







































Ecology, Economy and Society—the INSEE Journal 1 (2): 11 –17, July 2018 

 
COMMENTARY 
 

An Integrated Framework for Achieving Sustainable 
Development Goals Around the World 
 

Jianguo Liu  
 
1. INTRODUCTION  

One of the biggest global challenges is to achieve the United Nations’ 
Sustainable Development Goals (SDGs), agreed upon by 193 countries in 
2015. Many institutions and scholars have called for creating and 
synthesising knowledge for meeting the 17 ambitious goals (e.g., no 
poverty, zero hunger, biodiversity conservation, climate mitigation). Some 
studies recognise synergies and trade-offs among the goals within a place 
(International Council for Science 2017), but little attention has been paid 
to SDG interrelationships among different places (Liu 2017). 

The United Nations states that SDGs should be achieved around the world. 
For example, SDG 1 aims ‘to end poverty in all forms everywhere’. At 
present, the scores of SDGs are vastly different among countries (Sachs et 
al. 2017). For instance, the scores of SDG 2 (Zero hunger – ‘End hunger, 
achieve food security and improved nutrition and promote sustainable 
agriculture’) range from 22 (Yemen) to 86 (Sweden) (Figure 1). The vast 
majority of countries in Africa (e.g., Sudan, Chad, and Niger) are among 
those with the lowest scores, together with some Asian countries (e.g., 
India, Pakistan, Sri Lanka) and Latin American countries (e.g., El Salvador, 
Guatemala, Honduras). Japan, the US, and western European countries are 
among those with the highest scores on SDG 2. 

To achieve SDGs around the world, an integrated framework is required 
and many fundamental questions need to be answered. For instance, how 
can the SDGs be achieved everywhere? How do efforts for achieving the 

 
 Center for Systems Integration and Sustainability, Department of Fisheries and Wildlife, 
Michigan State University, East Lansing, MI 48823, USA; liuji@msu.edu.  

Copyright © Liu 2018. Released under Creative Commons Attribution-NonCommercial 4.0 
International licence (CC BY-NC 4.0) by the author.  

Published by Indian Society for Ecological Economics (INSEE), c/o Institute of Economic 
Growth, University Enclave, North Campus, Delhi 110007.  

ISSN: 2581-6152 (print); 2581-6101 (web). 

DOI: https://doi.org/10.37773/ees.v1i2.32  

https://doi.org/10.37773/ees.v1i2.32


Ecology, Economy and Society–the INSEE Journal [12] 

Figure 1. Scores of SDG 2 (Zero hunger – ‘End hunger, achieve food security 
and improved nutrition and promote sustainable agriculture’) 

 
Data source: Sachs et al. (2017). 

goals in one place offset or enhance goal-achieving efforts in other places? I 
first introduce the metacoupling framework and then apply the framework 
to illustrate the realisation of SDG 2. 

 

2. METACOUPLING FRAMEWORK 

The new integrated framework of metacoupling (human–nature interactions 
within as well between adjacent and distant places or systems; Liu 2017) can 
help address the questions raised above. Human–nature interactions shape 
all SDGs. The metacoupling framework builds on and expands research on 
coupled human and natural systems in which human and natural 
components interact with each other (Liu et al. 2007). 

Previous research efforts on coupled human and natural systems have 
generated some useful insights, but they typically concentrate on individual 
places (e.g., cities) (Kramer et al. 2018). While some studies have indicated 
that human actions (e.g., timber harvesting and manufacturing) in one place 
can affect human well-being and the environment in other places through 
trade and emissions of pollutants and greenhouse gases (GHG) (Lambin 
and Meyfroidt 2011; DeFries et al. 2010), they do not address SDGs 
explicitly. 

The metacoupling framework encompasses not only human–nature 
interactions within a system (intracoupling) or place (e.g., country, state, 
city, county) but also interactions between adjacent systems (pericoupling) 
and between distant systems (telecoupling). Intracoupling may include 
timber harvesting and farming in a specific place. There are many types of 
pericouplings and telecouplings, such as trade, migration, species invasion, 
foreign investment, technology transfer, knowledge transfer, and tourism. 



[13] Jianguo Liu 

Furthermore, there are interactions among intracoupling, pericoupling, and 
telecoupling (Liu 2017). 

The metacoupling framework consists of five interrelated components 
(systems, flows, agents, causes, and effects). A metacoupled system includes 
two or more coupled human and natural systems linked through flows (e.g., 
movement of matter, energy, information, capital, water, organisms, and 
people). Agents (e.g., farmers, traders, animals) are decision-making entities 
that boost or impede various flows. Causes are reasons (e.g., ecological, 
hydrological, geological, socio-economic, political, cultural factors) behind a 
metacoupling that produces various effects (e.g., ecological, hydrological, 
biogeochemical, biological, socio-economic). 

 

3. APPLYING THE METACOUPLING FRAMEWORK TO SDGS 

The metacoupling framework can help organise and coordinate efforts to 
achieve SDGs within a specific place as well as between adjacent and 
distant places. For example, to eliminate hunger across the world (SDG 2), 
under the metacoupling framework one needs to consider human–nature 
interactions not only within a country at the national level but also 
relationships between the focal country and adjacent and distant countries. 
Factors within the country may include food production and food demand. 
Food demand is a function of per capita food consumption and population 
size. Food production is influenced by many factors, such as available 
arable land, yield, labour, fertilisers, pesticides, water, crop varieties, policies, 
and harvest management. Crop varieties largely determine food nutrients, 
while the use of agrochemicals such as pesticides and herbicides affects 
food safety. The costs of production may vary among contexts that have 
different conditions. 

