A core comprises of a group of central and densely connected nodes which governs the overall behaviour of a network. It is recognised as one of the key meso-scale structures in complex networks. Profiling this meso-scale structure currently relies on a limited number of methods which are often complex and parameter dependent or require a null model. As a result, scalability issues are likely to arise when dealing with very large networks together with the need for subjective adjustment of parameters. The notion of a rich-club describes nodes which are essentially the hub of a network, as they play a dominating role in structural and functional properties. The definition of a rich-club naturally emphasises high degree nodes and divides a network into two subgroups. Here, we develop a method to characterise a rich-core in networks by theoretically coupling the underlying principle of a rich-club with the escape time of a random walker. The method is fast, scalable to large networks and completely parameter free. In particular, we show that the evolution of the core in World Trade and C. elegans networks correspond to responses to historical events and key stages in their physical development, respectively.

Whilst there is an increasing capability to instrument smart cities using fixed and mobile sensors to produce the big data to better understand and manage transportation use, there still exists a wide gap between the sustainability goals of smart cities, e.g., to promote less private car use at peak times, with respect to their ability to more dynamically support individualised shifts in multi-modal transportation use to help achieve such goals. We describe the development of the tripzoom system developed as part of the SUNSET—SUstainable social Network SErvices for Transport—project to research and develop a mobile and fixed traffic sensor system to help facilitate individual mobility shifts. Its main novelty was its ability to use mobile sensors to classify common multiple urban transportation modes, to generate information-rich individual and group mobility profiles and to couple this with the use of a targeted incentivised marketplace to gamify travel. This helps to promote mobility shifts towards achieving sustainability goals. This system was trialled in three European country cities operated as Living Labs over six months. Our main findings were that we were able to accomplish a level of behavioural shifts in travel behaviour. Hence, we have provided a proof-of-concept system that uses positive incentives to change individual travel behaviour.

Interdisciplinary research is on the rise globally. Yet, several studies have shown that it often achieves lower impact compared to more specialized work, and is less likely to attract funding. Here, we seek to reconcile such evidence by analyzing 44,419 research grants awarded by the research councils in the UK. We find that researchers with an interdisciplinary funding track record dominate the network of academic collaborations, both in terms of centrality and knowledge brokerage, but such a competitive advantage does not translate into immediate return. Our results based on a matched pair analysis show that interdisciplinary researchers achieve lower impact with their publications in the short run; however, they eventually outperform their specialized counterparts in funding performance, both in terms of volume and value. These findings suggest that pursuing an interdisciplinary career may require perseverance to overcome extra challenges, but can pave the way for a more successful endeavor.

Extreme climatic events such as drought are increasing in magnitude and frequency, representing one of the biggest threats to freshwaters across the globe. Although drought can cause extensive loss or turnover of biodiversity, food web structure often remains surprisingly unchanged. This topological constancy suggests that ecosystems undergo rewiring of biotic interactions resulting from adaptive species responses, although how compensatory mechanics collectively reorganise food webs are largely unknown. Here, we perform a merging of trophic ecology with an approach from network science (global network alignment, which optimises network comparison and reveals restructuring) to assess the impact of experimental drought on the topology of stream food webs. We found that whilst drought caused substantial biodiversity loss, trophic plasticity among the surviving consumers conserved 80% of the original food web topology, maintaining connectance and in turn stability. This structural inertia was driven by extensive rewiring among the surviving species, but in contrast to expectations, we observed considerable trophic plasticity among dietary specialists who in fact disproportionally rewired more than their generalist counterparts. These findings demonstrate that adaptive dietary shifts among specialist species play an underappreciated role in mitigating the effects of drought and governing the topological persistence of ecological networks.

In 2009, many governments implemented austerity measures. This often resulted in restrictions on science funding, increasing competition for funds. Here, we study the allocation of funding across universities by using a competitiveness measure from complexity science based on the bipartite network of universities and scientific subjects. Drawing on a comprehensive data set of 43,430 UK-funded grants between 2006 and 2020, a period covering the onset and relaxation of austerity, we provide two main results. First, we find that the effect of austerity on university grant income depended on research competitiveness: highly competitive universities increased grant income under austerity, while low-ranked universities lost income. Then, we study the resilience of science to austerity exploiting the natural experiment arising from the 2015 UK general election, when austerity was relaxed unexpectedly. We discover that the resilience of researchers at less competitive universities was surprisingly high. The number and size of grant applications grew more after 2015 at less competitive universities, increasing their grant income. Overall, results show that our network-based measure is a better proxy for research competitiveness than aggregate grant income across scientific subjects.