Tracking Carbon and Ammonia Emission Flows of China's Nitrogen Fertilizer System: Implications for Domestic and International Trade.

China is the world's largest producer, consumer, and exporter of synthetic nitrogen (N) fertilizer. To assess the impact of domestic demand and international exports, we quantified the life-cycle CO2eq and ammonia (NH3) emissions by tracking carbon (C) and nitrogen (N) flows from coal/gas mining through ammonia production to N fertilizer production, application, and export. In 2020, China's N fertilizer system emitted 496.04 Tg of CO2eq and 3.74 Tg of NH3, with ammonia production and N fertilizer application processes contributing 36 and 85% of the life-cycle CO2eq and NH3 emissions, respectively. As the largest importers of N fertilizer, India, Myanmar, South Korea, Malaysia, and the Philippines collectively shifted 112.41 Tg of CO2eq. For every ton of N fertilizer produced and used in China, 16 t of CO2eq and 0.18 t of NH3 were emitted, compared to 9.7 t of CO2eq and 0.13 t of NH3 in Europe. By adopting currently available technologies, improving N fertilizer utilization efficiency and employing nitrification inhibitors could synergistically reduce CO2eq emissions by 20% and NH3 emissions by 75%, while energy transformation efforts would primarily reduce CO2eq emissions by 59%. The production of ammonia using green electricity or green hydrogen could significantly enhance the decarbonization of China's N fertilizer system.

Extending weeknight sleep duration in late-sleeping adolescents using morning bright light on weekends: a 3-week maintenance study.

Study Objectives: Our sleep extension intervention in adolescents showed that gradually shifting weekday bedtime earlier plus one weekend of morning bright light advanced circadian phase and increased weeknight sleep duration. Here, we examine at-home maintenance of these changes. Methods: Fourteen adolescents (15.3-17.9 years; 7 female) completed a 7-week study. After usual sleep at home (2-week baseline), intervention participants (n = 8) gradually advanced weekday bedtime (1 hour earlier than baseline during week 3; 2 hours earlier in week 4) and received bright light (~6000 lux; 2.5 hours) on both mornings of the intervening weekend. During three maintenance weeks, intervention participants were instructed to maintain their school-day wake-up time on all days, keep their early week four bedtimes, except on weekends when they could go to bed up to 1 hour later, and get a 2.5-hour light box exposure within 5 minutes of waking on one morning (Saturday or Sunday) of both weekends at home. Control participants (n = 6) slept as usual at home and did not receive weekend bright light. Dim light melatonin onset (DLMO) was measured after the 2-week baseline, 2-week intervention, and 3-week maintenance in all participants. Actigraphic sleep-wake was collected throughout. Results: After the 2-week intervention, DLMOs advanced more compared to control (37.0 ±â€…40.0 minutes vs. -14.7 ±â€…16.6 minutes), weekday sleep duration increased by 69.7 ±â€…27.8 minutes and sleep onset was 103.7 ±â€…14.2 minutes earlier compared to baseline. After three maintenance weeks, intervention participants showed negligible DLMO delays (-4.9 ±â€…22.9 minutes); weekday fall-asleep times and sleep durations also remained stable. Conclusions: Early circadian phase and extended sleep can be maintained with at-home weekend bright light.

Fitness consequences of anthropogenic subsidies for a partially migratory wading bird.

Human activities are forcing wildlife to confront selective pressures different from those under which they evolved. In seasonal environments, migration evolved as an adaptation to fluctuating resource availability. Anthropogenic subsidies modify resource dynamics by providing a steady food source that is not subject to seasonality. Globally, many migratory populations are becoming increasingly resident in response to food supplementation. While these population-level shifts are assumed to arise from changing fitness consequences of individual behaviour in response to resource dynamics, these mechanisms are often difficult to quantify and disentangle. Here, we quantified fitness consequences of responses to anthropogenic subsidies in partially migratory wood storks (Mycteria americana) in the heavily urbanized southeastern United States. First, we tested whether individual migratory behaviour is linked to different responses to anthropogenic subsidies. Second, we quantified fitness consequences of these behavioural responses. We found that, in our system, migration and residency are alternative behavioural tactics associated with different responses to food supplementation. In turn, the use of anthropogenic resources alters a fitness component by enhancing nest survival. These results provide a mechanistic examination of how animals may respond to human-modified resource dynamics and how fitness consequences of individual tactics may translate into behavioural shifts at the population level.

