Table S2: Number of sites per combination of land-use LU and land-use intensity LUUI class for all the collated sources. Table S3: Variance inflation factors (VIF) for the variables used to model site-level compositional intactness. GVIF is the generalized variance inflation factor calculated as , which gives an indication of how much the standard errors are likely to be in inflated due to collinearity between explanatory variables. VIF was calculated using the corvif function of Zuur et al. (2009) Figure S1: Projected global net change in compositional intactness from 1500 to 2095 in Colombia. Grey shading (historical) and error bars (future) show ± 95% confidence intervals. Future projections are based on the four RCP scenarios (Table 2). Uncertainty estimates are based only on the modeled coefficients. Estimates of uncertainty were not available for the land-use projections.
Table S2: Number of sites per combination of land-use LU and land-use intensity LUUI class for all the collated sources. Table S3: Variance inflation factors (VIF) for the variables used to model site-level compositional intactness. GVIF is the generalized variance inflation factor calculated as , which gives an indication of how much the standard errors are likely to be in inflated due to collinearity between explanatory variables. VIF was calculated using the corvif function of Zuur et al. (2009) Figure S1: Projected global net change in compositional intactness from 1500 to 2095 in Colombia. Grey shading (historical) and error bars (future) show ± 95% confidence intervals. Future projections are based on the four RCP scenarios (Table 2). Uncertainty estimates are based only on the modeled coefficients. Estimates of uncertainty were not available for the land-use projections.