Monitoring Of Marine Ecosystems Research Articles

Utilizing fluctuation asymmetry to assess the effects of U-238 radioactivity on the marine ecosystem around the Madras nuclear power plant, India

The monitoring of marine ecosystems is crucial due to the growing threat posed by nuclear power plants and other nuclear anthropogenic emissions. In our work, we used a straightforward and low-cost biomonitoring technique called fluctuation asymmetry (FA) to examine the variation between the left and right sides (developmental instability) of organisms’ traits that were influenced by genetic and environmental variables in the early stages of ontogenesis. The specimens of fish (Leiognathus sp.) and crabs (Portunus sanguinolentus) were collected seasonally and used as bioindicators to determine the effects of Uranium-238 (U-238) radioactivity around a nuclear power plant. The obtained results revealed that FA values were not considered typical values (FA = 0) in all seasons. Moreover, FA values of Leiognathus sp. exhibited insignificant fluctuation for a particular characteristic through the different seasons, while a significant fluctuation occurred amongst the characteristics themselves throughout the same season. Inversely, FA values of the four characteristics in Portunus sanguinolentus displayed seasonal variation amongst them all. Statistically, there was a strong positive correlation (r = 0.5, p < 0.05) between U-238 radioactivity in the flesh of both organisms and the fluctuation asymmetry of different traits but it is not a sign that any radioactive pollution exists.

An integrated coastal ecosystem monitoring strategy: Pilot case in Naf-Saint Martin Peninsula, Bangladesh

Rapid population growth creating an excessive pressure on the marine environment and thus monitoring of marine ecosystem is essential. However, due to high technical and financial involvement, monitoring of coastal ecosystem is always challenging in developing countries. This study aims to develop an integrated coastal ecosystem monitoring system that combines scientific sampling, numerical model simulation and citizen science observations to monitor the coastal ecosystem of Bangladesh. This concept of integrated monitoring approach was piloted from January 2022 to April 2023 at the South East coastal zone of Bangladesh. Scientific sampling and numerical model simulations were performed for temperature and salinity data collection. Citizen science approach was employed to collect data on environmental conditions, fisheries, plankton, other marine resources, and plastic pollution. Numerical model simulations and citizen scientists observations of temperature and salinity showed good agreement with the scientifically collected data. In addition, citizen scientists observations on fisheries, plankton, other marine resources and plastic pollution were also in line with the existing database and previous studies. The proposed integrated monitoring approach presents a viable technique, creating a new avenue for coastal and marine ecosystem monitoring where infrastructural facilities are limited.

GEOAI FOR MARINE ECOSYSTEM MONITORING: A COMPLETE WORKFLOW TO GENERATE MAPS FROM AI MODEL PREDICTIONS

Abstract. Mapping and monitoring marine ecosystems imply several challenges for data collection and processing: water depth, restricted access to locations, instrumentation costs or weather constraints for sampling, among others. Nowadays, Artificial Intelligence (AI) and Geographic Information System (GIS) open source software can be combined in new kinds of workflows, to annotate and predict objects directly on georeferenced raster data (e.g. orthomosaics). Here, we describe and share the code of a generic method to train a deep learning model with spatial annotations and use it to directly generate model predictions as spatial features. This workflow has been tested and validated in three use cases related to marine ecosystem monitoring at different geographic scales: (i) segmentation of corals on orthomosaics made of underwater images to automate coral reef habitats mapping, (ii) detection and classification of fishing vessels on remote sensing satellite imagery to estimate a proxy of fishing effort (iii) segmentation of marine species and habitats on underwater images with a simple geolocation. Models have been successfully trained and the models predictions are displayed with maps in the three use cases.

