R rollapply bottom to top?

I'm trying to run rollapply from the bottom of my data.frame up to the top of my data.frame. Basically the last row in the data.frame (RBH) is the final measurement for a given subject in 2012. I then need to subtract each annual measurement in the previous years to calculate what the individual's size would have been each year prior.

Sample data.frame:

df1 <- structure(c(1.62, 3.96, 4.89, 6.61, 8.79, 
                   57.15, 2.43, 5.58, 7.2, 9.3, 
                   11.87, 66.6, 1.47, 3.49, 4.32,
                   NA, NA, 60.75),
                 .Dim = c(6L, 3L),
                 .Dimnames = list(c("2008", "2009", "2010","2011", "2012","RBH"),
                                  c("Tree001", "Tree002", "Tree003")))

Intended output:

Tree001 <- c(31.28, 32.90, 36.86, 41.75, 48.36, 57.15)    
Tree002 <- c(29.62, 32.05, 37.63, 44.83, 54.13, 66.00)    
Tree003 <- c(51.47, 52.94, 56.43, 60.75, NA, NA)    
df2 <- data.frame(Tree001, Tree002, Tree003)    
rownames(df2) <- 2007:2012

I've tried running rollapply backwards from a suggestion I found at Rollapply() backwards in R , but I didn't get the intended output. It came out as a list instead of a data.frame, and subtracted each value from the current cell, not from the running value.

Code I tried:

if ( !require(zoo) ) print(" Need pkg:zoo for rollapply")
df3 <- rollapply(df1[length(df1):1], width=2, diff, fill=NA, partial=T)    
df3    
 [1]     NA     NA     NA  -0.83  -2.02  65.13 -54.73  -2.57  -2.10  -1.62    
[11]  -3.15  54.72 -48.36  -2.18  -1.72  -0.93  -2.34     NA

Any suggestions would be appreciated.

This is closer to what you want:

df1[is.na(df1)] = 0 ##This is how you're actually treating it!
df1 = data.frame(df1)


> df2 = apply(df1[nrow(df1):1,], 2, function(x) c(x[1], x[1]-cumsum(x[-1])))
> df2 = df2[nrow(df2):1,]
> df2
     Tree001 Tree002 Tree003
2008   31.28   30.22   51.47
2009   32.90   32.65   52.94
2010   36.86   38.23   56.43
2011   41.75   45.43   60.75
2012   48.36   54.73   60.75
RBH    57.15   66.60   60.75