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Metafor multilevel metaregression: total variance increases when moderator added?

Very difficult to diagnose what is going on without actually seeing the data. But as I said on CV: Depending on the data, the variance components may not be estimated precisely, so negative values for those kinds of pseudo-R^2 statistics are quite possible. In fact, if a particular moderator is actually unrelated to the outcomes, then in roughly 50% of the cases, the pseudo-R^2 statistic will be negative.

See also:

Lopez-Lopez, J. A., Marin-Martinez, F., Sanchez-Meca, J., Van den Noortgate, W., & Viechtbauer, W. (2014). Estimation of the predictive power of the model in mixed-effects meta-regression: A simulation study. British Journal of Mathematical and Statistical Psychology, 67(1), 30-48.

We only examined the standard mixed-effects meta-regression model with a single moderator, but found that the pseudo-R^2 statistic can be all over the place unless k is quite large.

Now you seem to have a larger number of estimates (170), but these are nested in 'only' 26 studies. So, I suspect that the estimate-level variance component is estimated fairly precisely, but not the study-level variance component. You may want to examine the profile plots (with the profile() function) and/or get (profile-likelihood) CIs of the variance components (using the confint() function). Probably the CI for the study-level variance component is quite wide.

Best,
Wolfgang