[2D fourier transform]: Most people can't explain this
The scaling property of the Fourier transform tells you that if  $\mathcal{F}(x(t)) = X(f)$, then  $\mathcal{F}(x(at)) = \frac{1}{|a|}X(\frac{f}{a})$, with $a\neq 0$. So when you dilate in time, you contract in frequency, and vice-versa.

Now, for continuous 1D signals, the Fourier transform of a uniform box will be a cardinal sine. If you dilate the box, the cardinal sine will be contracted. This could be coarsely observed from the location of its zeros.

Here, you deal with a 2D discrete signal. So the result should be a discrete (or periodic) version of a cardinal sine. Its spread in one direction can be visually estimated by the horizontal and vertical black lines, since your 2D discrete Fourier transform is separable.

Now look at one horizontal line in your red boxes. The blackest dots that separate the horizontal gray/white bumps have the same location on both images. Now look at several lines. The black dots align vertically. So you see that the vertical lines are spaced in the same manner on the top and the bottom, which is exactly what you expect.

The result in the vertical direction is the controverse. Horizontal black lines are closer to each other in the bottom row.

What is sometimes misleading in Fourier plots is that some features in the frequency domain look orthogonal to those in the spatial domain. You can see more of this effect in An Intuitive Explanation of Fourier Theory.

If you want to gain additional conviction, crop a line from each spatial image, and an horizontal line from the spectrum, and superimpose the plots.