Inter-colony and inter-annual variation in discard use by albatross chicks revealed using isotopes and regurgitates

Effective marine ecosystem monitoring is critical for sustainable management. Monitoring seabird diets can convey important information on ecosystem health and seabird–fishery interactions. The diet of breeding black-browed albatross (Thalassarche melanophris) has previously been assessed using stomach content analysis (SCA) or stable isotope analysis (SIA), but not both methods together. Combining dietary sampling approaches reduces biases associated with using single methods. This study combines SCA and SIA to study the diet of black-browed albatross chicks, with a specific focus on fishery discard consumption, at two Falkland Islands colonies (New Island 51°43′S, 61°18′W and Steeple Jason Island 51°01′S, 61°13′W) during two consecutive breeding seasons (2019 and 2020). SCA provided high taxonomic resolution of short-term diet and priors for stable isotope mixing models, with multiple measures of dietary items (e.g. numeric frequency N%, frequency of occurrence FO%). By contrast, SIA of down feathers provided a single and more integrated dietary signal from throughout chick development. Although the two methods disagreed on the dominant prey group (SCA—crustacean; SIA—pelagic fish), the complementary information suggested a chick diet dominated by natural prey (SCA: 74%–93% [FO], 44%–98% [N]; SIA: minimum 87%–95% contribution). Nonetheless, SCA revealed that a high proportion of breeding adults do take discards. We detected consistent colony-specific diets in relation to prey species, but not in relation to higher discard use. Overall, discard consumption was highest in 2020, the year characterised by the poorest foraging conditions. Our results have implications for fisheries management and future dietary studies assessing discard use.

Transcriptomic analysis of polyketide synthesis in dinoflagellate, Prorocentrum lima

The benthic dinoflagellate Prorocentrum lima is among the most common toxic morphospecies with a cosmopolitan distribution. P. lima can produce polyketide compounds, such as okadaic acid (OA), dinophysistoxin (DTX) and their analogues, which are responsible for diarrhetic shellfish poisoning (DSP). Studying the molecular mechanism of DSP toxin biosynthesis is crucial for understanding the environmental driver influencing toxin biosynthesis as well as for better monitoring of marine ecosystems. Commonly, polyketides are produced by polyketide synthases (PKS). However, no gene has been confirmatively assigned to DSP toxin production. Here, we assembled a transcriptome from 94,730,858 Illumina RNAseq reads using Trinity, resulting in 147,527 unigenes with average sequence length of 1035 nt. Using bioinformatics analysis methods, we found 210 unigenes encoding single-domain PKS with sequence similarity to type I PKSs, as reported in other dinoflagellates. In addition, 15 transcripts encoding multi-domain PKS (forming typical type I PKSs modules) and 5 transcripts encoding hybrid nonribosomal peptide synthetase (NRPS)/PKS were found. Using comparative transcriptome and differential expression analysis, a total of 16 PKS genes were identified to be up-regulated in phosphorus-limited cultures, which was related to the up regulation of toxin expression. In concert with other recent transcriptome analyses, this study contributes to the building consensus that dinoflagellates may utilize a combination of Type I multi-domain and single-domain PKS proteins, in an as yet undefined manner, to synthesize polyketides. Our study provides valuable genomic resource for future research in order to understand the complex mechanism of toxin production in this dinoflagellate.

Automated detection of dolphin whistles with convolutional networks and transfer learning.

Effective conservation of maritime environments and wildlife management of endangered species require the implementation of efficient, accurate and scalable solutions for environmental monitoring. Ecoacoustics offers the advantages of non-invasive, long-duration sampling of environmental sounds and has the potential to become the reference tool for biodiversity surveying. However, the analysis and interpretation of acoustic data is a time-consuming process that often requires a great amount of human supervision. This issue might be tackled by exploiting modern techniques for automatic audio signal analysis, which have recently achieved impressive performance thanks to the advances in deep learning research. In this paper we show that convolutional neural networks can indeed significantly outperform traditional automatic methods in a challenging detection task: identification of dolphin whistles from underwater audio recordings. The proposed system can detect signals even in the presence of ambient noise, at the same time consistently reducing the likelihood of producing false positives and false negatives. Our results further support the adoption of artificial intelligence technology to improve the automatic monitoring of marine ecosystems.

Benthic Opportunistic Polychaete/Amphipod Ratio: An Indicator of Pollution or Modification of the Environment by Macroinvertebrates?

