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ABSTRACT Sustainability science seeks to understand human–nature interactions behind sustainability challenges, but has largely been place-based. Traditional sustainability efforts often solved problems in one place at the cost of other places, compromising global sustainability. The metacoupling framework offers a conceptual foundation and a holistic approach to integrating human–nature interactions within a place, as well as between adjacent places and between distant places worldwide. Its applications show broad utilities for advancing sustainability science with profound implications for global sustainable development. They have revealed effects of metacoupling on the performance, synergies, and trade-offs of United Nations Sustainable Development Goals (SDGs) across borders and across local to global scales; untangled complex interactions; identified new network attributes; unveiled spatio-temporal dynamics and effects of metacoupling; uncovered invisible feedbacks across metacoupled systems; expanded the nexus approach; detected and integrated hidden phenomena and overlooked issues; re-examined theories such as Tobler's First Law of Geography; and unfolded transformations among noncoupling, coupling, decoupling, and recoupling. Results from the applications are also helpful to achieve SDGs across space, amplify benefits of ecosystem restoration across boundaries and across scales, augment transboundary management, broaden spatial planning, boost supply chains, empower small agents in the large world, and shift from place-based to flow-based governance. Key topics for future research include cascading effects of an event in one place on other places both nearby and far away. Operationalizing the framework can benefit from further tracing flows across scales and space, uplifting the rigor of causal attribution, enlarging toolboxes, and elevating financial and human resources. Unleashing the full potential of the framework will generate more important scientific discoveries and more effective solutions for global justice and sustainable development.
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Cyberinfrastructure for sustainability sciences
Abstract Meeting the United Nation’ Sustainable Development Goals (SDGs) calls for an integrative scientific approach, combining expertise, data, models and tools across many disciplines towards addressing sustainability challenges at various spatial and temporal scales. This holistic approach, while necessary, exacerbates the big data and computational challenges already faced by researchers. Many challenges in sustainability research can be tackled by harnessing the power of advanced cyberinfrastructure (CI). The objective of this paper is to highlight the key components and technologies of CI necessary for meeting the data and computational needs of the SDG research community. An overview of the CI ecosystem in the United States is provided with a specific focus on the investments made by academic institutions, government agencies and industry at national, regional, and local levels. Despite these investments, this paper identifies barriers to the adoption of CI in sustainability research that include, but are not limited to access to support structures; recruitment, retention and nurturing of an agile workforce; and lack of local infrastructure. Relevant CI components such as data, software, computational resources, and human-centered advances are discussed to explore how to resolve the barriers. The paper highlights multiple challenges in pursuing SDGs based on the outcomes of several expert meetings. These include multi-scale integration of data and domain-specific models, availability and usability of data, uncertainty quantification, mismatch between spatiotemporal scales at which decisions are made and the information generated from scientific analysis, and scientific reproducibility. We discuss ongoing and future research for bridging CI and SDGs to address these challenges.
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- PAR ID:
- 10430028
- Publisher / Repository:
- IOP Publishing
- Date Published:
- Journal Name:
- Environmental Research Letters
- Volume:
- 18
- Issue:
- 7
- ISSN:
- 1748-9326
- Page Range / eLocation ID:
- Article No. 075002
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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