Assessing the response of mountain birds to rapid environmental change: conservation ecology of the Alpine Ring Ouzel (Turdus torquatus alpestris)

Mountain ecosystems are exposed to increasing threats globally, of which changes in land-use and climate are commonly regarded as the most serious. In this context of rapid environmental change, it is of fundamental importance to assess the current and future responses of high-elevation organisms. There is in fact an urgent need to understand the ecological and demographic mechanisms underlying mountain species’ distributions and population trends for proper conservation planning. Here, we focused on the Ring Ouzel Turdus torquatus, an emblematic thrush species of upland and mountainous regions of Europe. The main goal of this PhD thesis was to improve our knowledge of the ecology and demography of the alpestris subspecies, i.e. the Alpine Ring Ouzel, to identify possible drivers of negative trends in central Europe and envision possible conservation action. We first looked at functional ecological relationships, such as patterns of habitat selection and resource acquisition during the breeding season in the Swiss Alps, and how these relate to environmental variables. In a next step, we focused on demographic aspects and described the structure and dynamics of two focal populations in the western European Alps. We then examined behavioural and movement patterns across the annual cycle using tracking devices. Lastly, we relied on the initially accrued knowledge of species’ ecological requirements to parameterize a country-wide, fine-scale habitat suitability model. The latter was used to delineate key areas for the Ring Ouzel and evaluate its vulnerability to environmental change based on various scenarios. Our results demonstrate specific foraging preferences for soft and moist soils within a short and sparse grass sward, conditions that rapidly vanish from the breeding grounds as the season advances. This underlines strong temporal constraints on breeding, most probably driven by the brief time window of availability of the main prey, earthworms, as corroborated by the observed reduction in provisioning activity and efficiency in dry and warm weather contexts. Variations in weather conditions had, however, no clear impact on fitness parameters. Still, the narrow time window available for reproduction in the Alps may explain the apparent slower life-history strategy of Alpine populations when compared to Northern populations. Retrieved tracking data evidenced flexible seasonal and day-to-day movements but a year-round reliance on high-elevation regions, with winter quarters located in mountain ranges of Spain and Morocco. Finally, we reveal the more prominent role of climate compared to land-use in predictive models of species distribution and abundance. Indeed, climate shifts are expected to override the potential impact of land-use change in the coming decades, such as land abandonment and farming intensification. This highlights the vulnerability of the species to climate disruption, despite the strategies evolved to cope with environmental changes, in particular weather variation. Altogether, our findings unfortunately suggest limited leeway for implementing adaptive conservation strategies capable of fully mitigating the impacts of environmental change on Alpine Ring Ouzels. Nonetheless, recommendations for habitat management are framed while our predictive models constructed on fine-grained ecological information enable spatial prioritization of conservation programmes. These recommendations will not only help to conserve Alpine Ring Ouzels but also to maintain a rich biodiversity in Alpine treeline ecotones into the future

SDMtune: An R package to tune and evaluate species distribution models

Balancing model complexity is a key challenge of modern computational ecology, particularly so since the spread of machine learning algorithms. Species distribution models are often implemented using a wide variety of machine learning algorithms that can be fine-tuned to achieve the best model prediction while avoiding overfitting. We have released SDMtune, a new R package that aims to facilitate training, tuning, and evaluation of species distribution models in a unified framework. The main innovations of this package are its functions to perform data-driven variable selection, and a novel genetic algorithm to tune model hyperparameters. Real-time and interactive charts are displayed during the execution of several functions to help users understand the effect of removing a variable or varying model hyperparameters on model performance. SDMtune supports three different metrics to evaluate model performance: the area under the receiver operating characteristic curve, the true skill statistic, and Akaike's information criterion corrected for small sample sizes. It implements four statistical methods: artificial neural networks, boosted regression trees, maximum entropy modeling, and random forest. Moreover, it includes functions to display the outputs and create a final report. SDMtune therefore represents a new, unified and user-friendly framework for the still-growing field of species distribution modeling

