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Abstract Ocean warming is already causing widespread changes to coral reef ecosystems worldwide. Warming is having direct and indirect impacts on food webs, but their interaction is unclear. Warming directly affects fishes and invertebrates by increasing their metabolic rate, resulting in changes to demographic processes such as growth rates. Indirect effects involve a loss of reef habitat quality as coral bleaching reduces the availability of refuges. We used a size‐structured dynamic energy budget model of fishes and invertebrates, coupled to a spatially explicit model of coral and algae, to explore potential changes to ecosystem function with warming. Modeled changes in biomass for +3°C of warming were found to be controlled predominantly by the direct effects of warming on growth rates, rather than by indirect effects via the changed coral habitat. Crucially for fisheries, the biomass of predators decreased by at least 50% with +3°C of warming, and productivity of predators decreased by at least 60%.

Summary: Background: Uncertainty in patients' COVID-19 status contributes to treatment delays, nosocomial transmission, and operational pressures in hospitals. However, the typical turnaround time for laboratory PCR remains 12–24 h and lateral flow devices (LFDs) have limited sensitivity. Previously, we have shown that artificial intelligence-driven triage (CURIAL-1.0) can provide rapid COVID-19 screening using clinical data routinely available within 1 h of arrival to hospital. Here, we aimed to improve the time from arrival to the emergency department to the availability of a result, do external and prospective validation, and deploy a novel laboratory-free screening tool in a UK emergency department. Methods: We optimised our previous model, removing less informative predictors to improve generalisability and speed, developing the CURIAL-Lab model with vital signs and readily available blood tests (full blood count [FBC]; urea, creatinine, and electrolytes; liver function tests; and C-reactive protein) and the CURIAL-Rapide model with vital signs and FBC alone. Models were validated externally for emergency admissions to University Hospitals Birmingham, Bedfordshire Hospitals, and Portsmouth Hospitals University National Health Service (NHS) trusts, and prospectively at Oxford University Hospitals, by comparison with PCR testing. Next, we compared model performance directly against LFDs and evaluated a combined pathway that triaged patients who had either a positive CURIAL model result or a positive LFD to a COVID-19-suspected clinical area. Lastly, we deployed CURIAL-Rapide alongside an approved point-of-care FBC analyser to provide laboratory-free COVID-19 screening at the John Radcliffe Hospital (Oxford, UK). Our primary improvement outcome was time-to-result, and our performance measures were sensitivity, specificity, positive and negative predictive values, and area under receiver operating characteristic curve (AUROC). Findings: 72 223 patients met eligibility criteria across the four validating hospital groups, in a total validation period spanning Dec 1, 2019, to March 31, 2021. CURIAL-Lab and CURIAL-Rapide performed consistently across trusts (AUROC range 0·858–0·881, 95% CI 0·838–0·912, for CURIAL-Lab and 0·836–0·854, 0·814–0·889, for CURIAL-Rapide), achieving highest sensitivity at Portsmouth Hospitals (84·1%, Wilson's 95% CI 82·5–85·7, for CURIAL-Lab and 83·5%, 81·8–85·1, for CURIAL-Rapide) at specificities of 71·3% (70·9–71·8) for CURIAL-Lab and 63·6% (63·1–64·1) for CURIAL-Rapide. When combined with LFDs, model predictions improved triage sensitivity from 56·9% (51·7–62·0) for LFDs alone to 85·6% with CURIAL-Lab (81·6–88·9; AUROC 0·925) and 88·2% with CURIAL-Rapide (84·4–91·1; AUROC 0·919), thereby reducing missed COVID-19 cases by 65% with CURIAL-Lab and 72% with CURIAL-Rapide. For the prospective deployment of CURIAL-Rapide, 520 patients were enrolled for point-of-care FBC analysis between Feb 18 and May 10, 2021, of whom 436 received confirmatory PCR testing and ten (2·3%) tested positive. Median time from arrival to a CURIAL-Rapide result was 45 min (IQR 32–64), 16 min (26·3%) sooner than with LFDs (61 min, 37–99; log-rank p

The Tasman and Golden Bays (TBGB) are a semi-enclosed embayment system in New Zealand that supports numerous commercial and recreational activities. We present three ecosystem models of the TBGB ecosystem with varying levels of complexity, aimed at contributing as tools to aid in understanding this ecosystem and its responses to anthropogenic and natural pressures. We describe the process of data compilation through to model validation and analyse the importance of knowledge gaps with respect to model dynamics and results. We compare responses in all three models to historical fishing, and analyse similarities and differences in the dynamics of the three models. We assessed the most complex of the models against initialisation uncertainty and sensitivity to oceanographic variability and found it most sensitive to the latter. We recommend that scenarios relating to ecosystem dynamics of the TBGB ecosystem include sensitivities, especially oceanographic uncertainty, and compare responses across all three models where it is possible to do so.

The E2F transcription factors play a critical role in controlling cell fate. In Drosophila, the inactivation of E2F in either muscle or fat body results in lethality, suggesting an essential function for E2F in these tissues. However, the cellular and organismal consequences of inactivating E2F in these tissues are not fully understood. Here, we show that the E2F loss exerts both tissue-intrinsic and systemic effects. The proteomic profiling of E2F-deficient muscle and fat body revealed that E2F regulates carbohydrate metabolism, a conclusion further supported by metabolomic profiling. Intriguingly, animals with E2F-deficient fat body had a lower level of circulating trehalose and reduced storage of fat. Strikingly, a sugar supplement was sufficient to restore both trehalose and fat levels, and subsequently rescued animal lethality. Collectively, our data highlight the unexpected complexity of E2F mutant phenotype, which is a result of combining both tissue-specific and systemic changes that contribute to animal development.

It has been suggested that deep coral reefs offer a refuge against warming and mass bleaching. Here Frade et al. look at the 2016 bleaching event in the northern Great Barrier Reef and found that deep reefs initially acted as thermal refuges, though this effect lessened in the late summer months.

Despite general and wide-ranging negative effects of coral reef degradation on reef communities, hope might exist for reef-associated predators that use nursery habitats. When reef structural complexity is lost, refuge density declines and prey vulnerability increases. Here, we explore whether the presence of nursery habitats can promote high predator productivity on degraded reefs by mitigating the costs of increased vulnerability in early life, whilst allowing for the benefits of increased food availability in adulthood. We apply size-based ecosystem models of coral reefs with high and low structural complexity to predict fish biomass and productivity in the presence and absence of mangrove nurseries. Our scenarios allow us to elucidate the interacting effects of refuge availability and ontogenetic habitat shifts for fisheries productivity. We find that low complexity, degraded reefs with nurseries can support fisheries productivity that is equal to or greater than that in complex reefs that lack nurseries. We compare and validate model predictions with field data from Belize. Our results should inform reef fisheries management strategies and protected areas now and into the future.