<p>The near ubiquitous presence of pharmaceutical compounds in environmental waters represents an emerging cause for concern, but gaps remain in our understanding of how human and veterinary pharmaceuticals enter and travel through river catchments. A more holistic approach is needed in order to develop effective management strategies that conform to the catchment-based approach, although this is complicated by the patchy nature of available monitoring data for river water and by the significant seasonal variation in concentrations which makes comparisons even within datasets tenuous. Here, an exploration of pharmaceutical concentrations across the Aire catchment in the UK aims to provide insight into how the underlying connectivity of the catchment system, conceptualized as a source-pathway-receptor model, may determine observed patterns of contamination. To account for temporal variations of inputs and flow, samples collected on two separate occasions (corresponding to low and high flow conditions, respectively) were used to create two spatial snapshots for contamination with nine representative compounds. The snapshots were then used to explore spatial patterns in the catchment and what factors – topographic, physico-chemical, or related to potential sources and pathways for pharmaceutical pollution – may influence them. For the first snapshot, conducted in low flow conditions, none of the locations had concentrations above the limit of detection for five of the nine target analytes (Atenolol, Diclofenac, Erythomycin, Iopromide and Sulphadiazine). Results for the detected compounds have emphasized the difference in spatial patterns based on use category: as opposed to the veterinary use compound (Cypermethrin), the human use compounds (Carbamazepine, Lidocaine and Sucralose) showed significant correlation to contributing area, as well as to population served by the wastewater treatment plants upstream of the sampling sites and corresponding estimates for amounts of prescribed active ingredient. Sucralose also produced strong correlations to Carbamazepine and Lidocaine, supporting its use as a proxy for contamination with human pharmaceuticals, alongside the more frequently cited Carbamazepine. Ultimately, this research will inform the development of a graph representation of the system, used to assess the relative contribution of different pathways as they connect to the river channel and to inform as to the best intervention points within the catchment.</p>

The relationship between network structure and dynamics is one of the most extensively investigated problems in the theory of complex systems of recent years. Understanding this relationship is of relevance to a range of disciplines—from neuroscience to geomorphology. A major strategy of investigating this relationship is the quantitative comparison of a representation of network architecture (structural connectivity, SC) with a (network) representation of the dynamics (functional connectivity, FC). Here, we show that one can distinguish two classes of functional connectivity—one based on simultaneous activity (co-activity) of nodes, the other based on sequential activity of nodes. We delineate these two classes in different categories of dynamical processes—excitations, regular and chaotic oscillators—and provide examples for SC/FC correlations of both classes in each of these models. We expand the theoretical view of the SC/FC relationships, with conceptual instances of the SC and the two classes of FC for various application scenarios in geomorphology, ecology, systems biology, neuroscience and socio-ecological systems. Seeing the organisation of dynamical processes in a network either as governed by co-activity or by sequential activity allows us to bring some order in the myriad of observations relating structure and function of complex networks.