Ice age-driven range shifts of diploids and expanding autotetraploids of Biscutella laevigata within a conserved niche.

Early studies of the textbook mixed-ploidy system Biscutella laevigata highlighted diploids restricted to never-glaciated lowlands and tetraploids at high elevations across the European Alps, promoting the hypothesis that whole-genome duplication (WGD) is advantageous under environmental changes. Here we addressed long-held hypotheses on the role of hybridisation at the origin of the tetraploids, their single vs multiple origins, and whether a shift in climatic niche accompanied WGD. Climatic niche modelling together with spatial genetics and coalescent modelling based on ddRAD-seq genotyping of 17 diploid and 19 tetraploid populations was used to revisit the evolution of this species complex in space and time. Diploids differentiated into four genetic lineages corresponding to allopatric glacial refugia at the onset of the last ice age, whereas tetraploids displaying tetrasomic inheritance formed a uniform group that originated from southern diploids before the last glacial maximum. Derived from diploids occurring at high elevation, autotetraploids likely inherited their adaptation to high elevation rather than having evolved it through or after WGD. They further presented considerable postglacial expansion across the Alps and underwent admixture with diploids. Although the underpinnings of the successful expansion of autotetraploids remain elusive, differentiation in B. laevigata was chiefly driven by the glacial history of the Alps.

Can internal range structure predict range shifts?

Poleward and uphill range shifts are a common-but variable-response to climate change. We lack understanding regarding this interspecific variation; for example, functional traits show weak or mixed ability to predict range shifts. Characteristics of species' ranges may enhance prediction of range shifts. However, the explanatory power of many range characteristics-especially within-range abundance patterns-remains untested. Here, we introduce a hypothesis framework for predicting range-limit population trends and range shifts from the internal structure of the geographic range, specifically range edge hardness, defined as abundance within range edges relative to the whole range. The inertia hypothesis predicts that high edge abundance facilitates expansions along the leading range edge but creates inertia (either more individuals must disperse or perish) at the trailing range edge such that the trailing edge recedes slowly. In contrast, the limitation hypothesis suggests that hard range edges are the signature of strong limits (e.g. biotic interactions) that force faster contraction of the trailing edge but block expansions at the leading edge of the range. Using a long-term avian monitoring dataset from northern Minnesota, USA, we estimated population trends for 35 trailing-edge species and 18 leading-edge species and modelled their population trends as a function of range edge hardness derived from eBird data. We found limited evidence of associations between range edge hardness and range-limit population trends. Trailing-edge species with harder range edges were slightly more likely to be declining, demonstrating weak support for the limitation hypothesis. In contrast, leading-edge species with harder range edges were slightly more likely to be increasing, demonstrating weak support for the inertia hypothesis. These opposing results for the leading and trailing range edges might suggest that different mechanisms underpin range expansions and contractions, respectively. As data and state-of-the-art modelling efforts continue to proliferate, we will be ever better equipped to map abundance patterns within species' ranges, offering opportunities to anticipate range shifts through the lens of the geographic range.

Socioeconomic prerequisites determine national long-term biomonitoring efforts.

In the current anthropogenic era characterised by human-induced environmental changes, long-term biomonitoring has become a crucial component for understanding ecological patterns and detecting shifts in biodiversity. However, spatiotemporal inconsistencies in biomonitoring efforts hinder transboundary progress in understanding and mitigating global environmental change effectively. The International Long-Term Ecosystem Research (ILTER) network is one of the largest standardised biomonitoring initiatives worldwide, encompassing 44 countries globally, including 26 European countries that are part of the European Long-Term Ecosystem Research network (eLTER). To better understand the establishment and development of such long-term biomonitoring efforts, we analysed spatial and temporal trends within the eLTER network. Additionally, we evaluated the environmental, social, and economic factors influencing engagement in biomonitoring activities within this European network. Our findings reveal a spatial imbalance, with biomonitoring efforts concentrated in Central and Western European countries, where monitoring initiatives have typically been established for a longer duration. Furthermore, our analyses underscore the complex interplay of economic, geographic, and cultural factors in the development of long-term ecological research infrastructures. Countries with greater geographic connectivity, slower economic growth, and higher research activity are more likely to be involved in the eLTER network. The intensity of biomonitoring significantly increased with greater research investments, economic growth, and elevated levels of tourism. In contrast, it decreased in countries that are more inward-facing and exhibit a belief in their ability to control environmental outcomes independently. Addressing spatial gaps in monitoring necessitates enhanced support and funding to ensure comprehensive ecological monitoring over extended time periods. This is essential for achieving transboundary sustainability and effective biodiversity conservation in the face of global change drivers.