The development of sensitive indicators reflecting the state of the environment is an important issue for the monitoring of marine ecosystems. The spionid polychaete Marenzelleria arctia and pontoporeiid amphipod Monoporeia affinis are common macrobenthic species in the brackish Gulf of Finland (the easternmost Baltic Sea). This paper aims to apply the Benthic Opportunistic Polychaetes Amphipods (BOPA) and Benthic Opportunistic Annelid Amphipods (BO2A) indices based on the polychaete/amphipod ratio as indicators of the environmental state in this region. We analyzed the relationships between environmental variables and benthic indices based on samples from two benthic surveys in 2019 (10 sites) and 2020 (9 sites). The coastal sites were characterized by worse water quality (i.e., the higher concentration of hydrocarbons, total phosphorus and chlorophyll-a), but cleaner sediments (i.e., total phosphorus, organic carbon, polyaromatic hydrocarbons and trace metals) than offshore sites. The BOPA and BO2A correlated positively with the level of water pollution and negatively with sediment pollution. The activity of the benthic organisms seems to strongly influence the concentration of contaminants in sediments, so this factor hinders the use of BOPA and BO2A indices for the assessment of bottom sediments quality in the eastern Baltic Sea. At the same time, this study shows that BOPA and BO2A indices can be used in assessing water quality.

Marine monitoring in transition: On the verge of technological revolution?

Efforts to renew marine ecosystem monitoring to include advanced technology and cost-effective methods have been repeatedly called for. The current environmental legislation in European Union (EU) requires also ecosystem monitoring beyond the scope of conventional methods and sampling strategies. Despite several studies showing the benefits of new methods, the progress to adopt the methods in national monitoring programmes under legal requirements has been slow. In this study, we have reviewed the current use of a set of methods in marine monitoring programmes under the EU marine strategy framework directive (MSFD), which calls for a holistic view of the marine environment and thus requires tens of monitoring parameters by different methods. Here we assess how widely the new methods are being adopted in the EU member states implementing the MSFD. Our results show a relatively high adoption rate for certain methods, while others are widely ignored. We compare the results also with the monitoring strategies of the four regional sea conventions. We argue that the adoption of methods in European and regional programmes may positively influence the national use of new methods.

Citizen science to support coastal research and management: Insights from a seagrass monitoring case study in Hainan, China

Citizen science has an active role in coastal and marine ecosystem monitoring, including seagrass beds. However, as yet the use of citizen science in the marine environment is limited. Moreover, there are very few studies analyzing and evaluating existing successful case studies, and the need for such work to fill vast information gaps is arguably great. This study evaluates a seagrass citizen science monitoring case study conducted on the Chinese island of Hainan from three perspectives: public participation, scientific impact, and social-ecological/economic impact. It also analyzes and assesses the role of civil society organizations in the implementation of citizen science projects for the first time. Our results challenge the dominant view of citizen science as a two-party relationship between academic researchers and volunteers. The evaluation shows that the impact of the project was limited in terms of the scientific and social/ecological dimensions. Yet, the results indicate that both, researchers and civil society, benefit from taking part in citizen science initiatives, as it provides a bridge to promote the collaboration between academic institutions and civil society organizations. Finally, drawing upon the lessons learned in this case study we outline general critical features of citizen science projects that support marine conservation practice and policy.

Kayak Drone – a silent acoustic unmanned surface vehicle for marine research

Advancements in technologies have led to a rapid development of unmanned surface vehicles (USV) for marine ecosystem monitoring. The design, size, and scientific payload of the USVs differ as they are built for different purposes. Here, we present the design criteria and detailed technical solutions of a prototype USV which has been built to fulfill the following experimental and operational needs; the USV should be used for inshore and shallow water acoustic monitoring, offshore comparison of echo sounder recordings from the USV and research vessels, monitor natural fish schooling behavior and seabird-fish behavioral interactions. The prototype has been built over a period of 5 years with steadily quality improvements. As the hull is based on an expedition double kayak, the USV is named Kayak Drone, and we aimed at building the Kayak Drone using of-the-shelf hardware and existing open-source software. This allowed for the development of a modular and well-functioning USV at a relatively low cost. The Kayak Drone produces very little noise and in situ experiments show that the Kayak Drone can record echo sounder data of fish near the surface without disturbing their natural distribution and behavior. One in situ study shows that the Kayak Drone could navigate within a couple of meters from swimming puffin and other seabirds without triggering escape. These results demonstrate that the Kayak Drone can be utilized to produce unbiased survey estimates for fish distributed in shallow waters and near the surface, which is very important for many fish stock assessments and managements. Furthermore, it can also be used as a tool to observe the predation by seabirds on fish schools without interfering with their natural interspecific behavior, which traditionally has been very difficult. The use of the Kayak Drone is not restricted to these tasks, and we foresee that the Kayak Drone can be utilized in many different experiments where a silent platform is needed.

