I'm having some trouble interpreting the "random effects"-section in a summary generated from an lmer-model. I want to decide if my random effects are significant based on the output of summary, but I am not sure how to go about this. I have added my model and the summary()-output below.

A random effect is not what most of those of us who are not statisticians would expect.

Parameters associated with the particular levels of a covariate are sometimes called the “effects” of the levels. If the set of possible levels of the covariate is fixed and reproducible we model the covariate using fixed-effects parameters. If the levels that we observed represent a random sample from the set of all possible levels we incorporate random effects in the model.

There are two things to notice about this distinction between fixed-effects
parameters and random effects. First, the names are misleading because the distinction between fixed and random is more a property of the levels of the categorical covariate than a property of the effects associated with them. Secondly, we distinguish between “fixed-effects parameters”, which are indeed parameters in the statistical model, and “random effects”, which, strictly speaking, are not parameters. As we will see shortly, random effects are unobserved random variables.