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Global Marine Flyways Identified for Long-Distance Migrating Seabirds From Tracking Data
Get PDFAim: To identify the broad-scale oceanic migration routes (‘marine flyways’) used by multiple pelagic, long-distance migratory seabirds based on a global compilation of tracking data. Location: Global. Time Period: 1989–2023. Major Taxa Studied: Seabirds (Families: Phaethontidae, Hydrobatidae, Diomedeidae, Procellariidae, Laridae and Stercorariidae). Methods: We collated a comprehensive global tracking dataset that included the migratory routes of 48 pelagic and long-distance migrating seabird species across the Atlantic, Indian, Pacific and Southern Oceans. We grouped individuals that followed similar routes, independent of species or timings of migration, using a dynamic time warping clustering approach. We visualised the routes of each cluster using a line density analysis and used knowledge of seabird spatial ecology to combine the clusters to identify the broad-scale flyways followed by most pelagic migratory seabirds tracked to-date at an ocean-basin scale. Results: Six marine flyways were identified across the world\u27s oceans: the Atlantic Ocean Flyway, North Indian Ocean Flyway, East Indian Ocean Flyway, West Pacific Ocean Flyway, Pacific Ocean Flyway and Southern Ocean Flyway. Generally, the flyways were used bidirectionally, and individuals either followed sections of a flyway, a complete flyway, or their movements linked two or more flyways. Transhemispheric figure-of-eight routes in the Atlantic and Pacific oceans, and a circumnavigation flyway in the Southern Ocean correspond with major wind-driven ocean currents. Main Conclusions: The marine flyways identified demonstrate that pelagic seabirds have similar and repeatable migration routes across ocean-basin scales. Our study highlights the need to account for connectivity in seabird conservation and provides a framework for international cooperation
Handling skewness and directional tails in model-based clustering
Get PDFModel-based clustering is a powerful approach used in data analysis to unveil underlying patterns or groups within a data set. However, when applied to clusters that exhibit skewness, heavy tails, or both, the classification of data points becomes more challenging. In this study, we introduce two models considering two component-wise transformations of the observed data within a mixture of multiple scaled contaminated normal (MSCN) distributions. MSCN distributions are designed to enable a different tail behavior in each dimension and directional outlier detection in the direction of the principal components. Using the transformed MSCN distributions as components of a mixture, we obtain model-based clustering techniques that allow for 1) flexible cluster shapes in terms of skewness and kurtosis and 2) component-wise and directional outlier detection. We assess the efficacy of the proposed techniques by comparing them with model-based clustering methods that perform global or component-wise outlier detection using simulated and real data sets. This comparative analysis aims to demonstrate which practical clustering scenarios using the proposed MSCN-based approaches are advantageous
Use of Generative AI in Aiding Daily Professional Tasks: A Survey of Librarians’ Experiences
Get PDFThis study examines how librarians are using third-party generative AI (GAI) tools such as ChatGPT to aid their daily professional tasks. An online survey of 272 librarians found that text-generating AI tools were the most popular. The majority of respondents felt that GAI tools were effective in improving productivity. Key challenges included ensuring content accuracy and designing effective prompts. Top suggestions for better preparing librarians to use GAI include practical training on using GAI, establishing AI policies and guidelines, fostering collaboration and communities of practice, and providing access to useful GAI resources. The study highlights popular use cases that can inform professional development, while underscoring the need for hands-on training, institutional policies, opportunities to experiment with GAI, and access to enhanced tools. As GAI evolves, supporting librarians’ adoption will be crucial for harnessing its potential benefits
The Effects of Avatar Human-Likeness on Psychological Closeness in Virtual-Reality
Get PDFThis research explores the impact of avatar human-likeness on psychological closeness and its downstream consequences in virtual-reality work and learning environments. Study 1 suggests that people feel greater psychological closeness to more (vs. less) humanlike avatars. Study 2 applies machine learning to virtual-reality recordings and shows that people physically move closer to more (vs. less) humanlike avatars. Study 3 extends these findings by showing that avatar human-likeness positively influences attitudes toward adopting virtual-reality in education. Finally, Study 4 shows that enhanced psychological closeness to humanlike avatars promotes trust in instructors, leading to more favorable attitudes toward virtual experience. Two additional studies that conceptually replicate the main findings are reported in the Supporting Information. Results are consistent between hypothetical scenarios and real virtual-reality experiences, controlled experiments using within- and between-subjects designs, and self-reported measures of closeness and actual physical closeness. These findings provide implications for designing effective virtual-reality experiences in education and corporate settings, emphasizing the importance of humanlike avatars in fostering closeness and enhancing user experiences
A systematic review of machine learning in groundwater monitoring
