Turbid Conditions Research Articles

Seasonal biomass productivity and bioremediation performance of the novel aquaculture target species Gracilaria transtasmanica in nutrient-enriched and turbid conditions

In-situ macroalgal bioremediation is a promising solution for reducing excess nutrients in degraded estuaries. A critical first stage in developing macroalgal bioremediation for estuarine restoration is ensuring target species for cultivation can assimilate nutrients under relevant local conditions. The native red macroalga Gracilaria transtasmanica has been identified as a potential target for bioremediation in New Zealand estuaries. Therefore, the aim of this study was to assess the biomass productivity, photosynthetic health, and nitrogen removal of G. transtasmanica in batch cultures in winter (15.8–21.2 °C) and summer (18.6–29.9 °C) conditions under nitrogen and sediment levels representative of ambient (1 mg DIN L−1, 0.02 g sediment L−1) and extreme (10 mg DIN L−1, 0.25 g sediment L−1) conditions in estuarine habitats. Biomass productivity and total nitrogen removed were 45 and 50 % higher, respectively, in summer (0.4–4.3 g DW m−2, 6.0–30.7 mg N) compared to winter (0.6–1.8 g DW m−2, 6.1–9.1 mg N). In contrast, standardised nitrogen removal rates were higher in winter (37.8 mg N per g DW biomass growth ±0.6 S.E.) compared to summer (22.3 mg N per g DW biomass growth ±1.2 S.E.), suggesting that nitrogen uptake was independent of productivity under sub-optimal conditions. Turbidity reduced productivity in winter but increased productivity in summer. Optimal and effective quantum yields showed that the biomass was less stressed in winter, and that the functioning of photosystem II was negatively impacted during summer. These results demonstrate that G. transtasmanica can assimilate nutrients under a range of environmental conditions that are representative of both local background and high suspended sediment loads and nitrogen concentrations, and under ambient summer and winter conditions, even when biomass productivity is low. Gracilaria transtasmanica is therefore a viable target species for year-round in-situ bioremediation of nutrient-enriched estuaries.

Advanced deep learning framework for underwater object detection with multibeam forward-looking sonar

Underwater object detection (UOD) is an essential activity in maintaining and monitoring underwater infrastructure, playing an important role in their efficient and low-risk asset management. In underwater environments, sonar, recognized for overcoming the limitations of optical imaging in low-light and turbid conditions, has increasingly gained popularity for UOD. However, due to the low resolution and limited foreground-background contrast in sonar images, existing sonar-based object detection algorithms still face challenges regarding precision and transferability. To solve these challenges, this article proposes an advanced deep learning framework for UOD that uses the data from multibeam forward-looking sonar. The framework is adapted from the network architecture of YOLOv7, one of the state-of-the-art vision-based object detection algorithms, by incorporating unique optimizations in three key aspects: data preprocessing, feature fusion, and loss functions. These improvements are extensively tested on a dedicated public dataset, showing superior object classification performance compared to the selected existing sonar-based methods. Through experiments conducted on an underwater remotely operated vehicle, the proposed framework validates significant enhancements in target classification, localization, and transfer learning capabilities. Since the engineering structures have similar geometric shapes to the objects tested in this study, the proposed framework presents potential applicability to underwater structural inspection and monitoring, and autonomous asset management.

Kajian Dan Rancang Bangun Alat Pakan Ikan Otomatis (Smart Feeder) Pada Kolam Budidaya Ikan Berbasis Internet Of Things

In fish farming, the timing of fish feeding is very important, fish need regular and continuous feed. Feed is a component in fish farming that is useful for growth, so feeding is fundamental in fish farming. Overfeeding can increase production costs and degrade water quality. Fish farmers often have to do several activities at the same time, which can lead to errors in the amount of fish feed. This results in large feed costs and decreased pond water quality. Seeing these problems, a study was conducted that aims to create a tool that can monitor water quality and automatic fish feeders using Internet of Things (IoT) technology that functions to monitor feed schedules and water quality conditions that can be seen through applications on smartphones, in addition to monitoring water quality and automatic feeders, it can also display log data on the amount of fish feed that has been given, fish feed is running out and water turbidity conditions have reached more than 25 NTU. At the time of testing, the tool has worked well, the tool can monitor the amount of feed, and Turbidity sensor can read the level of water turbidity, this tool can also send realtimei information well, the time required in sending information on the application is ± 2 seconds

