Article
Computer Science, Hardware & Architecture
Zaid Yemeni, Haibin Wang, Waleed M. Ismael, Yanan Wang, Zhengming Chen
Summary: This study proposes an approach to reduce spatial and temporal redundancy in sensor-generated data, prolonging the lifespan of sensors and networks with balanced data reliability. The approach utilizes two levels, with the end nodes reducing temporal redundancy using Kalman filter, and the sink/base station minimizing spatial redundancy with SLGA and SLAA algorithms. Results show the proposed approach outperforms PFF and REDA algorithms in terms of redundancy and accuracy while maintaining acceptable energy consumption levels.
Article
Multidisciplinary Sciences
Rachel A. Short, Jenny L. McGuire, P. David Polly, A. Michelle Lawing
Summary: We are currently experiencing a modern biodiversity crisis that will reshape global community compositions and ecological functions. This study examines the relationship between vegetation cover and locomotor traits for artiodactyl and carnivoran communities using ecometrics. The results show that combining the locomotor traits of primary consumers (artiodactyls) and secondary consumers (carnivorans) into one trophically integrated ecometric model strengthens the ability to detect a functional relationship. Furthermore, applying this integrated model to paleontological sites reveals mismatches in the past and today, demonstrating the utility of the model for understanding community traits and their associated vegetations over time.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2023)
Article
Ecology
Carlos Zaragoza-Trello, Montserrat Vila, Jeroen Scheper, Isabelle Badenhausser, David Kleijn, Ignasi Bartomeus
Summary: By comparing pollination activity at the edge and centre of crop fields and over the day, we found that spatial and temporal niche complementarity significantly influences sunflower crop production. Only the visitation rate of hoverflies slightly differed between the centre and the edge of the fields, but plants pollinated only by small-sized pollinators experienced a decline in seed production with distance from the edge. Different pollinator species showed complementary peak activity periods throughout the day, and plants pollinated only in the morning or afternoon had higher seed weights.
BASIC AND APPLIED ECOLOGY
(2023)
Article
Computer Science, Artificial Intelligence
Mourad Lablack, Yanming Shen
Summary: Traffic forecasting is crucial for intelligent transportation systems. However, accurately predicting traffic conditions is challenging due to the complexity of traffic behavior and the non-Euclidean nature of traffic data. In this paper, we propose a highly optimized model called Spatio-Temporal Graph Mixformer (STGM) network, which utilizes a novel attention mechanism to capture the correlation between temporal and spatial dependencies. We address previous limitations by using convolution layers with different fields of view to capture long-short term temporal dependency, and by training an estimator model to express the contribution of a node to the desired prediction.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Fisheries
Juan F. Espinola-Novelo, Marcelo E. Oliva
Summary: The study evaluated the potential spatial and temporal variability of parasite communities affecting three marine fish species collected between 1993 and 2017. The results showed differences in the prevalence of most taxa at spatial and temporal scales, with some larval endoparasites remaining constant over time. Spatial stability was observed in samples from different localities, while temporal variability was noted in samples from different years. Temporal variability must be taken into account in studies regarding parasites as a tool for stock identification.
Article
Computer Science, Software Engineering
Chuanjun Ji, Yadang Chen, Zhi-Xin Yang, Enhua Wu
Summary: This paper explores the spatial-temporal redundancy issue in video object segmentation under a semi-supervised context and proposes an efficient VOS method. The proposed method reduces redundancy through spatio-temporal compression and improves computational efficiency through an efficient memory reader. Experimental results demonstrate its high performance on multiple datasets.
Article
Statistics & Probability
Francesca Gasperoni, Alessandra Luati, Lucia Paci, Enzo D'Innocenzo
Summary: A simultaneous autoregressive score-driven model is proposed for spatio-temporal data with heavy tails. It decomposes the spatially filtered process into a signal and noise, where the signal is approximated by a nonlinear function of past variables and explanatory variables, and the noise follows a multivariate Student-t distribution. The model's key feature is that the dynamics of the space-time varying signal are driven by the score of the conditional likelihood function. The score provides a robust update for the space-time varying location when the distribution is heavy-tailed. The study applies this model to brain scans recorded through functional magnetic resonance imaging, aiming to identify spontaneous activations in the brain regions by considering spatial and temporal dependence.
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
(2023)
Article
Ecology
Fearghal O'Donncha, Yihao Hu, Paulito Palmes, Meredith Burke, Ramon Filgueira, Jon Grant
Summary: This study introduces a novel spatio-temporal LSTM architecture for time series forecasting in environmental datasets, demonstrating its ability to accurately replicate complex signals and provide high performance. Learning from multiple sensors simultaneously can enhance robustness to missing data.