Gonadal rematuration and sex-specific reproductive impairment in Manila clams under ocean acidification.

Ocean acidification (OA) can affect marine bivalves at various levels of biological organization. Yet, little effort has been devoted to understanding how OA affects the reproductive events of marine bivalves during multiple cycles of maturation. Here, we tested sex-specific reproductive responses of Manila clams (Ruditapes philippinarum) to OA during gonadal rematuration. Under acidified conditions, both male and female clams exhibited delayed gonadal rematuration following spawning and impairments in gonadal tissues, which can be likely ascribed to lowered concentrations of hormones and vitellogenin. The findings indicate that marine bivalves experience significant declines in reproductive capacity as a result of OA during their reproductive cycles, with clear sex-specific differences. Consequently, it is essential to consider sex-specific reproduction responses of marine bivalves to OA when developing conservation strategies and forecasting population sustainability in a rapidly acidifying marine environment.

Quantifying the importance of ontogeny and prey type in modeling top-down and bottom-up effects of an ectothermic predator.

Dietary decisions by predators can affect prey abundance and overall food web dynamics. Many predators do not forage on the same prey at the same frequency throughout their lives. Ontogenetic shifts in prey preference are not, however, often accounted for when modeling food web relationships, despite growing literature that suggests that stage specific dietary relationships may be an important consideration when modeling trophic interactions. We investigated the importance of considering size-structure of a predator population with ontogenetic diet shifts in evaluating relationships with prey response using a manipulative experiment with the brown treesnake (Boiga irregularis) in Guam. After removing ~ 40% of the snake population via toxic mammal carrion, we measured the strength of the relationship between snake density and the response of two types of prey (lizards and mammals). We evaluated these relationships based on total population size or division of the population into stage specific size categories based on diet preference predictions. We hypothesized that the density of juvenile snakes would correlate more strongly with lizard detections, while adult snakes would better correlate to rodent detections. We also measured reproductive output following changes in rates of prey detection. As expected by known ontogenetic shifts in dietary preference, explicit stage-based models better predicted shifts in rates of observed prey items than did total predator density for both lizards and mammals. Additionally, rodent detections were predictive of one reproductive pulse from snakes, while lizard detections were not predictive or correlated. Our findings support that consideration of predatory species stage-based dietary preference can be meaningful for understanding food web dynamics, particularly when a predator has a broad diet or one that changes through time.

Deficits and opportunities, pivots and shifts for scaling-up voluntary medical male circumcision in Uganda: a qualitative reflexive thematic analysis study.

Despite voluntary medical male circumcision (VMMC) being a cost-effective intervention for preventing HIV transmission, its scale-up has faced challenges. Several interventions to address these challenges in priority countries, including Uganda, have not yielded the desired results. This cross-sectional qualitative study aimed to explore the factors that affect the demand for VMMC and identify possible solutions. Semi-structured phone interviews were conducted with 29 males aged at least 18 and not more than 65 drawn randomly from a database representative of the general population maintained by an independent research organisation. Reflexive thematic analysis was conducted, and data analysis was done using NVivo version 12. The results were presented in narrative format with supporting quotes. The study received ethical and regulatory clearance to be conducted in Uganda. The average age of the respondents was 28 years. Almost all respondents had some education, and most lived in rural areas. Two themes were generated, namely, 1) deficits and opportunities for VMMC, which are issues that currently hinder the uptake of VMMC but, if addressed, would lead to better demand, and 2) pivots and shifts for VMMC, which are changes that need to be made to improve the uptake of VMMC. We found that several challenges, including myths, misconceptions, health system gaps, and uncertainties about the postoperative period, hindered the uptake of VMMC. Pivots and shifts for improving the uptake of VMMC include intensifying VMMC campaigns, addressing inequities, and addressing access barriers. We concluded that several challenges, including myths and misconceptions, health system-related gaps, and uncertainties in the post-circumcision period, persist and negatively impact the scale-up of VMMC in Uganda. VMMC beneficiaries have plausible proposals for addressing challenges. The Uganda Ministry of Health should address the myths, misconceptions, health system-related gaps, and uncertainties about the postoperative period and should involve VMMC beneficiaries in reviewing interventions to address gaps.

