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Dataset 1: Brain and body size Published measures of brain size (g) for 131 species of seabird. Brain size estimates were generated from the measurement of adult skulls in museum collections using the endocast method. For each species, multiple specimens were measured and a mean value was calculated to provide a single, species-specific brain size estimate. To account for the allometric relationship between brain and body size, we also obtained information on body size (g). Dataset 2: Natal and adult dispersal rates We collated data on natal and adult dispersal rates by conducting a systematic literature search using the online database, Web of Science. The literature search generated a total of 793 papers and reports and from these, we extracted natal and adult dispersal rates. Here, natal dispersal is defined as the annual proportion of fledglings recruiting into a colony different from their natal colony, and adult dispersal is defined as the annual proportion of adults relocating to a new breeding colony. The final dataset included dispersal estimates from 47 studies and 29 species. For studies that provided multiple dispersal rate estimates, i.e., for different adult age classes or for males and females (n=9), we calculated a species mean value. For this final list, we also collated information on age at first breeding and fledging time. We selected age at first breeding to reflect the species-specific time that is available to prospect different colonies, and fledging time to reflect maternal investment. Where multiple species-specific values were provided for age at first breeding, we calculated the mean weighted by the percentage of individuals that had bred by each age. Where a range was provided for fledging time, we took the midpoint. Dataset 3: Extinction risk and threats We extracted a species’ threat status from the IUCN Red List database (iucnredlist.org, 2020) and their vulnerability to six relevant anthropogenic threats listed under the Threats Classification Scheme (v. 3.3, IUCN, 2020). The six anthropogenic threats we considered were: climate change, biological resource use (e.g., fishing), human intrusions and disturbance, invasive species, energy production and mining, and pollution. Threat vulnerability was classified as: ‘vulnerable’ or ‘not vulnerable’. We used the IUCN classifications to group species into two broader categories of extinction risk. Here, species classified as Critically Endangered (CR), Endangered (E) and Vulnerable (V) were defined as ‘threatened’, and species listed as Near Threatened (NT) and Least Concern (LC) were defined as ‘non-threatened’. The cognitive buffer hypothesis proposes that species with larger brains (relative to their body size) exhibit greater behavioural flexibility, conferring an advantage in unpredictable or novel environments. Therefore, behavioural flexibility – and relative brain size – are likely to be important predictors of a species’ vulnerability to anthropogenic pressures and, ultimately, extinction risk. However, current evidence linking brain size to species vulnerability and extinction risk is inconclusive. Furthermore, studies examining the relationship between relative brain size and behavioural flexibility have mainly focused on foraging innovations, whilst other forms of behavioural flexibility remain unexplored. In this study, we collate species-specific information and examine links between relative brain size, rates of natal and adult dispersal (a measure of flexibility in breeding site fidelity), vulnerability to six anthropogenic threats and extinction risk for 131 species of seabird. We focused our study on seabirds, a highly threatened group that displays large variation in both relative brain size and dispersal behaviour. We found a significant positive relationship between relative brain size and natal dispersal rate, suggesting that relative brain size could enhance flexibility in breeding site choice in seabirds, consistent with the cognitive buffer hypothesis. However, this relationship does not persist when we consider adult dispersal, possibly reflecting constraints imposed by mate selection and knowledge transfer in seabirds. We also show that relative brain size is negatively associated with vulnerability to climate change. These findings have immediate application for predicting interspecific variation in species’ vulnerability to climate change and identifying priority species for conservation.

Resilience is receiving increasing scientific attention, albeit its notion is still in progress and not univocal, especially when it comes to specific sectors such as energy. Energy and resilience policy is detected as a dominant strategy to achieve international development objectives throughout long-term sustainability and wellbeing goals. Energy resilience also crosses major energy policy issues – namely energy vulnerability, security, poverty, and justice. Making use of the Web Of Science 2018 release, this work aims at contributing to a clarification of the concept of energy resilience, proposing a taxonomy. The bibliometric outputs show a sharp increase in scientific publications on the issue. The bibliometric analysis suggests a taxonomy of energy resilience based on 7 approaches or strategies. The results suggest an evolution of the conceptual contributions, that enlarge resilience early use, merely applied to technical and hard sciences. Resilience is today used in different disciplines, including social sciences and sustainability studies, as part of a holistic approach centered on sustainable development.

AbstractSpecies extinction risk is accelerating due to anthropogenic climate change, making it urgent to protect vulnerable species through legal frameworks in order to facilitate conservation actions that help mitigate risk. Here, we discuss fundamental concepts for assessing climate change risks to species using the example of the emperor penguin (Aptenodytes forsteri), currently being considered for protection under the US Endangered Species Act (ESA). This species forms colonies on Antarctic sea ice, which is projected to significantly decline due to ongoing greenhouse gas (GHG) emissions. We project the dynamics of all known emperor penguin colonies under different GHG emission scenarios using a climate‐dependent meta‐population model including the effects of extreme climate events based on the observational satellite record of colonies. Assessments for listing species under the ESA require information about how species resiliency, redundancy and representation (3Rs) will be affected by threats within the foreseeable future. Our results show that if sea ice declines at the rate projected by climate models under current energy system trends and policies, the 3Rs would be dramatically reduced and almost all colonies would become quasi‐extinct by 2100. We conclude that the species should be listed as threatened under the ESA.

