Halospeciosus flavus gen. nov., sp. nov. and Haladaptatus caseinilyticus sp. nov., halophilic archaea isolated from saline soil of an inland solar saltern and offshore sediment.

Two novel halophilic archaeal strains (XZGYJ-43T and ZJ1T) were isolated from Mangkang ancient solar saltern (Tibet, PR China) and Zhujiang river inlet (Guangdong, PR China), respectively. The comparison of the 16S rRNA gene sequences revealed that strain XZGYJ-43T is related to the current species of the family Halobacteriaceae (89.2-91.7% similarity) and strain ZJ1T showed 94.7-98.3% similarity to the current species of the genus Haladaptatus. Phylogenetic analyses based on 16S rRNA genes, rpoB' genes and genomes indicated that strain XZGYJ-43T is separate from the related genera, Halocalculus, Salarchaeum and Halarchaeum of the family Halobacteriaceae, and strain ZJ1T tightly clusters with the current species of the genus Haladaptatus. The average nucleotide identity, digital DNA-DNA hybridization and average amino acid identity values between strain XZGYJ-43T and the current species of the family Halobacteriaceae were 71-75, 20-25 and 59-68 %, and these values between strain ZJ1T and the current species of the genus Haladaptatus were 77-81, 27-32 and 76-82 %, respectively, clearly below the thresholds for prokaryotic species demarcation. These two strains could be distinguished from their relatives according to differential phenotypic characteristics. The major polar lipids of strain XZGYJ-43T were phosphatidic acid (PA), phosphatidylglycerol (PG), phosphatidylglycerol phosphate methyl ester (PGP-Me), mannosyl glucosyl diether (DGD-1; DGD-PA) and sulphated mannosyl glucosyl diether (S-DGD-1; S-DGD-PA), and those of strain ZJ1T were PA, PG, PGP-Me, DGD-PA, S-DGD-1 (S-DGD-PA) and sulphated galactosyl mannosyl glucosyl diether. Based on phenotypic, phylogenetic and genomic data, strain XZGYJ-43T (=CGMCC 1.13890T=JCM 33735T) represents a novel species of a new genus within the family Halobacteriaceae, and strain ZJ1T (=CGMCC 1.18785T=JCM 34917T) represents a novel species of the genus Haladaptatus, for which the names Halospeciosus flavus gen. nov., sp. nov. and Haladaptatus caseinilyticus sp. nov. are proposed, respectively.

Distinct Assembly Processes Structure Planktonic Bacterial Communities Among Near- and Offshore Ecosystems in the Yangtze River Estuary.

The estuarine system functions as natural filters due to its ability to facilitate material transformation, planktonic bacteria play a crucial role in the cycling of complex nutrients and pollutants within estuaries, and understanding the community composition and assembly therein is crucial for comprehending bacterial ecology within estuaries. Despite extensive investigations into the composition and community assembly of two bacterial fractions (free-living, FLB; particle-attached, PAB), the process by which bacterioplankton communities in these two habitats assemble in the nearshore and offshore zones of estuarine ecosystems remains poorly understood. In this study, we conducted sampling in the Yangtze River Estuary (YRE) to investigate potential variations in the composition and community assembly of FLB and PAB in nearshore and offshore regions. We collected 90 samples of surface, middle, and bottom water from 16 sampling stations and performed 16S rRNA gene amplicon analysis along with environmental factor measurements. The results unveiled that the nearshore communities demonstrated significantly greater species richness and Chao1 indices compared to the offshore communities. In contrast, the nearshore communities had lower values of Shannon and Simpson indices. When compared to the FLB, the PAB exhibit a higher level of biodiversity and abundance. However, no distinct alpha and beta diversity differences were observed between the bottom, middle, and surface water layers. The community assembly analysis indicated that nearshore communities are predominantly shaped by deterministic processes, particularly due to heterogeneous selection of PAB; In contrast, offshore communities are governed more by stochastic processes, largely due to homogenizing dispersal of FLB. Consequently, the findings of this study demonstrate that nearshore and PAB communities exhibit higher levels of species diversity, while stochastic and deterministic processes exert distinct influences on communities among near- and offshore regions. This study further sheds new light on our understanding of the mechanisms governing bacterial communities in estuarine ecosystems.