Insight into the dynamics of a long-runout mass movement using single-grain feldspar luminescence in the Pokhara Valley, Nepal

Abstract. Mass movements play an important role in landscape evolution of high mountain areas such as the Himalayas. Yet, establishing numerical age control and reconstructing transport dynamics of past events is challenging. To fill this research gap, we bring luminescence dating to the test in an extremely challenging environment: the Pokhara Valley in Nepal. This is challenging for two reasons: (i) the optically stimulated luminescence (OSL) sensitivity of quartz, typically the mineral of choice for dating sediments younger than 100 ka, is poor, and (ii) highly rapid and turbid conditions during mass movement transport hamper sufficient OSL signal resetting prior to deposition, which eventually results in age overestimation. Here, we first assess the applicability of single-grain feldspar dating of medieval mass movement deposits catastrophically emplaced in the Pokhara Valley. Second, we exploit the poor bleaching mechanisms to get insight into the sediment dynamics of this paleo-mass movement through bleaching proxies. The Pokhara Valley is a unique setting for our case study, considering the availability of an extensive independent radiocarbon dataset as a geochronological benchmark. Single-grain infrared stimulated luminescence (IRSL) signals were measured at 50 ∘C (IRSL-50) and post-infrared infrared stimulated luminescence signals at 150 ∘C (pIRIR-150). Our results show that the IRSL-50 signal is better bleached than the pIRIR-150 signal. A bootstrapped minimum age model (bMAM) is applied to retrieve the youngest subpopulation to estimate the paleodose. However, burial ages calculated with this paleodose overestimate the radiocarbon ages by an average factor of ∼23 (IRSL-50) and ∼72 (pIRIR-150), showing that dating of the Pokhara Formation with a single-grain approach was not successful for most samples. Some samples, however, only slightly overestimate the true emplacement age and thus could be used for a rough age estimation. Large inheritances in combination with the scatter in the single-grain dose distributions show that the sediments have been transported under extremely limited light exposure prior to deposition, which is consistent with the highly turbid nature of the sediment-laden flood and debris flows depositing the Pokhara gravels. To investigate the sediment transport dynamics in more detail, we studied three bleaching proxies: the percentage of grains in saturation 2D0 criteria, the percentage of best-bleached grains (2σ range of bMAM-De) and the overdispersion (OD). None of the three bleaching proxies indicate a spatial relationship with runout distance of the mass movement deposits. We interpret this as evidence for the lack of bleaching during transport, which reflects the catastrophic nature of the event. While not providing reliable burial ages of the Pokhara mass movement deposits, single-grain feldspar dating can potentially be used as an age range finder method. Our approach shows the potential of luminescence techniques to provide insights in sediment transport dynamics of extreme and rare mass movement events in mountainous regions.

Potential to use free satellite imagery to retrieve the past bathymetry of large rivers

Information on bathymetric changes in large rivers is useful for flood planning, navigation, and predicting channel change. Recent studies have demonstrated the potential for measuring bathymetry of rivers from satellite images, but such studies have used high-resolution, expensive data applied to ideal river conditions, such as low turbidity. Many of the large rivers of the world are located in countries that cannot afford the carefully planned field surveys and commercial satellite images used in these studies. In this study we investigate whether past bathymetry of large rivers could be retrieved by using readily collated free satellite images, combined with the limited cross-sectional surveys that are typically available in less wealthy countries. We tested the method in the heavily regulated Han River of central China. The Landsat-8 and Sentinel-2 image-derived depth could quantitatively match in situ depths along cross-sections up to depths of 13.9 m, where the suspended sediment concentration was low due to dam regulation. However, in most of the river where turbidity was high, the method was less successful. The image-to-depth quantile transformation (IDQT) approach could improve passive bathymetry retrieval in cases like the Han River, where there was some spatial and temporal misalignment between in situ data and remote-sensing data. The lateral depth pattern up to the 2.5 m depth contour could also be qualitatively and visually interpreted over an extended length (15 km). These results suggest that there is potential to use free satellite imagery to derive bathymetry in many large rivers, but this potential can only be achieved in very limited (low turbidity) conditions, and with image to depth correlation analysis and band selection.

