Focus on global–local–global analysis of sustainability
Focus on global–local–global analysis of sustainability
复制标题
专注于全球-本地-全球可持续发展分析
DOI：
10.1088/1748-9326/acf8da
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发表时间：
2023
影响因子：
6.7
通讯作者：
Ramankutty, Navin
中科院分区：
文献类型：
--
作者：
Hertel, Thomas W.;Irwin, Elena;Polasky, Stephen;Ramankutty, Navin
本期特刊是2022年4月在普渡大学举办的一次研讨会的成果。它包括确保土地和水资源长期可持续性的全球-地方-全球挑战的五个主要方面的专题综合。这些主题层面包括：气候变化、生态系统和生物多样性、治理、水资源和网络基础设施。此外，从亚马逊河流域的环境压力到美国的地下水枯竭，GLG分析在特定的土地和水可持续性挑战中有八种应用。基于这些论文，我们得出结论，如果没有精细的地方分析，侧重于土地和水的可持续性的干预措施可能会被误导。但是，在没有更广泛的国家/全球背景的情况下制定此类政策也是有问题的--无论是从地方可持续发展压力的全球驱动因素的角度来看，还是从获取意想不到的溢出效应的角度来看。此外，由于当地和全球系统与中尺度过程相连，并由中尺度过程调节，因此解释关键的中尺度现象，如劳动力市场功能，对于描述GLG相互作用至关重要。我们还得出结论，在未来的工作中，增加GLG分析的复杂性还有很大的空间。然而，这也带来了巨大的风险。复杂性的增加可能会超过数据和建模能力，减缓研究速度，使结果更难理解和解释，并使与决策者和其他分析用户的有效沟通复杂化。我们认为，关于适当复杂性的研究指导是全球-地方-全球可持续性分析这一新兴领域的高度优先事项。
This special issue is the outcome of a workshop held at Purdue University in April 2022. It comprises thematic syntheses of five overarching dimensions of the Global-to-Local-to-Global (GLG) challenge to ensuring the long-term sustainability of land and water resources. These thematic dimensions include: climate change, ecosystems and biodiversity, governance, water resources and cyberinfrastructure. In addition, there are eight applications of GLG analysis to specific land and water sustainability challenges, ranging from environmental stress in the Amazon River Basin to groundwater depletion in the United States. Based on these papers, we conclude that, without fine-scale, local analysis, interventions focusing on land and water sustainability will likely be misguided. But formulating such policies without the broader, national/global context is also problematic – both from the point of view of the global drivers of local sustainability stresses, as well as to capture unanticipated spillovers. In addition, because local and global systems are connected to – and mediated by – meso-scale processes, accounting for key meso-scale phenomena, such as labor market functioning, is critical for characterizing GLG interactions. We also conclude that there is great scope for increasing the complexity of GLG analysis in future work. However, this carries significant risks. Increased complexity can outstrip data and modeling capabilities, slow down research, make results more difficult to understand and interpret, and complicate effective communication with decision-makers and other users of the analyses. We believe that research guidance regarding appropriate complexity is a high priority in the emerging field of Global-Local-Global analysis of sustainability.
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影响因子：
6.7
作者：
B. Cultice;E. Irwin;Mackenzie Jones
通讯作者：
B. Cultice;E. Irwin;Mackenzie Jones
影响因子：
6.7
作者：
Banerjee, Onil;Cicowiez, Martin;Macedo, Marcia N;Malek, Žiga;Verburg, Peter H;Goodwin, Sean;Vargas, Renato;Rattis, Ludmila;Bagstad, Kenneth J;Brando, Paulo M
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Brando, Paulo M
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影响因子：
6.7
作者：
Johnson, Justin Andrew;Brown, Molly E;Corong, Erwin;Dietrich, Jan Philipp;C Henry, Roslyn;von Jeetze, Patrick José;Leclère, David;Popp, Alexander;Thakrar, Sumil K;Williams, David R
通讯作者：
Williams, David R
影响因子：
6.7
作者：
Mosnier，Aline;Javalera-Rincon，Valeria;Zerriffi，Hisham
通讯作者：
Zerriffi，Hisham
影响因子：
6.7
作者：
Jing Liu;Laura C Bowling;C. Kucharik;S. Jame;U. Baldos;Larissa Jarvis;N. Ramankutty;Thomas W Hertel
通讯作者：
Jing Liu;Laura C Bowling;C. Kucharik;S. Jame;U. Baldos;Larissa Jarvis;N. Ramankutty;Thomas W Hertel