Evaluating drivers of recent large whale strandings on the East Coast of the United States.

Anthropogenic stressors threaten large whales globally. Effective management requires an understanding of where, when, and why threats are occurring. Strandings data provide key information on geographic hotspots of risk and the relative importance of various threats. There is currently considerable public interest in the increased frequency of large whale strandings occurring along the US East Coast of the United States since 2016. Interest is accentuated due to a purported link with offshore wind energy development. We reviewed spatiotemporal patterns of strandings, mortalities, and serious injuries of humpback whales (Megaptera novaeangliae), the species most frequently involved, for which the US government has declared an "unusual mortality event" (UME). Our analysis highlights the role of vessel strikes, exacerbated by recent changes in humpback whale distribution and vessel traffic.  Humpback whales have expanded into new foraging grounds in recent years. Mortalities due to vessel strikes have increased significantly in these newly occupied regions, which show high vessel traffic that also increased markedly during the UME. Surface feeding and feeding in shallow waters may have been contributing factors. We found no evidence that offshore wind development contributed to strandings or mortalities. This work highlights the need to consider behavioral, ecological, and anthropogenic factors to determine the drivers of mortality and serious injury in large whales and to provide informed guidance to decision-makers.

Análisis de las causantes de los recientes varamientos de ballenas en la costa este de los Estados Unidos Resumen El estrés antropogénico amenaza a las ballenas en todo el mundo. El manejo efectivo requiere comprender en dónde, cuándo y por qué ocurren las amenazas. Los datos de varamientos proporcionan información clave sobre los puntos críticos geográficos de riesgo y la importancia relativa de varias amenazas. Actualmente existe un interés público considerable por el incremento en la frecuencia de varamientos de ballenas que ocurren en la costa este de los Estados Unidos desde 2016, al cual el gobierno nacional ha denominado un "evento inusual de mortalidad" (EIM). El interés se acentúa debido a la supuesta conexión con el desarrollo de la energía eólica marina. Revisamos los patrones espaciotemporales de los varamientos, mortandad y lesiones graves de las ballenas jorobadas (Megaptera novaeangliae), la especie involucrada con mayor frecuencia. Nuestro análisis resalta el papel de las colisiones con navíos, agudizados por los cambios recientes en la distribución de la especie, y el tráfico de navíos. Las ballenas jorobadas se han expandido hacia nuevas áreas de forrajeo y los años recientes. La mortandad causada por las colisiones con navíos ha incrementado significativamente en estas regiones ocupadas recientemente, las cuales también muestran un tráfico elevado de navíos que también incrementó durante el EIM. La alimentación superficial y en áreas someras podrían ser factores contribuyentes. No encontramos evidencia de que la energía eólica marina contribuya a los varamientos o a la mortandad. Este trabajo resalta la necesidad de considerar los factores ecológicos, antropogénicos y de comportamiento para determinar las causas de la mortalidad y las lesiones graves en las ballenas y de proporcionar orientación informada para quienes toman las decisiones.

Photobacterium pectinilyticum sp. nov., a novel bacterium isolated from surface seawater of Qingdao offshore.

