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Climate change is impacting the function and distribution of habitats used by marine, coastal, and diadromous species. These impacts often exacerbate the anthropogenic stressors that habitats face, particularly in the coastal environment. We conducted a climate vulnerability assessment of 52 marine, estuarine, and riverine habitats in the Northeast U.S. to develop an ecosystem-scale understanding of the impact of climate change on these habitats. The trait-based assessment considers the overall vulnerability of a habitat to climate change to be a function of two main components, sensitivity and exposure, and relies on a process of expert elicitation. The climate vulnerability ranks ranged from low to very high, with living habitats identified as the most vulnerable. Over half of the habitats examined in this study are expected to be impacted negatively by climate change, while four habitats are expected to have positive effects. Coastal habitats were also identified as highly vulnerable, in part due to the influence of non-climate anthropogenic stressors. The results of this assessment provide regional managers and scientists with a tool to inform habitat conservation, restoration, and research priorities, fisheries and protected species management, and coastal and ocean planning.

Data extraction algorithms on data hypercubes, or datacubes, are traditionally only capable of cutting boxes of data along the datacube axes. For many use cases however, this returns much more data than users actually need, leading to an unnecessary consumption of I/O resources. In this paper, we propose an alternative feature extraction technique, which carefully computes the indices of data points contained within user-requested shapes. This enables data storage systems to only read and return bytes useful to user applications from the datacube. Our main algorithm is based on high-dimensional computational geometry concepts and operates by successively reducing polytopes down to the points contained within them. We analyse this algorithm in detail before providing results about its performance and scalability. In particular, we show it is possible to achieve data reductions of up to 99% using this algorithm instead of current state of practice data extraction methods, such as meteorological field extractions from ECMWF’s FDB data store, where feature shapes are extracted a posteriori as a post-processing step. As we discuss later on, this novel extraction method will considerably help scale access to large petabyte size data hypercubes in a variety of scientific fields.

Salmo salar (Atlantic Salmon) smolts are exposed to predation pressure as they migrate from freshwater into the estuary and near-shore marine environment. In particular, Phalacrocorax auritus (Double-crested Cormorants) are a predator of Atlantic salmon smolts during their estuary and near-shore migration. National Oceanic and Atmospheric Administration's (NOAA) National Marine Fisheries Services’ (NMFS) telemetry data collected prior to this study (1997–2003), suggest that smolts are being removed from the Narraguagus River on their downstream out-migration. This removal may be the result of Cormorant predation. We investigated whether smolt survival could be improved by disrupting normal Cormorant foraging activity by integrating passive smolt tracking and active harassment techniques. Smolt movement and usage of various portions of the estuary according to light condition and tidal stage were explored along with concurrent avian harassment. Although harassment only occurred in approximately 33% of available daylight hours during this study, the impacts were easily recognized. Non-lethal harassment effectively displaced Cormorants from feeding locations and reduced loss of emigrating smolts. In 2004, 83.3% (15 of 18) of all smolt mortalities occurred on days of non-harassment, compared to only 16.7% (3 of 18) on days when harassment occurred. Similarly in 2005, 87.5% (7 of 8) of all smolt mortalities occurred on days of non-harassment, compared to only 12.5% (1 of 8) on days when harassment occurred. Non-lethal harassment appeared to be an effective means to reduce loss of emigrating smolts in the Narraguagus River estuary.

All anadromous fishes, including juvenile salmon, encounter estuarine habitats as they transition from riverine to marine environments. We compare the estuarine use between juvenile Atlantic salmon (Salmo salar) in the Penobscot River estuary and Pacific salmon (Oncorhynchus spp.) in the Columbia River estuary. Both estuaries have been degraded by anthropogenic activities. Atlantic and Pacific salmon populations in both basins rely heavily on hatchery inputs for persistence. Pacific salmon, as a group, represent a continuum of estuarine use, from species that move through rapidly to those that make extensive use of estuarine habitats. While Atlantic salmon estuarine use is predominantly similar to rapidly moving Pacific salmon, they can exhibit nearly the entire range of Pacific salmon estuarine use. Both slow and rapidly migrating Atlantic and Pacific salmon actively feed in estuarine environments, consuming insect and invertebrate prey. Interactions between juvenile salmon and estuarine fish communities are poorly understood in both estuaries, although they experience similar avian and marine mammal predators. Estuaries are clearly important for Atlantic and Pacific salmon, yet our understanding of this use is currently insufficient to make informed judgments about habitat quality or overall estuary health. This review of salmonid migration through and residency within estuaries identifies actions that could hasten restoration of both Atlantic and Pacific salmon populations.