Clinical sequelae of gut microbiome development and disruption in hospitalized preterm infants.

Aberrant preterm infant gut microbiota assembly predisposes to early-life disorders and persistent health problems. Here, we characterize gut microbiome dynamics over the first 3 months of life in 236 preterm infants hospitalized in three neonatal intensive care units using shotgun metagenomics of 2,512 stools and metatranscriptomics of 1,381 stools. Strain tracking, taxonomic and functional profiling, and comprehensive clinical metadata identify Enterobacteriaceae, enterococci, and staphylococci as primarily exploiting available niches to populate the gut microbiome. Clostridioides difficile lineages persist between individuals in single centers, and Staphylococcus epidermidis lineages persist within and, unexpectedly, between centers. Collectively, antibiotic and non-antibiotic medications influence gut microbiome composition to greater extents than maternal or baseline variables. Finally, we identify a persistent low-diversity gut microbiome in neonates who develop necrotizing enterocolitis after day of life 40. Overall, we comprehensively describe gut microbiome dynamics in response to medical interventions in preterm, hospitalized neonates.

An adaptive cycle resilience perspective to understand the regime shifts of social-ecological system interactions over the past two millennia in the Tarim River Basin.

Socio-ecological systems (SESs) in arid regions have experienced multiple transformations throughout history due to human activities and natural forces. However, few studies have used the resilience cycle model to explain the resilience status and determinants of SESs over the past two millennia. This study proposes the adaptive cycle resilience (ACR) perspective to investigate regime shifts of socio-ecological system interactions in the Tarim River Basin (TRB) over the past two millennia. An ACR framework combining a piecewise linear regression model (PLR), ACR theory, and physical resilience models has been built to assess and quantify socio-ecological system resilience. Key indicators such as climate variability, settlement numbers, war frequency, glacier accumulation, and oasis area changes are identified and quantified to evaluate SESs adaptability and transformability. Glacier accumulation serves as a proxy for long-term climate change, while oasis area changes reflect the direct impact of human activities and environmental feedback on ecosystem productivity. Population and war indicators provide insights into social system stability and the impact of conflicts on SESs dynamics. The findings reveal that the 7th century and 1850s are critical points of regime shifts in the ACR. 200s BC-350s AD and 700s AD-900s AD are in the forward loop (r-K) period of the ACR. 350s AD-700s AD and 900s AD-1850s AD are the adaptive resilience backward loop (Ω-α) phase. Assessing the historical socio-ecological system resilience and identifying key transition points can inform proactive measures to mitigate potential regime shifts. Combining historical data with resilience theory provides a deep understanding of the ACR of SESs and their driving factors. This enriches the theoretical understanding of SESs and offers a robust case study for future resilience assessments and scenario analyses in arid regions.

Unravelling Influence Factors in Pattern Recognition Myoelectric Control Systems: The Impact of Limb Positions and Electrode Shifts.

Pattern recognition (PR)-based myoelectric control systems can naturally provide multifunctional and intuitive control of upper limb prostheses and restore lost limb function, but understanding their robustness remains an open scientific question. This study investigates how limb positions and electrode shifts-two factors that have been suggested to cause classification deterioration-affect classifiers' performance by quantifying changes in the class distribution using each factor as a class and computing the repeatability and modified separability indices. Ten intact-limb participants took part in the study. Linear discriminant analysis (LDA) was used as the classifier. The results confirmed previous studies that limb positions and electrode shifts deteriorate classification performance (14-21% decrease) with no difference between factors (p > 0.05). When considering limb positions and electrode shifts as classes, we could classify them with an accuracy of 96.13 ± 1.44% and 65.40 ± 8.23% for single and all motions, respectively. Testing on five amputees corroborated the above findings. We have demonstrated that each factor introduces changes in the feature space that are statistically new class instances. Thus, the feature space contains two statistically classifiable clusters when the same motion is collected in two different limb positions or electrode shifts. Our results are a step forward in understanding PR schemes' challenges for myoelectric control of prostheses and further validation needs be conducted on more amputee-related datasets.

