Environmental predictors
We used a generalized joint attribute model for dynamic data (below) to
assess how density-dependent and independent factors contribute to the
observed changes in relative abundance of species groups over time and
their steady-state predicted abundances across multiple global change
drivers (Clark et al. 2020). We jointly estimated the influence
of snow depth, nitrogen deposition and temperature on the
density-independent growth rates of dominant, subdominant, moderate and
rare species groups both in experimentally manipulated and control plots
over time. We incorporated continuous annual environmental data as model
predictors, following the approach of Farrer et al. (2014), as
environmental data were not available at the plot level for the entirety
of the study (See supplementary methods).