A Gram-staining-negative, facultative aerobic, motile strain, designated strain ZSDE20T, was isolated from the surface seawater of Qingdao offshore. Phylogenetic analysis of the 16S rRNA gene of strain ZSDE20T, affiliated it to the genus Photobacterium. It was closely related to Photobacterium lutimaris DF-42 T (98.92% 16S rRNA gene sequence similarity). Growth occurred at 4-28ºC (optimum 28ºC), pH 1.0-7.0 (optimum 7.0) and in the presence of 1-7% (w/v) NaCl (optimum 3%). The dominant fatty acids were summed feature 3 (C16:1 ω7c or/and C16:1 ω6c, 34.23%), summed feature 8 (C18:1 ω7c and C18:1 ω6c, 10.36%) and C16:0 (20.05%). The polar lipids of strain ZSDE20T comprised phosphatidylethanolamine, phosphatidylcholine, lyso-phosphatidylglycerol, phosphatidylethanolamine, phosphatidylinositol dimannoside, phosphatidylinositol mannosides and two unknown lipids. The major respiratory quinone was ubiquinone-8 (Q-8). The DNA G + C content of strain ZSDE20T was 45.6 mol%. Average nucleotide identity (ANI) values between ZSDE20T and its reference species were lower than the threshold for species delineation (95-96%); in silico DNA-DNA hybridization further showed that strain ZSDE20T had less than 70% similarity to its relatives. Based on the polyphasic evidences, strain ZSDE20T is proposed as representing a novel species of the genus Photobacterium, for which the name Photobacterium pectinilyticum sp. nov. is proposed. The type strain is ZSDE20T (= MCCC 1K06283T = KCTC 82885 T).

Case example of a female solo sailor competing in the Vendée Globe reveals extraordinary biological demands.

The Vendée Globe is a non-stop, unassisted, single-handed round the world sailing race. It is regarded as the toughest sailing race, requiring high cognitive functioning and constant alertness. Little is known about the amount of sleep restriction and nutritional deficit experienced at sea and effects that fatigue have on sailors' performance. This report aimed to investigate these aspects by monitoring one of the female participants of the latest Vendée Globe. Sleep, food intake and stress were self-reported daily using specific app. Cognitive assessments were digitally completed. Heart rate and activity intensity were measured using a wrist-worn wearable device. Mean self-report sleep duration per 24 h was 3 hours 40 minutes. By the end of the 95 race days, the sailor reached a caloric deficit of 27,900 kcal. On average, the sailor spent 50 minutes per day in moderate-to-vigorous activity. Cognitive assessments did not show any effect of fatigue or stress on completion time or performance. Recent technological and communication advancement for offshore sailors, enabled continuous data to be monitored in near real time, even from the Southern Ocean. Moving forward this will enable greater understanding of when sailors will be at risk of poor decision making, illness or injury.

Examining the Use of Offshore Online Gambling Sites in the United States via Routine Activities Theory: A SEM Analysis.

Despite the recent proliferation of legal online gambling in the Unites States, offshore gambling sites still remain prevalent, causing various problems in the U.S. Although numerous law violations occur in this domain, prior research has reported limited information about offshore gambling, mostly focusing on offshore gamblers' characteristics and motivations. Using routine activities theory, this study attempted to understand environmental and theoretical factors that affect the use of offshore sites by focusing on offshore gambling-generating contexts that involve offshore sites and online casino reviews. Major findings show that the online visibility of offshore sites may be a key predictor of the use of the sites by U.S. players. In addition, online casino reviews providing a blacklist of online gambling sites served as informal guardians, helping players avoid unreliable offshore gambling sites that pose a risk to their customers. Policy implications were suggested based on the findings and provided insights toward effective online gambling regulatory efforts.

Offshore Oil Spill Detection Based on CNN, DBSCAN, and Hyperspectral Imaging.

Offshore oil spills have the potential to inflict substantial ecological damage, underscoring the critical importance of timely offshore oil spill detection and remediation. At present, offshore oil spill detection typically combines hyperspectral imaging with deep learning techniques. While these methodologies have made significant advancements, they prove inadequate in scenarios requiring real-time detection due to limited model detection speeds. To address this challenge, a method for detecting oil spill areas is introduced, combining convolutional neural networks (CNNs) with the DBSCAN clustering algorithm. This method aims to enhance the efficiency of oil spill area detection in real-time scenarios, providing a potential solution to the limitations posed by the intricate structures of existing models. The proposed method includes a pre-feature selection process applied to the spectral data, followed by pixel classification using a convolutional neural network (CNN) model. Subsequently, the DBSCAN algorithm is employed to segment oil spill areas from the classification results. To validate our proposed method, we simulate an offshore oil spill environment in the laboratory, utilizing a hyperspectral sensing device to collect data and create a dataset. We then compare our method with three other models-DRSNet, CNN-Visual Transformer, and GCN-conducting a comprehensive analysis to evaluate the advantages and limitations of each model.

