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This manual describes the wide range of electromechanical, electrochemical and electro-optical transducers at the heart of current field-deployable ocean observing instruments. Their modes of operation, precision and accuracy are discussed in detail. Observing platforms ranging from the traditional to the most recently developed are described, as are the challenges of integrating instrument suits to individual platforms. Technical approaches are discussed to address environmental constraints on instrument and platform operation such as power sources, corrosion, biofouling and mechanical abrasion. Particular attention is also given to data generated by the networks of observing platforms that are typically integrated into value-added data visualization products, including numerical simulations or models. Readers will learn about acceptable data formats and representative model products. The last section of the book is devoted to the challenges of planning, deploying and maintaining coastal ocean observing systems. Readers will discover practical applications of ocean observations in diverse fields including natural resource conservation, commerce and recreation, safety and security, and climate change resiliency and adaptation. This volume will appeal to ocean engineers, oceanographers, commercial and recreational ocean data users, observing systems operators, and advanced undergraduate and graduate students in the field of ocean observing.

This important and informative new book outlines and discusses details of the basic principles and methods that are central to any study of fish condition, from a fish ecology and fisheries biology perspective. Condition and Health Indicators of Exploited Marine Fishes describes the potential capacities of condition indicators, providing examples showing the use of these indicators to solve practical problems in connection with fish ecology and fisheries research. By focusing on wild fish populations, the book complements the increasing number of scientific works that are contributing to show how fish condition studies are key to reveal problems in marine aquaculture, the effects of pollution, fish disease, and the importance of fish in human nutrition and medicine. Condition and Health Indicators of Exploited Marine Fishes provides a comprehensive introduction to the study of fish condition that will assist advanced undergraduate and postgraduate students, researchers and professionals, working in marine ecology and biology, fisheries biology, environmental sciences and fish pathology. All universities and research establishments where biological and environmental sciences, fisheries and aquaculture are studied and taught should have copies of this book on their shelves.

Marine environmental monitoring has tended to focus on site-specific methods of investigation. These traditional methods have low spatial and temporal resolution and are relatively labour intensive per unit area/time that they cover. To implement the Marine Strategy Framework Directive (MSFD), European Member States are required to improve marine monitoring and design monitoring networks. This can be achieved by developing and testing innovative and cost-effective monitoring systems, as well as indicators of environmental status. Here, we present several recently developed methodologies and technologies to improve marine biodiversity indicators and monitoring methods. The innovative tools are discussed concerning the technologies presently utilized as well as the advantages and disadvantages of their use in routine monitoring. In particular, the present analysis focuses on: (i) molecular approaches, including microarray, Real Time quantitative PCR (qPCR), and metagenetic (metabarcoding) tools; (ii) optical (remote) sensing and acoustic methods; and (iii) in situ monitoring instruments. We also discuss their applications in marine monitoring within the MSFD through the analysis of case studies in order to evaluate their potential utilization in future routine marine monitoring. We show that these recently-developed technologies can present clear advantages in accuracy, efficiency and cost.

Microplastic litter is a pervasive pollutant present in marine systems across the globe. The legacy of microplastics pollution in the marine environment today may remain for years to come due to the persistence of these materials. Microplastics are emerging contaminants of potential concern and as yet there are few recognised approaches for monitoring. In 2008, the EU Marine Strategy Framework Directive (MSFD, 2008/56/EC) included microplastics as an aspect to be measured. Here we outline the approach as discussed by the European Union expert group on marine litter, the technical Subgroup on Marine litter (TSG-ML), with a focus on the implementation of monitoring microplastics in seawater in European seas. It is concluded that harmonization and coherence is needed to achieve reliable monitoring.

Marine environments are delicate ecosystems which directly influence local climates, flora, fauna, and human activities. Their monitorization plays a key role in their preservation, which is most commonly done through the use of environmental sensing buoy networks. These devices transmit data by means of satellite communications or close-range base stations, which present several limitations and elevated infrastructure costs. Unmanned Aerial Vehicles (UAV) are another alternative for remote environmental monitoring which provide new types of data and ease of use. These aircraft are mainly used in video capture related applications, in its various light spectrums, and do not provide the same data as sensing buoys, nor can they be used for such extended periods of time. The aim of this research is to provide a flexible, easy to deploy and cost-effective Wireless Sensor Network (WSN) for monitoring marine environments. This proposal uses a UAV as a mobile data collector, low-power long-range communications and sensing buoys as part of a single WSN. A complete description of the design, development, and implementation of the various parts of this system is presented, as well as its validation in a real-world scenario.

The temperature and pressure of seawater are of great importance to investigate the environmental evolution for the research of ocean science. With this regard, we proposed and experimentally demonstrated a seawater temperature and pressure sensor realized by a polyimide (PI) tube-based Fabry-Perot interferometer (FPI) together with a fiber Bragg grating (FBG). Benefiting from the higher thermo-optical coefficient and larger elasticity of polymer than the fused silica fiber, the sensitivity of the sensor is largely improved. The FBG is used to compensate the cross effect of the temperature. The measured temperature and pressure sensitivities of the sensor are 18.910 nm/°C and −35.605 nm/MPa, respectively. Furthermore, the temperature and pressure information measured by the sensor can be achieved simultaneously using the sensitivity matrix method. In addition, the proposed sensor has advantages of easy fabrication, compact size, as well as capability of multiplexing and long-distance measurement, making it competitive and promising during the marine monitoring.