Regarding relationships between the focal country and other countries for 
achieving SDG 2, food trade and associated factors need to be considered. 
While food security has many dimensions, food quantity is fundamentally 
important. Given the space limitation, this commentary focuses on food 
quantity. The quantity of food and related products traded (flows) depend 
on supply, affordability, demand, and relevant policies (causes). For 
importing countries, the affordability of importing food is affected by food 
price and expandable income. For exporting countries, the supply or 
availability of food is influenced by food production, infrastructure of 
transporting food from production areas to export ports, political stability, 
and other related factors. Of course, trade policy and diplomatic 
relationships between trade partners influence the amount and timing of 
food trade. Many agents are involved, such as producers, traders, 



Ecology, Economy and Society–the INSEE Journal [14] 

policymakers, and consumers. As to effects of trade, the distances between 
importing and exporting countries may affect the economic and 
environmental costs (e.g., GHG emissions) of transporting food and the 
risk of food supply reliability. Generally speaking, the more distant the trade 
partners, the higher the cost in transportation. Trade between partners also 
generates spillover effects by affecting trade with other countries and 
emitting GHGs that drive global climate change. 

All countries produce food domestically as well as import and export food; 
however, net imports or exports vary drastically with four general patterns. 
One, many countries with low scores of SDG 2 (Figure 1) import more 
than export (Food and Agriculture Organization 2018). For example, 
Yemen, which has the lowest score on SDG 2, imported 64 million tons of 
food over 2000–2013. Russia and Saudi Arabia imported even more food 
than Yemen during that period although they have somewhat higher scores 
for SDG 2. 

Second, some countries with low scores on SDG 2, such as India and 
Guatemala, export more than import. During 2000–2013, India and 
Guatemala ranked 11th and 17th in net exports. At first glance, this may not 
make sense. However, these countries may rely on food exports to earn 
foreign cash or exchange for other goods and products even at the risk of 
exacerbating domestic food insecurity. This also demonstrates the 
complexity of achieving different SDGs simultaneously. 

Third, some countries with the highest scores of SDG 2 import the largest 
amounts of food in the world. For example, Japan ranked first in total net 
food imports during 2000–2013 even though its SDG 2 scores are among 
the highest. In fact, among the top net importers, seven countries (Republic 
of Korea, UK, Belgium, Germany, the Netherlands, and Italy, in addition to 
Japan) are in the top 20 highest scores for SDG 2, including the top two 
(Belgium and Republic of Korea). Finally, some countries with high scores 
of SDG 2 export the largest amounts of food, such as the US, Brazil, 
Australia, Canada, and France. 

Thus, for food security, it is not just a matter of either producing enough 
food domestically or importing food. Each strategy may have different 
costs associated with flows of energy and materials. As many as 66 
countries are not self-sufficient under water and land constraints alone 
(Fader et al. 2013). It is common to import materials and capital to produce 
more food domestically. For example, in Brazil, most of the fertilisers used 
for food production are imported from other countries. In 2016, Brazil 
imported nearly 25 million tons (or 73 per cent) of the fertilisers for 
domestic agricultural production (Brazilian National Fertiliser Association 
2017). Of that, about 90 per cent of the potassium-rich fertiliser was 



[15] Jianguo Liu 

imported from distant countries such as Canada, Belarus, Russia, and 
Germany (Foreign Trade and Services 2017). On the other hand, some 
countries such as the US and France achieve food self-sufficiency without 
imports (Fader et al. 2013). However, such self-sufficiency requires 
sufficient land, water, nutrients, etc. There are trade-offs with both financial 
and environmental costs of using resources within a country versus 
importing materials from other countries nearby or far away. 

Food production and demand also differ within a country. For example, 
many rural areas can produce food for self-sufficiency, but cities usually 
solely or mainly depend on food produced elsewhere. Even an increase in 
urban agriculture does not produce enough food to meet the consumption 
demand of city residents (Badami and Ramankutty 2015). Thus, to meet 
food demand among different areas, substantial food movement within a 
country is also needed.  

The example above focuses on applying the metacoupling framework to 
achieve SDG 2, but general approaches are applicable to address other 
SDGs and interactions among SDGs. For instance, for SDG 14 (life under 
water), it is important to protect not only water bodies such as oceans, but 
also terrestrial systems nearby and far away, because fertilisers and 
pesticides for meeting SDG 2 from terrestrial systems can flow into aquatic 
systems (Zeng et al. 2015), thus compromising SDG 14 and other SDGs. 

 

4. CONCLUDING REMARKS 

The metacoupling framework lays a good conceptual foundation to help 
achieve SDGs around the world. To turn the conceptualisation into reality, 
researchers in different places need to go beyond the traditional place-based 
and comparative studies. It is crucial to trace and integrate flows of people, 
information, goods, products, capital, energy, matter, and other entities 
such as organisms among different places. Paradigm shifts from scattered 
and separate research to systematic and integrated research can help 
transform sustainability science and generate novel insights for 
understanding complex SDG relationships within as well as between 
adjacent and distant places. Such new sustainability science is essential for 
developing effective policies and governance for realising intertwined SDGs 
across local to global scales. 

 

 

 



Ecology, Economy and Society–the INSEE Journal [16] 

ACKNOWLEDGEMENTS 

I would like to thank Sue Nichols and Nandan Nawn for their helpful edits, 
Shuxin Li for drawing Figure 1, and the US National Science Foundation 
and Michigan AgBioResearch for funding. 

 

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