We prepared a series of maps visualizing the foreign Ecological Footprint of each of 187 countries. For most countries the majority of their Footprint falls within their borders. However for these maps we looked exclusively at the foreign footprint. This allows a clearer understanding of the occurence of environmental burden shifting: a phenomenon in which environmentally impactful production is shifted abroad, in the worst case to more ecologically sensitive areas.
For each country C we calculated the spatial Ecological Footprint embodied in imports. For example, imported beef has a Footprint consisting of some hectares of pasture land, some hectares of cropland (to grow maize or soya for feed), and some associated GHG emissions due to bovine methane emissions, transportation, butchering, etc. These embodied Ecological Footprints were calculated using the National Ecological Footprint and Biocapacity Accounts published by Global Footprint Network and a new high-resolution global trade database recently published by the University of Sydney. The result is a dataset documenting the total Ecological Footprint, in hectares, each country C exerts in each of its trade partners. Using the same approach we also calculated the amount of water use associated with exports (also called "virtual water" or the Water Footprint), and the number of Red-Listed threatened species associated with export products.
The Water Footprint of each country C in each supplier country S is visualized by illuminating (lightening or darkening) a map of S’s surface freshwater in proportion to percent of S’s fresh water used for production of goods bound for C. The Scarce Water Footprint is calculated and visualized the same way but only considers the water within each country S that is considered to be scarce.
The Biodiversity Footprint was calculated by linking threatened species records from the IUCN Red List of Threatened and Endangered Species to the production activities driving those threats (e.g. deforestation for palm oil production, bottom trawling, etc.) and then tracing the implicated commodities to final consumers using the Eora trade database. Flows of biodiversity-implicated commodities are visualized using a flow map, where brighter and thicker paths reflect larger flows of biodiversity-implicated products.
These embodied Ecological Footprints from each origin country are visualized using an NPP-weighted scatter-fill algorithm. For example, USA imports timber from Brazil with a total Footprint of X hectares of forest land. This represents y% of Brazil’s forestry exports. After logarithmically scaling the entire trade dataset (to improve the visibility of smaller countries) we used an NPP-weighted scatter-fill algorithm to proportionally illuminate Brazil’s forests. With the NPP weighting scheme more bioproductive areas within Brazil appear denser and brighter than areas with lower NPP. Coloration reflects land use: greens show the Footprint within forested areas; purples show the imported Footprint on pasture and grazing lands, and light blues show the Footprint on farmland. CO2 emissions embodied in imports are not visualized using the same scatter-fill approach but instead are directly mapped to urbanized areas and colored using a red-to-yellow intensity scale.
Trade data are from the Eora trade database1. The Water and Scarce Water Footprint data are from the FAO AQUATSTAT database and the scarcity weighting calculation is described in 2. Biodiversity Footprints are taken from the study described in 3. Data on the Ecological Footprint of production are from Global Footprint Network 4 and were then linked to the Eora database to calculated embodied flows.
Land cover data are from XXXX (for forest, crop, and pasture land); YYY (for urbanized areas); and the global surface freshwater maps are from ESRI. NPP data are from ZZZ.
These visualizations were prepared by Daniel Moran at University of Sydney and Sharolyn Anderson at the University of South Australia. The Ecological Footprint data were provided by Mathis Wackernagel, Katsunori Iha, and Elias Lazarus at Global Fooprint Network. The international trade data were taken from the Eora MRIO database created by Manfred Lenzen, Keiichiro Kanemoto, Arne Geschke, and Daniel Moran at the University of Sydney.