Emerald Basin on the Scotian Shelf off Nova Scotia, Canada, is home to a globally unique population of the glass sponge Vazella pourtalesi. Through the analysis of both in situ photographs and trawl catch data from annual multispecies bottom-trawl surveys, we examined community composition, species density, and abundance of epibenthos and fish associated with V. pourtalesi compared to locations without this sponge. Using generalized linear models and analysis of similarities, the importance of V. pourtalesi in enhancing species density and abundance of the associated epibenthic community was assessed against that of the hard substrate on which it settles. Our results indicated that the megafaunal assemblage associated with V. pourtalesi was significantly different in composition and higher in species density and abundance compared to locations without V. pourtalesi. Analysis of similarity of trawl catch data indicated that fish communities associated with the sponge grounds are significantly different from those without V. pourtalesi, although no species were found exclusively on the sponge grounds. Our study provides further evidence of the role played by sponge grounds in shaping community structure and biodiversity of associated deep-sea epibenthic and fish communities. The mechanism for biodiversity enhancement within the sponge grounds formed by V. pourtalesi is likely the combined effect of both the sponge itself and its attachment substrate, which together comprise the habitat of the sponge grounds. We also discuss the role of habitat provision between the mixed-species tetractinellid sponges of the Flemish Cap and the monospecific glass sponge grounds of Emerald Basin.

Supercomputing power has been doubling approximately every 14 months for at least three decades, increasing the capabilities of scientific modelling at a similar rate. The first machines capable of one ExaFLOP (1018 floating-point operations per second) are expected by 2020. However, architectural changes required to reach 'exascale' are significant, with energy efficiency constraints leading to a huge growth in parallelization. A new era of computing has arrived, dubbed the 'many-core' era, in which the number of computing cores is increasing faster than CFD simulation sizes - prompting the research question for this thesis: 'What limits the strong scalability of CFD and its ability to handle many-core architectures? What can be done to improve the CFD algorithms in this respect?' A number of scalability investigations have been performed from 1 through to 2048 cores, using a semi-implicit, finite-volume CFD code: ReFRESCO; and the University of Southampton supercomputer: Iridis4. The main bottleneck to strong scalability is shown to be the linear equation-system solvers, occupying up to 95% of total wall-time on 2048 cores - where the poor scalability arises from synchronous, global, inter-process communications. Experiments have been performed with alternative, state-of-the-art linear solvers and preconditioners, without significant improvements, which motivates novel research into scalable linear solvers for CFD. The theory of 'chaotic relaxation' has been used to create a completely asynchronous Jacobi-like 'chaotic solver', showing almost perfect scalability, and performance far greater than their synchronous counterparts. However, these solvers lack the absolute numerical power to compete with existing solvers, especially as the resolution of the simulations increases. Following this, chaotic relaxation theory has been used to create a novel 'chaotic-cycle' multigrid solver, combining aspects of the chaotic solver and classical multigrid methods. Both of the solvers have been verified and tested using canonical test cases and practical CFD simulations. On 2048 cores, the chaotic-cycle multigrid solver performs up to 7.7× faster than a typical Krylov Subspace solver and 13.3× faster than classical V-cycle multigrid. With improvements to the implementation of coarse-grid communications and desynchronized residual computations, it is likely that the chaotic-cycle multigrid method will continue scaling to many thousands of cores, thus removing the main bottleneck to the strong-scalability of CFD. The novel chaotic solver and chaotic-cycle multigrid methods have been implemented as an open-source library, Chaos. It is hoped that work on these scalable solvers can be continued and applied to other disciplines.

