Is there something that R with the ape package can do better than Bioperl? In other words, should I invest in R or stick with my knowledge of C and Perl?
I was pretty good at BioPerl before I learned R, and I've gotten huge (and growing) returns on my investment in learning R. BioPerl and R/Bioconductor are not really rivals, rather complementary. I recommend both for optimal effectiveness.
I find BioPerl best for fast file transformations and general format munging with a low memory footprint. R is not good for this as it generally wants to (slowly) load everything into memory. R is much better at statistics and large data transformations, however.
I often do hybrid analysis where I transform data into an R readable form using BioPerl, then do the analysis in R.
The two are simply different.
If you need statistics you need R and the Bioconductor packages. If you need a quick sccipt or need to handle sequence data BioPerl is often better.
You first need to define what type of tasks will you'll want to be good at. There is no single tool or approach that does the job best, bioinformatics is a huge field. In a way your question is like asking: If I want to be a good doctor should I learn more about surgery or ophthalmology?
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The Biostrings package in Bioconductor can also be used when working with large sequences (whole chromosomes for instance). Still, I agree with Chris that Bioperl and R/Bioc are two different tools.