Hi Fiorella,
AKDE predicts future space use under the assumption that the current movement behavior continues. KDE does the same thing, but with the further assumption that the points were sampled IID.
When you only observe a few range crossings and your effective sample size is very low, AKDE's predicted area will be noticeably larger than the observed data, as there is a very good chance that the individual will go somewhere you haven't observed in the future, but the corresponding uncertainty estimate will be comparably large, because you don't really know where that will be. KDE will actually look similar if your nominal sample size were the effective sample size you estimated when running the AKDE analysis.
and other methods (that assume IID data or estimate the wrong target distribution) will fail to cross validate into the future.
If you want to assess how good you expect this prediction to be, I would look at how well the theoretical and empirical variograms match up.
Best,
Chris