An historical data set, collected in 1958 by Southward and Crisp, was used as a baseline for detecting change in the abundances of species in the rocky intertidal of Ireland. In 2003, the abundances of each of 27 species was assessed using the same methodologies (ACFOR [which stands for the categories: abundant, common, frequent, occasional and rare] abundance scales) at 63 shores examined in the historical study.Comparison of the ACFOR data over a 45-year period, between the historical survey and re-survey, showed statistically signi¢cant changes in the abundances of 12 of the 27 species examined. Two species (one classed as northern and one introduced) increased signi¢cantly in abundance while ten species (¢ve classed as northern, one classed as southern and four broadly distributed) decreased in abundance. The possible reasons for the changes in species abundances were assessed not only in the context of anthropogenic e¡ects, such as climate change and commercial exploitation, but also of operator error. The error or di¡erences recorded among operators (i.e. research scientists) when assessing species abundance using ACFOR categories was quanti¢ed on four shores. Signi¢cant change detected in three of the 12 species fell within the margin of operator error. This e¡ect of operator may have also contributed to the results of no change in the other 15 species between the two census periods. It was not possible to determine the e¡ect of operator on our results, which can increase the occurrence of a false positive (Type 1) or of a false negative (Type 2) outcome.

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Background Bacterial respiratory coinfection in the setting of SARS-CoV-2 infection remains poorly described. A description of coinfection and antimicrobial usage is needed to guide ongoing antimicrobial stewardship. Objectives To assess the rate of empirical antimicrobial treatment in COVID-19 cases, assess the rate and methods of microbiological sampling, assess the rate of bacterial respiratory coinfections and evaluate the factors associated with antimicrobial therapy in this cohort. Methods Inpatients with positive SARS-CoV-2 PCR were recruited. Antibiotic prescription, choice and duration were recorded. Taking of microbiological samples (sputum culture, blood culture, urinary antigens) and culture positivity rate was also recorded. Linear regression was performed to determine factors associated with prolonged antimicrobial administration. Results A total of 117 patients were recruited; 84 (72%) were prescribed antimicrobial therapy for lower respiratory tract infections. Respiratory pathogens were identified in seven (6%) patients. The median duration of antimicrobial therapy was 7 days. C-reactive protein level, oxygen requirement and positive cultures were associated with prolonged duration of therapy. Conclusions The rate of bacterial coinfection in SARS-CoV-2 is low. Despite this, prolonged courses of antimicrobial therapy were prescribed in our cohort. We recommend active antimicrobial stewardship in COVID-19 cases to ensure appropriate antimicrobial prescribing.

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