[setgree]

> The graph shows that those low p-values are more likely to be in papers

This is an important distinction, in my experience [0].

Many papers will report a p-value only if it is below a significance threshold, otherwise they will report "n.s." (no statistic) or will give a range (e.g. p > .1). This just means that in addition to pressure to shelve insignificant results, publication bias also manifests as a tendency to emphasize and carefully report significant findings, while mentioning in passing those that don't meet whatever threshold.

[0] I happen to be working on a meta-analysis of psychology and public health papers at the moment. One paper that we're reviewing constructs 32 separate statistical models, reports that many of the results are not significant, and then discusses the significant results at length.

[thaumasiotes]

> Many papers will report a p-value only if it is below a significance threshold, otherwise they will report "n.s." (no statistic) or will give a range (e.g. p > .1).

But the oddity here is a pronounced trend in the reported p-values that meet the significance threshold. The behavior you mention cannot create that trend.