Transfer Learning and Few-Shot Learning Based Deep Neural Network Models for Underwater Sonar Image Classification With a Few Samples

Acoustic imaging sonar systems are widely used for long-range underwater surveillance in various civilian and military applications. They provide 2-D images of underwater objects, even in turbid water conditions where optical underwater imaging systems fail. Achieving high accuracy in automatic deep learning based underwater image classification remains an open problem due to insufficient data availability, poor image resolution, low signal-to-noise ratio surroundings, etc. In this study, we conduct a comparative analysis of different advanced deep learning approaches, i.e., transfer learning and few-shot learning, to address the problem of automatic object classification in sonar images, using a few samples of data. Specifically, two metric learning-based approaches, i.e., siamese network and triplet network as well as library-based approaches, are studied under the few-shot learning paradigm. Extensive experiments are conducted on a novel custom-made dataset developed in-house, along with the publicly available SeabedObjectsKLSG dataset. In addition, the effectiveness of the sampling technique in handling class imbalance during model training is also investigated in this work. Our experimental results highlight that the few-shot learning based approach is a promising direction for future research on underwater image classification with a few samples.

Water Quality and Flooding Impact of the Record-Breaking Storm Gloria in the Ebro Delta (Western Mediterranean)

Extreme events are increasing in frequency and severity due to climate change, making the littoral zone even more vulnerable and requiring continuous monitoring for its optimized management. The low-lying Ebro Delta ecosystem, located in the NW Mediterranean, was subject to Storm Gloria in the winter of 2020, the most severe coastal storm registered in the area in decades and one of the most intense ever recorded in the Mediterranean. This event caused intense rainfall, severe flooding, the erosion of beaches, and the destruction of coastal infrastructures. In this study, the Landsat-8 and Sentinel-2 satellites were used to monitor the flooding impact and water quality status, including chlorophyll-a, suspended particulate matter, and turbidity, to evaluate the pre-, syn-, and post-storm scenarios. Image processing was carried out using the ACOLITE software and the on-the-cloud Google Earth Engine platform for the water quality and flood mapping, respectively, showing a consistent performance for both satellites. This cost-effective methodology allowed us to characterize the main water quality variation in the coastal environment during the storm and detect a higher flooding impact compared to the one registered three days later by the Copernicus Emergency Service for the same area. Moreover, the time series revealed how the detrimental impact on the water quality and turbidity conditions was restored two weeks after the extreme weather event. While transitional plumes of sediment discharge were formed, no phytoplankton blooms appeared during the study period in the delta. These results demonstrate that the workflow implemented is suitable for monitoring extreme coastal events using open satellite imagery at 10–30 m spatial resolution, thus providing valuable information for early warning to facilitate timely assistance and hazard impact evaluation. The integration of these tools into ecological disaster management can significantly improve current monitoring strategies, supporting decision-makers from the local to the national level in prevention, adaptation measures, and damage compensation.

Shoaling behaviour in response to turbidity in three-spined sticklebacks.