Tall trees drive the nest-site selection of wild Crested Ibis Nipponia nippon

Understanding how birds select breeding sites plays an important role in habitat protection, especially for the conservation of endangered species. With the increase in population size of the endangered Crested Ibis Nipponia nippon, its distribution range has expanded from mountain areas to plains located outside protected areas, representing a new challenge for conservation of the species. Identifying the current nesting habitat requirements is thus needed and can provide valuable information for the planning of new nature reserves. In this research, we surveyed a total of 117 nests across the whole distribution range from 2015 to 2019. We used generalized linear mixed-effects models to assess nesting preferences of the Crested Ibis in the wild. Results showed that in mountain areas, Masson pines Pinus massoniana were preferred (64.6%), whereas elms Ulmus pumila (44.9%) and aspens Populus davidiana (40.6%) were used more frequently lower down, probably because of their higher availability. In both mountain areas and plains the ibises selected tall nesting trees with larger diameter at breast height and preferred nesting rather high above ground, especially in plains where taller trees provided higher suitable nesting positions. The ibises also preferred nesting close to tree trunks, especially in mountain areas, probably for more safety from collapsing. Furthermore, in mountain areas, slope and distance to path had positive effects on nesting occurrence, and understorey coverage was avoided by nesting ibises, while these variables had little impact in plains. Our results indicate that, despite their range expansion, Crested Ibises rely on very specific habitat characteristics for nesting. We suggest relatively tall trees like elms and aspens should be preserved in plains. In addition, we highlight how selection patterns of Crested Ibises may vary, and that such variation should be addressed in conservation planning, especially in future reintroduction

Prospective observational cohort study on grading the severity of postoperative complications in global surgery research

Background The Clavien–Dindo classification is perhaps the most widely used approach for reporting postoperative complications in clinical trials. This system classifies complication severity by the treatment provided. However, it is unclear whether the Clavien–Dindo system can be used internationally in studies across differing healthcare systems in high- (HICs) and low- and middle-income countries (LMICs). Methods This was a secondary analysis of the International Surgical Outcomes Study (ISOS), a prospective observational cohort study of elective surgery in adults. Data collection occurred over a 7-day period. Severity of complications was graded using Clavien–Dindo and the simpler ISOS grading (mild, moderate or severe, based on guided investigator judgement). Severity grading was compared using the intraclass correlation coefficient (ICC). Data are presented as frequencies and ICC values (with 95 per cent c.i.). The analysis was stratified by income status of the country, comparing HICs with LMICs. Results A total of 44 814 patients were recruited from 474 hospitals in 27 countries (19 HICs and 8 LMICs). Some 7508 patients (16·8 per cent) experienced at least one postoperative complication, equivalent to 11 664 complications in total. Using the ISOS classification, 5504 of 11 664 complications (47·2 per cent) were graded as mild, 4244 (36·4 per cent) as moderate and 1916 (16·4 per cent) as severe. Using Clavien–Dindo, 6781 of 11 664 complications (58·1 per cent) were graded as I or II, 1740 (14·9 per cent) as III, 2408 (20·6 per cent) as IV and 735 (6·3 per cent) as V. Agreement between classification systems was poor overall (ICC 0·41, 95 per cent c.i. 0·20 to 0·55), and in LMICs (ICC 0·23, 0·05 to 0·38) and HICs (ICC 0·46, 0·25 to 0·59). Conclusion Caution is recommended when using a treatment approach to grade complications in global surgery studies, as this may introduce bias unintentionally

The surgical safety checklist and patient outcomes after surgery: a prospective observational cohort study, systematic review and meta-analysis

© 2017 British Journal of Anaesthesia Background: The surgical safety checklist is widely used to improve the quality of perioperative care. However, clinicians continue to debate the clinical effectiveness of this tool. Methods: Prospective analysis of data from the International Surgical Outcomes Study (ISOS), an international observational study of elective in-patient surgery, accompanied by a systematic review and meta-analysis of published literature. The exposure was surgical safety checklist use. The primary outcome was in-hospital mortality and the secondary outcome was postoperative complications. In the ISOS cohort, a multivariable multi-level generalized linear model was used to test associations. To further contextualise these findings, we included the results from the ISOS cohort in a meta-analysis. Results are reported as odds ratios (OR) with 95% confidence intervals. Results: We included 44 814 patients from 497 hospitals in 27 countries in the ISOS analysis. There were 40 245 (89.8%) patients exposed to the checklist, whilst 7508 (16.8%) sustained ≥1 postoperative complications and 207 (0.5%) died before hospital discharge. Checklist exposure was associated with reduced mortality [odds ratio (OR) 0.49 (0.32–0.77); P\u3c0.01], but no difference in complication rates [OR 1.02 (0.88–1.19); P=0.75]. In a systematic review, we screened 3732 records and identified 11 eligible studies of 453 292 patients including the ISOS cohort. Checklist exposure was associated with both reduced postoperative mortality [OR 0.75 (0.62–0.92); P\u3c0.01; I2=87%] and reduced complication rates [OR 0.73 (0.61–0.88); P\u3c0.01; I2=89%). Conclusions: Patients exposed to a surgical safety checklist experience better postoperative outcomes, but this could simply reflect wider quality of care in hospitals where checklist use is routine

Critical care admission following elective surgery was not associated with survival benefit: prospective analysis of data from 27 countries

This was an investigator initiated study funded by Nestle Health Sciences through an unrestricted research grant, and by a National Institute for Health Research (UK) Professorship held by RP. The study was sponsored by Queen Mary University of London