Survivorship bias is the idea that there might be an unknown filter that's filtering the data before you even get to see it. In the case of the plane, that's referring to a story from WW2, where planes returning from combat were recorded for where they were shot. Famously, the recommendation was to thicken the armor on places where the planes weren't hit, because the "unknown filter" in this case is that if the plane were shot down, then you would never be able to record where bullets hit on that plane. Hence, the most important areas of the plane are actually the places that weren't shot in the surviving planes.
In the case of the graph, this is a graph compiled from looking through a lot of papers and recording how significant a result is. Essentially a measure of how "interesting" the data is. Here, the unknown filter is that if a result weren't interesting, then it wouldn't get published. As a result, there's a gap right in the middle of the graph, which is where the data is least interesting. In recent times, there's been a philosophical argument that even uninteresting data should be published, so that at least it would prevent wasted time from multiple people attempting to do the same thing, each unaware that it's already been done before. Hence the reason why people made the graph in the first place
No reason, I suppose. In my opinion it seems to just be a holdover from the previous systems of publishing. The prestige of a journal is ranked based on how often it gets cited (or in other words, how influential the papers are within the journal). Publishing insignificant/uninteresting data would lower a journal's average citation count, which would make it seem less prestigious than other journals. Hence journals are incentivized to only publish interesting data. It's a shitty system that everyone knows is shitty but nobody has a good solution for how to fix it