ecospat (version 3.2)

ecospat.mdr: Minimum Dispersal Routes)

Description

ecospat.mdr is a function that implement a minimum cost arborescence approach to analyse the invasion routes of a species from dates occurrence data.

Usage

ecospat.mdr (data, xcol, ycol, datecol, mode, rep, mean.date.error, fixed.sources.rows)

Arguments

data

dataframe with occurence data. Each row correspond to an occurrence.

xcol

The column in data containing x coordinates.

ycol

The column in data containing y coordinates.

datecol

The column in data containing dates.

mode

"observed", "min" or "random". "observed" calculate routes using real dates. "min" reorder dates so the the total length of the routes are minimal. "random" reatribute dates randomly.

rep

number of iteration of the analyse. if > 1, boostrap support for each route is provided.

mean.date.error

mean number of years to substract to observed dates. It is the mean of the truncated negative exponential distribution from which the time to be substracted is randomly sampled.

fixed.sources.rows

the rows in data (as a vector) corresponding to source occurrence(s) that initiated the invasion(s). No incoming routes are not calculated for sources.

Value

A list is returned by the function with in positon [[1]], a datafame with each row corresponding to a route (with new/old coordinates, new/old dates, length of the route, timespan, dispersal rate), in position [[2]] the total route length, in position [[3]] the median dispersal rate and in position [[4]] the number of outgoing nodes (index of clustering of the network)

Details

The function draws an incoming route to each occurence from the closest occurrence already occupied (with a previous date) and allows to substract a random number of time (years) to the observed dates from a truncated negative exponential distribution. It is possible to run several iterations and to get boostrap support for each route. itexp and rtexp functions are small internal functions to set a truncated negative exponential distribution.

References

Hordijk, W. and O. Broennimann. 2012. Dispersal routes reconstruction and the minimum cost arborescence problem. Journal of theoretical biology, 308, 115-122.

Broennimann, O., P. Mraz, B. Petitpierre, A. Guisan, and H. Muller-Scharer. 2014. Contrasting spatio-temporal climatic niche dynamics during the eastern and western invasions of spotted knapweed in North America.Journal of biogeography, 41, 1126-1136.

Examples

# NOT RUN {
library(maps)

data(ecospat.testMdr)
data<- ecospat.testMdr
intros<-order(data$date)[1:2] # rows corresponding to first introductions

# plot observed situation

plot(data[,2:1],pch=15,cex=0.5)
points(data[intros,2:1],pch=19,col="red")
text(data[,2]+0.5,data[,1]+0.5,data[,3],cex=0.5)
map(add=TRUE)

# calculate minimum cost arborescence (MCA) of dispersal routes

obs<-ecospat.mdr(data=data,xcol=2,ycol=1,datecol=3,mode="min",rep=100,
                  mean.date.error=1,fixed.sources.rows=intros)

# plot MCA results
# arrows' thickness indicate support for the routes

mca<-obs[[1]]
plot(mca[,3:4],type="n",xlab="longitude",ylab="latitude")
arrows(mca[,1],mca[,2],mca[,3],mca[,4],length = 0.05,lwd=mca$bootstrap.value*2)
map(add=TRUE)

# plot intros

points(data[intros,2:1],pch=19,col="red")
text(data[intros,2]+0.5,data[intros,1]+0.5,data[intros,3],cex=1,col="red")

# dispersal routes statistics

obs[[2]] # total routes length in DD
obs[[3]] # median dispersal rate in DD/yr
obs[[4]] # number of outcoming nodes
# }