Boxplots (and violin plots, which I prefer because they convey more information, and the raw observations themselves) visualize observations and summary information of the observations. Barplots, as used in these communities, visualize parameter estimates. Typically, as in the example you give, the estimate is simply the group mean, so there actually is little difference, and the choice is down to a community's traditions and expectations.
However, suppose there is one grouping factor, and also one numerical covariate. Boxplots or violin plots can plot the data and their means per group. But we would lose the information about the covariate. A simple way of giving a visual summary would be to plot three bars per group: one with the estimated response within the group with the covariate at its 25% quantile, one with the covariate at its median and one with the covariate at its 75%. In each case, we can also add a whisker to show the standard error of the estimate. Note that boxplots can't convey this kind of information.
However, I would still say that a simple dot with whiskers would still be superior to the bar plot, if only because of the within-the-bar-bias that barplots induce. And in any case, one must note in the figure caption what the whiskers refer to - are they the estimate plus one standard error of the estimate (e.g., SEM), or plus two standard errors, or are they the standard deviation of the raw data being plotted, or what?