Many fresh and coastal waters are becoming increasingly turbid because of human activities, which may disrupt the visually mediated behaviours of aquatic organisms. Shoaling fish typically depend on vision to maintain collective behaviour, which has a range of benefits including protection from predators, enhanced foraging efficiency and access to mates. Previous studies of the effects of turbidity on shoaling behaviour have focussed on changes to nearest neighbour distance and average group-level behaviours. Here, we investigated whether and how experimental shoals of three-spined sticklebacks (Gasterosteus aculeatus) in clear (<10 Nephelometric Turbidity Units [NTU]) and turbid (~35 NTU) conditions differed in five local-level behaviours of individuals (nearest and furthest neighbour distance, heading difference with nearest neighbour, bearing angle to nearest neighbour and swimming speed). These variables are important for the emergent group-level properties of shoaling behaviour. We found an indirect effect of turbidity on nearest neighbour distances driven by a reduction in swimming speed, and a direct effect of turbidity which increased variability in furthest neighbour distances. In contrast, the alignment and relative position of individuals was not significantly altered in turbid compared to clear conditions. Overall, our results suggest that the shoals were usually robust to adverse effects of turbidity on collective behaviour, but group cohesion was occasionally lost during periods of instability.

Interactions between stoneworts (Charales) and waterbirds.

Stoneworts (Charales) are green algae that represent an important food resource for many waterbird species in Europe and elsewhere. Browsing avian herbivores (e.g. swan, goose, duck and coot species) consume Charales plant vegetative parts, by head-dipping, up-ending or diving. A lower fibre content and longer growing season may make Charales as attractive to such herbivores as sympatric submerged higher plant species in some circumstances. Charales respond to environmental stress (e.g. drought) by producing abundant diaspores, in the form of oospores (sexual) and bulbils (asexual), both rich in starch, generating abundant food for waterbirds at critical stages in their annual migratory cycles. Waterbirds feed on these by diving (e.g. common pochard Aythya ferina and red-crested pochard Netta rufina) or by filtering from the water column (e.g. dabbling duck species), ensuring dispersal of sexually produced and vegetative diaspores locally (because of predator swamping) and remotely (through endo- and ectozoochorous dispersal by long-distance migratory waterbirds). Greater invertebrate density and diversity associated with Charales canopies enhances their attractiveness over other submerged macrophyte beds to diving predators [e.g. tufted duck Aythya fuligula, common pochard and Eurasian coot Fulica atra (hereafter coot)]. Fish fry preying on these invertebrates use such vegetation as predator cover, in turn providing prey for avian piscivores such as grebes and cormorants. Abundant Charales contribute to maintaining a transparent water column due to canopy density, nutrient effects, dampening of sedimentation/remobilisation of suspended matter and nutrients and allelopathic effects on other plants (especially phytoplankton). Shallow, relatively eutrophic waters can flip between clear-water high-biodiversity (where Charales thrive) and turbid species-poor depauperate stable states (lacking Charales). Shifts between turbid conditions and rich submerged Charales beds have profound elevating effects on aquatic diversity, to which waterbirds show rapid aggregative responses, making them ideal indicator species of ecological change; in the case of Charales specialists (such as red-crested and common pochard), indicators of the presence and abundance of these plants. Large-bodied colonial nesting birds (e.g. cormorants, gulls, heron and egrets) aggregating along lake shores contribute high N and P loadings to water bodies sensitive to such external and internal inputs and can cause local eutrophication and potential loss of Charales. Despite variation from complete seasonal removal of Charales biomass to undetectable grazing effects by herbivorous birds, evidence suggests little effect of avian grazing on biomass accumulation or the stability of community composition (under otherwise stable conditions), but we urge more research on this under-researched topic. We also lack investigations of the relative foraging profitability of different Charales organs to waterbirds and the degree of viability of gyrogonites (fertilised and calcified oospores), vegetative bulbils and plant fragments after passage through the guts of waterbirds. We especially need to understand better how much the carbonate armour of these organs affects their viability/dispersal via waterbirds and urge more research on these neglected plants and their relationships and interactions with other organisms in the aquatic biota.

