Factors Affecting Shark Detection from Drone Patrols in Southeast Queensland, Eastern Australia

Drones enable the monitoring for sharks in real-time, enhancing the safety of ocean users with minimal impact on marine life. Yet, the effectiveness of drones for detecting sharks (especially potentially dangerous sharks; i.e., white shark, tiger shark, bull shark) has not yet been tested at Queensland beaches. To determine effectiveness, it is necessary to understand how environmental and operational factors affect the ability of drones to detect sharks. To assess this, we utilised data from the Queensland SharkSmart drone trial, which operated at five southeast Queensland beaches for 12 months in 2020–2021. The trial conducted 3369 flights, covering 1348 km and sighting 174 sharks (48 of which were >2 m in length). Of these, eight bull sharks and one white shark were detected, leading to four beach evacuations. The shark sighting rate was 3% when averaged across all beaches, with North Stradbroke Island (NSI) having the highest sighting rate (17.9%) and Coolum North the lowest (0%). Drone pilots were able to differentiate between key shark species, including white, bull and whaler sharks, and estimate total length of the sharks. Statistical analysis indicated that location, the sighting of other fauna, season and flight number (proxy for time of day) influenced the probability of sighting shark

Queensland SharkSmart Drone Trial Final Report

Remotely Piloted Aircraft Systems, commonly called drones, provide a high-definition aerial view of a wide expanse of ocean, allowing the detection of potentially dangerous sharks in real-time, whilst having a negligible impact on the environment and non-target species. In addition, they are capable of spotting a range of marine hazards and can assist in beach rescue operations, thus providing numerous safety benefits for water users. The beaches of South-East Queensland (SEQ) have relatively good water clarity and a high level of visitation, making them an ideal location to test drones for detecting sharks and improving the safety of water users (Cardno, 2019). North Queensland beaches typically have lower water clarity, although it is important to test drones under these conditions to assess whether they can be effective at detecting sharks. The Queensland SharkSmart drone trial commenced on 19 September 2020, as a partnership between the Queensland Government Department of Agriculture and Fisheries (DAF) and Surf Life Saving Queensland (SLSQ). The trial was part of the Queensland Government’s commitment to research and trialling alternatives to traditional shark control measures. Drones were operated at two beaches on the Sunshine Coast (Alexandra Headland and Coolum North), two beaches on the Gold Coast (Southport Main Beach and Burleigh Beach) and one beach on North Stradbroke Island (NSI; Ocean beach) between 19 September 2020 and 4 October 2021. Additionally, to assess the effectiveness of drones at detecting sharks under the different environmental conditions found at North Queensland (NQ) beaches, drones were operated at Palm Cove, Cairns and Alma Bay, Magnetic Island, from 26 June 2021 to 31 October 2021. Drones were operated on weekends, public holidays and school holidays by SLSQ pilots, with two flights per hour from approximately 8am until midday. Flights lasted 15 - 20 minutes and followed a 400 m transect behind the surf break. All footage was collected in 4K and securely archived for later analysis with key operational and environmental data collected for every flight. When a shark was sighted, the drone pilot lowered the aircraft to determine the species and size while estimating distance of the animal from water users. Data analysis quantified the numbers of sharks sighted at each beach and the rate of sightings as a percentage across the whole trial from 19 September 2020 to 31 October 2021. Generalised Linear Mixed Models (GLMMs) were applied to quantify the influence of environmental and operational factors on the sightability (probability of a shark being sighted) of sharks. The movement tracks of sharks were mapped to analyse their behaviour and identify if there was clustering of movements in certain areas. Sighting rates from drones were also compared with shark catch in adjacent nets and drumlines deployed as part of the Queensland Shark Control Program (SCP)

Very Early Optical Afterglows of Gamma-Ray Bursts: Evidence for Relative Paucity of Detection