ECOLOGICAL INFORMATICS
(2022)
Article
Computer Science, Artificial Intelligence
Azad Deihim, Eduardo Alonso, Dimitra Apostolopoulou
Summary: The prevalence of multivariate time series data has led to significant research and advancements in multivariate time series analysis. In this study, we propose a Spatio-Temporal Transformer with Relative Embeddings (STTRE) that incorporates the spatio-temporal nature of the data and achieves improved accuracy compared to other models.
Article
Environmental Sciences
Hui Fu, Korhan ozkan, Guixiang Yuan, Liselotte Sander Johansson, Martin Sondergaard, Torben L. Lauridsen, Erik Jeppesen
Summary: The study assessed the seasonal and annual trends in zooplankton community dynamics across 20 Danish lakes. It found significant seasonality and inter-annual decreases in spatial heterogeneity of zooplankton, with biotic drivers such as phytoplankton, macrophytes, and fish playing important roles. Local and regional drivers were identified as important variables influencing spatial zooplankton heterogeneity.
SCIENCE OF THE TOTAL ENVIRONMENT
(2021)
Article
Multidisciplinary Sciences
Brian A. Hoover, Marisol Garcia-Reyes, Sonia D. Batten, Chelle L. Gentemann, William J. Sydeman
Summary: The spatial structuring of mid-trophic level forage communities in the Gulf of Alaska is found to be stable yet influenced by ocean climatic conditions, with coastal communities showing greater variability compared to the central basin. This study highlights the importance of understanding spatial persistence and variability in regional communities for the overall health of fisheries and marine wildlife populations in the ecosystem.
Article
Automation & Control Systems
Xiangxiang Dai, Peng Yang, Xinyu Zhang, Zhewei Dai, Li Yu
Summary: The article proposes a system called Respire, which removes redundant frames on edge computing nodes to reduce the cost of transmission and processing while maintaining high analytic accuracy.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Environmental Sciences
Neeraj K. Singh, Markandeya, Manish K. Manar, Sheo P. Shukla, Devendra Mohan
Summary: Due to rapid urbanization and exponential growth in transportation, traffic noise has become a major concern as it not only disrupts daily life but also has severe adverse health effects on humans and can even lead to mortality. This paper focuses on analyzing the noise levels in Lucknow city over a decade and establishes its correlation with the impact on human health in terms of annoyance and sleep disturbance. The study reveals that the noise levels exceed prescribed standards in most locations during both day and night time, with Charbagh being the worst affected by noise pollution. The increase in noise levels over time has resulted in a higher percentage of residents experiencing sleep disturbance and annoyance.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2023)
Review
Computer Science, Artificial Intelligence
Jin Fan, Ke Zhang, Yipan Huang, Yifei Zhu, Baiping Chen
Summary: As industrial systems become more complex and monitoring sensors become more ubiquitous, multivariate time series prediction plays an increasingly important role in society. While recurrent neural networks with attention are the current state-of-the-art for this task, their limitations in handling complex data and long-term forecasting are recognized. This paper introduces a framework called PSTA-TCN, which combines parallel spatio-temporal attention mechanisms and stacked temporal convolutional networks (TCNs) to address these challenges. The proposed framework significantly reduces training time and improves accuracy, enabling stable predictions with windows up to 13 times longer than current methods.
NEURAL COMPUTING & APPLICATIONS
(2023)
Article
Chemistry, Analytical
Wenhao Wang, Zhenbing Liu, Haoxiang Lu, Rushi Lan, Zhaoyuan Zhang
Summary: This study proposes a new method for real-time video super-resolution, which effectively utilizes spatial and temporal information to generate high-resolution frames. The experimental results show that the proposed method achieves strong quantitative performance and visual quality, making it suitable for real-world deployment.
Article
Multidisciplinary Sciences
Matthew McLean, Rick D. Stuart-Smith, Sebastien Villeger, Arnaud Auber, Graham J. Edgar, M. Aaron MacNeil, Nicolas Loiseau, Fabien Leprieur, David Mouillot
Summary: Research indicates that despite differences in biogeography and evolutionary history, similar environments host reef fish assemblages with similar trait compositions. This suggests that similar trait-based management strategies can be applied across different regions, potentially leading to improved conservation outcomes.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2021)
Article
Biochemistry & Molecular Biology
Kelig Mahe, Bruno Ernande, Marc Herbin
Summary: The coelacanth, discovered in 1938, is likely to have a lifespan of around 100 years, making it one of the longest-living fish species. Despite its slow growth rate and life history, the coelacanth may be more threatened than previously considered due to its biological characteristics.