A Novel Approach of Marine Ecosystem Monitoring System with Multi-Sensory Submarine on Robotic Platform for Visualizing the Climate Change Effect over Oceanic Environment

It is obvious that the whole world is so much concerned about the terrifying escalation of climate change in the recent time period. This climate change effect can be visible in the land, atmospheric and oceanic area simultaneously. Though there have been multiple attempts of proposing solutions concerning the protection for the land area environmental balance, monitoring and surveillance. But unfortunately there have been a very handful of research work which predominantly concerns about the protection upon the environmental state of marine biological species and its ecosystem. So, the following research study proposes a solution which appears to be a full-fledged Bluetooth controlled Submarine prototype with a sensory chipboard attached inside its endo-skeleton which contains multiple sensors like DHT11 temperature-humidity, dust, CO2 and YL69 pH sensors. The sensory data provides the information of underwater whether the naval environment is habitable for the marine biological species or not, under the terrible effect of global climate change. The submarine prototype is fully functional in the surface and underwater scenario which contains a very unique mechanical design and circuitry with an exceptional sensor data streaming capability which can be used by marine biological researchers and oceanographers professionally as a full-fledged marine ecosystem monitoring device.
 HIGHLIGHTS
 
 Climate change is causing a very alarming effect in the oceanic area which is constantly threatening the future of marine biological species. The paper focuses on the constant monitoring over spacies with the help of a multi-sensory submarine with real time sensory data and remote navigation
 The unique clustering of multi-sensory circuity makes the sensory data more reliable while the vacuum controlled hydraulic pump motors make the navigation and diving of the submarine prototype very preciseand swift
 The navigation can be controlled with a globally unique and customized Submarine Navigator Smartphone Application
 The multi-sensory marine species monitoring submarine prototype appears to be a torch-bearer of the amalgamation of the fields such as IOT-Sensors and Robotics which paves the way for further IOT and Naval Robotics Research
 
 GRAPHICAL ABSTRACT

Disentangling the components of coastal fish biodiversity in southern Brittany by applying an environmental DNA approach

AbstractThe global biodiversity crisis from anthropogenic activities significantly weakens the functioning of marine ecosystems and jeopardizes their ecosystem services. Increasing monitoring of marine ecosystems is crucial to understand the breadth of the changes in biodiversity, ecosystem functioning and propose more effective conservation strategies. Such strategies should not only focus on maximizing the number of species (i.e., taxonomic diversity) but also the diversity of phylogenetic histories and ecological functions within communities. To support future conservation decisions, multicomponent biodiversity monitoring can be combined with high‐throughput species assemblage detection methods such as environmental DNA (eDNA) metabarcoding. Here, we used eDNA to assess fish biodiversity along the coast of southern Brittany (France, Iroise Sea). We filtered surface marine water from 17 sampling stations and applied an eDNA metabarcoding approach targeting Actinopterygii and Elasmobranchii taxa. We documented three complementary biodiversity components—taxonomic, phylogenetic, and functional diversity—and three diversity facets—richness, divergence and regularity. We identified a north/south contrast with higher diversity for the three facets of the biodiversity components in the northern part of the study area. The northern communities showed higher species richness, stronger phylogenetic overdispersion and lower functional clustering compared to the ones in the southern part, due to the higher diversity of habitats (reefs, rocky shores) and restricted access for fishing. Moreover, we also detected a higher level of taxonomic, phylogenetic, and functional uniqueness in many offshore stations compared to more coastal ones, with the presence of species typically living at greater depths (> 300 m), which suggests an influence of hydrodynamic structures and currents on eDNA dispersion and hence sample composition. eDNA metabarcoding can, therefore, be used as an efficient sampling method to reveal fine‐scale community compositions and in combination with functional and phylogenetic information to document multicomponent biodiversity gradients in coastal marine systems.

