALSE)
rg <- range_expansion1(rl, percI, param, b, tsteps, iter)
if(clock==1){
outputN[,clock] <- rg$NORTH$DISTANCE/1000
outputS[,clock] <- rg$SOUTH$DISTANCE/1000
outputE[,clock] <- rg$EAST$DISTANCE/1000
outputW[,clock] <- rg$WEST$DISTANCE/1000
}
outputN[,clock+1] <- rg$NORTH[,4]
outputS[,clock+1] <- rg$SOUTH[,4]
outputE[,clock+1] <- rg$EAST[,4]
outputW[,clock+1] <- rg$WEST[,4]
clock <- clock+1
}
if (variable=="area") varname <- "MEAN PATCH AREA"
if (variable=="dist") varname <- "MINIMUM DISTANCE BETWEEN PATCHES"
if (variable=="npatch") varname <- "NUMBER OF PATCHES"
if (variable=="sizevar") varname <- "STAND. DEV. OF PATCH SIZE"
names(outputN) <- c("DISTANCE(km)",as.character(var1))
names(outputS) <- c("DISTANCE(km)",as.character(var1))
names(outputE) <- c("DISTANCE(km)",as.character(var1))
names(outputW) <- c("DISTANCE(km)",as.character(var1))
outN <- as.data.frame(matrix(ncol=3,nrow=length(var1)))
names(outN) <- c(varname,"MEAN EXPANSION SPEED","MAXIMUM EXPANSION DISTANCE")
outN[,1] <- var1
for(i in 1:nrow(outN)){
val1 <- outputN[,i+1]
val2 <- length(val1[val1!=0])
if (val2==0) {
outN[i,2] <- NA
outN[i,3] <- NA
}
if (val2!=0) {
val3 <- outputN[,1][val2]
outN[i,2] <- val3/tsteps
outN[i,3] <- val3
}
}
outS <- as.data.frame(matrix(ncol=3,nrow=length(var1)))
names(outS) <- c(varname,"MEAN EXPANSION SPEED","MAXIMUM EXPANSION DISTANCE")
outS[,1] <- var1
for(i in 1:nrow(outS)){
val1 <- outputN[,i+1]
val2 <- length(val1[val1!=0])
if (val2==0) {
outS[i,2] <- NA
outS[i,3] <- NA
}
if (val2!=0) {
val3 <- outputN[,1][val2]
outS[i,2] <- val3/tsteps
outS[i,3] <- val3
}
}
outE <- as.data.frame(matrix(ncol=3,nrow=length(var1)))
names(outE) <- c(varname,"MEAN EXPANSION SPEED","MAXIMUM EXPANSION DISTANCE")
outE[,1] <- var1
for(i in 1:nrow(outE)){
val1 <- outputN[,i+1]
val2 <- length(val1[val1!=0])
if (val2==0) {
outE[i,2] <- NA
outE[i,3] <- NA
}
if (val2!=0) {
val3 <- outputN[,1][val2]
outE[i,2] <- val3/tsteps
outE[i,3] <- val3
}
}
outW <- as.data.frame(matrix(ncol=3,nrow=length(var1)))
names(outW) <- c(varname,"MEAN EXPANSION SPEED","MAXIMUM EXPANSION DISTANCE")
outW[,1] <- var1
for(i in 1:nrow(outW)){
val1 <- outputN[,i+1]
val2 <- length(val1[val1!=0])
if (val2==0) {
outW[i,2] <- NA
outW[i,3] <- NA
}
if (val2!=0) {
val3 <- outputN[,1][val2]
outW[i,2] <- val3/tsteps
outW[i,3] <- val3
}
}
pN2 <- gvisLineChart(outN, xvar = varname, yvar = "MAXIMUM EXPANSION DISTANCE", options = list(title = "North-Distance",
width = 500, height = 300, curveType = "function", legend = "none", titleTextStyle = "{colour:'black', fontName:'Courier', fontSize:16}",
vAxis = "{title: 'Maximum Expansion Distance(km)'}", hAxis = "{title: 'Variable'}", series = "[{color: '#006400'}]",
backgroundColor = "#D1EEEE"))
pS2 <- gvisLineChart(outS, xvar = varname, yvar = "MAXIMUM EXPANSION DISTANCE", options = list(title = "South-Distance",
width = 500, height = 300, curveType = "function", legend = "none", titleTextStyle = "{colour:'black', fontName:'Courier', fontSize:16}",
vAxis = "{title: 'Maximum Expansion Distance(km)'}", hAxis = "{title: 'Variable'}", series = "[{color: '#0000FF'}]",
backgroundColor = "#D1EEEE"))
pE2 <- gvisLineChart(outE, xvar = varname, yvar = "MAXIMUM EXPANSION DISTANCE", options = list(title = "East-Distance",
width = 500, height = 300, curveType = "function", legend = "none", titleTextStyle = "{colour:'black', fontName:'Courier', fontSize:16}",
vAxis = "{title: 'Maximum Expansion Distance(km)'}", hAxis = "{title: 'Variable'}", series = "[{color: '#8B0000'}]",
backgroundColor = "#D1EEEE"))
pW2 <- gvisLineChart(outW, xvar = varname, yvar = "MAXIMUM EXPANSION DISTANCE", options = list(title = "West-Distance",
width = 500, height = 300, curveType = "function", legend = "none", titleTextStyle = "{colour:'black', fontName:'Courier', fontSize:16}",
vAxis = "{title: 'Maximum Expansion Distance(km)'}", hAxis = "{title: 'Variable'}", series = "[{color: '#FF4500'}]",
backgroundColor = "#D1EEEE"))
ln1 <- gvisMerge(pN2, pS2, horizontal = TRUE)
ln2 <- gvisMerge(pE2, pW2, horizontal = TRUE)
ln.final <- gvisMerge(ln1, ln2, horizontal = FALSE)
ln.final$html$caption <- paste("<div><span> MetaLandSim range expansion simulation - Expansion scenarios produced
considering variation in ",varname,". </span><br />", sep = "")
ln.final$html$footer <- paste("\n<!-- htmlFooter -->\n<span> \n ",R.Version()$version.string,"• <a href=\"http://code.google.com/p/google-motion-charts-with-r/\">googleVis-", packageVersion("googleVis"),"</a>\n • MetaLandSim-",packageVersion("MetaLandSim"),"\n • <a href=\"https://developers.google.com/terms/\">Google Terms of Use</a> • <a href=\"https://google-developers.appspot.com/chart/interactive/docs/gallery/linechart.html#Data_Policy\">Data Policy</a>\n</span></div>\n</body>\n</html>\n", sep="")
output <- list(NORTH = outN, SOUTH = outS, EAST = outE, WEST = outW, SimN = outputN, SimS = outputS, SimE = outputE, SimW = outputW)
plot(ln.final)
return(output)
}
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