Thermal refugia reinforce macroalgal resilience against climate change in the southeastern Bay of Biscay.

Rising global temperatures present unprecedented challenges to marine ecosystems, demanding a profound understanding of their ecological dynamics for effective conservation strategies. Over a comprehensive macroalgal assessment spanning three decades, we investigated the spatiotemporal evolution of shallow-water benthic communities in the southern Bay of Biscay, uncovering climate-resilient areas amidst the ongoing phase shift in the region. Our investigation identified seven locations serving as potential climate refugia, where cold-affinity, canopy-forming macroalgal species persisted and community structure was similar to that observed in 1991. We unveiled a clear association between the emergence of these refugia, sea surface temperature (SST), and the Community Temperature Index, positioning SST as a significant driver of the observed phase shift in the region. Warming processes, defined as tropicalization (increase of warm-affinity species) and deborealization (decrease of cold-affinity species), were prominent outside refugia. In contrast, cooling processes, defined as borealization (increase of cold-affinity species) and detropicalization (decrease of warm-affinity species), prevailed inside refugia. Refugia exhibited approximately 35% lower warming processes compared to non-refuge areas. This resulted in a dominance of warm-affinity species outside refugia, contrasting with the stability observed within refugia. The persistence of canopy-forming species in refuge areas significantly contributed to maintaining ecosystem diversity and stability. These findings underscored the pivotal role of climate refugia in mitigating climate-driven impacts. Prioritizing the protection and restoration of these refugia can foster resilience and ensure the preservation of biodiversity for future generations. Our study illustrates the importance of refining our understanding of how marine ecosystems respond to climate change, offering actionable insights essential for informed conservation strategies and sustainable environmental management.

A unified Foot and Mouth Disease dataset for Uganda: evaluating machine learning predictive performance degradation under varying distributions.

In Uganda, the absence of a unified dataset for constructing machine learning models to predict Foot and Mouth Disease outbreaks hinders preparedness. Although machine learning models exhibit excellent predictive performance for Foot and Mouth Disease outbreaks under stationary conditions, they are susceptible to performance degradation in non-stationary environments. Rainfall and temperature are key factors influencing these outbreaks, and their variability due to climate change can significantly impact predictive performance. This study created a unified Foot and Mouth Disease dataset by integrating disparate sources and pre-processing data using mean imputation, duplicate removal, visualization, and merging techniques. To evaluate performance degradation, seven machine learning models were trained and assessed using metrics including accuracy, area under the receiver operating characteristic curve, recall, precision and F1-score. The dataset showed a significant class imbalance with more non-outbreaks than outbreaks, requiring data augmentation methods. Variability in rainfall and temperature impacted predictive performance, causing notable degradation. Random Forest with borderline SMOTE was the top-performing model in a stationary environment, achieving 92% accuracy, 0.97 area under the receiver operating characteristic curve, 0.94 recall, 0.90 precision, and 0.92 F1-score. However, under varying distributions, all models exhibited significant performance degradation, with random forest accuracy dropping to 46%, area under the receiver operating characteristic curve to 0.58, recall to 0.03, precision to 0.24, and F1-score to 0.06. This study underscores the creation of a unified Foot and Mouth Disease dataset for Uganda and reveals significant performance degradation in seven machine learning models under varying distributions. These findings highlight the need for new methods to address the impact of distribution variability on predictive performance.

Crop booms as regime shifts.

A crop boom is a sudden, nonlinear and intense expansion of a new crop. Despite their large impacts, boom-bust dynamics are not well understood; booms are largely unpredictable and difficult to steer once they unfold. Based on the striking resemblances between land regime shifts and crop booms, we apply complex systems theory, highlighting the potential for regime shifts, to provide new insights about crop boom dynamics. We analyse qualitative and quantitative data of rubber and banana plantation expansion in two forest frontier regions of northern Laos. We show that preconditions, including previous booms, explain the occurrence (why) of booms, and triggers like policy and market changes explain their timing (when). Yet, the most important features of booms, their intensity and nonlinearity (how), strongly depended on internal self-reinforcing feedbacks. We identify built-in feedbacks (neighbourhood effects and imitation) and emergent feedbacks (land rush) and show that they were social in nature, multi-scale from plot to region and subject to thresholds. We suggest that these are regular features of booms and propose a definition and causal-mechanistic explanation of crop booms, examining the overlap between booms and regime shifts and the role of frontiers. We then identify opportunities for management interventions before, during and after booms.