Brief floodplain inundation provides growth and survival benefits to a young-of-year fish in an intermittent river threatened by water development

Riverine floodplains are highly productive habitats that often act as nurseries for fish but are threatened by flow regulation. The Fitzroy River in northern Australia is facing development, but uncertainty exists regarding the extent to which floodplain habitats deliver benefits to fish, particularly given the brevity of seasonal floodplain inundation. We investigated the growth rate of young-of-year bony bream (Nematalosa erebi) in main channel and ephemeral floodplain habitats using age derived from otolith daily increments. We also investigated potential mechanisms influencing growth and modelled the consequences of differential growth rate on survival. Our results revealed higher growth occurred exclusively on the floodplain and that zooplankton biomass was the best predictor of growth rate. Modelling indicated that elevated growth rate in high-growth floodplain pools (top 25th percentile) could translate into substantial increases in survivorship. The positive effect of zooplankton biomass on growth was moderated under highly turbid conditions. Temperature had a minor influence on growth, and only in floodplain habitats. Our results indicate ephemeral floodplain habitats can deliver substantial growth and survival benefits to young-of-year fish even when floodplain inundation is brief. This study highlights the need to ensure that water policy safeguards floodplain habitats due to their important ecological role.

Scaling up benthic primary productivity estimates in a large intertidal estuary using remote sensing

As two main primary producers in temperate intertidal regions, seagrass and microphytobenthos (MPB) support estuarine ecosystem functions in multiple ways including stabilizing food webs and regulating sediment resuspension among others. Monitoring estuary productivity at large scales can inform ecosystem scale responses to environmental stressors (climate change, pollution and habitat degradation). Here we use a case study to show how Sentinel-2 data can be used to estimate estuary-wide emerged and submerged gross primary productivity (GPP) on intertidal flats by coupling a new machine learning model to map seagrass and unvegetated habitats with literature-derived photosynthesis-irradiance (P – I) relationships. The model consisted of (1) supervised classification with random forest to delineate seagrass and unvegetated areas and (2) artificial neural network (ANN) regression to predict % seagrass coverage. Our seagrass delineation by supervised classification had an overall accuracy of 0.96, while the ANN regression on seagrass coverage provided high predictive accuracy (R2 = 0.71 and RMSE = 0.11). The estimated GPP showed seagrass contributed slightly more to intertidal benthic productivity than MPB in the case-study estuary over the 3-year study period. This model can be used to predict the response of seagrass and MPB GPP to sea level rise, which shows that the future state may be very sensitive to increased turbidity. For example, by the year 2100, the model shows a sharp decline in productivity with sea level rise, assuming current turbidity trends, (loss of up to 52–53 % for seagrass and 23–45 % for MPB, a function of whether shoreward migration of seagrass is incorporated). However, GPP under conditions of unchanging turbidity (and no seagrass migration), exhibits minimal negative impact of sea level rise (loss of 3 % for seagrass and increase of 29 % for MPB). Therefore, controlling water turbidity might be an efficient solution to maintaining the current GPP as sea level rises.

Modeling the celestial distribution of skylight polarization patterns by incorporating the influence of both the sun and the moon through an analytical model.

The orientation of many polarization-sensitive animals and the hypothetical sky-polarimetric Viking navigation both rely on the polarization pattern of skylight. For 40 years, scientists have attempted to construct various models to simulate this pattern. However, existing theoretical models have only analyzed the polarization pattern of skylight that is influenced separately by the sun or the moon and have built their modeling frameworks based on the position of one light source. This approach fails to account for the combined influence of the sun and the moon on the distribution of skylight polarization patterns at certain times. In fact, ignoring the influence of the moon during the dawn and dusk periods in clear weather conditions may lead to significant errors in the simulation results compared to the measured data. In this paper, we present an analytical model that considers various factors, including skylight intensity, horizon correction factor, atmospheric turbidity condition, and combined influence of both the sun and moon on the distribution of polarized skylight. We believe our model demonstrates enhanced agreement with measured data and will further our understanding of how animals use the celestial polarization pattern for navigation, particularly when both the sun and the moon appear in the sky. Moreover, the findings of this study may facilitate the advancement of bio-inspired navigation systems.