Article
Biochemistry & Molecular Biology
Matthew McLean, David Mouillot, Aurore A. Maureaud, Tarek Hattab, M. Aaron MacNeil, Eric Goberville, Martin Lindegren, Georg Engelhard, Malin Pinsky, Arnaud Auber
Summary: As climate change progresses, species are moving towards the poles while subtropical and tropical species are entering temperate environments. The Community Temperature Index (CTI) has been widely used to track the mean thermal affinity of a community, showing an increase under global warming. However, this increase is not solely due to the rise in warm-affinity species, but also linked to the decrease in cold-affinity species. Tropicalization is more pronounced in warmer areas that have experienced greater warming, while deborealization is stronger in areas closer to human populations or with higher thermal diversity in the community.
Review
Ecology
David Mouillot, Nicolas Loiseau, Matthias Grenie, Adam C. Algar, Michele Allegra, Marc W. Cadotte, Nicolas Casajus, Pierre Denelle, Maya Gueguen, Anthony Maire, Brian Maitner, Brian J. McGill, Matthew McLean, Nicolas Mouquet, Francois Munoz, Wilfried Thuiller, Sebastien Villeger, Cyrille Violle, Arnaud Auber
Summary: Trait-based ecology aims to understand the impact of organismal trait diversity on ecosystem functioning and involves clustering species based on traits to identify those with unique combinations. A synthesis across multiple datasets shows a trade-off between trait space quality and operability between three to six dimensions, with low but variable robustness to trait omission. Invariant scaling relationships are highlighted, showing that as species richness increases, the number of unique species saturates while species disproportionately pack in the richest cluster.
Article
Environmental Sciences
Charles-Andre Timmerman, Carolina Giraldo, Pierre Cresson, Bruno Ernande, Morgane Travers-Trolet, Manuel Rouquette, Margaux Denamiel, Sebastien Lefebvre
Summary: This study found that the coupling between benthic and pelagic habitats in the Eastern English Channel is a permanent feature, potentially favored by shallow depth and driven by two trophic processes. Resource partitioning and the presence of generalist species allow fish to fully utilize available resources, maintaining the coupling between benthic and pelagic habitats.
MARINE ENVIRONMENTAL RESEARCH
(2021)
Article
Multidisciplinary Sciences
Kelig Mahe, Kirsteen MacKenzie, Djamila Ider, Andrea Massaro, Oussama Hamed, Alba Jurado-Ruzafa, Patricia Goncalves, Aikaterini Anastasopoulou, Angelique Jadaud, Chryssi Mytilineou, Marine Randon, Romain Elleboode, Alaia Morell, Zouhir Ramdane, Joanne Smith, Karen Bekaert, Rachid Amara, Helene de Pontual, Bruno Ernande
Summary: The study suggests that directional bilateral asymmetry in otolith shape could be a new method for stock identification. Research on common sole and bogue shows significant asymmetry among individuals caught in different locations, indicating potential separation based on shape asymmetry.
Article
Fisheries
Marion Claireaux, Fabian Zimmermann, Bruno Ernande, Mikko Heino, Katja Enberg
Summary: Growth is an important aspect of population dynamics and fisheries management. The influences of extrinsic and intrinsic factors on growth vary, with the importance of extrinsic factors changing over time. The effects of the environment on growth become less clear and relevant as the time series lengthens.
CANADIAN JOURNAL OF FISHERIES AND AQUATIC SCIENCES
(2022)
Article
Fisheries
Manuel Hidalgo, Valerio Bartolino, Marta Coll, Mary E. Hunsicker, Morgane Travers-Trolet, Howard Browman
Summary: The global challenge of climate change requires urgent development of innovative adaptive solutions for managing marine resources. Contributions to a themed article set explore emerging climate change impacts, assess system risks, evaluate adaptation options, and consider societal perceptions. Future development in adaptation science will require interdisciplinary collaboration and concrete solutions to address the challenges of climate change and human activity.
