Social capital is considered important for resilience across social levels, including communities, yet insights are scattered across disciplines. This meta-synthesis of 187 studies examines conceptual and empirical understandings of how social capital relates to resilience, identifying implications for community resilience and climate change practice. Different conceptualisations are highlighted, yet also limited focus on underlying dimensions of social capital and proactive types of resilience for engaging with the complex climate change challenge. Empirical insights show that structural and socio-cultural aspects of social capital, multiple other factors and formal actors are all important for shaping the role of social capital for guiding resilience outcomes. Thus, finding ways to work with these different elements is important. Greater attention on how and why outcomes emerge, interactions between factors, approaches of formal actors and different socio-cultural dimensions will advance understandings about how to nurture social capital for resilience in the context of climate change.

A paradigm is an accepted world view. If we do not continually question our paradigm then wider trends and movements will overtake the discipline leaving it ill adapted to future challenges. This Special Issue is an opportunity to keep systems thinking at the forefront of ergonomics theory and practice. Systems thinking prompts us to ask whether ergonomics, as a discipline, has been too timid? Too preoccupied with the resolution of immediate problems with industrial-age methods when, approaching fast, are developments which could render these operating assumptions an irrelevance. Practical case studies are presented to show how abstract systems problems can be tackled head-on to deliver highly innovative and cost-effective insights. The strategic direction of the discipline foregrounds high-quality systems problems. These are something the discipline is well able to respond to provided that the appropriate operating paradigms are selected. Practitioner Summary: High-quality systems problems are the future of the discipline. How do we convert obtuse sounding systems concepts into practical interventions? In this paper, the essence of systems thinking is distilled and practical case studies used to demonstrate the benefits of this new paradigm.

Network analysis is a useful tool to analyse the interactions and structure of graphs that represent the relationships among entities, such as sectors within an urban system. Connecting entities in this way is vital in understanding the complexity of the modern world, and how to navigate these complexities during an event. However, the field of network analysis has grown rapidly since the 1970s to produce a vast array of available metrics that describe different graph properties. This diversity allows network analysis to be applied across myriad research domains and contexts, however widespread applications have produced polysemic metrics. Challenges arise in identifying which method of network analysis to adopt, which metrics to choose, and how many are suitable. This paper undertakes a structured review of literature to provide clarity on raison d’etre behind metric selection and suggests a way forward for applied network analysis. It is essential that future studies explicitly report the rationale behind metric choice and describe how the mathematics relates to target concepts and themes. An exploratory metric analysis is an important step in identifying the most important metrics and understanding redundant ones. Finally, where applicable, one should select an optimal number of metrics that describe the network both locally and globally, so as to understand the interactions and structure as holistically as possible.

This paper argues that urban systems issues are design problems on a grand scale and that various disciplines aiming to address them can have only a partial view of the problem. It is necessary to draw boundaries around the detailed analyses of specific issues, but a way to map the wider system, to contextualize and more deeply understand how they are interrelated, is still lacking. Four complexity obstacles related to reasoning about complex systems are in our way, and to our knowledge no existing approach navigates them effectively. We propose a tool called the Abstraction Hierarchy as a way to do just this, in order to frame complex issues on a large scale, in a way accessible to all disciplines. To demonstrate the power of this systems model, the Abstraction Hierarchy is applied to an urban area. Through its application we demonstrate its capability to navigate all four obstacles and investigate previously unexplored space in urban systems research.

Climate change is a product of the Anthropocene, and the human–nature system in which we live. Effective climate change adaptation requires that we acknowledge this complexity. Theoretical literature on sustainability transitions has highlighted this and called for deeper acknowledgment of systems complexity in our research practices. Are we heeding these calls for ‘systems’ research? We used hydrohazards (floods and droughts) as an example research area to explore this question. We first distilled existing challenges for complex human–nature systems into six central concepts: Uncertainty, multiple spatial scales, multiple time scales, multimethod approaches, human–nature dimensions, and interactions. We then performed a systematic assessment of 737 articles to examine patterns in what methods are used and how these cover the complexity concepts. In general, results showed that many papers do not reference any of the complexity concepts, and no existing approach addresses all six. We used the detailed results to guide advancement from theoretical calls for action to specific next steps. Future research priorities include the development of methods for consideration of multiple hazards; for the study of interactions, particularly in linking the short- to medium-term time scales; to reduce data-intensivity; and to better integrate bottom–up and top–down approaches in a way that connects local context with higher-level decision-making. Overall this paper serves to build a shared conceptualisation of human–nature system complexity, map current practice, and navigate a complexity-smart trajectory for future research.