Notes on the ecology and distribution of a water flea complex (Anomopoda, Daphniidae) revealed by new DNA barcodes in the Iberian Peninsula

AbstractAvailable DNA barcodes of freshwater zooplankton are scarce in regions like the Iberian Peninsula, which harbours many rare and endemic species and is considered a hotspot of crustacean biodiversity. Recently, a new species of Ceriodaphnia (Cladocera: Daphniidae) was described using morphological analysis of specimens in the Mediterranean region and molecular data on a single locality in southern Spain. In our study, we detected the presence of the newly discovered taxa and here, we provide new DNA sequences on the barcoding region mitochondrial cytochrome c oxidase I together with ecological information of the recently described Ceriodaphnia smirnovi. Additionally, we built a molecular phylogenetic tree and genetically compared these specimens with previously available mitochondrial DNA sequences and with new sequences of the genus recovered in Iberia. Our data suggest that this morphospecies might contain some cryptic taxa and might be more common than previously thought, occupying temporary to semi‐permanent ecosystems, with vegetation and highly variable pH and turbidity conditions. Moreover, the existence of a non‐identified clade within our phylogenetic tree requires additional morphological research. Our study highlights the need for further research on microcrustacean biota to better constrain its spatial boundaries, phylogenetic relationship and determine species hiding cryptic diversity.

Synergistic effects between global warming and water quality change on modelled macrophyte species richness

Submerged freshwater macrophytes are crucial for the functioning of lakes. Their growth and survival follow environmental conditions like light, temperature, and nutrient availability. Hence, the impending increase in water temperature as well as changes of nutrients and turbidity will lead to changes in macrophyte geographic and depth distribution: Herein, we assess these potential changes. We apply an eco‐physiological macrophyte growth model to simulate biomass growth and survival of virtual species defined by random trait combinations within expert‐derived trait ranges for oligotraphentic, mesotraphentic, and eutraphentic species groups in deep lakes in Bavaria, Germany, which cover clear, moderate, and turbid lake conditions. The emergent potential species richness is compared with empirically observed species richness to evaluate general predictions for current conditions. Thereafter, we apply the model to scenarios of temperature increase and of turbidity and nutrient change to assess potential changes in species richness and the influence of species' traits on being an environmental change ‘winner' or ‘loser'. We find a cross‐lake, hump‐shaped pattern of potential species richness along depth. This largely reflects observed patterns, although mismatches were also detected and might be explained by missing processes and environmental heterogeneity within the lake. Rising temperature leads to increased richness of potential species in all lake types, species groups, and depths. Turbidity and nutrient change effects depend on depth and lake type. ‘Loser species' under increased turbidity and nutrient level are light consumptive and sensible to disturbances, while ‘winner species' have a high biomass production. These findings show that the hump‐shaped depth distributions of submerged macrophyte diversity can emerge solely considering eco‐physiology. The differential responses to environmental changes imply that management measures must account for lake type because those responses can have opposite trends depending on lake depth and type.

Comparative study on real-time pose estimation of vision-based unmanned underwater vehicles

Background: Navigation and localization are key to the successful execution of autonomous unmanned underwater vehicles (UUVs) in marine environmental monitoring, underwater 3D mapping, and ocean resource surveys. The estimation of the position and the orientation of autonomous UUVs are a long-standing challenging and fundamental problem. As one of the underwater sensors, camera has always been the focus of attention due to its advantages of low cost and rich content information in low visibility waters, especially in the fields of visual perception of the underwater environment, target recognition and tracking. At present, the visual real-time pose estimation technology that can be used for UUVs is mainly divided into geometry-based visual positioning algorithms and deep learning-based visual positioning algorithms. Methods: In order to compare the performance of different positioning algorithms and strategies, this paper uses C++ and python, takes the ORB-SLAM3 algorithm and DF-VO algorithm as representatives to conduct a comparative experiment and analysis. Results: The geometry-based algorithm ORB-SLAM3 is less affected by illumination, performs more stably in different underwater environments, and has a shorter calculation time, but its robustness is poor in complex environments. The visual positioning algorithm DF-VO based on deep learning takes longer time to compute, and the positioning accuracy is more easily affected by illumination, especially in dark conditions. However, its robustness is better in unstructured environments such as large-scale image rotation and dynamic object interference. Conclusions: In general, the deep learning-based algorithm is more robust, but multiple deep learning networks make it need more time to compute. The geometry-based method costs less time and is more accurate in low-light and turbid underwater conditions. However, in real underwater situations, these two methods can be connected as binocular vision or methods of multi-sensor combined pose estimation.

