estimate_indicatorNe_BG <- function (indNe_data_red)
{
    indicatorNe <- indNe_data_red %>%
      
      group_by(taxon, ) %>%
      
      summarise(n_pops = n(),
                n_pops_Ne_data_standart = sum(!is.na(Ne_combined_standart)), 
                n_pops_more_500_standart = sum(Ne_combined_standart > 500, na.rm = TRUE), 
                indicatorNe_standart = n_pops_more_500_standart/n_pops,
                
                n_pops_Ne_data_custom = sum(!is.na(Ne_combined_custom)), 
                n_pops_more_500_custom = sum(Ne_combined_custom > 500, na.rm = TRUE), 
                indicatorNe_custom = n_pops_more_500_custom/n_pops,
                
                n_pops_size_data = sum(!is.na(pop_size_class)),
                n_pops_large_size = sum(pop_size_class == "large_size"),
                percent_large_size = n_pops_large_size/n_pops_size_data,
                n_pops_medium_size = sum(pop_size_class == "medium_size"),
                percent_medium_size = n_pops_medium_size/n_pops_size_data,
                n_pops_small_size = sum(pop_size_class == "small_size"),
                percent_small_size = n_pops_small_size/n_pops_size_data,
    
        Nc_type_species = case_when(
          all(is.na(Nc_type)) ~ "No data",
          all(Nc_type == "Point_data") ~ "Point_data",
          all(Nc_type == "Range_data") ~ "Range_data",
          TRUE ~ "Mixed data"
        )
      )
}