A Review of Subsidence Monitoring Techniques in Offshore Environments.

In view of the ever-increasing global energy demands and the imperative for sustainability in extraction methods, this article surveys subsidence monitoring systems applied to oil and gas fields located in offshore areas. Subsidence is an issue that can harm infrastructure, whether onshore or especially offshore, so it must be carefully monitored to ensure safety and prevent potential environmental damage. A comprehensive review of major monitoring technologies used offshore is still lacking; here, we address this gap by evaluating several techniques, including InSAR, GNSSs, hydrostatic leveling, and fiber optic cables, among others. Their accuracy, applicability, and limitations within offshore operations have also been assessed. Based on an extensive literature review of more than 60 published papers and technical reports, we have found that no single method works best for all settings; instead, a combination of different monitoring approaches is more likely to provide a reliable subsidence assessment. We also present selected case histories to document the results achieved using integrated monitoring studies. With the emerging offshore energy industry, combining GNSSs, InSAR, and other subsidence monitoring technologies offers a pathway to achieving precision in the assessment of offshore infrastructural stability, thus underpinning the sustainability and safety of offshore oil and gas operations. Reliable and comprehensive subsidence monitoring systems are essential for safety, to protect the environment, and ensure the sustainable exploitation of hydrocarbon resources.

Fatigue Analysis of a Jacket-Supported Offshore Wind Turbine at Block Island Wind Farm.

Offshore wind-turbine (OWT) support structures are subjected to cyclic dynamic loads with variations in loadings from wind and waves as well as the rotation of blades throughout their lifetime. The magnitude and extent of the cyclic loading can create a fatigue limit state controlling the design of support structures. In this paper, the remaining fatigue life of the support structure for a GE Haliade 6 MW fixed-bottom jacket offshore wind turbine within the Block Island Wind Farm (BIWF) is assessed. The fatigue damage to the tower and the jacket support structure using stress time histories at instrumented and non-instrumented locations are processed. Two validated finite-element models are utilized for assessing the stress cycles. The modal expansion method and a simplified approach using static calculations of the responses are employed to estimate the stress at the non-instrumented locations-known as virtual sensors. It is found that the hotspots at the base of the tower have longer service lives than the jacket. The fatigue damage to the jacket leg joints is less than 20% and 40% of its fatigue capacity during the 25-year design lifetime of the BIWF OWT, using the modal expansion method and the simplified static approach, respectively.

Inspection of Floating Offshore Wind Turbines Using Multi-Rotor Unmanned Aerial Vehicles: Literature Review and Trends.

Operations and maintenance (O&M) of floating offshore wind turbines (FOWTs) require regular inspection activities to predict, detect, and troubleshoot faults at high altitudes and in harsh environments such as strong winds, waves, and tides. Their costs typically account for more than 30% of the lifetime cost due to high labor costs and long downtime. Different inspection methods, including manual inspection, permanent sensors, climbing robots, remotely operated vehicles (ROVs), and unmanned aerial vehicles (UAVs), can be employed to fulfill O&M missions. The UAVs, as an enabling technology, can deal with time and space constraints easily and complete tasks in a cost-effective and efficient manner, which have been widely used in different industries in recent years. This study provides valuable insights into the existing applications of UAVs in FOWT inspection, highlighting their potential to reduce the inspection cost and thereby reduce the cost of energy production. The article introduces the rationale for applying UAVs to FOWT inspection and examines the current technical status, research gaps, and future directions in this field by conducting a comprehensive literature review over the past 10 years. This paper will also include a review of UAVs' applications in other infrastructure inspections, such as onshore wind turbines, bridges, power lines, solar power plants, and offshore oil and gas fields, since FOWTs are still in the early stages of development. Finally, the trends of UAV technology and its application in FOWTs inspection are discussed, leading to our future research direction.