Temporal evolution and thematic shifts in sustainable construction and demolition waste management through building information modeling technologies: A text-mining analysis.

Construction and demolition activities are significant contributors to waste generation worldwide. As population growth accelerates worldwide, the amount of construction and demolition waste (C&DW) will increase proportionally unless proactive measures are implemented. This study analyzes the evolving research landscape on utilizing Building Information Modeling (BIM) technologies to advance sustainable C&DW management practices. A comprehensive text-mining analysis is conducted on 493 scholarly publications covering evolutions from January 2009 to February 2024 using the PRISMA framework. The research objectives are: (i) to identify key themes in domain of BIM technology in C&DW management using VOSviewer, (ii) to map the temporal evolution of research focus using SciMAT, and (iii) to identify emerging thematic trends.Co-occurrence analysis reveals three major research themes: (i) the use of digital twins and prefabrication for waste reduction, (ii) integrating environmental impact assessments, and (iii) data-driven decision-making. Strategic diagrams produced by SciMAT software uncover shifting priorities over the study period, with "reuse and recycling" emerging as motor themes, and "Prefabrication" (CIT = 481), "Decision Making" (CIT = 66), "Material Passport" (CIT = 92), and "Digital Twin" (CIT = 44) emerging as high-centrality and transversal themes. Temporal evolution mapping unveiled progressive integration of BIM tools such as (i) digital twins (TLS = 34, OCC = 9) and (ii) prefabrication (TLS = 40, OCC = 14), presenting opportunities to optimize waste reduction. This study offers a robust overview of the field, aiming to inform a diverse audience, including researchers from various disciplines, policymakers and industry professionals interested in advancing sustainable practices in C&DW management through innovative digital solutions.

From expansion to efficiency: Machine learning-based forecasting of Japan's building material stocks under demographic declines.

Japan's unique demographic trajectory, marked by population decline and aging, coupled with continued urbanization, presents distinct challenges for aligning built environment capacity with resource efficiency. This study aims to investigate the historical evolution and project future scenarios of building material stock (MS) and their spatial distribution across Japan's three major metropolitan areas. Through a comprehensive material flow and stock analysis, the historical accumulation of building materials from 2009 to 2020 was quantified, revealing a dominance of concrete and an increasing overall stock. The contributions of various driving factors to changes in construction areas were explored, identifying population dynamics as the predominant influence. Leveraging shared socioeconomic pathway scenarios (SSPs), this research forecasted building floor area and MS until 2050 under five distinct SSPs. The results indicated an overall reduction across all scenarios, yet with a continued concentration in high-density urban cores. The substantial gap between the highest and lowest projected MS scenarios highlighted opportunities for material conservation and emission reductions through sustainable practices. Sustainable urban development in densely populated regions necessitates a balance between infrastructure provision and environmental conservation, while in sparsely populated areas, the focus shifts to the efficient management and utilization of vacant properties and materials to cope with the impacts of significant population declines. By offering insights into the building floor area and MS implications of Japan's demographic changes, this study underscores the necessity of sustainable urban planning and resource management strategies to navigate the challenges posed by demographic shifts, ultimately contributing to sustainable development and environmental conservation goals.

Non-linear associations between night shifts and adverse events in nursing staff: a restricted cubic spline analysis.