Applying Acoustic Scattering Layer Descriptors to Depict Mid-Trophic Pelagic Organisation: The Case of Atlantic African Large Marine Ecosystems Continental Shelf

To identify key nonspecific organisational characteristics of the mid-trophic pelagic communities, which remain a challenge, we work with sound scattering layers (SSLs). Application was tested in the three African Atlantic Large Marine Ecosystems (AALMEs) to assess the utility of adapting and developing new acoustic variables. Our methodology allowed comparison between Large Marine Ecosystems (LMEs) based on 14 morphological, spatial and acoustic variables to characterize SSLs over time. These original variables were effective in monitoring and comparing the LMEs, and even allowed us to discriminate different organisations inside the Canary Current LME. Common traits identified for all AALMEs included the importance of the shallowest SSL. However, we identified an unexpected night-time pattern in SSL distributions in the Benguela Current LME which reflect a major difference in diel vertical migration mechanisms relative to other AALMEs. We also highlighted the predominance of elementary sampling unit (ESUs) with a single SSL and an unoccupied tiny layer close to the bottom, even if some ESUs presented up to six SSLs. Inter-annual changes in SSL organisation are highlighted by adaptation of original variables as the proportion of the water column occupied by SSLs and the relative importance of the shallowest SSL. SSL variables have been used mostly in deep water; here, we applied them on the continental shelf. SSL variables can be used to standardize the monitoring of marine ecosystems and capture change in spatial structure and function of mid-trophic pelagic marine ecosystems worldwide, even in data-poor areas where species identification of lower-trophic pelagic organism remains a challenge.

Assessing the Image Concept Drift at the OBSEA Coastal Underwater Cabled Observatory

The marine science community is engaged in the exploration and monitoring of biodiversity dynamics, with a special interest for understanding the ecosystem functioning and for tracking the growing anthropogenic impacts. The accurate monitoring of marine ecosystems requires the development of innovative and effective technological solutions to allow a remote and continuous collection of data. Cabled fixed observatories, equipped with camera systems and multiparametric sensors, allow for a non-invasive acquisition of valuable datasets, at a high-frequency rate and for periods extended in time. When large collections of visual data are acquired, the implementation of automated intelligent services is mandatory to automatically extract the relevant biological information from the gathered data. Nevertheless, the automated detection and classification of streamed visual data suffer from the “concept drift” phenomenon, consisting of a drop of performance over the time, mainly caused by the dynamic variation of the acquisition conditions. This work quantifies the degradation of the fish detection and classification performance on an image dataset acquired at the OBSEA cabled video-observatory over a one-year period and finally discusses the methodological solutions needed to implement an effective automated classification service operating in real time.

Drone-Based Characterization of Seagrass Habitats in the Tropical Waters of Zanzibar

Unmanned automatic systems (UAS) are increasingly being applied as an alternative to more costly time-consuming traditional methods for mapping and monitoring marine shallow-water ecosystems. Here, we demonstrate the utility of combining aerial drones with in situ imagery to characterize the habitat conditions of nine shallow-water seagrass-dominated areas on Unguja Island, Zanzibar. We applied object-based image analysis and a maximum likelihood algorithm on the drone images to derive habitat cover maps and important seagrass habitat parameters: the habitat composition; the seagrass species; the horizontal- and depth-percent covers, and the seascape fragmentation. We mapped nine sites covering 724 ha, categorized into seagrasses (55%), bare sediment (31%), corals (9%), and macroalgae (5%). An average of six seagrass species were found, and 20% of the nine sites were categorized as “dense cover” (40–70%). We achieved high map accuracy for the habitat types (87%), seagrass (80%), and seagrass species (76%). In all nine sites, we observed clear decreases in the seagrass covers with depths ranging from 30% at 1–2 m, to 1.6% at a 4–5 m depth. The depth dependency varied significantly among the seagrass species. Areas associated with low seagrass cover also had a more fragmented distribution pattern, with scattered seagrass populations. The seagrass cover was correlated negatively (r2 = 0.9, p < 0.01) with sea urchins. A multivariate analysis of the similarity (ANOSIM) of the biotic features, derived from the drone and in situ data, suggested that the nine sites could be organized into three significantly different coastal habitat types. This study demonstrates the high robustness of drones for characterizing complex seagrass habitat conditions in tropical waters. We recommend adopting drones, combined with in situ photos, for establishing a suite of important data relevant for marine ecosystem monitoring in the Western Indian Ocean (WIO).