ICES JOURNAL OF MARINE SCIENCE
(2022)
Article
Multidisciplinary Sciences
Marine Ballutaud, Morgane Travers-Trolet, Paul Marchal, Stanislas F. Dubois, Carolina Giraldo, Andrew C. Parnell, M. Teresa Nuche-Pascual, Sebastien Lefebvre
Summary: Stable isotope mixing models are used to reconstruct animal diet, but current research neglects the dynamics of isotopic ratios and the impact of time lag on diet reconstruction. By using a dynamic mixing model, it is possible to more accurately estimate the consumer's diet and avoid misinterpretation in ecosystem functioning and food-web structure analysis.
Letter
Multidisciplinary Sciences
Enric Sala, Juan Mayorga, Darcy Bradley, Reniel B. Cabral, Trisha B. Atwood, Arnaud Auber, William Cheung, Christopher Costello, Francesco Ferretti, Alan M. Friedlander, Steven D. Gaines, Cristina Garilao, Whitney Goodell, Benjamin S. Halpern, Audra Hinson, Kristin Kaschner, Kathleen Kesner-Reyes, Fabien Leprieur, Jane Lubchenco, Jennifer McGowan, Lance E. Morgan, David Mouillot, Juliano Palacios-Abrantes, Hugh P. Possingham, Kristin D. Rechberger, Boris Worm
Article
Multidisciplinary Sciences
Arnaud Auber, Conor Waldock, Anthony Maire, Eric Goberville, Camille Albouy, Adam C. Algar, Matthew McLean, Anik Brind'Amour, Alison L. Green, Mark Tupper, Laurent Vigliola, Kristin Kaschner, Kathleen Kesner-Reyes, Maria Beger, Jerry Tjiputra, Aurele Toussaint, Cyrille Violle, Nicolas Mouquet, Wilfried Thuiller, David Mouillot
Summary: This study presents a functional vulnerability framework that incorporates uncertainty and reference conditions, allowing for the quantification of vulnerability to a wide range of threats. Through case studies on marine fishes and mammals, the study demonstrates the relevance and operationality of the framework, as well as the geographic and temporal patterns of functional vulnerability.
NATURE COMMUNICATIONS
(2022)
Article
Ecology
Francois Munoz, Christopher A. Klausmeier, Pierre Gauzere, Gaurav Kandlikar, Elena Litchman, Nicolas Mouquet, Annette Ostling, Wilfried Thuiller, Adam C. Algar, Arnaud Auber, Marc W. Cadotte, Leo Delalandre, Pierre Denelle, Brian J. Enquist, Claire Fortunel, Matthias Grenie, Nicolas Loiseau, Lucie Mahaut, Anthony Maire, David Mouillot, Catalina Pimiento, Cyrille Violle, Nathan J. B. Kraft
Summary: Recent work has demonstrated that evaluating the distinctiveness of functional traits, which is the average trait distance of a species to other species in a community, can provide valuable insights into the dynamics of biodiversity and ecosystem functioning. However, the underlying ecological mechanisms that drive the emergence and persistence of functionally distinct species are not well understood. In this study, we address this issue by considering a heterogeneous fitness landscape, where functional dimensions encompass peaks that represent trait combinations resulting in positive population growth rates in a community. We identify four ecological cases that contribute to the emergence and persistence of functionally distinct species and provide examples and guidelines to distinguish between them. Additionally, we explore how stochastic dispersal limitation can lead to functional distinctiveness. Our framework offers a novel perspective on the relationship between fitness landscape heterogeneity and the functional composition of ecological assemblages.
Article
Evolutionary Biology
Andy Boens, Bruno Ernande, Pierre Petitgas, Christophe Lebigre
Summary: The declines in growth of European anchovy and sardine are found to be related to both fishing pressure and environmental changes. The adaptive response is significant in anchovy, with larger individuals selectively disappearing and growth declining when biomass increases. In contrast, sardine shows a plastic response, with higher growth associated with increasing biomass and changes in food availability.
EVOLUTIONARY APPLICATIONS
(2023)
Article
Ecology
Noemie Coulon, Martin Lindegren, Eric Goberville, Aurele Toussaint, Aurore Receveur, Arnaud Auber
Summary: The aim of this study is to investigate whether threatened species are also functionally rare and to identify which traits determine extinction risk. The results of the study show that in European continental shelf seas, 38% of the species threatened with extinction (9 out of 24 species) were identified as the most functionally distinct. The study emphasizes that species traits, especially functional rarity, should become an indispensable step in the development of conservation management plans.
GLOBAL ECOLOGY AND BIOGEOGRAPHY
(2023)
Editorial Material
Multidisciplinary Sciences
Daniel Ovando, Owen Liu, Renato Molina, Ana Parma, Cody Szuwalski
