Introduction

I used the “2016 Global Ecological Footprint” dataset provided by the Global Footprint Network to illustrate the highest ecological footprints (expressed in global hectares per capita) per country in 2016.

First, I selected the top 10 countries according to their ecological footprint: those are the ones, according to the data, that consume the most compared to what they produce in terms of resources (i.e. running an ecological deficit).

1. Importing dataset and cleaning names

df <- read_csv("countries.csv") %>% 
  clean_names()

head(df)
## # A tibble: 6 x 21
##   country region population_mill…   hdi gdp_per_capita cropland_footpr…
##   <chr>   <chr>             <dbl> <dbl> <chr>                     <dbl>
## 1 Afghan… Middl…            29.8   0.46 $614.66                    0.3 
## 2 Albania North…             3.16  0.73 $4,534.37                  0.78
## 3 Algeria Africa            38.5   0.73 $5,430.57                  0.6 
## 4 Angola  Africa            20.8   0.52 $4,665.91                  0.33
## 5 Antigu… Latin…             0.09  0.78 $13,205.10                NA   
## 6 Argent… Latin…            41.1   0.83 $13,540.00                 0.78
## # … with 15 more variables: grazing_footprint <dbl>, forest_footprint <dbl>,
## #   carbon_footprint <dbl>, fish_footprint <dbl>,
## #   total_ecological_footprint <dbl>, cropland <dbl>, grazing_land <dbl>,
## #   forest_land <dbl>, fishing_water <dbl>, urban_land <dbl>,
## #   total_biocapacity <dbl>, biocapacity_deficit_or_reserve <dbl>,
## #   earths_required <dbl>, countries_required <dbl>, data_quality <chr>

2. Selecting top 10 countries according to their ecological footprint and plotting

# Selecting top 10 countries and arranging by ecological footprint

top_10 <- top_n(df, n=10, total_ecological_footprint) %>% 
  arrange(desc(total_ecological_footprint))

# Plotting

ggplot(top_10,aes(x= reorder(country, -total_ecological_footprint), y=total_ecological_footprint, fill = total_ecological_footprint))+
  scale_fill_gradient(
  low = "#067736",
  high = "#EDBF2B",
  space = "Lab",
  na.value = "grey50",
  guide = "colourbar",
  aesthetics = "fill"
)+ 
  geom_col()+
  theme_economist()+
  theme(axis.text.x = element_text(angle = 40, vjust = 1, hjust =1),
        legend.position = "none")+
 
  # Changing labels
  
  labs(y = "Total Ecological Footprint in global hectares",
       x = '',
       title = "Highest Ecological Footprint Countries in 2016",
       caption = 'Source: 2016 Global Ecoogical Footprint, Global Footprint Network')

3. Observations and comments

This visualization reflects the “Country Overshoot Day” illustrations provided by the Footprint Network (2020 publication below) pretty well.

.

Observing it, I couldn’t help thinking about the correlation between a country’s development and its ecological footprint: how much does a country’s ecological footprint per capita grow along with its Human Developement Index (HDI)?

4. Investigating the correlation between HDI and national ecological footprint in 2016

ggplot(df, aes(x=hdi, y=total_ecological_footprint))+
  geom_point()+
  geom_smooth(method = "lm", se = FALSE)+
  theme_economist()+
  labs(y = "Total Ecological Footprint in global hectares",
       x = 'Human Development Index',
       title = "Ecological Footprint according to HDI",
       caption = 'Source: 2016 Global Ecoogical Footprint, Global Footprint Network')
## `geom_smooth()` using formula 'y ~ x'
## Warning: Removed 16 rows containing non-finite values (stat_smooth).
## Warning: Removed 16 rows containing missing values (geom_point).

5. Observations and comments

As assumed previously, there is a positive correlation between a country’s HDI and its population’s demand on nature compared to the available biocapacity.

The graph exemplifies the challenge of creating a high level of human well-being without depleting the planet’s or a region’s ecological resource base. Some models predict lower consumption and a more efficient use of resources over time. A few countries (e.g. Germany) have reduced their ecological footprint from consumption per capita since the 1990s. For now, however, these decreases do not compensate for the overall rise in ecological footprint.