Quantifying and categorising national extinction-risk footprints.

Biodiversity, essential to delivering the ecosystem services that support humanity, is under threat. Projections show that loss of biodiversity, specifically increases in species extinction, is likely to continue without significant intervention. Human activity is the principal driver of this loss, generating direct threats such as habitat loss and indirect threats such as climate change. Often, these threats are induced by consumption of products and services in locations far-removed from the affected species, creating a geographical displacement between cause and effect. Here we quantify and categorise extinction-risk footprints for 188 countries. Seventy-six countries are net importers of extinction-risk footprint, 16 countries are net exporters of extinction-risk footprint, and in 96 countries domestic consumption is the largest contributor to the extinction-risk footprint. These profiles provide insight into the underlying sources of consumption which contribute to species extinction risk, a valuable input to the formulation of interventions aimed at transforming humanity's interactions with biodiversity.

Impacts of climate change and extreme weather on food supply chains cascade across sectors and regions in Australia.

Disasters resulting from climate change and extreme weather events adversely impact crop and livestock production. While the direct impacts of these events on productivity are generally well known, the indirect supply-chain repercussions (spillovers) are still unclear. Here, applying an integrated modelling framework that considers economic and physical factors, we estimate spillovers in terms of social impacts (for example, loss of job and income) and health impacts (for example, nutrient availability and diet quality) resulting from disruptions in food supply chains, which cascade across regions and sectors. Our results demonstrate that post-disaster impacts are wide-ranging and diverse owing to the interconnected nature of supply chains. We find that fruit, vegetable and livestock sectors are the most affected, with effects flowing on to other non-food production sectors such as transport services. The ability to cope with disasters is determined by socio-demographic characteristics, with communities in rural areas being most affected.

A metric for spatially explicit contributions to science-based species targets.

The Convention on Biological Diversity's post-2020 Global Biodiversity Framework will probably include a goal to stabilize and restore the status of species. Its delivery would be facilitated by making the actions required to halt and reverse species loss spatially explicit. Here, we develop a species threat abatement and restoration (STAR) metric that is scalable across species, threats and geographies. STAR quantifies the contributions that abating threats and restoring habitats in specific places offer towards reducing extinction risk. While every nation can contribute towards halting biodiversity loss, Indonesia, Colombia, Mexico, Madagascar and Brazil combined have stewardship over 31% of total STAR values for terrestrial amphibians, birds and mammals. Among actions, sustainable crop production and forestry dominate, contributing 41% of total STAR values for these taxonomic groups. Key Biodiversity Areas cover 9% of the terrestrial surface but capture 47% of STAR values. STAR could support governmental and non-state actors in quantifying their contributions to meeting science-based species targets within the framework.

Global socio-economic losses and environmental gains from the Coronavirus pandemic.

On 3 April 2020, the Director-General of the WHO stated: "[COVID-19] is much more than a health crisis. We are all aware of the profound social and economic consequences of the pandemic (WHO, 2020)". Such consequences are the result of counter-measures such as lockdowns, and world-wide reductions in production and consumption, amplified by cascading impacts through international supply chains. Using a global multi-regional macro-economic model, we capture direct and indirect spill-over effects in terms of social and economic losses, as well as environmental effects of the pandemic. Based on information as of May 2020, we show that global consumption losses amount to 3.8$tr, triggering significant job (147 million full-time equivalent) and income (2.1$tr) losses. Global atmospheric emissions are reduced by 2.5Gt of greenhouse gases, 0.6Mt of PM2.5, and 5.1Mt of SO2 and NOx. While Asia, Europe and the USA have been the most directly impacted regions, and transport and tourism the immediately hit sectors, the indirect effects transmitted along international supply chains are being felt across the entire world economy. These ripple effects highlight the intrinsic link between socio-economic and environmental dimensions, and emphasise the challenge of addressing unsustainable global patterns. How humanity reacts to this crisis will define the post-pandemic world.

Global consumption and international trade in deforestation-associated commodities could influence malaria risk.

Deforestation can increase the transmission of malaria. Here, we build upon the existing link between malaria risk and deforestation by investigating how the global demand for commodities that increase deforestation can also increase malaria risk. We use a database of trade relationships to link the consumption of deforestation-implicated commodities in developed countries to estimates of country-level malaria risk in developing countries. We estimate that about 20% of the malaria risk in deforestation hotspots is driven by the international trade of deforestation-implicated export commodities, such as timber, wood products, tobacco, cocoa, coffee and cotton. By linking malaria risk to final consumers of commodities, we contribute information to support demand-side policy measures to complement existing malaria control interventions, with co-benefits for reducing deforestation and forest disturbance.

Supply-side carbon accounting and mitigation analysis for Beijing-Tianjin-Hebei urban agglomeration in China.

