.Fortran()

I have had a related conversation about .Fortran with Brian Ripley
(undercover), and I have learnt some valuable things, for instance
about English language. As a non-English speaking person I had hastily
assumed that `may' in ?.Fortran is more or less synonymous with `can',
but it seems that it rather is synonymous with `may not'. Now I have

two new valuable pieces of information:

ripley at stats.ox.ac.uk said:

A properly working version of g77 should work on some platforms
(including Linux), but not others (including Windows).

This explains why my plug-in Fortran library worked in Linux (RH7.1,
with gcc updates), but not when my mate tried that in Windows.

And this is the second piece:

ripley at stats.ox.ac.uk said:

BTW, no one said Fortran I/O would work, and it sometimes is a
problem.

This means that I have a problem. Does anybody here have a solution?

My problem is that there are plenty of legacy files in our field which
are written with so-called Cornell Ecology Programs (CEP) formats.
These are Fortran formatted files, and the actual format used is
written in the file (on its second line, or, I should say, `card'). I
thought that a nice solution was to write a Fortran program[me] to read
these files and pass the data and row and column names back to R which
then makes these into a data.frame. It was surprisingly easy and worked
beautifully in Linux, but crashed R in Windows. I made a small test
package in Fortran which made nothing but opened a file and read a
line. This crashed in Windows (I don't have access to Windows, so these
tests were made in Florida, and I never saw what happened). So it seems
that this is not portable. Now comes the question (finally, I hope
somebody got this far): Is there a R pluggable module to interpret
Fortran format (which may be tricky), so that I could read these lines
with plain C or plain R? (I once made a similar program[me] using
Scientific Python module in Python, but that was much more tricky than
using direct Fortran, and failed in some test files).

Another alternative is to let it be and make a separate stand-alone
program to change these files into, say, csv and then read them into R.
However, it was so nice when I suddenly had access to tens of my old
files within an R session, and I would like other people to share my
joy (sounds like a cheap thrill). Naturally, this works now in my
system, so my concern is rather abstract.