Random effects specification in gamlss in R

I would like to use the gamlss package for fitting a model benefiting from more available distributions in that package. However, I am struggling to correctly specify my random effects or at least I think there is a mistake because if I compare the output of a lmer model with Gaussian distribution and the gamlss model with Gaussian distribution output differs. If comparing a lm model without the random effects and a gamlss model with Gaussian distribution and without random effects output is similar.

I unfortunately cannot share my data to reproduce it. Here my code:

df <- subset.data.frame(GFW_food_agg, GFW_food_agg$fourC_area_perc < 200, select = c("ISO3", "Year", "Forest_loss_annual_perc_boxcox", "fourC_area_perc", "Pop_Dens_km2", "Pop_Growth_perc", "GDP_Capita_current_USD", "GDP_Capita_growth_perc", 
                                                                                     "GDP_AgrForFis_percGDP", "Gini_2008_2018", "Arable_land_perc", "Forest_loss_annual_perc_previous_year", "Forest_extent_2000_perc"))
fourC <- lmer(Forest_loss_annual_perc_boxcox ~ fourC_area_perc + Pop_Dens_km2 + Pop_Growth_perc + GDP_Capita_current_USD + 
              GDP_Capita_growth_perc + GDP_AgrForFis_percGDP + Gini_2008_2018 + Arable_land_perc + Forest_extent_2000_perc + (1|ISO3) + (1|Year), 
            data = df)
summary(fourC)
resid_panel(fourC)


df <- subset.data.frame(GFW_food_agg, GFW_food_agg$fourC_area_perc < 200, select = c("ISO3", "Year", "Forest_loss_annual_perc_boxcox", "fourC_area_perc", "Pop_Dens_km2", "Pop_Growth_perc", "GDP_Capita_current_USD", "GDP_Capita_growth_perc", 
                                                                                     "GDP_AgrForFis_percGDP", "Gini_2008_2018", "Arable_land_perc", "Forest_loss_annual_perc_previous_year", "Forest_extent_2000_perc"))
df <- na.omit(df)
df$ISO3 <- as.factor(df$ISO3)
df$Year <- as.factor(df$Year)
fourC <- gamlss(Forest_loss_annual_perc_boxcox ~ fourC_area_perc + Pop_Dens_km2 + Pop_Growth_perc + GDP_Capita_current_USD + 
                  GDP_Capita_growth_perc + GDP_AgrForFis_percGDP + Gini_2008_2018 + Arable_land_perc + Forest_extent_2000_perc + random(ISO3) + random(Year), 
                data = df, family = NO, control = gamlss.control(n.cyc = 200))
summary(fourC)
plot(fourC)

How do the random effects need to be specified in gamlss to be similar to the random effects in lmer?

If I specify the random effects instead using

re(random = ~1|ISO3) + re(random = ~1|Year)

I get the following error: Error in model.frame.default(formula = Forest_loss_annual_perc_boxcox ~ : variable lengths differ (found for 're(random = ~1 | ISO3)')