An Edge Computing Application of Fundamental Frequency Extraction for Ocean Currents and Waves.

This paper describes the design and optimization of a smart algorithm based on artificial intelligence to increase the accuracy of an ocean water current meter. The main purpose of water current meters is to obtain the fundamental frequency of the ocean waves and currents. The limiting factor in those underwater applications is power consumption and that is the reason to use only ultra-low power microcontrollers. On the other hand, nowadays extraction algorithms assume that the processed signal is defined in a fixed bandwidth. In our approach, belonging to the edge computing research area, we use a deep neural network to determine the narrow bandwidth for filtering the fundamental frequency of the ocean waves and currents on board instruments. The proposed solution is implemented on an 8 MHz ARM Cortex-M0+ microcontroller without a floating point unit requiring only 9.54 ms in the worst case based on a deep neural network solution. Compared to a greedy algorithm in terms of computational effort, our worst-case approach is 1.81 times faster than a fast Fourier transform with a length of 32 samples. The proposed solution is 2.33 times better when an artificial neural network approach is adopted.

Wind-Speed-Adaptive Resonant Piezoelectric Energy Harvester for Offshore Wind Energy Collection.

This paper proposes a wind-speed-adaptive resonant piezoelectric energy harvester for offshore wind energy collection (A-PEH). The device incorporates a coil spring structure, which sets the maximum threshold of the output rotational frequency, allowing the A-PEH to maintain a stable output rotational frequency over a broader range of wind speeds. When the maximum output excitation frequency of the A-PEH falls within the sub-resonant range of the piezoelectric beam, the device becomes wind-speed-adaptive, enabling it to operate in a sub-resonant state over a wider range of wind speeds. Offshore winds exhibit an annual average speed exceeding 5.5 m/s with significant variability. Drawing from the characteristics of offshore winds, a prototype of the A-PEH was fabricated. The experimental findings reveal that in wind speed environments, the device has a startup wind speed of 4 m/s, and operates in a sub-resonant state when the wind speed exceeds 6 m/s. At this point, the A-PEH achieves a maximum open-circuit voltage of 40 V and an average power of 0.64 mW. The wind-speed-adaptive capability of the A-PEH enhances its ability to harness offshore wind energy, showcasing its potential applications in offshore wind environments.

Ultra-Short-Term Offshore Wind Power Prediction Based on PCA-SSA-VMD and BiLSTM.

In order to realize the economic dispatch and safety stability of offshore wind farms, and to address the problems of strong randomness and strong time correlation in offshore wind power forecasting, this paper proposes a combined model of principal component analysis (PCA), sparrow algorithm (SSA), variational modal decomposition (VMD), and bidirectional long- and short-term memory neural network (BiLSTM). Firstly, the multivariate time series data were screened using the principal component analysis algorithm (PCA) to reduce the data dimensionality. Secondly, the variable modal decomposition (VMD) optimized by the SSA algorithm was applied to adaptively decompose the wind power time series data into a collection of different frequency components to eliminate the noise signals in the original data; on this basis, the hyperparameters of the BiLSTM model were optimized by integrating SSA algorithm, and the final power prediction value was obtained. Ultimately, the verification was conducted through simulation experiments; the results show that the model proposed in this paper effectively improves the prediction accuracy and verifies the effectiveness of the prediction model.

Vibration-Based SHM in the Synthetic Mooring Lines of the Semisubmersible OO-Star Wind Floater under Varying Environmental and Operational Conditions.