Challenges for Marine Ecological Assessments: Completeness of Findable, Accessible, Interoperable, and Reusable Biodiversity Data in European Seas

The ongoing contemporary biodiversity crisis may result in much of ocean’s biodiversity to be lost or deeply modified without even being known. As the climate and anthropogenic-related impacts on marine systems accelerate, biodiversity knowledge integration is urgently required to evaluate and monitor marine ecosystems and to support suitable responses to underpin a sustainable future. The Census of Marine Life (CoML, 2000–2010) was the largest global research program on marine biodiversity. A decade after, and coinciding with the steep increase of digitalization of our society, we review existing findability, accessibility, interoperability, and reusability (FAIR) biodiversity data coming from one of the most reliable online information systems: the Global Biodiversity Information Facility (GBIF). We evaluate the completeness of available datasets with respect to the CoML benchmark, along with progresses in understanding spatial–temporal patterns of marine biodiversity in the European Seas in the last decades. Overall, we observe severe biases in available biodiversity data toward the north-western marine regions (particularly around the United Kingdom and the North Sea), the most recent years (with a peak in the number of reported occurrences in the 2010s) and the most conspicuous, abundant, and likely “appealing” taxa (e.g., crustaceans, echinoderms or fish). These biases may hamper research applications, but also global-scale data needs and integrative assessments required to support cost-effective progresses toward global biodiversity conservation. National to international joint efforts aimed at enhancing data acquisition and mobilization from poorly known regions, periods, and taxa are desirable if we aim to address these potential biases for the effective monitoring of marine ecosystems and the evaluation of ongoing impacts on biogeographic patterns and ecosystem functioning and services.

Ecoacoustic indices in marine ecosystems: a review on recent developments, challenges, and future directions

Abstract Soundscape ecology has gained prominence in the monitoring of marine ecosystems due to its non-invasive characteristics and spatiotemporal efficiency. However, the development of ecoacoustic indices is a recent field that needs to address many challenges to fulfill its great potential, especially in the context of marine ecology. Here, we reviewed the most recent studies that used ecoacoustic indices in marine ecosystems. The literature search was conducted in the Scopus (Elsevier) database and used the chain referral sampling in the list of references of each publication. In total, we identified 27 publications that used ecoacoustic indices in marine environments such as coral reefs, rocky shores, coastal regions, and offshore regions. A total of four major limitations were identified and addressed, including: the challenge to find adequate acoustic bioindicators; the lack of a universal index or standardized protocol; the issue that most acoustic indices applied to marine environments have been developed to be used in terrestrial environments; and the lack of studies that have tested ecoacoustic indices under different environmental conditions. Once these challenges are addressed, the analysis of marine sound based on the interpretation of ecoacoustic indices has a great potential to become one of the most cost-effective tools for monitoring environments.

