Income-based variation in Sustainable Development Goal interaction networks

David Lusseau; Francesca Mancini

doi:10.1038/s41893-019-0231-4

Income-based variation in Sustainable Development Goal interaction networks

David Lusseau (Corresponding Author), Francesca Mancini

Research output: Contribution to journal › Article

13 Citations (Scopus)

17 Downloads (Pure)

Abstract

The 17 United Nations Sustainable Development Goals (SDGs) are set to change the way we live, and aim to create, by 2030, a sustainable future balancing equitable prosperity within planetary boundaries. Human, economic and natural resources must be used in tandem to achieve the SDGs; therefore, acting to resolve one SDG can impair or improve our ability to meet others that may need these resources to be used in different ways. Trade-offs arising from these SDG interactions are a key hurdle for SDG implementation. We estimate the network of SDG interactions—the sustainome—using global time series of SDG indicators for countries with different income levels. We analyse the network architecture to determine the hurdles and opportunities to maximize SDG implementation through their interactions. The relative contributions of SDGs to global sustainable success differ by country income. They also differ depending on whether we consider SDG goals or targets. However, limiting climate change, reducing inequalities and responsible consumption are key hurdles to achieving 2030 goals across countries. Focusing on poverty alleviation and reducing inequalities will have compound positive effects on all SDGs.

Original language	English
Pages (from-to)	242-247
Number of pages	6
Journal	Nature Sustainability
Volume	2
Issue number	3
Early online date	4 Mar 2019
DOIs	https://doi.org/10.1038/s41893-019-0231-4
Publication status	Published - Mar 2019

Keywords

global goals
sustainable development goals
network science
sustainome
sustainomics
sustainability

Access to Document

10.1038/s41893-019-0231-4Licence: Unspecified

Accepted Manuscript
This is the accepted author manuscript for an article to be published in Nature Sustainability. The final published version can be found at: http://dx.doi.org/10.1038/s41893-019-0231-4.
Accepted author manuscript, 1.1 MBLicence: Unspecified
Supplementary InformationAccepted author manuscript, 2.35 MBLicence: Unspecified

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Datasets

R code (and instruction for data retrieval) needed to replicate analyses in Lusseau & Mancini 2019 Nature Sustainability

Lusseau, D. (Creator), University of Aberdeen, 2017

https://github.com/dlusseau/sdg/

Dataset

Profiles

David Lusseau

Person: Academic

Cite this

Lusseau, D., & Mancini, F. (2019). Income-based variation in Sustainable Development Goal interaction networks. Nature Sustainability, 2(3), 242-247. https://doi.org/10.1038/s41893-019-0231-4

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title = "Income-based variation in Sustainable Development Goal interaction networks",

abstract = "The 17 United Nations Sustainable Development Goals (SDGs) are set to change the way we live, and aim to create, by 2030, a sustainable future balancing equitable prosperity within planetary boundaries. Human, economic and natural resources must be used in tandem to achieve the SDGs; therefore, acting to resolve one SDG can impair or improve our ability to meet others that may need these resources to be used in different ways. Trade-offs arising from these SDG interactions are a key hurdle for SDG implementation. We estimate the network of SDG interactions—the sustainome—using global time series of SDG indicators for countries with different income levels. We analyse the network architecture to determine the hurdles and opportunities to maximize SDG implementation through their interactions. The relative contributions of SDGs to global sustainable success differ by country income. They also differ depending on whether we consider SDG goals or targets. However, limiting climate change, reducing inequalities and responsible consumption are key hurdles to achieving 2030 goals across countries. Focusing on poverty alleviation and reducing inequalities will have compound positive effects on all SDGs.",

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