Foraging distribution of breeding northern fulmars is predicted by commercial fisheries

Funding: J.H.D. was funded by the Irish Research Council Enterprise Partnership Scheme, supported by the Petroleum Infrastructure Program. Field work on Little Saltee in 2018 and 2019 and S.d.G. were funded by the BlueFish project, funded by the European Regional Development fund through the Ireland Wales Cooperation Programme 2014−2020. Fieldwork on Eynhallow and St. Kilda was supported by Orkney Islands Council, the University of Aberdeen, the National Trust for Scotland and Talisman Energy (UK) Ltd. E.W.J.E. was funded by a Marine Alliance for Science and Technology for Scotland and University of Aberdeen studentship. Fieldwork elsewhere was funded by the EU Atlantic area INTERREG program via the Future of the Atlantic Marine Environment (FAME) project and by the RSPB, JNCC, Fair Isle Bird Observatory Trust and Marine Scotland, through the Seabird Tracking And Research (STAR) project. G.E.A. was funded by the MarPAMM project supported by the EU INTERREG VA Programme, managed by the Special EU Programmes Body (SEUPB).Habitat-use and distribution models are essential tools of conservation biology. For wide-ranging species, such models may be challenged by the expanse, remoteness and variability of their habitat, these challenges often being compounded by the species' mobility. In marine environments, direct observations and sampling are usually impractical over broad regions, and instead remotely sensed proxies of prey availability are often used to link species abundance or foraging behaviour to areas that are expected to provide food consistently. One source of food consumed by many marine top predators is fisheries waste, but habitat-use models rarely account for this interaction. We assessed the utility of commercial fishing effort as a covariate in foraging habitat models for northern fulmars Fulmarus glacialis, a species known to exploit fisheries waste, during their summer breeding season. First, we investigated the prevalence of fulmar-vessel interactions using concurrently tracked fulmars and fishing vessels. We infer that over half of our study individuals associate with fishing vessels while foraging, mostly with trawl-type vessels. We then used hidden Markov models to explain the spatio-temporal distribution of putative foraging behaviour as a function of a range of covariates. Persistent commercial fishing effort was a significant predictor of foraging behaviour, and was more important than commonly used environmental covariates retained in the model. This study demonstrates the effect of commercial fisheries on the foraging distribution and behaviour of a marine top predator, and supports the idea that, in some systems, incorporating human activities into distribution studies can improve model fit substantially.Publisher PDFPeer reviewe

Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

Background: Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery. Methods: This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation. Results: A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65). Discussion: Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability