I agree dynamic languages result in smaller codebases, but that's only because they tend to be so much more concise than most statically typed languages.
Also, as for large and complex projects done by distributed teams, I don't have to point much further than Django or Plone to prove dynamic typing works well in that context.
The plural of anecdote is not proof. Heck, it's not even data.
Heck, the examples you give aren't even anecdotes. They're just name-dropping. One would have to be pretty familiar with the codebases in question and the history of their development in order to be able to give a clear assessment of what, if any, impact dynamic typing might have had on them.
Fair enough. They prove large projects built by distributed teams are possible in at least one dynamic language.
There was a time I was familiar with both codebases (I have some catching up to do) and that's why I mentioned them. Both projects carry heavy heritage and are experiencing huge pressures to evolve and both are doing very well (from what I hear on the dev lists).
Sure, but even then one merely has an observation that there are these two large projects that are written in dynamic languages and are being successfully maintained.
That doesn't imply that they are being successfully maintained because they are written in dynamic languages, or despite being written in dynamic languages. And of course there's also the possibility that static vs. dynamic is a wash and doesn't really have an impact at all. Or that the potential impact of going with static or dynamic is heavily influenced by other factors - does the static language have type inference, does the dynamic language support duck typing, stuff like that.
Long story short, correlation does not, in and of itself, imply causation.
In any case, it's mostly an apples to oranges comparison. Observing from my heavily biased toward web applications experience, there aren't as many Python codebases as there are Java ones at least in part because you can do a lot more with a small Python codebase than you can do with a similarly sized Java codebase.
Also, as for large and complex projects done by distributed teams, I don't have to point much further than Django or Plone to prove dynamic typing works well in that context.