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Cities and urbanized regions are complex, dynamic, and highly integrated systems linking social, ecological, and technical infrastructure domains in ways that create deep challenges for good governance, policymaking, and planning. The combination of impacts from climate change in cities, air pollution, rapid population growth, multiple sources of development pressure and overall urban system complexity make it difficult for decision-makers to develop and guide development trajectories along more livable, equitable, and at the same time, more resilient pathways. Advancing urban sustainability and resilience agendas requires expanding the scope of inter- and trans-disciplinarity approaches, moving beyond the historically separate social–ecological and socio-technical approaches to jointly study social–ecological–technical infrastructure systems in cities. We take urban complexity as a given and suggest that in both research and practice we need to better capture and understand feedbacks, interdependencies, and non-linearities which create uncertainties and challenge the efficacy of governance practices to achieve normative goals for society. Here, we explore new methods, tools, and approaches to advance our understanding of urban system complexity through a series of journal special issue articles that examine urban structure–function relationships, urban sustainability transitions, green space availability, social–ecological memory, functional traits, and urban land use scenarios. [ABSTRACT FROM AUTHOR]

Automated decision making and predictive analytics through artificial intelligence, in combination with rapid progress in technologies such as sensor technology and robotics are likely to change the way individuals, communities, governments and private actors perceive and respond to climate and ecological change. Methods based on various forms of artificial intelligence are already today being applied in a number of research fields related to climate change and environmental monitoring. Investments into applications of these technologies in agriculture, forestry and the extraction of marine resources also seem to be increasing rapidly. Despite a growing interest in, and deployment of AI-technologies in domains critical for sustainability, few have explored possible systemic risks in depth. This article offers a global overview of the progress of such technologies in sectors with high impact potential for sustainability like farming, forestry and the extraction of marine resources. We also identify possible systemic risks in these domains including a) algorithmic bias and allocative harms; b) unequal access and benefits; c) cascading failures and external disruptions, and d) trade-offs between efficiency and resilience. We explore these emerging risks, identify critical questions, and discuss the limitations of current governance mechanisms in addressing AI sustainability risks in these sectors. • There is a growing interest in AI-technologies for sustainability. • Increased uses of these technologies could create new types of systemic risks. • We show a global uptake of AI-technologies in farming, forestry and marine management. • We explore gaps in principles and governance of AI from a sustainability perspective. [ABSTRACT FROM AUTHOR]

Abstract Climate change actions in cities worldwide are driving deep changes in urban governance. We ask whether new capacities for transformative climate governance are emerging in two cities that have experimented with urban climate governance: Rotterdam, the Netherlands, and New York City (NYC), United States. Transformative climate governance creates the conditions for developing integrated and innovative climate mitigation and adaptation policies and interventions that respond to and shape urban transformation dynamics and contribute to sustainability and resilience. The comparison of capacities for transformative climate governance in Rotterdam and NYC offers insights into the emerging features of urban climate governance vis-à-vis existing urban governance regimes: how urban climate governance is driven and delivered, what new governance conditions emerge, and whether these conditions enable transformative climate governance. In both cities, an integrated, experimental and inclusive approach to climate governance is emerging, which crosses multiple policy sectors and domains (e.g. transport, energy, health, justice), involves a variety of actors and facilitates innovative solutions. Envisioning, long-term goal and knowledge integration, experimentation and tapping into coalitions for change help to provide the basis (including guiding principles, urgency, actor networks, innovative solutions) for transformative climate governance. However, these transformative approaches tend to be still subordinate to business-as-usual interests and policy and planning approaches, which favour isolated, incremental and short-term responses. The challenge for strengthening transformative climate governance will be to develop rigorous institutional and organisational conditions that decisively stipulate a prioritisation of climate change across scales and sectors, provide action mandates and enable wider coordination, collaboration and learning. Highlights • Climate governance activities in cities drive deep changes in urban governance. • Transformative climate governance (TCG) supports desirable urban transformations. • Capacities for TCG manifest in new institutional, knowledge and network conditions. • Visioning, goal and knowledge integration and experimentation create TCG capacities. • Top-down institutional and organisational conditions need to be strengthened for TCG. [ABSTRACT FROM AUTHOR]