Marine managers commonly use ecological indicators in planning and evaluations; however, few programs monitor social and cultural impacts of management. Practical approaches to identifying and monitoring social and cultural aspects of communities’ relationships with their environment could assist many agencies in understanding the impacts of their efforts to achieve conservation goals. The Hawaiʻi Department of Land and Natural Resources, Division of Aquatic Resources (DAR) launched the Holomua Marine Initiative to collaborate and engage with communities to strengthen co-management efforts, which included integrating socio-cultural aspects into the planning and assessment of marine management. Our team, which included resource managers, Western and indigenous scientists, community leaders, students, agency, and university staff engaged in collaborative management efforts in Hawaiʻi, developed an approach to monitor the social and cultural impacts of DAR’s management actions. Through online collaborative workshops with community members and non-profit leaders engaged in marine conservation in Hawaiʻi, we co-developed socio-cultural principles and indicators based on their reciprocal relationships with the nearshore environment. During the workshops, we used small group activities, snow cards, sorting, and categorization to generate nine fundamental principles, with associated indicators, to guide marine management in Hawaiʻi. Many of the principles and indicators are comparable to those developed in other parts of the Pacific, revolving around themes including the perpetuation of local and indigenous knowledge across generations, and access to land and natural resources. Participants also suggested themes less prevalent in other research, such as the need to evaluate impacts of tourism on community relationships with coastal areas. We offer recommendations for the development of socio-cultural principles and indicators in other place-based contexts, and emphasize the importance of on-going community collaboration. Developing a socio-cultural monitoring framework with community members impacted by marine management decisions could enable others engaged in collaborative efforts, including government agencies, to holistically understand and address impacts of their policies and actions. Monitoring layered socio-cultural impacts of marine management on local and indigenous communities has the potential to shift management goals, and enhance long-term effectiveness and support for initiatives to protect coastal resources worldwide.

Efficient fish detection in underwater environments is crucial for monitoring marine biodiversity, yet it poses significant challenges due to low visibility, complex backdrops, and diverse fish morphologies. This study presents a vision-based cyber-physical solution leveraging an enhanced YOLO architecture with a novel Balanced Coverage and Penalization (BCP) loss function. Our key contributions included a novel multi-head detection strategy. This unique approach not only improved the model’s adaptability to diverse fish morphologies but also led to the development of the BCP metric, which reduced prediction-ground truth discrepancies, thereby enhancing detection accuracy and robustness. Experiments on the COD10K and Halibut datasets show consistent gains in precision and stability compared with existing methods. These results demonstrate the effectiveness of the BCP loss in refining spatial coverage and highlight its potential for scalable applications in smart aquaculture, automated fisheries management, and marine environmental monitoring.

Seabed habitat maps can help facilitate the management of marine environments. A variety of approaches exist for seabed habitat classification. Most partition the environment according to physical environmental characteristics, with an assumption that resulting habitat classes are biologically meaningful. In the absence of comprehensive broad‐scale biological data, this strategy offers a logical and pragmatic way of producing habitat maps to help manage the marine environment. Across Europe, the physical based European Nature Information System (EUNIS) classification has gained wide acceptance, with maps used to classify broadscale habitats within Marine Protected Areas and to design monitoring programmes. An alternative approach to habitat classification, made possible by increasing quantities of data, is to use the biology to identify meaningful habitats. With such contrasting approaches, the question arises as to which provides the most robust and efficient basis for biological monitoring. To investigate, we compared variability in macrofaunal assemblages across different EUNIS sediment classes to those of two new habitat classification approaches developed in this study. The first of these (PHY) is based on a wide suite of physical variables known to influence the fauna. The second (BIO) uses the fauna to identify meaningful habitats. Both classifications were produced using a training dataset (9,619 grab samples) and employing k‐means clustering and Random Forest Modelling. Power analysis of test set data (4,123 samples) was used to assess the number of samples required to detect a 20% change in taxon richness and total abundance across all classes of each classification approach. Results showed that across all habitat classes, the BIO classification required 49% and 31% fewer samples to detect the change in richness and abundance than EUNIS level 4. Whilst offering some improvement on EUNIS, PHY still required many more samples than BIO. Synthesis and applications. Habitat maps based on biological data have generally lower within‐habitat variability in community metrics than those produced using physical attributes alone. As a result, biologically‐based habitat maps could offer a more cost‐effective basis for ecological monitoring. Habitat maps based on biological data have generally lower within‐habitat variability in community metrics than those produced using physical attributes alone. As a result, biologically‐based habitat maps could offer a more cost‐effective basis for ecological monitoring.

In this paper the authors discuss the realization of a Long Range Wide Area Network (LoRaWAN) network infrastructure to be employed for monitoring activities within the marine environment. In particular, transmission ranges as well as the assessment of parameters like Signal to Noise Ratio (SNR) and Received Signal Strength Indicator (RSSI) are analyzed in the specific context of an aquaculture industrial plant, setting up a transmission channel from an offshore monitoring structure provided with a LoRaWAN transmitter, to an ashore receiving device composed of two LoRaWAN Gateways. A theoretical analysis about the feasibility of the transmission is provided. The performances of the system are then measured with different network parameters (in particular the Spreading Factor—SF) as well as with two different heights for the transmitting antenna. Test results prove that efficient data transmission can be achieved at a distance of 8.33 km even using worst case network settings: this suggests the effectiveness of the system even in harsher environmental conditions, thus entailing a lower quality of the transmission channel, or for larger transmission ranges.