Get PDFWith increasing concerns about water scarcity, groundwater has become crucial since this resource provides most of the freshwater needs. However, various human and natural activities often contaminate the groundwater, making it unsuitable for use. Over the years, scientists and engineers have used many methods to predict and track groundwater contamination as part of environmental monitoring. Consequently, there is an urgent need for improved methods, particularly in the face of increasing contamination. Machine learning has sometimes been used to monitor groundwater, air quality, and climate. Traditional methods must be improved due to the complexity and large amount of environmental data. This includes using hybrid models that combine traditional and new techniques. Despite the use of machine learning in many scientific areas, there is a lack of comprehensive reviews focusing on its use in environmental monitoring, especially groundwater monitoring. We aim to fill this gap by exploring machine-learning applications in groundwater monitoring. We discuss relevant methods, their limitations, and future potential. We summarize research on automating data processing and model training using groundwater sensor data. Our research underscores the transformative potential of machine learning to revolutionize long-term groundwater monitoring and contamination detection, providing valuable insights for future research and practical applications
Feedbacks Between Fjord Circulation, Mélange Melt, and the Subglacial Discharge Plume at Kangerlussuaq Glacier, East Greenland
No full textIn recent decades, the Greenland ice sheet has been losing ice and contributing substantially to global sea level rise. Approximately half of this recent loss is due to glacier acceleration, increasing the calving of icebergs into the ocean. This process has been linked with increased ocean heat content on the continental shelf, yet the pathways delivering this heat into Greenland\u27s fjords and its interactions with fjord-scale processes modulating glacier ice loss are still unclear. In this study, we use a series of numerical ocean model configurations to examine feedbacks between ocean circulation, subglacial discharge, submarine glacier melt, and ice mélange in Kangerlussuaq Fjord—a major fjord system where Greenland\u27s third-largest glacier terminates. We find that subglacial discharge is a major control on ocean properties, increasing the up-fjord advection of deep warm water more than 10-fold over fjords without discharge and modulating ocean temperature on the continental shelf near the fjord mouth. Further, discharge-driven upwelling increases ice mélange melt 3-fold, revealing that subglacial discharge is an important control on mélange melt, particularly in the summer when submarine glacier melt and subsequent glacier retreat is highest. These results suggest that subglacial plume activity contributes to the strong correlation between mélange thickness and retreat noted in previous studies and may contribute to extensive future retreat at Kangerlussuaq Glacier
How We Could Have Libertarian Free Will even if God Were a Total Know-It-All about the Future
Get PDFWe argue that libertarianism (roughly, the thesis that we have indeterministic, libertarian free will) is compatible with God\u27s infallible foreknowledge. We use eternalism (roughly, the thesis that reality is a 4-dimensional block and that past, present, and future objects exist) as an explanatory stepping stone between libertarianism and God\u27s foreknowledge: eternalism entails that (and comes close to explaining how) an omniscient God would know what we decide in the future even if we have libertarian free will. This account also explains what is wrong with standard fatalist arguments for the incompatibility of free will and God\u27s foreknowledge
The impact of vacations on urban women\u27s well-being from the perspective of feminist urbanism
Get PDFVacations are known to foster well-being outcomes, yet few researchers have accounted for the influence of individual attributes such as gender, residential setting, or cultural context. As a result, there is a noticeable gap in the well-being literature concerning well-being outcomes for female travelers whose subjectivities have been shaped in as well as by their residential environment (urban) and culture. Using qualitative inquiry informed by the feminist urbanism perspective, this study uncovered urban Chinese women\u27s cognitive representations of well-being outcomes from vacations. Findings revealed that vacations provide liberation from cultural constraints, boosting of social bonds and relationship building, enabling reflection on life and personal identity, and fostering learning and personal growth. Our findings, which integrated a feminist urbanism perspective that allowed for the influence of context (e.g., culture) as well as gender, partly overlap with existing research but also introduced new cognitive representations of well-being that advance well-being research
The evolving impacts of destination crisis event strength on tourists’ boycotting behavior: a crisis life cycle perspective
No full textDrawing on the crisis life cycle theory, this research examines the change patterns in tourist’ perceptions across the different stages of a destination crisis regarding a destination crisis event strength and likelihood of boycotting in response. The moderating effects of destination crisis event type and crisis response strategy were examined. The findings suggest the strength of tourists’ perception and interest in boycotting over the course of crisis follows a predictable inverted U-shape, a result that is robust to different crisis types. The result was also robust to both the apology and compensation response strategies. For both types the impact of the strategies did not differ significantly in the chronic crisis and crisis resolution stages. These findings indicate that destination crisis event managers should safeguard the interests of tourists and the sustainable development of the tourism industry by choosing response strategies according to the nature and cause of the crisis event
On Two-generator Subgroups of Mapping Torus Groups
Get PDFWe prove that if (Formula presented.) is the mapping torus group of an injective endomorphism (Formula presented.) of a free group (Formula presented.) (of possibly infinite rank), then every two-generator subgroup (Formula presented.) of (Formula presented.) is either free or a (finitary) sub-mapping torus. As an application we show that if (Formula presented.) is a fully irreducible atoroidal automorphism, then every two-generator subgroup of (Formula presented.) is either free or has finite index in (Formula presented.)