20 perennial plants

The following code will download the 461 projection matrices from 20 plant populations in

Ellis, MM, JL. Williams, P Lesica et al 2012. Matrix population models from 20 studies of perennial plant populations. Ecology 93:951

url <-  "http://esapubs.org/archive/ecol/E093/083/Transition_Matrices.txt"
x <- read.delim(url, stringsAsFactors=FALSE)
table(x$SPP)
ARFE ASSC ASTY CIPI CYFA DIFR ERCU GEPN HARA HOCO HYCU LAVE LISC LOCO NEMA PHEM PHIN SIAC SISP TRGR 
  14   31   35   35    9   50   40    7   64    6   30   29   15   10    5    5    5   20   12   39 

Details about species, populations and stage classes are included in the metadata. Some R code is also included to convert the MATLAB matrix strings, which I have simplified below (remove ; [ ], split the string, convert to number and then format as matrix using matrix2 in popbio package).

convert_mx <- function(mx, ...){
 mx <- as.numeric(strsplit(gsub(";|\\[|]", "", mx), " ")[[1]])
 matrix2(mx, ...)  # option to add stage class names
}

stages<-  c("germinants", "seedlings", "1-leaf", "small 3-leaf", "large 3-leaf", "reproductive")
trgr <- subset(x, SPP=="TRGR")
A <- lapply(trgr$Mx,  convert_mx,  stages)
names(A) <- paste( substr(trgr$POP, 6,7), substr(trgr$YR, 3,4), sep="")
A[[1]]
             germinants seedlings     1-leaf small 3-leaf large 3-leaf reproductive
germinants        0.000     0.000 0.00000000    0.0000000   0.00000000   12.9099600
seedlings         0.194     0.000 0.00000000    0.0000000   0.00000000    0.0000000
1-leaf            0.000     0.321 0.82051282    0.0000000   0.00000000    0.0000000
small 3-leaf      0.000     0.000 0.07051282    0.9047619   0.07692308    0.0000000
large 3-leaf      0.000     0.000 0.00000000    0.0952381   0.80769231    0.2884615
reproductive      0.000     0.000 0.00000000    0.0000000   0.11538462    0.7115385

image2(A[[1]], mar=c(1,7,7,1))
sapply(A[1:7], lambda)
     DC98      DC99      DC00      DC01      WH99      WH00      WH01 
1.0336861 1.0407601 0.9696774 0.9647957 0.9910988 0.8998307 1.0279880