A machine learning approach for spatiotemporal imputation of MODIS chlorophyll-a

ABSTRACT The Moderate Resolution Imaging Spectroradiometer (MODIS) level-3 chlorophyll-a (Chl-a) product is one of the widely used ocean colour products that is often used for water quality monitoring of marine ecosystems. However, this product includes a large amount of missing data due to high surface reflectance and cloudy conditions that inevitably affect its suitability for spatiotemporal analysis of water quality. The objective of this study was to compare four Machine Learning (ML) techniques including K-nearest neighbour (KNN), Support Vector Regression (SVR), Random Forest Regression (RFR), and Artificial Neural Network (ANN) with well-known Data Interpolation Empirical Orthogonal Function (DINEOF) method for spatiotemporal missing imputation of MODIS Chl-a. The Southern Caspian Sea, which has a high Chl-a concentration, was selected as the case study. A cross-validation approach ranging missing data ratio from 0.1 to 0.8 was implemented to investigate the optimal parameters of the models and compare their performance for missing imputation. The results indicated that all ML models, except KNN, outperformed the DINEOF method for missing imputation of MODIS Chl-a. The SVR with the highest accuracy and the lowest variability of errors had the best performance among the five competing models, while the KNN showed the worst performance. The main reason for the better accuracy of the SVR than the other models is its structural risk minimization procedure that leads to the better generalization of the SVR model. The current results showed that the ML techniques used in the current study, the SVR in particular, are able to produce reliable imputations of the MODIS Chl-a missing data and can be a useful tool in water quality monitoring of marine ecosystems.

Underwater Hyperspectral Imaging (UHI): A Review of Systems and Applications for Proximal Seafloor Ecosystem Studies

Marine ecosystem monitoring requires observations of its attributes at different spatial and temporal scales that traditional sampling methods (e.g., RGB imaging, sediment cores) struggle to efficiently provide. Proximal optical sensing methods can fill this observational gap by providing observations of, and tracking changes in, the functional features of marine ecosystems non-invasively. Underwater hyperspectral imaging (UHI) employed in proximity to the seafloor has shown a further potential to monitor pigmentation in benthic and sympagic phototrophic organisms at small spatial scales (mm–cm) and for the identification of minerals and taxa through their finely resolved spectral signatures. Despite the increasing number of studies applying UHI, a review of its applications, capabilities, and challenges for seafloor ecosystem research is overdue. In this review, we first detail how the limited band availability inherent to standard underwater cameras has led to a data analysis “bottleneck” in seafloor ecosystem research, in part due to the widespread implementation of underwater imaging platforms (e.g., remotely operated vehicles, time-lapse stations, towed cameras) that can acquire large image datasets. We discuss how hyperspectral technology brings unique opportunities to address the known limitations of RGB cameras for surveying marine environments. The review concludes by comparing how different studies harness the capacities of hyperspectral imaging, the types of methods required to validate observations, and the current challenges for accurate and replicable UHI research.

Low-cost action cameras offer potential for widespread acoustic monitoring of marine ecosystems

Underwater passive acoustic monitoring (PAM) is of growing importance for monitoring the health of aquatic environments. Standard practices use expensive hydrophones to sample soundscapes. They must either be linked to surface recording rigs or use autonomous instrumentation which comes at a premium cost. Although citizen science projects could be of great value to PAM by increasing the number of underwater recordings collected around the world, there is a lack of available low-cost and user-friendly recording hardware. However, consumer-grade action cameras potentially offer an accessible alternative to traditional hydrophones, capable of capturing underwater acoustic recordings.We evaluated the performance of two models of GoPro underwater action cameras deployed as PAM recorders. We tested these cameras against a research-grade hydrophone in a range of shallow tropical sea environments. First, in a sandy area away from reef habitat, we took simultaneous recordings of loudspeaker playbacks of known acoustic signals using all three instruments. We then performed repeated deployments on different coral reef sites in which all three instruments were placed side-by-side to record simultaneously the same natural reef soundscapes. We calculated eight of the most commonly used ecoacoustic indices used in marine soundscape ecology, and assessed the reliability and quantitative accuracy of these compared to the hydrophone.Although not calibrated, GoPros captured recordings from which selected ecoacoustic indices could be calculated reliably, including temporal variability, the acoustic complexity index and acoustic richness. Metrics derived from GoPros can be valuably compared between recordings taken using the same model, but are not directly comparable with hydrophone-derived values. We outline the best settings for collecting soundscape data with GoPros.Underwater action cameras are used frequently by marine scientists, sports enthusiasts and tourists around the world. Their capacity to capture soundscape recordings represents a valuable approach for the global expansion of PAM through citizen science.