As the industry transitions toward Floating Offshore Wind Turbines (FOWT) in greater depths, conventional chain mooring lines become impractical, prompting the adoption of synthetic fiber ropes. Despite their advantages, these mooring lines present challenges in inspection due to their exterior jacket, which prevents visual assessment. The current study focuses on vibration-based Structural Health Monitoring (SHM) in FOWT synthetic mooring lines under uncertainty arising from varying Environmental and Operational Conditions (EOCs). Six damage detection methods are assessed, utilizing either multiple models or a single functional model. The methods are based on Vector Autoregressive (VAR) or Transmittance Function Autoregressive with exogenous input (TF-ARX) models. All methods are evaluated through a Monte Carlo study involving 1100 simulations, utilizing acceleration signals generated from a finite element model of the OO-Star Wind Floater Semi 10 MW wind turbine. With signals from only two measuring positions, the methods demonstrate excellent results, detecting the stiffness reduction of a mooring line at levels 10% through 50%. The methods are also tested for healthy cases, with those utilizing TF-ARX models achieving zero false alarms, even for EOCs not encountered in the training data.

Phased Array Ultrasonic Method for Robotic Preload Measurement in Offshore Wind Turbine Bolted Connections.

This paper presents a novel approach for preload measurement of bolted connections, specifically tailored for offshore wind applications. The proposed method combines robotics, Phased Array Ultrasonic Testing (PAUT), nonlinear acoustoelasticity, and Finite Element Analysis (FEA). Acceptable defects, below a pre-defined size, are shown to have an impact on preload measurement, and therefore conducting simultaneous defect detection and preload measurement is discussed in this paper. The study demonstrates that even slight changes in the orientation of the ultrasonic transducer, the non-automated approach, can introduce a significant error of up to 140 MPa in bolt stress measurement and therefore a robotic approach is employed to achieve consistent and accurate measurements. Additionally, the study emphasises the significance of considering average preload for comparison with ultrasonic data, which is achieved through FEA simulations. The advantages of the proposed robotic PAUT method over single-element approaches are discussed, including the incorporation of nonlinearity, simultaneous defect detection and stress measurement, hardware and software adaptability, and notably, a substantial improvement in measurement accuracy. Based on the findings, the paper strongly recommends the adoption of the robotic PAUT approach for preload measurement, whilst acknowledging the required investment in hardware, software, and skilled personnel.

Combined Filtering Method for Offshore Oil and Gas Platform Point Cloud Data Based on KNN_PCF and Hy_WHF and Its Application in 3D Reconstruction.

With the increasing scale of deep-sea oil exploration and drilling platforms, the assessment, maintenance, and optimization of marine structures have become crucial. Traditional detection and manual measurement methods are inadequate for meeting these demands, but three-dimensional laser scanning technology offers a promising solution. However, the complexity of the marine environment, including waves and wind, often leads to problematic point cloud data characterized by noise points and redundancy. To address this challenge, this paper proposes a method that combines K-Nearest-Neighborhood filtering with a hyperbolic function-based weighted hybrid filtering. The experimental results demonstrate the exceptional performance of the algorithm in processing point cloud data from offshore oil and gas platforms. The method improves noise point filtering efficiency by approximately 11% and decreases the total error by 0.6 percentage points compared to existing technologies. Not only does this method accurately process anomalies in high-density areas-it also removes noise while preserving important details. Furthermore, the research method presented in this paper is particularly suited for processing large point cloud data in complex marine environments. It enhances data accuracy and optimizes the three-dimensional reconstruction of offshore oil and gas platforms, providing reliable dimensional information for land-based prefabrication of these platforms.

Offshore produced water treatment by a biofilm reactor on the seabed: The effect of temperature and matrix characteristics.

In many industrial processes a large amount of water with high salinity is co-produced whose treatment poses considerable challenges to the available technologies. The produced water (PW) from offshore operations is currently being discharged to sea without treatment for dissolved pollutants due to space limitations. A biofilter on the seabed adjacent to a production platform would negate all size restrictions, thus reducing the environmental impact of oil and gas production offshore. The moving bed biofilm reactor (MBBR) was investigated for PW treatment from different oilfields in the North Sea at 10 °C and 40 °C, corresponding to the sea and PW temperature, respectively. The six PW samples in study were characterized by high salinity and chemical oxygen demand with ecotoxic effects on marine algae S. pseudocostatum (0.4%

Bidding against the wind: A choice experiment in green energy, green jobs and offshore views in North Carolina, USA.