Very early observations with the Swift satellite of gamma-ray burst (GRB) afterglows reveal that the optical component is not detected in a large number of cases. This is in contrast to the bright optical flashes previously discovered in some GRBs (e.g. GRB 990123 and GRB 021211). Comparisons of the X-ray afterglow flux to the optical afterglow flux and prompt gamma-ray fluence is used to quantify the seemingly deficient optical, and in some cases X-ray, light at these early epochs. This comparison reveals that some of these bursts appear to have higher than normal gamma-ray efficiencies. We discuss possible mechanisms and their feasibility for explaining the apparent lack of early optical emission. The mechanisms considered include: foreground extinction, circumburst absorption, Ly-alpha blanketing and absorption due to high redshift, low density environments, rapid temporal decay, and intrinsic weakness of the reverse shock. Of these, foreground extinction, circumburst absorption, and high redshift provide the best explanations for most of the non-detections in our sample. There is tentative evidence of suppression of the strong reverse shock emission. This could be because of a Poynting-flux-dominated flow or a pure non-relativistic hydrodynamical reverse shock.Comment: 22 pages, 5 figures. Accepted for publication in Ap

Science Priorities for Seamounts: Research Links to Conservation and Management

Seamounts shape the topography of all ocean basins and can be hotspots of biological activity in the deep sea. The Census of Marine Life on Seamounts (CenSeam) was a field program that examined seamounts as part of the global Census of Marine Life (CoML) initiative from 2005 to 2010. CenSeam progressed seamount science by collating historical data, collecting new data, undertaking regional and global analyses of seamount biodiversity, mapping species and habitat distributions, challenging established paradigms of seamount ecology, developing new hypotheses, and documenting the impacts of human activities on seamounts. However, because of the large number of seamounts globally, much about the structure, function and connectivity of seamount ecosystems remains unexplored and unknown. Continual, and potentially increasing, threats to seamount resources from fishing and seabed mining are creating a pressing demand for research to inform conservation and management strategies. To meet this need, intensive science effort in the following areas will be needed: 1) Improved physical and biological data; of particular importance is information on seamount location, physical characteristics (e.g. habitat heterogeneity and complexity), more complete and intensive biodiversity inventories, and increased understanding of seamount connectivity and faunal dispersal; 2) New human impact data; these shall encompass better studies on the effects of human activities on seamount ecosystems, as well as monitoring long-term changes in seamount assemblages following impacts (e.g. recovery); 3) Global data repositories; there is a pressing need for more comprehensive fisheries catch and effort data, especially on the high seas, and compilation or maintenance of geological and biodiversity databases that underpin regional and global analyses; 4) Application of support tools in a data-poor environment; conservation and management will have to increasingly rely on predictive modelling techniques, critical evaluation of environmental surrogates as faunal “proxies”, and ecological risk assessment

Genomic Relationships, Novel Loci, and Pleiotropic Mechanisms across Eight Psychiatric Disorders

Genetic influences on psychiatric disorders transcend diagnostic boundaries, suggesting substantial pleiotropy of contributing loci. However, the nature and mechanisms of these pleiotropic effects remain unclear. We performed analyses of 232,964 cases and 494,162 controls from genome-wide studies of anorexia nervosa, attention-deficit/hyper-activity disorder, autism spectrum disorder, bipolar disorder, major depression, obsessive-compulsive disorder, schizophrenia, and Tourette syndrome. Genetic correlation analyses revealed a meaningful structure within the eight disorders, identifying three groups of inter-related disorders. Meta-analysis across these eight disorders detected 109 loci associated with at least two psychiatric disorders, including 23 loci with pleiotropic effects on four or more disorders and 11 loci with antagonistic effects on multiple disorders. The pleiotropic loci are located within genes that show heightened expression in the brain throughout the lifespan, beginning prenatally in the second trimester, and play prominent roles in neurodevelopmental processes. These findings have important implications for psychiatric nosology, drug development, and risk prediction.Peer reviewe

Multiorgan MRI findings after hospitalisation with COVID-19 in the UK (C-MORE): a prospective, multicentre, observational cohort study

