• Energy Research

Freshwater species and their habitats, and transportation networks are at heightened risk from changing climate and are priorities for adaptation, with the sheer abundance and individuality of road-river structures complicating mitigation efforts. We present a new spatial dataset of road-river structures attributed as culverts, bridges, or fords, and use this along with data on gradient and stream order to estimate structure sensitivity and exposure in and out of special areas of conservation (SAC) and built-up areas to determine vulnerability to damage across river catchments in Wales, UK. We then assess hazard of flooding likelihood at the most vulnerable structures to determine those posing high risk of impact on roads and river-obligate species (fishes and mussels) whose persistence depends on aquatic habitat connectivity. Over 5% (624/11,680) of structures are high vulnerability and located where flooding hazard is highest, posing high risk of impact to roads and river-obligate species. We assess reliability of our approach through an on-ground survey in a river catchment supporting an SAC and more than 40% (n = 255) of high-risk structures, and show that of the subset surveyed >50% had obvious physical degradation, streambank erosion, and scouring. Our findings help us to better understand which structures pose high-risk of impact to river-obligate species and humans with increased flooding likelihood.

Riverine ecosystems can be conceptualized as 'bioreactors' (the riverine bioreactor) which retain and decompose a wide range of organic substrates. The metabolic performance of the riverine bioreactor is linked to their community structure, the efficiency of energy transfer along food chains, and complex interactions among biotic and abiotic environmental factors. However, our understanding of the mechanistic functioning and capacity of the riverine bioreactor remains limited. We review the state of knowledge and outline major gaps in the understanding of biotic drivers of organic matter decomposition processes that occur in riverine ecosystems, across habitats, temporal dimensions, and latitudes influenced by climate change. We propose a novel, integrative analytical perspective to assess and predict decomposition processes in riverine ecosystems. We then use this model to analyse data to demonstrate that the size-spectra of a community can be used to predict decomposition rates by analysing an illustrative dataset. This modelling methodology allows comparison of the riverine bioreactor's performance across habitats and at a global scale. Our integrative analytical approach can be applied to advance understanding of the functioning and efficiency of the riverine bioreactor as hotspots of metabolic activity. Application of insights gained from such analyses could inform the development of strategies that promote the functioning of the riverine bioreactor across global ecosystems.