Offshore wind development is in its nascent stages in the United States. Recent research indicates that the visual impacts of offshore wind farms are viewed negatively by the general population. This North Carolina application is the first US-focused discrete choice experiment that explicitly asks respondents to consider the positive local and global benefits from offshore wind development, such as job creation and greenhouse gas emission reductions, simultaneously with their visual impacts. We find significant willingness to pay (WTP) for reducing the visual impacts of offshore wind farms, and that the extent of disamenity varies in the population and with placement along developed tourist towns (as much as $783/year for three years) or preserved coastlines (as much as $451/year for three years). We also find that some preference classes value projects that create permanent jobs and reduce carbon emissions. We use our estimates of preferences for the positive and negative attributes to explore specific wind farm configurations and locations that could achieve positive consensus in a heterogenous population.

To what extent can decommissioning options for marine artificial structures move us toward environmental targets?

Switching from fossil fuels to renewable energy is key to international energy transition efforts and the move toward net zero. For many nations, this requires decommissioning of hundreds of oil and gas infrastructure in the marine environment. Current international, regional and national legislation largely dictates that structures must be completely removed at end-of-life although, increasingly, alternative decommissioning options are being promoted and implemented. Yet, a paucity of real-world case studies describing the impacts of decommissioning on the environment make decision-making with respect to which option(s) might be optimal for meeting international and regional strategic environmental targets challenging. To address this gap, we draw together international expertise and judgment from marine environmental scientists on marine artificial structures as an alternative source of evidence that explores how different decommissioning options might ameliorate pressures that drive environmental status toward (or away) from environmental objectives. Synthesis reveals that for 37 United Nations and Oslo-Paris Commissions (OSPAR) global and regional environmental targets, experts consider repurposing or abandoning individual structures, or abandoning multiple structures across a region, as the options that would most strongly contribute toward targets. This collective view suggests complete removal may not be best for the environment or society. However, different decommissioning options act in different ways and make variable contributions toward environmental targets, such that policy makers and managers would likely need to prioritise some targets over others considering political, social, economic, and ecological contexts. Current policy may not result in optimal outcomes for the environment or society.

Developing expert scientific consensus on the environmental and societal effects of marine artificial structures prior to decommissioning.

Thousands of artificial ('human-made') structures are present in the marine environment, many at or approaching end-of-life and requiring urgent decisions regarding their decommissioning. No consensus has been reached on which decommissioning option(s) result in optimal environmental and societal outcomes, in part, owing to a paucity of evidence from real-world decommissioning case studies. To address this significant challenge, we asked a worldwide panel of scientists to provide their expert opinion. They were asked to identify and characterise the ecosystem effects of artificial structures in the sea, their causes and consequences, and to identify which, if any, should be retained following decommissioning. Experts considered that most of the pressures driving ecological and societal effects from marine artificial structures (MAS) were of medium severity, occur frequently, and are dependent on spatial scale with local-scale effects of greater magnitude than regional effects. The duration of many effects following decommissioning were considered to be relatively short, in the order of days. Overall, environmental effects of structures were considered marginally undesirable, while societal effects marginally desirable. Experts therefore indicated that any decision to leave MAS in place at end-of-life to be more beneficial to society than the natural environment. However, some individual environmental effects were considered desirable and worthy of retention, especially in certain geographic locations, where structures can support improved trophic linkages, increases in tourism, habitat provision, and population size, and provide stability in population dynamics. The expert analysis consensus that the effects of MAS are both negative and positive for the environment and society, gives no strong support for policy change whether removal or retention is favoured until further empirical evidence is available to justify change to the status quo. The combination of desirable and undesirable effects associated with MAS present a significant challenge for policy- and decision-makers in their justification to implement decommissioning options. Decisions may need to be decided on a case-by-case basis accounting for the trade-off in costs and benefits at a local level.