Atmospheric and Oceanic Sciences

Abstract A long‐standing formulation of quasilinear theory (Lyons, 1974b, https://doi.org/10.1017/s002237780002537x ), widely applied to wave‐particle interactions in the radiation belts and elsewhere, has recently been reconsidered (Cunningham, 2023, https://doi.org/10.1029/2023ja031703 ), focusing on several underexamined issues. One concerns the representation of Fourier‐transformed wave magnetic intensity as a frequency‐dependent term times a factor depending on wave normal angle, and its proper normalization. Here, the traditional version and its proposed replacement are shown to be mathematically equivalent, if their construction from individual wave measurements is done appropriately. Coordinate invertibility, behavior near the whistler‐mode resonance cone, and superposition are also addressed.

Urbanisation is reshaping ecosystems and increasing human–wildlife interactions. Wild boar (Sus scrofa), a highly adaptable species, is increasingly common in European cities, where it exploits natural and anthropogenic resources, often leading to conflict. Predicting when and where wild boars enter urban areas remains challenging, particularly using scalable tools such as remote sensing. Here, we show that temporal and spatial drivers of urban presence are decoupled in Barcelona over a 14-year period. Seasonal vegetation dynamics influenced the timing of urban incursions, with peaks in spring and late summer associated with changes in vegetation moisture and likely reinforced by increased energetic demands during reproduction and early lactation. However, remotely sensed vegetation indices captured these dynamics only partially, limiting their predictive power when used alone. Spatial variation in urban green area use was primarily explained by landscape structure, with proximity to streams and habitat fragmentation contributing similarly. Green areas near natural corridors were concentrated higher and had more variable presence, while heterogeneous landscapes likely facilitated repeated use by increasing access to foraging and refuge. Integrating remote sensing with landscape metrics can improve the anticipation and management of human–wildlife conflicts.

Abstract This article presents a systematic review on child and youth participation in climate assemblies. The objective is to analyse the experiences carried out to date, their evaluation processes and the impacts derived from them. With the PRISMA methodology, 18 documents, published between 2014 and 2025, were identified that describe 22 experiences in government-led, community and school contexts. The results show that most of the initiatives are promoted and run by adults, and the participation of children and young people tends to be consultative in nature. The assessment of the impact of these experiences is mainly based on facilitators’ and participants’ perceptions and testimonies without rigorous frameworks that make it possible to measure real effects at the individual, community, environmental and political levels. This lack of systematicity limits the understanding of the true scope of these initiatives. Therefore, the research highlights the need to develop robust assessment frameworks to measure real social impact and move towards more meaningful, inclusive and transformative youth participation in climate governance processes.

Hyperspectral images (HSIs) simultaneously capture spatial and spectral information of a target. Compared with conventional visible-light images, HSI can offer higher spectral resolution that facilitates more detailed characterization. However, most existing HSI classification methods primarily emphasize low-level and high-level feature interactions while lacking effective encoding of mid-level interactions, which are often more discriminative. Moreover, HSI classification is typically conducted with patch-based inputs; although this approach facilitates the extraction of spatial information surrounding the central pixel, it tends to inadvertently dilute the network’s focus away from the central pixel. To address these challenges, we propose a Large-to-Small Kernel Guided Multi-Level Aggregation network (LSGMA). A novel Multi-Level Aggregation (MLA) module is designed, which enhances the network’s emphasis on mid-level features. It enables the simultaneous extraction of low-, mid-, and high-level features, thereby ultimately improving the classification accuracy of the model. In addition, a Large-to-Small Kernel Guided Focus (LSGF) module is introduced that more effectively captures spatial neighborhood cues while maintaining strong focus on central features. Extensive experiments on four public datasets demonstrate that the proposed LSGMA network achieves superior performance compared with several state-of-the-art methods.

Anchoring systems for deep-water floating structures must withstand complex, hydro-mechanical (H-M) coupled uplift forces throughout an operational life extending over decades, yet fundamental understanding of this complicated H-M behavior remains insufficient. This paper presents a comprehensive review of H-M coupled foundation–seabed interactions under uplift loading. Key experimental findings are synthesized to demonstrate that the fundamental distinction between uplift and compression lies in the foundation-soil interface. Unique interfacial uplift behaviors are highlighted, including the progressive formation of an interfacial gap and the evolution of transient suction within it. This water-filled gap enables sustained tensile contact stress post-detachment, transforming traditional soil-structure interaction to the more general “soil–interfacial fluid–structure” interaction framework. A 1D conceptual model, representing a mechanistic extension of Terzaghi’s consolidation theory, is discussed to further elucidate these H-M mechanisms. For complex 3D numerical simulations, the limitations of traditional total-stress interface models are discussed, and specialized H-M thin-layer and zero-thickness interfaces designed for uplift modeling are critically examined regarding their advantages and limitations. The review concludes by outlining a roadmap for the next research frontier: high-fidelity treatments of sustained multidirectional cyclic loading, suction-induced liquefaction, and the long-term rheological evolution of the interface.

To improve emergency response efficiency in passenger ship fire accidents and ensure the life safety of passengers and crew, this paper proposes a dynamic route planning model for passenger ship fire evacuation that accounts for fire spread. Firstly, a passenger ship fire spread model is established based on the field simulation theory, and an emergency evacuation network model is constructed by determining the evacuation network topology from the fire propagation process. Secondly, the factors affecting emergency evacuation route planning during fire spread are analyzed, and a multi-objective optimization model for dynamic evacuation routes is developed. Thirdly, an improved ant colony optimization algorithm is designed to solve the problem. Finally, using the RP1 vessel from the publicly available ship evacuation dataset of the EU Seventh Framework Program SAFEGUARD project as a case study, simulation and comparative experiments are conducted. The results show that, in medium- and large-scale evacuation problems, the proposed method consistently maintains higher computational efficiency compared with the DABD algorithm and the FOA. In terms of objective optimization, it demonstrates that the proposed method has better effectiveness and feasibility than the shortest-path evacuation strategy, as it minimizes evacuation cost while satisfying assembly station capacity constraints and achieves a more balanced utilization of all emergency exits.