The Pan-African Consortium for the Evaluation of Anti-Tuberculosis Antibiotics (PanACEA) was designed to build tuberculosis (TB) trial capacity whilst conducting clinical trials on novel and existing agents to shorten and simplify TB treatment. PanACEA has now established a dynamic network of 11 sub-Saharan clinical trial sites and four European research institutions.In 2011, a capacity development program, funded by the European & Developing Countries Clinical Trials Partnership (EDCTP), was launched with four objectives, aiming at strengthening collaborating TB research sites to reach the ultimate goal of becoming self-sustainable institutions: networking; training; conducting clinical trials; and infrastructure scaling-up of sites.Assessment in six sub-Saharan TB-endemic countries (Gabon, Kenya, South Africa, Tanzania, Uganda and Zambia) were performed through a structured questionnaire, site visits, discussion with the PanACEA consortium, setting of milestones and identification of priorities and followed-up with evaluations of each site. The results of this needs-based assessment was then translated into capacity development measures.In the initial phase, over a four-year period (March 2011 - June 2014), the programme scaled-up six sites; conducted a monitoring training program for 11 participants; funded five MSc and four PhD students, fostering gender balance; conducted four epidemiological studies; supported sites to conduct five Phase II studies and formed a sustainable platform for TB research (panacea-tb.net).Our experience of conducting TB clinical trials within the PanACEA programme environment of mentoring, networking and training has provided a sound platform for establishing future sustainable research centres. Our goal of facilitating emergent clinical TB trial sites to better initiate and lead research activities has been mostly successful.

This paper uses data from Understanding Society: the UK Household Longitudinal Study to explore the association between fuel poverty and a set of wellbeing outcomes: life-satisfaction, self-reported health measures and more objectively measured biomarker data. Over and above the conventional income–fuel cost indicators, we also use more proximal heating deprivation indicators. We create and draw upon a set of composite indicators that concomitantly capture (the lack of) affordability and thermal comfort. Depending on which fuel deprivation indicator is used, we find heterogeneous associations between fuel poverty and our wellbeing outcomes. Employing combined fuel deprivation indicators, which takes into account the income–fuel cost balance and more proximal perceptions of heating adequacy, reveals the presence of more pronounced associations with life satisfaction and fibrinogen, one of our biological health measures. The presence of these strong associations would have been less pronounced or masked when using separately each of the components of our composite fuel deprivation indicators as well as in the case of self-reported generic measures of physical health. Lifestyle and chronic health conditions play a limited role in attenuating our results, while material deprivation partially, but not fully, attenuates our associations between fuel deprivation and wellbeing. These results remain robust when bounding analysis, IV and panel data models are employed to test the potential role of various sources of endogeneity biases. Our analysis suggests that composite fuel deprivation indicators may be useful energy policy instruments for uncovering the underlining mechanism via which fuel poverty may get “under the skin”.

There are substantial differences in carbon footprints across households. This study applied an environmentally extended multiregional input–output approach to estimate household carbon footprints for 12 different income groups of China’s 30 regions. Subsequently, carbon footprint Gini coefficients were calculated to measure carbon inequality for households across provinces. We found that the top 5% of income earners were responsible for 17% of the national household carbon footprint in 2012, while the bottom half of income earners caused only 25%. Carbon inequality declined with economic growth in China across space and time in two ways: first, carbon footprints showed greater convergence in the wealthier coastal regions than in the poorer inland regions; second, China’s national carbon footprint Gini coefficients declined from 0.44 in 2007 to 0.37 in 2012. We argue that economic growth not only increases income levels but also contributes to an overall reduction in carbon inequality in China.

ABSTRACTA semi-distributed hydrological model of the Niger River above and including the Inner Delta is developed. GCM-related uncertainty in climate change impacts are investigated using seven GCMs for a 2°C increase in global mean temperature, the hypothesised threshold of “dangerous” climate change. Declines in precipitation predominate, although some GCMs project increases for some sub-catchments, whilst PET increases for all scenarios. Inter-GCM uncertainty in projected precipitation is three to five times that of PET. With the exception of one GCM (HadGEM1), which projects a very small increase (3.9%), river inflows to the Delta decline. There is considerable uncertainty in the magnitude of these reductions, ranging from 0.8% (HadCM3) to 52.7% (IPSL). Whilst flood extent for HadGEM1 increases (mean annual peak +1405 km2/+10.2%), for other GCMs it declines. These declines range from almost negligible changes to a 7903 km2 (57.3%) reduction in the mean annual peak.Editor Z.W. Kundzewicz; Associate edi...