Introduction: The multiorgan impact of moderate to severe coronavirus infections in the post-acute phase is still poorly understood. We aimed to evaluate the excess burden of multiorgan abnormalities after hospitalisation with COVID-19, evaluate their determinants, and explore associations with patient-related outcome measures. Methods: In a prospective, UK-wide, multicentre MRI follow-up study (C-MORE), adults (aged ≥18 years) discharged from hospital following COVID-19 who were included in Tier 2 of the Post-hospitalisation COVID-19 study (PHOSP-COVID) and contemporary controls with no evidence of previous COVID-19 (SARS-CoV-2 nucleocapsid antibody negative) underwent multiorgan MRI (lungs, heart, brain, liver, and kidneys) with quantitative and qualitative assessment of images and clinical adjudication when relevant. Individuals with end-stage renal failure or contraindications to MRI were excluded. Participants also underwent detailed recording of symptoms, and physiological and biochemical tests. The primary outcome was the excess burden of multiorgan abnormalities (two or more organs) relative to controls, with further adjustments for potential confounders. The C-MORE study is ongoing and is registered with ClinicalTrials.gov, NCT04510025. Findings: Of 2710 participants in Tier 2 of PHOSP-COVID, 531 were recruited across 13 UK-wide C-MORE sites. After exclusions, 259 C-MORE patients (mean age 57 years [SD 12]; 158 [61%] male and 101 [39%] female) who were discharged from hospital with PCR-confirmed or clinically diagnosed COVID-19 between March 1, 2020, and Nov 1, 2021, and 52 non-COVID-19 controls from the community (mean age 49 years [SD 14]; 30 [58%] male and 22 [42%] female) were included in the analysis. Patients were assessed at a median of 5·0 months (IQR 4·2–6·3) after hospital discharge. Compared with non-COVID-19 controls, patients were older, living with more obesity, and had more comorbidities. Multiorgan abnormalities on MRI were more frequent in patients than in controls (157 [61%] of 259 vs 14 [27%] of 52; p<0·0001) and independently associated with COVID-19 status (odds ratio [OR] 2·9 [95% CI 1·5–5·8]; padjusted=0·0023) after adjusting for relevant confounders. Compared with controls, patients were more likely to have MRI evidence of lung abnormalities (p=0·0001; parenchymal abnormalities), brain abnormalities (p<0·0001; more white matter hyperintensities and regional brain volume reduction), and kidney abnormalities (p=0·014; lower medullary T1 and loss of corticomedullary differentiation), whereas cardiac and liver MRI abnormalities were similar between patients and controls. Patients with multiorgan abnormalities were older (difference in mean age 7 years [95% CI 4–10]; mean age of 59·8 years [SD 11·7] with multiorgan abnormalities vs mean age of 52·8 years [11·9] without multiorgan abnormalities; p<0·0001), more likely to have three or more comorbidities (OR 2·47 [1·32–4·82]; padjusted=0·0059), and more likely to have a more severe acute infection (acute CRP >5mg/L, OR 3·55 [1·23–11·88]; padjusted=0·025) than those without multiorgan abnormalities. Presence of lung MRI abnormalities was associated with a two-fold higher risk of chest tightness, and multiorgan MRI abnormalities were associated with severe and very severe persistent physical and mental health impairment (PHOSP-COVID symptom clusters) after hospitalisation. Interpretation: After hospitalisation for COVID-19, people are at risk of multiorgan abnormalities in the medium term. Our findings emphasise the need for proactive multidisciplinary care pathways, with the potential for imaging to guide surveillance frequency and therapeutic stratification

Community Composition of Elasmobranch Fishes Utilizing Intertidal Sand Flats in Moreton Bay, Queensland, Australia.

v. ill. 23 cm.QuarterlyThirteen elasmobranch species were collected during a 4-yr survey of the intertidal margins of Moreton Bay, a large subtropical embayment in southeastern Queensland, Australia. Stingrays were the most common large predators in the intertidal zone, with total catch dominated numerically by blue-spotted maskray, Neotrygon kuhlii (53.8%); estuary stingray, Dasyatis fluviorum (22.2%); and brown whipray, Himantura toshi (10.2%). There was a significant female bias within intertidal populations of N. kuhlii and D. fluviorum. Courtship behaviors were observed in July and September in D. fluviorum and in January for whitespotted eagle ray, Aetobatus narinari. Dasyatis fluviorum, a threatened Australian endemic stingray, remains locally abundant within the bay. Overall, the inshore elasmobranch fauna of Moreton Bay is relatively species rich compared with similar studies elsewhere in Australia, emphasizing the regional importance of this ecosystem