Exposure pathways matter: Aquatic phototrophic communities respond differently to agricultural run‐off exposed via sediment or water

Abstract Small shallow ponds are widespread but understudied water bodies in agricultural landscapes. Agricultural run‐off (ARO) transports pesticides and nutrients into adjacent aquatic ecosystems where they occur dissolved in the water column or are bound to sediments. Consequently, aquatic communities are affected by ARO via different exposure pathways. We hypothesize that sediment‐bound ARO mainly affects submerged rooted macrophytes, while phytoplankton and periphyton are more prone to ARO in water. These primary producers compete for resources resulting in a regime shift between alternative stable states of macrophyte or phytoplankton dominance. We hypothesize that warming increases nutrient release from sediments and thereby facilitates the occurrence of phytoplankton dominance. Using a full‐factorial microcosm design, we exposed aquatic primary producers to either sediment or water application of a mixture of common pesticides (terbuthylazine, pirimicarb, tebuconazole and copper) and nitrate at two concentrations and two temperatures (22°C and 26°C) for 4 weeks. Initial and final concentrations of pesticides and nitrate, final biomass of macrophytes, periphyton and phytoplankton, pesticide accumulation in macrophytes and changes in carbon, nitrogen and phosphorus content and selected exoenzyme activities in the sediment were measured. We found lower final macrophyte biomass for both ARO treatments compared to controls, indicating a prevalence of negative effects by herbicides and competition for light with other phototrophs. In contrast, phytoplankton and periphyton biomass increased, but only when exposed to ARO via the water column, indicating a prevalence of positive effects by nutrient supply. Microbial carbon and nutrient cycling in sediments was not affected by ARO. Higher temperature mitigated ARO‐related effects on macrophytes under sediment exposure. Synthesis and application. ARO poses a strong risk of submerged macrophyte loss and establishment of turbid conditions with phytoplankton dominance in aquatic ecosystems. In conclusion, exposure pathways as well as indirect and interacting effects of multiple stressors need to be considered when designing appropriate mitigation measures. Under climate change, we suggest to prioritize local measures as buffer strips a reduced use of pesticides and fertilizers, and sediment removal as appropriate measures to protect these vulnerable but widespread aquatic systems, which are highly relevant for biodiversity in agricultural landscapes.

Commercial Optical and Acoustic Sensor Performances under Varying Turbidity, Illumination, and Target Distances.

Acoustic and optical sensing modalities represent two of the primary sensing methods within underwater environments, and both have been researched extensively in previous works. Acoustic sensing is the premier method due to its high transmissivity in water and its relative immunity to environmental factors such as water clarity. Optical sensing is, however, valuable for many operational and inspection tasks and is readily understood by human operators. In this work, we quantify and compare the operational characteristics and environmental effects of turbidity and illumination on two commercial-off-the-shelf sensors and an additional augmented optical method, including: a high-frequency, forward-looking inspection sonar, a stereo camera with built-in stereo depth estimation, and color imaging, where a laser has been added for distance triangulation. The sensors have been compared in a controlled underwater environment with known target objects to ascertain quantitative operation performance, and it is shown that optical stereo depth estimation and laser triangulation operate satisfactorily at low and medium turbidites up to a distance of approximately one meter, with an error below 2 cm and 12 cm, respectively; acoustic measurements are almost completely unaffected up to two meters under high turbidity, with an error below 5 cm. Moreover, the stereo vision algorithm is slightly more robust than laser-line triangulation across turbidity and lighting conditions. Future work will concern the improvement of the stereo reconstruction and laser triangulation by algorithm enhancement and the fusion of the two sensing modalities.