This study presents the ClimEmpower framework, a user-driven approach to enhancing climate resilience across five climate-vulnerable regions in Southern Europe: Costa del Sol (Spain), Central Greece, the Troodos Mountains (Cyprus), Osijek-Baranja County (Croatia), and Sicily (Italy). The project employs a region-specific methodology that integrates climate risk assessments, stakeholder engagement through Communities of Practice (CoPs), and the development of innovative climate services tailored to local needs. These regions, characterized by unique environmental and socio-economic vulnerabilities, face shared hazards such as droughts, heatwaves, and floods, alongside region-specific challenges like salinization and biodiversity loss. ClimEmpower identifies critical gaps in high-resolution data, cross-sectoral collaboration, and capacity-building efforts, underscoring barriers to effective adaptation. This work aims to provide a foundational resource, offering a comprehensive overview of the current situation, including needs, gaps, priorities, and expectations across the target regions. By establishing this baseline, it facilitates future research and comparative analyses, contributing to the development of robust, region-specific resilience strategies. The ClimEmpower framework offers scalable and replicable solutions aligned with the European Green Deal’s climate resilience goals, advancing adaptation planning and providing actionable insights for broader European initiatives.

The collective response of electrons in an ultrathin foil target irradiated by an ultraintense (${\\sim}6\\times 10^{20}~\\text{W}~\\text{cm}^{-2}$) laser pulse is investigated experimentally and via 3D particle-in-cell simulations. It is shown that if the target is sufficiently thin that the laser induces significant radiation pressure, but not thin enough to become relativistically transparent to the laser light, the resulting relativistic electron beam is elliptical, with the major axis of the ellipse directed along the laser polarization axis. When the target thickness is decreased such that it becomes relativistically transparent early in the interaction with the laser pulse, diffraction of the transmitted laser light occurs through a so called ‘relativistic plasma aperture’, inducing structure in the spatial-intensity profile of the beam of energetic electrons. It is shown that the electron beam profile can be modified by variation of the target thickness and degree of ellipticity in the laser polarization.

Earth science datasets are growing rapidly in both volume and structural complexity. They increasingly contain richly labelled data with heterogeneous metadata and complex internal constraints that impose dependencies between variables and dimensions. Datacubes have become a common abstraction for organising such datasets, but traditional dense and orthogonal datacube models struggle to represent irregular, sparse or branching data spaces efficiently. In this paper, we introduce a generalised data hypercube representation based on compressed tree structures, which enables an accurate and compact description of complex data spaces. We describe the design of this representation and analyse its ability to capture sparsity and conditional relationships while remaining efficient to traverse. Using a concrete implementation, we study the performance characteristics of compressed tree data hypercubes and demonstrate their effectiveness as fast, cache-like indices over large backend data stores. Building on this representation, we present an integrated feature extraction system that operates directly on tree-based data hypercubes within the Polytope framework. By embedding data access strategies into the data hypercube abstraction itself, the system enables precise, sub-field data extraction and supports flexible, user-driven access patterns. We evaluate the performance of the integrated system and show how it enables new ways of interacting with complex datasets that are difficult to support using traditional access models. This work bridges the gap between expressive data hypercube models and efficient data access methods. In particular, it provides a unified framework that combines tree-based data representations with feature extraction capabilities. The proposed approach therefore offers a foundation for scalable and user-centric access to large heterogeneous Earth science datasets.

In the past 15 years, Pioneer Bank has introduced checking accounts, shifted focus from mortgage to retail and commercial lending, doubled checking accounts, added Internet banking, added mobile banking, built a new headquarters and doubled assets. \"For a community bank with 16 locations spread out over 300 miles, the capability to create efficient service solutions is vital,\" said Bancsource CEO Mychal Kempt, who previously was head of North American sales and services at Diebold.