INTRODUCTION: Existing studies suggest that the number of night shifts may impact the occurrence of adverse events. However, while this relationship is well-documented, previous research has not thoroughly examined the non-linear associations between night shifts and adverse events among nursing staff, which remains a gap in our understanding. METHODS: Participants were 1,774 Chinese nurse staff. Psychosocial characteristics were screened by The Chinese version of the multidimensional scale of perceived social support (MSPSS) for social support, the 9-item Patient Health Questionnaire (PHQ-9) for depressive symptoms, the Generalized Anxiety Disorder-7 (GAD-7) for anxiety symptoms. Binary logistic regression and restricted cubic splines were applied to analyze the data. The statistical software used were R version 3.6.2 and SPSS version 22.0. RESULTS: Over the past year, 325 cases (18.3%) were classified as adverse events. Logistic regression unveiled that social support played a protective role against adverse events, with an OR of 0.991 (95% CI: 0.983, 0.999). Furthermore, night shifts continued to surface as a substantial risk factor for adverse events, with an OR to 1.300 (95% CI: 1.181, 1.431). The restricted cubic spline regression model highlights a nonlinear relationship between night shifts and adverse events (P for non-liner < 0.001). The probability of adverse events increases with the number of night shifts, but compared to individuals working 3-4 night shifts per month, those working 5-6 night shifts per month have a lower probability of adverse events. CONCLUSION: Our findings indicate a non-linear relationship between the frequency of night shifts and adverse events, suggesting a complex interplay of factors. This highlights the need for nursing practice and policy to consider the intricacies of night shift scheduling and explore more reasonable rostering strategies to mitigate the probability of adverse events.

The past, the recent, and the ongoing evolutionary processes of the worldwide invasive ascidian Styela plicata.

Invasive species are one of the main threats to global biodiversity and, within marine ecosystems, tunicates feature some prominent examples. Styela plicata is an ascidian species inhabiting harbours in all temperate oceans and seas, thus being considered a thriving invasive species. However, this species' adaptive mechanisms, introduction history, and population structure have never been completely elucidated. Here, by genotyping 87 S. plicata individuals from 18 localities worldwide with 2b-RADseq, we confirm the global presence of four chromosome inversions, demonstrate population structuring on this species, detect local adaptation signals, and infer historical demographic events. We show that North Carolina individuals constitute an unrelated population, Atlanto-Mediterranean and Pacific localities form their own genetic clusters with substructuring, being the most evident the split between northern and southern Atlantic localities. The locality of South Carolina presents an intermediate genetic position between North Carolina and the other two groups pointing to a hybrid origin with recurrent gene flow. We generate and test demographic models, providing evidence of two independent introduction events to the Atlantic and Pacific, and an admixture that originated the population of South Carolina. Finally, we identify candidate loci for adaptation, with functions involved with cell processes, metabolism, development, and ion transport, among others. Overall, this study highlights the complex historical processes of S. plicata, which have led this species to its current distribution, population structure, and local adaptation footprint in oceans worldwide.

Multidecadal changes in coastal benthic species composition and ecosystem functioning occur independently of temperature-driven community shifts.

Rising global temperatures are often identified as the key driver impacting ecosystems and the services they provide by affecting biodiversity structure and function. A disproportionate amount of our understanding of biodiversity and function is from short-term experimental studies and static values of biodiversity indices, lacking the ability to monitor long-term trends and capture community dynamics. Here, we analyse a biennial dataset spanning 32 years of macroinvertebrate benthic communities and their functional response to increasing temperatures. We monitored changes in species' thermal affinities to examine warming-related shifts by selecting their mid-point global temperature distribution range and linking them to species' traits. We employed a novel weighted metric using Biological Trait Analysis (BTA) to gain better insights into the ecological potential of each species by incorporating species abundance and body size and selecting a subset of traits that represent five ecosystem functions: bioturbation activity, sediment stability, nutrient recycling and higher and lower trophic production. Using biodiversity indices (richness, Simpson's diversity and vulnerability) and functional indices (richness, Rao's Q and redundancy), the community structure showed no significant change over time with a narrow range of variation. However, we show shifts in species composition with warming and increases in the abundance of individuals, which altered ecosystem functioning positively and/or non-linearly. Yet, when higher taxonomic groupings than species were excluded from the analysis, there was only a weak increase in the measured change in community-weighted average thermal affinities, suggesting changes in ecosystem functions over time occur independently of temperature increase-related shifts in community composition. Other environmental factors driving species composition and abundance may be more important in these subtidal macrobenthic communities. This challenges the prevailing emphasis on temperature as the primary driver of ecological response to climate change and emphasises the necessity for a comprehensive understanding of the temporal dynamics of complex systems.