Assessment of the likely sensitivity to climate change for the key marine species in the southern Benguela system

Climate change is altering many environmental parameters of coastal waters and open oceans, leading to substantial present-day and projected changes in the distribution, abundance and phenology of marine species. Attempts to assess how each species might respond to climate change can be data-, resource- and time-intensive. Moreover, in many regions of the world, including South Africa, species may be of vital socioeconomic or ecological importance though critical gaps may exist in our basic biological or ecological knowledge of the species. Here, we adapt and apply a trait-based sensitivity assessment for the key marine species in the southern Benguela system to estimate their potential relative sensitivity to the impacts of climate change. For our analysis, 40 priority species were selected based on their socioeconomic, ecological and/or recreational importance in the system. An extensive literature review and consultation with experts was undertaken concerning each species to gather information on their life history, habitat use and potential stressors. Fourteen attributes were used to estimate the selected species’ sensitivity and capacity to respond to climate change. A score ranging from low to high sensitivity was given for each attribute, based on the available information. Similarly, a score was assigned to the type and quality of information used to score each particular attribute, allowing an assessment of data-quality inputs for each species. The analysis identified the white steenbras Lithognathus lithognathus, soupfin shark Galeorhinus galeus, St Joseph Callorhinchus capensis and abalone Haliotis midae as potentially the most sensitive species to climate-change impacts in the southern Benguela system. There were data gaps for larval dispersal and settlement and metamorphosis cues for most of the evaluated species. Our results can be used by resource managers to determine the type of monitoring, intervention and planning that may be required to best respond to climate change, given the limited resources and significant knowledge gaps in many cases

The SMARTscreen Trial: a randomised controlled trial investigating the efficacy of a GP-endorsed narrative SMS to increase participation in the Australian National Bowel Cancer Screening Program

The SMARTscreen Trial: a randomised controlled trial investigating the efficacy of a GP-endorsed narrative SMS to increase participation in the Australian National Bowel Cancer Screening Progra

Learning spaces: Built, natural and digital considerations for learning and learners

Learning spaces: Built, natural and digital considerations for learning and learner

Equalization of four cardiovascular risk algorithms after systematic recalibration: individual-participant meta-analysis of 86 prospective studies.

Aims: There is debate about the optimum algorithm for cardiovascular disease (CVD) risk estimation. We conducted head-to-head comparisons of four algorithms recommended by primary prevention guidelines, before and after 'recalibration', a method that adapts risk algorithms to take account of differences in the risk characteristics of the populations being studied. Methods and results: Using individual-participant data on 360 737 participants without CVD at baseline in 86 prospective studies from 22 countries, we compared the Framingham risk score (FRS), Systematic COronary Risk Evaluation (SCORE), pooled cohort equations (PCE), and Reynolds risk score (RRS). We calculated measures of risk discrimination and calibration, and modelled clinical implications of initiating statin therapy in people judged to be at 'high' 10 year CVD risk. Original risk algorithms were recalibrated using the risk factor profile and CVD incidence of target populations. The four algorithms had similar risk discrimination. Before recalibration, FRS, SCORE, and PCE over-predicted CVD risk on average by 10%, 52%, and 41%, respectively, whereas RRS under-predicted by 10%. Original versions of algorithms classified 29-39% of individuals aged ≥40 years as high risk. By contrast, recalibration reduced this proportion to 22-24% for every algorithm. We estimated that to prevent one CVD event, it would be necessary to initiate statin therapy in 44-51 such individuals using original algorithms, in contrast to 37-39 individuals with recalibrated algorithms. Conclusion: Before recalibration, the clinical performance of four widely used CVD risk algorithms varied substantially. By contrast, simple recalibration nearly equalized their performance and improved modelled targeting of preventive action to clinical need