Acute turbidity exposures with Port of Miami sediments impact Orbicella faveolata tissue regeneration

We evaluated acute turbidity effects on a threatened coral species (Orbicella faveolata) under three short-term challenge scenarios using a Port of Miami sediment homogenate to simulate turbid conditions during dredging. For these experiments we designed a simple coral challenge test system that kept turbidity stable, without adverse effects to the coral. A 96-h coral challenge experiment demonstrated that low turbidity levels (≥4 NTU) have negative effects on O. faveolata tissue regeneration. A 48-h turbidity exposure (maximum 30 NTU) had no effect on O. faveolata tissue regeneration, showing that short term turbidity exposures may not be detrimental to coral health. In a 13-day test, treated coral fragments (maximum 30 NTU) exhibited significant delays in tissue regeneration, but recovery was observed after approximately one week. The results presented here can be used to inform management decisions for proposed dredging activities proximal to coral reef habitats.

Light Beacon-Aided AUV Electromagnetic Localization for Landing on a Planar Docking Station

Autonomous underwater vehicles (AUVs) play an increasingly important role in underwater missions. However, traditional visual localization methods struggle to meet the accuracy requirements for AUV terminal docking in strong-illumination or turbid water conditions. This work proposes a universal navigation system using electromagnetic (EM) and light beacons for nontorpedo AUVs to be recovered using a planar docking station. The major challenge in designing this system is to deal with the incomplete sensing of the light and EM beacons. To solve this problem, a two-step fusion method of EM localization information is given first. The kinematic model of the AUV and visual information are also utilized to improve the robustness of the navigation system. Based on the localization result, a comprehensive docking strategy is proposed to address the time-varying sensing conditions. Localization and docking experiments were conducted in a pool. The test results show that the maximum EM localization error is less than 20 cm in both static and dynamic tests. The AUV completed all six docking attempts.

Control of diatom and chrysophyte cyst dynamics by a meteorologically driven mixing regime in eutrophic Lake Żabińskie, northern Poland

Abstract Ongoing climate warming has strong moderating control over aquatic processes, such as ice cover duration, length of the growing season, vertical mixing patterns, thermal stratification, and the availability of light and nutrients. These fundamental mechanisms in turn influence the population dynamics of aquatic organisms such as diatoms and chrysophytes. In our study, over 3.5 years with contrasting meteorological conditions, we investigated eutrophic Lake Żabińskie located in northeast Poland. By combining observational data of meteorological conditions, physicochemical variables measured in the water column, and modern sedimentation, we sought to explain the relationships between changes in meteorological conditions, dynamics of total fluxes and the taxonomic composition of diatoms and chrysophyte cysts. Our results show the direct influence of meteorological conditions on physicochemical conditions and their indirect influence on total diatom and chrysophyte cyst fluxes and taxonomic succession. The former refers to the importance of air temperature and wind speed in shaping the mixing regime of Lake Żabińskie, while the latter refers to the nutrient cycling driven by changes in the mixing regime, which in turn influences the formation of biotic signals in the sediment. Our study also revealed that the biotic response to unusual meteorological conditions that occurred in 2020 (i.e., warm winter without ice cover) differed from typical years in terms of the phenology of diatom and chrysophyte cyst blooms. However, this response was not as pronounced as in lakes with lower productivity and can be attributed to the already turbid conditions and high nutrient concentrations, which alter the threshold for noticeable changes to occur. The taxonomic composition of diatoms and chrysophyte cysts also changed in response to changes in meteorological conditions. Complex interactions between physical and chemical conditions masked the direct influences of meteorological conditions on lake biota under eutrophic conditions. Nevertheless, high‐resolution monitoring enabled indirect links to be recognised. Both phenology and turnover in community composition responded to changes in meteorological conditions. These results show how ongoing climate change might affect biota in eutrophic lakes in the future.