Cities play an important role in controlling climate change. Previous 'city-scale studies' have investigated consumption-based emission accounting for demand-side mitigation analysis. However, to date very few studies have presented income-based emissions accounting for supply-side mitigation strategies at the level of an urban agglomeration. To fill this gap, this research begins by accounting for the income-based carbon footprint of the Beijing-Tianjin-Hebei (BTH) urban agglomeration. The 14 cities that make up the BTH region were grouped into 4 types in order to analyse the emission patterns of each and to identify both labour-intensive and carbon-efficient sectors. The results from this analysis are presented in a number of heatmaps, which show emission patterns, labour-capital ratios and carbon efficiencies. The industry relocation among the 14 cities is then discussed with regards to the Beijing-Tianjin-Hebei Coordinated Development Strategy. The results indicate that the service sector of Beijing, several mining sectors of resource-oriented cities and the electricity production for all of the cities are the most carbon-intensive sectors from an income-based perspective; the labour-intensive sectors are typically carbon-efficient, and the combination of supply-side carbon emissions, carbon efficiency and labour-to-capital ratio helps identify the key sectors for providing policy-makers the direction of industrial adjustment and relocation.

Compiling and using input-output frameworks through collaborative virtual laboratories.

Compiling, deploying and utilising large-scale databases that integrate environmental and economic data have traditionally been labour- and cost-intensive processes, hindered by the large amount of disparate and misaligned data that must be collected and harmonised. The Australian Industrial Ecology Virtual Laboratory (IELab) is a novel, collaborative approach to compiling large-scale environmentally extended multi-region input-output (MRIO) models. The utility of the IELab product is greatly enhanced by avoiding the need to lock in an MRIO structure at the time the MRIO system is developed. The IELab advances the idea of the "mother-daughter" construction principle, whereby a regionally and sectorally very detailed "mother" table is set up, from which "daughter" tables are derived to suit specific research questions. By introducing a third tier - the "root classification" - IELab users are able to define their own mother-MRIO configuration, at no additional cost in terms of data handling. Customised mother-MRIOs can then be built, which maximise disaggregation in aspects that are useful to a family of research questions. The second innovation in the IELab system is to provide a highly automated collaborative research platform in a cloud-computing environment, greatly expediting workflows and making these computational benefits accessible to all users. Combining these two aspects realises many benefits. The collaborative nature of the IELab development project allows significant savings in resources. Timely deployment is possible by coupling automation procedures with the comprehensive input from multiple teams. User-defined MRIO tables, coupled with high performance computing, mean that MRIO analysis will be useful and accessible for a great many more research applications than would otherwise be possible. By ensuring that a common set of analytical tools such as for hybrid life-cycle assessment is adopted, the IELab will facilitate the harmonisation of fragmented, dispersed and misaligned raw data for the benefit of all interested parties.

Mapping the structure of the world economy.

We have developed a new series of environmentally extended multi-region input-output (MRIO) tables with applications in carbon, water, and ecological footprinting, and Life-Cycle Assessment, as well as trend and key driver analyses. Such applications have recently been at the forefront of global policy debates, such as about assigning responsibility for emissions embodied in internationally traded products. The new time series was constructed using advanced parallelized supercomputing resources, and significantly advances the previous state of art because of four innovations. First, it is available as a continuous 20-year time series of MRIO tables. Second, it distinguishes 187 individual countries comprising more than 15,000 industry sectors, and hence offers unsurpassed detail. Third, it provides information just 1-3 years delayed therefore significantly improving timeliness. Fourth, it presents MRIO elements with accompanying standard deviations in order to allow users to understand the reliability of data. These advances will lead to material improvements in the capability of applications that rely on input-output tables. The timeliness of information means that analyses are more relevant to current policy questions. The continuity of the time series enables the robust identification of key trends and drivers of global environmental change. The high country and sector detail drastically improves the resolution of Life-Cycle Assessments. Finally, the availability of information on uncertainty allows policy-makers to quantitatively judge the level of confidence that can be placed in the results of analyses.

Frameworks for comparing emissions associated with production, consumption, and international trade.

While the problem of climate change is being perceived as increasingly urgent, decision-makers struggle to agree on the distribution of responsibility across countries. In particular, representatives from countries hosting emissions-intensive exporting industries have argued that the importers of emissions-intensive goods should bear the responsibility, and ensuing penalties. Indeed, international trade and carbon leakage appear to play an increasingly important role in the carbon emissions debate. However, definitions of quantities describing the embodiment of carbon emissions in internationally traded products, and their measurement, have to be sufficiently robust before being able to underpin global policy. In this paper we critically examine a number of emissions accounting concepts, examine whether the ensuing carbon balances are compatible with monetary trade balances, discuss their different interpretations, and highlight implications for policy. In particular, we compare the emissions embodied in bilateral trade (EEBT) method which considers total trade flows with domestic emission intensities, with the multi-regional input-output (MRIO) method which considers trade only into final consumption with global emission intensities. If consumption-based emissions of different countries were to be compared, we would suggest an MRIO approach because of the global emissions coverage inherent in this method. If trade-adjusted emission inventories were to be compared, we would suggest an EEBT approach due to the consistency with a monetary trade balance.