The title of the article is (my emphasis):
Linking niche size and phylogenetic signals to predict future soil microbial relative abundances.
To look at bacterial abundance, they generated models that look at factors that affect bacterial abundance. In this case, this is a mathematical model that is used to describe the effect (emphasis mine):
Whereas a number of multivariate methods are largely descriptive and more appropriate for exploratory analyses, SEM is able to test a network of causal hypotheses and is recommended for evaluation of multivariate hypotheses (Grace, 2006; Grace et al., 2012). Specifically, we used SEM because it allows the evaluation of simultaneous influences...
...The method is thus appropriate for establishing probable causality at the system (for example, climate-vegetation-soil-bacteria), rather than the individual level (for example, climate–bacteria).
So, they are generating a model that looks specifically at establishing a causal model for bacterial abundance only. This model does not seek to establish causality for other factors, such as vegetation cover, even though this might be related to some of the factors being investigated. In fact the models explain mathematically only the significant factors for bacterial abundance, and factors that are left out of the model have no effect in the system being described - basically Occam's razor being applied.
You could indeed examine vegetation cover using a variables used in this system, but you would need to establish a whole new mathematical model to do so, and you might well find that the variables are different or need other factors not shown in this model.