I think it's really important that the model for users' scores (reputation) is changed. Specifically, I think the score should be discounted over time such that more weight is given to points that have been awarded recently.
(This applies generally to gamification and has been in the back of my mind for a while. Perhaps this has been suggested/considered before, but I couldn't find any related questions on here, so (encouraged by Jeff's latest blog post) here goes...)
Let us assume that an incentive for users to post answers to questions is to gain points. As it stands, the reward given to new users is severely diluted - the value associated with a point in the early days is much higher than the value of a point today.
My proposed solution in its simplest form would be to calculate a user's reputation based on the number of points they have been awarded in the last month. Or, preferably, a more complicated algorithm that was calculated over a longer period:
1.0 * [points from last month] + 0.9 * [points from month before last] + 0.8 * [points from month before month before last] + ...
Of course, this could be calculated more granularly, or with a non-linear function.
This would provide an incentive both for old members (to retain their score) and new members (making it possible to catch up with users on the leader board). The playing field would be levelled and the risk of stagnation reduced.
EDIT: Just found this question which looks similar.