New paper: Projections of coral cover and habitat change on turbid reefs under future sea-level rise

Rudy and Hywel have a new published paper: Projections of coral cover and habitat change on turbid reefs under future sea-level rise.

Global sea-level rise (SLR) is projected to increase water depths above coral reefs. Although the impacts of climate disturbance events on coral cover and three-dimensional complexity are well documented, knowledge of how higher sea levels will influence future reef habitat extent and bioconstruction is limited. Here, we use 31 reef cores, coupled with detailed benthic ecological data, from turbid reefs on the central Great Barrier Reef, Australia, to model broad-scale changes in reef habitat following adjustments to reef geomorphology under different SLR scenarios. Model outputs show that modest increases in relative water depth above reefs (Representative Concentration Pathway (RCP) 4.5) over the next 100 years will increase the spatial extent of habitats with low coral cover and generic diversity. More severe SLR (RCP8.5) will completely submerge reef flats and move reef slope coral communities below the euphotic depth, despite the high vertical accretion rates that characterize these reefs. Our findings suggest adverse future trajectories associated with high emission climate scenarios which could threaten turbid reefs globally and their capacity to act as coral refugia from climate change.

New funding for High Resolution Low Cost Air Quality Monitoring

Dr Rudy Arthur has bee awarded £10k by Exeter University’s Policy Engagement Fund for his project “High Resolution Low Cost Air Quality Monitoring”. Air pollution has a significant impact on respiratory diseases like asthma and lung cancer as well as being a significant contributing factor for cardiac disease. The government’s Committee on the Medical Effects of Air Pollutants reports up to 36,000 excess deaths each year in the UK due to NO2 pollution alone.

This project will work together with Haywards Heath Town Council to pilot a high-resolution air quality monitoring platform using low cost, off-the-shelf air quality monitors and cloud computing solutions. We will set up a website to display real time air-quality measurements on an interactive map available to the public. This will directly inform council policy on air pollution management by providing decision-critical information to local policy makers and help inform decisions on town planning, traffic management, walk-to-school routes, tree planting and more.

Hot But Habitable workshop – interdisciplinary collaboration to understand heatwaves

In early March, Hywel participated in the “Hot But Habitable” workshop at the Lorenz Centre in Leiden. The meeting was highly interdisciplinary, bringing medical doctors and city resilience planners together with climate scientists and sociologists (Hywel was the token geek!). It was also managed in an unusual way – for science, at least. There were no formal presentations and no Powerpoint, just a lot of open discussion. The result was a creative and stimulating event with a lot of new ideas. Since returning from Leiden, new collaborations with European partners are being developed to explore the use of social sensing to monitor the social impacts of extreme heat. Check out the Global Heat Health Information Network to find out more about heatwaves and the various projects that are going on.

New paper: Modularity and projection of bipartite networks

A new paper Modularity and projection of bipartite networks is now available online.

This paper investigates community detection by modularity maximisation on bipartite networks. In particular we are interested in how the operation of projection, using one node set of the bipartite network to infer connections between nodes in the other set, interacts with community detection. We first define a notion of modularity appropriate for a projected bipartite network and outline an algorithm for maximising it in order to partition the network. Using both real and synthetic networks we compare the communities found by five different algorithms, where each algorithm maximises a different modularity function and sees different aspects of the bipartite structure. Based on these results we suggest a simple ‘rule of thumb’ for finding communities in bipartite networks.

New Paper: Using social media to measure impacts of named storm events in the United Kingdom and Ireland

Michelle’s work on the social sensing of named storm events in the UK and Ireland was recently published in Meteorological Applications:

Using social media to measure impacts of named storm events in the United Kingdom and Ireland

Spruce, M., Arthur, R., Williams, H.T.P.


Despite increasing use of impact‐based weather warnings, the social impacts of extreme weather events lie beyond the reach of conventional meteorological observations and remain difficult to quantify. This presents a challenge for validation of warnings and weather impact models. This study considers the application of social sensing, the systematic analysis of unsolicited social media data to observe real‐world events, to determine the impacts of named storms in the United Kingdom and Ireland during the winter storm season 2017–2018. User posts on Twitter are analysed to show that social sensing can robustly detect and locate storm events. Comprehensive filtering of tweets containing weather keywords reveals that ~3% of tweets are relevant to severe weather events and, for those, locations could be derived for about 75%. Impacts of storms on Twitter users are explored using the text content of storm‐related tweets to assess changes in sentiment and topics of discussion over the period before, during and after each storm event. Sentiment shows a consistent response to storms, with an increase in expressed negative emotion. Topics of discussion move from warnings as the storm approaches, to local observations and reportage during the storm, to accounts of damage/disruption and sharing of news reports following the event. There is a high level of humour expressed throughout. This study demonstrates a novel methodology for identifying tweets which can be used to assess the impacts of storms and other extreme weather events. Further development could lead to improved understanding of social impacts of storms and impact model validation.


(Top) Time series of the number of tweets per day for named storm events (after filtering for relevance) versus the number of wind tweets per day for the 2017/2018 storm period. Ex‐Hurricane Ophelia produced very high numbers of tweets in the Named Storm and Wind collections for October 16, 2017; that is why plotted counts are truncated for display. Tweet counts for each collection on this date are ~170k (“Ophelia”) and ~60k (“wind”) respectively. (Bottom) Time series of the average UK/Ireland wind speed for the same period. Peaks in wind speed are identified by dashed lines between the two plots to allow visual comparison of wind speed and peaks in wind tweet activity